DRAFT
DO NOT CITE OR QUOTE
NCEA-W-0853
June 2000
External Review Draft
CHILD-SPECIFIC EXPOSURE FACTORS HANDBOOK
Prepared for:
U.S. Environmental Protection Agency
National Center for Environmental Assessment
Office of Research and Development
Washington, D.C. 20460
Contract No. 68-W-99-041
Work Assignment No. 2-11
Prepared by:
Versar, Inc.
6850 Versar Center
Springfield, VA 22151
NOTICE
THIS DOCUMENT IS A PRELIMINARY DRAFT. It has not been formally released by the
U.S. Environmental Protection Agency and should not at this stage be construed to represent
Agency policy. It is being circulated for comment on its technical accuracy and policy
implications.
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DISCLAIMER
This document is an external draft for review purposes only and does not constitute U.S.
Environmental Protection Agency policy. Mention of trade names or commercial products does
not constitute endorsement or recommendation for use.
1
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TABLE OF CONTENTS
1. INTRODUCTION 1-1
1.1 BACKGROUND 1-1
1.2 PURPOSE 1-3
1.3 INTENDED AUDIENCE 1-3
1.4 SELECTION OF STUDIES FOR THE HANDBOOK 1-4
1.5 APPROACH USED TO DEVELOP RECOMMENDATIONS FOR EXPOSURE
FACTORS 1-6
1.6 CHARACTERIZING VARIABILITY 1-7
1.7 USING THE HANDBOOK IN AN EXPOSURE ASSESSMENT 1-10
1.7.1 General Equation for Calculating Dose 1-11
1.8 FUTURE OR ON-GOING WORK 1-15
1.9 RESEARCH NEEDS 1-16
1.10 ORGANIZATION 1-17
1.11 REFERENCES FOR CHAPTER 1 1-19
2. BREAST MILK INTAKE 2-1
2.1 INTRODUCTION 2-1
2.2 STUDIES ON BREAST MILK INTAKE 2-2
2.3 STUDIES ON LIPID CONTENT AND FAT INTAKE FROM BREAST
MILK 2-5
2.4 OTHER FACTORS 2-7
2.5 RECOMMENDATIONS 2-8
2.6 REFERENCES FOR CHAPTER 2 2-10
3. FOOD INTAKE 3-1
3.1 INTRODUCTION 3-1
3.2 INTAKE RATE DISTRIBUTIONS FOR VARIOUS FOOD TYPES 3-3
3.3 FISH INTAKE RATES 3-6
3.3.1 General Population Studies 3-6
3.3.2 Freshwater Recreational Study 3-12
3.3.3 Native American Subsistence Study 3-14
3.4 FAT INTAKE 3-15
3.5 TOTAL DIETARY INTAKE AND CONTRIBUTIONS TO DIETARY
INTAKE 3-17
3.6 INTAKE OF HOME-PRODUCED FOODS 3-18
3.7 SERVING SIZE STUDY BASED ON THE USDA NFCS 3-23
3.8 CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE
RATES 3-23
3.9 FAT CONTENT OF MEAT AND DAIRY PRODUCTS 3-24
li
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TABLE OF CONTENTS (Continued)
3.10 RECOMMENDATIONS 3-25
3.11 REFERENCES FOR CHAPTER 3 3-27
APPENDIX 3A Calculations Used in the 1994-96 CSFII Analysis to Correct for Mixtures
APPENDIX 3B Food Codes and Definitions Used in Analysis of the 1994-96 Usda CSFII
Data
APPENDIX 3C Sample Calculation of Mean Daily Fat Intake Based On cdc (1994) Data
APPENDIX 3D Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS
Data
4. DRINKING WATER INTAKE 4-1
4.1 INTRODUCTION 4-1
4.2 DRINKING WATER INTAKE STUDIES 4-2
4.3. PREGNANT AND LACTATING WOMEN 4-7
4.4 RECOMMENDATIONS 4-8
4.5 REFERENCES FOR CHAPTER 4 4-9
5. SOIL INGESTION AND PICA 5-1
5.1 INTRODUCTION 5-1
5.2 SOIL INTAKE STUDIES 5-1
5.3 PREVALENCE OF PICA 5-18
5.4 DELIBERATE SOIL INGESTION AMONG CHILDREN 5-19
5.5 RECOMMENDATIONS 5-25
5.6 REFERENCES FOR CHAPTER 5 5-27
6. OTHER NON-DIETARY INGESTION FACTORS 6-1
6.1 INTRODUCTION 6-1
6.2 STUDIES RELATED TO NON-DIETARY INGESTION 6-2
6.3 RECOMMENDATIONS 6-9
6.4 REFERENCES FOR CHAPTER 6 6-11
7. INHALATION ROUTE 7-1
7.1 INTRODUCTION 7-1
7.2 INHALATION RATE STUDIES 7-1
7.3 RECOMMENDATIONS 7-7
7.4 REFERENCES FOR CHAPTER 7 7-9
APPENDIX 7A Ventilation Data 7A-1
iii
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TABLE OF CONTENTS (Continued)
8. DERMAL ROUTE 8-1
8.1 INTRODUCTION 8-1
8.2 SURFACE AREA 8-2
8.2.1 Background 8-2
8.2.2 Measurement Techniques 8-2
8.2.3 Body Surface Area Studies 8-3
8.2.4 Application of Body Surface Area Data 8-7
8.3 SOIL ADHERENCE TO SKIN 8-8
8.3.1 Background 8-8
8.3.2 Soil Adherence to Skin Studies 8-9
8.4 RECOMMENDATIONS 8-12
8.4.1 Body Surface Area 8-12
8.4.2 Soil Adherence to Skin 8-13
8.5 REFERENCES FOR CHAPTER 8 8-15
APPENDIX 8A Formulae for Total Body Surface Area
9. ACTIVITY FACTORS 9-1
9.1 INTRODUCTION 9-1
9.2 ACTIVITY PATTERNS 9-1
9.3 RECOMMENDATIONS 9-11
9.3.1 Recommendations for Activity Patterns 9-11
9.3.2 Summary of Recommended Activity Factors 9-13
9.4 REFERENCES FOR CHAPTER 9 9-14
10. CONSUMER PRODUCTS 10-1
10.1 BACKGROUND 10-1
10.2 CONSUMER PRODUCTS USE STUDIES 10-1
10.3 RECOMMENDATIONS 10-2
10.4 REFERENCES FOR CHAPTER 10 10-3
11. BODY WEIGHT STUDIES 11-1
11.1 INTRODUCTION 11-1
11.2 BODY WEIGHT STUDIES 11-1
11.3 RECOMMENDATIONS 11-3
11.4 REFERENCES FOR CHAPTER 11 11-5
iv
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TABLE OF CONTENTS (Continued)
12. LIFETIME 12-1
12.1 INTRODUCTION 12-1
12.2 DATA ON LIFETIME 12-1
12.3 RECOMMENDATIONS 12-2
12.4 REFERENCES FOR CHAPTER 12 12-3
v
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LIST OF TABLES
Table 1-1. Considerations Used to Rate Confidence in recommended Values 1-21
Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings 1-22
Table 1-3. Characterization of Variability in Exposure Factors 1-24
Table 2-1. Daily Intakes of Breast Milk 2-11
Table 2-2. Breast Milk Intake for Infants Aged 1 to 6 Months 2-11
Table 2-3. Breast Milk Intake among Exclusively Breast-fed
Infants During the First 4 Months of Life 2-12
Table 2-4. Breast Milk Intake During a 24-hour Period 2-13
Table 2-5. Breast Milk Intake Estimated by the Darling Study 2-14
Table 2-6. Lipid Content of Human Milk and Estimated Lipid Intake among Exclusively
Breast-fed Infants 2-14
Table 2-7. Predicted Lipid Intakes for Breast-fed Infants under 12 Months of Age 2-14
Table 2-8. Number of Meals per Day 2-15
Table 2-9. Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and
Infants at 5 or 6 Months Of Age in the United States in 1989a, by Ethnic Background
and Selected Demographic Variables 2-16
Table 2-10. Confidence in Breast Milk Intake Recommendations 2-17
Table 2-11. Breast Milk Intake Rates Derived from Key Studies 2-18
Table 2-12. Summary of Recommended Breast Milk And Lipid Intake Rates 2-19
Table 3-1. Weighted and Unweighted Number of Observations, 1994/96 CSFII Analysis .. 3-29
Table 3-2. Per Capita Intake of the Major Food Groups (g/kg-day as consumed) 3-30
Table 3-3. Per Capita Intake of Individual Foods (g/kg-day as consumed) 3-31
Table 3-4. Per Capita Intake of USD A Categories of Vegetables and Fruits (g/kg-day as
consumed) 3-33
Table 3-5. Per Capita Intake of Exposed/Protected Fruit and Vegetable Categories
(g/kg-day as consumed) 3-34
Table 3-6. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender
- As Consumed 3-35
Table 3-7. Consumers Only Distribution of Fish (Finfish and Shellfish) Intake by Age and
Gender - As Consumed 3-36
Table 3-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender -
Uncooked Fish Weight 3-37
Table 3-9. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender -
Uncooked Fish Weight 3-38
Table 3-10. Mean and 95th Percentile of Fish Consumption (g/day) by Sex and Age 3-39
Table 3-11. Best Fits of Lognormal Distributions Using the Nonlinear Optimization (Nlo)
Method 3-40
vi
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LIST OF TABLES (Continued)
Table 3-12. Number of Respondents Reporting Consumption of a Specified Number of
Servings of Seafood in 1 Month and Source of Seafood Eaten 3-40
Table 3-13. Mean Fish Intake Among Individuals Who Eat Fish and Reside in Households
With Recreational Fish Consumption 3-41
Table 3-14. Children's 5 and Under Fish Consumption Rates - Throughout Year 3-41
Table 3-15. Fat Intake Among Children Based on Data from the Bogalusa Heart Study,
1973-1982 (g/day) 3-42
Table 3-16. Fat Intake Among Children Based on Data from the Bogalusa Heart Study,
1973-1982 (g/kg/day) 3-43
Table 3-17. Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gender .... 3-44
Table 3-18. Per Capita Total Dietary Intake 3-45
Table 3-19. Per Capita Intake of Major Food Groups (g/day, as consumed) 3-46
Table 3-20. Per Capita Intake of Major Food Groups (g/kg/day, as consumed) 3-48
Table 3-21. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total
Food Intake for Individuals with Low-end, Mid-range, and High-end Total
Food Intake 3-50
Table 3-22. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total
Food Intake for Individuals with Low-end, Mid-range, and High-end Total
Meat Intake 3-52
Table 3-23. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total
Food Intake for Individuals with Low-end, Mid-range, and High-end Total Meat and
Dairy Intake 3-54
Table 3-24. Per Capita Intake of Total Foods and Major Food Groups, and Percent of
Total Food Intake for Individuals with Low-end, Mid-range, and High-end Total Fish
Intake 3-56
Table 3-25. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total
Food Intake for Individuals with Low-end, Mid-range, and High-end Total Fruit and
Vegetable Intake 3-58
Table 3-26. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total
Food Intake for Individuals with Low-end, Mid-range, and High-end Total
Dairy Intake 3-60
Table 3-27. Weighted and Unweighted Number of Observations (Individuals) for NFCS Data
Used in Analysis of Food Intake 3-62
Table 3-28. Consumer Only Intake of Homegrown Foods (g/kg-day)a - All Regions
Combined 3-63
Table 3-29. Percent Weight Losses from Food Preparation 3-64
Table 3-30. Quantity (as consumed) of Food Groups Consumed Per Eating Occasion and the
Percentage of Individuals Using These Foods in Three Days 3-65
Table 3-31. Mean Moisture Content of Selected Food Groups Expressed as Percentages of
Edible Portions 3-67
Table 3-32. Percent Moisture Content for Selected Fish Species 3-71
vii
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LIST OF TABLES (Continued)
Table 3-33. Percentage Lipid Content (Expressed as Percentages of 100 Grams of
Edible Portions) of Selected Meat, Dairy, and Fish Products 3-74
Table 3-34. Fat Content of Meat Products 3-78
Table 3-35. Summary of Recommended Values for Per Capita Intake of Foods, As
Consumed 3-79
Table 3-36. Confidence Intake Recommendations for Various Foods, Including Fish
(General Population) 3-81
Table 3-37. Confidence Intake Recommendations for Fish Consumption - Recreational
Freshwater Angler Population 3-82
Table 3-38. Confidence Intake Recommendations for Fish Consumption - Native American
Subsistence Population 3-83
Table 4-1. Estimated Direct and Indirect Community Total Water Ingestion By Source
for U.S. Population 4-10
Table 4-2. Estimate of Total Direct and Indirect Water Ingestion, All Sources By Broad
Age Category for U.S. Children 4-11
Table 4-3. Estimate of Direct and Indirect Community Water Ingestion By Fine Age
Category for U.S. Children 4-12
Table 4-4. Estimate of Direct and Indirect Community Water Ingestion By Broad Age
Category for U.S. Children 4-13
Table 4-5. Estimate of Direct and Indirect Bottled Water Ingestion By Fine Age Category
for U.S. Children 4-14
Table 4-6. Estimate of Direct and Indirect Bottled Water Ingestion By Broad Age Category
for U.S. Children 4-15
Table 4-7. Estimate of Direct and Indirect Other Water Ingestion By Fine Age Category
for U.S. Children 4-16
Table 4-8. Estimate of Direct and Indirect Other Water Ingestion By Broad Age Category
for U.S. Children 4-17
Table 4-9. Chi-square GOF statistics for 12 Models, Tapwater Data, Based on Maximum
Likelihood Method of Parameter Estimation 4-18
Table 4-10. P-Values for Chi-Square GOF Tests of 12 Models, Tapwater Data 4-18
Table 4-11. Results of Statistical Modeling of Tapwater Data (intake Rates in dL/kg-day)
Using 5-Parameter Generalized F and 2-Parameter Gamma, Lognormal and Weibull
Modles 4-19
Table 4-12. Total Fluid Intake of Women 15-49 Years Old 4-20
Table 4-13. Total Tapwater Intake of Women 15-49 Years Old 4-20
Table 4-14. Total Fluid (mL/Day) Derived from Various Dietary Sources by Women Aged
15-49 Years 4-21
Table 4-15. Summary of Recommended Community Drinking Water Intake Rates 4-22
Table 4-16. Confidence in Tapwater Intake Recommendations 4-23
Table 5-1. Estimated Daily Soil Ingestion Based on Aluminum, Silicon, and Titanium
Concentrations 5-29
viii
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LIST OF TABLES (Continued)
Table 5-2. Calculated Soil Ingestion by Nursery School Children 5-30
Table 5-3. Calculated Soil Ingestion by Hospitalized, Bedridden Children 5-31
Table 5-4. Mean and Standard Deviation Percentage Recovery of Eight Tracer Elements .. 5-31
Table 5-5. Soil and Dust Ingestion Estimates for Children Ages 1-4 Years 5-32
Table 5-6. Average Daily Soil Ingestion Values Based on Aluminum, Silicon, and Titanium
as Tracer Elements 5-32
Table 5-7. Geometric Mean (Gm) and Standard Deviation (Gsd) Ltm Values for Children at
Daycare Centers and Campgrounds 5-33
Table 5-8. Estimated Geometric Mean Ltm Values of Children Attending Daycare Centers
According to Age, Weather Category, and Sampling Period 5-34
Table 5-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64
Children (Mg/day) 5-35
Table 5-10. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on
Data for 64 Subjects Projected over 365 Days 5-35
Table 5-11. Estimated Soil Ingestion Rate Summary Statistics And Parameters for Distributions
Using Binder et Al. (1986) Data with Actual Fecal Weights 5-36
Table 5-12. 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) .... 5-37
Table 5-13. Soil Ingestion Estimates for Median and Best Four Trace Elements Based on
Food/Soil Ratios for 64 Anaconda Children (mg/day) Using Al, Si, Ti, Y, and Zr . . . 5-38
Table 5-14. Dust Ingestion Estimates for Median and Best Four Trace Elements Based
on Food/Soil Ratios for 64 Anaconda Children (mg/day) Using Al, Si, Ti, Y, and Zr 5-39
Table 5-15. Daily Soil Ingestion Estimation in a Soil-pica Child by Tracer and by Week
(mg/day) 5-40
Table 5-16. Ratios of Soil, Dust, and Residual Fecal Samples in the Soil Pica Child 5-41
Table 5-17. Daily variation of Soil Ingestion by Children Displaying Soil Pica in
Wong (1988) 5-42
Table 5-18. Prevalence of Non-Food Ingestion Mouthing Behaviors by Child's Age:
Percent of Children Whose Parents Reports the Behavior in the Past Month 5-43
Table 5-19. Average Outdoor Object Mouthing Scores for Children by Age, Frequency of
Sand/Dirt Play, and General Mouthing Quartiles 5-46
Table 5-20. Summary of Estimates of Soil Ingestion by Children 5-47
Table 5-21. Summary of Recommended Values for Soil Ingestion 5-47
Table 5-22. Confidence in Soil Intake Recommendation 5-48
Table 6-1. Extrapolated Total Mouthing Times Minutes per Day (time awake) 6-12
Table 6-2. Frequency of Contact, by Contact Variable Contacts per Hour 6-13
Table 6-3. Summary of Studies on Mouthing Behavior 6-14
Table 6-4. Summary of Mouthing Frequency Data 6-15
Table 6-5. Confidence in Mouthing Behavior Recommendations 6-16
Table 7-1. Calibration And Field Protocols For Self-monitoring of Activities
Grouped by Subject Panels 7-10
IX
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LIST OF TABLES (Continued)
Table 7-2. Subject Panel Inhalation Rates by Mean VR, Upper Percentiles,
And Self-estimated Breathing Rates 7-10
Table 7-3. Distribution of Predicted Intake Rates by Location And Activity Levels
For Elementary And High School Students 7-11
Table 7-4. Average Hours Spent Per Day in a Given Location and Activity
Level For Elementary (EL) and High School (HS) Students 7-11
Table 7-5. Distribution Patterns of Daily Inhalation Rates For Elementary (EL) And
High School (HS) Students Grouped by Activity Level 7-12
Table 7-6. Summary of Average Inhalation Rates (M3/hr) by Age Group And Activity Levels
For Laboratory Protocols 7-13
Table 7-7. Summary of Average Inhalation Rates (M3/hr) by Age Group And Activity
Levels in Field Protocols 7-14
Table 7-8. Comparisons of Estimated Basal Metabolic Rates (BMR) With Average
Food-energy Intakes For Individuals Sampled in The 1977-78 NFCS 7-15
Table 7-9. Daily Inhalation Rates Calculated From Food-energy Intakes 7-16
Table 7-10. Daily Inhalation Rates Obtained From The Ratios Of Total Energy
Expenditure to Basal Metabolic Rate (BMR) 7-17
Table 7-11. Inhalation Rates For Short-term Exposures 7-18
Table 7-12. Confidence in Inhalation Rate Recommendations 7-19
Table 7-13. Summary of Recommended Values For Inhalation 7-20
Table 7-14. Summary of Children's Inhalation Rates For Short-Term Exposure Studies . . . 7-21
Table 8-1. Total Body Surface Area of Male Children in Square Meters 8-17
Table 8-2. Total Body Surface Area of Female Children in Square Meters 8-18
Table 8-3. Percentage of Total Body Surface Area by Body Part For Children 8-19
Table 8-4. Descriptive Statistics For Surface Area/body Weight (SA/BW) Ratios (m2/kg) . . 8-20
Table 8-5. Clothing choices and assumed body surface areas exposed 8-21
Table 8-6. Estimated skin surface exposed during warm weather outdoor play for children
under age 5 (based on SCS-I data) 8-21
Table 8-7. Number and percentage of respondents with children and those reporting
outdoor play activities in both warm and cold weather 8-22
Table 8-8. Play frequency and duration for all child players (from SCS-II data) 8-22
Table 8-9. Hand washing and bathing frequency for all child players (from SCS-II data) . . . 8-23
Table 8-10. NHAPS and SCS-II play duration comparison 8-23
Table 8-11. NHAPS and SCS-II hand wash frequency comparison 8-24
Table 8-12. Summary of Field Studies 8-25
Table 8-13. Geometric Mean And Geometric Standard Deviations of Soil Adherence
by Activity And Body Region 8-26
Table 8-14. Summary of Groups Assayed in Round 2 of Field Measurements 8-27
Table 8-15. Attire for Individuals within Children's Groups Studied 8-28
x
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LIST OF TABLES (Continued)
Table 8-16. Geometric Means (Geometric Standard Deviations) of Round 2 Post-activity
Loadings 8-29
Table 8-17. Summary of Controlled Green House Trials - Children Playing 8-30
Table 8-18. Preactivity Loadings Recovered from Greenhouse Trial Children Volunteers .. 8-31
Table 8-19. Summary of Recommended Values For Skin Surface Area 8-33
Table 8-20. Confidence in Body Surface Area Measurement Recommendations 8-34
Table 8-21. Confidence in Soil Adherence to Skin Recommendations 8-35
Table 9-1. Mean Time Spent (minutes) Performing Major Activities Grouped by Age,
Sex and Type of Day 9-15
Table 9-2. Mean Time Spent (minutes) in Major Activities Grouped by Type of Day for
Five Different Age Groups 9-16
Table 9-3. Mean Time Spent Indoors and Outdoors Grouped by Age and Day of the
Week 9-17
Table 9-4. Mean Time Spent at Three Locations for both CARB and National Studies
(ages 12 years and older) 9-18
Table 9-5. Mean Time Spent (minutes/day) in Various Microenvironments Grouped by
Total Population and Gender (12 years and over) in the National and CARB Data . . 9-19
Table 9-6. Mean Time Spent (minutes/day) in Various Microenvironments by Type
of Day for the California and National Surveys 9-20
Table 9-7. Mean Time Spent (minutes/day) in Various Microenvironments by Age Groups
for the National and California Surveys 9-21
Table 9-8. Mean Time (minutes/day) Children Ages 12 Years and Under Spent in Ten Major
Activity Categories for All Respondents 9-22
Table 9-9. Mean Time Children Spent in Ten Major Activity Categories Grouped by Age and
Gender 9-23
Table 9-10. Mean Time Children Ages 12 Years and Under Spent in Ten Major Activity
Categories Grouped by Seasons and Regions 9-24
Table 9-11. Mean Time Children Ages 12 Years and Under Spent in Six Major Location
Categories for All Respondents (minutes/day) 9-25
Table 9-12. Mean Time Children Spent in Six Location Categories Grouped by Age and
Gender 9-25
Table 9-13. Mean Time Children Spent in Six Location Categories Grouped by Season and
Region 9-26
Table 9-14. Mean Time Children Spent in Proximity to Three Potential Exposures Grouped by
All Respondents, Age, and Gender 9-26
Table 9-15. Mean Time Spent Indoors and Outdoors Grouped by Age 9-31
Table 9-16. Range of Recommended Defaults for Dermal Exposure Factors 9-32
Table 9-17. Number of Times Taking a Shower at Specified Daily Frequencies by the Number of
Respondents 9-32
XI
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LIST OF TABLES (Continued)
Table 9-18. Time (minutes) Spent Taking a Shower and Spent in the Shower Room
After Taking a Shower by the Number of Respondents 9-32
Table 9-19. Time (minutes) Spent Taking a Shower and Spent in the Shower Immediately
After Showering 9-33
Table 9-20. Total Time Spent Altogether in the Shower or Bathtub and Time Spent
in the Bathroom Immediately After by Number of Respondents 9-33
Table 9-21. Total Number of Minutes Spent Altogether in the Shower or Bathtub and Spent
in the Bathroom Immediately Following a Shower or Bath 9-34
Table 9-22. Range of Number of Times Washing the Hands at Specified Daily Frequencies
by the Number of Respondents 9-34
Table 9-23. Number of Minutes Spent Working or Being Near Excessive Dust in the Air
(minutes/day) 9-34
Table 9-24. Range of Number of Times per Day a Motor Vehicle was Started in a Garage
or Carport and Started with the Garage Door Closed 9-35
Table 9-25. Number of Minutes Spent Playing on Sand, Gravel, Dirt, or Grass 9-35
Table 9-26. Number of Minutes Spent Playing in Sand, Gravel, Dirt or Grass
(minutes/day) 9-36
Table 9-27. Range of Number of Minutes Spent Playing on Grass in a Day by the Number of
Respondents 9-36
Table 9-28. Number of Minutes Spent Playing on Grass (minutes/day) 9-36
Table 9-29. Number of Times Swimming in a Month in Freshwater Swimming Pool by the
Number of Respondents 9-37
Table 9-30. Number of Minutes Spent Swimming in a Month in Freshwater Swimming Pool
(minutes/month) 9-37
Table 9-31. Range of the Average Amount of Time Actually Spent in the Water by Swimmers
by the Number of Respondents 9-37
Table 9-32. Statistics for 24-Hour Cumulative Number of Minutes Spent Playing Indoors and
Outdoors 9-38
Table 9-33. Statistics for 24-Hour Cumulative Number of Minutes Spent Sleeping/Napping 9-38
Table 9-34. Statistics for 24-Hour Cumulative Number of Minutes Spent Attending Full Time
School 9-38
Table 9-35. Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports
and for Time Spent in Sports/Exercise 9-39
Table 9-36. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Recreation
and Spent Walking 9-39
Table 9-37. Statistics for 24-Hour Cumulative Number of Minutes Spent in Bathing 9-40
Table 9-38. Statistics for 24-Hour Cumulative Number of Minutes Eating or Drinking .... 9-40
Table 9-39. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at School
and Indoors at a Restaurant 9-40
Table 9-40. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on
School Grounds/Playground, at a Park/Golf Course, and at a Pool/River/Lake 9-41
Xll
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LIST OF TABLES (Continued)
Table 9-41. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Kitchen
Bathroom, Bedroom, and in a Residence (All Rooms) 9-42
Table 9-42. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling Inside a
Vehicle 9-43
Table 9-43. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors (outside the
residence) and Outdoors Other Than Near a Residence or Vehicle, Such as Parks, Golf
Courses, or Farms 9-43
Table 9-44. Statistics for 24-Hour Cumulative Number of Minutes Spent in Malls, Grocery
Stores, or Other Stores 9-43
Table 9-45. Statistics for 24-hour Cumulative Number of Minutes Spent with Smokers
Present 9-44
Table 9-46. Range of Time (minutes) Spent Smoking Based on the Number of
Respondents 9-45
Table 9-47. Number of Minutes Spent Smoking (minutes/day) 9-45
Table 9-48. Gender and Age Groups 9-46
Table 9-49. Assignment of At-Home Activities to Ventilation Levels for Children 9-47
Table 9-50. Aggregate Time Spent (minutes/day) At-Home in Activity Groups
by Adolescents and Children 9-48
Table 9-51. Comparison of Mean Time (minutes/day) Spent At-Home by Gender
(Adolescents) 9-48
Table 9-52. Comparison of Mean Time (minutes/day) Spent At-Home by Gender and Age
for Children 9-48
Table 9-53. Number of Person-Days/Individualsa for Children in CHAD Database 9-49
Table 9-54. Number of Hours Per Day Children Spend in Various Microenvironments by Age
Average ฑ Std. Dev. (Percent of Children Reporting >0 Hours in Microenvironment) 9-50
Table 9-55. Average Number of Hours Per Day Children Spend Doing Various
Macroactivities While Indoors at Home by Age 9-51
Table 9-56. Confidence in Activity Patterns Recommendations 9-52
Table 9-57. Summary of Activity Pattern Studies 9-59
Table 9-58. Summary of Mean Time Spent Indoors and Outdoors from Several Studies . . . 9-60
Table 9-59. Summary of Recommended Values for Activity Factors 9-61
Table 10-1. Consumer Products Found in the Typical U.S. Household 10-4
Table 10-2. Number of Minutes Spent in Activities Working with or Near Household Cleaning
Agents Such as Scouring Powders or Ammonia (minutes/day) 10-7
Table 10-3 Number of Minutes Spent Using Any Microwave Oven (minutes/day) 10-7
Table 10-4. Number of Respondents Using a Humidifier at Home 10-7
Table 10-5. Number of Respondents Indicating that Pesticides Were Applied by the Professional
at Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies .... 10-8
Table 10-6. Number of Respondents Reporting Pesticides Applied by the Consumer at Home
To Eradicate Insects, Rodents, or Other Pests at Specified Frequencies 10-8
Xlll
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LIST OF TABLES (Continued)
Table 11-1. Smoothed Percentiles of Weight (In Kg) by Sex And Age: Statistics From
NCHS And Data From Fels Research Institute, Birth to 36 Months 11-6
Table 11-2. Body Weights of Childrenฎ (Kilograms) 11-9
Table 11-3. Weight in Kilograms For Males 6 Months-19 Years of Age-number Examine, Mean,
Standard Deviation, and Selected Percentiles, by Sex and Age:
United States, 1976-1980 11-10
Table 11-4. Weight in Kilograms For Females 6 Months-19 Years of Age - Number
Examine, Mean, Standard Deviation, And Selected Percentiles, By Sex And Age:
United States, 1976-1980 11-11
Table 11-5. Best-fit Parameters for Lognormal Distributions 11-12
Table 11-6. Statistics for Probability Plot Regression Analyses Male's Body Weights
6 Months to 20 Years of Age 11-13
Table 11-7. Body Weight Estimates (in kilograms) by Age and Gender, U.S. Population
1988-94 11-14
Table 11-8. Body Weight Estimates (in kilograms) by Age, U.S. Population 1988-94 .... 11-15
Table 11-9. Summary of Recommended Values for Body Weight 11-16
Table 11-10. Confidence in Body Weight Recommendations 11-17
Table 12-1. Expectation of Life at Birth, 1980 to 1993, And Projections, 1995 to
2010 (Years) 12-4
Table 12-2. Expectation of Life by Race, Sex, And Age: 1996 12-5
Table 12-3. Confidence in Lifetime Expectancy Recommendations 12-6
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LIST OF FIGURES
Figure 1-1. Schematic of Dose and Exposure: Oral Route 1-12
Figure 8-1. Schematic of Dose and Exposure: Dermal Route 8-2
Figure 8-2. Skin Coverage as Determined by Fluorescence vs. Body Part for Adults
Transplanting Plants and for Children Playing in Wet Soils 8-32
Figure 8-3. Gravimetric Loading vs. Body Part for Adult Transplanting Plants in Wet Soil
and for Children Playing in Wet and Dry Soils 8-32
Figure 9-1. Distribution of the Number of Hours per Day Study Children Spent Indoors
at Home 9-27
Figure 9-2. Distribution of the Number of Hours per Day Study Children Spent Indoors
Away from Home 9-28
Figure 9-3. Distribution of the Number of Hours per Day Study Children Spent Outdoors
at Home 9-29
Figure 9-4. Distribution of the Number of Hours per Day Study Children Spent Outdoors
Away from Home 9-30
Figure 11-1. Weight by Age percentiles for Girls Aged Birth-36 Months 11-7
Figure 11-2. Weight by Age Percentiles for Boys Aged Birth-36 Months 11-8
Figure 11-3. Mean Body Weights Estimates, U.S. Population, 1988-94 11-18
Figure 11-4. Median Body Weights Estimates, U.S. Population, 1988-94 11-19
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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 for children. Children are often more heavily exposed to environmental
toxicants than adults. They consume more food and water and have higher inhalation rates per
pound of body weight than adults. Young children play close to the ground and come into
contact with contaminated soil outdoors and with contaminated dust on surfaces and carpets
indoors. As another example, exposure to chemicals in breast milk affects infants and young
children.
