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Exposure Factors Handbook 

National Center for Environmental Assessment 

Office of Research and Development 
EFH

Table of Contents

Chapter 1 Introduction Chapter 2 Variability and

Chapter 3 Drinking Water Chapter 4 Soil Ingestion

Intake and Pica

Chapter 5 Inhalation Chapter 6 Dermal Route

Route

Chapter 7 Body Weight Chapter 8 Lifetime

Studies

Chapter 9 Intake of Fruits Chapter 10 Intake of Fish

and Vegetables and Shellfish

Chapter 11 Intake of Chapter 12 Intake of

Meat and Dairy Products Grain Products

Chapter 13 Intake Rates Chapter 14 Breast Milk

for Various Home Intake

Produced Food Items

Chapter 15 Activity Chapter 16 Consumer

Factors Products

Chapter 17 Residential Glossary

Building Characteristics

Uncertainty
Volume I - General Factors 

Chapter 1 - Introduction 

1. INTRODUCTION 

1.1. PURPOSE 

1.2. INTENDED AUDIENCE 

1.3. BACKGROUND 

1.3.1. Selection of Studies for the Handbook 

1.3.2. Using the Handbook in an Exposure Assessment 

1.3.3. Approach Used to Develop Recommendations for Exposure Factors 

1.3.4. Characterizing Variability 

1.4. GENERAL EQUATION FOR CALCULATING DOSE 

1.5. RESEARCH NEEDS 

1.6. ORGANIZATION 

REFERENCES FOR CHAPTER 1 

APPENDIX 1A 

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

Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings 

Table 1-3. Characterization of Variability in Exposure Factors 

Table 1A-1. Procedures for Modifying IRIS Risk Values for Non-standard Populations 

Figure 1-1. Schematic of Dose and Exposure: Oral Route 

Figure 1-2. Road Map to Exposure Factor Recommendations 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 2 - Variability and Uncertainty 

2. VARIABILITY AND UNCERTAINTY 

2.1. VARIABILITY VERSUS UNCERTAINTY 

2.2. TYPES OF VARIABILITY 

2.3. CONFRONTING VARIABILITY 

2.4. CONCERN ABOUT UNCERTAINTY 

2.5. TYPES OF UNCERTAINTY AND REDUCING UNCERTAINTY 

2.6. ANALYZING VARIABILITY AND UNCERTAINTY 

2.7. PRESENTING RESULTS OF VARIABILITY AND UNCERTAINTY ANALYSIS 

REFERENCES FOR CHAPTER 2 

Table 2-1. Four Strategies for Confronting Variability 

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

Table 2-3. Approaches to Quantitative Analysis of Uncertainty 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 3 - Drinking Water Intake 

3. DRINKING WATER INTAKE 

3.1. BACKGROUND 

3.2. KEY GENERAL POPULATION STUDIES ON DRINKING WATER INTAKE 

3.3. RELEVANT GENERAL POPULATION STUDIES ON DRINKING WATER 

INTAKE 

3.4. PREGNANT AND LACTATING WOMEN 

3.5. HIGH ACTIVITY LEVELS/HOT CLIMATES 

3.6. RECOMMENDATIONS 

REFERENCES FOR CHAPTER 3 

Table 3-1. Daily Total Tapwater Intake Distribution for Canadians, by Age Group 

(approx. 0.20 L increments, both sexes, combined seasons) 

Table 3-2. Average Daily Tapwater Intake of Canadians (expressed as milliliters per 

kilogram body weight) 

Table 3-3. Average Daily Total Tapwater Intake of Canadians, by Age and Season 

(L/day) 

Table 3-4. Average Daily Total Tapwater Intake of Canadians as a Function of Level of 

Physical Activity at Work and in Spare Time (16 years and older, combined 

seasons, L/day) 

Table 3-5. Average Daily Tapwater Intake by Canadians, Apportioned Among Various 

Beverages (both sexes, by age, combined seasons, L/day) 

Table 3-6. Total Tapwater Intake (mL/day) for Both Sexes Combined 

Table 3-7. Total Tapwater Intake (mL/kg-day) for Both Sexes Combined 

Table 3-8. Summary of Tapwater Intake by Age 

Table 3-9. Total Tapwater Intake (as percent of total water intake) by Broad Age 

Category 

Table 3-10. General Dietary Sources of Tapwater for Both Sexes 

Table 3-11. Summary Statistics for Best-Fit Lognormal Distributions for Water Intake 

Rates 

Table 3-12. Estimated Quantiles and Means for Total Tapwater Intake Rates (mL/day) 

Table 3-13. Assumed Tapwater Content of Beverages 

Table 3-14. Intake of Total Liquid, Total Tapwater, and Various Beverages (L/day) 

Table 3-15. Summary of Total Liquid and Total Tapwater Intake for Males and Females 

(L/day) 

Table 3-16. Measured Fluid Intakes (mL/day) 

Table 3-17. Intake Rates of Total Fluids and Total Tapwater by Age Group 

Table 3-18. Mean and Standard Error for the Daily Intake of Beverages and Tapwater by 

Age 

Table 3-19. Average Total Tapwater Intake Rate by Sex, Age, and Geographic Area 

Table 3-20. Frequency Distribution of Total Tapwater Intake Rates 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 3 - Drinking Water Intake 

Table 3-21. Mean Per Capita Drinking Water Intake Based on USDA, CSFII Data From 

1989-91 (mL/day) 

Table 3-22. Number of Respondents that Consumed Tapwater at a Specified Daily 

Frequency 

Table 3-23. Number of Respondents that Consumed Juice Reconstituted with Tapwater 

at a Specified Daily Frequency 

Table 3-24. Total Fluid Intake of Women 15-49 Years Old 

Table 3-25. Total Tapwater Intake of Women 15-49 Years Old 

Table 3-26. Total Fluid (mL/Day) Derived from Various Dietary Sources by Women Aged 

15-49 Years 

Table 3-27. Water Intake at Various Activity Levels (L/hr) 

Table 3-28. Planning Factors for Individual Tapwater Consumption 

Table 3-29. Drinking Water Intake Surveys 

Table 3-30. Summary of Recommended Drinking Water Intake Rates 

Table 3-31. Total Tapwater Consumption Rates From Key Studies 

Table 3-32. Daily Tapwater Intake Rates From Relevant Studies 

Table 3-33. Key Study Tapwater Intake Rates for Children 

Table 3-34. Summary of Intake Rates for Children in Relevant Studies 

Table 3-35. Confidence in Tapwater Intake Recommendations 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 4 - Soil Ingestion and Pica 

4. SOIL INGESTION AND PICA 

4.1 BACKGROUND 

4.2. KEY STUDIES ON SOIL INTAKE AMONG CHILDREN 

4.3. RELEVANT STUDIES ON SOIL INTAKE AMONG CHILDREN 

4.4. SOIL INTAKE AMONG ADULTS 

4.5. PREVALENCE OF PICA 

4.6. DELIBERATE SOIL INGESTION AMONG CHILDREN 

4.7. RECOMMENDATIONS 

REFERENCES FOR CHAPTER 4 

Table 4-1. Estimated Daily Soil Ingestion Based on Aluminum, Silicon, and Titanium 

Concentrations 

Table 4-2. Calculated Soil Ingestion by Nursery School Children 

Table 4-3. Calculated Soil Ingestion by Hospitalized, Bedridden Children 

Table 4-4. Mean and Standard Deviation Percentage Recovery of Eight Tracer 

Elements 

Table 4-5. Soil and Dust Ingestion Estimates for Children Aged 1-4 Years 

Table 4-6. Average Daily Soil Ingestion Values Based on Aluminum, Silicon, and 

Titanium as Tracer Elements 

Table 4-7. Geometric Mean (GM) and Standard Deviation (GSD) LTM Values for 

Children at Daycare Centers and Campgrounds 

Table 4-8. Estimated Geometric Mean LTM Values of Children Attending Daycare 

Centers According to Age, Weather Category, and Sampling Period 

Table 4-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates Per Child for 

64 Children (mg/day) 

Table 4-10. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on Data 

for 64 Subjects Projected Over 365 Days 

Table 4-11. Estimates of Soil Ingestion for Children 

Table 4-12. Estimated Soil Ingestion Rate Summary Statistics and Parameters for 

Distributions Using Binder et al. (1986) Data with Actual Fecal Weights 

Table 4-13. Tukey's Multiple Comparison of Mean Log Tracer Recovery in Adults 

Ingesting Known Quantities of Soil 

Table 4-14. Positive/Negative Error (bias) in Soil Ingestion Estimates in the Calabrese 

et al. (1989) Mass-balance Study: Effect on Mean Soil Ingestion Estimate 

(mg/day) 

Table 4-15. Soil Ingestion Rates for Assessment Purposes 

Table 4-16. Estimates of Soil Ingestion for Adults 

Table 4-17. Adult Daily Soil Ingestion by Week and Tracer Element After Subtracting 

Food and Capsule Ingestion, Based on Median Amherst Soil 

Concentrations: Means and Medians Over Subjects (mg) 
Volume I - General Factors 

Chapter 4 - Soil Ingestion and Pica 

Table 4-18. Daily Soil Ingestion Estimation in a Soil-Pica Child by Tracer and by Week 

(mg/day) 

Table 4-19. Ratios of Soil, Dust, and Residual Fecal Samples in the Pica Child 

Table 4-20. Soil Intake Studies 

Table 4-21. Confidence in Soil Intake Recommendation 

Table 4-22. Summary of Estimates of Soil Ingestion By Children 

Table 4-23. Summary of Recommended Values for Soil Ingestion 

Exposure Factors Handbook August 1997 August 1997
Volume I - General Factors 

Chapter 5 - Inhalation 

5. INHALATION ROUTE 

5.1. EXPOSURE EQUATION FOR INHALATION 

5.2. INHALATION RATE 

5.2.1. Background 

5.2.2. Key Inhalation Rate Studies 

5.2.3. Relevant Inhalation Rate Studies 

5.2.4. Recommendations 

REFERENCES FOR CHAPTER 5 

APPENDIX 5A 

Table 5-1. Calibration and Field Protocols for Self-Monitoring of Activities Grouped by 

Subject Panels 

Table 5-2. Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and 

Self-Estimated Breathing Rates 

Table 5-3. Distribution of Predicted IR by Location and Activity Levels for Elementary 

and High School Students 

Table 5-4. Average Hours Spent Per Day in a Given Location and Activity Level for 

Elementary (EL) and High School (HS) Students 

Table 5-5. Distribution Patterns of Daily Inhalation Rates for Elementary (EL) and High 

School (HS) Students Grouped by Activity Level 

3 Table 5-6. Summary of Average Inhalation Rates (m /hr) by Age Group and Activity 

Levels for Laboratory Protocols 

3 Table 5-7. Summary of Average Inhalation Rates (m /hr) by Age Group and Activity 

Levels in Field Protocols 

Table 5-8. Distributions of Individual and Group Inhalation/Ventilation Rate for Outdoor 

Workers 

3 Table 5-9. Individual Mean Inhalation Rate (m /hr) by Self-Estimated Breathing Rate or 

Job Activity Category for Outdoor Workers 

Table 5-10. Comparisons of Estimated Basal Metabolic Rates (BMR) with Average 

Food-Energy Intakes for Individuals Sampled in the 1977-78 NFCS 

Table 5-11. Daily Inhalation Rates Calculated from Food-Energy Intakes 

Table 5-12. Daily Inhalation Rates Obtained from the Ratios of Total Energy Expenditure 

to Basal Metabolic Rate (BMR) 

Table 5-13. Daily Inhalation Rates Based on Time-Activity Survey 

Table 5-14. Inhalation Rates for Short-Term Exposures 

Table 5-15. Daily Inhalation Rates Estimated From Daily Activities 

Table 5-16. Summary of Human Inhalation Rates for Men, Women, and Children by 

3 Activity Level (m /hour) 

Table 5-17. Activity Pattern Data Aggregated for Three Microenvironments by Activity 

Level for all Age Groups 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 5 - Inhalation 

Table 5-18. Summary of Daily Inhalation Rates Grouped by Age and Activity Level 

Table 5-19. Distribution Pattern of Predicted VR and EVR (equivalent ventilation rate) 

for 20 Outdoor Workers 

Table 5-20. Distribution Pattern of Inhalation Rate by Location and Activity Type for 

20 Outdoor Workers 

Table 5-21. Actual Inhalation Rates Measured at Four Ventilation Levels 

Table 5-22. Confidence in Inhalation Rate Recommendations 

Table 5-23. Summary of Recommended Values for Inhalation 

Table 5-24. Summary of Inhalation Rate Studies 

Table 5-25. Summary of Adult Inhalation Rates for Short-Term Exposure Studies 

Table 5-26. Summary of Children’s (18 years old or less) Inhalation Rates for 

Long-Term Exposure Studies 

Table 5-27. Summary of Children’s Inhalation Rates for Short-Term Exposure Studies 

Table 5A-1. Mean Minute Ventilation (V E , L/min) by Group and Activity for Laboratory

Protocols 

Table 5A-2. Mean Minute Ventilation (V E , L/min) by Group and Activity for Field

Protocols 

Table 5A-3. Characteristics of Individual Subjects: Anthropometric Data, Job 

Categories, Calibration Results 

Table 5A-4. Statistics of the Age/Gender Cohorts Used to Develop Regression 

Equations for Predicting Basal Metabolic Rates (BMR) 

Table 5A-5. Selected Ventilation Values During Different Activity Levels Obtained 

FromVarious Literature Sources 

Table 5A-6. Estimated Minute Ventilation Associated with Activity Level for Average 

Male Adult 

Table 5A-7. Minute Ventilation Ranges by Age, Sex, and Activity Level 

Figure 5-1. Schematic of Dose and Exposure: Respiratory Route 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 6 - Dermal 

6. DERMAL ROUTE 

6.1. EQUATION FOR DERMAL DOSE 

6.2. SURFACE AREA 

6.2.1. Background 

6.2.2. Measurement Techniques 

6.2.3. Key Body Surface Area Studies 

6.2.4. Relevant Surface Area Studies 

6.2.5. Application of Body Surface Area Data 

6.3. SOIL ADHERENCE TO SKIN 

6.3.1. Background 

6.3.2. Key Soil Adherence to Skin Studies 

6.3.3. Relevant Soil Adherence to Skin Studies 

6.4. RECOMMENDATIONS 

6.4.1. Body Surface Area 

6.4.2. Soil Adherence to Skin 

REFERENCES FOR CHAPTER 6 

APPENDIX 6A 

Table 6-1. Summary of Equation Parameters for Calculating Adult Body Surface Area 

Table 6-2. Surface Area of Adult Males in Square Meters 

Table 6-3. Surface Area of Adult Females in Square Meters 

2 Table 6-4. Surface Area of Body Part for Adults (m ) 

Table 6-5. Percentage of Total Body Surface Area by Part for Adults 

Table 6-6. Total Body Surface Area of Male Children in Square Meters 

Table 6-7. Total Body Surface Area of Female Children in Square Meters 

Table 6-8. Percentage of Total Body Surface Area by Body Part for Children 

Table 6-9. Descriptive Statistics for Surface Area/BodyWeight (SA/WB) Ratios (m /kg) 

2 Table 6-10. Statistical Results for Total Body Surface Area Distributions (m ) 

Table 6-11. Summary of Field Studies 

Table 6-12. Geometric Mean and Geometric Standard Deviations of Soil Adherence by 

Activity and Body Region 

Table 6-13. Summary of Surface Area Studies 

Table 6-14. Summary of Recommended Values for Skin Surface Area 

Table 6-15. Confidence in Body Surface Area Measurement Recommendations 

Table 6-16. Recommendations for Adult Body Surface Area 

Table 6-17. Summary of Soil Adherence Studies 

Table 6-18. Confidence in Soil Adherence to Skin Recommendations 

Table 6-A1. Estimated Parameter Values for Different Age Intervals 

Table 6-A2. Summary of Surface Area Parameter Values for the DuBois and DuBois 

Model 

Exposure Factors Handbook August 1997 

2 
Volume I - General Factors 

Chapter 6 - Dermal 

Figure 6-1. Schematic of Dose and Exposure: Dermal Route 

Figure 6-2. SA/BW Distributions for Infants, Adults, and All Ages Combined 

Figure 6-3. Surface Area Frequency Distribution: Men and Women 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 7 - Body Weight Studies 

7. BODY WEIGHT STUDIES 

7.1. KEY BODY WEIGHT STUDY 

7.2. RELEVANT BODY WEIGHT STUDIES 

7.3. RECOMMENDATIONS 

REFERENCES FOR CHAPTER 7 

Table 7-1. Smoothed Percentiles of Weight (in kg) by Sex and Age: Statistics from 

NCHS and Data from Fels Research Institute, Birth to 36 Months 

Table 7-2. Body Weights of Adults (kilograms) 

Table 7-3. Body Weights of Children (kilograms) 

Table 7-4. Weight in Kilograms for Males 18-74 Years of Age--Number Examined, 

Mean, Standard Deviation, and Selected Percentiles, by Race and Age: 

United States, 1976-1980 

Table 7-5. Weight in Kilograms for Females 18-74 Years of Age--Number Examined, 

Mean, Standard Deviation, and Selected Percentiles, by Race and Age: 

United States, 1976-1980 

Table 7-6. Weight in Kilograms for Males 6 Months-19 Years of Age--Number 

Examined, Mean, Standard Deviation, and Selected Percentiles, by Sex and 

Age: United States, 1976-1980 

Table 7-7. Weight in Kilograms for Females 6 Months-19 Years of Age--Number 

Examined, Mean, Standard Deviation, and Selected Percentiles, by Sex and 

Age: United States, 1976-1980 

Table 7-8. Statistics for Probability Plot Regression Analyses Female's Body Weights 

6 Months to 20 Years of Age 

Table 7-9. Statistics for Probability Plot Regression Analyses Male's Body Weights 6 

Months to 20 Years of Age 

Table 7-10. Summary of Body Weight Studies 

Table 7-11. Summary of Recommended Values for Body Weight 

Table 7-12. Confidence in Body Weight Recommendations 

Figure 7-1. Weight by Age Percentiles for Boys Aged Birth-36 Months 

Figure 7-2. Weight by Age Percentiles for Girls Aged Birth-36 Months 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 8 - Lifetime 

8. LIFETIME 

8.1. KEY STUDY ON LIFETIME 

8.2. RECOMMENDATIONS

REFERENCES FOR CHAPTER 8

Table 8-1. Expectation of Life at Birth, 1970 to 1993, and Projections, 1995 to 2010

Table 8-2. Expectation of Life by Race, Sex, and Age: 1992

Table 8-3. Confidence in Lifetime Expectancy Recommendations

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 9 - Intake of Fruits and Vegetables 

9. INTAKE OF FRUITS AND VEGETABLES 

9.1. BACKGROUND 

9.2. INTAKE STUDIES 

9.2.1. U.S. Department of Agriculture Nationwide Food Consumption Survey 

and Continuing Survey of Food Intake by Individuals 

9.2.2. Key Fruits and Vegetables Intake Study Based on the USDA CSFII 

9.2.3. Relevant Fruits and Vegetables Intake Studies 

9.2.4. Relevant Fruits and Vegetables Serving Size Study Based on the 

USDA NFCS 

9.2.5. Conversion Between As Consumed and Dry Weight Intake Rates 

9.3. RECOMMENDATIONS 

REFERENCES FOR CHAPTER 9 

APPENDIX 9A 

APPENDIX 9B 

Table 9-1. Sub-category Codes and Definitions Used in the CSFII 1989-91 Analysis 

Table 9-2. Weighted and Unweighted Number of Observations for 1989-91 CSFII Data 

Used in Analysis of Food Intake 

Table 9-3. Per Capita Intake of Total Fruits (g/kg-day as consumed) 

Table 9-4. Per Capita Intake of Total Vegetables (g/kg-day as consumed) 

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

consumed) 

Table 9-6. Per Capita Intake of USDA Categories of Fruits and Vegetables (g/kg-day 

as consumed) 

Table 9-7. Per Capita Intake of Exposed Fruits (g/kg-day as consumed) 

Table 9-8. Per Capita Intake of Protected Fruits (g/kg-day as consumed) 

Table 9-9. Per Capita Intake of Exposed Vegetables (g/kg-day as consumed) 

Table 9-10. Per Capita Intake of Protected Vegetables (g/kg-day as consumed) 

Table 9-11. Per Capita Intake of Root Vegetables (g/kg-day as consumed) 

Table 9-12. Mean Daily Intake of Fruits and Vegetables Per Individual in a Day for USDA 

1977-78, 87-88, 89-91, 94, and 95 Surveys 

Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables 

Based on All Sex/Age/Demographic Subgroups 

Table 9-14. Mean Total Fruit Intake (as consumed) in a Day by Sex and Age (1977­

1978) 

Table 9-15. Mean Total Fruit Intake (as consumed) in a Day by Sex an Age (1987-1988) 

Table 9-16. Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age 

(1977-1978) 

Table 9-17. Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age 

(1987-1988) 

Table 9-18. Mean Total Fruit Intake (as consumed) in a Day by Sex and Age (1994 and 

1995) 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 9 - Intake of Fruits and Vegetables 

Table 9-19. Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age (1994 

and 1995) 

Table 9-20. Mean Per Capita Intake of Fats and Oils (g/day as consumed) in a Day by 

Sex and Age (1994 and 1995) 

Table 9-21. Mean and Standard Error for the Per Capita Daily Intake of Food Class and 

Subclass by Region (g/day as consumed) 

Table 9-22. Mean and Standard Error for the Daily Intake of Food Subclasses Per Capita 

by Age (g/day as consumed) 

Table 9-23. Consumption of Foods (g dry weight/day) for Different Age Groups and 

Estimated Lifetime Average Daily Food Intakes for a US Citizen (averaged 

across sex) Calculated from the FDA Diet Data 

Table 9-24. Mean Daily Intake of Foods (grams) Based on the Nutrition Canada Dietary 

Survey 

Table 9-25. Per Capita Consumption of Fresh Fruits and Vegetables in 1991 

Table 9-26. Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating 

Occasion and the Percentage of Individuals Using These Foods in Three 

Days 

Table 9-27. Mean Moisture Content of Selected Fruits and Vegetables Expressed as 

Percentages of Edible Portions 

Table 9-28. Summary of Fruit and Vegetable Intake Studies 

Table 9-29. Summary of Recommended Values for Per Capita Intake of Fruits and 

Vegetables 

Table 9-30. Confidence in Fruit and Vegetable Intake Recommendations 

Table 9A-1. Fraction of Grain and Meat Mixture Intake Represented by Various Food 

Items/Groups 

Table 9 B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII 

Data 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 10 - Intake of Fish and Shellfish 

10. INTAKE OF FISH AND SHELLFISH 

10.1. BACKGROUND 

10.2. KEY GENERAL POPULATION STUDIES 

10.3. RELEVANT GENERAL POPULATION STUDIES 

10.4. KEY RECREATIONAL (MARINE FISH STUDIES) 

10.5. RELEVANT RECREATIONAL MARINE STUDIES 

10.6. KEY FRESHWATER RECREATIONAL STUDIES 

10.7. RELEVANT FRESHWATER RECREATIONAL STUDIES 

10.8. NATIVE AMERICAN FRESHWATER STUDIES 

10.9. OTHER FACTORS 

10.10. RECOMMENDATIONS 

10.10.1. Recommendations - General Population 

10.10.2. Recommendations - Recreational Marine Anglers 

10.10.3. Recommendations - Recreational Freshwater Anglers 

10.10.4. Recommendations - Native American Subsistence Populations 

REFERENCES FOR CHAPTER 10 

APPENDIX 10A 

APPENDIX 10B 

APPENDIX 10C 

Table 10-1. Total Fish Consumption by Demographic Variables 

Table 10-2. Mean and 95th Percentile of Fish Consumption (g/day) by Sex and Age 

Table 10-3. Percent Distribution of Total Fish Consumption for Females by Age 

Table 10-4. Percent Distribution of Total Fish Consumption for Males by Age 

Table 10-5. Mean Total Fish Consumption by Species 

Table 10-6. Best Fits of Lognormal Distributions Using the NonLinear Optimization 

(NLO) Method 

Table 10-7. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for 

the U.S. Population (Uncooked Fish Weight) 

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

Habitat for Consumers Only (Uncooked Fish Weight) 

Table 10-9. Per Capita Distribution of Fish Intake (mg/kg-day) by Habitat and Fish Type 

for U.S. Population (Uncooked Fish Weight) 

Table 10-10. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) by 

Habitat for Consumers Only (Uncooked Fish Weight) 

Table 10-11. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for 

the U.S. Population (Cooked Fish Weight - As Consumed)) 

Table 10-12. Per Capita Distribution of Fish Intake (g/day) by Habitat for Consumers Only 

(Cooked Fish Weight - As Consumed)) 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-13. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population by Age and Gender - As Consumed (Freshwater and 

Estuarine) 

Table 10-14. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population by Age and Gender - As Consumed (Marine)

Table 10-15. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population by Age and Gender - As Consumed (All Fish)

Table 10-16. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (grams/day) for 

the U.S. Population Aged 18 Years and Older by Habitat - As Consumed 

Table 10-17. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

the U.S. Population by Age and Gender - As Consumed (Freshwater and 

Estuarine) 

Table 10-18. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

the U.S. Population by Age and Gender - As Consumed (Marine) 

Table 10-19. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

the U.S. Population by Age and Gender - As Consumed (All Fish) 

Table 10-20. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

the U.S. Population Aged 18 Years and Older by Habitat - As Consumed 

Table 10-21. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only by Age and Gender - As Consumed (Freshwater and 

Estuarine) 

Table 10-22. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only by Age and Gender - As Consumed (Marine) 

Table 10-23. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only by Age and Gender - As Consumed (All Fish) 

Table 10-24. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only Aged 18 Years and Older by Habitat - As Consumed 

Table 10-25. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

Consumers Only by Age and Gender - As Consumed (Freshwater and 

Estuarine) 

Table 10-26. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

Consumers Only by Age and Gender - As Consumed (Marine) 

Table 10-27. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

Consumers Only by Age and Gender - As Consumed (All Fish) 

Table 10-28. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

Consumers Only Aged 18 Years and Older by Habitat - As Consumed 

Table 10-29. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population by Age and Gender - Uncooked Fish Weight (Freshwater 

and Estuarine) 

Table 10-30. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population by Age and Gender - Uncooked Fish Weight (Marine)

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-31. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population by Age and Gender - Uncooked Fish Weight (All Fish)

Table 10-32. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population Aged 18 Years and Older by Habitat - Uncooked Fish 

Weight 

Table 10-33. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

the U.S. Population by Age and Gender - Uncooked Fish Weight 

(Freshwater and Estuarine) 

Table 10-34. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

the U.S. Population by Age and Gender - Uncooked Fish Weight (Marine) 

Table 10-35. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

the U.S. Population by Age and Gender - Uncooked Fish Weight (All Fish) 

Table 10-36. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

the U.S. Population Aged 18 Years and Older by Habitat - Uncooked Fish 

Weight 

Table 10-37. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only by Age and Gender - Uncooked Fish Weight (Freshwater 

and Estuarine) 

Table 10-38. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only by Age and Gender - Uncooked Fish Weight (Marine) 

Table 10-39. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only by Age and Gender - Uncooked Fish Weight (All Fish) 

Table 10-40. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only Aged 18 Years and Older by Habitat - Uncooked Fish 

Weight 

Table 10-41. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

Consumers Only by Age and Gender - Uncooked Fish Weight (Freshwater 

and Estuarine) 

Table 10-42. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

Consumers Only by Age and Gender - Uncooked Fish Weight (Marine) 

Table 10-43. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

Consumers Only by Age and Gender - Uncooked Fish Weight (All Fish) 

Table 10-44. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for 

Consumers Only Aged 18 Years and Older by Habitat - Uncooked Fish 

Weight 

Table 10-45. Distribution of Quantity of Fish Consumed (in grams) Per Eating Occasion, 

by Age and Sex 

Table 10-46. Mean Fish Intake in a Day, by Sex and Age 

Table 10-47. Percent of Respondents That Responded Yes, No, or Don’t Know to Eating 

Seafood in 1 Month (including shellfish, eels, or squid) 

Table 10-48. Number of Respondents Reporting Consumption of a Specified Number of 

Servings of Seafood in 1 Month 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-49. Number of Respondents Reporting Monthly Consumption of Seafood That 

Was Purchased or Caught by Someone They Knew 

Table 10-50. Estimated Number of Participants in Marine Recreational Fishing by State 

and Subregion 

Table 10-51. Estimated Weight of Fish Caught (Catch Type A and B1) by Marine 

Recreational Fishermen, by Wave and Subregion 

Table 10-52. Average Daily Intake (g/day) of Marine Finfish, by Region and Coastal 

Status 

Table 10-53. Estimated Weight of Fish Caught (Catch Type A and B1) by Marine 

Recreational Fishermen by Species Group and Subregion, Atlantic and Gulf 

Table 10-54. Estimated Weight of Fish Caught (Catch Type A and B1) by Marine 

Recreational Fishermen by Species Group and Subregion, Pacific 

Table 10-55. Median Intake Rates Based on Demographic Data of Sport Fishermen and 

Their Family/Living Group 

Table 10-56. Cumulative Distribution of Total Fish/Shellfish Consumption by Surveyed 

Sport Fishermen in the Metropolitan Los Angeles Area 

Table 10-57. Catch Information for Primary Fish Species Kept by Sport Fishermen 

(n=1059) 

Table 10-58. Percent of Fishing Frequency During the Summer and Fall Seasons in 

Commencement Bay, Washington 

Table 10-59. Selected Percentile Consumption Estimates (g/day) for the Survey and Total 

Angler Populations Based on the Reanalysis of the Puffer et al. (1981) and 

Pierce et al. (1981) Data 

Table 10-60. Means and Standard Deviations of Selected Characteristics by 

Subpopulation Groups in Everglades, Florida 

Table 10-61. Mean Fish Intake Among Individuals Who Eat Fish and Reside in 

Households With Recreational Fish Consumption 

Table 10-62. Comparison of Seven-Day Recall and Estimated Seasonal Frequency for 

Fish Consumption 

Table 10-63. Distribution of Usual Fish Intake Among Survey Main Respondents Who 

Fished and Consumed Recreationally Caught Fish 

Table 10-64. Estimates of Fish Intake Rates of Licensed Sport Anglers in Maine During 

the 1989-1990 Ice Fishing or 1990 Open-Water Seasons 

Table 10-65. Analysis of Fish Consumption by Ethnic Groups for “All Waters” (g/day) 

Table 10-66. Total Consumption of Freshwater Fish Caught by All Survey Respondents 

During the 1990 Season 

Table 10-67. Mean Sport-Fish Consumption by Demographic Variables, Michigan Sport 

Anglers Fish Consumption Study, 1991-1992 

Table 10-68. Distribution of Fish Intake Rates (from all sources and from sport-caught 

sources) For 1992 Lake Ontario Anglers 

Table 10-69. Mean Annual Fish Consumption (g/day) for Lake Ontario Anglers, 1992, by 

Sociodemographic Characteristics 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 10 - Intake of Fish and Shellfish 

Table 10-70. Percentile and Mean Intake Rates for Wisconsin Sport Anglers 

Table 10-71. Sociodemographic Characteristics of Respondents 

Table 10-72. Number of Grams Per Day of Fish Consumed by All Adult Respondents 

(Consumers and Non-consumers Combined) - Throughout the Year 

Table 10-73. Fish Intake Throughout the Year by Sex, Age, and Location by All Adult 

Respondents 

Table 10-74. Children’s Fish Consumption Rates - Throughout Year 

Table 10-75. Sociodemographic Factors and Recent Fish Consumption 

Table 10-76. Number of Local Fish Meals Consumed Per Year by Time Period for All 

Respondents 

Table 10-77. Mean Number of Local Fish Meals Consumed Per Year by Time Period for 

All Respondents and Consumers Only 

Table 10-78. Mean Number of Local Fish Meals Consumed Per Year by Time Period and 

Selected Characteristics for All Respondents (Mohawk, N=97; Control, 

N=154) 

Table 10-79. Percentage of Individuals Using Various Cooking Methods at Specified 

Frequencies 

Table 10-80. Percent Moisture and Fat Content for Selected Species 

Table 10-81. Recommendations - General Population 

Table 10-82. Recommendations - General Population - Fish Serving Size 

Table 10-83. Recommendations - Recreational Marine Anglers 

Table 10-84. Recommendations - Freshwater Anglers 

Table 10-85. Recommendations - Native American Subsistence Populations 

Table 10-86. Summary of Fish Intake Studies 

Table 10-87. Confidence in Fish Intake Recommendations for General Population 

Table 10-88. Confidence in Fish Intake Recommendations for Recreational Marine 

Anglers 

Table 10-89. Confidence in Recommendations for Fish Consumption - Recreational 

Freshwater 

Table 10-90. Confidence in Recommendations for Native American Subsistence Fish 

Consumption 

Table 10B-1. Percent of Fish Meals Prepared Using Various Cooking Methods by 

Residence Size 

Table 10B-2. Percent of Fish Meals Prepared Using Various Cooking Methods by Age 

Table 10B-3. Percent of Fish Meals Prepared Using Various Cooking Methods by 

Ethnicity 

Table 10B-4. Percent of Fish Meals Prepared Using Various Cooking Methods by 

Education 

Table 10B-5. Percent of Fish Meals Prepared Using Various Cooking Methods by Income 

Table 10B-6. Percent of Fish Meals Where Fat was Trimmed or Skin was Removed, by 

Demographic Variables 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 10 - Intake of Fish and Shellfish 

Table 10B-7. Method of Cooking of Most Common Species Kept by Sportfishermen 

Table 10B-8. Adult Consumption of Fish Parts 

Table 10C-1. Daily Average Per Capita Estimates of Fish Consumption U.S. Population ­

Mean Consumption by Species Within Habitat - As Consumed Fish 

Table 10C-2. Daily Average Per Capita Estimates of Fish Consumption U.S. Population ­

Mean Consumption by Species Within Habitat - Uncooked Fish 

Table 10C-3. Daily Average Per Capita Estimates of Fish Consumption As Consumed 

Fish - Mean Consumption by Species Within Habitat - U.S. Population 

Table 10C-4. Daily Average Per Capita Estimates of Fish Consumption Uncooked Fish ­

Mean Consumption by Species Within Habitat - U.S. Population 

Figure 10-1. Seasonal Fish Consumption: Wisconsin Chippewa, 1990 

Figure 10-2. Peak Fish Consumption: Wisconsin Chippewa, 1990 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 11 - Intake of Meat and Dairy Products 

11. INTAKE OF MEAT AND DAIRY PRODUCTS 

11.1. INTAKE STUDIES 

11.1.1. U.S. Department of Agriculture Nationwide Food Consumption 

Survey and Continuing Survey of Food Intake by Individuals 

11.1.2. Key Meat and Dairy Products Intake Study Based on the CSFII 

11.1.3. Relevant Meat and Dairy Products Intake Studies 

11.2. FAT CONTENT OF MEAT AND DAIRY PRODUCTS 

11.3. CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE 

RATES 

11.4. RECOMMENDATIONS 

REFERENCES FOR CHAPTER 11 

APPENDIX 11A 

Table 11-1. Per Capita Intake of Total Meats (g/kg-day as consumed) 

Table 11-2. Per Capita Intake of Total Dairy Products (g/kg-day as consumed) 

Table 11-3. Per Capita Intake of Beef (g/kg-day as consumed) 

Table 11-4. Per Capita Intake of Pork (g/kg-day as consumed) 

Table 11-5. Per Capita Intake of Poultry (g/kg-day as consumed) 

Table 11-6. Per Capita Intake of Game (g/kg-day as consumed) 

Table 11-7. Per Capita Intake of Eggs (g/kg-day as consumed) 

Table 11-8. Main Daily Intake of Meat and Dairy Products Per Individual in a Day for 

USDA 1977-78, 87-88, 89-91, 94, and 95 Surveys 

Table 11-9. Mean Per Capita Intake Rates for Meat, Poultry, and Dairy Products (g/kgday as consumed) Based on All Sex/Age/Demographic Subgroups 

Table 11-10. Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as 

consumed) for 1977-1978 

Table 11-11. Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as 

consumed) for 1987-1988 

Table 11-12. Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day 

as consumed) for 1977-1978 

Table 11-13. Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day 

as consumed) for 1987-1988 

Table 11-14. Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as 

consumed) for 1994 and 1995 

Table 11-15. Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day 

as consumed) for 1994 and 1995 

Table 11-16. Mean and Standard Error for the Dietary Intake of Food Sub Classes Per 

Capita by Age (g/day as consumed) 

Table 11-17. Mean and Standard Error for the Per Capita Daily Intake of Food Class and 

Sub Class by Region (g/day as consumed) 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 11 - Intake of Meat and Dairy Products 

Table 11-18. Consumption of Meat, Poultry, and Dairy Products for Different Age Groups 

(averaged across sex), and Estimated Lifetime Average Intakes for 70 Kg 

Adult Citizens Calculated from the FDA Diet Data 

Table 11-19. Per Capita Consumption of Meat and Poultry in 1991 

Table 11-20. Per Capita Consumption of Dairy Products in 1991 

Table 11-21. Adult Mean Daily Intake (as consumed) of Meat and Poultry Grouped by 

Region and Gender 

Table 11-22. Amount (as consumed) of Meat Consumed by Adults Grouped by Frequency 

of Eatings 

Table 11-23. Quantity (as consumed) of Meat, Poultry, and Dairy Products Consumed Per 

Eating Occasion and the Percentage of Individuals Using These Foods in 

Three Days 

Table 11-24. Percentage Lipid Content (Expressed as Percentages of 100 Grams of 

Edible Portions) of Selected Meat and Dairy Products 

Table 11-25. Fat Content of Meat Products 

Table 11-26. Fat Intake, Contribution of Various Food Groups to Fat Intake, and 

Percentage of the Population in Various Meat Eater Groups of the U.S. 

Population 

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

Table 11-28. Percentage Mean Moisture Content (Expressed as Percentages of 100 

Grams of Edible Portions) 

Table 11-29. Summary of Meat, Poultry, and Dairy Intake Studies 

Table 11-30. Summary of Recommended Values for Per Capita Intake of Meat and Dairy 

Products and Serving Size 

Table 11-31. Confidence in Meats and Dairy Products Intake Recommendations 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 12 - Intake of Grain Products 

12. INTAKE OF GRAIN PRODUCTS 

12.1. INTAKE STUDIES 

12.1.1. U.S. Department of Agriculture Nationwide Food Consumption 

Survey and Continuing Survey of Food Intake by Individuals 

12.1.2. Key Grain Products Intake Studies Based on the CSFII 

12.1.3. Relevant Grain Products Intake Studies 

12.1.4. Key Grain Products Serving Size Study Based on the USDA 

NFCS 

12.2. CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE 

RATES 

12.3. RECOMMENDATIONS 

REFERENCES FOR CHAPTER 12 

APPENDIX 12A 

Table 12-1. Per Capita Intake of Total Grains Including Mixtures (g/kg-day as consumed) 

Table 12-2. Per Capita Intake of Breads (g/kg-day as consumed) 

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

Table 12-4. Per Capita Intake of Snacks Containing Grain (g/kg-day as consumed) 

Table 12-5. Per Capita Intake of Breakfast Foods (g/kg-day as consumed) 

Table 12-6. Per Capita Intake of Pasta (g/kg-day as consumed) 

Table 12-7. Per Capita Intake of Cooked Cereals (g/kg-day as consumed) 

Table 12-8. Per Capita Intake of Rice (g/kg-day as consumed) 

Table 12-9. Per Capita Intake of Ready-to-Eat Cereals (g/kg-day as consumed) 

Table 12-10. Per Capita Intake of Baby Cereals (g/kg-day as consumed) 

Table 12-11. Mean Daily Intakes of Grains Per Individual in a Day for USDA 1977-78, 87­

88, 89-91, 94, and 95 Surveys 

Table 12-12. Mean Per Capita Intake Rates for Grains Based on All 

Sex/Age/Demographic Subgroups 

Table 12-13. Mean Grain Intake Per Individual in a Day by Sex and Age (g/day as 

consumed) for 1977-1978 

Table 12-14. Mean Grain Intakes Per Individual in a Day by Sex and Age (g/day as 

consumed) for 1987-1988 

Table 12-15. Mean Grain Intakes Per Individual in a Day by Sex and Age (g/day as 

consumed) for 1994 and 1995 

Table 12-16. Mean and Standard Error for the Daily Per Capita Intake of Grains, by Age 

(g/day as consumed) 

Table 12-17. Mean and Standard Error for the Daily Intake of Grains, by Region (g/day as 

consumed) 

Table 12-18. Consumption of Grains (g dry weight/day) for Different Age Groups and 

Estimated Lifetime Average Daily Food Intakes for a U.S. Citizen (averaged 

across sex) Calculated from the FDA Diet Data 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 12 - Intake of Grain Products 

Table 12-19. Per Capita Consumption of Flour and Cereal Products in 1991 

Table 12-20. Quantity (as consumed) of Grain Products Consumed Per Eating Occasion 

and the Percentage of Individuals Using These Foods in Three Days 

Table 12-21. Mean Moisture Content of Selected Grains Expressed as Percentages of 

Edible Portions 

Table 12-22. Summary of Grain Intake Studies 

Table 12-23. Summary of Recommended Values for Per Capita Intake of Grain Products 

Table 12-24. Confidence in Grain Products Intake Recommendation 

Table 12A-1. Food Codes and Definitions Used in the Analysis of the 1989-91 USDA 

CSFII Grains Data 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 13 - Intake Rates for Various Home Produced Food Items 

13. INTAKE RATES FOR VARIOUS HOME PRODUCED FOOD ITEMS 

13.1. BACKGROUND 

13.2. METHODS 

13.3. RESULTS 

13.4. ADVANTAGES AND LIMITATIONS 

13.5. RECOMMENDATIONS 

REFERENCES FOR CHAPTER 13 

APPENDIX 13A 

Table 13-1. 1986 Vegetable Gardening by Demographic Factors 

Table 13-2. Percentage of Gardening Households Growing Different Vegetables in 1986 

Table 13-3. Sub-category Codes and Definitions 

Table 13-4. Weighted and Unweighted Number of Observations (Individuals) for NFCS 

Data Used in Analysis of Food Intake 

Table 13-5. Percent Weight Losses from Preparation of Various Meats 

Table 13-6. Percent Weight Losses from Preparation of Various Fruits 

Table 13-7. Percent Weight Losses from Preparation of Various Vegetables 

Table 13-8. Consumer Only Intake of Homegrown Fruits (g/kg-day) - All Regions 

Combined 

Table 13-9. Consumer Only Intake of Homegrown Fruits (g/kg-day) - Northeast 

Table 13-10. Consumer Only Intake of Homegrown Fruits (g/kg-day) - Midwest 

Table 13-11. Consumer Only Intake of Homegrown Fruits (g/kg-day) - South 

Table 13-12. Consumer Only Intake of Homegrown Fruits (g/kg-day) - West 

Table 13-13. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - All Regions 

Combined 

Table 13-14. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - Northeast 

Table 13-15. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - Midwest 

Table 13-16. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - South 

Table 13-17. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - West 

Table 13-18. Consumer Only Intake of Home Produced Meats (g/kg-day) - All Regions 

Combined 

Table 13-19. Consumer Only Intake of Home Produced Meats (g/kg-day) - Northeast 

Table 13-20. Consumer Only Intake of Home Produced Meats (g/kg-day) - Midwest 

Table 13-21. Consumer Only Intake of Home Produced Meats (g/kg-day) - South 

Table 13-22. Consumer Only Intake of Home Produced Meats (g/kg-day) - West 

Table 13-23. Consumer Only Intake of Home Caught Fish (g/kg-day) - All Regions 

Combined 

Table 13-24. Consumer Only Intake of Home Caught Fish (g/kg-day) - Northeast 

Table 13-25. Consumer Only Intake of Home Caught Fish (g/kg-day) - Midwest 

Table 13-26. Consumer Only Intake of Home Caught Fish (g/kg-day) - South 

Table 13-27. Consumer Only Intake of Home Caught Fish (g/kg-day) - West 

Table 13-28. Consumer Only Intake of Home Produced Dairy (g/kg-day) - All Regions 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 13 - Intake Rates for Various Home Produced Food Items 

Table 13-29. Consumer Only Intake of Home Produced Dairy (g/kg-day) - Northeast

Table 13-30. Consumer Only Intake of Home Produced Dairy (g/kg-day) - Midwest

Table 13-31. Consumer Only Intake of Home Produced Dairy (g/kg-day) - South

Table 13-32. Consumer Only Intake of Home Produced Dairy (g/kg-day) - West

Table 13-33. Seasonally Adjusted Consumer Only Homegrown Intake (g/kg-day)

Table 13-34. Consumer Only Intake of Homegrown Apples (g/kg-day)

Table 13-35. Consumer Only Intake of Homegrown Asparagus (g/kg-day)

Table 13-36. Consumer Only Intake of Home Produced Beef (g/kg-day)

Table 13-37. Consumer Only Intake of Homegrown Beets (g/kg-day)

Table 13-38. Consumer Only Intake of Homegrown Broccoli (g/kg-day)

Table 13-39. Consumer Only Intake of Homegrown Cabbage (g/kg-day)

Table 13-40. Consumer Only Intake of Homegrown Carrots (g/kg-day)

Table 13-41. Consumer Only Intake of Homegrown Corn (g/kg-day)

Table 13-42. Consumer Only Intake of Homegrown Cucumbers (g/kg-day)

Table 13-43. Consumer Only Intake of Home Produced Eggs (g/kg-day)

Table 13-44. Consumer Only Intake of Home Produced Game (g/kg-day)

Table 13-45. Consumer Only Intake of Home Produced Lettuce (g/kg-day)

Table 13-46. Consumer Only Intake of Home Produced Lima Beans (g/kg-day)

Table 13-47. Consumer Only Intake of Homegrown Okra (g/kg-day)

Table 13-48. Consumer Only Intake of Homegrown Onions (g/kg-day)

Table 13-49. Consumer Only Intake of Homegrown Other Berries (g/kg-day)

Table 13-50. Consumer Only Intake of Homegrown Peaches (g/kg-day)

Table 13-51. Consumer Only Intake of Homegrown Pears (g/kg-day)

Table 13-52. Consumer Only Intake of Homegrown Peas (g/kg-day)

Table 13-53. Consumer Only Intake of Homegrown Peppers (g/kg-day)

Table 13-54. Consumer Only Intake of Home Produced Pork (g/kg-day)

Table 13-55. Consumer Only Intake of Home Produced Poultry (g/kg-day)

Table 13-56. Consumer Only Intake of Homegrown Pumpkins (g/kg-day)

Table 13-57. Consumer Only Intake of Homegrown Snap Beans (g/kg-day)

Table 13-58. Consumer Only Intake of Homegrown Strawberries (g/kg-day)

Table 13-59. Consumer Only Intake of Homegrown Tomatoes (g/kg-day)

Table 13-60. Consumer Only Intake of Homegrown White Potatoes (g/kg-day)

Table 13-61. Consumer Only Intake of Homegrown Exposed Fruit (g/kg-day)

Table 13-62. Consumer Only Intake of Homegrown Protected Fruits (g/kg-day)

Table 13-63. Consumer Only Intake of Homegrown Exposed Vegetables (g/kg-day)

Table 13-64. Consumer Only Intake of Homegrown Protected Vegetables (g/kg-day)

Table 13-65. Consumer Only Intake of Homegrown Root Vegetables (g/kg-day)

Table 13-66. Consumer Only Intake of Homegrown Dark Green Vegetables (g/kg-day)

Table 13-67. Consumer Only Intake of Homegrown Deep Yellow Vegetables (g/kg-day)

Table 13-68. Consumer Only Intake of Homegrown Other Vegetables (g/kg-day)

Table 13-69. Consumer Only Intake of Homegrown Citrus (g/kg-day)

Table 13-70. Consumer Only Intake of Homegrown Other Fruit (g/kg-day)

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 13 - Intake Rates for Various Home Produced Food Items 

Table 13-71. Fraction of Food Intake that is Home Produced 

Table 13-72. Confidence in Homegrown Food Consumption Recommendations 

Table 13A-1. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS 

Data 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 14 - Breast Milk Intake 

14. BREAST MILK INTAKE 

14.1. BACKGROUND 

14.2. KEY STUDIES ON BREAST MILK INTAKE 

14.3. RELEVANT STUDIES ON BREAST MILK INTAKE 

14.4. KEY STUDIES ON LIPID CONTENT AND FAT INTAKE FROM BREAST 

MILK 

14.5. OTHER FACTORS 

14.6. RECOMMENDATIONS 

REFERENCES FOR CHAPTER 14 

Table 14-1. Daily Intakes of Breast Milk 

Table 14-2. Breast Milk Intake for Infants Aged 1 to 6 Months 

Table 14-3. Breast Milk Intake Among Exclusively Breast-fed Infants During the First 4 

Months of Life 

Table 14-4. Breast Milk Intake During a 24-Hour Period 

Table 14-5. Breast Milk Intake Estimated by the DARLING Study 

Table 14-6. Milk Intake for Bottle- and Breast-fed Infants by Age Group 

Table 14-7. Milk Intake for Boys and Girls 

Table 14-8. Intake of Breast Milk and Formula 

Table 14-9. Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively 

Breast-fed Infants 

Table 14-10. Predicted Lipid Intakes for Breast-fed Infants Under 12 Months of Age 

Table 14-11. Number of Meals Per Day 

Table 14-12. 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, by Ethnic 

Background and Selected Demographic Variables 

Table 14-13. Breast Milk Intake Studies 

Table 14-14. Confidence in Breast Milk Intake Recommendations 

Table 14-15. Breast Milk Intake Rates Derived From Key Studies 

Table 14-16. Summary of Recommended Breast Milk and Lipid Intake Rates 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 15 - Activity Factors 

15. ACTIVITY FACTORS 

15.1. ACTIVITY PATTERNS 

15.1.1. Key Activity Pattern Studies 

15.1.2. Relevant Activity Pattern Studies 

15.2. OCCUPATIONAL MOBILITY 

15.2.1. Background 

15.2.2. Key Occupational Mobility Studies 

15.3. POPULATION MOBILITY 

15.3.1. Background 

15.3.2. Key Population Mobility Studies 

15.3.3. Relevant Population Mobility Studies 

15.4. RECOMMENDATIONS 

15.4.1. Recommendations for Activity Patterns 

15.4.2. Recommendations: Occupational Mobility 

15.4.3. Recommendations: Population Mobility 

15.4.4. Summary of Recommended Activity Factors 

REFERENCES FOR CHAPTER 15 

APPENDIX 15A 

APPENDIX 15B 

Table 15-1. Time Use Table Locator Guide 

Table 15-2. Mean Time Spent (minutes) Performing Major Activities Grouped by Age, 

Sex and Type of Day 

Table 15-3. Mean Time Spent (minutes) in Major Activities Grouped by Type of Day for 

Five Different Age Groups 

Table 15-4. Cumulative Frequency Distribution of Average Shower Duration for 2,550 

Households 

Table 15-5. Mean Time Spent (minutes/day) in Ten Major Activity Categories Grouped 

by Total Sample and Gender for the CARB and National Studies (age 18-64 

years) 

Table 15-6. Total Mean Time Spent at Three Major Locations Grouped by Total Sample 

and Gender for the CARB and National Study (ages 18-64 years) 

Table 15-7. Mean Time Spent at Three Locations for both CARB and National Studies 

(ages 12 years and older) 

Table 15-8. Mean Time Spent (minutes/day) in Various Microenvironments Grouped by 

Total Population and Gender (12 years and over) in the National and CARB 

Data 

Table 15-9. Mean Time Spent (minutes/day) in Various Microenvironments by Type of 

Day for the California and National Surveys (sample population ages 12 

years and older) 

Table 15-10. Mean Time Spent (minutes/day) in Various Microenvironments by Age 

Groups for the National and California Surveys 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 15 - Activity Factors 

Table 15-11. Mean Time (minutes/day) Children Spent in Ten Major Activity Categories 

for All Respondents 

Table 15-12. Mean Time Children Spent in Ten Major Activity Categories Grouped by Age 

and Gender 

Table 15-13. Mean Time Children Spent in Ten Major Activity Categories Grouped by 

Seasons and Regions 

Table 15-14. Mean Time Children Spent in Six Major Location Categories for All 

Respondents (minutes/day) 

Table 15-15. Mean Time Children Spent in Six Location Categories Grouped by Age and 

Gender 

Table 15-16. Mean Time Children Spent in Six Location Categories Grouped by Season 

and Region 

Table 15-17. Mean Time Children Spent in Proximity to Three Potential Exposures 

Grouped by All Respondents, Age, and Gender 

Table 15-18. Range of Recommended Defaults for Dermal Exposure Factors 

Table 15-19. Number of Times Taking a Shower at Specified Daily Frequencies by the 

Number of Respondents 

Table 15-20. Times (minutes) Spent Taking Showers by the Number of Respondents 

Table 15-21. Number of Minutes Spent Taking a Shower (minutes/shower) 

Table 15-22. Time (minutes) Spent in the Shower Room Immediately After Showering by 

the Number of Respondents 

Table 15-23. Number of Minutes Spent in the Shower Room Immediately After Showering 

(minutes/shower) 

Table 15-24. Number of Baths Given or Taken in One Day by Number of Respondents 

Table 15-25. Total Time Spent Taking or Giving a Bath by the Number of Respondents 

Table 15-26. Number of Minutes Spent Giving and Taking the Bath(s) (minutes/bath) 

Table 15-27. Time Spent in the Bathroom Immediately After the Bath(s) by the Number 

of Respondents 

Table 15-28. Number of Minutes Spent in the Bathroom Immediately After the Bath(s) 

(minutes/bath) 

Table 15-29. Total Time Spent Altogether in the Shower or Bathtub by the Number of 

Respondents 

Table 15-30. Total Number of Minutes Spent Altogether in the Shower or Bathtub 

(minutes/bath) 

Table 15-31. Time Spent in the Bathroom Immediately Following a Shower or Bath by the 

Number of Respondents 

Table 15-32. Number of Minutes Spent in the Bathroom Immediately Following a Shower 

or Bath (minutes/bath) 

Table 15-33. Range of Number of Times Washing the Hands at Specified Daily 

Frequencies by the Number of Respondents 

Table 15-34. Number of Minutes Spent (at home) Working or Being Near Food While 

Fried, Grilled, or Barbequed (minutes/day) 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 15 - Activity Factors 

Table 15-35. Number of Minutes Spent (at home) Working or Being Near Open Flames 

Including Barbeque Flames (minutes/day) 

Table 15-36. Number of Minutes Spent Working or Being Near Excessive Dust in the Air 

(minutes/day) 

Table 15-37. Range of the Number of Times an Automobile or Motor Vehicle was Started 

in a Garage or Carport at Specified Daily Frequencies by the Number of 

Respondents 

Table 15-38. Range of the Number of Times Motor Vehicle Was Started with Garage Door 

Closed at Specified Daily Frequencies by the Number of Respondents 

Table 15-39. Number of Minutes Spent at a Gas Station or Auto Repair Shop 

(minutes/day) 

Table 15-40. Number of Minutes Spent at Home While the Windows Were Left Open 

(minutes/day) 

Table 15-41. Number of Minutes the Outside Door Was Left Open While at Home 

(minutes/day) 

Table 15-42. Number of Times an Outside Door Was Opened in the Home at Specified 

Daily Frequencies by the Number of Respondents 

Table 15-43. Number of Minutes Spent Running, Walking, or Standing Alongside a Road 

with Heavy Traffic (minutes/day) 

Table 15-44. Number of Minutes Spent in a Car, Van, Truck, or Bus in Heavy Traffic 

(minutes/day) 

Table 15-45. Number of Minutes Spent in a Parking Garage or Indoor Parking Lot 

(minutes/day) 

Table 15-46. Number of Minutes Spent Walking Outside to a Car in the Driveway or 

Outside Parking Areas (minutes/day) 

Table 15-47. Number of Minutes Spent Running or Walking Outside Other Than to the 

Car (minutes/day) 

Table 15-48. Number of Hours Spent Working for Pay (hours/week) 

Table 15-49. Number of Hours Spent Working for Pay Between 6PM and 6AM 

(hours/week) 

Table 15-50. Number of Hours Worked in a Week That Was Outdoors (hours/week) 

Table 15-51. Number of Times Floors Were Swept or Vacuumed at Specified Frequencies 

by the Number of Respondents 

Table 15-52. Number of Days Since the Floor Area in the Home Was Swept or Vacuumed 

by the Number of Respondents 

Table 15-53. Number of Loads of Laundry Washed in a Washing Machine at Home by the 

Number of Respondents 

Table 15-54. Number of Times Using a Dishwasher at Specified Frequencies by the 

Number of Respondents 

Table 15-55. Number of Times Washing Dishes by Hand at Specified Frequencies by the 

Number of Respondents 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 15 - Activity Factors 

Table 15-56. Number of Times for Washing Clothes in a Washing Machine at Specified 

Frequencies by the Number of Respondents 

Table 15-57. Number of Minutes Spent Playing on Sand or Gravel in a Day by the Number 

of Respondents 

Table 15-58. Number of Minutes Spent Playing in Sand or Gravel (minutes/day) 

Table 15-59. Number of Minutes Spent Playing in Outdoors on Sand, Gravel, Dirt, or 

Grass When Fill Dirt Was Present by the Number of Respondents 

Table 15-60. Number of Minutes Spent Playing on Sand, Gravel, Dirt, or Grass When Fill 

Dirt Was Present (minutes/day) 

Table 15-61. Range of the Time Spent Working in a Garden or Other Circumstances in a 

Month by the Number of Respondents 

Table 15-62. Number of Hours Spent Working with Soil in a Garden or Other 

Circumstances Working (hours/month) 

Table 15-63. Range of Number of Minutes Spent Playing on Grass in a Day by the 

Number of Respondents 

Table 15-64. Number of Minutes Spent Playing on Grass (minutes/day) 

Table 15-65. Number of Times Swimming in a Month in Freshwater Swimming Pool by the 

Number of Respondents 

Table 15-66. Range of the Average Amount of Time Actually Spent in the Water by 

Swimmers by the Number of Respondents 

Table 15-67. Number of Minutes Spent Swimming in a Month in Freshwater Swimming 

Pool (minutes/month) 

Table 15-68. Statistics for 24-Hour Cumulative Number of Minutes Spent Working in a 

Main Job 

Table 15-69. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food 

Preparation 

Table 15-70. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Cleanup 

Table 15-71. Statistics for 24-Hour Cumulative Number of Minutes Spent Cleaning House 

Table 15-72. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor 

Cleaning 

Table 15-73. Statistics for 24-Hour Cumulative Number of Minutes Spent in Clothes Care 

Table 15-74. Statistics for 24-Hour Cumulative Number of Minutes Spent in Car 

Repair/Maintenance 

Table 15-75. Statistics for 24-Hour Cumulative Number of Minutes Spent in Other Repairs 

Table 15-76. Statistics for 24-Hour Cumulative Number of Minutes Spent in Plant Care 

Table 15-77. Statistics for 24-Hour Cumulative Number of Minutes Spent in Animal Care 

Table 15-78. Statistics for 24-Hour Cumulative Number of Minutes Spent in Other 

Household Work 

Table 15-79. Statistics for 24-Hour Cumulative Number of Minutes Spent in Indoor Playing 

Table 15-80. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor 

Playing 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 15 - Activity Factors 

Table 15-81. Statistics for 24-Hour Cumulative Number of Minutes Spent for Car Repair 

Services 

Table 15-82. Statistics for 24-Hour Cumulative Number of Minutes Spent Washing, etc. 

Table 15-83. Statistics for 24-Hour Cumulative Number of Minutes Spent 

Sleeping/Napping 

Table 15-84. Statistics for 24-Hour Cumulative Number of Minutes Spent Attending Full 

Time School 

Table 15-85. Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports 

Table 15-86. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor 

Recreation 

Table 15-87. Statistics for 24-Hour Cumulative Number of Minutes Spent in Exercise 

Table 15-88. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food 

Preparation 

Table 15-89. Statistics for 24-Hour Cumulative Number of Minutes Spent Doing 

Dishes/Laundry 

Table 15-90. Statistics for 24-Hour Cumulative Number of Minutes Spent in Housekeeping 

Table 15-91. Statistics for 24-Hour Cumulative Number of Minutes Spent in Bathing 

Table 15-92. Statistics for 24-Hour Cumulative Number of Minutes Spent in 

Yardwork/Maintenance 

Table 15-93. Statistics for 24-Hour Cumulative Number of Minutes Spent in 

Sports/Exercise 

Table 15-94. Statistics for 24-Hour Cumulative Number of Minutes Eating or Drinking 

Table 15-95. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at an 

Auto Repair Shop/Gas Station 

Table 15-96. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a 

Gym/Health Club 

Table 15-97. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at the 

Laundromat 

Table 15-98. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at Work 

(non-specific) 

Table 15-99. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at the 

Dry Cleaners 

Table 15-100. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a 

Bar/Nightclub/Bowling Alley 

Table 15-101. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a 

Restaurant 

Table 15-102. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at 

School 

Table 15-103. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a 

Plant/Factory/Warehouse 

Table 15-104. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on 

a Sidewalk, Street, or in the Neighborhood 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 15 - Activity Factors 

Table 15-105. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors in a 

Parking Lot 

Table 15-106. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a 

Service Station or Gas Station 

Table 15-107. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a 

Construction Site 

Table 15-108. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on 

School Grounds/Playground 

Table 15-109. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a 

Park/Golf Course 

Table 15-110. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a 

Pool/River/Lake 

Table 15-111. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a 

Restaurant/Picnic 

Table 15-112. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a 

Farm 

Table 15-113. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the 

Kitchen 

Table 15-114. Statistics for 24-Hour Cumulative Number of Minutes Spent in the 

Bathroom 

Table 15-115. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the 

Bedroom 

Table 15-116. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the 

Garage 

Table 15-117. Statistics for 24-Hour Cumulative Number of Minutes Spent in the 

Basement 

Table 15-118. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the 

Utility Room or Laundry Room 

Table 15-119. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the 

Outdoor Pool or Spa 

Table 15-120. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the 

Yard or Other Areas Outside the House 

Table 15-121. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in a 

Car 

Table 15-122. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in a 

Truck (Pick-up/Van) 

Table 15-123. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on 

a Motorcycle, Moped, or Scooter 

Table 15-124. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in 

Other Trucks 

Table 15-125. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on 

a Bus 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 15 - Activity Factors 

Table 15-126. Statistics for 24-Hour Cumulative Number of Minutes Spent Walking 

Table 15-127. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on 

a Bicycle/Skateboard/ Rollerskate 

Table 15-128. Statistics for 24-Hour Cumulative Number of Minutes Spent Waiting on a 

Bus, Train etc., Stop 

Table 15-129. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on 

a Train/Subway/Rapid Transit 

Table 15-130. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on 

an Airplane 

Table 15-131. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors in a 

Residence (all rooms) 

Table 15-132. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors 

(outside the residence) 

Table 15-133. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling 

Inside a Vehicle 

Table 15-134. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Near 

a Vehicle 

Table 15-135. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors 

Other Than Near a Residence or Vehicle Such as Parks, Golf Courses, or 

Farms 

Table 15-136. Statistics for 24-Hour Cumulative Number of Minutes Spent in an Office or 

Factory 

Table 15-137. Statistics for 24-Hour Cumulative Number of Minutes Spent in Malls, 

Grocery Stores, or Other Stores 

Table 15-138. Statistics for 24-Hour Cumulative Number of Minutes Spent in Schools, 

Churches, Hospitals, and Public Buildings 

Table 15-139. Statistics for 24-Hour Cumulative Number of Minutes Spent in 

Bars/Nightclubs, Bowling Alleys, and Restaurants 

Table 15-140. Statistics for 24-Hour Cumulative Number of Minutes Spent in Other 

Outdoors Such as Auto Repair Shops, Laundromats, Gyms, and at Work 

(non-specific) 

Table 15-141. Statistics for 24-Hour Cumulative Number of Minutes Spent with Smokers 

Present 

Table 15-142. Range of Time (minutes) Spent Smoking Based on the Number of 

Respondents 

Table 15-143. Number of Minutes Spent Smoking (minutes/day) 

Table 15-144. Range of Time Spent Smoking Cigars or Pipe Tobacco by the Number of 

Respondents 

Table 15-145. Number of Minutes Spent Smoking Cigars or Pipe Tobacco (minutes/day) 

Table 15-146. Range of Numbers of Cigarettes Smoked Based on the Number of 

Respondents 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 15 - Activity Factors 

Table 15-147. Range of Numbers of Cigarettes Smoked by Other People Based on 

Number of Respondents 

Table 15-148. Range of Numbers of Cigarettes Smoked While at Home Based on the 

Number of Respondents 

Table 15-149. Differences in Time Use (hours/week) Grouped by Sex, Employment 

Status, and Marital Status for the Surveys Conducted in 1965 and 1975 

Table 15-150. Time Use (hours/week) Differences by Age for the Surveys Conducted in 

1965 and 1975 

Table 15-151. Time Use (hours/week) Differences by Education for the Surveys 

Conducted in 1965 and 1975 

Table 15-152. Time Use (hours/week) Differences by Race for the Surveys Conducted in 

1965 and 1975 

Table 15-153. Mean Time Spent (hours/week) in Ten Major Activity Categories Grouped 

by Regions 

Table 15-154. Total Mean Time Spent (minutes/day) in Ten Major Activity Categories 

Grouped by Type of Day 

Table 15-155. Mean Time Spent (minutes/day) in Ten Major Activity Categories During 

Four Waves of Interviews 

Table 15-156. Mean Time Spent (hours/week) in Ten Major Activity Categories Grouped 

by Gender 

Table 15-157. Percent Responses of Children’s “Play” (activities) Locations in Maryvale, 

Arizona 

Table 15-158. Occupational Tenure of Employed Individuals by Age and Sex 

Table 15-159. Occupational Tenure for Employed Individuals Grouped by Sex and Race 

Table 15-160. Occupational Tenure for Employed Individuals Grouped by Sex and 

Employment Status 

Table 15-161. Occupational Tenure of Employed Individuals Grouped by Major 

Occupational Groups and Age 

Table 15-162. Voluntary Occupational Mobility Rates for Workers Age 16 Years and 

Older 

Table 15-163. Values and Their Standard Errors for Average Total Residence Time, T, 

for Each Group in Survey 

Table 15-164. Total Residence Time, t (years), Corresponding to Selected Values of R(t) 

by Housing Category 

Table 15-165. Residence Time of Owner/Renter Occupied Units 

Table 15-166. Percent of Householders Living in Houses for Specified Ranges of Time 

Table 15-167. Descriptive Statistics for Residential Occupancy Period 

Table 15-168. Descriptive Statistics for Both Genders by Current Age 

Table 15-169. Summary of Residence Time of Recent Home Buyers (1993) 

Table 15-170. Tenure in Previous Home (Percentage Distribution) 

Table 15-171. Number of Miles Moved (Percentage Distribution) 

Table 15-172. Confidence in Activity Patterns Recommendations 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 15 - Activity Factors 

Table 15-173. Confidence in Occupational Mobility Recommendations 

Table 15-174. Recommendations for Population Mobility 

Table 15-175. Confidence in Population Mobility Recommendations 

Table 15-176. Summary of Recommended Values for Activity Factors 

Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries 

Table 15A-2. Differences in Average Time Spent in Different Activities Between 

California and National Studies (minutes per day for age 18-64 years) 

Table 15A-3. Time Spent in Various Microenvironments 

Table 15A-4. Major Time Use Activity Categories 

Table 15A-5. Mean Time Spent (minutes/day) for 87 Activities Grouped by Day of the 

Week 

Table 15A-6. Weighted Mean Hours Per Week by Gender: 87 Activities and 10 

Subtotals 

Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure 

Table 15B-1. Annual Geographical Mobility Rates, by Type of Movement for Selected 1­

Year Periods: 1960-1992 (numbers in thousands) 

Table 15B-2. Mobility of the Resident Population by State: 1980 

Figure 15-1. Distribution of Individuals Moving by Type of Move: 1991-92 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 16 - Consumer Products 

16. CONSUMER PRODUCTS 

16.1. BACKGROUND 

16.2. KEY CONSUMER PRODUCTS USE STUDIES 

16.3. RELEVANT CONSUMER PRODUCTS USE STUDY 

16.4. RECOMMENDATIONS 

REFERENCES FOR CHAPTER 16 

APPENDIX 16A 

Table 16-1. Consumer Products Found in the Typical U.S. Household

Table 16-2. Frequency of Use for Household Solvent Products (users-only)

Table 16-3. Exposure Time of Use for Household Solvent Products (users-only)

Table 16-4. Amount of Products Used for Household Solvent Products (users-only)

Table 16-5. Time Exposed After Duration of Use for Household Solvent Products (usersonly) 

Table 16-6. Frequency of Use and Amount of Product Used for Adhesive Removers 

Table 16-7. Adhesive Remover Usage by Gender 

Table 16-8. Frequency of Use and Amount of Product Used for Spray Paint 

Table 16-9. Spray Paint Usage by Gender 

Table 16-10. Frequency of Use and Amount of Product Used for Paint Removers/Strippers 

Table 16-11. Paint Stripper Usage by Gender 

Table 16-12. Total Exposure Time of Performing Task and Product Type Used by Task for 

Household Cleaning Products 

Table 16-13. Percentile Rankings for Total Exposure Time in Performing Household Tasks 

Table 16-14. Mean Percentile Rankings for Frequency of Performing Household Tasks 

Table 16-15. Mean and Percentile Rankings for Exposure Time Per Event of Performing 

Household Tasks 

Table 16-16. Total Exposure Time for Ten Product Groups Most Frequently Used for 

Household Cleaning 

Table 16-17. Total Exposure Time of Painting Activity of Interior Painters (hours) 

Table 16-18. Exposure Time of Interior Painting Activity/Occasion (hours) and Frequency 

of Occasions Spent Painting Per Year 

Table 16-19. Amount of Paint Used by Interior Painters 

Table 16-20. Number of Respondents Using Cologne, Perfume, Aftershave or Other 

Fragrances at Specified Daily Frequencies 

Table 16-21. Number of Respondents Using Any Aerosol Spray Product for Personal Care 

Item Such as Deodorant or Hair Spray at Specified Daily Frequencies 

Table 16-22. Number of Minutes Spent in Activities Working with or Being Near Freshly 

Applied Paints (minutes/day) 

Table 16-23. Number of Minutes Spent in Activities Working with or Near Household 

Cleaning Agents Such as Scouring Powders or Ammonia (minutes/day) 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 16 - Consumer Products 

Table 16-24. Number of Minutes Spent in Activities (at home or elsewhere) Working with 

or Near Floorwax, Furniture Wax or Shoe Polish (minutes/day) 

Table 16-25. Number of Minutes Spent in Activities Working with or Being Near Glue 

Table 16-26. Number of Minutes Spent in Activities Working with or Near Solvents, Fumes 

or Strong Smelling Chemicals (minutes/day) 

Table 16-27. Number of Minutes Spent in Activities Working with or Near Stain or Spot 

Removers (minutes/day) 

Table 16-28. Number of Minutes Spent in Activities Working with or Near Gasoline or 

Diesel-powered Equipment, Besides Automobiles (minutes/day) 

Table 16-29. Number of Minutes Spent Using Any Microwave Oven (minutes/day) 

Table 16-30. Number of Respondents Using a Humidifier at Home 

Table 16-31. Number of Respondents Indicating that Pesticides Were Applied by the 

Professional at Home to Eradicate Insects, Rodents, or Other Pests at 

Specified Frequencies 

Table 16-32. Number of Respondents Reporting Pesticides Applied by the Consumer at 

Home to Eradicate Insects, Rodents, or Other Pests at Specified 

Frequencies 

Table 16-33. Number of Minutes Spent in Activities Working with or Near Pesticides, 

Including Bug Sprays or Bug Strips (minutes/day) 

Table 16-34. Amount and Frequency of Use of Various Cosmetic and Baby Products 

Table 16-35. Summary of Consumer Products Use Studies 

Table 16A-1. Volumes Included in 1992 Simmons Study 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 17 - Residential Building Characteristics 

17. RESIDENTIAL BUILDING CHARACTERISTICS 

17.1. INTRODUCTION 

17.2. BUILDING CHARACTERISTICS 

17.2.1. Key Volumes of Residence Studies 

17.2.2. Volumes and Surface Areas of Rooms 

17.2.3. Mechanical System Configurations 

17.2.4. Type of Foundation 

17.3. TRANSPORT RATES 

17.3.1. 

17.3.2. 

17.3.3. 

17.3.4. 

17.3.5. 

17.3.6. 

17.3.7. 

17.4. SOURCES 

17.4.1. 

17.4.2. 

17.4.3. 

Background 

Air Exchange Rates 

Infiltration Models 

Deposition and Filtration 

Interzonal Airflows 

Water Uses 

House Dust and Soil 

Source Descriptions for Airborne Contaminants 

Source Descriptions for Waterborne Contaminants 

Soil and House Dust Sources 

17.5. ADVANCED CONCEPTS 

17.5.1. Uniform Mixing Assumption 

17.5.2. Reversible Sinks 

17.6 RECOMMENDATIONS 

REFERENCES FOR CHAPTER 17 

Table 17-1. Summary of Residential Volume Distributions 

Table 17-2. Average Estimated Volumes of U.S. Residences, by Housing Type and 

Ownership 

Table 17-3. Residential Volumes in Relation to Household Size and Year of Construction 

Table 17-4. Dimensional Quantities for Residential Rooms 

Table 17-5. Examples of Products and Materials Associated with Floor and Wall 

Surfaces in Residences 

Table 17-6. Percent of Residences with Basement, by Census Region and EPA Region 

Table 17-7. Percent of Residences with Certain Foundation Types by Census Region 

Table 17-8. States Associated with EPA Regions and Census Regions 

Table 17-9. Summary of Major Projects Providing Air Exchange Measurements in the 

PFT Database 

Table 17-10. Summary Statistics for Air Exchange Rates (air changes per hour-ACH), by 

Region 

Table 17-11. Distributions of Residential Air Exchange Rates by Climate Region and 

Season 

Exposure Factors Handbook August 1997 
Volume III - Activity Factors 

Chapter 17 - Residential Building Characteristics 

Table 17-12. Deposition Rates for Indoor Particles 

Table 17-13. Particle Deposition During Normal Activities 

Table 17-14. In-house Water Use Rates (gcd), by Study and Type of Use 

Table 17-15. Summary of Selected HUD and Power Authority Water Use Studies 

Table 17-16. Showering and Bathing Water Use Characteristics 

Table 17-17. Showering Characteristics for Various Types of Shower Heads 

Table 17-18. Toilet Water Use Characteristics 

Table 17-19. Toilet Frequency Use Characteristics 

Table 17-20. Dishwasher Frequency Use Characteristics 

Table 17-21. Dishwasher Water Use Characteristics 

Table 17-22. Clothes Washer Frequency Use Characteristics 

Table 17-23. Clothes Washer Water Use Characteristics 

Table 17-24. Range of Water Uses for Clothes Washers 

Table 17-25. Total Dust Loading for Carpeted Areas 

Table 17-26. Particle Deposition and Resuspension During Normal Activities 

Table 17-27. Dust Mass Loading After One Week Without Vacuum Cleaning 

Table 17-28. Simplified Source Descriptions for Airborne Contaminants 

Table 17-29. Volume of Residence Surveys 

Table 17-30. Air Exchange Rates Surveys 

Table 17-31. Recommendations - Residential Parameters 

Table 17-32. Confidence in House Volume Recommendations 

Table 17-33. Confidence in Air Exchange Rate Recommendations 

Figure 17-1. Elements of Residential Exposure 

Figure 17-2. Cumulative Frequency Distributions for Residential Volumes from the PFT 

Data Base and the U.S. DOE’s RECs 

Figure 17-3. Configuration for Residential Forced-air Systems 

Figure 17-4. Idealized Patterns of Particle Deposition Indoors 

Figure 17-5. Air Flows for Multiple-zone Systems 

Exposure Factors Handbook August 1997 
About the Handbook

The National Center for Environmental Assessment has prepared this handbook to address 

factors commonly used in exposure assessments. This handbook was first published in 1989 

in response to requests from many EPA Program and Regional offices for additional guidance 

on how to select values for exposure assessments. 

This document provides a summary of the available data on consumption of drinking water; 

consumption of fruits, vegetables, beef, dairy products, and fish; soil ingestion; inhalation rates; 

skin surface area; soil adherence; lifetime; activity patterns; body weight; consumer product use; 

and the reference residence. 

The handbook is equipped with a number of tools meant to help the user navigate through the 

Exposure Factors Handbook. The following is a description of these tools. 

Some of the links that appear throughout the document will transport the user to another 

portion of the handbook. An indication that the user has encountered a hypertext link is that the 

hand in the Adobe Acrobat Reader will change to a hand with a pointing finger or an arrow. 

Arrow buttons at the top of the screen are part of the Adobe Acrobat Reader program and will 

allow the user to move through files which have been opened. These arrows include: 

This button will move the user to the first page of a file. 

This button will move the user to the previous page. 

This button will move the user to the next page. 

This button will move the user to the last page of a file. 

This button will move the user to the last view displayed on the computer monitor. 

+ This button will magnify the view on the screen. Push the button, move the mouse to 

the portion of the screen the user wants magnified, and click the left mouse button. 

The user will need to use the last view button (the double arrow pointing to the left above) to 

maneuver from the tables to the text of the Exposure Factors Handbook. A more convenient 

way of maneuvering between the tables and text is being explored. 

At the left of each page in the Exposure Factors Handbook, the user will find a Bookmarks Panel

containing bookmarks to jump to any other chapter, table, appendix, or figure in the handbook. 
PREFACE 

The National Center for Environmental Assessment (NCEA) of EPA’s Office of 

Research and Development (ORD) has prepared this handbook to address factors 

commonly used in exposure assessments. This handbook was first published in 1989 in 

response to requests from many EPA Program and Regional offices for additional 

guidance on how to select values for exposure factors. 

Several events sparked the efforts to revise the Exposure Factors Handbook. First, 

since its publication in 1989, new data have become available. Second, the Risk 

Assessment Council issued a memorandum titled, "Guidance on Risk Characterization for 

Risk Managers and Risk Assessors," dated February 26, 1992, which emphasized the use 

of multiple descriptors of risk (i.e., measures of central tendency such as average or mean, 

or high end), and characterization of individual risk, population risk, important 

subpopulations. A new document was issued titled "Guidance for Risk Characterization," 

dated February 1995. This document is an update of the guidance issued with the 1992 

policy. Third, EPA published the revised Guidelines for Exposure Assessment in 1992. 

As part of the efforts to revise the handbook, the EPA Risk Assessment Forum 

sponsored a two-day peer involvement workshop which was conducted during the summer 

of 1993. The workshop was attended by 57 scientists from academia, consulting firms, 

private industry, the States, and other Federal agencies. The purpose of the workshop 

was to identify new data sources, to discuss adequacy of the data and the feasibility of 

developing statistical distributions and to establish priorities. 

As a result of the peer involvement workshop, three new chapters were added to 

the handbook. These chapters are: Consumer Product Use, Residential Building 

Characteristics, and Intake of Grains. This document also provides a summary of the 

Exposure Factors Handbook August 1997 
available data on consumption of drinking water; consumption of fruits, vegetables, beef, 

dairy products, grain products, and fish; breast milk intake; soil ingestion; inhalation rates; 

skin surface area; soil adherence; lifetime; activity patterns; and body weight. 

A new draft handbook that incorporated comments from the 1993 workshop was 

published for peer review in June 1995. A peer review workshop was held in July 1995 

to discuss comments on the draft handbook. A new draft of the handbook that addressed 

comments from the 1995 peer review workshop was submitted to the Science Advisory 

Board (SAB) for review in August 1996. An SAB workshop meeting was held December 

19-20, 1996, to discuss the comments of the SAB reviewers. Comments from the SAB 

review have been incorporated into the current handbook. 

Exposure Factors Handbook August 1997 
FOREWORD 

The National Center for Environmental Assessment (NCEA) of EPA's Office of 

Research and Development (ORD) has five main functions: (1) providing risk assessment 

research, methods, and guidelines; (2) performing health and ecological assessments; 

(3) developing, maintaining, and transferring risk assessment information and training; 

(4) helping ORD set research priorities; and (5) developing and maintaining resource 

support systems for NCEA. The activities under each of these functions are supported by 

and respond to the needs of the various program offices. In relation to the first function, 

NCEA sponsors projects aimed at developing or refining techniques used in exposure 

assessments. 

This handbook was first published in 1989 to provide statistical data on the various 

factors used in assessing exposure. This revised version of the handbook provides the 

up-to-date data on these exposure factors. The recommended values are based solely 

on our interpretations of the available data. In many situations different values may be 

appropriate to use in consideration of policy, precedent or other factors. 

Michael A. Callahan 

Director 

National Center for Environmental Assessment 

Washington Office 

Exposure Factors Handbook August 1997 
AUTHORS, CONTRIBUTORS, AND REVIEWERS 

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

Development was responsible for the preparation of this handbook. The original document 

was prepared by Versar Inc. under EPA Contract No. 68-02-4254, Work Assignment No. 

189. John Schaum, of NCEA-Washington Office, served as the EPA Work Assignment 

Manager, providing overall direction and coordination of the production effort as well as 

technical assistance and guidance. Revisions, updates, and additional preparation were 

provided by Versar Inc. under Contract Numbers 68-D0-0101, 68-D3-0013, and 

68-D5-0051. Russell Kinerson and Greg Kew have served as EPA Work Assignment 

Managers during previous efforts of the update process. Jackie Moya served as Work 

Assignment Manager for the current updated version, providing overall direction, technical 

assistance, and serving as contributing author. 

AUTHORS DESKTOP PUBLISHING GRAPHICS 

Patricia Wood Susan Perry Kathy Bowles 

Linda Phillips Jennifer Baker 

Aderonke Adenuga WORD PROCESSING 

Mike Koontz CD-ROM PRODUCTION 

Harry Rector Valerie Schwartz Charles Peck 

Charles Wilkes 

Maggie Wilson 

Exposure Assessment Division

Versar Inc.

Springfield, VA

Exposure Factors Handbook August 1997 
CONTRIBUTORS AND REVIEWERS 

The following EPA individuals have reviewed and/or have been contributing 

authors of this document. 

Michael Dellarco Paul Pinsky 

Robert McGaughy John Schaum 

Amy Mills Paul White 

Jacqueline Moya Amina Wilkins 

Susan Perlin Chieh Wu 

The following individuals were Science Advisory Board Reviewers: 

Members 

Dr. Joan Daisey 

Lawrence Berkley Laboratory 

Berkley, California

Dr. Paul Bailey 

Mobil Business Resources 

Corporation 

Paulsboro, New Jersey 

Dr. Robert Hazen 

State of New Jersey Department of 

Environmental Protection and 

Energy 

Trenton, New Jersey 

Dr. Timothy Larson 

Department of Civil Engineering 

University of Washington 

Seattle, Washington 

Dr. Kai-Shen Liu 

California Department of Health 

Services 

Berkeley, California 

Dr. Paul Lioy 

Environmental Occupational Health 

Sciences Institute 

Piscataway, New Jersey 

Dr. Maria Morandi 

University of Texas School of Public 

Health 

Houston, Texas 

Dr. Jonathan M. Samet

The Johns Hopkins University

Baltimore, Maryland 

Mr. Ron White 

American Lung Association 

Washington, D.C. 

Dr. Lauren Zeise 

California Environmental Protection 

Agency 

Berkeley, California 

Exposure Factors Handbook August 1997 
Federal Experts 

Dr. Richard Ellis Ms. Alanna J. Moshfegh 

U.S. Department of Agriculture U.S. Department of Agriculture

Washington, D.C. Washington, D.C.

An earlier draft of this document was peer reviewed by a panel of experts at a peer-review 

workshop held in 1995. Members of the Peer Review Panel were as follows: 

Edward Avol Patricia Guenther 

Department of Preventive Medicine Beltsville Human Nutrition 

School of Medicine Research Center 

University of Southern California U.S. Department of Agriculture 

James Axley P.J. (Bert) Hakkinen 

School of Architecture Paper Product Development & 

Yale University Paper 

Technology Divisions 

David Burmaster The Proctor & Gamble Company 

Alceon Corporation 

Mary Hama 

Steven Colome Beltsville Human Nutrition 

Integrated Environmental Services Research Center 

U.S. Department of Agriculture 

Michael DiNovi 

Chemistry Review Branch Dennis Jones 

U.S. Food & Drug Administration Agency for Toxic Substances & 

Disease Registry 

Dennis Druck 

Environmental Scientist John Kissel 

Center of Health Promotion & Department of Environmental 

Preventive Medicine Health 

U.S. Army School of Public Health & 

Community Medicine 

J. Mark Fly 

Department of Forestry, Wildlife, & Neil Klepeis

 Fisheries Information Systems & Services, 

University of Tennessee Inc. 

Larry Gephart 

Exxon Biomedical Sciences, Inc.

Exposure Factors Handbook August 1997 
Andrew Persily P. Barry Ryan 

National Institute of Standards & Department of Environmental & 

Technologies Occupational Health 

Rollins School of Public Health 

Barbara Petersen Emory University 

Technical Assessment Systems, 

Inc. Val Schaeffer 

U.S. Consumer Product Safety 

Thomas Phillips Commission 

Research Division 

California Air Resources Board Brad Shurdut 

DowElanco 

Paul Price 

ChemRisk John Talbott 

U.S. Department of Energy 

John Risher 

Division of Toxicology Frances Vecchio 

The Agency for Toxic Substances & Beltsville Human Nutrition 

Disease Registry Research Center 

U.S. Department of Agriculture 

John Robinson 

University of Maryland 

Peter Robinson 

The Proctor & Gamble Company 

Exposure Factors Handbook August 1997 
The following individuals within EPA have reviewed an earlier draft of this document 

and provided valuable comments: 

OFFICE REVIEWERS/CONTRIBUTORS 

Office of Research and Development Maurice Berry 

Jerry Blancato 

Elizabeth Bryan 

Curtis Dary 

Stan Durkee 

Manuel Gomez 

Wayne Marchant 

Sue Perlin 

James Quanckenboss 

Glen Rice 

Lance Wallace 

Office of Emergency and Remedial Jim Konz 

Response 

Office of Pollution, Pesticides and Pat Kennedy 

Toxic Substances Cathy Fehrenbacker 

Office of Water Denis Borum 

Helen Jacobs 

Office of Air Quality Planning and Warren Peters 

Standards 

EPA Regions Steve Ehlers - Reg. VI 

Maria Martinez - Reg. VI 

Mike Morton - Reg. VI 

Jeffrey Yurk - Reg. VI 

Youngmoo Kim - Reg. VI 

In addition, the National Exposure Research Laboratory (NERL) of the Office of 

Research and Development of EPA made an important contribution to this handbook by 

conducting additional analyses of the National Human Activity Pattern Survey (NHAPS) 

data. EPA input to the NHAPS data analysis came from Karen A. Hammerstrom and 

Jacqueline Moya from NCEA-Washington Office; William C. Nelson from NERL-RTP, and 

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

Vegas. 

Exposure Factors Handbook August 1997 
The EPA Office of Water made an important contribution by conducting an analysis of 

the USDA Continuing Survey of Food Intakes by Individual (CSFII) data. They provided 

fish intake rates for the general population. The analysis was conducted under the 

direction of Helen Jacobs from the Office of Water. 

Exposure Factors Handbook August 1997 
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Chapter 1 - Introduction 

1. INTRODUCTION 

1.1. PURPOSE 

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

behaviors and characteristics which affect exposure to environmental contaminants, and 

(2) recommend values to use for these factors. These recommendations are not legally 

binding on any EPA program and should be interpreted as suggestions which program 

offices or individual exposure assessors can consider and modify as needed. Most of 

these factors are best quantified on a site or situation-specific basis. The handbook has 

strived to include full discussions of the issues which assessors should consider in 

deciding how to use these data and recommendations. The handbook is intended to serve 

as a support document to EPA's Guidelines for Exposure Assessment (U.S. EPA, 1992a).

The Guidelines were developed to promote consistency among the various exposure 

assessment activities that are carried out by the various EPA program offices. This 

handbook assists in this goal by providing a consistent set of exposure factors to calculate 

dose. 

Purpose 

C	Summarize data on human behaviors and characteristics affecting exposure 

C	Recommend exposure factor values 

1.2. INTENDED AUDIENCE 

The Exposure Factors Handbook is addressed to exposure assessors inside the 

Agency as well as outside, who need to obtain data on standard factors needed to 

calculate human exposure to toxic chemicals. 

1.3. BACKGROUND 

This handbook is the update of an earlier version prepared in 1989. Revisions have 

been made in the following areas: 

• addition of drinking water rates for children; 

• changes in soil ingestion rates for children; 

• addition of soil ingestion rates for adults; 

• addition of tapwater consumption for adults and children; 

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Chapter 1 - Introduction 

• addition of mean daily intake of food class and subclass by region, age and per 

capita rates; 

• addition of mean moisture content of selected fruits, vegetables, grains, fish, 

meat, and dairy products; 

• addition of food intake by class in dry weight per kg of body weight per day; 

• update of homegrown food intake; 

• expansion of data in the dermal chapter; 

• update of fish intake data; 

• expansion of data for time spent at residence; 

• update of body weight data; 

• addition of body weight data for infants; 

• update of population mobility data; 

• addition of new data for average time spent in different locations and various 

microenviron-ments; 

• addition of data for occupational mobility; 

• addition of breast milk ingestion; 

• addition of consumer product use; and 

• addition of reference residence factors. 

Variation Among Studies 

This handbook is a compilation of available data from a variety of different sources. 

With very few exceptions, the data presented are the analyses of the individual study 

authors. Since the studies included in this handbook varied in terms of their objectives, 

design, scope, presentation of results, etc., the level of detail, statistics, and terminology 

may vary from study to study and from factor to factor. For example, some authors used 

geometric means to present their results, while others used arithmetic means or 

distributions. Authors have sometimes used different terms to describe the same racial 

populations. Within the constraint of presenting the original material as accurately as 

possible, EPA has made an effort to present discussions and results in a consistent 

manner. Further, 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. 

1.3.1. 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 estimating exposure factors. The handbook contains 

summaries of selected studies published through August 30, 1997. 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 1 - Introduction 

General Considerations 

Many scientific studies were reviewed for possible inclusion in this handbook. 

Studies were selected based on the following considerations: 

• Level of peer review: Studies were selected predominantly from the peerreviewed literature and final government reports. Internal or interim reports were 

therefore avoided. 

• Accessibility: Studies were preferred that the user could access in their entirety 

if needed. 

• Reproducibility: Studies were sought that contained sufficient information so that 

methods could be reproduced, or at least so the details of the author’s work could 

be accessed and evaluated. 

• Focus on exposure factor of interest: Studies were chosen 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. 

• Data pertinent to the U.S.: Studies were selected that addressed the U.S. 

population. Data from populations outside the U.S. were sometimes included if 

behavioral patterns and other characteristics of exposure were similar. 

• Primary data: Studies were deemed preferable if based on primary data, but 

studies based on secondary sources were also included where they offered an 

original analysis. For example, the handbook cites studies of food consumption 

based on original data collected by the USDA National Food Consumption 

Survey. 

• Current information: Studies were chosen only if they were sufficiently recent to 

represent current exposure conditions. This is an important consideration for 

those factors that change with time. 

• 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. 

• Validity of approach: Studies utilizing experimental procedures or approaches 

that more likely or closely capture the desired measurement were selected. In 

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Chapter 1 - Introduction 

general, 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 rely 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. 

• Representativeness of the population: Studies seeking to characterize the 

national population, 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. 

• Variability in the population: Studies were sought that characterized any 

variability within populations. 

• Minimal (or defined) bias in study design: Studies were sought that were designed 

with minimal bias, or at least if biases were suspected to be present, the direction 

of the bias (i.e., an over or under estimate of the parameter) was either stated or 

apparent from the study design. 

• Minimal (or defined) uncertainty in the data: Studies were sought with minimal 

uncertainty in the data, which was judged by evaluating all the considerations 

listed above. At least, studies were preferred that identified uncertainties, such 

as those due to inherent variability in environmental and exposure-related 

parameters or possible measurement error. Studies that documented Quality 

Assurance/Quality Control measures were preferable. 

Key versus relevant studies 

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. 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 Considerations." For 

example, in Chapter 14 of Volume III, one set of studies is deemed to best address the 

attributes listed and is designated as "key." Other applicable studies, including foreign 

data, believed to have value to handbook users, but having fewer attributes, are 

designated "relevant." 

Exposure Factors Handbook August 1997 
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Chapter 1 - Introduction 

Key vs. Relevant Studies 

C	Key studies used to derive recommendations 

C	Relevant studies included to provide additional perspective 

1.3.2. Using the Handbook in an Exposure Assessment 

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

pathways of exposure, (2) identifying the environmental media which transports the 

contaminant, (3) determining the contaminant concentration, (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 EPA guidance documents. These include, but are not 

limited to the following: 

• Guidelines for Exposure Assessment (U.S. EPA 1992a); 

• Dermal Exposure Assessment: Principles and Applications (U.S. EPA 1992b); 

• Methodology for Assessing Health Risks Associated with Indirect Exposure to 

Combustor Emissions (U.S. EPA, 1990); 

• Risk Assessment Guidance for Superfund (U.S. EPA, 1989); 

• Estimating Exposures to Dioxin-Like Compounds (U.S. EPA, 1994); 

• Superfund Exposure Assessment Manual (U.S. EPA, 1988a); 

• Selection Criteria for Mathematical Models Used in Exposure Assessments (U.S. 

EPA 1988b); 

• Selection Criteria for Mathematical Models Used in Exposure Assessments (U.S. 

EPA 1987); 

• Standard Scenarios for Estimating Exposure to Chemical Substances During Use 

of Consumer Products (U.S. EPA 1986a); 

• Pesticide Assessment Guidelines, Subdivisions K and U (U.S. EPA, 1984, 1986b); 

and 

• Methods for Assessing Exposure to Chemical Substances, Volumes 1-13 (U.S. 

EPA, 1983-1989). 

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. 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 1 - Introduction 

In addition to the references listed above, this handbook discusses the 

recommendations provided by the American Industrial Health Council (AIHC) - Exposure 

Factors Sourcebook (May 1994) for some of the major exposure factors. The AIHC 

Sourcebook summarizes and evaluates statistical data for various exposure factors used 

in risk assessments. Probability distributions for specific exposure factors were derived 

from the available scientific literature using @Risk simulation software. Each factor is 

described by a specific term, such as lognormal, normal, cumulative type, or triangular. 

Other distributions included Weibull, beta logistic, and gamma. Unlike this handbook, 

however, the Sourcebook does not provide a description and evaluation of every study 

available on each exposure factor. 

Most of the data presented in this handbook are derived from studies that targeted 

(1) the general population (e.g., USDA food consumptin surveys); and (2) a sample 

population from a specific area or group (e.g., Calabrese’s et al. (1989) soil ingestion study 

using children from the Amherst, Massachusetts, area). Due to unique activity patterns, 

preferences, practices and biological differences, various segments of the population may 

experience exposures that are different from those of the general population, which, in 

many cases, may be greater. It is necessary for risk or exposure assessors characterizing 

a diverse population, to identify and enumerate certain groups within the general 

population who are at risk for greater contaminant exposures or exhibit a heightened 

sensitivity to particular chemicals. For further guidance on addressing susceptible 

populations, it is recommended to consult the EPA, National Center for Environmental 

Assessment document Socio-demographic Data Used for Identifying Potentially Highly 

Exposed Subpopulations (to be released as a final document in the Fall of 1997). 

Most users of the handbook will be preparing estimates of exposure which are to be 

combined with dose-response factors to estimate risk. Some of the exposure factors (e.g., 

life time, body weight) presented in this document are also used in generating doseresponse relationships. In order to develop risk estimates properly, assessors must use 

dose-response relationships in a manner consistent with exposure conditions. Although, 

it is beyond the scope of this document to explain in detail how assessors should address 

this issue, a discussion (see Appendix A of this chapter) has been included which 

describes how dose-response factors can be modified to be consistent with the exposure 

factors for a population of interest. This should serve as a guide for when this issue is a 

concern. 

1.3.3. Approach Used to Develop Recommendations for Exposure Factors 

As discussed above, EPA first reviewed all literature pertaining to a factor and 

determined relevant and key studies. The key studies were used to derive 

recommendations for the values of each factor. The recommended values were derived 

solely from EPA’s interpretation of the available data. Different values may be appropriate 

Exposure Factors Handbook August 1997 
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Chapter 1 - Introduction 

for the user to select in consideration of policy, precedent, strategy, or other factors such 

as site-specific information. EPA’s procedure for developing recommendations was as 

follows: 

Recommendations and Confidence Ratings 

C	Recommendations based on data from single or multiple key studies 

C	Variability and limitation of the data evaluated 

C	Recommendations rated as low, medium, and high confidence 

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 is described in Section 1.3.1. 

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 value for that population. If there were 

multiple key studies, all 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 were 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 were presented and the user of this handbook must 

employ judgment in selecting the most appropriate value for the population of interest. 

In cases where the national population was of interest, the mid-point of the range was 

usually judged to be the most appropriate value. 

3. The variability of the factor across the population was discussed. If adequate data 

were available, the variability was described as either a series of percentiles or a 

distribution. 

4. Limitations of the data 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 have 

been used in the derivation of the recommended value. 

5. Finally, 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 EPA’s judgment on the quality of the underlying data used to derive 

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Chapter 1 - Introduction 

the recommendation. This judgment was made using the guidelines shown in Table 

1-1. Table 1-1 is an adaptation of the General Considerations discussed earlier in 

Section 1.3.1. Clearly this is a continuum from low to high and judgment was used to 

determine these ratings. Recommendations given in this handbook are accompanied 

by a discussion of the rationale for their rating. 

Table 1-2 summarizes EPA's recommendations and confidence ratings for the various 

exposure factors. 

It is important to note that the study elements listed in Table 1-1 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 depend on the exposure factor of 

interest. Also, the relative weights given to the elements for the various factors were 

subjective and based on the professional judgement of the authors of this handbook. In 

general, most studies would rank high with regard to "level of peer review," "accessibility," 

"focus on the factor of interest," and "data pertinent to the U.S." These elements are 

important for the study to be included in this handbook. However, a high score of these 

elements does not necessarily translate into a high overall score. Other elements in Table 

1-1 were also examined to determine the overall score. For example, the adequacy of 

data collection period may be more important when determining usual intake of foods in 

a population. On the other hand, 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 addition, 

some exposure factors are more easily measured than others. For example, soil ingestion 

by children is estimated by measuring, in the feces, the levels of certain elements found 

in soil. Body weight, however, can be measured directly and it is, therefore, a more 

reliable measurement. This is reflected in the 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. 

1.3.4. Characterizing Variability 

This document attempts to characterize variability of each of the factors. Variability 

is characterized in one or more of three ways: (1) as tables 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 in this document wherever 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 that 

variability has been characterized (i.e., average, upper percentiles, multiple percentiles, 

fitted distribution) are presented in Table 1-3. The term upper percentile is used 

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Chapter 1 - Introduction 

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. 

An attempt was made to present percentile values in the recommendations that are 

consistent with the exposure estimators defined in the Exposure Guidelines (i.e., mean, 

50th, 90th, 95th, 98th, and 99.9th percentile). This was not, however, always possible 

because either 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 Exposure Guidelines within the context of risk descriptors and not 

individual exopusure factors. For example, the Guidelines stated 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 use of Monte Carlo or other probabilistic analysis require a selection of 

distributions or histograms for the input parameters. Although this handbook is not 

intended to provide a complete guidance on the use of Monte Carlo and other probabilistic 

analyses, the following should be considered when using such techniques: 

C 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. 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. 

C It is important to note that the selection of distributions can be highly site specific 

and will always involve some degree of judgment. Distributions derived from 

national data may not represent local conditions. To the extent possible, an 

assessor should use distributions or frequency histograms derived from local 

surveys to assess risks locally. When distributional data are drawn from national 

or other surrogate population, it is important that the assessor address the extent 

to which local conditions may differ from the surrogate data. 

In addition to a qualitative statement of uncertainty, the representativeness 

assumption should be appropriately addressed as part of a sensitivity analysis. 

C Distribution functions to be used in Monte Carlo analysis may be derived by fitting 

an appropriate function to empirical data. In doing this, it should be recognized 

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Chapter 1 - Introduction 

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 way 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 which 

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 such as Statistical 

Methods for Environmental Pollution Monitoring, Gilbert, R.O., 1987, Van 

Nostrand Reinhold; off-the-shelf computer software such as Best-Fit by Palisade 

Corporation can be used to statistically determine the distributions that fit the 

data. 

C 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; and

- 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 - examples include: soil

ingestion by adults; 

-- 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 - examples include: 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 - examples include: soil 

ingestion by children. 

1.4. GENERAL EQUATION FOR CALCULATING DOSE 

The definition of exposure as used in the Exposure Guidelines (U.S. EPA, 1992a) is 

"condition of a chemical contacting the outer boundary of a human." This means contact 

with the visible exterior of a person such as the skin, and openings such as the mouth, 

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Chapter 1 - Introduction 

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). The magnitude of 

exposure (dose) is the amount of agent available at human exchange boundaries (skin, 

lungs, gut) where absorption takes place during some specified time. An example of 

exposure and dose for the oral route as presented in the the EPA Exposure Guidelines is 

shown in Figure 1-1. 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 over which exposure occurred. The ADD can be calculated by averaging 

the potential dose (Dpot) over body weight and an averaging time.

Total Potential Dose ADD ' pot Body Weight x Averaging Time (Eqn. 1-1) 

For cancer effects, where the biological response is usually described in terms of 

lifetime probabilities, even though exposure does not occur over the entire lifetime, doses 

are often presented as lifetime average daily doses (LADDs). The LADD takes the form 

of the Equation 1-1 with lifetime replacing averaging time. The LADD is a very common 

term used in carcinogen risk assessment where linear non-threshold models are 

employed. 

The total exposure can be expressed as follows: 

Total Potential Dose ' C x IR x ED (Eqn. 1-2) 

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 

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Chapter 1 - Introduction 

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 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. 

The exposure duration is the length of time that contaminant contact lasts. The time 

a person lives in an area, frequency of bathing, time spent indoors versus outdoors, etc. 

all affect the exposure duration. The Activity Factors Chapter (Volume III, Chapter 15) 

gives some examples of population behavior patterns, which may be useful for estimating 

exposure durations to be used in the exposure calculations. 

When the above parameter values 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 intake rate specified by the other parameters in 

the equation. 

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 exposure) the dose-response parameters for 

carcinogen risks have been adjusted for the difference in absorption across body barriers 

between humans and the experimental animals used to derive such parameters. 

Therefore, the exposure assessment in these cases is based on the 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. 

The lifetime value used in the LADD version of Equation 1-1 is the period of time over 

which the dose is averaged. For carcinogens, the derivation of the dose-response 

parameters usually assumes no explicit number of years as the duration of a lifetime, and 

the nominal value of 75 years is considered 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 administered 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. 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. 

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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 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 grams per day per kilogram 

body weight. 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 ingestion of fish, breast milk, and the 

inhalation of air are not normalized to body weight. In this case, the exposure assessor 

needs to use (in Equation 1-1) the average weight of the exposed population during the 

time when the exposure actually occurs. If the exposure occurs continuously throughout 

an individual’s life or only during the adult ages, using an adult weight of 71.8 kg should 

provide sufficient accuracy. If the body weight of the individuals in the population whose 

risk is being evaluated is non-standard in some way, such as for children or for firstgeneration immigrants who may be smaller than the national population, and if reasonable 

values are not available in the literature, then a model of intake as a function of body 

weight must be used. One such model is discussed in Appendix 1A of this chapter. Some 

of the parameters (primarily concentrations) used in estimating exposure are exclusively 

site specific, and therefore default recommendations could not be used. 

The food ingestion rate values provided in this handbook are generally expressed as 

"as consumed" since this is the fashion in which data are reported by survey respondents. 

This is of importance because concentration data to be used in the dose equation are 

generally measured in uncooked food samples. In most situations, the only practical 

choice is to use the "as consumed" ingestion rate and the uncooked concentration. 

However, it should be recognized that cooking generally results in some reductions in 

weight (e.g., loss of moisture), and that if the mass of the contaminant in the food remains 

constant, then the concentration of the contaminant in the cooked food item will increase. 

Therefore, if the "as consumed" ingestion rate and the uncooked concentration are used 

in the dose equation, dose may be underestimated. On the other hand, cooking may 

cause a reduction in mass of contaminant and other ingredients such that the overall 

concentration of contaminant does not change significantly. In this case, combining 

cooked ingestion rates and uncooked concentration will provide an appropriate estimate 

of dose. Ideally, food concentration data should be adjusted to account for changes after 

cooking, then the "as consumed" intake rates are appropriate. In the absence of data, it 

is reasonable to assume that no change in contaminant concentration occurs after 

cooking. Except for general population fish consumption and home produced foods, 

uncooked intake rate data were not available for presention in this handbook. Data on the 

general population fish consumption have been presented in this handbook (Section 10.2) 

in both "as consumed" and uncooked basis. It is important for the assessor to be aware 

Exposure Factors Handbook August 1997 
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Chapter 1 - Introduction 

of these issues and choose intake rate data that best matches the concentration data that 

is being used. 

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, such as 129 g of fish eaten 

per meal (U.S. EPA, 1996). The duration should be based on the number of 

events or, in this case, meals. 

• The intake rate also can be based on a long-term average, such as 10 g/day. In 

this case the duration should be based on the total time interval over which the 

exposure occurs. 

The objective is to define the terms so that when multiplied, they give the appropriate 

estimate of mass of 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. Consider the case in which 

a person eats a 129-g fish meal approximately five times per month (long-term average is 

21.5 g/day) for 30 years; or 21.5 g/day of fish every day for 30 years.

(129 g/meal)(5 meals/mo)(mo/30 d)(365 d/yr)(30 yrs) = 235,425 g 

(21.5 g/day)(365 d/yr)(30 yrs) = 235,425 g

Thus, a frequency of either 60 meals/year or a duration of 365 days/year could be used 

as long as it is matched with the appropriate intake rate. 

1.5. RESEARCH NEEDS 

In an earlier draft of this handbook, reviewers were asked to identify factors or areas 

where further research is needed. The following list is a compilation of areas for future 

research identified by the peer reviewers and authors of this document: 

• The data and information available with respect to occupational exposures are 

quite limited. Efforts need to be directed to identify data or references on 

occupational exposure. 

• Further research is necessary to refine estimates of fish consumption, particularly 

by subpopulations of subsistence fishermen. 

Exposure Factors Handbook August 1997 
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Chapter 1 - Introduction 

• Research is needed to better estimate soil intake rates, particularly how to 

extrapolate short-term data to chronic exposures. Data on soil intake rates by 

adults are very limited. Research in this area is also recommended. Research 

is also needed to refine methods to calculate soil intake rate (i.e., inconsistencies 

among tracers and input/output misalignment errors indicate a fundamental 

problem with the methods). Research is also needed to obtain more data to 

better estimate soil adherence. 

• In cases where several studies of equal quality and data collection procedures 

are available for an exposure factor, procedures need to be developed to combine 

the data in order to create a single distribution of likely values for that factor. 

• Reviewers recommended that the handbook be made available in CD ROM and 

that the data presented be made available in a format that will allow the users to 

conduct their own analysis. The intent is to provide a comprehensive factors tool 

with interactive menu to guide users to areas of interest, word searching features, 

and data base files. 

• Reviewers recommended that EPA derive distribution functions using the 

empirical data for the various exposure factors to be used in Monte Carlo or other 

probabilistic analysis. 

• Research is needed to derive a methodology to extrapolate from short-term data 

to long-term or chronic exposures. 

• Reviewers recommended that the consumer products chapter be expanded to 

include more products. A comprehensive literature search needs to be conducted 

to investigate other sources of data. 

• Breastmilk intake. 

• More recent data on tapwater intake. 

• SAB recommended analysis of 1994 and 1995 CSFII data. 

Exposure Factors Handbook August 1997 
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Chapter 1 - Introduction 

1.6. ORGANIZATION 

The handbook is organized into three volumes as follows: 

Volume I - General Factors 

Chapter 1 Provides the overall introduction to the 

handbook. 

Chapter 2 Presents an analysis of uncertainty and 

discusses methods that can be used to evaluate 

and present the uncertainty associated with 

exposure scenario estimates. 

Chapter 3 Provides factors for estimating human exposure 

through ingestion of water. 

Chapter 4 Provides factors for estimating exposure through 

ingestion of soil. 

Chapter 5 Provides factors for estimating exposure as a 

result of inhalation of vapors and particulates. 

Chapter 6 Presents factors for estimating dermal exposure 

to environmental contaminants that come in 

contact with the skin. 

Chapter 7 Provides data on body weight. 

Chapter 8 Provides data on life expectancy. 

Volume II - Ingestion Factors 

Chapter 9 Provides factors for estimating exposure through 

ingestion of fruits and vegetables. 

Chapter 10 Provides factors for estimating exposure through 

ingestion of fish. 

Chapter 11 Provides factors for estimating exposure through 

ingestion of meats and dairy products. 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 1 - Introduction 

Chapter 12 Presents data for estimating exposure through 

ingestion of grain products. 

Chapter 13 Presents factors for estimating exposure through 

ingestion of home produced food. 

Chapter 14 Presents data for estimating exposure through 

ingestion of breast milk. 

Volume III - Activity Factors 

Chapter 15 Presents data on activity factors (activity 

patterns, population mobility, and occupational 

mobility). 

Chapter 16 Presents data on consumer product use. 

Chapter 17 Presents factors used in estimating residential 

exposures. 

Figure 1-2 provides a roadmap to assist users of this handbook in locating 

recommended values and confidence ratings for the various exposure factors presented 

in these chapters. A glossary is provided at the end of Volume III. 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Appendix 1A 

APPENDIX 1A

 RISK CALCULATIONS USING EXPOSURE FACTORS HANDBOOK DATA 

AND DOSE-RESPONSE INFORMATION FROM THE 

INTEGRATED RISK INFORMATION SYSTEM (IRIS) 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Appendix 1A 

APPENDIX 1A 

RISK CALCULATIONS USING EXPOSURE FACTORS HANDBOOK 

DATA AND DOSE-RESPONSE INFORMATION FROM IRIS 

1. INTRODUCTION 

When calculating risk estimates for a specific population, whether the entire national 

population or some sub-population, the exposure information (either from this handbook 

or from other data) must be combined with dose-response information. The latter typically 

comes from the IRIS data base, which summarizes toxicity data for each agent separately. 

Care must be taken that the assumptions about population parameters in the doseresponse analysis are consistent with the population parameters used in the exposure 

analysis. This Appendix discusses procedures for insuring this consistency. 

In the IRIS derivation of threshold based dose-response relationships (U.S. EPA, 

1996), such as the RfD and the RfCs based on adverse systemic effects, there has 

generally been no explicit use of human exposure factors. In these cases the numerical 

value of the RfD and RfC comes directly from animal dosing experiments (and occasionally 

from human studies) and from the application of uncertainty factors to reflect issues such 

as the duration of the experiment, the fact that animals are being used to represent 

humans and the quality of the study. However in developing cancer dose-response (D-R) 

assessments, a standard exposure scenario is assumed in calculating the slope factor 

(i.e., human cancer risk per unit dose) on the basis of either animal bioassay data or 

human data. This standard scenario has traditionally been assumed to be typical of the 

3 U.S. population: 1) body weight = 70 kg; 2) air intake rate = 20 m /day; 3) drinking water 

intake = 2 liters/day; 4) lifetime = 70 years. In RfC derivations for cases involving an 

3 adverse effect on the respiratory tract, the air intake rate of 20 m /day is assumed. The 

use of these specific values has depended on whether the slope factor was derived from 

animal or human epidemiologic data: 

C Animal Data: For dose-resopnse (D-R) studies based on animal data, scale 

animal doses to human equivalent doses using a human body weight assumption 

of 70 kg. No explicit lifetime adjustment is necessary because the assumption is 

made that events occurring in the lifetime animal bioassay will occur with equal 

probability in a human lifetime, whatever that might happen to be. 

C Human Data - In the analysis of human studies (either occupational or general 

population), the Agency has usually made no explicit assumption of body weight 

or human lifetime. For both of these parameters there is an implicit assumption 

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Appendix 1A 

that the population usually of interest has the same descriptive parameters as the 

population analyzed by the Agency. In the rare situation where this assumption 

is known to be wrong, the Agency has made appropriate corrections so that the 

dose-response parameters represent the national average population. 

When the population of interest is different than the national average (standard) 

population, the dose-response parameter needs to be adjusted. In addition, when the 

population of interest is different than the population from which the exposure factors in 

this handbook were derived, the exposure factor needs to be adjusted. Two generic 

examples of situations where these adjustments are needed are as follows: 

A) Detailed study of recent data, such as are presented in this handbook, show that 

3 EPA’s standard assumptions (i.e., 70 kg body weight, 20 m /day air inhaled, and 2 L/day 

water intake) are inaccurate for the national population and may be inappropriate for subpopulations under consideration. The handbook addresses most of these situations by 

providing gender- and age-specific values and by normalizing the intake values to body 

weight when the data are available, but it may not have covered all possible situations. 

An example of a sub-population with a different mean body weight would be females, with 

an average body weight of 60 kg or children with a body weight dependent on age. 

Another example of a non-standard sub-population would be a sedentary hospital 

3 population with lower than 20 m /day air intake rates. 

B) The population variability of these parameters is of interest and it is desired to 

estimate percentile limits of the population variation. Although the detailed methods for 

estimating percentile limits of exposure and risk in a population are beyond the scope of 

this document, one would treat the body weight and the intake rates discussed in Sections 

2 to 4 of this appendix as distributions, rather than constants. 

2. CORRECTIONS FOR DOSE-RESPONSE PARAMETERS 

The correction factors for the dose-response values tabulated in the IRIS data base 

for carcinogens are summarized in Table 1A-1. Use of these correction parameters is 

necessary to avoid introducing errors into the risk analysis. The second column of Table 

1A-1 shows the dependencies that have been assumed in the typical situation where the 

human dose-response factors have been derived from the administered dose in animal 

studies. This table is applicable in most cases that will be encountered, but it is not 

applicable when: a) the effective dose has been derived with a pharmacokinetic model and 

b) the dose-response data has been derived from human data. In the former case, the 

subpopulation parameters need to be incorporated into the model. In the latter case, the 

correction factor for the dose-response parameter must be evaluated on a case-by case 

basis by examining the specific data and assumptions in the derivation of the parameter. 

Exposure Factors Handbook August 1997 
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Appendix 1A 

 As one example of the use of Table 1A-1, the recommended value for the average 

consumption of tapwater for adults in the U. S. population derived in this document 

(Chapter 3), is 1.4 liters per day. The drinking water unit risk for dichlorvos, as given in 

the IRIS information data base is 8.3 x 10-6 per μg/l, and was calculated from the slope 

factor assuming the standard intake, I S

W , of 2 liters per day. For the United States 

population drinking 1.4 liters of tap water per day the corrected drinking water unit risk 

-6 should be 8.3 x 10-6 x (1.4/2) = 5.8 x 10 per Fg/l. The risk to the average individual is 

then estimated by multiplying this by the average concentration in units of Fg/l. 

Another example is when the risk for women drinking water contaminated with 

dichlorvos is to be estimated. If the women have an average body weight of 60 kg, the 

correction factor for the drinking water unit risk is (disregarding the correction discussed 

2/3 in the above paragraph), from Table 1A-1, is (70/60) = 1.11. Here the ratio of 70 to 60 

is raised to the power of 2/3. The corrected water unit risk for dichlorvos is 8.3 x 10-6 x 

1.11 = 9.2 x 10-6 per Fg/l. As before, the risk to the average individual is estimated by 

multiplying this by the water concentration. 

When human data are used to derive the risk measure, there is a large variation in 

the different data sets encountered in IRIS, so no generalizations can be made about 

global corrections. However, the typical default exposure values used for the air intake 

3 of an air pollutant over an occupational lifetime are: air intake is 10 m /day for an 8-hour 

shift, 240 days per year with 40 years on the job. If there is continuous exposure to an 

ambient air pollutant, the lifetime dose is usually calculated assuming a 70-year lifetime. 

3. CORRECTIONS FOR INTAKE DATA 

When the body weight, W P, of the population of interest differs from the body weight, 

W E, of the population from which the exposure values in this handbook were derived, the 

following model furnishes a reasonable basis for estimating the intake of food and air (and 

probably water also) in the population of interest. Such a model is needed in the absence 

of data on the dependency of intake on body size. This occurs for inhalation data, where 

the intake data are not normalized to body weight, whereas the model is not needed for 

food and tap water intakes if they are given in units of intake per kg body weight. 

The model is based on the dependency of metabolic oxygen consumption on body 

size. Oxygen consumption is directly related to food (calorie) consumption and air intake 

and indirectly to water intake. For mammals of a wide range of species sizes (Prosser and 

Brown, 1961), and also for individuals of various sizes within a species, the oxygen 

consumption and calorie (food) intake varies as the body weight raised to a power between 

0.65 and 0.75. A value of 0.667 = 2/3 has been used in EPA as the default value for 

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Appendix 1A 

adjusting cross-species intakes, and the same factor has been used for intra-species 

intake adjustments. 

[NOTE: Following discussions by an interagency task force (Federal Register, 1992), 

the agreement was that a more accurate and defensible default value would be to choose 

the power to 3/4 rather than 2/3. A recent article (West et al., 1997) has provided a 

theoretical basis for the 3/4 power scaling. This will be the standard value to be used in 

future assessments, and all equations in this Appendix will be modified in future risk 

assessments. However, because risk assessors now use the current IRIS information, 

this discussion is presented with the previous default assumption of 2/3]. 

 With this model, the relation between the daily air intake in the population of interest, 

3 P E 3 IA

P = (m /day) , and the intake in the population described in this handbook, I = (m /day)E 

A 

is: 

P E 2/3 IA

P

 = IA

E

 x (W /W ) . 

4. CALCULATION OF RISKS FOR AIR CONTAMINANTS 

The risk is calculated by multiplying the IRIS air unit risk, corrected as described in 

Table 1A-1, by the air concentration. But since the correction factor involves the intake 

in the population of interest (IA

P

), that quantity must be included in the equation, as follows: 

P P (Risk) = (air unit risk) x (air concentration) 

S = (air unit risk) x (I P

/20) x (70/W )

P 2/3 x (air concentration) A 

S P E 2/3 = (air unit risk) x [( I /20)] x (70/W ) E x (W /W ) P 2/3 x (air concentration) A 

S = (air unit risk) x (I E

/20) x (70/W )

E 2/3 x (air concentration) A 

S In this equation the air unit risk from the IRIS data base (air unit risk) , the air intake

data in the handbook for the populations where it is available (I E

) and the body weight of A 

E that population (W ) are included along with the standard IRIS values of the air intake (20 

3 m /day) and body weight (70 kg). 

For food ingestion and tap water intake, if body weight-normalized intake values from 

this handbook are used, the intake data do not have to be corrected as in Section 3 above. 

In these cases, corrections to the dose-response parameters in Table 1A-1 are sufficient. 

Exposure Factors Handbook August 1997 
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Appendix 1A 

5. REFERENCES 

Federal Register. (1992) Cross-species scaling factor for carcinogen risk assessments 

based on equivalence of (mg/kg-day)

3/4. Draft report. Federal Register, 57(109): 

24152-24173, June 5, 1992. 

Prosser, C.L.; Brown, F.A. (1961) Comparative Animal physiology, 2nd edition. WB 

Saunders Co. p. 161. 

U.S. EPA. (1996) Background Documentation. Integrated Risk Information System 

(IRIS). Online. National Center for Environmental Assessment, Cincinnati, Ohio. 

Background Documentation available from: Risk Information Hotline, National Center 

for Environmental Assessment, U.S. EPA, 26 W. Martin Luther King Dr. Cincinnati, 

OH 45268. (513) 569-7254 

West, G.B.; Brown, J.H.; Enquist, B.J. (1997) A general model of the origin of allometric 

scaling laws in biology. Science 276:122-126. 

Exposure Factors Handbook August 1997 
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Chapter 2 - Variability and Uncertainty 

2. VARIABILITY AND UNCERTAINTY 

The chapters that follow will discuss exposure factors and algorithms for estimating 

exposure. Exposure factor values can be used to obtain a range of exposure estimates 

such as average, high-end and bounding estimates. It is instructive here to return to the 

general equation for potential Average Daily Dose (ADDpot) that was introduced in the 

opening chapter of this handbook: 

' Contaminant Concentration x Intake Rate x Exposure Duration ADDpot (Eqn. 2-1) Body Weight x Averaging Time 

With the exception of the contaminant concentration, all parameters in the above 

equation are considered exposure factors and, thus, are treated in fair detail in other 

chapters of this handbook. Each of the exposure factors involves humans, either in terms 

of their characteristics (e.g., body weight) or behaviors (e.g., amount of time spent in a 

specific location, which affects exposure duration). While the topics of variability and 

uncertainty apply equally to contaminant concentrations and the rest of the exposure 

factors in equation 2-1, the focus of this chapter is on variability and uncertainty as they 

relate to exposure factors. Consequently, examples provided in this chapter relate 

primarily to exposure factors, although contaminant concentrations may be used when they 

better illustrate the point under discussion. 

This chapter also is intended to acquaint the exposure assessor with some of the 

fundamental concepts and precepts related to variability and uncertainty, together with 

methods and considerations for evaluating and presenting the uncertainty associated with 

exposure estimates. Subsequent sections in this chapter are devoted to the following 

topics: 

• Distinction between variability and

uncertainty;

• Types of variability;

C	 Methods of confronting variability;

• Types of uncertainty and 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 

Exposure Factors Handbook August 1997 
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Chapter 2 - Variability and Uncertainty 

assessment is a component of risk-assessment process, the general concepts apply 

equally to the exposure-assessment component. 

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 

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. An instructive 

analogy has been drawn by the National Research Council (NRC, 1994: Chapter 10), 

based on the objective of estimating the distance between the earth and the moon. Prior 

to fairly recent technology developments, it was difficult to make accurate measurements 

of this distance, resulting in measurement uncertainty. Because the moon's orbit is 

elliptical, the distance is a variable quantity. If only a few measurements were to be taken 

without knowledge of the elliptical pattern, then either of the following incorrect conclusions 

might be reached: 

• That the measurements were faulty, thereby ascribing to uncertainty what was 

actually caused by variability; or 

• That the moon's orbit was random, thereby not allowing uncertainty to shed light 

on seemingly unexplainable differences that are in fact variable and predictable. 

A more fundamental error in the above situation would be to incorrectly estimate the 

true distance, by assuming that a few observations were sufficient. This latter pitfall -­

treating a highly variable quantity as if it were invariant or only uncertain -- is probably the 

most relevant to the exposure or risk assessor. 

Now consider a situation that relates to 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 

Exposure Factors Handbook August 1997 
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Chapter 2 - Variability and Uncertainty 

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. 

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 decision-makers 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 related to an individual's location, activity, and behavior or 

preferences at a particular point in time, as well as pollutant emission rates and 

physical/chemical processes that affect concentrations in various media (e.g., air, soil, 

food and water). The variations in pollutant-specific emissions or processes, and in 

individual locations, activities or behaviors, 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, three types of variability can be distinguished: 

• Variability across locations (Spatial Variability); 

• Variability over time (Temporal 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. 

Exposure Factors Handbook August 1997 
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Chapter 2 - Variability and Uncertainty 

Higher consumption may occur among populations located near large bodies of water 

such as the Great Lakes or coastal areas. As another example, outdoor pollutant levels 

can be affected at the regional level by industrial activities and at the local level by 

activities of individuals. In general, higher exposures tend to be associated with closer 

proximity to 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 

shorter-term variability are differences in industrial or personal activities on weekdays 

versus weekends or at different times of the day. 

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 and activity 

patterns. 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. 

2.3 . CONFRONTING VARIABILITY 

According to the National Research Council (NRC 1994), variability can be 

confronted 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 and hope for the best. This strategy tends to work best when the variability is 

relatively small. For example, the assumption that all adults weigh 70 kg is likely to be 

correct within ±25% for most adults. 

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 

Exposure Factors Handbook August 1997 
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Chapter 2 - Variability and Uncertainty 

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 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. 

2.4. CONCERN ABOUT UNCERTAINTY 

Why should the exposure assessor be concerned with uncertainty? As noted by the 

U.S. EPA (1992), exposure assessment can involve a broad array of information sources 

and analysis techniques. 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 by analogy. When scientists report 

quantities that they have measured, they are expected to routinely report an estimate of 

the probable error associated with such measurements. Because 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 uncertainties associated with their estimates. 

Exposure Factors Handbook August 1997 
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Chapter 2 - Variability and Uncertainty 

Additional reasons for addressing uncertainty in exposure or risk assessments (U.S. 

EPA, 1992, Morgan and Henrion, 1990) include the following: 

• Uncertain information from different sources of different quality often must be 

combined for the assessment; 

• Decisions need to be made about whether or how to expend resources to acquire 

additional information,; 

• Biases may result in so-called "best estimates" that in actuality are not very 

accurate; and 

• Important factors and potential sources of disagreement in a problem can be 

identified. 

Addressing uncertainty will increase the likelihood that results of an assessment or 

analysis will be used in an appropriate manner. Problems rarely are solved to everyone's 

satisfaction, and decisions rarely are reached on the basis of a single piece of evidence. 

Results of prior analyses can shed light on current assessments, particularly if they are 

couched in the context of prevailing uncertainty at the time of analysis. Exposure 

assessment tends to be an iterative process, beginning with a screening-level assessment 

that may identify the need for more in-depth assessment. One of the primary goals of the 

more detailed assessment is to reduce uncertainty in estimated exposures. This objective 

can be achieved more efficiently if guided by presentation and discussion of factors 

thought to be primarily responsible for uncertainty in prior estimates. 

2.5. TYPES OF UNCERTAINTY AND REDUCING UNCERTAINTY 

The problem of uncertainty in exposure or risk assessment is relatively large, and can 

quickly become too complex for facile treatment unless it is divided into smaller and more 

manageable topics. One method of division (Bogen, 1990) involves classifying sources 

of uncertainty according to the step in the risk assessment process (hazard identification, 

dose-response assessment, exposure assessment or risk characterization) at which they 

can occur. A more abstract and generalized approach preferred by some scientists is to 

partition all uncertainties among the three categories of bias, randomness and true 

variability. These ideas are discussed later in some examples. 

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). 

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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 above can be 

further defined by examining their principal causes. Sources and examples for each type 

of uncertainty are summarized in Table 2-2. 

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. 

2.6 . ANALYZING VARIABILITY AND UNCERTAINTY 

Exposure assessments often are developed in a phased approach. The initial phase 

usually screens out the exposure scenarios or pathways that are not expected to pose 

much risk, to eliminate them from more detailed, resource-intensive review. Screeninglevel assessments typically examine exposures 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 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. 

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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 reviews such as 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. 

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. 

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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 uncertainty is high, a sensitivity analysis can be used to 

credible 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 the Exposure Factors 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. At a minimum, the assessor should 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 upperpercentile 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? 

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Any exposure estimate developed by an assessor will have associated assumptions 

about the setting, chemical, population characteristics, and how contact 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 will be required 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. 

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Chapter 3 - Drinking Water Intake 

3. DRINKING WATER INTAKE 

3.1. BACKGROUND 

Drinking water is a potential source of human exposure to toxic substances. 

Contamination of drinking water may occur by, for example, percolation of toxics through 

the soil to ground water that is used as a source of drinking water; runoff or discharge to 

surface water that is used as a source of drinking water; intentional or unintentional 

addition of substances to treat water (e.g., chlorination); and leaching of materials from 

plumbing systems (e.g., lead). Estimating the magnitude of the potential dose of toxics 

from drinking water requires information on the quantity of water consumed. The purpose 

of this section is to describe key published studies that provide information on drinking 

water consumption (Section 3.2) and to provide recommendations of consumption rate 

values that should be used in exposure assessments (Section 3.6).

Currently, the U.S. EPA uses the quantity of 2 L per day for adults and 1 L per day 

for infants (individuals of 10 kg body mass or less) as default drinking water intake rates 

(U.S. EPA, 1980; 1991). These rates include drinking water consumed in the form of 

juices and other beverages containing tapwater (e.g., coffee). 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 some individuals in physically-demanding occupations or living in warmer regions may 

have high levels of water intake. 

Numerous studies cited in this chapter have generated data on drinking water intake 

rates. In general, these sources support EPA's use of 2 L/day for adults and 1 L/day for 

children as upper-percentile tapwater intake rates. Many of the studies have reported fluid 

intake rates for both total fluids and tapwater. Total fluid intake is defined as consumption 

of all types of fluids including tapwater, milk, soft drinks, alcoholic beverages, and water 

intrinsic to purchased foods. Total tapwater is defined as 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.). Data for both consumption categories are presented in the 

sections that follow. However, for the purposes of exposure assessments involving 

source-specific contaminated drinking water, intake rates based on total tapwater are 

more representative of source-specific tapwater intake. Given the assumption that 

purchased foods and beverages are widely distributed and less likely to contain sourcespecific water, the use of total fluid intake rates may overestimate the potential exposure 

to toxic substances present only in local water supplies; therefore tapwater intake, rather 

than total fluid intake, is emphasized in this section. 

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All studies on drinking water intake that are currently available are based on shortterm survey data. Although short-term data may be suitable for obtaining mean intake 

values that are representative of both short- and long-term consumption patterns, upperpercentile values may be different for short-term and long-term data because more 

variability generally occurs in short-term surveys. It should also be noted that most 

drinking water surveys currently available are based on recall. This may be a source of 

uncertainty in the estimated intake rates because of the subjective nature of this type of 

survey technique. 

The distribution of water intakes is usually, but not always, lognormal. Instead of 

presenting only the lognormal parameters, the actual percentile distributions are presented 

in this handbook, usually with a comment on whether or not it is lognormal. To facilitate 

comparisons between studies, the mean and the 90th percentiles are given for all studies 

where the distribution data are available. With these two parameters, along with 

information about which distribution is being followed, one can calculate, using standard 

formulas, the geometric mean and geometric standard deviation and hence any desired 

percentile of the distribution. Before doing such a calculation one must be sure that one 

of these distributions adequately fits the data. 

The available studies on drinking water consumption are summarized in the following 

sections. They have been classified as either key studies or relevant studies based on the 

applicability of their survey designs to exposure assessment of the entire United States 

population. Recommended intake rates are based on the results of key studies, but 

relevant studies are also presented to provide the reader with added perspective on the 

current state-of-knowledge pertaining to drinking water intake. 

3.2. KEY GENERAL POPULATION STUDIES ON DRINKING WATER INTAKE 

Canada Department of Health and Welfare (1981) - Tapwater Consumption in 

Canada - In a study conducted by the Canadian Department of Health and Welfare, 970 

individuals from 295 households were surveyed to determine the per capita total tapwater 

intake rates for various age/sex groups during winter and summer seasons (Canadian 

Ministry of National Health and Welfare, 1981). Intake rate was also evaluated as a 

function of physical activity. The population that was surveyed matched the Canadian 1976 

census with respect to the proportion in different age, regional, community size and 

dwelling type groups. Participants monitored water intake for a 2-day period (1 weekday, 

and 1 weekend day) in both late summer of 1977 and winter of 1978. All 970 individuals 

participated in both the summer and winter surveys. The amount of tapwater consumed 

was estimated based on the respondents' identification of the type and size of beverage 

container used, compared to standard sized vessels. The survey questionnaires included 

a pictorial guide to help participants in classifying the sizes of the vessels. For example, 

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a small glass of water was assumed to be equivalent to 4.0 ounces of water, and a large 

glass was assumed to contain 9.0 ounces of water. The study also accounted for water 

derived from ice cubes and popsicles, and water in soups, infant formula, and juices. The 

survey did not attempt to differentiate between tapwater consumed at home and tapwater 

consumed away from home. The survey also did not attempt to estimate intake rates for 

fluids other than tapwater. Consequently, no intake rates for total fluids were reported. 

Daily consumption distribution patterns for various age groups are presented in Table 

3-1. For adults (over 18 years of age) only, the average total tapwater intake rate was 

1.38 L/day, and the 90th percentile rate was 2.41 L/day as determined by graphical 

interpolation. These data follow a lognormal distribution. The intake data for males, 

females, and both sexes combined as a function of age and expressed in the units of 

milliliters (grams) per kilogram body weight are presented in Table 3-2. The tapwater 

survey did not include body weights of the participants, but the body weight information 

was taken from a Canadian health survey dated 1981; it averaged 65.1 kg for males and 

55.6 kg for females. Intake rates for specific age groups and seasons are presented in 

Table 3-3. The average daily total tapwater intake rates for all ages and seasons 

combined was 1.34 L/day, and the 90th percentile rate was 2.36 L/day. The summer 

intake rates are nearly the same as the winter intake rates. The authors speculate that the 

reason for the small seasonal variation here is that in Canada, even in the summer, the 

ambient temperature seldom exceeded 20 degrees C and marked increase in water 

consumption with high activity levels has been observed in other studies only when the 

ambient temperature has been higher than 20 degrees. Average daily total tapwater 

intake rates as a function of the level of physical activity, as estimated subjectively, are 

presented in Table 3-4. The amounts of tapwater consumed that are derived from various 

foods and beverages are presented in Table 3-5. Note that the consumption of direct 

“raw” tapwater is almost constant across all age groups from school-age children through 

the oldest ages. The increase in total tapwater consumption beyond school age is due to 

coffee and tea consumption. 

Data concerning the source of tapwater (municipal, well, or lake) was presented in 

one table of the study. This categorization is not appropriate for making conclusions about 

consumption of ground versus surface water. 

This survey may be more representative of total tapwater consumption than some 

other less comprehensive surveys because it included data for some tapwater-containing 

items not covered by other studies (i.e., ice cubes, popsicles, and infant formula). One 

potential source of error in the study is that estimated intake rates were based on 

identification of standard vessel sizes; the accuracy of this type of survey data is not 

known. The cooler climate of Canada may have reduced the importance of large tapwater 

intakes resulting from high activity levels, therefore making the study less applicable to the 

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Chapter 3 - Drinking Water Intake 

United States. The authors were not able to explain the surprisingly large variations 

between regional tapwater intakes; the largest regional difference was between Ontario 

(1.18 liters/day) and Quebec (1.55 liters/day).

Ershow and Cantor (1989) - Total Water and Tapwater Intake in the United States: 

Population-Based Estimates of Quantities and Sources - Ershow and Cantor (1989) 

estimated water intake rates based on data collected by the USDA 1977-1978 Nationwide 

Food Consumption Survey (NFCS). Daily intake rates for tapwater and total water were 

calculated for various age groups for males, females, and both sexes combined. Tapwater 

was defined as "all water from the household tap consumed directly as a beverage or used 

to prepare foods and beverages." Total water was defined as tapwater plus "water intrinsic 

to foods and beverages" (i.e., water contained in purchased food and beverages). The 

authors showed that the age, sex, and racial distribution of the surveyed population closely 

matched the estimated 1977 U. S. population. 

 Daily total tapwater intake rates, expressed as mL (grams) per day by age group are 

presented in Table 3-6. These data follow a lognormal distribution. The same data, 

expressed as mL (grams) per kg body weight per day are presented in Table 3-7. A 

summary of these tables, showing the mean, the 10th and 90th percentile intakes, 

expressed as both mL/day and mL/kg-day as a function of age, is presented in Table 3-8. 

This shows that the mean and 90th percentile intake rates for adults (ages 20 to 65+) are 

approximately 1,410 mL/day and 2,280 mL/day and for all ages the mean and 90th 

percentile intake rates are 1,190 mL/day and 2,090 mL/day. Note that older adults have 

greater intakes than do adults between age 20 and 65, an observation bearing on the 

interpretation of the Cantor, et al. (1987) study which surveyed a population that was older 

than the national average (see Section 3.3). 

Ershow and Cantor (1989) also measured total water intake for the same age groups 

and concluded that it averaged 2,070 mL/day for all groups combined and that tapwater 

intake (1,190 mL/day) is 55 percent of the total water intake. (The detailed intake data for 

various age groups are presented in Table 3-9). Ershow and Cantor (1989) also 

concluded that, for all age groups combined, the proportion of tapwater consumed as 

drinking water, foods, and beverages is 54 percent, 10 percent and 36 percent, 

respectively. (The detailed data on proportion of tapwater consumed for various age 

groups are presented in Table 3-10). Ershow and Cantor (1989) also observed that males 

of all age groups had higher total water and tapwater consumption rates than females; the 

variation of each from the combined-sexes mean was about 8 percent. 

Ershow and Cantor (1989) also presented data on total water intake and tapwater 

intake for children of various ages. They found, for infants and children between the ages 

of 6 months and 15 years, that the total water intake per unit body weight increased 

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smoothly and sharply from 30 mL/kg-day above age 15 years to 190 mL/kg-day for ages 

less than 6 months. This probably represents metabolic requirements for water as a 

dietary constituent. However, they found that the intake of tapwater alone went up only 

slightly with decreasing age (from 20 to 45 mL/kg-day as age decreases from 11 years to 

less than 6 months). Ershow and Cantor (1989) attributed this small effect of age on 

tapwater intake to the large number of alternative water sources (besides tapwater) used 

for the younger age groups. 

With respect to region of the country, the northeast states had slightly lower average 

tapwater intake (1,200 mL/day) than the three other regions (which were approximately 

equal at 1,400 mL/day). 

This survey has an adequately large size (26,446 individuals) and it is a 

representative sample of the United States population with respect to age distribution, sex, 

racial composition, and residential location. It is therefore suitable as a description of 

national tapwater consumption. The chief limitation of the study is that the data were 

collected in 1978 and do not reflect the expected increase in the consumption of soft drinks 

and bottled water or changes in the diet within the last two decades. Since the data were 

collected for only a three-day period, the extrapolation to chronic intake is uncertain. 

Roseberry and Burmaster (1992) - Lognormal Distributions for Water Intake -

Roseberry and Burmaster (1992) fit lognormal distributions to the water intake data 

reported by Ershow and Cantor (1989) and estimated population-wide distributions for total 

fluid and total tapwater intake based on proportions of the population in each age group. 

Their publication shows the data and the fitted log-normal distributions graphically. The 

mean was estimated as the zero intercept, and the standard deviation was estimated as 

the slope of the best fit line for the natural logarithm of the intake rates plotted against their 

corresponding z-scores (Roseberry and Burmaster, 1992). Least squares techniques were 

used to estimate the best fit straight lines for the transformed data. Summary statistics for 

the best-fit lognormal distribution are presented in Table 3-11. In this table, the simulated 

balanced population represents an adjustment to account for the different age distribution 

of the United States population in 1988 from the age distribution in 1978 when Ershow and 

Cantor (1989) collected their data. Table 3-12 summarizes the quantiles and means of 

tapwater intake as estimated from the best-fit distributions. The mean total tapwater intake 

rates for the two adult populations (age 20 to 65 years, and 65+ years) were estimated to 

be 1.27 and 1.34 L/day. 

These intake rates were based on the data originally presented by Ershow and 

Cantor (1989). Consequently, the same advantages and disadvantages associated with 

the Ershow and Cantor (1989) study apply to this data set. 

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Chapter 3 - Drinking Water Intake 

3.3. RELEVANT GENERAL POPULATION STUDIES ON DRINKING WATER INTAKE 

National Academy of Sciences (1977) - Drinking Water and Health - NAS (1977) 

calculated the average per capita water (liquid) consumption per day to be 1.63 L. This 

figure was based on a survey of the following literature sources: Evans (1941); Bourne 

and Kidder (1953); Walker et al. (1957); Wolf (1958); Guyton (1968); McNall and Schlegel 

(1968); Randall (1973); NAS (1974); and Pike and Brown (1975). Although the calculated 

average intake rate was 1.63 L per day, NAS (1977) adopted a larger rate (2 L per day) 

to represent the intake of the majority of water consumers. This value is relatively 

consistent with the total tapwater intakes rate estimated from the key studies presented 

previously. However, the use of the term "liquid" was not clearly defined in this study, and 

it is not known whether the populations surveyed are representative of the adult U.S. 

population. Consequently, the results of this study are of limited use in recommending 

total tapwater intake rates and this study is not considered a key study. 

Hopkins and Ellis (1980) - Drinking Water Consumption in Great Britain - A study 

conducted in Great Britain over a 6-week period during September and October 1978, 

estimated the drinking water consumption rates of 3,564 individuals from 1,320 households 

in England, Scotland, and Wales (Hopkins and Ellis, 1980). The participants were 

selected randomly and were asked to complete a questionnaire and a diary indicating the 

type and quantity of beverages consumed over a 1-week period. Total liquid intake 

included total tapwater taken at home and away from home; purchased alcoholic 

beverages; and non-tapwater-based drinks. Total tapwater included water content of tea, 

coffee, and other hot water drinks; homemade alcoholic beverages; and tapwater 

consumed directly as a beverage. The assumed tapwater contents for these beverages 

are presented in Table 3-13. Based on responses from 3,564 participants, the mean 

intake rates and frequency distribution data for various beverage categories were 

estimated by Hopkins and Ellis (1980). These data are listed in Table 3-14. The mean 

per capita total liquid intake rate for all individuals surveyed was 1.59 L/day, and the mean 

per capita total tapwater intake rate was 0.95 L/day, with a 90th percentile value of about 

1.3 L/day (which is the value of the percentile for the home tapwater alone in Table 3-14). 

Liquid intake rates were also estimated for males and females in various age groups. 

Table 3-15 summarizes the total liquid and total tapwater intake rates for 1,758 males and 

1,800 females grouped into six age categories (Hopkins and Ellis, 1980). The mean and 

90th percentile total tapwater intake values for adults over age 18 years are, respectively, 

1.07 L/day and 1.87 L/day, as determined by pooling data for males and females for the 

three adult age ranges in Table 3-15. This calculation assumes, as does Table 3-14 and 

3-15, that the underlying distribution is normal and not lognormal.

The advantage of using these data is that the responses were not generated on a 

recall basis, but by recording daily intake in diaries. The latter approach may result in 

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Chapter 3 - Drinking Water Intake 

more accurate responses being generated. Also, the use of total liquid and total tapwater 

was well defined in this study. However, the relatively short-term nature of the survey 

make extrapolation to long-term consumption patterns difficult. Also, these data were 

based on the population of Great Britain and not the United States. Drinking patterns may 

differ among these populations as a result of varying weather conditions and socioeconomic factors. For these reasons this study is not considered a key study in this 

document. 

International Commission on Radiological Protection (ICRP) (1981) - Report to the 

Task Group on Reference Man - Data on fluid intake levels have also been summarized 

by the International Commission on Radiological Protection (ICRP) in the Report of the 

Task Group on Reference Man (ICRP, 1981). These intake levels for adults and children 

are summarized in Table 3-16. The amount of drinking water (tapwater and water-based 

drinks) consumed by adults ranged from about 0.37 L/day to about 2.18 L/day under 

"normal" conditions. The levels for children ranged from 0.54 to 0.79 L/day. Because the 

populations, survey design, and intake categories are not clearly defined, this study has 

limited usefulness in developing recommended intake rates for use in exposure 

assessment. It is reported here as a relevant study because the findings, although poorly 

defined, are consistent with the results of other studies. 

Gillies and Paulin (1983) - Variability of Mineral Intakes from Drinking Water - Gillies 

and Paulin (1983) conducted a study to evaluate variability of mineral intake from drinking 

water. A study population of 109 adults (75 females; 34 males) ranging in age from 16 to 

80 years (mean age = 44 years) in New Zealand was asked to collect duplicate samples 

of water consumed directly from the tap or used in beverage preparation during a 24-hour 

period. Participants were asked to collect the samples on a day when all of the water 

consumed would be from their own home. Individuals were selected based on their 

willingness to participate and their ability to comprehend the collection procedures. The 

mean total tapwater intake rate for this population was 1.25 (±0.39) L/day, and the 90th 

percentile rate was 1.90 L/day. The median total tapwater intake rate (1.26 L/day) was 

very similar to the mean intake rate (Gillies and Paulin, 1983). The reported range was 

0.26 to 2.80 L/day.

The advantage of these data are that they were generated using duplicate sampling 

techniques. Because this approach is more objective than recall methods, it may result 

in more accurate response. However, these data are based on a short-term survey that 

may not be representative of long-term behavior, the population surveyed is small and the 

procedures for selecting the survey population were not designed to be representative of 

the New Zealand population, and the results may not be applicable to the United States. 

For these reasons the study is not regarded as a key study in this document. 

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Pennington (1983) - Revision of the Total Diet Study Food List and Diets - Based on 

data from the U.S. Food and Drug Administration's (FDA's) Total Diet Study, Pennington 

(1983) reported average intake rates for various foods and beverages for five age groups 

of the population. The Total Diet Study is conducted annually to monitor the nutrient and 

contaminant content of the U.S. food supply and to evaluate trends in consumption. 

Representative diets were developed based on 24-hour recall and 2-day diary data from 

the 1977-1978 U.S. Department of Agriculture (USDA) Nationwide Food Consumption 

Survey (NFCS) and 24-hour recall data from the Second National Health and Nutrition 

Examination Survey (NHANES II). The number of participants in NFCS and NHANES II 

was approximately 30,000 and 20,000, respectively. The diets were developed to 

"approximate 90 percent or more of the weight of the foods usually consumed" 

(Pennington, 1983). The source of water (bottled water as distinguished from tapwater) 

was not stated in the Pennington study. For the purposes of this report, the consumption 

rates for the food categories defined by Pennington (1983) were used to calculate total 

fluid and total water intake rates for five age groups. Total water includes water, tea, 

coffee, soft drinks, and soups and frozen juices that are reconstituted with water. 

Reconstituted soups were assumed to be composed of 50 percent water, and juices were 

assumed to contain 75 percent water. Total fluids include total water in addition to milk, 

ready-to-use infant formula, milk-based soups, carbonated soft drinks, alcoholic 

beverages, and canned fruit juices. These intake rates are presented in Table 3-17. 

Based on the average intake rates for total water for the two adult age groups, 1.04 and 

1.26 L/day, the average adult intake rate is about 1.15 L/day. These rates should be more 

representative of the amount of source-specific water consumed than are total fluid intake 

rates. Because this study was designed to measure food intake, and it used both USDA 

1978 data and NHANES II data, there was not necessarily a systematic attempt to define 

tapwater intake per se, as distinguished from bottled water. For this reason, it is not 

considered a key tapwater study in this document. 

U.S. EPA (1984) - An Estimation of the Daily Average Food Intake by Age and Sex 

for Use in Assessing the Radionuclide Intake of the General Population - Using data 

collected by USDA in the 1977-78 NFCS, U.S. EPA (1984) determined daily food and 

beverage intake levels by age to be used in assessing radionuclide intake through food 

consumption. Tapwater, water-based drinks, and soups were identified subcategories of 

the total beverage category. Daily intake rates for tapwater, water-based drinks, soup, and 

total beverage are presented in Table 3-18. As seen in Table 3-18, mean tapwater intake

for different adult age groups (age 20 years and older) ranged from 0.62 to 0.76 L/day, 

water-based drinks intake ranged from 0.34 to 0.69 L/day, soup intake ranged from 0.03 

to 0.06 L/day, and mean total beverage intake levels ranged from 1.48 to 1.73 L/day. Total 

tapwater intake rates were estimated by combining the average daily intakes of tapwater, 

water-based drinks, and soups for each age group. For adults (ages 20 years and older), 

mean total tapwater intake rates range from 1.04 to 1.47 L/day, and for children (ages <1 

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Chapter 3 - Drinking Water Intake 

to 19 years), mean intake rates range from 0.19 to 0.90 L/day. These intake rates do not 

include reconstituted infant formula. The total tapwater intake rates, derived by combining 

data on tapwater, water-based drinks, and soup should be more representative of sourcespecific drinking water intake than the total beverage intake rates reported in this study. 

These intake rates are based on the same USDA NFCS data used in Ershow and Cantor 

(1989). Therefore, the data limitations discussed previously also apply to this study. 

Cantor et al. (1987) - Bladder Cancer, Drinknig Water Source, and Tapwater 

Consumption - The National Cancer Institute (NCI), in a population-based, case control 

study investigating the possible relationship between bladder cancer and drinking water, 

interviewed approximately 8,000 adult white individuals, 21 to 84 years of age (2,805 

cases and 5,258 controls) in their homes, using a standardized questionnaire (Cantor et 

al., 1987). The cases and controls resided in one of five metropolitan areas (Atlanta, 

Detroit, New Orleans, San Francisco, and Seattle) and five States (Connecticut, Iowa, New 

Jersey, New Mexico, and Utah). The individuals interviewed were asked to recall the level 

of intake of tapwater and other beverages in a typical week during the winter prior to the 

interview. Total beverage intake was divided into the following two components: 

1) beverages derived from tapwater; and 2) beverages from other sources. Tapwater used 

in cooking foods and in ice cubes was apparently not considered. Participants also 

supplied information on the primary source of the water consumed (i.e., private well, 

community supply, bottled water, etc.). The control population was randomly selected from 

the general population and frequency matched to the bladder cancer case population in 

terms of age, sex, and geographic location of residence. The case population consisted 

of Whites only, had no people under the age of 21 years and 57 percent were over the age 

of 65 years. The fluid intake rates for the bladder cancer cases were not used because 

their participation in the study was based on selection factors that could bias the intake 

estimates for the general population. Based on responses from 5,258 White controls 

(3,892 males; 1,366 females), average tapwater intake rates for a "typical" week were 

compiled by sex, age group, and geographic region. These rates are listed in Table 3-19. 

The average total fluid intake rate was 2.01 L/day for men of which 70 percent (1.4 L/day) 

was derived from tapwater, and 1.72 L/day for women of which 79 percent (1.35 L/day) 

was derived from tapwater. Frequency distribution data for the 5,081 controls, for which 

the authors had information on both tapwater consumption and cigarette smoking habits, 

are presented in Table 3-20. These data follow a lognormal distribution having an average 

value of 1.30 L/day and an upper 90th percentile value of approximately 2.40 L/day. 

These values were determined by graphically interpolating the data of Table 3-20 after 

plotting it on log probability graph paper. These values represent the usual level of intake 

for this population of adults in the winter. 

A limitation associated with this data set is that the population surveyed was older 

than the general population and consisted exclusively of Whites. Also, the intake data are 

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Chapter 3 - Drinking Water Intake 

based on recall of behavior from the winter previous to the interview. Extrapolation to 

other seasons and intake durations is difficult. 

The authors presented data on person-years of residence with various types of water 

supply sources (municipal versus private, chlorinated versus nonchlorinated, and surface 

versus well water). Unfortunately, these data can not be used to draw conclusions about 

the National average apportionment of surface versus groundwater since a large fraction 

(24 percent) of municipal water intake in this survey could not be specifically attributed to 

either ground or surface water. 

AIHC (1994) - Exposure Factors Handbook - The Exposure Factors Sourcebook 

(AIHC, 1994) presented drinking water intake rate recommendations for adults. Although 

AIHC (1994) provided little information on the studies used to derive mean and upper 

percentile recom-mendations, the references indicate that several of the studies used were 

the same as ones categorized as relevant studies in this handbook. The mean adult 

drinking water recommendations in AIHC (1994) and this handbook are in agreement. 

However, the upper percentile value recommended by AIHC (1994) (2.0 L/day) is slightly 

lower than that recommended by this handbook (2.4 L/day). Based on data provided by 

Ershow and Cantor (1989), 2.0 L/day corresponds to only approximately the 84th 

percentile of the drinking water intake rate distribution. Thus, a slightly higher value is 

appropriate for representing the upper percentile (i.e., 90 to 95th percentile) of the 

distribution. AIHC (1994) also presents simulated distributions of drinking water intake 

based on Roseberry and Burmaster (1992). These distributions are also described in 

detail in Section 3.2 of this handbook. AIHC (1994) has been classified as a relevant 

rather than a key study because it is not the primary source for the data used to make 

recommendations for this document. 

USDA (1995) - Food and Nutrient Intakes by Individuals in the United States, 1 Day, 

1989-91. - USDA (1995) collected data on the quantity of "plain drinking water" and 

various other beverages consumed by individuals in 1 day during 1989 through 1991. The 

data were collected as part of USDA's Continuing Survey of Food Intakes by Individuals 

(CSFII). The data used to estimate mean per capita intake rates combined one-day 

dietary recall data from 3 survey years: 1989, 1990, and 1991 during which 15,128 

individuals supplied one-day intake data. Individuals from all income levels in the 48 

conterminous states and Washington D.C. were included in the sample. A complex threestage sampling design was employed and the overall response rate for the study was 58 

percent. To minimize the biasing effects of the low response rate and adjust for the 

seasonality, a series of weighting factors was incorporated into the data analysis. The 

intake rates based on this study are presented in Table 3-21. Table 3-21 includes data 

for: a) "plain drinking water", which might be assumed to mean tapwater directly 

consumed rather than bottled water; b) coffee and tea, which might be assumed to be 

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Chapter 3 - Drinking Water Intake 

constituted from tapwater; and 3) fruit drinks and ades, which might be assumed to be 

reconstituted from tapwater rather than canned products; and 4) the total of the three 

sources. With these assumptions, the mean per capita total intake of water is estimated 

to be 1,416 mL/day for adult males (i.e., 20 years of age and older), 1,288 mL/day for adult 

females (i.e., 20 years of age and older) and 1,150 mL/day for all ages and both sexes 

combined. Although these assumptions appear reasonable, a close reading of the 

definitions used by USDA (1995) reveals that the word “tapwater” does not occur, and this 

uncertainty prevents the use of this study as a key study of tapwater intake. 

The advantages of using these data are that; 1) the survey had a large sample size; 

2) the authors attempted to represent the general United States population by 

oversampling low-income groups and by weighting the data to compensate for low 

response rates; and 3) it reflects more recent intake data than the key studies. The 

disadvantages are that: 1) the response rate was low; 2) the word “tapwater” was not 

defined and the assumptions that must be used in order to compare the data with the 

other tapwater studies might not be valid; 3) the data collection period reflects only a oneday intake period, and may not reflect long-term drinking water intake patterns; and 4) data 

on the percentiles of the distribution of intakes were not given. 

Tsang and Klepeis (1996) - National Human Activity Pattern Survey (NHAPS) - The 

U.S. EPA collected information on the number of glasses of drinking water and juice 

reconstituted with tapwater consumed by the general population as part of the National 

Human Activity Pattern Survey (Tsang and Klepeis, 1996). NHAPS was conducted 

between October 1992 and September 1994. Over 9,000 individuals in the 48 contiguous 

United States provided data on the duration and frequency of selected activities and the 

time spent in selected microenvironments via 24-hour diaries. Over 4,000 NHAPS 

respondents also provided information of the number of 8-ounce glasses of water and the 

number of 8-ounce glasses of juice reconstituted with water than they drank during the 24­

hour survey period (Tables 3-22 and 3-23). The median number of glasses of tapwater 

consumed was 1-2 and the median number of glasses of juice with tapwater consumed 

was 1-2. 

For both individuals who drank tapwater and individuals who drank juices reconstituted 

with tapwater, the number of glasses ranged from 1 to 20. The highest percentage of the 

population (37.1 percent) who drank tapwater consumed 3-5 glasses and the highest 

percentage of the population (51.5 percent) who consumed juice reconstituted with 

tapwater drank 1-2 glasses. Based on the assumption that each glass contained 8 ounces 

of water (226.4 mL), the total volume of tapwater and juice with tapwater consumed would 

range from 0.23 L/day (1 glass) to 4.5 L/day (20 glasses) for respondents who drank 

tapwater. Using the same assumption, the volume of tapwater consumed for the 

population who consumed 3-5 glasses would be 0.68 L/day to 1.13 L/day and the volume 

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Chapter 3 - Drinking Water Intake 

of juice with tapwater consumed for the population who consumed 1-2 glasses would be 

0.23 L/day to 0.46 L/day. Assuming that the average individual consumes 3-5 glasses of 

tapwater plus 1-2 glasses of juice with tapwater, the range of total tapwater intake for this 

individual would range from 0.9 L/day to 1.64 L/day. These values are consistent with the 

average intake rates observed in other studies. 

The advantages of NHAPS is that the data were collected for a large number of 

individuals and that the data are representative of the U.S. population. However, 

evaluation of drinking water intake rates was not the primary purpose of the study and the 

data do not reflect the total volume of tapwater consumed. However, using the 

assumptions described above, the estimated drinking water intake rates from this study 

are within the same ranges observed for other drinking water studies. 

3.4. PREGNANT AND LACTATING WOMEN 

Ershow et al. (1991) - Intake of Tapwater and Total Water by Pregnant and Lactating 

Women - Ershow et al. (1991) used data from the 1977-78 USDA NFCS to estimate total 

fluid and total tapwater intake among pregnant and lactating women (ages 15-49 years). 

Data for 188 pregnant women, 77 lactating women, and 6,201 non-pregnant, non-lactating 

control women were evaluated. The participants were interviewed based on 24 hour 

recall, and then asked to record a food diary for the next 2 days. "Tapwater" included 

tapwater consumed directly as a beverage and tapwater used to prepare food and 

tapwater-based beverages. "Total water" was defined as all water from tapwater and nontapwater sources, including water contained in food. Estimated total fluid and total 

tapwater intake rates for the three groups are presented in Tables 3-24 and 3-25, 

respectively. Lactating women had the highest mean total fluid intake rate (2.24 L/day) 

compared with both pregnant women (2.08 L/day) and control women (1.94 L/day). 

Lactating women also had a higher mean total tapwater intake rate (1.31 L/day) than 

pregnant women (1.19 L/day) and control women (1.16 L/day). The tapwater distributions 

are neither normal nor lognormal, but lactating women had a higher mean tapwater intake 

than controls and pregnant women. Ershow et al. (1991) also reported that rural women 

(n=1,885) consumed more total water (1.99 L/day) and tapwater (1.24 L/day) than 

urban/suburban women (n=4,581, 1.93 and 1.13 L/day, respectively). Total water and 

tapwater intake rates were lowest in the northeastern region of the United States (1.82 and 

1.03 L/day) and highest in the western region of the United States (2.06 L/day and 1.21 

L/day). Mean intake per unit body weight was highest among lactating women for both 

total fluid and total tapwater intake. Total tapwater intake accounted for over 50 percent 

of mean total fluid in all three groups of women (Table 3-25). Drinking water accounted 

for the largest single proportion of the total fluid intake for control (30 percent), pregnant 

(34 percent), and lactating women (30 percent) (Table 3-26). All other beverages 

combined accounted for approximately 46 percent, 43 percent, and 45 percent of the total 

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Chapter 3 - Drinking Water Intake 

water intake for control, pregnant, and lactating women, respectively. Food accounted for 

the remaining portion of total water intake. 

The same advantages and limitations associated with the Ershow and Cantor (1989) 

data also apply to these data sets (Section 3.2). A further advantage of this study is that 

it provides information on estimates of total waterand tapwater intake rates for pregnant 

and lactating women. This topic has rarely been addressed in the literature. 

3.5. HIGH ACTIVITY LEVELS/HOT CLIMATES 

McNall and Schlegel (1968) - Practical Thermal Environmental Limits for Young 

Adult Males Working in Hot, Humid Environments - McNall and Schlegel (1968) conducted 

a study that evaluated the physiological tolerance of adult males working under varying 

degrees of physical activity. Subjects were required to pedal pedal-driven propeller fans 

for 8-hour work cycles under varying environmental conditions. The activity pattern for 

each individual was: cycled at 15 minute pedalling and 15 miute rest for each 8-hour 

period. Two groups of eight subjects each were used. Work rates were divided into three 

categories as follows: high activity level [0.15 horsepower (hp) per person], medium 

activity level (0.1 hp per person), and low activity level (0.05 hp per person). Evidence of 

physical stress (i.e., increased body temperature, blood pressure, etc.) was recorded, and 

individuals were eliminated from further testing if certain stress criteria were met. The 

amount of water consumed by the test subjects during the work cycles was also recorded. 

Water was provided to the individuals on request. The water intake rates obtained at the 

three different activity levels and the various environmental temperatures are presented 

in Table 3-27. The data presented are for test subjects with continuous data only (i.e., 

those test subjects who were not eliminated at any stage of the study as a result of stress 

conditions). Water intake was the highest at all activity levels when environmental 

temperatures were increased. The highest intake rate was observed at the low activity 

level at 100EF (0.65 L/hour) however, there were no data for higher activity levels at 

100EF. It should be noted that this study estimated intake on an hourly basis during 

various levels of physical activity. These hourly intake rates cannot be converted to daily 

intake rates by multiplying by 24 hours/day because they are only representative of intake 

during the specified activity levels and the intake rates for the rest of the day are not 

known. Therefore, comparison of intake rate values from this study cannot be made with 

values from the previously described studies on drinking water intake. 

United States Army (1983) - Water Consumption Planning Factors Study - The U.S. 

Army has developed water consumption planning factors to enable them to transport an 

adequate amount of water to soldiers in the field under various conditions (U.S. Army, 

1983). Both climate and activity levels were used to determine the appropriate water 

consumption needs. Consumption factors have been established for the following uses: 

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Chapter 3 - Drinking Water Intake 

1) drinking, 2) heat treatment, 3) personal hygiene, 4) centralized hygiene, 5) food 

preparation, 6) laundry, 7) medical treatment, 8) vehicle and aircraft maintenance, 

9) graves registration, and 10) construction. Only personal drinking water consumption 

factors are described here. 

Drinking water consumption planning factors are based on the estimated amount of 

water needed to replace fluids lost by urination, perspiration, and respiration. It assumes 

that water lost to urinary output averages one quart/day (0.9 L/day) and perspiration losses 

range from almost nothing in a controlled environment to 1.5 quarts/day (1.4 L/day) in a 

very hot climate where individuals are performing strenuous work. Water losses to 

respiration are typically very low except in extreme cold where water losses can range from 

1 to 3 quarts/day (0.9 to 2.8 L/day). This occurs when the humidity of inhaled air is near 

zero, but expired air is 98 percent saturated at body temperature (U.S. Army, 1983). 

Drinking water is defined by the U.S. Army (1983) as "all fluids consumed by individuals 

to satisfy body needs for internal water." This includes soups, hot and cold drinks, and 

tapwater. Planning factors have been established for hot, temperate, and cold climates 

based on the following mixture of activities among the work force: 15 percent of the force 

performing light work, 65 percent of the force performing medium work, and 20 percent of 

the force performing heavy work. Hot climates are defined as tropical and arid areas 

where the temperature is greater than 80EF. Temperate climates are defined as areas 

where the mean daily temperature ranges from 32EF to 80EF. Cold regions are areas 

where the mean daily temperature is less than 32EF. Drinking water consumption factors 

for these three climates are presented in Table 3-28. These factors are based on research 

on individuals and small unit training exercises. The estimates are assumed to be 

conservative because they are rounded up to account for the subjective nature of the 

activity mix and minor water losses that are not considered (U.S. Army, 1983). The 

advantage of using these data is that they provide a conservative estimate of drinking 

water intake among individuals performing at various levels of physical activity in hot, 

temperate, and cold climates. However, the planning factors described here are based on 

assumptions about water loss from urination, perspiration, and respiration, and are not 

based on survey data or actual measurements. 

3.6. RECOMMENDATIONS 

The key studies described in this section were used in selecting recommended 

drinking water (tapwater) consumption rates for adults and children. The studies on other 

subpopulations were not classified as key versus relevant. Although different survey 

designs and populations were utilized by key and relevant studies described in this report, 

the mean and upper-percentile estimates reported in these studies are reasonably similar. 

The general design of both key and relevant studies and their limitations are summarized 

in Table 3-29. It should be noted that studies that surveyed large representative samples 

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Chapter 3 - Drinking Water Intake 

of the population provide more reliable estimates of intake rates for the general population. 

Most of the surveys described here are based on short-term recall which may be biased 

toward excess intake rates. However, Cantor et al. (1987) noted that retrospective dietary 

assessments generally produce moderate correlations with "reference data from the past." 

A summary of the recommended values for drinking water intake rates is presented in 

Table 3-30. 

Adults - The total tapwater consumption rates for adults (older than 18 or 20 years) 

that have been reported in the key surveys can be summarized in Table 3-31. For 

comparison, values for daily tapwater intake for the relevant studies are shown in Table 

3-32. 

Note that both Ershow and Cantor (1989) and Pennington (1983) found that adults 

above 60 years of age had larger intakes than younger adults. This is difficult to reconcile 

with the Cantor et al. (1987) study because the latter, older population had a smaller 

average intake. Because of these results, combined with the fact that the Cantor et al. 

(1987) study was not intended to be representative of the U. S. population, it is not 

included here in the determination of the recommended value. The USDA (1995) data are 

not included because tapwater was not defined in the survey and because the response 

rate was low, although the results (showing lower intakes than the studies based on older 

data) may be accurately reflecting an expected lower use of tapwater (compared to 1978) 

because of increasing use of bottled water and soft drinks in recent years. 

A value of 1.41 L/day, which is the population-weighted mean of the two national 

studies (Ershow and Cantor, 1989 and Canadian Ministry of Health and Welfare, 1981) 

is the recommended average tapwater intake rate. 

The average of the 90th percentile values from the same two studies (2.35 L/day) is 

recommended as the appropriate upper limit. (The commonly-used 2.0 L/day intake rate 

corresponds to the 84th percentile of the intake rate distribution among the adults in the 

Ershow and Cantor (1989) study). In keeping with the desire to incorporate body weight 

into exposure assessments without introducing extraneous errors, the values from the 

Ershow and Cantor (1989) study (Tables 3-7 and 3-8) expressed as mL/kg-day are 

recommended in preference to the liters/day units. For adults, the mean and 90th 

percentile values are 21 mL/kg-day and 34.2 mL/kg/day, respectively. 

In the absence of actual data on chronic intake, the values in the previous paragraph 

are recommended as chronic values, although the chronic 90th upper percentile may very 

well be larger than 2.35 L/day. If a mathematical description of the intake distribution is 

needed, the parameters of lognormal fit to the Ershow and Cantor (1989) data (Tables 

3-11 and 3-12) generated by Roseberry and Burmaster (1992) may be used. The 

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Chapter 3 - Drinking Water Intake 

simulated balanced population distribution of intakes generated by Roseberry and 

Burmaster is not recommended for use in the post-1997 time frame, since it corrects the 

1978 data only for the differences in the age structure of the U. S. population between 

1978 and 1988. These recommended values are different than the 2 liters/day 

commonly assumed in EPA risk assessments. Assessors are encouraged to use values 

which most accurately reflect the exposed population. When using values other than 2 

liters/day, however, the assessors should consider if the dose estimate will be used to 

estimate risk by combining with a dose-response relationship which was derived assuming 

a tap water intake of 2 liters/day. If such an inconsistency exists, the assessor should 

adjust the dose-response relationship as described in Appendix 1 of Chapter 1. IRIS does 

not use a tap water intake assumption in the derivation of RfCs and RfDs, but does make 

the 2 liter/day assumption in the derivation of cancer slope factors and unit risks. 

Children - The tapwater intake rates for children reported in the key studies are 

summarized in Table 3-33. The intake rates, as expressed as liters per day, generally 

increase with age, and the data are consistent across ages for the two key studies except 

for the Canadian Ministry of Health and Welfare (1981) data for ages 6 to 17 years; it is 

recommended that any of the liters/day values that match the age range of interest except 

the Canada data for ages 6 to 17 years be used. The mL/kg-day intake values show a 

consistent downward trend with increasing ages; using the Ershow and Cantor (1989) data 

in preference to the Canadian Ministry of National Health and Welfare (1981) data is 

recommended where the age ranges overlap. 

The intakes for children as reported in the relevant studies are shown in Table 3-34. 

Disregarding the Roseberry and Burmaster study, which is a recalculation of the 

Ershow and Cantor (1989) study, the non-key studies generally have lower mean intake 

values than the Ershow and Cantor (1899) study. The reason is not known, but the results 

are not persuasive enough to discount the recommendations based on the latter study. 

Intake rates for specific percentiles of the distribution may be selected using the lognormal 

distribution data generated by Roseberry and Burmaster (1992) (Tables 3-11 and 3-12). 

Pregnant and Lactating Women -The data on tapwater intakes for control, pregnant, 

and lactating women are presented in Table 3-25. The recommended intake values are 

presented in Table 3-30. 

High Activity/Hot Climates - Data on intake rates for individuals performing strenuous 

activities under various environmental conditions are limited. None of these is classed as 

a key study because the populations in these studies are not representative of the general 

U.S. population. However, the data presented by McNall and Schlegel (1968) and U.S. 

Army (1983) provide bounding intake values for these individuals. According to McNall 

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Chapter 3 - Drinking Water Intake 

and Schlegel (1968), hourly intake can range from 0.21 to 0.65 L/hour depending on the 

temperature and activity level. Intake among physically active individuals can range from 

6 L/day in temperate climates to 11 L/day in hot climates (U.S. Army, 1983). 

A characterization of the overall confidence in the accuracy and appropriateness of 

the recommendations for drinking water is presented in Table 3-35. Although the study 

of Ershow and Cantor (1989) is of high quality and consistent with the other surveys, the 

low currency of the information (1978 data collection), in the presence of anecdotal 

information (not presented here) that the consumption of bottled water and beverages has 

increased since 1980 was the main reason for lowering the confidence score of the overall 

recommendations from high to medium. 

Exposure Factors Handbook August 1997 
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Chapter 4 - Soil Ingestion and Pica 

4. SOIL INGESTION AND PICA 

4.1. BACKGROUND 

The ingestion of soil is a potential source of human exposure to toxicants. The 

potential for exposure to contaminants via this source is greater for children because they 

are more likely to ingest more soil than adults as a result of behavioral patterns present 

during childhood. Inadvertent soil ingestion among children may occur through the 

mouthing of objects or hands. Mouthing behavior is considered to be a normal phase of 

childhood development. Adults may also ingest soil or dust particles that adhere to food, 

cigarettes, or their hands. Deliberate soil ingestion is defined as pica and is considered 

to be relatively uncommon. Because normal, inadvertent soil ingestion is more prevalent 

and data for individuals with pica behavior are limited, this section focuses primarily on 

normal soil ingestion that occurs as a result of mouthing or unintentional hand-to-mouth 

activity. 

Several studies have been conducted to estimate the amount of soil ingested by 

children. Most of the early studies attempted to estimate the amount of soil ingested by 

measuring the amount of dirt present on children's hands and making generalizations 

based on behavior. More recently, soil intake studies have been conducted using a 

methodology that measures trace elements in feces and soil that are believed to be poorly 

absorbed in the gut. These measurements are used to estimate the amount of soil 

ingested over a specified time period. The available studies on soil intake are summarized 

in the following sections. Studies on soil intake among children have been classified as 

either key studies or relevant studies based on their applicability to exposure assessment 

needs. Recommended intake rates are based on the results of key studies, but relevant 

studies are also presented to provide the reader with added perspective on the current 

state-of-knowledge pertaining to soil intake. Information on soil ingestion among adults 

is presented based on available data from a limited number of studies. This is an area 

where more data and more research are needed. Relevant information on the prevalence 

of pica and intake among individuals exhibiting pica behavior is also presented. 

4.2. KEY STUDIES ON SOIL INTAKE AMONG CHILDREN 

Binder et al. (1986) - Estimating Soil Ingestion: Use of Tracer Elements in Estimating 

the Amount of Soil Ingested by Young Children - Binder et al. (1986) studied the ingestion 

of soil among children 1 to 3 years of age who wore diapers using a tracer technique 

modified from a method previously used to measure soil ingestion among grazing animals. 

The children were studied during the summer of 1984 as part of a larger study of residents 

living near a lead smelter in East Helena, Montana. Soiled diapers were collected over 

a 3-day period from 65 children (42 males and 23 females), and composited samples of 

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Chapter 4 - Soil Ingestion and Pica 

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. This made them useful tracers for estimating soil intake. Excreta 

measurements were obtained for 59 of the children. Soil ingestion by each child was 

estimated based on each of the three tracer elements using a standard assumed fecal dry 

weight of 15 g/day, and the following equation: 

x Fi f

i,e Ti,e ' (Eqn. 4-1) Si,e 

where: 

Ti,e = estimated soil ingestion for child i based on element e (g/day); 

fi,e = concentration of element e in fecal sample of child i (mg/g); 

Fi = fecal dry weight (g/day); and 

Si,e = concentration of element e in child i's yard soil (mg/g). 

The analysis conducted by Binder et al. (1986) 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 housedust 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 4-1). 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 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 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., 

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>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. 

The advantages of this study are that a relatively large number of children were 

studied and tracer elements were used to estimate soil ingestion. However, the children 

studied may not be representative of the U.S. population and the study did not account for 

tracers ingested via foods or medicines. Also, the use of an assumed fecal weight instead 

of actual fecal weights may have biased the results of this study. Finally, because of the 

short-term nature of the survey, soil intake estimates may not be entirely representative 

of long-term behavior, especially at the upper-end of the distribution of intake. 

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 similar to that of Binder et al. (1986). Aluminum, titanium, and acid-insoluble 

residue (AIR) contents were determined for fecal samples from children, aged 2 to 4 years, 

attending a nursery school, and for samples of playground dirt at that school. Twentyseven daily fecal samples were obtained over a 5-day period for the 18 children examined. 

Using the average soil concentrations present at the school, and assuming a standard 

fecal dry weight of 10 g/day, Clausing et al. (1987) estimated soil ingestion for each tracer. 

Clausing et al. (1987) also collected eight daily fecal samples from six hospitalized, 

bedridden children. These children served as a control group, representing children who 

had very limited access to soil. 

The average quantity of soil ingested by the school children in this study was as 

follows: 230 mg/day (range 23 to 979 mg/day) for aluminum; 129 mg/day (range 48 to 362 

mg/day) for AIR; and 1,430 mg/day (range 64 to 11,620 mg/day) for titanium (Table 4-2).

As in the Binder et al. (1986) study, a fraction of the children (6/19) showed titanium values 

well above 1,000 mg/day, with most of the remaining children showing substantially lower 

values. Based on the Limiting Tracer Method (LTM), mean soil intake was estimated to 

be 105 mg/day with a population standard deviation of 67 mg/day (range 23 to 362 

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). 

Geometric mean soil intake was estimated to be 90 mg/day. This assumes that the 

maximum amount of soil ingested cannot be higher than the lowest estimate for the 

individual tracers. 

Mean soil intake for the hospitalized children was estimated to be 56 mg/day based 

on aluminum (Table 4-3). For titanium, three of the children had estimates well in excess 

of 1,000 mg/day, with the remaining three children in the range of 28 to 58 mg/day. 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 

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soil intake rate was 45 mg/day. The data on hospitalized children suggest a major nonsoil 

source of titanium for some children, and may suggest a background nonsoil source of 

aluminum. However, conditions specific to hospitalization (e.g., medications) were not 

considered. AIR measurements were not reported for the hospitalized children. Assuming 

that the tracer-based soil ingestion rates observed in hospitalized children actually 

represent background tracer intake from dietary and other nonsoil sources, mean soil 

ingestion by nursery school children was estimated to be 56 mg/day, based on the LTM 

(i.e., 105 mg/day for nursery school children minus 49 mg/day for hospitalized children) 

(Clausing et al. 1987). 

The advantages of this study are that Clausing et al. (1987) evaluated soil ingestion 

among two populations of children that had differences in access to soil, and corrected soil 

intake rates based on background estimates derived from the hospitalized group. 

However, a smaller number of children were used in this study than in the Binder et al. 

(1986) study and these children may not be representative of the U.S. population. Tracer 

elements in foods or medicines were not evaluated. Also, intake rates derived from this 

study may not be representative of soil intake over the long-term because of the short-term 

nature of the study. In addition, one of the factors that could affect soil intake rates is 

hygiene (e.g., hand washing frequency). Hygienic practices can vary across countries and 

cultures and may be more stringently emphasized in a more structured environment such 

as child care centers in The Netherlands and other European countries than in child care 

centers in the United States. 

Calabrese et al. (1989) - How Much Soil do Young Children Ingest: An Epidemiologic 

Study - Calabrese et al. (1989) studied soil ingestion among children using the basic tracer 

design developed by Binder et al. (1986). However, in contrast to the Binder et al. (1986) 

study, eight tracer elements (i.e., aluminum, barium, manganese, silicon, titanium, 

vanadium, yttrium, and zirconium) were analyzed instead of only three (i.e., aluminum, 

silicon, and titanium). A total of 64 children between the ages of 1 and 4 years old were 

included in the study. These children were all selected from the greater Amherst, 

Massachusetts area and were predominantly from two-parent households where the 

parents were highly educated. The Calabrese et al. (1989) study was conducted over 

eight days during a two week period and included the use of a mass-balance methodology 

in which duplicate samples of food, medicines, vitamins, and others were collected and 

analyzed on a daily basis, in addition to soil and dust samples collected from the child’s 

home and play area. Fecal and urine samples were also collected and analyzed for tracer 

elements. Toothpaste, low in tracer content, was provided to all participants. 

In order to validate the mass-balance methodology used to estimate soil ingestion 

rates among children and to determine which tracer elements provided the most reliable 

data on soil ingestion, known amounts of soil (i.e., 300 mg over three days and 1,500 mg 

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over three days) containing eight tracers were administered to six adult volunteers (i.e., 

three males and three females). Soil samples and feces samples from these adults and 

duplicate food samples were analyzed for tracer elements to calculate recovery rates of 

tracer elements in soil. Based on the adult validation study, Calabrese et al. (1989) 

confirmed that the tracer methodology could adequately detect tracer elements in feces 

at levels expected to correspond with soil intake rates in children. Calabrese et al. (1989) 

also found that aluminum, silicon, and yttrium were the most reliable of the eight tracer 

elements analyzed. The standard deviation of recovery of these three tracers was the 

lowest and the percentage of recovery was closest to 100 percent (Calabrese, et al., 

1989). The recovery of these three tracers ranged from 120 to 153 percent when 300 mg 

of soil had been ingested over a three-day period and from 88 to 94 percent when 1,500 

mg soil had been ingested over a three-day period (Table 4-4).

Using the three most reliable tracer elements, the mean soil intake rate for children, 

adjusted to account for the amount of tracer found in food and medicines, was estimated 

to be 153 mg/day based on aluminum, 154 mg/day based on silicon, and 85 mg/day based 

on yttrium (Table 4-5). Median intake rates were somewhat lower (29 mg/day for 

aluminum, 40 mg/day for silicon, and 9 mg/day for yttrium). Upper-percentile (i.e., 95th) 

values were 223 mg/day for aluminum, 276 mg/day for silicon, and 106 mg/day for yttrium. 

Similar results were observed when soil and dust ingestion was combined (Table 4-5). 

Intake of soil and dust was estimated using a weighted average of tracer concentration in 

dust composite samples and in soil composite samples based on the timechildren spent 

at home and away from home, and indoors and outdoors. Calabrese et al. (1989) 

suggested that the use of titanium as a tracer in earlier studies that lacked food ingestion 

data may have significantly overestimated soil intake because of the high levels of titanium 

in food. Using the median values of aluminum and silicon, Calabrese et al. (1989) 

estimated the quantity of soil ingested daily to be 29 mg/day and 40 mg/day, respectively. 

It should be noted that soil ingestion for one child in the study ranged from approximately 

10 to 14 grams/day during the second week of observation. Average soil ingestion for this 

child was 5 to 7 mg/day, based on the entire study period. 

The advantages of this study are that intake rates were corrected for tracer 

concentrations in foods and medicines and that the methodology was validated using 

adults. Also, intake was observed over a longer time period in this study than in earlier 

studies and the number of tracers used was larger than for other studies. A relatively large 

population was studied, but they may not be entirely representative of the U.S. population 

because they were selected from a single location. 

Davis et al. (1990) - Quantitative Estimates of Soil Ingestion in Normal Children 

Between the ages of 2 and 7 years: Population-Based Estimates Using Aluminum, Silicon, 

and Titanium as Soil Tracer Elements - Davis et al. (1990) also used a massExposure Factors Handbook August 1997 
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balance/tracer technique to estimate soil ingestion among children. In this study, 104 

children between the ages of 2 and 7 years were randomly selected from a three-city area 

in southeastern Washington State. The study was conducted over a seven day period, 

primarily during the summer. Daily soil ingestion was evaluated by collecting and 

analyzing soil and house dust samples, feces, urine, and duplicate food samples for 

aluminum, silicon, and titanium. In addition, information on dietary habits and 

demographics was collected in an attempt to identify behavioral and demographic 

characteristics that influence soil intake rates among children. The amount of soil ingested 

on a daily basis was estimated using the following equation: 

Si,e 

(DWf % DWp ) x (Ef % 2Eu ) & (DWfd x Efd ) ' Esoil

(Eqn. 4-2) 

where: 

Si,e = soil ingested for child i based on tracer e (g); 

DWf = feces dry weight (g); 

DW = feces dry weight on toilet paper (g); p 

Ef = tracer amount in feces (g/g);

E = tracer amount in urine (g/g); u 

DWfd = food dry weight (g);

Efd = tracer amount in food (g/g); and

E = tracer concentration in soil (g/g). soil 

The soil intake rates were corrected by adding the amount of tracer in vitamins and 

medications to the amount of tracer in food, and adjusting the food quantities, feces dry 

weights, and tracer concentrations in urine to account for missing samples. 

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 4-6). Median values were 25 mg/day for aluminum, 59 

mg/day for silicon, and 81 mg/day for titanium. Davis et al. (1990) 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 mass balance 

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. The adjusted mean soil/dust intake 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 intake rates 

were: 51.8 mg/day for aluminum, 112.4 mg/day for silicon, and 116.6 mg/day for titanium. 

Davis et al. (1990) also observed that the following demographic characteristics were 

associated with high soil intake rates: male sex, non-white racial group, low income, 

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operator/laborer as the principal occupation of the parent, and city of residence. However, 

none of these factors were predictive of soil intake rates when tested using multiple linear 

regression. 

The advantages of the Davis et al. (1990) study are that soil intake rates were 

corrected based on the tracer content of foods and medicines and that a relatively large 

number of children were sampled. Also, demographic and behavioral information was 

collected for the survey group. However, although a relatively large sample population 

was surveyed, these children were all from a single area of the U.S. and may not be 

representative of the U.S. population as a whole. The study was conducted over a oneweek period during the summer and may not be representative of long-term (i.e., annual) 

patterns of intake. 

Van Wïjnen et al. (1990) - Estimated Soil Ingestion by Children - In a 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 similar to that used by Clausing et al. 

(1987). Van Wïjnen et al. (1990) measured three tracers (i.e., titanium, aluminum, and 

AIR) in soil and feces and estimated soil ingestion based on the LTM. An average daily 

feces weight of 15 g dry weight was assumed. A total of 292 children attending daycare 

centers were sampled during the first of two sampling periods and 187 children were 

sampled in the second sampling period; 162 of these children were sampled during both 

periods (i.e., at the beginning and near the end of the summer of 1986). A total of 78 

children were sampled at campgrounds, and 15 hospitalized children were sampled. The 

mean values for these groups were: 162 mg/day for children in daycare centers, 213 

mg/day for campers and 93 mg/day for hospitalized children. Van Wïjnen et al. (1990) 

also reported geometric mean LTM values because soil intake 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, 174 

mg/day for children vacationing at campgrounds (Table 4-7) and 74 mg/day for 

hospitalized children (70-120 mg/day based on the 95 percent confidence limits of the 

mean). AIR was the limiting tracer in about 80 percent of the samples. Among children 

attending daycare centers, soil intake 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 4-8). Van Wïjnen et al. (1990) suggest that the mean LTM value for 

hospitalized infants represents background intake of tracers and should be used to correct 

the soil intake rates based on LTM values for other sampling groups. Using mean values, 

corrected soil intake 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 intake was estimated to range from 0 to 90 mg/day with a 90th 

percentile value of 190 mg/day for the various age categories within the daycare group and 

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30 to 200 mg/day with a 90th percentile value of 300 mg/day for the various age categories 

within the camping group. 

The advantage of this study is that soil intake was estimated for three different 

populations of children; one expected to have high intake, one expected to have "typical" 

intake, and one expected to have low or background-level intake. Van Wïjnen et al. (1990) 

used the background tracer measurements to correct soil intake rates for the other two 

populations. Tracer concentrations in food and medicine were not evaluated. Also, the 

population of children studied was relatively large, but may not be representative of the 

U.S. population. This study was conducted over a relatively short time period. Thus, 

estimated intake rates may not reflect long-term patterns, especially at the high-end of the 

distribution. Another limitation of this study is that values were not reported element-byelement which would be the preferred way of reporting. In addition, one of the factors that 

could affect soil intake rates is hygiene (e.g., hand washing frequency). Hygienic practices 

can vary across countries and cultures and may be more stringently emphasized in a more 

structured environment such as child care centers in The Netherlands and other European 

countries than in child care centers in the United States. 

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 

trace-element concentrations. Soil ingestion data for children obtained from the Amherst 

study (Calabrese et al., 1989) were reanalyzed by Stanek and Calabrese (1995a). In the 

Amherst study, soil ingestion measurements were made over a period of 2 weeks for a 

non-random sample of sixty-four children (ages of 1-4 years old) living adjacent to an 

academic area in western Massachusetts. During each week, duplicate food samples 

were collected for 3 consecutive days and fecal samples were collected for 4 consecutive 

days for each subject. The total amount of each of eight trace elements present in the 

food and fecal samples were measured. The eight trace elements are aluminum, barium, 

manganese, silicon, titanium, vanadium, yttrium, and zirconium. The authors expressed 

the amount of trace element in food input or fecal output as a "soil equivalent," which was 

defined as the amount of the element in average daily food intake (or average daily fecal 

output) divided by the concentration of the element in soil. A lag period of 28 hours 

between food intake and fecal output was assumed for all respondents. Day 1 for the 

food sample corresponded to the 24 hour period from midnight on Sunday to midnight on 

Monday of a study week; day 1 of the fecal sample corresponded to the 24 hour period 

from noon on Monday to noon on Tuesday (Stanek and Calabrese, 1995a). 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. 

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Additionally, estimates of the distribution of soil ingestion projected over a period of 365 

days were derived by fitting log-normal distributions to the “overall” daily soil ingestion 

estimates. 

Table 4-9 presents the estimates of mean daily soil ingestion intake per child 

(mg/day) for the 64 study participants. (The authors also presented estimates of the 

median values of daily intake for each child. For most risk assessment purposes the child 

mean values, which are proportional to the cumulative soil intake by the child, are needed 

instead of the median values.) The approach adopted in this paper led to changes in 

ingestion estimates from those presented in Calabrese et al. (1989). Specifically, among 

elements that may be more useful for estimation of ingestion, the mean estimates 

decreased for Al (153 mg/d to 122 mg/d) and Si ( 154 mg/d to 139 mg/d), but increased 

for Ti (218 mg/d to 271 mg/d) and Y (85 mg/d to 165 mg/d). The “overall” mean estimate 

from this reanalysis was 179 mg/d. Table 4-9 presents the empirical distribution of the the 

“overall” mean daily soil ingestion estimates for the 8-day study period (not based on 

lognormal modeling). The estimated intake based on the “overall” estimates is 45 mg/day 

or less for 50 percent of the children and 208 mg/day or less for 95 percent of the children. 

The upper percentile values for most of the individual trace elements are somewhat 

higher. Next, estimates of the respondents soil intake averaged over a period of 365 days 

were presented based upon the lognormal models fit to the daily ingestion estimates 

(Table 4-10). The estimated median value of the 64 respondents' daily soil ingestion 

averaged over a year is 75 mg/day, while the 95th percentile is 1,751 mg/day. 

A strength of this study is that it attempts to make full use of the collected data 

through estimation of daily ingestion rates for children. The data are then screened to 

remove less consistent tracer estimates and the remaining values are aggregated. 

Individual daily estimates of ingestion will be subject to larger errors than are weekly 

average values, particularly since the assumption of a constant lag time between food 

intake and fecal output may be not be correct for many subject days. The aggregation 

approach used to arrive at the “overall” ingestion estimates rests on the assumption that 

the mean ingestion estimates across acceptable tracers provides the most reliable 

ingestion estimates. The validity of this assumption depends on the particular set of 

tracers used in the study, and is not fully assessed. 

In developing the 365 day soil ingestion estimates, data that were obtained over a 

short period of time (as is the case with all available soil ingestion studies) were 

extrapolated over a year. The 2-week study period may not reflect variability in tracer 

element ingestion over a year. While Stanek and Calabrese (1995a) attempt to address 

this through lognormal modeling of the long term intake, new uncertainties are introduced 

through the parametric modeling of the limited subject day data. Also, the sample 

population size of the original study was small and site limited, and, therefore, is not 

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representative of the U.S. population. Study mean estimates of soil ingestion, such as the 

study mean estimates presented in Table 4-9, are substantially more reliable than any 

available distributional estimates. 

Stanek and Calabrese (1995b) - Soil Ingestion Estimates for Use in Site Evaluations 

Based on the Best Tracer Method - Stanek and Calabrese (1995b) recalculated ingestion 

rates that were estimated in three previous mass-balance studies (Calabrese et al., 1989 

and Davis et al., 1990 for children's soil ingestion, and Calabrese et al., 1990 for adult soil 

ingestion) using the Best Tracer Method (BTM). This method allows for the selection of 

the most recoverable tracer for a particular subject or group of subjects. The selection 

process involves ordering trace elements for each subject based on food/soil (F/S) ratios. 

These ratios are estimated by dividing the total amount of the tracer in food by the tracer 

concentration in soil. The F/S ratio is small when the tracer concentration in food is almost 

zero when compared to the tracer concentration in soil. A small F/S ratio is desirable 

because it lessens 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. Because the recoverability of tracers can vary within any group of 

individuals, the BTM uses a ranking scheme of F/S ratios to determine the best tracers for 

use in the ingestion rate calculation. To reduce 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 among individuals. 

For adults, Stanek and Calabrese (1995b) used data for 8 tracers from the Calabrese 

et al. (1990) study to estimate soil ingestion by the BTM. The lowest F/S ratios were Zr 

and Al and the element with the highest F/S ratio was Mn. For soil ingestion estimates 

based on the median of the lowest four F/S ratios, the tracers contributing most often to 

the soil ingestion estimates were Al, Si, Ti, Y, V, and Zr. Using the median of the soil 

ingestion rates based on the best four tracer elements, the average adult soil ingestion 

rate was estimated to be 64 mg/day with a median of 87 mg/day. The 90th percentile soil 

ingestion estimate was 142 mg/day. These estimates are based on 18 subject weeks for 

the six adult volunteers described in Calabrese et al. (1990). 

For children, Stanek and Calabrese (1995b) used data on 8 tracers from Calabrese 

et al., 1989 and data on 3 tracers from Davis et al. (1990) to estimate soil ingestion rates. 

The median of the soil ingestion estimates from the lowest four F/S ratios from the 

Calabrese et al. (1989) study most often included Al, Si, Ti, Y, and Zr. 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. These estimates are based on data for 128 subject weeks for the 64 children in 

the Calabrese et al. (1989) study. 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. 

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The 95th percentile estimate was 246 mg/day. These data are based on the three tracers 

(i.e., Al, Si, and Ti) from the Davis et al. (1990) study. When the Calabrese et al. (1989) 

and Davis et al. (1990) studies were combined, soil ingestion was estimated to be 113 

mg/day (mean); 37 mg/day (median); and 217 mg/day (95th percentile), using the BTM. 

This study provides a reevaluation of previous studies. Its advantages are that it 

combines data from 2 studies for children, one from California and one from 

Massachusetts, which increases the number of observations. It also corrects for biases 

associated with the differences in tracer metabolism. The limitations associated with the 

data used in this study are the same as the limitations described in the summaries of the 

Calabrese et al. (1989), Davis et al. (1990) and Calabrese et al. (1990) studies. 

4.3. RELEVANT STUDIES ON SOIL INTAKE AMONG CHILDREN 

Lepow et al. (1975) - Investigations Into Sources of Lead in the Environment of Urban 

Children - Lepow et al. (1975) used data from a previous study (Lepow et al., 1974) to 

estimate daily soil ingestion rates of children. Lepow et al. (1974) estimated ingestion of 

airborne lead fallout among urban children by: (1) analyzing surface dirt and dust samples 

from locations where children played; (2) measuring hand dirt by applying preweighed 

adhesive labels to the hands and weighing the amount of dirt that was removed; and (3) 

observing "mouthing" behavior over 3 to 6 hours of normal play. Twenty-two children from 

an urban area of Connecticut were included in the study. Lepow et al. (1975) used data 

from the 1974 study and found that the mean weight of soil/dust on the hands was 11 mg. 

Assuming that a child would put fingers or other "dirty" objects into his mouth about 10 

times a day ingesting 11 mg of dirt each time, Lepow et al. (1975) estimated that the daily 

soil ingestion rate would be about 100 mg/day. According to Lepow et al. (1975), the 

amount of hand dirt measured with this technique is probably an underestimate because 

dirt trapped in skin folds and creases was probably not removed by the adhesive label. 

Consequently, mean soil ingestion rates may be somewhat higher than the values 

estimated in this study. 

Day et al. (1975) - Lead in Urban Street Dust - Day et al. (1975) evaluated the 

contribution of incidental ingestion of lead-contaminated street dust and soil to children's 

total daily intake of lead by measuring the amount of lead in street dust and soil and 

estimating the amount of dirt ingested by children. The amount of soil that might be 

ingested was estimated by measuring the amount of dirt that was transferred to a "sticky 

sweet" during 30 minutes of play and assuming that a child might eat from 2 to 20 such 

sweets per day. Based on "a small number of direct measurements," Day et al. (1975) 

found that 5 to 50 mg of dirt from a child's hands may be transferred to a "sticky sweet" 

during 30 minutes of "normal playground activity. Assuming that all of the dirt is ingested 

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with the 2 to 20 "sticky sweets," Day et al. (1975) estimated that intake of soil among 

children could range from 10 to 1000 mg/day. 

Duggan and Williams (1977) - Lead in Dust in City Streets - Duggan and Williams 

(1977) assessed the risks associated with lead in street dust by analyzing street dust from 

areas in and around London for lead, and estimating the amount of hand dirt that a child 

might ingest. Duggan and Williams (1977) estimated the amount of dust that would be 

retained on the forefinger and thumb by removing a small amount of dust from a weighed 

amount, rubbing the forefinger and thumb together, and reweighing to determine the 

amount retained on the finger and thumb. The results of "a number of tests with several 

different people" indicated that the mean amount of dust retained on the finger and thumb 

was approximately 4 mg with a range of 2 to 7 mg (Duggan and Williams, 1977). 

Assuming that a child would suck his/her finger or thumb 10 times a day and that all of the 

dirt is removed each time and replaced with new dirt prior to subsequent mouthing 

behavior, Duggan and Williams (1977) estimated that 20 mg of dust would be ingested per 

day. 

Hawley et al. (1985) - Assessment of Health Risk from Exposure to Contaminated Soil 

- Using existing literature, Hawley (1985) developed scenarios for estimating exposure of 

young children, older children, and adults to contaminated soil. Annual soil ingestion rates 

were estimated based on assumed intake rates of soil and housedust for indoor and 

outdoor activities and assumptions about the duration and frequency of the activities. 

These soil ingestion rates were based on the assumption that the contaminated area is in 

a region having a winter season. Housedust was assumed to be comprised of 80 percent 

soil. 

Outdoor exposure to contaminated soil among young children (i.e., 2.5 years old) was 

assumed to occur 5 days per week during only 6 months of the year (i.e., mid-April through 

mid-October). Children were assumed to ingest 250 mg soil/day while playing outdoors 

based on data presented in Lepow et al. (1974; 1975) and Roels et al. (1980). Indoor 

exposures among this population were based on the assumption that young children ingest 

100 mg of housedust per day while spending all of their time indoors during the winter 

months, and 50 mg of housedust per day during the warmer months when only a portion 

of their time is spent indoors. Based on these assumptions, Hawley (1985) estimated that 

the annual average soil intake rate for young children is 150 mg/day (Table 4-11). Older 

children (i.e., 6 year olds) were assumed to ingest 50 mg of soil per day from an area 

equal to the area of the fingers on one hand while playing outdoors. This assumption was 

based on data from Lepow et al. (1975). Outdoor activities were assumed to occur each 

day over 5 months of the year (i.e., during May through October). These children were also 

assumed to ingest 3 mg/day of housedust from the indoor surfaces of the hands during 

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indoor activities occurring over the entire year. Using these data, Hawley (1985) estimated 

the annual average soil intake rate for older children to be 23.4 mg/day (Table 4-11).

Thompson and Burmaster (1991) - Parametric Distributions for Soil Ingestion by 

Children - Thompson and Burmaster (1991) developed parameterized distributions of soil 

ingestion rates for children based on a reanalysis of the data collected by Binder et al. 

(1986). In the original Binder et al. (1986) study, an assumed fecal weight of 15 g/day was 

used. Thompson and Burmaster reestimated the soil ingestion rates from the Binder et al. 

(1986) study using the actual stool weights of the study participants instead of the 

assumed stool weights. Because the actual stool weights averaged only 7.5 g/day, the soil 

ingestion estimates presented by Thompson and Burmaster (1991) are approximately onehalf of those reported by Binder et al. (1986). Table 4-12 presents the distribution of 

estimated soil ingestion rates calculated by Thompson and Burmaster (1991) based on the 

three tracers elements (i.e., aluminum, silicon, and titanium), and on the arithmetic average 

of soil ingestion based on aluminum and silicon. The mean soil intake rates were 97 

mg/day for aluminum, 85 mg/day for silicon, and 1,004 mg/day for titanium. The 90th 

percentile estimates were 197 mg/day for aluminum, 166 mg/day for silicon, and 2,105 

mg/day for titanium. Based on the arithmetic average of aluminum and silicon for each 

child, mean soil intake was estimated to be 91 mg/day and 90th percentile intake was 

estimated to be 143 mg/day. 

Thompson and Burmaster (1991) tested the hypothesis that soil ingestion rates based 

on the adjusted Binder et al. (1986) data for aluminum, silicon and the average of these 

two tracers were lognormally distributed. The distribution of soil intake based on titanium 

was not tested for lognormality because titanium may be present in food in high 

concentrations and the Binder et al. (1986) study did not correct for food sources of 

titanium (Thompson and Burmaster, 1991). Although visual inspection of the distributions 

for aluminum, silicon, and the average of these tracers all indicated that they may be 

lognormally distributed, statistical tests indicated that only silicon and the average of the 

silicon and aluminum tracers were lognormally distributed. Soil intake rates based on 

aluminum were not lognormally distributed. Table 4-12 also presents the lognormal 

distribution parameters and underlying normal distribution parameters (i.e., the natural 

logarithms of the data) for aluminum, silicon, and the average of these two tracers. 

According to the authors, "the parameters estimated from the underlying normal 

distribution are much more reliable and robust" (Thompson and Burmaster, 1991). 

The advantages of this study are that it provides percentile data and defines the 

shape of soil intake distributions. However, the number of data points used to fit the 

distribution was limited. In addition, the study did not generate "new" data. Instead, it 

provided a reanalysis of previously-reported data using actual fecal weights. No 

corrections were made for tracer intake from food or medicine and the results may not be 

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representative of long-term intake rates because the data were derived from a short-term 

study. 

Sedman and Mahmood (1994) - Soil Ingestion by Children and Adults Reconsidered 

Using the Results of Recent Tracer Studies - Sedman and Mahmood (1994) used the 

results of two recent children’s (Calabrese et al. 1989; Davis et al. 1990) tracer studies to

determine estimates of average daily soil ingestion in young children and for over a 

lifetime. In the two studies, the intake and excretion of a variety of tracers were monitored, 

and concentrations of tracers in soil adjacent to the children’s dwellings were determined 

(Sedman and Mahmood, 1994). From a mass balance approach, estimates of soil 

ingestion in these children were determined by dividing the excess tracer intake (i.e., 

quantity of tracer recovered in the feces in excess of the measured intake) by the average 

concentration of tracer in soil samples from each child's dwelling. Sedman and Mahmood 

(1994) adjusted the mean estimates of soil ingestion in children for each tracer (Y) from 

both studies to reflect that of a 2-year old child using the following equation: 

' x e (&0.112(yr) Y (Eqn. 4-3) i 

where:

Y = adjusted mean soil ingestion (mg/day) i 

x = a constant

yr = average age (2 years)

In addition to the study in young children, a study (Calabrese et al., 1989) in adults was

conducted to evaluate the tracer methodology. In the adult studies, percent recoveries of 

tracers were determined in six adults who ingested known quantities of tracers in 1.5 or 

0.3 grams of soil. The distribution of tracer recoveries from adults was evaluated using 

data analysis techniques involving visualization and exploratory data analysis (Sedman 

and Mahmood, 1994). From the results obtained in these studies, the distribution of tracer 

recoveries from adults were determined. In addition, an analysis of variance (ANOVA) and 

Tukey's multiple comparison methodologies were employed to identify differences in the 

recoveries of the various tracers (Sedman and Mahmood, 1994). 

From the adult studies, the ANOVA of the natural logarithm of the recoveries of 

tracers from 0.3 or 1.5 g of ingested soil showed a significant difference ( =0.05) among 

the estimates of recovery of the tracers regardless of whether the recoveries were 

combined or analyzed separately (Sedman and Mahmood, 1994). Sedman and Mahmood 

(1994) also reported that barium, manganese, and zirconium yielded significantly different 

estimates of soil ingestion than the other tracers (aluminum, silicon, yttrium, titanium, and 

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vanadium). Table 4-13 presents the Tukey's multiple comparison of mean log tracer 

recovery in adults ingesting known quantities of soil. 

The average ages of children in the two recent studies were 2.4 years in Calabrese,

et al. (1989) and 4.7 years in Davis et al. (1990). The mean of the adjusted levels of soil 

ingestion for a two year old child was 220 mg/kg for the Calabrese et al. (1989) study and 

170 mg/kg for the Davis et al. (1990) study (Sedman and Mahmood, 1994). From the 

adjusted soil ingestion estimates, based on a normal distribution of means, the mean 

estimate for a 2-year old child was 195 mg/day and the overall mean of soil ingestion and 

the standard error of the mean was 53 mg/day (Sedman and Mahmood, 1994). Based on 

uncertainties associated with the method employed, Sedman and Mahmood (1994) 

recommended a conservative estimate of soil ingestion in young children of 250 mg/day. 

Based on the 250 mg/day ingestion rate in a 2-year old child, an average daily soil 

ingestion over a lifetime was estimated to be 70 mg/day. The lifetime estimates were 

derived using the equation presented above that describes changes in soil ingestion with 

age (Sedman and Mahmood, 1994). 

AIHC Exposure Factors Sourcebook (1994) - The Exposure Factors Sourcebook 

(AIHC, 1994) uses data from the Calabrese et al. (1990) study to derive soil ingestion rates 

using zirconium as the tracer. More recent papers indicate that zirconium is not a good 

tracer. Therefore, the values recommended in the AIHC Sourcebook are not appropriate. 

Furthermore, because individuals were only studied for a short period of time, deriving a 

distribution of usual intake is not possible and is inappropriate. 

Calabrese and Stanek (1995) - Resolving Intertracer Inconsistencies in Soil Ingestion 

Estimation - Calabrese and Stanek (1995) explored sources and magnitude of positive and 

negative errors in soil ingestion estimates for children on a subject-week and trace element 

basis. Calabrese and Stanek (1995) identified possible sources of positive errors to be 

the following: 

 Ingestion of high levels of tracers before the study starts and low ingestion 

during study period may result in over estimation of soil ingestion; and 

 Ingestion of element tracers from a non-food or non-soil source during the 

study period. 

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Possible sources of negative bias identified by Calabrese and Stanek (1995) are the 

following: 

 Ingestion of tracers in food, but the tracers 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 which result in diminished detection of fecal 

tracers, but not in soil tracer levels. 

The authors developed an approach which attempted to reduce the magnitude of error in 

the individual trace element ingestion estimates. Results from a previous study conducted 

by Calabrese et al. (1989) were used to quantify these errors based on the following 

criteria: (1) a lag period of 28 hours was assumed for the passage of tracers ingested in 

food to the feces (this value was applied to all subject-day estimates); (2) daily soil 

ingestion rate was estimated for each tracer for each 24-hr day a fecal sample was 

obtained; (3) the median tracer-based soil ingestion rate for each subject-day was 

determined. Also, upper and lower bound 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; (4) negative errors due 

to missing fecal samples at the end of the study period were also determined (Calabrese 

and Stanek, 1995). 

Table 4-14 presents the estimated magnitude of positive and negative error for six 

tracer elements in the children's study (i.e., conducted by Calabrese et al., 1989). The 

original mean soil ingestion rates ranged from a low of 21 mg/day based on zirconium to 

a high of 459 mg/day based on titanium (Table 4-14). 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 (Table 4-14). Calabrese and Stanek (1995) 

concluded that correcting for errors at the individual level for each tracer element provides 

more reliable estimates of soil ingestion. 

This report is valuable in providing additional understanding of the nature of potential 

errors in trace element specific estimates of soil ingestion. However, the operational 

definition used for estimating the error in a trace element estimate was the observed 

difference of that tracer from a median tracer value. Specific identification of sources of 

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error, or direct evidence that individual tracers were indeed in error was not developed. 

Corrections to individual tracer means were then made according to how different values 

for that tracer were from the median values. This approach is based on the hypothesis 

that the median tracer value is the most accurate estimate of soil ingestion, and the validity 

of this assumption depends on the specific set of tracers used in the study and need not 

be correct. The approach used for the estimation of daily tracer intake is the same as in 

Stanek and Calabrese (1995a), and some limitations of that approach are mentioned in 

the review of that study. 

Sheppard (1995) - Parameter Values to Model the Soil Ingestion Pathway - Sheppard 

(1995) summarized the available literature on soil ingestion to estimate the amount of soil 

ingestion in humans for the purposes of risk assessment. Sheppard (1995) categorized 

the available soil ingestion studies into two general approaches: (1) those that measured 

the soil intake rate with the use of tracers in the soil, and (2) those that estimated soil 

ingestion based on activity (e.g., hand-to-mouth) and exposure duration. Sheppard (1995) 

provided estimates of soil intake based on previously published tracer studies. The data 

from these studies were assumed to be lognormally distributed due to the broad range, the 

concept that soil ingestion is never zero, and the possibility of very high values. In order 

to account for skewness in the data, geometric means rather than arithmetic means, were 

calculated by age, excluding pica and geophagy values. The geometric mean for soil 

ingestion rate for children under six was estimated to be 100 mg/day. For children over 

six and adults, the geometric mean intake rate was estimated to be 20 mg/day. Sheppard 

(1995) also provided soil ingestion estimates for indoor and outdoor activities based on 

data from Hawley (1985) and assumptions regarding duration of exposure (Table 4-15).

Sheppard's (1995) estimates, based on activity and exposure duration, are quite 

similar to the mean values from intake rate estimates described in previous sections. The 

advantages of this study are that the model can be used to calculate the ingestion rate 

from non-food sources with variability in exposure ingestion rates and exposure durations. 

The limitation of this study is that it does not introduce new data; previous data are reevaluated. In addition, because the model is based on previous data, the same 

advantages and limitations of those studies apply. 

4.4. SOIL INTAKE AMONG ADULTS 

Hawley 1985 - Assessment of Health Risk from Exposure to Contaminated Soil ­

Information on soil ingestion among adults is very limited. Hawley (1985) estimated soil 

ingestion among adults based on assumptions regarding activity patterns and 

corresponding ingestion amounts. Hawley (1985) assumed that adults ingest outdoor soil 

at a rate of 480 mg/day while engaged in yardwork or other physical activity. These 

outdoor exposures were assumed to occur 2 days/week during 5 months of the year (i.e., 

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May through October). The ingestion estimate was based on the assumption that a 50 

m/thick layer of soil is ingested from the inside surfaces of the thumb and fingers of one 

hand. Ingestion of indoor housedust was assumed to occur from typical living space 

activities such as eating and smoking, and work in attics or other uncleaned areas of the 

house. Hawley (1985) assumed that adults ingest an average of 0.56 mg housedust/day 

during typical living space activities and 110 mg housedust/day while working in attics. 

Attic work was assumed to occur 12 days/year. Hawley (1985) also assumed that soil 

comprises 80 percent of household dust. Based on these assumptions about soil intake 

and the frequency of indoor and outdoor activities, Hawley (1985) estimated the annual 

average soil intake rate for adults to be 60.5 mg/day (Table 4-16). 

The soil intake value estimated by Hawley (1985) is consistent with adult soil intake 

rates suggested by other researchers. Calabrese et al. (1987) suggested that soil intake 

among adults ranges from 1 to 100 mg/day. According to Calabrese et al. (1987), these 

values "are conjectural and based on fractional estimates" of earlier Center for Disease 

Control (CDC) estimates. In an evaluation of the scientific literature concerning soil 

ingestion rates for children and adults (Krablin, 1989), Arco Coal Company suggested that 

10 mg/day may be an appropriate value for adult soil ingestion. This value is based on 

"extrapolation from urine arsenic epidemiological studies and information on mouthing 

behavior and time activity patterns" (Krablin, 1989). 

Calabrese et al. (1990) - Preliminary Adult Soil Ingestion Estimates: Results of a Pilot 

Study- Calabrese et al. (1990) studied six adults to evaluate the extent to which they ingest 

soil. This adult study was originally part of the children soil ingestion study conducted by 

Calabrese and was used to validate part of the analytical methodology used in the children 

study. The participants were six healthy adults, three males and three females, 25-41 

years old. Each volunteer ingested one empty gelatin capsule at breakfast and one at 

dinner Monday, Tuesday, and Wednesday during the first week of the study. During the 

second week, they ingested 50 mg of sterilized soil within a gelatin capsule at breakfast 

and at dinner (a total of 100 mg of sterilized soil per day) for 3 days. For the third week, 

the participants ingested 250 mg of sterilized soil in a gelatin capsule at breakfast and at 

dinner (a total of 500 mg of soil per day) during the three days. Duplicate meal samples 

(food and beverage) were collected from the six adults. The sample included all foods 

ingested from breakfast Monday, through the evening meal Wednesday during each of the 

3 weeks. In addition, all medications and vitamins ingested by the adults were collected. 

Total excretory output were collected from Monday noon through Friday midnight over 3 

consecutive weeks. Table 4-17 provides the mean and median values of soil ingestion for 

each element by week. Data obtained from the first week, when empty gelatin capsules 

were ingested, may be used to derive an estimate of soil intake by adults. The mean 

intake rates for the eight tracers are: Al, 110 mg; Ba, -232 mg; Mn, 330 mg; Si, 30 mg; Ti, 

71 mg; V, 1,288 mg; Y, 63 mg; and Zr, 134 mg. 

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The advantage of this study is that it provides quantitative estimates of soil ingestion 

for adults. The study also corrected for tracer concentrations in foods and medicines. 

However, a limitation of this study is that a limited number of subjects were studied. In 

addition, the subjects were only studied for one week before soil capsules were ingested. 

4.5. PREVALENCE OF PICA 

The scientific literature define pica as "the repeated eating of non-nutritive 

substances" (Feldman, 1986). For the purposes of this handbook, pica is defined as an 

deliberately high soil ingestion rate. Numerous articles have been published that report 

on the incidence of pica among various populations. However, most of these papers 

describe pica for substances other than soil including sand, clay, paint, plaster, hair, string, 

cloth, glass, matches, paper, feces, and various other items. These papers indicate that 

the pica occurs in approximately half of all children between the ages of 1 and 3 years 

(Sayetta, 1986). The incidence of deliberate ingestion behavior in children has been 

shown to differ for different subpopulations. The incidence rate appears to be higher for 

black children than for white children. Approximately 30 percent of black children aged 1 

to 6 years are reported to have deliberate ingestion behavior, compared with 10 to 18 

percent of white children in the same age group (Danford, 1982). There does not appear 

to be any sex differences in the incidence rates for males or females (Kaplan and Sadock, 

1985). Lourie et al. (1963) states that the incidence of pica is higher among children in 

lower socioeconomic groups (i.e., 50 to 60 percent) than in higher income families (i.e., 

about 30 percent). Deliberate soil ingestion behavior appears to be more common in rural 

areas (Vermeer and Frate, 1979). A higher rate of pica has also been reported for 

pregnant women and individuals with poor nutritional status (Danford, 1982). In general, 

deliberate ingestion behavior is more frequent and more severe in mentally retarded 

children than in children in the general population (Behrman and Vaughan 1983, Danford 

1982, Forfar and Arneil 1984, Illingworth 1983, Sayetta 1986). 

It should be noted that the pica statistics cited above apply to the incidence of general 

pica and not soil pica. Information on the incidence of soil pica is limited, but it appears 

that soil pica is less common. A study by Vermeer and Frate (1979) showed that the 

incidence of geophagia (i.e., earth-eating) was about 16 percent among children from a 

rural black community in Mississippi. However, geophagia was described as a cultural 

practice among the community surveyed and may not be representative of the general 

population. Average daily consumption of soil was estimated to be 50 g/day. Bruhn and 

Pangborn (1971) reported the incidence of pica for "dirt" to be 19 percent in children, 14 

percent in pregnant women, and 3 percent in nonpregnant women. However, "dirt" was 

not clearly defined. The Bruhn and Pangborn (1971) study was conducted among 91 nonblack, low income families of migrant agricultural workers in California. Based on the data 

from the five key tracer studies (Binder et al., 1986; Clausing et al., 1987; Van Wïjnen et

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Chapter 4 - Soil Ingestion and Pica 

al., 1990; Davis et al., 1990; and Calabrese et al., 1989) only one child out of the more 

than 600 children involved in all of these studies ingested an amount of soil significantly 

greater than the range for other children. Although these studies did not include data for 

all populations and were representative of short-term ingestions only, it can be assumed 

that the incidence rate of deliberate soil ingestion behavior in the general population is 

low. However, it is incumbent upon the user to use the appropriate value for their specific 

study population. 

4.6. DELIBERATE SOIL INGESTION AMONG CHILDREN 

Information on the amount of soil ingested by children with abnormal soil ingestion 

behavior is limited. However, some evidence suggests that a rate on the order of 10 g/day 

may not be unreasonable. 

Calabrese et al. (1991) - Evidence of Soil Pica Behavior and Quantification of Soil 

Ingestion - Calabrese et al. (1991) estimated that upper range soil ingestion values may 

range from approximately 5-7 grams/day. This estimate was based on observations of one 

pica child among the 64 children who participated in the study. In the study, a 3.5-year old 

female exhibited extremely high soil ingestion behavior during one of the two weeks of 

observation. Intake ranged from 74 mg/day to 2.2 g/day during the first week of 

observation and 10.1 to 13.6 g/day during the second week of observation (Table 4-18).

These results are based on mass-balance analyses for seven (i.e., aluminum, barium, 

manganese, silicon, titanium, vanadium, and yttrium) of the eight tracer elements used. 

Intake rates based on zirconium was significantly lower but Calabrese et al. (1991) 

indicated that this may have "resulted from a limitation in the analytical protocol." 

Calabrese and Stanek (1992) - Distinguishing Outdoor Soil Ingestion from Indoor Dust 

Ingestion in a Soil Pica Child - Calabrese and Stanek (1992) quantitatively distinguished 

the amount of outdoor soil ingestion from indoor dust ingestion in a soil pica child. This 

study was based on a previous mass-balance study (conducted in 1991) in which a 3-1/2 

year old child ingested 10-13 grams of soil per day over the second week of a 2-week soil 

ingestion study. Also, the previous study utilized a soil tracer methodology with eight 

different tracers (Al, Ba, Mn, Si, Ti, V, Y, Zr). The reader is referred to Calabrese et al. 

(1989) for a detailed description and results of the soil ingestion study. Calabrese and 

Stanek (1992) distinguished indoor dust from outdoor soil in ingested soil based on a 

methodology which compared differential element ratios. 

Table 4-19 presents tracer ratios of soil, dust, and residual fecal samples in the soil 

pica child. Calabrese and Stanek (1992) reported that there was a maximum total of 28 

pairs of tracer ratios based on eight tracers. However, only 19 pairs of tracer ratios were 

available for quantitative evaluation as shown in Table 4-19. Of these 19 pairs, 9 fecal 

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tracer ratios fell within the boundaries for soil and dust (Table 4-19). For these 9 tracer 

soils, an interpolation was performed to estimate the relative contribution of soil and dust 

to the residual fecal tracer ratio. The other 10 fecal tracer ratios that fell outside the soil 

and dust boundaries were concluded to be 100 percent of the fecal tracer ratios from soil 

origin (Calabrese and Stanek, 1992). Also, the 9 residual fecal samples within the 

boundaries revealed that a high percentage (71-99 percent) of the residual fecal tracers 

were estimated to be of soil origin. Therefore, Calabrese and Stanek (1992) concluded 

that the predominant proportion of the fecal tracers was from outdoor soil and not from 

indoor dust origin. 

In conducting a risk assessment for TCDD, U.S. EPA (1984) used 5 g/day to 

represent the soil intake rate for pica children. The Centers for Disease Control (CDC) 

also investigated the potential for exposure to TCDD through the soil ingestion route. CDC 

used a value of 10 g/day to represent the amount of soil that a child with deliberate soil 

ingestion behavior might ingest (Kimbrough et al., 1984). These values are consistent with 

those observed by Calabrese et al. (1991). 

4.7. RECOMMENDATIONS 

The key studies described in this section were used to recommend values for soil 

intake among children. The key and relevant studies used different survey designs and 

study populations. These studies are summarized in Table 4-20. For example, some of 

the studies considered food and nonfood sources of trace elements, while others did not. 

In other studies, soil ingestion estimates were adjusted to account for the contribution of 

house dust to this estimate. Despite these differences, the mean and upper-percentile 

estimates reported for these studies are relatively consistent. The confidence rating for 

soil intake recommendations is presented in Table 4-21. 

It is important, however, to understand the various uncertainties associated with these 

values. First, individuals were not studied for sufficient periods of time to get a good 

estimate of the usual intake. Therefore, the values presented in this section may not be 

representative of long term exposures. Second, the experimental error in measuring soil 

ingestion values for individual children is also a source of uncertainty. For example, 

incomplete sample collection of both input (i.e., food and nonfood sources) and output 

(i.e., urine and feces) is a limitation for some of the studies conducted. In addition, an 

individual's soil ingestion value may be artificially high or low depending on the extent to 

which a mismatch between input and output occurs due to individual variation in the 

gastrointestinal transit time. Third, the degree to which the tracer elements used in these 

studies are absorbed in the human body is uncertain. Accuracy of the soil ingestion 

estimates depends on how good this assumption is. Fourth, there is uncertainty with 

regard to the homogeneity of soil samples and the accuracy of parent's knowledge about 

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their child's playing areas. Fifth, all the soil ingestion studies presented in this section with 

the exception of Calabrese et al. (1989) were conducted during the summer when soil 

contact is more likely. 

Although the recommendations presented below are derived from studies which were 

mostly conducted in the summer, exposure during the winter months when the ground is 

frozen or snow covered should not be considered as zero. Exposure during these months, 

although lower than in the summer months, would not be zero because some portion of the 

house dust comes from outdoor soil. 

Soil Ingestion Among Children - Estimates of the amount of soil ingested by children 

are summarized in Table 4-22. The mean values ranged from 39 mg/day to 271 mg/day 

with an average of 146 mg/day for soil ingestion and 191 mg/day for soil and dust 

ingestion. Results obtained using titanium as a tracer in the Binder et al. (1986) and 

Clausing et al. (1987) studies were not considered in the derivation of this 

recommendation because these studies did not take into consideration other sources of 

the element in the diet which for titanium seems to be significant. Therefore, these values 

may overestimate the soil intake. One can note that this group of mean values is 

consistent with the 200 mg/day value that EPA programs have used as a conservative 

mean estimate. Taking into consideration that the highest values were seen with titanium, 

which may exhibit greater variability than the other tracers, and the fact that the Calabrese 

et al. (1989) study included a pica child, 100 mg/day is the best estimate of the mean for 

children under 6 years of age. However, since the children were studied for short periods 

of time and the prevalence of pica behavior is not known, excluding the pica child from the 

calculations may underestimate soil intake rates. It is plausible that many children may 

exhibit some pica behavior if studied for longer periods of time. Over the period of study, 

upper percentile values ranged from 106 mg/day to 1,432 mg/day with an average of 383 

mg/day for soil ingestion and 587 mg/day for soil and dust ingestion. Rounding to one 

significant figure, the recommended upper percentile soil ingestion rate for children is 400 

mg/day. However, since the period of study was short, these values are not estimates of 

usual intake. The recommended values for soil ingestion among children and adults are 

summarized in Table 4-23. 

Data on soil ingestion rates for children who deliberately ingest soil are also limited. 

An ingestion rate of 10 g/day is a reasonable value for use in acute exposure 

assessments, based on the available information. It should be noted, however, that this 

value is based on only one pica child observed in the Calabrese et al. (1989) study. 

Soil Ingestion Among Adults - Only three studies have attempted to estimate adult soil 

ingestion. Hawley (1985) suggested a value of 480 mg/day for adults engaged in outdoor 

activities and a range of 0.56 to 110 mg/day of house dust during indoor activities. These 

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estimates were derived from assumptions about soil/dust levels on hands and mouthing 

behavior; no supporting measurements were made. Making further assumptions about 

frequencies of indoor and outdoor activities, Hawley (1985) derived an annual average of 

60.5 mg/day. Given the lack of supporting measurements, these estimates must be 

considered conjectural. Krablin (1989) used arsenic levels in urine (n=26) combined with 

information on mouthing behavior and activity patterns to suggest an estimate for adult soil 

ingestion of 10 mg/day. The study protocols are not well described and has not been 

formally published. Finally, Calabrese et al. (1990) conducted a tracer study on 6 adults 

and found a range of 30 to 100 mg/day. This study is probably the most reliable of the 

three, but still has two significant uncertainties: (1) representativeness of the general 

population is unknown due to the small study size (n=6); and (2) representativeness of 

long-term behavior is unknown since the study was conducted over only 2 weeks. In the 

past, many EPA risk assessments have assumed an adult soil ingestion rate of 50 mg/day 

for industrial settings and 100 mg/day for residential and agricultural scenarios. These 

values are within the range of estimates from the studies discussed above. Thus, 50 

mg/day still represents a reasonable central estimate of adult soil ingestion and is the 

recommended value in this handbook. This recommendation is clearly highly uncertain; 

however, and as indicated in Table 4-21, is given a low confidence rating. Considering 

the uncertainties in the central estimate, a recommendation for an upper percentile value 

would be inappropriate. Table 4-23 summarizes soil ingestion recommendations for 

adults. 

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Chapter 5 - Inhalation 

5. INHALATION ROUTE 

This chapter presents data and recommendations for inhalation rates that can be 

used to assess exposure to contaminants in air. The studies discussed in this chapter 

have been classified as key or relevant. Key studies are used as the basis for deriving 

recommendations and the relevant studies are included to provide additional background 

and perspective. The recommended inhalation rates are summarized in Section 5.2.4 and 

cover adults, children, and outdoor workers/athletes. 

Inclusion of this chapter in the Exposure Factors Handbook does not imply that 

assessors will always need to select and use inhalation rates when evaluating exposure 

to air contaminants. In fact, it is unnecessary to calculate inhaled dose when using doseresponse factors from Integrated Risk Information System (IRIS) (U.S. EPA, 1994). This 

is due to the fact that IRIS methodology accounts for inhalation rates in the development 

of “dose-response” relationships. When using IRIS for inhalation risk assessments, “doseresponse” relationships require only an average air concentration to evaluate health 

concerns: 

C For non-carcinogens, IRIS uses Reference Concentrations (RfC) which are 

expressed in concentration units. Hazard is evaluated by comparing the inspired 

air concentration to the RfC. 

C 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). 

3 IRIS employs a default inhalation rate of 20 m /day. This is greater than the 

recommendated value in this chapter. When using IRIS, adjustments of dose-response 

3 relationships using inhalation rates other than the default, 20 m /day, are not currently 

recommended. There are instances where the inhalation rate data presented in this 

chapter may be used for estimating average daily dose. For example, the inhalation 

average daily dose is often estimated in cases where a compative pathway analysis is 

desired or to determine a total dose by adding across pathways in cases where RfCs and 

unit risk factors are not available. 

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5.1. EXPOSURE EQUATION FOR INHALATION 

For those cases where the average daily dose (ADD) needs to be estimated, the 

general equation is: 

ADD = [[C x IR x ED] / [BW x AT]] (Eqn. 5-1) 

where: 

ADD = average daily dose (mg/kg-day); 

C = contaminant concentration in inhaled air (Fg/m ); 3 

IR = inhalation rate (m /day); 3 

ED = exposure duration (days); 

BW = body weight (kg); and 

AT = averaging time (days), for non-carcinogenic effects AT = ED, for carcinogenic or chronic effects 

AT = 70 years or 25,550 days (lifetime). 

The average daily dose is the 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. For compounds with 

carcinogenic or chronic effects, the lifetime average daily dose (LADD) is used. The LADD 

is the dose rate averaged over a lifetime. The contaminant concentration refers to the 

concentration of the contaminant in inhaled air. Exposure duration refers to the total time 

an individual is exposed to an air pollutant. 

5.2. INHALATION RATE 

5.2.1. Background 

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 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 (Figure 5-1). When constructing risk assessments that concern the inhalation route 

of exposure, one must be aware if any adjustments have been employed in the estimation 

of the pollutant concentration to account for this reduction in potential dose. 

The respiratory system is comprised of three regions: nasopharyngeal, 

tracheobronchial, and pulmonary. The nasopharyngeal region extends from the nose to 

the larynx. The tracheobronchial region forms the conducting airways between 

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nasopharynx and alveoli where gas exchange occurs. It consists of the trachea, bronchi, 

and bronchioles. The pulmonary regions consists of the acinus which is the site where gas 

exchange occurs; it is comprised of respiratory bronchioles, alveolar ducts and sacs, and 

alveoli. A detailed discussion of pulmonary anatomy and physiology can be found in: 

Benjamin (1988) and U.S. EPA (1989 and 1994) . 

Each region in the respiratory system can be involved with removing pollutants from 

inspired air. The nasopharyngeal region filters out large inhaled particles, moderates the 

temperature, and increases the humidity of the air. The surface of the tracheobronchial 

region is covered with ciliated mucous secreting cells which forms a mucociliary escalator 

that moves particles from deep regions of the lung to the oral cavity where they may be 

swallowed and then excreted. The branching pattern and physical dimensions of the these 

airways determine the pattern of deposition of airborne particles and absorption of gases 

by the respiratory tract. They decrease in diameter as they divide into a bifurcated 

branching network dilutes gases by axial diffusion of gases along the streamline of airways 

and radial diffusion of gases due to an increase in cross sectional area of the lungs. The 

velocity of the airstream in this decreasing branching network creates a turbulent force 

such that airborne particles can be deposited along the walls of these airways by 

impaction, interception, sedimentation, or diffusion depending on their size. The 

pulmonary region contains macrophages which engulf particles and pathogens that enter 

this portion of the lung. 

Notwithstanding these removal mechanisms, both gaseous and particulate pollutants 

can deposit in various regions of the lung. Both the physiology of the lung and the 

chemistry of the pollutant influences where the pollutant tends to deposit. 

Gaseous pollutants are evenly dispersed in the air stream. They come into contact 

with a large portion of the lung. Generally, their solubility and reactivity determines where 

they deposit in the lung. Water soluble and chemically reactive gases tend to deposit in 

the upper respiratory tract. Lipid soluble or non-reactive gases usually are not removed 

in the upper airways and tend to deposit in the distal portions of the lung. Gases can be 

absorbed into the blood stream or react with lung tissue. Gases can be removed from the 

lung by reaction with tissues or by expiration. The amount of gas retained in the lung or 

other parts of the body is mainly due to their solubility in blood. 

Chemically, particles are quite heterogenous. They range from aqueous soluble 

particles to solid insoluble particles. Their size, chemical composition, and the physical 

forces of breathing dictate where they tend to deposit in the lung. Large particles, those 

with a diameter of greater than 0.5 micrometers (um), not filtered out in the nasopharynx, 

tend to deposit in the upper respiratory tract at airway branching points due to impaction. 

The momentum of these particles in the air stream is such that they tend to collide with the 

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airway wall at branching points in the tracheobronchial region of the lung. Those particles 

not removed from the airstream by impaction will likely be deposited in small bronchi and 

bronchioles by sedimentation, a process where by particles settle out of the airstream due 

to the decrease in airstream velocity and the gravitational force on the particles. Small 

particles, less than 0.2 um, acquire a random motion due to bombardment by air 

molecules. This movement can cause particles to be deposited on the wall of an air way 

throughout the lungs. 

A special case exists for fibers. Fibers can deposit along the wall of an airway by a 

process known as interception. This occurs when a fiber makes contact with an airway 

wall. The likelihood of interception increases as airway diminish in diameter. Fiber shape 

influences deposition too. Long, thin, straight fibers tend to deposit in the deep region of 

the lung compared to thick or curved fibers. 

The health risk associated with human exposure to airborne toxics is a function of 

concentration of air pollutants, chemical species, duration of exposure, and inhalation rate. 

The dose delivered to target organs (including the lungs), the biologically effective dose, 

is dependent on the potentail dose, the applied dose and the internal dose (Figure 5-1) A 

detailed discussion of this concept can be found in Guidelines for Exposure Assessment 

(U.S. EPA, 1992). 

The estimation of applied dose for a given air pollutant is dependent on inhalation 

rate, commonly described as ventilation rate (VR) or breathing rate. VR is usually 

measured as minute volume, the volume in liters of air exhaled per minute(V E E ). V is the

product of the number of respiratory cycles in a minute and the volume of air respired 

during each respiratory cycle, the tidal volume( V ). T 

When interested in calculating internal dose, assessors must consider the alveolar 

ventilation rate. This is the amount of air available for exchange with alveoli per unit time. 

It is equivalent to the tidal volume( V ) minus the anatomic dead space of the lungs (the T 

space containing air that does not come into contact with the alveoli). Alveolar ventilation 

is approximately 70 percent of total ventilation; tidal volume is approximately 500 milliliters 

(ml) and the amount of anatomic dead space in the lungs is approximately 150 ml, 

approximately 30% of the amount of air inhaled (Menzel and Amdur, 1986). 

Breathing rates are affected by numerous individual characteristics, including age, 

gender, weight, health status, and levels of activity (running, walking, jogging, etc.). VRs 

are either measured directly using a spirometer and a collection system or indirectly from 

heart rate (HR) measurements. In many of the studies described in the following sections, 

HR measurements are usually correlated with VR in simple and multiple regression 

analysis. 

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The available studies on inhalation rates are summarized in the following sections. 

Inhalation rates are reported for adults and children (including infants) performing various 

activities and outdoor workers/ athletes. The activity levels have been categorized as 

resting, sedentary, light, moderate, and heavy. In most studies, the sample population 

kept diaries to record their physical activities, locations, and breathing rates. Ventilation 

rates were either measured, self-estimated or predicted from equations derived using VRHR calibration relationships. 

5.2.2. Key Inhalation Rate Studies 

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 (O ) in their 3 

daily activities in the Los Angeles area. The population surveyed consisted of seven 

subject panels: Panel 1: 20 healthy outdoor workers (15 males, 5 females, ages 19-50 

years); Panel 2: 17 healthy elementary school students (5 males, 12 females, ages 10-12 

years); Panel 3: 19 healthy high school students (7 males, 12 females, ages 13-17 years); 

Panel 4: 49 asthmatic adults (clinically mild, moderate, and severe, 15 males, 34 females, 

ages 18-50 years); Panel 5: 24 asthmatic adults from 2 neighborhoods of contrasting O3 

air quality (10 males, 14 females, ages 19-46 years); Panel 6: 13 young asthmatics (7 

males, 6 females, ages 11-16 years); Panel 7: construction workers (7 males, ages 26-34 

years). 

Initially, a calibration test was conducted, followed by a training session. Finally, a 

field study was conducted which involved subjects' collecting their own heart rate and diary 

data. During the calibration tests, VR and HR were measured simultaneously at each 

exercise level. From the calibration data an equation was developed using linear 

regression analysis to predict VR from measured HR (Linn et al., 1992).

In the field study, each subject (except construction workers) recorded in diaries: 

their daily activities, change in locations (indoors, outdoors, or in a vehicle), self-estimated 

breathing rates during each activity/location, and time spent at each activity/location. 

Healthy subjects recorded their HR once every 60 seconds, Asthmatic subjects recorded 

their diary information once every hour using a Heart Watch. Construction workers 

dictated their diary information to a technician accompanying them on the job. 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 5-1 presents the 

calibration and field protocols for self-monitoring of activities for each subject panel. 

Table 5-2 presents the mean VR, the 99th percentile VR, and the mean VR at each 

subjective activity level (slow, medium, fast). The mean VR and 99th percentile VR were 

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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 (Linn et al., 1992). The mean VR 

3 3 for healthy adults was 0.78 m /hr while the mean VR for asthmatic adults was 1.02 m /hr 

(Table 5-2). The preliminary data for construction workers indicated that during a 10-hr 

3 work shift, their mean VR (1.50 m /hr) exceeded the VRs of all other subject panels (Table 

5-2). Linn et al. (1992) reported that the diary data showed that most individuals except 

construction workers spent most of their time (in a typical day) indoors at slow activity 

level. During slow activity, asthmatic subjects had higher VRs than healthy subjects, 

except construction workers (Table 5-2). Also, Linn et al. (1992) 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 calibrated. Another 

limitation of this study 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 various subpopulations (i.e., healthy outdoor adult workers, 

healthy children, asthmatics, and construction workers). 

Spier et al. (1992) - Activity Patterns in Elementary and High School Students 

Exposed To Oxidant Pollution - Spier et al. (1992) investigated 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 for each: 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, change 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 during the 3 days once per minute by wearing a Heart Watch. VR 

values for each self-estimated breathing rate and activity type were estimated from the HR 

recordings by employing the VR and HR equation obtained from the calibration tests. 

The data presented in Table 5-3 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 hours spent indoors by high school students 

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(21.2 hours) were higher 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 5-4). Based on the data presented in Tables 5-3 

and 5-4, the average activity-specific inhalation rates for elementary (10-12 years) and 

high school (13-17 years) students were calculated in Table 5-5. For elementary school 

students, the average daily inhalation rates (based on indoor and outdoor locations) are 

3 3 3 15.8 m /day for light activities, 4.62 m /day for moderate activities, and 0.98 m /day for 

heavy activities. For high school students the daily inhalation rates for light, moderate, 3 3 and heavy activities are estimated to be 16.4 m /day, 3.1 m /day, and 0.54 m /day, 

respectively (Table 5-5). 

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. 

Adams (1993) - Measurement of Breathing Rate and Volume in Routinely Performed 

Daily Activities - 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 

used to predict inhalation rates through other measured variables: heart rate (HR), 

breathing frequency (f ), and oxygen consumption (V ). A total of 160 subjects B O2 

participated in the primary study. There were four age dependent groups: (1) children 6 

to 12.9 years old, (2) adolescents between 13 and 18.9 years old, (3) adults between 19 

and 59.9 years old, and (4) seniors >60 years old (Adams, 1993). An additional 40 

children from 6 to 12 years old and 12 young children from 3 to 5 years old were identified 

as subjects for pilot testing purposes in this age group (Adams, 1993). 

Resting protocols conducted in the laboratory for all age groups consisted of three 

phases (25 minutes each) of lying, sitting, and standing. They 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 

intensities made up of 6 minute intervals, at 3 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. 

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In the field, all children completed spontaneous play protocols, while the older 

adolescent population (16-18 years) completed car driving and riding, car maintenance 

(males), and housework (females) protocols. All adult females (19-60 years) and most of 

the senior (60-77 years) females completed housework, yardwork, and car driving and 

riding protocols. Adult and senior males completed car driving and riding, yardwork, and 

mowing protocols. HR, VR, and fB were measured during each protocol. Most protocols

were conducted for 30 minutes. All the active field protocols were conducted twice. 

During all activities in either the laboratory or field protocols, IR for the children's 

group revealed no significant gender differences, but those for the adult groups 

demonstrated gender differences. Therefore, IR data presented in Appendix Tables 5A-1 

and 5A-2 were categorized as young children, children (no gender),and for adult female, 

and adult male by activity levels (resting, sedentary, light, moderate, and heavy). These 

3 categorized data from the Appendix tables are summarized as IR in m /hr in Tables 5-6 

and 5-7. The laboratory protocols are shown in Table 5-6. Table 5-7 presents the mean 

inhalation rates by group and activity levels (light, sedentary, and moderate) in field 

protocols. A comparison of the data shown in Tables 5-6 and 5-7 suggest that during light 

and sedentary activities in laboratory and field protocols, similar inhalation rates were 

obtained for adult females and adult males. Accurate predictions of IR across all 

population groups and activity types were obtained by including body surface area (BSA), 

HR, and fB in multiple regression analysis (Adams, 1993). Adams (1993) calculated BSA

from measured height and weight using the equation: 

(0.425) BSA = Height(0.725) x Weight x 71.84. (Eqn. 5-2) 

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. An advantage of this study is that it provides inhalation data for all age groups. 

Linn et al. (1993) - Activity patterns in Ozone Exposed Construction Workers - Linn 

et al. (1993) estimated the inhalation rates of 19 construction workers who perform heavy 

outdoor labor before and during a typical work shift. The workers (laborers, iron workers, 

and carpenters) were employed at a site on a hospital campus in suburban Los Angeles. 

The construction site included a new hospital building and a separate medical office 

complex. The study was conducted between mid-July and early November, 1991. During 

this period, ozone (O ) levels were typically high. Initially, each subject was calibrated with 3 

a 25-minute exercise test that included slow walking, fast walking, jogging, lifting, and 

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carrying. All calibration tests were conducted in the mornings. VR and HR were measured 

simultaneously during the test. The data were analyzed using least squares regression 

to derive an equation for predicting VR at a given HR. Following the calibration tests, each 

subject recorded the type of activities to be performed during their work shift (i.e., 

sitting/standing, walking, lifting/carrying, and "working at trade" - defined as tasks specific 

to the individual's job classification). Location, and self-estimated breathing rates ("slow" 

similar to slow walking, "medium" similar to fast walking, and "fast" similar to running) were 

also recorded in the diary. During work, an investigator recorded the diary information 

dictated by the subjects. HR was recorded minute by minute for each subject before work 

and during the entire work shift. Thus, VR ranges for each breathing rate and activity 

category were estimated from the HR recordings by employing the relationship between 

VR and HR obtained from the calibration tests. 

A total of 182 hours of HR recordings were obtained during the survey from the 19 

volunteers; 144 hours reflected actual working time according to the diary records. The 

lowest actual working hours recorded was 6.6 hours and the highest recorded for a 

complete work shift was 11.6 hours (Linn et al., 1993). Summary statistics for predicted 

VR distributions for all subjects, and for job or site defined subgroups are presented in 

Table 5-8. The data reflect all recordings before and during work, and at break times. For 

3 all subjects, the mean IR was 1.68 m /hr with a standard deviation of ±0.72 (Table 5-8). 

Also, for most subjects, the 1st and 99th percentiles of HR were outside of the calibration 

range (calibration ranges are presented in Appendix Table 5A-3). Therefore, 

corresponding IR percentiles were extrapolated using the calibration data (Linn et al., 

1993). 

The data presented in Table 5-9 represent distribution patterns of IR for each subject, 

total subjects, and job or site defined subgroups by self-estimated breathing rates (slow, 

medium, fast) or by type of job activity. All data include working and non-working hours. 

The mean inhalation rates for most individuals showed statistically significant increases 

with higher self-estimated breathing rates or with increasingly strenuous job activity (Linn 

et al., 1993). Inhalation rates were higher in hospital site workers when compared with 

office site workers (Table 5-9). In spite of their higher predicted VR workers at the hospital 

site reported a higher percentage of slow breathing time (31 percent) than workers at the 

office site (20 percent), and a lower percentage of fast breathing time, 3 percent and 5 

percent, respectively (Linn et al., 1993). Therefore, individuals whose work was objectively 

heavier than average (from VR predictions) tended to describe their work as lighter than 

average (Linn et al., 1993). Linn et al. (1993) also concluded that during an O pollution 3 

episode, construction workers should experience similar microenvironmental O exposure 3 

concentrations as other healthy outdoor workers, but with approximately twice as high a 

VR. Therefore, the inhaled dose of O should be almost two times higher for typical heavy­ 3 

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construction workers than for typical healthy adults performing less strenuous outdoor 

jobs. 

A limitation associated with this study is the small sample size. Another limitation of 

this study is that calibration data were not obtained at extreme conditions. Therefore, it 

was necessary to predict IR values that were outside the calibration range. This may 

introduce an unknown amount of uncertainty to the data set. Subjective self-estimated 

breathing rates may be another source of uncertainty in the inhalation rates estimated. An 

advantage is that this study provides empirical data useful in exposure assessments for 

a subpopulation thought to be the most highly exposed common occupational group 

(outdoor workers). 

Layton (1993) - Metabolically Consistent Breathing Rates for Use in Dose 

Assessments - Layton (1993) presented a new 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 (Layton, 1993). However, in this study, breathing 

rates were calculated based on oxygen consumption associated with energy expenditures 

for short (hours) and long (weeks and months) periods of time, using the following general 

equation to calculate energy-dependent inhalation rates: 

VE = E x H x VQ (Eqn. 5-3) 

where: 3 VE = ventilation rate (L/min or m /hr);

E = energy expenditure rate; [kilojoules/minute (KJ/min) or megajoules/hour (MJ/hr)];

H = volume of oxygen [at standard temperature and pressure, dry air (STPD) consumed in the 3 production of 1 kilojoule (KJ) of energy expended (L/KJ or m /MJ)]; and

VQ = ventilatory equivalent (ratio of minute volume (L/min) to oxygen uptake (L/min)) unitless. 

Three alternative approaches were used 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, volume of oxygen (H), and ventilatory equivalent (VQ), as 

shown in the equation above. The average food energy intake data (Table 5-10) are 

based on approximately 30,000 individuals and were obtained from the USDA 1977-78 

Nationwide Food Consumption Survey (USDA-NFCS). The food energy intakes were 

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Chapter 5 - Inhalation 

adjusted upwards by a constant factor of 1.2 for all individuals 9 years and older (Layton, 

1993). This factor compensated for a consistent bias in USDA-NFCS 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 O /KJ which was determined 2 

from data reported in the 1977-78 USDA-NFCS and the second National Health and 

Nutrition Examination Survey (NHANES II). The survey sample for NHANES II was 

approximately 20,000 participants. The ventilatory equivalent (VQ) of 27 used was 

calculated as the geometric mean of VQ data that were obtained from several studies by 

Layton (1993). 

The inhalation rate estimation techniques are shown in footnote (a) of Table 5-11. 

Table 5-11 presents the daily inhalation rate for each age/gender cohort. The highest 

3 daily inhalation rates were reported for children between the ages of 6-8 years (10 m /day), 

3 3 for males between 15-18 years (17 m /day), and females between 9-11 years (13 m /day). 

3 Estimated average lifetime inhalation rates for males and females are 14 m /day and 10 

3 m /day, respectively (Table 5-11). 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 basal 

metabolic rate (BMR) times the oxygen uptake (H) times the 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 5-11. These data for active and inactive inhalation rates are also presented in Table 

5-11. For children, inactive and active inhalation rates ranged between 2.35 and 5.95 

3 3 m /day and 6.35 to 13.09 m /day, respectively. For adult males (19-64 years old), the 

3 average inactive and active inhalation rates were approximately 10 and 19 m /day, 

respectively. Also, the average inactive and active inhalation rates for adult females (19­

3 64 years old) were approximately 8 and 12 m /day, respectively. 

Second Approach 

Inhalation rates were calculated by multiplying the BMR of the population cohorts 

times A (ratio of total daily energy expenditure to daily BMR) times H times VQ. The BMR 

data obtained from literature were statistically analyzed and regression equations were 

developed to predict BMR from body weights of various age/gender cohorts (Layton, 

1993). The statistical data used to develop the regression equations are presented in 

Appendix Table 5A-4. The data obtained from the second approach are presented in 

3 Table 5-12. Inhalation rates for children (6 months - 10 years) ranged from 7.3-9.3 m /day 

3 3 for male and 5.6 to 8.6 m /day for female children and (10-18 years) was 15 m /day for 

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3 males and 12 m /day for females. Adult females (18 years and older) ranged from 9.9-11 

3 3 m /day and adult males (18 years and older) ranged from 13-17 m /day. These rates are 

similar to the daily inhalation rates obtained using the first approach. Also, the inactive 

inhalation rates obtained from the first approach are lower than the inhalation rates 

obtained using the second approach. This may be attributed to the BMR multiplier 

employed in the equation of the second approach to calculate inhalation rates. 

Third Approach 

Inhalation rates were calculated by multiplying estimated energy expenditures 

associated with different levels of physical activity engaged in over the course of an 

average day by VQ and H for each age/gender cohort. The energy expenditure associated 

with each level of activity was estimated by multiplying BMRs of each activity level by the 

metabolic equivalent (MET) and by the time spent per day performing each activity for 

each age/gender population. The time-activity data used in this approach were obtained 

from a survey conducted by Sallis et al. (1985) (Layton, 1993). In that survey, the 

physical-activity categories and associated MET values used were sleep, MET=1; lightactivity, MET=1.5; moderate activity, MET=4; hard activity, MET=6; and very hard activity, 

MET=10. The physical activities were based on recall by the test subject (Layton, 1993). 

The survey sample was 2,126 individuals (1,120 women and 1,006 men) ages 20-74 years 

that were randomly selected from four communities in California. The BMRs were 

estimated using the metabolic equations presented in Appendix Table 5A-4. The body 

weights were obtained from a study conducted by Najjar and Rowland (1987) which 

randomly sampled individuals from the U.S. population (Layton, 1993). Table 5-13 

3 3 presents the inhalation rates (V ) in m /day and m /hr for adult males and females aged E 

20-74 years at five physical activity levels. The total daily inhalation rates ranged from 13­

3 3 17 m /day for adult males and 11-15 m /day for adult females. 

The rates for adult females were higher when compared with the other two 

approaches. Layton (1993) reported that the estimated inhalation rates obtained from the 

third approach were particularly sensitive to the MET value that represented the energy 

expenditures for light activities. Layton (1993) stated further that in the original timeactivity survey (i.e., conducted by Sallis et al., 1985), time spent performing light activities 

was not presented. Therefore, the time spent at light activities was estimated by 

subtracting the total time spent at sleep, moderate, heavy, and very heavy activities from 

24 hours (Layton, 1993). The range of inhalation rates for adult females were 9.6 to 11 

3 3 3 m /day, 9.9 to 11 m /day, and 11 to 15 m /day, for the first, second, and third approach, 

3 respectively. The inhalation rates for adult males ranged from 13 to 16 m /day for the first 

3 approach, and 13 to 17 m /day for the second and third approaches. 

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Inhalation rates were also obtained for short-term exposures for various age/gender 

cohorts and five energy-expenditure categories (rest, sedentary, light, moderate, and 

heavy). BMRs were multiplied by the product of MET, H, and VQ. The data obtained for 

short term exposures are presented in Table 5-14. 

The major strengths of the Layton (1993) study are that it obtains similar results using 

three different approaches to estimate inhalation rates in different age groups and that the 

populations are large, consisting of men, women, and children. Explanations for 

differences in results due to metabolic measurements, reported diet, or activity patterns 

are supported by observations reported by other investigators in other studies. Major 

limitations of this study are that activity pattern levels estimated in this study are somewhat 

subjective, the explanation that activity pattern differences is responsible for the lower level 

obtained with the metabolic approach (25 percent) compared to the activity pattern 

approach is not well supported by the data, and different populations were used in each 

approach which may introduce error. 

5.2.3. Relevant Inhalation Rate Studies 

International Commission on Radiological Protection (ICRP) (1981) - Report of the 

Task Group on Reference Man - The International Commission of Radiological Protection 

(ICRP) estimated daily inhalation rates for reference adult males, adult females, children 

(10 years old), infant (1 year old), and newborn babies by using a time-activity-ventilation 

approach. This approach for estimating 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. ICRP (1981) compiled reference values (Appendix Table 

5A-5) of minute volume/inhalation rates from various literature sources. ICRP (1981) 

assumed that the daily activities of a reference man and woman, and child (10 yrs) 

consisted of 8 hours of rest and 16 hours of light activities. It was also assumed that 16 

hours were divided evenly between occupational and nonoccupational activities. It was 

assumed that a day consisted of 14 hours resting and 10 hours light activity for an infant 

(1 yr). A newborn's daily activities consisted of 23 hours resting and 1 hour light activity. 

Table 5-15 presents the daily inhalation rates obtained for all ages/genders. The 

3 3 estimated inhalation rates were 22.8 m /day for adult males, 21.1 m /day for adult females, 

3 3 14.8 m /day for children (age 10 years), 3.76 m /day for infants (age 1 year), and 0.78 

m /day for newborns. 

A limitation associated with this study is that the validity and accuracy of the 

inhalation rates data used in the compilation were not specified. This may introduce some 

degree of uncertainty in the results obtained. Also, the approach used involved assuming 

hours spent by various age/gender cohorts in specific activities. These assumptions may 

over/under-estimate the inhalation rates obtained. 

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U.S. EPA (1985) - Development of Statistical Distributions or Ranges of Standard 

Factors Used in Exposure Assessments - Due to a paucity of information in the literature 

regarding equations used to develop statistical distributions of minute 

ventilation/ventilation rate at all activity levels for male and female children and adults, the 

U.S. EPA (1985) compiled measured values of minute ventilation for various age/gender 

cohorts from early studies. In more recent investigations, minute ventilations have been 

measured more as background information than as research objective itself and the 

available studies have been for specific subpopulations such as obese, asthmatics, or 

marathon runners. The data compiled by the U.S. EPA (1985) for each age/gender 

cohorts were obtained at various activity levels. These levels were categorized as light, 

moderate, or heavy according to the criteria developed by the 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). The minute 

ventilation rates for adult males based on these activity level categories are detailed in 

Appendix Table 5A-6. 

Table 5-16 presents a summary of inhalation rates by age, gender, and activity level 

(detailed data are presented in Appendix Table 5A-7). A description of activities included 

in each activity level is also presented in Table 5-16. Table 5-16 indicates that at rest, the 

3 average adult inhalation rate is 0.5 m /hr. The mean inhalation rate for children at rest, 

3 ages 6 and 10 years, is 0.4 m /hr. Table 5-17 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 transportation vehicle was 1.77. Based 

on the data presented in Tables 5-16 and 5-17, a daily inhalation rate was calculated for

adults and children by using a time-activity-ventilation approach. These data are 

3 presented in Table 5-18. The calculated average daily inhalation rate is 16 m /day for 

3 adults. The average daily inhalation rate for children (6 and 10 yrs) is 18.9 m /day ([16.74 

+ 21.02]/2).

A limitation associated with this study is 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 subjects and the data are presented for both 

adults and children. 

Shamoo et al. (1990) - Improved Quantitation of Air Pollution Dose Rates by 

Improved Estimation of Ventilation Rate- Shamoo et al. (1990) conducted this study to 

develop and validate new methods to accurately estimate ventilation rates for typical 

individuals during their normal activities. Two practical approaches were tested for 

estimating ventilation rates indirectly: (1) volunteers were trained to estimate their own VR 

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Chapter 5 - Inhalation 

at various controlled levels of exercise; and (2) individual VR and HR relationships were 

determined in another set of volunteers during supervised exercise sessions (Shamoo et 

al., 1990). In the first approach, the training session involved 9 volunteers (3 females and 

6 males) from 21 to 37 years old. Initially the subjects were trained on a treadmill with 

regularly increasing speeds. VR measurements were recorded during the last minute of 

3 the 3-minute interval at each speed. VR was reported to the subjects as low (1.4 m /hr), 

3 3 3 medium (1.5-2.3 m /hr), heavy (2.4-3.8 m /hr), and very heavy (3.8 m /hr or higher) 

(Shamoo et al., 1990). 

Following the initial test, treadmill training sessions were conducted on a different day 

in which 7 different speeds were presented, each for 3 minutes in arbitrary order. VR was 

measured and the subjects were given feedback with the four ventilation ranges provided 

previously. After resting, a treadmill testing session was conducted in which seven speeds 

were presented in different arbitrary order from the training session. VR was measured 

and each subject estimated their own ventilation level at each speed. The correct level 

was then revealed to each subject after his/her own estimate. Subsequently, two 3-hour 

outdoor supervised exercise sessions were conducted in the summer on two consecutive 

days. Each hour consisted of 15 minutes each of rest, slow walking, jogging, and fast 

walking. The subjects' ventilation level and VR were recorded; however, no feedback was 

given to the subjects. Electrocardiograms were recorded via direct connection or telemetry 

and HR was measured concurrently with ventilation measurement for all treadmill 

sessions. 

The second approach consisted of two protocol phases (indoor/outdoor exercise 

sessions and field testing). Twenty outdoor adult workers between 19-50 years old were 

recruited. Indoor and outdoor supervised exercises similar to the protocols in the first 

approach were conducted; however, there were no feedbacks. Also, in this approach, 

electrocardiograms were recorded and HR was measured concurrently with VR. During 

the field testing phase, subjects were trained to record their activities during three different 

24-hour periods during one week. These periods included their most active working and 

non-working days. HR was measured quasi-continuously during the 24-hour periods that 

activities were recorded. The subjects recorded in a diary all changes in physical activity, 

location, and exercise levels during waking hours. Self-estimated activities in supervised 

exercises and field studies were categorized as slow (resting, slow walking or equivalent), 

medium (fast walking or equivalent), and fast (jogging or equivalent). 

Inhalation rates were not presented in this study. In the first approach, about 68 

percent of all self-estimates were correct for the 9 subjects sampled (Shamoo et al., 1990). 

Inaccurate self-estimates occurred in the younger male population who were highly 

physically fit and were competitive aerobic trainers. This subset of sample population 

tended to underestimate their own physical activity levels at higher VR ranges. Shamoo 

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Chapter 5 - Inhalation 

et al. (1990) attributed this to a "macho effect." In the second approach, a regression 

analysis was conducted that related the logarithm of VR to HR. The logarithm of VR 

correlated better with HR than VR itself (Shamoo et al., 1990). 

A limitation associated with this study is that the population sampled is not 

representative of the general U.S. population. Also, ventilation rates were not presented. 

Training individuals to estimate their VR may contribute to uncertainty in the results 

because the estimates are subjective. Another limitation is that calibration data were not 

obtained at extreme conditions; therefore, the VR/HR relationship obtained may be biased. 

An additional limitation is that training subjects may be too labor-intensive for widespread 

use in exposure assessment studies. An advantage of this study is that HR recordings are 

useful in predicting ventilation rates which in turn are useful in estimating exposure. 

Shamoo et al. (1991) - Activity Patterns in a Panel of Outdoor Workers Exposed to 

Oxidant Pollution - Shamoo et al. (1991) investigated summer activity patterns in 20 adult 

volunteers with potentially high exposure to ambient oxidant pollution. The selected 

volunteer subjects were 15 men and 5 women ages 19-50 years from the Los Angeles 

area. All volunteers worked outdoors at least 10 hours per week. The experimental 

approach involved two stages: (1) indirect objective estimation of VR from HR 

measurements; and (2) self estimation of inhalation/ventilation rates recorded by subjects 

in diaries during their normal activities. 

The approach consisted of calibrating the relationship between VR and HR for each 

test subject in controlled exercise; monitoring by subjects of their own normal activities with 

diaries and electronic HR recorders; and then relating VR with the activities described in 

the diaries (Shamoo et al., 1991). Calibration tests were conducted for indoor and outdoor 

supervised exercises to determine individual relationships between VR and HR. Indoors, 

each subject was tested on a treadmill at rest and at increasing speeds. HR and VR were 

measured at the third minute at each 3-minute interval speed. In addition, subjects were 

tested while walking a 90-meter course in a corridor at 3 self-selected speeds (normal, 

slower than normal, and faster than normal) for 3 minutes. 

Two outdoor testing sessions (one hour each) were conducted for each subject, 7 

days apart. Subjects exercised on a 260-meter asphalt course. A session involved 15 

minutes each of rest, slow walking, jogging, and fast walking during the first hour. The 

sequence was also repeated during the second hour. HR and VR measurements were 

recorded starting at the 8th minute of each 15-minute segment. Following the calibration 

tests, a field study was conducted in which subject's self-monitored their activities by filling 

out activity diary booklets, self-estimated their breathing rates, and their HR. Breathing 

rates were defined as sleep, slow (slow or normal walking); medium (fast walking); and fast 

(running) (Shamoo et al., 1991). Changes in location, activity, or breathing rates during 

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Chapter 5 - Inhalation 

three 24-hr periods within a week were recorded. These periods included their most active 

working and non-working days. Each subject wore Heart Watches which recorded their 

HR once per minute during the field study. Ventilation rates were estimated for the 

following categories: sleep, slow, medium, and fast. 

Calibration data were fit to the equation log (VR) = intercept + (slope x HR), each 

individual's intercept and slope were determined separately to provide a specific equation 

that predicts each subject's VR from measured HR (Shamoo et al., 1991). The average 

3 measured VRs were 0.48, 0.9, 1.68, and 4.02 m /hr for rest, slow walking or normal 

walking, fast walking and jogging, respectively (Shamoo et al., 1991). Collectively, the 

diary recordings showed that sleep occupied about 33 percent of the subject's time; slow 

activity 59 percent; medium activity 7 percent; and fast activity 1 percent. The diary data 

covered an average of 69 hours per subject (Shamoo et al., 1991). Table 5-19 presents 

the distribution pattern of predicted ventilation rates and equivalent ventilation rates (EVR) 

obtained at the four activity levels. EVR was defined as the VR per square meter of body 

surface area, and also as a percentage of the subjects average VR over the entire field 

3 monitoring period (Shamoo et al., 1991). The overall mean predicted VR was 0.42 m /hr 

3 3 3 for sleep; 0.71 m /hr for slow activity; 0.84 m /hr for medium activity; and 2.63 m /hr for fast 

activity. 

The mean predicted VR and standard deviation, and the percentage of time spent in 

each combination of VR, activity type (essential and non-essential), and location (indoor 

and outdoor) are presented in Table 5-20. Essential activities include income-related work, 

household chores, child care, study and other school activities, personal care and 

destination-oriented travel. Non-essential activities include sports and active leisure, 

passive leisure, some travel, and social or civic activities (Shamoo et al., 1991). Table 5­

20 shows that inhalation rates were higher outdoors than indoors at slow, medium, and 

fast activity levels. Also, inhalation rates were higher for outdoor non-essential activities 

than for indoor non-essential activity levels at slow, medium, and fast self-reported 

breathing rates (Table 5-20).

An advantage of this study is that subjective activity diary data can provide exposure 

modelers with useful rough estimates of VR for groups of generally healthy people. A 

limitation of this study is that the results obtained show high within-person and betweenperson variability in VR at each diary-recorded level, indicating that VR estimates from 

diary reports could potentially be substantially misleading in individual cases. Another 

limitation of this study is that elevated HR data of slow activity at the second hour of the 

exercise session reflect persistent effects of exercise and/or heat stress. Therefore, 

predictions of VR from the VR/HR relationship may be biased. 

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Chapter 5 - Inhalation 

Shamoo et al. (1992) - Effectiveness of Training Subjects to Estimate Their Level of 

Ventilation - Shamoo et al. (1992) conducted a study where nine non-sedentary subjects 

in good health were trained on a treadmill to estimate their own ventilation rates at four 

activity levels: low, medium, heavy, and very heavy. The purpose of the study was to train 

the subjects self-estimation of ventilation in the field and assess the effectiveness of the 

training (Shamoo et al., 1992). The subjects included 3 females and 6 males between 21 

to 37 years of age. The tests were conducted in four stages. First, an initial treadmill 

pretest was conducted indoors at various speeds until the four ventilation levels were 

experienced by each subject; VR was measured and feedback was given to the subjects. 

Second, two treadmill training sessions which involved seven 3-minute segments of 

varying speeds based on initial tests were conducted; VR was measured and feedback 

was given to the subjects. Another similar session was conducted; however, the subjects 

estimated their own ventilation level during the last 20 seconds of each segment and VR 

was measured during the last minute of each segment. Immediate feedback was given to 

the subject's estimate; and the third and fourth stages involved 2 outdoor sessions of 3 

hours each. Each hour comprised 15 minutes each of rest, slow walking, jogging, and fast 

walking. The subjects estimated their own ventilation level at the middle of each segment. 

The subject's estimate was verified by a respirometer which measured VR in the middle 

of each 15-minute activity. No feedback was given to the subject. The overall percent 

correct score obtained for all ventilation levels was 68 percent (Shamoo et al., 1992). 

Therefore, Shamoo et al. (1992) concluded that this training protocol was effective in 

training subjects to correctly estimate their minute ventilation levels. 

For this handbook, inhalation rates were analyzed from the raw data provided by 

Shamoo et al. (1992). Table 5-21 presents the mean inhalation rates obtained from this 

analysis at four ventilation levels in two microenvironments (i.e., indoors and outdoors) for 

3 all subjects. The mean inhalation rates for all subjects were 0.93, 1.92, 3.01, 4.80 m /hr 

for low, medium, heavy, and very heavy activities, respectively. 

The population sample size used in this study was small and was not selected to 

represent the general U.S. population. The training approach employed may not be cost 

effective because it was labor intensive; therefore, this approach may not be viable in field 

studies especially for field studies within large sample sizes. 

AIHC (1994) - The Exposure Factors Sourcebook - AIHC (1994) recommends an 

3 average adult inhalation rate of 18 m /day and presents values for children of various 

ages. These recommendations were derived from data presented in U.S. EPA (1989). 

The newer study by Layton (1993) was not considered. In addition, the Sourcebook 

presents probability distributions derived by Brorby and Finley (1993). For each 

distribution, the @Risk formula is provided for direct use in the @Risk simulation software 

(Palisade, 1992). The organization of this document makes it very convenient to use in 

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Chapter 5 - Inhalation 

support of Monte Carlo analysis. The reviews of the supporting studies are very brief with 

little analysis of their strengths and weaknesses. The Sourcebook has been classified as 

a relevant rather than key study because it is not the primary source for the data used to 

make recommendations in this document. The Sourcebook is very similar to this document 

in the sense that it summarizes exposure factor data and recommends values. As such, 

it is clearly relevant as an alternative information source on inhalation rates as well as 

other exposure factors. 

5.2.4. Recommendations 

In the Ozone Criteria Document prepared by the U.S. EPA Office of Environmental 

Criteria and Assessment, the EPA identified the collapsed range of activities and its 

3 corresponding VR as follows: light exercise (V < 23 L/min or 1.4 m /hr); moderate/ E 

3 medium exercise (V = 24-43 L/min or 1.4-2.6 m /hr); heavy exercise (V = 43-63 L/min or E E 

3 3 2.6-3.8 m /hr); and very heavy exercise (V > 64 L/min or 3.8 m /hr), (Adams, 1993). E 

Recent peer reviewed scientific papers and an EPA report comprise the studies that 

were evaluated in this Chapter. These studies were conducted in the United States among 

both men and women of different age groups. All are widely available. The confidence 

ratings in the inhalation rate recommendations are shown in Table 5-22. 

Each study focused on ventilation rates and factors that may affect them. Studies 

were conducted among randomly selected volunteers. Efforts were made to include men, 

women, different age groups, and different kinds of activities. Measurement methods are 

indirect, but reproducible. Methods are well described (except for questionnaires) and 

experimental error is well documented. There is general agreement with these estimates 

among researchers. 

The recommended inhalation rates for adults, children, and outdoor workers/athletes 

are based on the key studies described in this chapter (Table 5-23). Different survey 

designs and populations were utilized in the studies described in this Chapter. A summary 

of these designs, data generated, and their limitations/advantages are presented in Table 

5-24. Excluding the study by Layton (1993), the population surveyed in all of the key 

studies described in this report were limited to the Los Angeles area. This regional 

population may not represent the general U.S. population and may result in biases. 

However, based on other aspects of the study design, these studies were selected as the 

basis for recommended inhalation rates. 

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 values for adults, children (including 

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Chapter 5 - Inhalation 

infants), and outdoor workers/athletes for use in various exposure scenarios are discussed 

below. These rates were calculated by averaging the inhalation rates for each activity 

level from the various key studies (see Table 5-25). 

Adults (19-65+ yrs) - Adults in this recommendation include young to middle age 

adults (19-64 yrs), and older adults (65+ yrs). The daily average inhalation rates for long 

3 3 term exposure for adults are: 11.3 m /day for women and 15.2 m /day for men. These 

values are averages of the inhalation rates provided for males and females in each of the 

three approaches of Layton (1993) (Tables 5-11 through 5-14). An upper percentile is not 

recommended. Additional research and analysis of activity pattern data and dietary data 

in the future is necessary to attempt to calculate upper percentiles. 

The recommended value for the general population average inhalation rate, 11.3 

3 3 3 m /day for women and 15.2 m /day for men, is different than the 20 m /day which has 

commonly been assumed in past EPA risk assessments. 

In addition, recommendations are presented for various ages and special populations 

3 (athletes, outdoor workers) which also differ from 20 m /day. Assessors are encouraged 

to use values which most accurately reflect the exposed population. 

For exposure scenarios where the distribution of activity patterns is known, the 

following results, calculated from the studies referenced are shown in Table 5-25. Based 

on these key studies, the following recommendations are made: for short term exposures 

in which distribution of activity patterns are specified, the recommended average rates are 

3 3 0.4 3

/hr during rest; 0.5 m /hr for sedentary activities; 1.0 m /hr for light activities; 1.6 

3 3 m /hr for moderate activities; and 3.2 m /hr for heavy activities. 

Children (18 yrs old or less including infants) - For the purpose of this 

recommendation, children are defined as males and females between the ages of 1-18 

years old, while infants are individuals less than 1 year old. The inhalation rates for 

children are presented below according to different exposure scenarios. The daily 

inhalation rates for long-term dose assessments, are based on the first approach of Layton 

(1993) (Table 5-11) and are summarized in Table 5-26. 

Based on the key study results (i.e., Layton, 1993), the recommended daily inhalation 

3 rate for infants (children less than 1 yr), during long-term dose assessments is 4.5 m /day. 

 For children 1-2 years old, 3-5 years old, and 6-8 years old, the recommended daily 

3 3 3 inhalation rates are 6.8 m /day, 8.3 m /day, and 10 m /day, respectively. Recommended 

3 3 values for children aged 9-11 years are 14 m /day for males and 13 m /day for females. 

For children aged 12-14 years and 15-18 years, the recommended values are shown in 

Table 5-23. 

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Chapter 5 - Inhalation 

For short-term exposures for children aged 18 years and under, in which activity 

patterns are known, the data are summarized in Table 5-27. For short term exposures, the 

recommended average hourly inhalation rates are based on these key studies. They are 

3 3 averaged over each activity held as follows: 0.3 m /hr during rest; 0.4 m /hr for sedentary 

3 3 3 activities; 1.0 m /hr for light activities; 1.2 m /hr for moderate activities; and 1.9 m /hr for 

heavy activities. The recommended short-term exposure data also include infants (less 

than 1 yr). These values represent averages of the activity level data from key studies 

(Table 5-27). 

Outdoor Worker - Inhalation rate data for outdoor workers/athlete are limited. 

However, based on the key studies (Linn et al., 1992 and 1993), the recommended 

3 average hourly inhalation rate for outdoor workers is 1.3 m /hr and the upper-percentile 

3 rate is 3.3 m /hr (see Tables 5-5 and 5-8). This is calculated as the weighted mean of the 

99th percentile values reported for the individuals on Panels 1 and 7 in Tables 5-5 and the 

19 subjects in Table 5-8. The recommended average inhalation rates for outdoor workers 

based on the activity levels categorized as slow (light activities), medium (moderate 

3 3 3 activities), and fast (heavy activities) are 1.1 m /hr, 1.5 m /hr, and 2.5 m /hr, respectively. 

These values are based on the data from Linn et al. (1992 and 1993) and are the weighted 

mean of the values for the individuals on Panels 1 and 7 in Table 5-5 and the 19 outdoor 

workers in Table 5-9. Inhalation rates may be higher among outdoor workers/athletes 

because levels of activity outdoors may be higher. Therefore, this subpopulation group 

may be more susceptible to air pollutants and are considered a "high-risk" subgroup 

(Shamoo et al., 1991; Linn et al., 1992).

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Chapter 6 - Dermal 

6. DERMAL ROUTE 

Dermal exposure can occur during a variety of activities in different environmental 

media and microenvironments (U.S. EPA, 1992). These include: 

• Water (e.g., bathing, washing, swimming); 

• Soil (e.g., outdoor recreation, gardening, construction); 

• Sediment (e.g., wading, fishing); 

• Liquids (e.g., use of commercial products); 

• Vapors/fumes (e.g., use of commercial products); and 

• Indoors (e.g., carpets, floors, countertops). 

The major factors that must be considered when estimating dermal exposure are: the 

chemical concentration in contact with the skin, the potential dose, the extent of skin 

surface area exposed, the duration of exposure, the absorption of the chemical through 

the skin, the internal dose, and the amount of chemical that can be delivered to a target 

organ (i.e., biologically effective dose) (see Figure 6-1). A detailed discussion of these 

factors can be found in Guidelines for Exposure Assessment (U.S. EPA, 1992a). 

This chapter focuses on measurements of body surface areas and various factors 

needed to estimate dermal exposure to chemicals in water and soil. Information 

concerning dermal exposure to pollutants in indoor environments is limited. Useful 

information concerning estimates of body surface area can be found in “Development of 

Statistical Distributions or Ranges of Standard Factors Used in Exposure Assessments” 

(U.S. EPA, 1985). “Dermal Exposure Assessment: Principles and Applications (U.S. EPA, 

1992b), provides detailed information concerning dermal exposure using a stepwise guide 

in the exposure assessment process. 

The available studies have been classified as either key or relevant based on their 

applicability to exposure assessment needs and are summarized in this chapter. 

Recommended values are based on the results of the key studies. Relevant studies are 

presented to provide an added perspective on the state-of-knowledge pertaining to dermal 

exposure factors. All tables and figures presenting data from these studies are shown at 

the end of this chapter. 

6.1. EQUATION FOR DERMAL DOSE 

The average daily dose (ADD) is the 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. For 

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Chapter 6 - Dermal 

compounds with carcinogenic or chronic effects, the lifetime average daily dose (LADD) 

is used. The LADD is the dose rate averaged over a lifetime. 

For dermal contact with chemicals in soil or water, dermally absorbed average daily 

dose can be estimated by (U.S. EPA, 1992b): 

DA x EV x ED x EF x SA event ADD ' (Eqn. 6-1) BW x AT 

where: 

ADD = average daily dose (mg/kg-day); 2 DAevent = absorbed dose per event (mg/cm -event);

EV = event frequency (events/day);

ED = exposure duration (years);

EF = exposure frequency (days/year); 2 SA = skin surface area available for contact (cm );

BW = body weight (kg); and

AT = averaging time (days) for noncarcinogenic effects, AT = ED and for carcinogenic effects, AT = 70 years or 25,550 days.

This method is to be used to calculate the absorbed dose of a chemical. Total body 

surface area (SA) is assumed to be exposed for a period of time (ED). 

For dermal contact with water, the DA is estimated with consideration for the event 

permeability coefficient from water, the chemical concentration in water, and the event 

duration. The approach to estimate DA is different for inorganic and organic event 

compounds. The nonsteady-state approach to estimate the dermally absorbed dose from 

water is recommended as the preferred approach for organics which exhibit octanol-water 

partitioning (U.S. EPA, 1992b). First, this approach more accurately reflects normal 

human exposure conditions since the short contact times associated with bathing and 

swimming generally mean that steady state will not occur. Second, the approach accounts 

for uptake that can occur after the actual exposure event due to absorption of residual 

chemical trapped in skin tissue. Use of the nonsteady-state model for organics has 

implications for selecting permeability coefficient (K ) values (U.S. EPA, 1992b). It is p 

(DA 

recommended that the traditional steady-state approach be applied to inorganics (U.S. 

EPA, 1992b). Detailed information concerning how to estimate absorbed dose per event 

event) and K values can be found in Section 5.3.1 of “Dermal Exposure Assessment: p 

Principles and Applications” (U.S. EPA, 1992b). 

For dermal contact with contaminated soil, estimation of the DAevent is different from 

the estimation for dermal contact with chemicals in water. It is based on the concentration 

of the chemical in soil, the adherence factor of soil to skin, and the absorption fraction. 

Information for DAevent estimation from soil contact can be found in U.S. EPA (1992b), 

Section 6.4. 

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Chapter 6 - Dermal 

The apparent simplicity of the absorption fraction (percent absorbed) makes this 

approach appealing. However, it is not practical to apply it to water contact scenarios, 

such as swimming, because of the difficulty in estimating the total material contacted (U.S. 

EPA, 1992b). It is assumed that there is essentially an infinite amount of material 

available, and that the chemical will be replaced continuously, thereby increasing the 

amount of material (containing the chemical) available by some large unknown amount. 

Therefore, the permeability coefficient-based approach is recommended over the 

absorption fraction approach for determining the dermally absorbed dose of chemicals in 

aqueous media. 

Before the absorption fraction approach can be used in soil contact scenarios, the 

contaminant concentration in soil must be established. Not all of the chemical in a layer 

of dirt applied to skin may be bioavailable, nor is it assumed to be an internal dose. 

Because of the lack of K data for compounds bound to soil, and reduced uncertainty in p 

defining an applied dose, the absorption fraction-based approach is suggested for 

determining the internal dose of chemicals in soil. More detailed explanation of the 

equations, assumptions, and approaches can be found in “Dermal Exposure Assessment: 

Principles and Applications” (U.S. EPA. 1992b). 

6.2. SURFACE AREA 

6.2.1. Background 

The total surface area of skin exposed to a contaminant must be determined using 

measurement or estimation techniques before conducting a dermal exposure assessment. 

Depending on the exposure scenario, estimation of the surface area for the total body or 

a specific body part can be used to calculate the contact rate for the pollutant. This 

section presents estimates for total body surface area and for body parts and presents 

information on the application of body surface area data. 

6.2.2. Measurement 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. Consideration has been given for differences due to age, gender, and race. 

The results of the various techniques have been summarized in “Development of Statistical 

Distributions or Ranges of Standard Factors Used in Exposure Assessments” (U.S. EPA, 

1985). The coating method consists of coating either the whole body or specific body 

regions with a substance of known or measured area. Triangulation consists of marking 

the area of the body into geometric figures, then calculating the figure areas from their 

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Chapter 6 - Dermal 

linear dimensions. Surface integration is performed by using a planimeter and adding the 

areas. 

The triangulation measurement technique developed by Boyd (1935) has been found 

to be highly reliable. It estimates the surface area of the body using geometric 

approximations that assume parts of the body resemble geometric solids (Boyd, 1935). 

More recently, Popendorf and Leffingwell (1976), and Haycock et al. (1978) have 

developed similar geometric methods that assume body parts correspond to geometric 

solids, such as the sphere and cylinder. A linear method proposed by DuBois and DuBois 

(1916) is based on the principle that the surface areas of the parts of the body are 

proportional, rather than equal to the surface area of the solids they resemble. 

In addition to direct measurement techniques, several formulae have been proposed 

to estimate body surface area from measurements of other major body dimensions (i.e., 

height and weight) (U.S. EPA, 1985). Generally, the formulae are based on the principles 

that body density and shape are roughly the same and that the relationship of surface area 

to any dimension may be represented by the curve of central tendency of their plotted 

values or by the algebraic expression for the curve. A discussion and comparison of 

formulae to determine total body surface area are presented in Appendix 6A. 

6.2.3. Key Body Surface Area Studies 

U.S. EPA (1985) - Development of Statistical Distributions or Ranges of Standard 

Factors Used in Exposure Assessments - U.S. EPA (1985) analyzed the direct surface 

area measurement data of Gehan and George (1970) using the Statistical Processing 

System (SPS) software package of Buhyoff et al. (1982). Gehan and George (1970) 

selected 401 measurements made by Boyd (1935) that were complete for surface area, 

height, weight, and age for their analysis. Boyd (1935) had reported surface area 

estimates for 1,114 individuals using coating, triangulation, or surface integration methods 

(U.S. EPA, 1985). 

U.S. EPA (1985) used SPS to generate equations to calculate surface area as a 

function of height and weight. These equations were then used to calculate body surface 

area distributions of the U.S. population using the height and weight data obtained from 

the National Health and Nutrition Examination Survey (NHANES) II and the computer 

program QNTLS of Rochon and Kalsbeek (1983). 

The equation proposed by Gehan and George (1970) was determined by U.S. EPA 

(1985) to be the best choice for estimating total body surface area. However, the paper 

by Gehan and George (1970) gave insufficient information to estimate the standard error 

about the regression. Therefore, U.S. EPA (1985) used the 401 direct measurements of 

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children and adults and reanalyzed the data using the formula of Dubois and Dubois 

(1916) and SPS to obtain the standard error (U.S. EPA, 1985).

Regression equations were developed for specific body parts using the Dubois and 

Dubois (1916) formula and using the surface area of various body parts provided by Boyd 

(1935) and Van Graan (1969) in conjunction with SPS. Regression equations for adults 

were developed for the head, trunk (including the neck), upper extremities (arms and 

hands, upper arms, and forearms) and lower extremities (legs and feet, thighs, and lower 

legs) (U.S. EPA, 1985). Table 6-1 presents a summary of the equation parameters 

developed by U.S. EPA (1985) for calculating surface area of adult body parts. Equations 

to estimate the body part surface area of children were not developed because of 

insufficient data. 

Percentile estimates of total surface area and surface area of body parts developed 

by U.S. EPA (1985) using the regression equations and NHANES II height and weight data 

are presented in Tables 6-2 and 6-3 for adult males and adult females, respectively. The 

calculated mean surface areas of body parts for men and women are presented in Table 6­

4. The standard deviation, the minimum value, and the maximum value for each body part 

are included. The median total body surface area for men and women and the 

corresponding standard errors about the regressions are also given. It has been assumed 

that errors associated with height and weight are negligible (U.S. EPA, 1985). The data 

in Table 6-5 present the percentage of total body surface by body part for men and 

women. 

Percentile estimates for total surface area of male and female children presented in 

Tables 6-6 and 6-7 were calculated using the total surface area regression equation, 

NHANES II height and weight data, and using QNTLS. Estimates are not included for 

children younger than 2 years old because NHANES height data are not available for this 

age group. For children, the error associated with height and weight cannot be assumed 

to be zero because of their relatively small sizes. Therefore, the standard errors of the 

percentile estimates cannot be estimated, since it cannot be assumed that the errors 

associated with the exogenous variables (height and weight) are independent of that 

associated with the model; there are insufficient data to determine the relationship 

between these errors. 

Measurements of the surface area of children's body parts are summarized as a 

percentage of total surface area in Table 6-8. Because of the small sample size, the data 

cannot be assumed to represent the average percentage of surface area by body part for 

all children. Note that the percent of total body surface area contributed by the head 

decreases from childhood to adult, while the percent contributed by the leg increases. 

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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 

LADD equation. Phillips et al. (1993) concluded 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 is more appropriate than treating these factors as independent 

variables. Direct measurement (coating, triangulation, and surface integration) data from 

the scientific literature were used to calculate body surface area to body weight (SA/BW) 

ratios for three age groups (infants aged 0 to 2 years, children aged 2.1 to 17.9 years, and 

adults 18 years and older). These ratios were calculated by dividing body surface areas 

by corresponding body weights for the 401 individuals analyzed by Gehan and George 

(1970) and summarized by U.S. EPA (1985). Distributions of SA/BW ratios were 

developed and summary statistics were calculated for each of the three age groups and 

the combined data set. Summary statistics for these populations are presented in Table 

6-9. The shapes of these SA/BW distributions were determined using D'Agostino's test. 

The results indicate that the SA/BW ratios for infants are lognormally distributed and the 

SA/BW ratios for adults and all ages combined are normally distributed (Figure 6-2). 

SA/BW ratios for children were neither normally nor lognormally distributed. According to 

Phillips et al. (1993), SA/BW ratios should 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. 

6.2.4. Relevant Surface Area Studies 

Murray and Burmaster (1992) - Estimated Distributions for Total Body Surface Area 

of Men and Women in the United States - In this study, distributions of total body surface 

area for men and women ages 18 to 74 years were estimated using Monte Carlo 

simulations based on height and weight distribution data. Four different formulae for 

estimating body surface area as a function of height and weight were employed: Dubois 

and Dubois (1916); Boyd (1935); U.S. EPA (1985); and Costeff (1966). The formulae of 

Dubois and Dubois (1916); Boyd (1935); and U.S. EPA (1985) are based on height and 

weight. They are discussed in Appendix 6A. The formula developed by Costeff (1966) is 

based on 220 observations that estimate body surface area based on weight only. 

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This formula is: 

SA= 4W+7/W+90 (Eqn. 6-2) 

where: 2 SA = Surface Area (m ); and

W = Weight (kg).

Formulae were compared and the effect of the correlation between height and weight on 

the body surface area distribution was analyzed. 

Monte Carlo simulations were conducted to estimate body surface area distributions. 

They were based on the bivariate distributions estimated by Brainard and Burmaster 

(1992) for height and natural logarithm of weight and the formulae described above. A 

total of 5,000 random samples each for men and women were selected from the two 

correlated bivariate distributions. Body surface area calculations were made for each 

sample, and for each formula, resulting in body surface area distributions. Murray and 

Burmaster (1992), found that the body surface area frequency distributions were similar 

for the four models (Table 6-10). Using the U.S. EPA (1985) formula, the median surface 

2 2 area values were calculated to be 1.96 m for men and 1.69 m for women. The median 

value for women is identical to that generated by U.S. EPA (1985) but differs for men by 

approximately 1 percent. Body surface area was found to have lognormal distributions for 

both men and women (Figure 6-3). It was also found that assuming correlation between 

height and weight influences the final distribution by less than 1 percent. 

AIHC (1994) - Exposure Factors Sourcebook - The Exposure Factors Sourcebook 

(AIHC, 1994) provides similar body surface area data as presented here. Consistent with 

this document, average and percentile values are presented on the basis of age and 

gender. In addition, the Sourcebook presents point estimates of exposed skin surface 

areas for various scenarios on the basis of several published studies. Finally, the 

Sourcebook presents probability distributions based on U.S. EPA (1989) and as derived 

by Thompson and Burmaster (1991); Versar (1991); and Brorby and Finley (1993). For 

each distribution, the @Risk formula is provided for direct use in the @Risk simulation 

software (Palisade, 1992). The organization of this document, makes it very convenient 

to use in support of Monte Carlo analysis. The reviews of the supporting studies are very 

brief with little analysis of their strengths and weaknesses. The Sourcebook has been 

classified as a relevant rather than key study because it is not the primary source for the 

data used to make recommendations in this document. The Sourcebook is very similar to 

this document in the sense that it summarizes exposure factor data and recommends 

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values. As such, it is clearly relevant as an alternative information source on body surface 

area as well as other exposure factors. 

6.2.5. Application of Body Surface Area Data 

In many settings, it is likely that only certain parts of the body are exposed. All body 

parts that come in contact with a chemical must be considered to estimate the total surface 

area of the body exposed. The data in Table 6-4 may be used to estimate the total surface 

area of the particular body part(s). For example, to assess exposure to a chemical in a 

cleaning product for which only the hands are exposed, surface area values for hands from 

Table 6-4 can be used. For exposure to both hands and arms, mean surface areas for 

these parts from Table 6-4 may be summed to estimate the total surface area exposed. 

The mean surface area of these body parts for men and women is as follows: 

Surface Area (m ) 2

 Men Women 

Arms (includes upper arms and forearms) 0.228 0.210 

Hands 0.084 0.075 

Total area 0.312 0.285 

Therefore, the total body part surface area that may be in contact with the chemical in the 

2 2 cleaning product in this example is 0.312 m for men and 0.285 m for women. 

A common assumption is that clothing prevents dermal contact and subsequent 

absorption of contaminants. This assumption may be false in cases where the chemical 

may be able to penetrate clothing, such as in a fine dust or liquid suspension. Studies 

using personal patch monitors placed beneath clothing of pesticide workers exposed to 

fine mists and vapors show that a significant proportion of dermal exposure may occur at 

anatomical sites covered by clothing (U.S. EPA, 1992b). In addition, it has been 

demonstrated that a "pumping" effect can occur which causes material to move under 

loose clothing (U.S. EPA, 1992b). Furthermore, studies have demonstrated that hands 

cannot be considered to be protected from exposure even if waterproof gloves are worn 

(U.S. EPA, 1992b). This may be due to contamination to the interior surface of the gloves 

when donning or removing them during work activities (U.S. EPA, 1992b). Depending on 

the task, pesticide workers have been shown to experience 12 percent to 43 percent of 

their total exposure through their hands, approximately 20 percent to 23 percent through 

their heads and necks, and 36 percent to 64 percent through their torsos and arms, 

despite the use of protective gloves and clothing (U.S. EPA, 1992b). 

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For swimming and bathing scenarios, past exposure assessments have assumed that 

75 percent to 100 percent of the skin surface is exposed (U.S. EPA, 1992b). As shown in 

2 2 Table 6-4, total adult body surface areas can vary from about 17,000 cm to 23,000 cm . 2 The mean is reported as approximately 20,000 cm . 

2 For default purposes, adult body surface areas of 20,000 cm (central estimate) to 

2 23,000 cm (upper percentile) are recommended in U.S. EPA (1992b). Tables 6-2 and 6-3 

can also be used when the default values are not preferred. Central and upper-percentile 

values for children should be derived from Table 6-6 or 6-7. 

Unlike exposure to liquids, clothing may or may not be effective in limiting the extent 

of exposure to soil. The 1989 Exposure Factors Handbook presented two adult clothing 

scenarios for outdoor activities (U.S. EPA, 1989): 

Central tendency mid range: Individual wears long sleeve shirt, pants, and shoes. 

2 The exposed skin surface is limited to the head and hands (2,000 cm ).

Upper percentile: Individual wears a short sleeve shirt, shorts, and shoes. The

exposed skin surface is limited to the head, hands, forearms, and lower legs (5,300

2 cm ). 

The clothing scenarios presented above, suggest that roughly 10 percent to 25 percent 

of the skin area may be exposed to soil. Since some studies have suggested that 

exposure can occur under clothing, the upper end of this range was selected in Dermal 

Exposure Assessment: Principles and Applications (U.S. EPA, 1992b) for deriving 

defaults. Thus, taking 25 percent of the total body surface area results in defaults for 

2 2 adults of 5,000 cm to 5,800 cm . These values were obtained from the body surface 

2 2 areas in Table 6-2 after rounding to 20,000 cm and 23,000 cm , respectively. The range 

of defaults for children can be derived by multiplying the 50th and 95th percentiles by 0.25 

for the ages of interest. 

When addressing soil contact exposures, assessors may want to refine estimates of 

surface area exposed on the basis of seasonal conditions. For example, in moderate 

climates, it may be reasonable to assume that 5 percent of the skin is exposed during the 

winter, 10 percent during the spring and fall, and 25 percent during the summer. 

The previous discussion, has presented information about the area of skin exposed 

to soil. These estimates of exposed skin area should be useful to assessors using the 

traditional approach of multiplying the soil adherence factor by exposed skin area to 

estimate the total amount of soil on skin. The next section presents soil adherence data 

specific to activity and body part and is designed to be combined with the total surface 

area of that body part. No reduction of body part area is made for clothing coverage using 

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this approach. Thus, assessors who adopt this approach, should not use the defaults 

presented above for soil exposed skin area. Rather, they should use Table 6-4 to obtain 

total surface areas of specific body parts. See detailed discussion below. 

6.3. SOIL ADHERENCE TO SKIN 

6.3.1. Background 

Soil adherence to the surface of the skin is a required parameter to calculate dermal 

dose when the exposure scenario involves dermal contact with a chemical in soil. A 

number of studies have attempted to determine the magnitude of dermal soil adherence. 

These studies are described in detail in U.S. EPA (1992b). This section summarizes 

recent studies that estimate soil adherence to skin for use as exposure factors. 

6.3.2. Key Soil Adherence to Skin Studies 

Kissel et al. (1996a) - Factors Affecting Soil Adherence to Skin in Hand-Press Trials: 

Investigation of Soil Contact and Skin Coverage - Kissel et al. (1996a) conducted soil 

adherence experiments using five soil types (descriptor) obtained locally in the Seattle, 

Washington, area: sand (211), loamy sand (CP), loamy sand (85), sandy loam (228), and 

silt loam (72). All soils were analyzed by hydrometer (settling velocity) to determine 

composition. Clay contents 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 Fm. 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 difference in 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 could be directly 

correlated with moisture content, inversely correlated with particle size, and independent 

of clay content or organic carbon content. 

Kissel et al. (1996b) - Field Measurement of Dermal Soil Loading Attributable to 

Various Activities: Implications for Exposure Assessment - Further experiments were 

conducted by Kissel et al. (1996b) to estimate soil adherence associated with various 

indoor and outdoor activities: greenhouse gardening, tae kwon do karate, soccer, rugby, 

reed gathering, irrigation installation, truck farming, and playing in mud. A summary of 

field studies by activity, gender, age, field conditions, and clothing worn is presented in 

Table 6-11. Subjects’ body surfaces (forearms, hands, lower legs in all cases, faces, 

and/or feet; pairs in some cases) were washed before and after monitored activities. 

Paired samples were pooled into single ones. Mass recovered was converted to loading 

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using allometric models of surface area. These data are presented in Table 6-12. Results 

presented are based on direct measurement of soil loading on the surfaces of skin before 

and after occupational and recreational activities that may be expected to have soil contact 

(Kissel et al., 1996b). 

6.3.3. Relevant Soil Adherence to Skin Studies 

Lepow et al. (1975) - Investigations into Sources of Lead in the Environment of Urban 

Children - This study was conducted to identify the behavioral and environmental factors 

contributing to elevated lead levels in ten preschool children. The study was performed 

over 6 to 25 months. Samples of dirt from the hands of subjects were collected during the 

course of play around the areas where they lived. Preweighed self-adhesive labels were 

used to sample a standard area on the palm of the hands of 16 male and female children. 

The labels were pressed on a single area, often pressed several times, to obtain an 

adequate sample. In the laboratory, labels were equilibrated in a desiccant cabinet for 24 

hours (comparable to the preweighed desiccation), then the total weight was recorded. The 

mean weight of dirt from the 22 hand sample labels was 11 mg. This corresponds to 0.51 

2 mg/cm . Lepow et al. (1975) reported that this amount (11 mg) represented only a small 

fraction (percent not specified) of the total amount of surface dirt present on the hands, 

because much of the dirt may be trapped in skin folds and creases or there may be a 

patchy distribution of dirt on hands. 

Roels et al. (1980) - Exposure to Lead by the Oral and the Pulmonary Routes of 

Children Living in the Vicinity of a Primary Lead Smelter - Roels et al. (1980) examined 

blood lead levels among 661 children, 9 to 14 years old, who lived in the vicinity of a large 

lead smelter in Brussels, Belgium. During five different study periods, lead levels were 

assessed by rinsing the childrens’ hands in 500 mL dilute nitric acid. The amount of lead 

on the hands was divided by the concentration of lead in soil to estimate the amount of soil 

adhering to the hands. The mean soil amount adhering to the hands was 0.159 grams. 

Que Hee et al. (1985) - Evolution of Efficient Methods to Sample Lead Sources, Such 

as House Dust and Hand Dust, in the Homes of Children - Que Hee et al. (1985) used soil 

having particle sizes ranging from # 44 to 833 μm diameters, fractionated into six size 

ranges, to estimate the amount that adhered to the palm of the hand that are assumed to 

2 be approximately 160 cm (test subject with an average total body surface area of 16,000 

2 2 cm and a total hand surface area of 400 cm ). The amount of soil that adhered to skin 

was determined by applying approximately 5 g of soil for each size fraction, removing 

excess soil by shaking the hands, and then measuring the difference in weight before and 

after application. Several assumptions were made to apply these results to other soil 

types and exposure scenarios: (a) the soil is composed of particles of the indicated 

diameters; (b) all soil types and particle sizes adhere to the skin to the degree observed 

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in this study; and an equivalent weight of particles of any diameter adhere to the same 

surface area of skin. On average, 31.2 mg of soil adhered to the palm of the hand. 

Driver et al. (1989) - Soil Adherence to Human Skin - Driver et al. (1989) conducted 

soil adherence experiments using various soil types collected from sites in Virginia. A total 

of five soil types were collected: Hyde, Chapanoke, Panorama, Jackland, and Montalto. 

Both top soils and subsoils were collected for each soil type. The soils were also 

characterized by cation exchange capacity, organic content, clay mineralogy, and particle 

size distribution. The soils were dry sieved to obtain particle sizes of #250 μm and 

#150 μm. For each soil type, the amount of soil adhering to adult male hands, using both 

sieved and unsieved soils, was determined gravimetrically (i.e., measuring the difference 

in soil sample weight before and after soil application to the hands). 

An attempt was made to measure only the minimal or "monolayer" of soil adhering to 

the hands. This was done by mixing a pre-weighed amount of soil over the entire surface 

area of the hands for a period of approximately 30 seconds, followed by removal of excess 

soil by gently rubbing the hands together after contact with the soil. Excess soil that was 

removed from the hands was collected, weighed, and compared to the original soil sample 

2 weight. The authors measured average adherence of 1.40 mg/cm for particle sizes less 

than 150 μm, 0.95 mg/cm2 for particle sizes less than 250 μm, and 0.58 mg/cm2 for 

unsieved soils. Analysis of variance statistics showed that the most important factor 

affecting adherence variability was particle size (p < 0.001). The next most important 

factor is soil type and subtype (p < 0.001). The interaction of soil type and particle size 

was also significant, but at a lower significance level (p < 0.01). 

Driver et al. (1989) found statistically significant increases in soil adherence with 

decreasing particle size; whereas, Que Hee et al. (1985) found relatively small changes 

with changes in particle size. The amount of soil adherence found by Driver et al. (1989) 

was greater than that reported by Que Hee et al. (1985). 

Sedman (1989) - The Development of Applied Action Levels for Soil Contact: A 

Scenario for the Exposure of Humans to Soil in a Residential Setting - Sedman (1989) 

used the estimate from Roels et al. (1980), 0.159 g, and the average surface area of the 

2 hand of an 11 year old, 307 cm to estimate the amount of soil adhering per unit area of 

2 2 skin to be 0.9 mg/cm . This assumed that approximately 60 percent (185 cm ) of the lead 

on the hands was recovered by the method employed by Roels et al. (1980). 

Sedman (1989) used estimates from Lepow et al. (1975), Roels et al. (1980), and 

Que Hee et al. (1985) to develop a maximum soil load that could occur on the skin. A 

rounded arithmetic mean of 0.5 mg/cm2 was calculated from these three studies. 

According to Sedman (1989), this was near the maximum load of soil that could occur on 

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the skin but it is unlikely that most skin surfaces would be covered with this amount of soil 

(Sedman, 1989). 

Yang et al. (1989) - In vitro and In vivo Percutaneous Absorption of Benzo[a]pyrene 

from Petroleum Crude - Fortified Soil in the Rat - Yang et al. (1989) evaluated the 

percutaneous absorption of benzo[a]pyrene (BAP) in petroleum crude oil sorbed on soil 

using a modified in vitro technique. This method was used in preliminary experiments to 

determine the minimum amount of soil adhering to the skin of rats. Based on these results, 

percutaneous absorption experiments with the crude-sorbed soil were conducted with soil 

particles of <150 Fm only. This particle size was intended to represent the composition 

2 of the soil adhering to the skin surface. Approximately 9 mg/cm of soil was found to be 

the minimum amount required for a "monolayer" coverage of the skin surface in both in 

vitro and in vivo experiments. This value is larger than reports for human skin in the 

studies of Kissel et al., 1996a,b; Lepow et al., 1975; Roels et al., 1980; and Que Hee et 

al., 1985. Differences between the rat and human soil adhesion findings may be the result 

of differences in rat and human skin texture, the types of soils used, soil moisture content 

or possibly the methods of measuring soil adhesion (Yang et al., 1989). 

6.4. RECOMMENDATIONS 

6.4.1. Body Surface Area 

Body surface area estimates are based on direct measurements. Re-analysis of data 

collected by Boyd (1935) by several investigators (Gehan and George, 1970; U.S. EPA, 

1985; Murray and Burmaster, 1992; Phillips et al., 1993) constitutes much of this literature. 

Methods are highly reproducible and the results are widely accepted. The 

representativeness of these data to the general population is somewhat limited since 

variability due to race or gender have not been systematically addressed. 

Individual body surface area studies are summarized in Table 6-13 and the 

recommendations for body surface area are summarized in Table 6-14. Table 6-15 

presents the confidence ratings for various aspects of the recommendations for body 

surface area. The U.S. EPA (1985) study is based on generally accepted measurements 

that enjoy widespread usage, summarizes and compares previous reports in the literature, 

provides statistical distributions for adults, and provides data for total body surface area 

and body parts by gender for adults and children. However, the results are based on 401 

selected measurements from the original 1,114 made by Boyd (1935). More than half of 

the measurements are from children. Therefore, these estimates may be subject to 

selection bias and may not be representative of the general population nor specific ethnic 

groups. Phillips et al. (1993) analyses are based on direct measurement data that provide 

distributions of body surface area to calculate LADD. The results are consistent with 

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previous efforts to estimate body surface area. Analyses are based on 401 measurements 

selected from the original 1,114 measurements made by Boyd (1935) and data were not 

analyzed for specific body parts. The study by Murray and Burmaster (1992) provides 

frequency distributions for body surface area for men and women and produces results 

that are similar to those obtained by the U.S. EPA (1985), but do not provide data for body 

parts nor can results be applied to children. 

For most dermal exposure scenarios concerning adults, it is recommended that the 

body surface areas presented in Table 6-4 be used after determining which body parts will 

be exposed. Table 6-4 was selected because these data are straightforward 

determinations for most scenarios. However, for others, additional considerations may 

need to be addressed. For example, (1) the type of clothing worn could have a significant 

effect on the surface area exposed, and (2) climatic conditions will also affect the type of 

clothing worn and, thus, the skin surface area exposed. 

Frequency, event, and exposure duration for water activities and soil contact are 

presented in Activity Patterns, Volume III, Chapter 15 of this report. For each parameter, 

recommended values were derived for average and upper percentile values. Each of 

these considerations are also discussed in more detail in U.S. EPA (1992b). Data in 

Tables 6-2 and 6-3 can be used when surface area distributions are preferred. A range 

of recommended values for estimates of the skin surface area of children may be taken 

from Tables 6-6 and 6-7 using the 50th and 95th percentile values for age(s) of concern. 

The recommended 50th and 95th percentile values for adult skin surface area provided 

in U.S. EPA (1992b) are presented in Table 6-16. 

6.4.2. Soil Adherence to Skin 

Table 6-17 summarizes the relevant and key studies addressing soil adherence to 

skin. Both Lepow et al. (1975) and Roels et al. (1980) monitored typical exposures in 

children. They attempted to estimate typical exposure by recovery of accumulated soil 

from hands at specific time intervals. The efficiency of their sample collection methods is 

not known and may be subject to error. Only children were studied which may limit 

generalizing these results to adults. Later studies (Que Hee et al., 1985 and Driver et al., 

1989) attempted to characterize both soil properties and sample collection efficiency to 

estimate adherence of soil to skin. However, the experimental conditions used to expose 

skin to soil may not reflect typical dermal exposure situations. This provides useful 

information about the influence of soil characteristics on skin adherence, but the intimate 

contact of skin with soil required under the controlled experimental conditions in the 

studies by Driver et al. (1989) and Que Hee et al. (1985) may have exaggerated the 

amount of adherence over what typically occurs. 

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More recently, Kissel et al. (1996a; 1996b) have related dermal adherence to soil 

characteristics and to specific activities. In all cases, experimental design and 

measurement methods are straightforward and reproducible, but application of results is 

limited. Both controlled experiments and field studies are based on a limited number of 

measurements. Specific situations have been selected to assess soil adherence to skin. 

Consequently, variation due to individuals, protective clothing, temporal, or seasonal 

factors remain to be studied in more detail. Therefore, caution is required in interpretation 

and application of these results for exposure assessments. 

These studies are based on limited data, but suggest: 

• Soil properties influence adherence. Adherence increases with moisture content, 

decreases with particle size, but is relatively unaffected by clay or organic carbon 

content. 

• Adherence levels vary considerably across different parts of the body. The highest 

levels were found on common contact points such as hands, knees, and elbows; the 

least was detected on the face. 

• Adherence levels vary with activity. In general, the highest levels of soil adherence 

were seen in outdoor workers such as farmers and irrigation system installers, 

followed by outdoor recreation, and gardening activities. Very high adherence 

levels were seen in individuals contacting wet soils such as might occur during 

wading or other shore area recreational activities. 

In consideration, of these general observations and the recent data from Kissel et al. 

(1996a, 1996b), changes are needed from past EPA recommendations which used one 

adherence value to represent all soils, body parts, and activities. One approach would be 

to select the activity from Table 6-11 which best represents the exposure scenario of 

concern and use the corresponding adherence value from Table 6-12. Although this 

approach represents an improvement, it still has shortcomings. For example, it is difficult 

to decide which activity in Table 6-12 is most representative of a typical residential setting 

involving a variety of activities. It may be useful to combine these activities into general 

classes of low, moderate, and high contact. In the future, it may be possible to combine 

activity-specific soil adherence estimates with survey-specific soil adherence estimates 

with survey-derived data on activity frequency and duration to develop overall average soil 

contact rates. EPA is sponsoring research to develop such an approach. As this 

information becomes availble, updated recommendations will be issued. 

Table 6-12 provides the best estimates available on activity-specific adherence 

values, but are based on limited data. Therefore, they have a high degree of uncertainty 

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such that considerable judgment must be used when selecting them for an assessment. 

The confidence ratings for various aspects of this recommendation are summarized in 

Table 6-18. Insufficient data are available to develop a distribution or a probability 

function for soil loadings. 

Past EPA guidance has recommended assuming that soil exposure occurs primarily 

to exposed body surfaces and used typical clothing scenarios to derive estimates of 

exposed skin area. The approach recommended above for estimating soil adherence 

addresses this issue in a different manner. This change was motivated by two 

developments. First, increased acceptance that soil and dust particles can get under 

clothing and be deposited on skin. Second, recent studies of soil adherence have 

measured soil on entire body parts (whether or not they were covered by clothing) and 

averaged the amount of soil adhering to skin over the area of entire body part. The soil 

adherence levels resulting from these new studies must be combined with the surface area 

of the entire body part (not merely unclothed surface area) to estimate the amount of 

contaminant on skin. An important caveat, however, is that this approach assumes that 

clothing in the exposure scenario of interest matches the clothing in the studies used to 

derive these adherence levels such that the same degree of protection provided by 

clothing can be assumed in both cases. If clothing differs significantly between the studies 

reported here and the exposure scenarios under investigation, considerable judgment is 

needed to adjust either the adherence level or surface area assumption. 

The dermal adherence value represents the amount of soil on the skin at the time of 

measurement. Assuming that the amount measured on the skin represents its 

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). However, 

this is not recommended because the residence time of soils on skin has not been studied. 

Instead, it is recommended that these adherence values be interpreted on an event basis 

(U.S. EPA, 1992b).

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Appendix 6A 

APPENDIX 6A

FORMULAE FOR TOTAL BODY SURFACE AREA

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Appendix 6A 

APPENDIX 6A 

FORMULAE FOR TOTAL BODY SURFACE AREA 

Most formulae 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. 6A-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. Their model can be written: 

SA ' a0 H a1 W a2 (Eqn. 6A-2) 

where: 

SA = surface area in square meters; 

H = height in centimeters; and 

W = weight in kg. 

The values of a (0.007182), a (0.725), and a (0.425) were estimated from a 0 1 2 

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 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Appendix 6A 

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: a = 0.02350, a = 0.42246, and a = 0.51456. Hence, 0 1 2 

their equation for predicting surface area (SA) is: 

0.51456 SA = 0.02350 H0.42246 W (Eqn. 6A-3) 

or in logarithmic form: 

ln SA= -3.75080 + 0.42246 ln H + 0.51456 ln W (Eqn. 6A-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). 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Appendix 6A 

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: 

a2 SA = a0 Ha1 W ei (Eqn. 6A-5) i i i 

or in logarithmic form: 

ln (SA) = ln a + a ln H + a ln W + ln e (Eqn. 6A-6) i 0 l i 2 i i 

where: 

2 Sai = surface area of the i-th individual (m ); 

Hi = height of the i-th individual (cm); 

Wi = weight of the i-th individual (kg); 

a 0 1 , a , and a 2 = 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: 

0.517 SA = 0.0239 H0.417 W (Eqn. 6A-7) 

or in logarithmic form: 

ln SA = -3.73 + 0.417 ln H + 0.517 ln W (Eqn. 6A-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). 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Appendix 6A 

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 below: 

Table 6A-1. Estimated Parameter Values for Different Age Intervals 

Age Number a0 a1 a2 

group of persons 

All ages 401 0.02350 0.42246 0.51456 

<5 years old 229 0.02667 0.38217 0.53937 

$ 5 - <20 years old 42 0.03050 0.35129 0.54375 

$ 20 years old1 30 0.01545 0.54468 0.46336

 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 

2 was 0.03 m for an 18-year-old at the 97th percentile. The authors concluded that 

there is no advantage in using separate values of a , a , and a by age interval. 0 1 2 

Haycock et al. (1978) without knowledge of the work by Gehan and George 

(1970), developed values for the parameters a , a , and a for the DuBois and DuBois 0 1 2 

model. Their interest in making the DuBois and DuBois model more accurate resulted 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Appendix 6A 

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 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: 

0.5378 SA = 0.024265 H0.3964 W (Eqn. 6A-9) 

expressed logarithmically as: 

ln SA = ln 0.024265 + 0.3964 ln H + 0.5378 ln W (Eqn. 6A-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: 

ln SA = ln a0 + a1 ln H + a ln W (Eqn. 6A-11) 2 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Appendix 6A 

The values for a , a , and a obtained by the various authors discussed in this 0 1 2 

section are presented to follow: 

Table 6A-2. Summary of Surface Area Parameter Values for the DuBois and DuBois 

Model 

Author Number a0 a1 a2 

(year) of persons 

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 

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. 

Nomograms 

Sendroy and Cecchini (1954) proposed a graphical method whereby surface 

area could be read from a diagram relating height and weight to surface area. 

However, they do not give an explicit model for calculating surface area. The graph 

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 formulae of other authors discussed above. 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 7 - Body Weight Studies 

7. BODY WEIGHT STUDIES 

There are several physiological factors needed to calculate potential exposures. 

These include skin surface area (see Volume I, Section 6), inhalation rate (see Volume I,

Section 5) life expectancy (see Volume I, Section 8), and body weight. The average daily 

dose is typically normalized to the average body weight of the exposed population. If 

exposure occurs only during childhood years, the average child body weight during the 

exposure period should be used to estimate risk (U.S. EPA, 1989). Conversely, if adult 

exposures are being evaluated, an adult body weight value should be used. 

The purpose of this section is to describe published studies on body weight for the 

general U.S. population. The studies have been classified as either key or relevant 

studies, based on the criteria described in Volume I, Section 1.3.1. Recommended values 

are based on the results of key studies, but relevant studies are also presented to provide 

the reader with added perspective on the current state of knowledge pertaining to body 

weight. 

7.1. KEY BODY WEIGHT STUDY 

Hamill et al. (1979) - Physical Growth: National Center for Health Statistics 

Percentiles - A National Center for Health Statistics (NCHS) Task Force that included 

academic investigators and representatives from CDC Nutrition Surveillance Program 

selected, collated, integrated, and defined appropriate data sets to generate growth curves 

for the age interval: birth to 36 months developed (Hamill et al., 1979). The percentile 

curves were for assessing the physical growth of children in the U.S. They are based on 

accurate measurements made on large nationally representative samples of children 

(Hamill et al., 1979). Smoothed percentile curves were derived for body weight by age 

(Hamill et al., 1979). Curves were developed for boys and for girls. The data used to 

construct the curves were provided by the Fels Research Institute, Yellow Springs, Ohio. 

These data were from an ongoing longitudinal study where anthromopetric data from direct 

measurements are collected regularly from participants (~1,000) in various areas of the 

U.S. The NCHS used advanced statistical and computer technology to generate the 

growth curves. Table 7-1 presents the percentiles of weight by sex and age. Figures 7-1 

and 7-2 present weight by age percentiles for boys and for girls aged birth to 36 months, 

respectively. Limitations of this study are that mean body weight values were not reported 

and the data are more than 15 years old. However, this study does provide body weight 

data for infants less than 6 months old. 

NCHS (1987) - Anthropometric Reference Data and Prevalence of Overweight, United 

States, 1976-80 - Statistics on anthropometric measurements, including body weight, for 

the U.S. population were collected by NCHS through the second National Health and 

Nutrition Examination Survey (NHANES II). NHANES II was conducted on a nationwide 

Exposure Factors Handbook August 1997
Volume I - General Factors 

Chapter 7 - Body Weight Studies 

probability sample of approximately 28,000 persons, aged 6 months to 74 years, from the 

civilian, non-institutionalized population of the United States. Of the 28,000 persons, 

20,322 were interviewed and examined, resulting in a response rate of 73.1 percent. The 

survey began in February 1976 and was completed in February 1980. The sample was 

selected so that certain subgroups thought to be at high risk of malnutrition (persons with 

low incomes, preschool children, and the elderly) were oversampled. 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 (NCHS, 1987).

The 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 one's weight may vary between winter and 

summer and may fluctuate with recency of food and water intake and other daily activities 

(NCHS, 1987). Mean body weights of adults, by age, and their standard deviations are 

presented in Table 7-2 for men, women, and both sexes combined. Mean body weights 

and standard deviations for children, ages 6 months to 19 years, are presented in Table 

7-3 for boys, girls, and boys and girls combined. Percentile distributions of the body 

weights of adults by age and race for males are presented in Table 7-4, and for females

in Table 7-5. Data for children by age are presented in Table 7-6 for males, and for 

females in Table 7-7. 

Results shown in Tables 7-4 and 7-5 indicate that the mean weight for adult males 

is 78.1 kg and for adult females, 65.4 kg. It also shows that the mean weight for White 

males (78.5 kg) is greater than for Black males (77.9 kg). Additionally, mean weights are 

greater for Black females (71.2 kg) than for White females (64.8 kg). From Table 7-3, the

mean body weights for girls and boys are approximately the same from ages 6 months to 

14 years. Starting at years 15-19, the difference in mean body weight ranges from 6 to 11 

kg. 

7.2. RELEVANT BODY WEIGHT STUDIES 

Brainard and Burmaster (1992) - Bivariate Distributions for Height and Weight of Men 

and Women in the United States - Brainard and Burmaster (1992) examined data on the 

height and weight of adults published by the U.S. Public Health Service and fit bivariate 

distributions to the tabulated values for men and women, separately. 

Height and weight of 5,916 men and 6,588 women in the age range of 18 to 74 years 

were taken from the NHANES II study and statistically adjusted to represent the U.S. 

population aged 18 to 74 years with regard to age structure, sex, and race. Estimation 

techniques were used to fit normal distributions to the cumulative marginal data and 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 7 - Body Weight Studies 

goodness-of-fit tests were used to test the hypothesis that height and lognormal weight 

follow a normal distribution for each sex. It was found that the marginal distributions of 

height and lognormal weight for both men and women are Gaussian (normal) in form. This 

conclusion was reached by visual observation and the high R2 values for best-fit lines 

2 obtained using linear regression. The R values for men's height and lognormal weight are 

2 reported to be 0.999. The R values for women's height and lognormal weight are 0.999 

and 0.985, respectively. 