The National Center for Environmental Assessment has published the Exposure Factors
Handbook in 1997. This document includes exposure factors and related data on children, as well
as adults. However, the EPA Program Offices have identified the need to prepare a document
specifically for children's exposure factors. The goal of the Child-Specific Exposure Factors
Handbook is to fulfill this need.
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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.
The Exposure Factors Handbook was first published in 1989 to provide statistical data on
the various factors used in assessing exposure for the general population; it was revised and
published again in 1997. This Child-Specific Exposure Factors Handbook is being prepared to
focus on various factors used in assessing exposure, specifically for children ages 0-19 years old.
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.
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AUTHORS, CONTRIBUTORS, AND REVIEWERS
The National Center for Environmental Assessment (NCEA), Office of Research and
Development was responsible for the preparation of this handbook. This document has been
prepared by the Exposure Assessment Division of Versar Inc. in Springfield, VA under EPA
Contract No. 68-W-99-041, Work Assignments Nos 1-10 and 2-11. Jackie Moya served as
Work Assignment Manager, providing overall direction, technical assistance, and serving as
contributing author.
AUTHORS WORD PROCESSING
Versar Inc. Versar Inc.
Linda Phillips Susan Perry
Patricia Wood Valerie Schwartz
Marit Espevik
Todd Perry man
Clarkson Meredith
Didi Sinkowski
U.S. EPA
Jacqueline Moya
The following EPA individuals have reviewed an earlier draft of this document and provided
valuable comments:
Office of Research and Development Amina Wilkins
Office of Water Denis R. Borum
Health and Ecological Criteria Division
EPA Regions Lynn Flowers - Region III
Youngmoo Kim - Region VI
National Exposure Research Laboratory Tom McCurdy
Nicole Tulve
Valerie Zartarian
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 analysis of mouthing behavior data from the Davis 1995 study. Data
analysis was conducted by Nicolle Tulve.
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TABLE OF CONTENTS
1. INTRODUCTION 1-1
1.1 BACKGROUND 1-1
1.2 PURPOSE 1-3
1.3 INTENDED AUDIENCE 1-3
1.4 SELECTION OF STUDIES FOR THE HANDBOOK 1-4
1.5 APPROACH USED TO DEVELOP RECOMMENDATIONS FOR EXPOSURE
FACTORS 1-6
1.6 CHARACTERIZING VARIABILITY 1-7
1.7 USING THE HANDBOOK IN AN EXPOSURE ASSESSMENT 1-10
1.7.1 General Equation for Calculating Dose 1-11
1.8 FUTURE OR ON-GOING WORK 1-15
1.9 RESEARCH NEEDS 1-16
1.10 ORGANIZATION 1-17
1.11 REFERENCES FOR CHAPTER 1 1-19
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LIST OF TABLES
Table 1-1. Considerations Used to Rate Confidence
in recommended Values 1-21
Table 1-2. Summary of Exposure Factor Recommendations
and Confidence Ratings 1-22
Table 1-3. Characterization of Variability in Exposure Factors 1-24
LIST OF FIGURES
Figure 1-1. Schematic of Dose and Exposure: Oral Route 1-12
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1. INTRODUCTION
1.1 BACKGROUND
Because of differences in physiology and behaviors, exposures among children are
expected to be different than among adults. Children may be more highly exposed to
environmental toxicants than adults, because they consume more food and water, and have higher
inhalation rates per unit of body weight, and have higher surface area to volume than adults.
Also, young children play close to the ground and are more likely to come into contact with
contaminated soil outdoors and with contaminated dust on surfaces and carpets indoors. Children
may also be exposed to contaminants as a result of hand-to-mouth and object-to-mouth activities
as a result of behaviors existing during certain phases of childhood. As another example,
exposure to chemicals in breast milk affects specifically infants and young children. In terms of
risk, children may also be more vulnerable to environmental pollutants because of differences in
absorption, excretion, and metabolism (U.S. EPA, 1997a).
In April, 1997, President Clinton signed an Executive Order to Protect Children from
Environmental Health Risks and Safety Risks. The Order requires all federal agencies to address
health and safety risks to children, coordinate research priorities on children's health, and ensure
that their standards take into account special risks to children. To implement the President's
Executive Order, EPA established the Office of Children's Health Protection (OCHP), and offices
within EPA increased their efforts to provide a safe and healthy environment for children by
ensuring that all regulations, standards, policies, and risk assessments take into account risks to
children. Recent legislation, such as the Food Quality Protection Act and the Safe Drinking
Water Act amendments, has made children's health issues more explicit and research on children's
health issues is continually expanding. As a result of the emphasis on children's risk, the EPA
Office of Research and Development's (ORD) National Center for Environmental Assessment
(NCEA) issued a Children's Risk Policy, which emphasized the need to evaluate exposures and
risks among this population and ORD developed a Strategy for Research on Risks to Children
(Children's Research Strategy) (U.S. EPA, 1997a; 1999a). The goal of the Children's Research
Strategy is to improve risk assessments for children. This Child-specific Exposure Factors
Handbook is intended to support EPA/ORD/NCEA's efforts to improve exposure and risk
assessments for children.
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In 1997, EPA/ORD/NCEA published the Exposure Factors Handbook (U.S. EPA,
1997b). The Handbook includes exposure factors and related data on both adults and children.
OCHP's recently-issued its child-related risk assessment policy and methodology guidance
document survey (U.S. EPA, 1999b), highlighted the Exposure Factors Handbook (U.S. EPA,
1997b) as a source of information on exposure factors for children. EPA's Children's
Environmental Health Yearbook (U.S. EPA, 1998) also listed the Exposure Factors Handbook as
a source of exposure information for children. However, the EPA Program Offices identified the
need to consolidate all children exposure data into one document. The goal of this Child-specific
Exposure Factors Handbook is to fulfill this need. This Handbook provides non-chemical-
specific data on exposure factors that can be used to assess doses from dietary and non-dietary
ingestion exposure, dermal exposure, and inhalation exposure among children.
This handbook provides exposure factors for children in the following areas:
breast milk ingestion;
food ingestion, including homegrown foods and other dietary-related data;
drinking water ingestion;
soil ingestion;
rates of hand-to-mouth and object-to-mouth activity;
dermal exposure factors such as surface areas and soil adherence;
inhalation rates;
duration and frequency in different locations and various microenvironments;
duration and frequency of consumer product use;
body weight data; and
duration of lifetime.
This handbook is a compilation of available data from a variety of sources. Most of these
data have been described in detail in EPA's Exposure Factors Handbook (1997b), but data that
have been published subsequent to release of the Exposure Factors Handbook are also presented.
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
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different age ranges to describe data for children. 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.
1.2 PURPOSE
The purpose of the Child-specific Exposure Factors Handbook is to: (1) summarize key
data on human behaviors and characteristics which affect children's 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 data presented in this handbook have
come from various sources, including the EPA's Exposure Factor Handbook (U.S. EPA, 1997b),
government reports, and information presented in the scientific literature. The handbook has
strived to include discussions of the issues which assessors should consider in assessing exposure
among children, and may be used in conjunction with the EPA document: EPA/600/R-99/060
July 1999, entitled Socio-demographic Data Usedfor Identifying Potentially Highly Exposed
Subpopulations of Children, which is currently being drafted and provides population data for
children.
1.3 INTENDED AUDIENCE
The Child-specific Exposure Factors Handbook may be used by exposure assessors inside
the Agency as well as outside, who need to obtain data on standard factors needed to calculate
childhood exposure to toxic chemicals.
1.4 SELECTION OF STUDIES FOR THE HANDBOOK
Information in this handbook has been summarized from studies documented in the
scientific literature and other available sources. Studies were chosen that were seen as useful and
appropriate for estimating exposure factors. The handbook contains summaries of selected
studies published through 2000.
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General Considerations
Many scientific studies were reviewed for possible inclusion in this handbook. Generally,
studies identified in the Exposure Factors Handbook (U.S. EPA, 1997b) as key studies were also
included in this children's document. New studies that became available after publication of the
Exposure Factors Handbook were also included. Key studies from the Exposure Factors
Handbook were generally defined as the most useful for deriving exposure factors. The
recommended values for most exposure factors are based on the results of these studies. As in
the Exposure Factors Handbook, the key studies were selected based on the following
considerations:
Level of peer review. Studies were selected predominantly from the peer-reviewed
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.
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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 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.
1.5 APPROACH USED TO DEVELOP RECOMMENDATIONS FOR
EXPOSURE FACTORS
As discussed above, EPA first reviewed all literature pertaining to a factor and determined
key studies. These key studies were used to derive recommendations for the values of each
factor. The recommended values were derived solely from EPA's interpretation of the available
data. Different values may be appropriate for the user to select in consideration of policy,
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precedent, strategy, or other factors such as site-specific information. EPA's procedure for
developing recommendations was as follows:
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 1.4.
2. If only one study was classified as key for a particular factor, the mean value from that
study was selected as the recommended central 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 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 1.4. 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.
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Table 1-2 summarizes EPA's recommendations and confidence ratings for the various exposure
factors that apply to children.
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.
1.6 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.
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The term upper percentile is used throughout this handbook and it is intended to represent values
in the upper tail (i.e., between 90th and 99.9th percentile) of the distribution of values for a
particular exposure factor.
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 exposure 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:
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.
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.
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 that in
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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.
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;
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.
1.7 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);
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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).
Guiding Principles for Monte Carlo Assessments.
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.
Most of the data presented in this handbook are derived from studies that targeted (1) the
general population (e.g., USDA food consumption 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: EPA/600/R-99/060 July 1999, entitled, Socio-
demographic Data Usedfor Identifying Potentially Highly Exposed Subpopulations.
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1.7.1 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, 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 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.
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
ADD
Body Weight x Averaging Time
(1-1)
Total Potential Dose = C x IR x ED
(1-2)
Where:
C = Contaminant Concentration
IR = Intake Rate
ED = Exposure Duration
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Exposure
Chemical
Potential
Dose
Applied
Dose
Mouth
Internal
Dose
Metabolism
G.I. Tract
Biologically
Effective
Dose
Organ
Effect
Intake
Uptake
Figure 1-1. Schematic of Dose and Exposure: Oral Route
Source: U.S. EPA, 1992a
Contaminant concentration is the concentration of the contaminant in the medium (air,
food, soil, etc.) contacting the body and has units of mass/volume or mass/mass.
The intake rate refers to the rates of inhalation, ingestion, and dermal contact depending
on the route of exposure. For ingestion, the intake rate is simply the amount of food containing
the contaminant of interest that an individual ingests during some specific time period (units of
mass/time). Much of this handbook is devoted to rates of ingestion for some broad classes of
food. For inhalation, the intake rate is the rate at which contaminated air is inhaled. Factors 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 (Chapter 9) 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.
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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.
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 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 first-generation
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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 the Exposure Factors Handbook (U.S. EPA,
1997b). 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
presentation in this handbook. Data on the general population fish consumption have been
presented in this handbook (Chapter 3) in both "as consumed" and uncooked basis. It is
important for the assessor to be aware 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 (e.g., serving size per event). The
duration should be based on the number of events or, in this case, meals.
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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.
1.8 FUTURE OR ON-GOING WORK
EPA is also developing guidance on the use of exposure factors data. For future
information on the status of this guidance, it is recommended to consult the EPA National Center
for Environmental Assessment homepage (www.epa.gov/nceay Another on-going effort is the
Risk Assessment Forum project on defining age groups for children that are appropriate for use in
risk assessment.
1.9 RESEARCH NEEDS
The data for several exposure factors for children are limited. The following list is a
compilation of areas for future research related to childhood exposure factors:
More recent information is needed on breastmilk consumption.
Information on children's food handling practices that might exacerbate exposure is
needed to better characterize exposures among children.
Further research on fish intake among children, particularly recreational and
subsistence populations, is needed.
Research is needed to better estimate soil intake rates, particularly on how to
extrapolate short-term data to chronic exposures. Research is also needed to refine
the methods to calculate soil intake rates (i.e., inconsistencies among tracers and
input/output misalignment errors indicate a fundamental problem with the methods).
Additional information on soil ingestion among children that provides better estimates
of upper percentile rates is needed, in particular.
Further research is needed on non-dietary ingestion exposure factors, such as the
microenvironments in which children spend time and the types of materials that they
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contact, as well as information on the rate at which they contact contaminated
surfaces, the fraction of the contaminants that are transferred to skin and object
surfaces, and the amount of the object/skin entering the mouth.
Additional data on dermal exposure factors, such as the microenvironments in which
children spend time and the types of materials that they contact, as well as information
on the rate at which they contact contaminated surfaces, and the fraction of the
contaminants that are transferred to skin and object surfaces.
Further research is needed to obtain better soil adherence rates for additional activities
involving children.
Further data is needed on the frequency of use and kinds of consumer products used
by children.
Additional information on derivation of new surface area based on newer body weight
data.
Additional data on inhalation rates that are specific to children's activities are needed.
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.
Research is needed to derive a methodology to extrapolate from short-term data to
long-term or chronic exposures.
Further research is needed to estimate food consumption rates by children based on
the CSFII supplemental survey on children.
Regarding breast milk ingestion, research is needed on incidence and duration of
breast feeding.
1.10 ORGANIZATION
The handbook is organized as follows:
Chapter 1 Provides the overall introduction to the handbook
Chapter 2 Provides factors for estimating exposure through ingestion of breastmilk
Chapter 3 Provides factors for estimating human exposure through ingestion foods,
including fish
Chapter 4 Provides factors for estimating exposure through ingestion of drinking
water
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Chapter 5 Provides factors for estimating exposure as a result of ingestion of soil
Chapter 6 Presents factors for estimating exposure to environmental contaminants
from other non-dietary ingestion such as hand-to-mouth and object-to-
mouth activity
Chapter 7 Provides factors for estimating exposure as a result of inhalation of vapors
and particulates
Chapter 8 Provides factors for estimating dermal exposure to environmental
contaminants that come in contact with the skin
Chapter 9 Presents data on activity factors (activity patterns, population mobility, and
occupational mobility)
Chapter 10 Presents data on consumer product use
Chapter 11 Presents data on body weight
Chapter 12 Presents data on lifetime
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53
54
1.11 REFERENCES FOR CHAPTER 1
Calabrese, E.J.; Pastides, H.; Barnes, R.; Edwards, C.; Kostecki, P.T.; et al. (1989) How much soil do young
children ingest: an epidemiologic study. In: Petroleum Contaminated Soils, Lewis Publishers, Chelsea, MI.
pp. 363-397.
Gilbert, R.O. (1987) Statistical methods for environmental pollution monitoring. New York: VanNostrand
Reinhold.
U.S. EPA. (1983-1989) Methods for assessing exposure to chemical substances. Volumes 1-13. Washington, DC:
Office of Toxic Substances, Exposure Evaluation Division.
U.S. EPA. (1984) Pesticide assessment guidelines subdivision K, exposure: reentry protection. Office of Pesticide
Programs, Washington, DC. EPA/540/9-48/001. Available from NTIS, Springfield, VA; PB-85-120962.
U.S. EPA. (1986a) Standard scenarios for estimating exposure to chemical substances during use of consumer
products. Volumes I and II. Washington, DC: Office of Toxic Substance, Exposure Evaluation Division.
U.S. EPA. (1986b) Pesticide assessment guidelines subdivision U, applicator exposure monitoring. Office of
Pesticide Programs, Washington, DC. EPA/540/9-87/127. Available from NTIS, Springfield, VA;
PB-85-133286.
U.S. EPA. (1987) Selection criteria for mathematical models used in exposure assessments: surface water models.
Exposure Assessment Group, Office of Health and Environmental Assessment, Washington, DC.
WPA/600/8-87/042. Available from NTIS, Springfield, VA; PB-88-139928/AS.
U.S. EPA. (1988a) Superfund exposure assessment manual. Office of Emergency and Remedial Response,
Washington, DC. EPA/540/1-88/001. Available from NTIS, Springfield, VA; PB-89-135859.
U.S. EPA. (1988b) Selection criteria for mathematical models used in exposure assessments: groundwater models.
Exposure Assessment Group, Office of Health and Environmental Assessment, Washington, DC.
EPA/600/8-88/075. Available from NTIS, Springfield, VA; PB-88-248752/AS.
U.S. EPA. (1989) Risk assessment guidance for Superfund. Human health evaluation manual: part A. Interim
Final. Office of Solid Waste and Emergency Response, Washington, DC. Available from NTIS, Springfield,
VA; PB-90-155581.
U.S. EPA. (1990) Methodology for assessing health risks associated with indirect exposure to combustor emissions.
EPA 600/6-90/003. Available from NTIS, Springfield, VA; PB-90-187055/AS.
U.S. EPA. (1992a) Guidelines for exposure assessment. Washington, DC: Office of Research and Development,
Office of Health and Environmental Assessment. EPA/600/Z-92/001.
U.S. EPA. (1992b) Dermal exposure assessment: principles and applications. Washington, DC: Office of Health
and Environmental Assessments. EPA/600/8-9/01 IF.
U.S. EPA. (1994) Estimating exposures to dioxin-like compounds. (Draft Report). Office of Research and
Development, Washington, DC. EPA/600/6-88/005Cb.
U.S. EPA. (1997a) Office of Research and Development strategy for research on risks to children. Washington,
DC: Office of Research and Development, Science Council Review Draft.
U.S. EPA. (1997b) Exposure factors handbook. Washington, DC: National Center for Environmental
Assessment, Office of Research and Development. EPA/600/P-95/002Fa,b,c.
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U.S. EPA. (1998) The EPA children's environmental health yearbook. Washington, DC: U.S. Environmental
Protection Agency.
U.S. EPA. (1999a) Strategy for research on environmental risks to children. Washington, DC: Office of Research
and Development. External Peer Review Draft.
U.S. EPA. (1999b) Child-related risk assessment policy and methodology guidance document survey, draft report.
Washington, DC: Office of Children's Health Protection.
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Table 1-1. Considerations Used to Rate Confidence
in recommended Values
4
CONSIDERATIONS
HIGH CONFIDENCE
LOW CONFIDENCE
5
Study Elements
6
Level of peer review
The studies received high level of peer
review (e.g., they appear in peer review
journals).
The studies received limited peer review.
7
Accessibility
The studies are widely available to the
public.
The studies are difficult to obtain (e.g.,
draft reports, unpublished data).
8
Reproducibility
The results can be reproduced or
methodology can be followed and
evaluated.
The results cannot be reproduced, the
methodology is hard to follow, and the
author(s) cannot be located.
9
Focus on factor of interest
The studies focused on the exposure
factor of interest.
The purpose of the studies was to
characterize a related factor.
10
Data pertinent to U.S.
The studies focused on the U.S.
population.
The studies focused on populations
outside the U.S.
11
Primary data
The studies analyzed primary data.
The studies are based on secondary
sources.
12
Currency
The data were published after 1990.
The data were published before 1980.
13
Adequacy of data collection period
The study design captures the
measurement of interest (e.g., usual
consumption patterns of a population).
The study design does not very accurately
capture the measurement of interest.
14
Validity of approach
The studies used the best methodology
available to capture the measurement of
interest.
There are serious limitations with the
approach used.
15
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.
16
17
Representativeness of the
population
The study population is the same as
population of interest.
The study population is very different
from the population of interest.3
18
Variability in the population
The studies characterized variability in
the population studied.
The characterization of variability is
limited.
19
20
21
22
23
24
25
26
27
Lack of bias in study design
(a high rating is desirable)
Response rates
In-person interviews
Telephone interviews
Mail surveys
Potential bias in the studies are stated
or can be determined from the study
design.
The response rate is greater than 80
percent.
The response rate is greater than 80
percent.
The response rate is greater than 70
percent.
The study design introduces biases in the
results.
The response rate is less than 40 percent.
The response rate is less than 40 percent.
The response rate is less than 40 percent.
28
Measurement error
The study design minimizes
measurement errors.
Uncertainties with the data exist due to
measurement error.
29
Other Elements
30
Number of studies
The number of studies is greater than 3.
The number of studies is 1.
31
Agreement between researchers
The results of studies from different
researchers are in agreement.
The results of studies from different
researchers are in disagreement.
32
33 a Differences include age, sex, race, income, or other demographic parameters.
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Table 1-2. Summary of Exposure Factor Recommendations
and Confidence Ratings
4
EXPOSURE FACTOR
RECOMMENDATION
CONFIDENCE RATING
5
6
Breast milk intake rate
(1-6 months)
742 ml/day (average)
1,033 ml/day (upper percentile)
Medium
Medium
7
Drinking water intake rate
See Table 4-15 L/day (average)
See Table 4-15 L/day (90th percentile)
High
High
8
Total fruit intake rate
See Table 3-2 (per capita average)
See Table 3-2 (per capita 95th percentile)
High
Low
9
Total vegetable intake rate
See Table 3-2 (per capita average)
See Table 3-2 (per capita 95th percentile)
High
Low
10
Total meat intake rate
See Table 3-2 (per capita average)
See Table 3-2 (per capita 95th percentile)
High
Low
11
Total dairy intake rate
See Table 3-2 (per capita average)
See Table 3-2 (per capita 95th percentile)
High
Low
12
Total grain intake
See Table 3-2 (per capita average)
See Table 3-2 (per capita 95th percentile)
High
Low
13
Fat Intake
See Table 3-15
14
Fish intake rate
General Population
See Table 3-6 (total fish)
See Table 3-6 (marine)
See Table 3-6 (freshwater/estuarine)
Recreational fish intake
1-5 years, 370 mg/kg/day (average)
6-10 years, 280 mg/kg/day (average)
Native American Subsistence Population
<5 vears, 11 g/dav (average)
High (ave.)
Low (upper percentile)
Low
Low
Low
15
Home produced food intake
See Table 3-28
Medium (for means and
short-term distributions)
Low (for long-term
distributions)
16
17
Soil ingestion rate
Children
100 mg/day (average)
400 mg/day (upper percentile)
Pica child
10 g/day
Medium
Low
18
19
20
Inhalation rate
Children (<1 vear)
4.5 m3/day (average)
Children (1-12 vears)
8.7 m3/day (average)
High
High
21
22
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Table 1-2 (Cont'd). Summary of Exposure Factor Recommendations
and Confidence Ratings
4
EXPOSURE FACTOR
RECOMMENDATION
CONFIDENCE RATING
5
Surface area
Water contact (bathing and swimming)
Use total body surface area for children in Tables 8-1
through 8-2;
Soil contact (outdoor activities)
Use body part area based on Table 8-3
High
High
6
Soil adherence
Use values presented in Table 8-13 depending on activity
and body part
(central estimates only)
Low
7
Life expectancy
75 years
High
8
Body weights for children
Use values presented in Tables 11-3 and 11-4 (mean and
percentiles)
High
9
10
Body weights for infants (birth to 6
months)
Use values presented in Table 11-1 (percentiles)
High
11
Showering/Bathing
Showering time
10 min/day (average)
1 shower event/day
High
12
Swimming
Frequencv
1 event/month
Duration
60 min/event (median)
High
High
13
Time indoors
Children (ages 3-5 vears)
19 hr/day
Children (ages 6-14 vears)
20 hr/day
Children (ages 12-17 vears)
19 hrs/day
Medium
High
14
Time outdoors
Children (ages 3-5 vears)
2.8 hr/day
Children (ages 6-8 vears)
2.2 hr/day
Children (ages 9-14 vears)
1.8 hr/day
Children (ages 12-17 vears)
19 hr/day
Medium
High
15
16
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Table 1-3. Characterization of Variability in Exposure Factors
Exposure Factors
Average
Upper percentile
Multiple Percentiles
Fitted Distributions
Breast milk intake rate
~
~
Total intake rate for major food groups
~
~
Qualitative discussion for long-
term
~
Individual food intake rate
~
Drinking water intake rate
~
~
~
~
Fish intake rate for general population,
recreational marine, recreational freshwater,
and Native American
~
~
Serving size for foods
~
~
Home produced food intake rates
~
~
~
Soil intake rate
~
Qualitative discussion for long-
term
Inhalation rate
~
~
~
Surface area
Soil adherence
~
~
~
~
Life expectancy
Body weight
~
~
~
~
Time indoors
Time outdoors
Showering time
Occupational tenure
Population mobility
~
~
~
~
~
~
~
~
~
June 2000
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TABLE OF CONTENTS
2. BREAST MILK INTAKE 2-1
2.1 INTRODUCTION 2-1
2.2 STUDIES ON BREAST MILK INTAKE 2-2
2.3 STUDIES ON LIPID CONTENT AND FAT INTAKE FROM BREAST MILK
2-5
2.4 OTHER FACTORS 2-7
2.5 RECOMMENDATIONS 2-8
2.6 REFERENCES FOR CHAPTER 2 2-10
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LIST OF TABLES
Table 2-1. Daily Intakes of Breast Milk 2-11
Table 2-2. Breast Milk Intake for Infants Aged 1 to 6 Months 2-11
Table 2-3. Breast Milk Intake among Exclusively Breast-fed
Infants During the First 4 Months of Life 2-12
Table 2-4. Breast Milk Intake During a 24-hour Period 2-13
Table 2-5. Breast Milk Intake Estimated by the Darling Study 2-14
Table 2-6. Lipid Content of Human Milk and Estimated Lipid Intake among Exclusively Breast-
fed Infants 2-14
Table 2-7. Predicted Lipid Intakes for Breast-fed Infants under 12 Months of Age 2-14
Table 2-8. Number of Meals per Day 2-15
Table 2-9. Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at
5 or 6 Months Of Age in the United States in 1989a, by Ethnic Background and Selected
Demographic Variables11 2-16
Table 2-10. Confidence in Breast Milk Intake Recommendations 2-17
Table 2-11. Breast Milk Intake Rates Derived from Key Studies 2-18
Table 2-12. Summary of Recommended Breast Milk
And Lipid Intake Rates 2-19
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2. BREAST MILK INTAKE
2.1 INTRODUCTION
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
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among nursing mothers has been reported to be somewhat higher than the amount actually consumed
by the infant (NAS, 1991).
Key studies on breast milk intake are summarized in the following sections. Recommended
intake rates are based on the results of these key studies, as described in the Exposure Factors
Handbook. 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.
2.2 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
(Paoetal., 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 2-1. 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.
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Dewey and Lonnerdal (1983) - Milk and Nutrient Intakes of Breast-fed Infants from 1 to
6 Months - Dewey and Lonnerdal (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 Lonnerdal (1983), the mothers were all well educated and recruited through
Lamaze childbirth classes in the 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 2-2. 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 ฑ3.1
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 2-3). Intakes were also calculated on the basis of
body weight (Table 2-3). Based on the results of test weighings conducted over 48 to 96 hours, the
mean variation in individual daily intake was estimated to be 7.9ฑ3.6 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
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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 etal. (1988) - Studies on Human Lactation - Neville et al. (198 8) 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 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 2-4. 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 2-4 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). Seventy-three 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
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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 2-5). 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.
2.3 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 (39ฑ 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 etal. (1984)-Human Milk Intake and Growth in Exclusively Br east-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 2-6. The overall lipid content for the 4-month study period was 34.3 ฑ 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
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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 day-to-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 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 2-7). 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.
2.4 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
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of meals for these age groups was approximately 5 meals/day (Table 2-8). 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 Br east-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 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 18.1 percent of infants were still breast fed by age 6 months (Ryan,
1997). By 1995, the initiation of breastfeeding had increased to 59.7 percent and the rate of
breastfeeding at 6 months had increased to 21.6 percent (Ryan, 1997). 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 2-9 (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. Lonnerdal 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. Lonnerdal et al. (1976) stated that these results indicate that breast milk quality and
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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 marginally-
nourished women in this study were 690ฑ122 g/day at 3 months, 722ฑ105 g/day at 6 months, and
719ฑ119 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.
2.5 RECOMMENDATIONS
The 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 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. Table 2-10 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 studies described in this section are summarized in Table 2-11. 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 2-11. It
is consistent with the average intake rate of 718 to 777 mL/day estimated by NAS (1991) for infants
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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 2-12 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 ฑ 7.2 g/day (22.9 ฑ 7.0 mL/day) to 28.0 ฑ 8.5 g/day (27.2 ฑ 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 ฑ 7.4 g/day (26.0 ฑ 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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2.6 REFERENCES FOR CHAPTER 2
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.; Lonnerdal, B. (1983) Milk and nutrient intake of breast-fed infants from 1 to 6 months relation to
growth and fatness. Journal of Pediatric Gastroenterology and Nutrition. 2:497-506.
Dewey, K.G.; Heinig, J.; Nommsen, L.A.; Lonnerdal, B. (1991a) Maternal versus infant factors related to breast milk
intake and residual volume: the DARLING study. Pediatrics. 87:829-837.
Dewey, K.G.; Heinig, J.; Nommsen, L.; Lonnerdal, B. (1991b) Adequacy of energy intake among breast-fed infants
in the DARLING study: relationships to growth, velocity, morbidity, and activity levels. The Journal of Pediatrics.
119:538-547.
Hofvandcr. Y.; Hagman, U.; Hillervik, C.; Sjolin, S. (1982) The amount of milk consumed by 1-3 months oldbreast-
or bottle-fed infants. Acta Paediatr. Scand. 71:953-958.
Lonnerdal, B.; Forsum, E.; Gebre-Medhim, M.; Hombraes, L. (1976) Breast milk composition in Ethiopian and
Swedish mothers: lactose, nitrogen, and protein contents. The American Journal of Clinical Nutrition. 29:1134-
1141.
Maxwell, N.I.; Burmaster, D.E. (1993) A simulation model to estimate a distribution of lipid intake from breast milk
during the first year of life. Journal of Exposure Analysis and Environmental Epidemiology. 3:383-406.
National Academy of Sciences (NAS). (1991) Nutrition during lactation. Washington, DC. National Academy Press.
Neville, M.C.; Keller, R.; Seacat, J.; Lutes, V.; Neifert, M.; et al. (1988) Studies in human lactation: milk volumes
in lactating women during the onset of lactation and full lactation. 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 breastfeeding in the United States,
1984-1989. Pediatrics. 88:719-727.
Ryan, A.S. (1997) The resurgence of breastfeeding in the United States. 99(4):el2.
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Table 2-1. Daily Intakes of Breast Milk
3
Range of
4
Number of Infants Surveyed
Mean Intake
Daily Intake
5
Age
at Each Time Period
(mL/day)a
(mL/day)
6
Completely Breast-fed
7
1 month
11
600ฑ 159
426 - 989
8
3 months
2
833
645 - 1,000
9
6 months
1
682
616-786
10
Partially Breast-fed
11
1 month
4
485ฑ 79
398 -655
12
3 months
11
467ฑ 100
242 - 698
13
6 months
6
395ฑ 175
147 - 684
14
9 months
3
<554
451 -732
15
16
aData expressed as mean ฑ standard deviation.
17
18
Source: Pao et al. (1980).
19
20
21
22
23
24
Table 2-2. Breast Milk Intake for Infants Aged 1 to 6 Months
25
26
Age (months)
Number of Infants Mean (mL/day)
SD (mL/day)a
Range (mL/day)
27
1
16 673
192
341-1,003
28
2
19 756
170
449-1,055
29
3
16 782
172
492-1,053
30
4
13 810
142
593-1,045
31
5
11 805
117
554-1,045
32
6
11 896
122
675-1,096
33
34 ^Standard deviation.
35
36 Source: Dewey and Lonnerdal (1983).
37
38
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1
2
Table 2-3. Breast Milk Intake among Exclusively Breast-fed
3
4
Infants During the First 4 Months of Life
5
Number of Infants Breast Milk Intake3
Breast Milk Intake3
Body Weightb
6
Age (months) (g/day)
(g/kg-day)
(kg)
7
1 37 751.0 ฑ130.0
159.0 ฑ24.0
4.7
8
2 40 725.0 ฑ131.0
129.0 ฑ 19.0
5.6
9
3 37 723.0 ฑ114.0
117.0 ฑ20.0
6.2
10
4 41 740.0 ฑ128.0
111.0 ฑ 17.0
6.7
11
12
aData expressed as mean ฑ standard deviation.
13
bCalculated by dividing breast milk intake (g/day) by breast milk intake (g/kg-day).
14
15
Source: Butte etal. (1984).
16
17
18
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6
7
8
9
10
11
12
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15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Table 2-4. Breast Milk Intake During a 24-hour Period
Age
Mean
Standard Deviation
Range
(days)
Number of Infants
(g/day)
(g/day)
(g/day)
1
7
44
71
-31-149 3
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.
Source: Neville et al. (1988).
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1
2
3 Table 2-5. Breast Milk Intake Estimated by the Darling Study
4
5
Age (months) Number of Infants
Mean Intake (g/day) Standard Deviation (g/day)
6
3 73
812
133
7
6 60
769
171
8
9 50
646
217
9
12 42
448
251
10
Source: Dewey etal. (1991b).
11
12
13
14
15
Table 2-6. Lipid Content of Human Milk and Estimated Lipid Intake among Exclusively Breast-fed Infants
16
17
Age (months) Number Lipid
Lipid Lipid
Lipid
of Content
Content Intake
Intake
Observations (mg/g)3
(percent) b (g/day) 3
(g/kg-day)3
18
1 37 36.2 ฑ7.5
3.6 28.0 ฑ8.5
5.9 ฑ 1.7
19
2 40 34.4 ฑ6.8
3.4 25.2 ฑ7.1
4.4 ฑ 1.2
20
3 37 32.2 ฑ7.8
3.2 23.6 ฑ7.2
3.8 ฑ 1.2
21
4 41 34.8 ฑ10.8
3.5 25.6 ฑ8.6
3.8 ฑ 1.3
22
23
aData expressed as means ฑ standard deviations.
24
bPercents calculated from lipid content reported in mg/g.
25
26
Source: Butte, et al. (1984).
27
28
29
30
Table 2-7. Predicted Lipid Intakes for Breast-fed
31
Infants under 12 Months of Age
32
33
Statistic
Value
34
Number of Observations in Simulation
1,113
35
Minimum Lipid Intake
1.0 g/day
36
Maximum Lipid Intake
51.5 g/day
37
Arithmetic Mean Lipid Intake
26.8 g/day
38
Standard Deviation Lipid Intake
7.4 g/day
39
Source: Maxwell and Burmaster (1993).
40
41
42
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Table 2-8. Number of Meals per Day
Age (months) Bottle-fed Infants (meals/day)" Breast-fed (meals/day)"
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.
Source: Hofvander et al. (1982).
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4
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6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
Table 2-9. Percentage of Mothers Breast-feeding Newborn
Infants in the Hospital and Infants at 5 or 6 Months
Of Age in the United States in 1989a, by Ethnic
Background and Selected Demographic Variablesb
Total White Black Hispanic0
Category
Newborns
5-6 Mo
Newborns
5-6 Mo
Newborns
5-6 Mo
Newborns
5-6 Mo
Infants
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
College4
70.7
31.1
74.7
34.1
41.1
12.2
66.5
23.4
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 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.
bBased on data from Ross Laboratories.
'Hispanic is not exclusive of white or black.
dCollege includes all women who reported completing at least 1 year of college.
Source: NAS(1991).
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2
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7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Table 2-10. Confidence in Breast Milk Intake Recommendations
Considerations
Rationale
Rating
Study Elements
Level of peer review
Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data collection period
Validity of approach
Study size
Representativeness of the population
Characterization of variability
Lack of bias in study design (high
rating is desirable)
Measurement error
Other Elements
Number of studies
Agreement between researchers
Overall Rating
All key studies are from peer review literature. High
Papers are widely available from peer review journals. High
Methodology used was clearly presented. High
The focus of the studies was on estimating breast milk intake. High
Subpopulations of the U.S. were the focus of all the key studies. High
All the studies were based on primary data. High
Studies were conducted between 1980-1986. Although incidence Medium
of breast feeding may change with time, breast milk intake among
breastfed infants may not.
Infants were not studied long enough to fully characterize day to Medium
day variability.
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.
The sample sizes used in the key studies were fairly small (range Low
13-73).
Population is not representative of the U.S.; only mid-upper class, Low
well nourished mothers were studied. Socioeconomic factors may
affect the incidence of breastfeeding. Mother's nourishment may
affect milk production.
Not very well characterized. Infants under 1 month not captured, Low
mothers committed to breast feeding over 1 year not captured.
Bias in the studies was not characterized. Three out of 5 studies Low
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).
All mothers were well educated and trained in the use of the scale Medium
which helped minimize measurement error.
There are 5 key studies. High
There is good agreement among researchers. High
Studies were well designed. Results were consistent. Sample Medium
size 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.
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Table 2-11. Breast Milk Intake Rates Derived from Key Studies
Mean (mL/day)
N
Upper Percentile (mL/day)
(mean plus 2 standard deviations)
Reference
Age: 1 Month
600
729
747
673
weighted avg = 702
11
37
13
16
918
981
1,095
1,057
1,007"
Pao et al., 1980
Butte et al., 1984
Neville et al., 1988
Dewey and Lonnerdal, 1983
Age: 3 Months
833
2
...
702
37
923
712
12
934
782
16
1,126
788
73
1,046
weighted avg = 759
1,025"
Pao et al., 1980
Butte et al., 1984
Neville et al., 1988
Dewey and Lonnerdal, 1983
Dewey et al., 1991b
Age: 6Months
682
1
...
744
13
978
896
11
1,140
747
60
1,079
weighted avg = 765
l,059a
Pao et al., 1980
Neville et al., 1988
Dewey and Lonnerdal, 1983
Dewey et al., 1991b
Age: 9 Months
600
627
avg = 622
12
50
1,027
1,049
1,038
Neville et al., 1988
Dewey et al., 1991b
Age: 12 Months
391
435
weighted avg = 427
12-MONTH TIME WEIGHTED AVERAGE
688
9
42
877
923
900
Range 900-1,059
(middle of the range 980)
Neville et al., 1988
Dewey etal., 1991a; 1991b
"Middle of the range.
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7
8
9
10
11
12
13
14
15
Table 2-12. 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
Lipids"
<1 Year 26.0 mL/day 40.4 mL/day
"The recommended value for the lipid content of breastmilk is 4.0 percent.
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TABLE OF CONTENTS
3. FOOD INTAKE 3-1
3.1 INTRODUCTION 3-1
3.2 INTAKE RATE DISTRIBUTIONS FOR VARIOUS FOOD TYPES 3-3
3.3 FISH INTAKE RATES 3-6
3.3.1 General Population Studies 3-6
3.3.2 Freshwater Recreational Study 3-12
3.3.3 Native American Subsistence Study 3-14
3.4 FAT INTAKE 3-15
3.5 TOTAL DIETARY INTAKE AND CONTRIBUTIONS TO DIETARY
INTAKE 3-17
3.6 INTAKE OF HOME-PRODUCED FOODS 3-18
3.7 SERVING SIZE STUDY BASED ON THE USDA NFCS 3-23
3.8 CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE
RATES 3-23
3.9 FAT CONTENT OF MEAT AND DAIRY PRODUCTS 3-24
3.10 RECOMMENDATIONS 3-25
3.11 REFERENCES FOR CHAPTER 3 3-27
APPENDIX 3 a
APPENDIX 3b
APPENDIX 3 c
APPENDIX 3d
Calculations Used in the 1994-96 CSFII Analysis to Correct for Mixtures
Food Codes and Definitions Used in Analysis of the 1994-96 Usda CSFII
Data
Sample Calculation of Mean Daily Fat Intake Based On cdc (1994) Data
Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS
Data
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LIST OF TABLES
Table 3-1. Weighted and Unweighted Number of Observations, 1994/96 CSFII Analysis .. 3-29
Table 3-2. Per Capita Intake of the Major Food Groups (g/kg-day as consumed) 3-30
Table 3-3. Per Capita Intake of Individual Foods (g/kg-day as consumed) 3-31
Table 3-4. Per Capita Intake of USD A Categories of Vegetables and Fruits (g/kg-day as
consumed) 3-33
Table 3-5. Per Capita Intake of Exposed/Protected Fruit and Vegetable Categories (g/kg-day as
consumed) 3-34
Table 3-6. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender - As
Consumed 3-35
Table 3-7. Consumers Only Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender
- As Consumed 3-36
Table 3-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender -
Uncooked Fish Weight 3-37
Table 3-9. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender -
Uncooked Fish Weight 3-38
Table 3-10. Mean and 95th Percentile of Fish Consumption (g/day) by Sex and Agea 3-39
Table 3-11. Best Fits of Lognormal Distributions Using the Nonlinear Optimization (Nlo)
Method 3-40
Table 3-12. Number of Respondents Reporting Consumption of a Specified Number of Servings
of Seafood in 1 Month and Source of Seafood Eaten 3-40
Table 3-13. Mean Fish Intake Among Individuals Who Eat Fish and Reside
in Households With Recreational Fish Consumption 3-41
Table 3-14. Children's 5 and Under Fish Consumption Rates - Throughout Year 3-41
Table 3-15. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-
1982 (g/day) 3-42
Table 3-16. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-
1982 (g/kg/day) 3-43
Table 3-17. Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Genderฎ . . . 3-44
Table 3-18. Per Capita Total Dietary Intake 3-45
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Table 3-19. Per Capita Intake of Major Food Groups (g/day, as consumed) 3-46
Table 3-20. Per Capita Intake of Major Food Groups (g/kg/day, as consumed) 3-48
Table 3-21. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total
Food Intake for Individuals with Low-end, Mid-range, and High-end Total
Food Intake 3-50
Table 3-22. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total
Food Intake for Individuals with Low-end, Mid-range, and High-end Total
Meat Intake 3-52
Table 3-23. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total
Food Intake for Individuals with Low-end, Mid-range, and High-end Total Meat and
Dairy Intake 3-54
Table 3-24. Per Capita Intake of Total Foods and Major Food Groups, and Percent of
Total Food Intake for Individuals with Low-end, Mid-range, and High-end Total Fish
Intake 3-56
Table 3-25. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total
Food Intake for Individuals with Low-end, Mid-range, and High-end Total Fruit and
Vegetable Intake 3-58
Table 3-26. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total
Food Intake for Individuals with Low-end, Mid-range, and High-end Total
Dairy Intake 3-60
Table 3-27. Weighted and Unweighted Number of Observations (Individuals) for NFCS Data
Used in Analysis of Food Intake 3-62
Table 3-28. Consumer Only Intake of Homegrown Foods (g/kg-day)a - All Regions
Combined 3-63
Table 3-29. Percent Weight Losses from Food Preparation 3-64
Table 3-30. Quantity (as consumed) of Food Groups Consumed Per Eating Occasion and the
Percentage of Individuals Using These Foods in Three Days 3-65
Table 3-31. Mean Moisture Content of Selected Food Groups Expressed as Percentages of
Edible Portions 3-67
Table 3-32. Percent Moisture Content for Selected Fish Speciesฎ 3-71
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Table 3-35. Summary of Recommended Values for Per Capita Intake of Foods, As
Consumed 3-79
Table 3-36. Confidence Intake Recommendations for Various Foods, Including Fish (General
Population) 3-81
Table 3-37. Confidence Intake Recommendations for Fish Consumption - Recreational
Freshwater Angler Population 3-82
Table 3-38. Confidence Intake Recommendations for Fish Consumption - Native American
Subsistence Population 3-83
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24
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29
30
3. FOOD INTAKE
3.1 INTRODUCTION
Ingestion of contaminated foods is a potential pathway of exposure to toxic chemicals
among children. Fruits, vegetables, and grains 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. Meat, poultry, and
dairy products can become contaminated if animals are exposed to contaminated media (i.e., soil,
water, or feed crops). Contaminated finfish and shellfish are also 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. Intake rates for home produced food products are needed to assess exposure
to local contaminants present in homegrown or home caught foods.
Exposure to children from food ingestion may differ from that of adults because of
differences in the type and amounts of food eaten. Also, for many foods, the intake per unit body
weight is greater for children than adults. The most common foods eaten by children include
milk, nonfat solids; apple juice; apples, fresh; orange juice; pears, fresh; milk, fat, solids; peaches,
fresh; carrots; beef, lean; milk sugar (lactose); bananas, fresh; rice, milled; peas, succulent, garden;
beans, succulent, garden; oats; soybean oil; coconut oil; and wheat flour (Goldman, 1995).
The primary source of recent information on consumption rates of foods among children is
the U.S. Department of Agriculture's (USD A) Nationwide Food Consumption Survey (NFCS)
and the USDA Continuing Survey of Food Intakes by Individuals (CSFII). Data from the 1989-
91 and 1994-96 CSFIIs have been used in various studies to generate children's per capita intake
rates for both individual foods and the major food groups. Earlier studies have used USDA's
Nationwide Food Consumption Survey (NFCS) from 1977/78 or 1987/88. Because data from the
1989-91 and 1994-96 CSFIIs are available, data from the older surveys are not reported here,
except in the case of data on homegrown foods, which are based on the 1987/88 NFCS, and
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4
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7
8
9
10
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12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
serving size information, which is based on the 1977/78 NFCS. Older USDA data analyses can be
found in Exposure Factors Handbook (U.S. EPA 1997).
It should be noted that a variety of terms may be used to define intake. These terms (e.g.,
consumer-only intake, per capita intake, as consumed intake, dry weight intake) are defined below
to assist the reader in interpreting and using the intake rates that are appropriate for the exposure
scenario being assessed. Consumer-only intake is defined as the quantity of foods consumed only
by children 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 children (i.e., both
users and non-users). In general, per capita intake rates are appropriate for use in exposure
assessment for which average dose estimates for children are of interest because they represent
both children who ate the foods during the survey period and children who may eat the food items
at some time, but did not consume them during the survey period. Intake rates for the major food
categories include all forms of that food type. For example, total fruit intake refers to the sum of
all fruits consumed in a day including canned, dried, frozen, and fresh fruits. Likewise, total
vegetable intake refers to the sum of all vegetables consumed in a day including canned, dried,
frozen, and fresh vegetables.
Intake rates may be presented on an "as consumed" (e.g., cooked) basis or on the basis of
an uncooked weight. As consumed intake rates (g/day) are based on the weight of the food in the
form that it is consumed and should be used in assessments where the basis for the contaminant
concentrations in foods is whole weight. When data are based on "as consumed" form,
corrections to account for changes in portion sizes from cooking losses are generally not required.
When dry weight contaminant concentrations in foods are available, dry weight intake rates must
be used. Dry weight intake rates are based on the weight of the food consumed after the moisture
content has been removed.
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,
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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 foods, the major
food groups, and total foods among children, including homegrown foods; (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.
3.2 INTAKE RATE DISTRIBUTIONS FOR VARIOUS FOOD TYPES
U.S. EPA (2000) - Analysis of USDA 1994-96 CSFII Data to Generate Intake Rates for
Major Food Groups and Individual Foods - EPA's National Center for Environmental
Assessment (NCEA) analyzed three years of data from USDA's CSFII to generate distributions of
intake rates for various food items/groups. USDA conducts CSFII annually 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).
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. Using a
stratified sampling technique, individuals of all ages living in selected households in the 50 states
and Washington, D.C. were surveyed. Individuals provided 2 non-consecutive days of data,
based on 24-hour recall. The 2-day response rate for the 1994-96 CSFII was approximately 76
percent. Data from the 1994 1995, and 1996 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 (USDA, 1998).
The food groups selected for this analysis include the major food groups: total fruits, total
vegetables, total grains, total meats, and total dairy. Individual foods include fruit and vegetable
items such as: apples, bananas, 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). Individual meats include
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beef, eggs, game, pork, and poultry; and individual grain items include breads, breadfast foods,
cereals, pasta, rice, snacks, and sweets. Intake rates of total vegetables, tomatoes, and white
potatoes, total meats, fish, beef, pork, poultry, dairy, eggs, and total grains were adjusted to
account for the amount of these food items eaten as meat and grain mixtures as described in
Appendix 3 A. Food items/groups were identified in the CSFII data base according to USDA-
defined food codes. Appendix 3B 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, age,
body weight, weighting factor, and number of days that data were reported. Distributions of
intake were determined for children who provided data for two 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. Two-day average intake rates were calculated for
all individuals in the database for each of the food items/groups. These average daily intake rates
were divided by each individual's reported body weight to generate intake rates in units of g/kg-
day. The data were also weighted according to the two-day weights provided in the 1994-96
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 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. Intake data from the 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 generally required. 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 age groups
of children, including <1, 1-2, 3-5, 6-11, and 12-19 years. The total numbers of individuals in the
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data set, by age group are presented in Table 3-1. The food analysis was accomplished using the
SAS statistical programming system (SAS, 1990).
The results of this analysis are presented in Table 3-2 for total fruits, total vegetables, total
grains, total meats, total fish, and total dairy products. Table 3-3 provides data for individual
foods, and Table 3-4 for the various USD A categories. The data for exposed/protected and root
food items are presented in Table 3-5. 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 for the age
group of interest, as presented in Chapter 10 of this document should be used.
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., 2-day) do not necessarily reflect the long-term
distribution of average daily intake rates. The distributions generated from short-term and long-
term data will differ to the extent that each individual's intake varies from day to day; the
distributions will be similar to the extent that individual's 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., 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. Distributions are shown only for the major food
groups and broad categories of foods. For individual foods, only the mean standard deviation and
percent consuming are provided. 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.
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The advantages of using the 1949-96 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. The data set is the most recent of a series of publicly available USDA data sets, and should
reflect recent eating patterns in the United States. The data set includes three years of intake data
combined and are based on a two-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 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 3A-1 in the proportions specified in
that table. This may under- or over-estimate intake of certain foods among some individuals.
3.3 FISH INTAKE RATES
3.3.1 General Population Studies
U.S. EPA (1996) - Daily Average Per Capita Fish Consumption Estimates Based on the
Combined USDA 1989, 1990, and 1991 CSFIIEPA's Office of Water 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.
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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 fish-by-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.
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 (1996) 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
100a percentile and 100 (1 -a) percentile estimates from the non-parametric distribution of the
given point estimate (U.S. EPA, 1996). 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 3-6 presents data for daily average per capita fish consumption by age and gender in
g/day and in mg/kg/day, as consumed. Table 3-7 provides consumer only data in units of g/day
and mg/kg/day, as consumed. Tables 3-8 and 3-9 provide similar data on an uncooked basis.
These data are presented by selected age groupings (4 and under and 15-44) and gender.
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, 1992), excluded certain fish
containing foods (e.g., fish mixtures, frozen plate meals) in their calculations.
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EPA, Office of Water, is currently in the process of analyzing data from the 1994, 1995,
and 1996 CSFIIs. Total fish intake was estimated from the 1994-96 CSFII by EPA/NCEA (see
Section 3.2). The EPA, Office of Water data will be in this Handbook when available.
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. 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)".
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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 offish consumers," Javitz (1980) calculated means and percentiles of fish
consumption by age (Table 3-10). The overall mean fish intake rate among fish consumers was
calculated at 6.2 g/day for ages 0-9 years and 10.1 g/day for ages 10-19 years, the 95th percentile
fish ingestion rates were 16.5 g/day for ages 0-9 years and 26.8 g/day for ages 10-19 years.
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 optimal parameters. Ruffle
et al. (1994) determined that, of the three methods, the non-linear 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 3-11 presents the optimal lognormal parameters, the mean (//), 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
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relation DFC(p)=exp[//+ 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 consumption rate is given by exp[pi + 0.5s2].
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 USD A National Food Consumption
Surveys, which report consumption over a 3 day to one week period.
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(l+x/100)
to the log mean pi 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.
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
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4,700 participants also provided information on seafood consumption. Over 900 of these
participants were children between the ages of 1 and 17 years. The survey was conducted
between October 1992 and September 1994. Data were collected on the (1) number of people
that ate seafood in the last month, (2) the number of 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 the 900 children who
participated in the survey, approximately 43 percent reportedly ate seafood (including shellfish,
eels, or squid) in the last month. 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 3-12). The highest number of
respondents for all ages of children had 1-2 servings per month. Most of the respondents
purchased the seafood they ate (Table 3-12).