Brainard and Burmaster (1992) fit bivariate distributions to estimated numbers of men 

and women aged 18 to 74 years in cells representing 1 inch height intervals and 10 pound 

weight intervals. Adjusted height and lognormal weight data for men were fit to a single 

bivariate normal distribution with an estimated mean height of 1.75 meters (69.2 inches) 

and an estimated mean weight of 78.6 kg (173.2 pounds). For women, height and 

lognormal weight data were fit to a pair of superimposed bivariate normal distributions 

(Brainard and Burmaster, 1992). The average height and weight for women were 

estimated from the combined bivariate analyses. Mean height for women was estimated 

to be 1.62 meters (63.8 inches) and mean weight was estimated to be 65.8 kg (145.0 

pounds). For women, a calculation using a single bivarite normal distribution gave poor 

results (Brainard and Burmaster, 1992). According to Brainard and Burmaster, the 

distributions are suitable for use in Monte Carlo simulation. 

Burmaster et al. (1994) (Submitted 2/19/94 to Risk Analysis for Publication) ­

Lognormal Distributions of Body Weight as a Function of Age for Female and Male 

Children in the United States - Burmaster et al. (1994), performed data analysis to fit 

normal and lognormal distributions to the body weights of female and male children at age 

6 months to 20 years (Burmaster et al., 1994). 

Data used in this analysis were from the second survey of the National Center for 

Health Statistics, NHANES II, which included responses from 4,079 females and 4,379 

males 6 months to 20 years of age in the U.S. (Burmaster et al., 1994). 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 et al., 1994). Burmaster et al. (1994) conducted exploratory and quantitative 

data analyses, and fit normal and lognormal distributions to percentiles of body weight for 

children. Cumulative distribution functions (CDFs) were plotted for female and male body 

weights on both linear and logarithmic scales. 

Two models were used to assess the probability density functions (PDFs) of 

children's body weight. Linear and quadratic regression lines were fitted to the data. A 

number of goodness-of-fit measures were conducted on data generated by the two 

models. Burmaster et al. (1994) found that lognormal distributions give strong fits to the 

body weights of children, ages 6 months to 20 years. Statistics for the lognormal 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 7 - Body Weight Studies 

probability plots are presented in Tables 7-8 and 7-9. These data can be used for further 

analyses of body weight distribution (i.e., application of Monte Carlo analysis). 

AIHC - Exposure Factors Sourcebook - The Exposure Factors Sourcebook (AIHC, 

1994) provides similar body weight data as presented here. Consistent with this 

document, an average adult body weight of 72 kg is recommended on the basis of the 

NHANES II data (NCHS, 1987). These data are also used to derive probability 

distributions for adults and children. In addition, the Sourcebook presents probability 

distributions derived by Brainard and Burmaster (1992), Versar (1991) and Brorby and 

Finley (1993). For each distribution, the @Risk formula is provided for direct use in the 

@Risk simulation software (Palisade, 1992). The organization of this document, makes 

it very convenient to use in support of Monte Carlo analysis. The reviews of the supporting 

studies are very brief with little analysis of their strengths and weaknesses. The 

Sourcebook has been classified as a relevant rather than key study because it is not the 

primary source for the data used to make recommendations in this document. The 

Sourcebook is very similar to this document in the sense that it summarizes exposure 

factor data and recommends values. As such, it is clearly relevant as an alternative 

information source on body weights as well as other exposure factors. 

7.3. RECOMMENDATIONS 

The key studies described in this section was used in selecting recommended values 

for body weight. The general description of both the key and relevant studies are 

summarized in Table 7-10. The recommendations for body weight are summarized in 

Table 7-11. Table 7-12 presents the confidence ratings for body weight recommendations. 

The mean body weight for all adults (male and female, all age groups) combined is 71.8 

kg as shown in Table 7-2. The mean values for each age group in Table 7-2 were derived 

by adding the body weights for men and women and dividing by 2. If age and sex 

distribution of the exposed population is known, the mean body weight values in Table 7-2 

can be used. If percentile data are needed or if race is a factor, Tables 7-4 and 7-5 can be 

used to select the appropriate data for percentiles or mean values. 

For infants (birth to 6 months), appropriate values for body weight may be selected 

from Table 7-1. These data (percentile only) are presented for male and female infants. 

For children, appropriate mean values for weights may be selected from Table 7-3. If 

percentile values are needed, these data are presented in Table 7-6 for male children and 

in Table 7-7 for female children. 

Body weight is a function of age, gender, and race and populations of many geographic 

regions may vary from the general population across geographic regions. Therefore, the 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 7 - Body Weight Studies 

user should make appropriate adjustments when applying the percentiles to other 

geographic regions. 

The mean recommended value for adults (71.8 kg) is different than the 70 kg commonly 

assumed in EPA risk assessments. Assessors are encouraged to use values which most 

accurately reflect the exposed population. When using values other than 70 kg, however, 

the assessors should consider if the dose estimate will be used to estimate risk by 

combining with a dose-response relationship which was derived assuming a body weight 

of 70 kg. If such an inconsistency exists, the assessor should adjust the dose-response 

relationship as described in the appendix to Chapter 1. The Integrated Risk Information 

System (IRIS) does not use a 70 kg body weight assumption in the derivation of RfCs and 

RfDs, but does make this assumption in the derivation of cancer slope factors and unit 

risks. 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 8 - Lifetime 

8. LIFETIME 

The length of an individual’s life is an important factor to consider when evaluating 

cancer risk because the dose estimate is averaged over an individual’s lifetime. Since the 

averaging time is found in the denominator of the dose equation, a shorter lifetime would 

result in a higher potential risk estimate, and conversely, a longer life expectancy would 

produce a lower potential risk estimate. 

8.1. KEY STUDY ON LIFETIME 

Statistical data on life expectancy are published annually by the U.S. Department of 

Commerce in the publication: "Statistical Abstract of the United States." The latest year 

for which statistics are available is 1993. Available data on life expectancies for various 

subpopulations born in the years 1970 to 1993 are presented in Table 8-1. Data for 1993 

show that the life expectancy for an average person born in the United States in 1993 is 

75.5 years (U.S. Bureau of the Census, 1995). The table shows that the overall life 

expectancy has averaged approximately 75 years since 1982. The average life 

expectancy for males in 1993 was 72.1 years, and 78.9 years for females. The data 

consistently show an approximate 7 years difference in life expectancy for males and 

females from 1970 to present. Table 8-1 also indicates that life expectancy for white males 

(73.0 years) is consistently longer than for Black males (64.7 years). Additionally, it 

indicates that life expectancy for White females (79.5 years) is longer than for Black 

females (73.7), a difference of almost 6 years. Table 8-2 presents data for expectation of 

life for persons who were at a specific age in year 1990. These data are available by age, 

gender, and race and may be useful for deriving exposure estimates based on the age of 

a specific subpopulation. The data show that expectation of life is longer for females and 

for Whites. 

8.2. RECOMMENDATIONS 

Current data suggest that 75 years would be an appropriate value to reflect the 

average life expectancy of the general population and is the recommended value. If 

gender is a factor considered in the assessment, note that the average life expectancy 

value for females is higher than for males. It is recommended that the assessor use the 

appropriate value of 72.1 years for males or 78.9 years for females. If race is a 

consideration in assessing exposure for male individuals, note that the life expectancy is 

about 8 years longer for Whites than for Blacks. It is recommended that the assessor use 

the values of 73 years and 64.7 years for White males and Black males, respectively. 

Table 8-3 presents the confidence rating for life expectancy recommendations. 

Exposure Factors Handbook August 1997 
Volume I - General Factors 

Chapter 8 - Lifetime 

This recommended value is different than the 70 years commonly assumed for the 

general population in EPA risk assessments. Assessors are encouraged to use values 

which most accurately reflect the exposed population. When using values other than 70 

years, however, the assessors should consider if the dose estimate will be used to 

estimate risk by combining with a dose-response relationship which was derived assuming 

a lifetime of 70 years. If such an inconsistency exists, the assessor should adjust the 

dose-response relationship by multiplying by (lifetime/70). The Integrated Risk Information 

System (IRIS) does not use a 70 year lifetime assumption in the derivation of RfCs and 

RfDs, but does make this assumption in the derivation of some cancer slope factors or unit 

risks. 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 9 - Intake of Fruits and Vegetables 

9. INTAKE OF FRUITS AND VEGETABLES 

9.1. BACKGROUND 

Ingestion of contaminated fruits and vegetables is a potential pathway of human 

exposure to toxic chemicals. 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 

food contamination. 

The primary source of information on consumption rates of fruits and vegetables 

among the United States population is the U.S. Department of Agriculture's (USDA) 

Nationwide Food Consumption Survey (NFCS) and the USDA Continuing Survey of Food 

Intakes by Individuals (CSFII). Data from the NFCS have been used in various studies to 

generate consumer-only and per capita intake rates for both individual fruits and 

vegetables and total fruits and total vegetables. CSFII data from the 1989-1991 survey 

have been analyzed by EPA to generate per capita intake rates for various food items and 

food groups. 

Consumer-only intake is defined as the quantity of fruits and vegetables consumed 

by individuals who ate these food items during the survey period. Per capita intake rates 

are generated by averaging consumer-only intakes over the entire population of users and 

non-users. In general, per capita intake rates are appropriate for use in exposure 

assessment for which average dose estimates for the general population are of interest 

because they represent both individuals who ate the foods during the survey period and 

individuals who may eat the food items at some time, but did not consume them during the 

survey period. 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. 

For the purposes of this handbook, the distinctions between fruits and vegetables are 

those commonly used, not the botanical definitions. For example, in this report, tomatoes 

are considered vegetables, although technically they are fruits. 

Intake rates may be presented on either an as consumed or dry weight basis. As 

consumed intake rates (g/day) are based on the weight of the food in the form that it is 

consumed. In contrast, dry weight intake rates are based on the weight of the food 

consumed after the moisture content has been removed. In calculating exposures based 

on ingestion, the unit of weight used to measure intake should be consistent with those 

used in measuring the contaminant concentration in the produce. Intake data from the 

individual component of the NFCS and CSFII are based on "as eaten" (i.e., cooked or 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 9 - Intake of Fruits and Vegetables 

prepared) forms of the food items/groups. Thus, corrections to account for changes in 

portion sizes from cooking losses are not required. 

Estimating source-specific exposures to toxic chemicals in fruits and vegetables may 

also require information on the amount of fruits and vegetables that are exposed to or 

protected from contamination as a result of cultivation practices or the physical nature of 

the food product itself (i.e., those having protective coverings that are removed before 

eating would be considered protected), or the amount grown beneath the soil (i.e., most 

root crops such as potatoes). The percentages of foods grown above and below ground 

will be useful when the concentrations of contaminants in foods are estimated from 

concentrations in soil, water, and air. For example, vegetables grown below ground may 

be more likely to be contaminated by soil pollutants, but leafy above ground vegetables 

may be more likely to be contaminated by deposition of air pollutants on plant surfaces. 

The purpose of this section is to provide: (1) intake data for individual fruits and 

vegetables, and total fruits and total vegetables; (2) guidance for converting between as 

consumed and dry weight intake rates; and (3) intake data for exposed and protected fruits 

and vegetables and those grown below ground. Recommendations are based on average 

and upper-percentile intake among the general population of the U.S. Available data have 

been classified as being either a key or a relevant study based on the considerations 

discussed in Volume I, Section 1.3.1 of the Introduction. Recommendations are based on 

data from the CSFII 1989-1991 survey, which was considered the only key intake study 

for fruits and vegetables. Other relevant studies are also presented to provide the reader 

with added perspective on this topic. It should be noted that many of the relevant studies 

are based on data from USDA's NFCS and CSFII. The USDA NFCS and CSFII are 

described below. 

9.2. INTAKE STUDIES 

9.2.1. U.S. Department of Agriculture Nationwide Food Consumption Survey 

and Continuing Survey of Food Intake by Individuals 

USDA conducts the NFCS approximately every 10 years. The three most recent 

NFCSs were conducted in 1965-66, 1977-78, and 1987-88. The purpose of these surveys 

was to "analyze the food consumption behavior and dietary status of Americans" 

(USDA, 1992a). The survey uses a statistical sampling technique designed to ensure that 

all seasons, geographic regions of the U.S., and demographic and socioeconomic groups 

are represented. There are two components of the NFCS. The household component 

collects information on the socioeconomic and demographic characteristics of households, 

and the types, value, and sources of foods consumed over a 7-day period. The individual 

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component collects information on food intakes of individuals within each household over 

a 3-day period (USDA, 1992b). 

The same basic survey design was used for the three most recent NFCSs, but the 

sample sizes and statistical classifications used were somewhat different (USDA, 1992a). 

In 1965-66, 10,000 households were surveyed (USDA, 1972). The sample size increased 

to 15,000 households (over 36,000 individuals) in 1977-78, but decreased to 4,500 

households in 1987-88 because of budgetary constraints and a low response rate (37 

percent). Data from the 1977-78 NFCS are presented in this handbook because the data 

have been published by USDA in various publications and reanalyzed by various EPA 

offices according to the food items/groups commonly used to assess exposure. Published 

1-day data from the 1987-88 NFCS data are also presented. 

USDA also conducts the Continuing Survey of Food Intake by Individuals. The 

purpose of the survey is to "assess food consumption behavior and nutritional content of 

diets for policy implications relating to food production and marketing, food safety, food 

assistance, and nutrition education" (USDA, 1995). An EPA analysis of the 1989-91 CSFII 

data set is presented in this handbook. During 1989 through 1991, over 15,000 individuals 

participated in the CSFII (USDA, 1995). Using a stratified sampling technique, individuals 

of all ages living in selected households in the 48 conterminous states and Washington, 

D.C. were surveyed. Individuals provided 3 consecutive days of data, including a personal 

interview on the first day followed by 2-day dietary records. The 3-day response rate for 

the 1989-91 CSFII was approximately 45 percent. Published 1-day data from the 1994 

and 1995 CSFII are also presented. The 1994 and 1995 CSFII included data for 2 nonconsecutive survey days (although 2 days of data have been collected, only data for the 

first survey day have been analyzed and published by USDA). Over 5,500 individuals 

participated in these surveys (USDA, 1996a; 1996b). 

Individual average daily intake rates calculated from NFCS and CSFII data are based 

on averages of reported individual intakes over one day or three consecutive days. Such 

short term data are suitable for estimating mean average daily intake rates representative 

of both short-term and long-term consumption. However, the distribution of average daily 

intake rates generated using short term data (e.g., 3 day) do not necessarily reflect the 

long-term distribution of average daily intake rates. The distributions generated from short 

term and long term data will differ to the extent that each individual’s intake varies from day 

to day; the distributions will be similar to the extent that individuals’ intakes are constant 

from day to day. 

 Day to day variation in intake among individuals will be great for food item/groups that 

are highly seasonal and for items/groups that are eaten year around but that are not 

typically eaten every day. For these foods, the intake distribution generated from short 

term data will not be a good reflection of the long term distribution. On the other hand, for 

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broad categories of foods (e.g., vegetables) which are eaten on a daily basis throughout 

the year with minimal seasonality, the short term distribution may be a reasonable 

approximation of the true long term distribution, although it will show somewhat more 

variability. In this and the following section, distributions are shown only for the following 

broad categories of foods: fruits, vegetables, meats and dairy. Because of the increased 

variability of the short-term distribution, the short-term upper percentiles shown here will 

overestimate somewhat the corresponding percentiles of the long-term distribution. 

9.2.2. Key Fruits and Vegetables Intake Study Based on the USDA CSFII 

U.S. EPA Analysis of USDA 1989-91 CSFII Data - EPA analyzed three years of data 

from USDA's CSFII to generate distributions of intake rates for various fruit and vegetable 

items/groups. Data from the 1989, 1990, and 1991 CFSII were combined into a single 

data set to increase the number of observations available for analysis. Approximately 

15,000 individuals provided intake data over the three survey years. The fruit and 

vegetable items/groups selected for this analysis included total fruits and total vegetables; 

individual fruits such as: apples, peaches, pears, strawberries, and other berries; individual 

vegetables such as: asparagus, beets, broccoli, cabbage, carrots, corn, cucumbers, 

lettuce, lima beans, okra, onions, peas, peppers, pumpkin, snap beans, tomatoes, and 

white potatoes; fruits and vegetables categorized as exposed, protected and roots; and 

various USDA categories (i.e., citrus and other fruits, and dark green, deep yellow, and 

other vegetables). These fruit and vegetable categories were selected to be consistent 

with those evaluated in the homegrown food analysis presented in Chapter 13. Intake 

rates of total vegetables, tomatoes, and white potatoes were adjusted to account for the 

amount of these food items eaten as meat and grain mixtures as described in Appendix 

9A. Food items/groups were identified in the CSFII data base according to USDA-defined 

food codes. Appendix 9B presents the codes used to determine the various food groups. 

Intake rates for these food items/groups represent intake of all forms of the product (i.e., 

home produced and commercially produced). 

Individual identifiers in the database were used throughout the analysis to categorize 

populations according to demographics. These identifiers included identification number, 

region, urbanization, age, sex, race, body weight, weighting factor, season, and number 

of days that data were reported. Distributions of intake were determined for individuals 

who provided data for all three days of the survey. Individuals who did not provide 

information on body weight, or for which identifying information was unavailable, were 

excluded from the analysis. Three-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 g/kg-day. The data were also weighted according to the three-day weights 

provided in the 1991 CSFII. USDA sample weights are calculated to account for inherent 

biases in the sample selection process, and to adjust the sample population to reflect the 

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national population. Summary statistics for individual intake rates were generated on a 

per capita basis. That is, both users and non-users of the food item were included in the 

analysis. Mean consumer only intake rates may be calculated by dividing the mean per 

capita intake rate by the percent of the population consuming the food item of interest. 

Summary statistics included are: number of weighted and unweighted observations, 

percentage of the population using the food item/group being analyzed, mean intake rate, 

standard error, and percentiles of the intake rate distribution (i.e., 0, 1, 5, 10, 25, 50, 75, 

90, 95, 99, and 100th percentile). Data were provided for the total population using the 

food item being evaluated and for several demographic groups including: various age 

groups (i.e., <1, 1-2, 3-5, 6-11, 12-19, 20-39, 40-69, and 70+ years); regions (i.e., Midwest, 

Northeast, South, and West); urbanizations (i.e., Central City, Nonmetropolitan, and 

Suburban; seasons (i.e., winter, spring, summer, and fall); and races (i.e., White, Black, 

Asian, Native American, and other). Table 9-1 provides the codes, definitions, and a 

description of the data in these categories. The total numbers of individuals in the data 

set, by demographic group are presented in Table 9-2. The food analysis was 

accomplished using the SAS statistical programming system (SAS, 1990). 

The results of this analysis are presented in Tables 9-3 and 9-4 for total fruits and 

total vegetables, Table 9-5 for individual fruits and vegetables, and Table 9-6 for the 

various USDA categories. The data for exposed/protected and root food items are 

presented in Tables 9-7 through 9-11. These tables are presented at the end of this 

Chapter. The results are presented in units of g/kg-day. Thus, use of these data in 

calculating potential dose does not require the body weight factor to be included in the 

denominator of the average daily dose (ADD) equation. It should be noted that converting 

these intake rates into units of g/day by multiplying by a single average body weight is 

inappropriate, because individual intake rates were indexed to the reported body weights 

of the survey respondents. However, if there is a need to compare the intake data 

presented here to intake data in units of g/day, a body weight less than 70 kg (i.e., 

approximately 60 kg; calculated based on the number of respondents in each age category 

and the average body weights for these age groups, as presented in Chapter 7 of Volume 

I) should be used because the total survey population included children as well as adults. 

The advantages of using the 1989-91 CSFII data set are that the data are expected 

to be generally representative of the U.S. population and that it includes data on a wide 

variety of food types. However, it should be noted that the survey covers only the 48 

coterminous U.S. States; Hawaii, Alaska, and U.S. Territories are not included. The data 

set was the most recent of a series of publicly available USDA data sets (i.e., NFCS 1977­

78; NFCS 1987-88; CSFII 1989-91) at the time that EPA conducted the analysis for this 

handbook, and should reflect recent eating patterns in the United States. The data set 

includes three years of intake data combined. However, the 1989-91 CSFII data are 

based on a three day survey period. Short-term dietary data may not accurately reflect 

long-term eating patterns. This is particularly true for the tails (extremes) of the distribution 

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Chapter 9 - Intake of Fruits and Vegetables 

of food intake. In addition, the adjustment for including mixtures adds uncertainty to the 

intake rate distributions. The calculation for including mixtures assumes that intake of any 

mixture includes all of the foods identified in Appendix Table 9A-1 in the proportions 

specified in that table. This may under- or over-estimate intake of certain foods among 

some individuals. 

The data presented in this handbook for the USDA 1989-91 CSFII is not the most upto-date information on food intake. USDA has recently made available the data from its 

1994 and 1995 CSFII. Over 5,500 people nationwide participated in both of these surveys, 

providing recalled food intake information for 2 separate days. Although the 2-day data 

analysis has not been conducted, USDA published the results for the respondents’ intakes 

on the first day surveyed (USDA, 1996a; 1996b). USDA 1996 survey data will be made 

available later in 1997. As soon as 1996 data are available, EPA will take steps to get the 

3-year data (1994, 1995, and 1996) analyzed and the food ingestion factors updated. 

Meanwhile, Table 9-12 presents a comparison of the mean daily intakes per individual in 

a day for fruits and vegetables from the USDA survey data from years 1977-78, 19887-88, 

1989-91, 1994, and 1995. This table shows that food consumption patterns have changed 

for fruits when comparing 1977 and 1995 data. Consumption of fruits increased by 72 

percent, but vegetable intake remained relatively constant, when comparing data from 

1977 and 1995. However, only an 11 percent increase was observed when comparing fruit 

intake values from 1989-91 with the most recent data from 1994 and 1995. This indicates 

that the 1989-91 CSFII data are probably adequate for assessing ingestion exposure for 

current populations. 

9.2.3. Relevant Fruits and Vegetables Intake Studies 

The U.S. EPA's Dietary Risk Evaluation System (DRES) - USEPA, Office of Pesticide 

Programs - The U.S. EPA, Office of Pesticide Programs (OPP) uses the Dietary Risk 

Evaluation System (formerly the Tolerance Assessment System) to assess the dietary risk 

of pesticide use as part of the pesticide registration process. OPP sets tolerances for 

specific pesticides on raw agricultural commodities based on estimates of dietary risk. 

These estimates are calculated using pesticide residue data for the food item of concern 

and relevant consumption data. Intake rates are based primarily on the USDA 1977-78 

NFCS although intake rates for some food items are based on estimations from production 

volumes or other data (i.e., some items were assigned an arbitrary value of 0.000001 g/kgday) (Kariya, 1992). OPP has calculated per capita intake rates of individual fruits and 

vegetables for 22 subgroups (age, regional, and seasonal) of the population by 

determining the composition of NFCS food items and disaggregating complex food dishes 

into their component raw agricultural commodities (RACs) (White et al., 1983). 

The DRES per capita, as consumed intake rates for all age/sex/demographic groups 

combined are presented in Table 9-13. These data are based on both consumers and non 

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Chapter 9 - Intake of Fruits and Vegetables 

consumers of these food items. Data for specific subgroups of the population are not 

presented here, but are available through OPP via direct request. The data in Table 9-13 

may be useful for estimating the risks of exposure associated with the consumption of 

individual fruits and vegetables. It should be noted that these data are indexed to the 

reported body weights of the survey respondents and are expressed in units of grams of 

food consumed per kg bodyweight per day. Consequently, use of these data in calculating 

potential dose does not require the body weight factor in the denominator of the ADD 

equation. It should also be noted that conversion of these intake rates into units of g/day 

by multiplying by a single average body weight is not appropriate because the DRES data 

base did not rely on a single body weight for all individuals. Instead, DRES used the body 

weights reported by each individual surveyed to estimate consumption in units of g/kg-day. 

The advantages of using these data are that complex food dishes have been 

disaggregated to provide intake rates for a very large number of fruits and vegetables. 

These data are also based on the individual body weights of the respondents. Therefore, 

the use of these data in calculating exposure to toxic chemicals may provide more 

representative estimates of potential dose per unit body weight. However, because the 

data are based on NFCS short-term dietary recall the same limitations discussed 

previously for other NFCS data sets also apply here. In addition, consumption patterns 

may have changed since the data were collected in 1977-78. OPP is in the process of 

translating consumption information from the USDA CSFII 1989-91 survey to be used in 

DRES. 

Food and Nutrient Intakes of Individuals in One Day in the U.S., USDA (1980, 1992b, 

1996a, 1996b) - USDA calculated mean intake rates for total fruits and total vegetables 

using NFCS data from 1977-78 and 1987-88 (USDA, 1980; USDA, 1992b) and CSFII data 

from 1994 and 1995 (USDA, 1996a; 1996b). The mean per capita total intake rates are 

presented in Tables 9-14 and 9-15 for fruits and Tables 9-16 and 9-17 for vegetables. 

These values are based on intake data for one day from the 1977-78 and 1987-88 USDA 

NFCSs, respectively. Data from both surveys are presented here to demonstrate that 

although the 1987-88 survey had fewer respondents, the mean per capita intake rates for 

all individuals are in good agreement with the earlier survey. Also, slightly different age 

classifications were used in the two surveys providing a wider range of age categories 

from which exposure assessors may select appropriate intake rates. Tables 9-18 and 9-19 

present similar data from the 1994 and 1995 CSFII. The age groups used in this data set 

are the same as those used in the 1987-88 NFCS. Tables 9-14 through 9-19 include both 

per capita intake rates and intake rates for consumers-only for various ages of individuals. 

Intake rates for consumers-only were calculated by dividing the per capita consumption 

rate by the fraction of the population using vegetables or fruits in a day. The average per 

capita vegetable intake rate is 201 g/day based on the 1977-78 data (USDA, 1980), 182 

g/day based on the 1987-88 data (USDA, 1992b), 186 g/day based on the 1994 data, and 

188 g/day based on the 1995 data. For fruits the average per capita intake rate is 142 

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g/day based on the two most recent USDA NFCSs (USDA, 1980; USDA, 1992b), and 171 

g/day and 173 g/day based on the 1994 and 1995 CSFII, respectively (USDA, 1996a, 

1996b). One-day per capita intake data for fats or oils from the 1994 and 1995 CSFII 

surveys are presented in Table 9-20. This total fats and oils food category includes table 

and cooking fats, vegetable oils, salad dressings, nondairy cream substitutes, and sauces 

such as tartar sauce that are mainly fat or oil (USDA, 1996a). It does not include oils or 

fats that were ingredients in food mixtures. 

The advantages of using these data are that they provide intake estimates for all 

fruits, all vegetables, or all fats combined. Again, these estimates are based on one-day 

dietary data which may not reflect usual consumption patterns. 

U.S. EPA - Office of Radiation Programs - The U.S. EPA Office of Radiation Programs 

(ORP) has also used the USDA 1977-78 NFCS to estimate daily food intake (U.S. EPA, 

1984a; 1984b). ORP uses food consumption data to assess human intake of 

radionuclides in foods. The 1977-78 NFCS data have been reorganized by ORP, and 

food items have been classified according to the characteristics of radionuclide transport. 

Data for selected agricultural products are presented in Table 9-21 and Table 9-22. These 

data represent per capita, as consumed intake rates for total, leafy, exposed, and 

protected produce. Exposed produce refers to products (e.g., apples, pears, berries, etc.) 

that can intercept atmospherically deposited materials. The term protected refers to 

products (e.g., citrus fruit, carrots, corn, etc.) that are protected from deposition from the 

atmosphere. Although the fruit and vegetable classifications used in the study are 

somewhat limited in number, they provide alternative food categories that may be useful 

to exposure assessors. Because this study was based on the USDA NFCS, the limitations 

discussed previously regarding short-term dietary recall data also apply to the intake rates 

reported here. Also, consumption patterns may have changed since the data were 

collected in 1977-78. 

U.S. EPA - Office of Science and Technology - The U.S. EPA Office of Science and 

Technology (OST) within the Office of Water (formerly the Office of Water Regulations and 

Standards) used data from the FDA revision of the Total Diet Study Food Lists and Diets 

(Pennington, 1983) to calculate food intake rates (U.S. EPA, 1989). OST uses these 

consumption data in its risk assessment model for land application of municipal sludge. 

The FDA data used are based on the combined results of the USDA 1977-78, NFCS and 

the second National Health and Nutrition Examination Survey (NHANES II), 1976-80 

(U.S. EPA, 1989). Because food items are listed as prepared complex foods in the FDA 

Total Diet Study, each item was broken down into its component parts so that the amount 

of raw commodities consumed could be determined. Table 9-23 presents intake rates of 

various fruit and vegetable categories for various age groups and estimated lifetime 

ingestion rates that have been derived by U.S. EPA. Note that these are per capita intake 

rates tabulated as grams dry weight/day. Therefore, these rates differ from those in the 

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Chapter 9 - Intake of Fruits and Vegetables 

previous tables because U.S. EPA (1984a, 1984b) report intake rates on an as consumed 

basis. 

The EPA-OST analysis provides intake rates for additional food categories and 

estimates of lifetime average daily intake on a per capita basis. In contrast to the other 

analyses of USDA NFCS data, this study reports the data in terms of dry weight intake 

rates. Thus, conversion is not required when contaminants are to be estimated on a dry 

weight basis. These data, however, may not reflect current consumption patterns because 

they are based on data from 1977-78. 

Canadian Department of National Health and Welfare Nutrition Canada Survey - The 

Nutrition Canada Survey was conducted between 1970 and 1972 to "(a) examine the mean 

consumption of selected food groups and their contribution to nutrient intakes of 

Canadians, (b) examine patterns of food consumption and nutrient intake at various times 

of the day, and provide information on the changes in eating habits during pregnancy." 

(Canadian Department of National Health and Welfare, n.d.). The method used for 

collecting dietary intake data was 24-hour recall. The recall method relied on interview 

techniques in which the interviewee was asked to recall all foods and beverages 

consumed during the day preceding the interview. Intake rates were reported for various 

age/sex groups of the population and for pregnant women (Table 9-24). The report does 

not specify whether the values represent per capita or consumer-only intake rates. 

However, they appear to be consistent with the as consumed intake rates for consumersonly reported by USDA (1980, 1992b). It should be noted that these data are also based 

on short-term dietary recall and are based on the Canadian population. 

USDA (1993) - Food Consumption, Prices, and Expenditures, 1970-92 - The USDA's 

Economic Research Service (ERS) calculates the amount of food available for human 

consumption in the United States on an annual basis (USDA, 1993). Supply and utilization 

balance sheets are generated, based on the flow of food items from production to end 

uses for the years 1970 to 1992. Total available supply is estimated as the sum of 

production and imports (USDA, 1993). The availability of food for human use commonly 

termed as "food disappearance" is determined by subtracting exported foods from the total 

available supply (USDA, 1993). USDA (1993) calculates the per capita food consumption 

by dividing the total food disappearance by the total U.S. population. USDA (1993) 

estimated per capita consumption data for various fruit and vegetable products from 1970­

1992 (1992 data are published). In this section, the 1991 values, which are the most 

recent published final data, are presented. Retail weight per capita data are presented in 

Table 9-25. These data have been derived from the annual per capita values in units of 

pounds per year, presented by USDA (1993), by converting to units of g/day. 

One of the limitations of this study is that disappearance data do not account for 

losses from the food supply from waste or spoilage. As a result, intake rates based on 

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these data may overestimate daily consumption because they are based on the total 

quantity of marketable commodity utilized. Thus, these data represent bounding estimates 

of intake rates only. It should also be noted that per capita estimates based on food 

disappearance are not a direct measure of actual consumption or quantity ingested, 

instead the data are used as indicators of changes in usage over time (USDA, 1993). An 

advantage of this study is that it provides per capita consumption rates for fruits and 

vegetables that are representative of long-term intake because disappearance data are 

generated annually. 

AIHC, 1994 - Exposure Factors Sourcebook - The AIHC Sourcebook (AIHC, 1994) 

uses the data presented in the 1989 version of the Exposure Factors Handbook which 

reported data from the USDA 1977-78 NFCS. Distributions are provided in the @Risk 

format and the @Risk formula is also provided. In this handbook, new analyses of more 

recent data from the USDA 1989-91 CSFII are presented. Numbers, however, cannot be 

directly compared with previous values since the results from the new analysis are 

presented on a body weight basis. 

The Sourcebook was classified as a relevant study because it was not the primary 

source for the data to make recommendations in this document. However, it can be used 

as an alternative source of information. 

The advantage of using the CSFII and USDA NFCS data sets are that they are the 

largest publicly available data source on food intake patterns in the United States. Data 

are available for a wide variety of fruit and vegetable products and are intended to be 

representative of the U.S. population. 

9.2.4. Relevant Fruits and Vegetables Serving Size Study Based on the USDA 

NFCS 

Pao et al. (1982) - Foods Commonly Eaten by Individuals - Using data gathered in 

the 1977-78 USDA NFCS, Pao et al. (1982) calculated distributions for the quantities of 

individual fruit and vegetables consumed per eating occasion by members of the U.S. 

population (i.e., serving sizes), over a 3-day period. The data were collected during NFCS 

home interviews of 37,874 respondents, who were asked to recall food intake for the day 

preceding the interview, and record food intake the day of the interview and the day after 

the interview. 

Serving size data are presented on an as consumed (g/day) basis. The data 

presented in Table 9-26 are for all ages of the population, combined. If age-specific intake 

data are needed, refer to Pao et al. (1982). Although serving size data only are presented 

in this handbook, percentiles for the average quantities of individual fruits and vegetables 

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Chapter 9 - Intake of Fruits and Vegetables 

consumed by members of the U.S. population who had consumed these fruits and 

vegetables over a 3-day period can be found in Pao et al. (1982). 

The advantages of using these data are that they were derived from the USDA NFCS 

and are representative of the U.S. population. This data set provides serving size 

distributions for a number of commonly eaten fruits and vegetables, but the list of foods 

is limited and does not account for fruits and vegetables included in complex food dishes. 

Also, these data represent the quantity of fruits and vegetables consumed per eating 

occasion. Although these estimates are based on USDA NFCS 1977-78 data, serving 

size data have been collected but not published for the more recent USDA surveys. 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. 

However, it should be noted that serving sizes may have changed since the data were 

collected in 1977-78. 

9.2.5. Conversion Between As Consumed and Dry Weight Intake Rates 

As noted previously, intake rates may be reported in terms of units as consumed or 

units of dry weight. 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 unit of food consumption is grams dry weight/day, then 

the unit for the amount of pollutant in the food should be grams dry weight). 

If necessary, as consumed intake rates may be converted to dry weight intake rates 

using the moisture content percentages presented in Table 9-27 and the following 

equation: 

IR = IR * [(100-W)/100] (Eqn. 9-1) dw ac 

"Dry weight" intake rates may be converted to "as consumed" rates by using: 

IR = IR /[(100-W)/100] ac dw (Eqn. 9-2) 

where: 

IRdw = dry weight intake rate; 

IRac = as consumed intake rate; and 

W = percent water content. 

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Chapter 9 - Intake of Fruits and Vegetables 

9.3. RECOMMENDATIONS 

The 1989-91 CSFII data described in this section were used in selecting 

recommended fruit and vegetable intake rates for the general population and various 

subgroups of the United States population. The general design of both key and relevant 

studies are summarized in Table 9-28. Table 9-29 presents a summary of the 

recommended values for fruit and vegetable intake and Table 9-30 presents the 

confidence ratings for the fruit and vegetable intake recommendations. Based on the 

CSFII 1989-91, the recommended per capita fruit intake rate for the general population is 

3.4 g/kg-day and the recommended per capita vegetable intake rate for the general 

population is 4.3 g/kg-day. Per capita intake rates for specific food items, on a g/kg-day 

basis, may be obtained from Table 9-5. Percentiles of the per capita intake rate 

distribution in the general population for total fruits and total vegetables are presented in 

Tables 9-3 and 9-4. From these tables, the 95th percentile intake rates for fruits and 

vegetables are 12 g/kg-day and 10 g/kg-day, respectively. It is important to note that the 

distributions presented in Tables 9-3 through 9-4 are based on data collected over a 3-day 

period and may not necessarily reflect the long-term distribution of average daily intake 

rates. However, for these 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 will tend to overestimate the corresponding percentiles of the true 

long-term distribution. Intake rates for the home-produced form of these fruit and 

vegetable products are presented in Volume II, Chapter 13. It should be noted that 

because these recommendations are based on 1989-91 CSFII data, they may not reflect 

the most recent changes that may have occurred in consumption patterns. However, as 

indicated in Table 9-12, intake has remained fairly constant between 1989-91 and 1995.

Thus, the 1989-91 CSFII data are believed to be appropriate for assessing ingestion 

exposure for current populations. 

Exposure Factors Handbook August 1997 
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Appendix 9A 

APPENDIX 9A 

CALCULATIONS USED IN THE 1989-91 CSFII ANALYSIS TO CORRECT FOR 

MIXTURES 

Exposure Factors Handbook August 1997 
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Appendix 9A 

APPENDIX 9A 

Calculations Used in the 1989-91 CSFII Analysis to Correct for Mixtures 

Distributions of intake for various food groups were generated for the food/items 

groups using the USDA 1989-91 CSFII data set as described in Sections 9.2.2. and 11.1.2. 

However, several of the food categories used did not include meats, dairy products, and 

vegetables that were eaten as mixtures with other foods. Thus, adjusted intake rates were 

calculated for food items that were identified by USDA (1995) as comprising a significant 

portion of grain and meat mixtures. To account for the amount of these foods consumed 

as mixtures, the mean fractions of total meat or grain mixtures represented by these food 

items were calculated (Table 9A-1) using Appendix C of USDA (1995). Mean values for 

all individuals were used to calculate these fractions. These fractions were multiplied by 

each individual's intake rate for total meat mixtures or grain mixtures to calculate the 

amount of the individual's food mixture intake that can be categorized into one of the 

selected food groups. These amounts were then added to the total intakes rates for 

meats, grains, total vegetables, tomatoes, and white potatoes to calculate an individual's 

total intake of these food groups, as shown in the example for meats below. 

( Fr ( Frmeat/mt) % (IRmeat IR ) meat&adjusted ' (IR

gr mixtures meat/gr) % (IRmt mixtures 

where: 

IRmeat-adjusted = adjusted individual intake rate for total meat; 

IRgr mixtures = individual intake rate for grain mixtures; 

IRmt mixtures = individual intake rate for meat mixtures; 

IRmeat = individual intake rate for meats; 

Frmeat/gr = fraction of grain mixture that is meat; and 

Frmeat/mt = fraction of meat mixture that is meat. 

Population distributions for mixture-adjusted intakes were based on adjusted intake rates 

for the population of interest. 

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Chapter 10 - Intake of Fish and Shellfish 

10. INTAKE OF FISH AND SHELLFISH 

10.1. BACKGROUND 

Contaminated finfish and shellfish are potential sources of human exposure to toxic 

chemicals. Pollutants are carried in the surface waters, but also may be stored and 

accumulated in the sediments as a result of complex physical and chemical processes. 

Consequently, finfish and shellfish are exposed to these pollutants and may become 

sources of contaminated food. 

Accurately estimating exposure to a toxic chemical among a population that 

consumes fish from a polluted water body requires an estimation of intake rates of the 

caught fish by both fishermen and their families. Commercially caught fish are marketed 

widely, making the prediction of an individual's consumption from a particular commercial 

source difficult. Since the catch of recreational and subsistence fishermen is not "diluted" 

in this way, these individuals and their families represent the population that is most 

vulnerable to exposure by intake of contaminated fish from a specific location. 

This section focuses on intake rates of fish. Note that in this section the term fish 

refers to both finfish and shellfish. The following subsections address intake rates for the 

general population, and recreational and subsistence fishermen. Data are presented for 

intake rates for both marine and freshwater fish, when available. The available studies 

have been classified as either key or relevant based on the guidelines given in Volume I, 

Section 1.3. Recommended intake rates are based on the results of key studies, but other 

relevant studies are also presented to provide the reader with added perspective on the 

current state-of-knowledge pertaining to fish intake. 

Survey data on fish consumption have been collected using a number of different 

approaches which need to be considered in interpreting the survey results. Generally, 

surveys are either "creel" studies in which fishermen are interviewed while fishing, or 

broader population surveys using either mailed questionnaires or phone interviews. Both 

types of data can be useful for exposure assessment purposes, but somewhat different 

applications and interpretations are needed. In fact, results from creel studies have often 

been misinterpreted, due to inadequate knowledge of survey principles. Below, some basic 

facts about survey design are presented, followed by an analysis of the differences 

between creel and population based studies. 

The typical survey seeks to draw inferences about a larger population from a smaller 

sample of that population. This larger population, from which the survey sample is to be 

taken and to which the results of the survey are to be generalized, is denoted the target 

population of the survey. In order to generalize from the sample to the target population, 

the probability of being sampled must be known for each member of the target population. 

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This probability is reflected in weights assigned to each survey respondent, with weights 

being inversely proportional to sampling probability. When all members of the target 

population have the same probability of being sampled, all weights can be set to one and 

essentially ignored. 

In a mail or phone study of licensed anglers, the target population is generally all 

licensed anglers in a particular area, and in the studies presented, the sampling probability 

is essentially equal for all target population members. In a creel study, the target 

population is anyone who fishes at the locations being studied; generally, in a creel study, 

the probability of being sampled is not the same for all members of the target population. 

For instance, if the survey is conducted for one day at a site, then it will include all persons 

who fish there daily but only about 1/7 of the people who fish there weekly, 1/30th of the 

people who fish there monthly, etc. In this example, the probability of being sampled (or 

inverse weight) is seen to be proportional to the frequency of fishing. However, if the 

survey involves interviewers revisiting the same site on multiple days, and persons are 

only interviewed once for the survey, then the probability of being in the survey is not 

proportional to frequency; in fact, it increases less than proportionally with frequency. At 

the extreme of surveying the same site every day over the survey period with no reinterviewing, all members of the target population would have the same probability of being 

sampled regardless of fishing frequency, implying that the survey weights should all equal 

one. 

On the other hand, if the survey protocol calls for individuals to be interviewed each 

time an interviewer encounters them (i.e., without regard to whether they were previously 

interviewed), then the inverse weights will again be proportional to fishing frequency, no 

matter how many times interviewers revisit the same site. Note that when individuals can 

be interviewed multiple times, the results of each interview are included as separate 

records in the data base and the survey weights should be inversely proportional to the 

expected number of times that an individual’s interviews are included in the data base. 

In the published analyses of most creel studies, there is no mention of sampling 

weights; by default all weights are set to 1, implying equal probability of sampling. 

However, since the sampling probabilities in a creel study, even with repeated interviewing 

at a site, are highly dependent on fishing frequency, the fish intake distributions reported 

for these surveys are not reflective of the corresponding target populations. Instead, those 

individuals with high fishing frequencies are given too big a weight and the distribution is 

skewed to the right, i.e., it overestimates the target population distribution. 

Price et al. (1994) explained this problem and set out to rectify it by adding weights 

to creel survey data; he used data from two creel studies (Puffer et al., 1981 and Pierce 

et al., 1981) as examples. Price et al. (1994) used inverse fishing frequency as survey 

weights and produced revised estimates of median and 95th percentile intake for the 

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Chapter 10 - Intake of Fish and Shellfish 

above two studies. These revised estimates were dramatically lower than the original 

estimates. The approach of Price et al. (1994) is discussed in more detail in Section 10.5 

where the Puffer et al. (1981) and Pierce et al. (1981) studies are summarized. 

When the correct weights are applied to survey data, the resulting percentiles reflect, 

on average, the distribution in the target population; thus, for example, an estimated 90 

percent of the target population will have intake levels below the 90th percentile of the 

survey fish intake distribution. There is another way, however, of characterizing 

distributions in addition to the standard percentile approach; this approach is reflected in 

statements of the form “50 percent of the income is received by, for example, the top 10 

percent of the population, which consists of individuals making more than $100,000", for 

example. Note that the 50th percentile (median) of the income distribution is well below 

$100,000. Here the $100,000 level can be thought of as, not the 50th percentile of the 

population income distribution, but as the 50th percentile of the “resource utilization 

distribution” (see Appendix 10A for technical discussion of this distribution). Other 

percentiles of the resource utilization distribution have similar interpreta-tions; e.g., the 

90th percentile of the resource utilization distribution (for income) would be that level of 

income such that 90 percent of total income is received by individuals with incomes below 

this level and 10 percent by individuals with income above this level. This alternative 

approach to characterizing distributions is of particular interest when a relatively small 

fraction of individuals consumes a relatively large fraction of a resource, which is the case 

with regards to recreational fish consumption. In the studies of recreational anglers, this 

alternative approach, based on resource utilization, will be presented, where possible, in 

addition to the primary approach of presenting the standard percentiles of the fish intake 

distribution. 

It has been determined that the resource utilization approach to characterizing 

distributions has relevance to the interpretation of creel survey data. As mentioned above, 

most published analyses of creel surveys do not employ weights reflective of sampling 

probability, but instead give each respondent equal weight. For mathematical reasons that 

are explained in Appendix 10A, when creel analyses are performed in this (equal 

weighting) manner, the calculated percentiles of the fish intake distribution do not reflect 

the percentiles of the target population fish intake distribution but instead reflect 

(approximately) the percentiles of the “resource utilization distribution”. Thus, one would 

not expect 50 percent of the target population to be consuming above the median intake 

level as reported from such a creel survey, but instead would expect that 50 percent of the 

total recreational fish consumption would be individuals consuming above this level. As 

with the example above, and in accordance with the statement above that creel surveys 

analyzed in this manner overestimate intake distributions, the actual median level of intake 

in the target population will be less (probably considerably so) than this level and, 

accordingly, (considerably) less than 50 percent of the target population will be consuming 

at or above this level. These considerations are discussed when the results of individual 

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Chapter 10 - Intake of Fish and Shellfish 

creel surveys are presented in later sections and should be kept in mind whenever 

estimates based on creel survey data are utilized. 

The U.S. EPA has prepared a review of and an evaluation of five different survey 

methods used for obtaining fish consumption data. They are: 

• Recall-Telephone Survey; 

• Recall-Mail Survey; 

• Recall-Personal Interview; 

• Diary; and 

• Creel Census. 

The reader is referred to U.S. EPA 1992-Consumption Surveys for Fish and Shellfish for 

more detail on these survey methods and their advantages and limitations. 

10.2. KEY GENERAL POPULATION STUDIES 

Tuna Research Institute Survey - The Tuna Research Institute (TRI) funded a study 

of fish consumption which was performed by the National Purchase Diary (NPD) during the 

period of September, 1973 to August, 1974. The data tapes from this survey were obtained 

by the National Marine Fisheries Service (NMFS), which later, along with the FDA, USDA 

and TRI, conducted an intensive effort to identify and correct errors in the data base. 

Javitz (1980) summarized the TRI survey methodology and used the corrected tape to 

generate fish intake distributions for various sub-populations. 

The TRI survey sample included 6,980 families who were currently participating in 

a syndicated national purchase diary panel, 2,400 additional families where the head of 

household was female and under 35 years old; and 210 additional black families (Javitz, 

1980). Of the 9,590 families in the total sample, 7,662 families (25,162 individuals) 

completed the questionnaire, a response rate of 80 percent. The survey was weighted to 

represent the U.S. population based on a number of census-defined controls (i.e., census 

region, household size, income, presence of children, race and age). The calculations of 

means, percentiles, etc. were performed on a weighted basis with each person contributing 

in proportion to his/her assigned survey weight. 

The survey population was divided into 12 different sample segments and, for each 

of the 12 survey months, data were collected from a different segment. Each survey 

household was given a diary in which they recorded, over a one month period, the date 

of any fish meals consumed and the following accompanying information: the species of 

fish consumed, whether the fish was commercially or recreationally caught, the way the 

fish was packaged (canned, frozen fresh, dried, smoked), the amount of fish prepared and 

consumed, and the number of servings consumed by household members and guests. 

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Both meals eaten at home and away from home were recorded. The amount of fish 

prepared was determined as follows (Javitz, 1980): “For fresh fish, the weight was 

recorded in ounces and may have included the weight of the head and tail. For frozen fish, 

the weight was recorded in packaged ounces, and it was noted whether the fish was 

breaded or combined with other ingredients (e.g., TV dinners). For canned fish, the weight 

was recorded in packaged ounces and it was noted whether the fish was canned in water, 

oil, or with other ingredients (e.g., soups)”. 

Javitz (1980) reported that the corrected survey tapes contained data on 24,652 

individuals who consumed fish in the survey month and that tabulations performed by NPD 

indicated that these fish consumers represented 94 percent of the U.S. population. For 

this population of “fish consumers”, Javitz (1980) calculated means and percentiles of fish 

consumption by demographic variables (age, sex, race, census region and community 

type) and overall (Tables 10-1 through 10-4). The overall mean fish intake rate among fish 

consumers was calculated at 14.3 g/day and the 95th percentile at 41.7 g/day. 

As seen in Table 10-1, the mean and 95th percentile of fish consumption were higher 

for Asian-Americans as compared to the other racial groups. Other differences in intake 

rates are those between gender and age groups. While males (15.6 g/d) eat slightly more 

fish than females (13.2 g/d), and adults eat more fish than children, the corresponding 

differences in body weight would probably compensate for the different intake rates in 

exposure calculations (Javitz, 1980). There appeared to be no large differences in 

regional intake rates, although higher rates are shown in the New England and Middle 

Atlantic census regions. 

The mean and 95th percentile intake rates by age-gender groups are presented in 

Table 10-2. Tables 10-3 and 10-4 present the distribution of fish consumption for females 

and males, respectively, by age; these tables give the percentages of females/males in a 

given age bracket with intake rates within various ranges. Table 10-5 presents mean total 

fish consumption by fish species. 

The TRI survey data were also utilized by Rupp et al. (1980) to generate fish intake 

distributions for three age groups (<11, 12-18, and 19+ years) within each of the 9 census 

regions and for the entire United States. Separate distributions were derived for 

freshwater finfish, saltwater finfish and shellfish; thus, a total of 90 (3*3*10) different 

distributions were derived, each corresponding to intake of a specific category of fish for 

a given age group within a given region. The analysis of Rupp et al. (1980) included only 

those respondents with known age. This amounted to 23,213 respondents. 

Ruffle et al. (1994) used the percentiles data of Rupp et al. (1980) to estimate the 

best fitting lognormal parameters for each distribution. Three methods (non-linear 

optimization, first probability plot and second probability plot) were used to estimate 

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optimal parameters. Ruffle et al. (1994) determined that, of the three methods, the nonlinear optimization method (NLO) generally gave the best results. For some of the 

distributions fitted by the NLO method, however, it was determined that the lognormal 

model did not adequately fit the empirical fish intake distribution. Ruffle et al. (1994) used 

a criterion of minimum sum of squares (min SS) less than 30 to identify which distributions 

provided adequate fits. Of the 90 distributions studied, 77 were seen to have min SS < 30; 

for these, Ruffle et al. (1994) concluded that the NLO modeled lognormal distributions are 

“well suited for risk assessment”. Of the remaining 13 distributions, 12 had min SS > 30; 

for these Ruffle et al. (1994) concluded that modeled lognormal distributions “may also be 

appropriate for use when exercised with due care and with sensitivity analyses”. One 

distribution, that of freshwater finfish intake for children < 11 years of age in New England, 

could not be modeled due to the absence of any reported consumption. 

Table 10-6 presents the optimal lognormal parameters, the mean (F), standard 

deviation (s), and min SS, for all 89 modeled distributions. These parameters can be used 

to determine percentiles of the corresponding distribution of average daily fish 

consumption rates through the relation DFC(p)=exp[F+ z(p)s] where DFC(p) is the pth 

percentile of the distribution of average daily fish consumption rates and z(p) is the z-score 

associated with the pth percentile (e.g., z(50)=0 ). The mean average daily fish 

2 consumption rate is given by exp[F + 0.5s ]. 

The analyses of Javitz (1980) and Ruffle et al. (1994) were based on consumers only, 

who are estimated to represent 94.0 percent of the U.S. population. U.S. EPA estimated 

the mean intake in the general population by multiplying the fraction consuming, 0.94, by 

the mean among consumers reported by Javitz (1980) of 14.3 g/day; the resulting 

estimate is 13.4 g/day. The 95th percentile estimate of Javitz (1980) of 41.7 g/day among 

consumers would be essentially unchanged when applied to the general population; 41.7 

g/day would represent the 95.3 percentile (i.e., 100*[0.95*0.94+0.06]) among the general 

population. 

Advantages of the TRI data survey are that it was a large, nationally representative 

survey with a high response rate (80 percent) and was conducted over an entire year. In 

addition, consumption was recorded in a daily diary over a one month period; this format 

should be more reliable than one based on one-month recall. The upper percentiles 

presented are derived from one month of data, and are likely to overestimate the 

corresponding upper percentiles of the long-term (i.e., one year or more) average daily fish 

intake distribution. Similarly, the standard deviation of the fitted lognormal distribution 

probably overestimates the standard deviation of the long-term distribution. However, the 

period of this survey (one month) is considerably longer than those of many other 

consumption studies, including the USDA National Food Consumption Surveys, which 

report consumption over a 3 day to one week period. 

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Another obvious limitation of this data base is that it is now over twenty years out of 

date. Ruffle et al. (1994) considered this shortcoming and suggested that one may wish 

to shift the distribution upward to account for the recent increase in fish consumption. 

Adding ln(1+x/100) to the log mean F will shift the distribution upward by x percent (e.g., 

adding 0.22 = ln(1.25) increases the distribution by 25 percent). Although the TRI survey 

distinguished between recreationally and commercially caught fish, Javitz (1980), Rupp 

et al. (1980), and Ruffle et al. (1994) (which was based on Rupp et al., 1980) did not 

present analyses by this variable. 

U.S. EPA (1996a) - Daily Average Per Capita Fish Consumption Estimates Based on 

the Combined USDA 1989, 1990, and 1991 Continuing Survey of Food Intakes by 

Individuals (CSFII) — The USDA conducts the CSFII on an ongoing basis. U.S. EPA used 

the 1989, 1990, and 1991 CSFII data to generate fish intake estimates. Participants in the 

CSFII provided 3 consecutive days of dietary data. For the first day’s data, participants 

supplied dietary recall information to an in-home interviewer. Second and third day dietary 

intakes were recorded by participants. Data collection for the CSFII started in April of the 

given year and was completed in March of the following year. 

The CSFII contains 469 fish-related food codes; survey respondents reported 

consumption across 284 of these codes. Respondents estimated the weight of each food 

that they consumed. The fish component (by weight) of these foods was calculated using 

data from the recipe file for release 7 of the 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 utilized 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-eaten and uncooked basis. 

Each (fish-related) food code was assigned by EPA a habitat type of either 

freshwater/estuarine or marine. Food codes were also designated as finfish or shellfish.

 Average daily individual consumption (g/day) for a given fish type-by-habitat category 

(e.g., marine finfish) was calculated by summing the amount of fish consumed by the 

individual across the three reporting days for all fish-related food codes in the given fishby-habitat category and then dividing by 3. Individual consumption per day consuming 

fish (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 three survey 

days). The reported body-weight of the individual was used to convert consumption in 

g/day to consumption in g/kg-day. 

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Chapter 10 - Intake of Fish and Shellfish 

There were a total of 11,912 respondents in the combined data set who had three-day 

dietary intake data. Survey weights were assigned to this data set to make it 

representative of the U.S. population with respect to various demographic characteristics 

related to food intake. 

U.S. EPA (1996a) reported means, medians, upper percentiles, and 90-percent 

interval estimates for the 90th, 95th, and 99th percentiles. The 90-percent interval 

estimates are nonparametric estimates from bootstrap techniques. The bootstrap 

estimates result from the percentile method which estimates the lower and upper bounds 

for the interval estimate by the 100" percentile and 100 (1-") percentile estimates from 

the non-parametric distribution of the given point estimate (U.S. EPA, 1996a). 

Analyses of fish intake were performed on an as-eaten as well as on an uncooked 

equivalent basis and on a g/day and g/kg-day basis. Table 10-7 gives the mean and 

various percentiles of the distribution of per-capita fish intake rates (g/day) based on 

uncooked equivalent weight by habitat and fish type, for the general population. The mean 

per capita intake rate of finfish and shellfish from all habitats was 20.1 g/day. Per-capita 

consumption estimates by species are shown in Appendix 10C. Table 10-8 displays the 

mean and various percentiles of the distribution of total fish intake per day consuming fish, 

by habitat for consumers only. Also displayed is the percentage of the population 

consuming fish of the specified habitat during the three day survey period. Tables 10-9 

and 10-10 present similar results as above but on a mg/kg-day basis; Tables 10-11 and 

10-12 present results in the same format for fish intake (g/day) on an as-eaten (cooked) 

basis. 

Tables 10-13 through 10-44 present data for daily average per capita fish 

consumption by age and gender. These data are presented by selected age grouping (4 

and under, 15-44, 45 and older, all ages) and gender. Tables 10-13 through 10-20 

present fish intake data (g/day and mg/kg-day) on an as consumed basis for the general 

population and Tables 10-21 through 10-28 for consumers only. Tables 10-29 through 10­

44 provide intake data (g/day and mg/kg-day) on an uncooked equivalent basis for the 

same population groups described above. 

The advantages of this study are its large size, its relative currency and its 

representativeness. In addition, through use of the USDA recipe files, the analysis 

identified all fish-related food codes and estimated the percent fish content of each of 

these codes. By contrast, some analyses of the USDA National Food Consumption 

Surveys (NFCSs) which reported per capita fish intake rates ( e.g., Pao et al., 1982; 

USDA, 1992a), excluded certain fish containing foods (e.g., fish mixtures, frozen plate 

meals) in their calculations. 

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Chapter 10 - Intake of Fish and Shellfish 

Results from the 1977-1978 NFCS survey (Pao et al., 1982) showed that only a small 

percentage of consumers ate fish on more than one occasion per day. This implies that 

the distribution presented for fish intake per day consuming fish can be used as a 

surrogate for the distribution of fish intake per (fish) eating occasion (Table 10-8). 

Also, it should be noted that the 1989-91 CSFII data are not the most recent intake 

survey data. USDA has recently made available data from its 1994 and 1995 CSFII. Over 

5,500 people nationwide participated in both of these surveys, providing recalled food 

intake information for two separate days. Although the 2-day data analysis has not been 

conducted, USDA published results for the respondents’ intakes on the first day surveyed 

(USDA, 1996a; USDA, 1996b). USDA 1996 survey data will be made available later in 

1997. As soon as 1996 data are available, EPA will take steps to get the 3-year data 

(1994, 1995, 1996) analyzed and the food ingestion factors updated. Meanwhile, 

comparisons between the mean daily fish intake per individual in a day from the USDA 

survey data from years 1977-78, 1987-88, 1989-91, 1994, and 1995 indicate that fish 

intake has been relatively constant over time. The 1-day fish intake rates were 11 g/day, 

11 g/day, 13 g/day, 9 g/day, and 11 g/day for survey years 1977-78, 1987-88, 1989-91, 

1994, and 1995, respectively. This indicates that the 1989-91 CSFII data presented in this 

handbook are probably adequate for assessing fish ingestion exposure for current 

populations. 

10.3. RELEVANT GENERAL POPULATION STUDIES 

Pao et al. (1982) - Foods Commonly Eaten by Individuals: Amount Per Day and Per 

Eating Occasion - The USDA 1977-78 Nationwide Food Consumption Survey (NFCS) was 

described in Chapter 9. The survey consisted of a household and individual component. 

For the individual component, all members of surveyed households were asked to provide 

3 consecutive days of dietary data. For the first day’s data, participants supplied dietary 

recall information to an in-home interviewer. Second and third day dietary intakes were 

recorded by participants. A total of 15,000 households were included in the 1977-78 

NFCS and about 38,000 individuals completed the 3-day diet records. Fish intake was 

estimated based on consumption of fish products identified in the NFCS data base 

according to NFCS-defined food codes. These products included fresh, breaded, floured, 

canned, raw and dried fish, but not fish mixtures or frozen plate meals. 

Pao et al. (1982) used the 1977-78 NFCS to examine the quantity of fish consumed 

per eating occasion. For each individual consuming fish in the 3 day survey period, the 

quantity of fish consumed per eating occasion was derived by dividing the total reported 

fish intake over the 3 day period by the number of occasions the individual reported eating 

fish. The distributions, by age and sex, for the quantity of fish consumed per eating 

occasion are displayed in Table 10-45 (Pao et al., 1982). For the general population, the 

average quantity of fish consumed per fish meal was 117 g, with a 95th percentile of 284 

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g. Males in the age groups 19-34, 35-64 and 65-74 years had the highest average and 

95th percentile quantities among the age-sex groups presented. 

Pao et al. (1982) also used the data from this survey set to calculate per capita fish 

intake rates. However, because these data are now almost 20 years out of date, this 

analysis is not considered key with respect to assessing per capita intake (the average 

quantity of fish consumed per fish meal should be less subject to change over time than 

is per capita intake). In addition, fish mixtures and frozen plate meals were not included 

in the calculation of fish intake. The per capita fish intake rate reported by Pao et al. 

(1982) was 11.8 g/day. The 1977-1978 NFCS was a large and well designed survey and 

the data are representative of the U.S. population. 

USDA Nationwide Food Consumption Survey 1987-88 - The USDA 1987-88 

Nationwide Food Consumption Survey (NFCS) was described in Chapter 9. Briefly, the 

survey consisted of a household and individual component. The household component 

asked about household food consumption over the past one week period. For the 

individual component, each member of a surveyed household was interviewed (in person) 

and asked to recall all foods eaten the previous day; the information from this interview 

made up the “one day data” for the survey. In addition, members were instructed to fill out 

a detailed dietary record for the day of the interview and the following day. The data for 

this entire 3-day period made up the “3-day diet records”. A statistical sampling design 

was used to ensure that all seasons, geographic regions of the U.S., demographic, and 

socioeconomic groups were represented. Sampling weights were used to match the 

population distribution of 13 demographic characteristics related to food intake (USDA, 

1992a). 

Total fish intake was estimated based on consumption of fish products identified in 

the NFCS data base according to NFCS-defined food codes. These products included 

fresh, breaded, floured, canned, raw and dried fish, but not fish mixtures or frozen plate 

meals. 

A total of 4,500 households participated in the 1987-88 survey; the household 

response rate was 38 percent. One day data were obtained for 10,172 (81 percent) of the 

12,522 individuals in participating households; 8,468 (68 percent) individuals completed 

3-day diet records. 

USDA (1992b) used the one day data to derive per capita fish intake rate and intake 

rates for consumers of total fish. These rates, calculated by sex and age group, are 

shown in Table 10-46. Intake rates for consumers-only were calculated by dividing the per 

capita intake rates by the fractions of the population consuming fish in one day. 

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The 1987-1988 NFCS was also utilized to estimate consumption of home produced 

fish (as well as home produced fruits, vegetables, meats and dairy products) in the general 

U.S. population. The methodology for estimating home-produced intake rates was rather 

complex and involved combining the household and individual components of the NFCS; 

the methodology, as well as the estimated intake rates, are described in detail in Chapter 

12. However, since much of the rest of this chapter is concerned with estimating 

consumption of recreationally caught, i.e., home produced fish, the methods and results 

of Chapter 12, as they pertain to fish consumption, are summarized briefly here. 

A total of 2.1 percent of the survey population reported home produced fish 

consumption during the survey week. Among consumers, the mean intake rate was 2.07 

g/kg-day and the 95th percentile was 7.83 g/kg-day; the per-capita intake rate was 0.04 

g/kg-day. Note that intake rates for home-produced foods were indexed to the weight of 

the survey respondent and reported in g/kg-day. 

It is possible to compare the estimates of home-produced fish consumption derived 

in this analyses with estimates derived from studies of recreational anglers (described in 

Sections 10.4-10.8); however, the intake rates must be put into a similar context. The 

home-produced intake rates described refer to average daily intake rates among 

individuals consuming home-produced fish in a week; results from recreational angler 

studies, however, usually report average daily rates for those eating home-produced fish 

(or for those who recreationally fish) at least some time during the year. Since many of 

these latter individuals eat home-produced fish at a frequency of less than once per week, 

the average daily intake in this group would be expected to be less than that reported. 

The NFCS household component contains the question “Does anyone in your 

household fish?”. For the population answering yes to this question (21 percent of 

households), the NFCS data show that 9 percent consumed home-produced fish in the 

week of the survey; the mean intake rate for these consumers from fishing households 

was 2.2 g/kg-day. (Note that 91 percent of individuals reporting home grown fish 

consumption for the week of the survey indicated that a household member fishes; the 

overall mean intake rate among home-produced fish consumers, regardless of fishing 

status, was the above reported 2.07 g/kg-day). The per capita intake rate among those 

living in a fishing household is then calculated as 0.2 g/kg-day (2.2 * 0.09). Using the 

estimated average weight of survey participants of 59 kg, this translates into 11.8 g/day. 

Among members of fishing households, home-produced fish consumption accounted for 

32.5 percent of total fish consumption.

As discussed in Chapter 12 of this volume, intake rates for home-produced foods, 

including fish, are based on the results of the household survey, and as such, reflect the 

weight of fish taken into the household. In most of the recreational fish surveys discussed 

later in this section, the weight of the fish catch (which generally corresponds to the weight 

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taken into the household) is multiplied by an edible fraction to convert to an uncooked 

equivalent of the amount consumed. This fraction may be species specific, but some 

studies used an average value; these average values ranged from 0.3 to 0.5. Using a 

factor of 0.5 would convert the above 11.8 g/day rate to 5.9 g/day. This estimate, 5.9 

g/day, of the per-capita fish intake rate among members of fishing households is within the 

range of the per-capita intake rates among recreational anglers addressed in sections to 

follow. 

An advantage of analyses based on the 1987-1988 USDA NFCS is that the data set 

is a large, geographically and seasonally balanced survey of a representative sample of 

the U.S. population. The survey response rate, however, was low and an expert panel 

concluded that it was not possible to establish the presence or absence of non-response 

bias (USDA, 1992b). Limitations of the home-produced analysis are given in Chapter 12 

of this volume. 

Tsang and Klepeis (1996) - National Human Activity Pattern Survey (NHAPS) - The 

U.S. EPA collected information for the general population on the duration and frequency 

of time spent in selected activities and time spent in selected microenvironments via 

24-hour diaries. Over 9,000 individuals from 48 contiguous states participated in NHAPS. 

Approximately 4,700 participants also provided information on seafood consumption. The 

survey was conducted between October 1992 and September 1994. Data were collected 

on the (1) number of people that ate seafood in the last month, (2) the number of servings 

of seafood consumed, and (3) whether the seafood consumed was caught or purchased 

(Tsang and Klepeis, 1996). 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. Of those 4,700 respondents, 2,980 (59.6 percent) 

ate seafood (including shellfish, eels, or squid) in the last month (Table 10-47). The 

number of servings per month were categorized in ranges of 1-2, 3-5, 6-10, 11-19, and 20+ 

servings per month (Table 10-48). The highest percentage (35 percent) of respondent 

population had an intake of 3-5 servings per month. Most (92 percent) of the respondents 

purchased the seafood they ate (Table 10-49).

Intake data were not provided in the survey. However, intake of fish can be estimated 

using the information on the number of servings of fish eaten from this study and serving 

size data from other studies. The recommended mean value in this handbook for fish 

serving size is 129 g/serving (Table 10-82). Using this mean value for serving size and 

assuming that the average individual eats 3-5 servings per month, the amount of seafood 

eaten per month would range from 387 to 645 grams/month or 12.9 to 21.5 g/day for the 

highest percentage of the population. These values are within the range of mean intake 

values for total fish (20.1 g/day) calculated in the U.S. EPA analysis of the USDA CSFII 

data. It should be noted that an all inclusive description for seafood was not presented in 

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Tsang and Klepeis (1996). It is not known if processed or canned seafood and seafood 

mixtures are included in the seafood category. 

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 intake from this study are comparable to those observed in 

the EPA CSFII analysis. 

10.4. KEY RECREATIONAL (MARINE FISH STUDIES) 

National Marine Fisheries Service (1986a, b, c; 1993) - The National Marine Fisheries 

Service (NMFS) conducts systematic surveys, on a continuing basis, of marine 

recreational fishing. These surveys are designed to estimate the size of the recreational 

marine finfish catch by location, species and fishing mode. In addition, the surveys provide 

estimates for the total number of participants in marine recreational finfishing and the total 

number of fishing trips. The surveys are not designed to estimate individual consumption 

of fish from marine recreational sources, primarily because they do not attempt to estimate 

the number of individuals consuming the recreational catch. Intake rates for marine 

recreational anglers can be estimated, however, by employing assumptions derived from 

other data sources about the number of consumers. 

The NMFS surveys involve two components, telephone surveys and direct 

interviewing of fishermen in the field. The telephone survey randomly samples residents 

of coastal regions, defined generally as counties within 25 miles of the nearest seacoast, 

and inquires about participation in marine recreational fishing in the resident’s home state 

in the past year, and more specifically, in the past two months. This component of the 

survey is used to estimate, for each coastal state, the total number of coastal region 

residents who participate in marine recreational fishing (for finfish) within the state, as well 

as the total number of (within state) fishing trips these residents take. To estimate the total 

number of participants and fishing trips in the state, by coastal residents and others, a 

ratio approach, based on the field interview data, was used. Thus, if the field survey data 

found that there was a 4:1 ratio of fishing trips taken by coastal residents as compared to 

trips taken by non-coastal and out of state residents, then an additional 25 percent would 

be added to the number of trips taken by coastal residents to generate an estimate of the 

total number of within state trips. 

The field intercept survey is essentially a creel type survey. The survey utilizes a 

national site register which details marine fishing locations in each state. Sites for field 

interviews are chosen in proportion to fishing frequency at the site. Anglers fishing on 

shore, private boat, and charter/party boat modes who had completed their fishing were 

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interviewed. The field survey included questions about frequency of fishing, area of 

fishing, age, and place of residence. The fish catch was classified by the interviewer as 

either type A, type B1 or type B2 catch. The type A catch denoted fish that were taken 

whole from the fishing site and were available for inspection. The type B1 and B2 catch 

were not available for inspection; the former consisted of fish used as bait, filleted, or 

discarded dead while the latter was fish released alive. The type A catch was identified by 

species and weighed, with the weight reflecting total fish weight, including inedible parts. 

The type B1 catch was not weighed, but weights were estimated using the average weight 

derived from the type A catch for the given species, state, fishing mode and season of the 

year. For both the A and B1 catch, the intended disposition of the catch (e.g., plan to eat, 

plan to throw away, etc.) was ascertained. 

EPA obtained the raw data tapes from NMFS in order to generate intake distributions 

and other specialized analyses. Fish intake distributions were generated using the field 

survey tapes. Weights proportional to the inverse of the angler’s reported fishing 

frequency were employed to correct for the unequal probabilities of sampling; this was the 

same approach used by NMFS in deriving their estimates. Note that in the field survey, 

anglers were interviewed regardless of past interviewing experience; thus, the use of 

inverse fishing frequency as weights was justified (see Section 10.1).

For each angler interviewed in the field survey, the yearly amount of fish caught that 

was intended to be eaten by the angler and his/her family or friends was estimated by EPA 

as follows: 

Y = [(wt of A catch) * IA + (wt of B1 catch) * I B ] * [Fishing frequency] (Eqn. 10-1)

where I (I ) are indicator variables equal to 1 if the type A (B1) catch was intended to be A B 

eaten and equal to 0 otherwise. To convert Y to a daily fish intake rate by the angler, it was 

necessary to convert amount of fish caught to edible amount of fish, divide by the number 

of intended consumers, and convert from yearly to daily rate. Although theoretically 

possible, EPA chose not to use species specific edible fractions to convert overall weight 

to edible fish weight since edible fraction estimates were not readily available for many 

marine species. Instead, an average value of 0.5 was employed. For the number of 

intended consumers, EPA used an average value of 2.5 which was an average derived 

from the results of several studies of recreational fish consumption (Chemrisk, 1991; Puffer 

et al., 1981; West et al., 1989). Thus, the average daily intake rate (ADI) for each angler 

was calculated as 

ADI = Y * (0.5)/[2.5 * 365] (Eqn. 10-2) 

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Note that ADI will be 0 for those anglers who either did not intend to eat their catch or who 

did not catch any fish. The distribution of ADI among anglers was calculated by region and 

coastal status (i.e., coastal versus non-coastal counties). A mean ADI for the overall 

population of a given area was calculated as follows: first the estimated number of anglers 

in the area was multiplied by the average number of intended fish consumers (2.5) to get 

a total number of recreational marine finfish consumers. This number was then multiplied 

by the mean ADI among anglers to get the total recreational marine finfish consumption 

in the area. Finally, the mean ADI in the population was calculated by dividing total fish 

consumption by the total population in the area. 

The results presented below are based on the results of the 1993 survey. Samples 

sizes were 200,000 for the telephone survey and 120,000 for the field surveys. All coastal 

states in the continental U.S. were included in the survey except Texas and Washington. 

Table 10-50 presents the estimated number of coastal, non-coastal, and out-of-state 

fishing participants by state and region of fishing. Florida had the greatest number of both 

Atlantic and Gulf participants. The total number of coastal residents who participated in 

marine finfishing in their home state was 8 million; an additional 750,000 non-coastal 

residents participated in marine finfishing in their home state. 

Table 10-51 presents the estimated total weight of the A and B1 catch by region and 

time of year. For each region, the greatest catches were during the six-month period from 

May through October. This period accounted for about 90 percent of the North and 

Mid-Atlantic catch, about 80 percent of the Northern California and Oregon catch, about 

70 percent of the Southern Atlantic and Southern California catch and 62 percent of the 

Gulf catch. Note that in the North and Mid-Atlantic regions, field surveys were not done 

in January and February due to very low fishing activity. For all regions, over half the 

catch occurred within 3 miles of the shore or in inland waterways. 

Table 10-52 presents the mean and 95th percentile of average daily intake of 

recreationally caught marine finfish among anglers by region. The mean ADI among all 

anglers was 5.6, 7.2, and 2.0 g/day for the Atlantic, Gulf, and Pacific regions, respectively. 

Also given is the per-capita ADI in the overall population (anglers and non-anglers) of the 

region and in the overall coastal population of the region. Table 10-53 gives the 

distribution of the catch by species for the Atlantic and Gulf regions and Table 10-54 for 

Pacific regions. 

The NMFS surveys provide a large, up-to-date, and geographically representative 

sample of marine angler activity in the U.S. The major limitation of this data base in terms 

of estimating fish intake is the lack of information regarding the intended number of 

consumers of each angler’s catch. In this analysis, it was assumed that every angler’s 

catch was consumed by the same number (2.5) of people; this number was derived from 

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averaging the results of other studies. This assumption introduces a relatively low level 

of uncertainty in the estimated mean intake rates among anglers, but a somewhat higher 

level of uncertainty in the estimated intake distributions. It should be noted that under the 

above assumption, the distributions shown here pertain not only to the population of 

anglers, but also to the entire population of recreational fish consumers, which is 2.5 times 

the number of anglers. If the number of consumers was changed, to, for instance, 2.0, 

then the distribution would be increased by a factor of 1.25 (2.5/2.0), but the estimated 

population of recreational fish consumers to which the distribution would apply would 

decrease by a factor of 0.8 (2.0/2.5). Note that the mean intake rate of marine finfish in 

the overall population is independent of the assumption of number of intended fish 

consumers. 

Another uncertainty involves the use of 0.5 as an (average) edible fraction. This 

figure is somewhat conservative (i.e., the true average edible fraction is probably lower); 

thus, the intake rates calculated here may be biased upward somewhat. 

It should be noted again that the recreational fish intake distributions given refer only 

to marine finfish. In addition, the intake rates calculated are based only on the catch of 

anglers in their home state. Marine fishing performed out-of-state would not be included 

in these distributions. Therefore, these distributions give an estimate of consumption of 

locally caught fish. 

10.5. RELEVANT RECREATIONAL MARINE STUDIES 

Puffer et al. (1981) - Intake Rates of Potentially Hazardous Marine Fish Caught in the 

Metropolitan Los Angeles Area - Puffer et al. (1981) conducted a creel survey with sport 

fishermen in the Los Angeles area in 1980. The survey was conducted at 12 sites in the 

harbor and coastal areas to evaluate intake rates of potentially hazardous marine fish and 

shellfish by local, non-professional fishermen. It was conducted for the full 1980 calendar 

year, although inclement weather in January, February, and March limited the interview 

days. Each site was surveyed an average of three times per month, on different days, and 

at a different time of the day. The survey questionnaire was designed to collect 

information on demographic characteristics, fishing patterns, species, number of fish 

caught, and fish consumption patterns. Scales were used to obtain fish weights. 

Interviews were conducted only with anglers who had caught fish, and the anglers were 

interviewed only once during the entire survey period. 

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Chapter 10 - Intake of Fish and Shellfish 

Puffer et al. (1981) estimated daily consumption rates (grams/day) for each angler 

using the following equation: 

(K x N x W x F)/[E x 365] (Eqn. 10-3) 

where: 

K = edible fraction of fish (0.25 to 0.5 depending on species); 

N = number of fish in catch; 

W = average weight of (grams) fish in catch; 

F = frequency of fishing/year; and 

E = number of fish eaters in family/living group. 

No explicit survey weights were used in analyzing this survey; thus, each respondent’s 

data was given equal weight. 

A total of 1,059 anglers were interviewed for the survey. The ethnic and age 

distribution of respondents is shown in Table 10-55; 88 percent of respondents were male. 

The median intake rate was higher for Oriental/Samoan anglers (median 70.6 g/day) than 

for other ethnic groups and higher for those ages over 65 years (median 113.0 g/day) than 

for other age groups. Puffer et al. (1981) found similar median intake rates for seasons; 

36.3 g/day for November through March and 37.7 g/day for April through October. Puffer 

et al. (1981) also evaluated fish preparation methods; these data are presented in 

Appendix 10B. The cumulative distribution of recreational fish (finfish and shellfish) 

consumption by survey respondents is presented in Table 10-56; this distribution was 

calculated only for those fishermen who indicated they eat the fish they catch. The median 

fish consumption rate was 37 g/day and the 90th percentile rate was 225 g/day (Puffer et 

al., 1981). A description of catch patterns for primary fish species kept is presented in 

Table 10-57. 

As mentioned in the Background to this Chapter, intake distributions derived from 

analyses of creel surveys which did not employ weights reflective of sampling probabilities 

will overestimate the target population intake distribution and will, in fact, be more 

reflective of the “resource utilization distribution”. Therefore, the reported median level 

of 37.3 g/day does not reflect the fact that 50 percent of the target population has intake 

above this level; instead 50 percent of recreational fish consumption is by individuals 

consuming at or above 37.3 g/day. In order to generate an intake distribution reflective 

of that in the target population, weights inversely proportional to sampling probability need 

to be employed. Price et al. (1994) made this attempt with the Puffer et al. (1981) survey 

data, using inverse fishing frequencies as the sampling weights. Price et al. (1994) was 

unable to get the raw data for this survey, but using frequency tables and the average level 

of fish consumption per fishing trip provided in Puffer et al. (1981), generated an 

approximate revised intake distribution. This distribution was dramatically lower than that 

obtained by Puffer et al. (1981); the median was estimated at 2.9 g/day (compared with 

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37.3 from Puffer et al., 1981) and the 90th percentile at 35 g/day (compared to 225 g/day 

from Puffer et al., 1981). 

There are several limitations to the interpretation of the percentiles presented by both 

Puffer et al. (1981) and Price et al. (1994). As described in Appendix 10A, the 

interpretation of percentiles reported from creel surveys in terms of percentiles of the 

“resource utilization distribution” is approximate and depends on several assumptions. 

One of these assumptions is that sampling probability is proportional to inverse fishing 

frequency. In this survey, where interviewers revisited sites numerous times and anglers 

were not interviewed more than once, this assumption is not valid, though it is likely that 

the sampling probability is still highly dependant on fishing frequency so that the 

assumption does hold in an approximate sense. The validity of this assumption also 

impacts the interpretation of percentiles reported by Price et al. (1994) since inverse 

frequency was used as sampling weights. It is likely that the value (2.9 g/day) of Price et 

al. (1994) underestimates somewhat the median intake in the target population, but is 

much closer to the actual value than the Puffer et al. (1981) estimate of 37.3 g/day. Similar 

statements would apply about the 90th percentile. Similarly, the 37.3 g/day median value, 

if interpreted as the 50th percentile of the “resource utilization distribution”, is also 

somewhat of an underestimate. 

It should be noted again that the fish intake distribution generated by Puffer et al. 

(1981) (and by Price et al., 1994) was based only on fishermen who caught fish and ate 

the fish they caught. If all anglers were included, intake estimates would be somewhat 

lower. In contrast, the survey assumed that the number of fish caught at the time of the 

interview was all that would be caught that day. If it were possible to interview fishermen 

at the conclusion of their fishing day, intake estimates could be potentially higher. An 

additional factor potentially affecting intake rates is that fishing quarantines were imposed 

in early spring due to heavy sewage overflow (Puffer et al., 1981). 

Pierce et al. (1981) - Commencement Bay Seafood Consumption Study - Pierce et 

al. (1981) performed a local creel survey to examine seafood consumption patterns and 

demographics of sport fishermen in Commencement Bay, Washington. The objectives of 

this survey included determining (1) seafood consumption habits and demographics of 

non-commercial anglers catching seafood; (2) the extent to which resident fish were used 

as food; and (3) the method of preparation of the fish to be consumed. Salmon were 

excluded from the survey since it was believed that they had little potential for 

contamination. The first half of this survey was conducted from early July to midSeptember, 1980 and the second half from mid-September through most of November. 

During the summer months, interviewers visited each of 4 sub-areas of Commencement 

Bay on five mornings and five evenings; in the fall the areas were sampled 4 complete 

survey days. Interviews were conducted only with persons who had caught fish. The 

anglers were interviewed only once during the survey period. Data were recorded for 

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species, wet weight, size of the living group (family, place of residence, fishing frequency, 

planned uses of the fish, age, sex, and race (Pierce et al., 1981). The analysis of Pierce 

et al. (1981) did not employ explicit sampling weights (i.e., all weights were set to 1). 

There were 304 interviews in the summer and 204 in the fall. About 60 percent of 

anglers were white, 20 percent black, 19 percent Oriental and the rest Hispanic or Native 

American. Table 10-58 gives the distribution of fishing frequency calculated by Pierce et 

al. (1981); for both the summer and fall, more than half of the fishermen caught and 

consumed fish weekly. The dominant (by weight) species caught were Pacific Hake and 

Walleye Pollock. Pierce et al. (1981) did not present a distribution of fish intake or a mean 

fish intake rate. 

The U.S. EPA (1989a) used the Pierce et al. (1981) fishing frequency distribution and 

an estimate of the average amount of fish consumed per angling trip to create an 

approximate intake distribution for the Pierce et al. (1981) survey. The estimate of the 

amount of fish consumed per angling trip (380 g/person-trip) was based on data on mean 

fish catch weight and mean number of consumers reported in Pierce et. al. (1981) and on 

an edible fraction of 0.5. U.S. EPA (1989a) reported a median intake rate of 23 g/day. 

Price et al. (1994) obtained the raw data from this survey and performed a re-analysis 

using sampling weights proportional to inverse fishing frequency. The rationale for these 

weights is explained in Section 10.1 and in the discussion above of the Puffer et al. (1981) 

study. In the re-analysis, Price et al. (1994) found a median intake rate of 1.0 g/day and 

a 90th percentile rate of 13 g/day. The distribution of fishing frequency generated by 

Price et al. (1994) is shown in Table 10-59. Note that when equal weights were used, 

Price et al. (1994) found a median rate of 19 g/day, which was close to the approximate 

U.S. EPA (1989a) value reported above of 23 g/day.

The same limitations apply to interpreting the results presented here to those 

presented above in the discussion of Puffer et al. (1981). The median intake rate found 

by Price et al. (1994) (using inverse frequency weights) is more reflective of median intake 

in the target population than is the value of 19 g/day (or 23 g/day); the latter value reflects 

more the 50th percentile of the resource utilization distribution, (i.e., that anglers with 

intakes above 19 g/day consume 50 percent of the recreational fish catch). Similarly, the 

fishing frequency distribution generated by Price et al. (1994) is more reflective of the 

fishing frequency distribution in the target population than is the distribution presented in 

Pierce et al. (1981). Note the target population is those anglers who fished at 

Commencement Bay during the time period of the survey. 

As with the Puffer et al. (1981) data, these values (1.0 g/day and 19 g/day) are both 

probably underestimates since the sampling probabilities are less than proportional to 

fishing frequency; thus, the true target population median is probably somewhat above 1.0 

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g/day and the true 50th percentile of the resource utilization distribution is probably 

somewhat higher than 19 g/day. The data from this survey provide an indication of 

consumption patterns for the time period around 1980 in the Commencement Bay area. 

However, the data may not reflect current consumption patterns because fishing advisories 

were instituted due to local contamination. 

U.S. DHHS (1995) - Health Study to Assess the Human Health Effects of Mercury 

Exposure to Fish Consumed from the Everglades - A health study was conducted in two 

phases in the Everglades, Florida for the U.S. Department of Health and Human Services 

(U.S. DHHS, 1995). The objectives of the first phase were to: (a) describe the human 

populations at risk for mercury exposure through their consumption of fish and other 

contaminated animals from the Everglades and (b) evaluate the extent of mercury 

exposure in those persons consuming contaminated food and their compliance with the 

voluntary health advisory. The second phase of the study involved neurologic testing of 

all study participants who had total mercury levels in hair greater than 7.5 Fg/g. Study 

participants were identified by using special targeted screenings, mailings to residents, 

postings and multi-media advertisements of the study throughout the Everglades region, 

and direct discussions with people fishing along the canals and waterways in the 

contaminated areas. The contaminated areas were identified by the interviewers and longterm Everglade residents. Of a total of 1,794 individuals sampled, 405 individuals were 

eligible to participate in the study because they had consumed fish or wildlife from the 

Everglades at least once per month in the last 3 months of the study period. The majority 

of the eligible participants (> 93 percent) were either subsistence fishermen, Everglade 

residents, or both. Of the total eligible participants, 55 individuals refused to participate 

in the survey. Useable data were obtained from 330 respondents ranging in age from 10­

81 years of age (mean age 39 years ± 18.8) (U.S. DHHS, 1995). Respondents were 

administered a three page questionnaire from which demographic information, fishing and 

eating habits, and other variables were obtained (U.S. DHHS, 1995). 

Table 10-60 shows the ranges, means, and standard deviations of selected 

characteristics by subgroups of the survey population. Sixty-two percent of the 

respondents were male with a slight preponderance of black individuals (43 percent white, 

46 percent black non-Hispanic, and 11 percent Hispanic) (Table 10-60). Most of the 

respondents reported earning an annual income of $15,000 or less per family before taxes 

(U.S. DHHS, 1995). The mean number of years fished along the canals by the 

respondents was 15.8 years with a standard deviation of 15.8. The mean number of times 

per week fish consumers reported eating fish over the last 6 months and last month of the 

survey period was 1.8 and 1.5 per week with a standard deviation of 2.5 and 1.4, 

respectively (Table 10-60). Table 10-60 also indicates that 71 percent of the respondents 

reported knowing about the mercury health advisories. Of those who were aware, 26 

percent reported that they had lowered their consumption of fish caught in the Everglades 

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while the rest (74 percent) reported no change in consumption patterns (U.S. DHHS, 

1995). 

A limitation of this study is that fish intake rates (g/day) were not reported. Another 

limitation is that the survey was site limited, and, therefore, not representative of the U.S. 

population. An advantage of this study is that it is one of the few studies targeting 

subsistence fishermen. 

10.6. KEY FRESHWATER RECREATIONAL STUDIES 

West et al. (1989) - Michigan Sport Anglers Fish Consumption Survey, 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 recording respondents’ fish intake over a seven day period and a usual 

frequency component. For the short-term component, respondents were asked to identify 

all household members and list all fish meals consumed by each household member 

during the past seven days. The source of the fish for each meal was requested (selfcaught, gift, market, or restaurant). Respondents were asked to categorize serving size 

by comparison with pictures of 8 oz. fish portions; serving sizes could be designated as 

either “about the same size”, “less”, or “more” than the 8 oz. picture. 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 come 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 among individuals receiving 

questionnaires. 

In the analysis of the survey data by West et. al. (1989), the authors did not attempt 

to generate the distribution of recreationally caught fish intake in the survey population. 

EPA obtained the raw data of this survey for the purpose of generating fish intake 

distributions and other specialized analyses. 

As described elsewhere in this handbook, percentiles of the distribution of average 

daily intake reflective of long-term consumption patterns can not in general be estimated 

using short-term (e.g., one week) data. Such data can be used to estimate mean average 

daily intake rates (reflective of short or long term consumption); in addition, short term 

data can serve to validate estimates of usual intake based on longer recall. 

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EPA first analyzed the short term data with the intent of estimating mean fish intake 

rates. In order to compare these results with those based on usual intake, only 

respondents with information on both short term and usual intake were included in this 

analysis. For the analysis of the short term data, EPA modified the serving size weights 

used by West et al. (1989), which were 5, 8 and 10 oz., respectively, for portions that were 

less, about the same, and more than the 8 oz. picture. EPA examined the percentiles of 

the distribution of fish meal sizes reported in Pao et al. (1982) derived from the 1977-1978 

USDA National Food Consumption Survey and observed that a lognormal distribution 

provided a good visual fit to the percentile data. Using this lognormal distribution, the 

mean values for serving sizes greater than 8 oz. and for serving sizes at least 10 percent 

greater than 8 oz. were determined. In both cases a serving size of 12 oz. was consistent 

with the Pao et al. (1982) distribution. The weights used in the EPA analysis then were 

5, 8, and 12 oz. for fish meals described as less, about the same, and more than the 8 oz. 

picture, respectively. It should be noted that the mean serving size from Pao et al. (1982) 

was about 5 oz., well below the value of 8 oz. most commonly reported by respondents in 

the West et al. (1989) survey. 

Table 10-61 displays the mean number of total and recreational fish meals for each 

household member 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 on both a grams/day and grams/kg body weight/day basis. 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 survey 

respondents (i.e., licensed anglers) and about 84 percent of respondents who fished in the 

prior year reported some household recreational fish consumption. 

The EPA analysis next attempted to use the short term data to validate the usual 

intake data. West et al. (1989) asked the main respondent in each household to provide 

estimates of their usual frequency of fishing and eating fish, by season, during the 

previous year. The survey provides a series of frequency categories for each season and 

the respondent was asked to check the appropriate range. The ranges used for all 

questions were: almost daily, 2-4 times a week, once a week, 2-3 times a month, once a 

month, less often, none, and don’t know. For quantitative analysis of the data it is 

necessary to convert this categorical information into numerical frequency values. As 

some of the ranges are relatively broad, the choice of conversion values can have some 

effect on intake estimates. In order to obtain optimal values, the usual fish eating 

frequency reported by respondents for the season during which the questionnaire was 

completed was compared to the number of fish meals reportedly consumed by 

respondents over the seven day short-term recall period. The results of these 

comparisons are displayed in Table 10-62; it shows that, on average, there is general 

agreement between estimates made using one year recall and estimates based on seven 

day recall. The average number of meals (1.96/week) was at the bottom of the range for 

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the most frequent consumption group with data (2-4 meals/week). In contrast, for the lower 

usual frequency categories, the average number of meals was at the top, or exceeded the 

top of category range. This suggests some tendency for relatively infrequent fish eaters 

to underestimate their usual frequency of fish consumption. The last column of the table 

shows the estimated fish eating frequency per week that was selected for use in making 

quantitative estimates of usual fish intake. These values were guided by the values in the 

second column, except that frequency values that were inconsistent with the ranges 

provided to respondents in the survey were avoided. 

Using the four seasonal fish eating frequencies provided by respondents and the 

above conversions for reported intake frequency, EPA estimated the average number of 

fish meals per week for each respondent. This estimate, as well as the analysis above, 

pertain to the total number of fish meals eaten (in Michigan) regardless of the source of 

the fish. Respondents were not asked to provide a seasonal breakdown for eating 

frequency of recreationally caught fish; rather, they provided an overall estimate for the 

past year of the percent of fish they ate that was obtained from different sources. EPA 

estimated the annual frequency of recreationally caught fish meals by multiplying the 

estimated total number of fish meals by the reported percent of fish meals obtained from 

recreational sources; recreational sources were defined as either self caught or a gift from 

family or friends. 

The usual intake component of the survey did not include questions about the usual 

portion size for fish meals. In order to estimate usual fish intake, a portion size of 8 oz. 

was applied (the majority of respondents reported this meal size in the 7 day recall data). 

Individual body weight data were used to estimate intake on a g/kg-day basis. The fish 

intake distribution estimated by EPA is displayed in Table 10-63. 

The distribution shown in Table 10-63 is based on respondents who consumed 

recreational caught fish. As mentioned above, these represent 75 percent of all 

respondents and 84 percent of respondents who reported having fished in the prior year. 

Among this latter population, the mean recreational fish intake rate is 14.4*0.84=12.1 

g/day; the value of 38.7 g/day (95th percentile among consumers) corresponds to the 

95.8th percentile of the fish intake distribution in this (fishing) population. 

The advantages of this data set and analysis are that the survey was relatively large 

and contained both short-term and usual intake data. The presence of short term data 

allowed validation of the usual intake data which was based on long term recall; thus, 

some of the problems associated with surveys relying on long term recall are mitigated 

here. 

The response rate of this survey, 47 percent, was relatively low. In addition, the 

usual fish intake distribution generated here employed a constant fish meal size, 8 oz.. 

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Although use of this value as an average meal size was validated by the short-term recall 

results, the use of a constant meal size, even if correct on average, may seriously reduce 

the variation in the estimated fish intake distribution. 

This study was conducted in the winter and spring months of 1988. This period does 

not include the summer months when peak fishing activity can be anticipated, leading to 

the possibility that intake results based on the 7 day recall data may understate 

individuals’ usual (annual average) fish consumption. A second survey by West et al. 

(1993) gathered diary data on fish intake for respondents spaced over a full year. 

However, this later survey did not include questions about usual fish intake and has not 

been reanalyzed here. The mean recreational fish intake rates derived from the short term 

and usual components were quite similar, however, 14.0 versus 14.4 g/day. 

Chemrisk (1992) - Consumption of Freshwater Fish by Maine Anglers - Chemrisk 

conducted a study to characterize the rates of freshwater fish consumption among Maine 

residents (Chemrisk, 1992; Ebert et al., 1993). Since the only dietary source of local 

freshwater fish is recreational fish, the anglers in Maine were chosen as the survey 

population. The survey was designed to gather information on the consumption of fish 

caught by anglers from flowing (rivers and streams) and standing (lakes and ponds) water 

bodies. Respondents were asked to recall the frequency of fishing trips during the 1989­

1990 ice-fishing season and the 1990 open water season, the number of fish species 

caught during both seasons, and estimate the number of fish consumed from 15 fish 

species. The respondents were also asked to describe the number, species, and average 

length of each sport-caught fish consumed that had been gifts from other members of their 

households or other household. The weight of fish consumed by anglers was calculated 

by first multiplying the estimated weight of the fish by the edible fraction, and then dividing 

this product by the number of intended consumers. Species specific regression equations 

were utilized to estimate weight from the reported fish length. The edible fractions used 

were 0.4 for salmon, 0.78 for Atlantic smelt, and 0.3 for all other species (Ebert et al., 

1993).

A total of 2,500 prospective survey participants were randomly selected from a list of 

anglers licensed in Maine. The surveys were mailed in during October, 1990. Since this 

was before the end of the open fishing season, respondents were also asked to predict 

how many more open water fishing trips they would undertake in 1990. 

Chemrisk (1992) and Ebert et al. (1993) calculated distributions of freshwater fish 

intake for two populations, “all anglers” and “consuming anglers”. All anglers were 

defined as licensed anglers who fished during either the 1989-1990 ice-fishing season or 

the 1990 open-water season (consumers and non-consumers) and licensed anglers who 

did not fish but consumed freshwater fish caught in Maine during these seasons. 

“Consuming anglers” were defined as those anglers who consumed freshwater fish 

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obtained from Maine sources during the 1989-1990 ice fishing or 1990 open water fishing 

season. In addition, the distribution of fish intake from rivers and streams was also 

calculated for two populations, those fishing on rivers and streams (“river anglers”) and 

those consuming fish from rivers and streams (“consuming river anglers”). 

A total of 1,612 surveys were returned, giving a response rate of 64 percent; 1,369 

(85 percent) of the 1,612 respondents were included in the “all angler” population and 

1,053 (65 percent) were included in the “consuming angler” population. Freshwater fish 

intake distributions for these populations are presented in Table 10-64. The mean and 

95th percentile was 5.0 g/day and 21.0 g/day, respectively, for “ all anglers,” and 6.4 g/day 

and 26.0 g/day, respectively, for “consuming anglers.” Table 10-64 also presents intake 

distributions for fish caught from rivers and streams. Among “river anglers” the mean and 

95th percentiles were 1.9 g/day and 6.2 g/day, respectively, while among “consuming river 

anglers” the mean was 3.7 g/day and the 95th percentile was 12.0 g/day. Table 10-65 

presents fish intake distributions by ethnic group for consuming anglers. The highest 

mean intake rates reported are for Native Americans (10 g/day) and French Canadians 

(7.4 g/day). Because there was a low number of respondents for Hispanics, Asian/Pacific 

Islanders, and African Americans, intake rates within these subgroups were not calculated 

(Chemrisk, 1992).

The consumption, by species, of freshwater fish caught is presented in Table 10-66. 

The largest specie consumption was salmon from ice fishing (~292,000 grams); white 

perch (380,000 grams) for lakes and ponds; and Brooktrout (420,000 grams) for rivers and 

streams (Chemrisk, 1991). 

EPA obtained the raw data tapes from the marine anglers survey and performed 

some specialized analyses. One analysis involved examining the percentiles of the 

“resource utilization distribution” (this distribution was defined in Section 10.1). The 50th, 

or more generally the pth percentile of the resource utilization distribution, is defined as 

the consumption level such that p percent of the resource is consumed by individuals with 

consumptions below this level and 100-p percent by individuals with consumptions above 

this level. EPA found that 90 percent of recreational fish consumption was by individuals 

with intake rates above 3.1 g/day and 50 percent was by individuals with intakes above 20 

g/day. Those above 3.1 g/day make up about 30 percent of the “all angler” population and 

those above 20 g/day make up about 5 percent of this population; thus, the top 5 percent 

of the angler population consumed 50 percent of the recreational fish catch. 

EPA also performed an analysis of fish consumption among anglers and their 

families. This analysis was possible because the survey included questions on the 

number, sex, and age of each individual in the household and whether the individual 

consumed recreationally caught fish. The total population of licensed anglers in this 

survey and their household members was 4,872; the average household size for the 1,612 

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anglers in the survey was thus 3.0 persons. Fifty-six percent of the population was male 

and 30 percent was 18 or under. 

A total of 55 percent of this population was reported to consume freshwater 

recreationally caught fish in the year of the survey. The sex and ethnic distribution of the 

consumers was similar to that of the overall population. The distribution of fish intake 

among the overall household population, or among consumers in the household, can be 

calculated under the assumption that recreationally caught fish was shared equally among 

all members of the household reporting consumption of such fish (note this assumption 

was used above to calculate intake rates for anglers). With this assumption, the mean 

intake rate among consumers was 5.9 g/day with a median of 1.8 g/day and a 95th 

percentile of 23.1 g/day; for the overall population the mean was 3.2 g/day and the 95th 

percentile was 14.1 g/day. 

The results of this survey can be put into the context of the overall Maine population. 

The 1,612 anglers surveyed represent about 0.7 percent of the estimated 225,000 licensed 

anglers in Maine. It is reasonable to assume that licensed anglers and their families will 

have the highest exposure to recreationally caught freshwater fish. Thus, to estimate the 

number of persons in Maine with recreationally caught freshwater fish intake above, for 

instance, 6.5 g/day (the 80th percentile among household consumers in this survey), one 

can assume that virtually all persons came from the population of licensed anglers and 

their families. The number of persons above 6.5 g/day in the household survey population 

is calculated by taking 20 percent (i.e., 100 percent - 80 percent) of the consuming 

population in the survey; this number then is 0.2*(0.55*4872)=536. Dividing this number 

by the sampling fraction of 0.007 (0.7 percent) gives about 77,000 persons above 6.5 

g/day of recreational freshwater fish consumption statewide. The 1990 census showed the 

population of Maine to be 1.2 million people; thus the 77,000 persons above 6.5 g/day 

represent about 6 percent of the state’s population. 

Chemrisk (1992) reported that the fish consumption estimates obtained from the 

survey were conservative because of assumptions made in the analysis. The assumptions 

included: a 40 percent estimate as the edible portion of landlocked and Atlantic salmon; 

inclusion of the intended number of future fishing trips and an assumption that the average 

success and consumption rates for the individual angler during the trips already taken 

would continue through future trips. The data collected for this study were based on recall 

and self-reporting which may have resulted in a biased estimate. The social desirability 

of the sport and frequency of fishing are also bias contributing factors; successful anglers 

are among the highest consumers of freshwater fish (Chemrisk, 1992). Over reporting 

appears to be correlated with skill level and the importance of the activity to the individual; 

it is likely that the higher consumption rates may be substantially overstated (Chemrisk, 

1992). Additionally, fish advisories are in place in these areas and may affect the rate of 

fish consumption among anglers. The survey results showed that in 1990, 23 percent of 

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all anglers consumed no freshwater fish, and 55 percent of the river anglers ate no 

freshwater fish. An advantage of this study is that it presents area-specific consumption 

patterns and the sample size is rather large. 

West et al. (1993) - Michigan Sport Anglers Fish Consumption Study, 1991-1992 ­

This survey, financed by the Michigan Great Lakes Protection Fund, was a follow-up to the 

earlier 1989 Michigan survey described previously. The major purpose of 1991-1992 

survey was to provide short-term recall data of recreational fish consumption over a full 

year period; the 1989 survey, in contrast, was conducted over only a half year period 

(West et al., 1993). 

This survey was similar in design to the 1989 Michigan survey. A sample of 7,000 

persons with Michigan fishing licenses was drawn and surveys were mailed in 2-week 

cohorts over the period January, 1991 to January, 1992. Respondents were asked to 

report detailed fish consumption patterns during the preceding seven days, as well as 

demographic information; they were also asked if they currently eat fish. Enclosed with 

the survey were pictures of about a half pound of fish. Respondents were asked to 

indicate whether reported consumption at each meal was more, less or about the same as 

the picture. Based on responses to this question, respondents were assumed to have 

consumed 10, 5 or 8 ounces of fish, respectively. 

A total of 2,681 surveys were returned. West et al. (1993) calculated a response rate 

for the survey of 46.8 percent; this was derived by removing from the sample those 

respondents who could not be located or who did not reside in Michigan for at least six 

months. 

Of these 2,681 respondents, 2,475 (93 percent) reported that they currently eat fish; 

all subsequent analyses were restricted to the current fish eaters. The mean fish 

consumption rates were found to be 16.7 g/day for sport fish and 26.5 g/day for total fish 

(West et al., 1993). Table 10-67 shows mean sport-fish consumption rates by 

demographic categories. Rates were higher among minorities, people with low income, 

and people residing in smaller communities. Consumption rates in g/day were also higher 

in males than in females; however, this difference would likely disappear if rates were 

computed on a g/kg-day basis. 

West et al. (1993) estimated the 80th percentile of the survey fish consumption 

distribution. More extensive percentile calculations were performed by U.S. EPA (1995) 

using the raw data from the West et al. (1993) survey and calculated 50th, 90th, and 95th 

percentiles. However, since this survey only measured fish consumption over a short (one 

week) interval, the resulting distribution will not be indicative of the long-term fish 

consumption distribution and the upper percentiles reported from the EPA analysis will 

likely considerably overestimate the corresponding long term percentiles. The overall 95th 

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percentile calculated by U.S. EPA (1995) was 77.9; this is about double the 95th percentile 

estimated using year long consumption data from the 1989 Michigan survey. 

The limitations of this survey are the relatively low response rate and the fact that 

only three categories were used to assign fish portion size. The main study strengths were 

its relatively large size and its reliance on short-term recall. 

Connelly et al. (1996) - Sportfish Consumption Patterns of Lake Ontario Anglers and 

the Relationship to Health Advisories, 1992 - The objectives of this study were to provide 

accurate estimates of fish consumption (overall and sport caught) among Lake Ontario 

anglers and to evaluate the effect of Lake Ontario health advisory recommendations 

(Connelly et al., 1996). To target Lake Ontario anglers, a sample of 2,500 names was 

randomly drawn from 1990-1991 New York fishing license records for licenses purchased 

in six counties bordering Lake Ontario. Participation in the study was solicited by mail with 

potential participants encouraged to enroll in the study even if they fished infrequently or 

consumed little or no sport caught fish. The survey design involved three survey 

techniques including a mail questionnaire asking for 12 month recall of 1991 fishing trips 

and fish consumption, self-recording information in a diary for 1992 fishing trips and fish 

consumption, periodic telephone interviews to gather information recorded in the diary and 

a final telephone interview to determine awareness of health advisories (Connelly et al., 

1996).

Participants were instructed to record in the diary the species of fish eaten, meal size, 

method by which fish was acquired (sport-caught or other), fish preparation and cooking 

techniques used and the number of household members eating the meal. Fish meals were 

defined as finfish only. Meal size was estimated by participants by comparing their meal 

size to pictures of 8 oz. fish steaks and fillets on dinner plates. An 8 oz. size was assumed 

unless participants noted their meal size was smaller than 8 oz., in which case a 4 oz. size 

was assumed, or they noted it was larger than 8 oz., in which case a 12 oz. size was 

assumed. Participants were also asked to record information on fishing trips to Lake 

Ontario and species and length of any fish caught. 

From the initial sample of 2,500 license buyers, 1,993 (80 percent) were reachable 

by phone or mail and 1,410 of these were eligible for the study, in that they intended to fish 

Lake Ontario in 1992. A total of 1,202 of these 1,410, or 85 percent, agreed to participate 

in the study. Of the 1,202 participants, 853 either returned the diary or provided diary 

information by telephone. Due to changes in health advisories for Lake Ontario which 

resulted in less Lake Ontario fishing in 1992, only 43 percent, or 366 of these 853 persons 

indicated that they fished Lake Ontario during 1992. The study analyses summarized 

below concerning fish consumption and Lake Ontario fishing participation are based on 

these 366 persons. 

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Anglers who fished Lake Ontario reported an average of 30.3 (S.E. = 2.3) fish meals 

per person from all sources in 1992; of these meals 28 percent were sport caught 

(Connelly et al., 1996). Less than 1 percent ate no fish for the year and 16 percent ate no 

sport caught fish. The mean fish intake rate from all sources was 17.9 g/day and from sport 

caught sources was 4.9 g/day. Table 10-68 gives the distribution of fish intake rates from 

all sources and from sport caught fish. The median rates were 14.1 g/day for all sources 

and 2.2 g/day for sport caught; the 95th percentiles were 42.3 g/day and 17.9 g/day for all 

sources and sport caught, respectively. As seen in Table 10-69, statistically significant 

differences in intake rates were seen across age and residence groups, with residents 

of large cities and younger people having lower intake rates on average. 

The main advantage of this study is the diary format. This format provides more 

accurate information on fishing participation and fish consumption, than studies based on 

1 year recall (Ebert et al., 1993). However, a considerable portion of diary respondents 

participated in the study for only a portion of the year and some errors may have been 

generated in extrapolating these respondents’ results to the entire year (Connelly et al.,

1996). In addition, the response rate for this study was relatively low, 853 of 1,410 eligible 

respondents, or 60 percent, which may have engendered some non-response bias. 

The presence of health advisories should be taken into account when evaluating the 

intake rates observed in this study. Nearly all respondents (>95 percent) were aware of 

the Lake Ontario health advisory. This advisory counseled to eat none of 9 fish species 

from Lake Ontario and to eat no more than one meal per month of another 4 species. In 

addition, New York State issues a general advisory to eat no more than 52 sport caught 

fish meals per year. Among participants who fished Lake Ontario in 1992, 32 percent said 

they would eat more fish if health advisories did not exist. A significant fraction of 

respondents did not totally adhere to the fish advisory; however, 36 percent of 

respondents, and 72 percent of respondents reporting Lake Ontario fish consumption, ate 

at least one species of fish over the advisory limit. Interestingly, 90 percent of those 

violating the advisory reported that they believed they were eating within advisory limits. 

10.7. RELEVANT FRESHWATER RECREATIONAL STUDIES 

Fiore et al. (1989) - Sport Fish Consumption and Body Burden Levels of Chlorinated 

Hydrocarbons: A Study of Wisconsin Anglers. This survey, reported by Fiore et al. (1989), 

was conducted to assess sociodemographic factors and sport fishing habits of anglers, to 

evaluate anglers’ comprehension of and compliance with the Wisconsin Fish Consumption 

Advisory, to measure body burden levels of PCBs and DDE through analysis of blood 

serum samples and to examine the relationship between body burden levels and 

consumption of sport-caught fish. The survey targeted all Wisconsin residents who had 

purchased fishing or sporting licenses in 1984 in any of 10 pre-selected study counties. 

These counties were chosen in part based on their proximity to water bodies identified in 

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Wisconsin fish advisories. A total of 1,600 anglers were sent survey questionnaires during 

the summer of 1985. 

The survey questionnaire included questions about fishing history, locations fished, 

species targeted, kilograms caught for consumption, overall fish consumption (including 

commercially caught) and knowledge of fish advisories. The recall period was one year. 

A total of 801 surveys were returned (50 percent response rate). Of these, 601 (75 

percent) were from males and 200 from females; the mean age was 37 years. Fiore et al. 

(1989) reported that the mean number of fish meals for 1984 for all respondents was 18 

for sport-caught meals and 24 for non-sport caught meals. Fiore et al. (1989) assumed 

that each fish meal consisted of 8 ounces (227 grams) of fish to generate means and 

percentiles of fish intake. The reported per-capita intake rate of sport-caught fish was 11.2 

g/day; among consumers, who comprised 91 percent of all respondents, the mean sportcaught fish intake rate was 12.3 g/day and the 95th percentile was 37.3 g/day. The mean 

daily fish intake from all sources (both sport caught and commercial) was 26.1 g/day with 

a 95th percentile of 63.4 g/day. The 95th percentile of 37.3 g/day of sport caught fish 

represents 60 fish meals per year; 63.4 g/day (the 95th percentile of total fish intake) 

represents 102 fish meals per year. 

Fiore et al. (1989) assumed a (constant) meal size of 8 ounces (227 grams) of fish 

which may over-estimate average meal size. Pao et al. (1982), using data from the 1977­

78 USDA NFCS, reported an average fish meal size of slightly less than 150 grams for 

adult males. EPA obtained the raw data from this study and calculated the distribution of 

the number of sport-caught fish meals and the distribution of fish intake rates (using 150 

grams/meal); these distributions are presented in Table 10-70. With this average meal 

size, the per-capita estimate is 7.4 g/day. 

This study is limited in its ability to accurately estimate intake rates because of the 

absence of data on weight of fish consumed. Another limitation of this study is that the 

results are based on one year recall, which may tend to over-estimate the number of 

fishing trips (Ebert et al.,1993). In addition, the response rate was rather low (50 percent). 

Connelly et al. (1992) - Effects of Health Advisory and Advisory Changes on Fishing 

Habits and Fish Consumption in New York Sport Fisheries - Connelly et al. (1992) 

conducted a study to assess the awareness and knowledge of New York anglers about 

fishing advisories and contaminants found in fish and their fishing and fish consuming 

behaviors. The survey sample consisted of 2,000 anglers with New York State fishing 

licenses for the year beginning October 1, 1990 through September 30, 1991. A 

questionnaire was mailed to the survey sample in January, 1992. The questionnaire was 

designed to measure catch and consumption of fish, as well as methods of fish preparation 

and knowledge of and attitudes towards health advisories (Connelly et al., 1992). The 

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survey adjusted response rate was 52.8 percent (1,030 questionnaires were completed 

and 51 were not deliverable). 

The average and median number of fishing days per year were 27 and 15 days 

respectively (Connelly et al. 1992). The mean number of sport-caught fish meals was 11. 

About 25 percent of anglers reported that they did not consume sport-caught fish. 

Connelly et al. (1992) found that 80 percent of anglers statewide did not eat listed 

species or ate them within advisory limits and followed the 1 sport-caught fish meal per 

week recommended maximum. The other 20 percent of anglers exceeded the advisory 

recommendations in some way; 15 percent ate listed species above the limit and 5 percent 

ate more than one sport caught meal per week. 

Connelly et al. (1992) found that respondents eating more than one sport-caught 

meal per week were just as likely as those eating less than one meal per week to know the 

recommended level of sport-caught fish consumption, although less than 1/3 in each group 

knew the level. An estimated 85 percent of anglers were aware of the health advisory. 

Over 50 percent of respondents said that they made changes in their fishing or fish 

consumption behaviors in response to health advisories. 

The advisory included a section on methods that can be used to reduce contaminant 

exposure. Respondents were asked what methods they used for fish cleaning and 

cooking. Summary results on preparation and cooking methods are presented in Section 

10.9 and in Appendix 10B. 

A limitation of this study with respect to estimating fish intake rates is that only the 

number of sport-caught meals was ascertained, not the weight of fish consumed. The fish 

meal data can be converted to an intake rate (g/day) by assuming a value for a fish meal 

such as that from Pao et al. (1982) (about 150 grams as the average amount of fish 

consumed per eating occasion for adult males - males comprised 88 percent of 

respondents in the current study). Using 150 grams/meal the mean intake rate among the 

angler population would be 4.5 g/day; note that about 25 percent of this population 

reported no sport-caught fish consumption. 

The major focus of this study was not on consumption, per se, but on the knowledge 

of and impact of fish health advisories; Connelly et al. (1992) provides important 

information on these issues. 

Hudson River Sloop Clearwater, Inc. (1993) - Hudson River Angler Survey - Hudson 

River Sloop Clearwater, Inc. (1993) conducted a survey of adherence to fish consumption 

health advisories among Hudson River anglers. All fishing has been banned on the upper 

Hudson River where high levels of PCB contamination are well documented; while 

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voluntary recreational fish consumption advisories have been issued for areas south of the 

Troy Dam (Hudson River Sloop Clearwater, Inc., 1993). 

The survey consisted of direct interviews with 336 shore-based anglers between the 

months of June and November 1991, and April and July 1992. Socio-demographic 

characteristics of the respondents are presented in Table 10-71. The survey sites were 

selected based on observations of use by anglers, and legal accessibility. The selected 

sites included upper, mid-, and lower Hudson River sites located in both rural and urban 

settings. The interviews were conducted on weekends and weekdays during morning, 

midday, and evening periods. The anglers were asked specific questions concerning: 

fishing and fish consumption habits; perceptions of presence of contaminants in fish; 

perceptions of risks associated with consumption of recreationally caught fish; and 

awareness of, attitude toward, and response to fish consumption advisories or fishing 

bans. 

Approximately 92 percent of the survey respondents were male. The following 

statistics were provided by Hudson River Sloop Clearwater, Inc. (1993). The most 

common reason given for fishing was for recreation or enjoyment. Over 58 percent of 

those surveyed indicated that they eat their catch. Of those anglers who eat their catch, 

48 percent reported being aware of advisories. Approximately 24 percent of those who 

said they currently do not eat their catch, have done so in the past. Anglers were more 

likely to eat their catch from the lower Hudson areas where health advisories, rather than 

fishing bans, have been issued. Approximately 94 percent of Hispanic Americans were 

likely to eat their catch, while 77 percent of African Americans and 47 percent of 

Caucasian Americans intended to eat their catch. Of those who eat their catch, 87 percent 

were likely to share their meal with others (including women of childbearing age, and 

children under the age of fifteen). 

For subsistence anglers, more low-income than upper income anglers eat their catch 

(Hudson River Sloop Clearwater, Inc., 1993). Approximately 10 percent of the 

respondents stated that food was their primary reason for fishing; this group is more likely 

to be in the lowest per capita income group (Hudson River Sloop Clearwater, Inc., 1993). 

The average frequency of fish consumption reported was just under one (0.9) meal 

over the previous week, and three meals over the previous month. Approximately 35 

percent of all anglers who eat their catch exceeded the amounts recommended by the New 

York State health advisories. Less than half (48 percent) of all the anglers interviewed 

were aware of the State health advisories or fishing bans. Only 42 percent of those 

anglers aware of the advisories have changed their fishing habits as a result. 

The advantages of this study include: in-person interviews with 95 percent of all 

anglers approached; field-tested questions designed to minimize interviewer bias; and 

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candid responses concerning consumption of fish from contaminated waters. The 

limitations of this study are that specific intake amounts are not indicated, and that only 

shore-based anglers were interviewed. 

10.8. NATIVE AMERICAN FRESHWATER STUDIES 

Wolfe and Walker (1987) - Subsistence Economies in Alaska: Productivity, 

Geography, and Development Impacts - Wolfe and Walker (1987) analyzed a dataset from 

98 communities for harvests of fish, land mammals, marine mammals, and other wild 

resources. The analysis was performed to evaluate the distribution and productivity of 

subsistence harvests in Alaska during the 1980s. Harvest levels were used as a measure 

of productivity. Wolfe and Walker (1987) defined harvest to represent a single year's 

production from a complete seasonal round. The harvest levels were derived primarily 

from a compilation of data from subsistence studies conducted between 1980 to 1985 by 

various researchers in the Alaska Department of Fish and Game, Division of Subsistence. 

Of the 98 communities studied, four were large urban population centers and 94 were 

small communities. The harvests for these latter 94 communities were documented 

through detailed retrospective interviews with harvesters from a sample of households 

(Wolfe and Walker, 1987). Harvesters were asked to estimate the quantities of a 

particular species that were harvested and used by members of that household during the 

previous 12-month period. Wolfe and Walker (1987) converted harvests to a common unit 

for comparison, pounds dressed weight per capita per year, by multiplying the harvests of 

households within each community by standard factors converting total pounds to dressed 

weight, summing across households, and then dividing by the total number of household 

members in the household sample. Dressed weight varied by species and community but 

in general was 70 to 75 percent of total fish weight; dressed weight for fish represents that 

portion brought into the kitchen for use (Wolfe and Walker, 1987). 

Harvests for the four urban populations were developed from a statewide data set 

gathered by the Alaska Department of Fish and Game Divisions of Game and Sports Fish. 

Urban sport fish harvest estimates were derived from a survey that was mailed to a 

randomly selected statewide sample of anglers (Wolfe and Walker, 1987). Sport fish 

harvests were disaggregated by urban residency and the dataset was analyzed by 

converting the harvests into pounds and dividing by the 1983 urban population. 

For the overall analysis, each of the 98 communities was treated as a single unit of 

analysis and the entire group of communities was assumed to be a sample of all 

communities in Alaska (Wolfe and Walker, 1987). Each community was given equal 

weight, regardless of population size. Annual per capita harvests were calculated for 

each community. For the four urban centers, fish harvests ranged from 5 to 21 pounds 

per capita per year (6.2 g/day to 26.2 g/day). 

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The range for the 94 small communities was 25 to 1,239 pounds per capita per year 

(31 g/day to 1,541 g/day). For these 94 communities, the median per capita fish harvest 

was 130 pounds per year (162 g/day). In most (68 percent) of the 98 communities 

analyzed, resource harvests for fish were greater than the harvests of the other wildlife 

categories (land mammal, marine mammal, and other) combined. 

The communities in this study were not made up entirely of Alaska Natives. For 

roughly half the communities, Alaska Natives comprised 80 percent or more of the 

population, but for about 40 percent of the communities they comprised less than 50 

percent of the population. Wolfe and Walker (1987) performed a regression analysis which 

showed that the per capita harvest of a community tended to increase as a function of the 

percentage of Alaska Natives in the community. Although this analysis was done for total 

harvest (i.e., fish, land mammal, marine mammal and others) the same result should hold 

for fish harvest since fish harvest is highly correlated with total harvest. 

A limitation of this report is that it presents (per-capita) harvest rates as opposed to 

individual intake rates. Wolfe and Walker (1987) compared the per capita harvest rates 

reported to the results for the household component of the 1977-1978 USDA National 

Food Consumption Survey (NFCS). The NFCS showed that about 222 pounds of meat, 

fish, and poultry were purchased and brought into the household kitchen for each person 

each year in the western region of the United States. This contrasts with a median total 

resource harvest of 260 lbs/yr in the 94 communities studied. This comparison, and the 

fact that Wolfe and Walker (1987) state that “harvests represent that portion brought into 

the kitchen for use,” suggest that the same factors used to convert household consumption 

rates in the NFCS to individual intake rates can be used to convert per capita harvest rates 

to individual intake rates. In Section 10.3, a factor of 0.5 was used to convert fish 

consumption from household to individual intake rates. Applying this factor, the median 

per capita individual fish intake in the 94 communities would be 81 g/day and the range 

15.5 to 770 g/day.

A limitation of this study is that the data were based on 1-year recall from a mailed 

survey. An advantage of the study is that it is one of the few studies that present fish 

harvest patterns for subsistence populations. 

AIHC (1994) - Exposure Factors Sourcebook - The Exposure Factors Sourcebook 

(AIHC, 1994) provides data for non-marine fish intake consistent with this document. 

However, the total fish intake rate recommended in AIHC (1994) is approximately 40 

percent lower than that in this document. The fish intake rates presented in this handbook 

are based on more recent data from USDA CSFII (1989-1991). AIHC (1994) presents 

probability distributions in grams fish per kilogram of body weight for fish consumption 

based on data from U.S. EPA Guidance Manual, Assessing Human Health Risks from 

Chemically Contaminated Fish and Shellfish (U.S. EPA, 1989b). The @Risk formula is 

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Chapter 10 - Intake of Fish and Shellfish 

provided for direct use in the @Risk simulation software. The @Risk formula was 

provided for the distributions that were provided for the ingestion of freshwater finfish, 

saltwater finfish, and fish (unspecified) in the U.S. general population, children ages 1 to 

6 years, and males ages 13 years and above. Distributions were also provided for 

saltwater finfish ingestion in the general population and for females and for males 13 years 

of age and older. Distributions for shellfish ingestion were provided for the general 

population, children ages 1 to 6 years, and for males and females 13 years of age and 

above. Additionally, distributions for “unspecified” fish ingestion were presented for the 

above mentioned populations. 

The Sourcebook has been classified as a relevant rather than key study because it 

was not the primary source for the data used to make recommendations in this document. 

The Sourcebook is very similar to this document in the sense that it summarizes exposure 

factor data and recommends values. Therefore, it can be used as an alternative 

information source on fish intake. 

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 - CRITFC (1994) conducted a fish consumption survey among four Columbia 

River Basin Indian tribes during the fall and winter of 1991-1992. The target population 

included all adult tribal members who lived on or near the Yakama, Warm Springs, 

Umatilla or Nez Perce reservations. The survey was based on a stratified random 

sampling design where respondents were selected from patient registration files at the 

Indian Health Service. Interviews were performed in person at a central location on the 

member’s reservation. 

Information requested included annual and seasonal numbers of fish meals, average 

serving size per fish meal, species and part(s) of fish consumed, preparation methods, 

changes in patterns of consumption over the last 20 years and during ceremonies and 

festivals, breast feeding practices and 24 hour dietary recall (CRITFC, 1994). Foam 

sponge food models approximating four, eight, and twelve ounce fish fillets were provided 

to help respondents estimate average fish meal size. Fish intake rates were calculated 

by multiplying the annual frequency of fish meals by the average serving size per fish 

meal. 

The study was designed to give essentially equal sample sizes for each tribe. 

However, since the population sizes of the tribes were highly unequal, it was necessary 

to weight the data (in proportion to tribal population size) in order that the survey results 

represent the overall population of the four tribes. Such weights were applied to the 

analysis of adults; however, because the sample size for children was considered small, 

only an unweighted analysis was performed for this population (CRITFC, 1994). 

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The survey respondents consisted of 513 tribal members, 18 years old and above. 

Of these, 58 percent were female and 59 percent were under 40 years old. In addition, 

information for 204 children 5 years old and less was provided by the participating adult 

respondent. The overall response rate was 69 percent. 

The results of the survey showed that adults consumed an average of 1.71 fish 

meals/week and had an average intake of 58.7 grams/day (CRITFC, 1994). Table 10-72 

shows the adult fish intake distribution; the median was between 29 and 32 g/day and the 

95th percentile about 170 g/day. A small percentage (7 percent) of respondents indicated 

that they were not fish consumers. Table 10-73 shows that mean intake was slightly 

higher in males than females (63 g/d versus 56 g/d) and was higher in the over 60 years 

age group (74.4 g/d) than in the 18-39 years (57.6 g/d) or 40-59 years (55.8 g/d) age 

groups. Intake also tended to be higher among those living on the reservation. The mean 

intake for nursing mothers, 59.1 g/d, was similar to the overall mean intake. 

A total of 49 percent of respondents 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 selfharvesting, 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). 

The analysis of seasonal intake showed that May and June tended to be high 

consumption months and December and January low consumption months. The mean 

adult intake rate for May and June was 108 g/d while the mean intake rate for December 

and January was 30.7 g/d. Salmon was the species eaten by the highest number of 

respondents (92 percent) followed by trout (70 percent), lamprey (54 percent), and smelt 

(52 percent). Table 10-74 gives the fish intake distribution for children under 5 years of 

age. The mean intake rate was 19.6 g/d and the 95th percentile was approximately 70 g/d. 

The authors noted that some non-response bias may have occurred in the survey 

since respondents were more likely to live near the reservation and were more likely to be 

female than non-respondents. In addition, they hypothesized that non fish 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 

report 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 

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Chapter 10 - Intake of Fish and Shellfish 

respondents provided the same information for their children as for themselves, thereby 

the reliability of some of these data is questioned. 

Although the authors have noted these limitations, this study does present information 

on fish consumption patterns and habits for a Native American subpopulation. It should 

be noted that the number of surveys that address subsistence subpopulations is very 

limited. 

Peterson et al. (1994) - Fish Consumption Patterns and Blood Mercury Levels in 

Wisconsin Chippewa Indians - Peterson et al. (1994) investigated the extent of exposure 

of methylmercury to Chippewa Indians living on a Northern Wisconsin reservation who 

consume fish caught in northern Wisconsin lakes. The lakes in northern Wisconsin are 

known to be contaminated with mercury and the Chippewa have a reputation for high fish 

consumption (Peterson et al., 1994). The Chippewa Indians fish by the traditional method 

of spearfishing. Spearfishing (for walleye) occurs for about two weeks each spring after 

the ice breaks, and although only a small number of tribal members participate in it, the 

spearfishing harvest is distributed widely within the tribe by an informal distribution network 

of family and friends and through traditional tribal feasts (Peterson et al., 1994). 

Potential survey participants, 465 adults, 18 years of age and older, were randomly 

selected from the tribal registries (Peterson et al., 1994). Participants were asked to 

complete a questionnaire describing their routine fish consumption and, more extensively, 

their fish consumption during the two previous months. They were also asked to give a 

blood sample that would be tested for mercury content. The survey was carried out in May 

1990. A follow-up survey was conducted for a random sample of 75 non-respondents (80 

percent were reachable), and their demographic and fish consumption patterns were 

obtained. Peterson et al. (1994) reported that the non-respondents' socioeconomic and 

fish consumption were similar to the respondents. 

A total of 175 of the original random sample (38 percent) participated in the study. 

In addition, 152 nonrandomly selected participants were surveyed and included in the data 

analysis; these participants were reported by Peterson et al. (1994) to have fish 

consumption rates similar to those of the randomly selected participants. Results from the 

survey showed that fish consumption varied seasonally, with 50 percent of the 

respondents reporting April and May (spearfishing season) as the highest fish 

consumption months (Peterson et al., 1994). Table 10-75 shows the number of fish meals 

consumed per week during the last 2 months (recent consumption) before the survey was 

conducted and during the respondents’ peak consumption months grouped by gender, 

age, education, and employment level. During peak consumption months, males 

consumed more fish (1.9 meals per week) than females (1.5 meals per week), respondents 

under 35 years of age consumed more fish (1.8 meals per week) than respondents 35 

years of age and over (1.6 meals per week), and the unemployed consumed more fish (1.9 

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meals per week) than the employed (1.6 meals per week). During the highest fish 

consumption season (April and May), 50 percent of respondents reported eating one or 

less fish meals per week and only 2 percent reported daily fish consumption (Figures 10­

1 and 10-2). A total of 72 percent of respondents reported Walleye consumption in the 

previous two months. Peterson et al. (1994) also reported that the mean number of fish 

meals usually consumed per week by the respondents was 1.2. 

The mean fish consumption rate reported (1.2 fish meals per week, or 62.4 meals per 

year) in this survey was compared with the rate reported in a previous survey of Wisconsin 

anglers (Fiore et al., 1989) of 42 fish meals per year. These results indicate that the 

Chippewa Indians do not consume much more fish than the general Wisconsin angler 

population (Peterson et al., 1994). The differences in the two values may be attributed 

to differences in study methodology (Peterson et al., 1994). Note that this number (1.2 fish

meals per week) includes fish from all sources. Peterson et al. (1994) noted that 

subsistence fishing, defined as fishing as a major food source, appears rare among the 

Chippewa. Using the recommended rate in this handbook of 129 g/meal as the average 

weight of fish consumed per fish meal in the general population, the rate reported here of 

1.2 fish meals per week translates into a mean fish intake rate of 22 g/day in this 

population. 

Fitzgerald et al. (1995) - Fish PCB Concentrations and Consumption Patterns Among 

Mohawk Women at Akwesasne - Akwesasne is a native American community of ten 

thousand plus persons located along the St. Lawrence River (Fitzgerald et al., 1995). The 

local food chain has been contaminated with PCBs and some species have levels that 

exceed the U.S. FDA tolerance limits for human consumption (Fitzgerald et al., 1995). 

Fitzgerald et al. (1995) conducted a recall study from 1986 to 1992 to determine the fish 

consumption patterns among nursing Mohawk women residing near three industrial sites. 

The study sample consisted of 97 Mohawk women and 154 nursing Caucasian controls. 

The Mohawk mothers were significantly younger (mean age 24.9) than the controls (mean 

age 26.4) and had significantly more years of education (mean 13.1 for Mohawks versus 

12.4 for controls). A total of 97 out of 119 Mohawk nursing women responded, a response 

rate of 78 percent; 154 out of 287 control nursing Caucasian women responded, a 

response rate of 54 percent. 

Potential participants were identified prior to, or shortly after, delivery. The interviews 

were conducted at home within one month postpartum and were structured to collect 

information for sociodemographics, vital statistics, use of medications, occupational and 

residential histories, behavioral patterns (cigarette smoking and alcohol consumption), 

drinking water source, diet, and fish preparation methods (Fitzgerald et al., 1995). The 

dietary data collected were based on recall for food intake during the index pregnancy, the 

year before the pregnancy, and more than one year before the pregnancy. 

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The dietary assessment involved the report by each participant on the consumption 

of various foods with emphasis on local species of fish and game (Fitzgerald et al., 1995). 

This method combined food frequency and dietary histories to estimate usual intake. Food 

frequency was evaluated with a checklist of foods for indicating the amount of consumption 

of a participant per week, month or year. Information gathered for the dietary history 

included duration of consumption, changes in the diet, and food preparation method. 

Table 10-76 presents the number of local fish meals per year for both the Mohawk 

and control participants. The highest percentage of participants reported consuming 

between 1 and 9 local fish meals per year. Table 10-76 indicates that Mohawk 

respondents consumed statistically significantly more local fish than did control 

respondents during the two time periods prior to pregnancy; for the time period during 

pregnancy there was no significant difference in fish consumption between the two groups. 

Table 10-77 presents the mean number of local fish meals consumed per year by time 

period for all respondents and for those ever consuming (consumers only). A total of 82 

(85 percent) Mohawk mothers and 72 (47 percent) control mothers reported ever 

consuming local fish. The mean number of local fish meals consumed per year by 

Mohawk respondents declined over time, from 23.4 (over one year before pregnancy) to 

9.2 (less than one year before pregnancy) to 3.9 (during pregnancy); a similar decline was 

seen among consuming Mohawks only. There was also a decreasing trend over time in 

consumption among controls, though it was much less pronounced. 

Table 10-78 presents the mean number of fish meals consumed per year for all 

participants by time period and selected characteristics (age, education, cigarette smoking, 

and alcohol consumption). Pairwise contrasts indicated that control participants over 34 

years of age had the highest fish consumption of local fish meals (22.1) (Table 10-78). 

However, neither the overall nor pairwise differences by age among the Mohawk women 

over 34 years old were statistically significant, and may be due to the small sample size 

(N=6) (Fitzgerald et al., 1995). The most common fish consumed by Mohawk mothers was 

yellow perch; for controls the most common fish consumed was trout. 

An advantage of this study is that it presents data for fish consumption patterns for 

Native Americans as compared to a demographically similar group of Caucasians. 

Although the data are based on nursing mothers as participants, the study also captures 

consumption patterns prior to pregnancy (up to 1 year before and more than 1 year 

before). Fitzgerald et al. (1995) noted that dietary recall for a period more than one year 

before pregnancy may be inaccurate, but these data were the best available measure of 

the more distant past. They also noted that the observed decrease in fish consumption 

among Mohawks from the period one year before pregnancy to the period of pregnancy 

is due to a secular trend of declining fish consumption over time in Mohawks. This 

decrease, which was more pronounced than that seen in controls, may be due to health 

advisories promulgated by tribal, as well as state, officials. The authors note that this 

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decreasing secular trend in Mohawks is consistent with a survey from 1979-1980 that 

found an overall mean of 40 fish meals per year among male and female Mohawk adults. 

The data are presented as number of fish meals per year; the authors did not assign 

an average weight to fish meals. If assessors wanted to estimate the weight of fish 

consumed, some average value of weight per fish meal would have to be assumed. Pao 

et al. (1982) reported 104 grams as the average weight of fish consumed per eating 

occasion for females 19-34 years old. 

10.9. OTHER FACTORS 

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, some 

dioxin compounds) 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 (1996b). 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 (1996b) for a detailed review of 

these studies. In addition, some studies suggest that there is a significant decrease of 

contaminants in cooked fish when compared with raw fish (San Diego County, 1990). 

Several studies cited in this section have addressed fish preparation methods and parts 

of fish consumed. Table 10-79 provides summary results from these studies on fish 

preparation methods; further details on preparation methods, as well as results from some 

studies on parts of fish consumed, are presented in Appendix 10B. 

The moisture content (percent) and total fat content (percent) measured and/or 

calculated in various fish forms (i.e., raw, cooked, smoked, etc.) for selected fish species 

are presented in Table 10-80, based on data from USDA (1979-1984). The total percent 

fat content is based on the sum of saturated, monounsaturated, and polyunsaturated fat. 

The moisture content is based on the percent of water present. 

In some cases, the residue levels of contaminants in fish are reported as the 

concentration of contaminant per gram of fat. These contaminants are lipophilic 

compounds. When using 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 species of interest. Alternately, residue levels for the 

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Chapter 10 - Intake of Fish and Shellfish 

"as consumed" portions of fish may be estimated by multiplying the levels based on fat by 

the fraction of fat (Table 10-80) per product as follows: 

residue level g&fat residue level/g product = x (Eqn. 10-4) g&fat g&product 

The resulting residue levels may then be used in conjunction with "as consumed" 

consumption rates. 

Additionally, intake rates may be reported in terms of units as consumed or units of 

dry weight. 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 unit of food consumption is grams dry weight/day, then the 

unit for the amount of pollutant in the food should be grams dry weight). If necessary, as 

consumed intake rates may be converted to dry weight intake rates using the moisture 

content percentages of fish presented in Table 10-80 and the following equation: 

IR = IR * [(100-W)/100] (Eqn. 10-5) dw ac 

"Dry weight" intake rates may be converted to "as consumed" rates by using: 

IR = IRdw/[(100-W)/100] (Eqn. 10-6) ac 

where: 

IRdw = dry weight intake rate; 

IRac = as consumed intake rate; and 

W = percent water content. 

10.10. RECOMMENDATIONS 

Fish consumption rates are recommended based on the survey results presented in 

the key studies described in the preceding sections. Considerable variation exists in the 

mean and upper percentile fish consumption rates obtained from these studies. This can 

be attributed largely to the characteristics of the survey population (i.e., general 

population, recreational anglers) and the type of water body (i.e., marine, estuarine, 

freshwater), but other factors such as study design, method of data collection and 

geographic location also play a role. Based on these study variations, recommendations 

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Chapter 10 - Intake of Fish and Shellfish 

for consumption rates were classified into the following categories: 

• General Population; 

• Recreational Marine Anglers; 

• Recreational Freshwater Anglers; and 

• Native American Subsistence Fishing Populations 

The recommendations for each of these categories were rated according to the level 

of confidence the Agency has in the recommended values. These ratings were derived 

according to the principles outlined in Volume I, Section 1.3; the ratings and a summary 

of the rationale behind them are presented in tables which follow the discussion of each 

category. 

For exposure assessment purposes, the selection of the appropriate category (or 

categories) from above will depend on the exposure scenario being evaluated. Assessors 

should use the recommended values (or range of values) unless specific studies are felt 

to be particularly relevant to their needs, in which case results from a specific study or 

studies may be used. This is particularly true for the last two categories where no 

nationwide key studies exist. Even where national data exist, it may be advantageous to 

use regional estimates if the assessment targets a particular region. In addition, seasonal, 

age, and gender variations should be considered when appropriate. 

It should be noted that the recommended rates are based on mean (or median) 

values which represent a typical intake or central tendency for the population studied, and 

on upper estimates (i.e., 90th-99th percentiles) which represent the high-end fish 

consumption of the population studied. For the recreational angler populations, the 

recommended means and percentiles are based on all persons engaged in recreational 

fishing, not just those consuming recreationally caught fish. 

10.10.1. Recommendations - General Population 

The key study for estimating mean fish intake (reflective of both short-term and longterm consumption) is U.S. EPA (1996a) analysis of USDA CSFII 1989-1991. The 

recommended values for mean intake by habitat and fish type are shown in Table 10-81. 

For all fish (finfish and shellfish), the recommended values are 6.0 g/day for 

freshwater/ estuarine fish, 14.1 g/day for marine fish, and 20.1 g/day for all fish. Note that 

these values are reported as uncooked fish weight. This is important because the 

concentration 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. Although actual 

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consumption may be overestimated when intake is expressed in an uncooked basis, the 

net effect on the dose may be canceled out since the actual concentration may be 

underestimated when it is based on the uncooked sample. On the other hand, if the "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 consumed" intake 

rates are appropriate. For example, concentration may be expressed on a dry weight 

basis and, if data are available, loss of contaminant mass after cooking may be accounted 

for in the concentration. However, data on the effects of cooking in contaminant 

concentrations are limited and assessors generally make the conservative assumption that 

cooking has no effect on the contaminant mass. Both "as consumed" and uncooked fish 

intake values have been presented in this handbook so that the assessor can choose the 

intake data that best matches the concentration data that is being used. 

CSFII data were based on a short-term survey and could not be used to estimate the 

distribution over the long term of the average daily fish intake. The long-term average 

daily fish intake distribution can be estimated using the TRI study which provided dietary 

data for a one month period. However, because the data from the TRI study are now over 

20 years old, the value presented in Table 10-81 (56 g/day) has been adjusted by upward 

25 percent based on Ruffle et al. (1994) to reflect the increase in fish consumption since 

the TRI survey was conducted. In addition to the arguments provided by Ruffle et al. 

(1994) for adjusting the data upward, recent data from CSFII 1989-91 indicate an increase 

of fish intake of 33 percent when compared to USDA NFCS data from 1977-78. Therefore, 

the adjustment recommended by Ruffle et al. (1994) of 25 percent seems appropriate. 

Then, as suggested by Ruffle et al. (1994) the distributions generated from TRI should be 

shifted upward by 25 percent to estimate the current fish intake distribution. Thus, the 

recommended percentiles of long-term average daily fish intake are those of Javitz (1980) 

adjusted 25 percent upward (see Tables 10-3, 10-4). Alternatively, the log-normal 

distribution of Ruffle et al. (1994) (Table 10-6) may be used to approximate the long term

fish intake distribution; adjusting the log mean F by adding log(1.5)= 0.4, will shift the 

distribution upward by 25 percent. 

It is important to note that a limitation with these data is that the total amount of fish 

reported by respondents included fish from all sources (e.g., fresh, frozen, canned, 

domestic, international origin). Neither the TRI nor the CSFII surveys identified the source 

of the fish consumed. This type of information may be relevant for some assessments. 

It should be noted that because these recommendations are based on 1989-91 CSFII data, 

they may not reflect the most recent changes that may have occurred in consumption 

patterns. However, as indicated in Section 10.2, the 1989-91 CSFII data are believed to 

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be appropriate for assessing ingestion exposure for current populations because the rate 

of fish ingestion did not change dramatically between 1977-78 and 1995. 

The distribution of serving sizes may be useful for acute exposure assessments. The 

recommended values are 129 grams for mean serving size and 326 grams for the 95th 

percentile serving size based on the CSFII analyses (Table 10-82). 

10.10.2. Recommendations - Recreational Marine Anglers 

The recommended values presented in Table 10-83 are based on the surveys of the 

National Marine Fisheries Service (NMFS, 1993). The intake values are based on finfish 

consumption only. 

10.10.3. Recommendations - Recreational Freshwater Anglers 

The data presented in Table 10-84 are based on mailed questionnaire surveys (Ebert 

et al., 1993 and West et al., 1989; 1993) and a diary study (Connelly et al., 1992; 1996).

The mean intakes ranged from 5-17 g/day. The recommended mean and 95th percentile 

values for recreational freshwater anglers are 8 g/day and 25 g/day, respectively; these 

were derived by averaging the values from the three populations surveyed in the key 

studies. Since the two West et al. surveys studied the same population, the average of 

the means from the two studies was used to represent the mean for this population. The 

estimate from the West et al. (1989) survey was used to represent the 95th percentile for 

this population since the long term consumption percentiles could not be estimated from 

the West et al. (1993) study. 

10.10.4. Recommendations - Native American Subsistence Populations 

Fish consumption data for Native American subsistence populations are very limited. 

The CRITFC (1994) study gives a per-capita fish intake rate of 59 g/day and a 95th 

percentile of 170 g/day. The report by Wolfe and Walker (1987) presents harvest rates 

for 94 small communities engaged in subsistence harvests of natural resources. A factor 

of 0.5 was employed to convert the per-capita harvest rates presented in Wolfe and 

Walker (1987) to per capita individual consumption rates; this is the same factor used to 

convert from per capita household consumption rates to per capita individual consumption 

rates in the analysis of homegrown fish consumption from the 1987-1988 NFCS. Based 

on this factor, the median per-capita harvest in the 94 communities of 162 g/day (and the 

range of 31-1,540 g/day) is converted to the median per capita intake rate of 81 g/day 

(range 16-770 g/day) shown in Table 10-85. The recommended value for mean intake is 

70 g/day and the recommended 95th percentile is 170 g/day. 

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It should be emphasized that the above recommendations refer only to Native 

American subsistence fishing populations, not the Native American general population. 

Several studies show that intake rates of recreationally caught fish among Native 

Americans with state fishing licenses (West et al., 1989; Ebert et al., 1993) are somewhat 

higher (50-100 percent) than intake rates among other anglers, but far lower than the rates 

shown above for Native American subsistence populations. 

In addition, the studies of Peterson et al. (1994) and Fiore et al. (1989) show that 

total fish intake among a Native American population on a reservation (Chippewa in 

Wisconsin) is roughly comparable (50 percent higher) to total fish intake among licensed 

anglers in the same state. Also, the study of Fitzgerald et al. (1995) showed that pregnant 

women on a reservation (Mohawk in New York) have sport-caught fish intake rates 

comparable to those of a local white control population. 

The survey designs, data generated, and limitations/advantages of the studies 

described in this report are summarized and presented in Table 10-86. The confidence 

in recommendations is presented in Table 10-87. The confidence rating for recreational 

marine anglers is presented in Table 10-88. Confidence in fish intake recommendations 

for recreational freshwater fish consumption is presented in Table 10-89. The confidence 

in intake recommendations for Native American subsistence populations is presented in 

Table 10-90. 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Appendix 10A 

APPENDIX 10A

RESOURCE UTILIZATION DISTRIBUTION

Exposure Factors Handbook August 1997 
i 

Volume II - Food Ingestion Factors 

Appendix 10A 

Appendix 10A. Resource Utilization Distribution 

The percentiles of the resource utilization distribution of Y are to be distinguished 

from the percentiles of the (standard) distribution of Y. The latter percentiles show 

what percentage of individuals in the population are consuming below a given level. 

Thus, the 50th percentile of the distribution of Y is that level such that 50 percent of 

individuals consume below it; on the other hand, the 50th percentile of the resource 

utilization distribution is that level such that 50 percent of the overall consumption in 

the population is done by individuals consuming below it. 

The percentiles of the resource utilization distribution of Y will always be greater 

than or equal to the corresponding percentiles of the (standard) distribution of Y, and, 

in the case of recreational fish consumption, usually considerably exceed the standard 

percentiles. 

To generate the resource utilization distribution, one simply weights each 

observation in the data set by the Y level for that observation and performs a standard 

percentile analysis of weighted data. If the data already have weights, then one 

multiplies the original weights by the Y level for that observation, and then performs the 

percentile analysis. 

Under certain assumptions, the resource utilization percentiles of fish consumption 

may be related (approximately) to the (standard) percentiles of fish consumption 

derived from the analysis of creel studies. In this instance, it is assumed that the creel 

survey data analysis did not employ sampling weights (i.e., weights were implicitly set 

to one); this is the case for many of the published analyses of creel survey data. In 

creel studies the fish consumption rate for the ith individual is usually derived by 

multiplying the amount of fish consumption per fishing trip (say C ) by the frequency of i 

fishing (say f i ). If it is assumed that the probability of sampling of an angler is

proportional to fishing frequency, then sampling weights of inverse fishing frequency (1/ 

f ) should be employed in the analysis of the survey data. Above it was stated that for 

data that are already weighted the resource utilization distribution is generated by 

multiplying the original weights by the individual’s fish consumption level to create new 

weights. Thus, to generate the resource utilization distribution from the data with 

weights of (1/ f ), one multiplies (1/ f ) by the fish consumption level of f C to get new i i i i 

weights of C . i 

Now if C (amount of consumption per fishing trip) is constant over the population, i 

then these new weights are constant and can be taken to be one. But weights of one 

is what (it is assumed) were used in the original creel survey data analysis. Hence, the 

resource utilization distribution is exactly the same as the original (standard) 

distribution derived from the creel survey using constant weights. 

Exposure Factors Handbook August 1997 
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Appendix 10A 

The accuracy of this approximation of the resource utilization distribution of fish by 

the (standard) distribution of fish consumption derived from an unweighted analysis of 

creel survey data depends then on two factors, how approximately constant the C ‘s i 

are in the population and how approximately proportional the relationship between 

sampling probability and fishing frequency is. Sampling probability will be roughly 

proportional to frequency if repeated sampling at the same site is limited or if reinterviewing is performed independent of past interviewing status. 

Note: For any quantity Y that is consumed by individuals in a population, the 

percentiles of the “resource utilization distribution” of Y can be formally defined 

as follows: Y (R) is the pth percentile of the resource utilization distribution if p p 

percent of the overall consumption of Y in the population is done by individuals 

with consumption below Y (R) and 100-p percent is done by individuals with p 

consumption above Y (R). p 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 11 - Intake of Meat and Dairy Products 

11. INTAKE OF MEAT AND DAIRY PRODUCTS 

Consumption of meat, poultry, and dairy products is a potential pathway of exposure 

to toxic chemicals. These food sources can become contaminated if animals are exposed 

to contaminated media (i.e., soil, water, or feed crops). 

The U.S. Department of Agriculture's (USDA) Nationwide Food Consumption Survey 

(NFCS) and Continuing Survey of Food Intakes by Individuals (CSFII) are the primary 

sources of information on intake rates of meat and dairy products in the United States. 

Data from the NFCS have been used in various studies to generate consumer-only and 

per capita intake rates for both individual meat and dairy products and total meat and dairy 

products. CSFII 1989-91 survey data have been analyzed by EPA to generate per capita 

intake rates for various food items and food groups. As described in Volume II, Chapter 

9 - Intake of Fruits and Vegetables, consumer-only intake is defined as the quantity of 

meat and dairy products consumed by individuals who ate these food items during the 

survey period. Per capita intake rates are generated by averaging consumer-only intakes 

over the entire population of users and non-users. In general, per capita intake rates are 

appropriate for use in exposure assessments for which average dose estimates for the 

general population are of interest because they represent both individuals who ate the 

foods during the survey period and individuals who may eat the food items at some time, 

but did not consume them during the survey period. 

Intake rates may be presented on either an as consumed or dry weight basis. As 

consumed intake rates (g/day) are based on the weight of the food in the form that it is 

consumed. In contrast, dry weight intake rates are based on the weight of the food 

consumed after the moisture content has been removed. In calculating exposures based 

on ingestion, the unit of weight used to measure intake should be consistent with those 

used in measuring the contaminant concentration in the produce. Fat content data are 

also presented for various meat and dairy products. These data are needed for converting 

between residue levels on a whole-weight or as consumed basis and lipid basis. Intake 

data from the individual component of the NFCS and CSFII are based on "as eaten" (i.e., 

cooked or prepared) forms of the food items/groups. Thus, corrections to account for 

changes in portion sizes from cooking losses are not required. 

The purpose of this section is to provide: (1) intake data for individual meat and dairy 

products, total meat, and total dairy; (2) guidance for converting between as consumed 

and dry weight intake rates; and (3) data on the fat content in meat and dairy products. 

Recommendations are based on average and upper-percentile intake among the general 

population of the U.S. Available data have been classified as being either a key or a 

relevant study based on the considerations discussed in Volume I, Section 1.3.1 of the 

Introduction. Recommendations are based on data from the 1989-91 CSFII survey, which 

was considered the only key intake study for meats and dairy products. Other relevant 

Exposure Factors Handbook August 1997 
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Chapter 11 - Intake of Meat and Dairy Products 

studies are also presented to provide the reader with added perspective on this topic. It 

should be noted that most of the studies presented in this section are based on data from 

USDA's NFCS and CSFII. The USDA NFCS and CSFII are described below. 

11.1. INTAKE STUDIES 

11.1.1. U.S. Department of Agriculture Nationwide Food Consumption Survey and 

Continuing Survey of Food Intake by Individuals 

The NFCS and CSFII are the basis of much of the data on meat and dairy intake 

presented in this section. Data from the 1977-78 NFCS are presented because the data 

have been published by USDA in various reports and reanalyzed by various EPA offices 

according to the food items/groups commonly used to assess exposure. Published oneday data from the 1987-88 NFCS and 1994 and 1995 CSFII are also presented. Recently, 

EPA conducted an analysis of USDA's 1989-91 CSFII. These data were the most recent 

food survey data that were available to the public at the time that EPA analyzed the data 

for this Handbook. The results of EPA's analyses are presented here. Detailed 

descriptions of the NFCS and CSFII data are presented in Volume II, Chapter 9 - Intake 

of Fruits and Vegetables. 

Individual average daily intake rates calculated from NFCS and CSFII data are based 

on averages of reported individual intakes over one day or three consecutive days. Such 

short term data are suitable for estimating average daily intake rates representative of both 

short-term and long-term consumption. However, the distribution of average daily intake 

rates generated using short term data (e.g., 3 day) do not necessarily reflect the long-term 

distribution of average daily intake rates. The distributions generated from short term and 

long term data will differ to the extent that each individual’s intake varies from day to day; 

the distributions will be similar to the extent that individuals’ intakes are constant from day 

to day. 

Day-to-day variation in intake among individuals will be great for food item/groups 

that are highly seasonal and for items/groups that are eaten year around but that are not 

typically eaten every day. For these foods, the intake distribution generated from short 

term data will not be a good reflection of the long term distribution. On the other hand, for 

broad categories of foods (e.g., total meats) which are eaten on a daily basis throughout 

the year with minimal seasonality, the short term distribution may be a reasonable 

approximation of the true long term distribution, although it will show somewhat more 

variability. In this and the following section then, distributions are shown only for the 

following broad categories of foods: total meats and total dairy products. Because of the 

increased variability of the short-term distribution, the short-term upper percentiles shown 

will overestimate somewhat the corresponding percentiles of the long-term distribution. 

Exposure Factors Handbook August 1997 
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Chapter 11 - Intake of Meat and Dairy Products 

11.1.2. Key Meat and Dairy Products Intake Study Based on the CSFII 

U.S. EPA Analysis of 1989-91 USDA CSFII Data - EPA conducted an analysis of 

USDA's 1989-91 CSFII data set. The general methodology used in analyzing the data is 

presented in Volume II, Chapter 9 - Intake of Fruits and Vegetables of this Handbook. 

Intake rates were generated for the following meat and dairy products: total meats, total 

dairy, beef, pork, poultry, game, and eggs. Appendix 9B presents the food categories and 

codes used in generating intake rates for these food groups. These data have been 

corrected to account for mixtures as described in Volume II, Chapter 9 - Intake of Fruits 

and Vegetables and Appendix 9A. However, it should be noted that although total meats 

account for items such as luncheon meats, sausages, and organ meats, these items are 

not included in the individual meat groups (i.e., beef, poultry, etc.). Per capita intake rates 

for total meat and total dairy are presented in Tables 11-1 and 11-2 at the end of this 

Chapter. Tables 11-3 to 11-7 present per capita intake data for individual meats and eggs. 

The results are presented in units of g/kg-day. Thus, use of these data in calculating 

potential dose does not require the body weight factor to be included in the denominator 

of the average daily dose (ADD) equation. It should be noted that converting these intake 

rates into units of g/day by multiplying by a single average body weight is inappropriate, 

because individual intake rates were indexed to the reported body weights of the survey 

respondents. However, if there is a need to compare the intake data presented here to 

intake data in units of g/day, a body weight less than 70 kg (i.e., approximately 60 kg; 

calculated based on the number of respondents in each age category and the average 

body weights for these age groups, as presented in Volume I, Chapter 7, Body Weight) 

should be used because the total survey population included children as well as adults. 

The advantages of using the 1989-91 CSFII data set are that the data are expected 

to be representative of the U.S. population and that it includes data on a wide variety of 

food types. The data set was the most recent of a series of publicly available USDA data 

sets (i.e., NFCS 1977-78; NFCS 1987-88; CSFII 1989-91) at the time the analysis was 

conducted for this Handbook, and should reflect recent eating patterns in the United 

States. The data set includes three years of intake data combined. However, the 1989-91 

CSFII data are based on a three day survey period. Short-term dietary data may not 

accurately reflect long-term eating patterns. This is particularly true for the tails of the 

distribution of food intake. In addition, the adjustment for including mixtures adds 

uncertainty to the intake rate distributions. The calculation for including mixtures assumes 

that intake of any mixture includes all of the foods identified and the proportions specified 

in Appendix Table 9A-1. This assumption yields valid estimates of per capita 

consumption, but results in overestimates of the proportion of the population consuming 

individual meats; thus, the quantities reported in Tables 11-3 to 11-7 should be interpreted 

as upper bounds on the proportion consuming beef, pork, poultry, game, and eggs. 

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Chapter 11 - Intake of Meat and Dairy Products 

The data presented in this handbook for the USDA 1989-91 CSFII is not the most upto-date information on food intake. USDA has recently made available the data from its 

1994 and 1995 CSFII. Over 5,500 people nationwide participated in both of these 

surveys, providing recalled food intake information for 2 separate days. Although the twoday data analysis has not been conducted, USDA published the results for the 

respondents’ intakes on the first day surveyed (USDA, 1996a,b). USDA 1996 survey data 

will be made available later in 1997. As soon as 1996 data are available, EPA will take 

steps to get the 3-year data (1994, 1995, and 1996) analyzed and the food ingestion 

factors updated. Meanwhile, Table 11-8 presents a comparison of the mean daily intakes 

per individual in a day for the major meat and dairy groups from USDA survey data from 

years 1977-78, 1987-88, 1989-91, 1994, and 1995. This table shows that food 

consumption patterns have changed for beef and meat mixtures when comparing 1977 and 

1995 data. In particular, consumption of beef decreased by 50 percent when comparing 

data from 1977 and 1995, while consumption of meat mixtures increased by 44 percent. 

However, consumption of the food items presented in Table 11-8 has remained fairly 

constant when comparing values from 1989-91 with the most recent data from 1994 and 

1995. Meat mixtures show the largest change with an increase of 16 percent from 1989 

to 1995. This indicates that the 1989-91 CSFII data are probably adequate for assessing 

ingestion exposure for current populations; however, these data should be used with 

caution. 

It is interesting to note that there was not much variation in beef and poultry 

consumption from 1989-91 to 1995. This seems to contradict the other USDA reports that 

show that in recent years the U.S. population has been substituting beef for other sources 

of protein such as poultry and fish. One of those reports is the report titled Meat and 

Poultry Inspection; 1994 Report of the Secretary of Agriculture to the U.S. Congress 

(USDA, 1994). This USDA report shows a 39% increase in the number of poultry 

inspected at federally inspected plants in 1994 compared to 1984. In contrast, the 

number of meat animals inspected at federally inspected plants increased only by 2% from 

1984 to 1994. This trend in food consumption patterns was also reported in the USDA 

report titled Food Consumption, Prices, and Expenditures, 1970-92 (USDA, 1993). This 

report shows that in 1992, consumption among Americans averaged 18 pounds less red 

meat, 26 pounds more poultry, and 3 pounds more fish and shellfish than in 1970. This 

apparent contradiction may be explained by assuming that most of the increase in poultry 

consumption has occured in the meat mixtures and grain mixtures categories. There has 

been a considerable shift from consuming individual food items to food in mixtures (such 

as pizza, tacos, burritos, frozen entrees, and salads from grocery stores). This may explain 

why, in Table 11-8, domestic consumption has remained fairly constant in the past few 

years. 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 11 - Intake of Meat and Dairy Products 

11.1.3. Relevant Meat and Dairy Products Intake Studies 

The U.S. EPA's Dietary Risk Evaluation System (DRES) - U.S. EPA, Office of 

Pesticide Programs (OPP) - EPA OPP's DRES contains per capita intake rate data for 

various items of meat, poultry, and dairy products for 22 subgroups (age, regional, and 

seasonal) of the population. As described in Volume II, Chapter 9 - Intake of Fruits and 

Vegetables, intake data in DRES were generated by determining the composition of 

1977/78 NFCS food items and disaggregating complex food dishes into their component 

raw agricultural commodities (RACs) (White et al., 1983). The DRES per capita, as 

consumed intake rates for all age/sex/demographic groups combined are presented in 

Table 11-9. These data are based on both consumers and non-consumers of these food 

items. Data for specific subgroups of the population are not presented in this section, but 

are available through OPP via direct request. The data in Table 11-9 may be useful for 

estimating the risks of exposure associated with the consumption of the various meat, 

poultry, and dairy products presented. It should be noted that these data are indexed to 

the reported body weights of the survey respondents and are expressed in units of grams 

of food consumed per kg body weight per day. Consequently, use of these data in 

calculating potential dose does not require the body weight factor in the denominator of 

the average daily dose (ADD) equation. It should also be noted that conversion of these 

intake rates into units of g/day by multiplying by a single average body weight is not 

appropriate because the DRES data base did not rely on a single body weight for all 

individuals. Instead, DRES used the body weights reported by each individual surveyed 

to estimate consumption in units of g/kg-day. 

The advantages of using these data are that complex food dishes have been 

disaggregated to provide intake rates for a variety of meat, poultry, and dairy products. 

These data are also based on the individual body weights of the respondents. Therefore, 

the use of these data in calculating exposure to toxic chemicals may provide more 

representative estimates of potential dose per unit body weight. However, because the 

data are based on NFCS short-term dietary recall, the same limitations discussed 

previously for other NFCS data sets also apply here. In addition, consumption patterns 

may have changed since the data were collected in 1977-78. OPP is in the process of 

translating consumption information from the USDA CSFII 1989-91 survey to be used in 

DRES. 

Food and Nutrient Intakes of Individuals in One Day in the U.S., USDA (1980, 1992, 

1996a, 1996b) -USDA calculated mean per capita intake rates for meat and dairy products 

using NFCS data from 1977-78 and 1987-88 (USDA, 1980; 1992) and CSFII data from 

1994 and 1995 (USDA, 1996a; 1996b). The mean per capita intake rates for meat and 

dairy products are presented in Tables 11-10 and 11-11 for meats and Tables 11-12 and 

11-13 for dairy based on intake data for one day from the 1977-78 and 1987-88 USDA 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 11 - Intake of Meat and Dairy Products 

NFCSs. Tables 11-14 and 11-15 present similar data from the 1994 and 1995 CSFII for 

meats and dairy products, respectively. 

The advantages of using these data are that they provide mean intake estimates for 

all meat, poultry, and dairy products. The consumption estimates are based on short-term 

(i.e., 1-day) dietary data which may not reflect long-term consumption. 

U.S. EPA - Office of Radiation Programs - The U.S. EPA Office of Radiation Programs 

(ORP) has also used the USDA 1977-78 NFCS to estimate daily food intake. ORP uses 

food consumption data to assess human intake of radionuclides in foods (U.S. EPA, 

1984a; 1984b). The 1977-78 NFCS data have been reorganized by ORP, and food items 

have been classified according to the characteristics of radionuclide transport. The mean 

per capita dietary intake of food sub classes (milk, other dairy products, eggs, beef, pork, 

poultry, and other meat) grouped by age for the U.S. population is presented in Table 11­

16. The mean daily intake rates of meat, poultry, and dairy products for the U.S. 

population grouped by regions are presented in Table 11-17. Because this study was 

based on the USDA NFCS, the limitations and advantages associated with the USDA 

NFCS data also apply to these data. Also, consumption patterns may have changed since 

the data were collected in 1977-78. 

U.S. EPA - Office of Science and Technology - The U.S. EPA Office of Science and 

Technology (OST) within the Office of Water (formerly the Office of Water Regulations and 

Standards) used data from the FDA revision of the Total Diet Study Food Lists and Diets 

(Pennington, 1983) to calculate food intake rates. OST uses these consumption data in 

its risk assessment model for land application of municipal sludge. The FDA data used 

are based on the combined results of the USDA 1977-78 NFCS and the second National 

Health and Nutrition Examination Survey (NHANES II), 1976-80 (U.S. EPA, 1989). 

Because food items are listed as prepared complex foods in the FDA Total Diet Study, 

each item was broken down into its component parts so that the amount of raw 

commodities consumed could be determined. Table 11-18 presents intake rates for meat, 

poultry, and dairy products for various age groups. Estimated lifetime ingestion rates 

derived by U.S. EPA (1989) are also presented in Table 11-18. Note that these are per 

capita intake rates tabulated as grams dry weight/day. Therefore, these rates differ from 

those in the previous tables because Pao et al. (1982) and U.S. EPA (1984a, 1984b) 

report intake rates on an as consumed basis. 

The EPA-OST analysis provides intake rates for additional food categories and 

estimates of lifetime average daily intake on a per capita basis. In contrast to the other 

analyses of USDA NFCS data, this study reports the data in terms of dry weight intake 

rates. Thus, conversion is not required when contaminants are provided on a dry weight 

basis. These data, however, may not reflect current consumption patterns because they 

are based on 1977-78 data. 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 11 - Intake of Meat and Dairy Products 

USDA (1993) - Food Consumption, Prices, and Expenditures, 1970-92 -The USDA's 

Economic Research Service (ERS) calculates the amount of food available for human 

consumption in the United States annually. Supply and utilization balance sheets are 

generated. These are based on the flow of food items from production to end uses. Total 

available supply is estimated as the sum of production (i.e., some products are measured 

at the farm level or during processing), starting inventories, and imports (USDA, 1993). 

The availability of food for human use commonly termed as "food disappearance" is 

determined by subtracting exported foods, products used in industries, farm inputs (seed 

and feed) and end-of-the year inventories from the total available supply (USDA, 1993). 

USDA (1993) calculates the per capita food consumption by dividing the total food 

disappearance by the total U.S. population. 

USDA (1993) estimated per capita consumption data for meat, poultry, and dairy 

products from 1970-1992 (1992 data are preliminary). In this section, the 1991 values, 

which are the most recent final data, are presented. The meat consumption data were 

reported as carcass weight, retail weight equivalent, and boneless weight equivalent. The 

poultry consumption data were reported as ready-to-cook (RTC) weight, retail weight, and 

boneless weight (USDA, 1993). USDA (1993) defined beef carcass weight as the chilled 

hanging carcass, which includes the kidney and attached internal fat (kidney, pelvic, and 

heart fat), excludes the skin, head, feet, and unattached internal organs. The pork carcass 

weight includes the skin and feet, but excludes the kidney and attached internal fat. Retail 

weight equivalents assume all food was sold through retail foodstores; therefore, 

conversion factors (Table 11-19) were used to correct carcass or RTC to retail weight to

account for trimming, shrinkage, or loss of meat and chicken at these retail outlets (USDA, 

1993). Boneless equivalent values for meat (pork, veal, beef) and poultry excludes all 

bones, but includes separable fat sold on retail cuts of red meat. Pet food was considered 

as an apparent source of food disappearance for poultry in boneless weight estimates, 

while pet food was excluded for beef, veal, and pork (USDA, 1993). Table 11-19 presents 

per capita consumption in 1991 for red meat (carcass weight, retail equivalent, and 

boneless trimmed equivalent) and poultry (RTC, retail equivalent for chicken only, and 

boneless trimmed equivalent). Per capita consumption estimates based on boneless 

weights appear to be the most appropriate data for use in exposure assessments, because 

boneless meats are more representative of what people would actually consume. Table 

11-20 presents per capita consumption in 1991 for dairy products including eggs, milk, 

cheese, cream, and sour cream. 

One of the limitations of this study is that disappearance data do not account for 

losses from the food supply from waste, spoilage, or foods fed to pets. Thus, intake rates 

based on these data will overestimate daily consumption because they are based on the 

total quantity of marketable commodity utilized. Therefore, these data may be useful for 

estimating bounding exposure estimates. It should also be noted that per capita estimates 

based on food disappearance are not a direct measure of actual consumption or quantity 

Exposure Factors Handbook August 1997 
intake rate

Volume II - Food Ingestion Factors 

Chapter 11 - Intake of Meat and Dairy Products 

ingested, instead the data are used as indicators of changes in usage over time (USDA, 

1993). An advantage of this study is that it provides per capita consumption rates for 

meat, poultry, and dairy products which are representative of long-term intake because 

disappearance data are generated annually. Daily per capita intake rates are generated 

by dividing annual consumption by 365 days/year. 

National Live Stock and Meat Board (1993) - Eating in America Today: A Dietary 

Pattern and Intake Report - The National Live Stock and Meat Board (NLMB) (1993) 

assessed the nutritional value of the current American diet based on two factors: (1) the 

composition of the foods consumed, and (2) the amount of food consumed. Data used in 

this study were provided by MRCA Information Services, Inc. through MRCA's Nutritional 

Marketing Information Division. The survey conducted by MRCA consisted of a 2,000 

household panels of over 4,700 individuals. The survey sample was selected to be 

representative of the U.S. population. Information obtained from the survey by MRCA's 

Menu Census included food and beverage consumption over a period of 14 consecutive 

days. The head of the household recorded daily food and beverage consumption in-home 

and away-from-home in diaries for each household member. The survey period was from 

July 1, 1990 through June 30, 1991. This ensured that all days carried equal weights and 

provided a seasonally balanced data set. In addition, nutrient intake data calculated by 

the MRCA's Nutrient Intake Database (NID) (based on the 1987-88 USDA Food Intake 

Study) and information on food attitudes were also collected. It should be noted, however, 

that the 14 daily diaries provided only the incidence of eating each food product by an 

individual, but not the quantity eaten by each person. The for each individual 

was estimated by multiplying the eating frequency of a particular food item by the average 

amount eaten per eating occasion. The data on the average amount eaten per eating 

occasion were obtained from the USDA NFCS survey. 

Table 11-21 presents the adult daily mean intake of meat and poultry grouped by 

region and gender. The adult population was defined as consumers ages 19 and above 

(NLMB, 1993). Beef consumption was high in all regions compared to other meats and 

poultry (Table 11-21). The average daily consumption of meat in the U.S. was 114.2 g/day 

which included beef (57 percent), veal (0.5 percent), lamb (0.5 percent), game/variety 

meats (8 percent), processed meats (18 percent), and pork (16 percent) (NLMB, 1993). 

Table 11-22 shows the amount of meat consumed by the adult population grouped as nonmeat eaters (1 percent), light meat eaters (30 percent), medium meat eaters (33 percent), 

and heavy meat eaters (36 percent). 

The advantage of this study is that the survey period is longer (i.e., 14 days) than any 

other food consumption survey. The survey is also based on a nationally representative 

sample. The survey also accounts for foods eaten as mixtures. However, only mean 

values are provided. Therefore, distribution of long-term consumption patterns cannot be 

derived. In addition, the survey collects data on incidence of eating each food item and 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 11 - Intake of Meat and Dairy Products 

not actual consumption rates. This may introduce some bias in the results. The direction 

of this bias is unknown. 

AIHC (1994) - Exposure Factors Sourcebook - The AIHC Sourcebook (AIHC, 1994) 

uses the data presented in the 1989 version of the Exposure Factors Handbook which 

reported data from the USDA 1977-78 NFCS. In this Handbook, new analyses of more 

recent data from the USDA 1989-91 CSFII are presented. Numbers, however, cannot be 

directly compared with previous values since the results from the new analysis are 

presented on a body weight basis. The Sourcebook was selected as a relevant study 

because it was not the primary source for the data used to make recommendations in this 

document. However, it is an alternative information source. 

Pao et al. (1982) - Foods Commonly Eaten by Individuals - Using data gathered in 

the 1977-78 USDA NFCS, Pao et al. (1982) calculated percentiles for the quantities of 

meat, poultry, and dairy products consumed per eating occasion by members of the U.S. 

population. The data were collected during NFCS home interviews of 37,874 respondents, 

who were asked to recall food intake for the day preceding the interview, and record food 

intake the day of the interview and the day after the interview. Quantities consumed per 

eating occasion, are presented in Table 11-23. 

The advantages of using these data are that they were derived from the USDA NFCS 

and are representative of the U.S. population. This data set provides distributions of 

serving sizes for a number of commonly eaten meat, poultry, and dairy products, but the 

list of foods is limited and does not account for meat, poultry, and dairy products included 

in complex food dishes. Also, these data are based on short-term dietary recall and may 

not accurately reflect long-term consumption patterns. Although these data are based on 

the 1977-78 NFCS, serving size data have been collected but not published for the more 

recent USDA surveys. 

11.2. FAT CONTENT OF MEAT AND DAIRY PRODUCTS 

In some cases, the residue levels of contaminants in meat and dairy products 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 meat or dairy product of interest. Alternately, 

residue levels for the "as consumed" portions of these products may be estimated by 

multiplying the levels based on fat by the fraction of fat per product as follows: 

residue level ' residue level g&fat x (Eqn. 11-1) g&product g&fat g&product 

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Chapter 11 - Intake of Meat and Dairy Products 

The resulting residue levels may then be used in conjunction with "as consumed" 

consumption rates. The percentages of lipid fat in meat and dairy products have been 

reported in various publications. USDA's Agricultural Handbook Number 8 (USDA, 1979­

1984) provides composition data for agricultural products. It includes a listing of the total 

saturated, monounsaturated, and polyunsaturated fats for various meat and dairy items. 

Table 11-24 presents the total fat content for selected meat and dairy products taken from 

Handbook Number 8. The total percent fat content is based on the sum of saturated, 

monounsaturated, and polyunsaturated fats. 

The National Livestock and Meat Board (NLMB) (1993) used data from Agricultural 

Handbook Number 8 and consumption data to estimate the fat contribution to the U.S. diet. 

Total fat content in grams, based on a 3-ounce (85.05 g) cooked serving size, was 

reported for several categories (retail composites) of meats. These data are presented in 

Table 11-25 along with the corresponding percent fat content values for each product. 

NLMB (1993) also reported that 0.17 grams of fat are consumed per gram of meat (i.e., 

beef, pork, lamb, veal, game, processed meats, and variety meats) (17 percent) and 0.08 

grams of fat are consumed per gram of poultry (8 percent). 

The average total fat content of the U.S. diet was reported to be 68.3 g/day. The 

meat group (meat, poultry, fish, dry beans, eggs, and nuts) was reported to contribute the 

most to the average total fat in the diet (41 percent) (NLMB, 1993). Meats (i.e., beef, pork, 

lamb, veal, game, processed meats, and variety meats) reportedly contribute less than 30 

percent to the total fat of the average U.S. diet. The milk group contributes approximately 

12 percent to the average total fat in the U.S. diet (NLMB, 1993). Fat intake rates and the 

contributions of the major food groups to fat intake for heavy, medium, and light meat 

eaters, and non meat eaters are presented in Table 11-26 (NLMB, 1993). NLMB (1993) 

also reported the average meat fat intake to be 19.4 g/day, with beef contributing about 

50 percent of the fat to the diet from all meats. Processed meats contributed 31 percent; 

pork contributed 14 percent; game and variety meats contributed 4 percent; and lamb and 

veal contributed 1 percent to the average meat fat intake. 

The Center for Disease Control (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 14,001 respondents (73 percent response 

rate) provided dietary information based on a 24-hour recall. 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." 

Exposure Factors Handbook August 1997 
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Chapter 11 - Intake of Meat and Dairy Products 

CDC (1994) 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 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 mean daily fat 

intake was calculated for the various age groups and genders (see Appendix 11A for 

detailed calculation). Table 11-27 presents the grams of fat per day obtained from the 

daily consumption of foods and beverages grouped by age and gender for the U.S. 

population, based on this calculation. 

11.3. CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT 

INTAKE RATES 

As noted previously, intake rates may be reported in terms of units as consumed or 

units of dry weight. 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 unit of food consumption is grams dry weight/day, then 

the unit for the amount of pollutant in the food should be grams dry weight). If necessary, 

as consumed intake rates may be converted to dry weight intake rates using the moisture 

content percentages of meat, poultry and dairy products presented in Table 11-28 and the 

following equation: 

IR = IR * [(100-W)/100] (Eqn. 11-2) dw ac 

“Dry weight" intake rates may be converted to "as consumed" rates by using: 

 = IRdw/[(100-W)/100] (Eqn. 11-3) 

where: 

IRdw = dry weight intake rate; 

IR = as consumed intake rate; and 

IRac 

ac 

W = percent water content. 

11.4. RECOMMENDATIONS 

The 1989-91 CSFII data described in this section were used in selecting 

recommended meat, poultry, and dairy product intake rates for the general population and 

various subgroups of the United States population. The general design of both key and 

relevant studies are summarized in Table 11-29. The recommended values for intake of 

meat and dairy products are summarized in Table 11-30 and the confidence ratings for the 

recommended values for meat and dairy intake rates are presented in Table 11-31. Per 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 11 - Intake of Meat and Dairy Products 

capita intake rates for specific meat items, on a g/kg-day basis, may be obtained from 

Tables 11-3 to 11-7. Percentiles of the intake rate distribution in the general population 

for total meat and total dairy are presented in Tables 11-1 and 11-2. From these tables, 

the mean and 95th percentile intake rates for meats are 2.1 g/kg-day and 5.1 g/kg-day, 

respectively. The mean and 95th percentile intake rates for dairy products are 8.0 g/kgday and 29.7 g/kg-day. It is important to note that the data presented in Tables 11-1 

through 11-7 are based on data collected over a 3-day period 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 total dairy products), because they may be 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. 

Intake rates for the homeproduced form of these food items/groups are presented in 

Volume II, Chapter 13. It should be noted that because these recommendations are based 

on 1989-91 CSFII data, they may not reflect recent the most changes in consumption 

patterns. However, as indicated in Table 11-8, intake has remained fairly constant 

between 1989-91 and 1995. Thus, the 1989-91 CSFII data are believed to be appropriate 

for assessing ingestion exposure for current populations. 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Appendix 11A 

APPENDIX 11A 

SAMPLE CALCULATION OF MEAN DAILY FAT INTAKE BASED ON CDC (1994) 

DATA 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Appendix 11A 

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. 

0.34 x 2,095 kcal 

day 

x X g&fat 

day 

' 82 g&fat 

day 

ˆ	X ' 0.12 g&fat 

kcal 

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 and their percent TFEI from total 

dietary fat (33 percent) is as follows: 

1,591 kcal g&fat g&fat x 0.33 x 0.12 ' 63 

day kcal day 

Exposure Factors Handbook August 199 August 1997
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Chapter 12 - Intake of Grain Products 

12. INTAKE OF GRAIN PRODUCTS 

Consumption of grain products is a potential pathway of exposure to toxic chemicals. 

These food sources can become contaminated by absorption or deposition of ambient air 

pollutants onto the plants, contact with chemicals dissolved in rainfall or irrigation waters, 

or absorption of chemicals through plant roots from soil and ground water. The addition 

of pesticides, soil additives, and fertilizers may also result in contamination of grain 

products. 

The U.S. Department of Agriculture's (USDA) Nationwide Food Consumption Survey 

(NFCS) and Continuing Survey of Food Intakes by Individuals (CSFII) are the primary 

sources of information on intake rates of grain products in the United States. Data from 

the NFCS have been used in various studies to generate consumer-only and per capita 

intake rates for both individual grain products and total grains. CSFII 1989-91 survey data 

have been analyzed by EPA to generate per capita intake rates for various food items and 

food groups. As described in Volume II, Chapter 9 - Intake of Fruits and Vegetables, 

consumer-only intake is defined as the quantity of grain products consumed by individuals 

who ate these food items during the survey period. Per capita intake rates are generated 

by averaging consumer-only intakes over the entire population of users and non-users. 

In general, per capita intake rates are appropriate for use in exposure assessments for 

which average dose estimates for the general population are of interest because they 

represent both individuals who ate the foods during the survey period and individuals who 

may eat the food items at some time, but did not consume them during the survey period. 

This Chapter provides intake data for individual grain products and total grains. 

Recommendations are based on average and upper-percentile intake among the general 

population of the U.S. Available data have been classified as being either a key or a 

relevant study based on the considerations discussed in Volume I, Section 1.3.1 of the 

Introduction. Recommendations are based on data from the 1989-91 CSFII survey, which 

was considered the only key intake study for grain products. Other relevant studies are 

also presented to provide the reader with added perspective on this topic. It should be 

noted that most of the key and relevant studies presented in this Chapter are based on 

data from USDA's NFCS and CSFII. The USDA NFCS and CSFII are described below. 

12.1. INTAKE STUDIES 

12.1.1. U.S. Department of Agriculture Nationwide Food Consumption 

Survey and Continuing Survey of Food Intake by Individuals 

The NFCS and CSFII are the basis of much of the data on grain intake presented in 

this section. Data from the 1977-78 NFCS are presented because the data have been 

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Volume II - Food Ingestion Factors 

Chapter 12 - Intake of Grain Products 

published by USDA in various reports and reanalyzed by various EPA offices according 

to the food items/groups commonly used to assess exposure. Published one-day data 

from the 1987-88 NFCS and 1994 and 1994 CSFII are also presented. Recently, EPA 

conducted an analysis of USDA's 1989-91 CSFII. These data were the most recent food 

survey data available to the public at the time that EPA analyzed the data for this 

Handbook. The results of EPA's analyses are presented here. Detailed descriptions of 

the NFCS and CSFII data are presented in Volume II, Chapter 9 - Intake of Fruits and 

Vegetables. 

Individual average daily intake rates calculated from NFCS and CSFII data are based 

on averages of reported individual intakes over one day or three consecutive days. Such 

short term data are suitable for estimating average daily intake rates representative of both 

short-term and long-term consumption. However, the distribution of average daily intake 

rates generated using short term data (e.g., 3-day) do not necessarily reflect the long-term 

distribution of average daily intake rates. The distributions generated from short term and 

long term data will differ to the extent that each individual’s intake varies from day to day; 

the distributions will be similar to the extent that individuals’ intakes are constant from day 

to day.

 Day-to-day variation in intake among individuals will be great for food item/groups that 

are highly seasonal and for items/groups that are eaten year around, but that are not 

typically eaten every day. For these foods, the intake distribution generated from short 

term data will not be a good reflection of the long term distribution. On the other hand, for 

broad categories of foods (e.g., total grains) which are eaten on a daily basis throughout 

the year with minimal seasonality, 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 shown for the various grain categories. 

Because of the increased variability of the short-term distribution, the short-term upper 

percentiles shown will overestimate somewhat the corresponding percentiles of the longterm distribution. 

12.1.2. Key Grain Products Intake Studies Based on the CSFII 

U.S. EPA Analysis of 1989-91 USDA CSFII Data - EPA conducted an analysis of 

USDA's 1989-91 CSFII data set. The general methodology used in analyzing the data is 

presented in Volume II, Chapter 9 - Intake of Fruits and Vegetables of this Handbook. 

Intake rates were generated for the following grain products: total grains, breads, sweets, 

snacks, breakfast foods, pasta, cooked cereals, rice, ready-to-eat cereals, and baby 

cereals. Appendix 12A provides the food codes and descriptions used in this grain 

analysis. The data for total grains have been corrected to account for mixtures as 

described in Volume II, Chapter 9 - Intake of Fruits and Vegetables and Appendix 9A using 

an assumed grain content of 31 percent for grain mixtures and 13 percent for meat 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 12 - Intake of Grain Products 

mixtures. Per capita intake rates for total grains are presented in Tables 12-1. Table 12-2 

through 12-10 present per capita intake data for individual grain products. The results are 

presented in units of g/kg-day. Thus, use of these data in calculating potential dose does 

not require the body weight factor to be included in the denominator of the average daily 

dose (ADD) equation. It should be noted that converting these intake rates into units of 

g/day by multiplying by a single average body weight is inappropriate, because individual 

intake rates were indexed to the reported body weights of the survey respondents. 

However, if there is a need to compare the intake data presented here to intake data in 

units of g/day, a body weight less than 70 kg (i.e., approximately 60 kg; calculated based 

on the number of respondents in each age category and the average body weights for 

these age groups, as presented in Volume I, Chapter 7) should be used because the total 

survey population included children as well as adults. 

The advantages of using the 1989-91 CSFII data set are that the data are expected 

to be representative of the U.S. population and that it includes data on a wide variety of 

food types. The data set was the most recent of a series of publicly available USDA data 

sets (i.e., NFCS 1977-78; NFCS 1987-88; CSFII 1989-91) at the time the analysis was 

conducted for this Handbook, and should reflect recent eating patterns in the United 

States. The data set includes three years of intake data combined. However, the 1989-91 

CSFII data are based on a three day survey period. Short-term dietary data may not 

accurately reflect long-term eating patterns. This is particularly true for the tails of the 

distribution of food intake. In addition, the adjustment for including mixtures adds 

uncertainty to the intake rate distributions. The calculation for including mixtures assumes 

that intake of any mixture includes grains in the proportions specified in Appendix 

Table 9A-1. This assumption yields valid estimates of per capita consumption, but results 

in overestimates of the proportion of the population consuming total grains; thus, the 

quantities reported in Table 12-1 should be interpreted as upper bounds on the proportion 

of the population consuming grain products. 

The data presented in this handbook for the USDA 1989-91 CSFII is not the most upto-date information on food intake. USDA has recently made available the data from its 

1994 and 1995 CSFII. Over 5,500 people nationwide participated in both of these surveys 

providing recalled food intake informatin for 2 separate days. Although the 2-day data 

analysis has not been conducted, USDA published the results for the respondents’ intakes 

on the first day surveyed (USDA, 1996a; 1996b). USDA 1996 survey data will be made 

available later in 1997. As soon as 1996 data are available, EPA will take steps to get the 

3-year data (1994, 1995, and 1996) analyzed and the food ingestion factors updated. 

Meanwhile, Table 12-11 presents a comparison of the mean daily intakes per individual 

in a day for grains from the USDA survey data from years 1977-78, 1987-88, 1989-91, 

1994, and 1995. This table shows that food consumption patterns have changed for grains 

and grain mixtures when comparing 1977 and 1995 data. When comparing data from 

1977 and 1995, consumption of grains mixtures and grain increased by 106 percent and 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 12 - Intake of Grain Products 

41 percent, respectively. However, consumption of grains has remained fairly constant 

when comparing values from 1989-91 with the most recent data from 1994 and 1995. 

Grain mixtures and grains increase 20 percent and 11 percent, respectively from 1989 to 

1995. The 1989-91 CSFII data are probably adequate for assessing ingestion exposure 

for current populations, but these data should be used with caution. 

12.1.3. Relevant Grain Products Intake Studies 

The U.S. EPA's Dietary Risk Evaluation System (DRES) - USEPA, Office of Pesticide 

Programs (OPP) - EPA OPP's DRES contains per capita intake rate data for various grain 

products for 22 subgroups (age, regional, and seasonal) of the population. As described 

in Volume II, Chapter 9 - Intake of Fruits and Vegetables, intake data in DRES were 

generated by determining the composition of 1977/78 NFCS food items and 

disaggregating complex food dishes into their component raw agricultural commodities 

(RACs) (White et al., 1983). The DRES per capita, as consumed intake rates for all 

age/sex/demographic groups combined are presented in Table 12-12. These data are 

based on both consumers and non-consumers of these food items. Data for specific 

subgroups of the population are not presented in this section, but are available through 

OPP via direct request. The data in Table 12-12 may be useful for estimating the risks of 

exposure associated with the consumption of the various grain products presented. It 

should be noted that these data are indexed to the reported body weights of the survey 

respondents and are expressed in units of grams of food consumed per kg body weight 

per day. Consequently, use of these data in calculating potential dose does not require 

the body weight factor in the denominator of the average daily dose (ADD) equation. It 

should also be noted that conversion of these intake rates into units of g/day by multiplying 

by a single average body weight is not appropriate because the DRES data base did not 

rely on a single body weight for all individuals. Instead, DRES used the body weights 

reported by each individual surveyed to estimate consumption in units of g/kg-day. 

The advantages of using these data are that complex food dishes have been 

disaggregated to provide intake rates for a variety of grains. These data are also based 

on the individual body weights of the respondents. Therefore, the use of these data in 

calculating exposure to toxic chemicals may provide more representative estimates of 

potential dose per unit body weight. However, because the data are based on NFCS 

short-term dietary recall, the same limitations discussed previously for other NFCS data 

sets also apply here. In addition, consumption patterns may have changed since the data 

were collected in 1977-78. OPP is in the process of translating consumption information 

from the USDA CSFII 1989-91 survey to be used in DRES. 

Food and Nutrient Intakes of Individuals in One Day in the U.S., USDA (1980, 1992; 

1996a; 1996b) -USDA calculated mean per capita intake rates for total and individual grain 

products using NFCS data from 1977-78 and 1987-88 (USDA 1980; 1992) and CSFII data 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 12 - Intake of Grain Products 

from 1994 and 1995 (USDA, 1996a; 1996b). The mean per capita intake rates for grain 

products are presented in Tables 12-13 and 12-14 for the two NFCS survey years, 

respectively. Table 12-15 presents similar data from the 1994 and 1995 CSFII for grain 

products. 

The advantages of using these data are that they provide mean intake estimates for 

various grain products. The consumption estimates are based on short-term (i.e., 1-day) 

dietary data which may not reflect long-term consumption. 

U.S. EPA - Office of Radiation Programs - The U.S. EPA Office of Radiation Programs 

(ORP) has also used the USDA 1977-78 NFCS to estimate daily food intake. ORP uses 

food consumption data to assess human intake of radionuclides in foods (U.S. EPA, 

1984a; 1984b). The 1977-78 NFCS data have been reorganized by ORP, and food items 

have been classified according to the characteristics of radionuclide transport. The mean 

dietary per capita intake of grain products, grouped by age, for the U.S. population are 

presented in Table 12-16. The mean daily intake rates of grain products for the U.S. 

population grouped by regions are presented in Table 12-17. Because this study was 

based on the USDA NFCS, the limitations and advantages associated with the USDANFCS data also apply to this data set. Also, consumption patterns may have changed 

since the data were collected in 1977-78. 

U.S. EPA - Office of Science and Technology - The U.S. EPA Office of Science and 

Technology (OST) within the Office of Water (formerly the Office of Water Regulations and 

Standards) used data from the FDA revision of the Total Diet Study Food Lists and Diets 

(Pennington, 1983) to calculate food intake rates. OST uses these consumption data in 

its risk assessment model for land application of municipal sludge. The FDA data used 

are based on the combined results of the USDA 1977-78 NFCS and the second National 

Health and Nutrition Examination Survey (NHANES II), 1976-80 (U.S. EPA, 1989). 

Because food items are listed as prepared complex foods in the FDA Total Diet Study, 

each item was broken down into its component parts so that the amount of raw 

commodities consumed could be determined. Table 12-18 presents intake rates for grain 

products for various age groups. Estimated lifetime ingestion rates derived by U.S. EPA 

(1989) are also presented in Table 12-18. Note that these are per capita intake rates 

tabulated as grams dry weight/day. Therefore, these rates differ from those in the previous 

tables because USDA (1980; 1992) and U.S. EPA (1984a, 1984b) report intake rates on 

an as consumed basis. 

The EPA-OST analysis provides intake rates for additional food categories and 

estimates of lifetime average daily intake on a per capita basis. In contrast to the other 

analyses of USDA NFCS data, this study reports the data in terms of dry weight intake 

rates. Thus, conversion is not required when contaminants are provided on a dry weight 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 12 - Intake of Grain Products 

basis. These data, however, may not reflect current consumption patterns because they 

are based on 1977-78 data. 

USDA (1993) - Food Consumption, Prices, and Expenditures, 1970-92 - The USDA's 

Economic Research Service (ERS) calculates the amount of food available for human 

consumption in the United States annually. Supply and utilization balance sheets are 

generated. These are based on the flow of food items from production to end uses. Total 

available supply is estimated as the sum of production (i.e., some products are measured 

at the farm level or during processing), starting inventories, and imports (USDA, 1993). 

The availability of food for human use commonly termed as "food disappearance" is 

determined by subtracting exported foods, products used in industries, farm inputs (seed 

and feed) and end-of-the year inventories from the total available supply (USDA, 1993). 

USDA (1993) calculates the per capita food consumption by dividing the total food 

disappearance by the total U.S. population. 

USDA (1993) estimated per capita consumption data for grain products from 1970­

1992 (1992 data are preliminary). In this section, the 1991 values, which are the most 

recent final data, are presented. Table 12-19 presents per capita consumption in 1991 for 

grains. 

One of the limitations of this study is that disappearance data do not account for 

losses from the food supply from waste, spoilage, or foods fed to pets. Thus, intake rates 

based on these data may overestimate daily consumption because they are based on the 

total quantity of marketable commodity utilized. Therefore, these data may be useful for 

estimating bounding exposure estimates. It should also be noted that per capita estimates 

based on food disappearance are not a direct measure of actual consumption or quantity 

ingested, instead the data are used as indicators of changes in usage over time (USDA, 

1993). An advantage of this study is that it provides per capita consumption rates for 

grains which are representative of long-term intake because disappearance data are 

generated annually. Daily per capita intake rates are generated by dividing annual 

consumption by 365 days/year. 

12.1.4. Key Grain Products Serving Size Study Based on the USDA 

NFCS 

Pao et al. (1982) - Foods Commonly Eaten by Individuals - Using data gathered in 

the 1977-78 USDA NFCS, Pao et al. (1982) calculated percentiles for the quantities of 

grain products consumed per eating occasion by members of the U.S. population. The 

data were collected during NFCS home interviews of 37,874 respondents, who were asked 

to recall food intake for the day preceding the interview, and record food intake the day of 

the interview and the day after the interview. Quantities consumed per eating occasion, 

are presented in Table 12-20. 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 12 - Intake of Grain Products 

The advantages of using these data are that they were derived from the USDA NFCS 

and are representative of the U.S. population. This data set provides distributions of 

serving sizes for a number of commonly eaten grain products, but the list of foods is limited 

and does not account for grain products included in complex food dishes. Also, these data 

are based on short-term dietary recall and may not accurately reflect long-term 

consumption patterns. Although these data are based on the 1977-78 NFCS, serving size 

data have been collected, but not published, for the more recent USDA surveys. 

12.2. CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE RATES 

As noted previously, intake rates may be reported in terms of units as consumed or 

units of dry weight. 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 unit of food consumption is grams dry weight/day, then 

the unit for the amount of pollutant in the food should be grams dry weight). If necessary, 

as consumed intake rates may be converted to dry weight intake rates using the moisture 

content percentages of grain products presented in Table 12-21 and the following 

equation: 

IR = IR * [(100-W)/100] (Eqn. 12-1) dw ac 

“Dry weight" intake rates may be converted to "as consumed" rates by using: 

 = IRdw/[(100-W)/100] (Eqn. 12-2) 

where: 

IRdw = dry weight intake rate; 

IR = as consumed intake rate; and 

IRac 

ac 

W = percent water content. 

12.3. RECOMMENDATIONS 

The 1989-91 CSFII data described in this section were used in selecting 

recommended grain, product intake rates for the general population and various 

subgroups of the United States population. The general design of both key and relevant 

studies are summarized in Table 12-22 The recommended values for intake of grain 

products are summarized in Table 12-23 and the confidence ratings for the recommended 

values for grain intake rates are presented in Table 12-24. Per capita intake rates for 

specific grain items, on a g/kg-day basis, may be obtained from Tables 12-2 through 12­

Exposure Factors Handbook August 1997 
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Chapter 12 - Intake of Grain Products 

10. Percentiles of the intake rate distribution in the general population for total grains, are 

presented in Table 12-1. From these tables, the mean and 95th percentile intake rates for 

grains are 4.1 g/kg-day and 10.8 g/kg-day, respectively. It is important to note that the 

data presented in Tables 12-1 through 12-10 are based on data collected over a 3-day 

period and may not necessarily reflect the long-term distribution of average daily intake 

rates. However, for the broad categories of foods (i.e., total grains, breads), because they 

may be 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 

will tend to overestimate the corresponding percentiles of the true long-term distribution. 

It should be noted that because these recommendations are based on 1989-91 CSFII data, 

they may not reflect the most recent changes in consumption patterns. However, as 

indicated in Table 12-11, intake has remained fairly constant between 1989-19 and 1995. 

Thus, the 1989-91 CSFII data are believed to be appropriate for assessing ingestion 

exposure for current populations. 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 13 - Intake Rates for Various Home Produced Food Items 

13. INTAKE RATES FOR VARIOUS HOME PRODUCED FOOD ITEMS 

13.1. BACKGROUND 

Ingestion of contaminated foods is a potential pathway of exposure to toxic chemicals. 

Consumers of home produced food products may be of particular concern because 

exposure resulting from local site contamination may be higher for this subpopulation. 

According to a survey by the National Gardening Association (1987), a total of 34 million 

(or 38 percent) U.S. households participated in vegetable gardening in 1986. Table 13-1 

contains demographic data on vegetable gardening in 1986 by region/section, community 

size, and household size. 

Table 13-2 contains information on the types of vegetables grown by home gardeners 

in 1986. Tomatoes, peppers, onions, cucumbers, lettuce, beans, carrots, and corn are 

among the vegetables grown by the largest percentage of gardeners. Home produced 

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 plants 

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. Intake rates for home produced food products are needed to assess exposure 

to local contaminants present in homegrown or home caught foods. Recently, EPA 

analyzed data from the U.S. Department of Agriculture's (USDA) Nationwide Food 

Consumption Survey (NFCS) to generate distributions of intake rates for home produced 

foods. The methods used and the results of these analyses are presented below. 

13.2. METHODS 

Nationwide Food Consumption Survey (NFCS) data were used to generate intake 

rates for home produced foods. USDA conducts the NFCS every 10 years to analyze the 

food consumption behavior and dietary status of Americans (USDA, 1992). The most 

recent NFCS was conducted in 1987-88. The survey used a statistical sampling technique 

designed to ensure that all seasons, geographic regions of the 48 conterminous states in 

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 seven-day 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 three-day period 

(USDA, 1993). The sample size for the 1987-88 survey was approximately 4,300 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 13 - Intake Rates for Various Home Produced Food Items 

households (over 10,000 individuals). This is a decrease over the previous survey 

conducted in 1977-78 which sampled approximately 15,000 households (over 36,000 

individuals) (USDA, 1994). The sample size was lower in the 1987-88 survey as a result 

of budgetary constraints and low response rate (i.e., 38 percent for the household survey 

and 31 percent for the individual survey) (USDA, 1993). However, NFCS data from 1987­

88 were used to generate homegrown intake rates because they were the most recent data 

available and were believed to be more reflective of current eating patterns among the 

U.S. population.

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 non-response and other vagaries of the sample selection process" (USDA, 1987­

88). 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, 1987-88). 

For the purposes of this study, home produced foods were defined as homegrown 

fruits and vegetables, meat and dairy products derived from consumer-raised livestock or 

game meat, and home caught fish. The food items/groups selected for analysis included 

major food groups (i.e., total fruits, total vegetables, total meats, total dairy, total fish and 

shellfish), individual food items for which >30 households reported eating the home 

produced form of the item, fruits and vegetables categorized as exposed, protected, and 

roots, and various USDA fruit and vegetable subcategories (i.e., dark green vegetables, 

citrus fruits, etc.). Food items/groups were identified in the NFCS data base according to 

NFCS-defined food codes. Appendix 13A presents the codes used to determine the 

various food groups. 

Although the individual intake component of the NFCS gives the best measure of the 

amount of each food item eaten by each individual in the household, it could not be used 

directly to measure consumption of home produced food because the individual 

component does not identify the source of the food item (i.e., as home produced or not). 

Therefore, an analytical method which incorporated data from both the household and 

individual survey components was developed to estimate individual home produced food 

intake. The USDA household data were used to determine (1) the amount of each home 

produced 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. 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. 

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Chapter 13 - Intake Rates for Various Home Produced Food Items 

The individual survey data were used to generate average sex- and age-specific 

serving sizes for each food item. The age categories used in the analysis were as follows: 

1 to 2 years; 3 to 5 years; 6 to 11 years; 12 to 19 years; 20 to 39 years; 40 to 69 years; and 

over 70 years (intake rates were not calculated for children under 1; the rationale for this 

is discussed below). These serving sizes were used during subsequent analyses to 

generate homegrown food intake rates for individual household members. Assuming that 

the proportion of the household quantity of each homegrown food item/group was a 

function of the number of meals and the mean sex- and age-specific serving size for each 

family member, individual intakes of home produced food were calculated for all members 

of the survey population using SAS programming in which the following general equation 

was used: 

m qi i w ' Wf @ i n (Eqn. 13-1) ' m qi i i'1 

where: 

wi = Homegrown amount of food item/group attributed to member i during the week (g/week); 

Wf = Total quantity of homegrown 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 

q = Serving size for an individual within the age and sex category of the member (g/meal). i 

Daily intake of a homegrown food item/group was determined by dividing the weekly value 

(w ) by seven. Intake rates were indexed to the self-reported body weight of the survey 

respondent and reported in units of g/kg-day. Intake rates were not calculated for children 

under one year of age 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. In Section 13.5, a method for estimating per-capita homegrown 

intake in this age group is suggested. 

For the major food groups (fruits, vegetables, meats, dairy, and fish) and individual 

foods consumed by at least 30 households, distributions of home produced intake among 

consumers were generated for the entire data set and according to the following 

subcategories: age groups, urbanization categories, seasons, racial classifications, 

regions, and responses to the questionnaire. 

Consumers were defined as members of survey households who reported 

consumption of the food item/group of interest during the one week survey period. In 

addition, for the major food groups, distributions were generated for each region by 

season, urbanization, and responses to the questionnaire. Table 13-3 presents the codes, 

definitions, and a description of the data included in each of the subcategories. Intake 

rates were not calculated for food items/groups for which less than 30 households reported 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 13 - Intake Rates for Various Home Produced Food Items 

home produced usage because the number of observations may be inadequate for 

generating distributions that would be representative of that segment of consumers. Fruits 

and vegetables were also classified as exposed, protected, or roots, as shown in Appendix 

13A of this document. Exposed foods are those that are grown above ground and are 

likely to be contaminated by pollutants deposited on surfaces that are eaten. Protected 

products are those that have outer protective coatings that are typically removed before 

consumption. Distributions of intake were tabulated for these food classes for the same 

subcategories listed above. Distributions were also tabulated for the following USDA food 

classifications: dark green vegetables, deep yellow vegetables, other vegetables, citrus 

fruits, and other fruits. Finally, the percentages of total intake of the food items/groups 

consumed within survey households that can be attributed to home production were 

tabulated. The percentage of intake that was homegrown was calculated as the ratio of 

total intake of the homegrown food item/group by the survey population to the total intake 

of all forms of the food by the survey population. 

As disccussed in Section 13.3, percentiles of average daily intake derived from short 

time intervals (e.g., 7 days) will not, in general, be reflective of long term patterns. This 

is especially true regarding consumption of many homegrown products (e.g., fruits, 

vegetables), where there is often a strong seasonal component associated with their use. 

To try to derive, for the major food categories, the long term distribution of average daily 

intake rates from the short-term data available here, an approach was developed which 

attempted to account for seasonal variability in consumption. This approach used regional 

“seasonally adjusted distributions” to approximate regional long term distributions and then 

combined these regional adjusted distributions (in proportion to the weights for each 

region) to obtain a U.S. adjusted distribution which approximated the U.S. long term 

distribution. 

The percentiles of the seasonally adjusted distribution for a given region were 

generated by averaging the corresponding percentiles of each of the four seasonal 

distributions of the region. More formally, the seasonally adjusted distribution for each 

region is such that its inverse cumulative distribution function is the average of the inverse 

cumulative distribution functions of each of the seasonal distributions of that region. The 

use of regional seasonally adjusted distributions to approximate regional long term 

distributions is based on the assumption that each individual consumes at the same 

regional percentile levels for each season and consumes at a constant weekly rate 

throughout a given season. Thus, for instance, if the 60th percentile weekly intake level 

in the South is 14.0 g in the summer and 7.0 g in each of the three other seasons, then an 

individual in the South with an average weekly intake of 14.0 g over the summer would be 

assumed to have an intake of 14.0 g for each week of the summer and an intake of 7.0 g 

for each week of the other seasons. 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 13 - Intake Rates for Various Home Produced Food Items 

Note that the seasonally adjusted distributions derived above were generated using 

the overall distributions, i.e., both consumers and non-consumers. However, since all the 

other distributions presented in this section are based on consumers only, the percentiles 

for the adjusted distributions have been revised to reflect the percentiles among 

consumers only. Given the above assumption about how each individual consumes, the 

percentage consuming for the seasonally adjusted distributions give an estimate of the 

percentage of the population consuming the specified food category at any time during the 

year. 

The intake data presented here for consumers of home produced foods and the total 

number of individuals surveyed may be used to calculate the mean and the percentiles of 

the distribution of home produced food consumption in the overall population (consumers 

and non-consumers) as follows: 

Assuming that IR is the homegrown intake rate of food item/group at the pth 

p percentile

and N is the weighted number of individuals consuming the homegrown food item, and N c T 

is the weighted total number of individuals surveyed, then NT - N is the weighted number c 

of individuals who reported zero consumption of the food item. In addition, there are 

(p/100 x N ) individuals below the pth percentile. Therefore, the percentile that c 

corresponds to a particular intake rate (IR ) for the overall distribution of homegrown food p 

consumption (including consumers and nonconsumers) can be obtained by: 

P 

x N % (NT & N )c 100 c 

P th (Eqn. 13-2) ' 100 x overall NT 

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Volume II - Food Ingestion Factors 

Chapter 13 - Intake Rates for Various Home Produced Food Items 

For example, the percentile of the overall population that is equivalent to the 50th 

percentile consumer only intake rate for homegrown fruits would be calculated as follows: 

From Table 13-8, the 50th percentile homegrown fruit intake rate (IR ) is 1.07 g/kg-day. The weighted number of 50 

individuals consuming fruits (N c ) is 14,744,000. From Table 13-4, the weighted total number of individuals surveyed

(N ) is 188,019,000. The number of individuals consuming fruits below the 50th percentile is: T 

p/100 x N = (0.5) x (14,744,000) c 

N

= 7,372,000

The number of individuals that did not consume fruit during the survey period is:

T - Nc = 188,019,000 - 14,744,000

= 173,275,000 

The total number of individuals with homegrown intake rates at or below 1.07 g/kg-day is 

(p/100 x N c T c ) + (N - N ) = 7,372,000 + 173,275,000

= 180,647,000 

The percentile of the overall population that is represented by this intake rate is: 

' 100 x (180,647,000 / 188,109,000) th poverall ' 96th percentile 

Therefore, an intake rate of 1.07 g/kg-day of homegrown fruit corresponds to the 96th percentile of the overall 

population. 

Following the same procedure described above, 5.97 g/kg-day, which is the 90th 

percentile of the consumers only population, corresponds to the 99th percentile of the 

overall population. Likewise, 0.063 g/kg-day, which is the 1st percentile of the consumers 

only population, corresponds to the 92nd percentile of the overall population. Note that 

the consumers only distribution corresponds to the tail of the distribution for the overall 

population. Consumption rates below the 92nd percentile are very close to zero. The 

mean intake rate for the overall population can be calculated by multiplying the mean 

intake rate among consumers by the proportion of individuals consuming the homegrown 

food item, Nc/N . T 

Table 13-4 displays the weighted numbers N , as well as the unweighted total survey T 

sample sizes, for each subcategory and overall. It should be noted that the total 

unweighted number of observations in Table 13-4 (9,852) is somewhat lower than the 

number of observations reported by USDA because this study only used observations for 

family members for which age and body weight were specified. 

As mentioned above, the intake rates derived in this section are based on the amount 

of household food consumption. As measured by the NFCS, the amount of food 

“consumed” by the household is a measure of consumption in an economic sense, i.e., 

a measure of the weight of food brought into the household that has been consumed (used 

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Volume II - Food Ingestion Factors 

Chapter 13 - Intake Rates for Various Home Produced Food Items 

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. 

USDA estimated preparation losses for various foods (USDA, 1975). For meats, a 

net cooking loss, which includes dripping and volatile losses, and a net post cooking loss, 

which involves losses from cutting, bones, excess fat, scraps and juices, were derived for 

a variety of cuts and cooking methods. For each meat type (e.g., beef) EPA has averaged 

these losses across all cuts and cooking methods to obtain a mean net cooking loss and 

a mean net post cooking loss; these are displayed in Table 13-5. For individual fruits and 

vegetables, USDA (1975) also gave cooking and post-cooking losses. These data are 

presented in Tables 13-6 and 13-7. 

The following formulas can be used to convert the intake rates tabulated here to rates 

reflecting actual consumption: 

I

A=I×(1 - L1)×(1 - L2) (Eqn. 13-3) 

I

A 'I×(1&LP) (Eqn. 13-4) 

where I is the adjusted intake rate, I is the tabulated intake rate, L is the cooking loss, L A 1 2 

is the post-cooking loss and L is the paring or preparation loss. For fruits, corrections P 

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. To obtain preparation losses for food categories, the preparation 

losses of the individual foods making up the category can be averaged. 

In calculating ingestion exposure, assessors should use consistent forms in combining 

intake rates with contaminant concentrations. This issue has been previously discussed 

in the other food Chapters. 

13.3. RESULTS 

The intake rate distributions (among consumers) for total home produced fruits, 

vegetables, meats, fish and dairy products are shown, respectively, in Tables 13-8 through 

13-32 (displayed at the end of Chapter 13). Also shown in these tables is the proportion 

of respondents consuming the item during the (one-week) survey period. Homegrown 

vegetables were the most commonly consumed of the major food groups (18.3%), followed 

by fruit (7.8%), meat (4.9%), fish (2.1%), and dairy products (0.7%). The intake rates for 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 13 - Intake Rates for Various Home Produced Food Items 

the major food groups vary according to region, age, urbanization code, race, and 

response to survey questions. In general, intake rates of home produced foods are higher 

among populations in non-metropolitan and suburban areas and lowest in central city 

areas. Results of the regional analyses indicate that intake of homegrown fruits, 

vegetables, meat and dairy products is generally highest for individuals in the Midwest and 

South and lowest for those in the Northeast. Intake rates of home caught fish were 

generally highest among consumers in the South. Homegrown intake was generally higher 

among individuals who indicated that they operate a farm, grow their own vegetables, raise 

animals, and catch their own fish. The results of the seasonal analyses for all regions 

combined indicated that, in general, homegrown fruits and vegetables were eaten at a 

higher rate in summer, and home caught fish was consumed at a higher rate in spring; 

however, seasonal intake varied based on individual regions. Seasonally adjusted intake 

rate distributions for the major food groups are presented in Table 13-33. 

Tables 13-34 through 13-60 present distributions of intake for individual home 

produced food items for households that reported consuming the homegrown form of the 

food during the survey period. Intake rate distributions among consumers for homegrown 

foods categorized as exposed fruits and vegetables, protected fruits and vegetables, and 

root vegetables are presented in Tables 13-61 through 13-65; the intake distributions for 

various USDA classifications (e.g., dark green vegetables) are presented in Tables 13-66 

through 13-70. The results are presented in units of g/kg-day. Table 13-71 presents the 

fraction of household intake attributed to home produced forms of the food items/groups 

evaluated. Thus, use of these data in calculating potential dose does not require the body 

weight factor to be included in the denominator of the average daily dose (ADD) equation. 

It should be noted that converting these intake rates into units of g/day by multiplying by 

a single average body weight is inappropriate, because individual intake rates were 

indexed to the reported body weights of the survey respondents. However, if there is a 

need to compare the total intake data presented here to other intake data in units of g/day, 

a body weight less than 70 kg (i.e., approximately 60 kg; calculated based on the number 

of respondents in each age category and the average body weights for these age groups, 

as presented in Volume I, Chapter 7) should be used because the total survey population 

included children as well as adults. 

13.4. ADVANTAGES AND LIMITATIONS 

The USDA NFCS data set is the largest publicly available source of information on 

food consumption habits in the United States. The advantages of using this data set are 

that it is expected to be representative of the U.S. population and that it provides 

information on a wide variety of food groups. However, the data collected by the USDA 

NFCS are based on short-term dietary recall and the intake distributions generated from 

them may not accurately reflect long-term intake patterns, particularly with respect to the 

tails (extremes) of the distributions. Also, the two survey components (i.e., household and 

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Chapter 13 - Intake Rates for Various Home Produced Food Items 

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 high-end consumers 

within households because average serving sizes are used in calculating the proportion 

of homegrown 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 home 

produced food used within the household. However, not all family members may consume 

each home produced food item and serving sizes allocated here may not be entirely 

representative of the portion of household foods consumed by each family member. As 

was mentioned in Section 13.2, no analyses were performed for the under 1 year age 

group due to the above concerns. Below, in Section 13.5, a recommended approach for

dealing with this age group is presented. 

The preparation loss factors discussed in Section 13.2 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 1987-88 NFCS, it 

may not reflect recent changes in food consumption patterns. The low response rate 

associated with the 1987-88 NFCS also contributes to the uncertainty of the homegrown 

intake rates generated using these data. 

13.5. RECOMMENDATIONS 

The distribution data presented in this study may be used to assess exposure to 

contaminants in foods grown, raised, or caught at a specific site. Table 13-72 presents the 

confidence ratings for homegrown food intake. The recommended values for mean intake 

rates among consumers for the various home produced foods can be taken from the tables 

presented here; these can be converted to per capita rates by multiplying by the fraction 

consuming. The data presented here for consumers of home produced foods represent 

average daily intake rates of food items/groups over the seven-day survey period and do 

not account for variations in eating habits during the rest of the year; thus the percentiles 

presented here (except the seasonally adjusted) are only valid when considering 

exposures over time periods of about one week. Similarly, the figures for percentage 

consuming are also only valid over a one week time period. Since the tabulated 

percentiles reflect the distribution among consumers only, Eqn. 13-2 must be used to 

convert the percentiles shown here to ones valid for the general population. 

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Volume II - Food Ingestion Factors 

Chapter 13 - Intake Rates for Various Home Produced Food Items 

In contrast, the seasonally adjusted percentiles are designed to give percentiles of 

the long term distribution of average daily intake and the percentage consuming shown 

with this distribution is designed to estimate the percent of the population consuming at 

any time during a year. However, because the assumptions mentioned in Section 13.2 can 

not be verified to hold, these upper percentiles must be assigned a low confidence rating. 

Eqn. 13-2 may also be used with this distribution to convert percentiles among consumers 

to percentiles for the general population. 

For all the rates tabulated here, preparation loss factors should be applied, where 

appropriate. The form of the food used to estimate intake should be consistent with the 

form used to measure contaminant concentration. 

As described above, the tables do not display rates for children under 1 year of age. 

For this age group, it is recommended that per-capita homegrown consumption rates be 

estimated using the following approach. First, for each specific home produced food of 

interest, the ratio of per capita intake for children under 1 year compared to that of children 

1 to 2 years is calculated using the USDA CSFII 1989-1991 results displayed in Volume 

II, Chapters 9 and 11. Note these results are based on individual food intakes; however, 

they consider all sources of food, not just home produced. Second, the per-capita intake 

rate in the 1 to 2 year age group of the home produced food of interest is calculated as 

described above by multiplying the fraction consuming by the mean intake rate among 

consumers (both these numbers are displayed in the tables). Finally, the per capita 

homegrown intake rate in children under 1 year of the food of interest is estimated by 

multiplying the homegrown per-capita intake rate in the 1 to 2 year age group by the above 

ratio of intakes in the under 1 year age group as compared to the 1 to 2 year age group. 

The AIHC Sourcebook (AIHC, 1994) used data presented in the 1989 version of the 

Exposure Factors Handbook which reported data from the USDA 1977-78 NFCS. In this 

Handbook, new analyses of more recent data from USDA were conducted. Numbers, 

however, cannot be directly compared with previous values since the results from the new 

analyses are presented on a body weight basis. 

Exposure Factors Handbook August 1997 
Volume II - Food Ingestion Factors 

Chapter 14 - Breast Milk Intake 

14. BREAST MILK INTAKE 

14.1. BACKGROUND 

Breast milk is a potential source of exposure to toxic substances for nursing infants. 

Lipid soluble chemical compounds accumulate in body fat and may be transferred to 

breast-fed infants in the lipid portion of breast milk. Because nursing infants obtain most 

(if not all) of their dietary intake from breast milk, they are especially vulnerable to 

exposures to these compounds. Estimating the magnitude of the potential dose to infants 

from breast milk requires information on the quantity of breast milk consumed per day and 

the duration (months) over which breast-feeding occurs. Information on the fat content of 

breast milk is also needed for estimating dose from breast milk residue concentrations that 

have been indexed to lipid content. 

Several studies have generated data on breast milk intake. Typically, breast milk 

intake has been measured over a 24-hour period by weighing the infant before and after 

each feeding without changing its clothing (test weighing). The sum of the difference 

between the measured weights over the 24-hour period is assumed to be equivalent to the 

amount of breast milk consumed daily. Intakes measured using this procedure are often 

corrected for evaporative water losses (insensible water losses) between infant weighings 

(NAS, 1991). Neville et al. (1988) evaluated the validity of the test weight approach among 

bottle-fed infants by comparing the weights of milk taken from bottles with the differences 

between the infants' weights before and after feeding. When test weight data were 

corrected for insensible water loss, they were not significantly different from bottle weights. 

Conversions between weight and volume of breast milk consumed are made using the 

density of human milk (approximately 1.03 g/mL) (NAS, 1991). Recently, techniques for 

measuring breast milk intake using stable isotopes have been developed. However, few 

data based on this new technique have been published (NAS, 1991). 

Studies among nursing mothers in industrialized countries have shown that intakes 

among infants average approximately 750 to 800 g/day (728 to 777 mL/day) during the first 

4 to 5 months of life with a range of 450 to 1,200 g/day (437 to 1,165 mL/day) (NAS, 1991). 

Similar intakes have also been reported for developing countries (NAS, 1991). Infant birth 

weight and nursing frequency have been shown to influence the rate of intake (NAS, 

1991). Infants who are larger at birth and/or nurse more frequently have been shown to 

have higher intake rates. Also, breast milk production among nursing mothers has been 

reported to be somewhat higher than the amount actually consumed by the infant (NAS, 

1991). 

The available studies on breast milk intake are summarized in the following sections. 

Studies on breast milk intake rates have been classified as either key studies or relevant 

studies based on the criteria described in the Introduction (Volume I, Section 1.3.1). 

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Volume II - Food Ingestion Factors 

Chapter 14 - Breast Milk Intake 

Recommended intake rates are based on the results of key studies, but relevant studies 

are also presented to provide the reader with added perspective on the current state of 

knowledge pertaining to breast milk intake. 

Relevant data on lipid content and fat intake, breast-feeding duration and frequency, 

and the estimated percentage of the U.S. population that breast-feeds are also presented. 

14.2. KEY STUDIES ON BREAST MILK INTAKE 

Pao et al. (1980) - Milk Intakes and Feeding Patterns of Breast-fed Infants - Pao et 

al. (1980) conducted a study of 22 healthy breast-fed infants to estimate breast milk intake 

rates. Infants were categorized as completely breast-fed or partially breast-fed. Breast 

feeding mothers were recruited through LaLeche League groups. Except for one black 

infant, all other infants were from white middle-class families in southwestern Ohio. The 

goal of the study was to enroll infants as close to 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 

24-hour periods at each test interval. The weight of breast milk was converted to volume 

by assuming a density of 1.03 g/mL. Daily intake rates were calculated for each infant 

based on the mean of the three 24-hour periods. Mean daily breast milk intake rates for 

the infants surveyed at each time interval are presented in Table 14-1. For completely 

breast-fed infants, the mean intake rates were 600 mL/day at 1 month of age and 833 

mL/day at 3 months of age. Partially breast-fed infants had mean intake rates of 485 

mL/day, 467 mL/day, 395 mL/day, and 554 mL/day at 1, 3, 6, and 9 months of age, 

respectively. Pao et al. (1980) also noted that intake rates for boys in both groups were 

slightly higher than for girls. 

The advantage of this study is that data for both exclusively and partially breast-fed 

infants were collected for multiple time periods. Also, data for individual infants were 

collected over 3 consecutive days which would account for some individual variability. 

However, the number of infants in the study was relatively small and may not be entirely 

representative of the U.S. population, based on race and socioeconomic status, which may 

introduce some bias in the results. In addition, this study did not account for insensible 

water loss which may underestimate the amount of breast milk ingested. 

Dewey and Lönnerdal (1983) - Milk and Nutrient Intakes of Breast-fed Infants from 

1 to 6 Months - Dewey and Lönnerdal (1983) monitored the dietary intake of 20 breast-fed 

infants between the ages of 1 and 6 months. Most of the infants in the study were 

exclusively breast-fed (five were given some formula, and several were given small 

amounts of solid foods after 3 months of age). According to Dewey and Lönnerdal (1983), 

the mothers were all well educated and recruited through Lamaze childbirth classes in the 

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Volume II - Food Ingestion Factors 

Chapter 14 - Breast Milk Intake 

Davis area of California. Breast milk intake volume was estimated based on two 24-hour 

test weighings per month. Breast milk intake rates for the various age groups are 

presented in Table 14-2. Breast milk intake averaged 673, 782, and 896 mL/day at 1, 3, 

and 6 months of age, respectively. 

The advantage of this study is that it evaluated breast-fed infants for a period of 6 

months based on two 24-hour observations per infant per month. Corrections for 

insensible water loss apparently were not made. Also, the number of infants in the study 

was relatively small and may not be representative of U.S. population, based on race and 

socioeconomic status. 

Butte et al. (1984) - Human Milk Intake and Growth in Exclusively Breast-fed Infants ­

Breast milk intake was studied in exclusively breast-fed infants during the first 4 months 

of life (Butte et al., 1984). Breastfeeding mothers were recruited through the Baylor Milk 

Bank Program in Texas. Forty-five mother/infant pairs participated in the study. However, 

data for some time periods (i.e., 1, 2, 3, or 4 months) were missing for some mothers as 

a result of illness or other factors. The mothers were from the middle- to 

upper-socioeconomic stratum and had a mean age of 28.0 ± 3.1 years. A total of 41 

mothers were white, 2 were Hispanic, 1 was Asian, and 1 was West Indian. Infant growth 

progressed satisfactorily over the course of the study. The amount of milk ingested over 

a 24-hour period was determined using the test weighing procedure. Test weighing 

occurred over a 24-hour period for most participants, but intake among several infants was 

studied over longer periods (48 to 96 hours) to assess individual variation in intake. The 

study did not indicate whether the data were corrected for insensible water loss. Mean 

breast milk intake ranged from 723 g/day (702 mL/day) at 3 months to 751 g/day (729 

mL/day) at 1 month, with an overall mean of 733 g/day (712 mL/day) for the entire study 

period (Table 14-3). Intakes were also calculated on the basis of body weight 

(Table 14-3). Based on the results of test weighings conducted over 48 to 96 hours, the 

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 breast-fed 

infants were collected than were collected by Pao et al. (1980). However, data were 

collected over a shorter time period (i.e., 4 months compared to 6 months) and day-to-day 

variability was not characterized for all infants. In addition, the population studied may not 

be representative of the U.S. population based on race and socioeconomic status. 

Neville et al. (1988) - Studies on Human Lactation - Neville et al. (1988) studied 

breast milk intake among 13 infants during the first year of life. The mothers were all 

multiparous, nonsmoking, Caucasian women of middle- to upper-socioeconomic status 

living in Denver, Colorado (Neville et al., 1988). All women in the study practiced 

exclusive breast-feeding for at least 5 months. Solid foods were introduced at mean age 

of 7 months. Daily milk intake was estimated by the test weighing method with corrections 

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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. The 

estimated breast milk intakes for this study are listed in Table 14-4. Mean breast milk 

intakes were 770 g/day (748 mL/day), 734 g/day (713 mL/day), 766 g/day (744 mL/day), 

and 403 g/day (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 14-4 are 

estimated based on intake during only a 24-hour period. Consequently, these intake rates 

are based on short-term data that do not account for day-to-day variability among 

individual infants. Also, a smaller number of subjects was included than in the previous 

studies, and the population studied may not be representative of the U.S. population, 

based on race and socioeconomic status. 

Dewey et al. (1991a; 1991b) - The DARLING Study - The Davis Area Research on 

Lactation, Infant Nutrition and Growth (DARLING) study was conducted in 1986 to 

evaluate growth patterns, nutrient intake, morbidity, and activity levels in infants who were 

breast-fed for at least the first 12 months of life (Dewey et al., 1991a; 1991b). Seventythree infants aged 3 months were included in the study. The number of infants included 

in the study at subsequent time intervals 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" from the Davis area of California 

(Dewey et al., 1991a; 1991b). Breast milk intake was estimated by weighing the infants 

before and after each feeding and correcting for insensible water loss. Test weighings 

were conducted over a 4-day period every 3 months. The results of the study indicate that 

breast milk intake declines over the first 12 months of life. Mean breast milk intake was 

estimated to be 812 g/day (788 mL/day) at 3 months and 448 g/day (435 mL/day) at 12 

months (Table 14-5). Based on the estimated intakes at 3 months of age, variability 

between individuals (coefficient of variation (CV) = 16.3 percent) was higher than 

individual day-to-day variability (CV = 5.4 percent) for the infants in the study (Dewey et 

al., 1991a). 

The advantages of this study are that data were collected over a relatively long-time 

(4 days) period at each test interval which would account for some day-to-day infant 

variability, and corrections for insensible water loss were made. However, the population 

studied may not be representative of the U.S. population, based on race and 

socioeconomic status. 

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14.3. RELEVANT STUDIES ON BREAST MILK INTAKE 

Hofvander et al. (1982) - The Amount of Milk Consumed by 1- to 3-Month Old Breastor Bottle-Fed Infants - Hofvander et al. (1982) compared milk intake among breast-fed and 

bottle-fed infants at ages 1, 2, and 3 months of age. Intake of breast milk and breast milk 

substitutes was tabulated for 25 Swedish infants in each age group. Daily intake among 

breast-fed infants was estimated using the test weighing method. Test weighings were 

conducted over a 24-hour time period at each time interval. Daily milk intake among 

bottle-fed infants was estimated by measuring the volumetric differences in milk contained 

in bottles at the beginning and end of all feeding sessions in a 24-hour period. The mean 

intake rates for bottle-fed infants were slightly higher than for breast-fed infants for all age 

groups (Table 14-6). Also, boys consumed breast milk or breast milk substitutes at a 

slightly higher rate than girls (Table 14-7). Breast milk intake was estimated to be 656 

g/day (637 mL/day) at 1 month and 776 g/day (753 mL/day) at 3 months. 

This study was conducted among a small number of Swedish infants, but the results 

are similar to those summarized previously for U.S. studies. Insensible water losses were 

apparently not considered in this study, and only short-term data were collected. 

Köhler et al. (1984) - Food Intake and Growth of Infants Between Six and Twenty-six 

Weeks of Age on Breast Milk, Cow’s Milk, Formula, and Soy Formula - Köhler et al. (1984) 

evaluated breast milk and formula intake among normal infants between the ages of 6 and 

26 weeks. The study included 25 fully breast-fed and 34 formula-fed infants from 

suburban communities in Sweden. Intake among breast-fed infants was estimated using 

the test weighing method over a 48-hour test period. Intake among formula-fed infants 

was estimated by feeding infants from bottles with known volumes of formula and recording 

the amount consumed over a 48-hour period. Table 14-8 presents the mean breast milk 

and formula intake rates for the infants studied. Data were collected for both cow's milkbased formula and soy-based formula. The results indicated that the daily intake for 

bottle-fed infants was greater than for breast-fed infants. 

The advantages of this study are that it compares breast milk intake to formula intake 

and that test weightings were conducted over 2 consecutive days to account for variability 

in individual intake. Although the population studied was not representative of the U.S. 

population, similar intake rates were observed in the studies that were previously 

summarized. 

Axelsson et al. (1987) - Protein and Energy Intake During Weaning - Axelsson et al. 

(1987) measured food consumption and energy intake in 30 healthy Swedish infants 

between the ages of 4 and 6 months. Both formula-fed and breast-fed infants were 

studied. All infants were fed supplemental foods (i.e., pureed fruits and vegetables after 

4 months, and pureed meats and fish after 5 months). Milk intake among breast-fed 

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infants was estimated by weighing the infants before and after each feeding over a 2-day 

period at each sampling interval. Breast milk intake averaged 765 mL/day at 4.5 months 

of age, and 715 mL/day at 5.5 months of age. 

This study is based on short-term data, a small number of infants, and may not be 

representative of the U.S. population. However, the intake rates estimated by this study 

are similar to those generated by the U.S. studies that were summarized previously. 

14.4. KEY STUDIES ON LIPID CONTENT AND FAT INTAKE FROM BREAST 

MILK 

Human milk contains over 200 constituents including lipids, various proteins, 

carbohydrates, vitamins, minerals, and trace elements as well as enzymes and hormones 

(NAS, 1991). The lipid content of breast milk varies according to the length of time that 

an infant nurses. Lipid content increases from the beginning to the end of a single nursing 

session (NAS, 1991). The lipid portion accounts for approximately 4 percent of human 

breast milk (39 ± 4.0 g/L) (NAS, 1991). This value is supported by various studies that 

evaluated lipid content from human breast milk. Several studies also estimated the 

quantity of lipid consumed by breast-feeding 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 breast milk. 

Butte et al. (1984) - Human Milk Intake and Growth in Exclusively Breast-fed Infants ­

Butte et al., (1984) analyzed the lipid content of breast milk samples taken from women 

who participated in a study of breast milk intake among exclusively breast-fed infants. The 

study was conducted with over 40 women during a 4-month period. The mean lipid 

content of breast milk at various infants' ages is presented in Table 14-9. The overall lipid 

content for the 4-month study period was 34.3 ± 6.9 mg/g (3.4 percent). Butte et al. (1984) 

also calculated lipid intakes from 24-hour breast milk intakes and the lipid content of the 

human milk samples. Lipid intake was estimated to range from 23.6 g/day (3.8 g/kg-day) 

to 28.0 g/day (5.9 g/kg-day). 

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 breast milk 

lipid content from this study may not be entirely representative of breast milk lipid content 

among the U.S. population. Also, these estimates are based on short-term data and dayto-day variability was not characterized. 

Maxwell and Burmaster (1993) - A Simulation Model to Estimate a Distribution of Lipid 

Intake from Breast Milk Intake During the First Year of Life -Maxwell and Burmaster (1993) 

used a hypothetical population of 5,000 infants between birth and 1 year of age to simulate 

a distribution of daily lipid intake from breast milk. The hypothetical population 

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represented both bottle-fed and breast-fed infants aged 1 to 365 days. A distribution of 

daily lipid intake was developed based on data in Dewey et al. (1991b) on breast milk 

intake for infants at 3, 6, 9, and 12 months and breast milk lipid content, and survey data 

in Ryan et al. (1991) on the percentage of breast-fed infants under the age of 12 months 

(i.e., approximately 22 percent). A model was used to simulate intake among 1,113 of the 

5,000 infants that were expected to be breast-fed. 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 26.8 g/day and a standard deviation of 7.4 g/day (Table 

14-10). The model assumes that nursing infants are completely breast-fed and does not 

account for infants who are breast-fed longer than 1 year. Based on data collected by 

Dewey et al. (1991b), Maxwell and Burmaster (1993) estimated the lipid content of breast 

milk to be 36.7 g/L at 3 months (35.6 mg/g or 3.6%) and 40.2 g/L (39.0 mg/g or 3.9%) at 

12 months. 

The advantage of this study is that it provides a "snapshot" of daily lipid intake from 

breast milk for breast-fed infants. These results are, however, based on a simulation 

model and there are uncertainties associated with the assumptions made. The estimated 

mean lipid intake rate represents the average daily intake for nursing infants under 12 

months of age. These data are useful for performing exposure assessments when the age 

of the infant cannot be specified (i.e., 3 months or 6 months). Also, because intake rates 

are indexed to the lipid portion of the breast milk, they may be used in conjunction with 

residue concentrations indexed to fat content. 

14.5. OTHER FACTORS 

Other factors associated with breast milk intake include: the frequency of 

breast-feeding sessions per day, the duration of breast-feeding per event, the duration of 

breast-feeding during childhood, and the magnitude and nature of the population that 

breast-feeds. 

Frequency and Duration of Feeding - Hofvander et al. (1982) reported on the frequency 

of feeding among 25 bottle-fed and 25 breast-fed infants at ages 1, 2, and 3 months. The 

mean number of meals for these age groups was approximately 5 meals/day (Table 14­

11). Neville et al. (1988) reported slightly higher mean feeding frequencies. The mean 

number of meals per day for exclusively breast-fed infants was 7.3 at ages 2 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 breast feeding session is 16­

18 minutes. 

Population of Nursing Infants and Duration of Breast-Feeding During Infancy ­

According to NAS (1991), the percentage of breast-feeding women has changed 

dramatically over the years. Between 1936 and 1940, approximately 77 percent of infants 

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were breast fed, but the incidence of breast-feeding fell to approximately 22 percent in 

1972. The duration of breast-feeding also dropped from about 4 months in the early 1930s 

to 2 months in the late 1950s. After 1972, the incidence of breast-feeding began to rise 

again, reaching its peak at approximately 61 percent in 1982. The duration of 

breast-feeding also increased between 1972 and 1982. Approximately 10 percent of the 

mothers who initiated breast-feeding continued for at least 3 months in 1972; however, in 

1984, 37 percent continued breast-feeding beyond 3 months. In 1989, breast-feeding was 

initiated among 52.2 percent of newborn infants, and 40 percent continued for 3 months 

or longer (NAS, 1991). Based on the data for 1989, only about 20 percent of infants were 

still breast fed by age 5 to 6 months (NAS, 1991). Data on the actual length of time that 

infants continue to breast-feed beyond 5 or 6 months are limited (NAS, 1991). However, 

Maxwell and Burmaster (1993) estimated that approximately 22 percent of infants under 

1 year of age are breast-fed. This estimate is 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 breast-feeding practices may differ among ethnic and 

socioeconomic groups and among regions of the United States. The percentages of 

mothers who breast feed, based on ethnic background and demographic variables, are 

presented in Table 14-12 (NAS, 1991). 

Intake Rates Based on Nutritional Status - Information on differences in the quality and 

quantity of breast milk consumed based on ethnic or socioeconomic characteristics of the 

population is limited. Lönnerdal et al. (1976) studied breast 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; and similar 

data for well-nourished Swedish mothers were observed. Lönnerdal et al. (1976) stated 

that these results indicate that breast milk quality and quantity are not affected by maternal 

malnutrition. However, Brown et al. (1986a; 1986b) noted that the lactational capacity and 

energy concentration of marginally-nourished women in Bangladesh were "modestly less 

than in better nourished mothers." Breast 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 breast milk from women with larger measurements of arm circumference and 

triceps skinfold thickness had higher concentrations of fat and energy than mothers with 

less body fat. Positive correlations between maternal weight and milk fat concentrations 

were also observed. These results suggest that milk composition may be affected by 

maternal nutritional status. 

14.6. RECOMMENDATIONS 

The key studies described in this section were used in selecting recommended values 

for breast milk intake, fat content and fat intake, and other related factors. Although 

different survey designs, testing periods, and populations were utilized by the key and 

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Chapter 14 - Breast Milk Intake 

relevant studies to estimate intake, the mean and standard deviation estimates reported 

in these studies are relatively consistent. There are, however, limitations with the data. 

Data are not available for infants under 1 month of age. This subpopulation may be of 

particular concern since a larger number of newborns are totally breast fed. In addition, 

with the exception of Butte (1984), 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 10 years old 

and the sample size of the studies was small. Other subpopulations of concern such as 

mothers highly committed to breast feeding, sometimes for periods longer than 1 year, may 

not be captured by the studies presented in this chapter. Further research is needed to 

identify these subgroups and to get better estimates of breast milk intake rates. The 

general designs of both key and relevant studies and their limitations are summarized in 

Table 14-13. Table 14-14 presents the confidence rating for breast milk intake 

recommendations. 

Breast Milk Intake - The breast milk intake rates for nursing infants that have been 

reported in the key studies described in this section are summarized in Table 14-15. 

Based on the combined results of these studies, 742 mL/day is recommended to represent 

an average breast milk intake rate, and 1,033 mL/day represents an upper-percentile 

intake rate (based on the middle range of the mean plus 2 standard deviations) for infants 

between the ages of 1 and 6 months of age. The average value is the mean of the 

average intakes at 1, 3, and 6 months from the key studies listed in Table 14-15. It is 

consistent with the average intake rate of 718 to 777 mL/day estimated by NAS (1991) for 

infants during the first 4 to 5 months of life. Intake among older infants is somewhat lower, 

averaging 413 mL/day for 12-month olds (Neville et al. 1988; Dewey et al. 1991a; 1991b). 

When a time weighted average is calculated for the 12-month period, average breast milk 

intake is approximately 688 mL/day, and upper-percentile intake is approximately 980 

mL/day. Table 14-16 summarizes these recommended intake rates. 

Lipid Content and Lipid Intake - Recommended lipid intake rates are based on data from 

Butte et al. (1984) and Maxwell and Burmaster (1993). Butte et al. (1984) estimated that 

average lipid intake ranges from 23.6 ± 7.2 g/day (22.9 ± 7.0 mL/day) to 28.0 ± 8.5 g/day 

(27.2 ± 8.3 mL/day) between 1 and 4 months of age. These intake rates are consistent 

with those observed by Burmaster and Maxwell (1993) for infants under 1 year of age 

[(26.8 ± 7.4 g/day (26.0 ± 7.2 mL/day)]. Therefore, the recommended breast milk lipid 

intake rate for infants under 1 year of age is 26.0 mL/day and the upper-percentile value 

is 40.4 mL/day (based on the mean plus 2 standard deviations). The recommended value 

for breast milk fat content is 4.0 percent based on data from NAS (1991), Butte et al. 

(1984), and Maxwell and Burmaster (1993). 

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Chapter 15 - Activity Factors 

15. ACTIVITY FACTORS 

In calculating exposure, a person's average daily dose is determined from a 

combination of variables including the pollutant concentration, exposure duration, and 

frequency of exposure (Sexton and Ryan, 1987). These variables can be dependent on 

human activity patterns and time spent at each activity and/or location. A person's total 

exposure can be predicted using indirect approaches such as computerized mathematical 

models. This indirect approach of predicting exposure also requires activity patterns (time 

use) data. Thus, individual or group activities are important determinants of potential 

exposure because toxic chemicals introduced into the environment may not cause harm 

to an individual until an activity is performed subjecting the individual to contact with those 

contaminants. An individual's choice on how to spend time will vary according to their 

occupation, hobbies, culture, location, gender, age, and personal preferences. 

Educational level attained and socioeconomic status also influence chosen activities and 

their duration. 

The purpose of this section is to describe published time use studies that provide 

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 microenvironments. According to Robinson and 

Thomas (1991), microenvironments refer to a combination of activities and locations that 

yield potential exposures. Information on time spent in specific occupations and residing 

in specific areas also is included in this section. 

This section summarizes data on how much time individuals spend doing various 

activities and in various microenvironments. These data cover a wide scope of activities 

and populations. The following table (Table 15-1) should be used as a guide to locating

the information relevant to activities and microenvironments of concern. Assessors can 

consider using these data to develop exposure duration estimates for specific exposure 

scenarios. Available studies are grouped as key or relevant studies. The classifications 

of these studies are based on the applicability of their data to exposure assessments. All 

tables that provide data from these studies are presented at the back of this chapter. 

15.1. ACTIVITY PATTERNS 

The purpose of this section is to describe published time use studies that provide 

information on time-activity patterns of the national population and various sub-populations 

in the U.S. The studies involve survey designs where time diaries were used to collect 

information on the time spent at various activities and locations for children, adolescents, 

and adults, and to collect certain demographic and socioeconomic data. Available studies 

on time-activity data are summarized in the following sections. It should be noted that 

other site-limited studies, based on small sample sites, are available, but are not 

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presented in this section. The studies presented in this section are ones believed to be 

the most appropriate for the purpose of the handbook. Activity pattern studies are 

presented in Sections 15.1.1 and 15.1.2. 

15.1.1. Key Activity Pattern Studies 

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. This 

study was a follow-up of households from a previous survey conducted in 1975-76. The 

922 respondents in the 1981-82 study were those who had completed at least three out 

of four waves of interview in the 1975 - 1976 survey. Timmer et al. (1985) conducted the 

survey during February through December 1981, and households were contacted four 

times during a 3 month interval of the survey period. The first contact was a personal 

interview, followed by subsequent telephone interviews for most of the respondents. 

However, families with children were contacted personally and questionnaires were 

administered to a maximum of three children per household. 

The children surveyed were between the ages of 3 and 17 years and were 

interviewed twice. The questionnaires administered to children had two components: 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 administered to the children was 

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 above 

provided their own diary information and participated in the interview. Parents were asked 

to assess their children's socioemotional and intellectual development. A survey form was 

sent to a teacher of each school-age child to evaluate each child's socioemotional and 

intellectual development. The activity descriptor codes used in this study were developed 

by Juster et al. (1983). The activity codes and descriptors used for the adult time diaries 

in both surveys are presented in Appendix Table 15A-1. 

The mean time spent performing major activities on weekdays and weekends by age 

and sex, and type of day is presented in Table 15-2. On weekdays, children spend about 

40 percent of their time sleeping, 20 percent in school, and 10 percent eating, washing, 

dressing, and performing other personal activities (Timmer et al., 1985). The data in 

Table 15-2 indicates that girls spend more time than boys performing household work and 

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personal care activities, and less time playing sports. Also, children spend most of their 

free time watching television. Table 15-3 presents the mean time children spend during 

weekdays and weekends performing major activities by five different age groups. Also, the 

significant effects of each variable (i.e., age, sex) are shown in Table 15-3. Older children 

spend more time performing household and market work, studying and watching television, 

and less time eating, sleeping, and playing. Timmer et al. (1985) estimated that on the 

average, boys spend 19.4 hours a week watching television and girls spend 17.8 hours 

per week performing the same activity. 

A limitation associated with this study is that the data do not provide overall annual 

estimates of children's time use since the data were collected only during the time of the 

year when children attend school and not during school vacation. Another limitation is that 

a distribution pattern of children's time use was not provided. In addition, the survey was 

conducted in 1981 so there is a potential that activity patterns in children may have 

changed significantly from that period to the present. Therefore, application of these data 

for current exposure situations may bias exposure assessments results. An advantage of 

this survey is that diary recordings of activity patterns were kept and the data obtained 

were not based completely 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. 

James and Knuiman (1987) - An Application of Bayes Methodology to the Analysis 

of Diary Records from a Water Use Study - In 1987, James and Knuiman provided a 

distribution of the amount of time (1-20 minutes) spent showering by individuals in 

households located in Australia. The distribution presented in the study of James and 

Knuiman was based on diary records of 2,500 households. James and Knuiman (1987) 

reported that 50 additional households provided data for shower durations exceeding 20 

minutes, but were excluded from their analysis because specific values over 20 minutes 

were not reported. Using the data of James and Knuiman, a cumulative frequency 

distribution was derived for the handbook, based on the 2,550 households and is 

presented in Table 15-3. Based on the results in Table 15-3, approximate showering times 

are 7 minutes for the median value, 13 minutes for the 90th percentile, 16 minutes for the 

95th percentile, and >20 minutes for the 99th percentile. The mean shower length is 

approximately 8 minutes using the shower durations of 1 to 20 minutes. 

A mean value could not be calculated using the data for the 50 households that 

reported showering time >20 minutes. However, if a 30 minute showering time was 

assumed for the >20 minutes duration, the mean value would be 8.5 minutes as compared 

to a mean of 8 minutes if these households are excluded. Therefore, including the 50 

additional households would give a similar mean and the results at the upper end of the 

distribution would not be affected. 

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A limitation of the study is that the data are from households in Australia and may not 

be representative of U.S. households. An advantage is that it presents cumulative 

distribution data. 

Robinson and Thomas (1991) - Time Spent in Activities, Locations, and 

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 and from a similar 1985 national study, American's Use of Time. Data 

from the national study were recorded similarly to the CARB code categories, in order to 

make data comparisons (Robinson and Thomas, 1991). 

The CARB study involved residents who lived in the state of California. One adult 18 

years or older was randomly sampled in each household and was asked to complete a 

diary with entries for the previous day's activities and the location of each activity. Time 

use patterns for other individuals 12 years and older in the households contacted were 

also included in the diaries. Telephone interviews based on the random-digit-dialing 

(RDD) procedure were conducted for approximately 1,762 respondents in the CARB 

survey. These interviews were distributed across all days of the week and across different 

months of the year (between October 1987-August 1988). 

In the 1985 National study, single day diaries were collected from over 5,000 

respondents across the U.S., 12 years of age and older. The study was conducted during 

January through December 1985. Three modes of time diary collection were employed 

for this survey: mailback, telephone interview, and personal interview. Data obtained from 

the personal interviews were not used in this study (Robinson and Thomas, 1991). The 

sample population for the mail-back and telephone interview was selected based on a 

RDD method. The RDD was designed to represent all telephone households in the 

contiguous United States (Robinson and Thomas, 1991). In addition to estimates of time 

spent at various activities and locations, the survey design provided information on the 

employment status, age, education, race, and gender for each member of the respondent’s 

household. The mail-back procedure was based on a "tomorrow" approach, and the 

telephone interview was based on recall. In the "tomorrow" approach, respondents know, 

and agree ahead of time, that they will be keeping a diary (Robinson and Thomas, 1991).

Data comparisons by Robinson and Thomas (1991) were based on 10 major activity 

categories (100 sub-category codes) and 3 major locations (44 sub-location codes) 

employed in both the CARB and the 1985 national study. In order to make data 

comparisons, Robinson and Thomas (1991) excluded responses from individuals of ages 

65 years and older and 18 years or younger in both surveys. In addition, only mail-back 

responses were analyzed for the 1985 national study. The data were then weighted to 

project both the California and national population in terms of days of the week, region, 

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Chapter 15 - Activity Factors 

numbers of respondents per household, and 3 monthly seasons of the year (Robinson and 

Thomas, 1991). 

Table 15-5 shows the mean time spent in the 10 major activities by gender and for 

all respondents between the ages of 18-64 years (time use data for the individual activities 

are presented in Appendix Table 15A-2). In both studies respondents spent most of their 

time (642 mins/day) on personal needs and care (i.e., sleep). Californians spent more time 

on paid work, education and training, obtaining goods and services, and communication, 

and less time on household work, child care, organizational activities, entertainment/social 

activities, and recreation than the national population. The male and female population 

closely followed the same trends as the general population. Table 15-6 shows the mean 

time spent at 3 major locations for the CARB and national study grouped by total sample 

and gender, ages 18-64 years (time use data for the 44 detailed microenvironments are 

presented in Appendix Table 15A-3). Respondents spent most of their time at home, 892 

minutes/day for the CARB and 954 minutes/day for the national study. Californians spent 

more of their time away from home and traveling compared to the national population. 

In addition, Robinson and Thomas (1991) defined a set of 16 microenvironments 

based on the activity and location codes employed in both studies. The analysis included 

data for adolescents (12-17 years) and adults (65 years and older) in both the CARB study 

and the mail-back portion of the 1985 national study (Robinson and Thomas, 1991). The 

mean duration of time spent in locations for total sample population, 12 years and older, 

across three types of locations is presented in Table 15-7 for both studies. Respondents 

spent most of their time indoors, 1255 and 1279 minutes/day for the CARB and national 

study, respectively. 

Table 15-8 presents the mean duration of time and standard mean error for the 16 

microenvironments grouped by total sample population and gender. Also included is the 

mean time spent for respondents (“Doers”) who reported participating in each activity. 

Table 15-8 shows that in both studies men spend more time in work locations, 

automobiles and other vehicles, autoplaces (garages), and physical outdoor activities, 

outdoor sites. In contrast, women spend more time cooking, engaging in other kitchen 

activities, performing other chores, and shopping. The same trends also occur on a per 

participant basis. 

Table 15-9 shows the mean time spent in various microenvironments grouped by type 

of the day (weekday or weekend) in both studies. Generally, respondents spent most of 

their time during the weekends in restaurants/bars (CARB study), motor vehicles, outdoor 

activities, social-cultural settings, leisure/communication activities, and sleeping. 

Microenvironmental differences by age are presented in Table 15-10. Respondents in the 

age groups 18-24 years and 25-44 years spent most of their time in restaurants/bars and 

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Chapter 15 - Activity Factors 

traveling. The oldest age group, 65 years and older, spent most of their time in the kitchen 

(cooking and other kitchen related activities) and in communication activities. 

Limitations associated with the Robinson and Thomas (1991) study are that the 

CARB survey was based on recall and the survey was performed in California only. 

Therefore, if applied to other populations, the data set may be biased. Another limitation 

is that time distribution patterns (statistical analysis) were not provided for both studies. 

Also, the data are based on short term studies. An advantage of this study is that the 

1985 national study represents the general U.S. population. Also, the 1985 national study 

provides time estimates by activities, locations, and microenvironments grouped by age, 

gender, and type of day. Another advantage is that the data were compared and that, 

overall, both data sets showed similar patterns of activity (Robinson and Thomas, 1991). 

Wiley et al. (1991) - Study of Children's Activity Patterns - The California children's 

activity pattern survey design provided time estimates of children (under 12 years old) in 

various activities and locations (microenvironments) on a typical day (Wiley et al., 1991).

The sample population, which consisted of 1,200 respondents (including children under 

12 years of age and adult informants residing in the child's household), was selected using 

Waksberg RDD methods from English-speaking households. One child was selected from 

each household. If the selected child was 8 years old or less, the adult in the same 

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 (i.e., presence of smokers) on the diary day and the socio-demographic 

characteristics (i.e., age, gender, marital status of adult) 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-June 

1989), Summer (July-September 1989), Fall (October-December 1989), and Winter 

(January-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 average time respondents spent during the 10 activity categories for all 

children are presented in Table 15-11. Also included in this table are the detailed activity, 

including its code, with the highest mean duration of time; the percentage of respondents 

who reported participating in any activity (percent doing); and the mean, median, and 

maximum time duration for "doers." The dominant activity category, personal care (night 

sleep being the highest contributor), had the highest time expenditure of 794 mins/day 

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(13.2 hours/day). All respondents reported sleeping at night, resulting in a mean daily time 

per participant of 794 mins/day spent sleeping. The activity category "don't know" had a 

duration of about 2 mins/day and only 4 percent of the respondents reported missing 

activity time. 

Table 15-12 presents the mean time spent in the 10 activity categories by age and 

gender. Differences in activity patterns for boys and girls tended to be small. Table 15-13 

presents the mean time spent in the 10 activity categories grouped by seasons and 

California regions. There were seasonal differences for 5 activity categories: personal 

care, educational activities, social/entertainment, recreation, and communication/ passive 

leisure. Time expenditure differences in various regions of the State were minimal for 

childcare, work-related activities, shopping, personal care, education, social life, and 

recreation. 

Table 15-14 presents the distribution of time across six location categories. The 

participation rates (percent) of respondents, the mean, median, and maximum time for 

"doers." The detailed location with the highest average time expenditure are also shown. 

The largest amount of time spent was at home (1,078 minutes/day); 99 percent of 

respondents spent time at home (1,086 minutes/ participant/day). Tables 15-15 and 15-16 

show the average time spent in the six locations grouped by age and gender, and season 

and region, respectively. There are age differences in time expenditure in educational 

settings for boys and girls (Table 15-15). There are no differences in time expenditure at 

the six locations by regions, and time spent in school decreased in the summer months 

compared to other seasons (Table 15-16). Table 15-17 shows the average potential 

exposure time children spent in proximity to tobacco smoke, gasoline fumes, and gas oven 

fumes grouped by age and gender. The sampled children spent more time closer to 

tobacco smoke (77 mins/day) than gasoline fumes (2 mins/day) and gas oven fumes (11 

mins/day). 

A limitation of this study is that the sampling population was restricted to only Englishspeaking households; therefore, the data obtained does 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 seasons. 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 

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respondents to be inserted into its appropriate position during interviewing (Wiley et al., 

1991). 

U.S. EPA (1992) - Dermal Exposure Assessment: Principles and Applications - U.S. 

EPA (1992) addressed the variables of exposure time, frequency, and duration needed to 

calculate dermal exposure as related to activity. The reader is referred to the document 

for a detailed discussion of these variables in relation to soil and water related activities. 

The suggested values that can be used for dermal exposure are presented in Table 15-18. 

Limitations of this study are that the values are based on small data sets and a limited 

number of studies. An advantage is that it presents default values for frequency and 

duration for use in exposure assessments when specific data are not available. 

Tsang and Klepeis (1996) - National Human Activity Pattern Survey (NHAPS) - The 

National Human Activity Pattern Survey was conducted by the U.S. EPA (Tsang and 

Klepeis, 1996). It is the largest and most current human activity pattern survey available 

(Tsang and Klepeis, 1996). Data for 9,386 respondents in the 48 contiguous United States 

were collected via minute-by-minute 24-hour diaries between October 1992 and 

September 1994. Detailed data were collected for a maximum of 82 different possible 

locations, and a maximum of 91 different activities. Participants were selected using a 

Random Digit Dial (RDD) method and Computer Assisted Telephone Interviewing (CATI). 

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 matches the 1990 U.S. census population for each gender, age group, 

census region, and the day-of-week and seasonal responses are equally distributed. 

Saturdays and Sundays were over sampled to ensure an adequate weekend sample. 

The data presented are a compilation of 24-hour diary locations, activities, and followup exposure questions based on exposure-related events (personal, exposure, household 

characteristics, medical background) (Tsang and Klepeis, 1996). Data presented are 

reported in the form of means, percentages of time spent, and percentages of respondent 

occurrences. The diary data are useful for obtaining national representative distributions 

of time spent in a large variety of activities and locations in a single day (Tsang and 

Klepeis, 1996). According to Tsang and Klepeis (1996), the 24-hour diaries in the NHAPS 

are useful in probabilistic modeling (Monte-Carlo) that provides frequency distributions of 

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exposure. Overall survey results indicate that for time spent in microenvironments, the 

largest overall percentage of time was spent in residential-indoors (67 percent), followed 

by time spent outdoors (8 percent), and then time spent in vehicles (5 percent) (Tsang and 

Klepeis, 1996). Tables 15-19 through 15-146 provide data from the NHAPS study. 

NHAPS data on the time spent in selected activities are presented in Tables 15-19 through 

15-92. NHAPS data on the time spent in selected microenvironments are presented in 

Tables 15-93 to 15-139 and of these tables, Tables 15-66 through 15-139 present 24-hour 

cumulative statistics (mean, minimum, maximuim, and percentiles) data for time spent in 

various activities and in various microenvironments. 

C Tables 15-19 through 15-32 provide information on the frequency and duration 

of taking baths, frequency of taking showers, and on the amount of time spent in 

the shower or bathroom after completion of the activity. 

C Table 15-33 provides the frequency for washing the hands in a day. 

C Tables 15-34 through 15-36 present information on time spent by persons working 

with or being near foods while being grilled or barbecued; working with or near 

open flames; and working or being near excessive dust in the air. 

C Tables 15-37 through 15-39 provide data for the number of times a vehicle was 

started in a garage or carport and if started with the door closed; and for time 

spent at a gas station or repair shop. 

C Tables 15-40 through 15-42 present information on the number of times windows 

and doors were opened and the number of minutes they were left open at home 

while the respondent was at home. 

C Tables 15-43 through 15-47 provide data for time spent in heavy traffic either 

running, walking, standing, or in a vehicle; and for time spent in indoor and 

outdoor parking lots and garages. 

C Tables 15-48 through 15-50 present information for time spent working for pay; 

working at different times of day; and for the amount of that time was spent 

working outdoors. 

C Tables 15-51 through 15-56 provide information for number of times of performing 

household tasks in a day such as vacuuming, and washing dishes and clothes in 

a residence. 

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C	 Tables 15-57 through 15-64 present data for number of times per day and the 

duration for playing in sand, gravel, and dirt; and for working in circumstances 

where one comes in contact with soil such as in a garden. 

C	 Tables 15-65 through 15-67 provide information on the frequency of swimming in 

a fresh water swimming pool and the amount of time spent swimming during a 1­

month period. 

C Tables 15-68 through 15-87 present statistics for time spent in various major 

categories. They are as follows: Paid Work (main job); Household Work (food 

preparation and cleanup, cleaning house, clothes care); Child Care (indoor and 

outdoor playing); Obtaining Goods and Services (car repair); Personal Needs and 

Care (sleeping/napping); Free Time and Education (school); and Recreation 

(active sports, exercise, outdoor recreation). 

C Tables 15-88 through 15-94 provide statistics for time spent in various activities 

that are the results of regrouping/combining activities described in Tables 15-68 

through 15-87. Because the occurrences in some major categories were too 

small to conduct analyses, these categories were regrouped into broader 

categories so that new categories could be developed with a larger number of 

occurrences (Tsang and Klepeis, 1996). This regrouping was performed to create 

a better data set for estimating exposure activities from the available data (Tsang 

and Klepeis, 1996). 

C Tables 15-95 through 15-103 provide cumulative statistics for time spent in 

various indoor microenvironments such as repair shops/gas stations; bar/ night 

club/bowling alley; and at school. 

C Tables 15-104 through 15-112 present statistical data for time spent in various 

outdoor locations. These tables include data for locations such as 

schoolgrounds/ playground; parking lots; construction sites; parks and golf 

courses; and farms. 

C Tables 15-113 through 15-120 present statistics for time spent in various 

locations in the home. Data are presented for the number of minutes spent in the 

kitchen, bathroom, bedroom, garage, basement, utility room or laundry room; in 

the outdoor pool or spa; and in the yard or other areas outside the house. 

C Tables 15-121 through 15-130 provide data on time spent traveling and for 

traveling in various types of vehicles; and for time spent walking. 

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C	 Tables 15-131 through 15-140 provide statistics for total time spent indoors at 

home (categories regrouped/combined based on various data described in Tables 

15-95 through 15-130), including all rooms; outdoors at home; traveling inside a

vehicle; outdoors near a vehicle; outdoors other than near a residence; in an 

office or factory; in malls and other stores; in various public buildings; in bars, 

restaurants, etc.; and outdoor locations such as auto repair shops and 

laundromats. 

C Table 15-141 provides the number of minutes spent in an activity or 

microenvironment where a smoker was present. 

C Tables 15-142 and 15-143 present data for time spent smoking in a day. 

C Tables 15-144 through 15-148 provide information for time spent smoking 

selected tobacco products such as cigars, cigarettes, and pipe tobacco. 

Advantages of the NHAPS dataset 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 representative of all ages, gender, and is race specific. A disadvantage of the 

study is that means cannot be calculated for time spent over 60, 120, and 181 minutes in 

selected activities. Therefore, actual time spent at the high end of the distribution for these 

activities cannot be captured. 

15.1.2. Relevant Activity Pattern Studies 

Robinson - Changes in Americans' Use of Time: 1965-1975 (1977) - Robinson 

(1977) compared time use data obtained from two national surveys that were conducted 

in 1965-1966 and in 1975. Each survey used the time-diary method to collect data. The 

1965-66 survey excluded people in the following categories: (a) Non-Standard 

Metropolitan Statistical Area (non-SMSA) (designation of Census Bureau areas having no 

city with more than 50,000 population); (b) households where no adult members were in 

the labor force for at least 10 hours per week; (c) age 65 and over; and (d) farm-related 

occupations (Robinson, 1977). The 1,244 respondents in the 1965-66 study included 

either employed men and women or housewives (Robinson, 1977). The survey was 

conducted between November-December 1965 and March-April 1966. Respondents 

recorded their daily activities in time diaries by using the "tomorrow" approach. In this 

approach, diaries were kept on the day following the interviewer's initial contact. The 

interviewer then made a second call to the respondent to determine if the information in 

diaries were correct and to obtain additional data. Only one person per household was 

interviewed. The survey was designed to obtain information on time spent with family 

members, time spent at various locations during activities, and performing primary and 

secondary activities. 

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A similar study was conducted in 1975 from October through December. Unlike the 

1965-1966 survey, the 1975 survey included rural areas, farmers, the unemployed, 

students, and retirees. Time diary data were collected using the "yesterday" approach. 

In this approach, interviewers made only one contact with respondents (greater than 1500) 

and the diaries were filled out based on a 24-hour recall (Robinson, 1977). Time diary 

data were also collected from the respondents’ spouses. 

In both surveys, the various activities were coded into 96 categories, and then were 

combined into five major categories. Free-time activities were grouped into 5 subcategories (Appendix Table 15A-2). In order to compare data obtained from both surveys, 

Robinson (1977) excluded the same population groups in the 1975 survey that were 

excluded in the 1965-66 survey (i.e., farmers, rural residents). 

Results obtained from the surveys were presented by gender, age, marital and 

employment status, race, and education. Robinson (1977) reported the data collected in 

hours/week; however, the method for converting daily activities to hours/week were not 

presented. Table 15-149 shows the differences in time use by gender, employment, and 

marital status for five major activity categories and five subcategories for 1965 and 1975. 

Time spent on work related activities (i.e., work for pay and family care) was lower in 1975 

than in 1965 for employed men and women. Table 15-149 also shows that there was an 

overall increase in free time activities for all the six groups. The difference in time use in 

1965 and 1975 are presented by age, education, and race in Tables 15-150, 15-151, and

15-152, respectively. These tables include data for students and certain employed 

respondents that were excluded in Table 15-148 (Robinson, 1977). In 1975, the eldest 

group (ages 56-65 years) showed a decline in paid work, and an increase in family care, 

personal care and sleep (Table 15-150). Education level comparisons across the ten-year 

interval indicated that the less educated had a decrease in paid work and an increase in 

sleep and personal care; the most educated had an increase in work time and a decrease 

in other leisure (Table 15-151). For racial comparisons, Blacks spent less time at paid 

work than Whites across the ten-year interval (Table 15-152). Table 15-152 also shows 

that Blacks spent more time than Whites at free time activities in 1975. 

A limitation of the study survey design is that time use data were gathered as social 

indicators. Therefore, the activity categories presented may not be relevant in exposure 

assessments. Another limitation is that statistical analysis of the data set was not 

provided. Additional limitations are that the time use data are old and the data may not 

reflect recent changes in time use. The 1965 and 1975 data sets excluded certain 

population groups and, therefore, may not be entirely representative of the U.S. 

population. Another limitation is that these are short-term studies and may not necessarily 

represent long-term activity patterns. An advantage of this study is that time use data were 

presented by age, gender, race, education level, and employment and marital status. 

Another advantage is that earlier investigations on the study method (24-hr recall) 

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employed in the 1965 study revealed no systematic biases in reported activities (Robinson, 

1977). Robinson (1977) also noted that the time-diary method provides a "zero-sum" 

measure (i.e., since there are only 24 daily hours or 168 weekly hours, if time on one 

activity increases then time on another activity must decrease). 

Juster et al. (1983) - 1975-1981 Time Use Longitudinal Panel Study - The Time 

Allocation longitudinal study of the U.S. population began as part of a multinational project 

with the first survey conducted in 1965-66. A second national time use survey was 

conducted in 1975-1976 and another in 1981 (Juster et al. 1983). Juster et al. (1983) 

provided study descriptions of the second and third surveys. The surveys included a 

probability sample of the adult population (18 years and older) and children between the 

ages of 3 and 17 years in the United States. In both surveys, time use was measured from 

24-hour recall diaries administered to respondents and their spouses. The 1975-1976 

survey involved four waves of interview: wave 1, October-November 1975; wave 2, 

February 1976; wave 3, May-June 1976; wave 4, September 1976. The first wave was a 

personal interview and the other three waves were telephone interviews. The 1975-1976 

survey sample consisted of 2,300 individuals, and of that sample, 1,519 respondents. 

Four recall diaries (one from each wave of interviews) were obtained from 947 

respondents, with data on time use measures for two weekdays, one Saturday and one 

Sunday. The survey was designed to gather information for: employment status; earnings 

and other income; "consumption benefits for activities of respondents and their spouses;" 

health, friendships and associations of the respondents; stock technology available to the 

household, house repair, and maintenance activities of the family; division of labor in 

household work and related attitudes; physical characteristics of the respondents housing 

structure, net worth and housing values; job characteristics; and characteristics of mass 

media usage on a typical day (Juster et al., 1983). 

The 1981 survey was a follow-up of respondents and spouses who had completed 

at least three waves of interview in the 1975-1976 survey. For the 1981 survey, 920 

individuals were eligible. The survey design was similar to the 1975-1976 survey, however 

in this survey, the adult population was 25 years and older and consisted of 620 

respondents. Four waves of interviews were conducted between February - March 1981 

(wave 1), May - June 1981 (wave 2), September 1981 (wave 3), and November ­

December (wave 4). The 1981 survey included the respondents' children between the 

ages of 3 and 17 years. The survey design for children provided information on time use 

measures from two time diary reports: one school day and one non-school day. In 

addition, information for academic achievement measures, school and family life 

measures, and ratings from the children's teachers were gathered during the survey. 

Juster et al. (1983) did not report the time use data obtained for the 1975-1976 

survey or the 1981 survey. These data are stored in four tape files and can be obtained 

from the Inter-university Consortium for Political and Social Research (ICPSR) in Michigan. 

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The response rate for the first wave of interview (1975-76 survey) based on the original 

sample population was 66 percent, and response rates for the subsequent waves ranged 

from 42 percent (wave 4) to 50 percent (wave 2). In the 1981 survey, the response rate 

based on eligible respondents was 67 percent for the first interview, and ranged from 54 

percent (wave 4) to 60 percent (wave 2) in the subsequent interviews (Juster et al., 1983). 

The 1975-1976 survey included 87 activities. In the 1981 survey, these 87 activities were 

broken down into smaller components, resulting in 223 activities (Juster et al., 1983). The 

activity codes and descriptors used for the adult time diaries in both surveys are presented 

in Appendix Table 15A-1. 

A limitation of this study is that the surveys were not designed for exposure 

assessment purposes. Therefore, the time use data set may be biased. Another limitation 

is that time use data collected were based on a 24-hour diary recall. This may somewhat 

bias the data set obtained from this survey. An advantage associated with this survey is 

that it provides a database of information on various human activities. This information 

can be used to assess various exposure pathways and scenarios associated with these 

activities. Also, some of the data from these surveys were used in the studies conducted 

by Timmer et al. (1985) and Hill (1985). In addition, the activity descriptor codes 

developed in these studies were used by Timmer et al (1985), Hill (1985), and Robinson 

and Thomas (1991). These studies are presented in Sections 15.1.1 and 15.1.2. Another 

advantage of this survey is that the data are based on a national survey and conducted 

over a one year period, resulting in a seasonally balanced survey and one representative 

of the U.S. population. 

Hill (1985) - Patterns of Time Use - Hill (1985) investigated the total amount of time 

American adults spend in one year performing various activities and the variation in time 

use across three different dimensions: demographic characteristics, geographical location, 

and seasonal characteristics. In this study, time estimates were based on data collected 

from time diaries in four waves (1 per season) of a survey conducted in the fall of 1975 

through the fall of 1976 for the 1975-1976 Time Allocation Study. The sampling periods 

included two weekdays, one Saturday and one Sunday. The 1975-1976 Time Allocation 

Study provided information on the amount of time spent performing primary activities. The 

information gathered were responses to the survey question "What were you doing?" The 

survey also provided information on secondary activities (i.e., respondents performing 

more than one activity at the same time). Hill (1985) analyzed time estimates for 10 broad 

categories of activities based on data collected from 87 activities. These estimates 

included seasonal variation in time use patterns and comparisons of time use patterns for 

different days of the week. The 10 major categories and ranges of activity codes are listed 

in Appendix Table 15A-4. Hill (1985) collected data on time use for the major activity 

patterns in four different age groups (18-24, 25-44, 45-64, and 65 years and older). 

However, the time use data were summarized in graphs rather than in tables. 

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Analysis of the 1975-76 survey data revealed very small regional differences in time 

use among the broad activity patterns (Hill, 1985). The weighted mean hours per week 

spent performing the 10 major activity categories presented by region are shown in 

Table 15-153. In all regions, adults spent more time on personal care (included night 

sleep). Adults in the North Central region of the country spent more time on market work 

activities than adults in other regions of the country. Adults in the South spent more time 

on leisure activities (passive and active combined) than adults elsewhere (Table 15-153).

Table 15-154 presents the time spent per day, by the day of the week for the 10 major 

activity categories. Time spent on the 87 activities (components of the 10 major 

categories) are presented in Appendix Table 15A-5. Adult time use was dominated in 

descending order by personal care (including sleep), market work, passive leisure, and 

house work. Collectively, these activities represent about 80 percent of available time 

(Hill, 1985). 

According to Hill (1985), sleep was the single most dominant activity averaging about 

56.3 hours per week. Television watching (passive leisure) averaged about 21.8 hours 

per week, and housework activities averaged about 14.7 hours per week. Weekdays were 

predominantly market-work oriented. Weekends (Saturday and Sunday) were 

predominantly devoted to household tasks ("sleeping in," socializing, and active leisure) 

(Hill, 1985). Table 15-155 presents the mean time spent performing these 10 groups of 

activities during each wave of interview (fall, winter, spring, and summer). Adjustments 

were made to the data to assure equal distributions of weekdays, Saturdays, and Sundays 

(Hill, 1985). The data indicates that the time periods adults spent performing market work, 

child care, shopping, organizational activities, and active leisure were fairly constant 

throughout the year (Hill, 1985). The mean hours spent per week in performing the 10 

major activity patterns are presented by gender in Table 15-156 (time use patterns for all 

87 activities are presented in Appendix Table 15A-6). Table 15-156 indicates that time 

use patterns determined by data collected for the mid-1970's survey show gender 

differences. Men spent more time on activities related to labor market work and education, 

and women spent more time on household work activities. 

A limitation associated with this study is that the time data were obtained from an old 

survey conducted in the mid-1970s. Because of fairly rapid changes in American society, 

applying these data to current exposure assessments may result in some biases. Another 

limitation is that time use data were not presented for children. An advantage of this study 

is that time diaries were kept and data were not based on recall. The former approach 

may result in a more accurate data set. Another advantage of this study is that the survey 

is seasonally balanced since it was conducted throughout the year and the data are from 

a large survey sample. 

Sell (1989) - The Use of Children's Activity Patterns in the Development of a Strategy 

for Soil Sampling in West Central Phoenix - In a report prepared for the Arizona 

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Department of Environmental Quality, Sell (1989) investigated the activity patterns of 

preschool and school age children in the west central portion of Phoenix known as 

Maryvale. The survey was conducted in two parts: (1) most of the school age children 

were interviewed personally from May through June, 1989 in three schools; and (2) survey 

questionnaires were mailed to parents of preschool children. 

In the first survey, 15 percent of the total school population (2,008) was sampled with 

111 children in grades K-6 participating (response rate of 37 percent). The surveyed 

population was 53.2 percent male and 46.8 percent female. Of this population, 41 percent 

were Hispanics, 49.5 percent Anglos, 7.2 percent Blacks, and 1.7 percent Asians. The 

children interviewed were between the ages of 5 and 13 years. Within each school, the 

children in grades K-6 were stratified into two groups, primary (grades K-3) and 

intermediate (grades 4-6), and children were selected randomly from each group. Children 

in grades K-2 were either interviewed in school or at home in the presence of a parent or 

an adult care-provider. In the course of the interview, children were asked to identify 

locations of activity areas, social areas (i.e., places they went with friends), favorite areas, 

and locations of forts or clubhouses. Aerial photographs were used to mark these areas. 

The second survey involved only preschool children. Parents completed 

questionnaires which provided information on the amount of time their children spent 

outdoors, outdoor play locations, favorite places, digging areas, use of park or 

playgrounds, and swimming or wading locations. This survey was conducted between 

June-July 1989. One thousand (1,000) parents were sampled, but only 211 

questionnaires were usable out of 886 questionnaires received resulting in a response rate 

for the preschool's survey of about 24 percent. The sample population consisted of 

children 1 month and up to preschool age. Of this population, 53 percent were Anglos, 18 

percent Hispanics, 2 percent Blacks, and 3 percent Asians. 

The survey design considered the kinds of activities children engaged in, but not the 

amount of time children spent in each activity. Therefore, Sell (1989) presented the data 

obtained from the survey in terms of percent of respondents who engaged in specific 

activities or locations. A summary of percent responses of the preschool and school-age 

children's activities at various locations in the Maryvale study areas are presented in 

Table 15-157. Also included in this table is a ranking of children's play locations based 

on other existing research works. Based on the survey data, Sell (1989) reported that the 

median time preschool children spent outdoors on weekdays was 1-2 hours, and on 

weekends the median time spent outdoors was 2-5 hours. Most of these children played 

outside in their own yards, and some played in other people's yards or parks and 

playgrounds (Sell, 1989). 

Limitations associated with this study are that the survey design did not report the 

time spent in various activities or locations and the response rates obtained from the 

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surveys were low and, therefore, may result in biased data. In addition, because the 

survey was conducted in Arizona, the surveyed population does not represent the 

children's population on a national basis. Advantages of this study are that it provides 

data on various activities children engage in and locations of these activities, and provides 

for time spent outdoors. This information is useful in determining exposure pathways to 

toxic pollutants for children. 

Tarshis (1981) - The Average American Book - Tarshis (1981) compiled a book 

addressing the habits, tastes, lifestyles, and attitudes of the American people in which he 

reported data on time spent in personal grooming. The data presented are gathered from 

small surveys, the Newspaper Advertising Bureau, and magazines. Tarshis reported 

frequency and percentage data by gender and age for grooming activities such as 

showering and bathing as follows: 

• 90 percent take some sort of a bath in an average 24-hour period; 

• 5 percent average more than 1 shower or bath a day; 

• 75 percent of men shower, 25 percent take baths; 

• 50 percent of women take showers, 50 percent take baths; 

• 65 percent of teenage girls 16-19 shower daily; 

• 55 percent of teenage girls take at least one bath a week; 

• 50 percent of women use an additive in their bath every time they bathe; 

• People are more likely to shower than bathe if they are young and have higher 

income; and 

• Showering is more popular than bathing in large cities. 

Limitations of this study are that the data are compiled from other sources, and that 

the data are old; it is possible that these data may not reflect the current trends of the 

general population. An advantage of the study is that it presents frequency data that are 

useful in exposure assessment, especially concerning volatilization of chemicals from 

water. 

AIHC (1994) - Exposure Factors Sourcebook - The activity factors data presented in 

the Sourcebook are similar to that in this handbook. The AIHC Sourcebook uses tenure 

data from the Bureau of Labor Statistics (1987), while this handbook uses more recent 

data (Carey, 1988) and provides general and specific recommendations for various age 

groups. Distributions were derived using data presented in U.S. EPA (1989) version of this 

handbook, the Bureau of Labor Statistics (1987), and various other references. 

Distribution data and/or recommendations are presented for time in one residence, 

residential occupancy, time spent indoors/outdoors, hours at home/away from home for 

adults and children, hours at work for adults, working tenure, and shower duration. For 

each distribution, the @Risk formula is provided for direct use in the @Risk software 

(Palisade, 1992). The Sourcebook has been classified as a relevant rather than a key 

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study because it is not the primary source for the data used to make recommendations. 

It is a relevant source of alterative information. 

15.2. OCCUPATIONAL MOBILITY 

15.2.1. Background 

The amount of time spent in different types of occupations may affect the duration 

and/or magnitude of exposures to contaminants specific to those occupations. For 

example, an individual who spends an entire lifetime as a farmer may experience a longer 

duration of exposure to certain contaminants, especially pesticides, than individuals who 

have indoor occupations. Also, individual exposures to specific chemicals in the work 

place may be significantly reduced when individuals change jobs. Work place exposures 

among women may be of shorter duration than among men because women's careers may 

be interrupted by home and family responsibilities. The key studies presented in the 

following section provide occupational tenure for workers grouped by age, race, gender, 

and employment status. 

15.2.2. Key Occupational Mobility Studies 

Carey (1988) - Occupational Tenure in 1987: Many Workers Have Remained in Their 

Fields - Carey (1988) presented median occupational and employer tenure for different 

age groups, gender, earnings, ethnicity, and educational attainment. Occupational tenure 

was defined as "the cumulative number of years a person worked in his or her current 

occupation, regardless of number of employers, interruptions in employment, or time spent 

in other occupations" (Carey, 1988). The information presented was obtained from 

supplemental data to the January 1987 Current Population Study, a U.S. Bureau of the 

Census publication. Carey (1988) did not present information on the survey design. 

The median occupational tenure by age and gender, ethnicity, and employment status 

are presented in Tables 15-158, 15-159, and 15-160, respectively. The median 

occupational tenure of the working population (109.1 million people) 16 years of age and 

older in January of 1987, was 6.6 years (Table 15-158). Table 15-158 also shows that 

median occupational tenure increased from 1.9 years for workers 16-24 years old to 21.9 

years for workers 70 years and older. The median occupational tenure for men 16 years 

and older was higher (7.9 years) than for women of the same age group (5.4 years). Table 

15-159 indicates that whites had longer occupational tenure (6.7 years) than blacks (5.8 

years), and Hispanics (4.5 years). Full-time workers had more occupational tenure than 

part-time workers 7.2 years and 3.1 years, respectively (Table 15-160). 

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Table 15-161 presents the median occupational tenure among major occupational 

groups. The median tenure ranged from 4.1 years for service workers to 10.4 years for 

people employed in farming, forestry, and fishing. In addition, median occupational tenure 

among detailed occupations ranged from 24.8 years for barbers to 1.5 years for food 

counter and fountain workers (Appendix Table 15A-7).

The strength of an individual's attachment to a specific occupation has been 

attributed to the individual's investment in education (Carey, 1988). Carey (1988) reported 

the median occupational tenure for the surveyed working population by age and 

educational level. Workers with 5 or more years of college had the highest median 

occupational tenure of 10.1 years. Workers that were 65 years and older with 5 or more 

years of college had the highest occupational tenure level of 33.8 years. The median 

occupational tenure was 10.6 years for self-employed workers and 6.2 years for wage and 

salary workers (Carey, 1988). 

A limitation associated with this study is that the survey design employed in the data 

collection was not presented. Therefore, the validity and accuracy of the data set cannot 

be determined. Another limitation is that only median values were reported in the study. 

An advantage of this study is that occupational tenure (years spent in a specific 

occupation) was obtained for various age groups by gender, ethnicity, employment status, 

and educational level. Another advantage of this study is that the data were based on a 

survey population which appears to represent the general U.S. population. 

Carey (1990) - Occupational Tenure, Employer Tenure, and Occupational Mobility ­

Carey (1990) conducted another study that was similar in scope to the study of Carey 

(1988). The January 1987 Current Population Study (CPS) was used. This study provided 

data on occupational mobility and employer tenure in addition to occupational tenure. 

Occupational tenure was defined in Carey (1988) as the "the cumulative number of years 

a person worked in his or her current occupation, regardless of number of employees, 

interruptions in employment, or time spent in other locations." Employer tenure was 

defined as "the length of time a worker has been with the same employer," while 

occupational mobility was defined as "the number of workers who change from one 

occupation to another" (Carey, 1990). Occupational mobility was measured by asking 

individuals who were employed in both January 1986 and January 1987 if they were doing 

the same kind of work in each of these months (Carey, 1990). Carey (1990) further 

analyzed the occupational mobility data and obtained information on entry and exit rates 

for occupations. These rates were defined as "the percentage of persons employed in an 

occupation who had voluntarily entered it from another occupation" and an exit rate was 

defined as "the percentage of persons employed in an occupation who had voluntarily left 

for a new occupation" (Carey, 1990). 

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Table 15-162 shows the voluntary occupational mobility rates in January 1987 for 

workers 16 years and older. For all workers, the overall voluntary occupational mobility 

rate was 5.3 percent. These data also show that younger workers left occupations at a 

higher rate than older workers. Carey (1990) reported that 10 million of the 100.1 million 

individuals employed in January 1986 and in January 1987 had changed occupations 

during that period, resulting in an overall mobility rate of 9.9 percent. Executive, 

administrative, and managerial occupations had the highest entry rate of 5.3 percent, 

followed by administrative support (including clerical) at 4.9 percent. Sales had the 

highest exit rate of 5.3 percent and service had the second highest exit rate of 4.8 percent 

(Carey, 1990). In January 1987, the median employer tenure for all workers was 4.2 

years. The median employee tenure was 12.4 years for those workers that were 65 years 

of age and older (Carey, 1990). 

Because the study was conducted by Carey (1990) in a manner similar to that of the 

previous study (Carey, 1988), the same advantages and disadvantages associated with 

Carey (1988) also apply to this data set. 

15.3. POPULATION MOBILITY 

15.3.1. Background 

An assessment of population mobility can assist in determining the length of time a 

household is exposed in a particular location. For example, the duration of exposure to 

site-specific contamination, such as a polluted stream from which a family fishes or 

contaminated soil on which children play or vegetables are grown, will be directly related 

to the period of time residents live near the contaminated site. 

Information regarding population mobility is compiled and published by the U.S. 

Bureau of the Census (BOC). Banks, insurance companies, credit card companies, real 

estate and housing associations use residence history information. However, usually this 

information is confidential. Information compiled by the BOC provides information about 

population mobility; however, it is difficult to determine the average residence time of a 

homeowner or apartment dweller from this information. Census data provide 

representations of a cross-section of the population at specific points in time, but the 

surveys are not designed to follow individual families through time. The most current BOC 

information about annual geographical mobility and mobility by State is summarized in 

Appendix 15B. Figure 15-1 graphically displays the distribution of movers by type of move 

(BOC, 1993a). 

Available information was provided by the Oxford Development Corporation, the 

National Association of Realtors (NAR), and the BOC. According to Oxford Development 

Corporation, a property management firm, the typical residence time for an apartment 

dweller for their corporation has been estimated to range from 18 to 30 months (S. 

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Cameron Hendricks, Sales Department, Oxford Development Corporation, Gaithersburg, 

MD, personal communication with P. Wood (Versar) August 10, 1992). 

15.3.2. Key Population Mobility Studies 

Israeli and Nelson (1992) - Distribution and Expected Time of Residence for U.S. 

Households - In risk assessments, the average current residence time (time since moving 

into current residence) has often been used as a substitute for the average total residence 

time (time between moving into and out of a residence) (Israeli and Nelson, 1992). Israeli 

and Nelson (1992) have estimated distributions of expected time of residence for U.S. 

households. Distributions and averages for both current and total residence times were 

calculated for several housing categories using the 1985 and 1987 BOC housing survey 

data. The total residence time distribution was estimated from current residence time data 

by modeling the moving process (Israeli and Nelson, 1992). Israeli and Nelson (1992) 

estimated the average total residence time for a household to be approximately 4.6 years 

or 1/6 of the expected life span (see Table 15-163). The maximal total residence time that 

a given fraction of households will live in the same residence is presented in Table 15-164. 

For example, only 5 percent of the individuals in the "All Households" category will live in 

the same residence for 23 years and 95 percent will move in less than 23 years. 

The authors note that the data presented are for the expected time a household will 

stay in the same residence. The data do not predict the expected residence time for each 

member of the household, which is generally expected to be smaller (Israeli and 

Nelson, 1992). These values are more realistic estimates for the individual total residence 

time, than the average time a household has been living at its current residence. The 

expected total residence time for a household is consistently less than the average current 

residence time. This is the result of greater weighting of short residence time when 

calculating the average total residence time than when calculating the average current 

residence time (Israeli and Nelson, 1992). When averaging total residence over a time 

interval, frequent movers may appear several times, but when averaging current residence 

times, each household appears only once (Israeli and Nelson, 1992). According to Israeli 

and Nelson (1992), the residence time distribution developed by the model is skewed and 

the median values are considerably less than the means (T), which are less than the 

average current residence times. 

U.S. Bureau of the Census (1993b) - American Housing Survey for the United States

in 1991 - This survey is a national sample of 55,000 interviews in which collected data 

were presented owners, renters, Black householders, and Hispanic householders. The 

data reflect the number of years a unit has been occupied and represent all occupied 

housing units that the residents’ rented or owned at the time of the survey. 

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The results of the survey pertaining to residence time of owner/renter occupied units 

in the U.S. are presented in Table 15-165. Using the data in Table 15-165, the 

percentages of householders living in houses for specified time ranges were determined 

and are presented in Table 15-166. Based on the BOC data in Table 15-165, the 50th 

percentile and the 90th percentile values were calculated for the number of years lived in 

the householder's current house. These values were calculated by apportioning the total 

sample size (93,147 households) to the indicated percentile associated with the applicable 

range of years lived in the current home. Assuming an even distribution within the 

appropriate range, the 50th and 90th percentile values for years living in current home 

were determined to be 9.1 and 32.7 years, respectively. These were then rounded to 9 

and 33 years. Based on the above data, the range of 9 to 33 years is assumed to best 

represent a central tendency estimate of length of residence and upper percentile estimate 

of residence time, respectively. 

A limitation associated with the above analysis is the assumption that there is an even 

distribution within the different ranges. As a result, the 50th and 90th percentile values 

may be biased. 

Johnson and Capel (1992) - A Monte Carlo Approach to Simulating Residential 

Occupancy Periods and It's Application to the General U.S. Population - Johnson and 

Capel developed a methodology to estimate the distribution of the residential occupancy 

period (ROP) in the national population. ROP denotes the time (years) between a person 

moving into a residence and the time the person moves out or dies. The methodology 

used a Monte Carlo approach to simulate a distribution of ROP for 500,000 persons using 

data on population, mobility, and mortality. 

The methodology consisted of six steps. The first step defined the population of 

interest and categorized them by location, gender, age, sex, and race. Next the 

demographic groups were selected and the fraction of the specified population that fell into 

each group was developed using U.S. BOC data. A mobility table was developed based 

on census data, which provided the probability that a person with specified demographics 

did not move during the previous year. The fifth step used data on vital statistics published 

by the National Center for Health Statistics and developed a mortality table which provided 

the probability that individuals with specific demographic characteristics would die during 

the upcoming year. As a final step, a computer based algorithm was used to apply a 

Monte Carlo approach to a series of persons selected at random from the population being 

analyzed. 

Table 15-167 presents the results for residential occupancy periods for the total 

population, by gender. The estimated mean ROP for the total population was 11.7 years. 

The distribution was skewed (Johnson and Capel, 1992): the 25th, 50th, and 75th 

percentiles were 4, 9, and 16 years, respectively. The 90th, 95th, and 99th percentiles 

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were 26, 33, and 47 years, respectively. The mean ROP was 11.1 years for males and 

12.3 years for females, and the median value was 8 years for males and 9 years for 

females. 

Descriptive statistics for subgroups defined by current ages were also calculated. 

These data, presented by gender, are shown in Table 15-168. The mean ROP increases 

from age 3 to age 12 and there is a noticeable decrease at age 24. However, there is a 

steady increase from age 24 through age 81. 

There are a few biases within this methodology that have been noted by the authors. 

The probability of not moving is estimated as a function only of gender and age. The 

Monte Carlo process assumes that this probability is independent of (1) the calendar year 

to which it is applied, and (2) the past history of the person being simulated. These 

assumptions, according to Johnson and Capel (1992), are not entirely correct. They 

believe that extreme values are a function of sample size and will, for the most part, 

increase as the number of simulated persons increases. 

15.3.3. Relevant Population Mobility Studies 

National Association of Realtors (NAR) (1993) The Home Buying and Selling Process 

- The NAR survey was conducted by mailing a questionnaire to 15,000 home buyers 

throughout the U.S. who purchased homes during the second half of 1993. The survey 

was conducted in December 1993 and 1,763 usable responses were received, equaling 

a response rate of 12 percent (NAR, 1993). Of the respondents, forty-one percent were 

first time buyers. Home buyer names and addresses were obtained from Dataman 

Information Services (DIS). DIS compiles information on residential real estate 

transactions from more than 600 counties throughout the United States using courthouse 

deed records. Most of the 250 Metropolitan Statistical Areas are also covered in the DIS 

data compilation. 

The home buyers were questioned on the length of time they owned their previous 

home. Typical homebuyer (41%) was found to have lived in their previous home between 

4 and 7 years (Table 15-169). The survey results indicate that the average tenure of home 

buyers is 7.1 years based on an overall residence history of the respondents (NAR, 1993). 

In addition, the median length of residence in respondents' previous homes was found to 

be 6 years (see Table 15-170). 

The distances the respondents moved to their new homes were typically short 

distances. Data presented in Table 15-171 indicate that the mean distances range from 

230 miles for new home buyers and repeat buyers to 8 years for first time buyers and 

existing home buyers. Seventeen (17) percent of respondents purchased homes over 100 

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miles from their previous homes and 49 percent purchased homes less than 10 miles 

away. 

Lehman (1994) - Homeowners Relocating at Faster Pace - Lehman (1994) presents 

data gathered by the Chicago Title and Trust Family Insurers. The data indicate that, in 

1993, average U.S. homeowners moved every 12 years. In 1992, homeowners moved 

every 13.4 years and in 1991, every 14.3 years. Data from the U.S. Bureau of the Census 

indicate that 7 percent of the owner population moved in 1991. Based on this information, 

Lehman has concluded that it would take 12 years for 100 percent of owners to move. 

According to Lehman, Bill Harriett of the U.S. Bureau of the Census has been said that 14 

years is a closer estimate for the time required for 100 percent of home owners to move. 

An advantage of this study is that it provides percentile data for the residential occupancy 

period. 

15.4. RECOMMENDATIONS 

Assessors are commonly interested in a number of specific types of time use data 

including time/frequencies for bathing, showering, gardening, residence time, indoor 

versus outdoor time, swimming, occupational tenure, and population mobility. 

Recommendations for each of these are discussed below. The confidence 

recommendations for activity patterns is presented in Table 15-172. 

15.4.1. Recommendations for Activity Patterns 

Following are recommendations for selected activities known to increase an 

individual's exposure to certain chemicals. These activities are time spent indoors versus 

outdoors and gardening, bathing and showering, swimming, residential time spent indoors 

and outdoors, and traveling inside a vehicle. 

Time Spent Indoors Versus Outdoors and Gardening - Assessors often require 

knowledge of time individuals spend indoors versus outdoors. Ideally, this issue would 

be addressed on a site-specific basis since the times are likely to vary considerably 

depending on the climate, residential setting (i.e., rural versus urban), personal traits (i.e., 

age, health) and personal habits. The following general recommendation is offered in the 

absence of site-specific information. The key study by Robinson and Thomas (1991) 

compares the time use values derived in the CARB and National Studies; data are 

presented only for persons 12 years and older. The time use values did not differ 

significantly between the two studies and were averaged to provide the following 

recommended values. These values are applicable to individuals 12 years and older. 

Approximately 21 hrs/day are spent indoors; 1.5 hrs/day are spent outdoors, and 1.5 

hrs/day are spent in a vehicle. 

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Activities can vary significantly with differences in age. Special attention should be 

given to the activities of populations under the age of 12 years. Timmer et al. (1985) 

presented data on time spent in various activities for boys and girls ages 3-11 years. The 

study focused on activities performed indoors such as household work, personal care, 

eating, sleeping, school, studying, attending church, watching television, and engaging in 

household conversations. The average times spent in each indoor activity (and half the 

times spent in each activity which could have occurred indoors or outdoors) were summed. 

This procedure resulted in the following recommendations: 

• Indoor activities accounted for about 78 percent of the total time in weekdays and 

70 percent total time in weekend days. The corresponding times spent indoors are 

19 hrs/day for weekdays and 17 hrs/day on weekends. 

• Outdoor activities accounted for about 22 percent of children’s time during 

weekdays and 30 percent during the weekend. The corresponding times spent 

outdoors are 5 hrs/day for weekdays and 7 hrs/day on weekends. 

Assessors evaluating soil exposures are commonly interested in data on gardening 

times and frequencies. No data specific to time spent gardening could be found; thus, no 

firm recommendation could be made. However, three sets of data were found which 

indirectly relate to this issue which the assessor can consider in deriving time estimates 

for gardening: 

• Robinson and Thomas (1991) estimated the time spent in “other outdoor activities” 

(Table 15-8) as 1 hr/day. These data apply to populations 12 years and older. 

• Hill (1985) estimated that time spent in “house work and/or yard work” (Table 15­

153) as 2 hr/day. These data apply to adult populations. 

C	Tsang and Klepeis (1996) estimated that time spent in the garden or other 

circumstances working with soil for persons 18-64 years old (Table 15-62) for the 

90th, 95th, and 99th percentile at 16, 40, and 200 hours/month, respectively. 

U.S. EPA’s Dermal Exposure Assessment Document (1992) recommends, on the 

basis of judgement, an event frequency for the adult gardener, working outside: 1 to 2 

events/week during warmer months or about 40 events/year. An upper percentile value 

of 40 hours/month is recommended based on Tsang and Klepeis (1996). 

Baths and Showers - In the NHAPS study, 649 (~7 percent) of the total participants 

indicated either taking or giving at least one bath in a day. Those 649 respondents were 

subsequently asked the number of times they took or gave a bath in one day. The 

majority, 459 of 649 respondents, recorded taking or giving one bath in a day. These 

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results are presented in Table 15-24. The recommended bathing duration is 20 minutes. 

This is a 50th percentile value based on the NHAPS distribution shown on Table 15-26; 

the reported 90th percentile value is 45 minutes. 

The recommended shower frequency of one shower per day is based on the NHAPS 

data summarized in Table 15-19. This table showed that 3,594 of the 9,386 total 

participants indicated taking at least one shower the previous day. When asked the 

number of actual showers taken the previous day, the reported results ranged from one 

to ten showers; a majority (76 percent), of those 3,549 respondents, reported taking one 

shower the previous day. The NHAPS data shown on Table 15-19, Table 15-24, and 

Table 15-26 provide information grouped according to gender, age, race, employment, 

education, day of the week, seasonal conditions, and health conditions such as asthma, 

angina, and bronchitis/emphysema. 

Recommendations for showering duration are based on the key study conducted by 

Tsang and Klepeis (1996). A recommended value for average showering time is 10 

minutes (Table 15-20) based on professional judgement. This approximates the average 

showering value (8 minutes) of James and Knuiman (1987) (Table 15-18). The 

recommended 50th percentile value is 15 minutes, and the 95th percentile value is 35 

minutes (Table 15-21). Although these values are slightly higher than those of James and 

Knuiman (1987), they are believed to be more representative of U.S. households. 

Swimming - Data for swimming frequency is taken from the NHAPS Study (Tsang 

and Klepeis, 1996). Of 9,386 participants, 653 (about 7 percent), answered yes to the 

question “in the past month, did you swim in a freshwater pool?”. The results to this 

question are summarized in Table 15-65. The recorded number of times respondents 

swam in the past month ranged from 1 to 60 with the greatest number of respondents, 147 

(23 percent), reporting they swam one time per month. Thus, the recommended swimming 

frequency is one event/ month for the general population. The recommended swimming 

duration, 60 minutes per swimming event, is based on the NHAPS distribution shown on 

Table 15-67. Sixty minutes is based on the 50th percentile value; the 90th percentile value 

is 180 minutes per swimming event (based on one event/month); and the 99th percentile 

value is 181 minutes. This value (181) indicates that more than 180 minutes were spent. 

In addition, users can obtain frequency and duration data grouped according to 

gender, age, race, employment, education, day of the week, and season. Frequency and 

duration data is also available in Table 15-65 and Table 15-67, for swimmer respondents 

reporting health conditions such as asthma, angina, and bronchitis/ emphysema. 

Residential Time Spent Indoors and Outdoors - The recommendations for time 

spent indoors at one’s residence is 16.4 hours/day. This is based on the NHAPS data 

summarized in Table 15-131 which records the 50th percentile value of 985.0 minutes per 

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day (16.4 hours/day); and a 90th percentile value of 1,395 minutes per day (23.3 

hours/day). 

The recommended value for time spent outdoors at one’s residence is 2 hours per 

day based on Table 15-102 (generated by the NHAPS data). Values of 105 minutes per 

day for the 50th percentile and 362 minutes per day for the 90th percentile are shown in 

Table 15-102. 

Traveling Inside a Vehicle - The recommendation for time spent in a vehicle is 1 

hour and 20 minutes per day. This recommendation is based on two studies and (1) 

Robinson and Thomas (1991) and (2) The NHAPS data. The Robinson and Thomas study 

evaluated two independent studies, the CARB and the National Study. They respectively 

reported mean durations for time spent in a vehicle as 98 and 87 minutes per day which 

averages to 92 minutes per day or about 1.5 hours per day. The NHAPS data, as 

summarized on Table 15-133, provide a 50th percentile value of 70 minutes per day (or 

1 hour and 10 minutes) and a 90th percentile value of 190 minutes per day. Thus, the 

averaged value from these two studies is about 1 hour and 20 minutes. NHAPS data is 

grouped according to gender, race, age, employment status, census region, day of the 

week, season, and health condition of respondents. 

15.4.2. Recommendations: Occupational Mobility 

The median occupational tenure of the working population (109.1 million people) 

ages 16 years of age and older in January 1987 was 6.6 years (Carey, 1988). Since the 

occupational tenure varies significantly according to age it is recommended to use the age 

dependent values presented in Carey’s 1988 study (Table 15-158). When age cannot be 

determined, it is recommended to use the median tenure value of 6.6 years for working 

men and women 16 years and older. For persons 70 years and older, a tenure value of 

21.9 years is recommended for a working lifetime. A value of 30.5 years and 18.8 years 

is recommended for men and women, respectively. Part-time employment, race and the 

position held are important to consider in determining occupational tenure. The ratings 

indicating confidence in the occupational mobility recommendations are presented in Table 

15-173. It should be noted that the recommended values are not for use in evaluating job 

tenure. These data can be used for determining time spent in an occupation and not for 

time spent at a specific job site. 

15.4.3. Recommendations: Population Mobility 

There are three key studies from which the population mobility recommendations 

were derived: Israeli and Nelson (1992), U.S. Bureau of the Census (1993) - and Johnson 

and Capel (1992). Each study used a unique approach to estimate the length of time a 

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person resides in a household. The respective approaches were to (1) average current 

and total residence time; (2) model current residence time; and (3) determine the 

residential occupancy period. A summary of the approaches used and values 

recommended by each of these studies is presented in Table 15-174. 

The three studies provide residence time estimates that are very similar to the 9 year 

(50th percentile) and 30 year (95th percentile). Tables 15-163 and 15-164 show residence 

times for different types of residences and are recommended where assessors are 

interested in specific types of residences. The ratings indicating confidence in the 

population mobility recommendations is presented in Table 15-175. 

15.4.4. Summary of Recommended Activity Factors 

Table 15-176 includes a summation of the recommended activity pattern factors 

presented in this section and the studies which provided data on the specific activities. 

The type of activities include indoor activities, outdoor activities, time inside a vehicle, 

taking a bath or shower, swimming, working at a specific occupation, and residing in a 

particular location. 

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Chapter 16 - Consumer Products 

16. CONSUMER PRODUCTS 

16.1. BACKGROUND 

Consumer products may contain toxic or potentially toxic chemical constituents to 

which humans may be exposed as a result of their use. For example, methylene chloride 

and other solvents and carriers are common in consumer products and may have human 

health concerns. Potential pathways of exposure to consumer products or chemicals 

released from consumer products during use occur via ingestion, inhalation, and dermal 

contact. Exposure assessments that address consumer products involve characterization 

of these potential exposure pathways and calculating exposure or dose (based on 

exposure pathway) of chemical substances released during use of consumer products. 

In order to estimate specific-pathway exposure for consumer products or their components, 

the following information is needed: amount of product used; concentration of product in 

each type of activity; percent weight of chemical present in product; duration and 

frequency of use or activity; and for dermal exposure, the amount of solution on skin after 

exposure (Hakkinen et al., 1991; U.S. EPA, 1987). 

This chapter presents information on the amount of product used, frequency of use, 

and duration of use for various consumer products typically found in consumer 

households. All tables that present information for these consumer products are located 

at the end of this chapter. U.S. EPA (1987) has complied a comprehensive list of consumer 

products found in typical American households. This list of consumer products is 

presented in Table 16-1. It should be noted that this chapter does not provide an 

exhaustive treatment of all consumer products, but rather provides some background and 

data that can be utilized in an exposure assessment. Also, the data presented may not 

capture information needed to assess the highly exposed population (e.g., consumers who 

use commercial/ industrial strength products at home). The studies presented in the 

following sections represent readily available surveys for which data were collected on the 

frequency and duration of use and amount of use of cleaning products, painting products, 

household solvent products, cosmetic and other personal care products, household 

equipment, pesticides, and tobacco. The studies have been classified as either key or 

relevant based on their applicability to exposure assessment needs. 

The reader is also referred to a document developed by the U.S. EPA, Office of Toxic 

Substances: Standard Scenarios for Estimating Exposure to Chemical Substances During 

Use of Consumer Products - Volumes I and II (U.S. EPA, 1986). This document presents 

data and supporting information required to assess consumer exposure to constituents in 

household cleaners and components of adhesives. Information presented includes a 

description of standard scenarios selected to represent upper bound exposures for each 

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Chapter 16 - Consumer Products 

product. Values are also presented for parameters that are needed to estimate exposure 

for defined exposure routes and pathways assumed for each scenario. 

An additional reference is the Simmons Market Research Bureau (SMRB), "Simmons 

Study of Media and Markets." This document provides an example of marketing data that 

are available that may be useful in assessing exposure to selected products. The reports 

are published annually. Data are collected on the buying habits of the U.S. populations 

over the past 12 months. This information is collected for over 1,000 consumer products. 

Data are presented on frequency of use, total number of buyers in each use category, and 

selected demographics. The consumer product data are presented according to the 

"buyer" and not necessarily according to the "user" (actively exposed person). It may be 

necessary to adjust the data to reflect potential uses in a household. The reports are 

available for purchase from the Simmons Market Research Bureau, (212) 916-8970. 

Appendix Table 16A-1 presents a list of product categories in SMRB for which information 

is available. 

16.2. KEY CONSUMER PRODUCTS USE STUDIES 

Westat (1987a) - Household Solvent Products: A National Usage Survey - Westat 

(1987a) conducted a nationwide survey to determine consumer exposure to common 

household products believed to contain methylene chloride or its substitutes 

(trichloroethane, trichloroethylene, carbon tetrachloride, perchloroethylene, and 

1,1,1,2,2,2- trichlorotrifluoroethane). The survey methodology was comprised of three 

phases. In the first phase, the sample population was generated by using a random digit 

dialing (RDD) procedure. Using this procedure, telephone numbers of households were 

randomly selected by utilizing an unbiased, equal probability of selection method, known 

as the "Waksberg Method" (Westat, 1987a). After the respondents in the selected 

households (18 years and older) agreed to participate in the survey, the second phase was 

initiated. It involved a mailout of questionnaires and product pictures to each respondent. 

In the third phase, a telephone follow-up call was made to those respondents who did not 

respond to the mailed questionnaire within a 4-week period. The same questionnaire was 

administered over the telephone to participants who did not respond to the mailed 

questionnaire. Of the 6,700 individuals contacted for the survey, 4,920 individuals either 

responded to the mailed questionnaire or to a telephone interview (a response rate of 73 

percent). Survey questions included how often the products were used in the last 12 

months; when they were last used; how much time was spent using a product (per 

occasion or year), and the time the respondent remained in the room after use; how much 

of a product was used per occasion or year; and what protective measures were used 

(Westat, 1987a).

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Thirty-two categories of common household products were included in the survey and 

are presented in Table 16-2. Tables 16-2, 16-3, 16-4, and 16-5 provide means, medians, 

and percentile rankings for the following variables: frequency of use, exposure time, 

amount of use, and time exposed after use. 

An advantage of this study is that the random digit dialing procedure (Waksberg 

Method) used in identifying participants for this survey enabled a diverse selection of a 

representative, unbiased, sample of the U.S. population (Westat 1987a). Also, empirical 

data generated from this study will provide more accurate calculations of human exposure 

to consumer household products than estimates previously used. However, a limitation 

associated with this study is that the data generated were based on recall behavior. 

Another limitation is that extrapolation of these data to long-term use patterns may be 

difficult. 

Abt (1992) - Methylene Chloride Consumer Use Study Survey Findings - As part of 

a plan to assess the effectiveness of labeling of consumer products containing methylene 

chloride, Abt conducted a telephone survey of nearly five thousand households (Abt, 

1992). The survey was conducted in April and May of 1991. Three classes of products 

were of concern: paint strippers, non-automotive spray paint, and adhesive removers. 

The survey paralleled a 1986 consumer use survey sponsored jointly by Abt and the U.S. 

EPA. Results of the survey were the following (Abt, 1992):

• Compared to the 1986 findings, a significantly smaller proportion of current survey 

respondents used a paint stripper, spray paint, or adhesive remover. 

• The proportion of the population who used the three products recently (within the 

past year) decreased substantially. 

• Those who used the products reported a significantly longer time since their last 

use. 

• For all three products, the reported amount used per year was significantly higher 

in the current survey. 

The survey was conducted to estimate the percent of the U.S. adult population using 

paint remover, adhesive remover, and non-automotive spray paint. In addition, an 

estimate of the population using these products containing methylene chloride was 

determined. A survey question-naire was developed to collect product usage data and 

demographic data. The survey sample was generated using a RDD technique. 

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A total of 4,997 product screener interviews were conducted for the product interview 

sections; the number of respondents were: 381 for paint strippers, 58 for adhesive 

removers, and 791 for non-automotive spray paint. Survey responses were weighted to 

allow estimation at the level of the total U.S. population (Abt, 1992). A follow-up mail 

survey was also conducted using a short questionnaire. Respondents who had used the 

product in the past year or had purchased the product in the past 2 years and still had the 

container were asked to respond to the questionnaire (Abt, 1992). Of the mail 

questionnaires (527) sent out, 259 were returned. The questionnaire responses included 

67 on paint strippers, 6 on adhesive removers, and 186 on non-automotive spray paint. 

Results of the survey are presented in Tables 16-6 through 16-11 (N's are unweighted). 

Data are presented for recent users. Recent users were defined as persons who have 

used the product within the last year of the survey or who have purchased the product in 

the past 2 years. 

An advantage of this survey is that the survey population was large and the survey 

responses were weighted to represent the U.S. population. In addition, the survey was 

designed to collect data for frequency of product use and amount of product used by 

gender. A limitation of the survey is that the data were generated based on recall 

behavior. Extrapolation of these data to accurately reflect long-term use patterns may be 

difficult. 

Westat (1987b) - National Usage Survey of Household Cleaning Products - Westat 

(1987b) collected usage data from a nationwide survey to assess the magnitude of 

exposure of consumers to various products used when performing certain household 

cleaning tasks. The survey was conducted between the middle of November, 1985 to the 

middle of January, 1986. Telephone interviews were conducted with 193 households. 

According to Westat (1987b), the resulting response rate for this survey was 78 percent. 

The Waksberg method discussed previously in the Westat (1987a) study was also used

in randomly selecting telephone numbers employed in the Westat (1987b) survey. The 

survey was designed to obtain information on cleaning activities performed in the interior 

of the home during the previous year. The person who did the majority of the cleaning in 

the kitchen and bathroom areas of each household was interviewed. Of those 

respondents, the primary cleaner was female in 160 households (83 percent) and male in 

30 households (16 percent); the sex of the respondents in three remaining households was 

not ascertained (Westat, 1987b). Data obtained from the survey included the frequency 

of performing 14 different cleaning tasks; the amount of time (duration) spent at each task; 

the cleaning product most frequently used; the type of product (liquid, powder, aerosol or 

spray pump) used; and the protective measures taken during cleaning such as wearing 

rubber gloves or having a window open or an exhaust fan on (Westat, 1987b). 

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The survey data are presented in Tables 16-12 through 16-16. Table 16-12 presents 

the mean and median total exposure time of use for each cleaning task and the product 

type preferred for each task. The percentile rankings for the total time exposed to the 

products used for 14 cleaning tasks are presented in Table 16-13. The mean and 

percentile rankings of the frequency in performing each task are presented in Table 16-14. 

Table 16-15 shows the mean and percentile rankings for exposure time per event of 

performing household tasks. The mean and percentile rankings for total number of hours 

spent per year using the top 10 product groups are presented in Table 16-16. 

Westat (1987b) randomly selected a subset of 30 respondents from the original 

survey and reinterviewed them during the first two weeks of March, 1986 as a reliability 

check on the recall data obtained from the original phone survey. Frequency and duration 

data for 3 of the original 14 cleaning tasks were obtained from the reinterviews. In a 

second effort to validate the phone survey, 50 respondents of the original phone survey 

participated in a four-week diary study (between February and March, 1986) of 8 of the 14 

cleaning tasks originally studied. The diary approach assessed the validity of using a onetime telephone survey to determine usual cleaning behavior (Westat, 1987b). The data 

(i.e., frequency and duration) obtained from the reinterviews and the diary approach were 

lower than the data from the original telephone survey. The data from the reinterviews and 

the diary approach were more consistent with each other. Westat (1987b) attributed the

significant differences in the data obtained from these surveys to seasonal changes rather 

than methodological problems. 

A limitation of this survey is evident from the reliability and validity check of the data 

conducted by Westat (1987b). The data obtained from the telephone survey may reflect 

heavier seasonal cleaning because the survey was conducted during the holidays 

(November through January). Therefore, usage data obtained in this study may be biased 

and may represent upper bound estimates. Another limitation of this study is the small 

size of the sample population. An advantage of this survey is that the RDD procedure 

(Waksberg Method) used provides unbiased results of sample selection and reduces the 

number of unproductive calls. Another advantage of this study is that it provides empirical 

data on frequency and duration of consumer use, thereby eliminating best judgment or 

guesswork. 

Westat (1987c) - National Household Survey of Interior Painters - Westat (1987c) 

conducted a study between November, 1985 and January, 1986 to obtain usage 

information to estimate the magnitude of exposure of consumers to different types of 

painting and painting related products used while painting the interior of the home. Sevenhundred and seventy-seven households were sampled to determine whether any 

household member had painted the interior of the home during the last 12 months prior to 

the survey date. Of the sampled households, 208 households (27 percent) had a 

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household member who had painted during the last 12 months. Based on the households 

with primary painters, the response rate was 90 percent (Westat, 1987c). The person in 

each household who did most of the interior painting during the last 12 months was 

interviewed over the telephone. The RDD procedure (Waksberg Method) previously 

described in Westat (1987a) was used to generate sample blocks of telephone numbers 

in this survey. Questions were asked on frequency and time spent for interior painting 

activities; the amount of paint used; and protective measures used (i.e., wearing gloves, 

hats, and masks or keeping a window open) (Westat, 1987c). Fifty-three percent of the 

primary painters in the households interviewed were male, 46 percent were female, and 

the sex of the remaining 1 percent was not ascertained. Three types of painting products 

were used in this study; latex paint, oil-based paint, and wood stains and varnishes. Of 

the respondents, 94.7 percent used latex paint, 16.8 percent used oil-based paint, and 

20.2 percent used wood stains and varnishes.

Data generated from this survey are summarized in Tables 16-17, 16-18, and 16-19. 

Table 16-17 presents the mean, standard duration, and percentile rankings for the total 

exposure time for painting activity by paint type. Table 16-18 presents the mean and 

standard exposure time for the painting activity per occasion for each paint type. A 

"painting occasion" is defined as a time period from start to cleanup (Westat 1987c). 

Table 16-18 also presents the frequency and percentile rankings of painting occasions per 

year. Table 16-19 presents the total amount of paint used by interior painters. 

In addition, 30 respondents from the original survey were reinterviewed in April 1986, 

as a reliability check on the recall data obtained from the original painting survey. There 

were no significant differences between the data obtained from the reinterviews and the 

original painting survey (Westat, 1987c). 

An advantage of this survey, based on the reliability check conducted by Westat 

(1987c), is the stability in the painting data obtained. Another advantage of this survey is 

that the response rate was high (90 percent), therefore, minimizing non-response bias. 

Also, the Waksberg Method employed provides an unbiased equal probability method of 

RDD. A limitation of the survey is the data are based on 12-month recall and may not 

accurately reflect long-term use patterns. 

Tsang and Klepeis (1996) - National Human Activity Pattern Survey (NHAPS) - The 

U.S. EPA collected information for the general population on the duration and frequency 

of selected activities and the time spent in selected microenvironments via 24-hour diaries. 

Over 9000 individuals from 48 contiguous states participated in NHAPS. The survey was 

conducted between October 1992 and September 1994. Individuals were interviewed to 

categorize their 24-hour routines (diaries) and/or answer follow-up exposure questions that 

were related to exposure events. Data were collected based on selected socioeconomic 

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(gender, age, race, education, etc.) and geographic (census region, state, etc.) factors and 

time/season (day of week, month) (Tsang and Klepeis, 1996).

Data were collected for a maximum of 82 possible microenvironments and 91 different 

activities (Tsang and Klepeis, 1996). Respondents were also asked exposure-related 

follow up questions, mostly on air and water exposure pathways, on specific pollutant 

sources (paint, glue, etc.), or prolonged background activities (tobacco smoke, gas 

heaters, etc.) (Tsang and Klepeis, 1996).

As part of the survey, data were also collected on duration and frequency of use of 

selected consumer products. These data are presented in Tables 16-20 through 16-34. 

Distribution data are presented for selected percentiles (where possible). Other data are 

presented in ranges of time spent in an activity (e.g., working with or near a product being 

used) or ranges for the number of times an activity involving a consumer product was 

performed. Tables 16-20 through 16-34 provide duration and/or frequency data for the 

following categories: selected cosmetics and personal care items; household cleaners and 

other household products; household equipment; pesticides; and tobacco products. 

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. In addition, frequency 

distributions of time spent and frequency of occurrence data for activities and locations are 

provided, when possible. Also, data on 9,386 different respondents are grouped by 

various socioeconomic, geographic, time/seasonal factors. A disadvantage of NHAPS is 

that means cannot be calculated for consumers who spent more than 60 or 120 minutes 

(depending on the activity) in an activity using a consumer product. Therefore, a good 

estimate of the high consumer activities cannot be captured. 