Intake data were not provided in the survey. However, intake of fish can be estimated
using the information on the number of servings of fish eaten from this study and serving size data
for each age group from other studies (e.g., Pao et al., 1982). Using this mean value for serving
size and assuming that the average child eats 1-2 servings per month, the age-specific amount of
seafood eaten per month can be estimated.
The advantages of NHAPS is that the data were collected for a large number of
individuals and are representative of the U.S. general population. However, evaluation of seafood
intake was not the primary purpose of the study and the data do not reflect the actual amount of
seafood that was eaten. However, using the assumption described above, the estimated seafood
intake from this study are comparable to those observed in the EPA CSFII analysis. It should be
noted that an all inclusive description for seafood was not presented in Tsang and Klepeis (1996).
It is not known if processed or canned seafood and seafood mixtures are included in the seafood
category.
3.3.2 Freshwater Recreational Study
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
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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 (self-caught, 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.
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
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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 3-13 displays the mean number of total and recreational fish meals for each
household member between age 1 and 20 years based on the seven day recall data. Also shown
are mean fish intake rates derived by applying the weights described above to each fish meal.
Intake was calculated 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 advantages of this data set and analysis are that the survey was relatively large and
contained both short-term and usual intake data. The response rate of this survey, 47 percent,
was relatively low. This study was conducted in the winter and spring months of 1989. This
period does not include the summer months when peak fishing activity can be anticipated, leading
to the possibility that intake results based on the 7 day recall data may understate individuals'
usual (annual average) fish consumption.
3.3.3 Native American Subsistence Study
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
Native American tribes during the fall and winter of 1991-1992. The target population included
all adult tribal members who lived on or near the Yakama, Warm Springs, Umatilla or Nez Perce
reservations. The survey was based on a stratified random sampling design where respondents
were selected from patient registration files at the Indian Health Service. Interviews were
performed in person at a central location on the member's reservation. Information for 204
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children 5 years old and less was provided by the participating adult respondent. The overall
response rate was 69 percent.
Information requested included annual and seasonal numbers of fish meals, average
serving size per fish meal, species and part(s) of fish consumed, and preparation methods based on
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).
A total of 49 percent of respondents of the total survey population reported that they
caught fish from the Columbia River basin and its tributaries for personal use or for tribal
ceremonies and distributions to other tribe members and 88 percent reported that they obtained
fish from either self-harvesting, family or friends, at tribal ceremonies or from tribal distributions.
Of all fish consumed, 41 percent came from self or family harvesting, 11 percent from the harvest
of friends, 35 percent from tribal ceremonies or distribution, 9 percent from stores and 4 percent
from other sources (CRITFC, 1994).
The analysis of seasonal intake showed that May and June tended to be high consumption
months and December and January low consumption months. Table 3-14 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
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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 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.
3.4 FAT INTAKE
Cresenta et al. (1988), Nicklas (1993), and Frank et al. (1986) analyzed dietary fat intake
data as part of the Bogalusa heart study. The Bogalusa study "is an epidemiologic investigation
of cardiovascular risk-factor variables and environmental determinants in a population that began
20 years ago" (Nicklas, 1995). The Bogalusa study has collected dietary data on subjects residing
in Bogalusa, Louisiana, since 1973. Among other things, the study collected fat intake data for
children, adolescents, and young adults. Researchers have examined various cohorts of subjects,
including (1) six cohorts of 10-year olds, (2) two cohorts of 13-year olds, (3) one cohort of
subjects from 6 months to 4 years of age, and (4) one cohort of subjects from 10 to 17 years of
age (Nicklas, 1995). In order to collect the data, interviewers used the 24-hour dietary recall
method. According to Nicklas (1995), "the diets of children in the Bogalusa study are similar to
those reported in national studies of children." Thus, these data are useful in evaluating the
variability of fat intake among the general population for the purposes of evaluating variability in
exposure for dioxin-like compounds among this group. Data for 6-month old to 17-year old
individuals collected during 1973 to 1982 are presented in Tables 3-15 and 3-16 (Frank et al.,
1986). Data are presented for total fats, animal fats, vegetable fats, and fish fats in units of g/day
and g/kg/day, respectively.
Total fat intake and intake of individual fat products was also estimated by EPA/NCEA
using data from the 1994/96 CSFII. It should be noted that the fat intake rates presented here
include all forms of fats (i.e., added fats such as butter and vegetable oil as well as fats consumed
in meats and fish).
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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."
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 3C for detailed calculation). Table 3-17
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.
3.5 TOTAL DIETARY INTAKE AND CONTRIBUTIONS TO DIETARY
INTAKE
U.S. EPA (2000) - 1994-96 CSFII Total Diet Analysis. Using data from the 1994-1996
CSFII, total dietary intake was also evaluated. Total dietary intake was defined as intake of the
sum of all foods in the following major food groups: dairy, eggs, meats, fish, fats, grains,
vegetables, and fruits, using the same foods codes as those described in Appendix 3B, and the
same method for allocation of mixtures as described in Appendix 3A. Beverages; sugar, candy,
and sweets, and nuts and nut products were not included. Distributions of total dietary intake
were generated, as described previously, for various age groups. Means, standard errors, and
percentiles of total dietary intake were estimated in units of g/kg/day, as well as g/day.
To evaluate variability in the contributions of the major food groups to total dietary
intake, individuals were ranked from lowest to highest, based on total dietary intake. Three
subsets of individuals were defined, as follows: a group at the low end of the distribution of total
intake (i.e., below the 10th percentile of total intake), a central group (i.e., the 45th to 55th
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percentile of total intake), and a group at the high end of the distribution of total intake (i.e.,
above the 90th percentile of total intake). Mean total dietary intake, mean intake of each of the
major food groups, and the fraction of total dietary intake that each of these food groups
represents was calculated for each of the three populations (i.e., individuals with low-end, central,
and high-end total dietary intake). A similar analysis was conducted to estimate the contribution
of the major food groups to total dietary intake for individuals at the low-end, central, and high-
end of the distribution of total meat intake, total dairy intake, total meat and dairy intake, total
fish intake, and fruit and vegetable intake. For example, to evaluate the variability in the diets of
individuals at the low-end, central range, and high-end of the distribution of total meat intake,
survey individuals were ranked according to their reported total meat intake. Three subsets of
individuals were formed as described above. Mean total dietary intake, intake of the major food
groups, and the fraction of total dietary intake represented by each of the major food groups were
tabulated. This analysis was conducted for the following age groups of the population: <1 year,
1-2 years, 3-5 years, 6-11 years, and 12-19 years. The data were tabulated in units of g/kg/day
and g/day.
Distributions of total dietary intake are presented in Table 3-18 in units of g/day and
g/kg/day. Tables 3-19 and 3-20 compare total dietary intake to intake of the various major food
groups for the various age groups in units of g/day and g/kg/day. Tables 3-21 through 3-26
present the contributions of the major food groups to total dietary intake for individuals (in the
various age groups) at the low-end, central, and high-end of the distribution of total dietary
intake, total meat intake, total meat and dairy intake, total fish intake, total fruit and vegetable
intake, and total dairy intake in units of g/day and g/kg/day.
3.6 INTAKE OF HOME-PRODUCED FOODS
U.S. EPA (1997) - EPA 's Analysis of the 1987/88 NFCS to Estimate Homegrown Intake
Rates. 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 (USDA, 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
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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 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 USD A data were adjusted by applying the sample weights calculated by USD A 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
such as 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.) were also evaluated for the
general population (U.S. EPA, 1997). However, age-specific data for children are not presented
here because of the small numbers of observations for children eating individual homegrown foods
in the data set. Food items/groups were identified in the NFCS data base according to NFCS-
defined food codes. Appendix 3D 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 group eaten by each individual in the household, it could not be used directly
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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.
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 (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:
w. = w,
/
m.q,
(Eqn. 3-1)
where:
w; = 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);
ir^ = Number of meals of household food consumed by member i during the week
(meals/week); and
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q; = Serving size for an individual within the age and sex category of the member
(g/meal).
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.
For the major food groups (fruits, vegetables, meats, dairy, and fish) consumed by at least
30 households, distributions of home produced intake among consumers were generated by age
group. Consumers were defined as members of survey households who reported consumption of
the food item/group of interest during the one week survey period. 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 discussed previously, percentiles
of average daily intake derived from short time intervals (e.g., 7 days) will not, in general, be
reflective of long term patterns.
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 IRp is the homegrown intake rate of food item/group at the pth percentile
and Nc is the weighted number of individuals consuming the homegrown food item, and Nx is the
weighted total number of individuals surveyed, then Nx - Nc is the weighted number of individuals
who reported zero consumption of the food item. In addition, there are (p/100 x Nc) individuals
below the pth percentile. Therefore, the percentile that corresponds to a particular intake rate
(IRp) for the overall distribution of homegrown food consumption (including consumers and
nonconsumers) can be obtained by:
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f P
x
derail = 100 x
V100
(Eqn. 3-2)
nt
Table 3-27 displays the weighted numbers Nx, as well as the unweighted total survey
sample sizes, for each subcategory and overall. It should be noted that the total unweighted
number of observations in Table 3-27 (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.
Table 3-28 present homegrown intake rates for fruits, vegetables, meats, and fish,
respectively. 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 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.
Mean values for all meats and fish are provided in Table 3-29. For individual fruits and
vegetables, USDA (1975) also gave cooking and post-cooking losses. These data, averaged
across all types of fruits and vegetables to give mean net cooking and post cooking losses are also
provided in Table 3-29.
The following formula can be used to convert the homegrown intake rates tabulated here
to rates reflecting actual consumption:
IA = Ix(l-Li)x(l-L2)
(Eqn. 3-3)
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where IA is the adjusted intake rate, I is the tabulated intake rate, L, is the cooking or preparation
loss, and L2 is the post-cooking loss. For fruits, corrections based on postcooking losses only
apply to fruits that are eaten in cooked forms. For raw forms of the fruits, paring or preparation
loss data should be used to correct for losses from removal of skin, peel, core, caps, pits, stems,
and defects, or draining of liquids from canned or frozen forms.
In calculating ingestion exposure, assessors should use consistent forms in combining
intake rates with contaminant concentrations, as previously discussed.
3.7 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 in Table 3-30 for various
age groups of the population. Only the mean and standard deviation serving size data and percent
of the population consuming the food during the 3-day survey period are presented in this
handbook. Percentiles of serving sizes of the foods consumed by these age groups of the U.S.
population can be found in 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 sizes for a number of
commonly eaten foods, 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 foods
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.
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3.8 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 3-31 and Table 3-32 and the following
equation:
IRdw= IRac* [(100-W)/100] (Eqn.3-4)
"Dry weight" intake rates may be converted to "as consumed" rates by using:
IRac = IRdw/[(100-W)/100] (Eqn. 3-5)
where:
IRthv = dry weight intake rate;
IRac = as consumed intake rate; and
W = percent water content.
3.9 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:
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residue level residue level g-fat
= x 2
g-product g-fat g-product
(Eqn. 3-6)
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, 1979-1986) 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 3-33 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 to estimate total fat content in grams, based on a 3-ounce (85.05 g) cooked
serving size, and the corresponding percent fat content values for several categories of meats
(Table 3-34). 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).
3.10 RECOMMENDATIONS
The 1994-96 CSFII data described in this section were used in selecting recommended
intake rates for most food groups for general population children. For fish intake among general
population children, the 1989-91 CSFII analyses were used to recommend intake rates. For
recreational fish intake and intake among Native American populations, the data for children are
limited. Fat intake data are also limited. The studies that address these populations should be
used in exposure assessments where these populations are of interest (see Tables 3-13 and 3-17).
Table 3-35 presents a summary of the recommended values for food intake and Table 3-36
presents the confidence ratings for the food intake (including fish) recommendations for general
population children. Table 3-37 present the confidence ratings for fish intake recommendations
for the freshwater recreational population and Table 3-38 for Native American subsistence
populations. Per capita intake rates for specific food items, on a g/kg-day basis, may be obtained
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1 from Table 3-3. Percentiles of the per capita intake rate distributions for the major food groups in
2 the general population are presented in Table 3-2. It is important to note that these distributions
3 are based on data collected over a 2-day period and may not necessarily reflect the long-term
4 distribution of average daily intake rates. However, for these broad categories of food, because
5 they are eaten on a daily basis throughout the year with minimal seasonality, the short term
6 distribution may be a reasonable approximation of the long-term distribution, although it will
7 display somewhat increased variability. This implies that the upper percentiles shown here will
8 tend to overestimate the corresponding percentiles of the true long-term distribution.
June 2000
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31
32
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35
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38
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40
41
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49
50
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3.11 REFERENCES FOR CHAPTER 3
CDC. (1994) Dietary fat and total food-energy intake. Third National Health and Nutrition Examination Survey,
Phase 1, 1988-91. Morbidity and Mortality Weekly Report, February 25, 1994: 43(7)118-125.
Columbia River Inter-Tribal Fish Commission (CRITFC). (1994) A fish consumption survey of the Umatilla, Nez
Perce, Yakama and Warm Springs tribes of the Columbia River Basin. Technical Report 94-3. Portland, OR:
CRIFTC.
Cresanta, J.L.; Farris, R.P.; Croft, J.B.; Frank, G.C.; Berenson, G.S. (1988) Trends in fatty acid intakes of 10-
year-old children, 1973-1982. Journal of American Dietetic Association. 88:178-184.
Frank, G.C.; Webber, L.S.; Farris, R.P.; Berenson, G.S. (1986) Dietary databook: quantifying dietary intakes of
infants, children, and adolescents, the Bogalusa heart study, 1973-1983. National Research and
Demonstration Center - Arteriosclerosis, Louisiana State University Medical Center, New Orleans, Louisiana.
Goldman, L. (1995) Children - unique and vulnerable. Environmental risks facing children and recommendations
for response. Environmental Health Perspectives. 103(6): 13-17.
Javitz, H. (1980) Seafood consumption data analysis. SRI International. Final report prepared for EPA Office of
Water Regulations and Standards. EPA Contract 68-01-3887.
National Livestock and Meat Board (NLMB). (1993) Eating in America today: A dietary pattern and intake
report. National Livestock and Meat Board. Chicago, IL.
Nicklas, T.A. (1995) Dietary studies of children: The Bogalusa Heart Study experience. Journal of the American
Dietetic Association. 95:1127-1133.
Nicklas, T.A.; Webber, L.S.; Srinivasan, S.R.; Berenson, G.S. (1993) Secular trends in dietary intakes and
cardiovascular risk factors in 10-y-old children: the Bogalusa heart study (1973-1988). American Journal of
Clinical Nutrition. 57:930-937.
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.
Ruffle, B.; Burmaster, D.; Anderson, P.; Gordon, D. (1994) Lognormal distributions for fish consumption by the
general U.S. population. Risk Analysis 14(4):395-404.
Rupp, E.; Miler, F.L.; Baes, C.F. III. (1980) Some results of recent surveys of fish and shellfish consumption by
age and region of U.S. residents. Health Physics 39:165-175.
SAS Institute, Inc. (1990) SAS Procedures Guide, Version 6, Third Edition, Cary, NC: SAS Institute, Inc., 1990,
705 pp.
Tsang, A.M.; Klepeis, N.E. (1996) Results tables from a detailed analysis of the National Human Activity Pattern
Survey (NHAPS) response. Draft Report prepared for the U.S. Environmental Protection Agency by Lockheed
Martin, Contract No. 68-W6-001, Delivery Order No. 13.
USD A. (1975) Food yields summarized by different stages of preparation. Agricultural Handbook No. 102.
Washington, DC: U.S. Department of Agriculture, Agriculture Research Service.
USD A. (1979-1986) Agricultural Handbook No. 8. United States Department of Agriculture.
June 2000
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7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
USDA. (1987-88) Dataset: Nationwide Food Consumption Survey 1987/88 Household Food Use. U.S.
Department of Agriculture. Washington, D.C. 1987/88 NFCS 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, 1987-88. Nationwide Food
Consumption Survey 1987-88, NFCS Report No. 87-1-1.
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-l.
USDA. (1995) Food and nutrient intakes by individuals in the United States, 1 day, 1989-91. U.S. Department of
Agriculture, Agricultural Research Service. NFS Report No. 91-2.
USDA. (1998) 1994-96 Continuing Survey of Food Intakes by Individuals (CSFII) and 1994-96 Diet and Health
Knowledge Survey (DKHS). CD-ROM. U.S. Department of Agriculture, Agricultural Research Service.
Available from the National Technical Information Service, Springfield, VA.
U.S. EPA. (1996) Daily average per capita fish consumption estimates based on the combined USDA 1989, 1990
and 1991 continuing survey of food intakes by individuals (CSFII) 1989-91 data. Volumes I and II.
Preliminary Draft Report. Washington, DC: Office of Water.
U.S. EPA. (1997) Exposure Factors Handbook. Washington, DC: Office of Research and Development.
EPA/600/P-95/002F.
U.S. EPA. (2000) CSFII analysis of food intake. Report prepared for U.S. EPA, Office of Research and
Development, National Center for Environmental Assessment by Versar, Inc.
West, P.C.; Fly, M.J.; Marans, R.; Larkin, F. (1989) Michigan sport anglers fish consumption survey. A report to
the Michigan Toxic Substance Control Commission. Michigan Department of Management and Budget
Contract No. 87-20141.
June 2000
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8
9
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11
12
13
14
15
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17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Table 3-1. Weighted and Unweighted Number of Observations, 1994/96 CSFII Analysis
Weighted
Unweighted
Population
Number of
Number of
Group
Observations
Observations
Total
261,897,260
15,303
Age Group (years)
<01
3,772,296
359
01-02
8,270,523
1,356
03-05
12,376,836
1,435
06-11
23,408,882
1,432
12-19
29,657,098
1,398
20-39
81,672,622
2,992
40-69
81,480,145
4,921
70+
21,258,858
1,410
Season
Fall
65,474,320
3,653
Spring
65,474,321
4,015
Summer
65,474,320
4,143
Winter
65,474,299
3,492
Urbanization
Central City
83,904,160
4,600
Nonmetropolitan
55,263,514
3,778
Suburban
122,729,586
6,925
Race
Asian
7,764,799
387
Black
33,466,094
1,963
Native American
1,669,637
115
Other/NA
14,321,336
972
White
204,675,394
11,866
Region
Midwest
61,512,403
3,658
Northeast
51,416,379
2,737
South
91,294,341
5,474
West
57.674.137
3.434
June 2000
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5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
Table 3-2. Per Capita Intake of the Major Food Groups (g/kg-day as consumed)
Population
Group
Percent
Consuming
MEAN
SE
PI
P5
P10
P25
P50
P75
P90
P95
P99
P100
Fruits
Age (years)
<01
56.8%
13.18
1.106
0
0
0
0
7.559
22.67
35.69
41.18
63.73
110.2
1-2
85.5%
19.31
0.521
0
0
0
6.351
15.52
27.45
41.62
53.9
77.26
125.3
3-5
79.0%
11.02
0.341
0
0
0
2.273
8.102
16.34
26.44
32.68
52.99
105.2
6-11
71.2%
5.393
0.2
0
0
0
0
3.351
7.874
13.63
17.95
28.45
44.57
12-19
60.7%
2.771
0.133
0
0
0
0
1.371
4.116
7.978
10.97
16.64
32.23
Vegetables
Age (years)
<01
50.1%
6.902
0.721
0
0
0
0
2.337
12.23
17.86
24.18
36.28
102.6
1-2
95.4%
9.528
0.213
0
0.471
1.929
4.534
8.013
12.58
18.72
23.28
33.46
83.29
3-5
92.7%
7.295
0.159
0
0
1.348
3.411
6.231
9.69
13.93
18.27
28.99
45.54
6-11
93.2%
5.337
0.118
0
0
1.12
2.48
4.334
7.103
10.44
13.54
21.21
52.27
12-19
97.9%
4.034
0.085
0
0.633
1.121
2.14
3.404
5.145
7.399
9.346
14.68
42.43
Grains
Age (years)
<01
64.9%
4.124
0.416
0
0
0
0
1.575
5.438
12.97
20.24
26.61
40.13
1-2
95.6%
11.21
0.202
0
1.686
3.594
6.434
9.807
14.27
21.04
24.71
34.67
47.99
3-5
93.1%
10.29
0.197
0
0
3.674
6.292
9.177
13.13
17.77
21.07
33.64
120.9
6-11
93.4%
7.2
0.122
0
0
2.452
4.285
6.656
9.413
12.92
15.55
19.89
36.3
12-19
98.2%
4.401
0.08
0
1.13
1.543
2.452
3.788
5.541
7.899
9.702
14.08
34.57
Meats
Age (years)
<01
32.3%
1.132
0.198
0
0
0
0
0
1.383
3.87
5.853
10.59
12.37
1-2
94.0%
4.422
0.094
0
0
0.759
1.909
3.845
6.195
8.869
10.16
14.66
24.44
3-5
92.2%
4.144
0.08
0
0
0.768
2.125
3.814
5.624
7.847
9.436
13.1
20.74
6-11
92.4%
2.919
0.06
0
0
0.523
1.418
2.52
3.996
5.555
6.802
10.23
17.6
12-19
97.3%
2.158
0.046
0
0.266
0.527
1.106
1.947
2.835
3.93
4.865
7.459
26.75
Fish
Age (years)
<01
20.9%
0.108
0.047
0
0
0
0
0
0
0.325
0.527
1.562
4.685
1-2
58.2%
0.368
0.037
0
0
0
0
0.08
0.286
0.783
1.791
4.687
14.42
3-5
56.4%
0.316
0.03
0
0
0
0
0.069
0.245
0.661
1.736
4.567
9.553
6-11
57.5%
0.259
0.025
0
0
0
0
0.058
0.178
0.479
1.346
4.234
6.686
12-19
62.9%
0.204
0.017
0
0
0
0
0.055
0.172
0.417
1.1
2.499
5.354
Dairy Products
Age (years)
<01
83.6%
111.4
4.855
0
0
2.522
63.89
102.2
158.6
197.8
235.3
318.3
576.3
1-2
95.7%
37.48
0.779
0
0.412
6.677
17.75
31.76
51.44
73.89
90.15
132.8
182.8
3-5
92.9%
20.91
0.402
0
0
3.473
10.18
18.73
29.16
41.24
48.75
66.16
89.72
6-11
93.3%
13.92
0.276
0
0
2.167
6.438
12.35
19.25
27.34
33.46
43.43
80.78
12-19
96.9%
6.119
0.16
0
0.168
0.413
1.832
4.467
8.803
13.49
17.79
27.84
38.01
Note: SE = Standard error
P = Percentile of the distribution
Source: Based on EPA's analyses of the 1994-96 CSFII
June 2000
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Table 3-3. Per Capita Intake of Individual Foods (g/kg-day as consumed)
Population
Group
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Apples
Asparagus
Bananas
Beets
Broccoli
Age (years)
<01
41.2%
7.03
0.977
0.0%
0
0
21.4%
1.153
0.342
0.6%
0.032
0.247
1.1%
0.017
0.11
01-02
55.1%
8.02
0.448
0.7%
0.014
0.082
35.0%
1.688
0.138
0.4%
0.004
0.035
8.6%
0.242
0.095
03-05
47.7%
4.103
0.273
0.7%
0.009
0.041
20.8%
0.713
0.095
0.6%
0.012
0.051
7.8%
0.137
0.06
06-11
34.1%
1.437
0.135
0.8%
0.014
0.065
14.2%
0.353
0.073
0.3%
0.003
0.033
6.8%
0.108
0.055
12-19
20.0%
0.582
0.093
0.3%
0.003
0.022
9.4%
0.119
0.037
0.2%
0.001
0.015
5.8%
0.064
0.036
Cabbage
Carrots
Corn
Cucumbers
Lettuce
Age (years)
<01
0.6%
0.023
0.209
12.3%
0.678
0.348
2.2%
0.164
0.355
0.3%
0
0.011
0.0%
0
0
01-02
3.8%
0.071
0.07
14.5%
0.343
0.177
18.5%
0.462
0.097
6.9%
0.089
0.054
11.0%
0.109
0.035
03-05
5.7%
0.099
0.06
15.1%
0.182
0.043
19.2%
0.426
0.071
11.2%
0.13
0.059
18.9%
0.166
0.029
06-11
6.7%
0.074
0.04
17.8%
0.153
0.032
21.0%
0.316
0.046
14.7%
0.123
0.038
24.7%
0.184
0.027
12-19
5.8%
0.039
0.024
13.1%
0.057
0.019
12.8%
0.144
0.036
15.2%
0.094
0.037
35.6%
0.177
0.018
Lima Beans
Okra
Onions
Other Berries
Peaches
Age (years)
<01
0.3%
0
0.008
0.0%
0
0
0.3%
0.007
0.135
0.3%
0.005
0.068
12.8%
0.856
0.393
01-02
1.6%
0.037
0.074
1.0%
0.01
0.041
4.1%
0.019
0.021
1.5%
0.073
0.229
9.7%
0.447
0.145
03-05
0.8%
0.01
0.044
0.3%
0.006
0.084
4.7%
0.022
0.021
1.7%
0.034
0.084
7.2%
0.248
0.117
06-11
1.0%
0.018
0.057
0.8%
0.008
0.03
6.7%
0.026
0.017
1.8%
0.029
0.057
5.6%
0.125
0.077
12-19
0.5%
0.007
0.062
0.7%
0.003
0.018
12.9%
0.044
0.015
1.4%
0.016
0.043
4.0%
0.064
0.051
Pears
Peas
Peppers
Pumpkins
Snap Beans
Age (years)
<01
14.8%
1.354
0.49
9.2%
0.603
0.313
0.3%
0.001
0.014
7.5%
0.433
0.383
11.7%
0.624
0.267
01-02
8.5%
0.393
0.159
12.3%
0.257
0.072
1.5%
0.007
0.015
1.0%
0.054
0.172
19.4%
0.49
0.086
03-05
5.0%
0.178
0.114
9.1%
0.163
0.054
3.1%
0.018
0.023
0.3%
0.003
0.034
15.3%
0.239
0.05
06-11
5.2%
0.114
0.07
7.8%
0.111
0.049
4.7%
0.018
0.015
0.1%
0.001
0.017
12.2%
0.16
0.057
12-19
1.7%
0.023
0.039
5.6%
0.06
0.037
7.4%
0.018
0.01
0.1%
0.002
0.039
7.9%
0.063
0.024
Strawberries
Tomatoes
White Potatoes
Breads
Breakfast Foods (Grains)
Age (years)
<01
0.6%
0.007
0.086
28.7%
0.518
0.119
27.6%
0.537
0.151
15.0%
0.256
0.114
1.7%
0.048
0.162
01-02
4.4%
0.116
0.091
88.8%
2.139
0.076
77.4%
2.245
0.1
76.9%
1.95
0.063
19.5%
0.429
0.066
03-05
4.4%
0.096
0.081
87.7%
1.741
0.059
77.6%
2.027
0.085
85.6%
2.289
0.054
21.5%
0.391
0.055
06-11
4.5%
0.064
0.053
89.4%
1.217
0.037
79.0%
1.51
0.058
87.0%
1.698
0.04
21.9%
0.37
0.045
12-19
3.8%
0.032
0.026
94.8%
1.01
0.025
84.3%
1.243
0.049
86.4%
1.068
0.026
12.7%
0.13
0.031
Cereals (Baby) Cereals (Cooked) Cereals (Ready-to-Eat) Pasta Rice
June 2000
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3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
t?
Table 3-3. Per Capita Intake of Individual Foods (g/kg-day as consumed) (continued)
Population
Group
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Age (years)
<01
52.9%
1.595
0.265
5.6%
0.931
0.819
8.6%
0.059
0.048
2.5%
0.066
0.149
3.9%
0.167
0.283
1-2
6.5%
0.162
0.095
16.6%
1.618
0.286
65.0%
0.965
0.039
16.2%
0.795
0.152
19.1%
0.905
0.166
3-5
0.3%
0.004
0.055
14.7%
1.26
0.283
68.5%
1.1
0.038
12.5%
0.552
0.128
16.3%
0.795
0.179
6-11
0.1%
0
0.002
8.7%
0.471
0.171
63.1%
0.794
0.031
12.3%
0.488
0.115
16.1%
0.492
0.098
12-19
0.0%
0
0
5.9%
0.164
0.09
44.6%
0.36
0.023
12.1%
0.264
0.088
17.2%
0.462
0.105
Snacks (Grains)
Sweets (Grains)
Beef
Eggs
Game
Age (years)
<01
13.9%
0.135
0.063
10.6%
0.158
0.096
29.0%
0.508
0.111
29.0%
0.405
0.142
0.0%
0
0
1-2
57.5%
0.738
0.039
53.9%
1.155
0.066
88.9%
1.389
0.045
88.8%
1.174
0.055
0.5%
0.009
0.067
3-5
54.5%
0.701
0.042
62.1%
1.342
0.064
86.1%
1.311
0.042
84.5%
0.65
0.037
0.6%
0.009
0.054
6-11
51.0%
0.461
0.03
63.4%
1.151
0.055
87.7%
1.073
0.035
85.3%
0.4
0.025
1.0%
0.013
0.053
12-19
45.6%
0.287
0.022
54.6%
0.621
0.033
92.9%
0.917
0.033
91.0%
0.286
0.015
0.8%
0.006
0.027
Pork
Poultry
Butter
Margarine
Dressing
Age (years)
<01
29.0%
0.092
0.03
30.4%
0.35
0.1
1.1%
0.002
0.007
2.2%
0.004
0.011
0.8%
0.003
0.02
01-02
86.7%
0.4
0.025
89.7%
1.408
0.051
12.9%
0.034
0.01
30.1%
0.073
0.009
11.7%
0.062
0.02
03-05
84.5%
0.375
0.024
88.1%
1.307
0.047
13.7%
0.04
0.01
31.6%
0.085
0.009
18.3%
0.084
0.016
06-11
85.0%
0.265
0.016
87.8%
0.829
0.032
14.9%
0.03
0.008
31.4%
0.062
0.007
23.1%
0.094
0.013
12-19
90.2%
0.209
0.011
93.3%
0.619
0.022
11.6%
0.015
0.005
24.0%
0.034
0.005
24.2%
0.08
0.011
Mayonnaise
Sauce
Vegetable Oil
Age (years)
<01
0.6%
0.001
0.005
0.0%
0
0
0.6%
0.005
0.057
01-02
9.1%
0.024
0.01
0.4%
0.004
0.025
0.4%
0.001
0.014
03-05
14.8%
0.036
0.008
0.8%
0.003
0.016
0.7%
0.002
0.007
06-11
16.4%
0.028
0.006
0.7%
0.003
0.013
0.4%
0.001
0.008
12-19
21.5%
0.032
0.005
1.3%
0.005
0.012
0.5%
0
0.002
NOTE: SE = Standard error
P = Percentile of the distribution
Source: Based on EPA's analyses of the 1989-91 CSFII
June 2000
3-31
DRAFT-DO NOT QUOTE OR CITE
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Table 3-4. Per Capita Intake of USDA Categories of Vegetables and Fruits (g/kg-day as consumed)
Population
Group
Percent
Consuming
MEAN
SE
PI
P5
P10
P25
P50
P75
P90
P95
P99
P100
Dark Green Vegetables
Age (years)
<01
1.7%
0.045
0.219
0
0
0
0
0
0
0
0
0.678
9.77
1-2
12.5%
0.328
0.098
0
0
0
0
0
0
0.845
2.315
6.513
20.94
3-5
10.9%
0.197
0.063
0
0
0
0
0
0
0.224
1.488
4.127
12.72
6-11
9.9%
0.154
0.054
0
0
0
0
0
0
0.162
1.042
3.655
6.761
12-19
9.4%
0.124
0.041
0
0
0
0
0
0
0.15
0.935
2.792
4.333
Deep Yellow Vegetables
Age (years)
<01
4.5%
0.162
0.217
0
0
0
0
0
0
0
0.372
5.708
7.862
1-2
15.2%
0.276
0.065
0
0
0
0
0
0
0.728
2.131
4.235
11.72
3-5
16.9%
0.243
0.051
0
0
0
0
0
0
0.716
1.729
4.299
8.268
6-11
19.3%
0.18
0.035
0
0
0
0
0
0
0.658
1.18
2.45
10.84
12-19
14.3%
0.071
0.021
0
0
0
0
0
0
0.152
0.506
1.387
4.85
Citrus Fruits
Age (years)
<01
4.5%
0.213
0.392
0
0
0
0
0
0
0
0
8.578
30.25
1-2
37.7%
4.018
0.341
0
0
0
0
0
5.741
12.87
18.71
37.07
113.4
3-5
38.9%
2.946
0.22
0
0
0
0
0
4.704
9.308
13.03
21.21
66.54
6-11
35.0%
1.9
0.163
0
0
0
0
0
2.745
6.329
9.465
16.74
27.94
12-19
36.1%
1.409
0.121
0
0
0
0
0
1.92
4.652
7.16
12.87
17.93
Other Fruits
Age (years)
<01
55.4%
12.93
1.11
0
0
0
0
7.266
22.67
35.38
41.18
63.42
110.2
1-2
79.6%
15.27
0.496
0
0
0 2.817
10.69
23
35.16
48.17
70.31
105.5
3-5
71.4%
8.071
0.311
0
0
0
0
4.92
11.76
20.53
27.38
44.08
84.57
6-11
62.0%
3.493
0.163
0
0
0
0
1.901
5.102
9.341
12.81
22.22
38.47
12-19
43.1%
1.362
0.104
0
0
0
0
0
1.833
4.153
6.261
12.71
32.23
Other Vegetables
Age (years)
<01
10.9%
0.466
0.293
0
0
0
0
0
0
0.565
2.853
11.07
14.76
1-2
62.4%
2.161
0.125
0
0
0
0
0.75
2.961
6.35
8.871
16.07
53.61
3-5
64.5%
1.726
0.091
0
0
0
0
0.706
2.239
4.693
7.206
13.35
21.71
6-11
66.3%
1.328
0.067
0
0
0
0
0.62
1.836
3.639
4.858
9.762
28.58
12-19
ox
00
00
^0
0.804
0.042
0
0
0
0
0.33
1.127
2.086
2.961
6.27
12.56
March 2000
3-32
DRAFT-DO NOT QUOTE OR CITE
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
Table 3-5. Per Capita Intake of Exposed/Protected Fruit and Vegetable Categories (g/kg-day as consumed)
Population
Group
Percent
Consuming
Mean
SE
PI
P5
P10
P25
P50
P75
P90
P95
P99
P100
Exposed Fruits
Age (years)
<01
49.9%
10.02
0.995
0
0
0
0
4.449
16.53
30.09
38.78
58.46
69.61
01-02
68.6%
10.9
0.469
0
0
0
0
5.695
15.68
29.37
38.99
65.81
101.3
03-05
60.7%
5.637
0.277
0
0
0
0
2.717
8.096
15.84
22.18
34.98
77.08
06-11
49.3%
2.197
0.136
0
0
0
0
0
3.075
6.338
8.777
17.55
32.2
12-19
31.9%
0.872
0.087
0
0
0
0
0
1.07
2.857
4.85
8.787
14.91
Protected Fruits
Age (years)
<01
27.0%
1.719
0.392
0
0
0
0
0
1.957
6.013
8.344
16.61
30.25
01-02
62.1%
6.449
0.309
0
0
0
0
3.59
9.186
17.84
24.18
39.03
113.4
03-05
54.5%
4.356
0.223
0
0
0
0
2.062
6.721
12.14
17.16
27.9
66.54
06-11
49.0%
2.702
0.165
0
0
0
0
0.165
3.817
8.074
11.44
19.81
31.71
12-19
46.4%
1.809
0.124
0
0
0
0
0
2.612
5.417
8.402
15.43
27.02
Exposed Vegetables
Age (years)
<01
18.1%
1.189
0.371
0
0
0
0
0
0
4.991
7.353
14.65
19.04
1-2
63.4%
1.996
0.114
0
0
0
0
0.591
2.678
5.753
8.551
14.87
45.03
3-5
68.2%
1.63
0.083
0
0
0
0
0.674
2.241
4.442
6.378
12.79
25.07
6-11
70.6%
1.235
0.058
0
0
0
0
0.601
1.58
3.417
4.836
8.102
19.6
12-19
76.4%
0.966
0.041
0
0
0
0.055
0.53
1.338
2.53
3.61
5.767
13.02
Protected Vegetables
Age (years)
<01
18.9%
1.281
0.371
0
0
0
0
0
0
5.42
7.785
11.9
23.1
01-02
41.4%
1.469
0.125
0
0
0
0
0
1.863
4.422
7.042
14.16
27.81
03-05
38.8%
1.079
0.09
0
0
0
0
0
1.402
3.52
5.417
10.3
17.99
06-11
38.7%
0.778
0.065
0
0
0
0
0
1.042
2.583
3.894
7.496
26.51
12-19
31.2%
0.462
0.055
0
0
0
0
0
0.437
1.517
2.348
5.766
21.55
Root Vegetables
Age (years)
<01
30.4%
1.812
0.355
0
0
0
0
0
2.307
6.944
9.582
15.59
32.92
01-02
68.2%
2.572
0.134
0
0
0
0
1.447
3.562
6.774
8.331
16.78
83.29
03-05
71.1%
2.191
0.091
0
0
0
0
1.355
3.215
5.512
7.125
14.06
32.05
06-11
73.7%
1.62
0.063
0
0
0
0
1.034
2.315
4.171
5.325
9.492
20.59
12-19
76.2%
1.263
0.053
0
0
0
0.094
0.823
1.747
3.015
3.992
7.661
22.47
NOTE: SE = Standard error
P = Percentile of the distribution
Source: Based on EPA's analyses of the 1989-91 CSFII
March 2000
3-33
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-6. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender - As Consumed
Sample
Mean
90th %
95th %
99th %
Mean
90th %
95th %
99th %
Age (years)
Size
(g/day)
(g/day)
(g/day)
(g/day)
(mg/kg-day)
(mg/kg-day)
(mg/kg-day)
(mg/kg-day)
Freshwater and Estuarine
Females
14 or under
1431
1.58
1.44
12.51
36.09
67.12
57.30
460.16
1356.54
15-44
2891
4.28
10.90
28.80
70.87
66.22
174.96
451.04
1188.16
Males
14 or under
1546
2.17
0.99
14.94
48.72
73.93
28.10
723.93
1290.10
15-44
2151
6.14
18.19
48.61
96.32
75.35
230.13
577.84
1132.23
Both Sexes
14 or under
2977
1.88
1.31
13.90
40.77
70.59
53.24
556.34
1347.67
15-44
5042
5.17
13.88
36.21
86.14
70.58
197.11
502.26
1167.57
Marine
Females
14 or under
1431
6.60
24.84
37.32
87.05
256.90
936.94
1545.15
3060.22
15-44
2891
9.97
36.83
55.53
105.32
159.79
573.49
873.73
1700.21
Males
14 or under
1546
7.25
24.85
49.89
92.64
230.25
846.57
1504.37
2885.08
15-44
2151
13.33
52.73
71.49
116.51
165.92
626.85
933.05
1472.98
Both Sexes
14 or under
2977
6.93
24.88
42.07
91.64
243.31
873.87
1522.52
3059.93
15-44
5042
11.58
44.24
62.18
110.07
162.72
602.58
893.82
1576.09
All Fish
Females
14 or under
1431
8.19
32.28
43.09
95.19
324.02
1091.52
1690.99
3982.60
15-44
2891
14.25
47.13
71.58
120.84
226.01
755.51
1126.02
2195.86
Males
14 or under
1546
9.42
34.85
52.85
98.36
304.17
1172.17
1575.43
3393.84
15-44
2151
19.46
68.60
93.65
149.07
241.27
867.70
1208.43
1760.48
Both Sexes
14 or under
2977
8.82
32.88
50.95
98.33
313.90
1128.26
1679.91
3419.49
15-44
5042
16.74
57.88
84.59
138.21
233.30
828.12
1155.30
2003.46
Source: U.S. EPA, 1996.
March 2000
3-34
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-7. Consumers Only Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender - As Consumed
Age (years)
Sample
Size
Mean
(g/day)
90th %
(g/day)
95th %
(g/day)
99th %
(g/day)
Mean
(mg/kg-day)
90th %
(mg/kg-day)
95th %
(mg/kg-day)
99th %
(mg/kg-day)
Freshwater and Estuarine
Females
14 or under
15-44
138
445
38.44
61.40
91.30
148.83
128.97
185.44
182.66
363.56
1639.20
961.58
3915.56
2578.81
6271.09
3403.75
10113.24
6167.24
Males
14 or under
15-44
157
356
52.44
81.56
112.05
224.01
154.44
275
230.74
371
1798.24
1004.96
3759.29
2744.61
3952.99
3348.86
7907.38
4569.62
Both Sexes
14 or under
15-44
295
801
45.73
71.44
108.36
180.67
136.24
230.95
214.62
371.52
1721.99
983.19
3760.67
2616.63
4208.18
3360.85
9789.49
5089.78
Marine
Females
14 or under
15-44
315
774
69.04
76.53
114.23
149.78
162.37
178.74
336.59
271.06
2591.57
1227.41
5074.80
2469.67
6504.67
3007.98
9970.44
4800.68
Males
14 or under
15-44
348
565
78.44
104.57
160.97
191.29
190.68
227.56
336.98
316.69
2471.15
1302.62
4852.33
2390.20
5860.72
2882.91
8495.57
3887.23
Both Sexes
14 or under
15-44
663
1339
73.62
89.93
153.2
171.88
176.9
209.17
337.24
308.06
2532.95
1263.35
5068.69
2464.80
6376.47
2961.92
8749.02
4251.47
All Fish
Females
14 or under
15-44
378
952
69.54
88.8
126.22
170.01
165.27
212.56
338.04
361.04
2683.51
1414.54
5299.68
2726.46
7160.73
3740.83
12473.65
6703.25
Males
14 or under
15-44
429
702
79.72
124.78
161.62
230.77
190
296.66
308.59
397.7
2568.93
1545.93
4714.97
2854.49
5818.08
3773.51
9350.89
5254.04
Both Sexes
14 or under
15-44
807
1654
74.8
106.06
153.7
203.33
178.08
271.66
337.46
372.77
2624.35
1477.57
5020.14
2798.37
6904.83
3747.88
10384.82
5386.43
Source: U.S. EPA, 1996.
March 2000
3-35
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender - Uncooked Fish Weight
Age (years)
Sample
Size
Mean
(g/day)
90th %
(g/day)
95th %
(g/day)
99th %
(g/day)
Mean
(mg/kg-day)
90th %
(mg/kg-day)
95th % 99th %
(mg/kg-day) (mg/kg-day)
Freshwater and Estuarine
Females
14 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
1431
2891
1546
2151
2977
5042
1.99
5.50
2.69
7.87
2.35
6.64
1.81
13.62
1.07
22.10
1.72
18.30
15.88
36.68
18.47
63.26
17.46
47.31
46.82
94.93
57.07
126.61
50.14
109.66
84.78
85.15
91.62
96.91
88.26
90.77
70.75
202.83
38.98
281.17
66.00
250.26
599.06
584.79
868.97
740.91
717.37
631.31
1713.06
1411.42
1642.60
1589.97
1688.55
1529.94
Marine
Females
14 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
1431
2891
1546
2151
2977
5042
8.61
12.84
9.40
17.11
9.02
14.88
31.23
46.66
31.32
66.06
31.52
55.99
49.75)
72.16)
65.37
93.32
56.35
80.70
104.26)
133.69
118.42
155.16
117.75
138.23
333.99
206.03
296.99
212.88
315.12
209.30
1132.99
762.54
1089.46
800.79
1123.28
780.16
1959.91
1137.58
1907.65
1191.75
1909.37
1174.69
3776.60
2174.21
3723.81
1890.42
3820.21
2019.59
All Fish
Females
14 or under
15-44
Males
14 or under
15-44
Both Sexes
14 or under
15-44
1431
2891
1546
2151
2977
5042
10.60
18.35
12.09
24.98
11.36
21.51
41.10
62.21
45.59
87.15
43.00
75.15
56.16
93.13
68.18
122.29
65.34
109.57
130.78
155.75
127.20
197.15
130.41
175.73
418.76
291.18
388.61
309.78
403.38
300.06
1389.10
993.92
1476.31
1096.57
1442.72
1040.98
2341.90
1436.00
2038.58
1566.39
2191.90
1514.82
4985.96
2726.50
4294.12
2275.15
4425.27
2481.23
Source: U.S. EPA, 1996.
March 2000
3-36
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-9. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Age and Gender - Uncooked Fish Weight
Sample
Mean
90th %
95th %
99th %
Mean
90th %
95th %
99th %
Age (years)
Size
(g/day)
(g/day)
(g/day)
(g/day)
(mg/kg-day)
(mg/kg-day)
(mg/kg-day)
(mg/kg-day)
Freshwater and Estuarine
Females
14 or under
138
48.3
117.27
161.44
230.63
2070.41
4450.54
6915.31
13269.61
15-44
445
78.56
191.95
242.76
472.21
1229.97
3045.41
4191.25
7711.43
Males
14 or under
157
64.91
141.35
193.79
287.28
2229.31
4638.34
5071.41
9622.15
15-44
356
104.86
269.96
343.66
494.38
1294.27
3318.89
4275.83
5974.96
Both Sexes
14 or under
295
56.95
134.89
166.32
262.87
2153.11
4634.82
5756.93
12388.27
15-44
801
91.66
237.27
322.06
494.64
1261.99
3276.06
4246.63
6625.15
Marine
Females
14 or under
315
89.92
169.23
198.62
432.51
3359.10
6058.97
8573.62
13050.09
15-44
774
98.53
194.59
231.22
317.42
1582.77
3129.41
3854.14
5961.80
Males
14 or under
348
101.5
205.49
242.28
408.68
3180.45
6434.20
8089.26
10764.01
15-44
565
133.86
244.46
297.67
393.14
1666.42
3102.24
3651.10
4998.14
Both Sexes
14 or under
663
95.56
189.32
231.72
442.87
3272.13
6278.74
8424.77
11838.54
15-44
1339
115.41
223.99
263.76
383.16
1622.75
3120.60
3682.17
5517.95
All Fish
Females
14 or under
378
89.73
163.47
204.14
476.56
3448.73
7100.43
9012.18
15381.13
15-44
952
114.04
220.63
277.69
461.54
1818.32
3506.20
4661.96
8789.33
Males
14 or under
429
102.01
205.25
244.46
386.47
3273.63
5734.46
7570.83
11891.85
15-44
702
160.06
305.61
379.38
495.51
1983.16
3720.05
4769.44
6121.56
Both Sexes
14 or under
807
96.07
195.35
232.85
466.09
3358.33
6333.46
8611.73
12406.35
15-44
1654
136.12
262.15
343.86
488.9
1897.40
3674.88
4709.78
7276.18
Source: U.S. EPA, 1996.
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1 Table 3-10. Mean and 95th Percentile of Fish Consumption (g/day) by Sex and Age"
2
3
4
Age (years)
Total Fish
Mean
95th Percentile
5
Female
0-9
6.1
17.3
10 - 19
9.0
25.0
6
Male
0-9
6.3
15.8
10 - 19
11.2
29.1
7
Male & Female
0-9
6.2
16.5
10-19
10 1
76 8
8
9 " The calculations in this table are based upon respondents who consumed fish in the month of the survey. These
10 respondents are estimated to represent 94.0% of the U.S. population.
11 Source: Javitz, 1980.
12
13
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4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Table 3-11. Best Fits of Lognormal Distributions Using the Nonlinear Optimization (Nlo) Method
Teenagers Children
Shellfish
M -0.183 0.854
o 1.092 0.730
(minSS) 1.19 16.06
Finfish (freshwater)
M 0.578 -0.559
o 0.822 1.141
(minSS) 23.51 2.19
Finfish (saltwater)
M 1.691 0.881
o 0.830 0.970
(min SS) 0_33 4.31
The following equations may be used with the appropriate )j, and o values to obtain an average Daily Consumption Rate (DCR),
in grams, and percentiles of the DCR distribution.
DCR50 = exp {pi)
DCR90 = exp [u + z(0.90) o]
DCR99 = exp [u + z(0.99) o]
DCRavg = exp [fj. + 0.5 a2]
Source: Ruffle et al., 1994.
Table 3-12. Number of Respondents Reporting Consumption of a Specified Number of Servings
of Seafood in 1 Month and Source of Seafood Eaten
Population
Number of Servings in a Month
Group
Total N
1-2
3-5
6-10
11-19
20+
DK
Mostly
Purchased
Mostly
Caught
DK
Age (years)
1-4
102
55
29
12
2
*
4
94
8
*
5-11
166
72
57
21
6
4
6
153
9
4
12-17
137
68
54
9
2
1
3
129
6
2
Note: * = Missing data; DK = Don't know; % = Row percentage; N = Sample size; Refused = Respondent refused to answer.
Source: Tsang andKlepeis, 1996.
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
Table 3-13. Mean Fish Intake Among Individuals Who Eat Fish and Reside
in Households With Recreational Fish Consumption
Recreational Recreational Total Fish Recreational
All Fish Fish Total Fish Fish grams/ Fish grams/
Group meals/week meals/week n grams/day grams/day kg/day kg/day
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
Source: U.S. EPA analysis using data from West et al., 1989.
Table 3-14. Children's 5 and Under Fish Consumption Rates - Throughout Year
Number of Grams/Dav
Unweighted Cumul;
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.
March 2000
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
Table 3-15. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/day)
Age
(years)
N
Mean
St.
Dev.
P10
P25
P50
P75
P90
Minimu
m
Maximum
Total Fat Intake
6 Mo.
125
37.1
17.5
18.7
25.6
33.9
46.3
60.8
3.4
107.6
1
99
59.1
26.0
29.1
40.4
56.1
71.4
94.4
21.6
152.7
2
135
86.7
41.3
39.9
55.5
79.2
110.5
141.1
26.5
236.4
3
106
91.6
38.8
50.2
63.6
82.6
114.6
153.0
32.6
232.5
4
219
98.6
56.1
46.0
66.8
87.0
114.6
163.3
29.3
584.6
10
871
93.2
50.8
45.7
60.5
81.4
111.3
154.5
14.6
529.5
13
148
107.0
53.9
53.0
69.8
90.8
130.7
184.1
9.8
282.2
15
108
97.7
48.7
46.1
65.2
85.8
124.0
165.2
10.0
251.3
17
159
107.8
64.3
41.4
59.7
97.3
140.2
195.1
8.5
327.4
Total Animal Fat
6 Mo.
125
18.4
16.0
0.7
4.2
13.9
28.4
42.5
0.0
61.1
1
99
36.5
20.0
15.2
23.1
33.0
45.9
65.3
0.0
127.1
2
135
49.5
28.3
20.1
28.9
42.1
66.0
81.4
10.0
153.4
3
106
50.1
29.4
21.3
29.1
42.9
64.4
88.9
14.1
182.6
4
219
50.8
31.7
21.4
28.1
42.6
66.4
92.6
5.9
242.2
10
871
54.1
39.6
20.3
30.6
45.0
64.6
97.5
0.0
412.3
13
148
56.2
39.8
19.8
28.5
44.8
72.8
109.4
4.7
209.6
15
108
53.8
35.1
15.9
28.3
44.7
67.9
105.8
0.6
182.1
17
159
64.4
48.5
15.2
30.7
51.6
86.6
128.8
2.6
230.3
Total Vegetable Fat Intake
6 Mo.
125
9.2
12.8
0.6
1.2
2.8
11.6
29.4
0.0
53.2
1
99
15.4
14.3
3.7
6.1
11.3
18.1
38.0
0.2
70.2
2
135
19.3
16.3
3.8
7.9
14.8
26.6
42.9
0.7
96.6
3
106
21.1
15.5
3.9
8.6
18.7
26.6
45.2
1.0
70.4
4
219
24.5
18.6
5.7
10.4
21.8
33.3
48.5
0.9
109.0
10
871
23.7
21.6
4.3
9.5
18.3
30.6
49.0
0.6
203.7
13
148
34.3
27.4
8.4
17.9
31.2
44.6
57.5
0.0
238.3
15
108
27.3
22.8
5.1
11.9
22.6
38.1
54.4
0.7
132.2
17
159
25.7
21.3
4.2
11.7
20.8
32.9
47.6
0.0
141.5
Total Fish Fat Intake
6 Mo.
125
0.046
0.130
0.000
0.000
0.000
0.000
0.140
0.000
0.900
1
99
0.047
0.233
0.000
0.000
0.000
0.000
0.000
0.000
1.900
2
135
0.036
0.229
0.000
0.000
0.000
0.000
0.000
0.000
1.900
3
106
0.100
0.591
0.000
0.000
0.000
0.000
0.000
0.000
4.500
4
219
2.255
31.05
0.000
0.000
0.000
0.000
0.000
0.000
459.2
10
871
0.292
1.452
0.000
0.000
0.000
0.000
0.000
0.000
19.2
13
148
0.269
2.151
0.000
0.000
0.000
0.000
0.000
0.000
25.4
15
108
0.431
1.467
0.000
0.000
0.000
0.000
0.000
0.000
9.500
17
159
0.465
2.010
0.000
0.000
0.000
0.000
0.000
0.000
15.3
Source: Frank etal., 1986.
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
Table 3-16. Fat Intake Among Children Based on Data from the Bogalusa Heart Study, 1973-1982 (g/kg/day)
Age
(years)
N
Mean
St.
Dev.
P10
P25
P50
P75
P90
Minimu
m
Maximum
Total Fat Intake
6 Mo.
125
4.94
2.32
2.41
3.28
4.67
6.19
7.97
0.39
13.16
1
99
6.12
2.75
3.03
4.11
5.66
7.47
9.53
2.27
16.38
2
132
6.98
3.34
3.37
4.45
6.15
8.56
11.94
2.14
18.69
3
106
6.40
2.67
3.61
4.56
5.50
8.16
9.93
2.18
16.73
4
218
6.05
3.66
2.88
3.96
5.24
6.97
9.98
2.03
38.21
10
861
2.70
1.52
1.23
1.68
2.35
3.32
4.54
0.33
13.86
13
147
2.28
1.30
1.03
1.47
1.99
2.80
3.81
0.21
10.19
15
105
1.73
0.84
0.84
1.18
1.54
2.14
3.13
0.15
4.73
17
149
1.77
1.02
0.69
0.92
1.62
2.24
3.10
0.16
6.23
Total Animal Fat
6 Mo.
125
2.43
2.13
0.08
0.60
2.03
3.74
5.47
0.00
8.99
1
99
3.78
2.12
1.70
2.37
3.39
4.90
6.48
0.00
13.64
2
132
3.99
2.31
1.73
2.29
3.36
5.22
6.69
0.67
13.40
3
106
3.50
2.01
1.56
2.07
3.13
4.18
6.05
0.90
13.14
4
218
3.12
2.05
1.26
1.73
2.64
4.04
5.38
0.39
15.43
10
861
1.56
1.16
0.55
0.84
1.28
1.92
2.83
0.00
10.79
13
147
1.19
0.86
0.40
0.59
0.94
1.59
2.28
0.08
5.19
15
105
0.95
0.62
0.32
0.54
0.81
1.25
1.90
0.01
3.07
17
149
1.04
0.77
0.26
0.51
0.83
1.38
1.97
0.05
4.15
Total Vegetable Fat Intake
6 Mo.
125
1.237
1.794
0.079
0.160
0.354
1.558
4.076
0.000
8.199
1
99
1.594
1.550
0.401
0.630
1.169
1.868
3.784
0.022
7.610
2
132
1.561
1.381
0.299
0.647
1.134
2.037
3.504
0.057
8.474
3
106
1.474
1.066
0.277
0.603
1.359
1.963
2.958
0.077
5.047
4
218
1.492
1.153
0.356
0.617
1.208
2.059
2.827
0.061
7.315
10
861
0.685
0.638
0.127
0.257
0.516
0.863
1.440
0.019
4.244
13
147
0.748
0.790
0.161
0.381
0.606
0.931
1.248
0.000
8.603
15
105
0.490
0.397
0.086
0.225
0.436
0.653
0.904
0.010
2.226
17
149
0.439
0.359
0.071
0.175
0.353
0.597
0.908
0.000
2.128
Total Fish Fat Intake
6 Mo.
125
0.006
0.018
0.000
0.000
0.000
0.000
0.021
0.000
0.127
1
99
0.005
0.026
0.000
0.000
0.000
0.000
0.000
0.000
0.219
2
132
0.003
0.018
0.000
0.000
0.000
0.000
0.000
0.000
0.160
3
106
0.007
0.042
0.000
0.000
0.000
0.000
0.000
0.000
0.341
4
218
0.148
2.034
0.000
0.000
0.000
0.000
0.000
0.000
30.03
10
861
0.009
0.047
0.000
0.000
0.000
0.000
0.000
0.000
0.625
13
147
0.005
0.036
0.000
0.000
0.000
0.000
0.000
0.000
0.405
15
105
0.008
0.028
0.000
0.000
0.000
0.000
0.000
0.000
0.189
17
149
0.008
0.033
0.000
0.000
0.000
0.000
0.000
0.000
0.234
Source: Frank etal., 1986.