16.3. RELEVANT CONSUMER PRODUCTS USE STUDY 

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 one-week 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). 

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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 (CTFA, 1983). 

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 

(CTFA, 1983). Table 16-34 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. 

16.4. RECOMMENDATIONS 

Due to the large range and variation among consumer products and their exposure 

pathways, it is not feasible to specify recommended exposure values as has been done 

in other chapters of this handbook. The user is referred to the contents and references 

in the chapter to derive appropriate exposure factors. Table 16-35 summarizes the key 

and relevant studies in this chapter. In order to estimate consumer exposure to household 

products, several types of information are needed for the exposure equation. The 

information needed includes frequency and duration of use, amount of product used, 

percent weight of the chemical of concern found in the product, and for dermal exposure, 

the amount of the solution on the skin after exposure. The studies of Westat (1987a, b, 

and c), (Abt, 1992), and Tsang and Klepeis (1996) provide information on amount, 

duration, and frequency of use of household products. The frequency and duration of use 

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and amount of product used for some household and other consumer products can be 

obtained from Tables 16-2 through 16-34. Exposure to chemicals present in common 

household products can be estimated by utilizing data presented in these tables and the 

appropriate exposure equation. It should be noted that if these data are used to model 

indoor air concentrations, the values for time of use, time exposed after use, and frequency 

in the indoor air, should be the same values used in the dose equation for frequency and 

contact time for a given individual. 

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Chapter 17 - Residential Building Characteristics 

17. RESIDENTIAL BUILDING CHARACTERISTICS 

17.1. INTRODUCTION 

Unlike previous chapters in this handbook which focus on human behavior or 

characteristics that affect exposure, this chapter focuses on residence characteristics. 

Assessment of exposure in residential settings requires information on the availability of 

the chemical(s) of concern at the point of exposure, characteristics of the structure and 

microenvironment that affect exposure, and human presence within the residence. The 

purpose of this chapter is to provide data that are available on residence characteristics 

that affect exposure in an indoor environment. Source-receptor relationships in residential 

exposure scenarios can be complex due to interactions among sources, and 

transport/transformation processes that result from chemical-specific and building-specific 

factors. Figure 17-1 illustrates the complex factors that must be considered when 

conducting exposure assessments in a residential setting. In addition to sources within 

the building, chemicals of concern may enter the indoor environment from outdoor air, soil, 

gas, water supply, tracked-in soil, and industrial work clothes worn by the residents. 

Indoor concentrations are affected by loss mechanisms, also illustrated in Figure 17-1, 

involving chemical reactions, deposition to and re-emission from surfaces, and transport 

out of the building. Particle-bound chemicals can enter indoor air through resuspension. 

Indoor air concentrations of gas-phase organic chemicals are affected by the presence of 

reversible sinks formed by a wide range of indoor materials. In addition, the activity of 

human receptors greatly affects their exposure as they move from room to room, entering 

and leaving the exposure scene. 

Inhalation exposure assessments in residential and other indoor settings are modeled 

by considering the building as an assemblage of one or more well-mixed zones. A zone 

is defined as one room, a group of interconnected rooms, or an entire building. This 

macroscopic level, well-mixed perspective forms the basis for interpretation of 

measurement data as well as simulation of hypothetical scenarios. Exposure assessment 

models on a macroscopic level incorporate important physical factors and processes. 

These well-mixed, macroscopic models have been used to perform indoor air quality 

simulations (Axley, 1989), as well as indoor air exposure assessments (McKone, 1989; 

Ryan, 1991). Nazzaroff and Cass (1986) and Wilkes et al. (1992) have used codeintensive computer programs featuring finite difference or finite element numerical 

techniques to model mass balance. A simplified approach using desk top spreadsheet 

programs has been used by Jennings et al. (1985). 

In order to model mass balance of indoor contaminants, the indoor air volume is 

represented as a network of interconnected zones. Because conditions in a given zone 

are determined by interactions with other connecting zones, the multizone model is stated 

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as a system of simultaneous equations. The mathematical framework for modeling indoor 

air has been reviewed by Sinden (1978) and Sandberg (1984). 

Indoor air quality models typically are not software products that can be purchased 

as "off-the-shelf" items. Most existing software models are research tools that have been 

developed for specific purposes and are being continuously refined by researchers. 

Leading examples of indoor air models implemented as software products are as follows: 

• CONTAM -- developed at the National Institute of Standards and Technology 

(NIST) with support from U.S. EPA and the U.S. Department of Energy (DOE) 

(Axley, 1988; Grot, 1991; Walton, 1993); 

• EXPOSURE -- developed at the Indoor Air Branch of U.S. EPA Air and Energy 

Engineering Research Laboratory (EPA/AEERL) (Sparks, 1988, 1991); 

• MCCEM -- the Multi-Chamber Consumer Exposure Model developed for U.S 

EPA Office of Pollution Prevention and Toxics (EPA/OPPT) (GEOMET, 1989; 

Koontz and Nagda, 1991); and 

• THERdbASE -- the Total Human Exposure Relational Data Base and Advanced 

Simulation Environment software developed by researchers at the Harry Reid 

Center for Environmental Studies at University Nevada, Las Vegas (UNLV) 

(Pandian et al., 1993). 

Section 17.2 of this chapter summarizes existing data on building characteristics 

(volumes, surface areas, mechanical systems, and types of foundations). Section 17.3 

summarizes transport phenomena that affect chemical transport (airflow, chemical-specific 

deposition and filtration, and effects of water supply and soil tracking). Section 17.4 

provides information on various types of indoor sources associated with airborne 

exposure, waterborne sources, and soil/house dust sources. Section 17.5 summarizes 

advanced concepts. 

17.2. BUILDING CHARACTERISTICS 

17.2.1. Key Volumes of Residence Studies 

Versar (1990) - Database on Perfluorocarbon Tracer (PFT) Ventilation Measurements 

- A database of time-averaged air exchange and interzonal airflow measurements in more 

than 4,000 residences has been compiled by Versar (1990) to allow researchers to access 

these data (see Section 17.3.2). These data were collected between 1982 and 1987. The 

residences that appear in this database are not a random sample of U.S. homes; however, 

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they do represent a compilation of homes visited in about 100 different field studies, some 

of which involved random sampling. In each study, the house volumes were directly 

measured or estimated. The collective homes visited in these field projects are not 

geographically balanced; a large fraction of these homes are located in southern 

California. Statistical weighting techniques were applied in developing estimates of 

nationwide distributions (see Section 17.3.2) to compensate for the geographic imbalance. 

U.S. DOE (1995) - Housing Characteristics 1993, Residential Energy Consumption 

Survey (RECS) - Measurement surveys have not been conducted to directly characterize 

the range and distribution of volumes for a random sample of U.S. residences. Related 

data, however, are regularly collected through the U.S. DOE’s RECS (U.S. DOE, 1995).

In addition to collecting information on energy use, this triennial survey collects data on 

housing characteristics including direct measurements of total and heated floor space for 

buildings visited by survey specialists. For the most recent survey (1993), a multistage 

probability sample of over 7,000 residences was surveyed, representing 96 million 

residences nationwide. The survey response rate was 81.2 percent. Volumes were 

estimated from the RECS measurements by multiplying the heated floor space area by an 

assumed ceiling height of 8 feet, recognizing that this assumed height may not apply 

universally to all homes. 

Results for residential volume distributions from the RECS (Thompson, 1995) are 

presented in Table 17-1. Estimated parameters of residential volume distributions (in 

cubic meters) from the PFT database (Versar, 1990) are also summarized in Table 17-1, 

for comparison to the RECS data. The arithmetic means from the two sources are 

identical (369 cubic meters). The medians (50th percentiles) are very similar: 310 cubic 

meters for the RECS data, and 321 cubic meters for the PFT database. Cumulative 

frequency distributions from the two sources (Figure 17-2) also are quite similar, especially 

between the 50th and 75th percentiles. 

The RECS also provides relationships between average residential floor areas and 

factors such as housing type, ownership, household size and structure age. The 

predominant housing type--single-family detached homes--also has the largest average 

volume (Table 17-2). Multifamily units and mobile homes have volumes averaging about 

half that of single-family detached homes, with single-family attached homes about halfway 

between these extremes. Within each category of housing type, owner-occupied 

residences average about 50 percent greater volume than rental units. The relationship 

of residential volume to household size (Table 17-3) is of particular interest for purposes

of exposure assessment. For example, one-person households would not include 

children, and the data in the table indicate that multi-person households occupy 

residences averaging about 50 percent greater volume than residences occupied by oneperson households. 

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Data on year of construction indicate a slight decrease in residential volumes 

between 1950 and 1984, followed by an increasing trend over the next decade. A ceiling 

height of 8 feet was assumed in estimating the average volumes, whereas there may have 

been some time-related trends in ceiling height. 

Murray (1996) - Analysis of RECS and PFT Databases. Using a database from the 

1993 RECS and an assumed ceiling height of 8 feet, Murray (1996) estimated a mean 

3 residential volume of 382 m using RECS estimates of heated floor space. This estimate 

is slightly different from the mean of 369 m3 given in Table 17-1. Murray’s (1996) 

sensitivity analysis indicated that when a fixed ceiling height of 8 feet was replaced with 

a randomly varying height with a mean of 8 feet, there was little effect on the standard 

deviation of the estimated distribution. From a separate analysis of the PFT database, 

based on 1,751 individual household measure-ments, Murray (1996) estimated an average 

3 volume of 369 m , the same as previously given in Table 17-1. In performing this analysis, 

the author carefully reviewed the PFT database in an effort to use each residence only 

once, for those residences thought to have multiple PFT measurements. 

17.2.2. Volumes and Surface Areas of Rooms 

Room Volumes - Volumes of individual rooms are dependent on the building size and 

configuration, but summary data are not readily available. The exposure assessor is 

advised to define specific rooms, or assemblies of rooms, that best fit the scenario of 

interest. Most models for predicting indoor-air concentrations specify airflows in cubic 

meters per hour and, correspondingly, express volumes in cubic meters. A measurement 

in cubic feet can be converted to cubic meters by multiplying the value in cubic feet by 

3 3 0.0283 m /ft . For example, a bedroom that is 9 feet wide by 12 feet long by 8 feet high 

has a volume of 864 cubic feet or 24.5 cubic meters. Similarly, a living room with 

dimensions of 12 feet wide by 20 feet long by 8 feet high has a volume of 1920 cubic feet 

or 54.3 cubic meters, and a bathroom with dimensions of 5 feet by 12 feet by 8 feet has 

a volume of 480 cubic feet or 13.6 cubic meters. 

Murray (1996) analyzed the distribution of selected residential zones (i.e., a series 

of connected rooms) using the PFT database. The author analyzed the "kitchen zone" and 

the "bedroom zone" for houses in the Los Angeles area that were labeled in this manner 

by field researchers, and "basement," "first floor," and "second floor" zones for houses 

outside of Los Angeles for which the researchers labeled individual floors as zones. The 

kitchen zone contained the kitchen in addition to any of the following associated spaces: 

utility room, dining room, living room and family room. The bedroom zone contained all 

the bedrooms plus any bathrooms and hallways associated with the bedrooms. The 

following summary statistics (mean ± standard deviation) were reported by Murray (1996) 

3 for the volumes of the zones described above: 199 ± 115 m for the kitchen zone, 128 ± 

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3 3 3 67 m for the bedroom zone, 205 ± 64 m for the basement, 233 ± 72 m for the first floor, 

3 and 233 ± 111 m for the second floor. 

Surface Areas - The surface areas of floors are commonly considered in relation to 

the room or house volume, and their relative loadings are expressed as a surface area-tovolume, or loading ratio. Table 17-4 provides the basis for calculating loading ratios for 

typical-sized rooms. Constant features in the examples are: a room width of 12 feet and 

a ceiling height of 8 feet (typical for residential buildings), or a ceiling height 12 feet 

(typical for commercial buildings). The loading ratios for the 8-foot ceiling height range 

2 2 -3 2 2 -3 from 0.98 m m-3 to 2.18 m m for wall area and from 0.36 m m-3 to 0.44 m m for floor area. 

In comparison, ASTM Standard E 1333 (ASTM, 1990), for large-chamber testing of 

formaldehyde levels from wood products, specifies the following loading ratios: (1) 0.95 

2 -3 m m for testing plywood (assumes plywood or paneling on all four walls of a typical size 

2 room); and (2) 0.43 m m-3 for testing particleboard (assumes that particleboard decking or 

underlayment would be used as a substrate for the entire floor of a structure). 

Products and Materials - Table 17-5 presents examples of assumed amounts of 

selected products and materials used in constructing or finishing residential surfaces 

(Tucker, 1991). Products used for floor surfaces include adhesive, varnish and wood 

stain; and materials used for walls include paneling, painted gypsum board, and wallpaper. 

Particleboard and chipboard are commonly used for interior furnishings such as shelves 

or cabinets, but could also be used for decking or underlayment. It should be noted that 

numbers presented in Table 17-5 for surface area are based on typical values for 

residences, and they are presented as examples. In contrast to the concept of loading 

ratios presented above (as a surface area), the numbers in Table 17-5 also are not scaled 

to any particular residential volume. In some cases, it may be preferable for the exposure 

assessor to use professional judgment in combination with the loading ratios given above. 

For example, if the exposure scenario involves residential carpeting, either as an indoor 

2 source or as an indoor sink, then the ASTM loading ratio of 0.43 m m-3 for floor materials 

could be multiplied by an assumed residential volume and assumed fractional coverage 

of carpeting to derive an estimate of the surface area. More specifically, a residence with 

3 2 -3 a volume of 300 m , a loading ratio of 0.43 m m and coverage of 80% would have 103 m2 

of carpeting. The estimates discussed here relate to macroscopic surfaces; the true 

surface area for carpeting, for example, would be considerably larger because of the 

nature of its fibrous material. 

Furnishings - Information on the relative abundance of specific types of indoor 

furnishings, such as draperies or upholstered furniture, was not readily available. The 

exposure assessor is advised to rely on common sense and professional judgment. For 

example, the number of beds in a residence is usually related to household size, and 

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information has been provided (Table 17-3) on average house volume in relation to 

household size. 

17.2.3. Mechanical System Configurations 

Mechanical systems for air movement in residences can affect the migration and 

mixing of pollutants released indoors and the rate of pollutant removal. Three types of 

mechanical systems are: (1) systems associated with heating and air conditioning (HAC); 

(2) systems whose primary function is providing localized exhaust; and (3) systems 

intended to increase the overall air exchange rate of the residence. 

Portable space heaters intended to serve a single room, or a series of adjacent 

rooms, may or may not be equipped with blowers that promote air movement and mixing. 

Without a blower, these heaters still have the ability to induce mixing through convective 

heat transfer. If the heater is a source of combustion pollutants, as with unvented gas or 

kerosene space heaters, then the combination of convective heat transfer and thermal 

buoyancy of combustion products will result in fairly rapid dispersal of such pollutants. 

The pollutants will disperse throughout the floor where the heater is located and to floors 

above the heater, but will not disperse to floors below. 

Central forced-air HAC systems are common in many residences. Such systems, 

through a network of supply/return ducts and registers, can achieve fairly complete mixing 

within 20 to 30 minutes (Koontz et al., 1988). The air handler for such systems is 

commonly equipped with a filter (see Figure 17-3) that can remove particle-phase 

contaminants. Further removal of particles, via deposition on various room surfaces (see 

Section 17.3.2), is accomplished through increased air movement when the air handler is 

operating. 

Figure 17-3 also distinguishes forced-air HAC systems by the return layout in relation 

to supply registers. The return layout shown in the upper portion of the figure is the type 

most commonly found in residential settings. On any floor of the residence, it is typical to 

find one or more supply registers to individual rooms, with one or two centralized return 

registers. With this layout, supply/return imbalances can often occur in individual rooms, 

particularly if the interior doors to rooms are closed. In comparison, the supply/return 

layout shown in the lower portion of the figure by design tends to achieve a balance in 

individual rooms or zones. Airflow imbalances can also be caused by inadvertent duct 

leakage to unconditioned spaces such as attics, basements, and crawl spaces. Such 

imbalances usually depressurize the house, thereby increasing the likelihood of 

contaminant entry via soil-gas transport or through spillage of combustion products from 

vented fossil-fuel appliances such as fireplaces and gas/oil furnaces. 

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Mechanical devices such as kitchen fans, bathroom fans, and clothes dryers are 

intended primarily to provide localized removal of unwanted heat, moisture, or odors. 

Operation of these devices tends to increase the air exchange rate between the indoors 

and outdoors. Because local exhaust devices are designed to be near certain indoor 

sources, their effective removal rate for locally generated pollutants is greater than would 

be expected from the dilution effect of increased air exchange. Operation of these devices 

also tends to depressurize the house, because replacement air usually is not provided to 

balance the exhausted air. 

An alternative approach to pollutant removal is one which relies on an increase in air 

exchange to dilute pollutants generated indoors. This approach can be accomplished 

using heat recovery ventilators (HRVs) or energy recovery ventilators (ERVs). Both types 

of ventilators are designed to provide balanced supply and exhaust airflows and are 

intended to recover most of the energy that normally is lost when additional outdoor air is 

introduced. Although ventilators can provide for more rapid dilution of internally generated 

pollutants, they also increase the rate at which outdoor pollutants are brought into the 

house. A distinguishing feature of the two types is that ERVs provide for recovery of latent 

heat (moisture) in addition to sensible heat. Moreover, ERVs typically recover latent heat 

using a moisture-transfer device such as a desiccant wheel. It has been observed in some 

studies that the transfer of moisture between outbound and inbound air streams can result 

in some re-entrainment of indoor pollutants that otherwise would have been exhausted 

from the house (Andersson et al., 1993). Inadvertent air communication between the 

supply and exhaust air streams can have a similar effect. 

Studies quantifying the effect of mechanical devices on air exchange using tracer-gas 

measurements are uncommon and typically provide only anecdotal data. The common 

approach is for the expected increment in the air exchange rate to be estimated from the 

rated airflow capacity of the device(s). For example, if a device with a rated capacity of 

100 cubic feet per minute (cfm), or 170 cubic meters per hour, is operated continuously in 

a house with a volume of 400 cubic meters, then the expected increment in the air 

3 3 exchange rate of the house would be 170 m h-1 / 400 m , or approximately 0.4 air changes 

per hour. 

17.2.4. Type of Foundation 

The type of foundation of a residence is of interest in residential exposure 

assessment. It provides some indication of the number of stories and house configuration, 

and provides an indication of the relative potential for soil-gas transport. For example, 

such transport can occur readily in homes with enclosed crawl spaces. Homes with 

basements provide some resistance, but still have numerous pathways for soil-gas entry. 

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By comparison, homes with crawl spaces open to the outside have significant opportunities 

for dilution of soil gases prior to transport into the house. 

Lucas et al. (1992) - National Residential Radon Survey - The National Resdental 

Radon Survey, sponsored by the U.S. EPA, was conducted by Lucas et al. (1992) in about 

5,700 households nationwide. In addition to radon measurements, information on a 

number of housing characteristics was collected, including whether each house had a 

basement. The estimated percentage (45.2 percent) of homes in the U.S. having 

basements (Table 17-6) from this survey is the same as found by the RECS (Table 17-7).

The National Residential Radon Survey provides data for more refined geographical 

areas, with a breakdown by the 10 EPA Regions. The New England region (i.e., EPA 

Region 1), which includes Connecticut, Maine, Massachusetts, New Hampshire, Rhode 

Island, and Vermont, had the highest prevalence of basements (93 percent). The lowest 

prevalence (4 percent) was for the South Central region (i.e., EPA Region 6), which 

includes Arkansas, Louisiana, New Mexico, Oklahoma, and Texas. Table 17-8 presents 

the States associated with each Census Region and EPA Region. 

U.S. DOE (1995) - Housing Characteristics 1993 - Residential Energy Consumption 

Survey (RECS) - The most recent RECS (described in Section 17.2.1) was administered

in 1993 to over 7,000 households (U.S. DOE, 1995). The type of information requested 

by the survey questionnaire included the type of foundation for the residence (i.e., 

basement, enclosed crawl space, crawl space open to outside or concrete slab). This 

information was not obtained for multifamily structures with five or more dwelling units or 

for mobile homes. Table 17-7 presents estimates from the survey of the percentage of 

residences with each foundation type, by census region, and for the entire U.S. The 

percentages can add to more than 100 percent because some residences have more than 

one type of foundation; for example, most split-level structures have a partial basement 

combined with some crawlspace that typically is enclosed. 

The data in Table 17-7 indicate that close to half (45 percent) of residences 

nationwide have a basement, and that fewer than 10 percent have a crawl space that is 

open to outside. It also shows that a large fraction of homes have concrete slabs (31 

percent). There are also variations by census region. For example, nearly 80 percent of 

the residences in the Northeast and Midwest regions have basements. In the South and 

West regions, the predominant foundation types are concrete slabs and enclosed crawl 

spaces. Table 17-8 illustrates the four Census Regions. 

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17.3. TRANSPORT RATES 

17.3.1. Background 

Major air transport pathways for airborne substances in residences include the 

following: 

• Air exchange - Air leakage through windows, doorways, intakes and exhausts, 

and “adventitious openings” (i.e., cracks and seams) that combine to form the 

leakage configuration of the building envelope plus natural and mechanical 

ventilation; 

• Interzonal airflows - Transport through doorways, ductwork, and service 

chaseways that interconnect rooms or zones within a building; and 

• Local circulation - Convective and advective air circulation and mixing within a 

room or within a zone. 

The distribution of airflows across the building envelope that contribute to air 

exchange and the interzonal airflows along interior flowpaths is determined by the interior 

pressure distribution. The forces causing the airflows are temperature differences, the 

actions of wind, and mechanical ventilation systems. Basic concepts have been reviewed 

by ASHRAE (1993). Indoor-outdoor and room-to-room temperature differences create 

density differences that help determine basic patterns of air motion. During the heating 

season, warmer indoor air tends to rise to exit the building at upper levels by stack action. 

Exiting air is replaced at lower levels by an influx of colder outdoor air. During the cooling 

season, this pattern is reversed: stack forces during the cooling season are generally not 

as strong as in the heating season because the indoor-outdoor temperature differences 

are not pronounced. 

In examining a data base of air leakage measurements, Sherman and Dickerhoff 

(1996) observed that houses built prior to 1980 showed a clear increase in leakage with 

increasing age and were leakier, on average, than newer houses. They further observed 

that the post-1980 houses did not show any trend in leakiness with age. 

The position of the neutral pressure level (i.e., the point where indoor-outdoor 

pressures are equal) depends on the leakage configuration of the building envelope. The 

stack effect arising from indoor-outdoor temperature differences is also influenced by the 

partitioning of the building interior. When there is free communication between floors or 

stories, the building behaves as a single volume affected by a generally rising current 

during the heating season and a generally falling current during the cooling season. When 

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vertical communication is restricted, each level essentially becomes an independent zone. 

As the wind flows past a building, regions of positive and negative pressure (relative to 

indoors) are created within the building; positive pressures induce an influx of air, whereas 

negative pressures induce an outflow. Wind effects and stack effects combine to 

determine a net inflow or outflow. 

The final element of indoor transport involves the actions of mechanical ventilation 

systems that circulate indoor air through the use of fans. Mechanical ventilation systems 

may be connected to heating/cooling systems that, depending on the type of building, 

recirculate thermally treated indoor air or a mixture of fresh air and recirculated air. 

Mechanical systems also may be solely dedicated to exhausting air from a designated 

area, as with some kitchen range hoods and bath exhausts, or to recirculating air in 

designated areas as with a room fan. Local air circulation also is influenced by the 

movement of people and the operation of local heat sources. 

17.3.2. Air Exchange Rates 

Air exchange is the balanced flow into and out of a building, and is composed of three 

processes: (1) infiltration - air leakage through random cracks, interstices, and other 

unintentional openings in the building envelope; (2) natural ventilation - airflows through 

open windows, doors, and other designed openings in the building envelope; and (3) 

forced or mechanical ventilation - controlled air movement driven by fans. For nearly all 

indoor exposure scenarios, air exchange is treated as the principal means of diluting 

indoor concentrations. The air exchange rate is generally expressed in terms of air 

3 -1 changes per hour (ACH, with units of h-1 ), the ratio of the airflow (m h ) to the volume 

(m ). 

No measurement surveys have been conducted to directly evaluate the range and 

distribution of residential air exchange rates. Although a significant number of air 

exchange measurements have been carried out over the years, there has been a diversity 

of protocols and study objectives. Since the early 1980s, however, an inexpensive 

perfluorocarbon tracer (PFT) technique has been used to measure time-averaged air 

exchange and interzonal airflows in thousands of occupied residences using essentially 

similar protocols (Dietz et al., 1986). The PFT technique utilizes miniature permeation 

tubes as tracer emitters and passive samplers to collect the tracers. The passive samplers 

are returned to the laboratory for analysis by gas chromatography. These measurement 

results have been compiled to allow various researchers to access the data (Versar, 

1990). 

Nazaroff et al. (1988) - Prior to the Koontz and Rector (1995) study, Nazaroff et al. 

(1988) aggregated the data from two studies conducted earlier using tracer-gas decay. 

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At the time these studies were conducted, they were the largest U.S. studies to include air 

exchange measurements. The first (Grot and Clark, 1981) was conducted in 255 dwellings 

occupied by low-income families in 14 different cities. The geometric mean ± standard 

deviation for the air exchange measurements in these homes, with a median house age 

of 45 years, was 0.90 ± 2.13 ACH. The second study (Grimsrud et al., 1983) involved 312 

newer residences, with a median age of less than 10 years. Based on measurements 

taken during the heating season, the geometric mean ± standard deviation for these 

homes was 0.53 ± 1.71 ACH. Based on an aggregation of the two distributions with 

proportional weighting by the respective number of houses studied, Nazaroff et al. (1988) 

developed an overall distribution with a geometric mean of 0.68 ACH and a geometric 

standard deviation of 2.01. 

Versar (1990) - Database of PFT Ventilation Measurements - The residences 

included in the PFT database do not constitute a random sample across the United States. 

They represent a compilation of homes visited in the course of about 100 separate fieldresearch projects by various organizations, some of which involved random sampling and 

some of which involved judgmental or fortuitous sampling. The larger projects in the PFT 

database are summarized in Table 17-9, in terms of the number of measurements 

(samples), states where, and months when, samples were taken, and summary statistics 

for their respective distributions of measured air exchange rates. For selected projects 

(LBL, RTI, SOCAL), multiple measurements were taken for the same house, usually during 

different seasons. A large majority of the measurements are from the SOCAL project that 

was conducted in Southern California. The means of the respective studies generally 

range from 0.2 to 1.0 ACH, with the exception of two California projects--RTI2 and 

SOCAL2. Both projects involved measurements in Southern California during a time of 

year (July) when windows would likely be opened by many occupants. 

Koontz and Rector (1995) - Estimation of Distributions for Residential Air Exchange 

Rates - In analyzing the composite data from various projects (2,971 measurements), 

Koontz and Rector (1995) assigned weights to the results from each state to compensate 

for the geographic imbalance in locations where PFT measurements were taken. The 

results were weighted in such a way that the resultant number of cases would represent 

each state in proportion to its share of occupied housing units, as determined from the 

1990 U.S. Census of Population and Housing. 

Summary statistics from the Koontz and Rector (1995) analysis are shown in Table 

17-10, for the country as a whole and by census regions. Based on the statistics for all 

regions combined, the authors suggested that a 10th percentile value of 0.18 ACH would 

be appropriate as a conservative estimator for air exchange in residential settings, and that 

the 50th percentile value of 0.45 ACH would be appropriate as a typical air exchange rate. 

In applying conservative or typical values of air exchange rates, it is important to realize 

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the limitations of the underlying data base. Although the estimates are based on 

thousands of measurements, the residences represented in the database are not a random 

sample of the United States housing stock. The sample population is not balanced in 

terms of geography or time of year. Statistical techniques were applied to compensate for 

some of these imbalances. In addition, PFT measurements of air exchange rates assume 

uniform mixing of the tracer within the building. This is not always so easily achieved. 

Furthermore, the degree of mixing can vary from day to day and house to house because 

of the nature of the factors controlling mixing (e.g., convective air monitoring driven by 

weather, and type and operation of the heating system). The relative placement of the 

PFT source and the sampler can also cause variability and uncertainty. It should be noted 

that sampling is typically done in a single location in a house which may not represent the 

average from that house. In addition, very high and very low values of air exchange rates 

based on PFT measurements have greater uncertainties than those in the middle of the 

distribution. Despite such limitations, the estimates in Table 17-10 are believed to 

represent the best available information on the distribution of air exchange rates across 

United States residences throughout the year. 

Murray and Burmaster (1995) - Residential Air Exchange Rates in the United States: 

Empirical and Estimated Parametric Distributions by Season and Climatic Region - Murray 

and Burmaster (1995) analyzed the PFT database using 2,844 measurements (essentially 

the same cases as analyzed by Koontz and Rector (1995), but without the compensating 

weights). These authors summarized distributions for subsets of the data defined by 

climate region and season. The coldest region was defined as having 7,000 or more 

heating degree days, the colder region as 5,500-6,999 degree days, the warmer region as 

2,500-5,499 degree days, and the warmest region as fewer than 2,500 degree days. The 

months of December, January and February were defined as winter, March, April and May 

were defined as spring, and so on. The results of Murray and Burmaster (1995) are 

summarized in Table 17-11. Neglecting the summer results in the colder regions which 

have only a few observations, the results indicate that the highest air exchange rates occur 

in the warmest climate region during the summer. As noted earlier (Section 17.3.2), many

of the measurements in the warmer climate region were from field studies conducted in 

Southern California during a time of year (July) when windows would tend to be open in 

that area. Data for this region in particular should be used with caution since other areas 

within this region tend to have very hot summers and residences use air conditioners, 

resulting in lower air exchange rates. The lowest rates generally occur in the colder 

regions during the fall (Table 17-11). 

17.3.3. Infiltration Models 

A variety of mathematical models exist for prediction of air infiltration rates in 

individual buildings. A number of these models have been reviewed, for example, by 

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Liddament and Allen (1983), and by Persily and Linteris (1984). Basic principles are 

concisely summarized in the ASHRAE Handbook of Fundamentals (ASHRAE, 1993). 

These models have a similar theoretical basis; all address indoor-outdoor pressure 

differences that are maintained by the actions of wind and stack (temperature difference) 

effects. The models generally incorporate a network of airflows where nodes representing 

regions of different pressure are interconnected by leakage paths. Individual models differ 

in details such as the number of nodes they can treat or the specifics of leakage paths 

(e.g., individual components such as cracks around doors or windows versus a 

combination of components such as an entire section of a building). Such models are not 

easily applied by exposure assessors, however, because the required inputs (e.g., inferred 

leakage areas, crack lengths) for the model are not easy to gather. 

Another approach for estimating air infiltration rates is developing empirical models. 

Such models generally rely on collection of infiltration measurements in a specific building 

under a variety of weather conditions. The relationship between the infiltration rate and 

weather conditions can then be estimated through regression analysis, and is usually 

stated in the following form: 

A ' a%b *Ti & T *% cU n (Eqn. 17-1) o 

where: -1 A = air infiltration rate (h )

Ti = indoor temperature (EC)

To = outdoor temperature (EC) -1 U = windspeed (ms )

n is an exponent with a value typically between 1 and 2

a, b and c are parameters to be estimated

Relatively good predictive accuracy usually can be obtained for individual buildings 

through this approach. However, exposure assessors often do not have the information 

resources required to develop parameter estimates for making such predictions. 

A reasonable compromise between the theoretical and empirical approaches has 

been developed in the model specified by Dietz et al. (1986). The model, drawn from 

correlation analysis of environmental measurements and air infiltration data, is formulated 

as follows: 

A ' L 0.006)T % 0.03 

C 

U 1.5 (Eqn. 17-2) 

where: 

A = average air changes per hour or infiltration rate, h-1

L = generalized house leakiness factor (1 < L < 5)

C = terrain sheltering factor (1 < C < 10)

)T = indoor-outdoor temperature difference (CE) -1 U = windspeed (ms )

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The value of L is greater as house leakiness increases and the value of C is greater 

as terrain sheltering (reflects shielding of nearby wind barrier) increases. Although the 

above model has not been extensively validated, it has intuitive appeal and it is possible 

for the user to develop reasonable estimates for L and C with limited guidance. Historical 

data from various U.S. airports are available for estimation of the temperature and 

windspeed parameters. As an example application, consider a house that has central 

values of 3 and 5 for L and C, respectively. Under conditions where the indoor 

temperature is 20 EC (68 EF), the outdoor temperature is 0 EC (32 E F) and the windspeed 

is 5 ms-1, the predicted infiltration rate for that house would be 3 (0.006 x 20 + 0.03/5 x 

51.5), or 0.56 air changes per hour. This prediction applies under the condition that 

exterior doors and windows are closed, and does not include the contributions, if any, from 

mechanical systems (see Section 17.2.3). Occupant behavior, such as opening windows, 

can, of course, overwhelm the idealized effects of temperature and wind speed. 

17.3.4. Deposition and Filtration 

Deposition refers to the removal of airborne substances to available surfaces that 

occurs as a result of gravitational settling and diffusion, as well as electrophoresis and 

thermophoresis. Filtration is driven by similar processes, but is confined to material 

through which air passes. Filtration is usually a matter of design, whereas deposition is 

a matter of fact. 

17.3.4.1. Deposition 

The deposition of particulate matter and reactive gas-phase pollutants to indoor 

-1 surfaces is often stated in terms of a characteristic deposition velocity (m h ) allied to the

-3 surface-to-volume ratio (m2 m ) of the building or room interior, forming a first order loss 

-1 rate (h ) similar to that of air exchange. Theoretical considerations specific to indoor 

environments have been summarized in comprehensive reviews by Nazaroff and Cass 

(1989) and Nazaroff et al. (1993).

 For airborne particles, deposition rates depend on aerosol properties (size, shape, 

density) as well as room factors (thermal gradients, turbulence, surface geometry). The 

motions of larger particles are dominated by gravitational settling; the motions of smaller 

particles are subject to convection and diffusion. Consequently, larger particles tend to 

accumulate more rapidly on floors and up-facing surfaces while smaller particles may 

accumulate on surfaces facing in any direction. Figure 17-4 illustrates the general trend 

for particle deposition across the size range of general concern for inhalation exposure 

(<10 Fm). The current thought is that theoretical calculations of deposition rates are likely 

to provide unsatisfactory results due to knowledge gaps relating to near-surface air 

motions and other sources of inhomogeneity (Nazaroff et al., 1993). 

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Wallace (1996) - Indoor Particles: A Review - In a major review of indoor particles, 

Wallace (1996) cited overall particle deposition rates for respirable (PM2.5), inhalable 

(PM ), and coarse (difference between PM and PM2.5) size fractions determined from 10 10 

EPA’s PTEAM study. These values, listed in Table 17-12, were derived from 

measurements conducted in nearly 200 residences. 

Thatcher and Layton (1995) - Deposition, Resuspension, and Penetration of Particles 

Within a Residence - Thatcher and Layton (1995) evaluated removal rates for indoor 

particles in four size ranges (1-5, 5-10, 10-25, and >25 Fm) in a study of one house 

occupied by a family of four. These values are listed in Table 17-13. In a subsequent 

evaluation of data collected in 100 Dutch residences, Layton and Thatcher (1995) 

estimated settling velocities of 2.7 m h-1 for lead-bearing particles captured in total 

suspended particulate matter (TSP) samples. 

17.3.4.2. Filtration 

A variety of air cleaning techniques have been applied to residential settings. Basic 

principles related to residential-scale air cleaning technologies have been summarized in 

conjunction with reporting early test results (Offerman et al., 1984). General engineering 

principles are summarized in ASHRAE (1988). In addition to fibrous filters integrated into 

central heating and air conditioning systems, extended surface filters and High Efficiency 

Particle Arrest (HEPA) filters as well as electrostatic systems are available to increase 

removal efficiency. Free-standing air cleaners (portable and/or console) are also being 

used. Product-by-product test results reported by Hanley et al. (1994); Shaughnessy et al. 

(1994); and Offerman et al. (1984) exhibit considerable variability across systems, ranging 

from ineffectual (< 1% efficiency) to nearly complete removal. 

17.3.5. Interzonal Airflows 

Residential structures consist of a number of rooms that may be connected 

horizontally, vertically, or both horizontally and vertically. Before considering residential 

structures as a detailed network of rooms, it is convenient to divide them into one or more 

zones. At a minimum, each floor is typically defined as a separate zone. For indoor air 

exposure assessments, further divisions are sometimes made within a floor, depending on 

(1) locations of specific contaminant sources and (2) the presumed degree of air 

communication among areas with and without sources. 

Defining the airflow balance for a multiple-zone exposure scenario rapidly increases 

the information requirements as rooms or zones are added. As shown in Figure 17-5, a 

single-zone system (considering the entire building as a single well-mixed volume) 

requires only two airflows to define air exchange. Further, because air exchange is 

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balanced flow (air does not "pile up" in the building, nor is a vacuum formed), only one 

number (the air exchange rate) is needed. With two zones, six airflows are needed to 

accommodate interzonal airflows plus air exchange; with three zones, twelve airflows are 

required. In some cases, the complexity can be reduced using judicious (if not convenient) 

assumptions. Interzonal airflows connecting nonadjacent rooms can be set to zero, for 

example, if flow pathways do not exist. Symmetry also can be applied to the system by 

assuming that each flow pair is balanced. 

17.3.6. Water Uses 

Among indoor water uses, showering, bathing and handwashing of dishes or clothes 

provide the primary opportunities for dermal exposure. Virtually all indoor water uses will 

result in some volatilization of chemicals, leading to inhalation exposure. 

The exposure potential for a given situation will depend on the source of water, the 

types and extents of water uses, and the extent of volatilization of specific chemicals. 

According to the results of the 1987 Annual Housing Survey (U.S. Bureau of the Census, 

1992), 84.7 percent of all U.S. housing units receive water from a public system or private 

company (as opposed to a well). Across the four major regions defined by the U.S. 

Census Bureau (Northeast, South, Midwest, and West), the percentage varies from 82.5 

in the Midwest region to 93.2 in the West region (the Northeast and South regions both are 

very close to the national percentage). 

The primary types of water use indoors can be classified as showering/bathing, toilet 

use, clothes washing, dishwashing, and faucet use (e.g., for drinking, cooking, general 

cleaning, or washing hands). Substantial information on water use has been collected in 

California households by the Metropolitan Water District of Southern California (MWD, 

1991) and by the East Bay Municipal Utility District (EBMUD, 1992). An earlier study by 

the U.S. Department of Housing and Urban Development (U.S. DHUD, 1984) monitored 

water use in 200 households over a 20-month period. The household selection process 

for this study was not random; it involved volunteers from water companies and 

engineering organizations, most of which were located in large metropolitan areas. 

Nazaroff et al. (1988) also assembled the results of several smaller surveys, typically 

involving between 5 and 50 households each. 

A common feature of the various studies cited above is that the results were all 

reported in gallons per capita per day (gcd), or in units that could be easily converted to 

gcd. Most studies also provided estimates by type of use--shower/bath, toilet, laundry, 

dishwashing, and other (e.g., faucets). A summary of the various study results is provided 

in Table 17-14. There is generally about a threefold variation across studies for total inhouse water use as well as each type of use. Central values for total use, were obtained 

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by taking the mean and median across the studies for each type of water use and then 

summing these means/medians across uses. These central values are shown at the 

bottom of the table. The means and medians were summed across types of uses to obtain 

the mean for all uses combined because only a subset of the studies reported values for 

other uses. 

The following sections provide a summary of the water use characteristics for the 

primary types of water uses indoors. To the extent found in the literature, each water use 

is described in terms of the frequency of use; flowrate during the use; quantity of water 

used during each occurrence of the water use; and quantity used by an average person. 

Table 17-15 summarizes the studies of U.S. DHUD and the Power Authorities by locations 

and number of households. 

Caution should be exercised when using the data collected in these studies and 

shown here. The participants in these studies are not a representative sample of the 

general population. The participants consisted of volunteers, mostly from large 

metropolitan areas. 

Showering and Bathing Water Use Characteristics - The HUD study (U.S. DHUD, 

1984) monitored 162 households for shower duration. The individuals were also 

subdivided by people who only shower or only bath. The results are given in Table 17-16. 

The flowrates of various types of shower heads were also evaluated in the study 

(Table 17-17).

Toilet Water Use Characteristics - The HUD study (U.S. DHUD, 1984) reported water 

volume per flush for various types of toilets and monitored 162 households for shower 

duration. The results of this study are shown in Table 17-18. Since the HUD study was 

conducted prior to 1984, the newer (post 1984) conserving toilets that are designed to use 

approximately 1.6 gallons per flush were not tested. 

The frequency of use for toilets in households was examined in several studies (U.S. 

DHUD, 1984; Ligman, et al., 1974; Siegrist, 1976). The observed mean frequencies in 

these studies are given in Table 17-19. Tables 17-20 through 17-24 present indoor water 

use frequencies for dishwashers and clothes washers. 

17.3.7. House Dust and Soil 

House dust is a complex mixture of biologically-derived material (animal dander, 

fungal spores, etc.), particulate matter deposited from the indoor aerosol, and soil particles 

brought in by foot traffic. House dust may contain VOCs (see, for example, Wolkoff and 

Wilkins, 1994; Hirvonen et al., 1995), pesticides from imported soil particles as well as 

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Chapter 17 - Residential Building Characteristics 

from direct applications indoors (see, for example, Roberts et al., 1991), and trace metals 

derived from outdoor sources (see, for example, Layton and Thatcher, 1995). The indoor 

abundance of house dust depends on the interplay of deposition from the airborne state, 

resuspension due to various activities, direct accumulation, and infiltration. 

In the absence of indoor sources, indoor concentrations of particulate matter are 

significantly lower than outdoor levels. For some time, this observation supported the idea 

that a significant fraction of the outdoor aerosol is filtered out by the building envelope. 

More recent data, however, have shown that deposition (incompletely addressed in earlier 

studies) accounts for the indoor-outdoor contrast, and outdoor particles smaller than 10 

Fm aerodynamic diameter penetrate the building envelope as completely as nonreactive 

gases (Wallace, 1996). 

Roberts et al. (1991) - Development and Field Testing of a High Volume Sampler for 

Pesticides and Toxics in Dust - Dust loadings, reported by Roberts et al. (1991) were also 

measured in conjunction with the Non-Occupational Pesticide Exposure Study (NOPES). 

In this study house dust was sampled from a representative grid using a specially 

constructed high-volume surface sampler (HVS2). The surface sampler collection 

efficiency was verified in conformance with ASTM F608 (ASTM, 1989). The data 

summarized in Table 17-25 were collected from carpeted areas in volunteer households 

in Florida encountered during the course of NOPES. Seven of the nine sites were singlefamily detached homes, and two were mobile homes. The authors noted that the two 

houses exhibiting the highest dust loadings were only those homes where a vacuum 

cleaner was not used for housekeeping. 

Thatcher and Layton (1995) - Deposition, Resuspension and Penetration of Particles 

Within a Residence - Relatively few studies have been conducted at the level of detail 

needed to clarify the dynamics of indoor aerosols. One intensive study of a California 

residence (Thatcher and Layton, 1995), however, provides instructive results. Using a 

model-based analysis for data collected under controlled circumstances, the investigators 

verified penetration of the outdoor aerosol and estimated rates for particle deposition and 

resuspension (Table 17-26). The investigators stressed that normal household activities

are a significant source of airborne particles larger than 5 Fm. During the study, they 

observed that just walking into and out of a room could momentarily double the 

concentration. The airborne abundance of submicrometer particles, on the other hand, was 

unaffected by either cleaning or walking. 

Mass loading of floor surfaces (Table 17-27) was measured in the study of Thatcher

and Layton (1995) by thoroughly cleaning the house and sampling accumulated dust, after 

one week of normal habitation. Methodology, validated under ASTM F608 (ASTM, 1989), 

showed fine dust recovery efficiencies of 50 percent with new carpet and 72 percent for 

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linoleum. Tracked areas showed consistently higher accumulations than untracked areas, 

confirming the importance of tracked-in material. Differences between tracked areas 

upstairs and downstairs show that tracked-in material is not readily transported upstairs. 

The consistency of untracked carpeted areas throughout the house, suggests that, in the 

absence of tracking, particle transport processes are similar on both floors. 

17.4. SOURCES 

Product- and chemical-specific mechanisms for indoor sources can be described 

using simple emission factors to represent instantaneous releases, as well as constant 

releases over defined time periods; more complex formulations may be required for timevarying sources. Guidance documents for characterizing indoor sources within the context 

of the exposure assessment process are limited (see, for example, Jennings et al., 1987; 

Wolkoff, 1995). Fairly extensive guidance exists in the technical literature, however, 

provided that the exposure assessor has the means to define (or estimate) key 

mechanisms and chemical-specific parameters. Basic concepts are summarized below 

for the broad source categories that relate to airborne contaminants, waterborne 

contaminants, and for soil/house dust indoor sources. 

17.4.1. Source Descriptions for Airborne Contaminants 

Table 17-28 summarizes simplified indoor source descriptions for airborne chemicals 

for direct discharge sources (e.g., combustion, pressurized propellant products), as well 

as emanation sources (e.g., evaporation from “wet” films, diffusion from porous media), 

and transport-related sources (e.g., infiltration of outdoor air contaminants, soil gas entry). 

Direct-discharge sources can be approximated using simple formulas that relate 

pollutant mass released to characteristic process rates. Combustion sources, for example, 

may be stated in terms of an emission factor, fuel content (or heating value), and fuel 

consumption (or carrier delivery) rate. Emission factors for combustion products of general 

concern (e.g., CO, NO ) have been measured for a number of combustion appliances x 

using room-sized chambers (see, for example, Relwani et al., 1986). Other directdischarge sources would include volatiles released from water use and from pressurized 

consumer products. Resuspension of house dust (see Section 17.3.7) would take on a 

similar form by combining an activity-specific rate constant with an applicable dust mass. 

Diffusion-limited sources (e.g., carpet backing, furniture, flooring, dried paint) 

represent probably the greatest challenge in source characterization for indoor air quality. 

Vapor-phase organics dominate this group, offering great complexity because (1) there is 

a fairly long list of chemicals that could be of concern, (2) ubiquitous consumer products, 

building materials, coatings, and furnishings contain varying amounts of different 

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Chapter 17 - Residential Building Characteristics 

chemicals, (3) source dynamics may include nonlinear mechanisms, and (4) for many of 

the chemicals, emitting as well as non-emitting materials evident in realistic settings may 

promote reversible and irreversible sink effects. Very detailed descriptions for diffusionlimited sources can be constructed to link specific properties of the chemical, the source 

material, and the receiving environment to calculate expected behavior (see, for example, 

Schwope et al., 1992; Cussler, 1984). Validation to actual circumstances, however, suffers 

practical shortfalls because many parameters simply cannot be measured directly. 

o s 

The exponential formulation listed in Table 17-28 was derived based on a series of 

papers generated during the development of chamber testing methodology by EPA (Dunn, 

1987; Dunn and Tichenor, 1988; Dunn and Chen, 1993). This framework represents an 

empirical alternative that works best when the results of chamber tests are available. 

Estimates for the initial emission rate (E ) and decay factor (k ) can be developed for 

hypothetical sources from information on pollutant mass available for release (M) and 

supporting assumptions. 

Assuming that a critical time period (t c ) coincides with reduction of the emission rate

to a critical level (E ) or with the release of a critical fraction of the total mass (M ), the c c 

decay factor can be estimated by solving either of these relationships: 

M c Ec 

'e &kst

c or c 

'1&e &kst

(Eqn. 17-3) Eo M

The critical time period can be derived from product-specific considerations (e.g., 

equating drying time for a paint to 90 percent emissions reduction). Given such an 

estimate for k , the initial emission rate can be estimated by integrating the emission s 

formula to infinite time under the assumption that all chemical mass is released: 

s Eo M' 

m

E e &k tdt' 

k o (Eqn. 17-4) 

s o 

The basis for the exponential source algorithm has also been extended to the 

description of more complex diffusion-limited sources. With these sources, diffusive or 

evaporative transport at the interface may be much more rapid than diffusive transport from 

within the source material, so that the abundance at the source/air interface becomes 

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Chapter 17 - Residential Building Characteristics 

depleted, limiting the transfer rate to the air. Such effects can prevail with skin formation 

in "wet" sources like stains and paints (see, for example, Chang and Guo, 1992). Similar 

emission profiles have been observed with the emanation of formaldehyde from 

particleboard with "rapid" decline as formaldehyde evaporates from surface sites of the 

particleboard over the first few weeks. It is then followed by a much slower decline over 

ensuing years as formaldehyde diffuses from within the matrix to reach the surface (see, 

for example, Zinn et al., 1990). 

Transport-based sources bring contaminated air from other areas into the airspace 

of concern. Examples include infiltration of outdoor contaminants, and soil gas entry. Soil 

gas entry is a particularly complex phenomenon, and is frequently treated as a separate 

modeling issue (Little et al., 1992; Sextro, 1994). Room-to-room migration of indoor 

contaminants would also fall under this category, but this concept is best considered using 

the multiple-zone model. 

17.4.2. Source Descriptions for Waterborne Contaminants 

Residential water supplies may convey chemicals to which occupants can be exposed 

through ingestion, dermal contact, or inhalation. These chemicals may appear in the form 

of contaminants (e.g., trichloroethylene) as well as naturally-occurring byproducts of water 

system history (e.g., chloroform, radon). Among indoor water uses, showering, bathing and 

handwashing of dishes or clothes provide the primary opportunities for dermal exposure. 

The escape of volatile chemicals to the gas phase associates water use with inhalation 

exposure. The exposure potential for a given situation will depend on the source of water, 

the types and extents of water uses, and the extent of volatilization of specific chemicals. 

Primary types of residential water use (summarized in Section 17.3) include 

showering/bathing, toilet use, clothes washing, dishwashing, and faucet use (e.g., for 

drinking, cooking, general cleaning, or washing hands). 

Upper-bounding estimates of chemical release rates from water use can be 

formulated as simple emission factors by combining the concentration in the feed water 

3 -1 (g m-3) with the flow rate for the water use (m h ), and assuming that the chemical 

escapes to the gas phase. For some chemicals, however, not all of the chemical escapes 

in realistic situations due to diffusion-limited transport and solubility factors. For inhalation 

exposure estimates, this may not pose a problem because the bounding estimate would 

overestimate emissions by no more than approximately a factor of two. For multiple 

exposure pathways, the chemical mass remaining in the water may be of importance. 

Refined estimates of volatile emissions are usually considered under two-resistance theory 

to accommodate mass transport aspects of the water-air system (see, for example, Little, 

1992; Andelman, 1990; McKone, 1987). 

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Chapter 17 - Residential Building Characteristics 

Release rates are formulated as: 

S ' K m FW C w & 

Ca 

H (Eqn. 17-5) 

where: 

S = chemical release rate (g h ) -1 

Km = dimensionless mass-transfer coefficient 

Fw = water flow rate (m h ) 3 -1 

Cw = concentration in feed water (g m ) -3 

Ca = concentration in air (g m ) -3 

H = dimensionless Henry’s Law constant 

Because the emission rate is dependent on the air concentration, recursive 

techniques are required. The mass transfer coefficient is a function of water use 

characteristics (e.g., water droplet size spectrum, fall distance, water film) and chemical 

properties (diffusion in gas and liquid phases). Estimates of practical value are based on 

empirical tests to incorporate system characteristics into a single parameter (see, for 

example, Giardino et al., 1990). Once characteristics of one chemical-water use system 

are known (reference chemical, subscript r), the mass transfer coefficient for another 

chemical (index chemical, subscript i) delivered by the same system can be estimated 

using formulations identified in the review by Little (1992): 

1 

K 

DLi 

DLr 

1/2 

' 1 

KLr 

' 1 

KGr 

& 1 

H 

DGr 

DGi 

2/3 DLi 

DLr 

1/2 

(Eqn. 17-6) 

where: 

D = L liquid diffusivity (m2 -1 

D = G gas diffusivity (m2 -1 

K = liquid-phase mass transfer coefficient L 

K = G gas-phase mass transfer coefficient

H = dimensionless Henry’s Law constant 

s ) 

s ) 

17.4.3. Soil and House Dust Sources 

The rate process descriptions compiled for soil and house dust in Section 17.3 

-1 provide inputs for estimating indoor emission rates (S , g h ) in terms of dust mass loading d 

-1 2 (M , g m-2) combined with resuspension rates (R , h ) and floor area (A , m ): d d f 

Sd ' Md Rd Af (Eqn. 17-7) 

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Because house dust is a complex mixture, transfer of particle-bound constituents to 

the gas phase may be of concern for some exposure assessments. For emission 

estimates, one would then need to consider particle mass residing in each reservoir (dust 

deposit, airborne). 

17.5. ADVANCED CONCEPTS 

17.5.1. Uniform Mixing Assumption 

Many exposure measurements are predicated on the assumption of uniform mixing 

within a room or zone of a house. Mage and Ott (1994) offers an extensive review of the 

history of use and misuse of the concept. Experimental work by Baughman et al. (1994) 

and Drescher et al. (1995) indicates that, for an instantaneous release from a point source 

in a room, fairly complete mixing is achieved within 10 minutes when convective flow is 

induced by solar radiation. However, up to 100 minutes may be required for complete 

mixing under quiescent (nearly isothermal) conditions. While these experiments were 

conducted at extremely low air exchange rates (< 0.1 ACH), based on the results, attention 

is focused on mixing within a room. 

The situation changes if a human invokes a point source for a longer period and 

remains in the immediate vicinity of that source. Personal exposure in the near vicinity of 

a source can be much higher than the well-mixed assumption would suggest. A series of 

experiments conducted by GEOMET (1989) for the U.S. EPA involved controlled pointsource releases of carbon monoxide tracer (CO), each for 30 minutes. "Breathing-zone" 

measurements located within 0.4 m of the release point were ten times higher than for 

other locations in the room during early stages of mixing and transport. 

Similar investigations conducted by Furtaw et al. (1995) involved a series of 

experiments in a controlled-environment room-sized chamber. Furtaw et al. (1995) studied 

spatial concentration gradients around a continuous point source simulated by sulfur 

hexafluoride (SF ) tracer with a human moving about the room. Average breathing-zone 6 

concentrations when the subject was near the source exceeded those several meters away 

by a factor that varied inversely with the ventilation intensity in the room. At typical room 

ventilation rates, the ratio of source-proximate to slightly-removed concentration was on 

the order of 2:1. 

17.5.2. Reversible Sinks 

For some chemicals, the actions of reversible sinks are of concern. For an initially 

“clean” condition in the sink material, sorption effects can greatly deplete indoor 

concentrations. However, once enough of the chemical has been adsorbed, the diffusion 

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Chapter 17 - Residential Building Characteristics 

gradient will reverse, allowing the chemical to escape. For persistent indoor sources, such 

effects can serve to reduce indoor levels initially but once the system equilibrates, the net 

effect on the average concentration of the reversible sink is negligible. Over suitably short 

time frames, this can also affect integrated exposure. For indoor sources whose emission 

profile declines with time (or ends abruptly), reversible sinks can serve to extend the 

emissions period as the chemical desorbs long after direct emissions are finished. 

Reversible sink effects have been observed for a number of chemicals in the presence of 

carpeting, wall coverings, and other materials commonly found in residential environments. 

Interactive sinks (and models of the processes) are of a special importance; while 

sink effects can greatly reduce indoor air concentrations, re-emission at lower rates over 

longer time periods could greatly extend the exposure period of concern. For completely 

reversible sinks, the extended time could bring the cumulative exposure to levels 

approaching the sink-free case. Recent publications (Axley et al., 1993; Tichenor et al., 

1991) show that first principles provide useful guidance in postulating models and setting 

assumptions for reversible/irreversible sink models. Sorption/desorption can be described 

in terms of Langmuir (monolayer) as well as Brunauer-Emmet-Teller (BET, multilayer) 

adsorption. 

17.6 RECOMMENDATIONS 

Table 17-29 presents a summary of volume of residence surveys and Table 17-30 

presents a summary of air exchange rates surveys. Table 17-31 presents the 

recommended values. Tables 17-32 and 17-33 provide the confidence in 

recommendations for house volume and air exchange rates, respectively. Key studies or 

analyses described in this chapter were used in selecting recommended values for 

residential volume. The air exchange rate data presented in the studies are extremely 

limited. Therefore, studies have not been classified as key or relevant studies. However, 

recommendations have been provided for air exchange rates and the confidence 

recommendation has been assigned a "low" overall rating. Therefore, these values should 

be used with caution. Both central and conservative values are provided. These two 

parameters -- volume and air exchange rate -- can be used by exposure assessors in 

modeling indoor-air concentrations as one of the inputs to exposure estimation. Other 

inputs to the modeling effort include rates of indoor pollutant generation and losses to 

(and, in some cases, re-emissions from) indoor sinks. Other things being equal (i.e., 

holding constant the pollutant generation rate and effect of indoor sinks), lower values for 

either the indoor volume or the air exchange rate will result in higher indoor-air 

concentrations. Thus, values near the lower end of the distribution (e.g., 10th percentile) 

for either parameter are appropriate in developing conservative estimates of exposure. 

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Chapter 17 - Residential Building Characteristics 

For the volume of a residence, both key studies (U.S. DOE (1995) and Versar (1990) 

3 PFT database) have the same mean value -- 369 m (see Table 17-1). This mean value 

is recommended as a central estimate residential volume. Intuitively, the 10th percentile 

3 of the distribution from either study -- 147 m for RECS survey or 167 m3 for the PFT 

database -- is too conservative a value, as both these values are lower than the mean 

volume for multifamily dwelling units (see Table 17-2). Instead, the 25th percentile -- 209 

3 3 m3 for RECS survey or 225 m for PFT database, averaging 217 m across the two key 

studies -- is recommended (Table 17-1).

For the residential air exchange rate, the median value of 0.45 air changes per hour 

(ACH) from the PFT database (see Table 17-9) is recommended as a typical value (Koontz 

and Rector, 1995). This median value is very close to the geometric mean of the 

measurements in the PFT database analyzed by Koontz and Rector (1995). The 

arithmetic mean is not preferred because it is influenced fairly heavily by extreme values 

at the upper tail of the distribution. For a conservative value, the 10th percentile for the 

PFT database -- 0.18 ACH -- is recommended (Table 17-10).

There are some uncertainties in, or limitations on, the distribution for volumes and air 

exchange rates that are presented in this chapter. For example, the RECS used to infer 

volume distributions used a nationwide probability sample, but measured floor area rather 

than total volume. By comparison, field studies contributing to the PFT data base 

measured house volumes directly, but the aggregate sampling frame for these studies is 

not statistically representative of the national housing stock. 

Although the PFT methodology is relatively simple to implement, it is subject to errors 

and uncertainties. The general performance of the sampling and analytical aspects of the 

system are quite good. That is, laboratory analysis will measure the correct time-weightedaverage tracer concentration to within a few percent (Dietz et al., 1986). Nonetheless, 

significant errors can arise when conditions in the measurement scene greatly deviate from 

idealizations calling for constant, well-mixed conditions. Principal concerns focus on the 

effects of naturally varying air exchange and the effects of temperature in the permeation 

source. 

Sherman (1989) carried out an error analysis of the PFT methodology using 

mathematical models combined with typical weather data to calculate how an ideal 

sampling system would perform in a time-varying environment. He found that for simple 

single-story (ranch) and two-story plus basement (colonial) layouts, seasonal 

measurements would underpredict seasonal average air exchange by 20 to 30 percent. 

Underprediction can occur because the PFT methodology is measuring the effective 

ventilation (the product of ventilation efficiency and air exchange), and the temporal 

efficiency will generally be less than unity over averaging periods of this length. Sherman 

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Chapter 17 - Residential Building Characteristics 

(1989) also noted, however, that while the bias could have an impact on determining air 

exchange (absent knowledge of ventilation efficiency) for calculating energy loads, the 

effective air exchange term is directly relevant to determining average indoor 

concentrations resulting from constant sources. 

Leaderer et al. (1985) conducted a series of experiments in a room-sizedenvironmental chamber to evaluate the practical impacts of varying air exchange and the 

temperature response of the permeation sources. The negative bias anticipated in the 

measured (effective) versus actual air exchange as conditions varied diurnally between 

0.4 and 1.5. ACH was evident but minor (3 to 6 percent), most likely due to the mechanical 

mixing in the chamber and the relatively short integration time (72 h). Similarly, cycling 

temperature diurnally over an 8EC range (holding air exchange steady at 0.6 ACH) would 

cause concentrations changes of about 20 percent as emissions fluctuated. The 

investigators found, however, that using a time-weighted average temperature to define 

the emission rate reduced the temperature bias to essentially zero. 

Exposure Factors Handbook August 1997 
Table 1-1. Considerations Used to Rate Confidence in Recommended Values 

CONSIDERATIONS HIGH CONFIDENCE LOW CONFIDENCE 

Study Elements 

Level of peer review The studies received high level of peer The studies received limited peer review. 

review (e.g., they appear in peer review 

journals). 

Accessibility The studies are widely available to the The studies are difficult to obtain (e.g., draft 

public. reports, unpublished data). 

Reproducibility The results can be reproduced or The results cannot be reproduced, the 

methodology can be followed and methodology is hard to follow, and the 

evaluated. author(s) cannot be located. 

Focus on factor of interest The studies focused on the exposure factor The purpose of the studies was to 

of interest. characterize a related factor. 

Data pertinent to U.S. The studies focused on the U.S. The studies focused on populations outside 

population. the U.S. 

Primary data The studies analyzed primary data. The studies are based on secondary 

sources. 

Currency The data were published after 1990. The data were published before 1980. 

Adequacy of data collection period The study design captures the The study design does not very accurately 

measurement of interest (e.g., usual capture the measurement of interest. 

consumption patterns of a population). 

Validity of approach The studies used the best methodology There are serious limitations with the 

available to capture the measurement of approach used. 

interest. 

Study sizes The sample size is greater than 100 samples. The sample size is less than 20 samples. 

The sample size depends on how the target population is defined. As the size of a sample 

relative to the total size of the target population increases, estimates are made with greater 

statistical assurance that the sample results reflect actual characteristics of the target 

population. 

Representativeness of the population The study population is the same as The study population is very different from 

population of interest. the population of interest.a 

Variability in the population The studies characterized variability in the The characterization of variability is limited. 

population studied. 

Lack of bias in study design Potential bias in the studies are stated or The study design introduces biases in the 

(a high rating is desirable) can be determined from the study design. results. 

Response rates

 In-person interviews The response rate is greater than 80 The response rate is less than 40 percent.

 Telephone interviews percent. The response rate is less than 40 percent.

 Mail surveys The response rate is greater than 80 The response rate is less than 40 percent. 

percent. 

The respnose rate is greater than 70 

percent. 

Measurement error The study design minimizes measurement Uncertainties with the data exist due to 

errors. measurement error. 

Other Elements 

Number of studies The number of studies is greater than 3. The number of studies is 1. 

Agreement between researchers The results of studies from different The results of studies from different 

researchers are in agreement. researchers are in disagreement.

a Differences include age, sex, race, income, or other demographic parameters. 
Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings 

EXPOSURE FACTOR RECOMMENDATION CONFIDENCE RATING 

Drinking water intake rate 21 ml/kg-day/1.4 L/day (average) Medium 

34 ml/kg-day/2.3 L/day (90th percentile) Medium 

Percentiles and distribution also included 

Means and percentiles also included for pregnant 

and lactating women 

Total fruit intake rate 3.4 g/kg-day ( per capita average) Medium 

12.4 g/kg-day (per capita 95th percentile) Low 

Percentiles also included 

Means presented for individual fruits 

Total vegetable intake rate 4.3 g/kg-day ( per capita average) Medium 

10 g/kg-day (per capita 95th percentile) Low 

Percentiles also included 

Means presented for individual vegetables 

Total meat intake rate 2.1 g/kg-day ( per capita average) Medium 

5.1 g/kg-day (per capita 95th percentile) Low 

Percentiles also included 

Percentiles also presented for individual meats 

Total dairy intake rate 8.0 g/kg-day (per capita average) Medium 

29.7 g/kg-day (per capita 95th percentile) Low 

Percentiles also included 

Means presented for individual dairy products 

Grain intake 4.1 g/kg-day (per capita average) High 

10.8 g/kg-day (per capita 95th percentile) Low in long-term upper percentiles 

Percentiles also included 

Breast milk intake rate 742 ml/day (average) Medium 

1,033 ml/day (upper percentile) Medium 

Fish intake rate General Population 

20.1 g/day (total fish) average High 

14.1 g/day (marine) average High 

6.0 g/day (freshwater/estuarine)average High 

53 g/day (total fish) 95th percentile long-term Medium 

Percentiles also included 

Serving size High 

129 g (average) High 

326 g (95th percentile) 

Recreational marine anglers Medium 

2 - 7 g/day (finfish only) 

Recreational freshwater Medium 

8 g/day (average) Medium 

25 g/day (95th percentile) 

Native American Subsistence Population Medium 

70 g/day (average) Low 

170 g/day (95th percentile) 
Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings (continued) 

EXPOSURE FACTOR RECOMMENDATION CONFIDENCE RATING 

Home produced food intake Total Fruits Medium (for means and short2.7 g/kg-day (consumer only average) term distributions) 

11.1 g/kg-day (consumer only 95th percentile) Low (for long-term distributions) 

Percentiles also included 

Total vegetables 

2.1 g/kg-day ( consumer only average) 

7.5 g/kg-day (consumer only 95th percentile) 

Percentiles also included 

Total meats 

2.2 g/kg-day (consumer only average) 

6.8 g/kg-day (consumer only 95th percentile) 

Percentiles also included 

Total dairy products 

14 g/kg-day (consumer only average) 

44 g/kg-day (consumer only 95th percentile) 

Percentiles also included 

Inhalation rate Children (<1 year) High 

4.5 m /day (average) 3 

Children (1-12 years) High 

8.7 m /day (average) 3 

Adult Females High 

11.3 m /day (average) 3 

Adult Males High 

15.2 m /day (average) 3 

Surface area Water contact (bathing and swimming) High 

Use total body surface area for children in Tables 6-6 

through 6-8; for adults use Tables 6-2 through 6-4 

(percentiles are included) 

Soil contact (outdoor activities) High 

Use whole body part area based on Table 6-6 through 

6-8 for children and 6-2 through 6-4 for adults 

(percentiles are included) 

Soil adherence Use values presented in Table 6-16 depending on Low 

activity and body part 

(central estimates only) 

Soil ingestion rate Children Medium 

100 mg/day (average) 

400 mg/day (upper percentile) 

Adults Low 

50 mg/day (average) 

Pica child Low 

10 g/day 

Life expectancy 75 years High 

Body weight for adults 71.8 kg High 

Percentiles also presented in tables 7-4 and 7-5 

Body weights for children Use values presented in Tables 7-6 and 7-7 (mean High 

and percentiles) 

Body weights for infants (birth to 6 Use values presented in Table 7-1 (percentiles) High 

months) 
Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings (continued) 

EXPOSURE FACTOR RECOMMENDATION CONFIDENCE RATING 

Showering/Bathing Showering time High 

10 min/day (average) 

35 min/day (95th percentile) 

(percentiles are also included) 

Bathing time High 

20 min/event (median) 

45 min/event (90th percentile) 

Bathing/showering frequency High 

1 shower event/day 

Swimming Frequency High 

1 event/month 

Duration High 

60 min/event (median) 

180 min/event (90th percentile) 

Time indoors Children (ages 3-11) Medium

 19 hr/day (weekdays)

 17 hr/day (weekends) 

Adults (ages 12 and older) Medium

 21 hr/day 

Residential High 

16.4 hrs/day 

Time outdoors Children (ages 3-11) Medium 

5 hr/day (weekdays) 

7 hr/day (weekends) 

Adults Medium 

1.5 hr/day 

Residential High 

2 hrs/day 

Time spent inside vehicle Adults 

1 hr 20 min/day Medium 

Occupational tenure 6.6 years (16 years old and older) High 

Population mobility 9 years (average) Medium 

30 years (95th percentile) Medium 

Residence volume 369 m (average) Medium 3 

217 m (conservative) Medium 3 

Residential air exchange 0.45 (median) Low 

0.18 (conservative) Low 
Table 1-3. Characterization of Variability in Exposure Factors 

Exposure Factors Average Upper percentile Multiple Percentiles Fitted Distributions 

Drinking water intake rate T T T T 

Total fruits and total vegetables intake T T T 

rate Qualitative discussion for 

long-term 

Individual fruits and individual vegetables T 

intake rate 

Total meats and dairy products intake T T T 

rate Qualitative discussion for 

long-term 

Individual meats and dairy products T 

intake rate 

Grains intake T T T 

Breast milk intake rate T T 

Fish intake rate for general population, T T 

recreational marine, recreational 

freshwater, and native american 

Serving size for fish T T T 

Homeproduced food intake rates T T T 

Soil intake rate T Qualitative discussion for 

long-term 

Inhalation rate T T 

Surface area T T T 

Soil adherence T 

Life expectancy T 

Body weight T T T 

Time indoors T 

Time outdoors T 

Showering time T T T 

Occupational tenure T 

Population mobility T T T 

Residence volume T 

Residential air exchange T 
Table 1A-1. Procedures for Modifying IRIS Risk Values for Non-standard Populationsa,b 

IRIS Risk Measure IRIS Risk Measure is Proportional Correction Factor (CF) for modifying c [Units] to:b IRIS Risk Measures: 

S 1/3 = (70)1/3 P Slope Factor (W ) (W /70)1/3 

[per mg/(kg/day)] 

2/3] Water Unit Risk P P IW

S

/[(W ) S 2/3] = 2/[(70) (I )/2 x [70/(W )]2/3 

W 

[per μg/l] 

2/3] P P Air Unit Risk: IA

S

/[(W ) S 2/3] = 20/[(70) (I )/20 x [70/(W )]2/3 

A 

A. Particles or aerosols 3 [per μg/m ], air concentration by

 weight 

Air Unit Risk: No explicit proportionality to body 1.0

 B. Gases weight or air intake is assumed. ppm by volume is assumed to be

 [per parts per million], air the effective dose in both animals

 concentration by volume, and humans.

a W = Body weight (kg)

IW = Drinking water intake (liters per day)

IA = Air intake (cubic meters per day)

b S S W , I S,

W A , I denote standard parameters assumed by IRIS

c Modified risk measure = (CF) x IRIS value 

W P P, I , I P 

W A denote non-standard parameters of the actual population
Biologically 

Effective 

Dose 

Potential Applied Internal 

Dose Dose Dose 

Chemical 

Exposure 

Organ 

Metabolism 

Effect 

Mouth G.I. Tract 

Intake Uptake 

Figure 1-1. Schematic of Dose and Exposure: Oral Route 

Source: U.S. EPA, 1992a 
Figure 1-2. Road Map to Exposure Factor Recommendations


EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Ingestion 

Inhalation 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

SECTION
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Drinking Water 

Intake Rate 

Fruit and Vegetable Intake Rate 

Meat and Dairy Intake Rate 

Homegrown Foods 

Breast milk Intake Rate 

Fish and Shellfish Intake Rate 

Soil Intake Rate 

Ingestion 

Inhalation 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

Grain Intake 

SECTION
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Drinking Water 

Intake Rate 

Adults 

Children 

Pregnant Women 

High Activity 

Fruit and Vegetable Intake Rate 

Meat and Dairy Intake Rate 

Homegrown Foods 

Breast milk Intake Rate 

Fish and Shellfish Intake Rate 

Soil Intake Rate 

I 3 

Ingestion 

Inhalation 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

3 /3-35 

Grain Intake 

SECTION 

.6
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Drinking Water 

Intake Rate 

Fruit and Vegetable Intake Rate 

Meat and Dairy Intake Rate 

Homegrown Foods 

Breast milk Intake Rate 

Fish and Shellfish Intake Rate 

Soil Intake Rate 

Ingestion 

Inhalation 

II 9 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Various Demographic Groups — Age, 

Region, Season, Urbanization, Race 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

9.3/9-30 

Grain Intake 

SECTION
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Drinking Water 

Intake Rate 

Fruit and Vegetable Intake Rate 

Meat and Dairy Intake Rate 

Homegrown Foods 

Breast milk Intake Rate 

Fish and Shellfish Intake Rate 

Soil Intake Rate 

Ingestion 

Inhalation 

II 11 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Various Demographic Groups — Age, 

Region, Season, Urbanization, Race 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

11.4/11-31 

Grain Intake 

SECTION
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Drinking Water 

Intake Rate 

Fruit and Vegetable Intake Rate 

Meat and Dairy Intake Rate 

Homegrown Foods 

Breast milk Intake Rate 

Fish and Shellfish Intake Rate 

Soil Intake Rate 

Ingestion 

Inhalation 

II 13 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Various Demographic Groups — Age, 

Region, Season, Urbanization, Race 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

13.5/13-72 

Grain Intake 

SECTION
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Drinking Water 

Intake Rate 

Fruit and Vegetable Intake Rate 

Meat and Dairy Intake Rate 

Homegrown Foods 

Breast milk Intake Rate 

Fish and Shellfish Intake Rate 

Soil Intake Rate 

Nursing Infants Ingestion 

Inhalation 

II 14 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

14.6/14-14 

Grain Intake 

SECTION
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Drinking Water 

Intake Rate 

Fruit and Vegetable Intake Rate 

Meat and Dairy Intake Rate 

Homegrown Foods 

Breast milk Intake Rate 

Fish and Shellfish Intake Rate 

Soil Intake Rate 

General Population 

Freshwater Recreational 

Marine Recreational 

Subsistence 

Ingestion 

Inhalation 

10 

10 

10 

10 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

10 /10-87 

10 /10-89 

1 /10-88 

10 /10-90 

II 

II 

II 

II 

Grain Intake 

SECTION

.10.1

.10.3

0.10.2

.10.4
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Drinking Water 

Intake Rate 

Fruit and Vegetable Intake Rate 

Meat and Dairy Intake Rate 

Homegrown Foods 

Breast milk Intake Rate 

Fish and Shellfish Intake Rate 

Soil Intake Rate 

Ingestion 

Inhalation 

I 4 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

4.7/4-21 

Grain Intake 

Typical Children 

Adults 

Pica Children 

Region, Season, Urbanization, Race 

SECTION

Various Demographic Groups — Age, 
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Drinking Water 

Intake Rate 

Fruit and Vegetable Intake Rate 

Meat and Dairy Intake Rate 

Homegrown Foods 

Breast milk Intake Rate 

Fish and Shellfish Intake Rate 

Soil Intake Rate 

Ingestion 

Inhalation 

12 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

Grain Intake 12.3/12-24

Typical Children 

Adults 

Pica Children 

Region, Season, Urbanization, Race II 

SECTION

Various Demographic Groups — Age, 
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Inhalation 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Inhalation Rate Adults 

Children 

High Activity 

I 5. 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

5.2.4/5-23 

Ingestion 

SECTION
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Ingestion 

Inhalation 

CHAPTER 

RECOMMENDATIONS/ 

RATINGS TABLE PAGE NOS. 

6. 

6. 

Dermal 

Skin Surface Area Adults 

Children I 

Soil Adherence n I

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

6-8/6-25 

General Population 6-8/6-27
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Ingestion 

Inhalation 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

Body Weight 

Lifetime 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

SECTION
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Ingestion 

Inhalation 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

Body Weight 

Lifetime 

Adults 

Children I 7 (All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

/7-12 

SECTION

7.3
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Ingestion 

Inhalation 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

Body Weight 

Lifetime Adults 

Children I 8 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

/

SECTION

8.2 8-3 
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Ingestion 

Inhalation 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

Activity Patterns 

Occupational Mobility 

Population Mobility 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

III 15 

III 15 

III 15 

Adults 

Children 

Adults 

Children 

Adults 

(All Routes) 

Consumer Product Use 

(All Routes) 

Residential 

Building Characteristics 

/

/

/

SECTION

15.4.1 15-172 

15.4.2 15-173 

15.4.3 15-175 
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Ingestion 

Inhalation 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

Frequency of Use (All Routes) 

Consumer Product Use III 16 

Adults 

Amount Used Adults 

(All Routes) 

Residential 

Building Characteristics 

SECTION

16.4 
Figure 1-2. Road Map to Exposure Factor Recommendations

EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME 

Ingestion 

Inhalation 

CHAPTER 

RECOMMENDATIONS 

/ RATINGS TABLE 

Dermal 

(All Routes) 

Human Characteristics 

(All Routes) 

Activity Factors 

(All Routes) 

Consumer Product Use 

Water Use 

Air Exchange Rates 

House Volumes 

Building Characteristics 

(All Routes) 

Residential 

Building Characteristics General Population III 17 /

SECTION

17.6 17-32, 17-33 
Table 2-1. Four Strategies for Confronting Variability 

Strategy Example Comment 

Ignore variability Assume that all adults Works best when variability is small 

weigh 70 kg 

Disaggregate the Develop distributions of Variability will be smaller in each group 

variability body weight for 

age/gender groups 

Use the average Use average body weight Can the average be estimated reliably given what 

value for adults is known about the variability? 

Use a maximum or Use a lower-end value Conservative approach -- can lead to 

minimum value from the weight distribution unrealistically high exposure estimate if taken for 

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

Type of Uncertainty Sources Examples 

Scenario 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 

Parameter Uncertainty Measurement errors Imprecise or biased measurements 

Sampling errors Small or unrepresentative samples 

Variability In time, space or activities 

Surrogate data Structurally-related chemicals 

Model Uncertainty Relationship errors Incorrect inference on the basis for correlations 

Modeling errors Excluding relevant variables 
Table 2-3. Approaches to Quantitative Analysis of Uncertainty 

Approach 

Sensitivity Analysis 

Analytical Uncertainty Propagation 

Probabilistic Uncertainty Analysis 

Classical Statistical Methods 

Description 

Changing one input variable at a time while 

leaving others constant, to examine effect on 

output 

Examining how uncertainty in individual 

parameters affects the overall uncertainty of 

the exposure assessment 

Varying each of the input variables over 

various values of their respective probability 

distributions 

Estimating the population exposure 

distribution directly, based on measured 

values from a representative sample 

Example 

Fix each input at lower (then upper) bound 

while holding others at nominal values (e.g., 

medians) 

Analytically or numerically obtain a partial 

derivative of the exposure equation with 

respect to each input parameter 

Assign probability density function to each 

parameter; randomly sample values from 

each distribution and insert them in the 

exposure equation (Monte Carlo) 

Compute confidence interval estimates for 

various percentiles of the exposure 

distribution 
Table 3-1. Daily Total Tapwater Intake Distribution for Canadians, by Age Group 

(approx. 0.20 L increments, both sexes, combined seasons) 

Amount Consumeda 

L/day 

5 and u

% 

Age

nder

Number 

Group (years)

6-17 

% Number 

18 and over 

% Number 

0.00 - 0.21 11.1 9 2.8 7 0.5 3 

0.22 - 0.43 17.3 14 10.0 25 1.9 12 

0.44 - 0.65 24.8 20 13.2 33 5.9 38 

0.66 - 0.86 9.9 8 13.6 34 8.5 54 

0.87 - 1.07 11.1 9 14.4 36 13.1 84 

1.08 - 1.29 11.1 9 14.8 37 14.8 94 

1.30 - 1.50 4.9 4 9.6 24 15.3 98 

1.51 - 1.71 6.2 5 6.8 17 12.1 77 

1.72 - 1.93 1.2 1 2.4 6 6.9 44 

1.94 - 2.14 1.2 1 1.2 3 5.6 36 

2.15 - 2.36 1.2 1 4.0 10 3.4 22 

2.37 - 2.57 - 0 0.4 1 3.1 20 

2.58 - 2.79 - 0 2.4 6 2.7 17 

2.80 - 3.00 - 0 2.4 6 1.4 9 

3.01 - 3.21 - 0 0.4 1 1.1 7 

3.22 - 3.43 - 0 - 0 0.9 6 

3.44 - 3.64 - 0 - 0 0.8 5 

3.65 - 3.86 - 0 - 0 - 0 

>3.86 - 0 1.6 4 2.0 13 

TOTAL 100.0 81 100.0 250 100.0 639 

a Includes tapwater and foods and beverages derived from tapwater. 

Source: Canadian Ministry of National Health and Welfare, 1981. 
Table 3-2. Average Daily Tapwater Intake of Canadians 

(expressed as milliliters per kilogram body weight) 

Average Daily Intake (mL/kg) 

Age Group (years) Females Males Both Sexes 

<3 53 35 45 

3-5 49 48 48 

6-17 24 27 26 

18-34 23 19 21 

35-54 25 19 22 

55+ 24 21 22 

Total Population 24 21 22 

Source: Canadian Ministry of National Health and Welfare, 

1981. 
Table 3-3. Average Daily Total Tapwater Intake of Canadians, by Age and Season (L/day)a 

Age (years) 

<3 3-5 6-17 18-34 35-54 <55 All Ages 

Average 

Summer 0.57 0.86 1.14 1.33 1.52 1.53 1.31 

Winter 0.66 0.88 1.13 1.42 1.59 1.62 1.37 

Summer/Winter 0.61 0.87 1.14 1.38 1.55 1.57 1.34 

90th Percentile 

Summer/Winter 1.50 1.50 2.21 2.57 2.57 2.29 2.36 

a Includes tapwater and foods and beverages derived from tapwater. 

Source: Canadian Ministry of National Health and Welfare, 1981. 
Table 3-4. Average Daily Total Tapwater Intake of Canadians as a Function of 

Level of Physical Activity at Work and in Spare Time 

(16 years and older, combined seasons, L/day) 

Work Spare Time 

Activity Consumption Number of Respondents Consumption Number of Respondents 

Level L/day L/day a 

b b 

Extremely Active 1.72 99 1.57 52 

Very Active 1.47 244 1.51 151 

Somewhat Active 1.47 217 1.44 302 

Not Very Active 1.27 67 1.52 131 

Not At All Active 1.30 16 1.35 26 

Did Not State 1.30 45 1.31 26 

TOTAL 688 688 

The levels of physical activity listed here were not defined any further by the survey report, and categorization of activity level by a 

survey participants is assumed to be subjective. 

Includes tapwater and foods and beverages derived from tapwater. b 

Source: Canadian Ministry of National Health and Welfare, 1981. 
Table 3-5. Average Daily Tapwater Intake by Canadians, Apportioned Among Various Beverages 

(both sexes, by age, combined seasons, L/day)a 

Age Group (years) 

Under 3 3-5 6-17 18-34 35-54 55 and Over 

Total Number in Group 34 47 250 232 254 153 

Water 0.14 0.31 0.42 0.39 0.38 0.38 

Ice/Mix 0.01 0.01 0.02 0.04 0.03 0.02 

Tea * 0.01 0.05 0.21 0.31 0.42 

Coffee 0.01 * 0.06 0.37 0.50 0.42 

"Other Type of Drink" 0.21 0.34 0.34 0.20 0.14 0.11 

Reconstituted Milk 0.10 0.08 0.12 0.05 0.04 0.08 

Soup 0.04 0.08 0.07 0.06 0.08 0.11 

Homemade Beer/Wine * * 0.02 0.04 0.07 0.03 

Homemade Popsicles 0.01 0.03 0.03 0.01 * * 

Baby Formula, etc. 0.09 * * * * * 

TOTAL 0.61 0.86 1.14 1.38 1.55 1.57 

Includes tapwater and foods and beverages derived from tapwater. a 

* Less than 0.01 L/day 

Source: Canadian Ministry of National Health and Welfare, 1981. 
Table 3-6. Total Tapwater Intake (mL/day) for Both Sexes Combineda 

Number of 

Age (years) Observations Mean SD 

Percentile Distribution 

S.E. of 

Mean 1 5 10 25 50 75 90 95 99 

<0.5 182 272 247 18 * 0 0 80 240 332 640 800 * 

0.5 - 0.9 221 328 265 

1 - 3 1498 646 390 

4 - 6 1702 742 406 

7 - 10 2405 787 417 

11 - 14 2803 925 521 

15 - 19 2998 999 593 

20 - 44 7171 1255 709 

45 - 64 4560 1546 723 

65 - 74 1663 1500 660 

75+ 878 1381 600 

Infants (ages <1) 403 302 258 

Children (ages 1-10) 5605 736 410 

Teens (ages 11-19) 5801 965 562 

Adults (ages 20-64) 11731 1366 728 

Adults (ages 65+) 2541 1459 643 

All 26081 1193 702 

18 * 0 0 117 268 480 688 764 * 

10 33 169 240 374 567 820 1162 1419 1899 

10 68 204 303 459 660 972 1302 1520 1932 

9 68 241 318 484 731 1016 1338 1556 1998 

10 76 244 360 561 838 1196 1621 1924 2503 

11 55 239 348 587 897 1294 1763 2134 2871 

8 105 337 483 766 1144 1610 2121 2559 3634 

11 335 591 745 1057 1439 1898 2451 2870 3994 

16 301 611 766 1044 1394 1873 2333 2693 3479 

20 279 568 728 961 1302 1706 2170 2476 3087 

13 0 0 0 113 240 424 649 775 1102 

5 56 192 286 442 665 960 1294 1516 1954 

7 67 240 353 574 867 1246 1701 2026 2748 

7 148 416 559 870 1252 1737 2268 2707 3780 

13 299 598 751 1019 1367 1806 2287 2636 3338 

4 80 286 423 690 1081 1561 2092 2477 3415 

a Total tapwater is defined as "all water from the household tap consumed directly as a beverage or used to prepare foods and beverages." 

* Value not reported due to insufficient number of observations. 

Source: Ershow and Cantor, 1989. 
Table 3-7. Total Tapwater Intake (mL/kg-day) for Both Sexes Combineda 

Number of 

Observations 

Age (years) Mean SD Mean 1 5 10 25 50 75 90 

S.E. of Actual Weighted 

Count Count 95 99 

<0.5 182 201.2 52.4 53.2 3.9 * 0.0 0.0 14.8 37.8 66.1 128.3 155.6 * 

0.5 - 0.9 221 243.2 36.2 29.2 2.0 * 0.0 0.0 15.3 32.2 48.1 69.4 102.9 * 

1 - 3 1498 1687.7 46.8 28.1 0.7 2.7 11.8 17.8 27.2 41.4 60.4 82.1 101.6 140.6 

4 - 6 1702 1923.9 37.9 21.8 0.5 3.4 10.3 14.9 21.9 33.3 48.7 69.3 81.1 103.4 

7 - 10 2405 2742.4 26.9 15.3 0.3 2.2 7.4 10.3 16.0 24.0 35.5 47.3 55.2 70.5 

11 - 14 2803 3146.9 20.2 11.6 0.2 1.5 4.9 7.5 11.9 18.1 26.2 35.7 41.9 55.0 

15 - 19 2998 3677.9 16.4 9.6 0.2 1.0 3.9 5.7 9.6 14.8 21.5 29.0 35.0 46.3 

20 - 44 7171 13444.5 18.6 10.7 0.1 1.6 4.9 7.1 11.2 16.8 23.7 32.2 38.4 53.4 

45 - 64 4560 8300.4 22.0 10.8 0.2 4.4 8.0 10.3 14.7 20.2 27.2 35.5 42.1 57.8 

65 - 74 1663 2740.2 21.9 9.9 0.2 4.6 8.7 10.9 15.1 20.2 27.2 35.2 40.6 51.6 

75+ 878 1401.8 21.6 9.5 0.3 3.8 8.8 10.7 15.0 20.5 27.1 33.9 38.6 47.2 

Infants (ages <1) 403 444.3 43.5 42.5 2.1 0.0 0.0 0.0 15.3 35.3 54.7 101.8 126.5 220.5 

Children (ages 1-10) 5605 6354.1 35.5 22.9 0.3 2.7 8.3 12.5 19.6 30.5 46.0 64.4 79.4 113.9 

Teens (ages 11-19) 5801 6824.9 18.2 10.8 0.1 1.2 4.3 6.5 10.6 16.3 23.6 32.3 38.9 52.6 

Adults (ages 20-64) 11731 21744.9 19.9 10.8 0.1 2.2 5.9 8.0 12.4 18.2 25.3 33.7 40.0 54.8 

Adults (ages 65+) 2541 4142.0 21.8 9.8 0.2 4.5 8.7 10.9 15.0 20.3 27.1 34.7 40.0 51.3 

All 26081 39510.2 22.6 15.4 0.1 1.7 5.8 8.2 13.0 19.4 28.0 39.8 50.0 79.8 

Total tapwater is defined as "all water from the household tap consumed directly as a beverage or used to prepare foods and beverages." a 

* Value not reported due to insufficient number of observations. 

Source: Ershow and Cantor, 1989. 
Table 3-8. Summary of Tapwater Intake by Age

Age Group Intake (mL/day) Intake (mL/kg-day)

Mean 10th-90th Percentiles Mean 10th-90th Percentiles

Infants (<1 year) 302 0-649 43.5 0 - 100

Children (1-10 years) 736 286-1,294 35.5 12.5 - 64.4

Teens (11-19 years) 965 353-1,701 18.2 6.5 - 32.3

Adults (20 -64 years) 1,366 559-2,268 19.9 8.0 - 33.7

Adults (65+ years) 1,459 751-2,287 21.8 10.9 - 34.7

All ages 1,193 423-2,092 22.6 8.2 - 39.8

Source: Ershow and Cantor (1989)
Table 3-9. Total Tapwater Intake (as percent of total water intake) by Broad Age Categorya,b 

Age (years) Mean 

Percentile Distribution 

1 5 10 25 50 75 90 95 99 

<1 26 0 0 0 12 22 37 55 62 82 

1-10 45 6 19 24 34 45 57 67 72 81 

11-19 47 6 18 24 35 47 59 69 74 83 

20-64 59 12 27 35 49 61 72 79 83 90 

65+ 65 25 41 47 58 67 74 81 84 90 

Does not include pregnant women, lactating women, or breast-fed children. a 

Total tapwater is defined as "all water from the household tap consumed directly as a beverage or used to prepare foods and b 

beverages." 

0 = Less than 0.5 percent. 

Source: Ershow and Cantor, 1989. 
Table 3-10. General Dietary Sources of Tapwater for Both Sexesa,b 

Age

(years) Source

Mean

% of Tapwater 

Standard

Deviation 5 25 50 75 95 99

c <1 Food 11

Drinking Water 69

Other Beverages 20

All Sources 100

24 0 0 0 10 70 100

37 0 39 87 100 100 100

33 0 0 0 22 100 100

c 1-10 Food 15

Drinking Water 65

Other Beverages 20

All Sources 100

16 0 5 10 19 44 100

25 0 52 70 84 96 100

21 0 0 15 32 63 93

c 11-19 Food 13

Drinking Water 65

Other Beverages 22

All Sources 100

15 0 3 8 17 38 100

25 0 52 70 85 98 100

23 0 0 16 34 68 96

c 20-64 Food 8

Drinking Water 47

Other Beverages 45

All Sources 100

10 0 2 5 11 25 49

26 0 29 48 67 91 100

26 0 25 44 63 91 100

c 65+ Food 8

Drinking Water 50

Other Beverages 42

All Sources 100

9 0 2 5 11 23 38

23 0 36 52 66 87 99

23 3 27 40 57 85 100

c All Food 10

Drinking Water 54

Other Beverages 36

All Sources 100

13 0 2 6 13 31 64

27 0 36 56 75 95 100

27 0 14 34 55 87 100

a Does not include pregnant women, lactating women, or breast-fed children. b Individual values may not add to totals due to rounding. c Food category includes soups. 

0 = Less than 0.5 percent. 

Source: Ershow and Cantor, 1989. 
Table 3-11. Summary Statistics for Best-Fit Lognormal Distributions for Water Intake Ratesa 

ln Total Fluid 

Group Intake Rate 

(age in years) F	 F	 R2 

0 < age <1 6.979 0.291 0.996 

1 # age <11 7.182 0.340 0.953 

11 # age <20 7.490 0.347 0.966 

20 # age <65 7.563 0.400 0.977 

65 # age 7.583 0.360 0.988 

All ages 7.487 0.405 0.984 

Simulated balanced population 7.492 0.407 1.000 

ln Total Tapwater 

Group Intake 

(age in years) F	 F	 R2 

0 < age <1 5.587 0.615 0.970 

1 # age <11 6.429 0.498 0.984 

11 # age <20 6.667 0.535 0.986 

20 # age <65 7.023 0.489 0.956 

65 # age 7.088 0.476 0.978 

All ages 6.870 0.530 0.978 

Simulated balanced population 6.864 0.575 0.995 

a These values (mL/day) were used in the following equations to estimate the quantiles and averages for 

total tapwater intake shown in Tables 3-12. . 97.5 percentile intake rate = exp [F + (1.96 F)] . 75 percentile intake rate = exp [F + (0.6745 F)] 

50 percentile intake rate = exp [F] . 25 percentile intake rate = exp [F - (0.6745 F)] . 2.5 percentile intake rate = exp [F - (1.96 F)] . Mean intake rate - exp [F + 0.5 F2

)] 

Source: Roseberry and Burmaster, 1992. 
Table 3-12. Estimated Quantiles and Means for Total Tapwater Intake Rates (mL/day)a 

Age Group Percentile Arithmetic 

(years) Average 2.5 25 50 75 97.5 

0 <age < 1 80 176 267 404 891 323 

1 # age < 11 233 443 620 867 1,644 701 

11 # age < 20 275 548 786 1,128 2,243 907 

20 # age < 65 430 807 1,122 1,561 2,926 1,265 

65 # age 471 869 1,198 1,651 3,044 1,341 

All ages 341 674 963 1,377 2,721 1,108 

Simulated Balanced Population 310 649 957 1,411 2,954 1,129 

Total tapwater is defined as "all water from the household tap consumed directly as a beverage or used to prepare foods and a 

beverages." 

Source: Roseberry and Burmaster, 1992 
Table 3-13. Assumed Tapwater Content of Beverages 

Beverage % 

Tapwater 

Cold Water 100 

Home-made Beer/Cider/Lager 100 

Home-made Wine 100 

Other Hot Water Drinks 100 

Ground/Instant Coffee:a

 Black 100

 White 80

 Half Milk 50

 All Milk 0 

Tea 80 

Hot Milk 0 

Cocoa/Other Hot Milk Drinks 0 

Water-based Fruit Drink 75 

Fizzy Drinks 0 

Fruit Juice 1 0 b 

Fruit Juice 2 75 b 

Milk 0 

Mineral Water 0 c 

Bought cider/beer/lager 0 

Bought Wine 0 

a Black - coffee with all water, milk not added; White - coffee with 80%

water, 20% milk; 

Half Milk - coffee with 50% water, 50% milk; All Milk - coffee with all 

milk, water not added; 

Fruit juice: individuals were asked in the questionnaire if they b 

consumed ready-made fruit juice (type 1 above), or the variety that is 

diluted (type 2); 

Information on volume of mineral water consumed was obtained only c 

as "number of bottles per week." A bottle was estimated at 500 mL, 

and the volume was split so that 2/7 was assumed to be consumed on 

weekends, and 5/7 during the week. 

Source: Hopkins and Ellis, 1980. 
Table 3-14. Intake of Total Liquid, Total Tapwater, and Various Beverages (L/day) 

All Individuals Consumers Onlya

Beverage Approx. 95% Approx. 95% 

Confidence Percentage of Mean Approx. Confidence 

Mean Approx. Std. Interval for 10 and 90 1 and 99 Total Number Intake Std. Error Interval for Mean 

Intake Error of Mean Mean Percentiles Percentiles of Individuals of Mean 

Total Liquid 1.589 0.0203 1.547-1.629 0.77-2.57 0.34-4.50 100.0 1.589 0.0203 1.547-1.629 

Total Liquid Home 1.104 0.0143 1.075-1.133 0.49-1.79 0.23-3.10 100.0 1.104 0.0143 1.075-1.133 

Total Liquid Away 0.484 0.0152 0.454-0.514 0.00-1.15 0.00-2.89 89.9 0.539 0.0163 0.506-0.572 

Total Tapwater 0.955 0.0129 0.929-0.981 0.39-1.57 0.10-2.60 99.8 0.958 0.0129 0.932-0.984 

Total Tapwater Home 0.754 0.0116 0.731-0.777 0.26-1.31 0.02-2.30 99.4 0.759 0.0116 0.736-0.782 

Total Tapwater Away 0.201 0.0056 0.190-0.212 0.00-0.49 0.00-0.96 79.6 0.253 0.0063 0.240-0.266 

Tea 0.584 0.0122 0.560-0.608 0.01-1.19 0.00-2.03 90.9 0.643 0.0125 0.618-0.668 

Coffee 0.190 0.0059 0.178-0.202 0.00-0.56 0.00-1.27 63.0 0.302 0.0105 0.281-0.323 

Other Hot Water 0.011 0.0015 0.008-0.014 0.00-0.00 0.00-0.25 9.2 0.120 0.0133 0.093-0.147 

Drinks 

Cold Water 0.103 0.0049 0.093-0.113 0.00-0.31 0.00-0.85 51.0 0.203 0.0083 0.186-0.220 

Fruit Drinks 0.057 0.0027 0.052-0.062 0.00-0.19 0.00-0.49 46.2 0.123 0.0049 0.113-0.133 

Non Tapwater 0.427 0.0058 0.415-0.439 0.20-0.70 0.06-1.27 99.8 0.428 0.0058 0.416-0.440 

Home-brew 0.010 0.0017 0.007-0.013 0.00-0.00 0.00-0.20 7.0 0.138 0.0209 0.096-0.180 

Bought Alcoholic 0.206 0.0123 0.181-0.231 0.00-0.68 0.00-2.33 43.5 0.474 0.0250 0.424-0.524 

Beverages

a Consumers only is defined as only those individuals who reported consuming the beverage during the survey period. 

Source: Hopkin and Ellis, 1980. 
Table 3-15. Summary of Total Liquid and Total Tapwater Intake for Males and Females (L/day) 

Number Mean Intake 

Beverage Age

Group

(years) Male Female Male Female

Approx. Std. Error of Approx 95% Confidence 10 and 90 Percentiles 

Mean Interval for Mean 

Male Female Male Female Male Female 

1-4 88 75 0.853 0.888

5-11 249 201 0.986 0.902

12-17 180 169 1.401 1.198

0.0557 0.0660 0.742-0.964 0.756-1.020 0.38-1.51 0.39-1.48 

0.0296 0.0306 0.917-1.045 0.841-0.963 0.54-1.48 0.51-1.39 

0.0619 0.0429 1.277-1.525 1.112-1.284 0.75-2.27 0.65-1.74 Total Liquid 

Intake 18-30 333 350 2.184 

31-54 512 551 2.112 

55+ 396 454 1.830 

1.547 0.0691 0.0392 2.046-2.322 1.469-1.625 1.12-3.49 0.93-2.30 

1.601 0.0526 0.0215 2.007-2.217 1.558-1.694 1.15-3.27 0.95-2.36 

1.482 0.0498 0.0356 1.730-1.930 1.411-1.553 1.03-2.77 0.84-2.17 

1-4 88 75 0.477 0.464 0.0403 0.0453 0.396-0.558 0.373-0.555 0.17-0.85 0.15-0.89 

5-11 249 201 0.550 0.533 0.0223 0.0239 0.505-0.595 0.485-0.581 0.22-0.90 0.22-0.93 

Total 12-17 180 169 0.805 0.725 0.0372 0.0328 0.731-0.8790 0.659-0.791 0.29-1.35 0.31-1.16 Tapwater 

Intake 18-30 333 350 1.006 

31-54 512 551 1.201 

55+ 396 454 1.133 

0.991 0.0363 0.0304 0.933-1.079 0.930-1.052 0.45-1.62 0.50-1.55 

1.091 0.0309 0.0240 1.139-1.263 1.043-1.139 0.64-1.88 0.62-1.68 

1.027 0.0347 0.0273 1.064-1.202 0.972-1.082 0.62-1.72 0.54-1.57 

Source: Hopkin and Ellis, 1980. 
Table 3-16. Measured Fluid Intakes (mL/day) 

Subject Total Fluids Milk Tapwater Drinks 

Water-Based a 

Adults ("normal" conditions) 1000-2400 120-450 b 45-730 320-1450 

Adults (high environmental 2840-3410

 temperature to 32EC) 3256 ± 

SD = 900 

Adults (moderately active) 3700 

Children (5-14 yr) 1000-1200 330-500 ca. 200 ca. 380 

1310-1670 540-650 540-790

 Includes tea, coffee, soft drinks, beer, cider, wine, etc. a

 "Normal" conditions refer to typical environmental temperature and activity levels. b 

Source: ICRP, 1981. 
Table 3-17. Intake Rates of Total Fluids and Total Tapwater by Age Group

Average Daily Consumption Rate (L/day)

Age Group Total Fluids Total Tapwater a b

6-11 months 0.80 0.20

2 years 0.99 0.50

14-16 years 1.47 0.72

25-30 years 1.76 1.04

60-65 years 1.63 1.26

Includes milk, "ready-to-use" formula, milk-based soup, carbonated soda, alcoholic a

beverages, canned juices, water, coffee, tea, reconstituted juices, and reconstituted soups. 

Does not include reconstituted infant formula.

Includes water, coffee, tea, reconstituted juices, and reconstituted soups. b

Source: Derived from Pennington, 1983.
Table 3-18. Mean and Standard Error for the Daily Intake of Beverages and Tapwater by Age 

Age (years) Tapwater Intake Water-Based Drinks Soups Total Beverage Intake 

(mL) (mL) (mL) (mL) a 

b 

All ages 662.5 ± 9.9 457.1 ± 6.7 45.9 ± 1.2 1434.0 ± 13.7 

Under 1 170.7 ± 64.5 8.3 ± 43.7 10.1 ± 7.9 307.0 ± 89.2

 1 to 4 434.6 ± 31.4 97.9 ± 21.5 43.8 ± 3.9 743.0 ± 43.5

 5 to 9 521.0 ± 26.4 116.5 ± 18.0 36.6 ± 3.2 861.0 ± 36.5 

10 to 14 620.2 ± 24.7 140.0 ± 16.9 35.4 ± 3.0 1025.0 ± 34.2 

15 to 19 664.7 ± 26.0 201.5 ± 17.7 34.8 ± 3.2 1241.0 ± 35.9 

20 to 24 656.4 ± 33.9 343.1 ± 23.1 38.9 ± 4.2 1484.0 ± 46.9 

25 to 29 619.8 ± 34.6 441.6 ± 23.6 41.3 ± 4.2 1531.0 ± 48.0 

30 to 39 636.5 ± 27.2 601.0 ± 18.6 40.6 ± 3.3 1642.0 ± 37.7 

40 to 59 735.3 ± 21.1 686.5 ± 14.4 51.6 ± 2.6 1732.0 ± 29.3 

60 and over 762.5 ± 23.7 561.1 ± 16.2 59.4 ± 2.9 1547.0 ± 32.8 

Includes water-based drinks such as coffee, etc. Reconstituted infant formula does not appear to be included in this group. a 

Includes tapwater and water-based drinks such as coffee, tea, soups, and other drinks such as soft drinks, fruitades, and b 

alcoholic drinks. 

Source: U.S. EPA, 1984. 
Table 3-19. Average Total Tapwater Intake Rate by Sex

Age, and Geographic Area

Group/Subgroup Respondents L/day

Number of Tapwater Intake,

Average Total a,b

Total group 5,258 1.39

Sex

Males 3,892 1.40

Females 1,366 1.35

Age, years

21-44 291 1.30

45-64 1,991 1.48

65-84 2,976 1.33

Geographic area

Atlanta 207 1.39

Connecticut 844 1.37

Detroit 429 1.33

Iowa 743 1.61

New Jersey 1,542 1.27

New Mexico 165 1.49

New Orleans 112 1.61

San Francisco 621 1.36

Seattle 316 1.44

Utah 279 1.35

Standard deviations not reported in Cantor et al. (1987). a

Total tapwater defined as all water and beverages derived from tapwater. b

Source: Cantor et al., 1987.
Table 3-20. Frequency Distribution of Total

 Tapwater Intake Ratesa 

Consumption Cumulative Frequency 

Rate (L/day) Frequency (%) (%) b 

b 

# 0.80 20.6 20.6 

0.81-1.12 21.3 41.9 

1.13-1.44 20.5 62.4 

1.45-1.95 19.5 81.9 

$1.96 18.1 100.0 

a Represents consumption of tapwater and beverages derived from

tapwater in a "typical" winter week. 

Extracted from Table 3 in Cantor et al. (1987). b 

Source: Cantor, et al., 1987. 
Table 3-21 Mean Per Capita Drinking Water Intake Based on USDA, CSFII Data From 1989-91 (mL/day) 

Sex and Age Plain Drinking Fruit Drinks 

(years) Water Coffee Tea and Ades Total a 

Males and Females:

 Under 1 194 0 <0.5 17 211.5

 1-2 333 <0.5 9 85 427.5

 3-5 409 2 26 100 537

 5 & Under 359 1 17 86 463 

Males: 

6-11 537 2 44 114 697 

12-19 725 12 95 104 936 

20-29 842 168 136 101 1,247 

30-39 793 407 136 50 1,386 

40-49 745 534 149 53 1,481 

50-59 755 551 168 51 1,525 

60-69 946 506 115 34 1,601 

70-79 824 430 115 45 1,414 

80 and over 747 326 165 57 1,295 

20 and over 809 408 139 60 1,416 

Females: 

6-11 476 1 40 86 603 

12-19 604 21 87 87 799 

20-29 739 154 120 61 1,074 

30-39 732 317 136 59 1,244 

40-49 781 412 174 36 1,403 

50-59 819 438 137 37 1,431 

60-69 829 429 124 36 1,418 

70-79 772 324 161 34 1,291 

80 and over 856 275 149 28 1,308 

20 and over 774 327 141 46 1,288 

All individuals 711 260 114 65 1,150 

Includes regular and low calorie fruit drinks, punches, and ades, including those made from powdered mix and frozen concentrate. a 

Excludes fruit juices and carbonated drinks. 

Source: USDA, 1995. 
Table 3-22. Number of Respondents that Consumed Tapwater at a Specified Daily Frequency 

Number of Glasses in a Day 

Population Group Total N None 1-2 3-5 6-9 10-19 20+ DK 

Overall 4,663 1,334 1,225 1,253 500 151 31 138 

Gender 

Male 2,163 604 

Female 2,498 728 

Refused 2 2 

582 569 216 87 25 65 

643 684 284 64 6 73 

• • • • • • Age (years) 

1-4 263 114

5-11 348 90

12-17 326 86

18-64 2,972 908

> 64 670 117

96 40 7 1 0 5 

127 86 15 7 2 20 

109 88 22 7 • 11 

751 769 334 115 26 54 

127 243 112 20 2 42 

Race 

White 3,774 1,048

Black 463 147

Asian 77 25

Some Others 96 36

Hispanic 193 63

Refused 60 15

1,024 1,026 416 123 25 92 

113 129 38 9 1 21 

18 23 6 1 • 4 

18 22 6 7 2 5 

42 40 28 10 2 7 

10 13 6 1 1 9 

Hispanic 

No 4,244 1,202

Yes 347 116

DK 26 5

Refused 46 11

1,134 1,162 451 129 26 116 

80 73 41 18 4 13 

6 7 4 3 • 1 

5 11 4 1 1 8 

Employment 

Full-time 2,017 637

Part-time 379 90

Not Employed 1,309 313

Refused 32 6

525 497 218 72 18 40 

94 120 50 13 7 5 

275 413 188 49 3 54 

4 11 1 2 1 4 

Education 

< High School 399 89

High School Graduate 1,253 364

< College 895 258

College Graduate 650 195

Post Graduate 445 127

95 118 51 14 2 28 

315 330 132 52 13 37 

197 275 118 31 5 9 

157 181 82 19 4 6 

109 113 62 16 3 12 

Census Region 

Northeast 1,048 351

Midwest 1,036 243

South 1,601 450

West 978 290

262 266 95 32 7 28 

285 308 127 26 9 33 

437 408 165 62 11 57 

241 271 113 31 4 20 

Day of Week 

Weekday 3,156 864 840 862 334 96 27 106 

Weekend 1,507 470 385 391 166 55 4 32 

Season 

Winter 1,264 398

Spring 1,181 337

Summer 1,275 352

Fall 943 247

321 336 128 45 5 26 

282 339 127 33 10 40 

323 344 155 41 9 40 

299 234 90 32 7 32 

Asthma 

No 4,287 1,232 

Yes 341 96 

DK 35 6 

1,137 1,155 459 134 29 115 

83 91 40 16 1 13 

5 7 1 1 1 10 

Angina 

No 4,500 1,308 

Yes 125 18 

DK 38 8 

1,195 1,206 470 143 29 123 

25 40 27 6 1 6 

5 7 3 2 1 9 

Bronchitis/Emphysema 

No 4,424 1,280 1,161 1,189 474 142 29 124 

Yes 203 48 55 58 24 9 1 5 

DK 36 6 9 6 2 • 1 9 

NOTE: "•" = Missing Data

 "DK" = Don't know

 N = sample size

 Refused = respondent refused to answer 

Source: Tsang and Kleipeis, 1996 
Table 3-23. Number of Respondents that Consumed Juice Reconstituted with Tapwater at a Specified Daily Frequency 

Number of Glasses in a Day 

Population Group Total N None 1-2 3-5 6-9 10-19 20+ DK 

Overall 4,663 1,877 1,418 933 241 73 21 66 

Gender 

Male 2,163 897 

Female 2,498 980 

Refused 2 • 

590 451 124 35 17 33 

826 482 117 38 4 33 

2 • • • • • Age (years) 

1-4 263 126

5-11 348 123

12-17 326 112

18-64 2,972 1,277

> 64 670 206

71 48 11 4 1 2 

140 58 12 2 1 11 

118 63 18 7 1 4 

817 614 155 46 16 30 

252 133 43 12 2 14 

Race 

White 3,774 1,479

Black 463 200

Asian 77 33

Some Others 96 46

Hispanic 193 95

Refused 60 24

1,168 774 216 57 16 44 

142 83 15 9 1 7 

27 15 1 • • 0 

19 24 2 1 3 1 

51 30 5 5 1 5 

11 7 2 1 • 9 

Hispanic 

No 4,244 1,681

Yes 347 165

DK 26 11

Refused 46 20

1,318 863 226 64 17 49 

87 61 14 7 4 7 

6 5 • 1 • 3 

7 4 1 1 • 7 

Employment 

Full-time 2,017 871

Part-time 379 156

Not Employed 1,309 479

Refused 32 15

559 412 103 32 9 20 

102 88 19 7 2 5 

426 265 75 20 7 21 

4 4 2 1 • 3 

Education 

< High School 399 146

High School Graduate 1,253 520

< College 895 367

College Graduate 650 274

Post Graduate 445 182

131 82 25 7 2 4 

355 254 68 21 7 17 

253 192 47 18 5 11 

201 125 31 7 1 5 

130 92 26 5 3 4 

Census Region 

Northeast 1,048 440

Midwest 1,036 396

South 1,601 593

West 978 448

297 220 51 13 4 15 

337 200 63 17 4 14 

516 332 84 26 10 28 

268 181 43 17 3 9 

Day of Week 

Weekday 3,156 1,261 969 616 162 51 11 46 

Weekend 1,507 616 449 307 79 22 10 20 

Season 

Winter 1,264 529

Spring 1,181 473

Summer 1,275 490

Fall 943 385

382 245 66 23 4 10 

382 215 54 19 8 17 

389 263 68 18 6 28 

265 210 53 13 3 11 

Asthma 

No 4,287 1,734 

Yes 341 130 

DK 35 13 

1,313 853 216 69 20 55 

102 74 25 3 1 5 

3 6 • 1 • 6 

Angina 

No 4,500 1,834 

Yes 125 31 

DK 38 12 

1,362 900 231 67 20 59 

53 25 7 5 1 1 

3 8 3 1 • 6 

Bronchitis/Emphysema 

No 4,424 1,782 

Yes 203 84 

DK 36 11 

1,361 882 230 65 21 57 

53 44 10 6 • 3 

4 7 1 2 • 6 

NOTE: "•" = Missing Data

 "DK" = Don't know

 N = sample size

 Refused = Respondent refused to answer 

Source: Tsang and Klepeis, 1996 
Table 3-24. Total Fluid Intake of Women 15-49 Years Old 

Percentile Distribution 

Reproductive Standard 

Status Mean Deviation a 5 10 25 50 75 90 95 

mL/day

 Control 1940 686 995 1172 1467 1835 2305 2831 3186

 Pregnant 2076 743 1085 1236 1553 1928 2444 3028 3475

 Lactating 2242 658 1185 1434 1833 2164 2658 3169 3353 

mL/kg/day

 Control 32.3 12.3 15.8 18.5 23.8 30.5 38.7 48.4 55.4

 Pregnant 32.1 11.8 16.4 17.8 17.8 30.5 40.4 48.9 53.5

 Lactating 37.0 11.6 19.6 21.8 21.8 35.1 45.0 53.7 59.2

 Number of observations: nonpregnant, nonlactating controls (n = 6,201); pregnant (n = 188); lactating (n = 77). a 

Source: Ershow et al., 1991. 
Table 3-25. Total Tapwater Intake of Women 15-49 Years Old 

Percentile Distribution 

Reproductive Mean Standard 

Statusa Deviation 5 10 25 50 75 90 95 

mL/day

 Control 1157 635 310 

Pregnant 1189 699 274 

Lactating 1310 591 430 

453 709 1065 1503 1983 2310

419 713 1063 1501 2191 2424

612 855 1330 1693 1945 2191 

mL/kg/day

 Control 19.1 10.8 

Pregnant 18.3 10.4 

Lactating 21.4 9.8 

5.2 7.5 11.7 17.3 24.4 33.1 39.1

4.9 5.9 10.7 16.4 23.8 34.5 39.6

7.4 9.8 14.8 20.5 26.8 35.1 37.4 

Fraction of daily fluid intake that is tapwater (%)

 Control 57.2 18.0 24.6

Pregnant 54.1 18.2 21.2

Lactating 57.0 15.8 27.4

32.2 45.9 59.0 70.7 79.0 83.2

27.9 42.9 54.8 67.6 76.6 83.2

38.0 49.5 58.1 65.9 76.4 80.5 

a Number of observations: nonpregnant, nonlactating controls (n = 6,201); pregnant (n = 188); lactating (n = 77). 

Source: Ershow et al., 1991. 
c 

Table 3-26. Total Fluid (mL/Day) Derived from Various Dietary Sources by Women Aged 15-49 Yearsa 

Control Women Pregnant Women Lactating Women 

Percentile Percentile Percentile 

Meanb Meanb Meanb 

Sources 50 95 50 95 50 95 

Drinking Water 583 480 1440 695 640 1760 677 560 1600 

Milk and Milk Drinks 162 107 523 308 273 749 306 285 820 

Other Dairy Products 23 8 93 24 9 93 36 27 113 

Meats, Poultry, Fish, Eggs 126 114 263 121 104 252 133 117 256 

Legumes, Nuts, and Seeds 13 0 77 18 0 88 15 0 72 

Grains and Grain Products 90 65 257 98 69 246 119 82 387 

Citrus and Noncitrus Fruit Juices 57 0 234 69 0 280 64 0 219 

Fruits, Potatoes, Vegetables, Tomatoes 198 171 459 212 185 486 245 197 582 

Fats, Oils, Dressings, Sugars, Sweets 9 3 41 9 3 40 10 6 50 

Tea 148 0 630 132 0 617 253 77 848 

Coffee and Coffee Substitutes 291 159 1045 197 0 955 205 80 955 

Carbonated Soft Drinksc 174 110 590 130 73 464 117 57 440 

Noncarbonated Soft Drinksc 38 0 222 48 0 257 38 0 222 

Beer 17 0 110 7 0 0 17 0 147 

Wine Spirits, Liqueurs, Mixed Drinks 10 0 66 5 0 25 6 0 59 

All Sources 1940 NA NA 2076 NA NA 2242 NA NA 

a Number of observations: nonpregnant, nonlactating controls (n = 6,201); pregnant (n = 188); lactating (n = 77). 

b Individual means may not add to all-sources total due to rounding. 

Includes regular, low-calorie, and noncalorie soft drinks. 

NA: Not appropriate to sum the columns for the 50th and 95th percentiles of intake. 

Source: Ershow et al., 1991. 
Table 3-27. Water Intake at Various Activity Levels (L/hr)a 

Room Activity Level 

Temperature (EF) b 

High (0.15 hp/man) Medium (0.10 hp/man) c c 

No. Intake No. Intake d 

Low (0.05 hp/man)c 

No. Intake 

100 -­ -­ -­ -­ 15 0.653 

(0.75) 

95 18 0.540 12 0.345 

(0.31) (0.59) 

6 0.50 

(0.31) 

90 7 0.286 7 0.385 

(0.26) (0.26) 

16 0.23 

(0.20) 

85 7 0.218 16 0.213 

(0.36) (0.20) 

-­ -­

80 16 0.222 -­ --

(0.14) 

-­ -­

Data expressed as mean intake with standard deviation in parentheses. a 

Humidity = 80 percent; air velocity = 60 ft/min. b 

The symbol "hp" refers to horsepower. c 

Number of subjects with continuous data. d 

Source: McNall and Schlegel, 1968. 
Table 3-28. Planning Factors for Individual Tapwater Consumption 

Environmental Condition Recommended Planning Factor (gal/day) Recommended Planning Factor (L/day) a a,b 

Hot 3.0 11.4 

Temperate 1.5 5.7 

Cold 2.0 7.6 

c 

d 

e 

Based on a mix of activities among the work force as follows: 15% light work; 65% medium work; 20% heavy work. These factors a 

apply to the conventional battlefield where no nuclear, biological, or chemical weapons are used. 

Converted from gal/day to L/day. b 

This assumes 1 quart/12-hour rest period/man for perspiration losses and 1 quart/day/man for urination plus 6 quarts/12-hours light c 

work/man, 9 quarts/12-hours moderate work/man, and 12 quarts/12-hours heavy work/man. 

This assumes 1 quart/12-hour rest period/man for perspiration losses and 1 quart/day/man for urination plus 1 quart/12-hours light d 

work/man, 3 quarts/12-hours moderate work/man, and 6 quarts/12-hours heavy work/man. 

This assumes 1 quart/12-hour rest period/man for perspiration losses, 1 quart/day/man for urination, and 2 quarts/day/man for e 

respiration losses plus 1 quart/12-hours light work/man, 3 quarts/12-hours moderate work/man, and 6 quarts/6-hours heavy 

work/man. 

Source: U.S. Army, 1983. 
Table 3-29. Drinking Water Intake Surveys 

Study 

Number of Individuals 

Consumed Type Population Surveyed 

Type of Water Time Period/ Survey 

Comments 

KEY 

Canadian Ministry of 970 Total tapwater Weekday and weekend All ages; Canada Seasonal data; includes many tapwaterNational Health and consumption day in both summer and containing items not commonly surveyed; 

Welfare, 1981 winter; estimation based possible bias because identification of 

on sizes and types of vessel size used as survey techniques; 

containers used short-term study 

Ershow and Cantor, Based on data from Total tapwater; total 3-day recall, diaries All ages; large sample Short-term recall data; seasonally 

1989 NFCS; approximately fluid consumption representative of U.S. balanced data 

30,000 individuals population 

Rosenberry and Based on data from Total tapwater; total 3-day recall, diaries All ages; large sample Short-term recall data; seasonally 

Burmaster, 1992 Ershow and Cantor, fluid consumption representative of US balanced; suitable for Monte Carlo 

1989 population simulations 

RELEVANT 

Cantor et al., 1987 5,258 Total tapwater; total 1 week/usual intake in Adults only; weighted Based on recall of behavior from previous 

fluid consumption winter based on recall toward older adults; U.S. winter; short-term data; population not 

population representative of general U.S. population 

Gillies and Paulin, 109 Total tapwater 24 hours; duplicate water Adults only; New Zealand Based on short-term data 

1983 consumption samples collected 

Hopkin and Ellis, 3,564 Total tapwater, total 1 week period, diaries All ages; Great Britain Short-term diary data 

1980 liquid consumption 

ICRP, 1981 Based on data from Water and water-based NA NA a a Survey design and intake categories not 

several sources drinks; milk; total fluids clearly defined 

NAS, 1977 Calculated average Average per capita NA NA a a Total tapwater not reported; population and 

based on several "liquid" consumption survey design not reported 

sources 
Table 3-29. Drinking Water Intake Surveys (continued) 

Study 

Number of Individuals 

Type Population Surveyed 

Type of Water Consumed Time Period/ Survey 

Comments 

Pennington, 1983 Based on NFCS and 

NHANES II; approximately 

30,000 and 20,000 

participants, respectively 

Total tapwater; total fluid NFCS:24-hour recall NFCS:1 month to 97 years; 

consumption on 2-day dairy; NHANES II:6 months to 74 

NHANES II:24-hour years; representative 

recall samples of U.S. population 

Based on short-term recall data 

USDA, 1995 Based on 89-91 CSF11; 

approximately 15,000 

individuals 

Plain drinking water, 1-day recall All ages, large sample 

coffee, tea, fruit drinks representative of U.S. 

and ades population 

Short-term recall data; seasonally 

adjusted 

U.S. EPA, 1984 Based on NFCS; 

approximately 30,000 

individuals 

Tapwater; water based 3-day recall, diaries All ages; large sample 

foods and beverages; representative of U.S. 

soups; beverage population 

consumption 

Short-term recall data; seasonally 

balanced 

U.S. EPA, 1995 Over 4,000 participants of 

NHAPS 

Number of glasses of 24-hour diaries All ages, large 

drinking water and juice representative sample of 

with tapwater U.S. population 

Does not provide data on the volume 

of tapwater consumed 

McNall and 

Schlegel, 1968 

Based on 2 groups of 8 

subjects each 

Tapwater 8-hour work cycle Males between 17-25 years 

of age; small sample; high 

activity levels/hot climates 

Based on short-term data 

U.S. Army, 1983 NA All fluids consumed to NA High activity levels/hot 

satisfy body needs for climates 

internal water; includes 

Study designed to provide water 

consumption planning factors for 

various activities and field conditions; 

soups, hot and cold 

drinks and tapwater 

based on estimated amount of water 

required to account for losses from 

urination, perspiration, and respiration

 Not applicable. a 
<1 year 0.30 L/day 0.24 L/day 0.65 L/day 0.76 L/day Tables 3-6, a 

44 mL/kg-day 35 mL/kg-day 102 mL/kg-day 127 mL/kg-day 3-7, and 3­

8 

<3 years 0.61 L/day -- 1.5 L/day -- Table3-3 c 

3-5 years 0.87 L/day -- 1.5 L/day -- Table3-3 c 

1-10 years 0.74 L/day 0.66 L/day 1.3 L/day 1.5 L/day Tables 3-6, a 

35 mL/kg-day 31 mL/kg-day 64 mL/kg-day 79.4 mL/kg- 3-7, and 3­

day 8 

11-19 years 0.97 L/day 0.87 L/day 1.7 L/day 2.0 L/day Tables 3-6, a 

18 mL/kg-day 16 mL/kg-day 32 mL/kg-day 40 mL/kg-day 3-7, and 3­

8 

Adults 1.4 L/day 1.3 L/day 2.3 L/day Tables 3-6, a 

21 mL/kg-day 19 mL/kg-day 34 mL/kg-day 3-7, and 3­

8 

Pregnant Women 1.2 L/day 1.1 L/day 2.2 L/day 2.4 L/day Table 3-25 ,d 

18.3 mL/kg-day 16 mL/kg-day 35 mL/kg-day 40 mL/kg-day 

Lactating Women 1.3 L/day 1.3 L/day 1.9 L/day 2.2 L/day Table 3-25 ,d 

21.4 mL/kg-day 21 mL/kg-day 35 mL/kg-day 37 mL/kg-day 

Adults in High 0.21 to 0.65 L/hour, depending on ambient temperature and activity level; see Table 3-27. 

Activity/Hot Climate 

Conditionse 

Active Adults 6 L/day (temperate climate) to 11 L/day (hot climate); see Table 3-28. f 

Table 3-30. Summary of Recommended Drinking Water Intake Rates 

Percentiles 

Age Group/ 

Population Mean 50th 90th 95th Multiple 

a Source: Ershow and Cantor, 1989 

b Source: Roseberry and Burmaster, 1992 

c Source: Canadian Ministry of Health and Welfare, 1981 

d Ershow et al. (1991) presented data for pregnant women, lactating women, and control women. 

e Source: McNall and Schlegal, 1968 

f Source: U.S. Army, 1983 

Table 3-11b 

Table 3-11b 

Table 3-11b 

Table 3-11b 

Fitted 

Distributions 
Table 3-31. Total Tapwater Consumption Rates From Key Studies 

Mean (L/day) Percentile Number in Reference 

90th 

(L/day) Survey 

1.38 2.41 639 Canadian Ministry of Health 

1.41 2.28 11,731 Ershow and Cantor, 1989

 and Welfare, 1981 
Table 3-32. Daily Tapwater Intake Rates From Relevant Studies

Mean (L/day) 90th Percentile Reference

1.30 2.40 Cantor et al., 1987 a

1.63 (calculated) -- NAS, 1977

1.25 1.90 Gillies and Paulin, 1983

1.04 (25 to 30 yrs) -- Pennington, 1983

1.26 (60 to 65 yrs) -- Pennington, 1983

1.04-1.47 (ages 20+) -- U.S. EPA, 1984

1.37 (20 to 64 yrs) 2.27 Ershow and Cantor, 1989

1.46 (65+ yrs) 2.29 Ershow and Cantor, 1989

1.15 -- USDA, 1995

1.07 1.87 Hopkins and Ellis, 1980

 Age of the Cantor et al. (1987) population was higher than the U.S. average. a
Table 3-33. Key Study Tapwater Intake Rates for Children 

Age Mean 90th Percentile 

(years) (L/day) (L/day) Reference 

<1 0.30 0.65 Ershow and Cantor, 1989 

<3 0.61 1.50 Canadian Ministry of National Health and Welfare, 1981 

3-5 0.87 1.50 Canadian Ministry of National Health and Welfare, 1981 

1-10 0.74 1.29 Ershow and Cantor, 1989 

6-17 1.14 2.21 Canadian Ministry of National Health and Welfare, 1981 

11-19 0.97 1.70 Ershow and Cantor, 1989 
Table 3-34. Summary of Intake Rates for 

Children in Relevant Studies 

Mean 

Age (L/day) Reference 

6-11 months 0.20 Pennington, 1983 

<1 yr 0.19 U.S. EPA, 1984 

<1 yr 0.32 Roseberry and Burmaster, 1992 

2 yrs 0.50 Pennington, 1983 

1-4 yrs 0.58 U.S. EPA, 1984 

5-9 yrs 0.67 U.S. EPA, 1984 

1-10 yrs 0.70 Roseberry and Burmaster, 1992 

10-14 yrs 0.80 U.S. EPA, 1984 

14-16 yrs 0.72 Pennington, 1983 

15-19 yrs 0.90 U.S. EPA, 1984 

11-19 yrs 0.91 Roseberry and Burmaster, 1992 
Table 3-35. Confidence in Tapwater Intake Recommendations 

Considerations Rationale Rating 

Study Elements

 • Level of peer review The study of Ershow and Cantor (1989) had a thorough expert High 

panel review. Review procedures were not reported in the 

Canadian study; it was a government report. Other reports 

presented are published in scientific journals.

 • Accessibility The two monographs are available from the sponsoring High 

agencies; the others are library-accessible.

 • Reproducibility Methods are well-described. High

 • Focus on factor of interest The studies are directly relevant to tapwater. High

 • Data pertinent to U.S. See “representativeness” below. NA

 • Primary data The two monographs used recent primary data (less than one High 

week) on recall of intake.

 • Currency Data were all collected in the 1978 era. Tapwater use may Low 

have changed since that time period.

 • Adequacy of data collection These are one- to three-day intake data. However, long term Medium

 period variability may be small. Their use as a chronic intake 

measure can be assumed.

 • Validity of approach The approach was competently executed. High

 • Study size This study was the largest monograph that had data for 11,000 High 

individuals.

 • Representativeness of the The Ershow and Cantor (1989) and Canadian surveys were High

 population validated as demographically representative. 

• Characterization of The full distributions were given in the main studies. High

 variability

 • Lack of bias in study design Bias was not apparent. High

 (high rating is desirable)

 • Measurement error No physical measurements were taken. The method relied on Medium 

recent recall of standardized volumes of drinking water 

containers, and was not validated. 

Other Elements

 • Number of studies There were two key studies for the adult and child High for adult and 

recommendations. There were six other studies for adults, children. 

one study for pregnant and lactating women, and two studies Low for the other 

for high activity/hot climates. recommended 

subpopulation values.

 • Agreement between This agreement was good. High

 researchers 

Overall Rating The data are excellent, but are not current. Medium 
Table 4-1. Estimated Daily Soil Ingestion Based on Aluminum, Silicon, and Titanium Concentrations 

Standard Geometric 

Estimation Mean Median Deviation Range 95th Percentile Mean 

Method (mg/day) (mg/day) (mg/day) (mg/day) (mg/day) (mg/day) 

Aluminum 181 121 203 25-1,324 584 128 

Silicon 184 136 175 31-799 5,78 130 

Titanium 1,834 618 3,091 4-17,076 9,590 401 

Minimum 108 88 121 4-708 386 65 

Source: Binder et al., 1986. 
Table 4-2. Calculated Soil Ingestion by Nursery School Children 

Soil Ingestion as Soil Ingestion as Soil Ingestion as 

Sample Calculated from Ti Calculated from Al Calculated from AIR Limiting Tracer 

Child Number (mg/day) (mg/day) (mg/day) (mg/day) 

1 L3 103 300 107 103 

L14 154 211 172 154 

L25 130 23 - 23 

2 L5 131 - 71 71 

L13 184 103 82 82 

L27 142 81 84 81 

3 L2 124 42 84 42 

L17 670 566 174 174 

4 L4 246 62 145 62 

L11 2,990 65 139 65 

5 L8 293 - 108 108 

L21 313 - 152 152 

6 L12 1,110 693 362 362 

L16 176 - 145 145 

7 L18 11,620 - 120 120 

L22 11,320 77 - 77 

8 L1 3,060 82 96 82 

9 L6 624 979 111 111 

10 L7 600 200 124 124 

11 L9 133 - 95 95 

12 L10 354 195 106 106 

13 L15 2,400 - 48 48 

14 L19 124 71 93 71 

15 L20 269 212 274 212 

16 L23 1,130 51 84 51 

17 L24 64 566 - 64 

18 L26 184 56 - 56 

Arithmetic Mean 1,431 232 129 105 

Source: Adapted from Clausing et al. 1987. 
Table 4-3. Calculated Soil Ingestion by Hospitalized, Bedridden Children 

Soil Ingestion as Soil Ingestion as 

Calculated from Ti Calculated from Al Limiting Tracer 

Child Sample (mg/day) (mg/day) (mg/day) 

1 G5 3,290 57 

G6 4,790 71 

57 

71 

2 G1 28 26 26 

3 G2 6,570 94 

G8 2,480 57 

84 

57 

4 G3 28 77 28 

5 G4 1,100 30 30 

6 G7 58 38 38 

Arithmetic Mean 2,293 56 49 

Source: Adapted from Clausing et al. 1987. 
Table 4-4. Mean and Standard Deviation Percentage Recovery of Eight Tracer Elements 

Tracer Element 

300 mg Soil Ingested 1500 mg Soil Ingested 

Mean SD Mean SD 

Al 152.8 107.5 93.5 15.5 

Ba 2304.3 4533.0 149.8 69.5 

Mn 1177.2 1341.0 248.3 183.6 

Si 139.3 149.6 91.8 16.6 

Ti 251.5 316.0 286.3 380.0 

V 345.0 247.0 147.6 66.8 

Y 120.5 42.4 87.5 12.6 

Zr 80.6 43.7 54.6 33.4 

Source: Adapted from Calabrese et al., 1989. 
Table 4-5. Soil and Dust Ingestion Estimates for Children Aged 1-4 Years 

Intake (mg/day)a

Tracer Element

N Mean Median SD 95th Maximum 

Percentile 

Aluminum

 soil 64 153 29 852 223 6,837

 dust 64 317 31 1,272 506 8,462

 soil/dust combined 64 154 30 629 478 4,929 

Silicon

 soil 64 154 40 693 276 5,549

 dust 64 964 49 6,848 692 54,870

 soil/dust combined 64 483 49 3,105 653 24,900 

Yttrium

 soil 62 85 9 890 106 6,736

 dust 64 62 15 687 169 5,096

 soil/dust combined 62 65 11 717 159 5,269 

Titanium

 soil 64 218 55 1,150 1,432 6,707

 dust 64 163 28 659 1,266 3,354

 soil/dust combined 64 170 30 691 1,059 3,597 

a Corrected for Tracer Concentrations in Foods 

Source: Adapted from Calabrese et al., 1989. 
Table 4-6. Average Daily Soil Ingestion Values Based on Aluminum, Silicon, and Titanium as Tracer Elementsa 

Element Mean Median Mean Range 

(mg/d) (mg/d) (mg/d) (mg/d) 

Standard Error of the 

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 

Excludes three children who did not provide any samples (N=101). a 

Negative values occurred as a result of correction for nonsoil sources of the tracer elements. b 

Source: Adapted from Davis et al., 1990. 
Table 4-7. Geometric Mean (GM) and Standard Deviation (GSD) LTM Values 

for Children at Daycare Centers and Campgrounds 

Daycare Centers Campgrounds 

Age (yrs) Sex n GM LTM GSD LTM n GM LTM GSD LTM 

(mg/day) (mg/day) (mg/day) (mg/day) 

<1 Girls 3 81 1.09 - - -

Boys 1 75 - - - -

1-<2 Girls 20 124 1.87 3 207 1.99 

Boys 17 114 1.47 5 312 2.58 

2-<3 Girls 34 118 1.74 4 367 2.44 

Boys 17 96 1.53 8 232 2.15 

3-4 Girls 26 111 1.57 6 164 1.27 

Boys 29 110 1.32 8 148 1.42 

4-<5 Girls 1 180 - 19 164 1.48 

Boys 4 99 1.62 18 136 1.30 

All girls 86 117 1.70 36 179 1.67 

All boys 72 104 1.46 42 169 1.79 

Total 162a 111 1.60 78b 174 1.73 

a Age and/or sex not registered for eight children. b Age not registered for seven children. 

Source: Adapted from Van Wijnen et al., 1990. 
Table 4-8. Estimated Geometric Mean LTM Values of Children Attending Daycare Centers 

According to Age, Weather Category, and Sampling Period 

First Sampling Period Second Sampling Period 

Weather Category Age (years) 

n 

Bad <1 3 

Estimated Geometric Mean Estimated Geometric Mean 

LTM Value LTM Value 

(mg/day) n (mg/day) 

94 3 67 

(>4 days/week precipitation) 1-<2 18 103 33 80 

2-<3 33 109 48 

4-<5 

Reasonable <1 

(2-3 days/week precipitation) 1-<2 

2-<3 

3-<4 

4-<5 

Good <1 

(<2 days/week precipitation) 1-<2 

2-<3 

3-<4 

4-<5 

Source: Van Wijnen et al., 1990. 

91 

5 124 6 109 

1 61 

10 96 

13 99 

19 94 

1 61 

4 102 

42 229 

65 166 

67 138 

10 132 
Table 4-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates Per Child for 64 Children (mg/day) a 

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 

For each child, estimates of soil ingestion were formed on days 4-8 and the mean of these estimates was then evaluated for each a 

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 4-10. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on 

Data for 64 Subjects Projected Over 365 Daysa 

Range 1 - 2,268 mg/d 

50th Percentile (median) 75 mg/d 

90th Percentile 1,190 mg/d 

95th Percentile 1,751 mg/d 

b

 Based on fitting a log-normal distribution to model daily soil a

 ingestion values.

 Subject with pica excluded. b 

Source: Stanek and Calabrese, 1995a. 
Table 4-11. Estimates of Soil Ingestion for Children 

Annual Average 

Exposure Days/Year Fraction Soil Soil Intake 

Scenarios Media (mg/day) Activity Content (mg/day) 

Young Child (2.5 Years Old) 

Outdoor Activities (Summer) Soil 250 130 1 90 

Indoor Activities (Summer) Dust 50 182 0.8 20 

Indoor Activities (Winter Dust 100 182 0.8 40 

TOTAL SOIL INTAKE 150 

Older Child (6 Years Old) 

Outdoor Activities (Summer) Soil 50 152 1 21 

Indoor Activities (Year-Round) Dust 3 365 0.8 2.4 

TOTAL SOIL INTAKE 23.4 

Source: Hawley, 1985. 
Table 4-12. Estimated Soil Ingestion Rate Summary Statistics and Parameters for Distributions 

Using Binder et al. (1986) Data with Actual Fecal Weights 

Soil Intake (mg/day)

Trace Element Basis

A1 Si Ti MEANa 

Mean 97 

Min 11 

10th 21 

20th 33 

30th 39 

40th 43 

Med 45 

60th 55 

70th 73 

80th 104 

90th 197 

Max 1,201 

85 1,004 91 

10 1 13 

19 3 22 

23 22 34 

36 47 43 

52 172 49 

60 293 59 

65 475 69 

79 724 92 

106 1,071 100 

166 2,105 143 

642 14,061 921 

Lognormal Distribution Parameters 

Median 45 

Standard Deviation 169 

Arithmetic Mean 97 

60 -- 59 

95 -- 126 

85 -- 91 

Underlying Normal Distribution Parameters 

Mean 4.06 4.07 -- 4.13 

Standard Deviation 0.88 0.85 -- 0.80 

a MEAN = arithmetic average of soil ingestion based on aluminum and silicon. 

Source: Thompson and Burmaster, 1991. 
Table 4-13. Tukey's Multiple Comparison of Mean Log Tracer Recovery in Adults Ingesting Known Quantities of Soil 

Tracer Reported Mean Age Adjusted Mean 

(mg/day) (mg/day) 

Calabrese et al., 1989 Study 

Aluminum 153 160 

Silicon 154 161 

Titanium 218 228 

Vanadium 459 480 

Yttrium 85 89 

Davis et al., 1990 Study 

Aluminum 39 53 

Silicon 81 111 

Titanium 246 333 

Age adjusted mean estimates of soil ingestion in young children. Mean estimates of soil ingestion for each tracer in each a 

study were adjusted using the following equation: 

Y = x e(-0.112 * yr), where Y = adjusted mean soil ingestion (mg/day), x = a constant, and yr = age in years.

Source: Sedman and Mahmood, 1994. 
Table 4-14. Positive/Negative Error (bias) in Soil Ingestion Estimates in the Calabrese et al. (1989) Mass-balance Study: 

Effect on Mean Soil Ingestion Estimate (mg/day)a 

Negative Error 

Lack of Fecal 

Sample on Final Other Total Negative Total Positive Original Adjusted 

Study Day Causes Error Error Net Error Mean Mean b 

Aluminum 14 11 25 43 +18 153 136 

Silicon 15 6 21 41 +20 154 133 

Titanium 82 187 269 282 +13 218 208 

Vanadium 66 55 121 432 +311 459 148 

Yttrium 8 26 34 22 -12 85 97 

Zirconium 6 91 97 5 -92 21 113 

How to read table: for example, aluminum as a soil tracer displayed both negative and positive error. The cumulative total negative a 

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 128-subject-weeks in milligrams of soil ingested per day. b 

Source: Calabrese and Stanek, 1995. 
Table 4-15. Soil Ingestion Rates for Assessment Purposes 

Receptor Age Setting Hands Ingestion Rate Exposure Ingestion 

Soil Load on Soil Exposure Suggested Average Daily Soil 

(mg/cm ) (mg/hr) Durations (mg/day) 2 

(hr/yr) 

Pica Child --- 1,000 200 500 

2.5 yrs Outdoor 0.5 20 1,000 50 

Indoor 0.4 3 Remaining 60 a 

6 yrs Outdoor 0.5 10 700 20 

Indoor 0.04 0.15 5,000 2 

Adult Gardening 1.0 20 300 20 

Indoor 0.04 0.03 5,000 0.4

 Hawley (1985) assumed the child spent all the time at home, so that the indoor time was 8,760 hours/year minus the outdoor time. a 

Source: Sheppard, 1995 
Table 4-16. Estimates of Soil Ingestion for Adults 

Annual Average Soil 

Exposure Days/Year Fraction Soil Intake 

Scenarios Media (mg/day) Activity Content (mg/day) 

Adult 

Work in attic (year-round) Dust 110 12 0.8 3 

Living Space (year-round) Dust 0.56 365 0.8 0.5 

Outdoor Work (summer) Soil 480 43 1 57 

TOTAL SOIL INTAKE 60.5 

Source: Hawley, 1985. 
Table 4-17. Adult Daily Soil Ingestion Estimates by Week and Tracer Element After Subtracting Food and Capsule Ingestion,

 Based on Median Amherst Soil Concentrations: Means and Medians Over Subjects (mg)a 

Week Al Ba Mn Si Ti V Y Zr 

Means 

1 110 -232 330 30 71 1,288 63 134 

2 98 12,265 1,306 14 25 43 21 58 

3 28 201 790 -23 896 532 67 -74 

Medians 

1 60 -71 388 31 102 1,192 44 124 

2 85 597 1,368 15 112 150 35 65 

3 66 386 831 -27 156 047 60 -144

 Data were converted to milligrams a

 Negative values occur because of correction for food and capsule ingestion. b 

Source: Calabrese et al., 1990 
Table 4-18. Daily Soil Ingestion Estimation in a Soil-Pica Child 

by Tracer and by Week (mg/day) 

Tracer Estimated Soil Estimated Soil 

Week 1 Week 2 

Ingestion Ingestion 

Al 74 13,600 

Ba 458 12,088 

Mn 2,221 12,341 

Si 142 10,955 

Ti 1,543 11,870 

V 1,269 10,071 

Y 147 13,325 

Zr 86 2,695 

Source: Calabrese et al., 1991 
Table 4-19. Ratios of Soil, Dust, and Residual Fecal Samples in the Soil Pica Child 

Tracer Ratio Pairs Soil Fecal Dust Soil Origin as Predicted by Specific Tracer 

Estimated % of Residual Fecal Tracers of 

Ratios 

1. Mn/Ti 208.368 215.241 260.126 87 

2. Ba/Ti 187.448 206.191 115.837 100 

3. Si/Ti 148.117 136.662 7.490 92 

4. V/Ti 14.603 10.261 17.887 100 

5. Ai/Ti 18.410 21.087 13.326 100 

6. Y/Ti 8.577 9.621 5.669 100 

7. Mn/Y 24.293 22.373 45.882 100 

8. Ba/Y 21.854 21.432 20.432 71 

9. Si/Y 17.268 14.205 1.321 81 

10. V/Y 1.702 1.067 3.155 100 

11. Al/Y 2.146 2.192 2.351 88 

12. Mn/Al 11.318 10.207 19.520 100 

13. Ba/Al 10.182 9.778 8.692 73 

14. Si/Al 8.045 6.481 0.562 81 

15. V/Al 0.793 0.487 1.342 100 

16. Si/V 10.143 13.318 0.419 100 

17. Mn/Si 1.407 1.575 34.732 99 

18. Ba/Si 1.266 1.509 15.466 83 

19. Mn/Ba 1.112 1.044 2.246 100 

Source: Calabrese and Stanek, 1992. 
Table 4-20. Soil Intake Studies 

Study Study Type Observations Age 

Number of Population Studied 

Comments 

CHILDREN KEY STUDIES: 

Binder et al., 1986 Tracer study using aluminum, silicon, 59 children 1-3 years Children living near lead Did not account for tracer in food 

and titanium smelter in Montana and medicine; used assumed fecal 

weight of 15 g/day; short-term study 

conducted over 3 days 

Calabrese et al., 1989 Tracer - mass balance study using 64 Children 1-4 years Children from greater Corrected for tracer in food and 

aluminum, barium, manganese, silicon, Amherst area of medicine; study conducted over 

titanium, vanadium, ytrium, and Massachusetts; highly- two-week period; used adults to 

zirconium educated parents validate methods; one pica child in 

study group. 

Clausing et al., 1987 Tracer study using aluminum, acid 18 nursery school 2-4 years Dutch children Did not account for tracer in food 

insoluble residue, and titanium children; 6 and medicines; used tracer-based 

hospitalized intake rates for hospitalized 

children children as background values; 

short-term study conducted over 5 

days 

Davis et al., 1990 Tracer - mass balance study using 104 children 2-7 years Children from 3-city area Corrected for tracer in food and 

aluminum silicon and titanium in Washington State medicine; short-term study 

conducted over seven-day period; 

collected information on 

demographic characteristics 

affecting soil intake. 

Stanek and Calabrese, Adjusted soil intake estimates 64 children 1-4 years Same children as in Based on data from Calabrese et 

1995a Calabrese et al., 1989 al., 1989 

Stanek and Calabrese, Recalculated intake rates based on three 164 children 1-7 years Children from three Based on studies of Calabrese et 

1995b previous mass-balance studies using the 6 adults 25-41 years mass-balance studies al., 1989; Davis et al., 1990; and 

Best Tracer Method Calabrese et al., 1990. 

Van Wïjnen et al., 1990 Tracer study using aluminum, acid 292 daycare 1-5 years Dutch children Did not account for tracer in food 

insoluble residue, and titanium children; 78 and medicines; used tracer-based 

campers; 15 intake for hospitalized children as 

hospitalized background values; evaluated 

children population (campers) with greater 

access to soil; evaluated 

differences in soil intake due to 

weather conditions. 

CHILDREN RELEVANT STUDIES: 

AIHC, 1994 Reanalysis of data from Calabrese et al., 6 adults 21-41 years Health adults Used data from Calabrese et al. 

1990 (1990) study to derive soil ingestion 

rates using zirconium as a tracer; 

recent studies indicate that 

zirconium is not a good tracer 

Calabrese and Stanek, Evaluated errors in soil ingestion 64 children 1-4 years Study population of Based on Calabrese et al., 1989 

1995 estimates Calabrese et al., 1989 data. 
Table 4-20. Soil Intake Studies (continued) 

Study Study Type Observations Age 

Number of Population Studied 

Comments 

CHILDREN RELEVANT STUDIES (continued): 

Day et al., 1977 Measured dirt on sticky sweets Not specified Not specified Not specified Based on observations and crude 

and assumed number of sweets measurements. 

eaten per day 

Duggan and Williams, 1977 Measured soil on fingers and Not specified Not specified Areas around London Based on observations and crude 

observed mouthing behavior measurements. 

Hawley, 1985 Assumed soil intake rates based Not specified Young children, Not specified No data on soil intake collected; 

on nature and duration of activities older children, estimates based on assumptions 

adults regarding data from previous 

studies. 

Lepow et al., 1974; 1975 Measured soil on hands and 22 children 2-6 years Urban children from Based on observations over 3-6 

observed mouthing behavior Connecticut hours of play and crude 

measurement techniques. 

Sedman and Mahmood, 1994 Adjusted data from earlier tracer­ 64 children from Adjusted to 2­ Same children as in Based on data from Calabrese et al., 

mass balance studies to generate Calabrese et al., year old child Calabrese et al., 1989 1989 and Davis et al., 1990. 

mean soil intake rates for a 2-year 1989 study and 104 and Davis et al., 1990 

old child children from Davis et study 

al., 1990 study 

Sheppard, 1995 Provides estimates based on the Not specified 1 year-adults Various Presents mean estimates for 

current literature on soil ingestion (age not children and adults; provides 

from tracer methods and specified) ingestion estimates for indoor and 

recommends values for use in outdoor activities based on Hawley, 

assessments 1985. 

Thompson and Burmaster, Re-evaluation of Binder et al., 59 children 1-3 years Children living near Re-calculated soil intake rates from 

1991 1986 data lead smelter in Binder et al., 1986 data using actual 

Montana fecal weights instead of assumed 

weights. 

ADULT SOIL INTAKE STUDIES: 

Hawley, 1985 Assumed soil intake rates based Not specified Young children, Not specified No data on soil intake collected; 

on nature and duration of activities older children, estimates based on assumptions 

adults regarding data from previous 

studies. 

Calabrese et al., 1990 Measured excretory output after 6 adults 21-41 years Healthy adult Data used to validate the analytical 

ingestion of capsules with volunteers methodology used in the children’s 

sterilized soil study (Calabrese, 1989). 

PICA STUDIES: 

Calabrese et al., 1991 Tracer - mass balance 1 pica child 3.5 years 1 pica child from Child was observed as part of the 

greater Amherst area Calabrese et al., 1989 study. 

of Massachusetts 

Calabrese and Stanek, 1992 Reanalysis of data from Calabrese 1 pica child 3.5 years 1 pica child from Distinguished between outdoor soil 

et al., 1991 greater Amherst area ingestion and indoor dust ingestion 

of Massachusetts in a soil pica child. 
Table 4-21. Confidence in Soil Intake Recommendation 

Considerations Rationale Rating 

Study Elements 

C	 Level of peer review All key studies are from peer review literature. High 

C	 Accessibility Papers are widely available from peer review journals. High 

C	 Reproducibility Methodology used was presented, but results are difficult to Medium 

reproduce. 

C	 Focus on factor of interest The focus of the studies was on estimating soil intake rate by High (for children) 

children; studies did not focus on intake rate by adults. Low (for adults) 

C	 Data pertinent to U.S. Two of the key studies focused on Dutch children; other Medium 

studies used children from specific areas of the U.S. 

C	 Primary data All the studies were based on primary data. High 

C	 Currency Studies were conducted after 1980. High 

C	 Adequacy of data collection Children were not studied long enough to fully characterize day Medium 

period to day variability. 

C	 Validity of approach The basic approach is the only practical way to study soil Medium 

intake, but refinements are needed in tracer selection and 

matching input with outputs. The more recent studies 

corrected the data for sources of the tracers in food. There 

are, however, some concerns about absorption of the tracers 

into the body and lag time between input and output. 

C	 Study size The sample sizes used in the key studies were adequate for Medium (for children) 

children. However, only few adults have been studied. Low (for adults) 

C	 Representativeness of the The study population may not be representative of the U.S. in Low 

population terms of race, socio-economics, and geographical location; 

Studies focused on specific areas; two of the studies used 

Dutch children. 

C	 Characterization of variability Day-to-day variability was not very well characterized. Low 

C	 Lack of bias in study design The selection of the population studied may introduce some Medium 

(high rating is desirable) bias in the results (i.e., children near a smelter site, volunteers 

in nursery school, Dutch children). 

C	 Measurement error Errors may result due to problems with absorption of the Medium 

tracers in the body and mismatching inputs and outputs. 

Other Elements 

C	 Number of studies There are 7 key studies. High 

C	 Agreement between researchers Despite the variability, there is general agreement among Medium 

researchers on central estimates of daily intake for children. 

Overall Rating Studies were well designed; results were fairly consistent; Medium (for children 

sample size was adequate for children and very small for - long-term central 

adults; accuracy of methodology is uncertain; variability cannot estimate) 

be characterized due to limitations in data collection period. Low (for adults) 

Insufficient data to recommend upper percentile estimates for Low (for upper 

both children and adults. percentile) 
Table 4-22. Summary of Estimates of Soil Ingestion by Children 

Mean (mg/day) Upper Percentile (mg/day) References 

Al Si AIR Ti Y Al Si Ti Y a 

181 184 584 578 Binder et al. 1986 

230 129 Clausing et al. 1987 

39 82 245.5 Davis et al. 1990 

64.5 160 268.4 b 

153 154 218 85 223 276 1,432 106 Calabrese et al. 1989 

154 483 170 65 478 653 1,059 159 b 

122 139 -­ 271 165 254 224 279 144 Stanek and Calabrese, 1995a 

133 217 Stanek and Calabrese, 1995b c 

69-120 Van Wïjnen et al. 1990 d 

b 

b 

b 

b b b 

c 

b b b 

Average = 146 mg/day soil 383 mg/day soil 

191 mg/day soil and dust 587 mg/day soil and dust 

combined combined 

AIR = Acid Insoluble Residue a 

Soil and dust combined b 

BTM c 

LTM; corrected value d 
Table 4-23. Summary of Recommended Values for Soil Ingestion 

Population Mean Upper Percentile 

Children 100 mg/day 400 mg/day 

Adults 50 mg/day -­

Pica child 10 g/day --­

a 

c 

b 

200 mg/day may be used as a conservative estimate of the mean (see text). a 

Study period was short; therefore, these values are not estimates of usual intake. b 

To be used in acute exposure assessments. Based on only one pica child (Calabrese et al., 1989). c 
Table 5-1. Calibration and Field Protocols for Self-Monitoring of Activities Grouped by Subject Panels 

Panel Calibration Protocol Field Protocol 

Panel 1 - Healthy Outdoor Workers ­ Laboratory treadmill exercise tests, indoor 3 days in 1 typical summer week (included 

15 female, 5 male, age 19-50 hallway walking tests at different self- most active workday and most active day off); 

chosen speeds, 2 outdoor tests consisted HR recordings and activity diary during 

of 1-hour cycles each of rest, walking, and waking hours. 

jogging. 

Panel 2 - Healthy Elementary School Outdoor exercises each consisted of 20 Saturday, Sunday and Monday (school day) in 

Students - 5 male, 12 female, age minute rest, slow walking, jogging and fast early autumn; HR recordings and activity diary 

10-12 walking during waking hours and during sleep. 

Panel 3 - Healthy High School Outdoor exercises each consisted of 20 Same as Panel 2, however, no HR recordings 

Students - 7 male, 12 female, age minute rest, slow walking, jogging and fast during sleep for most subjects. 

13-17 walking 

Panel 4 - Adult Asthmatics, clinically Treadmill and hallway exercise tests 1 typical summer week, 1 typical winter week; 

mild, moderate, and severe - 15 hourly activity/health diary during waking 

male, 34 female, age 18-50 hours; lung function tests 3 times daily; HR 

recordings during waking hours on at least 3 

days (including most active work day and day 

off). 

Panel 5 - Adult Asthmatics from 2 Treadmill and hallway exercise tests Similar to Panel 4, personal NO and acid 

neighborhoods of contrasting O3 air exposure monitoring included. (Panels 4 and

quality - 10 male, 14 female, age 19­ 5 were studied in different years, and had 10 

46 subjects in common). 

2 

Panel 6 - Young Asthmatics - 7 male, Laboratory exercise tests on bicycles and Similar to Panel 4, summer monitoring for 2 

6 female, age 11-16 treadmills successive weeks, including 2 controlled 

exposure studies with few or no observable 

respiratory effects. 

Panel 7 - Construction Workers - 7 Performed similar exercises as Panel 2 HR recordings and diary information during 1 

male, age 26-34 and 3, and also performed job-related tests typical summer work day. 

including lifting and carrying a 9-kg pipe. 

Source: Linn et al., 1992 
c 

Table 5-2. Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and Self-Estimated Breathing Rates 

3 Inhalation Rates (m /hr) 

Panel Na Mean VR 99th Percentile Mean VR at Activity Levels 

(m /hr) 3 VR (m /hr) 3 b 

Slow Mediumc Fastc 

Healthy

 1 - Adults 20 0.78 2.46 0.72 1.02 3.06

 2 - Elementary School Students 17 0.90 1.98 0.84 0.96 1.14

 3 - High School Students 19 0.84 2.22 0.78 1.14 1.62

 7 - Construction Workersc 7 1.50 4.26 1.26 1.50 1.68 

Asthmatics

 4 - Adults 49 1.02 1.92 1.02 1.68 2.46

 5 - Adultsd 24 1.20 2.40 1.20 2.04 4.02 

6 - Elementary and High School 13 1.20 2.40 1.20 1.20 1.50 

Students 

a Number of individuals in each survey panel. b Some subjects did not report medium and/or fast activity. Group means were calculated from individual means (i.e., give equal 

weight to each individual who recorded any time at the indicated activity level). 

Construction workers recorded only on 1 day, mostly during work, while others recorded on $ 1 work or school day and $ 1 day 

off. d Excluding subjects also in Panel 4. 

Source: Linn et al., 1992. 
Table 5-3. Distribution of Predicted IR by Location and Activity Levels for Elementary and High School Students 

Age % Recorded 

(yrs) Student Location Activity Level Timea 

Inhalation Rates (m /hr) 3 

Percentile Rankingsb 

Mean ± SD 1st 50th 99.9th 

10-12 EL Indoors slow 49.6 0.84 ± 0.36 0.18 0.78 2.34 c 

(n =17) medium 23.6 0.96 ± 0.42 0.24 0.84 2.58 d 

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 HS Indoors slow 70.7 0.78 ± 0.36 0.30 0.72 3.24 c 

(n =19) medium 10.9 0.96 ± 0.42 0.42 0.84 4.02 d 

fast 1.4 1.26 ± 0.66 0.54 1.08 6.84c 

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 

Recorded time averaged about 23 hr per elementary school student and 33 hr. per high school student, over 72-hr. periods. a 

Geometric means closely approximated 50th percentiles; geometric standard deviations were 1.2-1.3 for HR, 1.5-1.8 for VR. b 

EL = elementary school student; HS = high school student. c 

N = number of students that participated in survey. d 

Highest single value. e 

Source: Spier et al., 1992. 
Table 5-4. Average Hours Spent Per Day in a Given Location and Activity Level for Elementary (EL) and High School (HS) Students 

Student Total Time Spent 

(EL , n =17; HS , N =19) Location (hrs/day) a c b c 

Activity Level 

Slow Medium Fast 

EL Indoor 16.3 2.9 0.4 19.6 

EL Outdoor 2.2 1.7 0.5 4.4 

HS Indoor 19.5 1.5 0.2 21.2 

HS Outdoor 1.2 1.3 0.2 2.7 

Elementary school (EL) students were between 10-12 years old. a 

High school (HS) students were between 13-17 years old. b 

N corresponds to number of school students. c 

Source: Spier et al., 1992. 
Table 5-5. Distribution Patterns of Daily Inhalation Rates for Elementary (EL) and High School (HS) Students Grouped by Activity 

Level 

Students (yrs) Location Activity type (m /day) 

Age Mean IR Percentile Rankings a 

b 

3 

1st 50th 99.9th 

EL (n =17) 10-12 Indoor Light 13.7 2.93 12.71 38.14 c 

Moderate 2.8 0.70 2.44 7.48 

Heavy 0.4 0.096 0.34 1.37 

EL Outdoor Light 2.1 0.79 1.72 9.50 

Moderate 1.84 0.41 1.63 5.71 

Heavy 0.57 0.24 0.48 1.80 

HS (n=19) 13-17 Indoor Light 15.2 5.85 14.04 63.18 

Moderate 1.4 0.63 1.26 6.03 

Heavy 0.25 0.11 0.22 1.37 

HS Outdoor Light 1.15 0.50 1.08 6.34 

Moderate 1.64 0.62 1.40 7.41 

Heavy 0.29 0.096 0.20 1.19 

For this report, activity type presented in Table 5-2 was redefined as light activity for slow, moderate activity for medium, and a 

heavy activity for fast. 

Daily inhalation rate was calculated by multiplying the hours spent at each activity level (Table 5-4) by the corresponding b 

inhalation rate (Table 5-3). 

Number of elementary (EL) and high school students (HS). c 

Source: Adapted from Spier et al., 1992 (Generated using data from Tables 5-3 and 5-4). 
Table 5-6. Summary of Average Inhalation Rates (m /hr) by Age Group and Activity Levels for Laboratory Protocols 3 

Age Group Resting Sedentary Light Moderate Heavy a b c d e 

Young Children 0.37 0.40 0.65 DNP DNP f g 

Children 0.45 0.47 0.95 1.74 2.23 h 

Adult Females 0.43 0.48 1.33 2.76 2.96 i j 

Adult Males 0.54 0.60 1.45 1.93 3.63 k 

Resting defined as lying (see Appendix Table 5A-1 for original data). a 

Sedentary defined as sitting and standing (see Appendix Table 5A-1 for original data). b 

Light defined as walking at speed level 1.5 - 3.0 mph (see Appendix Table 5A-1 for original data). c 

Moderate defined as fast walking (3.3 - 4.0 mph) and slow running (3.5 - 4.0 mph) (see Appendix Table 5A-1 for original data). d 

Heavy defined as fast running (4.5 - 6.0 mph) (see Appendix Table 5A-1 for original data). e 

Young children (both genders) 3 - 5.9 yrs old. f 

DNP. Group did not perform this protocol or N was too small for appropriate mean comparisons. All young children did not run. g 

Children (both genders) 6 - 12.9 yrs old. h 

Adult females defined as adolescent, young to middle aged, and older adult females. i 

Older adults not included in mean value since they did not perform running protocols at particular speeds. j 

Adult males defined as adolescent, young to middle aged, and older adult males. k 

Source: Adapted from Adams, 1993. 
Table 5-7. Summary of Average Inhalation Rates (m /hr) by Age Group and 3 

Activity Levels in Field Protocols 

Age Group Light Sedentary Moderate a b c 

Young Children DNP DNP 0.68 d e 

Children DNP DNP 1.07 f 

Adult Females 1.10 0.51 DNP g h 

Adult Males 1.40 0.62 1.78 i j 

Light activity was defined as car maintenance (males), housework (females), a 

and yard work (females) (see Appendix Table 5A-2 for original data). 

Sedentary activity was defined as car driving and riding (both genders) (see b 

Appendix Table 5A-2 for original data). 

Moderate activity was defined as mowing (males); wood working (males); c 

yard work (males); and play (children) (see Appendix Table 5A-2 for original 

data). 

Young children (both genders) = 3 - 5.9 yrs old. d 

DNP. Group did not perform this protocol or N was too small for appropriate e 

mean comparisons. 

Children (both genders) = 6 - 12.9 yrs old. f 

Adult females defined as adolescent, young to middle aged, and older adult g 

females. 

Older adults not included in mean value since they did not perform this h 

activity. 

Adult males defined as adolescent, young to middle aged, and older adult i 

males. 

Adolescents not included in mean value since they did not perform this j 

activity. 

Source: Adams, 1993. 
Table 5-8. Distributions of Individual and Group Inhalation/Ventilation Rate for Outdoor Workers 

Ventilation Rate (VR) (m /hr) 3 

Percentile 

Population Group and Subgroupa Mean ± SD 1 50 99 

All Subjects (n = 19) b 1.68 ± 0.72 0.66 1.62 3.90 

Job 

GCW /Laborers (n=5) c 1.44 ± 0.66 0.48 1.32 3.66 

Iron Workers (n=3) 1.62 ± 0.66 0.60 1.56 3.24 

Carpenters (n=11) 1.86 ± 0.78 0.78 1.74 4.14 

Site 

Medical Office Site (n=7) 1.38 ± 0.66 0.60 1.20 3.72 

Hospital Site (n=12) 1.86 ± 0.78 0.72 1.80 3.96 

a 

b Each group or subgroup mean was calculated from individual means, not from pooled data. 

n = number of individuals performing specific jobs or number of individuals at survey sites. c GCW - general construction worker. 

Source: Linn et al., 1993. 
Table 5-9. Individual Mean Inhalation Rate (m /hr) by Self-Estimated Breathing Rate or Job Activity Category for Outdoor Workers 3 

Self-Estimated Job Activity Category (m /hr) 

Breathing Rate (m /hr) 3 

3 

Population Group and Subgroup Slow Med Fast Sit/Std Walk Carry Tradeb 

All Subjects (n=19) 1.44 1.86 2.04 1.56 1.80 2.10 1.92 

Job 

GCW /Laborers (n=5) 1.20 1.56 1.68 1.26 1.44 1.74 1.56 a 

Iron Workers (n=3) 1.38 1.86 2.10 1.62 1.74 1.98 1.92 

Carpenters (n=11) 1.62 2.04 2.28 1.62 1.92 2.28 2.04 

Site 

Office Site (n=7) 1.14 1.44 1.62 1.14 1.38 1.68 1.44 

Hospital Site (n=12) 1.62 2.16 2.40 1.80 2.04 2.34 2.16 

GCW - general construction worker a 

Trade - "Working at Trade" (i.e., tasks specific to the individual's job classification) b 

Source: Linn et al., 1993 
Table 5-10. Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-Energy Intakes for 

Individuals Sampled in the 1977-78 NFCS 

Cohort/Age Body Weight BMR Energy Intake (EFD) Ratio a 

(years) kg MJ d kcal d MJ d kcal d EFD/BMR -1b -1c -1 -1 

Children

 Under 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 10.8 2568 1.41

 19 to 22 74 7.56 1804 10.0 2395 1.33

 23 to 34 79 7.87 1879 10.1 2418 1.29

 35 to 50 82 7.59 1811 9.51 2270 1.25

 51 to 64 80 7.49 1788 9.04 2158 1.21

 65 to 74 76 6.18 1476 8.02 1913 1.30

 75 + 71 5.94 1417 7.82 1866 1.32 

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

 19 to 22 59 5.69 1359 6.71 1601 1.18

 23 to 34 62 5.88 1403 6.72 1603 1.14

 35 to 50 66 5.78 1380 6.34 1514 1.10

 51 to 64 67 5.82 1388 6.40 1528 1.10

 65 to 74 66 5.26 1256 5.99 1430 1.14

 75 + 62 5.11 1220 5.94 1417 1.16 

Calculated from the appropriate age and gender-based BMR equations given in Appendix Table 5A-4. a 

MJ d - mega joules/day b -1 

kcal d - kilo calories/day c -1 

Source: Layton, 1993. 
Table 5-11. Daily Inhalation Rates Calculated from Food-Energy Intakes 

Daily Inhalation Inhalation Rates 

Rate Sleep MET Value Inactive Active a b c c 

Cohort/Age (years) L (m /day) (h) A F (m /day) (m /day) d 3 e f 3 3 

Children 

<1 

1 - 2 

3 - 5 

6 - 8 

1 4.5 11 1.9 2.7 2.35 6.35 

2 6.8 11 1.6 2.2 4.16 9.15 

3 8.3 10 1.7 2.2 4.98 10.96 

3 10 10 1.7 2.2 5.95 13.09 

Males 

9 - 11 

12 - 14 

15 - 18 

19 - 22 

23 - 34 

35 - 50 

51 - 64 

65 - 74 

75+ 

Lifetime average g 

3 14 9 1.9 2.5 7.32 18.3 

3 15 9 1.8 2.2 8.71 19.16 

4 17 8 1.7 2.1 10.31 21.65 

4 16 8 1.6 1.9 10.21 19.4 

11 16 8 1.5 1.8 10.62 19.12 

16 15 8 1.5 1.8 10.25 18.45 

14 15 8 1.4 1.7 10.11 17.19 

10 13 8 1.6 1.8 8.34 15.01 

1 13 8 1.6 1.9 8.02 15.24 

14 

Females 

9 - 11 

12 - 14 

15 - 18 

19 - 22 

23 - 34 

35 - 50 

51 - 64 

65 - 74 

75+ 

Lifetime average g 

3 13 9 1.9 2.5 6.63 16.58 

3 12 9 1.6 2.0 7.61 15.20 

4 12 8 1.5 1.7 8.14 13.84 

4 11 8 1.4 1.6 7.68 12.29 

11 11 8 1.4 1.6 7.94 12.7 

16 10 8 1.3 1.5 7.80 11.7 

14 10 8 1.3 1.5 7.86 11.8 

10 9.7 8 1.4 1.5 7.10 10.65 

1 9.6 8 1.4 1.6 6.90 11.04 

10 

Daily inhalation rate was calculated by multiplying the EFD values (see Table 5-10) by H x VQ x (m 1,000 L ) for subjects under 9 years of a 3 -1 

age and by 1.2 x H x VQ x (m 1,000 L ) (for subjects 9 years of age and older (see text for explanation). 3 -1 

Where: 

EFD = Food energy intake (Kcal/day) or (MJ/day) 

H = Oxygen uptake = 0.05 LO /KJ or 0.21 LO /Kcal 2 2 

VQ = Ventilation equivalent = 27 = geometric mean of VQs (unitless) 

MET = Metabolic equivalent b 

Inhalation rate for inactive periods was calculated as BMR x H x VQ x (d 1,440 min ) and for active periods by multiplying inactive inhalation c -1 

rate by F (See footnote f); BMR values are from Table 5-10. 

Where: 

BMR = Basal metabolic rate (MJ/day) or (kg/hr) 

L is the number of years for each age cohort. d 

For individuals 9 years of age and older, A was calculated by multiplying the ratio for EFD/BMR (unitless) (Table 5-10) by the factor 1.2 (see e 

text for explanation). 

F = (24A - S)/(24 - S) (unitless), ratio of the rate of energy expenditure during active hours to the estimated BMR (unitless) f 

Where: 

S = Number of hours spent sleeping each day (hrs) 

Lifetime average was calculated by multiplying individual inhalation rate by corresponding L values summing the products across cohorts and g 

dividing the result by 75, the total of the cohort age spans. 

Source: Layton, 1993. 
Table 5-12. Daily Inhalation Rates Obtained from the Ratios 

of Total Energy Expenditure to Basal Metabolic Rate (BMR) 

Gender/Age Body Weight BMR H Inhalation Rate, V 

(yrs) (kg) (MJ/day) VQ A (m O /MJ) (m /day) 

a b 

c 3 

2 

E 3 d 

Male 

0.5 - <3 14 3.4 27 1.6 0.05 7.3 

3 - <10 23 4.3 27 1.6 0.05 9.3 

10 - <18 53 6.7 27 1.7 0.05 15 

18 - <30 76 7.7 27 1.59 0.05 17 

30 - <60 80 7.5 27 1.59 0.05 16 

60+ 75 6.1 27 1.59 0.05 13 

Female 

0.5 - <3 11 2.6 27 1.6 0.05 5.6 

3 - <10 23 4.0 27 1.6 0.05 8.6 

10 - <18 50 5.7 27 1.5 0.05 12 

18 - <30 62 5.9 27 1.38 0.05 11 

30 - <60 68 5.8 27 1.38 0.05 11 

60+ 67 5.3 27 1.38 0.05 9.9 

Body weight was based on the average weights for age/gender cohorts in the U.S. population. a 

The BMRs (basal metabolic rate) are calculated using the respective body weights and BMR equations (see Appendix Table 5A-4). b 

The values of the BMR multiplier (EFD/BMR) for those 18 years and older were derived from the Basiotis et al. (1989) study: Male c 

= 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 5-11 for 12-14 years and 15-18 years, age brackets for males and 

females were used: male = 1.7 and female = 1.5. 

Inhalation rate = BMR x A x H x VQ; VQ = ventilation equivalent and H = oxygen uptake. d 

Source: Layton, 1993. 
Table 5-13. Daily Inhalation Rates Based on Time-Activity Survey 

Age (yrs) 

and Activity MET 

Males Females 

Body 

Weight BMR Duration E V V a b c d 

E 

e 

3 E 

f 

(kg) (KJ/hr) (hr/day) (MJ/day) (m /day) (m 3/hr) 

Body 

Weight BMR Duration E V V 

(KJ/hr) (hr/day) (MJ/day) (m /day) (m /hr) a 

(kg) 

b c d E e 

3 E 

f 

3 

20-34 

Sleep 1 

Light 1.5 

Moderate 4 

Hard 6 

Very Hard 10 

Totals 

35-49 

Sleep 1 

Light 1.5 

Moderate 4 

Hard 6 

Very Hard 10 

Totals 

50-64 

Sleep 1 

Light 1.5 

Moderate 4 

Hard 6 

Very Hard 10 

Totals 

65-74 

Sleep 1 

Light 1.5 

Moderate 4 

Hard 6 

Very Hard 10 

Totals 

76 320 7.2 2.3 3.1 0.4 

76 320 14.5 7.0 9.4 0.7 

76 320 1.2 1.5 2.1 1.7 

76 320 0.64 1.2 1.7 2.6 

76 320 0.23 0.74 1.0 4.3 

24 17 17 

81 314 7.1 2.2 3.0 0.4 

81 314 14.6 6.9 9.3 0.6 

81 314 1.4 1.8 2.4 1.7 

81 314 0.59 1.1 1.5 2.5 

81 314 0.29 0.91 1.2 4.2 

24 13 17 

80 312 7.3 2.3 3.1 0.4 

80 312 14.9 7.0 9.4 0.6 

80 312 1.1 1.4 1.9 1.7 

80 312 0.50 0.94 1.3 2.5 

80 312 0.14 0.44 0.6 4.2 

24 12 16 

75 256 7.3 1.9 2.5 0.3 

75 256 14.9 5.7 7.7 0.5 

75 256 1.1 1.1 1.5 1.4 

75 256 0.5 0.8 1.0 2.1 

75 256 0.14 0.36 0.48 3.5 

24 9.8 13 

62 283 7.2 2.0 2.8 0.4 

62 283 14.5 6.2 8.3 0.6 

62 283 1.2 1.4 1.8 1.5 

62 283 0.64 1.1 1.5 2.3 

62 283 0.23 0.65 0.88 3.8 

24 11 15 

67 242 7.1 1.7 2.3 0.3 

67 242 14.6 5.3 7.2 0.5 

67 242 1.4 1.4 1.8 1.3 

67 242 0.59 0.9 1.2 2.0 

67 242 0.29 0.70 0.95 3.2 

24 9.9 13 

68 244 7.3 1.8 2.4 0.3 

68 244 14.9 5.4 7.4 0.5 

68 244 1.1 1.1 1.4 1.3 

68 244 0.5 0.7 1.0 2.0 

68 244 0.14 0.34 0.46 3.3 

24 9.4 13 

67 221 7.3 1.6 2.2 0.3 

67 221 14.9 4.9 6.7 0.4 

67 221 1.1 1.0 1.3 1.2 

67 221 0.5 0.7 0.9 1.8 

67 221 0.14 0.31 0.42 3.0 

24 8.5 11 

Body weights were obtained from Najjar and Rowland (1987) a 

The basal metabolic rates (BMRs) for the age/gender cohorts were calculated using the respective body weights and the BMR equations (Appendix Table 5A-4) b 

Duration of activities were obtained from Sallis et al. (1985) c 

Energy expenditure rate (E) was calculated by multiplying BMR (KJ/hr) x (MJ/1000 KJ) x duration (hr/day) x MET d 

V (inhalation rate) was calculated by multiplying E (MJ/day) by H(0.05 m oxygen/MJ) by VQ (27) e E 

3 

V (m /hr) was calculated by multiplying BMR (KJ/hr) x (MJ/1000 KJ) x MET x H (0.05 m oxygen/MJ) x VQ (27) f 

E 

3 3 

Source: Layton, 1993. 
c 

Table 5-14. Inhalation Rates for Short-Term Exposures 

Activity Type 

Rest Sedentary Light Moderate Heavy 

Gender/Age (yrs) Weight BMRb MET (BMR Multiplier) 

(kg)a (MJ/day) 1 1.2 2c 4d 10e 

Inhalation Rate (m /hr) 3 f,g 

Male

 0.5 - <3 14 3.40 0.19 0.23 0.38 0.78 1.92

 3 - <10 23 4.30 0.24 0.29 0.49 0.96 2.40

 10 - <18 53 6.70 0.38 0.45 0.78 1.50 3.78

 18 - <30 76 7.70 0.43 0.52 0.84 1.74 4.32

 30 - <60 80 7.50 0.42 0.50 0.84 1.68 4.20

 60+ 75 6.10 0.34 0.41 0.66 1.38 3.42 

Female

 0.5 - <3 11 2.60 0.14 0.17 0.29 0.60 1.44

 3 - <10 23 4.00 0.23 0.27 0.45 0.90 2.28

 10 - <18 50 5.70 0.32 0.38 0.66 1.26 3.18

 18 - <30 62 5.90 0.33 0.40 0.66 1.32 3.30

 30 - <60 68 5.80 0.32 0.39 0.66 1.32 3.24

 60+ 67 5.30 0.30 0.36 0.59 1.20 3.00 

a Body weights were based on average weights for age/gender cohorts of the U.S. population b The BMRs for the age/gender cohorts were calculated using the respective body weights and the BMR equations (Appendix Table 5A-4). 

Range of 1.5 - 2.5. d Range of 3 - 5. e Range of >5 - 20. f The inhalation rate was calculated by multiplying BMR (MJ/day) x H (0.05 L/KJ) x MET x VQ (27) x (d/1,440 min) g 3 Original data were presented in L/min. Conversion to m /hr was obtained as follows: 60 min m3 L x x hr 1000L min 

Source: Layton, 1993. 
Table 5-15. Daily Inhalation Rates Estimated From Daily Activitiesa 

Inhalation Rate (IR) 

Subject Resting Light Activity Daily Inhalation 

(m /hr) (m /hr) Rate (DIR) 3 3 b 

(m /day) 3 

Adult Man 0.45 1.2 22.8 

Adult Woman 0.36 1.14 21.1 

Child (10 yrs) 0.29 0.78 14.8 

Infant (1 yr) 0.09 0.25 3.76 

Newborn 0.03 0.09 0.78 

DIR ' 1 

T j

K 

i'1 

IRiti 

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 

IR i = Corresponding inhalation rate at i activity th 

t i = Hours spent during the i activity th 

k = Number of activity periods 

T = Total time of the exposure period (i.e., a day) 

Source: ICRP, 1981 
Table 5-16. Summary of Human Inhalation Rates for Men, Women, and Children by Activity Level (m /hour) 3 a 

n Resting n Light n Moderate n Heavy b c d e f 

Adult male 454 0.7 102 0.8 102 2.5 267 4.8 

Adult female 595 0.3 786 0.5 106 1.6 211 2.9 

Average adult 0.5 0.6 2.1 3.9 g 

Child, age 6 years 8 0.4 16 0.8 4 2.0 5 2.3 

Child, age 10 years 10 0.4 40 1.0 29 3.2 43 3.9 

Values of inhalation rates for males, females, and children (male and female) presented in this table represent the mean of values reported for a 

each activity level in 1985. (See Appendix Table 5A-7 for a detailed listing of the data from U.S. EPA, 1985.) 

n = number of observations at each activity level. b 

Includes watching television, reading, and sleeping. c 

Includes most domestic work, attending to personal needs and care, hobbies, and conducting minor indoor repairs and home improvements. d 

Includes heavy indoor cleanup, performance of major indoor repairs and alterations, and climbing stairs. e 

Includes vigorous physical exercise and climbing stairs carrying a load. f 

Derived by taking the mean of the adult male and adult female values for each activity level. g 

Source: Adapted from U.S. EPA, 1985. 
Table 5-17. Activity Pattern Data Aggregated for Three Microenvironments by 

Activity Level for all Age Groups 

Microenvironment Activity Level Microenvironment at Each Activity 

Average Hours Per Day in Each 

Level 

Indoors Resting 9.82 

Outdoors Resting 0.505 

In Transportation Vehicle Resting 0.86 

Light 9.82 

Moderate 0.71 

Heavy 0.098

 TOTAL 20.4 

Light 0.505 

Moderate 0.65 

Heavy 0.12

 TOTAL 1.77 

Light 0.86 

Moderate 0.05 

Heavy 0.0012

 TOTAL 1.77 

Source: Adapted from U.S. EPA, 1985. 
Table 5-18. Summary of Daily Inhalation Rates Grouped by

 Age and Activity level 

Subject 

Daily Inhalation Rate (m /day) Total Daily IR 3 a b 

(m /day) 3 

Resting Light Moderate Heavy 

Adult Male 7.83 8.95 3.53 1.05 21.4 

Adult Female 3.35 5.59 2.26 0.64 11.8 

Adult Average 5.60 6.71 2.96 0.85 16 c 

Child 4.47 8.95 2.82 0.50 16.74

 (age 6) 

Child 4.47 11.19 4.51 0.85 21.02 

(age 10) 

IR ' 1 

T j

K 

i'1 

IRit

i 

Daily inhalation rate was calculated using the following equation: a 

IR = inhalation rate at i activity (Table 5-18) i 

th 

t = hours spent per day during i activity (Table 5-19) i 

th 

k = number of activity periods 

T = total time of the exposure period (e.g., a day) 

Total daily inhalation rate was calculated by summing the specific activity (resting, b 

light, moderate, heavy) daily inhalation rate. 

Source: Generated using the data from U.S. EPA (1985) as shown in Tables 5-16 

and 5-17. 
c 

Table 5-19. Distribution Pattern of Predicted VR and EVR (equivalent ventilation rate) for 20 Outdoor Workers 

3 a b 3 2 VR (m /hr) EVR (m /hr/m body surface) 

Self-Reported Arithmetic Geometric Arithmetic Geometric c Activity Level N Mean ± SD 

Sleep 18,597 0.42 ± 0.16 

Slow 41,745 0.71 ± 0.4 

Medium 3,898 0.84 ± 0.47 

Fast 572 2.63 ± 2.16 

Mean ± SD Mean ± SD Mean ± SD 

0.39 ± 0.08 0.23 ± 0.08 0.22 ± 0.08 

0.65 ± 0.09 0.38 ± 0.20 0.35 ± 0.09 

0.76 ± 0.09 0.48 ± 0.24 0.44 ± 0.09 

1.87 ± 0.14 1.42 ± 1.20 1.00 ± 0.14 

Percentile Rankings, VR 

1 5 10 50 90 95 99 99.9 

Sleep 0.18 0.18 0.24 0.36 0.66 0.72 0.90 1.20 

Slow 0.30 0.36 0.36 0.66 1.08 1.32 1.98 4.38 

Medium 0.36 0.42 0.48 0.72 1.32 1.68 2.64 3.84 

Fast 0.42 0.54 0.60 1.74 5.70 6.84 9.18 10.26 

Percentile Rankings, EVR

1 5 10 50 90 95 99 99.9 

Sleep 0.12 0.12 0.12 0.24 0.36 0.36 0.48 0.60 

Slow 0.18 0.18 0.24 0.36 0.54 0.66 1.08 2.40 

Medium 0.18 0.24 0.30 0.42 0.72 0.90 1.38 2.28 

Fast 0.24 0.30 0.36 0.90 3.24 3.72 4.86 5.52 

a 3 Data presented by Shamoo et al. (1991) in liters/minute were converted to m /hr. b EVR = VR per square meter of body surface area. 

Number of minutes with valid appearing heart rate records and corresponding daily records of breathing rate. 

Source: Shamoo et al., 1991 
Table 5-20. Distribution Pattern of Inhalation Rate by Location and Activity Type for 20 Outdoor Workers 

Location Activity Type Activity Level % of Time ± SD % of Avg. a 

Self-reported Inhalation rate (m /hr) 3 b 

c 

Indoor Essential Sleep 28.7 0.42 ± 0.12 69 ± 15 

Slow 29.5 0.72 ± 0.36 106 ± 43 

Medium 2.4 0.72 ± 0.30 129 ± 38 

Fast 0 0 0 

Indoor Non-essential Slow 20.4 0.66 ± 0.36 98 ± 36 

Medium 0.9 0.78 ± 0.30 120 ± 50 

Fast 0.2 1.86 ± 0.96 278 ± 124 

Outdoor Essential Slow 11.3 0.78 ± 0.36 117 ± 42 

Medium 1.8 0.84 ± 0.54 130 ± 56 

Fast 0 0 0 

Outdoor Non-essential Slow 3.2 0.90 ± 0.66 136 ± 90 

Medium 0.8 1.26 ± 0.60 213 ± 91 

Fast 0.7 2.82 ± 2.28 362 ± 275 

Essential activities include income-related, work, household chores, child care, study and other school activities, personal care, a 

and destination-oriented travel; Non-essential activities include sports and active leisure, passive leisure, some travel, and social or 

civic activities. 

Data presented by Shamoo et al. (1991) in liters/mintue were converted to m /hr. b 3 

Statistic was calculated by converting each VR for a given subject to a percentage of her/his overall average. c 

Source: Adapted from Shamoo et al., (1991). 
Table 5-21. Actual Inhalation Rates Measured at 

Four Ventilation Levels 

Subject Location 

Mean Inhalation Rate (m /hr) a 3 a 

Low Medium Heavy Heavy Very 

All subjects Indoor 1.23 1.83 3.13 4.13 

(Treadmill

post)

Outdoor 0.88 1.96 2.93 4.90 

Total 0.93 1.92 3.01 4.80 

60 min 

hr x m 3 1000L x L min 

Original data were presented in L/min. Conversion to m /hr was obtained as a 3 

follows: 

Source: Adapted from Shamoo et al., 1992 
Table 5-22. Confidence in Inhalation Rate Recommendations 

Considerations Rationale Rating 

Study Elements C	 Peer Review Studies are from peer reviewed journal articles and an EPA peer

reviewed report. High 

C	 Accessibility Studies in journals have wide circulation.

EPA reports are available from the National Technical Information

Service. 

High 

C	 Reproducibility Information on questionnaires and interviews were not provided. Medium 

C	 Focus on factor of interest Studies focused on ventilation rates and factors influencing them. High 

C	 Data pertinent to U.S. Studies conducted in the U.S. High 

C	 Primary data Both data collection and re-analysis of existing data occurred. Medium 

C	 Currency Recent studies were evaluated. High 

C	 Adequacy of data collection period Effort was made to collect data over time. High 

C	 Validity of approach Measurements were made by indirect methods. Medium 

C	 Representativeness of the population An effort has been made to consider age and gender, but not

systematically. 

Medium 

C	 Characterization of variability An effort has been made to address age and gender, but not

systematically. High 

C	 Lack of bias in study design Subjects were selected randomly from volunteers and measured in the High 

same way. 

C	 Measurement error Measurement error is well documented by statistics, but procedures

measure factor indirectly. 

Medium 

Other Elements 

C	 Number of studies Five key studies and six relevant studies were evaluated. 

C	 Agreement between researchers There is general agreement among researchers using different

experimental methods. High 

Overall Rating Several studies exist that attempt to estimate inhalation rates

according to age, gender and activity. High 
Table 5-23. Summary of Recommended Values for Inhalation 

Population Mean Upper Percentile 

Long-term Exposures 

Infants 

<1 year 4.5 m /day --­

Children 

1-2 years 6.8 m /day ---

3-5 years 8.3 m /day ---

6-8 years 10 m /day ---

9-11 years 

males 14 m /day --­

females 13 m /day ---

12-14 years 

males 15 m /day --­

females 12 m /day ---

15-18 years 

males 17 m /day --­

females 12 m /day --­

Adults (19-65+ yrs) 

females 11.3 m /day --­

males 15.2 m /day --­

3 

3 

3 

3 

3 

3 

3 

3 

3 

3 

3 

3 

Short-term Exposures 

Adults 

Rest 0.4 m /hr --­

Sedentary Activities 0.5 m /hr --­

Light Activities 1.0 m /hr --­

Moderate Activities 1.6 m /hr --­

Heavy Activities 3.2 m /hr --­

3 

3 

3 

3 

3 

Children 

Rest 0.3 m /hr --­

Sedentary Activities 0.4 m /hr --­

Light Activities 1.0 m /hr --­

Moderate Activities 1.2 m /hr --­

Heavy Activities 1.9 m /hr --­

Outdoor Workers 

Hourly Average 1.3 m /hr 3.3 m /hr 

Slow Activities 1.1 m /hr 

Moderate Activities 1.5 m /hr 

Heavy Activities 2.5 m /hr 

3 

3 

3 

3 

3 

3 

3 

3 

3 

3 

Note: See Tables 5-25, 5-26, and 5-27 for reference studies. 
Table 5-24. Summary of Inhalation Rate Studies 

Study Population Surveyed Survey Time Period Data Generated Limitations/Advantages 

KEY INHALATION RATE STUDIES: 

Adams, 1993 n=160, ages 6-77; n = 40, ages 3-12. Three 25 min phases of resting Mean values of IR for adult HR correlated poorly with IR. 

protocol in the lab 6 mins of active males and females and children 

protocols in the lab. 30 min by their activity levels. 

phases of field protocols repeated 

once. 

Layton, 1993 NFCS survey: n.30,000; NHANES survey: Daily IRs; IRs at 5 activity levels; Reported food biases in the dietary 

n.20,000 and IR for short-term exposures surveys employed; time activity 

Time Activity survey: n.2,126 at 5 activity levels. survey was based on recall. 

Linn et al., 1992 Panel 1 - 20 healthy outdoor workers, ages Late spring and early autumn. 3 Mean and upper estimates of IR; Small sample size; Calibration data 

19-50; Panel 2 - 17 healthy elementary diary days. Construction workers' Mean IR at 3 activity levels. not obtained over full HR range; 

school students, ages 10-12; Panel 3 - 19 diary day. activities based on short-term diary 

healthy high school students, ages 13-17; data. 

Panel 4 - 49 adult asthmatics, ages 18-50; 

Panel 5 - 24 adult asthmatics, ages 19-46; 

Panel 6 - 13 young asthmatics, ages 11­

16; Panel 7 - 7 construction workers, ages 

26-34. 

Linn et al., 1993 n=19 construction workers. (Mid-July-early November, 1991) Distribution patterns of hourly IR Small sample population size; 

Diary recordings before work, by activity level. breathing rates subjective in nature; 

during work and break times activities based on short-term diary 

data. 

Spier et al., 1992 n=36 students, ages 10-17. (Late September - October) Distribution patterns of hourly IR Activities based on short-term diary 

Involved 3 consecutive days of by activity levels and location data; self-estimated breathing rate 

diary recording by younger population was biased; 

small sample population size. 

RELEVANT INHALATION RATE STUDIES: 

ICRP, 1974 Based on data from other references -­ Reference daily IR for adult Validity and accuracy of data set 

females, adult males, children employed not defined; IR was 

(10 yrs), and infant (1 yr) estimated not measured. 

Shamoo et al., n=9 volunteer workers ages 21-37, n=20 Involved 3-min indoor session/two No IR data presented. No useful data were presented for 

1990 outdoor workers, 19-50 years old. 3-hr outdoor session at 4 activity dose assessments studies. 

levels 

Shamoo et al., n=20 outdoor workers, ages 19-50 Diary recordings of three 24-hr. Distribution patterns of IR and Small sample size; short-term diary 

1991 periods within a week. EVR by activity levels and data. 

location. 

Shamoo et al., n=9 non-sedentary subjects, ages 21-37. 3-min. intervals of indoor Actual measured ventilation Small sample size; training 

1992 exercises/two 3-hr outdoor rates presented. approach may not be cost-effective; 

exercise sessions at 4 activity VR obtained for outdoor workers 

levels. which are sensitive subpopulation. 

U.S. EPA, 1985 Based on data from several literature -­ Estimated IR for adult males, Validity and accuracy of data set 

sources adult females and children (ages employed not defined; IR was 

6 and 10) by various activity estimated not measured. 

levels. 

Note: IR = inhalation rate; HR = heart rate; EVR = equivalent ventilation rate. 
Table 5-25. Summary of Adult Inhalation Rates for Short-Term Exposure Studies 

Rest 

Arithmetic Mean (m /hr) 3 

Reference 

Activity Level 

Sedentary Light Moderate High 

0.5 0.5 1.4 2.4 3.3 Adams, 1993 (Lab protocols) 

-- 0.6 1.2 1.8 -­ Adams, 1993 (Field protocols) 

0.4 0.4 0.7 1.4 3.6 Layton, 1993 (Short-term 

exposure) 

0.4 -- 0.6 1.5 3.0 Layton, 1993 (3rd approach) 

-­ -- 1.0 1.6 3.0 Linn et al., 1992 
Table 5-26. Summary of Children’s (18 years old or less) Inhalation Rates for Long-Term Exposure Studiesa 

Arithmetic Mean (m /day) 3 

Age Males Females Females Reference 

Males and 

less than 1 yr -­ -- 4.5 Layton, 1993 

1-2 years -­ -- 6.8 Layton, 1993 

3-5 years -­ -- 8.3 Layton, 1993 

6-8 years -­ -­ 10 Layton, 1993 

9-11 years 14 13 -­ Layton, 1993 

12-14 years 15 12 -­ Layton, 1993 

15-18 years 17 12 -­ Layton, 1993

 Layton, 1993 1st approach. a 
Table 5-27. Summary of Children’s Inhalation Rates for Short-Term Exposure Studies 

Rest 

Arithmetic Mean (m /hr) 3 

Reference 

Activity Level 

Sedentary Light Moderate High 

0.4 0.4 0.8 -­ -­ Adams, 1993 (Lab protocols) 

-­ -­ -- 0.9 -­ Adams, 1993 (Field protocols) 

0.2 0.3 0.5 1.0 2.5 Layton, 1993 (Short-term data) 

-­ -- 1.8 2.0 2.2 Spier et al., 1992 (10-12 yrs) 

-­ -- 0.8 1.0 11 Linn et al., 1992 (10-12 yrs) 
Table 5A-1. Mean Minute Ventilation (V , L/min) by Group and Activity for Laboratory Protocols E 

Activity Young Children Children Adult Females Adult Males a 

Lying 6.19 7.51 7.12 8.93 

Sitting 6.48 7.28 7.72 9.30 

Standing 6.76 8.49 8.36 10.65 

Walking 1.5 mph 10.25 DNP DNP DNP 

1.875 mph 10.53 DNP DNP DNP 

2.0 mph DNP 14.13 DNP DNP 

2.25 mph 11.68 DNP DNP DNP 

2.5 mph DNP 15.58 20.32 24.13 

3.0 mph DNP 17.79 24.20 DNP 

3.3 mph DNP DNP DNP 27.90 

4.0 mph DNP DNP DNP 36.53 

Running 3.5 mph DNP 26.77 DNP DNP 

4.0 mph DNP 31.35 46.03 DNP 

4.5 mph DNP 37.22 47.86 57.30 

5.0 mph DNP DNP 50.78 58.45 

6.0 mph DNP DNP DNP 65.66 

b 

b 

b 

b 

Young Children, male and female 3-5.9 yr olds; Children, male and female 6-12.9 yr olds; Adult Females, a 

adolescent, young to middle-aged, and older adult females; Adult Males, adolescent, young to middle-aged, 

and older adult males; DNP, group did not perform this protocol or N was too small for appropriate mean 

comparisons 

Older adults not included in the mean value since they did not perform running protocol at particular speeds. b 

Source: Adams, 1993. 
Table 5A-2. Mean Minute Ventilation (V , L/min) by Group and Activity for Field Protocols E 

Activity Young Children Adult Females Adult Males 

Childrena 

Play 11.31 17.89 DNP DNP 

Car Driving DNP DNP 8.95 10.79 

Car Riding DNP DNP 8.19 9.83 

Yardwork DNP DNP 19.23 26.07 /31.89 

Housework DNP DNP 17.38 DNP 

Car Maintenance DNP DNP DNP 23.21 

Mowing DNP DNP DNP 36.55 

Woodworking DNP DNP DNP 24.42 

e b c 

d 

e 

e 

Young Children, male and female 3-5.9 yr olds; Children, male and female 6-12.9 yr olds; Adult Females, a 

adolescent, young to middle-aged, and older adult females; Adult Males, adolescent, young to middle-aged, 

and older adult males; DNP, group did not perform this protocol or N was too small for appropriate mean 

comparisons; 

Mean value for young to middle-aged adults only b 

Mean value for older adults only c 

Older adults not included in the mean value since they did not perform this activity. d 

Adolescents not included in mean value since they did not perform this activity e 

Source: Adams, 1993. 
Table 5A-3. Characteristics of Individual Subjects: Anthropometric Data, Job Categories, Calibration Results 

Subj. # Age (years) Ht. (in.) Wt. (lb.) 

Calibration 

Ethnic Group Job Site HR r a b c 

Ranged 

2e 

1761 26 71 180 Wht GCW Ofc 69-108 .91 

1763 29 63 135 Asn GCW Ofc 80-112 .95 

1764 32 71 165 Blk Car Ofc 56-87 .95 

1765 30 73 145 Wht GCW Ofc 66-126 .97 

1766 31 67 170 His Car Ofc 75-112 .89 

1767 34 74 220 Wht Car Ofc 59-114 .98 

1768 32 69 155 Blk GCW Ofc 62-152 .95 

1769 32 77 230 Wht Car Hosp 69-132 .99 

1770 26 70 180 Wht Car Hosp 63-106 .89 

1771 39 66 150 Wht Car Hosp 88-118 .91 

1772 32 71 260 Wht Car Hosp 83-130 .97 

1773 39 69 170 Wht Irn Hosp 77-128 .95 

1774 23 68 150 His Car Hosp 68-139 .98 

1775 42 67 150 Wht Irn Hosp 76-118 .88 

1776 29 70 180 His Car Hosp 68-152 .99 

1778 35 76 220 Ind Car Hosp 70-129 .94 

1779 40 70 175 Wht Car Hosp 72-140 .99 

1780 37 75 242 His Irn Hosp 68-120 .98 

1781 38 65 165 His Lab Hosp 66-121 .89 

Mean 33 70 181 70-123 .94 

SD 5 4 36 8-16 .04 

Abbreviations are interpreted as follows. Ethnic Group: Asn = Asian-Pacific, Blk = Black, His = Hispanic, Ind = American a 

Indian, Wht = White 

Job: Car = carpenter, GCW = general construction worker, Irn = ironworker, Lab = laborer b 

Site: Hosp = hospital buidling, Ofc = medical office complex. Calibration data c 

HR range = range of heart rates in calibration study d 

r = coefficient of determination (proportion of ventilation rate variability explainable by heart rate variability under calibration-study e 2 

conditions, using quadratic prediction equation). 

Source: Linn et al., 1993. 
Table 5A-4. Statistics of the Age/Gender Cohorts Used to Develop Regression Equations for Predicting Basal Metabolic Rates 

(BMR) 

Gender/Age BMR Body 

Weight 

(y) MJ d ±SD CV (kg) N BMR Equation r -1 a b c d 

Males

 Under 3 1.51 0.918 0.61 6.6 162 0.249 bw - 0.127 0.95

 3 to < 10 4.14 0.498 0.12 21 338 0.095 bw + 2.110 0.83

 10 to < 18 5.86 1.171 0.20 42 734 0.074 bw + 2.754 0.93

 18 to < 30 6.87 0.843 0.12 63 2879 0.063 bw + 2.896 0.65

 30 to < 60 6.75 0.872 0.13 64 646 0.048 bw + 3.653 0.6

 60 + 5.59 0.928 0.17 62 50 0.049 bw + 2.459 0.71 

Females

 Under 3 1.54 0.915 0.59 6.9 137 0.244 bw - 0.130 0.96

 3 to < 10 3.85 0.493 0.13 21 413 0.085 bw + 2.033 0.81

 10 to < 18 5.04 0.780 0.15 38 575 0.056 bw + 2.898 0.8

 18 to < 30 5.33 0.721 0.14 53 829 0.062 bw + 2.036 0.73

 30 to < 60 5.62 0.630 0.11 61 372 0.034 bw + 3.538 0.68

 60 + 4.85 0.605 0.12 56 38 0.038 bw + 2.755 0.68 

Coefficient of variation (SD/mean) a 

N = number of subjects b 

Body weight (bw) in kg c 

coefficient of correlation d 

Source: Layton, 1993. 
Table 5A-5. Selected Ventilation Values During Different Activity Levels Obtained From Various Literature Sources 

Col. 1 2 3 4 5 6 

Line Subject W (kg) Exercise 

Resting Light Activity Heavy Work Maximal Work During 

f VT V* f VT V* f VT V* f VT V* 

1 Man 68.5 12 750 7.4 17 1670 29 21 2030 43 

2 1.7 m SA 12 500 6 

3 30y; 170 cm L 15 500 7.5 16 1250 20 

4 20-33 y 70.4 40 3050 111 

5 Woman 54 12 340 4.5 19 860 16 30 880 25 

6 30 y; 160 cm L 15 400 6 20 940 19 

7 20-25 y; 165.8 cm L 60.3 46 2100 90 

8 Pregnant (8th mo) 16 650 10 

Adult 

2 

9 male, 14-16 y 16 330 5.2 53 2520 113 

10 male, 14-15 y 59.4 

11 female, 14-16 y 15 300 4.5 

12 female, 14-15 y; 164.9 cm L 56 52 1870 88 

Adolescent 

13 10 y; 140 cm L 16 300 4.8 24 600 14 

14 males, 10-11 y 36.5 58 1330 71 

15 males, 10-11 y; 140.6 cm L 32.5 61 1050 61 

16 females, 4-6 y 20.8 70 600 40 

17 females, 4-6 y; 111.6 cm L 18.4 66 520 34 

18 Infant, 1 y 30 48 1.4 

19 Newborn 2.5 34 15 0.5 

20 20 hrs-13 wk 2.5-5.3 68 51 3.5 

21 9.6 hrs 3.6 25 21 0.5 

22 6.6 days 3.7 29 21 0.6 

Children 

a 

b a,b b 

W = body weights referable to the dimension quoted in column 1; f = frequency (breaths/min); VT = tidal volume (ml); V* = minute volume (l/min); SA = surface area; cm L = 

length/height; y = years of age; wk = week. 

Calculated from V* = f x VT. a 

Crying. b 

Source: ICRP, 1981. 
Table 5A-6. Estimated Minute Ventilation Associated with Activity Level for Average Male Adulta 

Level of work L/min Representative activities 

Light 13 Level walking at 2 mph; washing clothes 

Light 19 Level walking at 3 mph; bowling; scrubbing floors 

Light 25 Dancing; pushing wheelbarrow with 15-kg load; simple construction; stacking 

firewood 

Moderate 30 Easy cycling; pushing wheelbarrow with 75-kg load; using sledgehammer 

Moderate 35 Climbing stairs; playing tennis; digging with spade 

Moderate 40 Cycling at 13 mph; walking on snow; digging trenches 

Heavy 55 Cross-country skiing; rock climbing; stair climbing 

Heavy 63 with load; playing squash or handball; chopping 

Very heavy 72 with axe 

Very heavy 85 Level running at 10 mph; competitive cycling 

Severe 100+ Competitive long distance running; cross-country skiing 

Average adult assumed to weigh 70 kg. a 

Source: Adapted from U.S. EPA, 1985 
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Table 5A-7. Minute Ventilation Ranges by Age, Sex, and Activity Level 

Ventilation ranges 

(liters/minute)

 Age Sex Resting Light Moderate Heavy 

(years) n Range Mean n Range Mean n Range Mean n Range Mean

 Infants M/F 316 0.25 - 2.09 0.84 

2 F 

M 

3 F 

M 

4 F 2 32.0 - 32.5 32.3 

M 4 39.3 - 43.3 41.2

 5 F 3 31.0 - 35.0 32.8 

M 3 30.9 - 42.6 37.5

 6 F 2 35.9 - 38.9 37.4 

M 8 5.0 - 7.0 6.5 16 5.0 - 32.0 13.9 4 28.0 - 43.0 33.3 3 35.5 - 43.5 40.3

 7 F 3 48.2 - 51.4 49.6 

M 2 44.1 - 55.8 50.0

 8 F 4 51.2 - 67.6 57.6 

M 3 59.3 - 62.2 60.7

 9 F 27 55.8 - 63.4 50.9 

M 7 59.5 - 75.2 65.7

 10 F 21 46.2 - 71.1 60.4 

M 10 5.2 - 8.3 7.1 20 5.2 - 35.0 17.2 9 41.0 - 68.0 53.4 6 63.9 - 74.6 70.5 

F 7 49.7 - 80.9 63.5 

M 20 20.3 20 33.1 9 47.6 - 77.5 65.5

 12 F 54 4.1 - 16.1 15.4 4 19.6 - 46.3 26.5 31 65.5 - 79.9 71.8 

M 56 7.2 - 16.3 15.4 6 18.5 - 46.3 34.1 9 58.1 - 84.7 67.7

 13 F 5 7.2 - 15.4 9.9 5 18.5 - 46.3 30.3 7 67.6 - 102.6 87.7 

M 16 3.1 - 15.4 8.9 30 3.1 - 24.9 16.4 29 14.4 - 48.4 32.8 38 27.8 - 105.0 57.9

 14 F 53 3.1 - 15.6 14.9 3 21.6 - 37.1 28.1 5 80.7 - 100.7 88.9 

M 77 3.1 - 27.8 14.2 24 24.7 - 55.0 39.7 16 42.2 - 121.0 86.9

 15 F 1 6.2 1 26.8 6 68.4 - 97.1 87.1 

M 8 3.1 - 26.8 11.1 7 27.8 - 46.3 39.3 6 48.4 - 140.3 110.5

 16 F 50 15.2 8 73.6 - 119.1 93.9 

M 50 15.6 3 79.6 - 132.2 102.5

 17 F 2 91.9 - 95.3 93.6 

M 12 5.8 - 9.0 7.3 12 40.0 - 63.0 48.6 3 89.4 - 139.3 107.7

 18 F 

M 9 99.7 - 143.0 120.9

 Adults F 595 4.2 - 11.66 5.7 786 4.2 - 29.4 8.1 106 20.7 - 34.2 26.5 211 23.4 - 114.8 47.9

 Adults M 454 2.3 - 18.8 12.2 102 2.3 - 27.6 13.8 102 14.4 - 78.0 40.9 267 34.6 - 183.4 80.0

 n = number of observations 3 Note: Values in liters/minute can be converted to units of m /hour by multiplying by the conversion factor, 60 minutes/hour 

1000 liters/m3

 Source: Adapted from U.S. EPA, 1985. 
Biologically 

Effective 

Dose 

Potential Applied Internal 

Dose Dose Dose 

Chemical 

Exposure 

Organ 

Metabolism 

Effect 

Mouth / Nose Lung 

Intake Uptake 

Figure 5-1. Schematic of Dose and Exposure: Respiratory Route 

Source: U.S. EPA, 1992. 
Table 6-1. Summary of Equation Parameters for Calculating Adult Body Surface Area 

Body Part N P R S.E. 

Equation for surface areas (m ) 2 

a W H 2 o 

a1 a2 

Head

 Female 57 0.0256 0.124 0.189 0.01 0.302 0.00678

 Male 32 0.0492 0.339 -0.0950 0.01 0.222 0.0202 

Trunk

 Female 57 0.188 0.647 -0.304 0.001 0.877 0.00567

 Male 32 0.0240 0.808 -0.0131 0.001 0.894 0.0118 

Upper Extremities

Female 57 0.0288 0.341 0.175 0.001 0.526 0.00833

 Male 48 0.00329 0.466 0.524 0.001 0.821 0.0101 

Arms

 Female 13 0.00223 0.201 0.748 0.01 0.731 0.00996

 Male 32 0.00111 0.616 0.561 0.001 0.892 0.0177 

Upper Arms

Male 6 8.70 0.741 -1.40 0.25 0.576 0.0387 

Forearms

 Male 6 0.326 0.858 -0.895 0.05 0.897 0.0207 

Hands

 Female 12 0.0131 0.412 0.0274 0.1 0.447 0.0172

 Male 32 0.0257 0.573 -0.218 0.001 0.575 0.0187 

b 

Lower Extremities 105 0.00286 0.458 0.696 0.001 0.802 0.00633 c

 Legs 45 0.00240 0.542 0.626 0.001 0.780 0.0130

 Thighs 45 0.00352 0.629 0.379 0.001 0.739 0.0149

 Lower legs 45 0.000276 0.416 0.973 0.001 0.727 0.0149 

Feet 45 0.000618 0.372 0.725 0.001 0.651 0.0147 

SA = a W H a a1 a2 

o 

W = Weight in kilograms; H = Height in centimeters; P = Level of significance; R = Coefficient of determination; 2 

SA = Surface Area; S.E. = Standard error; N = Number of observations 

One observation for a female whose body weight exceeded the 95 percentile was not used. b 

Although two separate regressions were marginally indicated by the F test, pooling was done for consistency with individual c 

components of lower extremities. 

Source: U.S. EPA, 1985. 
Table 6-2. Surface Area of Adult Males in Square Meters 

Percentile 

Body part 5 10 15 25 50 75 85 90 95 S.E.a 

Total 1.66 1.72 1.76 1.82 1.94 2.07 2.14 2.20 2.28 0.00374 

Head 0.119 0.121 0.123 0.124 0.130 0.135 0.138 0.140 0.143 0.0202 

Trunkb 0.591 0.622 0.643 0.674 0.739 0.807 0.851 0.883 0.935c 0.0118 

Upper extremities 0.321 0.332 0.340 0.350 0.372 0.395 0.408 0.418 0.432c 0.00101

 Arms 0.241 0.252 0.259 0.270 0.291 0.314c 0.328c 0.339c 0.354c 0.00387

 Forearms 0.106 0.111 0.115 0.121 0.131 0.144c 0.151c 0.157c 0.166c 0.0207

 Hands 0.085 0.088 0.090 0.093 0.099 0.105 0.109 0.112 0.117 0.0187 

Lower extremities 0.653 0.676 0.692 0.715 0.761 0.810 0.838 0.858 0.888c 0.00633

 Legs 0.539 0.561 0.576 0.597 0.640 0.686c 0.714c 0.734c 0.762c 0.0130

 Thighs 0.318 0.331 0.341 0.354 0.382 0.411c 0.429c 0.443c 0.463c 0.0149

 Lower legs 0.218 0.226 0.232 0.240 0.256 0.272 0.282 0.288 0.299 0.0149

 Feet 0.114 0.118 0.120 0.124 0.131 0.138 0.142 0.145 0.149 0.0147 

a Standard error for the 5-95 percentile of each body part. b Trunk includes neck. c Percentile estimates exceed the maximum measured values upon which the equations are based. 

Source: U.S. EPA, 1985. 
Table 6-3. Surface Area of Adult Females in Square Meters 

Percentile 

Body part 5 10 15 25 50 75 85 90 95 S.E.a 

Total 1.45 1.49 1.53 1.58 1.69c 1.82 1.91 1.98 2.09 0.00374 

Head 0.106 0.107 0.108 0.109 0.111 0.113 0.114 0.115 0.117 0.00678 

Trunkb 0.490 0.507 0.518 0.538 0.579 0.636 0.677 0.704 0.752 0.00567 

Upper extremities 0.260 0.265 0.269 0.274 0.287 0.301 0.311 0.318 0.329 0.00833

 Arms 0.210 0.214 0.217 0.221 0.230 0.238c 0.243c 0.247c 0.253c 0.00996

 Hands 0.0730 0.0746 0.0757 0.0777 0.0817 0.0868 0.0903 0.0927 0.0966c 0.0172 c c c 

Lower extremities 

Legs 

Thighs 

Lower legs 

Feet 

0.564 

0.460 

0.271 

0.186 

0.100 

0.582 

0.477 

0.281 

0.192 

0.103 

0.595 

0.488 

0.289 

0.197 

0.105 

0.615 

0.507 

0.300 

0.204 

0.108 

0.657 

0.546 

0.326 

0.218 

0.114 

0.704 

0.592 

0.357 

0.233 

0.121 

0.736 

0.623 

0.379 

0.243 

0.126 

0.757 

0.645 

0.394 

0.249 

0.129 

0.796 

0.683 

0.421 

0.261 

0.134 

c 

c 

0.00633

0.0130

0.0149

0.0149

0.0147 

a Standard error for the 5-95 percentile of each body part. b Trunk includes neck. c Percentile estimates exceed the maximum measured values upon which the equations are based. 

Source: U.S. EPA, 1985. 
2 Table 6-4. Surface Area by Body Part for Adults (m ) 

Men Women

Body part a N Mean (sd)b Min. - Max. N Mean (sd) Min. - Max. 

Head 32 0.118 (0.0160) 0.090 - 0.161 57 0.110 (0.00625) 0.0953 - 0.127

 Trunk 32 0.569 (0.104) 0.306 - 0.893 57 0.542 (0.0712) 0.437 - 0.867

 (Incl. Neck)

 Upper extremities 48 0.319 (0.0461) 0.169 - 0.429

Arms 32 0.228 (0.0374) 0.109 - 0.292

Upper arms 6 0.143 (0.0143) 0.122 - 0.156

 Forearms 6 0.114 (0.0127) 0.0945 - 0.136

 Hands 32 0.084 (0.0127) 0.0596 - 0.113

57 0.276 (0.0241) 0.215 - 0.333

13 0.210 (0.0129) 0.193 - 0.235

 - - - - - ­

- - - - ­

12 0.0746 (0.00510) 0.0639 0.0824

 Lower extremities 48 0.636 (0.0994) 0.283 - 0.868

Legs 32 0.505 (0.0885) 0.221 - 0.656

Thighs 32 0.198 (0.1470) 0.128 - 0.403

Lower legs 32 0.207 (0.0379) 0.093 - 0.296

Feet 32 0.112 (0.0177) 0.0611 - 0.156

57 0.626 (0.0675) 0.492 - 0.809

13 0.488 (0.0515) 0.423 - 0.585

13 0.258 (0.0333) 0.258 - 0.360

13 0.194 (0.0240) 0.165 - 0.229

13 0.0975 (0.00903) 0.0834 - 0.115

c e c e TOTAL 1.94 (0.00374)d 1.66 - 2.28 1.69 (0.00374)d 1.45 - 2.09 

a

 number of observations.

b

 standard deviation.

c

 median (see Table 6-2).

d

 standard error.

e

 percentiles (5th - 95th).

Source: Adapted from U.S. EPA, 1985.
Table 6-5. Percentage of Total Body Surface Area by Part for Adults 

Men Women 

a Body part N Mean (s.d.)b Min. - Max. N Mean (s.d.) Min. - Max. 

Head 32 7.8 (1.0) 6.1 - 10.6 57 7.1 (0.6) 5.6 - 8.1 

Trunk 32 35.9 (2.1) 30.5 - 41.4 57 34.8 (1.9) 32.8 - 41.7 

Upper extremities 48 18.8 (1.1) 16.4 - 21.0 

Arms 32 14.1 (0.9) 12.5 - 15.5 

Upper arms 6 7.4 (0.5) 6.7 - 8.1

 Forearms 6 5.9 (0.3) 5.4 - 6.3

 Hands 32 5.2 (0.5) 4.6 - 7.0 

57 17.9 (0.9) 15.6 - 19.9

13 14.0 (0.6) 12.4 - 14.8

 - - - - - ­

- - - - ­

12 5.1 (0.3) 4.4 5.4 

Lower extremities 48 37.5 (1.9) 33.3 - 41.2 

Legs 32 31.2 (1.6) 26.1 - 33.4 

Thighs 32 18.4 (1.2) 15.2 - 20.2 

Lower legs 32 12.8 (1.0) 11.0 - 15.8 

Feet 32 7.0 (0.5) 6.0 - 7.9 

57 40.3 (1.6) 36.0 - 43.2

13 32.4 (1.6) 29.8 - 35.3

13 19.5 (1.1) 18.0 - 21.7

13 12.8 (1.0) 11.4 - 14.9

13 6.5 (0.3) 6.0 - 7.0 

a Number of observations. b Standard deviation. 

Source: Adapted from U.S. EPA, 1985. 
Table 6-6. Total Body Surface Area of Male Children in Square Metersa 

Percentile 

Age (yr)b 

5 10 15 

2 < 3 0.527 0.544 0.552 

3 < 4 0.585 0.606 0.620 

4 < 5 0.633 0.658 0.673 

5 < 6 0.692 0.721 0.732 

6 < 7 0.757 0.788 0.809 

7 < 8 0.794 0.832 0.848 

8 < 9 0.836 0.897 0.914 

9 < 10 0.932 0.966 0.988 

10 < 11 1.01 1.04 1.06 

11 < 12 1.00 1.06 1.12 

12 < 13 1.11 1.13 1.20 

13 < 14 1.20 1.24 1.27 

14 < 15 1.33 1.39 1.45 

15 < 16 1.45 1.49 1.52 

16 < 17 1.55 1.59 1.61 

17 < 18 1.54 1.56 1.62 

25 50 75 85 90 95 

0.569 0.603 0.629 0.643 0.661 0.682 

0.636 0.664 0.700 0.719 0.729 0.764 

0.689 0.731 0.771 0,796 0.809 0.845 

0.746 0.793 0.840 0.864 0.895 0.918 

0.821 0.866 0.915 0.957 1.01 1.06 

0.877 0.936 0.993 1.01 1.06 1.11 

0.932 1.00 1.06 1.12 1.17 1.24 

1.00 1.07 1.13 1.16 1.25 1.29 

1.10 1.18 1.28 1.35 1.40 1.48 

1.16 1.23 1.40 1.47 1.53 1.60 

1.25 1.34 1.47 1.52 1.62 1.76 

1.30 1.47 1.62 1.67 1.75 1.81 

1.51 1.61 1.73 1.78 1.84 1.91 

1.60 1.70 1.79 1.84 1.90 2.02 

1.66 1.76 1.87 1.98 2.03 2.16 

1.69 1.80 1.91 1.96 2.03 2.09

 3 < 6 0.616 0.636 0.649 

6 < 9 0.787 0.814 0.834 

9 < 12 0.972 1.00 1.02 

12 < 15 1.19 1.24 1.27 

15 < 18 1.50 1.55 1.59 

0.673 0.728 0.785 0.817 0.842 0.876

0.866 0.931 1.01 1.05 1.09 1.14

1.07 1.16 1.28 1.36 1.42 1.52 

1.32 1.49 1.64 1.73 1.77 1.85 

1.65 1.75 1.86 1.94 2.01 2.11 

a Lack of height measurements for children <2 years in NHANES II precluded calculation of surface areas for this age group. b Estimated values calculated using NHANES II data. 

Source: U.S. EPA, 1985. 
Table 6-7. Total Body Surface Area of Female Children in Square Metersa 

Percentile 

Age (yr) 5 10 15 25 50 75 85 90 b 95 

2 < 3 0.516 0.532 0.544 0.557 0.579 0.610 0.623 0.637 0.653

 3 < 4 0.555 0.570 0.589 0.607 0.649 0.688 0.707 0.721 0.737

 4 < 5 0.627 0.639 0.649 0.666 0.706 0.758 0.777 0.794 0.820

 5 < 6 0.675 0.700 0.714 0.735 0.779 0.830 0.870 0.902 0.952

 6 < 7 0.723 0.748 0.770 0.791 0.843 0.914 0.961 0.989 1.03

 7 < 8 0.792 0.808 0.819 0.854 0.917 0.977 1.02 1.06 1.13

 8 < 9 0.863 0.888 0.913 0.932 1.00 1.05 1.08 1.11 1.18

 9 < 10 0.897 0.948 0.969 1.01 1.06 1.14 1.22 1.31 1.41 

10 < 11 0.981 1.01 1.05 1.10 1.17 1.29 1.34 1.37 1.43 

11 < 12 1.06 1.09 1.12 1.16 1.30 1.40 1.50 1.56 1.62 

12 < 13 1.13 1.19 1.24 1.27 1.40 1.51 1.62 1.64 1.70 

13 < 14 1.21 1.28 1.32 1.38 1.48 1.59 1.67 1.75 1.86 

14 < 15 1.31 1.34 1.39 1.45 1.55 1.66 1.74 1.76 1.88 

15 < 16 1.38 1.49 1.43 1.47 1.57 1.67 1.72 1.76 1.83 

16 < 17 1.40 1.46 1.48 1.53 1.60 1.69 1.79 1.84 1.91 

17 < 18 1.42 1.49 1.51 1.56 1.63 1.73 1.80 1.84 1.94

 3 < 6 0.585 0.610 0.630 0.654 0.711 0.770 0.808 0.831 0.879

 6 < 9 0.754 0.790 0.804 0.845 0.919 1.00 1.04 1.07 1.13

 9 < 12 0.957 0.990 1.03 1.06 1.16 1.31 1.38 1.43 1.56 

12 < 15 1.21 1.27 1.30 1.37 1.48 1.61 1.68 1.74 1.82 

15 < 18 1.40 1.44 1.47 1.51 1.60 1.70 1.76 1.82 1.92 

Lack of height measurements for children <2 years in NHANES II precluded calculation of surface areas for this age group. a 

Estimated values calculated using NHANES II data. b 

Source: U.S. EPA, 1985. 
Table 6-8. Percentage of Total Body Surface Area by Body Part for Children 

Percent of Total 

Age (yr) M:F 

N 

Head Trunk Arms Hands 

Mean Min-Max Mean Min-Max Mean Min-Max Mean Min-Max Mean

Legs Feet 

Min-Max Mean Min-Max 

< 1 2:0 18.2 18.2-18.3 35.7 34.8-36.6 13.7 12.4-15.1 5.3 5.21-5.39 20.6 18.2-22.9 6.54 6.49-6.59 

1 < 2 1:1 16.5 16.5-16.5 35.5 34.5-36.6 13.0 12.8-13.1 5.68 5.57-5.78 23.1 22.1-24.0 6.27 5.84-6.70 

2 < 3 1:0 14.2 38.5 11.8 5.30 23.2 7.07 

3 < 4 0:5 13.6 13.3-14.0 31.9 29.9-32.8 14.4 14.2-14.7 6.07 5.83-6.32 26.8 26.0-28.6 7.21 6.80-7.88 

4 < 5 1:3 13.8 12.1-15.3 31.5 30.5-32.4 14.0 13.0-15.5 5.70 5.15-6.62 27.8 26.0-29.3 7.29 6.91-8.10 

5 < 6 

6 < 7 1:0 13.1 35.1 13.1 4.71 27.1 6.90 

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 5.30 5.15-5.44 28.7 28.5-28.8 7.58 7.38-7.77 

10 < 11 

11 < 12 

12 < 13 1:0 8.74 34.7 13.7 5.39 30.5 7.03 

13 < 14 1:0 9.97 32.7 12.1 5.11 32.0 8.02 

14 < 15 

15 < 16 

16 < 17 1:0 7.96 32.7 13.1 5.68 33.6 6.93 

17 < 18 1:0 7.58 31.7 17.5 5.13 30.8 

N: Number of subjects, male to female ratios. 

Source: U.S. EPA 1985. 

7.28 
Table 6-9. Descriptive Statistics for Surface Area/Body Weight (SA/BW) Ratios (m /kg) 2 

Age (yrs.) Mean Min-Max SD SE 

Range a b 

Percentiles 

5 10 25 50 75 90 95 

0-2 0.0641 0.0421-0.1142 0.0114 7.84e-4 0.0470 0.0507 0.0563 0.0617 0.0719 0.0784 0.0846 

2.1 - 17.9 0.0423 0.0268-0.0670 0.0076 1.05e-3 0.0291 0.0328 0.0376 0.0422 0.0454 0.0501 0.0594 

$ 18 0.0284 0.0200-0.0351 0.0028 7.68e-6 0.0238 0.0244 0.0270 0.0286 0.0302 0.0316 0.0329 

All ages 0.0489 0.0200-0.1142 0.0187 9.33e-4 0.0253 0.0272 0.0299 0.0495 0.0631 0.0740 0.0788 

Standard deviation. a 

Standard error of the mean. b 

Source: Phillips et al., 1993. 
Table 6-10. Statistical Results for Total Body Surface Area Distributions (m )

2 

Men 

U.S. EPA Boyd DuBois and DuBois Costeff 

Mean 1.97 1.95 1.94 1.89 

Median 1.96 1.94 1.94 1.89 

Mode 1.96 1.91 1.90 1.90 

Standard Deviation 0.19 0.18 0.17 0.16 

Skewness 0.27 0.26 0.23 0.04 

Kurtosis 3.08 3.06 3.02 2.92 

Women 

U.S. EPA Boyd DuBois and DuBois Costeff 

Mean 1.73 1.71 1.69 1.71 

Median 1.69 1.68 1.67 1.68 

Mode 1.68 1.62 1.60 1.66 

Standard Deviation 0.21 0.20 0.18 0.21 

Skewness 0.92 0.88 0.77 0.69 

Kurtosis 4.30 4.21 4.01 3.52 

Source: Murray and Burmaster, 1992 
Table 6-11. Summary of Field Studies 

Activity Month (hrs) N 

Eventa 

b M F Age Conditions Clothing 

Indoor 

Tae Kwon Do Feb. 1.5 7 6 1 8-42 Carpeted floor All in longsleeve-long pants martial 

arts uniform, sleeves rolled back, 

barefoot 

Greenhouse Workers Mar. 5.25 2 1 1 37-39 Plant watering,spraying, soil Long pants, elbow length short 

blending, sterilization sleeve shirt, no gloves 

Indoor Kids No. 1 Jan. 2 4 3 1 6-13 Playing on carpeted floor 3 of 4 short pants, 2 of 4 short 

sleeves, socks, no shoes 

Indoor Kids No. 2 Feb. 2 6 4 2 3-13 Playing on carpeted floor 5of 6 long pants, 5 of 6 long 

sleeves, socks, no shoes 

Indoor Totals 19 14 5 

Outdoor 

Daycare Kids No. 1a Aug. 3.5 6 5 1 1-6.5 Indoors: linoleum surface; 4 of 6 in long pants, 4 of 6 short 

outdoors: grass, bare earth, sleeves, shoes 

barked area 

Daycare Kids No. 1b Aug. 4 6 5 1 1-6.5 Indoors: linoleum surface; 4 of 6 in long pants, 4 of 6 short 

outdoors: grass, bare earth, sleeves, no shoes 

barked area 

Daycare Kids No.2c Sept. 8 5 4 1 1-4 Indoors, low napped carpeting, 4 of 5 long pants, 3of 5 long 

linoleum surfaces sleeves, all barefoot for part of the 

day 

Daycare Kids No. 3 Nov. 8 4 3 1 1-4.5 Indoors: linoleum surface, All long pants, 3 of 4 long sleeves, 

outside: grass, bare earth, socks and shoes 

barked area 

Soccer No. 1 Nov. 0.67 8 8 0 13-15 Half grass-half bare earth 6 of 8 long sleeves, 4 of 8 long 

pants, 3 of 4 short pants and shin 

guards 

Soccer No. 2 Mar. 1.5 8 0 8 24-34 All-weather field (sand-ground All in short sleeve shirts, shorts, 

tires) knee socks, shin guards 

Soccer No. 3 Nov. 1.5 7 0 7 24-34 All-weather field (sand-ground All in short sleeve shirts, shorts, 

tires) knee socks, shin guards 

Groundskeepers No. 1 Mar. 1.5 2 1 1 29-52 Campus grounds, urban All in long pants, intermittent use of 

horticulture center, arboretum gloves 

Groundskeepers No. 2 Mar. 4.25 5 3 2 22-37 Campus grounds,urban All in long pants, intermittent use of 

horticulture center, arboretum gloves 

Groundskeepers No. 3 Mar. 8 7 5 2 30-62 Campus grounds,urban All in long pants, intermittent use of 

horticulture center, arboretum gloves 

Groundskeepers No. 4 Aug. 4.25 7 4 3 22-38 Campus grounds,urban 5 of 7 in short sleeve shirts, 

horticulture center, arboretum intermittent use of gloves 

Groundskeepers No. 5 Aug. 8 8 6 2 19-64 Campus grounds,urban 5 of 8 in short sleeve shirts, 

horticulture center, arboretum intermittent use of gloves 

Landscape/Rockery June 9 4 3 1 27-43 Digging (manual All long pants, 2 long sleeves, all 

andmechanical), rock moving socks and boots 

IrrigationInstallers Oct. 3 6 6 0 23-41 Landscaping,surface restoration All in long pants, 3 of 6 short sleeve 

or sleeveless shirts 

Gardeners No. 1 Aug. 4 8 1 7 16-35 Weeding, pruning,digging a 6 of 8 long pants, 7 of 8 short 

trench sleeves, 1 sleeveless, socks, 

shoes, intermittent use of gloves 
Table 6-11. Summary of Field Studies (continued) 

Activity Month (hrs) N M F Age Conditions Clothing 

Eventa 

b 

Gardeners No. 2 Aug. 4 7 2 5 26-52 Weeding, pruning, digging a 3 of 7 long pants, 5of 7 short 

trench, picking fruit, cleaning sleeves, 1 sleeveless, socks, 

shoes, no gloves 

Rugby No. 1 Mar. 1.75 8 8 0 20-22 Mixed grass-barewet field All in short sleeve shirts, shorts, 

variable sock lengths 

Rugby No. 2 July 2 8 8 0 23-33 Grass field (80% oftime) and all- All in shorts, 7 of 8 in short sleeve 

weather field (mix of gravel, shirts, 6 of 8 in low socks 

sand, and clay) (20% oftime) 

Rugby No. 3 Sept. 2.75 7 7 0 24-30 Compacted mixedgrass and All short pants, 7 of 8 short or rolled 

bare earth field up sleeves, socks, shoes 

Archeologists July 11.5 7 3 4 16-35 Digging withtrowel, screening 6 of 7 short pants,all short sleeves, 

dirt, sorting 3 no shoes or socks, 2 sandals 

Construction Workers Sept. 8 8 8 0 21-30 Mixed bare earth and concrete 5 of 8 pants,7 of 8 short sleeves, all 

surfaces, dust and debris socks and shoes 

Utility Workers No.1 July 9.5 5 5 0 24-45 Cleaning, fixing mains, All long pants,short sleeves, socks, 

excavation (backhoe and boots, gloves sometimes 

shovel) 

Utility Workers No.2 Aug. 9.5 6 6 0 23-44 Cleaning, fixing mains, All long pants, 5 of 6 short sleeves, 

excavation (backhoe and socks, boots, gloves sometimes 

shovel) 

Equip. Operators No.1 Aug. 8 4 4 0 21-54 Earth scraping withheavy All long pants, 3 of 4 short sleeves, 

machinery, dusty conditions socks, boots, 2 of 4 gloves 

Equip. Operators No.2 Aug. 8 4 4 0 21-54 Earth scraping withheavy All long pants, 3 of 4 short sleeves, 

machinery, dusty conditions socks, boots, 1 gloves 

Farmers No. 1 May 2 4 2 2 39-44 Manual weeding,mechanical All in long pants, heavy shoes, short 

cultivation sleeve shirts, no gloves 

Farmers No. 2 July 2 6 4 2 18-43 Manual weeding,mechanical 2 of 6 short, 4 of 6long pants, 1 of 6 

cultivation long sleeve shirt, no gloves 

Reed Gatherers Aug. 2 4 0 4 42-67 Tidal flats 2 of 4 shortsleeve shirts/knee 

length pants, all wore shoes 

Kids-in-mud No. 1 Sept. 0.17 6 5 1 9-14 Lake shoreline All in short sleeve T-shirts, shorts, 

barefoot 

Kids-in-mud No. 2 Sept. 0.33 6 5 1 9-14 Lake shoreline All in short sleeveT-shirts, shorts, 

barefoot 

Outdoor Totals 181 125 56 

a Event duration 

b Number of subject 

c Activities were confined to the house 

Sources: Kissel et al., 1996b; Holmes et al., 1996 (submitted for publication). 
-- -- -- --

-- -- -- --

--

-- --

Table 6-12. Geometric Mean and Geometric Standard Deviations of 

Soil Adherence by Activity and Body Region 

Post-activity Dermal Soil Loadings (mg/cm2) 

Activity Na 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 

GreenhouseWorkers 2 0.043 0.0064 0.0015 0.0050 

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 0.026 0.030 0.079 

1.9 1.9 1.7 2.4 

Daycare Kids No. 1b 6 0.15 0.031 0.023 0.13 

2.1 1.8 1.2 1.4 

Daycare Kids No. 2 5 0.073 0.023 0.011 0.044 

1.6 1.4 1.4 1.3 

Daycare Kids No. 3 4 0.036 0.012 0.014 0.0053 

1.3 1.2 3.0 5.1 

Outdoor 

Soccer No. 1 8 0.11 0.011 0.031 0.012 

1.8 2.0 3.8 1.5 

Soccer No. 2 8 0.035 0.0043 0.014 0.016 

3.9 2.2 5.3 1.5 

Soccer No. 3 7 0.019 0.0029 0.0081 0.012 

1.5 2.2 1.6 1.6 

Groundskeepers No. 1 2 0.15 0.005 0.0021 0.018 

Groundskeepers No. 2 5 0.098 0.0021 0.0010 0.010 

2.1 2.6 1.5 2.0 

Groundskeepers No. 3 7 0.030 0.0022 0.0009 0.0044 0.0040 

2.3 1.9 1.8 2.6 

Groundskeepers No. 4 7 0.045 0.014 0.0008 0.0026 0.018 

1.9 1.8 1.9 1.6 

Groundskeepers No. 5 8 0.032 0.022 0.0010 0.0039 

1.7 2.8 1.4 2.1 

Landscape/Rockery 4 0.072 0.030 0.0057 

2.1 2.1 1.9 

Irrigation Installers 6 0.19 0.018 0.0054 0.0063 

1.6 3.2 1.8 1.3 

Gardeners No. 1 8 0.20 0.050 0.072 0.058 0.17 

1.9 2.1 1.6 
--

Table 6-12. Geometric Mean and Geometric Standard Deviations of 

Soil Adherence by Activity and Body Region (continued) 

Post-activity Dermal Soil Loadings (mg/cm2) 

Activity Na Hands Arms Legs Faces Feet 

Gardeners No. 2 7 0.18 0.054 0.022 0.047 0.26 

3.4 2.9 2.0 1.6 

Rugby No. 1 8 0.40 0.27 0.36 0.059 

1.7 1.6 1.7 2.7 

Rugby No. 2 8 0.14 0.11 0.15 0.046 

1.4 1.6 1.6 1.4 

Rugby No. 3 7 0.049 0.031 0.057 0.020 

1.7 1.3 1.2 1.5 

Archeologists 7 0.14 0.041 0.028 0.050 0.24 

1.3 1.9 4.1 1.8 1.4 

Construction Workers 8 0.24 0.098 0.066 0.029 

1.5 1.5 1.4 1.6 

Utility Workers No.1 5 0.32 0.20 0.10 

1.7 2.7 1.5 

Utility Workers No. 2 6 0.27 0.30 0.10 

2.1 1.8 1.5 

Equip. Operators No. 1 4 0.26 0.089 0.10 

2.5 1.6 1.4 

Equip. Operators No. 2 4 0.32 0.27 0.23 

1.6 1.4 1.7 

Farmers No. 1 4 0.41 0.059 0.0058 0.018 

1.6 3.2 2.7 1.4 

Farmers No. 2 6 0.47 0.13 0.037 0.041 

1.4 2.2 3.9 3.0 

Reed Gatherers 4 0.66 0.036 0.16 0.63 

1.8 2.1 9.2 7.1 

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

 Number of subjects. a 

Sources: Kissel et al., 1996b; Holmes et al., 1996 (submitted for publication). 
Table 6-13. Summary of Surface Area Studies 

Surface Area 

Study 

No. of Individuals 

Type of Surface Area 

Measurement 

Recommended 

Formulae Used 

Population 

Surveyed Comments 

KEY STUDIES 

Phillips et al. (1993) Based on data from 

U.S. EPA (1985): 401 

individuals 

NA calculated surface area to 

body weight ratios 

Children 

Adults 

Developed distributions of 

SA/BW and calculated 

summary statistics for 3 age 

groups and the combined data 

set 

U.S. EPA (1985) 401 individuals Based on Gehan and 

George (1970) 

SA=0.0239*W *H 0.517 0.417 Children 

Adults 

Provides statistical distribution 

data for total SA and SA of 

body parts 

RELEVANT STUDIES 

AICH (1994) Based on data from 

U.S. EPA (1989); 

Brainard et al. (1991); 

Brorby and Finley 

(1993) 

@Risk simulation 

software 

Various Adults 

Children 

Distribution data for: adult 

men and women and both 

sexes combined; total skin 

area, children 8-18 years; 

exposed skin area (hands and 

forearms); head; upper body 

Murray and Burmaster 

(1992) 

Based on data from 

U.S. EPA (1985): N = 

401; 

Dubois and Dubois 

(1976): N = 9; 

Boyd (1935): N = 231; 

Costeff (1966): N = 

220 

Calculated based on 

regression equation using 

the data of U.S. EPA 

(1985) 

Various Children 

Adults 

Analysis of and comparision 

of four models developed by 

Dubois & Dubois (1916), 

Boyd (1935), U.S. EPA 

(1985), and Costeff (1966). 

Presents frequency 

distribtions 
Table 6-14. Summary of Recommended Values for Skin Surface Area 

Surface Area Central Tendency Upper Percentile Multiple Percentiles 

Adults 

Whole body and body see Tables 6-4 and 6-5 see Tables 6-2 and 6-3 see Tables 6-2 and 6-3 

parts 

Bathing/swimming 20,000 cm2 23,000 cm2 --­

Outdoor soil contact 5,000 cm2 5,800 cm2 --­

Children 

Whole body --- see Tables 6-6 and 6-7 see Tables 6-6 and 6-7 

Body parts --- see Table 6-8 see Table 6-8 
Table 6-15. Confidence in Body Surface Area Measurement Recommendations 

Considerations Rationale Rating 

Study Elements

 • Level of Peer Review Studies were from peer reviewed journal articles.

EPA report was peer reviewed before distribution. High 

• Accessibility The journals used have wide circulation. 

EPA report available from National Technical

Information Service.

High 

• Reproducibility Experimental methods are well-described. High

 • Focus on factor of interest Experiments measured skin area directly. High

 • Data pertinent to U.S. Experiments conducted in the U.S. High

 • Primary data Re-analysis of primary data in more detail by two

different investigators .

Low 

• Currency Neither rapidly changing nor controversial area;

estimates made in 1935 deemed to be accurate and 

Low 

subsequently used by others.

 • Adequacy of data collection Not relevant to exposure factor; parameter not time period dependent.NA

 • Validity of approach Approach used by other investigators; not challenged

in other studies. High 

• Representativeness of the Not statistically representative of U.S. population. populationMedium

 • Characterization of variability Individual variability due to age, race, or gender not

studied.

Low 

• Lack of bias in study design Objective subject selection and measurement methods

used; results reproduced by others with different

methods.

High 

• Measurement error Measurement variations are low; adequately described

by normal statistics. 

Low/Medium 

Other Elements

 • Number of studies 1 experiment; two independent re-analyses of this data Medium 

set.

 • Agreement among researchers Consistent results obtained with different analyses; but

from a single set of measurements. 

Medium 

Overall Rating This factor can be directly measured. It is not subject

to dispute. Influence of age, race, or gender have not

been detailed adequately in these studies. 

High 
Table 6-16. Recommendations for Adult Body Surface Area 

Water Contact 

50th 95th 

Bathing and Swimming 20,000 cm2 

Soil Contact 

23,000 cm2 

Outdoor Activities 

50th 

5,000 cm2 

95th 

5,800 cm2 

Source: U.S. EPA, 1992. 
Table 6-17. Summary of Soil Adherence Studies 

Study Fraction Adherence Surveyed Comments 

Size Soil Population 

(Fm) (mg/cm )

2 

KEY STUDIES 

Kissel et al., 1996a <150, 150­ Various 28 adults Data presented for soil loadings by 

200, >250 24 children body part. See Table 6-11. 

Kissell et al., 1996b -­ Various 12 children Data presented by activity and body 

89 adults part. 

RELEVANT STUDIES 

Driver et al., 1989 <150 1.40 Adults Used 5 soil types and 2-3 soil 

<250 0.95 Adults horizons (top soils and subsoils); 

unsieved 0.58 Adults placed soil over entire hand of test 

subject, excess removed by shaking 

the hands. 

Lepow et al., 1975 -- 0.5 10 children Dirt from hands collected during 

play. Represents only fraction of 

total present, some dirt may be 

trapped in skin folds. 

Que Hee et al., 1985 -- 1.5 1 adult Assumed exposed area = 20 cm . 

2 

Test subject was 14 years old. 

Roels et al., 1980 -- 0.9-1.5 661 children Subjects lived near smelter in 

Brussels, Belgium. Mean amount 

adhering to soil was 0.159 g. 

Sedman, 1989 -- 0.9; 0.5 Children Used estimate of Roels et al. (1980) 

and average surface of hand of an 

11 year old; used estimates of 

Lepow et al. (1975), Roels et al. 

(1980), and Que Hee et al. (1985) 

to develop mean of 0.5 mg/cm . 

2 

Yang et al., 1989 <150 9 Rats Rat skin "monolayer" (i.e., minimal 

amount of soil covering the skin); in 

vitro and in vivo experiments. 
Table 6-18. Confidence in Soil Adherence to Skin Recommendations 

Considerations Rationale Rating 

Study Elements

 • Level of Peer Review Studies were from peer reviewed journal articles. High

 • Accessibility Articles were published in widely circulated journals. High

 • Reproducibility Reports clearly describe experimental method. High

 • Focus on factor of interest The goal of the studies was to determine soil High 

adherence to skin.

 • Data pertinent to U.S. Experiments were conducted in the U.S. High

 • Primary data Experiments were directly measure soil adherence to High 

skin; exposure and dose of chemicals in soil were 

measured indirectly or estimated from soil contact.

 • Currency New studies were presented. High

 • Adequacy of data collection Seasonal factors may be important, but have not been Medium

 period studied adequately.

 • Validity of approach Skin rinsing technique is a widely employed procedure. High

 • Representativeness of the Studies were limited to the State of Washington and Low

 population may not be representative of other locales.

 • Characterization of variability Variability in soil adherence is affected by many factors Low 

including soil properties, activity and individual behavior 

patterns.

 • Lack of bias in study design The studies attempted to measure soil adherence in High 

selected activities and conditions to identify important 

activities and groups.

 • Measurement error The experimental error is low and well controlled, but Low/High 

application of results to other similar activities may be 

subject to variation. 

Other Elements

 • Number of studies The experiments were controlled as they were Medium 

conducted by a few laboratories; activity patterns were 

studied by only one laboratory.

 • Agreement among researchers Results from key study were consistent with earlier Medium 

estimates from relevant studies and assumptions, but 

are limited to hand data. 

Overall Rating Data are limited, therefore it is difficult to extrapolate Low 

from experiments and field observations to general 

conditions . 
Biologically 

Effective 

Dose 

Chemical 

Exposure 

Internal 

Dose Potential Applied 

Dose Dose 

Organ 

Metabolism 

Effect 

Skin 

Uptake 

Figure 6-1. Schematic of Dose and Exposure: Dermal Route 

Source: U.S. EPA, 1992a. 
Figure 6-2. SA/BW Distributions for Infants, Adults, and All Ages Combined 

Source: Phillips et al., 1993. 
Figure 6-3. Frequency Distributions for the Surface Area of Men and Women 

Source: Murray and Burmaster, 1992. 
Table 7-1. Smoothed Percentiles of Weight (in kg) by Sex and Age: 

Statistics from NCHS and Data from Fels Research Institute, Birth to 36 Months 

Smoothed Percentile a 

5th 10th 25th 50th 75th 90th 95th 

Sex and Age Weight in Kilograms 

Male 

Birth 2.54 2.78 3.00 3.27 3.64 3.82 4.15 

1 Month 3.16 3.43 3.82 4.29 4.75 5.14 5.38 

3 Months 4.43 4.78 5.32 5.98 6.56 7.14 7.37 

6 Months 6.20 6.61 7.20 7.85 8.49 9.10 9.46 

9 Months 7.52 7.95 8.56 9.18 9.88 10.49 10.93 

12 Months 8.43 8.84 9.49 10.15 10.91 11.54 11.99 

18 Months 9.59 9.92 10.67 11.47 12.31 13.05 13.44 

24 Months 10.54 10.85 11.65 12.59 13.44 14.29 14.70 

30 Months 11.44 11.80 12.63 13.67 14.51 15.47 15.97 

36 Months 12.26 12.69 13.58 14.69 15.59 16.66 17.28 

Female 

Birth 2.36 2.58 2.93 3.23 3.52 3.64 3.81 

1 Month 2.97 3.22 3.59 3.98 4.36 4.65 4.92 

3 Months 4.18 4.47 4.88 5.40 5.90 6.39 6.74 

6 Months 5.79 6.12 6.60 7.21 7.83 8.38 8.73 

9 Months 7.00 7.34 7.89 8.56 9.24 9.83 10.17 

12 Months 7.84 8.19 8.81 9.53 10.23 10.87 11.24 

18 Months 8.92 9.30 10.04 10.82 11.55 12.30 12.76 

24 Months 9.87 10.26 11.10 11.90 12.74 13.57 14.08 

30 Months 10.78 11.21 12.11 12.93 13.93 14.81 15.35 

36 Months 11.60 12.07 12.99 13.93 15.03 15.97 16.54

 Smoothed by cubic-spline approximation. a 

Source: Hamill et al., 1979. 
a Table 7-2. Body Weights of Adults (kilograms) 

Men and Women 

Men Women 

Age (years) Mean Std. Dev. Mean (kg) Std. Dev. Mean (kg) 

(kg) 

18 < 25 73.8 12.7 60.6 11.9 67.2 

25 < 35 78.7 13.7 64.2 15.0 71.5 

35 < 45 80.9 13.4 67.1 15.2 74.0 

45 < 55 80.9 13.6 68.0 15.3 74.5 

55 < 65 78.8 12.8 67.9 14.7 73.4 

65 < 75 74.8 12.8 66.6 13.8 70.7 

18 < 75 78.1 13.5 65.4 14.6 71.8 

Note: 1 kg = 2.2046 pounds.

a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. 

Source: Adapted from National Center for Health Statistics (NCHS), 1987. 
a Table 7-3. Body Weights of Children (kilograms) 

Boys Girls Boys and Girls 

Age Mean Std. Dev. Mean (kg) Std. Dev. (kg) 

Mean 

(kg) 

6-11 months 9.4 1.3 8.8 1.2 9.1 

1 year 11.8 1.9 10.8 1.4 11.3 

2 years 13.6 1.7 13.0 1.5 13.3 

3 years 15.7 2.0 14.9 2.1 15.3 

4 years 17.8 2.5 17.0 2.4 17.4 

5 years 19.8 3.0 19.6 3.3 19.7 

6 years 23.0 4.0 22.1 4.0 22.6 

7 years 25.1 3.9 24.7 5.0 24.9 

8 years 28.2 6.2 27.9 5.7 28.1 

9 years 31.1 6.3 31.9 8.4 31.5 

10 years 36.4 7.7 36.1 8.0 36.3 

11 years 40.3 10.1 41.8 10.9 41.1 

12 years 44.2 10.1 46.4 10.1 45.3 

13 years 49.9 12.3 50.9 11.8 50.4 

14 years 57.1 11.0 54.8 11.1 56.0 

15 years 61.0 11.0 55.1 9.8 58.1 

16 years 67.1 12.4 58.l 10.1 62.6 

17 years 66.7 11.5 59.6 11.4 63.2 

18 years 71.1 12.7 59.0 11.1 65.1 

19 years 71.7 11.6 60.2 11.0 66.0 

Note: 1 kg = 2.2046 pounds.

a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. 

Source: Adapted from National Center for Health Statistics (NCHS), 1987. 
Table 7-4. Weight in Kilograms for Males 18-74 Years of Age--Number Examined, Mean, Standard 

Deviation, and Selected Percentiles, by Race and Age: United States, 1976-1980a 

Percentile 

Number of 

Persons Mean Standard 

Race and Age Examined (kg) Deviation 5th 10th 15th 25th 50th 75th 85th 90th 95th 

All racesb 

18-74 years ..... 5,916 78.1 13.5 58.6 62.3 64.9 68.7 76.9 85.6 91.3 95.7 102.7 

18-24 years ....... 988 73.8 12.7 56.8 60.4 61.9 64.8 72.0 80.3 85.1 90.4 99.5 

25-34 years ..... 1,067 78.7 13.7 59.5 62.9 65.4 69.3 77.5 85.6 91.1 95.1 102.7 

35-44 years ....... 745 80.9 13.4 59.7 65.1 67.7 72.1 79.9 88.1 94.8 98.8 104.3 

45-54 years ....... 690 80.9 13.6 50.8 65.2 67.2 71.7 79.0 89.4 94.5 99.5 105.3 

55-64 years ..... 1,227 78.8 12.8 59.9 63.8 66.4 70.2 77.7 85.6 90.5 94.7 102.3 

65-74 years ..... 1,199 74.8 12.8 54.4 58.5 61.2 66.1 74.2 82.7 87.9 91.2 96.6 

White 

18-74 years ..... 5,148 78.5 13.1 59.3 62.8 65.5 69.4 77.3 85.6 91.4 95.5 102.3 

18-24 years ....... 846 74.2 12.8 56.8 60.5 62.0 65.0 72.4 80.6 85.5 91.0 100.0 

25-34 years ....... 901 79.0 13.1 59.9 63.7 65.9 69.8 78.0 85.6 91.3 95.3 102.7 

35-44 years ....... 653 81.4 12.8 62.3 66.6 68.8 72.9 80.1 88.2 94.6 98.7 104.1 

45-54 years ....... 617 81.0 13.4 62.0 66.1 67.3 71.9 79.0 89.4 94.2 99.0 104.5 

55-64 years ..... 1,086 78.9 12.4 60.5 64.5 66.6 70.6 78.2 85.6 90.4 94.5 101.7 

65-74 years ..... 1,045 75.4 12.4 55.5 59.5 62.5 67.0 74.7 83.0 87.9 91.2 96.0 

Black 

18-74 years ....... 649 77.9 15.2 58.0 61.1 63.6 67.2 75.3 85.4 92.9 98.3 105.4 

18-24 years ....... 121 72.2 12.0 58.3 60.9 62.3 64.9 70.8 77.1 81.8 83.7 93.6 

25-34 years ....... 139 78.2 16.3 58.7 63.4 64.9 68.4 75.3 84.4 90.6 92.2 106.3 

35-44 years ........ 70 82.5 15.4 *c 61.7 65.2 69.7 83.1 94.8 100.4 104.2 * 

45-54 years ........ 62 82.4 14.5 * 64.7 67.0 73.2 81.8 93.0 100.0 102.5 * 

55-64 years ....... 129 78.6 14.7 56.8 61.4 64.3 68.0 77.0 86.5 93.8 98.6 104.7 

65-74 years ....... 128 73.3 15.3 52.5 56.7 58.0 61.0 71.2 81.1 90.8 97.3 105.1 

Note: 1 kg = 2.2046 pounds.

a

 Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.

b

 Includes all other races not shown as separate categories.

c Data not available.

Source: National Center for Health Statistics, 1987. 
Table 7-5. Weight in Kilograms for Females 18-74 Years of Age--Number Examined, Mean, Standard 

Deviation, and Selected Percentiles, by Race and Age: United States, 1976-1980a 

Percentile 

Number of 

Persons Mean Standard 

Race and Age Examined (kg) Deviation 5th 10th 15th 25th 50th 75th 85th 90th 95th 

All racesb 

18-74 years .... 6,588 65.4 14.6 47.7 50.3 52.2 55.4 62.4 72.1 79.2 84.4 93.1 

18-24 years .... 1,066 60.6 11.9 46.6 49.1 50.6 53.2 58.0 65.0 70.4 75.3 82.9 

25-34 years .... 1,170 64.2 15.0 47.4 49.6 51.4 54.3 60.9 69.6 78.4 84.1 93.5 

35-44 years ...... 844 67.1 15.2 49.2 52.0 53.3 56.9 63.4 73.9 81.7 87.5 98.9 

45-54 years ...... 763 68.0 15.3 48.5 51.3 53.3 57.3 65.5 75.7 82.1 87.6 96.0 

55-64 years .... 1,329 67.9 14.7 48.6 51.3 54.1 57.3 65.2 75.3 82.3 87.5 95.1 

65-74 years .... 1,416 66.6 13.8 47.1 50.8 53.2 57.4 64.8 73.8 79.8 84.4 91.3 

White 

18-74 years .... 5,686 64.8 14.1 47.7 50.3 52.2 55.2 62.1 71.1 77.9 83.3 91.5 

18-24 years ...... 892 60.4 11.6 47.3 49.5 50.8 53.3 57.9 64.8 69.7 74.3 82.4 

25-34 years .... 1,000 63.6 14.5 47.3 49.5 51.3 54.0 60.6 68.9 76.3 81.5 89.7 

35-44 years ...... 726 66.1 14.5 49.3 51.8 52.9 56.3 62.4 71.9 79.7 85.8 94.9 

45-54 years ...... 647 67.3 14.4 48.6 51.3 53.4 57.0 65.0 74.8 81.1 85.6 94.5 

55-64 years .... 1,176 67.2 14.4 48.5 50.7 53.7 57.1 64.7 74.5 81.8 86.2 92.8 

65-74 years .... 1,245 66.2 13.7 47.2 50.7 52.9 57.2 64.3 72.9 79.2 84.3 91.2 

Black 

18-74 years ...... 782 71.2 17.3 48.8 51.6 55.1 59.1 67.8 80.6 87.4 94.9 105.1 

18-24 years ...... 147 63.1 13.9 46.2 49.0 50.6 53.8 60.4 70.0 75.8 79.1 89.3 

25-34 years ...... 145 69.3 16.7 48.3 50.8 53.1 57.8 65.3 80.2 87.1 91.5 102.7 

35-44 years ...... 103 75.3 18.4 50.7 55.2 57.2 63.0 70.2 85.2 95.3 103.5 113.1 

45-54 years ...... 100 77.7 18.8 55.1 60.3 60.8 64.5 74.3 83.6 94.5 98.2 117.5 

55-64 years ...... 135 75.8 16.4 54.2 55.2 57.6 65.4 74.6 83.4 91.9 95.5 108.5 

65-74 years ...... 152 72.4 13.6 52.9 56.4 60.3 64.0 70.0 82.2 84.4 86.5 98.1 

Note: 1 kg = 2.2046 pounds.

a

 Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.

b Includes all other races not shown as separate categories.

Source: National Center for Health Statistics, 1987. 
Table 7-6. Weight in Kilograms for Males 6 Months-19 Years of Age--Number Examined, Mean, Standard 

Deviation, and Selected Percentiles, by Sex and Age: United States, 1976-1980a 

Percentile 

Number of 

Persons Mean 

Age Examined (kg) 

Standard 

Deviation 5th 10th 15th 25th 50th 75th 85th 90th 95th 

6-11 months ...... 179 9.4 

1 years .......... 370 11.8 

2 years .......... 375 13.6 

3 years .......... 418 15.7 

4 years .......... 404 17.8 

5 years .......... 397 19.8 

6 years .......... 133 23.0 

7 years .......... 148 25.1 

8 years .......... 147 28.2 

9 years .......... 145 31.1 

10 years ......... 157 36.4 

11 years ......... 155 40.3 

12 years ......... 145 44.2 

13 years ......... 173 49.9 

14 years ......... 186 57.1 

15 years ......... 184 61.0 

16 years ......... 178 67.1 

17 years ......... 173 66.7 

18 years ......... 164 71.1 

19 years ......... 148 71.7 

1.3 7.5 

1.9 9.6 

1.7 11.1 

2.0 12.9 

2.5 14.1 

3.0 16.0 

4.0 18.6 

3.9 19.7 

6.2 20.4 

6.3 24.0 

7.7 27.2 

10.1 26.8 

10.1 30.7 

12.3 35.4 

11.0 41.0 

11.0 46.2 

12.4 51.4 

11.5 50.7 

12.7 54.1 

11.6 55.9 

7.6 

10.0 

11.6 

13.5 

15.0 

16.8 

19.2 

20.8 

22.7 

25.6 

28.2 

28.8 

32.5 

37.0 

44.5 

49.1 

54.3 

53.4 

56.6 

57.9 

8.2 

10.3 

11.8 

13.9 

15.3 

17.1 

19.8 

21.2 

23.6 

26.0 

29.6 

31.8 

35.4 

38.3 

46.4 

50.6 

56.1 

54.8 

60.3 

60.5 

8.6 

10.8 

12.6 

14.4 

16.0 

17.7 

20.3 

22.2 

24.6 

27.1 

31.4 

33.5 

37.8 

40.1 

49.8 

54.2 

57.6 

58.8 

61.9 

63.8 

9.4 

11.7 

13.5 

15.4 

17.6 

19.4 

22.0 

24.8 

27.5 

30.2 

34.8 

37.3 

42.5 

48.4 

56.4 

60.1 

64.4 

65.8 

70.4 

69.5 

10.1 

12.6 

14.5 

16.8 

19.0 

21.3 

24.1 

26.9 

29.9 

33.0 

39.2 

46.4 

48.8 

56.3 

63.3 

64.9 

73.6 

72.0 

76.6 

77.9 

10.7 10.9 11.4 

13.1 13.6 14.4 

15.2 15.8 16.5 

17.4 17.9 19.1 

19.9 20.9 22.2 

22.9 23.7 25.4 

26.4 28.3 30.1 

28.2 29.6 33.9 

33.0 35.5 39.1 

35.4 38.6 43.1 

43.5 46.3 53.4 

52.0 57.0 61.0 

52.6 58.9 67.5 

59.8 64.2 69.9 

66.1 68.9 77.0 

68.7 72.8 81.3 

78.1 82.2 91.2 

76.8 82.3 88.9 

80.0 83.5 95.3 

84.3 86.8 92.1 

Note: 1 kg = 2.2046 pounds.

a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. 

Source: National Center for Health Statistics, 1987. 
Table 7-7. Weight in Kilograms for Females 6 Months-19 Years of Age--Number Examined, Mean, Standard 

Deviation, and Selected Percentiles, by Sex and Age: United States, 1976-1980a 

Percentile 

Number of 

Persons Mean Standard 

Age Examined (kg) Deviation 5th 10th 15th 25th 50th 75th 85th 90th 95th 

6-11 months ...... 177 8.8 1.2 6.6 7.3 7.5 7.9 8.9 9.4 10.1 10.4 10.9 

1 years .......... 336 10.8 1.4 8.8 9.1 9.4 9.9 10.7 11.7 12.4 12.7 13.4 

2 years .......... 336 13.0 1.5 10.8 11.2 11.6 12.0 12.7 13.8 14.5 14.9 15.9 

3 years .......... 366 14.9 2.1 11.7 12.3 12.9 13.4 14.7 16.1 17.0 17.4 18.4 

4 years .......... 396 17.0 2.4 13.7 14.3 14.5 15.2 16.7 18.4 19.3 20.2 21.1 

5 years .......... 364 19.6 3.3 15.3 16.1 16.7 17.2 19.0 21.2 22.8 24.7 26.6 

6 years .......... 135 22.1 4.0 17.0 17.8 18.6 19.3 21.3 23.8 26.6 28.9 29.6 

7 years .......... 157 24.7 5.0 19.2 19.5 19.8 21.4 23.8 27.1 28.7 30.3 34.0 

8 years .......... 123 27.9 5.7 21.4 22.3 23.3 24.4 27.5 30.2 31.3 33.2 36.5 

9 years .......... 149 31.9 8.4 22.9 25.0 25.8 27.0 29.7 33.6 39.3 43.3 48.4 

10 years ......... 136 36.1 8.0 25.7 27.5 29.0 31.0 34.5 39.5 44.2 45.8 49.6 

11 years ......... 140 41.8 10.9 29.8 30.3 31.3 33.9 40.3 45.8 51.0 56.6 60.0 

12 years ......... 147 46.4 10.1 32.3 35.0 36.7 39.1 45.4 52.6 58.0 60.5 64.3 

13 years ......... 162 50.9 11.8 35.4 39.0 40.3 44.1 49.0 55.2 60.9 66.4 76.3 

14 years ......... 178 54.8 11.1 40.3 42.8 43.7 47.4 53.1 60.3 65.7 67.6 75.2 

15 years ......... 145 55.1 9.8 44.0 45.1 46.5 48.2 53.3 59.6 62.2 65.5 76.6 

16 years ......... 170 58.1 10.1 44.1 47.3 48.9 51.3 55.6 62.5 68.9 73.3 76.8 

17 years ......... 134 59.6 11.4 44.5 48.9 50.5 52.2 58.4 63.4 68.4 71.6 81.8 

18 years ......... 170 59.0 11.1 45.3 49.5 50.8 52.8 56.4 63.0 66.0 70.1 78.0 

19 years ......... 158 60.2 11.0 48.5 49.7 51.7 53.9 57.1 64.4 70.7 74.8 78.1 

Note: 1 kg = 2.2046 pounds.

a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. 

Source: National Center for Health Statistics, 1987. 
Table 7-8. Statistics for Probability Plot Regression Analyses 

Female's Body Weights 6 Months to 20 Years of Age 

Lognormal Probability Plots 

Age Linear Curve 

F	2 F a 

2 

a 

6 months to 1 year 2.16 0.145 

1 to 2 years 2.38 0.128 

2 to 3 years 2.56 0.112 

3 to 4 years 2.69 0.137 

4 to 5 years 2.83 0.133 

5 to 6 years 2.98 0.163 

6 to 7 years 3.10 0.174 

7 to 8 years 3.19 0.174 

8 to 9 years 3.31 0.156 

9 to 10 years 3.46 0.214 

10 to 11 years 3.57 0.199 

11 to 12 years 3.71 0.226 

12 to 13 years 3.82 0.213 

13 to 14 years 3.92 0.216 

14 to 15 years 3.99 0.187 

15 to 16 years 4.00 0.156 

16 to 17 years 4.06 0.167 

17 to 18 years 4.08 0.165 

18 to 19 years 4.07 0.147 

19 to 20 years 4.10 0.149 

a F	, F - correspond to the mean and standard deviation, 2 2 

respectively, of the lognormal distribution of body weight (kg). 

Source: Burmaster et al., 1994. 
Table 7-9. Statistics for Probability Plot Regression 

Analyses 

Male's Body Weights 6 Months to 20 Years of Age 

Lognormal Probability Plots 

Age Linear Curve 

F2 

a F2 a 

6 months to 1 year 2.23 0.132 

1 to 2 years 2.46 0.119 

2 to 3 years 2.60 0.120 

3 to 4 years 2.75 0.114 

4 to 5 years 2.87 0.133 

5 to 6 years 2.99 0.138 

6 to 7 years 3.13 0.145 

7 to 8 years 3.21 0.151 

8 to 9 years 3.33 0.181 

9 to 10 years 3.43 0.165 

10 to 11 years 3.59 0.195 

11 to 12 years 3.69 0.252 

12 to 13 years 3.78 0.224 

13 to 14 years 3.88 0.215 

14 to 15 years 4.02 0.181 

15 to 16 years 4.09 0.159 

16 to 17 years 4.20 0.168 

17 to 18 years 4.19 0.167 

18 to 19 years 4.25 0.159 

19 to 20 years 4.26 0.154 

a F	2 2 , F - correspond to the mean and standard

deviation, respectively, of the lognormal distribution of 

body weight (kg). 

Source: Burmaster et al., 1994. 
Table 7-10. Summary of Body Weight Studies 

Study Number of Subjects Population Comments 

KEY STUDIES 

Hamill et al. (1979) ~1,000 U.S. general Authors noted that data are accurate measurements 

population from a large nationally representative sample of 

children. 

NCHS, 1987 

(NHANES II) 

20,322 U.S. general Based on civilian non-institutionalized population aged 

population 6 months to 74 years. Response rate was 73.1 

percent. 

RELEVANT STUDIES 

Brainard and Burmaster, 

1992 

12,501 (5,916 men and U.S. general Used data from NHANES II to fit bivarite distributions 

6,588 women) population to women and men age 18 to 74 years. 

Burmaster et al., 1994 8,458 (4,079 females and U.S. general Used data from NHANES II to develop fitted 

4,379 males) population distributions for children aged 6 to 20 years old. 

Adjusted for non-response by age, gender, and race. 
Table 7-11. Summary of Recommended Values for Body Weight 

Population Mean Upper Percentile Multiple Percentiles 

Adults 71.8 kg (See Table 7-2) See Tables 7-4 and 7-5 See Tables 7-4 and 7-5 

Children See Table 7-3 See Tables 7-6 and 7-7 See Tables 7-6 and 7-7 

Infants Not Available See Table 7-1 See Table 7-1 
Table 7-12. Confidence in Body Weight Recommendations 

Considerations Rationale Rating 

Study Elements

 • Level of peer review NHANES II was the major source of data for NCHS (1987). This is a High 

published study which received a high level of peer review. The 

Hamill et al. (1979) is a peer reviewed journal publication.

 • Accessibility Both studies are available to the public. High

 • Reproducibility Results can be reproduced by analyzing NHANES II data and the High 

Fels Research Institute data.

 • Focus on factor of interest The studies focused on body weight, the exposure factor of interest. High

 • Data pertinent to US The data represent the U.S. population. High

 • Primary data The primary data were generated from NHANES II data and Fels Medium 

studies, thus these data are secondary.

 • Currency The data were collected between 1976-1980. Low

 • Adequacy of data collection The NHANES II study included data collected over a period of 4 High

 period years. Body weight measurements were taken at various times of the 

day and at different seasons of the year.

 • Validity of approach Direct body weights were measured for both studies. For NHANES II, High 

subgroups at risk for malnutrition were over-sampled. Weighting was 

accomplished by inflating examination results for those not examined 

and were stratified by race, age, and sex. The Fels data are from an 

ongoing longitudinal study where the data are collected regularly.

 • Study size The sample size consisted of 28,000 persons for NHANES II. Author High 

noted in Hamill et al. (1979) that the data set was large.

 • Representativeness of the Data collected focused on the U.S. population for both studies. High

 population

 • Characterization of Both studies characterized variability regarding age and sex. High

 variability Additionally NHANES II characterized race (for Blacks, Whites and 

total populations) and sampled persons with low income.

 • Lack of bias in study design There are no apparent biases in the study designs for NHANES II. Medium­

(high rating is desirable) The study design for collecting the Fels data was not provided. High

 • Measurement error For NHANES II, measurement error should be low since body weights High 

were performed in a mobile examination center using standardized 

procedures and equipment. Also, measurements were taken at 

various times of the day to account for weight fluctuations as a result 

of recent food or water intake. The authors of Hamill et al. (1979) 

report that study data are based on accurate direct measurements 

from an ongoing longitudinal study. 

Other Elements

 • Number of studies There are two studies. Low

 • Agreement between researchers There is consistency among the two studies. High 

Overall Rating High 
Figure 7-1. Weight by Age Percentiles for Boys Aged Birth-36 Months 

Source: Hamill et al., 1979. 
Figure 7-2. Weight by Age Percentiles for Girls Aged Birth-36 Months 

Source: Hamill et al., 1979 
Table 8-1. Expectation of Life at Birth, 1970 to 1993, and Projections, 1995 to 2010 (years)a 

YEAR 

TOTAL WHITE BLACK AND OTHER BLACK b 

Total Male Female Total Male Female Total Male Female Total Male Femal 

e 

1970 70.8 67.1 74.7 71.7 68.0 75.6 65.3 61.3 69.4 64.1 60.0 68.3 

1975 72.6 68.8 76.6 73.4 69.5 77.3 68.0 63.7 72.4 66.8 62.4 71.3 

1980 73.7 70.0 77.4 74.4 70.7 78.1 69.5 65.3 73.6 68.1 63.8 72.5 

1981 74.1 70.4 77.8 74.8 71.1 78.4 70.3 66.2 74.4 68.9 64.5 73.2 

1982 74.5 70.8 78.1 75.1 71.5 78.7 70.9 66.8 74.9 69.4 65.1 73.6 

1983 74.6 71.0 78.1 75.2 71.6 78.7 70.9 67.0 74.7 69.4 65.2 73.5 

1984 74.7 71.1 78.2 75.3 71.8 78.7 71.1 67.2 74.9 69.5 65.3 73.6 

1985 74.7 71.1 78.2 75.3 71.8 78.7 71.0 67.0 74.8 69.3 65.0 73.4 

1986 74.7 71.2 78.2 75.4 71.9 78.8 70.9 66.8 74.9 69.1 64.8 73.4 

1987 74.9 71.4 78.3 75.6 72.1 78.9 71.0 66.9 75.0 69.1 64.7 73.4 

1988 74.9 71.4 78.3 75.6 72.2 78.9 70.8 66.7 74.8 68.9 64.4 73.2 

1989 75.1 71.7 78.5 75.9 72.5 79.2 70.9 66.7 74.9 68.8 64.3 73.3 

1990 75.4 71.8 78.8 76.1 72.7 79.4 71.2 67.0 75.2 69.1 64.5 73.6 

1991 75.5 71.0 78.9 76.3 72.9 79.6 71.5 67.3 75.5 69.3 64.6 73.8 

1992 75.8 72.3 79.1 76.5 73.2 79.8 71.8 67.7 75.7 69.6 65.0 73.9 

1993 75.5 72.1 78.9 76.3 73.0 79.5 71.5 67.4 75.5 69.3 64.7 73.7 

Projections 1995 76.3 72.8 79.7 77.0 73.7 80.3 72.5 68.2 76.8 70.3 65.8 74.8 c 

2000 76.7 73.2 80.2 77.6 74.3 80.9 72.9 68.3 77.5 70.2 65.3 75.1 

2005 77.3 73.8 80.7 78.2 74.9 81.4 73.6 69.1 78.1 70.7 65.9 75.5 

2010 77.9 74.5 81.3 78.8 75.6 81.0 74.3 69.9 78.7 71.3 66.5 76.0 

Excludes deaths of nonresidents of the United States. a 

Racial descriptions were not provided in the data source. b 

Based on middle mortality assumptions; for details, see U.S. Bureau of the Census, Current Population Reports, Series P­ c 

25, No. 1104. 

Source: Bureau of the Census, 1995. 
Table 8-2. Expectation of Life by Race, Sex, and Age: 1992 

Expectation of Life in Years 

White Black 

Age in 1990 

(years) Total Male Female Male Female 

At birth 75.8 73.2 79.8 65.0 73.9 

1 75.4 72.8 79.3 65.2 74.1 

2 74.5 71.8 78.3 64.3 73.1 

3 73.5 70.9 77.3 63.4 72.2 

4 72.5 69.9 76.3 62.4 71.2 

5 71.6 68.9 75.4 61.4 70.3 

6 70.6 67.9 74.4 60.5 69.3 

7 69.6 66.9 73.4 59.5 68.3 

8 68.6 65.9 72.4 58.5 67.3 

9 67.6 65.0 71.4 57.5 66.3 

10 66.6 64.0 70.4 56.5 65.4 

11 65.6 63.0 69.4 55.5 64.4 

12 64.6 62.0 68.4 54.6 63.4 

13 63.7 61.0 67.4 53.6 62.4 

14 62.7 60.0 66.5 52.6 61.4 

15 61.7 59.1 65.5 51.7 60.4 

16 60.7 58.1 64.5 50.7 59.5 

17 59.8 57.2 63.5 49.8 58.5 

18 58.8 56.2 62.5 48.9 57.5 

19 57.9 55.3 61.6 48.1 56.6 

20 56.9 54.3 60.6 47.2 55.6 

21 56.0 53.4 59.6 46.3 54.6 

22 55.1 52.5 58.7 45.5 53.7 

23 54.1 51.6 57.7 44.6 52.7 

24 53.2 50.6 56.7 43.8 51.8 

25 52.2 49.7 55.7 42.9 50.8 

26 51.3 48.8 54.8 42.1 49.9 

27 50.4 47.8 53.8 41.2 48.9 

28 49.4 46.9 52.8 40.4 48.0 

29 48.5 46.0 51.8 39.5 47.1 

30 47.5 45.1 50.9 38.7 46.1 

31 46.6 44.1 49.9 37.8 45.2 

32 45.7 43.2 48.9 37.0 44.3 

33 44.7 42.3 48.0 36.2 43.4 

34 43.8 41.4 47.0 35.3 42.4 

35 42.9 40.5 46.0 34.5 41.5 

36 42.0 39.6 45.1 33.7 40.6 

37 41.0 38.7 44.1 32.9 39.7 

38 40.1 37.8 43.2 32.1 38.8 

39 39.2 36.9 42.2 31.3 37.9 

40 38.3 36.0 41.2 30.5 37.1 

41 37.4 35.1 40.3 29.7 36.2 

42 36.5 34.2 39.3 28.9 35.3 

43 35.6 33.3 38.4 28.2 34.4 

44 34.7 32.4 37.5 27.4 33.6 

45 33.8 31.5 36.5 26.7 32.7 

46 32.9 30.6 35.6 25.9 31.9 

47 32.0 29.7 34.7 25.2 31.0 

48 31.1 28.8 33.7 24.4 30.2 

49 30.2 28.0 32.8 23.7 29.3 
Table 8-2. Expectation of Life by Race, Sex, and Age: 1992 (continued) 

Expectation of Life in Years 

White Black 

Age in 1990 

(years) Total Male Female Male Female 

50 29.3 27.1 31.9 23.0 28.5 

51 28.5 26.3 31.0 22.3 27.7 

52 27.6 25.4 30.1 21.5 26.8 

53 26.8 24.6 29.2 20.8 26.0 

54 25.9 23.7 28.3 20.1 25.3 

55 25.1 22.9 27.5 19.5 24.5 

56 24.3 22.1 26.6 18.8 23.7 

57 23.5 21.3 25.7 18.2 23.0 

58 22.7 20.6 24.9 17.6 22.2 

59 21.9 19.8 24.1 16.9 21.5 

60 21.1 19.1 23.2 16.3 20.8 

61 20.4 18.3 22.4 15.8 20.1 

62 19.7 17.6 21.6 15.2 19.4 

63 18.9 16.9 20.8 14.6 18.7 

64 18.2 16.2 20.0 14.1 18.0 

65 17.5 15.5 19.3 13.5 17.4 

70 14.2 12.4 15.6 11.0 14.3 

75 11.2 9.6 12.2 8.9 11.4 

80 8.5 7.2 9.2 6.8 8.6 

85 and over 6.2 5.3 6.6 5.1 6.3 

Source: U.S. Bureau of Census, 1995. 
Table 8-3. Confidence in Lifetime Expectancy Recommendations 

Considerations Rationale Rating 

Study Elements 

• Level of peer review Data are published and have received extensive peer review. High 

• Accessibility The study was widely available to the public (Census data). High 

• Reproducibility Results can be reproduced by analyzing Census data. High 

• Focus on factor of interest Statistical data on life expectancy were published in this study. High 

• Data pertinent to US The study focused on the U.S. population. High 

• Primary data Primary data were analyzed. High 

• Currency The study was published in 1995 and discusses life expectancy High 

trends from 1970 to 1993. The study has also made projections for 

1995 until the year 2010. 

• Adequacy of data collection period The data analyzed were collected over a period of years. High 

• Validity of approach Census data is collected and analyzed over a period of years. High 

• Study size This study was based on U.S. Census data, thus the population High 

study size is expected to be greater than 100. 

• Representativeness of the population The data are representative of the U.S. population. High 

• Characterization of variability Data were averaged by gender and race but only for Blacks and Medium 

Whites; no other nationalities were represented within the section. 

• Lack of bias in study design (High There are no apparent biases. High 

rating is desirable) 

• Measurement error Measurement error may be attributed to portions of the population that Medium 

avoid or provide misleading information on census surveys. 

Other Elements 

• Number of studies Data presented in the section are from the U.S. Bureau of the Low 

Census publication. 

• Agreement between researchers Recommendation was based on only one study, but it is widely High 

accepted. 

Overall Rating HIGH 
Table 9-1. Sub-category Codes and Definitions Used in the CSFII 1989-91 Analysis 

Code Definition Description 

Regiona 

1 Northeast Includes Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, 

2 Midwest Includes Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, 

3 South Includes Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, 

4 West Includes Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, 

Rhode Island, and Vermont 

Ohio, South Dakota, and Wisconsin 

Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and 

West Virginia 

Washington, and Wyoming 

Urbanization 

1 Central City Cities with populations of 50,000 or more that is the main city within the metropolitan statistical area 

2 Suburban 

3 Nonmetropolitan city. 

(MSA). 

An area that is generally within the boundaries of an MSA, but is not within the legal limit of the central 

An area that is not within an MSA. 

Season 

Spring - April, May, June 

Summe - July, August, September 

r 

Fall 

Winter 

- October, November, December 

- January, February, March 

Race 

1 -­ White (Caucasian) 

2 -­ Black 

3 -­ Asian and Pacific Islander 

4 -­ Native American, Aleuts, and Eskimos 

5, 8, 9 Other/NA Don't know, no answer, some other race

 Alaska and Hawaii were not included. a 

Source: CSFII 1989-91. 
Table 9-2. Weighted and Unweighted Number of Observations for 

1989-91 CSFII Data Used in Analysis of Food Intake 

Demographic Factor Weighted Unweighted 

Total 242,707,000 11,912 

Age 

<01 7,394,000 424 

01-02 7,827,000 450 

03-05 11,795,000 603 

06-11 21,830,000 1,147 

12-19 26,046,000 1,250 

20-39 78,680,000 3,555 

40-69 71,899,000 3,380 

70+ 17,236,000 1,103 

Season 

Fall 60,633,000 3,117 

Spring 60,689,000 3,077 

Summer 60,683,000 2,856 

Winter 60,702,000 2,862 

Urbanization 

Central City 73,410,000 3,607 

Nonmetropolitan 53,993,000 3,119 

Suburban 115,304,000 5,186 

Race 

Asian 2,871,000 149 

Black 29,721,000 1,632 

Native American 2,102,000 171 

Other/NA 7,556,000 350 

White 200,457,000 9,610 

Region 

Northeast 59,285,000 3,007 

Midwest 50,099,000 2,180 

South 83,741,000 4,203 

West 49,582,000 2,522 
Table 9-3. Per Capita Intake of Total Fruits (g/kg-day as consumed) 

Population Percent 

Group Consum Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

ing 

Total 69.0% 3.381 0.068 0 0 0 0 1.68 4.16 7.98 12.44 26.54 210.72 

Age (years) 

< 01 67.9% 14.898 1.285 0 0 0 0 8.80 21.90 35.98 42.77 88.42 210.72 

01-02 76.7% 11.836 0.582 0 0 0 2.80 9.76 17.99 25.70 30.69 52.27 80.19 

03-05 80.8% 8.422 0.364 0 0 0 2.22 6.37 12.53 19.29 22.78 32.83 52.87 

06-11 79.2% 5.047 0.160 0 0 0 1.30 3.86 7.17 11.79 14.49 21.53 30.37 

12-19 62.6% 2.183 0.095 0 0 0 0 1.36 3.38 5.66 7.24 11.80 16.86 

20-39 58.8% 1.875 0.056 0 0 0 0 1.06 2.82 5.08 6.43 10.26 41.58 

40-69 71.0% 2.119 0.051 0 0 0 0 1.36 3.24 5.20 6.73 10.52 23.07 

70 + 83.3% 2.982 0.087 0 0 0 0.89 2.42 4.28 6.77 8.31 11.89 15.00 

Season 

Fall 68.9% 3.579 0.169 0 0 0 0 1.66 3.94 8.20 13.41 32.62 204.28 

Spring 68.3% 3.249 0.116 0 0 0 0 1.73 4.14 7.43 12.22 23.71 88.42 

Summer 70.4% 3.381 0.131 0 0 0 0 1.80 4.29 7.87 12.26 23.11 210.72 

Winter 68.4% 3.314 0.119 0 0 0 0 1.52 4.27 8.33 12.17 26.54 75.52 

Urbanization 

Central City 68.8% 3.288 0.114 0 0 0 0 1.66 4.00 7.82 11.94 23.73 210.72 

Nonmetropolitan 67.4% 3.107 0.113 0 0 0 0 1.51 3.94 7.52 12.25 26.04 84.34 

Suburban 70.1% 3.567 0.113 0 0 0 0 1.80 4.40 8.43 13.19 28.13 204.28 

Race 

Asian 77.2% 5.839 0.632 0 0 0 1.24 4.20 6.76 17.30 20.65 29.61 38.95 

Black 63.7% 3.279 0.188 0 0 0 0 1.51 4.25 7.70 12.34 26.54 210.72 

Native American 61.4% 3.319 0.490 0 0 0 0 1.58 4.31 7.57 16.02 22.66 29.24 

Other/NA 64.9% 4.027 0.465 0 0 0 0 1.77 5.10 10.92 14.96 47.78 53.89 

White 70.1% 3.337 0.075 0 0 0 0 1.66 4.06 7.87 12.21 26.48 204.28 

Region 

Midwest 69.9% 3.236 0.120 0 0 0 0 1.58 4.07 7.87 11.30 28.64 84.34 

Northeast 73.9% 3.665 0.143 0 0 0 0.07 1.84 4.70 8.37 12.75 31.67 88.42 

South 62.0% 3.017 0.105 0 0 0 0 1.42 3.80 7.39 11.67 24.67 210.72 

West 75.4% 3.880 0.187 0 0 0 0.17 2.08 4.45 9.18 14.61 25.49 204.28 

NOTE: SE = Standard error

 P = Percentile of the distribution 

Source: Based on EPA's analyses of the 1989-91 CSFII 
Table 9-4. Per Capita Intake of Total Vegetables (g/kg-day as consumed) 

Population Percent 

Group Consumi Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

ng 

Total 97.2% 4.259 0.029 0 0.75 1.29 2.26 3.60 5.37 7.93 10.00 15.65 44.99 

Age (years) 

< 01 74.8% 6.802 0.375 0 0 0 0 5.52 10.41 15.27 19.29 29.61 44.99 

01-02 95.6% 7.952 0.228 0 1.33 2.32 4.65 7.28 10.26 14.77 16.32 21.24 32.10 

03-05 97.2% 7.125 0.200 0 1.11 2.15 3.79 5.83 9.64 13.87 15.43 25.09 35.56 

06-11 97.6% 5.549 0.109 0 1.03 1.72 3.09 4.82 7.31 10.06 11.74 18.39 31.30 

12-19 98.1% 3.807 0.070 0 0.85 1.30 2.16 3.49 4.71 6.80 8.52 12.26 27.84 

20-39 98.2% 3.529 0.037 0 0.75 1.22 2.06 3.16 4.54 6.36 7.63 10.69 17.07 

40-69 98.3% 3.741 0.039 0 0.85 1.34 2.19 3.43 4.94 6.56 7.78 10.91 24.51 

70 + 98.3% 4.068 0.071 0 0.96 1.47 2.47 3.67 5.35 6.89 8.17 11.96 18.92 

Season 

Fall 97.8% 4.366 0.063 0 0.86 1.31 2.28 3.56 5.28 8.33 10.52 17.95 35.56 

Spring 96.9% 4.095 0.055 0 0.72 1.20 2.19 3.45 5.19 7.67 9.85 15.33 44.99 

Summer 97.0% 4.181 0.059 0 0.58 1.16 2.21 3.54 5.34 7.73 9.54 15.14 41.68 

Winter 97.0% 4.394 0.056 0 0.86 1.40 2.36 3.78 5.67 8.03 9.69 15.23 29.69 

Urbanization 

Central City 97.4% 4.059 0.053 0 0.67 1.22 2.08 3.34 5.17 7.74 9.51 16.04 44.99 

Nonmetropolitan 96.3% 4.450 0.060 0 0.86 1.41 2.44 3.72 5.66 8.28 10.08 16.27 35.56 

Suburban 97.6% 4.296 0.044 0 0.82 1.31 2.30 3.64 5.38 7.86 10.17 15.39 41.68 

Race 

Asian 93.3% 4.913 0.330 0 0 1.53 2.06 3.66 7.52 10.32 14.84 15.43 16.76 

Black 96.1% 4.228 0.093 0 0.36 0.85 1.99 3.19 5.46 8.80 11.35 18.39 32.10 

Native American 87.1% 4.880 0.277 0 0 0.58 2.40 4.22 6.85 8.87 11.37 13.89 21.77 

Other/NA 96.6% 4.762 0.183 0 0 1.11 2.46 4.24 6.20 9.33 11.93 15.02 22.14 

White 97.6% 4.229 0.031 0 0.86 1.37 2.30 3.60 5.32 7.74 9.75 15.31 44.99 

Region 

Midwest 97.0% 4.123 0.061 0 0.75 1.20 2.09 3.35 5.16 8.03 9.87 16.90 35.56 

Northeast 97.2% 4.494 0.073 0 0.69 1.29 2.37 3.77 5.70 8.42 11.00 15.86 41.68 

South 97.4% 4.268 0.047 0 0.86 1.39 2.31 3.66 5.32 7.76 9.80 15.31 44.99 

West 96.9% 4.168 0.060 0 0.60 1.22 2.25 3.57 5.38 7.78 9.53 15.28 35.56 

NOTE: SE = Standard error

 P = Percentile of the distribution 

Source: Based on EPA's analyses of the 1989-91 CSFII 
Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) 

Apples Asparagus Bananas Beets 

Population Percent Percent Percent Percent 

Group Consuming Mean SE Consuming Mean SE Consuming Mean SE Consuming Mean SE 

Total 28.4% 0.854 0.052 1.5% 0.012 0.008 20.9% 0.27 0.02 1.8% 0.009 0.010 

Age (years) 

< 01 41.7% 5.042 0.823 0.0% 0 0 24.3% 1.33 0.27 1.2% 0.045 0.296 

01-02 42.9% 4.085 0.508 0.2% 0.003 0.041 23.3% 0.86 0.17 0.7% 0.006 0.055 

03-05 44.1% 3.004 0.312 0.2% 0.001 0.038 20.1% 0.46 0.09 0.5% 0.006 0.056 

06-11 41.6% 1.501 0.123 0.3% 0.001 0.019 16.2% 0.29 0.05 0.9% 0.008 0.040 

12-19 23.0% 0.394 0.062 0.3% 0.003 0.033 13.3% 0.16 0.03 0.6% 0.001 0.010 

20-39 21.3% 0.337 0.033 1.1% 0.008 0.012 14.4% 0.13 0.02 1.3% 0.004 0.007 

40-69 26.0% 0.356 0.027 2.5% 0.025 0.016 26.0% 0.22 0.02 2.4% 0.009 0.009 

70 + 30.8% 0.435 0.052 3.5% 0.026 0.028 37.4% 0.36 0.03 5.2% 0.029 0.022 

Season 

Fall 33.7% 1.094 0.116 0.8% 0.005 0.013 19.3% 0.25 0.03 1.2% 0.009 0.040 

Spring 25.9% 0.667 0.078 2.7% 0.023 0.017 21.3% 0.27 0.03 2.0% 0.009 0.012 

Summer 23.2% 0.751 0.122 1.1% 0.006 0.014 20.5% 0.23 0.03 1.7% 0.005 0.008 

Winter 30.4% 0.905 0.095 1.3% 0.015 0.018 22.6% 0.31 0.03 2.3% 0.011 0.013 

Urbanization 

Central City 27.4% 0.749 0.081 1.1% 0.013 0.018 19.6% 0.25 0.03 1.3% 0.008 0.031 

Nonmetropolitan 26.8% 0.759 0.104 1.3% 0.011 0.015 20.5% 0.24 0.03 1.8% 0.010 0.013 

Suburban 29.9% 0.965 0.083 1.8% 0.013 0.012 21.9% 0.29 0.03 2.0% 0.008 0.009 

Race 

Asian 38.3% 0.871 0.327 2.7% 0.067 0.123 33.6% 0.54 0.20 0.7% 0.040 0.320 

Black 22.7% 0.688 0.159 0.3% 0.003 0.019 14.4% 0.19 0.04 1.1% 0.007 0.024 

Native American 20.5% 0.407 0.273 0.0% 0 0 17.5% 0.36 0.16 1.2% 0.003 0.028 

Other/NA 24.9% 0.964 0.256 0.6% 0.001 0.009 20.6% 0.33 0.15 0.9% 0.015 0.101 

White 29.4% 0.879 0.057 1.7% 0.013 0.009 21.8% 0.27 0.02 1.9% 0.008 0.010 

Region 

Midwest 29.1% 0.782 0.082 1.8% 0.015 0.016 18.8% 0.25 0.03 0.8% 0.010 0.049 

Northeast 31.5% 0.953 0.116 1.6% 0.015 0.022 23.0% 0.26 0.04 2.3% 0.008 0.012 

South 23.6% 0.828 0.099 1.0% 0.010 0.014 19.3% 0.28 0.03 1.8% 0.009 0.011 

West 32.7% 0.885 0.121 1.8% 0.012 0.015 24.0% 0.27 0.03 2.4% 0.008 0.009 
Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued) 

Broccoli Cabbage Carrots Corn 

Population Percent Percent Percent Percent 

Group Consuming Mean SE Consuming Mean SE Consuming Mean SE Consuming Mean SE 

Total 10.9% 0.107 0.012 12.2% 0.088 0.009 16.9% 0.115 0.010 24.1% 0.206 0.010 

Age (years) 

< 01 4.2% 0.142 0.224 2.4% 0.023 0.078 13.4% 0.379 0.165 17.5% 0.356 0.128 

01-02 7.6% 0.234 0.134 5.1% 0.086 0.089 13.3% 0.214 0.085 32.9% 0.587 0.091 

03-05 10.1% 0.307 0.118 7.5% 0.107 0.081 15.1% 0.148 0.052 31.5% 0.490 0.070 

06-11 6.8% 0.098 0.052 7.5% 0.049 0.027 17.1% 0.154 0.037 35.8% 0.367 0.032 

12-19 8.2% 0.065 0.028 8.5% 0.065 0.028 11.8% 0.056 0.018 24.0% 0.173 0.024 

20-39 11.4% 0.081 0.015 10.6% 0.070 0.015 15.2% 0.076 0.013 23.8% 0.154 0.013 

40-69 13.8% 0.102 0.016 17.1% 0.115 0.015 20.1% 0.120 0.016 20.4% 0.138 0.013 

70 + 11.8% 0.115 0.028 21.1% 0.151 0.025 21.3% 0.132 0.022 19.0% 0.140 0.027 

Season 

Fall 10.8% 0.089 0.024 12.3% 0.092 0.019 17.7% 0.100 0.017 23.6% 0.171 0.018 

Spring 11.7% 0.122 0.022 12.4% 0.086 0.018 16.5% 0.117 0.022 24.7% 0.204 0.019 

Summer 8.8% 0.120 0.032 12.3% 0.097 0.018 13.9% 0.083 0.017 24.8% 0.244 0.022 

Winter 12.3% 0.098 0.020 11.9% 0.076 0.014 19.2% 0.160 0.022 23.2% 0.205 0.020 

Urbanization 

Central City 10.6% 0.119 0.024 10.8% 0.073 0.015 15.5% 0.111 0.019 22.4% 0.182 0.017 

Nonmetropolitan 9.0% 0.067 0.017 13.7% 0.102 0.016 14.4% 0.095 0.017 27.6% 0.255 0.020 

Suburban 12.2% 0.119 0.019 12.4% 0.091 0.014 19.2% 0.127 0.015 23.1% 0.198 0.015 

Race 

Asian 15.4% 0.209 0.166 27.5% 0.400 0.100 28.2% 0.177 0.101 14.1% 0.134 0.080 

Black 8.3% 0.154 0.047 13.9% 0.129 0.029 7.0% 0.066 0.036 24.6% 0.226 0.028 

Native American 5.3% 0.021 0.045 4.7% 0.037 0.068 11.1% 0.097 0.075 30.4% 0.373 0.099 

Other/NA 10.3% 0.180 0.100 6.0% 0.041 0.044 12.9% 0.104 0.063 16.9% 0.160 0.065 

White 11.4% 0.097 0.012 12.1% 0.080 0.009 18.6% 0.122 0.011 24.3% 0.204 0.011 

Region 

Midwest 8.4% 0.077 0.025 10.1% 0.065 0.016 16.2% 0.100 0.018 26.8% 0.242 0.020 

Northeast 13.5% 0.113 0.026 11.6% 0.083 0.022 19.0% 0.151 0.027 23.3% 0.208 0.026 

South 9.8% 0.109 0.022 14.4% 0.106 0.015 12.4% 0.074 0.015 24.9% 0.219 0.016 

West 13.4% 0.135 0.025 11.8% 0.088 0.016 23.3% 0.166 0.021 20.1% 0.138 0.018 
Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued) 

Cucumbers Lettuce Lima Beans Okra 

Population Percent Percent Percent Percent 

Group Consuming Mean SE Consuming Mean SE Consuming Mean SE Consuming Mean SE 

Total 15.8% 0.063 0.006 41.3% 0.224 0.006 0.9% 0.006 0.007 1.3% 0.009 0.007 

Age (years) 

< 01 2.4% 0.021 0.107 6.8% 0.025 0.026 0.5% 0.005 0.055 0.5% 0.003 0.040 

01-02 7.3% 0.062 0.069 18.2% 0.116 0.039 0.4% 0.006 0.069 0.2% 0.004 0.068 

03-05 12.1% 0.083 0.046 29.4% 0.191 0.031 0.0% 0 0 0.7% 0.013 0.046 

06-11 14.9% 0.086 0.032 36.3% 0.247 0.027 0.3% 0.002 0.017 0.3% 0.005 0.028 

12-19 12.6% 0.050 0.017 40.4% 0.187 0.014 0.5% 0.003 0.019 1.4% 0.011 0.027 

20-39 17.0% 0.057 0.009 44.4% 0.231 0.010 0.7% 0.005 0.012 1.0% 0.008 0.016 

40-69 19.8% 0.070 0.008 51.0% 0.264 0.010 1.5% 0.010 0.013 1.8% 0.008 0.010 

70 + 14.8% 0.055 0.016 37.4% 0.203 0.017 1.9% 0.008 0.019 2.7% 0.015 0.021 

Season 

Fall 14.3% 0.056 0.014 38.1% 0.175 0.010 0.8% 0.004 0.010 0.9% 0.004 0.009 

Spring 15.8% 0.060 0.009 43.5% 0.259 0.011 1.0% 0.008 0.015 0.8% 0.009 0.020 

Summer 19.0% 0.092 0.014 42.3% 0.218 0.012 0.9% 0.006 0.014 2.2% 0.016 0.015 

Winter 14.3% 0.044 0.010 41.5% 0.243 0.013 1.0% 0.007 0.013 1.3% 0.006 0.012 

Urbanization 

Central City 15.1% 0.061 0.011 37.9% 0.196 0.009 0.5% 0.004 0.011 1.0% 0.004 0.008 

Nonmetropolitan 15.1% 0.071 0.013 39.9% 0.221 0.012 1.5% 0.015 0.018 1.8% 0.013 0.015 

Suburban 16.7% 0.060 0.008 44.6% 0.242 0.009 0.9% 0.004 0.007 1.2% 0.010 0.012 

Race 

Asian 16.1% 0.065 0.036 40.3% 0.231 0.050 0.0% 0 0 4.7% 0.084 0.074 

Black 7.8% 0.040 0.021 27.1% 0.134 0.014 0.9% 0.006 0.021 2.1% 0.024 0.029 

Native American 6.4% 0.037 0.042 42.7% 0.146 0.034 0.0% 0 0 0.0% 0 0 

Other/NA 10.9% 0.038 0.029 41.1% 0.186 0.027 0.0% 0 0 1.7% 0.004 0.023 

White 17.5% 0.067 0.007 43.7% 0.239 0.007 1.0% 0.006 0.007 1.1% 0.006 0.007 

Region 

Midwest 15.1% 0.074 0.014 36.1% 0.191 0.012 0.4% 0.005 0.019 0.2% 0 0.004 

Northeast 18.9% 0.097 0.018 43.9% 0.246 0.014 0.5% 0.003 0.013 0.6% 0.009 0.031 

South 13.8% 0.042 0.007 39.3% 0.210 0.009 1.8% 0.011 0.011 3.2% 0.016 0.010 

West 17.2% 0.050 0.011 48.7% 0.263 0.013 0.5% 0.002 0.009 0.2% 0.005 0.022 
Table 9-5. Per Capita Intake of Fruits and Vegetables (g/kg-day as consumed) (continued) 

Onions Other Berries Peaches Pears 

Population Percent Percent Percent Percent 

Group Consuming Mean SE Consuming Mean SE Consuming Mean SE Consuming Mean SE 

Total 17.4% 0.040 0.003 2.5% 0.029 0.017 8.6% 0.131 0.019 4.8% 0.098 0.036 

Age (years) 

< 01 1.9% 0.004 0.022 0.9% 0.092 0.369 14.2% 0.855 0.268 12.3% 1.286 0.598 

01-02 6.4% 0.012 0.017 1.3% 0.053 0.248 8.9% 0.286 0.158 2.7% 0.105 0.243 

03-05 8.0% 0.023 0.016 2.2% 0.039 0.073 10.0% 0.283 0.121 4.5% 0.144 0.141 

06-11 9.7% 0.033 0.015 1.4% 0.014 0.056 13.8% 0.250 0.063 7.8% 0.147 0.057 

12-19 12.2% 0.030 0.010 0.8% 0.011 0.029 6.9% 0.084 0.037 3.4% 0.025 0.027 

20-39 20.5% 0.040 0.005 2.3% 0.024 0.030 4.2% 0.037 0.019 2.4% 0.026 0.019 

40-69 24.0% 0.054 0.005 3.2% 0.031 0.023 8.7% 0.090 0.021 5.2% 0.062 0.022 

70 + 16.5% 0.043 0.012 5.1% 0.049 0.040 16.1% 0.161 0.033 7.8% 0.087 0.037 

Season 

Fall 16.3% 0.045 0.007 2.6% 0.024 0.023 6.4% 0.113 0.043 5.5% 0.159 0.107 

Spring 19.7% 0.040 0.005 1.9% 0.019 0.024 8.4% 0.107 0.037 4.3% 0.071 0.041 

Summer 18.7% 0.040 0.005 3.4% 0.032 0.027 12.5% 0.166 0.033 4.2% 0.076 0.066 

Winter 14.8% 0.033 0.006 2.0% 0.042 0.058 7.4% 0.136 0.041 5.1% 0.088 0.039 

Urbanization 

Central City 16.4% 0.043 0.006 2.9% 0.033 0.030 7.3% 0.121 0.035 4.5% 0.120 0.091 

Nonmetropolitan 15.7% 0.033 0.005 1.6% 0.016 0.019 9.8% 0.156 0.034 5.4% 0.083 0.033 

Suburban 19.1% 0.041 0.004 2.7% 0.033 0.028 8.8% 0.125 0.029 4.6% 0.092 0.050 

Race 

Asian 20.8% 0.090 0.042 2.7% 0.014 0.057 6.7% 0.202 0.235 2.7% 0.053 0.151 

Black 9.6% 0.034 0.014 0.9% 0.008 0.034 5.6% 0.111 0.053 2.9% 0.066 0.056 

Native American 5.3% 0.018 0.022 2.3% 0.072 0.165 9.9% 0.192 0.158 1.2% 0.003 0.053 

Other/NA 15.1% 0.057 0.022 0.9% 0.015 0.069 4.3% 0.118 0.145 5.1% 0.063 0.089 

White 19.0% 0.039 0.003 2.8% 0.033 0.019 9.3% 0.132 0.021 5.2% 0.106 0.042 

Region 

Midwest 13.8% 0.033 0.006 2.3% 0.022 0.020 9.6% 0.155 0.040 6.0% 0.121 0.054 

Northeast 20.6% 0.057 0.009 3.2% 0.023 0.024 9.0% 0.132 0.048 5.7% 0.108 0.064 

South 17.2% 0.034 0.004 1.7% 0.030 0.037 7.9% 0.113 0.027 3.6% 0.051 0.023 

West 19.2% 0.039 0.006 3.3% 0.043 0.045 8.3% 0.131 0.042 4.5% 0.142 0.142 
Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued) 

Peas Peppers Pumpkins Snap Beans 

Population Percent Percent Percent Percent 

Group Consuming Mean SE Consuming Mean SE Consuming Mean SE Consuming Mean SE 

Total 12.8% 0.095 0.009 6.5% 0.022 0.005 1.0% 0.026 0.032 21.5% 0.146 0.008 

Age (years) 

< 01 13.7% 0.294 0.142 0.7% 0.003 0.025 5.2% 0.497 0.363 16.7% 0.439 0.154 

01-02 13.6% 0.174 0.083 2.4% 0.011 0.031 0.4% 0.030 0.253 24.9% 0.383 0.070 

03-05 12.9% 0.199 0.077 3.0% 0.014 0.032 0.7% 0.018 0.148 25.0% 0.274 0.048 

06-11 13.2% 0.120 0.029 4.7% 0.019 0.016 0.4% 0.012 0.118 25.6% 0.183 0.024 

12-19 8.4% 0.053 0.021 5.3% 0.017 0.014 0.2% 0 0.007 18.3% 0.112 0.018 

20-39 10.9% 0.067 0.013 7.9% 0.026 0.009 0.6% 0.007 0.026 19.0% 0.096 0.010 

40-69 14.8% 0.084 0.011 8.6% 0.027 0.008 1.2% 0.011 0.018 22.3% 0.124 0.011 

70 + 16.4% 0.117 0.024 4.7% 0.010 0.008 1.7% 0.034 0.053 25.5% 0.149 0.019 

Season 

Fall 13.2% 0.120 0.023 6.0% 0.023 0.009 1.9% 0.043 0.056 21.5% 0.164 0.018 

Spring 12.6% 0.077 0.015 7.3% 0.021 0.009 0.6% 0.034 0.105 18.9% 0.109 0.013 

Summer 11.2% 0.074 0.019 7.9% 0.023 0.009 0.4% 0.012 0.064 22.3% 0.147 0.016 

Winter 14.1% 0.111 0.017 4.7% 0.019 0.010 1.0% 0.015 0.037 23.7% 0.163 0.017 

Urbanization 

Central City 11.7% 0.085 0.018 6.5% 0.023 0.009 1.1% 0.035 0.068 20.2% 0.133 0.015 

Nonmetropolitan 14.5% 0.113 0.020 6.0% 0.017 0.006 0.5% 0.015 0.068 22.3% 0.141 0.013 

Suburban 12.5% 0.094 0.014 6.8% 0.023 0.007 1.3% 0.025 0.041 22.0% 0.156 0.013 

Race 

Asian 8.1% 0.047 0.071 8.1% 0.102 0.112 0.7% 0.005 0.057 13.4% 0.059 0.050 

Black 17.0% 0.143 0.032 3.6% 0.005 0.007 0.3% 0.037 0.238 24.1% 0.188 0.022 

Native American 2.9% 0.007 0.035 5.3% 0.015 0.031 0.0% 0 0 21.1% 0.119 0.048 

Other/NA 6.9% 0.037 0.058 11.1% 0.037 0.024 0.9% 0.024 0.208 15.1% 0.168 0.073 

White 12.5% 0.092 0.010 6.8% 0.022 0.005 1.2% 0.025 0.030 21.5% 0.140 0.009 

Region 

Midwest 10.9% 0.071 0.014 4.7% 0.016 0.011 1.2% 0.027 0.050 22.4% 0.146 0.014 

Northeast 12.5% 0.101 0.026 9.0% 0.036 0.012 1.4% 0.061 0.106 19.7% 0.131 0.020 

South 16.2% 0.126 0.017 5.8% 0.015 0.006 0.5% 0.002 0.026 24.3% 0.177 0.014 

West 9.5% 0.067 0.018 7.6% 0.025 0.010 1.3% 0.030 0.060 17.5% 0.107 0.019 
Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued) 

Strawberries Tomatoes White Potatoes 

Population Percent Percent Percent 

Group Consuming Mean SE Consuming Mean SE Consuming Mean SE 

Total 3.4% 0.039 0.019 91.8% 0.876 0.010 87.6% 1.093 0.013 

Age (years) 

< 01 0.7% 0.018 0.154 64.2% 1.116 0.094 59.9% 1.102 0.128 

01-02 1.6% 0.155 0.598 93.8% 1.838 0.103 84.2% 2.228 0.113 

03-05 3.2% 0.045 0.080 94.9% 1.700 0.072 88.1% 1.817 0.086 

06-11 3.3% 0.052 0.058 95.2% 1.160 0.032 90.5% 1.702 0.058 

12-19 2.3% 0.016 0.028 95.5% 0.852 0.022 90.1% 1.238 0.042 

20-39 2.7% 0.028 0.020 94.7% 0.791 0.013 88.6% 0.897 0.018 

40-69 4.5% 0.042 0.020 90.6% 0.673 0.013 88.1% 0.882 0.018 

70 + 5.8% 0.050 0.040 87.2% 0.689 0.027 88.9% 0.865 0.031 

Season 

Fall 1.3% 0.008 0.017 92.5% 0.907 0.021 88.9% 1.169 0.027 

Spring 7.7% 0.105 0.045 90.6% 0.808 0.018 86.3% 1.036 0.024 

Summer 2.2% 0.030 0.032 92.4% 0.946 0.019 86.5% 1.001 0.029 

Winter 2.5% 0.013 0.015 91.9% 0.844 0.018 88.7% 1.167 0.024 

Urbanization 

Central City 2.8% 0.028 0.020 91.5% 0.827 0.017 84.7% 1.017 0.025 

Nonmetropolitan 3.8% 0.052 0.029 90.7% 0.827 0.018 89.4% 1.211 0.027 

Suburban 3.6% 0.040 0.035 92.8% 0.931 0.015 88.5% 1.087 0.019 

Race 

Asian 3.4% 0.395 1.152 90.6% 1.147 0.110 77.2% 0.446 0.062 

Black 1.5% 0.031 0.056 87.4% 0.713 0.027 83.3% 1.202 0.047 

Native American 1.8% 0.023 0.120 84.2% 0.890 0.073 85.4% 1.735 0.134 

Other/NA 1.4% 0.007 0.042 91.4% 1.004 0.049 77.1% 1.036 0.080 

White 3.9% 0.037 0.013 92.8% 0.892 0.011 88.9% 1.082 0.014 

Region 

Midwest 4.8% 0.051 0.025 92.2% 0.814 0.019 89.2% 1.246 0.029 

Northeast 3.3% 0.059 0.079 93.0% 0.988 0.024 86.6% 1.090 0.030 

South 2.6% 0.025 0.019 90.7% 0.831 0.016 88.5% 1.074 0.021 

West 3.3% 0.028 0.025 92.3% 0.914 0.021 85.1% 0.946 0.026 

NOTE: SE = Standard error

 P = Percentile of the distribution 

Source: Based on EPA's analyses of the 1989-91 CSFII 
Table 9-6. Per Capita Intake of USDA Categories of Fruits and Vegetables (g/kg-day as consumed) 

Dark Green Vegetables Deep Yellow Vegetables Citrus Fruits Other Fruits Other Vegetables 

Population Percent Percent Percent Percent Percent 

Group Consuming Mean SE Consuming Mean SE Consuming Mean SE Consuming Mean SE Consuming Mean SE 

Total 19.1% 0.180 0.012 20.0% 0.147 0.010 38.0% 1.236 0.039 57.7% 2.141 0.063 83.1% 1.316 0.016 

Age (years) 

< 01 7.5% 0.180 0.177 10.1% 0.178 0.157 24.8% 1.929 0.586 61.6% 12.855 1.284 41.7% 1.346 0.200 

01-02 12.4% 0.364 0.137 14.4% 0.281 0.109 43.6% 4.237 0.459 66.4% 7.599 0.498 73.6% 2.077 0.136 

03-05 14.8% 0.390 0.119 16.3% 0.177 0.063 41.0% 2.596 0.267 70.0% 5.826 0.348 78.9% 1.979 0.102 

06-11 13.3% 0.150 0.044 19.1% 0.185 0.043 40.5% 1.805 0.138 70.1% 3.242 0.126 83.2% 1.534 0.062 

12-19 14.3% 0.112 0.030 14.0% 0.080 0.020 37.0% 1.130 0.085 47.3% 1.053 0.070 81.0% 0.950 0.035 

20-39 18.8% 0.137 0.016 17.5% 0.100 0.015 33.4% 0.903 0.049 44.9% 0.972 0.042 84.1% 1.081 0.022 

40-69 24.4% 0.187 0.016 24.8% 0.164 0.017 39.9% 0.864 0.045 60.9% 1.255 0.038 88.3% 1.374 0.026 

70 + 24.6% 0.255 0.034 29.4% 0.245 0.028 46.8% 1.155 0.069 76.1% 1.827 0.067 87.7% 1.615 0.046 

Season 

Fall 19.6% 0.169 0.023 22.7% 0.156 0.020 38.3% 1.211 0.074 57.6% 2.354 0.171 82.5% 1.276 0.032 

Spring 21.0% 0.187 0.020 19.7% 0.144 0.023 38.4% 1.225 0.072 56.4% 2.024 0.102 83.3% 1.297 0.030 

Summer 15.4% 0.182 0.029 15.6% 0.094 0.017 33.8% 1.136 0.093 60.8% 2.245 0.112 83.1% 1.332 0.032 

Winter 20.0% 0.180 0.024 21.9% 0.192 0.023 41.3% 1.371 0.073 56.0% 1.943 0.106 83.4% 1.361 0.031 

Urbanization 

Central City 20.5% 0.197 0.021 18.6% 0.133 0.019 39.8% 1.187 0.072 55.3% 2.090 0.100 81.4% 1.245 0.027 

Nonmetropolitan 16.0% 0.133 0.020 18.4% 0.138 0.021 34.2% 1.153 0.074 57.8% 1.954 0.100 83.2% 1.407 0.033 

Suburban 19.9% 0.190 0.019 22.0% 0.160 0.016 39.1% 1.306 0.058 59.2% 2.262 0.110 84.1% 1.319 0.023 

Race 

Asian 30.9% 0.327 0.127 29.5% 0.221 0.118 51.0% 2.479 0.453 69.8% 3.360 0.547 85.2% 2.228 0.205 

Black 25.9% 0.318 0.039 12.5% 0.104 0.029 40.1% 1.474 0.135 46.2% 1.806 0.156 78.1% 1.232 0.044 

Native American 9.4% 0.126 0.092 10.5% 0.081 0.060 33.3% 0.945 0.219 50.9% 2.375 0.431 75.4% 1.077 0.107 

Other/NA 15.1% 0.224 0.087 13.4% 0.106 0.071 40.3% 1.439 0.229 52.0% 2.589 0.452 76.3% 1.116 0.104 

White 18.1% 0.156 0.012 21.6% 0.154 0.011 37.4% 1.178 0.041 59.8% 2.154 0.071 84.2% 1.326 0.017 

Region 

Midwest 12.6% 0.125 0.026 18.7% 0.128 0.020 35.5% 1.099 0.077 59.8% 2.137 0.108 81.2% 1.186 0.029 

Northeast 21.1% 0.185 0.026 22.1% 0.175 0.026 45.6% 1.430 0.079 60.5% 2.235 0.132 84.5% 1.445 0.040 

South 20.5% 0.206 0.021 16.8% 0.119 0.018 33.5% 1.090 0.067 50.3% 1.927 0.095 83.2% 1.346 0.026 

West 22.6% 0.195 0.022 25.2% 0.187 0.021 41.8% 1.449 0.092 65.0% 2.414 0.182 83.8% 1.293 0.033 

NOTE: SE = Standard error

 P = Percentile of the distribution 

Source: Based on EPA's analyses of the 1989-91 CSFII 
Table 9-7. Per Capita Intake of Exposed Fruits (g/kg-day as consumed) 

Population Percent 

Group Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 44.1% 1.435 0.062 0 0 0 0 0 1.402 3.496 6.075 17.823 204.28 

Age (years) 

< 01 54.7% 9.224 1.247 0 0 0 0 2.897 12.336 26.98 33.216 75.353 204.28 

01-02 55.3% 5.682 0.486 0 0 0 0 2.897 8.598 15.187 19.107 33.353 80.189 

03-05 56.9% 4.324 0.344 0 0 0 0 2.305 5.766 11.65 19.049 24.123 48.728 

06-11 58.8% 2.316 0.12 0 0 0 0 1.379 3.32 5.879 8.585 15.318 25.367 

12-19 36.4% 0.682 0.065 0 0 0 0 0 0.871 2.158 3.214 6.703 10.766 

20-39 32.7% 0.596 0.038 0 0 0 0 0 0.754 1.984 2.858 5.911 28.486 

40-69 44.3% 0.716 0.031 0 0 0 0 0 1.102 2.139 3.048 5.127 13.206 

70 + 57.7% 1.032 0.058 0 0 0 0 0.534 1.452 2.894 4.042 6.983 10.631 

Season 

Fall 45.5% 1.753 0.179 0 0 0 0 0 1.521 3.64 7.537 25.206 204.28 

Spring 42.6% 1.184 0.078 0 0 0 0 0 1.283 3.208 5.505 14.872 84.336 

Summer 45.3% 1.44 0.113 0 0 0 0 0 1.389 3.451 6.313 17.427 98.133 

Winter 43.0% 1.362 0.097 0 0 0 0 0 1.441 3.54 5.703 18.752 59.848 

Urbanization 

Central City 42.4% 1.322 0.088 0 0 0 0 0 1.328 3.481 6.075 15.927 80.189 

Nonmetropolitan 44.0% 1.335 0.097 0 0 0 0 0 1.445 3.32 5.505 16.057 84.336 

Suburban 45.3% 1.553 0.112 0 0 0 0 0 1.442 3.686 6.614 20.444 204.28 

Race 

Asian 52.3% 2.118 0.541 0 0 0 0 0.654 1.674 4.299 8.678 25.206 27.337 

Black 34.6% 1.132 0.149 0 0 0 0 0 1.045 2.888 4.618 17.351 80.189 

Native American 35.7% 0.939 0.316 0 0 0 0 0 0.922 2.271 4.157 15.635 17.684 

Other/NA 34.0% 1.614 0.408 0 0 0 0 0 1.659 4.084 8.529 35.073 36.71 

White 46.1% 1.468 0.07 0 0 0 0 0 1.441 3.593 6.104 17.427 204.28 

Region 

Midwest 47.3% 1.422 0.091 0 0 0 0 0 1.645 3.501 6.114 16.438 84.336 

Northeast 47.3% 1.518 0.118 0 0 0 0 0 1.49 3.898 6.834 19.393 75.353 

South 36.9% 1.271 0.092 0 0 0 0 0 1.177 3.104 5.695 19.91 80.189 

West 49.4% 1.643 0.198 0 0 0 0 0 1.443 3.774 7.009 15.947 204.28 

NOTE: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA’s analyses of the 1989-91 CSFII 
Table 9-8. Per Capita Intake of Protected Fruits (g/kg-day as consumed) 

Population Percent 

Group Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 52.9% 1.692 0.037 0 0 0 0 0.598 2.316 4.687 6.717 13.019 136.69 

Age (years) 

< 01 38.9% 3.097 0.528 0 0 0 0 0 4.353 9.963 15.242 23.624 136.69 

01-02 56.7% 5.518 0.455 0 0 0 0 2.618 9.049 15.677 20.912 27.432 49.904 

03-05 57.0% 3.443 0.235 0 0 0 0 1.948 5.606 9.826 13.018 17.729 35.141 

06-11 56.2% 2.339 0.125 0 0 0 0 1.079 3.727 6.92 8.688 12.807 27.945 

12-19 47.7% 1.401 0.081 0 0 0 0 0.598 2.234 4.341 5.761 7.894 15.503 

20-39 45.4% 1.188 0.047 0 0 0 0 0.108 1.694 3.645 4.844 8.205 29.275 

40-69 57.3% 1.284 0.043 0 0 0 0 0.583 2.009 3.541 4.596 7.719 21.372 

70 + 67.5% 1.78 0.072 0 0 0 0 1.236 2.706 4.363 5.779 8.611 15.003 

Season 

Fall 50.2% 1.539 0.071 0 0 0 0 0.269 2.04 4.323 6.509 13.595 26.751 

Spring 53.9% 1.75 0.072 0 0 0 0 0.688 2.407 4.681 6.787 13.032 44.68 

Summer 54.1% 1.754 0.082 0 0 0 0 0.672 2.471 4.732 6.571 15.503 136.69 

Winter 53.7% 1.727 0.071 0 0 0 0 0.621 2.423 4.941 6.905 12.166 30.692 

Urbanization 

Central City 53.3% 1.632 0.069 0 0 0 0 0.625 2.276 4.497 6.099 11.535 136.69 

Nonmetropolitan 49.4% 1.55 0.069 0 0 0 0 0.334 2.115 4.368 6.961 12.076 29.275 

Suburban 54.7% 1.797 0.056 0 0 0 0 0.667 2.472 4.897 6.826 14.399 44.68 

Race 

Asian 69.8% 3.279 0.429 0 0 0 0 2.052 4.382 6.981 17.729 17.729 18.792 

Black 49.6% 1.861 0.126 0 0 0 0 0.621 2.695 5.64 7.241 13.572 136.69 

Native American 46.8% 2.019 0.33 0 0 0 0 0.851 2.701 5.995 10.354 11.554 15.244 

Other/NA 51.7% 2.014 0.263 0 0 0 0 0.845 2.472 5.759 8.88 14.279 44.68 

White 53.4% 1.629 0.039 0 0 0 0 0.574 2.238 4.527 6.425 12.53 49.904 

Region 

Midwest 49.5% 1.501 0.072 0 0 0 0 0.265 2.07 4.353 6.099 12.53 49.904 

Northeast 59.4% 1.887 0.08 0 0 0 0 0.838 2.675 5.371 7.268 13.018 42.347 

South 47.6% 1.56 0.064 0 0 0 0 0.465 2.147 4.443 6.39 12.076 136.69 

West 60.1% 1.947 0.084 0 0 0 0 0.854 2.613 4.88 7.836 16.064 44.68 

NOTE: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA’s analyses of the 1989-91 CSFII 
Table 9-9. Per Capita Intake of Exposed Vegetables (g/kg-day as consumed) 

Population Percent 

Group Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 84.9% 1.49 0.016 0 0 0 0.367 1.043 2.067 3.403 4.515 7.727 20.492 

Age (years) 

< 01 42.7% 1.208 0.17 0 0 0 0 0 1.55 3.834 6.451 11.524 18.592 

01-02 78.0% 2.268 0.145 0 0 0 0.299 1.132 3.616 5.855 7.404 12.808 20.492 

03-05 83.6% 2.245 0.119 0 0 0 0.329 1.411 3.061 5.433 7.664 12.493 17.872 

06-11 84.7% 1.606 0.059 0 0 0 0.293 1.062 2.222 3.769 5.118 9.161 15.741 

12-19 83.6% 1.181 0.04 0 0 0 0.253 0.804 1.696 2.756 3.84 5.699 12.139 

20-39 86.3% 1.3 0.025 0 0 0 0.331 0.923 1.87 2.968 3.692 6.327 14.837 

40-69 89.9% 1.568 0.026 0 0 0.07 0.557 1.22 2.177 3.42 4.443 6.274 13.624 

70 + 86.4% 1.603 0.044 0 0 0 0.672 1.326 2.214 3.344 4.206 5.928 12.814 

Season 

Fall 82.8% 1.383 0.033 0 0 0 0.29 0.951 1.824 3.151 4.283 8.783 18.592 

Spring 85.0% 1.475 0.031 0 0 0 0.383 1.028 2.075 3.406 4.562 7.403 20.492 

Summer 87.1% 1.634 0.033 0 0 0 0.432 1.272 2.289 3.68 4.765 7.399 18.283 

Winter 84.9% 1.468 0.033 0 0 0 0.367 0.999 2.09 3.109 4.464 7.664 16.152 

Urbanization 

Central City 83.6% 1.413 0.029 0 0 0 0.302 0.957 1.952 3.278 4.331 8.17 20.492 

Nonmetropolitan 85.8% 1.55 0.031 0 0 0 0.471 1.185 2.146 3.499 4.59 7.283 17.872 

Suburban 85.2% 1.511 0.025 0 0 0 0.356 1.055 2.098 3.464 4.683 7.664 16.152 

Race 

Asian 83.2% 2.133 0.195 0 0 0 0.606 1.537 3.135 4.746 6.883 10.325 11.841 

Black 81.8% 1.472 0.051 0 0 0 0.308 0.908 1.88 3.217 4.989 9.219 16.141 

Native American 75.4% 1.501 0.141 0 0 0 0.168 1.018 2.423 3.445 4.155 6.424 8.189 

Other/NA 85.4% 1.682 0.092 0 0 0 0.338 1.287 2.748 3.644 4.697 6.933 8.368 

White 85.6% 1.476 0.017 0 0 0 0.371 1.045 2.067 3.376 4.464 7.359 20.492 

Region 

Midwest 80.9% 1.215 0.029 0 0 0 0.239 0.824 1.683 2.843 3.834 6.35 20.492 

Northeast 84.7% 1.561 0.041 0 0 0 0.378 1.051 2.126 3.564 4.994 8.243 18.283 

South 86.7% 1.609 0.027 0 0 0 0.434 1.208 2.254 3.575 4.562 7.404 14.568 

West 86.6% 1.546 0.035 0 0 0 0.424 1.127 2.158 3.524 4.7 7.664 16.152 

NOTE: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA’s analyses of the 1989-91 CSFII 
Table 9-10. Per Capita Intake of Protected Vegetables (g/kg-day as consumed) 

Population Percent 

Group Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 34.0% 0.332 0.012 0 0 0 0 0 0.414 1.038 1.637 3.394 14.4 

Age (years) 

< 01 30.9% 1.144 0.192 0 0 0 0 0 1.435 4.584 6.25 8.752 14.4 

01-02 41.6% 0.794 0.104 0 0 0 0 0 1.201 2.232 3.766 6.488 9.74 

03-05 39.8% 0.703 0.081 0 0 0 0 0 1.205 2.443 3.053 4.811 11.3 

06-11 44.3% 0.5 0.035 0 0 0 0 0 0.848 1.439 2.058 3.32 8.6 

12-19 30.1% 0.229 0.025 0 0 0 0 0 0.332 0.824 1.339 2.138 4.94 

20-39 31.6% 0.233 0.015 0 0 0 0 0 0.323 0.78 1.161 2.427 5.6 

40-69 32.4% 0.239 0.014 0 0 0 0 0 0.362 0.772 1.164 2.033 6.25 

70 + 34.6% 0.303 0.028 0 0 0 0 0 0.427 1.015 1.491 2.291 5.34 

Season 

Fall 34.1% 0.336 0.025 0 0 0 0 0 0.394 1.064 1.725 3.674 11.3 

Spring 34.8% 0.32 0.024 0 0 0 0 0 0.421 0.96 1.435 3.493 14.4 

Summer 32.5% 0.334 0.024 0 0 0 0 0 0.411 1.116 1.7 3.492 10.4 

Winter 34.4% 0.337 0.022 0 0 0 0 0 0.42 1.109 1.724 2.945 8.68 

Urbanization 

Central City 31.7% 0.303 0.022 0 0 0 0 0 0.354 0.971 1.619 3.098 14.4 

Nonmetropolitan 37.9% 0.396 0.024 0 0 0 0 0 0.514 1.22 1.725 3.826 11.3 

Suburban 33.1% 0.32 0.018 0 0 0 0 0 0.39 1.029 1.591 3.32 14.1 

Race 

Asian 16.1% 0.166 0.081 0 0 0 0 0 0 0.636 1.201 1.506 3.17 

Black 37.3% 0.411 0.038 0 0 0 0 0 0.502 1.29 2.014 4.579 9.07 

Native American 32.7% 0.38 0.095 0 0 0 0 0 0.446 1.062 1.826 2.85 4.64 

Other/NA 22.9% 0.221 0.074 0 0 0 0 0 0 0.644 1.369 2.767 5.6 

White 34.1% 0.326 0.013 0 0 0 0 0 0.413 1.014 1.587 3.317 14.4 

Region 

Midwest 35.8% 0.344 0.022 0 0 0 0 0 0.46 1.127 1.674 3.013 11.3 

Northeast 32.4% 0.369 0.036 0 0 0 0 0 0.376 1.102 1.835 5.022 14.1 

South 36.8% 0.358 0.019 0 0 0 0 0 0.48 1.093 1.726 3.484 14.4 

West 28.4% 0.236 0.022 0 0 0 0 0 0.178 0.791 1.257 2.688 6.25 

NOTE: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA’s analyses of the 1989-91 CSFII 
Table 9-11. Per Capita Intake of Root Vegetables (g/kg-day as consumed) 

Population Percent 

Group Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 80.7% 1.245 0.015 0 0 0 0.226 0.832 1.675 2.974 4.029 7.074 30.609 

Age (years) 

< 01 52.4% 1.857 0.204 0 0 0 0 0.184 2.66 5.337 8.233 12.5 30.609 

01-02 76.2% 2.398 0.129 0 0 0 0.52 1.879 3.542 5.695 7.084 10.449 16.27 

03-05 77.9% 1.914 0.096 0 0 0 0.203 1.344 2.998 4.596 6.14 7.505 17.416 

06-11 84.4% 1.85 0.065 0 0 0 0.381 1.23 2.638 4.449 6.018 8.165 17.107 

12-19 81.4% 1.29 0.045 0 0 0 0.279 0.909 1.739 3.051 4.177 5.74 24.949 

20-39 81.6% 0.988 0.02 0 0 0 0.182 0.717 1.37 2.385 3.096 5.025 8.002 

40-69 82.8% 1.059 0.021 0 0 0 0.244 0.807 1.488 2.454 3.087 4.983 9.043 

70 + 80.6% 1.109 0.04 0 0 0 0.312 0.821 1.549 2.535 3.203 5.636 10.723 

Season 

Fall 80.6% 1.324 0.032 0 0 0 0.213 0.893 1.756 3.238 4.402 7.484 15.625 

Spring 80.5% 1.204 0.029 0 0 0 0.228 0.858 1.557 2.752 3.889 6.644 30.609 

Summer 80.3% 1.102 0.031 0 0 0 0.152 0.655 1.452 2.669 3.858 7.751 24.949 

Winter 81.5% 1.348 0.029 0 0 0 0.339 0.97 1.953 3.1 4.137 5.989 17.416 

Urbanization 

Central City 77.6% 1.167 0.029 0 0 0 0.176 0.755 1.545 2.826 3.903 7.505 30.609 

Nonmetropolitan 82.3% 1.33 0.03 0 0 0 0.311 0.893 1.795 3.256 4.422 6.946 19.449 

Suburban 81.9% 1.254 0.023 0 0 0 0.21 0.861 1.708 2.972 4.017 7.079 17.416 

Race 

Asian 55.0% 0.743 0.146 0 0 0 0 0.274 0.814 1.764 3.546 7.269 10.702 

Black 73.8% 1.309 0.052 0 0 0 0.134 0.761 1.627 3.337 5.358 7.968 17.534 

Native American 78.9% 1.791 0.137 0 0 0 0.655 1.47 2.762 3.858 4.705 7.067 13.578 

Other/NA 65.4% 1.239 0.11 0 0 0 0 0.635 1.75 3.38 4.861 8.253 10.415 

White 82.9% 1.237 0.016 0 0 0 0.25 0.858 1.673 2.887 3.942 6.651 30.609 

Region 

Midwest 82.2% 1.361 0.033 0 0 0 0.29 0.889 1.844 3.238 4.386 7.968 19.449 

Northeast 80.2% 1.304 0.037 0 0 0 0.21 0.912 1.781 3.212 4.246 7.022 24.949 

South 81.2% 1.183 0.024 0 0 0 0.25 0.796 1.591 2.82 3.906 6.926 30.609 

West 78.5% 1.15 0.032 0 0 0 0.146 0.786 1.56 2.673 3.683 7.269 13.578 

NOTE: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA’s analyses of the 1989-91 CSFII 
Table 9-12. Mean Daily Intake of Fruits and Vegetables Per Individual in a Day for USDA 1977-78, 87-88, 89-91, 94, and 95 Surveys 

Food Product 77-78 Data 87-88 Data 89-91 Data 94 Data 95 Data 

(g/day) (g/day) (g/day) (g/day) (g/day) 

Fruits 142 142 156 171 173 

Vegetables 201 182 179 186 188 

Source: USDA, 1980; 1992; 1996a; 1996b. 
Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups 

a Raw Agricultural Commodity 

Alfalfa Sprouts 

Apples-Dried 

Apples-Fresh 

Apples-Juice 

Apricots-Dried 

Apricots-Fresh 

Artichokes-Globe 

Artichokes-Jerusalem 

Asparagus 

Avocados 

Bamboo Shoots 

Bananas-Dried 

Bananas-Fresh 

Bananas-Unspecified 

Beans-Dry-Blackeye Peas (cowpeas) 

Beans-Dry-Broad Beans (Mature 

Seed) 

Beans-Dry-Garbanzo (Chick Pea) 

Beans-Dry-Great Northern 

Beans-Dry-Hyacinth (Mature Seeds) 

Beans-Dry-Kidney 

Beans-Dry-Lima 

Beans-Dry-Navy (Pea) 

Beans-Dry-Other 

Beans-Dry-Pigeon Beans 

Beans-Dry-Pinto 

Beans-Succulent-Broad Beans 

(Immature Seed) 

Beans-Succulent-Green 

Beans-Succulent-Hyacinth (Young 

Pods) 

Beans-Succulent-Lima 

Beans-Succulent-Other 

Beans-Succulent-Yellow, Wax 

Beans-Unspecified 

Average Consumption 

(Grams/kg Body Weight-Day) 

0.0001393 

0.0002064 

0.4567290 

0.2216490 

0.0004040 

0.0336893 

0.0032120 

0.0000010 

0.0131098 

0.0125370 

0.0001464 

0.0004489 

0.2240382 

0.0032970 

0.0024735 

0.0000000 

0.0005258 

0.0000010 

0.0000000 

0.0136313 

0.0079892 

0.0374073 

0.0398251 

0.0000357 

0.0363498 

0.0000000 

0.2000500 

0.0000000 

0.0256648 

0.0263838 

0.0054634 

0.0052345 

Standard Error 

0.0000319 

0.0000566 

0.0142203 

0.0142069 

0.0001457 

0.0022029 

0.0007696 

* 

0.0010290 

0.0020182 

0.0000505 

0.0001232 

0.0088206 

0.0004938 

0.0005469 

* 

0.0001590 

* 

* 

0.0045628 

0.0016493 

0.0023595 

0.0023773 

0.0000357 

0.0048479 

* 

0.0062554 

* 

0.0021327 

0.0042782 

0.0009518 

0.0012082 
Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups 

(continued) 

Average Consumption 

Raw Agricultural Commoditya (Grams/kg Body Weight-Day) 

Beets-Roots 0.0216142 

Beets-Tops (Greens) 0.0008287 

Bitter Melon 0.0000232 

Blackberries 0.0064268 

Blueberries 0.0090474 

Boysenberries 0.0007313 

Bread Nuts 0.0000010 

Bread Fruit 0.0000737 

Broccoli 0.0491295 

Brussel Sprouts 0.0068480 

Cabbage-Chinese/Celery, Inc. Bok 0.0045632 

Choy 

Cabbage-Green and Red 0.0936402 

Cactus Pads 0.0000010 

Cantaloupes 0.0444220 

Carambola 0.0000010 

Carob 0.0000913 

Carrots 0.1734794 

Casabas 0.0007703 

Cassava (Yuca Blanca) 0.0002095 

Cauliflower 0.0158368 

Celery 0.0609611 

Cherimoya 0.0000010 

Cherries-Dried 0.0000010 

Cherries-Fresh 0.0321754 

Cherries-Juice 0.0034080 

Chicory (French or Belgian Endive) 0.0006707 

Chili Peppers 0.0000000 

Chives 0.0000193 

Citrus Citron 0.0001573 

Coconut-Copra 0.0012860 

Coconut-Fresh 0.0001927 

Coconut-Water 0.0000005 

Standard Error 

0.0014187 

0.0003755 

0.0000233 

0.0007316 

0.0008951 

0.0006284 

* 

0.0000590 

0.0032966 

0.0009061 

0.0020966 

0.0039046 

* 

0.0029515 

* 

0.0000474 

0.0041640 

0.0003057 

0.00001574 

0.0011522 

0.0014495 

* 

* 

0.0024966 

0.0009078 

0.0001465 

* 

0.0000070 

0.0000324 

0.0000927 

0.0000684 

0.0000005 
Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups 

(continued) 

Raw Agricultural Commodity (Grams/kg Body Weight-Day) Standard Error a 

Average Consumption 

Collards 0.0188966 0.0032628 

Corn, Pop 0.0067714 0.0003348 

Corn, Sweet 0.2367071 0.0062226 

Crabapples 0.0003740 * 

Cranberries 0.0150137 0.0006153 

Cranberries-Juice 0.0170794 0.0022223 

Crenshaws 0.0000010 * 

Cress, Upland 0.0000010 * 

Cress, Garden, Field 0.0000000 * 

Cucumbers 0.0720821 0.0034389 

Currants 0.0005462 0.0000892 

Dandelion 0.0005039 0.0002225 

Dates 0.0006662 0.0001498 

Dewberries 0.0023430 * 

Eggplant 0.0061858 0.0007645 

Elderberries 0.0001364 0.0001365 

Endive, Curley and Escarole 0.0011851 0.0001929 

Fennel 0.0000000 * 

Figs 0.0027847 0.0005254 

Garlic 0.0007621 0.0000230 

Genip (Spanish Lime) 0.0000010 * 

Ginkgo Nuts 0.0000010 * 

Gooseberries 0.0003953 0.0001341 

Grapefruit-Juice 0.0773585 0.0053846 

Grapefruit-Pulp 0.0684644 0.0032321 

Grapes-Fresh 0.0437931 0.0023071 

Grapes-Juice 0.0900960 0.0058627 

Grapes-Leaves 0.0000119 0.0000887 

Grapes-Raisins 0.0169730 0.0009221 

Groundcherries (Poha or Cape- 0.0000000 * 

Gooseberries) 

Guava 0.0000945 0.0000558 

Honeydew Melons 0.0183628 0.0042879 
Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups 

(continued) 

Raw Agricultural Commodity (Grams/kg Body Weight-Day) Standard Error a 

Average Consumption 

Huckleberries (Gaylussacia) 0.0000010 * 

Juneberry 0.0000010 * 

Kale 0.0015036 0.0006070 

Kiwi 0.0000191 0.0000191 

Kohlrabi 0.0002357 0.0001028 

Kumquats 0.0000798 0.0000574 

Lambsquarter 0.0000481 0.0000481 

Leafy Oriental Vegetables 0.0000010 * 

Leeks 0.0000388 0.0000221 

Lemons-Juice 0.0189564 0.0009004 

Lemons-Peel 0.0002570 0.0001082 

Lemons-Pulp 0.0002149 0.0000378 

Lemons-Unspecified 0.0020695 0.0003048 

Lentiles-Split 0.0000079 0.0000064 

Lentiles-Whole 0.0012022 0.0002351 

Lettuce-Head Varieties 0.2122803 0.0059226 

Lettuce-Leafy Varieties 0.0044328 0.0003840 

Lettuce-Unspecified 0.0092008 0.0004328 

Limes-Juice 0.0032895 0.0005473 

Limes-Pulp 0.0000941 0.0000344 

Limes-Unspecified 0.0000010 * 

Loganberries 0.0002040 * 

Logan Fruit 0.0000010 * 

Loquats 0.0000000 * 

Lychee-Dried 0.0000010 * 

Lychees (Litchi) 0.0000010 * 

Maney (Mammee Apple) 0.0000010 * 

Mangoes 0.0005539 0.0002121 

Mulberries 0.0000010 * 

Mung Beans (Sprouts) 0.0066521 0.0006462 

Mushrooms 0.0213881 0.0009651 

Mustard Greens 0.0145284 0.0024053 
Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups 

(continued) 

Average Consumption 

Raw Agricultural Commoditya (Grams/kg Body Weight-Day) 

Nectarines 0.0129663 

Okra 0.0146352 

Olives 0.0031757 

Onions-Dehydrated or Dried 0.0001192 

Onions-Dry-Bulb (Cipollini) 0.1060612 

Onions-Green 0.0019556 

Oranges-Juice 1.0947265 

Oranges-Peel 0.0001358 

Oranges-Pulp 0.1503524 

Papayas-Dried 0.0009598 

Papayas-Fresh 0.0013389 

Papayas-Juice 0.0030536 

Parsley Roots 0.0000010 

Parsley 0.0036679 

Parsnips 0.0006974 

Passion Fruit (Granadilla) 0.0000010 

Pawpaws 0.0000010 

Peaches-Dried 0.0000496 

Peaches-Fresh 0.2153916 

Pears-Dried 0.0000475 

Pears-Fresh 0.1224735 

Peas (Garden)-Green Immature 0.1719997 

Peas (Garden)-Mature Seeds, Dry 0.0017502 

Peppers, Sweet, Garden 0.0215525 

Peppers-Other 0.0043594 

Persimmons 0.0004008 

Persian Melons 0.0000010 

Pimentos 0.0019485 

Pineapple-Dried 0.0000248 

Pineapple-Fresh, Pulp 0.0308283 

Pineapple-Fresh, Juice 0.0371824 

Pitanga (Surinam Cherry) 0.0000010 

Standard Error 

0.0013460 

0.0017782 

0.0002457 

0.0000456 

0.0021564 

0.0001848 

0.0283937 

0.0000085 

0.0092049 

0.0000520 

0.0005055 

0.0012795 

* 

0.0001459 

0.0001746 

* 

* 

0.0000152 

0.0078691 

0.0000279 

0.0050442 

0.0067868 

0.0002004 

0.0010091 

0.0004748 

0.0002236 

* 

0.0001482 

0.0000195 

0.0017136 

0.0026438 

* 
Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups 

(continued) 

Average Consumption 

Raw Agricultural Commoditya (Grams/kg Body Weight-Day) 

Plantains 0.0016370 

Plums, Prune-Juice 0.0137548 

Plums (Damsons)-Fresh 0.0248626 

Plums-Prunes (Dried) 0.0058071 

Poke Greens 0.0002957 

Pomegranates 0.0000820 

Potatoes (White)-Whole 0.3400582 

Potatoes (White)-Unspecified 0.0000822 

Potatoes (White)-Peeled 0.7842573 

Potatoes (White)-Dry 0.0012994 

Potatoes (White)-Peel Only 0.0000217 

Pumpkin 0.0044182 

Quinces 0.0001870 

Radishes-Roots 0.0015558 

Radishes-Tops 0.0000000 

Raspberries 0.0028661 

Rhubarb 0.0037685 

Rutabagas-Roots 0.0027949 

Rutabagas-Tops 0.0000000 

Salsify (Oyster Plant) 0.0000028 

Shallots 0.0000000 

Soursop (Annona Muricata) 0.0000010 

Soybeans-Sprouted Seeds 0.0000000 

Spinach 0.0435310 

Squash-Summer 0.0316479 

Squash-Winter 0.0324417 

Strawberries 0.0347089 

Sugar Apples (Sweetsop) 0.0000010 

Sweetpotatoes (including Yams) 0.0388326 

Swiss Chard 0.0016915 

Tangelos 0.0025555 

Tangerine-Juice 0.0000839 

Standard Error 

0.0007074 

0.0017904 

0.0020953 

0.0005890 

0.0001475 

0.0000478 

0.0102200 

0.0000093 

0.0184579 

0.0001896 

0.0000133 

0.0004354 

* 

0.0001505 

* 

0.0005845 

0.0006588 

0.0009720 

* 

0.0000028 

* 

* 

* 

0.0030656 

0.0022956 

0.0026580 

0.0020514 

* 

0.0035926 

0.0004642 

0.0006668 

0.0000567 
Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups 

(continued) 

Raw Agricultural Commodity (Grams/kg Body Weight-Day) Standard Error a 

Average Consumption 

Tangerines 0.0088441 0.0010948 

Tapioca 0.0012199 0.0000951 

Taro-Greens 0.0000010 * 

Taro-Root 0.0000010 * 

Tomatoes-Catsup 0.0420320 0.0015878 

Tomatoes-Juice 0.0551351 0.0029515 

Tomatoes-Paste 0.0394767 0.0012512 

Tomatoes-Puree 0.17012311 0.0054679 

Tomatoes-Whole 0.4920164 0.0080927 

Towelgourd 0.0000010 * 

Turnips-Roots 0.0082392 0.0014045 

Turnips-Tops 0.0147111 0.0025845 

Water Chestnuts 0.0004060 0.0000682 

Watercress 0.0003553 0.0001564 

Watermelon 0.0765054 0.0068930 

Yambean, Tuber 0.0000422 0.0000402 

Yautia, Tannier 0.0000856 0.0000571 

Youngberries 0.0003570 * 

* Not reported

 Consumed in any raw or prepared form a 

Source: DRES data base (based on 1977-78 NFCS data). 
Table 9-14. Mean Total Fruit Intake (as consumed) in a Day by Sex and Age (1977-1978)a 

Age (yr) Per Capita Intake Percent of Population Using Intake (g/day) for Users Only 

(g/day) Fruit in a Day 

b 

Males and Females 

1 and under 169 86.8 196 

1-2 146 62.9 231 

3-5 134 56.1 239 

6-8 152 60.1 253 

Males 

9-11 133 50.5 263 

12-14 120 51.2 236 

15-18 147 47.0 313 

19-22 107 39.4 271 

23-34 141 46.4 305 

35-50 115 44.0 262 

51-64 171 62.4 275 

65-74 174 62.2 281 

75 and over 186 62.6 197 

Females 

9-11 148 59.7 247 

12-14 120 48.7 247 

15-18 126 49.9 251 

19-22 133 48.0 278 

23-34 122 47.7 255 

35-50 133 52.8 252 

51-64 171 66.7 256 

65-74 179 69.3 259 

75 and over 189 64.7 292 

Males and Females 

All ages 142 54.2 263

 Based on USDA Nationwide Food Consumption Survey (1977-1978) data for one day. a

 Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population using fruit in a day. b 

Source: USDA, 1980. 
Table 9-15. Mean Total Fruit Intake (as consumed) in a Day by Sex and Age (1987-1988)a 

Age (yr) Per Capita Intake (g/day) Fruit in 1 Day 

Percent of Population Using Intake (g/day) for Users Onlyb 

Males and Females 

5 and under 157 59.2 265 

Males

 6-11 182 63.8 285

 12-19 158 49.4 320

 20 and over 133 46.5 286 

Females

 6-11 154 58.3 264

 12-19 131 47.1 278

 20 and over 140 52.7 266 

Males and Females 

All Ages 142 51.4 276 

Based on USDA Nationwide Food Consumption Survey (1987-1988) data for one day. a 

Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population using fruits in a day. b 

Source: USDA, 1992b. 
Table 9-16. Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age (1977-1978)a 

Age (yr) Per Capita Intake Percent of Population Using Intake (g/day) for Users 

(g/day) Vegetables in a Day Onlyb 

Males and Females 

1 and under 76 62.7 121 

1-2 91 78.0 116 

3-5 100 79.3 126 

6-8 136 84.3 161 

Males 

9-11 138 83.5 165 

12-14 184 84.5 217 

15-18 216 85.9 251 

19-22 226 84.7 267 

23-34 248 88.5 280 

35-50 261 86.8 300 

51-64 285 90.3 316 

65-74 265 88.5 300 

75 and over 264 93.6 281 

Females 

9-11 139 83.7 166 

12-14 154 84.6 183 

15-18 178 83.8 212 

19-22 184 81.1 227 

23-34 187 84.7 221 

35-50 187 84.6 221 

51-64 229 89.8 255 

65-74 221 87.2 253 

75 & over 198 88.1 226 

Males and Females 

All Ages 201 85.6 235 

Based on USDA Nationwide Food Consumption Survey (1977-1978) data for one day. a 

Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population using vegetables in a b 

day. 

Source: USDA, 1980. 
Table 9-17. Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age (1987-1988)a 

Age (yr) Per Capita Intake (g/day) Vegetables in a Day Intake (g/day) for Users Only 

Percent of Population Using b 

Males and Females

 5 and under 81 74.0 109 

Males

 6-11 129 86.8 149

 12-19 173 85.2 203

 20 and over 232 85.0 273 

Females

 6-11 129 80.6 160

 12-19 129 75.8 170

 20 and over 183 82.9 221 

Males and Females 

All Ages 182 82.6 220 

Based on USDA Nationwide Food Consumption Survey (1987-1988) data for one day. a 

Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population using vegetables in a b 

day. 

Source: USDA, 1992b. 
Table 9-18. Mean Total Fruit Intake (as consumed) in a Day by Sex and Age (1994 and 1995)a 

Age (yr) Per Capita Intake (g/day) Fruit in 1 Day Intake (g/day) for Users Only 

Percent of Population Using b 

1994 1995 1994 1995 1994 1995 

Males and Females 

5 and under 230 221 70.6 72.6 326 304 

Males

 6-11 176 219 59.8 62.2 294 352

 12-19 169 210 44.0 47.1 384 446

 20 and over 175 170 50.2 49.6 349 342 

Females

 6-11 174 172 59.3 63.6 293 270

 12-19 148 167 47.1 44.4 314 376

 20 and over 157 155 55.1 54.4 285 285 

Males and Females 

All Ages 171 173 54.1 54.2 316 319 

Based on USDA CSFII (1994 and 1995) data for one day. a 

Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population using fruits in a day. b 

Source: USDA, 1996a; 1996b. 
Table 9-19. Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age (1994 and 1995)a 

Age (yr) Per Capita Intake (g/day) Vegetables in 1 Day Intake (g/day) for Users Only 

Percent of Population Using b 

1994 1995 1994 1995 1994 1995 

Males and Females 

5 and under 80 83 75.2 75.0 106 111 

Males

 6-11 118 111 82.4 80.6 143 138

 12-19 154 202 74.9 79.0 206 256

 20 and over 242 241 85.9 86.4 282 278 

Females

 6-11 115 108 82.9 79.1 139 137

 12-19 132 144 78.5 76.0 168 189

 20 and over 190 189 84.7 83.2 224 227 

Males and Females 

All Ages 186 188 83.2 82.6 223 228 

Based on USDA CSFII (1994 and 1995) data for one day. a 

Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population using vegetables in a b 

day. 

Source: USDA, 1996a; 1996b. 
c 

Table 9-20. Mean Per Capita Intake of Fats and Oils (g/day as consumed) in a Day by Sex and Age (1994 and 

1995)a 

Total Fats and Oilsb Table Fatsc Salad Dressingsd 

1994 1995 1994 1995 1994 1995 

Males and Females 

5 and 4 3 2 2 2 1 

under 

Males 

6-11 8 7 3 3 5 4 

12-19 11 14 2 5 8 10 

20 and 19 18 5 5 11 10 

over 

Females 

6-11 7 8 3 3 4 4 

12-19 9 9 2 3 6 6 

20 and 16 14 4 5 10 7 

over 

Males and Females 

All Ages 14 14 4 4 9 8 

a Based on USDA CSFII 1994 and 1995 data for one day. b Table fats, cooking fats, vegetable oils, salad dressings, nondairy cream substitutes, sauces that are mainly fat

and oil.

Butter, margarines, blends of butter with margarines or vegetable oils, and butter replacements. d Regular and reduced- and low-calorie dressings and mayonnaise. 

Source: USDA, 1996a; 1996b. 
Table 9-21. Mean and Standard Error for the Per Capita Daily Intake of Food Class and Subclass by Region (g/day as consumed) 

US population Northeast North Central South West 

Total Produce 282.6 ± 3.5 270.6 ± 6.9 282.4 ± 6.7 280.7 ± 5.6 303.1 ± 8.2 

Leafy 39.2 ± 0.8 38.1 ± 1.5 37.1 ± 1.5 38.4 ± 1.2 45.3 ± 1.8 a 

Exposed 86.0 ± 1.5 88.5 ± 3.0 87.8 ± 2.9 76.9 ± 2.4 95.5 ± 3.6 b 

Protected 150.4 ± 2.3 137.2 ± 4.5 150.1 ± 4.3 160.1 ± 3.6 152.5 ± 5.3 c 

Other 7.0 ± 0.3 6.9 ± 0.6 7.3 ± 0.5 5.4 ± 0.4 9.8 ± 0.7 

Produce belonging to this category include: cabbage, cauliflower, broccoli, celery, lettuce, and spinach. a 

Produce belonging to this category include: apples, pears, berries, cucumber, squash, grapes, peaches, apricots, plums, b 

prunes, string beans, pea pods, and tomatoes. 

Produce belonging to this category include: carrots, beets, turnips, parsnips, citrus fruits, sweet corn, legumes (peas, beans, c 

etc.), melons, onion, and potatoes. 

NOTE: Northeast = Maine, New Hampshire, Vermont, Massachusetts, Connecticut, Rhode Island, New York, New Jersey, and 

Pennsylvania. 

North Central = Ohio, Illinois, Indiana, Wisconsin, Michigan, Minnesota, Iowa, Missouri, North Dakota, South Dakota, 

Nebraska, and Kansas. 

South = Maryland, Delaware, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, 

Florida, Kentucky, Tennessee, Alabama, Mississippi, Arkansas, Louisiana, Texas, and Oklahoma. 

West = Montana, Idaho, Wyoming, Utah, Colorado, New Mexico, Arizona, Nevada, Washington, Oregon, and California. 

Source: U.S. EPA, 1984b (based on 1977-78 NFCS data). 
Table 9-22.Mean and Standard Error for the Daily Intake of Food Subclasses Per Capita by Age (g/day as consumed) 

Age (years) Leafy produce Exposed produce Protected produce Other produce a b c 

All Ages 39.2 ± 0.8 86.0 ± 1.5 150.4 ± 2.3 7.0 ± 0.3 

<1 3.2 ± 4.9 75.5 ± 9.8 50.8 ± 14.7 25.5 ± 1.8 

1-4 9.1 ± 2.4 55.6 ± 4.8 94.5 ± 7.2 5.1 ± 0.9 

5-9 20.1 ± 2.0 69.2 ± 4.8 128.9 ± 6.1 4.3 ± 0.8 

10-14 26.1 ± 1.9 76.8 ± 3.8 151.7 ± 5.7 8.1 ± 0.7 

15-19 31.4 ± 2.0 71.9 ± 4.0 156.6 ± 6.0 6.2 ± 0.7 

20-24 35.3 ± 2.6 65.6 ± 5.2 144.5 ± 7.8 5.0 ± 1.0 

25-29 41.4 ± 2.7 73.4 ± 5.3 149.8 ± 8.0 7.0 ± 1.0 

30-39 44.4 ± 2.1 77.1 ± 4.2 150.5 ± 6.3 6.1 ± 0.8 

40-59 51.3 ± 1.6 94.7 ± 3.3 162.9 ± 4.9 6.9 ± 0.6 

$ 60 45.4 ± 1.8 114.2 ± 3.6 163.9 ± 5.5 7.6 ± 0.7 

Produce belonging to this category include: cabbage, cauliflower, broccoli, celery, lettuce, and spinach. a 

Produce belonging to this category include: apples, pears, berries, cucumber, squash, grapes, peaches, apricots, plums, prunes, b 

string beans, pea pods, and tomatoes. 

Produce belonging to this category include: carrots, beets, turnips, parsnips, citrus fruits, sweet corn, legumes (peas, beans, etc.), c 

melons, onion, and potatoes. 

Source: U.S. EPA, 1984a (based on 1977-78 NFCS data). 
Table 9-23. Consumption of Foods (g dry weight/day) for Different Age Groups and 

Estimated Lifetime Average Daily Food Intakes for a US Citizen 

(averaged across sex) Calculated from the FDA Diet Data 

Age (in years) 

Estimated Lifetime 

Intakea (0-1) (1-5) (6-13) (14-19) (20-44) (45-70) 

Potatoes 5.67 10.03 14.72 19.40 17.28 14.79 15.60 

Leafy Veg. 0.84 0.49 0.85 1.22 2.16 2.65 1.97 

Legume Veg. 3.81 4.56 6.51 8.45 9.81 9.50 8.75 

Root Veg. 3.04 0.67 1.20 1.73 1.77 1.64 1.60 

Garden fruits 0.66 1.67 2.57 3.47 4.75 4.86 4.15 

Peanuts 0.34 2.21 2.56 2.91 2.43 1.91 2.25 

Mushrooms 0.00 0.01 0.03 0.04 0.14 0.06 0.08 

Veg. Oils 27.62 17.69 27.54 37.04 37.20 27.84 31.24

a The estimated lifetime dietary intakes were estimated by: 

Estimated lifetime = IR(0-1) + 5yrs * IR (1-5) + 8 yrs * IR (6-13) + 6 yrs * IR (14-19) + 25 yrs * IR (20-44) + 25 yrs * IR (45-70) 

70 years 

where IR = the intake rate for a specific age group. 

Source: U.S. EPA, 1989 (based on 1977-78 NFCS and NHANES II data). 
Table 9-24. Mean Daily Intake of Foods (grams) Based on the Nutrition Canada Dietary Surveya 

Age (yrs) Sample Size Fruit Products Including Potatoes Potatoes Legumes 

Fruit and Vegetables Not Nuts and 

Males and Females 

1-4 1031 258 56 75 6 

5-11 1995 312 83 110 13 

Males 

12-19 1070 237 94 185 20 

20-39 999 244 155 189 15 

40-64 1222 194 134 131 15 

65+ 881 165 118 124 8 

Females 

12-19 1162 237 97 115 15 

20-39 1347 204 134 99 8 

40-64 1500 239 136 79 10 

65+ 818 208 103 80 5 

Pregnant Females 

--­ 769 301 156 114 15 

Report does not specify whether means were calculated per capita or for consumers only. The reported values are consistent a 

with the as consumed intake rates for consumers only reported by USDA (1980). 

Source: Canadian Department of National Health and Welfare, n.d. 
Table 9-25. Per Capita Consumption of Fresh Fruits and Vegetables in 1991a 

Fresh Fruits Fresh Vegetables 

Food Item Consumption 

Per Capita 

(g/day)b 

Food Item Consumption 

Per Capita 

(g/day)b 

Citrus 

Oranges (includes Temple 10.2 

oranges) 1.6 

Tangerines and Tangelos 3.1 

Lemons 0.9 

Limes 7.1 

Grapefruit 22.9 

Total Fresh Citrus 

Noncitrus 21.8 

Apples 0.1 

Apricots 1.7 

Avocados 31.2 

Bananas 0.5 

Cherries 0.4 

Cranberries 8.2 

Grapes 0.5 

Kiwi Fruit 1.0 

Mangoes 7.6 

Peaches & Nectarines 3.7 

Pears 2.2 

Pineapple 0.3 

Papayas 1.7 

Plums and Prunes 4.1 

Strawberries 85.0 

Total Fresh Noncitrus 107.7 

Total Fresh Fruits 

Artichokes 0.62 

Asparagus 0.75 

Snap Beans 1.4 

Broccoli 3.5 

Brussel Sprouts 0.4 

Cabbage 9.5 

Carrots 9.0 

Cauliflower 2.2 

Sweet Corn 6.6 

Cucumber 5.2 

Eggplant 0.5 

Escarole/Endive 0.3 

Garlic 1.6 

Head Lettuce 30.2 

Onions 18.4 

Bell Peppers 5.8 

Radishes 0.6 

Spinach 0.9 

Tomatoes 16.3 

Total Fresh Vegetables 126.1 

Celery 7.8

 Based on retail-weight equivalent. Includes imports; excludes exports and foods grown in home gardens. Data for 1991 used. a

 Original data were presented in lbs/yr; data were converted to g/day by multiplying by a factor of 454 g/lb and dividing by 365 b 

days/yr. 

Source: USDA, 1993. 
Table 9-26. Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating Occasion and the Percentage of Individuals Using These Foods in Three Days 

Consumers-only 

Food category % Indiv. using Quantity consumed per eating Quantity consumed per eating occasion at specified percentiles (g)a 

food in 3 days occasion (g) 

5 25 50 75 90 95 99 

Average Standard 

Deviation 

Raw vegetables 

White potatoes 74.4 125 90 29 63 105 170 235 280 426 

Cabbage and coleslaw 9.7 68 45 15 40 60 90 120 120 240 

Carrots 5 43 40 4 13 31 55 100 122 183 

Cucumbers 5.6 80 76 8 24 70 110 158 220 316 

Lettuce and tossed salad 50.7 65 59 10 20 55 93 140 186 270 

Mature onions 8.5 31 33 3 17 18 36 57 72 180 

Tomatoes 27.8 81 55 30 45 62 113 123 182 246 

Cooked vegetables 

Broccoli 6.2 112 68 30 78 90 155 185 190 350 

Cabbage 4.7 128 83 28 75 145 150 225 300 450 

Carrots 9.8 70 59 19 46 75 92 150 155 276 

Corn, whole kernel 23.9 95 56 21 65 83 123 170 170 330 

Lima beans 2.8 110 75 21 67 88 170 175 219 350 

Mixed vegetables 3.4 117 69 28 91 94 182 187 187 374 

Cowpeas, field peas, black- 2.9 131 88 22 88 88 175 196 350 350 

eyed peas 

Green peas 18.3 90 57 20 43 85 85 170 170 330 

Spinach 4.5 121 70 24 78 103 185 205 205 380 

String beans 27.3 86 54 18 67 70 135 140 140 280 

Summer squash 2.8 145 98 27 105 108 215 215 352 430 

Sweet potatoes 4.1 136 87 38 86 114 185 225 238 450 

Tomato juice 3.9 91 122 91 122 182 243 243 363 486 

Cucumber pickles 9.2 45 45 7 16 30 65 90 130 222 

Fruits 

Grapefruit 4.7 159 58 106 134 134 165 268 268 330 

Grapefruit juice 3.6 202 99 95 125 186 247 250 375 500 

Oranges 9 146 57 73 145 145 145 180 228 360 

Orange juice 35.5 190 84 95 125 187 249 249 311 498 

Apples 18.2 141 49 69 138 138 138 212 212 276 

Applesauce, cooked apples 9.8 134 86 28 64 128 130 255 155 488 

Apple juice 3.8 191 101 63 124 186 248 248 372 496 

Cantaloupe 3.3 171 91 61 136 136 272 272 272 529 

Raw peaches 4.5 160 75 76 152 152 152 304 304 456 

Raw pears 3.1 163 69 82 164 164 164 164 328 328 

Raw strawberries 2.1 100 58 37 75 75 149 149 180 298

a Percentiles are cumulative; for example, 50 percent of people eat 105 g white potatoes per day or less. 

Source: Pao et al., 1982 (based on 1977-78 NFCS data). 
Table 9-27. Mean Moisture Content of Selected Fruits and Vegetables Expressed as Percentages of Edible Portions 

Food Moisture Content (Percent) Comments 

Raw Cooked 

Fruit

 Apples - dried 31.76 84.13* sulfured; *without added sugar

 Apples - 83.93* 84.46** *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 31.09 85.56* sulfured; *without added sugar

 Bananas 74.26

 Blackberries 85.64

 Blueberries 84.61 86.59* *frozen unsweetened

 Boysenberries 85.90 frozen unsweetened

 Cantaloupes - unspecified 89.78

 Casabas 91.00

 Cherries - sweet 80.76 84.95* *canned, juice pack

 Crabapples 78.94

 Cranberries 86.54

 Cranberries - juice cocktail 85.00 bottled

 Currants (red and white) 83.95

 Elderberries 79.80

 Grapefruit 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 15.42 seedless

 Honeydew melons 89.66

 Kiwi fruit 83.05

 Kumquats 81.70

 Lemons - juice 90.73 92.46* *canned or bottled

 Lemons - peel 81.60

 Lemons - pulp 88.98

 Limes - juice 90.21 92.52* *canned or bottled

 Limes - unspecified 88.26

 Loganberries 84.61

 Mulberries 87.68

 Nectarines 86.28

 Oranges - unspecified 86.75 all varieties

 Peaches 87.66 87.49* *canned juice pack

 Pears - dried 26.69 64.44* sulfured; *without added sugar

 Pears - fresh 83.81 86.47* *canned juice pack

 Pineapple 86.50 83.51* *canned juice pack

 Pineapple - juice 85.53 canned

 Plums 85.20

 Quinces 83.80

 Raspberries 86.57

 Strawberries 91.57 89.97* *frozen unsweetened

 Tangerine - juice 88.90 87.00* *canned sweetened

 Tangerines 87.60 89.51* *canned juice pack

 Watermelon 91.51 

Vegetables

 Alfalfa sprouts 91.14

 Artichokes - globe & French 84.38 86.50 boiled, drained

 Artichokes - Jerusalem 78.01 
Table 9-27. Mean Moisture Content of Selected Fruits and Vegetables Expressed as Percentages of Edible Portions (continued) 

Food Moisture Content (Percent) Comments 

Raw Cooked

 Asparagus 92.25 92.04 boiled, drained

 Bamboo shoots 91.00 95.92 boiled, drained

 Beans - dry

 Beans - dry - blackeye peas (cowpeas) 66.80 71.80 boiled, drained

 Beans - dry - hyacinth (mature seeds) 87.87 86.90 boiled, drained

 Beans - dry - navy (pea) 79.15 76.02 boiled, drained

 Beans - dry - pinto 81.30 93.39 boiled, drained

 Beans - lima 70.24 67.17 boiled, drained

 Beans - snap - Italian - green - yellow 90.27 89.22 boiled, drained

 Beets 87.32 90.90 boiled, drained

 Beets - tops (greens) 92.15 89.13 boiled, drained

 Broccoli 90.69 90.20 boiled, drained

 Brussel sprouts 86.00 87.32 boiled, drained

 Cabbage - Chinese/celery, 

including bok choy 95.32 95.55 boiled, drained

 Cabbage - red 91.55 93.60 boiled, drained

 Cabbage - savoy 91.00 92.00 boiled, drained

 Carrots 87.79 87.38 boiled, drained

 Cassava (yucca blanca) 68.51

 Cauliflower 92.26 92.50 boiled, drained

 Celeriac 88.00 92.30 boiled, drained

 Celery 94.70 95.00 boiled, drained

 Chili peppers 87.74 92.50* *canned solids & liquid

 Chives 92.00

 Cole slaw 81.50

 Collards 93.90 95.72 boiled, drained

 Corn - sweet 75.96 69.57 boiled, drained

 Cress - garden - field 89.40 92.50 boiled, drained

 Cress - garden 89.40 92.50 boiled, drained

 Cucumbers 96.05

 Dandelion - greens 85.60 89.80 boiled, drained

 Eggplant 91.93 91.77 boiled, drained

 Endive 93.79

 Garlic 58.58

 Kale 84.46 91.20 boiled, drained

 Kohlrabi 91.00 90.30 boiled, drained

 Lambsquarter 84.30 88.90 boiled, drained

 Leeks 83.00 90.80 boiled, drained

 Lentils - whole 67.34 68.70 stir-fried

 Lettuce - iceberg 95.89

 Lettuce - romaine 94.91

 Mung beans (sprouts) 90.40 93.39 boiled, drained

 Mushrooms 91.81 91.08 boiled, drained

 Mustard greens 90.80 94.46 boiled, drained

 Okra 89.58 89.91 boiled, drained

 Onions 90.82 92.24 boiled, drained

 Onions - dehydrated or dried 3.93

 Parsley 88.31

 Parsley roots 88.31

 Parsnips 79.53 77.72 boiled, drained

 Peas (garden) - mature seeds - dry 88.89 88.91 boiled, drained

 Peppers - sweet - garden 92.77 94.70 boiled, drained

 Potatoes (white) - peeled 78.96 75.42 baked 
Table 9-27. Mean Moisture Content of Selected Fruits and Vegetables Expressed as Percentages of Edible Portions (continued) 

Food Moisture Content (Percent) Comments 

Raw Cooked

 Potatoes (white) - whole 

Pumpkin 

Radishes - roots 

Rhubarb 

Rutabagas - unspecified 

Salsify (oyster plant) 

Shallots 

Soybeans - sprouted seeds 

Spinach 

Squash - summer 

Squash - winter 

Sweetpotatoes (including yams) 

Swiss chard 

Tapioca - pearl 

Taro - greens 

Taro - root 

Tomatoes - juice 

Tomatoes - paste 

Tomatoes - puree 

Tomatoes - raw 

Tomatoes - whole 

Towelgourd 

Turnips - roots 

Turnips - tops 

 Water chestnuts 

Yambean - tuber 

Source: USDA, 1979-1986. 

83.29 71.20 baked

91.60 93.69 boiled, drained

94.84

93.61 67.79 frozen, cooked with added sugar

89.66 90.10 boiled, drained

77.00 81.00 boiled, drained

79.80

69.05 79.45 steamed

91.58 91.21 boiled, drained

93.68 93.70 all varieties; boiled, drained

88.71 89.01 all varieties; baked

72.84 71.85 baked in skin

92.66 92.65 boiled, drained

10.99 dry

85.66 92.15 steamed

70.64 63.80

93.90 canned

74.06 canned

87.26 canned

93.95

93.95 92.40 boiled, drained

93.85 84.29 boiled, drained

91.87 93.60 boiled, drained

91.07 93.20 boiled, drained

73.46

89.15 87.93 boiled, drained
Table 9-28. Summary of Fruit and Vegetable Intake Studies 

Study in Calculating Intake Types of Data Used Units 

Survey Population Used 

Food Items 

KEY STUDIES 

EPA Analysis of 1989­ Per capita data; 1989-91 CSFII data; g/kg-day; as consumed Major food groups; individual food 

91 USDA CSFII data consumer only data can Based on 3-day average individual items; exposed and protected fruits 

be calculated intake rate and vegetables; USDA food 

categories 

RELEVANT STUDIES 

AIHC, 1994 Per Capita Based on the 1977-78 USDA NFCS g/day Distributions for vegetables using 

data provided in the 1989 version of @Risk software. 

the Exposure Factors Handbook. 

Canadian Department Not known if per capita or 1970-72 survey based on 24-hour g/day; not known if as Fruit and fruit products, vegetables 

of National Health and consumers only dietary recall consumed not including potatoes and nuts 

Welfare, n.d. and legumes 

EPA's DRES Per capita (i.e., 1977-78 NFCS g/kg-day; as consumed Intake for a wide variety of fruits 

consumers and 3-day individual intake data and vegetables presented; complex 

nonconsumers) food groups were disaggregated 

Pao et al., 1982 Consumers only serving 1977-78 NFCS g; as consumed Serving sizes for only a limited 

size data provided 3-day individual intake data number of products 

USDA, 1980; 1992b; Per capita and consumer 1977-78 and 1987-88 NFCS, and g/day; as consumed Total fruits and total vegetables 

1996a; 1996b only 1994 and 1995 CSFII 

1-day individual intake data 

USDA, 1993 Per capita consumption Based on food supply and utilization g/day; as consumed Various food groups 

based on "food data provided by the National 

disappearance" Agricultural Statistics Service 

(NASS), Customs Service Reports, 

and trade associations 

U.S. EPA/ORP, 1984a; Per capita 1977-78 NFCS g/day; as consumed Exposed, protected, and leafy 

1984b Individual intake data produce 

U.S. EPA/OST, 1989 Estimated lifetime dietary Based on FDA Total Diet Study Food g/day; dry weight Various food groups; complex 

intake List which used 1977-78 NFCS data, foods disaggregated 

and NHANES II data 
--- ---

Table 9-29. Summary of Recommended Values for Per Capita Intake of Fruits and Vegetables 

Mean 95th Percentile Multiple Percentiles Study 

Total Fruit Intake 

3.4 g/kg-day 12 g/kg-day see Table 9-3 EPA Analysis of CSFII 

1989-91 Data 

Total Vegetable Intake 

4.3 g/kg-day 10 g/kg-day see Table 9-4 EPA Analysis of CSFII 

1989-91 Data 

Individual Fruit and Vegetables Intake 

see Table 9-5 EPA Analysis of CSFII 

1989-91 Data 
Table 9-30. Confidence in Fruit and Vegetable Intake Recommendations 

Considerations Rationale Rating 

Study Elements

 • Level of peer review USDA CSFII survey receives high level of peer High 

review. EPA analysis of these data has been 

peer reviewed outside the Agency.

 • Accessibility CSFII data are publicly available. High

 • Reproducibility Enough information is included to reproduce High 

results.

 • Focus on factor of interest Analysis is specifically designed to address High 

food intake.

 • Data pertinent to U.S. Data focuses on the U.S. population. High

 • Primary data This is new analysis of primary data. High

 • Currency Were the most current data publicly available at High 

the time the analysis was conducted for the 

Handbook.

 • Adequacy of data collection Survey is designed to collect short-term data. Medium confidence for average

 period values; 

Low confidence for long term 

percentile distribution

 • Validity of approach Survey methodology was adequate. High

 • Study size Study size was very large and therefore High 

adequate.

 • Representativeness of the The population studied was the U.S. High

 population population.

 • Characterization of variability Survey was not designed to capture long term Medium 

day-to-day variability. Short term distributions 

are provided.

 • Lack of bias in study design Response rate was adequate. Medium

 (high rating is desirable)

 • Measurement error No measurements were taken. The study N/A 

relied on survey data. 

Other Elements

 • Number of studies 1; CSFII 1989-91 was the most recent data set Low 

publicly available at the time the analysis was 

conducted for the Handbook. Therefore, it was 

the only study classified as key study.

 • Agreement between researchers Although the CSFII was the only study High 

classified as key study, the results are in good 

agreement with earlier data. 

Overall Rating The survey is representative of U.S. population. High confidence in the average; 

Although there was only one study considered Low confidence in the long-term 

key, these data are the most recent and are in upper percentiles 

agreement with earlier data. The approach 

used to analyzed the data was adequate. 

However, due to the limitations of the survey 

design estimation of long-term percentile values 

(especially the upper percentiles) is uncertain. 
Table 9A-1. Fraction of Grain and Meat Mixture Intake Represented by Various Food Items/Groups 

Grain Mixtures 

total vegetables 0.2360 

tomatoes 0.1685 

white potatoes 0.0000 

total meats 0.0787 

beef 0.0449 

pork 0.0112 

poultry 0.0112 

dairy 0.1348 

total grains 0.3146 

Meat Mixtures 

total vegetables 0.2778 

tomatoes 0.1111 

white potatoes 0.0333 

total meats 0.3556 

beef 0.2000 

pork 0.0222 

poultry 0.0778 

dairy 0.0556 

total grains 0.1333 
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data 

Food 

Product 

Food Codes 

MAJOR FOOD GROUPS 

Total Fruits 6­ Fruits (includes baby foods) 

citrus fruits and juices 

dried fruits 

other fruits 

fruits/juices & nectar 

fruit/juices baby food 

Total 

Vegetables 

7­ Vegetables (all forms) 411- Beans/legumes 

white potatoes & PR starchy 412- Beans/legumes 

dark green vegetables 413- Beans/legumes 

deep yellow vegetables (includes baby foods; mixtures, mostly vegetables; does not 

tomatoes and tom. mixtures include nuts and seeds) 

other vegetables 

veg. and mixtures/baby food 

veg. with meat mixtures 

Total Meats 20­ Meat, type not specified (excludes meat, poultry, and fish with non-meat items; frozen 

21­ Beef plate meals; soups and gravies with meat, poultry and fish 

22­ Pork base; and gelatin-based drinks; includes baby foods) 

23­ Lamb, veal, game, carcass meat 

24­ Poultry 

25­ Organ meats, sausages, lunchmeats, meat spreads 

Total Dairy 1­ Milk and Milk Products (includes regular fluid milk, human milk, imitation milk 

milk and milk drinks products, yogurt, milk-based meal replacements, and infant 

cream and cream substitutes formulas) 

milk desserts, sauces, and gravies 

cheeses 

INDIVIDUAL FOODS 

White 

Potatoes 

71­ White Potatoes and PR Starchy Veg. (does not include vegetables soups; vegetable mixtures; or 

baked, boiled, chips, sticks, creamed, scalloped, au vegetable with meat mixtures) 

gratin, fried, mashed, stuffed, puffs, salad, recipes, 

soups, Puerto Rican starchy vegetables 

Peppers 7512100 Pepper, hot chili, raw 7522606 Pepper, red, cooked, fat added 

7512200 Pepper, raw 7522609 Pepper, hot, cooked, NS as to fat added 

7512210 Pepper, sweet green, raw 7522610 Pepper, hot, cooked, fat not added 

7512220 Pepper, sweet red, raw 7522611 Pepper, hot, cooked, fat added 

7522600 Pepper, green, cooked, NS as to fat added 7551101 Peppers, hot, sauce 

7522601 Pepper, green, cooked, fat not added 7551102 Peppers, pickled 

7522602 Pepper, green, cooked, fat added 7551105 Peppers, hot pickled 

7522604 Pepper, red, cooked, NS as to fat added (does not include vegetable soups; vegetable mixtures; or 

7522605 Pepper, red, cooked, fat not added vegetable with meat mixtures) 

Onions 7510950 Chives, raw 7522102 Onions, mature cooked, fat added 

7511150 Garlic, raw 7522103 Onions, pearl cooked 

7511250 Leek, raw 7522104 Onions, young green cooked, NS as to fat 

7511701 Onions, young green, raw 7522105 Onions, young green cooked, fat not added 

7511702 Onions, mature 7522106 Onions, young green cooked, fat added 

7521550 Chives, dried 7522110 Onion, dehydrated 

7521740 Garlic, cooked 7541501 Onions, creamed 

7521840 Leek, cooked 7541502 Onion rings 

7522100 Onions, mature cooked, NS as to fat added (does not include vegetable soups; vegetable mixtures; or 

7522101 Onions, mature cooked, fat not added vegetable with meat mixtures) 
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued) 

Food 

Product 

Food Codes 

Corn 7510960 Corn, raw 7521621 Corn, cooked, white/fat not added 

7521600 Corn, cooked, NS as to color/fat added 7521622 Corn, cooked, white/fat added 

7521601 Corn, cooked, NS as to color/fat not added 7521625 Corn, white, cream style 

7521602 Corn, cooked, NS as to color/fat added 7521630 Corn, yellow, canned, low sodium, NS fat 

7521605 Corn, cooked, NS as to color/cream style 7521631 Corn, yell., canned, low sod., fat not add 

7521607 Corn, cooked, dried 7521632 Corn, yell., canned, low sod., fat added 

7521610 Corn, cooked, yellow/NS as to fat added 7521749 Hominy, cooked 

7521611 Corn, cooked, yellow/fat not added 752175­ Hominy, cooked 

7521612 Corn, cooked, yellow/fat added 7541101 Corn scalloped or pudding 

7521615 Corn, yellow, cream style 7541102 Corn fritter 

7521616 Corn, cooked, yell. & wh./NS as to fat 7541103 Corn with cream sauce 

7521617 Corn, cooked, yell. & wh./fat not added 7550101 Corn relish 

7521618 Corn, cooked, yell. & wh./fat added 76405­ Corn, baby 

7521619 Corn, yellow, cream style, fat added (does not include vegetable soups; vegetable mixtures; or 

7521620 Corn, cooked, white/NS as to fat added vegetable with meat mixtures; includes baby food) 

Apples 6210110 Apples, dried, uncooked 6310141 Apple rings, fried 

6210115 Apples, dried, uncooked, low sodium 6310142 Apple, pickled 

6210120 Apples, dried, cooked, NS as to sweetener 6310150 Apple, fried 

6210122 Apples, dried, cooked, unsweetened 6340101 Apple, salad 

6210123 Apples, dried, cooked, with sugar 6340106 Apple, candied 

6210130 Apple chips 6410101 Apple cider 

6310100 Apples, raw 6410401 Apple juice 

6310111 Applesauce, NS as to sweetener 6410405 Apple juice with vitamin C 

6310112 Applesauce, unsweetened 6410409 Apple juice with calcium 

6310113 Applesauce with sugar 6710200 Applesauce baby fd., NS as to str. or jr. 

6310114 Applesauce with low calorie sweetener 6710201 Applesauce baby food, strained 

6310121 Apples, cooked or canned with syrup 6710202 Applesauce baby food, junior 

6310131 Apple, baked NS as to sweetener 6720200 Apple juice, baby food 

6310132 Apple, baked, unsweetened (includes baby food; except mixtures) 

6310133 Apple, baked with sugar 

Tomatoes 74­ Tomatoes and Tomato Mixtures 

raw, cooked, juices, sauces, mixtures, soups, 

sandwiches 

Snap Beans 7510180 Beans, string, green, raw 7520602 Beans, string, cooked, yellow/fat 

7520498 Beans, string, cooked, NS color/fat added 7540301 Beans, string, green, creamed 

7520499 Beans, string, cooked, NS color/no fat 7540302 Beans, string, green, w/mushroom sauce 

7520500 Beans, string, cooked, NS color & fat 7540401 Beans, string, yellow, creamed 

7520501 Beans, string, cooked, green/NS fat 7550011 Beans, string, green, pickled 

7520502 Beans, string, cooked, green/no fat 7640100 Beans, green, string, baby 

7520503 Beans, string, cooked, green/fat 7640101 Beans, green, string, baby, str. 

7520511 Beans, str., canned, low sod.,green/NS fat 7640102 Beans, green, string, baby, junior 

7520512 Beans, str., canned, low sod.,green/no fat 7640103 Beans, green, string, baby, creamed 

7520513 Beans, str., canned, low sod.,green/fat (does not include vegetable soups; vegetable mixtures; or 

7520600 Beans, string, cooked, yellow/NS fat vegetable with meat mixtures; includes baby foods) 

7520601 Beans, string, cooked, yellow/no fat 

Beef 21­ Beef (excludes meat, poultry, and fish with non-meat items; frozen 

beef, nfs plate meals; soups and gravies with meat, poultry and fish 

beef steak base; and gelatin-based drinks; includes baby food) 

beef oxtails, neckbones, ribs 

roasts, stew meat, corned, brisket, sandwich steaks 

ground beef, patties, meatballs 

other beef items 

beef baby food 
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued)

Food 

Product 

Food Codes 

Pork 22­ Pork 

pork, nfs; ground dehydrated 

chops 

steaks, cutlets 

ham 

roasts 

Canadian bacon 

bacon, salt pork 

other pork items 

pork baby food 

(excludes meat, poultry, and fish with non-meat items; frozen 

plate meals; soups and gravies with meat, poultry and fish 

base; and gelatin-based drinks; includes baby food) 

Game 233- Game (excludes meat, poultry, and fish with non-meat items; frozen 

plate meals; soups and gravies with meat, poultry and fish 

base; and gelatin-based drinks) 

Poultry 24­ Poultry 

chicken 

turkey 

duck 

other poultry 

poultry baby food 

(excludes meat, poultry, and fish with non-meat items; frozen 

plate meals; soups and gravies with meat, poultry and fish 

base; and gelatin-based drinks; includes baby food) 

Eggs 3­ Eggs 

eggs 

egg mixtures 

egg substitutes 

eggs baby food 

froz. meals with egg as main ingred. 

(includes baby foods) 

Broccoli 722- Broccoli (all forms) (does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures) 

Carrots 7310­ Carrots (all forms) 

7311140 Carrots in Sauce 

7311200 Carrot Chips 

76201­ Carrots, baby 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures; includes baby foods except 

mixtures) 

Pumpkin 732­ Pumpkin (all forms) 

733­ Winter squash (all forms) 

76205­ Squash, baby 

(does not include vegetable soups; vegetables mixtures; or 

vegetable with meat mixtures; includes baby foods) 

Asparagus 7510080 Asparagus, raw 

75202­ Asparagus, cooked 

7540101 Asparagus, creamed or with cheese 

(does not include vegetable soups; vegetables mixtures, or 

vegetable with meat mixtures) 

Lima Beans 7510200 Lima Beans, raw 

752040­ Lima Beans, cooked 

752041­ Lima Beans, canned 

75402­ Lima Beans with sauce 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures; does not include succotash) 

Cabbage 7510300 Cabbage, raw 

7510400 Cabbage, Chinese, raw 

7510500 Cabbage, red, raw 

7514100 Cabbage salad or coleslaw 

7514130 Cabbage, Chinese, salad 

75210­ Chinese Cabbage, cooked 

75211­ Green Cabbage, cooked 

75212­ Red Cabbage, cooked 

752130­ Savoy Cabbage, cooked 

75230­ Sauerkraut, cooked 

7540701 Cabbage, creamed 

755025­ Cabbage, pickled or in relish 

(does not include vegetable soups; vegetable mixtures; or 

vegetable with meat mixtures) 
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued) 

Food 

Product 

Food Codes 

Lettuce 75113­ Lettuce, raw (does not include vegetable soups; vegetable mixtures; or 

75143­ Lettuce salad with other veg. vegetable with meat mixtures) 

7514410 Lettuce, wilted, with bacon dressing 

7522005 Lettuce, cooked 

Okra 7522000 Okra, cooked, NS as to fat 7541450 Okra, fried 

7522001 Okra, cooked, fat not added 7550700 Okra, pickled 

7522002 Okra, cooked, fat added (does not include vegetable soups; vegetable mixtures; or 

7522010 Lufta, cooked (Chinese Okra) vegetable with meat mixtures) 

Peas 7512000 Peas, green, raw 7541660 Pea salad with cheese 

7512775 Snowpeas, raw 75417­ Peas, with sauce or creamed 

75223­ Peas, cowpeas, field or blackeye, cooked 76409­ Peas, baby 

75224­ Peas, green, cooked 76411­ Peas, creamed, baby 

75225­ Peas, pigeon, cooked (does not include vegetable soups; vegetable mixtures; or 

75231­ Snowpeas, cooked vegetable with meat mixtures; includes baby foods except 

7541650 Pea salad mixtures) 

Cucumbers 7511100 Cucumbers, raw 7550305 Cucumber pickles, fresh 

75142­ Cucumber salads 7550307 Cucumber, Kim Chee 

752167­ Cucumbers, cooked 7550311 Cucumber pickles, dill, reduced salt 

7550301 Cucumber pickles, dill 7550314 Cucumber pickles, sweet, reduced salt 

7550302 Cucumber pickles, relish (does not include vegetable soups; vegetable mixtures; or 

7550303 Cucumber pickles, sour vegetable with meat mixtures) 

7550304 Cucumber pickles, sweet 

Beets 7510250 Beets, raw 7550021 Beets, pickled 

752080­ Beets, cooked 76403­ Beets, baby 

752081­ Beets, canned (does not include vegetable soups; vegetable mixtures; or 

7540501 Beets, harvard vegetable with meat mixtures; includes baby foods except 

mixtures) 

Strawberrie 

s 

6322­ Strawberries (includes baby food; except mixtures) 

6413250 Strawberry Juice 

Other 

Berries 

6320­ Other Berries 6410460 Blackberry Juice 

6321­ Other Berries 64105­ Cranberry Juice 

6341101 Cranberry salad (includes baby food; except mixtures) 

Peaches 62116­ Dried Peaches 67108­ Peaches ,baby 

63135­ Peaches 6711450 Peaches, dry, baby 

6412203 Peach Juice (includes baby food; except mixtures) 

6420501 Peach Nectar 

Pears 62119­ Dried Pears 67109­ Pears, baby 

63137­ Pears 6711455 Pears, dry, baby 

6341201 Pear salad 6721200 Pear juice, baby 

6421501 Pear Nectar (includes baby food; except mixtures) 
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued) 

Food Food Codes 

Product 

EXPOSED/PROTECTED FRUITS/VEGETABLES, ROOT VEGETABLES 

Exposed 

Fruits 

621011­

621012­

6210130 

62104­

62108­

62110­

62116­

62119­

62121­

62122­

Apple, dried 63143­ Plum 

Apple, dried 63146­ Quince 

Apple chips 63147- Rhubarb/Sapodillo 

Apricot, dried 632­ Berries 

Currants, dried 64101­ Apple Cider 

Date, dried 64104­ Apple Juice 

Peaches, dried 6410409 Apple juice with calcium 

Pears, dried 64105­ Cranberry Juice 

Plum, dried 64116­ Grape Juice 

Prune, dried 64122­ Peach Juice 

62125­

63101­

63102­

63103­

63111­

63112­

63113­

63115­

63117­

63123­

6312601 

63131­

63135­

63137­

63139­

Raisins 64132- Prune/Strawberry Juice 

Apples/applesauce 6420101 Apricot Nectar 

Wi-apple 64205­ Peach Nectar 

Apricots 64215­ Pear Nectar 

Cherries, maraschino 67102­ Applesauce, baby 

Acerola 67108­ Peaches, baby 

Cherries, sour 67109­ Pears, baby 

Cherries, sweet 6711450 Peaches, baby, dry 

Currants, raw 6711455 Pears, baby, dry 

Grapes 67202­ Apple Juice, baby 

Juneberry 6720380 White Grape Juice, baby 

Nectarine 67212­ Pear Juice, baby 

Peach (includes baby foods/juices except mixtures; excludes 

Pear fruit mixtures) 

Persimmons 

Protected 

Fruits 

61­

62107­

62113­

62114­

62120­

62126­

63105­

63107­

Citrus Fr., Juices (incl. cit. juice mixtures) 63145­ Pomegranate 

Bananas, dried 63148­ Sweetsop, Soursop, Tamarind 

Figs, dried 63149­ Watermelon 

Lychees/Papayas, dried 64120­ Papaya Juice 

Pineapple, dried 64121­ Passion Fruit Juice 

Tamarind, dried 64124­ Pineapple Juice 

Avocado, raw 64125­ Pineapple juice 

Bananas 64133­ Watermelon Juice 

63109­

63110­

63119­

63121­

63125­

6312650 

Cantaloupe, Carambola 6420150 Banana Nectar 

Cassaba Melon 64202­ Cantaloupe Nectar 

Figs 64203­ Guava Nectar 

Genip 64204­ Mango Nectar 

Guava/Jackfruit, raw 64210­ Papaya Nectar 

Kiwi 64213­ Passion Fruit Nectar 

6312651 

6312660 

63127­

63129­

63133­

63134­

63141­

Lychee, raw 64221­ Soursop Nectar 

Lychee, cooked 6710503 Bananas, baby 

Honeydew 6711500 Bananas, baby, dry 

Mango 6720500 Orange Juice, baby 

Papaya 6721300 Pineapple Juice, baby 

Passion Fruit (includes baby foods/juices except mixtures; excludes fruit 

Pineapple mixtures) 
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued) 

Food Food Codes 

Product 

Exposed 

Veg. 

721­ Dark Green Leafy Veg. 752167­ Cucumber, cooked 

722­ Dark Green Nonleafy Veg. 752170­ Eggplant, cooked 

74­ Tomatoes and Tomato Mixtures 752171­ Fern shoots 

7510050 Alfalfa Sprouts 752172­ Fern shoots 

7510075 Artichoke, Jerusalem, raw 752173­ Flowers of sesbania, squash or lily 

7510080 Asparagus, raw 7521801 Kohlrabi, cooked 

75101­ Beans, sprouts and green, raw 75219­ Mushrooms, cooked 

7510260 Broccoflower, raw 75220- Okra/lettuce, cooked 

7510275 Brussel Sprouts, raw 7522116 Palm Hearts, cooked 

7510280 Buckwheat Sprouts, raw 7522121 Parsley, cooked 

7510300 Cabbage, raw 75226­ Peppers, pimento, cooked 

7510400 Cabbage, Chinese, raw 75230­ Sauerkraut, cooked/canned 

7510500 Cabbage, Red, raw 75231­ Snowpeas, cooked 

7510700 Cauliflower, raw 75232­ Seaweed 

7510900 Celery, raw 75233­ Summer Squash 

7510950 Chives, raw 7540050 Artichokes, stuffed 

7511100 Cucumber, raw 7540101 Asparagus, creamed or with cheese 

7511120 Eggplant, raw 75403­ Beans, green with sauce 

7511200 Kohlrabi, raw 75404­ Beans, yellow with sauce 

75113­ Lettuce, raw 7540601 Brussel Sprouts, creamed 

7511500 Mushrooms, raw 7540701 Cabbage, creamed 

7511900 Parsley 75409­ Cauliflower, creamed 

7512100 Pepper, hot chili 75410- Celery/Chiles, creamed 

75122­ Peppers, raw 75412­ Eggplant, fried, with sauce, etc. 

7512750 Seaweed, raw 75413­ Kohlrabi, creamed 

7512775 Snowpeas, raw 75414­ Mushrooms, Okra, fried, stuffed, creamed 

75128­ Summer Squash, raw 754180­ Squash, baked, fried, creamed, etc. 

7513210 Celery Juice 7541822 Christophine, creamed 

7514100 Cabbage or cole slaw 7550011 Beans, pickled 

7514130 Chinese Cabbage Salad 7550051 Celery, pickled 

7514150 Celery with cheese 7550201 Cauliflower, pickled 

75142­ Cucumber salads 755025­ Cabbage, pickled 

75143­ Lettuce salads 7550301 Cucumber pickles, dill 

7514410 Lettuce, wilted with bacon dressing 7550302 Cucumber pickles, relish 

7514600 Greek salad 7550303 Cucumber pickles, sour 

7514700 Spinach salad 7550304 Cucumber pickles, sweet 

7520060 Algae, dried 7550305 Cucumber pickles, fresh 

75201­ Artichoke, cooked 7550307 Cucumber, Kim Chee 

75202­ Asparagus, cooked 7550308 Eggplant, pickled 

75203­ Bamboo shoots, cooked 7550311 Cucumber pickles, dill, reduced salt 

752049­ Beans, string, cooked 7550314 Cucumber pickles, sweet, reduced salt 

75205­ Beans, green, cooked/canned 7550500 Mushrooms, pickled 

75206­ Beans, yellow, cooked/canned 7550700 Okra, pickled 

75207­ Bean Sprouts, cooked 75510­ Olives 

752085­ Breadfruit 7551101 Peppers, hot 

752087­ Broccoflower, cooked 7551102 Peppers,pickled 

752090­ Brussel Sprouts, cooked 7551104 Peppers, hot pickled 

75210­ Cabbage, Chinese, cooked 7551301 Seaweed, pickled 

75211­ Cabbage, green, cooked 7553500 Zucchini, pickled 

75212­ Cabbage, red, cooked 76102­ Dark Green Veg., baby 

752130­ Cabbage, savoy, cooked 76401­ Beans, baby (excl. most soups & mixtures) 

75214­ Cauliflower 411- Beans/legumes 

75215­ Celery, Chives, Christophine (chayote) 412- Beans/legumes 

413- Beans/legumes 
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued) 

Food Food Codes 

Product 

Protected 

Veg. 

732­ Pumpkin 752175­ Hominy 

733­ Winter Squash 75223­ Peas, cowpeas, field or blackeye, cooked 

7510200 Lima Beans, raw 75224­ Peas, green, cooked 

7510550 Cactus, raw 75225­ Peas, pigeon, cooked 

7510960 Corn, raw 75301­ Succotash 

7512000 Peas, raw 75402­ Lima Beans with sauce 

7520070 Aloe vera juice 75411­ Corn, scalloped, fritter, with cream 

752040­ Lima Beans, cooked 7541650 Pea salad 

752041­ Lima Beans, canned 7541660 Pea salad with cheese 

7520829 Bitter Melon 75417­ Peas, with sauce or creamed 

752083­ Bitter Melon, cooked 7550101 Corn relish 

7520950 Burdock 76205­ Squash, yellow, baby 

752131­ Cactus 76405­ Corn, baby 

752160­ Corn, cooked 76409­ Peas, baby 

752161­ Corn, yellow, cooked 76411­ Peas, creamed, baby 

752162­ Corn, white, cooked (does not include vegetable soups; vegetable mixtures; or 

752163­ Corn, canned vegetable with meat mixtures) 

7521749 Hominy 

Root 

Vegetables 

71­ White Potatoes and Puerto Rican St. Veg. 7522110 Onions, dehydrated 

7310­ Carrots 752220­ Parsnips, cooked 

7311140 Carrots in sauce 75227­ Radishes, cooked 

7311200 Carrot chips 75228­ Rutabaga, cooked 

734­ Sweetpotatoes 75229­ Salsify, cooked 

7510250 Beets, raw 75234­ Turnip, cooked 

7511150 Garlic, raw 75235­ Water Chestnut 

7511180 Jicama (yambean), raw 7540501 Beets, harvard 

7511250 Leeks, raw 75415­ Onions, creamed, fried 

75117­ Onions, raw 7541601 Parsnips, creamed 

7512500 Radish, raw 7541810 Turnips, creamed 

7512700 Rutabaga, raw 7550021 Beets, pickled 

7512900 Turnip, raw 7550309 Horseradish 

752080­ Beets, cooked 7551201 Radishes, pickled 

752081­ Beets, canned 7553403 Turnip, pickled 

7521362 Cassava 76201­ Carrots, baby 

7521740 Garlic, cooked 76209­ Sweetpotatoes, baby 

7521771 Horseradish 76403­ Beets, baby 

7521840 Leek, cooked (does not include vegetable soups; vegetable mixtures; or 

7521850 Lotus root vegetable with meat mixtures) 

752210­ Onions, cooked 

USDA SUBCATEGORIES 

Dark Green 72­ Dark Green Vegetables 

Vegetables all forms 

leafy, nonleafy, dk. gr. veg. soups 

Deep 73­ Deep Yellow Vegetables 

Yellow all forms 

Vegetables carrots, pumpkin, squash, sweetpotatoes, dp. yell. 

veg. soups 

Other 75­ Other Vegetables 

Vegetables all forms 

Citrus Fruits 61­ Citrus Fruits and Juices 6720700 Orange-Pineapple Juice, baby food 

6720500 Orange Juice, baby food 6721100 Orange-Apple-Banana Juice, baby food 

6720600 Orange-Apricot Juice, baby food (excludes dried fruits) 
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued) 

Food Food Codes 

Product 

Other Fruits 62­ Dried Fruits 67204­ Baby Juices 

63­ Other Fruits 67212­ Baby Juices 

64­ Fruit Juices and Nectars Excluding Citrus 67213­ Baby Juices 

671­ Fruits, baby 6725- Baby Juice 

67202­ Apple Juice, baby 673­ Baby Fruits 

67203­ Baby Juices 674­ Baby Fruits 

MIXTURES 

Meat 27­ Meat Mixtures (includes frozen plate meals and soups) 

Mixtures 28­

Grain 

Mixtures 

58­ Grain Mixtures (includes frozen plate meals and soups) 
Table 10-1. Total Fish Consumption by

 Demographic Variablesa 

Demographic Category 

Intake (g/person/day) 

Mean 95th Percentile 

Race 

Caucasian 14.2 41.2 

Black 16.0 45.2 

Oriental 21.0 67.3 

Other 13.2 29.4 

Sex 

Female 13.2 38.4 

Male 15.6 44.8 

Age (years) 

0-9 6.2 16.5 

10-19 10.1 26.8 

20-29 14.5 38.3 

30-39 15.8 42.9 

40-49 17.4 48.1 

50-59 20.9 53.4 

60-69 21.7 55.4 

70+ 13.3 39.8 

Census Region 

New England 16.3 46.5 

Middle Atlantic 16.2 47.8 

East North Central 12.9 36.9 

West North Central 12.0 35.2 

South Atlantic 15.2 44.1 

East South Central 13.0 38.4 

West South Central 14.4 43.6 

Mountain 12.1 32.1 

Pacific 14.2 39.6 

Community Type 

Rural, non-SMSA 13.0 38.3 

Central city, 2M or more 19.0 55.6 

Outside central city, 2M or more 15.9 47.3 

Central city, 1M - 2M 15.4 41.7 

Outside central city, 1M - 2M 14.5 41.5 

Central city, 500K - 1M 14.2 41.0 

Outside central city, 500K - 1M 14.0 39.7 

Outside central city, 250K - 500K 12.2 32.1 

Central city, 250K - 500K 14.1 40.5 

Central city, 50K - 250K 13.8 43.4 

Outside central city, 50K - 250K 11.3 31.7 

Other urban 13.5 39.2 

The calculations in this table are based on respondents who consumed fish during the survey month. These a 

respondents are estimated to represent 94 percent of the U.S. population. 

Source: Javitz, 1980. 
Table 10-2. Mean and 95th Percentile of Fish 

Consumption (g/day) by Sex and Agea 

Total Fish 

Age (years) Mean 95th Percentile 

Female 0 - 9 6.1 17.3 

10 - 19 9.0 25.0 

20 - 19 13.4 34.5 

30 - 39 14.9 41.8 

40 - 49 16.7 49.6 

50 - 59 19.5 50.1 

60 - 69 19.0 46.3 

70+ 10.7 31.7 

Male 0 - 9 6.3 15.8 

10 - 19 11.2 29.1 

20 - 19 16.1 43.7 

30 - 39 17.0 45.6 

40 - 49 18.2 47.7 

50 - 59 22.8 57.5 

60 - 69 24.4 61.1 

70+ 15.8 45.7 

Overall 14.3 41.7 

The calculations in this table are based upon respondents who consumed fish in the month of the survey. a 

These respondents are estimated to represent 94.0% of the U.S. population. 

Source: Javitz, 1980. 
Table 10-3. Percent Distribution of Total Fish Consumption for Females by Agea 

Consumption Category (g/day) 

0.0-5.0 5.1-10.0 10.1-15.0 15.1-20.0 20.1-25.0 25.1-30.0 30.1-37.5 37.6-47.5 47.6-60.0 60.1-122.5 over 122

Age (yrs) Percentage 

0-9 55.5 26.8 11.0 3.7 1.0 1.1 0.7 0.3 0.0 0.0 0.0 

10-19 17.8 31.4 15.4 6.9 3.5 2.4 1.2 0.7 0.2 0.4 0.0 

20-29 28.1 26.1 20.4 11.8 6.7 3.5 4.4 2.2 0.9 0.9 0.0 

30-39 22.4 23.6 18.0 12.7 8.3 4.8 3.8 2.8 1.9 1.7 0.1 

40-49 17.5 21.9 20.7 13.2 9.3 4.5 4.6 2.8 3.4 2.1 0.2 

50-59 17.0 17.4 16.8 15.5 10.5 8.5 6.8 5.2 4.2 2.0 0.2 

60-69 11.5 16.9 20.6 15.9 9.1 9.2 6.0 6.1 2.4 2.1 0.2 

70+ 41.9 22.1 12.3 9.7 5.2 2.9 2.6 1.2 0.8 1.2 0.1 

Overall 28.9 24.0 16.8 10.7 6.4 4.3 3.5 2.4 1.6 1.2 0.1 

a The percentage of females in an age bracket whose average daily fish consumption is within the specified range. 

The calculations in this table are based upon the respondents who consumed fish during the month of the survey. These respondents are estimated to represent 94% of the 

U.S. population.

Source: Javitz, 1980. 
Table 10-4. Percent Distribution of Total Fish Consumption for Males by Agea 

Consumption Category (g/day) 

0.0-5.0 5.1-10.0 10.1-15.0 15.1-20.0 20.1-25.0 25.1-30.0 30.1-37.5 37.6-47.5 47.6-60.0 60.1-122.5 over 122.

Age (yrs) Percentage 

0-9 52.1 30.1 11.9 3.1 1.2 0.6 0.7 0.1 0.2 0.1 0.0 

10-19 27.8 29.3 19.0 10.4 6.0 3.2 1.7 1.7 0.4 0.5 0.0 

20-29 16.7 22.9 19.6 14.5 8.8 6.2 4.4 3.1 1.9 1.9 0.1 

30-39 16.6 21.2 19.2 13.2 9.5 7.3 5.2 3.2 1.3 2.2 0.0 

40-49 11.9 22.3 18.6 14.7 8.4 8.5 5.3 5.2 3.3 1.7 0.1 

50-59 9.9 15.2 15.4 14.4 10.4 9.7 8.7 7.6 4.3 4.1 0.2 

60-69 7.4 15.0 15.6 12.8 11.4 8.5 9.9 8.3 5.5 5.5 0.1 

70+ 24.5 21.7 15.7 9.9 9.8 5.3 5.4 3.1 1.7 2.8 0.1 

Overall 22.6 23.1 17.0 11.3 7.7 5.7 4.6 3.6 2.2 2.1 0.1 

a The percentage of males in an age bracket whose average daily fish consumption is within the specified range. 

The calculations in this table are based upon respondents who consumed fish during the month of the survey. These respondents are estimated to represent 94% of the U.S

population. 

Source: Javitz, 1980. 
Table 10-5. Mean Total Fish Consumption by Speciesa 

Species (g/day) 

Mean consumption 

Species (g/day) 

Mean consumption 

Not reported 

Abalone 

Anchovies 

Bassb 

Bluefish 

Bluegillsb 

Bonitob 

Buffalofish 

Butterfish 

Carpb 

Catfish (Freshwater)b 

Catfish (Marine)b 

Clamsb 

Cod 

Crab, King 

Crab, other than Kingb 

Crappieb 

Croakerb 

Dolphinb 

Drums 

Floundersb 

Groupers 

Haddock 

Hake 

Halibutb 

Herring 

Kingfish 

Lobster (Northern)b 

Lobster (Spiny) 

Mackerel, Jack 

Mackerel, other than Jack 

1.173 

0.014 

0.010 

0.258 

0.070 

0.089 

0.035 

0.022 

0.010 

0.016 

0.292 

0.014 

0.442 

0.407 

0.030 

0.254 

0.076 

0.028 

0.012 

0.019 

1.179 

0.026 

0.399 

0.117 

0.170 

0.224 

0.009 

0.162 

0.074 

0.002 

0.172 

Mullet 

Oysters 

Perch (Freshwater) 

Perch (Marine) 

Pike (Marine) 

Pollock 

Pompano 

Rockfish 

Sablefish 

Salmon 

Scallops 

Scup 

Sharks 

Shrimp 

Smelt 

Snapper 

Snook 

Spot 

Squid and Octopi 

Sunfish 

Swordfish 

Tilefish 

Trout (Freshwater) 

Trout (Marine) 

Tuna, light 

Tuna, White Albacore 

Whitefish 

Other finfish 

Other shellfish 

b 

b 

b 

b 

b 

b 

b 

b 

b 

b 

b 

b 

b 

b 

b 

b 

0.029 

0.291 

0.062 

0.773 

0.154 

0.266 

0.004 

0.027 

0.002 

0.533 

0.127 

0.014 

0.001 

1.464 

0.057 

0.146 

0.005 

0.046 

0.016 

0.020 

0.012 

0.003 

0.294 

0.070 

3.491 

0.008 

0.141 

0.403 

0.013 

The calculations in this table are based upon respondents who consumed fish during the month of the survey. These a 

respondents are estimated to represent 94% percent of the U.S. population. 

Designated as freshwater or estuarine species by Stephan (1980). b 

Source: Javitz, 1980. 
Table 10-6. Best Fits of Lognormal Distributions Using the NonLinear Optimization (NLO) Method

Adults Teenagers Children

Shellfish

F 1.370 -0.183 0.854

F 0.858 1.092 0.730

(min SS) 27.57 1.19 16.06

Finfish (freshwater)

F 0.334 0.578 -0.559

F 1.183 0.822 1.141

(min SS) 6.45 23.51 2.19

Finfish (saltwater)

F 2.311 1.691 0.881

F 0.72 0.830 0.970

(min SS) 30.13 0.33 4.31

The following equations may be used with the appropriate F and F values to obtain an average Daily Consumption Rate (DCR), in

grams, and percentiles of the DCR distribution. 

DCR50 = exp (F)

DCR90 = exp [F + z(0.90) @ F]

DCR99 = exp [F + z(0.99) @ F]

DCR = exp [F + 0.5 @ F ] avg

2

Source: Ruffle et al., 1994.
Table 10-7. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S. Population 

(Uncooked Fish Weight) 

Estimate (90% Interval) 

Habitat Statistic Finfish Shellfish Total 

Fresh/Estuarine Mean 

50th% 

90th% 

95th% 

99th% 

3.6 (3.0 - 4.1) 

0.0 (0.0 - 0.0) 

0.4 (0.00 - 0.7) 

21.7 (14.8 - 25.8) 

87.3 (80.1 - 98.0) 

2.4 (2.0 - 2.8) 

0.0 (0.0 - 0.0) 

0.0 (0.0 - 0.3) 

13.3 (11.7 - 17.8) 

63.6 (60.4 - 68.5) 

6.0 (5.3 - 6.7) 

0.0 (0.0 - 0.0) 

15.9 (14.4 - 17.8) 

40.0 (37.9 - 44.8) 

107.6 (98.3 - 109.1) 

Marine Mean 

50th% 

90th% 

95th% 

99th% 

12.5 (11.5 - 13.5) 

0.0 (0.0 - 0.0) 

47.5 (43.6 - 49.8) 

74.6 (70.3 - 76.3) 

133.0 (127.8 - 143.2) 

1.6 (1.3 - 1.9) 

0.0 (0.0 - 0.0) 

0.0 (0.0 - 0.0) 

0.0 (0.0 - 6.8) 

50.3 (44.5 - 59.0) 

14.1 (13.1 - 15.1) 

0.0 (0.0 - 0.0) 

52.1 (47.8 - 55.9) 

76.5 (74.6 - 80.9) 

138.2 (133.0 - 155.1) 

All Fish Mean 

50th% 

90th% 

95th% 

99th% 

16.1 (15.0 - 17.2) 

0.0 (0.0 - 0.0) 

59.1 (54.6 - 62.3) 

84.4 (81.3 - 89.6) 

156.7 (148.7 - 168.1) 

4.0 (3.4 - 4.6) 

0.0 (0.0 - 0.0) 

0.0 (0.0 - 3.5) 

22.7 (21.8 - 26.6) 

99.0 (87.8 - 109.6) 

20.1 (18.8 - 21.4) 

0.0 (0.0 - 0.0) 

70.1 (65.4 - 74.2) 

102.0 (99.3 - 106.7) 

173.2 (162.8 - 176.5) 

Note: Percentile confidence intervals estimated using the bootstrap method with 1,000 replications; percent consuming gives the 

percentage of individuals consuming the specified category of fish during the 3-day survey period. Estimates are projected from a 

sample of 11,912 individuals to the U.S. population. 

Source: U.S. EPA, 1996a. 
Table 10-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) by Habitat for Consumers Only

(Uncooked Fish Weight)

Habitat Statistic Estimate 90% Interval

Fresh/Estuarine Mean 86.2 78.4 - 94.0 a

50th% 48.8 45.6 - 54.9

90th% 217.9 205.3 - 237.3

95th% 290.0 267.1 - 325.6

99th% 489.3 424.9 - 534.2

Percent Consuming 18.5

Marine Mean 113.1 107.8 - 118.4 b

50th% 93.3 92.0 - 94.9

90th% 222.7 216.5 - 225.6

95th% 271.7 260.6 - 279.9

99th% 415.9 367.3 - 440.5

Percent Consuming 30.1

All Fish Mean 129.0 123.7 - 134.3 c

50th% 101.9 98.9 - 103.9

90th% 249.1 241.0 - 264.1

95th% 326.0 306.1 - 335.6

99th% 497.5 469.2 - 519.7

Percent Consuming 36.9

Note: Percentile confidence intervals estimated using the bootstrap method with 1,000 replications; percent consuming gives the

percentage of individuals consuming the specified category of fish during the 3-day survey period.

a Sample size = 1,892; population size = 44,946,000

b Sample size = 3,184; population size = 73,100,000

c Sample size = 3,927; population size = 89,800,000

Source: U.S. EPA, 1996a.
Table 10-9. Per Capita Distribution of Fish Intake (mg/kg-day) by Habitat and Fish Type for U.S. Population 

(Uncooked Fish Weight) 

Estimate (90% Interval) 

Habitat Statistic Finfish Shellfish Total 

Fresh/Estuarin 

e 

Mean 

50th% 

90th% 

95th% 

99th% 

58.1 (48.4 - 67.7) 

0.0 (0.0 - 0.0) 

5.9 (0.0 - 12.3) 

340.5 (252.9 - 410.1) 

1,401.9 (1,283.9 - 1,511.8) 

35.9 (30.2 - 41.6) 

0.0 (0.0 - 0.0) 

0.0 (0.0 - 3.8) 

190.0 (155.7 - 268.3) 

953.5 (871.3 - 1,007.4) 

94.0 (83.4 - 104.6) 

0.0 (0.0 - 0.0) 

251.8 (222.5 - 282.6) 

677.7 (631.9 - 729.1) 

1,593.3 (1,511.8 - 1,659.2) 

Marine Mean 

50th% 

90th% 

95th% 

99th% 

215.8 (195.9 - 235.6) 

0.0 (0.0 - 0.0) 

783.4 (752.5 - 842.2) 

1,208.1 (1,149.5 - 1,264.9) 

2,400.0 (2,284.2 - 2,660.1) 

24.3 (20.6 - 28.0) 

0.0 (0.0 - 0.0) 

0.0 (0.0 - 0.0) 

0.0 (0.0 - 88.8 

701.3 (636.2 - 944.7) 

240.1 (220.1 - 260.0) 

0.0 (0.0 - 0.0) 

855.6 (809.7 - 909.8) 

1,271.5 (1,227.2 - 1,371.2) 

2,575.3 (2,393.2 - 2,708.6) 

All Fish Mean 

50th% 

90th% 

95th% 

99th% 

273.9 (252.0 - 295.7) 

0.0 (0.0 - 0.0) 

966.1 (893.3 - 1,039.5) 

1,434.3 (1,371.2 - 1,526.8) 

2,857.5 (2,649.6 - 3,003.6) 

60.2 (52.3 - 68.2) 

0.0 (0.0 - 0.0) 

0.0 (0.0 - 47.4) 

372.5 (324.1 - 460.5) 

1,412.4 (1,296.0 - 1,552.1) 

334.1 (311.3 - 356.9) 

0.0 (0.0 - 0.0) 

1,123.1 (1,090.8 - 1,179.0) 

1,684.2 (1,620.5 - 1,718.5) 

3,092.8 (2,973.7 - 3,250.2) 

Note: Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Estimates are 

projected from a sample of 11,912 individuals to the U.S. population. 

Source: U.S. EPA, 1996a. 
Table 10-10. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) by Habitat for Consumers Only

(Uncooked Fish Weight)

Habitat Statistic Estimate 90% Interval

Fresh/Estuarine Mean 1,363.4 1,242.2 - 1,484.7 a

50th% 819.7 736.9 - 895.7

90th% 3,325.1 3,232.6 - 3,677.0

95th% 4,408.2 4,085.6 - 4,781.3

99th% 7,957.5 6,979.2 - 8,921.0

Percent Consuming 18.5

Marine Mean 1,927.0 1,829.5 - 2,024.4 b

50th% 1,507.7 1,470.7 - 1,538.8

90th% 3,752.9 3,632.0 - 4,001.2

95th% 5,018.7 4,852.1 - 5,267.3

99th% 8,448.3 7,215.7 - 9,136.9

Percent Consuming 30.1

All Fish Mean 2,145.3 2,055.9 - 2,234.6 c

50th% 1,662.8 1,610.7 - 1,720.1

90th% 4,223.9 4,085.8 - 4,454.2

95th% 5,477.9 5,163.3 - 5,686.0

99th% 9,171.5 8,605.4 - 9,796.6

Percent Consuming 36.9

Note: Percentile confidence intervals estimated using the bootstrap method with 1,000 replications; percent consuming gives the

percentage of individuals consuming the specified category of fish during the 3-day survey period.

a Sample size = 1,892; population size = 44,946,000

b Sample size = 3,184; population size = 73,100,000

c Sample size = 3,927; population size = 89,800,000

Source: U.S. EPA, 1996a.
Table 10-11. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S. Population 

(Cooked Fish Weight - As Consumed) 

Estimate (90% Interval) 

Habitat Statistic Finfish Shellfish Total 

Fresh/Estuarine Mean 2.8 (2.4 - 3.3) 1.9 (1.6 - 2.2) 4.7 (4.2 - 5.3) 

50th% 0.0 (0.0 - 0.0) 0.0 (0.0 - 0.0) 0.0 (0.0 - 0.0) 

90th% 0.3 (0.0 - 0.7) 0.0 (0.0 - 0.2) 12.6 (10.9 - 14.0) 

95th% 17.2 (12.9 - 20.8) 10.1 (7.9 - 13.8) 32.2 (29.8 - 35.2) 

99th% 70.9 (60.3 - 75.7) 49.9 (45.6 - 56.4) 82.5 (77.2 - 86.4) 

Marine Mean 9.7 (9.0 - 10.5) 1.2 (1.0 - 1.4) 10.9 (10.1 - 11.7) 

50th% 0.0 (0.0 - 0.0) 0.0 (0.0 - 0.0) 0.0 (0.0 - 0.0) 

90th% 37.3 (33.7 - 37.4) 0.0 (0.0 - 0.0) 39.5 (37.3 - 42.9) 

95th% 56.2 (55.6 - 58.2) 0.0 (0.0 - 5.3) 59.6 (57.0 - 61.8) 

99th% 103.1 (98.5 - 112.0) 37.0 (35.4 - 44.5) 106.8 (104.6 - 114.6) 

All Fish Mean 12.6 (11.7 - 13.4) 3.1 (2.7 - 3.5) 15.7 (14.7 - 16.6) 

50th% 0.0 (0.0 - 0.0) 0.0 (0.0 - 0.0) 0.0 (0.0 - 0.-0) 

90th% 46.0 (43.6 - 49.0) 0.0 (0.0 - 2.6) 55.0 (51.4 - 56.0) 

95th% 67.0 (63.0 - 70.7) 18.9 (16.7 - 22.1) 78.3 (75.2 - 80.6) 

99th% 119.1 (113.9 - 125.9) 74.3 (68.7 - 82.0) 133.5 (125.3 - 140.2) 

Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Estimates are projected 

from a sample of 11,912 individuals to the U.S. population. 

Source: U.S. EPA, 1996a. 
Table 10-12. Per Capita Distribution of Fish Intake (g/day) by Habitat for Consumers Only

(Cooked Fish Weight - As Consumed)

Habitat Statistic Estimate 90% Interval

Fresh/Estuarine Mean 68.0 61.9 - 74.1 a

50th% 39.5 36.2 - 44.7

90th% 170.8 158.7 - 181.8

95th% 224.8 212.9 - 246.0

99th% 374.7 336.5 - 341.3

Percent Consuming 18.5

Marine Mean 87.8 83.7 - 91.8 b

50th% 71.8 69.7 - 74.2

90th% 169.4 167.0 - 173.7

95th% 208.5 198.1 - 221.7

99th% 320.4 292.8 - 341.9

Percent Consuming 30.1

All Fish Mean 100.6 96.7 - 104.6 c

50th% 80.8 79.3 - 83.9

90th% 197.4 188.7 - 205.1

95th% 253.4 231.5 - 264.5

99th% 371.6 359.3 - 401.6

Percent Consuming 36.9

Note: Percentile confidence intervals estimated using the bootstrap method with 1,000 replications; percent consuming gives the

percentage of individuals consuming the specified category of fish during the 3-day survey period.

a Sample size = 1,892; population size = 44,946,000

b Sample size = 3,184; population size = 73,100,000

c Sample size = 3,927; population size = 89,800,000

Source: U.S. EPA, 1996a.
Table 10-13. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for the U.S. Population by Age and Gender - As Consumed 

(Freshwater and Estuarine) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 

15 - 44 

45 or older 

All ages 

1431 1.58 (1.06-2.10) 1.44 (0.00-4.07) 12.51 (6.00-14.20) 36.09 (28.53-43.20) 

2891 4.28 (3.55-5.02) 10.90 (8.79-13.84) 28.80 (26.26-33.53) 70.87 (64.74-90.56) 

2340 5.27 (4.21-6.32) 18.72 (15.19-22.12) 34.67 (29.17-39.38) 85.35 (71.71-100.50) 

6662 4.02 (3.43-4.61) 10.66 (8.11-13.19) 28.11 (23.14-31.27) 71.98 (60.38-86.40) 

Males 

14 or under 

15 - 44 

45 or older 

All ages 

1546 2.17 (1.32-3.02) 0.99 (0.21-6.67) 14.94 (11.88-22.33) 48.72 (37.48-52.29) 

2151 6.14 (5.08-7.19) 18.19 (10.21-24.20) 48.61 (35.42-54.65) 96.32 (85.60-115.75) 

1553 7.12 (5.87-8.38) 22.67 (19.28-27.83) 46.62 (41.27-58.01) 103.07 (86.41-125.11) 

5250 5.46 (4.81-6.11) 16.05 (12.41-19.30) 40.29 (35.92-43.73) 86.40 (78.37-103.07) 

Both Sexes 

14 or under 

15 - 44 

45 or older 

All ages 

2977 1.88 (1.36-2.40) 1.31 (0.00-4.33) 13.90 (9.32-15.05) 40.77 (35.15-44.82) 

5042 5.17 (4.46-5.87) 13.88 (12.05-17.21) 36.21 (28.64-47.31) 86.14 (74.67-96.67) 

3893 6.11 (5.20-7.02) 21.48 (16.69-23.33) 40.55 (35.80-47.31) 88.18 (85.33-103.07) 

11912 4.71 (4.17-5.25) 12.62 (10.91-13.98) 32.16 (29.81-35.15) 82.45 (77.17-86.40) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Source: U.S. EPA, 1996a. 
Table 10-14. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day)

 for the U.S. Population by Age and Gender - As Consumed 

(Marine) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 

15 - 44 

45 or older 

All ages 

1431 6.60 (5.16-8.05) 24.84 (18.67-31.20) 37.32 (32.27-42.05) 87.05 (63.26-112.06) 

2891 9.97 (8.94-11.01) 36.83 (31.42-41.99) 55.53 (47.67-59.59) 105.32 (96.98-112.00) 

2340 12.59 (11.36-13.82) 42.92 (38.92-47.66) 63.85 (57.27-72.36) 103.08 (91.61-121.52) 

6662 10.10 (9.27-10.93) 36.97 (34.86-37.33) 55.54 (51.67-56.98) 102.01 (97.67-110.69) 

Males 

14 or under 

15 - 44 

45 or older 

All ages 

1546 7.25 (5.72-8.79) 24.85 (19.92-33.85) 49.89 (42.09-56.45) 92.64 (65.87-132.39) 

2151 13.33 (11.89-14.77) 52.73 (48.34-55.80) 71.49 (63.99-80.00) 116.51 (106.06-143.31) 

1553 13.32 (11.73-14.92) 50.39 (47.13-53.33) 64.51 (61.64-74.58) 116.86 (106.93-144.94) 

5250 11.85 (10.75-12.95) 47.13 (44.52-49.80) 64.50 (62.46-67.53) 113.94 (103.47-130.00) 

Both Sexes 

14 or under 

15 - 44 

45 or older 

All ages 

2977 6.93 (5.63-8.23) 24.88 (22.64-28.08) 42.07 (38.15-48.96) 91.64 (68.59-112.06) 

5042 11.58 (10.55-12.60) 44.24 (39.84-46.70) 62.18 (57.88-69.72) 110.07 (103.50-120.49) 

3893 12.92 (11.86-13.98) 46.51 (38.98-50.97) 64.19 (60.67-72.00) 113.33 (104.59-119.53) 

11912 10.94 (10.14-11.73) 39.51 (37.29-42.91) 59.62 (57.03-61.84) 106.84 (104.59-114.55) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Source: U.S. EPA, 1996a. 
Table 10-15. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for the U.S. Population by Age and Gender - As Consumed 

(All Fish) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 

15 - 44 

45 or older 

All ages 

1431 8.19 (6.53-9.84) 32.28 (26.78-37.33) 43.09 (37.99-51.55) 95.19 (63.26-113.96) 

2891 14.25 (12.96-15.55) 47.13 (41.95-55.83) 71.58 (64.74-82.11) 120.84 (110.69-132.79) 

2340 17.86 (16.19-19.52) 56.70 (54.13-62.99) 81.94 (74.63-88.23) 130.51 (122.02-140.21) 

6662 14.13 (13.07-15.18) 46.44 (43.63-49.67) 70.23 (67.27-73.91) 120.22 (112.06-126.07) 

Males 

14 or under 

15 - 44 

45 or older 

All ages 

1546 9.42 (7.60-11.25) 34.85 (27.77-42.09) 52.85 (49.93-62.50) 98.36 (71.74-132.39) 

2151 19.46 (17.75-21.18) 68.60 (65.74-74.70) 93.65 (85.60-96.96) 149.07 (142.73-154.41) 

1553 20.45 (18.41-22.49) 64.44 (61.33-69.27) 87.21 (85.33-100.19) 168.49 (143.78-174.55) 

5250 17.31 (16.04-18.59) 60.23 (56.91-62.99) 85.69 (80.61-93.32) 143.91 (135.35-154.15) 

Both Sexes 

14 or under 

15 - 44 

45 or older 

All ages 

2977 8.82 (7.39-10.24) 32.88 (27.97-37.11) 50.95 (44.64-53.86) 98.33 (86.40-113.96) 

5042 16.74 (15.54-17.94) 57.88 (56.00-60.85) 84.59 (79.91-90.83) 138.21 (122.84-149.15) 

3893 19.03 (17.54-20.52) 61.32 (56.00-65.74) 86.21 (77.42-94.70) 143.91 (131.12-171.37) 

11912 15.65 (14.67-16.63) 55.02 (51.38-56.00) 78.34 (75.21-80.56) 133.46 (125.27-140.21) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Source: U.S. EPA, 1996a. 
Table 10-16. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for the U.S. Population Aged 18 Years and Older by Habitat - As Consumed 

Grams/day 

90% Interval 

Habitat Statistic Estimate Lower Bound Upper Bound 

Fresh/Estuarine Mean 5.59 4.91 6.28 

50th % 0.00 0.00 0.00 

90th % 17.80 14.89 20.63 

95th % 39.04 36.13 42.16 

99th % 86.30 81.99 96.67 

Marine Mean 12.42 11.55 13.29 

50th % 0.00 0.00 0.00 

90th % 45.98 44.48 48.34 

95th % 64.08 61.61 68.05 

99th % 111.38 101.94 120.49 

All Fish Mean 18.01 16.85 19.17 

50th % 0.00 0.00 0.00 

90th % 60.64 57.06 64.63 

95th % 86.25 80.29 91.00 

99th % 142.96 134.23 154.15 

Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.

Note: Estimates are projected from a sample of 8,478 individuals of age 18 and older to the U.S. population of

177,807,000 individuals of age 18 and older using 3-year combined survey weights.

Source: U.S. EPA, 1996a.
Table 10-17. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population by Age and Gender - As Consumed 

(Freshwater and Estuarine) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 1431 67.12 (46.16-88.09) 57.30 (0.00-128.52) 460.16 (218.56-559.86) 1356.54 (1295.24-2118.93) 

15 - 44 2891 66.22 (55.35-77.08) 174.96 (115.11-205.05) 451.04 (421.65-505.49) 1188.16 (977.85-1278.63) 

45 or older 2340 78.29 (63.27-93.30) 273.63 (209.63-300.11) 548.66 (466.18-633.87) 1251.00 (1038.97-1324.90) 

All ages 6662 70.32 (60.09-80.55) 177.91 (132.69-212.30) 497.30 (442.20-558.85) 1269.76 (1093.19-1328.24) 

Males 

14 or under 1546 73.93 (44.89-102.96) 28.10 (8.86-231.33) 723.93 (423.52-785.58) 1290.10 (1279.82-1355.11) 

15 - 44 2151 75.35 (62.00-88.70) 230.13 (132.30-309.85) 577.84 (410.09-706.31) 1132.23 (1028.61-1416.47) 

45 or older 1553 86.75 (70.91-102.58) 291.50 (230.15-364.24) 584.96 (512.66-630.77) 1231.60 (1115.58-1566.68) 

All ages 5250 78.36 (69.10-87.61) 231.57 (186.27-276.04) 589.22 (549.64-630.09) 1265.10 (1133.18-1355.11) 

Both Sexes 

14 or under 2977 70.59 (53.29-87.89) 53.24 (0.00-118.48) 556.34 (417.11-683.80) 1347.67 (1279.82-1390.82) 

15 - 44 5042 70.58 (61.27-79.89) 197.11 (154.78-229.29) 502.26 (410.09-604.29) 1167.57 (1021.96-1279.82) 

45 or older 3893 82.12 (70.19-94.05) 286.93 (228.49-332.88) 566.30 (505.10-625.21) 1251.55 (1115.58-1324.90) 

All ages 11912 74.16 (65.74-82.57) 204.00 (177.97-225.16) 547.64 (505.10-565.37) 1274.55 (1197.29-1324.90) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Source: U.S. EPA, 1996a. 
Table 10-18. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population by Age and Gender - As Consumed 

(Marine) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 1431 256.90 (207.04-306.76) 936.94 (723.73-1055.43) 1545.15 (1260.24-1760.26) 3060.22 (2403.50-4354.46) 

15 - 44 2891 159.79 (142.76-176.82) 573.49 (493.39-663.16) 873.73 (780.56-929.55) 1700.21 (1578.65-1815.48) 

45 or older 2340 191.08 (171.33-210.83) 644.33 (608.39-725.83) 978.84 (881.06-1103.01) 1694.58 (1488.32-1791.84) 

All ages 6662 190.61 (172.89-208.33) 658.64 (627.61-700.33) 1024.76 (958.94-1096.14) 1979.45 (1793.40-2137.78) 

Males 

14 or under 1546 230.25 (188.33-272.17) 846.57 (734.83-987.18) 1504.37 (1320.60-1749.26) 2885.08 (2631.87-3430.60) 

15 - 44 2151 165.92 (147.73-184.12) 626.85 (593.90-680.90) 933.05 (833.43-982.30) 1472.98 (1411.97-1525.47) 

45 or older 1553 164.37 (144.87-183.87) 621.00 (562.90-691.03) 839.06 (800.23-946.97) 1422.94 (1293.89-1791.31) 

All ages 5250 181.08 (163.00-199.15) 670.19 (622.62-714.53) 981.87 (934.45-1071.54) 1923.63 (1802.17-1972.86) 

Both Sexes 

14 or under 2977 243.31 (202.43-284.18) 873.87 (741.53-1093.69) 1522.52 (1371.10-1587.20) 3059.93 (2732.63-3430.60) 

15 - 44 5042 162.72 (148.13-177.31) 602.58 (564.88-648.54) 893.82 (856.58-940.85) 1576.09 (1503.11-1697.71) 

45 or older 3893 178.99 (164.13-193.84) 628.06 (555.84-700.65) 914.67 (825.21-1040.75) 1568.85 (1483.71-1760.74) 

All ages 11912 186.06 (170.81-201.31) 663.00 (627.39-717.18) 991.96 (960.40-1044.69) 1942.17 (1815.48-2042.99) 

Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Source: U.S. EPA, 1996a. 
Table 10-19. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population by Age and Gender - As Consumed 

(All Fish) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 1431 324.02 (264.25-383.80) 1091.52 (929.29-1407.54) 1690.99 (1513.97-2072.35) 3982.60 (3219.32-4568.45) 

15 - 44 2891 226.01 (205.01-247.01) 755.51 (641.02-879.29) 1126.02 (975.49-1269.56) 2195.86 (1762.90-2310.54) 

45 or older 2340 269.37 (243.36-295.38) 862.18 (796.63-955.82) 1296.64 (1186.00-1344.85) 2147.32 (1791.84-2354.25) 

All ages 6662 260.93 (239.15-282.72) 873.61 (796.63-911.89) 1323.29 (1269.56-1418.85) 2361.12 (2272.41-2598.14) 

Males 

14 or under 1546 304.17 (251.91-356.43) 1172.17 (1085.62-1320.60) 1575.43 (1496.19-1943.82) 3393.84 (2731.95-3733.22) 

15 - 44 2151 241.27 (219.25-263.29) 867.70 (814.06-919.25) 1208.43 (1101.68-1266.32) 1760.48 (1611.45-1851.26) 

45 or older 1553 251.12 (225.48-276.76) 797.83 (762.30-858.52) 1122.80 (1041.28-1266.18) 1922.33 (1786.53-2275.93) 

All ages 5250 259.43 (239.81-279.06) 894.96 (842.29-938.16) 1298.95 (1224.82-1366.86) 2346.64 (1972.86-2631.87) 

Both Sexes 

14 or under 2977 313.90 (268.42-359.38) 1128.26 (1005.58-1320.60) 1679.91 (1546.20-1848.43) 3419.49 (3184.04-3733.22) 

15 - 44 5042 233.30 (216.16-250.44) 828.12 (771.73-868.89) 1155.30 (1102.57-1212.19) 2003.46 (1787.65-2182.19) 

45 or older 3893 261.10 (240.34-281.87) 818.10 (771.23-882.53) 1249.97 (1101.32-1323.53) 1967.01 (1796.52-2257.50) 

All ages 11912 260.22 (242.60-277.83) 880.47 (844.35-918.79) 1308.54 (1267.15-1346.71) 2356.54 (2224.54-2556.68) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Source: U.S. EPA, 1996a. 
Table 10-20. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population Aged 18 Years and Older by Habitat - As Consumed 

90% Interval 

Habitat Statistic Estimate Lower Bound Upper Bound 

Fresh/Estuarine Mean 75.56 66.37 84.75 

50th % 0.00 0.00 0.00 

90th % 242.49 205.05 277.26 

95th % 547.61 493.47 587.37 

99th % 1,171.84 1,123.52 1,252.78 

Marine Mean 172.86 160.73 184.99 

50th % 0.00 0.00 0.00 

90th % 624.83 598.84 670.34 

95th % 911.05 877.29 952.66 

99th % 1,573.20 1,468.43 1,713.17 

All Fish Mean 248.42 232.19 264.64 

50th % 0.00 0.00 0.00 

90th % 829.02 791.06 872.61 

95th % 1,197.36 1,133.18 1,264.74 

99th % 2,014.67 1,839.55 2,180.87 

Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.

Note: Estimates are projected from a sample of 8,478 individuals of age 18 and older to the population of 177,807,000

individuals of age 18 and older using 3-year combined survey weights.

Source: U.S. EPA, 1996a.
Table 10-21. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day)

 for Consumers Only by Age and Gender - As Consumed 

(Freshwater and Estuarine) 

Age Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Sample 

Females 

14 or under 138 38.44 91.30 128.97 182.66 

15 - 44 445 61.40 148.83 185.44 363.56 

45 or older 453 62.49 150.67 214.91 296.69 

All ages 1036 58.82 (51.57-66.06) 145.65 (130.73-152.24) 190.28 (173.88-219.03) 330.41 (259.20-526.69) 

Males 

14 or under 157 52.44 112.05 154.44 230.74 

15 - 44 356 81.56 224.01 275.02 371.53 

45 or older 343 82.23 192.31 255.68 449.09 

All ages 856 77.50 (70.21-84.80) 197.93 (169.51-224.85) 253.48 (216.54-290.00) 404.65 (371.63-421.60) 

Both Sexes 

14 or under 295 45.73 108.36 136.24 214.62 

15 - 44 801 71.44 180.67 230.95 371.52 

45 or older 796 71.81 174.54 231.38 427.73 

All ages 1892 68.00 (61.92-74.07) 170.84 (158.74-181.79) 224.78 (212.91-245.98) 374.74 (336.50-431.34) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Acute Consumers only are individuals with reported fish consumption at least once during the three day reporting period. 

Source: U.S. EPA, 1996a. 
Table 10-22. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for Consumers Only by Age and Gender - As Consumed 

(Marine) 

Age Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Sample 

Females 

14 or under 315 69.04 114.23 162.37 336.59 

15 - 44 774 76.53 149.78 178.74 271.06 

45 or older 715 85.24 167.11 218.35 264.8 

All ages 1804 78.47 (74.43-82.51) 155.38 (147.00-166.64) 195.15 (179.12-212.07) 279.79 (263.48-336.17) 

Males 

14 or under 348 78.44 160.97 190.68 336.98 

15 - 44 565 104.57 191.29 227.56 316.69 

45 or older 467 101.46 188.77 259.85 333.18 

All ages 1380 98.59 (93.16-104.03) 184.53 (173.46-194.13) 224.89 (210.00-250.28) 328.18 (310.42-348.49) 

Both Sexes 

14 or under 663 73.62 153.2 176.9 337.24 

15 - 44 1339 89.93 171.88 209.17 308.06 

45 or older 1182 92.19 178.33 223.82 314.44 

All ages 3184 87.77 (83.74-91.80) 169.39 (167.00-173.65) 209.50 (198.11-221.73) 320.41 (292.80-341.88) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Acute Consumers only are individuals with reported fish consumption at least once during the three day reporting period. 

Source: U.S. EPA, 1996a. 
Table 10-23. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for Consumers Only by Age and Gender - As Consumed 

(All Fish) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 378 69.54 126.22 165.27 338.04 

15 - 44 952 88.8 170.01 212.56 361.04 

45 or older 879 96.47 184.42 226.25 310.12 

All ages 2209 88.47 (83.98-92.97) 170.10 (166.63-173.88) 220.56 (201.97-236.00) 340.71 (289.17-368.51) 

Males 

14 or under 429 79.72 161.62 190 308.59 

15 - 44 702 124.78 230.77 296.66 397.7 

45 or older 587 119.44 224.82 262.43 434.28 

All ages 1718 114.18 (108.79-119.56) 219.96 (209.17-229.91) 272.49 (254.99-301.51) 411.68 (371.43-447.85) 

Both Sexes 

14 or under 807 74.8 153.7 178.08 337.46 

15 - 44 1654 106.06 203.33 271.66 372.77 

45 or older 1466 106.62 209.34 254.69 407.14 

All ages 3927 100.63 (96.66-104.60) 197.44 (188.74-205.12) 253.38 (231.51-264.45) 371.59 (359.29-401.61) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Acute Consumers only are individuals with reported fish consumption at least once during the three day reporting period. 

Source: U.S. EPA, 1996a. 
Table 10-24. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for Consumers Only Aged 18 Years and Older by Habitat - As Consumed 

90% Interval 

Habitat Statistic Estimate Lower Bound Upper Bound 

Fresh/Estuarine Mean 70.91 64.16 77.65 

n = 1,541 50th % 42.45 37.24 46.91 

N = 37,166,000 90th % 176.58 165.08 193.26 

95th % 230.41 224.00 255.55 

99th % 402.56 358.58 518.41 

Marine Mean 91.49 87.35 95.64 

n = 2,432 50th % 77.56 74.89 78.52 

N = 57,830,000 90th % 172.29 168.00 182.00 

95th % 215.62 201.99 225.63 

99th % 313.05 292.80 324.81 

All Fish Mean 106.39 102.37 110.41 

n = 3,007 50th % 85.36 84.00 87.36 

N = 70,949,000 90th % 206.76 197.84 213.00 

95th % 258.22 241.00 266.86 

99th % 399.26 336.50 423.56 

Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.

Note: Consumers only are individuals who consumed fish at least once during the 3-day reporting period; n = sample size; N =

population size.

Estimates are projected from a sample of consumers only 18 years of age and older to the population of consumers only 18 years of age

and older using 3-year combined survey weights. The population for this survey consisted of individuals in the 48 conterminous states.

Source: U.S. EPA, 1996a.
Table 10-25. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only by Age and Gender - As Consumed 

(Freshwater and Estuarine) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 0 0 0 0 0 

14 or under 138 1639.20 3915.56 6271.09 10113.24 

15 - 44 445 961.58 2578.81 3403.75 6167.24 

45 or older 453 927.85 2229.97 2894.18 4338.36 

All ages 1036 1037.29 (905.50-1169.09) 2582.5 (2248.8-2734.5) 3434.16 (2927.72-3979.82) 6923.5 (4757.8-9134.9) 

Males 0 0 0 0 0 

14 or under 157 1798.24 3759.29 3952.99 7907.38 

15 - 44 356 1004.96 2744.61 3348.86 4569.62 

45 or older 343 992.11 2448.54 3281.38 5716.41 

All ages 856 1117.74 (1011.55-1223.94) 2789.95 (2526.87-3132.65) 3399.26 (3256.87-3907.77) 5259.97 (4834.34-6593.97) 

Both Sexes 0 0 0 0 0 

14 or under 295 1721.99 3760.67 4208.18 9789.49 

15 - 44 801 983.19 2616.63 3360.85 5089.78 

45 or older 796 958.20 2394.21 3121.09 5157.95 

All ages 1892 1076.80 (980.00-1173.61) 2695.81 (2546.77-2819.33) 3399.46 (3132.65-3839.47) 6526.10 (5270.61-6931.61) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Consumers only are individuals with reported fish consumption at least once during the three day reporting period. 

Source: U.S. EPA, 1996a. 
Table 10-26. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day)

 for Consumers Only by Age and Gender - As Consumed 

(Marine) 

Age Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 

Sample 

99th % (90% B.I.) 

Females 

14 or under 315 2591.57 5074.80 6504.67 9970.44 

15 - 44 774 1227.41 2469.67 3007.98 4800.68 

45 or older 715 1293.99 2642.60 3565.34 4237.73 

All ages 1804 1486.90 (1400.58-1573.23) 2992.38 (2841.13-3303.96) 3961.24 (3768.48-4192.13) 6521.73 (5792.54-7794.41) 

Males 

14 or under 348 2471.15 4852.33 5860.72 8495.57 

15 - 44 565 1302.62 2390.20 2882.91 3887.23 

45 or older 467 1242.49 2251.43 2877.73 4016.80 

All ages 1380 1505.19 (1411.84-1598.55) 2899.23 (2797.30-3199.05) 3836.02 (3563.32-4581.61) 5859.85 (5247.79-7895.62) 

Both Sexes 

14 or under 663 2532.95 5068.69 6376.47 8749.02 

15 - 44 1339 1263.35 2464.80 2961.92 4251.47 

45 or older 1182 1271.92 2461.37 3383.46 4220.78 

All ages 3184 1495.37 (1422.63-1568.12) 2956.38 (2838.46-3083.70) 3887.52 (3770.65-4113.22) 6510.73 (5772.57-6852.01) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Consumers only are individuals with reported fish consumption at least once during the three day reporting period. 

Source: U.S. EPA, 1996a. 
Table 10-27. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumer Only by Age and Gender - As Consumed 

(All Fish) 

Age Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 

Sample 

99th % (90% B.I.) 

Females 

14 or under 378 2683.51 5299.68 7160.73 12473.65 

15 - 44 952 1414.54 2726.46 3740.83 6703.25 

45 or older 879 1449.43 2838.76 3736.61 4693.94 

All ages 2209 1637.08 (1546.08-1728.08) 3122.82 (2992.63-3308.93) 4312.16 (3969.22-4710.75) 7163.38 (6852.67-7794.41) 

Males 

14 or under 429 2568.93 4714.97 5818.08 9350.89 

15 - 44 702 1545.93 2854.49 3773.51 5254.04 

45 or older 587 1451.06 2841.35 3366.84 5091.31 

All ages 1718 1715.79 (1636.68-1794.90) 3399.26 (3290.97-3766.18) 4244.32 (4015.03-4581.61) 6818.35 (5792.54-7588.15) 

Both Sexes 

14 or under 807 2624.35 5020.14 6904.83 10384.82 

15 - 44 1654 1477.57 2798.37 3747.88 5386.43 

45 or older 1466 1450.15 2839.04 3515.81 4922.99 

All ages 3927 1674.31 (1606.79-1741.83) 3299.54 (3133.69-3462.35) 4258.69 (4065.32-4483.83) 7126.90 (6644.11-7794.41) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Consumers only are individuals with reported fish consumption at least once during the three day reporting period. 

Source: U.S. EPA, 1996a. 
Table 10-28. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only Aged 18 Years and Older by Habitat - As Consumed 

Milligrams/kilogram/person/day 

90% Interval 

Habitat Statistic Estimate Lower Bound Upper Bound 

Fresh/Estuarine Mean 959.15 867.58 1,050.72 

n = 1,541 50th % 601.88 532.31 656.86 

N = 37,166,000 90th % 2,442.97 2,233.16 2,606.66 

95th % 3,116.28 2,839.90 3,303.96 

99th % 5,151.98 4,432.30 6,931.61 

Marine Mean 1,270.78 1,214.65 1,326.90 

n = 2,432 50th % 1,062.93 1,019.60 1,087.06 

N = 57,830,000 90th % 2,467.68 2,331.88 2,585.09 

95th % 3,116.74 2,906.16 3,264.98 

99th % 4,250.22 4,037.74 4,387.96 

All Fish Mean 1,461.71 1,406.34 1,517.09 

n = 3,007 50th % 1,189.29 1,156.77 1,225.43 

N = 70,949,000 90th % 2,802.28 2,685.81 2,868.73 

95th % 3,588.11 3,308.93 3,798.54 

99th % 5,355.90 5,095.58 5,766.99 

Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.

Note: Consumers only are individuals who consumed fish at least once during the 3-day reporting period; n = sample size; N =

population size

Estimates are projected from a sample of consumers only 18 years of age and older to the population of consumers only 18 years of age

and older using 3-year combined survey weights. The population for this survey consisted of individuals in the 48 conterminous states.

Source: U.S. EPA, 1996a.
Table 10-29. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for the U.S. Population by Age and Gender - Uncooked Fish Weight 

(Freshwater and Estuarine) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 

15 - 44 

45 or older 

All ages 

1431 1.99 (1.34-2.64) 1.81 (0.00-4.63) 15.88 (7.89-18.38) 46.82 (36.72-54.55) 

2891 5.50 (4.53-6.48) 13.62 (9.99-18.11) 36.68 (32.53-40.31) 94.93 (75.74-114.34) 

2340 6.65 (5.30-8.00) 24.18 (18.11-27.41) 46.91 (37.94-52.92) 108.90 (92.06-123.72) 

6662 5.13 (4.37-5.88) 13.31 (10.48-16.67) 35.63 (28.92-40.07) 94.61 (77.70-109.09) 

Males 

14 or under 

15 - 44 

45 or older 

All ages 

1546 2.69 (1.62-3.76) 1.07 (0.33-8.67) 18.47 (14.39-25.91) 57.07 (47.32-65.37) 

2151 7.87 (6.46-9.29) 22.10 (13.43-31.80) 63.26 (50.62-70.12) 126.61 (108.54-162.80) 

1553 8.87 (7.32-10.43) 28.74 (24.23-33.07) 61.15 (52.57-71.59) 125.90 (112.28-147.62) 

5250 6.91 (6.07-7.75) 19.00 (14.99-23.69) 51.43 (47.32-54.82) 112.11 (108.54-127.19) 

Both Sexes 

14 or under 

15 - 44 

45 or older 

All ages 

2977 2.35 (1.70-3.00) 1.72 (0.00-5.00) 17.46 (12.78-18.68) 50.14 (43.58-55.00) 

5042 6.64 (5.71-7.56) 18.30 (14.99-21.14) 47.31 (36.22-59.65) 109.66 (94.43-127.19) 

3893 7.66 (6.50-8.81) 26.11 (21.95-28.85) 52.92 (45.73-61.51) 113.10 (107.18-133.74) 

11912 5.98(5.29-6.67) 15.89(14.39-17.76) 40.03(37.94-44.75) 107.63(98.25-109.09) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Source: U.S. EPA, 1996a. 
Table 10-30. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for the U.S. Population by Age and Gender - Uncooked Fish Weight 

(Marine) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 

15 - 44 

45 or older 

All ages 

1431 8.61 (6.67-10.56) 31.23 (26.85-37.29) 49.75 (41.46-57.49) 104.26 (83.35-140.07) 

2891 12.84 (11.51-14.18) 46.66 (38.35-54.30) 72.16 (63.12-77.18) 133.69 (121.33-142.82) 

2340 16.26 (14.68-17.84) 56.01 (50.00-61.97) 84.71 (75.05-93.29) 131.43 (112.07-156.01) 

6662 13.05 (11.97-14.12) 46.70 (44.49-49.72) 72.22 (65.55-75.47) 130.73 (121.33-137.18) 

Males 

14 or under 

15 - 44 

45 or older 

All ages 

1546 9.40 (7.36-11.45) 31.32 (25.20-44.12) 65.37 (54.60-73.39) 118.42 (82.34-176.52) 

2151 17.11 (15.31-18.90) 66.06 (62.21-73.20) 93.32 (81.26-106.67) 155.16 (136.77-181.18) 

1553 17.22 (15.19-19.25) 62.64 (59.39-68.44) 84.96 (79.93-99.44) 146.78 (142.58-185.44) 

5250 15.27 (13.86-16.68) 61.12 (56.59-63.09) 81.89 (77.91-87.16) 147.09 (134.55-174.31) 

Both Sexes 

14 or under 

15 - 44 

45 or older 

All ages 

2977 9.02 (7.28-10.75) 31.52 (30.19-35.75) 56.35 (50.22-62.25) 117.75 (91.82-140.07) 

5042 14.88 (13.57-16.19) 55.99 (53.04-61.33) 80.70 (75.19-87.16) 138.23 (128.40-157.23) 

3893 16.69 (15.34-18.04) 59.12 (52.84-64.53) 84.92 (76.67-93.32) 142.92 (134.55-155.13) 

11912 14.11(13.07-15.14) 52.10(47.83-55.93) 76.51(74.58-80.89) 138.22(132.98-155.13) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Source: U.S. EPA, 1996a. 
Table 10-31. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day)

 for the U.S. Population by Age and Gender - Uncooked Fish Weight 

(All Fish) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 

15 - 44 

45 or older 

All ages 

1431 10.60 (8.40-12.81) 41.10 (35.80-47.57) 56.16 (49.78-65.55) 130.78 (83.35-160.66) 

2891 18.35 (16.67-20.02) 62.21 (54.47-73.56) 93.13 (82.29-108.03) 155.75 (137.18-174.31) 

2340 22.91 (20.78-25.04) 74.56 (65.37-79.67) 107.66 (97.64-111.71) 159.97 (157.17-173.74) 

6662 18.17 (16.82-19.53) 61.08 (56.94-63.12) 92.03 (86.94-96.11) 157.08 (147.34-168.83) 

Males 

14 or under 

15 - 44 

45 or older 

All ages 

1546 12.09 (9.70-14.49) 45.59 (34.69-53.11) 68.18 (64.28-79.90) 127.20 (87.29-176.52) 

2151 24.98 (22.79-27.17) 87.15 (80.89-94.63) 122.29 (111.05-124.83) 197.15 (179.86-198.87) 

1553 26.09 (23.52-28.67) 81.76 (76.67-88.03) 112.33 (109.65-130.36) 211.20 (190.74-223.72) 

5250 22.18 (20.52-23.83) 76.13 (74.22-79.92) 110.88 (108.54-118.56) 180.90 (174.39-198.87) 

Both Sexes 

14 or under 

15 - 44 

45 or older 

All ages 

2977 11.36 (9.49-13.24) 43.00 (34.69-47.32) 65.34 (56.28-68.51) 130.41 (107.12-160.66) 

5042 21.51 (19.97-23.06) 75.15 (73.56-79.71) 109.57 (106.72-117.47) 175.73 (162.80-198.63) 

3893 24.35 (22.46-26.24) 77.57 (72.07-84.02) 110.13 (100.42-119.87) 180.74 (164.76-210.75) 

11912 20.08(18.82-21.35) 70.11 (65.37-74.20) 102.01 (99.26-106.67) 173.18 (162.80-176.52) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Source: U.S. EPA, 1996a. 
Table 10-32. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for the U.S. Population Aged 18 Years and Older by Habitat - Uncooked Fish Weight 

90% Interval 

Habitat Statistic Estimate Lower Bound Upper Bound 

Fresh/Estuarine Mean 7.09 6.22 7.96 

50th % 0.00 0.00 0.00 

90th % 21.72 18.52 25.82 

95th % 49.89 47.32 54.67 

99th % 111.13 107.18 116.38 

Marine Mean 16.01 14.89 17.12 

50th % 0.00 0.00 0.00 

90th % 59.35 56.59 61.49 

95th % 82.95 80.37 88.36 

99th % 142.78 131.02 156.89 

All Fish Mean 23.10 21.62 24.58 

50th % 0.00 0.00 0.00 

90th % 76.84 74.37 80.13 

95th % 110.28 106.67 115.32 

99th % 177.44 171.73 198.63 

Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.

NOTE: Estimates are projected from a sample of 8,478 individuals of age 18 and older to the U.S. population

of 177,807,000 individuals of age 18 and older using 3-year combined survey weights.

Source: U.S. EPA, 1996a.
Table 10-33. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population by Age and Gender - Uncooked Fish Weight 

(Freshwater and Estuarine) 

Age Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Sample 

Females 

14 or under 1431 84.78 (58.06-111.50) 70.75 (0.00-143.13) 599.06 (266.71-722.58) 1713.06 (1511.78-2313.50) 

15 - 44 2891 85.15 (70.68-99.62) 202.83 (153.48-259.97) 584.79 (538.05-631.86) 1411.42 (1236.72-1659.15) 

45 or older 2340 98.97 (79.89-118.04) 333.38 (269.96-379.98) 733.74 (606.36-820.68) 1561.40 (1331.46-1667.88) 

All ages 6662 89.54 (76.51-102.58) 225.51 (176.38-280.11) 625.30 (552.99-713.85) 1558.08 (1394.99-1659.15) 

Males 

14 or under 1546 91.62 (55.18-128.05) 38.98 (12.26-281.50) 868.97 (485.33-1063.50) 1642.60 (1599.78-1693.88) 

15 - 44 2151 96.91 (78.91-114.90) 281.17 (165.37-387.46) 740.91 (546.79-850.52) 1589.97 (1353.43-1992.23) 

45 or older 1553 107.87 (88.47-127.28) 361.99 (304.96-455.29) 702.35 (628.25-810.62) 1612.49 (1344.07-1848.39) 

All ages 5250 98.86 (87.19-110.52) 292.58 (217.42-342.11) 755.53 (677.47-790.85) 1596.61 (1538.89-1711.41) 

Both Sexes 

14 or under 2977 88.26 (66.69-109.83) 66.00 (0.00-143.13) 717.37 (485.60-880.64) 1688.55 (1511.78-1824.44) 

15 - 44 5042 90.77 (78.37-103.16) 250.26 (194.04-289.19) 631.31 (538.05-773.91) 1529.94 (1352.50-1659.15) 

45 or older 3893 103.00 (87.86-118.15) 345.69 (291.80-423.39) 719.81 (637.94-790.85) 1590.13 (1373.97-1668.93) 

All ages 11912 93.99 (83.41-104.57) 251.82 (222.54-282.58) 677.66 (631.86-729.11) 1593.28 (1511.78-1659.15) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Source: U.S. EPA, 1996a. 
Table 10-34. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population by Age and Gender - Uncooked Fish Weight 

(Marine) 

Age Sample Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 

Size 

99th % (90% B.I.) 

Females 

14 or under 1431 333.99 (267.25-400.72) 1132.99 (864.83-1407.24) 1959.91 (1780.61-2347.02) 3776.60 (3173.86-5736.90) 

15 - 44 2891 206.03 (183.95-228.11) 762.54 (617.86-857.55) 1137.58 (1036.38-1211.86) 2174.21 (2014.41-2393.16) 

45 or older 2340 246.73 (221.45-272.00) 829.52 (777.87-944.26) 1236.00 (1174.14-1413.34) 2161.65 (1952.51-2303.80) 

All ages 6662 246.47 (223.28-269.66) 847.60 (811.19-893.29) 1305.49 (1215.53-1385.66) 2615.85 (2365.65-2857.62) 

Males 

14 or under 1546 296.99 (241.85-352.13) 1089.46 (1003.46-1256.97) 1907.65 (1685.30-2186.58) 3723.81 (3274.93-4574.13) 

15 - 44 2151 212.88 (190.31-235.44) 800.79 (741.29-859.61) 1191.75 (1096.61-1245.94) 1890.42 (1685.30-1969.63) 

45 or older 1553 212.15 (187.25-237.04) 792.86 (747.56-890.31) 1100.20 (1039.02-1210.66) 1842.38 (1749.67-2219.32) 

All ages 5250 233.07 (209.65-256.49) 859.01 (798.27-907.76) 1255.35 (1204.46-1382.05) 2520.94 (2263.58-2733.15) 

Both Sexes 

14 or under 2977 315.12 (260.95-369.29) 1123.28 (993.12-1371.24) 1909.37 (1785.09-2062.64) 3820.21 (3370.59-4574.13) 

15 - 44 5042 209.30 (190.68-227.92) 780.16 (722.86-843.41) 1174.69 (1104.42-1215.53) 2019.59 (1918.45-2237.22) 

45 or older 3893 231.06 (212.18-249.95) 813.12 (747.56-907.76) 1193.22 (1076.85-1333.72) 2029.16 (1863.17-2219.32) 

All ages 11912 240.07 (220.14-260.01) 855.63 (809.67-909.76) 1271.54 (1227.16-1371.24) 2575.29 (2393.16-2708.59) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Source: U.S. EPA, 1996a. 
Table 10-35. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population by Age and Gender - Uncooked Fish Weight 

(All Fish) 

Age Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Sample 

Females 

14 or under 1431 418.76 (339.58-497.95) 1389.10 (1150.77-1785.09) 2341.90 (2062.64-2860.52) 4985.96 (3971.54-5736.90) 

15 - 44 2891 291.18 (263.86-318.50) 993.92 (854.63-1127.32) 1436.00 (1234.66-1631.25) 2726.50 (2406.11-3044.81) 

45 or older 2340 345.69 (312.49-378.90) 1122.26 (1050.15-1230.68) 1669.72 (1556.83-1784.37) 2684.71 (2303.80-3064.38) 

All ages 6662 336.01 (307.83-364.20) 1120.91 (1054.05-1172.38) 1720.84 (1642.63-1855.69) 3093.76 (2973.66-3265.54) 

Males 

14 or under 1546 388.61 (320.66-456.56) 1476.31 (1371.24-1632.55) 2038.58 (1909.00-2631.42) 4294.12 (3556.31-4574.13) 

15 - 44 2151 309.78 (281.55-338.02) 1096.57 (1044.57-1194.06) 1566.39 (1410.20-1609.35) 2275.15 (2047.18-2465.77) 

45 or older 1553 320.02 (287.79-352.25) 1013.05 (955.37-1096.43) 1459.73 (1340.97-1601.79) 2392.05 (2233.16-2806.51) 

All ages 5250 331.93 (306.46-357.40) 1126.66 (1081.06-1225.66) 1621.80 (1599.78-1696.20) 3031.31 (2806.51-3274.93) 

Both Sexes 

14 or under 2977 403.38 (343.65-463.12) 1442.72 (1279.82-1672.75) 2191.90 (2021.16-2536.75) 4425.27 (4000.27-4669.59) 

15 - 44 5042 300.06 (277.94-322.19) 1040.98 (1003.55-1097.08) 1514.82 (1421.34-1572.40) 2481.23 (2383.54-2773.15) 

45 or older 3893 334.07 (307.87-360.26) 1069.14 (978.95-1140.98) 1579.43 (1373.97-1696.20) 2653.45 (2292.45-2806.51) 

All ages 11912 334.06 (311.25-356.88) 1123.14 (1090.76-1178.95) 1684.23 (1620.48-1718.51) 3092.77 (2973.66-3250.20) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Source: U.S. EPA, 1996a. 
Table 10-36. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population Aged 18 Years and Older by Habitat - Uncooked Fish Weight 

90% Interval 

Habitat Statistic Estimate Lower Bound Upper Bound 

Fresh/Estuarine Mean 95.99 84.30 107.69 

50th % 0.00 0.00 0.00 

90th % 306.74 259.97 334.58 

95th % 677.39 626.01 734.34 

99th % 1,547.81 1,411.56 1,599.78 

Marine Mean 222.86 207.34 238.37 

50th % 0.00 0.00 0.00 

90th % 810.43 778.50 859.61 

95th % 1,190.45 1,145.61 1,219.60 

99th % 2,033.92 1,870.09 2,263.58 

All Fish Mean 318.85 298.20 339.49 

50th % 0.00 0.00 0.00 

90th % 1,061.14 1,016.87 1,105.01 

95th % 1,548.77 1,464.72 1,609.14 

99th % 2,559.07 2,444.24 2,764.50 

Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications.

NOTE: Estimates are projected from a sample of 8,478 individuals of age 18 and older to the population of

177,807,000 individuals of age 18 and older using 3-year combined survey weights.

Source: U.S. EPA, 1996a.
Table 10-37. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for Consumers Only by Age and Gender - Uncooked Fish Weight 

(Freshwater and Estuarine) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 138 48.3 117.27 161.44 230.63 

15 - 44 445 78.56 191.95 242.76 472.21 

45 or older 453 78.77 192.32 258.56 368.84 

All ages 1036 74.67 (65.46-83.88) 181.08 (171.19-197.59) 239.59 (220.69-284.70) 409.00 (345.96-671.54) 

Males 

14 or under 157 64.91 141.35 193.79 287.28 

15 - 44 356 104.86 269.96 343.66 494.38 

45 or older 343 102.56 234.28 326.96 539.77 

All ages 856 98.12 (88.60-107.64) 246.93 (212.93-283.90) 324.53 (283.28-381.58) 499.19 (488.41-532.32) 

Both Sexes 

14 or under 295 56.95 134.89 166.32 262.87 

15 - 44 801 91.66 237.27 322.06 494.64 

45 or older 796 90 220.76 295.41 523.94 

All ages 1892 86.19 (78.41-93.97) 217.92 (205.28-237.27) 290.04 (267.10-325.61) 489.29 (424.87-534.20) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Consumers only are individuals reported fish consumption at least once during the three day reporting period. 

Source: U.S. EPA, 1996a. 
Table 10-38. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for Consumers Only by Age and Gender - Uncooked Fish Weight 

(Marine) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 315 89.92 169.23 198.62 432.51 

15 - 44 774 98.53 194.59 231.22 317.42 

45 or older 715 110 214.73 279.67 345.37 

All ages 1804 101.30 (95.90-106.69) 195.37 (186.67-213.33) 252.43 (231.53-278.16) 372.17 (314.67-428.00) 

Males 

14 or under 348 101.5 205.49 242.28 408.68 

15 - 44 565 133.86 244.46 297.67 393.14 

45 or older 467 131.2 243.33 327.14 428.72 

All ages 1380 126.85 (119.75-133.94) 238.64 (225.57-247.01) 296.68 (279.95-316.81) 425.98 (403.66-481.95) 

Both Sexes 

14 or under 663 95.56 189.32 231.72 442.87 

15 - 44 1339 115.41 223.99 263.76 383.16 

45 or older 1182 119.08 226.55 288.16 418.23 

All ages 3184 113.11 (107.79-118.43) 222.67 (216.50-225.56) 271.70 (260.62-279.95) 415.88 (367.26-440.45) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Consumers only are individuals with reported fish consumption at least once during the three day reporting period. 

Source: U.S. EPA, 1996a. 
Table 10-39. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for Consumers Only by Age and Gender - Uncooked Fish Weight 

(All Fish) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 

14 or under 378 89.73 163.47 204.14 476.56 

15 - 44 952 114.04 220.63 277.69 461.54 

45 or older 879 123.61 236.3 298.66 397.43 

All ages 2209 113.58 (107.69-119.47) 220.44 (206.27-226.80) 287.08 (257.09-312.42) 448.57 (393.68-531.63) 

Males 

14 or under 429 102.01 205.25 244.46 386.47 

15 - 44 702 160.06 305.61 379.38 495.51 

45 or older 587 152.52 292.95 350.26 555.11 

All ages 1718 146.18 (138.99-153.38) 283.46 (261.72-297.95) 350.99 (328.70-382.33) 520.51 (488.41-591.47) 

Both Sexes 

14 or under 807 96.07 195.35 232.85 466.09 

15 - 44 1654 136.12 262.15 343.86 488.9 

45 or older 1466 136.38 263.95 326.94 510.25 

All ages 3927 129.00 (123.74-134.27) 249.09 (240.99-264.10) 326.00 (306.02-335.58) 497.54 (469.23-519.67) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Consumers only are individuals reported fish consumption at least once during the three day reporting period. 

Source: U.S. EPA, 1996a. 
Table 10-40. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) 

for Consumers Only Aged 18 Years and Older by Habitat - Uncooked Fish Weight

90% Interval

Habitat Statistic Estimate Lower Bound Upper Bound

Fresh/Estuarine Mean 89.88 81.41 98.35

n = 1,541 50th % 53.64 46.44 57.81

N = 37,166,000 90th % 223.11 206.58 237.27

95th % 296.89 283.90 325.61

99th % 502.93 448.23 654.55

Marine Mean 117.83 112.47 123.20

n = 2,432 50th % 98.79 95.69 100.76

N = 57,830,000 90th % 225.51 222.67 234.00

95th % 279.50 261.47 289.44

99th % 403.48 369.10 427.73

All Fish Mean 136.33 131.11 141.55

n = 3,007 50th % 111.50 108.53 112.00

N = 70,949,000 90th % 262.03 253.24 272.71

95th % 328.66 323.61 340.52

99th % 506.02 435.44 531.63

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications.

Note: Consumers only are individuals who consumed fish at least once during the 3-day reporting period; n = sample size; and N =

population size. Estimates are projected from a sample of consumers only 18 years of age and older to the population of consumers

only 18 years of age and older using 3-year combined survey weights. The population for this survey consisted of individuals in the 48

conterminous states.

Source: U.S. EPA, 1996a.
Table 10-41. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only by Age and Gender - Uncooked Fish Weight 

(Freshwater and Estuarine) 

Age Sample Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 

Size 

99th % (90% B.I.) 

Females 

14 or under 138 2070.41 4450.54 6915.31 13269.61 

15 - 44 445 1229.97 3045.41 4191.25 7711.43 

45 or older 453 1171.17 2886.48 3519.87 5577.34 

All ages 1036 1317.18 (1150.10-1484.26) 3250.31 (2988.81-3491.38) 4240.89 (3710.16-5025.02) 8912.52 (6385.55-11533.98) 

Males 

14 or under 157 2229.31 4638.34 5071.41 9622.15 

15 - 44 356 1294.27 3318.89 4275.83 5974.96 

45 or older 343 1235.55 2898.00 4097.24 7217.68 

All ages 856 1411.35 (1278.61-1544.08) 3579.06 (3225.84-4060.30) 4615.66 (4121.91-5081.65) 6594.61 (5980.19-7944.55) 

Both Sexes 

14 or under 295 2153.11 4634.82 5756.93 12388.27 

15 - 44 801 1261.99 3276.06 4246.63 6625.15 

45 or older 796 1201.57 2892.52 3981.84 6378.11 

All ages 1892 1363.44 (1242.24-1484.65) 3325.14 (3232.58-3676.99) 4408.18 (4085.55-4781.34) 7957.50 (6979.20-8920.99) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Consumers only are individuals with reported fish consumption at least once during the three day reporting period. 

Source: U.S. EPA, 1996a. 
Table 10-42. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only by Age and Gender - Uncooked Fish Weight 

(Marine) 

Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) 

Females 0 0 0 0 0 

14 or under 315 3359.10 6058.97 8573.62 13050.09 

15 - 44 774 1582.77 3129.41 3854.14 5961.80 

45 or older 715 1669.73 3429.24 4397.07 5476.02 

All ages 1804 1920.77 (1804.28-2037.26) 3793.20 (3618.55-4328.00) 5083.63 (4953.40-5552.65) 8576.60 (7527.83-9743.01) 

Males 0 0 0 0 0 

14 or under 348 3180.45 6434.20 8089.26 10764.01 

15 - 44 565 1666.42 3102.24 3651.10 4998.14 

45 or older 467 1604.71 2931.17 3725.63 5373.82 

All ages 1380 1934.12 (1812.97-2055.28) 3736.16 (3548.08-4072.42) 4884.60 (4454.15-5710.83) 8066.96 (6852.67-9869.52) 

Both Sexes 0 0 0 0 0 

14 or under 663 3272.13 6278.74 8424.77 11838.54 

15 - 44 1339 1622.75 3120.60 3682.17 5517.95 

45 or older 1182 1641.87 3320.87 4328.34 5406.76 

All ages 3184 1926.95 (1829.50-2024.39) 3752.89 (3631.98-4001.16) 5018.74 (4852.08-5267.31) 8448.28 (7215.72-9136.89) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Consumers only are individuals with reported fish consumption at least once during the three day reporting period. 

Source: U.S. EPA, 1996a. 
Table 10-43. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumer Only by Age and Gender - Uncooked Fish Weight 

(All Fish) 

Age Sample Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 

Size 

99th % (90% B.I.) 

Females 

14 or under 378 3448.73 7100.43 9012.18 15381.13 

15 - 44 952 1818.32 3506.20 4661.96 8789.33 

45 or older 879 1857.64 3520.90 4740.11 6561.13 

All ages 2209 2102.20 (1982.89-2221.51) 4092.51 (3842.15-4282.08) 5545.07 (5080.72-6007.28) 9630.23 (8166.44-9796.61) 

Males 

14 or under 429 3273.63 5734.46 7570.83 11891.85 

15 - 44 702 1983.16 3720.05 4769.44 6121.56 

45 or older 587 1850.69 3534.61 4311.83 6374.34 

All ages 1718 2193.24 (2089.20-2297.28) 4385.06 (4121.91-4776.34) 5351.38 (5055.10-5727.01) 8596.82 (7816.70-10199.24) 

Both Sexes 

14 or under 807 3358.33 6333.46 8611.73 12406.35 

15 - 44 1654 1897.40 3674.88 4709.78 7276.18 

45 or older 1466 1854.57 3522.43 4615.22 6440.17 

All ages 3927 2145.26 (2055.92-2234.61) 4223.91 (4085.76-4454.15) 5477.86 (5163.33-5686.04) 9171.52 (8605.35-9796.61) 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. 

Consumers only are individuals with reported fish consumption at least once during the three day reporting period. 

Source: U.S. EPA, 1996a. 
Table 10-44. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only Aged 18 Years and Older by Habitat - Uncooked Fish Weight 

90% Interval 

Habitat Statistic Estimate Lower Bound Upper Bound 

Fresh/Estuarine Mean 1,216.82 1,101.74 1,331.90 

n = 1,541 50th % 740.93 639.11 822.65 

N = 37,166,000 90th % 3,050.95 2,931.26 3,270.80 

95th % 4,025.44 3,639.76 4,121.91 

99th % 6,638.62 6,007.28 8,920.99 

Marine Mean 1,637.10 1,564.27 1,709.92 

n = 2,432 50th % 1,370.42 1,302.29 1,422.69 

N = 57,830,000 90th % 3,169.02 3,006.55 3,328.98 

95th % 3,926.74 3,632.70 4,156.98 

99th % 5,452.75 5,353.12 5,596.31 

All Fish Mean 1,873.84 1,801.93 1,945.75 

n = 3,007 50th % 1,515.91 1,477.99 1,570.40 

N = 70,949,000 90th % 3,599.04 3,443.64 3,676.99 

95th % 4,665.15 4,264.03 4,812.97 

99th % 7,022.47 6,459.64 7,294.80 

Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications.

Note: Consumers only are individuals who consumed fish at least once during the 3-day reporting period; n = sample size; and N =

population size. Estimates are projected from a sample of consumers only 18 years of age and older to the population of consumers

only 18 years of age and older using 3-year combined survey weights. The population for this survey consisted of individuals in the 48

conterminous states.

Source: U.S. EPA, 1996a.
Table 10-45. Distribution of Quantity of Fish Consumed (in grams) Per Eating Occasion, by Age and Sex 

Percentiles 

Age (years)-Sex Group Mean SD 5th 25th 50th 75th 90th 95th 99th 

1-2 Male-Female 52 38 8 28 43 58 112 125 168 

3-5 Male-Female 70 51 12 36 57 85 113 170 240 

6-8 Male-Female 81 58 19 40 72 112 160 170 288 

9-14 Male 101 78 28 56 84 113 170 255 425 

9-14 Female 86 62 19 45 79 112 168 206 288 

15-18 Male 117 115 20 57 85 142 200 252 454 

15-18 Female 111 102 24 56 85 130 225 270 568 

19-34 Male 149 125 28 64 113 196 284 362 643 

19-34 Female 104 74 20 57 85 135 184 227 394 

35-64 Male 147 116 28 80 113 180 258 360 577 

35-64 Female 119 98 20 57 85 152 227 280 480 

65-74 Male 145 109 35 75 113 180 270 392 480 

65-74 Female 123 87 24 61 103 168 227 304 448 

75+ Male 124 68 36 80 106 170 227 227 336 

75+ Female 112 69 20 61 112 151 196 225 360 

Overall 117 98 20 57 85 152 227 284 456 

Source: Pao et al., 1982. 
Table 10-46. Mean Fish Intake in a Day, by Sex and Agea 

Sex Per capita intake Percent of population Mean intake (g/day) for 

Age (year) (g/day) consuming fish in 1 day consumers onlyb 

Males or Females 

5 and under 4 6.0 67 

Males 

6-11 3 3.7 79 

12-19 3 2.2 136 

20 and over 15 10.9 138 

Females 

6-11 7 7.1 99 

12-19 9 9.0 100 

20 and over 12 10.9 110 

All individuals 11 9.4 117 

Based on USDA Nationwide Food Consumption Survey 1987-88 data for one day. a 

Intake for users only was calculated by dividing the per capita consumption rate by the fraction of the population consuming fish in b 

one day. 

Source: USDA, 1992b. 
Table 10-47. Percent of Respondents That Responded Yes, No, or Don’t Know to Eating Seafood in 1 Month (including shellfish, eels, or squid) 

Response 

Population Group Total N No Yes DK 

N % N % N % 

Overall 4663 1811 38.8 2780 59.6 72 1.5 

Gender 

* 2 1

Male 2163 821

Female 2498 989

50.0 1 50.0 * * 

38.0 1311 60.6 31 1.4 

39.6 1468 58.8 41 1.6 

Age (years) 

* 84 25

1-4 263 160

5-11 348 177

12-17 326 179

18-64 2972 997

>64 670 273

29.8 42 50.0 17 20.2 

60.8 102 38.8 1 0.4 

50.9 166 47.7 5 1.4 

54.9 137 42.0 10 3.1 

33.5 1946 65.5 29 1.0 

40.7 387 57.8 10 1.5 

Race 

* 60 20

White 3774 1475

Black 463 156

Asian 77 21

Some Others 96 39

Hispanic 193 100

33.3 22 36.7 18 30.0 

39.1 2249 59.6 50 1.3 

33.7 304 65.7 3 0.6 

27.3 56 72.7 * * 

40.6 56 58.3 1 1.0 

51.8 93 48.2 * * 

Hispanic 

* 46 10

No 4243 1625

Yes 348 165

DK 26 11

21.7 412 43.0 28 41.3 

31.2 1366 67.7 21 1.2 

35.4 236 62.3 9 * 

40.4 766 58.5 14 * 

Employment 

* 958 518

Full Time 2017 630

Part Time 379 134

Not Employed 1309 529

54.1 412 43.0 28 2.9 

31.2 1366 67.7 21 1.0 

35.4 236 62.3 9 2.4 

40.4 766 58.5 14 1.1 

Education 

* 1021 550

< High School 399 196

High School Graduate 1253 501

< College 895 304

College Graduate 650 159

Post Graduate 445 101

53.9 434 42.5 37 3.6 

49.1 198 49.6 45 1.3 

40.0 739 59.0 13 1.0 

34.0 584 65.3 7 0.8 

24.5 484 74.5 7 1.1 

22.7 341 76.6 3 0.7 

Census Region 

Northeast 1048 370

Midwest 1036 449

South 1601 590

West 978 402

35.3 655 62.5 23 2.2 

43.3 575 55.5 12 1.2 

36.9 989 61.8 22 1.4 

41.1 561 57.4 15 1.5 

Day of Week 

Weekday 3156 1254 39.7 1848 58.6 54 1.7 

Weekend 1507 557 37.0 932 61.8 18 1.2 

Season 

Winter 1264 462

Spring 1181 469

Summer 1275 506

Fall 943 374

36.6 780 61.7 22 1.7 

39.7 691 58.5 21 1.8 

39.7 745 58.4 24 1.9 

39.7 564 59.8 5 0.5 

Asthma 

No 4287 1674 

Yes 341 131 

DK 35 6 

39.0 2563 59.8 50 1.2 

38.4 207 60.7 3 0.9 

17.7 10 28.6 19 54.3 

Angina 

No 4500 1750 

Yes 125 56 

DK 38 50 

38.9 2698 60.0 52 1.2 

44.8 68 54.4 1 0.8 

13.2 14 36.8 19 50.0 

Bronchitis/Emphysema 

No 4424 1726 

Yes 203 80 

DK 36 5 

9.0 2648 59.6 50 1.1 

39.4 121 59.6 2 1.0 

13.9 11 30.6 20 55.6 

Note: * = Missing data; DK = Don’t know; % = Row percentage; N = Sample size 

Source: Tsang and Klepeis, 1996. 
Table 10-48. Number of Respondents Reporting Consumption of a Specified Number of Servings of Seafood in 1 Month 

Population Group Total N Number of Servings in a Month 

1-2 3-5 6-10 11-19 20+ DK 

Overall 2780 918 990 519 191 98 64 

Gender 

* 1311 405

Male 1468 512

Female 1 1

458 261 101 57 29 

532 258 90 41 35 

* * * * * 

Age (years) 

* 42 13

1-4 102 55

5-11 166 72

12-17 137 68

18-64 1946 603

>64 387 107

16 5 4 1 3 

29 12 2 * 4 

57 21 6 4 6 

54 9 2 1 3 

679 408 145 79 32 

155 64 32 13 16 

Race 

* 2249 731

White 304 105

Black 56 15

Asian 56 22

Some Others 93 41

Hispanic 22 4

818 428 155 76 41 

103 56 16 10 14 

17 11 5 5 3 

18 6 5 3 2 

25 14 9 2 2 

9 4 1 2 2 

Hispanic 

* 2566 844

No 182 68

Yes 15 5

DK 17 1

922 480 175 88 57 

52 34 15 8 5 

8 2 * * * 

8 3 1 2 2 

Employment 

* 399 190

Full Time 1366 407

Part Time 236 70

Not Employed 766 249

Refused 13 2

140 40 11 5 13 

466 307 107 57 22 

95 46 14 8 3 

285 124 57 26 25 

4 2 2 2 1 

Education 

* 434 205

< High School 198 88

High School Graduate 739 267

< College 584 161

College Graduate 484 115

Post Graduate 341 82

149 47 12 7 14 

62 20 6 10 12 

266 119 46 21 20 

219 122 48 26 8 

183 121 43 17 5 

111 90 36 17 5 

Census Region 

Northeast 655 191

Midwest 575 199

South 989 336

West 561 192

241 137 62 12 12 

221 102 17 22 14 

339 175 70 41 28 

189 105 42 23 10 

Day of Week 

Weekday 1848 602 661 346 129 70 40 

Weekend 932 316 329 173 62 28 24 

Season 

Winter 780 262

Spring 691 240

Summer 745 220

Fall 564 196

284 131 60 28 15 

244 123 45 25 14 

249 160 59 31 26 

213 105 27 14 9 

Asthma 

No 2563 846 

Yes 207 69 

DK 10 3 

917 475 180 88 57 

71 42 11 9 5 

2 2 * 1 2 

Angina 

No 2698 896 

Yes 68 19 

DK 14 3 

Bronchitis/Emphysema 

No 2648 877 

Yes 121 37 

DK 11 4 

960 509 183 95 55 

27 8 7 1 6 

3 2 1 2 3 

940 495 185 91 60 

47 23 6 6 2 

3 1 * 1 2 

Note: * = Missing data; DK = Don’t know; % = Row percentage; N = Sample size; Refused = Respondent refused to answer. 

Source: Tsang and Klepeis, 1996. 
Table 10-49. Numer of Respondents Reporting Monthly Consumption of Seafood That Was Purchased or Caught by Someone They Knew 

Population Group Total N * Mostly Purchased Mostly Caught DK 

Overall 2780 3 2584 154 39 

Gender 

* 1311 1 1206 85 19 

Male 1468 2 1377 69 20 

Female 1 * 1 * * 

Age (years) 

* 42 * 39 3 * 

1-4 102 * 94 8 * 

5-11 166 * 153 9 4 

12-17 137 * 129 6 2 

18-64 1946 3 1810 106 27 

>64 387 * 359 22 6 

Race 

* 2249 1 2092 124 32 

White 304 1 280 19 4 

Black 56 * 50 4 2 

Asian 56 * 55 * 1 

Some Others 93 * 86 7 * 

Hispanic 22 1 21 * * 

Hispanic 

* 2566 2 2387 140 37 

No 182 * 169 13 * 

Yes 15 * 12 1 2 

DK 17 1 16 * * 

Employment 

* 399 * 368 25 6 

Full Time 1366 2 1285 64 15 

Part Time 236 1 217 15 3 

Not Employed 766 * 701 50 15 

Refused 13 * 13 * * 

Education 

* 434 * 401 26 7 

< High School 198 * 174 20 4 

High School Graduate 739 * 680 48 11 

< College 584 2 547 28 7 

College Graduate 484 * 460 19 5 

Post Graduate 341 1 322 13 5 

Census Region 

Northeast 655 2 627 21 5 

Midwest 575 * 547 20 8 

South 989 1 897 73 18 

West 561 * 513 40 8 

Day of Week 

Weekday 1848 2 1724 100 22 

Weekend 932 1 860 54 17 

Season 

Winter 780 * 741 35 4 

Spring 691 * 655 27 9 

Summer 745 2 674 54 15 

Fall 564 1 514 38 11 

Asthma 

No 2563 2 2384 142 35 

Yes 207 1 190 12 4 

DK 10 * 10 * * 

Angina 37 

No 2698 3 2507 151 2 

Yes 68 * 63 3 * 

DK 14 * 14 * 

Bronchitis/Emphysema 

No 2648 3 2457 149 39 

Yes 121 * 116 5 * 

DK 11 * 11 * * 

Note: * = Missing data; DK = Don’t know; N = Sample size; Refused = Respondent refused to answer. 

Source: Tsang and Klepeis, 1996. 
Table 10-50. Estimated Number of Participants in Marine Recreational Fishing by State and Subregion 

Subregion State Coastal Non Coastal Out of State Total Participants 

Participants Participants 

a 

a 

Pacific So. California 902 8 159 910 

N. California 534 99 63 633 

Oregon 265 19 78 284 

TOTAL 1,701 126 

North Atlantic Connecticut 186 * 47 186 

Maine 93 9 100 102 

Massachusetts 377 69 273 446 

New Hampshire 34 10 32 44 

Rhode Island 97 * 157 97 

TOTAL 787 88 

b 

Mid-Atlantic Delaware 90 * 159 90 

Maryland 540 32 268 572 

New Jersey 583 9 433 592 

New York 539 13 70 552 

Virginia 294 29 131 323 

TOTAL 1,046 83 

South Atlantic Florida 1,201 * 741 1,201 

Georgia 89 61 29 150 

N. Carolina 398 224 745 622 

S. Carolina 131 77 304 208 

TOTAL 1,819 362 

Gulf of Mexico Alabama 95 9 101 104 

Florida 1,053 * 1,349 1,053 

Louisiana 394 48 63 442 

Mississippi 157 42 51 200 

TOTAL 1,699 99 

GRAND TOTAL 8,053 760 

Not additive across states. One person can be counted as "OUT OF STATE" for more than one state. a 

An asterisk (*) denotes no non-coastal counties in state. b 

Source: NMFS, 1993. 
Table 10-51. Estimated Weight of Fish Caught (Catch Type A and B1) by 

Marine Recreational Fishermen, by Wave and Subregion 

Atlantic and Gulf Pacific 

Region Weight (1000 kg) Region Weight (1000 kg) 

Jan/Feb South Atlantic 1,060 So. California 

Gulf 3,683 N. California 

418 

101 

TOTAL 4,743 TOTAL 

Oregon 

684 

165 

Mar/Apr North Atlantic 310 So. California 

Mid Atlantic 1,030 N. California 

South Atlantic 1,913 Oregon

Gulf 3,703 TOTAL 

TOTAL 6,956 

590 

346 

144 

1,080 

May/Jun North Atlantic 3,272 N. California 

Mid Atlantic 4,815 Oregon

South Atlantic 4,234 TOTAL 

So.California 

563 

581 

2,339 

1,195 

Gulf 5,936 

TOTAL 18,257 So. California 1,566 

Jul/Aug North Atlantic 4,003 Oregon

Mid Atlantic 9,693 TOTAL 

South Atlantic 4,032 

N. California 

39 

2,706 

1,101 

Gulf 5,964 So. California 

TOTAL 23,692 N. California 

859 

1,032 

Sep/Oct North Atlantic 2,980 TOTAL 

Mid Atlantic 7,798 

South Atlantic 3,296 So. California 

Oregon

2,615 

447 

724 

Gulf 7,516 N. California 

TOTAL 21,590 Oregon

TOTAL 

417 

65 

929 

Nov/Dec North Atlantic 456 

Mid Atlantic 1,649 GRAND TOTAL 

South Atlantic 2,404 

10,353 

Gulf 4,278 

TOTAL 8,787 

GRAND TOTAL 84,025 

Source: NMFS, 1993. 
c 

Table 10-52. Average Daily Intake (g/day) of Marine Finfish, by Region and Coastal Status 

Intake Among Anglers 

Per-Capita Per-Capita Proportion of 

Regiona Mean 95th Percentile (Coastal)b (Coastal & Non-Coastal)c Population Coasta

N. Atlantic 6.2 20.1 1.2 1.1 0.82 

Mid-Atlantic 6.3 18.9 1.2 0.9 0.70 

S. Atlantic 4.7 15.9 1.5 1.0 0.51 

All Atlantic 5.6 18.0 1.3 0.9 0.66 

Gulf 7.2 26.1 3.0 1.9 0.60 

S. California 2.0 5.5 0.2 0.2 0.96 

N. California 2.0 5.7 0.3 0.3 0.70 

Oregon 2.2 8.9 0.5 0.5 0.87 

All Pacific 2.0 6.8 0.3 0.3 0.86 

a N. Atlantic - ME, NH, MA, RI, and CT; Mid-Atlantic - NY, NJ, MD, DE, and VA; S. Atlantic - NC, SC, GA, and FL (Atlantic Coast); Gulf - AL, MS,

LA, and FL (Gulf Coast). 

b Mean intake rate among entire coastal population of region. 

Mean intake rate among entire population of region. 

Source: NMFS, 1993. 
Table 10-53. Estimated Weight of Fish Caught (Catch Type A and B1) by Marine Recreational Fishermen a

 by Species Group and Subregion, Atlantic and Gulf 

North Atlantic Mid Atlantic South Atlantic Gulf All Regions 

(1,000 kg) (1,000 kg) (1,000 kg) (1,000 kg) (1,000 kg) 

Cartilaginous fishes 66 1,673 162 318 2,219 

Eels 14 9 * 0 b c 23 

Herrings 118 69 1 89 177 

Catfishes 0 306 138 535 979 

Toadfishes 0 7 0 * 7 

Cods and Hakes 2,404 988 4 0 1,396 

Searobins 2 68 * * 70 

Sculpins 1 * 0 0 1 

Temperate Basses 837 2,166 22 4 2,229 

Sea Basses 22 2,166 644 2,477 5,309 

Bluefish 4,177 3,962 1,065 158 5,362 

Jacks 0 138 760 2,477 3,375 

Dolphins 65 809 2,435 1,599 4,908 

Snappers 0 * 508 3,219 3,727 

Grunts 0 9 239 816 1,064 

Porgies 132 417 1,082 2,629 4,160 

Drums 3 2,458 2,953 9,866 15,280 

Mullets 1 43 382 658 1,084 

Barracudas 0 * 356 244 600 

Wrasses 783 1,953 46 113 2,895 

Mackerels and Tunas 878 3,348 4,738 4,036 13,000 

Flounders 512 4,259 532 377 5,680 

Triggerfishes/Filefishes 0 48 109 544 701 

Puffers * 16 56 4 76 

Other fishes 105 72 709 915 1,801 

For Catch Type A and B1, the fish were not thrown back. a 

An asterisk (*) denotes data not reported. b 

Zero (0) = < 1000 kg. c 

Source: NMFS, 1993. 
Table 10-54. Estimated Weight of Fish Caught (Catch Type A and B1) by Marine Recreational a

 Fishermen by Species Group and Subregion, Pacific 

Southern California Northern California Oregon 

Species Group (1,000 kg) (1,000 kg) (1,000 kg) Total 

Cartilaginous fish 35 162 1 198 

Sturgeons 0 89 13 b 102 

Herrings 10 15 40 65 

Anchovies * 7 0 c 7 

Smelts 0 71 0 71 

Cods and Hakes 0 0 0 0 

Silversides 58 148 0 206 

Striped Bass 0 51 0 51 

Sea Basses 1,319 17 0 1,336 

Jacks 469 17 1 487 

Croakers 141 136 0 277 

Sea Chubs 53 1 0 54 

Surfperches 74 221 47 342 

Pacific Barracuda 866 10 0 876 

Wrasses 73 5 0 78 

Tunas and Mackerels 1,260 36 1 1,297 

Rockfishes 409 1,713 890 3,012 

California Scorpionfish 86 0 0 86 

Sablefishes 0 0 5 5 

Greenlings 22 492 363 877 

Sculpins 6 81 44 131 

Flatfishes 106 251 5 362 

Other fishes 89 36 307 432 

For Catch Type A and B1, the fish were not thrown back. a 

Zero (0) = <1000 kg. b 

An asterisk (*) denotes data not reported. c 

Source: NMFS, 1993. 
Table 10-55. Median Intake Rates Based on Demographic Data of Sport Fishermen and Their Family/Living Group 

Percent of total interviewed Median intake rates 

(g/person-day) 

Ethnic Group 

Caucasian 42 46.0 

Black 24 24.2 

Mexican-American 16 33.0 

Oriental/Samoan 13 70.6 

Other 5 -­

Age (years) 

< 17 11 27.2 

18 - 40 52 32.5 

41 - 65 28 39.0 

> 65 9 113.0 

a

 Not reported. a 

Source: Puffer et al., 1981. 
Table 10-56. Cumulative Distribution of Total Fish/Shellfish Consumption by Surveyed Sport Fishermen

 in the Metropolitan Los Angeles Area 

Percentile Intake rate (g/person-day) 

5 2.3 

10 4.0 

20 8.3 

30 15.5 

40 23.9 

50 36.9 

60 53.2 

70 79.8 

80 120.8 

90 224.8 

95 338.8 

Source: Puffer et al. (1981). 
Table 10-57. Catch Information for Primary Fish Species Kept by Sport Fishermen (n = 1059) 

Species Average Weight (Grams) Percent of Fishermen who Caught 

White Croaker 153 34 

Pacific Mackerel 334 25 

Pacific Bonito 717 18 

Queenfish 143 17 

Jacksmelt 223 13 

Walleye Perch 115 10 

Shiner Perch 54 7 

Opaleye 307 6 

Black Perch 196 5 

Kelp Bass 440 5 

California Halibut 1752 4 

Shellfish 421 3 a

 Crab, mussels, lobster, abalone. a 

Source: Modified from Puffer et al., 1981. 
Table 10-58. Percent of Fishing Frequency During the Summer and Fall Seasons in Commencement Bay, Washington 

Fishing Frequency in the Summer in the Fall in the Fall 

Frequency Percent Frequency Percent Frequency Percent a b c 

Daily 10.4 8.3 5.8 

Weekly 50.3 52.3 51.0 

Monthly 20.1 15.9 21.1 

Bimonthly 6.7 3.8 4.2 

Biyearly 4.4 6.1 6.3 

Yearly 8.1 13.6 11.6 

Summer - July through September, includes 5 survey days and 4 survey areas (i.e., area #1, #2, #3 and #4) a 

Fall - September through November, includes 4 survey days and 4 survey areas (i.e., area #1, #2, #3 and #4) b 

Fall - September through November, includes 4 survey days described in footnote plus an additional survey area (5 survey c b 

areas) (i.e., area #1, #2, #3, #4 and #5) 

Source: Pierce et al., 1981. 
Table 10-59. Selected Percentile Consumption Estimates (g/day) for the Survey and Total Angler Populations 

Based on the Reanalysis of the Puffer et al. (1981) and Pierce et al. (1981) Data 

50th Percentile 90th Percentile 

Survey Population

 Puffer et al. (1981) 37 225

 Pierce et al. (1981) 19 155 

Average 28 190 

Total Angler Population

 Puffer et al. (1981) 2.9 35

 Pierce et al. (1981) 1.0 13 

a b 

Average 2.0 24 

Estimated based on the average intake for the 0 - 90th percentile anglers. a 

Estimated based on the average intake for the 91st - 96th percentile anglers. b 

Source: Price et al., 1994. 
Table 10-60. Means and Standard Deviations of Selected Characteristics by 

Subpopulation Groups in Everglades, Florida 

Variables Mean ± Std. Dev. 

(N =330) a 

b 

Range 

Age (years) 38.6 ± 18.8 2 - 81 

Sex

 Female 38% -­

Male 62% --

Race/ethnicity

 Black 46% -­

White 43% -­

Hispanic 11% -­

Number of Years Fished 15.8 ± 15.8 0 - 70 

Number Per Week Fished in Past 6 Months of Survey Period 1.8 ± 2.5 0 - 20 

Number Per Week Fished in Last Month of Survey Period 1.5 ± 1.4 0 - 12 

Aware of Health Advisories 71% -­

Number of respondents who reported consuming fish a 

Std. Dev. = standard deviation b 

Source: U.S. DHHS, 1995 
Table 10-61. Mean Fish Intake Among Individuals Who Eat Fish and Reside 

in Households With Recreational Fish Consumption 

Recreational Recreational Total Fish Recreationa

All Fish Fish meals/week Total Fish Fish grams/ Fish grams/ 

Group meals/week n grams/day grams/day kg/day kg/day 

All household 0.686 0.332 2196 21.9 11.0 0.356 0.178 

members 

Respondents (i.e., 0.873 0.398 748 29.4 14.0 0.364 0.168 

licensed anglers) 

Age Groups (years) 

1-5 0.463 0.223 121 11.4 5.63 0.737 0.369 

6 to 10 0.49 0.278 151 13.6 7.94 0.481 0.276 

1 to 20 0.407 0.229 349 12.3 7.27 0.219 0.123 

21 to 40 0.651 0.291 793 22 10.2 0.306 0.139 

40 to 60 0.923 0.42 547 29.3 14.2 0.387 0.186 

60 to 70 0.856 0.431 160 28.2 14.5 0.377 0.193 

71 to 80 1.0 0.622 45 32.3 20.1 0.441 0.271 

80+ 0.8 0.6 10 26.5 20 0.437 0.345 

Source: U.S. EPA analysis using data from West et al., 1989. 
Table 10-62. Comparison of Seven-Day Recall and Estimated Seasonal Frequency for Fish Consumption 

Usual Fish Consumption Mean Fish Meals/Week Usual frequency Value Selected 

Frequency Category 7-day Recall Data for Data Analysis (times/week) 

Almost daily no data 4 [if needed] 

2-4 times a week 1.96 2 

Once a week 1.19 1.2 

2-3 times a month 0.840 (3.6 times/month) 0.7 (3 times/month) 

Once a month 0.459 (1.9 times/month) 0.4 (1.7 times/month) 

Less often 0.306 (1.3 times/month) 0.2 (0.9 times/month) 

Source: U.S. EPA analysis using data from West et al., 1989. 
Table 10-63. Distribution of Usual Fish Intake Among Survey Main Respondents 

Who Fished and Consumed Recreationally Caught Fish 

Recreational Recreational 

All Fish Recreational All Fish Intake Fish Intake All Fish Intake Fish Intake 

Meals/Week Fish grams/day grams/day grams/ kg/day grams/kg/day 

Meals/Week 

n 738 738 738 738 726 726 

mean 0.859 0.447 27.74 14.42 0.353 0.1806 

10% 0.300 0.040 9.69 1.29 0.119 0.0159 

25% 0.475 0.125 15.34 4.04 0.187 0.0504 

50% 0.750 0.338 24.21 10.90 0.315 0.1357 

75% 1.200 0.672 38.74 21.71 0.478 0.2676 

90% 1.400 1.050 45.20 33.90 0.634 0.4146 

95% 1.800 1.200 58.11 38.74 0.747 0.4920 

Source: U.S. EPA analysis using data from West et al., 1989. 
Table 10-64. Estimates of Fish Intake Rates of Licensed Sport Anglers in Maine During the 1989-1990

 Ice Fishing or 1990 Open-Water Seasonsa 

Intake Rates (grams/day) 

Percentile Rankings All Waters Rivers and Streams b 

All Anglers Consuming Anglers River Anglers Consuming Anglers c 

(N = 1,369) (N = 1,053) (N = 741) (N = 464) 

d e 

50th (median) 1.1 2.0 0.19 0.99 

66th 2.6 4.0 0.71 1.8 

75th 4.2 5.8 1.3 2.5 

90th 11.0 13.0 3.7 6.1 

95th 21.0 26.0 6.2 12.0 

Arithmetic Mean 5.0 6.4 1.9 3.7 f 

[79] [77] [82] [81] 

Estimates are based on rank except for those of arithmetic mean. a 

All waters based on fish obtained from all lakes, ponds, streams and rivers in Maine, from other household sources and from b 

other non-household sources. 

Licensed anglers who fished during the seasons studied and did or did not consume freshwater fish, and licensed anglers who c 

did not fish but ate freshwater fish caught in Maine during those seasons. 

Licensed anglers who consumed freshwater fish caught in Maine during the seasons studied. d 

Those of the "all anglers" who fished on rivers or streams (consumers and nonconsumers). e 

Values in brackets [ ] are percentiles at the mean consumption rates. f 

Source: Chemrisk, 1991; Ebert et al., 1993. 
Table 10-65. Analysis of Fish Consumption by Ethnic Groups for "All Waters" (g/day)a 

Consuming Anglersb 

French Native Other White 

Canadian Irish Italian American Non-Hispanic Scandinavia

Heritage Heritage Heritage Heritage Heritage Heritage 

N of Cases 201 138 27 96 533 37 

Median (50th percentile) 2.3 2.4 1.8 2.3 1.9 1.3 c,d 

66th percentile 4.1 4.4 2.6 4.7 3.8 2.6 c,d 

75th percentile 6.2 6.0 5.0 6.2 5.7 4.9 c,d 

Arithmetic Mean 7.4 5.2 4.5 10 6.0 5.3 c 

Percentile at the Mean 80 70 74 83 76 78 d 

90th percentile 15 12 12 16 13 9.4 c,d 

95th percentile 27 20 21 51 24 25 c,d 

Percentile at 6.5 g/day 77 75 81 77 77 84 d,e 

"All Waters" based on fish obtained from all lakes, ponds, streams and rivers in Maine, from other household sources and from a 

other non-household sources. 

"Consuming Anglers" refers to only those anglers who consumed freshwater fish obtained from Maine sources during the 1989

b 

1990 ice fishing or 1990 open water fishing season. 

The average consumption per day by freshwater fish consumers in the household. c 

Calculated by rank without any assumption of statistical distribution. d 

Fish consumption rate recommended by U.S. EPA (1984) for use in establishing ambient water quality standards. e 

Source: Chemrisk, 1991. 
Table 10-66. Total Consumption of Freshwater Fish Caught by All Survey Respondents During the 1990 Season 

Species 

Ice Fishing Lakes and Ponds Rivers and Streams 

Quantity Grams Quantity Grams Quantity Grams 

Consumed (x10 ) Consumed (x10 ) Consumed (x10 ) 

(#) Consumed (#) Consumed (#) Consume

3 3 3 

Landlocked salmon 832 290 928 340 305 120 

Atlantic salmon 3 1.1 33 9.9 17 11 

Togue (Lake trout) 483 200 459 160 33 2.7 

Brook trout 1,309 100 3,294 210 10,185 420 

Brown trout 275 54 375 56 338 23 

Yellow perch 235 9.1 1,649 52 188 7.4 

White perch 2,544 160 6,540 380 3,013 180 

Bass (smallmouth and largemouth) 474 120 73 5.9 787 130 

Pickerel 1,091 180 553 91 303 45 

Lake whitefish 111 20 558 13 55 2.7 

Hornpout (Catfish and bullheads) 47 8.2 1,291 100 180 7.8 

Bottom fish (Suckers, carp and sturgeon) 50 81 62 22 100 6.7 

Chub 0 0 252 35 219 130 

Smelt 7,808 150 428 4.9 4,269 37 

Other 201 210 90 110 54 45 

TOTALS 15,463 1,583.4 16,587 1,590 20,046 1,168 

Source: Chemrisk, 1991. 
Table 10-67. Mean Sport-Fish Consumption by Demographic Variables, Michigan Sport 

Anglers Fish Consumption Study, 1991-1992 

N Mean (g/day) 95% C.I. 

Incomea 

<$15,000 290 21.0 16.3 - 25.8 

$15,000 - $24,999 369 20.6 15.5 - 25.7 

$25,000 - $39,999 662 17.5 15.0 - 20.1 

>$40,000 871 14.7 12.8 - 16.7 

Education 

Some High School 299 16.5 12.9 - 20.1 

High School Degree 1,074 17.0 14.9 - 19.1 

Some College-College Degree 825 17.6 14.9 - 20.2 

Post Graduate 231 14.5 10.5 - 18.6 

Residence Sizeb 

Large City/Suburb (>100,000) 487 14.6 11.8 - 17.3 

Small City (20,000-100,000) 464 12.9 10.7 - 15.0 

Town (2,000-20,000) 475 19.4 15.5 - 23.3 

Small Town (100-2,000) 272 22.8 16.8 - 28.8 

Rural, Non Farm 598 17.7 15.1 - 20.3 

Farm 140 15.1 10.3 - 20.0 

Age (years) 

16-29 266 18.9 13.9 - 23.9 

30-39 583 16.6 13.5 - 19.7 

40-49 556 16.5 13.4 - 19.6 

50-59 419 16.5 13.6 - 19.4 

60+ 596 16.2 13.8 - 18.6 

Sexa 

Male 299 17.5 15.8 - 19.1 

Female 1,074 13.7 11.2 - 16.3 

Race/Ethnicityb 

Minority 160 23.2 13.4 - 33.1 

White 2,289 16.3 14.9 - 17.6

 P < .01, F test a

 P < .05, F test b 

Source: West et al., 1993 
Table 10-68. Distribution of Fish Intake Rates 

(from all sources and from sport-caught sources) 

For 1992 Lake Ontario Anglers

Percentile of Lake Ontario Anglers Fish from All Sources (g/day) Sport-Caught Fish (g/day)

25% 8.8 0.6

50% 14.1 2.2

75% 23.2 6.6

90% 34.2 13.2

95% 42.3 17.9

99% 56.6 39.8

Source. Connelly et al., 1996.
Table 10-69. Mean Annual Fish Consumption (g/day) 

for Lake Ontario Anglers, 1992, 

by Sociodemographic Characteristics 

Mean Consumption 

Demographic Group Fish from all Sources Sport-Caught Fish 

Overall 17.9 4.9 

Residence

 Rural 17.6 5.1

 Small City 20.8 6.3

 City (25-100,000) 19.8 5.8

 City (> 100,000) 13.1 2.2 

Income

 < $20,000 20.5 4.9

 $21,000-34,000 17.5 4.7

 $34,000-50,000 16.5 4.8

 >$50,000 20.7 6.1 

Age (years)

 <30 13.0 4.1

 30-39 16.6 4.3

 40-49 18.6 5.1

 50+ 21.9 6.4 

Education

 < High School 17.3 7.1

 High School Graduate 17.8 4.7

 Some College 18.8 5.5

 College Graduate 17.4 4.2

 Some Post Grad. 20.5 5.9 

Note - Scheffe’s test showed statistically significant differences between residence types (for all sources and sport 

caught) and age groups (all sources). 

Source: Connelly et al., 1996. 
Table 10-70. Percentile and Mean Intake Rates for Wisconsin Sport Anglers 

Percentile Annual Number of Sport Caught Meals Intake Rate of Sport-Caught Meals (g/day

25th 4 1.7 

50th 10 4.1 

75th 25 10.2 

90th 50 20.6 

95th 60 24.6 

98th 100 41.1 

100th 365 150 

Mean 18 7.4 

Source: Raw data on sport-caught meals from Fiore et al., 1989. EPA calculated intake rates using a value of 150 

grams per fish meal; this value is dervied from Pao et al., 1982. 
Table 10-71. Sociodemographic Characteristics 

of Respondents

Category Subcategory Percent of Totala

Geographic Distribution Upper Hudson 18 %

Mid Hudson 35 %

Lower Hudson 48 %

Age Distribution (years) < 14 3 %

15 - 29 26 %

30 - 44 35 %

45 - 59 23 %

> 60 12 %

Annual Household Income < $10,000 16 %

$10 - 29,999 41 %

$30 - 49,999 29 %

$50 - 69,999 10 %

$70 - 89,999 2 %

> $90,000 3 %

Ethnic Background Caucasian American 67 %

African American 21 %

Hispanic American 10 %

Asian American 1 %

Native American 1 %

 A total of 336 shore-based anglers were interviewed a

Source: Hudson River Sloop Clearwater, Inc., 1993
Table 10-72. Number of Grams Per Day of Fish Consumed by All Adult Respondents 

(Consumers and Non-consumers Combined) - Throughout the Year 

Number of Grams/Day Cumulative Percent Number of Grams/Day Cumulative Percent 

0.00 8.9% 64.8 80.6% 

1.6 9.0% 72.9 81.2% 

3.2 10.4% 77.0 81.4% 

4.0 10.8% 81.0 83.3% 

4.9 10.9% 97.2 89.3% 

6.5 12.8% 130 92.2% 

7.3 12.9% 146 93.7% 

8.1 13.7% 162 94.4% 

9.7 14.4% 170 94.8% 

12.2 14.9% 194 97.2% 

13.0 16.3% 243 97.3% 

16.2 22.8% 259 97.4% 

19.4 24.0% 292 97.6% 

20.2 24.1% 324 98.3% 

24.3 27.9% 340 98.7% 

29.2 28.1% 389 99.0% 

32.4 52.5% 486 99.6% 

38.9 52.9% 648 99.7% 

40.5 56.5% 778 99.9% 

48.6 67.6% 972 100% 

N = 500 

Weighted Mean = 58.7 grams/day (g/d) 

Weighted SE = 3.64 

90th Percentile: 97.2 g/d < (90th) < 130 g/d 

95th Percentile . 170 g/d 

99th Percentile = 389 g/d 

Source: CRITFC, 1994 
Table 10-73. Fish Intake Throughout the Year by Sex, Age, and Location by All Adult Respondents 

N (grams/day) Weighted SE 

Weighted Mean 

Sex 

Female 278 55.8 4.78 

Male 222 62.6 5.60 

Total 500 58.7 3.64 

Age (years) 

18-39 287 57.6 4.87 

40-59 155 55.8 4.88 

60 & Older 58 74.4 15.3 

Total 500 58.7 3.64 

Location 

On Reservation 440 60.2 3.98 

Off Reservation 60 47.9 8.25 

Total 500 58.7 3.64 

Source: CRITFC, 1994. 
Table 10-74. Children's Fish Consumption Rates - Throughout Year 

Number of Grams/Day Unweighted Cumulative Percent 

0.0 21.1% 

0.4 21.6% 

0.8 22.2% 

1.6 24.7% 

2.4 25.3% 

3.2 28.4% 

4.1 32.0% 

4.9 33.5% 

6.5 35.6% 

8.1 47.4% 

9.7 48.5% 

12.2 51.0% 

13.0 51.5% 

16.2 72.7% 

19.4 73.2% 

20.3 74.2% 

24.3 76.3% 

32.4 87.1% 

48.6 91.2% 

64.8 94.3% 

72.9 96.4% 

81.0 97.4% 

97.2 98.5% 

162.0 100% 

N = 194 

Unweighted Mean = 19.6 grams/day 

Unweighted SE = 1.94 

Source: CRITFC, 1994. 
Table 10-75. Sociodemographic Factors and Recent Fish Consumption 

Peak Consumptiona Recent Consumptionb 

d Averagec $3 (%) Walleye N. Pike Muskellunge Bass 

All participants (N-323) 1.7 20 4.2 0.3 0.3 0.5 

Gender 

Male (n-148) 1.9 26 5.1 0.5a 0.5 0.7a 

Female (n-175) 1.5 15 3.4 0.2 0.1 0.3 

Age (y) 

<35 (n-150) 1.8 23 5.3a 0.3 0.2 0.7 

$35 (n-173) 1.6 17 3.2 0.4 0.3 0.3 

High School Graduate 

No (n-105) 1.6 18 3.6 0.2 0.4 0.7 

Yes (n-218) 1.7 21 4.4 0.4 0.2 0.4 

Unemployed 

Yes (n-78) 1.9 27 4.8 0.6 0.6 1.1 

No (n-245) 1.6 18 4.0 0.3 0.2 0.3 

a Highest number of fish meals consumed/week. b Number of meals of each species in the previous 2 months. c Average peak fish consumption. d Percentage of population reporting peak fish consumption of $3 fish meals/week. 

Source: Peterson et al., 1994. 
Table 10-76. Number of Local Fish Meals Consumed Per Year by Time Period for All Respondents 

Time Period 

Number of 

Local Fish During Pregnancy #1 Yr. Before Pregnancya >Yr. Before Pregnancyb 

Meals 

Consumed Per Mohawk Control Mohawk Control Mohawk Control 

Year Nc % Nc % Nc % Nc % Nc % Nc % 

None 63 64.9 109 

1 - 9 24 24.7 24 

10 - 19 5 5.2 7 

20 - 29 1 1.0 5 

30 - 39 0 0.0 2 

40 - 49 0 0.0 1 

50+ 4 4.1 6 

Total 97 100.0 154 

70.8 42 43.3 99 64.3 20 20.6 93 60.4 

15.6 40 41.2 31 20.1 42 43.3 35 22.7 

4.5 4 4.1 6 3.9 6 6.2 8 5.2 

3.3 3 3.1 3 1.9 9 9.3 5 3.3 

1.3 0 0.0 3 1.9 1 1.0 1 0.6 

0.6 1 1.0 1 0.6 1 1.0 1 0.6 

3.9 7 7.2 11 7.1 18 18.6 11 7.1 

100.0 97 100.0 154 100.0 97 100.0 154 100.0 

a p <0.05 for Mohawk vs. Control. b p <0.001 for Mohawk vs. Control. c N = number of respondents. 

Source: Fitzgerald et al., 1995. 
Table 10-77. Mean Number of Local Fish Meals Consumed Per Year by Time

 Period for All Respondents and Consumers Only 

All Respondents Consumers Only 

(N=97 Mohawks and 154 Controls) (N=82 Mohawks and 72 Controls)

During #1 Yr. Before >1 Yr. Before During #1 Yr. Before >1 Yr. Befor

Pregnancy Pregnancy Pregnancy Pregnancy Pregnancy Pregnancy 

Mohaw 3.9 (1.2) 9.2 (2.3) 23.4 (4.3)a 4.6 (1.3) 10.9 (2.7) 27.6 (4.9) 

k 7.3 (2.1) 10.7 (2.6) 10.9 (2.7) 15.5 (4.2)a 23.0 (5.1)b 23.0 (5.5) 

Control 

a p <0.001 for Mohawk vs. Control. b p<0.05 for Mohawk vs. Control 

( ) = standard error. 

Test for linear trend: 

p<0.001 for Mohawk (All participants and consumers only); 

p=0.07 for Controls (All participants and consumers only). 

Source: Fitzgerald et al., 1995. 
c 

Table 10-78. Mean Number of Local Fish Meals Consumed Per Year by Time Period and Selected 

Characteristics for All Respondents (Mohawk, N=97; Control, N=154) 

Time Period 

During Pregnancy #1 Year Before Pregnancy >1 Year Before Pregnancy 

Background Variable Mohawk Control Mohawk Control Mohawk Control 

Age (Yrs) 

<20 7.7 0.8 13.5 13.9 27.4 10.4 

20 - 24 1.3 5.9 5.7 14.5 20.4 15.9 

25 - 29 3.9 9.9 15.5 6.2 25.1 5.4 

30 - 34 12.0 7.6 9.5 2.9 12.0 5.6 

>34 1.8 11.2 1.8 26.2 52.3 22.1a 

Education (Yrs) 

<12 6.3 7.9 14.8 12.4 24.7 8.6 

12 7.3 5.4 8.1 8.4 15.3 11.4 

13 - 15 1.7 10.1 8.0 15.4 29.2 13.3 

>15 0.9 6.8 10.7 0.8 18.7 2.1 

Cigarette Smoking 

Yes 3.8 8.8 10.4 13.0 31.6 10.9 

No 3.9 6.4 8.4 8.3 18.1 10.8 

Alcohol Consumption 

Yes 4.2 9.9 6.8 13.8 18.0 14.8 

No 3.8 6.3b 12.1 4.7c 29.8 2.9d 

a F (4,149) = 2.66, p=0.035 for Age Among Controls. b F (1,152) = 3.77, p=0.054 for Alcohol Among Controls. 

F (1,152) = 5.20, p=0.024 for Alcohol Among Controls. d F (1,152) = 6.42, p=0.012 for Alcohol Among Controls. 

Source: Fitzgerald et al., 1995. 
Table 10-79. Percentage of Individuals Using Various Cooking Methods at Specified Frequencies 

Study Frequency Bake Fry Grill Poach Boil Smoke 

Use Pan Fry Deep Broil or 

Raw Oth

Connelly et al., Always 24(a) 51 13 24(a) 

1992 Ever 75(a) 88 59 75(a) 

Connelly et al., Always 13 4 4 

1996 Ever 84 72 42 

CRITFC, 1994 At least 79 51 14 27 11 46 31 

monthly 

1 34(

29

49(

Ever 98 80 25 39 17 73 66 3 67(

71

75(

Fitzgerald et al., Not 94(e)(f) 71(e)(g) 

1995 Specified 

Puffer et al., As Primary 16.3 52.5 12 

1981 Method

0.25 19(

24 and 75 listed as bake, BBQ, or poach a

 Dried b

 Roasted c

 Canned d

 Not specified whether deep or pan fried e

 Mohawk women f

 Control population g

 boil, stew, soup, or steam h 
Table 10-80. Percent Moisture and Fat Content for Selected Speciesa 

Species (%) (%) Comments 

Moisture 

Content Total Fat Content b 

FINFISH 

Anchovy, European 73.37 4.101 Raw 

Bass 75.66 3.273 Freshwater, mixed species, raw 

Bass, Striped 79.22 1.951 Raw 

Bluefish 70.86 3.768 Raw 

Butterfish 74.13 NA Raw 

Carp 76.31 4.842 Raw 

Catfish 76.39 3.597 Channel, raw 

Cod, Atlantic 81.22 0.456 Atlantic, raw 

Cod, Pacific 81.28 0.407 Raw 

Croaker, Atlantic 78.03 2.701 Raw 

Dolphinfish, Mahimahi 77.55 0.474 Raw 

Drum, Freshwater 77.33 4.463 Raw 

Flatfish, Flounder and Sole 79.06 0.845 Raw 

Grouper 79.22 0.756 Raw, mixed species 

Haddock 79.92 0.489 Raw 

Halibut, Atlantic & Pacific 77.92 1.812 Raw 

Halibut, Greenland 70.27 12.164 Raw 

Herring, Atlantic & Turbot, domestic species 72.05 7.909 Raw 

Herring, Pacific 71.52 12.552 Raw 

Mackerel, Atlantic 63.55 9.076 Raw 

Mackerel, Jack 69.17 4.587 Canned, drained solids 

Mackerel, King 75.85 1.587 Raw 

Mackerel, Pacific & Jack 70.15 6.816 Canned, drained solids 

Mackerel, Spanish 71.67 5.097 Raw 

Monkfish 83.24 NA Raw 

Mullet, Striped 77.01 2.909 Raw 

Ocean Perch, Atlantic 78.70 1.296 Raw 

Perch, Mixed species 79.13 0.705 Raw 

Pike, Northern 78.92 0.477 Raw 

Pike, Walleye 79.31 0.990 Raw 

50.30 8.535 Canned in oil, drained solids 

69.63 6.208 Cooked, dry heat 

58.81 12.224 Channel, cooked, breaded and fried 

75.61 0.582 Canned, solids and liquids 

75.92 0.584 Cooked, dry heat 

16.14 1.608 Dried and salted 

59.76 11.713 Cooked, breaded and fried 

73.16 1.084 Cooked, dry heat 

73.36 0.970 Cooked, dry heat 

74.25 0.627 Cooked, dry heat 

71.48 0.651 Smoked 

71.69 2.324 Cooked, dry heat 

64.16 10.140 Cooked, dry heat 

59.70 10.822 Kippered 

55.22 16.007 Pickled 

53.27 15.482 Cooked, dry heat 

68.46 5.745 Cooked, dry heat 

70.52 3.730 Cooked, dry heat 

72.69 1.661 Cooked, dry heat 

73.25 0.904 Cooked, dry heat 

72.97 0.611 Cooked, dry heat 
Table 10-80. Percent Moisture and Fat Content for Selected Species (continued) a 

Species (%) (%) Comments 

Moisture Total Fat 

Content Content b 

Pollock, Alaska & Walleye 81.56 0.701 Raw 

Pollock, Atlantic 78.18 0.730 Raw 

Rockfish, Pacific, mixed species 79.26 1.182 Raw (Mixed species) 

Roughy, Orange 75.90 3.630 Raw 

Salmon, Atlantic 68.50 5.625 Raw 

Salmon, Chinook 73.17 9.061 Raw 

Salmon, Chum 75.38 3.279 Raw 

Salmon, Coho 72.63 4.908 Raw 

Salmon, Pink 76.35 2.845 Raw 

Salmon, Red & Sockeye 70.24 4.560 Raw 

Sardine, Atlantic 59.61 10.545 Canned in oil, drained solids with bone 

Sardine, Pacific 68.30 11.054 Canned in tomato sauce, drained solids with bone 

Sea Bass, mixed species 78.27 1.678 Cooked, dry heat 

Seatrout, mixed species 78.09 2.618 Raw 

Shad, American 68.19 NA Raw 

Shark, mixed species 73.58 3.941 Raw 

Snapper, mixed species 76.87 0.995 Raw 

Sole, Spot 75.95 3.870 Raw 

Sturgeon, mixed species 76.55 3.544 Raw 

Sucker, white 79.71 1.965 Raw 

Sunfish, Pumpkinseed 79.50 0.502 Raw 

Swordfish 75.62 3.564 Raw 

Trout, mixed species 71.42 5.901 Raw 

Trout, Rainbow 71.48 2.883 Raw 

Tuna, light meat 59.83 7.368 Canned in oil, drained solids 

Tuna, white meat 64.02 NA Canned in oil 

Tuna, Bluefish, fresh 68.09 4.296 Raw 

Turbot, European 76.95 NA Raw 

Whitefish, mixed species 72.77 5.051 Raw 

Whiting, mixed species 80.27 0.948 Raw 

Yellowtail, mixed species 74.52 NA Raw 

74.06 0.929 Cooked, dry heat 

73.41 1.515 Cooked, dry heat (mixed species) 

72.00 3.947 Smoked 

70.77 4.922 Canned, drained solids with bone 

65.35 6.213 Cooked, moist heat 

68.81 5.391 Canned, solids with bone and liquid 

68.72 6.697 Canned, drained solids with bone 

61.84 9.616 Cooked, dry heat 

72.14 2.152 Raw 

60.09 12.841 Cooked, batter-dipped and fried 

70.35 1.275 Cooked, dry heat 

69.94 4.544 Cooked, dry heat 

62.50 3.829 Smoked 

68.75 4.569 Cooked, dry heat 

63.43 3.696 Cooked, dry heat 

74.51 0.730 Canned in water, drained solids 

69.48 2.220 Canned in water, drained solids 

59.09 5.509 Cooked, dry heat 

70.83 0.799 Smoked 

74.71 1.216 Cooked, dry heat 
Table 10-80. Percent Moisture and Fat Content for Selected Species (continued) a 

Species (%) (%) Comments 

Moisture Total Fat 

Content Content b 

SHELLFISH 

Crab, Alaska King 79.57 NA Raw 

Crab, Blue 79.02 0.801 Raw 

Crab, Dungeness 79.18 0.616 Raw 

Crab, Queen 80.58 0.821 Raw 

Crayfish, mixed species 80.79 0.732 Raw 

Lobster, Northern 76.76 NA Raw 

Shrimp, mixed species 75.86 1.250 Raw 

Spiny Lobster, mixed species 74.07 1.102 Imitation made from surimi, raw 

Clam, mixed species 81.82 0.456 Raw 

Mussel, Blue 80.58 1.538 Raw 

Octopus, common 80.25 0.628 Raw 

Oyster, Eastern 85.14 1.620 Raw 

Oyster, Pacific 82.06 1.752 Raw 

Scallop, mixed species 78.57 0.377 Raw 

Squid 78.55 0.989 Raw 

77.55 0.854 Cooked, moist heat 

79.16 0.910 Canned (dry pack or drained solids of wet pack) 

77.43 1.188 Cooked, moist heat 

71.00 6.571 Crab cakes 

75.37 0.939 Cooked, moist heat 

76.03 0.358 Cooked, moist heat 

72.56 1.421 Canned (dry pack or drained solids of wet pack) 

52.86 10.984 Cooked, breaded and fried 

77.28 0.926 Cooked, moist heat 

63.64 0.912 Canned, drained solids 

97.70 NA Canned, liquid 

61.55 10.098 Cooked, breaded and fried 

63.64 0.912 Cooked, moist heat 

61.15 3.076 Cooked, moist heat 

85.14 1.620 Canned (solids and liquid based) raw 

64.72 11.212 Cooked, breaded and fried 

70.28 3.240 Cooked, moist heat 

58.44 10.023 Cooked, breaded and fried 

73.82 NA Imitation, made from Surimi 

64.54 6.763 Cooked, fried 

Imitation, made from surimi 

Data are reported as in the Handbook a 

Total Fat Content - saturated, monosaturated and polyunsaturated b 

NA = Not available 

Source: USDA, 1979-1984 - U.S. Agricultural Handbook No. 8 
Table 10-81. Recommendations - General Population

Mean Intake 95th Percentile of Long-term

(g/day) Intake Distribution (g/day) Study (Reference)

20.1 (Total Fish) U.S. EPA Analysis of CSFII, 1989-9

14.1 (Marine Fish)

 6.0 (Freshwater/Estuarine Fish)

53 (Value of 42 from Javitz was adjusted TRI (Javitz, 1980; Ruffle et al., 1994

upward by 25 percent to account for

recent increase in fish consumption) 
Table 10-82. Recommendations - General Population ­

Fish Serving Size

 Mean Intake (grams) 95th Percentile (grams) Study (Reference) 

129 326 1989-1991 CSFII (U.S. EPA, 1996) 
Table 10-83. Recommendations - Recreational Marine Anglers

 Mean Intake (g/day) 95th Percentile (g/day) Study Location Study 

5.6 18.0 Atlantic NMFS, 1993 

7.2 26.0 Gulf 

2.0 6.8 Pacific 
Table 10-84. Recommendations - Freshwater Anglers 

Mean Intake (g/day) Upper Percentile (g/day) Study Location Reference 

5 13 (95th percentile) Maine Ebert et al., 1992 

5 18 (95th percentile) New York Connelly et al., 1996 

12 39 (96th percentile) Michigan West et al, 1989 

17 --­ Michigan West et al, 1993 
---

---

---

Table 10-85. Recommendations - Native American Subsistence Populations 

Per-Capita (or Mean) Intake Upper Percentile 

(g/day) (g/day) Study Population Reference 

59 170 (95th) 4 Columbia River Tribes CRITFC, 1994 

16 94 Alaska Communities Wolfe and Walker, 198

(Lowest of 94) 

81 94 Alaska Communities Wolfe and Walker, 198

(Median of 94) 

770 94 Alaska Communities Wolfe and Walker, 198

(Highest of 94) 
Table 10-86. Summary of Fish Intake Studies 

Source of Data 

(Reference) 

Population 

Surveyed 

Survey Time Period/Type Analyses Performed (References) Limitations/Advantages 

General Population 

Key Studies 

Javitz, 1980 - TRI 

Survey 

25,162 individuals ­

general population; 

the TRI Survey 

sample 

Sept. 1973-Aug. 1974 (1 year Mean and distribution of fish 

survey). Completed diary over 1 consumption rates grouped by race, 

month period on date of meal age, gender, census region, fish 

consumption, species of fish, species, community type, and religion. 

packaging type, amount of fish Lognormal distribution fit to fish intake 

prepared, number of servings distribution by age and region by Ruffle 

consumed, etc. et al. (1994). 

High response rate (80%); population 

was large and geographically and 

seasonally representative; 

consumption rates based on one 

month of diary data; survey data is over 

20 years out of date 

U.S. EPA, 1996a 11,912 individuals ­

general population 

Participants provided 3 Analysis of CSFII 1989-91. Fish 

consecutive days of dietary data. grouped by habitat (freshwater vs. 

Three survey years (1989-1991) marine) and type (finfish vs. shellfish). 

combined into one data set. Per capita fish intake rates calculated 

using cooked and uncooked equivalent 

weight and reported in g/day and g/kgday; also intake distribution per day 

eating fish. 

Large, geographically representative 

study; relatively recent. Based on 

short-term (3 day) data so long-term 

percentiles of fish intake distribution 

could not be estimated. 

Relevant Studies 

AIHC, 1994 -­ -­ Distributions using @Risk simulation 

software. 

Limited reviews of supporting studies; 

good alternative source of information. 

Pao et al., 1982 37,874 individuals ­

general population 

Participants provided 3 Mean and distribution of average daily 

consecutive days of dietary data. fish intake and average fish intake per 

Survey conducted between April eating occasion; by age-sex groups and 

1977 and March 1978. overall. 

Population was large and 

geographically representative; data 

were based on short-term dietary 

recall; data are almost 20 years out of 

date. 

Tsang and Klepeis, 

1996 

9,386 individuals ­

general population 

Participants provided 24-hour diary Frequency of eating fish and number of 

data. Follow-up questionnaires, servings per month provided. 

survey conducted between 

October 1992 and September 

1994. 

Population large and geographically 

and seasonally balanced; data based 

on recall; intake data not provided. 

USDA, 1992 10,000 individualsgeneral population Participants provided 3 Per capita fish intake rates and percent 

consecutive days of dietary data. of population consuming fish in one 

Survey conducted between April day; by age and sex. 

1987 and March 1988. 

Population was large and 

geographically and seasonally 

balanced; data based on short-term 

dietary recall. 
Table 10-86. Summary of Fish Intake Studies (continued) 

Source of Data 

(Reference) 

Population Surveyed Survey Time Period/Type Analyses Performed (References) Limitations/Advantages 

Recreational-Marine Fish 

Key Study 

NMFS 1986a, b, c; 1993 Atlantic and Gulf Coasts -

41,000 field interviews and 

58,000 telephone 

interviews; Pacific Coast -

38,000 field interviews and 

73,000 telephone 

interviews. 

Telephone interviews with residents Intake rates were not calculated; 

of coastal counties; information on total catch size grouped by marine 

fishing frequency and mode of fishing species, seasons, and number of 

trips. Field interviews with marine fishermen for each coastal region 

anglers; information on area and were presented. 

mode fished, fishing frequency, 

species caught, weight of fish, and 

whether fish were intended to be 

Population was large geographically 

and seasonally balanced; fish caught 

were weighed in the field. No 

information on number of potential 

consumers of catch. 

consumed. 

Relevant Studies 

Pierce et al., 1981 ~500 anglers in 

Commencement Bay, 

Washington 

July-November 1980; creel survey Distribution of fishing frequency; 

interviews conducted consisting of 5 total weight of catch grouped by 

summer days and 4 fall days. species. Re-analysis by Price et 

al. (1994) using inverse fishing 

frequency as sample weights. 

Local survey. Original analysis by 

Pierce et al. (1981) did not calculate 

intake rates; analysis over-estimated 

fishing frequency distribution by 

oversampling frequent anglers. Reanalysis by Price et. al. (1994) 

involved several assumptions; thus 

results are questionable. 

Puffer et al., 1981 1,067 anglers in the Los 

Angeles, California area. 

Creel survey conducted for the full Distribution of sport fish intake 

1980 calendar year. rates. Median rates by age, 

ethnicity and fish species. Reanalysis by Price et al. (1994) 

using inverse fishing frequency as 

sample weights. 

Local survey. Original (unweighted) 

analysis over-estimated fish intake by 

oversampling frequent anglers. Reanalysis by Price et al. (1994) involves 

several assumptions; thus results are 

questionable. 

U.S. DHHS, 1995 330 everglade residents/ 

subsistence fishermen or 

both 

1992-1993; questionnaire with Provides data for fishing frequency 

demographic information and fishing by sex, age, and ethnicity. 

and eating habits. 

Intake rates were not reported, study 

not representative of the U.S. 

population; one of few studies that 

target subsistence fishermen. 
Table 10-86. Summary of Fish Intake Studies (continued) 

Source of Data 

(Reference) Population Surveyed Survey Time Period/Type Analyses Performed (References) Limitations/Advantages 

Recreational Fresh Water Fish 

Key Studies 

Chemrisk, 1991; Ebert 1,612 licensed Maine 1989-1990 ice fishing season and Mean and distribution of fish Data based on one year recall; high 

et al., 1993 anglers 1990 open water season; mailed consumption rates by ethnic groups response rate; area-specific 

survey; one year recall of frequency and overall. Mean and distribution of consumption patterns. 

of fishing trips, number and length fish consumption rates for fish from 

of fish species caught. rivers and streams. EPA analysis of 

fish intake for household members. 

Connelly et al., 1996 825 anglers with NY State Survey consisted of self-recording Distribution of intake rates of sport Meal size estimated by comparison 

fishing licenses intending to information in a diary for 1992 caught fish. with pictures of 8 oz. fish meals. 

fish Lake Ontario. fishing trips and fish consumption. 

West et al., 1993 2,681 persons with January 1991 through January 1992; Mean consumption rate for sport Relatively low response made and 

Michigan fishing licenses mailed survey; 7-day recall; and total fish by demographic only three categories were used to 

demographics information category (West et al., 1993) and assign fish portion size. Relatively 

requested, and quantity of fish 50th, 90th, and 95th percentile (U.S. large-scale study and reliance on 

eaten, if any, at each meal based on EPA, 1995). short-term recall. 

a photograph of 1/2 lb of fish (more 

about same, or less). 

West et al., 1989 1,171 Michigan residents January-May 1988; anglers Mean intake rates of self-caught fish Weight of fish consumed was 

with fishing licenses completed questionnaires based on based on 7-day recall period estimated using a picture of an 8 oz. 

7-day and 1-year recall. and mean and percentiles of self- fish meal; smaller meals were 

caught fish intake based on one year judged to be 5 oz., larger ones 10 

recall. oz. 

Relevant Studies 

Connelly et al., 1992 1,030 anglers licensed in Survey mailed out in Jan. 1992; one Knowledge and effects of fish health Response rate of 52.8%; only 

New York year recall of the period Oct. 1990­ advisories. Mean number of sport- number of fish mealsreported. 

Sept. 1991 caught fish meals. 

Fiore et al., 1989 801 individuals with 1985 summer; mailed survey; one Mean number of sport caught fish Constant meal size assumed. 

Wisconsin fish or sporting year recall of sport fish meals of Wisconsin anglers. 

licenses consumption. 

Hudson River Sloop 336 shore-based anglers Survey conducted June-November Knowledge and adherance to health Data collected from personal 

Clearwater, Inc. 1991; April-July 1992. Onsite advsisories interviews; intake data not provided; 

(1993) interview with anglers fish meal data provided. 
Table 10-86. Summary of Fish Intake Studies (continued) 

Source of Data 

(Reference) Population Surveyed Survey Time Period/Type Analyses Performed (References) Limitations/Advantages 

Native American 

Key Studies 

CRITFC, 1994 Four tribes in Washington 

state; total of 513 adults 

and 204 children under five 

Fall and Winter of 1991-1992; stratified Mean and distribution of fish intake 

random sampling approach; in-person rates for adults and for children. 

interviews; information requested Mean intake rates by age and 

included 24-hour dietary recall, gender. Frequency of cooking and 

seasonal and annual number of fish preparation methods. 

meals, average weight of fish meals 

and species consumed. 

Survey was done at only one time of 

the year and involved one year recall; 

fish intake rates were based on all fish 

sources but great majority was locally 

caught; study provides consumption 

and habits for subsistence 

subpopulation group. 

Fitzgerald et al. 97 Mohawk women in New 

1995 York; 154 Caucasian 

women; nursing mothers 

1988-1992, up to 3-year recall Mean number of sport-caught fish 

meals per year. 

Survey for nursing mothers only, recall 

for up to 3 years; small sample size; 

may be representative of Mohawk 

women; measured in fish meals. 

Petersen et al., 327 residents of Chippewa 

1994 reservation, Wisconsin 

Self-administered questionaire Mean number of fish meals per 

completed in May, 1990. year. 

Did not distinguish between commercial 

and sport-caught meals. 

Wolfe and Walker, Ninety-eight communities 

1987 in Alaska surveyed by 

various researchers 

Surveys conducted between 1980 and Distribution among communities of 

1985; data based on 1-year recall annual per-capita harvests for 

period. Annual per capita harvest of each resource category. 

fish, land mammals, marine mammals 

and other resources estimated for 

each community. 

Data based on 1-year recall; data 

provided are harvest data that must be 

converted to individual intake rates; 

surveyed communities are only a 

sample of all Alaska communities. 

NFMS - National Marine Fisheries Services. a 
Table 10-87. Confidence in Fish Intake Recommendations for General Population 

Considerations Rationale Rating 

Study Elements 

C	 Level of peer review Peer reviewed by USDA and EPA. High 

C	 Accessibility CSFII data are publicly available. Javitz is a High (CSFII) 

contractor report to EPA. Medium (Javitz) 

C	 Reproducibility Enough information is available to reproduce High 

results. 

C	 Focus on factor of interest The studies focused on fish ingestion. High 

C	 Data pertinent to U.S. The studies were conducted for U.S. High 

population. 

C	 Primary data The studies are primary studies. High 

C	 Currency Studies were conducted from 1973-1974 to Medium (mean) 

1989-1991. Low (Long-Term Distribution) 

C	 Adequacy of data collection period Long-term distribution are based on one month High (Mean) 

data collection period. Medium (Long-term distribution) 

C	 Validity of approach Data are collected using diaries and one-day Medium 

recall. However, data adjusted to account for 

changes in eating pattern. 

C	 Study size The Range of samples was 10,000 -37,000. High 

C	 Representativeness of the The data are representative of overall U.S. High 

population population. 

C	 Characterization of variability Long-term distribution (generated from 1973­ Medium 

1974 data) was shifted upward based on recent 

increase in mean consumption. 

C	 Lack of bias in study design (high Response rates were fairly high; there was no High 

rating is desirable) obvious source of bias. 

C	 Measurement error Estimates of intake amounts were imprecise. Medium 

Other Elements 

C	 Number of studies There was 1 study for the mean, the results of Low 

2 studies were utilized for long-term 

distribution. 

C	 Agreement between researchers Medium 

Overall Rating Medium (Mean) 

Low (Long-term distribution) 
Table 10-88. Confidence in Fish Intake Recommendations for Recreational Marine Anglers 

Considerations Rationale Rating 

Study Elements 

C	 Level of peer review Data were reviewed by NMFS and EPA. High 

C	 Accessibility The analysis of the NMFS data is presented in the High 

Handbook and NMFS data can be found in NMFS 

publications. 

C	 Reproducibility Enough information is available to reproduce results. High 

C	 Focus on factor of interest Studies focused on fish catch rather than fish consumption Medium 

per se. 

C	 Data pertinent to U.S. The studies were conducted in the U.S. High 

C	 Primary data Data are from primary studies. High 

C	 Currency The data were based on 1993 studies. High 

C	 Adequacy of data collection period Data were collected once for each angler. The yearly catch Medium 

of anglers were estimated from catch on intercepted trip and 

reported fishing frequency. 

C	 Validity of approach The creel survey provided data on fishing frequency and fish Medium 

weight; telephone survey data provided number of anglers. 

An average value was used for the number of intended fish 

consumers and edible fraction. 

C	 Study size Studies encompassed a population of over 100,000. High 

C	 Representativeness of the Data were representative of overall U.S. coastal state High 

population population. 

C	 Characterization of variability Distributions were generated. High 

C	 Lack of bias in study design (high Response rates were fairly high; There was no obvious High 

rating is desirable) source of bias. 

C	 Measurement error Fish were weighed in the field. High 

Other Elements 

C	 Number of studies There was 1 study. Low 

C	 Agreement between researchers N/A 

Overall Rating Medium 
Table 10-89. Confidence in Recommendations for Fish Consumption - Recreational Freshwater 

Considerations Rationale Rating 

Study Elements 

C	 Level of peer review Studies can be found in peer reviewed journals and has High 

been reviewed by the EPA. 

C	 Accessibility The original study analyses are reported in accessible High 

journals. Subsequent EPA analyses are detailed in 

Handbook. 

C	 Reproducibility Enough information is available to reproduce results. High 

C	 Focus on factor of interest Studies focused on ingestion of fish by the recreational High 

freshwater angler. 

C	 Data pertinent to U.S. The studies were conducted in the U.S. High 

C	 Primary data Data are from primary references. High 

C	 Currency Studies were conducted between 1988-1992. High 

C	 Adequacy of data collection period Data were collected for one year period for 3 studies; and a High 

one week period for one study. 

C	 Validity of approach Data presented are as follows: one year recall of fishing trips Medium 

(2 studies), one week recall of fish consumption (1 study), 

and one year diary survey (1 study). Weight of fish 

consumed was estimated using approximate weight of fish 

catch and edible fraction or approximate weight of fish meal. 

C	 Study size Study population ranged from 800-2600. High 

C	 Representativeness of the Each study was localized to a single state or area. Low 

population 

C	 Characterization of variability Distributions were generated. High 

C	 Lack of bias in study design (high Response rates were fairly high. One year recall of fishing Medium 

rating is desirable) trips may result in overestimate. 

C	 Measurement error Weight of fish portions were estimated in one study, fish Medium 

weight was estimated from reported fish length in another 

study. 

Other Elements 

C	 Number of studies There are 4 key studies. High 

C	 Agreement between researchers Intake rates in different parts of country may be expected to Medium 

show some variation. 

Overall Rating The main drawback is that studies are not nationally Medium 

representative and not representative of long-term 

consumption. 
Table 10-90. Confidence in Recommendations for Native American Subsistence Fish Consumption 

Considerations Rationale Rating 

Study Elements 

C	 Level of peer review Studies are from peer reviewed journal (1 study), and Medium 

technical reports (1study). 

C	 Accessibility Journal articles are publicly available. CRITFC is a Medium 

technical report. 

C	 Reproducibility The studies were adequately detailed. High 

C	 Focus on factor of interest Studies focused on fish ingestion and fish harvest. High 

C	 Data pertinent to U.S. All studies were specific to area in the U.S. High 

C	 Primary data One study used primary data, the other used Medium 

secondary data. 

C	 Currency Data were from early 1980's to 1992. Medium 

C	 Adequacy of data collection period Data collected for one year period. High 

C	 Validity of approach One study used fish harvest data; EPA used a factor Medium 

to convert to individual intake. Other study measured 

individual intake directly. 

C	 Study size The sample population was 500 for the study with Medium 

primary data. 

C	 Representativeness of the Only two states were represented. Low 

population 

C	 Characterization of variability Individual variation were not described in summary Medium 

study. 

C	 Lack of bias in study design (high The response rate was 69% in study with primary Medium 

rating is desirable) data. Bias was hard to evaluate in summary study. 

C	 Measurement error The weight of the fish was estimated. Medium 

Other Elements 

C	 Number of studies There were two studies; only one study described Medium 

individual variation in intake. 

C	 Agreement between researchers Range of per-capita rates from summary study High 

includes per-capita rate from study with primary data. 

Overall Rating Studies are not nationally representative. Upper Medium (per capita intake) 

percentiles are based on only one study. Low (upper percentiles) 
Table 10B-1. Percent of Fish Meals Prepared Using Various Cooking Methods by Residence Sizea 

Residence Size City/Suburb Small City Town Small Town Farm 

Large Rural NonFarm 

Total Fish 

Cooking Method 

Pan Fried 32.7 31.0 36.0 32.4 38.6 51.6 

Deep Fried 19.6 24.0 23.3 24.7 26.2 15.7 

Boiled 6.0 3.0 3.4 3.7 3.4 3.5 

Grilled/Broiled 23.6 20.8 13.8 21.4 13.7 13.1 

Baked 12.4 12.4 10.0 10.3 12.7 6.4 

Combination 2.5 6.0 8.3 5.0 2.3 7.0 

Other (Smoked, etc.) 3.2 2.8 5.2 1.9 2.9 1.8 

Don't Know 0.0000 0.0000 0.0000 0.5 0.2 -­

Total (N) 393 317 388 256 483 b 94 

Sport Fish 

Pan Fried 45.8 45.7 47.6 41.4 51.2 63.3 

Deep Fried 12.2 14.5 17.5 15.2 21.9 7.3 

Boiled 2.8 2.3 2.9 0.5 3.6 0 

Grilled/Broiled 20.2 17.6 10.6 25.3 8.2 10.4 

Baked 11.8 8.8 6.3 8.7 9.7 6.9 

Combination 2.7 8.5 10.4 6.7 1.9 9.3 

Other (smoked, etc.) 4.5 2.7 4.9 1.5 3.5 2.8 

Don't Know 0 0 0 0.7 0 0 

Total (N) 205 171 257 176 314 62 

Large City = over 100,000; Small City = 20,000-100,000; Town = 2,000-20,000; Small Town = 100-2,000. a 

N = Total number of respondents b 

Source: West et al., 1993. 
Table 10B-2. Percent of Fish Meals Prepared Using Various Cooking Methods by Age 

Age (years) 17-30 31-40 41-50 51-64 >64 Overall 

Total Fish 

Cooking Method 

Pan Fried 45.9 31.7 30.5 33.9 40.7 35.3 

Deep Fried 23.0 24.7 26.9 23.7 14.0 23.5 

Boiled 0.0000 6.0 3.6 3.9 4.3 3.9 

Grilled or Boiled 15.6 15.2 24.3 16.1 18.8 17.8 

Baked 10.8 13.0 8.7 12.8 11.5 11.4 

Combination 3.1 5.2 2.2 6.5 6.8 4.7 

Other (Smoked, etc.) 1.6 4.2 3.5 2.7 4.0 3.2 

Don't Know 0.0000 0.0000 0.3 0.4 0.0000 0.2 

Total (N) 246 448 417 502 287 a 1946 

Sport Fish 

Pan Fried 57.6 42.6 43.4 46.6 54.1 47.9 

Deep Fried 18.2 21.0 17.3 14.8 7.7 16.5 

Boiled 0.0000 4.4 0.8 3.2 3.1 2.4 

Grilled/Broiled 15.0 10.1 25.9 12.2 12.2 14.8 

Baked 3.6 10.4 6.4 11.7 9.9 8.9 

Combination 3.8 7.2 3.0 7.5 8.2 5.9 

Other (Smoked, etc.) 1.7 4.3 3.2 3.5 4.8 3.5 

Don't Know 0.0000 0.0000 0.0000 0.4 0.0000 0.1 

Total (N) 174 287 246 294 163 1187

a N = Total number of respondents. 

Source: West et al., 1993. 
Table 10B-3. Percent of Fish Meals Prepared Using Various Cooking Methods by Ethnicity 

Ethnicity Black Native American Hispanic White Other 

Total Fish 

Cooking Method 

Pan Fried 40.5 37.5 16.1 35.8 18.5 

Deep Fried 27.0 22.0 83.9 22.7 18.4 

Boiled 0 1.1 0 4.3 0 

Grilled/Broiled 19.4 9.8 0 17.7 57.6 

Baked 1.9 16.3 0 11.7 5.4 

Combination 9.5 6.2 0 4.5 0 

Other (Smoked, etc.) 1.6 4.2 3.5 2.7 4.0 

Don't Know 0 0 0.3 0.4 0 

Total (N) 52 84 12 1,744 a 33 

Sport Fish 

Pan Fried 44.9 47.9 52.1 48.8 22.0 

Deep Fried 36.2 20.2 47.9 15.7 9.6 

Boiled 0 0 0 2.7 0 

Grilled/Broiled 0 1.5 0 14.7 61.9 

Baked 5.3 18.2 0 8.6 6.4 

Combination 13.6 8.6 0 5.6 0 

Other (Smoked, etc.) 0 3.6 0 3.7 0 

Total (N) 19 60 4 39 0

a N = Total number of respondents. 

Source: West et al., 1993. 
Table 10B-4. Percent of Fish Meals Prepared Using Various Cooking Methods by Education 

Education Through Some H.S. H.S. Degree College Degree Education 

Post Graduate 

Total Fish 

Cooking Method 

Pan Fried 44.7 41.8 28.8 22.9 

Deep Fried 23.6 23.6 23.8 19.4 

Boiled 2.2 2.8 5.1 5.8 

Grilled/Broiled 8.9 10.9 23.8 34.1 

Baked 8.1 12.1 11.6 12.8 

Combination 10.0 5.1 3.0 3.8 

Other (Smoked, etc.) 2.1 3.4 4.0 1.3 

Don't Know 0.5 0.3 0 0 

Total (N) 236 775 704 a 211 

Sport Fish 

Pan Fried 56.1 52.4 41.8 36.3 

Deep Fried 13.6 15.8 18.6 12.9 

Boiled 2.8 2.4 3.0 0 

Grilled/Baked 6.3 9.4 21.7 28.3 

Baked 7.4 10.6 6.1 14.9 

Combination 10.1 6.3 3.9 6.5 

Other (Smoked, etc.) 2.8 3.3 4.6 1.0 

Don't Know 0.8 0 0 0 

Total (N) 146 524 421 91

a N = Total number of respondents. 

Source: West et al., 1993. 
Table 10B-5. Percent of Fish Meals Prepared Using Various Cooking Methods by Income 

Income 0 - $24,999 $25,000 - $39,999 $40,000 - or more 

Total Fish 

Cooking Method 

Pan Fried 44.8 39.1 26.5 

Deep Fried 21.7 22.2 23.4 

Boiled 2.1 3.5 5.6 

Grilled/Broiled 11.3 15.8 25.0 

Baked 9.1 12.3 13.3 

Combination 8.7 2.9 2.5 

Other (Smoked, etc.) 2.4 4.0 3.5 

Don't Know 0 0.2 0.3 

Total (N) 544 518 714 a 

Sport Fish 

Pan Fried 51.5 51.4 42.0 

Deep Fried 15.8 15.8 17.2 

Boiled 1.8 2.1 3.7 

Grilled/Broiled 12.0 12.2 19.4 

Baked 7.2 10.0 10.0 

Combination 9.1 3.8 3.5 

Other (Smoked, etc.) 2.7 4.6 3.8 

Don't Know 0 0 0.3 

Total (N) 387 344 369

a N = Total number of respondents. 

Source: West et al., 1993. 
Table 10B-6. Percent of Fish Meals Where Fat was Trimmed or Skin was Removed, by Demographic Variables 

Total Fish Sport Fish 

Population Trimmed Fat (%) Skin Off (%) Trimmed Fat (%) Skin Off (%) 

Residence Size 

Large City/Suburb 51.7 31.6 56.7 28.9 

Small City 56.9 34.1 59.3 36.2 

Town 50.3 33.4 51.7 33.7 

Small Town 52.6 45.2 55.8 51.3 

Rural Non-Farm 42.4 32.4 46.2 34.6 

Farm 37.3 38.1 39.4 42.1 

Age (years) 

17-30 50.6 36.5 53.9 39.3 

31-40 49.7 29.7 51.6 29.9 

41-50 53.0 32.2 58.8 37.0 

51-65 48.1 35.6 48.8 37.2 

Over 65 41.6 43.1 43.0 42.9 

Ethnicity 

Black 25.8 37.1 16.0 40.1 

Native American 50.0 41.4 56.3 36.7 

Hispanic 59.5 7.1 50.0 23.0 

White 49.3 34.0 51.8 35.6 

Other 77.1 61.6 75.7 65.5 

Education 

Some High School 50.8 43.9 49.7 47.1 

High School Degree 47.2 37.1 49.5 37.6 

College Degree 51.9 31.9 55.9 33.8 

Post-Graduate 47.6 26.6 53.4 38.7 

Income 

<$25,000 50.5 43.8 50.6 47.3 

$25-39,999 47.8 34.0 54.9 34.6 

$40,000 or more 50.2 28.6 51.7 27.7 

Overall 49.0 34.7 52.1 36.5 

Source: Modified from West et. al., 1993. 
Table 10B-7. Method of Cooking of Most Common Species Kept by Sportfishermen 

Species Percent of Anglers Use as Primary Cooking Method (Percent) 

Catching Species 

Deep Fry Pan Fry Bake and Charcoal Raw Otherb 

Broil 

White Croaker 34% 19% 

Pacific Mackerel 25% 10% 

Pacific Bonito 18% 5% 

Queenfish 17% 15% 

Jacksmelt 13% 17% 

Walleye Perch 10% 12% 

Shiner Perch 7% 11% 

Opaleye 6% 16% 

Black Perch 5% 18% 

Kelp Bass 5% 12% 

California Halibut 4% 13% 

64% 12% 0% 5% 

41% 28% 0% 21% 

33% 43% 2% 17% 

70% 6% 1% 8% 

57% 19% 0% 7% 

69% 6% 0% 13% 

72% 8% 0% 11% 

56% 14% 0% 14% 

53% 14% 0% 15% 

55% 21% 0% 12% 

60% 24% 0% 3% a Shellfish 3% 0% 0% 0% 0% 100% 

(n = 1059)

a

 Crab, mussels, lobster, abalone 

b Boil, soup, steam, stew 

Source: Modified from Puffer et al., 1981. 
Table 10B-8. Adult Consumption of Fish Parts 

Weighted Percent Consuming Specific Parts 

Number 

Species Consuming Fillet Skin Head Eggs Bones Organs 

Salmon 473 95.1% 55.8% 42.7% 42.8% 12.1% 3.7% 

Lamprey 249 86.4% 89.3% 18.1% 4.6% 5.2% 3.2% 

Trout 365 89.4% 68.5% 13.7% 8.7% 7.1% 2.3% 

Smelt 209 78.8% 88.9% 37.4% 46.4% 28.4% 27.9% 

Whitefish 125 93.8% 53.8% 15.4% 20.6% 6.0% 0.0% 

Sturgeon 121 94.6% 18.2% 6.2% 11.9% 2.6% 0.3% 

Walleye 46 100% 20.7% 6.2% 9.8% 2.4% 0.9% 

Squawfish 15 89.7% 34.1% 8.1% 11.1% 5.9% 0.0% 

Sucker 42 89.3% 50.0% 19.4% 30.4% 9.8% 2.1% 

Shad 16 93.5% 15.7% 0.0% 0.0% 3.3% 0.0% 

Source: CRITFC, 1994. 
Table 10C-1. Daily Average Per Capita Estimates of Fish Consumption 

U.S. Population - Mean Consumption by Species Within Habitat - As Consumed Fish 

Habitat Species Grams/Person/Day 

Estimated Mean 

Habitat Species Grams/Person/Day 

Estimated Mean 

Habitat Species Grams/Person/Da

Estimated Mean 

Estuarine Shrimp 1.37241 

Freshwater Catfish 1.06776 

Marine Tuna 4.19998 

Perch 0.52580 

Flatfish (Estuarine) 0.43485 

Crab (Estuarine) 0.29086 

Flounder 0.24590 

Oyster 0.17840 

Clam (Estuarine) 0.14605 

Mullet 0.07089 

Croaker 0.05021 

Herring 0.02937 

Smelts 0.02768 

Scallop (Estuarine) 0.00247 

Anchovy 0.00228 

Scup 0.00050 

Sturgeon 0.00040 

Trout 0.43050 

Carp 0.04846 

Pike 0.01978 

Salmon (Freshwater) 0.00881 

Clam (Marine) 1.66153 

Cod 1.22627 

Flatfish (Marine) 1.06307 

Salmon (Marine) 0.73778 

Haddock 0.51533 

Pollock 0.44970 

Crab (Marine) 0.33870 

Ocean Perch 0.31878 

Porgy 0.29844 

Scallop (Marine) 0.21805 

Sea Bass 0.20794 

Lobster 0.20001 

Marine Swordfish 0.13879 

Cod 1.22827 

(Cont) Squid 0.12196 

Sardine 0.10013 

Pompano 0.09131 

Sole 0.07396 

Mackerel 0.06379 

Whiting 0.05498 

Halibut 0.02463 

Mussels 0.02217 

Shark 0.01901 

Whitefish 0.00916 

Seafood 0.00574 

Snapper 0.00539 

Octopus 0.00375 

Barracuda 0.00111 

Unknown Fish 0.00186 

All Tuna 4.19998 

Species Clam (Marine) 1.66153 

Catfish 1.06776 

Faltfish (Marine) 1.06307 

Salmon (Marine) 0.73778 

Perch 0.52580 

Haddock 0.51533 

Pollock 0.44970 

Flatfish (Estuarine) 0.43485 

Trout 0.43050 

Crab (Marine) 0.33870 

Ocean Perch 0.31878 

Porgy 0.29844 

Crab (Estuarine) 0.29088 

Abalone 0.00075 

Shrimp 1.38883 

All Species Flounder 0.24590 

Herring 0.02937 

Whitefish 0.00916 

(Cont) Scallop (Marine) 0.21805 

Sea Bass 0.20794 

Lobster 0.20001 

Oyster 0.17840 

Clam (Estuarine) 0.14605 

Swordfish 0.13879 

Squid 0.12196 

Sardine 0.10313 

Pompano 0.09131 

Sole 0.07396 

Mullet 0.07089 

Mackarel 0.06379 

Whiting 0.05498 

Croaker 0.05021 

Smelts 0.02768 

Halibut 0.02463 

Mussels 0.02217 

Pike 0.01978 

Salmon (Freshwater) 0.00881 

Seafood 0.00574 

Snapper 0.00539 

Octopus 0.00375 

Scallop (Estuarine) 0.00247 

Anchovy 0.00228 

Fish 0.00166 

Barracuda 0.00111 

Abalone 0.00075 

Scup 0.00050 

Sturgeon 0.00040 

Carp 0.04846 

Shark 0.01901 

Notes: Estimates are projected from a sample of 11,912 individuals to the U.S. population of 242,707,000 using 3-year combined survey weights. The population for this survey consisted 

individuals in the 48 conteminous states. 

Source of individual consumption data: USDA Combined 1989, 1990, and 1991 Continuing Survey of Food Intakes by Individuals (CSFII). 

The fish component of foods containing fish was calculated using data from the recipe file for release 7 of the USDA’s Nutrient Data Base for Individual Food Intake Surveys. 
Table 10C-2. Daily Average Per Capita Estimates of Fish Consumption 

U.S. Population - Mean Consumption by Species Within Habitat - Uncooked Fish 

Habitat Species Grams/Person/Day 

Estimated Mean 

Habitat Species Grams/Person/Day 

Estimated Mean 

Habitat Species Grams/Person/Day 

Estimated Mean 

Estuarine Shrimp 1.78619 

Freshwater Catfish 1.38715 

Marine Tuna 5.67438 

Perch 0.66494 

Flatfish (Estuarine) 0.50832 

Crab (Estuarine) 0.40848 

Flounder 0.28559 

Oyster 0.18827 

Mullet 0.08959 

Croaker 0.06539 

Smelts 0.03470 

Herring 0.03408 

Clam (Estuarine) 0.03339 

Anchovy 0.00304 

Scallop (Estuarine) 0.00297 

Scup 0.00050 

Sturgeon 0.00040 

Trout 0.53777 

Carp 0.06012 

Pike 0.02244 

Salmon (Freshwater) 0.01183 

Cod 1.47609 

Flatfish (Marine) 1.24268 

Salmon (Marine) 0.99093 

Haddock 0.62219 

Pollock 0.52906 

Crab (Marine) 0.47567 

Porgy 0.42587 

Ocean Perch 0.39327 

Clam (Marine) 0.37982 

Lobster 0.27583 

Sea Bass 0.26661 

Scallop (Marine) 0.26199 

Marine Swordfish 0.17903 

Catfish 1.38715 

(Cont) Squid 0.14420 

Sardine 0.13750 

Pompano 0.12160 

Mackerel 0.09866 

Sole 0.08339 

Whiting 0.06514 

Mussels 0.03718 

Halibut 0.03030 

Shark 0.02385 

Whitefish 0.00916 

Snapper 0.00551 

Octopus 0.00457 

Barracuda 0.00130 

Abalone 0.00094 

Unknown Fish 0.00248 

All Tuna 5.67438 

Species Shrimp 1.78619 

Flatfish (Marine) 1.24268 

Salmon (Marine) 0.99093 

Perch 0.66494 

Haddock 0.62219 

Trout 0.53777 

Pollock 0.52906 

Flatfish (Estuarine) 0.50832 

Crab (Marine) 0.47567 

Porgy 0.42587 

Crab (Estuarine) 0.40848 

Ocean Perch 0.39327 

Clam (Marine) 0.37982 

Seafood 0.00043 

Cod 1.47609 

All Species Flounder 0.28559 

Smelts 0.03470 

Salmon (Freshwater) 0.01183 

(Cont) Lobster 0.27563 

Sea Bass 0.26661 

Scallop (Marine) 0.26199 

Oyster 0.18827 

Swordfish 0.17903 

Squid 0.14420 

Sardine 0.13750 

Pompano 0.12160 

Mackarel 0.09866 

Mullet 0.08958 

Sole 0.08339 

Croaker 0.06539 

Whiting 0.06514 

Carp 0.06012 

Herring 0.03406 

Clam (Estuarine) 0.03339 

Halibut 0.03030 

Shark 0.02385 

Whitefish 0.00916 

Snapper 0.00551 

Octopus 0.00457 

Anchovy 0.00304 

Scallop (Estuarine) 0.00297 

Fish 0.00248 

Barracuda 0.00130 

Abalone 0.00094 

Scup 0.00050 

Seafood 0.00043 

Sturgeon 0.00040 

Mussels 0.03718 

Pike 0.02244 

Notes: Estimates are projected from a sample of 11,912 individuals to the U.S. population of 242,707,000 using 3-year combined survey weights. The population for this survey consisted 

of individuals in the 48 conteminous states. 

Source of individual consumption data: USDA Combined 1989, 1990, and 1991 Continuing Survey of Food Intakes by Individuals (CSFII). 

Amount of consumed fish recorded by survey respondents was converted to uncooked fish quantities using data from the recipe file for release 7 of USDA’s Nutrient Data Base for 

Individual Food Intake Surveys. The fish component of foods containing fish was calculated using data from the recipe file for release 7 of the USDA’s Nutrient Data Base for Individual 

Food Intake Surveys. 
Table 10C-3. Daily Average Per Capita Estimates Of Fish Consumption 

As Consumed Fish - Mean Consumption by Species Within Habitat 

U.S. Population 

Estimated Estimated Estimated 

Habitat Species Mean Habitat Species Mean Habitat Species Mean 

Grams/person/day Grams/person/day Grams/person/day 

Estuarine Shrimp 1.37241 Marine (Con't.) Swordfish 0.13879 All Species Flounder 

Perch 0.52580 Squid 0.12196 (Con't.) Scallop (Marine) 

Flatfish 0.43485 Sardine 0.10313 Sea Bass 

0.24590 

0.21805 

0.20794 

Crab 0.29086 Pompano 0.09131 Lobster 

Flounder 0.24590 Sole 0.07396 Oyster 

Oyster 0.17419 Mackerel 0.06379 Swordfish 

Mullet 0.07089 Whiting 0.05498 Squid 

Croaker 0.05021 Halibut 0.02463 Sardine 

0.20001 

0.17419 

0.13879 

0.12196 

0.10313 

Herring 0.02937 Mussels 0.02217 Pompano 

Smelts 0.02768 Shark 0.01901 Sole 

0.09131 

0.07396 

Clam 0.02691 Whitefish 0.00916 Mullet 0.07089 

Freshwater Catfish 1.06776 Smelts 

Scallop 0.00247 Snapper 0.00539 Mackerel 

Anchovy 0.00228 Octopus 0.00375 Whiting 

Scup 0.00050 Barracuda 0.00111 Croaker 

Sturgeon 0.00040 Abalone 0.00075 Carp 

Seafood 0.00043 Herring 

0.02768 

0.06379 

0.05498 

0.05021 

0.04846 

0.02937 

Trout 0.43050 Unknown Fish 0.00186 Clam (Estuarine) 

Carp 0.04846 Halibut 

Pike 0.01978 All Species Tuna 4.19998 Mussels 

Salmon 0.00881 Shrimp 1.37241 Pike 

Cod 1.22827 Shark 

0.02691 

0.02463 

0.02217 

0.01978 

0.01901 

Marine Tuna 4.19998 Catfish 1.06776 Whitefish 0.00916 

Cod 1.22827 Flatfish (Marine) 1.06307 Salmon (Freshwater) 

Flatfish 1.06307 Salmon (Marine) 0.73778 Snapper 

Salmon 0.73778 Perch 0.52580 Octopus 

Haddock 0.51533 Haddock 0.51533 Scallop (Estuarine) 

Pollock 0.44970 Pollock 0.44970 Anchovy 

Crab 0.33870 Flatfish (Estuarine) 0.43485 Fish 

Ocean Perch 0.31878 Trout 0.43050 Barracuda 

0.00881 

0.00539 

0.00375 

0.00247 

0.00228 

0.00186 

0.00111 

Clam 0.30617 Crab (Marine) 0.33870 Abalone 

Porgy 0.29844 Ocean Perch 0.31878 Scup 

Scallop 0.21805 Clam (Marine) 0.30617 Seafood 

Sea Bass 0.20794 Porgy 0.29844 Sturgeon 

Lobster 0.20001 Crab (Estuarine) 0.29086 

0.00075 

0.00050 

0.00043 

0.00040 

Estimates are projected from a sample of 11,912 individuals to the U.S. population of 242,707,000 using 3-year combined survey weights. 

Source: U.S. EPA, 1996a. 
Table 10C-4. Daily Average Per Capita Estimates Of Fish Consumption 

Uncooked Fish** - Mean Consumption by Species Within Habitat 

U.S. Population 

Estimated Estimated Estimated 

Habitat Species Mean Habitat Species Mean Habitat Species Mean 

Grams/person/day Grams/person/day Grams/person/day 

Estuarine Shrimp 1.78619 Marine (Con't.) Swordfish 0.17903 All Species Flounder 

Perch 0.66494 Squid 0.14420 (Con't.) Lobster 

Flatfish 0.50832 Sardine 0.13750 Sea Bass 

0.28559 

0.27563 

0.26661 

Crab 0.40848 Pompano 0.12160 Scallop (Marine) 

Flounder 0.28559 Mackerel 0.09866 Oyster 

Oyster 0.18827 Sole 0.08339 Swordfish 

Mullet 0.08958 Whiting 0.06514 Squid 

Croaker 0.06539 Mussels 0.03718 Sardine 

0.26199 

0.18827 

0.17903 

0.14420 

0.13750 

Smelts 0.03470 Halibut 0.03030 Pompano 

Herring 0.03408 Shark 0.02385 Mackerel 

Clam 0.03339 Whitefish 0.00916 Mullet 

0.12160 

0.09866 

0.08958 

Anchovy 0.00304 Snapper 0.00551 Sole 

Scallop 0.00297 Octopus 0.00457 Croaker 

Scup 0.00050 Barracuda 0.00130 Whiting 

Sturgeon 0.00040 Abalone 0.00094 Carp 

Seafood 0.00043 Mussels 

0.08339 

0.06539 

0.06514 

0.06012 

0.03718 

Freshwater Catfish 1.38715 Smelts 0.03470 

Trout 0.53777 Unknown Fish 0.00248 Herring 

Carp 0.06012 Clam (Estuarine) 

Pike 0.02244 All Species Tuna 5.67438 Halibut 

Salmon 0.01183 Shrimp 1.78619 Shark 

Cod 1.47609 Pike 

0.03408 

0.03339 

0.03030 

0.02385 

0.02244 

Marine Tuna 5.67438 Catfish 1.38715 Salmon (Freshwater) 

Cod 1.47609 Flatfish (Marine) 1.24268 Whitefish 

Flatfish 1.24268 Salmon (Marine) 0.99093 Snapper 

Salmon 0.99093 Perch 0.66494 Octopus 

Haddock 0.62219 Haddock 0.62219 Anchovy 

Pollock 0.52906 Trout 0.53777 Scallop (Estuarine) 

Crab 0.47567 Pollock 0.52906 Fish 

0.01183 

0.00916 

0.00551 

0.00457 

0.00304 

0.00297 

0.00248 

Porgy 0.42587 Flatfish (Estuarine) 0.50832 Barracuda 

Ocean Perch 0.39327 Crab (Marine) 0.47567 Abalone 

Clam 0.37982 Porgy 0.42587 Scup 

Lobster 0.27563 Crab (Estuarine) 0.40848 Seafood 

Sea Bass 0.26661 Ocean Perch 0.39327 Sturgeon 

Scallop 0.26199 Clam (Marine) 0.37982 

0.00130 

0.00094 

0.00050 

0.00043 

0.00040 

Estimates are projected from a sample of 11,912 individuals to the U.S. population of 242,707,000 using 3-year combined survey weights. 

Source: U.S. EPA, 1996a. 
Figure 10-1. Seasonal Fish Consumption: Wisconsin Chippewa, 1990 

Figure 10-2. Peak Fish Consumption: Wisconsin Chippewa, 1990 

Source: Peterson et al., 1994. 
Table 11-1. Per Capita Intake of Total Meats (g/kg-day as consumed) 

Population Percent 

Group Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 96.4% 2.146 0.014 0 0.33 0.63 1.13 1.84 2.78 4.06 5.06 7.67 25.67 

Age (years) 

< 01 66.7% 2.867 0.187 0 0 0 0 2.34 4.72 6.52 8.56 11.52 25.67 

01-02 95.6% 4.384 0.116 0 1.07 1.58 2.70 4.13 5.38 7.69 8.41 11.88 21.61 

03-05 97.5% 3.873 0.092 0 1.12 1.38 2.21 3.50 5.04 6.64 8.23 11.25 15.00 

06-11 97.6% 3.011 0.052 0 0.66 1.02 1.80 2.78 3.98 5.12 6.08 8.38 11.68 

12-19 97.7% 2.078 0.034 0 0.42 0.67 1.19 1.99 2.79 3.49 4.40 5.95 8.28 

20-39 97.9% 1.923 0.019 0 0.39 0.64 1.09 1.73 2.54 3.49 4.14 5.46 8.37 

40-69 97.3% 1.700 0.017 0 0.36 0.59 1.03 1.58 2.20 2.95 3.47 4.73 7.64 

70 + 97.1% 1.531 0.028 0 0.32 0.49 0.89 1.42 2.03 2.73 3.20 4.28 6.63 

Season 

Fall 97.1% 2.182 0.029 0 0.37 0.66 1.15 1.85 2.80 4.11 5.16 8.06 25.67 

Spring 95.8% 2.053 0.027 0 0.26 0.61 1.09 1.75 2.63 3.93 4.91 7.31 15.00 

Summer 96.3% 2.178 0.031 0 0.35 0.63 1.11 1.86 2.84 4.10 5.18 7.86 18.19 

Winter 96.4% 2.173 0.029 0 0.30 0.63 1.18 1.88 2.87 4.06 5.05 7.35 14.61 

Urbanization 

Central City 96.7% 2.163 0.028 0 0.25 0.59 1.09 1.79 2.82 4.14 5.22 7.97 25.67 

Nonmetropolitan 95.7% 2.168 0.028 0 0.30 0.63 1.15 1.90 2.79 4.04 5.12 7.69 14.61 

Suburban 96.6% 2.126 0.021 0 0.39 0.64 1.13 1.84 2.74 4.03 4.94 7.31 15.00 

Race 

Asian 89.3% 2.233 0.131 0 0 0.60 1.10 1.86 3.23 4.49 4.66 6.86 8.13 

Black 95.5% 2.434 0.053 0 0.33 0.62 1.15 1.94 3.02 5.03 6.14 9.87 25.67 

Native American 86.5% 2.269 0.131 0 0 0.41 1.32 1.87 3.38 4.64 5.09 7.32 8.57 

Other/NA 95.1% 2.628 0.109 0 0 0.65 1.40 2.29 3.34 4.90 6.03 11.25 11.25 

White 96.9% 2.083 0.015 0 0.34 0.63 1.12 1.81 2.72 3.87 4.87 7.18 18.19 

Region 

Midwest 96.5% 2.204 0.029 0 0.44 0.69 1.21 1.85 2.82 4.08 5.05 7.86 21.61 

Northeast 96.5% 2.148 0.033 0 0.35 0.67 1.16 1.89 2.75 3.98 4.99 8.27 15.00 

South 96.7% 2.249 0.025 0 0.37 0.68 1.18 1.90 2.88 4.35 5.34 7.73 13.42 

West 95.8% 1.903 0.030 0 0.08 0.47 0.92 1.60 2.54 3.69 4.57 6.64 25.67 

NOTE: SE = Standard error

Source: Based on EPA's analyses of the 1989-91 CSFII 

 P = Percentile of the distribution 
Table 11-2. Per Capita Intake of Total Dairy Products (g/kg-day as consumed) 

Population Percent 

Group Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 97.1% 8.015 0.147 0 0.15 0.40 1.36 3.61 8.18 18.55 29.72 72.16 390.53 

< 01 89.6% 62.735 2.800 0 0 0.61 24.68 45.78 91.12 136.69 170.86 210.72 390.53 

01-02 95.6% 26.262 0.743 0 2.69 8.19 15.22 23.48 36.13 45.72 55.07 69.42 108.95 

03-05 97.5% 21.149 0.517 0 3.27 6.75 11.89 19.52 28.31 39.54 44.16 57.58 62.88 

06-11 97.4% 13.334 0.264 0 1.81 3.54 6.72 11.88 18.58 25.38 28.76 39.60 62.55 

12-19 97.9% 6.293 0.147 0 0.27 0.61 2.31 5.29 9.20 12.75 15.12 23.58 53.47 

20-39 97.9% 3.618 0.062 0 0.12 0.30 0.95 2.64 5.04 8.15 10.64 17.23 43.31 

40-69 96.9% 3.098 0.053 0 0.10 0.26 0.94 2.23 4.36 6.99 9.05 12.99 34.42 

70 + 97.6% 3.715 0.104 0 0.16 0.47 1.46 3.03 4.93 8.03 9.63 16.49 26.33 

Season 

Fall 97.7% 8.262 0.286 0 0.17 0.38 1.32 3.53 8.31 20.16 32.71 75.83 351.48 

Spring 96.8% 8.273 0.335 0 0.13 0.39 1.37 3.50 7.88 18.02 27.02 116.00 390.53 

Summer 96.8% 7.561 0.257 0 0.14 0.37 1.37 3.51 7.93 18.01 30.86 64.95 347.93 

Winter 97.1% 7.964 0.293 0 0.16 0.43 1.39 3.90 8.77 17.60 27.34 63.27 307.54 

Urbanization 

Central City 97.2% 8.528 0.309 0 0.17 0.41 1.44 3.78 8.05 18.25 29.51 106.93 318.93 

96.6% 7.224 0.261 0 0.10 0.28 1.08 3.34 7.82 17.28 24.70 59.17 390.53 

Suburban 97.4% 8.058 0.209 0 0.17 0.43 1.42 3.61 8.45 19.50 32.04 69.42 351.48 

Race 

Asian 94.0% 8.730 1.264 0 0 0.14 0.63 3.86 7.23 21.62 36.16 72.01 124.26 

Black 94.8% 7.816 0.498 0 0.03 0.11 0.64 2.49 7.29 17.28 27.78 116.00 347.93 

Native American 88.9% 6.987 1.057 0 0.02 0.14 0.81 2.83 8.06 20.20 24.17 66.71 139.37 

Other/NA 97.1% 10.727 1.002 0 0.12 0.33 1.03 4.15 11.28 34.64 40.33 121.50 166.48 

White 97.7% 7.943 0.156 0 0.22 0.49 1.50 3.76 8.24 18.16 28.76 66.11 390.53 

Region 

Midwest 97.3% 9.291 0.341 0 0.20 0.50 1.66 4.20 9.61 21.33 34.35 90.88 390.53 

Northeast 97.2% 7.890 0.330 0 0.18 0.42 1.42 3.41 7.54 18.07 32.04 78.15 307.54 

South 97.3% 6.926 0.225 0 0.11 0.27 1.01 3.10 7.49 15.86 25.76 54.94 347.93 

West 96.7% 8.454 0.313 0 0.17 0.49 1.60 3.93 8.67 19.88 29.89 84.46 174.65 

NOTE: SE = Standard error

Source: Based on EPA's analyses of the 1989-91 CSFII 

Age (years) 

Nonmetropolitan 

 P = Percentile of the distribution 
Population Percent 

Group Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 91% 0.825 0.007 0 0 0.055 0.268 0.626 1.163 1.804 2.327 3.478 7.959 

Age (years) 

< 01 64% 0.941 0.075 0 0 0 0 0.488 1.417 2.536 3.205 5.776 7.959 

01-02 93% 1.46 0.056 0 0 0.187 0.531 1.339 2.166 2.783 3.65 4.741 7.571 

03-05 95% 1.392 0.05 0 0 0.14 0.506 1.162 1.905 3.163 3.573 5.908 6.769 

06-11 95% 1.095 0.028 0 0.028 0.102 0.337 0.924 1.56 2.376 2.92 3.944 6.024 

12-19 95% 0.83 0.02 0 0.032 0.114 0.3 0.654 1.204 1.775 2.192 3.108 4.508 

20-39 94% 0.789 0.012 0 0 0.087 0.297 0.644 1.109 1.662 2.165 3.059 6.086 

40-69 90% 0.667 0.011 0 0 0.031 0.221 0.536 0.977 1.458 1.76 2.474 4.968 

70 + 87% 0.568 0.018 0 0 0 0.151 0.427 0.817 1.324 1.651 2.62 4.02 

Season 

Fall 92% 0.834 0.014 0 0 0.063 0.296 0.665 1.167 1.785 2.277 3.339 6.086 

Spring 91% 0.797 0.014 0 0 0.046 0.254 0.595 1.132 1.788 2.295 3.531 7.959 

Summer 90% 0.845 0.017 0 0 0.045 0.254 0.605 1.187 1.887 2.519 3.707 7.085 

Winter 92% 0.823 0.015 0 0 0.066 0.272 0.636 1.157 1.767 2.271 3.266 7.571 

Urbanization 

Central City 91% 0.808 0.013 0 0 0.037 0.271 0.611 1.13 1.777 2.329 3.325 6.182 

Nonmetropolitan 91% 0.841 0.015 0 0 0.064 0.269 0.637 1.196 1.852 2.308 3.531 6.66 

Suburban 92% 0.828 0.011 0 0 0.059 0.265 0.63 1.163 1.797 2.337 3.511 7.959 

Race 

Asian 89% 0.895 0.072 0 0 0.08 0.228 0.694 1.251 2.065 2.444 3.135 5.862 

Black 87% 0.665 0.019 0 0 0 0.151 0.42 0.963 1.488 2.177 3.126 6.769 

Native American 82% 0.995 0.088 0 0 0.016 0.182 0.73 1.299 2.338 2.825 4.958 6.66 

Other/NA 90% 1.159 0.069 0 0 0 0.389 0.739 1.63 2.756 3.269 5.908 6.182 

White 93% 0.833 0.008 0 0 0.068 0.284 0.651 1.18 1.784 2.28 3.41 7.959 

Region 

Midwest 92% 0.853 0.015 0 0 0.07 0.31 0.66 1.191 1.853 2.345 3.65 6.468 

Northeast 93% 0.805 0.017 0 0 0.054 0.253 0.595 1.136 1.816 2.352 3.41 6.769 

South 90% 0.846 0.013 0 0 0.058 0.268 0.648 1.195 1.805 2.324 3.511 7.959 

West 92% 0.775 0.016 0 0 0.039 0.235 0.562 1.105 1.73 2.226 3.219 6.66 

NOTE: SE = Standard error 

Source: Based on EPA’s analyses of the 1989-91 CSFII 

Table 11-3. Per Capita Intake of Beef (g/kg-day as consumed) 

P = Percentile of the distribution 
Population Percent 

Group Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 90.2% 0.261 0.005 0 0 0.005 0.031 0.083 0.263 0.735 1.137 2.384 8.231 

Age (years) 

< 01 63.0% 0.291 0.04 0 0 0 0 0.078 0.228 0.69 1.671 3.269 5.431 

01-02 92.4% 0.492 0.041 0 0 0.033 0.071 0.182 0.424 1.525 2.633 3.633 6.94 

03-05 95.0% 0.473 0.035 0 0 0.021 0.057 0.147 0.362 1.372 2.35 3.309 8.231 

06-11 94.5% 0.352 0.018 0 0 0.015 0.052 0.116 0.311 1.098 1.418 2.869 5.024 

12-19 94.0% 0.27 0.013 0 0 0.012 0.039 0.09 0.289 0.742 1.118 2.699 5.157 

20-39 92.5% 0.23 0.007 0 0 0.009 0.031 0.08 0.233 0.704 1.039 1.747 6.363 

40-69 88.3% 0.212 0.007 0 0 0 0.025 0.068 0.242 0.613 0.915 1.865 4.342 

70 + 86.5% 0.207 0.011 0 0 0 0.016 0.061 0.223 0.667 0.924 1.74 3.035 

Season 

Fall 91.9% 0.254 0.008 0 0 0.01 0.037 0.098 0.267 0.723 1.045 2.118 5.338 

Spring 88.8% 0.264 0.009 0 0 0 0.027 0.076 0.265 0.728 1.19 2.762 6.94 

Summer 89.4% 0.245 0.01 0 0 0 0.027 0.072 0.22 0.688 1.097 2.43 8.231 

Winter 90.6% 0.279 0.009 0 0 0.006 0.032 0.084 0.3 0.819 1.195 2.608 5.946 

Urbanization 

Central City 89.5% 0.258 0.009 0 0 0.001 0.027 0.076 0.235 0.736 1.085 2.699 6.94 

Nonmetropolitan 90.3% 0.299 0.01 0 0 0.007 0.038 0.099 0.324 0.863 1.212 2.808 8.231 

Suburban 90.6% 0.244 0.006 0 0 0.006 0.03 0.078 0.253 0.678 1.098 2.269 5.946 

Race 

Asian 85.9% 0.256 0.049 0 0 0.003 0.027 0.057 0.192 0.72 1.157 2.487 3.966 

Black 89.2% 0.418 0.019 0 0 0.002 0.035 0.123 0.48 1.19 2.108 3.178 8.231 

Native American 83.6% 0.188 0.024 0 0 0 0.027 0.08 0.179 0.473 0.889 1.317 1.662 

Other/NA 88.3% 0.191 0.021 0 0 0 0.027 0.075 0.183 0.48 0.845 1.638 5.252 

White 90.6% 0.241 0.005 0 0 0.006 0.031 0.081 0.249 0.685 1.061 2.035 5.946 

Region 

Midwest 91.3% 0.284 0.009 0 0 0.006 0.034 0.095 0.318 0.776 1.113 2.487 6.362 

Northeast 90.4% 0.236 0.01 0 0 0.005 0.027 0.071 0.227 0.699 1.064 2.11 5.338 

South 89.5% 0.283 0.008 0 0 0.005 0.032 0.09 0.281 0.802 1.212 2.769 8.231 

West 89.7% 0.22 0.009 0 0 0 0.028 0.072 0.198 0.59 1.009 1.944 5.946 

NOTE: SE = Standard error 

Source: Based on EPA’s analyses of the 1989-91 CSFII 

Table 11-4. Per Capita Intake of Pork (g/kg-day as consumed) 

P = Percentile of the distribution 
Population Percent 

Group Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 91.7% 0.598 0.007 0 0 0.015 0.097 0.344 0.83 1.506 2.035 3.273 12.239 

Age (years) 

< 01 64.9% 0.816 0.087 0 0 0 0 0.178 1.07 2.467 3.453 7.373 12.239 

01-02 94.2% 1.156 0.064 0 0.017 0.08 0.211 0.636 1.695 2.931 4.144 5.429 11.747 

03-05 95.0% 1.068 0.049 0 0 0.044 0.18 0.607 1.647 2.662 3.603 5.024 7.565 

06-11 95.7% 0.871 0.028 0 0.022 0.047 0.166 0.556 1.364 2.182 2.851 3.861 6.936 

12-19 94.3% 0.558 0.017 0 0 0.02 0.088 0.378 0.813 1.476 1.806 2.394 3.535 

20-39 94.6% 0.53 0.01 0 0.005 0.021 0.098 0.332 0.768 1.35 1.744 2.666 3.801 

40-69 90.5% 0.477 0.01 0 0 0.011 0.084 0.294 0.696 1.192 1.528 2.358 6.219 

70 + 86.7% 0.463 0.017 0 0 0 0.072 0.286 0.692 1.189 1.539 2.284 4.092 

Season 

Fall 92.9% 0.635 0.015 0 0 0.022 0.112 0.366 0.867 1.571 2.209 3.543 12.239 

Spring 91.0% 0.538 0.013 0 0 0.009 0.071 0.305 0.74 1.368 1.829 3.052 11.543 

Summer 90.4% 0.625 0.015 0 0 0.013 0.089 0.359 0.905 1.562 2.171 3.863 6.596 

Winter 92.6% 0.595 0.014 0 0 0.025 0.113 0.372 0.82 1.443 1.94 3.091 8.418 

Urbanization 

Central City 91.7% 0.627 0.014 0 0 0.011 0.095 0.333 0.877 1.589 2.218 3.518 12.239 

Nonmetropolitan 90.6% 0.54 0.013 0 0 0.014 0.093 0.314 0.781 1.321 1.71 3.077 11.543 

Suburban 92.4% 0.608 0.011 0 0 0.02 0.1 0.37 0.842 1.542 2.06 3.111 8.306 

Race 

Asian 88.6% 0.79 0.068 0 0 0.035 0.112 0.503 1.15 1.901 2.368 2.939 4.745 

Black 91.9% 0.798 0.025 0 0 0.02 0.143 0.521 1.133 1.867 2.352 4.288 12.239 

Native American 80.7% 0.54 0.051 0 0 0 0.071 0.324 0.985 1.343 1.545 2.348 4.158 

Other/NA 91.7% 0.81 0.049 0 0 0.005 0.169 0.467 1.252 2.11 2.695 3.863 4.002 

White 92.0% 0.559 0.007 0 0 0.016 0.092 0.318 0.771 1.419 1.906 3.091 11.543 

Region 

Midwest 91.7% 0.551 0.014 0 0 0.013 0.095 0.318 0.735 1.328 1.938 3.244 11.747 

Northeast 92.7% 0.651 0.017 0 0 0.016 0.093 0.391 0.934 1.687 2.134 3.38 8.306 

South 91.7% 0.643 0.012 0 0 0.02 0.106 0.394 0.93 1.581 2.173 3.426 8.418 

West 91.0% 0.526 0.014 0 0 0.011 0.086 0.28 0.754 1.33 1.766 2.942 12.239 

NOTE: SE = Standard error 

Source: Based on EPA’s analyses of the 1989-91 CSFII 

Table 11-5. Per Capita Intake of Poultry (g/kg-day as consumed) 

P = Percentile of the distribution
Population Percent 

Group Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 1.2% 0.01 0.01 0 0 0 0 0 0 0 0 0.098 5.081 

Age (years) 

< 01 0.5% 0.014 0.091 0 0 0 0 0 0 0 0 1.113 1.866 

01-02 0.9% 0.026 0.125 0 0 0 0 0 0 0 0 0.692 2.638 

03-05 1.5% 0.01 0.04 0 0 0 0 0 0 0 0 0 2.953 

06-11 1.1% 0.004 0.016 0 0 0 0 0 0 0 0 0 1.176 

12-19 1.0% 0.004 0.019 0 0 0 0 0 0 0 0 0 1.78 

20-39 1.3% 0.01 0.021 0 0 0 0 0 0 0 0 0.098 5.081 

40-69 1.3% 0.012 0.017 0 0 0 0 0 0 0 0 0.462 2.882 

70 + 1.1% 0.002 0.01 0 0 0 0 0 0 0 0 0 2.261 

Season 

Fall 1.7% 0.016 0.022 0 0 0 0 0 0 0 0 0.521 3.488 

Spring 0.7% 0.006 0.019 0 0 0 0 0 0 0 0 0 2.882 

Summer 0.7% 0.003 0.012 0 0 0 0 0 0 0 0 0 1.78 

Winter 1.6% 0.013 0.021 0 0 0 0 0 0 0 0 0.446 5.081 

Urbanization 

Central City 0.7% 0.005 0.014 0 0 0 0 0 0 0 0 0 1.8 

Nonmetropolitan 2.0% 0.019 0.018 0 0 0 0 0 0 0 0 0.822 1.866 

Suburban 1.1% 0.008 0.018 0 0 0 0 0 0 0 0 0 5.081 

Race 

Asian 0.0% 0 0 0 0 0 0 0 0 0 0 0 0 

Black 0.1% 0.001 0.027 0 0 0 0 0 0 0 0 0 0.887 

Native American 0.6% 0.001 0.012 0 0 0 0 0 0 0 0 0 0.255 

Other/NA 0.3% 0.003 0.046 0 0 0 0 0 0 0 0 0 0.636 

White 1.4% 0.011 0.011 0 0 0 0 0 0 0 0 0.329 5.081 

Region 

Midwest 2.2% 0.012 0.012 0 0 0 0 0 0 0 0 0.588 1.866 

Northeast 0.5% 0.005 0.026 0 0 0 0 0 0 0 0 0 2.055 

South 0.8% 0.009 0.025 0 0 0 0 0 0 0 0 0 5.081 

West 1.3% 0.012 0.022 0 0 0 0 0 0 0 0 0.446 2.953 

NOTE: SE = Standard error 

Source: Based on EPA’s analyses of the 1989-91 CSFII 

Table 11-6. Per Capita Intake of Game (g/kg-day as consumed) 

P = Percentile of the distribution 
Population Percent 

Group Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 41.4% 0.317 0.009 0 0 0 0 0 0.445 0.968 1.422 2.953 13.757 

Age (years) 

< 01 32.3% 0.791 0.126 0 0 0 0 0 1.537 2.744 3.645 5.487 13.757 

01-02 43.3% 0.822 0.087 0 0 0 0 0 1.381 2.604 3.299 5.242 8.577 

03-05 39.6% 0.677 0.088 0 0 0 0 0 0.89 2.224 3.106 7.475 10.799 

06-11 36.6% 0.414 0.033 0 0 0 0 0 0.735 1.312 1.617 3.037 6.331 

12-19 36.0% 0.244 0.023 0 0 0 0 0 0.345 0.828 1.26 2.137 4.12 

20-39 43.3% 0.271 0.012 0 0 0 0 0 0.439 0.897 1.193 1.764 5.392 

40-69 44.0% 0.225 0.009 0 0 0 0 0 0.375 0.725 1.029 1.496 3.216 

70 + 42.0% 0.218 0.017 0 0 0 0 0 0.328 0.653 0.969 1.582 2.791 

Season 

Fall 40.1% 0.291 0.017 0 0 0 0 0 0.422 0.871 1.237 2.744 6.331 

Spring 42.7% 0.307 0.017 0 0 0 0 0 0.402 1.015 1.42 2.604 13.548 

Summer 40.5% 0.344 0.02 0 0 0 0 0 0.476 1.035 1.496 3.533 13.757 

Winter 42.2% 0.325 0.019 0 0 0 0 0 0.47 0.98 1.409 2.841 11.39 

Urbanization 

Central City 41.6% 0.315 0.018 0 0 0 0 0 0.423 0.924 1.422 3.106 13.757 

Nonmetropolitan 43.8% 0.338 0.018 0 0 0 0 0 0.493 1.043 1.438 2.826 13.548 

Suburban 39.7% 0.309 0.013 0 0 0 0 0 0.434 0.95 1.399 2.73 11.39 

Race 

Asian 38.9% 0.452 0.094 0 0 0 0 0 0.615 1.47 2.604 2.672 2.672 

Black 48.9% 0.385 0.023 0 0 0 0 0 0.595 1.134 1.486 2.881 6.213 

Native American 49.7% 0.491 0.17 0 0 0 0 0 0.457 1.395 1.61 10.799 13.548 

Other/NA 55.1% 0.472 0.056 0 0 0 0 0 0.712 1.26 2.247 3.292 5.997 

White 39.5% 0.297 0.01 0 0 0 0 0 0.408 0.922 1.368 2.906 13.757 

Region 

Midwest 36.9% 0.288 0.019 0 0 0 0 0 0.35 0.893 1.44 3.106 13.548 

Northeast 35.9% 0.264 0.02 0 0 0 0 0 0.376 0.791 1.229 2.815 11.39 

South 44.3% 0.325 0.014 0 0 0 0 0 0.469 0.999 1.422 2.531 8.737 

West 46.6% 0.392 0.022 0 0 0 0 0 0.563 1.135 1.603 3.08 13.757 

NOTE: SE = Standard error 

Source: Based on EPA’s analyses of the 1989-91 CSFII 

Table 11-7. Per Capita Intake of Eggs (g/kg-day as consumed) 

P = Percentile of the distribution 
95 Surveys 

Food Product (g-day) (g/day) (g/day) (g/day) (g/day) 

77-78 Data 87-88 Data 89-91 Data 94 Data 95 Data 

Beef 52 32 26 24 27 

Poultry 25 26 27 29 24 

Meat Mixtures 69 86 90 95 104 1 

Dairy Products 314 290 286 277 284 2 

Includes mixtures having meat, poultry, or fish as a main ingredient; frozen meals in which the main course is a 1 

meat, poultry, or fish item; meat, poultry, or fish sandwiches coded as a single item; and baby-food meat and 

poultry mixtures. 2 

drinks, meal replacements with milk, milk-based infant formulas, and unreconstituted dry milk and powdered 

mixtures. 

Sources: USDA, 1980; 1992; 1996a; 1996b. 

Table 11-8. Main Daily Intake of Meat and Dairy Products Per Individual in a Day for USDA 1977-78, 87-88, 89-91, 94, and 

Includes total milk, cream, milk desserts, and cheese. Total milk includes fluid milk, yogurt, flavored milk, milk 
Table 11-9. Mean Per Capita Intake Rates for Meat, Poultry, and Dairy Products (g/kg-d as consumed) 

Based on All Sex/Age/Demographic Subgroups 

Average Consumption 

Raw Agricultural Commoditya (Grams/kg Body Weight/Day) Standard Error 

0.0134468 

0.0134468 

0.0060264 

0.0060264 

0.0033996 

0.0005652 

0.0007012 

0.0004123 

0.0048605 

0.0003059 

0.0014002 

0.0159453 

NA 

NA 

0.0000238 

NA 

NA 

0.0001139 

NA 

0.00003544 

0.0000381 

0.0000197 

0.0005956 

0.0000079 

NA 

0.0015077 

0.0022720 

0.0003233 

0.0032032 

0.0000106 

0.0004288 

0.0060683 

0.0010935 

0.0000339 

0.0000370 

0.0007933 

0.0026028 

0.0000552 

NA 

0.0001440 

0.0007590 

0.0076651 

0.0004441 

0.0004295 

NA 

0.0005727 

0.0021616 

Chicken - Flesh (+ Skin, w/o Bones) 0.0104779 

NA = Not applicable

 Consumed in any raw or prepared form. a 

Source: DRES database (based on 1977-78 NFCS) 

Milk-Non-Fat Solids 0.9033354 

Milk-Non-Fat Solids (Food additive) 0.9033354 

Milk-Fat Solids 0.4297199 

Milk-Fat Solids (Food additive) 0.4297199 

Milk Sugar (Lactose) 0.0374270 

Beef-Meat Byproducts 0.0176621 

Beef (Organ Meats) - Other 0.0060345 

Beef - Dried 0.0025325 

Beef (Boneless) - Fat (Beef Tallow) 0.3720755 

Beef (Organ Meats) - Kidney 0.0004798 

Beef (Organ Meats) - Liver 0.0206980 

Beef (Boneless) - Lean (w/o Removeable Fat) 1.1619987 

Goat-Meat Byproducts 0.0000000 

Goat (Organ Meats) - Other 0.0000000 

Goat (Boneless) - Fat 0.0000397 

Goat (Organ Meats) - Kidney 0.0000000 

Goat (Organ Meats) - Liver 0.0000000 

Goat (Boneless) - Lean (w/o Removeable Fat) 0.0001891 

Horse 0.0000000 

Rabbit 0.0014207 

Sheep - Meat Byproducts 0.0000501 

Sheep (Organ Meats) - Other 0.0000109 

Sheep (Boneless) - Fat 0.0042966 

Sheep (Organ Meats) - Kidney 0.0000090 

Sheep (Organ Meats) - Liver 0.0000000 

Sheep (Boneless) - Lean (w/o Removeable Fat) 0.0124842 

Pork - Meat Byproducts 0.0250792 

Pork (Organ Meats) - Other 0.0038496 

Pork (Boneless) - Fat (Including Lard) 0.2082022 

Pork (Organ Meats) - Kidney 0.0000168 

Pork (Organ Meats) - Liver 0.0048194 

Pork (Boneless) - Lean (w/o Removeable Fat) 0.3912467 

Meat, Game 0.0063507 

Turkey - Byproducts 0.0002358 

Turkey - Giblets (Liver) 0.0000537 

Turkey - Flesh (w/o Skin, w/o Bones) 0.0078728 

Turkey - Flesh (+ Skin, w/o Bones) 0.0481655 

Turkey - Unspecified 0.0000954 

Poultry, Other - Byproducts 0.0000000 

Poultry, Other - Giblets (Liver) 0.0002321 

Poultry, Other - Flesh (+ Skin, w/o Bones) 0.0053882 

Eggs - Whole 0.5645020 

Eggs - White Only 0.0092044 

Eggs - Yolk Only 0.0066323 

Chicken - Byproducts 0.0000000 

Chicken - Giblets (Liver) 0.0050626 

Chicken - Flesh (w/o Skin, w/o Bones) 0.0601361 

0.3793205 
a 

Group Age (yrs.) Poultry and Beef Pork Game Luncheon Meats, Poultry Only Mixtures 

Total Lamb, Frankfurters,

 Meat, Veal, Sausages, Total Chicken Meat 

Fish Spreads 

c 

Males and Females 

1 and Under 72 9 4 3 2 4 1 51 

1-2 91 18 6 (b) 15 16 13 32 

3-5 121 23 8 (b) 15 19 19 49 

6-8 149 33 15 1 17 20 19 55 

Males 

9-11 188 41 22 3 19 24 21 71 

12-14 218 53 18 (b) 25 27 24 87 

15-18 272 82 24 1 25 37 32 93 

19-22 310 90 21 2 33 45 43 112 

23-34 285 86 27 1 30 31 29 94 

35-50 295 75 28 1 26 31 28 113 

51-64 274 70 32 1 29 31 29 86 

65-74 231 54 25 2 22 29 26 72 

75 and Over 196 41 39 7 19 28 25 54 

Females 

9-11 162 38 17 1 20 27 23 55 

12-14 176 47 19 1 18 23 22 61 

15-18 180 46 14 2 16 28 27 61 

19-22 184 52 19 1 18 26 24 61 

23-34 183 48 17 1 16 24 22 66 

35-50 187 49 19 2 14 24 21 63 

51-64 187 52 19 2 12 26 24 60 

65-74 159 34 21 4 12 30 25 47 

75 and Over 134 31 17 2 9 19 16 49 

Males and Females 

All Ages 207 54 20 2 20 27 24 72

Based on USDA Nationwide Food Consumption Survey 1977-78 data for one day. a

Less than 0.5 g/day but more than 0. b

Includes mixtures containing meat, poultry, or fish as a main ingredient. c 

Table 11-10. Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as consumed) for 1977-1978 

Source: USDA, 1980. 
a 

Group Poultry, and Veal, Sausages, Total Chicken Meat 

Age (yrs.) Fish Beef Pork Game Luncheon Poultry Only Mixtures 

Total Meat, Lamb, Frankfurters, 

Meats 

b 

Males and Females

 5 and Under 92 10 9 <0.5 11 14 12 39 

Males

 6-11 156 22 14 <0.5 13 27 24 74

 12-19 252 38 17 1 20 27 20 142

 20 and over 250 44 19 23 2 31 25 108 

Females

 6-11 151 26 9 1 11 20 17 74

 12-19 169 31 10 <0.5 18 17 13 80

 20 and over 170 29 12 1 13 24 18 73 

All individuals 193 32 14 1 17 26 20 86

Based on USDA Nationwide Food Consumption Survey 1987-88 data for one day. a

Includes mixtures containing meat, poultry, or fish as a main ingredient. b 

Table 11-11. Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as consumed) for 1987-1988 

Source: USDA, 1992. 
a 

Group Age (yrs.) Total Milk Fluid Milk Cheese Eggs 

1 and Under 618 361 1 5 

1-2 404 397 8 20 

3-5 353 330 9 22 

6-8 433 401 10 18 

9-11 432 402 8 26 

12-14 504 461 9 28 

15-18 519 467 13 31 

19-22 388 353 15 32 

23-34 243 213 21 38 

35-50 203 192 18 41 

51-64 180 173 17 36 

65-74 217 204 14 36 

75 and Over 193 184 18 41 

9-11 402 371 7 14 

12-14 387 343 11 19 

15-18 316 279 11 21 

19-22 224 205 18 26 

23-34 182 158 19 26 

35-50 130 117 18 23 

51-64 139 128 19 24 

65-74 166 156 14 22 

75 and Over 214 205 20 19 

All Ages 266 242 15 27

 Based on USDA Nationwide Food Consumption Survey 1977-78 data for one day. a 

Table 11-12. Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day as consumed) for 1977-1978 

Source: USDA, 1980. 
a 

Group Age (yrs.) Total Fluid Milk Whole Milk Lowfat/Skim Cheese Eggs 

Milk 

Males and Females

 5 and under 347 177 129 7 11 

Males

 6-11 439 224 159 10 17

 12-19 392 183 168 12 17

 20 and over 202 88 94 17 27 

Females

 6-11 310 135 135 9 14

 12-19 260 124 114 12 18

 20 and over 148 55 81 15 17 

All individuals 224 99 102 14 20

 Based on USDA Nationwide Food Consumption Survey 1987-88 data for one day. a 

Table 11-13. Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day as consumed) for 1987-1988 

Source: USDA, 1992. 
a 

Frankfurters, 

Total Meat, Sausages, 

Group Poultry, and Lamb, Veal, Luncheon Meat 

Age (yrs.) Fish Beef Pork Game Meats Total Poultry Chicken Only Mixturesc 

1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 

Males and Females

 5 and Under 94 87 10 8 6 4 (b) (b) 17 18 16 15 14 14 41 39 

Males

 6-11 131 161 19 18 9 7 0 (b) 22 27 19 25 16 22 51 68

 12-19 238 256 31 29 11 11 1 1 21 27 40 26 29 23 119 150

 20 and over 266 283 35 41 17 14 2 1 29 27 39 31 30 27 124 149 

Females

 6-11 117 136 18 16 5 5 (b) (b) 18 20 19 17 15 14 51 69

 12-19 164 158 23 22 5 7 (b) 0 16 10 20 19 15 18 94 82

 20 and over 168 167 18 21 9 11 1 1 16 15 25 22 20 19 87 83 

All individuals 195 202 24 27 11 10 1 1 21 21 29 24 23 21 98 104

 Based on USDA CSFII 1994 and 1995 data for one day. a

 Less than 0.5 g/day but more than 0. b

 Includes mixtures containing meat, poultry, or fish as a main ingredient. c 

Table 11-14. Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as consumed) for 1994 and 1995 

Source: USDA, 1996a; 1996b. 
a 

Group Age (yrs.) Total Fluid Milk Whole Milk Lowfat Milk Cheese Eggs 

1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 

Males and Females .

 5 and under 424 441 169 165 130 129 12 9 11 13 

Males

 6-11 407 400 107 128 188 164 11 12 13 15

 12-19 346 396 105 105 160 176 19 20 18 24

 20 and over 195 206 50 57 83 88 19 16 23 23 

Females

 6-11 340 330 101 93 136 146 17 13 12 15

 12-19 239 235 75 71 88 107 14 13 13 17

 20 and over 157 158 37 32 56 57 16 15 15 16 

All individuals 229 236 65 66 89 92 17 15 17 19

 Based on USDA CSFII 1994 and 1995 data for one day. a 

Table 11-15. Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day as consumed) for 1994 and 1995 

Source: USDA, 1996a; 1996b. 
Table 11-16. Mean and Standard Error for the Dietary Intake 

of Food Sub Classes Per Capita by Age (g/day as consumed) 

Age (yrs.) Milk Products Eggs Beef Pork 

Fresh Cows’ Other Dairy 

Poultry Other Mea

All Ages 253.5 ± 4.9 55.1 ± 1.2 26.9 ± 0.5 87.6 ± 1.1 28.2 ± 0.6 31.3 ± 0.8 25.1 ± 0.4 

<1 272.0 ± 31.9 296.7 ± 7.6 4.9 ± 3.2 18.4 ± 7.4 5.8 ± 3.6 18.4 ± 4.9 2.6 ± 2.8 

1-4 337.3 ± 15.6 41.0 ± 3.7 19.8 ± 1.6 42.2 ± 3.7 13.6 ± 1.8 19.0 ± 2.4 17.6 ± 1.4 

5-9 446.2 ± 13.1 47.3 ± 3.1 17.0 ± 1.3 63.4 ± 3.1 18.2 ± 1.5 24.7 ± 2.0 22.3 ± 1.2 

10-14 456.0 ± 12.3 53.3 ± 2.9 19.3 ± 1.2 81.9 ± 2.9 22.2 ± 1.4 30.0 ± 1.9 26.1 ± 1.1 

15-19 404.8 ± 12.9 52.9 ± 3.1 24.8 ± 1.3 99.5 ± 3.0 29.5 ± 1.5 33.0 ± 2.0 27.6 ± 1.1 

20-24 264.3 ± 16.4 44.2 ± 4.0 28.3 ± 1.7 103.7 ± 3.9 29.6 ± 1.9 33.0 ± 2.6 28.8 ± 1.5 

25-29 217.6 ± 17.2 51.5 ± 4.1 27.9 ± 1.7 103.8 ± 4.0 31.8 ± 2.0 33.8 ± 2.7 28.9 ± 1.5 

30-39 182.9 ± 13.5 53.8 ± 3.2 30.1 ± 1.4 105.8 ± 3.2 33.0 ± 1.5 34.0 ± 2.1 28.4 ± 1.2 

40-59 169.1 ± 10.5 52.0 ± 2.5 31.1 ± 1.0 99.0 ± 2.5 33.5 ± 1.2 33.8 ± 1.6 27.4 ± 0.9 

$60 192.4 ± 11.8 55.9 ± 2.8 28.7 ± 1.2 74.3 ± 2.8 27.5 ± 1.3 31.5 ± 1.8 21.1 ± 1.0 

Source: U.S. EPA, 1984a (based on 1977-78 NFCS).
consumed) 

US Population Northeast South West 

Dairy Products (Total) 308.6 ± 5.3 318.6 ± 10.4 336.1 ± 10.0 253.6 ± 8.4 348.1 ± 12.3 

Fresh Cows Milk 253.5 ± 4.9 256.1 ± 9.7 279.7 ± 9.4 211.0 ± 7.8 283.5 ± 11.5 

Other 55.1 ± 1.2 62.5 ± 2.3 56.5 ± 2.2 42.6 ± 1.9 64.6 ± 2.7 

Eggs 26.9 ± 0.5 23.8 ± 1.0 23.5 ± 0.9 31.0 ± 0.8 29.1 ± 1.2 

Meats (Total) 172.2 ± 1.6 169.9 ± 3.3 176.9 ± 3.1 171.9 ± 2.6 168.6 ± 3.9 

Beef and Veal 87.6 ± 1.1 82.3 ± 2.3 92.9 ± 2.2 84.0 ± 1.8 92.9 ± 2.7 

Pork 28.2 ± 0.6 28.8 ± 1.1 29.6 ± 1.1 30.1 ± 0.9 22.1 ± 1.3 

Poultry 31.3 ± 0.8 31.7 ± 1.5 26.6 ± 1.4 36.5 ± 1.2 28.9 ± 1.8 

Other 25.1 ± 0.4 27.1 ± 0.9 27.8 ± 0.8 21.3 ± 0.7 24.7 ± 1.0 

NOTE: Northeast = Maine, New Hampshire, Vermont, Massachusetts, Connecticut, Rhode Island, New York, New 

Jersey, and Pennsylvania. 

North Central = Ohio, Illinois, Indiana, Wisconsin, Michigan, Minnesota, Iowa, Missouri, North Dakota, South 

Dakota, Nebraska, and Kansas. 

South = Maryland, Delaware, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, 

Georgia, Florida, Kentucky, Tennessee, Alabama, Mississippi, Arkansas, Louisiana, Texas, and Oklahoma. 

West = Montana, Idaho, Wyoming, Utah, Colorado, New Mexico, Arizona, Nevada, Washington, Oregon, and 

California. 

Source: U.S. EPA, 1984b (based on 1977-78 NFCS). 

Table 11-17. Mean and Standard Error for the Per Capita Daily Intake of Food Class and Sub Class by Region (g/day as 

North Central
Estimated Lifetime Average Intakes for 70 Kg Adult Citizens Calculated from the FDA Diet Data. 

Produce (0-1 yrs) 1-6 yrs) (6-14 yrs) (14-20 yrs) (20-45 yrs) (45-70 yrs) Lifetime 

Baby Toddler Child Teen Adult Old Estimated 

Intakea 

g - dry weight/day 

Beef 3.99 9.66 15.64 21.62 23.28 18.34 19.25 

Beef Liver 0.17 0.24 0.30 0.36 1.08 1.2 0.89 

Lamb 0.14 0.08 0.06 0.05 0.30 0.21 0.20 

Pork 1.34 4.29 6.57 8.86 10.27 9.94 9.05 

Poultry 2.27 3.76 5.39 7.03 7.64 6.87 6.70 

Dairy 40.70 32.94 38.23 43.52 27.52 22.41 28.87 

Eggs 3.27 6.91 7.22 7.52 8.35 9.33 8.32 

Beef Fat 2.45 6.48 11.34 16.22 20.40 14.07 15.50 

Beef Liver Fat 0.05 0.07 0.08 0.10 0.29 0.33 0.25 

Lamb Fat 0.14 0.08 0.07 0.06 0.31 0.22 0.21 

Dairy Fat 38.99 16.48 20.46 24.43 18.97 14.51 18.13 

Pork Fat 2.01 8.19 10.47 12.75 14.48 13.04 12.73 

Poultry Fat 1.10 0.83 1.12 1.41 1.54 1.31 1.34 

a The estimated lifetime dietary intakes were estimated by: 

Estimated lifetime intake = IR(0-1) + 5yrs * IR (1-5) + 8 yrs * IR (6-13) + 6 yrs * IR (14-19) + 25 yrs * IR (20-44) + 25 yrs * IR (45-70) 

70 years 

where IR = the intake rate for a specific age group. 

Table 11-18. Consumption of Meat, Poultry, and Dairy Products for Different Age Groups (averaged across sex), and 

Source: U.S. EPA, 1989 (based in 1977-78 NFCS and NHANES II data). 
a 

Food Item (g/day) (g/day) (g/day) (g/day) 

Per Capita Consumption Per Capita Per Capita Consumption Retail Per Capita Consumption Bonele

Consumption RTC Cut Equivalent Trimmed Equivalent b 

f 

c 

f 

d 

f 

e 

f 

Red Meat 

Beef 118.3 --- 82.8 78.4 

Veal 1.5 --- 1.2 0.99 

Pork 8.0 --- 62.1 58.3 

Lamb and Mutton 2.0 --- 1.7 1.2 

Total 201.7 --- 147.9 139.1 g 

Poultry 

Young Chicken --­ --- 78.3 --­

Other Chicken --­ --- 1.7 --­

Chicken --- 91.3 --- 54.5 

Turkey --- 22.2 --- 17.5 

Total --- 109.2 77.0 72.1 g 

h,i 

h 

Includes processed meats and poultry in a fresh basis; excludes shipments to U.S. territories; uses U.S. total population, July 1, and does not include a 

residents of the U.S. territories. b 

RTC - ready-to-cook poultry weight is the entire dressed bird which includes bones, skin, fat, liver, heart, gizzard, and neck. c 

Retail equivalents in 1991 were converted from carcass weight by multiplying by a factor of 0.7, 0.83, 0.89, and 0.776 for beef, veal, lamb, and pork, d 

respectively; 0.877 was the factor used each for young chicken and other chicken. e 

and pork, respectively; 0.597, 0.597 and 0.790 were the factors used for young chicken, other chicken, and turkey. 

Original data were presented in lbs; converted to g/day by multiplying by a factor of 453.6 g/lb and dividing by 365 days/yr. f 

Computed from unrounded data. g 

Includes skin, neck, and giblets. h 

Excludes amount of RTC chicken going to pet food as well as some water leakage that occurs when chicken is cut-up before packaging. i 

Table 11-19. Per Capita Consumption of Meat and Poultry in 1991

Carcass Weight 

Beef-Carcass-Weight is the weight of the chilled hanging carcass, which includes the kidney and attached internal fat [kidney, pelvic, and heart fat (kph)] 

but not head, feet, and unattached internal organs. Definitions of carcass weight for other red meats differ slightly. 

Boneless equivalent for red meat derived from carcass weight in 1991 by using conversion factors of 0.663, 0.685, 0.658 and 0.729 for beef, veal, lamb, 

Source: USDA, 1993. 
a 

Food Item Per Capita 

Consumption 

(g/day)j 

Food Item Per Capita 

Consumption 

(g/day)j 

Eggs 

Farm Weight 37.8 b,e 

Retail Weight 37.3 c,e 

Fluid Milk and Cream 289.7 

Plain Whole Milk 105.3 

Lowfat Plain Milk (2%) 98.1 

Lowfat Plain Milk (1%) 25.8 

Skim Plain Milk 29.7 

Whole Flavored Milk and Drink 3.4 

Lowfat Flavored Milk and Drink 8.5 

Buttermilk (lowfat and skim) 4.2 

Half and Half Cream 3.9 

Light Cream 0.4 

Heavy Cream 1.6 

Sour Cream 3.2 

Eggnog 0.5 

Evaporated and Condensed Milki 

Canned Whole Milk 2.6 

Bulk Whole Milk 1.4 

Bulk and Canned Skim Milk 6.2 

Total 10.2 e 

Dry Milk Productsi 

Dry Whole Milk 0.5 

Nonfat Dry Milk 3.2 

Dry Buttermilk 0.3 

Total 4.0 e 

Dried Whey 4.5 

Butter 5.2 

Cheese 

American 

Cheddar 11.2 

Italian 

Provolone 0.8 

Romano 0.2 

Parmesan 0.6 

Mozzarella 9.0 

Ricotta 1.0 

Other 0.07 

Miscellaneous 

Swiss 1.5 

Brick 0.07 

Muenster 0.5 

Cream 1.9 

Neufchatel 0.3 

Other 1.2 

Processed Products 

Cheese 6.1 

Foods and spreads 4.7 

Cheese Content 8.5 

Cottage Cheese (lowfat) 1.6 

Frozen Dairy Products 

Ice Cream 20.3 

Ice Milk 9.2 

Sherbet 1.5 

Total 36.4 

Other 2.5 d 

f 

Blue 0.2 g 

Consumed as Natural 22.6 

Other Frozen Products 5.3 h 

e 

All Diary Products 

USDA Donations 17.1 

Commercial Sales 685.2 

Total 702.4 

All per capita consumption figures use U.S. total populations, except fluid milk and cream data, which are based on a 

does not include U.S. territories. 

A dozen eggs converted at 1.57 pounds. b 

The factor for converting farm weight to retail weight was 0.97 in 1960 and was increased 0.003 per year until 0.985 was c 

reached in 1990. 

Includes Colby, washed curd, Monterey, and Jack. d 

Computed from unrounded data. e 

Includes imports of Gruyere and Emmenthaler. f 

Includes Gorgonzola. g 

Includes mellorine, frozen yogurt beginning 1981, and other nonstandardized frozen diary products. h 

Includes quantities used in other dairy products. i 

Original data were presented in lbs, conversions to g/day were calculated by multiplying by a factor of 453.6 and j 

dividing by 365 days. 

Table 11-20. Per Capita Consumption of Dairy Products in 1991

U.S. residential population. For eggs, excludes shipments to U.S. territories, uses U.S. total population, July 1, which 

Source: USDA, 1993. 
a 

Mean Daily Intake (g/day) 

Region 

Food Item 

Pacific Mountain North Central Northeast South 

Male Female Male Female Male Female Male Female Male Fema

Beef 84.8 52.8 89.8 59.6 86.8 55.9 71.8 46.6 87.3 54.9 

Pork 18.6 12.6 23.7 16.8 26.5 18.8 22.4 15.9 24.4 17.2 

Lamb 1.3 1.2 0.5 0.3 0.4 0.4 1.3 1.0 0.5 0.3 

Veal 0.4 0.2 0.2 0.2 0.4 0.4 2.8 1.5 0.3 0.3 

Variety 

Meats/Game 11.1 7.9 9.1 7.4 11.9 8.0 8.1 6.8 9.4 7.8 

Processed Meats 22.8 15.4 22.9 13.2 26.3 15.8 21.2 15.5 26.0 17.0 

Poultry 67.3 56.1 51.0 45.2 51.7 44.7 56.2 49.2 57.7 50.2 

Adult population represents consumers ages 19 and above. a 

NOTE: Pacific = Washington, Oregon and California 

Mountain = Montana, Idaho, Wyoming, Utah, Colorado, New Mexico, Arizona, and Nevada 

North Central = Ohio, Illinois, Indiana, Wisconsin, Michigan, Minnesota, Iowa, Missouri, North Dakota, South 

Dakota, Nebraska, and Kansas. 

Northeast = Maine, New Hampshire, Vermont, Massachusetts, Connecticut, Rhode Island, New York, New 

Jersey, and Pennsylvania. 

South = Maryland, Delaware, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, 

Georgia, Florida, Kentucky, Tennessee, Alabama, Mississippi, Arkansas, Louisiana, Texas, and Oklahoma. 

Table 11-21. Adult Mean Daily Intake (as consumed) of Meat and Poultry Grouped by Region and Gender

Source: National Livestock and Meat Board, 1993. 
e 

Frequency of Eatings Eaters (g) (g/day) 

Percent of Total for 14 Days Intake 

Percent of Eaters Total 

Consumption Median Daily 

Male Female 

Non-Meat Eaters 1% 20 80 None None a 

Light Meat Eaters 30% 27 73 <1025 54 b 

Medium Meat Eaters 33% 39 61 1025-1584 93 c 

Heavy Meat Eaters 36% 73 27 >1548 144 d 

a 

b 

to include children. 

This person may be of either sex, might be on a diet, and probably lives in a household of 2-4 people, which may c 

include children. 

Male who is not on a diet and lives in a household of 2-4 individuals, which may include children. d 

Adult population represents consumers ages 19 and above. e 

Table 11-22. Amount (as consumed) of Meat Consumed by Adults Grouped by Frequency of Eatings

A female who is employed and on a diet. She lives alone or in a small household (without children). 

Female who may or may not be on a diet. There are probably 2-4 people in her household but that number is not likely 

Source: National Livestock and Meat Board, 1993. 
and the Percentage of Individuals Using These Foods in Three Days 

% Indiv. using Quantity consumed per eating 

food in 3 days occasion Consumers-only 

Food category (g) Quantity consumed per eating occasion at Specified Percentiles (g) 

Average Standard 5 25 50 75 90 95 99 

Deviation 

Meata 84.6 107 85 16 46 86 140 224 252 432 

Beef 67.3 133 85 41 84 112 168 224 280 448 

Pork 49.9 69 69 8 16 44 92 160 194 320 

Lamb 1.5 146 84 43 88 123 184 227 280 448 

Veal 2.3 130 71 42 84 112 168 224 276 352 

Poultry 42.8 128 77 42 82 112 168 224 280 388 

Chicken 38.7 131 76 43 84 112 170 224 280 388 

Turkey 5.8 105 73 28 57 86 129 172 240 350 

Dairy Products 

Eggs 54.3 82 44 40 50 64 100 128 150 237 

Butter 31.4 12 13 2 5 7 14 28 28 57 

Margarine 43.1 11 11 2 5 7 14 28 28 57 

Milkb 82.5 203 134 15 122 244 245 366 488 552 

Cheesec 40 41 28 14 28 28 56 58 85 140 

a Meat - beef, pork, lamb, and veal. 

b Milk - fluid milk, milk beverages, and milk-based infant formulas. 

c Cheese - natural and processed cheese. 

Table 11-23. Quantity (as consumed) of Meat, Poultry, and Dairy Products Consumed Per Eating Occasion 

Source: Pao et al., 1982 (based on 1977-78 NFCS). 
of Selected Meat and Dairy Productsa 

Product Fat Percentage Comment 

Meats 

Beef 

Lean only 6.16 Raw 

Lean and fat, 1/4 in. fat trim 9.91 Cooked 

Brisket (point half) 19.24 Raw 

Lean and fat 21.54 Cooked 

Brisket (flat half) 

Lean and fat 22.40 Raw 

Lean only 4.03 Raw 

Pork 

Lean only 5.88 Raw 

Lean and fat 14.95 Raw 

Cured shoulder, blade roll, lean and fat 20.02 Unheated 

Cured ham, lean and fat 12.07 Center slice 

Cured ham, lean only 7.57 Raw, center, country style 

Sausage 38.24 Raw, fresh 

Ham 4.55 Cooked, extra lean (5% fat) 

Ham 9.55 Cooked, (11% fat) 

9.66 Cooked 

17.18 Cooked 

Lamb 

Lean 5.25 Raw 

Lean and fat 21.59 Raw 

9.52 Cooked 

20.94 Cooked 

Veal 

Lean 2.87 Raw 

Lean and fat 6.77 Raw 

6.58 Cooked 

11.39 Cooked 

Rabbit 

Composite of cuts 5.55 Raw 

8.05 Cooked 

Chicken 

Meat only 3.08 Raw 

Meat and skin 15.06 Raw 

7.41 Cooked 

13.60 Cooked 

Turkey 

Meat only 2.86 Raw 

Meat and skin 8.02 Raw 

Ground 6.66 Raw 

4.97 Cooked 

9.73 Cooked 

Table 11-24. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions)
a 

Product Fat Percentage Comment 

Dairy 

Milk 

Whole 3.16 3.3% fat, raw or pasteurized 

Human 4.17 Whole, mature, fluid 

Lowfat (1%) 0.83 Fluid 

Lowfat (2%) 1.83 Fluid 

Skim 0.17 Fluid 

Cream 

Half and half 18.32 Table or coffee, fluid 

Medium 23.71 25% fat, fluid 

Heavy-whipping 35.09 Fluid 

Sour 19.88 Cultured 

Butter 76.93 Regular 

Cheese 

American 29.63 Pasteurized 

Cheddar 31.42 

Swiss 26.02 

Cream 33.07 

Parmesan 24.50; 28.46 Hard; grated 

Cottage 1.83 Lowfat, 2% fat 

Colby 30.45 

Blue 27.26 

Provolone 25.24 

Mozzarella 20.48 

Yogurt 1.47 Plain, lowfat 

Eggs 8.35 Chicken, whole raw, fresh or frozen

Based on the lipid content in 100 grams, edible portion. a 

Table 11-24. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions)

 of Selected Meat and Dairy Products (continued) 

Source: USDA, 1979-1984.
Table 11-25. Fat Content of Meat Products 

Meat Product Total Fat Percent Fat 

3-oz cooked serving (85.05 g) (g) Content (%) 

Beef, retail composite, lean only 8.4 9.9 

Pork, retail composite, lean only 8.0 9.4 

Lamb, retail composite, lean only 8.1 9.5 

Veal, retail composite, lean only 5.6 6.6 

Broiler chicken, flesh only 6.3 7.4 

Turkey, flesh only 4.2 4.9 

Source: National Livestock and Meat Board, 1993 

. 
Various Meat Eater Groups of the U.S. Population 

Total Heavy Meat Medium Meat Light Meat Non-Meat 

Population Eaters Eaters Eaters Eaters 

Average Fat Intake (g) 68.3 84.5 62.5 53.5 32.3 

Percent of Population 100 36 33 30 1 

Meat Group (%) 41 44 40 37 33 a 

Bread Group (%) 24 23 24 26 25 

Milk Group (%) 12 11 13 14 14 

Fruits (%) 1 1 1 1 1 

Vegetables (%) 9 9 9 9 11 

Fats/oil/sweets (%) 13 12 13 14 17

 Meat Group includes meat, poultry, dry beans, eggs, and nuts. a 

Table 11-26. Fat Intake, Contribution of Various Food Groups to Fat Intake, and Percentage of the Population in 

Source: National Livestock and MeatBoard, 1993. 
Table 11-27. Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gendera 

Total Males Females 

Age N Mean Fat Intake N Mean Fat Intake N Mean Fat In

(yrs) (g/day) (g/day) (g/day) 

2-11 (months) 871 37.52 439 38.31 432 36.95 

1-2 1,231 49.96 601 51.74 630 48.33 

3-5 1,647 60.39 744 70.27 803 61.51 

6-11 1,745 74.17 868 79.45 877 68.95 

12-16 711 85.19 338 101.94 373 71.23 

16-19 785 100.50 308 123.23 397 77.46 

20-29 1,882 97.12 844 118.28 638 76.52 

30-39 1,628 93.84 736 114.28 791 74.06 

40-49 1,228 84.90 626 99.26 602 70.80 

50-59 929 79.29 473 96.11 456 63.32 

60-69 1,108 69.15 646 80.80 560 59.52 

70-79 851 61.44 444 73.35 407 53.34 

$ 80 809 54.61 290 68.09 313 47.84 

Total 14,801 81.91 7,322 97.18 7,479 67.52 

$ 2 13,314 82.77 6,594 98.74 8,720 68.06 

Total dietary fat intake includes all fat (i.e., saturated and unsaturated) derived from consumption of foods and a 

beverages (excluding plain drinking water). 

Source: Adapted from CDC, 1994. 
Table 11-28. Percentage Mean Moisture Content (Expressed as Percentages of 100 Grams of Edible Portions)a 

Food Moisture Content Comments 

Percent 

Meat 

Beef 71.60 Raw, composite, trimmed, retail cuts 

Beef liver 68.99 Raw 

Chicken (light meat) 74.86 Raw, without skin 

Chicken (dark meat) 75.99 Raw, without skin 

Duck - domestic 73.77 Raw 

Duck - wild 75.51 Raw 

Goose - domestic 68.30 Raw 

Ham - cured 66.92 Raw 

Horse 72.63 Raw, roasted 

Lamb 73.42 Raw, composite, trimmed, retail cuts 

Lard 0.00 

Pork 70.00 Raw 

Rabbit - domestic 72.81 Raw 

Turkey 74.16 Cooked, roasted 

Dairy Products 

Eggs 74.57 Raw 

Butter 15.87 Raw 

39.16 Regular

 Cheddar 36.75

 Swiss 37.21

 Parmesan, hard 29.16

 Parmesan, grated 17.66

 Cream, whipping, heavy 57.71

 Cottage, lowfat 79.31

 Colby 38.20

 Blue 42.41

 Cream 53.75 

Yogurt

 Plain, lowfat 85.07

 Plain, with fat 87.90 Made from whole milk 

Human milk - estimated 

from USDA Survey

 Human 87.50 Whole, mature, fluid

 Skim 90.80

 Lowfat 90.80 1% 

63.98 Cooked, roasted 

69.11 Raw, roasted

 Based on the water content in 100 grams, edible portion. a 

Cheese American pasteurized 

Source: USDA, 1979-1984. 
Survey Population Used in 

Study Calculating Intake Types of Data Used Food Items 

KEY STUDIES 

EPA Analysis of Per capita 1989-91 CSFII data; g/kg-day; as consumed Distributions of intake rates for total 

1989-91 CSFII Data Based on 3-day average meats and total dairy; individual 

individual intake rates. food items. 

RELEVANT STUDIES 

AIHC, 1994 Adults, Per Capita g/day Distribution for beef consumption 

presented in the 1989 version presented in @Risk format. 

of the Exposure Factors 

Handbook that were analyzed 

by Finley and Paustenbach 

(1992). 

EPA's DRES Per capita (i.e., consumers 1977-78 NFCS g/kg-day; as consumed Intake for a wide variety of meats, 

(White et al., 1983) and nonconsumers) 3-day individual intake data poultry, and dairy products 

presented; complex food groups 

were disaggregated 

NLMB, 1993 Adult daily mean intake MRCA’s Menu Census g/day; as consumed Intake rates for various meats by 

rates region and gender. 

Pao et al., 1982 Consumers only serving 1977-78 NFCS g; as consumed Distributions of serving sizes for 

size data provided 3-day individual intake data meats, poultry, and diary products. 

USDA, 1980; 1992; Per capita and consumer 1977-78 and 1987-88 NFCS, g/day; as consumed Total meat, poultry and fish, total 

1996a; 1996b only grouped by age and and 1994 and 1995 CSFII poultry, total milk, cheese and eggs. 

sex 1-day individual intake data 

USDA, 1993 Per capita consumption Based on food supply and g/day; as consumed Intake rates of meats, poultry, and 

based on "food utilization data which were diary products; intake rates of 

disappearance" provided by National individual food items. 

Agricultural Statistics Service 

(NASS), Customs Service 

reports, and trade 

associations. 

U.S. EPA/ORP, Per capita 1977-78 NFCS g/day; as consumed Mean intake rates for total meats, 

1984a; 1984b Individual intake data total diary products, and individual 

food items. 

U.S. EPA/OST, Estimated lifetime dietary Based on FDA Total Diet g/day; dry weight Various food groups; complex 

1989 intake Study Food List which used foods disaggregated 

1977-78 NFCS data, and 

NHANES II data 

Table 11-29. Summary of Meat, Poultry, and Dairy Intake Studies 

Units 

USDA NFCS 1977-78 data 
Meat and Dairy Products and Serving Size 

Mean 95th Percentile Multiple Percentiles Study 

Total Meat Intake 

2.1 g/kg-day 5.1 g/kg-day see Table 11-1 EPA Analysis of CSFII 1989-91 Data 

Total Dairy Intake 

8.0 g/kg-day 29.7 g/kg-day see Table 11-2 EPA Analysis of CSFII 1989-91 Data 

Individual Meat and Dairy Products 

see Tables 11-3 to 11-7 see Tables 11-3 to see Tables 11-3 to 11-7 EPA Analysis of CSFII 1989-91 Data 

11-7 

Table 11-30. Summary of Recommended Values for Per Capita Intake of
Considerations Rationale Rating 

Study Elements

 • Level of peer review USDA CSFII survey receives high level of peer High 

reviewed outside the Agency.

 • Accessibility CSFII data are publicly available. High

 • Reproducibility Enough information is included to reproduce High 

results.

 • Focus on factor of interest Analysis is specifically designed to address food High 

intake.

 • Data pertinent to U.S. Data focuses on the U.S. population. High

 • Primary data This is new analysis of primary data. High

 • Currency Were the most current data publicly available at High 

the time the analysis was conducted for this 

Handbook.

 • Adequacy of data collection period Survey is designed to collect short-term data. Medium confidence for average values

Low confidence for long term percentil

distribution

 • Validity of approach Survey methodology was adequate. High

 • Study size Study size was very large and therefore High 

adequate.

 • Representativeness of the population The population studied was the U.S. population. High

 • Characterization of variability Survey was not designed to capture long term Medium 

are provided for various age groups, regions, etc.

 • Lack of bias in study design (high rating is desirable) Response rate was adequate. Medium

 • Measurement error N/A 

on survey data. 

Other Elements

 • Number of studies 1 Low

 CSFII was the most recent data set publicly 

available at the time the analysis was conducted 

study classified as key study.

 • Agreement between researchers Although the CSFII was the only study classified High 

as key study, the results are in good agreement 

with earlier data. 

Overall Rating The survey is representative of U.S. population. High confidence in the average; 

Although there was only one study considered Low confidence in the long-term upper 

key, these data are the most recent and are in percentiles 

to the limitations of the survey design, 

estimation of long-term percentile values 

(especially the upper percentiles) is uncertain. 