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Table 3-17. Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gender3
Total
Males
Females
Age
Mean Fat Intake
Mean Fat Intake
Mean Fat Intake
(yrs)
N
(g/day)
N
(g/day)
N
(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
a Total dietary fat intake includes all fat (i.e., saturated and unsaturated) derived from consumption of foods and beverages
(excluding plain drinking water).
Source: Adapted from CDC, 1994.
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
Table 3-18. Per Capita Total Dietary Intake
Population
Percent
Adjusted
Group
Consuming
Mean
SE
PI
P5
P10
P25
P50
P75
P90
P95
P99
P100
(g/day, as consumed)
Age (years)
Age < 01
92.2%
1.0E+03
2.6E+01
8.0E+00
1.3E+02
3.5E+02
8.4E+02
1.1E+03
1.3E+03
1.6E+03
1.8E+03
2.3E+03
2.5E+03
Age 01-02
100.0%
1.1E+03
1.1E+01
3.2E+02
5.1E+02
6.2E+02
8.1E+02
1.1E+03
1.3E+03
1.6E+03
1.8E+03
2.2E+03
2.8E+03
Age 03-05
100.0%
1.0E+03
9.9E+00
3.4E+02
5.0E+02
5.8E+02
7.6E+02
1.0E+03
1.2E+03
1.5E+03
1.7E+03
2.1E+03
2.6E+03
Age 06-11
100.0%
1.1E+03
1.1E+01
4.0E+02
5.7E+02
6.7E+02
8.3E+02
1.1E+03
1.3E+03
1.7E+03
1.9E+03
2.3E+03
3.6E+03
Age 12-19
100.0%
1.2E+03
1.7E+01
2.9E+02
4.2E+02
5.6E+02
7.8E+02
1.1E+03
1.5E+03
1.9E+03
2.3E+03
3.2E+03
9.0E+03
(s/ks/dav. as consumed)
Age (years)
Age < 01
88.0%
1.4e+02
4.6e+00
0
6.9e+00
2.4e+01
1.0e+02
1.4e+02
1.8e+02
2.2e+02
2.4e+02
3.2e+02
5.8e+02
Age 01-02
96.0%
8.4e+01
l.le+00
0
2.6e+01
3.9e+01
6.0e+01
8.1e+01
1.0e+02
1.3e+02
1.5e+02
1.9e+02
2.6e+02
Age 03-05
93.2%
5.5e+01
7.3e-01
0
0.0e+00
2.6e+01
3.8e+01
5.4e+01
7.0e+01
8.9e+01
1.0e+02
1.3e+02
1.9e+02
Age 06-11
93.4%
3.6e+01
5.1e-01
0
0.0e+00
1.5e+01
2.4e+01
3.4e+01
4.6e+01
6.0e+01
6.9e+01
8.9e+01
1.2e+02
Aae 12-19
98.2%
2.0e+01
3.1e-01
0
6.2e+00
8.1e+00
1.2e+01
1.8e+01
2.6e+01
3.5e+01
4.0e+01
5.8e+01
1.2e+02
Note: SE = Standard error.
P = percentile of the distribution.
Source: Based on EPA's analysis of the 1994-96 CSFII.
June 2000
3-44
DRAFT-DO NOT QUOTE OR CITE
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Table 3-19. Per Capita Intake of Major Food Groups (g/day, as consumed)
Food
Group
Percent
Consuming
MEAN
Adjusted
SE
PI
P5
P10
P25
P50
P75
P90
P95
P99
P100
Age <1 Year
Tota
Dietary Intake
92.2%
1.0E+03
2.6E+01
8.0E+00
1.3E+02
3.5E+02
8.4E+02
1.1E+03
1.3E+03
1.6E+03
1.8E+03
2.3E+03
2.5E+03
Tota
Dairy Intake
87.7%
7.9E+02
2.4E+01
0.0E+00
3.1E+00
1.3E+02
6.1E+02
8.1E+02
9.9E+02
1.3E+03
1.5E+03
2.0E+03
2.1E+03
Tota
Meat Intake
33.4%
1.1E+01
1.9E+00
0.0E+00
0.0E+00
0.0E+00
0.0E+00
0.0E+00
1.3E+01
3.5E+01
5.7E+01
8.9E+01
1.2E+02
Tota
Egg Intake
30.1%
3.9E+00
1.3E+00
0.0E+00
0.0E+00
0.0E+00
0.0E+00
0.0E+00
6.3E-01
2.7E+00
3.8E+01
7.5E+01
8.9E+01
Tota
Fish Intake
20.9%
9.6E-01
4.2E-01
0.0E+00
0.0E+00
0.0E+00
0.0E+00
0.0E+00
0.0E+00
2.5E+00
5.0E+00
1.3E+01
4.3E+01
Tota
Grain Intake
67.4%
3.7E+01
3.6E+00
0.0E+00
0.0E+00
0.0E+00
0.0E+00
1.4E+01
4.7E+01
1.2E+02
1.8E+02
2.4E+02
3.6E+02
Tota
Vegetable Intake
52.4%
6.0E+01
5.7E+00
0.0E+00
0.0E+00
0.0E+00
0.0E+00
2.8E+01
1.1E+02
1.6E+02
1.9E+02
3.0E+02
7.0E+02
Tota
Fruit Intake
58.8%
1.1E+02
9.0E+00
0.0E+00
0.0E+00
0.0E+00
0.0E+00
6.4E+01
1.9E+02
2.9E+02
3.5E+02
5.6E+02
7.5E+02
Tota
Fat Intake"
30.1%
7.5E-01
1.5E-01
0.0E+00
0.0E+00
0.0E+00
0.0E+00
0.0E+00
1.3E+00
2.5E+00
3.3E+00
7.5E+00
1.1E+01
Ages 1-2 Years
Tota
Dietary Intake
100.0%
1.1E+03
1.1E+01
3.2E+02
5.1E+02
6.2E+02
8.1E+02
1.1E+03
1.3E+03
1.6E+03
1.8E+03
2.2E+03
2.8E+03
Tota
Dairy Intake
99.7%
4.8E+02
8.3E+00
5.3E+00
7.0E+01
1.3E+02
2.6E+02
4.3E+02
6.5E+02
8.9E+02
1.1E+03
1.4E+03
2.0E+03
Tota
Meat Intake
97.8%
5.9E+01
1.2E+00
0.0E+00
6.2E+00
1.2E+01
2.7E+01
5.2E+01
8.2E+01
1.2E+02
1.4E+02
1.9E+02
3.2E+02
Tota
Egg Intake
92.5%
1.6E+01
7.1E-01
0.0E+00
0.0E+00
1.7E-01
8.1E-01
2.3E+00
2.4E+01
4.9E+01
7.0E+01
1.1E+02
1.9E+02
Tota
Fish Intake
60.7%
4.9E+00
4.7E-01
0.0E+00
0.0E+00
0.0E+00
0.0E+00
1.2E+00
3.9E+00
1.1E+01
2.4E+01
6.9E+01
1.7E+02
Tota
Grain Intake
99.6%
1.5E+02
2.4E+00
1.6E+01
3.9E+01
5.4E+01
8.7E+01
1.3E+02
1.9E+02
2.6E+02
3.2E+02
4.5E+02
6.5E+02
Tota
Vegetable Intake
99.3%
1.3E+02
2.5E+00
3.9E+00
1.9E+01
3.4E+01
6.6E+01
1.1E+02
1.6E+02
2.4E+02
3.1E+02
4.4E+02
7.1E+02
Tota
Fruit Intake
89.0%
2.5E+02
6.4E+00
0.0E+00
0.0E+00
0.0E+00
9.3E+01
2.0E+02
3.6E+02
5.4E+02
7.1E+02
9.2E+02
2.1E+03
Tota
Fat Intake"
93.9%
5.5E+00
1.5E-01
0.0E+00
0.0E+00
6.7E-01
1.9E+00
4.1E+00
7.2E+00
1.2E+01
1.6E+01
2.6E+01
5.0E+01
Ages 3-5 Years
Tota
Dietary Intake
100.0%
1.0E+03
9.9E+00
3.4E+02
5.0E+02
5.8E+02
7.6E+02
1.0E+03
1.2E+03
1.5E+03
1.7E+03
2.1E+03
2.6E+03
Tota
Dairy Intake
99.6%
3.9E+02
6.3E+00
7.8E+00
7.4E+01
1.2E+02
2.2E+02
3.6E+02
5.1E+02
7.2E+02
8.3E+02
1.2E+03
1.7E+03
Tota
Meat Intake
99.0%
7.9E+01
1.3E+00
0.0E+00
1.6E+01
2.4E+01
4.4E+01
7.2E+01
1.0E+02
1.4E+02
1.7E+02
2.4E+02
3.8E+02
Tota
Egg Intake
90.8%
1.3E+01
7.0E-01
0.0E+00
0.0E+00
8.3E-02
7.3E-01
1.8E+00
2.0E+01
4.3E+01
6.3E+01
1.1E+02
2.5E+02
Tota
Fish Intake
61.0%
6.1E+00
5.4E-01
0.0E+00
0.0E+00
0.0E+00
0.0E+00
1.7E+00
5.0E+00
1.4E+01
3.4E+01
8.0E+01
2.0E+02
Tota
Grain Intake
99.8%
1.9E+02
2.8E+00
4.7E+01
7.0E+01
8.8E+01
1.2E+02
1.7E+02
2.4E+02
3.1E+02
3.6E+02
5.3E+02
1.6E+03
Tota
Vegetable Intake
99.4%
1.4E+02
2.5E+00
3.4E+00
2.4E+01
4.0E+01
7.4E+01
1.2E+02
1.8E+02
2.6E+02
3.2E+02
4.8E+02
7.6E+02
Tota
Fruit Intake
84.4%
2.1E+02
5.5E+00
0.0E+00
0.0E+00
0.0E+00
6.2E+01
1.6E+02
3.1E+02
4.7E+02
5.6E+02
8.4E+02
1.9E+03
Tota
Fat Intake"
95.6%
7.8E+00
2.0E-01
0.0E+00
1.7E-01
1.0E+00
2.7E+00
5.6E+00
1.1E+01
1.8E+01
2.2E+01
3.7E+01
6.3E+01
Ages 6-11 Years
Tota
Dietary Intake
100.0%
1.1E+03
1.1E+01
4.0E+02
5.7E+02
6.7E+02
8.3E+02
1.1E+03
1.3E+03
1.7E+03
1.9E+03
2.3E+03
3.6E+03
Tota
Dairy Intake
99.7%
4.3E+02
6.7E+00
1.4E+01
7.6E+01
1.3E+02
2.5E+02
3.9E+02
5.8E+02
7.7E+02
8.6E+02
1.2E+03
2.7E+03
Tota
Meat Intake
99.0%
9.4E+01
1.6E+00
2.5E+00
1.8E+01
2.8E+01
5.1E+01
8.5E+01
1.2E+02
1.7E+02
2.0E+02
3.0E+02
4.1E+02
Tota
Egg Intake
91.6%
1.3E+01
7.3E-01
0.0E+00
0.0E+00
2.1E-01
9.0E-01
2.2E+00
6.5E+00
4.6E+01
6.6E+01
1.3E+02
2.2E+02
Tota
Fish Intake
62.4%
8.9E+00
7.9E-01
0.0E+00
0.0E+00
0.0E+00
0.0E+00
2.4E+00
6.1E+00
1.9E+01
4.4E+01
1.3E+02
2.1E+02
Tota
Grain Intake
99.9%
2.3E+02
2.9E+00
5.0E+01
8.5E+01
1.1E+02
1.5E+02
2.1E+02
2.8E+02
3.7E+02
4.3E+02
5.9E+02
7.8E+02
Tota
Vegetable Intake
99.7%
1.7E+02
3.1E+00
1.0E+01
3.6E+01
5.4E+01
9.1E+01
1.4E+02
2.2E+02
3.2E+02
3.9E+02
5.9E+02
1.2E+03
Tota
Fruit Intake
77.0%
1.7E+02
5.6E+00
0.0E+00
0.0E+00
0.0E+00
3.0E+01
1.2E+02
2.6E+02
4.3E+02
5.1E+02
8.7E+02
1.2E+03
Tota
Fat Intake"
96.9%
1.1E+01
2.8E-01
0.0E+00
7.8E-01
1.6E+00
3.7E+00
7.7E+00
1.4E+01
2.4E+01
3.0E+01
5.2E+01
8.2E+01
Ages 12-19 Years
Total Dietary Intake
100.0%
1.2E+03
1.7E+01
2.9E+02
4.2E+02
5.6E+02
7.8E+02
1.1E+03
1.5E+03
1.9E+03
2.3E+03
3.2E+03
9.0E+03
June 2000
3-45
DRAFT-DO NOT QUOTE OR CITE
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Table 3-19. Per Capita Intake of Major Food Groups (g/day, as consumed) (continued)
Food Percent Adjusted
Group
Consuming
MEAN
SE
PI
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total Dairy Intake
98.7%
3.6E+02
8.8E+00
0.0E+00
1.4E+01
3.2E+01
1.1E+02
2.7E+02
5.1E+02
7.8E+02
1.0E+03
1.5E+03
2.0E+03
Total Meat Intake
99.1%
1.3E+02
2.9E+00
2.9E+00
2.0E+01
3.6E+01
7.0E+01
1.2E+02
1.7E+02
2.5E+02
3.0E+02
4.4E+02
2.1E+03
Total Egg Intake
92.7%
1.8E+01
9.5E-01
0.0E+00
0.0E+00
4.4E-01
1.5E+00
3.3E+00
1.1E+01
6.4E+01
8.8E+01
1.5E+02
3.1E+02
Total Fish Intake
64.4%
1.2E+01
1.0E+00
0.0E+00
0.0E+00
0.0E+00
0.0E+00
3.7E+00
1.1E+01
2.5E+01
6.0E+01
1.5E+02
3.7E+02
Total Grain Intake
100.0%
2.6E+02
4.2E+00
3.9E+01
7.8E+01
1.1E+02
1.6E+02
2.3E+02
3.4E+02
4.4E+02
5.3E+02
8.4E+02
1.7E+03
Total Vegetable Intake
99.6%
2.4E+02
5.1E+00
1.8E+01
4.8E+01
7.3E+01
1.3E+02
2.1E+02
3.1E+02
4.4E+02
5.4E+02
8.1E+02
3.3E+03
Total Fruit Intake
61.9%
1.6E+02
7.6E+00
0.0E+00
0.0E+00
0.0E+00
0.0E+00
8.4E+01
2.4E+02
4.3E+02
6.2E+02
9.3E+02
2.0E+03
Total Fat Tntakpa
96 7%
1 6F+01
4 6F-01
0 OF+OO
9 7F-01
7 4F+00
3F+00
1 IF+01
7 OF+01
3 7F+01
4 9F+01
8 SF+01
1 3F+07
a Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
Note: SE = Standard error.
P = percentile of the distribution.
Source: Based on EPA's analysis of the 1994-96 CSFII.
June 2000
3-46
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-20. Per Capita Intake of Major Food Groups (g/kg/day, as consumed)
Food
Group
Percent
Consuming
MEAN
Adjusted
SE
PI
P5 P10
P25
P50
P75
P90
P95
P99
P100
Age <1 Year
Tota
Dietary Intake
88.0%
1.4E+02
4.6E+00
0.0E+00
6.9E+00 2.4E+01
1.0E+02
1.4E+02
1.8E+02
2.2E+02
2.4E+02
3.2E+02
5.8E+02
Tota
Dairy Intake
83.6%
1.1E+02
4.9E+00
0.0E+00
0.0E+00 2.5E+00
6.4E+01
1.0E+02
1.6E+02
2.0E+02
2.4E+02
3.2E+02
5.8E+02
Tota
Meat Intake
32.3%
1.1E+00
2.0E-01
0.0E+00
0.0E+00 0.0E+00
0.0E+00
0.0E+00
1.4E+00
3.9E+00
5.9E+00
1.1E+01
1.2E+01
Tota
Egg Intake
29.0%
4.1E-01
1.4E-01
0.0E+00
0.0E+00 0.0E+00
0.0E+00
0.0E+00
7.0E-02
2.3E-01
3.3E+00
8.3E+00
1.1E+01
Tota
Fish Intake
20.9%
1.1E-01
4.7E-02
0.0E+00
0.0E+00 0.0E+00
0.0E+00
0.0E+00
0.0E+00
3.3E-01
5.3E-01
1.6E+00
4.7E+00
Tota
Grain Intake
64.9%
4.1E+00
4.2E-01
0.0E+00
0.0E+00 0.0E+00
0.0E+00
1.6E+00
5.4E+00
1.3E+01
2.0E+01
2.7E+01
4.0E+01
Tota
Vegetable Intake
50.1%
6.9E+00
7.2E-01
0.0E+00
0.0E+00 0.0E+00
0.0E+00
2.3E+00
1.2E+01
1.8E+01
2.4E+01
3.6E+01
1.0E+02
Tota
Fruit Intake
56.8%
1.3E+01
1.1E+00
0.0E+00
0.0E+00 0.0E+00
0.0E+00
7.6E+00
2.3E+01
3.6E+01
4.1E+01
6.4E+01
1.1E+02
Tota
Fat Intake"
29.2%
8.3E-02
1.7E-02
0.0E+00
0.0E+00 0.0E+00
0.0E+00
0.0E+00
1.4E-01
2.6E-01
4.0E-01
7.2E-01
1.7E+00
Ages 1-2 Years
Tota
Dietary Intake
96.0%
8.4E+01
1.1E+00
0.0E+00
2.6E+01 3.9E+01
6.0E+01
8.1E+01
1.0E+02
1.3E+02
1.5E+02
1.9E+02
2.6E+02
Tota
Dairy Intake
95.7%
3.7E+01
7.8E-01
0.0E+00
4.1E-01 6.7E+00
1.8E+01
3.2E+01
5.1E+01
7.4E+01
9.0E+01
1.3E+02
1.8E+02
Tota
Meat Intake
94.0%
4.4E+00
9.4E-02
0.0E+00
0.0E+00 7.6E-01
1.9E+00
3.8E+00
6.2E+00
8.9E+00
1.0E+01
1.5E+01
2.4E+01
Tota
Egg Intake
88.8%
1.2E+00
5.5E-02
0.0E+00
0.0E+00 0.0E+00
5.3E-02
1.6E-01
1.8E+00
3.8E+00
5.1E+00
8.3E+00
1.4E+01
Tota
Fish Intake
58.2%
3.7E-01
3.7E-02
0.0E+00
0.0E+00 0.0E+00
0.0E+00
8.0E-02
2.9E-01
7.8E-01
1.8E+00
4.7E+00
1.4E+01
Tota
Grain Intake
95.6%
1.1E+01
2.0E-01
0.0E+00
1.7E+00 3.6E+00
6.4E+00
9.8E+00
1.4E+01
2.1E+01
2.5E+01
3.5E+01
4.8E+01
Tota
Vegetable Intake
95.4%
9.5E+00
2.1E-01
0.0E+00
4.7E-01 1.9E+00
4.5E+00
8.0E+00
1.3E+01
1.9E+01
2.3E+01
3.3E+01
8.3E+01
Tota
Fruit Intake
85.5%
1.9E+01
5.2E-01
0.0E+00
0.0E+00 0.0E+00
6.4E+00
1.6E+01
2.7E+01
4.2E+01
5.4E+01
7.7E+01
1.3E+02
Tota
Fat Intakea
90.1%
4.2E-01
1.2E-02
0.0E+00
0.0E+00 1.0E-02
1.4E-01
3.1E-01
5.5E-01
9.1E-01
1.2E+00
2.2E+00
3.3E+00
Ages 3-5 Years
Tota
Dietary Intake
93.2%
5.5E+01
7.3E-01
0.0E+00
0.0E+00 2.6E+01
3.8E+01
5.4E+01
7.0E+01
8.9E+01
1.0E+02
1.3E+02
1.9E+02
Tota
Dairy Intake
92.9%
2.1E+01
4.0E-01
0.0E+00
0.0E+00 3.5E+00
1.0E+01
1.9E+01
2.9E+01
4.1E+01
4.9E+01
6.6E+01
9.0E+01
Tota
Meat Intake
92.2%
4.1E+00
8.0E-02
0.0E+00
0.0E+00 7.7E-01
2.1E+00
3.8E+00
5.6E+00
7.8E+00
9.4E+00
1.3E+01
2.1E+01
Tota
Egg Intake
84.5%
6.5E-01
3.7E-02
0.0E+00
0.0E+00 0.0E+00
3.0E-02
8.8E-02
4.6E-01
2.1E+00
3.4E+00
6.1E+00
1.3E+01
Tota
Fish Intake
56.4%
3.2E-01
3.0E-02
0.0E+00
0.0E+00 0.0E+00
0.0E+00
6.9E-02
2.5E-01
6.6E-01
1.7E+00
4.6E+00
9.6E+00
Tota
Grain Intake
93.1%
1.0E+01
2.0E-01
0.0E+00
0.0E+00 3.7E+00
6.3E+00
9.2E+00
1.3E+01
1.8E+01
2.1E+01
3.4E+01
1.2E+02
Tota
Vegetable Intake
92.7%
7.3E+00
1.6E-01
0.0E+00
0.0E+00 1.3E+00
3.4E+00
6.2E+00
9.7E+00
1.4E+01
1.8E+01
2.9E+01
4.6E+01
Tota
Fruit Intake
79.0%
1.1E+01
3.4E-01
0.0E+00
0.0E+00 0.0E+00
2.3E+00
8.1E+00
1.6E+01
2.6E+01
3.3E+01
5.3E+01
1.1E+02
Tota
Fat Intake"
89.2%
4.2E-01
1.2E-02
0.0E+00
0.0E+00 0.0E+00
1.3E-01
3.0E-01
5.9E-01
9.5E-01
1.3E+00
1.8E+00
3.1E+00
Ages 6-11 Years
Tota
Dietary Intake
93.4%
3.6E+01
5.1E-01
0.0E+00
0.0E+00 1.5E+01
2.4E+01
3.4E+01
4.6E+01
6.0E+01
6.9E+01
8.9E+01
1.2E+02
Tota
Dairy Intake
93.3%
1.4E+01
2.8E-01
0.0E+00
0.0E+00 2.2E+00
6.4E+00
1.2E+01
1.9E+01
2.7E+01
3.3E+01
4.3E+01
8.1E+01
Tota
Meat Intake
92.4%
2.9E+00
6.0E-02
0.0E+00
0.0E+00 5.2E-01
1.4E+00
2.5E+00
4.0E+00
5.6E+00
6.8E+00
1.0E+01
1.8E+01
Tota
Egg Intake
85.3%
4.0E-01
2.5E-02
0.0E+00
0.0E+00 0.0E+00
2.2E-02
6.3E-02
1.8E-01
1.4E+00
2.2E+00
4.4E+00
9.3E+00
Tota
Fish Intake
57.5%
2.6E-01
2.5E-02
0.0E+00
0.0E+00 0.0E+00
0.0E+00
5.8E-02
1.8E-01
4.8E-01
1.3E+00
4.2E+00
6.7E+00
Tota
Grain Intake
93.4%
7.2E+00
1.2E-01
0.0E+00
0.0E+00 2.5E+00
4.3E+00
6.7E+00
9.4E+00
1.3E+01
1.6E+01
2.0E+01
3.6E+01
Tota
Vegetable Intake
93.2%
5.3E+00
1.2E-01
0.0E+00
0.0E+00 1.1E+00
2.5E+00
4.3E+00
7.1E+00
1.0E+01
1.4E+01
2.1E+01
5.2E+01
Tota
Fruit Intake
71.2%
5.4E+00
2.0E-01
0.0E+00
0.0E+00 0.0E+00
0.0E+00
3.4E+00
7.9E+00
1.4E+01
1.8E+01
2.8E+01
4.5E+01
Tota
Fat Intake"
90.5%
3.4E-01
1.0E-02
0.0E+00
0.0E+00 2.2E-02
9.8E-02
2.3E-01
4.5E-01
8.0E-01
1.1E+00
1.5E+00
3.1E+00
Ages 12-19 Years
Total Dietary Intake
98.2%
2.0E+01
3.1E-01
0.0E+00
6.2E+00 8.1E+00
1.2E+01
1.8E+01
2.6E+01
3.5E+01
4.0E+01
5.8E+01
1.2E+02
June 2000 3-47 DRAFT-DO NOT QUOTE OR CITE
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Table 3-20. Per Capita Intake of Major Food Groups (g/kg/day, as consumed) (continued)
Food
Percent
Adjusted
Group
Consuming
MEAN
SE
PI
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total Dairy Intake
96.9%
6.1E+00
1.6E-01
0.0E+00
1.7E-01
4.1E-01
1.8E+00
4.5E+00
8.8E+00
1.3E+01
1.8E+01
2.8E+01
3.8E+01
Total Meat Intake
97.3%
2.2E+00
4.6E-02
0.0E+00
2.7E-01
5.3E-01
1.1E+00
1.9E+00
2.8E+00
3.9E+00
4.9E+00
7.5E+00
2.7E+01
Total Egg Intake
91.0%
2.9E-01
1.5E-02
0.0E+00
0.0E+00
6.0E-03
2.4E-02
5.5E-02
1.8E-01
1.0E+00
1.4E+00
2.5E+00
4.7E+00
Total Fish Intake
62.9%
2.0E-01
1.7E-02
0.0E+00
0.0E+00
0.0E+00
0.0E+00
5.5E-02
1.7E-01
4.2E-01
1.1E+00
2.5E+00
5.4E+00
Total Grain Intake
98.2%
4.4E+00
8.0E-02
0.0E+00
1.1E+00
1.5E+00
2.5E+00
3.8E+00
5.5E+00
7.9E+00
9.7E+00
1.4E+01
3.5E+01
Total Vegetable Intake
97.9%
4.0E+00
8.5E-02
0.0E+00
6.3E-01
1.1E+00
2.1E+00
3.4E+00
5.1E+00
7.4E+00
9.3E+00
1.5E+01
4.2E+01
Total Fruit Intake
60.7%
2.8E+00
1.3E-01
0.0E+00
0.0E+00
0.0E+00
0.0E+00
1.4E+00
4.1E+00
8.0E+00
1.1E+01
1.7E+01
3.2E+01
Total Fat Tntakpa
9
-------
Table 3-21. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Food Intake
Food Low-end consumers Mid-range consumers High-end consumers Low-end consumers Mid-range consumers High-end consumers
Group Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent
Age <1 Year (g/day, as consumed) j Age <1 Year (g/kg/day, as consumed)
Total Foods 1.4E+00 100.0% 9.9E+02 100.0% 1.8E+03 100.0% ! 0.0E+00 0.0% 1.3E+02 100.0% 2.6E+02 100.0%
Total Dairy 9.4E-02 6.8% 8.4E+02 84.9% 1.4E+03 79.9% i 0.0E+00 0.0% 9.6E+01 75.2% 2.4E+02 92.1%
Total Meats 0.0E+00 0.0% 4.9E+00 0.5% 7.7E+00 0.4% i 0.0E+00 0.0% 1.8E+00 1.4% 1.8E-01 0.1%
Total Fish 0.0E+00 0.0% 4.6E-01 0.0% 6.0E-01 0.0% i 0.0E+00 0.0% 1.2E-01 0.1% 2.3E-02 0.0%
Total Eggs 0.0E+00 0.0% 2.8E+00 0.3% 1.4E+00 0.1% i 0.0E+00 0.0% 1.0E+00 0.8% 8.0E-03 0.0%
Total Grains 5.8E-01 41.7% 2.1E+01 2.1% 6.8E+01 3.8% i 0.0E+00 0.0% 5.3E+00 4.1% 4.0E+00 1.5%
Total Vegetables 4.0E-01 28.7% 2.6E+01 2.6% 1.1E+02 6.1% i 0.0E+00 0.0% 7.8E+00 6.1% 6.9E+00 2.6%