Table 11-31. Confidence in Meats and Dairy Products Intake Recommendations 

review. EPA analysis of these data has been peer 

day-to-day variability. Short term distributions 

No measurements were taken. The study relied 

for this Handbook. Therefore, it was the only 

agreement with earlier data. The approach used 

to analyze the data was adequate. However, due 
Table 12-1. Per Capita Intake of Total Grains Including Mixtures (g/kg-day as consumed)a 

Population Group Percent MEAN SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Consuming 

Total 97.5% 4.061 0.033 0 0.74 1.16 1.90 3.06 4.96 8.04 10.77 18.53 42.98 

Age (years) 

< 01 80.4% 7.049 0.361 0 0 0 1.46 6.05 10.18 16.75 19.50 27.61 37.41 

1-2 95.8% 10.567 0.285 0 2.86 4.34 6.55 9.59 14.06 18.92 21.57 28.22 42.98 

3-5 97.5% 9.492 0.201 0 3.13 4.35 6.09 8.91 11.88 15.13 19.14 23.87 33.08 

6-11 97.7% 6.422 0.117 0 2.14 2.88 4.07 5.70 7.82 10.26 12.85 21.40 31.93 

12-19 98.2% 3.764 0.065 0 1.15 1.52 2.16 3.31 4.81 6.46 8.03 10.92 19.30 

20-39 98.4% 3.095 0.035 0 0.70 1.08 1.75 2.73 4.00 5.47 6.55 9.57 25.71 

40-69 98.3% 2.792 0.031 0 0.69 0.98 1.59 2.47 3.54 4.96 6.09 8.40 20.34 

70 + 98.7% 3.263 0.066 0.38 0.89 1.24 1.86 2.72 4.04 5.81 7.63 10.47 21.45 

Season 

Fall 97.9% 4.282 0.066 0 0.84 1.24 2.07 3.19 5.19 8.54 11.88 19.10 37.77 

Spring 97.0% 3.983 0.071 0 0.70 1.10 1.79 2.95 4.73 7.78 10.52 23.87 31.93 

Summer 97.5% 3.948 0.062 0 0.74 1.13 1.82 2.99 4.96 7.98 10.16 15.34 30.13 

Winter 97.6% 4.031 0.063 0 0.70 1.17 1.95 3.17 4.99 8.00 10.48 16.86 42.98 

Urbanization 

Central City 97.6% 4.159 0.061 0 0.75 1.13 1.91 3.06 5.07 8.71 11.61 17.69 37.77 

Nonmetropolitan 96.9% 4.013 0.067 0 0.60 1.11 1.85 3.12 4.93 7.81 10.08 21.05 31.93 

Suburban 97.8% 4.02 0.049 0 0.80 1.18 1.90 3.04 4.91 7.79 10.63 18.53 42.98 

Race 

Asian 94.0% 6.479 0.402 0 0 1.46 3.02 5.44 9.07 14.13 14.63 20.65 23.78 

Black 96.9% 4.372 0.103 0 0.55 0.94 1.81 3.05 5.69 9.47 12.47 18.96 40.07 

Native American 87.7% 3.98 0.276 0 0 0.61 1.63 3.67 5.81 6.90 9.00 20.43 21.84 

Other/NA 97.1% 4.561 0.208 0 0 1.21 2.26 3.56 5.36 8.87 11.72 22.07 30.51 

White 97.9% 3.962 0.035 0 0.79 1.18 1.90 3.03 4.80 7.79 10.20 18.07 42.98 

Region 

Midwest 97.3% 4.016 0.07 0 0.79 1.17 1.90 2.92 4.69 7.80 11.04 20.36 31.93 

Northeast 97.6% 4.255 0.079 0 0.78 1.26 2.02 3.19 5.37 8.44 11.61 17.73 42.98 

South 97.9% 3.943 0.052 0 0.71 1.10 1.83 3.06 4.89 8.13 10.20 16.42 40.07 

West 97.2% 4.116 0.072 0 0.69 1.13 1.92 3.13 5.03 7.98 10.90 19.50 25.89 

Includes breads; sweets such as cakes, pie, and pastries; snack and breakfast foods made with grains; pasta; cooked ready-to-eat, and baby cereals, rice and grain a 

mixtures. 

Note: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA’s analysis of the 1989-91 CSFII. 
Table 12-2. Per Capita Intake of Breads (g/kg-day as consumed)a 

Population Group Percent MEAN SE P1 P5 P10 P25 P50 P75 

Consuming 

P90 P95 P99 P100 

Total 91.6% 1.133 0.010 0 0 0.19 0.48 0.90 1.50 2.31 3.04 4.67 12.99 

Age (years) 

< 01 50.9% 1.072 0.102 0 0 0 0 0.34 1.65 3.29 4.06 6.09 12.99 

1-2 88.9% 2.611 0.089 0 0 0.44 1.17 2.39 3.86 4.68 5.42 8.23 10.29 

3-5 91.9% 2.217 0.063 0 0 0.44 1.19 2.03 3.04 4.01 5.14 6.95 12.35 

6-11 93.4% 1.668 0.037 0 0 0.40 0.88 1.44 2.18 3.16 3.98 5.95 9.17 

12-19 91.8% 1.068 0.025 0 0 0.21 0.45 0.91 1.46 2.15 2.78 3.43 7.44 

20-39 92.9% 0.936 0.012 0 0 0.18 0.43 0.81 1.27 1.81 2.27 3.41 7.04 

40-69 93.7% 0.915 0.011 0 0 0.20 0.46 0.81 1.25 1.77 2.08 2.83 11.16 

70 + 95.1% 0.976 0.021 0 0.15 0.29 0.56 0.87 1.31 1.76 2.15 2.76 11.81 

Season 

Fall 91.3% 1.181 0.020 0 0 0.17 0.50 0.94 1.57 2.45 3.16 5.27 11.81 

Spring 91.4% 1.095 0.018 0 0 0.18 0.48 0.89 1.45 2.18 2.91 4.54 12.35 

Summer 92.4% 1.126 0.018 0 0 0.21 0.48 0.90 1.51 2.24 2.98 4.43 9.17 

Winter 91.2% 1.129 0.019 0 0 0.19 0.47 0.89 1.50 2.37 3.07 4.66 12.99 

Urbanization 

Central City 91.2% 1.127 0.017 0 0 0.18 0.49 0.91 1.50 2.33 2.98 4.50 11.81 

Nonmetropolitan 91.7% 1.184 0.020 0 0 0.18 0.48 0.93 1.54 2.51 3.24 4.97 12.99 

Suburban 91.8% 1.113 0.014 0 0 0.19 0.49 0.89 1.49 2.20 2.89 4.68 12.35 

Race 

Asian 78.5% 0.981 0.078 0 0 0 0.34 0.86 1.51 2.57 2.61 3.34 3.34 

Black 88.8% 1.159 0.030 0 0 0.11 0.37 0.84 1.55 2.59 3.29 5.58 8.94 

Native American 81.3% 1.336 0.133 0 0 0.13 0.41 0.72 1.80 2.91 4.13 9.09 11.71 

Other/NA 89.1% 1.333 0.067 0 0 0 0.62 1.11 1.70 2.66 3.79 6.16 9.98 

White 92.5% 1.121 0.010 0 0 0.20 0.51 0.91 1.48 2.23 2.95 4.51 12.99 

Region 

Midwest 91.2% 1.109 0.018 0 0 0.20 0.50 0.90 1.49 2.22 2.91 4.43 7.97 

Northeast 91.1% 1.104 0.021 0 0 0.18 0.51 0.90 1.48 2.26 2.83 4.50 9.98 

South 91.8% 1.155 0.017 0 0 0.18 0.46 0.92 1.54 2.41 3.13 4.89 12.99 

West 92.1% 1.153 0.022 0 0 0.19 0.49 0.91 1.48 2.35 3.12 5.14 12.35 

Includes breads, rolls, muffins, bagels, biscuits, cornbread, and tortillas. a 

Note: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA’s analysis of the 1989-91 CSFII. 
Table 12-3. Per Capita Intake of Sweets (g/kg-day as consumed) a 

Populatio n Percent MEAN SE P1 P5 P10 P25 P50 P75 

Group Consuming 

P90 P95 P99 P100 

Total 50.2% 0.508 0.011 0 0 0 0 0.13 0.71 1.50 2.12 3.96 13.39 

Age (years) 

< 01 28.1% 0.447 0.096 0 0 0 0 0 0.41 1.42 2.26 5.51 9.35 

1-2 49.6% 1.144 0.111 0 0 0 0 0.43 1.75 3.32 4.87 6.51 13.39 

3-5 59.2% 1.139 0.079 0 0 0 0 0.56 1.82 3.01 4.33 6.78 9.25 

6-11 63.7% 0.881 0.046 0 0 0 0 0.43 1.29 2.33 3.28 5.39 12.97 

12-19 54.0% 0.511 0.030 0 0 0 0 0.22 0.75 1.47 1.99 3.25 9.65 

20-39 45.0% 0.383 0.015 0 0 0 0 0 0.59 1.24 1.66 2.48 7.45 

40-69 49.1% 0.381 0.015 0 0 0 0 0.08 0.55 1.13 1.58 2.70 5.70 

70 + 56.3% 0.444 0.029 0 0 0 0 0.16 0.63 1.29 1.64 2.73 6.94 

Season 

Fall 52.9% 0.533 0.022 0 0 0 0 0.14 0.76 1.55 2.21 3.82 13.39 

Spring 48.3% 0.466 0.021 0 0 0 0 0.10 0.65 1.36 1.82 3.58 9.35 

Summer 48.5% 0.527 0.025 0 0 0 0 0.06 0.70 2.35 4.54 8.73 

Winter 51.2% 0.508 0.022 0 0 0 0 0.19 0.71 1.50 2.00 4.00 10.84 

Urbanization 

Central City 45.3% 0.495 0.021 0 0 0 0 0.11 0.65 1.55 2.12 4.24 9.94 

Nonmetropolitan 52.3% 0.593 0.025 0 0 0 0 0.25 0.82 1.58 2.34 4.52 13.39 

Suburban 52.4% 0.477 0.015 0 0 0 0 0.10 0.69 1.42 2.00 3.55 9.65 

Race 

Asian 37.6% 0.515 0.101 0 0 0 0 0.05 0.78 1.82 2.22 2.52 4.06 

Black 39.3% 0.387 0.030 0 0 0 0 0 0.46 1.20 1.71 3.51 9.67 

Native American 33.9% 0.325 0.075 0 0 0 0 0 0.33 1.47 1.48 2.44 3.78 

Other/NA 32.3% 0.283 0.088 0 0 0 0 0 0.21 0.64 1.45 3.04 9.94 

White 53.2% 0.537 0.012 0 0 0 0 0.17 0.77 1.55 2.17 4.09 13.39 

Region 

Midwest 53.0% 0.573 0.024 0 0 0 0 0.17 0.79 1.65 2.41 4.00 12.97 

Northeast 55.9% 0.587 0.027 0 0 0 0 0.22 0.83 1.63 2.21 4.60 13.39 

South 47.5% 0.471 0.018 0 0 0 0 0.09 0.65 1.39 1.98 3.89 10.84 

West 46.7% 0.416 0.022 0 0 0 0 0 0.55 1.25 1.91 3.33 9.65 

Includes cakes, cookies, pies, pastries, doughnuts, breakfast bars, and coffee cakes. a 

NOTE: SE = Standard error

 P = Percentile of the distribution 

Source: Based on EPA's analysis of the 1989-91 CSFII. 
Table 12-4. Per Capita Intake of Snacks Containing Grain (g/kg-day as consumed) a 

Population Group Percent MEAN SE P1 P5 P10 P25 P50 P75 P90 

Consuming 

P95 P99 P100 

Total 40.3% 0.160 0.005 0 0 0 0 0 0.18 0.47 0.78 1.74 6.73 

Age (years) 

< 01 31.4% 0.321 0.064 0 0 0 0 0 0.35 1.24 1.82 4.66 5.73 

1-2 46.7% 0.398 0.040 0 0 0 0 0.10 0.65 1.30 1.61 2.03 6.73 

3-5 48.9% 0.393 0.034 0 0 0 0 0.12 0.58 1.22 1.65 2.20 4.76 

6-11 43.1% 0.269 0.023 0 0 0 0 0 0.32 0.86 1.24 2.43 4.00 

12-19 40.2% 0.170 0.016 0 0 0 0 0 0.21 0.50 0.74 1.94 3.51 

20-39 38.2% 0.123 0.007 0 0 0 0 0 0.15 0.41 0.60 1.21 4.60 

40-69 40.3% 0.104 0.006 0 0 0 0 0 0.14 0.33 0.46 1.06 2.85 

70 + 40.9% 0.074 0.007 0 0 0 0 0 0.10 0.20 0.36 0.70 1.47 

Season 

Fall 41.6% 0.180 0.012 0 0 0 0 0 0.18 0.50 0.87 1.99 6.73 

Spring 38.3% 0.136 0.009 0 0 0 0 0 0.15 0.43 0.67 1.29 3.43 

Summer 37.5% 0.165 0.010 0 0 0 0 0 0.18 0.52 0.86 1.72 5.73 

Winter 43.9% 0.160 0.010 0 0 0 0 0 0.19 0.44 0.76 1.77 4.60 

Urbanization 

Central City 36.5% 0.158 0.010 0 0 0 0 0 0.16 0.46 0.81 1.81 3.70 

Nonmetropolitan 39.8% 0.144 0.009 0 0 0 0 0 0.17 0.44 0.66 1.32 4.76 

Suburban 43.3% 0.169 0.008 0 0 0 0 0 0.18 0.50 0.80 1.75 6.73 

Race 

Asian 22.1% 0.077 0.035 0 0 0 0 0 0.04 0.27 0.37 1.09 1.34 

Black 25.9% 0.107 0.014 0 0 0 0 0 0.07 0.33 0.59 1.19 4.76 

Native American 30.4% 0.142 0.050 0 0 0 0 0 0.16 0.32 0.44 1.29 4.60 

Other/NA 28.3% 0.139 0.026 0 0 0 0 0 0.17 0.43 0.69 1.27 1.91 

White 43.7% 0.170 0.006 0 0 0 0 0 0.19 0.49 0.81 1.80 6.73 

Region 

Midwest 45.2% 0.202 0.012 0 0 0 0 0 0.23 0.57 0.99 1.95 6.73 

Northeast 35.8% 0.113 0.010 0 0 0 0 0 0.10 0.35 0.61 1.28 5.73 

South 39.8% 0.162 0.008 0 0 0 0 0 0.19 0.46 0.80 1.63 4.76 

West 39.4% 0.155 0.011 0 0 0 0 0 0.16 0.46 0.76 1.81 4.60 

Includes grain snacks such as crackers, salty snacks, popcorn, and pretzels. a 

NOTE: SE = Standard error

 P = Percentile of the distribution 

Source: Based on EPA's analysis of the 1989-91 CSFII. 
Table 12-5. Per Capita Intake of Breakfast Foods (g/kg-day as consumed) a 

Population Group Percent MEAN SE P1 P5 P10 P25 P50 P75 

Consuming 

P90 P95 P99 P100 

Total 15.0% 0.144 0.012 0 0 0 0 0 0 0.46 0.95 2.46 13.61 

Age (years) 

< 01 13.2% 0.255 0.108 0 0 0 0 0 0 0.57 2.08 3.82 5.72 

1-2 20.9% 0.418 0.103 0 0 0 0 0 0.37 1.54 2.50 4.62 9.92 

3-5 24.5% 0.446 0.078 0 0 0 0 0 0.56 1.63 2.33 3.92 11.90 

6-11 25.0% 0.307 0.045 0 0 0 0 0 0.31 1.12 1.69 2.82 13.61 

12-19 18.4% 0.193 0.038 0 0 0 0 0 0 0.65 1.16 3.06 5.38 

20-39 13.2% 0.086 0.014 0 0 0 0 0 0 0.31 0.61 1.53 4.41 

40-69 10.8% 0.063 0.011 0 0 0 0 0 0 0.23 0.51 0.95 2.98 

70 + 12.5% 0.096 0.025 0 0 0 0 0 0 0.41 0.65 1.37 3.09 

Season 

Fall 15.1% 0.146 0.021 0 0 0 0 0 0 0.49 0.93 2.61 6.83 

Spring 13.2% 0.120 0.023 0 0 0 0 0 0 0.34 0.71 2.32 6.23 

Summer 14.8% 0.145 0.022 0 0 0 0 0 0 0.53 0.98 2.02 7.41 

Winter 17.0% 0.168 0.027 0 0 0 0 0 0 0.55 1.04 2.94 13.61 

Urbanization 

Central City 15.1% 0.142 0.021 0 0 0 0 0 0 0.42 0.93 2.61 7.17 

Nonmetropolitan 13.3% 0.120 0.020 0 0 0 0 0 0 0.39 0.85 1.97 7.41 

Suburban 15.9% 0.157 0.019 0 0 0 0 0 0 0.52 1.06 2.45 13.61 

Race 

Asian 10.1% 0.076 0.060 0 0 0 0 0 0 0.24 0.61 1.04 1.46 

Black 11.9% 0.114 0.032 0 0 0 0 0 0 0.20 0.78 2.46 7.41 

Native American 18.7% 0.156 0.073 0 0 0 0 0 0.21 0.53 0.61 1.23 6.83 

Other/NA 13.7% 0.079 0.037 0 0 0 0 0 0 0.40 0.43 1.40 2.33 

White 15.6% 0.152 0.013 0 0 0 0 0 0 0.51 0.97 2.56 13.61 

Region 

Midwest 14.7% 0.121 0.020 0 0 0 0 0 0 0.38 0.75 2.06 7.41 

Northeast 15.2% 0.158 0.034 0 0 0 0 0 0 0.43 1.02 2.61 13.61 

South 12.3% 0.130 0.019 0 0 0 0 0 0 0.42 0.92 2.33 4.59 

West 19.7% 0.184 0.024 0 0 0 0 0 0 0.67 1.14 2.58 6.96 

Includes breakfast foods made with grains such as pancakes, waffles, and french toast. a 

NOTE: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA's analysis of the 1989-91. 
Table 12-6. Per Capita Intake of Pasta (g/kg-day as consumed) 

Populatio n Percent MEAN SE P1 P5 P10 P25 P50 P75 

Group Consuming 

P90 P95 P99 P100 

Total 13.6% 0.233 0.018 0 0 0 0 0 0 0.90 1.60 3.67 24.01 

Age (years) 

< 01 7.3% 0.172 0.124 0 0 0 0 0 0 0.00 1.18 3.79 6.43 

1-2 14.0% 0.569 0.212 0 0 0 0 0 0 1.72 5.14 6.68 24.01 

3-5 15.3% 0.543 0.142 0 0 0 0 0 0 2.19 3.37 6.51 7.72 

6-11 15.9% 0.338 0.063 0 0 0 0 0 0 1.47 2.35 3.43 7.72 

12-19 14.3% 0.194 0.047 0 0 0 0 0 0 0.77 1.47 3.36 7.24 

20-39 15.2% 0.232 0.027 0 0 0 0 0 0 0.96 1.57 2.83 7.17 

40-69 12.5% 0.172 0.028 0 0 0 0 0 0 0.62 1.32 2.67 10.20 

70 + 9.9% 0.083 0.029 0 0 0 0 0 0 0.03 0.76 1.57 2.62 

Season 

Fall 14.0% 0.239 0.038 0 0 0 0 0 0 0.94 1.72 3.77 24.01 

Spring 13.9% 0.250 0.036 0 0 0 0 0 0 0.96 1.65 3.28 9.47 

Summer 13.6% 0.251 0.039 0 0 0 0 0 0 0.97 1.72 3.80 11.12 

Winter 12.9% 0.193 0.034 0 0 0 0 0 0 0.68 1.33 3.22 8.73 

Urbanization 

Central City 12.9% 0.197 0.034 0 0 0 0 0 0 0.65 1.34 3.43 24.01 

Nonmetropolitan 11.4% 0.171 0.032 0 0 0 0 0 0 0.63 1.33 2.48 11.12 

Suburban 15.4% 0.286 0.028 0 0 0 0 0 0 1.12 1.96 3.92 10.20 

Race 

Asian 18.8% 0.918 0.355 0 0 0 0 0 0.70 3.80 5.78 6.51 10.20 

Black 6.6% 0.138 0.054 0 0 0 0 0 0 0.00 1.08 3.27 5.14 

Other/NA 8.6% 0.115 0.083 0 0 0 0 0 0 0.00 1.16 2.43 3.86 

White 15.1% 0.243 0.019 0 0 0 0 0 0 0.94 1.65 3.46 24.01 

Region 

Midwest 12.8% 0.182 0.030 0 0 0 0 0 0 0.74 1.24 2.76 9.46 

Northeast 21.9% 0.367 0.043 0 0 0 0 0 0 1.47 2.14 4.62 24.01 

South 9.2% 0.179 0.035 0 0 0 0 0 0 0.45 1.32 3.63 11.12 

West 14.7% 0.252 0.038 0 0 0 0 0 0 1.07 1.63 3.25 10.20 

NOTE: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA's analysis of the 1989-91 CSFII. 
Table 12-7. Per Capita Intake of Cooked Cereals (g/kg-day as consumed) 

Population Percent MEAN SE P1 P5 P10 P25 P50 P75 

Group Consuming 

P90 P95 P99 P100 

Total 17.1% 0.441 0.035 0 0 0 0 0 0 1.37 2.79 8.18 28.63 

Age (years) 

< 01 17.9% 1.350 0.417 0 0 0 0 0 0 7.17 8.60 20.47 24.16 

1-2 23.6% 1.783 0.365 0 0 0 0 0 1.39 7.00 9.41 14.84 28.63 

3-5 21.2% 1.335 0.258 0 0 0 0 0 0 4.99 8.18 12.51 18.66 

6-11 18.1% 0.669 0.142 0 0 0 0 0 0 2.32 4.49 10.76 16.42 

12-19 11.0% 0.156 0.065 0 0 0 0 0 0 0 1.26 3.34 11.85 

20-39 10.5% 0.166 0.040 0 0 0 0 0 0 0 1.33 3.33 13.18 

40-69 18.3% 0.307 0.036 0 0 0 0 0 0 1.30 2.20 3.97 18.23 

70 + 35.3% 0.782 0.079 0 0 0 0 0 1.08 2.71 3.80 7.37 10.03 

Season 

Fall 21.2% 0.573 0.066 0 0 0 0 0 0 1.90 3.71 9.15 28.63 

Spring 15.8% 0.439 0.082 0 0 0 0 0 0 1.07 2.29 12.28 21.84 

Summer 12.1% 0.288 0.069 0 0 0 0 0 0 0.55 1.98 5.37 24.16 

Winter 19.1% 0.463 0.062 0 0 0 0 0 0 1.57 3.12 7.00 24.34 

Urbanization 

Central City 19.3% 0.523 0.068 0 0 0 0 0 0 1.52 3.27 10.03 28.63 

Nonmetropolitan 20.0% 0.483 0.066 0 0 0 0 0 0 1.52 2.72 7.41 20.94 

Suburban 13.9% 0.369 0.052 0 0 0 0 0 0 1.09 2.35 7.37 24.34 

Race 

Black 30.3% 0.838 0.092 0 0 0 0 0 0.65 2.95 4.45 10.03 28.63 

Native American 17.5% 0.372 0.196 0 0 0 0 0 0 2.15 2.99 4.80 5.73 

Other/NA 12.6% 0.510 0.293 0 0 0 0 0 0 1.12 3.18 7.60 20.94 

White 15.1% 0.382 0.039 0 0 0 0 0 0 1.11 2.32 7.38 24.34 

Region 

Midwest 15.5% 0.507 0.083 0 0 0 0 0 0 1.39 3.01 10.32 21.85 

Northeast 13.2% 0.395 0.093 0 0 0 0 0 0 1.00 2.73 7.02 24.34 

South 21.4% 0.396 0.044 0 0 0 0 0 0 1.40 2.48 5.53 28.63 

West 15.2% 0.483 0.086 0 0 0 0 0 0 1.45 3.12 9.41 16.47 

NOTE: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA's analysis of the 1989-91 CSFII. 
Table 12-8. Per Capita Intake of Rice (g/kg-day as consumed) 

Population Percent MEAN SE P1 P5 P10 P25 P50 P75 

Group Consuming 

P90 P95 P99 P100 

Total 20.0% 0.357 0.022 0 0 0 0 0 0 1.26 2.15 4.85 17.59 

Age (years) 

< 01 11.8% 0.405 0.209 0 0 0 0 0 0 1.40 2.89 7.87 15.54 

1-2 24.4% 0.811 0.192 0 0 0 0 0 0.36 3.36 4.52 9.81 17.59 

3-5 25.0% 0.736 0.127 0 0 0 0 0 0.76 2.83 3.77 6.70 14.35 

6-11 20.8% 0.504 0.090 0 0 0 0 0 0 1.71 3.33 7.86 13.39 

12-19 20.1% 0.316 0.052 0 0 0 0 0 0 1.26 1.91 3.74 9.60 

20-39 21.3% 0.341 0.037 0 0 0 0 0 0 1.20 1.90 5.02 12.69 

40-69 19.6% 0.259 0.028 0 0 0 0 0 0 0.94 1.64 3.35 12.00 

70 + 14.9% 0.229 0.050 0 0 0 0 0 0 0.81 1.73 3.12 7.97 

Season 

Fall 18.8% 0.307 0.041 0 0 0 0 0 0 0.94 2.13 4.92 16.74 

Spring 21.5% 0.395 0.046 0 0 0 0 0 0 1.34 2.47 5.05 15.54 

Summer 19.3% 0.376 0.045 0 0 0 0 0 0 1.31 2.05 5.02 12.55 

Winter 20.5% 0.350 0.041 0 0 0 0 0 0 1.37 2.09 4.17 17.59 

Urbanization 

Central City 26.1% 0.449 0.039 0 0 0 0 0 0.18 1.51 2.51 5.54 16.74 

Nonmetropolitan 15.9% 0.311 0.046 0 0 0 0 0 0 1.04 1.90 5.02 12.91 

Suburban 18.3% 0.320 0.031 0 0 0 0 0 0 1.16 2.01 4.30 17.59 

Race 

Asian 72.5% 2.353 0.316 0 0 0 0 1.32 2.83 6.20 10.39 15.06 17.59 

Black 37.2% 0.603 0.048 0 0 0 0 0 0.87 2.08 2.93 5.16 12.91 

Other/NA 37.7% 0.655 0.116 0 0 0 0 0 0.80 2.15 3.78 6.06 10.71 

White 15.9% 0.281 0.023 0 0 0 0 0 0 0.94 1.79 4.30 15.54 

Region 

Midwest 12.3% 0.207 0.046 0 0 0 0 0 0 0.62 1.25 3.59 13.39 

Northeast 20.3% 0.378 0.050 0 0 0 0 0 0 1.45 2.15 4.65 16.74 

South 25.2% 0.455 0.036 0 0 0 0 0 0 1.62 2.71 5.21 15.54 

West 20.4% 0.349 0.045 0 0 0 0 0 0 1.25 1.84 4.52 17.59 

NOTE: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA's analysis of the 1989-91 CSFII. 
Table 12-9. Per Capita Intake of Ready-to-Eat Cereals (g/kg-day as consumed)a 

Population Group Percent MEAN SE P1 P5 P10 P25 P50 P75 P90 

Consuming 

P95 P99 P100 

Total 45.6% 0.306 0.007 0 0 0 0 0 0.42 0.92 1.37 2.61 7.12 

Age (years) 

< 01 38.9% 0.431 0.059 0 0 0 0 0 0.64 1.55 1.94 3.40 4.40 

1-2 70.7% 0.954 0.057 0 0 0 0 0.74 1.46 2.28 2.89 4.77 6.47 

3-5 77.3% 1.026 0.044 0 0 0 0.31 0.83 1.48 2.35 2.99 3.67 5.65 

6-11 69.0% 0.631 0.025 0 0 0 0 0.45 0.92 1.55 1.97 3.12 7.12 

12-19 50.8% 0.317 0.019 0 0 0 0 0.16 0.48 0.90 1.14 2.61 4.06 

20-39 34.3% 0.174 0.010 0 0 0 0 0 0.23 0.61 0.88 1.51 5.11 

40-69 37.1% 0.166 0.008 0 0 0 0 0 0.25 0.55 0.74 1.32 3.36 

70 + 52.4% 0.222 0.013 0 0 0 0 0.08 0.36 0.64 0.83 1.55 2.71 

Season 

Fall 45.2% 0.293 0.014 0 0 0 0 0 0.40 0.94 1.42 2.38 7.12 

Spring 45.6% 0.320 0.015 0 0 0 0 0 0.44 0.95 1.42 2.69 5.88 

Summer 46.6% 0.330 0.016 0 0 0 0 0 0.45 0.99 1.42 2.82 5.65 

Winter 44.8% 0.280 0.014 0 0 0 0 0 0.39 0.81 1.22 2.61 6.47 

Urbanization 

Central City 46.6% 0.319 0.014 0 0 0 0 0 0.43 0.94 1.42 2.86 5.11 

Nonmetropolitan 43.6% 0.283 0.014 0 0 0 0 0 0.38 0.85 1.33 2.52 7.12 

Suburban 46.0% 0.307 0.011 0 0 0 0 0 0.44 0.93 1.36 2.46 6.47 

Race 

Asian 33.6% 0.218 0.065 0 0 0 0 0 0.24 0.81 1.28 2.79 3.12 

Black 41.1% 0.269 0.018 0 0 0 0 0 0.40 0.82 1.16 2.50 4.46 

Native American 38.6% 0.298 0.078 0 0 0 0 0 0.32 0.76 1.23 3.26 4.40 

Other/NA 42.9% 0.340 0.050 0 0 0 0 0 0.43 1.12 1.59 2.69 4.18 

White 46.7% 0.311 0.008 0 0 0 0 0 0.42 0.94 1.39 2.61 7.12 

Region 

Midwest 48.7% 0.328 0.015 0 0 0 0 0 0.47 0.98 1.37 2.55 7.12 

Northeast 46.9% 0.286 0.017 0 0 0 0 0 0.38 0.89 1.33 2.70 6.47 

South 41.4% 0.284 0.012 0 0 0 0 0 0.40 0.81 1.26 2.34 5.88 

West 47.7% 0.336 0.016 0 0 0 0 0 0.46 1.05 1.47 2.84 5.11

a Incluldes dry ready-to-eat corn, rice, wheat, and bran cereals in the form of flakes, puffs, etc. 

NOTE: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA’s analysis of the 1989-91 CSFII. 
Table 12-10. Per Capita Intake of Baby Cereals (g/kg-day as consumed) 

Population Group Percent MEAN SE P1 P5 P10 P25 P50 P75 P90 P95 P99 

Consuming 

P100 

Total 1.1% 0.037 0.051 0 0 0 0 0 0 0 0 0 22.57 

Age (years)a 

< 01 28.5% 1.205 0.280 0 0 0 0 0 0.64 4.59 6.94 16.99 22.57 

Season 

Fall 1.1% 0.036 0.075 0 0 0 0 0 0 0 0 0.69 14.94 

Spring 1.1% 0.059 0.138 0 0 0 0 0 0 0 0 0.13 16.99 

Summer 1.0% 0.017 0.068 0 0 0 0 0 0 0 0 0 12.03 

Winter 1.0% 0.035 0.107 0 0 0 0 0 0 0 0 0 22.57 

Urbanization 

Central City 1.3% 0.048 0.088 0 0 0 0 0 0 0 0 1.05 22.57 

Nonmetropolitan 0.9% 0.011 0.040 0 0 0 0 0 0 0 0 0 9.41 

Suburban 1.0% 0.042 0.093 0 0 0 0 0 0 0 0 0 16.99 

Race 

Asian 0.7% 0.017 0.137 0 0 0 0 0 0 0 0 1.10 1.10 

Black 2.1% 0.092 0.151 0 0 0 0 0 0 0 0 4.59 22.57 

Native American 1.2% 0.010 0.088 0 0 0 0 0 0 0 0 0 1.63 

Other/NA 3.1% 0.050 0.133 0 0 0 0 0 0 0 0 2.94 13.42 

White 0.8% 0.029 0.059 0 0 0 0 0 0 0 0 0 16.99 

Region 

Midwest 1.1% 0.020 0.050 0 0 0 0 0 0 0 0 0 12.50 

Northeast 1.0% 0.084 0.208 0 0 0 0 0 0 0 0 1.25 16.99 

South 1.0% 0.016 0.060 0 0 0 0 0 0 0 0 0 22.57 

West 1.1% 0.046 0.101 0 0 0 0 0 0 0 0 1.18 10.18

 Data presented only for children less than 1 year of age. Available data for other age groups was based on a very small number of observations a 

NOTE: SE = Standard error 

P = Percentile of the distribution 

Source: Based on EPA's analysis of the 1989-91 CSFII. 
Table 12-11. Mean Daily Intakes of Grains Per Individual in a Day for 

USDA 1977-78, 87-88, 89-91, 94, and 95 Surveys 

77-78 Data 87-88 Data 89-91 Data 94 Data 95 Data 

Food Product (g/day) (g/day) (g/day) (g/day) (g/day) 

Grains 215 237 273 300 303 

Grains 52 72 89 112 107 

Mixtures 

Source: USDA, 1980; 1992; 1996a; 1996b. 
Table 12-12. Mean Per Capita Intake Rates for Grains Based on All Sex/Age/Demographic Subgroups 

Raw Agricultural Commodity (Grams/kg Body Weight-Day) Standard Error a 

Average Consumption 

Oats 0.0825748 0.0026061 

Rice-rough 0.0030600 0.0004343 

Rice-milled 0.1552627 0.0083546 

Rye-rough 0.0000010 --

Rye-germ 0.0002735 0.0000483 

Rye-flour 0.0040285 0.0002922 

Wheat-rough 0.1406118 0.0050410 

Wheat-germ 0.0008051 0.0000789 

Wheat-bran 0.0121575 0.0004864 

Wheat-flour 1.2572489 0.0127412 

Millet 0.0000216 0.0000104

 Consumed in any raw or prepared form. a 

Source: DRES data base (based on 1977-78 NFCS). 
Table 12-13. Mean Grain Intake Per Individual in a Day by Sex and Age (g/day as consumed) for 1977-1978 a 

Group Age (years) Total Grains Biscuits Goods Cereals, Pasta Mainly Grain 

Breads, Rolls, Other Baked Mixtures, b 

Males and Females 

Under 1 42 4 5 30 3 

1-2 158 27 24 44 63 

3-5 181 46 37 54 45 

6-8 206 53 56 60 38 

Males 

9-11 238 67 56 51 64 

12-14 288 76 80 57 74 

15-18 303 91 77 53 82 

19-22 253 84 53 64 52 

23-34 256 82 60 40 74 

35-50 234 82 58 44 50 

51-64 229 78 57 48 46 

65-74 235 71 60 69 35 

75 and Over 196 70 50 58 19 

Females 

9-11 214 58 59 44 53 

12-14 235 57 61 45 72 

15-18 196 57 43 41 55 

19-22 161 44 36 33 48 

23-34 163 49 38 32 44 

35-50 161 49 37 32 43 

51-64 155 52 40 36 27 

65-74 175 57 42 47 29 

75 and Over 178 54 44 58 22 

Males and Females 

All Ages 204 62 49 44 49

 Based on USDA Nationwide Food Consumption Survey 1977-78 data for one day. a

 Includes mixtures containing grain as the main ingredient. b 

Source: USDA, 1980. 
Table 12-14. Mean Grain Intakes Per Individual in a Day by Sex and Age (g/day as consumed) for 1987-1988 a 

Quick 

Breads, Cakes, Crackers, 

Yeast Pancakes, Cookies, Popcorn, Mixtures 

Group Total Breads French Pastries, Pretzels, Cereals 

Age (years) Grains and Rolls Toast Pies Corn Chips and Pastas 

, Mostly 

Grainb 

Males and Females 5 and Under 167 30 8 22 4 52 51 

Males 74 83 

6-11 268 51 16 37 8 72 82 

12-19 304 65 28 45 10 58 83 

20 and Over 272 65 20 37 8 

Females 

6-11 231 43 19 30 6 66 68 

12-19 239 45 13 29 7 52 91 

20 and Over 208 45 14 28 6 53 62 

All Individuals 237 52 16 32 7 57 72 

Based on USDA Nationwide Food Consumption Survey 1987-88 data for one day. a 

Includes mixtures containing grain as the main ingredient. b 

Source: USDA, 1992. 
Table 12-15. Mean Grain Intakes Per Individual in a Day by Sex and Age (g/day as consumed) for 1994 and 1995 a 

Crackers, 

Quick Breads, Cakes, Cookies, Popcorn, 

Group Yeast Breads Pancakes, Pastries, Pies Pretzels, Corn Cereals and Mixtures, Mostly 

Age (years) Total Grains and Rolls French Toast Chips Pastas Grainb 

1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 

Males and Females 

5 and Under 213 210 26 28 11 11 22 23 8 7 58 57 89 84 

Males 

6-11 285 341 51 45 15 21 42 46 12 18 66 97 101 115 

12-19 417 364 53 54 30 21 54 43 17 22 82 84 180 138 

20 and Over 357 365 64 61 22 24 43 46 13 15 86 91 128 128 

Females 

6-11 260 286 43 46 16 21 37 51 11 14 57 54 94 100 

12-19 317 296 40 37 16 14 39 35 17 16 63 52 142 143 

20 and Over 254 257 44 45 16 15 33 34 9 10 59 69 92 83 

All Individuals 300 303 50 49 18 19 38 39 12 13 70 76 112 107 

Based on USDA CSFII 1994 and 1995 data for one day. a 

Includes mixtures containing grain as the main ingredient. b 

Source: USDA, 1996a; 1996b. 
Table 12-16. Mean and Standard Error for the Daily Per Capita Intake of Grains, by Age (g/day as consumed) 

Age (years) Breads Cereals Other Grains 

All ages 147.3+1.4 29.9+1.3 22.9+1.7 

Under 1 16.2+9.2 37.9+8.2 1.8+10.9 

1 to 4 104.6+4.5 38.4+4.0 14.8+5.4 

5 to 9 154.3+3.8 39.5+3.4 22.7+4.5 

10 to 14 186.2+3.6 36.4+3.2 25.6+4.2 

15 to 19 188.5+3.7 28.8+3.3 27.8+4.4 

20 to 24 166.5+4.9 20.2+4.3 25.0+5.8 

25 to 29 170.0+5.0 18.2+4.4 26.6+5.9 

30 to 39 156.8+3.9 18.8+3.5 26.4+4.6 

40 to 59 144.4+3.1 24.7+2.7 23.3+3.6 

60 and over 122.1+3.4 42.5+3.0 19.3+4.0 

Source: U.S. EPA, 1984a (based on 1977-78 NFCS). 
Table 12-17. Mean and Standard Error for the Daily Intake of Grains, by Region (g/day as consumed) 

Region Total Grains Breads Cereals Other 

Grains 

All Regions 200.0+3.0 147.3+1.4 29.9+1.3 22.9+1.7 

Northeast 203.5+5.8 153.1+2.8 24.6+2.5 25.9+3.3 

North Central 192.8+5.6 150.9+2.7 28.7+2.4 13.3+3.2 

South 202.2+4.7 143.9+2.3 34.6+2.0 23.7+2.7 

West 202.6+6.9 139.5+3.3 30.9+3.0 32.1+4.0 

NOTE: Northeast = Maine, New Hampshire, Vermont, Massachusetts, Connecticut, Rhode Island, New York, New Jersey, and 

Pennsylvania. 

North Central = Ohio, Illinois, Indiana, Wisconsin, Michigan, Minnesota, Iowa, Missouri, North Dakota, South Dakota, 

Nebraska, and Kansas. 

South = Maryland, Delaware, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, 

Florida, Kentucky, Tennessee, Alabama, Mississippi, Arkansas, Louisiana, Texas, and Oklahoma. 

West = Montana, Idaho, Wyoming, Utah, Colorado, New Mexico, Arizona, Nevada, Washington, Oregon, and California. 

Source: U.S. EPA, 1984b (based on 1977-78 NFCS). 
Table 12-18. Consumption of Grains (g dry weight/day) for Different Age Groups and 

Estimated Lifetime Average Daily Food Intakes for a U.S. Citizen 

(averaged across sex) Calculated from the FDA Diet Data 

Age (years) Estimated lifetime a 

(0-1) (1-5) (6-13) (14-19) (20-44) (45-70) 

Wheat 27.60 42.23 60.80 79.36 65.86 55.13 60.30 

Corn 4.00 15.35 19.28 23.21 12.83 14.82 12.01 

Rice 2.22 4.58 5.24 5.89 5.78 4.21 5.03 

Oats 3.73 2.65 2.27 1.89 1.32 2.00 1.85 

Other Grain 0.01 0.08 0.41 0.73 13.45 4.41 6.49 

Total Grain 37.56 64.82 87.58 110.34 90.59 76.12 84.19

a The estimated lifetime dietary intakes were estimated by: 

Estimated lifetime = IR(0-1) + 5yrs * IR (1-5) + 8 yrs * IR (6-13) + 6 yrs * IR (14-19) + 25 yrs * IR (20-44) + 25 yrs * IR (45-70) 

70 years 

where IR = the intake rate for a specific age group. 

Source: U.S. EPA, 1989 (based on 1977-78 NFCS and NHANES II data). 
Table 12-19. Per Capita Consumption of Flour and Cereal Products in 1991a 

Food Item (g/day) 

Per Capita Consumption a 

Total Wheat Flour 169.8 b 

Rye Flour 0.7 

Rice 20.9 c 

Total Corn Products 27.2 d 

Oat Products 10.7 e 

Barley Products 1.1 f 

Total Flour and Cereal Products 230.6 g 

Original data were presented in lbs/yr; data were converted to g/day by multiplying by a factor of 454 g/lb and dividing by 365 a 

days/yr. Consumption of most items at the processing level. Excludes quantities used in alcoholic beverages and fuel. 

Includes white, whole wheat, and durum flour. b 

Milled basis. c 

Includes corn flour and meal, hominy and grits, and corn starch. d 

Includes rolled oats, ready-to-eat cereals, oat flour, and oat bran. e 

Includes barley flour, pearl barley, and malt and malt extract used in food processing. f 

Excludes wheat not ground into flour, for example, shredded wheat breakfast cereals. g 

Source: USDA, 1993. 
Table 12-20. Quantity (as consumed) of Grain Products Consumed Per Eating Occasion 

and the Percentage of Individuals Using These Foods in Three Days 

Food category food in 3 (g) Quantity consumed per eating occasion at specified percentiles (g) 

% Indiv. Quantity consumed 

using per eating occasion Consumers-only 

days 

Average Standard 5 25 50 75 90 95 99 

Deviation 

Yeast Breads 93.7 46 26 21 25 44 50 75 100 140 

Pancakes 8.3 113 85 27 54 81 146 219 282 438 

Waffles 2.9 87 74 20 40 78 100 158 200 400 

Tortillas 2.9 69 39 28 30 60 90 120 140 210 

Cakes and Cupcakes 25.5 79 59 23 41 63 99 144 184 284 

Cookies 30.8 32 30 7 14 26 40 60 84 144 

Pies 11.9 129 60 57 97 120 150 195 236 360 

Doughnuts 9.9 64 40 26 42 43 84 106 126 208 

Crackers 26.2 22 21 6 12 15 24 42 57 113 

Popcorn 5.6 19 22 5 9 15 18 36 45 108 

Pretzels 2.2 29 28 3 12 21 36 57 85 160 

Corn-based Salty Snacks 5.9 33 30 9 18 21 40 60 80 156 

Pasta 11.4 153 108 35 70 140 210 280 320 560 

Rice 18.5 147 91 41 88 165 125 263 350 438 

Cooked Cereals 12.4 203 110 31 123 240 245 360 480 490 

Ready-to-Eat Cereals 43.4 36 25 8 22 29 45 60 84 120 

Source: Pao et al., 1982 (based on 1977-78 NFCS). 
Table 12-21. Mean Moisture Content of Selected Grains Expressed as Percentages of Edible Portions 

Food Comments 

Moisture Content (Percent) 

Raw Cooked 

Barley - pearled 10.09 68.80 

Corn - grain - endosperm 10.37 

Corn - grain - bran 3.71 crude 

Millet 8.67 71.41 

Oats 8.22 

Rice - rough - white 11.62 68.72 

Rye - rough 10.95 

Rye - flour - medium 9.85 

Sorghum (including milo) 9.20 

Wheat - rough - hard white 9.57 

Wheat - germ 11.12 crude 

Wheat - bran 9.89 crude 

Wheat - flour - whole grain 10.27 

Source: USDA, 1979-1986. 
Table 12-22. Summary of Grain Intake Studies 

Study Calculating Intake Types of Data Used Units 

Survey Population Used in 

Food Items 

KEY STUDIES 

EPA Analysis of 1989-91 

CSFII Data 

Per capita 1989-91 CSFII data; g/kg-day; as 

Based on 3-day average consumed 

individual intake rates. 

Distributions of intake rates for total 

grain; individual grain items 

RELEVANT STUDIES 

EPA's DRES 

(White et al., 1983) 

Per capita (i.e., consumers 1977-78 NFCS g/kg-day; as 

and nonconsumers) 3-day individual intake data consumed 

Intake for a wide variety of grain 

products presented; complex food 

groups were disaggregated 

Pao et al., 1982 Consumers only serving size 1977-78 NFCS g; as consumed 

data provided 3-day individual intake data 

Distributions of serving sizes for grain 

products 

USDA, 1980; 1992; 

1996a; 1996b 

Per capita and consumer 1977-78 and 1987-88 NFCS, g/day; as consumed 

only grouped by age and sex and 1994 and 1995 CSFII 

1-day individual intake data 

Total grains and various grain 

products 

USDA, 1993b Per capita consumption Based on food supply and g/day; as consumed 

based on "food utilization data 

Intake rates of grain products 

disappearance" 

U.S. EPA/ORP, 

1984a; 1984b 

Per capita 1977-78 NFCS g/day; as consumed 

Individual intake data 

Mean intake rates for total grain 

products, and individual grain items. 

U.S. EPA/OST, 1989 Estimated lifetime dietary Based on FDA Total Diet Study g/day; dry weight 

intake Food List which used 1977-78 

NFCS data, and NHANES II 

data 

Various food groups; complex foods 

disaggregated 
Table 12-23. Summary of Recommended Values for Per Capita Intake of Grain Products 

Mean 95th Percentile Multiple Percentiles Study 

Total Grain Intake 

4.1 g/kg-day 10.8 g/kg-day see Table 12-1 EPA Analysis of CSFII 1989-91 Data 

Individual Grain Products 

see Tables 12-2 to 12-10 see Tables 12-2 to 12-10 see Table 12-2 to 12-10 EPA Analysis of CSFII 1989-91 Data 
Table 12-24. Confidence in Grain Products Intake Recommendation 

Considerations Rationale Rating 

Study Elements

 • Level of peer review USDA CSFII survey receives high level of peer High 

review. EPA analysis of these data has been peer 

reviewed outside the Agency.

 • Accessibility CSFII data are publicly available. High

 • Reproducibility Enough information is included to reproduce results. High

 • Focus on factor of Analysis is specifically designed to address food High

 interest intake.

 • Data pertinent to U.S. Data focuses on the U.S. population. High

 • Primary data This is new analysis of primary data. High

 • Currency Were the most current data publicly available at the High 

time the analysis was conducted for this Handbook.

 • Adequacy of data Survey is designed to collect short-term data. Medium confidence for average values;

 collection period Low confidence for long term percentile 

distribution

 • Validity of approach Survey methodology was adequate. High

 • Study size Study size was very large and therefore adequate. High

 • Representativeness of the The population studied was the U.S. population. High

 population

 • Characterization of Survey was not designed to capture long term day-to- Medium

 variability day variability. Short term distributions are provided 

for various age groups, regions, etc.

 • Lack of bias in study design Response rate was adequate. Medium

 (high rating is desirable)

 • Measurement error No measurements were taken. The study relied on N/A 

survey data. 

Other Elements

 • Number of studies 1 Low

 CSFII was the most recent data set publicly available 

at the time the analysis was conducted for this 

Handbook. Therefore, it was the only study classified 

as key study.

 • Agreement between researchers Although the CSFII was the only study classified as High 

key study, the results are in good agreement with 

earlier data. 

Overall Rating The survey is representative of U.S. population. High confidence in the average; 

Although there was only one study considered key, Low confidence in the long-term upper 

these data are the most recent and are in agreement percentiles 

with earlier data. The approach used to analyze the 

data was adequate. However, due to the limitations 

of the survey design estimation of long-term 

percentile values (especially the upper percentiles) is 

uncertain. 
Table 12A-1. Food Codes and Definitions Used in the Analysis of the 1989-91 USDA CSFII Grains Data 

Food Product Food Codes and Descriptions Food Product Food Codes and Descriptions 

Total Grains 51­ breads Pasta 561­ macaroni 

52­ tortillas noodles 

53­ sweets spaghetti 

54­ snacks 

55­ breakfast foods 

561­ pasta 

562­ cooked cereals and rice 

57- ready-to-eat and baby cereals 

Also includes the average portion of grain 

mixtures (i.e., 31 percent) and the average 

portion of meat mixtures (i.e., 13 percent) 

made up by grain. 

Breads 51­ breads Cooked 56200­ includes grits,oatmeal, 

rolls Cereals 56201­ cornmeal mush, millet, 

muffins 56202­ etc. 

bagel 56203­

biscuits 562069­

corn bread 56207­

52­ tortillas 56208­

56209­

Sweets 53­ cakes Rice 56204­ includes all varieties of 

cookies 56205­ rice 

pies 5620601 

pastries 

doughnuts 

breakfast bars 

coffee cakes 

Snacks 54­ crackers Ready-to-eat 570­ includes all varieties of 

salty snacks Cereals 571- ready-to-eat cereals 

popcorn 572­

pretzels 573­

574­

575­

576­

Breakfast 55­ pancakes Baby Cereals 578­ baby cereals 

Foods waffles 

french toast 

Grain Mixtures 58­ grain mixtures Meat Mixtures 27­ meat mixtures 

28­
Table 13-1. 1986 Vegetable Gardening by Demographic Factors 

Demographic gardens (%) households (million) 

Factor 

Percentage of total 

households that have Number of 

Total 38 34 

Region/section

 East 33 7.3

 New England 37 1.9

 Mid-Atlantic 32 5.4

 Midwest 50 11.0

 East Central 50 6.6

 West Central 50 4.5

 South 33 9.0

 Deep South 44 3.1

 Rest of South 29 5.9

 West 37 6.2

 Rocky Mountain 53 2.3

 Pacific 32 4.2 

Size of community

 City 26 6.2

 Suburb 33 10.2

 Small town 32 3.4

 Rural 61 14.0 

Household size

 Single, separated, 54 8.5

 divorced, widowed

 Married, no children 45 11.9

 Married, with children 44 13.2 

Source: National Gardening Association, 1987. 
Table 13-2. Percentage of Gardening Households 

Growing Different Vegetables in 1986 

Vegetable Percent 

Artichokes 0.8 

Asparagus 8.2 

Beans 43.4 

Beets 20.6 

Broccoli 19.6 

Brussel sprouts 5.7 

Cabbage 29.6 

Carrots 34.9 

Cauliflower 14.0 

Celery 5.4 

Chard 3.5 

Corn 34.4 

Cucumbers 49.9 

Dried peas 2.5 

Dry beans 8.9 

Eggplant 13.0 

Herbs 9.8 

Kale 3.1 

Kohlrabi 3.0 

Leeks 1.2 

Lettuce 41.7 

Melons 21.9 

Okra 13.6 

Onions 50.3 

Oriental vegetables 2.1 

Parsnips 2.2 

Peanuts 1.9 

Peas 29.0 

Peppers 57.7 

Potatoes 25.5 

Pumpkins 10.2 

Radishes 30.7 

Rhubarb 12.2 

Spinach 10.2 

Summer squash 25.7 

Sunflowers 8.2 

Sweet potatoes 5.7 

Tomato 85.4 

Turnips 10.7 

Winter squash 11.1 

Source: National Gardening Association, 1987. 
Table 13-3. Sub-category Codes and Definitions 

Code Definition Description 

Regiona 

1 Northeast Includes Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New 

York, Pennsylvania, Rhode Island, and Vermont 

2 Midwest Includes Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, 

North Dakota, Ohio, South Dakota, and Wisconsin 

3 South Includes Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, 

Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South 

Carolina, Tennessee, Texas, Virginia, and West Virginia 

4 West Includes Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, 

Utah, Washington, and Wyoming 

Urbanization 

1 Central City Cities with populations of 50,000 or more that is the main city within the metropolitan 

statistical area (MSA). 

2 Suburban An area that is generally within the boundaries of an MSA, but is not within the legal 

limit of the central city. 

3 Nonmetropolitan An area that is not within an MSA. 

Race 

1 -­ White (Caucasian) 

2 -­ Black 

3 -­ Asian and Pacific Islander 

4 -­ Native American, Aleuts, and Eskimos 

5, 8, 9 Other/NA Don't know, no answer, some other race 

Responses to Survey Questions 

Grow Question 75 Did anyone in the household grow any vegetables or fruit for use in the household? 

Raise Question 76 Did anyone in the household produce any animal products such as milk, eggs, meat, 

Animals or poultry for home use in your household? 

Fish/Hunt Question 77 Did anyone in the household catch any fish or shoot game for home use? 

Farm Question 79 Did anyone in the household operate a farm or ranch? 

Season 

Spring - April, May, June 

Summer - July, August, September 

Fall - October, November, December 

Winter - January, February, March

 Alaska and Hawaii were not included. a 

Source: USDA 1987-88. 
Table 13-4. Weighted and Unweighted Number of Observations (Individuals) for NFCS Data Used in Analysis of Food Intake 

All Regions Northeast Midwest South West 

wgtd unwgtd wgtd unwgtd wgtd unwgtd wgtd unwgtd wgtd unwgtd 

Total 188019000 9852 41167000 2018 46395000 2592 64331000 3399 36066000 1841 

Age (years)

 < 01 2814000 156 545000 29 812000 44 889000 51 568000 32

 01-02 5699000 321 1070000 56 1757000 101 1792000 105 1080000 59

 03-05 8103000 461 1490000 92 2251000 133 2543000 140 1789000 95

 06-11 16711000 937 3589000 185 4263000 263 5217000 284 3612000 204

 12-19 20488000 1084 4445000 210 5490000 310 6720000 369 3833000 195

 20-39 61606000 3058 12699000 600 15627000 823 21786000 1070 11494000 565

 40-69 56718000 3039 13500000 670 13006000 740 19635000 1080 10577000 549

 70 + 15880000 796 3829000 176 3189000 178 5749000 300 3113000 142 

Season

 Fall 47667000 1577 9386000 277 14399000 496 13186000 439 10696000 365

 Spring 46155000 3954 10538000 803 10657000 1026 16802000 1437 8158000 688

 Summer 45485000 1423 9460000 275 10227000 338 17752000 562 7986000 246

 Winter 48712000 2898 11783000 663 11112000 732 16591000 961 9226000 542 

Urbanization

 Central City 56352000 2217 9668000 332 17397000 681 17245000 715 12042000 489

 Nonmetropolitan 45023000 3001 5521000 369 14296000 1053 19100000 1197 6106000 382

 Surburban 86584000 4632 25978000 1317 14702000 858 27986000 1487 17918000 970 

Race

 Asian 2413000 114 333000 13 849000 37 654000 32 577000 32

 Black 21746000 1116 3542000 132 2794000 126 13701000 772 1709000 86

 Native American 1482000 91 38000 4 116000 6 162000 8 1166000 73

 Other/NA 4787000 235 1084000 51 966000 37 1545000 86 1192000 61

 White 157531000 8294 36170000 1818 41670000 2386 48269000 2501 31422000 1589 

Response to Questionnaire

 Do you garden? 68152000 3744 12501000 667 22348000 1272 20518000 1136 12725000 667

 Do you raise animals? 10097000 631 1178000 70 3742000 247 2603000 162 2574000 152

 Do you hunt? 20216000 1148 3418000 194 6948000 411 6610000 366 3240000 177

 Do you fish? 39733000 2194 5950000 321 12621000 725 13595000 756 7567000 392

 Do you farm? 7329000 435 830000 42 2681000 173 2232000 130 1586000 90 
Table 13-5. Percent Weight Losses from Preparation of Various Meats 

Meat Type Mean Range of Means Deviation Mean Range of Means Deviation 

Mean Net Cooking Loss (%) Mean Net Post Cooking Loss (%) a b 

Standard Standard 

Beef 27 11 to 42 7 24 10 to 46 9 

Pork 28 1 to 67 10 36 14 to 52 11 

Chicken 32 7 to 55 9 31 16 to 51 8 

Turkey 32 11 to 57 7 28 8 to 48 10 

Lamb 30 25 to 37 5 34 14 to 61 14 

Veal 29 10.to 45 11 25 18 to 37 9 

Fish 30 -19 to 81 19 11 1 to 26 6 c 

Shellfish 33 1 to 94 30 10 10 to 10 0 d 

Includes dripping and volatile losses during cooking. Averaged over various cuts and preparation methods. a 

Includes losses from cutting, shrinkage, excess fat, bones, scraps, and juices. Averaged over various cuts and preparation b 

methods. 

Averaged over a variety of fish, to include: bass, bluefish, butterfish, cod, flounder, haddock, halibut, lake trout, makerel, c 

perch, porgy, red snapper, rockfish, salmon, sea trout, shad, smelt, sole, spot, squid, swordfish steak, trout, and whitefish. 

Averaged over a variety of shellfish, to include: clams, crab, crayfish, lobster, oysters, and shrimp and shrimp dishes. d 

Source: USDA, 1975. 
Table 13-6. Percent Weight Losses from Preparation of Various Fruits 

Type of Fruit Mean Means Deviation Mean Means Standard 

Mean Net Post Cooking Loss (%) Mean Paring or Preparation Loss (%) a b,c 

Range of Standard Range of 

Apples 25 3 to 42 13 22 13 to 40 NA 

Pears -­ -­ -­ 22 12 to 60 NA 

Peaches 36 19 to 50 12 24 6 to 68 NA 

Strawberries -­ -­ -­ 10 6 to 14 NA 

Oranges -­ -­ -­ 29 19 to 38 NA 

b 

b 

41 25 to 47 NA c 

b 

b 

30 96 to 41 15 c 

b 

b 

b 

c 

b 

b 

c 

b 

b 

b 

c 

b 

b 

c 

b 

Includes losses from draining cooked forms. a 

Includes losses from removal of skin or peel, core or pit, stems or caps, seeds and defects. b 

Includes losses from removal of drained liquids from canned or frozen forms. c 

Source: USDA, 1975 
Table 13-7. Percent Weight Losses from Preparation of Various Vegetables 

Type of Standard Standard 

Vegetable Mean Range of Means Deviation Mean Range of Means Deviation 

Mean Net Cooking Loss (%) Mean Net Post Cooking Loss (%) a b 

Asparagus 23 5 to 47 16 -­ -­ -­

Beets 28 4 to 60 17 -­ -­ -­

Broccoli 14 0 to 39 13 -­ -­ -­

Cabbage 11 4 to 20 6 -­ -­ -­

Carrots 19 2 to 41 12 -­ -­ -­

Corn 26 -1 to 64 22 -­ -­ -­

Cucumbers 18 5 to 40 14 -­ -­ -­

Lettuce 22 6 to 36 12 -­ -­ -­

Lima Beans -12 -143 to 56 69 -­ -­ -­

Okra 12 -10 to 40 16 -­ -­ -­

Onions 5 -90 to 63 38 -­ -­ -­

Peas, green 2 -147 to 62 63 -­ -­ -­

Peppers 13 3 to 27 9 -­ -­ -­

Pumpkins 19 8 to 30 11 -­ -­ -­

Snap Beans 18 5 to 42 13 -­ -­ -­

Tomatoes 15 2 to 34 10 -­ -­ -­

Potatoes -22 -527 to 46 121 22 1 to 33 11 

Includes losses due to paring, trimming, flowering the stalk, thawing, draining, scraping, shelling, slicing, husking, a 

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. b 

Source: USDA, 1975 
Table 13-8. Consumer Only Intake of Homegrown Fruits (g/kg-day) - All Regions Combined 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 14744000 817 7.84 2.68E+00 1.89E-01 6.26E-02 1.68E-01 2.78E-01 4.97E-01 1.07E+00 2.37E+00 5.97E+00 1.11E+01 2.40E+01 6.06E+01 

Age (years)

 01-02 360000 23 6.32 8.74E+00 3.10E+00 9.59E-01 1.09E+00 1.30E+00 1.64E+00 3.48E+00 7.98E+00 1.93E+01 6.06E+01 6.06E+01 6.06E+01

 03-05 550000 34 6.79 4.07E+00 1.48E+00 1.00E-02 1.00E-02 3.62E-01 9.77E-01 1.92E+00 2.73E+00 6.02E+00 8.91E+00 4.83E+01 4.83E+01

 06-11 1044000 75 6.25 3.59E+00 6.76E-01 1.00E-02 1.91E-01 4.02E-01 6.97E-01 1.31E+00 3.08E+00 1.18E+01 1.58E+01 3.22E+01 3.22E+01

 12-19 1189000 67 5.80 1.94E+00 3.66E-01 8.74E-02 1.27E-01 2.67E-01 4.41E-01 6.61E-01 2.35E+00 6.76E+00 8.34E+00 1.85E+01 1.85E+01

 20-39 3163000 164 5.13 1.95E+00 3.33E-01 8.14E-02 1.28E-01 2.04E-01 3.74E-01 7.03E-01 1.77E+00 4.17E+00 6.84E+00 1.61E+01 3.70E+01

 40-69 5633000 309 9.93 2.66E+00 3.04E-01 6.26E-02 1.91E-01 2.86E-01 4.69E-01 1.03E+00 2.33E+00 5.81E+00 1.30E+01 2.38E+01 5.33E+01

 70 + 2620000 134 16.50 2.25E+00 2.34E-01 4.41E-02 2.24E-01 3.80E-01 6.11E-01 1.18E+00 2.35E+00 5.21E+00 8.69E+00 1.17E+01 1.53E+01 

Season

 Fall 3137000 108 6.58 1.57E+00 1.59E-01 2.63E-01 3.04E-01 3.90E-01 5.70E-01 1.04E+00 1.92E+00 3.48E+00 4.97E+00 1.06E+01 1.06E+01

 Spring 2963000 301 6.42 1.58E+00 1.37E-01 8.89E-02 1.98E-01 2.54E-01 4.23E-01 8.57E-01 1.70E+00 4.07E+00 5.10E+00 8.12E+00 3.17E+01

 Summer 4356000 145 9.58 3.86E+00 6.40E-01 1.00E-02 9.18E-02 1.56E-01 4.45E-01 1.26E+00 3.31E+00 1.09E+01 1.46E+01 5.33E+01 6.06E+01

 Winter 4288000 263 8.80 3.08E+00 3.41E-01 4.41E-02 1.72E-01 2.69E-01 5.56E-01 1.15E+00 2.61E+00 8.04E+00 1.53E+01 2.49E+01 4.83E+01 

Urbanization

 Central City 3668000 143 6.51 2.31E+00 2.64E-01 4.41E-02 1.82E-01 3.33E-01 5.67E-01 1.08E+00 2.46E+00 5.34E+00 1.05E+01 1.43E+01 1.93E+01

 Nonmetropolitan 4118000 278 9.15 2.41E+00 3.09E-01 6.26E-02 1.27E-01 2.32E-01 4.50E-01 1.15E+00 2.42E+00 4.46E+00 8.34E+00 2.40E+01 5.33E+01

 Suburban 6898000 394 7.97 3.07E+00 3.22E-01 1.25E-01 2.30E-01 2.95E-01 4.91E-01 9.93E-01 2.33E+00 7.26E+00 1.52E+01 3.70E+01 6.06E+01 

Race

 Black 450000 20 2.07 1.87E+00 8.53E-01 1.32E-01 2.84E-01 4.55E-01 6.08E-01 1.13E+00 1.53E+00 2.29E+00 2.29E+00 1.93E+01 1.93E+01

 White 14185000 793 9.00 2.73E+00 1.94E-01 7.22E-02 1.82E-01 2.82E-01 5.10E-01 1.07E+00 2.46E+00 6.10E+00 1.17E+01 2.40E+01 6.06E+01 

Questionnaire Response

 Households who garden 12742000 709 18.70 2.79E+00 2.10E-01 5.60E-02 1.84E-01 2.87E-01 5.30E-01 1.12E+00 2.50E+00 6.10E+00 1.18E+01 2.49E+01 6.06E+01

 Households who farm 1917000 112 26.16 2.58E+00 2.59E-01 7.22E-02 2.76E-01 4.13E-01 7.53E-01 1.61E+00 3.62E+00 5.97E+00 7.82E+00 1.58E+01 1.58E+01 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987/88 NFCS 
Table 13-9. Consumer Only Intake of Homegrown Fruits (g/kg-day) - Northeast 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P

Total 1279000 72 3.11 9.29E-01 2.20E-01 7.91E-02 8.48E-02 1.61E-01 3.11E-01 4.85E-01 7.82E-01 1.29E+00 2.16E+00 1.17E+01 1.1

Season

 Fall 260000 8 2.77 * * * * * * * * * * * 

 Spring 352000 31 3.34 8.80E-01 2.32E-01 8.74E-02 1.61E-01 1.68E-01 2.87E-01 4.85E-01 8.79E-01 1.83E+00 2.16E+00 7.13E+00 7.1

 Summer 271000 9 2.86 * * * * * * * * * * * 

 Winter 396000 24 3.36 7.10E-01 1.13E-01 1.84E-01 2.07E-01 2.30E-01 2.93E-01 5.42E-01 8.81E-01 1.38E+00 1.79E+00 2.75E+00 2.7

Urbanization

 Central City 50000 3 0.52 * * * * * * * * * * * 

 Nonmetropolitan 176000 10 3.19 * * * * * * * * * * * 

 Suburban 1053000 59 4.05 1.05E+00 2.63E-01 1.84E-01 2.30E-01 2.93E-01 4.37E-01 5.43E-01 8.12E-01 1.29E+00 2.75E+00 1.17E+01 1.1

Questionnaire Response

 Households who garden 983000 59 7.86 1.04E+00 2.64E-01 8.74E-02 1.82E-01 2.13E-01 3.75E-01 5.43E-01 8.81E-01 1.38E+00 2.75E+00 1.17E+01 1.1

 Households who farm 132000 4 15.90 * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-10. Consumer Only Intake of Homegrown Fruits (g/kg-day) - Midwest 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 4683000 302 10.09 3.01E+00 4.13E-01 4.41E-02 1.25E-01 2.35E-01 4.68E-01 1.03E+00 2.31E+00 6.76E+00 1.39E+01 5.33E+01 6.06E+01 

Season

 Fall 1138000 43 7.90 1.54E+00 1.86E-01 2.63E-01 3.04E-01 4.74E-01 6.11E-01 1.07E+00 1.92E+00 3.48E+00 4.34E+00 5.33E+00 5.33E+00

 Spring 1154000 133 10.83 1.69E+00 2.76E-01 8.89E-02 2.09E-01 2.62E-01 4.23E-01 9.23E-01 1.72E+00 2.89E+00 4.47E+00 1.60E+01 3.17E+01

 Summer 1299000 44 12.70 7.03E+00 1.85E+00 6.26E-02 9.18E-02 1.25E-01 4.28E-01 1.55E+00 8.34E+00 1.61E+01 3.70E+01 6.06E+01 6.06E+01

 Winter 1092000 82 9.83 1.18E+00 1.80E-01 2.57E-02 5.60E-02 1.46E-01 3.62E-01 6.09E-01 1.42E+00 2.61E+00 3.73E+00 1.09E+01 1.09E+01 

Urbanization

 Central City 1058000 42 6.08 1.84E+00 3.93E-01 4.15E-02 1.01E-01 2.63E-01 5.21E-01 1.07E+00 1.90E+00 2.82E+00 9.74E+00 1.09E+01 1.09E+01

 Nonmetropolitan 1920000 147 13.43 2.52E+00 5.43E-01 5.60E-02 1.08E-01 1.46E-01 3.96E-01 1.03E+00 2.07E+00 4.43E+00 6.84E+00 5.33E+01 5.33E+01

 Suburban 1705000 113 11.60 4.29E+00 8.72E-01 9.18E-02 2.04E-01 3.10E-01 4.81E-01 7.64E-01 3.01E+00 1.39E+01 1.80E+01 6.06E+01 6.06E+01 

Response to Questionnaire

 Households who garden 4060000 267 18.17 3.27E+00 4.69E-01 4.41E-02 1.01E-01 2.04E-01 4.48E-01 1.07E+00 2.37E+00 7.15E+00 1.46E+01 5.33E+01 6.06E+01

 Households who farm 694000 57 25.89 2.59E+00 3.01E-01 5.60E-02 1.91E-01 4.08E-01 1.26E+00 1.63E+00 3.89E+00 6.76E+00 8.34E+00 1.11E+01 1.11E+01 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-11. Consumer Only Intake of Homegrown Fruits (g/kg-day) - South 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 4148000 208 6.45 2.97E+00 3.00E-01 1.12E-01 2.42E-01 3.55E-01 5.97E-01 1.35E+00 3.01E+00 8.18E+00 1.41E+01 2.38E+01 2.40E+01 

Season

 Fall 896000 29 6.80 1.99E+00 4.39E-01 3.92E-01 4.27E-01 4.46E-01 6.50E-01 1.13E+00 1.96E+00 4.97E+00 8.18E+00 1.06E+01 1.06E+01

 Spring 620000 59 3.69 2.05E+00 2.55E-01 1.55E-01 2.82E-01 3.11E-01 4.50E-01 1.06E+00 4.09E+00 5.01E+00 6.58E+00 7.05E+00 7.05E+00

 Summer 1328000 46 7.48 2.84E+00 6.50E-01 8.14E-02 1.56E-01 2.67E-01 4.41E-01 1.31E+00 2.83E+00 6.10E+00 1.43E+01 2.40E+01 2.40E+01

 Winter 1304000 74 7.86 4.21E+00 6.51E-01 1.12E-01 2.36E-01 3.82E-01 8.92E-01 1.88E+00 3.71E+00 1.41E+01 1.97E+01 2.38E+01 2.38E+01 

Urbanization

 Central City 1066000 39 6.18 3.33E+00 5.39E-01 2.36E-01 3.92E-01 4.55E-01 8.34E-01 2.55E+00 4.77E+00 8.18E+00 1.06E+01 1.43E+01 1.43E+01

 Nonmetropolitan 1548000 89 8.10 2.56E+00 3.87E-01 8.14E-02 2.67E-01 3.38E-01 6.12E-01 1.40E+00 2.83E+00 5.97E+00 1.04E+01 2.40E+01 2.40E+01

 Suburban 1534000 80 5.48 3.14E+00 6.02E-01 1.12E-01 1.56E-01 2.84E-01 5.08E-01 1.10E+00 2.29E+00 1.18E+01 1.55E+01 2.38E+01 2.38E+01 

Response to Questionnaire

 Households who garden 3469000 174 16.91 2.82E+00 2.94E-01 1.56E-01 2.84E-01 3.84E-01 6.50E-01 1.39E+00 2.94E+00 6.10E+00 1.41E+01 2.11E+01 2.40E+01

 Households who farm 296000 16 13.26 * * * * * * * * * * * * 

* Intake data not provided for subpopulatins for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-12. Consumer Only Intake of Homegrown Fruits (g/kg-day) - West 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 4574000 233 12.68 2.62E+00 3.07E-01 1.50E-01 2.75E-01 3.33E-01 6.17E-01 1.20E+00 2.42E+00 5.39E+00 1.09E+01 2.49E+01 4.83E+01 

Season

 Fall 843000 28 7.88 1.47E+00 2.49E-01 2.91E-01 2.91E-01 2.95E-01 4.83E-01 1.04E+00 2.15E+00 2.99E+00 4.65E+00 5.39E+00 5.39E+00

 Spring 837000 78 10.26 1.37E+00 1.59E-01 1.73E-01 1.96E-01 2.51E-01 5.10E-01 9.81E-01 1.61E+00 2.95E+00 5.29E+00 6.68E+00 7.02E+00

 Summer 1398000 44 17.51 2.47E+00 4.72E-01 1.86E-01 2.75E-01 4.04E-01 6.17E-01 1.28E+00 3.14E+00 7.26E+00 1.09E+01 1.30E+01 1.30E+01

 Winter 1496000 83 16.22 4.10E+00 7.91E-01 7.14E-02 2.96E-01 3.33E-01 7.74E-01 1.51E+00 3.74E+00 1.11E+01 1.85E+01 4.83E+01 4.83E+01 

Urbanization

 Central City 1494000 59 12.41 1.99E+00 4.24E-01 7.14E-02 2.35E-01 3.42E-01 5.26E-01 8.63E-01 2.04E+00 4.63E+00 9.52E+00 1.93E+01 1.93E+01

 Nonmetropolitan 474000 32 7.76 2.24E+00 5.25E-01 1.84E-01 2.76E-01 4.24E-01 6.25E-01 7.68E-01 2.64E+00 4.25E+00 1.09E+01 1.09E+01 1.09E+01

 Suburban 2606000 142 14.54 3.04E+00 4.63E-01 1.83E-01 2.75E-01 3.14E-01 7.10E-01 1.39E+00 3.14E+00 5.81E+00 1.03E+01 3.22E+01 4.83E+01 

Response to Questionnaire

 Households who garden 4170000 207 32.77 2.76E+00 3.39E-01 1.00E-01 2.75E-01 3.14E-01 6.29E-01 1.20E+00 2.54E+00 5.81E+00 1.09E+01 2.49E+01 4.83E+01

 Households who farm 795000 35 50.13 1.85E+00 2.59E-01 2.75E-01 2.76E-01 5.98E-01 7.10E-01 1.26E+00 2.50E+00 4.63E+00 5.00E+00 6.81E+00 6.81E+00 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-13. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - All Regions Combined 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 34392000 1855 18.29 2.08E+00 6.76E-02 4.79E-03 1.10E-01 1.80E-01 4.47E-01 1.11E+00 2.47E+00 5.20E+00 7.54E+00 1.55E+01 2.70E

Age

 01-02 951000 53 16.69 5.20E+00 8.47E-01 2.32E-02 2.45E-01 3.82E-01 1.23E+00 3.27E+00 5.83E+00 1.31E+01 1.96E+01 2.70E+01 2.70E

 03-05 1235000 76 15.24 2.46E+00 2.79E-01 0.00E+00 4.94E-02 3.94E-01 7.13E-01 1.25E+00 3.91E+00 6.35E+00 7.74E+00 1.06E+01 1.28E

 06-11 3024000 171 18.10 2.02E+00 2.54E-01 5.95E-03 1.00E-01 1.60E-01 4.00E-01 8.86E-01 2.21E+00 4.64E+00 6.16E+00 1.76E+01 2.36E

 12-19 3293000 183 16.07 1.48E+00 1.35E-01 0.00E+00 6.46E-02 1.45E-01 3.22E-01 8.09E-01 1.83E+00 3.71E+00 6.03E+00 7.71E+00 9.04E

 20-39 8593000 437 13.95 1.47E+00 9.59E-02 1.69E-02 7.77E-02 1.57E-01 2.73E-01 7.61E-01 1.91E+00 3.44E+00 4.92E+00 1.05E+01 2.06E

 40-69 12828000 700 22.62 2.07E+00 1.02E-01 5.13E-03 1.19E-01 2.14E-01 5.26E-01 1.18E+00 2.47E+00 5.12E+00 6.94E+00 1.49E+01 2.29E

 70 + 4002000 211 25.20 2.51E+00 1.94E-01 5.21E-03 1.51E-01 2.39E-01 5.81E-01 1.37E+00 3.69E+00 6.35E+00 8.20E+00 1.25E+01 1.55E

Seasons

 Fall 11026000 394 23.13 1.88E+00 1.28E-01 4.98E-02 1.13E-01 1.80E-01 4.13E-01 9.83E-01 2.11E+00 4.88E+00 6.94E+00 1.25E+01 1.89E

 Spring 6540000 661 14.17 1.36E+00 7.23E-02 2.44E-03 4.47E-02 1.35E-01 3.21E-01 7.04E-01 1.63E+00 3.37E+00 5.21E+00 8.35E+00 2.36E

 Summer 11081000 375 24.36 2.86E+00 1.93E-01 6.93E-02 1.57E-01 2.24E-01 7.12E-01 1.62E+00 3.44E+00 6.99E+00 9.75E+00 1.87E+01 2.70E

 Winter 5745000 425 11.79 1.79E+00 1.14E-01 3.73E-03 4.49E-02 1.56E-01 4.69E-01 1.05E+00 2.27E+00 3.85E+00 6.01E+00 1.06E+01 2.06E

Urbanizations

 Central City 6183000 228 10.97 1.40E+00 1.23E-01 1.01E-02 6.59E-02 1.50E-01 3.00E-01 7.50E-01 1.67E+00 3.83E+00 4.67E+00 9.96E+00 1.66E

 Nonmetropolitan 13808000 878 30.67 2.68E+00 1.19E-01 2.12E-02 1.58E-01 2.58E-01 5.99E-01 1.45E+00 3.27E+00 6.35E+00 9.33E+00 1.75E+01 2.70E

 Suburban 14341000 747 16.56 1.82E+00 9.12E-02 3.34E-03 1.10E-01 1.63E-01 3.94E-01 9.63E-01 2.18E+00 4.32E+00 6.78E+00 1.25E+01 2.06E

Race

 Black 1872000 111 8.61 1.78E+00 2.33E-01 0.00E+00 7.77E-02 1.39E-01 4.38E-01 9.32E-01 2.06E+00 4.68E+00 5.70E+00 8.20E+00 1.89E

 White 31917000 1714 20.26 2.10E+00 7.09E-02 7.34E-03 1.13E-01 1.84E-01 4.54E-01 1.12E+00 2.48E+00 5.18E+00 7.68E+00 1.55E+01 2.70E

Response to Questionnaire

 Households who garden 30217000 1643 44.34 2.17E+00 7.09E-02 5.21E-03 1.11E-01 1.85E-01 4.84E-01 1.18E+00 2.68E+00 5.35E+00 7.72E+00 1.55E+01 2.36E

 Households who farm 4319000 262 58.93 3.29E+00 2.51E-01 0.00E+00 1.61E-01 2.92E-01 8.46E-01 1.67E+00 3.61E+00 8.88E+00 1.18E+01 1.76E+01 2.36E

NOTE: SE = standard error

 P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-14. Cnnsumer Only Intake of Homegrown Vegetables (g/kg-day) - Northeast 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 4883000 236 11.86 1.78E+00 1.68E-01 2.18E-03 8.27E-02 1.43E-01 2.80E-01 7.47E-01 1.89E+00 6.03E+00 7.82E+00 1.27E+01 1.49E+01 

Seasons

 Fall 1396000 41 14.87 1.49E+00 4.06E-01 8.27E-02 1.34E-01 1.74E-01 2.69E-01 5.81E-01 1.17E+00 6.64E+00 9.97E+00 1.02E+01 1.02E+01

 Spring 1204000 102 11.43 8.18E-01 1.07E-01 0.00E+00 2.89E-03 4.47E-02 1.72E-01 4.55E-01 9.52E-01 2.26E+00 3.11E+00 6.52E+00 6.78E+00

 Summer 1544000 48 16.32 2.83E+00 4.67E-01 1.11E-01 1.45E-01 1.59E-01 7.38E-01 1.29E+00 3.63E+00 7.82E+00 9.75E+00 1.49E+01 1.49E+01

 Winter 739000 45 6.27 1.67E+00 2.74E-01 3.23E-03 4.23E-03 9.15E-02 2.56E-01 1.25E+00 2.77E+00 3.63E+00 6.10E+00 8.44E+00 8.44E+00 

Urbanizations

 Central City 380000 14 3.93 * * * * * * * * * * * *

 Nonmetropolitan 787000 48 14.25 3.05E+00 5.41E-01 0.00E+00 4.68E-02 1.14E-01 2.02E-01 2.18E+00 4.61E+00 9.04E+00 1.27E+01 1.49E+01 1.49E+01

 Suburban 3716000 174 14.30 1.59E+00 1.74E-01 2.44E-03 8.27E-02 1.42E-01 2.75E-01 7.18E-01 1.64E+00 4.82E+00 6.80E+00 1.02E+01 1.02E+01 

Response to Questionnaire

 Households who garden 4381000 211 35.05 1.92E+00 1.84E-01 2.18E-03 8.27E-02 1.42E-01 3.10E-01 8.83E-01 2.18E+00 6.16E+00 7.82E+00 1.27E+01 1.49E+01

 Households who farm 352000 19 42.41 * * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-15. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - Midwest 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 12160000 699 26.21 2.26E+00 1.20E-01 1.59E-02 7.77E-02 1.80E-01 4.88E-01 1.15E+00 2.58E+00 5.64E+00 7.74E+00 1.75E+01 2.36E+01 

Seasons

 Fall 4914000 180 34.13 1.84E+00 1.76E-01 1.01E-02 6.51E-02 1.60E-01 4.16E-01 1.03E+00 2.10E+00 5.27E+00 6.88E+00 1.31E+01 1.31E+01

 Spring 2048000 246 19.22 1.65E+00 1.49E-01 6.04E-02 1.53E-01 2.21E-01 4.59E-01 9.13E-01 1.72E+00 4.49E+00 5.83E+00 1.28E+01 2.36E+01

 Summer 3319000 115 32.45 3.38E+00 3.87E-01 1.05E-01 1.62E-01 3.02E-01 8.47E-01 2.07E+00 3.94E+00 7.72E+00 1.40E+01 1.96E+01 2.29E+01

 Winter 1879000 158 16.91 2.05E+00 2.64E-01 2.41E-03 2.14E-02 6.59E-02 3.62E-01 8.77E-01 2.13E+00 5.32E+00 7.83E+00 1.67E+01 2.06E+01 

Urbanizations

 Central City 3177000 113 18.26 1.36E+00 1.91E-01 0.00E+00 6.05E-02 1.10E-01 2.45E-01 7.13E-01 1.67E+00 3.94E+00 5.50E+00 9.96E+00 1.66E+01

 Nonmetropolitan 5344000 379 37.38 2.73E+00 1.86E-01 2.12E-02 1.13E-01 2.61E-01 5.98E-01 1.31E+00 3.15E+00 7.19E+00 1.06E+01 1.75E+01 2.36E+01

 Suburban 3639000 207 24.75 2.35E+00 2.16E-01 3.26E-02 1.54E-01 2.22E-01 6.36E-01 1.39E+00 2.75E+00 4.87E+00 7.18E+00 1.96E+01 2.06E+01 

Response to Questionnaire

 Households who garden 10927000 632 48.89 2.33E+00 1.27E-01 1.59E-02 1.04E-01 1.76E-01 5.03E-01 1.18E+00 2.74E+00 5.81E+00 7.75E+00 1.67E+01 2.36E+01

 Households who farm 1401000 104 52.26 3.97E+00 4.31E-01 1.40E-01 3.35E-01 5.51E-01 8.67E-01 2.18E+00 5.24E+00 1.06E+01 1.44E+01 1.75E+01 2.36E+01 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-16. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - South 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 1125400 618 17.49 2.19E+00 1.21E-01 2.92E-02 1.60E-01 2.41E-01 5.63E-01 1.24E+00 2.69E+00 4.92E+00 7.43E+00 1.70E+01 2.70E+01 

0 

Seasons

 Fall 2875000 101 21.80 2.07E+00 2.82E-01 9.59E-02 1.13E-01 1.91E-01 5.24E-01 1.14E+00 2.69E+00 4.48E+00 6.02E+00 1.55E+01 1.89E+01

 Spring 2096000 214 12.47 1.55E+00 1.13E-01 1.41E-02 9.21E-02 2.61E-01 5.33E-01 9.35E-01 2.07E+00 3.58E+00 4.81E+00 8.35E+00 1.03E+01

 Summer 4273000 151 24.07 2.73E+00 3.16E-01 1.10E-01 1.72E-01 2.50E-01 6.15E-01 1.54E+00 3.15E+00 5.99E+00 9.70E+00 2.36E+01 2.70E+01

 Winter 2010000 152 12.12 1.88E+00 1.37E-01 3.03E-03 1.63E-01 3.53E-01 6.40E-01 1.37E+00 2.69E+00 3.79E+00 5.35E+00 7.47E+00 8.36E+00 

Urbanizations

 Central City 1144000 45 6.63 1.10E+00 1.62E-01 1.10E-02 9.59E-02 1.50E-01 2.63E-01 6.15E-01 1.37E+00 2.79E+00 3.70E+00 4.21E+00 4.58E+00

 Nonmetropolitan 6565000 386 34.37 2.78E+00 1.84E-01 5.08E-02 2.23E-01 3.50E-01 7.12E-01 1.66E+00 3.31E+00 5.99E+00 9.56E+00 1.89E+01 2.70E+01

 Suburban 3545000 187 12.67 1.44E+00 1.13E-01 0.00E+00 1.13E-01 1.99E-01 3.96E-01 9.33E-01 1.72E+00 3.61E+00 5.26E+00 8.20E+00 8.20E+00 

Response to Questionnaire

 Households who garden 9447000 522 46.04 2.27E+00 1.22E-01 3.46E-02 1.61E-01 2.62E-01 6.10E-01 1.37E+00 3.02E+00 5.18E+00 7.43E+00 1.55E+01 2.36E+01

 Households who farm 1609000 91 72.09 3.34E+00 4.57E-01 0.00E+00 1.32E-01 2.33E-01 1.03E+00 1.72E+00 3.15E+00 9.56E+00 1.18E+01 2.36E+01 2.36E+01

 NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-17. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - West 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 6035000 300 16.73 1.81E+00 1.38E-01 7.35E-03 9.85E-02 1.66E-01 3.79E-01 9.01E-01 2.21E+00 4.64E+00 6.21E+00 1.14E+01 1.55E+0

Seasons

 Fall 1841000 72 17.21 2.01E+00 2.93E-01 9.83E-02 1.50E-01 2.04E-01 4.81E-01 1.21E+00 2.21E+00 4.85E+00 7.72E+00 1.25E+01 1.25E+0

 Spring 1192000 99 14.61 1.06E+00 1.74E-01 3.31E-03 7.35E-03 4.66E-02 1.95E-01 3.56E-01 9.08E-01 3.37E+00 5.54E+00 8.60E+00 8.60E+0

 Summer 1885000 59 23.60 2.39E+00 3.71E-01 6.93E-02 1.04E-01 2.46E-01 5.45E-01 1.37E+00 3.23E+00 4.67E+00 8.36E+00 1.55E+01 1.55E+0

 Winter 1117000 70 12.11 1.28E+00 1.72E-01 1.29E-02 1.52E-01 1.99E-01 4.83E-01 7.65E-01 1.43E+00 2.81E+00 5.12E+00 7.57E+00 7.98E+0

Urbanizations

 Central City 1482000 56 12.31 1.80E+00 2.76E-01 2.58E-02 7.39E-02 1.57E-01 4.81E-01 1.10E+00 2.95E+00 4.64E+00 4.85E+00 1.14E+01 1.14E+0

 Nonmetropolitan 1112000 65 18.21 1.52E+00 2.24E-01 3.42E-03 9.80E-03 2.04E-01 2.69E-01 6.75E-01 2.13E+00 4.13E+00 5.12E+00 8.16E+00 8.16E+0

 Suburban 3441000 179 19.20 1.90E+00 1.98E-01 1.29E-02 1.04E-01 1.52E-01 3.94E-01 9.32E-01 2.20E+00 4.63E+00 7.98E+00 1.25E+01 1.55E+0

Response to Questionnaire

 Households who garden 5402000 276 42.45 1.91E+00 1.04E-03 8.53E-03 1.04E-01 1.66E-01 4.33E-01 1.07E+00 2.37E+00 4.67E+00 6.21E+00 1.25E+01 1.55E+0

 Households who farm 957000 48 60.34 2.73E+00 3.32E-03 1.17E-01 4.14E-01 4.69E-01 7.65E-01 1.42E+00 3.27E+00 6.94E+00 1.09E+01 1.55E+01 1.55E+0

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-18. Consumer Only Intake of Home Produced Meats (g/kg-day) - All Regions Combined 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 9257000 569 4.92 2.21E+00 1.07E-01 1.21E-01 2.37E-01 3.74E-01 6.60E-01 1.39E+00 2.89E+00 4.89E+00 6.78E+00 1.40E+01 2.32E+

Age

 01-02 276000 22 4.84 3.65E+00 6.10E-01 3.85E-01 9.49E-01 9.49E-01 1.19E+00 2.66E+00 4.72E+00 8.68E+00 1.00E+01 1.15E+01 1.15E+

 03-05 396000 26 4.89 3.61E+00 5.09E-01 8.01E-01 8.01E-01 1.51E+00 2.17E+00 2.82E+00 3.72E+00 7.84E+00 9.13E+00 1.30E+01 1.30E+

 06-11 1064000 65 6.37 3.65E+00 4.51E-01 3.72E-01 6.52E-01 7.21E-01 1.28E+00 2.09E+00 4.71E+00 8.00E+00 1.40E+01 1.53E+01 1.53E+

 12-19 1272000 78 6.21 1.70E+00 1.68E-01 1.90E-01 3.20E-01 4.70E-01 6.23E-01 1.23E+00 2.35E+00 3.66E+00 4.34E+00 6.78E+00 7.51E+

 20-39 2732000 158 4.43 1.82E+00 1.53E-01 1.23E-01 1.85E-01 2.95E-01 5.28E-01 1.11E+00 2.65E+00 4.52E+00 6.23E+00 9.17E+00 1.09E+

 40-69 2872000 179 5.06 1.72E+00 1.11E-01 1.81E-02 2.12E-01 3.43E-01 5.84E-01 1.17E+00 2.38E+00 3.67E+00 5.16E+00 5.90E+00 7.46E+

 70 + 441000 28 2.78 1.39E+00 2.34E-01 9.26E-02 9.26E-02 1.25E-01 5.47E-01 1.01E+00 1.81E+00 2.82E+00 3.48E+00 7.41E+00 7.41E+

Seasons

 Fall 2852000 107 5.98 1.57E+00 1.39E-01 1.23E-01 2.10E-01 3.52E-01 5.21E-01 1.11E+00 2.27E+00 3.19E+00 4.41E+00 6.78E+00 7.84E+

 Spring 1726000 197 3.74 2.37E+00 1.52E-01 2.44E-01 3.20E-01 4.46E-01 7.76E-01 1.69E+00 3.48E+00 5.00E+00 6.67E+00 1.01E+01 1.30E+

 Summer 2368000 89 5.21 3.10E+00 3.82E-01 1.81E-02 1.85E-01 4.06E-01 8.52E-01 1.77E+00 4.34E+00 7.01E+00 1.05E+01 2.23E+01 2.23E+

 Winter 2311000 176 4.74 1.98E+00 1.74E-01 1.35E-01 2.37E-01 3.67E-01 6.48E-01 1.33E+00 2.43E+00 3.96E+00 6.40E+00 1.09E+01 2.32E+

Urbanizations

 Central City 736000 28 1.31 1.15E+00 1.83E-01 1.82E-01 1.85E-01 2.10E-01 4.42E-01 7.21E-01 1.58E+00 2.69E+00 3.40E+00 3.64E+00 3.64E+

 Nonmetropolitan 4932000 315 10.95 2.70E+00 1.76E-01 1.23E-01 2.63E-01 4.06E-01 7.49E-01 1.63E+00 3.41E+00 6.06E+00 8.47E+00 1.53E+01 2.32E+

 Suburban 3589000 226 4.15 1.77E+00 1.03E-01 2.90E-02 2.87E-01 3.67E-01 6.80E-01 1.33E+00 2.49E+00 3.66E+00 4.71E+00 7.20E+00 1.01E+

Race

 Black 128000 6 0.59 * * * * * * * * * * *

 White 8995000 556 5.71 2.26E+00 1.09E-01 9.26E-02 2.57E-01 3.86E-01 6.80E-01 1.41E+00 2.91E+00 5.00E+00 7.01E+00 1.40E+01 2.32E+

Response to Questionnaire

 Households who 5256000 343 52.06 2.80E+00 1.45E-01 2.12E-01 3.86E-01 6.23E-01 1.03E+00 1.94E+00 3.49E+00 5.90E+00 7.84E+00 1.40E+01 2.32E+

 raise animals

 Households who farm 3842000 243 52.42 2.86E+00 1.85E-01 1.97E-01 4.45E-01 5.98E-01 8.94E-01 1.84E+00 3.64E+00 6.09E+00 8.00E+00 1.40E+01 2.32E+

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-19. Consumer Only Intake of Home Produced Meats (g/kg-day) - Northeast 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P

Total 1113000 52 2.70 1.46E+00 2.10E-01 2.92E-01 3.40E-01 3.52E-01 6.44E-01 8.94E-01 1.87E+00 2.68E+00 2.89E+00 1.09E+01 1.09

Seasons

 Fall 569000 18 6.06 * * * * * * * * * * * 

 Spring 66000 8 0.63 * * * * * * * * * * * 

 Summer 176000 6 1.86 * * * * * * * * * * * 

 Winter 302000 20 2.56 2.02E+00 5.56E-01 2.92E-01 3.14E-01 4.30E-01 6.19E-01 1.11E+00 2.38E+00 2.93E+00 7.46E+00 1.09E+01 1.09

Urbanizations

 Central City 0 0 0.00

 Nonmetropolitan 391000 17 7.08 * * * * * * * * * * * 

 Suburban 722000 35 2.78 1.49E+00 1.53E-01 2.92E-01 3.52E-01 4.30E-01 6.80E-01 1.39E+00 2.34E+00 2.68E+00 2.89E+00 3.61E+00 3.61

Response to Questionnaire 

Households who raise animals 509000 25 43.21 2.03E+00 3.85E-01 6.19E-01 6.46E-01 6.46E-01 8.78E-01 1.62E+00 2.38E+00 2.93E+00 7.46E+00 1.09E+01 1.09

 Households who farm 373000 15 44.94 * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-20. Consumer Only Intake of Home Produced Meats (g/kg-day) - Midwest 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 

Total 3974000 266 8.57 2.55E+00 1.81E-01 1.25E-01 2.57E-01 3.85E-01 6.60E-01 1.40E+00 3.39E+00 5.75E+00 7.20E+00 1.53E+01 2.2

Seasons

 Fall 1261000 49 8.76 1.76E+00 2.31E-01 2.10E-01 2.57E-01 3.72E-01 4.95E-01 1.19E+00 2.66E+00 3.49E+00 6.06E+00 6.78E+00 6.7

 Spring 940000 116 8.82 2.58E+00 2.24E-01 2.44E-01 3.11E-01 4.08E-01 7.33E-01 1.98E+00 3.67E+00 5.14E+00 7.79E+00 1.15E+01 1.3

 Summer 930000 38 9.09 4.10E+00 7.45E-01 9.26E-02 1.25E-01 5.78E-01 8.93E-01 2.87E+00 5.42E+00 8.93E+00 1.53E+01 2.23E+01 2.2

 Winter 843000 63 7.59 2.00E+00 2.41E-01 1.21E-01 2.37E-01 3.28E-01 6.48E-01 1.36E+00 2.69E+00 4.11E+00 5.30E+00 8.10E+00 1.2

Urbanizations

 Central City 460000 18 2.64 * * * * * * * * * * * 

 Nonmetropolitan 2477000 175 17.33 3.15E+00 2.58E-01 9.26E-02 2.95E-01 4.25E-01 8.16E-01 2.38E+00 4.34E+00 6.15E+00 9.17E+00 1.53E+01 2.2

 Suburban 1037000 73 7.05 1.75E+00 1.99E-01 2.87E-01 3.65E-01 4.08E-01 6.60E-01 1.11E+00 2.03E+00 4.16E+00 5.39E+00 7.20E+00 1.0

Response to Questionnaire 

Households who raise animals 2165000 165 57.86 3.20E+00 2.23E-01 2.56E-01 3.86E-01 5.78E-01 1.07E+00 2.56E+00 4.42E+00 6.06E+00 9.13E+00 1.53E+01 1.5

 Households who farm 1483000 108 55.32 3.32E+00 2.91E-01 3.65E-01 5.43E-01 5.89E-01 1.07E+00 2.75E+00 4.71E+00 6.78E+00 9.17E+00 1.53E+01 1.5

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-21. Consumer Only Intake of Home Produced Meats (g/kg-day) - South 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 2355000 146 3.66 2.24E+00 1.94E-01 1.81E-02 1.56E-01 2.97E-01 7.21E-01 1.53E+00 3.07E+00 5.07E+00 6.71E+00 1.40E+01 1.40E+01 

Seasons

 Fall 758000 28 5.75 1.81E+00 2.87E-01 1.23E-01 1.56E-01 1.90E-01 8.19E-01 1.53E+00 2.38E+00 3.19E+00 4.41E+00 7.84E+00 7.84E+00

 Spring 511000 53 3.04 2.33E+00 2.66E-01 1.93E-01 2.97E-01 4.99E-01 7.52E-01 1.80E+00 2.82E+00 5.16E+00 6.71E+00 7.51E+00 7.51E+00

 Summer 522000 18 2.94 * * * * * * * * * * * *

 Winter 564000 47 3.40 1.80E+00 2.45E-01 3.70E-02 1.97E-01 2.51E-01 7.16E-01 1.40E+00 2.17E+00 3.55E+00 4.58E+00 8.47E+00 8.47E+00 

Urbanizations

 Central City 40000 1 0.23 * * * * * * * * * * * *

 Nonmetropolitan 1687000 97 8.83 2.45E+00 2.59E-01 1.23E-01 1.90E-01 4.02E-01 7.77E-01 1.61E+00 3.19E+00 6.09E+00 7.84E+00 1.40E+01 1.40E+01

 Suburban 628000 48 2.24 1.79E+00 2.30E-01 1.81E-02 2.90E-02 3.70E-02 6.28E-01 1.40E+00 2.31E+00 4.56E+00 4.61E+00 6.40E+00 6.40E+00 

Response to Questionnaire 

Households who raise animals 1222000 74 46.95 3.16E+00 3.16E-01 2.63E-01 6.67E-01 8.35E-01 1.34E+00 2.11E+00 3.79E+00 6.67E+00 8.47E+00 1.40E+01 1.40E+01

 Households who farm 1228000 72 55.02 2.85E+00 3.24E-01 1.95E-01 4.99E-01 5.98E-01 1.01E+00 1.93E+00 3.48E+00 6.23E+00 8.47E+00 1.40E+01 1.40E+01 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-22. Consumer Only Intake of Home Produced Meats (g/kg-day) - West 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 1815000 105 5.03 1.89E+00 2.12E-01 1.52E-01 2.25E-01 3.90E-01 6.58E-01 1.42E+00 2.49E+00 3.66E+00 4.71E+00 8.00E+00 2.32E+0

Seasons

 Fall 264000 12 2.47 * * * * * * * * * * * *

 Spring 209000 20 2.56 1.86E+00 2.27E-01 2.99E-01 4.25E-01 8.70E-01 1.22E+00 1.56E+00 2.43E+00 3.48E+00 4.20E+00 4.20E+00 4.20E+0

 Summer 740000 27 9.27 2.20E+00 3.18E-01 1.85E-01 4.06E-01 5.35E-01 1.07E+00 1.69E+00 3.27E+00 4.44E+00 4.71E+00 8.00E+00 8.00E+0

 Winter 602000 46 6.53 2.11E+00 4.55E-01 1.35E-01 3.56E-01 4.28E-01 6.72E-01 1.19E+00 2.35E+00 3.64E+00 7.02E+00 2.32E+01 2.32E+0

Urbanizations

 Central City 236000 9 1.96 * * * * * * * * * * * *

 Nonmetropolitan 377000 26 6.17 2.10E+00 7.00E-01 3.30E-01 3.30E-01 4.06E-01 6.72E-01 1.19E+00 1.77E+00 3.72E+00 4.97E+00 2.32E+01 2.32E+0

 Suburban 1202000 70 6.71 1.95E+00 1.99E-01 1.52E-01 2.25E-01 3.67E-01 7.80E-01 1.52E+00 2.71E+00 4.20E+00 4.71E+00 8.00E+00 8.00E+0

Response to Questionnaire 

Households who raise animals 1360000 79 52.84 2.12E+00 2.65E-01 1.52E-01 2.25E-01 3.90E-01 8.15E-01 1.56E+00 2.71E+00 4.20E+00 4.97E+00 8.00E+00 2.32E+0

 Households who farm 758000 48 47.79 2.41E+00 4.26E-01 1.35E-01 3.30E-01 4.67E-01 7.85E-01 1.55E+00 2.91E+00 4.71E+00 7.02E+00 2.32E+01 2.32E+0

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-23. Consumer Only Intake of Home Caught Fish (g/kg-day) - All Regions Combined 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 3914000 239 2.08 2.07E+00 2.38E-01 8.16E-02 9.11E-02 1.95E-01 2.28E-01 4.31E-01 9.97E-01 2.17E+00 4.68E+00 7.83E+00 1.55E+0

Age

 01-02 82000 6 1.44 * * * * * * * * * * * *

 03-05 142000 11 1.75 * * * * * * * * * * * *

 06-11 382000 29 2.29 2.78E+00 8.40E-01 1.60E-01 1.60E-01 1.84E-01 2.28E-01 5.47E-01 1.03E+00 3.67E+00 7.05E+00 7.85E+00 2.53E+0

 12-19 346000 21 1.69 1.52E+00 4.07E-01 1.95E-01 1.95E-01 1.95E-01 1.95E-01 3.11E-01 9.84E-01 1.79E+00 4.68E+00 6.67E+00 8.44E+0

 20-39 962000 59 1.56 1.91E+00 3.34E-01 8.16E-02 8.16E-02 9.11E-02 1.18E-01 4.43E-01 1.06E+00 2.18E+00 4.46E+00 9.57E+00 1.30E+0

 40-69 1524000 86 2.69 1.79E+00 2.56E-01 9.47E-02 9.47E-02 2.10E-01 2.75E-01 3.45E-01 9.85E-01 1.99E+00 4.43E+00 6.56E+00 1.08E+0

 70 + 450000 24 2.83 1.22E+00 2.30E-01 9.88E-02 9.88E-02 2.33E-01 2.33E-01 5.68E-01 7.64E-01 1.56E+00 3.73E+00 3.73E+00 5.12E+0

Season

 Fall 1220000 45 2.56 1.31E+00 2.16E-01 1.84E-01 1.84E-01 1.96E-01 2.10E-01 3.18E-01 9.16E-01 1.79E+00 2.64E+00 3.73E+00 6.56E+0

 Spring 1112000 114 2.41 3.08E+00 5.55E-01 9.88E-02 1.16E-01 3.08E-01 3.40E-01 5.59E-01 1.27E+00 2.64E+00 6.68E+00 1.08E+01 3.73E+0

 Summer 911000 29 2.00 1.88E+00 4.24E-01 8.16E-02 8.16E-02 9.11E-02 2.04E-01 3.01E-01 7.64E-01 3.19E+00 4.43E+00 5.65E+00 9.57E+0

 Winter 671000 51 1.38 2.05E+00 3.68E-01 9.47E-02 9.47E-02 1.11E-01 1.60E-01 5.10E-01 1.06E+00 2.09E+00 5.89E+00 7.85E+00 1.31E+0

Urbanization

 Central City 999000 46 1.77 1.79E+00 3.40E-01 9.47E-02 9.47E-02 1.60E-01 2.84E-01 6.08E-01 1.07E+00 1.85E+00 3.73E+00 9.57E+00 9.57E+0

 Nonmetropolitan 1174000 94 2.61 3.15E+00 5.74E-01 9.88E-02 1.16E-01 3.10E-01 3.62E-01 5.68E-01 1.88E+00 3.86E+00 6.52E+00 7.83E+00 3.73E+0

 Suburban 1741000 99 2.01 1.50E+00 2.30E-01 8.16E-02 8.16E-02 1.84E-01 2.01E-01 2.86E-01 5.87E-01 1.38E+00 4.37E+00 7.05E+00 1.08E+0

Race

 Black 593000 41 2.73 1.81E+00 3.74E-01 1.84E-01 1.84E-01 2.01E-01 2.86E-01 3.18E-01 9.84E-01 2.17E+00 4.68E+00 9.57E+00 9.57E+0

 White 3228000 188 2.05 2.07E+00 2.81E-01 8.16E-02 8.16E-02 1.60E-01 2.27E-01 3.93E-01 9.97E-01 2.16E+00 4.99E+00 6.68E+00 1.61E+0

Response to Questionnaire

 Households who fish 3553000 220 8.94 2.22E+00 2.58E-01 8.16E-02 8.16E-02 1.84E-01 2.27E-01 4.66E-01 1.09E+00 2.23E+00 5.61E+00 7.85E+00 1.61E+0

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-24. Consumer Only Intake of Home Caught Fish (g/kg-day) - Northeast 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 334000 12 0.81 * * * * * * * * * * * * 

Season

 Fall 135000 4 1.44 * * * * * * * * * * * *

 Spring 14000 2 0.13 * * * * * * * * * * * *

 Summer 132000 3 1.40 * * * * * * * * * * * *

 Winter 53000 3 0.45 * * * * * * * * * * * * 

Urbanization

 Central City 0

 Nonmetropolitan 42000 4 0.76 * * * * * * * * * * * *

 Suburban 292000 8 1.12 * * * * * * * * * * * * 

Response to Questionnaire

 Households who fish 334000 12 5.61 * * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-25. Consumer Only Intake of Home Caught Fish (g/kg-day) - Midwest 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 1113000 71 2.40 2.13E+00 4.19E-01 8.16E-02 8.16E-02 1.96E-01 2.27E-01 4.71E-01 1.03E+00 1.95E+00 6.10E+00 6.56E+00 1.61E+01 

Season

 Fall 362000 13 2.51 * * * * * * * * * * * *

 Spring 224000 27 2.10 3.45E+00 1.22E+00 1.16E-01 1.16E-01 1.18E-01 3.10E-01 4.87E-01 8.21E-01 1.67E+00 1.55E+01 1.61E+01 2.53E+01

 Summer 264000 8 2.58 * * * * * * * * * * * *

 Winter 263000 23 2.37 2.38E+00 5.33E-01 5.10E-01 5.10E-01 5.10E-01 5.48E-01 1.03E+00 1.56E+00 2.13E+00 5.89E+00 6.10E+00 1.31E+01 

Urbanization

 Central City 190000 9 1.09 * * * * * * * * * * *

 Nonmetropolitan 501000 40 3.50 3.42E+00 7.17E-01 1.16E-01 1.16E-01 3.30E-01 4.66E-01 5.33E-01 1.88E+00 5.65E+00 6.56E+00 1.31E+01 2.53E+01

 Suburban 422000 22 2.87 9.09E-01 1.81E-01 8.16E-02 8.16E-02 8.16E-02 1.96E-01 3.01E-01 5.48E-01 1.28E+00 2.09E+00 2.78E+00 3.73E+00 

Response to Questionnaire

 Households who fish 956000 60 7.57 2.35E+00 4.85E-01 8.16E-02 8.16E-02 1.18E-01 2.27E-01 4.66E-01 1.12E+00 2.16E+00 6.52E+00 6.56E+00 2.53E+01 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-26. Consumer Only Intake of Home Caught Fish (g/kg-day) - South 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P

Total 1440000 101 2.24 2.74E+00 4.76E-01 9.47E-02 9.47E-02 2.04E-01 2.86E-01 5.07E-01 1.48E+00 3.37E+00 5.61E+00 8.44E+00 3.73

Season

 Fall 274000 11 2.08 * * * * * * * * * * * 

 Spring 538000 58 3.20 4.00E+00 9.42E-01 3.08E-01 3.08E-01 3.87E-01 4.46E-01 8.74E-01 1.94E+00 3.71E+00 8.33E+00 1.30E+01 4.52

 Summer 376000 14 2.12 * * * * * * * * * * * 

 Winter 252000 18 1.52 * * * * * * * * * * * 

Urbanization

 Central City 281000 16 1.63 * * * * * * * * * * * 

 Nonmetropolitan 550000 41 2.88 3.33E+00 1.06E+00 2.85E-01 2.85E-01 3.38E-01 5.07E-01 1.12E+00 1.94E+00 3.19E+00 4.43E+00 6.67E+00 4.52

 Suburban 609000 44 2.18 2.73E+00 4.98E-01 2.04E-01 2.04E-01 2.75E-01 2.86E-01 4.26E-01 1.08E+00 4.37E+00 8.33E+00 1.04E+01 1.3

Response to Questionnaire

 Households who fish 1280000 95 9.42 3.00E+00 5.14E-01 9.47E-02 9.47E-02 2.04E-01 2.80E-01 7.06E-01 1.93E+00 3.67E+00 6.68E+00 8.44E+00 3.73

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standrad error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-27. Consumer Only Intake of Home Caught Fish (g/kg-day) - West 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 1027000 55 2.85 1.57E+00 2.72E-01 9.88E-02 1.60E-01 2.01E-01 2.38E-01 4.43E-01 8.38E-01 1.79E+00 3.73E+00 5.67E+00 9.57E+00 

Season

 Fall 449000 17 4.20 * * * * * * * * * * * *

 Spring 336000 27 4.12 1.35E+00 2.94E-01 9.88E-02 9.88E-02 2.38E-01 3.27E-01 4.43E-01 6.08E-01 1.68E+00 4.68E+00 5.61E+00 5.67E+00

 Summer 139000 4 1.74 * * * * * * * * * * * *

 Winter 103000 7 1.12 * * * * * * * * * * * * 

Urbanization

 Central City 528000 21 4.38 2.03E+00 5.25E-01 3.27E-01 3.27E-01 4.33E-01 5.29E-01 7.12E-01 1.45E+00 1.85E+00 3.73E+00 9.57E+00 9.57E+00

 Nonmetropolitan 81000 9 1.33 * * * * * * * * * * * *

 Suburban 418000 25 2.33 1.09E+00 2.49E-01 1.84E-01 1.84E-01 2.01E-01 2.10E-01 3.08E-01 5.87E-01 1.21E+00 2.90E+00 4.68E+00 5.61E+00 

Response to Questionnaire *

 Households who fish 983000 53 12.99 1.63E+00 2.81E-01 9.88E-02 1.60E-01 2.01E-01 2.18E-01 5.47E-01 9.64E-01 1.79E+00 3.73E+00 5.67E+00 9.57E+00 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-28. Consumer Only Intake of Home Produced Dairy (g/kg-day) - All Regions 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 1409000 89 0.75 1.40E+01 1.62E+00 1.80E-01 4.46E-01 5.08E-01 3.18E+00 1.02E+01 1.95E+01 3.42E+01 4.40E+01 7.26E+01 1.11E+02 

Age

 01-02 79000 6 1.39 * * * * * * * * * * * *

 03-05 57000 5 0.70 * * * * * * * * * * * *

 06-11 264000 16 1.58 * * * * * * * * * * * *

 12-19 84000 5 0.41 * * * * * * * * * * * *

 20-39 612000 36 0.99 7.41E+00 1.02E+00 2.05E-01 3.96E-01 4.46E-01 1.89E+00 6.46E+00 1.21E+01 1.54E+01 1.95E+01 2.30E+01 2.30E+01

 40-69 216000 16 0.38 * * * * * * * * * * * *

 70 + 77000 3 0.48 * * * * * * * * * * * * 

Seasons

 Fall 211000 7 0.44 * * * * * * * * * * * *

 Spring 253000 27 0.55 1.78E+01 4.27E+00 6.28E-01 6.54E-01 6.72E-01 5.06E+00 1.22E+01 1.95E+01 5.09E+01 8.01E+01 1.11E+02 1.11E+02

 Summer 549000 22 1.21 1.53E+01 2.73E+00 4.46E-01 4.46E-01 5.08E-01 5.36E+00 1.06E+01 2.51E+01 3.49E+01 3.67E+01 4.68E+01 4.68E+01

 Winter 396000 33 0.81 8.08E+00 1.99E+00 1.80E-01 2.05E-01 2.80E-01 7.36E-01 5.47E+00 1.15E+01 1.98E+01 2.04E+01 7.26E+01 7.26E+01 

Urbanizations

 Central City 115000 7 0.20 * * * * * * * * * * * *

 Nonmetropolitan 988000 59 2.19 1.68E+01 2.10E+00 4.79E-01 9.58E-01 1.89E+00 6.74E+00 1.08E+01 2.04E+01 3.49E+01 4.40E+01 8.01E+01 1.11E+02

 Suburban 306000 23 0.35 9.86E+00 2.38E+00 3.96E-01 3.96E-01 4.46E-01 5.71E-01 5.36E+00 1.31E+01 2.81E+01 2.89E+01 5.09E+01 5.09E+01 

Race

 Black 0 0 0.00

 White 1382000 86 0.88 1.43E+01 1.65E+00 1.80E-01 4.46E-01 5.08E-01 3.82E+00 1.03E+01 1.95E+01 3.42E+01 4.40E+01 8.01E+01 1.11E+02 

Response to Questionnaire

 Households who raise animals 1228000 80 12.16 1.59E+01 1.73E+00 1.80E-01 3.96E-01 1.89E+00 6.13E+00 1.08E+01 1.96E+01 3.49E+01 4.40E+01 8.01E+01 1.11E+02

 Households who farm 1020000 63 13.92 1.71E+01 1.99E+00 3.96E-01 7.36E-01 3.18E+00 9.06E+00 1.21E+01 2.04E+01 3.49E+01 4.40E+01 8.01E+01 1.11E+02 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-29. Consumer Only Intake of Home Produced Dairy (g/kg-day) - Northeast 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 312000 16 0.76 * * * * * * * * * * * * 

Seasons

 Fall 48000 2 0.51 * * * * * * * * * * * *

 Spring 36000 4 0.34 * * * * * * * * * * * *

 Summer 116000 4 1.23 * * * * * * * * * * * *

 Winter 112000 6 0.95 * * * * * * * * * * * * 

Urbanizations

 Central City 0 0 0.00

 Nonmetropolitan 240000 10 4.35 * * * * * * * * * * * *

 Suburban 72000 6 0.28 * * * * * * * * * * * * 

Response to Questionnaire 

Households who raise animals 312000 16 26.49 * * * * * * * * * * * *

 Households who farm 312000 16 37.59 * * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-30. Consumer Only Intake of Home Produced Dairy (g/kg-day) - Midwest 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 594000 36 1.28 1.86E+01 3.15E+00 4.46E-01 4.46E-01 1.97E+00 8.27E+00 1.24E+01 2.30E+01 4.40E+01 4.68E+01 1.11E+02 1.11E+02 

Seasons

 Fall 163000 5 1.13 * * * * * * * * * * * *

 Spring 94000 12 0.88 * * * * * * * * * * * *

 Summer 252000 11 2.46 * * * * * * * * * * * *

 Winter 85000 8 0.76 * * * * * * * * * * * * 

Urbanizations

 Central City 43000 1 0.25 * * * * * * * * * * * *

 Nonmetropolitan 463000 31 3.24 2.33E+01 3.40E+00 4.25E+00 8.27E+00 9.06E+00 1.21E+01 1.60E+01 3.14E+01 4.40E+01 4.68E+01 1.11E+02 1.11E+02

 Suburban 88000 4 0.60 * * * * * * * * * * * * 

Response to Questionnaire 

Households who raise animals 490000 32 13.09 2.23E+01 3.33E+00 4.25E+00 5.36E+00 8.27E+00 1.08E+01 1.54E+01 3.14E+01 4.40E+01 4.68E+01 1.11E+02 1.11E+02

 Households who farm 490000 32 18.28 2.23E+01 3.33E+00 4.25E+00 5.36E+00 8.27E+00 1.08E+01 1.54E+01 3.14E+01 4.40E+01 4.68E+01 1.11E+02 1.11E+02 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-31. Consumer Only Intake of Home Produced Dairy (g/kg-day) - South 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P

Total 242000 17 0.38 * * * * * * * * * * * 

Seasons 

Fall 0 0 0.00

 Spring 27000 3 0.16 * * * * * * * * * * * 

 Summer 131000 5 0.74 * * * * * * * * * * * 

 Winter 84000 9 0.51 * * * * * * * * * * * 

Urbanizations

 Central City 27000 3 0.16 * * * * * * * * * * * 

 Nonmetropolitan 215000 14 1.13 * * * * * * * * * * * 

 Suburban 0 0 0.00 

Response to Questionnaire

 Households who raise animals 215000 14 8.26 * * * * * * * * * * * 

 Households who farm 148000 8 6.63 * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-32. Consumer Only Intake of Home Produced Dairy (g/kg-day) - West 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 261000 20 0.72 1.00E+01 2.75E+00 1.80E-01 1.80E-01 2.05E-01 5.08E-01 6.10E+00 1.33E+01 2.81E+01 2.89E+01 5.09E+01 5.09E+01 

Seasons 

Fall 0 0 0.00

 Spring 96000 8 1.18 * * * * * * * * * * * *

 Summer 50000 2 0.63 * * * * * * * * * * * *

 Winter 115000 10 1.25 * * * * * * * * * * * * 

Urbanizations

 Central City 45000 3 0.37 * * * * * * * * * * * *

 Nonmetropolitan 70000 4 1.15 * * * * * * * * * * * *

 Suburban 146000 13 0.81 * * * * * * * * * * * * 

Response to Questionnaire 

Households who raise animals 211000 18 8.20 * * * * * * * * * * * *

 Households who farm 70000 7 4.41 * * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-33. Seasonally Adjusted Consumer Only Homegrown Intake (g/kg-day) 

Population 

Group 

Percent 

Consuming 

P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total Vegetables 

Northeast 16.50 1.16E-03 1.59E-02 3.56E-02 1.99E-01 4.55E-01 1.37E+00 3.32E+00 5.70E+00 8.78E+00 1.01E+01 

Midwest 33.25 3.69E-03 4.11E-02 8.26E-02 2.91E-01 8.11E-01 1.96E+00 4.40E+00 7.41E+00 1.31E+00 2.01E+01 

South 24.00 4.78E-03 3.24E-02 5.58E-02 2.05E-01 6.10E-01 1.86E+00 3.95E+00 5.63E+00 1.20E+01 1.62E+01 

West 23.75 1.80E-03 1.91E-02 3.83E-02 1.14E-01 4.92E-01 1.46E+00 2.99E+00 5.04E+00 8.91E+00 1.12E+01 

All Regions 24.60 5.00E-03 2.90E-02 5.90E-02 2.19E-01 6.38E-01 1.80E+00 4.00E+00 6.08E+00 1.17E+01 2.01E+01 

Total Fruit 

Northeast 3.50 3.96E-03 1.97E-02 4.76E-02 1.73E-01 3.61E-01 6.55E-01 1.48E+00 3.00E+00 5.10E+00 5.63E+00 

Midwest 12.75 1.22E-03 7.01E-03 1.46E-02 1.36E-01 7.87E-01 2.98E+00 5.79E+00 9.52E+00 2.22E+01 2.71E+01 

South 8.00 6.13E-03 3.23E-02 1.09E-01 3.84E-01 9.47E-01 2.10E+00 6.70+00 1.02E+01 1.49E+01 1.64E+01 

West 17.75 5.50E-04 5.66E-02 8.82E-02 2.87E-01 6.88E-01 1.81E+00 4.75E+00 8.54E+00 1.45E+01 1.84E+01 

All Regions 10.10 2.00E-03 1.90E-02 6.20E-02 2.50E-01 7.52E-01 2.35E+00 5.61E+00 9.12E+00 1.76E+01 2.71E+01 

Total Meat 

Northeast 6.25 3.78E-03 3.01E-02 7.94E-02 1.25E-01 2.11E-01 7.00E-01 1.56E+00 1.91E+00 4.09E+00 4.80E+00 

Midwest 9.25 1.77E-03 3.68E-02 2.21E-01 5.25E-02 1.61E+00 3.41E+00 5.25E+00 7.45E+00 1.19E+01 1.36E+01 

South 5.75 6.12E-03 2.88E-02 5.02E-02 1.86E-01 5.30E-01 1.84E+00 3.78E+00 4.95E+00 8.45E+00 9.45E+00 

West 9.50 7.24E-04 2.83E-02 9.56E-02 2.35E-01 5.64E-01 1.30E+00 2.29E+00 3.38E+00 7.20E+00 9.10E+00 

All Regions 7.40 3.20E-03 3.90E-02 9.20E-02 2.20E-01 6.55E-01 1.96E+00 4.05E+00 5.17E+00 9.40E+00 1.36E+01 
Table 13-34. Consumer Only Intake of Homegrown Apples (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 5306000 272 2.82 1.19E+00 7.58E-02 8.34E-02 2.30E-01 2.84E-01 4.50E-01 8.17E-01 1.47E+00 2.38E+00 3.40E+00 5.42E+00 1.01E+0

Age

 01-02 199000 12 3.49 * * * * * * * * * * * *

 03-05 291000 16 3.59 * * * * * * * * * * * *

 06-11 402000 25 2.41 1.28E+00 1.88E-01 4.72E-01 4.72E-01 5.63E-01 7.40E-01 9.56E-01 1.29E+00 2.98E+00 4.00E+00 4.00E+00 4.00E+0

 12-19 296000 12 1.44 * * * * * * * * * * * *

 20-39 1268000 61 2.06 7.95E-01 1.07E-01 1.85E-01 2.30E-01 2.56E-01 3.04E-01 6.02E-01 9.22E-01 1.55E+00 1.97E+00 5.42E+00 5.42E+0

 40-69 1719000 90 3.03 9.61E-01 1.37E-01 5.57E-02 8.94E-02 2.55E-01 3.98E-01 6.48E-01 1.08E+00 1.59E+00 2.38E+00 9.83E+00 9.83E+0

 70 + 1061000 52 6.68 1.45E+00 1.41E-01 1.99E-01 2.60E-01 4.46E-01 6.27E-01 1.18E+00 1.82E+00 3.40E+00 3.62E+00 4.20E+00 4.20E+0

Season

 Fall 1707000 60 3.58 1.28E+00 1.24E-01 2.56E-01 2.95E-01 3.20E-01 5.83E-01 1.03E+00 1.66E+00 2.69E+00 3.40E+00 4.25E+00 4.25E+0

 Spring 639000 74 1.38 9.50E-01 1.14E-01 1.94E-01 2.38E-01 2.84E-01 3.76E-01 5.67E-01 1.10E+00 2.00E+00 2.78E+00 5.87E+00 5.87E+0

 Summer 1935000 68 4.25 1.12E+00 1.69E-01 5.57E-02 8.94E-02 1.86E-01 3.98E-01 6.92E-01 1.41E+00 2.29E+00 2.98E+00 9.83E+00 9.83E+0

 Winter 1025000 70 2.10 1.30E+00 1.78E-01 1.85E-01 2.30E-01 3.23E-01 5.71E-01 8.81E-01 1.59E+00 2.75E+00 3.40E+00 1.01E+01 1.01E+0

Urbanization

 Central City 912000 30 1.62 1.24E+00 2.60E-01 2.31E-01 2.56E-01 3.92E-01 5.10E-01 9.17E-01 1.59E+00 2.19E+00 2.26E+00 1.01E+01 1.01E+0

 Nonmetropolitan 2118000 122 4.70 1.27E+00 1.26E-01 5.57E-02 1.18E-01 2.49E-01 4.11E-01 9.00E-01 1.55E+00 2.92E+00 3.48E+00 9.83E+00 9.83E+0

 Suburban 2276000 120 2.63 1.09E+00 9.16E-02 1.86E-01 2.37E-01 2.91E-01 4.37E-01 7.74E-01 1.29E+00 2.29E+00 3.40E+00 5.42E+00 5.42E+0

Race

 Black 84000 4 0.39 * * * * * * * * * * * *

 White 5222000 268 3.31 1.18E+00 7.67E-02 8.34E-02 2.30E-01 2.79E-01 4.48E-01 7.98E-01 1.41E+00 2.38E+00 3.40E+00 5.42E+00 1.01E+0

Region

 Midwest 2044000 123 4.41 1.38E+00 1.45E-01 2.16E-01 2.85E-01 3.04E-01 5.20E-01 9.23E-01 1.61E+00 2.69E+00 3.40E+00 9.83E+00 1.01E+0

 Northeast 442000 18 1.07 * * * * * * * * * * * *

 South 1310000 65 2.04 1.10E+00 1.07E-01 1.99E-01 2.38E-01 3.01E-01 4.39E-01 9.17E-01 1.38E+00 1.90E+00 2.98E+00 4.00E+00 4.91E+0

 West 1510000 66 4.19 1.20E+00 1.29E-01 5.57E-02 1.86E-01 2.64E-01 4.72E-01 7.89E-01 1.82E+00 2.75E+00 3.62E+00 4.25E+00 4.25E+0

Response to Questionnaire

 Households who garden 4707000 246 6.91 1.21E+00 8.22E-02 1.27E-01 2.49E-01 2.95E-01 4.70E-01 8.17E-01 1.47E+00 2.38E+00 3.40E+00 5.87E+00 1.01E+0

 Households who farm 1299000 68 17.72 1.39E+00 1.31E-01 5.57E-02 3.57E-01 5.36E-01 7.03E-01 9.56E-01 1.58E+00 2.99E+00 4.00E+00 4.91E+00 5.87E+0

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distibution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-35. Consumer Only Intake of Homegrown Asparagus (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P

Total 763000 66 0.41 5.59E-01 5.12E-02 1.00E-01 1.41E-01 1.91E-01 2.75E-01 4.00E-01 7.07E-01 1.12E+00 1.63E+00 1.97E+00 1.9

Age

 01-02 8000 1 0.14 * * * * * * * * * * * 

 03-05 25000 3 0.31 * * * * * * * * * * * 

 06-11 31000 3 0.19 * * * * * * * * * * * 

 12-19 70000 5 0.34 * * * * * * * * * * * 

 20-39 144000 11 0.23 * * * * * * * * * * * 

 40-69 430000 38 0.76 4.65E-01 5.38E-02 1.10E-01 1.13E-01 1.81E-01 2.34E-01 4.00E-01 5.96E-01 8.84E-01 1.24E+00 1.75E+00 1.7

 70 + 55000 5 0.35 * * * * * * * * * * * 

Season

 Fall 62000 2 0.13 * * * * * * * * * * * 

 Spring 608000 59 1.32 6.12E-01 5.75E-02 1.00E-01 1.57E-01 1.91E-01 2.98E-01 4.46E-01 8.8/.4E-01 1.18E+00 1.63E+00 1.97E+00 1.9

 Summer 0 0 0.00

 Winter 93000 5 0.19 * * * * * * * * * * * 

Urbanization

 Central City 190000 9 0.34 * * * * * * * * * * * 

 Nonmetropolitan 215000 27 0.48 7.59E-01 1.19E-01 1.00E-01 1.13E-01 1.41E-01 2.30E-01 5.43E-01 1.24E+00 1.75E+00 1.92E+00 1.97E+00 1.9

 Suburban 358000 30 0.41 4.27E-01 4.05E-02 1.10E-01 1.69E-01 1.81E-01 2.75E-01 3.65E-01 5.79E-01 7.01E-01 9.31E-01 1.12E+00 1.1

Race

 Black 0 0 0.00

 White 763000 66 0.48 5.59E-01 5.12E-02 1.00E-01 1.41E-01 1.91E-01 2.75E-01 4.00E-01 7.07E-01 1.12E+00 1.63E+00 1.97E+00 1.9

Region

 Midwest 368000 33 0.79 4.78E-01 6.49E-02 1.00E-01 1.10E-01 1.41E-01 2.28E-01 4.00E-01 6.14E-01 9.31E-01 1.12E+00 1.97E+00 1.9

 Northeast 270000 20 0.66 7.17E-01 9.99E-02 1.81E-01 2.34E-01 2.34E-01 3.65E-01 5.96E-01 9.29E-01 1.24E+00 1.63E+00 1.92E+00 1.9

 South 95000 9 0.15 * * * * * * * * * * * 

 West 30000 4 0.08 * * * * * * * * * * * 

Response to Questionnaire

 Households who garden 669000 59 0.98 5.33E-01 5.50E-02 1.00E-01 1.41E-01 1.81E-01 2.75E-01 4.00E-01 6.99E-01 1.12E+00 1.63E+00 1.97E+00 1.9

 Households who farm 157000 16 2.14 * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-36. Consumer Only Intake of Home Produced Beef (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 4958000 304 2.64 2.45E+00 1.49E-01 1.83E-01 3.74E-01 4.65E-01 8.78E-01 1.61E+00 3.07E+00 5.29E+00 7.24E+00 1.33E+01 1.94E+01 

Age

 01-02 110000 8 1.93 * * * * * * * * * * * *

 03-05 234000 13 2.89 * * * * * * * * * * * *

 06-11 695000 38 4.16 3.77E+00 5.94E-01 3.54E-01 6.63E-01 7.53E-01 1.32E+00 2.11E+00 4.43E+00 1.14E+01 1.25E+01 1.33E+01 1.33E+01

 12-19 656000 41 3.20 1.72E+00 1.63E-01 3.78E-01 4.78E-01 5.13E-01 8.96E-01 1.51E+00 2.44E+00 3.53E+00 3.57E+00 4.28E+00 4.28E+00

 20-39 1495000 83 2.43 2.06E+00 2.00E-01 2.69E-01 3.52E-01 3.94E-01 6.80E-01 1.59E+00 2.73E+00 4.88E+00 6.50E+00 8.26E+00 8.26E+00

 40-69 1490000 105 2.63 1.84E+00 1.41E-01 1.83E-01 3.61E-01 4.55E-01 8.33E-01 1.52E+00 2.38E+00 4.10E+00 5.39E+00 5.90E+00 5.90E+00

 70 + 188000 11 1.18 * * * * * * * * * * * * 

Season

 Fall 1404000 55 2.95 1.55E+00 1.74E-01 1.83E-01 3.52E-01 3.61E-01 5.17E-01 1.33E+00 2.01E+00 2.86E+00 3.90E+00 7.24E+00 7.24E+00

 Spring 911000 108 1.97 2.32E+00 1.63E-01 2.70E-01 3.90E-01 5.10E-01 1.04E+00 1.96E+00 3.29E+00 4.22E+00 5.23E+00 8.62E+00 9.28E+00

 Summer 1755000 69 3.86 3.48E+00 4.12E-01 1.02E-01 6.08E-01 7.45E-01 1.02E+00 2.44E+00 4.43E+00 7.51E+00 1.14E+01 1.87E+01 1.87E+01

 Winter 888000 72 1.82 1.95E+00 2.75E-01 3.93E-02 3.75E-01 3.94E-01 6.74E-01 1.33E+00 2.14E+00 4.23E+00 5.39E+00 1.94E+01 1.94E+01 

Urbanization

 Central City 100000 5 0.18 * * * * * * * * * * * *

 Nonmetropolitan 3070000 194 6.82 2.80E+00 2.18E-01 1.83E-01 3.77E-01 4.99E-01 8.64E-01 1.81E+00 3.57E+00 6.03E+00 8.44E+00 1.87E+01 1.94E+01

 Suburban 1788000 105 2.07 1.93E+00 1.50E-01 2.67E-01 3.75E-01 4.16E-01 9.07E-01 1.52E+00 2.44E+00 4.06E+00 5.10E+00 7.51E+00 9.28E+00 

Race

 Black 0 0 0.00

 White 4950000 303 3.14 2.45E+00 1.50E-01 1.83E-01 3.74E-01 4.65E-01 8.78E-01 1.61E+00 3.07E+00 5.29E+00 7.24E+00 1.33E+01 1.94E+01 

Region

 Midwest 2261000 161 4.87 2.83E+00 2.31E-01 1.83E-01 3.54E-01 4.16E-01 8.47E-01 2.01E+00 3.66E+00 5.90E+00 8.39E+00 1.87E+01 1.87E+01

 Northeast 586000 25 1.42 1.44E+00 2.13E-01 3.52E-01 3.52E-01 4.73E-01 7.42E-01 1.06E+00 1.68E+00 2.62E+00 2.62E+00 6.03E+00 6.03E+00

 South 1042000 61 1.62 2.45E+00 3.46E-01 1.02E-01 3.90E-01 5.84E-01 8.16E-01 1.59E+00 2.41E+00 6.36E+00 7.24E+00 1.33E+01 1.33E+01

 West 1069000 57 2.96 2.20E+00 2.83E-01 3.13E-01 3.80E-01 5.56E-01 1.04E+00 1.60E+00 2.86E+00 4.06E+00 4.42E+00 7.51E+00 1.94E+01 

Response to Questionnaire 

Households who raise animals 3699000 239 36.63 2.66E+00 1.60E-01 1.83E-01 3.88E-01 6.63E-01 1.04E+00 1.83E+00 3.48E+00 5.39E+00 7.51E+00 1.25E+01 1.94E+01

 Households who farm 2850000 182 38.89 2.63E+00 1.96E-01 2.70E-01 3.94E-01 5.85E-01 8.96E-01 1.64E+00 3.25E+00 5.39E+00 7.51E+00 1.13E+01 1.94E+01 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-37. Consumer Only Intake of Homegrown Beets (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 2214000 125 1.18 5.12E-01 4.96E-02 3.21E-02 7.37E-02 1.09E-01 1.88E-01 3.97E-01 5.87E-01 1.03E+00 1.36E+00 3.69E+00 4.08E+00 

Age

 01-02 27000 2 0.47 * * * * * * * * * * * *

 03-05 51000 4 0.63 * * * * * * * * * * * *

 06-11 167000 10 1.00 * * * * * * * * * * * *

 12-19 227000 13 1.11 * * * * * * * * * * * *

 20-39 383000 22 0.62 3.81E-01 6.26E-02 7.57E-02 7.57E-02 1.22E-01 1.43E-01 2.85E-01 5.56E-01 9.99E-01 9.99E-01 1.12E+00 1.12E+00

 40-69 951000 51 1.68 4.28E-01 4.34E-02 5.00E-02 7.31E-02 7.46E-02 2.05E-01 3.97E-01 5.49E-01 9.25E-01 1.15E+00 1.40E+00 1.40E+00

 70 + 408000 23 2.57 5.80E-01 8.80E-02 3.21E-02 3.21E-02 4.76E-02 2.71E-01 4.49E-01 9.09E-01 1.36E+00 1.36E+00 1.59E+00 1.59E+00 

Season

 Fall 562000 21 1.18 5.45E-01 9.36E-02 3.21E-02 4.76E-02 5.00E-02 2.57E-01 3.56E-01 9.49E-01 1.36E+00 1.36E+00 1.40E+00 1.40E+00

 Spring 558000 55 1.21 4.70E-01 8.98E-02 7.46E-02 8.06E-02 1.09E-01 1.43E-01 2.73E-01 4.47E-01 8.73E-01 1.59E+00 4.08E+00 4.08E+00

 Summer 676000 22 1.49 3.85E-01 4.54E-02 7.57E-02 1.20E-01 1.22E-01 1.84E-01 3.97E-01 5.49E-01 6.24E-01 9.09E-01 9.09E-01 9.09E-01

 Winter 418000 27 0.86 7.30E-01 1.54E-01 7.31E-02 7.31E-02 7.37E-02 2.80E-01 5.20E-01 8.28E-01 1.13E+00 2.32E+00 3.69E+00 3.69E+00 

Urbanization

 Central City 651000 27 1.16 5.18E-01 1.15E-01 1.11E-01 1.35E-01 1.83E-01 2.57E-01 4.01E-01 5.49E-01 9.09E-01 1.12E+00 3.69E+00 3.69E+00

 Nonmetropolitan 758000 51 1.68 5.77E-01 9.06E-02 5.00E-02 7.31E-02 7.37E-02 1.80E-01 3.86E-01 6.61E-01 1.36E+00 1.40E+00 4.08E+00 4.08E+00

 Suburban 805000 47 0.93 4.45E-01 5.77E-02 3.21E-02 4.76E-02 8.06E-02 1.43E-01 3.97E-01 5.56E-01 9.25E-01 9.99E-01 2.32E+00 2.32E+00 

Race

 Black 0 0 0.00

 White 2186000 124 1.39 5.18E-01 4.99E-02 3.21E-02 7.46E-02 1.13E-01 2.05E-01 3.97E-01 5.87E-01 1.03E+00 1.36E+00 3.69E+00 4.08E+00 

Region

 Midwest 885000 53 1.91 6.30E-01 7.93E-02 5.00E-02 1.13E-01 1.83E-01 3.15E-01 4.54E-01 9.09E-01 1.15E+00 1.36E+00 3.69E+00 3.69E+00

 Northeast 230000 13 0.56 * * * * * * * * * * * *

 South 545000 31 0.85 4.51E-01 1.17E-01 7.46E-02 7.57E-02 8.06E-02 1.80E-01 2.64E-01 4.84E-01 6.61E-01 9.44E-01 4.08E+00 4.08E+00

 West 554000 28 1.54 3.96E-01 7.75E-02 3.21E-02 4.76E-02 7.31E-02 1.21E-01 2.86E-01 5.49E-01 6.24E-01 7.04E-01 2.32E+00 2.32E+00 

Response to Questionnaire

 Households who garden 2107000 120 3.09 5.26E-01 5.16E-02 3.21E-02 7.37E-02 9.56E-02 2.05E-01 4.01E-01 6.06E-01 1.03E+00 1.36E+00 3.69E+00 4.08E+00

 Households who farm 229000 11 3.12 * * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-38. Consumer Only Intake of Homegrown Broccoli (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 

Total 1745000 80 0.93 4.20E-01 4.75E-02 7.61E-02 8.24E-02 1.56E-01 1.96E-01 2.90E-01 4.59E-01 8.15E-01 9.74E-01 2.48E+00 

Age

 01-02 0 0 0.00

 03-05 13000 1 0.16 * * * * * * * * * * * 

 06-11 187000 9 1.12 * * * * * * * * * * * 

 12-19 102000 4 0.50 * * * * * * * * * * * 

 20-39 486000 19 0.79 * * * * * * * * * * * 

 40-69 761000 37 1.34 4.12E-01 6.50E-02 8.24E-02 1.06E-01 1.64E-01 2.22E-01 3.51E-01 4.61E-01 6.14E-01 8.15E-01 3.02E+00 

 70 + 196000 10 1.23 * * * * * * * * * * * 

Season

 Fall 624000 20 1.31 2.87E-01 3.70E-02 7.99E-02 7.99E-02 8.24E-02 1.75E-01 2.31E-01 3.79E-01 4.52E-01 5.29E-01 8.15E-01 

 Spring 258000 27 0.56 5.43E-01 1.18E-01 4.50E-02 1.54E-01 1.70E-01 2.65E-01 3.31E-01 5.89E-01 1.25E+00 2.37E+00 3.02E+00 

 Summer 682000 22 1.50 5.08E-01 1.05E-01 7.61E-02 1.29E-01 1.78E-01 2.15E-01 3.99E-01 6.61E-01 8.86E-01 9.74E-01 2.48E+00 

 Winter 181000 11 0.37 * * * * * * * * * * * 

Urbanization

 Central City 165000 5 0.29 * * * * * * * * * * * 

 Nonmetropolitan 647000 34 1.44 4.23E-01 4.21E-02 4.50E-02 1.29E-01 1.70E-01 2.23E-01 3.69E-01 5.89E-01 7.47E-01 8.86E-01 9.74E-01 

 Suburban 933000 41 1.08 4.29E-01 8.26E-02 7.99E-02 8.24E-02 1.44E-01 2.13E-01 2.44E-01 4.41E-01 6.84E-01 2.37E+00 2.48E+00 

Race

 Black 0 0 0.00

 White 1719000 79 1.09 4.22E-01 4.81E-02 7.61E-02 8.24E-02 1.56E-01 1.96E-01 2.88E-01 4.59E-01 8.15E-01 9.74E-01 2.48E+00 

Region

 Midwest 792000 38 1.71 2.63E-01 5.86E-02 7.61E-02 7.99E-02 8.24E-02 1.75E-01 2.13E-01 2.75E-01 3.44E-01 4.03E-01 3.02E+00 

 Northeast 427000 19 1.04 * * * * * * * * * * * 

 South 373000 16 0.58 * * * * * * * * * * * 

 West 153000 7 0.42 * * * * * * * * * * * 

Response to Questionnaire

 Households who garden 1729000 78 2.54 4.22E-01 4.83E-02 7.61E-02 8.24E-02 1.64E-01 1.96E-01 2.90E-01 4.59E-01 8.15E-01 9.74E-01 2.48E+00 

 Households who farm 599000 29 8.17 4.66E-01 8.37E-02 4.50E-02 7.61E-02 1.54E-01 1.95E-01 3.10E-01 6.61E-01 8.86E-01 9.74E-01 3.02E+00 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distibution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-39. Consumer Only Intake of Homegrown Cabbage (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P10

Total 2019000 89 1.07 1.03E+00 1.00E-01 1.07E-01 2.03E-01 3.17E-01 4.21E-01 7.76E-01 1.33E+00 1.97E+00 2.35E+00 5.43E+00 5.43E

Age

 01-02 14000 2 0.25 * * * * * * * * * * * *

 03-05 29000 1 0.36 * * * * * * * * * * * *

 06-11 61000 3 0.37 * * * * * * * * * * * *

 12-19 203000 9 0.99 * * * * * * * * * * * *

 20-39 391000 16 0.63 * * * * * * * * * * * *

 40-69 966000 44 1.70 1.14E+00 1.80E-01 2.17E-01 2.22E-01 3.25E-01 4.08E-01 7.13E-01 1.41E+00 1.82E+00 5.29E+00 5.43E+00 5.43E

 70 + 326000 13 2.05 * * * * * * * * * * * * 

Season

 Fall 570000 21 1.20 1.28E+00 3.24E-01 1.86E-01 1.86E-01 2.03E-01 3.85E-01 5.42E-01 1.49E+00 5.29E+00 5.43E+00 5.43E+00 5.43E

 Spring 126000 15 0.27 * * * * * * * * * * * *

 Summer 1142000 39 2.51 9.65E-01 9.35E-02 2.01E-01 2.22E-01 3.25E-01 5.55E-01 8.28E-01 1.24E+00 1.79E+00 2.35E+00 2.77E+00 2.77E

 Winter 181000 14 0.37 * * * * * * * * * * * * 

Urbanization

 Central City 157000 5 0.28 * * * * * * * * * * * *

 Nonmetropolitan 1079000 48 2.40 9.37E-01 8.83E-02 2.01E-01 3.17E-01 3.40E-01 4.54E-01 7.13E-01 1.33E+00 1.79E+00 2.35E+00 2.77E+00 2.77E

 Suburban 783000 36 0.90 1.26E+00 2.11E-01 3.20E-02 2.22E-01 3.25E-01 4.49E-01 1.05E+00 1.37E+00 2.17E+00 5.29E+00 5.43E+00 5.43E

Race

 Black 7000 1 0.03 * * * * * * * * * * * *

 White 1867000 83 1.19 1.05E+00 1.07E-01 1.07E-01 2.03E-01 2.46E-01 4.13E-01 7.88E-01 1.37E+00 1.97E+00 2.35E+00 5.43E+00 5.43E

Region

 Midwest 884000 37 1.91 7.42E-01 7.35E-02 1.07E-01 1.86E-01 2.22E-01 3.55E-01 5.95E-01 1.10E+00 1.29E+00 1.49E+00 1.82E+00 1.98E

 Northeast 277000 11 0.67 * * * * * * * * * * * *

 South 616000 32 0.96 1.11E+00 1.34E-01 3.20E-02 2.01E-01 2.17E-01 4.49E-01 8.50E-01 1.79E+00 2.17E+00 2.35E+00 2.77E+00 2.77E

 West 242000 9 0.67 * * * * * * * * * * * * 

Response to Questionnaire

 Households who garden 1921000 86 2.82 1.07E+00 1.03E-01 1.07E-01 2.03E-01 3.17E-01 4.54E-01 7.88E-01 1.37E+00 1.97E+00 2.35E+00 5.43E+00 5.43E

 Households who farm 546000 26 7.45 9.96E-01 1.15E-01 2.01E-01 2.06E-01 3.51E-01 5.87E-01 8.28E-01 1.37E+00 1.79E+00 2.35E+00 2.35E+00 2.35E

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-40. Consumer Only Intake of Homegrown Carrots (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 4322000 193 2.30 4.38E-01 4.29E-02 4.12E-02 6.35E-02 9.23E-02 1.79E-01 3.28E-01 5.25E-01 7.95E-01 1.08E+00 2.21E+00 7.79E+00 

Age

 01-02 51000 4 0.89 * * * * * * * * * * * *

 03-05 53000 3 0.65 * * * * * * * * * * * *

 06-11 299000 14 1.79 * * * * * * * * * * * *

 12-19 389000 17 1.90 * * * * * * * * * * * *

 20-39 1043000 46 1.69 2.83E-01 3.46E-02 4.47E-02 5.02E-02 8.00E-02 1.20E-01 1.99E-01 4.09E-01 5.64E-01 7.56E-01 1.19E+00 1.19E+00

 40-69 1848000 82 3.26 4.25E-01 3.42E-02 3.90E-02 6.74E-02 1.23E-01 2.15E-01 3.67E-01 5.50E-01 7.76E-01 1.01E+00 1.53E+00 2.21E+00

 70 + 574000 24 3.61 4.44E-01 5.50E-02 7.39E-02 1.79E-01 1.96E-01 2.60E-01 3.70E-01 5.39E-01 9.64E-01 1.08E+00 1.08E+00 1.08E+00 

Season

 Fall 1810000 66 3.80 4.61E-01 9.77E-02 9.09E-02 1.10E-01 1.20E-01 1.99E-01 3.08E-01 5.09E-01 7.76E-01 1.08E+00 1.71E+00 7.79E+00

 Spring 267000 28 0.58 5.55E-01 1.01E-01 1.39E-01 1.49E-01 2.02E-01 2.16E-01 3.92E-01 6.09E-01 9.94E-01 2.11E+00 2.94E+00 2.94E+00

 Summer 1544000 49 3.39 3.88E-01 3.95E-02 4.12E-02 5.02E-02 6.74E-02 1.64E-01 3.76E-01 5.13E-01 8.40E-01 9.64E-01 1.19E+00 1.19E+00

 Winter 701000 50 1.44 4.44E-01 7.44E-02 3.90E-02 4.34E-02 6.35E-02 1.56E-01 2.25E-01 6.40E-01 1.05E+00 1.53E+00 3.06E+00 3.06E+00 

Urbanization

 Central City 963000 29 1.71 2.82E-01 3.86E-02 3.90E-02 6.35E-02 8.00E-02 1.63E-01 2.09E-01 3.85E-01 5.25E-01 5.88E-01 9.64E-01 9.64E-01

 Nonmetropolitan 1675000 94 3.72 5.18E-01 8.98E-02 4.12E-02 5.36E-02 6.81E-02 2.00E-01 3.28E-01 5.13E-01 9.55E-01 1.19E+00 7.79E+00 7.79E+00

 Suburban 1684000 70 1.94 4.48E-01 4.02E-02 6.74E-02 9.09E-02 1.16E-01 2.02E-01 3.77E-01 6.35E-01 7.95E-01 1.09E+00 1.71E+00 1.71E+00 

Race

 Black 107000 7 0.49 * * * * * * * * * * * *

 White 3970000 178 2.52 4.13E-01 2.58E-02 4.34E-02 7.96E-02 1.11E-01 1.94E-01 3.33E-01 5.27E-01 7.76E-01 1.01E+00 1.59E+00 3.06E+00 

Region

 Midwest 2001000 97 4.31 4.57E-01 3.99E-02 3.90E-02 8.00E-02 1.37E-01 2.00E-01 3.73E-01 5.39E-01 9.55E-01 1.10E+00 2.11E+00 3.06E+00

 Northeast 735000 29 1.79 4.05E-01 8.79E-02 4.12E-02 5.36E-02 6.15E-02 9.34E-02 1.49E-01 6.35E-01 1.09E+00 1.71E+00 2.21E+00 2.21E+00

 South 378000 20 0.59 6.27E-01 3.60E-01 4.47E-02 4.47E-02 5.02E-02 1.49E-01 2.72E-01 4.09E-01 5.02E-01 9.94E-01 7.79E+00 7.79E+00

 West 1208000 47 3.35 3.68E-01 3.24E-02 6.74E-02 9.11E-02 1.43E-01 1.90E-01 3.33E-01 4.59E-01 7.56E-01 8.40E-01 9.64E-01 9.64E-01 

Response to Questionnaire

 Households who garden 4054000 182 5.95 4.04E-01 2.67E-02 4.12E-02 6.81E-02 9.34E-02 1.79E-01 3.28E-01 5.09E-01 7.62E-01 1.08E+00 1.71E+00 3.06E+00

 Households who farm 833000 40 11.37 3.60E-01 5.95E-02 9.09E-02 9.34E-02 1.10E-01 1.79E-01 2.28E-01 4.59E-01 6.19E-01 1.19E+00 2.11E+00 2.94E+00 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA' analyses of the 1987-88 NFCS 
Table 13-41. Consumer Only Intake of Homegrown Corn (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P1

Total 6891000 421 3.67 8.92E-01 6.48E-02 5.15E-02 1.22E-01 1.65E-01 2.44E-01 4.80E-01 9.07E-01 1.88E+00 3.37E+00 7.44E+00 9.23E

Age

 01-02 205000 13 3.60 * * * * * * * * * * * *

 03-05 313000 24 3.86 1.25E+00 2.57E-01 3.25E-01 3.25E-01 4.00E-01 5.98E-01 1.00E+00 1.21E+00 1.67E+00 5.35E+00 5.35E+00 5.35E

 06-11 689000 43 4.12 9.32E-01 1.66E-01 1.10E-01 1.19E-01 1.89E-01 2.52E-01 5.13E-01 1.08E+00 3.13E+00 3.37E+00 4.52E+00 4.52E

 12-19 530000 32 2.59 5.92E-01 9.56E-02 9.87E-02 1.05E-01 1.35E-01 2.12E-01 3.43E-01 7.11E-01 1.55E+00 1.88E+00 1.88E+00 1.88E

 20-39 1913000 108 3.11 5.97E-01 6.00E-02 6.59E-02 1.41E-01 1.52E-01 2.08E-01 3.71E-01 7.08E-01 1.53E+00 2.04E+00 3.70E+00 3.70E

 40-69 2265000 142 3.99 8.64E-01 1.05E-01 1.13E-01 1.52E-01 1.66E-01 2.55E-01 5.16E-01 8.83E-01 1.42E+00 3.22E+00 7.44E+00 7.44E

 70 + 871000 53 5.48 9.43E-01 2.59E-01 3.91E-02 5.15E-02 1.05E-01 1.88E-01 3.64E-01 7.57E-01 1.34E+00 6.49E+00 9.23E+00 9.23E

Season

 Fall 2458000 89 5.16 5.44E-01 8.37E-02 3.91E-02 1.05E-01 1.42E-01 1.88E-01 3.17E-01 5.46E-01 1.27E+00 1.42E+00 5.35E+00 5.69E

 Spring 1380000 160 2.99 6.35E-01 5.57E-02 1.42E-01 1.68E-01 1.93E-01 2.64E-01 4.48E-01 7.68E-01 1.21E+00 1.57E+00 5.15E+00 6.68E

 Summer 1777000 62 3.91 1.82E+00 2.62E-01 6.59E-02 1.78E-01 3.43E-01 6.44E-01 9.36E-01 2.13E+00 4.52E+00 6.84E+00 9.23E+00 9.23E

 Winter 1276000 110 2.62 5.45E-01 4.67E-02 1.14E-01 1.20E-01 1.49E-01 2.22E-01 4.05E-01 6.14E-01 1.16E+00 1.47E+00 2.04E+00 3.94E

Urbanization

 Central City 748000 27 1.33 7.37E-01 1.41E-01 3.91E-02 3.91E-02 5.15E-02 1.77E-01 5.46E-01 9.29E-01 2.04E+00 2.23E+00 3.04E+00 3.04E

 Nonmetropolitan 4122000 268 9.16 9.63E-01 8.18E-02 7.40E-02 1.22E-01 1.66E-01 2.49E-01 5.31E-01 1.00E+00 2.13E+00 3.38E+00 7.44E+00 8.97E

 Suburban 2021000 126 2.33 8.04E-01 1.30E-01 1.05E-01 1.53E-01 1.66E-01 2.39E-01 3.96E-01 6.47E-01 1.34E+00 1.71E+00 9.23E+00 9.23E

Race

 Black 188000 9 0.86 * * * * * * * * * * * *

 White 6703000 412 4.26 8.87E-01 6.51E-02 5.15E-02 1.22E-01 1.63E-01 2.37E-01 4.80E-01 8.84E-01 1.88E+00 3.22E+00 7.44E+00 9.23E

Region

 Midwest 2557000 188 5.51 9.34E-01 9.74E-02 3.91E-02 1.19E-01 1.68E-01 2.47E-01 4.56E-01 9.29E-01 2.28E+00 3.22E+00 6.84E+00 7.44E

 Northeast 586000 33 1.42 6.14E-01 8.42E-02 9.87E-02 1.66E-01 1.86E-01 2.44E-01 3.81E-01 8.83E-01 1.34E+00 1.71E+00 1.71E+00 1.71E

 South 2745000 153 4.27 8.73E-01 9.52E-02 7.40E-02 1.22E-01 1.66E-01 2.83E-01 5.61E-01 9.35E-01 1.55E+00 3.37E+00 5.69E+00 8.97E

 West 1003000 47 2.78 9.99E-01 2.77E-01 1.05E-01 1.47E-01 1.52E-01 1.77E-01 3.96E-01 7.45E-01 2.23E+00 6.49E+00 9.23E+00 9.23E

Response to Questionnaire

 Households who garden 6233000 387 9.15 8.75E-01 6.30E-02 5.15E-02 1.35E-01 1.65E-01 2.44E-01 5.02E-01 9.14E-01 1.82E+00 3.13E+00 6.84E+00 9.23E

 Households who farm 1739000 114 23.73 1.20E+00 1.77E-01 3.91E-02 1.08E-01 1.66E-01 2.29E-01 3.81E-01 9.74E-01 3.37E+00 6.49E+00 9.23E+00 9.23E

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distributions 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-42. Consumer Only Intake of Homegrown Cucumbers (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 3994000 141 2.12 1.02E+00 1.55E-01 3.08E-02 6.71E-02 1.08E-01 2.40E-01 5.40E-01 1.13E+00 2.11E+00 2.79E+00 1.34E+01 1.37E+01 

Age

 01-02 132000 5 2.32 * * * * * * * * * * * *

 03-05 107000 4 1.32 * * * * * * * * * * * *

 06-11 356000 12 2.13 * * * * * * * * * * * *

 12-19 254000 10 1.24 * * * * * * * * * * * *

 20-39 864000 29 1.40 5.04E-01 9.27E-02 3.08E-02 5.45E-02 6.31E-02 1.83E-01 3.09E-01 6.17E-01 1.35E+00 1.49E+00 2.12E+00 2.12E+00

 40-69 1882000 68 3.32 1.33E+00 3.01E-01 4.16E-02 7.46E-02 1.76E-01 3.93E-01 6.84E-01 1.29E+00 2.11E+00 3.27E+00 1.37E+01 1.37E+01

 70 + 399000 13 2.51 * * * * * * * * * * * * 

Season

 Fall 370000 12 0.78 * * * * * * * * * * * *

 Spring 197000 15 0.43 * * * * * * * * * * * *

 Summer 3427000 114 7.53 1.06E+00 1.83E-01 0.00E+00 7.46E-02 1.08E-01 2.42E-01 5.18E-01 1.13E+00 2.12E+00 2.79E+00 1.34E+01 1.37E+01

 Winter 0 0 0.00 

Urbanization

 Central City 640000 18 1.14 * * * * * * * * * * * *

 Nonmetropolitan 1530000 64 3.40 1.74E+00 3.43E-01 1.01E-01 1.21E-01 1.90E-01 3.86E-01 1.06E+00 1.67E+00 3.09E+00 4.50E+00 1.37E+01 1.37E+01

 Suburban 1824000 59 2.11 6.71E-01 7.52E-02 0.00E+00 7.46E-02 1.62E-01 2.78E-01 4.99E-01 8.33E-01 1.34E+00 1.73E+00 3.27E+00 3.27E+00 

Race

 Black 86000 2 0.40 * * * * * * * * * * * *

 White 3724000 132 2.36 9.35E-01 1.62E-01 3.08E-02 6.31E-02 1.01E-01 2.22E-01 5.01E-01 1.03E+00 1.49E+00 2.40E+00 1.34E+01 1.37E+01 

Region

 Midwest 969000 31 2.09 1.00E+00 3.92E-01 3.08E-02 4.16E-02 5.45E-02 1.35E-01 4.53E-01 1.03E+00 2.35E+00 2.45E+00 1.34E+01 1.34E+01

 Northeast 689000 22 1.67 1.92E+00 6.78E-01 2.33E-01 2.78E-01 2.78E-01 4.75E-01 6.84E-01 1.53E+00 4.18E+00 1.17E+01 1.37E+01 1.37E+01

 South 1317000 54 2.05 8.85E-01 1.05E-01 0.00E+00 1.21E-01 1.83E-01 2.87E-01 7.53E-01 1.28E+00 1.73E+00 2.13E+00 4.50E+00 4.50E+00

 West 1019000 34 2.83 6.01E-01 1.06E-01 6.71E-02 7.46E-02 1.01E-01 2.09E-01 4.30E-01 7.01E-01 1.29E+00 2.11E+00 3.27E+00 3.27E+00 

Response to Questionnaire

 Households who garden 3465000 123 5.08 1.05E+00 1.75E-01 3.08E-02 6.71E-02 1.01E-01 2.78E-01 5.18E-01 1.13E+00 2.11E+00 2.79E+00 1.34E+01 1.37E+01

 Households who farm 710000 29 9.69 6.99E-01 1.07E-01 0.00E+00 0.00E+00 1.43E-01 1.88E-01 3.86E-01 1.27E+00 1.49E+00 1.71E+00 2.09E+00 2.09E+00 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-43. Consumer Only Intake of Home Produced Eggs (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 2075000 124 1.10 7.31E-01 1.00E-01 7.16E-02 1.50E-01 1.75E-01 2.68E-01 4.66E-01 9.02E-01 1.36E+00 1.69E+00 6.58E+00 1.35E+01 

Age

 01-02 21000 3 0.37 * * * * * * * * * * * *

 03-05 20000 2 0.25 * * * * * * * * * * * *

 06-11 170000 12 1.02 * * * * * * * * * * * *

 12-19 163000 14 0.80 * * * * * * * * * * * *

 20-39 474000 30 0.77 6.32E-01 9.23E-02 7.16E-02 7.16E-02 2.15E-01 3.00E-01 4.16E-01 8.14E-01 1.32E+00 1.93E+00 2.50E+00 2.50E+00

 40-69 718000 43 1.27 5.91E-01 5.77E-02 1.37E-01 1.41E-01 1.52E-01 3.17E-01 5.14E-01 8.44E-01 1.30E+00 1.36E+00 1.38E+00 1.38E+00

 70 + 489000 18 3.08 * * * * * * * * * * * * 

Seasons

 Fall 542000 18 1.14 * * * * * * * * * * * *

 Spring 460000 54 1.00 1.31E+00 2.88E-01 1.57E-01 3.25E-01 3.94E-01 5.02E-01 6.66E-01 1.31E+00 2.10E+00 3.26E+00 1.35E+01 1.35E+01

 Summer 723000 26 1.59 4.96E-01 8.14E-02 7.16E-02 1.37E-01 1.41E-01 2.60E-01 3.32E-01 5.41E-01 1.36E+00 1.51E+00 1.65E+00 1.65E+00

 Winter 350000 26 0.72 8.60E-01 9.50E-02 1.67E-01 1.75E-01 2.15E-01 4.03E-01 7.51E-01 1.17E+00 1.62E+00 1.93E+00 1.93E+00 1.93E+00 

Urbanization

 Central City 251000 9 0.45 * * * * * * * * * * * *

 Nonmetropolitan 1076000 65 2.39 7.34E-01 1.23E-01 7.16E-02 1.41E-01 1.67E-01 2.60E-01 4.74E-01 9.16E-01 1.34E+00 1.65E+00 6.58E+00 9.16E+00

 Suburban 748000 50 0.86 8.54E-01 1.98E-01 1.37E-01 1.50E-01 2.06E-01 3.80E-01 5.88E-01 1.17E+00 1.36E+00 1.85E+00 1.35E+01 1.35E+01 

Race

 Black 63000 9 0.29 * * * * * * * * * * * *

 White 2012000 115 1.28 7.41E-01 1.05E-01 7.16E-02 1.50E-01 1.75E-01 2.68E-01 4.82E-01 9.03E-01 1.36E+00 1.69E+00 6.58E+00 1.35E+01 

Region

 Midwest 665000 37 1.43 7.93E-01 1.96E-01 7.16E-02 1.37E-01 1.41E-01 2.17E-01 3.39E-01 1.08E+00 1.51E+00 2.10E+00 9.16E+00 9.16E+00

 Northeast 87000 7 0.21 * * * * * * * * * * * *

 South 823000 44 1.28 5.36E-01 6.46E-02 1.52E-01 1.77E-01 1.96E-01 2.60E-01 3.60E-01 5.99E-01 1.18E+00 1.62E+00 1.93E+00 1.93E+00

 West 500000 36 1.39 9.21E-01 2.75E-01 1.67E-01 2.06E-01 2.08E-01 4.58E-01 6.66E-01 1.05E+00 1.36E+00 1.36E+00 1.35E+01 1.35E+01 

Response to Questionnaire 

Households who raise animals 1824000 113 18.06 7.46E-01 1.11E-01 7.16E-02 1.50E-01 1.65E-01 2.56E-01 4.82E-01 9.02E-01 1.36E+00 1.85E+00 6.58E+00 1.35E+01

 Households who farm 741000 44 10.11 8.98E-01 1.70E-01 1.52E-01 1.65E-01 1.77E-01 2.72E-01 6.66E-01 1.19E+00 1.65E+00 1.85E+00 6.58E+00 9.16E+00 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-44. Consumer Only Intake of Home Produced Game (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 2707000 185 1.44 9.67E-01 6.14E-02 0.00E+00 1.17E-01 2.10E-01 3.97E-01 7.09E-01 1.22E+00 2.27E+00 2.67E+00 3.61E+00 4.59E+00 

Age

 01-02 89000 8 1.56 * * * * * * * * * * * *

 03-05 94000 8 1.16 * * * * * * * * * * * *

 06-11 362000 28 2.17 1.09E+00 1.44E-01 1.16E-01 2.31E-01 4.28E-01 6.33E-01 7.61E-01 1.48E+00 2.67E+00 2.85E+00 2.90E+00 2.90E+00

 12-19 462000 27 2.25 1.04E+00 1.39E-01 2.10E-01 2.10E-01 2.91E-01 6.30E-01 8.46E-01 1.22E+00 1.99E+00 3.13E+00 3.13E+00 3.13E+00

 20-39 844000 59 1.37 8.24E-01 1.08E-01 1.04E-01 1.17E-01 1.88E-01 3.01E-01 6.31E-01 1.09E+00 1.57E+00 2.50E+00 4.59E+00 4.59E+00

 40-69 694000 41 1.22 9.64E-01 1.40E-01 1.24E-01 1.72E-01 2.87E-01 3.42E-01 5.10E-01 1.41E+00 2.51E+00 3.19E+00 3.61E+00 3.61E+00

 70 + 74000 7 0.47 * * * * * * * * * * * * 

Season

 Fall 876000 31 1.84 9.97E-01 1.56E-01 1.17E-01 1.48E-01 2.18E-01 4.28E-01 6.33E-01 1.19E+00 2.50E+00 3.13E+00 3.19E+00 3.19E+00

 Spring 554000 68 1.20 9.06E-01 8.78E-02 0.00E+00 1.04E-01 1.72E-01 4.43E-01 7.46E-01 1.22E+00 1.75E+00 2.52E+00 3.61E+00 3.61E+00

 Summer 273000 9 0.60 * * * * * * * * * * * *

 Winter 1004000 77 2.06 1.07E+00 1.05E-01 0.00E+00 0.00E+00 1.65E-01 3.88E-01 8.18E-01 1.52E+00 2.20E+00 2.67E+00 4.59E+00 4.59E+00 

Urbanization

 Central City 506000 20 0.90 6.89E-01 1.27E-01 0.00E+00 0.00E+00 1.88E-01 2.77E-01 6.30E-01 7.74E-01 1.48E+00 1.99E+00 2.34E+00 2.34E+00

 Nonmetropolitan 1259000 101 2.80 9.45E-01 8.91E-02 0.00E+00 1.17E-01 1.65E-01 3.20E-01 6.59E-01 1.19E+00 2.27E+00 3.05E+00 4.59E+00 4.59E+00

 Suburban 942000 64 1.09 1.15E+00 1.04E-01 0.00E+00 2.56E-01 3.97E-01 5.21E-01 8.18E-01 1.52E+00 2.51E+00 2.85E+00 3.13E+00 3.61E+00 

Race

 Black 0 0 0.00

 White 2605000 182 1.65 9.77E-01 6.30E-02 0.00E+00 1.17E-01 2.02E-01 3.76E-01 7.29E-01 1.38E+00 2.34E+00 2.85E+00 3.61E+00 4.59E+00 

Region

 Midwest 1321000 97 2.85 8.83E-01 8.32E-02 0.00E+00 7.53E-02 2.18E-01 3.42E-01 6.12E-01 1.10E+00 1.99E+00 2.51E+00 4.59E+00 4.59E+00

 Northeast 394000 20 0.96 1.13E+00 2.16E-01 2.87E-01 2.87E-01 3.21E-01 4.30E-01 7.74E-01 1.41E+00 3.13E+00 3.13E+00 3.61E+00 3.61E+00

 South 609000 47 0.95 1.26E+00 1.29E-01 0.00E+00 1.17E-01 1.48E-01 6.32E-01 1.09E+00 1.93E+00 2.38E+00 3.19E+00 3.19E+00 3.19E+00

 West 383000 21 1.06 6.28E-01 7.21E-02 1.24E-01 1.51E-01 1.88E-01 3.97E-01 6.33E-01 7.74E-01 1.12E+00 1.22E+00 1.52E+00 1.52E+00 

Response to Questionnaire

 Households who hunt 2357000 158 11.66 1.04E+00 6.84E-02 0.00E+00 1.40E-01 2.77E-01 4.42E-01 7.46E-01 1.44E+00 2.38E+00 2.90E+00 3.61E+00 4.59E+00 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-45. Consumer Only Intake of Home Produced Lettuce (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 1520000 80 0.81 3.87E-01 3.18E-02 0.00E+00 4.49E-02 9.43E-02 1.70E-01 2.84E-01 5.45E-01 8.36E-01 1.03E+00 1.05E+00 1.28E+00 

Age

 01-02 54000 4 0.95 * * * * * * * * * * * *

 03-05 25000 2 0.31 * * * * * * * * * * * *

 06-11 173000 7 1.04 * * * * * * * * * * * *

 12-19 71000 3 0.35 * * * * * * * * * * * *

 20-39 379000 17 0.62 * * * * * * * * * * * *

 40-69 485000 26 0.86 4.84E-01 6.07E-02 1.15E-01 1.15E-01 1.24E-01 2.21E-01 4.91E-01 6.84E-01 8.86E-01 1.05E+00 1.28E+00 1.28E+00

 70 + 317000 20 2.00 4.52E-01 7.17E-02 5.04E-02 6.71E-02 1.12E-01 2.23E-01 2.88E-01 5.68E-01 1.03E+00 1.03E+00 1.03E+00 1.03E+00 

Season

 Fall 214000 8 0.45 * * * * * * * * * * * *

 Spring 352000 35 0.76 4.52E-01 4.86E-02 5.04E-02 6.71E-02 1.24E-01 1.99E-01 4.53E-01 5.79E-01 7.98E-01 9.94E-01 1.28E+00 1.28E+00

 Summer 856000 30 1.88 3.02E-01 3.96E-02 1.98E-02 3.35E-02 4.93E-02 1.42E-01 2.30E-01 4.24E-01 5.98E-01 8.14E-01 8.86E-01 8.86E-01

 Winter 98000 7 0.20 * * * * * * * * * * * * 

Urbanization

 Central City 268000 8 0.48 * * * * * * * * * * * *

 Nonmetropolitan 566000 36 1.26 3.67E-01 4.78E-02 1.98E-02 3.35E-02 4.49E-02 1.23E-01 2.88E-01 5.45E-01 8.14E-01 8.86E-01 1.28E+00 1.28E+00

 Suburban 686000 36 0.79 3.49E-01 4.32E-02 0.00E+00 9.43E-02 9.68E-02 1.53E-01 2.30E-01 4.91E-01 7.67E-01 9.94E-01 1.05E+00 1.05E+00 

Race

 Black 51000 3 0.23 * * * * * * * * * * * *

 White 1434000 75 0.91 3.79E-01 3.33E-02 0.00E+00 4.49E-02 9.43E-02 1.56E-01 2.75E-01 5.45E-01 8.86E-01 1.03E+00 1.05E+00 1.28E+00 

Region

 Midwest 630000 33 1.36 3.83E-01 5.54E-02 1.98E-02 3.35E-02 4.49E-02 1.56E-01 2.34E-01 5.68E-01 9.42E-01 1.03E+00 1.03E+00 1.03E+00

 Northeast 336000 16 0.82 * * * * * * * * * * * *

 South 305000 20 0.47 3.52E-01 5.74E-02 0.00E+00 0.00E+00 1.27E-01 1.64E-01 2.75E-01 4.83E-01 5.79E-01 1.04E+00 1.28E+00 1.28E+00

 West 249000 11 0.69 * * * * * * * * * * * * 

Responses to Questionnaire

 Households who garden 1506000 78 2.21 3.90E-01 3.22E-02 0.00E+00 4.49E-02 9.43E-02 1.74E-01 2.84E-01 5.45E-01 8.36E-01 1.03E+00 1.05E+00 1.28E+00

 Households who farm 304000 18 4.15 * * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-46. Consumer Only Intake of Home Produced Lima Beans (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 1917000 109 1.02 4.53E-01 4.11E-02 0.00E+00 9.19E-02 1.21E-01 1.88E-01 2.90E-01 5.45E-01 9.90E-01 1.69E+00 1.86E+00 1.91E+00 

Age

 01-02 62000 3 1.09 * * * * * * * * * * * *

 03-05 35000 2 0.43 * * * * * * * * * * * *

 06-11 95000 7 0.57 * * * * * * * * * * * *

 12-19 108000 6 0.53 * * * * * * * * * * * *

 20-39 464000 20 0.75 3.84E-01 6.87E-02 3.23E-02 1.08E-01 1.30E-01 1.77E-01 2.34E-01 4.87E-01 9.37E-01 1.10E+00 1.10E+00 1.10E+00

 40-69 757000 44 1.33 4.54E-01 6.30E-02 9.19E-02 1.06E-01 1.21E-01 2.04E-01 2.93E-01 5.60E-01 8.69E-01 1.71E+00 1.91E+00 1.91E+00

 70 + 361000 25 2.27 5.23E-01 1.05E-01 8.20E-02 1.86E-01 1.88E-01 2.25E-01 2.86E-01 6.38E-01 1.86E+00 1.86E+00 1.86E+00 1.86E+00 

Season

 Fall 375000 14 0.79 * * * * * * * * * * * *

 Spring 316000 39 0.68 4.19E-01 5.50E-02 8.20E-02 9.02E-02 1.31E-01 2.32E-01 3.06E-01 5.45E-01 7.48E-01 1.31E+00 1.91E+00 1.91E+00

 Summer 883000 29 1.94 4.99E-01 9.68E-02 0.00E+00 9.43E-02 1.21E-01 1.72E-01 2.90E-01 4.87E-01 1.53E+00 1.71E+00 1.86E+00 1.86E+00

 Winter 343000 27 0.70 5.27E-01 6.25E-02 0.00E+00 3.23E-02 1.08E-01 3.05E-01 5.39E-01 7.58E-01 8.61E-01 8.69E-01 1.69E+00 1.69E+00 

Urbanization

 Central City 204000 8 0.36 * * * * * * * * * * * *

 Nonmetropolitan 1075000 69 2.39 2.99E-01 3.22E-02 3.23E-02 9.43E-02 1.21E-01 1.71E-01 2.12E-01 3.20E-01 4.87E-01 7.69E-01 1.69E+00 1.91E+00

 Suburban 638000 32 0.74 7.53E-01 9.60E-02 0.00E+00 8.20E-02 9.19E-02 3.20E-01 6.78E-01 9.90E-01 1.71E+00 1.86E+00 1.86E+00 1.86E+00 

Race

 Black 213000 9 0.98 * * * * * * * * * * * *

 White 1704000 100 1.08 3.83E-01 3.27E-02 0.00E+00 9.19E-02 1.08E-01 1.77E-01 2.54E-01 4.87E-01 8.61E-01 9.90E-01 1.53E+00 1.91E+00 

Region

 Midwest 588000 36 1.27 4.28E-01 6.17E-02 0.00E+00 0.00E+00 1.06E-01 2.53E-01 3.06E-01 4.15E-01 9.90E-01 1.53E+00 1.69E+00 1.69E+00

 Northeast 68000 6 0.17 * * * * * * * * * * * *

 South 1261000 67 1.96 4.72E-01 5.62E-02 3.23E-02 1.03E-01 1.30E-01 1.77E-01 2.49E-01 6.34E-01 1.10E+00 1.71E+00 1.86E+00 1.91E+00

 West 0 0 0.00 

Response to Questionnaire

 Households who garden 1610000 97 2.36 4.47E-01 4.49E-02 3.23E-02 9.43E-02 1.21E-01 1.77E-01 2.85E-01 5.26E-01 9.37E-01 1.71E+00 1.86E+00 1.91E+00

 Households who farm 62000 6 0.85 * * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-47. Consumer Only Intake of Homegrown Okra (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P10

Total 1696000 82 0.90 3.91E-01 3.81E-02 0.00E+00 5.03E-02 9.59E-02 1.48E-01 2.99E-01 4.58E-01 7.81E-01 1.21E+00 1.53E+00 1.53E+

Age

 01-02 53000 2 0.93 * * * * * * * * * * * *

 03-05 68000 3 0.84 * * * * * * * * * * * *

 06-11 218000 11 1.30 * * * * * * * * * * * *

 12-19 194000 9 0.95 * * * * * * * * * * * *

 20-39 417000 18 0.68 * * * * * * * * * * * *

 40-69 587000 32 1.03 4.00E-01 4.73E-02 6.57E-02 1.11E-01 1.37E-01 2.47E-01 3.07E-01 4.62E-01 7.81E-01 1.14E+00 1.14E+00 1.14E+

 70 + 130000 6 0.82 * * * * * * * * * * * * 

Season

 Fall 228000 9 0.48 * * * * * * * * * * * *

 Spring 236000 24 0.51 3.87E-01 6.22E-02 2.98E-02 4.58E-02 6.57E-02 1.10E-01 4.10E-01 5.95E-01 7.81E-01 9.99E-01 1.07E+00 1.07E+

 Summer 1144000 41 2.52 3.86E-01 5.75E-02 0.00E+00 5.03E-02 9.59E-02 1.44E-01 2.99E-01 4.38E-01 1.15E+00 1.53E+00 1.53E+00 1.53E+

 Winter 88000 8 0.18 * * * * * * * * * * * * 

Urbanization

 Central City 204000 6 0.36 * * * * * * * * * * * *

 Nonmetropolitan 1043000 55 2.32 3.65E-01 4.99E-02 0.00E+00 2.69E-02 8.48E-02 1.48E-01 2.57E-01 4.38E-01 7.81E-01 1.53E+00 1.53E+00 1.53E+

 Suburban 449000 21 0.52 5.14E-01 6.97E-02 6.57E-02 9.60E-02 1.11E-01 3.13E-01 4.62E-01 6.00E-01 1.14E+00 1.15E+00 1.15E+00 1.15E+

Race

 Black 236000 13 1.09 * * * * * * * * * * * *

 White 1419000 68 0.90 4.26E-01 4.40E-02 0.00E+00 6.57E-02 9.60E-02 1.76E-01 3.30E-01 5.23E-01 1.14E+00 1.21E+00 1.53E+00 1.53E+

Region

 Midwest 113000 7 0.24 * * * * * * * * * * * *

 Northeast 

 South 1443000 70 2.24 3.73E-01 4.21E-02 0.00E+00 5.03E-02 8.48E-02 1.44E-01 2.59E-01 4.38E-01 7.47E-01 1.21E+00 1.53E+00 1.53E+

 West 140000 5 0.39 * * * * * * * * * * * * 

Response to Questionnaire

 Households who garden 1564000 77 2.29 3.84E-01 4.05E-02 0.00E+00 5.03E-02 9.59E-02 1.48E-01 2.98E-01 4.52E-01 1.07E+00 1.21E+00 1.53E+00 1.53E+

 Households who farm 233000 14 3.18 * * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-48. Consumer Only Intake of Homegrown Onions (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 6718000 370 3.57 2.96E-01 1.87E-02 3.68E-03 9.09E-03 2.90E-02 8.81E-02 2.06E-01 3.77E-01 6.09E-01 9.12E-01 1.49E+00 3.11E+

Age

 01-02 291000 17 5.11 * * * * * * * * * * * *

 03-05 178000 9 2.20 * * * * * * * * * * * *

 06-11 530000 31 3.17 3.03E-01 5.61E-02 9.80E-03 1.08E-02 2.76E-02 1.06E-01 2.28E-01 3.83E-01 6.09E-01 1.36E+00 1.36E+00 1.36E+

 12-19 652000 37 3.18 2.11E-01 3.65E-02 5.14E-03 8.36E-03 8.58E-03 5.97E-02 1.42E-01 2.55E-01 5.74E-01 7.59E-01 9.12E-01 9.12E-

 20-39 1566000 78 2.54 2.88E-01 3.40E-02 9.09E-03 3.80E-02 5.80E-02 9.40E-02 1.91E-01 3.04E-01 6.38E-01 9.35E-01 1.49E+00 1.49E+

 40-69 2402000 143 4.23 2.50E-01 2.07E-02 3.03E-03 4.59E-03 1.11E-02 7.66E-02 1.72E-01 3.58E-01 5.52E-01 6.90E-01 1.11E+00 1.41E+

 70 + 1038000 52 6.54 4.33E-01 8.86E-02 4.76E-03 6.68E-03 2.68E-02 1.35E-01 2.86E-01 4.61E-01 5.63E-01 2.68E+00 3.11E+00 3.11E+

Season

 Fall 1557000 59 3.27 3.75E-01 6.93E-02 3.68E-03 2.55E-02 5.80E-02 1.23E-01 2.55E-01 4.36E-01 6.03E-01 7.83E-01 3.11E+00 3.11E+

 Spring 1434000 147 3.11 1.95E-01 1.96E-02 2.01E-03 5.47E-03 2.68E-02 5.73E-02 1.06E-01 2.59E-01 4.26E-01 5.23E-01 1.41E+00 1.77E+

 Summer 2891000 101 6.36 3.06E-01 2.91E-02 8.58E-03 1.68E-02 4.22E-02 1.08E-01 2.28E-01 3.76E-01 6.90E-01 9.69E-01 1.49E+00 1.49E+

 Winter 836000 63 1.72 2.88E-01 3.86E-02 3.03E-03 4.59E-03 5.04E-03 3.06E-02 1.99E-01 4.60E-01 6.42E-01 9.16E-01 1.36E+00 1.36E+

Urbanization

 Central City 890000 37 1.58 2.16E-01 2.85E-02 4.76E-03 1.02E-02 2.55E-02 6.60E-02 1.93E-01 2.96E-01 5.18E-01 5.63E-01 5.63E-01 5.63E-

 Nonmetropolitan 2944000 177 6.54 3.24E-01 2.06E-02 8.12E-03 3.14E-02 6.75E-02 1.42E-01 2.55E-01 4.33E-01 6.30E-01 9.12E-01 1.49E+00 1.77E+

 Suburban 2884000 156 3.33 2.92E-01 3.70E-02 3.03E-03 5.20E-03 1.10E-02 5.85E-02 1.30E-01 3.56E-01 6.35E-01 9.69E-01 3.11E+00 3.11E+

Race

 Black 253000 16 1.16 * * * * * * * * * * * *

 White 6266000 345 3.98 3.08E-01 1.99E-02 3.57E-03 9.09E-03 3.06E-02 9.16E-02 2.24E-01 3.86E-01 6.18E-01 9.35E-01 1.77E+00 3.11E+

Region

 Midwest 2487000 143 5.36 2.70E-01 1.94E-02 4.25E-03 4.02E-02 5.73E-02 1.02E-01 2.24E-01 3.43E-01 5.63E-01 7.24E-01 1.34E+00 1.34E+

 Northeast 876000 52 2.13 2.32E-01 4.43E-02 2.01E-03 3.73E-03 8.36E-03 1.08E-02 1.08E-01 3.53E-01 6.35E-01 1.05E+00 1.36E+00 1.41E+

 South 1919000 107 2.98 3.32E-01 2.93E-02 4.79E-03 2.76E-02 3.70E-02 1.46E-01 2.51E-01 3.93E-01 6.90E-01 1.08E+00 1.49E+00 1.77E+

 West 1436000 68 3.98 3.32E-01 6.90E-02 3.57E-03 6.68E-03 1.68E-02 5.68E-02 1.52E-01 3.86E-01 5.49E-01 9.69E-01 3.11E+00 3.11E+

Response to Questionnaire

 Households who garden 6441000 356 9.45 3.00E-01 1.93E-02 3.68E-03 9.09E-03 3.06E-02 9.11E-02 2.13E-01 3.81E-01 6.09E-01 9.16E-01 1.77E+00 3.11E+

 Households who farm 1390000 81 18.97 3.75E-01 3.84E-02 3.00E-02 4.04E-02 5.15E-02 1.11E-01 2.78E-01 5.15E-01 9.35E-01 1.11E+00 1.49E+00 1.49E+

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distributions 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-49. Consumer Only Intake of Homegrown Other Berries (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 1626000 99 0.86 4.80E-01 4.24E-02 0.00E+00 4.68E-02 9.24E-02 2.32E-01 3.84E-01 5.89E-01 1.07E+00 1.28E+00 2.21E+00 2.21E+

Age

 01-02 41000 2 0.72 * * * * * * * * * * * *

 03-05 53000 3 0.65 * * * * * * * * * * * *

 06-11 106000 10 0.63 * * * * * * * * * * * *

 12-19 79000 5 0.39 * * * * * * * * * * * *

 20-39 309000 20 0.50 3.90E-01 6.31E-02 7.95E-02 9.18E-02 9.18E-02 1.25E-01 3.30E-01 5.52E-01 7.94E-01 1.07E+00 1.07E+00 1.07E+

 40-69 871000 51 1.54 4.89E-01 5.72E-02 7.69E-02 1.01E-01 1.34E-01 2.48E-01 3.89E-01 6.12E-01 7.68E-01 1.28E+00 2.21E+00 2.21E+

 70 + 159000 7 1.00 * * * * * * * * * * * * 

Season

 Fall 379000 13 0.80 * * * * * * * * * * * *

 Spring 287000 29 0.62 3.06E-01 4.11E-02 4.68E-02 4.68E-02 7.69E-02 1.84E-01 2.54E-01 4.08E-01 5.40E-01 7.24E-01 1.07E+00 1.07E+

 Summer 502000 18 1.10 * * * * * * * * * * * *

 Winter 458000 39 0.94 5.35E-01 7.39E-02 0.00E+00 1.02E-01 1.59E-01 2.32E-01 3.89E-01 6.23E-01 1.07E+00 1.95E+00 2.08E+00 2.08E+

Urbanization

 Central City 378000 15 0.67 * * * * * * * * * * * *

 Nonmetropolitan 466000 37 1.04 6.43E-01 8.96E-02 0.00E+00 9.24E-02 1.02E-01 2.51E-01 4.39E-01 1.02E+00 1.31E+00 2.21E+00 2.21E+00 2.21E+

 Suburban 722000 45 0.83 4.48E-01 5.32E-02 9.18E-02 1.25E-01 1.58E-01 2.58E-01 3.84E-01 5.35E-01 5.89E-01 9.02E-01 2.08E+00 2.08E+

Race

 Black 76000 4 0.35 * * * * * * * * * * * *

 White 1490000 93 0.95 5.03E-01 4.43E-02 4.68E-02 9.18E-02 1.01E-01 2.51E-01 3.95E-01 6.04E-01 1.07E+00 1.31E+00 2.21E+00 2.21E+

Region

 Midwest 736000 56 1.59 4.57E-01 6.26E-02 0.00E+00 7.69E-02 9.18E-02 1.25E-01 3.00E-01 5.87E-01 1.12E+00 1.28E+00 2.21E+00 2.21E+

 Northeast 211000 11 0.51 * * * * * * * * * * * *

 South 204000 12 0.32 * * * * * * * * * * * *

 West 415000 18 1.15 * * * * * * * * * * * * 

Response t o 

Questionnaire

 Households who garden 1333000 84 1.96 4.72E-01 4.83E-02 1.00E-02 0.00E+00 9.18E-02 2.00E-01 3.53E-01 5.52E-01 1.07E+00 1.28E+00 2.21E+00 2.21E+

 Households who farm 219000 16 2.99 * * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-50. Consumer Only Intake of Homegrown Peaches (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 

Total 2941000 193 1.56 1.67E+00 1.70E-01 5.20E-02 1.65E-01 2.25E-01 4.74E-01 8.97E-01 1.88E+00 3.79E+00 6.36E+00 1.23E+01 

Age

 01-02 103000 8 1.81 * * * * * * * * * * * 

 03-05 65000 6 0.80 * * * * * * * * * * * 

 06-11 329000 26 1.97 3.11E+00 6.32E-01 9.75E-02 1.01E-01 1.40E-01 6.25E-01 1.13E+00 6.36E+00 8.53E+00 8.53E+00 1.15E+01 

 12-19 177000 13 0.86 * * * * * * * * * * * 

 20-39 573000 35 0.93 1.17E+00 1.74E-01 5.07E-02 5.50E-02 2.25E-01 4.74E-01 8.09E-01 1.30E+00 2.92E+00 2.99E+00 5.27E+00 

 40-69 1076000 70 1.90 1.53E+00 2.83E-01 5.87E-02 1.90E-01 2.39E-01 5.56E-01 8.92E-01 1.61E+00 2.63E+00 4.43E+00 1.23E+01 

 70 + 598000 33 3.77 1.01E+00 1.97E-01 9.13E-02 1.38E-01 1.79E-01 2.82E-01 8.22E-01 1.19E+00 1.60E+00 3.79E+00 7.13E+00 

Season

 Fall 485000 19 1.02 * * * * * * * * * * * 

 Spring 756000 91 1.64 1.67E+00 3.04E-01 5.07E-02 5.87E-02 1.01E-01 2.76E-01 7.74E-01 1.45E+00 4.44E+00 6.77E+00 2.23E+01 

 Summer 1081000 35 2.38 2.26E+00 4.78E-01 1.65E-01 2.25E-01 3.61E-01 5.67E-01 1.12E+00 2.99E+00 6.36E+00 8.53E+00 1.23E+01 

 Winter 619000 48 1.27 1.25E+00 1.03E-01 3.52E-02 2.39E-01 5.56E-01 7.79E-01 1.04E+00 1.71E+00 2.35E+00 2.60E+00 3.56E+00 

Urbanization

 Central City 429000 12 0.76 * * * * * * * * * * * 

 Nonmetropolitan 1110000 99 2.47 1.87E+00 2.59E-01 5.87E-02 2.62E-01 3.93E-01 6.46E-01 1.02E+00 2.18E+00 3.86E+00 6.36E+00 1.15E+01 

 Suburban 1402000 82 1.62 1.47E+00 1.75E-01 5.07E-02 1.40E-01 2.04E-01 4.61E-01 9.20E-01 1.87E+00 3.79E+00 4.43E+00 7.37E+00 

Race

 Black 39000 1 0.18 * * * * * * * * * * * 

 White 2861000 191 1.82 1.70E+00 1.73E-01 5.20E-02 1.65E-01 2.30E-01 5.03E-01 8.97E-01 1.96E+00 3.79E+00 6.36E+00 1.23E+01 

Region

 Midwest 824000 75 1.78 1.39E+00 2.91E-01 1.76E-01 2.20E-01 2.59E-01 4.60E-01 7.40E-01 1.19E+00 3.06E+00 3.56E+00 1.15E+01 

 Northeast 75000 5 0.18 * * * * * * * * * * * 

 South 852000 51 1.32 1.67E+00 2.57E-01 3.52E-02 1.38E-01 1.79E-01 6.43E-01 1.02E+00 1.96E+00 3.83E+00 6.36E+00 8.53E+00 

 West 1190000 62 3.30 1.80E+00 3.26E-01 5.07E-02 1.40E-01 2.25E-01 4.68E-01 8.63E-01 1.94E+00 4.43E+00 7.37E+00 1.23E+01 

Response to Questionnaire

 Households who garden 2660000 174 3.90 1.75E+00 1.85E-01 5.20E-02 1.66E-01 2.59E-01 5.26E-01 9.25E-01 1.96E+00 3.79E+00 6.36E+00 1.23E+01 

 Households who farm 769000 54 10.49 1.56E+00 2.49E-01 6.79E-02 1.76E-01 2.26E-01 4.61E-01 9.02E-01 2.02E+00 2.99E+00 6.36E+00 8.53E+00 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-51. Consumer Only Intake of Homegrown Pears (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P10

Total 1513000 94 0.80 9.37E-01 9.68E-02 1.01E-01 1.84E-01 2.38E-01 4.28E-01 6.82E-01 1.09E+00 1.60E+00 2.76E+00 5.16E+00 5.16E

Age

 01-02 24000 3 0.42 * * * * * * * * * * * *

 03-05 45000 3 0.56 * * * * * * * * * * * *

 06-11 145000 10 0.87 * * * * * * * * * * * *

 12-19 121000 7 0.59 * * * * * * * * * * * *

 20-39 365000 23 0.59 6.19E-01 6.42E-02 1.13E-01 3.18E-01 3.79E-01 4.28E-01 5.03E-01 6.82E-01 1.22E+00 1.24E+00 1.24E+00 1.24E

 40-69 557000 33 0.98 6.57E-01 5.53E-02 1.01E-01 1.08E-01 3.33E-01 4.23E-01 6.45E-01 9.22E-01 1.10E+00 1.13E+00 1.51E+00 1.51E

 70 + 256000 15 1.61 * * * * * * * * * * * * 

Season

 Fall 308000 11 0.65 * * * * * * * * * * * *

 Spring 355000 39 0.77 6.87E-01 7.89E-02 1.01E-01 1.13E-01 1.82E-01 3.38E-01 6.02E-01 8.66E-01 1.15E+00 1.83E+00 2.54E+00 2.54E

 Summer 474000 16 1.04 * * * * * * * * * * * *

 Winter 376000 28 0.77 1.48E+00 2.77E-01 1.08E-01 1.08E-01 3.79E-01 6.45E-01 9.49E-01 1.38E+00 4.82E+00 5.16E+00 5.16E+00 5.16E

Urbanization

 Central City 222000 11 0.39 * * * * * * * * * * * *

 Nonmetropolitan 634000 44 1.41 7.81E-01 8.52E-02 3.33E-01 3.52E-01 4.19E-01 4.43E-01 5.70E-01 8.13E-01 1.56E+00 1.86E+00 2.88E+00 2.88E

 Suburban 657000 39 0.76 8.50E-01 1.17E-01 1.01E-01 1.08E-01 1.82E-01 3.89E-01 7.29E-01 1.10E+00 1.50E+00 2.57E+00 4.79E+00 4.79E

Race

 Black 51000 3 0.23 * * * * * * * * * * * *

 White 1462000 91 0.93 9.65E-01 9.88E-02 1.08E-01 2.38E-01 3.52E-01 4.43E-01 7.01E-01 1.09E+00 1.60E+00 2.88E+00 5.16E+00 5.16E

Region

 Midwest 688000 57 1.48 8.71E-01 9.49E-02 2.22E-01 3.38E-01 3.76E-01 4.43E-01 6.45E-01 1.04E+00 1.60E+00 2.57E+00 4.79E+00 4.79E

 Northeast 18000 2 0.04 * * * * * * * * * * * *

 South 377000 13 0.59 * * * * * * * * * * * *

 West 430000 22 1.19 1.14E+00 2.89E-01 1.01E-01 1.08E-01 1.13E-01 3.56E-01 7.52E-01 1.13E+00 2.76E+00 4.82E+00 5.16E+00 5.16E

Response to Questionnaire

 Households who garden 1312000 85 1.93 9.45E-01 1.04E-01 1.01E-01 1.82E-01 3.52E-01 4.31E-01 6.75E-01 1.09E+00 1.56E+00 2.88E+00 5.16E+00 5.16E

 Households who farm 528000 35 7.20 1.09E+00 2.10E-01 1.08E-01 2.22E-01 3.76E-01 4.28E-01 6.14E-01 1.09E+00 2.76E+00 4.82E+00 5.16E+00 5.16E

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-52. Consumer Only Intake of Homegrown Peas (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 4252000 226 2.26 5.05E-01 3.23E-02 4.58E-02 1.02E-01 1.40E-01 2.28E-01 3.21E-01 6.22E-01 1.04E+00 1.46E+00 2.66E+00 2.89E+00 

Age

 01-02 163000 9 2.86 * * * * * * * * * * * *

 03-05 140000 7 1.73 * * * * * * * * * * * *

 06-11 515000 26 3.08 6.05E-01 8.91E-02 1.54E-01 1.54E-01 2.18E-01 3.04E-01 3.87E-01 9.00E-01 1.35E+00 1.40E+00 2.06E+00 2.06E+00

 12-19 377000 22 1.84 4.08E-01 4.28E-02 5.81E-02 1.33E-01 1.58E-01 2.35E-01 3.58E-01 5.02E-01 7.10E-01 8.22E-01 8.22E-01 8.22E-01

 20-39 1121000 52 1.82 4.08E-01 6.21E-02 9.96E-02 1.15E-01 1.40E-01 1.80E-01 2.54E-01 4.06E-01 8.47E-01 1.36E+00 2.71E+00 2.71E+00

 40-69 1366000 80 2.41 4.58E-01 4.61E-02 6.78E-02 1.02E-01 1.20E-01 2.26E-01 3.04E-01 6.10E-01 9.95E-01 1.30E+00 2.36E+00 2.36E+00

 70 + 458000 26 2.88 3.34E-01 5.58E-02 3.48E-02 3.48E-02 4.58E-02 1.84E-01 2.73E-01 3.72E-01 9.95E-01 9.95E-01 1.46E+00 1.46E+00 

Season

 Fall 1239000 41 2.60 3.03E-01 2.97E-02 3.48E-02 4.58E-02 1.15E-01 2.09E-01 2.62E-01 3.53E-01 5.99E-01 7.14E-01 9.95E-01 9.95E-01

 Spring 765000 78 1.66 4.38E-01 4.26E-02 5.81E-02 1.08E-01 1.18E-01 1.90E-01 3.26E-01 5.16E-01 9.19E-01 1.40E+00 2.06E+00 2.06E+00

 Summer 1516000 51 3.33 5.85E-01 7.36E-02 6.78E-02 1.27E-01 1.74E-01 2.24E-01 3.87E-01 8.22E-01 1.35E+00 1.60E+00 2.66E+00 2.66E+00

 Winter 732000 56 1.50 7.53E-01 8.86E-02 1.17E-01 1.84E-01 2.12E-01 2.73E-01 5.44E-01 9.48E-01 1.54E+00 2.36E+00 2.89E+00 2.89E+00 

Urbanization

 Central City 558000 19 0.99 * * * * * * * * * * * *

 Nonmetropolitan 2028000 126 4.50 4.81E-01 3.55E-02 8.42E-02 1.36E-01 1.74E-01 2.48E-01 3.53E-01 5.79E-01 1.04E+00 1.36E+00 1.89E+00 2.89E+00

 Suburban 1666000 81 1.92 5.13E-01 4.63E-02 6.78E-02 1.15E-01 1.34E-01 2.29E-01 3.87E-01 6.84E-01 9.95E-01 1.30E+00 2.28E+00 2.36E+00 

Race

 Black 355000 19 1.63 * * * * * * * * * * * *

 White 3784000 203 2.40 4.95E-01 3.35E-02 3.48E-02 1.02E-01 1.33E-01 2.18E-01 3.26E-01 6.00E-01 9.99E-01 1.40E+00 2.66E+00 2.89E+00 

Region

 Midwest 1004000 55 2.16 4.03E-01 7.24E-02 3.48E-02 4.58E-02 9.96E-02 1.40E-01 2.52E-01 3.53E-01 8.80E-01 1.54E+00 2.71E+00 2.89E+00

 Northeast 241000 14 0.59 * * * * * * * * * * * *

 South 2449000 132 3.81 5.67E-01 4.30E-02 1.27E-01 1.74E-01 1.96E-01 2.62E-01 3.72E-01 6.82E-01 1.24E+00 1.60E+00 2.66E+00 2.66E+00

 West 558000 25 1.55 3.77E-01 5.70E-02 6.78E-02 6.78E-02 1.02E-01 2.18E-01 2.73E-01 4.79E-01 9.00E-01 9.40E-01 1.40E+00 1.40E+00 

Response to Questionnaire

 Households who garden 3980000 214 5.84 5.13E-01 3.39E-02 3.48E-02 1.02E-01 1.40E-01 2.28E-01 3.21E-01 6.28E-01 1.04E+00 1.54E+00 2.66E+00 2.89E+00

 Households who farm 884000 55 12.06 4.59E-01 5.83E-02 3.48E-02 4.58E-02 8.65E-02 2.08E-01 3.53E-01 5.16E-01 9.00E-01 1.40E+00 1.60E+00 2.89E+00 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-53. Consumer Only Intake of Homegrown Peppers (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 5153000 208 2.74 

Age

 01-02 163000 6 2.86 * * * * * * * * * * * *

 03-05 108000 5 1.33 * * * * * * * * * * * *

 06-11 578000 26 3.46 2.26E-01 4.09E-02 0.00E+00 0.00E+00 3.03E-02 8.99E-02 1.62E-01 2.98E-01 4.25E-01 7.70E-01 8.45E-01 8.45E-0

 12-19 342000 16 1.67 * * * * * * * * * * * *

 20-39 1048000 40 1.70 2.24E-01 6.10E-02 1.74E-02 3.26E-02 5.66E-02 8.55E-02 1.19E-01 2.18E-01 3.97E-01 6.24E-01 2.48E+00 2.48E+

 40-69 2221000 88 3.92 2.50E-01 2.78E-02 5.32E-03 3.40E-02 4.52E-02 7.58E-02 1.66E-01 3.21E-01 4.77E-01 7.44E-01 1.50E+00 1.50E+

 70 + 646000 25 4.07 2.56E-01 6.22E-02 1.73E-02 2.15E-02 2.30E-02 7.47E-02 1.38E-01 2.39E-01 9.24E-01 9.39E-01 1.07E+00 1.07E+

Season

 Fall 1726000 53 3.62 1.97E-01 2.51E-02 0.00E+00 3.26E-02 4.05E-02 8.55E-02 1.66E-01 2.39E-01 3.49E-01 3.97E-01 1.07E+00 1.07E+

 Spring 255000 28 0.55 2.95E-01 7.15E-02 0.00E+00 1.73E-02 3.86E-02 6.93E-02 1.47E-01 3.21E-01 1.09E+00 1.20E+00 1.53E+00 1.53E+

 Summer 2672000 94 5.87

 Winter 500000 33 1.03 

Urbanization

 Central City 865000 30 1.53 2.46E-01 4.23E-02 3.86E-02 5.66E-02 6.72E-02 1.10E-01 1.84E-01 2.73E-01 3.61E-01 9.39E-01 1.10E+00 1.10E+

 Nonmetropolitan 1982000 89 4.40 2.42E-01 3.93E-02 5.32E-03 2.22E-02 3.34E-02 6.93E-02 1.19E-01 2.72E-01 5.37E-01 7.70E-01 2.48E+00 2.48E+

 Suburban 2246000 87 2.59 2.47E-01 3.00E-02 0.00E+00 2.70E-02 3.50E-02 8.55E-02 1.60E-01 2.91E-01 4.90E-01 9.73E-01 1.50E+00 1.53E+

Race

 Black 127000 6 0.58 * * * * * * * * * * * *

 White 4892000 198 3.11 2.47E-01 2.23E-02 1.74E-02 2.96E-02 4.05E-02 8.55E-02 1.54E-01 2.91E-01 4.90E-01 9.24E-01 1.81E+00 2.48E+

Region

 Midwest 1790000 74 3.86 2.34E-01 4.06E-02 5.32E-03 2.22E-02 3.26E-02 5.98E-02 1.47E-01 2.57E-01 3.90E-01 8.45E-01 2.48E+00 2.48E+

 Northeast 786000 31 1.91

 South 1739000 72 2.70 2.30E-01 2.89E-02 3.34E-02 6.74E-02 7.60E-02 1.07E-01 1.66E-01 2.73E-01 4.25E-01 5.26E-01 1.81E+00 1.81E+

 West 778000 29 2.16 2.13E-01 5.04E-02 1.73E-02 2.30E-02 2.70E-02 4.05E-02 8.58E-02 2.53E-01 5.37E-01 9.24E-01 1.07E+00 1.07E+

Response to Questionnaire

 Households who garden 4898000 199 7.19 2.35E-01 2.09E-02 0.00E+00 2.22E-02 3.40E-02 7.58E-02 1.54E-01 2.85E-01 4.77E-01 8.45E-01 1.50E+00 2.48E+

 Households who farm 867000 35 11.83 3.03E-01 7.50E-02 0.00E+00 2.70E-02 2.96E-02 7.11E-02 1.66E-01 3.55E-01 6.00E-01 8.45E-01 2.48E+00 2.48E+

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-54. Consumer Only Intake of Home Produced Pork (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 1732000 121 0.92 1.23E+00 9.63E-02 9.26E-02 1.40E-01 3.05E-01 5.41E-01 8.96E-01 1.71E+00 2.73E+00 3.37E+00 4.93E+00 7.41E+0

Age

 01-02 38000 5 0.67 * * * * * * * * * * * *

 03-05 26000 3 0.32 * * * * * * * * * * * *

 06-11 129000 11 0.77 * * * * * * * * * * * *

 12-19 291000 20 1.42 1.28E+00 2.42E-01 3.05E-01 3.23E-01 3.37E-01 5.24E-01 8.85E-01 1.75E+00 3.69E+00 3.69E+00 4.29E+00 4.29E+0

 20-39 511000 32 0.83 1.21E+00 1.80E-01 1.11E-01 2.83E-01 4.09E-01 5.52E-01 7.89E-01 1.43E+00 2.90E+00 3.08E+00 4.93E+00 4.93E+0

 40-69 557000 38 0.98 1.02E+00 1.15E-01 1.19E-01 1.81E-01 2.22E-01 4.05E-01 8.11E-01 1.71E+00 1.78E+00 2.28E+00 3.16E+00 3.16E+0

 70 + 180000 12 1.13 * * * * * * * * * * * * 

Season

 Fall 362000 13 0.76 * * * * * * * * * * * *

 Spring 547000 59 1.19 1.13E+00 1.29E-01 1.11E-01 1.40E-01 2.22E-01 3.52E-01 8.96E-01 1.50E+00 2.68E+00 3.68E+00 4.29E+00 4.29E+0

 Summer 379000 15 0.83 * * * * * * * * * * * *

 Winter 444000 34 0.91 1.40E+00 2.39E-01 1.26E-01 2.58E-01 3.77E-01 5.03E-01 8.83E-01 2.21E+00 3.08E+00 4.93E+00 7.41E+00 7.41E+0

Urbanization

 Central City 90000 2 0.16 * * * * * * * * * * * *

 Nonmetropolitan 1178000 77 2.62 1.39E+00 1.31E-01 9.26E-02 2.15E-01 4.05E-01 6.17E-01 9.66E-01 1.75E+00 3.16E+00 3.69E+00 4.93E+00 7.41E+0

 Suburban 464000 42 0.54 8.77E-01 1.20E-01 1.11E-01 1.19E-01 1.81E-01 3.31E-01 5.89E-01 1.10E+00 2.28E+00 2.73E+00 2.90E+00 2.90E+0

Race

 Black 0 0 0.00

 White 1732000 121 1.10 1.23E+00 9.63E-02 9.26E-02 1.40E-01 3.05E-01 5.41E-01 8.96E-01 1.71E+00 2.73E+00 3.37E+00 4.93E+00 7.41E+0

Region

 Midwest 844000 64 1.82 1.06E+00 1.19E-01 9.26E-02 1.19E-01 2.13E-01 5.02E-01 6.72E-01 1.20E+00 2.68E+00 3.37E+00 3.69E+00 3.73E+0

 Northeast 97000 5 0.24 * * * * * * * * * * * *

 South 554000 32 0.86 1.35E+00 1.46E-01 1.81E-01 2.58E-01 3.37E-01 8.11E-01 1.26E+00 1.75E+00 2.44E+00 3.08E+00 4.29E+00 4.29E+0

 West 237000 20 0.66 1.15E+00 3.09E-01 1.26E-01 3.23E-01 3.77E-01 4.40E-01 7.29E-01 1.10E+00 1.75E+00 2.73E+00 7.41E+00 7.41E+0

Response to Questionnaire 

Households who raise animals 1428000 100 14.14 1.34E+00 9.86E-02 1.40E-01 3.23E-01 4.05E-01 5.89E-01 9.66E-01 1.75E+00 2.90E+00 3.37E+00 4.29E+00 4.93E+0

 Households who farm 1218000 82 16.62 1.30E+00 1.11E-01 2.15E-01 3.42E-01 4.08E-01 5.85E-01 9.24E-01 1.71E+00 3.08E+00 3.69E+00 4.93E+00 4.93E+0

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-55. Consumer Only Intake of Home Produced Poultry (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 1816000 105 0.97 1.57E+00 1.15E-01 1.95E-01 3.03E-01 4.18E-01 6.37E-01 1.23E+00 2.19E+00 3.17E+00 3.83E+00 5.33E+00 6.17E+00 

Age

 01-02 91000 8 1.60 * * * * * * * * * * * *

 03-05 70000 5 0.86 * * * * * * * * * * * *

 06-11 205000 12 1.23 * * * * * * * * * * * *

 12-19 194000 12 0.95 * * * * * * * * * * * *

 20-39 574000 33 0.93 1.17E+00 1.47E-01 1.73E-01 4.02E-01 4.02E-01 5.57E-01 1.15E+00 1.37E+00 1.80E+00 2.93E+00 4.59E+00 4.59E+00

 40-69 568000 30 1.00 1.51E+00 2.43E-01 1.95E-01 1.97E-01 3.03E-01 4.91E-01 7.74E-01 2.69E+00 3.29E+00 4.60E+00 5.15E+00 5.15E+00

 70 + 80000 3 0.50 * * * * * * * * * * * * 

Season

 Fall 562000 23 1.18 1.52E+00 1.75E-01 4.07E-01 4.18E-01 4.60E-01 8.11E-01 1.39E+00 2.23E+00 2.69E+00 3.17E+00 3.17E+00 3.17E+00

 Spring 374000 34 0.81 1.87E+00 2.79E-01 1.73E-01 2.28E-01 3.03E-01 5.22E-01 1.38E+00 3.29E+00 4.60E+00 5.15E+00 5.33E+00 5.33E+00

 Summer 312000 11 0.69 * * * * * * * * * * * *

 Winter 568000 37 1.17 1.55E+00 2.00E-01 1.95E-01 1.97E-01 4.33E-01 5.95E-01 1.23E+00 2.18E+00 2.95E+00 3.47E+00 6.17E+00 6.17E+00 

Urbanization

 Central City 230000 8 0.41 * * * * * * * * * * * *

 Nonmetropolitan 997000 56 2.21 1.48E+00 1.32E-01 1.95E-01 2.82E-01 4.07E-01 6.72E-01 1.19E+00 2.10E+00 3.17E+00 3.29E+00 3.86E+00 5.33E+00

 Suburban 589000 41 0.68 1.94E+00 2.30E-01 2.28E-01 2.67E-01 4.33E-01 6.24E-01 1.59E+00 2.69E+00 4.59E+00 4.83E+00 6.17E+00 6.17E+00 

Race

 Black 44000 2 0.20 * * * * * * * * * * * *

 White 1772000 103 1.12 1.57E+00 1.17E-01 1.95E-01 3.03E-01 4.18E-01 6.24E-01 1.23E+00 2.19E+00 3.17E+00 3.86E+00 5.33E+00 6.17E+00 

Region

 Midwest 765000 41 1.65 1.60E+00 1.40E-01 4.07E-01 4.18E-01 5.57E-01 9.79E-01 1.39E+00 2.19E+00 2.70E+00 3.17E+00 3.86E+00 5.33E+00

 Northeast 64000 4 0.16 * * * * * * * * * * * *

 South 654000 38 1.02 1.67E+00 2.50E-01 1.73E-01 1.97E-01 3.03E-01 4.60E-01 9.08E-01 2.11E+00 4.59E+00 4.83E+00 6.17E+00 6.17E+00

 West 333000 22 0.92 1.24E+00 1.80E-01 2.67E-01 2.67E-01 4.27E-01 5.60E-01 1.02E+00 1.89E+00 2.45E+00 2.93E+00 2.93E+00 2.93E+00 

Response to Questionnaire

 Households who raise animals 1333000 81 13.20 1.58E+00 1.18E-01 2.28E-01 4.07E-01 4.72E-01 7.09E-01 1.37E+00 2.19E+00 2.93E+00 3.29E+00 5.33E+00 6.17E+00

 Households who farm 917000 59 12.51 1.54E+00 1.79E-01 1.95E-01 2.28E-01 3.03E-01 5.95E-01 1.06E+00 2.18E+00 3.47E+00 4.83E+00 6.17E+00 6.17E+00 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-56. Consumer Only Intake of Homegrown Pumpkins (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P

Total 2041000 87 1.09 7.78E-01 6.83E-02 1.25E-01 1.84E-01 2.41E-01 3.18E-01 5.55E-01 1.07E+00 1.47E+00 1.79E+00 3.02E+00 4.4

Age

 01-02 73000 4 1.28 * * * * * * * * * * * 

 03-05 18000 2 0.22 * * * * * * * * * * * 

 06-11 229000 9 1.37 * * * * * * * * * * * 

 12-19 244000 10 1.19 * * * * * * * * * * * 

 20-39 657000 26 1.07 8.01E-01 1.29E-01 1.76E-01 1.84E-01 3.01E-01 3.77E-01 4.77E-01 1.03E+00 1.73E+00 2.67E+00 2.67E+00 2.6

 40-69 415000 20 0.73 8.22E-01 1.57E-01 2.86E-01 2.86E-01 3.16E-01 3.71E-01 5.23E-01 9.62E-01 1.47E+00 3.02E+00 3.02E+00 3.0

 70 + 373000 15 2.35 * * * * * * * * * * * 

Season

 Fall 1345000 49 2.82 8.19E-01 8.91E-02 1.25E-01 1.76E-01 2.81E-01 3.71E-01 6.14E-01 1.17E+00 1.73E+00 1.79E+00 3.02E+00 3.0

 Spring 48000 6 0.10 * * * * * * * * * * * 

 Summer 405000 13 0.89 * * * * * * * * * * * 

 Winter 243000 19 0.50 * * * * * * * * * * * 

Urbanization

 Central City 565000 20 1.00 6.29E-01 1.08E-01 1.84E-01 1.84E-01 2.41E-01 2.81E-01 3.77E-01 9.40E-01 1.24E+00 1.33E+00 2.24E+00 2.2

 Nonmetropolitan 863000 44 1.92 6.44E-01 9.64E-02 1.25E-01 1.65E-01 1.89E-01 3.10E-01 5.10E-01 6.65E-01 1.22E+00 1.45E+00 4.48E+00 4.4

 Suburban 613000 23 0.71 1.10E+00 1.34E-01 2.86E-01 2.88E-01 3.01E-01 4.67E-01 1.04E+00 1.47E+00 1.79E+00 2.67E+00 2.67E+00 2.6

Race

 Black 22000 1 0.10 * * * * * * * * * * * 

 White 2019000 86 1.28 7.82E-01 6.90E-02 1.25E-01 1.84E-01 2.41E-01 3.16E-01 5.55E-01 1.10E+00 1.47E+00 1.79E+00 3.02E+00 4.4

Region

 Midwest 1370000 54 2.95 8.21E-01 9.68E-02 1.25E-01 2.34E-01 2.41E-01 3.18E-01 5.72E-01 1.04E+00 1.73E+00 2.67E+00 3.02E+00 4.4

 Northeast 15000 1 0.04 * * * * * * * * * * * 

 South 179000 10 0.28 * * * * * * * * * * * 

 West 477000 22 1.32 7.87E-01 9.65E-02 1.76E-01 1.89E-01 3.08E-01 3.71E-01 7.44E-01 1.17E+00 1.47E+00 1.51E+00 1.51E+00 1.5

Response to Questionnaire

 Households who garden 1987000 85 2.92 7.70E-01 6.93E-02 1.25E-01 1.84E-01 2.41E-01 3.16E-01 5.55E-01 1.04E+00 1.46E+00 1.79E+00 3.02E+00 4.4

 Households who farm 449000 18 6.13 * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-57. Consumer Only Intake of Homegrown Snap Beans (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P

Total 12308000 739 6.55 8.00E-01 3.02E-02 5.65E-02 1.49E-01 1.88E-01 3.38E-01 5.69E-01 1.04E+00 1.58E+00 2.01E+00 3.90E+00 9.9

Age

 01-02 246000 17 4.32 * * * * * * * * * * * 

 03-05 455000 32 5.62 1.49E+00 2.37E-01 0.00E+00 0.00E+00 3.49E-01 9.01E-01 1.16E+00 1.66E+00 3.20E+00 4.88E+00 6.90E+00 6.9

 06-11 862000 62 5.16 8.97E-01 1.15E-01 0.00E+00 1.99E-01 2.21E-01 3.21E-01 6.42E-01 1.21E+00 1.79E+00 2.75E+00 4.81E+00 5.6

 12-19 1151000 69 5.62 6.38E-01 6.10E-02 0.00E+00 1.61E-01 2.22E-01 3.20E-01 5.04E-01 8.11E-01 1.34E+00 1.79E+00 2.72E+00 2.7

 20-39 2677000 160 4.35 6.13E-01 4.09E-02 7.05E-02 1.31E-01 1.57E-01 2.60E-01 4.96E-01 7.85E-01 1.24E+00 1.64E+00 2.05E+00 4.2

 40-69 4987000 292 8.79 7.19E-01 3.20E-02 9.99E-02 1.61E-01 2.28E-01 3.62E-01 5.61E-01 8.59E-01 1.45E+00 1.77E+00 2.70E+00 4.2

 70 + 1801000 100 11.34 9.15E-01 1.16E-01 5.65E-02 7.44E-02 1.51E-01 3.69E-01 6.38E-01 1.22E+00 1.70E+00 2.01E+00 9.96E+00 9.9

Season

 Fall 3813000 137 8.00 8.12E-01 8.19E-02 5.65E-02 1.50E-01 1.83E-01 2.72E-01 5.39E-01 1.18E+00 1.52E+00 2.01E+00 4.82E+00 9.9

 Spring 2706000 288 5.86 9.00E-01 5.44E-02 2.93E-02 1.51E-01 2.19E-01 3.70E-01 5.91E-01 1.11E+00 1.72E+00 2.85E+00 5.66E+00 6.9

 Summer 2946000 98 6.48 6.33E-01 4.81E-02 0.00E+00 1.18E-01 1.57E-01 3.31E-01 5.04E-01 8.50E-01 1.30E+00 1.70E+00 2.05E+00 2.6

 Winter 2843000 216 5.84 8.64E-01 5.28E-02 1.14E-01 1.80E-01 2.44E-01 4.24E-01 6.20E-01 1.12E+00 1.72E+00 2.02E+00 3.85E+00 7.8

Urbanization

 Central City 2205000 78 3.91 5.97E-01 5.59E-02 5.65E-02 7.44E-02 1.59E-01 2.56E-01 5.12E-01 7.12E-01 1.23E+00 1.54E+00 1.93E+00 3.3

 Nonmetropolitan 5696000 404 12.65 9.61E-01 5.06E-02 9.35E-02 1.77E-01 2.29E-01 3.67E-01 6.75E-01 1.19E+00 1.89E+00 2.70E+00 4.88E+00 9.9

 Suburban 4347000 255 5.02 7.04E-01 3.76E-02 9.67E-02 1.39E-01 1.88E-01 3.41E-01 5.20E-01 9.32E-01 1.36E+00 1.77E+00 2.98E+00 6.0

Race

 Black 634000 36 2.92 7.55E-01 1.43E-01 2.51E-01 2.51E-01 2.79E-01 2.99E-01 4.78E-01 1.04E+00 1.30E+00 1.34E+00 5.98E+00 5.9

 White 11519000 694 7.31 8.10E-01 3.12E-02 7.05E-02 1.50E-01 1.89E-01 3.49E-01 5.73E-01 1.06E+00 1.63E+00 2.01E+00 3.90E+00 9.9

Region

 Midwest 4651000 307 10.02 8.60E-01 6.11E-02 7.44E-02 1.54E-01 1.89E-01 3.36E-01 5.50E-01 9.88E-01 1.70E+00 2.47E+00 4.88E+00 9.9

 Northeast 990000 52 2.40 5.66E-01 6.63E-02 0.00E+00 9.66E-02 1.06E-01 1.81E-01 4.91E-01 8.15E-01 1.28E+00 1.36E+00 1.97E+00 3.0

 South 4755000 286 7.39 8.82E-01 4.04E-02 1.33E-01 2.13E-01 2.51E-01 3.98E-01 6.75E-01 1.22E+00 1.72E+00 2.01E+00 3.23E+00 5.9

 West 1852000 92 5.14 5.92E-01 4.35E-02 7.05E-02 1.43E-01 1.83E-01 2.72E-01 5.14E-01 7.41E-01 1.20E+00 1.52E+00 2.19E+00 2.1

Response to Questionnaire

 Households who garden 11843000 700 17.38 7.90E-01 3.08E-02 5.65E-02 1.49E-01 1.87E-01 3.31E-01 5.63E-01 1.02E+00 1.60E+00 2.01E+00 3.85E+00 9.9

 Households who farm 2591000 157 35.35 7.95E-01 4.78E-02 5.65E-02 1.27E-01 1.89E-01 4.05E-01 6.59E-01 1.12E+00 1.54E+00 1.98E+00 2.96E+00 4.2

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-58. Consumer Only Intake of Homegrown Strawberries (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 2057000 139 1.09 6.52E-01 5.15E-02 4.15E-02 8.16E-02 1.18E-01 2.55E-01 4.67E-01 8.20E-01 1.47E+00 1.77E+00 2.72E+00 4.83E+00 

Age

 01-02 30000 2 0.53 * * * * * * * * * * * *

 03-05 66000 6 0.81 * * * * * * * * * * * *

 06-11 153000 15 0.92 * * * * * * * * * * * *

 12-19 201000 11 0.98 * * * * * * * * * * * *

 20-39 316000 22 0.51 3.21E-01 6.41E-02 7.92E-02 8.16E-02 1.05E-01 1.18E-01 2.05E-01 4.59E-01 8.20E-01 9.73E-01 1.56E+00 1.56E+00

 40-69 833000 55 1.47 6.44E-01 6.37E-02 2.44E-02 6.53E-02 1.75E-01 3.55E-01 5.83E-01 9.41E-01 1.42E+00 1.47E+00 2.37E+00 2.37E+00

 70 + 449000 27 2.83 6.36E-01 1.11E-01 4.15E-02 4.41E-02 8.64E-02 2.62E-01 4.69E-01 7.00E-01 1.66E+00 1.89E+00 2.72E+00 2.72E+00 

Season

 Fall 250000 8 0.52 * * * * * * * * * * * *

 Spring 598000 66 1.30 8.30E-01 1.03E-01 7.92E-02 8.92E-02 1.80E-01 2.75E-01 4.69E-01 9.73E-01 1.93E+00 2.54E+00 4.83E+00 4.83E+00

 Summer 388000 11 0.85 * * * * * * * * * * * *

 Winter 821000 54 1.69 5.13E-01 6.42E-02 2.44E-02 4.41E-02 1.05E-01 2.07E-01 3.86E-01 6.01E-01 1.27E+00 1.46E+00 2.37E+00 2.37E+00 

Urbanization

 Central City 505000 23 0.90 7.54E-01 1.22E-01 4.15E-02 4.41E-02 8.92E-02 3.82E-01 4.88E-01 1.33E+00 1.47E+00 1.69E+00 2.37E+00 2.37E+00

 Nonmetropolitan 664000 52 1.47 6.18E-01 1.05E-01 2.44E-02 6.53E-02 8.16E-02 1.25E-01 3.85E-01 8.14E-01 1.66E+00 2.16E+00 4.83E+00 4.83E+00

 Suburban 888000 64 1.03 6.20E-01 5.88E-02 7.92E-02 1.81E-01 2.21E-01 3.45E-01 5.30E-01 6.96E-01 1.27E+00 1.56E+00 2.97E+00 2.97E+00 

Race

 Black 0 0 0.00

 White 2057000 139 1.31 6.52E-01 5.15E-02 4.15E-02 8.16E-02 1.18E-01 2.55E-01 4.67E-01 8.20E-01 1.47E+00 1.77E+00 2.72E+00 4.83E+00 

Region

 Midwest 1123000 76 2.42 6.85E-01 8.28E-02 2.44E-02 6.53E-02 8.16E-02 1.82E-01 4.16E-01 1.00E+00 1.66E+00 1.93E+00 2.97E+00 4.83E+00

 Northeast 382000 25 0.93 6.35E-01 1.01E-01 8.92E-02 1.59E-01 1.82E-01 2.55E-01 4.67E-01 8.65E-01 1.46E+00 1.83E+00 2.16E+00 2.16E+00

 South 333000 23 0.52 6.69E-01 8.41E-02 1.33E-01 2.05E-01 3.77E-01 5.15E-01 6.21E-01 6.96E-01 1.00E+00 1.00E+00 2.72E+00 2.72E+00

 West 219000 15 0.61 * * * * * * * * * * * * 

Response to Questionnaire

 Households who garden 1843000 123 2.70 6.37E-01 5.48E-02 4.15E-02 7.92E-02 1.18E-01 2.28E-01 4.53E-01 8.20E-01 1.46E+00 1.77E+00 2.54E+00 4.83E+00

 Households who farm 87000 9 1.19 * * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-59. Consumer Only Intake of Homegrown Tomatoes (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P1

Total 16737000 743 8.90 1.18E+00 5.26E-02 7.57E-02 1.52E-01 2.34E-01 3.92E-01 7.43E-01 1.46E+00 2.50E+00 3.54E+00 7.26E+00 1.93

Age

 01-02 572000 26 10.04 3.14E+00 5.30E-01 7.26E-01 8.55E-01 9.34E-01 1.23E+00 1.66E+00 4.00E+00 7.26E+00 1.07E+01 1.07E+01 1.07

 03-05 516000 26 6.37 1.61E+00 2.65E-01 4.96E-01 5.07E-01 5.07E-01 7.54E-01 1.25E+00 1.65E+00 3.00E+00 6.25E+00 6.25E+00 6.25

 06-11 1093000 51 6.54 1.63E+00 2.68E-01 2.17E-01 3.10E-01 3.92E-01 5.30E-01 7.55E-01 1.66E+00 5.20E+00 5.70E+00 9.14E+00 9.14

 12-19 1411000 61 6.89 7.15E-01 8.52E-02 0.00E+00 0.00E+00 1.82E-01 2.68E-01 5.21E-01 8.50E-01 1.67E+00 1.94E+00 3.39E+00 3.39

 20-39 4169000 175 6.77 8.54E-01 1.03E-01 7.32E-02 1.31E-01 1.47E-01 2.54E-01 5.15E-01 1.00E+00 1.83E+00 2.10E+00 5.52E+00 1.93

 40-69 6758000 305 11.92 1.05E+00 5.23E-02 1.13E-01 1.73E-01 2.81E-01 3.97E-01 7.46E-01 1.41E+00 2.40E+00 3.05E+00 4.50E+00 5.00

 70 + 1989000 89 12.53 1.26E+00 9.40E-02 1.13E-01 2.36E-01 2.98E-01 4.82E-01 1.14E+00 1.77E+00 2.51E+00 2.99E+00 3.67E+00 3.67

Season

 Fall 5516000 201 11.57 1.02E+00 8.55E-02 7.32E-02 1.35E-01 2.23E-01 3.43E-01 5.95E-01 1.34E+00 2.24E+00 2.87E+00 6.25E+00 1.07

 Spring 1264000 127 2.74 8.39E-01 6.26E-02 1.36E-01 1.89E-01 2.39E-01 3.73E-01 6.31E-01 1.11E+00 1.75E+00 2.00E+00 3.79E+00 5.28

 Summer 8122000 279 17.86 1.30E+00 8.75E-02 1.05E-01 1.66E-01 2.36E-01 4.08E-01 8.03E-01 1.55E+00 3.05E+00 4.05E+00 7.26E+00 1.09

 Winter 1835000 136 3.77 1.37E+00 1.77E-01 9.07E-02 2.07E-01 2.85E-01 4.97E-01 8.29E-01 1.49E+00 2.48E+00 3.38E+00 8.29E+00 1.93

Urbanization

 Central City 2680000 90 4.76 1.10E+00 1.27E-01 0.00E+00 1.52E-01 2.25E-01 3.54E-01 7.54E-01 1.51E+00 2.16E+00 2.95E+00 7.26E+00 8.29

 Nonmetropolitan 7389000 378 16.41 1.26E+00 7.35E-02 1.13E-01 2.16E-01 2.62E-01 4.23E-01 7.62E-01 1.47E+00 2.77E+00 3.85E+00 6.87E+00 1.07

 Suburban 6668000 275 7.70 1.13E+00 9.14E-02 7.57E-02 1.35E-01 1.78E-01 3.70E-01 6.68E-01 1.38E+00 2.35E+00 3.32E+00 5.52E+00 1.93

Race

 Black 743000 28 3.42 6.14E-01 8.60E-02 0.00E+00 0.00E+00 7.32E-02 2.36E-01 5.07E-01 9.02E-01 1.18E+00 1.55E+00 1.66E+00 1.66

 White 15658000 703 9.94 1.22E+00 5.54E-02 1.05E-01 1.68E-01 2.41E-01 4.06E-01 7.55E-01 1.49E+00 2.55E+00 3.59E+00 7.26E+00 1.93

Region

 Midwest 6747000 322 14.54 1.18E+00 8.91E-02 6.34E-02 1.45E-01 2.06E-01 3.62E-01 6.82E-01 1.41E+00 2.51E+00 3.69E+00 6.87E+00 1.93

 Northeast 2480000 87 6.02 1.17E+00 1.64E-01 7.57E-02 1.35E-01 1.48E-01 3.50E-01 7.51E-01 1.38E+00 2.44E+00 3.52E+00 1.09E+01 1.09

 South 4358000 202 6.77 1.15E+00 9.07E-02 0.00E+00 2.07E-01 2.53E-01 4.23E-01 7.46E-01 1.43E+00 2.32E+00 3.67E+00 6.82E+00 9.14

 West 3152000 132 8.74 1.23E+00 9.90E-02 1.80E-01 2.39E-01 2.84E-01 4.11E-01 7.65E-01 1.84E+00 2.78E+00 3.08E+00 7.26E+00 7.26

Response to Questionnaire

 Households who garden 14791000 661 21.70 1.21E+00 5.70E-02 7.57E-02 1.52E-01 2.34E-01 4.06E-01 7.58E-01 1.50E+00 2.51E+00 3.52E+00 7.26E+00 1.93

 Households who farm 2269000 112 30.96 1.42E+00 1.58E-01 0.00E+00 1.80E-01 2.26E-01 4.23E-01 7.66E-01 1.86E+00 3.55E+00 5.20E+00 9.14E+00 9.14

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-60. Consumer Only Intake of Homegrown White Potatoes (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P10

Total 5895000 281 3.14 1.66E+00 1.05E-01 0.00E+00 1.87E-01 3.08E-01 5.50E-01 1.27E+00 2.07E+00 3.11E+00 4.76E+00 9.52E+00 1.28E

Age

 01-02 147000 10 2.58 * * * * * * * * * * * *

 03-05 119000 6 1.47 * * * * * * * * * * * *

 06-11 431000 24 2.58 2.19E+00 3.85E-01 0.00E+00 0.00E+00 4.10E-01 7.20E-01 1.76E+00 3.10E+00 5.94E+00 6.52E+00 6.52E+00 6.52E

 12-19 751000 31 3.67 1.26E+00 1.85E-01 6.67E-02 1.87E-01 2.59E-01 3.84E-01 1.22E+00 1.80E+00 2.95E+00 3.11E+00 4.14E+00 4.14E

 20-39 1501000 66 2.44 1.24E+00 1.21E-01 1.64E-01 1.64E-01 1.96E-01 4.77E-01 1.00E+00 1.62E+00 2.54E+00 3.08E+00 4.29E+00 5.09E

 40-69 1855000 95 3.27 1.86E+00 2.29E-01 1.27E-01 2.62E-01 3.50E-01 6.99E-01 1.31E+00 2.04E+00 3.43E+00 5.29E+00 1.28E+01 1.28E

 70 + 1021000 45 6.43 1.27E+00 1.22E-01 2.06E-01 2.17E-01 3.57E-01 5.50E-01 1.21E+00 1.69E+00 2.35E+00 2.88E+00 3.92E+00 3.92E

Season

 Fall 2267000 86 4.76 1.63E+00 2.23E-01 1.64E-01 2.23E-01 2.65E-01 4.61E-01 1.13E+00 1.79E+00 3.43E+00 4.14E+00 1.28E+01 1.28E

 Spring 527000 58 1.14 1.23E+00 1.28E-01 6.67E-02 1.05E-01 1.96E-01 4.10E-01 8.55E-01 1.91E+00 2.86E+00 3.08E+00 4.28E+00 4.28E

 Summer 2403000 81 5.28 1.63E+00 1.82E-01 0.00E+00 1.87E-01 3.19E-01 6.20E-01 1.32E+00 2.09E+00 3.08E+00 5.29E+00 9.43E+00 9.43E

 Winter 698000 56 1.43 2.17E+00 1.98E-01 1.41E-01 3.95E-01 4.97E-01 8.64E-01 2.02E+00 2.95E+00 4.26E+00 5.40E+00 6.00E+00 6.00E

Urbanization

 Central City 679000 25 1.20 9.60E-01 1.51E-01 1.64E-01 1.64E-01 1.75E-01 3.75E-01 5.55E-01 1.52E+00 2.07E+00 2.25E+00 2.54E+00 2.54E

 Nonmetropolitan 3046000 159 6.77 1.96E+00 1.55E-01 1.84E-01 2.65E-01 3.68E-01 7.67E-01 1.50E+00 2.38E+00 3.55E+00 5.64E+00 1.28E+01 1.28E

 Suburban 2110000 95 2.44 1.49E+00 1.67E-01 1.05E-01 1.87E-01 3.19E-01 5.40E-01 9.29E-01 1.68E+00 3.11E+00 4.76E+00 9.43E+00 9.43E

Race

 Black 140000 5 0.64 * * * * * * * * * * * *

 White 5550000 269 3.52 1.67E+00 1.09E-01 1.41E-01 2.06E-01 3.08E-01 5.50E-01 1.28E+00 2.09E+00 3.11E+00 4.76E+00 9.52E+00 1.28E

Region

 Midwest 2587000 133 5.58 1.77E+00 1.47E-01 1.75E-01 2.36E-01 3.39E-01 6.41E-01 1.35E+00 2.15E+00 3.77E+00 5.29E+00 9.43E+00 9.43E

 Northeast 656000 31 1.59 1.28E+00 2.04E-01 6.67E-02 1.27E-01 1.67E-01 3.48E-01 8.64E-01 1.97E+00 2.95E+00 3.80E+00 5.09E+00 5.09E

 South 1796000 84 2.79 2.08E+00 2.39E-01 1.64E-01 3.50E-01 4.61E-01 9.24E-01 1.56E+00 2.40E+00 3.44E+00 5.64E+00 1.28E+01 1.28E

 West 796000 31 2.21 7.61E-01 1.05E-01 1.64E-01 2.16E-01 2.59E-01 4.11E-01 5.43E-01 9.63E-01 1.40E+00 1.95E+00 3.11E+00 3.11E

Response to Questionnaire

 Households who garden 5291000 250 7.76 1.65E+00 1.09E-01 0.00E+00 2.06E-01 3.08E-01 5.55E-01 1.28E+00 2.09E+00 3.10E+00 4.28E+00 9.52E+00 1.28E

 Households who farm 1082000 62 14.76 1.83E+00 1.78E-01 6.67E-02 2.06E-01 5.76E-01 9.24E-01 1.46E+00 2.31E+00 3.80E+00 5.09E+00 6.52E+00 6.52E

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-61. Consumer Only Intake of Homegrown Exposed Fruit (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 11770000 679 6.26 1.49E+00 8.13E-02 4.41E-02 1.37E-01 2.55E-01 4.46E-01 8.33E-01 1.70E+00 3.16E+00 4.78E+00 1.20E+01 3.25E+0

Age

 01-02 306000 19 5.37 * * * * * * * * * * * *

 03-05 470000 30 5.80 2.60E+00 7.78E-01 0.00E+00 0.00E+00 3.73E-01 1.00E+00 1.82E+00 2.64E+00 5.41E+00 6.07E+00 3.25E+01 3.25E+0

 06-11 915000 68 5.48 2.52E+00 4.24E-01 0.00E+00 1.71E-01 3.73E-01 6.19E-01 1.11E+00 2.91E+00 6.98E+00 1.17E+01 1.57E+01 1.59E+0

 12-19 896000 50 4.37 1.33E+00 2.06E-01 8.46E-02 1.23E-01 2.58E-01 4.04E-01 6.09E-01 2.27E+00 3.41E+00 4.78E+00 5.90E+00 5.90E+0

 20-39 2521000 139 4.09 1.09E+00 1.44E-01 7.93E-02 1.30E-01 1.67E-01 3.04E-01 6.15E-01 1.07E+00 2.00E+00 3.58E+00 1.29E+01 1.29E+0

 40-69 4272000 247 7.53 1.25E+00 1.10E-01 6.46E-02 1.64E-01 2.54E-01 4.39E-01 7.19E-01 1.40E+00 2.61E+00 3.25E+00 1.30E+01 1.30E+0

 70 + 2285000 118 14.39 1.39E+00 1.17E-01 4.41E-02 2.07E-01 2.82E-01 5.71E-01 9.57E-01 1.66E+00 3.73E+00 4.42E+00 5.39E+00 7.13E+0

Season

 Fall 2877000 100 6.04 1.37E+00 1.16E-01 2.59E-01 2.91E-01 3.42E-01 5.43E-01 1.03E+00 1.88E+00 2.88E+00 4.25E+00 5.41E+00 5.41E+0

 Spring 2466000 265 5.34 1.49E+00 1.51E-01 8.91E-02 1.98E-01 2.54E-01 4.32E-01 8.56E-01 1.65E+00 2.91E+00 4.67E+00 8.27E+00 3.25E+0

 Summer 3588000 122 7.89 1.75E+00 2.50E-01 0.00E+00 8.66E-02 1.30E-01 3.89E-01 6.41E-01 1.76E+00 4.29E+00 6.12E+00 1.30E+01 1.57E+0

 Winter 2839000 192 5.83 1.27E+00 1.06E-01 4.15E-02 1.04E-01 2.31E-01 4.59E-01 8.29E-01 1.55E+00 2.61E+00 4.66E+00 8.16E+00 1.13E+0

Urbanization

 Central City 2552000 99 4.53 1.34E+00 1.98E-01 4.41E-02 1.01E-01 2.59E-01 4.46E-01 8.63E-01 1.60E+00 2.37E+00 2.88E+00 1.30E+01 1.30E+0

 Nonmetropolitan 3891000 269 8.64 1.78E+00 1.67E-01 6.46E-02 1.04E-01 1.67E-01 4.15E-01 9.42E-01 1.94E+00 4.07E+00 5.98E+00 1.57E+01 3.25E+0

 Suburban 5267000 309 6.08 1.36E+00 9.00E-02 9.18E-02 2.07E-01 2.93E-01 4.69E-01 7.73E-01 1.65E+00 3.16E+00 4.67E+00 7.29E+00 1.29E+0

Race

 Black 250000 12 1.15 * * * * * * * * * * * *

 White 11411000 663 7.24 1.51E+00 8.33E-02 6.49E-02 1.55E-01 2.59E-01 4.49E-01 8.56E-01 1.72E+00 3.31E+00 4.78E+00 1.20E+01 3.25E+0

Region

 Midwest 4429000 293 9.55 1.60E+00 1.42E-01 4.41E-02 1.25E-01 2.23E-01 4.23E-01 8.78E-01 1.88E+00 3.58E+00 4.78E+00 1.20E+01 3.25E+0

 Northeast 1219000 69 2.96 7.55E-01 1.18E-01 8.08E-02 8.66E-02 1.65E-01 3.00E-01 4.74E-01 7.84E-01 1.39E+00 2.86E+00 5.21E+00 7.13E+0

 South 2532000 141 3.94 1.51E+00 1.84E-01 7.93E-02 2.32E-01 3.01E-01 5.08E-01 9.16E-01 1.63E+00 2.63E+00 5.98E+00 1.57E+01 1.57E+0

 West 3530000 174 9.79 1.60E+00 1.43E-01 1.00E-01 2.40E-01 3.17E-01 5.69E-01 9.57E-01 1.97E+00 3.72E+00 5.00E+00 1.30E+01 1.30E+0

Response to Questionnaire

 Households who garden 10197000 596 14.96 1.55E+00 9.12E-02 4.15E-02 1.58E-01 2.58E-01 4.49E-01 8.78E-01 1.73E+00 3.41E+00 5.00E+00 1.29E+01 3.25E+0

 Households who farm 1917000 112 26.16 2.32E+00 2.50E-01 7.21E-02 2.76E-01 3.71E-01 6.81E-01 1.30E+00 3.14E+00 5.00E+00 6.12E+00 1.57E+01 1.57E+0

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-62. Consumer Only Intake of Homegrown Protected Fruits (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 3855000 173 2.05 5.74E+00 6.25E-01 1.50E-01 2.66E-01 3.35E-01 9.33E-01 2.34E+00 7.45E+00 1.60E+01 1.97E+01 4.73E+01 5.36E+0

Age

 01-02 79000 5 1.39 * * * * * * * * * * * *

 03-05 80000 4 0.99 * * * * * * * * * * * *

 06-11 181000 9 1.08 * * * * * * * * * * * *

 12-19 377000 20 1.84 2.96E+00 9.93E-01 1.17E-01 1.60E-01 2.83E-01 3.93E-01 1.23E+00 2.84E+00 7.44E+00 1.14E+01 1.91E+01 1.91E+0

 20-39 755000 29 1.23 4.51E+00 1.08E+00 1.81E-01 3.62E-01 4.87E-01 1.22E+00 1.88E+00 4.47E+00 1.46E+01 1.61E+01 2.41E+01 2.41E+0

 40-69 1702000 77 3.00 5.65E+00 8.66E-01 1.12E-01 2.44E-01 2.87E-01 6.69E-01 2.22E+00 9.36E+00 1.55E+01 2.12E+01 4.13E+01 4.13E+0

 70 + 601000 26 3.78 4.44E+00 6.91E-01 2.62E-01 2.62E-01 2.85E-01 1.95E+00 3.29E+00 7.06E+00 8.97E+00 9.97E+00 1.52E+01 1.52E+0

Season

 Fall 394000 12 0.83 * * * * * * * * * * * *

 Spring 497000 36 1.08 2.08E+00 3.47E-01 1.60E-01 1.81E-01 2.55E-01 3.78E-01 1.22E+00 4.08E+00 5.10E+00 6.57E+00 6.79E+00 6.79E+00

 Summer 1425000 47 3.13 7.39E+00 1.45E+00 1.12E-01 2.66E-01 3.93E-01 1.25E+00 3.06E+00 1.03E+01 1.66E+01 2.41E+01 5.36E+01 5.36E+0

 Winter 1539000 78 3.16 6.24E+00 9.10E-01 1.50E-01 3.02E-01 3.76E-01 1.39E+00 2.65E+00 8.23E+00 1.78E+01 2.12E+01 4.73E+01 4.73E+0

Urbanization

 Central City 1312000 50 2.33 3.94E+00 5.80E-01 1.50E-01 2.62E-01 3.33E-01 8.34E-01 3.01E+00 5.01E+00 9.23E+00 9.97E+00 1.88E+01 1.88E+0

 Nonmetropolitan 506000 19 1.12 * * * * * * * * * * * *

 Suburban 2037000 104 2.35 6.83E+00 9.38E-01 1.12E-01 2.53E-01 2.92E-01 5.94E-01 2.01E+00 1.03E+01 1.79E+01 2.38E+01 5.36E+01 5.36E+0

Race

 Black 200000 8 0.92 * * * * * * * * * * * *

 White 3655000 165 2.32 5.91E+00 6.48E-01 1.17E-01 2.62E-01 3.33E-01 1.06E+00 2.44E+00 7.46E+00 1.60E+01 2.12E+01 4.73E+01 5.36E+0

Region

 Midwest 657000 24 1.42 1.07E+01 2.60E+00 2.53E-01 2.62E-01 2.85E-01 1.18E+00 7.44E+00 1.46E+01 2.41E+01 4.13E+01 5.36E+01 5.36E+0

 Northeast 105000 5 0.26 * * * * * * * * * * * *

 South 1805000 74 2.81 4.77E+00 6.47E-01 1.60E-01 3.64E-01 4.50E-01 1.23E+00 2.54E+00 5.10E+00 1.52E+01 1.66E+01 2.38E+01 2.40E+0

 West 1288000 70 3.57 4.85E+00 9.26E-01 1.12E-01 1.81E-01 2.68E-01 4.94E-01 1.84E+00 5.34E+00 1.23E+01 1.88E+01 4.73E+01 4.73E+0

Response to Questionnaire

 Households who garden 3360000 146 4.93 5.90E+00 6.97E-01 1.17E-01 2.65E-01 3.35E-01 1.16E+00 2.42E+00 7.46E+00 1.60E+01 1.91E+01 4.73E+01 5.36E+0

 Households who farm 357000 14 4.87 * * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-63. Consumer Only Intake of Homegrown Exposed Vegetables (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 

Total 28762000 1511 15.30 1.52E+00 5.10E-02 3.25E-03 9.15E-02 1.72E-01 3.95E-01 8.60E-01 1.83E+00 3.55E+00 5.12E+00 1.03E+01 2.0

Age

 01-02 815000 43 14.30 3.48E+00 5.14E-01 2.28E-02 2.39E-01 8.34E-01 1.20E+00 1.89E+00 4.23E+00 1.07E+01 1.19E+01 1.21E+01 1.2

 03-05 1069000 62 13.19 1.74E+00 2.20E-01 0.00E+00 7.23E-03 4.85E-02 5.79E-01 1.16E+00 2.53E+00 3.47E+00 6.29E+00 7.36E+00 8.8

 06-11 2454000 134 14.68 1.39E+00 1.76E-01 0.00E+00 4.44E-02 9.42E-02 3.12E-01 6.43E-01 1.60E+00 3.22E+00 5.47E+00 1.33E+01 1.3

 12-19 2611000 143 12.74 1.07E+00 9.43E-02 0.00E+00 2.92E-02 1.42E-01 3.04E-01 6.56E-01 1.46E+00 2.35E+00 3.78E+00 5.67E+00 5.6

 20-39 6969000 348 11.31 1.05E+00 8.14E-02 8.20E-03 6.56E-02 1.17E-01 2.55E-01 5.58E-01 1.26E+00 2.33E+00 3.32E+00 7.57E+00 2.0

 40-69 10993000 579 19.38 1.60E+00 8.32E-02 3.25E-03 1.41E-01 2.44E-01 4.79E-01 9.81E-01 1.92E+00 3.59E+00 5.22E+00 8.99E+00 1.9

 70 + 3517000 185 22.15 1.68E+00 1.21E-01 5.21E-03 1.51E-01 2.39E-01 5.22E-01 1.13E+00 2.38E+00 4.08E+00 4.96E+00 6.96E+00 1.0

Season

 Fall 8865000 314 18.60 1.31E+00 9.80E-02 5.24E-02 1.11E-01 1.80E-01 3.33E-01 6.49E-01 1.56E+00 3.13E+00 4.45E+00 8.92E+00 1.2

 Spring 4863000 487 10.54 1.14E+00 6.35E-02 2.35E-03 4.53E-02 1.53E-01 3.38E-01 6.58E-01 1.39E+00 2.76E+00 4.02E+00 7.51E+00 1.0

 Summer 10151000 348 22.32 2.03E+00 1.26E-01 2.17E-03 1.13E-01 2.04E-01 6.07E-01 1.30E+00 2.52E+00 4.32E+00 6.35E+00 1.27E+01 1.9

 Winter 4883000 362 10.02 1.21E+00 9.50E-02 4.23E-03 2.28E-02 1.37E-01 3.70E-01 6.67E-01 1.42E+00 2.76E+00 3.69E+00 8.86E+00 2.0

Urbanization

 Central City 4859000 173 8.62 1.11E+00 1.02E-01 1.01E-02 6.04E-02 8.02E-02 2.83E-01 7.01E-01 1.43E+00 2.49E+00 3.29E+00 8.34E+00 1.2

 Nonmetropolitan 11577000 711 25.71 1.87E+00 8.79E-02 1.65E-02 1.72E-01 2.52E-01 5.01E-01 1.16E+00 2.20E+00 4.12E+00 6.10E+00 1.22E+01 1.9

 Suburban 12266000 625 14.17 1.35E+00 7.01E-02 2.93E-03 9.68E-02 1.56E-01 3.55E-01 7.44E-01 1.58E+00 3.22E+00 5.22E+00 8.61E+00 2.0

Race

 Black 1713000 100 7.88 1.23E+00 1.27E-01 0.00E+00 7.74E-02 1.41E-01 3.52E-01 8.93E-01 1.51E+00 3.32E+00 3.92E+00 5.55E+00 7.1

 White 26551000 1386 16.85 1.53E+00 5.41E-02 4.67E-03 9.74E-02 1.77E-01 3.95E-01 8.59E-01 1.82E+00 3.48E+00 5.12E+00 1.03E+01 2.0

Region

 Midwest 10402000 570 22.42 1.48E+00 8.91E-02 1.00E-02 7.14E-02 1.57E-01 3.88E-01 8.06E-01 1.69E+00 3.55E+00 4.67E+00 1.19E+01 2.0

 Northeast 4050000 191 9.84 1.65E+00 1.78E-01 2.35E-03 8.05E-02 1.38E-01 2.61E-01 6.65E-01 1.75E+00 5.58E+00 6.80E+00 1.27E+01 1.4

 South 9238000 503 14.36 1.55E+00 7.79E-02 5.20E-02 1.63E-01 2.61E-01 5.18E-01 9.99E-01 1.92E+00 3.19E+00 4.52E+00 9.92E+00 1.3

 West 5012000 245 13.90 1.43E+00 1.02E-01 3.25E-03 2.61E-02 1.45E-01 3.91E-01 7.63E-01 2.13E+00 3.45E+00 4.84E+00 7.51E+00 8.3

Response to Questionnaire

 Households who garden 25737000 1361 37.76 1.57 5.50E-02 3.25E-03 8.87E-02 1.68E-01 4.13E-01 8.89E-01 1.97E+00 3.63E+00 5.45E+00 1.03E+01 2.0

 Households who farm 3596000 207 49.07 2.17 1.61E-01 0.00E+00 1.84E-01 3.72E-01 6.47E-01 1.38E+00 2.81E+00 6.01E+00 6.83E+00 1.03E+01 1.3

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-64. Consumer Only Intake of Homegrown Protected Vegetables (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P1

Total 11428000 656 6.08 1.01E+00 4.95E-02 1.03E-01 1.54E-01 1.94E-01 3.22E-01 6.25E-01 1.20E+00 2.24E+00 3.05E+00 6.49E+00 9.42

Age

 01-02 348000 21 6.11 2.46E+00 4.91E-01 3.15E-01 3.15E-01 5.38E-01 1.36E+00 1.94E+00 2.96E+00 3.88E+00 9.42E+00 9.42E+00 9.42

 03-05 440000 32 5.43 1.30E+00 2.13E-01 2.33E-01 2.33E-01 3.22E-01 4.80E-01 1.04E+00 1.48E+00 2.51E+00 5.10E+00 5.31E+00 5.31

 06-11 1052000 63 6.30 1.10E+00 1.34E-01 1.89E-01 2.08E-01 3.18E-01 3.87E-01 7.91E-01 1.31E+00 2.14E+00 3.12E+00 5.40E+00 5.40

 12-19 910000 51 4.44 7.76E-01 8.71E-02 5.88E-02 1.61E-01 2.39E-01 3.54E-01 5.83E-01 8.24E-01 1.85E+00 2.20E+00 2.69E+00 2.69

 20-39 3227000 164 5.24 7.62E-01 6.03E-02 1.13E-01 1.52E-01 1.71E-01 2.41E-01 5.08E-01 9.67E-01 1.73E+00 2.51E+00 3.63E+00 4.76

 40-69 3818000 226 6.73 9.30E-01 7.32E-02 6.87E-02 1.35E-01 1.66E-01 3.16E-01 6.03E-01 1.11E+00 1.87E+00 3.04E+00 6.84E+00 7.44

 70 + 1442000 89 9.08 1.05E+00 1.62E-01 1.19E-01 2.10E-01 2.42E-01 3.57E-01 5.72E-01 1.21E+00 1.86E+00 3.05E+00 9.23E+00 9.23

Season

 Fall 3907000 143 8.20 8.51E-01 7.02E-02 1.19E-01 1.61E-01 2.04E-01 3.22E-01 5.68E-01 1.10E+00 1.73E+00 2.51E+00 4.78E+00 5.31

 Spring 2086000 236 4.52 7.02E-01 4.48E-02 5.88E-02 1.35E-01 1.70E-01 2.66E-01 4.90E-01 9.08E-01 1.44E+00 1.86E+00 3.74E+00 5.73

 Summer 3559000 118 7.82 1.40E+00 1.56E-01 1.03E-01 1.77E-01 2.33E-01 3.81E-01 7.81E-01 1.69E+00 3.05E+00 5.40E+00 9.23E+00 9.42

 Winter 1876000 159 3.85 9.30E-01 7.70E-02 1.18E-01 1.42E-01 1.82E-01 3.12E-01 6.01E-01 1.20E+00 2.32E+00 3.06E+00 4.76E+00 6.39

Urbanization

 Central City 1342000 49 2.38 9.96E-01 1.51E-01 1.19E-01 1.53E-01 1.67E-01 3.18E-01 7.21E-01 1.18E+00 2.36E+00 2.83E+00 4.78E+00 4.78

 Nonmetropolitan 5934000 391 13.18 1.07E+00 6.36E-02 1.14E-01 1.66E-01 2.14E-01 3.53E-01 6.48E-01 1.30E+00 2.51E+00 3.55E+00 6.84E+00 9.42

 Suburban 4152000 216 4.80 9.26E-01 7.97E-02 6.87E-02 1.50E-01 1.88E-01 2.94E-01 5.64E-01 1.15E+00 1.85E+00 2.67E+00 6.49E+00 9.23

Race

 Black 479000 27 2.20 1.50E+00 2.25E-01 1.62E-01 2.64E-01 3.31E-01 8.66E-01 9.35E-01 2.20E+00 3.05E+00 3.23E+00 4.95E+00 4.95

 White 10836000 625 6.88 9.93E-01 4.83E-02 1.03E-01 1.53E-01 1.92E-01 3.21E-01 6.10E-01 1.20E+00 2.17E+00 3.04E+00 6.49E+00 9.42

Region

 Midwest 4359000 273 9.40 1.01E+00 7.38E-02 1.13E-01 1.71E-01 2.31E-01 3.26E-01 5.72E-01 1.08E+00 2.45E+00 3.68E+00 6.84E+00 7.44

 Northeast 807000 48 1.96 7.01E-01 8.99E-02 5.88E-02 1.50E-01 1.68E-01 2.65E-01 5.09E-01 9.91E-01 1.71E+00 2.33E+00 2.77E+00 2.77

 South 4449000 253 6.92 1.08E+00 7.17E-02 1.29E-01 1.71E-01 2.14E-01 3.76E-01 7.12E-01 1.38E+00 2.32E+00 3.05E+00 5.40E+00 9.42

 West 1813000 82 5.03 9.57E-01 1.62E-01 6.87E-02 1.19E-01 1.52E-01 2.08E-01 4.79E-01 1.01E+00 1.86E+00 3.12E+00 9.23E+00 9.23

Response to Questionnaire

 Households who garden 10286000 602 15.09 1.01E+00 4.73E-02 1.03E-01 1.53E-01 1.92E-01 3.36E-01 6.42E-01 1.21E+00 2.32E+00 3.05E+00 6.49E+00 9.23

 Households who farm 2325000 142 31.72 1.30E+00 1.45E-01 8.65E-02 1.66E-01 2.09E-01 3.37E-01 5.99E-01 1.40E+00 3.55E+00 5.40E+00 9.23E+00 9.23

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-65. Consumer Only Intake of Homegrown Root Vegetables (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 13750000 743 7.31 1.16E+00 5.84E-02 4.72E-03 3.64E-02 1.12E-01 2.51E-01 6.66E-01 1.47E+00 2.81E+00 3.71E+00 9.52E+00 1.28E+01 

Age

 01-02 371000 22 6.51 2.52E+00 6.10E-01 1.66E-01 1.66E-01 2.19E-01 3.59E-01 9.20E-01 3.67E+00 7.25E+00 1.04E+01 1.04E+01 1.04E+01

 03-05 390000 23 4.81 1.28E+00 3.24E-01 0.00E+00 0.00E+00 1.17E-01 2.25E-01 4.62E-01 1.68E+00 4.26E+00 4.73E+00 4.73E+00 4.73E+00

 06-11 1106000 67 6.62 1.32E+00 2.14E-01 0.00E+00 1.39E-02 3.64E-02 2.32E-01 5.23E-01 1.63E+00 3.83E+00 5.59E+00 7.47E+00 7.47E+00

 12-19 1465000 76 7.15 9.37E-01 1.19E-01 7.59E-03 8.00E-03 6.84E-02 2.69E-01 5.65E-01 1.37E+00 2.26E+00 3.32E+00 5.13E+00 5.13E+00

 20-39 3252000 164 5.28 8.74E-01 7.39E-02 1.21E-02 5.35E-02 9.93E-02 2.00E-01 5.64E-01 1.24E+00 2.11E+00 3.08E+00 4.64E+00 6.03E+00

 40-69 4903000 276 8.64 1.13E+00 9.86E-02 3.34E-03 3.29E-02 1.17E-01 2.51E-01 6.75E-01 1.27E+00 2.74E+00 3.56E+00 9.52E+00 1.28E+01

 70 + 2096000 107 13.20 1.22E+00 1.02E-01 1.73E-02 2.90E-02 1.69E-01 3.76E-01 8.51E-01 1.71E+00 2.86E+00 3.21E+00 4.01E+00 4.77E+00 

Season

 Fall 4026000 153 8.45 1.42E+00 1.53E-01 5.15E-02 1.38E-01 1.72E-01 3.09E-01 9.20E-01 1.67E+00 3.26E+00 3.85E+00 1.23E+01 1.28E+01

 Spring 2552000 260 5.53 6.87E-01 6.08E-02 3.34E-03 1.73E-02 3.00E-02 1.44E-01 3.65E-01 7.69E-01 1.69E+00 2.80E+00 4.24E+00 7.69E+00

 Summer 5011000 169 11.02 1.19E+00 1.20E-01 0.00E+00 4.76E-02 1.32E-01 2.77E-01 7.26E-01 1.51E+00 2.74E+00 3.64E+00 1.04E+01 1.19E+01

 Winter 2161000 161 4.44 1.17E+00 1.19E-01 3.23E-03 8.57E-03 4.34E-02 2.38E-01 5.57E-01 1.56E+00 3.08E+00 4.14E+00 6.21E+00 1.13E+01 

Urbanization

 Central City 2385000 96 4.23 7.49E-01 8.40E-02 2.68E-02 3.90E-02 1.43E-01 2.23E-01 4.26E-01 9.16E-01 1.91E+00 2.70E+00 3.56E+00 3.93E+00

 Nonmetropolitan 6094000 366 13.54 1.43E+00 9.81E-02 8.57E-03 6.87E-02 1.29E-01 2.78E-01 7.58E-01 1.85E+00 3.32E+00 4.24E+00 1.13E+01 1.28E+01

 Suburban 5211000 279 6.02 1.06E+00 8.62E-02 3.73E-03 1.21E-02 7.17E-02 2.32E-01 7.34E-01 1.19E+00 2.34E+00 3.26E+00 6.29E+00 1.19E+01 

Race

 Black 521000 31 2.40 8.83E-01 3.93E-01 4.72E-03 9.28E-03 3.64E-02 8.82E-02 5.42E-01 7.65E-01 1.06E+00 1.25E+00 1.23E+01 1.23E+01

 White 12861000 697 8.16 1.18E+00 5.97E-02 7.79E-03 4.58E-02 1.29E-01 2.61E-01 6.80E-01 1.50E+00 2.82E+00 3.72E+00 9.52E+00 1.28E+01 

Region

 Midwest 5572000 314 12.01 1.31E+00 9.54E-02 3.37E-02 7.48E-02 1.66E-01 2.69E-01 7.39E-01 1.67E+00 3.23E+00 4.26E+00 1.04E+01 1.19E+01

 Northeast 1721000 92 4.18 8.38E-01 1.03E-01 3.23E-03 7.79E-03 8.69E-03 1.43E-01 4.81E-01 1.18E+00 2.05E+00 2.77E+00 4.78E+00 6.03E+00

 South 3842000 205 5.97 1.38E+00 1.38E-01 1.10E-02 5.35E-02 1.32E-01 2.77E-01 6.90E-01 1.70E+00 3.32E+00 3.83E+00 1.23E+01 1.28E+01

 West 2555000 130 7.08 7.68E-01 6.43E-02 4.72E-03 2.24E-02 1.14E-01 2.38E-01 5.70E-01 9.77E-01 1.69E+00 2.45E+00 3.72E+00 3.72E+00 

Response to Questionnaire

 Households who garden 12578000 682 18.46 1.15E+00 5.72E-02 4.79E-03 3.64E-02 1.17E-01 2.58E-01 6.74E-01 1.50E+00 2.81E+00 3.64E+00 7.47E+00 1.28E+01

 Households who farm 2367000 136 32.30 1.39E+00 1.26E-01 1.11E-01 1.58E-01 1.84E-01 3.65E-01 8.83E-01 1.85E+00 3.11E+00 4.58E+00 7.47E+00 7.69E+00 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-66. Consumer Only Intake of Homegrown Dark Green Vegetables (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P

Total 8855000 428 4.71 3.91E-01 2.95E-02 2.01E-03 4.28E-03 1.01E-02 8.70E-02 2.11E-01 4.35E-01 9.19E-01 1.25E+00 3.53E+00 5.8

Age

 01-02 180000 8 3.16 * * * * * * * * * * * 

 03-05 226000 12 2.79 * * * * * * * * * * * 

 06-11 826000 39 4.94 3.05E-01 5.19E-02 0.00E+00 6.34E-03 2.42E-02 9.00E-02 1.81E-01 3.87E-01 9.48E-01 1.04E+00 1.28E+00 1.2

 12-19 628000 32 3.07 4.20E-01 1.47E-01 4.92E-03 5.38E-03 6.65E-03 5.62E-02 2.03E-01 3.73E-01 9.24E-01 1.64E+00 4.86E+00 4.8

 20-39 1976000 87 3.21 3.36E-01 6.09E-02 2.21E-03 3.74E-03 1.00E-02 8.70E-02 1.76E-01 3.79E-01 6.69E-01 9.19E-01 2.94E+00 4.2

 40-69 3710000 184 6.54 4.01E-01 4.24E-02 2.25E-03 3.67E-03 2.60E-02 8.19E-02 2.33E-01 4.80E-01 9.79E-01 1.25E+00 3.29E+00 5.8

 70 + 1253000 63 7.89 4.08E-01 7.27E-02 2.84E-03 4.23E-03 5.68E-03 1.10E-01 2.31E-01 4.69E-01 9.29E-01 1.08E+00 3.45E+00 3.4

Season

 Fall 2683000 88 5.63 4.41E-01 7.42E-02 1.01E-02 4.46E-02 8.70E-02 1.45E-01 2.38E-01 4.59E-01 7.90E-01 1.08E+00 3.86E+00 4.2

 Spring 1251000 127 2.71 5.59E-01 7.90E-02 1.63E-03 3.66E-03 5.72E-03 1.01E-01 3.09E-01 5.38E-01 1.28E+00 2.81E+00 4.86E+00 5.8

 Summer 3580000 124 7.87 3.39E-01 4.10E-02 0.00E+00 2.84E-03 5.68E-03 6.34E-02 1.51E-01 4.05E-01 9.79E-01 1.15E+00 2.48E+00 2.4

 Winter 1341000 89 2.75 2.72E-01 3.92E-02 2.01E-03 3.97E-03 5.21E-03 2.30E-02 1.51E-01 3.71E-01 6.59E-01 1.17E+00 2.04E+00 2.1

Urbanization

 Central City 1298000 48 2.30 2.69E-01 3.68E-02 2.84E-03 4.71E-03 1.01E-02 1.06E-01 2.05E-01 3.24E-01 6.32E-01 9.19E-01 1.07E+00 1.0

 Nonmetropolitan 3218000 167 7.15 3.31E-01 3.54E-02 2.21E-03 4.67E-03 1.70E-02 6.86E-02 1.72E-01 4.52E-01 7.52E-01 1.00E+00 2.48E+00 5.8

 Suburban 4279000 211 4.94 4.79E-01 5.23E-02 2.25E-03 5.21E-03 2.15E-02 9.22E-02 2.33E-01 4.59E-01 1.15E+00 2.18E+00 3.86E+00 4.8

Race

 Black 724000 49 3.33 1.04E+00 1.80E-01 0.00E+00 1.00E-01 1.13E-01 2.21E-01 5.52E-01 1.17E+00 3.29E+00 3.86E+00 4.86E+00 4.8

 White 7963000 373 5.05 3.21E-01 2.20E-02 2.25E-03 4.67E-03 1.01E-02 7.75E-02 1.99E-01 3.79E-01 7.76E-01 1.07E+00 2.37E+00 5.8

Region

 Midwest 2668000 121 5.75 2.81E-01 3.54E-02 2.84E-03 4.77E-03 6.26E-03 6.34E-02 2.11E-01 3.58E-01 4.96E-01 9.79E-01 2.48E+00 3.0

 Northeast 1554000 76 3.77 5.08E-01 9.14E-02 2.17E-03 2.80E-03 4.23E-03 5.62E-02 1.96E-01 4.92E-01 1.25E+00 1.93E+00 3.53E+00 5.8

 South 2945000 148 4.58 4.78E-01 5.07E-02 3.64E-02 6.83E-02 9.23E-02 1.45E-01 2.87E-01 6.43E-01 9.24E-01 1.28E+00 3.86E+00 4.2

 West 1628000 81 4.51 3.18E-01 7.25E-02 2.25E-03 3.37E-03 6.34E-03 3.50E-02 1.10E-01 3.09E-01 6.59E-01 9.29E-01 4.86E+00 4.8

Response to Questionnaire

 Households who garden 8521000 412 12.50 3.95E-01 3.03E-02 1.63E-03 4.23E-03 1.05E-02 8.76E-02 2.12E-01 4.48E-01 9.19E-01 1.25E+00 3.53E+00 5.8

 Households who farm 1450000 66 19.78 3.80E-01 6.08E-02 1.62E-03 4.67E-03 5.38E-03 6.68E-02 2.31E-01 4.84E-01 9.48E-01 1.25E+00 2.48E+00 3.0

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-67. Consumer Only Intake of Homegrown Deep Yellow Vegetables (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P10

Total 5467000 245 2.91 6.43E-01 4.44E-02 4.34E-02 6.70E-02 1.26E-01 2.22E-01 4.17E-01 7.74E-01 1.44E+00 2.03E+00 2.67E+00 6.63E

Age

 01-02 124000 8 2.18 * * * * * * * * * * * *

 03-05 61000 4 0.75 * * * * * * * * * * * *

 06-11 382000 17 2.29 * * * * * * * * * * * *

 12-19 493000 21 2.41 4.73E-01 9.18E-02 6.05E-02 6.05E-02 6.29E-02 9.07E-02 3.63E-01 7.79E-01 1.13E+00 1.44E+00 1.58E+00 1.58E

 20-39 1475000 63 2.39 5.32E-01 7.54E-02 4.89E-02 5.55E-02 1.15E-01 1.66E-01 3.05E-01 5.11E-01 1.22E+00 2.03E+00 2.67E+00 2.67E

 40-69 2074000 96 3.66 5.39E-01 5.15E-02 3.90E-02 9.22E-02 1.43E-01 2.21E-01 4.03E-01 6.54E-01 1.09E+00 1.33E+00 3.02E+00 3.02E

 70 + 761000 32 4.79 7.81E-01 9.20E-02 7.64E-02 2.02E-01 2.77E-01 3.70E-01 5.72E-01 1.24E+00 1.61E+00 1.99E+00 1.99E+00 1.99E

Season

 Fall 2664000 97 5.59 7.38E-01 8.18E-02 9.21E-02 1.22E-01 1.43E-01 2.61E-01 4.51E-01 9.74E-01 1.73E+00 2.23E+00 3.02E+00 6.63E

 Spring 315000 34 0.68 5.64E-01 7.52E-02 1.43E-01 1.45E-01 1.98E-01 2.47E-01 4.45E-01 6.43E-01 1.01E+00 1.42E+00 2.41E+00 2.41E

 Summer 1619000 52 3.56 5.09E-01 6.37E-02 4.16E-02 5.49E-02 6.48E-02 2.26E-01 4.10E-01 6.35E-01 9.64E-01 1.67E+00 2.31E+00 2.31E

 Winter 869000 62 1.78 6.29E-01 9.15E-02 3.90E-02 4.34E-02 6.29E-02 1.72E-01 3.52E-01 7.96E-01 1.54E+00 2.23E+00 4.37E+00 4.37E

Urbanization

 Central City 1308000 43 2.32 5.07E-01 7.07E-02 3.90E-02 6.29E-02 1.43E-01 2.13E-01 3.88E-01 5.88E-01 9.64E-01 1.41E+00 2.24E+00 2.24E

 Nonmetropolitan 2100000 118 4.66 6.66E-01 7.72E-02 4.16E-02 5.55E-02 9.07E-02 2.20E-01 3.70E-01 8.65E-01 1.39E+00 2.12E+00 4.37E+00 6.63E

 Suburban 2059000 84 2.38 7.07E-01 6.99E-02 6.48E-02 9.22E-02 1.26E-01 2.62E-01 4.25E-01 9.74E-01 1.67E+00 2.03E+00 2.67E+00 2.67E

Race

 Black 129000 8 0.59 * * * * * * * * * * * *

 White 5093000 229 3.23 6.45E-01 4.03E-02 4.89E-02 9.21E-02 1.43E-01 2.41E-01 4.25E-01 7.96E-01 1.50E+00 2.03E+00 2.67E+00 4.37E

Region

 Midwest 2792000 128 6.02 7.52E-01 6.01E-02 4.34E-02 1.32E-01 1.93E-01 2.82E-01 5.09E-01 9.55E-01 1.73E+00 2.23E+00 3.02E+00 4.37E

 Northeast 735000 29 1.79 3.96E-01 8.06E-02 4.16E-02 5.55E-02 6.05E-02 9.22E-02 1.50E-01 6.35E-01 1.09E+00 1.37E+00 2.21E+00 2.21E

 South 557000 30 0.87 5.39E-01 2.08E-01 4.89E-02 5.49E-02 7.74E-02 2.20E-01 3.05E-01 4.38E-01 7.74E-01 1.22E+00 6.63E+00 6.63E

 West 1383000 58 3.83 5.97E-01 7.07E-02 6.48E-02 1.27E-01 1.43E-01 2.21E-01 4.10E-01 6.42E-01 1.44E+00 1.89E+00 2.31E+00 2.31E

Response to Questionnaire

 Households who garden 5177000 233 7.60 6.23E-01 3.93E-02 4.16E-02 9.07E-02 1.32E-01 2.32E-01 4.15E-01 7.50E-01 1.42E+00 1.99E+00 2.67E+00 4.37E

 Households who farm 1088000 51 14.85 6.06E-01 8.52E-02 9.21E-02 9.22E-02 1.22E-01 1.94E-01 3.40E-01 9.40E-01 1.28E+00 1.73E+00 3.02E+00 3.02E

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table13-68. Consumer Only Intake of Homegrown Other Vegetables (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 25221000 1437 13.41 1.38E+00 5.00E-02 9.44E-03 1.07E-01 1.76E-01 3.62E-01 7.78E-01 1.65E+00 3.09E+00 4.52E+00 9.95E+00 1.84E+01 

Age

 01-02 613000 38 10.76 3.80E+00 6.27E-01 1.92E-01 2.73E-01 4.04E-01 1.04E+00 2.61E+00 4.55E+00 7.74E+00 1.12E+01 1.80E+01 1.80E+01

 03-05 887000 59 10.95 2.15E+00 2.67E-01 0.00E+00 2.28E-01 3.72E-01 7.20E-01 1.37E+00 3.16E+00 4.47E+00 5.96E+00 8.41E+00 1.40E+01

 06-11 2149000 134 12.86 1.30E+00 1.38E-01 0.00E+00 1.21E-01 1.93E-01 3.54E-01 8.00E-01 1.61E+00 3.04E+00 4.57E+00 9.95E+00 9.95E+00

 12-19 2379000 141 11.61 9.80E-01 8.56E-02 0.00E+00 5.76E-02 1.15E-01 3.17E-01 6.40E-01 1.33E+00 2.05E+00 3.17E+00 5.41E+00 5.41E+00

 20-39 6020000 328 9.77 9.30E-01 6.00E-02 3.19E-02 9.37E-02 1.48E-01 2.43E-01 5.60E-01 1.12E+00 2.19E+00 3.04E+00 5.10E+00 7.00E+00

 40-69 9649000 547 17.01 1.40E+00 8.72E-02 5.20E-03 1.11E-01 1.86E-01 3.95E-01 8.43E-01 1.58E+00 2.92E+00 4.65E+00 1.41E+01 1.84E+01

 70 + 3226000 174 20.31 1.58E+00 1.41E-01 1.85E-02 1.52E-01 2.38E-01 4.62E-01 9.48E-01 1.91E+00 3.46E+00 5.79E+00 9.96E+00 1.14E+01 

Season

 Fall 6934000 253 14.55 1.19E+00 8.62E-02 4.92E-02 1.48E-01 1.86E-01 3.28E-01 7.16E-01 1.44E+00 2.74E+00 4.00E+00 6.74E+00 9.96E+00

 Spring 5407000 567 11.71 1.16E+00 6.19E-02 3.66E-03 4.32E-02 1.04E-01 3.10E-01 7.10E-01 1.39E+00 2.67E+00 4.21E+00 7.35E+00 1.40E+01

 Summer 8454000 283 18.59 1.79E+00 1.53E-01 0.00E+00 1.18E-01 1.81E-01 3.85E-01 9.68E-01 1.97E+00 4.13E+00 6.14E+00 1.46E+01 1.84E+01

 Winter 4426000 334 9.09 1.19E+00 7.28E-02 4.79E-03 1.41E-01 2.31E-01 4.09E-01 7.33E-01 1.49E+00 2.41E+00 3.37E+00 7.00E+00 1.10E+01 

Urbanization

 Central City 4148000 161 7.36 9.66E-01 8.81E-02 3.50E-02 9.37E-02 1.63E-01 3.24E-01 6.07E-01 1.23E+00 1.97E+00 3.22E+00 7.00E+00 8.85E+00

 Nonmetropolitan 10721000 710 23.81 1.78E+00 8.99E-02 2.74E-02 1.60E-01 2.26E-01 4.68E-01 1.01E+00 2.01E+00 4.05E+00 5.74E+00 1.41E+01 1.84E+01

 Suburban 10292000 564 11.89 1.14E+00 5.98E-02 4.79E-03 8.98E-02 1.46E-01 3.06E-01 6.47E-01 1.44E+00 2.69E+00 3.77E+00 6.81E+00 1.14E+01 

Race

 Black 1347000 84 6.19 1.30E+00 1.70E-01 4.41E-02 1.74E-01 2.06E-01 3.50E-01 7.11E-01 1.49E+00 3.88E+00 5.47E+00 6.21E+00 7.72E+00

 White 23367000 1327 14.83 1.39E+00 5.26E-02 1.29E-02 1.10E-01 1.79E-01 3.76E-01 7.93E-01 1.65E+00 3.04E+00 4.49E+00 9.96E+00 1.84E+01 

Region

 Midwest 8296000 522 17.88 1.43E+00 9.25E-02 3.19E-02 1.21E-01 1.90E-01 3.66E-01 7.29E-01 1.65E+00 3.05E+00 4.65E+00 1.12E+01 1.84E+01

 Northeast 2914000 162 7.08 1.33E+00 1.65E-01 1.97E-03 5.69E-02 1.07E-01 2.44E-01 5.97E-01 1.64E+00 3.07E+00 5.41E+00 1.20E+01 1.41E+01

 South 9218000 518 14.33 1.53E+00 7.82E-02 1.41E-02 1.68E-01 2.53E-01 4.87E-01 1.03E+00 1.76E+00 3.37E+00 4.70E+00 8.33E+00 1.80E+01

 West 4733000 233 13.12 1.08E+00 9.85E-02 1.11E-02 7.06E-02 1.22E-01 2.55E-01 5.73E-01 1.21E+00 2.41E+00 3.73E+00 8.02E+00 1.14E+01 

Response to Questionnaire

 Households who garden 22417000 1291 32.89 1.44E+00 5.25E-02 1.11E-02 1.11E-01 1.80E-01 3.84E-01 8.18E-01 1.70E+00 3.22E+00 4.65E+00 9.95E+00 1.84E+01

 Households who farm 3965000 239 54.10 1.95E+00 1.63E-01 1.41E-02 1.36E-01 2.34E-01 5.20E-01 1.21E+00 2.04E+00 5.32E+00 7.02E+00 1.46E+01 1.59E+01 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-69. Consumer Only Intake of Homegrown Citrus (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 2530000 125 1.35 4.76E+00 6.05E-01 7.82E-02 1.57E-01 2.86E-01 7.56E-01 1.99E+00 5.10E+00 1.41E+01 1.97E+01 3.22E+01 4.79E+0

Age

 01-02 54000 4 0.95 * * * * * * * * * * * *

 03-05 51000 3 0.63 * * * * * * * * * * * *

 06-11 181000 9 1.08 * * * * * * * * * * * *

 12-19 194000 14 0.95 * * * * * * * * * * * *

 20-39 402000 18 0.65 * * * * * * * * * * * *

 40-69 1183000 55 2.09 4.54E+00 8.06E-01 8.11E-02 1.50E-01 2.47E-01 5.21E-01 1.74E+00 5.24E+00 1.52E+01 1.97E+01 2.38E+01 2.38E+0

 70 + 457000 21 2.88 4.43E+00 7.58E-01 7.82E-02 7.82E-02 4.94E-01 1.95E+00 3.53E+00 6.94E+00 8.97E+00 8.97E+00 1.57E+01 1.57E+0

Season

 Fall 280000 8 0.59 * * * * * * * * * * * *

 Spring 437000 33 0.95 2.31E+00 3.76E-01 1.57E-01 1.84E-01 2.35E-01 3.69E-01 1.36E+00 4.15E+00 5.10E+00 6.50E+00 7.52E+00 7.52E+0

 Summer 334000 11 0.73 * * * * * * * * * * * *

 Winter 1479000 73 3.04 6.47E+00 9.53E-01 1.50E-01 3.33E-01 4.94E-01 1.64E+00 2.93E+00 8.59E+00 1.91E+01 2.38E+01 4.79E+01 4.79E+0

Urbanization

 Central City 1053000 43 1.87 3.57E+00 5.18E-01 1.50E-01 3.33E-01 4.50E-01 1.13E+00 3.01E+00 4.97E+00 7.46E+00 8.97E+00 2.00E+01 2.00E+0

 Nonmetropolitan 0 0 0.00

 Suburban 1477000 82 1.71 5.61E+00 9.14E-01 7.82E-02 1.14E-01 2.47E-01 5.17E-01 1.81E+00 8.12E+00 1.79E+01 2.38E+01 4.79E+01 4.79E+0

Race

 Black 200000 8 0.92 * * * * * * * * * * * *

 White 2330000 117 1.48 4.93E+00 6.31E-01 7.82E-02 1.50E-01 2.84E-01 7.82E-01 2.34E+00 5.34E+00 1.41E+01 1.97E+01 3.22E+01 4.79E+0

Region

 Midwest 64000 4 0.14 * * * * * * * * * * * *

 Northeast 0 0 0.00

 South 1240000 55 1.93 5.18E+00 7.37E-01 1.57E-01 3.76E-01 6.44E-01 1.60E+00 3.42E+00 6.50E+00 1.41E+01 1.97E+01 2.38E+01 2.38E+0

 West 1226000 66 3.40 4.56E+00 9.79E-01 7.82E-02 1.14E-01 2.35E-01 3.69E-01 1.42E+00 4.53E+00 1.24E+01 2.00E+01 4.79E+01 4.79E+0

Response to Questionnaire

 Households who garden 2151000 102 3.16 4.55E+00 6.61E-01 7.82E-02 1.50E-01 2.84E-01 7.56E-01 1.99E+00 4.99E+00 1.24E+01 1.79E+01 3.22E+01 4.79E+0

 Households who farm 130000 5 1.77 * * * * * * * * * * * * 

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distributions 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Sources: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-70. Consumer Only Intake of Homegrown Other Fruit (g/kg-day) 

Population Nc Nc % 

Group wgtd unwgtd Consuming Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 

Total 12615000 706 6.71 2.20E+00 1.86E-01 5.41E-02 1.47E-01 2.55E-01 4.60E-01 9.06E-01 1.91E+00 4.59E+00 8.12E+00 1.84E+01 6.26E+

Age

 01-02 306000 19 5.37 * * * * * * * * * * * *

 03-05 499000 31 6.16 2.66E+00 7.60E-01 0.00E+00 0.00E+00 3.80E-01 1.02E+00 1.87E+00 2.71E+00 5.54E+00 6.30E+00 3.32E+01 3.32E+

 06-11 915000 68 5.48 2.60E+00 4.38E-01 0.00E+00 1.77E-01 3.86E-01 6.37E-01 1.14E+00 2.99E+00 7.13E+00 1.21E+01 1.62E+01 1.65E+

 12-19 1021000 54 4.98 1.62E+00 2.77E-01 8.40E-02 1.20E-01 2.57E-01 3.86E-01 6.09E-01 2.36E+00 3.92E+00 6.81E+00 8.12E+00 8.12E+

 20-39 2761000 146 4.48 1.85E+00 3.72E-01 7.94E-02 1.30E-01 1.80E-01 3.07E-01 6.20E-01 1.39E+00 3.70E+00 6.64E+00 3.70E+01 3.70E+

 40-69 4610000 259 8.13 2.09E+00 3.08E-01 6.52E-02 1.47E-01 2.54E-01 4.44E-01 7.68E-01 1.77E+00 3.17E+00 9.77E+00 1.84E+01 5.33E+

 70 + 2326000 119 14.65 1.66E+00 1.84E-01 4.41E-02 2.07E-01 3.56E-01 5.71E-01 1.07E+00 1.65E+00 4.06E+00 5.21E+00 1.17E+01 1.17E+

Season

 Fall 2923000 102 6.13 1.39E+00 1.14E-01 2.59E-01 3.04E-01 3.81E-01 5.67E-01 1.07E+00 1.88E+00 2.89E+00 4.06E+00 5.39E+00 5.54E+

 Spring 2526000 268 5.47 1.47E+00 1.51E-01 8.66E-02 1.98E-01 2.54E-01 4.25E-01 8.33E-01 1.65E+00 2.89E+00 4.59E+00 8.26E+00 3.32E+

 Summer 4327000 144 9.51

 Winter 2839000 192 5.83 1.29E+00 1.08E-01 4.15E-02 1.01E-01 2.25E-01 4.54E-01 8.33E-01 1.55E+00 2.70E+00 4.79E+00 8.06E+00 1.13E+

Urbanization

 Central City 2681000 102 4.76 1.79E+00 2.88E-01 4.41E-02 1.66E-01 2.91E-01 5.21E-01 8.87E-01 1.60E+00 2.61E+00 1.04E+01 1.54E+01 1.54E+

 Nonmetropolitan 4118000 278 9.15 2.43E+00 3.10E-01 6.52E-02 1.20E-01 2.38E-01 4.50E-01 1.13E+00 2.43E+00 4.60E+00 8.12E+00 2.40E+01 5.33E+

 Suburban 5756000 324 6.65 2.25E+00 3.06E-01 1.25E-01 1.99E-01 2.82E-01 4.46E-01 7.64E-01 1.81E+00 4.72E+00 7.61E+00 1.84E+01 6.26E+

Race

 Black 250000 12 1.15 * * * * * * * * * * * *

 White 12256000 690 7.78 2.24E+00 1.91E-01 6.96E-02 1.50E-01 2.59E-01 4.66E-01 9.16E-01 1.94E+00 4.65E+00 8.26E+00 1.84E+01 6.26E+

Region

 Midwest 4619000 298 9.96 3.07E+00 4.25E-01 4.41E-02 1.25E-01 2.35E-01 4.54E-01 1.04E+00 2.35E+00 6.73E+00 1.42E+01 5.33E+01 6.26E+

 Northeast 1279000 72 3.11 9.32E-01 2.20E-01 7.98E-02 8.55E-02 1.62E-01 3.11E-01 4.75E-01 8.12E-01 1.29E+00 2.16E+00 1.17E+01 1.17E+

 South 3004000 157 4.67 1.99E+00 2.59E-01 7.94E-02 2.38E-01 2.99E-01 5.46E-01 1.10E+00 1.82E+00 4.06E+00 6.30E+00 1.62E+01 2.40E+

 West 3653000 177 10.13 1.76E+00 1.64E-01 1.00E-01 2.16E-01 2.91E-01 5.44E-01 9.71E-01 2.04E+00 4.35E+00 5.75E+00 1.30E+01 1.30E+

Response to Questionnaire

 Households who garden 10926000 619 16.03 2.38E+00 2.12E-01 4.41E-02 1.58E-01 2.57E-01 4.74E-01 9.94E-01 1.96E+00 4.94E+00 1.04E+01 1.84E+01 6.26E+

 Households who farm 1917000 112 26.16 2.57E+00 2.65E-01 6.96E-02 2.76E-01 3.61E-01 7.33E-01 1.55E+00 3.62E+00 5.80E+00 8.06E+00 1.62E+01 1.62E+

* Intake data not provided for subpopulations for which there were less than 20 observations 

NOTE: SE = standard error 

P = percentile of the distribution 

Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey. 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-71. Fraction of Food Intake that is Home Produced 

Total Total Total Total Total Exposed Protected Root Exposed 

Fruits Vegetables Meats Dairy Fish Vegetables Vegetables Vegetables Fruits 

 Total 0.040 0.068 0.024 0.012 0.094 0.095 0.069 0.043 0.050 

Season

 Fall 0.021 0.081 0.020 0.008 0.076 0.106 0.073 0.06 0.039 

 Spring 0.021 0.037 0.020 0.011 0.160 0.05 0.039 0.02 0.047 

 Summer 0.058 0.116 0.034 0.022 0.079 0.164 0.101 0.066 0.068 

 Winter 0.059 0.041 0.022 0.008 0.063 0.052 0.048 0.026 0.044 

Urbanization

 Central City 0.027 0.027 0.003 0.000 0.053 0.037 0.027 0.016 0.030 

 Nonmetropolitan 0.052 0.144 0.064 0.043 0.219 0.207 0.134 0.088 0.100 

 Surburban 0.047 0.058 0.018 0.004 0.075 0.079 0.054 0.035 0.043 

Race

 Black 0.007 0.027 0.001 0.000 0.063 0.037 0.029 0.012 0.008 

 White 0.049 0.081 0.031 0.014 0.110 0.109 0.081 0.050 0.059 

Regions

 Northeast 0.005 0.038 0.009 0.010 0.008 0.062 0.016 0.018 0.010 

 Midwest 0.059 0.112 0.046 0.024 0.133 0.148 0.109 0.077 0.078 

 South 0.042 0.069 0.017 0.006 0.126 0.091 0.077 0.042 0.040 

 West 0.062 0.057 0.023 0.007 0.108 0.079 0.060 0.029 0.075 

Questionnaire Response

 Households who garden 0.101 0.173 0.233 0.178 0.106 0.116 

 Households who raise animals 0.306 0.207

 Households who farm 0.161 0.308 0.319 0.254 0.420 0.394 0.173 0.328 

 Households who fish 0.325 
Table 13-71. Fraction of Food Intake that is Home Produced (continued) 

Dark Green Deep Yellow Other Citrus Other 

Vegetables Vegetables Vegetables Fruits Fruits Apples Peaches Pears Strawberries Other 

 Total 0.044 0.065 0.069 0.038 0.042 0.030 0.147 0.067 0.111 0

Season

 Fall 0.059 0.099 0.069 0.114 0.027 0.032 0.09 0.038 0.408 0

 Spring 0.037 0.017 0.051 0.014 0.025 0.013 0.206 0.075 0.064 0

 Summer 0.063 0.08 0.114 0.01 0.07 0.053 0.133 0.066 0.088 0

 Winter 0.018 0.041 0.044 0.091 0.03 0.024 0.183 0.111 0.217 0

Urbanization

 Central City 0.012 0.038 0.026 0.035 0.022 0.017 0.087 0.038 0.107 0

 Nonmetropolitan 0.090 0.122 0.154 0.000 0.077 0.066 0.272 0.155 0.133 0

 Surburban 0.054 0.058 0.053 0.056 0.042 0.024 0.121 0.068 0.101 0

Race

 Black 0.053 0.056 0.026 0.012 0.004 0.007 0.018 0.004 0.000 0

 White 0.043 0.071 0.082 0.045 0.051 0.035 0.164 0.089 0.125 0

Regions

 Northeast 0.039 0.019 0.034 0.000 0.008 0.004 0.027 0.002 0.085 0

 Midwest 0.054 0.174 0.102 0.001 0.083 0.052 0.164 0.112 0.209 0

 South 0.049 0.022 0.077 0.060 0.031 0.024 0.143 0.080 0.072 0

 West 0.034 0.063 0.055 0.103 0.046 0.043 0.238 0.093 0.044 0

Questionnaire Response

 Households who garden 0.120 0.140 0.180 0.087 0.107 0.070 0.316 0.169 0.232 0

 Households who farm 0.220 0.328 0.368 0.005 0.227 0.292 0.461 0.606 0.057 0
Table 13-71. Fraction of food Intake that is Home Produced (continued) 

Asparagus Beets Broccoli Cabbage Carrots Corn Cucumbers Lettuce Lima Beans Okra O

 Total 0.063 0.203 0.015 0.038 0.043 0.078 0.148 0.010 0.121 0.270 

Season

 Fall 0.024 0.199 0.013 0.054 0.066 0.076 0.055 0.013 0.07 0.299 

 Spring 0.103 0.191 0.011 0.011 0.015 0.048 0.04 0.01 0.082 0.211 

 Summer 0 0.209 0.034 0.08 0.063 0.118 0.32 0.017 0.176 0.304 

 Winter 0.019 0.215 0.006 0.008 0.025 0.043 0 0.002 0.129 0.123 

Urbanization

 Central City 0.058 0.212 0.004 0.004 0.018 0.025 0.029 0.009 0.037 0.068 

 Nonmetropolitan 0.145 0.377 0.040 0.082 0.091 0.173 0.377 0.017 0.132 0.411 

 Surburban 0.040 0.127 0.016 0.045 0.039 0.047 0.088 0.009 0.165 0.299 

Race

 Black 0.000 0.000 0.000 0.001 0.068 0.019 0.060 0.007 0.103 0.069 

 White 0.071 0.224 0.018 0.056 0.042 0.093 0.155 0.011 0.135 0.373 

Regions

 Northeast 0.091 0.074 0.020 0.047 0.025 0.020 0.147 0.009 0.026 0.000 

 Midwest 0.194 0.432 0.025 0.053 0.101 0.124 0.193 0.020 0.149 0.224 

 South 0.015 0.145 0.013 0.029 0.020 0.088 0.140 0.006 0.140 0.291 

 West 0.015 0.202 0.006 0.029 0.039 0.069 0.119 0.009 0.000 0.333 

Questionnaire Response

 Households who garden 0.125 0.420 0.043 0.099 0.103 0.220 0.349 0.031 0.258 0.618 

 Households who farm 0.432 0.316 0.159 0.219 0.185 0.524 0.524 0.063 0.103 0.821 
Table 13-71. Fraction of Food Intake that is Home Produced (continued) 

Peas Peppers Pumpkin Snap Beans Tomatoes White Beef Game Pork Poultry 

Potatoes

 Total 0.069 0.107 0.155 0.155 0.184 0.038 0.038 0.276 0.013 0.011 

Season

 Fall 0.046 0.138 0.161 0.199 0.215 0.058 0.028 0.336 0.012 0.011 

 Spring 0.048 0.031 0.046 0.152 0.045 0.01 0.027 0.265 0.015 0.012 

 Summer 0.126 0.194 0.19 0.123 0.318 0.06 0.072 0.1 0.01 0.007 

 Winter 0.065 0.03 0.154 0.147 0.103 0.022 0.022 0.33 0.014 0.014 

Urbanization

 Central City 0.033 0.067 0.130 0.066 0.100 0.009 0.001 0.146 0.001 0.002 

 Nonmetropolitan 0.123 0.228 0.250 0.307 0.313 0.080 0.107 0.323 0.040 0.026 

 Surburban 0.064 0.086 0.127 0.118 0.156 0.029 0.026 0.316 0.006 0.011 

Race

 Black 0.047 0.039 0.022 0.046 0.060 0.007 0.000 0.000 0.000 0.001 

 White 0.076 0.121 0.187 0.186 0.202 0.044 0.048 0.359 0.017 0.014 

Regions

 Northeast 0.021 0.067 0.002 0.052 0.117 0.016 0.014 0.202 0.006 0.002 

 Midwest 0.058 0.188 0.357 0.243 0.291 0.065 0.076 0.513 0.021 0.021 

 South 0.106 0.113 0.044 0.161 0.149 0.042 0.022 0.199 0.012 0.012 

 West 0.051 0.082 0.181 0.108 0.182 0.013 0.041 0.207 0.011 0.008 

Questionnaire Response

 Households who garden 0.193 0.246 0.230 0.384 0.398 0.090

 Households who farm 0.308 0.564 0.824 0.623 0.616 0.134 0.485 0.242 0.156 

 Households who raise animals 0.478 0.239 0.151 

 Households who hunt 0.729 

Source: Based on EPA's analyses of the 1987-88 NFCS 
Table 13-72. Confidence in Homegrown Food Consumption Recommendations 

Considerations Rationale Rating 

Study Elements

 • Level of Peer Review USDA and EPA review High

 • Accessibility Methods described in detail in Handbook High

 • Reproducibility see above High

 • Focus on factor of interest Yes High

 • Data pertinent to U.S. U.S. population High

 • Primary data Yes High

 • Currency 1987-88 Medium

 • Adequacy of data Statistical method used to estimate long- High (Means & Short-term distributions)

 collection period term distribution from one-week survey Low (Long-term distributions) 

data. 

• Validity of approach Individual intakes inferred from household Medium (Means) 

consumption. Low (Distributions)

 • Study size 10,000 individuals, 4500 households High

 • Representativeness of the Nationwide survey representative of High

 population general U.S. population

 • Bias in study design (high Non-response bias can not be ruled out Medium

 rating desirable) due to low response rate.

 • Measurement Error Individuals’ estimates of food weights Medium

 (high rating desirable) imprecise 

Other Elements

 • Number of studies 1 Low

 • Agreement between N/A

 researchers 

Overall Rating Highest confidence in means, lowest Medium (Means) 

confidence in long term percentiles Medium

 (Short-term distributions) 

Low (Long-term 

distributions) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data 

Food Household Code/Definition Individual Code 

Product 

MAJOR FOOD GROUPS 

Total Fruits 50­ Fresh Fruits 6­ Fruits 

citrus 

other vitamin-C rich 

citrus fruits and juices 

dried fruits 

other fruits other fruits 

512- Commercially Canned Fruits 

522- Commercially Frozen Fruits 

533- Canned Fruit Juice 

534- Frozen Fruit Juice 

fruits/juices & nectar 

fruit/juices baby food 

(includes baby foods) 

535- Aseptically Packed Fruit Juice 

536- Fresh Fruit Juice 

542- Dried Fruits 

(includes baby foods) 

Total 

Vegetables 

48­ Potatoes, Sweetpotatoes 

49­ Fresh Vegetables 

dark green 

deep yellow 

tomatoes 

7­ Vegetables (all forms) 

white potatoes & PR starchy 

dark green vegetables 

deep yellow vegetables 

tomatoes and tom. mixtures 

light green 

other 

511- Commercially Canned Vegetables 

521- Commercially Frozen Vegetables 

531- Canned Vegetable Juice 

532- Frozen Vegetable Juice 

537- Fresh Vegetable Juice 

538- Aseptically Packed Vegetable Juice 

541- Dried Vegetables 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures/dinners) 

other vegetables 

veg. and mixtures/baby food 

veg. with meat mixtures 

(includes baby foods; mixtures, mostly vegetables) 

Total Meats 44­ Meat 

beef 

20­ Meat, type not specified 

21­ Beef 

pork 

veal 

lamb 

mutton 

goat 

game 

lunch meat 

mixtures 

451- Poultry 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

22­ Pork 

23­ Lamb, veal, game, carcass meat 

24­ Poultry 

25­ Organ meats, sausages, lunchmeats, meat 

spreads 

(excludes meat, poultry, and fish with non-meat items; 

frozen plate meals; soups and gravies with meat, poultry 

and fish base; and gelatin-based drinks; includes baby 

foods) 

Total Dairy 40­ Milk Equivalent 

fresh fluid milk 

1­ Milk and Milk Products 

milk and milk drinks 

processed milk 

cream and cream substitutes 

frozen desserts with milk 

cream and cream substitutes 

milk desserts, sauces, and gravies 

cheeses 

cheese 

dairy-based dips 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners) 

(includes regular fluid milk, human milk, imitation milk 

products, yogurt, milk-based meal replacements, and 

infant formulas) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food Household Code/Definition Individual Code 

Product 

Total Fish 452- Fish, Shellfish 26­ Fish, Shellfish 

various species 

fresh, frozen, commercial, dried 

various species and forms 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners) 

(excludes meat, poultry, and fish with non-meat items; 

frozen plate meals; soups and gravies with meat, poultry 

and fish base; and gelatin-based drinks) 

INDIVIDUAL FOODS 

White 

Potatoes 

4811­ White Potatoes, fresh 

4821­ White Potatoes, commercially canned 

4831­ White Potatoes, commercially frozen 

4841­ White Potatoes, dehydrated 

4851­ White Potatoes, chips, sticks, salad 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners) 

71­ White Potatoes and PR Starchy Veg. 

baked, boiled, chips, sticks, creamed, 

scalloped, au gratin, fried, mashed, stuffed, 

puffs, salad, recipes, soups, Puerto Rican 

starchy vegetables 

(does not include vegetables soups; vegetable mixtures; 

or vegetable with meat mixtures) 

Peppers 4913- Green/Red Peppers, fresh 

5111201 Sweet Green Peppers, commercially canned 

5111202 Hot Chili Peppers, commercially canned 

5211301 Sweet Green Peppers, commercially frozen 

5211302 Green Chili Peppers, commercially frozen 

5211303 Red Chili Peppers, commercially frozen 

5413112 Sweet Green Peppers, dry 

5413113 Red Chili Peppers, dry 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners) 

7512100 Pepper, hot chili, raw 

7512200 Pepper, raw 

7512210 Pepper, sweet green, raw 

7512220 Pepper, sweet red, raw 

7522600 Pepper, green, cooked, NS as to fat added 

7522601 Pepper, green, cooked, fat not added 

7522602 Pepper, green, cooked, fat added 

7522604 Pepper, red, cooked, NS as to fat added 

7522605 Pepper, red, cooked, fat not added 

7522606 Pepper, red, cooked, fat added 

7522609 Pepper, hot, cooked, NS as to fat added 

7522610 Pepper, hot, cooked, fat not added 

7522611 Pepper, hot, cooked, fat added 

7551101 Peppers, hot, sauce 

7551102 Peppers, pickled 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures) 

Onions 4953­ Onions, Garlic, fresh 7510950 Chives, raw 

onions 7511150 Garlic, raw 

chives 7511250 Leek, raw 

garlic 

leeks 

7511701 Onions, young green, raw 

7511702 Onions, mature 

5114908 Garlic Pulp, raw 

5114915 Onions, commercially canned 

5213722 Onions, commercially frozen 

5213723 Onions with Sauce, commercially frozen 

5413103 Chives, dried 

7521550 Chives, dried 

7521740 Garlic, cooked 

7522100 Onions, mature cooked, NS as to fat added 

7522101 Onions, mature cooked, fat not added 

7522102 Onions, mature cooked, fat added 

5413105 Garlic Flakes, dried 

5413110 Onion Flakes, dried 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners) 

7522103 Onions, pearl cooked 

7522104 Onions, young green cooked, NS as to fat 

7522105 Onions, young green cooked, fat not added 

7522106 Onions, young green cooked, fat added 

7522110 Onion, dehydrated 

7541501 Onions, creamed 

7541502 Onion rings 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food Household Code/Definition Individual Code 

Product 

Corn 4956­ Corn, fresh 7510960 Corn, raw 

5114601 Yellow Corn, commercially canned 

5114602 White Corn, commercially canned 

5114603 Yellow Creamed Corn, commercially canned 

5114604 White Creamed Corn, commercially canned 

5114605 Corn on Cob, commercially canned 

5114607 Hominy, canned 

5115306 Low Sodium Corn, commercially canned 

5115307 Low Sodium Cr. Corn, commercially canned 

5213501 Yellow Corn on Cob, commercially frozen 

5213502 Yellow Corn off Cob, commercially frozen 

5213503 Yell. Corn with Sauce, commercially frozen 

5213504 Corn with other Veg., commercially frozen 

5213505 White Corn on Cob, commercially frozen 

5213506 White Corn off Cob, commercially frozen 

5213507 Wh. Corn with Sauce, commercially frozen 

5413104 Corn, dried 

5413106 Hominy, dry 

5413603 Corn, instant baby food 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby food) 

7521600 Corn, cooked, NS as to color/fat added 

7521601 Corn, cooked, NS as to color/fat not added 

7521602 Corn, cooked, NS as to color/fat added 

7521605 Corn, cooked, NS as to color/cream style 

7521607 Corn, cooked, dried 

7521610 Corn, cooked, yellow/NS as to fat added 

7521611 Corn, cooked, yellow/fat not added 

7521612 Corn, cooked, yellow/fat added 

7521615 Corn, yellow, cream style 

7521616 Corn, cooked, yell. & wh./NS as to fat 

7521617 Corn, cooked, yell. & wh./fat not added 

7521618 Corn, cooked, yell. & wh./fat added 

7521619 Corn, yellow, cream style, fat added 

7521620 Corn, cooked, white/NS as to fat added 

7521621 Corn, cooked, white/fat not added 

7521622 Corn, cooked, white/fat added 

7521625 Corn, white, cream style 

7521630 Corn, yellow, canned, low sodium, NS fat 

7521631 Corn, yell., canned, low sod., fat not add 

7521632 Corn, yell., canned, low sod., fat added 

7521749 Hominy, cooked 

752175- Hominy, cooked 

7541101 Corn scalloped or pudding 

7541102 Corn fritter 

7541103 Corn with cream sauce 

7550101 Corn relish 

76405­ Corn, baby 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures; includes baby food) 

Apples 5031­ Apples, fresh 

5122101 Applesauce with sugar, commercially canned 

5122102 Applesauce without sugar, comm. canned 

5122103 Apple Pie Filling, commercially canned 

5122104 Apples, Applesauce, baby/jr., comm. canned 

5122106 Apple Pie Filling, Low Cal., comm. canned 

5223101 Apple Slices, commercially frozen 

5332101 Apple Juice, canned 

5332102 Apple Juice, baby, Comm. canned 

5342201 Apple Juice, comm. frozen 

5342202 Apple Juice, home frozen 

5352101 Apple Juice, aseptically packed 

5362101 Apple Juice, fresh 

5423101 Apples, dried 

(includes baby food; except mixtures) 

6210110 Apples, dried, uncooked 

6210115 Apples, dried, uncooked, low sodium 

6210120 Apples, dried, cooked, NS as to sweetener 

6210122 Apples, dried, cooked, unsweetened 

6210123 Apples, dried, cooked, with sugar 

6310100 Apples, raw 

6310111 Applesauce, NS as to sweetener 

6310112 Applesauce, unsweetened 

6310113 Applesauce with sugar 

6310114 Applesauce with low calorie sweetener 

6310121 Apples, cooked or canned with syrup 

6310131 Apple, baked NS as to sweetener 

6310132 Apple, baked, unsweetened 

6310133 Apple, baked with sugar 

6310141 Apple rings, fried 

6310142 Apple, pickled 

6310150 Apple, fried 

6340101 Apple, salad 

6340106 Apple, candied 

6410101 Apple cider 

6410401 Apple juice 

6410405 Apple juice with vitamin C 

6710200 Applesauce baby fd., NS as to str. or jr. 

6710201 Applesauce baby food, strained 

6710202 Applesauce baby food, junior 

6720200 Apple juice, baby food 

(includes baby food; except mixtures) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food 

Product 

Household Code/Definition Individual Code 

Tomatoes 4931­ Tomatoes, fresh 

5113­ Tomatoes, commercially canned 

5115201 Tomatoes, low sodium, commercially canned 

5115202 Tomato Sauce, low sodium, comm. canned 

5115203 Tomato Paste, low sodium, comm. canned 

5115204 Tomato Puree, low sodium, comm. canned 

5311­ Canned Tomato Juice and Tomato Mixtures 

5321­ Frozen Tomato Juice 

5371­ Fresh Tomato Juice 

5381102 Tomato Juice, aseptically packed 

5413115 Tomatoes, dry 

5614­ Tomato Soup 

5624­ Condensed Tomato Soup 

5654­ Dry Tomato Soup 

(does not include mixtures, and ready-to-eat dinners) 

74­ Tomatoes and Tomato Mixtures 

raw, cooked, juices, sauces, mixtures, soups, 

sandwiches 

Snap Beans 4943­ Snap or Wax Beans, fresh 

5114401 Green or Snap Beans, commercially canned 

5114402 Wax or Yellow Beans, commercially canned 

5114403 Beans, baby/jr., commercially canned 

5115302 Green Beans, low sodium, comm. canned 

5115303 Yell. or Wax Beans, low sod., comm. canned 

5213301 Snap or Green Beans, comm. frozen 

5213302 Snap or Green w/sauce, comm. frozen 

5213303 Snap or Green Beans w/other veg., comm. fr. 

5213304 Sp. or Gr. Beans w/other veg./sc., comm. fr. 

5213305 Wax or Yell. Beans, comm. frozen 

(does not include soups, mixtures, and ready-to-eat 

dinners; includes baby foods) 

7510180 Beans, string, green, raw 

7520498 Beans, string, cooked, NS color/fat added 

7520499 Beans, string, cooked, NS color/no fat 

7520500 Beans, string, cooked, NS color & fat 

7520501 Beans, string, cooked, green/NS fat 

7520502 Beans, string, cooked, green/no fat 

7520503 Beans, string, cooked, green/fat 

7520511 Beans, str., canned, low sod.,green/NS fat 

7520512 Beans, str., canned, low sod.,green/no fat 

7520513 Beans, str., canned, low sod.,green/fat 

7520600 Beans, string, cooked, yellow/NS fat 

7520601 Beans, string, cooked, yellow/no fat 

7520602 Beans, string, cooked, yellow/fat 

7540301 Beans, string, green, creamed 

7540302 Beans, string, green, w/mushroom sauce 

7540401 Beans, string, yellow, creamed 

7550011 Beans, string, green, pickled 

7640100 Beans, green, string, baby 

7640101 Beans, green, string, baby, str. 

7640102 Beans, green, string, baby, junior 

7640103 Beans, green, string, baby, creamed 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures; includes baby foods) 

Beef 441- Beef 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

21­ Beef 

beef, nfs 

beef steak 

beef oxtails, neckbones, ribs 

roasts, stew meat, corned, brisket, sandwich 

steaks 

ground beef, patties, meatballs 

other beef items 

beef baby food 

(excludes meat, poultry, and fish with non-meat items; 

frozen plate meals; soups and gravies with meat, poultry 

and fish base; and gelatin-based drinks; includes baby 

food) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food 

Product 

Household Code/Definition Individual Code 

Pork 442- Pork 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

22­ Pork 

pork, nfs; ground dehydrated 

chops 

steaks, cutlets 

ham 

roasts 

Canadian bacon 

bacon, salt pork 

other pork items 

pork baby food 

(excludes meat, poultry, and fish with non-meat items; 

frozen plate meals; soups and gravies with meat, poultry 

and fish base; and gelatin-based drinks; includes baby 

food) 

Game 445- Variety Meat, Game 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

233- Game 

(excludes meat, poultry, and fish with non-meat items; 

frozen plate meals; soups and gravies with meat, poultry 

and fish base; and gelatin-based drinks) 

Poultry 451- Poultry 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

24­ Poultry 

chicken 

turkey 

duck 

other poultry 

poultry baby food 

(excludes meat, poultry, and fish with non-meat items; 

frozen plate meals; soups and gravies with meat, poultry 

and fish base; and gelatin-based drinks; includes baby 

food) 

Eggs 46­ Eggs (fresh equivalent) 

fresh 

processed eggs, substitutes 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

3­ Eggs 

eggs 

egg mixtures 

egg substitutes 

eggs baby food 

froz. meals with egg as main ingred. 

(includes baby foods) 

Broccoli 4912­ Fresh Broccoli (and home canned/froz.) 

5111203 Broccoli, comm. canned 

52112­ Comm. Frozen Broccoli 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

722- Broccoli (all forms) 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures) 

Carrots 4921­ Fresh Carrots (and home canned/froz.) 

51121- Comm. Canned Carrots 

5115101 Carrots, Low Sodium, Comm. Canned 

52121- Comm. Frozen Carrots 

5312103 Comm. Canned Carrot Juice 

5372102 Carrot Juice Fresh 

5413502 Carrots, Dried Baby Food 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7310­ Carrots (all forms) 

7311140 Carrots in Sauce 

7311200 Carrot Chips 

76201­ Carrots, baby 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures; includes baby foods 

except mixtures) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food 

Product 

Household Code/Definition Individual Code 

Pumpkin 4922­ Fresh Pumpkin, Winter Squash (and home 

canned/froz.) 

51122- Pumpkin/Squash, Baby or Junior, Comm. 

Canned 

52122­ Winter Squash, Comm. Frozen 

5413504 Squash, Dried Baby Food 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

732- Pumpkin (all forms) 

733- Winter squash (all forms) 

76205­ Squash, baby 

(does not include vegetable soups; vegetables mixtures; 

or vegetable with meat mixtures; includes baby foods) 

Asparagus 4941­ Fresh Asparagus (and home canned/froz.) 

5114101 Comm. Canned Asparagus 

5115301 Asparagus, Low Sodium, Comm. Canned 

52131­ Comm. Frozen Asparagus 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7510080 Asparagus, raw 

75202- Asparagus, cooked 

7540101 Asparagus, creamed or with cheese 

(does not include vegetable soups; vegetables mixtures, 

or vegetable with meat mixtures) 

Lima Beans 4942­ Fresh Lima and Fava Beans (and home 

canned/froz.) 

5114204 Comm. Canned Mature Lima Beans 

5114301 Comm. Canned Green Lima Beans 

5115304 Comm. Canned Low Sodium Lima Beans 

52132­ Comm. Frozen Lima Beans 

54111­ Dried Lima Beans 

5411306 Dried Fava Beans 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures; does not include succotash) 

7510200 Lima Beans, raw 

752040- Lima Beans, cooked 

752041- Lima Beans, canned 

75402­ Lima Beans with sauce 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures; does not include 

succotash) 

Cabbage 4944­ Fresh Cabbage (and home canned/froz.) 

4958601 Sauerkraut, home canned or pkgd 

5114801 Sauerkraut, comm. canned 

5114904 Comm. Canned Cabbage 

5114905 Comm. Canned Cabbage (no sauce; incl. 

baby) 

5115501 Sauerkraut, low sodium., comm. canned 

5312102 Sauerkraut Juice, comm. canned 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7510300 Cabbage, raw 

7510400 Cabbage, Chinese, raw 

7510500 Cabbage, red, raw 

7514100 Cabbage salad or coleslaw 

7514130 Cabbage, Chinese, salad 

75210­ Chinese Cabbage, cooked 

75211­ Green Cabbage, cooked 

75212­ Red Cabbage, cooked 

752130- Savoy Cabbage, cooked 

75230­ Sauerkraut, cooked 

7540701 Cabbage, creamed 

755025- Cabbage, pickled or in relish 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures) 

Lettuce 4945­ Fresh Lettuce, French Endive (and home 

canned/froz.) 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

75113­ Lettuce, raw 

75143­ Lettuce salad with other veg. 

7514410 Lettuce, wilted, with bacon dressing 

7522005 Lettuce, cooked 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures) 

Okra 4946­ Fresh Okra (and home canned/froz.) 

5114914 Comm. Canned Okra 

5213720 Comm. Frozen Okra 

5213721 Comm. Frozen Okra with Oth. Veg. & Sauce 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7522000 Okra, cooked, NS as to fat 

7522001 Okra, cooked, fat not added 

7522002 Okra, cooked, fat added 

7522010 Lufta, cooked (Chinese Okra) 

7541450 Okra, fried 

7550700 Okra, pickled 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food 

Product 

Household Code/Definition Individual Code 

Peas 4947­ Fresh Peas (and home canned/froz.) 

51147­ Comm Canned Peas (incl. baby) 

5115310 Low Sodium Green or English Peas (canned) 

5115314 Low Sod. 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 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7512000 Peas, green, raw 

7512775 Snowpeas, raw 

75223­ Peas, cowpeas, field or blackeye, cooked 

75224­ Peas, green, cooked 

75225­ Peas, pigeon, cooked 

75231­ Snowpeas, cooked 

7541650 Pea salad 

7541660 Pea salad with cheese 

75417­ Peas, with sauce or creamed 

76409­ Peas, baby 

76411­ Peas, creamed, baby 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures; includes baby foods 

except mixtures) 

Cucumbers 4952­ Fresh Cucumbers (and home canned/froz.) 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7511100 Cucumbers, raw 

75142­ Cucumber salads 

752167- Cucumbers, cooked 

7550301 Cucumber pickles, dill 

7550302 Cucumber pickles, relish 

7550303 Cucumber pickles, sour 

7550304 Cucumber pickles, sweet 

7550305 Cucumber pickles, fresh 

7550307 Cucumber, Kim Chee 

7550311 Cucumber pickles, dill, reduced salt 

7550314 Cucumber pickles, sweet, reduced salt 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures) 

Beets 4954­ Fresh Beets (and home canned/froz.) 

51145­ Comm. Canned Beets (incl. baby) 

5115305 Low Sodium Beets (canned) 

5213714 Comm. Frozen Beets 

5312104 Beet Juice 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7510250 Beets, raw 

752080- Beets, cooked 

752081- Beets, canned 

7540501 Beets, harvard 

7550021 Beets, pickled 

76403­ Beets, baby 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures; includes baby foods 

except mixtures) 

Strawberries 5022­ Fresh Strawberries 

5122801 Comm. Canned Strawberries with sugar 

5122802 Comm. Canned Strawberries without sugar 

5122803 Canned Strawberry Pie Filling 

5222­ Comm. Frozen Strawberries 

(does not include ready-to-eat dinners; includes baby 

foods except mixtures) 

6322­ Strawberries 

6413250 Strawberry Juice 

(includes baby food; except mixtures) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food Household Code/Definition Individual Code 

Product 

Other 5033­ Fresh Berries Other than Strawberries 6320­ Other Berries 

Berries 5122804 Comm. Canned Blackberries with sugar 

5122805 Comm. Canned Blackberries without sugar 

5122806 Comm. Canned Blueberries with sugar 

5122807 Comm. Canned Blueberries without sugar 

5122808 Canned Blueberry Pie Filling 

5122809 Comm. Canned Gooseberries with sugar 

5122810 Comm. Canned Gooseberries without sugar 

5122811 Comm. Canned Raspberries with sugar 

5122812 Comm. Canned Raspberries without sugar 

5122813 Comm. Canned Cranberry Sauce 

5122815 Comm. Canned Cranberry-Orange Relish 

52233­ Comm. Frozen Berries (not strawberries) 

5332404 Blackberry Juice (home and comm. canned) 

5423114 Dried Berries (not strawberries) 

(does not include ready-to-eat dinners; includes baby 

foods except mixtures) 

6321­ Other Berries 

6341101 Cranberry salad 

6410460 Blackberry Juice 

64105­ Cranberry Juice 

(includes baby food; except mixtures) 

Peaches 5036­ Fresh Peaches 62116­ Dried Peaches 

51224­ Comm. Canned Peaches (incl. baby) 

5223601 Comm. Frozen Peaches 

63135­ Peaches 

6412203 Peach Juice 

5332405 Home Canned Peach Juice 6420501 Peach Nectar 

5423105 Dried Peaches (baby) 

5423106 Dried Peaches 

(does not include ready-to-eat dinners; includes baby 

foods except mixtures) 

67108- Peaches,baby 

6711450 Peaches, dry, baby 

(includes baby food; except mixtures) 

Pears 5037­ Fresh Pears 62119­ Dried Pears 

51225­ Comm. Canned Pears (incl. baby) 

5332403 Comm. Canned Pear Juice, baby 

5362204 Fresh Pear Juice 

63137­ Pears 

6341201 Pear salad 

6421501 Pear Nectar 

5423107 Dried Pears 

(does not include ready-to-eat dinners; includes baby 

foods except mixtures) 

67109­ Pears, baby 

6711455 Pears, dry, baby 

(includes baby food; except mixtures) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food Household Code/Definition Individual Code 

Product 

EXPOSED/PROTECTED FRUITS/VEGETABLES, ROOT VEGETABLES 

Exposed 

Fruits 

5022­ Strawberries, fresh 

5023101 Acerola, fresh 

5023401 Currants, fresh 

62101­ Apple, dried 

62104­ Apricot, dried 

62108­ Currants, dried 

5031- Apples/Applesauce, fresh 

5033­ Berries other than Strawberries, fresh 

62110­ Date, dried 

62116­ Peaches, dried 

5034­ Cherries, fresh 62119­ Pears, dried 

5036­ Peaches, fresh 62121­ Plum, dried 

5037­ Pears, fresh 62122­ Prune, dried 

50381­ Apricots, Nectarines, Loquats, fresh 

5038305 Dates, fresh 

50384­ Grapes, fresh 

50386­ Plums, fresh 

50387­ Rhubarb, fresh 

62125­ Raisins 

63101- Apples/applesauce 

63102- Wi-apple 

63103­ Apricots 

63111­ Cherries, maraschino 

5038805 Persimmons, fresh 63112­ Acerola 

5038901 Sapote, fresh 

51221- Apples/Applesauce, canned 

51222­ Apricots, canned 

51223­ Cherries, canned 

51224­ Peaches, canned 

51225­ Pears, canned 

63113­ Cherries, sour 

63115­ Cherries, sweet 

63117­ Currants, raw 

63123­ Grapes 

6312601 Juneberry 

63131­ Nectarine 

51228­ Berries, canned 63135­ Peach 

5122903 Grapes with sugar, canned 

5122904 Grapes without sugar, canned 

5122905 Plums with sugar, canned 

5122906 Plums without sugar, canned 

5122907 Plums, canned, baby 

5122911 Prunes, canned, baby 

5122912 Prunes, with sugar, canned 

5122913 Prunes, without sugar, canned 

5122914 Raisin Pie Filling 

5222­ Frozen Strawberries 

52231­ Apples Slices, frozen 

52233­ Berries, frozen 

52234­ Cherries, frozen 

52236­ Peaches, frozen 

63137­ Pear 

63139­ Persimmons 

63143­ Plum 

63146­ Quince 

63147- Rhubarb/Sapodillo 

632- Berries 

64101­ Apple Cider 

64104­ Apple Juice 

64105­ Cranberry Juice 

64116­ Grape Juice 

64122­ Peach Juice 

64132- Prune/Strawberry Juice 

6420101 Apricot Nectar 

64205­ Peach Nectar 

52239­ Rhubarb, frozen 64215­ Pear Nectar 

53321­ Canned Apple Juice 

53322­ Canned Grape Juice 

67102­ Applesauce, baby 

67108­ Peaches, baby 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food Household Code/Definition Individual Code 

Product 

Exposed 

Fruits 

(continued) 

5332402 Canned Prune Juice 

5332403 Canned Pear Juice 

5332404 Canned Blackberry Juice 

5332405 Canned Peach Juice 

53421­ Frozen Grape Juice 

5342201 Frozen Apple Juice, comm. fr. 

5342202 Frozen Apple Juice, home fr. 

5352101 Apple Juice, asep. packed 

5352201 Grape Juice, asep. packed 

5362101 Apple Juice, fresh 

5362202 Apricot Juice, fresh 

5362203 Grape Juice, fresh 

5362204 Pear Juice, fresh 

67109­ Pears, baby 

6711450 Peaches, baby, dry 

6711455 Pears, baby, dry 

67202­ Apple Juice, baby 

6720380 White Grape Juice, baby 

67212­ Pear Juice, baby 

(includes baby foods/juices except mixtures; excludes 

fruit mixtures) 

5362205 Prune Juice, fresh 

5421­ Dried Prunes 

5422­ Raisins, Currants, dried 

5423101 Dry Apples 

5423102 Dry Apricots 

5423103 Dates without pits 

5423104 Dates with pits 

5423105 Peaches, dry, baby 

5423106 Peaches, dry 

5423107 Pears, dry 

5423114 Berries, dry 

5423115 Cherries, dry 

(includes baby foods) 

Protected 

Fruits 

501- Citrus Fruits, fresh 

5021­ Cantaloupe, fresh 

5023201 Mangoes, fresh 

5023301 Guava, fresh 

5023601 Kiwi, fresh 

5023701 Papayas, fresh 

5023801 Passion Fruit, fresh 

61­ Citrus Fr., Juices (incl. cit. juice mixtures) 

62107­ Bananas, dried 

62113­ Figs, dried 

62114- Lychees/Papayas, dried 

62120­ Pineapple, dried 

62126­ Tamarind, dried 

63105­ Avocado, raw 

5032­ Bananas, Plantains, fresh 63107­ Bananas 

5035­ Melons other than Cantaloupe, fresh 

50382­ Avocados, fresh 

63109­ Cantaloupe, Carambola 

63110­ Cassaba Melon 

5038301 Figs, fresh 

5038302 Figs, cooked 

5038303 Figs, home canned 

5038304 Figs, home frozen 

50385­ Pineapple, fresh 

5038801 Pomegranates, fresh 

5038902 Cherimoya, fresh 

5038903 Jackfruit, fresh 

5038904 Breadfruit, fresh 

5038905 Tamarind, fresh 

63119­ Figs 

63121­ Genip 

63125- Guava/Jackfruit, raw 

6312650 Kiwi 

6312651 Lychee, raw 

6312660 Lychee, cooked 

63127­ Honeydew 

63129­ Mango 

63133­ Papaya 

63134­ Passion Fruit 

5038906 Carambola, fresh 

5038907 Longan, fresh 

5121­ Citrus, canned 

51226­ Pineapple, canned 

5122901 Figs with sugar, canned 

5122902 Figs without sugar, canned 

5122909 Bananas, canned, baby 

5122910 Bananas and Pineapple, canned, baby 

5122915 Litchis, canned 

63141­ Pineapple 

63145­ Pomegranate 

63148­ Sweetsop, Soursop, Tamarind 

63149­ Watermelon 

64120­ Papaya Juice 

64121­ Passion Fruit Juice 

64124­ Pineapple Juice 

64133­ Watermelon Juice 

6420150 Banana Nectar 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food 

Product 

Household Code/Definition Individual Code 

Protected 

Fruits 

(continued) 

5122916 Mangos with sugar, canned 

5122917 Mangos without sugar, canned 

5122918 Mangos, canned, baby 

5122920 Guava with sugar, canned 

5122921 Guava without sugar, canned 

5122923 Papaya with sugar, canned 

5122924 Papaya without sugar, canned 

52232­ Bananas, frozen 

52235­ Melon, frozen 

52237­ Pineapple, frozen 

5331­ Canned Citrus Juices 

53323­ Canned Pineapple Juice 

5332408 Canned Papaya Juice 

5332410 Canned Mango Juice 

5332501 Canned Papaya Concentrate 

5341­ Frozen Citrus Juice 

64202­ Cantaloupe Nectar 

64203­ Guava Nectar 

64204­ Mango Nectar 

64210­ Papaya Nectar 

64213­ Passion Fruit Nectar 

64221­ Soursop Nectar 

6710503 Bananas, baby 

6711500 Bananas, baby, dry 

6720500 Orange Juice, baby 

6721300 Pineapple Juice, baby 

(includes baby foods/juices except mixtures; excludes 

fruit mixtures) 

5342203 Frozen Pineapple Juice 

5351­ Citrus and Citrus Blend Juices, asep. packed 

5352302 Pineapple Juice, asep. packed 

5361­ Fresh Citrus and Citrus Blend Juices 

5362206 Papaya Juice, fresh 

5362207 Pineapple-Coconut Juice, fresh 

5362208 Mango Juice, fresh 

5362209 Pineapple Juice, fresh 

5423108 Pineapple, dry 

5423109 Papaya, dry 

5423110 Bananas, dry 

5423111 Mangos, dry 

5423117 Litchis, dry 

5423118 Tamarind, dry 

5423119 Plantain, dry 

(includes baby foods) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food 

Product 

Household Code/Definition Individual Code 

Exposed 

Veg. 

491- Fresh Dark Green Vegetables 

493- Fresh Tomatoes 

4941­ Fresh Asparagus 

4943­ Fresh Beans, Snap or Wax 

4944­ Fresh Cabbage 

4945­ Fresh Lettuce 

4946­ Fresh Okra 

49481­ Fresh Artichokes 

49483­ Fresh Brussel Sprouts 

4951­ Fresh Celery 

4952­ Fresh Cucumbers 

4955­ Fresh Cauliflower 

4958103 Fresh Kohlrabi 

721- Dark Green Leafy Veg. 

722- Dark Green Nonleafy Veg. 

74­ Tomatoes and Tomato Mixtures 

7510050 Alfalfa Sprouts 

7510075 Artichoke, Jerusalem, raw 

7510080 Asparagus, raw 

75101­ Beans, sprouts and green, raw 

7510275 Brussel Sprouts, raw 

7510280 Buckwheat Sprouts, raw 

7510300 Cabbage, raw 

7510400 Cabbage, Chinese, raw 

7510500 Cabbage, Red, raw 

7510700 Cauliflower, raw 

4958111 Fresh Jerusalem Artichokes 

4958112 Fresh Mushrooms 

7510900 Celery, raw 

7510950 Chives, raw 

4958113 Mushrooms, home canned 7511100 Cucumber, raw 

4958114 Mushrooms, home frozen 

4958118 Fresh Eggplant 

4958119 Eggplant, cooked 

4958120 Eggplant, home frozen 

4958200 Fresh Summer Squash 

4958201 Summer Squash, cooked 

4958202 Summer Squash, home canned 

4958203 Summer Squash, home frozen 

4958402 Fresh Bean Sprouts 

4958403 Fresh Alfalfa Sprouts 

4958504 Bamboo Shoots 

4958506 Seaweed 

4958508 Tree Fern, fresh 

4958601 Sauerkraut 

5111­ Dark Green Vegetables (all are exposed) 

5113­ Tomatoes 

7511120 Eggplant, raw 

7511200 Kohlrabi, raw 

75113­ Lettuce, raw 

7511500 Mushrooms, raw 

7511900 Parsley 

7512100 Pepper, hot chili 

75122­ Peppers, raw 

7512750 Seaweed, raw 

7512775 Snowpeas, raw 

75128­ Summer Squash, raw 

7513210 Celery Juice 

7514100 Cabbage or cole slaw 

7514130 Chinese Cabbage Salad 

7514150 Celery with cheese 

75142­ Cucumber salads 

75143­ Lettuce salads 

5114101 Asparagus, comm. canned 

51144­ Beans, green, snap, yellow, comm. canned 

5114704 Snow Peas, comm. canned 

5114801 Sauerkraut, comm. canned 

5114901 Artichokes, comm. canned 

7514410 Lettuce, wilted with bacon dressing 

7514600 Greek salad 

7514700 Spinach salad 

7520600 Algae, dried 

75201­ Artichoke, cooked 

5114902 Bamboo Shoots, comm. canned 

5114903 Bean Sprouts, comm. canned 

5114904 Cabbage, comm. canned 

5114905 Cabbage, comm. canned, no sauce 

5114906 Cauliflower, comm. canned, no sauce 

5114907 Eggplant, comm. canned, no sauce 

5114913 Mushrooms, comm. canned 

75202­ Asparagus, cooked 

75203­ Bamboo shoots, cooked 

752049- Beans, string, cooked 

75205­ Beans, green, cooked/canned 

75206­ Beans, yellow, cooked/canned 

75207­ Bean Sprouts, cooked 

752085- Breadfruit 

5114914 Okra, comm. canned 

5114918 Seaweeds, comm. canned 

5114920 Summer Squash, comm. canned 

752090- Brussel Sprouts, cooked 

75210­ Cabbage, Chinese, cooked 

75211­ Cabbage, green, cooked 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food 

Product 

Household Code/Definition Individual Code 

Exposed 

Veg. 

(cont.) 

5114923 Chinese or Celery Cabbage, comm. canned 

51152­ Tomatoes, canned, low sod. 

5115301 Asparagus, canned, low sod. 

5115302 Beans, Green, canned, low sod. 

5115303 Beans, Yellow, canned, low sod. 

75212­ Cabbage, red, cooked 

752130- Cabbage, savoy, cooked 

75214­ Cauliflower 

75215­ Celery, Chives, Christophine (chayote) 

752167- Cucumber, cooked 

5115309 Mushrooms, canned, low sod. 

51154­ Greens, canned, low sod. 

752170- Eggplant, cooked 

752171- Fern shoots 

5115501 Sauerkraut, low sodium 752172- Fern shoots 

5211­ Dark Gr. Veg., comm. frozen (all exp.) 

52131­ Asparagus, comm. froz. 

52133­ Beans, snap, green, yellow, comm. froz. 

5213407 Peapods, comm froz. 

5213408 Peapods, with sauce, comm froz. 

5213409 Peapods, with other veg., comm froz. 

5213701 Brussel Sprouts, comm. froz. 

5213702 Brussel Sprouts, comm. froz. with cheese 

5213703 Brussel Sprouts, comm. froz. with other veg. 

5213705 Cauliflower, comm. froz. 

752173- Flowers of sesbania, squash or lily 

7521801 Kohlrabi, cooked 

75219­ Mushrooms, cooked 

75220- Okra/lettuce, cooked 

7522116 Palm Hearts, cooked 

7522121 Parsley, cooked 

75226­ Peppers, pimento, cooked 

75230­ Sauerkraut, cooked/canned 

75231­ Snowpeas, cooked 

75232­ Seaweed 

5213706 Cauliflower, comm. froz. with sauce 

5213707 Cauliflower, comm. froz. with other veg. 

5213708 Caul., comm. froz. with other veg. & sauce 

5213709 Summer Squash, comm. froz. 

5213710 Summer Squash, comm. froz. with other veg. 

5213716 Eggplant, comm. froz. 

5213718 Mushrooms with sauce, comm. froz. 

5213719 Mushrooms, comm. froz. 

75233­ Summer Squash 

7540050 Artichokes, stuffed 

7540101 Asparagus, creamed or with cheese 

75403­ Beans, green with sauce 

75404­ Beans, yellow with sauce 

7540601 Brussel Sprouts, creamed 

7540701 Cabbage, creamed 

75409­ Cauliflower, creamed 

5213720 Okra, comm. froz. 

5213721 Okra, comm. froz., with sauce 

5311­ Canned Tomato Juice and Tomato Mixtures 

75410- Celery/Chiles, creamed 

75412­ Eggplant, fried, with sauce, etc. 

75413­ Kohlrabi, creamed 

5312102 Canned Sauerkraut Juice 75414­ Mushrooms, Okra, fried, stuffed, creamed 

5321­ Frozen Tomato Juice 

5371­ Fresh Tomato Juice 

5381102 Aseptically Packed Tomato Juice 

5413101 Dry Algae 

5413102 Dry Celery 

5413103 Dry Chives 

5413109 Dry Mushrooms 

5413111 Dry Parsley 

5413112 Dry Green Peppers 

5413113 Dry Red Peppers 

5413114 Dry Seaweed 

5413115 Dry Tomatoes 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

754180- Squash, baked, fried, creamed, etc. 

7541822 Christophine, creamed 

7550011 Beans, pickled 

7550051 Celery, pickled 

7550201 Cauliflower, pickled 

755025- Cabbage, pickled 

7550301 Cucumber pickles, dill 

7550302 Cucumber pickles, relish 

7550303 Cucumber pickles, sour 

7550304 Cucumber pickles, sweet 

7550305 Cucumber pickles, fresh 

7550307 Cucumber, Kim Chee 

7550308 Eggplant, pickled 

7550311 Cucumber pickles, dill, reduced salt 

7550314 Cucumber pickles, sweet, reduced salt 

7550500 Mushrooms, pickled 

7550700 Okra, pickled 

75510­ Olives 

7551101 Peppers, hot 

7551102 Peppers,pickled 

7551301 Seaweed, pickled 

7553500 Zucchini, pickled 

76102­ Dark Green Veg., baby 

76401­ Beans, baby (excl. most soups & mixtures) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food 

Product 

Household Code/Definition Individual Code 

Protected 

Veg. 

4922­ Fresh Pumpkin, Winter Squash 

4942­ Fresh Lima Beans 

4947­ Fresh Peas 

732- Pumpkin 

733- Winter Squash 

7510200 Lima Beans, raw 

49482­ Fresh Soy Beans 

4956­ Fresh Corn 

7510550 Cactus, raw 

7510960 Corn, raw 

4958303 Succotash, home canned 7512000 Peas, raw 

4958304 Succotash, home frozen 

4958401 Fresh Cactus (prickly pear) 

4958503 Burdock 

7520070 Aloe vera juice 

752040- Lima Beans, cooked 

752041- Lima Beans, canned 

4958505 Bitter Melon 7520829 Bitter Melon 

4958507 Horseradish Tree Pods 752083- Bitter Melon, cooked 

51122­ Comm. Canned Pumpkin and Squash (baby) 

51142­ Beans, comm. canned 

7520950 Burdock 

752131- Cactus 

51143­ Beans, lima and soy, comm. canned 

51146­ Corn, comm. canned 

5114701 Peas, green, comm. canned 

5114702 Peas, baby, comm. canned 

5114703 Peas, blackeye, comm. canned 

5114705 Pigeon Peas, comm. canned 

5114919 Succotash, comm. canned 

5115304 Lima Beans, canned, low sod. 

5115306 Corn, canned, low sod. 

5115307 Creamed Corn, canned, low sod. 

752160- Corn, cooked 

752161- Corn, yellow, cooked 

752162- Corn, white, cooked 

752163- Corn, canned 

7521749 Hominy 

752175- Hominy 

75223­ Peas, cowpeas, field or blackeye, cooked 

75224­ Peas, green, cooked 

75225­ Peas, pigeon, cooked 

75301­ Succotash 

511531- Peas and Beans, canned, low sod. 75402­ Lima Beans with sauce 

52122­ Winter Squash, comm. froz. 

52132­ Lima Beans, comm. froz. 

75411­ Corn, scalloped, fritter, with cream 

7541650 Pea salad 

5213401 Peas, gr., comm. froz. 

5213402 Peas, gr., with sauce, comm. froz. 

5213403 Peas, gr., with other veg., comm. froz. 

5213404 Peas, gr., with other veg., comm. froz. 

5213405 Peas, blackeye, comm froz. 

5213406 Peas, blackeye, with sauce, comm froz. 

52135­ Corn, comm. froz. 

5213712 Artichoke Hearts, comm. froz. 

5213713 Baked Beans, comm. froz. 

5213717 Kidney Beans, comm. froz. 

5213724 Succotash, comm. froz. 

7541660 Pea salad with cheese 

75417­ Peas, with sauce or creamed 

7550101 Corn relish 

76205­ Squash, yellow, baby 

76405­ Corn, baby 

76409­ Peas, baby 

76411­ Peas, creamed, baby 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures) 

5411­ Dried Beans 

5412­ Dried Peas and Lentils 

5413104 Dry Corn 

5413106 Dry Hominy 

5413504 Dry Squash, baby 

5413603 Dry Creamed Corn, baby 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food 

Product 

Household Code/Definition Individual Code 

Root 

Vegetables 

48­ Potatoes, Sweetpotatoes 

4921­ Fresh Carrots 

4953­ Fresh Onions, Garlic 

71­ White Potatoes and Puerto Rican St. Veg. 

7310­ Carrots 

7311140 Carrots in sauce 

4954­ Fresh Beets 

4957­ Fresh Turnips 

4958101 Fresh Celeriac 

7311200 Carrot chips 

734- Sweetpotatoes 

7510250 Beets, raw 

4958102 Fresh Horseradish 7511150 Garlic, raw 

4958104 Fresh Radishes, no greens 

4958105 Radishes, home canned 

7511180 Jicama (yambean), raw 

7511250 Leeks, raw 

4958106 Radishes, home frozen 75117­ Onions, raw 

4958107 Fresh Radishes, with greens 

4958108 Fresh Salsify 

4958109 Fresh Rutabagas 

4958110 Rutabagas, home frozen 

4958115 Fresh Parsnips 

4958116 Parsnips, home canned 

4958117 Parsnips, home frozen 

4958502 Fresh Lotus Root 

7512500 Radish, raw 

7512700 Rutabaga, raw 

7512900 Turnip, raw 

752080- Beets, cooked 

752081- Beets, canned 

7521362 Cassava 

7521740 Garlic, cooked 

7521771 Horseradish 

4958509 Ginger Root 

4958510 Jicama, including yambean 

51121­ Carrots, comm. canned 

51145­ Beets, comm. canned 

5114908 Garlic Pulp, comm. canned 

5114910 Horseradish, comm. prep. 

5114915 Onions, comm. canned 

5114916 Rutabagas, comm. canned 

5114917 Salsify, comm. canned 

5114921 Turnips, comm. canned 

5114922 Water Chestnuts, comm. canned 

7521850 Lotus root 

752210- Onions, cooked 

7522110 Onions, dehydrated 

752220- Parsnips, cooked 

75227­ Radishes, cooked 

75228­ Rutabaga, cooked 

75229­ Salsify, cooked 

75234­ Turnip, cooked 

75235­ Water Chestnut 

7540501 Beets, harvard 

75415­ Onions, creamed, fried 

51151­ Carrots, canned, low sod. 

5115305 Beets, canned, low sod. 

5115502 Turnips, low sod. 

52121­ Carrots, comm. froz. 

7541601 Parsnips, creamed 

7541810 Turnips, creamed 

7550021 Beets, pickled 

7550309 Horseradish 

5213714 Beets, comm. froz. 

5213722 Onions, comm. froz. 

5213723 Onions, comm. froz., with sauce 

5213725 Turnips, comm. froz. 

5312103 Canned Carrot Juice 

5312104 Canned Beet Juice 

5372102 Fresh Carrot Juice 

5413105 Dry Garlic 

5413110 Dry Onion 

5413502 Dry Carrots, baby 

5413503 Dry Sweet Potatoes, baby 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures) 

7551201 Radishes, pickled 

7553403 Turnip, pickled 

76201­ Carrots, baby 

76209­ Sweetpotatoes, baby 

76403­ Beets, baby 

(does not include vegetable soups; vegetable mixtures; 

or vegetable with meat mixtures) 
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) 

Food Household Code/Definition Individual Code 

Product 

USDA SUBCATEGORIES 

Dark Green 

Vegetables 

491- Fresh Dark Green Vegetables 

5111­ Comm. Canned Dark Green Veg. 

51154­ Low Sodium Dark Green Veg. 

5211­ Comm. Frozen Dark Green Veg. 

5413111 Dry Parsley 

5413112 Dry Green Peppers 

5413113 Dry Red Peppers 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures/dinners; excludes vegetable juices and dried 

vegetables) 

72­ Dark Green Vegetables 

all forms 

leafy, nonleafy, dk. gr. veg. soups 

Deep Yellow 

Vegetables 

492- Fresh Deep Yellow Vegetables 

5112­ Comm. Canned Deep Yellow Veg. 

51151­ Low Sodium Carrots 

5212­ Comm. Frozen Deep Yellow Veg. 

5312103 Carrot Juice 

73­ Deep Yellow Vegetables 

all forms 

carrots, pumpkin, squash, sweetpotatoes, dp. 

yell. veg. soups 

54135­ Dry Carrots, Squash, Sw. Potatoes 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures/dinners; excludes vegetable juices and dried 

vegetables) 

Other 

Vegetables 

494- Fresh Light Green Vegetables 

495- Fresh Other Vegetables 

5114­ Comm. Canned Other Veg. 

51153­ Low Sodium Other Veg. 

51155­ Low Sodium Other Veg. 

5213­ Comm. Frozen Other Veg. 

5312102 Sauerkraut Juice 

75­ Other Vegetables 

all forms 

5312104 Beet Juice 

5411­ Dreid Beans 

5412­ Dried Peas, Lentils 

541310- Dried Other Veg. 

5413114 Dry Seaweed 

5413603 Dry Cr. Corn, baby 

(does not include soups, sauces, gravies, mixtures, and 

ready-to-eat dinners; includes baby foods except 

mixtures/dinners; excludes vegetable juices and dried 

vegetables) 

Citrus Fruits 501- Fresh Citrus Fruits 61­ Citrus Fruits and Juices 

5121­ Comm. Canned Citrus Fruits 

5331­ Canned Citrus and Citrus Blend Juice 

5341­ Frozen Citrus and Citrus Blend Juice 

5351­ Aseptically Packed Citrus and Citr. Blend 

Juice 

5361­ Fresh Citrus and Citrus Blend Juice 

6720500 Orange Juice, baby food 

6720600 Orange-Apricot Juice, baby food 

6720700 Orange-Pineapple Juice, baby food 

6721100 Orange-Apple-Banana Juice, baby food 

(excludes dried fruits) 

(includes baby foods; excludes dried fruits) 

Other Fruits 502- Fresh Other Vitamin C-Rich Fruits 62­ Dried Fruits 

503- Fresh Other Fruits 63­ Other Fruits 

5122­ Comm. Canned Fruits Other than Citrus 

5222­ Frozen Strawberries 

5223­ Frozen Other than Citr. or Vitamin C-Rich Fr. 

5332­ Canned Fruit Juice Other than Citrus 

5342­ Frozen Juices Other than Citrus 

5352­ Aseptically Packed Fruit Juice Other than Citr. 

5362­ Fresh Fruit Juice Other than Citrus 

542- Dry Fruits 

(includes baby foods; excludes dried fruits) 

64­ Fruit Juices and Nectars Excluding Citrus 

671- Fruits, baby 

67202­ Apple Juice, baby 

67203­ Baby Juices 

67204­ Baby Juices 

67212­ Baby Juices 

67213­ Baby Juices 

673- Baby Fruits 

674- Baby Fruits 
Table 14-1. Daily Intakes of Breast Milk 

Number of 

Age Period (mL/day) 

Infants Surveyed 

at Each Time Mean Intake a (mL/day) 

Range of 

Daily Intake 

Completely Breast-fed 

1 month 11 600 ± 159 426 - 989 

3 months 2 833 645 - 1,000 

6 months 1 682 616 - 786 

Partially Breast-fed 

1 month 4 485 ± 79 398 - 655 

3 months 11 467 ± 100 242 - 698 

6 months 6 395 ± 175 147 - 684 

9 months 3 <554 451 - 732

 Data expressed as mean ± standard deviation. a 

Source: Pao et al., 1980. 
Table 14-2. Breast Milk Intake for Infants Aged 1 to 6 Months 

Age Number of Mean SD Range 

(months) Infants (mL/day) (mL/day) (mL/day) a 

1 16 673 192 341-1,003 

2 19 756 170 449-1,055 

3 16 782 172 492-1,053 

4 13 810 142 593-1,045 

5 11 805 117 554-1,045 

6 11 896 122 675-1,096

 Standard deviation. a 

Source: Dewey and Lönnerdal, 1983. 
Table 14-3. Breast Milk Intake Among Exclusively Breast-fed 

Infants During the First 4 Months of Life 

Age (months) of Intake Intake Weight 

Number Breast Milk Breast Milk Body 

Infants (g/day) (g/kg-day) (kg) 

a a b 

1 37 751.0 ± 130.0 159.0 ± 24.0 4.7 

2 40 725.0 ± 131.0 129.0 ± 19.0 5.6 

3 37 723.0 ± 114.0 117.0 ± 20.0 6.2 

4 41 740.0 ± 128.0 111.0 ± 17.0 6.7 

Data expressed as mean ± standard deviation. a 

Calculated by dividing breast milk intake (g/day) by breast milk intake (g/kg-day). b 

Source: Butte et al., 1984. 
Table 14-4. Breast Milk Intake During a 24-Hour Period 

Standard 

Age Number of Mean Deviation Range 

(days) Infants (g/day) (g/day) (g/day) 

1 7 44 71 -31-149 a

2 10 182 86 44-355 

3 11 371 153 209-688 

4 11 451 176 164-694 

5 12 498 129 323-736 

6 10 508 167 315-861 

7 8 573 167 406-842 

8 9 581 159 410-923 

9 10 580 76 470-720 

10 10 589 132 366-866 

11 8 615 168 398-934 

14 10 653 154 416-922 

21 10 651 84 554-786 

28 13 770 179 495-1144 

35 12 668 117 465-930 

42 12 711 111 554-896 

49 10 709 115 559-922 

56 13 694 98 556-859 

90 12 734 114 613-942 

120 13 711 100 570-847 

150 13 838 134 688-1173 

180 13 766 121 508-936 

210 12 721 154 486-963 

240 10 622 210 288-1002 

270 12 618 220 223-871 

300 11 551 234 129-894 

330 9 554 240 120-860 

360 9 403 250 65-770 

Negative value due to insensible water loss correction. a 

Source: Neville et al., 1988. 
Table 14-5. Breast Milk Intake Estimated by the DARLING Study 

Age (months) Number of Mean Intake Standard Deviation 

Infants (g/day) (g/day) 

3 73 812 133 

6 60 769 171 

9 50 646 217 

12 42 448 251 

Source: Dewey et al. (1991b). 
Table 14-6. Milk Intake for Bottle- and Breast-fed 

Infants by Age Group 

Age Breast Milk Substitutes Breast Milk 

(months) Mean (g/day) Mean (g/day) a a 

1 713 656 

2 811 773 

3 853 776 

(500-1,000) (360-860) 

(670-1,180) (575-985) 

(655-1,065) (600-930)

 Range given in parentheses. a 

Source: Hofvander et al., 1982. 
Table 14-7. Milk Intake for Boys and Girls 

Boys Girls 

Mean Mean 

Age (g/day) N (g/day) N 

Breast milk 

1 663 12 649 13 

2 791 14 750 11 

3 811 12 743 13 

Breast milk substitute 

1 753 10 687 15 

2 863 13 753 12 

3 862 13 843 12 

Source: Hofvander et al., 1982. 
Table 14-8. Intake of Breast Milk and Formula 

Breast Milk Cow's Formula Soy Formula 

Age N Mean SD N Mean SD N Mean SD 

(wks) (g/day) (g/day) (g/day) (g/day) (g/day) (g/day

6 26 746 101 20 823 111 13 792 127 

14 21 726 143 19 921 95 13 942 78 

22 13 722 114 18 818 201 13 861 196 

26 12 689 120 18 722 209 12 776 159 

Source: Köhler et al., 1984. 
Table 14-9. Lipid Content of Human Milk and Estimated Lipid Intake 

Among Exclusively Breast-fed Infants 

Age (months) Number Lipid Lipid Lipid 

of Content Content Intake 

Observations (mg/g) (percent) (g/day) a b a 

Lipid 

Intake 

(g/kg-day) a 

1 37 36.2 ± 7.5 3.6 28.0 ± 8.5 5.9 ± 1.7 

2 40 34.4 ± 6.8 3.4 25.2 ± 7.1 4.4 ± 1.2 

3 37 32.2 ± 7.8 3.2 23.6 ± 7.2 3.8 ± 1.2 

4 41 34.8 ± 10.8 3.5 25.6 ± 8.6 3.8 ± 1.3 

Data expressed as means ± standard deviations. a 

Percents calculated from lipid content reported in mg/g. b 

Source: Butte, et al., 1984. 
Table 14-10. Predicted Lipid Intakes for Breast-fed Infants 

Under 12 Months of Age 

Statistic Value 

Number of Observations in Simulation 1,113 

Minimum Lipid Intake 1.0 g/day 

Maximum Lipid Intake 51.5 g/day 

Arithmetic Mean Lipid Intake 26.8 g/day 

Standard Deviation Lipid Intake 7.4 g/day 

Source: Maxwell and Burmaster, 1993. 
Table 14-11. Number of Meals Per Day 

Age (months) Bottle-fed Infants Breast-fed 

(meals/day) (meals/day) a a 

1 5.4 (4-7) 5.8 (5-7) 

2 4.8 (4-6) 5.3 (5-7) 

3 4.7 (3-6) 5.1 (4-8) 

Data expressed as mean with range in parentheses. a 

Source: Hofvander et al., 1982. 
Table 14-12. 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 , by Ethnic Background and Selected Demographic Variables a b 

Total White Black Hispanicc 

Category Newborns 5-6 Mo Newborn 5-6 Mo Newborns 5-6 Mo Newborns 5-6 Mo 

Infants s Infants Infants Infants 

All mothers 52.2 19.6 58.5 22.7 23.0 7.0 48.4 15.0 

Parity

 Primiparous 52.6 16.6 58.3 18.9 23.1 5.9 49.9 13.2

 Multiparous 51.7 22.7 58.7 26.8 23.0 7.9 47.2 16.5 

Marital status

 Married 59.8 24.0 61.9 25.3 35.8 12.3 55.3 18.8

 Unmarried 30.8 7.7 40.3 9.8 17.2 4.6 37.5 8.6 

Maternal age

 <20 yr 30.2 6.2 36.8 7.2 13.5 3.6 35.3 6.9

 20-24 yr 45.2 12.7 50.8 14.5 19.4 4.7 46.9 12.6

 25-29 yr 58.8 22.9 63.1 25.0 29.9 9.4 56.2 19.5

 30-34 yr 65.5 31.4 70.1 34.8 35.4 13.6 57.6 23.4 

$35 yr 66.5 36.2 71.9 40.5 35.6 14.3 53.9 24.4 

Maternal education

 No college 42.1 13.4 48.3 15.6 17.6 5.5 42.6 12.2

 College 70.7 31.1 74.7 34.1 41.1 12.2 66.5 23.4 d 

Family income

 <$7,000 28.8 7.9 36.7 9.4 14.5 4.3 35.3 10.3

 $7,000-$14,999 44.0 13.5 49.0 15.2 23.5 7.3 47.2 13.0

 $15,000-$24,999 54.7 20.4 57.7 22.3 31.7 8.7 52.6 16.5 

$$25,000 66.3 27.6 67.8 28.7 42.8 14.5 65.4 23.0 

Maternal employment

 Full time 50.8 10.2 54.8 10.8 30.6 6.9 50.4 9.5

 Part time 59.4 23.0 63.8 25.5 26.0 6.6 59.4 17.7

 Not employed 51.0 23.1 58.7 27.5 19.3 7.2 46.0 16.7 

U.S. census region

 New England 52.2 20.3 53.2 21.4 35.6 5.0 47.6 14.9

 Middle Atlantic 47.4 18.4 52.4 21.8 30.6 9.7 41.4 10.8

 East North Central 47.6 18.1 53.2 20.7 21.0 7.2 46.2 12.6

 West North Central 55.9 19.9 58.2 20.7 27.7 7.9 50.8 22.8

 South Atlantic 43.8 14.8 53.8 18.7 19.6 5.7 48.0 13.8

 East South Central 37.9 12.4 45.1 15.0 14.2 3.7 23.5 5.0

 West South Central 46.0 14.7 56.2 18.4 14.5 3.8 39.2 11.4

 Mountain 70.2 30.4 74.9 33.0 31.5 11.0 53.9 18.2

 Pacific 70.3 28.7 76.7 33.4 43.9 15.0 58.5 19.7 

Mothers were surveyed when their infants were 6 months of age. They were asked to recall the method of feeding the infant a 

when in the hospital, at age 1 week, at months 1 through 5, and on the day preceding completion of the survey. Numbers in 

the columns labeled "5-6 Mo Infants" are an average of the 5-month and previous day responses. 

Based on data from Ross Laboratories. b 

Hispanic is not exclusive of white or black. c 

College includes all women who reported completing at least 1 year of college. d 

Source: NAS, 1991. 
Table 14-13. Breast Milk Intake Studies 

Study Individuals 

Number of 

Type of Feeding Sampling Time and Interval Population Studied Comments 

KEY STUDIES 

Butte et al., 1984 45 Exclusively breast-fed 

for first 4 months 

Most infants studied over 1 Mid- to upperday only, at 1, 2, 3, 4 months socioeconomic stratum 

some studied over 48 to 96 

Estimated breast milk intake; 

corrected for insensible water loss 

hours to study individual 

variability 

Dewey et al., 

1991a; 1991b 

73 Breast-fed for 12 

months; exclusively 

breast-fed for at least 

first 4 months 

Test weighing over 4-day Highly educated, highperiod every 3 months for 1 socioeconomic class from 

year Davis area of California 

Estimated breast milk intake; 

corrected for insensible water loss 

Dewey and 

Lönnerdal, 1983 

20 Most infants exclusively 

breast-fed 

Two test weighings per month Mid to upper class from 

for 6 months Davis area of California 

Estimated breast milk intake; did 

not correct for insensible water 

loss 

Neville et al., 

1988 

13 Exclusively breast-fed 

infants 

Infants studied over 24-hour Nonsmoking Caucasian 

period at each sampling mothers; middle- to 

interval; numerous sampling upper-socioeconomic 

intervals over first year of life status 

Estimated breast milk intake and 

lipid intake; corrected for 

insensible water loss; estimated 

frequency and duration of feeding 

Pao et al., 1980 22 Completely or partially 

breast-fed infants 

Three consecutive days at 1, White middle class from 

3, 6, and 9 months southeastern Ohio 

Estimated breast milk intake; did 

not correct for insensible water 

loss 
Table 14-13. Breast Milk Intake Studies (continued) 

Study Individuals 

Number of 

Type of Feeding Sampling Time and Interval Population Studied Comments 

RELEVANT 

STUDIES 

Axelsson et al., 

1987 

30 Breast-fed infants and Studied over 2-day periods Swedish infants 

infants fed formula with at 4.5 and 5.5 months of 

Measured intake rates; not 

corrected for insensible water loss 

two different energy age 

contents 

Brown et al., 1986a; 

1986b 

58, 60 Breast-fed infants Studied over 3 days at each Bangledeshi infants; 

interval marginally nourished 

mothers 

Measured milk and nutrient intake 

based on nutritional status; not 

corrected for insensible water loss 

Hofvander et al., 

1982 

50 25 breast-fed and 25 Studied 24-hour period at 1, Swedish infants 

formula-fed infants 2, and 3 months 

Estimated breast milk and formula 

intake; no corrections for insensible 

water loss among breast-fed infants; 

estimated frequency of feeding 

Köhler et al., 1984 59 25 fully breast-fed and 34 Studied over 48-hour Swedish infants 

formula-fed infants periods at 6, 14, 22, and 26 

weeks of age 

Estimated breast milk and formula 

intake based on nutritional status; 

no corrections for insensible water 

loss among breast-fed infants 

Maxwell and 

Burmaster, 1993 

1,113 Population of 1,113 NA NA 

breast-fed infants based 

on a hypothetical 

population of 5,000 

breast-fed and bottle-fed 

Simulated distribution of breast milk 

intake based on data from Dewey 

1991a; estimated percent of breastfed infants under 12 months of age 

infants 

NAS, 1991 NA Breast-fed infants NA NA Summarizes current 

state-of-knowledge on breast milk 

volume, composition and 

breast-feeding populations 
Table 14-14. Confidence in Breast Milk Intake Recommendations 

Considerations Rationale Rating 

Study Elements 

C	 Level of peer review All key studies are from peer review literature. High 

C	 Accessibility Papers are widely available from peer review journals. High 

C	 Reproducibility Methodology used was clearly presented. High 

C	 Focus on factor of interest The focus of the studies was on estimating breast milk intake. High 

C	 Data pertinent to U.S. Subpopulations of the U.S. were the focus of all the key studies. High 

C	 Primary data All the studies were based on primary data. High 

C	 Currency Studies were conducted between 1980-1986. Although incidence of Medium 

breast feeding may change with time, breast milk intake among 

breastfed infants may not. 

C	 Adequacy of data collection period Infants were not studied long enough to fully characterize day to day Medium 

variability. 

C	 Validity of approach Methodology uses changes in body weight as a surrogate for total Medium 

ingestion. This is the best methodology there is to estimate breast milk 

ingestion. Mothers were instructed in the use of infant scales to 

minimize measurement errors. Three out of the 5 studies corrected 

data for insensible water loss. 

C	 Study size The sample sizes used in the key studies were fairly small (range 13­

73). 

C	 Representativeness of the Population is not representative of the U.S.; only mid-upper class, well Low 

population nourished mothers were studied. Socioeconomic factors may affect 

the incidence of breastfeeding. Mother’s nourishment may affect milk 

production. 

C	 Characterization of variability Not very well characterized. Infants under 1 month not captured, Low 

mothers committed to breast feeding over 1 year not captured. 

C	 Lack of bias in study design (high Bias in the studies was not characterized. Three out of 5 studies Low 

rating is desirable) corrected for insensible water loss. Not correcting for insensible water 

loss may underestimate intake. Mothers selected for the studies were 

volunteers; therefore response rate does not apply. Population studied 

may introduce some bias in the results (see above). 

C	 Measurement error All mothers were well educated and trained in the use of the scale Medium 

which helped minimize measurement error. 

Other Elements 

C	 Number of studies There are 5 key studies. High 

C	 Agreement between researchers There is good agreement among researchers. High 

Overall Rating Studies were well designed. Results were consistent. Sample size Medium 

was fairly low and not representative of U.S. population or population of 

nursing mothers. Variability cannot be characterized due to limitations 

in data collection period. 
Table 14-15. Breast Milk Intake Rates Derived From Key Studies 

Upper Percentile (mL/day) 

Mean (mL/day) N (mean plus 2 standard Reference 

deviations) 

Age: 1 Month 

600 11 918 Pao et al., 1980 

729 37 981 Butte et al., 1984 

747 13 1,095 Neville et al., 1988 

673 16 1,057 Dewey and Lönnerdal, 1983 

weighted avg = 702 1,007a 

Age: 3 Months 

833 2 --­ Pao et al., 1980 

702 37 923 Butte et al., 1984 

712 12 934 Neville et al., 1988 

782 16 1,126 Dewey and Lönnerdal, 1983 

788 73 1,046 Dewey et al., 1991b 

weighted avg = 759 1,025a 

Age: 6 Months 

682 1 --­ Pao et al., 1980 

744 13 978 Neville et al., 1988 

896 11 1,140 Dewey and Lönnerdal, 1983 

747 60 1,079 Dewey et al., 1991b 

weighted avg = 765 1,059a 

Age: 9 Months 

600 12 1,027 Neville et al., 1988 

627 50 1,049 Dewey et al., 1991b 

avg = 622 1,038 

Age: 12 Months 

391 9 877 Neville et al., 1988 

435 42 923 Dewey et al., 1991a; 1991b 

weighted avg = 427 900 

12-MONTH TIME WEIGHTED 

AVERAGE Range 900-1,059 

(middle of the range 980)

688 

Middle of the range. a 
Table 14-16. Summary of Recommended Breast Milk and Lipid Intake Rates 

Age Mean Upper Percentile 

Breast Milk 

1-6 Months 742 mL/day 1,033 mL/day 

12 Month Average 688 mL/day 980 mL/day 

Lipidsa 

<1 Year 26.0 mL/day 40.4 mL/day

a The recommended value for the lipid content of breastmilk is 4.0 percent. 
Table 15-1. Time Use Table Locator Guide 

Percentile Basis Population Application Study Table 

Averages Activity Children 3-17 yrs National Timmer et al., 1985 15-2 

Distribution Activity Children and Teens National Timmer et al., 1985 15-3 

Distribution Showering Adults Foreign-Australia James and Knuiman, 1987 15-4 

Tsang and Klepeis, 1996 15-24 

Averages Activity Adults 18-64 yrs National Robinson and Thomas, 1991 15-5 

Averages Activity Adults 18-64 yrs Regional-CA Robinson and Thomas, 1991 15-5 

Averages Microenvironment Adults 18-64 yrs National/Regional-CA Robinson and Thomas, 1991 15-6 

Averages Microenvironment Children and Adult Regional-California Robinson and Thomas, 1991 15-7 to 15-10 

Averages Microenvironment Children and Adults National Robinson and Thomas, 1991 15-7 to 15-10 

Averages Activity Infants and Children Regional-California Wiley et al., 1991 15-11 

Distribution Activity Infants and Children Regional-California Wiley et al., 1991 15-12 

Averages Activity by season Infants and Children Regional-California Wiley et al., 1991 15-13 

Averages Microenvironment Infants and Children Regional-California Wiley et al., 1991 15-14 

Distribution Microenvironment Infant and Children Regional-California Wiley et al., 1991 15-15 

Averages Microenvironment by Infants and Children Regional-California Wiley et al., 1991 15-16 

season 

Distribution Microenvironment near Infant and Children Regional-California Wiley et al., 1991 15-17 

pollutant 

Averages Bathing and swimming Adults Regional-National USEPA, 1992 15-18 

Tsang and Klepeis, 1996 15-22, 15-63 

Average Activity by employment Adults National Robinson, 1977 15-147 

Averages Occupational Tenure Teens and Adults National Carey, 1988 15-157 

by race and gender 

Averages Occupational Tenure Teens and Adults National Carey, 1988 15-158 

by employment and 

gender 

Distribution Occupational Tenure Teens and Adults National Carey, 1988 15-159 

by employment 

Distribution Occupational Mobility Teens and Adults National Carey, 1990 15-160 

by age 

Distribution Population Mobility by All ages National Census, 1993 Figure 15-1 

locale 

Averages Residence Time by All ages National Israeli and Nelson, 1992 15-161 

region, setting 

Distribution Residence Time by All ages National Israeli and Nelson, 1992 15-162 

region, setting 

Distribution Residence Time by All ages National Census, 1993 15-163 

year moved in 

Distribution Residence Time by All ages National Census, 1993 15-164 

years in current home 

Distribution Residence Time by All ages National Johnson and Capel, 1992 15-165 

gender 

Distribution Residence Time by age All ages National Johnson and Capel, 1992 15-166 

Distribution Residence Time by All ages National NAR, 1993 15-167 

years in previous house 

Distribution Residence Time by All ages National NAR, 1993 15-168 

tenure in previous 

home 

Distribution Relocation Distance All ages National NAR, 1993 15-169 
-- -- -- --

Table 15-2. Mean Time Spent (minutes) Performing Major Activities Grouped by Age, Sex and Type of Day 

Activity Age (3-11 years) Age (12-17 years) 

Duration of Time (mins/day) Duration of Time (mins/day) 

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 a 

Percent of Time Accounted 94% 92% 93% 89% 93% 92% 88% 89% 

for by Activities Above 

a NA = Unknown 

Source: Timmer et al., 1985. 
Table 15-3. Mean Time Spent (minutes) in Major Activities Grouped by Type of Day for Five Different Age Groups 

Time Duration (mins) Significant 

Effectsa 

Weekday Weekend 

Age (years) 3-5 6-8 9-11 12-14 15-17 3-5 6-8 9-11 12-14 15-17 

Activities 

Market Work -­ 14 8 14 28 

Personal Care 41 49 40 56 60 

Household Work 14 15 18 27 34 

Eating 82 81 73 69 67 

Sleeping 630 595 548 473 499 

School 137 292 315 344 314 

Studying 2 8 29 33 33 

Church 4 9 9 9 3 

Visiting 14 15 10 21 20 

Sports 5 24 21 40 46 

Outdoor activities 4 9 8 7 11 

Hobbies 0 2 2 4 6 

Art Activities 5 4 3 3 12 

Other Passive Leisure 9 1 2 6 4 

Playing 218 111 65 31 14 

TV 111 99 146 142 108 

Reading 5 5 9 10 12 

Being read to 2 2 0 0 0 

NA 30 14 23 25 7 

-­ 4 10 29 48 

47 45 44 60 51 A,S,AxS (F>M

17 27 51 72 60 A,S, AxS (F>M

81 80 78 68 65 A 

634 641 596 604 562 A 

-­ -­ -­ -­ -­

1 2 12 15 30 A 

55 56 53 32 37 A 

10 8 13 22 56 A (Weekend 

only) 

3 30 42 51 37 A,S (M>F) 

8 23 39 25 26 

1 5 3 8 3 

4 4 4 7 10 

6 10 7 10 18 A 

267 180 92 35 21 A,S (M>F) 

122 136 185 169 157 A,S, AxS (M>F

4 9 10 10 18 A 

3 2 0 0 0 A 

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. 

Source: Timmer et al., 1985. 
Table 15-4. Cumulative Frequency Distribution of Average

Shower Duration for 2,550 Households

Shower duration (minutes) Cumulative frequency (percentage)

1 0.2

2 0.8

3 3.1

4 9.6

5 22.1

6 37.5

7 51.6

8 62.5

9 72.0

10 79.4

11 84.5

12 88.4

13 90.6

14 92.3

15 93.7

16 94.9

17 95.7

18 96.7

19 97.6

20 98.0

<20 100.0

Source: Adapted from James and Knuiman, 1987.
Table 15-5. Mean Time Spent (minutes/day) in Ten Major Activity Categories Grouped by Total Sample 

and Gender for the CARB and National Studies (age 18-64 years) 

Time Duration (mins/day) 

Activity Category Activity CARB National CARB National a 

Codes (1987-88) (1985) (1987-88) (1985) b 

Total Sample Men Women Men Women 

n = 1,359 n = 1,980 n = 639 n = 720 n = 921 n = 1,059 c 

Paid Work 00-09 273 252 346 200 323 190 

Household Work 10-19 102 118 68 137 79 155 

Child Care 20-29 23 25 12 36 11 43 

Obtaining Goods and 30-39 61 55 48 73 44 62 

Services 

Personal Needs and 40-49 642 642 630 655 636 645 

Care 

Education and Training 50-59 22 19 25 20 21 16 

Organizational Activities 60-69 12 17 11 13 12 20 

Entertainment/Social 70-79 60 62 57 55 64 62 

Activities 

Recreation 80-89 43 50 53 31 69 43 

Communication 90-99 202 196 192 214 197 194 

a,b Time use for components of activity categories and codes are shown in Appendix Table 15A-6. 

c n = total diary days. 

Source: Robinson and Thomas, 1991 
Table 15-6. Total Mean Time Spent at Three Major Locations Grouped by Total Sample and Gender 

for the CARB and National Study (ages 18-64 years) 

Location Code CARB National CARB National a b 

(1987-88) (1985) (1987-88) (1985) 

Total Sample Men Women Men Women 

n = 1359 n = 1980 n = 39 n = 720 n = 921 n = 1059 c c c c c c 

At Home WC01-13 892 954 822 963 886 1022 

Away From Home WC21-40 430 384 487 371 445 324 

Travel WC51-61 116 94 130 102 101 87 

Not Ascertained WC99 2 8 1 4 8 7 

Total Time 1440 1440 1440 1440 1440 1440 

a,b Time use data for the 44 components of location and location codes are presented in Appendix Table 15A-7. 

c n = total diary days. 

Source: Robinson and Thomas, 1991. 
c 

Table 15-7. Mean Time Spent at Three Locations for both CARB and 

National Studies (ages 12 years and older) 

Mean duration (mins/day) 

Location Category CARB National 

(n = 1762)b S.E.a (n = 2762)b S.E. 

Indoor 1255c 28 1279c 21 

Outdoor 86d 5 74d 4 

In-Vehicle 98d 4 87d 2 

Total Time Spent 1440 1440 

a S.E. = Standard Error of Mean b Weighted Number - National sample population was weighted to obtain a ratio of 46.5 males and 53.5 females,

in equal proportion for each day of the week, and for each quarter of the year.

Difference between the mean values for the CARB and national studies is not statistically significant. d Difference between the mean values for the CARB and national studies is statistically significant at the 0.05 level. 

Source: Robinson and Thomas, 1991. 
Table 15-8. Mean Time Spent (minutes/day) in Various Microenvironments Grouped by Total Population and Gender (12 years and over) in the National and CARB Data 

National Data 

Mean Duration (mins/day) (standard error)a 

N = 1284b "Doer"c N = 1478b "Doer" N = 2762b "Doer" 

Microenvironment Men Men Women Women Total Total 

Autoplaces 5 (1) 90 1 (0) 35 3 (0) 66 

Restaurant/bar 22 (2) 73 20 (2) 79 21 (1) 77 

In-vehicle 92 (3) 99 82 (3) 94 87 (2) 97 

In-Vehicle/other 1 (1) 166 1 (0) 69 1 (0) 91 

Physical/outdoors 24 (3) 139 11 (2) 101 17 (2) 135 

Physical/indoors 11 (1) 84 6 (1) 57 8 (1) 74 

Work/study-residence 17 (2) 153 15 (2) 150 16 (1) 142 

Work/study-other 221 (10) 429 142 (7) 384 179 (6) 390 

Cooking 14 (1) 35 52 (2) 67 34 (1) 57 

Other activities/kitchen 54 (3) 69 90 (4) 102 73 (2) 88 

Chores/child 88 (3) 89 153 (5) 154 123 93) 124 

Shop/errand 23 (2) 56 38 (2) 74 31 (1) 67 

Other/outdoors 70 (6) 131 43 (4) 97 56 (4) 120 

Social/cultural 71 (4) 118 75 (4) 110 73 (3) 118 

Leisure-eat/indoors 235 (8) 241 215 (7) 224 224 (5) 232 

Sleep/indoors 491 (14) 492 496 (11) 497 494 (9) 495 

CARB Data 

Mean Duration (mins/day) (standard error)a 

N = 867b "Doer"c N = 895b "Doer" N = 1762b "Doer" 

Microenvironment Men Men Women Women Total Total 

Autoplaces 31 (8) 142 9 (2) 50 20 (4) 108 

Restaurant/bar 45 (4) 106 28 (3) 86 36 (3) 102 

In-vehicle 105 (7) 119 85 (4) 100 95 (4) 111 

In-Vehicle/other 4 (1) 79 3 (2) 106 3 (1) 94 

Physical/outdoors 25 (3) 131 8 (1) 86 17 (2) 107 

Physical/indoors 8 (1) 63 5 (1) 70 7 (1) 68 

Work/study-residence 14 (3) 126 11 (2) 120 13 (2) 131 

Work/study-other 213 (14) 398 156 (11) 383 184 (9) 450 

Cooking 12 (1) 43 42 (2) 65 27 (1) 55 

Other activities/kitchen 38 (3) 65 60 (4) 82 49 (2) 74 

Chores/child 66 (4) 75 134 (6) 140 100 (4) 109 

Shop/errand 21 (3) 61 41 (3) 78 31 (2) 70 

Other/outdoors 95 (9) 153 44 (4) 82 69 (5) 117 

Social/cultural 47 (4) 112 59 (5) 114 53 (3) 112 

Leisure-eat/indoors 223 (10) 240 251 (10) 263 237 (7) 250 

Sleep/indoors 492 (17) 499 504 (15) 506 498 (12) 501 

a Standard error of the mean 

b Weighted number Doer = Respondents who reported participating in each activity/location spent in microenvironments. Source: Robinson and Thomas, 1991. 

c 
Table 15-9. Mean Time Spent (minutes/day) in Various Microenvironments by Type

 of Day for the California and National Surveys 

(sample population ages 12 years and older) 

Weekday Mean Duration (standard error) a Mean Duration for "Doer"b 

Microenvironment (mins/day) (mins/day) 

CARB NAT c c (n=1259) (n=1973) CARB NAT 

1 Autoplaces 21 (5) 

2 Restaurant/Bar 29 (3) 

3 In-Vehicle/Internal Combustion 90 (5) 

4 In-Vehicle/Other 3 (1) 

5 Physical/Outdoors 14 (2) 

6 Physical/Indoors 7 (1) 

7 Work/Study-Residence 14 (2) 

8 Work/Study-Other 228 (11) 

9 Cooking 27 (2) 

10 Other Activities/Kitchen 51 (3) 

11 Chores/Child 99 (5) 

12 Shop/Errand 30 (2) 

13 Other/Outdoors 67 (6) 

14 Social/Cultural 42 (3) 

15 Leisure-Eat/Indoors 230 (9) 

16 Sleep/Indoors 490 (14) 

3 (1) 108 73

20 (2) 83 73

85 (2) 104 95

1 (0) 71 116

15 (2) 106 118

8 (1) 64 68

16 (2) 116 147

225 (8) 401 415

35 (2) 58 57 

73 (3) 76 87 

124 (4) 108 125 

30 (2) 67 63 

51 (4) 117 107 

62 (3) 99 101 

211 (6) 244 218 

481 (10) 495 483 

Weekend a Mean Duration (standard error) Mean Duration for "Doer"b 

Microenvironment (mins/day) (mins/day) 

CARB NAT c c (n=503) (n=789) CARB NAT 

1 Autoplaces 19 (4) 

2 Restaurant/Bar 55 (6) 

3 In-Vehicle/Internal Combustion 108 (8) 

4 In-Vehicle/Other 5 (3) 

5 Physical/Outdoors 23 (3) 

6 Physical/Indoors 7 (1) 

7 Work/Study-Residence 10 (2) 

8 Work/Study-Other 74 (11) 

9 Cooking 27 (2) 

10 Other Activities/Kitchen 44 (3) 

11 Chores/Child 103 (7) 

12 Shop/Errand 35 (4) 

13 Other/Outdoors 74 (7) 

14 Social/Cultural 79 (7) 

15 Leisure-Eat/Indoors 256 (12) 

16 Sleep/Indoors 520 (20) 

3 (1) 82 62

23 (2) 127 84

91 (6) 125 100

0 (0) 130 30

23 (4) 134 132

9 (2) 72 80

15 (3) 155 165

64 (6) 328 361

34 (2) 60 55 

73 (4) 71 90 

120 (5) 114 121 

35 (3) 81 75 

67 (7) 126 132 

99 (6) 140 141 

257 (11) 273 268 

525 (17) 521 525

a

 Standard Error of Mean

b

 Doer = Respondent who reported participating in each activity/location spent in microenvironments.

c Weighted Number

Source: Robinson and Thomas, 1991.
Table 15-10. Mean Time Spent (minutes/day) in Various Microenvironments by Age Groups for the National and California Surveys 

National Data 

Microenvironment Mean Duration (Standard Error)a 

Age 12-17 Age 18-24 Age 24-44 Age 45-64 Age 65+ 

years 

N=340b "Doer"c years N=340 "Doer" 

years 

N=340 "Doer" 

years 

N=340 "Doer" 

years 

N=340 "Doer" 

Autoplaces 2 (1) 73 7 (2) 137 2 (1) 43 4 (1) 73 4 (2) 57 

Restaurant/bar 9 (2) 60 28 (3) 70 25 (3) 86 19 (2) 67 20 (5) 74 

In-vehicle/internal 

combustion 

79 (7) 88 103 (8) 109 94 (4) 101 82 (5) 91 62 (5) 80 

In-vehicle/other 0 (0) 12 1 (1) 160 1 (0) 80 1 (1) 198 1 (1) 277 

Physical/outdoors 32 (8) 130 17 (4) 110 19 (4) 164 7 (1) 79 15 (4) 81 

Physical/indoors 15 (3) 87 8 (2) 76 7 (1) 71 7 (2) 77 7 (1) 51 

Work/studyresidence 22 (4) 82 19 (6) 185 16 (2) 181 9 (2) 169 5 (3) 297 

Work/study-other 159 (14) 354 207 (20) 391 220 (11) 422 180 (13) 429 35 (6) 341 

Cooking 11 (3) 40 18 (2) 39 38 (2) 57 43 (3) 64 50 (5) 65 

Other 

activities/kitchen 53 (4) 64 42 (3) 55 70 (4) 86 90 (6) 101 108 (9) 119 

Chores/child 91 (7) 92 124 (9) 125 133 (6) 134 121 (6) 122 119 (7) 121 

Shop/errands 26 (4) 68 31 (4) 65 33 (2) 66 33 (3) 67 35 (5) 69 

Other/outdoors 70 (13) 129 34 (4) 84 48 (6) 105 60 (7) 118 82 (13) 140 

Social/cultural 87 (10) 120 100 (12) 141 56 (3) 94 73 (6) 116 85 (8) 122 

Leisureeat/indoors 237 (16) 242 181 (11) 189 200 (8) 208 238 (11) 244 303 (20) 312 

Sleep/indoors 548 (31) 551 511 (26) 512 479 (14) 480 472 (15) 472 507 (26) 509 
Table 15-10. Mean Time Spent (minutes/day) in Various Microenvironments by Age Groups (continued) 

CARB Data a Microenvironment Mean Duration (Standard Error) 

Age 12-17 Age 18-24 Age 24-44 Age 45-64 Age 65+ 

years years years years years c N=183b "Doer" N=250 "Doer" N=749 "Doer" N=406 "Doer" N=158 "Doer" 

Autoplaces 16 (8) 124 16 (4)

Restaurant/bar 16 (4) 44 40 (8)

In-vehicle/internal 78 (11) 89 111 (13)

combustion

In-vehicle/other 1 (0) 19 3 (1)

Physical/outdoors 32 (7) 110 13 (3)

Physical/indoors 20 (4) 65 5 (2)

Work/study- 25 (5) 76 30 (11)

residence

Work/study-other 196 (30) 339 201 (24)

Cooking 3 (1) 19 14 (2)

Other 31 (4) 51 31 (5) activities/kitchen

Chores/child 72 (11) 77 79 (8)

Shop/errands 14 (3) 50 35 (7)

Other/outdoors 58 (8) 78 80 (15)

Social/cultural 63 (14) 109 65 (10)

Leisure-eat/indoors 260 (27) 270 211 (19)

Sleep/indoors 557 (44) 560 506 (30)

71 25 (9) 114 20 (5) 94 9 (2) 53 

98 44 (5) 116 31 (4) 82 25 (7) 99 

122 98 (5) 111 100 (11) 117 63 (8) 89 

60 5 (2) 143 2 (1) 56 2 (1) 53 

88 17 (3) 128 14 (3) 123 15 (4) 104 

77 6 (1) 61 5 (1) 77 3 (1) 48 

161 7 (2) 137 10 (3) 139 5 (3) 195 

344 215 (14) 410 173 (20) 429 30 (11) 336 

40 32 (2) 59 31 (3) 68 41 (7) 69 

55 43 (3) 65 62 (6) 91 97 (14) 119 

85 110 (6) 119 99 (8) 109 123 (15) 141 

71 33 (4) 71 32 (3) 77 35 (5) 76 

130 68 (8) 127 76 (12) 134 55 (7) 101 

110 50 (5) 122 50 (5) 107 49 (7) 114 

234 202 (9) 215 248 (15) 261 386 (34) 394 

510 487 (17) 491 485 (23) 491 502 (31) 502 

a Standard error. b All N’s are weighted number. c Doer = Respondents who reported participating in each activity/location spent in microenvironments. Source: Robinson and Thomas, 1991. 
Table 15-11. Mean Time (minutes/day) Children Spent in Ten Major Activity Categories for All Respondents 

Activity Category (mins/day) Doing (mins/day) (mins/day) (mins/day) (code) 

Mean Duration Duration Duration Detailed Activity with 

Duration % for Doers for Doer for Doers Highest Avg. Minutes 

Mean Median Maximum 

b 

Work-related 10 25 39 30 405 Eating at work/school/daycare (06

a 

Household 53 86 61 40 602 Travel to household (199) 

Childcare < 1 < 1 83 30 290 Other child care (27) 

Goods/Services 21 26 81 60 450 Errands (38) 

Personal Needs and Care 794 100 794 770 1440 Night sleep (45) c 

Education 110 35 316 335 790 School classes (50) d 

Organizational Activities 4 4 111 105 435 Attend meetings (60) 

Entertain/Social 15 17 87 60 490 Visiting with others (75) 

Recreation 239 92 260 240 835 Games (87) 

Communication/Passive 192 93 205 180 898 TV use (91) 

Leisure 

Don't know/Not coded 2 4 41 15 600 -­

All Activities 1441 e

a

 Includes eating at school or daycare, an activity not grouped under the "education activities" (codes 50-59, 549).

b

 "Doers" indicate the respondents who reported participating in each activity category. 

c

 Personal care includes night sleepand daytime naps, eating, travel for personal care.

d

 Education includes student and other classes, homework, library, travel for education. 

e Column total may not sum to 1440 due to rounding error 

Source: Wiley et al., 1991. 
Table 15-12. Mean Time Children Spent in Ten Major Activity Categories Grouped by Age and Gender 

Mean Duration (minutes/day) 

Activity 

Category 

Boys 

All 

Girls 

All 

0-2 yrs 3-5 yrs 6-8 yrs 9-11 yrs Ages 0-2 yrs 3-5 yrs 6-8 yrs 9-11 yrs Ages 

Work-related 4 9 14 12 10 5 12 11 10 10 

Household 33 45 55 65 48 58 44 51 76 57 

Childcare 0 0 0 1 <1 0 0 0 4 1 

Goods/Services 20 22 19 14 19 22 25 23 22 23 

Personal Needs and 914 799 736 690 792 906 816 766 701 797 

Carea 

Educationb 60 67 171 138 106 41 95 150 176 115 

Organizational Activities 1 3 7 6 4 6 1 4 6 4 

Entertainment/Social 3 15 5 34 13 5 16 9 36 17 

Recreation 217 311 236 229 250 223 255 238 194 228 

Communication/Passive

Leisure 

187 166 195 250 197 171 173 189 213 186 

Don't know/Not coded 1 4 1 1 2 3 1 <1 3 2 

All Activitiesc 1440 1441 1439 1440 1442 1440 1438 1441 1441 1440 

Sample Sizes

Unweighted N's

172 151 145 156 624 141 151 124 160 576 

a

 Personal needs and care includes night sleep and daytime naps, eating, travel for personal care.

b

 Education includes student and other classes, homework, library, travel for education. 

The column totals may differ from 1440 due to rounding error. C 

Source: Wiley et al., 1991. 
c 

Table 15-13. Mean Time Children Spent in Ten Major Activity Categories Grouped by Seasons and Regions 

Mean Duration (minutes/day) 

Activity Category Season Region of California 

Winter 

(Jan-Mar) Spring (Apr-June) 

Summer 

(July-Sept) 

Fall 

(Oct-Dec) 

All 

Seasons 

So. 

Coast Bay Area 

Rest of 

State 

All 

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 

Carea 

Educationb 124 137 49 131 110 109 115 109 110 

Organizational 

Activities 

3 5 5 3 4 2 6 6 4 

Entertainment/Social 14 12 12 22 15 17 10 16 15 

Recreation 221 243 282 211 239 230 241 249 239 

Communication/Passiv 

e Leisure 

203 180 189 195 192 206 190 175 192 

Don't know/Not coded <1 2 3 <1 2 1 1 3 2 

All Activitiesc 1442 1439 1441 1441 1441 1440 1442 1439 1441 

Sample Sizes 318 204 407 271 1200 224 263 713 1200 

(Unweighted)

a Personal needs and care includes night sleep and daytime naps, eating, travel for personal care. B Education includes student and other classes, homework, library, travel for education.

The column totals may not be equal to 1440 due to rounding error.

Source: Wiley et al., 1991. 
Table 15-14. Mean Time Children Spent in Six Major Location Categories for All Respondents (minutes/day) 

Location Category Duration % Duration Duration Duration for Detailed Location with Highest 

Mean Mean Median Maximum 

(mins) Doing for Doers for Doers Doers Avg. Time (mins) (mins) (mins) 

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, 24 35 69 50 475 Shopping mall Shopping Places 

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 

Source: Wiley et al., 1991. 
Table 15-15. Mean Time Children Spent in Six Location Categories Grouped by Age and Gender 

Mean Duration (minutes/day) 

Boys Girls 

Location Category All All 

0-2 yrs 3-5 yrs 6-8 yrs 9-11 yrs Boys 0-2 yrs 3-5 yrs 6-8 yrs 9-11 yrs Girls 

Home 1,157 1,134 1,044 1,020 1,094 1,151 1,099 1,021 968 1,061 

School/Childcare 86 88 144 120 108 59 102 133 149 111 

Friend's/Other's House 67 73 77 109 80 56 47 125 102 80 

Stores, Restaurants, 21 25 22 15 21 23 35 27 26 28 

Shopping Places 

In-transit 54 62 61 62 59 76 88 53 93 79 

Other Locations 54 58 92 114 77 73 68 81 102 81 

Don't Know/Not Coded <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 

All Locationsa 1,439 1,440 1,439 1,440 1,439 1,438 1,440 1,440 1,440 1,440 

Sample Sizes 172 151 145 156 624 141 151 124 160 576 

(Unweighted)

a The column totals may not sum to 1,440 due to rounding error. 

Source: Wiley et al., 1991. 
Table 15-16. Mean Time Children Spent in Six Location Categories Grouped by Season and Region 

Mean Duration (minutes/day) 

Season Region of California 

Location Category Winter Spring Summer Fall All So. Bay Rest of Al

(Jan-Mar) (Apr-June) (July-Sept) (Oct-Dec) Seasons Coast Area State Regio

Home 1,091 1,042 1,097 1,081 1,078 1,078 1,078 1,078 1,0

School/Childcare 119 141 52 124 109 113 103 108 1

Friend's/Other's 69 75 108 69 80 73 86 86 

House 

Stores, Restaurants, 22 21 30 24 24 26 23 23 

Shopping Places 

In-transit 75 75 60 65 69 71 73 63 

Other Locations 63 85 93 76 79 79 76 81 

Don't Know/Not <1 <1 <1 <1 <1 <1 <1 <1 

Coded 

a All Locations 1,439 1,439 1,440 1,439 1,439 1,439 1,440 1,440 1,4

Sample Sizes 318 204 407 271 1,200 224 263 713 1,2

(Unweighted N's)

a The column totals may not sum to 1,440 due to rounding error. 

Source: Wiley et al., 1991. 
Table 15-17. Mean Time Children Spent in Proximity to Three Potential Exposures Grouped by All Respondents, Age, and Gender 

Mean Duration (minutes/day) 

Girls Potential Exposures Boys 

All All All 

Children 0-2 yrs 3-5 yrs 6-8 yrs 9-11 yrs Boys 0-2 yrs 3-5 yrs 6-8 yrs 9-11 yrs Girls 

Tobacco Smoke 77 115 75 66 66 82 77 68 71 74 73 

Gasoline Fumes 2 2 1 1 4 2 1 1 3 1 1 

Gas Oven Fumes 11 10 15 12 11 12 12 10 10 7 10 

Sample Sizes a (Unweighted N's) 1,166 168 148 144 150 610 140 147 122 147 556 

a Respondents with missing data were excluded. 

Source: Wiley et al., 1991. 
Table 15-18. Range of Recommended Defaults for Dermal Exposure Factors 

Water Contact Soil Contact 

Bathing Swimming 

Central Upper Central Upper Central Upper 

Event time and 10 min/event 15 min/event 0.5 hr/event 1.0 hr/event 40 events/yr 350 events/yr 

frequencya 1 event/day 1 event/day 1 event/day 1 event/day 

350 days/yr 350 days/yr 5 days/yr 150 days/yr 

Exposure 9 years 30 years 9 years 30 years 9 years 30 years 

duration 

a Bathing event time is presented to be representative of baths as well as showers. 

Source: U.S. EPA 1992. 
Table 15-19. Number of Times Taking a Shower at Specified Daily Frequencies by the Number of Respondents 

TImes/Day 

Total N 0 1 2 3 4 5 8 10 11:1-0+ DK 

Overall 3594 2 2747 802 30 1 1 1 1 4 5 

Gender 

Male 1720 * 1259 436 21 1 * * * 1 2 

Female 1872 2 1486 366 9 * 1 1 1 3 3 

Refused 2 * 2 * * * * * * * * 

Age (years) * 64 * 46 17 * * * * * * 1 

1-4 41 * 30 9 1 * * * * * 1 

5-11 140 * 112 26 1 * * * * * 1 

12-17 270 * 199 65 6 * * * * * * 

18-64 2650 1 1983 636 21 1 1 1 1 3 2 

> 64 429 1 377 49 1 * * * * 1 * 

Race 

White 2911 2 2323 562 17 * 1 * * 4 2 

Black 349 * 199 140 7 1 * 1 * * 1 

Asian 64 * 49 14 1 * * * * * * 

Some Others 65 * 40 23 2 * * * * * * 

Hispanic 162 * 103 56 2 * * * 1 * * 

Refused 43 * 33 7 1 * * * * * 2 

Hispanic No 3269 2 2521 711 24 1 1 1 * 4 4 

Yes 277 * 190 81 5 * * * 1 * * 

DK 17 * 13 4 * * * * * * * 

Refused 31 * 23 6 1 * * * * * 1 

Employment * 439 * 330 99 8 * * * * * 2 

Full Time 1838 1 1361 454 17 * * * 1 2 2 

Part Time 328 1 261 65 * * 1 * * * * 

Not Employed 967 * 780 177 5 1 * 1 * 2 1 

Refused 22 * 15 7 * * * * * * * 

Education 

* 515 * 382 121 9 * * * * * 3 

< High School 297 * 240 54 2 * * * * 1 * 

High School Graduate 1042 1 789 243 5 * 1 1 * 1 1 

< College 772 1 589 176 4 * * * 1 * 1 

College Graduate 576 * 434 133 7 1 * * * 1 * 

Post Graduate 392 * 313 75 3 * * * * 1 * 

Census Region Northeast 828 * 622 196 7 * * * * * 3 

Midwest 756 * 621 131 3 * * * * * 1 

South 1246 1 893 334 14 1 * * * 3 * 

West 764 1 611 141 6 * 1 1 1 1 1 

Day of Week Weekday 2481 * 1889 563 17 1 1 1 1 4 4 

Weekend 1113 2 858 239 13 * * * * * 1 

Season 

Winter 941 * 732 198 9 * * * * 1 1 

Spring 889 * 674 205 7 * * * 1 * 2 

Summer 1003 * 735 254 10 1 * * * 2 1 

Fall 761 2 606 145 4 * 1 1 * 1 1 

Asthma 

No 3312 2 2543 730 25 1 1 1 1 4 4 

Yes 261 * 189 67 5 * * * * * * 

DK 21 * 15 5 * * * * * * 1 

Angina No 3481 1 2653 786 29 1 1 1 1 4 4 

Yes 91 1 77 12 1 * * * * * * 

DK 22 * 17 4 * * * * * * 1 

Bronchitis/Emphysema No 3419 2 2620 758 27 1 1 1 1 4 4 

Yes 154 * 112 39 3 * * * * * * 

DK 21 * 15 5 * * * * * * 1 

Note: * Signifies missing data; Dk= don't know; N = sample size.

Source: Tsang and Klepeis,1996 
Table 15-20. Times (minutes) Spent Taking Showers by the Number of Respondents 

Minutes/Shower

Total N 

*-* 0-10 10-20 20-30 30-40 40-50 50-60 60-61 

Overall 3594 47 1640 1348 397 72 52 51 17 

Gender 

Male 1720 13 788 625 213 35 25 14 7 

Female 1872 34 850 693 184 37 27 37 10 

Refused 2 * 2 * * * * * * 

Age

* 64 6 27 23 3 1 * 2 2 

1-4 41 1 13 14 10 1 * 2 * 

5-11 140 1 60 52 18 3 2 4 * 

12-17 270 2 94 104 40 13 9 7 1 

18-64 2650 16 1238 977 288 50 37 33 11 

>64 429 21 208 148 38 4 4 3 3 

Race 

White 2911 38 1406 1070 292 39 31 26 9 

Black 349 5 115 120 58 20 11 16 4 

Asian 64 * 25 25 10 1 2 * 1 

Some Others 65 * 18 29 6 3 4 4 1 

Hispanic 162 1 57 60 25 8 4 5 2 

Refused 43 3 19 14 6 1 * * * 

Hispanic

No 3269 43 1526 1188 352 61 42 44 13 

Yes 277 1 98 109 40 10 8 7 4 

DK 17 * 5 9 1 * 2 * * 

Refused 31 3 11 12 4 1 * * * 

Employment

* 439 4 163 165 66 17 10 12 2 

Full Time 1838 10 875 682 191 32 20 20 8 

Part Time 328 4 160 112 39 4 5 3 1 

Not Employed 967 27 431 355 97 19 16 16 6 

Refused 22 2 11 4 4 * 1 * * 

Education 

* 515 10 190 186 79 21 13 14 2 

< High School 297 8 93 125 51 6 7 6 1 

High School Graduate 1042 12 451 409 108 23 17 16 6 

< College 772 12 377 271 79 14 6 7 6 

College Graduate 576 2 297 211 50 5 5 5 1 

Post Graduate 392 3 232 116 30 3 4 3 1 

Census Region

Northeast 828 7 374 326 79 15 11 12 4 

Midwest 756 11 385 253 70 16 9 9 3 

South 1246 26 490 461 179 35 26 23 6 

West 764 3 391 278 69 6 6 7 4 

Day of Week

Weekday 2481 34 1134 908 279 46 38 32 10 

Weekend 1113 13 506 410 118 26 14 19 7 

Season 

Winter 941 12 421 358 95 18 15 16 6 

Spring 889 14 410 314 93 21 14 18 5 

Summer 1003 11 435 366 128 29 17 12 5 

Fall 761 10 374 280 81 4 6 5 1 

Asthma 

No 3312 38 1526 1222 362 65 44 41 14 

Yes 261 4 108 89 33 7 8 10 2 

DK 21 5 6 7 2 * * * 1 

Angina 3481 

No 91 36 1591 1276 389 70 51 51 17 

Yes 22 7 38 36 8 1 1 * * 

DK 4 11 6 * 1 * * * 

Bronchitis/Emphysema

No 3419 40 1566 1258 375 67 47 50 16 

Yes 154 3 66 54 19 5 5 1 1 

DK 21 4 8 6 3 * * * * 

NOTE: * - Missing data; DK = don’t know; N = sample size; Refused = Refused to answer. A value of 61 for number of minutes

signifies that more than 60 minutes were spent.

Source: Tsang and Klepeis, 1996.
Table 15-21. Number of Minutes Spent Taking a Shower (minutes/shower) 

Percentiles 

Total 

Category Population Group N 1 2 5 10 25 50 75 91 95 98 99 100 

Overall 3547 3 4 5 5 10 15 20 30 35 50 60 61 

Gender Male 1707 3 4 5 5 10 15 20 30 30 45 60 61 

Gender Female 1838 3 4 5 5 10 15 20 30 40 60 60 61 

Age (years) 1-4 40 5 5 5 5 5 10 17.5 30 50 60 60 60 

Age (years) 5-11 139 3 4 5 5 10 15 20 30 40 60 60 60 

Age (years) 12-17 268 5 5 5 7 10 15 25 35 45 60 60 61 

Age (years) 18-64 2634 3 3 5 5 10 15 20 30 30 45 60 61 

Age (years) >64 408 3 3 5 5 10 10 20 30 30 45 60 61 

Race White 2873 3 4 5 5 10 13 20 30 30 45 60 61 

Race Black 344 4 4 5 6 10 20 30 40 60 60 61 61 

Race Asian 64 1 3 4 5 10 15 20 30 40 48 61 61 

Race Some Others 65 3 3 5 10 10 15 30 45 60 60 61 61 

Race Hispanic 161 3 4 5 6 10 15 25 40 45 60 61 61 

Hispanic No 3226 3 4 5 5 10 15 20 30 30 45 60 61 

Hispanic Yes 276 3 4 5 6 10 15 22.5 39 45 60 61 61 

Employment Full Time 1828 3 4 5 5 10 15 20 30 30 45 60 61 

Employment Part Time 324 2 3 5 5 10 12 20 30 30 45 60 60 

Employment Not Employed 940 3 3 5 5 10 15 20 30 40 60 60 61 

Education < High School 289 4 5 5 8 10 15 20 30 40 60 60 61 

Education High School Graduate 1030 2 3 5 5 10 15 20 30 40 60 60 61 

Education < College 760 3 5 5 5 10 12 20 30 30 45 60 61 

Education College Graduate 574 3 3 5 5 10 10 20 25 30 40 60 61 

Education Post Graduate 389 2 3 4 5 7 10 15 25 30 45 60 61 

Census Region Northeast 821 4 5 5 5 10 15 20 30 32 50 60 61 

Census Region Midwest 745 3 4 5 5 10 10 20 30 30 45 60 61 

Census Region South 1220 3 3 5 5 10 15 20 30 40 60 60 61 

Census Region West 761 2 3 5 5 10 10 15 30 30 45 60 61 

Day of Week Weekday 2447 3 4 5 5 10 15 20 30 35 48 60 61 

Day of Week Weekend 1100 3 4 5 5 10 15 20 30 40 60 60 61 

Season Winter 929 3 4 5 5 10 15 20 30 40 60 60 61 

Season Spring 875 3 4 5 5 10 15 20 30 40 60 60 61 

Season Summer 992 2 3 5 5 10 15 20 30 40 45 60 61 

Season Fall 751 3 4 5 5 10 12 20 30 30 40 48 61 

Asthma No 3274 3 4 5 5 10 15 20 30 32 45 60 61 

Asthma Yes 257 3 4 5 5 10 15 20 40 50 60 60 61 

Angina No 3445 3 4 5 5 10 15 20 30 35 50 60 61 

Angina Yes 84 3 4 5 5 10 15 15 30 30 40 45 45 

Bronchitis/Emphysema No 3379 3 4 5 5 10 15 20 30 35 50 60 61 

Bronchitis/Emphysema Yes 151 3 4 5 5 10 15 20 30 40 48 60 61 

NOTE: A value of 61 for number of minutes signifies that more than 60 minutes were spent. N = doer sample size. Percentiles are the 

percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996. 
Table 15-22. Time (minutes) Spent in the Shower Room Immediately After Showering by the Number of Respondents 

Minutes/Shower 

Total N *-* 0-0 0-10 10-20 20-30 30-40 40-50 50-60 61-61 

Overall 3594 61 241 2561 509 138 24 28 27 5 

Gender 

Male 1720 22 113 1316 207 46 5 4 6 1 

Female 1872 39 128 1243 302 92 19 24 21 4 

Refused 2 * * 2 * * * * * * 

Age (years) * 64 6 9 37 7 3 * 1 1 * 

1-4 41 * 5 31 3 1 * 1 * * 

5-11 140 3 9 110 14 3 * * 1 * 

12-17 270 1 17 206 29 10 3 2 1 1 

18-64 2650 31 171 1897 388 99 19 18 23 4 

> 64 429 20 30 280 68 22 2 6 1 * 

Race 

White 2911 39 189 2074 430 110 20 23 21 5 

Black 349 8 23 254 42 17 * 3 2 * 

Asian 64 * 7 45 9 2 * * 1 * 

Some Others 65 3 7 41 6 3 3 1 1 * 

Hispanic 162 6 11 118 19 4 1 1 2 * 

Refused 43 5 4 29 3 2 * * * * 

Hispanic No 3269 48 216 2328 470 130 23 26 23 5 

Yes 277 8 19 200 35 8 1 2 4 * 

DK 17 1 2 11 3 * * * * * 

Refused 31 4 4 22 1 * * * * * 

Employment * 439 4 28 336 48 14 3 4 2 ?* 

Full Time 1838 20 109 1332 267 71 12 11 16 * 

Part Time 328 5 21 223 55 13 4 4 3 * 

Not Employed 967 29 81 655 138 39 5 9 6 5 

Refused 22 3 2 15 1 1 * * * * 

Education 

* 515 11 38 390 51 15 3 4 2 1 

< High School 297 14 18 193 48 16 * 6 1 1 

High School Graduate 1042 17 68 733 160 37 6 7 13 1 

< College 772 11 56 536 118 33 7 4 5 2 

College Graduate 576 3 28 426 86 19 8 3 3 * 

Post Graduate 392 5 33 283 46 18 * 4 3 * 

Census Region Northeast 828 6 61 603 116 20 6 8 8 * 

Midwest 756 19 39 536 118 29 5 3 7 * 

South 1246 26 74 885 171 58 10 15 4 3 

West 764 10 67 537 104 31 3 2 8 2 

Day of Week Weekday 2481 43 165 1784 342 88 20 16 19 4 

Weekend 1113 18 76 777 167 50 4 12 8 1 

Season 

Winter 941 11 50 678 138 36 13 9 4 2 

Spring 889 13 56 636 125 37 4 8 9 1 

Summer 1003 25 92 691 138 39 5 5 7 1 

Fall 761 12 43 556 108 26 2 6 7 1 

Asthma 

No 3312 52 225 2374 465 123 19 24 26 4 

Yes 261 2 14 178 42 15 5 3 1 1 

DK 21 7 2 9 2 * * 1 * * 

Angina No 3481 52 233 2495 486 132 24 27 27 5 

Yes 91 3 5 55 22 5 * 1 * * 

DK 22 6 3 11 1 1 * * * * 

Bronchitis/Emphysema No 3419 53 226 2446 482 131 23 27 26 5 

Yes 154 2 12 104 26 7 1 1 1 * 

DK 21 6 3 11 1 * * * * * 

NOTE: * Signifies missing data. DK= respondents answered don't know. Refused = respondents refused to answer. N = doer 

sample size in specified range of number of minutes spent. A value of 61 for number of minutes signifies that more than 60 minutes

were spent.

Source: Tsang and Klepeis,1996 
Table 15-23. Number of Minutes Spent in the Shower Room Immediately After Showering (minutes/shower) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 3533 0 0 0 1 3 5 10 20 30 40 50 61 

Gender Male 1698 0 0 0 1 3 5 10 15 20 30 30 61 

Gender Female 1833 0 0 0 1 3 5 12 20 30 45 60 61 

Age (years) 1-4 41 0 0 0 0 1 5 10 15 20 45 45 45 

Age (years) 5-11 137 0 0 0 1 2 5 10 15 20 30 30 60 

Age (years) 12-17 2619 0 0 0 1 3 5 10 20 30 40 52 61 

Age (years) 18-64 2619 0 0 0 1 3 5 10 20 30 40 52 61 

Age (years) > 64 409 0 0 0 1 4 5 10 20 30 35 45 60 

Race White 2872 0 0 0 1 3 5 10 20 30 40 50 61 

Race Black 341 0 0 0 1 3 5 10 20 25 30 45 60 

Race Asian 64 0 0 0 0 2 5 10 15 20 30 60 60 

Race Some Others 62 0 0 0 0 3 5 10 30 35 45 52 52 

Race Hispanic 156 0 0 0 1 3 5 10 20 25 40 60 60 

Hispanic No 3221 0 0 0 1 3 5 10 20 30 40 50 61 

Hispanic Yes 269 0 0 0 1 3 5 10 20 25 45 60 60 

Employment Full Time 1818 0 0 0 1 3 5 10 20 30 35 50 60 

Employment Part Time 323 0 0 0 1 3 5 10 20 30 45 50 60 

Employment Not Employed 938 0 0 0 1 3 5 10 20 30 45 60 61 

Education < High School 283 0 0 0 1 3 5 15 20 30 45 45 61 

Education High School Graduate 1025 0 0 0 1 3 5 10 20 30 45 60 61 

Education < College 761 0 0 0 1 3 5 10 20 30 35 50 61 

Education College Graduate 573 0 0 1 1 3 5 10 20 30 35 45 60 

Education Post Graduate 387 0 0 0 1 2 5 10 20 30 30 45 60 

Census Region Northeast 822 0 0 0 1 3 5 10 20 25 40 50 60 

Census Region Midwest 737 0 0 0 1 3 5 10 20 30 35 45 60 

Census Region South 1220 0 0 0 1 3 5 10 20 30 40 45 61 

Census Region West 754 0 0 0 1 2 5 10 20 30 30 60 61 

Day of Week Weekday 2438 0 0 0 1 3 5 10 20 30 40 50 61 

Day of Week Weekend 1095 0 0 0 1 3 5 10 20 30 40 50 61 

Season Winter 930 0 0 0 1 4 5 10 20 30 40 45 61 

Season Spring 876 0 0 0 1 2 5 10 20 30 45 60 61 

Season Summer 978 0 0 0 1 3 5 10 20 30 30 50 61 

Season Fall 749 0 0 0 1 3 5 10 20 25 40 53 61 

Asthma No 3260 0 0 0 1 3 5 10 20 30 38 50 61 

Asthma Yes 259 0 0 0 1 3 5 13 20 30 40 45 61 

Angina No 3429 0 0 0 1 3 5 10 20 30 40 50 61 

Angina Yes 88 0 0 0 2 3 8.5 15 20 30 30 45 45 

Bronchitis/Emphysema No 3366 0 0 0 1 3 5 10 20 30 40 50 61 

Bronchitis/Emphysema Yes 152 0 0 0 1 2.5 5 10 20 30 30 45 60 

NOTE: N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. A value of 61 for 

number of minutes signifies that more than 60 minutes were spent.

Source: Tsang and Klepeis,1996 
Table 15-24. Number of Baths Given or Taken in One Day by Number of Respondents 

Number of Baths/Day 

Total N 1 2 3 4 5 6 7 10 11 15 DK 

Overall 649 459 144 20 9 4 2 1 1 1 3 5 

Gender 

Male 159 117 33 5 1 * 1 1 * * 1 * 

Female 490 342 111 15 8 4 1 * 1 1 2 5 

Age (years)

* 9 8 1 * * * * * * * * * 

18-64 491 322 127 20 9 4 2 1 1 1 2 2 

> 64 149 129 16 * * * * * * * 1 3 

Race 

White 487 364 92 13 7 2 1 * * 1 2 5 

Black 106 68 29 5 1 * 1 1 1 * * * 

Asian 12 5 5 * 1 * * * * * 1 * 

Some Others 12 7 4 1 * * * * * * * * 

Hispanic 26 10 13 1 * 2 * * * * * * 

Refused 6 5 1 * * * * * * * * * 

Hispanic

No 600 430 127 19 9 2 2 1 1 1 3 5 

Yes 40 21 16 1 * 2 * * * * * * 

DK 6 5 1 * * * * * * * * * 

Refused 3 3 * * * * * * * * * * 

Employment

* 1 1 * * * * * * * * * * 

Full Time 283 183 76 12 5 * 2 1 1 1 1 1 

Part Time 76 56 17 1 1 1 * * * * * * 

Not Employed 287 217 51 7 3 3 * * * * 2 4 

Refused 2 2 * * * * * * * * * * 

Education 

* 4 4 * * * * * * * * * * 

< High School 96 66 19 3 2 2 * * * * 1 3 

High School Graduate 235 167 54 8 2 * 1 1 * * * 2 

< College 163 112 38 6 2 2 1 * * 1 1 * 

College Graduate 102 68 28 3 2 * * * 1 * * * 

Post Graduate 49 42 5 * 1 * * * * * 1 * 

Census Region

Northeast 137 100 25 3 4 1 1 * * 1 * 2 

Midwest 151 116 29 4 1 * * * 1 * * * 

South 255 164 70 9 2 3 1 1 * * 2 3 

West 106 79 20 4 2 * * * * * 1 * 

Day of Week

Weekday 415 299 89 10 4 2 2 1 1 1 2 4 

Weekend 234 160 55 10 5 2 * * * * 1 1 

Season 

Winter 178 124 37 10 1 3 * * * * 1 2 

Spring 160 126 27 4 1 * * 1 * * * 1 

Summer 174 112 49 4 3 1 1 * 1 * 2 1 

Fall 137 97 31 2 4 * 1 * * 1 * 1 

Asthma 

No 596 424 129 19 7 4 2 1 1 1 3 5 

Yes 52 34 15 1 2 * * * * * * * 

DK 1 1 * * * * * * * * * * 

Angina

No 620 435 141 19 9 4 2 1 1 1 3 4 

Yes 26 22 2 1 * * * * * * * 1 

DK 3 2 1 * * * * * * * * * 

Bronchitis/Emphysema

No 610 429 137 20 9 4 2 1 1 1 2 4 

Yes 36 27 7 * * * * * * * 1 1 

DK 3 3 * * * * * * * * * * 

NOTE: * Signifies missing data; Dk= respondents answered don't know; N = sample size; Refused = respondents refused to answer. 

Source: Tsang and Klepeis,1996 
Table 15-25. Total Time Spent Taking or Giving a Bath by the Number of Respondents 

Minutes/Bath 

Total N *-* 0-10 10-20 20-30 30-40 40-50 50-60 61-61 

Overall 649 18 153 237 128 27 29 36 21 

Gender 

Male 159 4 48 59 23 8 4 7 6 

Female 490 14 105 178 105 19 25 29 15 

Age (years) * 9 2 2 4 1 * * * * 

18-64 491 6 105 174 111 22 24 31 18 

> 64 149 10 46 59 16 5 5 5 3 

Race 

White 487 11 124 185 97 16 19 24 11 

Black 106 4 16 35 19 8 9 9 6 

Asian 12 * 2 6 3 1 * * * 

Some Others 12 * 2 3 5 1 * * 1 

Hispanic 26 1 8 6 3 1 1 3 3 

Refused 6 2 1 2 1 * * * * 

Hispanic No 600 16 136 224 120 26 27 33 18 

Yes 40 1 15 10 6 1 1 3 3 

DK 6 * 1 2 2 * 1 * * 

Refused 3 1 1 1 * * * * * 

Employment * 1 * * * 1 * * * * 

Full Time 283 4 58 107 64 12 12 19 7 

Part Time 76 1 26 26 15 5 1 2 * 

Not Employed 287 12 69 104 48 10 16 15 13 

Refused 2 1 * * * * * * 1 

Education 

* 4 1 * 2 1 * * * * 

< High School 96 7 15 35 16 3 6 7 7 

High School Graduate 235 6 57 85 51 13 5 11 7 

< College 163 4 45 53 32 4 11 8 6 

College Graduate 102 * 18 44 20 5 5 9 1 

Post Graduate 49 * 18 18 8 2 2 1 * 

Census Region Northeast 137 5 43 36 31 6 7 6 3 

Midwest 151 2 42 67 26 3 3 5 3 

South 255 9 42 87 55 16 14 21 11 

West 106 2 26 47 16 2 5 4 4 

Day of Week Weekday 415 12 90 161 84 11 23 23 11 

Weekend 234 6 63 76 44 16 6 13 10 

Season 

Winter 178 5 44 63 33 9 11 9 4 

Spring 160 6 39 60 27 9 7 6 6 

Summer 174 3 43 62 34 7 4 14 7 

Fall 137 4 27 52 34 2 7 7 4 

Asthma 

No 596 16 144 218 114 26 28 33 17 

Yes 52 1 9 19 14 1 1 3 4 

DK 1 1 * * * * * * * 

Angina No 620 14 147 226 124 25 28 35 21 

Yes 26 3 6 10 3 2 1 1 * 

DK 3 1 * 1 1 * * * * 

Bronchitis/Emphysema No 610 15 150 218 119 26 26 35 21 

Yes 36 2 3 17 9 1 3 1 * 

DK 3 1 * 2 * * * * * 

NOTE: * Signifies missing data. Dk= respondents answered don't know. Refused = respondents refused to answer. N = doer 

sample size in a specified range of number of minutes spent. A value of 61 for number of minutes signifies that more than 60 minutes 

were spent. 

Source: Tsang and Klepeis,1996 
Table 15-26. Number of Minutes Spent Giving and Taking the Bath(s) (minutes/bath) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 631 2 5 5 10 15 20 30 45 60 61 61 61 

Gender Male 155 1 4 5 6 10 15 30 45 60 61 61 61 

Gender Female 476 3 5 5 10 15 20 30 45 60 61 61 61 

Age (years) 18-64 485 2 5 5 10 15 20 30 60 60 61 61 61 

Age (years) > 64 139 3 5 5 5 10 15 20 40 60 61 61 61 

Race White 476 1 4 5 10 10 20 30 45 60 61 61 61 

Race Black 102 5 5 9 10 15 22.5 40 60 61 61 61 61 

Race Asian 12 10 10 10 10 15 20 27.5 30 40 40 40 40 

Race Some Others 12 5 5 5 10 15 27.5 30 40 61 61 61 61 

Race Hispanic 25 2 2 5 5 10 20 45 61 61 61 61 61 

Hispanic No 584 2 5 5 10 15 20 30 45 60 61 61 61 

Hispanic Yes 39 2 2 5 5 10 20 30 60 61 61 61 61 

Employment Full Time 279 1 4 5 10 15 20 30 45 60 61 61 61 

Employment Part Time 75 3 4 5 10 10 20 30 35 40 60 60 60 

Employment Not Employed 275 2 5 5 10 10 20 30 60 60 61 61 61 

Education < High School 89 1 5 10 10 15 20 35 60 61 61 61 61 

Education High School Graduate 229 5 5 5 10 12 20 30 45 60 61 61 61 

Education < College 159 1 2 5 6 10 20 30 45 60 61 61 61 

Education College Graduate 102 5 5 8 10 15 20 30 45 60 60 60 61 

Education Post Graduate 49 1 1 5 5 10 15 25 40 45 60 60 60 

Census Region Northeast 132 1 5 5 6 10 15 30 45 60 61 61 61 

Census Region Midwest 149 2 4 5 7 10 20 30 30 60 61 61 61 

Census Region South 246 3 5 10 10 15 20 35 60 60 61 61 61 

Census Region West 104 5 5 5 10 11 20 30 45 60 61 61 61 

Day of Week Weekday 403 2 5 5 10 15 20 30 45 60 61 61 61 

Day of Week Weekend 228 4 5 5 10 10 20 30 60 60 61 61 61 

Season Winter 173 2 5 5 10 10 20 30 45 60 61 61 61 

Season Spring 154 1 3 5 10 10 20 30 45 60 61 61 61 

Season Summer 171 5 5 5 10 10 20 30 60 60 61 61 61 

Season Fall 133 4 5 8 10 15 20 30 45 60 61 61 61 

Asthma No 580 2 5 5 10 12 20 30 45 60 61 61 61 

Asthma Yes 51 4 5 5 10 15 20 30 60 61 61 61 61 

Angina No 606 2 5 5 10 15 20 30 45 60 61 61 61 

Angina Yes 23 5 5 5 5 10 15 30 40 45 60 60 60 

Bronchitis/Emphysema No 595 2 5 5 10 10 20 30 45 60 61 61 61 

Bronchitis/Emphysema Yes 34 5 5 8 15 15 20 30 45 45 60 60 60 

NOTE: N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. A value of 61 for 

number of minutes signifies that more than 60 minutes were spent. 

Source: Tsang and Klepeis,1996 
Table 15-27. Time Spent in the Bathroom Immediately After the Bath(s) by the Number of Respondents 

Minutes/Bath 

Total N *-* 0-0 0-10 10-20 20-30 30-40 40-50 50-60 61-61 

Overall 649 25 85 422 74 23 7 6 5 2 

Gender Male 159 6 18 118 11 4 1 1 * * 

Female 490 19 67 304 63 19 6 5 5 2 

Age (years) * 9 2 2 4 1 * * * * * 

18-64 491 7 71 336 50 14 4 5 2 2 

> 64 149 16 12 82 23 9 3 1 3 * 

Race White 487 22 59 319 58 15 4 4 5 1 Black 106 2 14 67 13 5 3 2 * * 

Asian 12 * 2 9 1 * * * * * Some Others 12 * 5 6 1 * * * * * Hispanic 26 * 4 18 * 3 * * * 1 Refused 6 1 1 3 1 * * * * * 

Hispanic No 600 25 76 390 71 20 7 6 4 1 Yes 40 * 7 28 1 3 * * * 1 

DK 6 * 1 3 1 * * * 1 * Refused 3 * 1 1 1 * * * * * 

Employment * 1 * * 1 * * * * * * 

Full Time 283 6 35 203 30 7 1 1 * * 

Part Time 76 1 9 54 8 2 2 * * * 

Not Employed 287 18 41 164 35 14 4 4 5 2 

Refused 2 * * * 1 * * 1 * * 

Education * 4 1 * 2 1 * * * * * 

< High School 96 10 11 51 12 7 1 * 2 2 High School Graduate 235 6 35 158 22 7 3 3 1 * < College 163 4 17 113 18 4 3 2 2 * College Graduate 102 2 14 66 15 4 * 1 * * 

Post Graduate 49 2 8 32 6 1 * * * * 

Census Region Northeast 137 8 13 91 16 8 * * 1 * 

Midwest 151 5 20 100 18 3 2 1 2 * South 255 9 31 164 30 9 5 4 1 2 West 106 3 21 67 10 3 * 1 1 * 

Day of Week Weekday 415 17 53 280 40 16 2 4 2 1 Weekend 234 8 32 142 34 7 5 2 3 1 

Season Winter 178 3 14 122 24 7 3 1 2 2 Spring 160 8 21 96 20 8 4 2 1 * Summer 174 9 31 110 16 6 * 2 * * 

Fall 137 5 19 94 14 2 * 1 2 * 

Asthma No 596 24 75 388 69 21 7 5 5 2 

Yes 52 1 10 34 4 2 * 1 * * 

DK 1 * * * 1 * * * * * 

Angina No 620 23 82 405 70 22 6 6 4 2 Yes 26 2 2 17 3 1 * * 1 * 

DK 3 * 1 * 1 * 1 * * * 

Bronchitis/Emphysema No 610 22 78 400 71 21 6 5 5 2 Yes 36 3 6 21 2 2 1 1 * * 

DK 3 * 1 1 1 * * * * * 

Note: * Signifies missing data. Dk= respondents answered don't know. Refused = respondents refused to answer. N = doer sample 

size in specified range of number of minutes spent. A value of 61 for number of minutes signifies that more than 60 minutes were 

spent. 

Source: Tsang and Klepeis,1996 
Table 15-28. Number of Minutes Spent in the Bathroom Immediately After the Bath(s) (minutes/bath) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 624 0 0 0 0 2 5 10 20 30 45 55 61 

Gender Male 153 0 0 0 0 2 5 10 12 20 30 35 45 

Gender Female 471 0 0 0 0 2 5 10 20 30 45 60 61 

Age (years) 18-64 484 0 0 0 0 2 5 10 15 25 40 50 61 

Age (years) > 64 133 0 0 0 1 5 10 15 30 35 55 60 60 

Race White 465 0 0 0 0 2 5 10 18 30 45 58 61 

Race Black 104 0 0 0 0 2 5 10 20 30 40 45 45 

Race Asian 12 0 0 0 0 2 5 7.5 10 20 20 20 20 

Race Some Others 12 0 0 0 0 0 3 7.5 10 15 15 15 15 

Race Hispanic 26 0 0 0 0 1 5 10 25 25 61 61 61 

Hispanic No 575 0 0 0 0 2 5 10 20 30 40 50 61 

Hispanic Yes 40 0 0 0 0 1 5 10 22.5 25 61 61 61 

Employment Full Time 277 0 0 0 0 2 5 10 15 20 30 30 45 

Employment Part Time 75 0 0 0 0 3 5 10 15 25 35 40 40 

Employment Not Employed 269 0 0 0 0 2 5 10 25 35 58 60 61 

Education < High School 86 0 0 0 0 5 10 15 30 35 61 61 61 

Education High School Graduate 229 0 0 0 0 2 5 10 15 30 40 45 58 

Education < College 159 0 0 0 0 2 5 10 15 30 45 60 60 

Education College Graduate 100 0 0 0 0 1.5 5 10 19 25 30 37.5 45 

Education Post Graduate 47 0 0 0 0 1 5 10 15 20 30 30 30 

Census Region Northeast 129 0 0 0 0 2 5 10 20 30 30 30 60 

Census Region Midwest 146 0 0 0 0 2 5 10 15 25 50 60 60 

Census Region South 246 0 0 0 0 3 5 10 20 30 45 55 61 

Census Region West 103 0 0 0 0 1 5 10 20 20 30 45 58 

Day of Week Weekday 398 0 0 0 0 2 5 10 18 30 40 50 61 

Day of Week Weekend 226 0 0 0 0 3 5 10 20 30 45 60 61 

Season Winter 175 0 0 0 1 3 5 10 20 30 58 61 61 

Season Spring 152 0 0 0 0 2 5 10 20 30 40 45 60 

Season Summer 165 0 0 0 0 2 5 10 15 20 30 45 50 

Season Fall 132 0 0 0 0 2 5 10 15 20 45 55 60 

Asthma No 572 0 0 0 0 2 5 10 20 30 45 58 61 

Asthma Yes 51 0 0 0 0 1 5 10 15 30 30 45 45 

Angina No 597 0 0 0 0 2 5 10 20 30 45 58 61 

Angina Yes 24 0 0 0 1 5 5 10 15 30 55 55 55 

Bronchitis/Emphysema No 588 0 0 0 0 2 5 10 20 30 45 58 61 

Bronchitis/Emphysema Yes 33 0 0 0 0 2 5 10 30 40 45 45 45 

NOTE: N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. A value of 61 for

number of minutes signifies that more than 60 minutes were spent.

Source: Tsang and Klepeis,1996
Table 15-29. Total Time Spent Altogether in the Shower or Bathtub by the Number of Respondents 

Minutes/Bath 

Total *-* 0-0 0-10 10-20 20-30 30-40 40-50 50-60 70-80 80-90 90-100 100-110 110-120 121-121 

N 

Overall 4290 38 5 1903 1577 548 46 65 67 3 6 2 1 21 8 

Gender Male 1934 8 1 872 735 234 19 24 24 1 1 1 1 10 3 Female 2355 30 4 1031 841 314 27 41 43 2 5 1 * 11 5 Refused 1 * * * 1 * * * * * * * * * * 

Age (years) * 86 5 1 26 36 12 * 1 4 * * * * * 1 

1-4 198 * * 35 84 50 2 13 7 1 1 1 * 4 * 

5-11 265 2 * 64 107 66 3 7 7 2 2 1 1 2 1 

12-17 239 * * 78 96 46 5 5 8 * * * * 1 * 

18-64 2919 15 1 1429 1051 303 32 31 35 * 3 * * 13 6 

> 64 583 16 3 271 203 71 4 8 6 * * * * 1 * 

Race White 3452 27 4 1616 1248 401 35 44 50 1 3 * 1 16 6 Black 453 7 1 141 177 89 7 11 11 2 * 1 * 4 2 

Asian 74 * * 33 31 7 * 1 1 * 1 * * * * Some Others 78 * * 24 28 19 2 3 2 * * * * * * 

Hispanic 180 2 * 63 79 24 2 4 2 * 2 1 * 1 * Refused 53 2 * 26 14 8 * 2 1 * * * * * * 

Hispanic No 3892 31 4 1744 1423 496 41 56 62 3 4 1 1 18 8 Yes 333 5 1 128 136 40 5 8 5 * 2 1 * 2 * 

DK 21 1 * 7 8 4 * * * * * * * 1 * Refused 44 1 * 24 10 8 * 1 * * * * * * * 

Employment * 692 2 * 172 284 162 9 24 22 3 3 2 1 7 1 Full Time 1985 11 2 1002 707 190 20 20 18 * * * * 12 3 Part Time 400 5 1 190 147 44 4 4 5 * * * * * * 

Not Employed 1181 20 2 524 429 146 13 17 22 * 3 * * 1 4 

Refused 32 * * 15 10 6 * * * * * * * 1 * 

Education * 775 6 * 200 317 175 10 26 24 3 3 2 1 7 1 

< High School 386 10 2 132 147 66 7 8 10 * 1 * * 1 2 High School Graduate 1254 12 1 574 476 138 14 14 18 * * * * 4 3 < College 864 2 * 414 331 93 6 7 8 * 1 * * 2 * College Graduate 558 4 1 308 168 53 7 7 4 * 1 * * 5 * 

Post Graduate 453 4 1 275 138 23 2 3 3 * * * * 2 2 

Census Region Northeast 927 7 * 436 328 106 11 14 12 1 2 1 * 6 3 

Midwest 956 9 3 440 343 126 5 15 10 * 2 1 * 2 * South 1513 16 2 601 588 208 22 25 35 2 1 * 1 8 4 West 894 6 * 426 318 108 8 11 10 * 1 * * 5 1 

Day of Week Weekday 2881 23 3 1346 1038 336 30 40 39 1 1 2 1 16 5 Weekend 1409 15 2 557 539 212 16 25 28 2 5 * * 5 3 

Season Winter 1124 8 1 504 417 137 14 13 19 1 * * * 7 3 Spring 1145 15 3 499 417 149 9 22 17 1 3 1 * 7 2 Summer 1165 11 1 495 420 176 14 19 19 1 2 1 * 5 1 

Fall 856 4 * 405 323 86 9 11 12 * 1 * 1 2 2 

Asthma No 3946 35 5 1767 1445 502 38 53 65 3 5 2 1 19 6 

Yes 327 2 * 128 128 43 8 11 2 * 1 * * 2 2 

DK 17 1 * 8 4 3 * 1 * * * * * * * 

Angina No 4151 34 5 1839 1529 530 45 62 66 3 6 2 1 21 8 Yes 114 3 * 52 41 14 1 2 1 * * * * * * 

DK 25 1 * 12 7 4 * 1 * * * * * * * 

Bronchitis/Emphysema No 4059 34 3 1803 1502 517 42 58 63 3 5 2 1 19 7 Yes 207 2 2 86 71 28 4 6 4 * 1 * * 2 1 

DK 24 2 * 14 4 3 * 1 * * * * * * * 

Note: * Signifies missing data. DK = respondents answered "don't know". Refused = respondents refused to answer. N = doer sample size in 

specified range of number of minutes spent. A value of "121" for number of minutes signifies that more than 120 minutes were spent. 

Source: Tsang and Klepeis,1996 
Table 15-30. Total Number of Minutes Spent Altogether in the Shower or Bathtub (minutes/bath) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 4252 3 4 5 5 10 15 20 30 35 60 60 121 

Gender Male 1926 3 4 5 5 10 15 20 30 30 60 60 121 

Gender Female 2325 3 4 5 5 10 15 20 30 40 60 75 121 

Age (years) 1-4 198 1 5 5 10 15 20 30 45 60 120 120 120 

Age (years) 5-11 263 4 5 5 10 13 20 30 30 60 90 120 121 

Age (years) 12-17 239 4 4 5 7 10 15 30 30 45 60 60 120 

Age (years) 18-64 2904 3 4 5 5 10 13.5 20 30 30 50 60 121 

Age (years) > 64 567 2 3 5 5 10 15 20 30 30 45 60 120 

Race White 3425 3 4 5 5 10 15 20 30 30 60 60 121 

Race Black 446 4 4 5 6 10 15 25 30 45 75 120 121 

Race Asian 74 5 5 5 7 10 15 15 30 30 60 90 90 

Race Some Others 78 5 5 5 7 10 15 30 30 45 60 60 60 

Race Hispanic 178 1 3 5 7 10 15 20 30 45 90 100 120 

Hispanic No 3861 3 4 5 5 10 15 20 30 35 60 60 121 

Hispanic Yes 328 1 3 5 5 10 15 20 30 45 60 90 120 

Employment Full Time 1974 3 4 5 5 10 10 20 30 30 45 60 121 

Employment Part Time 395 3 3 5 5 10 15 20 30 30 45 60 60 

Employment Not Employed 1161 2 3 5 5 10 15 20 30 35 60 60 121 

Education < High School 376 1 4 5 5 10 15 25 30 45 60 90 121 

Education High School Graduate 1242 3 4 5 5 10 15 20 30 30 60 60 121 

Education < College 862 3 4 5 5 10 15 20 30 30 45 60 120 

Education College Graduate 554 3 3 5 5 10 10 15 30 30 45 90 120 

Education Post Graduate 449 3 4 5 5 8 10 15 20 30 45 60 121 

Census Region Northeast 920 4 4 5 5 10 15 20 30 35 60 100 121 

Census Region Midwest 947 3 4 5 5 10 15 20 30 30 45 60 120 

Census Region South 1497 3 4 5 5 10 15 20 30 45 60 75 121 

Census Region West 888 3 3 5 5 10 15 20 30 30 45 60 121 

Day of Week Weekday 2858 3 4 5 5 10 15 20 30 30 60 60 121 

Day of Week Weekend 1394 3 4 5 5 10 15 20 30 40 60 75 121 

Season Winter 1116 3 4 5 5 10 15 20 30 35 60 60 121 

Season Spring 1130 3 4 5 5 10 15 20 30 40 60 90 121 

Season Summer 1154 3 4 5 5 10 15 20 30 40 60 60 121 

Season Fall 852 3 5 5 5 10 15 20 30 30 60 60 121 

Asthma No 3911 3 4 5 5 10 15 20 30 30 60 60 121 

Asthma Yes 325 3 4 5 5 10 15 20 30 45 60 120 121 

Angina No 4117 3 4 5 5 10 15 20 30 35 60 60 121 

Angina Yes 111 3 4 5 5 10 15 20 30 30 45 45 60 

Bronchitis/Emphysema No 4025 3 4 5 5 10 15 20 30 30 60 60 121 

Bronchitis/Emphysema Yes 205 1 3 5 5 10 15 20 30 45 60 120 121 

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: Tsang and Klepeis, 1996. 
Table 15-31. Time Spent in the Bathroom Immediately Following a Shower or Bath by the Number of Respondents 

Minutes/Shower or Bath 

Total N *-* 0-0 0-10 10-20 20-30 30-40 40-50 50-60 70-80 80-90 110-120 121-121 

Overall 4290 108 348 2770 713 250 20 32 35 1 2 7 4 

Gender Male 1934 37 138 1357 312 67 5 8 6 * * 1 3 Female 2355 71 210 1413 400 183 15 24 29 1 2 6 1 Refused 1 * * * 1 * * * * * * * * 

Age (years) * 86 12 8 38 19 6 * 1 1 * * * 1 

1-4 198 2 59 123 12 * 1 1 * * * * * 

5-11 265 5 33 198 23 3 1 * 1 * * 1 * 

12-17 239 1 17 165 34 16 1 3 2 * * * * 

18-64 2919 53 184 1901 517 189 14 25 26 1 1 5 3 

> 64 583 35 47 345 108 36 3 2 5 * 1 1 * 

Race White 3452 80 271 2235 590 194 15 29 24 1 2 7 4 Black 453 15 49 276 63 35 4 2 9 * * * * 

Asian 74 * 8 48 12 4 1 1 * * * * * Some Others 78 2 7 46 19 3 * * 1 * * * * 

Hispanic 180 4 8 134 21 12 * * 1 * * * * Refused 53 7 5 31 8 2 * * * * * * * 

Hispanic No 3892 95 316 2504 655 227 19 32 32 1 1 6 4 Yes 333 8 28 227 46 21 1 * 2 * * * * 

DK 21 * 1 10 5 2 * * 1 * 1 1 * Refused 44 5 3 29 7 * * * * * * * * 

Employment * 692 8 111 479 66 17 3 4 3 * * 1 * 

Full Time 1985 36 122 1302 357 120 10 16 14 1 1 3 3 Part Time 400 8 22 256 71 32 2 5 2 * * 2 * 

Not Employed 1181 52 93 712 214 79 5 7 16 * 1 1 1 

Refused 32 4 * 21 5 2 * * * * * * * 

Education * 775 14 114 531 82 20 3 7 3 * * 1 * 

< High School 386 28 30 220 65 30 2 1 5 * 2 1 2 High School Graduate 1254 34 89 799 204 92 8 12 10 1 * 4 1 < College 864 17 59 568 158 46 4 2 9 * * * 1 College Graduate 558 8 27 362 115 31 2 8 5 * * * * 

Post Graduate 453 7 29 290 89 31 1 2 3 * * 1 * 

Census Region Northeast 927 20 69 614 161 49 3 2 6 * * 1 2 

Midwest 956 27 86 600 155 57 5 13 11 * * 1 1 South 1513 41 119 971 255 93 8 7 10 1 2 5 1 West 894 20 74 585 142 51 4 10 8 * * * * 

Day of Week Weekday 2881 79 224 1889 474 153 15 19 19 1 1 5 2 Weekend 1409 29 124 881 239 97 5 13 16 * 1 2 2 

Season Winter 1124 34 77 726 193 65 7 8 9 * 1 3 1 Spring 1145 26 99 756 167 70 4 12 10 * * 1 * Summer 1165 36 112 740 184 66 6 9 8 1 1 2 * 

Fall 856 12 60 548 169 49 3 3 8 * * 1 3 

Asthma No 3946 101 306 2540 673 236 18 30 32 1 1 6 2 

Yes 327 5 41 219 37 14 2 2 3 * 1 1 2 

DK 17 2 1 11 3 * * * * * * * * 

Angina No 4151 99 333 2687 691 241 20 32 34 1 2 7 4 Yes 114 6 13 68 17 9 * * 1 * * * * 

DK 25 3 2 15 5 * * * * * * * * 

Bronchitis/Emphysema No 4059 98 325 2623 684 236 19 31 32 1 1 6 3 Yes 207 6 22 133 24 14 1 1 3 * 1 1 1 

DK 24 4 1 14 5 * * * * * * * * 

Note: * Signifies missing data. A value of "121" for number of minutes signifies that more than 120 minutes were spent. DK= respondents 

answered "don't know". Refused = respondents refused to answer. N = doer sample size in a specified range or number of minutes 

spent. 

Source: Tsang and Klepeis, 
Table 15-32. Number of Minutes Spent in the Bathroom Immediately Following a Shower or Bath (minutes/bath) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 4182 0 0 0 1 4 5 15 20 30 40 60 121 

Gender Male 1897 0 0 0 1 3 5 10 15 20 30 40 121 

Gender Female 2284 0 0 0 1 5 10 15 30 30 45 60 121 

Age (years) 1-4 196 0 0 0 0 0 2 5 10 15 20 35 45 

Age (years) 5-11 260 0 0 0 0 2 5 10 15 15 30 35 120 

Age (years) 12-17 238 0 0 0 2 5 5 10 20 30 45 45 60 

Age (years) 18-64 2866 0 0 0 1 5 10 15 20 30 45 60 121 

Age (years) > 64 548 0 0 0 1 4 10 15 20 30 40 60 120 

Race White 3372 0 0 0 1 4 5 15 20 30 40 60 121 

Race Black 438 0 0 0 0 4 6 15 30 30 60 60 60 

Race Asian 74 0 0 0 0 2 5 10 20 30 35 45 45 

Race Some Others 76 0 0 0 1 5 10 15 20 25 30 60 60 

Race Hispanic 176 0 0 1 1 3 5 10 20 30 30 30 60 

Hispanic No 3797 0 0 0 1 4 5 15 20 30 45 60 121 

Hispanic Yes 325 0 0 0 1 3 5 10 20 30 30 30 60 

Employment Full Time 1949 0 0 0 1 5 10 15 20 30 40 60 121 

Employment Part Time 392 0 0 0 2 5 10 15 25 30 45 60 120 

Employment Not Employed 1129 0 0 0 1 5 10 15 20 30 45 60 121 

Education < High School 358 0 0 0 1 5 10 15 30 30 60 90 121 

Education High School Graduate 1220 0 0 0 1 5 10 15 25 30 45 60 121 

Education < College 847 0 0 0 1 5 10 15 20 30 30 60 121 

Education College Graduate 550 0 0 1 2 5 10 15 20 30 45 45 60 

Education Post Graduate 446 0 0 0 1 5 8 15 20 30 30 50 120 

Census Region Northeast 907 0 0 0 1 5 5 10 20 30 30 45 121 

Census Region Midwest 929 0 0 0 1 5 5 15 20 30 45 60 121 

Census Region South 1472 0 0 0 1 3.5 5 15 20 30 40 60 121 

Census Region West 874 0 0 0 1 3 5 10 20 30 45 45 60 

Day of Week Weekday 2802 0 0 0 1 4 5 10 20 30 35 50 121 

Day of Week Weekend 1380 0 0 0 1 4 8 15 20 30 45 60 121 

Season Winter 1090 0 0 0 1 5 7 15 20 30 45 60 121 

Season Spring 1119 0 0 0 1 3 5 10 20 30 45 50 120 

Season Summer 1129 0 0 0 1 3 5 10 20 30 40 52 120 

Season Fall 844 0 0 0 1 5 8 15 20 30 35 60 121 

Asthma No 3845 0 0 0 1 4 5 15 20 30 40 60 121 

Asthma Yes 322 0 0 0 0 3 5 10 20 30 60 90 121 

Angina No 4052 0 0 0 1 4 5 15 20 30 40 60 121 

Angina Yes 108 0 0 0 0 4.5 5.5 12.5 20 30 30 30 60 

Bronchitis/emphysema No 3961 0 0 0 1 4 5 15 20 30 40 60 121 

Bronchitis/emphysema Yes 201 0 0 0 0 4 10 10 30 30 60 88 121 

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: Tsang and Klepeis, 1996. 
Table 15-33. Range of Number of Times Washing the Hands at Specified Daily Frequencies by the Number of Respondents 

Number of Times/Day 

Total N *-* 0-0 1-2 3-5 6-9 10-19 20-29 30+ DK 

Overall 4663 38 34 311 1692 1106 892 223 178 189 

Gender Male 2163 16 19 218 975 487 286 59 49 54 Female 2498 22 15 92 716 619 606 164 129 135 

Refused 2 * * 1 1 * * * * * 

Age (years) * 84 8 * 1 25 15 11 4 5 15 

1-4 263 * 15 62 125 35 11 2 3 10 

5-11 348 1 5 61 191 48 21 4 2 15 

12-17 326 3 6 46 159 64 30 7 2 9 

18-64 2972 18 7 131 1029 760 640 168 143 76 

> 64 670 8 1 10 163 184 179 38 23 64 

Race White 3774 21 28 251 1377 902 740 181 140 134 

Black 463 6 2 30 149 120 85 19 23 29 Asian 77 1 * 5 29 19 12 4 1 6 Some Others 96 * 1 10 39 16 15 8 5 2 Hispanic 193 1 3 14 78 42 31 10 5 9 

Refused 60 9 * 1 20 7 9 1 4 9 

Hispanic No 4244 27 29 276 1536 1022 823 205 164 162 

Yes 347 2 5 33 130 76 57 17 10 17 DK 26 * * 1 12 4 5 1 1 2 Refused 46 9 * 1 14 4 7 * 3 8 

Employment * 926 4 26 165 471 145 61 13 7 34 Full Time 2017 12 4 96 707 525 406 116 103 48 Part Time 379 * * 13 142 101 86 10 15 12 

Not Employed 1309 18 4 36 365 327 334 83 52 90 Refused 32 4 * 1 7 8 5 1 1 5 

Education 

* 1021 13 26 174 507 158 74 13 12 44 < High School 399 2 * 8 120 96 88 26 24 35 High School Graduate 1253 12 4 56 391 318 298 70 47 57 < College 895 2 3 28 284 246 197 59 48 28 

College Graduate 650 6 * 23 238 174 139 28 27 15 Post Graduate 445 3 1 22 152 114 96 27 20 10 

Census Region Northeast 1048 9 6 68 404 243 195 55 38 30 Midwest 1036 5 7 68 373 251 212 41 38 41 South 1601 14 11 108 559 379 299 79 66 86 West 978 10 10 67 356 233 186 48 36 32 

Day of Week Weekday 3156 34 22 199 1103 764 599 155 147 133 Weekend 1507 4 12 112 589 342 293 68 31 56 

Season Winter 1264 6 10 91 507 286 223 55 51 35 Spring 1181 13 9 78 406 283 238 60 44 50 

Summer 1275 15 9 78 443 315 232 65 48 70 Fall 943 4 6 64 336 222 199 43 35 34 

Asthma 

No 4287 28 32 283 1562 1024 819 207 165 167 Yes 341 1 2 26 126 77 69 16 10 14 DK 35 9 * 2 4 5 4 * 3 8 

Angina No 4500 28 34 306 1652 1069 851 218 171 171 Yes 125 2 * 3 32 34 36 5 3 10 DK 38 8 * 2 8 3 5 * 4 8 

Bronchitis/Emphysema No 4424 27 33 302 1627 1040 835 213 172 175 Yes 203 3 1 7 57 61 55 10 3 6 

DK 36 8 * 2 8 5 2 * 3 8 

Note: * Signifies missing data. N = doer sample size in a specified range or number of minutes spent. DK= respondents answered

"don't know". Refused = respondents refused to answer. 

Source: Tsang and Klepeis,1996
Table 15-34. Number of Minutes Spent (at home) Working or Being Near Food While Fried, Grilled, or Barbequed (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 1055 0 1 2 5 10 20 30 105 121 121 121 121 

Gender Male 485 0 1 2 5 10 20 30 90 121 121 121 121 

Gender Female 570 0 0 2 5 10 20 30 120 121 121 121 121 

Age (years) 1-4 35 0 0 2 2 5 20 30 45 60 60 60 60 

Age (years) 5-11 82 0 0 0 2 5 15 30 60 90 121 121 121 

Age (years) 12-17 82 0 0 2 4 10 20 45 60 90 121 121 121 

Age (years) 18-64 747 0 2 3 5 10 20 40 120 121 121 121 121 

Age (years) > 64 96 0 1 3 5 10 20 30 60 120 121 121 121 

Race White 848 0 1 2 5 10 20 30 105 121 121 121 121 

Race Black 115 2 2 5 5 10 20 30 61 121 121 121 121 

Race Asian 18 0 0 0 0 5 10 20 121 121 121 121 121 

Race Some Others 16 5 5 5 5 12.5 20 45 121 121 121 121 121 

Race Hispanic 48 0 0 5 5 15 30 60 90 121 121 121 121 

Hispanic No 960 0 1 2 5 10 20 30 90 121 121 121 121 

Hispanic Yes 84 0 1 2 5 10 20 60 121 121 121 121 121 

Employment Full Time 506 1 2 3 5 10 20 45 121 121 121 121 121 

Employment Part Time 95 0 1 2 5 10 15 40 90 121 121 121 121 

Employment Not Employed 252 0 1 3 5 10 20 30 90 121 121 121 121 

Education < High School 96 0 1 2 5 10 22.5 52.5 121 121 121 121 121 

Education High School Graduate 318 0 2 5 5 10 20 30 120 121 121 121 121 

Education < College 208 0 2 3 5 10 20 35 121 121 121 121 121 

Education College Graduate 135 1 1 2 5 10 20 30 90 121 121 121 121 

Education Post Graduate 83 0 2 5 5 10 15 30 60 121 121 121 121 

Census Region Northeast 198 0 2 3 5 10 15 30 90 121 121 121 121 

Census Region Midwest 248 0 0 4 5 10 20 30 121 121 121 121 121 

Census Region South 399 0 1 2 5 10 20 40 90 121 121 121 121 

Census Region West 210 0 0 2 5 7 15 30 60 121 121 121 121 

Day of Week Weekday 662 0 1 3 5 10 20 30 90 121 121 121 121 

Day of Week Weekend 393 0 1 2 5 10 20 30 120 121 121 121 121 

Season Winter 267 0 2 2 5 10 20 30 60 121 121 121 121 

Season Spring 296 0 0 3 5 10 20 45 120 121 121 121 121 

Season Summer 299 0 0 3 5 10 20 30 90 121 121 121 121 

Season Fall 193 0 0 2 5 10 20 30 121 121 121 121 121 

Asthma No 960 0 1 2.5 5 10 20 30 90 121 121 121 121 

Asthma Yes 92 0 0 2 5 15 30 60 121 121 121 121 121 

Angina No 1032 0 1 2 5 10 20 30 95 121 121 121 121 

Angina Yes 19 0 0 0 5 15 30 30 121 121 121 121 121 

Bronchitis/Emphysema No 1005 0 1 2 5 10 20 30 90 121 121 121 121 

Bronchitis/Emphysema Yes 47 0 0 3 5 10 30 60 121 121 121 121 121 

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: Tsang and Klepeis, 1996. 
Table 15-35. Number of Minutes Spent (at home) Working or Being Near Open Flames Including Barbeque Flames (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 479 0 0 1 2 10 20 60 121 121 121 121 121 

Gender Male 252 0 0 1 2 10 20 60 121 121 121 121 121 

Gender Female 227 0 0 2 2 10 20 30 121 121 121 121 121 

Age (years) 1-4 14 0 0 0 0 5 10 30 121 121 121 121 121 

Age (years) 5-11 29 0 0 0 0 5 15 30 90 121 121 121 121 

Age (years) 12-17 28 0 0 1 2 10 22.5 42.5 60 60 90 90 90 

Age (years) 18-64 372 0 0 1 3 10 20 60 121 121 121 121 121 

Age (years) :> 64 31 2 2 2 4 5 17 30 120 121 121 121 121 

Race White 407 0 0 1 2 10 20 45 121 121 121 121 121 

Race Black 31 0 0 0 2 5 20 30 60 121 121 121 121 

Race Asian 5 5 5 5 5 20 40 121 121 121 121 121 121 

Race Some Others 8 10 10 10 10 11 22.5 60 121 121 121 121 121 

Race Hispanic 22 2 2 3 5 5 30 60 120 121 121 121 121 

Hispanic No 436 0 0 1 2 10 20 42.5 121 121 121 121 121 

Hispanic Yes 36 2 2 3 5 11 60 90 121 121 121 121 121 

Employment Full Time 262 0 0 1 2 10 20 60 121 121 121 121 121 

Employment Part Time 44 0 0 1 4 5 15 52.5 121 121 121 121 121 

Employment Not Employed 99 0 1 2 3 10 20 40 120 121 121 121 121 

Education < High School 27 2 2 2 3 5 20 60 121 121 121 121 121 

Education High School Graduate 130 0 0 2 3 10 20 60 121 121 121 121 121 

Education < College 92 0 0 1 2 10 30 90 121 121 121 121 121 

Education College Graduate 95 0 1 2 5 10 20 40 121 121 121 121 121 

Education Post Graduate 55 0 0 0 2 10 20 40 121 121 121 121 121 

Census Region Northeast 124 0 0 1 3 10 15 30 121 121 121 121 121 

Census Region Midwest 112 0 0 2 3 10 20 45 121 121 121 121 121 

Census Region South 149 0 0 1 2 5 20 60 121 121 121 121 121 

Census Region West 94 0 0 1 2 10 20 60 121 121 121 121 121 

Day of Week Weekday 284 0 0 1 3 10 15 30 121 121 121 121 121 

Day of Week Weekend 195 0 0 1 2 10 30 60 121 121 121 121 121 

Season Winter 142 0 0 0 2 10 20 60 121 121 121 121 121 

Season Spring 115 0 1 2 3 10 20 60 120 121 121 121 121 

Season Summer 137 0 0 2 3 10 20 45 121 121 121 121 121 

Season Fall 85 1 1 1 3 10 20 40 121 121 121 121 121 

Asthma No 443 0 0 1 2 10 20 45 121 121 121 121 121 

Asthma Yes 35 0 0 3 3 15 30 120 121 121 121 121 121 

Angina No 461 0 0 1 2 10 20 45 121 121 121 121 121 

Angina Yes 15 2 2 2 2 10 15 60 121 121 121 121 121 

Bronchitis/Emphysema No 461 0 0 1 2 10 20 45 121 121 121 121 121 

Bronchitis/Emphysema Yes 16 3 3 3 5 12.5 37.5 106 121 121 121 121 121 

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: Tsang and Klepeis, 1996. 
Table 15-36. Number of Minutes Spent Working or Being Near Excessive Dust in the Air (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 679 0 2 5 7 30 121 121 121 121 121 121 121 

Gender Male 341 1 2 5 8 30 121 121 121 121 121 121 121 

Gender Female 338 0 2 5 5 30 121 121 121 121 121 121 121 

Age (years) 1-4 22 0 0 0 2 5 75 121 121 121 121 121 121 

Age (years) 5-11 50 0 0.5 2 4 15 75 121 121 121 121 121 121 

Age (years) 12-17 52 0 1 2 5 5 20 120 121 121 121 121 121 

Age (years) 18-64 513 2 5 5 10 30 121 121 121 121 121 121 121 

Age (years) 5:> 64 38 2 2 2 5 35 105.5 121 121 121 121 121 121 

Race White 556 0 2 5 8 30 121 121 121 121 121 121 121 

Race Black 66 1 3 5 5 20 121 121 121 121 121 121 121 

Race Asian 7 20 20 20 20 60 90 121 121 121 121 121 121 

Race Some Others 15 5 5 5 10 60 120 121 121 121 121 121 121 

Race Hispanic 29 3 3 5 7 20 121 121 121 121 121 121 121 

Hispanic No 611 0 2 5 5 30 121 121 121 121 121 121 121 

Hispanic Yes 57 0 3 3 10 30 121 121 121 121 121 121 121 

Employment Full Time 368 2 5 7 15 37.5 121 121 121 121 121 121 121 

Employment Part Time 66 0 2 5 5 20 120 121 121 121 121 121 121 

Employment Not Employed 122 0 2 5 8 30 121 121 121 121 121 121 121 

Education < High School 52 2 5 5 7 35 121 121 121 121 121 121 121 

Education High School Graduate 199 0 0 5 10 30 121 121 121 121 121 121 121 

Education < College 140 5 5 10 20 60 121 121 121 121 121 121 121 

Education College Graduate 82 1 2 5 15 30 121 121 121 121 121 121 121 

Education Post Graduate 76 3 5 5 10 37.5 121 121 121 121 121 121 121 

Census Region Northeast 138 0 0 5 5 20 121 121 121 121 121 121 121 

Census Region Midwest 145 2 2 5 10 30 121 121 121 121 121 121 121 

Census Region South 227 1 2 5 5 30 121 121 121 121 121 121 121 

Census Region West 169 0 3 5 10 30 120 121 121 121 121 121 121 

Day of Week Weekday 471 0 1 5 7 30 121 121 121 121 121 121 121 

Day of Week Weekend 208 2 2 5 5 30 121 121 121 121 121 121 121 

Season Winter 154 0 0 5 5 30 121 121 121 121 121 121 121 

Season Spring 193 0 1 3 5 20 121 121 121 121 121 121 121 

Season Summer 193 2 2 5 10 30 121 121 121 121 121 121 121 

Season Fall 139 3 5 5 10 30 121 121 121 121 121 121 121 

Asthma No 606 0 2 5 5 30 121 121 121 121 121 121 121 

Asthma Yes 73 0 3 5 10 30 121 121 121 121 121 121 121 

Angina No 662 0 2 5 7 30 121 121 121 121 121 121 121 

Angina Yes 15 3 3 3 30 60 121 121 121 121 121 121 121 

Bronchitis/Emphysema No 637 0 2 5 7 30 121 121 121 121 121 121 121 

Bronchitis/Emphysema Yes 41 0 0 5 5 30 121 121 121 121 121 121 121 

Note: A valueof "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: Tsang and Klepeis, 1996. 
Table 15-37. Range of the Number of Times an Automobile or Motor Vehicle was Started in a Garage or Carport at Specified Daily Frequencies by the Number of Respondents 

Times/day 

Total N 1-2 3-5 6-9 10+ Dk 

Overall 2009 1321 559 78 17 34 

Gender 

Male 939 588 290 40 7 14 

Female 1070 733 269 38 10 20 

Age(years) * 20 13 2 1 1 3 

1-4 111 68 39 2 2 * 

5-11 150 93 49 6 * 2 

12-17 145 86 42 12 1 4 

18-64 1287 840 367 50 12 18 

> 64 296 221 60 7 1 7 

Race 

White 1763 1164 486 69 17 27 

Black 110 70 31 4 * 5 

Asian 46 34 10 2 * * 

Some Others 24 19 5 * * * 

Hispanic 55 26 24 3 * 2 

Refused 11 8 3 * * * 

Hispanic No 1879 1239 519 74 17 30 

Yes 111 68 35 4 * 4 

DK 12 9 3 * * * 

Refused 7 5 2 * * * 

Employment * 398 241 127 20 3 7 

Full Time 919 610 253 35 9 12 

Part Time 149 93 48 4 2 2 

Not Employed 536 372 129 19 3 13 

Refused 7 5 2 * * * 

Education 

* 427 262 134 21 4 6 

< High School 84 59 17 2 1 5 

High School Graduate 464 336 107 13 2 6 

< College 440 304 107 20 5 4 

College Graduate 326 201 106 10 2 7 

Post Graduate 268 159 88 12 3 6 

Census Region Northeast 289 213 64 8 2 2 

Midwest 541 360 142 29 2 8 

South 702 430 221 27 8 16 

West 477 318 132 14 5 8 

Day of Week Weekday 1383 903 386 63 11 20 

Weekend 626 418 173 15 6 14 

Season 

Winter 567 396 136 20 5 10 

Spring 518 336 141 25 5 11 

Summer 525 313 178 18 6 10 

Fall 399 276 104 15 1 3 

Asthma 

No 1861 1228 514 70 17 32 

Yes 146 92 44 8 * 2 

DK 2 1 1 * * * 

Angina No 1959 1288 545 76 17 33 

Yes 48 33 12 2 * 1 

DK 2 * 2 * * * 

Bronchitis/Emphysema No 1922 1266 532 74 17 33 

Yes 84 54 25 4 * 1 

DK 3 1 2 * * * 

Note: "*" Signifies missing data; "DK" = respondent answered don't know; Refused - the respondent refused to answer; N = doer

sample size.

Source: Tsang and Klepeis, 1996
Table 15-38. Range of the Number of Times Motor Vehicle Was Started with Garage Door Closed at Specified Daily Frequencies by the Number of Respondents 

Times/day 

Total N None 1-2 3-5 6-9 Dk 

Overall 2009 1830 99 26 2 52 

Gender 

Male 939 860 41 15 * 23 

Female 1070 970 58 11 2 29 

Age (years)

* 20 14 1 * * 5 

1-4 111 99 8 2 * 2 

5-11 150 141 6 * * 3 

12-17 145 127 9 4 1 4 

18-64 1287 1184 57 18 1 27 

> 64 296 265 18 2 * 11 

Race 

White 1763 1616 82 22 1 42 

Black 110 95 6 2 1 6 

Asian 46 41 4 * * 1 

Some Others 24 21 2 * * 1 

Hispanic 55 46 5 2 * 2 

Refused 11 11 * * * * 

Hispanic

No 1879 1714 92 23 2 48 

Yes 111 97 7 3 * 4 

DK 12 12 * * * * 

Refused 7 7 * * * * 

Employment

* 398 360 22 5 1 10 

Full Time 919 840 46 13 1 19 

Part Time 149 137 6 2 * 4 

Not Employed 536 488 24 5 * 19 

Refused 7 5 1 1 * * 

Education 

* 427 387 23 6 1 10 

< High School 84 74 2 1 * 7 

High School Graduate 464 429 24 2 * 9 

< College 440 399 24 8 1 8 

College Graduate 326 299 12 6 * 9 

Post Graduate 268 242 14 3 * 9 

Census Region

Northeast 289 270 10 5 1 3 

Midwest 541 500 22 4 1 14 

South 702 628 42 8 * 24 

West 477 432 25 9 * 11 

Day of Week

Weekday 1383 1269 66 21 * 27 

Weekend 626 561 33 5 2 25 

Season 

Winter 567 509 32 9 1 16 

Spring 518 470 29 3 * 16 

Summer 525 476 23 11 * 15 

Fall 399 375 15 3 1 5 

Asthma 

No 1861 1696 92 23 1 49 

Yes 146 132 7 3 1 3 

DK 2 2 * * * * 

Angina

No 1959 1785 96 26 2 50 

Yes 48 43 3 * * 2 

DK 2 2 * * * * 

Bronchitis/Emphysema

No 1922 1747 96 26 2 51

Yes 84 80 3 * * 1

DK 3 3 * * * *

Note: "*" Signifies missing data; "DK" = respondents answered don't know; N = doer sample size; Refused = the respondent refused

to answer.

Source: Tsang and Klepeis, 1996
Table 15-39. Number of Minutes Spent at a Gas Station or Auto Repair Shop (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 967 1 2 3 4 5 6 10 30 90 121 121 121 

Gender Male 552 2 2 3 4 5 7 10 30 120 121 121 121 

Gender Female 414 0 1 2 3 5 5.5 10 15 30 121 121 121 

Age (years) 1-4 29 0 0 0 0 5 5 10 20 60 121 121 121 

Age (years) 5-11 42 2 2 2 3 5 5 10 15 15 120 120 120 

Age (years) 12-17 57 1 3 3 5 5 5 10 20 30 60 121 121 

Age (years) 18-64 760 1 2 3 4 5 5.5 10 30 120 121 121 121 

Age (years) > 64 67 0 2 3 4 5 10 15 15 40 120 120 120 

Race White 788 1 2 3 4 5 7.5 10 30 120 121 121 121 

Race Black 95 0 1 2 3 5 5 10 15 15 20 120 120 

Race Asian 13 2 2 2 2 5 5 10 10 10 10 10 10 

Race Some Others 22 5 5 5 5 5 5 12 20 30 30 30 30 

Race Hispanic 42 0 0 3 4 5 10 15 25 30 121 121 121 

Hispanic No 875 1 2 3 4 5 6 10 30 120 121 121 121 

Hispanic Yes 82 0 2 2 3 5 8 10 20 35 121 121 121 

Employment Full Time 542 1 2 3 4 5 7 10 30 121 121 121 121 

Employment Part Time 107 2 3 4 5 5 10 10 30 120 121 121 121 

Employment Not Employed 186 1 1 3 4 5 10 10 20 40 120 120 121 

Education < High School 70 0 2 3 4.5 5 10 30 121 121 121 121 121 

Education High School Graduate 293 1 2 3 5 5 8 15 30 121 121 121 121 

Education < College 213 1 2 2 4 5 8 10 15 60 121 121 121 

Education College Graduate 143 2 2 3 4 5 5 10 15 30 121 121 121 

Education Post Graduate 106 1 2 3 3 5 7 10 15 35 56 90 120 

Census Region Northeast 167 1 2 3 5 5 5 10 30 121 121 121 121 

Census Region Midwest 246 0 2 2 3 5 8 10 30 120 121 121 121 

Census Region South 348 0 1 3 4 5 6.5 10 20 45 120 121 121 

Census Region West 206 2 2 3 4 5 8 10 20 70 121 121 121 

Day of Week Weekday 634 1 2 3 4 5 7 10 30 121 121 121 121 

Day of Week Weekend 333 1 1 3 4 5 5 10 15 30 120 121 121 

Season Winter 236 1 1 3 4 5 6 10 20 60 121 121 121 

Season Spring 232 2 2 3 5 5 7.5 15 30 120 121 121 121 

Season Summer 282 0 2 3 4 5 10 10 30 120 121 121 121 

Season Fall 217 1 2 2 3 5 5 10 15 35 121 121 121 

Asthma No 892 1 2 3 4 5 7 10 25 90 121 121 121 

Asthma Yes 74 0 2 2 3 5 5 10 30 120 121 121 121 

Angina No 947 1 2 3 4 5 6 10 30 90 121 121 121 

Angina Yes 17 3 3 3 4 10 10 15 15 121 121 121 121 

Bronchitis/Emphysema No 920 1 2 3 4 5 7 10 25 60 121 121 121 

Bronchitis/Emphysema Yes 45 2 2 2 3 5 5 15 120 120 121 121 121 

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: Tsang and Klepeis, 1996. 
Table 15-40. Number of Minutes Spent at Home While the Windows Were Left Open (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 1960 2 10 30 180 360 840 961 961 961 961 961 961 

Gender Male 893 5 10 30 180 360 840 961 961 961 961 961 961 

Gender Female 1067 2 10 30 119 360 840 961 961 961 961 961 961 

Age (years) 1-4 99 0 1 10 180 180 600 961 961 961 961 961 961 

Age (years) 5-11 159 3 10 20 60 360 600 961 961 961 961 961 961 

Age (years) 12-17 101 2 5 24 180 360 600 961 961 961 961 961 961 

Age (years) 18-64 1282 6 16 60 180 360 840 961 961 961 961 961 961 

Age (years) > 64 282 1 5 30 180 360 840 961 961 961 961 961 961 

Race White 1558 2 10 30 180 360 840 961 961 961 961 961 961 

Race Black 208 3 10 30 180 360 840 961 961 961 961 961 961 

Race Asian 47 10 10 16 180 360 600 961 961 961 961 961 961 

Race Some Others 44 1 1 60 90 180 600 961 961 961 961 961 961 

Race Hispanic 80 2 20 30 60 360 600 961 961 961 961 961 961 

Hispanic No 1775 2 10 30 180 360 840 961 961 961 961 961 961 

Hispanic Yes 156 20 20 30 180 180 840 961 961 961 961 961 961 

Employment Full Time 822 5 15 30 180 360 840 961 961 961 961 961 961 

Employment Part Time 190 1 7 30 60 180 840 961 961 961 961 961 961 

Employment Not Employed 576 5 10 60 180 360 840 961 961 961 961 961 961 

Education < High School 163 1 6 30 90 360 840 961 961 961 961 961 961 

Education High School Graduate 542 2 10 60 180 360 840 961 961 961 961 961 961 

Education < College 408 5 15 30 119 360 840 961 961 961 961 961 961 

Education College Graduate 247 15 15 60 100 360 840 961 961 961 961 961 961 

Education Post Graduate 216 10 10 30 180 360 840 961 961 961 961 961 961 

Census Region Northeast 498 3 10 30 119 360 840 961 961 961 961 961 961 

Census Region Midwest 390 5 10 60 180 360 840 961 961 961 961 961 961 

Census Region South 494 1 6 30 90 360 600 961 961 961 961 961 961 

Census Region West 578 2 10 30 180 360 840 961 961 961 961 961 961 

Day of Week Weekday 1285 3 10 30 180 360 840 961 961 961 961 961 961 

Day of Week Weekend 675 2 10 30 119 360 840 961 961 961 961 961 961 

Season Winter 308 1 2 10 24 180 360 961 961 961 961 961 961 

Season Spring 661 10 20 60 180 360 600 961 961 961 961 961 961 

Season Summer 680 10 30 180 180 600 961 961 961 961 961 961 961 

Season Fall 311 3 5 30 60 180 600 961 961 961 961 961 961 

Asthma No 1809 2 10 30 180 360 840 961 961 961 961 961 961 

Asthma Yes 145 5 10 60 118 360 840 961 961 961 961 961 961 

Angina No 1902 3 10 30 180 360 840 961 961 961 961 961 961 

Angina Yes 49 1 1 24 30 180 961 961 961 961 961 961 961 

Bronchitis/Emphysema No 1850 2 10 30 180 360 840 961 961 961 961 961 961 

Bronchitis/Emphysema Yes 100 5 15 35 180 480 961 961 961 961 961 961 961 

Note: Values of "180", "360", "600","840" and "961" for number of minutes signify that 2-4 hours, 4-8 hours, 8-12 hours, 12-16 hours, 

and more than 16 hours, respectively, were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a 

given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-41. Number of Minutes the Outside Door Was Left Open While at Home (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 1170 0 1 5 10 60 180 600 600 721 721 721 721 

Gender Male 505 0 1 3 10 60 180 600 600 721 721 721 721 

Gender Female 665 1 1 5 10 60 180 600 600 721 721 721 721 

Age (years) 1-4 68 0 0 2 10 30 180 360 721 721 721 721 721 

Age (years) 5-11 109 0 1 3 10 60 180 600 600 600 721 721 721 

Age (years) 12-17 79 0 1 3 5 60 180 360 600 721 721 721 721 

Age (years) 18-64 718 1 1 3 10 60 180 600 600 721 721 721 721 

Age (years) > 64 180 1 1 10 20 180 360 600 721 721 721 721 721 

Race White 968 0 1 5 10 60 180 600 600 721 721 721 721 

Race Black 100 1 2.5 5.5 13 60 180 600 600 600 660.5 721 721 

Race Asian 23 1 1 2 60 180 360 600 600 721 721 721 721 

Race Some Others 22 1 1 1 15 30 180 600 600 721 721 721 721 

Race Hispanic 45 0 0 5 5 45 180 360 600 600 721 721 721 

Hispanic No 1073 0 1 3 10 60 180 600 600 721 721 721 721 

Hispanic Yes 81 0 1 5 10 45 180 360 600 600 721 721 721 

Employment Full Time 451 1 1 3 10 60 180 600 600 721 721 721 721 

Employment Part Time 93 0 3 5 15 60 180 600 600 721 721 721 721 

Employment Not Employed 362 1 1 5 10 60 360 600 600 721 721 721 721 

Education < High School 96 1 1 2 11 75 360 600 600 721 721 721 721 

Education High School Graduate 309 1 3 5 10 60 180 600 600 721 721 721 721 

Education < College 225 0 1 3 10 60 180 600 600 721 721 721 721 

Education College Graduate 150 0 0.5 1 15 60 180 600 600 721 721 721 721 

Education Post Graduate 124 2 2 3 5 30 180 600 600 721 721 721 721 

Census Region Northeast 223 1 2 5 10 90 180 600 600 721 721 721 721 

Census Region Midwest 221 0 0 2 10 60 180 600 600 721 721 721 721 

Census Region South 361 1 1 5 10 60 180 360 600 600 721 721 721 

Census Region West 365 0 1 5 15 60 180 600 600 721 721 721 721 

Day of Week Weekday 732 0 1 5 10 60 180 600 600 721 721 721 721 

Day of Week Weekend 438 1 1 5 10 60 180 600 600 721 721 721 721 

Season Winter 184 0 0 2 3 10 60 180 600 600 600 600 600 

Season Spring 407 1 1 5 20 180 360 600 600 721 721 721 721 

Season Summer 385 0 2 10 30 180 360 600 721 721 721 721 721 

Season Fall 194 1 1 2 10 30 180 360 600 600 600 600 600 

Asthma No 1072 0 1 5 10 60 180 600 600 721 721 721 721 

Asthma Yes 97 1 1 3 6 30 180 600 600 721 721 721 721 

Angina No 1133 0 1 5 10 60 180 600 600 721 721 721 721 

Angina Yes 36 1 1 3 10 104.5 360 360 600 721 721 721 721 

Bronchitis/emphysema No 1105 0 1 3 10 60 180 600 600 721 721 721 721 

Bronchitis/emphysema Yes 63 5 5 10 10 90 180 600 600 600 721 721 721 

Note: Values of "180", "360","600", and "721" for number of minutes signify that 2-4 hours, 4-8 hours, 8-12 hours, and over 12 hours, 

respectively, were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-42. Number of Times an Outside Door Was Opened in the Home at Specified Daily Frequencies by the Number of Respondents 

Times/Day 

Total N 1-2 3-5 6-9 10-19 20+ DK 

Overall 1187 192 248 229 267 196 55 

Gender 

Male 511 80 96 100 118 93 24 

Female 676 112 152 129 149 103 31 

Age (years) * 19 6 3 2 3 1 4 

1-4 68 13 14 8 17 13 3 

5-11 109 15 16 18 31 23 6 

12-17 79 11 17 17 13 17 4 

18-64 730 112 145 156 171 123 23 

> 64 182 35 53 28 32 19 15 

Race 

White 979 155 193 188 233 168 42 

Black 103 22 28 21 12 14 6 

Asian 23 1 9 4 6 2 1 

Some Others 22 3 4 2 7 4 2 

Hispanic 46 8 11 10 8 8 1 

Refused 14 3 3 4 1 * 3 

Hispanic No 1086 179 227 208 244 180 48 

Yes 83 11 17 16 20 15 4 

DK 7 * 2 1 3 1 * 

Refused 11 2 2 4 * * 3 

Employment * 255 40 46 43 60 53 13 

Full Time 458 79 98 95 104 72 10 

Part Time 95 14 20 19 22 18 2 

Not Employed 369 58 81 69 80 52 29 

Refused 10 1 3 3 1 1 1 

Education 

* 267 42 48 46 63 54 14 

< High School 98 21 17 15 18 20 7 

High School Graduate 318 48 66 65 71 54 14 

< College 228 44 52 37 49 34 12 

College Graduate 150 21 37 39 31 19 3 

Post Graduate 126 16 28 27 35 15 5 

Census Region Northeast 228 37 38 49 53 38 13 

Midwest 225 44 54 39 50 33 5 

South 365 59 81 69 71 66 19 

West 369 52 75 72 93 59 18 

Day of Week Weekday 746 116 167 156 167 106 34 

Weekend 441 76 81 73 100 90 21 

Season 

Winter 185 19 51 39 42 27 7 

Spring 417 73 94 66 90 73 21 

Summer 387 72 68 81 80 66 20 

Fall 198 28 35 43 55 30 7 

Asthma 

No 1087 175 228 211 245 179 49 

Yes 99 16 20 18 22 17 6 

DK 1 1 * * * * * 

Angina No 1147 183 241 221 259 192 51 

Yes 39 8 7 8 8 4 4 

DK 1 1 * * * * * 

Bronchitis/emphysema No 1121 179 230 216 258 186 52 

Yes 64 12 18 12 9 10 3 

DK 2 1 * 1 * * * 

Note: * Signifies missing data; "DK" = respondent answered don't know; N = sample size; Refused = respondent refused to answer.

Source: Tsang and Klepeis, 1996 
Table 15-43. Number of Minutes Spent Running, Walking, or Standing Alongside a Road with Heavy Traffic (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 401 0 1 2 2 5 15 30 60 121 121 121 121 

Gender Male 202 1 1 2 3 5 17.5 45 120 121 121 121 121 

Gender Female 198 0 0 1 2 5 10 30 60 120 121 121 121 

Age (years) 1-4 12 1 1 1 2 4 7.5 30 60 60 60 60 60 

Age (years) 5-11 20 1 1 1.5 2 5 6 12.5 25 60 90 90 90 

Age (years) 12-17 27 0 0 2 2 4 5 30 60 90 120 120 120 

Age (years) 18-64 304 0 1 1 2 5 15 30 90 121 121 121 121 

Age (years) > 64 31 2 2 2 4 5 20 45 60 121 121 121 121 

Race White 306 0 1 2 2 5 15 30 110 121 121 121 121 

Race Black 51 0 0 1 1 3 7 30 50 60 60 121 121 

Race Asian 10 3 3 3 4 5 7.5 15 17.5 20 20 20 20 

Race Some Others 7 2 2 2 2 5 10 45 121 121 121 121 121 

Race Hispanic 24 2 2 2 3 10 17.5 40 60 60 120 120 120 

Hispanic No 356 0 1 1 2 5 15 30 90 121 121 121 121 

Hispanic Yes 43 1 1 2 2 5 10 30 60 120 121 121 121 

Employment Full Time 214 0 1 1 2 5 15 30 120 121 121 121 121 

Employment Part Time 50 0 0.5 2 2 5 15 30 90 121 121 121 121 

Employment Not Employed 76 0 1 2 3 5.5 15 30 60 110 120 121 121 

Education < High School 18 4 4 4 5 6 10 15 30 121 121 121 121 

Education High School Graduate 106 1 1 2 2 5 15 60 121 121 121 121 121 

Education < College 84 0 0 1 3 5.5 20 40 120 121 121 121 121 

Education College Graduate 79 0 1 1 2 5 15 30 60 90 121 121 121 

Education Post Graduate 50 1 1 2 2 5 10 20 52.5 90 120 120 120 

Census Region Northeast 129 1 1 2 2 5 20 50 120 121 121 121 121 

Census Region Midwest 83 0 0 1 2 5 10 20 60 121 121 121 121 

Census Region South 105 0 0 1 2 5 15 30 90 121 121 121 121 

Census Region West 84 1 2 2 3 5 15 30 60 120 121 121 121 

Day of Week Weekday 303 0 0 2 2 5 15 30 60 120 121 121 121 

Day of Week Weekend 98 1 1 2 3 5 15 30 121 121 121 121 121 

Season Winter 104 0 0 1 2 4.5 10 20 60 110 121 121 121 

Season Spring 114 1 1 2 2 6 20 60 120 121 121 121 121 

Season Summer 104 0 1 2 2 5 10 30 60 121 121 121 121 

Season Fall 79 0 1 2 3 5 20 35 120 121 121 121 121 

Asthma No 370 0 1 2 2 5 15 30 60 121 121 121 121 

Asthma Yes 31 0 0 1 2 5 15 30 120 121 121 121 121 

Angina No 393 0 1 2 2 5 15 30 90 121 121 121 121 

Angina Yes 8 2 2 2 2 6.5 17.5 30 60 60 60 60 60 

Bronchitis/Emphysema No 378 0 1 1 2 5 15 30 60 121 121 121 121 

Bronchitis/Emphysema Yes 22 2 2 5 5 5 17.5 30 121 121 121 121 121 

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: Tsang and Klepeis,1996 
Table 15-44. Number of Minutes Spent in a Car, Van, Truck, or Bus in Heavy Traffic (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 1197 1 2 5 5 10 20 60 120 121 121 121 121 

Gender Male 534 1 2 4 5 10 20 60 120 121 121 121 121 

Gender Female 663 1 2 5 5 10 25 60 120 121 121 121 121 

Age (years) 1-4 33 4 4 5 5 10 15 30 60 60 121 121 121 

Age (years) 5-11 63 1 2 5 5 10 20 45 60 120 121 121 121 

Age (years) 12-17 52 3 3 4 5 9 12.5 27.5 90 120 120 121 121 

Age (years) 18-64 889 1 2 5 5 10 25 60 120 121 121 121 121 

Age (years) > 64 139 3 3 5 5 15 30 60 121 121 121 121 121 

Race White 959 1 2 4 5 10 25 60 120 121 121 121 121 

Race Black 133 2 3 5 5 10 20 40 90 120 121 121 121 

Race Asian 20 5 5 5 5 11 20 30 45 52.5 60 60 60 

Race Some Others 24 5 5 10 10 12.5 30 60 90 120 121 121 121 

Race Hispanic 55 1 2 5 5 10 20 60 120 121 121 121 121 

Hispanic No 1097 1 2 5 5 10 20 60 120 121 121 121 121 

Hispanic Yes 95 1 2 5 5 10 20 90 121 121 121 121 121 

Employment Full Time 659 1 2 5 5 10 30 60 120 121 121 121 121 

Employment Part Time 108 2 2 4 5 10 20 48.5 121 121 121 121 121 

Employment Not Employed 279 1 2 5 5 10 30 60 120 121 121 121 121 

Education < High School 81 0 3 5 10 10 20 40 121 121 121 121 121 

Education High School Graduate 352 1 2 5 5 10 30 60 120 121 121 121 121 

Education < College 276 1 2 3 5 15 30 60 120 121 121 121 121 

Education College Graduate 176 1 2 4 5 12.5 30 60 120 121 121 121 121 

Education Post Graduate 150 2 2 5 5 10 20 60 97.5 120 121 121 121 

Census Region Northeast 229 2 2 4 5 10 20 60 120 121 121 121 121 

Census Region Midwest 263 2 2 5 5 10 30 45 120 121 121 121 121 

Census Region South 429 1 2 5 5 10 30 60 120 121 121 121 121 

Census Region West 276 1 2 5 5 10 20 60 120 121 121 121 121 

Day of Week Weekday 927 1 2 5 5 10 20 60 120 121 121 121 121 

Day of Week Weekend 270 2 2 5 5 10 25 60 120 121 121 121 121 

Season Winter 286 1 2 5 5 10 20 60 120 121 121 121 121 

Season Spring 317 1 2 5 5 10 30 60 120 121 121 121 121 

Season Summer 312 1 3 5 5 10 30 60 120 121 121 121 121 

Season Fall 282 2 2 4 5 10 20 45 120 121 121 121 121 

Asthma No 1108 1 2 5 5 10 20 60 120 121 121 121 121 

Asthma Yes 89 2 2 5 5 10 30 60 121 121 121 121 121 

Angina No 1159 1 2 5 5 10 20 60 120 121 121 121 121 

Angina Yes 35 0 0 5 5 10 30 70 121 121 121 121 121 

Bronchitis/emphysema No 1130 2 2 5 5 10 20 60 120 121 121 121 121 

Bronchitis/emphysema Yes 64 1 1 2 5 10 27.5 51 120 121 121 121 121 

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: Tsang and Klepeis,1996 
Table 15-45. Number of Minutes Spent in a Parking Garage or Indoor Parking Lot (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 294 0 1 1 2 3 5 10 30 60 121 121 121 

Gender Male 138 1 1 1 2 4 5 15 60 121 121 121 121 

Gender Female 156 0 1 1 2 3 5 10 20 40 60 120 121 

Age (years) 1-4 8 0 0 0 0 2 3.5 5 10 10 10 10 10 

Age (years) 5-11 15 1 1 1 2 3 5 10 45 60 60 60 60 

Age (years) 12-17 20 0 0 0.5 1.5 2 7.5 15 45 90.5 121 121 121 

Age (years) 18-64 229 1 1 2 2 5 5 10 30 60 121 121 121 

Age (years) > 64 18 0 0 0 2 3 5 15 45 90 90 90 90 

Race White 208 1 1 2 2 3 5 10 30 60 121 121 121 

Race Black 34 0 0 1 1 5 5 15 20 30 30 30 30 

Race Asian 15 2 2 2 2 2 10 60 120 121 121 121 121 

Race Some Others 7 3 3 3 3 3 5 15 121 121 121 121 121 

Race Hispanic 28 1 1 1 2 4.5 10 20 60 120 121 121 121 

Hispanic No 251 0 1 1 2 3 5 10 30 60 120 121 121 

Hispanic Yes 39 1 1 1 3 5 10 30 121 121 121 121 121 

Employment Full Time 171 1 1 1 2 3 5 10 30 60 121 121 121 

Employment Part Time 23 2 2 5 5 5 5 10 30 60 121 121 121 

Employment Not Employed 58 0 1 1 2 4 10 20 40 120 121 121 121 

Education < High School 13 0 0 0 5 5 10 10 30 121 121 121 121 

Education High School Graduate 58 1 1 1 2 3 9.5 30 90 121 121 121 121 

Education < College 54 1 1 2 2 4 5 15 40 120 120 121 121 

Education College Graduate 72 1 1 2 2 4.5 5 10 15 60 120 121 121 

Education Post Graduate 50 1 1 2 2 5 5 10 12.5 20 40 60 60 

Census Region Northeast 53 2 2 2 2 5 6 10 30 90 121 121 121 

Census Region Midwest 59 0 0 1 2 3 5 10 30 60 121 121 121 

Census Region South 92 1 1 2 2 3.5 5 10 30 60 121 121 121 

Census Region West 90 0 1 1 1.5 4 5 15 45 60 121 121 121 

Day of Week Weekday 208 0 1 1 2 3 5 10 30 60 121 121 121 

Day of Week Weekend 86 1 1 2 2 5 7 15 30 60 121 121 121 

Season Winter 67 0 1 1 2 3 5 10 20 30 120 121 121 

Season Spring 78 0 1 1 2 3 5.5 15 60 120 121 121 121 

Season Summer 85 0 1 2 2 5 5 15 30 90 121 121 121 

Season Fall 64 1 1 2 2 4.5 5 10 30 45 121 121 121 

Asthma No 263 1 1 2 2 3 5 10 30 60 121 121 121 

Asthma Yes 30 0 0 1 1 4 7 10 30 121 121 121 121 

Angina No 291 0 1 1 2 4 5 10 30 60 121 121 121 

Angina Yes 2 3 3 3 3 3 46.5 90 90 90 90 90 90 

Bronchitis/emphysema No 281 0 1 1 2 3 5 10 30 60 121 121 121 

Bronchitis/emphysema Yes 12 2 2 2 5 5 5.5 10 60 120 120 120 120 

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: Tsang and Klepeis,1996 
Table 15-46. Number of Minutes Spent Walking Outside to a Car in the Driveway or Outside Parking Areas (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 3303 0 0 0 0 2 5 10 20 30 60 121 121 

Gender Male 1511 0 0 0 0 2 4 10 20 30 60 121 121 

Gender Female 1791 0 0 0 0 2 5 10 20 30 60 60 121 

Age (years) 1-4 132 0 0 0 0 1.5 2 5 15 20 30 60 121 

Age (years) 5-11 245 0 0 0 0 1 2 5 15 30 45 80 121 

Age (years) 12-17 202 0 0 0 0 1 5 10 20 30 30 60 121 

Age (years) 18-64 2303 0 0 0 0 2 5 10 20 30 60 120 121 

Age (years) > 64 373 0 0 0 1 2 5 10 15 30 30 88 121 

Race White 2756 0 0 0 0 2 5 10 20 30 60 120 121 

Race Black 279 0 0 0 0 1 3 5 10 20 30 45 88 

Race Asian 53 0 0 0 0 1 3 10 15 30 32 45 45 

Race Some Others 63 0 0 0 0 2 5 10 30 30 60 120 120 

Race Hispanic 127 0 0 1 1 2 5 10 20 60 120 121 121 

Hispanic No 3029 0 0 0 0 2 5 10 20 30 60 120 121 

Hispanic Yes 235 0 0 0 0 2 5 10 20 60 120 121 121 

Employment Full Time 1613 0 0 0 0 2 5 10 20 30 60 120 121 

Employment Part Time 312 0 0 0 1 2 5 10 20 45 120 121 121 

Employment Not Employed 785 0 0 0 0 2 5 10 20 30 60 60 121 

Education < High School 241 0 0 0 0 2 4 10 20 30 110 121 121 

Education High School Graduate 935 0 0 0 0 2 5 10 20 30 60 121 121 

Education < College 680 0 0 0 1 2 5 10 20 30 60 120 121 

Education College Graduate 445 0 0 0 0 2 5 10 20 30 60 60 121 

Education Post Graduate 381 0 0 0 1 2 5 10 15 25 30 120 121 

Census Region Northeast 680 0 0 0 0 2 5 10 15 30 60 90 121 

Census Region Midwest 763 0 0 0 1 2 5 10 15 30 60 120 121 

Census Region South 1149 0 0 0 0 2 4 10 20 30 60 90 121 

Census Region West 711 0 0 0 0 2 5 10 20 30 60 120 121 

Day of Week Weekday 2209 0 0 0 0 2 5 10 20 30 60 120 121 

Day of Week Weekend 1094 0 0 0 0 2 5 10 20 30 60 120 121 

Season Winter 855 0 0 0 0 1 4 10 15 30 30 100 121 

Season Spring 890 0 0 0 0 2 5 10 20 30 100 120 121 

Season Summer 903 0 0 0 0 2 4 10 20 30 60 60 121 

Season Fall 655 0 0 0 1 2 5 10 15 30 45 110 121 

Asthma No 3063 0 0 0 0 2 5 10 20 30 60 120 121 

Asthma Yes 234 0 0 0 1 2 5 10 15 30 120 121 121 

Angina No 3219 0 0 0 0 2 5 10 20 30 60 120 121 

Angina Yes 72 0 0 0 0 2 5 10 15 30 45 110 110 

Bronchitis/Emphysema No 3132 0 0 0 0 2 5 10 20 30 60 120 121 

Bronchitis/Emphysema Yes 162 0 0 0 0 2 5 10 20 30 110 121 121 

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: Tsang and Klepeis,1996 
Table 15-47. Number of Minutes Spent Running or Walking Outside Other Than to the Car (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 1273 1 1 3 5 15 45 120 121 121 121 121 121 

Gender Male 605 2 2 5 10 20 60 121 121 121 121 121 121 

Gender Female 668 0 1 2 5 15 30 116 121 121 121 121 121 

Age (years) 1-4 82 3 3 5 10 30 120 121 121 121 121 121 21 

Age (yeaars) 5-11 149 4 5 5 10 30 120 121 121 121 121 121 21 

Age (years) 12-17 110 5 5 5 10 15 60 121 121 121 121 121 121 

Age (years) 18-64 772 0 1 2 5 15 30 120 121 121 121 121 121 

Age (years) 5:> 64 143 1 1 2 5 15 30 60 121 121 121 121 121 

Race White 1051 1 1 3 5 15 45 121 121 121 121 121 121 

Race Black 111 0 1 3 5 15 35 120 121 121 121 121 121 

Race Asian 21 2 2 10 10 15 30 70 120 121 121 121 121 

Race Some Others 23 5 5 10 15 20 60 121 121 121 121 121 121 

Race 5:hispanic 55 2 3 8 10 20 40 90 121 121 121 121 121 

Hispanic No 1156 1 1 3 5 15 45 120 121 121 121 121 121 

Hispanic Yes 99 1 2 2 10 20 60 121 121 121 121 121 121 

Employment Full Time 517 0 1 2 5 15 30 120 121 121 121 121 121 

Employment Part Time 112 1 2 2 5 15 30 90 121 121 121 121 121 

Employment Not Employed 300 1 1 3 5 15 30 120 121 121 121 121 121 

Education < High School 97 0 1 3 5 15 30 90 121 121 121 121 121 

Education High School Graduate 287 0 0 2 5 15 30 120 121 121 121 121 121 

Education < College 234 1 1 2 5 15 30 120 121 121 121 121 121 

Education College Graduate 153 1 2 5 10 20 45 120 121 121 121 121 121 

Education Post Graduate 138 1 1 3 5 15 37.5 90 121 121 121 121 121 

Census Region Northeast 265 1 1 3 5 20 45 120 121 121 121 121 121 

Census Region Midwest 286 1 2 5 5 15 40 121 121 121 121 121 121 

Census Region South 412 1 1 3 5 15 45 121 121 121 121 121 121 

Census Region West 310 1 1 3 5.5 15 45 120 121 121 121 121 121 

Day of Week Weekday 843 1 1 3 5 15 40 120 121 121 121 121 121 

Day of Week Weekend 430 1 2 4 5 20 60 121 121 121 121 121 21 

Season Winter 312 0 2 2 5 10 42.5 90 121 121 121 121 21 

Season Spring 403 1 2 4 10 20 60 121 121 121 121 121 121 

Season Summer 396 1 1 3 10 20 55 121 121 121 121 121 21 

Season Fall 162 1 1 2 5 15 30 120 121 121 121 121 121 

Asthma No 1162 1 1 3 5 15 45 120 121 121 121 121 21 

Asthma Yes 105 2 4 5 6 15 45 121 121 121 121 121 21 

Angina No 1240 1 1 3 5 15 45 120 121 121 121 121 121 

Angina Yes 25 1 1 5 5 15 45 121 121 121 121 121 121 

Bronchitis/Emphysema No 1204 1 1 3 5 15 45 120 121 121 121 121 121 

Bronchitis/Emphysema Yes 62 1 2 4 5 15 30 120 121 121 121 121 121 

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: Tsang and Klepeis,1996 
Table 15-48. Number of Hours Spent Working for Pay (hours/week) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 4896 0 0 0 12 33 40 50 60 61 61 61 61 

Gender Male 2466 0 0 0 18 40 40 53 61 61 61 61 61 

Gender Female 2430 0 0 0 6 28 40 43 55 60 61 61 61 

Age (years) 1-4 0 * * * * * * * * * * * * 

Age (years) 5-11 0 * * * * * * * * * * * * 

Age (years) 12-17 14 0 0 0 1 9 18.5 24 26 31 31 31 31 

Age (years) 18-64 4625 0 0 0 15 35 40 50 60 61 61 61 61 

Age (years) > 64 181 0 0 0 0 5 21 40 50 61 61 61 61 

Race White 3990 0 0 0 10 32 40 50 60 61 61 61 61 

Race Black 499 0 0 0 18 35 40 46 60 61 61 61 61 

Race Asian 76 0 0 0 7 36.5 40 50 61 61 61 61 61 

Race Some Others 87 0 0 0 0 30 40 50 60 61 61 61 61 

Race Hispanic 194 0 0 0 15 32 40 48 60 60 61 61 61 

Hispanic No 4494 0 0 0 12 33 40 50 60 61 61 61 61 

Hispanic Yes 341 0 0 0 8 32 40 50 60 61 61 61 61 

Employment Full Time 4094 0 0 0 30 40 40 50 60 61 61 61 61 

Employment Part Time 802 0 0 0 0 10 20 30 38 40 61 61 61 

Employment Not Employed 0 * * * * * * * * * * * * 

Education < High School 308 0 0 0 1 21 40 48 61 61 61 61 61 

Education High School Graduate 1598 0 0 0 12 32 40 48 60 61 61 61 61 

Education < College 1251 0 0 0 15 30 40 50 60 61 61 61 61 

Education College Graduate 954 0 0 0 16 40 40 50 60 61 61 61 61 

Education Post Graduate 716 0 0 0 10 35 40 50 60 61 61 61 61 

Census Region Northeast 1096 0 0 0 14 32 40 50 60 61 61 61 61 

Census Region Midwest 1118 0 0 0 12 32 40 50 60 61 61 61 61 

Census Region South 1675 0 0 0 12 35 40 50 60 61 61 61 61 

Census Region West 1007 0 0 0 9 30 40 50 60 61 61 61 61 

Day of Week Weekday 3306 0 0 0 10 33 40 50 60 61 61 61 61 

Day of Week Weekend 1590 0 0 0 12 33 40 48 60 61 61 61 61 

Season Winter 1306 0 0 0 10 32 40 50 60 61 61 61 61 

Season Spring 1197 0 0 0 15 35 40 50 60 61 61 61 61 

Season Summer 1343 0 0 0 3 33 40 48 60 61 61 61 61 

Season Fall 1050 0 0 0 14.5 32 40 50 60 61 61 61 61 

Asthma No 4579 0 0 0 12 34 40 50 60 61 61 61 61 

Asthma Yes 302 0 0 0 9 30 40 48 60 61 61 61 61 

Angina No 4811 0 0 0 12 34 40 50 60 61 61 61 61 

Angina Yes 66 0 0 0 0 20 40 44 60 61 61 61 61 

Bronchitis/Emphysema No 4699 0 0 0 12 33 40 50 6 61 61 61 61 

Bronchitis/Emphysema Yes 182 0 0 0 6 30 40 48 60 61 61 61 61 

Note: * Signifies missing data. A value of "61" for number of hours signifies that more than 60 hours were spent. N = doer sample size. 

Percentiles are the percentage of doers below or equal to a given number of hours. 

Source: Tsang and Klepeis, 1996. 
Table 15-49. Number of Hours Spent Working for Pay Between 6PM and 6AM (hours/week) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 4894 0 0 0 0 0 0 8 30 45 61 61 61 

Gender Male 2465 0 0 0 0 0 0 10 35 50 61 61 61 

Gender Female 2429 0 0 0 0 0 0 5 20 39 61 61 61 

Age (years) 1-4 0 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 5-11 0 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 12-17 14 0 0 0 0 0 4.5 20 24 25 25 25 25 

Age (years) 18-64 4623 0 0 0 0 0 0 8 30 42 61 61 61 

Age (years) > 64 181 0 0 0 0 0 0 0 20 61 61 61 61 

Race White 3989 0 0 0 0 0 0 8 25 40 61 61 61 

Race Black 499 0 0 0 0 0 0 10 40 61 61 61 61 

Race Asian 75 0 0 0 0 0 0 12 30 61 61 61 61 

Race Some Others 87 0 0 0 0 0 0 7 25 45 61 61 61 

Race Hispanic 194 0 0 0 0 0 0 15 35 48 61 61 61 

Hispanic No 4492 0 0 0 0 0 0 8 27 40 61 61 61 

Hispanic Yes 341 0 0 0 0 0 0 13 35 50 61 61 61 

Employment Full Time 4092 0 0 0 0 0 0 8 30 45 61 61 61 

Employment Part Time 802 0 0 0 0 0 0 6 20 35 61 61 61 

Employment Not Employed 0 0 0 0 0 0 0 0 0 0 0 0 0 

Education < High School 308 0 0 0 0 0 0 11 50 61 61 61 61 

Education High School Graduate 1597 0 0 0 0 0 0 8 35 50 61 61 61 

Education < College 1251 0 0 0 0 0 0 9 26 40 60 61 61 

Education College Graduate 953 0 0 0 0 0 0 8 20 40 61 61 61 

Education Post Graduate 716 0 0 0 0 0 0 7 20 30 61 61 61 

Census Region Northeast 1096 0 0 0 0 0 0 7 24 40 61 61 61 

Census Region Midwest 1118 0 0 0 0 0 0 10 30 42 61 61 61 

Census Region South 1674 0 0 0 0 0 0 7 30 48 61 61 61 

Census Region West 1006 0 0 0 0 0 0 10 30 47 61 61 61 

Day of Week Weekday 3306 0 0 0 0 0 0 8 30 48 61 61 61 

Day of Week Weekend 1588 0 0 0 0 0 0 7 28 40 61 61 61 

Season Winter 1305 0 0 0 0 0 0 8 28 40 61 61 61 

Season Spring 1197 0 0 0 0 0 0 8 30 48 61 61 61 

Season Summer 1342 0 0 0 0 0 0 9 30 48 61 61 61 

Season Fall 1050 0 0 0 0 0 0 7 25 40 61 61 61 

Asthma No 4578 0 0 0 0 0 0 8 30 45 61 61 61 

Asthma Yes 301 0 0 0 0 0 0 8 28 36 61 61 61 

Angina No 4809 0 0 0 0 0 0 8 30 44 61 61 61 

Angina Yes 66 0 0 0 0 0 0 7 36 40 61 61 61 

Bronchitis/Emphysema No 4697 0 0 0 0 0 0 8 30 43 61 61 61 

Bronchitis/Emphysema Yes 182 0 0 0 0 0 0 10 40 50 61 61 61 

Note: A Value of "61" for number of hours signifies that more than 60 hours were spent. N = doer sample size. Percentiles are the 

percentage of doers below or equal to a given number of hours. 

Source: Tsang and Klepeis, 1996. 
Table 15-50. Number of Hours Worked in a Week That Was Outdoors (hours/week) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 4891 0 0 0 0 0 0 1 30 50 61 61 61 

Gender Male 2463 0 0 0 0 0 0 16 42 60 61 61 61 

Gender Female 2428 0 0 0 0 0 0 0 2 12 55 61 61 

Age (years) 1-4 0 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 5-11 0 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 12-17 14 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 18-64 4621 0 0 0 0 0 0 1 30 50 61 61 61 

Age (years) > 64 181 0 0 0 0 0 0 2 29 60 61 61 61 

Race White 3986 0 0 0 0 0 0 2 30 50 61 61 61 

Race Black 499 0 0 0 0 0 0 0 25 48 61 61 61 

Race Asian 75 0 0 0 0 0 0 0 3 30 40 61 61 

Race Some Others 87 0 0 0 0 0 0 1 17 40 48 61 61 

Race Hispanic 194 0 0 0 0 0 0 2 30 50 61 61 61 

Hispanic No 4489 0 0 0 0 0 0 1 30 48 61 61 61 

Hispanic Yes 341 0 0 0 0 0 0 2 35 60 61 61 61 

Employment Full Time 4090 0 0 0 0 0 0 2 35 50 61 61 61 

Employment Part Time 801 0 0 0 0 0 0 0 15 30 61 61 61 

Employment Not Employed 0 0 0 0 0 0 0 0 0 0 0 0 0 

Education < High School 308 0 0 0 0 0 0 16.5 55 61 61 61 61 

Education High School Graduate 1594 0 0 0 0 0 0 6 40 60 61 61 61 

Education < College 1251 0 0 0 0 0 0 1 30 46 61 61 61 

Education College Graduate 953 0 0 0 0 0 0 0 20 35 50 61 61 

Education Post Graduate 716 0 0 0 0 0 0 0 4 15 60 61 61 

Census Region Northeast 1094 0 0 0 0 0 0 0 25 40 61 61 61 

Census Region Midwest 1117 0 0 0 0 0 0 0 30 50 61 61 61 

Census Region South 1674 0 0 0 0 0 0 2 32 55 61 61 61 

Census Region West 1006 0 0 0 0 0 0 2 33 50 61 61 61 

Day of Week Weekday 3305 0 0 0 0 0 0 1 32 50 61 61 61 

Day of Week Weekend 1586 0 0 0 0 0 0 1 30 48 61 61 61 

Season Winter 1305 0 0 0 0 0 0 0 25 50 61 61 61 

Season Spring 1195 0 0 0 0 0 0 2 30 50 61 61 61 

Season Summer 1341 0 0 0 0 0 0 2 36 50 61 61 61 

Season Fall 1050 0 0 0 0 0 0 0 30 45 61 61 61 

Asthma No 4576 0 0 0 0 0 0 1 30 50 61 61 61 

Asthma Yes 300 0 0 0 0 0 0 0 31 50 61 61 61 

Angina No 4806 0 0 0 0 0 0 1 30 50 61 61 61 

Angina Yes 66 0 0 0 0 0 0 4 35 50 61 61 61 

Bronchitis/Emphysema No 4694 0 0 0 0 0 0 1 30 50 61 61 61 

Bronchitis/Emphysema Yes 182 0 0 0 0 0 0 2 30 60 61 61 61 

NOTE: A value of "61" for number of hours signifies that more than 60 hours were spent. N = doer sample size. Percentiles are the 

percentage of doers below or equal to a given number of hours. 

Source: Tsang and Klepeis,1996 
Table 15-51. Number of Times Floors Were Swept or Vacuumed at Specified Frequencies by the Number of Respondents 

Number of Times 

Total N Almost Every Day 3-5/week 1-2/week 1-2/month < Often Never DK 

Overall 4663 921 1108 2178 373 48 10 25 

Gender 

Male 2163 415 520 976 201 27 5 19 

Female 2498 505 588 1201 172 21 5 6 

Refused 2 1 0 1 0 0 0 0 

Age (years) * 84 16 11 41 12 3 0 1 

1-4 263 96 74 88 4 0 0 1 

5-11 348 115 107 120 6 0 0 0 

12-17 326 82 83 144 15 2 0 0 

18-64 2972 524 723 1420 252 34 6 13 

> 64 670 88 110 365 84 9 4 10 

Race 

White 3774 641 879 1868 324 36 8 18 

Black 463 167 115 150 19 5 2 5 

Asian 77 11 15 39 8 3 0 1 

Some Others 96 26 29 32 8 1 0 0 

Hispanic 193 68 61 55 7 2 0 0 

Refused 60 8 9 34 7 1 0 1 

Hispanic No 4244 799 988 2035 345 43 9 25 

Yes 347 106 107 110 21 3 0 0 

DK 26 8 3 11 2 1 1 0 

Refused 46 8 10 22 5 1 0 0 

Employment * 926 290 267 342 24 2 0 1 

Full Time 2017 291 486 1018 184 27 2 9 

Part Time 379 82 82 177 34 1 0 3 

Not Employed 1309 256 263 626 127 18 8 11 

Refused 32 2 10 15 4 0 0 1 

Education 

* 1021 314 285 384 31 4 0 3 

< High School 399 110 91 162 20 6 2 8 

High School Graduate 1253 269 302 591 69 12 3 7 

< College 895 130 223 438 93 8 2 1 

College Graduate 650 64 132 346 93 9 3 3 

Post Graduate 445 34 75 257 67 9 0 3 

Census Region Northeast 1048 236 230 484 83 8 2 5 

Midwest 1036 156 249 527 86 10 2 6 

South 1601 376 403 707 93 11 2 9 

West 978 153 226 460 111 19 4 5 

Day of Week Weekday 3156 631 765 1458 248 33 5 16 

Weekend 1507 290 343 720 125 15 5 9 

Season 

Winter 1264 268 309 557 105 15 2 8 

Spring 1181 217 286 560 96 12 3 7 

Summer 1275 251 312 596 94 13 1 8 

Fall 943 185 201 465 78 8 4 2 

Asthma 

No 4287 821 1013 2030 351 39 10 23 

Yes 341 95 88 133 17 7 0 1 

DK 35 5 7 15 5 2 0 1 

Angina No 4500 892 1080 2098 352 44 10 24 

Yes 125 21 23 63 16 2 0 0 

DK 38 8 5 17 5 2 0 1 

Bronchitis/emphysema No 4424 871 1064 2063 349 44 9 24 

Yes 203 45 39 99 17 2 1 0 

DK 36 5 5 16 7 2 0 1 

Note: * Signifies missing data; DK = respondent answered don't know; N = sample size; Refused = respondent refused to answer. 

Source: Tsang and Klepeis, 1996 
Table 15-52. Number of Days Since the Floor Area in the Home Was Swept or Vacuumed by the Number of Respondents 

Number of Days since That Area Was Swept-vacuumed 

Swept- >2 

Total 0 Vacuumed 1 2 3 4 5 6 7 8 10 14 Weeks Dk 

N Yes'day 

Overall 9386 8112 550 278 189 85 63 31 17 26 2 1 5 16 11 

Gender 

Male 4294 3688 245 

Female 5088 4421 304 

Refused 4 3 1 

136 100 35 37 19 8 10 1 0 3 7 5 

142 89 50 26 12 9 16 1 1 2 9 6 

0 0 0 0 0 0 0 0 0 0 0 0 

Age (years)

* 187 180 1 

1-4 499 67 199 

5-11 703 393 121 

12-17 589 533 30 

18-64 6059 5592 198 

> 64 1349 1347 1 

0 3 1 0 0 0 0 0 0 0 1 1 

93 54 24 19 17 9 7 0 1 2 6 1 

70 50 23 22 8 2 4 1 0 2 2 5 

12 6 3 0 0 1 2 0 0 0 2 0 

102 76 34 22 6 5 13 1 0 1 5 4 

1 0 0 0 0 0 0 0 0 0 0 0 

Race 

White 7591 6586 398 

Black 945 825 72 

Asian 157 138 5 

Some Others 182 141 21 

Hispanic 385 300 52 

Refused 126 122 2 

232 152 72 55 29 14 24 2 1 5 13 8 

18 17 7 3 1 2 0 0 0 0 0 0 

6 2 2 1 0 0 1 0 0 0 1 1 

7 9 2 1 0 0 0 0 0 0 1 0 

15 9 2 2 0 1 1 0 0 0 1 2 

0 0 0 1 1 0 0 0 0 0 0 0 

Hispanic

No 8534 7421 460 

Yes 702 549 88 

Dk 47 42 1 

Refused 103 100 1 

248 170 80 57 29 15 24 2 1 5 14 8 

29 17 5 4 2 2 2 0 0 0 1 3 

1 1 0 1 0 0 0 0 0 0 1 0 

0 1 0 1 0 0 0 0 0 0 0 0 

Employment

* 1773 974 349 

Full Time 4096 3826 96 

Part Time 802 741 28 

Not Employed 2644 2502 77 

Refused 71 69 0 

175 112 50 41 25 12 13 1 1 4 9 7 

64 50 21 18 6 4 6 1 0 0 4 0 

10 8 6 2 0 0 4 0 0 1 1 1 

29 18 8 2 0 1 3 0 0 0 1 3 

0 1 0 0 0 0 0 0 0 0 1 0 

Education 

* 1968 1162 353 

< High School 834 793 24 

High School Graduate 2612 2447 76 

< College 1801 1681 55 

College Graduate 1247 1155 28 

Post Graduate 924 874 14 

175 114 50 41 25 12 13 1 1 4 10 7 

13 2 1 0 0 0 0 0 0 0 0 1 

39 26 9 7 1 2 0 1 0 0 2 2 

25 18 10 6 0 1 3 0 0 0 2 0 

19 17 10 5 3 1 7 0 0 0 1 1 

7 12 5 4 2 1 3 0 0 1 1 0 

Census Region

Northeast 2075 1793 129 

Midwest 2102 1826 108 

South 3243 2805 193 

West 1966 1688 120 

65 35 18 4 9 9 6 0 0 0 5 2 

59 47 21 17 7 2 6 2 1 2 2 2 

87 75 26 27 8 3 8 0 0 2 5 4 

67 32 20 15 7 3 6 0 0 1 4 3 

Day of Week

Weekday 6316 5487 366 160 125 57 51 18 13 15 2 1 4 11 6 

Weekend 3070 2625 184 118 64 28 12 13 4 11 0 0 1 5 5 

Season 

Winter 2524 2144 162 

Spring 2438 2112 121 

Summer 2536 2187 167 

Fall 1888 1669 100 

79 61 27 17 7 3 13 0 0 1 5 5 

90 48 19 19 9 7 4 0 0 2 5 2 

68 41 26 19 12 3 3 0 1 2 4 3 

41 39 13 8 3 4 6 2 0 0 2 1 

Asthma 

No 8629 7455 502 

Yes 694 596 48 

Dk 63 61 0 

262 171 80 59 30 13 22 2 1 5 16 11 

15 17 5 4 1 4 4 0 0 0 0 0 

1 1 0 0 0 0 0 0 0 0 0 0 

Angina

No 9061 7793 547 

Yes 250 246 2 

Dk 75 73 1 

277 189 83 63 31 17 26 2 1 5 16 11 

1 0 1 0 0 0 0 0 0 0 0 0 

0 0 1 0 0 0 0 0 0 0 0 0 

Bronchitis/emphysema

No 8882 7645 536 268 182 84 61 31 17 25 2 1 5 15 10 

Yes 433 397 13 10 7 1 2 0 0 1 0 0 0 1 1 

Dk 71 70 1 0 0 0 0 0 0 0 0 0 0 0 0 

Note: * Signifies missing data; DK = respondents answered don't know; N= sample size; Refused = respondent refused to answer.

Source: Tsang and Klepeis, 1996 
Table 15-53. Number of Loads of Laundry Washed in a Washing Machine at Home by the Number of Respondents 

Number of Loads/Day Total N 1 2 3 4 5 6 7 8 9 10 >10 DK 

Overall 1762 582 604 303 123 55 27 11 12 1 5 1 38 

Gender 

Male 678 219 241 120 41 17 8 * * 1 1 * 30 

Female 1083 363 363 183 82 38 19 10 12 * 4 1 8 

Refused 1 * * * * * * 1 * * * * * 

Age (years) * 30 9 14 2 3 1 * * * * * * 1 

1-4 109 29 36 24 12 5 2 * * * 1 * * 

5-11 141 38 55 28 8 6 2 1 * 1 1 * 1 

12-17 127 39 52 22 10 1 1 * 1 * * * 1 

18-64 1161 385 376 209 80 35 22 9 11 * 3 1 30 

> 64 194 82 71 18 10 7 * 1 * * * * 5 

Race 

White 1511 513 519 254 101 48 23 11 12 1 3 * 26 

Black 112 27 41 23 11 4 1 * * * 1 * 4 

Asian 22 7 4 3 5 * * * * * * * 3 

Some Others 31 8 12 5 1 1 1 * * * * * 3 

Hispanic 68 18 24 15 5 2 2 * * * 1 * 1 

Refused 18 9 4 3 * * * * * * * 1 1 

Hispanic No 1615 536 556 271 115 50 24 11 12 1 4 * 35 

Yes 126 38 42 26 8 5 3 * * * 1 * 3 

DK 6 * 2 4 * * * * * * * * * 

Refused 15 8 4 2 * * * * * * * 1 * 

Employment * 369 102 143 71 29 12 5 1 1 1 2 * 2 

Full Time 734 259 244 128 42 20 10 5 4 * 2 * 20 

Part Time 160 58 53 23 10 8 3 * 1 * * * 4 

Not Employed 482 158 158 79 41 15 8 5 6 * 1 1 10 

Refused 17 5 6 2 1 * 1 * * * * * 2 

Education 

* 413 118 160 77 32 12 6 1 1 1 2 * 3 

< High School 133 44 44 22 10 4 3 2 * * * * 4 

High School Graduate 508 175 166 85 35 18 8 3 4 * * * 14 

< College 321 105 101 61 25 9 3 2 5 * 2 1 7 

College Graduate 212 83 68 32 11 8 4 * 1 * * * 5 

Post Graduate 175 57 65 26 10 4 3 3 1 * 1 * 5 

Census Region Northeast 367 111 146 57 23 13 7 2 1 * * * 7 

Midwest 406 125 123 76 42 14 5 3 6 1 * 1 10 

South 628 205 228 110 39 17 6 6 4 * 3 * 10 

West 361 141 107 60 19 11 9 * 1 * 2 * 11 

Day of Week Weekday 1172 418 409 194 62 29 17 7 7 1 1 1 26 

Weekend 590 164 195 109 61 26 10 4 5 * 4 * 12 

Season 

Winter 458 154 159 73 31 14 6 3 4 1 3 1 9 

Spring 465 154 159 87 28 10 10 3 2 * 1 * 11 

Summer 482 158 166 85 38 11 8 4 3 * 1 * 8 

Fall 357 116 120 58 26 20 3 1 3 * * * 10 

Asthma 

No 1615 548 545 274 105 50 27 11 12 1 5 1 36 

Yes 140 31 56 28 18 5 * * * * * * 2 

DK 7 3 3 1 * * * * * * * * * 

Angina No 1710 564 592 294 113 54 26 11 12 1 5 1 37 

Yes 40 14 9 7 8 1 1 * * * * * * 

DK 12 4 3 2 2 * * * * * * * 1 

Bronchitis/Emphysema No 1658 544 572 285 112 53 26 10 12 1 5 1 37 

Yes 96 36 28 16 11 2 1 1 * * * * 1 

DK 8 2 4 2 * * * * * * * * * 

Note: * Signifies missing data; "DK" = respondent answered don't know; N= sample size; Refused = respondent refused to answer.

Source: Tsang And Klepeis, 1996 
Table 15-54. Number of Times Using a Dishwasher at Specified Frequencies by the Number of Respondents 

Number of Times/Week

Total N * Almost Every Day 3-5/Week 1-2/Week <1-2/Week DK 

Overall 2635 1 557 678 529 824 46 

Gender 

Male 1235 * 259 282 247 417 30 

Female 1399 1 298 396 282 406 16 

Refused 1 * * * * 1 * 

Age (years) * 35 * 4 13 11 6 1 

1-4 145 * 9 4 3 118 11 

5-11 211 * 14 8 15 157 17 

12-17 206 * 27 33 31 113 2 

18-64 1718 * 438 512 397 360 11 

> 64 320 1 65 108 72 70 4 

Race 

White 2267 1 504 603 487 637 35 

Black 163 * 19 32 19 90 3 

Asian 54 * 7 8 7 31 1 

Some Others 45 * 9 8 1 24 3 

Hispanic 84 * 13 15 12 40 4 

Refused 22 * 5 12 3 2 * 

Hispanic No 2444 1 524 635 504 739 41 

Yes 164 * 27 32 21 79 5 

DK 11 * 2 2 2 5 * 

Refused 16 * 4 9 2 1 * 

Employment * 552 * 49 45 46 382 30 

Full Time 1191 * 276 359 298 249 9 

Part Time 204 * 48 70 46 38 2 

Not Employed 678 1 181 200 136 155 5 

Refused 10 * 3 4 3 * * 

Education 

* 593 * 55 51 55 400 32 

< High School 124 1 29 27 26 41 * 

High School Graduate 582 * 153 173 114 132 10 

< College 560 * 144 181 117 117 1 

College Graduate 446 * 105 134 126 80 1 

Post Graduate 330 * 71 112 91 54 2 

Census Region Northeast 538 * 133 144 95 159 7 

Midwest 514 * 116 130 110 152 6 

South 953 * 200 251 169 312 21 

West 630 1 108 153 155 201 12 

Day of Week Weekday 1768 1 378 466 341 549 33 

Weekend 867 * 179 212 188 275 13 

Season 

Winter 711 * 144 175 149 223 20 

Spring 664 1 122 181 132 214 14 

Summer 721 * 157 185 134 239 6 

Fall 539 * 134 137 114 148 6 

Asthma 

No 2439 1 521 622 492 765 38 

Yes 189 * 35 54 35 58 7 

DK 7 * 1 2 2 1 1 

Angina No 2570 1 538 664 512 809 46 

Yes 60 * 19 11 16 14 * 

DK 5 * * 3 1 1 * 

Bronchitis/Emphysema No 2533 1 540 646 504 796 46 

Yes 93 * 16 27 23 27 * 

DK 9 * 1 5 2 1 * 

Note: * Signifies missing data; "DK" = respondent answered don't know; N= sample size; Refused = respondent refused to answer.

Source: Tsang And Klepeis, 1996 
Table 15-55. Number of Times Washing Dishes by Hand at Specified Frequencies by the Number of Respondents 

Number of Times/Week

Total N * Almost Every 3-5/Week 1-2/Week <1-2/Week DK 

Day 

Overall 3626 1 2600 490 326 197 12 

Gender 

Male 1554 * 982 264 183 117 8 

Female 2071 1 1618 225 143 80 4 

Refused 1 * * 1 * * * 

Age (years) * 65 * 51 6 2 6 * 

1-4 1 * * * 1 * * 

5-11 103 * 12 14 33 44 * 

12-17 228 * 57 45 69 56 1 

18-64 2642 1 1979 379 201 76 6 

> 64 587 * 501 46 20 15 5 

Race 

White 2928 1 2114 391 257 157 8 

Black 385 * 261 61 40 21 2 

Asian 61 * 48 6 3 4 * 

Some Others 67 * 44 9 9 5 * 

Hispanic 147 * 108 17 12 8 2 

Refused 38 * 25 6 5 2 * 

Hispanic No 3322 1 2383 454 296 178 10 

Yes 258 * 185 32 25 14 2 

DK 21 * 16 * 3 2 * 

Refused 25 * 16 4 2 3 * 

Employment * 328 * 71 57 102 97 1 

Full Time 1765 * 1282 284 145 50 4 

Part Time 349 * 270 44 17 15 3 

Not Employed 1165 1 965 104 60 31 4 

Refused 19 * 12 1 2 4 * 

Education 

* 386 * 101 65 107 112 1 

< High School 354 * 298 26 15 12 3 

High School Graduate 1106 1 856 140 74 30 5 

< College 796 * 606 116 57 16 1 

College Graduate 591 * 445 86 47 13 * 

Post Graduate 393 * 294 57 26 14 2 

Census Region Northeast 832 * 636 90 60 43 3 

Midwest 811 * 569 114 81 45 2 

South 1214 1 840 175 124 70 4 

West 769 * 555 111 61 39 3 

Day of Week Weekday 2474 * 1759 335 236 136 8 

Weekend 1152 1 841 155 90 61 4 

Season 

Winter 985 * 691 138 90 63 3 

Spring 902 1 648 117 85 46 5 

Summer 987 * 705 132 92 55 3 

Fall 752 * 556 103 59 33 1 

Asthma 

No 3345 1 2407 455 290 183 9 

Yes 263 * 179 33 34 14 3 

DK 18 * 14 2 2 * * 

Angina No 3501 * 2499 475 321 194 12 

Yes 105 1 86 11 5 2 * 

DK 20 * 15 4 * 1 * 

Bronchitis/Emphysema No 3438 1 2459 460 314 192 12 

Yes 169 * 126 27 11 5 * 

DK 19 * 15 3 1 * * 

Note: * Signifies missing data; "DK" = respondent answered don't know; N= sample size; Refused = respondent refused to answer.

Source: Tsang And Klepeis, 1996 
Table 15-56. Number of Times for Washing Clothes in a Washing Machine at Specified Frequencies by the Number of Respondents 

Number of Times/Week 

Total N * Almost Every 3-5 /Day 1-2/week <1/week Never DK 

Day 

Overall 4663 404 566 1033 1827 331 465 37 

Gender 

Male 2163 212 

Female 2498 191 

Refused 2 1 

211 458 811 154 300 17 

355 575 1015 177 165 20 

* * 1 * * * 

Age (years)

* 84 3

1-4 263 261

5-11 348 101

12-17 326 1

18-64 2972 31

> 64 670 7

6 11 47 3 2 12 

* * * * 1 1 

2 4 16 15 206 4 

22 29 83 67 124 * 

489 832 1328 197 83 12 

47 157 353 49 49 8 

Race 

White 3774 316 

Black 463 39 

Asian 77 4 

Some Others 96 16 

Hispanic 193 29 

Refused 60 * 

499 883 1445 246 370 15 

33 72 207 52 55 5 

1 12 39 13 8 * 

10 15 36 8 11 * 

19 41 77 10 17 * 

4 10 23 2 4 17 

Hispanic

No 4244 342 

Yes 347 59 

DK 26 2 

Refused 46 1 

528 950 1674 307 424 19 

31 69 130 20 38 * 

3 6 10 3 2 * 

4 8 13 1 1 18 

Employment

* 926 366

Full Time 2017 21

Part Time 379 6

Not Employed 1309 10

Refused 32 1

23 32 97 76 327 5 

305 569 929 119 66 8 

64 101 166 29 13 * 

170 326 628 105 58 12 

4 5 7 2 1 12 

Education 

* 1021 367

< High School 399 3

High School Graduate 1253 14

< College 895 3

College Graduate 650 12

Post Graduate 445 5

33 37 129 89 343 23 

61 88 178 40 27 2 

218 367 548 55 47 4 

126 261 432 51 19 3 

78 171 321 57 9 2 

50 109 219 39 20 3 

Census Region

Northeast 1048 84 

Midwest 1036 88 

South 1601 147 

West 978 85 

119 216 454 81 87 7 

108 229 408 78 121 4 

229 376 557 97 182 13 

110 212 408 75 75 13 

Day of Week Weekday 3156 257 407 697 1217 232 320 26 

Weekend 1507 147 159 336 610 99 145 11 

Season 

Winter 1264 121

Spring 1181 122

Summer 1275 102

Fall 943 59

157 273 472 101 129 11 

135 259 464 82 113 6 

163 280 484 88 142 16 

111 221 407 60 81 4 

Asthma 

No 4287 371 

Yes 341 32 

DK 35 1 

522 951 1700 303 421 19 

42 79 118 26 43 1 

2 3 9 2 1 17 

Angina

No 4500 403 

Yes 125 * 

DK 38 1 

555 993 1759 321 451 18 

8 37 58 7 13 2 

3 3 10 3 1 17 

Bronchitis/emphysema

No 4424 397 549 979 1724 315 441 19 

Yes 203 7 15 51 92 14 23 1 

DK 36 * 2 3 11 2 1 17 

Note: * Signifies missing data; "DK" = respondent answered don't know; N= sample size; Refused = respondent refused to answer.

Source: Tsang And Klepeis, 1996 
Table 15-57. Number of Minutes Spent Playing on Sand or Gravel in a Day by the Number of Respondents 

Minutes/Day 

Total N *-* 0-0 0-10 10-20 20-30 30-40 40-50 50-60 70-80 80-90 90-100 110-120 121 

Overall 700 41 348 42 34 57 4 12 66 2 9 2 27 56 

Gender 

Male 352 18 189 20 

Female 347 23 158 22 

Refusedused 1 * 1 * 

13 25 * 7 32 * 7 1 10 30 

21 32 4 5 34 2 2 1 17 26 

* * * * * * * * * * 

Age (years) * 3 1 * *

1-4 216 13 115 15

5-11 200 7 96 11

12-17 41 1 23 1

18-64 237 18 112 15

> 64 3 1 2 *

1 * * * * * * * * 1 

9 15 2 3 15 1 5 * 7 16 

12 14 * 5 25 1 2 1 6 20 

2 4 * * 3 * * 1 3 3 

10 24 2 4 23 * 2 * 11 16 

* * * * * * * * * * 

Race 

White 568 34 274 

Black 68 4 42 

Asian 5 * 2 

Some Others 16 2 9 

Hispanic 41 * 19 

Refused 2 2 

37 30 49 2 9 57 1 8 2 21 44 

5 3 2 * 1 4 * * * 3 4 

* * 1 * * 1 * * * * 1 

* * * 2 * 1 * * * * 3 

* 1 5 * 2 3 1 1 * 3 4 

* * * * * * * * * * * 

Hispanic No 619 36 309 

Yes 77 5 36 

DK 3 * 2 

Refused 1 * 1 

41 29 49 4 10 59 1 7 2 23 49 

1 4 8 * 2 7 1 2 * 4 7 

* 1 * * * * * * * * * 

* * * * * * * * * * * 

Employment * 461 22 234

Full Time 149 9 73

Part Time 29 2 10

Not Employed 60 7 31

Refused 1 1 *

27 24 33 2 8 43 2 7 2 16 41 

7 7 16 1 3 17 * 2 * 6 8 

4 1 2 1 * 4 * * * 2 3 

4 2 6 * 1 2 * * * 3 4 

* * * * * * * * * * * 

Education 

* 461 22 234

< High School 22 5 9

High School Graduate 73 4 39

< College 66 2 34

College Graduate 54 4 26

Post Graduate 24 4 6

27 24 33 2 8 43 2 7 2 16 41 

* * 3 * * 1 * * * 2 2 

4 1 8 1 * 6 * 1 * 2 7 

6 2 6 * 2 6 * * * 4 4 

3 3 6 1 2 7 * * * * 2 

2 4 1 * * 3 * 1 * 3 * 

Census Region Northeast 124 8 60 

Midwest 128 6 69 

South 273 17 133 

West 175 10 86 

8 5 7 * 4 16 * 1 * 6 9 

8 6 14 * 2 11 * 2 * 3 7 

18 12 25 3 3 30 * 3 2 6 21 

8 11 11 1 3 9 2 3 * 12 19 

Day of Week Weekday 445 35 216 27 22 40 3 10 37 2 6 2 17 28 

Weekend 255 6 132 15 12 17 1 2 29 * 3 * 10 28 

Season 

Winter 107 10 44 

Spring 240 8 113 

Summer 262 12 146 

Fall 91 11 45 

9 6 11 1 2 8 2 1 * 4 9 

21 14 22 1 3 25 * 2 * 12 19 

5 9 20 2 5 25 * 5 2 9 22 

7 5 4 * 2 8 * 1 * 2 6 

Asthma 

No 638 38 319 39 

Yes 61 3 28 3 

DK 1 * 1 * 

34 51 4 10 57 2 9 2 22 51 

* 6 * 2 9 * * * 5 5 

* * * * * * * * * * 

Angina No 699 40 348 42 34 57 4 12 66 2 9 2 27 56 

DK 1 1 * * * * * * * * * * * * 

Bronchitis/Emphysema No 679 41 339 41 34 54 4 12 62 2 9 2 26 53 

Yes 21 * 9 1 * 3 * * 4 * * * 1 3 

Note: "*" = Signifies missing data. "DK" = Don't know. Refused = refused to answer. N = Doer sample size in specified range of

number of minutes spent. A value of "121" for number of minutes signifies that more than 120 minutes were spent.

Source: Tsang and Klepeis, 1996.
Table 15-58. Number of Minutes Spent Playing in Sand or Gravel (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 659 0 0 0 0 0 0 45 120 121 121 121 121 

Gender Male 334 0 0 0 0 0 0 45 120 121 121 121 121 

Gender Female 324 0 0 0 0 0 1 60 120 121 121 121 121 

Age (years) 1-4 203 0 0 0 0 0 0 30 120 121 121 121 121 

Age (years) 5-11 193 0 0 0 0 0 3 60 121 121 121 121 121 

Age (years) 12-17 40 0 0 0 0 0 0 45 120 121 121 121 121 

Age (years) 18-64 219 0 0 0 0 0 0 45 120 121 121 121 121 

Age (years) > 64 2 0 0 0 0 0 0 0 0 0 0 0 0 

Race White 534 0 0 0 0 0 0 50 120 121 121 121 121 

Race Black 64 0 0 0 0 0 0 15 120 121 121 121 121 

Race Asian 5 0 0 0 0 0 30 60 121 121 121 121 121 

Race Some Others 15 0 0 0 0 0 0 60 121 121 121 121 121 

Race Hispanic 39 0 0 0 0 0 15 60 121 121 121 121 121 

Hispanic No 583 0 0 0 0 0 0 45 120 121 121 121 121 

Hispanic Yes 72 0 0 0 0 0 1.5 60 120 121 121 121 121 

Employment Full Time 140 0 0 0 0 0 0 45 105 121 121 121 121 

Employment Part Time 27 0 0 0 0 0 10 60 121 121 121 121 121 

Employment Not Employed 53 0 0 0 0 0 0 30 120 121 121 121 121 

Education < High School 17 0 0 0 0 0 0 60 121 121 121 121 121 

Education High School Graduate 69 0 0 0 0 0 0 30 121 121 121 121 121 

Education < College 64 0 0 0 0 0 0 37.5 120 121 121 121 121 

Education College Graduate 50 0 0 0 0 0 0 30 60 60 121 121 121 

Education Post Graduate 20 0 0 0 0 0 15 60 120 120 120 120 120 

Census Region Northeast 116 0 0 0 0 0 0 60 120 121 121 121 121 

Census Region Midwest 122 0 0 0 0 0 0 30 60 121 121 121 121 

Census Region South 256 0 0 0 0 0 0 45 120 121 121 121 121 

Census Region West 165 0 0 0 0 0 0 60 121 121 121 121 121 

Day of Week Weekday 410 0 0 0 0 0 0 40 120 121 121 121 121 

Day of Week Weekend 249 0 0 0 0 0 0 60 121 121 121 121 121 

Season Winter 97 0 0 0 0 0 5 45 120 121 121 121 121 

Season Spring 232 0 0 0 0 0 1 52.5 120 121 121 121 121 

Season Summer 250 0 0 0 0 0 0 60 120 121 121 121 121 

Season Fall 80 0 0 0 0 0 0 30 105 121 121 121 121 

Asthma No 600 0 0 0 0 0 0 45 120 121 121 121 121 

Asthma Yes 58 0 0 0 0 0 3 60 120 121 121 121 121 

Angina No 659 0 0 0 0 0 0 45 120 121 121 121 121 

Bronchitis/emphysema No 638 0 0 0 0 0 0 45 120 121 121 121 121 

Bronchitis/emphysema Yes 21 0 0 0 0 0 30 60 121 121 121 121 121 

NOTE: A value of "121" for number of minutes signifies that more than 120 minutes were spent. N = doer sample size. Percentiles 

are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis,1996 
Table 15-59. Number of Minutes Spent Playing in Outdoors on Sand, Gravel, Dirt, or Grass When Fill Dirt Was Present by the Number of Respondents 

Minutes/Day 

Total N *-* 0-0 0-10 10-20 20-30 30-40 40-50 50-60 70-80 80-90 110-120 121 

Overall 700 53 380 51 29 48 1 6 60 7 1 21 43 

Gender 

Male 352 26 183 22 18 33 * 3 24 5 1 16 21 

Female 347 27 196 29 11 15 1 3 36 2 * 5 22 

Refused 1 * 1 * * * * * * * * * * 

Age (years) * 3 * * 1 * * * * 1 * * * 1 

1-4 216 11 118 14 10 13 1 4 18 4 * 7 16 

5-11 200 15 103 14 8 15 * 1 17 1 * 9 17 

12-17 41 3 19 3 2 7 * * 4 1 * 2 * 

18-64 237 23 138 19 9 13 * 1 20 1 1 3 9 

> 64 3 1 2 * * * * * * * * * * 

Race 

White 568 40 317 40 21 38 * 5 48 5 1 15 38 

Black 68 8 33 5 2 6 * 1 7 1 * 3 2 

Asian 5 * 2 * * 2 * * * * * * 1 

Some Others 16 * 10 1 2 1 1 * 1 * * * * 

Hispanic 41 5 17 5 4 * * * 4 1 * 3 2 

Refused 2 * 1 * * 1 * * * * * * * 

Hispanic No 619 45 345 42 21 44 1 6 54 5 1 17 38 

Yes 77 8 32 9 8 3 * * 6 2 * 4 5 

DK 3 * 3 * * * * * * * * * * 

Refused 1 * * * * 1 * * * * * * * 

Employment * 461 29 240 32 20 35 1 5 40 6 * 18 35 

Full Time 149 11 91 8 8 8 * 1 12 1 1 3 5 

Part Time 29 4 17 3 * 2 * * 2 * * * 1 

Not Employed 60 8 32 8 1 3 * * 6 * * * 2 

Refused 1 1 * * * * * * * * * * * 

Education 

* 461 29 240 32 20 35 1 5 40 6 * 18 35 

< High School 22 5 9 * * 3 * * 2 * * 1 2 

High School Graduate 73 6 44 7 2 3 * * 7 1 1 1 1 

< College 66 4 38 7 3 3 * 1 7 * * * 3 

College Graduate 54 3 35 3 4 4 * * 3 * * * 2 

Post Graduate 24 6 14 2 * * * * 1 * * 1 * 

Census Region Northeast 124 6 70 13 3 5 * * 18 1 * 2 6 

Midwest 128 12 77 6 7 10 * 1 7 2 * 2 4 

South 273 23 153 17 12 20 * 3 17 4 * 11 13 

West 175 12 80 15 7 13 1 2 18 * 1 6 20 

Day of Week Weekday 445 39 235 34 21 34 1 2 38 6 1 10 24 

Weekend 255 14 145 17 8 14 * 4 22 1 * 11 19 

Season 

Winter 107 14 51 6 6 5 * 2 7 2 * 2 12 

Spring 240 10 134 17 10 20 1 2 21 2 * 10 13 

Summer 262 17 143 19 12 19 * 1 25 2 1 8 15 

Fall 91 12 52 9 1 4 * 1 7 1 * 1 3 

Asthma 

No 638 48 354 47 25 41 1 5 50 7 1 19 40 

Yes 61 5 25 4 4 7 * 1 10 * * 2 3 

DK 1 * 1 * * * * * * * * * * 

Anngina No 699 53 380 51 29 48 1 6 60 6 1 21 43 

DK 1 * * * * * * * * 1 * * * 

Bronchitis/Emphysema No 679 52 368 51 28 46 1 5 57 7 1 21 42 

Yes 21 1 12 * 1 2 * 1 3 * * * 1 

Note: "*" Signifies missing data. "DK"k = Respondents answered don't know. Refused = Respondents refused to answer. N = Doer 

sample size in specified range of number of minutes spent. A value of "121" for number of minutes signifies that more than 120 minutes 

were spent. 

Source: Tsang and Klepeis, 1996. 
Table 15-60. Number of Minutes Spent Playing on Sand, Gravel, Dirt, or Grass When Fill Dirt Was Present (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 647 0 0 0 0 0 0 30 100 121 121 121 121 

Gender Male 326 0 0 0 0 0 0 30 120 121 121 121 121 

Gender Female 320 0 0 0 0 0 0 30 60 121 121 121 121 

Age (years) 1-4 205 0 0 0 0 0 0 30 120 121 121 121 121 

Age (years) 5-11 185 0 0 0 0 0 0 30 120 121 121 121 121 

Age (years) 12-17 38 0 0 0 0 0 0.5 30 60 120 120 120 120 

Age (years) 18-64 214 0 0 0 0 0 0 15 60 120 121 121 121 

Age (years) > 64 2 0 0 0 0 0 0 0 0 0 0 0 0 

Race White 528 0 0 0 0 0 0 30 120 121 121 121 121 

Race Black 60 0 0 0 0 0 0 30 74 120 121 121 121 

Race Asian 5 0 0 0 0 0 30 30 121 121 121 121 121 

Race Some Others 16 0 0 0 0 0 0 20 40 60 60 60 60 

Race Hispanic 36 0 0 0 0 0 1 60 120 121 121 121 121 

Hispanic No 574 0 0 0 0 0 0 30 90 121 121 121 121 

Hispanic Yes 69 0 0 0 0 0 1 30 120 121 121 121 121 

Employment Full Time 138 0 0 0 0 0 0 15 60 120 121 121 121 

Employment Part Time 25 0 0 0 0 0 0 10 60 60 121 121 121 

Employment Not Employed 52 0 0 0 0 0 0 10 60 60 121 121 121 

Education < High School 17 0 0 0 0 0 0 60 121 121 121 121 121 

Education High School Graduate 67 0 0 0 0 0 0 10 60 88 120 121 121 

Education < College 62 0 0 0 0 0 0 15 60 60 121 121 121 

Education College Graduate 51 0 0 0 0 0 0 15 30 60 121 121 121 

Education Post Graduate 18 0 0 0 0 0 0 0 60 120 120 120 120 

Census Region Northeast 118 0 0 0 0 0 0 30 60 121 121 121 121 

Census Region Midwest 116 0 0 0 0 0 0 20 60 120 121 121 121 

Census Region South 250 0 0 0 0 0 0 30 90 121 121 121 121 

Census Region West 163 0 0 0 0 0 1 60 121 121 121 121 121 

Day of Week Weekday 406 0 0 0 0 0 0 30 88 121 121 121 121 

Day of Week Weekend 241 0 0 0 0 0 0 30 120 121 121 121 121 

Season Winter 93 0 0 0 0 0 0 45 121 121 121 121 121 

Season Spring 230 0 0 0 0 0 0 30 105 121 121 121 121 

Season Summer 245 0 0 0 0 0 0 30 90 121 121 121 121 

Season Fall 79 0 0 0 0 0 0 10 60 120 121 121 121 

Asthma No 590 0 0 0 0 0 0 30 110 121 121 121 121 

Asthma Yes 56 0 0 0 0 0 10 60 60 121 121 121 121 

Angina No 646 0 0 0 0 0 0 30 100 121 121 121 121 

Bronchitis/Emphysema No 627 0 0 0 0 0 0 30 120 121 121 121 121 

Bronchitis/Emphysema Yes 20 0 0 0 0 0 0 37.5 60 90.5 121 121 121 

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: Tsang and Klepeis,1996 
Table 15-61. Range of the Time Spent Working in a Garden or Other Circumstances in a Month by the Number of Respondents 

Hours/Month 

Total N *-* 0-0 0-24 24-48 48-72 72-96 96-120 120- 144- 168- 192- 216- 240- 264- 288- 3

144 168 192 216 240 264 288 312 3

Overall 4663 91 2928 1312 145 81 28 23 1 10 5 12 8 3 1 1 

Gender 

Male 2163 38 1309 628 77 41 16 9 1 8 4 10 8 2 1 * 

Female 2498 53 1618 683 68 40 12 14 * 2 1 2 * 1 * 1 

Refused 2 * 1 1 * * * * * * * * * * * * 

Age (years) * 84 11 51 17 * 2 2 1 * * * * * * * * 

1-4 263 7 189 55 4 3 2 2 * 1 * * * * * * 

5-11 348 7 225 100 9 4 * * * * 1 * * * 1 * 

12-17 326 5 236 75 6 1 * 1 * * 1 1 * * * * 

18-64 2972 37 1813 900 97 52 16 16 1 7 1 8 8 3 * * 

> 64 670 24 414 165 29 19 8 3 * 2 2 3 * * * 1 

Race 

White 3774 59 2303 1128 127 69 22 21 1 7 4 11 7 3 1 1 

Black 463 9 351 77 9 8 3 * * 2 1 * 1 * * * 

Asian 77 1 50 25 1 * * * * * * * * * * * 

Some Others 96 2 64 23 2 2 1 * * 1 * 1 * * * * 

Hispanic 193 6 126 50 5 1 2 1 * * * * * * * * 

Refused 60 14 34 9 1 1 * 1 * * * * * * * * 

Hispanic No 4244 65 2669 1206 135 73 25 20 1 8 5 12 8 3 1 1 

Yes 347 11 218 94 9 6 3 3 * 1 * * * * * * 

DK 26 1 18 5 * 1 * * * 1 * * * * * * 

Refused 46 14 23 7 1 1 * * * * * * * * * * 

Employment * 926 19 638 230 20 8 2 3 * 1 2 1 * * 1 * 

Full Time 2017 18 1235 600 68 35 12 9 1 7 1 10 8 2 * * 

Part Time 379 4 234 120 9 3 2 4 * 2 * * * * * * 

Not Employed 1309 39 808 354 48 35 12 7 * * 2 1 * 1 * 1 

Refused 32 11 13 8 * * * * * * * * * * * * 

Education 

* 1021 34 699 246 22 8 3 3 * 1 2 1 * * 1 * 

< High School 399 18 263 86 11 9 4 4 * 1 * 1 * * * * 

High School 1253 25 770 355 41 22 9 7 * 5 2 8 4 * * 1 

Graduate 895 11 545 265 33 18 6 3 * 1 * 2 4 3 * * 

< College 650 1 406 200 19 12 3 5 * 1 1 * * * * * 

College Graduate 445 2 245 160 19 12 3 1 1 1 * * * * * * 

Post Graduate 

Census Region Northeast 1048 17 714 259 24 12 4 8 * 3 * 2 1 * 1 * 

Midwest 1036 23 687 273 19 18 5 3 * * * 3 * 3 * * 

South 1601 35 989 446 64 26 11 7 1 4 4 3 6 * * 1 

West 978 16 538 334 38 25 8 5 * 3 1 4 1 * * * 

Day of Week Weekday 3156 62 1982 890 96 54 18 15 1 8 3 6 7 2 * 1 

Weekend 1507 29 946 422 49 27 10 8 * 2 2 6 1 1 1 * 

Season 

Winter 1264 9 1038 171 20 9 5 3 * 2 2 2 * * * 1 

Spring 1181 29 614 434 50 20 8 7 * 4 1 4 5 2 * * 

Summer 1275 39 690 421 56 33 12 9 1 2 1 3 3 1 * * 

Fall 943 14 586 286 19 19 3 4 * 2 1 3 * * 1 * 

Asthma 

No 4287 70 2697 1206 135 77 27 23 1 10 5 12 6 3 1 1 

Yes 341 6 216 101 10 4 1 * * * * * 2 * * * 

DK 35 15 15 5 * * * * * * * * * * * * 

Angina No 4500 74 2825 1277 143 77 28 21 1 10 5 12 8 3 1 1 

Yes 125 4 86 29 1 3 * 2 * * * * * * * * 

DK 38 13 17 6 1 1 * * * * * * * * * * 

Bronchitis/emphysema No 4424 72 2766 1265 140 77 27 22 1 10 5 12 8 3 1 1 

Yes 203 5 146 43 5 2 1 1 * * * * * * * * 

DK 36 14 16 4 * 2 * * * * * * * * * * 

Note: * Signifies missing data. DK = respondents answered don't know. Refused = respondents refused to answer. N = doer sample size in

specified range of number of minutes spent.

Source: Tsang and Klepeis,1996 
Table 15-62. Number of Hours Spent Working with Soil in a Garden or Other Circumstances Working (hours/month) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 4572 0 0 0 0 0 0 3 15 40 88 160 320 

Gender Male 2125 0 0 0 0 0 0 3 20 50 150 230 320 

Gender Female 2445 0 0 0 0 0 0 2 12 30 60 90 320 

Age (years) 1-4 256 0 0 0 0 0 0 1 7 20 60 120 150 

Age (years) 5-11 341 0 0 0 0 0 0 2 10 20 50 60 320 

Age (years) 12-17 321 0 0 0 0 0 0 1 5 10 40 60 200 

Age (years) 18-64 2935 0 0 0 0 0 0 3 16 40 90 200 320 

Age (years) > 64 646 0 0 0 0 0 0 3 25 60 90 160 300 

Race White 3715 0 0 0 0 0 0 3 16 40 88 160 320 

Race Black 454 0 0 0 0 0 0 0 8 30 60 160 320 

Race Asian 76 0 0 0 0 0 0 1.5 6 15 24 40 40 

Race Some Others 94 0 0 0 0 0 0 2 15 60 150 200 200 

Race Hispanic 187 0 0 0 0 0 0 2 12 25 90 320 320 

Hispanic No 4179 0 0 0 0 0 0 3 15 40 80 180 320 

Hispanic Yes 336 0 0 0 0 0 0 2 15 32 90 120 320 

Employment Full Time 1999 0 0 0 0 0 0 4 20 45 144 240 320 

Employment Part Time 375 0 0 0 0 0 0 3 12 32 90 120 320 

Employment Not Employed 1270 0 0 0 0 0 0 3 20 45 64 100 320 

Education < High School 381 0 0 0 0 0 0 2 16 60 120 160 320 

Education High School Grad 1228 0 0 0 0 0 0 3.5 20 50 120 200 320 

Education < College 884 0 0 0 0 0 0 4 20 40 90 240 320 

Education College Grad. 649 0 0 0 0 0 0 3 16 40 70 100 320 

Education Post Grad. 443 0 0 0 0 0 0 5 20 40 61 90 320 

Census Region Northeast 1031 0 0 0 0 0 0 1 10 30 90 120 320 

Census Region Midwest 1013 0 0 0 0 0 0 2 10 30 60 120 320 

Census Region South 1566 0 0 0 0 0 0 3 18 40 90 180 320 

Census Region West 962 0 0 0 0 0 0 5 20 50 90 200 320 

Day of Week Weekday 3094 0 0 0 0 0 0 3 15 40 80 160 320 

Day of Week Weekend 1478 0 0 0 0 0 0 3 15 40 90 150 320 

Season Winter 1255 0 0 0 0 0 0 0 4 12 50 90 320 

Season Spring 1152 0 0 0 0 0 0 5 20 45 110 200 320 

Season Summer 1236 0 0 0 0 0 0 5 25 50 96 160 320 

Season Fall 929 0 0 0 0 0 0 3 10 30 88 180 320 

Asthma No 4217 0 0 0 0 0 0 3 15 40 90 160 320 

Asthma Yes 335 0 0 0 0 0 0 2 12 30 60 80 320 

Angina No 4426 0 0 0 0 0 0 3 15 40 88 160 320 

Angina Yes 121 0 0 0 0 0 0 2 7 24 60 110 120 

Bronchitis/Emphysema No 4352 0 0 0 0 0 0 3 15 40 88 180 320 

Bronchitis/Emphysema Yes 198 0 0 0 0 0 0 1 7 24 60 80 100 

Note: * Signifies missing data. DK = respondents answered don't know. Refused = respondents refused to answer. N = doer 

sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-63. Range of Number of Minutes Spent Playing on Grass in a Day by the Number of Respondents 

Minutes/Day 

Total *-* 0-0 0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90- 100- 110- 121-

N 100 110 120 121 

Overall 700 43 79 49 49 85 7 11 125 1 1 21 1 2 66 160 

Gender 

Male 352 25 35 23 25 41 3 5 64 * 1 12 * 1 33 84 

Female 347 18 44 26 24 44 4 6 61 1 * 9 1 1 33 75 

Refused 1 * * * * * * * * * * * * * * 1 

Age (years) * 3 * * 1 1 * * * * * * * * * * 1 

1-4 216 10 24 19 21 25 1 4 35 * 1 8 * 1 18 49 

5-11 200 15 24 10 10 19 2 3 38 1 * 8 1 * 20 49 

12-17 41 2 5 1 2 8 * 1 8 * * 1 * * 8 5 

18-64 237 16 26 18 15 32 4 3 44 * * 4 * 1 20 54 

> 64 3 * * * * 1 * * * * * * * * * 2 

Race 

White 568 36 65 40 39 58 7 9 98 1 1 17 1 1 56 139 

Black 68 3 4 6 7 14 * 1 15 * * 2 * * 5 11 

Asian 5 * * 1 * 3 * * * * * * * * * 1 

Some Others 16 * 4 * 1 1 * * 4 * * 1 * * 2 3 

Hispanic 41 4 5 2 2 9 * * 8 * * 1 * 1 3 6 

Refused 2 * 1 * * * * 1 * * * * * * * * 

Hispanic No 619 38 65 44 42 73 6 11 110 1 1 18 1 1 62 146 

Yes 77 5 13 5 7 11 1 * 14 * * 3 * 1 4 13 

DK 3 * * * * 1 * * 1 * * * * * * 1 

Refused 1 * 1 * * * * * * * * * * * * * 

Employment * 461 27 54 31 34 52 3 8 81 1 1 17 1 1 46 104 

Full Time 149 8 16 12 10 21 3 3 25 * * 2 * * 13 36 

Part Time 29 2 5 1 1 6 * * 4 * * 2 * * 3 5 

Not Employed 60 5 4 5 4 6 1 * 15 * * * * 1 4 15 

Refused 1 1 * * * * * * * * * * * * * * 

Education 

* 461 27 54 31 34 52 3 8 81 1 1 17 1 1 46 104 

< High School 22 2 2 1 1 4 * * 3 * * * * 1 3 5 

High School Graduate 73 4 8 9 4 6 1 1 9 * * 3 * * 6 22 

< College 66 2 7 4 6 13 2 * 20 * * * * * 3 9 

College Graduate 54 3 5 3 4 6 1 1 10 * * * * * 6 15 

Post Graduate 24 5 3 1 * 4 * 1 2 * * 1 * * 2 5 

Census Region Northeast 124 5 14 10 4 13 * 3 26 * * 2 1 * 10 36 

Midwest 128 8 7 10 10 15 1 3 23 * 1 4 * * 15 31 

South 273 21 22 20 25 30 5 4 52 1 * 11 * 2 23 57 

West 175 9 36 9 10 27 1 1 24 * * 4 * * 18 36 

Day of Week Weekday 445 33 55 35 32 55 3 7 82 * 1 15 1 1 38 87 

Weekend 255 10 24 14 17 30 4 4 43 1 * 6 * 1 28 73 

Season 

Winter 107 12 22 6 6 15 2 * 15 * * 5 * * 5 19 

Spring 240 9 23 16 13 28 1 5 49 * * 7 1 1 26 61 

Summer 262 12 20 20 18 36 2 5 48 1 * 7 * 1 29 63 

Fall 91 10 14 7 12 6 2 1 13 * 1 2 * * 6 17 

Asthma 

No 638 38 73 46 44 78 7 9 114 1 1 18 1 2 60 146 

Yes 61 5 6 3 5 7 * 2 10 * * 3 * * 6 14 

DK 1 * * * * * * * 1 * * * * * * * 

Angina No 699 43 79 49 48 85 7 11 125 1 1 21 1 2 66 160 

DK 1 * * * 1 * * * * * * * * * * * 

Bronchitis/emphysema No 679 43 76 49 47 83 7 11 120 1 1 20 1 2 65 153 

Yes 21 * 3 * 2 2 * * 5 * * 1 * * 1 7 

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. Refused = respondent refused to answer.

Source: Tsang and Klepeis,1996. 
Table 15-64. Number of Minutes Spent Playing on Grass (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 657 0 0 0 0 20 60 120 121 121 121 121 121 

Gender Male 327 0 0 0 0 20 60 121 121 121 121 121 121 

Gender Female 329 0 0 0 0 15 60 120 121 121 121 121 121 

Age (years) 1-4 206 0 0 0 0 15 60 120 121 121 121 121 121 

Age (years) 5-11 185 0 0 0 0 30 60 121 121 121 121 121 121 

Age (years) 12-17 39 0 0 0 0 30 60 120 121 121 121 121 121 

Age (years) 18-64 221 0 0 0 0 20 60 120 121 121 121 121 121 

Age (years) > 64 3 30 30 30 30 30 121 121 121 121 121 121 121 

Race White 532 0 0 0 0 20 60 121 121 121 121 121 121 

Race Black 65 0 0 0 3 20 58 90 121 121 121 121 121 

Race Asian 5 10 10 10 10 30 30 30 121 121 121 121 121 

Race Some Others 16 0 0 0 0 10 60 120 121 121 121 121 121 

Race Hispanic 37 0 0 0 0 30 60 110 121 121 121 121 121 

Hispanic No 581 0 0 0 0 20 60 121 121 121 121 121 121 

Hispanic Yes 72 0 0 0 0 10 35 100 121 121 121 121 121 

Employment Full Time 141 0 0 0 0 20 60 121 121 121 121 121 121 

Employment Part Time 27 0 0 0 0 15 60 120 121 121 121 121 121 

Employment Not Employed 55 0 0 0 5 23 60 121 121 121 121 121 121 

Education < High School 20 0 0 0 5 30 60 120.5 121 121 121 121 121 

Education High School Graduate 69 0 0 0 0 15 60 121 121 121 121 121 121 

Education < College 64 0 0 0 0 17.5 46.5 60 121 121 121 121 121 

Education College Graduate 51 0 0 0 1 30 60 121 121 121 121 121 121 

Education Post Graduate 19 0 0 0 0 25 60 121 121 121 121 121 121 

Census Region Northeast 119 0 0 0 0 30 60 121 121 121 121 121 121 

Census Region Midwest 120 0 0 0 7.5 30 60 121 121 121 121 121 121 

Census Region South 252 0 0 0 1 20 60 120 121 121 121 121 121 

Census Region West 166 0 0 0 0 10 45 120 121 121 121 121 121 

Day of Week Weekday 412 0 0 0 0 15 60 120 121 121 121 121 121 

Day of Week Weekend 245 0 0 0 1 30 60 121 121 121 121 121 121 

Season Winter 95 0 0 0 0 4 30 120 121 121 121 121 121 

Season Spring 231 0 0 0 1 30 60 121 121 121 121 121 121 

Season Summer 250 0 0 0 1.5 30 60 121 121 121 121 121 121 

Season Fall 81 0 0 0 0 10 35 120 121 121 121 121 121 

Asthma No 600 0 0 0 0 20 60 120 121 121 121 121 121 

Asthma Yes 56 0 0 0 0 22.5 60 120.5 121 121 121 121 121 

Angina No 656 0 0 0 0 20 60 120 121 121 121 121 121 

Bronchitis/Emphysema No 636 0 0 0 0 20 60 120 121 121 121 121 121 

Bronchitis/Emphysema Yes 21 0 0 0 0 30 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: Tsang and Klepeis,1996 
Table 15-65. Number of Times Swimming in a Month in Freshwater Swimming Pool by the Number of Respondents 

Times/Month 

Total N 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 

Overall 653 147 94 73 47 42 26 11 26 2 38 3 27 2 2 27 2 

Gender 

Male 300 62 47 37 20 16 17 5 9 2 16 2 13 1 * 16 1 

Female 352 85 47 36 27 26 9 6 17 * 22 1 14 1 1 11 1 

Refused 1 * * * * * * * * * * * * * 1 * * 

Age (years) * 8 2 2 1 1 1 1 * * * * * * * * * * 

1-4 63 11 14 7 3 3 4 1 3 1 4 * 2 1 1 2 * 

5-11 100 16 15 7 9 6 4 2 4 * 7 * 5 * * 11 2 

12-17 84 21 13 7 4 8 4 2 3 1 8 * 1 * * 2 * 

18-64 360 86 48 50 27 22 11 5 14 * 18 3 15 1 1 10 * 

> 64 38 11 2 1 3 2 2 1 2 * 1 * 4 * * 2 * 

Race 

White 555 126 74 64 44 32 25 10 23 2 36 1 23 2 2 21 1 

Black 30 8 7 1 * 2 * * 1 * * 2 * * * 2 1 

Asian 13 3 2 2 * 1 * 1 1 * 1 * 1 * * * * 

Some Others 12 2 * 2 2 1 * * * * * * * * * 4 * 

Hispanic 35 5 8 4 1 6 1 * 1 * 1 * 3 * * * * 

Refused 8 3 3 * * * * * * * * * * * * * * 

Hispanic No 591 135 81 68 44 35 25 10 25 2 36 3 24 1 2 24 2 

Yes 55 10 11 5 2 6 1 1 1 * 2 * 3 1 * 3 * 

DK 2 * * * 1 1 * * * * * * * * * * * 

Refused 5 2 2 * * * * * * * * * * * * * * 

Employment * 243 47 41 21 17 15 12 5 10 2 18 * 8 1 1 15 2 

Full Time 240 56 38 38 15 13 10 3 8 * 10 1 8 1 1 6 * 

Part Time 43 13 2 4 3 8 * 1 1 * 4 2 2 * * 1 * 

Not Employed 122 30 12 10 12 6 3 2 7 * 6 * 9 * * 5 * 

Refused 5 1 1 * * * 1 * * * * * * * * * * 

Education 

* 257 51 43 21 18 17 12 5 11 2 19 * 8 1 1 15 2 

< High School 16 2 2 3 * 3 1 1 1 * * 1 * * * * * 

High School Graduate 112 28 15 16 11 6 5 1 1 * 5 1 5 * 1 3 * 

<College 104 29 11 11 2 9 2 3 7 * 4 1 7 * * 3 * 

College Graduate 93 22 12 14 10 2 3 * 2 * 5 * 6 * * 4 * 

Post Graduate 71 15 11 8 6 5 3 1 4 * 5 * 1 1 * 2 * 

Census Region Northeast 136 32 15 10 16 9 4 1 4 * 13 1 8 1 2 4 * 

Midwest 130 35 21 17 8 6 7 2 4 * 9 * 4 1 * 6 * 

South 235 46 36 29 13 15 12 7 10 2 10 2 8 * * 9 2 

West 152 34 22 17 10 12 3 1 8 * 6 * 7 * * 8 * 

Day of Week Weekday 445 97 67 52 36 25 15 9 14 1 24 2 18 2 2 21 1 

Weekend 208 50 27 21 11 17 11 2 12 1 14 1 9 * * 6 1 

Season 

Winter 62 19 12 5 3 1 2 * 6 * 2 1 3 * * * * 

Spring 174 55 25 19 13 9 7 3 7 * 8 * 7 * * 2 1 

Summer 363 61 45 41 29 26 15 8 12 2 27 2 14 2 2 24 1 

Fall 54 12 12 8 2 6 2 * 1 * 1 * 3 * * 1 * 

Asthma 

No 590 132 81 67 43 38 25 10 24 2 37 3 25 2 2 22 2 

Yes 56 14 11 5 4 3 1 1 2 * 1 * 2 * * 5 * 

DK 7 1 2 1 * 1 * * * * * * * * * * * 

Angina No 639 143 90 73 47 41 26 10 26 2 37 3 27 2 2 26 2 

Yes 8 3 1 * * 1 * 1 * * * * * * * 1 * 

DK 6 1 3 * * * * * * * 1 * * * * * * 

Bronchitis/Emphysema No 621 138 91 71 45 40 25 10 24 2 38 2 27 2 2 25 2 

Yes 26 8 1 2 1 2 1 1 1 * * 1 * * * 2 * 

DK 6 1 2 * 1 * * * 1 * * * * * * * * 
Table 15-65. Number of Times Swimming in a Month in Freshwater Swimming Pool by the Number of Respondents (continued) 

Times/Month 

18 20 23 24 25 26 28 29 30 31 32 40 42 45 50 60 DK 

Overall 2 25 1 1 9 2 1 1 26 2 1 2 2 1 1 2 5 

Gender 

Male * 10 * * 4 2 1 * 10 2 1 1 1 * * * 4 

Female 2 15 1 1 5 * * 1 16 * * 1 1 1 1 2 1 

Refused * * * * * * * * * * * * * * * * * 

Age (years) * * * * * * * * * * * * * * * * * * 

1-4 * 2 * * * * * 1 2 * 1 * * * * * * 

5-11 * 3 * 1 2 * * * 5 * * * * * 1 * * 

12-17 1 4 * * * 1 * * 2 * * * * * * 1 1 

18-64 * 15 1 * 7 1 1 * 15 2 * 2 1 1 * * 3 

> 64 1 1 * * * * * * 2 * * * 1 * * 1 1 

Race 

White 2 19 1 1 9 2 1 1 19 2 1 2 2 * * 2 5 

Black * 3 * * * * * * 3 * * * * * * * * 

Asian * 1 * * * * * * * * * * * * * * * 

Some Others * * * * * * * * * * * * * * 1 * * 

Hispanic * 1 * * * * * * 3 * * * * 1 * * * 

Refused * 1 * * * * * * 1 * * * * * * * * 

Hispanic No 2 23 1 1 9 2 1 1 20 2 1 2 2 * 1 2 4 

Yes * 1 * * * * * * 6 * * * * 1 * * 1 

DK * * * * * * * * * * * * * * * * * 

Refused * 1 * * * * * * * * * * * * * * * 

Employment * 1 9 * 1 2 1 * 1 9 * 1 * * * 1 1 1 

Full Time * 8 * * 5 * 1 * 10 2 * 2 1 1 * * 2 

Part Time * * * * 1 * * * 1 * * * * * * * * 

Not Employed 1 7 1 * 1 1 * * 6 * * * 1 * * 1 1 

Refused * 1 * * * * * * * * * * * * * * 1 

Education 

* 1 11 * 1 2 2 * 1 9 * 1 * * * 1 1 1 

< High School * 1 * * * * * * 1 * * * * * * * * 

High School Graduate * 6 * * 1 * * * 4 * * * 1 * * 1 1 

< College * 3 1 * 4 * * * 4 * * * * 1 * * 2 

College Graduate * 2 * * 2 * * * 3 2 * 2 1 * * * 1 

Post Graduate 1 2 * * * * 1 * 5 * * * * * * * * 

Census Region Northeast * 7 * * 2 1 * * 2 1 * 1 1 * * * 1 

Midwest * 4 * * 1 * * * 4 * * * 1 * * * * 

South 2 7 1 1 4 * 1 1 9 1 * 1 * * 1 1 4 

West * 7 * * 2 1 * * 11 * 1 * * 1 * 1 * 

Day of Week Weekday 1 18 1 1 7 1 1 * 19 * 1 1 * 1 1 2 4 

Weekend 1 7 * * 2 1 * 1 7 2 * 1 2 * * * 1 

Season 

Winter 1 3 * * * 1 1 * * 1 * * 1 * * * * 

Spring * 8 * * 2 * * * 3 * * * 1 * 1 1 2 

Summer 1 10 1 1 7 1 * 1 21 1 1 2 * 1 * 1 3 

Fall * 4 * * * * * * 2 * * * * * * * * 

Asthma 

No 2 21 1 1 9 1 1 1 23 2 1 2 2 1 * 2 5 

Yes * 3 * * * 1 * * 2 * * * * * 1 * * 

DK * 1 * * * * * * 1 * * * * * * * * 

Angina No 2 24 1 1 9 2 1 1 26 2 1 2 1 1 1 2 5 

Yes * * * * * * * * * * * * 1 * * * * 

DK * 1 * * * * * * * * * * * * * * * 

Bronchitis/Emphysema No 2 22 1 1 9 2 1 1 23 2 1 2 2 1 1 2 4 

Yes * 2 * * * * * * 3 * * * * * * * 1 

DK * 1 * * * * * * * * * * * * * * * 

Note: * Signifies missing data; "DK" = respondent answered don't know; N= sample size; Refused = respondent refused to answer.

Source: Tsang And Klepeis, 1996 
Table 15-66. Range of the Average Amount of Time Actually Spent in the Water by Swimmers by the Number of Respondents 

Minutes/Month 

Total 0- 10- 20- 30- 40- 50- 60- 70- 80- 90- 110- 150- 180- 181-

N *-* 10 20 30 40 50 60 70 80 90 100 120 150 180 181 

Overall 653 13 62 75 120 20 39 131 8 2 31 2 68 10 32 40 

Gender 

Male 300 5 31 38 60 6 17 55 3 

Female 352 7 31 37 60 14 22 76 5 

Refused 1 1 * * * * * * * 

* 18 1 28 6 17 15 

2 13 1 40 4 15 25 

* * * * * * * 

Age (years) * 8 1 2 1 2 *

1-4 63 3 5 12 12 1

5-11 100 5 3 2 12 5

12-17 84 1 3 7 10 2

18-64 360 3 45 50 75 8

> 64 38 * 4 3 9 4

* * * * * * 2 * * * 

4 8 * * 2 * 7 1 3 5 

4 25 * * 7 * 16 2 11 8 

6 15 * 1 8 1 14 4 6 6 

22 74 8 * 13 1 26 3 12 20 

3 9 * 1 1 * 3 * * 1 

Race 

White 555 7 53 67 

Black 30 3 1 1 

Asian 13 * 1 1 

Some Others 12 * 1 2 

Hispanic 35 1 5 4 

Refused 8 2 1 * 

105 18 36 109 8 2 24 2 59 9 26 30 

4 * * 8 * * 5 * 1 1 1 5 

3 1 * 4 * * 1 * 1 * * 1 

1 * * 3 * * * * 2 * 1 2 

4 1 2 7 * * 1 * 4 * 4 2 

3 * 1 * * * * * 1 * * * 

Hispanic No 591 11 57 67 108 19 

Yes 55 1 5 8 10 1 

DK 2 * * * * * 

Refused 5 1 * * 2 * 

35 120 8 2 29 2 62 9 28 34 

3 10 * * 2 * 5 1 4 5 

* 1 * * * * * * * 1 

1 * * * * * 1 * * * 

Employment * 243 9 11 20 34 8 13 48 * Full Time 240 3 31 29 51 4 14 51 3

Part Time 43 * 3 10 12 1 3 2 1

Not Employed 122 1 16 16 21 7 8 30 4

Refused 5 * 1 * 2 * 1 * *

1 16 1 37 7 19 19 

* 8 * 21 3 10 12 

* 5 * 2 * * 4 

1 2 1 7 * 3 5 

* * * 1 * * * 

Education 

* 257 9 13 22 35 8

< High School 16 * 4 2 3 *

High School Graduate 112 1 12 10 16 5

< College 104 2 15 16 27 2

College Graduate 93 1 8 15 21 2

Post Graduate 71 * 10 10 18 3

15 50 * 1 17 1 39 7 20 20 

* 3 1 * 1 * * * * 2 

8 26 1 1 5 1 11 * 5 10 

4 20 3 * 4 * 6 1 2 2 

6 17 1 * 1 * 10 2 4 5 

6 15 2 * 3 * 2 * 1 1 

Census Region Northeast 136 2 12 17 28 5

Midwest 130 3 10 17 27 4

South 235 8 20 19 37 6

West 152 * 20 22 28 5

9 20 3 1 4 * 13 3 9 10 

8 24 1 * 6 * 17 1 7 5 

15 56 * * 13 1 26 4 12 18 

7 31 4 1 8 1 12 2 4 7 

Day of Week Weekday 445 11 45 52 82 14 23 87 7 2 19 * 46 8 22 27 

Weekend 208 2 17 23 38 6 16 44 1 * 12 2 22 2 10 13 

Season 

Winter 62 2 6 6 10 5 3 14 * Spring 174 3 21 24 37 7 12 32 * Summer 363 7 29 36 64 6 20 77 6

Fall 54 1 6 9 9 2 4 8 2

* 3 1 7 1 1 3 

2 6 1 13 3 6 7 

* 20 * 44 6 23 25 

* 2 * 4 * 2 5 

Asthma 

No 590 12 52 71 114 19 33 117 8 

Yes 56 1 9 3 4 * 5 14 * 

DK 7 * 1 1 2 1 1 * * 

2 26 2 64 9 26 35 

* 5 * 3 1 6 5 

* * * 1 * * * 

Angina No 639 13 60 73 118 19 37 130 8 

Yes 8 * * 2 1 1 1 1 * 

DK 6 * 2 * 1 * 1 * * 

2 30 2 66 10 32 39 

* 1 * 1 * * * 

* * * 1 * * 1 

Bronchitis/emphysema No 621 13 56 72 115 19 37 123 7 2 31 2 67 10 30 37 

Yes 26 * 5 3 4 1 1 7 * * * * * * 2 3 

DK 6 * 1 * 1 * 1 1 1 * * * 1 * * * 

Note: * Signifies missing data. DK = respondents answered don't know. Ref = respondents refused to answer. N = doer sample size

in specified range of number of minutes spent. Values of 120 , 150 , and 180 for number of minutes signify that 2 hours, 2.5 hours,

and 3 hours, respectively, were spent.

Source: Tsang and Klepeis,1996.
Table 15-67. Number of Minutes Spent Swimming in a Month in Freshwater Swimming Pool (minutes/month) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 640 2 3 10 15 30 60 90 180 181 181 181 181 

Gender Male 295 3 4 8 10 30 45 90 180 181 181 181 181 

Gender Female 345 2 3 10 15 30 60 90 180 181 181 181 181 

Age (years) 1-4 60 3 3 7.5 15 20 42.5 120 180 181 181 181 181 

Age (years) 5-11 95 2 3 20 30 45 60 120 180 181 181 181 181 

Age (years) 12-17 83 4 5 15 20 40 60 120 180 181 181 181 181 

Age (years) 18-64 357 2 3 5 10 20 45 60 120 181 181 181 181 

Age (years) > 64 38 5 5 8 10 30 40 60 120 120 181 181 181 

Race White 548 2 3 10 15 30 45 90 180 181 181 181 181 

Race Black 27 10 10 15 30 60 60 150 181 181 181 181 181 

Race Asian 13 4 4 4 20 30 60 60 120 181 181 181 181 

Race Some Others 12 2 2 2 15 25 60 150 181 181 181 181 181 

Race Hispanic 34 3 3 5 10 20 60 120 180 181 181 181 181 

Hispanic No 580 2 3 10 15 30 60 90 180 181 181 181 181 

Hispanic Yes 54 3 5 5 15 30 52.5 120 180 181 181 181 181 

Employment Full Time 237 3 4 5 10 20 45 60 150 181 181 181 181 

Employment Part Time 43 2 2 5 15 20 30 90 120 181 181 181 181 

Employment Not Employed 121 2 2 8 10 20 45 60 120 180 181 181 181 

Education < High School 16 1 1 1 2 12.5 30 60.5 181 181 181 181 181 

Education High School Graduate 111 3 5 8 10 30 60 90 180 181 181 181 181 

Education < College 102 3 3 5 10 20 30 60 120 120 180 181 181 

Education College Graduate 92 2 3 10 15 22.5 42.5 60.5 150 181 181 181 181 

Education Post Graduate 71 5 10 10 10 20 30 60 70 120 180 181 181 

Census Region Northeast 134 4 8 10 15 30 45 120 180 181 181 181 181 

Census Region Midwest 127 5 5 10 15 30 45 90 150 180 181 181 181 

Census Region South 227 2 3 5 15 30 60 120 180 181 181 181 181 

Census Region West 152 2 3 5 10 20 45 61 120 180 181 181 181 

Day of Week Weekday 434 2 3 8 10 30 60 90 180 181 181 181 181 

Day of Week Weekend 206 4 5 10 15 30 60 90 180 181 181 181 181 

Season Winter 60 2 3 5 12.5 30 52.5 90 120 180.5 181 181 181 

Season Spring 171 2 4 5 10 20 40 60 120 180 181 181 181 

Season Summer 356 3 3 10 15 30 60 120 180 181 181 181 181 

Season Fall 53 2 10 10 10 20 45 70 180 181 181 181 181 

Asthma No 578 2 3 10 15 30 55 90 180 181 181 181 181 

Asthma Yes 55 2 3 4 10 30 60 120 180 181 181 181 181 

Angina No 626 2 3 10 15 30 60 90 180 181 181 181 181 

Angina Yes 8 15 15 15 15 25 42.5 75 120 120 120 120 120 

Bronchitis/Emphysema No 608 3 3 10 15 30 60 90 180 181 181 181 181 

Bronchitis/Emphysema Yes 26 2 2 5 5 15 42.5 60 181 181 181 181 181 

Note: A Value of 181 for number of minutes signifies that more than 180 minutes were spent. N = doer sample size. Percentiles are 

the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis,1996. 
Table 15-68. Statistics for 24-Hour Cumulative Number of Minutes Spent Working in a Main Job 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 3259 475.909 179.067 3.1367 1 1440 120 395 500 570 660 740 840 930 

Gender Male 1733 492.305 186.996 4.4919 1 1440 120 417 510 595 690 770 890 955 

Gender Female 1526 457.288 167.74 4.294 2 1440 120 390 485 543 620 690 785 850 

Age (years) * 80 472.375 183.298 20.4933 5 940 117.5 377.5 482.5 560 672.5 850 900 940 

Age (years) 1-4 3 16.667 11.547 6.6667 10 30 10 10 10 30 30 30 30 30 

Age (years) 5-11 10 150.4 185.796 58.754 2 550 2 10 67.5 264 447.5 550 550 550 

Age (years) 12-17 38 293.158 180.681 29.3103 5 840 15 185 269 390 510 675 840 840 

Age (years) 18-64 2993 484.822 173.083 3.1638 1 1440 140 420 505 570 660 745 840 930 

Age (years) > 64 135 366.148 208.656 17.9582 5 990 30 185 395 500 600 660 840 940 

Race White 2630 477.536 179.01 3.4906 1 1440 120 400 500 570 660 735 845 933 

Race Black 343 466.551 175.989 9.5025 5 1037 105 390 490 550 655 735 880 990 

Race Asian 57 464.053 177.305 23.4846 5 870 45 390 493 553 660 750 780 870 

Race Some Others 56 477.411 181.661 24.2754 45 855 75 415 510 570 680 765 780 855 

Race Hispanic 125 465.88 185.322 16.5757 2 840 95 360 485 580 720 750 825 840 

Race Refused 48 492.083 191.623 27.6584 50 957 120 410 507.5 575 810 840 957 957 

Hispanic No 2980 475.393 179.214 3.2829 1 1440 120 395 500 570 660 740 850 940 

Hispanic Yes 221 481.493 174.32 11.726 2 1106 150 405 505 580 670 740 825 840 

Hispanic DK 12 529.583 146.226 42.2117 295 757 295 425 554 610 710 757 757 757 

Hispanic Refused 46 468.522 201.347 29.687 10 860 115 350 497.5 585 780 818 860 860 

Employment * 47 257.915 202.833 29.5863 2 840 5 65 245 390 540 625 840 840 

Employment Full Time 2679 504.35 164.818 3.1843 1 1440 180 450 510 582 675 750 855 950 

Employment Part Time 395 364.587 159.361 8.0183 5 945 80 250 365 480 540 600 675 795 

Employment Not Employed 112 270.946 216.024 20.4123 4 990 9 82.5 245 377.5 600 675 795 870 

Employment Refused 26 513.577 155.456 30.4875 170 840 225 440 510 570 778 790 840 840 

Education * 108 343.037 211.879 20.3881 2 860 10 176.5 342.5 510 610 675 840 840 

Education < High School 217 473.502 216.729 14.7125 4 1440 85 360 485 568 710 795 940 1080 

Education High School Graduate 1045 482.03 180.638 5.5879 1 1440 120 405 500 565 670 765 890 979 

Education < College 795 475.585 174.025 6.172 2 1440 140 409 495 563 648 750 825 905 

Education College Graduate 627 484.526 159.816 6.3824 5 1005 120 424 510 570 645 720 765 815 

Education Post Graduate 467 483.041 169.574 7.847 1 945 125 400 510 590 660 730 810 860 

Census Region Northeast 721 475.964 180.84 6.7348 1 1440 120 405 495 570 669 740 890 950 

Census Region Midwest 755 477.008 182.167 6.6297 2 1440 120 395 495 570 660 750 825 940 

Census Region South 1142 478.231 176.739 5.23 1 1440 105 405 505 570 660 735 840 900 

Census Region West 641 470.415 177.801 7.0227 5 1080 120 390 500 570 657 730 850 880 

Day Of Week Weekday 2788 487.858 166.167 3.147 1 1440 155 425 505 570 660 740 840 930 

Day Of Week Weekend 471 405.18 229.526 10.576 2 1440 30 245 415 555 670 770 870 960 

Season Winter 864 475.784 172.828 5.8797 5 1440 150 390 495 570 660 735 835 900 

Season Spring 791 472.972 195.425 6.9485 1 1440 75 390 495 570 670 765 850 915 

Season Summer 910 477.185 179.907 5.9639 1 1215 120 400 500 565 670 750 890 979 

Season Fall 694 477.739 165.961 6.2998 2 1005 130 405 510 570 645 720 780 840 

Asthma No 3042 477.013 176.967 3.2086 1 1440 120 400 500 570 660 740 840 930 

Asthma Yes 195 453.354 204.227 14.625 5 1440 45 345 480 550 668 793 855 979 

Asthma DK 22 523.182 216.952 46.2542 170 1215 225 430 500 565 780 860 1215 1215 

Angina No 3192 475.735 178.389 3.1574 1 1440 120 395 500 570 660 740 840 930 

Angina Yes 44 472.068 200.68 30.2536 10 990 60 386 500 572.5 679 730 990 990 

Angina DK 23 507.391 230.296 48.02 80 1215 170 430 500 565 780 860 1215 1215 

Bronchitis/Emphysema No 3120 476.547 178.194 3.1902 1 1440 120 400 500 570 660 740 840 930 

Bronchitis/Emphysema Yes 116 446.991 189.381 17.5836 5 985 30 367.5 480 557.5 644 720 800 855 

Bronchitis/Emphysema DK 23 535.217 226.256 47.1777 170 1215 225 430 500 600 860 875 1215 1215 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-69. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Preparation 

Percentiles 

Category Population Group N Mean Stdev Stderr 

All 4278 52.35 52.877 0.8084 

Gender Male 1342 37.77 42.133 1.1501 

Gender Female 2936 59.02 55.872 1.0311 

Age (years) * 94 52 43.217 4.4575 

Age (years) 1-4 24 56.46 60.37 12.3229 

Age (years) 5-11 60 25.17 29.688 3.8327 

Age (years) 12-17 131 21.7 37.69 3.293 

Age (years) 18-64 3173 52.07 52.872 0.9386 

Age (years) > 64 796 60.5 54.669 1.9377 

Race White 3584 51.62 53.259 0.8896 

Race Black 377 57.03 52.289 2.693 

Race Asian 62 54 41.822 5.3115 

Race Some Others 66 50.59 53.237 6.553 

Race Hispanic 132 58.76 49.73 4.3285 

Race Refused 57 53.14 49.297 6.5295 

Hispanic No 3960 51.84 52.603 0.8359 

Hispanic Yes 254 58.99 56.694 3.5573 

Hispanic DK 20 54.95 53.2 11.8959 

Hispanic Refused 44 58.61 53.296 8.0346 

Employment * 210 27.17 40.549 2.7981 

Employment Full Time 1988 45.46 46.66 1.0465 

Employment Part Time 419 53.85 55.413 2.7071 

Employment Not Employed 1626 63.62 57.743 1.432 

Employment Refused 35 53.54 66.78 11.2879 

Education * 291 31.71 42.621 2.4985 

Education < High School 450 61.26 53.232 2.5094 

Education High School Graduate 1449 58.84 56.665 1.4886 

Education < College 954 51.99 52.238 1.6913 

Education College Graduate 659 46.2 48.078 1.8728 

Education Post Graduate 475 46.04 48.686 2.2339 

Census Region Northeast 953 52.3 53.178 1.7226 

Census Region Midwest 956 53.23 51.814 1.6758 

Census Region South 1452 53.35 53.471 1.4032 

Census Region West 917 49.91 52.72 1.741 

Day Of Week Weekday 2995 50.05 49.979 0.9132 

Day Of Week Weekend 1283 57.72 58.762 1.6405 

Season Winter 1174 50.62 48.626 1.4192 

Season Spring 1038 54.39 54.484 1.6911 

Season Summer 1147 51.34 54.194 1.6002 

Season Fall 919 53.54 54.535 1.7989 

Asthma No 3948 52.02 53.176 0.8463 

Asthma Yes 300 57.14 49.443 2.8546 

Asthma DK 30 47.63 44.812 8.1815 

Angina No 4091 52.18 52.97 0.8282 

Angina Yes 149 56.81 48.238 3.9518 

Angina DK 38 53.97 60.417 9.8009 

Bronchitis/Emphysema No 4024 52.01 53.092 0.837 

Bronchitis/Emphysema Yes 216 56.91 46.683 3.1764 

Bronchitis/Emphysema DK 38 62.39 61.703 10.0096 

Min Max 5 25 50 75 90 95 98 99 

1 555 5 20 35 65 115 150 210 265 

1 480 5 13 30 50 80 105 150 210 

1 555 5 25 45 75 120 155 224 272 

5 215 5 20 40 60 110 150 195 215 

5 240 5 22.5 30 75 150 180 240 240 

1 120 2 5 11 30 60 107 120 120 

1 385 2 5 10 30 55 70 90 90 

1 555 5 20 35 65 110 145 210 265 

1 525 5 25 45 80 120 150 240 270 

1 555 5 19 35 65 110 145 210 265 

1 390 5 20 40 75 120 150 210 240 

2 210 5 20 50 70 105 130 175 210 

1 295 5 15 33.5 70 115 150 210 295 

2 315 5 23.5 52.5 79.5 110 135 225 285 

2 210 5 20 40 60 120 180 195 210 

1 555 5 20 35 65 111 145 205 255 

2 420 5 20 45 75 120 155 240 315 

6 240 8 25 45 60 112.5 180 240 240 

2 210 5 27.5 37.5 80 150 180 210 210 

1 385 2 5 15 30 60 90 120 180 

1 480 5 15 30 60 90 130 180 240 

2 520 5 20 40 65 105 125 205 255 

1 555 5 29 45 90 125 170 240 275 

2 340 2 20 30 60 120 195 340 340 

1 385 2 5 15 37 75 120 155 195 

1 555 5 30 45 90 120 150 197 225 

1 520 5 22 45 75 120 155 240 310 

1 525 5 20 34.5 65 110 150 210 245 

1 515 5 15 30 60 100 125 180 224 

1 375 5 15 30 60 95 135 200 270 

1 480 5 20 40 60 110 140 205 255 

1 520 5 20 35 65 120 150 210 265 

1 555 5 15.5 35 70 120 150 195 245 

1 515 5 15 31 60 105 135 225 265 

1 555 5 19 35 60 105 132 180 240 

1 420 5 20 40 75 130 180 240 300 

1 480 5 18 35 65 110 135 195 240 

1 525 5 20 38.5 70 120 150 224 265 

1 555 5 20 35 60 110 137 208 300 

1 520 5 20 37 67 120 155 200 265 

1 555 5 20 35 65 110 145 210 265 

1 272 5 20.5 45 75 120 160 199 240 

2 195 5 10 32.5 60 117.5 120 195 195 

1 555 5 20 35 65 115 150 210 265 

1 340 5 25 45 80 120 135 180 210 

2 240 2 10 32.5 60 120 240 240 240 

1 555 5 20 35 65 110 145 210 265 

3 240 5 20 45 85 120 150 198 210 

2 240 2 20 42.5 90 150 240 240 240 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-70. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Cleanup 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1143 32.9948 40.379 1.1944 1 825 8 15 30 35 60 85 120 135 

Gender Male 204 27.4951 20.398 1.4282 1 180 10 15 25 30 50 60 80 85 

Gender Female 939 34.1896 43.44 1.4176 1 825 5 15 30 35 60 90 120 150 

Age (years) * 24 31.0417 28.013 5.7182 10 120 10 15 30 30 60 105 120 120 

Age (years) 1-4 5 41.6 48.04 21.4839 3 120 3 15 15 55 120 120 120 120 

Age (years) 5-11 9 28.4444 21.634 7.2113 1 75 1 15 30 30 75 75 75 75 

Age (years) 12-17 28 26.75 20.573 3.8879 2 90 5 12.5 20 30 60 65 90 90 

Age (years) 18-64 808 31.3317 27.053 0.9517 1 330 10 15 30 30 60 80 120 120 

Age (years) > 64 269 38.8067 67.357 4.1068 1 825 5 15 30 40 60 105 130 270 

Race White 976 32.9652 41.685 1.3343 1 825 8 15 30 35 60 84 120 130 

Race Black 82 33.2805 28.602 3.1585 5 180 10 15 30 30 65 90 120 180 

Race Asian 11 27.0909 22.047 6.6476 3 75 3 15 15 30 60 75 75 75 

Race Some Others 17 29.7059 34.797 8.4396 5 150 5 10 15 30 60 150 150 150 

Race Hispanic 42 35.6429 39.899 6.1565 3 255 10 15 30 40 50 60 255 255 

Race Refused 15 34 28.234 7.2899 5 90 5 10 30 60 90 90 90 90 

Hispanic No 1057 32.7351 40.353 1.2412 1 825 5 15 30 35 60 85 120 130 

Hispanic Yes 68 38.9265 44.877 5.4422 3 270 10 15 30 40 60 120 255 270 

Hispanic DK 6 24.1667 9.704 3.9616 10 35 10 15 27.5 30 35 35 35 35 

Hispanic Refused 12 26.6667 18.257 5.2705 5 60 5 12.5 25 32.5 60 60 60 60 

Employment * 39 28.1538 25.77 4.1265 1 120 2 15 15 30 65 90 120 120 

Employment Full Time 432 28.4236 22.686 1.0915 2 255 8 15 25 30 50 60 90 120 

Employment Part Time 134 28.903 21.322 1.842 3 150 10 15 25 30 60 60 95 100 

Employment Not Employed 528 38.2254 53.763 2.3398 1 825 5 15 30 45 60 105 120 250 

Employment Refused 10 28 21.884 6.9202 10 60 10 10 17.5 55 60 60 60 60 

Education * 59 27.2542 22.695 2.9546 1 120 3 10 20 30 60 75 90 120 

Education < High School 135 41.8593 58.603 5.0437 2 570 5 15 30 45 85 120 180 270 

Education High School Graduate 445 33.3483 45.827 2.1724 1 825 10 15 30 30 60 90 120 120 

Education < College 259 33.5907 30.026 1.8657 5 255 10 15 30 45 60 85 105 150 

Education College Graduate 142 27.7254 21.846 1.8333 1 180 10 15 22.5 30 50 60 90 120 

Education Post Graduate 103 28.9029 34.476 3.397 3 330 5 15 25 30 50 60 60 120 

Census Region Northeast 295 32.6169 28.347 1.6504 3 270 5 15 30 40 60 90 120 120 

Census Region Midwest 252 28.4643 22.677 1.4285 1 210 5 15 30 30 50 60 85 120 

Census Region South 343 35.9242 52.496 2.8345 1 825 10 15 30 40 65 90 120 180 

Census Region West 253 33.9763 46.539 2.9259 3 570 10 15 27 30 60 75 120 255 

Day Of Week Weekday 782 32.1957 43.579 1.5584 1 825 8 15 30 30 60 75 120 120 

Day Of Week Weekend 361 34.7258 32.371 1.7037 5 270 8 15 30 40 60 90 120 180 

Season Winter 303 33.1188 51.809 2.9763 1 825 8 15 30 30 60 85 120 120 

Season Spring 245 30.2939 26.108 1.668 2 250 10 15 30 30 60 65 105 120 

Season Summer 293 33.157 29.932 1.7487 2 270 5 15 30 40 60 90 120 135 

Season Fall 302 34.904 45.406 2.6128 1 570 8 15 30 40 60 90 120 180 

Asthma No 1047 32.7708 40.408 1.2488 1 825 6 15 30 35 60 85 120 120 

Asthma Yes 91 35.956 40.996 4.2975 2 255 8 15 30 40 60 90 250 255 

Asthma DK 5 26 20.736 9.2736 10 60 10 10 20 30 60 60 60 60 

Angina No 1092 32.9661 40.95 1.2392 1 825 8 15 30 35 60 85 120 150 

Angina Yes 45 32.3111 22.926 3.4175 5 120 5 15 30 45 60 60 120 120 

Angina DK 6 43.3333 41.793 17.062 10 120 10 10 30 60 120 120 120 120 

Bronchitis/Emphysema No 1065 31.77 28.195 0.864 1 330 8 15 30 35 60 80 120 120 

Bronchitis/Emphysema Yes 71 50.8592 118.417 14.0535 3 825 5 15 29 35 70 105 570 825 

Bronchitis/Emphysema DK 7 38.1429 41.119 15.5417 2 120 2 10 30 60 120 120 120 120 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-71. Statistics for 24-Hour Cumulative Number of Minutes Spent Cleaning House 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1910 114.798 111.683 2.5555 1 810 10 30 80 150 255 335 465 525 

Gender Male 351 100.353 110.445 5.8951 1 810 10 30 60 120 240 310 400 495 

Gender Female 1559 118.051 111.737 2.8299 1 790 15 40 90 160 255 340 465 540 

Age (years) * 45 136.2 114.124 17.0127 10 480 10 55 105 180 297 320 480 480 

Age (years) 1-4 11 74.091 69.42 20.9308 10 270 10 40 60 90 90 270 270 270 

Age (years) 5-11 49 42.633 35.19 5.0271 1 180 5 20 30 53 90 120 180 180 

Age (years) 12-17 67 78.746 79.357 9.695 1 300 5 20 55 105 240 240 285 300 

Age (years) 18-64 1307 115.55 111.597 3.0868 1 810 15 30 85 150 270 350 435 510 

Age (years) > 64 431 125.132 118.341 5.7003 3 790 10 45 90 170 250 340 540 570 

Race White 1614 115.85 111.348 2.7716 1 790 10 35 85 155 255 330 435 540 

Race Black 139 108.712 106.826 9.0609 1 490 5 30 80 135 270 358 480 484 

Race Asian 32 97.656 101.091 17.8705 15 425 15 30 60 127.5 265 345 425 425 

Race Some Others 26 80.5 58.059 11.3864 5 210 10 35 60 115 185 190 210 210 

Race Hispanic 73 99.781 110.669 12.9528 5 548 10 30 60 120 210 345 470 548 

Race Refused 26 179.615 176.878 34.6886 10 810 20 30 135 240 390 465 810 810 

Hispanic No 1740 114.153 109.99 2.6368 1 790 10 30 80 150 255 330 435 525 

Hispanic Yes 134 110.134 115.754 9.9996 5 658 10 34 60 135 240 360 480 548 

Hispanic DK 14 136.071 131.591 35.1691 10 510 10 30 92.5 210 240 510 510 510 

Hispanic Refused 22 180.682 177.33 37.8069 10 810 20 45 138 240 340 390 810 810 

Employment * 128 64.453 66.811 5.9053 1 300 5 22.5 45 77.5 180 240 270 285 

Employment Full Time 673 100.944 99.87 3.8497 1 655 10 30 60 120 240 310 410 480 

Employment Part Time 195 119.415 115.568 8.276 1 660 15 45 85 175 265 390 480 540 

Employment Not Employed 901 129.566 118.009 3.9314 3 790 15 50 95 180 285 360 480 570 

Employment Refused 13 235 218.908 60.7142 10 810 10 120 180 255 450 810 810 810 

Education * 161 81.379 98.129 7.7337 1 810 5 28 45 100 225 265 300 375 

Education < High School 234 135.731 121.618 7.9504 3 715 10 50 115 180 297 390 540 560 

Education High School Graduate 665 121.899 118.814 4.6074 2 790 15 40 90 160 270 360 484 610 

Education < College 432 108.343 100.456 4.8332 1 570 10 30 85 149 240 315 420 470 

Education College Graduate 247 101.097 96.605 6.1468 1 525 15 30 60 127 240 315 390 465 

Education Post Graduate 171 126.105 118.897 9.0923 5 655 15 45 90 180 280 390 495 540 

Census Region Northeast 454 116.969 117.268 5.5037 2 790 10 30 90 164 240 330 480 655 

Census Region Midwest 406 114.086 111.049 5.5113 1 720 10 30 80 150 240 325 475 495 

Census Region South 636 114.36 112.921 4.4776 1 810 10 30 80 150 270 360 435 525 

Census Region West 414 113.79 104.234 5.1228 5 720 15 40 82.5 160 240 330 400 470 

Day Of Week Weekday 1287 108.319 108.542 3.0256 1 790 10 30 70 150 240 315 465 540 

Day Of Week Weekend 623 128.185 116.861 4.682 1 810 15 45 90 180 290 370 435 525 

Season Winter 464 105.554 98.348 4.5657 1 810 10 30 75 150 240 285 360 465 

Season Spring 445 114.202 109.757 5.203 3 720 15 30 75 165 240 340 465 525 

Season Summer 546 109.908 113.686 4.8653 1 690 10 30 71 135 245 365 465 548 

Season Fall 455 130.677 122.137 5.7259 1 790 15 45 90 180 300 390 480 560 

Asthma No 1764 114.32 110.119 2.6219 1 790 10 30 82.5 150 255 330 450 525 

Asthma Yes 133 114.699 117.523 10.1905 5 690 10 33 64 150 270 390 470 480 

Asthma DK 13 180.769 214.533 59.5007 10 810 10 45 120 240 340 810 810 810 

Angina No 1826 113.702 110.563 2.5874 1 790 14 30 80 150 255 330 465 525 

Angina Yes 70 120.371 103.11 12.324 5 394 5 30 90 190 262.5 320 370 394 

Angina DK 14 230 210.868 56.3569 10 810 10 120 210 255 480 810 810 810 

Bronchitis/Emphysema No 1791 113.894 111.025 2.6234 1 790 10 30 80 150 255 340 450 540 

Bronchitis/Emphysema Yes 100 118.11 104.363 10.4363 5 480 7.5 32.5 90 180 262.5 297.5 467.5 475 

Bronchitis/Emphysema DK 19 182.632 179.253 41.1234 5 810 5 50 150 240 340 810 810 810 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-72. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Cleaning 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 692 145.9 121.42 4.616 2 720 25 60 120 180 300 405 510 570 

Gender Male 417 160.8 131.68 6.448 10 720 30 60 120 200 345 480 533 600 

Gender Female 275 123.2 99.98 6.029 2 635 10 60 90 160 268 330 390 465 

Age (years) * 13 210.5 157.91 43.796 30 600 30 112 140 250 395 600 600 600 

Age (years) 1-4 4 138.3 116.84 58.421 30 285 30 45 119 231.5 285 285 285 285 

Age (years) 5-11 12 104.6 62.921 18.164 30 210 30 58 80 165 190 210 210 210 

Age (years) 12-17 20 142.3 96.274 21.527 30 385 32.5 75 127 157.5 300 372.5 385 385 

Age (years) 18-64 479 147.4 125.22 5.721 2 690 15 60 120 180 310 435 520 570 

Age (years) > 64 164 139.9 112.13 8.756 2 720 30 60 120 172.5 300 350 480 510 

Race White 621 146.4 122.18 4.903 2 720 25 60 120 180 305 410 510 560 

Race Black 30 134.2 99.049 18.084 2 405 10 60 117.5 190 262.5 330 405 405 

Race Asian 6 65 27.568 11.255 30 90 30 30 77.5 85 90 90 90 90 

Race Some Others 12 163.5 97.091 28.028 39 380 39 90 157.5 187.5 290 380 380 380 

Race Hispanic 14 128.2 82.593 22.074 30 300 30 65 105 180 255 300 300 300 

Race Refused 9 206.7 213.95 71.317 30 600 30 60 120 300 600 600 600 600 

Hispanic No 652 145.6 121.19 4.746 2 720 25 60 120 180 300 405 510 560 

Hispanic Yes 26 115.3 76.402 14.984 10 300 25 60 116.5 145 240 255 300 300 

Hispanic DK 5 218 103.05 46.087 120 380 120 140 210 240 380 380 380 380 

Hispanic Refused 9 216.7 206.64 68.88 60 600 60 60 120 300 600 600 600 600 

Employment * 38 132.1 88.152 14.3 30 385 30 60 115 165 255 360 385 385 

Employment Full Time 315 147.7 123.2 6.942 4 690 30 60 120 180 300 435 530 560 

Employment Part Time 52 135.1 103.74 14.387 2 470 15 60 112.5 180 300 325 325 470 

Employment Not Employed 280 145.1 122.82 7.34 2 720 20 60 120 180 310 412.5 480 655 

Employment Refused 7 252.9 216.41 81.794 15 600 15 120 120 465 600 600 600 600 

Education * 46 136.8 115.99 17.101 2 600 30 60 112.5 165 285 360 600 600 

Education < High School 96 146 124.59 12.716 2 510 10 60 119.5 180 330 465 480 510 

Education High School Graduate 237 154.2 126.38 8.209 5 720 30 60 120 180 310 415 520 660 

Education < College 142 146.7 119.87 10.059 4 655 30 60 120 185 270 375 560 570 

Education College Graduate 99 137.3 124.43 12.505 10 555 15 60 95 175 325 475 533 555 

Education Post Graduate 72 134.3 103.25 12.168 10 495 30 60 120 165 290 345 465 495 

Census Region Northeast 144 135.2 113.42 9.451 5 600 15 60 110 185 300 330 510 555 

Census Region Midwest 155 131 111.34 8.943 4 655 15 60 95 150 270 360 510 560 

Census Region South 218 158.7 117.58 7.964 2 635 30 70 120 195 330 415 510 520 

Census Region West 175 151.8 138.65 10.481 2 720 25 60 120 180 355 475 530 690 

Day Of Week Weekday 420 132.5 109.32 5.334 4 660 20 60 105 175 285 360 475 530 

Day Of Week Weekend 272 166.6 135.66 8.225 2 720 30 60 120 227.5 345 495 533 635 

Season Winter 128 149.5 135.12 11.943 4 600 15 59.5 102.5 225 345 465 510 520 

Season Spring 252 151.3 116.12 7.315 5 690 30 70 120 180 300 410 510 530 

Season Summer 205 133 104.23 7.28 5 635 20 60 120 180 270 325 475 555 

Season Fall 107 153.4 144.65 13.984 2 720 15 60 120 180 360 480 655 660 

Asthma No 640 147.3 121.44 4.8 2 720 27.5 60 120 180 307.5 400 510 560 

Asthma Yes 47 109.1 87.096 12.704 5 510 15 60 90 135 210 240 510 510 

Asthma DK 5 312 230.04 102.879 60 600 60 120 300 480 600 600 600 600 

Angina No 665 143.6 118.92 4.611 2 720 25 60 120 180 300 385 510 560 

Angina Yes 18 144.7 96.703 22.793 30 330 30 60 135 165 330 330 330 330 

Angina DK 9 318.9 213.67 71.223 10 600 10 120 325 480 600 600 600 600 

Bronchitis/emphysema No 661 146.2 120.68 4.694 2 720 30 60 120 180 300 395 510 560 

Bronchitis/emphysema Yes 26 104.8 85.282 16.725 5 375 10 60 90 135 225 300 375 375 

Bronchitis/emphysema DK 5 312 230.04 102.879 60 600 60 120 300 480 600 600 600 600 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-73. Statistics for 24-Hour Cumulative Number of Minutes Spent in Clothes Care 

Percentiles 

Category Population Group N Mean Stdev Stderr 

All 893 79.479 73.355 2.455 

Gender Male 117 72.248 67.028 6.197 

Gender Female 776 80.57 74.241 2.665 

Age (years) * 10 59.5 34.757 10.991 

Age (years) 1-4 4 70 94.251 47.126 

Age (years) 5-11 11 39 33.856 10.208 

Age (years) 12-17 21 37.476 39.447 8.608 

Age (years) 18-64 702 80.474 74.354 2.806 

Age (years) > 64 145 85.455 73.545 6.108 

Race White 737 80.096 73.392 2.703 

Race Black 99 68.636 65.289 6.562 

Race Asian 7 107.857 48.807 18.447 

Race Some Others 10 62.4 39.09 12.361 

Race Hispanic 33 92.879 78.01 13.58 

Race Refused 7 100.714 166.018 62.749 

Hispanic No 836 78.248 72.306 2.501 

Hispanic Yes 51 91.176 71.178 9.967 

Hispanic DK 3 118.333 62.517 36.094 

Hispanic Refused 3 185 251.942 145.459 

Employment * 34 43.412 46.313 7.943 

Employment Full Time 402 73.443 73.706 3.676 

Employment Part Time 116 80.724 68.545 6.364 

Employment Not Employed 336 89.804 75.166 4.101 

Employment Refused 5 87.4 74.725 33.418 

Education * 43 47.488 48.217 7.353 

Education < High School 102 86.51 60.048 5.946 

Education High School Graduate 337 85.19 82.249 4.48 

Education < College 193 85.87 78.466 5.648 

Education College Graduate 127 67.756 56.995 5.058 

Education Post Graduate 91 68.374 64.714 6.784 

Census Region Northeast 222 76.905 67.875 4.555 

Census Region Midwest 201 78.448 75.998 5.36 

Census Region South 304 81.839 75.654 4.339 

Census Region West 166 79.849 73.398 5.697 

Day Of Week Weekday 607 75.853 72.909 2.959 

Day Of Week Weekend 286 87.175 73.832 4.366 

Season Winter 254 82.291 80.245 5.035 

Season Spring 213 86.103 79.325 5.435 

Season Summer 259 76.722 68.328 4.246 

Season Fall 167 71.03 60.463 4.679 

Asthma No 829 79.534 74.024 2.571 

Asthma Yes 62 79.855 65.269 8.289 

Asthma DK 2 45 21.213 15 

Angina No 867 79.516 73.48 2.496 

Angina Yes 22 81.591 75.756 16.151 

Angina DK 4 60 24.495 12.247 

Bronchitis/emphysema No 834 78.45 73.617 2.549 

Bronchitis/emphysema Yes 58 94.621 68.927 9.051 

Bronchitis/emphysema DK 1 60 0 0 

Min Max 5 25 50 75 90 95 98 99 

2 535 10 30 60 118 175 210 300 375 

5 360 7 20 60 90 150 210 300 335 

2 535 10 30 60 120 180 225 300 375 

15 120 15 25 60 90 105 120 120 120 

5 210 5 17.5 32.5 122.5 210 210 210 210 

2 92 2 5 30 60 90 92 92 92 

3 150 5 10 20 60 80 120 150 150 

2 535 10 28 60 120 180 210 300 360 

2 375 10 30 60 120 180 245 300 375 

2 535 10 30 60 118 175 223 300 375 

5 300 5 15 45 110 165 210 240 300 

60 210 60 80 90 120 210 210 210 210 

18 120 18 21 65 90 120 120 120 120 

5 265 5 20 90 150 210 225 265 265 

15 475 15 20 45 60 475 475 475 475 

2 535 10 30 60 115 165 210 300 360 

5 265 5 20 90 150 190 225 225 265 

55 180 55 55 120 180 180 180 180 180 

20 475 20 20 60 475 475 475 475 475 

2 210 3 10 30 60 92 150 210 210 

2 535 5 20 60 100 155 223 300 360 

2 335 10 30 67.5 117.5 180 225 240 330 

2 475 10 35 60 120 185 235 300 375 

2 180 2 45 60 150 180 180 180 180 

2 210 5 10 30 60 92 150 210 210 

10 265 15 38 65 120 175 210 240 245 

2 535 10 30 60 120 180 240 375 445 

2 475 5 21 60 120 190 240 300 375 

5 260 10 20 60 90 150 190 225 225 

5 360 5 20 60 90 145 210 245 360 

2 535 10 30 60 120 150 200 245 300 

2 475 5 20 60 115 170 210 265 420 

5 450 10 30 60 115 170 235 330 375 

2 405 5 20 60 120 180 223 300 360 

2 475 5 25 60 105 160 210 300 375 

5 535 10 30 65 120 180 223 300 335 

2 475 7 23 60 120 190 225 330 445 

2 450 10 30 60 120 180 240 335 375 

2 535 8 30 60 115 154 190 240 360 

3 300 5 25 60 105 150 195 240 300 

2 535 10 30 60 118 180 225 300 360 

5 375 10 30 66.5 120 154 180 200 375 

30 60 30 30 45 60 60 60 60 60 

2 535 10 30 60 120 178 210 300 375 

5 335 10 30 60 120 155 195 335 335 

30 90 30 45 60 75 90 90 90 90 

2 535 8 25 60 115 170 210 300 375 

5 335 15 60 77.5 120 190 240 300 335 

60 60 60 60 60 60 60 60 60 60 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-74. Statistics for 24-Hour Cumulative Number of Minutes Spent in Car Repair/Maintenance 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 145 123.407 147.198 12.224 5 700 5 30 60 150 300 495 670 690 

Gender Male 110 135.582 152.737 14.563 5 700 5 30 85 170 300 505 600 670 

Gender Female 35 85.143 122.441 20.696 5 690 5 15 45 120 180 270 690 690 

Age (years) * 1 60 * * 60 60 60 60 60 60 60 60 60 60 

Age (years) 1-4 1 150 * * 150 150 150 150 150 150 150 150 150 150 

Age (years) 5-11 1 300 * * 300 300 300 300 300 300 300 300 300 300 

Age (years) 12-17 8 106.875 163.837 57.925 20 505 20 30 45 90 505 505 505 505 

Age (years) 18-64 114 130.342 156.511 14.659 5 700 5 30 77.5 165 300 520 670 690 

Age (years) > 64 20 83.5 68.347 15.283 10 300 12.5 30 70 120 150 240 300 300 

Race White 112 139.607 158.66 14.992 5 700 10 30 90 175 300 520 670 690 

Race Black 19 85.789 93.516 21.454 5 300 5 20 60 95 300 300 300 300 

Race Asian 2 10 7.071 5 5 15 5 5 10 15 15 15 15 15 

Race Some Others 6 43.333 42.387 17.304 5 120 5 10 32.5 60 120 120 120 120 

Race Hispanic 6 58 51.595 21.063 5 120 5 13 45 120 120 120 120 120 

Hispanic No 133 123.617 144.993 12.573 5 700 5 30 80 150 300 495 670 690 

Hispanic Yes 10 98.8 153.362 48.497 5 520 5 30 45 120 320 520 520 520 

Hispanic DK 2 232.5 321.734 227.5 5 460 5 5 233 460 460 460 460 460 

Employment * 10 130.5 156.87 49.607 20 505 20 30 52.5 150 402.5 505 505 505 

Employment Full Time 77 122.091 150.192 17.116 5 700 5 30 60 165 300 520 670 700 

Employment Part Time 12 123.167 138.769 40.059 8 495 8 40 72.5 150 270 495 495 495 

Employment Not Employed 46 124.13 146.952 21.667 5 690 10 30 90 120 300 480 690 690 

Education * 13 120 139.523 38.697 15 505 15 30 60 120 300 505 505 505 

Education < High School 17 185.882 224.418 54.429 5 670 5 30 90 220 555 670 670 670 

Education High School Graduate 50 111.52 128.261 18.139 5 690 5 30 67.5 120 270 350 585 690 

Education < College 31 138.226 169.231 30.395 5 700 10 30 85 180 280 600 700 700 

Education College Graduate 20 93.25 99.344 22.214 10 300 10 15 45 135 285 300 300 300 

Education Post Graduate 14 103.429 97.566 26.076 5 300 5 30 75 120 300 300 300 300 

Census Region Northeast 28 130.75 163.729 30.942 8 690 10 30 60 200 300 520 690 690 

Census Region Midwest 31 149.839 173.193 31.106 10 670 10 45 90 120 350 600 670 670 

Census Region South 45 106.778 131.409 19.589 5 700 5 30 60 120 240 300 700 700 

Census Region West 41 116.659 132.206 20.647 5 505 5 30 60 120 300 460 505 505 

Day Of Week Weekday 79 108.519 125.914 14.166 5 690 5 15 60 150 280 350 480 690 

Day Of Week Weekend 66 141.227 168.477 20.738 5 700 10 45 82.5 150 495 555 670 700 

Season Winter 49 130.673 167.715 23.959 5 690 5 30 60 165 350 600 690 690 

Season Spring 39 136.667 156.042 24.987 5 700 5 45 85 150 300 555 700 700 

Season Summer 35 121.514 137.704 23.276 5 505 5 30 60 150 300 480 505 505 

Season Fall 22 86.727 87.502 18.655 5 300 8 10 70 120 240 270 300 300 

Asthma No 137 117.657 139.579 11.925 5 700 5 30 60 120 300 495 600 690 

Asthma Yes 8 221.875 235.553 83.281 15 670 15 30 150 365 670 670 670 670 

Angina No 139 125.712 149.156 12.651 5 700 5 30 75 150 300 505 670 690 

Angina Yes 5 51 72.921 32.611 5 180 5 15 20 35 180 180 180 180 

Angina DK 1 165 * * 165 165 165 165 165 165 165 165 165 165 

Bronchitis/Emphysema No 140 122.279 145.67 12.311 5 700 5 30 67.5 135 300 500 670 690 

Bronchitis/Emphysema Yes 5 155 203.347 90.94 5 460 5 10 30 270 460 460 460 460 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". N = doer sample size. Mean = Mean 24-hour cumulative number of

minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. 

Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-75. Statitstics for 24-Hour Cumulative Number of Minutes Spent in Other Repairs 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 288 184.816 184.111 10.849 2 1080 10 36.5 120 300 425 525 690 840 

Gender Male 200 205.045 187.704 13.273 2 1080 10 60 150 327.5 460 555 680 810 

Gender Female 88 138.841 167.784 17.886 3 900 5 17.5 72.5 192.5 360 425 750 900 

Age (years) * 1 540 * * 540 540 540 540 540 540 540 540 540 540 

Age (years) 5-11 3 66.667 55.076 31.798 10 120 10 10 70 120 120 120 120 120 

Age (years) 12-17 14 119.5 103.383 27.63 15 345 15 30 90 180 285 345 345 345 

Age (years) 18-64 221 198.471 192.928 12.978 2 1080 10 45 120 325 434 570 750 840 

Age (years) > 64 49 141.878 146.868 20.981 2 526 10 30 75 209 390 480 526 526 

Race White 264 186.367 184.944 11.382 2 1080 10 36.5 120 300 430 525 670 840 

Race Black 13 150.385 207.961 57.678 10 750 10 30 90 120 390 750 750 750 

Race Asian 3 321.667 89.489 51.667 270 425 270 270 270 425 425 425 425 425 

Race Some Others 3 173.667 165.228 95.395 45 360 45 45 116 360 360 360 360 360 

Race Hispanic 4 127.5 122.848 61.424 10 290 10 35 105 220 290 290 290 290 

Race Refused 1 75 * * 75 75 75 75 75 75 75 75 75 75 

Hispanic No 278 184.917 184.467 11.064 2 1080 10 35 120 300 425 525 690 840 

Hispanic Yes 9 160.556 180.666 60.222 10 575 10 60 60 210 575 575 575 575 

Hispanic DK 1 375 * * 375 375 375 375 375 375 375 375 375 375 

Employment * 17 110.176 97.439 23.632 10 345 10 30 90 180 285 345 345 345 

Employment Full Time 140 199.993 206.025 17.412 5 1080 8.5 60 120 297.5 470 600 840 900 

Employment Part Time 27 167.963 153.74 29.587 5 490 10 25 120 302 390 434 490 490 

Employment Not Employed 102 183.314 169.14 16.747 2 670 10 30 120 315 420 480 526 600 

Employment Refused 2 61 83.439 59 2 120 2 2 61 120 120 120 120 120 

Education * 18 110.722 94.558 22.287 10 345 10 30 90 180 285 345 345 345 

Education < High School 23 214.348 215.017 44.834 15 900 30 45 120 360 480 490 900 900 

Education High School Graduate 90 194.4 196.472 20.71 3 840 5 30 132.5 300 447 575 780 840 

Education < College 64 202.156 200.764 25.095 2 1080 10 32.5 130 355 420 480 600 1080 

Education College Graduate 54 169 154.537 21.03 5 525 10 60 97.5 270 425 490 510 525 

Education Post Graduate 39 172.923 174.213 27.896 2 690 7 38 120 270 420 600 690 690 

Census Region Northeast 55 166.164 181.344 24.452 3 840 5 30 75 210 415 525 600 840 

Census Region Midwest 77 188.909 170.219 19.398 10 780 15 60 120 315 420 460 670 780 

Census Region South 89 202.281 212.332 22.507 2 1080 10 30 120 315 480 570 900 1080 

Census Region West 67 172.224 161.66 19.75 2 750 7 60 120 243 340 526 690 750 

Day Of Week Weekday 188 178.213 171.94 12.54 2 780 10 42.5 110 300 430 490 600 750 

Day Of Week Weekend 100 197.23 205.392 20.539 3 1080 5 32.5 145 296.5 420 585 870 990 

Season Winter 62 167.097 172.076 21.854 3 600 5 15 90 300 445 490 540 600 

Season Spring 65 203.123 216.629 26.87 5 900 10 45 120 300 480 670 840 900 

Season Summer 95 180.442 182.013 18.674 2 1080 10 60 120 290 390 510 750 1080 

Season Fall 66 189.727 164.551 20.255 2 600 10 55 120 330 420 435 600 600 

Asthma No 264 180.33 183.699 11.306 2 1080 10 36.5 120 288.5 420 525 690 840 

Asthma Yes 24 234.167 185.283 37.821 5 670 10 45 210 352.5 480 510 670 670 

Angina No 281 179.687 175.258 10.455 2 900 10 30 120 295 420 490 670 780 

Angina Yes 6 448.333 369.995 151.05 90 1080 90 100 410 600 1080 1080 1080 1080 

Angina DK 1 45 * * 45 45 45 45 45 45 45 45 45 45 

Bronchitis/emphysema No 276 184.681 185.591 11.171 2 1080 10 36.5 120 299 430 526 690 840 

Bronchitis/emphysema Yes 12 187.917 152.591 44.049 5 405 5 45 165 350 360 405 405 405 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-76. Statistics for 24-Hour Cumulative Number of Minutes Spent in Plant Care 

Percentiles 

Category Population Group N Mean Stdev Stderr 

All 254 103.602 108.761 6.824 

Gender Male 84 146.274 145.969 15.926 

Gender Female 170 82.518 76.759 5.887 

Age (years) * 4 51.25 24.622 12.311 

Age (years) 5-11 5 121 120.955 54.093 

Age (years) 12-17 3 51 61.262 35.369 

Age (years) 18-64 157 100.49 104.921 8.374 

Age (years) > 64 85 112.647 118.439 12.846 

Race White 233 102.124 106.695 6.99 

Race Black 8 81.25 90.149 31.872 

Race Asian 3 140 45.826 26.458 

Race Some Others 2 137.5 187.383 132.5 

Race Hispanic 6 164.167 209.796 85.649 

Race Refused 2 95 49.497 35 

Hispanic No 244 102.971 106.161 6.796 

Hispanic Yes 7 149.286 195.521 73.9 

Hispanic DK 1 60 * * 

Hispanic Refused 2 42.5 24.749 17.5 

Employment * 8 94.75 103.657 36.648 

Employment Full Time 94 94.436 111.848 11.536 

Employment Part Time 25 112.2 104.812 20.962 

Employment Not Employed 124 108.387 108.655 9.758 

Employment Refused 3 145 99.875 57.663 

Education * 9 86.444 100.113 33.371 

Education < High School 30 92.333 108.753 19.855 

Education High School Graduate 93 87.656 95.248 9.877 

Education < College 47 118.298 112.855 16.462 

Education College Graduate 35 139 107.818 18.225 

Education Post Graduate 40 104.75 131.036 20.719 

Census Region Northeast 55 116.055 116.677 15.733 

Census Region Midwest 41 101.659 109.248 17.062 

Census Region South 77 82.078 76.081 8.67 

Census Region West 81 116.593 126.602 14.067 

Day Of Week Weekday 170 104.559 105.561 8.096 

Day Of Week Weekend 84 101.667 115.595 12.612 

Season Winter 15 135.333 170.592 44.047 

Season Spring 96 124.323 108.656 11.09 

Season Summer 111 89.82 100.882 9.575 

Season Fall 32 74.375 87.894 15.538 

Asthma No 239 105 108.541 7.021 

Asthma Yes 15 81.333 113.68 29.352 

Angina No 240 103.083 107.762 6.956 

Angina Yes 13 120.769 130.286 36.135 

Angina DK 1 5 * * 

Bronchitis/emphysema No 248 105.202 109.525 6.955 

Bronchitis/emphysema Yes 6 37.5 24.238 9.895 

Min Max 5 25 50 75 90 95 98 99 

3 630 10 30 60 130 225 300 480 570 

10 630 15 32.5 105 195 380 480 570 630 

3 630 10 30 60 120 180 210 270 325 

15 70 15 37.5 60 65 70 70 70 70 

35 330 35 60 60 120 330 330 330 330 

3 120 3 3 30 120 120 120 120 120 

5 570 10 30 60 135 225 300 475 565 

5 630 10 35 75 135 240 280 630 630 

3 630 10 30 60 120 225 300 480 570 

15 280 15 15 50 112.5 280 280 280 280 

90 180 90 90 150 180 180 180 180 180 

5 270 5 5 138 270 270 270 270 270 

15 565 15 15 90 210 565 565 565 565 

60 130 60 60 95 130 130 130 130 130 

3 630 10 30 60 132.5 225 280 480 570 

15 565 15 15 60 210 565 565 565 565 

60 60 60 60 60 60 60 60 60 60 

25 60 25 25 42.5 60 60 60 60 60 

3 330 3 32.5 60 120 330 330 330 330 

5 630 10 30 60 120 195 325 570 630 

15 485 15 30 90 150 210 270 485 485 

5 630 10 40 72.5 127.5 240 270 480 565 

60 255 60 60 120 255 255 255 255 255 

3 330 3 30 60 120 330 330 330 330 

10 475 10 15 60 120 170 420 475 475 

5 565 10 30 60 120 180 255 480 565 

5 630 10 50 90 150 240 240 630 630 

15 485 15 55 120 195 280 325 485 485 

15 630 15 30 60 120 217.5 420 630 630 

3 485 10 30 70 150 250 420 480 485 

5 630 30 30 60 120 195 270 630 630 

5 475 10 30 60 120 175 225 300 475 

10 630 14 30 75 150 240 330 570 630 

3 630 14 30 60 130 225 280 480 565 

5 630 10 30 60 127.5 240 325 570 630 

5 565 5 30 60 175 485 565 565 565 

5 570 15 45 90 150 270 330 475 570 

3 630 10 30 60 120 190 225 420 630 

5 480 10 25 47.5 102.5 135 195 480 480 

3 630 10 30 60 135 235 300 485 570 

5 450 5 15 55 90 175 450 450 450 

3 630 10 30 60 125 225 290 480 570 

15 485 15 55 60 135 270 485 485 485 

5 5 5 5 5 5 5 5 5 5 

3 630 10 30 60 135 235 300 485 570 

5 60 5 15 42.5 60 60 60 60 60 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-77. Statistics for 24-Hour Cumulative Number of Minutes Spent in Animal Care 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 764 48.168 65.029 2.3527 1 760 5 10 30 60 120 155 230 312 

Gender Male 282 57.291 81.786 4.8703 1 760 5 15 30 65 120 180 308 340 

Gender Female 482 42.83 52.182 2.3768 1 450 3 10 28.5 60 105 140 187 273 

Age (years) * 13 37.462 38.606 10.7074 2 135 2 5 30 55 80 135 135 135 

Age (years) 1-4 9 59.222 44.291 14.7637 3 140 3 30 60 90 140 140 140 140 

Age (years) 5-11 27 47.296 43.1 8.2946 2 179 8 15 38 65 120 150 179 179 

Age (years) 12-17 49 55.204 68.276 9.7537 3 308 5 10 25 90 175 180 308 308 

Age (years) 18-64 530 45.928 66.581 2.8921 1 760 3 10 30 60 109 150 230 280 

Age (years) > 64 136 54.824 64.527 5.5331 1 383 5 15 30 60 135 180 340 340 

Race White 696 47.757 62.011 2.3505 1 760 4 10 30 60 120 155 240 312 

Race Black 26 37.577 39.832 7.8117 1 145 1 10 25 45 120 120 145 145 

Race Asian 5 30.4 21.87 9.7806 10 60 10 15 20 47 60 60 60 60 

Race Some Others 12 100 193.567 55.878 5 690 5 17.5 30 65 205 690 690 690 

Race Hispanic 17 37.765 44.992 10.9123 5 180 5 15 30 35 120 180 180 180 

Race Refused 8 73.75 58.478 20.675 5 180 5 32.5 55 115 180 180 180 180 

Hispanic No 712 47.81 61.479 2.304 1 760 4 10 30 60 120 151 230 308 

Hispanic Yes 39 50.872 112.78 18.0593 2 690 3 10 20 35 120 180 690 690 

Hispanic DK 6 50 77.071 31.4643 10 205 10 10 15 45 205 205 205 205 

Hispanic Refused 7 67.857 62.039 23.4485 5 180 5 20 60 120 180 180 180 180 

Employment * 86 51.221 56.803 6.1252 2 308 5 15 30 70 120 175 240 308 

Employment Full Time 376 44.918 71.458 3.6852 1 760 3 10 25 60 90 145 240 340 

Employment Part Time 60 48.883 56.285 7.2664 3 230 5 12.5 20 60 152.5 176.5 205 230 

Employment Not Employed 233 52.459 59.357 3.8886 1 383 5 15 30 60 120 180 273 330 

Employment Refused 9 38.889 53.897 17.9656 5 180 5 20 30 30 180 180 180 180 

Education * 98 52.347 57.02 5.7599 2 308 5 15 30 70 140 180 240 308 

Education < High School 63 51.492 68.122 8.5825 1 383 5 15 30 60 120 225 273 383 

Education High School Graduate 231 52.913 75.819 4.9885 1 760 5 10 30 70 120 165 245 330 

Education < College 150 40.593 49.247 4.021 1 280 4 10 20 55 97.5 155 205 230 

Education College Graduate 121 51.273 79.213 7.2012 1 690 3 15 30 60 110 135 340 340 

Education Post Graduate 101 38.713 40.069 3.987 1 240 5 12 30 57 80 105 150 185 

Census Region Northeast 171 39.789 44.88 3.432 1 273 3 10 25 60 90 120 205 245 

Census Region Midwest 181 49.773 58.716 4.3644 1 330 4 14 30 60 120 180 240 312 

Census Region South 247 51.389 75.022 4.7736 1 760 5 15 30 60 120 165 308 383 

Census Region West 165 50.267 72.551 5.6481 1 690 3 10 30 60 120 155 210 340 

Day Of Week Weekday 527 46.602 66.468 2.8954 1 760 4 10 30 60 115 155 195 280 

Day Of Week Weekend 237 51.65 61.703 4.0081 1 383 5 15 30 60 120 180 273 330 

Season Winter 221 44.62 66.372 4.4647 1 690 4 10 25 55 95 160 225 245 

Season Spring 201 52.99 60.351 4.2568 1 340 5 15 30 60 120 175 240 330 

Season Summer 216 51.426 76.405 5.1987 1 760 5 15 30 64 120 165 240 383 

Season Fall 126 41.111 45.413 4.0457 1 280 3 10 25 60 110 135 180 180 

Asthma No 705 48.401 65.505 2.4671 1 760 4 10 30 60 120 155 225 308 

Asthma Yes 57 45.386 60.468 8.0091 1 330 5 10 30 55 105 195 240 330 

Asthma DK 2 45 21.213 15 30 60 30 30 45 60 60 60 60 60 

Angina No 734 47.834 64.308 2.3737 1 760 5 10 30 60 120 155 225 280 

Angina Yes 27 58.704 85.601 16.474 2 340 3 15 30 60 135 330 340 340 

Angina DK 3 35 22.913 13.2288 15 60 15 15 30 60 60 60 60 60 

Bronchitis/emphysema No 718 48.357 65.56 2.4467 1 760 4 10 30 60 120 160 230 308 

Bronchitis/emphysema Yes 43 45.395 58.522 8.9245 2 330 5 10 30 55 90 150 330 330 

Bronchtis/emphysema DK 3 42.667 15.535 8.9691 30 60 30 30 38 60 60 60 60 60 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-78. Statistics for 24-Hour Cumulative Number of Minutes Spent in Other Household Work 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1322 68.6354 98.697 2.7145 1 905 5 15 30 75 195 255 360 480 

Gender Male 478 70.3661 101.833 4.6577 1 905 5 10 30 90 195 265 375 480 

Gender Female 844 67.6552 96.923 3.3362 1 720 5 15 30 75 190 255 360 496 

Age (years) * 21 93.4286 113.994 24.8756 4 403 5 15 30 180 225 300 403 403 

Age (years) 1-4 15 57.1333 85.7 22.1277 1 290 1 6 25 60 230 290 290 290 

Age (years) 5-11 56 24.9464 30.134 4.0269 1 150 2 5 12.5 30 60 90 120 150 

Age (years) 12-17 84 39.4762 51.785 5.6502 1 230 2 5 16.5 50 120 150 210 230 

Age (years) 18-64 918 71.2353 101.54 3.3513 1 905 5 15 30 90 195 265 375 540 

Age (years) > 64 228 78.114 106.158 7.0305 1 665 5 14.5 30 90 225 295 420 480 

Race White 1118 70.6977 98.015 2.9314 1 720 5 15 30 80 195 265 375 480 

Race Black 102 46.1176 65.201 6.4558 1 300 3 10 15 50 120 210 255 260 

Race Asian 20 71.9 76.619 17.1324 1 315 1.5 22.5 60 105 162.5 260 315 315 

Race Some Others 22 67.7727 190.288 40.5695 1 905 2 10 15 30 90 155 905 905 

Race Hispanic 43 65.6512 118.419 18.0587 5 660 5 10 20 60 155 270 660 660 

Race Refused 17 72.9412 108.744 26.3742 5 420 5 15 20 75 210 420 420 420 

Hispanic No 1218 67.8342 93.324 2.674 1 720 5 15 30 75 195 255 358 420 

Hispanic Yes 81 80.5185 159.202 17.6891 1 905 5 10 20 60 155 360 665 905 

Hispanic DK 7 54.1429 74.627 28.2062 1 210 1 10 25 90 210 210 210 210 

Hispanic Refused 16 75.8125 113.469 28.3673 5 420 5 15 25 82.5 233 420 420 420 

Employment * 153 37.0196 52.694 4.2601 1 290 2 5 15 45 90 150 225 230 

Employment Full Time 555 70.0342 103.005 4.3723 1 905 5 15 30 85 195 265 375 540 

Employment Part Time 124 62.0726 86.315 7.7513 2 420 5 15 30 65 190 240 400 403 

Employment Not Employed 482 78.3008 105.529 4.8067 1 685 5 15 30 100 224 270 420 575 

Employment Refused 8 95.625 110.014 38.8959 5 300 5 17.5 32.5 180 300 300 300 300 

Education * 175 42.7086 64.901 4.906 1 450 2 5 15 45 120 192 233 300 

Education < High School 96 82.5313 114.62 11.6983 1 660 5 15 30 117.5 240 328 420 660 

Education High School Graduate 418 75.5574 105.946 5.182 1 720 5 15 30 90 215 270 420 540 

Education < College 290 71.3724 100.836 5.9213 1 905 5 15 30 100 192.5 270 330 375 

Education College Graduate 196 73.6173 104.18 7.4414 1 600 5 15 30 85 190 330 400 585 

Education Post Graduate 147 58.7007 81.662 6.7354 1 570 4 10 30 65 150 210 315 420 

Census Region Northeast 307 62.8632 91.306 5.2111 1 665 5 15 30 63 180 255 360 400 

Census Region Midwest 318 70.8679 98.179 5.5056 1 590 5 15 30 90 180 270 375 570 

Census Region South 394 74.7056 106.703 5.3756 1 720 5 10 30 85 215 296 380 600 

Census Region West 303 64.2475 95.504 5.4866 1 905 5 13 30 75 180 240 330 420 

Day Of Week Weekday 857 71.5496 106.351 3.6329 1 905 5 10 30 85 210 295 380 570 

Day Of Week Weekend 465 63.2645 82.596 3.8303 1 600 5 15 30 75 170 225 296 403 

Season Winter 353 64.1558 91.547 4.8726 1 590 5 15 30 65 195 240 345 480 

Season Spring 327 82.844 118.992 6.5803 1 905 5 15 30 115 240 305 420 585 

Season Summer 391 62.1125 97.341 4.9227 1 685 5 10 30 60 160 255 400 570 

Season Fall 251 66.5857 77.867 4.9149 1 480 5 15 35 90 180 230 292 345 

Asthma No 1211 67.8423 98.123 2.8197 1 905 5 15 30 75 190 255 360 480 

Asthma Yes 103 75.6893 104.033 10.2507 1 575 5 15 30 100 210 240 400 480 

Asthma DK 8 97.875 120.21 42.5006 5 300 5 15 17.5 206.5 300 300 300 300 

Angina No 1269 68.2041 99.025 2.7798 1 905 5 15 30 75 190 255 375 496 

Angina Yes 44 77.1364 86.104 12.9807 5 300 5 10 30 132.5 220 240 300 300 

Angina DK 9 87.8889 116.368 38.7895 5 300 5 15 15 180 300 300 300 300 

Bronchitis/Emphysema No 1247 67.8043 97.936 2.7734 1 905 5 15 30 75 190 255 360 480 

Bronchitis/Emphysema Yes 64 83.4844 111.726 13.9658 1 575 5 15 32.5 117.5 220 265 480 575 

Bronchitis/Emphysema DK 11 76.4545 107.17 32.3131 5 300 5 15 20 180 233 300 300 300 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-79. Statistics for 24-Hour Cumulative Number of Minutes Spent in Indoor Playing 

Percentiles 

Category Population Group 

All 

Gender Male 

Gender Female 

Age (years) * 

Age (years) 1-4 

Age (years) 5-11 

Age (years) 12-17 

Age (years) 18-64 

Age (years) > 64 

Race White 

Race Black 

Race Asian 

Race Some Others 

Race Hispanic 

Race Refused 

Hispanic No 

Hispanic Yes 

Hispanic Refused 

Employment * 

Employment Full Time 

Employment Part Time 

Employment Not Employed 

Education * 

Education < High School 

Education High School Graduate 

Education < College 

Education College Graduate 

Education Post Graduate 

Census Region Northeast 

Census Region Midwest 

Census Region South 

Census Region West 

Day Of Week Weekday 

Day Of Week Weekend 

Season Winter 

Season Spring 

Season Summer 

Season Fall 

Asthma No 

Asthma Yes 

Asthma DK 

Angina No 

Angina Yes 

Angina DK 

Bronchitis/emphysema No 

Bronchitis/emphysema Yes 

Bronchitis/emphysema DK 

N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

188 105 82.7 6.03 2 510 20 55 90 127.5 190 270 390 435 

65 117 97.1 12 10 510 20 60 90 135 255 300 435 510 

123 99.5 73.8 6.65 2 420 20 55 76 120 190 225 340 375 

3 127 47.3 27.3 90 180 90 90 110 180 180 180 180 180 

11 130 80.2 24.2 15 270 15 60 115 180 255 270 270 270 

11 93.6 64.3 19.4 30 195 30 30 60 175 180 195 195 195 

4 82.5 45 22.5 30 120 30 45 90 120 120 120 120 120 

149 103 86 7.05 2 510 20 55 76 120 190 292 420 435 

10 124 76.4 24.2 20 270 20 75 100 150 248 270 270 270 

153 110 84.3 6.82 2 510 20 60 90 130 190 270 390 435 

13 95 84.8 23.5 15 255 15 30 60 180 220 255 255 255 

5 71 56.8 25.4 10 150 10 30 60 105 150 150 150 150 

7 108 96.5 36.5 30 300 30 55 60 175 300 300 300 300 

8 68.4 46.4 16.4 42 180 42 45 50 67.5 180 180 180 180 

2 64 65.1 46 18 110 18 18 64 110 110 110 110 110 

172 107 83.9 6.4 2 510 20 60 90 132.5 190 270 390 435 

15 88.1 71.4 18.4 42 300 42 45 60 100 180 300 300 300 

1 110 * * 110 110 110 110 110 110 110 110 110 110 

26 108 69.9 13.7 15 270 30 55 105 160 195 255 270 270 

74 102 95 11 2 510 15 45 70 125 195 300 435 510 

20 124 74 16.6 30 340 36 60 120 165 200 280 340 340 

68 102 76 9.21 15 420 30 60 85 120 180 245 390 420 

27 108 68.6 13.2 15 270 30 55 110 160 195 255 270 270 

16 89.4 58.8 14.7 20 220 20 52.5 60 125 180 220 220 220 

59 102 83.6 10.9 2 435 20 55 75 135 180 340 375 435 

33 112 97.7 17 10 510 20 55 90 120 190 300 510 510 

37 125 96.1 15.8 15 420 15 60 105 155 270 390 420 420 

16 72.5 40.4 10.1 10 150 10 37.5 65 102.5 120 150 150 150 

46 110 94.4 13.9 2 420 20 60 75 120 245 375 420 420 

40 111 75.8 12 15 340 17.5 50 95 175 193 256 340 340 

64 100 73 9.13 10 435 30 52.5 87.5 127.5 180 225 270 435 

38 102 92.2 15 10 510 18 60 60 120 180 300 510 510 

128 99.4 71 6.27 2 435 20 55 90 120 180 245 300 340 

60 118 13 13.3 15 510 30 60 90 150 245 382.5 420 510 

49 130 99.2 14.2 18 420 20 60 105 180 300 375 420 420 

36 85.7 55.7 9.28 2 270 20 45 77.5 112.5 155 180 270 270 

47 92.7 77 11.2 10 435 30 45 60 120 180 195 435 435 

56 107 82.7 11 10 510 15 60 90 127.5 195 255 270 510 

174 107 84.1 6.38 2 510 20 55 90 130 190 270 390 435 

13 88.5 66.4 18.4 20 245 20 30 75 120 180 245 245 245 

1 110 * * 110 110 110 110 110 110 110 110 110 110 

184 104 80.7 5.95 2 510 20 55 90 122.5 190 270 375 435 

3 210 167 96.4 60 390 60 60 180 390 390 390 390 390 

1 110 * * 110 110 110 110 110 110 110 110 110 110 

177 107 83.5 6.27 2 510 20 60 90 130 190 270 390 435 

10 80.1 72.5 22.9 10 245 10 30 60 76 208 245 245 245 

1 110 * * 110 110 110 110 110 110 110 110 110 110 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = 

Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of 

minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-80. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Playing 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 59 97.373 95.372 12.416 5 435 15 45 60 110 210 360 420 435 

Gender Male 26 108.192 94.783 18.588 15 360 15 60 75 135 280 345 360 360 

Gender Female 33 88.848 96.425 16.785 5 435 5 45 60 100 150 420 435 435 

Age (years) * 1 170 * * 170 170 170 170 170 170 170 170 170 170 

Age (years) 1-4 4 83.25 89.66 44.83 15 210 15 20 54 146.5 210 210 210 210 

Age (years) 5-11 9 148.333 144.265 48.088 5 360 5 55 60 280 360 360 360 360 

Age (years) 12-17 1 15 * * 15 15 15 15 15 15 15 15 15 15 

Age (years) 18-64 40 92.05 86.358 13.654 20 435 27.5 52.5 65 102.5 142.5 307 435 435 

Age (years) > 64 4 52.5 15 7.5 30 60 30 45 60 60 60 60 60 60 

Race White 50 93.94 90.208 12.757 5 420 15 45 60 100 202 345 390 420 

Race Black 2 86.5 37.477 26.5 60 113 60 60 86.5 113 113 113 113 113 

Race Asian 1 100 * * 100 100 100 100 100 100 100 100 100 100 

Race Some Others 1 30 * * 30 30 30 30 30 30 30 30 30 30 

Race Hispanic 5 149 164.864 73.729 20 435 20 60 110 120 435 435 435 435 

Hispanic No 51 93.333 89.747 12.567 5 420 15 45 60 100 194 345 360 420 

Hispanic Yes 8 123.125 130.218 46.039 20 435 20 60 90 115 435 435 435 435 

Employment * 15 123.533 124.379 32.115 5 360 5 15 60 210 345 360 360 360 

Employment Full Time 15 67.2 30.887 7.975 20 135 20 45 60 85 113 135 135 135 

Employment Part Time 7 87.714 54.129 20.459 30 194 30 60 60 110 194 194 194 194 

Employment Not Employed 22 103.182 110.136 23.481 25 435 30 45 60 105 150 420 435 435 

Education * 15 123.533 124.379 32.115 5 360 5 15 60 210 345 360 360 360 

Education < High School 5 57 6.708 3 45 60 45 60 60 60 60 60 60 60 

Education High School Graduate 10 148.5 150.482 47.586 30 435 30 60 95 135 427.5 435 435 435 

Education < College 18 74.667 45.169 10.646 20 194 20 45 60 95 150 194 194 194 

Education College Graduate 8 75.375 35.492 12.548 30 120 30 45 75 106.5 120 120 120 120 

Education Post Graduate 3 58.333 24.664 14.24 30 75 30 30 70 75 75 75 75 75 

Census Region Northeast 17 114.059 103.26 25.044 15 360 15 60 70 120 345 360 360 360 

Census Region Midwest 12 78.583 32.354 9.34 30 150 30 60 65 97.5 113 150 150 150 

Census Region South 15 109.667 109.536 28.282 30 420 30 30 60 135 280 420 420 420 

Census Region West 15 81.2 107.674 27.801 5 435 5 20 60 105 165 435 435 435 

Day Of Week Weekday 42 86.81 79.211 12.223 5 360 15 30 60 100 165 280 360 360 

Day Of Week Weekend 17 123.471 126.007 30.561 25 435 25 45 60 120 420 435 435 435 

Season Winter 10 66.5 46.251 14.626 5 150 5 30 60 105 135 150 150 150 

Season Spring 10 135.3 114.735 36.283 45 435 45 60 108 165 302.5 435 435 435 

Season Summer 31 92.355 94.966 17.056 5 420 15 45 60 100 210 345 420 420 

Season Fall 8 108 115.681 40.899 25 360 25 30 67.5 142 360 360 360 360 

Asthma No 56 94.821 91.447 12.22 5 435 15 45 60 107.5 194 360 420 435 

Asthma Yes 3 145 173.853 100.374 30 345 30 30 60 345 345 345 345 345 

Angina No 58 96.983 96.158 12.626 5 435 15 45 60 105 210 360 420 435 

Angina Yes 1 120 * * 120 120 120 120 120 120 120 120 120 120 

Bronchitis/Emphysema No 55 90.018 87.056 11.739 5 435 15 45 60 100 170 345 360 435 

Bronchitis/Emphysema Yes 4 198.5 157.509 78.754 60 420 60 90 157 307 420 420 420 420 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". N = doer sample size. Mean = Mean 24-hour cumulative number of 

minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. 

Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-81. Statistics for 24-Hour Cumulative Number of Minutes Spent for Car Repair Services 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 259 33.7876 53.772 3.3413 1 358 5 5 10 30 90 180 195 270 

Gender Male 128 41.6953 65.45 5.7851 1 358 4 5 15 45 120 180 270 280 

Gender Female 131 26.0611 37.84 3.3061 2 180 5 5 10 30 65 105 180 180 

Age (years) * 2 88 2.828 2 86 90 86 86 88 90 90 90 90 90 

Age (years) 1-4 8 33.125 43.666 15.438 5 115 5 5 12.5 55 115 115 115 115 

Age (years) 5-11 6 18.3333 20.897 8.531 5 60 5 5 12.5 15 60 60 60 60 

Age (years) 12-17 13 31.3077 32.638 9.0521 3 95 3 5 10 55 79 95 95 95 

Age (years) 18-64 204 32.4853 52.731 3.6919 1 280 5 5 10 30 85 180 195 265 

Age (years) > 64 26 44.8462 75.446 14.796 1 358 2 10 15 50 105 180 358 358 

Race White 226 33.8451 51.028 3.3943 1 280 5 5 10 35 90 175 195 265 

Race Black 19 49.3158 90.675 20.802 1 358 1 5 10 44 180 358 358 358 

Race Asian 3 11.6667 11.547 6.6667 5 25 5 5 5 25 25 25 25 25 

Race Some Others 5 11 8.944 4 5 25 5 5 5 15 25 25 25 25 

Race Hispanic 6 12.5 6.124 2.5 5 20 5 5 15 15 20 20 20 20 

Hispanic No 247 34.6154 54.728 3.4822 1 358 5 5 10 35 90 180 245 270 

Hispanic Yes 12 16.75 22.471 6.4867 5 86 5 5 12.5 15 20 86 86 86 

Employment * 26 27.7692 33.586 6.5868 3 115 5 5 10 50 90 95 115 115 

Employment Full Time 137 31.8759 52.912 4.5206 1 280 4 5 10 30 85 175 265 270 

Employment Part Time 25 32.96 49.672 9.9344 5 180 5 7 15 30 105 180 180 180 

Employment Not Employed 70 40.4714 62.833 7.51 1 358 4 10 15 35 103 180 245 358 

Employment Refused 1 5 * * 5 5 5 5 5 5 5 5 5 5 

Education * 28 28.4643 32.992 6.2349 3 115 5 5 12.5 52.5 90 95 115 115 

Education < High School 20 36.15 51.714 11.564 5 180 5 10 15 45 117.5 177.5 180 180 

Education High School Graduate 64 41.0781 62.959 7.8698 2 280 5 5 15 47.5 105 180 265 280 

Education < College 68 36.2206 59.709 7.2407 1 358 2 5 15 37.5 90 180 180 358 

Education College Graduate 41 29.6829 54.536 8.5171 1 270 4 5 10 25 60 160 270 270 

Education Post Graduate 38 24.2632 36.541 5.9277 5 195 5 5 10 20 70 95 195 195 

Census Region Northeast 45 40.4889 58.498 8.7204 2 270 5 5 15 60 105 180 270 270 

Census Region Midwest 66 34.6364 56.367 6.9383 2 280 5 5 10 35 70 180 265 280 

Census Region South 88 34.8182 60.547 6.4543 1 358 3 5 10 30 95 180 245 358 

Census Region West 60 26.3167 33.054 4.2673 4 175 5 5 12.5 30 80 95.5 115 175 

Day Of Week Weekday 176 36.0227 57.142 4.3072 1 358 5 5 15 30 101 180 265 280 

Day Of Week Weekend 83 29.0482 45.78 5.025 1 245 3 5 10 30 79 95 195 245 

Season Winter 70 19.4857 27.784 3.3208 1 180 2 5 10 20 60 60 90 180 

Season Spring 70 36.5286 48.821 5.8352 2 245 5 5 15 50 105 150 180 245 

Season Summer 79 41.5316 66.665 7.5004 2 358 5 5 15 30 160 180 270 358 

Season Fall 40 38.725 64.266 10.161 2 280 5 5 12.5 39.5 90.5 222.5 280 280 

Asthma No 238 34.7731 55.08 3.5703 1 358 4 5 10 35 90 180 245 270 

Asthma Yes 21 22.619 34.735 7.5799 5 150 5 5 15 15 35 90 150 150 

Angina No 253 32.6324 51.888 3.2622 1 358 5 5 10 30 90 160 180 270 

Angina Yes 6 82.5 102.896 42.007 10 245 10 15 22.5 180 245 245 245 245 

Bronchitis/emphysema No 247 33.0607 52.903 3.3661 1 358 5 5 10 30 90 175 195 270 

Bronchitis/emphysema Yes 12 48.75 70.522 20.358 5 245 5 5 15 77.5 95 245 245 245 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-82. Statistics for 24-Hour Cumulative Number of Minutes Spent Washing, etc. 

Percentiles 

Category Population Group N Mean Stdev Stderr Min 

All 6029 23.9338 25.5661 0.3293 1 

Gender Male 2785 23.4154 28.8168 0.5461 1 

Gender Female 3242 24.3816 22.4026 0.3935 1 

Gender Refused 2 20 14.1421 10 10 

Age (years) * 110 25.9182 30.4752 2.9057 3 

Age (years) 1-4 318 29.2673 16.5524 0.9282 5 

Age (years) 5-11 407 26.5184 35.9626 1.7826 2 

Age (years) 12-17 411 22.4088 14.6309 0.7217 1 

Age (years) 18-64 4154 22.7939 21.6279 0.3356 1 

Age (years) > 64 629 27.7424 43.1415 1.7202 1 

Race White 4794 23.1558 26.1288 0.3774 1 

Race Black 664 28.7816 24.2016 0.9392 3 

Race Asian 110 24.4727 17.5493 1.6733 5 

Race Some Others 119 28.6471 27.4768 2.5188 3 

Race Hispanic 269 23.8364 19.8318 1.2092 1 

Race Refused 73 22.7945 20.46 2.3947 3 

Hispanic No 5476 23.8088 25.0872 0.339 1 

Hispanic Yes 465 25.7312 31.6942 1.4698 1 

Hispanic DK 30 23.8 15.0319 2.7444 5 

Hispanic Refused 58 21.3966 18.5708 2.4385 5 

Employment * 1116 25.9758 25.169 0.7534 1 

Employment Full Time 2975 22.0733 21.4639 0.3935 1 

Employment Part Time 518 22.3996 17.1137 0.7519 1 

Employment Not Employed 1378 26.9354 34.8572 0.939 1 

Employment Refused 42 21.9048 15.8865 2.4513 5 

Education * 1245 25.3888 24.2988 0.6887 1 

Education < High School 440 30.6 46.38 2.2111 1 

Education High School Graduate 1634 23.7699 20.0081 0.495 1 

Education < College 1228 22.8575 19.6959 0.5621 1 

Education College Graduate 844 22.5936 32.3617 1.1139 1 

Education Post Graduate 638 20.7618 18.4597 0.7308 2 

Census Region Northeast 1356 23.3274 21.7583 0.5909 1 

Census Region Midwest 1303 22.9294 27.432 0.76 1 

Census Region South 2136 25.2116 21.6627 0.4687 1 

Census Region West 1234 23.4489 32.6116 0.9284 1 

Day Of Week Weekday 4184 22.9441 25.7284 0.3978 1 

Day Of Week Weekend 1845 26.1783 25.0567 0.5833 1 

Season Winter 1688 24.6226 20.295 0.494 1 

Season Spring 1584 26.3295 38.468 0.9665 1 

Season Summer 1636 21.8264 15.5411 0.3842 1 

Season Fall 1121 22.587 20.8871 0.6238 1 

Asthma No 5559 23.9538 26.1095 0.3502 1 

Asthma Yes 437 24.2288 18.3575 0.8782 1 

Asthma DK 33 16.6667 8.7202 1.518 5 

Angina No 5866 23.9529 25.8029 0.3369 1 

Angina Yes 125 25.176 15.6613 1.4008 3 

Angina DK 38 16.8947 8.5481 1.3867 5 

Bronchitis/Emphysema No 5749 23.8629 25.8064 0.3404 1 

Bronchitis/Emphysema Yes 249 26.49 20.7475 1.3148 1 

Bronchitis/Emphysema DK 31 16.5484 8.0616 1.4479 5 

Max 5 25 50 75 90 95 98 99 

705 5 10 20 30 45 60 75 90 

705 5 10 15 30 45 55 65 90 

555 5 10 20 30 45 60 80 90 

30 10 10 20 30 30 30 30 30 

300 5 10 20 30 41.5 60 60 80 

125 10 15 30 30 50 60 75 85 

690 7 15 20 30 45 60 60 75 

90 5 10 18 30 42 50 60 60 

555 5 10 15 30 45 60 75 90 

705 5 12 20 30 45 65 90 120 

705 5 10 15 30 45 60 70 90 

270 5 15 20 35 60 65 90 105 

90 5 15 20 30 47.5 60 85 90 

240 8 15 25 30 50 60 100 150 

210 5 10 20 30 45 60 75 90 

105 5 10 15 30 60 75 90 105 

705 5 10 20 30 45 60 75 90 

570 5 15 20 30 45 60 75 90 

60 10 15 17.5 30 50 60 60 60 

105 5 10 15 25 30 60 80 105 

690 7 15 20 30 45 60 60 75 

555 5 10 15 30 45 60 65 85 

135 5 10 15 30 45 60 70 90 

705 5 10 20 30 50 60 90 120 

90 5 10 15 30 30 45 90 90 

690 6 15 20 30 45 60 60 80 

570 5 15 20 30 50 60 90 240 

270 5 10 20 30 45 60 75 90 

255 5 10 15 30 45 60 75 90 

705 5 10 15 30 40 60 75 110 

240 5 10 15 30 45 60 65 85 

360 5 10 15 30 45 60 75 90 

570 5 10 15 30 45 60 70 85 

300 5 15 20 30 45 60 85 105 

705 5 10 15 30 45 60 65 85 

705 5 10 15 30 45 60 65 90 

555 5 15 20 30 50 60 90 100 

300 5 10 20 30 45 60 75 90 

705 5 13 20 30 45 60 90 125 

150 5 10 15 30 40 55 60 75 

340 5 10 15 30 45 60 75 90 

705 5 10 20 30 45 60 75 90 

145 5 15 20 30 45 60 90 95 

30 5 10 15 25 30 30 30 30 

705 5 10 20 30 45 60 75 90 

100 6 15 25 30 45 60 60 75 

35 5 10 15 25 30 30 35 35 

705 5 10 20 30 45 60 75 90 

150 5 15 20 30 60 60 95 105 

30 5 10 15 25 30 30 30 30 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-83. Statistics for 24-Hour Cumulative Number of Minutes Spent Sleeping/Napping 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 9362 526.287 134.435 1.3894 30 1430 345 445 510 600 690 760 850 925 

Gender Male 4283 523.333 135.183 2.0656 30 1295 330 435 510 600 690 765 860 925 

Gender Female 5075 528.685 133.743 1.8774 30 1430 350 450 510 600 690 750 840 925 

Gender Refused 4 645 123.693 61.8466 540 780 540 540 630 750 780 780 780 780 

Age (years) * 185 502.281 125.424 9.2214 195 908 330 420 480 555 655 745 865 900 

Age (years) 1-4 499 732.363 124.328 5.5657 270 1320 540 655 720 810 900 930 1005 1110 

Age (years) 5-11 702 625.058 100.656 3.799 120 1110 480 570 630 680 725 780 840 875 

Age (years) 12-17 588 563.719 110.83 4.5706 150 1015 395 484 550 630 705 750 810 900 

Age (years) 18-64 6041 496.93 123.019 1.5828 30 1420 330 420 480 555 630 705 780 868 

Age (years) > 64 1347 517.084 117.477 3.2009 30 1430 345 450 510 570 660 720 780 860 

Race White 7576 523.598 129.545 1.4883 30 1430 350 445 510 600 690 750 840 900 

Race Black 940 541.303 162.726 5.3076 60 1415 315 424 530 630 737.5 822.5 940 1020 

Race Asian 156 537.09 118.072 9.4533 300 920 345 467.5 540 600 690 735 840 870 

Race Some Others 181 528.823 142.25 10.5734 60 905 300 420 525 630 720 769 810 842 

Race Hispanic 383 537.966 148.886 7.6077 60 1125 315 450 540 630 720 765 870 930 

Race Refused 126 523.421 143.695 12.8014 180 1140 330 420 510 600 720 780 870 930 

Hispanic No 8514 525.205 133.218 1.4438 30 1430 345 445 510 600 690 750 855 925 

Hispanic Yes 700 540.053 147.143 5.5615 60 1125 320 450 540 630 720 777.5 842.5 915 

Hispanic DK 45 527.467 139.269 20.7609 195 842 345 420 515 659 690 710 842 842 

Hispanic Refused 103 521.592 138.874 13.6837 240 930 330 420 510 590 720 780 865 870 

Employment * 1771 636.604 128.545 3.0545 120 1320 440 555 630 705 802 860 930 975 

Employment Full Time 4085 487.152 118.9 1.8603 30 1420 325 420 480 540 628 685 770 840 

Employment Part Time 798 502.764 117.416 4.1565 60 1005 330 435 495 570 645 720 780 860 

Employment Not Employed 2638 520.277 125.549 2.4444 30 1430 345 450 510 590 660 720 800 885 

Employment Refused 70 513.671 136.491 16.3138 210 930 320 420 490 570 696.5 780 900 930 

Education * 1966 625.586 133.976 3.0216 120 1420 420 540 628 699 790 855 926 975 

Education < High School 832 515.445 135.697 4.7045 30 1317 300 435 510 585 670 750 860 900 

Education High School Graduate 2604 505.367 123.006 2.4105 30 1430 330 420 495 570 659 720 780 840 

Education < College 1791 496.616 119.862 2.8323 60 1350 315 420 480 565 630 690 779 845 

Education College Graduate 1245 492.516 117.558 3.3317 75 1404 330 420 480 540 629 690 775 900 

Education Post Graduate 924 486.737 110.394 3.6317 105 1295 345 420 480 540 615 660 725 800 

Census Region Northeast 2068 523.129 133.703 2.9401 55 1420 345 435 510 600 690 760 860 930 

Census Region Midwest 2096 520.846 127.642 2.788 30 1215 330 440 510 598 690 745 840 870 

Census Region South 3234 529.019 135.651 2.3854 30 1430 345 450 510 600 699 765 855 925 

Census Region West 1964 530.918 139.966 3.1583 60 1404 345 449.5 510 600 690 769 862 940 

Day Of Week Weekday 6303 511.13 131.826 1.6605 30 1430 330 420 495 570 670 745 840 920 

Day Of Week Weekend 3059 557.517 134.392 2.4299 30 1420 360 480 540 630 720 780 870 925 

Season Winter 2514 534.911 134.719 2.6869 55 1404 355 450 520 600 700 780 870 930 

Season Spring 2431 526.839 130.49 2.6466 30 1175 345 445 510 600 690 750 840 900 

Season Summer 2533 527.653 139.46 2.771 30 1430 330 435 510 600 699 765 840 930 

Season Fall 1884 512.228 131.14 3.0213 60 1420 330 430 505 570 660 735 840 900 

Asthma No 8608 525.05 133.571 1.4397 30 1430 345 445 510 600 690 750 840 915 

Asthma Yes 692 540.061 143.571 5.4577 30 1404 330 450 537.5 617.5 715 780 900 945 

Asthma DK 62 544.194 140.992 17.906 300 1035 330 465 535 600 720 780 930 1035 

Angina No 9039 526.754 134.235 1.4119 30 1420 345 445 510 600 690 760 855 925 

Angina Yes 249 513.743 137.698 8.7263 60 1430 300 445 510 595 660 735 795 845 

Angina DK 74 511.392 146.297 17.0067 30 930 300 420 510 600 720 780 840 930 

Bronchitis/Emphysema No 8860 526.549 134.267 1.4264 30 1430 345 445 510 600 690 760 850 924 

Bronchitis/Emphysema Yes 432 521.713 138.459 6.6616 80 1110 300 420 510 600 705 765 840 930 

Bronchitis/Emphysema DK 70 521.243 131.857 15.7599 210 930 300 450 510 600 690 745 840 930 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-84. Statistics for 24-Hour Cumulative Number of Minutes Spent Attending Full Time School 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 884 358.537 130.347 4.384 1 840 95 300 390 435 483 550 600 640 

Gender Male 468 369.301 123.186 5.6943 20 840 120 320 390 435 485 555 595 645 

Gender Female 416 346.428 137.1 6.7219 1 710 75 262.5 385 430 480 535 600 628 

Age (years) * 7 232.143 148.123 55.9853 10 495 10 180 210 320 495 495 495 495 

Age (years) 1-4 56 365.036 199.152 26.6128 20 710 30 172.5 427.5 530 595 628 665 710 

Age (years) 5-11 297 387.811 98.013 5.6873 60 645 170 360 390 435 485 555 600 630 

Age (years) 12-17 271 392.28 84.986 5.1625 10 605 200 375 405 435 460 485 510 555 

Age (years) 18-64 247 292.194 154.58 9.8357 1 840 60 180 289 400 480 535 645 785 

Age (years) > 64 6 203.333 147.366 60.1618 75 480 75 120 152.5 240 480 480 480 480 

Race White 665 362.913 128.548 4.9849 1 825 107 310 392 435 485 550 600 630 

Race Black 92 351.793 129.647 13.5166 40 710 70 286.5 387.5 432.5 465 526 645 710 

Race Asian 33 346.303 156.009 24.1576 90 840 120 225 365 435 500 565 840 840 

Race Some Others 29 337.828 148.115 27.5043 58 553 70 212 360 445 502 540 553 553 

Race Hispanic 58 345.259 124.048 16.2883 30 565 85 260 377.5 430 480 510 510 565 

Race Refused 7 285 157.03 59.3517 60 440 60 150 290 440 440 440 440 440 

Hispanic No 771 359.565 130.825 4.7116 1 840 100 300 390 435 483 550 600 645 

Hispanic Yes 103 353.107 126.354 12.4501 30 630 85 269 385 425 483 510 595 600 

Hispanic DK 4 315.5 167.773 83.8863 65 416 65 221 391 410 415 415 415 415 

Hispanic Refused 6 348.333 140.594 57.3973 150 445 150 185 435 440 445 445 445 445 

Employment * 608 386.497 107.308 4.3519 10 710 165 361 400 440 485 550 595 625 

Employment Full Time 49 206.551 133.583 19.0833 5 502 15 115 180 305 430 461 502 502 

Employment Part Time 89 304.652 134.791 14.2879 25 695 90 210 295 395 480 500 585 695 

Employment Not Employed 135 325.274 161.049 13.8609 1 840 60 215 340 420 500 605 785 825 

Employment Refused 3 270 147.224 85 185 440 185 185 440 440 440 440 440 440 

Education * 666 384.985 107.925 4.182 10 710 160 360 400 440 485 550 595 625 

Education < High School 14 267.071 129.31 34.5595 5 415 5 175 310 357 385 415 415 415 

Education High School Graduate 54 238.481 141.148 19.2079 58 785 60 125 212 330 400 480 480 785 

Education < College 100 303.35 170.598 17.0598 1 840 60 185 272.5 415 525.5 613.5 760 832.5 

Education College Graduate 24 238.417 145.897 29.781 25 565 30 135 200 360 430 460 565 565 

Education Post Graduate 26 302.808 144.149 28.2699 10 535 95 210 300 461 500 502 535 535 

Census Region Northeast 186 351.597 127.019 9.3135 60 825 120 268 375 420 483 520 600 785 

Census Region Midwest 200 358.07 123.934 8.7634 5 645 87.5 307.5 392.5 425 470 527.5 577.5 602 

Census Region South 322 373.879 139.7 7.7852 10 840 60 330 405 450 500 565 625 645 

Census Region West 176 338.335 120.469 9.0807 1 630 120 262.5 375 410 465 540 555 600 

Day Of Week Weekday 858 363.66 126.018 4.3022 1 840 120 310 390 435 485 550 600 640 

Day Of Week Weekend 26 189.5 158.415 31.0677 15 465 20 60 120 300 460 465 465 465 

Season Winter 302 375.113 118.518 6.8199 5 695 150 330 395 440 495 550 612 640 

Season Spring 287 353.359 133.705 7.8924 10 840 90 290 390 430 475 500 570 710 

Season Summer 125 332.448 142.088 12.7088 40 630 70 217 375 425 470 550 600 600 

Season Fall 170 357.018 132.833 10.1878 1 785 120 285 380 430 510 565 605 645 

Asthma No 784 357.969 130.658 4.6663 1 840 95 295 390 435 485 550 595 630 

Asthma Yes 96 362.958 127.895 13.0533 20 695 95 334 390 427.5 475 540 645 695 

Asthma DK 4 363.75 162.551 81.2756 120 450 120 280 442.5 447.5 450 450 450 450 

Angina No 875 358.57 130.546 4.4133 1 840 95 300 390 435 483 550 600 640 

Angina Yes 4 382.5 87.702 43.8511 255 455 255 330 410 435 455 455 455 455 

Angina DK 5 333.6 140.481 62.8248 120 460 120 270 378 440 460 460 460 460 

Bronchitis/Emphysema No 851 359.132 130.435 4.4713 1 840 95 300 390 435 485 550 600 640 

Bronchitis/Emphysema Yes 27 340.111 132.683 25.5349 30 605 60 305 365 435 450 460 605 605 

Bronchitis/Emphysema DK 6 357.167 121.491 49.5987 120 440 120 350 396.5 440 440 440 440 440 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-85. Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1384 123.994 112.825 3.0328 1 1130 15 50 90 165 267 330 435 525 

Gender Male 753 136.781 120.777 4.4014 1 1130 20 60 105 180 285 375 500 558 

Gender Female 629 108.628 100.648 4.0131 1 1065 15 38 75 150 240 300 370 435 

Gender Refused 2 142.5 38.891 27.5 115 170 115 115 142.5 170 170 170 170 170 

Age (years) * 23 108.696 78.628 16.395 5 290 30 40 90 155 220 225 290 290 

Age (years) 1-4 105 115.848 98.855 9.6472 10 630 30 45 90 159 250 330 345 390 

Age (years) 5-11 247 148.87 126.627 8.0571 2 975 20 60 120 188 320 390 510 558 

Age (years) 12-17 215 137.46 124.516 8.4919 5 1065 15 60 110 180 265 375 470 520 

Age (years) 18-64 642 120.315 110.376 4.3562 1 1130 15 45 90 160 250 330 450 525 

Age (years) > 64 152 88.007 80.207 6.5056 1 380 15 30 60 120 220 285 315 330 

Race White 1139 125.994 116.168 3.4421 1 1130 15 50 90 165 270 340 452 530 

Race Black 109 113.431 96.788 9.2706 5 440 10 45 86 150 240 332 430 435 

Race Asian 30 89.933 79.214 14.4625 5 310 10 30 60 145 215 235 310 310 

Race Some Others 35 135.371 112.206 18.9663 15 553 20 60 105 195 270 330 553 553 

Race Hispanic 59 116.288 91.326 11.8897 1 520 15 45 115 145 240 305 345 520 

Race Refused 12 120 86.576 24.9924 40 300 40 60 95 130 290 300 300 300 

Hispanic No 1250 124.471 113.469 3.2094 1 1130 15 45 90 165 270 330 435 515 

Hispanic Yes 120 121.2 110.791 10.1138 1 630 15 50 90 147.5 240 335 520 553 

Hispanic DK 4 113.75 57.5 28.75 60 185 60 67.5 105 160 185 185 185 185 

Hispanic Refused 10 102 72.119 22.8059 40 290 40 60 82.5 105 215 290 290 290 

Employment * 561 137.073 120.838 5.1018 2 1065 20 60 110 180 285 370 452 558 

Employment Full Time 375 117.579 107.304 5.5412 5 1130 20 45 90 155 240 305 380 525 

Employment Part Time 87 116.207 87.553 9.3867 1 450 15 60 95 160 235 285 355 450 

Employment Not Employed 352 112.537 109.99 5.8625 1 600 10 30 70 150 270 330 475 520 

Employment Refused 9 99.444 77.235 25.7451 30 280 30 45 90 120 280 280 280 280 

Education * 610 137.702 121.227 4.9083 2 1065 20 60 110 180 285 370 470 558 

Education < High School 86 101.047 99.745 10.7558 10 570 15 30 60 135 225 270 510 570 

Education High School Graduate 233 116.794 116.802 7.652 1 1130 20 45 85 150 240 300 420 530 

Education < College 178 115.781 100.276 7.516 1 525 15 45 90 160 270 340 418 475 

Education College Graduate 165 116.218 97.925 7.6235 1 600 15 50 90 150 250 310 380 450 

Education Post Graduate 112 106.446 97.879 9.2487 5 375 10 40 60 142.5 270 330 360 375 

Census Region Northeast 333 131.967 129.1 7.0746 1 1130 15 60 100 170 275 345 485 558 

Census Region Midwest 254 116.882 101.859 6.3912 5 570 18 45 90 150 255 315 430 440 

Census Region South 479 119.476 108.664 4.965 1 975 15 45 90 160 265 330 410 462 

Census Region West 318 128.132 108.811 6.1018 1 625 25 55 92.5 175 295 330 500 525 

Day Of Week Weekday 902 115.47 97.84 3.2577 1 650 15 45 90 150 240 300 395 485 

Day Of Week Weekend 482 139.946 135.196 6.158 1 1130 20 59 100 180 300 380 500 565 

Season Winter 316 115.589 115.201 6.4806 1 1065 15 45 85 155 240 305 370 475 

Season Spring 423 130.775 105.017 5.1061 5 650 30 60 105 175 270 330 435 515 

Season Summer 425 129.541 115.123 5.5843 1 625 15 45 95 178 290 375 462 530 

Season Fall 220 112.314 118.325 7.9775 1 1130 15 43 77.5 143.5 240 290 460 565 

Asthma No 1266 122.461 109.594 3.0801 1 1130 15 45 90 162 266 330 430 515 

Asthma Yes 105 144.829 145.828 14.2314 1 1065 15 60 110 180 300 390 553 565 

Asthma DK 13 105 110.416 30.6239 30 450 30 60 60 90 165 450 450 450 

Angina No 1343 125.491 113.589 3.0995 1 1130 15 50 90 165 270 332 440 525 

Angina Yes 33 72.091 73.998 12.8815 5 330 5 30 50 60 180 275 330 330 

Angina DK 8 86.875 41.139 14.5448 40 155 40 60 75 115 155 155 155 155 

Bronchitis/Emphysema No 1331 124.101 113.19 3.1026 1 1130 15 50 90 165 267 330 435 520 

Bronchitis/Emphysema Yes 43 130 112.663 17.181 10 553 30 45 110 165 270 340 553 553 

Bronchitis/Emphysema DK 10 84 39.847 12.6007 40 155 40 60 75 105 147.5 155 155 155 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean

24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max =

maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-86. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Recreation 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 253 211.23 185.48 11.661 5 1440 20 60 165 300 480 574 670 690 

Gender Male 140 231.78 207.41 17.529 5 1440 17.5 67.5 177 330 502.5 600 690 735 

Gender Female 112 183.67 150.15 14.188 5 645 20 60 150 255 380 525 585 630 

Gender Refused 1 420 * * 420 420 420 420 420 420 420 420 420 420 

Age (years) * 2 337.5 201.53 142.5 195 480 195 195 337.5 480 480 480 480 480 

Age (years) 1-4 13 166.54 177.06 49.109 15 630 15 30 130 180 370 630 630 630 

Age (years) 5-11 21 206.14 156.17 34.078 30 585 60 90 165 245 360 574 585 585 

Age (years) 12-17 27 155.07 128.28 24.687 5 465 5 60 135 225 420 420 465 465 

Age (years) 18-64 158 223.61 192.97 15.352 5 1440 30 80 172.5 310 505 585 690 690 

Age (years) > 64 32 211.06 206.59 36.521 5 735 5 30 171 375 495 600 735 735 

Race White 225 209.77 182.74 12.183 5 1440 20 60 165 300 460 570 670 690 

Race Black 16 233.88 231.3 57.825 5 690 5 42.5 150 450 585 690 690 690 

Race Asian 3 203.33 262.22 151.39 30 505 30 30 75 505 505 505 505 505 

Race Some Others 2 327.5 130.82 92.5 235 420 235 235 327.5 420 420 420 420 420 

Race Hispanic 4 77.5 53.929 26.964 20 150 20 42.5 70 112.5 150 150 150 150 

Race Refused 3 308.33 209.42 120.91 180 550 180 180 195 550 550 550 550 550 

Hispanic No 238 211.8 187.07 12.126 5 1440 20 60 165 300 480 585 690 690 

Hispanic Yes 12 175.5 149.06 43.029 15 511 15 70 150 255 340 511 511 511 

Hispanic Refused 3 308.33 209.42 120.91 180 550 180 180 195 550 550 550 550 550 

Employment * 60 177.1 150.02 19.368 5 630 12.5 60 147.5 230 395 519.5 585 630 

Employment Full Time 104 210.74 153.37 15.039 5 670 30 82.5 180 294 419 511 600 645 

Employment Part Time 19 205.26 204.04 46.81 30 690 30 60 150 180 570 690 690 690 

Employment Not Employed 68 244.44 245.03 29.715 5 1440 15 60 179.5 375 525 690 735 1440 

Employment Refused 2 187.5 10.607 7.5 180 195 180 180 187.5 195 195 195 195 195 

Education * 64 176.73 145.32 18.165 5 630 15 60 152.5 225 370 465 585 630 

Education < High School 22 259.41 177.97 37.943 5 600 30 105 247.5 380 525 600 600 600 

Education High School Graduate 59 238.2 228.99 29.812 15 1440 20 90 175 310 511 670 690 1440 

Education < College 54 218.09 172.21 23.434 5 690 25 65 172.5 345 460 550 570 690 

Education College Graduate 31 224.71 193.06 34.675 20 690 30 60 150 325 505 645 690 690 

Education Post Graduate 23 157.61 178.18 37.153 5 735 10 50 80 200 370 480 735 735 

Census Region Northeast 52 189.6 160.88 22.31 5 690 30 60 162.5 231.5 370 574 670 690 

Census Region Midwest 54 212.09 228.41 31.083 5 1440 20 60 177.5 280 419 600 735 1440 

Census Region South 84 217.26 175.27 19.123 5 645 15 62.5 150 347.5 495 525 600 645 

Census Region West 63 220.29 179.71 22.642 10 690 30 75 165 280 545 585 690 690 

Day Of Week Weekday 129 197.21 195.32 17.197 5 1440 15 60 150 275 465 525 670 735 

Day Of Week Weekend 124 225.81 174.26 15.649 5 690 20 85 180 310 480 600 690 690 

Season Winter 31 196.61 165.52 29.728 5 585 5 60 165 280 440 550 585 585 

Season Spring 75 198.85 161.67 18.668 5 690 25 75 180 270 465 545 670 690 

Season Summer 102 228.16 204.18 20.217 5 1440 30 75 179.5 325 459 585 690 690 

Season Fall 45 203.53 193.83 28.895 5 735 20 60 120 330 505 574 735 735 

Asthma No 232 208.24 187.69 12.323 5 1440 20 60 159 294 480 585 690 690 

Asthma Yes 19 250.21 166.64 38.23 15 570 15 80 255 350 525 570 570 570 

Asthma DK 2 187.5 10.607 7.5 180 195 180 180 187.5 195 195 195 195 195 

Angina No 245 206.82 184.85 11.81 5 1440 20 60 160 288 480 570 670 690 

Angina Yes 6 399.17 151.21 61.731 285 690 285 310 345 420 690 690 690 690 

Angina DK 2 187.5 10.607 7.5 180 195 180 180 187.5 195 195 195 195 195 

Bronchitis/Emphysema No 238 212.24 189.23 12.266 5 1440 20 60 165 300 495 585 690 690 

Bronchitis/Emphysema Yes 13 196.31 122.22 33.896 5 370 5 117 160 310 340 370 370 370 

Bronchitis/Emphysema DK 2 187.5 10.607 7.5 180 195 180 180 187.5 195 195 195 195 195 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-87. Statistics for 24-Hour Cumulative Number of Minutes Spent in Exercise 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 564 77.429 70.438 2.966 4 670 15 30 60 100 150 195 275 420 

Gender Male 262 84.676 75.778 4.6816 5 670 20 30 60 117 165 205 285 450 

Gender Female 302 71.142 64.927 3.7361 4 525 15 30 60 90 125 175 265 360 

Age (years) * 10 76.5 74.014 23.405 15 270 15 30 60 90 187.5 270 270 270 

Age (years) 1-4 11 127.273 187.18 56.437 15 670 15 30 60 150 160 670 670 670 

Age (years) 5-11 26 132.5 126.31 24.772 15 525 25 60 90 180 275 450 525 525 

Age (years) 12-17 35 67.829 41.589 7.0298 15 180 20 30 60 100 120 150 180 180 

Age (years) 18-64 407 77.572 63.597 3.1524 4 480 20 30 60 100 145 185 265 300 

Age (years) > 64 75 54.853 44.455 5.1332 6 195 10 25 40 70 120 150 193 195 

Race White 480 78.015 71.517 3.2643 4 670 15 30 60 100 150 194 285 450 

Race Black 34 74.706 44.67 7.6608 15 250 15 45 60 105 120 130 250 250 

Race Asian 10 46.3 25.038 7.9177 15 95 15 30 41.5 60 82.5 95 95 95 

Race Some Others 14 80.214 73.944 19.762 30 275 30 30 47.5 90 179 275 275 275 

Race Hispanic 19 63 60.658 13.916 15 265 15 30 45 60 160 265 265 265 

Race Refused 7 128.571 130.47 49.313 30 360 30 55 60 270 360 360 360 360 

Hispanic No 516 76.872 70.111 3.0865 4 670 15 30 60 99 145 193 275 420 

Hispanic Yes 38 76.553 59.516 9.6548 15 265 20 30 60 110 160 250 265 265 

Hispanic DK 3 65 69.462 40.104 20 145 20 20 30 145 145 145 145 145 

Hispanic Refused 7 128.571 130.47 49.313 30 360 30 55 60 270 360 360 360 360 

Employment * 72 99.014 111.6 13.153 15 670 20 30 60 120 180 275 525 670 

Employment Full Time 300 72.663 55.618 3.2111 5 460 20 30 60 90 130 179.5 240 291 

Employment Part Time 50 85.98 83.568 11.818 10 420 20 30 60 92 167.5 300 390 420 

Employment Not Employed 139 72.683 63.36 5.3742 4 480 10 30 60 90 135 195 240 265 

Employment Refused 3 113.333 135.77 78.387 30 270 30 30 40 270 270 270 270 270 

Education * 83 101.976 110.97 12.18 15 670 25 30 60 120 205 275 525 670 

Education < High School 21 58.238 66.062 14.416 10 300 10 28 30 60 90 165 300 300 

Education High School Graduate 124 81.048 63.037 5.6609 4 298 15 30 60 115 179 205 250 265 

Education < College 104 80.856 70.181 6.8818 15 480 20 30 60 112.5 150 170 240 420 

Education College Graduate 110 73.627 62.548 5.9637 5 460 20 30 60 98 130 180 285 297 

Education Post Graduate 122 60.861 38.368 3.4737 5 240 15 30 60 80 110 127 165 185 

Census Region Northeast 130 88.423 77.649 6.8102 10 450 15 30 60 120 200 240 297 420 

Census Region Midwest 101 63.564 44.33 4.411 10 300 15 30 60 89 115 120 170 215 

Census Region South 177 75.311 71.62 5.3833 5 525 15 30 60 90 150 185 298 480 

Census Region West 156 79.647 75.331 6.0313 4 670 20 30 60 104 130 183 270 460 

Day Of Week Weekday 426 73.096 63.872 3.0946 4 670 15 30 60 90 130 180 240 298 

Day Of Week Weekend 138 90.804 86.574 7.3697 6 525 15 30 60 120 200 265 420 460 

Season Winter 150 67.387 49.859 4.071 8 285 15 30 60 90 127.5 175 212.5 240 

Season Spring 140 74.871 55.395 4.6817 10 360 17.5 30 60 90 147.5 181 220 298 

Season Summer 192 93.188 91.294 6.5886 5 670 20 30 62.5 120 180 250 450 525 

Season Fall 82 63.268 63.277 6.9878 4 460 15 30 45 75 120 135 300 460 

Asthma No 523 76.625 70.247 3.0717 4 670 15 30 60 100 150 185 265 420 

Asthma Yes 37 78.243 51.454 8.459 20 275 20 45 65 100 120 200 275 275 

Asthma DK 4 175 167.03 83.517 10 360 10 35 165 315 360 360 360 360 

Angina No 553 77.259 69.366 2.9497 4 670 15 30 60 100 145 193 265 420 

Angina Yes 7 27.286 19.576 7.3992 6 60 6 10 25 45 60 60 60 60 

Angina DK 4 188.75 150.35 75.177 60 360 60 62.5 167.5 315 360 360 360 360 

Bronchitis/Emphysema No 542 77.098 69.465 2.9838 4 670 15 30 60 100 145 185 265 420 

Bronchitis/Emphysema Yes 17 64.588 60.635 14.706 10 275 10 30 50 63 120 275 275 275 

Bronchitis/EMphysema DK 5 157 149.57 66.888 15 360 15 60 80 270 360 360 360 360 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-88. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Preparationa 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 4278 52.37 52.8802 0.8085 1 555 5 20 35 65 115 150 210 265 

Gender Male 1341 37.8106 42.1779 1.1518 1 480 5 13 30 50 80 105 150 210 

Gender Female 2937 59.0177 55.862 1.0308 1 555 5 25 45 75 120 155 224 272 

Age (years) * 94 52 43.2171 4.4575 5 215 5 20 40 60 110 150 195 215 

Age (years) 1-4 24 56.4583 60.3699 12.3229 5 240 5 22.5 30 75 150 180 240 240 

Age (years) 5-11 60 25.1667 29.6877 3.8327 1 120 2 5 11 30 60 107 120 120 

Age (years) 12-17 131 21.7023 37.6902 3.293 1 385 2 5 10 30 55 70 90 90 

Age (years) 18-64 3173 52.0905 52.8766 0.9387 1 555 5 20 35 65 110 145 210 265 

Age (years) > 64 796 60.5025 54.669 1.9377 1 525 5 25 45 80 120 150 240 270 

Race White 3584 51.6205 53.2589 0.8896 1 555 5 19 35 65 110 145 210 265 

Race Black 377 57.0265 52.2893 2.693 1 390 5 20 40 75 120 150 210 240 

Race Asian 62 54 41.8224 5.3115 2 210 5 20 50 70 105 130 175 210 

Race Some Others 66 50.5909 53.2368 6.553 1 295 5 15 33.5 70 115 150 210 295 

Race Hispanic 132 59.2121 49.7947 4.3341 2 315 5 23.5 55 80 110 135 225 285 

Race Refused 57 53.1404 49.297 6.5295 2 210 5 20 40 60 120 180 195 210 

Hispanic No 3960 51.848 52.6035 0.8359 1 555 5 20 35 65 111 145 205 255 

Hispanic Yes 254 59.2244 56.7225 3.5591 2 420 5 20 45 75 120 155 240 315 

Hispanic DK 20 54.95 53.2002 11.8959 6 240 8 25 45 60 112.5 180 240 240 

Hispanic Refused 44 58.6136 53.2957 8.0346 2 210 5 27.5 37.5 80 150 180 210 210 

Employment * 210 27.1667 40.5487 2.7981 1 385 2 5 15 30 60 90 120 180 

Employment Full Time 1988 45.4874 46.6734 1.0468 1 480 5 15 30 60 90 130 180 240 

Employment Part Time 420 53.8643 55.3474 2.7007 2 520 5 20 40 65 105 125 205 255 

Employment Not Employed 1625 63.6357 57.7587 1.4328 1 555 5 29 45 90 125 170 240 275 

Employment Refused 35 53.5429 66.7803 11.2879 2 340 2 20 30 60 120 195 340 340 

Education * 291 31.7079 42.6211 2.4985 1 385 2 5 15 37 75 120 155 195 

Education < High School 450 61.2556 53.2321 2.5094 1 555 5 30 45 90 120 150 197 225 

Education High School Graduate 1449 58.8392 56.6653 1.4886 1 520 5 22 45 75 120 155 240 310 

Education < College 954 52.0073 52.2377 1.6913 1 525 5 20 34.5 65 110 150 210 245 

Education College Graduate 659 46.2018 48.0775 1.8728 1 515 5 15 30 60 100 125 180 224 

Education Post Graduate 475 46.1621 48.7374 2.2362 1 375 5 15 30 60 96 135 200 270 

Census Region Northeast 952 52.312 53.2054 1.7244 1 480 5 20 40 61 110 140 205 255 

Census Region Midwest 956 53.2333 51.8139 1.6758 1 520 5 20 35 65 120 150 210 265 

Census Region South 1453 53.3944 53.4621 1.4025 1 555 5 16 35 70 120 150 195 245 

Census Region West 917 49.9073 52.7204 1.741 1 515 5 15 31 60 105 135 225 265 

Day Of Week Weekday 2995 50.0571 49.979 0.9132 1 555 5 19 35 60 105 132 180 240 

Day Of Week Weekend 1283 57.7693 58.7687 1.6407 1 420 5 20 40 75 130 180 240 300 

Season Winter 1173 50.6206 48.6464 1.4204 1 480 5 18 35 65 110 135 195 240 

Season Spring 1038 54.3892 54.484 1.6911 1 525 5 20 38.5 70 120 150 224 265 

Season Summer 1148 51.3972 54.1854 1.5992 1 555 5 20 35 60 110 137 208 300 

Season Fall 919 53.5375 54.5349 1.7989 1 520 5 20 37 67 120 155 200 265 

Asthma No 3948 52.0433 53.1805 0.8464 1 555 5 20 35 65 110 145 210 265 

Asthma Yes 300 57.1433 49.4425 2.8546 1 272 5 20.5 45 75 120 160 199 240 

Asthma DK 30 47.6333 44.8119 8.1815 2 195 5 10 32.5 60 117.5 120 195 195 

Angina No 4091 52.1936 52.9733 0.8282 1 555 5 20 35 65 115 150 210 265 

Angina Yes 149 56.8054 48.2377 3.9518 1 340 5 25 45 80 120 135 180 210 

Angina DK 38 53.9737 60.4168 9.8009 2 240 2 10 32.5 60 120 240 240 240 

Bronchitis/Emphysema No 4024 52.0318 53.0963 0.837 1 555 5 20 35 65 110 145 210 265 

Bronchitis/Emphysema Yes 216 56.9074 46.6833 3.1764 3 240 5 20 45 85 120 150 198 210 

Bronchitis/Emphysema DK 38 62.3947 61.7031 10.0096 2 240 2 20 42.5 90 150 240 240 240 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean

24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max =

maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-89. Statistics for 24-Hour Cumulative Number of Minutes Spent Doing Dishes/Laundrya 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1865 61.7882 68.894 1.5953 1 825 10 20 30 80 150 190 255 335 

Gender Male 324 46.1142 50.179 2.7877 1 360 10 15 30 60 120 135 210 260 

Gender Female 1541 65.0837 71.793 1.8289 1 825 10 20 35 90 150 200 270 340 

Age (years) * 32 43.75 46.49 8.2183 10 225 10 15 30 55 90 150 225 225 

Age (years) 1-4 10 49.3 66.545 21.0434 3 210 3 5 22.5 55 165 210 210 210 

Age (years) 5-11 20 34.25 28.799 6.4395 1 92 1.5 15 30 58 82.5 91 92 92 

Age (years) 12-17 47 32.6809 30.603 4.4639 2 150 5 10 20 45 65 90 150 150 

Age (years) 18-64 1371 63.2356 67.104 1.8123 1 565 10 20 30 90 150 198 245 335 

Age (years) > 64 385 63.4416 79.738 4.0638 1 825 9 20 35 80 135 195 285 375 

Race White 1560 62.2173 69.493 1.7595 1 825 10 20 30 85 147.5 190 270 335 

Race Black 170 57.8471 60.026 4.6038 5 390 5 17 30 75 150 180 235 240 

Race Asian 19 56.7368 51.705 11.862 3 210 3 15 30 90 120 210 210 210 

Race Some Others 25 45.96 41.361 8.2721 5 150 10 15 30 80 120 120 150 150 

Race Hispanic 71 69.0141 75.626 8.9752 3 325 5 20 35 105 200 225 275 325 

Race Refused 20 60.75 104.217 23.3037 5 475 7.5 15 30 60 127.5 305 475 475 

Hispanic No 1732 61.3077 68.206 1.6389 1 825 10 20 30 80 140 180 250 335 

Hispanic Yes 112 68.2589 71.468 6.7531 3 325 5 20 30 103 180 225 270 275 

Hispanic DK 7 75.7143 66.548 25.1526 10 180 10 15 55 150 180 180 180 180 

Hispanic Refused 14 62.5 122.266 32.677 5 475 5 15 25 35 120 475 475 475 

Employment * 73 35.3288 37.364 4.3732 1 210 3 15 20 50 80 120 150 210 

Employment Full Time 776 56.9549 63.42 2.2766 2 565 10 20 30 70 125 180 240 335 

Employment Part Time 214 63.7243 64.791 4.429 2 340 10 15 30 90 151 205 240 275 

Employment Not Employed 789 68.5234 76.296 2.7162 1 825 10 25 40 90 158 210 285 375 

Employment Refused 13 58.2308 59.448 16.4878 10 180 10 10 30 100 150 180 180 180 

Education * 99 37.5253 38.655 3.885 1 210 3 10 30 55 90 120 180 210 

Education < High School 216 69.7824 69.956 4.7599 2 570 10 26.5 45 90 151 195 245 315 

Education High School Graduate 683 67.3616 76.746 2.9366 1 825 10 20 40 90 150 205 285 405 

Education < College 422 64.3033 72.277 3.5184 2 475 10 20 30 85 155 210 285 360 

Education College Graduate 262 51.4466 49.386 3.0511 1 260 10 15 30 70 120 158 200 225 

Education Post Graduate 183 53.6831 60.208 4.4507 3 360 5 15 30 60 120 190 245 330 

Census Region Northeast 471 59.5223 60.067 2.7677 2 565 10 20 35 75 135 180 210 285 

Census Region Midwest 405 60.3235 68.244 3.3911 1 480 5 15 30 75 150 198 240 285 

Census Region South 602 65.8156 75.076 3.0599 1 825 10 20 35 90 150 210 270 360 

Census Region West 387 59.814 69.562 3.536 2 570 10 15 30 70 150 210 270 345 

Day Of Week Weekday 1270 59.5402 68.798 1.9305 1 825 9 20 30 75 137.5 190 245 330 

Day Of Week Weekend 595 66.5866 68.909 2.825 5 565 10 20 40 90 150 210 275 340 

Season Winter 503 65.3479 79.461 3.543 1 825 10 20 30 90 150 210 300 360 

Season Spring 438 62.7763 67.751 3.2373 2 450 10 20 35 75 150 190 285 335 

Season Summer 510 61.7294 62.801 2.7809 2 565 10 20 40 90 140 180 240 270 

Season Fall 414 56.4903 63.125 3.1024 1 570 8 15 30 65 130 195 230 270 

Asthma No 1712 61.9533 69.64 1.6831 1 825 10 20 30 85 150 195 270 335 

Asthma Yes 147 60.8912 60.62 4.9999 2 375 10 20 30 76 151 180 250 255 

Asthma DK 6 36.6667 41.793 17.062 10 120 10 10 25 30 120 120 120 120 

Angina No 1790 62.0788 69.212 1.6359 1 825 10 20 30 85 150 190 255 335 

Angina Yes 66 54.7576 62.985 7.7529 5 335 9 25 30 60 120 200 315 335 

Angina DK 9 55.5556 44.19 14.7301 10 120 10 30 30 90 120 120 120 120 

Bronchitis/Emphysema No 1746 60.5063 65.326 1.5634 1 565 10 20 30 80 140 190 250 325 

Bronchitis/Emphysema Yes 112 82.7143 109.505 10.3473 3 825 5 20 57.5 103 170 240 360 570 

Bronchitis/Emphysema DK 7 46.7143 51.403 19.4284 2 120 2 10 30 120 120 120 120 120 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 

24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = 

maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

a Includes food cleanup, clothes care. 

Source: Tsang and Klepeis, 1996. 
Table 15-90. Statistics for 24-Hour Cumulative Number of Minutes Spent in Housekeepinga 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1943 118.833 113.369 2.5719 1 810 10 40 90 165 270 345 465 540 

Gender Male 370 109.419 116.541 6.0587 1 810 10 30 60 150 270 360 425 560 

Gender Female 1573 121.047 112.533 2.8374 1 790 15 45 90 165 270 345 465 540 

Age (years) * 47 146.043 121.3 17.6935 10 480 10 45 115 240 300 375 480 480 

Age (years) 1-4 11 74.091 69.42 20.9308 10 270 10 40 60 90 90 270 270 270 

Age (years) 5-11 54 42.852 34.096 4.6399 1 180 5 20 30 53 80 120 150 180 

Age (years) 12-17 72 78.111 75.546 8.9031 1 300 5 27.5 60 105 210 240 285 300 

Age (years) 18-64 1316 120.422 113.654 3.133 1 810 15 40 90 165 270 360 465 525 

Age > 64 443 128.217 118.925 5.6503 3 790 10 55 90 180 270 345 540 570 

Race White 1649 119.056 112.184 2.7626 1 790 10 40 90 165 265 340 465 540 

Race Black 137 116.555 109.394 9.3462 1 490 5 30 90 150 300 358 480 484 

Race Asian 32 98.75 100.467 17.7602 15 425 15 30 60 127.5 265 345 425 425 

Race Some Others 26 82.423 56.436 11.0681 5 210 15 40 60 115 185 190 210 210 

Race Hispanic 71 112.648 129.335 15.3492 5 660 8 30 60 135 270 465 518 660 

Race Refused 28 189.286 176.198 33.2983 10 810 20 52.5 147.5 247.5 420 465 810 810 

Hispanic No 1771 117.443 110.586 2.6278 1 790 10 40 90 165 265 335 425 525 

Hispanic Yes 134 121.657 129.578 11.1939 5 660 10 35 85 135 270 470 540 658 

Hispanic DK 15 146.867 127.912 33.0268 10 510 10 30 120 210 240 510 510 510 

Hispanic Refused 23 191.087 180.296 37.5944 10 810 20 45 150 255 390 420 810 810 

Employment * 138 65.565 68.838 5.8599 1 375 5 25 45 80 180 240 285 300 

Employment Full Time 673 106.579 102.376 3.9463 1 655 10 30 70 145 240 325 413 490 

Employment Part Time 193 124.72 117.48 8.4564 1 660 15 45 90 180 270 390 480 540 

Employment Not Employed 925 132.681 119.442 3.9272 3 790 15 55 105 180 295 370 484 600 

Employment Refused 14 236.786 208.221 55.6495 10 810 10 120 182.5 300 430 810 810 810 

Education * 171 82.164 96.944 7.4135 1 810 5 30 45 105 220 270 300 375 

Education < High School 246 140.736 125.356 7.9924 3 715 10 60 120 180 300 400 540 660 

Education High School Graduate 677 125.078 120.495 4.631 2 790 15 45 90 175 270 375 490 610 

Education < College 433 112.898 100.145 4.8127 1 570 10 40 90 150 240 320 420 470 

Education College Graduate 245 107.302 102.244 6.5321 1 585 15 30 60 150 240 328 405 465 

Education Post Graduate 171 130.813 117.998 9.0236 5 655 15 60 90 180 280 390 495 540 

Census Region Northeast 464 119.235 116.368 5.4022 2 790 10 35 90 165 245 330 480 655 

Census Region Midwest 413 117.855 112.595 5.5405 1 715 10 34 88 165 255 345 480 525 

Census Region South 648 119.912 116.159 4.5631 1 810 10 40 90 165 285 370 435 540 

Census Region West 418 117.679 106.559 5.212 5 720 15 40 90 165 255 340 420 470 

Day Of Week Weekday 1316 113.21 111.913 3.085 1 790 10 30 75 150 255 330 470 550 

Day Of Week Weekend 627 130.635 115.567 4.6153 1 810 15 55 90 180 290 370 435 525 

Season Winter 470 111.4 100.617 4.6411 1 810 10 45 85 160 240 290 390 480 

Season Spring 451 122.621 114.024 5.3692 3 720 15 40 90 180 270 360 465 540 

Season Summer 563 111.803 114.5 4.8256 1 690 10 30 75 135 255 365 465 610 

Season Fall 459 131.344 122.391 5.7127 1 790 15 45 90 180 300 390 480 560 

Asthma No 1789 118.529 112.075 2.6497 1 790 10 40 90 165 270 345 465 540 

Asthma Yes 140 115.664 115.811 9.7878 5 690 10 36.5 67 150 277.5 377.5 470 480 

Asthma DK 14 189.286 208.565 55.7414 10 810 10 45 122.5 255 340 810 810 810 

Angina No 1853 117.731 112.346 2.6099 1 790 13 40 90 160 265 345 465 540 

Angina Yes 75 122.88 103.762 11.9814 5 394 5 30 90 210 270 320 370 394 

Angina DK 15 234.667 204 52.6725 10 810 10 120 240 300 480 810 810 810 

Bronchitis/Emphysema No 1816 118.073 112.929 2.65 1 790 10 40 90 160 270 355 465 540 

Bronchitis/Emphysema Yes 107 118.701 102.942 9.9518 5 480 10 30 90 180 255 290 465 470 

Bronchitis/Emphysema DK 20 188.5 176.435 39.452 5 810 7.5 85 155 240 320 575 810 810 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

a Includes cleaning house, other repairs, and household work. 

Source: Tsang and Klepeis, 1996. 
Table 15-91. Statistics for 24-Hour Cumulative Number of Minutes Spent in Bathing (a) 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 6416 26.0842 29.6711 0.3704 1 705 5 10 20 30 50 60 90 120 

Gender Male 2930 24.2416 31.0251 0.5732 1 705 5 10 20 30 45 60 75 100 

Gender Female 3484 27.6372 28.4021 0.4812 1 555 5 10 20 30 60 75 105 135 

Gender Refused 2 20 14.1421 10 10 30 10 10 20 30 30 30 30 30 

Age (years) * 114 29.0088 38.9855 3.6513 2 300 5 10 20 30 60 60 105 275 

Age (years) 1-4 330 29.9727 19.4226 1.0692 1 170 10 15 30 31 54.5 60 85 90 

Age (years) 5-11 438 25.7511 35.3164 1.6875 1 690 5 15 20 30 45 60 60 75 

Age (years) 12-17 444 23.1216 18.7078 0.8878 1 210 5 10 18 30 45 60 65 90 

Age (years) 18-64 4383 25.4312 27.1553 0.4102 1 555 5 10 20 30 50 60 90 120 

Age (years) > 64 707 29.9123 44.502 1.6737 1 705 5 10 20 30 60 85 120 150 

Race White 5117 25.0233 28.5494 0.3991 1 705 5 10 20 30 45 60 90 115 

Race Black 707 31.4851 31.5524 1.1866 1 295 5 15 22 40 60 80 120 170 

Race Asian 112 28.1786 29.7661 2.8126 5 270 5 15 20 30 60 75 90 90 

Race Some Others 122 30.2213 27.2726 2.4691 1 240 8 15 27.5 35 50 60 100 150 

Race Hispanic 280 28.7786 39.2648 2.3465 2 546 5 15 20 31.5 54.5 62.5 90 155 

Race Refused 78 27.5769 40.3235 4.5657 3 275 5 10 15 30 60 100 195 275 

Hispanic No 5835 25.8833 28.5411 0.3736 1 705 5 10 20 30 50 60 90 120 

Hispanic Yes 486 28.751 40.5582 1.8398 2 570 5 15 20 30 50 60 90 140 

Hispanic DK 33 25.7576 16.7724 2.9197 5 65 10 15 20 30 55 65 65 65 

Hispanic Refused 62 24.2581 37.2268 4.7278 3 275 5 10 15 25 30 60 105 275 

Employment * 1189 26.1329 26.4288 0.7665 1 690 5 15 20 30 45 60 75 90 

Employment Full Time 3095 24.1499 25.0984 0.4511 1 555 5 10 15 30 45 60 85 110 

Employment Part Time 558 24.7616 23.2468 0.9841 1 295 5 10 20 30 46 60 90 110 

Employment Not Employed 1528 30.3161 39.9341 1.0216 1 705 5 10 20 30 60 85 120 155 

Employment Refused 46 30.4348 45.176 6.6608 3 275 5 10 15 30 55 105 275 275 

Education * 1330 25.6759 26.4094 0.7242 1 690 5 15 20 30 45 60 75 90 

Education < High School 474 33.3122 53.0129 2.435 1 570 5 15 20.5 33 60 85 110 300 

Education High School Graduate 1758 25.822 23.5699 0.5621 1 270 5 10 20 30 50 60 90 120 

Education < College 1288 26.4099 27.0338 0.7533 1 255 5 10 20 30 55 75 105 150 

Education College Graduate 897 25.3813 34.8197 1.1626 1 705 5 10 15 30 50 65 105 135 

Education Post Graduate 669 22.7788 23.0661 0.8918 1 257 5 10 15 30 45 60 85 100 

Census Region Northeast 1444 25.0478 24.2512 0.6382 1 360 5 10 20 30 50 60 90 105 

Census Region Midwest 1402 24.602 30.2958 0.8091 1 570 5 10 15 30 45 60 85 115 

Census Region South 2266 27.4086 26.0895 0.5481 1 300 5 15 20 30 55 65 100 135 

Census Region West 1304 26.5238 38.8092 1.0747 1 705 5 10 20 30 48 60 90 133 

Day Of Week Weekday 4427 25.2896 30.2913 0.4553 1 705 5 10 20 30 45 60 90 115 

Day Of Week Weekend 1989 27.8527 28.1689 0.6316 1 555 5 15 20 30 60 68 100 130 

Season Winter 1796 26.858 26.9167 0.6351 1 546 5 11 20 30 50 60 90 110 

Season Spring 1645 28.5854 41.0512 1.0121 1 705 5 15 20 30 60 70 115 150 

Season Summer 1744 23.9295 20.7343 0.4965 1 270 5 10 19.5 30 45 60 80 100 

Season Fall 1231 24.6653 25.5885 0.7293 1 340 5 10 17 30 50 60 95 120 

Asthma No 5912 26.0658 30.0373 0.3907 1 705 5 10 20 30 50 60 90 120 

Asthma Yes 468 26.5427 22.9543 1.0611 1 210 5 15 20 30 46 60 100 120 

Asthma DK 36 23.1389 44.0728 7.3455 3 275 5 10 15 25 30 30 275 275 

Angina No 6243 26.0042 29.0175 0.3673 1 705 5 10 20 30 50 60 90 120 

Angina Yes 131 31.145 49.5427 4.3286 5 546 5 15 25 30 50 60 105 131 

Angina DK 42 22.1905 40.9153 6.3134 3 275 5 10 15 25 30 30 275 275 

Bronchitis/Emphysema No 6112 26.0545 29.857 0.3819 1 705 5 10 20 30 50 60 90 120 

Bronchitis/Emphysema Yes 268 27.2463 22.162 1.3538 1 150 5 13 20 30 60 60 95 131 

Bronchitis/Emphysema DK 36 22.4722 44.0859 7.3477 3 275 5 10 15 22.5 30 30 275 275 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

a Includes baby and child care, personal care services, washing and personal hygiene (bathing, showering, etc.) 

Source: Tsang and Klepeis, 1996. 
Table 15-92. Statistics for 24-Hour Cumulative Number of Minutes Spent in Yardwork/Maintenance (a) 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1414 147.69 148.216 3.942 1 1080 5 45 100 205 360 470 570 655 

Gender Male 804 174.84 160.191 5.649 2 1080 10 60 120 249.5 415 510 600 670 

Gender Female 610 111.91 121.979 4.939 1 900 5 30 75 145 277.5 360 465 510 

Age (years) * 20 181.85 170.345 38.09 5 600 10 60 116 240 467.5 570 600 600 

Age (years) 1-4 12 93.167 80.805 23.326 5 285 5 30 82.5 132.5 178 285 285 285 

Age (years) 5-11 26 96.154 85.532 16.774 5 330 5 39 60 120 210 300 330 330 

Age (years) 12-17 54 116 116.758 15.889 3 505 5 30 90 150 285 385 450 505 

Age (years) 18-64 1015 150.22 154.486 4.849 1 1080 5 35 100 210 360 480 585 670 

Age (years) > 64 287 149.3 133.834 7.9 2 810 10 60 120 205 330 420 525 630 

Race White 1249 151.52 150.205 4.25 1 1080 5 45 105 210 360 480 575 660 

Race Black 77 114.53 127.124 14.487 2 750 5 20 65 165 285 355 405 750 

Race Asian 13 140 150.111 41.633 5 425 5 15 85 210 360 425 425 425 

Race Some Others 26 117.23 110.647 21.7 5 380 5 30 88 178 290 360 380 380 

Race Hispanic 37 102.11 113.508 18.661 5 565 5 20 60 120 255 300 565 565 

Race Refused 12 177.08 190.793 55.077 30 600 30 60 97.5 215 510 600 600 600 

Hispanic No 1331 148.69 147.962 4.056 1 1080 5 45 105 209 360 465 570 660 

Hispanic Yes 65 106.17 127.4 15.802 5 575 5 20 60 120 255 300 565 575 

Hispanic DK 8 248.75 206.48 73.002 5 585 5 90 190 420 585 585 585 585 

Hispanic Refused 10 203.5 200.056 63.263 60 600 60 60 120 300 555 600 600 600 

Employment * 92 106.82 101.779 10.611 3 505 5 31.5 77 147.5 240 330 450 505 

Employment Full Time 664 146.73 155.488 6.034 1 1080 5 35 90 202.5 360 490 575 690 

Employment Part Time 121 134.51 130.79 11.89 2 554 5 30 90 200 317 390 490 495 

Employment Not Employed 526 157.76 147.022 6.41 2 810 10 60 120 220 370 480 595 655 

Employment Refused 11 211.55 198.724 59.918 2 600 2 60 120 375 465 600 600 600 

Education * 105 113.47 113.854 11.111 2 600 5 33 79 150 285 360 450 505 

Education < High School 160 158.46 164.764 13.026 2 900 7.5 45 111 210 412.5 492.5 595 810 

Education High School Graduate 465 151.39 146.985 6.816 3 840 5 50 110 210 345 460 575 690 

Education < College 305 152.84 157.011 8.99 2 1080 5 45 95 210 360 473 600 630 

Education College Graduate 211 145.36 138.849 9.559 1 625 5 40 105 225 330 465 525 533 

Education Post Graduate 168 142.2 147.773 11.401 2 690 5 30 90 180 340 470 570 630 

Census Region Northeast 291 140.5 139.641 8.186 3 840 5 40 90 200 330 450 525 600 

Census Region Midwest 314 145.1 143.219 8.082 2 780 10 55 95 195 360 445 560 655 

Census Region South 438 152.69 156.36 7.471 2 1080 5 45 111 205 375 480 585 635 

Census Region West 371 149.63 149.345 7.754 1 750 5 40 104 210 350 480 575 690 

Day Of Week Weekday 878 140.86 140.753 4.75 1 810 5 40 92.5 190 345 460 560 625 

Day Of Week Weekend 536 158.88 159.193 6.876 2 1080 5 50 116.5 225 380 510 600 690 

Season Winter 289 139.35 151.711 8.924 1 690 5 30 75 195 360 480 565 600 

Season Spring 438 162.23 150.477 7.19 3 900 10 60 120 220 360 480 570 700 

Season Summer 458 137.92 140.291 6.555 2 1080 5 40 90 180 310 440 555 630 

Season Fall 229 149.97 153.398 10.137 2 720 5 40 97 210 390 480 600 655 

Asthma No 1311 146.95 147.084 4.062 1 1080 5 45 100 200 355 465 570 635 

Asthma Yes 98 149.27 155.758 15.734 5 670 5 30 90 210 445 480 670 670 

Asthma DK 5 312 230.043 102.879 60 600 60 120 300 480 600 600 600 600 

Angina No 1360 145.34 145.05 3.933 1 900 5 45 100 200 355 465 570 655 

Angina Yes 42 192.62 203.363 31.38 5 1080 15 60 142.5 255 465 485 1080 1080 

Angina DK 12 257.08 216.716 62.56 5 600 5 52.5 232.5 472.5 510 600 600 600 

Bronchitis/Emphysema No 1352 148.48 148.534 4.04 1 1080 5 45 105 205 360 470 570 660 

Bronchitis/Emphysema Yes 57 114.65 121.376 16.077 5 460 5 30 60 135 340 375 405 460 

Bronchitis/Emphysema DK 5 312 230.043 102.879 60 600 60 120 300 480 600 600 600 600 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

a Includes car repair services, other repairs services, outdoor cleaning, car repair maintenance, other repairs, plant care, other household work, 

domestic crafts, domestic arts. 

Source: Tsang and Klepeis, 1996. 
Table 15-93. Statistics for 24-Hour Cumulative Number of Minutes Spent in Sports/Exercise (a) 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1852 116.322 107.947 2.5084 1 1130 17 45 85 150 253 316 420 515 

Gender Male 958 130.669 117.216 3.7871 1 1130 20 55 97.5 175 270 355 475 558 

Gender Female 892 100.854 94.795 3.174 1 1065 15 35 65 130 230 285 370 435 

Gender Refused 2 142.5 38.891 27.5 115 170 115 115 143 170 170 170 170 170 

Age (years) * 32 102.031 79.32 14.022 5 290 15 40 80 137.5 225 270 290 290 

Age (years) 1-4 114 118.982 109.17 10.2247 10 670 25 45 90 159 250 330 390 630 

Age (years) 5-11 262 153.496 130.58 8.0673 2 975 20 60 120 200 330 415 525 580 

Age (years) 12-17 237 134.717 122.228 7.9396 5 1065 15 60 110 179 265 360 470 520 

Age (years) 18-64 992 109.692 100.801 3.2004 1 1130 20 45 75 145 240 300 405 510 

Age (years) > 64 215 82.051 75.995 5.1828 1 380 10 30 60 110 195 270 310 316 

Race White 1541 117.524 110.622 2.818 1 1130 20 45 85 150 255 320 435 525 

Race Black 135 110.4 93.06 8.0094 5 440 15 45 85 150 220 340 430 435 

Race Asian 37 85.432 73.897 12.1486 5 310 10 30 60 95 210 235 310 310 

Race Some Others 47 124.702 106.397 15.5196 15 553 30 40 85 180 270 325 553 553 

Race Hispanic 74 108.892 89.177 10.3667 1 520 15 45 90 145 225 270 345 520 

Race Refused 18 130 111.698 26.3275 30 420 30 60 82.5 140 300 420 420 420 

Hispanic No 1678 116.451 108.276 2.6432 1 1130 17 45 85 150 253 316 430 510 

Hispanic Yes 151 115.583 106.428 8.661 1 630 15 45 90 145 240 325 415 553 

Hispanic DK 7 92.857 62.773 23.726 20 185 20 30 75 145 185 185 185 185 

Hispanic Refused 16 120 110 27.5 30 420 30 60 70 122.5 290 420 420 420 

Employment * 606 138.658 123.665 5.0235 2 1065 20 60 110 180 285 375 470 580 

Employment Full Time 644 102.315 94.146 3.7099 5 1130 20 45 67.5 130 225 280 360 405 

Employment Part Time 125 115.272 91.33 8.1688 1 450 15 45 90 160 220 300 420 420 

Employment Not Employed 465 107.239 104.105 4.8277 1 600 10 31 70 135 250 310 462 515 

Employment Refused 12 102.917 87.917 25.3794 30 280 30 40 75 130 270 280 280 280 

Education * 663 139.46 123.813 4.8085 2 1065 20 60 110 180 285 383 510 580 

Education < High School 103 96.243 97.046 9.5622 10 570 15 30 60 135 210 270 305 510 

Education High School Graduate 341 109.276 106.483 5.7664 1 1130 15 40 75 150 235 285 405 485 

Education < College 265 110.068 94.836 5.8257 1 525 17 45 80 145 240 305 418 475 

Education College Graduate 258 105.717 92.204 5.7404 1 600 20 45 70 130 240 297 343 450 

Education Post Graduate 222 87.149 79.704 5.3494 5 375 15 30 60 105 208 290 355 360 

Census Region Northeast 437 126.865 122.905 5.8793 1 1130 15 50 95 165 270 338 470 558 

Census Region Midwest 341 105.889 94.38 5.111 5 570 20 40 75 135 240 280 430 438 

Census Region South 627 112.774 104.846 4.1872 1 975 15 45 80 150 250 313 410 462 

Census Region West 447 118.951 105.629 4.9961 4 670 22 48 85 160 250 325 475 525 

Day Of Week Weekday 1264 107.154 94.026 2.6447 1 670 15 45 75 140 235 285 375 485 

Day Of Week Weekend 588 136.029 130.966 5.401 1 1130 20 51.5 90 180 297 380 462 558 

Season Winter 448 104.094 104.108 4.9187 1 1065 15 40 70 130 230 280 360 420 

Season Spring 533 123.452 100.904 4.3706 5 650 25 60 90 162 267 330 420 500 

Season Summer 579 125.988 114.358 4.7525 1 670 15 45 90 160 283 360 470 545 

Season Fall 292 102.901 110.416 6.4616 4 1130 15 40 60 127.5 225 275 460 565 

Asthma No 1699 114.927 105.239 2.5532 1 1130 17 45 85 150 250 310 420 510 

Asthma Yes 137 132.131 134.238 11.4687 1 1065 15 60 90 165 265 390 553 565 

Asthma DK 16 129.063 134.786 33.6966 10 450 10 60 60 152.5 420 450 450 450 

Angina No 1801 117.3 108.373 2.5537 1 1130 20 45 89 150 254 316 430 515 

Angina Yes 40 68 70.942 11.217 5 330 5.5 30 47.5 60 172.5 235 330 330 

Angina DK 11 131.818 116.023 34.9823 40 420 40 60 90 155 270 420 420 420 

Bronchitis/Emphysema No 1782 116.226 107.987 2.5581 1 1130 17 45 85 150 250 315 430 515 

Bronchitis/Emphysema Yes 56 119.429 108.516 14.501 10 553 20 42.5 75 172.5 270 340 410 553 

Bronchitis/Emphysema DK 14 116.071 108.187 28.9143 15 420 15 60 85 140 270 420 420 420 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

a Includes active sports, exercise, hobbies. 

Source: Tsang and Klepeis, 1996. 
Table 15-94. Statistics for 24-Hour Cumulative Number of Minutes Eating or Drinking 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 8627 74.8821 54.8419 0.5904 1 900 15 35 60 96 140 175 215 270 

Gender Male 3979 75.8316 56.2313 0.8914 1 900 15 39 60 96 140 180 210 270 

Gender Female 4644 74.0814 53.6353 0.7871 2 640 15 34 60 98 140 170 225 270 

Gender Refused 4 60 21.2132 10.6066 30 75 30 45 67.5 75 75 75 75 75 

Age (years) * 157 75.3248 50.1255 4.0005 10 315 15 30 65 100 145 150 195 285 

Age (years) 1-4 492 93.4837 52.8671 2.3834 2 345 20 60 90 120 160 190 225 270 

Age (years) 5-11 680 68.5412 38.9518 1.4937 5 255 15 40 65 90 120 142.5 165 195 

Age (years) 12-17 538 55.8587 34.9903 1.5085 2 210 10 30 50 75 105 125 150 170 

Age (years) 18-64 5464 71.8673 55.1199 0.7457 1 900 15 30 60 90 135 170 220 270 

Age (years) > 64 1296 91.7014 62.6665 1.7407 5 750 20 50 80 120 165 200 270 295 

Race White 7049 77.0058 55.6564 0.6629 1 900 15 40 64 100 145 180 225 270 

Race Black 808 59.9047 46.5954 1.6392 2 505 15 30 50 75 119 140 200 225 

Race Asian 148 80.4054 47.8283 3.9315 2 305 15 45 72.5 106.5 150 160 200 200 

Race Some Others 168 66.0417 52.0928 4.019 7 525 15 30 59.5 83 120 135 190 200 

Race Hispanic 345 68.7043 51.8926 2.7938 2 435 12 30 60 90 125 165 195 225 

Race Refused 109 74.2477 60.8473 5.8281 8 410 20 30 60 90 130 180 290 315 

Hispanic No 7861 75.5599 55.2306 0.6229 1 900 15 35 60 100 140 175 220 270 

Hispanic Yes 639 68.2754 50.1994 1.9859 2 435 15 30 60 90 120 155 195 225 

Hispanic DK 41 60.4146 37.1039 5.7947 5 150 15 30 55 90 120 130 150 150 

Hispanic Refused 86 68.9186 55.4732 5.9818 8 410 15 30 60 90 115 155 210 410 

Employment * 1695 72.2083 44.9086 1.0908 2 345 15 40 65 90 133 150 195 210 

Employment Full Time 3684 70.6097 55.0998 0.9078 1 900 15 30 60 90 135 165 225 270 

Employment Part Time 715 72.2112 55.4476 2.0736 2 509 15 30 60 90 135 170 230 260 

Employment Not Employed 2472 83.9498 59.1281 1.1892 2 750 15 45 75 110 150 185 235 285 

Employment Refused 61 71.0492 60.9843 7.8082 8 385 15 30 55 90 120 145 235 385 

Education * 1867 70.85 45.3955 1.0506 2 375 15 38 60 90 130 150 190 210 

Education < High School 758 72.3206 57.4352 2.0861 2 460 15 30 60 90 135 180 230 315 

Education High School Graduate 2363 74.8565 57.1005 1.1746 1 900 15 35 60 96 140 175 220 270 

Education < College 1612 73.9237 56.5324 1.408 2 525 15 30 60 90 145 175 230 275 

Education College Graduate 1160 78.4991 55.4196 1.6272 1 640 15 40 65 105 145 180 220 265 

Education Post Graduate 867 82.8166 59.6871 2.0271 2 750 15 40 70 110 150 185 240 270 

Census Region Northeast 1916 78.2766 59.1627 1.3516 1 750 15 37 65 102.5 145 180 240 285 

Census Region Midwest 1928 75.8117 51.3702 1.1699 1 435 15 40 64 100 140 175 210 255 

Census Region South 2960 71.3916 55.0903 1.0126 2 900 15 30 60 90 135 165 210 270 

Census Region West 1823 75.9989 52.9755 1.2407 2 500 15 35 60 100 150 180 210 240 

Day Of Week Weekday 5813 71.2069 52.0446 0.6826 1 900 15 33 60 90 130 165 210 250 

Day Of Week Weekend 2814 82.4741 59.5052 1.1217 2 630 15 40 70 110 150 190 240 297 

Season Winter 2332 76.0931 56.4379 1.1687 2 640 15 38.5 65 95.5 140 175 240 275 

Season Spring 2222 76.3096 55.207 1.1712 1 630 15 35 60 100 145 178 220 275 

Season Summer 2352 73.4787 53.2506 1.098 1 750 15 35 60 95 135 170 210 260 

Season Fall 1721 73.3161 54.2737 1.3083 2 900 15 30 60 95 140 175 210 232 

Asthma No 7937 75.2016 54.8093 0.6152 1 900 15 35 60 100 140 175 215 270 

Asthma Yes 635 71.3732 55.0353 2.184 2 460 15 30 60 90 133 170 225 285 

Asthma DK 55 69.2909 56.5874 7.6302 8 335 15 30 60 90 120 210 215 335 

Angina No 8318 74.5795 54.4372 0.5969 1 900 15 35 60 95 140 175 210 265 

Angina Yes 243 85.0288 63.5335 4.0757 2 500 15 45 75 115 160 180 285 330 

Angina DK 66 75.6667 67.304 8.2845 5 435 15 30 60 90 150 195 215 435 

Bronchitis/Emphysema No 8169 74.6605 54.3234 0.601 1 900 15 35 60 95 140 170 210 260 

Bronchitis/Emphysema Yes 397 80.6599 65.2442 3.2745 2 460 15 30 60 110 150 180 285 360 

Bronchitis/Emphysema DK 61 66.9508 47.7188 6.1098 8 230 15 30 60 90 120 155 215 230 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-95. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at an Auto Repair Shop/Gas Station 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 153 190.693 234.506 18.959 1 930 5 15 60 360 565 645 695 748 

Gender Male 105 241.476 250.274 24.424 2 930 5 15 115 495 600 675 700 748 

Gender Female 48 79.604 144.512 20.858 1 595 3 10 15 70 295 485 595 595 

Age (years) * 3 161.667 115.578 66.729 90 295 90 90 100 295 295 295 295 295 

Age (years) 1-4 4 40 50.166 25.083 10 115 10 12.5 17.5 67.5 115 115 115 115 

Age (years) 5-11 5 22 21.679 9.695 5 60 5 15 15 15 60 60 60 60 

Age (years) 12-17 7 153.857 205.069 77.509 3 505 3 5 55 390 505 505 505 505 

Age (years) 18-64 118 223.847 249.335 22.953 1 930 5 15 75 480 600 675 700 748 

Age (years) > 64 16 58.125 96.889 24.222 2 358 2 15 20 42.5 225 358 358 358 

Race White 130 195.538 237.537 20.833 1 930 5 15 60 390 587.5 645 700 748 

Race Black 12 149.667 203.31 58.691 2 565 2 6.5 75 229 495 565 565 565 

Race Asian 5 173 231.236 103.412 5 525 5 15 25 295 525 525 525 525 

Race Some Others 3 15 10 5.774 5 25 5 5 15 25 25 25 25 25 

Race Hispanic 3 350 330.114 190.591 15 675 15 15 360 675 675 675 675 675 

Hispanic No 148 188.926 233.749 19.214 1 930 5 15 60 369.5 565 630 700 748 

Hispanic Yes 5 243 279.701 125.086 15 675 15 15 150 360 675 675 675 675 

Employment * 16 84.188 146.714 36.678 3 505 3 12.5 17.5 69.5 390 505 505 505 

Employment Full Time 84 283.571 263.755 28.778 3 930 5 17.5 230 540 630 680 748 930 

Employment Part Time 16 104.188 147.369 36.842 5 390 5 12.5 17.5 187.5 359 390 390 390 

Employment Not Employed 35 65.914 94.745 16.015 1 432 2 15 30 90 160 358 432 432 

Employment Refused 2 17.5 17.678 12.5 5 30 5 5 17.5 30 30 30 30 30 

Education * 18 95.056 153.879 36.27 3 505 3 10 17.5 79 390 505 505 505 

Education < High School 16 327.188 301.181 75.295 5 930 5 60 278 615 675 930 930 930 

Education High School Graduate 51 233.353 243.089 34.039 2 748 5 20 120 480 565 675 695 748 

Education < College 32 253.469 252.8 44.689 2 700 5 15 157 517.5 595 680 700 700 

Education College Graduate 19 72.895 126.321 28.98 1 508 1 5 20 90 295 508 508 508 

Education Post Graduate 17 49 73.388 17.799 5 235 5 10 15 35 225 235 235 235 

Census Region Northeast 29 247.31 257.069 47.737 2 930 3 30 120 432 600 748 930 930 

Census Region Midwest 48 230.896 251.622 36.318 1 700 5 17.5 74.5 510 600 680 700 700 

Census Region South 43 165.721 211.591 32.267 3 675 5 15 50 358 555 595 675 675 

Census Region West 33 115 198.907 34.625 5 675 5 10 15 100 505 645 675 675 

Day Of Week Weekday 121 204.645 244.861 22.26 1 930 5 15 60 390 595 675 700 748 

Day Of Week Weekend 32 137.938 184.175 32.558 2 540 3 15 40 200 505 510 540 540 

Season Winter 28 177.143 258.088 48.774 2 930 5 15 30 355 595 700 930 930 

Season Spring 44 189.636 223.267 33.659 2 645 5 15 79.5 384.5 565 600 645 645 

Season Summer 52 171.692 223.809 31.037 1 680 3 10 30 347.5 540 675 675 680 

Season Fall 29 239.448 251.391 46.682 5 748 8 35 95 445 605 695 748 748 

Asthma No 145 191.29 235.288 19.54 1 930 5 15 60 360 565 645 700 748 

Asthma Yes 8 179.875 234.838 83.028 5 600 5 5 37.5 374.5 600 600 600 600 

Angina No 149 191.047 235.262 19.273 1 930 5 15 60 360 585 645 700 748 

Angina Yes 4 177.5 235.744 117.872 5 510 5 10 97.5 345 510 510 510 510 

Bronchitis/Emphysema No 146 189.048 234.959 19.445 1 930 5 15 57.5 360 585 645 700 748 

Bronchitis/Emphysema Yes 7 225 239.948 90.692 5 555 5 5 95 510 555 555 555 555 

Note: A "*" Signifies missing data. Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. 

Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the

percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-96. Statistics for 24-Hour Cumulative Numbr of Minutes Spent Indoors at a Gym/Health Club 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 364 129.651 104.343 5.4691 5 686 30 60 110 155 240 320 525 600 

Gender Male 176 147.193 115.554 8.7102 5 686 30 77.5 120 175 285 360 533 660 

Gender Female 188 113.229 89.876 6.5549 5 660 30 60 92.5 135 200 279 420 560 

Age (years) * 6 202.5 227.854 93.0211 30 560 30 55 75 420 560 560 560 560 

Age (years) 1-4 5 156 29.875 13.3604 105 180 105 160 160 175 180 180 180 180 

Age (years) 5-11 28 105.286 69.537 13.1413 5 325 30 58 82.5 141 165 270 325 325 

Age (years) 12-17 39 165.385 122.056 19.5447 15 660 30 90 138 206 330 440 660 660 

Age (years) 18-64 254 123.134 98.827 6.2009 5 686 30 60 100 150 210 295 475 600 

Age (years) > 64 32 141.375 114.216 20.1907 10 533 30 60 103 173 292 340 533 533 

Race White 307 134.261 109.36 6.2415 5 686 30 65 110 164 255 330 533 600 

Race Black 30 117.7 75.418 13.7693 5 320 10 60 115 145 235 285 320 320 

Race Asian 10 75.2 36.484 11.5372 30 145 30 54 60 95 133 145 145 145 

Race Some Others 11 112.909 69.077 20.8276 25 270 25 65 90 153 179 270 270 270 

Race Hispanic 4 83.75 42.696 21.3478 40 140 40 52.5 77.5 115 140 140 140 140 

Race Refused 2 57.5 3.536 2.5 55 60 55 55 57.5 60 60 60 60 60 

Hispanic No 345 132.017 105.901 5.7015 5 686 30 65 110 160 240 325 533 600 

Hispanic Yes 17 90.118 58.765 14.2527 5 255 5 60 90 115 140 255 255 255 

Hispanic Refused 2 57.5 3.536 2.5 55 60 55 55 57.5 60 60 60 60 60 

Employment * 72 139.625 103.274 12.171 5 660 30 76 120 165 265 330 440 660 

Employment Full Time 176 131.193 112.511 8.4808 5 686 30 60 110 150 240 330 560 660 

Employment Part Time 40 129.25 92.836 14.6787 25 420 35 60 95 168 285 325 420 420 

Employment Not Employed 75 117.867 91.345 10.5477 5 533 25 60 90 145 230 285 475 533 

Employment Refused 1 40 * * 40 40 40 40 40 40 40 40 40 40 

Education * 81 136.877 99.66 11.0733 5 660 30 75 120 164 215 325 440 660 

Education < High School 9 110.556 97.706 32.5688 10 300 10 30 80 165 300 300 300 300 

Education High School Graduate 61 128.475 110.005 14.0847 5 660 25 75 105 145 210 310 525 660 

Education < College 71 145.634 129.073 15.3181 5 600 35 65 110 170 285 533 560 600 

Education College Graduate 81 121.975 99.467 11.0519 15 686 30 60 98 135 220 285 420 686 

Education Post Graduate 61 115.639 76.916 9.8481 10 415 40 60 90 145 225 265 320 415 

Census Region Northeast 83 140.53 107.244 11.7716 20 660 40 70 120 170 240 330 600 660 

Census Region Midwest 62 127 88.661 11.26 5 440 25 60 113 170 285 300 340 440 

Census Region South 118 125.669 107.038 9.8537 5 660 15 60 105 150 240 330 533 540 

Census Region West 101 126.99 108.452 10.7914 5 686 50 60 92 135 225 292 525 560 

Day Of Week Weekday 281 121.26 96.577 5.7613 5 686 30 60 98 145 210 295 475 560 

Day Of Week Weekend 83 158.06 123.652 13.5726 5 660 30 77 120 180 285 415 600 660 

Season Winter 127 139.795 108.258 9.6063 5 686 25 75 120 177 240 330 533 660 

Season Spring 85 141.459 115.229 12.4983 10 600 30 65 102 164 285 340 560 600 

Season Summer 81 109.864 87.411 9.7123 5 525 30 60 90 130 160 310 440 525 

Season Fall 71 119.944 98.963 11.7447 20 660 30 56 98 150 215 295 420 660 

Asthma No 333 132.39 106.796 5.8524 5 686 30 62 110 160 255 325 533 600 

Asthma Yes 28 100.071 69.387 13.113 5 330 25 60 86 118 210 230 330 330 

Asthma DK 3 101.667 55.752 32.1887 60 165 60 60 80 165 165 165 165 165 

Angina No 357 130.499 104.98 5.5561 5 686 30 62 110 155 240 325 525 600 

Angina Yes 4 90 47.61 23.8048 60 160 60 60 70 120 160 160 160 160 

Angina DK 3 81.667 65.256 37.6755 30 155 30 30 60 155 155 155 155 155 

Bronchitis/Emphysema No 352 130.696 104.843 5.5882 5 686 30 61 110 158 240 320 525 600 

Bronchitis/Emphysema Yes 10 97.3 92.848 29.361 10 330 10 45 76.5 120 245 330 330 330 

Bronchitis/Emphysema DK 2 107.5 67.175 47.5 60 155 60 60 108 155 155 155 155 155 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-97. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at the Laundromat 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 40 99.275 85.209 13.4727 2 500 5 54.5 91 120 153 238 500 500 

Gender Male 9 150.222 146.822 48.9407 2 500 2 115 120 150 500 500 500 500 

Gender Female 31 84.484 51.822 9.3075 5 265 5 50 80 115 137 155 265 265 

Age (years) 5-11 3 80.667 17.926 10.3494 60 92 60 60 90 92 92 92 92 92 

Age (years) 18-64 33 101.182 91.724 15.967 2 500 5 50 90 120 155 265 500 500 

Age (years) > 64 4 97.5 63.574 31.7871 5 150 5 60 118 135 150 150 150 150 

Race White 31 102.161 93.832 16.8527 2 500 5 50 90 120 155 265 500 500 

Race Black 6 75.667 50.306 20.5372 5 130 5 34 85 115 130 130 130 130 

Race Hispanic 3 116.667 30.551 17.6383 90 150 90 90 110 150 150 150 150 150 

Hispanic No 37 97.865 88.241 14.5068 2 500 5 50 90 120 155 265 500 500 

Hispanic Yes 3 116.667 30.551 17.6383 90 150 90 90 110 150 150 150 150 150 

Employment * 3 80.667 17.926 10.3494 60 92 60 60 90 92 92 92 92 92 

Employment Full Time 20 97.6 104.739 23.4203 2 500 4 42 83.5 115 143 328 500 500 

Employment Part Time 4 127.5 91.879 45.9393 75 265 75 77.5 85 178 265 265 265 265 

Employment Not Employed 13 97.462 60.852 16.8772 5 210 5 45 115 137 150 210 210 210 

Education * 3 80.667 17.926 10.3494 60 92 60 60 90 92 92 92 92 92 

Education < High School 6 95 53.292 21.7562 5 150 5 60 113 130 150 150 150 150 

Education High School Graduate 17 101.353 64.434 15.6275 5 265 5 59 90 120 210 265 265 265 

Education < College 6 91.5 56.387 23.0199 10 155 10 34 115 120 155 155 155 155 

Education College Graduate 7 126.429 168.219 63.5808 5 500 5 45 70 110 500 500 500 500 

Education Post Graduate 1 2 * * 2 2 2 2 2 2 2 2 2 2 

Census Region Northeast 6 168.667 166.465 67.9591 45 500 45 75 126 140 500 500 500 500 

Census Region Midwest 8 94 60.328 21.3291 5 210 5 57.5 93.5 118 210 210 210 210 

Census Region South 18 85.944 61.82 14.5711 2 265 2 50 76 115 155 265 265 265 

Census Region West 8 82.5 52.915 18.7083 5 150 5 35 100 118 150 150 150 150 

Day Of Week Weekday 25 103.32 100.663 20.1326 2 500 5 50 90 115 155 265 500 500 

Day Of Week Weekend 15 92.533 52.697 13.6063 10 210 10 60 92 130 150 210 210 210 

Season Winter 11 86.455 57.98 17.4816 2 210 2 45 80 120 140 210 210 210 

Season Spring 12 85.583 71.678 20.6916 5 265 5 35 73.5 120 130 265 265 265 

Season Summer 12 118.667 125.78 36.3096 5 500 5 55 101 113 137 500 500 500 

Season Fall 5 113.8 48.422 21.655 34 155 34 115 115 150 155 155 155 155 

Asthma No 37 95.459 83.88 13.7897 2 500 5 50 90 120 150 210 500 500 

Asthma Yes 3 146.333 106.514 61.4962 59 265 59 59 115 265 265 265 265 265 

Angina No 40 99.275 85.209 13.4727 2 500 5 54.5 91 120 153 238 500 500 

Bronchitis/Emphysema No 35 92.314 84.343 14.2565 2 500 5 50 90 115 130 210 500 500 

Bronchitis/Emphysema Yes 5 148 83.262 37.2357 30 265 30 140 150 155 265 265 265 265 

Note: A "*" Signifies missing data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard 

deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of

doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-98. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at Work (non-specific) 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 137 393.949 242.649 20.731 5 979 15 180 440 555 662 810 940 960 

Gender Male 96 435.271 243.979 24.901 10 979 20 245 473 598 765 840 960 979 

Gender Female 41 297.195 212.415 33.174 5 780 15 90 280 495 550 590 780 780 

Age (years) * 4 568.75 394.723 197.362 90 940 90 248 623 890 940 940 940 940 

Age (years) 1-4 2 200 70.711 50 150 250 150 150 200 250 250 250 250 250 

Age (years) 5-11 4 33.75 11.087 5.543 20 45 20 25 35 42.5 45 45 45 45 

Age (years) 12-17 2 207.5 166.17 117.5 90 325 90 90 208 325 325 325 325 325 

Age (years) 18-64 121 409.678 230.934 20.994 5 979 15 240 450 560 660 793 850 960 

Age (years) > 64 4 293.75 289.464 144.732 10 610 10 50 278 538 610 610 610 610 

Race White 113 397.903 235.199 22.126 5 979 15 210 450 555 660 780 940 960 

Race Black 13 379.231 286.501 79.461 10 850 10 85 405 510 810 850 850 850 

Race Some Others 1 405 * * 405 405 405 405 405 405 405 405 405 405 

Race Hispanic 9 314.778 266.161 88.72 30 793 30 95 245 440 793 793 793 793 

Race Refused 1 840 * * 840 840 840 840 840 840 840 840 840 840 

Hispanic No 121 388.702 242.092 22.008 5 979 15 180 405 550 660 795 940 960 

Hispanic Yes 12 361.083 242.06 69.877 30 793 30 138 370 510 660 793 793 793 

Hispanic DK 2 585 35.355 25 560 610 560 560 585 610 610 610 610 610 

Hispanic Refused 2 717.5 173.241 122.5 595 840 595 595 718 840 840 840 840 840 

Employment * 8 118.75 113.916 40.275 20 325 20 35 67.5 200 325 325 325 325 

Employment Full Time 97 440.732 237.56 24.121 10 979 15 300 480 585 690 815 960 979 

Employment Part Time 21 341.19 188.235 41.076 30 795 115 240 330 435 590 610 795 795 

Employment Not Employed 9 250.556 218.567 72.856 5 630 5 95 150 360 630 630 630 630 

Employment Refused 2 425 586.899 415 10 840 10 10 425 840 840 840 840 840 

Education * 11 234.091 266.306 80.294 20 840 20 40 150 325 610 840 840 840 

Education < High School 12 460.417 181.727 52.46 115 795 115 330 495 558 615 795 795 795 

Education High School Graduate 50 409.6 273.717 38.709 5 979 15 150 463 619 735 940 969.5 979 

Education < College 29 368.897 237.58 44.117 10 850 10 160 405 510 660 765 850 850 

Education College Graduate 22 405.682 184.225 39.277 90 815 150 240 375 540 595 645 815 815 

Education Post Graduate 13 443.692 218.128 60.498 10 793 10 360 500 585 630 793 793 793 

Census Region Northeast 22 405.545 193.817 41.322 15 765 90 320 398 540 660 662 765 765 

Census Region Midwest 26 418.577 250.898 49.205 10 940 13 180 473 610 690 780 940 940 

Census Region South 58 379.707 233.179 30.618 5 979 10 150 420 540 619 810 815 979 

Census Region West 31 391.71 289.538 52.003 10 960 20 90 405 630 795 850 960 960 

Day Of Week Weekday 121 401.843 242.472 22.043 5 979 15 210 450 560 660 810 940 960 

Day Of Week Weekend 16 334.25 243.28 60.82 13 795 13 97.5 340 495 690 795 795 795 

Season Winter 42 390.81 241.456 37.257 10 960 30 175 405 550 660 765 960 960 

Season Spring 34 361.324 236.996 40.644 10 840 30 150 360 525 660 815 840 840 

Season Summer 41 400.902 262.9 41.058 5 979 13 210 450 570 690 810 979 979 

Season Fall 20 441.75 219.411 49.062 10 793 12.5 285 490 620 661 727.5 793 793 

Asthma No 124 393.218 237.29 21.309 5 960 20 180 440 553 660 795 850 940 

Asthma Yes 13 400.923 300.15 83.247 10 979 10 240 320 590 793 979 979 979 

Angina No 133 397.677 243.291 21.096 5 979 15 190 440 555 662 810 940 960 

Angina Yes 3 266.667 255.799 147.686 90 560 90 90 150 560 560 560 560 560 

Angina DK 1 280 * * 280 280 280 280 280 280 280 280 280 280 

Bronchitis/Emphysema No 131 397.13 242.048 21.148 5 979 20 180 440 555 662 810 940 960 

Bronchitis/Emphysema Yes 5 333.4 299.365 133.88 10 619 10 13 460 565 619 619 619 619 

Bronchitis/Emphysema DK 1 280 * * 280 280 280 280 280 280 280 280 280 280 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-99. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at the Dry Cleaners 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 34 82.029 151.651 26.008 2 515 5 5 10 90 325 500 515 515 

Gender Male 11 105.545 166.006 50.053 2 515 2 5 10 103 325 515 515 515 

Gender Female 23 70.783 146.839 30.618 5 500 5 5 10 35 300 485 500 500 

Age (years) * 1 485 * * 485 485 485 485 485 485 485 485 485 485 

Age (years) 1-4 2 20 21.213 15 5 35 5 5 20 35 35 35 35 35 

Age (years) 18-64 28 61.036 120.923 22.852 2 515 5 5 10 55 300 325 515 515 

Age (years) > 64 3 185 273.359 157.824 10 500 10 10 45 500 500 500 500 500 

Race White 25 70.72 143.744 28.749 2 515 5 5 10 35 300 485 515 515 

Race Black 7 131.429 198.95 75.196 5 500 5 10 20 325 500 500 500 500 

Race Some Others 1 10 * * 10 10 10 10 10 10 10 10 10 10 

Race Hispanic 1 91 * * 91 91 91 91 91 91 91 91 91 91 

Hispanic No 31 83.806 158.483 28.464 2 515 5 5 10 45 325 500 515 515 

Hispanic Yes 3 63.667 46.479 26.835 10 91 10 10 90 91 91 91 91 91 

Employment * 2 20 21.213 15 5 35 5 5 20 35 35 35 35 35 

Employment Full Time 25 83.12 151.81 30.362 2 515 5 5 10 90 325 485 515 515 

Employment Part Time 1 500 * * 500 500 500 500 500 500 500 500 500 500 

Employment Not Employed 6 28.5 33.934 13.853 5 91 5 10 10 45 91 91 91 91 

Education * 2 20 21.213 15 5 35 5 5 20 35 35 35 35 35 

Education < High School 4 234 209.191 104.595 45 500 45 68 196 400 500 500 500 500 

Education High School Graduate 8 84.125 165.008 58.339 5 485 5 13 17.5 62 485 485 485 485 

Education < College 6 146.333 220.347 89.956 5 515 5 10 11.5 325 515 515 515 515 

Education College Graduate 12 13.5 24.247 6.999 2 90 2 5 5 10 10 90 90 90 

Education Post Graduate 2 50 63.64 45 5 95 5 5 50 95 95 95 95 95 

Census Region Northeast 8 110 187.293 66.218 5 485 5 5 10 180 485 485 485 485 

Census Region Midwest 10 19.1 30.101 9.519 5 103 5 5 7.5 20 61.5 103 103 103 

Census Region South 8 197 211.975 74.945 15 515 15 30 93 400 515 515 515 515 

Census Region West 8 17.75 29.359 10.38 2 90 2 5 10 10 90 90 90 90 

Day Of Week Weekday 23 93.957 172.77 36.025 2 515 5 5 10 90 485 500 515 515 

Day Of Week Weekend 11 57.091 95.985 28.941 5 325 5 5 10 95 103 325 325 325 

Season Winter 12 74.583 158.092 45.637 5 485 5 5 10 13 325 485 485 485 

Season Spring 4 44.5 41.685 20.843 10 103 10 15 32.5 74 103 103 103 103 

Season Summer 8 20.25 32.012 11.318 2 95 2 5 5 23 95 95 95 95 

Season Fall 10 155.4 205.739 65.061 5 515 5 13 55 300 507.5 515 515 515 

Asthma No 32 86.688 155.244 27.443 2 515 5 5 11.5 91 325 500 515 515 

Asthma Yes 2 7.5 3.536 2.5 5 10 5 5 7.5 10 10 10 10 10 

Angina No 33 83.909 153.599 26.738 2 515 5 5 10 90 325 500 515 515 

Angina Yes 1 20 * * 20 20 20 20 20 20 20 20 20 20 

Bronchitis/Emphysema No 33 84.061 153.532 26.726 2 515 5 5 10 90 325 500 515 515 

Bronchitis/Emphysema Yes 1 15 * * 15 15 15 15 15 15 15 15 15 15 

Note: A "*" Signifies missing data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. 

Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or

equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-100. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Bar/Nightclub/Bowling Alley 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 352 175.818 132.206 7.047 3 870 30 90 150 222.5 328 487 570 615 

Gender Male 213 174.319 133.151 9.123 5 870 30 90 140 220 340 479 568 615 

Gender Female 139 178.115 131.191 11.127 3 630 30 95 150 225 300 530 600 605 

Age (years) * 4 158.75 98.011 49.006 75 300 75 98 130 220 300 300 300 300 

Age (years) 5-11 4 98.75 57.5 28.75 45 170 45 53 90 145 170 170 170 170 

Age (years) 12-17 8 151.25 77.678 27.463 50 270 50 80 160 205 270 270 270 270 

Age (years) 18-64 313 180.192 136.706 7.727 3 870 30 90 150 225 370 498 590 615 

Age (years) > 64 23 141.217 85.243 17.774 5 328 30 75 135 180 240 325 328 328 

Race White 297 173.623 132.592 7.694 3 870 30 90 140 220 328 487 590 630 

Race Black 25 205.44 126.551 25.31 50 540 60 120 180 240 417 498 540 540 

Race Asian 8 169.875 153.311 54.204 5 479 5 38 175 225 479 479 479 479 

Race Some Others 7 197.286 187.607 70.909 70 615 70 110 135 185 615 615 615 615 

Race Hispanic 10 121.3 52.326 16.547 5 198 5 105 117.5 160 179 198 198 198 

Race Refused 5 246.6 127.153 56.864 73 410 73 180 270 300 410 410 410 410 

Hispanic No 327 177.131 134.457 7.435 3 870 30 90 150 225 340 489 590 615 

Hispanic Yes 20 144.9 85.08 19.024 5 440 38 110 120 160 221.5 342.5 440 440 

Hispanic DK 2 142.5 31.82 22.5 120 165 120 120 142.5 165 165 165 165 165 

Hispanic Refused 3 261 171.852 99.219 73 410 73 73 300 410 410 410 410 410 

Employment * 12 133.75 73.55 21.232 45 270 45 60 135 177.5 225 270 270 270 

Employment Full Time 223 182.439 138.308 9.262 5 870 30 90 150 228 340 525 600 630 

Employment Part Time 43 201.233 155.454 23.706 5 615 45 90 150 270 455 520 615 615 

Employment Not Employed 70 146.3 97.375 11.639 3 479 30 73 122.5 180 255 328 462 479 

Employment Refused 4 176.25 115.136 57.568 45 300 45 83 180 270 300 300 300 300 

Education * 13 146.538 84.172 23.345 45 300 45 60 150 185 270 300 300 300 

Education < High School 28 218.036 170.225 32.17 60 870 75 120 174.5 235 420 568 870 870 

Education High School Graduate 117 177.778 130.078 12.026 3 630 25 90 150 225 360 489 540 570 

Education < College 95 205.274 152.829 15.68 5 650 30 105 180 240 462 590 615 650 

Education College Graduate 55 141.764 92.766 12.509 10 417 20 75 120 205 265 340 410 417 

Education Post Graduate 44 131.364 90.209 13.599 30 400 30 60 110 177.5 265 290 400 400 

Census Region Northeast 83 179.337 137.039 15.042 5 650 45 89 140 240 328 489 630 650 

Census Region Midwest 88 169.818 126.238 13.457 5 615 30 90 147.5 211.5 299 487 568 615 

Census Region South 91 175.714 132.028 13.84 3 870 35 90 148 225 270 462 570 870 

Census Region West 90 178.544 135.533 14.286 5 605 30 85 152.5 225 407 479 590 605 

Day Of Week Weekday 192 167.458 133.473 9.633 5 650 30 80 120 210 340 520 590 605 

Day Of Week Weekend 160 185.85 130.378 10.307 3 870 45 108 165 228 321.5 474.5 568 630 

Season Winter 93 182.667 131.674 13.654 5 650 40 87 150 240 410 455 560 650 

Season Spring 83 186.12 147.597 16.201 5 870 30 90 140 230 380 498 570 870 

Season Summer 99 160.313 130.672 13.133 3 630 30 75 120 189 285 530 605 630 

Season Fall 77 176.377 117.154 13.351 15 615 30 100 165 220 299 410 600 615 

Asthma No 331 176.308 133.715 7.35 3 870 30 90 150 225 340 487 590 615 

Asthma Yes 18 169.444 108.978 25.686 60 530 60 105 135 210 270 530 530 530 

Asthma DK 3 160 124.9 72.111 60 300 60 60 120 300 300 300 300 300 

Angina No 345 176.98 132.759 7.148 3 870 30 90 150 225 340 487 590 615 

Angina Yes 5 82 47.249 21.131 5 120 5 75 90 120 120 120 120 120 

Angina DK 2 210 127.279 90 120 300 120 120 210 300 300 300 300 300 

Bronchitis/Emphysema No 333 177.273 133.27 7.303 3 870 30 90 150 225 340 487 590 615 

Bronchitis/Emphysema Yes 17 148.588 108.499 26.315 50 530 50 110 120 175 210 530 530 530 

Bronchitis/Emphysema DK 2 165 190.919 135 30 300 30 30 165 300 300 300 300 300 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-101. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Restaurant 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 2059 94.539 119.93 2.643 1 925 10 30 60 95 185 351 548 660 

Gender Male 986 87.498 114.17 3.6358 1 900 10 30 60 90 160 305 550 660 

Gender Female 1073 101.01 124.69 3.8065 1 925 10 40 60 105 230 380 540 670 

Age (years) * 30 126.13 138.22 25.2349 15 495 30 45 60 150 397.5 490 495 495 

Age (years) 1-4 61 62.705 47.701 6.1075 4 330 10 35 55 85 115 120 130 330 

Age (years) 5-11 84 56.69 38.144 4.1618 5 180 10 30 45 85 120 120 140 180 

Age (years) 12-17 122 69.836 78.361 7.0945 2 455 10 30 45 65 165 250 325 360 

Age (years) 18-64 1503 101.21 131.22 3.3846 1 925 10 30 60 105 211 400 570 675 

Age (years) > 64 259 83.583 83.517 5.1895 3 750 19 45 60 90 150 215 315 520 

Race White 1747 91.658 114.69 2.744 1 925 10 30 60 95 175 320 535 640 

Race Black 148 102.82 141.28 11.613 3 805 5 30 60 95 295 430 555 735 

Race Asian 37 81.297 78.948 12.979 15 480 18 30 60 90 135 200 480 480 

Race Some Others 30 145.17 194.83 35.5705 5 765 10 45 82.5 120 432.5 750 765 765 

Race Hispanic 78 123 156.78 17.7518 10 700 15 40 60 110 375 585 660 700 

Race Refused 19 123.84 127.64 29.2833 20 480 20 30 70 210 330 480 480 480 

Hispanic No 1911 92.945 117.6 2.6901 1 925 10 30 60 95 180 330 542 645 

Hispanic Yes 129 116.7 147.95 13.0261 1 765 15 40 60 115 360 435 660 700 

Hispanic DK 5 76 134.32 60.0708 5 315 5 10 10 40 315 315 315 315 

Hispanic Refused 14 114.5 134.74 36.0117 30 480 30 30 60 90 330 480 480 480 

Employment * 263 62.251 57.907 3.5707 2 455 10 30 45 80 120 140 273 330 

Employment Full Time 1063 105.48 142.37 4.3668 1 925 10 35 60 105 235 485 630 735 

Employment Part Time 208 122.61 144.83 10.0423 1 805 5 32.5 65 122.5 320 441 595 660 

Employment Not Employed 515 76.33 61.418 2.7064 3 490 15 40 60 90 145 195 260 315 

Employment Refused 10 135 133.52 42.223 30 425 30 60 82.5 135 377.5 425 425 425 

Education * 299 72.177 79.595 4.6031 1 548 10 30 50 85 130 250 360 480 

Education < High School 132 134.77 171.84 14.9567 5 925 10 30 60 151.5 375 535 700 750 

Education High School Graduate 590 99.439 136.32 5.612 3 910 10 35 60 90 202.5 435 645 680 

Education < College 431 94.935 114.88 5.5338 1 770 10 35 60 105 180 340 550 640 

Education College Graduate 359 89.515 104.13 5.4957 1 765 10 35 60 100 165 295 490 570 

Education Post Graduate 248 95.012 109.37 6.9452 3 765 15 40 60 115 180 260 560 675 

Census Region Northeast 409 94.379 113.64 5.619 2 765 15 35 60 100 210 330 507 585 

Census Region Midwest 504 96.895 120.86 5.3833 1 805 10 30 60 105 190 340 560 675 

Census Region South 680 92.666 125.1 4.7972 2 910 10 30 60 90 194.5 365 550 650 

Census Region West 466 94.863 116.88 5.4145 1 925 10 30 60 110 175 375 535 640 

Day Of Week Weekday 1291 97.338 128.83 3.5855 1 925 10 30 60 93 210 377 555 700 

Day Of Week Weekend 768 89.833 103.16 3.7224 1 770 10 36 60 105 155 280 510 620 

Season Winter 524 97.735 125.69 5.491 3 875 15 35 60 105 178 351 595 685 

Season Spring 559 91.642 109.7 4.6399 2 925 10 35 60 95 180 360 505 555 

Season Summer 556 95.121 123.03 5.2177 1 910 10 30 60 94 210 360 555 675 

Season Fall 420 93.636 121.74 5.9401 1 900 10 30 60 95 185 325 540 653 

Asthma No 1903 94.081 117.41 2.6915 1 910 10 35 60 100 180 330 545 653 

Asthma Yes 150 96.267 143.56 11.7219 4 925 10 30 45.5 90 237.5 485 590 670 

Asthma DK 6 196.33 220.89 90.1782 30 480 30 30 79 480 480 480 480 480 

Angina No 1998 94.926 120.73 2.701 1 925 10 30 60 100 190 355 550 660 

Angina Yes 50 68.98 53.608 7.5813 3 340 15 45 60 90 105 120 286 340 

Angina DK 11 140.27 171.27 51.6393 30 480 30 30 70 120 480 480 480 480 

Bronchitis/Emphysema No 1945 93.746 117.67 2.668 1 910 10 30 60 97 180 335 548 653 

Bronchitis/Emphysema Yes 104 96.077 130.13 12.7602 5 925 15 30 60 90 235 360 500 620 

Bronchitis/Emphysema DK 10 232.8 288.24 91.1492 10 875 10 30 79 480 677.5 875 875 875 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-102. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at School 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1224 343.35 179.099 5.119 1 995 10 210 395 454 540 585 660 723 

Gender Male 581 358.599 167.7 6.957 1 995 30 255 400 450 540 600 690 778 

Gender Female 643 329.572 187.875 7.409 1 855 5 180 390 455 540 582 640 683 

Age (years) * 18 314.056 230.927 54.43 5 713 5 165 247.5 520 625 713 713 713 

Age (years) 1-4 43 288.465 217.621 33.187 5 665 10 60 269 500 580 595 665 665 

Age (years) 5-11 302 396.308 109.216 6.285 5 665 170 365 403 445 535 565 625 640 

Age (years) 12-17 287 402.551 125.512 7.409 15 855 120 383 420 450 500 565 710 778 

Age (years) 18-64 550 295.422 207.294 8.839 1 995 5 104 300 460 552.5 612 683 785 

Age (years) > 64 24 187.708 187.012 38.174 2 585 3 45 120 327.5 480 510 585 585 

Race White 928 348.525 180.458 5.924 1 995 10 212.5 400 458 545 600 665 723 

Race Black 131 339.809 169.282 14.79 2 855 15 230 390 445 510 580 624 645 

Race Asian 39 332.385 179.918 28.81 5 840 20 190 365 450 560 580 840 840 

Race Some Others 36 363.583 155.557 25.926 10 820 105 272.5 366 457.5 502 598 820 820 

Race Hispanic 76 294.039 175.697 20.154 2 565 10 142.5 362.5 432 495 525 540 565 

Race Refused 14 279.714 221.268 59.136 5 681 5 60 260 440 625 681 681 681 

Hispanic No 1082 344.924 179.58 5.459 1 995 10 210 395 455 540 598 665 730 

Hispanic Yes 127 333.016 173.803 15.423 2 820 15 200 390 445 500 565 600 630 

Hispanic DK 5 293 244.672 109.42 3 562 3 65 415 420 562 562 562 562 

Hispanic Refused 10 329.5 180.053 56.938 5 625 5 200 350 445 537.5 625 625 625 

Employment * 616 390.294 130.206 5.246 5 855 115 365 410 450 525 570 640 665 

Employment Full Time 275 331.269 222.021 13.388 1 995 5 115 405 510 575 625 690 755 

Employment Part Time 138 280.891 174.844 14.884 1 800 10 160 285 412 480 537 660 683 

Employment Not Employed 190 258.674 199.529 14.475 1 855 5 60 262.5 410 527.5 572 778 840 

Employment Refused 5 166 179.074 80.084 5 440 5 5 180 200 440 440 440 440 

Education * 679 388.943 132.842 5.098 5 855 100 360 410 450 525 580 640 710 

Education < High School 24 233.333 179.648 36.67 1 540 2 30 297.5 373.5 460 465 540 540 

Education High School Graduate 114 186.649 193.608 18.133 1 785 4 20 107.5 295 480 580 645 690 

Education < College 173 281.41 209.872 15.956 1 995 5 120 255 425 550 640 820 855 

Education College Graduate 93 300.43 208.704 21.642 1 755 5 115 320 470 540 580 730 755 

Education Post Graduate 141 373.525 193.443 16.291 1 683 15 250 442 510 575 615 655 680 

Census Region Northeast 261 345.724 181.522 11.236 1 995 11 210 385 455 535 620 710 855 

Census Region Midwest 290 334.445 176.652 10.373 1 730 10 180 390 440 530 585 645 683 

Census Region South 427 354.037 178.547 8.641 1 855 10 235 415 462 540 575 640 755 

Census Region West 246 332.78 180.277 11.494 1 820 15 195 377.5 440 555 595 681 713 

Day Of Week Weekday 1179 346.838 177.477 5.169 1 995 10 222 395 455 540 585 655 723 

Day Of Week Weekend 45 251.978 198.543 29.597 20 820 40 105 180 360 555 632 820 820 

Season Winter 392 369.298 164.363 8.302 1 855 20 285 405 457 545 600 680 710 

Season Spring 353 355.057 165.488 8.808 1 855 12 250 400 455 535 575 636 713 

Season Summer 207 316.763 196.364 13.648 2 995 10 125 365 445 557 585 640 723 

Season Fall 272 310.996 195.332 11.844 1 855 5 120 365 445 540 595 660 778 

Asthma No 1095 342.779 179.195 5.415 1 995 10 200 390 455 540 585 660 723 

Asthma Yes 124 350.669 178.785 16.055 1 855 10 250 401.5 445 535 605 645 800 

Asthma DK 5 287 190.676 85.273 5 445 5 180 365 440 445 445 445 445 

Angina No 1209 344.629 178.874 5.144 1 995 10 210 395 455 540 595 660 723 

Angina Yes 9 205.778 169.545 56.515 15 510 15 90 180 275 510 510 510 510 

Angina DK 6 292.167 178.908 73.039 5 480 5 180 324 440 480 480 480 480 

Bronchitis/Emphysema No 1175 344.826 178.845 5.217 1 995 10 212 395 455 540 595 660 730 

Bronchitis/Emphysema Yes 42 306.714 188.249 29.047 3 632 10 120 377.5 444 465 580 632 632 

Bronchitis/Emphysema DK 7 315.429 163.691 61.869 5 440 5 180 378 440 440 440 440 440 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-103. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Plant/Factory/Warehouse 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 383 450.896 204.367 10.443 2 997 30 350 510 568 670 705 770 855 

Gender Male 271 460.458 205.102 12.459 2 997 30 365 515 575 675 720 780 870 

Gender Female 112 427.759 201.609 19.05 5 820 15 314.5 510 555 600 675 705 720 

Age (years) * 6 405.667 304.05 124.13 30 780 30 120 414.5 675 780 780 780 780 

Age (years) 1-4 1 20 * * 20 20 20 20 20 20 20 20 20 20 

Age (years) 5-11 2 107.5 123.744 87.5 20 195 20 20 107.5 195 195 195 195 195 

Age (years) 12-17 4 108 136.404 68.202 10 307 10 20 57.5 196 307 307 307 307 

Age (years) 18-64 353 463.683 196.321 10.449 5 997 30 385 520 570 670 705 770 855 

Age (years) > 64 17 347.765 210.909 51.153 2 705 2 180 450 495 550 705 705 705 

Race White 322 451.789 201.135 11.209 5 890 30 355 517.5 568 650 690 770 840 

Race Black 32 466.438 172.559 30.504 2 750 30 382.5 497.5 550 675 720 750 750 

Race Asian 3 263.333 378.462 218.51 30 700 30 30 60 700 700 700 700 700 

Race Some Others 6 585.333 156.91 64.058 310 780 310 565 591 675 780 780 780 780 

Race Hispanic 15 385.8 231.348 59.734 5 765 5 230 435 515 760 765 765 765 

Race Refused 5 440.4 387.419 173.26 30 997 30 115 520 540 997 997 997 997 

Hispanic No 350 454.137 202.78 10.839 2 997 30 365 512.5 570 666.5 700 770 855 

Hispanic Yes 26 419.615 213.155 41.803 5 765 15 240 482.5 550 675 760 765 765 

Hispanic DK 2 425 162.635 115 310 540 310 310 425 540 540 540 540 540 

Hispanic Refused 5 397 314.833 140.8 30 780 30 115 520 540 780 780 780 780 

Employment * 7 95.286 113.83 43.024 10 307 10 20 30 195 307 307 307 307 

Employment Full Time 333 481.417 185.222 10.15 5 997 50 440 525 580 675 720 780 855 

Employment Part Time 23 359.87 170.619 35.577 40 585 45 240 390 505 527 535 585 585 

Employment Not Employed 19 179.316 221.341 50.779 2 705 2 25 60 295 640 705 705 705 

Employment Refused 1 30 * * 30 30 30 30 30 30 30 30 30 30 

Education * 13 184 234.182 64.95 10 780 10 20 85 270 510 780 780 780 

Education < High School 38 491.237 195.919 31.782 2 855 5 435 525 600 705 765 855 855 

Education High School Graduate 190 465.374 188.699 13.69 5 997 30 380 520 565 667.5 705 760 890 

Education < College 85 450.494 199.674 21.658 15 870 40 375 510 565 635 680 820 870 

Education College Graduate 43 463.163 206.51 31.492 5 840 60 405 520 600 670 690 840 840 

Education Post Graduate 14 357.5 255.702 68.339 10 700 10 90 355 550 675 700 700 700 

Census Region Northeast 71 449.423 207.98 24.683 5 890 15 300 510 565 675 725 780 890 

Census Region Midwest 113 462.035 196.506 18.486 2 997 30 405 520 570 640 700 770 820 

Census Region South 136 465.912 199.315 17.091 5 870 20 382 522.5 570 670 720 840 855 

Census Region West 63 400.159 221.13 27.86 10 760 30 185 490 550 675 690 710 760 

Day Of Week Weekday 319 476.445 190.875 10.687 5 997 30 435 525 580 675 710 770 855 

Day Of Week Weekend 64 323.547 222.63 27.829 2 820 10 107.5 357.5 507.5 560 620 780 820 

Season Winter 89 468.157 188.472 19.978 10 997 30 360 520 565 660 690 780 997 

Season Spring 91 445.198 212.648 22.292 10 870 30 270 505 570 675 760 840 870 

Season Summer 127 440.646 210.285 18.66 2 890 15 370 510 560 645 700 765 855 

Season Fall 76 454.632 204.721 23.483 5 760 30 352.5 520 591 675 690 720 760 

Asthma No 364 452.948 203.838 10.684 2 997 30 355 512.5 570 675 705 770 855 

Asthma Yes 17 412.353 187.025 45.36 20 580 20 340 495 540 550 580 580 580 

Asthma DK 2 405 530.33 375 30 780 30 30 405 780 780 780 780 780 

Angina No 375 453.928 202.31 10.447 2 997 30 360 515 570 670 705 770 855 

Angina Yes 5 231 168.389 75.306 60 475 60 90 230 300 475 475 475 475 

Angina DK 3 438.333 379.418 219.06 30 780 30 30 505 780 780 780 780 780 

Bronchitis/Emphysema No 362 450.235 204.588 10.753 2 997 30 350 510 565 663 700 770 855 

Bronchitis/Emphysema Yes 19 468.316 175.293 40.215 50 720 50 375 510 568 690 720 720 720 

Bronchitis/Emphysema DK 2 405 530.33 375 30 780 30 30 405 780 780 780 780 780 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-104. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on a Sidewalk, Street, or in the Neighborhood 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 896 85.785 133.828 4.4709 1 1440 2 15 40 90 223 405 565 615 

Gender Male 409 108.775 168.11 8.3125 1 1440 3 20 45 120 330 525 615 710 

Gender Female 487 66.476 91.863 4.1627 1 580 1 15 35 75 152 255 435 465 

Age (years) * 15 72.533 69.418 17.9236 1 290 1 40 55 90 120 290 290 290 

Age (years) 1-4 30 54.8 52.731 9.6274 1 235 2 10 42.5 78 125 158 235 235 

Age (years) 5-11 75 110.813 116.76 13.4823 1 540 5 20 65 178 240 410 465 540 

Age (years) 12-17 74 52.554 74.776 8.6925 1 435 2 15 30 60 125 200 338 435 

Age (years) 18-64 580 94.279 153.933 6.3917 1 1440 2 15 40 82.5 277.5 480 600 690 

Age (years) > 64 122 59.418 61.519 5.5696 1 380 2 20 40 75 120 190 235 270 

Race White 727 85.735 136.504 5.0627 1 1440 2 15 41 90 215 405 570 675 

Race Black 87 89.184 132.669 14.2236 1 565 2 10 35 120 324 426 540 565 

Race Asian 11 88.727 114.01 34.3752 2 405 2 30 45 120 149 405 405 405 

Race Some Others 18 80.556 105.981 24.98 10 420 10 20 40 75 240 420 420 420 

Race Hispanic 42 71.357 110.769 17.092 1 525 1 20 40 75 135 290 525 525 

Race Refused 11 122.909 117.699 35.4876 2 310 2 40 60 290 300 310 310 310 

Hispanic No 807 87.482 136.129 4.792 1 1440 2 15 45 90 225 410 565 600 

Hispanic Yes 79 67.797 110.301 12.4098 1 615 1 15 30 62 140 300 525 615 

Hispanic DK 1 2 * * 2 2 2 2 2 2 2 2 2 2 

Hispanic Refused 9 100.778 115.933 38.6443 2 310 2 40 60 90 310 310 310 310 

Employment * 176 79.182 96.345 7.2622 1 540 2 15 45 110 200 260 435 465 

Employment Full Time 384 102.221 169.534 8.6515 1 1440 3 15 40.5 75 330 525 600 710 

Employment Part Time 74 74.446 113.86 13.2359 1 795 1 15 42.5 86 180 255 390 795 

Employment Not Employed 255 69.996 94.045 5.8893 1 615 1 15 40 85 152 270 380 485 

Employment Refused 7 45.143 36.64 13.8485 2 90 2 4 40 90 90 90 90 90 

Education * 198 74.914 92.253 6.5561 1 540 2 15 40.5 90 185 240 435 465 

Education < High School 56 131.232 247.289 33.0454 1 1440 1 15 40 118 465 710 735 1440 

Education High School Graduate 223 100.233 146.92 9.8385 1 795 5 20 45 95 275 480 600 680 

Education < College 172 77.186 128.752 9.8173 1 675 1 10 30 75 180 435 570 600 

Education College Graduate 138 76.275 106.589 9.0734 1 600 3 20 45 70 205 310 485 565 

Education Post Graduate 109 78.229 121.311 11.6195 1 710 5 20 45 60 200 330 560 570 

Census Region Northeast 202 89.134 132.343 9.3116 1 735 3 15 45 90 235 410 530 570 

Census Region Midwest 193 87.855 153.329 11.0369 1 1440 2 15 30 85 240 355 565 600 

Census Region South 298 79.943 125.46 7.2677 1 710 2 15 35 75 185 420 532 680 

Census Region West 203 89.059 127.909 8.9775 1 795 1 20 45 105 210 300 570 615 

Day Of Week Weekday 642 86.684 143.938 5.6808 1 1440 2 15 40 80 223 426 585 680 

Day Of Week Weekend 254 83.512 104.207 6.5385 1 565 2 25 45 90 220 310 440 480 

Season Winter 210 73.548 144.308 9.9582 1 1440 1 15 33 60 160 270 560 710 

Season Spring 242 97.913 137.243 8.8223 1 795 4 25 45 120 240 435 570 675 

Season Summer 276 83.989 123.086 7.4089 1 690 4 15 45 90 200 420 525 580 

Season Fall 168 86.56 131.855 10.1729 1 710 2 15 40 90 240 405 600 615 

Asthma No 832 86.108 129.455 4.488 1 795 2 15 40 90 225 418 565 600 

Asthma Yes 57 85.596 193.133 25.5811 1 1440 1 15 35 90 180 235 260 1440 

Asthma DK 7 48.857 27.973 10.5727 2 90 2 30 60 60 90 90 90 90 

Angina No 857 86.177 134.897 4.608 1 1440 2 15 40 90 223 410 565 615 

Angina Yes 33 81.727 117.393 20.4356 1 465 1 17 45 60 250 380 465 465 

Angina DK 6 52 29.257 11.9443 2 90 2 40 60 60 90 90 90 90 

Bronchitis/Emphysema No 855 84.837 132.316 4.5251 1 1440 2 15 40 85 225 405 560 600 

Bronchitis/Emphysema Yes 34 117.735 176.429 30.2574 3 735 8 30 45 120 215 690 735 735 

Bronchitis/Emphysema DK 7 46.286 27.482 10.3871 2 90 2 32 40 60 90 90 90 90 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-105. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors in a Parking Lot 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 226 70.721 126.651 8.425 1 910 2 10 20 60 190 309 510 580 

Gender Male 106 100.34 167.159 16.236 1 910 5 15 30 110 315 495 580 720 

Gender Female 120 44.558 64.826 5.918 1 295 1 5 20 46.5 167.5 187.5 248 285 

Age (years) * 3 135 195 112.58 15 360 15 15 30 360 360 360 360 360 

Age (years) 1-4 11 39.818 38.449 11.593 5 110 5 10 20 90 90 110 110 110 

Age (years) 5-11 5 62 63.699 28.487 5 170 5 30 45 60 170 170 170 170 

Age (years) 12-17 12 93.75 90.81 26.214 5 248 5 17.5 52 163 238 248 248 248 

Age (years) 18-64 182 69.984 132.655 9.833 1 910 2 10 20 60 190 309 550 720 

Age (years) > 64 13 74.462 127.9 35.473 1 465 1 10 25 60 180 465 465 465 

Race White 180 72.122 128.299 9.563 1 910 2 10 20.5 64 205 302 510 720 

Race Black 18 102.444 167.776 39.545 2 580 2 6 27.5 130 495 580 580 580 

Race Asian 3 21.667 7.638 4.41 15 30 15 15 20 30 30 30 30 30 

Race Some Others 5 50 46.098 20.616 5 115 5 10 45 75 115 115 115 115 

Race Hispanic 17 25.706 39.365 9.547 1 165 1 10 10 20 60 165 165 165 

Race Refused 3 135 195 112.58 15 360 15 15 30 360 360 360 360 360 

Hispanic No 196 69.26 114.078 8.148 1 720 2 10 24 67.5 190 295 495 580 

Hispanic Yes 25 42.92 103.34 20.668 1 510 1 5 10 20 75 165 510 510 

Hispanic DK 2 465 629.325 445 20 910 20 20 465 910 910 910 910 910 

Hispanic Refused 3 135 195 112.58 15 360 15 15 30 360 360 360 360 360 

Employment * 26 55.577 59.88 11.743 5 238 5 15 30 90 145 170 238 238 

Employment Full Time 117 83.325 155.119 14.341 1 910 2 10 20 60 240 495 580 720 

Employment Part Time 37 75.378 114.734 18.862 1 465 1 5 21 90 180 450 465 465 

Employment Not Employed 43 37.093 46.8 7.137 1 210 1 10 20 60 90 134 210 210 

Employment Refused 3 135 195 112.58 15 360 15 15 30 360 360 360 360 360 

Education * 33 69.697 85.644 14.909 1 360 5 15 30 90 180 248 360 360 

Education < High School 16 73.25 176.778 44.194 2 720 2 7.5 22.5 32.5 165 720 720 720 

Education High School Graduate 83 83 124.358 13.65 1 580 5 10 25 90 215 315 495 580 

Education < College 49 75.898 162.674 23.239 1 910 2 10 20 60 210 450 910 910 

Education College Graduate 23 48.783 107.169 22.346 1 510 2 5 10 30 130 135 510 510 

Education Post Graduate 22 35.5 54.472 11.613 1 185 1 5 15 30 115 180 185 185 

Census Region Northeast 56 57.357 82.622 11.041 1 495 1 12.5 27.5 75 135 180 295 495 

Census Region Midwest 48 73.438 118.574 17.115 1 550 5 10 25 62.5 248 315 550 550 

Census Region South 75 57.92 106.421 12.288 1 720 2 7 20 50 185 238 360 720 

Census Region West 47 104.298 189.916 27.702 3 910 5 10 20 90 450 510 910 910 

Day Of Week Weekday 154 64.851 136.686 11.014 1 910 2 7 20 43 180 450 550 720 

Day Of Week Weekend 72 83.278 101.675 11.982 1 465 5 15 35 113 240 309 360 465 

Season Winter 45 50.533 64.702 9.645 2 309 5 15 30 63 130 180 309 309 

Season Spring 57 82.912 131.245 17.384 1 495 1 10 20 90 240 465 495 495 

Season Summer 75 72.027 146.21 16.883 1 910 2 10 20 60 205 315 580 910 

Season Fall 49 73.082 133.165 19.024 1 720 1 10 20 75 205 295 720 720 

Asthma No 204 62.98 109.369 7.657 1 720 2 10 20 60 180 248 495 510 

Asthma Yes 18 149.722 238.456 56.205 1 910 1 15 45 145 580 910 910 910 

Asthma DK 4 110 166.883 83.442 15 360 15 22.5 32.5 198 360 360 360 360 

Angina No 217 69.263 127.076 8.626 1 910 2 10 20 60 185 309 510 580 

Angina Yes 5 99.6 83.056 37.144 35 238 35 40 75 110 238 238 238 238 

Angina DK 4 113.75 164.792 82.396 15 360 15 22.5 40 205 360 360 360 360 

Bronchitis/Emphysema No 211 65.555 114.21 7.863 1 720 2 10 20 60 180 295 495 550 

Bronchitis/Emphysema Yes 11 142.364 265.976 80.195 1 910 1 10 40 180 240 910 910 910 

Bronchitis/Emphysema DK 4 146.25 160.799 80.399 15 360 15 22.5 105 270 360 360 360 360 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-106. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Service Station or Gas Station 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 191 50.597 125.489 9.0801 1 790 5 5 10 20 105 365 570 645 

Gender Male 90 73.522 149.969 15.8082 1 645 5 5 10 30 325 495 600 645 

Gender Female 101 30.168 94.915 9.4444 2 790 5 5 10 15 44 105 180 510 

Age (years) * 1 86 * * 86 86 86 86 86 86 86 86 86 86 

Age (years) 1-4 3 6.667 2.887 1.6667 5 10 5 5 5 10 10 10 10 10 

Age (years) 5-11 3 66.667 98.277 56.7401 5 180 5 5 15 180 180 180 180 180 

Age (years) 12-17 11 7.818 4.513 1.3606 1 15 1 5 5 10 15 15 15 15 

Age (years) 18-64 157 54.185 135.636 10.8249 2 790 5 5 10 15 110 390 570 645 

Age (years) > 64 16 47.813 69.497 17.3744 5 240 5 10 18 55 180 240 240 240 

Race White 170 50.941 124.015 9.5115 2 790 5 5 10 20 107.5 365 520 600 

Race Black 11 80.727 191.433 57.7192 4 645 4 5 5 44 140 645 645 645 

Race Asian 1 5 * * 5 5 5 5 5 5 5 5 5 5 

Race Some Others 3 16.667 20.207 11.6667 5 40 5 5 5 40 40 40 40 40 

Race Hispanic 5 10.2 7.596 3.3971 1 20 1 5 10 15 20 20 20 20 

Race Refused 1 10 * * 10 10 10 10 10 10 10 10 10 10 

Hispanic No 179 53.056 129.15 9.6531 2 790 5 5 10 20 130 380 570 645 

Hispanic Yes 12 13.917 23.008 6.6418 1 86 1 5 7.5 10 15 86 86 86 

Employment * 16 18.813 43.196 10.799 1 180 1 5 7.5 12.5 15 180 180 180 

Employment Full Time 110 55.827 136.782 13.0417 2 645 5 5 10 15 99 495 570 600 

Employment Part Time 26 34.731 71.829 14.0868 3 355 5 5 10 25 100 130 355 355 

Employment Not Employed 38 40.237 76.973 12.4867 4 380 5 5 10 20 140 240 380 380 

Employment Refused 1 790 * * 790 790 790 790 790 790 790 790 790 790 

Education * 18 17.833 40.712 9.5958 1 180 1 5 7.5 15 15 180 180 180 

Education < High School 16 103 164.12 41.03 5 520 5 10 15 140 365 520 520 520 

Education High School Graduate 46 85.739 162.855 24.0116 3 645 5 5 10 85 380 495 645 645 

Education < College 58 41.759 121.08 15.8986 2 790 4 5 13 20 60 110 510 790 

Education College Graduate 30 36.633 111.641 20.3828 2 570 4 5 6.5 15 30 270 570 570 

Education Post Graduate 23 10 6.396 1.3337 5 30 5 5 10 10 20 20 30 30 

Census Region Northeast 33 59.697 149.173 25.9677 2 600 3 5 10 20 105 570 600 600 

Census Region Midwest 48 28.563 77.552 11.1936 2 510 5 5 10 15 60 110 510 510 

Census Region South 68 49.882 133.967 16.2459 1 790 5 5 10 15 130 295 645 790 

Census Region West 42 69.786 135.545 20.9151 4 520 5 5 13 40 270 390 520 520 

Day Of Week Weekday 122 58.402 145.085 13.1354 2 790 5 5 10 20 130 495 600 645 

Day Of Week Weekend 69 36.797 79.004 9.5109 1 390 4 5 10 15 88 240 380 390 

Season Winter 56 37.536 100.602 13.4435 2 600 4 5 10 15 60 270 355 600 

Season Spring 54 80.13 157.514 21.4349 1 645 5 5 10 60 380 510 570 645 

Season Summer 51 46.51 137.689 19.2804 2 790 5 5 10 15 35 365 520 790 

Season Fall 30 28.767 58.93 10.7591 3 295 5 5 8.5 15 93 130 295 295 

Asthma No 174 53.517 130.777 9.9141 1 790 5 5 10 20 130 380 570 645 

Asthma Yes 16 15.75 25.736 6.434 2 110 2 5 7.5 15 20 110 110 110 

Asthma DK 1 100 * * 100 100 100 100 100 100 100 100 100 100 

Angina No 184 46.788 120.622 8.8923 1 790 5 5 10 15 88 295 570 645 

Angina Yes 7 150.714 206.81 78.1667 10 510 10 15 20 380 510 510 510 510 

Bronchitis/Emphysema No 181 47.122 123.971 9.2147 1 790 5 5 10 15 85 295 570 645 

Bronchitis/Emphysema Yes 10 113.5 142.946 45.2036 5 380 5 10 58 140 367.5 380 380 380 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean

24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max =

maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-107. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Construction Site 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 143 437.098 242.073 20.243 1 1190 10 240 510 600 675 740 930 985 

Gender Male 130 461.531 232.511 20.393 1 1190 10 300 522.5 600 688.5 745 930 985 

Gender Female 13 192.769 202.794 56.245 5 630 5 60 135 165 535 630 630 630 

Age (years) * 1 510 * * 510 510 510 510 510 510 510 510 510 510 

Age (years) 1-4 2 240 254.558 180 60 420 60 60 240 420 420 420 420 420 

Age (years) 12-17 1 10 * * 10 10 10 10 10 10 10 10 10 10 

Age (years) 18-64 133 444.549 243.017 21.072 1 1190 10 240 520 600 687 745 930 985 

Age (years) > 64 6 396.667 188.75 77.057 60 560 60 300 460 540 560 560 560 560 

Race White 125 430.872 247.432 22.131 5 1190 10 240 510 600 687 740 930 985 

Race Black 10 430.1 233.307 73.778 1 630 1 170 550 585 615 630 630 630 

Race Some Others 2 492.5 60.104 42.5 450 535 450 450 492.5 535 535 535 535 535 

Race Hispanic 3 501.667 170.318 98.333 305 600 305 305 600 600 600 600 600 600 

Race Refused 3 618.333 166.458 96.105 510 810 510 510 535 810 810 810 810 810 

Hispanic No 129 426.202 247.087 21.755 1 1190 10 180 510 600 665 735 930 985 

Hispanic Yes 9 496.111 166.429 55.476 240 765 240 410 505 600 765 765 765 765 

Hispanic DK 2 577.5 180.312 127.5 450 705 450 450 577.5 705 705 705 705 705 

Hispanic Refused 3 635 156.125 90.139 510 810 510 510 585 810 810 810 810 810 

Employment * 3 163.333 223.681 129.142 10 420 10 10 60 420 420 420 420 420 

Employment Full Time 127 456.803 236.198 20.959 1 1190 15 285 520 605 690 745 930 985 

Employment Part Time 6 495.833 171.389 69.969 155 600 155 510 555 600 600 600 600 600 

Employment Not Employed 7 146.571 162.79 61.529 5 430 5 6 60 300 430 430 430 430 

Education * 4 250 251.794 125.897 10 510 10 35 240 465 510 510 510 510 

Education < High School 12 500.833 227.035 65.539 60 930 60 375 525 592.5 735 930 930 930 

Education High School Graduate 68 482.162 228.976 27.767 5 1190 20 395 522.5 592.5 720 780 985 1190 

Education < College 41 417.683 241.023 37.641 1 745 10 170 520 615 645 687 745 745 

Education College Graduate 14 372.357 247.278 66.088 15 660 15 120 440 585 643 660 660 660 

Education Post Graduate 4 92.5 137.265 68.632 5 295 5 7.5 35 177.5 295 295 295 295 

Census Region Northeast 28 481.714 238.306 45.036 5 985 6 357.5 532.5 650 695 740 985 985 

Census Region Midwest 30 343.967 231.025 42.179 5 810 10 120 342 525 637.5 660 810 810 

Census Region South 57 474.018 248.301 32.888 1 1190 10 410 535 615 720 765 780 1190 

Census Region West 28 417.107 226.287 42.764 15 930 60 235 500 570 630 656 930 930 

Day Of Week Weekday 121 455.116 238.494 21.681 5 1190 15 285 525 600 687 745 930 985 

Day Of Week Weekend 22 338 243.022 51.813 1 705 5 60 407.5 525 600 645 705 705 

Season Winter 34 418.5 268.44 46.037 1 1190 5 155 505 570 645 695 1190 1190 

Season Spring 33 412.242 223.533 38.912 10 810 60 230 490 570 635 740 810 810 

Season Summer 46 477.739 221.422 32.647 10 985 60 325 515 630 705 745 985 985 

Season Fall 30 423.2 264.183 48.233 5 930 6 135 532.5 585 700 780 930 930 

Asthma No 137 437.161 243.531 20.806 1 1190 10 240 510 600 675 745 930 985 

Asthma Yes 6 435.667 225.957 92.247 60 690 60 354 440 630 690 690 690 690 

Angina No 139 439.108 242.331 20.554 1 1190 10 240 510 600 687 745 930 985 

Angina Yes 4 367.25 256.288 128.144 10 570 10 182 444.5 552.5 570 570 570 570 

Bronchitis/Emphysema No 140 433.257 240.003 20.284 1 1190 10 240 510 600 670 737.5 810 930 

Bronchitis/Emphysema Yes 3 616.333 328.664 189.755 354 985 354 354 510 985 985 985 985 985 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-108. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on School Grounds/Playground 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 259 98.386 110.056 6.839 1 690 5 30 70 120 208 300 540 570 

Gender Male 0.136 118.007 126.395 10.84 1 690 10 35 85 148.5 255 370 555 625 

Gender Female 123 76.691 83.861 7.562 1 570 5 20 51 120 180 225 270 440 

Age (years) * 2 275 374.767 265 10 540 10 10 275 540 540 540 540 540 

Age (years) 1-4 9 85 61.084 20.36 10 175 10 30 65 140 175 175 175 175 

Age (years) 5-11 64 88.016 95.638 11.96 5 625 10 30 60 120 170 220 315 625 

Age (years) 12-17 76 78.658 88.179 10.12 3 570 5 25 55 105 165 225 370 570 

Age (years) 18-64 101 119.812 127.563 12.69 1 690 5 30 85 165 240 360 540 555 

Age (years) > 64 7 65 47.258 17.86 5 150 5 30 60 95 150 150 150 150 

Race White 208 98.212 106.512 7.385 1 690 9 30 70 125 190 281 510 555 

Race Black 23 128.435 157.54 32.85 5 570 5 25 67 170 300 540 570 570 

Race Asian 6 59 66.076 26.98 10 179 10 10 35 85 179 179 179 179 

Race Some Others 7 70 59.652 22.55 10 180 10 10 60 105 180 180 180 180 

Race Hispanic 15 83.733 102.972 26.59 1 370 1 10 30 120 228 370 370 370 

Hispanic No 225 102.613 113.686 7.579 3 690 9 30 70 125 210 300 540 570 

Hispanic Yes 32 71.219 79.899 14.12 1 370 1 12.5 32.5 110 150 228 370 370 

Hispanic DK 2 57.5 31.82 22.5 35 80 35 35 57.5 80 80 80 80 80 

Employment * 143 80.161 88.031 7.362 3 625 9 25 55 115 160 215 315 570 

Employment Full Time 48 130.271 127.162 18.35 1 555 10 40 85 180 300 360 555 555 

Employment Part Time 24 129.708 158.934 32.44 3 690 10 35 85 143.5 228 510 690 690 

Employment Not Employed 42 95.429 94.776 14.62 1 440 5 30 80 120 180 235 440 440 

Employment Refused 2 322.5 307.591 217.5 105 540 105 105 323 540 540 540 540 540 

Education * 162 86.593 94.553 7.429 3 625 10 27 60 120 170 220 370 570 

Education < High School 11 124.818 171.918 51.84 1 540 1 5 45 180 345 540 540 540 

Education High School Graduate 33 113.636 110.669 19.27 3 555 5 30 90 160 240 290 555 555 

Education < College 19 129.842 147.389 33.81 5 510 5 33 70 210 440 510 510 510 

Education College Graduate 19 122.105 149.938 34.4 5 690 5 50 85 125 235 690 690 690 

Education Post Graduate 15 102.933 98.093 25.33 1 360 1 30 75 125 235 360 360 360 

Census Region Northeast 66 105.955 115.248 14.19 5 690 10 30 85 150 190 281 540 690 

Census Region Midwest 53 86.057 109.203 15 3 540 5 20 50 115 190 290 510 540 

Census Region South 82 85.463 92.353 10.2 1 570 5 30 60 115 180 255 360 570 

Census Region West 58 119.31 125.638 16.5 1 625 10 30 85 160 235 440 555 625 

Day Of Week Weekday 205 87.02 105.524 7.37 1 625 5 25 55 115 180 240 540 555 

Day Of Week Weekend 54 141.537 117.065 15.93 10 690 25 67 113 180 290 345 440 690 

Season Winter 53 72.189 101.951 14 1 555 3 20 35 85 130 315 440 /555 

Season Spring 88 108.614 96.502 10.29 5 540 10 45 85 147.5 215 255 510 540 

Season Summer 65 116.446 137.897 17.1 5 690 10 30 75 135 270 360 625 690 

Season Fall 53 85.453 96.241 13.22 5 540 5 20 55 120 180 235 345 540 

Asthma No 237 100.941 113.236 7.355 1 690 5 30 70 120 215 315 540 570 

Asthma Yes 22 70.864 61.977 13.21 5 179 10 15 45 145 160 165 179 179 

Angina No 254 99.118 110.809 6.953 1 690 5 30 68.5 120 208 300 540 570 

Angina Yes 5 61.2 53.383 23.87 1 130 1 15 70 90 130 130 130 130 

Bronchitis/Emphysema No 248 100.565 111.621 7.088 1 690 5 30 71 125 210 300 540 570 

Bronchitis/Emphysema Yes 10 52.7 45.363 14.35 9 160 9 22 44 60 125 160 160 160 

Bronchitis/Emphysema DK 1 15 0 0 15 15 15 15 15 15 15 15 15 15 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean

24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max =

maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-109. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Park/Golf Course 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 

All 506 198.603 190.248 8.4575 1 1065 20 60 135 270 465 590 748 8

Gender Male 291 205.825 183.101 10.7336 1 1015 25 60 150 285 510 590 730 7

Gender Female 214 187.748 199.367 13.6284 5 1065 15 55 120 250 435 590 870 9

Gender Refused 1 420 * * 420 420 420 420 420 420 420 420 420 4

Age (years) * 10 122.4 60.183 19.0317 30 225 30 60 120 160 202 225 225 2

Age (years) 1-4 21 149.857 176.25 38.4609 21 755 25 50 85 150 360 425 755 7

Age (years) 5-11 54 207.556 184.496 25.1068 25 665 35 70 125 275 555 635 660 6

Age (years) 12-17 52 238.462 242.198 33.5869 15 1065 15 60 147.5 337.5 590 840 915 10

Age (years) 18-64 314 197.838 185.939 10.4931 1 1015 20 60 150 270 440 580 748 8

Age (years) > 64 55 188.964 182.919 24.6648 10 735 20 30 120 300 510 570 590 7

Race White 441 205.338 195.266 9.2984 1 1065 20 60 150 275 480 605 795 9

Race Black 19 114.474 103.667 23.7829 15 425 15 30 90 155 240 425 425 4

Race Asian 8 185.625 233.398 82.5186 30 665 30 32.5 47.5 315 665 665 665 6

Race Some Others 16 171.25 154.229 38.5572 30 560 30 58 119.5 235 405 560 560 5

Race Hispanic 20 169.45 135.803 30.3664 30 555 32.5 77 145 205 372.5 495 555 5

Race Refused 2 75 63.64 45 30 120 30 30 75 120 120 120 120 1

Hispanic No 469 202.706 193.555 8.9376 1 1065 20 60 135 270 480 605 755 9

Hispanic Yes 34 154.824 135.043 23.1596 15 555 30 60 137.5 175 310 555 555 5

Hispanic DK 1 10 * * 10 10 10 10 10 10 10 10 10 

Hispanic Refused 2 75 63.64 45 30 120 30 30 75 120 120 120 120 1

Employment * 128 208.242 209.644 18.5301 15 1065 25 60 120 275 555 645 840 9

Employment Full Time 201 195.831 188.984 13.3299 8 1015 25 60 135 270 450 570 748 9

Employment Part Time 41 213.488 215.602 33.6714 20 870 20 60 132 260 540 660 870 8

Employment Not Employed 132 190.932 166.019 14.4501 1 810 15 60 160 270 420 525 730 7

Employment Refused 4 130 106.771 53.3854 30 280 30 60 105 200 280 280 280 2

Education * 140 202.743 204.676 17.2983 15 1065 20.5 60 120 270 498.5 640 840 9

Education < High School 32 180.844 207.784 36.7315 30 995 30 30 110 245 385 570 995 9

Education High School Graduate 108 219.676 197.223 18.9778 10 1015 20 77.5 162.5 281 545 625 730 8

Education <College 93 191.57 171.177 17.7502 1 870 15 60 150 275 440 510 748 8

Education College Graduate 83 203.53 183.095 20.0973 5 930 23 60 145 270 450 590 795 9

Education Post Graduate 50 157.76 166.568 23.5562 10 735 20 45 75 255 337.5 555 703 7

Census Region Northeast 106 184.858 177.429 17.2334 1 1065 20 60 124 240 450 574 635 6

Census Region Midwest 124 194.629 188.667 16.9428 10 1015 30 60 135 255 420 590 735 9

Census Region South 136 218.846 211.474 18.1337 10 930 20 60 150 325 525 720 840 9

Census Region West 140 192.864 179.421 15.1639 5 870 17.5 58 131 272.5 430 575 755 8

Day Of Week Weekday 276 195.996 189.287 11.3938 5 1015 20 60 145 252.5 510 625 748 8

Day Of Week Weekend 230 201.73 191.76 12.6443 1 1065 20 60 130 280 454.5 580 810 9

Season Winter 83 209.072 195.228 21.429 15 1065 30 60 165 275 440 660 795 10

Season Spring 163 168.479 159.071 12.4594 8 930 20 50 120 235 360 510 570 7

Season Summer 192 219.615 199.872 14.4245 5 1015 20 65 155 290 535 630 840 9

Season Fall 68 198.706 217.911 26.4256 1 995 20 60 117.5 280 555 735 810 9

Asthma No 466 192.127 178.759 8.2808 1 1015 20 60 135 270 450 580 700 7

Asthma Yes 38 284.526 288.727 46.8377 30 1065 35 90 170 390 870 995 1065 10

Asthma DK 2 75 63.64 45 30 120 30 30 75 120 120 120 120 1

Angina No 494 197.881 189.761 8.5378 1 1065 20 60 135 270 459 590 755 9

Angina Yes 9 247.778 235.267 78.4224 35 730 35 60 120 330 730 730 730 7

Angina DK 3 170 170.587 98.4886 30 360 30 30 120 360 360 360 360 3

Bronchitis/Emphysema No 490 196.978 184.633 8.3409 1 1065 20 60 145 270 454.5 585 735 8

Bronchitis/Emphysema Yes 14 273.143 339.073 90.6211 20 995 20 75 100 280 930 995 995 9

Bronchitis/Emphysema DK 2 75 63.64 45 30 120 30 30 75 120 120 120 120 1

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-110. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Pool/River/Lake 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 283 209.555 185.668 11.037 5 1440 25 60 150 296 480 570 670 690 

Gender Male 152 229.829 202.702 16.441 10 1440 30 82.5 174 305 510 600 690 900 

Gender Female 131 186.031 161.293 14.092 5 645 20 60 135 280 440 550 630 630 

Age (years) * 6 175 156.971 64.083 60 480 60 85 115 195 480 480 480 480 

Age (years) 1-4 14 250.571 177.508 47.441 90 630 90 130 167.5 370 560 630 630 630 

Age (years) 5-11 29 175.448 117.875 21.889 25 390 30 60 145 293 365 375 390 390 

Age (years) 12-17 22 128.318 94.389 20.124 40 420 58 60 82.5 210 225 235 420 420 

Age (years) 18-64 187 224.492 203.822 14.905 5 1440 20 60 150 320 511 615 690 900 

Age (years) > 64 25 194.2 161.757 32.351 20 525 30 60 115 277 480 510 525 525 

Race White 246 201.565 182.298 11.623 5 1440 25 60 145 285 440 560 670 690 

Race Black 12 380.583 231.89 66.941 20 690 20 177.5 450 562.5 615 690 690 690 

Race Asian 4 265 247.083 123.54 30 505 30 52.5 262.5 477.5 505 505 505 505 

Race Some Others 5 237 129.933 58.108 70 435 70 220 225 235 435 435 435 435 

Race Hispanic 12 161 131.699 38.018 20 390 20 52.5 112.5 265 375 390 390 390 

Race Refused 4 243.75 208.621 104.31 90 550 90 115 167.5 372.5 550 550 550 550 

Hispanic No 259 208.923 187.792 11.669 5 1440 25 60 150 295 480 585 670 690 

Hispanic Yes 20 210.9 160.142 35.809 20 540 28.5 87.5 155 337.5 450.5 525.5 540 540 

Hispanic Refused 4 243.75 208.621 104.31 90 550 90 115 167.5 372.5 550 550 550 550 

Employment * 66 176.879 131.256 16.156 25 630 40 70 142.5 235 370 420 560 630 

Employment Full Time 119 210.748 176.089 16.142 10 900 20 65 150 298 510 600 645 670 

Employment Part Time 26 217.038 199.926 39.209 20 670 30 60 120 320 570 580 670 670 

Employment Not Employed 69 238.884 236.16 28.43 5 1440 20 65 145 370 510 630 690 1440 

Employment Refused 3 141.667 52.52 30.322 90 195 90 90 140 195 195 195 195 195 

Education * 73 172.932 129.988 15.214 20 630 30 70 140 225 370 420 560 630 

Education < High School 18 267.611 159.382 37.567 40 600 40 145 247.5 375 525 600 600 600 

Education High School Graduate 69 213.217 224.126 26.982 10 1440 20 60 145 285 511 670 690 1440 

Education < College 62 233.258 192.408 24.436 5 690 30 65 150 360 550 580 615 690 

Education College Graduate 37 230.919 187.271 30.787 14 645 20 70 173 400 505 630 645 645 

Education Post Graduate 24 172.708 196.977 40.208 20 900 25 45 112.5 240 370 480 900 900 

Census Region Northeast 61 220.689 172.373 22.07 30 900 30 60 180 325 390 510 670 900 

Census Region Midwest 41 219.22 257.201 40.168 10 1440 20 60 120 280 480 600 1440 1440 

Census Region South 111 182.198 161.288 15.309 5 670 20 60 118 280 420 525 630 645 

Census Region West 70 237.571 181.838 21.734 25 690 40 90 180 300 547.5 615 690 690 

Day Of Week Weekday 165 188.77 179.894 14.005 10 1440 30 60 125 255 420 511 615 670 

Day Of Week Weekend 118 238.619 190.432 17.531 5 900 20 75 187.5 350 555 630 690 690 

Season Winter 30 173.167 181.68 33.17 20 630 20 40 102.5 270 492.5 585 630 630 

Season Spring 77 206.468 163.551 18.638 15 690 30 80 180 288 480 555 670 690 

Season Summer 151 219.709 196.809 16.016 5 1440 26 65 155 300 445 580 630 900 

Season Fall 25 201.4 189.663 37.933 20 670 45 70 105 310 510 510 670 670 

Asthma No 262 209.004 188.208 11.628 5 1440 25 60 150 295 480 580 670 690 

Asthma Yes 17 238.824 161.966 39.282 15 570 15 105 225 350 525 570 570 570 

Asthma DK 4 121.25 59.214 29.607 60 195 60 75 115 167.5 195 195 195 195 

Angina No 272 205.897 185.199 11.229 5 1440 25 60 145 290.5 480 570 645 690 

Angina Yes 8 359.375 178.774 63.206 60 690 60 287.5 340 435 690 690 690 690 

Angina DK 3 141.667 52.52 30.322 90 195 90 90 140 195 195 195 195 195 

Bronchitis/Emphysema No 266 210.974 189.082 11.593 5 1440 25 60 150 296 480 580 670 690 

Bronchitis/Emphysema Yes 14 197.143 131.54 35.156 15 440 15 90 172.5 300 370 440 440 440 

Bronchitis/Emphysema DK 3 141.667 52.52 30.322 90 195 90 90 140 195 195 195 195 195 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-111. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Restaurant/Picnic 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 64 81.016 114.7 14.337 3 540 5 12.5 30 107.5 165 270 540 540 

Gender Male 31 111.839 148.921 26.747 5 540 5 20 60 150 270 540 540 540 

Gender Female 33 52.061 57.66 10.037 3 210 3 8 30 80 135 180 210 210 

Age (years) 1-4 6 57.5 61.38 25.058 5 160 5 15 30 105 160 160 160 160 

Age (years) 5-11 5 112.8 202.59 90.601 5 473 5 6 20 60 473 473 473 473 

Age (years) 12-17 6 60 55.408 22.62 5 150 5 30 35 105 150 150 150 150 

Age (years) 18-64 46 84.804 116.85 17.229 3 540 5 10 50 120 180 270 540 540 

Age (years) > 64 1 15 * * 15 15 15 15 15 15 15 15 15 15 

Race White 54 76 105.032 14.293 3 540 5 15 30 105 165 270 473 540 

Race Black 4 57.75 83.108 41.554 5 180 5 5.5 23 110 180 180 180 180 

Race Asian 1 75 * * 75 75 75 75 75 75 75 75 75 75 

Race Some Others 2 97.5 31.82 22.5 75 120 75 75 97.5 120 120 120 120 120 

Race Hispanic 2 20 14.142 10 10 30 10 10 20 30 30 30 30 30 

Race Refused 1 540 * * 540 540 540 540 540 540 540 540 540 540 

Hispanic No 60 81.833 117.521 15.172 3 540 5 12.5 30 107.5 172.5 371.5 540 540 

Hispanic Yes 4 68.75 66.63 33.315 10 160 10 20 52.5 117.5 160 160 160 160 

Employment * 17 74.647 114.206 27.699 5 473 5 15 30 105 160 473 473 473 

Employment Full Time 37 70.838 67.86 11.156 3 270 5 15 55 120 165 210 270 270 

Employment Part Time 4 42 32.031 16.016 3 75 3 16.5 45 67.5 75 75 75 75 

Employment Not Employed 6 187.833 272.841 111.387 5 540 5 7 17.5 540 540 540 540 540 

Education * 18 70.667 112.076 26.416 3 473 3 6 30 105 160 473 473 473 

Education < High School 1 540 * * 540 540 540 540 540 540 540 540 540 540 

Education High School Graduate 11 56.182 84.536 25.489 3 270 3 10 20 60 165 270 270 270 

Education < College 10 108.6 164.611 52.055 5 540 5 7 30 150 352.5 540 540 540 

Education College Graduate 11 68.636 59.544 17.953 10 210 10 20 55 110 120 210 210 210 

Education Post Graduate 13 70.308 53.494 14.836 6 180 6 15 75 80 140 180 180 180 

Census Region Northeast 19 88.105 116.181 26.654 3 473 3 10 60 120 270 473 473 473 

Census Region Midwest 15 102.6 140.685 36.325 3 540 3 15 45 165 210 540 540 540 

Census Region South 16 48.563 47.25 11.812 5 140 5 8.5 30 92.5 120 140 140 140 

Census Region West 14 85.357 138.737 37.079 10 540 10 15 30 75 160 540 540 540 

Day Of Week Weekday 35 51.2 52.665 8.902 3 180 3 15 30 75 150 165 180 180 

Day Of Week Weekend 29 117 154.21 28.636 5 540 5 10 60 135 473 540 540 540 

Season Winter 8 79.375 75.187 26.583 10 210 10 20 52.5 135 210 210 210 210 

Season Spring 14 138.429 172.811 46.186 5 540 5 30 65 180 473 540 540 540 

Season Summer 28 71 105.063 19.855 3 540 3 7.5 35 100 150 160 540 540 

Season Fall 14 44.571 52.2 13.951 5 165 5 10 20 60 150 165 165 165 

Asthma No 61 82.131 117.182 15.004 3 540 5 10 30 110 165 270 540 540 

Asthma Yes 3 58.333 40.723 23.511 30 105 30 30 40 105 105 105 105 105 

Angina No 63 82.222 115.211 14.515 3 540 5 15 30 110 165 270 540 540 

Angina Yes 1 5 * * 5 5 5 5 5 5 5 5 5 5 

Bronchitis/Emphysema No 63 81.667 115.502 14.552 3 540 5 10 30 110 165 270 540 540 

Bronchitis/Emphysema Yes 1 40 * * 40 40 40 40 40 40 40 40 40 40 

Note: A "*" Signifies missing data. Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. 

Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the

percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-112. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Farm 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 128 252.703 232.537 20.554 5 955 20 75 176.5 427.5 600 730 855 933 

Gender Male 86 305.186 251.432 27.113 5 955 29 90 230 500 660 780 933 955 

Gender Female 42 145.238 137.207 21.171 5 600 20 50 105 210 265 482 600 600 

Age (years) * 1 510 * * 510 510 510 510 510 510 510 510 510 510 

Age (years) 1-4 3 121.667 52.52 30.322 70 175 70 70 120 175 175 175 175 175 

Age (years) 5-11 7 111.286 76.952 29.085 25 264 25 50 100 130 264 264 264 264 

Age (years) 12-17 9 157.778 85.416 28.472 29 265 29 90 175 265 265 265 256 265 

Age (years) 18-64 91 296.67 252.209 26.439 5 955 20 80 230 500 635 780 933 955 

Age (years) > 64 17 133.824 134.182 32.544 5 495 5 50 85 160 360 495 495 495 

Race White 120 260.217 236.226 21.564 5 955 20 75 180 472.5 607.5 745 855 933 

Race Black 4 58.75 30.923 15.462 25 85 25 32.5 62.5 85 85 85 85 85 

Race Some Others 2 165 21.213 15 150 180 150 150 165 180 180 180 180 180 

Race Hispanic 2 277.5 222.739 157.5 120 435 120 120 277.5 435 435 435 435 435 

Hispanic No 123 252.61 234.762 21.168 5 955 20 70 178 420 600 730 855 933 

Hispanic Yes 4 297.5 189.143 94.571 120 485 120 135 292..5 460 485 485 485 485 

Hispanic Refused 1 85 * * 85 85 85 85 85 85 85 85 85 85 

Employment * 19 134.947 77.658 17.816 25 265 25 86 120 180 264 265 265 265 

Employment Full Time 73 314.781 258.07 30.205 5 955 20 85 240 525 660 780 933 955 

Employment Part Time 11 283 183.589 55.354 45 525 45 150 230 490 495 525 525 525 

Employment Not Employed 24 152.917 183.977 37.554 5 825 5 35 90 205 280 495 825 825 

E mployment Refused 1 20 * * 20 20 20 20 20 20 20 20 20 20 

Education * 20 137.2 76.255 17.051 25 265 27 88 120 180 262 264.5 265 265 

Education < High School 12 305 211.058 60.927 30 635 30 97.5 325 492.5 510 635 635 635 

Education High School Graduate 50 314.54 280.31 39.642 5 955 20 85 215 525 745 855 944 955 

Education < College 25 186.6 165.994 33.199 5 555 15 60 155 255 482 525 555 555 

Education College Graduate 12 290.417 242.903 70.12 30 615 30 67.5 202.5 530 600 615 615 615 

Education Post Graduate 9 229.444 246.062 82.021 5 780 5 80 150 210 780 780 780 780 

Census Region Northeast 11 238.182 299.143 90.195 5 955 5 30 100 490 520 955 955 955 

Census Region Midwest 42 202.31 196.644 30.343 15 780 20 654 125 265 510 635 780 780 

Census Region South 57 279.702 239.345 31.702 5 933 25 85 195 482 635 760 825 933 

Census Region West 18 293.667 242.324 57.116 5 855 5 120 220 525 615 855 855 855 

Day Of Week Weekday 78 276.859 243.801 27.605 5 955 15 85 180 485 615 780 933 955 

Day Of Week Weekend 50 215.02 210.635 29.788 5 855 25 60 120 290 525 700 792.5 855 

Season Winter 32 205.25 207.666 36.711 5 955 22 77.5 120 245 495 540 955 955 

Season Spring 40 224.4 213.304 33.726 5 825 25 60 152.5 342.5 525 625 825 825 

Season Summer 43 276.093 247.758 37.783 5 933 20 70 230 435 660 760 933 933 

Season Fall 13 379.231 264.904 73.471 15 780 15 200 280 600 730 780 780 780 

Asthma No 120 256.983 235.209 21.472 5 955 21 75 180 427.5 607.5 745 855 933 

Asthma Yes 8 188.5 188.481 66.638 5 500 5 700 110 321.5 500 500 500 500 

Angina No 127 253.039 233.426 20.713 5 955 20 75 175 435 600 730 855 933 

Angina Yes 1 210 * * 210 210 210 210 210 210 210 210 210 210 

Bronchitis/Emphysema No 125 256.208 233.892 20.92 5 955 22 75 178 435 600 730 855 933 

Bronchitis/Emphysema Yes 3 106.667 95.699 55.252 5 195 5 5 120 195 195 195 195 195 

Note: A "*" Signifies missing data. Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. 

Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the

percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-113. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Kitchen 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 7063 92.646 94.207 1.121 1 1320 10 30 60 120 205 270 365 460 

Gender Male 2988 74.998 80.79 1.478 1 840 10 30 55 90 155 215 300 392 

Gender Female 4072 105.636 101.03 1.5832 1 1320 10 35 75 145 230 295 395 475 

Gender Refused 3 40 31.225 18.028 15 75 15 15 30 75 75 75 75 75 

Age (years) * 144 102.688 110.82 9.235 5 840 15 30 70 130 215 260 485 540 

Age (years) 1-4 335 73.719 54.382 2.9712 5 392 15 30 60 100 140 180 225 240 

Age (years) 5-11 477 60.468 52.988 2.4262 1 690 10 30 50 75 120 150 180 235 

Age (years) 12-17 396 55.02 58.111 2.9202 1 450 5 15 36 65 125 155 240 340 

Age (years) 18-64 4531 90.313 90.893 1.3503 1 1320 10 30 60 120 200 260 345 420 

Age (years) > 64 1180 131.388 119.55 3.4802 3 825 15 49 100 172 275 360 490 620 

Race White 5827 95.076 95.151 1.2465 1 840 10 30 65 120 210 273 380 465 

Race Black 641 79.376 91.989 3.6333 2 1320 10 30 60 100 175 230 275 380 

Race Asian 113 89.363 95.45 8.9792 5 690 10 30 75 115 150 220 265 650 

Race Some Others 119 69.059 60.786 5.5722 2 315 7 30 55 90 150 195 210 315 

Race Hispanic 266 84.203 77.297 4.7394 1 585 10 30 60 110 190 240 305 360 

Race Refused 97 90.33 113.55 11.53 5 880 7 30 60 90 190 275 480 880 

Hispanic No 6458 93.422 94.778 1.1794 1 1320 10 30 60 120 210 270 370 460 

Hispanic Yes 497 83.889 82.921 3.7195 1 675 10 30 60 110 180 240 315 415 

Hispanic DK 32 82.25 71.901 12.71 5 300 10 35 60 112.5 185 240 300 300 

Hispanic Refused 76 88.421 118.56 13.6 5 880 7 30 60 90 190 240 480 880 

Employment * 1200 62.348 55.431 1.6001 1 690 10 30 50 85 125 152.5 212.5 260 

Employment Full Time 2965 77.748 77.466 1.4227 1 840 10 30 60 100 165 225 300 376 

Employment Part Time 608 97.699 94.046 3.8141 1 755 10 30 70 133.5 213 270 405 445 

Employment Not Employed 2239 126.929 115.78 2.4468 1 1320 12 45 95 175 270 342 470 545 

Employment Refused 51 106.373 168.46 23.589 2 880 5 30 48 130 210 250 840 880 

Education * 1346 63.922 62.315 1.6985 1 880 10 30 50 85 130 165 235 285 

Education < High School 678 108.114 102.88 3.9511 1 775 10 34 80 150 230 295 405 545 

Education High School Graduate 2043 107.208 102.33 2.264 1 840 10 35 75 150 235 300 415 500 

Education < College 1348 94.359 101.17 2.7555 1 1320 10 30 60 120 210 280 380 450 

Education College Graduate 933 91.874 92.098 3.0152 2 840 10 30 60 120 200 261 330 410 

Education Post Graduate 715 88.227 87.661 3.2783 1 770 10 30 60 113 190 260 380 405 

Census Region Northeast 1645 99.632 99.739 2.4591 1 840 10 30 70 130 210 300 390 465 

Census Region Midwest 1601 96.066 93.567 2.3384 1 833 10 30 65 125 213 270 355 450 

Census Region South 2383 86.253 87.055 1.7833 1 880 10 30 60 115 190 245 330 420 

Census Region West 1434 91.441 99.061 2.6159 1 1320 10 30 60 119 195 255 380 480 

Day Of Week Weekday 4849 90.068 92.218 1.3243 1 1320 10 30 60 119 195 255 360 450 

Day Of Week Weekend 2214 98.294 98.207 2.0871 1 840 10 30 65.5 135 220 280 390 480 

Season Winter 1938 96.575 100.32 2.2787 1 1320 10 30 65 120 210 285 390 485 

Season Spring 1780 89.02 90.187 2.1376 1 840 10 30 60 120 195 255 350 420 

Season Summer 1890 89.316 90.984 2.0928 1 880 10 30 60 120 195 255 362 430 

Season Fall 1455 96.177 94.494 2.4773 1 770 10 30 65 125 210 275 375 470 

Asthma No 6510 92.448 93.602 1.1601 1 1320 10 30 60 120 205 270 365 450 

Asthma Yes 503 94.038 96.001 4.2805 1 785 10 30 60 120 210 270 345 450 

Asthma DK 50 104.44 143.73 20.326 7 880 10 30 60 120 195 240 712.5 880 

Angina No 6798 91.625 93.03 1.1283 1 1320 10 30 60 120 200 265 360 450 

Angina Yes 207 122.469 111.41 7.7437 4 657 10 45 100 155 255 360 415 620 

Angina DK 58 105.948 138.38 18.17 2 880 10 30 60 135 240 240 545 880 

Bronchitis/Emphysema No 6671 91.827 92.587 1.1336 1 1320 10 30 60 120 200 265 360 445 

Bronchitis/Emphysema Yes 338 104.784 113.39 6.1676 1 825 10 30 71 135 225 300 480 657 

Bronchitis/Emphysema DK 54 117.889 142.41 19.38 2 880 10 30 76 160 240 275 545 880 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-114. Statistics for 24-Hour Cumulative Number of Minutes Spent in the Bathroom 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 6661 35.0237 48.796 0.5979 1 870 5 15 25 40 60 90 137 255 

Gender Male 3006 32.689 50.366 0.9186 1 870 5 15 20.5 35 60 75 150 300 

Gender Female 3653 36.9491 47.399 0.7842 1 665 5 15 30 45 70 90 135 240 

Gender Refused 2 27.5 3.536 2.5 25 30 25 25 27.5 30 30 30 30 30 

Age (years) * 122 43.8689 67.007 6.0665 2 530 5 15 30 45 85 120 300 360 

Age (years) 1-4 328 35.939 46.499 2.5675 1 600 10 15 30 40 60 75 125 270 

Age (years) 5-11 490 30.9673 38.609 1.7442 1 535 5 15 27 35 52.5 60 100 200 

Age (years) 12-17 445 29.0517 32.934 1.5612 1 547 5 15 20 35 60 65 90 100 

Age (years) 18-64 4486 34.4884 46.067 0.6878 1 665 5 15 25 40 60 90 135 250 

Age (years) > 64 790 42.1975 69.431 2.4703 1 870 5 15 30 45 75 120 240 360 

Race White 5338 34.3164 48.628 0.6656 1 870 5 15 25 40 60 85 135 255 

Race Black 711 36.8678 39.559 1.4836 1 460 5 15 30 45 70 98 135 186 

Race Asian 117 33.5556 41.449 3.8319 5 375 5 15 25 40 60 90 110 210 

Race Some Others 134 47.306 69.649 6.0167 1 535 5 15 30 45 95 120 315 422 

Race Hispanic 283 38.6396 61.494 3.6554 1 546 5 15 24 45 60 80 270 425 

Race Refused 78 34.6026 49.182 5.5687 3 360 5 10 20 35 60 135 165 360 

Hispanic No 6067 34.5332 45.887 0.5891 1 705 5 15 25 40 60 90 135 240 

Hispanic Yes 498 39.2309 68.582 3.0733 1 870 5 15 25 45 60 90 270 425 

Hispanic DK 33 44.4242 72.269 12.58 5 422 10 15 30 45 60 120 422 422 

Hispanic Refused 63 44.0794 95.224 11.997 3 665 5 10 20 35 60 150 360 665 

Employment * 1240 31.9645 39.652 1.1261 1 600 5 15 30 35 60 70 100 180 

Employment Full Time 3130 33.4086 44.827 0.8012 1 595 5 15 25 40 60 80 123 240 

Employment Part Time 583 35.5232 43.932 1.8195 1 430 5 15 29 45 60 90 140 270 

Employment Not Employed 1661 40.1854 61.587 1.5111 1 870 5 15 30 45 75 110 210 340 

Employment Refused 47 34.6809 54.835 7.9986 3 360 5 15 25 30 55 75 360 360 

Education * 1386 32.1717 42.788 1.1493 1 665 5 15 25 35 60 70 110 200 

Education < High School 522 40.8736 64.533 2.8245 1 870 5 15 30 45 70 100 240 350 

Education High School Graduate 1857 35.832 50.155 1.1639 1 600 5 15 25 40 63 90 135 270 

Education < College 1305 36.0797 44.121 1.2214 1 540 5 15 25 45 70 95 150 225 

Education College Graduate 913 34.9912 54.071 1.7895 1 705 5 15 20 40 60 90 150 340 

Education Post Graduate 678 32.1475 42.82 1.6445 1 460 5 15 22 40 60 75 110 300 

Census Region Northeast 1497 34.3287 51.244 1.3244 1 600 5 15 25 40 60 80 140 335 

Census Region Midwest 1465 35.7802 54.521 1.4245 1 870 5 15 25 40 60 90 145 315 

Census Region South 2340 35.0739 42.003 0.8683 1 510 5 15 30 40 60 90 135 214 

Census Region West 1359 34.8874 50.399 1.3671 1 705 5 15 25 40 60 90 140 250 

Day Of Week Weekday 4613 33.9035 46.663 0.687 1 870 5 15 25 40 60 85 135 240 

Day Of Week Weekend 2048 37.5469 53.214 1.1759 1 600 5 15 30 45 65 90 150 300 

Season Winter 1853 37.0232 50.658 1.1768 1 665 5 15 30 42 65 90 150 270 

Season Spring 1747 36.6474 50.536 1.2091 1 870 5 15 30 45 60 90 135 240 

Season Summer 1772 32.7788 44.543 1.0582 1 570 5 15 25 38 60 80 135 210 

Season Fall 1289 33.0349 49.108 1.3678 1 540 5 11 20 35 60 90 140 303 

Asthma No 6132 34.9204 48.833 0.6236 1 870 5 15 25 40 60 90 135 255 

Asthma Yes 493 35.2495 38.157 1.7185 1 410 5 15 30 45 65 90 140 220 

Asthma DK 36 49.5278 121.114 20.186 3 665 5 10 17.5 30 60 360 665 665 

Angina No 6473 34.5801 46.79 0.5816 1 870 5 15 25 40 60 90 135 240 

Angina Yes 145 51.9103 88.284 7.3316 3 600 7 20 30 45 75 185 546 570 

Angina DK 43 44.8605 111.216 16.96 3 665 5 10 15 30 50 110 665 665 

Bronchitis/Emphysema No 6327 34.8211 48.073 0.6044 1 870 5 15 25 40 60 90 135 255 

Bronchitis/Emphysema Yes 296 36.8378 47.481 2.7598 1 600 5 15 30 43.5 60 90 180 250 

Bronchitis/Emphysema DK 38 54.6316 122.723 19.908 3 665 5 10 17.5 30 110 360 665 665 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-115. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Bedroom 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 9151 563.12 184.644 1.9302 3 1440 300 460 540 660 780 880 1005 1141 

Gender Male 4157 549.648 182.976 2.8379 3 1440 285 450 540 640 780 860 980 1095 

Gender Female 4990 574.274 185.332 2.6236 5 1440 312 470 555 660 790 900 1030 1185 

Gender Refused 4 648.75 122.772 61.386 540 785 540 545 635 752.5 785 785 785 785 

Age (years) * 184 525.065 193.498 14.265 15 1440 195 420 513 600 720 860 950 1295 

Age (years) 1-4 488 741.988 167.051 7.562 30 1440 489 635 740 840 930 990 1095 1200 

Age (years) 5-11 689 669.144 162.888 6.2055 35 1440 435 600 665 740 840 915 1065 1140 

Age (years) 12-17 577 636.189 210.883 8.7792 15 1375 165 542 645 750 875 970 1040 1210 

Age (years) 18-64 5891 532.699 172.964 2.2535 3 1440 295 440 520 610 723 820 975 1110 

Age (years) > 64 1322 550.8 171.997 4.7305 15 1440 315 475 540 610 735 840 1000 1140 

Race White 7403 553.424 175.912 2.0445 3 1440 300 455 540 640 760 850 975 1105 

Race Black 923 612.33 219.9 7.2381 15 1440 300 480 597 725 895 990 1160 1323 

Race Asian 153 612.261 187.417 15.152 25 1285 345 510 600 705 830 950 1005 1245 

Race Some Others 174 590.713 200.214 15.178 15 1405 300 464 580 700 830 960 1050 1152 

Race Hispanic 378 602.577 214.353 11.025 25 1440 265 480 587.5 720 865 958 1095 1213 

Race Refused 120 555.842 198.564 18.126 30 1405 285 440 534 630 762.5 875 1290 1295 

Hispanic No 8326 560.878 182.574 2.0009 3 1440 300 460 540 650 780 870 1000 1140 

Hispanic Yes 684 597.402 206.333 7.8893 15 1440 300 480 585 713 840 958 1095 1200 

Hispanic DK 43 542.279 169.881 25.907 135 1002 300 420 555 660 756 830 1002 1002 

Hispanic Refused 98 523.439 180.194 18.202 30 1295 255 415 515 600 735 795 930 1295 

Employment * 1736 679.52 185.535 4.453 15 1440 390 590 675 785 892 960 1065 1170 

Employment Full Time 3992 513.454 157.599 2.4943 3 1440 283 435 510 585 680 765 890 1000 

Employment Part Time 777 551.613 169.425 6.0781 15 1335 330 455 540 630 750 835 1005 1100 

Employment Not Employed 2578 566.409 191.218 3.7661 5 1440 300 478 540 650 780 905 1095 1223 

Employment Refused 68 513.971 209.558 25.413 30 1440 210 420 497.5 585 725 795 1200 1440 

Education * 1925 668.265 188.751 4.302 15 1440 360 575 663 780 885 960 1060 1170 

Education < High School 807 554.809 180.581 6.3567 5 1440 300 450 540 630 775 860 1015 1160 

Education High School Graduate 2549 534.057 176.208 3.4901 3 1440 285 447 520 607 720 835 975 1151 

Education < College 1740 539.07 176.123 4.2222 5 1440 282 450 530 615 735 825 1005 1135 

Education College Graduate 1223 526.025 164.899 4.7152 15 1404 300 445 515 600 713 785 965 1070 

Education Post Graduate 907 525.192 160.567 5.3315 3 1355 315 445 510 600 690 780 950 1095 

Census Region Northeast 2037 561.515 185.273 4.105 5 1440 300 457 540 655 781 885 1020 1139 

Census Region Midwest 2045 552.402 179.232 3.9634 3 1440 280 450 540 643 765 860 965 1035 

Census Region South 3156 570.023 186.38 3.3177 10 1440 300 465 552 660 790 900 1055 1155 

Census Region West 1913 564.897 186.373 4.2611 5 1440 305 460 540 660 793 875 995 1152 

Day Of Week Weekday 6169 552.611 174.489 2.2216 3 1440 325 450 539 635 760 855 975 1130 

Day Of Week Weekend 2982 584.861 202.361 3.7057 3 1440 223 480 570 690 825 920 1055 1170 

Season Winter 2475 576 183.782 3.6942 5 1440 305 475 555 660 805 900 1035 1148 

Season Spring 2365 558.956 176.729 3.6341 15 1440 315 455 540 655 770 855 960 1095 

Season Summer 2461 566.114 195.229 3.9354 3 1440 285 455 545 660 810 900 1030 1190 

Season Fall 1850 547.23 179.924 4.1832 3 1440 270 450 537.5 630 750 850 960 1100 

Asthma No 8420 560.814 182.769 1.9918 3 1440 300 460 540 655 780 870 1000 1140 

Asthma Yes 671 593.846 201.517 7.7795 30 1440 300 475 580 690 835 946 1060 1327 

Asthma DK 60 543.117 218.404 28.196 30 1295 223 423 540 605 760 982.5 1275 1295 

Angina No 8836 564.211 183.935 1.9568 3 1440 300 460 540 660 785 880 1005 1140 

Angina Yes 244 535.545 203.888 13.053 20 1440 215 450 522.5 612.5 770 840 1135 1230 

Angina DK 71 522.113 193.937 23.016 30 1295 180 420 540 600 690 820 990 1295 

Bronchitis/Emphysema No 8660 563.08 184.244 1.9799 3 1440 300 460 540 660 780 880 1005 1141 

Bronchitis/Emphysema Yes 423 570.102 192.041 9.3373 15 1440 294 450 555 660 795 900 1055 1110 

Bronchitis/Emphysema DK 68 524.765 186.701 22.641 30 1295 240 420 540 600 700 820 930 1295 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-116. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Garage 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 193 117.782 144.451 10.398 1 790 5 20 60 150 296 480 665 690 

Gender Male 120 144.058 162.612 14.844 2 790 10 30 93.5 182.5 315 518 675 690 

Gender Female 73 74.589 94.322 11.04 1 530 5 15 30 120 180 240 450 530 

Age (years) * 1 20 * * 20 20 20 20 20 20 20 20 20 20 

Age (years) 1-4 4 83.5 47.459 23.729 15 120 15 52 99.5 115 120 120 120 120 

Age (years) 5-11 6 63.333 63.377 25.874 10 165 10 25 30 120 165 165 165 165 

Age (years) 12-17 12 80.833 78.383 22.627 10 240 10 20 50.5 147.5 185 240 240 240 

Age (years) 18-64 130 134.508 165.117 14.482 1 790 5 20 67.5 180 360 526 675 690 

Age (years) > 64 40 88.55 84.108 13.299 5 300 7.5 25 60 142.5 227.5 270 300 300 

Race White 165 109.509 127.523 9.928 1 690 5 20 60 135 240 315 526 675 

Race Black 12 205 219.483 63.359 5 570 5 37.5 90 405 530 570 570 570 

Race Asian 1 5 * * 5 5 5 5 5 5 5 5 5 5 

Race Some Others 6 186.333 308.416 125.91 10 790 10 18 30 240 790 790 790 790 

Race Hispanic 8 120 164.859 58.287 15 510 15 22.5 60 135 510 510 510 510 

Race Refused 1 120 * * 120 120 120 120 120 120 120 120 120 120 

Hispanic No 174 116.615 138.452 10.496 1 690 5 20 60 155 296 460 570 675 

Hispanic Yes 17 128.588 207.294 50.276 5 790 5 20 60 110 510 790 790 790 

Hispanic Refused 2 127.5 10.607 7.5 120 135 120 120 127.5 135 135 135 135 135 

Employment * 21 79.714 67.545 14.74 10 240 15 25 51 120 165 185 240 240 

Employment Full Time 85 145.259 175.17 19 1 790 5 20 65 180 405 530 675 790 

Employment Part Time 17 50.118 51.967 12.604 5 194 5 15 30 60 135 194 194 194 

Employment Not Employed 70 112.271 127.392 15.226 5 690 5 30 75 135 255 450 480 690 

Education * 22 76.545 67.572 14.406 10 240 10 20 50.5 120 165 185 240 240 

Education < High School 14 188.929 195.036 52.126 5 675 5 30 120 235 510 675 675 675 

Education High School Graduate 63 127.286 159.283 20.068 2 690 5 25 60 165 300 530 665 690 

Education < College 48 121.583 147.764 21.328 5 790 10 30 60 140 296 450 790 790 

Education College Graduate 25 118.2 145.773 29.155 5 480 5 20 60 120 405 460 480 480 

Education Post Graduate 21 75.857 88.067 19.218 1 300 2 10 30 120 195 260 300 300 

Census Region Northeast 23 137.174 159.451 33.248 5 510 15 30 60 195 460 510 510 510 

Census Region Midwest 42 131.381 166.398 25.676 10 690 20 40 87.5 120 260 665 690 690 

Census Region South 60 103.683 128.598 16.602 2 570 5 12.5 52.5 127.5 283 427.5 480 570 

Census Region West 68 115.265 139.682 16.939 1 790 5 20 72.5 152.5 300 315 530 790 

Day Of Week Weekday 116 128.664 158.968 14.76 1 790 5 25 60 165 315 510 665 690 

Day Of Week Weekend 77 101.39 118.416 13.495 2 675 10 20 60 120 240 300 526 675 

Season Winter 51 115.608 161.848 22.663 2 690 5 15 50 150 240 526 665 690 

Season Spring 59 136.763 163.341 21.265 5 790 10 30 90 165 315 570 675 790 

Season Summer 51 101.078 121.329 16.989 1 530 5 20 60 120 260 450 460 530 

Season Fall 32 112.875 110.217 19.484 5 480 10 25 85 157.5 240 315 480 480 

Asthma No 184 118.598 146.349 10.789 1 790 5 25 60 150 300 480 665 690 

Asthma Yes 9 101.111 102.585 34.195 5 270 5 15 60 180 270 270 270 270 

Angina No 187 118.219 146.174 10.689 1 790 5 20 60 150 300 480 665 690 

Angina Yes 6 104.167 78.639 32.104 10 220 10 25 110 150 220 220 220 220 

Bronchitis/Emphysema No 185 114.146 142.947 10.51 1 790 5 20 60 135 260 480 665 690 

Bronchitis/Emphysema Yes 8 201.875 163.64 57.856 15 450 15 60 177.5 337.5 450 450 450 450 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-117. Statistics for 24-Hour Cumulative Number of Minutes Spent in the Basement 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 274 142.15 162.882 9.84 1 931 10 30 90 180 330 535 705 765 

Gender Male 132 160.386 180.747 15.732 1 931 10 40 90 202.5 490 565 720 765 

Gender Female 141 125.66 143.283 12.067 2 810 10 30 75 175 265 420 705 720 

Gender Refused 1 60 * * 60 60 60 60 60 60 60 60 60 60 

Age (years) * 3 171.667 122.712 70.848 30 245 30 30 240 245 245 245 245 245 

Age (years) 1-4 8 94.75 55.695 19.691 28 180 28 47.5 90 137.5 180 180 180 180 

Age (years) 5-11 25 135.4 145.945 29.189 15 705 15 60 105 140 270 420 705 705 

Age (years) 12-17 26 97.462 113.063 22.173 1 515 10 30 60 150 240 275 515 515 

Age (years) 18-64 170 151.271 172.66 13.242 1 810 5 30 90 210 410 555 720 765 

Age (years) > 64 42 143.833 173.502 26.772 5 931 10 40 90 170 330 455 931 931 

Race White 248 133.75 154.08 9.784 1 810 10 30 90 167.5 315 510 705 720 

Race Black 15 183.8 165.472 42.725 12 515 12 40 150 270 450 515 515 515 

Race Asian 2 135 106.066 75 60 210 60 60 135 210 210 210 210 210 

Race Some Others 3 468.667 455.654 263.072 20 931 20 20 455 931 931 931 931 931 

Race Hispanic 1 30 * * 30 30 30 30 30 30 30 30 30 30 

Race Refused 5 263.2 173.071 77.4 60 540 60 231 240 245 540 540 540 540 

Hispanic No 263 139.046 161.666 9.969 1 931 10 30 90 180 330 510 705 765 

Hispanic Yes 6 185 197.332 80.561 15 555 15 30 150 210 555 555 555 555 

Hispanic DK 1 185 * * 185 185 185 185 185 185 185 185 185 185 

Hispanic Refused 4 271.25 198.762 99.381 60 540 60 150 242.5 392.5 540 540 540 540 

Employment * 57 115.561 124.205 16.451 1 705 12 40 90 150 240 420 515 705 

Employment Full Time 107 149.075 178.633 17.269 1 810 5 30 75 210 450 540 720 765 

Employment Part Time 22 115 114.808 24.477 10 535 25 60 77.5 150 185 290 535 535 

Employment Not Employed 85 157.953 176.347 19.128 5 931 10 35 120 210 330 600 720 931 

Employment Refused 3 151.667 110.265 63.661 30 245 30 30 180 245 245 245 245 245 

Education * 65 129.492 133.447 16.552 1 705 15 45 90 160 270 420 535 705 

Education < High School 15 169.867 203.464 52.534 5 605 5 30 90 255 565 605 605 605 

Education High School Graduate 78 159.385 188.681 21.364 5 810 5 40 90 195 420 720 765 810 

Education < College 48 160.583 184.204 26.588 2 931 10 25 120 202.5 400 600 931 931 

Education College Graduate 39 146.744 150.808 24.149 10 555 10 30 70 210 450 510 555 555 

Education Post Graduate 29 73.138 66.272 12.306 1 245 10 30 60 100 210 210 245 245 

Census Region Northeast 90 115.611 118.744 12.517 5 555 10 40 72.5 150 250 400 540 555 

Census Region Midwest 123 129.024 146.939 13.249 2 765 10 30 90 180 270 510 605 630 

Census Region South 35 187.971 205.847 34.794 10 931 28 45 110 255 450 720 931 931 

Census Region West 26 234.423 247.688 48.576 1 810 1 30 165 325 705 720 810 810 

Day Of Week Weekday 178 135.331 159.404 11.948 1 810 10 30 82.5 180 315 535 720 765 

Day Of Week Weekend 96 154.792 169.263 17.275 5 931 10 50 97.5 190 450 540 600 931 

Season Winter 80 144.475 147.022 16.438 5 630 13.5 30 90 220.5 315 480 610 630 

Season Spring 65 174.215 196.783 24.408 1 931 5 60 105 210 490 555 810 931 

Season Summer 79 142.367 180.698 20.33 1 765 5 30 85 150 455 605 720 765 

Season Fall 50 96.4 83.08 11.749 5 332 10 30 60 145 240 255 301 332 

Asthma No 253 143.126 164.183 10.322 1 931 10 35 90 180 330 540 705 765 

Asthma Yes 20 124.65 150.961 33.756 1 510 5.5 16 72.5 177.5 382.5 510 510 510 

Asthma DK 1 245 * * 245 245 245 245 245 245 245 245 245 245 

Angina No 269 141.409 163.736 9.983 1 931 10 30 90 180 330 535 705 765 

Angina Yes 3 201.667 122.1 70.494 65 300 65 65 240 300 300 300 300 300 

Angina DK 2 152.5 130.815 92.5 60 245 60 60 152.5 245 245 245 245 245 

Bronchitis/Emphysema No 265 138.996 160.98 9.889 1 931 10 30 90 180 330 515 705 765 

Bronchitis/Emphysema Yes 8 233.75 214.172 75.721 20 605 20 67.5 180 375 605 605 605 605 

Bronchitis/Emphysema DK 1 245 * * 245 245 245 245 245 245 245 245 245 245 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-118. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Utility Room or Laundry Room 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 458 73.218 71.872 3.358 1 510 5 25 60 100 150 200 300 360 

Gender Male 70 78.443 95.687 11.437 1 510 5 20 60 90 167.5 345 360 510 

Gender Female 388 72.276 66.796 3.391 2 510 5 28 60 105 150 190 240 330 

Age (years) * 6 65.833 34.412 14.049 25 120 25 40 60 90 120 120 120 120 

Age (years) 1-4 3 75 116.94 67.515 5 210 5 5 10 210 210 210 210 210 

Age (years) 5-11 3 105.667 168.423 97.239 2 300 2 2 15 300 300 300 300 300 

Age (years) 12-17 8 55.5 77.107 27.261 1 240 1 17 33 52.5 240 240 240 240 

Age (years) 18-64 362 73.58 73.87 3.882 2 510 5 20 60 105 150 195 325 405 

Age (years) > 64 76 72.592 58.092 6.664 2 345 10 30 60 90 150 180 245 345 

Race White 400 69.243 65.801 3.29 2 510 5 25 60 90 150 180 258 352.5 

Race Black 35 100.514 103.238 17.45 1 510 5 20 60 135 240 300 510 510 

Race Asian 4 82.5 37.749 18.875 30 120 30 60 90 105 120 120 120 120 

Race Some Others 6 86.667 27.869 11.377 60 120 60 65 78 120 120 120 120 120 

Race Hispanic 10 95.9 78.827 24.927 4 225 4 20 105 120 217.5 225 225 225 

Race Refused 3 170 264.15 152.507 15 475 15 15 20 475 475 475 475 475 

Hispanic No 435 72.069 69.87 3.35 1 510 5 25 60 90 150 190 300 360 

Hispanic Yes 20 81.7 62.982 14.083 4 225 4.5 40 60 120 182.5 218 225 225 

Hispanic DK 1 55 * * 55 55 55 55 55 55 55 55 55 55 

Hispanic Refused 2 247.5 321.734 227.5 20 475 20 20 248 475 475 475 475 475 

Employment * 12 76.75 107.831 31.128 1 300 1 4 23 135 240 300 300 300 

Employment Full Time 206 69.184 78.438 5.465 2 510 5 20 60 90 135 203 360 405 

Employment Part Time 51 72.216 62.506 8.753 2 225 5 15 55 120 150 180 225 225 

Employment Not Employed 187 77.679 63.835 4.668 5 475 10 30 60 115 150 180 245 345 

Employment Refused 2 76 104.652 74 2 150 2 2 76 150 150 150 150 150 

Education * 17 72 90.881 22.042 1 300 1 10 35 90 240 300 300 300 

Education < High School 51 71.765 49.445 6.924 15 245 20 30 60 90 120 180 195 245 

Education High School Graduate 163 71.583 71.583 5.607 2 510 6 30 60 90 140 180 325 405 

Education < College 107 77.234 71.721 6.934 2 475 5 20 60 120 155 200 225 240 

Education College Gradutae 60 74.033 77.252 9.973 5 510 10 27 60 97.5 154 190 203 510 

Education Post Graduate 60 71.267 79.857 10.31 5 360 5 18 60 90 155 263 360 360 

Census Region Northeast 105 80.933 84.595 8.256 2 510 5 25 60 120 180 225 345 360 

Census Region Midwest 116 64.948 63.307 5.878 2 475 5 15 60 90 135 155 215 240 

Census Region South 151 72.695 69.541 5.659 1 510 10 30 60 90 150 210 245 330 

Census Region West 86 75.872 69.9 7.537 4 405 5 30 60 115 150 180 360 405 

Day Of Week Weekday 322 68.643 66.724 3.718 1 510 5 23 60 90 140 180 240 345 

Day Of Week Weekend 136 84.051 82.05 7.036 5 510 10 30 60 120 180 240 360 405 

Season Winter 145 75.248 80.989 6.726 1 510 5 17 60 90 165 215 360 475 

Season Spring 89 81.888 83.016 8.8 5 510 10 30 60 100 180 240 405 510 

Season Summer 132 69.25 60.815 5.293 2 360 5 25 60 120 135 155 240 325 

Season Fall 92 67.326 58.613 6.111 3 345 10 22 60 90 125 180 245 345 

Asthma No 432 73.764 73.182 3.521 1 510 5 25 60 105 150 200 325 360 

Asthma Yes 26 64.154 44.791 8.784 10 200 10 25 60 90 120 130 200 200 

Angina No 440 72.134 70.217 3.347 1 510 5 25 60 100 150 185 270 360 

Angina Yes 16 103.125 109.877 27.469 5 360 5 30 60 138 345 360 360 360 

Angina DK 2 72.5 17.678 12.5 60 85 60 60 73 85 85 85 85 85 

Bronchitis/emphysema No 428 73.276 73.484 3.552 1 510 5 24 60 105 150 200 325 360 

Bronchitis/emphysema Yes 30 72.4 43.498 7.942 10 200 15 45 60 90 125 150 200 200 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-119. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Outdoor Pool or Spa 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 85 115.318 103.713 11.249 1 450 15 34 90 150 255 360 450 450 

Gender Male 34 113.676 106.758 18.309 5 450 10 45 75 150 258 360 450 450 

Gender Female 51 116.412 102.691 14.38 1 450 15 30 90 178 240 360 390 450 

Age (years) * 2 60 63.64 45 15 105 15 15 60 105 105 105 105 105 

Age (years) 1-4 9 85.556 86.329 28.776 15 255 15 30 60 75 255 255 255 255 

Age (years) 5-11 15 164.2 103.969 26.845 25 450 25 105 140 185 300 450 450 450 

Age (years) 12-17 5 97 53.805 24.062 40 180 40 60 100 105 180 180 180 180 

Age (years) 18-64 44 117.614 112.718 16.993 4 450 15 32 82.5 155 297 360 450 450 

Age (years) > 64 10 78.9 85.318 26.98 1 258 1 20 52.5 90 226.5 258 258 258 

Race White 75 120.893 107.723 12.439 1 450 15 34 90 180 258 360 450 450 

Race Black 5 66 59.729 26.711 10 150 10 20 45 105 150 150 150 150 

Race Some Others 1 105 * * 105 105 105 105 105 105 105 105 105 105 

Race Hispanic 2 112.5 53.033 37.5 75 150 75 75 112.5 150 150 150 150 150 

Race Refused 2 37.5 31.82 22.5 15 60 15 15 37.5 60 60 60 60 60 

Hispanic No 78 116.821 104.631 11.847 1 450 10 34 90 160 255 360 450 450 

Hispanic Yes 5 123 108.374 48.466 30 300 30 60 75 150 300 300 300 300 

Hispanic Refused 2 37.5 31.82 22.5 15 60 15 15 37.5 60 60 60 60 60 

Employment * 29 128.207 96.956 18.004 15 450 20 60 105 178 255 300 450 450 

Employment Full Time 27 111.889 102.499 19.726 4 390 10 30 90 150 297 360 390 390 

Employment Part Time 2 237.5 300.52 212.5 25 450 25 25 237.5 450 450 450 450 450 

Employment Not Employed 26 98.962 94.835 18.599 1 360 5 30 67.5 130 240 258 360 360 

Employment Refused 1 15 * * 15 15 15 15 15 15 15 15 15 15 

Education * 30 124.433 97.486 17.798 15 450 15 60 105 178 250 300 450 450 

Education < High School 8 109.375 155.367 54.93 5 450 5 15 37.5 157.5 450 450 450 450 

Education High School Graduate 15 150 130.516 33.699 1 390 1 45 105 240 360 390 390 390 

Education < College 17 80.529 66.66 16.167 4 240 4 30 75 90 225 240 240 240 

Education College Graduate 9 120.556 107.308 35.769 15 297 15 30 85 180 297 297 297 297 

Education Post Graduate 6 81.667 42.032 17.159 30 135 30 60 67.5 130 135 135 135 135 

Census Region Northeast 23 135.348 113.518 23.67 1 450 10 40 100 225 245 297 450 450 

Census Region Midwest 16 64.625 63.636 15.909 4 255 4 25 52.5 82.5 135 255 255 255 

Census Region South 23 114.696 78.499 16.368 15 390 20 60 105 150 185 210 390 390 

Census Region West 23 131.174 129.262 26.953 15 450 25 30 75 195 360 360 450 450 

Day Of Week Weekday 56 114.464 106.726 14.262 1 450 5 30 90 155 255 390 450 450 

Day Of Week Weekend 29 116.966 99.452 18.468 10 360 20 45 85 150 297 360 360 360 

Season Winter 10 118.9 159.415 50.412 4 450 4 20 30 135 405 450 450 450 

Season Spring 24 97.417 74.622 15.232 10 360 30 52.5 80 120 180 195 360 360 

Season Summer 47 124.511 104.25 15.206 1 450 15 40 90 185 255 300 450 450 

Season Fall 4 105.75 107.481 53.741 30 258 30 30 67.5 181.5 258 258 258 258 

Asthma No 73 109.89 105.481 12.346 1 450 10 30 75 140 255 360 450 450 

Asthma Yes 11 160.455 82.355 24.831 85 360 85 90 150 225 225 360 360 360 

Asthma DK 1 15 * * 15 15 15 15 15 15 15 15 15 15 

Angina No 84 116.512 103.746 11.32 1 450 15 37 90 155 255 360 450 450 

Angina DK 1 15 * * 15 15 15 15 15 15 15 15 15 15 

Bronchitis/Emphysema No 78 115.731 101.786 11.525 1 450 10 40 90 150 255 360 450 450 

Bronchitis/Emphysema Yes 6 126.667 137.792 56.253 15 360 15 25 67.5 225 360 360 360 360 

Bronchitis/Emphysema DK 1 15 * * 15 15 15 15 15 15 15 15 15 15 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-120. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Yard or Other Areas Outside the House 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 2308 137.587 144.112 2.9997 1 1290 10 40 90 180 320 420 570 660 

Gender Male 1198 158.448 160.016 4.6231 1 1290 10 60 120 198 360 500 627 730 

Gender Female 1107 114.887 120.869 3.6328 1 1065 5 30 75 150 285 360 450 560 

Gender Refused 3 183.333 60.277 34.801 120 240 120 120 190 240 240 240 240 240 

Age (years) * 27 167.37 164.484 31.6549 2 600 5 60 120 230 395 600 600 600 

Age (years) 1-4 151 135.311 111.483 9.0723 5 630 25 60 90 180 305 345 450 480 

Age (years) 5-11 271 150.594 135.111 8.2074 2 1250 20 60 120 190 310 405 553 570 

Age (years) 12-17 157 113.153 117.746 9.3972 2 660 5 30 80 150 240 405 462 610 

Age (years) 18-64 1301 136.382 147.923 4.1011 1 1080 5 30 90 180 330 435 570 715 

Age (years) > 64 401 141.125 155.213 7.751 1 1290 10 45 90 180 302 465 598 660 

Race White 1966 139.037 145.534 3.2823 1 1290 10 40 90 180 330 435 570 670 

Race Black 173 128.416 144.607 10.9943 1 1250 5 30 95 180 270 390 462 745 

Race Asian 21 101.19 88.485 19.3091 12 360 15 35 90 125 210 240 360 360 

Race Some Others 37 183.541 161.858 26.6094 2 750 3 84 120 270 380 553 750 750 

Race Hispanic 83 106.108 96.781 10.6231 2 610 5 35 75 145 240 270 330 610 

Race Refused 28 152.321 151.049 28.5455 5 600 5 60 97.5 210 360 510 600 600 

Hispanic No 2122 137.711 144.33 3.1332 1 1290 10 40 90 180 320 420 570 670 

Hispanic Yes 153 125 134.265 10.8547 1 750 5 30 85 150 270 435 575 630 

Hispanic DK 10 213.8 192.232 60.7892 3 585 3 60 145 380 503 585 585 585 

Hispanic Refused 23 176.739 156.551 32.6431 5 600 5 60 160 240 360 510 600 600 

Employment * 581 137.501 125.562 5.2092 2 1250 15 60 110 180 300 370 480 570 

Employment Full Time 807 131.087 150.703 5.305 1 1080 5 30 80 175 307 450 600 745 

Employment Part Time 166 126.145 134.084 10.407 1 1080 10 30 77.5 180 300 360 450 485 

Employment Not Employed 739 146.097 149.672 5.5058 1 1290 10 45 100 185 360 465 585 655 

Employment Refused 15 198 239.029 61.7171 5 660 5 30 120 465 600 660 660 660 

Education * 615 136.348 125.656 5.0669 2 1250 15 60 105 180 300 370 480 570 

Education < High School 236 161.017 186.469 12.1381 2 1290 10 45 105 195 390 510 765 915 

Education High School Graduate 618 144.706 144.929 5.8299 1 840 5 40 100 195 360 479 555 660 

Education < College 381 128.843 141.194 7.2336 1 1080 5 35 85 175 300 400 585 720 

Education College Graduate 251 122.968 135.802 8.5717 1 750 10 30 75 160 300 390 575 690 

Education Post Graduate 207 127.126 149.975 10.424 1 1065 5 30 78 150 320 435 570 630 

Census Region Northeast 473 137.67 132.769 6.1047 1 750 10 45 90 185 317 420 532 600 

Census Region Midwest 456 138.853 155.656 7.2893 2 1290 10 45 90 180 300 440 575 690 

Census Region South 832 136.472 146.655 5.0843 1 1080 10 35 90 180 310 420 570 730 

Census Region West 547 138.155 139.946 5.9837 1 750 5 36 90 180 330 460 570 630 

Day Of Week Weekday 1453 126.919 131.579 3.4519 1 1250 5 35 90 165 300 395 553 610 

Day Of Week Weekend 855 155.716 161.693 5.5298 1 1290 10 45 110 210 360 475 630 745 

Season Winter 399 112.19 135.967 6.8068 1 1080 5 30 60 140 300 380 540 690 

Season Spring 787 149.738 139.245 4.9635 1 915 10 60 120 195 338 430 555 660 

Season Summer 796 143.681 155.886 5.5252 1 1290 10 45 99 180 330 450 610 715 

Season Fall 326 124.457 130.523 7.229 1 720 10 35 87.5 160 300 380 510 655 

Asthma No 2129 137.746 144.41 3.1297 1 1290 10 40 90 180 315 420 570 690 

Asthma Yes 166 131.566 136.006 10.5561 1 670 10 30 90 165 345 450 553 610 

Asthma DK 13 188.462 192.141 53.2904 5 600 5 60 90 300 480 600 600 600 

Angina No 2228 136.521 141.088 2.989 1 1290 10 41 90 180 315 420 570 660 

Angina Yes 63 158.683 216.341 27.2564 2 1080 5 30 75 180 420 485 1065 1080 

Angina DK 17 199.118 191.305 46.3983 5 600 5 35 120 325 480 600 600 600 

Bronchitis/Emphysema No 2191 138.793 144.994 3.0976 1 1290 10 45 90 180 320 430 570 690 

Bronchitis/Emphysema Yes 105 104.438 111.282 10.86 1 553 5 30 60 145 270 360 415 475 

Bronchitis/Emphysema DK 12 207.5 192.23 55.4919 5 600 5 60 140 330 480 600 600 600 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-121. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in a Car 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 6560 87.4261 88.186 1.0888 1 1280 10 34 63 110 175 240 345 450 

Gender Male 2852 90.7398 97.337 1.8227 1 1280 10 30 63 115 185 254 360 526 

Gender Female 3706 84.9069 80.374 1.3203 1 878 10 35 63.5 110 165 220 335 420 

Gender Refused 2 30 14.142 10 20 40 20 20 30 40 40 40 40 40 

Age (years) * 120 94.025 90.218 8.2358 7 593 10 37.5 71.5 120 180 222.5 435 450 

Age (years) 1-4 297 63.0101 56.758 3.2934 2 390 10 25 45 80 135 180 235 270 

Age (years) 5-11 449 64.6325 81.08 3.8264 1 900 5 20 40 85 145 175 310 345 

Age (years) 12-17 393 64.8346 70.974 3.5802 1 630 9 20 41 80 136 185 300 380 

Age (years) 18-64 4489 93.8278 92.302 1.3776 1 1280 13 40 70 120 184 250 360 495 

Age (years) > 64 812 83.5283 79.436 2.7877 4 780 10 30 60 110 165 225 315 405 

Race White 5337 87.6283 89.72 1.2281 1 1280 10 31 64 110 175 240 360 460 

Race Black 640 86.8063 74.343 2.9387 1 690 10 35 65 115 180 240 305 330 

Race Asian 117 78.7607 66.315 6.1309 5 360 20 35 60 95 135 225 320 330 

Race Some Others 121 87.6942 84.48 7.68 3 540 10 30 60 120 180 250 330 345 

Race Hispanic 265 90.0717 101.474 6.2335 2 825 15 35 65 100 165 235 465 620 

Race Refused 80 82.4 73.314 8.1967 5 420 12 30 60 120 167.5 229.5 315 420 

Hispanic No 5987 87.4657 87.603 1.1322 1 1280 10 35 65 110 175 240 345 440 

Hispanic Yes 477 88.543 97.206 4.4507 2 825 10 30 60 103 180 240 388 595 

Hispanic DK 29 63.8966 73.131 13.5801 5 325 6 20 40 60 187 200 325 325 

Hispanic Refused 67 86.1194 78.361 9.5733 5 420 14 30 60 120 180 239 315 420 

Employment * 1124 64.2482 72.331 2.1575 1 900 5 20 45 81 136 180 270 345 

Employment Full Time 3134 93.5568 92.167 1.6464 2 1280 15 40 70 120 180 242 360 490 

Employment Part Time 632 90.0506 81.969 3.2605 2 878 10 40 70 116.5 175 230 330 384 

Employment Not Employed 1629 90.3603 90.224 2.2354 1 780 10 35 60 115 195 250 365 465 

Employment Refused 41 97.1707 83.994 13.1176 10 330 15 30 75 120 220 290 330 330 

Education * 1260 66.531 72.305 2.0369 1 900 6 21 45 85 145 186.5 270 350 

Education < High School 434 86.0115 82.143 3.943 5 620 10 35 60 115 165 210 360 455 

Education High School Graduate 1805 91.8476 91.088 2.144 1 870 10 38 65 115 190 255 385 465 

Education < College 1335 93.2427 94.302 2.581 2 1280 10 36 70 120 180 250 380 460 

Education College Graduate 992 95.6683 95.468 3.0311 4 840 14 40 73 120 185 250 370 580 

Education Post Graduate 734 91.5395 82.009 3.027 4 905 20 40 75 115 175 235 330 380 

Census Region Northeast 1412 85.8343 83.847 2.2314 1 780 10 33 60 110 170 240 330 410 

Census Region Midwest 1492 89.0992 86.623 2.2426 4 825 10 35 65 112.5 180 250 360 465 

Census Region South 2251 88.2625 89.347 1.8832 1 900 10 34 65 115 175 235 338 490 

Census Region West 1405 85.9089 92.167 2.4589 2 1280 10 30 60 110 175 235 345 435 

Day Of Week Weekday 4427 83.9248 85.023 1.2779 1 905 10 30 60 105 165 225 330 440 

Day Of Week Weekend 2133 94.6929 94.018 2.0357 1 1280 10 35 70 120 190 265 360 455 

Season Winter 1703 83.4692 82.128 1.9902 1 870 10 30 60 105 165 230 350 425 

Season Spring 1735 88.589 91.537 2.1976 1 905 10 30 60 110 180 250 380 480 

Season Summer 1767 88.0266 86.471 2.0571 1 900 10 35 65 115 170 235 330 450 

Season Fall 1355 90.1269 93.173 2.5312 1 1280 10 35 70 115 170 240 335 545 

Asthma No 6063 87.4143 88.032 1.1306 1 1280 10 34 63 110 175 240 350 450 

Asthma Yes 463 88.2419 92.088 4.2797 4 870 15 34 64 110 165 245 345 505 

Asthma DK 34 78.4118 57.362 9.8376 10 239 10 30 71 100 160 220 239 239 

Angina No 6368 87.54 88.695 1.1115 1 1280 10 34 63.5 110 175 240 350 450 

Angina Yes 154 82.1753 68.568 5.5254 8 365 10 30 60 115 162 214 285 320 

Angina DK 38 89.6053 72.877 11.8221 10 360 10 35 73.5 120 180 239 360 360 

Bronchitis/Emphysema No 6224 87.5517 88.855 1.1263 1 1280 10 34 62 110 175 240 350 450 

Bronchitis/Emphysema Yes 300 85.5833 76.155 4.3968 1 505 10 35 68.5 109 185 237.5 305 435 

Bronchitis/Emphysema DK 36 81.0556 63.142 10.5237 5 239 10 30 71 120 175 220 239 239 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-122. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in a Truck (Pick-up/Van) 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1172 85.3 95.867 2.8003 1 955 10 30 60 110 180 240 395 478 

Gender Male 760 91.097 105.368 3.8221 1 955 10 30 60 115 190 265 450 620 

Gender Female 412 74.607 74.197 3.6554 1 510 10 25 55 95 165 220 300 355 

Age (years) * 13 110.769 129.178 35.8274 10 450 10 35 60 90 300 450 450 450 

Age (years) 1-4 41 80.829 154.295 24.0969 1 955 10 15 35 70 206 210 955 955 

Age (years) 5-11 89 47.607 44.208 4.6861 1 240 7 15 30 65 110 130 180 240 

Age (years) 12-17 80 66.763 71.084 7.9475 5 352 5.5 15 37 93.5 180 222.5 265 352 

Age (years) 18-64 859 91.42 97.968 3.3426 2 750 10 30 60 115 189 260 440 555 

Age (years) > 64 90 79 82.42 8.6878 10 453 12 30 48.5 105 185 265 390 453 

Race White 1022 84.717 96.222 3.0099 1 955 10 30 60 110 180 235 390 510 

Race Black 68 91.294 98.465 11.9406 6 453 14 27.5 62.5 105.5 220 295 450 453 

Race Asian 3 138.333 63.311 36.5529 90 210 90 90 115 210 210 210 210 210 

Race Some Others 20 67.2 48.46 10.836 5 165 7.5 25 62.5 102.5 137 154.5 165 165 

Race Hispanic 48 92.792 99.31 14.3341 5 440 10 27.5 60 120 224 330 440 440 

Race Refused 11 88.182 110.754 33.3935 10 390 10 30 60 65 190 390 390 390 

Hispanic No 1069 85.112 95.567 2.9229 1 955 10 30 60 110 180 240 390 478 

Hispanic Yes 87 89.103 100.75 10.8015 5 630 5 29 60 115 210 230 440 630 

Hispanic DK 5 58 36.187 16.1833 20 97 20 20 68 85 97 97 97 97 

Hispanic Refused 11 85.909 111.643 33.6615 10 390 10 30 35 65 190 390 390 390 

Employment * 205 60.176 86.416 6.0355 1 955 7 15 30 75 146 185 240 265 

Employment Full Time 642 93.288 101.354 4.0001 4 750 10 30 60 120 192 270 450 555 

Employment Part Time 97 89.351 88.958 9.0323 2 460 6 30 60 120 190 270 450 460 

Employment Not Employed 217 83.032 85.775 5.8228 5 655 10 30 60 110 180 235 300 355 

Employment Refused 11 96.364 114.26 34.4508 10 390 10 30 35 170 190 390 390 390 

Education * 230 64.043 86.936 5.7324 1 955 7 15 35 85 160 206 245 352 

Education < High School 119 90.471 81.711 7.4904 5 453 14 35 60 120 195 280 295 450 

Education High School Graduate 392 87.594 94.724 4.7843 2 675 10 30 60 115 185 255 450 510 

Education < College 238 91.992 111.776 7.2454 4 750 10 30 60 110 190 290 555 655 

Education College Graduate 127 85.228 74.586 6.6184 5 370 15 30 60 110 180 230 345 355 

Education Post Graduate 66 112.439 117.975 14.5217 10 650 10 35 80 135 220 412 445 650 

Census Region Northeast 170 85.365 104.161 7.9888 2 695 10 20 50 110 186 260 445 630 

Census Region Midwest 268 91.209 94.43 5.7682 1 750 10 30 60 118.5 205 245 390 460 

Census Region South 491 87.279 100.099 4.5174 4 955 10 30 60 111 180 235 445 595 

Census Region West 243 74.741 81.299 5.2153 5 478 10 23 52 90 160 235 395 440 

Day Of Week Weekday 796 80.083 90.569 3.2101 1 750 10 30 55 101 170 230 375 510 

Day Of Week Weekend 376 96.346 105.493 5.4404 2 955 12 30 60.5 120 192 280 430 460 

Season Winter 322 78.543 91.604 5.1049 1 955 10 29 51 95 170 220 355 445 

Season Spring 300 92.477 100.164 5.783 1 695 10 30 60 120 208 267.5 442.5 549 

Season Summer 323 86.133 99.255 5.5227 2 750 10 30 60 110 180 233 430 595 

Season Fall 227 84.216 90.861 6.0306 5 675 10 30 60 105 165 265 395 465 

Asthma No 1092 85.288 93.452 2.828 1 750 10 30 60 110 184 240 412 478 

Asthma Yes 72 83.639 125.252 14.7611 5 955 10 20 46 115 170 235 395 955 

Asthma DK 8 101.875 129.668 45.8446 10 390 10 20 60 127.5 390 390 390 390 

Angina No 1142 84.868 95.219 2.8177 1 955 10 30 60 110 180 235 395 475 

Angina Yes 20 93.4 116.003 25.939 5 555 7.5 37.5 70 103 140.5 350.5 555 555 

Angina DK 10 118.5 128.583 40.6615 10 390 10 30 60 190 340 390 390 390 

Bronchitis/Emphysema No 1128 85.469 96.579 2.8756 1 955 10 30 60 110 180 240 412 478 

Bronchitis/Emphysema Yes 35 77.8 60.527 10.2308 5 240 5 30 60 120 165 220 240 240 

Bronchitis/Emphysema DK 9 93.333 123.92 41.3068 10 390 10 20 60 65 390 390 390 390 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-123. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Motorcycle, Moped, or Scooter 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 32 100.125 152.222 26.909 1 535 5 25 31 98 375 510 535 535 

Gender Male 29 104.276 158.322 29.4 1 535 5 25 32 80 485 510 535 535 

Gender Female 3 60 74.666 43.108 5 145 5 5 30 145 145 145 145 145 

Age (years) 5-11 2 42.5 53.033 37.5 5 80 5 5 42.5 80 80 80 80 80 

Age (years) 12-17 1 180 * * 180 180 180 180 180 180 180 180 180 180 

Age (years) 18-64 28 103.893 160.69 30.367 1 535 5 25 31 90.5 485 510 535 535 

Age (years) > 64 1 30 * * 30 30 30 30 30 30 30 30 30 30 

Race White 31 101.516 154.532 27.755 1 535 5 25 30 116 375 510 535 535 

Race Black 1 57 * * 57 57 57 57 57 57 57 57 57 57 

Hispanic No 31 102.387 154.191 27.693 1 535 5 25 32 116 375 510 535 535 

Hispanic Yes 1 30 * * 30 30 30 30 30 30 30 30 30 30 

Employment * 3 88.333 87.797 50.69 5 180 5 5 80 180 180 180 180 180 

Employment Full Time 23 62.783 100.105 20.873 1 485 5 25 30 57 142 145 485 485 

Employment Not Employed 6 249.167 251.663 102.741 10 535 10 30 205 510 535 535 535 535 

Education * 3 88.333 87.797 50.69 5 180 5 5 80 180 180 180 180 180 

Education < High School 3 305 247.538 142.916 30 510 30 30 375 510 510 510 510 510 

Education High School Graduate 15 95.667 170.645 44.06 1 535 1 25 30 57 485 535 535 535 

Education < College 6 45.833 49.54 20.224 10 145 10 20 32.5 35 145 145 145 145 

Education College Graduate 4 70.5 51.423 25.712 20 142 20 37.5 60 103.5 142 142 142 142 

Education Post Graduate 1 32 * * 32 32 32 32 32 32 32 32 32 32 

Census Region Northeast 6 24.167 8.01 3.27 10 30 10 20 27.5 30 30 30 30 30 

Census Region Midwest 12 191.583 216.501 62.499 1 535 1 28 68.5 430 510 535 535 535 

Census Region South 6 67.167 66.764 27.256 5 180 5 32 35 116 180 180 180 180 

Census Region West 8 44.625 44.654 15.788 5 142 5 15 30 60 142 142 142 142 

Day Of Week Weekday 21 71.333 110.425 24.097 5 510 5 25 32 65 145 180 510 510 

Day Of Week Weekend 11 155.091 205.865 62.071 1 535 1 20 30 375 485 535 535 535 

Season Winter 5 124 230.011 102.864 5 535 5 20 25 35 535 535 535 535 

Season Spring 12 121.833 153.631 44.349 1 485 1 28 43.5 143.5 375 485 485 485 

Season Summer 8 55.875 52.267 18.479 20 180 20 30 33.5 60 180 180 180 180 

Season Fall 7 96.429 184.249 69.639 5 510 5 5 30 80 510 510 510 510 

Asthma No 30 85.1 134.187 24.499 1 510 5 25 30 65 277.5 485 510 510 

Asthma Yes 2 325.5 296.278 209.5 116 535 116 116 325.5 535 535 535 535 535 

Angina No 31 102.387 154.191 27.693 1 535 5 25 32 116 375 510 535 535 

Angina Yes 1 30 * * 30 30 30 30 30 30 30 30 30 30 

Bronchitis/Emphysema No 31 101.516 154.532 27.755 1 535 5 25 30 116 375 510 535 535 

Bronchitis/Emphysema Yes 1 57 * * 57 57 57 57 57 57 57 57 57 57 

Note: A "*" Signifies missing data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. 

Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal

to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-124. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in Other Trucks 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 124 135.121 235.635 21.16 1 1440 5 25 48 107.5 270 690 960 1080 

Gender Male 80 174.888 283.085 31.65 1 1440 5 27 60 139 640 772.5 1080 1440 

Gender Female 44 62.818 57.438 8.659 1 270 5 20 45 90 145 180 270 270 

Age (years) * 1 35 * * 35 35 35 35 35 35 35 35 35 35 

Age (years) 1-4 4 79 26.47 13.235 46 105 46 58 82.5 100 105 105 105 105 

Age (years) 5-11 9 37.875 28.002 9.9 10 95 10 18.5 30 50.5 95 95 95 95 

Age (years) 12-17 7 116.857 83.071 31.398 10 250 10 60 90 195 250 250 250 250 

Age (years) 18-64 96 153.24 263.424 26.886 1 1440 5 22.5 45 117 600 750 1080 1440 

Age (years) > 64 9 71.5 57.887 20.466 18 186 18 25 60 99 186 186 186 186 

Race White 110 1440 242.807 23.151 1 1440 5 25 60 120 412.5 735 960 1080 

Race Black 8 46.125 36.314 12.839 10 100 10 15 32.5 82 100 100 100 100 

Race Asian 1 40 * * 40 40 40 40 40 40 40 40 40 40 

Race Some Others 1 95 * * 95 95 95 95 95 95 95 95 95 95 

Race Hispanic 3 246.333 366.947 211.86 29 670 29 29 40 670 670 670 670 670 

Race Refused 1 35 * * 35 35 35 35 35 35 35 35 35 35 

Hispanic No 113 133.673 240.595 22.633 1 1440 5 20 45 100 270 735 960 1080 

Hispanic Yes 9 170 200.709 66.903 29 670 29 41 105 180 670 670 670 670 

Hispanic DK 1 85 * * 85 85 85 85 85 85 85 85 85 85 

Hispanic Refused 1 35 * * 35 35 35 35 35 35 35 35 35 35 

Employment * 18 79.278 63.15 14.885 10 250 10 35 65 95 195 250 250 250 

Employment Full Time 79 168.468 286.399 32.222 1 1440 5 20 45 114 670 795 1080 1440 

Employment Part Time 6 96 103.894 42.415 2 255 2 5 55 180 255 255 255 255 

Employment Not Employed 19 75.105 57.278 13.14 10 186 10 25 75 120 180 186 186 186 

Employment Refused 2 20 21.213 15 5 35 5 5 20 35 35 35 35 35 

Education * 21 70.333 62.607 13.662 5 250 10 25 60 95 138 195 250 250 

Education < High School 10 389 505.656 159.9 5 1440 5 25 45 750 1117.5 1440 1440 1440 

Education High School Graduate 48 156.958 257.81 37.212 1 1080 5 19 52.5 130 610 690 1080 1080 

Education < College 24 116.25 124.385 25.39 29 600 32 42.5 77.5 120 255 270 600 600 

Education College Graduate 10 53 53.24 16.836 10 180 10 15 30 90 135 180 180 180 

Education Post Graduate 11 48.545 55.111 16.617 1 186 1 15 30 78 103 186 186 186 

Census Region Northeast 28 119.179 237.794 44.939 2 1080 5 27.5 45.5 90 180 795 1080 1080 

Census Region Midwest 36 189.194 318.577 53.096 1 1440 5 17 45 197.5 600 960 1440 1440 

Census Region South 42 100.595 151.868 23.434 1 750 5 22 55 114 186 205 750 750 

Census Region West 18 132.333 194.344 45.807 10 670 10 35 67.5 105 610 670 670 670 

Day Of Week Weekday 82 134.793 197.96 21.861 1 795 5 25 60 120 555 670 750 795 

Day Of Week Weekend 42 135.762 298.573 46.071 1 1440 5 18 45 75 250 960 1440 1440 

Season Winter 36 126.444 219.584 36.597 5 1080 10 26 53 92.5 270 670 1080 1080 

Season Spring 29 199.793 350.125 65.017 1 1440 5 15 35 180 795 960 1440 1440 

Season Summer 38 87.447 125.316 20.329 2 750 5 32 60 95 195 255 750 750 

Season Fall 21 146.952 213.871 46.67 1 735 15 30 74 120 600 600 735 735 

Asthma No 116 133.69 238.543 22.148 1 1440 5 21 48 104 270 735 960 1080 

Asthma Yes 7 173.143 210.169 79.436 32 610 32 35 60 250 610 610 610 610 

Asthma DK 1 35 * * 35 35 35 35 35 35 35 35 35 35 

Angina No 120 138.725 238.702 21.79 1 1440 5 25 60 112 412.5 712.5 960 1080 

Angina Yes 3 24.333 13.65 7.881 15 40 15 15 18 40 40 40 40 40 

Angina DK 1 35 * * 35 35 35 35 35 35 35 35 35 35 

Bronchitis/Emphysema No 116 135.612 242.76 22.54 1 1440 5 23.5 45 101.5 555 735 960 1080 

Bronchitis/Emphysema Yes 7 141.286 83.38 31.515 18 250 18 60 180 195 250 250 250 250 

Bronchitis/Emphysema DK 1 35 * * 35 35 35 35 35 35 35 35 35 35 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-125. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Bus 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 469 74.648 93.532 4.3189 2 945 10 30 55 90 125 180 435 570 

Gender Male 219 77.251 104.119 7.0357 5 945 10 30 55 90 135 180 460 570 

Gender Female 250 72.368 83.306 5.2688 2 640 15 30 55 90 120 175 420 501 

Age (years) * 14 145 167.177 44.68 10 605 10 60 100 140 435 605 605 605 

Age (years) 1-4 5 56 40.218 17.986 15 120 15 30 55 60 120 120 120 120 

Age (years) 5-11 133 48.383 29.431 2.552 5 140 10 25 43 67 90 110 120 122 

Age (years) 12-17 143 59.413 46.343 3.8754 7 370 10 30 54 75 110 135 179 225 

Age (years) 18-64 147 96.639 128.354 10.587 2 945 10 30 60 110 180 405 640 690 

Age (years) > 64 27 131.963 144.641 27.836 10 570 20 45 73 130 435 460 570 570 

Race White 311 70.071 89.462 5.0729 2 945 10 30 54 80 120 147 405 501 

Race Black 101 85.178 92.396 9.1937 5 570 15 35 60 110 140 185 460 468 

Race Asian 15 58 58.487 15.101 5 175 5 20 20 120 155 175 175 175 

Race Some Others 14 107.143 176.48 47.166 20 690 20 30 42.5 100 225 690 690 690 

Race Hispanic 24 65.542 71.515 14.598 15 370 20 30 42.5 87 90 120 370 370 

Race Refused 4 168 196.195 98.098 10 435 10 21 113.5 315 435 435 435 435 

Hispanic No 415 72.839 86.077 4.2253 2 945 10 30 55 90 125 165 420 468 

Hispanic Yes 46 83.913 138.922 20.483 7 690 15 30 37.5 85 145 370 690 690 

Hispanic DK 2 47.5 10.607 7.5 40 55 40 40 47.5 55 55 55 55 55 

Hispanic Refused 6 137.833 159.631 65.169 10 435 10 32 77.5 195 435 435 435 435 

Employment * 274 54.018 39.364 2.3781 5 370 10 29 49.5 70 100 120 150 179 

Employment Full Time 95 122.579 168.8 17.319 5 945 10 30 60 120 405 570 690 945 

Employment Part Time 34 83.265 79.298 13.6 2 468 10 40 60 100 135 185 468 468 

Employment Not Employed 61 80.262 69.212 8.8617 5 460 10 30 65 120 135 165 205 460 

Employment Refused 5 167.4 169.916 75.989 10 435 10 32 165 195 435 435 435 435 

Education * 295 55.302 44.964 2.6179 5 435 10 29 49 70 100 120 155 225 

Education < High School 25 120.4 124.272 24.854 10 570 30 45 90 135 195 405 570 570 

Education High School Graduate 57 111.579 116.718 15.46 10 501 20 45 73 120 225 435 468 501 

Education < College 38 108.842 133.431 21.645 10 640 20 40 75 120 195 605 640 640 

Education College Graduate 30 84.633 128.087 23.385 2 690 5 30 60 90 130 300 690 690 

Education Post Graduate 24 110.458 199.236 40.669 5 945 10 29 60 101.5 125 460 945 945 

Census Region Northeast 145 77.062 75.41 6.2624 7 435 15 30 60 95 135 180 435 435 

Census Region Midwest 102 69.676 103.283 10.227 2 945 10 30 55 85 120 125 175 468 

Census Region South 142 71.718 82.846 6.9523 5 570 10 30 50 80 135 180 460 501 

Census Region West 80 81.813 124.342 13.902 5 690 12.5 30 41.5 90 127.5 297.5 640 690 

Day Of Week Weekday 426 70.61 84.646 4.1011 2 690 10 30 50 85 120 165 435 501 

Day Of Week Weekend 43 114.651 152.229 23.215 10 945 20 45 90 120 180 300 945 945 

Season Winter 158 78.285 98.116 7.8057 5 690 10 30 58 90 125 180 435 605 

Season Spring 140 61.636 53.541 4.525 2 460 10 30 50 75 120 137.5 205 225 

Season Summer 94 86.617 116.695 12.036 5 945 10 30 60 95 155 225 435 945 

Season Fall 77 76.234 107.505 12.251 5 640 10 30 50 80 125 175 570 640 

Asthma No 413 76.448 96.792 4.7628 2 945 10 30 55 90 125 180 435 570 

Asthma Yes 50 55.36 39.329 5.562 5 195 10 30 47.5 71 115 135 165 195 

Asthma DK 6 111.5 161.48 65.924 10 435 10 32 46 100 435 435 435 435 

Angina No 459 73.373 91.312 4.2621 2 945 10 30 55 90 125 179 420 570 

Angina Yes 4 168.75 182.683 91.341 20 435 20 60 110 277.5 435 435 435 435 

Angina DK 6 109.5 162.362 66.284 10 435 10 30 41 100 435 435 435 435 

Bronchitis/Emphysema No 442 74.814 94.281 4.4845 2 945 10 30 55 90 125 180 435 570 

Bronchitis/Emphysema Yes 19 58.158 39.881 9.1493 10 155 10 30 55 65 125 155 155 155 

Bronchitis/Emphysema DK 8 104.625 137.907 48.757 10 435 10 28.5 67.5 100 435 435 435 435 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-126. Statistics for 24-Hour Cumulative Number of Minutes Spent Walking 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1639 29.6718 41.617 1.028 1 540 2 6 16 39 65 95 151 190 

Gender Male 755 32.4781 48.2611 1.7564 1 540 2 7 20 40 70 100 170 270 

Gender Female 883 27.2831 34.8259 1.172 1 360 2 6 15 35 60 94 140 171 

Gender Refused 1 20 * * 20 20 20 20 20 20 20 20 20 20 

Age (years) * 38 29.5263 23.7416 3.8514 1 100 2 10 25 40 60 80 100 100 

Age (years) 1-4 58 24.3276 26.3268 3.4569 1 160 2 10 15 35 60 60 70 160 

Age (years) 5-11 155 18.2129 21.0263 1.6889 1 170 1 5 10 25 40 60 65 100 

Age (years) 12-17 223 25.8341 32.3753 2.168 1 190 2 6 15 30 60 100 135 151 

Age (years) 18-64 944 31.8252 44.9705 1.4637 1 410 2 6 18.5 40 70 110 171 250 

Age (years) > 64 221 33.81 49.3278 3.3181 1 540 2 10 20 45 73 95 155 180 

Race White 1289 29.5912 43.6801 1.2166 1 540 2 6 15 35 65 100 160 225 

Race Black 175 34.8114 39.7274 3.0031 1 250 2 10 20 50 75 125 160 194 

Race Asian 36 26.5556 24.6535 4.1089 1 100 1 10 20 30 60 78 100 100 

Race Some Others 30 23.7667 21.2192 3.8741 1 60 1 6 17 43 60 60 60 60 

Race Hispanic 88 23.0795 21.1058 2.2499 1 100 2 5.5 15 37 50 60 92 100 

Race Refused 21 33.1905 32.9555 7.1915 4 150 8 15 20 40 65 65 150 150 

Hispanic No 1467 29.8718 41.0288 1.0712 1 410 2 6 16 40 65 100 155 194 

Hispanic Yes 144 26.8403 48.7064 4.0589 1 540 2 5.5 15 35 60 70 100 135 

Hispanic DK 10 30.2 28.8359 9.1187 2 80 2 10 17.5 55 77.5 80 80 80 

Hispanic Refused 18 35.7222 34.7847 8.1988 8 150 8 15 25 55 65 150 150 150 

Employment * 431 22.768 28.0141 1.3494 1 190 2 5 13 30 55 65 131 151 

Employment Full Time 561 30.9519 43.7734 1.8481 1 365 2 7 16 40 70 100 180 250 

Employment Part Time 153 26.8693 37.1231 3.0012 1 295 2 5 15 35 60 92 135 165 

Employment Not Employed 482 35.5249 49.4109 2.2506 1 540 2 10 20 50 75 120 150 250 

Employment Refused 12 18.4167 13.4601 3.8856 5 55 5 10 16.5 20 30 55 55 55 

Education * 472 22.6737 27.6375 1.2721 1 190 2 5 13 30 55 65 130 151 

Education < High School 138 42.7174 71.9429 6.1242 1 540 3 7 20 50 115 145 360 365 

Education High School Graduate 366 29.2596 41.5618 2.1725 1 410 2 5 18 35 65 100 150 240 

Education < College 288 32.5313 39.3063 2.3161 1 295 2 9.5 20 45 75 100 160 180 

Education College Graduate 210 29.7667 38.813 2.6784 1 300 2 8 18.5 40 60 90 140 225 

Education Post Graduate 165 34.5818 44.6107 3.4729 1 360 2 10 20 45 80 95 180 200 

Census Region Northeast 507 34.9172 45.2549 2.0098 1 365 2 10 20 45 75 107 170 250 

Census Region Midwest 321 29.271 46.8743 2.6163 1 540 2 6 15 31 60 105 160 180 

Census Region South 423 24.9976 37.6654 1.8314 1 410 2 5 10 30 60 80 135 171 

Census Region West 388 28.2448 35.029 1.7783 1 285 2 8 15 40 60 90 140 180 

Day Of Week Weekday 1182 29.2902 39.1911 1.1399 1 540 2 7 18 40 65 92 145 180 

Day Of Week Weekend 457 30.6586 47.3511 2.215 1 410 2 5 15 35 60 120 171 200 

Season Winter 412 32.3034 47.7062 2.3503 1 365 2 6 20 38.5 75 120 180 250 

Season Spring 459 28.854 41.54 1.9389 1 540 2 6 16 35 60 90 146 180 

Season Summer 475 26.6084 31.325 1.4373 1 270 2 6 15 35 60 85 123 160 

Season Fall 293 32.2184 46.6936 2.7279 1 410 2 8 20 45 61 105 155 295 

Asthma No 1504 29.6011 41.9939 1.0828 1 540 2 6 16 35.5 65 95 152 190 

Asthma Yes 120 29.7417 38.3451 3.5004 1 250 2 5 15 40 70 117.5 135 150 

Asthma DK 15 36.2 27.8162 7.1821 5 90 5 10 30 60 75 90 90 90 

Angina No 1578 29.5076 41.4718 1.044 1 540 2 6 16 38 65 95 151 190 

Angina Yes 44 29 36.0633 5.4367 2 150 4 6 14.5 36 60 115 150 150 

Angina DK 17 46.6471 63.1456 15.3151 5 270 5 10 30 60 90 270 270 270 

Bronchitis/Emphysema No 1553 29.7173 42.1023 1.0684 1 540 2 6 16 38 65 95 151 194 

Bronchitis/Emphysema Yes 67 26.9851 31.8774 3.8944 1 165 2 5 16 40 60 90 130 165 

Bronchitis/Emphysema DK 19 35.4211 31.3658 7.1958 3 110 3 10 30 60 90 110 110 110 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-127. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Bicycle/Skateboard/Rollerskate 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 115 45.1217 53.35 4.9749 1 400 5 11 30 60 102 151 195 205 

Gender Male 82 43.2073 56.113 6.1966 1 400 5 10 27.5 50 90 120 195 400 

Gender Female 33 49.8788 46.228 8.0472 5 205 5 15 45 60 105 165 205 205 

Age (years) * 2 15 7.071 5 10 20 10 10 15 20 20 20 20 20 

Age (years) 1-4 2 20 14.142 10 10 30 10 10 20 30 30 30 30 30 

Age (years) 5-11 18 40.2778 52.985 12.4886 1 195 1 10 15 55 151 195 195 195 

Age (years) 12-17 33 31.9697 27.929 4.8618 2 115 5 10 25 45 65 102 115 115 

Age (years) 18-64 53 53.2264 62.916 8.6422 5 400 5 20 30 65 105 165 180 400 

Age (years) > 64 7 74 67.295 25.4353 23 205 23 25 35 110 205 205 205 205 

Race White 98 46.7245 56.914 5.7492 1 400 5 11 30 60 110 165 205 400 

Race Black 7 41.1429 21.737 8.2156 5 65 5 25 50 60 65 65 65 65 

Race Asian 2 6 1.414 1 5 7 5 5 6 7 7 7 7 7 

Race Some Others 4 47.5 23.629 11.8145 30 80 30 30 40 65 80 80 80 80 

Race Hispanic 3 33.3333 25.166 14.5297 10 60 10 10 30 60 60 60 60 60 

Race Refused 1 20 * * 20 20 20 20 20 20 20 20 20 20 

Hispanic No 106 45.8679 55.172 5.3587 1 400 5 10 30 60 105 151 195 205 

Hispanic Yes 8 38.375 23.323 8.2461 10 80 10 23.5 30 55 80 80 80 80 

Hispanic Refused 1 20 * * 20 20 20 20 20 20 20 20 20 20 

Employment * 52 33.8462 38.258 5.3054 1 195 2 10 20 47.5 65 115 151 195 

Employment Full Time 27 56.8519 76.863 14.7923 5 400 5 15 30 60 115 120 400 400 

Employment Part Time 7 40.8571 24.768 9.3616 10 90 10 30 35 46 90 90 90 90 

Employment Not Employed 27 55.4815 54.258 10.442 5 205 5 20 30 90 165 180 205 205 

Employment Refused 2 55 49.497 35 20 90 20 20 55 90 90 90 90 90 

Education * 56 33.3929 36.945 4.937 1 195 2 10 20 45 65 115 151 195 

Education < High School 3 98.3333 77.835 44.9382 25 180 25 25 90 180 180 180 180 180 

Education High School Graduate 18 41.5556 49.048 11.5606 5 205 5 15 30 46 100 205 205 205 

Education < College 18 42.9444 35.049 8.261 5 120 5 20 30 60 115 120 120 120 

Education College Graduate 11 89.8182 111.308 33.5605 15 400 15 25 53 90 165 400 400 400 

Education Post Graduate 9 57.2222 38.415 12.8049 5 110 5 20 60 90 110 110 110 110 

Census Region Northeast 20 42.05 35.057 7.839 5 102 5 10 32.5 77.5 95 101 102 102 

Census Region Midwest 24 39.125 47.505 9.6969 2 180 5 10 18.5 57.5 90 165 180 180 

Census Region South 26 64.6923 87.03 17.0681 1 400 2 15 32.5 75 195 205 400 400 

Census Region West 45 38.3778 32.614 4.8619 5 151 5 18 30 50 80 115 151 151 

Day Of Week Weekday 83 44.5783 56.02 6.149 5 400 5 15 30 60 90 151 205 400 

Day Of Week Weekend 32 46.5313 46.508 8.2215 1 195 2 10 32.5 75 110 120 195 195 

Season Winter 20 38.6 44.951 10.0513 1 205 3.5 12.5 27.5 47.5 75 147.5 205 205 

Season Spring 46 34.7826 35.036 5.1657 5 195 5 10 22.5 46 80 90 195 195 

Season Summer 34 61.7059 72.243 12.3896 2 400 5 20 42.5 90 115 165 400 400 

Season Fall 15 47.9333 55.663 14.3721 2 180 2 10 20 75 151 180 180 180 

Asthma No 95 48.5368 57.246 5.8733 1 400 5 15 30 60 110 165 205 400 

Asthma Yes 18 29.3333 24.22 5.7086 5 90 5 7 32.5 40 60 90 90 90 

Asthma DK 2 25 7.071 5 20 30 20 20 25 30 30 30 30 30 

Angina No 114 45.3421 53.533 5.0138 1 400 5 11 30 60 102 151 195 205 

Angina DK 1 20 * * 20 20 20 20 20 20 20 20 20 20 

Bronchitis/Emphysema No 109 45.1284 53.909 5.1636 1 400 5 15 30 60 102 151 195 205 

Bronchitis/Emphysema Yes 5 50 49.624 22.1923 5 115 5 10 30 90 115 115 115 115 

Bronchitis/Emphysema DK 1 20 * * 20 20 20 20 20 20 20 20 20 20 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-128. Statistics for 24-Hour Cumulative Number of Minutes Spent Waiting on a Bus, Train, etc. Stop 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 151 18.702 18.7513 1.526 1 128 4 7 15 20 40 45 67 120 

Gender Male 61 16.3443 17.9934 2.3038 1 120 4 5 11 20 30 45 65 120 

Gender Female 90 20.3 19.1818 2.02319 1 128 4 10 15 30 42.5 60 75 128 

Age (years) * 2 21 5.6569 4 17 25 17 17 21 25 25 25 25 25 

Age (years) 1-4 2 8 9.8995 7 1 15 1 1 8 15 15 15 15 15 

Age (years) 5-11 32 12.5 10.7283 1.8965 2 45 2 5 10 15 20 43 45 45 

Age (years) 12-17 50 13.78 11.4843 1.6241 1 74 3 5 10 20 23 30 52.5 75 

Age (years) 18-64 54 25.5 25.616 3.4859 1 128 5 10 15 30 60 67 120 128 

Age (years) > 64 11 27.2727 13.484 4.0656 5 45 5 20 30 40 45 45 45 45 

Race White 115 18.2522 17.9501 1.6739 1 128 4 5 15 22 40 45 67 75 

Race Black 21 17.4762 11.9901 2.6164 1 45 3 10 15 23 35 40 45 45 

Race Asian 3 10 5 2.8868 5 15 5 5 10 15 15 15 15 15 

Race Some Others 1 15 * * 15 15 15 15 15 15 15 15 15 15 

Race Hispanic 10 29.8 35.8137 11.3253 5 120 5 10 16.5 20 92.5 120 120 120 

Race Refused 1 15 * * 15 15 15 15 15 15 15 15 15 15 

Hispanic No 136 18.0956 17.1036 1.4666 1 128 4 6 15 22.5 40 45 67 75 

Hispanic Yes 13 25.2308 32.4427 8.998 1 120 1 10 15 20 65 120 120 120 

Hispanic DK 1 20 * * 20 20 20 20 20 20 20 20 20 20 

Hispanic Refused 1 15 * * 15 15 15 15 15 15 15 15 15 15 

Employment * 79 13.1646 11.3707 1.2793 1 75 2 5 10 15 23 35 45 75 

Employment Full Time 31 24.9355 24.8125 4.4565 1 128 5 10 15 30 45 65 128 128 

Employment Part Time 15 31.6667 31.5179 8.1379 5 120 5 10 17 45 67 120 120 120 

Employment Not Employed 26 20.6154 12.7061 2.4919 5 45 5 10 20 30 40 45 45 45 

Education * 87 12.931 10.9723 1.1763 1 75 3 5 10 15 23 30 45 75 

Education < High School 6 32.5 11.726 4.7871 15 45 15 25 32.5 45 45 45 45 45 

Education High School Graduate 25 23.56 24.5749 4.915 5 120 5 10 15 30 45 67 120 120 

Education < College 9 28.333 19.2029 6.401 10 60 10 10 20 45 60 60 60 60 

Education College Graduate 16 33.8125 31.1239 7.781 5 128 5 10 30 37.5 65 128 128 128 

Education Post Graduate 8 14.875 8.3741 2.9607 1 30 1 40.5 15 18.5 30 30 30 30 

Census Region Northeast 63 20.4921 23.43 2.9519 1 128 3 6 15 22 40 65 120 128 

Census Region Midwest 27 17.4074 13.1244 2.5258 3 60 4 5 15 20 35 35 60 60 

Census Region South 39 19.8205 16.6684 2.6691 4 75 5 10 15 28 45 65 75 75 

Census Region West 22 13.1818 11.3458 2.4189 1 45 1 5 10 15 30 30 45 45 

Day Of Week Weekday 128 17.7891 18.9656 1.6763 1 128 3 5.5 15 20 35 45 75 120 

Day Of Week Weekend 23 23.7826 17.0026 3.5453 5 65 5 10 20 35 45 60 65 65 

Season Winter 55 19.9273 15.5693 2.0994 1 75 2 10 15 25 43 60 65 75 

Season Spring 43 17.186 20.6574 3.1502 1 120 4 5 10 20 33 45 120 120 

Season Summer 28 24 25.4675 4.8129 5 128 5 10 15 32.5 45 67 128 128 

Season Fall 25 12.68 9.8815 1.9763 1 45 4 5 10 15 20 35 45 45 

Asthma No 139 18.7698 18.7788 1.5928 1 128 3 10 15 20 40 45 75 120 

Asthma Yes 10 20 20.5372 6.4944 4 65 4 5 12 30 55 65 65 65 

Asthma DK 2 7.5 3.5355 2.5 5 10 5 5 7.5 10 10 10 10 10 

Angina No 151 18.702 18.7513 1.526 1 128 4 7 15 20 40 45 67 120 

Bronchitis/Emphysema No 145 18.6552 18.969 1.5753 1 128 4 6 15 20 40 45 75 120 

Bronchitis/Emphysema Yes 6 19.8333 13.5561 5.5342 9 45 9 10 16 23 45 45 45 45 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-129. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Train/Subway/Rapid Transit 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Mi Max 5 25 50 75 90 95 98 99 n 

All 116 97.767 136.346 12.659 1 810 5 27.5 60 120 189 415 690 720 

Gender Male 62 91.613 119.437 15.168 5 720 10 24 60 120 180 240 480 720 

Gender Female 54 104.833 154.349 21.004 1 810 2 30 60 120 195 480 690 810 

Age (years) * 8 191.875 256.82 90.8 20 810 20 55 117.5 180 810 810 810 810 

Age (years) 1-4 2 92.5 38.891 27.5 65 120 65 65 92.5 120 120 120 120 120 

Age (years) 5-11 3 166.667 271.401 156.693 5 480 5 5 15 480 480 480 480 480 

Age (years) 12-17 2 100 56.569 40 60 140 60 60 100 140 140 140 140 140 

Age (years) 18-64 92 84.967 106.533 11.107 1 720 5 30 60 104.5 175 240 480 720 

Age (years) > 64 9 122.667 219.531 73.177 10 690 10 10 24 120 690 690 690 690 

Race White 64 89.5 139.691 17.461 1 720 5 22 55 74 195 380 690 720 

Race Black 26 131.385 168.356 33.017 5 810 10 35 117.5 135 195 480 810 810 

Race Asian 3 79.667 17.039 9.838 60 90 60 60 89 90 90 90 90 90 

Race Some Others 4 71.25 47.675 23.838 30 140 30 42.5 57.5 100 140 140 140 140 

Race Hispanic 16 88.625 98.922 24.731 5 415 5 20 70 112.5 165 415 415 415 

Race Refused 3 85 56.347 32.532 20 120 20 20 115 120 120 120 120 120 

Hispanic No 89 101.281 149.687 15.867 1 810 5 25 60 120 195 480 720 810 

Hispanic Yes 22 86.955 85.561 18.242 5 415 10 40 70 120 130 165 415 415 

Hispanic DK 2 79.5 34.648 24.5 55 104 55 55 79.5 104 104 104 104 104 

Hispanic Refused 3 85 56.347 32.532 20 120 20 20 115 120 120 120 120 120 

Employment * 7 126.429 163.598 61.834 5 480 5 15 65 140 480 480 480 480 

Employment Full Time 76 98.526 128.056 14.689 1 720 5 30 60 120 189 380 690 720 

Employment Part Time 10 61.7 46.375 14.665 5 160 5 15 57.5 89 125 160 160 160 

Employment Not Employed 21 101.714 186.201 40.632 1 810 10 10 55 90 165 415 810 810 

Employment Refused 2 107.5 123.744 87.5 20 195 20 20 107.5 195 195 195 195 195 

Education * 10 122 140.024 44.279 5 480 5 20 92.5 140 337.5 480 480 480 

Education < High School 6 181.833 311.76 127.275 1 810 1 5 70 135 810 810 810 810 

Education High School Graduate 30 89.433 109.191 19.935 1 480 2 30 60 120 177.5 415 480 480 

Education < College 26 125.692 189.64 37.192 10 720 10 20 60 120 380 690 720 720 

Education College Graduate 24 66.5 50.332 10.274 5 180 10 24.5 55 102.5 125 175 180 180 

Education Post Graduate 20 74.15 59.415 13.286 10 240 12.5 30 60 97 164.5 214.5 240 240 

Census Region Northeast 72 111.847 134.554 15.857 10 810 20 49 62.5 122.5 189 415 690 810 

Census Region Midwest 14 64.214 109.483 29.261 2 380 2 10 22.5 50 240 380 380 380 

Census Region South 15 75.733 121.139 31.278 1 480 1 10 30 90 160 480 480 480 

Census Region West 15 83.533 179.444 46.332 5 720 5 10 30 75 120 720 720 720 

Day Of Week Weekday 96 101.604 127.189 12.981 1 720 10 30 60 120 195 415 690 720 

Day Of Week Weekend 20 79.35 176.643 39.499 2 810 3.5 7.5 32.5 60 120 465 810 810 

Season Winter 26 138.192 196.327 38.503 5 810 10 30 79.5 130 240 720 810 810 

Season Spring 29 77.276 89.479 16.616 2 480 5 25 60 105 135 175 480 480 

Season Summer 37 106.081 140.735 23.137 5 690 10 30 60 120 195 480 690 690 

Season Fall 24 65.917 82.217 16.782 1 380 1 15 42.5 82.5 160 180 380 380 

Asthma No 106 94.151 122.865 11.934 1 720 5 30 60 120 180 380 480 690 

Asthma Yes 7 146.571 294.036 111.135 1 810 1 10 30 90 810 810 810 810 

Asthma DK 3 111.667 87.797 50.69 20 195 20 20 120 195 195 195 195 195 

Angina No 112 96.527 137.946 13.035 1 810 5 27.5 60 117.5 175 415 690 720 

Angina DK 4 132.5 82.916 41.458 20 195 20 70 157.5 195 195 195 195 195 

Bronchitis/Emphysema No 112 98.179 138.009 13.041 1 810 5 30 60 120 180 415 690 720 

Bronchitis/Emphysema Yes 1 10 * * 10 10 10 10 10 10 10 10 10 10 

Bronchitis/Emphysema DK 3 111.667 87.797 50.69 20 195 20 20 120 195 195 195 195 195 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-130. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on an Airplane 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 53 234 203.736 27.985 10 900 15 70 210 300 480 660 900 900 

Gender Male 28 241.25 230.979 43.651 15 900 20 65 210 292.5 555 900 900 900 

Gender Female 25 225.88 172.581 34.516 10 660 15 110 210 300 480 510 660 660 

Age (years) * 3 175 145.688 84.113 15 300 15 15 210 300 300 300 300 300 

Age (years) 12-17 3 113.333 118.568 68.455 15 245 15 15 80 245 245 245 245 245 

Age (years) 18-64 42 226.429 193.962 29.929 10 900 20 60 202.5 300 480 555 900 900 

Age (years) > 64 5 405.4 292.392 130.762 195 900 195 210 287 435 900 900 900 900 

Race White 44 241.068 215.555 32.496 10 900 15 65 210 300 510 660 900 900 

Race Black 7 199.286 134.364 50.785 15 435 15 110 210 255 435 435 435 435 

Race Asian 1 60 * * 60 60 60 60 60 60 60 60 60 60 

Race Hispanic 1 340 * * 340 340 340 340 340 340 340 340 340 340 

Hispanic No 51 234.745 206.224 28.877 10 900 15 60 210 300 480 660 900 900 

Hispanic Yes 2 215 176.777 125 90 340 90 90 215 340 340 340 340 340 

Employment * 3 113.333 118.568 68.455 15 245 15 15 80 245 245 245 245 245 

Employment Full Time 33 212.424 194.008 33.773 15 900 20 60 180 285 480 555 900 900 

Employment Part Time 3 510 375.899 217.025 150 900 150 150 480 900 900 900 900 900 

Employment Not Employed 13 259.385 168.387 46.702 10 660 10 195 225 300 435 660 660 660 

Employment Refused 1 150 * * 150 150 150 150 150 150 150 150 150 150 

Education * 4 122.5 98.531 49.265 15 245 15 47.5 115 197.5 245 245 245 245 

Education < High School 4 111.25 179.647 89.823 10 380 10 12.5 27.5 210 380 380 380 380 

Education High School Graduate 9 253.889 191.046 63.682 15 660 15 195 270 285 660 660 660 660 

Education < College 13 293.846 170.784 47.367 20 555 20 180 300 435 510 555 555 555 

Education College Graduate 15 194.8 113.998 29.434 45 480 45 90 210 255 287 480 480 480 

Education Post Graduate 8 305 375.129 132.628 20 900 20 45 137.5 577.5 900 900 900 900 

Census Region Northeast 17 254.706 234.81 56.95 15 900 15 70 245 380 510 900 900 900 

Census Region Midwest 17 235.118 234.348 56.838 15 900 15 60 195 287 660 900 900 900 

Census Region South 9 212.778 103.565 34.522 15 340 15 150 255 270 340 340 340 340 

Census Region West 10 216 181.702 57.459 10 555 10 45 202.5 240 517.5 555 555 555 

Day Of Week Weekday 37 258.919 192.755 31.689 15 900 15 150 230 305 510 660 900 900 

Day Of Week Weekend 16 176.375 222.825 55.706 10 900 10 37.5 95 262.5 360 900 900 900 

Season Winter 17 216.294 172.818 41.914 20 660 20 60 210 275 480 660 660 660 

Season Spring 14 191.786 160.547 42.908 15 555 15 90 150 230 435 555 555 555 

Season Summer 17 230.882 222.171 53.884 10 900 10 60 245 300 480 900 900 900 

Season Fall 5 423 294.398 131.659 180 900 180 240 285 510 900 900 900 900 

Asthma No 51 224.843 201.484 28.213 10 900 15 60 210 287 480 660 900 900 

Asthma Yes 2 467.5 123.744 87.5 380 555 380 380 467.5 555 555 555 555 555 

Angina No 51 233.725 207.562 29.064 10 900 15 60 210 300 480 660 900 900 

Angina Yes 2 241 65.054 46 195 287 195 195 241 287 287 287 287 287 

Bronchitis/Emphysema No 51 231.608 206.7 28.944 10 900 15 60 210 300 480 660 900 900 

Bronchitis/Emphysema Yes 2 295 120.208 85 210 380 210 210 295 380 380 380 380 380 

Note: A "*" Signifies missing data. Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev 

= standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage

of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-131. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors in a Residence (all rooms) 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 9343 1001.39 275.143 2.8465 8 1440 575 795 985 1235 1395 1440 1440 1440 

Gender Male 4269 945.9 273.498 4.1859 8 1440 540 750 900 1160 1350 1430 1440 1440 

Gender Female 5070 1048.07 267.864 3.7619 30 1440 620 840 1050 1280 1420 1440 1440 1440 

Gender Refused 4 1060 135.647 67.8233 900 1200 900 950 1070 1170 1200 1200 1200 1200 

Age (years) * 187 1001.07 279.866 20.4658 265 1440 565 799 955 1230 1440 1440 1440 1440 

Age (years) 1-4 498 1211.64 218.745 9.8022 270 1440 795 1065 1260 1410 1440 1440 1440 1440 

Age (years) 5-11 700 1005.13 222.335 8.4035 190 1440 686 845 975 1165 1334 1412.5 1440 1440 

Age (years) 12-17 588 969.5 241.776 9.9707 95 1440 585 811.5 950 1155 1310 1405 1440 1440 

Age (years) 18-64 6022 947.91 273.033 3.5184 8 1440 540 750 900 1165 1350 1428 1440 1440 

Age (years) > 64 1348 1174.64 229.344 6.2466 60 1440 760 1030 1210 1375 1440 1440 1440 1440 

Race White 7556 999.36 275.678 3.1714 8 1440 570 795 980 1235 1395 1440 1440 1440 

Race Black 941 1015.95 272.54 8.8845 190 1440 600 815 1000 1245 1410 1440 1440 1440 

Race Asian 157 983.52 254.689 20.3264 30 1440 600 810 930 1180 1355 1420 1440 1440 

Race Some Others 181 996.09 268.283 19.9413 10 1440 604 805 975 1198 1380 1440 1440 1440 

Race Hispanic 382 1009.4 281.75 14.4156 55 1440 555 810 1004.5 1250 1410 1440 1440 1440 

Race Refused 126 1019.69 276.578 24.6396 270 1440 575 840 975 1255 1440 1440 1440 1440 

Hispanic No 8498 1000.38 275.436 2.9879 8 1440 575 795 980 1235 1395 1440 1440 1440 

Hispanic Yes 696 1009.84 270.816 10.2653 55 1440 585 810 1000 1230 1405 1440 1440 1440 

Hispanic DK 46 1097.87 286.655 42.265 401 1440 645 835 1172.5 1355 1440 1440 1440 1440 

Hispanic Refused 103 984.08 269.485 26.5531 270 1440 565 810 950 1200 1375 1440 1440 1440 

Employment * 1768 1053.3 248.46 5.909 95 1440 675 870 1030 1255 1413 1440 1440 1440 

Employment Full Time 4068 881.03 259.166 4.0634 8 1440 515 715 835 1045.5 1290 1385 1440 1440 

Employment Part Time 797 982.44 243.085 8.6105 255 1440 600 820 970 1170 1320 1380 1440 1440 

Employment Not Employed 2639 1158.03 233.775 4.5507 60 1440 735 1015 1190 1350 1440 1440 1440 1440 

Employment Refused 71 995.08 268.059 31.8128 445 1440 575 810 940 1255 1440 1440 1440 1440 

Education * 1963 1044.47 251.888 5.6852 95 1440 660 855 1020 1254 1410 1440 1440 1440 

Education < High School 829 1093.37 278.592 9.6759 150 1440 630 870 1130 1345 1440 1440 1440 1440 

Education High School Graduate 2602 1008.1 279.281 5.4751 30 1440 565 803 995 1245 1400 1440 1440 1440 

Education < College 1788 974.34 272.599 6.4468 10 1440 570 775 930 1205 1371 1436 1440 1440 

Education College Graduate 1240 939.49 275.004 7.8096 30 1440 528 745 885 1165 1335 1427.5 1440 1440 

Education Post Graduate 921 943.67 274.27 9.0375 8 1440 540 750 900 1155 1350 1410 1440 1440 

Census Region Northeast 2068 1003.4 278.441 6.1229 30 1440 570 795 980 1245 1405 1440 1440 1440 

Census Region Midwest 2087 1001.73 280.646 6.1432 8 1440 565 790 989 1250 1390 1440 1440 1440 

Census Region South 3230 999 270.19 4.7541 10 1440 585 800 970 1228 1400 1440 1440 1440 

Census Region West 1958 1002.84 273.992 6.192 30 1440 575 800 1000 1230 1390 1440 1440 1440 

Day Of Week Weekday 6286 965.69 272.596 3.4382 30 1440 567 770 911 1190 1380 1440 1440 1440 

Day Of Week Weekend 3057 1074.81 265.676 4.8051 8 1440 615 895 1105 1290 1420 1440 1440 1440 

Season Winter 2513 1034.92 278.237 5.5503 30 1440 590 825 1015 1285 1432 1440 1440 1440 

Season Spring 2424 977.88 267.177 5.4267 10 1440 580 780 955 1185 1370 1435 1440 1440 

Season Summer 2522 980.52 273.962 5.4553 8 1440 555 785 960 1201 1365 1440 1440 1440 

Season Fall 1884 1014.84 277.47 6.3926 30 1440 589 805 997 1260 1405 1440 1440 1440 

Asthma No 8591 999.12 274.377 2.9602 8 1440 576 795 980 1230 1393 1440 1440 1440 

Asthma Yes 689 1027.42 284.437 10.8362 190 1440 555 825 1025 1260 1430 1440 1440 1440 

Asthma DK 63 1025.68 264.342 33.3039 445 1440 630 840 960 1315 1410 1440 1440 1440 

Angina No 9019 997.77 274.112 2.8863 8 1440 575 795 975 1230 1391 1440 1440 1440 

Angina Yes 249 1125.47 281.353 17.83 180 1440 660 925 1185 1380 1440 1440 1440 1440 

Angina DK 75 1024.08 285.059 32.9158 150 1440 560 840 975 1305 1425 1440 1440 1440 

Bronchitis/Emphysema No 8840 997.66 274.78 2.9225 8 1440 575 795 975 1230 1395 1440 1440 1440 

Bronchitis/Emphysema Yes 432 1070.48 273.759 13.1712 205 1440 585 867.5 1110 1292.5 1440 1440 1440 1440 

Bronchitis/Emphysema DK 71 1045.48 273.047 32.4047 445 1440 565 845 975 1320 1440 1440 1440 1440 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996. 
Table 15-132. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors (outside the residence) 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 3124 154.03 158.302 2.8322 1 1290 5 40 105 210 362 480 610 715 

Gender Male 1533 174.908 173.671 4.4356 1 1290 10 60 120 240 420 540 680 745 

Gender Female 1588 133.524 138.801 3.4831 1 1065 5 30 90 190 325 415 525 610 

Gender Refused 3 340 140 80.829 240 500 240 240 280 500 500 500 500 500 

Age (years) * 40 163.95 179.615 28.3996 2 720 3.5 40 107.5 212.5 430 600 720 720 

Age (years) 1-4 201 195.652 163.732 11.5488 3 715 30 75 135 270 430 535 625 699 

Age (years) 5-11 353 187.564 158.575 8.4401 4 1250 20 80 150 265 365 479 600 720 

Age (years) 12-17 219 135.26 137.031 9.2597 1 720 5 35 100 190 300 452 545 610 

Age (years) 18-64 1809 144.244 155.13 3.6473 1 1080 5 30 90 199 360 470 600 715 

Age (years) > 64 502 156.448 168.259 7.5098 1 1290 5 36 110 210 375 485 645 735 

Race White 2622 156.787 160.173 3.1281 1 1290 5 45 105 215 375 485 625 720 

Race Black 255 141.557 153.169 9.5918 1 1250 5 30 95 195 330 420 535 645 

Race Asian 34 115.765 135.554 23.2474 1 480 5 20 60 150 360 450 480 480 

Race Some Others 53 167 149.049 20.4735 3 750 5 60 130 238 320 475 553 750 

Race Hispanic 125 117.28 128.886 11.5279 1 720 5 30 70 150 270 355 590 610 

Race Refused 35 187.143 163.771 27.6824 5 600 5 60 170 240 450 510 600 600 

Hispanic No 2857 153.812 158.38 2.9631 1 1290 5 40 105 210 362 480 610 720 

Hispanic Yes 222 146.405 154.069 10.3405 1 750 5 30 112.5 200 345 480 640 690 

Hispanic DK 15 191.533 178.278 46.0312 15 585 15 40 140 380 420 585 585 585 

Hispanic Refused 30 212.5 165.335 30.186 5 600 5 60 180 345 457.5 510 600 600 

Employment * 774 175.762 156.127 5.6119 1 1250 15 60 125 245 380 480 610 705 

Employment Full Time 1110 141.308 159.947 4.8008 1 1080 5 30 85 195 358.5 490 660 745 

Employment Part Time 240 134.663 140.78 9.0873 1 1080 5 30 90 182.5 332.5 422.5 485 525 

Employment Not Employed 978 156.052 159.151 5.0891 1 1290 5 40 115 220 375 480 610 701 

Employment Refused 22 152.727 209.828 44.7355 5 660 5 15 60 125 555 600 660 660 

Education * 825 174.105 156.184 5.4376 1 1250 15 60 125 240 380 480 610 699 

Education < High School 306 171.941 188.396 10.7699 1 1290 7 45 120 240 405 510 765 855 

Education High School Graduate 837 153.633 154.781 5.35 1 840 5 35 105 215 380 480 598 701 

Education < College 527 143.362 157.106 6.8436 1 1080 5 30 90 195 360 465 615 720 

Education College Graduate 355 126.868 142.575 7.5671 1 750 5 30 80 170 300 415 615 690 

Education Post Graduate 274 130.504 150.996 9.122 1 1065 5 30 75 180 325 465 570 660 

Census Region Northeast 635 147.967 143.678 5.7017 1 750 5 35 105 215 345 450 575 610 

Census Region Midwest 639 156.028 169.151 6.6915 1 1290 5 45 102 210 360 500 655 750 

Census Region South 1120 158.577 165.201 4.9363 1 1080 5 40 110 210 390 495 640 745 

Census Region West 730 150.579 149.63 5.5381 1 855 5 36 105 213 360 465 575 660 

Day Of Week Weekday 1933 141.157 148.958 3.388 1 1250 5 31 90 190 345 452 598 698 

Day Of Week Weekend 1191 174.924 170.399 4.9375 1 1290 10 50 120 260 400 500 660 745 

Season Winter 548 113.96 138.121 5.9002 1 1080 5 25 60 150 280 380 540 690 

Season Spring 1034 171.915 159.391 4.9568 1 990 10 60 120 240 390 495 645 730 

Season Summer 1098 168.309 168.2 5.076 1 1290 5 50 120 235 400 510 630 715 

Season Fall 444 126.525 140.747 6.6796 1 960 5 30 75 162.5 313 420 575 655 

Asthma No 2869 154.516 159.172 2.9717 1 1290 5 40 105 210 365 480 615 720 

Asthma Yes 236 145.835 145.523 9.4727 1 885 5 45 105 190 360 450 575 610 

Asthma DK 19 182.421 181.024 41.5298 1 600 1 60 120 300 480 600 600 600 

Angina No 3023 153.218 156.257 2.842 1 1290 5 40 105 210 360 479 610 707 

Angina Yes 76 172.855 222.319 25.5017 2 1080 5 30 68.5 252.5 465 660 1065 1080 

Angina DK 25 195 170.434 34.0869 5 600 5 60 150 300 465 480 600 600 

Bronchitis/Emphysema No 2968 154.884 158.787 2.9146 1 1290 5 40 105 210 367 480 615 715 

Bronchitis/Emphysema Yes 139 129.353 142.494 12.0862 1 855 5 30 75 175 327 415 553 735 

Bronchitis/Emphysema DK 17 206.765 179.765 43.5994 5 600 5 60 170 300 480 600 600 600 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-133. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling Inside a Vehicle 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 7743 97.278 104.938 1.1926 1 1440 12 40 70 120 190 270 425 570 

Gender Male 3603 103.696 119.736 1.9948 1 1440 10 40 70 120 205 295 478 655 

Gender Female 4138 91.721 89.756 1.3953 1 995 12 40 70 115 180 240 385 465 

Gender Refused 2 30 14.142 10 20 40 20 20 30 40 40 40 40 40 

Age (years) * 144 117.035 129.103 10.7586 5 810 20 40 80 142.5 210 435 593 660 

Age (years) 1-4 335 68.116 75.531 4.1267 1 955 10 30 47 85 150 200 245 270 

Age (years) 5-11 571 71.033 77.62 3.2483 1 900 10 25 51 90 140 171 275 360 

Age (years) 12-17 500 81.53 79.8 3.5687 1 790 10 30 60 100 165.5 232.5 345 405 

Age (years) 18-64 5286 104.011 111.1 1.5281 1 1440 15 43 75 120 200 285 450 620 

Age (years) > 64 907 90.87 93.881 3.1173 4 900 10 35 60 120 190 258 400 460 

Race White 6288 97.248 107.173 1.3515 1 1440 10 40 70 120 190 270 425 595 

Race Black 766 98.723 91.337 3.3001 2 810 15 45 75 120 195 265 390 485 

Race Asian 133 83.414 74.929 6.4972 5 540 20 35 70 105 150 210 330 360 

Race Some Others 144 96.181 93.965 7.8304 3 690 10 40 69.5 127.5 180 250 345 540 

Race Hispanic 319 101.734 110.376 6.1799 2 825 20 41 70 120 190 335 465 620 

Race Refused 93 93.591 90.073 9.3401 10 480 15 30 65 120 205 255 420 480 

Hispanic No 7050 97.149 104.847 1.2487 1 1440 10 40 70 120 190 270 420 566 

Hispanic Yes 578 100.043 109.048 4.5358 2 825 15 40 70 120 190 285 480 630 

Hispanic DK 34 73 68.279 11.7098 5 325 6 25 60 97 175 200 325 325 

Hispanic Refused 81 98.914 95.273 10.5859 10 480 15 30 65 130 220 255 420 480 

Employment * 1388 73.609 77.782 2.0878 1 955 10 30 55 90 150 195 275 382 

Employment Full Time 3732 105.816 116.18 1.9018 4 1440 16 45 75 124 198 290 475 660 

Employment Part Time 720 98.763 94.999 3.5404 2 960 10 45 75 120 195 260 380 470 

Employment Not Employed 1849 96.561 99.534 2.3147 1 995 10 37 65 120 200 275 420 526 

Employment Refused 54 120.296 108.615 14.7807 10 480 20 35 88 190 290 330 390 480 

Education * 1550 76.39 78.923 2.0047 1 955 10 30 60 95 155 201 302.5 385 

Education < High School 561 100.822 120.246 5.0768 5 1440 15 40 70 120 180 265 460 620 

Education High School Graduate 2166 101.605 107.594 2.3118 1 1210 12 40 70 120 210 286 445 570 

Education < College 1556 103.215 110.128 2.7919 2 1280 15 40 75 120 195 285 460 630 

Education College Graduate 1108 104.532 109.485 3.2891 4 1215 15 45 75 125 200 280 450 675 

Education Post Graduate 802 101.938 108.688 3.8379 4 1357 20 45 75.5 120 195 270 365 480 

Census Region Northeast 1662 98.585 106.64 2.6158 1 1215 15 40 70 120 190 275 425 570 

Census Region Midwest 1759 101.229 114.641 2.7334 1 1440 10 40 70 120 205 290 435 595 

Census Region South 2704 96.051 97.72 1.8792 1 955 13 40 70 120 190 250 420 558 

Census Region West 1618 93.689 103.717 2.5785 2 1280 10 35 65 115 180 260 420 540 

Day Of Week Weekday 5289 94.437 101.435 1.3948 1 1215 10 40 66 115 180 260 435 575 

Day Of Week Weekend 2454 103.399 111.892 2.2587 1 1440 13 40 75 125 205 280 420 540 

Season Winter 2037 94.31 101.375 2.2461 1 1080 10 35 65 116 190 270 425 544 

Season Spring 2032 99.612 110.464 2.4505 1 1440 12 40 70 120 200 275 440 546 

Season Summer 2090 97.792 103.76 2.2696 1 1357 10 40 70 120 190 260 415 558 

Season Fall 1584 97.419 103.714 2.6059 1 1280 14 40 70 120 180 265 420 620 

Asthma No 7152 97.262 104.554 1.2363 1 1440 10 40 70 120 190 270 425 570 

Asthma Yes 544 97.241 110.792 4.7502 4 955 17 40 65 116.5 180 255 460 705 

Asthma DK 47 100 95.192 13.8852 10 480 10 30 75 120 220 239 480 480 

Angina No 7516 97.288 105.235 1.2139 1 1440 11 40 70 120 190 270 425 570 

Angina Yes 172 93.07 93.142 7.102 8 615 15 30 65 120 185 280 420 540 

Angina DK 55 108.945 99.695 13.4429 10 480 20 35 75 150 235 360 390 480 

Bronchitis/Emphysema No 7349 97.559 106.055 1.2371 1 1440 10 40 70 120 190 270 425 580 

Bronchitis/Emphysema Yes 342 90.971 79.287 4.2873 2 505 15 40 70 115 195 240 325 460 

Bronchitis/Emphysema DK 52 98.942 93.767 13.0031 5 480 10 30 73.5 145 195 239 390 480 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-134. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Near a Vehicle 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 2825 79.828 143.82 2.7059 1 1440 2 10 30 65 200 465 600 675 

Gender Male 1388 111.21 184.96 4.9645 1 1440 3 11 30.5 90 430 570 675 735 

Gender Female 1436 49.541 75.947 2.0042 1 790 2 10 25 60 120 180 290 420 

Gender Refused 1 20 * * 20 20 20 20 20 20 20 20 20 20 

Age (years) * 51 64.373 90.949 12.7354 1 510 4 20 40 65 125 290 360 510 

Age (years) 1-4 102 45.99 59.489 5.8903 1 420 2 10 30 60 105 160 192 245 

Age (years) 5-11 230 55.909 86.475 5.702 1 540 2 10 20 60 170 215 360 465 

Age (years) 12-17 313 40.879 55.718 3.1494 1 435 3 10 21 45 100 160 220 260 

Age (years) 18-64 1787 96.365 169.13 4.0009 1 1440 2 10 30 75 325 539 645 720 

Age (years) > 64 342 57.55 85.255 4.61 1 560 4 10 30 60 120 205 450 510 

Race White 2275 81.787 148.41 3.1116 1 1440 2 10 30 68 210 480 600 695 

Race Black 278 78.374 130.69 7.838 1 645 2 10 30 70 190 435 580 600 

Race Asian 51 42.431 61.693 8.6387 1 405 2 10 28 60 85 120 150 405 

Race Some Others 50 73.06 113.02 15.9836 1 535 2 15 40 60 167.5 420 492.5 535 

Race Hispanic 136 55.066 100.19 8.591 1 600 2 10 25 54.5 110 170 525 600 

Race Refused 35 124.4 186.88 31.5887 4 810 10 20 40 120 360 565 810 810 

Hispanic No 2552 79.761 142.98 2.8303 1 1440 2 10 30 65 200 457 600 665 

Hispanic Yes 230 68.091 125.96 8.3058 1 765 2 10 30 60 147.5 410 565 615 

Hispanic DK 13 185.31 321.29 89.1098 2 985 2 10 25 100 705 985 985 985 

Hispanic Refused 30 129.83 198.28 36.2 10 810 10 20 40 98 435 585 810 810 

Employment * 632 46.989 68.827 2.7378 1 540 2 10 23 55 120 180 265 360 

Employment Full Time 1169 114.86 193.04 5.646 1 1440 2 10 30 90 485 570 690 740 

Employment Part Time 254 67.118 114.34 7.174 1 795 2 10 30 63 165 280 510 600 

Employment Not Employed 751 56.792 84.927 3.099 1 690 2 10 30 60 130 210 360 465 

Employment Refused 19 96.947 185.76 42.616 5 790 5 20 30 90 360 790 790 790 

Education * 702 47.098 70.151 2.6477 1 540 2 10 24 55 120 180 265 360 

Education < High School 222 105.76 193.65 12.9967 1 1440 4 10 30 90 365 540 720 735 

Education High School Graduate 702 113.18 185.75 7.0107 1 1410 2 10 35 90 455 555 665 740 

Education < College 537 87.927 157.3 6.7878 1 985 2 10 30 70 240 540 635 705 

Education College Graduate 367 70.905 117.85 6.1515 1 660 2 10 30 68 170 325 565 600 

Education Post Graduate 295 55.186 86.872 5.0579 1 710 3 10 30 60 120 200 362 560 

Census Region Northeast 749 75.734 130.56 4.7705 1 985 3 10 30 70 179 375 570 665 

Census Region Midwest 586 77.445 141.21 5.8332 1 1440 2 10 30 60 210 390 560 645 

Census Region South 836 86.447 160.31 5.5443 1 1410 2 10 30 61.5 240 525 643 710 

Census Region West 654 78.19 138.28 5.4072 1 985 2 10 30 65 180 435 570 615 

Day Of Week Weekday 2018 84.241 155.61 3.4639 1 1440 2 10 30 65 215 515 625 705 

Day Of Week Weekend 807 68.793 108.2 3.8088 1 705 2 10 30 65 180 310 465 540 

Season Winter 703 70.91 141.83 5.3492 1 1440 2 10 26 60 160 365 570 643 

Season Spring 791 80.542 135.48 4.817 1 810 2 10 30 74 215 435 570 645 

Season Summer 819 84.178 150.3 5.2519 1 985 2 10 30 70 210 510 615 705 

Season Fall 512 84.01 148.27 6.5525 1 930 2 10 30 70 225 510 600 690 

Asthma No 2596 80.366 143.21 2.8107 1 1410 2 10 30 65 205 475 600 675 

Asthma Yes 205 75.088 157.15 10.9756 1 1440 2 10 30 65 160 309 580 690 

Asthma DK 24 62.083 78.548 16.0335 5 360 5 17.5 35 67.5 98 225 360 360 

Angina No 2726 79.57 144.32 2.7642 1 1440 2 10 30 65 196 465 600 687 

Angina Yes 76 92.434 139.38 15.9879 1 570 3 10 35 91 354 465 535 570 

Angina DK 23 68.696 91.209 19.0183 5 360 10 20 40 75 98 330 360 360 

Bronchitis/Emphysema No 2684 79.404 142.84 2.7572 1 1440 2 10 30 65 197 465 600 665 

Bronchitis/Emphysema Yes 115 93.843 175.36 16.3523 1 985 2 10 30 90 225 465 735 985 

Bronchitis/Emphysema DK 26 61.615 72.201 14.1598 5 360 7 27 40 75 110 180 360 360 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-135. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Other Than Near a Residence or Vehicle Such as Parks, Golf Courses, or Farms 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1383 200.153 202.665 5.45 1 1440 10 60 130 276 510 600 748 915 

Gender Male 789 223.482 208.727 7.431 1 1440 20 60 150 315 540 635 765 900 

Gender Female 593 168.742 189.993 7.802 1 1440 10 40 105 238 420 540 700 930 

Gender Refused 1 420 * * 420 420 420 420 420 420 420 420 420 420 

Age (years) * 19 183.368 160.349 36.787 10 540 10 60 140 220 510 540 540 540 

Age (years) 1-4 54 164.648 177.34 24.133 1 980 10 60 120 175 370 560 630 980 

Age (years) 5-11 159 171.34 177.947 14.112 5 1210 15 55 115 221 405 574 660 725 

Age (years) 12-17 175 156.903 174.411 13.184 5 1065 10 45 100 210 385 570 735 915 

Age (years) 18-64 858 219.425 215.094 7.343 1 1440 10 60 150 310 540 635 780 933 

Age (years) > 64 118 181.932 180.158 16.585 5 900 20 55 112.5 280 480 570 600 735 

Race White 1186 202.615 203.396 5.906 1 1440 14 60 134.5 280 510 615 750 930 

Race Black 81 185.84 195.119 21.68 1 765 5 40 108 240 540 585 690 765 

Race Asian 20 169.45 189.122 42.289 10 665 10 32.5 95 230 477.5 585 665 665 

Race Some Others 30 187.5 161.849 29.549 10 560 10 60 120 270 437.5 535 560 560 

Race Hispanic 57 158.298 203.27 26.924 1 1305 5 30 110 228 370 435 555 1305 

Race Refused 9 380 250.637 83.546 30 810 30 195 435 540 810 810 810 810 

Hispanic No 1267 202.593 203.353 5.713 1 1440 10 60 130 280 510 615 748 915 

Hispanic Yes 103 163.942 185.155 18.244 1 1305 10 30 115 228 400 511 555 555 

Hispanic DK 4 67.5 59.231 29.616 10 145 10 22.5 57.5 112.5 145 145 145 145 

Hispanic Refused 9 330 259.459 86.486 30 810 30 140 210 510 810 810 810 810 

Employment * 383 163.846 176.805 9.034 1 1210 10 51 110 215 385 560 665 915 

Employment Full Time 555 228.526 219.372 9.312 1 1305 14 60 150 335 545 645 825 955 

Employment Part Time 126 202.556 211.673 18.857 3 1440 10 60 125 280 510 580 690 700 

Employment Not Employed 309 191.469 189.268 10.767 1 1440 10 50 125 275 480 565 690 735 

Employment Refused 10 254 240.899 76.179 30 810 30 105 167.5 280 675 810 810 810 

Education * 429 163.949 175.476 8.472 1 1210 10 55 115 210 385 560 665 840 

Education < High School 83 264.482 255.463 28.041 1 1305 30 60 180 480 555 600 1100 1305 

Education High School Graduate 313 228.613 228.235 12.901 3 1440 10 60 160 310 570 690 855 990 

Education < College 250 217.984 202.991 12.838 1 1440 10 60 152.5 330 510 555 715 765 

Education College Graduate 185 207.27 190.178 13.982 1 930 20 60 128 285 505 600 690 795 

Education Post Graduate 123 163.642 173.04 15.603 1 900 10 45 90 240 385 480 735 780 

Census Region Northeast 279 196.824 208.372 12.475 1 1305 10 60 130 265 480 590 900 1130 

Census Region Midwest 309 196.702 211.59 12.037 1 1440 10 50 120 270 510 635 740 900 

Census Region South 468 198.432 195.071 9.017 1 933 15 60 120 285 510 600 748 825 

Census Region West 327 208.716 200.465 11.086 1 1440 15 60 150 285 525 580 725 855 

Day Of Week Weekday 851 183.982 197.931 6.785 1 1440 10 45 119 240 490 585 735 900 

Day Of Week Weekend 532 226.019 207.598 9 1 1440 20 68.5 155 320 525 630 810 915 

Season Winter 241 175.676 192.682 12.412 1 1065 10 35 93 253 450 585 750 810 

Season Spring 412 185.806 174.522 8.598 5 980 15 60 130 240 473 555 665 740 

Season Summer 508 224.996 220.748 9.794 1 1440 15 60 150 305 540 630 840 990 

Season Fall 222 196.5 213.598 14.336 1 1130 10 35 120 280 540 600 780 900 

Asthma No 1283 196.564 196.894 5.497 1 1440 10 60 125 270 495 600 730 855 

Asthma Yes 93 244.344 263.314 27.304 5 1440 15 60 150 350 530 810 1100 1440 

Asthma DK 7 270.714 274.415 103.719 30 810 30 60 195 450 810 810 810 810 

Angina No 1352 199.038 202.274 5.501 1 1440 10 60 130 270 510 600 740 915 

Angina Yes 25 238.64 205.994 41.199 1 730 5 60 210 340 465 690 730 730 

Angina DK 6 290.833 275.979 112.668 30 810 30 140 202.5 360 810 810 810 810 

Bronchitis/Emphysema No 1326 199.761 200.843 5.516 1 1440 10 60 130 275 500 600 735 900 

Bronchitis/Emphysema Yes 51 206.431 239.756 33.573 5 1100 10 50 110 305 540 700 930 1100 

Bronchitis/Emphysema DK 6 233.333 294.035 120.039 15 810 15 30 167.5 210 810 810 810 810 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996. 
Table 15-136. Statistics for 24-Hour Cumulative Number of Minutes Spent in an Office or Factory 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1975 393.972 230.763 5.1926 1 1440 9 180 485 550 630 675 765 818 

Gender Male 1012 410.816 233.454 7.3386 1 1440 10 225 495 565 645 710 780 855 

Gender Female 963 376.271 226.676 7.3045 1 855 5 120 480 540 600 645 710 750 

Age (years) * 49 438.918 232.58 33.2257 10 900 20 299 500 555 675 780 900 900 

Age (years) 1-4 12 31.583 25.639 7.4013 5 90 5 12.5 25 44.5 60 90 90 90 

Age (years) 5-11 14 100.929 155.126 41.4593 2 580 2 10 32.5 178 195 580 580 580 

Age (years) 12-17 19 145.421 181.118 41.5512 1 625 1 10 50 240 510 625 625 625 

Age (years) 18-64 1749 418.971 218.445 5.2233 1 1440 10 273 500 555 630 680 765 818 

Age (years) > 64 132 145.848 193.973 16.8832 1 705 3 10 40 205 495 540 640 675 

Race White 1612 387.646 231.968 5.7776 1 1440 6 150 480 550 628 675 750 800 

Race Black 191 413.911 218 15.7739 1 1037 10 268 485 540 635 720 803 900 

Race Asian 42 428.024 216.759 33.4466 10 780 30 285 491.5 553 660 745 780 780 

Race Some Others 28 480.893 200.859 37.9588 40 795 75 347.5 540 582.5 715 780 795 795 

Race Hispanic 74 394.459 237.847 27.6492 1 840 5 230 492.5 560 645 720 765 840 

Race Refused 28 482.893 246.079 46.5046 30 997 30 373 532.5 607.5 818 860 997 997 

Hispanic No 1805 393.453 229.593 5.404 1 1440 10 180 483 550 630 675 755 810 

Hispanic Yes 138 393.645 238.608 20.3116 1 840 5 180 497.5 560 644 675 765 795 

Hispanic DK 7 262.571 242.131 91.5168 1 610 1 12 245 540 610 610 610 610 

Hispanic Refused 25 470.04 258.753 51.7505 17 860 30 311 525 615 810 818 860 860 

Employment * 43 121.279 177.984 27.1423 1 685 2 10 40 178 307 580 685 685 

Employment Full Time 1535 455.571 200.299 5.1124 1 1440 15 400 510 570 644 700 775 837 

Employment Part Time 164 293.03 196.95 15.3792 1 750 10 95 342.5 480 525 555 585 615 

Employment Not Employed 213 77.643 122.957 8.4249 1 705 3 10 30 90 215 305 570 640 

Employment Refused 20 449.15 184.813 41.3256 30 675 60 334 522.5 550 645 675 675 675 

Education * 80 225.1 248.547 27.7884 1 860 3 15 105 470 607.5 675 780 860 

Education < High School 104 329.548 264.402 25.9267 2 930 5 50.5 388.5 552.5 640 705 765 855 

Education High School Graduate 631 396.876 228.074 9.0795 1 997 10 210 492 550 615 675 760 800 

Education < College 462 393.108 228.826 10.6459 1 1440 5 210 480 540 615 660 770 820 

Education College Graduate 415 437.231 205.198 10.0728 1 900 10 325 510 570 640 690 750 800 

Education Post Graduate 283 396.883 232.151 13.7999 2 860 5 175 480 565 640 675 780 818 

Census Region Northeast 465 399.075 226.243 10.4918 1 930 10 215 485 550 625 675 765 840 

Census Region Midwest 439 389.31 229.075 10.9331 1 997 8 180 480 550 630 670 750 800 

Census Region South 666 408.637 228.181 8.8418 1 1440 10 225 497.5 555 630 675 760 840 

Census Region West 405 369.052 240.375 11.9443 1 900 5 95 470 550 630 675 760 800 

Day Of Week Weekday 1759 406.795 225.173 5.3689 1 997 10 237 495 555 630 675 755 810 

Day Of Week Weekend 216 289.551 249.076 16.9475 1 1440 3 30 282.5 495 600 670 800 900 

Season Winter 531 390.716 231.677 10.0539 1 997 10 180 480 550 625 675 755 835 

Season Spring 470 385.198 240.678 11.1016 1 1440 5 120 480 553 630 695 775 837 

Season Summer 550 393.524 224.454 9.5708 1 1037 9 200 482.5 540 613.5 675 753 810 

Season Fall 424 408.358 226.578 11.0036 1 840 10 238.5 500 566.5 640 675 750 770 

Asthma No 1845 394.976 230.383 5.3635 1 1440 8 185 490 550 630 675 760 810 

Asthma Yes 114 371.693 231.336 21.6666 3 840 10 120 462.5 540 630 675 800 837 

Asthma DK 16 437 272.067 68.0168 5 860 5 232.5 520 587.5 780 860 860 860 

Angina No 1931 395.718 229.668 5.2265 1 1440 10 195 490 550 630 675 760 811 

Angina Yes 26 265.462 246.766 48.3947 5 650 9 15 175 490 630 645 650 650 

Angina DK 18 392.333 282.64 66.619 5 860 5 30 490 550 780 860 860 860 

Bronchitis/Emphysema No 1873 395.611 229.961 5.3135 1 1440 8 195 490 550 630 675 760 818 

Bronchitis/Emphysema Yes 86 356.43 236.119 25.4614 5 800 10 75 427.5 540 620 660 720 800 

Bronchitis/Emphysema DK 16 403.875 289.456 72.3641 5 860 5 30 490 582.5 780 860 860 860 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-137. Statistics for 24-Hour Cumulative Number of Minutes Spent in Malls, Grocery Stores, or Other Stores 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 2697 114.975 140.961 2.7143 1 1080 10 30 60 135 285 482 570 640 

Gender Male 1020 120.159 157.143 4.9203 1 840 5 30 60 130 375 530 609 658 

Gender Female 1677 111.822 130.088 3.1766 1 1080 10 30 60 135 255 400 550 600 

Age (years) * 50 139.44 137.586 19.4576 15 660 20 45 92.5 180 338.5 420 565 660 

Age (years) 1-4 110 90.036 77.887 7.4263 5 420 10 40 65 105 210 250 359 360 

Age (years) 5-11 129 77.674 68.035 5.9901 3 320 5 30 60 110 180 225 255 280 

Age (years) 12-17 140 88.714 101.361 8.5666 1 530 5 20 45 123.5 222.5 317.5 384 413 

Age (years) 18-64 1871 125.927 156.815 3.6253 1 1080 10 30 60 150 360 525 600 658 

Age (years) > 64 397 88.572 88.477 4.4405 1 655 10 30 60 120 180 255 400 470 

Race White 2234 111.563 139.443 2.9502 1 1080 10 30 60 130 265 495 570 640 

Race Black 237 123 152.318 9.8941 2 800 10 25 60 135 370 480 600 613 

Race Asian 37 158.892 151.725 24.9434 2 600 14 50 105 220 410 480 600 600 

Race Some Others 52 150.231 146.737 20.3488 5 660 14 65 102.5 180 280 588 600 660 

Race Hispanic 110 133.145 138.309 13.1872 1 720 10 35 90 195 310 450 535 540 

Race Refused 27 124.741 131.136 25.2372 10 515 10 30 60 207 300 380 515 515 

Hispanic No 2476 114.387 141.819 2.8501 1 1080 10 30 60 131.5 285 495 570 640 

Hispanic Yes 188 126.074 133.15 9.711 1 720 10 30 90 172.5 270 450 540 610 

Hispanic DK 12 49.417 37.689 10.8798 2 122 2 17.5 47.5 69.5 105 122 122 122 

Hispanic Refused 21 122.429 138.488 30.2206 10 515 20 33 60 180 290 380 515 515 

Employment * 372 86.946 86.322 4.4756 1 660 5 30 60 120 206 255 360 384 

Employment Full Time 1170 136.797 176.691 5.1656 1 1080 10 30 60 150 480 562 640 690 

Employment Part Time 285 134.123 147.732 8.7509 2 540 6 30 65 186 400 480 520 540 

Employment Not Employed 854 91.198 87.218 2.9846 1 585 10 30 60 120 195 255 360 420 

Employment Refused 16 98.938 110.033 27.5083 10 357 10 31.5 52.5 115 290 357 357 357 

Education * 420 88.262 91.922 4.4853 1 660 5 29 60 120 210 262.5 384 420 

Education < High School 206 128.937 155.722 10.8497 2 1080 10 30 75 150 330 500 570 605 

Education High School Graduate 792 126.295 158.884 5.6457 1 960 5 30 60 150 365 524 600 660 

Education < College 583 129.849 149.53 6.1929 1 800 10 30 70 165 345 510 563 651 

Education College Graduate 411 117.876 144.142 7.11 1 720 10 30 60 135 290 515 600 640 

Education Post Graduate 285 78.182 95.665 5.6667 1 630 10 25 50 90 160 250 450 555 

Census Region Northeast 622 110.201 134.942 5.4107 1 755 5 30 60 130 280 465 563 600 

Census Region Midwest 601 108.243 133.098 5.4292 2 840 10 30 60 130 250 440 560 645 

Census Region South 871 127.922 155.825 5.2799 1 1080 10 30 60 155 320 520 600 660 

Census Region West 603 107.909 130.742 5.3242 1 840 10 30 60 120 255 430 550 600 

Day Of Week Weekday 1721 117.451 148.879 3.5887 1 1080 10 30 60 135 320 510 586 650 

Day Of Week Weekend 976 110.61 125.747 4.0251 1 840 5 30 65 135 255 380 560 608 

Season Winter 683 111.71 134 5.1274 2 840 10 30 60 135 255 420 568 660 

Season Spring 679 115.844 142.21 5.4575 1 720 10 30 60 130 300 500 588 645 

Season Summer 759 113.138 147.47 5.3528 1 1080 5 30 60 125 300 510 570 610 

Season Fall 576 120.243 138.948 5.7895 1 840 10 30 60 160 295 480 550 640 

Asthma No 2480 116.246 142.351 2.8585 1 1080 10 30 60 135 287.5 495 575 640 

Asthma Yes 208 101.111 124.977 8.6656 1 600 5 30 60 120 245 420 545 550 

Asthma DK 9 85.111 79.634 26.5447 33 290 33 55 58 60 290 290 290 290 

Angina No 2607 115.981 142.101 2.7831 1 1080 10 30 60 135 290 495 570 640 

Angina Yes 74 90.838 103.912 12.0795 2 630 15 37 64 105 150 190 510 630 

Angina DK 16 62.688 68.084 17.021 2 290 2 30 55 60 110 290 290 290 

Bronchitis/Emphysema No 2553 115.736 141.704 2.8045 1 1080 10 30 60 135 285 481 570 640 

Bronchitis/Emphysema Yes 130 104.754 131.336 11.5189 5 613 10 25 60 135 192.5 505 575 609 

Bronchitis/Emphysema DK 14 71.143 66.864 17.8701 20 290 20 35 56.5 70 110 290 290 290 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-138. Statistics for 24-Hour Cumulative Number of Minutes Spent in Schools, Churches, Hospitals, and Public Buildings 

Percentile 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 2932 274.332 205.942 3.8033 1 1440 20 95 221 430 540 615 725 805 

Gender Male 1234 285.147 206.713 5.8845 1 1440 30 110 255 425 540 620 745 840 

Gender Female 1698 266.472 205.082 4.9769 1 1440 20 90 200 430 540 610 713 800 

Age (years) * 50 268.96 221.042 31.2601 5 1030 30 100 192.5 400 590 625 871.5 1030 

Age (years) 1-4 98 233 235.787 23.8181 1 1440 5 60 150 390 545 595 900 1440 

Age (years) 5-11 391 351.202 149.578 7.5645 5 665 70 245 389 440 535 562 625 645 

Age (years) 12-17 355 366.338 161.247 8.5581 1 935 60 260 415 446 502 605 710 805 

Age (years) 18-64 1653 267.707 221.203 5.4407 1 1440 15 87 190 450 570 655 760 855 

Age (years) > 64 385 151.091 128.639 6.556 5 710 21 60 115 195 340 435 525 615 

Race White 2310 268.239 204.323 4.2512 1 1440 20 90 210 429 540 612 705 765 

Race Black 332 303.473 207.071 11.3645 1 1440 35 135 285 440 540 630 775 1000 

Race Asian 61 295 199.398 25.5302 5 900 30 135 240 425 535 565 840 900 

Race Some Others 57 314.684 203.549 26.9607 10 967 30 135 360 455 525 598 820 967 

Race Hispanic 141 283.936 229.828 19.355 2 1440 11 100 237 430 525 630 840 940 

Race Refused 31 257.774 192.517 34.5771 5 681 5 120 240 430 495 625 681 681 

Hispanic No 2654 271.293 203.551 3.9511 1 1440 20 94 215 425 540 612 712 800 

Hispanic Yes 240 306.388 230.835 14.9003 1 1440 20 110 287.5 444.5 567.5 695 840 940 

Hispanic DK 13 279.385 230.736 63.9946 35 760 35 65 235 420 562 760 760 760 

Hispanic Refused 25 286.6 175.367 35.0734 5 625 55 145 255 440 495 565 625 625 

Employment * 821 343.484 171.113 5.9719 1 1440 55 190 393 441 520 570 645 713 

Employment Full Time 1029 300.3 239.785 7.4751 1 1440 15 90 215 510 610 685 775 900 

Employment Part Time 293 251.324 199.326 11.6447 1 1030 20 85 200 387 525 610 800 880 

Employment Not Employed 775 176.406 148.414 5.3312 1 855 15 60 121 250 400 475 570 641 

Employment Refused 14 212.857 147.736 39.484 5 440 5 120 190 305 430 440 440 440 

Education * 917 340.328 172.613 5.7002 1 1440 45 190 390 440 525 580 645 713 

Education < High School 166 172.602 138.026 10.7129 1 735 27 70 123.5 235 375 465 525 640 

Education High School Graduate 617 207.29 199.027 8.0125 1 1440 15 60 135 295 510 585 690 785 

Education < College 520 247.492 213.609 9.3674 1 1000 15 85 165 420 552.5 640 760 855 

Education College Graduate 351 261.581 214.287 11.4378 1 1005 15 85 180 450 560 625 750 800 

Education Post Graduate 361 319.114 236.166 12.4298 1 1440 30 110 290 510 615 683 765 900 

Census Region Northeast 645 272.747 211.594 8.3315 1 1440 25 90 215 420 545 630 735 855 

Census Region Midwest 686 275.394 207.157 7.9093 1 1440 30 88 239 425 540 615 745 850 

Census Region South 1036 278.387 201.004 6.2449 1 1440 20 110 230 440 535 600 690 778 

Census Region West 565 267.418 207.214 8.7176 1 1440 15 100 200 420 555 620 712 820 

Day Of Week Weekday 2091 309.844 212.577 4.6488 1 1440 15 115 340 460 565 632 750 855 

Day Of Week Weekend 841 186.039 156.873 5.4094 1 1440 40 85 140 230 385 525 640 735 

Season Winter 847 296.587 201.244 6.9148 1 1440 30 120 285 444 545 615 710 770 

Season Spring 805 276.761 204.618 7.2118 1 1440 30 110 220 420 535 600 725 840 

Season Summer 667 254.115 209.724 8.1205 1 1015 20 80 180 420 550 630 738 890 

Season Fall 613 262.39 207.33 8.374 1 1005 14 75 210 425 540 615 712 778 

Asthma No 2689 273.193 207.301 3.9977 1 1440 20 94 217 430 540 615 725 820 

Asthma Yes 229 287.974 191.578 12.6598 1 855 25 120 275 435 533 605 645 800 

Asthma DK 14 270 171.24 45.7658 5 565 5 145 280 430 445 565 565 565 

Angina No 2836 277.127 206.396 3.8757 1 1440 20 100 230 430 540 615 725 805 

Angina Yes 78 176.423 172.803 19.5661 5 890 28 60 120 195 480 575 625 890 

Angina DK 18 258.278 165.599 39.0321 3 565 3 145 270 378 480 565 565 565 

Bronchitis/Emphysema No 2794 276.999 207.348 3.9227 1 1440 20 95 228 430 540 615 726 840 

Bronchitis/Emphysema Yes 121 212.562 166.349 15.1226 10 662 30 90 145 375 445 490 605 630 

Bronchitis/Emphysema DK 17 275.765 163.401 39.6306 5 565 5 145 305 415 440 565 565 565 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-139. Statistics for 24-Hour Cumulative Number of Minutes Spent in Bars/Nightclubs, Bowling Alleys, and Restaurants 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 2296 111.735 131.368 2.7416 1 925 10 40 60 120 255 405 568 660 

Gender Male 1127 109.497 129.654 3.8621 1 900 10 35 60 120 240 377 560 660 

Gender Female 1169 113.892 133.019 3.8905 2 925 10 45 60 120 270 424 570 645 

Age (years) * 32 138.094 151.816 26.8376 15 610 30 47.5 65 150 315 495 610 610 

Age (years) 1-4 61 62.705 47.701 6.1075 4 330 10 35 55 85 115 120 130 330 

Age (years) 5-11 88 58.602 39.746 4.2369 5 180 10 30 45 85 120 137 170 180 

Age (years) 12-17 127 76.614 82.038 7.2797 2 455 10 30 50 90 220 270 325 360 

Age (years) 18-64 1718 121.371 142.223 3.4313 1 925 10 40 65 135 285 462 600 680 

Age (years) > 64 270 92.207 90.483 5.5066 3 750 20 45 62.5 100 177.5 255 358 520 

Race White 1945 108.84 127.174 2.8836 1 925 10 40 60 120 240 388 560 645 

Race Black 167 121.88 147.847 11.4408 5 805 10 30 60 153 300 490 555 735 

Race Asian 42 103.976 104.151 16.0709 5 497 30 40 62.5 120 200 240 497 497 

Race Some Others 36 159.333 196.721 32.7868 5 765 10 52.5 90 137.5 495 750 765 765 

Race Hispanic 83 130.205 161.594 17.7373 5 813 15 40 65 143 360 485 700 813 

Race Refused 23 155.913 135.696 28.2945 20 480 30 60 88 270 330 410 480 480 

Hispanic No 2131 110.53 129.679 2.8092 1 925 10 40 60 120 245 395 560 650 

Hispanic Yes 141 127.319 153.659 12.9404 1 813 15 40 70 120 360 440 700 765 

Hispanic DK 7 95 115.109 43.507 5 315 5 10 40 165 315 315 315 315 

Hispanic Refused 17 140.353 147.503 35.7748 30 480 30 40 70 210 410 480 480 480 

Employment * 273 65.85 61.078 3.6966 2 455 10 30 50 85 120 182 273 330 

Employment Full Time 1215 125.765 151.364 4.3424 1 925 10 40 63 135 300 500 640 735 

Employment Part Time 236 144.729 157.886 10.2775 1 813 10 47.5 80 180 385 520 615 745 

Employment Not Employed 559 88.642 77.231 3.2665 3 610 15 45 60 115 180 240 315 388 

Employment Refused 13 158.077 127.157 35.267 30 425 30 70 105 240 330 425 425 425 

Education * 309 76.006 81.68 4.6466 1 548 10 30 55 90 165 255 330 455 

Education < High School 155 154.155 175.537 14.0995 5 925 15 40 90 209 388 545 700 870 

Education High School Graduate 665 119.502 145.414 5.6389 3 910 10 45 60 120 290 485 630 680 

Education < College 498 121.321 137.839 6.1767 2 775 10 40 75 135 270 440 610 675 

Education College Graduate 395 101.096 109.709 5.5201 1 765 15 40 60 120 225 330 507 570 

Education Post Graduate 274 107.091 117.52 7.0997 3 765 15 40 65 120 220 330 560 675 

Census Region Northeast 462 115.771 127.168 5.9164 2 765 15 45 70 120 270 380 560 650 

Census Region Midwest 561 113.688 132.476 5.5932 1 813 10 40 65 120 250 410 570 675 

Census Region South 748 105.619 133.036 4.8643 2 910 13 35 60 110 240 390 555 650 

Census Region West 525 114.81 131.486 5.7385 1 925 10 37 70 130 245 417 590 640 

Day Of Week Weekday 1407 112.164 138.508 3.6926 1 925 10 35 60 120 270 430 595 675 

Day Of Week Weekend 889 111.055 119.269 4.0001 2 870 10 45 70 120 235 351 535 630 

Season Winter 584 116.783 135.982 5.627 3 875 15 40 68.5 120 265 440 595 735 

Season Spring 615 108.416 124.727 5.0295 2 925 15 41 65 120 240 395 542 585 

Season Summer 622 110.543 132.965 5.3314 1 910 10 35 60 120 260 390 605 660 

Season Fall 475 111.385 132.104 6.0614 1 900 10 35 60 125 265 355 550 770 

Asthma No 2124 111.768 129.918 2.819 1 910 10 40 60 120 255 390 568 660 

Asthma Yes 163 107.301 145.813 11.4209 4 925 10 30 57 118 265 485 560 670 

Asthma DK 9 184.222 186.348 62.1159 30 480 30 60 88 300 480 480 480 480 

Angina No 2229 112.481 132.361 2.8035 1 925 10 40 60 120 260 410 570 660 

Angina Yes 54 71.463 52.513 7.1461 3 340 15 45 60 90 120 120 232 340 

Angina DK 13 151 162.726 45.132 30 480 30 35 88 120 480 480 480 480 

Bronchitis/Emphysema No 2171 111.178 129.886 2.7876 1 910 10 40 60 120 255 400 560 660 

Bronchitis/Emphysema Yes 114 109.807 134.998 12.6437 5 925 15 43 65 120 235 375 530 620 

Bronchitis/Emphysema DK 11 241.636 274.085 82.6397 10 875 10 30 88 480 480 875 875 875 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-140. Statistics for 24-Hour Cumulative Number of Minutes Spent in Other Outdoors Such as Auto Repair Shops, Laundromats, Gyms, and at Work (non-specific) 

Percentiles 

Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 1214 225.747 231.111 6.633 1 1440 10 56 120 370 568 670 800 910 

Gender Male 612 260.322 239.586 9.685 1 1040 10 60 160 460 605 695 815 930 

Gender Female 602 190.598 216.774 8.835 1 1440 10 45 105 260 535 600 720 855 

Age (years) * 21 264.524 273.733 59.733 15 940 30 75 100 420 560 840 940 940 

Age (years) 1-4 27 92.296 74.852 14.405 10 270 15 25 65 160 180 250 270 270 

Age (years) 5-11 59 134.678 186.691 24.305 5 910 5 30 80 145 325 720 855 910 

Age (years) 12-17 76 164.368 159.542 18.301 1 660 5 45 130 208 450 550 600 660 

Age (years) 18-64 903 250.29 243.45 8.101 1 1440 10 60 135 450 600 690 815 945 

Age (years) > 64 128 152.813 159.777 14.122 2 770 12 45 95 202.5 420 510 600 610 

Race White 996 226.348 228.881 7.252 1 1440 10 58.5 120 370 580 665 780 910 

Race Black 118 228.102 256.391 23.603 2 1430 5 45 120 358 525 720 990 1150 

Race Asian 25 194.68 196.484 39.297 5 600 25 58 90 300 525 530 600 600 

Race Some Others 23 211.217 236.332 49.279 5 800 10 25 115 405 515 680 800 800 

Race Hispanic 42 250.19 229.16 35.36 5 793 15 60 165 420 600 675 793 793 

Race Refused 10 146.5 246.555 77.967 15 840 15 55 67.5 105 495 840 840 840 

Hispanic No 1133 224.325 231.063 6.865 1 1440 10 55 120 360 565 670 810 930 

Hispanic Yes 68 230.088 215.421 26.124 5 793 15 61.5 127.5 398 545 660 790 793 

Hispanic DK 5 483.2 240.867 107.719 55 623 55 560 568 610 623 623 623 623 

Hispanic Refused 8 229.375 310.592 109.811 30 840 30 42.5 67.5 372.5 840 840 840 840 

Employment * 162 140.031 158.915 12.486 1 910 10 30 103.5 170 325 505 660 855 

Employment Full Time 652 276.345 250.945 9.828 2 1430 10 60 162.5 508 619 700 815 945 

Employment Part Time 132 240.909 227.902 19.836 5 1440 15 67.5 170 360 510 620 815 1005 

Employment Not Employed 259 145.347 173.086 10.755 1 1150 5 40 90 160 432 540 704 770 

Employment Refused 9 194.444 278.752 92.917 15 840 15 40 75 150 840 840 840 840 

Education * 186 148.097 168.067 12.323 1 910 5 30 109.5 177 330 520 720 855 

Education < High School 88 301.966 251.244 26.783 5 930 15 60 265 487.5 670 780 815 930 

Education High School Graduate 324 249.086 243.136 13.508 2 1150 10 53.5 126 435 595 690 815 979 

Education < College 251 266.996 256.435 16.186 2 1440 10 60 155 480 600 710 800 990 

Education College Graduate 217 202.014 217.284 14.75 1 1005 5 55 110 295 570 645 760 855 

Education Post Graduate 148 191.764 198.819 16.343 2 870 10 60 105 262.5 535 590 700 793 

Census Region Northeast 275 218.171 216.166 13.035 2 990 10 60 120 360 544 660 765 855 

Census Region Midwest 254 250.689 241.492 15.153 1 1005 10 55 150 460 600 695 815 940 

Census Region South 401 223.691 239.929 11.981 1 1440 10 47 120 360 560 635 815 979 

Census Region West 284 213.68 222.324 13.193 2 960 10 60 120 305 585 675 793 850 

Day Of Week Weekday 900 224.954 232.145 7.738 1 1430 10 58.5 120 367.5 565 672.5 815 942.5 

Day Of Week Weekend 314 228.019 228.476 12.894 2 1440 8 52 120 376 580 665 720 815 

Season Winter 347 241.715 239.749 12.87 2 1440 10 60 155 390 585 660 897 960 

Season Spring 321 220.343 220.658 12.316 1 1005 10 54 115 390 550 630 730 815 

Season Summer 294 224.418 244.957 14.286 1 1040 5 45 115 360 595 760 855 979 

Season Fall 252 212.194 214.928 13.539 1 990 15 55.5 120 327.5 540 660 710 793 

Asthma No 1123 225.742 229.228 6.84 1 1440 10 55 125 370 565 660 780 897 

Asthma Yes 84 228.5 259.329 28.295 1 979 10 59.5 100 351 660 793 910 979 

Asthma DK 7 193.571 201.406 76.124 15 510 15 60 80 450 510 510 510 510 

Angina No 1178 225.259 231.28 6.739 1 1440 10 55 120 360 570 670 810 930 

Angina Yes 28 227.75 218.573 41.306 5 770 12 62.5 135 425 560 600 770 770 

Angina DK 8 290.625 269.171 95.166 15 780 15 67.5 217.5 480 780 780 780 780 

Bronchitis/Emphysema No 1166 226.724 232.003 6.794 1 1440 10 58 120 370 570 670 810 930 

Bronchitis/Emphysema Yes 41 198.829 213.198 33.296 5 780 10 45 95 330 550 565 780 780 

Bronchitis/Emphysema DK 7 220.714 197.261 74.558 15 510 15 60 155 450 510 510 510 510 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum 

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-141. Statistics for 24-Hour Cumulative Number of Minutes Spent with Smokers Present 

Percentiles 

Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 

All 4005 381.494 300.479 4.748 1 1440 30 120 319 595 815 925 1060 1170 

Gender Male 1967 411.359 313 7.057 1 1440 30 135 355 638 855 965 1105 1217 

Gender Female 2035 352.771 285.139 6.321 1 1440 29 105 285 545 780 870 995 1110 

Gender Refused 3 283.333 188.171 108.641 105 480 105 105 265 480 480 480 480 480 

Age (years) * 54 386.259 305.371 41.556 5 1440 25 105 370 555 780 995 995 1440 

Age (years) 1-4 155 366.561 324.464 26.062 5 1440 30 90 273 570 825 1010 1140 1305 

Age (years) 5-11 224 318.071 314.016 20.981 1 1440 25 105 190 475 775 1050 1210 1250 

Age (years) 12-17 256 245.77 243.61 15.226 1 1260 10 60 165 360 595 774 864 1020 

Age (years) 18-64 2976 403.067 299.434 5.489 2 1440 30 134.5 355 625 830 930 1047 1150 

Age (years) > 64 340 342.694 292.209 15.847 5 1440 30 100 240 540 797.5 880 1015 1205 

Race White 3279 389.219 303.032 5.292 1 1440 30 120 330 610 825 930 1060 1190 

Race Black 395 359.977 287.96 14.489 2 1440 22 118 300 538 775 905 1080 1160 

Race Asian 48 262.063 209.928 30.3 5 800 10 64 212.5 412.5 560 630 800 800 

Race Some Others 79 420.671 339.247 38.168 10 1328 30 135 310 655 885 1140 1305 1328 

Race Hispanic 165 292.624 250.208 19.479 5 1095 15 75 220 475 660 800 845 945 

Race Refused 39 393.538 325.254 52.082 25 1110 30 115 290 655 865 1040 1110 1110 

Hispanic No 3666 384.913 301.22 4.975 1 1440 30 120 324 600 822 930 1060 1170 

Hispanic Yes 288 336.191 280.874 16.551 1 1440 20 115 252 512 760 850 1010 1260 

Hispanic DK 18 369.833 371.484 87.56 15 1440 15 90 220 600 760 1440 1440 1440 

Hispanic Refused 33 403.364 322.819 56.195 25 1110 30 120 325 655 840 1040 1110 1110 

Employment * 624 301.723 295.529 11.831 1 1440 15 75 190 450 735 900 1140 1230 

Employment Full Time 2042 405.894 296.349 6.558 2 1440 30 135 364.5 625 835 925 1005 1110 

Employment Part Time 381 378.013 291.098 14.913 5 1440 30 135 325 585 805 915 1080 1245 

Employment Not Employed 935 383.833 308.691 10.095 3 1440 30 120 310 600 825 930 1110 1290 

Employment Refused 23 341.957 254.245 53.014 25 925 30 120 325 450 715 885 925 925 

Education * 704 308.635 292.801 11.035 1 1440 15 87.5 205 465 741 900 1095 1217 

Education < High School 377 497.719 317.756 16.365 2 1440 40 225 465 775 905 990 1120 1369 

Education High School Graduate 1315 425.682 301.711 8.32 3 1440 30 155 390 650 840 928 1060 1202 

Education < College 829 388.807 295.753 10.272 5 1435 30 135 330 600 810 930 1050 1155 

Education College Graduate 473 325.871 272.694 12.538 2 1140 30 90 240 499 735 860 990 1035 

Education Post Graduate 307 282.518 257.117 14.674 3 1205 20 60 200 430 665 810 900 983 

Census Region Northeast 932 369.46 287.677 9.423 2 1440 30 120 314 565 800 892 990 1095 

Census Region Midwest 938 384.067 304.829 9.953 2 1440 29 120 319.5 600 825 930 1080 1140 

Census Region South 1409 404.028 308.501 8.219 1 1440 30 130 345 630 840 943 1090 1205 

Census Region West 726 349.883 291.992 10.837 1 1440 30 110 274 541 800 900 1045 1180 

Day Of Week Weekday 2661 374.746 296.185 5.742 1 1440 30 120 315 578 810 915 1045 1150 

Day Of Week Weekend 1344 394.854 308.482 8.415 1 1440 30 120 321.5 625 833 940 1110 1260 

Season Winter 1046 374.159 304.183 9.405 1 1440 25 115 295 590 815 925 1080 1170 

Season Spring 1034 384.762 301.561 9.378 2 1440 30 120 320 610 810 900 1105 1215 

Season Summer 1059 385.134 300.394 9.231 2 1440 30 120 330 591 840 940 1040 1130 

Season Fall 866 381.999 295.104 10.028 2 1440 30 120 324 590 810 915 1030 1150 

Asthma No 3687 378.806 298.378 4.914 1 1440 30 120 315 591 810 915 1050 1170 

Asthma Yes 298 416.862 323.967 18.767 5 1440 20 135 342.5 652 870 1015 1202 1335 

Asthma DK 20 350 304.324 68.049 25 995 27.5 60 290 540 795 902.5 995 995 

Angina No 3892 380.923 299.475 4.8 1 1440 30 120 320 595 815 920 1060 1170 

Angina Yes 87 404.31 345.105 36.999 2 1380 30 120 270 703 910 1015 1320 1380 

Angina DK 26 390.577 300.394 58.912 25 995 30 115 342.5 670 780 790 995 995 

Bronchitis/Emphysema No 3749 378.662 298.576 4.876 1 1440 30 120 315 590 810 915 1060 1170 

Bronchitis/Emphysema Yes 236 431.157 326.848 21.276 5 1380 30 150 362.5 680 892 980 1205 1260 

Bronchitis/Emphysema DK 20 326.25 291.068 65.085 10 995 17.5 85 222.5 540 755 887.5 995 995 

Note: A "*" Signifies missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour 

cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum

number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsang and Klepeis, 1996.
Table 15-142 Range of Time (minutes) Spent Smoking Based on the Number of Respondents 

Number of Minutes 

Total N *-* 0- 60- 120- 180- 240- 300- 360- 420- 480- 540- 600-

60 120 180 240 300 360 420 480 540 600 660 

Overall 9386 5381 628 444 338 285 258 242 236 192 228 186 185 

Gender 

Male 4294 2327 280 184 167 141 119 114 128 92 101 92 89 Female 5088 3053 348 259 171 144 138 128 108 99 127 94 96 Refused 4 1 * 1 * * 1 * * 1 * * * 

Age (years) * 187 133 10 6

1-4 499 344 29 23

5-11 703 479 40 38

12-17 589 333 75 31

18-64 6059 3083 412 305

> 64 1349 1009 62 41

2 3 2 4 3 6 4 3 3 

14 8 10 7 8 7 8 7 5 

32 23 10 9 6 12 6 11 6 

30 20 22 15 13 7 13 5 3 

225 196 195 187 192 143 184 148 154 

35 35 19 20 14 17 13 12 14 

Race 

White 7591 4312 496 368 

Black 945 550 66 41 

Asian 157 109 12 3 

Some Others 182 103 10 8 

Hispanic 385 220 39 17 

Refused 126 87 5 7 

261 233 208 208 186 154 173 160 149 

37 26 29 18 31 23 33 15 22 

7 5 3 2 5 3 3 2 1 

9 5 7 3 2 3 5 4 4 

21 13 9 9 10 8 12 5 6 

3 3 2 2 2 1 2 * 3 

Hispanic No 8534 4868 573 396 

Yes 702 414 48 38 

DK 47 29 3 4 

Refused 103 70 4 6 

295 267 238 226 213 181 202 173 168 

38 16 18 14 21 10 23 11 13 

2 * 1 * 1 * 1 2 1 

3 2 1 2 1 1 2 * 3 

Employment * 1773 1149 143 91

Full Time 4096 2054 286 203

Part Time 802 421 51 42

Not Employed 2644 1709 145 105

Refused 71 48 3 3

74 50 39 29 26 28 27 22 14 

140 141 124 126 134 96 134 109 110 

36 25 32 27 17 23 28 12 16 

87 67 61 56 58 43 38 43 44 

1 2 2 4 1 2 1 * 1 

Education 

* 1968 1264 153 98

< High School 834 457 34 28

High School Graduate 2612 1297 160 115

< College 1801 972 114 87

College Graduate 1247 774 88 70

Post Graduate 924 617 79 46

81 56 49 38 30 31 30 27 18 

23 16 15 23 38 15 20 26 12 

94 86 92 84 69 71 93 64 76 

76 62 50 56 49 44 52 35 44 

42 38 32 24 32 23 20 22 21 

22 27 20 17 18 8 13 12 14 

Census Region Northeast 2075 1143 150 108

Midwest 2102 1164 145 110

South 3243 1834 206 137

West 1966 1240 127 89

66 73 61 63 54 52 56 40 38 

75 65 69 37 63 42 55 51 41 

116 106 76 92 85 58 87 60 76 

81 41 52 50 34 40 30 35 30 

Day of Week Weekday 6316 3655 430 301 227 188 164 146 171 127 169 128 116 

Weekend 3070 1726 198 143 111 97 94 96 65 65 59 58 69 

Season 

Winter 2524 1478 180 113

Spring 2438 1404 154 120

Summer 2536 1477 165 116

Fall 1888 1022 129 95

91 81 65 68 53 39 60 48 41 

82 73 73 61 61 50 58 40 61 

88 71 64 64 68 61 52 57 45 

77 60 56 49 54 42 58 41 38 

Asthma 

No 8629 4942 580 419 308 264 237 223 216 175 213 172 173 

Yes 694 396 42 24 29 20 20 17 20 16 13 13 12 

DK 63 43 6 1 1 1 1 2 * 1 2 1 * 

Angina No 9061 5169 610 430 331 273 252 235 233 187 223 184 181 

Yes 250 63 13 11 5 11 5 5 2 5 4 * 4 

DK 75 49 5 3 2 1 1 2 1 * 1 2 * 

Bronchitis/emphysema No 8882 5133 593 423 311 267 246 224 219 182 215 177 174 

Yes 433 197 30 20 24 17 11 16 17 10 11 7 11 

DK 71 51 5 1 3 1 1 2 * * 2 2 * 
Table 15-142 Range of Time (minutes) Spent Smoking Based on the Number of Respondents (continued) 

Number of Minutes 

660- 720- 780- 840- 900- 960- 1020- 1080- 1140- 1200- 1260- 1320- 1380-

720 780 840 900 960 1020 1080 1140 1200 1260 1320 1380 1440 

Overall 149 135 162 105 83 53 27 21 12 12 3 6 15 

Gender 

Male 84 76 87 

Female 65 59 75 

Refused * * * 

66 48 37 18 14 9 6 3 3 10 

39 35 17 9 7 3 6 * 3 5 

* * * * * * * * * * 

Age (years) * 2 1 1

1-4 3 5 6

5-11 7 2 5

12-17 7 3 5

18-64 119 114 129

> 64 11 10 16

1 * 2 * * * * * * 1 

3 2 3 2 2 1 * 1 * 1 

2 * 1 5 2 2 3 * * 2 

3 1 1 * * * 2 * * * 

91 72 44 18 17 9 5 2 5 10 

5 8 2 2 * * 2 * 1 1 

Race 

White 135 118 139 

Black 7 10 8 

Asian * * 2 

Some Others 3 2 6 

Hispanic 3 3 6 

Refused 1 2 1 

90 74 49 21 16 11 11 2 3 14 

9 6 3 5 2 1 * * 2 1 

* * * * * * * * * * 

2 2 * * 1 * 1 1 1 * 

2 1 * * 1 * * * * * 

2 * 1 1 1 * * * * * 

Hispanic No 141 127 149 

Yes 5 6 11 

DK 1 1 * 

Refused 2 1 2 

96 81 52 25 19 12 11 2 6 13 

8 2 1 1 1 * 1 1 * 1 

* * * * * * * * * 1 

1 * * 1 1 * * * * * 

Employment * 16 10 16

Full Time 83 82 82

Part Time 18 11 16

Not Employed 31 32 48

Refused 1 * *

8 3 5 7 4 3 5 1 * 3 

72 50 34 10 11 5 2 * 2 6 

6 10 2 2 3 * 2 * 1 1 

18 19 12 8 3 4 3 2 3 5 

1 1 * * * * * * * * 

Education 

* 19 12 18

< High School 15 24 34

High School Graduate 60 64 62

< College 36 22 29

College Graduate 11 9 12

Post Graduate 8 4 7

10 3 7 8 4 3 5 1 * 3 

16 16 7 6 2 1 1 * 2 3 

45 33 17 6 5 5 3 1 2 8 

18 23 12 5 6 3 2 1 2 1 

10 6 8 1 4 * * * * * 

6 2 2 1 * * 1 * * * 

Census Region Northeast 37 34 34

Midwest 36 28 36

South 52 63 60

West 24 10 32

23 20 10 2 4 2 2 * 1 2 

29 15 13 11 8 1 2 1 1 4 

37 37 21 11 6 7 5 * 4 7 

16 11 9 3 3 2 3 2 * 2 

Day of Week Weekday 95 84 103 63 55 38 17 12 8 8 2 1 8 

Weekend 54 51 59 42 28 15 10 9 4 4 1 5 7 

Season 

Winter 30 47 46

Spring 41 36 44

Summer 38 23 45

Fall 40 29 27

26 21 11 7 6 4 1 2 1 5 

29 10 14 5 5 4 5 1 2 5 

31 33 13 11 5 2 3 * 2 2 

19 19 15 4 5 2 3 * 1 3 

Asthma 

No 134 124 150 92 

Yes 15 9 11 13 

DK * 2 1 * 

77 47 24 20 9 9 3 5 13 

6 5 3 1 3 3 * 1 2 

* 1 * * * * * * * 

Angina No 141 130 157 103 82 

Yes 4 3 4 2 1 

DK 4 2 1 * * 

48 26 20 12 12 2 5 15 

4 1 1 * * 1 1 * 

1 * * * * * * * 

Bronchitis/emphysema No 139 128 150 91 75 48 25 20 11 9 3 4 15 

Yes 10 5 12 14 8 4 2 1 1 3 * 2 * 

DK * 2 * * * 1 * * * * * * * 

Note: * = Missing Data; DK =Don't know; N = Number of Respondents; Refused = Respondent Refused to Answer. 