Total Fruits 3.2E-01 22.8% 9.5E+01 9.6% 1.7E+02 9.5% i 0.0E+00 0.0% 1.6E+01 12.2% 9.6E+00 3.7%
Total^Mฃ^^_^^_0ฃEiซ0__0ฃ%_^^i0E;01^_^_0J%_^^^;01^_^_0ฃ%__i_0ฃE+00__0i0%_^Ji4E;01^_^_0il%_^^i0E;02__0i0%_
Ages 1-2 Years (g/day, as consumed) j Ages 1-2 Years (g/kg/day, as consumed)
Total Foods 4.8E+02 100.0% 1.1E+03 100.0% 1.9E+03 100.0% ! 1.9E+01 100% 8.1E+01 100.0% 1.6E+02 100.0%
Total Dairy 1.6E+02 33.3% 4.5E+02 42.5% 9.2E+02 49.1% i 6.0E+00 31% 3.4E+01 42.5% 8.3E+01 52.3%
Total Meats 4.8E+01 10.0% 5.9E+01 5.6% 7.0E+01 3.7% i 2.0E+00 11% 4.8E+00 5.9% 5.6E+00 3.5%
Total Fish 2.4E+00 0.5% 5.6E+00 0.5% 6.9E+00 0.4% i 8.9E-02 0% 5.5E-01 0.7% 5.0E-01 0.3%
Total Eggs 1.2E+01 2.5% 1.5E+01 1.5% 2.3E+01 1.2% i 6.7E-01 3% 1.4E+00 1.7% 1.6E+00 1.0%
Total Grains 1.0E+02 21.0% 1.5E+02 14.5% 1.8E+02 9.8% i 4.2E+00 22% 1.1E+01 13.6% 1.5E+01 9.2%
Total Vegetables 7.4E+01 15.3% 1.2E+02 11.5% 1.9E+02 10.0% i 3.2E+00 17% 1.0E+01 12.5% 1.5E+01 9.6%
Total Fruits 8.0E+01 16.7% 2.5E+02 23.3% 4.7E+02 25.3% i 2.8E+00 14% 1.8E+01 22.6% 3.8E+01 23.7%
Total^Mฃ^^_^^^i7Eiซ0__0i8%_^^i7Eiซ0__0i5%_^^i5Eiซ0__0i4%_iji6E;01^_^^4^_^^i4E;01^_^_0i5%_^^i7E;01^_^_0i4%_
Ages 3-5 Years (g/day, as consumed) j Ages 3-5 Years (g/kg/day, as consumed)
Total Foods 4.7E+02 100.0% 1.0E+03 100.0% 1.8E+03 100.0% ! 6.8E+00 100.0% 5.4E+01 100.0% 1.1E+02 100.0%
Total Dairy 1.5E+02 31.0% 4.0E+02 40.0% 7.2E+02 39.9% i 1.8E+00 27.1% 2.2E+01 40.6% 4.1E+01 37.9%
Total Meats 6.1E+01 12.9% 7.8E+01 7.9% 1.0E+02 5.8% i 9.5E-01 14.0% 4.5E+00 8.3% 6.3E+00 5.9%
Total Fish 4.1E+00 0.9% 6.5E+00 0.7% 1.0E+01 0.6% i 4.1E-02 0.6% 3.1E-01 0.6% 4.6E-01 0.4%
Total Eggs 1.0E+01 2.1% 1.1E+01 1.1% 2.5E+01 1.4% i 2.0E-01 2.9% 6.4E-01 1.2% 1.1E+00 1.0%
Total Grains 1.1E+02 24.0% 1.9E+02 18.6% 2.8E+02 15.5% i 1.8E+00 27.0% 1.0E+01 18.6% 1.8E+01 16.9%
Total Vegetables 8.1E+01 17.0% 1.3E+02 13.2% 2.1E+02 11.9% i 1.2E+00 17.2% 7.1E+00 13.1% 1.3E+01 12.0%
Total Fruits 5.3E+01 11.1% 1.8E+02 17.9% 4.4E+02 24.4% i 6.9E-01 10.1% 9.1E+00 16.9% 2.7E+01 25.2%
Total^Mฃ^^_^^^^i7Eiซ0_^Ji0%_^^Eiซ0__0i7%_^i2Eiซl^__0i7%_i_8i3E;02^_^Ji2%_^^i5E;01^_^_0i8%__6i5E;01^_^_0i6%_
Ages 6-11 Years (g/day, as consumed) j Ages 6-11 Years (g/kg/day, as consumed)
Total Foods 5.4E+02 100.0% 1.1E+03 100.0% 1.9E+03 100.0% ! 3.8E+00 100.0% 3.3E+01 100.0% 7.2E+01 100.0%
Total Dairy 1.6E+02 30.1% 3.9E+02 36.5% 7.8E+02 39.9% i 9.9E-01 26.2% 1.3E+01 39.7% 3.0E+01 41.4%
Total Meats 7.7E+01 14.3% 1.0E+02 9.5% 1.2E+02 6.1% i 5.8E-01 15.3% 3.1E+00 9.2% 4.7E+00 6.6%
Total Fish 8.2E+00 1.5% 7.5E+00 0.7% 1.2E+01 0.6% i 5.3E-02 1.4% 2.6E-01 0.8% 3.6E-01 0.5%
Total Eggs 7.6E+00 1.4% 1.1E+01 1.0% 2.0E+01 1.0% i 9.2E-02 2.4% 4.5E-01 1.3% 7.7E-01 1.1%
Total Grains 1.4E+02 26.2% 2.2E+02 20.3% 3.4E+02 17.5% i 1.1E+00 30.0% 7.0E+00 21.0% 1.3E+01 17.9%
Total Vegetables 9.3E+01 17.4% 1.7E+02 16.5% 2.8E+02 14.4% i 7.5E-01 19.7% 4.7E+00 13.9% 9.9E+00 13.8%
Total Fruits 4.3E+01 8.1% 1.5E+02 14.5% 3.8E+02 19.7% i 1.3E-01 3.4% 4.4E+00 13.1% 1.3E+01 17.9%
Total^Mฃ^^_^^^i7Eiซ0_^JJ%__9i9Eiซ0__0i9%_^i5Eiซl^__0i8%_i_6ฃE;02^_^Ji6%_^^i2E;01^_^Ji0%_^^i6E;01^_^_0i8%_
. Vi^es 12-19 Years (i; day, as consumed) j . Vi^es 12-19 Years (i; ki; day, as consumed)
June 2000
3-49
DRAFT-DO NOT QUOTE OR CITE
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Table 3-21. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Food Intake (continued)
Food
Low-end consumers
Mid-range consumers
High-end consumers
Low-end consumers
Mid-range consumers
High-end consumers
Group
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Total Foods
4.1E+02
100.0%
1.1E+03
100.0%
2.4E+03
100.0%
5.1E+00
100.0%
1.8E+01
100.0%
4.4E+01
100.0%
Total Dairy
6.2E+01
15.1%
2.9E+02
26.8%
8.5E+02
35.1%
8.7E-01
17.1%
4.7E+00
26.7%
1.6E+01
36.1%
Total Meats
7.7E+01
18.6%
1.2E+02
11.6%
2.2E+02
8.9%
8.6E-01
17.0%
2.1E+00
12.1%
3.5E+00
7.9%
Total Fish
6.9E+00
1.7%
8.7E+00
0.8%
2.2E+01
0.9%
8.4E-02
1.7%
1.5E-01
0.9%
3.6E-01
0.8%
Total Eggs
7.3E+00
1.8%
1.7E+01
1.6%
2.7E+01
1.1%
9.9E-02
1.9%
3.0E-01
1.7%
4.0E-01
0.9%
Total Grains
1.1E+02
27.6%
2.4E+02
22.6%
4.3E+02
17.9%
1.5E+00
29.3%
4.0E+00
22.5%
8.6E+00
19.5%
Total Vegetables
1.1E+02
26.6%
2.3E+02
21.9%
4.4E+02
18.0%
1.3E+00
26.5%
3.6E+00
20.6%
7.3E+00
16.6%
Total Fruits
2.8E+01
6.8%
1.4E+02
13.5%
4.1E+02
17.0%
2.4E-01
4.7%
2.5E+00
14.1%
7.5E+00
17.1%
Total Fatsa
7 8F+00
1 9%
1 4F+01
1 3%
7 6F+01
1 1%
9 1F-O?
1 8%
7 5F-01
1 4%
4 4F-01
1 0%
a Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
Source: Based on U.S. EPA analysis of 1994-96 CSFII.
June 2000
3-50
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-22. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Meat Intake
Food
Low-end consumers
Mid-range consumers
High-end consumers
Low-end consumers
Mid-range consumers
High-end consumers
Group
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
<1 Year (g day. as consumec
Age <1 Year (g kg day. as consume
J)
Tota
Foods
8.0E+02
100.0%
7.6E+02
100.0%
1.3E+03
100.0%
1.2E+02
100.0%
1.1E+02
100.0%
1.4E+02
100.0%
Tota
Dairy
6.5E+02
80.9%
6.5E+02
85.9%
7.9E+02
61.0%
1.1E+02
84.7%
1.0E+02
89.8%
8.9E+01
61.9%
Tota
Meats
0.0E+00
0.0%
0.0E+00
0.0%
5.8E+01
4.4%
0.0E+00
0.0%
0.0E+00
0.0%
6.2E+00
4.3%
Tota
Fish
0.0E+00
0.0%
0.0E+00
0.0%
4.6E+00
0.4%
0.0E+00
0.0%
0.0E+00
0.0%
5.3E-01
0.4%
Tota
Eggs
0.0E+00
0.0%
3.5E-01
0.0%
1.6E+01
1.2%
0.0E+00
0.0%
3.9E-02
0.0%
1.4E+00
1.0%
Tota
Grains
8.0E+00
1.0%
8.8E+00
1.2%
1.0E+02
7.9%
1.1E+00
0.9%
8.1E-01
0.7%
1.0E+01
7.2%
Tota
Vegetables
3.5E+01
4.3%
2.7E+01
3.5%
1.4E+02
10.4%
4.3E+00
3.4%
2.6E+00
2.3%
1.7E+01
11.5%
Tota
Fruits
1.1E+02
13.8%
7.0E+01
9.3%
1.9E+02
14.5%
1.4E+01
11.0%
7.9E+00
7.1%
1.9E+01
13.4%
Tota
Fatsa
0.0E+00
0.0%
8.3E-03
0.0%
2.7E+00
0.2%
0.0E+00
0.0%
8.0E-04
0.0%
3.0E-01
0.2%
Ages 1-2 Years
(g day. as consumed)
Ages
1-2 Years (g kg day. as consumed)
Tota
Foods
1.0E+03
100.0%
1.0E+03
100.0%
1.2E+03
100.0%
5.6E+01
100%
8.4E+01
100.0%
1.0E+02
100.0%
Tota
Dairy
5.9E+02
56.9%
4.8E+02
45.8%
4.3E+02
35.6%
3.2E+01
57%
3.6E+01
42.9%
3.9E+01
38.9%
Tota
Meats
5.9E+00
0.6%
5.2E+01
5.0%
1.5E+02
12.5%
1.6E-01
0%
3.9E+00
4.7%
1.1E+01
11.3%
Tota
Fish
3.3E+00
0.3%
5.5E+00
0.5%
7.9E+00
0.6%
9.8E-02
0%
4.0E-01
0.5%
7.0E-01
0.7%
Tota
Eggs
1.0E+01
1.0%
1.5E+01
1.4%
2.2E+01
1.8%
4.0E-01
1%
1.4E+00
1.7%
1.4E+00
1.4%
Tota
Grains
1.0E+02
9.7%
1.4E+02
13.6%
1.7E+02
14.3%
4.7E+00
8%
1.1E+01
13.4%
1.4E+01
13.8%
Tota
Vegetables
1.0E+02
9.8%
1.1E+02
10.8%
1.7E+02
13.7%
6.1E+00
11%
9.7E+00
11.5%
1.3E+01
13.4%
Tota
Fruits
2.2E+02
21.6%
2.3E+02
22.4%
2.5E+02
20.8%
1.2E+01
22%
2.1E+01
24.7%
2.0E+01
19.9%
Tota
Fatsa
2.4E+00
0.2%
5.4E+00
0.5%
7.9E+00
0.7%
8.4E-02
0%
4.3E-01
0.5%
6.1E-01
0.6%
Ages 3-5 Years
(g day. as consumed)
Ages 3-5 Years (g kg day. as consumed)
Tota
Foods
9.7E+02
100.0%
9.6E+02
100.0%
1.3E+03
100.0%
1.8E+01
100.0%
5.8E+01
100.0%
7.5E+01
100.0%
Tota
Dairy
4.0E+02
41.3%
3.7E+02
38.8%
3.7E+02
29.9%
7.9E+00
44.6%
2.3E+01
40.2%
2.4E+01
31.7%
Tota
Meats
1.3E+01
1.4%
7.0E+01
7.3%
1.9E+02
14.9%
7.8E-02
0.4%
3.8E+00
6.5%
1.0E+01
13.9%
Tota
Fish
6.5E+00
0.7%
4.6E+00
0.5%
7.7E+00
0.6%
1.2E-01
0.7%
4.0E-01
0.7%
2.8E-01
0.4%
Tota
Eggs
1.2E+01
1.2%
1.6E+01
1.6%
1.9E+01
1.5%
1.4E-01
0.8%
6.6E-01
1.1%
1.0E+00
1.4%
Tota
Grains
1.9E+02
19.6%
1.7E+02
17.8%
2.3E+02
18.7%
3.2E+00
17.7%
9.9E+00
17.1%
1.4E+01
18.5%
Tota
Vegetables
1.1E+02
10.9%
1.4E+02
14.5%
1.9E+02
14.9%
1.6E+00
9.0%
7.5E+00
13.0%
1.1E+01
15.3%
Tota
Fruits
2.4E+02
24.4%
1.8E+02
18.7%
2.3E+02
18.7%
4.7E+00
26.5%
1.2E+01
20.7%
1.3E+01
18.1%
Tota
Fatsa
4.8E+00
0.5%
7.2E+00
0.7%
1.1E+01
0.9%
6.3E-02
0.4%
4.1E-01
0.7%
6.1E-01
0.8%
Ages 6-11 Years (g/dav, as consumed)
Ages 6-11 Years (g kg day. as consumed)
Tota
Foods
1.0E+03
100.0%
1.1E+03
100.0%
1.3E+03
100.0%
1.3E+01
100.0%
3.4E+01
100.0%
5.2E+01
100.0%
Tota
Dairy
4.3E+02
42.6%
4.3E+02
39.4%
4.3E+02
32.1%
5.5E+00
42.9%
1.3E+01
38.7%
1.8E+01
34.8%
Tota
Meats
1.6E+01
1.6%
8.8E+01
8.0%
2.2E+02
16.7%
5.8E-02
0.4%
2.6E+00
7.5%
7.7E+00
14.7%
Tota
Fish
4.7E+00
0.5%
8.7E+00
0.8%
8.8E+00
0.7%
9.7E-02
0.8%
2.8E-01
0.8%
3.0E-01
0.6%
Tota
Eggs
1.1E+01
1.1%
1.2E+01
1.1%
1.5E+01
1.1%
1.7E-01
1.3%
5.0E-01
1.5%
6.7E-01
1.3%
Tota
Grains
2.2E+02
21.4%
2.1E+02
19.6%
2.5E+02
18.6%
2.8E+00
21.7%
6.9E+00
20.0%
9.8E+00
18.9%
Tota
Vegetables
1.4E+02
13.4%
1.8E+02
16.0%
2.5E+02
18.3%
1.9E+00
14.7%
5.2E+00
15.2%
8.7E+00
16.7%
Tota
Fruits
1.9E+02
18.6%
1.6E+02
14.1%
1.6E+02
11.7%
2.3E+00
17.6%
5.2E+00
15.3%
6.3E+00
12.2%
Tota
Fats"
8.0E+00
0.8%
1.1E+01
1.0%
1.2E+01
0.9%
7.8E-02
0.6%
3.3E-01
0.9%
4.4E-01
0.8%
Ages 12-19 Years (g/day, as consumed)
Ages 12-19 Years (g/kg/day, as consumed)
June 2000
3-51
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Table 3-22. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Meat Intake (continued)
Food Low-end consumers Mid-range consumers High-end consumers Low-end consumers Mid-range consumers High-end consumers
Group Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent
Total Foods
9.3E+02
100.0%
1.1E+03
100.0%
1.7E+03
100.0%
1.3E+01
100.0%
2.0E+01
100.0%
3.0E+01
100.0%
Total Dairy
3.1E+02
33.4%
3.5E+02
31.2%
3.7E+02
22.2%
4.3E+00
33.8%
6.1E+00
30.9%
7.4E+00
24.6%
Total Meats
1.9E+01
2.0%
1.2E+02
10.3%
3.3E+02
19.8%
2.3E-01
1.8%
1.9E+00
9.6%
5.5E+00
18.2%
Total Fish
8.2E+00
0.9%
9.6E+00
0.9%
1.7E+01
1.0%
9.5E-02
0.7%
2.4E-01
1.2%
2.7E-01
0.9%
Total Eggs
1.1E+01
1.2%
1.0E+01
0.9%
2.8E+01
1.7%
1.6E-01
1.3%
2.4E-01
1.2%
4.2E-01
1.4%
Total Grains
2.2E+02
23.7%
2.5E+02
22.7%
3.5E+02
21.1%
3.2E+00
24.9%
4.4E+00
22.2%
6.4E+00
21.2%
Total Vegetables
1.9E+02
20.0%
2.2E+02
19.3%
3.8E+02
22.7%
2.5E+00
19.9%
3.7E+00
18.8%
6.2E+00
20.7%
Total Fruits
1.6E+02
17.6%
1.5E+02
13.4%
1.7E+02
10.1%
2.1E+00
16.3%
2.9E+00
14.7%
3.6E+00
11.8%
Total Fatsa
1 7F+01
1 3%
1 4F+01
1 3%
7 4F+01
1 Wn
1 6F-01
1 7%
7 7F-01
1 4%
3 9F-01
1 3%
a Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
Source: Based on U.S. EPA analysis of 1994-96 CSFII.
June 2000
3-52
DRAFT-DO NOT QUOTE OR CITE
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Table 3-23. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Meat and Dairy Intake
Food Low-end consumers Mid-range consumers High-end consumers Low-end consumers Mid-range consumers High-end consumers
GrฐuP Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent
Total Foods 4.2E+01 100.0% 1.0E+03 100.0% 1.7E+03 100.0% : 5.6E+00 100.0% 1.3E+02 100.0% 2.5E+02 100.0%
Total Dairy 0.0E+00 0.0% 7.8E+02 74.9% 1.5E+03 89.2% i 0.0E+00 0.0% 9.4E+01 73.0% 2.5E+02 98.8%
Total Meats 0.0E+00 0.0% 1.3E+01 1.3% 5.9E+00 0.3% i 0.0E+00 0.0% 1.7E+00 1.3% 3.0E-02 0.0%
Total Fish 0.0E+00 0.0% 2.0E+00 0.2% 2.6E-01 0.0% i 0.0E+00 0.0% 2.2E-01 0.2% 4.3E-03 0.0%
Total Eggs 0.0E+00 0.0% 6.0E+00 0.6% 1.0E+00 0.1% i 0.0E+00 0.0% 2.9E-01 0.2% 1.1E-03 0.0%
Total Grains 3.5E+00 8.5% 5.2E+01 4.9% 3.2E+01 1.9% i 4.8E-01 8.6% 5.0E+00 3.9% 7.7E-01 0.3%
Total Vegetables 1.1E+01 25.7% 7.1E+01 6.8% 5.1E+01 3.0% i 1.7E+00 29.9% 9.2E+00 7.1% 9.6E-01 0.4%
Total Fruits 2.7E+01 65.8% 1.2E+02 11.2% 9.4E+01 5.5% i 3.4E+00 61.5% 1.8E+01 14.2% 1.4E+00 0.5%
Total^Mฃ^^_^^_0ฃEiซ0__0ฃ%_^JJ^0__0J%_^^i3E;01^_^_0ฃ%__i_0ฃEiซ0__0i0%__8i5E;02^_^_0il%__6i7E;03^_^_0i0%_
Total Foods 7.2E+02 100.0% 1.1E+03 100.0% 1.7E+03 100.0% : 3.2E+01 100% 8.3E+01 100.0% 1.5E+02 100.0%
Total Dairy 7.4E+01 10.3% 4.2E+02 39.6% 1.1E+03 66.4% i 2.4E+00 7% 3.2E+01 38.3% 9.7E+01 66.7%
Total Meats 4.9E+01 6.7% 6.2E+01 5.8% 5.9E+01 3.5% i 1.9E+00 6% 5.0E+00 6.0% 4.9E+00 3.4%
Total Fish 3.7E+00 0.5% 5.7E+00 0.5% 4.4E+00 0.3% i 7.6E-02 0% 3.5E-01 0.4% 4.0E-01 0.3%
Total Eggs 2.0E+01 2.8% 1.6E+01 1.5% 1.5E+01 0.9% i 1.1E+00 3% 1.3E+00 1.6% 1.3E+00 0.9%
Total Grains 1.6E+02 22.8% 1.6E+02 14.8% 1.3E+02 7.9% i 7.5E+00 24% 1.2E+01 14.3% 1.1E+01 7.7%
Total Vegetables 1.2E+02 16.9% 1.2E+02 11.0% 1.3E+02 7.6% i 5.5E+00 17% 1.1E+01 12.7% 1.2E+01 8.0%
Total Fruits 2.8E+02 39.3% 2.8E+02 26.2% 2.2E+02 13.0% i 1.3E+01 41% 2.2E+01 26.2% 1.9E+01 12.7%
Totol^Mฃ^^_^^^^i6Eiซ0__0i6%_^^i8Eiซ0__0i5%_^^i3Eiซ0__0i3%_i^ฃ;01^_^^4^_^^i7E;01^_^_0i6%_^^ilE;01^_^_0i3%_
Total Foods 7.0E+02 100.0% 9.8E+02 100.0% 1.6E+03 100.0% : 1.3E+01 100.0% 5.5E+01 100.0% 9.5E+01 100.0%
Total Dairy 7.8E+01 11.2% 3.6E+02 37.1% 8.9E+02 55.4% i 7.9E-01 6.2% 1.9E+01 34.3% 5.2E+01 54.9%
Total Meats 5.9E+01 8.4% 7.5E+01 7.6% 8.7E+01 5.4% i 8.4E-01 6.6% 4.6E+00 8.4% 5.5E+00 5.9%
Total Fish 5.9E+00 0.8% 7.5E+00 0.8% 6.7E+00 0.4% i 6.8E-02 0.5% 3.5E-01 0.6% 3.2E-01 0.3%
Total Eggs 1.4E+01 2.0% 1.5E+01 1.5% 1.7E+01 1.1% i 2.9E-01 2.3% 7.6E-01 1.4% 8.3E-01 0.9%
Total Grains 1.8E+02 26.1% 1.8E+02 18.4% 2.2E+02 13.5% i 3.2E+00 25.7% 1.1E+01 19.4% 1.3E+01 14.1%
Total Vegetables 1.3E+02 17.9% 1.3E+02 13.3% 1.5E+02 9.4% i 2.4E+00 18.9% 7.8E+00 14.3% 9.2E+00 9.8%
Total Fruits 2.3E+02 32.6% 2.0E+02 20.5% 2.3E+02 14.2% i 4.9E+00 38.6% 1.1E+01 20.9% 1.3E+01 13.7%
Totol^Mฃ^^_^^_6i6Eiซ0__0i9%_^^i5Eiซ0__0i8%__8i9Eiซ0__0i6%_iji5E;01^_^JJ%_^^ฃ;01^_^_0i8%_^^i5E;01^_^_0i5%_
Total Foods 7.2E+02 100.0% 1.1E+03 100.0% 1.8E+03 100.0% : 5.9E+00 100.0% 3.5E+01 100.0% 6.7E+01 100.0%
Total Dairy 8.4E+01 11.7% 3.9E+02 36.7% 9.1E+02 51.2% i 4.4E-01 7.4% 1.2E+01 33.7% 3.4E+01 51.3%
Total Meats 7.2E+01 10.0% 1.0E+02 9.5% 1.2E+02 7.0% i 5.7E-01 9.6% 3.3E+00 9.4% 4.6E+00 6.9%
Total Fish 9.9E+00 1.4% 6.8E+00 0.6% 8.6E+00 0.5% i 3.7E-02 0.6% 2.5E-01 0.7% 3.0E-01 0.5%
Total Eggs 1.3E+01 1.8% 1.4E+01 1.4% 1.5E+01 0.8% i 1.6E-01 2.7% 5.7E-01 1.6% 6.0E-01 0.9%
Total Grains 1.9E+02 26.2% 2.2E+02 20.9% 2.8E+02 16.0% i 1.6E+00 27.7% 7.7E+00 21.9% 1.1E+01 16.6%
Total Vegetables 1.7E+02 23.0% 1.7E+02 15.9% 2.0E+02 11.5% i 1.5E+00 26.0% 5.4E+00 15.2% 8.1E+00 12.1%
Total Fruits 1.8E+02 24.6% 1.5E+02 14.0% 2.2E+02 12.2% i 1.5E+00 24.7% 5.8E+00 16.5% 7.3E+00 11.0%
Total^Mฃ^^_^^_9i8Eiซ0_^Ji4%__9i6Eiซ0__0i9%_^Ji3Eiซl^__0i7%_i_8i5E;02^_^Ji4%_^^i6E;01^_^Ji0%_^^i0E;01^_^_0i8%_
. Vi^es 12-19 Years (i; day, as consumed) j . Vi^es 12-19 Years (i; ki; day, as consumed)
June 2000
3-53
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Table 3-23. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Meat and Dairy Intake (continued)
Food Low-end consumers Mid-range consumers High-end consumers Low-end consumers Mid-range consumers High-end consumers
Group Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent
Total Foods
6.2E+02
100.0%
1.1E+03
100.0%
2.2E+03
100.0%
7.9E+00
100.0%
1.8E+01
100.0%
3.9E+01
100.0%
Total Dairy
3.0E+01
4.9%
2.7E+02
25.0%
1.0E+03
47.4%
3.7E-01
4.7%
4.4E+00
24.4%
1.9E+01
47.6%
Total Meats
5.6E+01
9.1%
1.4E+02
13.0%
2.0E+02
9.0%
6.6E-01
8.4%
2.2E+00
12.4%
3.3E+00
8.4%
Total Fish
8.2E+00
1.3%
9.3E+00
0.9%
1.3E+01
0.6%
1.3E-01
1.6%
1.9E-01
1.0%
2.5E-01
0.6%
Total Eggs
2.0E+01
3.2%
1.8E+01
1.6%
2.2E+01
1.0%
2.3E-01
2.9%
2.4E-01
1.4%
3.9E-01
1.0%
Total Grains
1.8E+02
28.7%
2.6E+02
24.4%
3.6E+02
16.6%
2.4E+00
30.2%
4.5E+00
25.1%
6.7E+00
17.0%
Total Vegetables
1.7E+02
28.2%
2.3E+02
21.5%
3.3E+02
15.2%
2.1E+00
27.3%
3.6E+00
19.9%
5.6E+00
14.3%
Total Fruits
1.4E+02
22.9%
1.3E+02
12.2%
2.0E+02
9.2%
1.8E+00
23.1%
2.6E+00
14.6%
4.0E+00
10.2%
Total Fatsa
q QF+nn
1 6%
1 5F+01
1 4%
7 7F+01
1 0%
1 4F-01
1 7%
7 7F-01
1 7%
3 7F-01
0 9%
a Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
Source: Based on U.S. EPA analysis of 1994-96 CSFII.