Source: Tsang And Klepeis, 1996. 
Table 15-143 Number of Minutes Spent Smoking (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 9386 0 0 0 0 0 0 240 615 795 930 1035 1440 

Gender Male 4294 0 0 0 0 0 0 310 685 840 983 1095 1440 

Gender Female 5088 0 0 0 0 0 0 180 545 725 870 960 1440 

Age (years) 1-4 499 0 0 0 0 0 0 75 455 735 975 1095 1440 

Age (years) 5-11 703 0 0 0 0 0 0 82 370 625 975 1140 1440 

Age (years) 12-17 589 0 0 0 0 0 0 130 377 542 810 864 1260 

Age (years) 18-64 6059 0 0 0 0 0 0 345 675 830 950 1045 1440 

Age (years) > 64 1349 0 0 0 0 0 0 10 340 622 825 910 1440 

Race White 7591 0 0 0 0 0 0 250 630 805 940 1035 1440 

Race Black 945 0 0 0 0 0 0 225 540 715 910 1071 1440 

Race Asian 157 0 0 0 0 0 0 60 375 494 565 790 800 

Race Some Others 182 0 0 0 0 0 0 255 680 815 1140 1305 1328 

Race Hispanic 385 0 0 0 0 0 0 175 481 652 813 845 1095 

Hispanic No 8534 0 0 0 0 0 0 243 625 800 940 1035 1440 

Hispanic Yes 702 0 0 0 0 0 0 175 518 680 850 920 1440 

Employment Full Time 4096 0 0 0 0 0 0 360 687 835 945 1005 1440 

Employment Part Time 802 0 0 0 0 0 0 295 630 793 930 1054 1440 

Employment Not Employed 2644 0 0 0 0 0 0 144.5 555 768 915 1045 1440 

Education < High School 834 0 0 0 0 0 0 420 790 880 1004 1105 1440 

Education High School Graduate 2612 0 0 0 0 0 5 390 710 840 956 1060 1440 

Education < College 1801 0 0 0 0 0 0 288 630 805 945 1045 1435 

Education College Graduate 1247 0 0 0 0 0 0 135 480 660 860 970 1140 

Education Post Graduate 924 0 0 0 0 0 0 60 380 595 795 860 1205 

Census Region Northeast 2075 0 0 0 0 0 0 259 610 775 915 990 1440 

Census Region Midwest 2102 0 0 0 0 0 0 255 630 810 945 1054 1440 

Census Region South 3243 0 0 0 0 0 0 275 655 810 950 1060 1440 

Census Region West 1966 0 0 0 0 0 0 140 510 710 885 990 1440 

Day of Week Weekday 6316 0 0 0 0 0 0 225 595 780 925 1015 1440 

Day of Week Weekend 3070 0 0 0 0 0 0 260 651 810 950 1080 1440 

Season Winter 2524 0 0 0 0 0 0 210 600 790 930 1034 1440 

Season Spring 2438 0 0 0 0 0 0 240 626 785 920 1060 1440 

Season Summer 2536 0 0 0 0 0 0 235 600 810 940 1020 1440 

Season Fall 1888 0 0 0 0 0 0 285 630 791 945 1020 1440 

Asthma No 8629 0 0 0 0 0 0 240 610 790 928 1020 1440 

Asthma Yes 694 0 0 0 0 0 0 270 668 855 1020 1170 1440 

Angina No 9061 0 0 0 0 0 0 240 615 795 930 1034 1440 

Angina Yes 250 0 0 0 0 0 0 125 615 835 1007.5 1125 1380 

Bronchitis/emphysema No 8882 0 0 0 0 0 0 235 605 785 928 1020 1440 

Bronchitis/emphysema Yes 433 0 0 0 0 0 50 405 810 900 1040 1205 1380 

Note: N = Doer Sample Size; Percentiles are the Percentage of Doers below or Equal to a Given Number of Minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-144 Range of Time Spent Smoking Cigars or Pipe Tobacco by the Number of Respondents 

Total N Number of Minutes per Day 

*-* 0-3 3-6 6-9 9-12 12-15 15-18 18-61 

Overall 62 5 10 8 6 1 2 9 21 

Gender 

Male 58 5 8 7 6 1 2 9 20 

Female 4 * 2 1 * * * * 1 

Age (years) 

5-11 1 

12-17 1 

18-64 46 

> 64 14 

* * 1 * * * * * 

1 * * * * * * * 

3 10 4 6 1 1 5 16 

1 * 3 * * 1 4 5 

Race 

White 53 

Black 5 

Some Others 1 

Hispanic 3 

3 8 7 4 1 1 9 20 

1 2 1 1 * * * * 

1 * * * * * * * 

* * * 1 * 1 * 1 

Hispanic 

No 57 5 9 8 5 * 1 9 20 

Yes 5 * 1 * 1 1 1 * 1 

Employment 

* 2

Full Time 39

Part Time 3

Not Employed 17

Refused 1

1 * 1 * * * * * 

2 7 4 5 1 1 4 15 

* 3 * * * * * * 

1 * 3 1 * 1 5 6 

1 * * * * * * * 

Education 

* 2

< High School 2

High School Graduate 24

< College 18

College Graduate 10

Post Graduate 6

1 * 1 * * * * * 

* * * * * 1 * 1 

2 4 4 3 * * 3 8 

2 4 * * 1 * 4 7 

* 2 2 2 * * 1 3 

* * 1 1 * 1 1 2 

Census Region 

Northeast 20

Midwest 19

South 12

West 11

3 1 4 * 1 * 1 10 

* 4 4 2 * 1 4 4 

1 3 * 2 * 1 1 4 

1 2 * 2 * * 3 3 

Day of Week 

Weekday 40 3 7 5 2 1 * 7 15 

Weekend 22 2 3 3 4 * 2 2 6 

Season 

Winter 16

Spring 19

Summer 19

Fall 8

* 3 5 1 * 1 3 3 

3 4 1 1 * * 2 8 

1 1 1 4 1 1 2 8 

1 2 1 * * * 2 2 

Asthma 

No 59 5 8 8 6 1 2 8 21 

Yes 3 * 2 * * * * 1 * 

Angina 

No 60 5 10 8 6 1 2 8 20 

Yes 2 * * * * * * 1 1 

Bronchitis/emphysema 

No 60 4 10 8 6 1 2 8 21 

Yes 2 1 * * * * * 1 * 

Note: * Signifies missing data; Refused = respondents refused to answer; N = doer sample size in specified range of number of 

minutes spent. 

A value of "61" for number of minutes signifies that more than 60 minutes were spent. 

Source: Tsang and Klepeis, 1996. 
Table 15-145 Number of Minutes Spent Smoking Cigars or Pipe Tobacco (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 57 2 3 3 10 20 60 61 61 61 61 61 61 

Gender Male 53 3 5 10 10 20 60 61 61 61 61 61 61 

Gender Female 4 2 2 2 2 2.5 9 38 61 61 61 61 61 

Age (years) 5-11 1 15 15 15 15 15 15 15 15 15 15 15 15 

Age (years) 12-17 0 0 0 0 0 0 0 0 0 0 0 0 0 

Age (years) 18-64 43 2 2 3 10 15 45 61 61 61 61 61 61 

Age (years) > 64 13 15 15 15 20 45 60 61 61 61 61 61 61 

Race White 50 2 2.5 3 10 20 60 61 61 61 61 61 61 

Race Black 4 10 10 10 10 10 15 25 30 30 30 30 30 

Race Some Others 0 0 0 0 0 0 0 0 0 0 0 0 0 

Race Hispanic 3 30 30 30 30 30 45 61 61 61 61 61 61 

Hispanic No 52 2 3 3 10 20 60 61 61 61 61 61 61 

Hispanic Yes 5 10 10 10 10 30 40 45 61 61 61 61 61 

Employment Full Time 37 2 2 3 10 20 60 61 61 61 61 61 61 

Employment Part Time 3 3 3 3 3 3 10 10 10 10 10 10 10 

Employment Not Employed 16 15 15 15 20 37.5 60 61 61 61 61 61 61 

Education < High School 2 45 45 45 45 45 53 61 61 61 61 61 61 

Education High School Graduate 22 2 2 10 10 15 45 61 61 61 61 61 61 

Education < College 16 3 3 3 3 25 60 61 61 61 61 61 61 

Education College Graduate 10 5 5 5 7.5 20 30 61 61 61 61 61 61 

Education Post Graduate 6 20 20 20 20 30 52.5 61 61 61 61 61 61 

Census Region Northeast 17 10 10 10 20 20 61 61 61 61 61 61 61 

Census Region Midwest 19 2 2 2 3 15 30 60 61 61 61 61 61 

Census Region South 11 10 10 10 10 10 45 61 61 61 61 61 61 

Census Region West 10 10 10 10 10 30 60 61 61 61 61 61 61 

Day of Week Weekday 37 2 2 3 10 20 60 61 61 61 61 61 61 

Day of Week Weekend 20 3 3 6.5 10 20 37.5 61 61 61 61 61 61 

Season Winter 16 3 3 3 10 15 25 60 61 61 61 61 61 

Season Spring 16 2 2 2 5 15 60.5 61 61 61 61 61 61 

Season Summer 18 10 10 10 20 30 60 61 61 61 61 61 61 

Season Fall 7 3 3 3 3 10 60 61 61 61 61 61 61 

Asthma No 54 2 3 10 10 20 60 61 61 61 61 61 61 

Asthma Yes 3 3 3 3 3 3 5 60 60 60 60 60 60 

Angina No 55 2 3 3 10 20 60 61 61 61 61 61 61 

Angina Yes 2 60 60 60 60 60 60.5 61 61 61 61 61 61 

Bronchitis/emphysema No 56 2 3 3 10 20 60 61 61 61 61 61 61 

Bronchitis/emphysema Yes 1 60 60 60 60 60 60 60 60 60 60 60 60 

Note: A value of "61" for number of minutes signifies that more than 60 minutes were spent; N = doer sample size. Percentiles are the 

percentage of doers below or equal to a given number of minutes. 

Source: Tsang and Klepeis, 1996. 
Table 15-146 Range of Numbers of Cigarettes Smoked Based on the Number of Respondents 

Total N Number of Cigarettes Smoked by Respondent on the Day Before the Survey 

* None 1-2 3-5 6-9 10-14 15-24 25-35 36+ DK 

Overall 4663 530 3288 45 92 88 182 315 56 57 10 

Gender 

Male 2163 278 1467 

Female 2498 251 1820 

Refused 2 1 1 

24 38 32 81 167 30 43 3 

21 54 56 101 148 26 14 7 

* * * * * * * * 

Age (years) 

* 84 2

1-4 263 263

5-11 348 258

12-17 326 1

18-64 2972 5

> 64 670 1

72 1 1 * 2 3 1 1 1 

* * * * * * * * * 

88 * 1 * * 1 * * * 

315 * 1 3 2 3 * * 1 

2232 42 76 75 156 276 54 51 5 

581 2 13 10 22 32 1 5 3 

Race 

White 3774 413 

Black 463 53 

Aian 77 5 

Some Others 96 22 

Hispanic 193 37 

Refused 60 * 

2664 30 63 63 156 272 54 52 7 

319 7 18 22 17 22 1 1 3 

71 * * * * 1 * * * 

55 1 4 1 5 6 1 1 * 

133 7 5 2 2 7 * * * 

46 * 2 * 2 7 * 3 * 

Hispanic 

No 4244 452 

Yes 347 75 

DK 26 2 

Refused 46 1 

3010 33 79 79 173 297 56 55 10 

225 11 10 7 7 12 * * * 

18 * 2 2 1 1 * * * 

35 1 1 * 1 5 * 2 * 

Employment 

* 926 526

Full Time 2017 1

Part Time 379 * Not Employed 1309 3

Refused 32 *

388 * 2 3 2 3 * * 2 

1510 34 55 51 100 193 37 34 2 

307 5 7 6 23 22 4 3 2 

1058 6 28 28 57 92 14 20 3 

25 * * * * 5 1 * 1 

Education 

* 1021 526

< High School 399 3

High School Graduate 1253 1

< College 895 * College Graduate 650 * Post Graduate 445 *

473 * 4 3 4 8 * 1 2 

279 1 9 12 27 42 8 16 2 

899 16 44 35 73 138 23 23 1 

696 11 19 20 44 75 18 9 3 

547 11 10 13 26 32 5 5 1 

394 6 6 5 8 20 2 3 1 

Census Region 

Northeast 1048 112

Midwest 1036 110

South 1601 193

West 978 115

747 4 12 19 49 78 10 16 1 

746 11 25 19 29 73 13 8 2 

1079 17 37 34 76 108 29 24 4 

716 13 18 16 28 56 4 9 3 

Day of Week 

Weekday 3156 341 2239 28 66 61 116 217 38 43 7 

Weekend 1507 189 1049 17 26 27 66 98 18 14 3 

Season 

Winter 1264 163

Spring 1181 148

Summer 1275 142

Fall 943 77

883 16 23 21 50 71 18 14 5 

819 13 22 14 45 94 14 10 2 

906 7 20 32 47 89 12 17 3 

680 9 27 21 40 61 12 16 * 

Asthma 

No 4287 480 3023 

Yes 341 48 239 

DK 35 2 26 

40 85 80 171 292 51 56 9 

5 6 8 10 18 5 1 1 

* 1 * 1 5 * * * 

Angina 

No 4500 526 3161 

Yes 125 2 99 

DK 38 2 28 

45 88 85 175 304 52 54 10 

* 3 3 5 8 3 2 * 

* 1 * 2 3 1 1 * 

Bronchitis/emphysema 

No 4424 519 3138 43 80 81 170 284 48 52 9 

Yes 203 11 120 2 11 6 11 28 8 5 1 

DK 36 * 30 * 1 1 1 3 * * * 

Note: * = Missing Data; DK = Don't Know; N= Number of Respndents; Refused = Respondent Refused to Answer 

Source: Tsang and Klepeis, 1996. 
Table 15-147 Range of Number of Cigarettes Smoked by Other People Based on Number of Respondents 

Total N Number of Cigarettes Smoked By Others 

* None 1-2 3-5 6-9 10-14 15-24 25-35 36+ DK 

Overall 4723 898 3209 55 108 78 122 121 19 28 85 

Gender 

Male 2131 468 1403 

Female 2590 428 1806 

Refused 2 2 * 

21 35 39 61 46 11 12 35 

34 73 39 61 75 8 16 50 

* * * * * * * * 

Age (years) 

* 103 11

1-4 236 236

5-11 355 355

12-17 263 263

18-64 3087 32

> 64 679 1

82 * 2 * * 3 * 1 4 

* * * * * * * * * 

* * * * * * * * * 

* * * * * * * * * 

2506 46 97 74 116 109 16 24 67 

621 9 9 4 6 9 3 3 14 

Race 

White 3817 675 

Black 482 119 

Asian 80 21 

Some Others 86 29 

Hispanic 192 50 

Refused 66 4 

2616 42 89 70 106 107 18 24 70 

309 7 8 6 9 9 1 2 12 

57 1 * * 1 * * * * 

51 * * 1 3 1 * 1 * 

120 5 9 1 3 1 * 1 2 

56 * 2 * * 3 * * 1 

Hispanic 

No 4290 796 

Yes 355 95 

DK 21 4 

Refused 57 3 

2928 49 91 73 114 118 19 25 77 

223 5 15 3 7 1 * 1 5 

11 1 * 1 1 * * 2 1 

47 * 2 1 * 2 * * 2 

Employment 

* 847 845

Full Time 2079 * Part Time 423 21

Not Employed 1335 30

Refused 39 2

2 * * * * * * * * 

1740 28 64 50 73 59 9 10 46 

336 6 15 4 14 11 1 3 12 

1098 21 28 24 35 48 9 15 27 

33 * 1 * * 3 * * * 

Education 

* 947 897

< High School 435 * High School Graduate 1359 * < College 906 1

College Graduate 597 * Post Graduate 479 *

44 * 1 * * 4 * * 1 

336 6 18 9 17 16 4 10 19 

1097 25 38 40 47 62 9 9 32 

748 10 29 22 36 22 5 9 24 

536 9 15 5 17 11 * * 4 

448 5 7 2 5 6 1 * 5 

Census Region 

Northeast 1027 201

Midwest 1066 196

South 1642 320

West 988 181

690 14 29 18 14 32 3 4 22 

726 15 28 13 27 25 4 7 25 

1090 17 36 33 58 44 7 15 22 

703 9 15 14 23 20 5 2 16 

Day of Week 

Weekday 3160 596 2178 33 76 54 77 69 12 14 51 

Weekend 1563 302 1031 22 32 24 45 52 7 14 34 

Season 

Winter 1260 266

Spring 1257 270

Summer 1261 240

Fall 945 122

841 17 23 19 29 34 7 6 18 

821 14 35 22 27 32 4 10 22 

863 13 25 18 35 30 3 6 28 

684 11 25 19 31 25 5 6 17 

Asthma 

No 4342 802 2989 

Yes 353 95 196 

DK 28 1 24 

52 97 69 117 104 15 22 75 

3 10 9 5 16 4 6 9 

* 1 * * 1 * * 1 

Angina 

No 4561 894 3068 

Yes 125 1 110 

DK 37 3 31 

53 104 78 121 116 19 26 82 

2 3 * 1 4 * 2 2 

* 1 * * 1 * * 1 

Bronchitis/emphysema 

No 4458 875 3016 

Yes 230 21 163 

DK 35 2 30 

53 99 75 115 108 17 23 77 

2 8 3 7 12 2 5 7 

* 1 * * 1 * * 1 

Note: * = Missing Data; DK =Don't know; N = Number of Respondents; Refused = Respondent Refused to Answer. 

Source: Tsang And Klepeis, 1996. 
Table 15-148 Range of the Number of Cigarettes Smoked While at Home Based on the Number of Respondents 

Total N Number of Cigarettes Smoked by Respondent at Home 

* None 1-2 3-5 6-9 10-14 15-24 25-35 36+ DK 

Overall 4723 516 3358 51 193 126 224 180 23 29 23 

Gender 

Male 2131 277 1463 

Female 2590 237 1895 

Refused 2 2 * 

24 86 53 91 98 11 17 11 

27 107 73 133 82 12 12 12 

* * * * * * * * 

Age (years) 

* 103 8

1-4 236 236

5-11 355 268

12-17 263 2

18-64 3087 1

> 64 679 1

83 * 2 4 1 2 1 * 2 

* * * * * * * * * 

86 * * * 1 * * * * 

248 * 6 2 3 1 1 * * 

2352 47 170 110 193 150 21 26 17 

589 4 15 10 26 27 0 3 4 

Race 

White 3817 391 

Black 482 61 

Asian 80 13 

Some Others 86 17 

Hispanic 192 32 

Refused 66 2 

2700 30 152 103 208 164 22 28 19 

345 10 27 20 9 6 1 * 3 

65 * 2 * * * * * * 

58 1 3 1 2 3 * 1 * 

140 8 3 2 3 4 * * * 

50 2 6 * 2 3 * * 1 

Hispanic 

No 4290 451 

Yes 355 64 

DK 21 * 

Refused 57 1 

3045 41 182 121 210 167 23 29 21 

252 8 4 5 10 11 * * 1 

18 * 1 * 2 * * * * 

43 2 6 * 2 2 * * 1 

Employment 

* 847 514

Full Time 2079 1

Part Time 423 *

Not Employed 1335 1

Refused 39 *

322 * 5 1 3 1 1 * * 

1598 33 122 88 117 87 11 10 12 

346 4 17 10 27 12 3 3 1 

1060 14 47 27 76 78 7 16 9 

32 * 2 * 1 2 1 * 1 

Education 

* 947 514

< High School 435 * High School Graduate 1359 *

< College 906 2

College Graduate 597 *

Post Graduate 479 *

406 1 9 3 6 4 2 * 2 

309 5 20 17 32 26 7 12 7 

989 21 78 64 98 84 7 11 7 

701 17 51 25 56 39 4 5 6 

524 6 20 11 19 13 2 1 1 

429 1 15 6 13 14 1 * * 

Census Region 

Northeast 1027 121

Midwest 1066 102

South 1642 177

West 988 116

721 11 39 22 50 46 8 5 4 

764 12 52 32 53 33 5 7 6 

1159 16 62 51 81 63 8 14 11 

714 12 40 21 40 38 2 3 2 

Day of Week 

Weekday 3160 336 2277 32 129 87 134 118 14 18 15 

Weekend 1563 180 1081 19 64 39 90 62 9 11 8 

Season 

Winter 1260 153

Spring 1257 152

Summer 1261 139

Fall 945 72

873 18 53 39 59 42 10 6 7 

901 7 51 22 55 54 1 6 8 

896 10 44 33 64 53 7 10 5 

688 16 45 32 46 31 5 7 3 

Asthma 

No 4342 470 3100 

Yes 353 46 234 

DK 28 * 24 

45 176 112 208 165 20 25 21 

5 15 14 16 15 3 4 1 

1 2 * * * * * 1 

Angina 

No 4561 515 3225 

Yes 125 * 104 

DK 37 1 29 

49 188 123 217 173 23 26 22 

1 2 3 5 7 * 3 * 

1 3 * 2 * * * 1 

Bronchitis/emphysema 

No 4458 501 3179 

Yes 230 15 149 

DK 35 * 30 

46 179 121 210 159 21 20 22 

4 12 5 14 20 2 9 * 

1 2 * * 1 * * 1 

Note: * = Missing Data; DK =Don't Know; N= Number of Respondents; Refused = Respondent Refused to Answer 

Source: Tsang and Klepeis, 1996. 
Table 15-149. Differences in Time Use (hours/week) Grouped by Sex, Employment Status, and Marital Status a

for the Surveys Conducted in 1965 and 1975

Employed Men Employed Women Housewives Total

Urban Data Married Single Married Single Married Single

1965 (N=448) (N=73) (N=190) (N=152) (N=341) (N=14) (N=1

Sleep 53.1 50.6 53.8 52.6 53.9 58.8 53

Work for Pay 51.3 51.4 38.4 39.8 0.5 1.6 33

Family Care 9.0 7.7 28.8 20.6 50.0 45.7 25

Personal Care 20.9 22.2 20.3 21.7 22.6 23.0 21

Free Time 33.7 36.1 26.7 33.3 41.0 38.9 34

 Organizations 2.6 3.6 1.4 3.7 3.4 3.4 2

 Media 17.1 13.9 10.7 11.1 15.3 19.1 14

 Social Life 7.2 10.4 7.9 9.6 12.6 10.2 9

 Recreation 1.4 1.3 0.6 0.5 0.6 1.1 0

 Other Leisure 5.4 6.9 6.1 8.4 9.1 5.1 7

Total Time 168.0 168.0 168.0 168.0 168.0 168.0 168

(Free) (33.7) (36.1) (26.7) (33.3) (41.0) (38.9) (34

1975 (N=245) (N=87) (N=117) (N=108) (N=141) (N=28) (N=

Sleep 53.4 54.1 55.1 54.3 56.8 58.6 54

Work for Pay 47.4 40.0 30.1 38.8 1.1 0.0 32

Family Care 9.7 9.0 24.9 16.6 44.3 42.8 20

Personal Care 21.4 20.0 26.2 21.9 21.4 19.2 21

Free Time 36.1 44.9 31.7 36.4 44.4 47.4 38

 Organizations 3.7 4.8 1.1 4.4 4.8 3.0 3

 Media 18.9 18.5 15.6 14.5 20.4 27.2 18

 Social Life 6.4 8.9 6.6 8.9 10.1 9.1 7

 Recreation 1.3 4.1 0.8 0.5 0.7 0.4 1

 Other Leisure 5.8 8.6 6.5 8.1 8.4 7.7 7

Total Time 168.0 168.0 168.0 168.0 168.0 168.0 168

(Free) (36.1) (44.9) (31.7) (36.4) (44.4) (47.4) (38

Data weighted to ensure equal days of the week. a

Source: Robinson, 1977.
Table 15-150. Time Use (hours/week) Differences by Age for the Surveys Conducted in 1965 and 1975 a 

Mean Duration (hrs/wk) 

Age Group (years) 

18-25 25-35 36-45 46-55 56-65 

1965 1975 1965 1975 1965 1975 1965 1975 1965 1975 

Activity (N=200) (N=149) (N=321) (N=234) (N=306) (N=150) (N=252) (N=141) (N=156) (N=11

Sleep 54.2 55.4 52.5 53.9 53.1 54.7 53.9 55.4 53.6 56.

Work for Pay 32.6 27.0 29.2 33.4 33.1 34.4 33.4 31.0 35.9 20.

Family Care 21.2 15.3 30.4 21.6 25.4 20.4 24.9 23.2 20.4 23.

Personal Care 20.9 20.3 20.3 20.8 22.5 21.1 22.4 23.1 20.9 26.

Free Time 39.1 50.0 35.6 38.4 33.8 37.3 33.4 35.2 37.1 41.

 Organizations 4.8 8.4 3.0 4.2 3.0 3.3 2.0 3.1 2.9 3.

 Media 13.8 18.5 14.6 17.2 14.5 18.3 15.3 18.8 17.4 22.

 Social Life 11.3 10.7 10.3 8.7 8.4 7.8 8.6 5.4 8.1 6.

 Recreation 0.9 2.6 1.2 1.3 0.8 1.0 0.6 1.3 1.1 1.

 Other Leisure 8.3 9.8 6.5 7.0 7.1 6.9 6.9 6.6 7.6 8.

Total Time Free 168.0 168.0 168.0 168.0 168.0 168.0 168.0 168.0 168.0 168.

Time (39.1) (50.0) (35.6) (38.4) (33.8) (37.3) (33.4) (35.2) (37.1) (41.

 Data weighted to ensure equal days of the week. a 

Source: Robinson, 1977. 
Table 15-151. Time Use (hours/week) Differences by Education for the Surveys Conducted in 1965 and 1975 a 

Mean duration (hours/week) 

Age Group (in years) 

0-8 9-11 12 13-15 16+

Activity 

1965 1975 1965 1975 1965 1975 1965 1975 1965 1975 

(N=171) (N=75) (N=220) (N=114) (N=452) (N=319) (N=195) (N=137) (N=191) (N=144) 

Sleep 54.9 57.0 52.3 53.7 53.0 55.5 53.6 53.6 53.6 54.8 

Work for Pay 31.6 30.0 33.1 32.0 30.9 26.9 34.4 27.5 34.5 38.0 

Family Care 24.7 18.7 25.4 21.7 28.9 23.5 21.7 18.9 21.2 16.8 

Personal Care 20.8 22.9 20.9 22.0 21.1 22.1 21.7 10.5 22.7 22.3 

Free Time 35.9 39.4 36.1 38.6 34.1 40.0 36.5 47.5 35.9 36.1

 Organizations 1.8 3.0 1.5 2.2 2.5 3.7 5.8 9.1 4.7 4.1

 Media 19.3 18.0 16.5 20.7 14.2 19.0 13.3 19.7 12.5 16.2

 Social Life 7.7 8.4 9.8 7.9 9.5 8.5 9.0 7.7 10.2 8.1

 Recreation 0.9 1.3 1.4 0.7 0.7 1.3 1.1 2.0 0.9 1.3

 Other Leisure 6.3 8.7 7.0 7.1 7.2 7.5 7.4 9.0 7.7 6.4 

Total Time 168.0 168.0 168.0 (36.2) 168.0 168.0 168.0 168.0 (36.6) 168.0 168.0 (36.0) 168.0 (3

Free Time (36.0) (39.4) (38.6) (34.1) (40.0) (47.5) 

a Data weighted to ensure equal days of the week. 

Source: Robinson, 1977. 
a Table 15-152. Time Use (hours/week) Differences by Race for the Surveys Conducted in 1965 and 1975 

Mean duration (hours/week) 

White Black

 1965 1975 1965 1975 

(N = 1030) (N = 680) (N = 103) (N = 77) 

Activity Category 

Sleep 53.4 54.5 50.9 54.8 

Work for Pay 31.9 30.0 36.6 30.0 

Family Care 26.0 21.1 23.6 17.6 

Personal Care 21.8 22.1 20.0 21.0 

Free Time 34.9 40.3 36.9 44.6

 Organizations 2.8 4.4 3.0 4.9

 Media 14.8 18.7 15.7 19.6

 Social Life 9.3 8.2 9.1 9.8

 Recreation 1.1 1.5 0.6 0.4

 Other Leisure 6.9 7.5 8.4 9.9 

Total Time 168.0 168.0 168.0 168.0 

Free Time (34.9) (40.3) (36.8) (44.6) 

a Data weighted to ensure equal days of the week. 

Source: Robinson, 1977. 
c 

a Table 15-153. Mean Time Spent (hours/week) in Ten Major Activity Categories Grouped by Regions 

Totalb 

N=975 

Activity West North Central Northeast South 

Mean S.D.c 

N=200 N=304 N=185 N=286 

Activity Actegtory 

Market Work 23.44 29.02 27.34 24.21 26.15 23.83 

House/yard work 14.64 14.17 14.29 15.44 14.66 12.09 

Child care 2.50 2.82 2.32 2.66 2.62 5.14 

Services/shop 5.22 5.64 4.92 4.72 5.15 5.40 

Personal care 79.23 76.62 78.11 79.38 78.24 12.70 

Education 2.94 1.43 0.95 1.45 1.65 6.34 

Organizations 3.42 2.97 2.45 2.68 2.88 5.40 

Social 8.26 8.42 8.98 8.22 8.43 8.17 

entertainment 

Active leisure 5.94 5.28 4.77 5.86 5.49 7.81 

Passive leisure 22.47 21.71 23.94 23.47 22.80 13.35 

Total Time 168.00 168.00 168.00 168.00 168.00 0.09 

a Weighted for day of week, panel loss (not defined in report), and correspondence to Census. Data may not add to totals shown 

due to rounding. b N = surveyed population. 

S.D. = standard deviation.

Source: Hill, 1985. 
Table 15-154. Total Mean Time Spent (minutes/day) in Ten Major Activity Categories Grouped by Type of Day 

Time Duration (mins/day) 

Weekday Saturday Sunday 

[N = 831] [N = 831] [N = 831] a 

Activity Category 

Market Work 288.0 (257.7) 97.9 (211.9) 58.0 (164.8) b 

House/Yardwork 126.3 (119.3) 160.5 (157.2) 124.5 (133.3) 

Child Care 26.6 (50.9) 19.4 (51.5) 24.8 (61.9) 

Services/Shopping 48.7 (58.7) 64.4 (92.5) 21.6 (49.9) 

Personal Care 639.2 (114.8) 706.8 (169.8) 734.3 (156.5) 

Education 16.4 (64.4) 5.4 (38.1) 7.3 (48.0) 

Organizations 21.1 (49.7) 18.4 (75.2) 58.5 (104.5) 

Social Entertainment 54.9 (69.2) 1,114.1 (156.0) 110.0 (151.2) 

Active Leisure 37.9 (71.11) 61.4 (126.5) 64.5 (120.6) 

Passive Leisure 181.1 (121.9) 191.8 (161.6) 236.5 (167.1) 

Total Time 1,440 1,440 1,440 

a N = Number of respondents. 

b ( ) = Numbers in parentheses are standard deviations. 

Source: Hill, 1985. 
Table 15-155. Mean Time Spent (minutes/day) in Ten Major Activity Categories During Four Waves of Interviewsa 

Fall Winter Spring Summer Range of 

(Nov. 1, 1975) (Feb. 28, 1976) (June 1, 1976) (Sept. 21, 1976) Standard b 

N=861 N=861 N=861 Deviations 

b b b 

Activity Category Wave 1 Wave 2 Wave 3 Wave 4 

Market work 222.94 226.53 210.44 230.92 272-287 

House/yard work 133.16 135.58 143.10 119.95 129-156 

Child care 25.50 22.44 25.51 21.07 49-58 

Services/shop 48.98 44.09 44.61 47.75 76-79 

Personal care 652.95 678.14 688.27 674.85 143-181 

Education 22.79 12.57 2.87 10.76 32-93 

Organizations 25.30 22.55 23.21 29.91 68-87 

Social entertainment 63.87 67.11 83.90 72.24 102-127 

Active leisure 42.71 47.46 46.19 42.30 96-105 

Passive leisure 210.75 183.48 171.85 190.19 144-162 

Total Time 1440.00 1440.00 1440.00 1440.00 -­

Weighted for day of week, panel loss (not defined in report), and correspondence to Census. a 

Dates by which 50% of the interviews for each wave were taken. b 

Source: Hill, 1985. 
Table 15-156. Mean Time Spent (hours/week) in Ten Major 

Activity Categories Grouped by Gendera 

Time duration (hours/week) 

Men Women Men and Women 

n = 140 n = 561 n = 971 

Activity Category 

Market work 35.8 (23.6)b 17.9 (20.7) 26.2 (23.8) 

House/yard 8.5 (9.0) 20.0 (11.9) 14.7 (12.1) 

Child care 1.2 (2.5) 3.9 (6.4) 2.6 (5.2) 

Services/shop 3.9 (4.5) 6.3 (5.9) 5.2 (5.4) 

Personal care 77.3 (13.0) 79.0 (12.4) 78.2 (12.7) 

Education 2.3 (7.7) 1.1 (4.8) 1.7 (6.4) 

Organizations 2.5 (5.5) 3.2 (5.3) 2.9 (5.4) 

Social entertainment 7.9 (8.3) 8.9 (8.0) 8.4 (8.2) 

Active leisure 5.9 (8.2) 5.2 (7.4) 5.5 (7.8) 

Passive leisure 22.8 (14.1) 22.7 (12.7) 22.8 (13.3) 

Total time 168.1 168.1 168.1 

Detailed components of activities (87) are presented in Table 1A-4. a 

( ) = Numbers in parentheses are standard deviations. b 

Source: Hill, 1985. 
Table 15-157. Percent Responses of Children's "Play" (activities) Locations in Maryvale, Arizonaa 

Location Percent Responses Ranking of Children's "Play" 

Locationsc 

Preschool Primary Grades (K-3) Intermediate Grades 

n = 211 n = 45 (4-6) 

n = 66 

Residential Yards 143 124 132 Residential (Own and Others) b b b 

School Playgrounds 0 53 52 Parks and Recreation Areas 

Parks and Recreation Areas 42 53 33 Street/Path/Alley 

Commercial 2 24 27 Natural/Vacant Areas 

Industrial 0 0 2 School 

Institutional 1 2 0 Institutional 

Streets 3 24 41 Commercial 

Alleys 1 2 9 Parking Lots 

Parking Lots 0 9 9 Child Built Places 

Vacant Lots/Canals/Fields 1 7 8 Water 

Industrial 

Survey was conducted in Maryvale (West Central Phoenix), Arizona. a 

Percentages greater than 100, because many children played in more than one location. b 

Ranking of children's activity locations were obtained from other literature sources. c 

Source: Sell, 1989. 
Table 15-158. Occupational Tenure of Employed Individuals by Age and Sex a 

Median Tenure (years) 

Age Group (years) All Workers Men Women 

16-24 1.9 2.0 1.9 

25-29 4.4 4.6 4.1 

30-34 6.9 7.6 6.0 

35-39 9.0 10.4 7.0 

40-44 10.7 13.8 8.0 

45-49 13.3 17.5 10.0 

50-54 15.2 20.0 10.8 

55-59 17.7 21.9 12.4 

60-64 19.4 23.9 14.5 

65-69 20.1 26.9 15.6 

70 and older 21.9 30.5 18.8 

Total 6.6 7.9 5.4 

a Working population = 109.1 million persons 

Source: Carey, 1988. 
Table 15-159. Occupational Tenure for Employed Individuals Grouped by Sex and Race a 

Median Tenure (Years) 

Race All Individuals Men Women 

White 6.7 8.3 5.4 

Black 5.8 5.8 5.8 

Hispanic 4.5 5.1 3.7

 Working population = 109.1 million persons. a 

Source: Carey, 1988. 
Table 15-160. Occupational Tenure for Employed Individuals Grouped by Sex and Employment Status a 

Median Tenure (Years) 

Employment Status All Individuals Men Women 

Full-Time 7.2 8.4 5.9 

Part-Time 3.1 2.4 3.6 

a Working population = 109.9 million persons. 

Source: Carey, 1988. 
a Table 15-161. Occupational Tenure of Employed Individuals Grouped by Major Occupational Groups and Age 

Median Tenure (years) 

Occupational Group Age Group 

Totalb 16-24 25-34 35-44 45-54 55-64 65+ 

Executive, Administrative, and Managerial 8.4 2.4 5.6 10.1 15.1 17.9 26.3 

Professional Specialty 9.6 2.0 5.7 12.0 18.2 25.6 36.2 

Technicians and Related Support 6.9 2.2 5.7 10.9 17.7 20.8 22.2 

Sales Occupations 5.1 1.7 4.7 7.7 10.5 15.5 21.6 

Administrative Support, including Clerical 5.4 2.1 5.0 7.6 10.9 14.6 15.4 

Service Occupations 4.1 1.7 4.4 6.9 9.0 10.6 10.4 

Precision Production, Craft, and Repair 9.3 2.6 7.1 13.5 19.9 25.7 30.1 

Operators, Fabricators, and Laborers 5.5 1.7 4.6 9.1 13.7 18.1 14.7 

Farming, Forestry, and Fishing 10.4 2.9 7.9 13.5 20.7 30.5 39.8 

a Working population = 109.1 million persons. 

b Includes all workers 16 years and older 

Source: Carey, 1988. 
Table 15-162. Voluntary Occupational Mobility Rates for Workers Age 16 Years and Older a 

Age Group (years) Occupational Mobility Rateb 

(Percent) 

16-24 12.7 

25-34 6.6 

35-44 4.0 

45-54 1.9 

55-64 1.0 

64 and older 0.3 

Total, age 16 and older 5.3 

a Working population = 109.1 million persons. 

b Occupational mobility rate = percentage of persons employed in an occupation who had voluntarily entered it from 

another occupation. 

Source: Carey, 1990. 
Table 15-163. Values and Their Standard Errors for Average Total Residence Time, T, for Each Group in Surveya 

Average total Households (percent) 

residence time S.D.ST Average current 

Households T (years) residence 1985 1987 

TCR (years) 

All households 4.55 ± 0.60 8.68 10.56±0.10 100.0 100.0 

Renters 2.35±0.14 

Owners 11.36±3.87 

Farms 17.31±13.81 

Urban 4.19±0.53 

Rural 7.80±1.17 

Northeast region 7.37±0.88 

Midwest region 5.11±0.68 

South region 3.96±0.47 

West region 3.49±0.57 

4.02 4.62±0.08 36.5 36.0 

13.72 13.96±0.12 63.5 64.0 

18.69 18.75±0.38 2.1 1.9 

8.17 10.07±0.10 74.9 74.5 

11.28 12.06±0.23 25.1 25.5 

11.48 12.64±0.12 21.2 20.9 

9.37 11.15±0.10 25.0 24.5 

8.03 10.12±0.08 34.0 34.4 

6.84 8.44±0.11 19.8 20.2 

a

Values of the average current residence time, T , are given for comparison. CR 

Source: Israeli and Nelson, 1992. 
Table 15-164. Total Residence Time, t (years), Corresponding to Selected Values of R(t) by Housing Category a 

R(t) = 0.05 0.1 0.25 0.5 0.75 

All households 23.1 12.9 3.7 1.4 0.5 

Renters 8.0 5.2 2.6 1.2 0.5 

Owners 41.4 32.0 17.1 5.2 1.4 

Farms 58.4 48.3 26.7 10.0 2.4 

Urban 21.7 10.9 3.4 1.4 0.5 

Rural 32.3 21.7 9.1 3.3 1.2 

Northeast region 34.4 22.3 7.5 2.8 1.0 

Midwest region 25.7 15.0 4.3 1.6 0.6 

South region 20.7 10.8 3.0 1.2 0.4 

West region 17.1 8.9 2.9 1.2 0.4

a R(t) = fraction of households living in the same residence for t years or more. 

Source: Israeli and Nelson, 1992. 
Table 15-165. Residence Time of Owner/Renter Occupied Units

Year household moved into unit Total occupied units (numbers in thousands)

1990-1994 24,534

1985-1989 27,054

1980-1984 10,613

1975-1979 9,369

1970-1974 6,233

1960-1969 7,933

1950-1959 4,754

1940-1949 1,772

1939 or earlier 885

Total 93,147

Source: U.S. Bureau of the Census, 1993b.
Table 15-166. Percent of Householders Living in Houses for Specified Ranges of Time

Years lived in current home Percent of total households

0-4 26.34

5-9 29.04

10-14 11.39

15-19 10.06

20-24 6.69

25-34 8.52

35-44 5.1

45-54 1.9

> 55 0.95

Total 99.99 a

a Total does not equal 100 due to rounding errors.

Source: Adapted from U.S. Bureau of the Census, 1993b.
Table 15-167. Descriptive Statistics for Residential Occupancy Period 

Statistic 

Mean

5th percentile

10th percentile

25th percentile

50th percentile

75th percentile

90th percentile

95th percentile

98th percentile

99th percentile

99.5th percentile

99.8th percentile

99.9th percentile

Second largest value

Largest value

a = Number of simulated persons 

Source: Johnson and Capel, 1992. 

Residential occupancy period (years) 

Both genders Males only Females only 

Na = 500,000 N = 244,274 N = 255,726 

11.7 11.1 12.3

2 2 2

2 2 2

3 4 5

9 8 9

16 15 17

26 24 28

33 31 35

41 39 43

47 44 49

51 48 53

55 53 58

59 56 61

75 73 75

87 73 87
Table 15-168. Descriptive Statistics for Both Genders by Current Age 

Residential occupancy period (years) 

Percentile Current 

age, years Mean 25 50 75 90 95 99 

3 6.5 3 5 8 13 17 22 

6 8.0 4 7 10 15 18 22 

9 8.9 5

12 9.3 5

15 9.1 5

18 8.2 4

21 6.0 2

24 5.2 2

27 6.0 3

30 7.3 3

33 8.7 4

36 10.4 5

39 12.0 5

42 13.5 6

45 15.3 7

48 16.6 8

51 17.4 9

54 18.3 9

57 19.1 10

60 19.7 11

63 20.2 11

66 20.7 12

69 21.2 12

72 21.6 13

75 21.5 13

78 21.4 12

81 21.2 11

84 20.3 11

87 20.6 10

90 18.9 8

All ages 11.7 4

Source: Johnson and Capel, 1992. 

8 12 16 18 22 

9 13 16 18 23 

8 12 16 18 23 

7 11 16 19 23 

4 8 13 17 23 

4 6 11 15 25 

5 8 12 16 27 

6 9 14 19 32 

7 11 17 23 39 

8 13 21 28 47 

9 15 24 31 48 

11 18 27 35 49 

13 20 31 38 52 

14 22 32 39 52 

15 24 33 39 50 

16 25 34 40 50 

17 26 35 41 51 

18 27 35 40 51 

19 27 36 41 51 

20 28 36 41 50 

20 29 37 42 50 

20 29 37 43 53 

20 29 38 43 53 

19 29 38 44 53 

20 29 39 45 55 

19 28 37 44 56 

18 29 39 46 57 

15 27 40 47 56 

9 16 26 33 47 
Table 15-169. Summary of Residence Time of Recent Home Buyers (1993) 

Number of years lived in previous house Percent of Respondents 

1 year or less 2 

2-3 16 

4-7 40 

8-9 10 

10 years or more 32 

Source: NAR, 1993 
Table 15-170. Tenure in Previous Home (Percentage Distribution) 

Percent 

1987 1989 1991 1993 

One year or less 5 8 4 2 

2-3 Years 25 15 21 16 

4-7 Years 36 22 37 40 

8-9 Years 10 11 9 10 

10 or More Years 24 34 29 32

 Total 100 100 100 100 

Median 6 6 6 6 

Source: NAR, 1993 
Table 15-171. Number of Miles Moved (Percentage Distribution) 

First-Time Repeat Buyer New Home Existing Home 

All Buyers Buyer Buyer Buyer 

Miles Percent 

Less than 5 miles 29 33 27 23 31 

5 to 9 miles 20 25 16 18 20 

10 to 19 miles 18 20 17 20 17 

20 to 34 miles 9 11 8 12 9 

35 to 50 miles 2 2 2 2 3 

51 to 100 miles 5 2 6 6 4 

Over 100 miles 17 6 24 19 16 

Total 100 100 100 100 100 

Median 9 8 11 11 8 

Mean 200 110 270 230 190 

Source: NAR, 1993 
Table 15-172. Confidence in Activity Patterns Recommendations 

Considerations Rationale Rating 

TIME SPENT INDOORS VS. OUTDOORS 

Study Elements 

• Level of peer review The studies received high level of peer review. High 

• Accessibility The studies are widely available to the public. High 

• Reproducibility The reproducibility of these studies is left to question. Evidence has shown Medium 

that activities have tended to shift over the past decade since the studies were 

published, due to economic conditions and technological developments, etc. 

Thus, it is assumed there would be differences in reproducing these results. 

However, if data were reanalyzed in the same manner the results are 

expected to be the same. 

• Focus on factor of The study focused on general activity patterns. One study delineated High 

interest between indoor and outdoor use of time but in many cases the locations 

were specified. Thus, any assumptions were made about the indoor or 

outdoor location where event took place. 

• Data pertinent to US The studies focused on the U.S. population and California. High 

• Primary data One study analyzed data from a two primary studies. Data from the High 

remaining study was collected to via questionnaires and interviews. 

• Currency The studies were published in 1985 (data was collected 1981-1982), 1987, Medium 

1991 (data was collected 1987-1990) and 1992. 

• Adequacy of data In one study, households were sampled 4 times during 3 month intervals from High 

collection period February to December, 1981. Robinson’s data was based on 1) the CARB 

Study where data was collected October 1987 to August 1988; and 2) the 

National Study where data was collected January through December 1985. 

• Validity of approach The approach used to collect data was direct and included questionnaires or High 

interviews. Responses where based on diaries and ‘mailback’ surveys based 

on what the person planned to do the following day (the “tomorrow 

approach”). A 24 hour diary was used in another study. 

• Study size The study sizes ranged from 922 to 5,000 depending on the sub-group High 

considered. 

• Representativeness of Timmer focused on activities of children. Robinson studies activities of both High 

the population children and adults. The studies are representative of the US population and 

California State. 

• Characterization of Variability was characterized by age, gender, and day of the week; location of Medium 

variability activities and various age categories for children. There was no mention of 

race and no socio-economic characterizations made. 

• Lack of bias in study Biases noted were sampled during time when children were in school Medium 

design (high rating is (activities during vacation time are not represented); activities in the 1980's 

desirable) may different than they are now; 

• Measurement error Measurement or recording error may occur since the diaries were based on Medium 

recall (in most cases a 24 hour recall). 

Other Elements 

• Number of studies Two High 

• Agreement between Difficult to compare due to varying categories of activities and the unique age Not 

researchers distributions found within each study. Ranked 

Overall Rating Medium 
Table 15-172. Confidence in Activity Patterns Recommendations (continued) 

Considerations Rationale Rating 

TIME SPENT IN A VEHICLE 

Study Elements 

• Level of peer review The study received high level of peer review. High 

• Accessibility The study is widely available to the public. High 

• Reproducibility The reproducibility of these studies is left to question. Evidence has shown Medium 

that activities have tended to shift over the past decade since the studies were 

published, due to economic conditions, technological developments, etc. 

Thus, it is assumed there would be differences in reproducing these results. 

• Focus on factor of The study focused specifically focused on time spent in vehicle. High 

interest 

• Data pertinent to US The studies focused on the U.S. population and California. High 

• Primary data Robinson’s study analyzed data from two primary studies, thus it secondary High 

data. 

• Currency The studies were published in 1985 (data was collected 1981-1982), 1987, Medium 

1991 (data was collected 1987-1990) and 1992. 

• Adequacy of data In one study, households were sampled 4 times during 3 month intervals from High 

collection period February to December, 1981. Robinson’s data was based on 1) the Wiley et 

al. (1991) Study where data was collected October 1987 to August 1988; 

and 2) the National Study where data was collected January through 

December 1985. 

• Validity of approach The approach used to collect primary data was based on diary entries High 

recorded the previous day with follow-up telephone interviews. Another study 

collected time diary data via mailback of questionnaires, telephone interviews. 

‘Mailback’ surveys were based on the “tomorrow approach” where person 

knew they were to record in diaries in advance. 

• Study size The study sizes ranged from 922 to 5,000 depending on the sub-group High 

considered. 

• Representativeness of The studies are representative of the US population and California State. High 

the population 

• Characterization of Variability was characterized by age, gender, and day of the week. There was Medium 

variability no mention of race and no socio-economic characterizations made. 

• Lack of bias in study Both studies lacked time distributions and were based on short-term data. Medium 

design (high rating is Wiley et al. (1991) data was based recall, is limited to California’s population, 

desirable) and only considered English speaking households. 

• Measurement error Measurement or recording error may occur when diaries were based on 24 Medium 

hr recall. 

Other Elements 

• Number of studies One secondary study analyzing two primary studies Medium 

• Agreement between Similar activity patterns were found in both studies. High 

researchers 

Overall Rating Medium 
Table 15-172. Confidence in Activity Patterns Recommendations (continued) 

Considerations Rationale Rating 

TIME SPENT SHOWERING 

Study Elements 

• Level of peer review The study received high level of peer review. High 

• Accessibility Currently, raw data are available to only EPA. It is not known when data will Low 

be publicly available. 

• Reproducibility Results are reproducible. High 

• Focus on factor of The study focused specifically focused on time spent showering. High 

interest 

• Data pertinent to US The study focused on the U.S. general population. High 

• Primary data The study was based on primary data. High 

• Currency The study was published in 1996. High 

• Adequacy of data The data were collected between October 1992 and September 1994. High 

collection period 

• Validity of approach The study used a valid methodology and approach which, in addition to 24­ High 

hour diaries, collected information on temporal conditions and demographic 

data such as geographic location and socioeconomic status for various U.S. 

subgroups. 

• Study size Study consisted of 9,386 total participants.. High 

• Representativeness of The data were representative of the U.S. population. High 

the population 

• Characterization of The study provides a distribution on showering duration. High 

variability 

• Lack of bias in study The study includes distributions for showering duration. Study is based on High 

design (high rating is short-term data. 

desirable) 

• Measurement error Measurement or recording error may occur because diaries are based on 24­ Medium 

hour recall. 

Other Elements 

• Number of studies One; the study was a national study. Low 

• Agreement between Recommendation is based on only one study but it is a widely accepted study High 

researchers and average value is comparable to a second key study. 

Overall Rating High 
Table 15-172. Confidence in Activity Patterns Recommendations (continued) 

Considerations Rationale Rating 

TIME SPENT BATHING 

Study Elements 

• Level of peer review The study received high level of peer review. High 

• Accessibility Currently, raw data are available to only EPA. It is not known when data will Low 

be publicly available. 

• Reproducibility Results can be reproduced or methodology can be followed and evaluated High 

provided comparable economic and social conditions exists. 

• Focus on factor of The survey collected information on duration and frequency of selected High 

interest activities and time spent in selected micro-environments. 

• Data pertinent to US The data represents the U.S. population. High 

• Primary data The study was based on primary data. High 

• Currency The study was published in 1996. High 

• Adequacy of data The data were collected between October 1992 and September 1994. High 

collection period 

• Validity of approach The study used a valid methodology and approach which, in addition to 24­ High 

hour diaries, collected information on temporal conditions and demographic 

data such as geographic location and socioeconomic status for various U.S. 

subgroups. Responses were weighted according to this demographic data. 

• Study size The study consisted of 9,386 total participants. High 

• Representativeness of The studies were based on the U.S. population. High 

the population 

• Characterization of The study provided data that varied across geographic region, race, gender, High 

variability employment status, educational level, day of the week, seasonal conditions, 

and medical conditions of respondent.. 

• Lack of bias in study The study includes distributions for bathing duration. Study is based on Medium 

design (high rating is short-term data. 

desirable) 

• Measurement error Measurement or recording error may occur because diaries were based on Medium 

24-hour recall. 

Other Elements 

• Number of studies One; the study was based on one, primary, national study. Low 

• Agreement between Recommendation was based on only one study. Not 

researchers Ranked 

Overall Rating High 
Table 15-172. Confidence in Activity Patterns Recommendations (continued) 

Considerations Rationale Rating 

SHOWER AND BATHING FREQUENCY 

Study Elements 

• Level of peer review The study received high level of peer review. High 

• Accessibility Currently, raw data is available to only EPA. It is not known when data will be Low 

publicly available. 

• Reproducibility Results can be reproduced or methodology can be followed and evaluated High 

provided comparable economic and social conditions exists. 

• Focus on factor of The survey collected information on duration and frequency of selected High 

interest activities and time spent in selected micro-environments. 

• Data pertinent to US The data represents the U.S. population High 

• Primary data The study was based on primary data. High 

• Currency The study was published in 1996. High 

• Adequacy of data The data were collected between October 1992 and September 1994. High 

collection period 

• Validity of approach The study used a valid methodology and approach which, in addition to 24­ High 

hour diaries, collected information on temporal conditions and demographic 

data such as geographic location and socioeconomic status for various U.S. 

subgroups. Responses were weighted according to this demographic data. 

• Study size The study consisted of 9,386 total participants High 

• Representativeness of Studies were based on the U.S. population. High 

the population 

• Characterization of The study provided data that varied across geographic region, race, gender, High 

variability employment status, educational level, day of the week, seasonal conditions, 

and medical conditions of respondent.. 

• Lack of bias in study Study is based on short term data.. Medium 

design (high rating is 

desirable) 

• Measurement error Measurement or recording error may occur because diaries were based on Medium 

24-hour recall. 

Other Elements 

• Number of studies One; the study was based on one, primary, national study. Low 

• Agreement between Recommendation was based on only one study. Not 

researchers Ranked 

Overall Rating High 
Table 15-172. Confidence in Activity Patterns Recommendations (continued) 

Considerations Rationale Rating 

TIME SPENT SWIMMING 

Study Elements 

• Level of peer review Study received high level of peer review. High 

• Accessibility Currently, raw data is available to only EPA. It is not known when data will be Low 

publicly available. 

• Reproducibility Results can be reproduced or methodology can be followed and evaluated High 

provided comparable economic and social conditions exists. 

• Focus on factor of The survey collected information on duration and frequency of selected High 

interest activities and time spent in selected micro-environments. 

• Data pertinent to US The data represents the U.S. population High 

• Primary data The study was based on primary data. High 

• Currency The study was published in 1996. High 

• Adequacy of data The data were collected between October 1992 and September 1994. High 

collection period 

• Validity of approach The study used a valid methodology and approach which, in addition to 24­ High 

hour diaries, collected information on temporal conditions and demographic 

data such as geographic location and socioeconomic status for various U.S. 

subgroups. Responses were weighted according to this demographic data. 

• Study size The study consisted of 9,386 total participants High 

• Representativeness of Studies were based on the U.S. population. High 

the population 

• Characterization of The study provided data that varied across geographic region, race, gender, High 

variability employment status, educational level, day of the week, seasonal conditions, 

and medical conditions of respondent.. 

• Lack of bias in study The study includes distributions for swimming duration. Study is based on Medium 

design (high rating is short term data. 

desirable) 

• Measurement error Measurement or recording error may occur because diaries were based on Medium 

24-hour recall. 

Other Elements 

• Number of studies One; the study was based on one, primary, national study. Low 

• Agreement between Recommendation was based on only one study. Not 

researchers Ranked 

Overall Rating High 
Table 15-172. Confidence in Activity Patterns Recommendations (continued) 

Considerations Rationale Rating 

RESIDENTIAL TIME SPENT INDOORS AND OUTDOORS 

Study Elements 

• Level of peer review The study received high level of peer review. High 

• Accessibility Currently, raw data is available to only EPA. It is not known when data will be Low 

publicly available. 

• Reproducibility Results can be reproduced or methodology can be followed and evaluated High 

provided comparable economic and social conditions exists. 

• Focus on factor of The survey collected information on duration and frequency of selected High 

interest activities and time spent in selected micro-environments. 

• Data pertinent to US The data represents the U.S. population High 

• Primary data The study was based on primary data. High 

• Currency The study was published in 1996. High 

• Adequacy of data Data were collected between October 1992 and September 1994. High 

collection period 

• Validity of approach The study used a valid methodology and approach which, in addition to 24­ High 

hour diaries, collected information on temporal conditions and demographic 

data such as geographic location and socioeconomic status for various U.S. 

subgroups. Responses were weighted according to this demographic data. 

• Study size The study consisted of 9,386 total participants High 

• Representativeness of The studies were based on the U.S. population. High 

the population 

• Characterization of The study provided data that varied across geographic region, race, gender, High 

variability employment status, educational level, day of the week, seasonal conditions, 

and medical conditions of respondent.. 

• Lack of bias in study The study includes distribitions for time spent indoors and outdoors at ones Medium 

design (high rating is residence. Study is based on short term data. 

desirable) 

• Measurement error Measurement or recording error may occur because diaries were based on Medium 

24-hour recall. 

Other Elements 

• Number of studies One; the study was based on one, primary, national study. Low 

• Agreement between Recommendation was based on only one study. Not 

researchers Ranked 

Overall Rating High 
Table 15-173. Confidence in Occupational Mobility Recommendations 

Considerations Rationale Rating 

Study Elements 

• Level of peer review The studies received high level of peer review High 

• Accessibility The studies are widely available to the public. High 

• Reproducibility If the data were re-collected in the same fashion, it is questionable whether Medium 

the results would be the same based on changes in the economy that have 

occurred since study was conducted (more than 10 years ago). If the same 

data were analyzed according to the design of the study then it is expected 

the results would be the same. 

• Focus on factor of Occupational tenure was the focus of both key studies. High 

interest 

• Data pertinent to US The data represents the U.S. population. High 

• Primary data The two studies are secondary data sources since they are based on Medium 

supplemental data to the January 1987 Current Population Study (a U.S. 

Census publication). 

• Currency The studies were published in 1988 (data was collection in 1987) and 1990 Medium 

(data collected from 1986-1987). 

• Adequacy of data The studies are based on census data, which is collected over a period of High 

collection period years. One study analyzed data for January 1987. The remaining study 

based data between a January 1986 and January 1987 time frame. 

• Validity of approach The studies used a valid methodologies and approaches. High 

• Study size The study size for one is 109 Million; the remaining study’s sample size was High 

100.1 Million. 

• Representativeness of The data are representative of the U.S. population. High 

the population 

• Characterization of The studies provided averaged data according to gender, race, and High 

variability education; age averages and percentiles were provided. 

• Lack of bias in study Much of the original study data is not available. Only median values are Medium 

design (high rating is reported. 

desirable) 

• Measurement error There is no apparent error in measurement High 

Other Elements 

• Number of studies Two Medium 

• Agreement between Difficult to compare between the number of years worked on a job and entry Not 

researchers verses exit rate of various occupations. One set of data was recorded in Ranked 

number of years. The other set of data was recorded as a percent motility 

rate and grouped by age. 

Overall Rating High 
Table 15-174. Recommendations for Population Mobility 

Study Value Method 

Israeli and Nelson, 1992 4.6 yr (averge) Average of current and total 

1/6 a person’s lifetime residence times

 (70 yr) = 11.7 (modeled) 

US Bureau of the Census, 1993 9 yr (50th percentile) Current residence time 

33 yr (90th percentile) 

Johnson and Capel, 1992 26 yr (90th percentile) Residential occupancy period 

33 yr (95th percentile) 

47 yr (99th percentile) 

12 yr (mean) 
Table 15-175. Confidence in Population Mobility Recommendations 

Considerations Rationale Rating 

Study Elements 

• Level of peer review The studies received high levels of peer review and appear in publications. High 

• Accessibility The studies are widely available to the public. High 

• Reproducibility Results can be reproduced or methodology can be followed and evaluated. High 

• Focus on factor of The Census data provided length of time at current. Two of the studies used Medium 

interest modeling to estimate total time. 

• Data pertinent to US The data is based on the U.S. population High 

• Primary data Two studies based results on modeled data and one based results on Medium 

interviews. 

• Currency The reports were published in 1992 (based on data collected in 1985-1987) Medium 

and 1993 (based on data collected from 1939 and 1994 (projected) . 

• Adequacy of data The collection period was based on data collected over several years. High 

collection period 

• Validity of approach There are some concerns regarding the validity of approach. Data does not Medium 

account for each member of the household, values are more realistic 

estimates for the individual’s total residence time, than the average time a 

household has been living at its current residence. The moving process was 

modeled. In another study data was assumed to have an even distribution 

within the different ranges which may bias the 50th and 90th percentiles. 

• Study size The study size ranged from 15,000 to 500, 000. High 

• Representativeness of Studies were based on the U.S. population. High 

the population 

• Characterization of Variability across several geographic regions was noted. Type of ownership Medium 

variability was also addressed. One study provided data grouped by race. 

• Lack of bias in study Mentioned above in validity of approach section. Not 

design (high rating is Ranked 

desirable) 

• Measurement error There is no apparent error in measurement. High 

Other Elements 

• Number of studies Three High 

• Agreement between The studies produced very similar results. High 

researchers 

Overall Rating Medium 
Table 15-176. Summary of Recommended Values for Activity Factors 

Type Value Study 

Indoor Activities Children (ages 3-11) 

19 hr/day (weekdays) 

17 hr/day (weekends) 

Adults (ages 12 and older) 

21 hr/day 

Timmer et al., 1985 -Key study 

Timmer et al., 1985 -Key study 

Robinson and Thomas, 1991 - Key 

study 

Outdoor Activities Children 

5 hr/day (weekdays) 

7 hr/day (weekends) 

Adults 

1.5 hr/day 

Timmer et al., 1985 -Key study 

Timmer et al., 1985 -Key study 

Robinson and Thomas, 1991 - Key 

study 

Time Spent Inside 

Vehicle 

Adults 

1.3 hr/day 

Robinson and Thomas, 1991 - Key 

study 

Tsang and Klepeis, 1996 - Key study 

Taking Baths 20 minutes/event Tsang and Klepeis, 1996 - Key study 

Taking Showers 10 min/day shower duration 

1 shower event/day 

Tsang and Klepeis, 1996 - Key study 

Tsang and Klepeis, 1996 - Key study 

Occupational Tenure 6.6 yrs (16 years and older) Carey, 1988 - Key study 

Population Mobility Average: 9 yr 

95th percentile: 30 yr 

US Bureau of the Census, 1993; 

Israeli and Nelson, 1992; Johnson 

and Capel, 1992 - Key study 

Swimming 1 event/month 

60 minutes/event 

Tsang and Klepeis, 1996 - Key study 

Residential 

Indoors

 Outdoors 16.4 hr/day 

2 hr/day 

Tsang and Klepeis, 1996 - Key study
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries 

WORK AND OTHER INCOME-PRODUCING ACTIVITIES 

Paid Work 

01 - Normal work: activities at the main job including work brought home, travel that is part of the job, and 

overtime; "working," "at work" 

- Work at home; work activities for pay done in the home when home is the main workplace (include 

travel as above) 

02 - Job search; looking for work, including visits to employment agencies, phone calls to prospective 

employers, answering want ads

- Unemployment benefits; applying for or collecting unemployment compensation

- Welfare, food stamps; applying for or collecting welfare, food stamps

05 - Second job; paid work activities that are not part of the main job (use this code only when R* clearly 

indicates a second job or "other" job); paid work for those not having main job; garage sales, rental 

property 

06 - Lunch at the workplace; lunch eaten at work, cafeteria, lunchroom when "where" = work (lunch at 

a restaurant, code 44; lunch at home, code 43) 

- Eating, smoking, drinking coffee as a secondary activity while working (at workplace) 

07 - Before and/or after work at the workplace; activities at the workplace before starting or after stopping 

work; include "conversations," other work. Do not code secondary activities with this primary activity 

- Other work-related 

08 - Coffee breaks and other breaks at the workplace; unscheduled breaks and other nonwork during 

work hours at the workplace; "took a break"; "had coffee" (as a primary activity). Do not code 

secondary activities with this primary activity 

09 - Travel; to and from the workplace when R's travel to and from work were both interrupted by stops; 

waiting for related travel 

- Travel to and from the workplace, including time spent awaiting transportation 

HOUSEHOLD ACTIVITIES 

Indoor 

10 - Meal preparation: cooking, fixing lunches 

- Serving food, setting table, putting groceries away. unloading car after grocery shopping 

11 - Doing dishes, rinsing dishes, loading dishwasher 

- Meal cleanup, clearing table, unloading dishwasher 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

HOUSEHOLD ACTIVITIES (continued) 

Indoor (continued) 

12 - Miscellaneous, "worked around house." NA if indoor or outdoor - Routine indoor cleaning and chores, 

picking up, dusting, making beds, washing windows, vacuuming, "cleaning," "fall/spring cleaning," 

"housework" 

14 - Laundry and clothes care - wash 

- Laundry and clothes care - iron, fold, mending, putting away clothes ("Sewing" code 84) 

16 - Repairs indoors; fixing, repairing appliances 

- Repairs indoors; fixing, repairing furniture 

- Repairs indoors; fixing, repairing furnace, plumbing, painting a room 

17 - Care of houseplants 

19 - Other indoor, NA whether cleaning or repair; "did things in house" 

Outdoor 

13 - Routine outdoor cleaning and chores; yard work, raking leaves, mowing grass, garbage removal, 

snow shoveling, putting on storm windows, cleaning garage, cutting wood 

16 - Repair, maintenance, exterior; fixing repairs outdoors, painting the house, fixing the roof, repairing the 

driveway (patching) 

- Home improvements: additions to and remodeling done to the house, garage; new roof 

- Improvement to grounds around house; repaved driveway 

17 - Gardening; flower or vegetable gardening; spading, weeding, composting, picking, worked in garden" 

19 - Other outdoor; "worked outside," "puttering in garage 

MISCELLANEOUS HOUSEHOLD CHORES 

16 - Car care; necessary repairs and routine care to cars; tune up 

- Car maintenance; changed oil, changed tires, washed cars; "worked on car" except when clearly as 

a hobby - (code 83) 

17 - Pet care; care of household pets including activities with pets; playing with the dog; walking the dog; 

(caring for pets of relatives, friends, code 42) 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

MISCELLANEOUS HOUSEHOLD CHORES (continued) 

19 - Household paperwork; paying bills, balancing the checkbook, making lists, getting the mail, working 

on the budget 

- Other household chores; (no travel), picking up things at home, e.g., "picked up deposit slips" (relate 

travel to purpose) 

CHILD CARE 

Child Care for Children of Household 

20 - Baby care; care to children aged 4 and under 

21 - Child care; care to children aged 5*-17 

- Child care; mixed ages or NA ages of children 

22 - Helping/teaching children learn, fix, make things; helping son bake cookies; helping daughter fix bike 

- Help with homework or supervising homework 

23 - Giving children orders or instructions; asking them to help; telling the*i*n to behave 

- Disciplining child; yelling at kids, spanking children; correcting children's behavior

- Reading to child

- Conversations with household children only; listening to children

24 - Indoor playing; other indoor activities with children (including games ("playing") unless obviously 

outdoor games) 

25 - Outdoor playing; outdoor activities with children including sports, walks, biking with, other outdoor 

games 

- Coaching/leading outdoor, nonorganizational activities 

26 - Medical care at home or outside home; activities associated with children's health; "took son to 

doctor," "gave daughter medicine" 

Other Child Care 

27 - Babysitting (unpaid) or child care outside R's home or for children not residing in HH 

- Coordinating or facilitating child's social or instructional nonschool activities; (travel related, code 29) 

- Other child care, including phone conversations relating to child care other than medical 

29 - Travel related to child's social and instructional nonschool activities 

- Other travel related to child care activities; waiting for related travel 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

OBTAINING GOODS AND SERVICES 

Goods (include phone calls to obtain goods) 

30 - Groceries; supermarket, shopping for food 

- All other shopping for goods; including for clothing, small appliances; at drugstores, hardware stores, 

department stores, "downtown" or "uptown," "shopping," "shopping center," buying gas, "window 

shopping" 

31 - Durable household goods; shopping for large appliances, cars, furniture 

- House, apartment: activities connected to buying, selling, renting, looking for house, apartment, 

including phone calls; showing house, including traveling around looking at real estate property (for 

own use) 

Services (include phone conversations to obtain services) 

32 - Personal care; beauty, barber shop; hairdressers 

33 - Medical care for self; visits to doctor, dentist, optometrist, including making appointments 

34 - Financial services; activities related to taking care of financial business; going to the bank, paying 

utility bills (not by mail), going to accountant, tax office, loan agency, insurance office 

- Other government services: post office, driver's license, sporting licenses, marriage licenses, police 

station 

35 - Auto services; repair and other auto services including waiting for such services 

- Clothes repair and cleaning; cleaners, laundromat, tailor 

- Appliance repair: including furnace, water heater, electric or battery operated appliances; including 

watching repair person 

- Household repair services: including furniture; other repair services NA type; including watching repair 

person 

37 - Other professional services; lawyer, counseling (therapy) 

- Picking up food at a takeout place - no travel 

- Other services, "going to the dump" 

38 - Errands; "running errands," NA whether for goods or services; borrowing goods 

39 - Related travel; travel related to obtaining goods and services and/or household activities except 31; 

waiting for related travel 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

PERSONAL NEEDS AND CARE 

Care to Self 

40 - Washing, showering, bathing 

- Dressing; getting ready, packing and unpacking clothes, personal hygiene, going to the bathroom 

41 - Medical care at home to self 

43 - Meals at home; including coffee, drinking, smoking, food from a restaurant eaten at home, 

"breakfast," "lunch" 

44 - Meals away from home; eaten at a friend's home (including coffee, drinking, smoking) 

- Meals away from home, except at workplace (06) or at friend's home (44); eating at restaurants, out 

for coffee 

45 - Night sleep; longest sleep for day; (may occur during day for night shift workers) including "in bed," 

but not asleep 

46 - Naps and resting; rest periods, "dozing," "laying down" (relaxing code 98) 

48 - Sex, making out 

- Personal, private; "none of your business" 

- Affection between household members; giving and getting hugs, kisses, sitting on laps 

Help and Care to Others 

41 - Medical care to adults in household (HH) 

42 - Nonmedical care to adults in HH; routine nonmedical care to adults in household; "got my wife up," 

"ran a bath for my husband" 

- Help and care to relatives not living in HH; helping care for, providing for needs of relatives; (except 

travel) helping move, bringing food, assisting in emergencies, doing housework for relatives; visiting 

when sick 

- Help and care to neighbors, friends

- Help and care to others, NA relationship to respondent

Other Personal and Helping 

48 - Other personal; watching personal care activities 

49 - Travel (helping); travel related to code 42, including travel that is the helping activity; waiting for 

related travel 

- Other personal travel; travel related to other personal care activities; waiting for related travel; travel, 

NA purpose of trip - e.g., "went to Memphis" (no further explanation given) 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

EDUCATION AND PROFESSIONAL TRAINING 

50 - Student (full-time); attending classes, school if full-time student; includes daycare, nursery school for 

children not in school 

51 - Other classes, courses, lectures, academic or professional; R not a full-time student or NA whether 

a student; being tutored 

54 - Homework, studying, research, reading, related to classes or profession, except for current job (code 

07); "went to the library" 

56 - Other education 

59 - Other school-related travel; travel related to education coded above; waiting for related travel; travel 

to school not originating from home 

ORGANIZATIONAL ACTIVITIES 

Volunteer, Helping Organizations: hospital volunteer group, United Fund, Red Cross, Big Brother/Sister 

63 - Attending meetings of volunteer, helping organizations 

- Officer work; work as an officer of volunteer, helping organizations; R must indicate he/she is an 

officer to be coded here 

- Fund raising activities as a member of volunteer helping organization, collecting money, planning a 

collection drive 

- Direct help to individuals or groups as a member of volunteer helping organizations; visiting, bringing 

food, driving 

- Other activities as a member of volunteer helping organizations, including social events and meals 

Religious Practice 

65 - Attending services of a church or synagogue, including participating in the service; ushering, singing 

in choir, leading youth group, going to church, funerals 

- Individual practice; religious practice carried out as an individual or in a small group; praying, 

meditating, Bible study group (not a church), visiting graves 

Religious Groups 

64 - Meetings: religious helping groups; attending meetings of helping - oriented church groups -ladies 

aid circle, missionary society, Knights of Columbus 

- Other activities; religious helping groups; other activities as a member of groups listed above, 

including social activities and meals 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

ORGANIZATIONAL ACTIVITIES (continued) 

Religious Groups (continued) 

- Meetings: other church groups; attending meetings of church group, not primarily helping-oriented, 

or NA if helping-oriented 

- Other activities, other church groups; other activities as a member of church groups that are not 

helping-oriented or NA if helping, including social activities and meals; choir practice; Bible class 

Professional/Union Organizations: State Education Association; AFL-CIO; Teamsters 

60 - Meetings; professional/union; attending meetings of professional or union groups 

- Other activities, professional/union; other activities as a member of professional or union group 

including social activities and meals 

Child/Youth/Family Organizations: PTA, PTO; Boy/Girl Scouts; Little Leagues; YMCA/YWCA; school 

volunteer 

67 - Meetings, family organizations; attending meetings of child/youth/family*-oriented organizations 

- Other activities, family organizations; other activities as a member of child/youth/family-oriented 

organizations including social activities and meals 

Fraternal Organizations: Moose, VFW, Kiwanis, Lions, Civitan, Chamber of Commerce, Shriners, 

American Legion 

66 - Meetings, fraternal organizations; attending meetings of fraternal organizations 

- Other activities, fraternal organizations; other activities as a member of fraternal organizations 

including social activities and helping activities and meals 

Political Party and Civic Participation: Citizens' groups, Young Democrats, Young Republicans, radical 

political groups, civic duties 

62 - Meetings, political/citizen organizations; attending meetings of a political party or citizen group, 

including city council 

- Other activities, political/citizen organizations; other participation in political party and citizens' groups, 

including social activities, voting, jury duty, helping with elections, and meals 

Special Interest/Identity Organizations (including groups based on sex, race, national origin); NOW; 

NAACP; Polish-American Society; neighborhood, block organizations; CR groups; senior citizens; Weight 

Watchers 

61 - Meetings: identify organizations; attending meetings of special interest, identity organizations 

- Other activities, identity organizations; other activities as a member of a special interest, identity 

organization, including social activities and meals 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

ORGANIZATIONAL ACTIVITIES (continued) 

Other Miscellaneous Organizations, do not fit above 

68 - Other organizations; any activities as a member of an organization not fitting into above categories; 

(meetings and other activities included here) 

Travel Related to Organizational Activities 

69 - Travel related to organizational activities as a member of a volunteer (helping) organization (code 63); 

including travel that is the helping activity, waiting for related travel 

- Travel (other organization-related); travel related to all other organization activities; waiting for related 

travel 

ENTERTAINMENT/SOCIAL ACTIVITIES 

Attending Spectacles, Events 

70 - Sports; attending sports events - football, basketball, hockey, etc. 

71 - Miscellaneous spectacles, events: circus, fairs, rock concerts, accidents 

72 - Movies; "went to the show" 

73 - Theater, opera, concert, ballet 

74 - Museums, art galleries, exhibitions, zoos 

Socializing 

75 - Visiting with others; socializing with people other than R's own HH members either at R's home or 

another home (visiting on the phone, code 96); talking/chatting in the context of receiving a visit or 

paying a visit 

76 - Party; reception, weddings 

77 - At bar; cocktail lounge, nightclub; socializing or hoping to socialize at bar, lounge 

- Dancing 

78 - Other events; other events or socializing, do not fit above 

79 - Related travel; waiting for related travel 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

SPORTS AND ACTIVE LEISURE 

Active Sports 

80 - Football, basketball, baseball, volleyball, hockey. soccer, field hockey 

- Tennis, squash, racquetball, paddleball 

- Golf, miniature golf 

- Swimming, waterskiing 

- Skiing, ice skating, sledding, roller skating 

- Bowling; pool, ping-pong, pinball 

- Frisbee, catch 

- Exercises, yoga (gymnastics - code 86) 

- Judo, boxing, wrestling 

Out of Doors 

81 - Hunting 

- Fishing 

- Boating, sailing, canoeing 

- Camping, at the beach 

- Snowmobiling, dune-buggies 

- Gliding, ballooning, flying 

- Excursions, pleasure drives (no destination), rides with the family 

- Picnicking 

Walking, Biking 

82 - Walking for pleasure 

- Hiking 

- Jogging, running 

- Bicycling 

- Motorcycling 

- Horseback riding 

Hobbies 

83 - Photography 

- Working on cars - not necessarily related to their running; customizing, painting 

- Working on or repairing leisure time equipment (repairing the boat, "sorting out fishing tackle") 

- Collections, scrapbooks 

- Carpentry and woodworking (as a hobby) 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

SPORTS AND ACTIVE LEISURE (continued) 

Domestic Crafts 

84 - Preserving foodstuffs (canning, pickling) 

- Knitting, needlework, weaving, crocheting (including classes), crewel, embroidery, quilting, quilling, 

macrame 

- Sewing 

- Care of animals/livestock when R is not a farmer (pets, code 17; "farmer", code 01, work) 

Art and Literature 

85 - Sculpture, painting, potting, drawing 

- Literature, poetry, writing (not letters), writing a diary 

Music/Theater/Dance 

86 - Playing a musical instrument (include practicing), whistling 

- Singing 

- Acting (rehearsal for play) 

- Nonsocial dancing (ballet, modern dance, body movement) 

- Gymnastics (lessons - code 88) 

Games 

87 - Playing card games (bridge, poker) 

- Playing board games (Monopoly, Yahtzee, etc.), bingo, dominoes 

- Playing social games (scavenger hunts), "played games" - NA kind 

- Puzzles 

Classes/Lessons for Active Leisure Activity 

88 - Lessons in sports activities: swimming, golf, tennis. skating, roller skating 

- Lessons in gymnastics, dance, judo, body movement 

- Lessons in music, singing, instruments 

- Other lessons, not listed above 

Travel 

89 - Related travel; travel related to sports and active leisure; waiting for related travel: vacation travel 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

PASSIVE LEISURE 

90 - Radio 

91 - TV 

92 - Records, tapes, "listening to music," listening to others playing a musical instrument 

93 - Reading books (current job related, code 07; professionally or class related, code 54) 

94 - Reading magazines, reviews, pamphlets 

- Reading NA what; or other 

95 - Reading newspapers 

96 - Phone conversations - not coded elsewhere, including all visiting by phone 

- Other talking/conversations; face-to-face conversations, not coded elsewhere (if children in HH only, 

code 23); visiting other than 75 

- Conversations with HH members only - adults only or children and adults 

- Arguing or fighting with people other than HH members only, household and nonhousehold 

members, or NA 

- Arguing or fighting with HH members only 

97 - Letters (reading or writing); reading mail 

98 - Relaxing 

- Thinking, planning; reflecting 

- "doing nothing," "sat"; just sat; 

- Other passive leisure, smoking dope, pestering, teasing, joking around, messing around; laughing 

99 - Related travel: waiting for related travel 

MISSING DATA CODES 

- Activities of others reported - R's activity not specified

- NA activities; a time gap of greater than 10 minutes.

EXAMPLES OF ACTIVITIES IN "OTHER" CATEGORIES 

Other Work Related 

07 - Foster parent activities 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

EXAMPLES OF ACTIVITIES IN "OTHER" CATEGORIES (continued) 

Other Household 

19 - Typing 

- Wrapping presents 

- Checked refrigerator for shopping list 

- Unpacked gifts from shower 

- Packing/unpacking car 

- "Settled in" after trip 

- Hooked up boat to car 

- Showed wife car (R was fixing) 

- Packing to move 

- Moved boxes 

- Looking/searching for things at home (inside or out) 

Other Child Care 

27 - Waited for son to get hair cut 

- Picked up nephew at sister's house 

- "Played with kids" (R's children from previous marriage not living with R) 

- Called babysitter 

Other Services 

37 - Left clothing at Goodwill 

- Unloaded furniture (just purchased) 

- Returned books (at library) 

- Brought clothes in from car (after laundromat) 

- Delivered some stuff to a friend 

- Waited for father to pick up meat 

- Waited for stores to open 

- Put away things from swap meet 

- Sat in car waiting for rain to stop before shopping 

- Waiting for others while they are shopping 

- Showing mom what I bought 

Other Personal 

48 - Waiting to hear from daughter 

- Stopped at home, NA what for 

- Getting hysterical 

- Breaking up a fight (not child care related) 

- Waited for wife to get up 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

EXAMPLES OF ACTIVITIES IN "OTHER" CATEGORIES (continued) 

Other Personal (continued) 

- Waiting for dinner at brother's house

- Waiting for plane (meeting someone at airport)

- Laughing

- Crying

- Moaning - head hurt

- Watching personal care activities ("watched dad shave")

Other Education 

56 - Watched a film 

- In discussion group 

Other Organization 

68 - Attending "Club House coffee klatch" 

- Waited for church activities to begin 

- "Meeting" NA kind 

- Cleanup after banquet 

- Checked into swap meet - selling and looking 

Other Social, Entertainment 

78 - Waiting for movies, other events 

- Opening presents (at a party) 

- Looking at gifts 

- Decorating for party 

- Tour of a home (friends or otherwise) 

- Waiting for date 

- Preparing for a shower (baby shower) 

- Unloaded uniforms (for parade) 

Other Active Leisure 

88 - Fed birds, bird watching 

- Astrology 

- Swinging 

- At park 

- Showing slides 

- Showing sketches 

(continued on the following page) 
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) 

EXAMPLES OF ACTIVITIES IN "OTHER" CATEGORIES (continued) 

Other Active Leisure (continued) 

- Recording music

- Hung around airport (NA reason)

- Picked up fishing gear

- Inspecting motorcycle

- Arranging flowers

- Work on model airplane

- Picked asparagus

- Picked up softball equipment

- Registered to play golf

- Toured a village or lodge (coded 81)

Other Passive Leisure

98 - Lying in sun 

- Listening to birds 

- Looking at slides 

- Stopped at excavating place 

- Looking at pictures 

- Walked around outside 

- Waiting for a call 

- Watched plane leave 

- Girl watching/boy watching 

- Watching boats 

- Wasted time 

- In and out of house 

- Home movies 

* R = Respondent

HH = Household. 

Source: Juster et al., 1983. 
Table 15A-2. Differences in Average Time Spent in Different Activities Between California 

and National Studies (minutes per day for age 18-64 years) 

California National California National 

00-49 NON-FREE TIME 1987-88 1985 50-59 Free Time 1987-88 1985 

(1359) (1980) (1359) (1980) 

00-09 PAID WORK 50-99 EDUCATION AND TRAINING 

00 (not used) 50 Students' Classes 9 5 

01 Main Job 224 211 51 Other Classes 1 3 

02 Unemployment 1 1 52 (not used) - -

03 Travel during work 8 NR 53 (not used) - -

04 (not used) - - 54 Homework 8 7 

05 Second job 3 3 55 Library * 1 

06 Eating 6 8 56 Other Education 1 1 

07 Before/after work 1 2 57 (not used) - -

08 Breaks 2 2 58 (not used) - -

09 Travel to/from work 28 25 59 Travel, Education 3 2 

10-19 HOUSEHOLD WORK 60-69 ORGANIZATIONAL ACTIVITIES 

10 Food Preparation 29 36 60 Professional/Union 0 1 

11 Meal Cleanup 10 11 61 Special Interest * 1 

12 Cleaning House 21 24 62 Political/Civic 0 * 

13 Outdoor Cleaning 9 7 63 Volunteer/Helping 1 1 

14 Clothes Care 7 11 64 Religious Groups 1 2 

15 Car Repair/Maintenance (by 5 5 65 Religious Practice 5 7 

R) 

16 Other Repairs (by R) 8 6 66 Fraternal 0 * 

17 Plant Care 3 5 67 Child/Youth/Family 1 * 

18 Animal Care 3 5 68 Other Organizations 2 1 

19 Other Household 7 8 69 Travel Organizations 2 4 

20-29 CHILD CARE 70-79 ENTERTAINMENT/ SOCIAL ACTIVITIES 

20 Baby Care 3 8 70 Sports Events 2 2 

21 Child Care 7 5 71 Entertainment Events 5 1 

22 Helping/Teaching 2 1 72 Movies 2 3 

23 Talking/Reading 1 1 73 Theatre 1 1 

24 Indoor Playing 2 3 74 Museums 1 * 

25 Outdoor Playing 2 1 75 Visiting 26 25 

26 Medical care - Care * 1 76 Parties 6 7 

27 Other Child Care 2 1 77 Bars/Lounges 4 6 

28 (At Dry Cleaners) * NR 78 Other Social * 1 

29 Travel, Child care 4 4 79 Travel, Events/Social 13 16 
Table 15A-2. Differences in Average Time Spent in Different Activities Between California 

and National Studies (minutes per day for age 18-64 years) (continued) 

California National California National 

00-49 NON-FREE TIME 1987-88 1985 50-59 Free Time 1987-88 1985 

(1359) (1980) (1359) (1980) 

30-39 OBTAINING GOODS AND 80-89 RECREATION 

SERVICES 

30 Everyday Shopping 8 5 80 Active Sports 15 13 

31 Durable/House Shop 19 20 81 Outdoor 3 7 

32 Personal Services 1 1 82 Walking/Hiking 5 4 

33 Medical Appointments 2 2 83 Hobbies 1 1 

34 Gov't/Financial Service 3 2 84 Domestic Crafts 3 6 

35 Car Repair services 2 1 85 Art * 1 

36 Other Repair services * 1 86 Music/Drama/Dance 3 2 

37 Other Services 2 2 87 Games 5 7 

38 Errands * 1 88 Computer Use/Other 3 3 

39 Travel, Goods and Services 24 20 89 Travel, Recreation 5 6 

40-49 PERSONAL NEEDS AND 90-99 COMMUNICATION 

CARE 

40 Washing, Etc. 21 25 90 Radio 1 3 

41 Medical Care 3 1 91 TV 130 126 

42 Help and Care 3 4 92 Records/Tapes 3 1 

43 Meals At Home 44 50 93 Read Books 4 7 

44 Meals Out 27 20 94 Reading Magazines/Other 16 10 

45 Night Sleep 480 469 95 Reading Newspaper 11 9 

46 Naps/Day Sleep 16 16 96 Conversations 15 25 

47 Dressing, Etc. 24 32 97 Writing 8 9 

48 NA Activity 2 12 98 Think, Relax 9 6 

49 Travel, Personal Care/NA 22 13 99 Travel, Communication 5 * 

NR = Not Recorded in National Total Travel 108 90 

Survey 

* = Less than 0.5 Min. per day (Codes 09, 29, 39, 49, 59, 

69, 79, 89, 99) 

Source: Robinson and Thomas, 1991. 
-- -- --

-- -- --

-- --

-- -- --

Table 15A-3. Time Spent in Various Microenvironments 

Mean duration 

Men Women Totala 

Code Description N = 639 N = 914 N = 720 N = 1059 N = 1980 N = 1359 

California National California National California National 

AT HOME 

Kitchen 46 56 98 135 72 104 

Living Room 181 136 98 180 189 158 

Dining Room 18 10 22 18 19 15 

Bathroom 27 27 38 43 33 38 

Bedroom 481 478 534 531 508 521 

Study 8 10 6 7 7 8 

Garage 14 5 6 1 19 2 

Basement <0.5 4 <0.5 6 <0.5 5 

Utility Room 1 0 3 5 2 4 

Pool, Spa 1 NR 1 NRb 1 NRb 

Yard 33 21 27 37 

Room to Room 9 160c 34 116 21 40 

Other NR Room 3 4 3 22 

Total at home 822 888 963 1022 892 954 

AWAY FROM HOME 

Office 78 261 94 155 86 193 

Plant 73 12 42 

Grocery Store 12 18 14 33 13 30 

Shopping Mall 30 40 35 

School 25 13 29 11 27 15 

Other Public Places 18 10 14 12 

Hospital 9 NR 24 NR 17 3 

Restaurant 35 22 25 18 30 23 

Bar-Night Club 15 5 10 

Church 7 8 5 11 6 10 

Indoor Gym 4 NR 4 NR 4 NR 

Other's Home 60 42 61 45 61 43 

Auto Repair 18 NR 4 NR 11 NR 

Playground 16 27 8 16 12 NR 

Hotel-Motel 7 NR 8 NR 8 NR 

Dry Cleaners <0.5 NR 1 NR 1 NR 

Beauty Parlor <0.5 NR 4 NR 2 NR 

Other Locations 3 NR 1 NR 2 NR 

Other Indoor 17 41 7 24 12 24 

Other Outdoor 60 NR 13 NR 37 6 

Total away 

from home 487 445 371 324 430 383 
-- -- --

-- --

-- -- --

-- --

-- -- --

-- --

-- --

-- --

-- --

-- -- -- --

c 

Table 15A-3. Time Spent in Various Microenvironments (continued) 

Code Description N = 639 

California 

Mean duration 

Men Women Totala 

N = 914 N = 720 N = 1059 N = 1980 N = 1359 

National California National California National 

TRAVEL 

Car 76 77 76 

Van/Truck 30 86 11 77 20 88 

Walking 10 8 9 2 

Bus Stop <0.5 1 1 

Bus 6 2 4 3 

Rapid Train 1 1 1 

Other Travel 2 1 1 <0.5 

Airplane 1 15 <0.5 10 1 1 

Bicycle 1 <0.5 1 NR 

Motorcycle 2 <0.5 1 NR 

Other or Missing 1 <0.5 1 NR

 . 

Total travel 130 101 102 87 116 94 

Not ascertained 1 8 4 7 2 9 

Total Time Outdoors 88 70 

a Totals do not necessarily reflect exact averages presented for each gender. Totals were revised, but revisions for each gender were 

not provided. b NR = Not Reported

Is total mean duration for those categories; breakdowns per category were not reported.

Source: Robinson and Thomas, 1991.

 National California 

Note: Percent at home men = 62 men = 57 

women = 71 women = 67 

total = 67 total = 62 

Percent away from home men = 31 men = 34 

women = 23 women = 26 

total = 27 total = 30 

Percent in travel men = 7 men = 9 

women = 6 women = 7 

total = 7 total = 8 
Table 15A-4. Major Time Use Activity Categoriesa 

Activity code Activity 

01-09 Market work 

10-19 House/yard work 

20-29 Child care 

30-39 Services/shopping 

40-49 Personal care 

50-59 Education 

60-69 Organizations 

70-79 Social entertainment 

80-89 Active leisure 

90-99 Passive leisure

 Appendix Table 15A-5 presents a detailed explanation of the coding and activities. a 

Source: Hill, 1985. 
Table 15A-5. Mean Time Spent (minutes/day) for 87 Activities Grouped by Day of the Week 

Weekday Saturday Sunday 

N=831 N=831 N=831 

Activity Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. 

01-Normal Work 240.54 219.10 82.43 184.41 46.74 139.71 

02-Unemployment Acts 0.98 9.43 0.00 0.00 0.00 0.00 

05-Second Job 3.76 25.04 2.84 32.64 2.65 27.30 

06-Lunch At Work 10.00 15.81 1.82 7.88 1.43 8.29 

07-Before/After Work 3.51 10.05 1.45 9.79 1.66 13.76 

08-Coffee Breaks 5.05 11.53 1.59 7.32 0.93 8.52 

09-Travel: To/From Work 24.03 30.37 7.74 22.00 4.60 17.55 

10-Meal Preparation 42.18 46.59 40.37 59.82 42.38 57.42 

11-Meal Cleanup 12.48 19.25 12.07 22.96 13.97 25.85 

12-Indoor Cleaning 26.37 43.84 38.88 80.39 21.73 48.70 

13-Outdoor Cleaning 7.48 25.45 15.71 58.00 9.01 39.39 

14-Laundry 13.35 30.39 11.48 31.04 7.79 25.43 

16-Repairs/Maintenance 9.61 35.43 17.36 72.50 13.56 62.12 

17-Garden/Pet Care 8.52 25.15 14.75 49.17 8.47 37.54 

19-Other Household 6.26 20.62 9.82 37.58 7.60 32.17 

20-Baby Care 6.29 22.91 5.89 30.72 6.26 33.78 

21-Child Care 6.26 16.34 5.38 21.58 7.09 23.15 

22-Helping/Teaching 1.36 8.28 0.23 3.64 0.76 6.52 

23-Reading/Talking 2.47 8.65 1.71 10.84 1.53 9.97 

24-Indoor Playing 1.75 8.72 0.90 7.82 2.45 15.11 

25-Outdoor Playing 0.73 6.33 1.23 13.03 0.91 10.30 

26-Medical Care-Child 0.64 7.42 0.16 2.79 0.44 7.20 

27-Babysitting/Other 2.93 14.56 2.16 19.11 3.28 24.89 

29-Travel: Child Care 4.18 10.97 1.71 8.72 2.08 10.56 

30-Everyday Shopping 19.73 30.28 33.52 61.38 10.13 30.18 

31-Durable/House Shop 0.58 4.83 1.46 14.04 1.65 17.92 

32-Personal Care Services 1.93 10.04 3.42 18.94 0.02 0.69 

33-Medical Appointments 3.43 14.49 0.60 6.63 0.00 0.00 

34-Gov't/Financial Services 1.90 6.07 0.66 4.34 0.03 0.43 

35-Repair Services 1.33 7.14 1.25 10.24 0.52 5.61 

37-Other Services 1.13 7.17 1.55 9.57 0.72 4.34 

38-Errands 0.74 8.03 0.35 5.27 0.04 1.04 

39-Travel: Goods/Services 17.93 23.58 21.61 36.35 8.45 21.64 

40-Washing/Dressing 44.03 29.82 44.25 41.20 47.54 40.15 

41-Medical Care R/HH Adults 0.77 6.19 1.29 15.90 1.45 29.18 

42-Help & Care 8.43 28.17 12.19 52.58 14.32 55.13 

43-Meals At Home 53.45 35.57 57.86 49.25 61.84 49.27 

44-Meals Out 19.55 31.20 31.13 56.03 25.95 47.60 

45-Night Sleep 468.49 79.42 498.40 115.55 528.86 115.84 

46-Naps/Resting 22.07 43.92 30.67 74.98 27.56 66.01 

48-N.A. Activities 7.52 22.32 11.72 41.61 8.18 35.79 

49-Travel: Personal 14.87 27.76 19.33 50.42 18.58 46.36 

50-Students' Classes 6.33 33.79 0.96 18.17 0.96 20.07 

51-Other Classes 2.65 17.92 0.40 11.52 0.27 5.63 
Table 15A-5. Mean Time Spent (minutes/day) for 87 Activities Grouped by Day of the Week (continued) 

Weekday Saturday Sunday 

N=831 N=831 N=831 

Activity Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. 

54-Homework 4.56 24.35 3.48 27.98 5.40 38.68 

56-Other Education 0.53 5.91 0.15 2.75 0.45 9.85 

59-Travel: Education 2.29 10.36 0.35 4.26 0.21 3.14 

60-Professional/Union Orgs. 0.51 7.27 0.13 3.64 0.44 8.34 

61-Identity Organizations 1.53 11.19 1.24 35.63 0.48 7.58 

62-Political/Citizen Orgs 0.14 1.25 0.07 1.91 0.19 5.55 

63-Volunteer/Helping Orgs 1.08 10.08 0.02 0.45 0.41 7.09 

64-Religious Groups 2.96 17.33 3.05 27.73 8.59 33.31 

65-Religious Practice 4.98 19.92 7.13 30.12 34.05 62.06 

66-Fraternal Organizations 0.85 9.28 1.73 27.71 0.31 6.67 

67-Child/Family Organizations 1.70 11.69 1.04 17.83 0.26 7.63 

68-Other Organizations 3.91 22.85 1.31 20.28 1.71 17.52 

69-Traves: Organizations 3.41 9.83 2.66 12.22 12.07 37.64 

70-Sport Events 2.22 13.45 6.29 42.05 3.44 27.78 

71-Miscellaneous Events 0.32 4.89 1.94 19.90 1.96 19.75 

72-Movies 1.65 11.03 4.74 27.04 3.35 22.65 

73-Theater 0.69 7.13 2.66 27.79 0.77 10.37 

74-Museums 0.19 3.32 0.90 13.62 0.72 11.17 

75-Visiting w/Others 33.14 51.69 56.78 95.61 69.65 114.58 

76-Parties 2.81 16.49 12.63 56.11 7.16 39.02 

77-Bars/Lounges 3.62 18.07 7.23 35.09 3.91 26.95 

78-Other Events 1.39 11.55 1.33 15.52 1.00 10.80 

79-Travel: Events/Social 8.90 16.19 19.55 43.38 18.02 34.45 

80-Active Sports 5.30 19.60 9.23 43.69 11.39 48.66 

81-Outdoors 5.11 33.00 11.58 55.07 15.52 62.68 

82-Walking/Biking 2.08 9.70 5.87 36.38 5.92 32.28 

83-Hobbies 1.78 11.73 3.20 32.43 4.10 31.55 

84-Domestic Crafts 11.18 37.03 8.67 40.49 6.41 34.82 

85-Art/Literature 0.99 10.84 0.86 13.59 1.13 15.07 

86-Music/Drama/Dance 0.45 4.91 0.83 8.83 0.63 8.32 

87-Games 5.06 22.91 10.14 45.11 7.89 40.45 

88-Classes/Other 2.65 15.83 2.56 29.92 3.37 23.60 

89-Travel: Active Leisure 3.31 14.77 8.50 48.72 8.19 38.11 

90-Radio 2.89 12.19 3.53 23.42 2.88 18.50 

91-TV 113.01 103.89 118.99 131.24 149.67 141.43 

92-Records/Tapes 2.58 20.26 2.40 16.09 2.03 16.08 

93-Reading Books 4.41 18.09 2.76 17.85 5.23 30.13 

94-Reading Magazines/N.A. 13.72 31.73 16.33 46.24 17.18 51.01 

95-Reading Newspapers 12.03 22.65 12.19 34.96 26.01 44.47 

96-Conversations 18.68 28.59 15.45 35.27 14.57 34.60 

97-Letters 2.83 12.23 1.61 10.80 1.96 12.59 

98-Other Passive Leisure 9.72 25.02 17.24 57.21 15.28 47.86 

99-Travel: Passive Leisure 1.26 5.44 1.32 6.80 1.72 9.87 

Source: Hill, 1985. 
Table 15A-6. Weighted Mean Hours Per Week by Gender: 87 Activities and 10 Subtotals 

Men Women Men and women

 N=410 N=561 N=971 

Activity Mean Std. dev. Mean Std. dev. Mean Std. dev. 

01 - Normal work 29.78 20.41 14.99 17.62 21.82 20.33 

02 - Unemployment acts 0.14 1.06 0.08 0.75 0.11 0.90 

05 - Second job 0.73 3.20 0.17 1.62 0.43 2.49 

06 - Lunch at work 1.08 1.43 0.65 1.21 0.85 1.33 

07 - Before/after work 0.51 1.27 0.23 0.69 0.36 1.01 

08 - Coffee breaks 0.57 1.05 0.36 1.03 0.46 1.04 

09 - Travel: to/from work 2.98 2.87 1.45 2.17 2.16 2.63 

10 - Meal preparation 1.57 2.61 7.25 5.04 4.63 4.98 

11 - Meal cleanup 0.33 0.83 2.30 2.19 1.39 1.97 

12 - Indoor cleaning 0.85 2.01 5.03 5.05 3.10 4.46 

13 - Outdoor cleaning 1.59 3.59 0.56 1.59 1.03 2.75 

14 - Laundry 0.13 0.72 2.44 3.34 1.38 2.75 

16 - Repairs/maintenance 2.14 4.29 0.68 3.43 1.35 3.92 

17 - Gardening/pet care 0.94 2.78 1.00 2.19 0.97 2.48 

19 - Other household 0.92 2.42 0.72 1.84 0.81 2.13 

20 - Baby care 0.24 1.20 0.90 3.04 0.60 2.40 

21 - Child care 0.24 0.78 0.99 2.11 0.64 1.68 

22 - Helping/teaching 0.07 0.61 0.15 0.76 0.11 0.70 

23 - Reading/talking 0.07 0.35 0.30 0.86 0.19 0.68 

24 - Indoor playing 0.13 0.69 0.18 0.82 0.16 0.76 

25 - Outdoor playing 0.06 0.37 0.12 0.72 0.09 0.58 

26 - Medical care - child 0.01 0.09 0.09 0.67 0.05 0.50 

27 - Babysitting/other 0.14 0.78 0.64 2.58 0.41 1.98 

29 - Travel: child care 0.23 0.67 0.50 1.21 0.38 1.00 

30 - Everyday shopping 1.45 2.18 2.78 3.25 2.17 2.89 

31 - Durables/house shopping 0.19 1.39 0.08 0.51 0.13 1.01 

32 - Personal care services 0.06 0.42 0.35 1.14 0.22 0.90 

33 - Medical appointments 0.15 0.75 0.37 1.63 0.27 1.31 

34 - Govt/financial services 0.15 0.44 0.19 0.61 0.17 0.54 

35 - Repair services 0.11 0.45 0.17 0.78 0.14 0.65 

37 - Other services 0.11 0.61 0.13 0.61 0.12 0.61 

38 - Errands 0.04 0.41 0.06 0.68 0.05 0.57 

39 - Travel: goods/services 1.60 2.02 2.14 2.17 1.89 2.12 

(Continued on the following page) 
Table 15A-6. Weighted Mean Hours Per Week by Gender: 87 Activities and 10 Subtotals (continued)

 Men Women Men and women

 N=410 N=561 N=971 

Activity Mean Std. dev. Mean Std. dev. Mean Std. dev. 

40 - Washing/dressing 4.33 2.39 5.43 3.24 4.92 2.93 

41 - Medical care - adults 0.09 0.67 0.18 1.00 0.14 0.86 

42 - Help and care 1.02 2.84 1.30 3.04 1.17 2.95 

43 - Meals at home 6.59 3.87 6.32 3.53 6.44 3.69 

44 - Meals out 2.72 3.48 2.24 2.73 2.46 3.10 

45 - Night sleep 55.76 8.43 56.74 8.49 56.29 8.47 

46 - Naps/resting 2.94 5.18 3.19 4.70 3.08 4.93 

48 - N.A. activities 1.77 6.12 1.99 5.70 1.89 5.89 

49 - Travel: personal 2.06 2.59 1.61 2.51 1.82 2.56 

50 - Students' classes 0.92 4.00 0.38 2.51 0.63 3.29 

51 - Other classes 0.23 1.68 0.15 1.05 0.18 1.38 

54 - Homework 0.76 3.48 0.38 1.87 0.56 2.74 

56 - Other education 0.11 0.86 0.02 0.22 0.06 0.61 

59 - Travel: education 0.29 1.07 0.16 1.06 0.22 1.07 

60 - Professional/union organizations 0.04 0.46 0.04 0.62 0.04 0.55 

61 - Identity organizations 0.14 0.97 0.18 1.55 0.16 1.31 

62 - Political/citizen organizations 0.01 0.08 0.02 0.15 0.01 0.12 

63 - Volunteer/helping organizations 0.02 0.32 0.14 1.05 0.09 0.80 

64 - Religious groups 0.38 1.82 0.41 1.61 0.40 1.71 

65 - Religious practice 0.89 2.05 1.31 2.97 1.12 1.60 

66 - Fraternal organizations 0.16 1.17 0.05 0.66 0.10 0.93 

67 - Child/family organizations 0.10 0.88 0.21 1.33 0.16 1.15 

68 - Other organizations 0.34 2.40 0.32 1.53 0.32 1.98 

69 - Travel: organizations 0.43 1.04 0.52 1.02 0.48 1.03 

70 - Sports events 0.30 1.31 0.26 1.28 0.28 1.29 

71 - Miscellaneous events 0.07 0.52 0.08 0.59 0.07 0.56 

72 - Movies 0.31 1.25 0.26 1.13 0.28 1.19 

73 - Theatre 0.13 0.93 0.06 0.48 0.09 0.72 

74 - Museums 0.04 0.37 0.03 0.35 0.03 0.36 

75 - Visiting with others 4.24 5.72 5.84 6.42 5.10 6.16 

76 - Parties 0.64 2.05 0.44 1.65 0.53 1.84 

77 - Bars/lounges 0.71 2.21 0.46 2.09 0.57 2.15 

78 - Other events 0.12 0.72 0.18 1.18 0.15 0.99 

79 - Travel: events/social 1.40 1.82 1.26 1.67 1.32 1.74 

(Continued on the following page) 
Table 15A-6. Weighted Mean Hours Per Week by Gender: 87 Activities and 10 Subtotals (continued)

 Men Women Men and women

 N=410 N=561 N=971 

Activity Mean Std. dev. Mean Std. dev. Mean Std. dev. 

80 - Active sports 

81 - Outdoors 

82 - Walking/biking 

83 - Hobbies 

84 - Domestic crafts 

85 - Art/literature 

86 - Music/drama/dance 

87 - Games 

88 - Classes/other 

89 - Travel: active leisure 

90 - Radio 

91 - TV 

92 - Records/tapes 

93 - Reading books 

94 - Reading magazines/N.A. 

95 - Reading newspapers 

96 - Conversations 

97 - Letters 

98 - Other passive leisure 

99 - Travel: passive leisure 

Source: Hill, 1985. 

1.05 2.62 0.50 1.68 0.76 2.18 

1.49 4.59 0.48 1.67 0.94 3.39 

0.52 1.31 0.23 0.98 0.36 1.16 

0.69 3.88 0.06 0.43 0.35 2.67 

0.30 1.59 2.00 4.72 1.21 3.93 

0.05 0.45 0.13 1.03 0.09 0.81 

0.06 0.49 0.07 0.47 0.07 0.48 

0.60 2.00 0.99 3.16 0.81 2.69 

0.41 1.75 0.28 1.50 0.34 1.62 

0.76 1.91 0.43 1.43 0.58 1.68 

0.39 1.40 0.39 1.55 0.39 1.49 

14.75 12.14 13.95 10.67 14.32 11.38 

0.46 2.35 0.33 2.13 0.39 2.23 

0.37 1.52 0.56 1.83 0.47 1.70 

1.32 2.81 1.97 3.67 1.67 3.32 

1.86 2.72 1.47 2.27 1.65 2.49 

1.61 2.19 2.18 2.74 1.91 2.52 

0.20 1.06 0.31 1.12 0.26 1.10 

1.68 3.53 1.41 3.32 1.53 3.42 

0.18 0.49 0.13 0.49 0.15 0.49 
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure

 Median years of 

Occupation occupational tenure 

Barbers 24.8 

Farmers, except horticultural 21.1 

Railroad conductors and yardmasters 18.4 

Clergy 15.8 

Dentists 15.7 

Telephone line installers and repairers 15.0 

Millwrights 14.8 

Locomotive operating occupations 14.8 

Managers; farmers, except horticultural 14.4 

Telephone installers and repairers 14.3 

Airplane pilots and navigators 14.0 

Supervisors: police and detectives 13.8 

Grader, dozer, and scraper operators 13.3 

Tailors 13.3 

Civil engineers 13.0 

Crane and tower operators 12.9 

Supervisors, n.e.c. 12.9 

Teachers, secondary school 12.5 

Teachers, elementary school 12.4 

Dental laboratory and medical applicance technicians 12.3 

Separating, filtering, and clarifying machine oeprators 12.1 

Tool and die makers 12.0 

Lathe and turning machine operators 11.9 

Machinists 11.9 

Pharmacists 11.8 

Stationary engineers 11.7 

Mechanical engineers 11.4 

Chemists, except biochemists 11.1 

Inspectors, testers, and graders 11.0 

Electricians 11.0 

Operating engineers 11.0 

Radiologic technicians 10.9 

Electrical power installers and repairers 10.8 

Supervisors; mechanics and repairers 10.7 

Heavy equipment mechanics 10.7 

Bus, truck, and stationary engine mechanics 10.7 

Physicians 10.7 

Construction inspectors 10.7 

Cabinet makers and bench carpenters 10.6 

Industrial machinery repairers 10.6 

Automobile body and related repairers 10.4 

(Continued on the following page) 
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued)

 Median years of 

Occupation occupational tenure 

Electrical and electronic engineers 10.4 

Plumbers, pipefitters, and steamfitters 10.4 

Licensed practical nurses 10.3 

Brickmasons and stonemasons 10.2 

Truck drivers, heavy 10.1 

Tile setters, hard and soft 10.1 

Lawyers 10.1 

Supervisors: production occupations 10.1 

Administrators, education and related fields 10.1 

Engineers, n.e.c. 10.0 

Excavating and loading machine operators 10.0 

Firefighting occupations 10.0 

Aircraft engine mechanics 10.0 

Police and detectives, public service 9.7 

Counselors, educational and vocational 9.7 

Architects 9.6 

Stuctural metal workers 9.6 

Aerospace engineers 9.6 

Miscellaneous aterial moving equipment operators 9.4 

Dental hygienists 9.4 

Automobile mechanics 9.3 

Registered nurses 9.3 

Speech therapists 9.3 

Binding and twisting machine operators 9.3 

Managers and administrators, n.e.c. 9.1 

Personnel and labor relations managers 9.0 

Office machine repairer 9.0 

Electronic repairers, commercial and industrial equipment 9.0 

Welders and cutters 9.0 

Punching and stamping press machine operators 9.0 

Sheet metal workers 8.9 

Administrators and officials, public administraion 8.9 

Hairdressers and cosmetologists 8.9 

Industrial engineers 8.9 

Librarians 8.8 

Inspectors and compliance officers, except construction 8.8 

Upholsterers 8.6 

Payroll and timekeeping clerks 8.6 

Furnace, kiln, and oven operators, except food 8.6 

Surveying and mapping technicians 8.6 

Chemical engineers 8.6 

(continued on the following page) 
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued)

Median years of

 Occupation occupational tenure

Sheriffs, bailiffs, and other law enforcement officers 8.6

Concrete and terrazzo finishers 8.6

Sales representatives, mining, manufacturing, and wholesale 8.6

Supervisors: general office 8.6

Specified mechanics and repairers, n.e.c. 8.5

Stenographers 8.5

Typesetters and compositors 8.5

Financial managers 8.4

Psychologists 8.4

Teachers: special education 8.4

Statistical clerks 8.3

Designers 8.3

Water and Sewage Treatment plant operators 8.3

Printing machine operators 8.2

Heating, air conditioning, and refrigeration mechanics 8.1

Supervisors; distribution, scheduling, and adjusting clerks 8.1

Insurance sales occupations 8.1

Carpenters 8.0

Public transportation attendants 8.0

Drafting occupations 8.0

Butchers and meatcutters 8.0

Miscellaneous electrical and electronic equipment repairers 7.9

Dressmakers 7.9

Musicians and composers 7.9

Supervisors and proprietors; sales occupations 7.9

Painters, Sculptors, craft-artists, and artist printmakers 7.9

Mechanics and repairers, not specified 7.7

Engineering technicians, n.e.c. 7.7

Clinical laboratory technologists and technicians 7.7

Purchasing managers 7.7

Purchasing agents and buyers, n.e.c. 7.7

Photographers 7.6

Chemical technicians 7.6

Managers; properties and real estate 7.6

Accountants and auditors 7.6

Religious workers, n.e.c. 7.6

Secretaries 7.5

Social workers 7.5

Operations and systems researchers and analysts 7.4

Postal clerks, except mail carriers 7.4

Managers; marketing, advertising, and public relations 7.3

(continued on the following page)
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued) 

Median years of 

Occupation occupational tenure 

Farm workers 7.3 

Managers; medicine and health 7.2 

Data processing equipment repairers 7.2 

Bookkeepers, accounting and auditing clerks 7.1 

Grinding, abrading, buffing, and polishing machine operators 7.0 

Management related occupations, n.e.c. 7.0 

Supervisiors; cleaning and building service workers 7.0 

Management analysts 7.0 

Science technicians, n.e.c. 7.0 

Mail carriers, postal service 7.0 

Knitting, looping, taping, and weaving machine operators 6.9 

Electrical and electronic technicians 6.9 

Painting and paint spraying machine operators 6.9 

Postsecondary teachers, subject not specified 6.8 

Crossing guards 6.8 

Inhalation therapists 6.7 

Carpet installers 6.7 

Computer systems analysts and scientists 6.6 

Other financial officers 6.6 

Industrial truck and tractor equipment operators 6.6 

Textile sewing machine operators 6.6 

Correctional institution officers 6.5 

Teachers, prekindergarten and kindergarten 6.4 

Supervisors; financial records processing 6.4 

Miscellaneous Textile machine operators 6.4 

Production inspectors, checkers, and examiners 6.3 

Actors and directors 6.3 

Health technologists and technicians, n.e.c. 6.3 

Miscellaneous machine operators, n.e.c. 6.2 

Private household cleaners, and servants 6.2 

Buyers, wholesale and retail trade, excluding farm products 6.0 

Real estate sales occupations 6.0 

Electrical and electronic equipment assemblers 6.0 

Bus drivers 6.0 

Editors and reporters 6.0 

Laundering and dry cleaning machine operators 6.0 

Meter readers 5.9 

Painters, construction and maintenance 5.9 

Driver-sales workers 5.9 

Teachers, n.e.c. 5.9 

Order clerks 5.8 

Physicians' assistants 5.8 

(continued on the following page) 
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued) 

Median years of 

Occupation occupational tenure 

Billing clerks 5.8 

Drywall installers 5.7 

Construction trades, n.e.c. 5.7 

Telephone operators 5.7 

Authors 5.6 

Nursing aides, orderlies, and attendants 5.6 

Dental assistants 5.6 

Timber cutting and logging occupations 5.5 

Molding and casting machine operators 5.5 

Miscellaneous hand-working occupations 5.5 

Production coordinators 5.5 

Public relations specialists 5.5 

Personnel clerks, except payroll and bookkeeping 5.4 

Assemblers 5.4 

Securities and financial services sales occupations 5.4 

Salesworkers, furniture and home furnishings 5.4 

Insurance adjusters, examiners, and investigators 5.3 

Pressing machine operators 5.3 

Roofers 5.3 

Graders and sorters, except agricultural 5.3 

Supervisors; related agricultural occupations 5.2 

Typists 5.2 

Supervisors; motor vehicle operators 5.2 

Personnel, training, and labor relations specialists 5.2 

Legal assistants 5.2 

Physical therapists 5.2 

Advertising and related sales occupations 5.1 

Records clerks 5.1 

Economists 5.1 

Technicians, n.e.c. 5.0 

Expediters 5.0 

Sales occupations, other business services 4.9 

Computer operators 4.8 

Computer programmers 4.8 

Investigators and adjusters, except insurance 4.8 

Underwriters 4.8 

Salesworkers, parts 4.8 

Artists, performers, and related workers, n.e.c. 4.8 

Teachers' aides 4.6 

Maids and housemen 4.6 

Sawing machine operators 4.6 

Machine operators, not specified 4.5 

Weighers, measurers, and checkers 4.5 

(continued on the following page) 
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued) 

Median years of

 Occupation occupational tenure 

Traffic, shipping, and receiving clerks 4.5 

Salesworkers, hardware and building supplies 4.5 

Biological technicians 4.4 

Athletes 4.4 

Bill and account collectors 4.4 

Taxicab drivers and chauffeurs 4.4 

Slicing and cutting machine operators 4.3 

Administrative support occupations, n.e.c. 4.3 

Mixing and blending machine operators 4.3 

Waiters and waitresses 4.2 

Janitors and cleaners 4.2 

Production helpers 4.1 

General office clerks 4.0 

Machine feeders and offbearers 3.9 

Interviewers 3.9 

Bartenders 3.9 

Eligibility clerks, social welfare 3.9 

Bank tellers 3.8 

Cooks, except short-order 3.8 

Health aides, except nursing 3.7 

Laborers, except construction 3.7 

Welfare service aides 3.7 

Salesworkers, motor vehicles and boats 3.7 

Cost and rate clerks 3.6 

Construction laborers 3.6 

Hand packers and packagers 3.5 

Transportation ticket and reservation agents 3.5 

Animal caretakers, except farm 3.5 

Photographic process machine operators 3.5 

Freight, stock, and material movers, hand, n.e.c. 3.4 

Data-entry keyers 3.4 

Bakers 3.4 

Dispatchers 3.3 

Guards and police, except public service 3.3 

Packaging and filling machine operators 3.3 

Receptionists 3.3 

Library clerks 3.3 

Truckdrivers, light 3.2 

Salesworkers, radio, television, hi-fi, and appliances 3.2 

Salesworkers, apparel 3.1 

Sales counter clerks 3.1 

Salesworkers, other commodities 3.1 

(continued on the following page) 
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued) 

Median years of 

Occupation occupational tenure 

Small engine repairers 3.1 

Supervisors, food preparation and service occupations 3.0 

Health record technologists and technicians 2.9 

Helpers, construction trades 2.9 

Attendants, amusement and recreation facilities 2.8 

Street and door-to-door salesworkers 2.7 

Child-care workers, private household 2.7 

Child-care workers, except private household 2.7 

Information clerks, n.e.c. 2.7 

Hotel clerks 2.7 

Personal service occupations, n.e.c. 2.7 

Salesworkers, shoes 2.6 

Garage and service station related occupations 2.6 

Short-order cooks 2.5 

File clerks 2.5 

Cashiers 2.4 

Mail clerks, except postal service 2.3 

Miscellaneous food preparation occupations 2.3 

News vendors 2.3 

Vehicle washers and equipment cleaners 2.3 

Messengers 2.3 

Kitchen workers, food preparation 2.1 

Stock handlers and baggers 1.9 

Waiters and waitresses assistants 1.7 

Food counter, fountain, and related occupations 1.5

a n.e.c. - not elsewhere classified

Source: Carey, 1988. 
Table 15B-1. Annual Geographical Mobility Rates, by Type of Movement for 

Selected 1-Year Periods: 1960-1992 (numbers in thousands) 

Residing in the United States at beginning of period 

Residing 

outside the 

Different Different County United States 

house, at the 

Mobility Total same Same Different Different beginning of 

period movers Total county Total State State Region period 

NUMBER 

1991-92 42,800 41,545 26,587 14,957 7,853 7,105 3,285 1,255 

1990-91 41,539 40,154 25,151 15,003 7,881 7,122 3,384 1,385 

1989-90 43,381 41,821 25,726 16,094 8,061 8,033 3,761 1,560 

1988-89 42,620 41,153 26,123 15,030 7,949 7,081 3,258 1,467 

1987-88 42,174 40,974 26,201 14,772 7,727 7,046 3,098 1,200 

1986-87 43,693 42,551 27,196 15,355 8,762 6,593 3,546 1,142 

1985-86 43,237 42,037 26,401 15,636 8,665 6,791 3,778 1,200 

1984-85 46,470 45,043 30,126 14,917 7,995 6,921 3,647 1,427 

1983-84 39,379 38,300 23,659 14,641 8,198 6,444 3,540 1,079 

1982-83 37,408 36,430 22,858 13,572 7,403 6,169 3,192 978 

1981-82 38,127 37,039 23,081 13,959 7,330 6,628 3,679 1,088 

1980-81 38,200 36,887 23,097 13,789 7,614 6,175 3,363 1,313 

1970-71 37,705 36,161 23,018 13,143 6,197 6,946 3,936 1,544 

1960-61 36,533 35,535 24,289 11,246 5,493 5,753 3,097 988 

PERCENT 

1991-92 17.3 16.8 10.7 6.0 3.2 2.9 1.3 0.5 

1990-91 17.0 16.4 10.3 6.1 3.2 2.9 1.4 0.6 

1989-90 17.9 17.3 10.6 6.6 3.3 3.3 1.6 0.6 

1988-89 17.8 17.2 10.9 6.3 3.3 3.0 1.4 0.6 

1987-88 17.8 17.3 11.0 6.2 3.3 3.0 1.3 0.5 

1986-87 18.6 18.1 11.6 6.5 3.7 2.8 1.5 0.5 

1985-86 18.6 18.0 11.3 6.7 3.7 3.0 1.6 0.5 

1984-85 20.2 19.6 13.1 6.5 3.5 3.0 1.6 0.6 

1983-84 17.3 16.8 10.4 6.4 3.6 2.8 1.6 0.5 

1982-83 16.6 16.1 10.1 6.0 3.3 2.7 1.4 0.4 

1981-82 17.0 16.6 10.3 6.2 3.3 3.0 1.6 0.5 

1980-81 17.2 16.6 10.4 6.2 3.4 2.8 1.5 0.6 

1970-71 18.7 17.9 11.4 6.5 3.1 3.4 2.0 0.8 

1960-61 20.6 20.0 13.7 6.3 3.1 3.2 1.7 0.6 

Source: U.S. Bureau of Census, 1993. 
Table 15B-2. Mobility of the Resident Population by State: 1980

 Percent distribution ­

residence in 1975a 

Persons Same 

5 years house 

old, and in Different Different Different 

overb 1980 house, county, county, 

Region, division, 1980 as same same different 

and state (1,000) 1975 county state state 

United States 210,323 53.6 25.1 9.8 9.7 

Northeast 46,052 61.7 22.3 8.0 6.1 

New England 11,594 59.1 23.4 6.7 9.2 

Maine 1,047 56.9 24.0 7.5 10.8 

New Hampshire 857 51.6 22.8 6.2 18.5 

Vermont 476 54.4 23.9 6.5 14.3 

Massachusetts 5,398 61.0 22.7 7.6 7.0 

Rhode Island 891 60.5 23.9 5.0 8.7 

Connecticut 2,925 59.0 24.4 5.5 9.3 

Middle Atlantic 34,458 62.6 21.9 8.4 5.0 

New York 16,432 61.5 22.6 9.3 3.8 

New Jersey 6,904 61.5 20.0 8.6 7.8 

Pennsylvania 11,122 65.0 22.0 7.1 5.2 

Midwest 54,513 55.4 26.4 10.2 7.0 

East North Central 38,623 56.0 27.4 9.6 6.0 

Ohio 10,015 56.7 27.9 9.0 5.7 

Indiana 5,074 54.8 27.5 9.6 7.6 

Illinois 10,593 55.5 28.5 8.1 6.1 

Michigan 8,582 56.4 26.2 11.3 5.1 

Wisconsin 4,360 56.2 25.5 11.0 6.7 

West North Central 15,890 53.9 24.0 11.8 9.4 

Minnesota 3,770 55.6 22.8 13.3 7.3 

Iowa 2,693 55.6 25.0 10.9 7.9 

Missouri 4,564 54.0 24.1 11.8 9.4 

North Dakota 598 51.7 23.1 11.4 12.7 

South Dakota 633 52.9 23.2 12.1 11.1 

Nebraska 1,448 53.1 24.4 11.0 10.5 

Kansas 2,184 50.2 25.1 10.7 12.6 

(Continued on the following page) 
Table 15B-2. Mobility of the Resident Population by State: 1980 (continued)

 Percent distribution ­

residence in 1975a 

Persons Same 

5 years house 

old, and in Different Different Different 

overb 1980 house, county, county, 

Region, division, 1980 as same same different 

and state (1,000) 1975 county state state 

South 69,880 52.4 24.1 10.0 12.0 

South Atlantic 34,498 52.7 22.4 9.7 13.6 

Delaware 555 57.0 26.3 2.0 13.3 

Maryland 3,947 55.5 21.9 10.3 10.4 

District of Columbia 603 58.2 22.7 NA 16.3 

Virginia 4,99i 51.0 17.9 15.0 13.9 

West Virginia 1,806 60.9 23.4 6.6 8.6 

North Carolina 5,476 56.9 23.5 8.9 9.8 

South Carolina 2,884 57.5 22.3 7.7 11.5 

Georgia 5,052 52.5 22.8 12.2 11.5 

Florida 9,183 46.2 23.7 7.8 19.6 

East South Central 13,556 56.0 25.9 7.9 9.5 

Kentucky 3,379 54.4 27.2 8.6 9.0 

Tennessee 4,269 54.2 27.2 7.4 10.6 

Alabama 3,601 57.6 25.3 7.4 8.9 

Mississippi 2,307 59.0 22.5 8.6 9.2 

West South Central 21,826 49.6 25.6 11.8 11.0 

Arkansas 2,113 53.1 24.8 9.1 12.4 

Louisiana 3,847 57.0 24.3 9.2 8.4 

Oklahoma 2,793 47.6 24.9 12.3 13.7 

Texas 13,074 47.3 26.2 12.9 11.0 

West 39,879 43.8 28.3 11.0 13.4 

Mountain 10,386 42.7 25.1 9.1 21.1 

Montana 722 47.3 24.5 12.3 15.0 

Idaho 852 44.4 24.7 9.5 20.0 

Wyoming 425 38.4 23.6 8.6 28.3 

Colorado 2,676 39.8 22.7 14.8 20.6 

New Mexico 1,188 50.3 23.2 7.2 17.4 

Arizona 2,506 41.9 27.1 5.0 23.9 

Utah 1,272 45.8 27.8 8.4 16.0 

Nevada 745 34.8 27.4 3.6 31.5 

(continued on the following page) 
Table 15B-2. Mobility of the Resident Population by State: 1980 (continued)

 Percent distribution ­

residence in 1975a 

Persons Same 

5 years house 

old, and in Different Different Different 

overb 1980 house, county, county, 

Region, division, 1980 as same same different 

and state (1,000) 1975 county state state 

Pacific 29,493 44.2 29.4 11.6 10.7 

Washington 3,825 43.7 27.7 10.1 16.2 

Oregon 2,437 41.4 26.6 13.4 16.9 

California 21,980 44.6 30.2 12.1 8.5 

Alaska 363 32.2 27.6 8.7 29.1 

Hawaii 888 49.3 25.2 2.8 16.9

a

 Survey assessed changes in residence between 1975 and 1980.

b Includes persons residing abroad in 1975.

NA = not applicable.

Source: U.S. Bureau of the Census, Statistical Abstract, 1984. 
Different State 

16.8% 

Different County 

Same State 

18.5% Abroad 

2.9% 

Local Movers, Within 

Same County 

61.95% 

Figure 15-1. Distribution of Individuals Moving by Type of Move: 1991-92 

Source: U.S. Bureau of the Census, 1993a 
Table 16-1. Consumer Products Found in the Typical U.S. Householda 

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) 

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) 
Table 16-1. Consumer Products Found in the Typical U.S. Household (continued) a 

Consumer Product Category Consumer Product 

Household Maintenance Products Fabric rinse/softener (powder) 

(continued) 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) 

Home Building/Improvement Products (DIY) Adhesives, specialty (liquid) b 

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) 
Table 16-1. Consumer Products Found in the Typical U.S. Household (continued) a 

Consumer Product Category Consumer Product 

Home Building/Improvement Products (DIY) Paint/varnish removers b

 (Continued) 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 subjective listing based on consumer use profiles. a 

DIY = Do It Yourself. b 

Source: U.S. EPA, 1987. 
Table 16-2. Frequency of Use for Household Solvent Products (users-only) 

Products 

Percentile Rankings for Frequency of Use/Year 

Mean Std. dev. Min. 1 5 10 25 50 75 90 95 99 Max. 

Spray Shoe Polish 10.28 20.10 1.00 1.00 1.00 1.00 2.00 4.00 8.00 24.30 52.00 111.26 156.00 

Water Repellents/Protectors 3.50 11.70 1.00 1.00 1.00 1.00 1.00 2.00 3.00 6.00 10.00 35.70 300.00 

Spot Removers 15.59 43.34 1.00 1.00 1.00 1.00 2.00 3.00 10.00 40.00 52.00 300.00 365.00 

Solvent-Type Cleaning Fluids or Degreasers 16.46 44.12 1.00 1.00 1.00 1.00 2.00 4.00 12.00 46.00 52.00 300.00 365.00 

Wood Floor and Paneling Cleaners 8.48 20.89 1.00 1.00 1.00 1.00 NA 2.00 6.00 24.00 50.00 56.00 350.00 

TypeWriter Correction Fluid 40.00 74.78 1.00 1.00 1.00 2.00 4.00 12.00 40.00 100.00 200.00 365.00 520.00 

Adhesives 8.89 26.20 1.00 1.00 1.00 1.00 2.00 3.00 6.00 15.00 28.00 100.00 500.00 

Adhesive Removers 4.22 12.30 1.00 1.00 1.00 1.00 1.00 1.00 3.00 6.00 16.80 100.00 100.00 

Silicone Lubricants 10.32 25.44 1.00 1.00 1.00 1.00 2.00 3.00 10.00 20.00 46.35 150.00 300.00 

Other Lubricants (excluding Automotive) 10.66 25.46 1.00 1.00 1.00 1.00 2.00 4.00 10.00 20.00 50.00 100.00 420.00 

Specialized Electronic Cleaners (for TVs, Etc.) 13.41 38.16 1.00 1.00 1.00 1.00 2.00 3.00 10.00 24.00 52.00 224.50 400.00 

Latex Paint 3.93 20.81 1.00 1.00 1.00 1.00 1.00 2.00 4.00 6.00 10.00 30.00 800.00 

Oil Paint 5.66 23.10 1.00 1.00 1.00 1.00 1.00 1.00 3.00 6.00 12.00 139.20 300.00 

Wood Stains, Varnishes, and Finishes 4.21 12.19 1.00 1.00 1.00 1.00 1.00 2.00 4.00 7.00 12.00 50.80 250.00 

Paint Removers/Strippers 3.68 9.10 1.00 1.00 1.00 1.00 4.00 2.00 3.00 6.00 11.80 44.56 100.00 

Paint Thinners 6.78 22.10 0.03 0.03 0.10 0.23 1.00 2.00 4.00 12.00 23.00 100.00 352.00 

Aerosol Spray Paint 4.22 15.59 1.00 1.00 1.00 1.00 1.00 2.00 4.00 6.10 12.00 31.05 365.00 

Primers and Special Primers 3.43 8.76 1.00 1.00 1.00 1.00 1.00 1.00 3.00 6.00 10.00 50.06 104.00 

Aerosol Rust Removers 6.17 9.82 1.00 1.00 1.00 1.00 1.00 2.00 6.00 15.00 24.45 50.90 80.00 

Outdoor Water Repellents (for Wood or Cement) 2.07 3.71 1.00 1.00 1.00 1.00 1.00 2.00 2.00 3.00 5.90 12.00 52.00 

Glass Frostings, Window Tints, and Artificial 2.78 21.96 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 27.20 365.00 

Snow 

Engine Degreasers 4.18 13.72 1.00 1.00 1.00 1.00 1.00 2.00 3.25 6.70 12.00 41.70 300.00 

Carburetor Cleaners 3.77 7.10 1.00 1.00 1.00 1.00 1.00 2.00 3.00 6.00 12.00 47.28 100.00 

Aerosol Spray Paints for Cars 4.50 9.71 1.00 1.00 1.00 1.00 1.00 2.00 4.00 10.00 15.00 60.00 100.00 

Auto Spray Primers 6.42 33.89 1.00 1.00 1.00 1.00 1.00 2.00 3.75 10.00 15.00 139.00 500.00 

Spray Lubricant for Cars 10.31 30.71 1.00 1.00 1.00 1.00 2.00 3.00 6.00 20.00 40.00 105.60 365.00 

Transmission Cleaners 2.28 3.55 1.00 NA 1.00 1.00 1.00 1.00 2.00 3.00 9.00 NA 26.00 

Battery Terminal Protectors 3.95 24.33 1.00 1.00 1.00 1.00 1.00 2.00 2.00 4.00 6.55 41.30 365.00 

Brake Quieters Cleaners 3.00 6.06 1.00 NA 1.00 1.00 1.00 2.00 2.00 6.00 10.40 NA 52.00 

Gasket Remover 2.50 4.39 1.00 NA 1.00 1.00 1.00 1.00 2.00 5.00 6.50 NA 30.00 

Tire/Hubcap Cleaners 11.18 18.67 1.00 1.00 1.00 1.00 2.00 4.00 12.00 30.00 50.00 77.00 200.00 

Ignition and Wire Dryers 3.01 5.71 1.00 1.00 1.00 1.00 1.00 2.00 3.00 5.00 9.70 44.52 60.00 

NA = Not Available 

Source: Westat, 1987a 
Table 16-3. Exposure Time of Use for Household Solvent Products (users-only) 

Percentile Rankings for Duration of Use (minutes) 

Mean Std. 

Products (mins) dev. Min. 1 5 10 25 50 75 90 95 99 Max. 

Spray Shoe Polish 7.49 9.60 0.02 0.03 0.25 0.50 2.00 5.00 10.00 18.00 30.00 60.00 60.00 

Water Repellents/Protectors 14.46 24.10 0.02 0.08 0.50 1.40 3.00 10.00 15.00 30.00 60.00 120.00 480.00 

Spot Removers 10.68 22.36 0.02 0.03 0.08 0.25 2.00 5.00 10.00 30.00 30.00 120.00 360.00 

Solvent-Type Cleaning Fluids or 29.48 97.49 0.02 0.03 1.00 2.00 5.00 15.00 30.00 60.00 120.00 300.00 1800.00 

Degreasers 

Wood Floor and Paneling Cleaners 74.04 128.43 0.02 1.00 5.00 10.00 20.00 30.00 90.00 147.00 240.00 480.00 2700.00 

TypeWriter Correction Fluid 7.62 29.66 0.02 0.02 0.03 0.03 0.17 1.00 2.00 10.00 32.00 120.00 480.00 

Adhesives 15.58 81.80 0.02 0.03 0.08 0.33 1.00 4.25 10.00 30.00 60.00 180.00 2880.00 

Adhesive Removers 121.20 171.63 0.03 0.03 1.45 3.00 15.00 60.00 120.00 246.00 480.00 960.00 960.00 

Silicone Lubricants 10.42 29.47 0.02 0.03 0.08 0.17 0.50 2.00 10.00 20.00 45.00 180.00 360.00 

Other Lubricants (excluding 8.12 32.20 0.02 0.03 0.05 0.08 0.50 2.00 5.00 15.00 30.00 90.00 900.00

 Automotive) 

Specialized Electronic Cleaners 9.47 45.35 0.02 0.03 0.08 0.17 0.50 2.00 5.00 20.00 30.00 93.60 900.00

 (for TVs, Etc.) 

Latex Paint 295.08 476.11 0.02 1.00 22.50 30.00 90.00 180.00 360.00 480.00 810.00 2880.00 5760.00 

Oil Paint 194.12 345.68 0.02 0.51 15.00 30.00 60.00 12.00 240.00 480.00 579.00 1702.80 5760.00 

Wood Stains, Varnishes, and Finishes 117.17 193.05 0.02 0.74 5.00 10.00 30.00 60.00 120.00 140.00 360.00 720.00 280.00 

Paint Removers/Strippers 125.27 286.59 0.02 0.38 5.00 5.00 20.00 60.00 120.00 240.00 420.00 1200.00 4320.00 

Paint Thinners 39.43 114.85 0.02 0.08 1.00 2.00 5.00 10.00 30.00 60.00 180.00 480.00 2400.00 

Aerosol Spray Paint 39.54 87.79 0.02 0.17 2.00 5.00 10.00 20.00 45.00 60.00 120.00 300.00 1800.00 

Primers and Special Primers 91.29 175.05 0.05 0.24 3.00 5.00 15.00 30.00 120.00 240.00 360.00 981.60 1920.00 

Aerosol Rust Removers 18.57 48.54 0.02 0.05 0.17 0.25 2.00 5.00 20.00 60.00 60.00 130.20 720.00 

Outdoor Water Repellents 104.94 115.36 0.02 0.05 5.00 15.00 30.00 60.00 120.00 240.00 300.00 480.00 960.00

 (for Wood or Cement) 29.45 48.16 0.03 0.14 2.00 3.00 5.00 15.00 30.00 60.00 96.00 268.80 360.00 

Glass Frostings, Window Tints, and 29.29 48.14 0.02 0.95 2.00 5.00 10.00 15.00 30.00 60.00 120.00 180.00 900.00

 Artificial Snow 

Engine Degreasers, 13.57 23.00 0.02 0.08 0.33 1.00 3.00 7.00 15.00 30.00 45.00 120.00 300.00

 Carburetor Cleaners 

Aerosol Spray Paints for Cars 42.77 71.39 0.03 0.19 1.00 3.00 10.00 20.00 60.00 120.00 145.00 360.00 900.00 

Auto Spray Primers 51.45 86.11 0.05 0.22 2.00 5.00 10.00 27.50 60.00 120.00 180.00 529.20 600.00 

Spray Lubricant for Cars 9.90 35.62 0.02 0.03 0.08 0.17 1.00 5.00 10.00 15.00 30.00 120.00 720.00 

Transmission Cleaners 27.90 61.44 0.17 NA 0.35 1.80 5.00 15.00 30.00 60.00 60.00 NA 450.00 

Battery Terminal Protectors 9.61 18.15 0.03 0.04 0.08 0.23 1.00 5.00 10.00 20.00 30.00 120.00 180.00 

Brake Quieters/Cleaners 23.38 36.32 0.07 NA 0.50 1.00 5.00 15.00 30.00 49.50 120.00 NA 240.00 

Gasket Remover 23.57 27.18 0.33 NA 0.50 2.00 6.25 15.00 30.00 60.00 60.00 NA 180.00 

Tire/Hubcap Cleaners 22.66 23.94 0.08 0.71 3.00 5.00 10.00 15.00 30.00 60.00 60.00 120.00 240.00 

Ignition and Wire Dryers 7.24 8.48 0.02 0.02 0.08 0.47 1.50 5.00 10.00 15.00 25.50 48.60 60.00 

NA = Not Available 

Source: Westat, 1987a 
Table 16-4. Amount of Products Used for Household Solvent Products (users-only) 

Percentile Rankings for Amount of Products Used (ounces/yr) 

Mean Std. 

Products (ounces/yr) dev Min. 1 5 10 25 50 75 90 95 99 Max. 

Spray Shoe Polish 9.90 17.90 0.04 0.20 0.63 1.00 2.00 4.50 10.00 24.00 36.00 99.36 180.00 

Water Repellents/Protectors 11.38 22.00 0.04 0.47 0.98 1.43 2.75 6.00 12.00 24.00 33.00 121.84 450.00 

Spot Removers 26.32 90.10 0.01 0.24 0.60 1.00 2.00 5.50 16.00 48.00 119.20 384.00 1600.00 

Solvent-Type Cleaning Fluids or 58.30 226.97 0.04 0.50 2.00 3.00 6.50 16.00 32.00 96.00 192.00 845.00 5120.00

 Degreasers 

Wood Floor and Paneling Cleaners 28.41 57.23 0.03 0.80 2.45 3.50 7.00 14.00 30.00 64.00 96.00 204.40 1144.00 

TypeWriter Correction Fluid 4.14 13.72 0.01 0.02 0.06 0.12 0.30 0.94 2.40 8.00 18.00 67.44 181.80 

Adhesives 7.49 55.90 0.01 0.02 0.05 0.12 0.35 1.00 3.00 8.00 20.00 128.00 1280.00 

Adhesive Removers 34.46 96.60 0.25 0.29 1.22 2.80 6.00 10.88 32.00 64.00 138.70 665.60 1024.00 

Silicone Lubricants 12.50 27.85 0.02 0.20 0.69 1.00 2.25 4.50 12.00 24.00 41.20 192.00 312.00 

Other Lubricants (excluding 9.93 44.18 0.01 0.18 0.30 0.52 1.00 2.25 8.00 18.00 32.00 128.00 1280.00

 Automotive) 

Specialized Electronic Cleaners 9.48 55.26 0.01 0.05 0.13 0.25 0.52 2.00 6.00 12.65 24.00 109.84 1024.00

 (for TVs, Etc.) 

Latex Paint 371.27 543.86 0.03 4.00 12.92 32.00 64.00 256.00 384.00 857.60 1280.00 2560.00 6400.00 

Oil Paint 168.92 367.82 0.02 0.33 4.00 8.00 25.20 64.00 148.48 384.00 640.00 1532.16 5120.00 

Wood Stains, Varnishes, and 65.06 174.01 0.12 1.09 4.00 4.00 8.00 16.00 64.00 128.00 256.00 768.00 3840.00

 Finishes 

Paint Removers/Strippers 63.73 144.33 0.64 1.50 4.00 8.00 16.00 32.00 64.00 128.00 256.00 512.00 2560.00 

Paint Thinners 69.45 190.55 0.03 0.45 3.10 4.00 8.00 20.48 64.00 128.00 256.00 640.00 3200.00 

Aerosol Spray Paint 30.75 52.84 0.02 0.75 2.01 3.25 7.00 13.00 32.00 65.00 104.00 240.00 1053.00 

Primers and Special Primers 68.39 171.21 0.01 0.09 1.30 3.23 8.00 16.00 60.00 128.00 256.00 867.75 1920.00 

Aerosol Rust Removers 18.21 81.37 0.09 0.25 1.00 1.43 2.75 8.00 13.00 32.00 42.60 199.80 1280.00 

Outdoor Water Repellents 148.71 280.65 0.01 0.37 3.63 8.00 16.00 64.00 128.00 448.00 640.00 979.20 3200.00

 (for Wood or Cement) 

Glass Frostings, Window Tints, and 13.82 14.91 1.00 1.40 2.38 3.25 6.00 12.00 14.00 28.00 33.00 98.40 120.00

 Artificial Snow 

Engine Degreasers 46.95 135.17 0.04 1.56 4.00 6.00 12.00 16.00 36.00 80.00 160.00 480.00 2560.00 

Carburetor Cleaners 22.00 50.60 0.10 0.50 1.50 3.00 5.22 12.00 16.00 39.00 75.00 212.00 672.00 

Aerosol Spray Paints for Cars 44.95 89.78 0.04 0.14 1.50 3.00 6.12 16.00 48.00 100.80 156.00 557.76 900.00 

Auto Spray Primers 70.37 274.56 0.12 0.77 3.00 4.00 9.00 16.00 48.00 128.00 222.00 1167.36 3840.00 

Spray Lubricant for Cars 18.63 54.74 0.08 0.40 0.96 1.00 2.75 6.00 15.50 36.00 64.00 240.00 864.00 

Transmission Cleaners 35.71 62.93 2.00 NA 3.75 4.00 8.00 15.00 32.00 77.00 140.00 NA 360.00 

Battery Terminal Protectors 16.49 87.84 0.12 0.13 0.58 1.00 2.00 4.00 8.00 15.00 24.60 627.00 1050.00 

Brake Quieters/Cleaners 11.72 13.25 0.50 NA 1.00 2.00 3.02 8.00 14.25 32.00 38.60 NA 78.00 

Gasket Remover 13.25 22.35 0.50 NA 1.00 1.00 3.75 7.75 16.00 24.00 58.40 NA 160.00 

Tire/Hubcap Cleaners 31.58 80.39 0.12 0.50 1.82 3.00 6.00 12.00 28.00 64.00 96.00 443.52 960.00 

Ignition and Wire Dryers 9.02 14.59 0.13 0.32 1.09 1.50 3.00 6.00 10.75 16.00 20.55 113.04 120.00 

NA = Not Available 

Source: Westat, 1987a 
Table 16-5. Time Exposed After Duration of Use for Household Solvent Products (users-only) 

Percentile Rankings for Time Exposed After Duration of Use (minutes) 

Products Mean Std. 

(mins) dev. Min. 1 5 10 25 50 75 90 95 99 Max. 

Spray Shoe Polish 31.40 80.50 0.00 0.00 0.00 0.00 0.00 5.00 20.00 120.00 120.00 480.00 720.00 

Water Repellents/Protectors 37.95 111.40 0.00 0.00 0.00 0.00 0.00 3.00 20.00 120.00 240.00 480.00 1800.00 

Spot Removers 43.65 106.97 0.00 0.00 0.00 0.00 1.00 5,.00 30.00 120.00 240.00 480.00 1440.00 

Solvent-Type Cleaning Fluids or Degreasers 33.29 90.39 0.00 0.00 0.00 0.00 0.00 3.00 28.75 60.00 180.00 480.00 1440.00 

Wood Floor and Paneling Cleaners 96.75 192.88 0.00 0.00 0.00 0.00 5.00 30.00 120.00 240.00 480.00 1062.00 1440.00 

TypeWriter Correction Fluid 124.70 153.46 0.00 0.00 1.00 5.00 30.00 60.00 180.00 360.00 480.00 600.00 1800.00 

Adhesives 68.88 163.72 0.00 0.00 0.00 0.00 1.00 10.00 60.00 180.00 360.00 720.00 2100.00 

Adhesive Removers 94.12 157.69 0.00 0.00 0.00 0.00 1.75 20.00 120.00 360.00 480.00 720.00 720.00 

Silicone Lubricants 30.77 107.39 0.00 0.00 0.00 0.00 0.00 0.00 10.00 60.00 180.00 480.00 1440.00 

Other Lubricants (excluding Automotive) 47.45 127.11 0.00 0.00 0.00 0.00 0.00 2.00 30.00 120.00 240.00 485.40 1440.00 

Specialized Electronic Cleaners 117.24 154.38 0.00 0.00 0.00 1.00 10.00 60.00 180.00 300.00 480.00 720.00 1440.00

 (for TVs, Etc.) 

Latex Paint 91.38 254.61 0.00 0.00 0.00 0.00 0.00 5.00 60.00 240.00 480.00 1440.00 2880.00 

Oil Paint 44.56 155.19 0.00 0.00 0.00 0.00 0.00 0.00 30.00 120.00 240.00 480.00 2880.00 

Wood Stains, Varnishes, and Finishes 48.33 156.44 0.00 0.00 0.00 0.00 0.00 1.00 30.00 120.00 240.00 694.00 2880.00 

Paint Removers/Strippers 31.38 103.07 0.00 0.00 0.00 0.00 0.00 0.00 20.00 60.00 180.00 541.20 1440.00 

Paint Thinners 32.86 105.62 0.00 0.00 0.00 0.00 0.00 0.00 15.00 60.00 180.00 480.00 1440.00 

Aerosol Spray Paint 12.70 62.80 0.00 0.00 0.00 0.00 0.00 0.00 1.00 30.00 60.00 260.50 1440.00 

Primers and Special Primers 22.28 65.57 0.00 0.00 0.00 0.00 0.00 0.00 10.00 60.00 120.00 319.20 720.00 

Aerosol Rust Removers 15.06 47.58 0.00 0.00 0.00 0.00 0.00 0.00 5.00 60.00 60.00 190.20 600.00 

Outdoor Water Repellents 8.33 43.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.00 58.50 309.60 420.00

 (for Wood or Cement) 

Glass Frostings, Window Tints, and Artificial 137.87 243.21 0.00 0.00 0.00 0.00 3.00 60.00 180.00 360.00 480.00 1440.00 1800.00

 Snow 

Engine Degreasers 4.52 24.39 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 15.50 120.00 360.00 

Carburetor Cleaners 7.51 68.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 30.00 120.60 1800.00 

Aerosol Spray Paints for Cars 10.71 45.53 0.00 0.00 0.00 0.00 0.00 0.00 0.00 17.50 60.00 282.00 480.00 

Auto Spray Primers 11.37 45.08 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20.00 77.25 360.00 360.00 

Spray Lubricant for Cars 4.54 30.67 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.00 15.00 70.20 420.00 

Transmission Cleaners 5.29 29.50 0.00 NA 0.00 0.00 0.00 0.00 0.00 5.00 22.50 NA 240.00 

Battery Terminal Protectors 3.25 17.27 0.00 NA 0.00 0.00 0.00 0.00 0.00 2.90 15.00 120.00 180.00 

Brake Quieters/Cleaners 10.27 30.02 0.00 NA 0.00 0.00 0.00 0.00 0.00 30.00 120.00 NA 120.00 

Gasket Remover 27.56 58.54 0.00 NA 0.00 0.00 0.00 0.00 12.50 120.00 180.00 NA 240.00 

Tire/Hubcap Cleaners 1.51 20.43 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 30.00 480.00 

Ignition and Wire Dryers 6.39 31.63 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 30.00 216.60 240.00 

NA = Not Available 

Source: Westat, 1987a 
Table 16-6. Frequency of Use and Amount of Product Used for Adhesive Removers 

No. of Times Minutes in Amount Used in 

Used Within the Minutes Minutes in Room Room After Past Year (Fluid Amount per 

Last 12 Months Using After Using Using oz.) a b Use (Fluid oz.) 

N=58 N=52 N=51 N=5 N=51 N=51 

Mean 1.66 172.87 13.79 143.37 96.95 81.84 

Standard deviation 1.67 304.50 67.40 169.31 213.20 210.44 

Minimum Value 1.00 5.00 0.00 5.00 13.00 5.20

 1st Percentile 1.00 5.00 0.00 5.00 13.00 5.20

 5th Percentile 1.00 10.00 0.00 5.00 13.00 6.50

 10th Percentile 1.00 15.00 0.00 5.00 16.00 10.67

 25th Percentile 1.00 29.50 0.00 20.00 16.00 16.00 

Median Value 1.00 120.00 0.00 120.00 32.00 26.00

 75th Percentile 2.00 240.00 0.00 420.00 96.00 64.00

 90th Percentile 3.00 480.00 0.00 420.00 128.00 128.00

 95th Percentile 5.00 1440.00 120.00 420.00 384.00 192.00

 99th Percentile 12.00 1440.00 420.00 420.00 1280.00 1280.00 

Maximum Value 12.00 1440.00 420.00 1440.00 1280.00 1280.00

a

 Includes those who did not spend anytime in the room after use. 

b Includes only those who spent time in the room. 

Source: Abt, 1992. 
Table 16-7. Adhesive Remover Usage by Gender 

Gender 

Male Female 

N=25 N=33 

Mean number of months since last time adhesive remover was used - includes all 35.33 43.89

 respondents. (Unweighted N=240) 

Mean number of uses of product in the past year. 1.94 1.30 

Mean number of minutes spent with the product during last use. 127.95 233.43 

Mean number of minutes spent in the room after last use of product. (Includes all 19.76 0

 recent users) 

Mean number of minutes spent in the room after last use of product. (Includes only 143.37 0

 those who did not leave immediately) 

Mean ounces of product used in the past year. 70.48 139.71 

Mean ounces of product used per use in the past year. 48.70 130.36 

Source: Abt, 1992. 
Table 16-8. Frequency of Use and Amount of Product Used for Spray Paint 

No. of Times Minutes in Amount Used in 

Used Within the Minutes Minutes in Room Room After Past Year Amount per 

Last 12 Months Using After Using Using (Fluid oz.) a b Use (Fluid oz.) 

N=775 N=786 N=791 N=35 N=778 N=778 

Mean 8.23 40.87 3.55 65.06 83.92 19.04 

Standard deviation 31.98 71.71 22.03 70.02 175.32 25.34 

Minimum Value 1.00 1.00 0.00 1.00 13.00 0.36

 1st Percentile 1.00 1.00 0.00 1.00 13.00 0.36

 5th Percentile 1.00 3.00 0.00 1.00 13.00 3.47

 10th Percentile 1.00 5.00 0.00 10.00 13.00 6.50

 25th Percentile 1.00 10.00 0.00 15.00 13.00 9.75 

Median Value 2.00 20.00 0.00 30.00 26.00 13.00

 75th Percentile 4.00 45.00 0.00 60.00 65.00 21.67

 90th Percentile 11.00 90.00 0.00 120.00 156.00 36.11

 95th Percentile 20.00 120.00 0.00 120.00 260.00 52.00

 99th Percentile 104.00 360.00 120.00 300.00 1170.00 104.00 

Maximum Value 365.00 960.00 300.00 300.00 1664.00 312.00

a

 Includes those who did not spend anytime in the room after use. 

b Includes only those who spent time in the room. 

Source: Abt, 1992. 
Table 16-9. Spray Paint Usage by Gender 

Gender 

Male Female 

N=405 N=386 

Mean number of months since last time spray paint was used - includes all 17.39 26.46

 respondents. (Unweighted N=1724) 

Mean number of uses of product in the past year. 10.45 4.63 

Mean number of minutes spent with the product during last use. 40.87 40.88 

Mean number of minutes spent in the room after last use of product. (Includes all 5.49 0.40

 recent users) 

Mean number of minutes spent in the room after last use of product. (Includes only 67.76 34.69

 those who did not leave immediately) 

Mean ounces of product used in the past year. 103.07 59.99 

Mean ounces of product used per use in the past year. 18.50 19.92 

Source: Abt, 1992. 
Table 16-10. Frequency of Use and Amount of Product Used for Paint Removers/Strippers 

No. of Times Amount Used in 

Used Within the Minutes Minutes in Minutes in Past Year Amount per 

Last 12 Months Using Room After Room After (Fluid oz.) Use (Fluid oz.) 

N=316 N=390 Using Using N=307 a b N=307 

N=390 N=39 

Mean 3.54 144.59 12.96 93.88 142.05 64.84 

Standard deviation 7.32 175.54 85.07 211.71 321.73 157.50 

Minimum Value 1.00 2.00 0.00 1.00 15.00 0.35

 1st Percentile 1.00 5.00 0.00 1.00 15.00 2.67

 5th Percentile 1.00 15.00 0.00 1.00 16.00 8.00

 10th Percentile 1.00 20.00 0.00 3.00 16.00 10.67

 25th Percentile 1.00 45.00 0.00 10.00 32.00 16.00 

Median Value 2.00 120.00 0.00 60.00 64.00 32.00

 75th Percentile 3.00 180.00 0.00 120.00 128.00 64.00

 90th Percentile 6.00 360.00 10.00 180.00 256.00 128.00

 95th Percentile 12.00 480.00 60.00 420.00 384.00 192.00

 99th Percentile 50.00 720.00 180.00 1440.00 1920.00 320.00 

Maximum Value 70.00 1440.00 1440.00 1440.00 3200.00 2560.00

a

 Includes those who did not spend anytime in the room after use. 

b Includes only those who spent time in the room. 

Source: Abt, 1992. 
Table 16-11. Paint Stripper Usage by Gender 

Gender 

Male Female 

N=156 N=162 

Mean number of months since last time paint stripper was used - includes all 32.07 47.63

 respondents. (Unweighted N=1724) 

Mean number of uses of product in the past year. 3.88 3.01 

Mean number of minutes spent with the product during last use. 136.70 156.85 

Mean number of minutes spent in the room after last use of product. (Includes all 15.07 9.80

 recent users) 

Mean number of minutes spent in the room after last use of product. (Includes only 101.42 80.15

 those who did not leave immediately) 

Mean ounces of product used in the past year. 160.27 114.05 

Mean ounces of product used per use in the past year. 74.32 50.29 

Source: Abt, 1992. 
Table 16-12. Total Exposure Time of Performing Task and Product Type 

Used by Task for Household Cleaning Products 

Mean Median Product Type Percent of 

Tasks (hrs/year) (hrs/year) Used Preference 

Clean Bathroom Sinks and Tubs 44 26 Liquid 

Powder 

29% 

44% 

Aerosol 16% 

Spray pump 

Other 

10% 

1% 

Clean Kitchen Sinks 41 18 Liquid 

Powder 

31% 

61% 

Aerosol 2% 

Spray pump 

Other 

4% 

2% 

Clean Inside of Cabinets 12 5 Liquid 

(such as kitchen) Powder 

Aerosol 

68% 

12% 

2% 

Spray pump 

Other 

16% 

2% 

Clean Outside of Cabinets 21 6 Liquid 

Powder 

61% 

8% 

Aerosol 16% 

Spray pump 

Other 

13% 

2% 

Wipe Off Kitchen Counters 92 55 Liquid 

Powder 

67% 

13% 

Aerosol 2% 

Spray pump 

Other 

15% 

3% 

Thoroughly Clean Counters 24 13 Liquid 

Powder 

56% 

21% 

Aerosol 5% 

Spray pump 

Other 

17% 

1% 

Clean Bathroom Floors 20 9 Liquid 

Powder 

70% 

21% 

Aerosol 2% 

Spray pump 

Other 

4% 

3% 

Clean Kitchen Floors 31 14 Liquid 

Powder 

70% 

27% 

Aerosol 2% 

Spray pump 

Other 

1% 

-­

Clean Bathroom or Other Tilted or Ceramic Walls 16 9 Liquid 

Powder 

37% 

18% 

Aerosol 17% 

Spray pump 

Other 

25% 

3% 
Table 16-12. Total Exposure Time of Performing Task and Product Type Used by 

Task for Household Cleaning Products (continued) 

Mean Median Product Type Percent of 

Tasks (hrs/year) (hrs/year) Used Preference 

Clean Outside of Windows 13 6 Liquid 

Powder 

27% 

2% 

Aerosol 6% 

Spray pump 

Other 

65% 

-­

Clean Inside of Windows 18 6 Liquid 

Powder 

24% 

1% 

Aerosol 8% 

Spray pump 

Other 

66% 

2% 

Clean Glass Surfaces Such as Mirrors & Tables 34 13 Liquid 

Powder 

13% 

1% 

Aerosol 8% 

Spray pump 

Other 

76% 

2% 

Clean Outside of Refrigerator and Other Appliances 27 13 Liquid 

Powder 

48% 

3% 

Aerosol 7% 

Spray pump 

Other 

38% 

4% 

Clean Spots or Dirt on Walls or Doors 19 8 Liquid 

Finishes Powder 

46% 

15% 

Aerosol 4% 

Spray pump 

Other 

30% 

4% 

Source: Westat, 1987b. 
Table 16-13. Percentile Rankings for Total Exposure Time in Performing Household Tasks 

Percentile Rankings for Total Exposure Exposure Time Performing Task 

(hrs/yr) 

Tasks 100th 95th 90th 75th 50th 25th 10th 0th 

Clean Bathroom Sinks and Tubs 365 121.67 91.25 52 26 13 5.2 0.4 

Clean Kitchen Sinks 547.5 121.67 97.6 60.83 18.25 8.67 3.47 0.33 

Clean Inside of Kitchen Cabinets 208 48 32.48 12 4.75 2 1 0.17 

Clean Outside of Cabinets 780 78.66 36 17.33 6 2 0.967 0.07 

Wipe Off Kitchen Counters 912.5 456.25 231.16 91.25 54.75 24.33 12.17 1.2 

Thoroughly Clean Counters 547.5 94.43 52 26 13 6 1.75 0.17 

Clean Bathroom Floors 365 71.49 36.83 26 8.67 4.33 2 0.1 

Clean Kitchen Floors 730 96.98 52 26 14 8.67 4.33 0.5 

Clean Bathroom or Other Tilted or Ceramic 208 52 36 26 8.67 3 1 0.17

 Walls 

Clean Outside of Windows 468 32.6 24 11.5 6 2 1.5 0.07 

Clean Inside of Windows 273 72 36 19.5 6 3 1.15 0.07 

Clean Glass Surfaces Such as Mirrors & Tables 1460 104 60.83 26 13 6 1.73 0.17 

Clean Outside Refrigerator and Other 365 95.29 91.25 30.42 13 4.33 1.81 0.1

 Appliances 

Clean Spots or Dirt on Walls or Doors 312 78 52 24 8 2 0.568 0.07 

Source: Westat, 1987b. 
Table 16-14. Mean Percentile Rankings for Frequency of Performing Household Tasks 

Percentile Rankings 

Tasks Mean 

0th 10th 25th 50th 75th 90th 95th 100th 

Clean bathroom sinks and tubs 3 x/week 0.2 x/week 1 x/week 1 x/week 2 x/week 3.5 x/week 7 x/week 7 x/week 42 x/week 

Clean kitchen sinks 7 x/week 0 x/week 1 x/week 2 x/week 7 x/week 7 x/week 15 x/week 21 x/week 28 x/week 

Clean inside of cabinets such as those in the 9 x/year 1 x/year 1 x/year 1 x/year 2 x/year 12 x/year 12 x/year 52 x/year 156 x/year

 kitchen 

Clean outside of cabinets 3 x/month 0.1 x/month 0.1 x/month 0.3 x/month 1 x/month 4 x/month 4 x/month 22 x/month 30 x/month 

Wipe off counters such as those in the 2 x/day 0 x/day 0.4 x/day 1 x/day 1 x/day 3 x/day 4 x/day 6 x/day 16 x/day

 kitchen 

Thoroughly clean counters 8 x/month 0.1 x/month 0.8 x/month 1 x/month 4 x/month 4 x/month 30 x/month 30 x/month 183 x/month 

Clean bathroom floors 6 x/month 0.2 x/month 1 x/month 2 x/month 4 x/month 4 x/month 13 x/month 30 x/month 30 x/month 

Clean kitchen floors 6 x/month 0.1 x/month 1 x/month 2 x/month 4 x/month 4 x/month 13 x/month 30 x/month 30 x/month 

Clean bathroom or other tiled or ceramic 4 x/month 0.1 x/month 0.2 x/month 1 x/month 2 x/month 4 x/month 9 x/month 13 x/month 30 x/month

 walls 

Clean outside of windows 5 x/year 1 x/year 1 x/year 1 x/year 2 x/year 4 x/year 12 x/year 12 x/year 156 x/year 

Clean inside of windows 10 x/year 1 x/year 1 x/year 2 x/year 4 x/year 12 x/year 24 x/year 52 x/year 156 x/year 

Clean other glass surfaces such as mirrors 7 x/month 0.1 x/month 1 x/month 2 x/month 4 x/month 4 x/month 17 x/month 30 x/month 61 x/month

 and tables 

Clean outside of refrigerator and other 10 x/month 0.2 x/month 1 x/month 2 x/month 4 x/month 13 x/month 30 x/month 30 x/month 61 x/month

 appliances 

Clean spots or dirt on walls or doors 6 x/month 0.1 x/month 0.2 x/month 0.3 x/month 1 x/month 4 x/month 13 x/month 30 x/month 152 x/month 

Source: Westat, 1987b. 
16-15. Mean and Percentile Rankings for Exposure Time Per Event of Performing Household Tasks 

Percentile Rankings (minutes/event) 

Mean 

Tasks (minutes/event) 0th 10th 25th 50th 75th 90th 95th 100th 

Clean bathroom sinks and tubs 

Clean kitchen sinks 

Clean inside of cabinets such as those in the 

kitchen 

Clean outside of cabinets 

Wipe off counters such as those in the kitchen 

Thoroughly clean counters 

Clean bathroom floors 

Clean kitchen floors 

Clean bathroom or other tiled or ceramic walls 

Clean outside of windows 

Clean inside of windows 

Clean other glass surfaces such as mirrors and 

tables 

Clean outside of refrigerator and other 

appliances 

Clean spots or dirt on walls or doors 

Source: Westat, 1987b. 

20 1 5 10 15 30 45 60 90 

10 1 2 3 5 10 15 20 480 

137 5 24 44 120 180 240 360 2,880

52 1 5 15 30 60 120 180 330 

9 1 2 3 5 10 15 30 120 

25 1 5 10 15 30 60 90 180 

16 1 5 10 15 20 30 38 60 

30 2 10 15 20 30 60 60 180 

34 1 5 15 30 45 60 120 240 

180 4 30 60 120 240 420 480 1,200 

127 4 20 45 90 158 300 381 1,200 

24 1 5 10 15 30 60 60 180

19 1 4 5 10 20 30 45 240

50 1 5 10 20 60 120 216 960 
Table 16-16. Total Exposure Time for Ten Product Groups Most Frequently Used for Household Cleaninga 

Percentile Rankings of Total Exposure Time 

Mean (hrs/yr) 

Products (hrs/yr) 

0th 10th 25th 50th 75th 90th 95th 100th 

Dish Detergents 107 0.2 6 24 56 134 274 486 941 

Glass Cleaners 67 0.4 3 12 29 62 139 260 1,508 

Floor Cleaners 52 0.7 4 7 22 52 102 414 449 

Furniture Polish 32 0.1 0.3 1 12 36 101 215 243 

Bathroom Tile Cleaners 47 0.5 2 8 17 48 115 287 369 

Liquid Cleansers 68 0.2 2 9 22 52 122 215 2,381 

Scouring Powders 78 0.3 9 17 35 92 165 281 747 

Laundry Detergents 66 0.6 8 14 48 103 174 202 202 

Rug Cleaners/Shampoos 12 0.3 0.3 0.3 9 26 26 26 26 

All Purpose Cleaners 64 0.3 4 9 26 77 174 262 677 

a The data in Table 16-15 above reflect for only the 14 tasks included in the survey. Therefore, many of the durations reported in 

the table underestimate the hours of the use of the product group. For example, use of dish detergents to wash dishes is not 

included. 

Source: Westat, 1987b. 
Table 16-17. Total Exposure Time of Painting Activity of Interior Painters (hours) 

Percentile Rankings for Duration of Painting Activity 

Mean (hrs) 

Types of Paint (hrs) Std. dev. 

Min. 10 25 50 75 90 95 Max. 

Latex 12.2 11.28 1 3 4 9 15 24 40 248 

Oil-based 10.68 15.56 1 1.6 3 6 10 21.6 65.6 72 

Wood Stains and Varnishes 8.57 10.85 1 1 2 4 9.3 24 40 42 

Source: Westat, 1987c. 
Table 16-18. Exposure Time of Interior Painting Activity/Occasion (hours) and Frequency of Occasions Spent Painting Per Year 

Types of Paint Duration of Frequency of 

Painting/Occasion Occasions Spent 

(hrs) Painting/Year Percentile Rankings for Frequency of Occasions Spent Painting 

Mean Median Mean Std. dev. Min 10 25 50 75 90 95 Max. 

Latex 2.97 3 4.16 5.54 1 1 2 3 4 9 10 62 

Oil-based 2.14 3 5.06 11.98 1 1 1 2 4 8 26 72 

Wood Stains and 2.15 2 4.02 4.89 1 1 1 2 4 9 20 20

 Varnishes 

Source: Westat, 1987c. 
Table 16-19. Amount of Paint Used by Interior Painters 

Percentile Rankings for Amount of Paint Used 

Median Mean Std. (gallons) 

Types of Paint (gallons) (gallons) dev. 

Min 10 25 50 75 90 95 Max. 

Latex 3.0 3.89 4.56 0.13 1 2 3 5 8 10 50 

Oil-based 2.0 2.55 3.03 0.13 0.25 0.5 2 3 7 12 12 

Wood Stains and 0.75 0.88 0.81 0.13 0.14 0.25 0.75 1 2 2 4.25

 Varnishes 

Source: Westat, 1987c. 
Table 16-20. Number of Respondents Using Cologne, Perfume, Aftershave or Other Fragrances at Specified Daily Frequencies 

Number of Times Used in a Day 

Population Group Total N 1-2 3-5 6-9 10+ DK 

Overall 2223 2100 113 4 2 4 

Gender 

Male 912 

Female 1311 

Age (Years) 

* 33 

5-11 26 

12-17 144 

18-64 1735 

> 64 285 

868 44 * * * 

1232 69 4 2 4 

. 

31 1 1 * * 

24 2 * * * 

133 9 * 1 1 

1635 93 3 1 3 

277 8 * * * 

Race 

White 1781 

Black 242 

Asian 30 

Some Others 38 

Hispanic 111 

Refused 21 

1684 91 4 * 2 

233 7 * 1 1 

30 * * * * 

35 3 * * * 

98 11 * 1 1 

20 1 * * * 

Hispanic 

No 2012 

Yes 182 

DK 11 

Refused 18 

1909 95 4 1 3 

165 15 * 1 1 

9 2 * * * 

17 1 * * * 

Employment 

* 157

Full Time 1195

Part Time 240

Not Employed 618

Refused 13

145 10 * 1 1 

1125 67 2 * 1 

228 11 * 1 * 

591 23 2 * 2 

11 2 * * * 

Education 

* 208

< High School 190

High School Graduate 739

< College 504

College Graduate 331

Post Graduate 251

194 12 * 1 1 

177 13 * * * 

704 32 2 * 1 

480 21 * 1 2 

308 21 2 * * 

237 14 * * * 

Census Region 

Northeast 459

Midwest 530

South 813

West 421

434 21 3 * 1 

502 25 1 * 2 

766 46 * 1 * 

398 21 * 1 1 

Day of Week 

Weekday 1480 1402 71 3 * 4 

Weekend 743 698 42 1 2 * 

Season 

Winter 604

Spring 588

Summer 568

Fall 463

574 26 1 1 2 

549 36 1 1 1 

535 31 2 * * 

442 20 * * 1 

Asthma 

No 2075 

Yes 143 

DK 5 

1959 106 4 2 4 

136 7 * * * 

5 * * * * 

Angina 

No 2161 

Yes 52 

DK 10 

2043 108 4 2 4 

47 5 * * * 

10 * * * * 

Bronchitis/emphysema 

No 2112 1994 108 4 2 4 

Yes 103 98 5 * * * 

DK 8 8 * * * * 

Note: * = Missing Data; DK = Don't Know; Refused = Respondents Refused to Answer; N = Number of Respondents. 

Source: Tsang and Klepeis, 1996. 
Table 16-21. Number of Respondents Using Any Aerosol Spray Product for Personal Care Item 

Such as Deodorant or Hair Spray at Specified Daily Frequencies 

Population Group Total N 1 2 3 

Number of Times Used in a Day 

4 5 6 7 10 10+ DK 

Overall 1491 1019 352 57 22 17 2 1 3 10 8 

Gender . Male 528 375 125 14 4 3 2 0 0 2 3 

Female 962 644 226 43 18 14 0 1 3 8 5 

Refused 1 0 1 0 0 0 0 0 0 0 0 

Age (years) 

0 27 14 8 1 2 1 0 0 0 0 1 

1-4 40 30 9 0 0 1 0 0 0 0 0 

5-11 75 57 14 1 1 1 1 0 0 0 0 

12-17 103 53 31 12 4 1 0 0 1 1 0 

18-64 1071 724 263 39 15 13 1 1 2 8 5 

> 64 175 141 27 4 0 0 0 0 0 1 2 

Race 

White 1232 855 285 47 17 8 2 0 3 10 5 

Black 131 84 32 5 3 5 0 0 0 0 2 

Asian 24 18 5 0 0 0 0 0 0 0 1 

Some Others 22 12 8 1 0 0 0 1 0 0 0 

Hispanic 

Refused 

73 

9 

45 

5 

19 

3 

4 

0 

1 

1 

4 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

Hispanic 

No 1359 937 316 49 20 13 2 1 3 10 8 

Yes 119 74 32 7 2 4 0 0 0 0 0 

DK 6 3 2 1 0 0 0 0 0 0 0 

Refused 7 5 2 0 0 0 0 0 0 0 0 

Employment 

0 210 137 52 11 4 3 1 0 1 1 0 

Full Time 714 492 171 24 11 5 1 1 1 4 4 

Part Time 152 99 35 7 0 5 0 0 0 4 2 

Not Employed 

Refused 

404 

11 

284 

7 

92 

2 

14 

1 

6 

1 

4 

0 

0 

0 

0 

0 

1 

0 

1 

0 

2 

0 

Education 

0 240 151 61 14 6 4 1 0 1 2 0 

< High School 

High School Graduate 

< College 

College Graduate 

Post Graduate 

128 

528 

311 

161 

123 

83 

365 

212 

115 

93 

37 

121 

77 

34 

22 

2 

23 

7 

8 

3 

1 

7 

3 

1 

4 

1 

5 

6 

1 

0 

0 

1 

0 

0 

0 

0 

0 

1 

0 

0 

0 

2 

0 

0 

0 

2 

1 

4 

1 

0 

2 

3 

1 

1 

1 

Census Region 

Northeast 292 201 70 8 8 1 0 0 0 1 3 

Midwest 340 227 85 14 4 3 1 0 1 3 2 

South 585 388 148 23 8 8 0 1 2 4 3 

West 274 203 49 12 2 5 1 0 0 2 0 

Day of Week 

Weekday 

Weekend 

994 

497 

695 

324 

220 

132 

35 

22 

17 

5 

12 

5 

1 

1 

0 

1 

1 

2 

7 

3 

6 

2 

Season 

Winter 381 264 86 15 5 4 0 0 0 4 3 

Spring 

Summer 

408 

400 

269 

282 

104 

86 

12 

21 

9 

5 

9 

2 

0 

1 

1 

0 

1 

0 

1 

1 

2 

2 

Fall 302 204 76 9 3 2 1 0 2 4 1 

Asthma 

No 1387 950 327 53 20 15 2 1 1 10 8 

Yes 100 66 24 4 2 2 0 0 2 0 0 

DK 4 3 1 0 0 0 0 0 0 0 0 

Angina 

No 1451 990 344 55 22 17 2 1 3 9 8 

Yes 35 26 7 1 0 0 0 0 0 1 0 

DK 5 3 1 1 0 0 0 0 0 0 0 

Bronchitis/emphysema 

No 1411 972 322 55 22 17 2 1 3 9 8 

Yes 74 44 29 1 0 0 0 0 0 0 0 

DK 6 3 1 1 0 0 0 0 0 1 0 

Note: * = Missing Data; "DK" = Don't Know; Refused = Respondents Refused To Answer; N= Sample Size 

Source: Tsang And Klepeis, 1996. 
Table 16-22. Number of Minutes Spent in Activities Working with or Being Near Freshly Applied Paints (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 276 0 0 1 2 15 60 121 121 121 121 121 121 

Gender Male 145 0 0 1 2 10 48 121 121 121 121 121 121 

Gender Female 131 0 0 1 3 15 120 121 121 121 121 121 121 

Age (years) 1-4 7 3 3 3 3 5 15 121 121 121 121 121 121 

Age (years) 5-11 12 5 5 5 15 20 45 120 120 121 121 121 121 

Age (years) 12-17 20 0 0 0.5 3 8 45 75 121 121 121 121 121 

Age (years) 18-64 212 0 0 1 2 11 60 121 121 121 121 121 121 

Age (years) > 64 20 0 0 0 2.5 17.5 90 121 121 121 121 121 121 

Race White 241 0 0 2 4 15 60 121 121 121 121 121 121 

Race Black 16 0 0 0 1 2.5 10 90 121 121 121 121 121 

Race Asian 3 20 20 20 20 20 30 60 60 60 60 60 60 

Race Some Others 2 10 10 10 10 10 20 30 30 30 30 30 30 

Race Hispanic 12 0 0 0 1 3.5 27.5 120.5 121 121 121 121 121 

Hispanic No 257 0 0 1 3 15 60 121 121 121 121 121 121 

Hispanic Yes 17 0 0 0 1 6 45 121 121 121 121 121 121 

Employment Full Time 145 0 1 2 3 10 60 121 121 121 121 121 121 

Employment Part Time 31 0 0 0 1 30 60 121 121 121 121 121 121 

Employment Not Employed 61 0 0 0 2 30 120 121 121 121 121 121 121 

Education < High School 13 0 0 0 1 5 45 121 121 121 121 121 121 

Education High School Graduate 74 0 1 1 5 20 120 121 121 121 121 121 121 

Education < College 72 0 0 2 2 12.5 105 121 121 121 121 121 121 

Education College Graduate 42 0 0 0 1 6 60 121 121 121 121 121 121 

Education Post Graduate 30 2 2 3 4.5 15 30 121 121 121 121 121 121 

Census Region Northeast 60 0 0 2 5 25 120 121 121 121 121 121 121 

Census Region Midwest 70 0 0 0 2 10 55 121 121 121 121 121 121 

Census Region South 90 0 0 1 2 10 47.5 121 121 121 121 121 121 

Census Region West 56 1 1 1 3 12.5 75 121 121 121 121 121 121 

Day of Week Weekday 222 0 0 1 2 15 60 121 121 121 121 121 121 

Day of Week Weekend 54 0 0 0 5 15 45 121 121 121 121 121 121 

Season Winter 67 0 1 2 3 15 60 121 121 121 121 121 121 

Season Spring 74 0 0 1 2 10 30 121 121 121 121 121 121 

Season Summer 76 0 0 0 2 13.5 90 121 121 121 121 121 121 

Season Fall 59 0 1 2 5 20 120 121 121 121 121 121 121 

Asthma No 257 0 0 1 2 15 60 121 121 121 121 121 121 

Asthma Yes 19 1 1 1 2 10 45 121 121 121 121 121 121 

Angina No 270 0 0 1 2 12 60 121 121 121 121 121 121 

Angina Yes 6 45 45 45 45 60 121 121 121 121 121 121 121 

Bronchitis/emphysema No 265 0 0 1 3 15 60 121 121 121 121 121 121 

Bronchitis/emphysema Yes 11 0 0 0 2 5 45 121 121 121 121 121 121 

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: Tsang and Klepeis, 1996. 
Table 16-23. Number of Minutes Spent in Activities Working with or Near Household Cleaning

 Agents Such as Scouring Powders or Ammonia (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 905 0 0 0 1 4 10 20 60 121 121 121 121 

Gender Male 278 0 0 1 2 3 10 20 60 121 121 121 121 

Gender Female 627 0 0 0 1 4 10 20 60 120 121 121 121 

Age (years) 1-4 21 0 0 0 0 5 10 15 20 30 121 121 121 

Age (years) 5-11 26 1 1 2 2 3 5 15 30 30 30 30 30 

Age (years) 12-17 41 0 0 0 0 2 5 10 40 60 60 60 60 

Age (years) 18-64 672 0 0 1 2 5 10 20 60 121 121 121 121 

Age (years) > 64 127 0 0 0 1 3 5 15 30 60 120 121 121 

Race White 721 0 0 1 1 4 10 20 60 121 121 121 121 

Race Black 112 0 0 0 1 2 5 12 30 90 121 121 121 

Race Asian 16 0 0 0 5 5 10 15 20 30 30 30 30 

Race Some Others 19 2 2 2 3 5 10 20 30 60 60 60 60 

Race Hispanic 30 0 0 1 2.5 10 15 30 60 90 121 121 121 

Hispanic No 838 0 0 0 1 3 10 20 60 121 121 121 121 

Hispanic Yes 58 0 0 1 2 5 12.5 30 60 120 121 121 121 

Employment Full Time 422 0 0 1 1 4 10 30 60 121 121 121 121 

Employment Part Time 98 0 0 1 2 5 10 20 60 121 121 121 121 

Employment Not Employed 296 0 0 0 2 3 10 15 60 120 121 121 121 

Education < High School 76 0 0 1 2 2 12.5 30 120 121 121 121 121 

Education High School Graduate 304 0 0 0 2 5 10 20 60 120 121 121 121 

Education < College 204 0 0 0 1 4.5 10 30 120 121 121 121 121 

Education College Graduate 114 0 1 1 2 5 10 20 60 90 121 121 121 

Education Post Graduate 109 0 0 1 1 3 5 15 30 60 121 121 121 

Census Region Northeast 207 0 0 0 1 3 5 15 45 120 121 121 121 

Census Region Midwest 180 0 0 0 1 5 10 30 75 121 121 121 121 

Census Region South 309 0 0 1 2 4 10 20 60 120 121 121 121 

Census Region West 209 0 0 1 1 4 10 20 60 121 121 121 121 

Day of Week Weekday 580 0 0 0 1 3 10 20 60 121 121 121 121 

Day of Week Weekend 325 0 0 1 2 5 10 20 60 90 121 121 121 

Season Winter 240 0 0 0 2 3 10 20 75 121 121 121 121 

Season Spring 220 0 0 0 1 3 10 17.5 52.5 104 121 121 121 

Season Summer 244 0 0 0 2 4 10 20 30 60 121 121 121 

Season Fall 201 0 0 1 2 5 10 30 90 121 121 121 121 

Asthma No 826 0 0 0 1 3 10 20 60 120 121 121 121 

Asthma Yes 79 0 0 1 2 5 10 30 120 121 121 121 121 

Angina No 868 0 0 0 1 4 10 20 60 121 121 121 121 

Angina Yes 33 0 0 2 2 5 5 30 120 121 121 121 121 

Bronchitis/emphysema No 843 0 0 0 1 4 10 20 60 120 121 121 121 

Bronchitis/emphysema Yes 60 0 0 1 2 3.5 10 32.5 120.5 121 121 121 121 

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: Tsang and Klepeis, 1996. 
Table 16-24. Number of Minutes Spent in Activities (at home or elsewhere) Working with

 or Near Floorwax, Furniture Wax or Shoe Polish (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 325 0 0 2 2 5 10 30 60 121 121 121 121 

Gender Male 96 0 0 1 2 5 11 30 121 121 121 121 121 

Gender Female 229 0 0 2 3 5 10 30 60 121 121 121 121 

Age (years) 1-4 13 0 0 0 5 10 15 20 60 121 121 121 121 

Age (years) 5-11 21 0 0 2 2 3 5 10 35 60 120 120 120 

Age (years) 12-17 15 0 0 0 1 2 10 25 45 121 121 121 121 

Age (years) 18-64 238 0 0 2 3 5 15 30 120 121 121 121 121 

Age (years) > 64 34 0 0 0 2 5 10 20 35 121 121 121 121 

Race White 267 0 0 2 2 5 10 30 60 121 121 121 121 

Race Black 32 2 2 2 5 5 15 30 60 121 121 121 121 

Race Asian 1 4 4 4 4 4 4 4 4 4 4 4 4 

Race Some Others 6 0 0 0 0 2 22.5 60 121 121 121 121 121 

Race Hispanic 18 1 1 1 4 5 12.5 30 120 121 121 121 121 

Hispanic No 291 0 0 2 2 5 10 30 60 121 121 121 121 

Hispanic Yes 31 1 1 4 5 5 10 30 90 120 121 121 121 

Employment Full Time 150 0 0.5 2 3 5 15 30 121 121 121 121 121 

Employment Part Time 32 3 3 5 5 10 15 30 60 121 121 121 121 

Employment Not Employed 92 0 0 1 2 5 10 20 60 120 121 121 121 

Education < High School 26 2 2 3 5 5 10 15 60 60 60 60 60 

Education High School Graduate 115 0 0 2 3 5 12 30 120 121 121 121 121 

Education < College 70 0 1 2 3 10 15 30 75 121 121 121 121 

Education College Graduate 29 2 2 3 5 7 30 60 121 121 121 121 121 

Education Post Graduate 31 0 0 0 2 4 10 30 60 121 121 121 121 

Census Region Northeast 77 0 0 2 3 5 10 30 60 121 121 121 121 

Census Region Midwest 70 0 0 1 2 5 10 25 90 121 121 121 121 

Census Region South 125 0 0 2 2 5 10 30 120 121 121 121 121 

Census Region West 53 0 0 1 3 5 15 30 120 121 121 121 121 

Day of Week Weekday 210 0 0 2 2 5 10 30 120 121 121 121 121 

Day of Week Weekend 115 0 0 2 3 5 10 30 60 120 121 121 121 

Season Winter 92 0 1 2 4 7 13.5 30 121 121 121 121 121 

Season Spring 78 0 0 1 2 5 15 30 60 121 121 121 121 

Season Summer 81 0 0 2 2 5 15 30 120 121 121 121 121 

Season Fall 74 0 0 0 2 5 10 15 60 121 121 121 121 

Asthma No 296 0 0 2 2 5 10 30 60 121 121 121 121 

Asthma Yes 29 0 0 0 2 5 15 30 121 121 121 121 121 

Angina No 312 0 0 2 2 5 10 30 60 121 121 121 121 

Angina Yes 12 0 0 0 2 4 10 12.5 30 121 121 121 121 

Bronchitis/emphysema No 302 0 0 2 2 5 10 30 90 121 121 121 121 

Bronchitis/emphysema Yes 22 0 0 2 2 5 10 15 20 20 121 121 121 

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: Tsang and Klepeis, 1996. 
Table 16-25. Number of Minutes Spent in Activities Working with or Being Near Glue (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 294 0 0 0 1 5 15 60 121 121 121 121 121 

Gender Male 151 0 0 0 2 5 15 70 121 121 121 121 121 

Gender Female 143 0 0 0 1 5 15 30 121 121 121 121 121 

Age (years) 1-4 6 0 0 0 0 30 30 30 50 50 50 50 50 

Age (years) 5-11 36 2 2 3 5 5 12.5 25 30 60 120 120 120 

Age (years) 12-17 34 0 0 1 2 5 10 30 30 60 120 120 120 

Age (years) 18-64 207 0 0 0 1 5 20 90 121 121 121 121 121 

Age (years) > 64 10 0 0 0 0 0 3.5 60 120.5 121 121 121 121 

Race White 241 0 0 0 1 5 15 60 121 121 121 121 121 

Race Black 28 0 0 0 2 5 12.5 45 121 121 121 121 121 

Race Asian 4 10 10 10 10 12.5 17.5 40 60 60 60 60 60 

Race Some Others 7 1 1 1 1 3 30 90 120 120 120 120 120 

Race Hispanic 12 5 5 5 5 5 27.5 90 121 121 121 121 121 

Hispanic No 260 0 0 0 1 5 15 60 121 121 121 121 121 

Hispanic Yes 27 3 3 5 5 5 30 120 121 121 121 121 121 

Employment Full Time 150 0 0 0 1 5 20 120 121 121 121 121 121 

Employment Part Time 24 1 1 2 3 10 27.5 90 121 121 121 121 121 

Employment Not Employed 46 0 0 0 0 2 10 30 121 121 121 121 121 

Education < High School 11 0 0 0 0 1 5 10 60 121 121 121 121 

Education High School Graduate 69 0 0 0 1 5 20 90 121 121 121 121 121 

Education < College 66 0 0 0 1 5 27.5 121 121 121 121 121 121 

Education College Graduate 37 0 0 0 1 5 15 30 121 121 121 121 121 

Education Post Graduate 32 0 0 0 1 5 15 60 121 121 121 121 121 

Census Region Northeast 55 0 0 0 1 5 20 60 121 121 121 121 121 

Census Region Midwest 71 0 0 1 2 5 15 60 121 121 121 121 121 

Census Region South 98 0 0 0 1 5 15 60 121 121 121 121 121 

Census Region West 70 0 0 0 1 5 15 60 121 121 121 121 121 

Day of Week Weekday 228 0 0 0 1 5 15 60 121 121 121 121 121 

Day of Week Weekend 66 0 0 0 1 5 15 60 121 121 121 121 121 

Season Winter 85 0 0 0 2 5 15 45 121 121 121 121 121 

Season Spring 74 0 0 0 2 5 10 30 121 121 121 121 121 

Season Summer 66 0 0 0 1 10 20 121 121 121 121 121 121 

Season Fall 69 0 0 0 1 5 15 60 121 121 121 121 121 

Asthma No 266 0 0 0 1 5 15 60 121 121 121 121 121 

Asthma Yes 28 0 0 0 1 5 17.5 40 121 121 121 121 121 

Angina No 290 0 0 0 1 5 15 60 121 121 121 121 121 

Angina Yes 3 1 1 1 1 1 121 121 121 121 121 121 121 

Bronchitis/emphysema No 283 0 0 0 1 5 15 60 121 121 121 121 121 

Bronchitis/emphysema Yes 11 1 1 1 1 2 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: Tsang and Klepeis, 1996. 
Table 16-26. Number of Minutes Spent in Activities Working with or Near Solvents, Fumes or Strong Smelling Chemicals (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 495 0 0 0 2 5 20 121 121 121 121 121 121 

Gender Male 258 0 0 1 2 5 30 121 121 121 121 121 121 

Gender Female 237 0 0 0 1 5 15 90 121 121 121 121 121 

Age (years) 1-4 7 0 0 0 0 1 5 60 121 121 121 121 121 

Age (years) 5-11 16 0 0 0 2 5 5 17.5 45 70 70 70 70 

Age (years) 12-17 38 0 0 0 0 5 10 60 121 121 121 121 121 

Age (years) 18-64 407 0 0 1 2 5 30 121 121 121 121 121 121 

Age (years) > 64 21 0 0 0 0 2 5 15 121 121 121 121 121 

Race White 413 0 0 0 2 5 20 121 121 121 121 121 121 

Race Black 40 0 0 1 3.5 9 60 121 121 121 121 121 121 

Race Asian 8 5 5 5 5 10 37.5 120.5 121 121 121 121 121 

Race Some Others 8 2 2 2 2 2.5 5 60 121 121 121 121 121 

Race Hispanic 23 0 0 0 0 5 30 121 121 121 121 121 121 

Hispanic No 449 0 0 0 2 5 20 121 121 121 121 121 121 

Hispanic Yes 41 0 0 0 0 5 20 121 121 121 121 121 121 

Employment Full Time 299 0 0 1 2 10 30 121 121 121 121 121 121 

Employment Part Time 44 0 0 2 2 5 22.5 121 121 121 121 121 121 

Employment Not Employed 91 0 0 0 0 2 10 60 121 121 121 121 121 

Education < High School 35 0 0 1 2 5 15 121 121 121 121 121 121 

Education High School Graduate 138 0 0 1 2 5 30 121 121 121 121 121 121 

Education < College 128 0 0 1 2 5 30 121 121 121 121 121 121 

Education College Graduate 69 0 0 0 1 5 30 121 121 121 121 121 121 

Education Post Graduate 60 0 0 0 1.5 5 27.5 121 121 121 121 121 121 

Census Region Northeast 101 0 0 2 2 5 20 121 121 121 121 121 121 

Census Region Midwest 122 0 0 0 2 5 30 121 121 121 121 121 121 

Census Region South 165 0 0 0 2 5 20 121 121 121 121 121 121 

Census Region West 107 0 0 0 2 5 20 121 121 121 121 121 121 

Day of Week Weekday 362 0 0 0 2 5 30 121 121 121 121 121 121 

Day of Week Weekend 133 0 0 0 2 5 15 90 121 121 121 121 121 

Season Winter 128 0 0 0 2 5 20 95 121 121 121 121 121 

Season Spring 127 0 0 0 1 5 20 121 121 121 121 121 121 

Season Summer 149 0 0 1 2 5 21 121 121 121 121 121 121 

Season Fall 91 0 0 1 2 5 30 121 121 121 121 121 121 

Asthma No 445 0 0 0 2 5 20 121 121 121 121 121 121 

Asthma Yes 50 0 0 1 1 5 15 121 121 121 121 121 121 

Angina No 489 0 0 0 2 5 20 121 121 121 121 121 121 

Angina Yes 6 0 0 0 0 2 15 121 121 121 121 121 121 

Bronchitis/emphysema No 469 0 0 0 2 5 20 121 121 121 121 121 121 

Bronchitis/emphysema Yes 26 2 2 2 2 5 17.5 60 121 121 121 121 121 

Note: A Value of "121" for Number of Minutes Signifies That More than 120 Minutes Were Spent; N = Doer Sample Size; Percentiles Are 

the Percentage of Doers below or Equal to a Given Number of Minutes. 

Source: Tsang and Klepeis, 1996. 
Table 16-27. Number of Minutes Spent in Activities Working with or Near Stain or Spot Removers (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 109 0 0 0 0 2 5 15 60 121 121 121 121 

Gender Male 42 0 0 0 0 3 5 60 121 121 121 121 121 

Gender Female 67 0 0 0 0 2 5 10 20 30 60 120 120 

Age (years) 1-4 3 0 0 0 0 0 0 3 3 3 3 3 3 

Age (years) 5-11 3 3 3 3 3 3 5 5 5 5 5 5 5 

Age (years) 12-17 7 0 0 0 0 5 15 35 60 60 60 60 60 

Age (years) 18-64 87 0 0 0 0 2 5 15 60 121 121 121 121 

Age (years) > 64 9 0 0 0 0 2 3 15 121 121 121 121 121 

Race White 88 0 0 0 0 2 5 15 60 121 121 121 121 

Race Black 9 0 0 0 0 5 5 6 121 121 121 121 121 

Race Asian 2 5 5 5 5 5 7.5 10 10 10 10 10 10 

Race Some Others 3 0 0 0 0 0 2 3 3 3 3 3 3 

Race Hispanic 7 1 1 1 1 2 5 30 35 35 35 35 35 

Hispanic No 97 0 0 0 0 2 5 15 60 121 121 121 121 

Hispanic Yes 12 0 0 0 1 2 3 22.5 35 121 121 121 121 

Employment Full Time 62 0 0 0 0 2 5 15 120 121 121 121 121 

Employment Part Time 8 0 0 0 0 3 5 12.5 20 20 20 20 20 

Employment Not Employed 25 0 0 0 0 2 4 15 60 121 121 121 121 

Education < High School 6 3 3 3 3 3 20 30 60 60 60 60 60 

Education High School Graduate 34 0 0 0 0 1 4 10 120 121 121 121 121 

Education < College 22 0 0 0 1 3 5 15 20 121 121 121 121 

Education College Graduate 16 0 0 0 1 3 5 12.5 60 121 121 121 121 

Education Post Graduate 16 0 0 0 0 1 5 15 20 121 121 121 121 

Census Region Northeast 21 0 0 1 1 3 5 10 121 121 121 121 121 

Census Region Midwest 25 0 0 0 0 2 5 15 60 60 121 121 121 

Census Region South 38 0 0 0 0 2 5 15 60 120 121 121 121 

Census Region West 25 0 0 0 0 2 5 25 60 60 121 121 121 

Day of Week Weekday 75 0 0 0 0 2 5 15 120 121 121 121 121 

Day of Week Weekend 34 0 0 0 0 2 5 15 60 60 120 120 120 

Season Winter 26 0 0 0 0 2 5 15 60 120 120 120 120 

Season Spring 30 0 0 0 0.5 2 5 15 32.5 121 121 121 121 

Season Summer 37 0 0 0 0 2 5 20 121 121 121 121 121 

Season Fall 16 0 0 0 1 5 5 15 60 121 121 121 121 

Asthma No 100 0 0 0 0 2 5 15 60 120.5 121 121 121 

Asthma Yes 9 0 0 0 0 2 5 6 121 121 121 121 121 

Angina No 109 0 0 0 0 2 5 15 60 121 121 121 121 

Bronchitis/emphysema No 105 0 0 0 0 2 5 15 60 121 121 121 121 

Bronchitis/emphysema Yes 4 0 0 0 0 0.5 1.5 8.5 15 15 15 15 15 

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: Tsang and Klepeis, 1996. 
Table 16-28. Number of Minutes Spent in Activities Working with or Near Gasoline or 

Diesel-powered Equipment, Besides Automobiles (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 390 0 0 1 3 10 60 121 121 121 121 121 121 

Gender Male 271 0 0 1 3 15 60 121 121 121 121 121 121 

Gender Female 119 1 1 1 2 8 30 120 121 121 121 121 121 

Age (years) 1-4 14 0 0 0 1 5 22.5 120 121 121 121 121 121 

Age (years) 5-11 12 1 1 1 3 7.5 25 50 60 60 60 60 60 

Age (years) 12-17 25 2 2 5 5 13 35 120 121 121 121 121 121 

Age (years) 18-64 312 0 0 1 3 15 60 121 121 121 121 121 121 

Age (years) > 64 26 2 2 2 3 10 25 90 121 121 121 121 121 

Race White 355 0 1 1 3 15 60 121 121 121 121 121 121 

Race Black 15 1 1 1 1 2 15 121 121 121 121 121 121 

Race Asian 8 0 0 0 0 5 11.5 17.5 90 90 90 90 90 

Race Some Others 2 1 1 1 1 1 23 45 45 45 45 45 45 

Race Hispanic 8 3 3 3 3 10 105.5 121 121 121 121 121 121 

Hispanic No 367 0 0 1 3 10 60 121 121 121 121 121 121 

Hispanic Yes 19 1 1 1 2 5 30 121 121 121 121 121 121 

Employment Full Time 237 0 0 1 2 20 90 121 121 121 121 121 121 

Employment Part Time 33 1 1 2 2 10 45 121 121 121 121 121 121 

Employment Not Employed 66 0 0 2 4 10 30 121 121 121 121 121 121 

Education < High School 33 0 0 1 2 6 60 121 121 121 121 121 121 

Education High School Graduate 135 1 1 2 5 20 90 121 121 121 121 121 121 

Education < College 89 0 1 2 3 15 60 121 121 121 121 121 121 

Education College Graduate 48 0 0 0 1 10 60 120 121 121 121 121 121 

Education Post Graduate 30 0 0 1 1.5 10 30 120 121 121 121 121 121 

Census Region Northeast 57 0 1 1 1 10 60 121 121 121 121 121 121 

Census Region Midwest 117 0 0 1 5 15 90 121 121 121 121 121 121 

Census Region South 151 0 1 2 3 10 60 121 121 121 121 121 121 

Census Region West 65 0 0 1 3 10 45 121 121 121 121 121 121 

Day of Week Weekday 278 0 0 1 2 10 60 121 121 121 121 121 121 

Day of Week Weekend 112 1 1 2 5 15 45 120 121 121 121 121 121 

Season Winter 97 0 0 1 2 10 60 121 121 121 121 121 121 

Season Spring 110 0 1 1 3 10 60 121 121 121 121 121 121 

Season Summer 119 0 1 2 5 15 60 121 121 121 121 121 121 

Season Fall 64 0 1 1 2 5 30 121 121 121 121 121 121 

Asthma No 361 0 0 1 3 10 60 121 121 121 121 121 121 

Asthma Yes 28 2 2 3 3 30 120.5 121 121 121 121 121 121 

Angina No 381 0 0 1 3 10 60 121 121 121 121 121 121 

Angina Yes 7 15 15 15 15 20 45 121 121 121 121 121 121 

Bronchitis/emphysema No 368 0 0 1 3 15 60 121 121 121 121 121 121 

Bronchitis/emphysema Yes 21 2 2 3 3 5 45 121 121 121 121 121 121 

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: Tsang and Klepeis, 1996. 
Table 16-29. Number of Minutes Spent Using Any Microwave Oven (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 2298 0 0 1 1 3 5 10 15 30 40 60 121 

Gender Male 948 0 0 1 1 2 5 10 15 30 40 67 121 

Gender Female 1350 0 0 1 1.5 3 5 10 20 30 42.5 60 121 

Age (years) 5-11 62 0 0 0 1 1 2 5 10 15 20 30 30 

Age (years) 12-17 141 0 0 0 1 2 3 5 10 15 30 30 60 

Age (years) 18-64 1686 0 0 1 2 3 5 10 15 25 45 60 121 

Age (years) > 64 375 0 0 1 2 3 5 10 20 30 60 60 70 

Race White 1953 0 0 1 2 3 5 10 16 30 40 60 121 

Race Black 182 0 0 1 1 2 3 6 15 20 30 30 121 

Race Asian 38 0 0 1 1 3 5 10 20 30 60 60 60 

Race Some Others 29 0 0 2 2 3 5 10 30 30 50 50 50 

Race Hispanic 74 0 0 0 1 2 3 10 15 45 120 121 121 

Hispanic No 2128 0 0 1 1 3 5 10 15 30 35 60 121 

Hispanic Yes 139 0 0 0 1 2 5 10 20 30 120 120 121 

Employment Full Time 1114 0 0 1 1 3 5 10 15 30 34 60 121 

Employment Part Time 237 0 0 1 1 3 5 10 20 30 60 120 121 

Employment Not Employed 734 0 0 1 2 3 5 10 20 30 45 60 120 

Education < High School 190 0 0 0 1.5 3 5 10 20 33 60 121 121 

Education High School Graduate 717 0 0 1 2 3 5 10 20 30 45 60 121 

Education < College 518 0 0 1 2 3 5 10 18 30 60 120 121 

Education College Graduate 347 0 0 1 2 3 5 10 15 25 30 60 70 

Education Post Graduate 288 0 0 1 1 3 5 10 15 20 30 30 90 

Census Region Northeast 420 0 0 1 2 2 5 10 20 30 60 60 121 

Census Region Midwest 545 0 0 1 1 3 5 10 15 30 35 60 121 

Census Region South 831 0 0 1 2 3 5 10 16 30 45 60 121 

Census Region West 502 0 0 1 1 2 5 10 15 20 30 60 121 

Day of Week Weekday 1567 0 0 1 1 3 5 10 15 25 30 60 121 

Day of Week Weekend 731 0 0 1 1 2 5 10 20 30 50 120 121 

Season Winter 657 0 0 1 2 2 5 10 15 30 40 67 121 

Season Spring 577 0 0 1 2 3 5 10 20 30 45 60 120 

Season Summer 565 0 0 0 1 2 5 10 15 20 30 60 120 

Season Fall 499 0 0 1 1 2 5 10 20 30 45 120 121 

Asthma No 2109 0 0 1 1 2 5 10 15 30 40 60 121 

Asthma Yes 180 0 0 1 2 3 5 10 19 30 45 60 121 

Angina No 2212 0 0 1 1 2 5 10 15 30 40 60 121 

Angina Yes 72 0 0 1 2 3 6 10 15 30 45 60 60 

Bronchitis/emphysema No 2164 0 0 1 1 2 5 10 15 30 40 60 121 

Bronchitis/emphysema Yes 124 0 0 1 1 3 5 10 30 30 60 120 121 

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: Tsang and Klepeis, 1996. 
Table 16-30. Number of Respondents Using a Humidifier at Home 

Frequency 

Almost 

Total N Every 3-5 Times a 1-2 Times a 1-2 Times a DK 

Day Week Week Month 

Overall 1047 300 121 107 495 24 

Gender 

Male 455 

Female 591 

Refused 1 

135 53 48 208 11 

165 68 59 286 13 

* * * 1 * 

Age (years) 

* 16

1-4 111

5-11 88

12-17 83

18-64 629

> 64 120

3 1 3 7 2 

33 16 7 53 2 

18 10 12 46 2 

21 7 5 49 1 

183 77 70 287 12 

42 10 10 53 5 

Race 

White 879 

Black 93 

Asian 18 

Some Others 20 

Hispanic 30 

Refused 7 

268 98 79 414 20 

24 10 15 42 2 

3 2 1 11 1 

1 3 4 12 * 

2 7 8 13 * 

2 1 * 3 1 

Hispanic 

No 978 

Yes 60 

DK 5 

Refused 4 

286 109 95 466 22 

11 11 12 25 1 

3 * * 2 * 

* 1 0 2 1 

Employment 

* 279

Full Time 416

Part Time 88

Not Employed 256

Refused 8

70 32 25 147 5 

124 43 44 194 11 

22 14 9 43 * 

82 29 29 109 7 

2 3 * 2 1 

Education 

* 303

< High School 86

High School Graduate 251

< College 188

College Graduate 119

Post Graduate 100

74 36 27 160 6 

27 15 14 29 1 

85 27 28 104 7 

53 16 17 97 5 

32 17 13 56 1 

29 10 8 49 4 

Census Region 

Northeast 273

Midwest 326

South 302

West 146

84 26 28 132 3 

102 37 32 142 13 

83 42 31 141 5 

31 16 16 80 3 

Day of Week 

Weekday 698 196 83 70 335 14 

Weekend 349 104 38 37 160 10 

Season 

Winter 320

Spring 257

Summer 269

Fall 201

135 46 34 98 7 

58 23 29 144 3 

56 27 20 155 11 

51 25 24 98 3 

Asthma 

No 948 

Yes 92 

DK 7 

272 110 95 448 23 

27 9 10 45 1 

1 2 2 2 * 

Angina 

No 1015 

Yes 24 

DK 8 

290 116 103 482 24 

8 4 3 9 * 

2 1 1 4 * 

Bronchitis/emphysema 

No 994 278 117 102 473 24 

Yes 48 21 3 4 20 * 

DK 5 1 1 1 2 * 

Note: * = Missing Data; DK= Don't Know; Refused = Respondent Refused to Answer; N = Number of Respondents 

Source: Tsang and Klepeis, 1996. 
Table 16-31. Number of Respondents Indicating that Pesticides Were Applied by the Professional at Home 

to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies 

Total N Number of Times Over a 6-month Period 

Pesticides Were Applied by Professionals 

None 1-2 3-5 6-9 10+ DK 

Overall 1946 1057 562 134 150 20 23 

Gender 

Male 897 

Female 1048 

Refused 1 

498 248 64 64 11 12 

558 314 70 86 9 11 

1 * * * * * 

Age (years 

* 33

1-4 113

5-11 150

12-17 143

18-64 1264

> 64 243

17 8 4 4 * * 

60 35 11 6 1 * 

84 37 10 18 1 * 

90 40 5 6 * 2 

660 387 89 97 15 16 

146 55 15 19 3 5 

Race 

White 1532 

Black 231 

Asian 24 

Some Others 38 

Hispanic 100 

Refused 21 

856 429 98 117 14 18 

107 78 20 17 4 5 

13 10 1 * * * 

24 8 4 2 * * 

45 33 10 11 1 * 

12 4 1 3 1 * 

Hispanic 

No 1750 

Yes 172 

DK 8 

Refused 16 

960 499 121 130 19 21 

83 56 12 18 1 2 

5 3 * * * * 

9 4 1 2 * * 

Employment 

* 398

Full Time 855

Part Time 163

Not Employed 512

Refused 18

229 111 24 30 2 2 

463 252 59 60 11 10 

84 50 14 12 2 1 

272 145 35 46 5 9 

9 4 2 2 * 1 

Education 

* 436

< High School 137

High School Graduate 483

< College 416

College Graduate 272

Post Graduate 202

246 122 27 35 2 4 

80 31 11 10 1 4 

265 140 26 38 9 5 

218 131 28 29 4 6 

137 87 25 20 2 1 

111 51 17 18 2 3 

Census Region 

Northeast 335

Midwest 318

South 875

West 418

201 85 2 22 3 4 

202 84 17 13 * 2 

404 298 63 86 11 13 

250 95 34 29 6 4 

Day of Week 

Weekday 1303 702 374 91 105 16 15 

Weekend 643 355 188 43 45 4 8 

Season 

Winter 466

Spring 449

Summer 584

Fall 447

247 129 29 46 9 6 

240 128 30 43 3 5 

324 172 40 34 6 8 

246 133 35 27 2 4 

Asthma 

No 1766 

Yes 167 

DK 13 

969 509 121 129 16 22 

80 50 13 19 4 1 

8 3 * 2 * * 

Angina 

No 1880 

Yes 53 

DK 13 

1019 549 131 141 19 21 

30 10 3 7 1 2 

8 3 * 2 * * 

Bronchitis/emphysema 

No 1833 1004 524 127 140 18 20 

Yes 101 46 36 7 8 1 3 

DK 12 7 2 * 2 1 * 

Note: * = Missing Data; DK= Don't know; Refused = Respondent Refused to Answer; N = Number of Respondents 

Source: Tsang and Klepeis, 1996. 
Table 16-32. Number of Respondents Reporting Pesticides Applied by the Consumer at Home 

To Eradicate Insects, Rodents, or Other Pests at Specified Frequencies 

Total N Number of Times Over a 6-month 

Period Pesticides Applied by Resident 

None 1-2 3-5 6-9 10+ DK 

Overall 1946 721 754 286 73 83 29 

Gender 

Male 897 

Female 1048 

Refused 1 

318 367 135 31 35 11 

403 386 151 42 48 18 

* 1 * * * * 

Age (years) 

* 33

1-4 113

5-11 150

12-17 143

18-64 1264

> 64 243

13 12 3 1 4 * 

46 46 15 3 3 * 

50 70 24 1 4 1 

45 64 21 5 8 * 

473 477 192 48 55 19 

94 85 31 15 9 9 

Race 

White 1532 

Black 231 

Asian 24 

Some Others 38 

Hispanic 100 

Refused 21 

574 600 227 55 50 26 

81 77 36 10 25 2 

4 15 3 1 1 * 

11 12 11 1 2 1 

41 42 9 5 3 * 

10 8 * 1 2 * 

Hispanic 

No 1750 

Yes 172 

DK 8 

Refused 16 

647 677 258 63 76 29 

66 67 26 10 3 * 

2 3 1 * 2 * 

6 7 1 * 2 * 

Employment 

* 398

Full Time 855

Part Time 163

Not Employed 512

Refused 18

139 176 59 9 14 1 

298 342 131 37 35 12 

67 66 20 4 5 1 

209 163 76 23 27 14 

8 7 * * 2 1 

Education 

* 436

< High School 137

High School Graduate 483

< College 416

College Graduate 272

Post Graduate 202

157 189 62 10 17 1 

44 50 19 4 14 6 

184 196 53 21 18 11 

157 158 63 18 16 4 

97 97 53 9 12 4 

82 64 36 11 6 3 

Census Region 

Northeast 335

Midwest 318

South 875

West 418

112 131 56 12 19 5 

108 145 35 12 12 6 

363 316 119 30 37 10 

138 162 76 19 15 8 

Day of Week 

Weekday 1303 485 503 186 44 66 19 

Weekend 643 236 251 100 29 17 10 

Season 

Winter 466

Spring 449

Summer 584

Fall 447

190 153 75 18 21 9 

170 192 51 15 16 5 

204 233 89 21 27 10 

157 176 71 19 19 5 

Asthma 

No 1766 

Yes 167 

DK 13 

643 695 261 70 70 27 

73 54 25 3 11 1 

5 5 * * 2 1 

Angina 

No 1880 

Yes 53 

DK 13 

696 731 276 70 80 27 

21 19 8 3 1 1 

4 4 2 0 2 1 

Bronchitis/emphysema 

No 1833 675 715 272 72 71 28 

Yes 101 41 35 14 1 10 * 

DK 12 5 4 * * 2 1 

Note: * = Missing Data; DK= Don't know; Refused = Respondent Refused to Answer; N = Number of Respondents 

Source: Tsang and Klepeis, 1996. 
Table 16-33. Number of Minutes Spent in Activities Working with or Near Pesticides, Including Bug Sprays or Bug Strips (minutes/day) 

Percentiles 

Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 

Overall 257 0 0 0 0 2 10 60 121 121 121 121 121 

Gender Male 121 0 0 1 1 2 10 90 121 121 121 121 121 

Gender Female 136 0 0 0 2 0 35 121 121 121 121 121 

Age (years) 1-4 6 1 1 1 1 3 10 15 20 20 20 20 20 

Age (years) 5-11 16 0 0 0 0 1.5 7.5 30 121 121 121 121 121 

Age (years) 12-17 10 0 0 0 0 2 2.5 40 121 121 121 121 121 

Age (years) 18-64 190 0 0 0 1 2 10 88 121 121 121 121 121 

Age (years) > 64 31 0 0 0 0 2 5 15 60 121 121 121 121 

Race White 199 0 0 0 1 2 10 60 121 121 121 121 121 

Race Black 36 0 0 0 0 1 3 20 121 121 121 121 121 

Race Asian 2 5 5 5 5 5 7.5 10 10 10 10 10 10 

Race Some Others 4 0 0 0 0 1.5 6.5 10 10 10 10 10 10 

Race Hispanic 15 0 0 0 0 2 20 121 121 121 121 121 121 

Hispanic No 231 0 0 0 0 2 10 60 121 121 121 121 121 

Hispanic Yes 25 0 0 0 1 5 20 121 121 121 121 121 121 

Employment Full Time 124 0 0 0 1 2 10 120.5 121 121 121 121 121 

Employment Part Time 26 0 0 0 1 2 5 60 121 121 121 121 121 

Employment Not Employed 75 0 0 0 0 2 5 30 121 121 121 121 121 

Education < High School 20 1 1 1 1 2.5 22.5 105.5 121 121 121 121 121 

Education High School Graduate 87 0 0 0 0 2 10 45 121 121 121 121 121 

Education < College 56 0 0 0 1 2 10 89 121 121 121 121 121 

Education College Graduate 29 0 0 0 0 1 10 90 121 121 121 121 121 

Education Post Graduate 29 0 0 0 0 3 10 30 121 121 121 121 121 

Census Region Northeast 45 0 0 1 2 5 10 88 121 121 121 121 121 

Census Region Midwest 51 0 0 0 0 2 10 121 121 121 121 121 121 

Census Region South 106 0 0 0 0 2 5 30 121 121 121 121 121 

Census Region West 55 0 0 0 1 2 10 45 121 121 121 121 121 

Day of Week Weekday 183 0 0 0 0 2 10 60 121 121 121 121 121 

Day of Week Weekend 74 0 0 0 1 3 10 30 121 121 121 121 121 

Season Winter 39 0 0 0 0 2 5 90 121 121 121 121 121 

Season Spring 78 0 0 0 0 2 10 60 121 121 121 121 121 

Season Summer 105 0 0 0 1 2 10 60 121 121 121 121 121 

Season Fall 35 0 0 0 0 1 10 60 121 121 121 121 121 

Asthma No 231 0 0 0 1 2 10 60 121 121 121 121 121 

Asthma Yes 24 0 0 0 0 1 5 90.5 121 121 121 121 121 

Angina No 244 0 0 0 0 2 10 60 121 121 121 121 121 

Angina Yes 8 1 1 1 1 2 5 75.5 121 121 121 121 121 

Bronchitis/emphysema No 240 0 0 0 0 2 10 60 121 121 121 121 121 

Bronchitis/emphysema Yes 14 1 1 1 2 2 5 30 121 121 121 121 121 

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: Tsang and Klepeis, 1996. 
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Table 16-34. Amount and Frequency of Use of Various Cosmetic and Baby Products 

Average Frequency of Use Upper 90th Percentile Frequency of Use 

Amount of (per day) (per day) 

Product Type Product Per a Survey Type Survey Type Application

(grams) b Market

Cosmetic Research

CTFA Co. Bureau c

Market 

Cosmetic Research 

CTFA Co. Bureau 

Baby Lotion - baby use 1.4 0.38 1.0 0.57 2.0 

Baby Lotion - adult use 1.0 0.22 0.19 0.24d 0.86 1.0 1.0d 

Baby Oil - baby usec 1.3 0.14 1.2 0.14 3.0 

Baby Oil - adult use 5.0 0.06 0.13 0.29 0.57 

Baby Powder - baby usec 0.8 5.36 1.5 0.35d 8.43 3.0 1.0d 

Baby Powder - adult use 0.8 0.13 0.22 0.57 1.0 

Baby Cream - baby usec 0.43 1.3 0.43 3.0 

Baby Cream - adult use 0.07 0.10 0.14 0.14e 

Baby Shampoo - baby usec 0.5 0.14 0.11f 0.14 0.43f 

Baby Shampoo - adult use 5.0 0.02 0.86e 

Bath Oils 14.7 0.08 0.19 0.22g 0.29 0.86 1.0g 

Bath Tablets 0.003 0.008 0.14e 0.14e 

Bath Salts 18.9 0.006 0.013 0.14e 0.14e 

Bubble Baths 11.8 0.088 0.13 0.43 0.57 

Bath Capsules 0.018 0.019 0.29e 0.14e 

Bath Crystals 0.006 0.29e 0.14e 

Eyebrow Pencil 0.27 0.49 1.0 1.0 

Eyeliner 0.42 0.68 0.27 1.43 1.0 1.0 

Eye Shadow 0.69 0.78 0.40 1.43 1.0 1.0 

Eye Lotion 0.094 0.34 0.43 1.0 

Eye Makeup Remover 0.29 0.45 1.0 1.0 

Mascara 0.79 0.87 0.46 1.29 1.0 1.5 

Under Eye Cover 0.79 0.29 

Blusher & Rouge 0.011 1.18 1.24 0.55 2.0 1.43 1.5 

Face Powders 0.085 0.35 0.67 0.33 1.29 1.0 1.0 

Foundations 0.265 0.46 0.78 0.47 1.0 1.0 1.5 

Leg and Body Paints 0.003 0.011 0.14e 0.14e 

Lipstick & Lip Gloss 1.73 1.23 2.62 4.0 2.86 6.0 

Makeup Bases 0.13 0.24 0.64 0.86 1.0 

Makeup Fixatives 0.052 0.12 0.14 1.0 

Sunscreen 3.18 0.003 0.002 0.14e 0.005 

Colognes & Toilet Water 0.65 0.68 0.85 0.56 1.71 1.43 1.5 

Perfumes 0.23 0.29 0.26 0.38 0.86 1.0 1.5 
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Table 16-34. Amount and Frequency of Use of Various Cosmetic and Baby Products (continued) 

Average Frequency of Use Upper 90th Percentile Frequency of Use 

Amount of (per day) (per day) 

Product Type Product Per 

Applicationa 

(grams) 

Survey Type 

Marketb 

Survey Type 

Market 

Cosmetic Research Cosmetic Research 

CTFA Co. Bureau CTFA Co. 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 
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Table 16-34. Amount and Frequency of Use of Various Cosmetic and Baby Products (continued) 

Average Frequency of Use Upper 90th Percentile Frequency of Use 

Amount of (per day) (per day) 

Product Type Product Per 

Applicationa 

(g) 

Survey Type 

Marketb 

Survey Type 

Market 

Cosmetic Research Cosmetic Research 

CTFA Co. Bureau CTFA Co. Bureau 

Paste Masks (mud packs) 3.7 0.027 0.20 0.14 0.43 

Skin Lighteners 0.024 d 0.14d 

Skin Fresheners & Astringents 2.0 0.33 0.56 1.0 1.43 

Wrinkle Smoothers (removers) 0.38 0.021 0.15 1.0d 1.0 

Facial Cream 0.55 0.0061 0.0061 

Permanent Wave 101 0.003 0.001 0.0082 0.005 

Hair Straighteners 0.156 0.0007 0.005d 

Hair Dye 0.001 0.005 0.004d 0.014 

Hair Lighteners 0.0003 0.005d 

Hair Bleaches 0.0005 0.02d 

Hair Tints 0.0001 0.005d 

Hair Rinse (coloring) 0.0004 0.02d 

Shampoo (coloring) 0.0005 0.02d 

Hair Color Spray d 

Shave Cream 1.73 0.082 0.36 

a Values reported are the averages of the responses reported by the twenty companies interviewed.

(--'s) indicate no data available. b The averages shown for the Market Research Bureau are not true averages - this is due to the fact that in many cases the class of 

most frequent users 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. d Usage data reflected "entire household" use for both baby lotion and baby oil. e Fewer than 10% of individuals surveyed used these products. Value listed is lowest frequency among individuals reporting usage. 

In the case of wave sets, skin lighteners, and hair color spray, none of the individuals surveyed by the CTFA used this product during

the period of the study. f Usage data reflected "entire household" use. g Usage data reflected total bath product usage. h None of the individuals surveyed reported using this product. 

Source: CTFA, 1983. 
Table 16-35. Summary of Consumer Products Use Studies 

Study Study Size Approach Relevant Population Comments 

KEY STUDIES 

Abt, 1992 4,997 product interviews; 

527 mailed questionnaires 

Direct - interviews and Adults 

questionnaires 

Random digit dialing method used to select sample. 

Information on use of 3 products containing methyl chlor

was requested. 

Westat, 1987a 4,920 individuals Direct - questionnaire 18+ yrs selected to be 

representative of US 

population 

Waksberg Method (random digit dialing) used to select 

sample. Respondents asked to recall use in past 2 mon

32 catagories of household products containing methyl 

chloride. 

Westat, 1987b 193 households Direct - telephone survey; 2 Adult household members 

post-survey validation efforts: 30 who do cleaning tasks in 

reinterviewed, then another 50 household 

reeinterviewed 

Waksberg Method (random digit dialing) used to select 

sample. Household use of cleaning products requested. 

Phone survey during end of year holidays may reflect bia

usage data. Two validation resurveys conducted 3 mont

after survey. 

Westat, 1987c 777 households Direct - telephone survey; 1 Household members who do 

post-survey validation effort painting tasks in household 

conducted with 30 reinterviewed 

Waksberg Method (random digit dialing) used to select 

sample. Painting product use information in past 12 mo

was requested. One validation resurvey conducted 3 mo

after survey. 

Tsang and Klepeis, 1996 9,386 individuals Direct - interviews and Representative of U.S. 

questionnaires general population 

National Human Activity Patterns Survey (NHAPS). 

Participants selected using random Dial Digit (RDD) and 

Computer Assisted Telephone Interviewing (CATI). 24-h

diary data, and follow-up questions; nationally representa

represent all seasons, age groups, and genders. 

RELEVANT STUDY 

CTFA, 1983 Survey 1: 47 women 

employees and relatives or 

employees 

Survey 2: 1,129 cosmetics 

purchasers 

Survey 3: 19,035 females 

Survey 1: Direct - 1 wk Survey 1: 16-61 yr old 

prospective survey females 

Survey 2: Direct - prospective Survey 2: Customers of 

survey cosmetic manufacturer 

Survey 3: Direct - 9.5 months. Survey 3: Market research 

prospective survey company sampled female 

consumers nationwide 

Interviewees asked to recall their use of cosmetics and s

baby products during a specific past time period. Survey

and 2 had small populations, but Survey 3 had large 

population selected to be representative of U.S. populatio
Table 16A-1. Volumes Included in 1992 Simmons Study 

The volumes included in the Media series are as follows: 

M1 Publications: Total Audiences 

M2 Publications: Qualitative Measurements And In-Home Audiences 

M3 Publications: Duplication Of Audiences 

M4 Multi-Media Audiences: Adults 

M5 Multi-Media Audiences: Males 

M6 Multi-Media Audiences: Females and Mothers 

M7 Business To Business 

M8 Multi-Media Reach and Frequency and Television Attentiveness & Special Events 

The following volumes are included in the Product series: 

P1 Automobiles, cycles, Trucks & Vans 

P2 Automotive Products & Services 

P3 Travel 

P4 Banking, Investments, Insurance, Credit Cards & Contributions, Memberships & Public Activities 

P5 Games & Toys, Children's & Babies' Apparel & Specialty Products 

P6 Computers, Books, Discs, Records, Tapes, Stereo, Telephones, TV & Video 

P7 Appliances, Garden Care, Sewing & Photography 

P8 Home Furnishings & Home Improvements 

P9 Sports & Leisure 

P10 Restaurants, Stores & Grocery Shopping 

P11 Direct Mail & Other In-Home Shopping, Yellow Pages, Florist, Telegrams, Faxes & Greeting Cards 

P12 Jewelry, Watches, Luggage, Writing Tools & Men's Apparel 

P13 Women's Apparel 

P14 Distilled Spirits, Mixed Drinks, Malt Beverages, Wine & Tobacco Products 

P15 Coffee, Tea, Cocoa, Milk, Soft Drinks, Juices & Bottled Water 

P16 Dairy Products, Desserts, Baking & Bread Products 

P17 Cereals & Spreads, Rice, Pasta, Pizza, Mexican Foods, Fruits & Vegetables 

P18 Soup, Meat, Fish, Poultry, Condiments & Dressings 

P19 Chewing Gum, Candy, Cookies & Snacks 

P20 Soap, Laundry, Paper Products & Kitchen Wraps 

P21 Household Cleaners, Room Deodorizers, Pest Controls & Pet Foods 

P22 Health Care Products & Remedies 

P23 Oral Hygiene Products, Skin Care, Deodorants & Drug Stores 

P24 Hair Care, Shaving Products & Fragrances 

P25 Women's Beauty Aids, Cosmetics & Personal Products 

P26 Relative Volume of Consumption 
Table 17-1. Summary of Residential Volume Distributions

 in Cubic Metersa 

Parameter RECS Data (1) PFT Database (2)

Arithmetic Mean 

Standard Deviation 

10th Percentile 

25th Percentile 

50th Percentile 

75th Percentile 

90th Percentile 

369 

258 

147 

209 

310 

476 

672 

369 

209 

167 

225 

321 

473 

575

a In cubic meters 

Sources: (1) Thompson, 1995; (2) Versar, 1990 
Table 17-2. Average Estimated Volumes of U.S. Residences, by Housing Type and Ownership 

Ownership 

Owner-Occupied Rental All Units 

Volumea Percent Volumea Percent Volumea Percent 

Housing Type (m ) 3 of Total (m ) 3 of Total (m ) 3 of Total 

Single-Family 471 53.1 323 8.5 451 61.7

 (Detached) 

Single-Family 406 4.6 291 2.9 362 7.5 

(Attached) 

Multifamily 362 1.6 216 6.7 243 8.3 

(2-4 units) 

Multifamily 241 1.7 183 15.2 190 16.8 

(5+ Units) 

Mobile Home 221 4.6 170 1.2 210 5.8 

All Types 441 65.4 233 34.6 369 100.0

a Volumes calculated from floor areas assuming a ceiling height of 8 feet. 

Source: Adapted from U.S. DOE, 1995. 
Table 17-3. Residential Volumes in Relation to Household 

Size and Year of Construction 

Volumea 

(m ) Percent of Total 3 

Household Size 

1 Person 269 24.3 

2 Persons 386 32.8 

3 Persons 387 17.2 

4 Persons 431 15.1 

5 Persons 433 7.0 

6 or More Persons 408 3.6 

All Sizes 369 100.0 

Year of Construction 

1939 or before 385 21.1 

1940 to 1949 338 7.1 

1950 to 1959 365 13.5 

1960 to 1969 358 15.5 

1970 to 1979 350 18.7 

1980 to 1984 344 8.8 

1985 to 1987 387 5.7 

1988 to 1990 419 4.9 

1991 to 1993 438 4.7 

All Years 369 100.0 a

 Volumes calculated from floor areas assuming a ceiling height 

of 8 feet. 

Source: U.S. DOE, 1995. 
Table 17-4. Dimensional Quantities for Residential Rooms 

Nominal Dimensions (m) (m) (m) (m ) (m ) 

Length Width Height Volume Wall Area 3 2 (m ) Floor Area 2 (m ) Total Area 2

 Eight Foot Ceiling 

12’x15’ 4.6 3.7 2.4 41 40 17 74 

12’x12’ 3.7 3.7 2.4 33 36 13 62 

10’x12’ 3.0 3.7 2.4 27 33 11 55 

9’x12’ 2.7 3.7 2.4 24 31 10 51 

6’x12’ 1.8 3.7 2.4 16 27 7 40 

4’x12’ 1.2 3.7 2.4 11 24 4 32

 Twelve Foot Ceiling 

12’x15’ 4.6 3.7 3.7 61 60 17 94 

12’x12’ 3.7 3.7 3.7 49 54 13 80 

10’x12’ 3.0 3.7 3.7 41 49 11 71 

9’x12’ 2.7 3.7 3.7 37 47 10 67 

6’x12’ 1.8 3.7 3.7 24 40 7 54 

4’x12’ 1.2 3.7 3.7 16 36 4 44 
Table 17-5. Examples of Products and Materials Associated with Floor 

and Wall Surfaces in Residences 

Material Sources of 

Assumed Amount 

Surface Covereda 

Silicone caulk 0.2 m2 

Floor adhesive 10.0 m2 

Floor wax 50.0 m2 

Wood stain 10.0 m2 

Polyurethane wood finish 10.0 m2 

Floor varnish or lacquer 50.0 m2 

Plywood paneling 100.0 m2 

Chipboard 100.0 m2 

Gypsum board 100.0 m2 

Wallpaper 100.0 m2

 Based on typical values for a residence. a 

Source: Adapted from Tucker, 1991. 
Table 17-6. Percent of Residences with Basement, by 

Census Region and EPA Region 

Census Region Region Residences with 

EPA Percent of 

Basements 

Northeast 1 93.4 

Northeast 2 55.9 

Northeast 3 67.9 

South 4 19.3 

Midwest 5 73.5 

South 6 4.1 

Midwest 7 75.3 

West 8 68.5 

West 9 10.3 

West 10 11.5 

All Regions 45.2 

Source: Lucas et al., 1992. 
Table 17-7. Percent of Residences with Certain Foundation Types by Census Region 

Percent of Residencesa 

Census Region With 

Basement 

With 

Enclosed 

Crawlspace 

With Crawlspace

Open to Outside 

With 

Concrete Slab 

Northeast 78.0 12.6 2.8 15.8 

Midwest 78.1 19.5 5.6 14.7 

South 18.6 31.8 11.0 44.6 

West 19.4 36.7 8.1 43.5 

All Regions 45.2 26.0 7.5 31.3

a Percentage may add to more than 100 percent because more than one foundation type may apply to a given residence. 

Source: U.S. DOE, 1995. 
Table 17-8. States Associated with EPA Regions and Census Regions 

US EPA Regions 

Region 1 Region 4 Region 6 Region 9 

Connecticut Alabama Arkansas Arizona 

Maine Florida Louisiana California 

Massachusetts Georgia New Mexico Hawaii 

New Hampshire Kentucky Oklahoma Nevada 

Rhode Island Mississippi Texas 

Vermont North Carolina Region 10 

Region 2 Tennessee Iowa Idaho 

New Jersey Kansas Oregon 

New York Region 5 Missouri Washington 

Region 3 Indiana 

Delaware Michigan Region 8 

District of Columbia Minnesota Colorado 

Maryland Ohio Montana 

Pennsylvania Wisconsin North Dakota 

Virginia South Dakota 

West Virginia Utah 

South Carolina Region 7 Alaska 

Illinois Nebraska 

Wyoming 

US Bureau of Census Regions 

Northeast Region Midwest Region South Region West Region 

Connecticut Illinois Alabama Alaska 

Maine Indiana Arkansas Arizona 

Massachusetts Iowa Delaware California 

New Hampshire Kansas District of Columbia Colorado 

New Jersey Michigan Florida Hawaii 

New York Minnesota Georgia Idaho 

Pennsylvania Missouri Kentucky Montana 

Rhode island Nebraska Louisiana Nevada 

Vermont North Dakota Maryland New Mexico 

Ohio Mississippi Oregon 

South Dakota North Carolina Utah 

Wisconsin Oklahoma Washington 

South Carolina Wyoming 

Tennessee 

Texas 

Virginia 

West Virginia 
Table 17-9. Summary of Major Projects Providing Air Exchange Measurements 

in the PFT Database 

Number of Mean Air Percentiles a Project Code State Month(s) Measurements Exchange SDb 

Rate 10th 25th 50th 75th 90th 

ADM CA 5-7 29

BSG CA 1,8-12 40

GSS AZ 1-3,8-9 25

FLEMING NY 1-6,8-12 56

GEOMET1 FL 1,6-8,10-12 18

GEOMET2 MD 1-6 23

GEOMET3 TX 1-3 42

LAMBERT1 ID 2-3,10-11 36

LAMBERT2 MT 1-3,11 51

LAMBERT3 OR 1-3,10-12 83

LAMBERT4 WA 1-3,10-12 114

LBL1 OR 1-4,10-12 126

LBL2 WA 1-4,10-12 71

LBL3 ID 1-5,11-12 23

LBL4 WA 1-4,11-12 29

LBL5 WA 2-4 21

LBL6 ID 3-4 19

NAHB MN 1-5,9-12 28

NYSDH NY 1-2,4,12 74

PEI MD 3-4 140

PIERCE CT 1-3 25

RTI1 CA 2 45

RTI2 CA 7 41

RTI3 NY 1-4 397

SOCAL1 CA 3 551

SOCAL2 CA 7 408

SOCAL3 CA 1 330

UMINN MN 1-4 35

UWISC WI 2-5 57

0.70 0.52 0.29 0.36 0.48 0.81 1.75 

0.53 0.30 0.21 0.30 0.40 0.70 0.90 

0.39 0.21 0.16 0.23 0.33 0.49 0.77 

0.24 0.28 0.05 0.12 0.22 0.29 0.37 

0.31 0.16 0.15 0.18 0.25 0.48 0.60 

0.59 0.34 0.12 0.29 0.65 0.83 0.92 

0.87 0.59 0.33 0.51 0.71 1.09 1.58 

0.25 0.13 0.10 0.17 0.23 0.33 0.49 

0.23 0.15 0.10 0.14 0.19 0.26 0.38 

0.46 0.40 0.19 0.26 0.38 0.56 0.80 

0.30 0.15 0.14 0.20 0.30 0.39 0.50 

0.56 0.37 0.28 0.35 0.45 0.60 1.02 

0.36 0.19 0.18 0.25 0.32 0.42 0.52 

1.03 0.47 0.37 0.73 0.99 1.34 1.76 

0.39 0.27 0.14 0.18 0.36 0.47 0.63 

0.36 0.21 0.13 0.19 0.30 0.47 0.62 

0.28 0.14 0.11 0.17 0.26 0.38 0.55 

0.22 0.11 0.11 0.16 0.20 0.24 0.38 

0.59 0.37 0.28 0.37 0.50 0.68 1.07 

0.59 0.45 0.15 0.26 0.49 0.83 1.20 

0.80 1.14 0.20 0.22 0.38 0.77 2.35 

0.90 0.73 0.38 0.48 0.78 1.08 1.52 

2.77 2.12 0.79 1.18 2.31 3.59 5.89 

0.55 0.37 0.26 0.33 0.44 0.63 0.94 

0.81 0.66 0.29 0.44 0.66 0.94 1.43 

1.51 1.48 0.35 0.59 1.08 1.90 3.11 

0.76 1.76 0.26 0.37 0.48 0.75 1.11 

0.36 0.32 0.17 0.20 0.28 0.40 0.56 

0.82 0.76 0.22 0.33 0.55 1.04 1.87

a 1 = January, 2 = February, etc. 

b Standard deviation 

Source: Adapted from Versar, 1990. 
Table 17-10. Summary Statistics for Air Exchange Rates 

(air changes per hour-ACH), by Region 

West Region Region Region 

North Central Northeast 

South Region All Regions 

Arithmetic Mean 0.66 0.57 0.71 0.61 0.63 

Arithmetic Standard Deviation 0.87 0.63 0.60 0.51 0.65 

Geometric Mean 0.47 0.39 0.54 0.46 0.46 

Geometric Standard Deviation 2.11 2.36 2.14 2.28 2.25 

10th Percentile 0.20 0.16 0.23 0.16 0.18 

50th Percentile 0.43 0.35 0.49 0.49 0.45 

90th Percentile 1.25 1.49 1.33 1.21 1.26 

Maximum 23.32 4.52 5.49 3.44 23.32 

Source: Koontz and Rector, 1995. 
-- -- -- -- -- --

Table 17-11. Distributions of Residential Air Exchange Rates by Climate Region and Season a 

Percentiles 

Arithmetic Standard 

Climate Season Sample Size Mean Deviation 10th 25th 50th 75th 90th 

Region 

Coldest Winter 161 0.36 0.28 0.11 0.18 0.27 0.48 0.71 

Spring 254 0.44 0.31 0.18 0.24 0.36 0.53 0.80 

Summer 5 0.82 0.69 0.27 0.41 0.57 1.08 2.01 

Fall 47 0.25 0.12 0.10 0.15 0.22 0.34 0.42 

Colder Winter 428 0.57 0.43 0.21 0.30 0.42 0.69 1.18 

Spring 43 0.52 0.91 0.13 0.21 0.24 0.39 0.83 

Summer 2 1.31 

Fall 23 0.35 0.18 0.15 0.22 0.33 0.41 0.59 

Warmer Winter 96 0.47 0.40 0.19 0.26 0.39 0.58 0.78 

Spring 165 0.59 0.43 0.18 0.28 0.48 0.82 1.11 

Summer 34 0.68 0.50 0.27 0.36 0.51 0.83 1.30 

Fall 37 0.51 0.25 0.30 0.30 0.44 0.60 0.82 

Warmest Winter 454 0.63 0.52 0.24 0.34 0.48 0.78 1.13 

Spring 589 0.77 0.62 0.28 0.42 0.63 0.92 1.42 

Summer 488 1.57 1.56 0.33 0.58 1.10 1.98 3.28 

Fall 18 0.72 1.43 0.22 0.25 0.42 0.46 0.74

a In air changes per hour 

Source: Murray and Burmaster, 1995. 
Table 17-12. Deposition Rates for Indoor Particles 

Size Fraction Deposition Rate 

PM 2.5 0.39 h

PM 10 0.65 h

Coarse 1.0 h 

-1 

-1 

-1 

Source: Adapted from Wallace, 1996. 
Table 17-13. Particle Deposition During Normal Activities 

Particle Size Range Particle Removal Rate 

(h ) -1 

1-5 0.5 

5-10 1.4 

10-25 2.4 

>25 4.1 

Source: Adapted from Thatcher and Layton, 1995. 
Table 17-14. In-house Water Use Rates (gcd), by Study and Type of Use 

Study All Uses or Bath Toilet Laundry Dishwashing Other 

Total, Shower 

MWD 93 26 30 20 5 12 1 

EBMUD 67 20 28 9 4 6 2 

U.S. DHUD 40 15 10 13 2 -­ 3 

Nazaroff et al., 1988 52 6 17 11 18 -­

Study 1

 Study 2

 - Rural 46 11 18 14 3 -­

- Urban 43 10 18 11 4 -­

Study 3 42 9 20 7 4 2

 Study 4 45 9 15 11 4 6

 Study 5 70 21 32 7 7 3

 Study 6 59 20 24 8 4 3

 Study 7 40 10 9 11 5 5

 Study 8 52-86 20-40 4-6 20-30 8-10 -­

Mean Across Studies 59 17 18 13 6 5 5 

Median Across Studies 53 15 18 11 4 5 5 

Metropolitan Water District of Southern California, 1991. 1 

East Bay Municipal Utility District, 1992. 2 

U.S. Department of Housing and Urban Development, 1984. 3 

Results of eight separate studies. 4 

The average value from each range reported in Study No. 8 was used to calculate the median across studies. The mean and 5 

median for the "Total, all Uses" column were obtained by summing across the means and medians for individual types of water 

use. 
Table 17-15. Summary of Selected HUD and Power Authority Water Use Studies 

Number of Households Location Reference 

U.S. DHUD Studies 

Study 1 37 Los Angeles, CA a,b 

Study 2 7 Sacramento, CA a,c 

Study 3 40 Walnut Creek, CA a,c 

Study 4 7 Washington, DC a 

Study 5 21 Sacramento, CA a 

Study 6 19 Los Angeles, CA a 

Power Authority Studies 

Study 1 32 Seattle, WA a 

Study 2 23 Denver, CO a 

Study 3 15 Aurora, CO a 

Study 4 10 Fairfax, VA a 

TOTAL 211 

Sources: 

U.S. Department of Housing and Urban Development, 1984. a 

Metropolitan Water District of Southern California, 1991. b 

East Bay Municipal Utility District, 1992. c 
Table 17-16. Showering and Bathing Water Use Characteristics 

Characteristic Mean Duration Mean Frequency 

Individuals who Shower only 10.4 minutes/shower 0.74 showers/day/person 

Individuals who Bath only NA 0.41 baths/day/person 

Individuals who Shower and Bath NA NA 

Source: Adapted from U. S. DHUD, 1984. 
Table 17-17. Showering Characteristics for Various Types of Shower Heads 

Shower Head Type Mean Flow Rate 

(gpm) 

Non-Conserving (> 3 gpm) 3.4 

Low Flow (# 3 gpm) 1.9 

Restrictor (# 3 gpm) 2.1 

Zinplas 1.8 a 

Turbojector 1.3 a

 Types of low flow water fixtures. a 

Source: Adapted from U.S. DHUD, 1984. 
Table 17-18. Toilet Water Use Characteristics 

Toilet Type Average Water Use 

(gallons/flush) 

Non-Conserving 5.5 

Bottles 5.0 

Bags 4.8 

Dams 4.5 

Low-flush 3.5 

Source: Adapted from U.S. DHUD, 1984. 
Table 17-19. Toilet Frequency Use Characteristics 

Study 

Flush Frequency 

(flushes/person/day) 

U.S. DHUD, 1984 4.2 flushes/household/day a 

Ligman, et al., 1974 Rural, M-F 3.6 flushes/person/day 

Ligman, et al., 1974 Rural, Sat-Sun 3.8 flushes/person/day 

Ligman, et al., 1974 Urban, M-F 3.6 flushes/person/day 

Ligman, et al., 1974 Urban, Sat-Sun 3.1 flushes/person/day 

Siegrist, 1976 2.3 flushes/person/day 

Unweighted Mean 3.43 flushes/person/day

 The HUD value may in fact be flushes/household/day a 
Table 17-20. Dishwasher Frequency Use Characteristics 

Study Use Frequency 

U.S. DHUD, 1984 0.47 loads/person/day 

Ligman, et al., 1974 Rural 1.3 loads/day 

Siegrist, 1976 0.39 loads/person/day 

Unweighted Mean 0.92 loads/day 
Table 17-21. Dishwasher Water Use Characteristics 

Brand (gallons/regular cycle) (minutes) 

Average Water Use Cycle Duration 

140EF 120EF 

Maytag 11.5 75 --

Frigidaire 12 75 75 

General Electric 10.5 80 95 

Sears 10 75 95 

Whirlpool 9.5 60 110 

White/Westinghouse 12 75 75 

Waste King 11.5 65 85 

Kitchen Aid 9.5 80 80 

Magic Chef 11.5 70 -­

Unweighted Mean 10.9 72.8 87.9 

Source: Adapted from Consumer Reports, 1987. 
Table 17-22. Clothes Washer Frequency Use Characteristics 

Study Use Frequency 

U.S. DHUD, 1984 0.3 loads/person/day 

Ligman, et al., 1974 Rural 0.34 loads/person/day 

Ligman, et al., 1974 Urban 0.27 loads/person/day 

Siegrist, 1976 0.31 loads/day 
Table 17-23. Clothes Washer Water Use Characteristics 

Brand 

Average Water Use Cycle Duration 

(gallons/regular cycle) (minutes) 

Maytag 41 32 

Frigidaire 48 40 

General Electric 51 48 

Hotpoint 51 48 

Sears 49 40 

Whirlpool 53 44 

White/Westinghouse 54 47 

Kelvinator 46 52 

Norge 55 49 

Source: Adapted from Consumer Reports, 1982. 
Table 17-24. Range of Water Uses for Clothes Washers 

Type of Clothes Washer Range of Water Use 

Conventional 27-59 gallons/load 

Low Water 16-19 gallons/load 

All Clothes Washers 16-59 gallons/load 

Source: Adapted from Consumer Reports, 1982. 
Table 17-25. Total Dust Loading for Carpeted Areas 

Household Total Dust Load Fine Dust (<150 Fm) Load 

(g-m ) (g-m ) -2 -2 

1 10.8 6.6 

2 4.2 3.0 

3 0.3 0.1 

4 2.2; 0.8 1.2; 0.3 

5 1.4; 4.3 1.0; 1.1 

6 0.8 0.3 

7 6.6 4.7 

8 33.7 23.3 

9 812.7 168.9 

Source: Adapted from Roberts et al., 1991. 
Table 17-26. Particle Deposition and Resuspension During Normal Activities 

Particle Size Range 

(Fm) 

Particle Particle Resuspension Deposition Rate 

Rate 

(h ) -1 (h ) -1 

0.3-0.5 (not measured) 9.9 x 10 

0.6-1 (not measured) 4.4 x 10 

1-5 0.5 1.8 x 10 

5-10 1.4 8.3 x 10 

10-25 2.4 3.8 x 10 

>25 4.1 3.4 x 10 

-7 

-7 

-5 

-5 

-4 

-5 

Source: Adapted from Thatcher and Layton, 1995. 
Table 17-27. Dust Mass Loading After One Week Without Vacuum Cleaning 

Location in Test House Dust Loading (gm-2)

Tracked area of downstairs carpet 2.20 

Untracked area of downstairs carpet 0.58 

Tracked area of linoleum 0.08 

Untracked area of linoleum 0.06 

Tracked area of upstairs carpet 1.08 

Untracked area of upstairs carpet 0.60 

Front doormat 43.34 

Source: Adapted from Thatcher and Layton, 1995. 
Table 17-28. Simplified Source Descriptions for Airborne Contaminants 

Description Components Dimensions 

Direct Discharge 

Combustion E H M 

Volume Discharge Q C _,	

Mass Discharge 

f f f 

E = emission factor f 

H = fuel content f 

M f = fuel consumption rate

p p 

Q p = volume delivery rate

C = concentration in carrier p 

,	 = transfer efficiency 

Mp e w ,

M p = mass delivery rate

w e = weight fraction

,	 = transfer efficiency 

Diffusion Limited 

(D *	 )(C - C )A 

Exponential 

f s i i 

-1 

D f = diffusivity

* = boundary layer thickness -1 

C = vapor pressure of s 

surface 

C i = room concentration

A i = area

A Ei o e-k t 

A i = area

E o = initial unit emission rate

k = emission decay factor 

t = time 

Transport 

Infiltration Q C 

Interzonal Q = air flow from zone j 

Soil Gas C = air concentration in zone 

ji j 

ji 

j 

j 

g h 

g h 

g J 

J mol 

mol h 

m h 

g m 

g g 

g h 

g h 

g g 

g g 

-1 

-1 

-1 

-1 

-1 

3 -1 

-3 

-1 

-1 

-1

 -1 

-1 

g h 

m h 

m 

g m 

-1

 2 -1 

-3 

g m-3 

m2 

g h-1 

m 2 

g h m-1 -2 

h-1 

h 

g h 

m h 

g m 

-1 

3 -1 

-3 
Table 17-29. Volume of Residence Surveys 

Study 

Number of 

Residences Survey Type Areas Surveyed Comments 

Key Studies 

U.S. DOE, 1995 

(RECS) 

Over 7,000 Direct measurement of floor Nationwide (random sample) 

area; estimation of volume 

Volumes were estimated assuming 8 ft. 

ceiling height. Provides relationships 

between average residential volumes 

and facilities such as housing type, 

ownership, household size, and 

structure age. 

Versar, 1990 

(PFT database) 

Over 2,000 Direct measurement and Nationwide (not random 

estimated sample); a large fraction located 

in CA 

Sample was not geographically 

balanced; statistical weighting was 

applied to develop nationwide 

distributions 

Murray, 1996 7,041 (RECS) 

1,751 (PFT) 

Direct measurements and RECS-Nationwide (random 

estimated sample); PFT - Nationwide (not 

random sample); a large fraction 

located in CA 

Duplicate measurement were eliminated; 

tested the effects of using 8 ft. 

assumption on ceiling height to calculate 

volume; data from both databases were 

analyzed. 
Table 17-30. Air Exchange Rates Surveys 

Study Survey Type Areas Surveyed 

Number of 

Residences/Measurements Comments 

Versar, 1990 

(PFT database) 

Over 2,000 residences Measurements using Nationwide (not random 

PFT technique sample); a large fraction located 

in CA 

Multiple measurements on the 

same home were included. 

Koontz & Rector, 1995 

(PFT database) 

2,971 measurements Measurements using Nationwide (not random 

PFT technique sample); a large fraction located 

in CA 

Multiple measurements on the 

same home were included. 

Compensated for geographic 

imbalances. Data are presented by 

region of the country and season. 

Murray and Burmaster, 1995 

(PFT database) 

2,844 measurements Measurements using Nationwide (not random 

PFT technique sample); a large fraction located 

in CA 

Multiple measurements on the 

same home were included. Did not 

compensate for geographical 

imbalances. Data are presented by 

climate region and season. 

Nazaroff et al., 1988 255 (Grot and Clark, 1981) Direct measurement 255, low-income families in 14 

cities 

Sample size was small and not 

representative of the U.S. 

312 (Grimsrud, 1983) Direct measurement 321, newer residences, median 

age <10 years 

Sample size was small and not 

representative of the U.S. 
Table 17-31. Recommendations - Residential Parameters 

3 a 3 Volume of Residence 369 m (central estimate) 217 m (mean)b 

c Air Exchange Rate 0.45 ACH (median) 0.18 ACH (10th percentile)d 

a Same mean value presented in two studies (Table 17-1) - recommended to be used as the central estimate. 

b Mean of two 25th percentile values (Table 17-1) - recommended to be used as the mean value. 

c Recommended to be used as a typical value (Table 17-10). 

d Recommended to be used as a conservative value (Table 17-10). 
Table 17-32. Confidence in House Volume Recommendations 

Considerations Rationale Rating 

Study Elements

 • Level of peer review All key studies are from peer reviewed literature. High

 • Accessibility Papers are widely available from peer review journals. High

 • Reproducibility Direct measurements were made. High

 • Focus on factor of The focus of the studies was on estimating house High

 interest volume as well as other factors.

 • Data pertinent to U.S. Residences in the U.S. was the focus of the key High 

studies.

 • Primary data All the studies were based on primary data. High

 • Currency Measurements in the PFT database were taken Medium 

between 1982-1987. The RECS survey was 

conducted in 1993.

 • Adequacy of data Not applicable

 collection period

 • Validity of approach For the RECS survey, volumes were estimated Medium 

assuming an 8 ft. ceiling height. The effect of this 

assumption has been tested by Murray (1996) and 

found to be insignificant.

 • Study size The sample sizes used in the key studies were fairly Medium 

large, although only 1 study (RECS) was 

representative of the whole U.S. Not all samples 

were selected at random; however, RECS samples 

were selected at random.

 • Representativeness of the RECS sample is representative of the U.S. Medium

 population

 • Characterization of Distributions are presented by housing type and Medium

 variability regions; although some of the sample sizes for the 

subcategories were small.

 • Lack of bias in study design Selection of residences was random for RECS. Medium

 (high rating is desirable)

 • Measurement error Some measurement error may exist since surface Medium 

areas were estimated using the assumption of 8 ft. 

ceiling height. 

Other Elements

 • Number of studies There are 3 key studies; however there are only 2 Low 

data sets.

 • Agreement between researchers There is good agreement among researchers. High 

Overall Rating Results were consistent; 1 study (RECS) was Medium 

representative of residences in the whole U.S.; 

volumes were estimated rather than measured in 

some cases. 
Table 17-33. Confidence in Air Exchange Rate Recommendations 

Considerations Rationale Rating 

Study Elements

 • Level of peer review The studies appear in peer reviewed literature. High 

Although there are 3 studies, they are all based on 

the same database (PFT database).

 • Accessibility Papers are widely available from government reports High 

and peer review journals.

 • Reproducibility Precision across repeat analyses has been Medium 

documented to be acceptable.

 • Focus on factor of The focus of the studies was on estimating air High

 interest exchange rates as well as other factors.

 • Data pertinent to U.S. Residences in the U.S. was the focus of the PFT High 

database.

 • Primary data All the studies were based on primary data. High

 • Currency Measurements in the PFT database were taken Medium 

between 1982-1987.

 • Adequacy of data Only short term data were collected; some residences Medium

 collection period were measured during different seasons; however, 

long term air exchange rates are not well 

characterized.

 • Validity of approach Although the PFT technology is an EPA standard Low 

method (Method IP-4A), it has some major limitations 

(e.g., uniform mixing assumption).

 • Study size The sample sizes used in the key studies were fairly Medium 

large, although not representative of the whole U.S. 

Not all samples were selected at random.

 • Representativeness of the Sample is not representative of the U.S.. Low

 population

 • Characterization of Distributions are presented by U.S. regions, seasons, Low

 variability and climatic regions; although some of the sample 

sizes for the subcategories were small and not 

representative of U.S. The utility is limited..

 • Lack of bias in study design Bias may result since the selection of residences was Low

 (high rating is desirable) not random.

 • Measurement error Some measurement error may exist. Medium 

Other Elements

 • Number of studies There are 3 key studies; however there are only 1 Medium 

data set. However, the database contains results of 

20 projects of varying scope.

 • Agreement between researchers Not applicable 

Overall Rating Sample was not representative of residences in the Low 

whole U.S., but covered the range of occurrence. 

PFT methodology has limitations. Uniform mixing 

assumption may not be adequate. Results will vary 

depending on placement of samples and on whether 

windows and doors are closed or opened. 
Figure 17-1. Elements of Residential Exposure 
Figure 17-2. Cumulative Frequency Distributions for Residential Volumes 

from the PFT Data Base and the U.S. DOE’s RECs. 
Figure 17-3. Configuration for Residential Forced-air Systems 
Figure 17-4. 

Source: Adapted from Nazaroff and Cass, 1989. 

Idealized Patterns of Particle Deposition Indoors 
Figure 17-5. Air Flows for Multiple-zone Systems 
Glossary 

GLOSSARY 

Absorption fraction (percent absorbed) - The relative amount of a substance that penetrates through a 

barrier into the body, reported as a unitless fraction. 

Accuracy - The measure of the correctness of data, as given by the difference between the measured value 

and the true or standard value. 

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. 

Air exchange rate - Rate of air leakage through windows, doorways, intakes and exhausts, and “adventitious 

openings” (i.e., cracks and seams) that combine to form the leakage configuration of the building envelope plus 

natural and mechanical ventilation. 

Ambient - The conditions surrounding a person, sampling location, etc. 

Analytical uncertainty propagation - Examines how uncertainty in individual parameters affects the overall 

uncertainty of the exposure assessment. The uncertainties associated with various parameters may propagate 

through a model very differently, even if they have approximately the same uncertainty. Since uncertainty 

propagation is a function of both the data and the model structure, this procedure evaluates both input 

variances and model sensitivity. 

As consumed intake rates - Intake rates that are based on the weight of the food in the form that it is 

consumed. 

Average daily dose - 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 nonchronic effects. The ADD is usually expressed in terms of mg/kg-day or other mass/mass-time units. 

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. 

Boneless equivalent - Weights of meat (pork, veal, beef) and poultry, excluding all bones, but including 

separable fat sold on retail cuts of red meat. 

Carcass weight - Weight of the chilled hanging carcass, which includes the kidney and attached internal fat 

(kidney, pelvic, and heart fat), excludes the skin, head, feet, and unattached internal organs. The pork carcass 

weight includes the skin and feet but excludes the kidney and attached internal fat. 

Chronic intake - The long term period over which a substance crosses the outer boundary of an organism 

without passing an absorption barrier. 

Comparability - The ability to describe likenesses and differences in the quality and relevance of two or more 

data sets. 

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. 

Exposure Factors Handbook August 1997 
Glossary 

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 Census - Approach used by fishery managers to obtain harvest data collected onsite from single anglers 

or from larger-scale commercial type operations. 

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. 

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. 

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. 

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 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-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. 

Employer tenure - The length of time a worker has been with the same employer. 

Exposed foods - Those foods that are grown above ground and are likely to be contaminated by pollutants 

deposited on surfaces that are eaten. 

Exposure duration - Total time an individual is exposed to the chemical being evaluated. 

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 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 Factors Handbook August 1997 
Glossary 

Exposure scenario - A set of facts, assumptions, and interferences about how exposure takes place that aids 

the exposure assessor in evaluating estimating, or quantifying exposures. 

Exposure - 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 duration - Length of time over which contact with the contaminant lasts. 

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. 

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. 

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 

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. 

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). 

Interzonal airflows - Transport of air through doorways, ductwork, and service chaseways that interconnect 

rooms or zones within a building. 

Lifetime average daily dose - 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. 

Local circulation - Convective and adjective air circulation and mixing within a room or within a zone. 

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. 

Exposure Factors Handbook August 1997 
Glossary 

Median value - The value in a measurement data set such that half the measured values are greater and half 

are less. 

Microenvironment - The combination of activities and locations that yield potential exposure. 

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. 

Occupational mobility - An indicator of the frequency at which workers change from one occupation to 

another. 

Occupational tenure - The cumulative number of years a person worked in his or her current occupation, 

regardless of number of employers, interruptions in employment, or time spent in other occupations. 

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 - Deliberate ingestion of non-nutritive substances such as soil. 

Population mobility - An indicator of the frequency at which individuals move from one residential location to 

another. 

Potential dose - The amount of a chemical contained in material ingested, air breathed, or bulk material 

applied to the skin. 

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. 

Probabilistic uncertainty analysis - Technique that assigns a probability density function to each input 

parameter, then randomly selects values from each of the distributions and inserts them into the exposure 

equation. Repeated calculations produce a distribution of predicted values, reflecting the combined impact of 

variability in each input to the calculation. Monte Carlo is a common type of probabilistic Uncertainty analysis. 

Protected foods - Those foods that have outer protective coatings that are typically removed before 

consumption. 

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. 

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. 

Exposure Factors Handbook August 1997 
Glossary 

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. 

3 Residential volume - The volume (m ) of the structure in which an individual resides and may be exposed to

airborne contaminants. 

Residential occupancy period - The time (years) between a person moving into a residence and the time 

the person moves out or dies. 

Resource utilization - For any quantity Y that is consumed by individuals in a population, the percentiles of the 

“resource utilization distribution” of Y can be formally defined as follows: Y (R) is the pth percentile of the p 

resource utilization distribution if p percent of the overall consumption of Y in the population is done by 

individuals with consumption below Y (R) and 100-p percent is done by individuals with consumption above p 

Y (R). p 

Retail weight equivalent - Weight of food as sold through retail foodstores; therefore, conversion factors are 

used to correct carcass weight to retail weight to account for trimming, shrinkage, or loss of meat and chicken 

at retail outlets. 

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. 

Screening-level assessments - Typically examine exposures that would fall on or beyond the high end of the 

expected exposure distribution. 

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. 

Soil adherence - The quantity of soil that adheres to the skin and from which chemical contaminants are 

available for uptake at the skin surface. 

Subsistence fishermen - Individuals who consume fresh caught fish as a major source of food. 

Test weighing - A method for estimating breast milk intake over a 24-hour period in which the infant is weighed 

before and after each feeding without changing its clothing. The sum of the difference between the measured 

weights over the 24-hour period is assumed to be equivalent to the amount of breast milk consumed daily. 

Total tapwater - 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.). 

Exposure Factors Handbook August 1997 
Glossary 

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. 

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 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. 

Volume of exhaled air (V E ) - Product of the number of respiratory cycles in a minute and the volume of air 

respired during each respiratory cycle (tidal volume, V ). T 

Exposure Factors Handbook August 1997 
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Nationwide Food Consumption Survey 1987-88, NFCS Rpt. No. 87-I-1. 

USDA. (1993) Food consumption, prices, and expenditures (1970-1992) U.S. 

Department of Agriculture, Economic Research Service. Statistical Bulletin, No. 867. 

USDA. (1994) Meat and poultry inspection; 1994 report of the Secretary of Agriculture 

to the U.S. Congress. Washington, DC: U.S. Department of Agriculture. 

USDA. (1996a) Data tables: results from USDA’s 1994 Continuing Survey of Food 

Intakes by Individuals and 1994 Diet and Health Knowledge Survey. U.S. 

Department of Agriculture, Agricultural Research Service, Riverdale, MD. 

USDA. (1996b) Data tables: results from USDA’s 1995 Continuing Survey of Food 

Intakes by Individuals and 1995 Diet and Health Knowledge Survey. U.S. 

Department of Agriculture, Agricultural Research Service, Riverdale, MD. 

U.S. EPA. (1984a) An estimation of the daily average food intake by age and sex for 

use in assessing the radionuclide intake of individuals in the general population. 

EPA-520/1-84-021. 

U.S. EPA. (1984b) An estimation of the daily food intake based on data from the 

1977-1978 USDA Nationwide Food Consumption Survey. Washington, DC: Office of 

Radiation Programs. EPA-520/1-84-015. 

U.S. EPA. (1989) Development of risk assessment methodologies for land application 

and distribution and marketing of municipal sludge. Washington, DC: Office of 

Science and Technology. EPA 600/-89/001. 

White, S.B.; Peterson, B.; Clayton, C.A.; Duncan, D.P. (1983) Interim Report Number 

1: The construction of a raw agricultural commodity consumption data base. 

Prepared by Research Triangle Institute for EPA Office of Pesticide Programs.

REFERENCES FOR CHAPTER 12 

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 Economics Report No. 44. 
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USDA. (1980) Food and nutrient intakes of individuals in one day in the United States, 

Spring 1977. U.S. Department of Agriculture. Nationwide Food Consumption 

Survey 1977-1978. Preliminary Report No. 2. 

USDA. (1992) Food and nutrient intakes by individuals in the United States, 1 day, 

1987-88. U.S. Department of Agriculture, Human Nutrition Information Service. 

Nationwide Food Consumption Survey 1987-88, NFCS Rpt. No. 87-I-1. 

USDA. (1993) Food consumption prices and expenditures (1970-1992) U.S. 

Department of Agriculture, Economic Research Service. Statistical Bulletin, No. 867. 

USDA. (1996a) Data tables: results from USDA’s 1994 Continuing Survey of Food 

Intakes by Individuals and 1994 Diet and Health Knowledge Survey. U.S. 

Department of Agriculture, Agricultural Research Service, Riverdale, MD. 

USDA. (1996b) Data tables: results from USDA’s 1995 Continuing Survey of Food 

Intakes by Individuals and 1995 Diet and Health Knowledge Survey. U.S. 

Department of Agriculture, Agricultural Research Service, Riverdale, MD. 

U.S. EPA. (1984a) An estimation of the daily average food intake by age and sex for 

use in assessing the radionuclide intake of individuals in the general population. 

EPA-520/1-84-021. 

U.S. EPA. (1984b) An estimation of the daily food intake based on data from the 

1977-1978 USDA Nationwide Food Consumption Survey. Washington, DC: Office 

of Radiation Programs. EPA-520/1-84-015. 

U.S. EPA. (1989) Development of risk assessment methodologies for land application 

and distribution and marketing of municipal sludge. Washington, DC: Office of 

Science and Technology. EPA 600/-89/001. 

White, S.B.; Peterson, B.; Clayton, C.A.; Duncan, D.P. (1983) Interim Report Number 

1: The construction of a raw agricultural commodity consumption data base. 

Prepared by Research Triangle Institute for EPA Office of Pesticide Programs.

REFERENCES FOR CHAPTER 13 

American Industrial Health Council (AIHC) (1994) Exposure factors sourcebook. AIHC, 

Washington, DC. 

National Gardening Association. (1987) National gardening survey: 1986-1987. 

Burlington, Vermont: The National Gardening Association, Inc. 
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Handbook No. 102. U.S. Department of Agriculture, Agricultural Research Service, 

Washington, DC. 

USDA. (1987-88) Dataset: Nationwide Food Consumption Survey 1987/88 Household 

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Database. 

USDA. (1992) Changes in food consumption and expenditures in American 

households during the 1980's. U.S. Department of Agriculture. Washington, D.C. 

Statistical Bulletin No. 849. 

USDA. (1993) Food and nutrient intakes by individuals in the United States, 1 Day, 

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USDA. (1994) Food consumption and dietary levels of households in the United 

States, 1987-88. U.S. Department of Agriculture, Agricultural Research Service. 

Report No. 87-H-1. 

REFERENCES FOR CHAPTER 14 

Axelsson, I.; Borulf, S.; Righard, L.; Räihä, N. (1987) Protein and energy intake during 

weaning: effects and growth. Acta Paediatr. Scand. 76:321-327. 

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: 909-919. 

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 breast-fed infants. Journal of Pediatrics. 104:187-195. 

Dewey, K.G.; Lönnerdal, B. (1983) Milk and nutrient intake of breast-fed infants from 1 

to 6 months:relation to growth and fatness. Journal of Pediatric Gastroenterology 

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factors related to breast milk intake and residual volume: the DARLING study. 

Pediatrics. 87:829-837. 
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Hofvander, Y.; Hagman, U.; Hillervik, C.; Sjolin, S. (1982) The amount of milk 

consumed by 1-3 months old breast- or bottle-fed infants. Acta Paediatr. Scand. 

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formula. Acta Paediatr. Scand. 73:40-48. 

Lönnerdal, B.; Forsum, E.; Gebre-Medhim, M.; Hombraes, L. (1976) Breast milk 

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Maxwell, N.I.; Burmaster, D.E. (1993) A simulation model to estimate a distribution of 

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human lactation: milk volumes in lactating women during the onset of lactation and 

full lactation. American Journal of Clinical Nutrition. 48:1375-1386. 

Pao, E.M.; Hines, J.M.; Roche, A.F. (1980) Milk intakes and feeding patterns of 

breast-fed infants. Journal of the American Dietetic Association. 77:540-545. 

Ryan, A.S.; Rush, D.; Krieger, F.W.; Lewandowski, G.E. (1991) Recent declines in 

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AIHC. (1994) Exposure factors sourcebook. Washington, DC. American Industrial 

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Bureau of Labor Statistics. (1987) Most occupational exposures are voluntary. 

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Hill, M.S. (1985) Patterns of time use. In: Juster, F.T.; Stafford, F.P., eds. Time, 

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James, I.R.; Knuiman, M.W. (1987) An application of Bayes methodology to the 

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Juster, F.T.; Hill, M.S.; Stafford, F.P.; Parsons, J.E. (1983) Study description. 

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U.S. EPA. (1989) Exposure factors handbook. Washington, DC: Office of Health and 

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particles within a residence. Atmos. Environ. 29(13):1487-1497. 

Thompson, W. (1995) U.S. Department of Energy (U.S. DOE) and Energy Information 

Administration. Personal communication on distribution of heated floor space area 

from the 1993 RECS. 

Tichenor, B.A.; Guo, Z.; Dunn, J.E.; Sparks, L.E.; Mason, M.A. (1991) The interaction 

of vapor phase organic compounds with indoor sinks. Indoor Air 1:23-35. 

Tucker, W.G. (1991) Emission of organic substances from indoor surface materials. 

Environ. Internat. 17:357-363. 

U.S. Bureau of the Census. (1992) Statistical abstract of the United States: 1992 

(112th edition). Table No. 1230, p. 721. Washington, DC.: U.S. Department of 

Commerce. 

U.S. DHUD. (1984) Residential water conservation projects: summary report. Report 

Number HUD-PDR-903. Washington, DC: U.S. Department of Housing and Urban 

Development, Office of Policy Development and Research. 

U.S. DOE. (1995) Housing characteristics 1993, Residential Energy Consumption

Survey (RECS) Report No. DOE/EIA-0314 (93), Washington, DC: U.S. Department 

of Energy, Energy Information Administration 

Versar. (1990) Database of perfluorocarbon tracer (PFT) ventilation measurements: 

description and user's manual. USEPA Contract No. 68-02-4254, Task No. 39. 
Washington, D.C: U.S.Environmental Protection Agency, Office of Toxic

Substances.

Wallace, L.A. (1996) Indoor particles: A review. J. Air and Waste Management Assoc. 

(46)2:98-126. 

Walton, G.N. (1993) CONTAM 93 User Manual. NISTIR 5385. Gaithersburg, MD: 

National Institute of Standards and Technology. 

Wilkes, C.R.; Small, M.J.; Andelman, J.B.; Giardino, N.J.; Marshall, J. (1992) Inhalation 

exposure model for volatile chemicals from indoor uses of water. Atmospheric 

Environment (26A)12:2227-2236. 

Wolkoff, P. (1995) Volatile organic compounds: sources, measurements, emissions, 

and the impact on indoor air quality. Indoor Air Supplement No. 3/95, pp 1-73. 

Wolkoff, P.; Wilkins, C.K. (1994) Indoor VOCs from household floor dust: comparison 

of headspace with desorbed VOCs; Method for VOC release determination. Indoor 

Air 4:248-254. 

Zinn, T.W.; Cline, D.; Lehmann, W.F. (1990) Long-term study of formaldehyde 

emission decay from particleboard. Forest Products Journal (40)6:15-18. 
DOWNLOADABLE TABLES FOR CHAPTER 3 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 3-1. Daily Total Tapwater Intake Distribution for Canadians, by Age Group 

(approx. 0.20 L increments, both sexes, combined seasons) [WK1, 3 kb] 

Table 3-6. Total Tapwater Intake (mL/day) for Both Sexes Combined [WK1, 3 kb] 

Table 3-7. Total Tapwater Intake (mL/kg-day) for Both Sexes Combined [WK1, 5 kb] 

Table 3-9. Total Tapwater Intake (as percent of total water intake) by Broad Age 

Category [WK1, 1 kb] 

Table 3-10. General Dietary Sources of Tapwater for Both Sexes [WK1, 3 kb] 

Table 3-12. Estimated Quantiles and Means for Total Tapwater Intake Rates (mL/day) 

[WK1, 1 kb] 
DOWNLOADABLE TABLES FOR CHAPTER 4 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 4-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates Per Child for 

64 Children (mg/day) [WK1, 3 kb] 

Table 4-10. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on 

Data for 64 Subjects Projected Over 365 Days [WK1, 1 kb] 
DOWNLOADABLE TABLES FOR CHAPTER 5 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 5-3. Distribution of Predicted IR by Location and Activity Levels for Elementary 

and High School Students [WK1, 2 kb] 

Table 5-5. Distribution Patterns of Daily Inhalation Rates for Elementary (EL) and 

High School (HS) Students Grouped by Activity Level [WK1, 2 kb] 

Table 5-11. Daily Inhalation Rates Calculated from Food-Energy Intakes [WK1, 5 kb] 

Table 5-12. Daily Inhalation Rates Obtained from the Ratios of Total Energy 

Expenditure to Basal Metabolic Rate (BMR) [WK1, 2 kb] 

Table 5-14. Inhalation Rates for Short-Term Exposures [WK1, 3 kb] 

Table 5-19. Distribution Pattern of Predicted VR and EVR (equivalent ventilation rate) 

for 20 Outdoor Workers [WK1, 3 kb] 

Table 5A-3. Characteristics of Individual Subjects: Anthropometric Data, Job 

Categories, Calibration Results [WK1, 4 kb] 

Table 5A-7. Minute Ventilation Ranges by Age, Sex, and Activity Level [WK1, 9 kb] 
DOWNLOADABLE TABLES FOR CHAPTER 6 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 6-2. Surface Area of Adult Males in Square Meters [WK1, 3 kb] 

Table 6-3. Surface Area of Adult Females in Square Meters [WK1, 3 kb] 

Table 6-6. Total Body Surface Area of Male Children in Square Meters [WK1, 4 kb] 

Table 6-7. Total Body Surface Area of Female Children in Square Meters 

[WK1, 4 kb] 

Table 6-9. Descriptive Statistics for Surface Area/BodyWeight (SA/WB) Ratios (m /kg) 

[WK1, 1 kb]
DOWNLOADABLE TABLES FOR CHAPTER 7 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 7-4. Weight in Kilograms for Males 18-74 Years of Age--Number Examined, 

Mean, Standard Deviation, and Selected Percentiles, by Race and Age: 

United States, 1976-1980 [WK1, 5 kb] 

Table 7-5. Weight in Kilograms for Females 18-74 Years of Age--Number Examined, 

Mean, Standard Deviation, and Selected Percentiles, by Race and Age: 

United States, 1976-1980 [WK1, 5 kb] 

Table 7-6. Weight in Kilograms for Males 6 Months-19 Years of Age--Number 

Examined, Mean, Standard Deviation, and Selected Percentiles, by Sex 

and Age: United States, 1976-1980 [WK1, 5 kb] 

Table 7-7. Weight in Kilograms for Females 6 Months-19 Years of Age--Number 

Examined, Mean, Standard Deviation, and Selected Percentiles, by Sex 

and Age: United States, 1976-1980 [WK1, 5 kb] 
DOWNLOADABLE TABLES FOR CHAPTER 8 

The following selected table is available for download as a Lotus 1-2-3 worksheet. 

Table 8-1. Expectation of Life at Birth, 1970 to 1993, and Projections, 1995 to 2010 

[WK1, 5 kb] 
DOWNLOADABLE TABLES FOR CHAPTER 9 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 9-3. Per Capita Intake of Total Fruits (g/kg-day as consumed) [WK1, 6 kb] 

Table 9-4. Per Capita Intake of Total Vegetables (g/kg-day as consumed) 

[WK1, 6 kb] 

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

consumed) [WK1, 31 kb] 

Table 9-6. Per Capita Intake of USDA Categories of Fruits and Vegetables (g/kg-day 

as consumed) [WK1, 9 kb] 

Table 9-7. Per Capita Intake of Exposed Fruits (g/kg-day as consumed) [WK1, 7 kb] 

Table 9-8. Per Capita Intake of Protected Fruits (g/kg-day as consumed) 

[WK1, 7 kb] 

Table 9-9. Per Capita Intake of Exposed Vegetables (g/kg-day as consumed) 

[WK1, 7 kb] 

Table 9-10. Per Capita Intake of Protected Vegetables (g/kg-day as consumed) 

[WK1, 7 kb] 

Table 9-11. Per Capita Intake of Root Vegetables (g/kg-day as consumed) 

[WK1, 7 kb] 

Table 9-26. Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating 

Occasion and the Percentage of Individuals Using These Foods in Three 

Days [WK1, 6 kb] 
DOWNLOADABLE TABLES FOR CHAPTER 10 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 10-3. Percent Distribution of Total Fish Consumption for Females by Age 

[WK1, 3 kb] 

Table 10-4. Percent Distribution of Total Fish Consumption for Males by Age 

[WK1, 3 kb] 

Table 10-7. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for 

the U.S. Population (Uncooked Fish Weight) [WK1, 2 kb] 

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

Habitat for Consumers Only (Uncooked Fish Weight) [WK1, 2 kb] 

Table 10-9. Per Capita Distribution of Fish Intake (mg/kg-day) by Habitat and Fish 

Type for U.S. Population (Uncooked Fish Weight) [WK1, 2 kb] 

Table 10-10. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

by Habitat for Consumers Only (Uncooked Fish Weight) [WK1, 2 kb] 

Table 10-11. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for 

the U.S. Population (Cooked Fish Weight - As Consumed) [WK1, 2 kb] 

Table 10-12. Per Capita Distribution of Fish Intake (g/day) by Habitat for Consumers 

Only (Cooked Fish Weight - As Consumed) [WK1, 2 kb] 

Table 10-13. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population by Age and Gender - As Consumed (Freshwater and 

Estuarine) [WK1, 2 kb] 

Table 10-14. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population by Age and Gender - As Consumed (Marine) 

[WK1, 2 kb] 

Table 10-15. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population by Age and Gender - As Consumed (All Fish) 

[WK1, 2 kb] 

Table 10-16. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (grams/day) 

for the U.S. Population Aged 18 Years and Older by Habitat - As 

Consumed [WK1, 2 kb] 

Table 10-17. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population by Age and Gender - As Consumed (Freshwater 

and Estuarine) [WK1, 2 kb] 

Table 10-18. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population by Age and Gender - As Consumed (Marine) 

[WK1, 2 kb] 
Table 10-19. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population by Age and Gender - As Consumed (All Fish) 

[WK1, 3 kb] 

Table 10-20. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population Aged 18 Years and Older by Habitat - As 

Consumed [WK1, 2 kb] 

Table 10-21. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only by Age and Gender - As Consumed (Freshwater and 

Estuarine) [WK1, 2 kb] 

Table 10-22. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only by Age and Gender - As Consumed (Marine) 

[WK1, 2 kb] 

Table 10-23. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only by Age and Gender - As Consumed (All Fish) 

[WK1, 2 kb] 

Table 10-24. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only Aged 18 Years and Older by Habitat - As Consumed 

[WK1, 3 kb] 

Table 10-25. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only by Age and Gender - As Consumed (Freshwater and 

Estuarine) [WK1, 2 kb] 

Table 10-26. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only by Age and Gender - As Consumed (Marine) 

[WK1, 2 kb] 

Table 10-27. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only by Age and Gender - As Consumed (All Fish) 

[WK1, 2 kb] 

Table 10-28. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only Aged 18 Years and Older by Habitat - As Consumed 

[WK1, 3 kb] 

Table 10-29. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population by Age and Gender - Uncooked Fish Weight (Freshwater 

and Estuarine) [WK1, 2 kb] 

Table 10-30. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population by Age and Gender - Uncooked Fish Weight (Marine) 

[WK1, 2 kb] 

Table 10-31. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population by Age and Gender - Uncooked Fish Weight (All Fish) 

[WK1, 2 kb] 
Table 10-32. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the 

U.S. Population Aged 18 Years and Older by Habitat - Uncooked Fish 

Weight [WK1, 2 kb] 

Table 10-33. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population by Age and Gender - Uncooked Fish Weight 

(Freshwater and Estuarine) [WK1, 2 kb] 

Table 10-34. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population by Age and Gender - Uncooked Fish Weight 

(Marine) [WK1, 3 kb] 

Table 10-35. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population by Age and Gender - Uncooked Fish Weight (All 

Fish) [WK1, 3 kb] 

Table 10-36. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for the U.S. Population Aged 18 Years and Older by Habitat - Uncooked 

Fish Weight [WK1, 2 kb] 

Table 10-37. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only by Age and Gender - Uncooked Fish Weight (Freshwater 

and Estuarine) [WK1, 2 kb] 

Table 10-38. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only by Age and Gender - Uncooked Fish Weight (Marine) 

[WK1, 2 kb] 

Table 10-39. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only by Age and Gender - Uncooked Fish Weight (All Fish) 

[WK1, 2 kb] 

Table 10-40. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for 

Consumers Only Aged 18 Years and Older by Habitat - Uncooked Fish 

Weight [WK1, 3 kb] 

Table 10-41. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only by Age and Gender - Uncooked Fish Weight 

(Freshwater and Estuarine) [WK1, 2 kb] 

Table 10-42. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only by Age and Gender - Uncooked Fish Weight (Marine) 

[WK1, 2 kb] 

Table 10-43. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only by Age and Gender - Uncooked Fish Weight (All 

Fish) [WK1, 2 kb] 

Table 10-44. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) 

for Consumers Only Aged 18 Years and Older by Habitat - Uncooked Fish 

Weight [WK1, 3 kb] 

Table 10-45. Distribution of Quantity of Fish Consumed (in grams) Per Eating Occasion, 

by Age and Sex [WK1, 2 kb] 
Table 10-63. Distribution of Usual Fish Intake Among Survey Main Respondents Who 

Fished and Consumed Recreationally Caught Fish [WK1, 1 kb] 

Table 10-68. Distribution of Fish Intake Rates (from all sources and from sport-caught 

sources) For 1992 Lake Ontario Anglers [WK1, 1 kb] 

Table 10-72. Number of Grams Per Day of Fish Consumed by All Adult Respondents 

(Consumers and Non-consumers Combined) - Throughout the Year 

[WK1, 2 kb] 

Table 10-74. Children’s Fish Consumption Rates - Throughout Year [WK1, 1 kb] 
DOWNLOADABLE TABLES FOR CHAPTER 11 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 11-1. Per Capita Intake of Total Meats (g/kg-day as consumed) [WK1, 6 kb] 

Table 11-2. Per Capita Intake of Total Dairy Products (g/kg-day as consumed) 

[WK1, 6 kb] 

Table 11-3. Per Capita Intake of Beef (g/kg-day as consumed) [WK1, 6 kb] 

Table 11-4. Per Capita Intake of Pork (g/kg-day as consumed) [WK1, 6 kb] 

Table 11-5. Per Capita Intake of Poultry (g/kg-day as consumed) [WK1, 6 kb] 

Table 11-6. Per Capita Intake of Game (g/kg-day as consumed) [WK1, 5 kb] 

Table 11-7. Per Capita Intake of Eggs (g/kg-day as consumed) [WK1, 6 kb] 

Table 11-23. Quantity (as consumed) of Meat, Poultry, and Dairy Products Consumed 

Per Eating Occasion and the Percentage of Individuals Using These 

Foods in Three Days [WK1, 2 kb] 
DOWNLOADABLE TABLES FOR CHAPTER 12 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 12-1. Per Capita Intake of Total Grains Including Mixtures (g/kg-day as 

consumed) [WK1, 6 kb] 

Table 12-2. Per Capita Intake of Breads (g/kg-day as consumed) [WK1, 6 kb] 

Table 12-3. Per Capita Intake of Sweets (g/kg-day as consumed) [WK1, 6 kb] 

Table 12-4. Per Capita Intake of Snacks Containing Grain (g/kg-day as consumed) 

[WK1, 6 kb] 

Table 12-5. Per Capita Intake of Breakfast Foods (g/kg-day as consumed) 

[WK1, 6 kb] 

Table 12-6. Per Capita Intake of Pasta (g/kg-day as consumed) [WK1, 5 kb] 

Table 12-7. Per Capita Intake of Cooked Cereals (g/kg-day as consumed) 

[WK1, 5 kb] 

Table 12-8. Per Capita Intake of Rice (g/kg-day as consumed) [WK1, 5 kb] 

Table 12-9. Per Capita Intake of Ready-to-Eat Cereals (g/kg-day as consumed) 

[WK1, 6 kb] 

Table 12-10. Per Capita Intake of Baby Cereals (g/kg-day as consumed) [WK1, 4 kb] 

Table 12-20. Quantity (as consumed) of Grain Products Consumed Per Eating 

Occasion and the Percentage of Individuals Using These Foods in Three 

Days [WK1, 3 kb] 
DOWNLOADABLE TABLES FOR CHAPTER 13 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 13-8. Consumer Only Intake of Homegrown Fruits (g/kg-day) - All Regions 

Combined [WK1, 6 kb] 

Table 13-9. Consumer Only Intake of Homegrown Fruits (g/kg-day) - Northeast 

[WK1, 3 kb] 

Table 13-10. Consumer Only Intake of Homegrown Fruits (g/kg-day) - Midwest 

[WK1, 3 kb] 

Table 13-11. Consumer Only Intake of Homegrown Fruits (g/kg-day) - South 

[WK1, 4 kb] 

Table 13-12. Consumer Only Intake of Homegrown Fruits (g/kg-day) - West 

[WK1, 3 kb] 

Table 13-13. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - All Regions 

Combined [WK1, 6 kb] 

Table 13-14. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - Northeast 

[WK1, 3 kb] 

Table 13-15. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - Midwest 

[WK1, 3 kb] 

Table 13-16. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - South 

[WK1, 3 kb] 

Table 13-17. Consumer Only Intake of Homegrown Vegetables (g/kg-day) - West 

[WK1, 3 kb] 

Table 13-18. Consumer Only Intake of Home Produced Meats (g/kg-day) - All Regions 

Combined [WK1, 6 kb] 

Table 13-19. Consumer Only Intake of Home Produced Meats (g/kg-day) - Northeast 

[WK1, 3 kb] 

Table 13-20. Consumer Only Intake of Home Produced Meats (g/kg-day) - Midwest 

[WK1, 3 kb] 

Table 13-21. Consumer Only Intake of Home Produced Meats (g/kg-day) - South 

[WK1, 3 kb] 

Table 13-22. Consumer Only Intake of Home Produced Meats (g/kg-day) - West 

[WK1, 3 kb] 

Table 13-23. Consumer Only Intake of Home Caught Fish (g/kg-day) - All Regions 

Combined [WK1, 5 kb] 
Table 13-24. Consumer Only Intake of Home Caught Fish (g/kg-day) - Northeast 

[WK1, 2 kb] 

Table 13-25. Consumer Only Intake of Home Caught Fish (g/kg-day) - Midwest 

[WK1, 3 kb] 

Table 13-26. Consumer Only Intake of Home Caught Fish (g/kg-day) - South 

[WK1, 3 kb] 

Table 13-27. Consumer Only Intake of Home Caught Fish (g/kg-day) - West 

[WK1, 3 kb] 

Table 13-28. Consumer Only Intake of Home Produced Dairy (g/kg-day) - All Regions 

[WK1, 5 kb] 

Table 13-29. Consumer Only Intake of Home Produced Dairy (g/kg-day) – Northeast 

[WK1, 3 kb] 

Table 13-30. Consumer Only Intake of Home Produced Dairy (g/kg-day) – Midwest 

[WK1, 3 kb] 

Table 13-31. Consumer Only Intake of Home Produced Dairy (g/kg-day) - South 

[WK1, 2 kb] 

Table 13-32. Consumer Only Intake of Home Produced Dairy (g/kg-day) - West 

[WK1, 3 kb] 

Table 13-33. Seasonally Adjusted Consumer Only Homegrown Intake (g/kg-day) 

[WK1, 3 kb] 

Table 13-34. Consumer Only Intake of Homegrown Apples (g/kg-day) [WK1, 7 kb] 

Table 13-35. Consumer Only Intake of Homegrown Asparagus (g/kg-day) [WK1, 6 kb] 

Table 13-36. Consumer Only Intake of Home Produced Beef (g/kg-day) [WK1, 6 kb] 

Table 13-37. Consumer Only Intake of Homegrown Beets (g/kg-day) [WK1, 6 kb] 

Table 13-38. Consumer Only Intake of Homegrown Broccoli (g/kg-day) [WK1, 6 kb] 

Table 13-39. Consumer Only Intake of Homegrown Cabbage (g/kg-day) [WK1, 6 kb] 

Table 13-40. Consumer Only Intake of Homegrown Carrots (g/kg-day) [WK1, 7 kb] 

Table 13-41. Consumer Only Intake of Homegrown Corn (g/kg-day) [WK1, 7 kb] 

Table 13-42. Consumer Only Intake of Homegrown Cucumbers (g/kg-day) [WK1, 6 kb] 

Table 13-43. Consumer Only Intake of Home Produced Eggs (g/kg-day) [WK1, 6 kb] 

Table 13-44. Consumer Only Intake of Home Produced Game (g/kg-day) [WK1, 6 kb] 

Table 13-45. Consumer Only Intake of Home Produced Lettuce (g/kg-day) [WK1, 6 kb] 

Table 13-46. Consumer Only Intake of Home Produced Lima Beans (g/kg-day) 

[WK1, 6 kb] 

Table 13-47. Consumer Only Intake of Homegrown Okra (g/kg-day) [WK1, 6 kb] 

Table 13-48. Consumer Only Intake of Homegrown Onions (g/kg-day) [WK1, 7 kb] 
Table 13-49. Consumer Only Intake of Homegrown Other Berries (g/kg-day) 

[WK1, 6 kb] 

Table 13-50. Consumer Only Intake of Homegrown Peaches (g/kg-day) [WK1, 6 kb] 

Table 13-51. Consumer Only Intake of Homegrown Pears (g/kg-day) [WK1, 6 kb] 

Table 13-52. Consumer Only Intake of Homegrown Peas (g/kg-day) [WK1, 7 kb] 

Table 13-53. Consumer Only Intake of Homegrown Peppers (g/kg-day) [WK1, 6 kb] 

Table 13-54. Consumer Only Intake of Home Produced Pork (g/kg-day) [WK1, 6 kb] 

Table 13-55. Consumer Only Intake of Home Produced Poultry (g/kg-day) [WK1, 6 kb] 

Table 13-56. Consumer Only Intake of Homegrown Pumpkins (g/kg-day) [WK1, 6 kb] 

Table 13-57. Consumer Only Intake of Homegrown Snap Beans (g/kg-day) 

[WK1, 7 kb] 

Table 13-58. Consumer Only Intake of Homegrown Strawberries (g/kg-day) 

[WK1, 6 kb] 

Table 13-59. Consumer Only Intake of Homegrown Tomatoes (g/kg-day) [WK1, 7 kb] 

Table 13-60. Consumer Only Intake of Homegrown White Potatoes (g/kg-day) 

[WK1, 7 kb] 

Table 13-61. Consumer Only Intake of Homegrown Exposed Fruit (g/kg-day) 

[WK1, 7 kb] 

Table 13-62. Consumer Only Intake of Homegrown Protected Fruits (g/kg-day) 

[WK1, 6 kb] 

Table 13-63. Consumer Only Intake of Homegrown Exposed Vegetables (g/kg-day) 

[WK1, 7 kb] 

Table 13-64. Consumer Only Intake of Homegrown Protected Vegetables (g/kg-day) 

[WK1, 7 kb] 

Table 13-65. Consumer Only Intake of Homegrown Root Vegetables (g/kg-day) 

[WK1, 7 kb] 

Table 13-66. Consumer Only Intake of Homegrown Dark Green Vegetables (g/kg-day) 

[WK1, 7 kb] 

Table 13-67. Consumer Only Intake of Homegrown Deep Yellow Vegetables (g/kg-day) 

[WK1, 7 kb] 

Table 13-68. Consumer Only Intake of Homegrown Other Vegetables (g/kg-day) 

[WK1, 7 kb] 

Table 13-69. Consumer Only Intake of Homegrown Citrus (g/kg-day) [WK1, 6 kb] 

Table 13-70. Consumer Only Intake of Homegrown Other Fruit (g/kg-day) [WK1, 6 kb] 
DOWNLOADABLE TABLES FOR CHAPTER 15 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 15-18. Range of Recommended Defaults for Dermal Exposure Factors 

[WK1, 1 kb] 

Table 15-19. Number of Times Taking a Shower at Specified Daily Frequencies by the 

Number of Respondents [WK1, 8 kb] 

Table 15-20. Times (minutes) Spent Taking Showers by the Number of Respondents 

[WK1, 7 kb] 

Table 15-21. Number of Minutes Spent Taking a Shower (minutes/shower) 

[WK1, 7 kb] 

Table 15-22. Time (minutes) Spent in the Shower Room Immediately After Showering 

by the Number of Respondents [WK1, 8 kb] 

Table 15-23. Number of Minutes Spent in the Shower Room Immediately After 

Showering (minutes/shower) [WK1, 7 kb] 

Table 15-24. Number of Baths Given or Taken in One Day by Number of Respondents 

[WK1, 8 kb] 

Table 15-25. Total Time Spent Taking or Giving a Bath by the Number of Respondents 

[WK1, 7 kb] 

Table 15-26. Number of Minutes Spent Giving and Taking the Bath(s) (minutes/bath) 

[WK1, 7 kb] 

Table 15-27. Time Spent in the Bathroom Immediately After the Bath(s) by the Number 

of Respondents [WK1, 8 kb] 

Table 15-28. Number of Minutes Spent in the Bathroom Immediately After the Bath(s) 

(minutes/bath) [WK1, 7 kb] 

Table 15-29. Total Time Spent Altogether in the Shower or Bathtub by the Number of 

Respondents [WK1, 11 kb] 

Table 15-30. Total Number of Minutes Spent Altogether in the Shower or Bathtub 

(minutes/bath) [WK1, 7 kb] 

Table 15-31. Time Spent in the Bathroom Immediately Following a Shower or Bath by 

the Number of Respondents [WK1, 10 kb] 

Table 15-32. Number of Minutes Spent in the Bathroom Immediately Following a 

Shower or Bath (minutes/bath) [WK1, 7 kb] 

Table 15-33. Range of Number of Times Washing the Hands at Specified Daily 

Frequencies by the Number of Respondents [WK1, 7 kb] 
Table 15-50. Number of Hours Worked in a Week That Was Outdoors (hours/week) 

[WK1, 7 kb] 

Table 15-57. Number of Minutes Spent Playing on Sand or Gravel in a Day by the 

Number of Respondents [WK1, 10 kb] 

Table 15-58. Number of Minutes Spent Playing in Sand or Gravel (minutes/day) 

[WK1, 7 kb] 

Table 15-59. Number of Minutes Spent Playing in Outdoors on Sand, Gravel, Dirt, or 

Grass When Fill Dirt Was Present by the Number of Respondents 

[WK1, 10 kb] 

Table 15-60. Number of Minutes Spent Playing on Sand, Gravel, Dirt, or Grass When 

Fill Dirt Was Present (minutes/day) [WK1, 7 kb] 

Table 15-61. Range of the Time Spent Working in a Garden or Other Circumstances in 

a Month by the Number of Respondents [WK1, 11 kb] 

Table 15-62. Number of Hours Spent Working with Soil in a Garden or Other 

Circumstances Working (hours/month) [WK1, 7 kb] 

Table 15-63. Range of Number of Minutes Spent Playing on Grass in a Day by the 

Number of Respondents [WK1, 11 kb] 

Table 15-64. Number of Minutes Spent Playing on Grass (minutes/day) [WK1, 7 kb] 

Table 15-65. Number of Times Swimming in a Month in Freshwater Swimming Pool by 

the Number of Respondents [WK1, 21 kb] 

Table 15-66. Range of the Average Amount of Time Actually Spent in the Water by 

Swimmers by the Number of Respondents [WK1, 12 kb] 

Table 15-67. Number of Minutes Spent Swimming in a Month in Freshwater Swimming 

Pool (minutes/month) [WK1, 8 kb] 

Table 15-79. Statistics for 24-Hour Cumulative Number of Minutes Spent in Indoor 

Playing [WK1, 11 kb] 

Table 15-80. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor 

Playing [WK1, 10 kb] 

Table 15-85. Statistics for 24-Hour Cumulative Number of Minutes Spent in Active 

Sports [WK1, 12 kb] 

Table 15-86. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor 

Recreation [WK1, 12 kb] 

Table 15-87. Statistics for 24-Hour Cumulative Number of Minutes Spent in Exercise 

[WK1, 12 kb] 

Table 15-91. Statistics for 24-Hour Cumulative Number of Minutes Spent in Bathing 

[WK1, 12 kb] 

Table 15-92. Statistics for 24-Hour Cumulative Number of Minutes Spent in 

Yardwork/Maintenance [WK1, 12 kb] 
Table 15-93. Statistics for 24-Hour Cumulative Number of Minutes Spent in 

Sports/Exercise [WK1, 12 kb] 

Table 15-102. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at 

School [WK1, 12 kb] 

Table 15-108. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on 

School Grounds/Playground [WK1, 11 kb] 

Table 15-110. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at 

a Pool/River/Lake [WK1, 12 kb] 

Table 15-113. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in 

the Kitchen [WK1, 12 kb] 

Table 15-114. Statistics for 24-Hour Cumulative Number of Minutes Spent in the 

Bathroom [WK1, 12 kb] 

Table 15-115. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in 

the Bedroom [WK1, 12 kb] 

Table 15-116. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in 

the Garage [WK1, 11 kb] 

Table 15-117. Statistics for 24-Hour Cumulative Number of Minutes Spent in the 

Basement [WK1, 12 kb] 

Table 15-118. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in 

the Utility Room or Laundry Room [WK1, 11 kb] 

Table 15-121. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in 

a Car [WK1, 12 kb] 

Table 15-122. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in 

a Truck (Pick-up/Van) [WK1, 12 kb] 

Table 15-123. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on 

a Motorcycle, Moped, or Scooter [WK1, 9 kb] 

Table 15-124. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in 

Other Trucks [WK1, 12 kb] 

Table 15-125. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on 

a Bus [WK1, 12 kb] 

Table 15-126. Statistics for 24-Hour Cumulative Number of Minutes Spent Walking 

[WK1, 12 kb] 

Table 15-127. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on 

a Bicycle/Skateboard/ Rollerskate [WK1, 11 kb] 

Table 15-128. Statistics for 24-Hour Cumulative Number of Minutes Spent Waiting on a 

Bus, Train etc., Stop [WK1, 11 kb] 

Table 15-129. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on 

a Train/Subway/Rapid Transit [WK1, 12 kb] 
Table 15-130. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on 

an Airplane [WK1, 10 kb] 

Table 15-131. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors in a 

Residence (all rooms) [WK1, 12 kb] 

Table 15-132. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors 

(outside the residence) [WK1, 12 kb] 

Table 15-133. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling 

Inside a Vehicle [WK1, 12 kb] 

Table 15-135. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors 

Other Than Near a Residence or Vehicle Such as Parks, Golf Courses, 

or Farms [WK1, 12 kb] 

Table 15-166. Percent of Householders Living in Houses for Specified Ranges of Time 

[WK1, 1 kb] 

Table 15-167. Descriptive Statistics for Residential Occupancy Period [WK1, 1 kb] 

Table 15-168. Descriptive Statistics for Both Genders by Current Age [WK1, 3 kb] 
DOWNLOADABLE TABLES FOR CHAPTER 16 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 16-2. Frequency of Use for Household Solvent Products (users-only) 

[WK1, 6 kb] 

Table 16-3. Exposure Time of Use for Household Solvent Products (users-only) 

[WK1, 7 kb] 

Table 16-4. Amount of Products Used for Household Solvent Products (users-only) 

[WK1, 7 kb] 

Table 16-5. Time Exposed After Duration of Use for Household Solvent Products 

(users-only) [WK1, 6 kb] 

Table 16-6. Frequency of Use and Amount of Product Used for Adhesive Removers 

[WK1, 2 kb] 

Table 16-8. Frequency of Use and Amount of Product Used for Spray Paint 

[WK1, 2 kb] 

Table 16-10. Frequency of Use and Amount of Product Used for Paint 

Removers/Strippers [WK1, 2 kb] 

Table 16-13. Percentile Rankings for Total Exposure Time in Performing Household 

Tasks [WK1, 2 kb] 

Table 16-14. Mean Percentile Rankings for Frequency of Performing Household Tasks 

[WK1, 3 kb] 

Table 16-15. Mean and Percentile Rankings for Exposure Time Per Event of 

Performing Household Tasks [WK1, 2 kb] 

Table 16-16. Total Exposure Time for Ten Product Groups Most Frequently Used for 

Household Cleaning [WK1, 2 kb] 

Table 16-17. Total Exposure Time of Painting Activity of Interior Painters (hours) 

[WK1, 1 kb] 

Table 16-18. Exposure Time of Interior Painting Activity/Occasion (hours) and 

Frequency of Occasions Spent Painting Per Year [WK1, 1 kb] 

Table 16-19. Amount of Paint Used by Interior Painters [WK1, 1 kb] 

Table 16-20. Number of Respondents Using Cologne, Perfume, Aftershave or Other 

Fragrances at Specified Daily Frequencies [WK1, 5 kb] 

Table 16-21. Number of Respondents Using Any Aerosol Spray Product for Personal 

Care Item Such as Deodorant or Hair Spray at Specified Daily 

Frequencies [WK1, 7 kb] 
Table 16-22. Number of Minutes Spent in Activities Working with or Being Near Freshly 

Applied Paints (minutes/day) [WK1, 8 kb] 

Table 16-23. Number of Minutes Spent in Activities Working with or Near Household 

Cleaning Agents Such as Scouring Powders or Ammonia (minutes/day) 

[WK1, 8 kb] 

Table 16-24. Number of Minutes Spent in Activities (at home or elsewhere) Working 

with or Near Floorwax, Furniture Wax or Shoe Polish (minutes/day) 

[WK1, 8 kb] 

Table 16-25. Number of Minutes Spent in Activities Working with or Being Near Glue 

[WK1, 7 kb] 

Table 16-26. Number of Minutes Spent in Activities Working with or Near Solvents, 

Fumes or Strong Smelling Chemicals (minutes/day) [WK1, 8 kb] 

Table 16-27. Number of Minutes Spent in Activities Working with or Near Stain or Spot 

Removers (minutes/day) [WK1, 7 kb] 

Table 16-28. Number of Minutes Spent in Activities Working with or Near Gasoline or 

Diesel-powered Equipment, Besides Automobiles (minutes/day) 

[WK1, 8 kb] 

Table 16-29. Number of Minutes Spent Using Any Microwave Oven (minutes/day) 

[WK1, 7 kb] 

Table 16-30. Number of Respondents Using a Humidifier at Home [WK1, 5 kb] 

Table 16-31. Number of Respondents Indicating that Pesticides Were Applied by the 

Professional at Home to Eradicate Insects, Rodents, or Other Pests at 

Specified Frequencies [WK1, 5 kb] 

Table 16-32. Number of Respondents Reporting Pesticides Applied by the Consumer at 

Home to Eradicate Insects, Rodents, or Other Pests at Specified 

Frequencies [WK1, 5 kb] 

Table 16-33. Number of Minutes Spent in Activities Working with or Near Pesticides, 

Including Bug Sprays or Bug Strips (minutes/day) [WK1, 8 kb] 
DOWNLOADABLE TABLES FOR CHAPTER 17 

The following selected tables are available for download as Lotus 1-2-3 worksheets. 

Table 17-1. Summary of Residential Volume Distributions [WK1, 1 kb] 

Table 17-9. Summary of Major Projects Providing Air Exchange Measurements in the 

PFT Database [WK1, 6 kb] 

Table 17-11. Distributions of Residential Air Exchange Rates by Climate Region and 

Season [WK1, 3 kb]