June 2000
3-54
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-24. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Fish Intake
Food
Low-end consumers
Mid-range consumers
High-end consumers
Low-end consumers
Mid-range consumers
High-end consumers
Group
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
e <1 Year (g day. as consumec
Age <1 Year (g kg day. as consumec
1)
Tota
Foods
8.8E+02
100.0%
8.4E+02
100.0%
1.2E+03
100.0%
1.3E+02
100.0%
1.2E+02
100.0%
1.4E+02
100.0%
Tota
Dairy
6.9E+02
78.0%
7.0E+02
83.0%
6.8E+02
58.5%
1.1E+02
82.0%
1.0E+02
85.8%
8.1E+01
59.2%
Tota
Meats
3.6E+00
0.4%
7.7E+00
0.9%
3.7E+01
3.2%
4.0E-01
0.3%
7.7E-01
0.7%
4.3E+00
3.1%
Tota
Fish
0.0E+00
0.0%
0.0E+00
0.0%
6.7E+00
0.6%
0.0E+00
0.0%
0.0E+00
0.0%
7.7E-01
0.6%
Tota
Eggs
1.1E+00
0.1%
3.2E+00
0.4%
7.2E+00
0.6%
1.3E-01
0.1%
3.7E-01
0.3%
7.7E-01
0.6%
Tota
Grains
1.4E+01
1.6%
3.0E+01
3.5%
9.2E+01
7.9%
1.6E+00
1.2%
3.6E+00
3.0%
1.1E+01
7.8%
Tota
Vegetables
4.4E+01
5.0%
4.8E+01
5.7%
1.4E+02
12.0%
5.6E+00
4.2%
5.3E+00
4.5%
1.7E+01
12.7%
Tota
Fruits
1.3E+02
14.9%
5.3E+01
6.3%
2.0E+02
16.9%
1.6E+01
12.2%
6.5E+00
5.5%
2.2E+01
15.8%
Tota
Fatsa
1.3E-01
0.0%
8.3E-01
0.1%
2.9E+00
0.2%
1.7E-02
0.0%
1.2E-01
0.1%
3.3E-01
1.3E+02
Ages 1-2 Years
(g day. as consumed)
Ages
1-2 Years (g kg day. as consumed)
Tota
Foods
1.1E+03
100.0%
9.5E+02
100.0%
1.2E+03
100.0%
8.4E+01
100%
7.8E+01
100.0%
9.4E+01
100.0%
Tota
Dairy
4.5E+02
41.1%
4.5E+02
48.0%
4.6E+02
39.1%
3.6E+01
43%
3.8E+01
48.7%
3.7E+01
40.0%
Tota
Meats
5.5E+01
5.0%
4.7E+01
5.0%
7.4E+01
6.3%
4.0E+00
5%
3.8E+00
4.9%
6.1E+00
6.5%
Tota
Fish
0.0E+00
0.0%
1.2E+00
0.1%
3.7E+01
3.1%
0.0E+00
0%
7.9E-02
0.1%
2.8E+00
2.9%
Tota
Eggs
1.6E+01
1.4%
1.2E+01
1.3%
1.6E+01
1.4%
1.1E+00
1%
9.2E-01
1.2%
1.3E+00
1.3%
Tota
Grains
1.6E+02
14.4%
1.3E+02
13.7%
1.6E+02
13.5%
1.2E+01
14%
1.0E+01
12.9%
1.3E+01
13.5%
Tota
Vegetables
1.2E+02
10.6%
1.1E+02
11.4%
1.4E+02
12.0%
8.5E+00
10%
8.7E+00
11.2%
1.1E+01
12.1%
Tota
Fruits
3.0E+02
27.0%
1.9E+02
20.0%
2.8E+02
24.0%
2.3E+01
27%
1.6E+01
20.7%
2.2E+01
23.1%
Tota
Fatsa
5.2E+00
0.5%
4.5E+00
0.5%
6.7E+00
0.6%
3.8E-01
0%
3.4E-01
0.4%
5.5E-01
0.6%
Ages 3-5 Years
(g day. as consumed)
Ages 3-5 Years (g kg day. as consumed)
Tota
Foods
1.1E+03
100.0%
9.4E+02
100.0%
1.1E+03
100.0%
5.9E+01
100.0%
5.5E+01
100.0%
6.4E+01
100.0%
Tota
Dairy
4.1E+02
38.7%
3.5E+02
37.7%
4.0E+02
35.7%
2.2E+01
38.2%
2.1E+01
38.2%
2.4E+01
36.6%
Tota
Meats
6.5E+01
6.1%
7.4E+01
7.9%
8.4E+01
7.4%
3.5E+00
6.0%
4.3E+00
7.8%
4.6E+00
7.2%
Tota
Fish
0.0E+00
0.0%
1.6E+00
0.2%
4.2E+01
3.7%
0.0E+00
0.0%
6.2E-02
0.1%
2.2E+00
3.5%
Tota
Eggs
1.0E+01
1.0%
1.2E+01
1.3%
1.4E+01
1.3%
5.6E-01
1.0%
5.5E-01
1.0%
7.7E-01
1.2%
Tota
Grains
2.2E+02
20.6%
1.7E+02
18.4%
2.0E+02
17.6%
1.2E+01
21.3%
1.0E+01
18.6%
1.1E+01
17.3%
Tota
Vegetables
1.3E+02
11.7%
1.3E+02
14.3%
1.6E+02
14.4%
6.9E+00
11.8%
6.9E+00
12.6%
9.3E+00
14.5%
Tota
Fruits
2.3E+02
21.2%
1.8E+02
19.5%
2.2E+02
19.2%
1.2E+01
21.0%
1.1E+01
20.9%
1.2E+01
18.9%
Tota
Fatsa
7.1E+00
0.7%
6.9E+00
0.7%
9.9E+00
0.9%
3.9E-01
0.7%
3.8E-01
0.7%
5.5E-01
0.9%
Ages 6-11 Years (g/dav, as consumed)
Ages 6-11 Years (g kg day. as consumed)
Tota
Foods
1.1E+03
100.0%
1.1E+03
100.0%
1.2E+03
100.0%
3.7E+01
100.0%
3.3E+01
100.0%
4.3E+01
100.0%
Tota
Dairy
4.5E+02
41.6%
4.3E+02
40.4%
4.2E+02
34.6%
1.5E+01
41.5%
1.2E+01
37.0%
1.6E+01
36.5%
Tota
Meats
9.1E+01
8.3%
8.0E+01
7.6%
1.0E+02
8.4%
3.0E+00
8.2%
2.8E+00
8.4%
3.8E+00
8.7%
Tota
Fish
0.0E+00
0.0%
2.2E+00
0.2%
5.7E+01
4.7%
0.0E+00
0.0%
5.3E-02
0.2%
1.7E+00
3.9%
Tota
Eggs
1.1E+01
1.0%
1.3E+01
1.2%
1.6E+01
1.3%
3.7E-01
1.0%
3.8E-01
1.2%
5.2E-01
1.2%
Tota
Grains
2.1E+02
19.3%
2.2E+02
20.5%
2.3E+02
18.7%
6.9E+00
19.0%
7.0E+00
21.3%
8.0E+00
18.5%
Tota
Vegetables
1.3E+02
11.4%
1.6E+02
15.3%
1.8E+02
14.6%
4.1E+00
11.3%
5.4E+00
16.6%
6.4E+00
14.8%
Tota
Fruits
1.9E+02
17.5%
1.5E+02
13.9%
2.0E+02
16.8%
6.6E+00
18.1%
4.7E+00
14.4%
6.7E+00
15.4%
Tota
Fats"
9.6E+00
0.9%
8.6E+00
0.8%
1.1E+01
0.9%
3.2E-01
0.9%
2.9E-01
0.9%
3.8E-01
0.9%
Ages 12-19 Years (g/day, as consumed)
Ages 12-19 Years (g/kg/day, as consumed)
June 2000
3-55
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Table 3-24. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake
for Individuals with Low-end, Mid-range, and High-end Total Fish Intake (continued)
Food
Group
Low-end consumers
Mid-range consumers
High-end consumers
Low-end consumers
Mid-range consumers
High-end consumers
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Total Foods
1.1E+03
100.0%
1.1E+03
100.0%
1.4E+03
100.0%
1.9E+01
100.0%
1.8E+01
100.0%
2.5E+01
100.0%
Total Dairy
4.1E+02
36.2%
3.3E+02
30.9%
3.3E+02
23.2%
7.0E+00
36.5%
5.7E+00
32.0%
6.3E+00
24.7%
Total Meats
1.1E+02
9.5%
1.2E+02
11.2%
1.7E+02
11.9%
1.8E+00
9.4%
1.8E+00
10.3%
3.0E+00
11.6%
Total Fish
0.0E+00
0.0%
3.4E+00
0.3%
7.5E+01
5.2%
0.0E+00
0.0%
5.4E-02
0.3%
1.2E+00
4.8%
Total Eggs
1.4E+01
1.2%
1.5E+01
1.4%
2.1E+01
1.4%
2.3E-01
1.2%
2.4E-01
1.3%
3.5E-01
1.4%
Total Grains
2.4E+02
21.1%
2.4E+02
22.2%
2.9E+02
20.5%
4.0E+00
20.7%
3.9E+00
21.6%
5.5E+00
21.7%
Total Vegetables
2.0E+02
17.9%
2.1E+02
20.0%
3.1E+02
21.7%
3.4E+00
17.6%
3.4E+00
19.3%
5.2E+00
20.3%
Total Fruits
1.5E+02
12.9%
1.3E+02
12.7%
2.1E+02
14.5%
2.6E+00
13.5%
2.5E+00
13.9%
3.6E+00
14.0%
Total Fatsa
1 4F+01
1 7%
1 3F+01
1 3%
7 7F+01
1 5%
7 7F-01
1 7%
7 1F-01
1 7%
3 7F-01
1 5%
a Includes added fats such as butter, margarine, dressings and
sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
Source: Based on U.S. EPA analysis of 1994-96 CSFII.
June 2000
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Table 3-25. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for
Individuals with Low-end, Mid-range, and High-end Total Fruit and Vegetable Intake
Food
Low-end consumers
Mid-range consumers
High-end consumers
Low-end consumers
Mid-range consumers
High-end consumers
Group
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
e <1 Year (g day. as consumec
Age <1 Year (g kg day. as consumec
1)
Tota
Foods
6.7E+02
100.0%
8.9E+02
100.0%
1.3E+03
100.0%
1.3E+02
100.0%
1.1E+02
100.0%
1.6E+02
100.0%
Tota
Dairy
6.7E+02
99.5%
7.2E+02
81.4%
7.0E+02
51.9%
1.3E+02
99.6%
9.0E+01
84.6%
8.1E+01
52.0%
Tota
Meats
0.0E+00
0.0%
1.2E+01
1.3%
2.1E+01
1.5%
0.0E+00
0.0%
1.1E+00
1.1%
2.0E+00
1.3%
Tota
Fish
0.0E+00
0.0%
6.3E-01
0.1%
2.3E+00
0.2%
0.0E+00
0.0%
6.8E-02
0.1%
2.0E-01
0.1%
Tota
Eggs
0.0E+00
0.0%
9.4E+00
1.1%
7.1E+00
0.5%
0.0E+00
0.0%
9.1E-01
0.9%
2.5E-01
0.2%
Tota
Grains
3.1E+00
0.5%
4.5E+01
5.1%
6.4E+01
4.7%
5.5E-01
0.4%
4.2E+00
4.0%
7.4E+00
4.8%
Tota
Vegetables
0.0E+00
0.0%
4.9E+01
5.5%
1.6E+02
11.9%
0.0E+00
0.0%
4.3E+00
4.1%
2.1E+01
13.6%
Tota
Fruits
0.0E+00
0.0%
4.9E+01
5.5%
3.9E+02
29.2%
0.0E+00
0.0%
5.7E+00
5.3%
4.3E+01
28.0%
Tota
Fatsa
0.0E+00
0.0%
7.6E-01
0.1%
1.2E+00
0.1%
0.0E+00
0.0%
7.9E-02
0.1%
1.2E-01
0.1%
Ages 1-2 Years
(g day. as consumed)
Ages
1-2 Years (g kg day. as consumed)
Tota
Foods
7.5E+02
100.0%
1.0E+03
100.0%
1.6E+03
100.0%
3.4E+01
100%
8.3E+01
100.0%
1.3E+02
100.0%
Tota
Dairy
4.7E+02
63.5%
4.6E+02
44.3%
4.4E+02
27.8%
2.3E+01
66%
3.8E+01
45.5%
3.8E+01
29.1%
Tota
Meats
5.4E+01
7.3%
6.4E+01
6.1%
6.4E+01
4.0%
2.5E+00
7%
5.2E+00
6.2%
5.1E+00
3.9%
Tota
Fish
4.1E+00
0.5%
7.5E+00
0.7%
7.8E+00
0.5%
1.5E-01
0%
6.1E-01
0.7%
4.3E-01
0.3%
Tota
Eggs
1.5E+01
2.0%
1.3E+01
1.3%
2.1E+01
1.3%
7.4E-01
2%
1.2E+00
1.5%
1.8E+00
1.4%
Tota
Grains
1.2E+02
16.3%
1.6E+02
15.0%
1.5E+02
9.5%
5.6E+00
16%
1.2E+01
14.7%
1.3E+01
9.9%
Tota
Vegetables
5.7E+01
7.6%
1.2E+02
11.5%
2.0E+02
12.7%
2.1E+00
6%
9.5E+00
11.4%
1.7E+01
12.9%
Tota
Fruits
1.7E+01
2.3%
2.1E+02
20.6%
6.9E+02
43.7%
4.1E-01
1%
1.6E+01
19.5%
5.6E+01
42.2%
Tota
Fatsa
3.9E+00
0.5%
5.5E+00
0.5%
6.4E+00
0.4%
1.5E-01
0%
3.8E-01
0.5%
5.2E-01
0.4%
Ages 3-5 Years
(g day. as consumed)
Ages 3-5 Years (g kg day. as consumed)
Tota
Foods
7.0E+02
100.0%
1.0E+03
100.0%
1.6E+03
100.0%
1.2E+01
100.0%
5.4E+01
100.0%
9.6E+01
100.0%
Tota
Dairy
3.9E+02
56.3%
3.9E+02
39.4%
4.1E+02
26.2%
7.1E+00
57.5%
2.2E+01
40.9%
2.6E+01
26.9%
Tota
Meats
6.5E+01
9.3%
8.2E+01
8.3%
8.4E+01
5.4%
1.1E+00
9.2%
4.7E+00
8.7%
5.0E+00
5.3%
Tota
Fish
5.2E+00
0.7%
7.5E+00
0.8%
8.7E+00
0.6%
9.6E-02
0.8%
3.5E-01
0.6%
4.8E-01
0.5%
Tota
Eggs
1.1E+01
1.5%
1.2E+01
1.2%
2.3E+01
1.4%
1.9E-01
1.5%
5.0E-01
0.9%
1.1E+00
1.2%
Tota
Grains
1.5E+02
22.1%
1.9E+02
19.4%
2.1E+02
13.4%
3.1E+00
25.1%
1.0E+01
19.0%
1.3E+01
13.9%
Tota
Vegetables
5.4E+01
7.8%
1.5E+02
14.7%
2.2E+02
14.3%
6.0E-01
4.9%
7.1E+00
13.1%
1.3E+01
14.0%
Tota
Fruits
1.0E+01
1.5%
1.5E+02
15.5%
6.0E+02
38.0%
3.0E-02
0.2%
8.6E+00
15.9%
3.6E+01
37.7%
Tota
Fatsa
4.9E+00
0.7%
8.1E+00
0.8%
1.1E+01
0.7%
8.2E-02
0.7%
4.5E-01
0.8%
6.0E-01
0.6%
Ages 6-11 Years (g/dav, as consumed)
Ages 6-11 Years (g kg day. as consumed)
Tota
Foods
7.3E+02
100.0%
1.1E+03
100.0%
1.7E+03
100.0%
6.5E+00
100.0%
3.5E+01
100.0%
6.3E+01
100.0%
Tota
Dairy
3.7E+02
51.0%
4.5E+02
40.4%
4.6E+02
27.2%
3.2E+00
50.3%
1.5E+01
42.7%
1.8E+01
29.4%
Tota
Meats
7.5E+01
10.3%
1.0E+02
9.0%
1.0E+02
6.1%
6.6E-01
10.2%
3.2E+00
9.2%
3.9E+00
6.2%
Tota
Fish
9.7E+00
1.3%
9.8E+00
0.9%
1.1E+01
0.7%
3.5E-02
0.5%
2.4E-01
0.7%
3.5E-01
0.6%
Tota
Eggs
1.0E+01
1.4%
1.2E+01
1.1%
1.8E+01
1.0%
1.3E-01
2.0%
3.5E-01
1.0%
7.4E-01
1.2%
Tota
Grains
1.8E+02
25.5%
2.4E+02
21.2%
2.5E+02
15.0%
1.9E+00
29.6%
7.1E+00
20.5%
1.0E+01
16.2%
Tota
Vegetables
6.2E+01
8.5%
1.7E+02
15.0%
3.0E+02
17.9%
3.9E-01
6.0%
4.8E+00
13.8%
1.1E+01
17.2%
Tota
Fruits
8.6E+00
1.2%
1.3E+02
11.5%
5.3E+02
31.3%
4.1E-02
0.6%
3.9E+00
11.1%
1.8E+01
28.6%
Tota
Fats"
5.2E+00
0.7%
1.1E+01
1.0%
1.4E+01
0.9%
3.9E-02
0.6%
3.1E-01
0.9%
4.9E-01
0.8%
Ages 12-19 Years (g/day, as consumed)
Ages 12-19 Years (g/kg/day, as consumed)
June 2000
3-57
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Table 3-25. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for
Individuals with Low-end, Mid-range, and High-end Total Fruit and Vegetable Intake (continued)
Food Low-end consumers Mid-range consumers High-end consumers Low-end consumers Mid-range consumers High-end consumers
Group Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent Intake Percent
Total Foods
6.8E+02
100.0%
1.1E+03
100.0%
2.1E+03
100.0%
8.4E+00
100.0%
1.8E+01
100.0%
3.8E+01
100.0%
Total Dairy
2.9E+02
42.5%
3.4E+02
31.4%
4.5E+02
21.7%
3.6E+00
43.2%
6.1E+00
32.8%
8.5E+00
22.6%
Total Meats
1.0E+02
15.2%
1.3E+02
11.7%
1.8E+02
8.7%
1.3E+00
15.0%
2.3E+00
12.2%
2.9E+00
7.7%
Total Fish
5.0E+00
0.7%
1.1E+01
1.0%
2.0E+01
1.0%
6.9E-02
0.8%
2.0E-01
1.1%
3.3E-01
0.9%
Total Eggs
1.3E+01
1.9%
1.8E+01
1.7%
2.4E+01
1.1%
1.5E-01
1.8%
2.7E-01
1.5%
4.3E-01
1.1%
Total Grains
2.0E+02
28.5%
2.6E+02
23.7%
3.6E+02
17.1%
2.4E+00
28.5%
4.3E+00
23.2%
6.8E+00
18.1%
Total Vegetables
6.6E+01
9.6%
2.4E+02
22.2%
4.5E+02
21.6%
7.6E-01
9.1%
4.0E+00
21.8%
7.8E+00
20.7%
Total Fruits
3.3E+00
0.5%
7.5E+01
6.9%
5.8E+02
27.5%
4.5E-02
0.5%
1.1E+00
6.0%
1.0E+01
27.7%
Total Fatsa
7 6F+00
1 1%
1 6F+01
1 5%
7 5F+01
1 7%
8 6F-07
1 0%
7 6F-01
1 4%
4 7F-01
1 1%
a Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
Source: Based on U.S. EPA analysis of 1994-96 CSFII.
June 2000
3-58
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Table 3-26. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for
Individuals with Low-end, Mid-range, and High-end Total Dairy Intake
Food Low-end consumers Mid-range consumers High-end consumers j Low-end consumers Mid-range consumers High-end consumers
GrฐuP Intake Percent Intake Percent Intake Percent : Intake Percent Intake Percent Intake Percent
Total Foods 2.2E+01 100.0% 1.0E+03 100.0% 1.7E+03 100.0% : 2.5E+00 100.0% 1.3E+02 100.0% 2.5E+02 100.0%
Total Dairy 0.0E+00 0.0% 7.8E+02 74.4% 1.5E+03 89.2% i 0.0E+00 0.0% 9.4E+01 73.4% 2.5E+02 98.8%
Total Meats 0.0E+00 0.0% 1.4E+01 1.4% 5.9E+00 0.3% i 0.0E+00 0.0% 1.9E+00 1.5% 3.0E-02 0.0%
Total Fish 0.0E+00 0.0% 1.8E+00 0.2% 2.6E-01 0.0% i 0.0E+00 0.0% 3.1E-01 0.2% 4.3E-03 0.0%
Total Eggs 0.0E+00 0.0% 4.4E+00 0.4% 1.0E+00 0.1% i 0.0E+00 0.0% 3.0E-01 0.2% 1.1E-03 0.0%
Total Grains 2.5E+00 11.7% 5.1E+01 4.9% 3.2E+01 1.9% i 1.1E-01 4.6% 4.8E+00 3.8% 7.7E-01 0.3%
Total Vegetables 5.8E+00 26.9% 6.9E+01 6.6% 5.1E+01 3.0% i 7.6E-01 30.4% 8.9E+00 7.0% 9.6E-01 0.4%
Total Fruits 1.3E+01 61.4% 1.3E+02 12.0% 9.4E+01 5.5% i 1.6E+00 65.0% 1.8E+01 13.8% 1.4E+00 0.5%
Total^Mฃ^^_^^_0ฃEiซ0__0ฃ%__9i2E;01^_^_0J%_^^i3E;01^_^_0ฃ%__i_0ฃEiซ0__0i0%^_^JJ^01^_^_0il%__6i7E;03^_^_0i0%_
Total Foods 7.4E+02 100.0% 1.1E+03 100.0% 1.6E+03 100.0% : 3.3E+01 100% 8.2E+01 100.0% 1.4E+02 100.0%
Total Dairy 6.5E+01 8.8% 4.2E+02 39.7% 1.1E+03 67.2% i 1.9E+00 6% 3.2E+01 38.7% 9.8E+01 67.6%
Total Meats 6.8E+01 9.1% 6.5E+01 6.1% 5.0E+01 3.1% i 2.8E+00 8% 4.8E+00 5.9% 4.1E+00 2.8%
Total Fish 4.3E+00 0.6% 6.5E+00 0.6% 4.5E+00 0.3% i 7.4E-02 0% 5.3E-01 0.7% 3.2E-01 0.2%
Total Eggs 2.4E+01 3.2% 1.7E+01 1.6% 1.5E+01 0.9% i 1.2E+00 4% 1.1E+00 1.3% 1.2E+00 0.9%
Total Grains 1.7E+02 22.8% 1.5E+02 14.3% 1.3E+02 7.8% i 8.0E+00 24% 1.2E+01 14.6% 1.1E+01 7.6%
Total Vegetables 1.4E+02 18.4% 1.1E+02 10.4% 1.2E+02 7.4% i 6.3E+00 19% 1.0E+01 12.4% 1.1E+01 7.8%
Total Fruits 2.7E+02 36.4% 2.8E+02 26.6% 2.1E+02 13.0% i 1.3E+01 39% 2.1E+01 26.0% 1.9E+01 12.9%
Totol^Mฃ^^_^^^i8Eiซ0__0i8%_^^i6Eiซ0__0i5%_^^i2Eiซ0__0i3%_i^i5E;01^_^^4^_^^ilฃ;01^_^_0i5%_^^i8E;01^_^_0i3%_
Total Foods 7.0E+02 100.0% 9.8E+02 100.0% 1.6E+03 100.0% : 1.3E+01 100.0% 5.3E+01 100.0% 9.4E+01 100.0%
Total Dairy 6.6E+01 9.4% 3.6E+02 36.7% 9.0E+02 56.8% i 4.8E-01 3.7% 1.9E+01 35.5% 5.2E+01 55.4%
Total Meats 8.3E+01 11.9% 8.6E+01 8.8% 7.5E+01 4.7% i 1.6E+00 12.1% 4.1E+00 7.8% 4.7E+00 5.0%
Total Fish 5.3E+00 0.8% 5.9E+00 0.6% 6.2E+00 0.4% i 1.0E-01 0.8% 2.9E-01 0.5% 3.4E-01 0.4%
Total Eggs 1.6E+01 2.2% 9.5E+00 1.0% 1.6E+01 1.0% i 3.3E-01 2.5% 5.9E-01 1.1% 8.9E-01 0.9%
Total Grains 1.8E+02 25.8% 1.8E+02 18.8% 2.1E+02 13.2% i 3.4E+00 25.5% 9.5E+00 17.9% 1.3E+01 13.9%
Total Vegetables 1.3E+02 18.4% 1.4E+02 14.7% 1.5E+02 9.2% i 2.6E+00 19.9% 7.8E+00 14.7% 9.3E+00 9.9%
Total Fruits 2.2E+02 30.7% 1.8E+02 18.7% 2.2E+02 14.1% i 4.5E+00 34.4% 1.1E+01 21.6% 1.3E+01 13.9%
Total^Mฃ^^_^^_6i7Eiซ0_^Ji0%_^^^iซ0__0i7%__8i5Eiซ0__0i5%_iji6E;01^_^Ji2%_^^ilE;01^_^_0i8%_^^i5E;01^_^_0i5%_
Total Foods 7.3E+02 100.0% 1.0E+03 100.0% 1.7E+03 100.0% : 7.3E+00 100.0% 3.3E+01 100.0% 6.6E+01 100.0%
Total Dairy 7.1E+01 9.7% 3.9E+02 38.0% 9.2E+02 52.6% i 2.3E-01 3.2% 1.2E+01 36.4% 3.5E+01 52.9%
Total Meats 1.0E+02 14.0% 9.2E+01 9.0% 9.9E+01 5.7% i 1.2E+00 16.0% 2.9E+00 8.8% 3.8E+00 5.9%
Total Fish 1.0E+01 1.4% 7.4E+00 0.7% 7.4E+00 0.4% i 5.9E-02 0.8% 2.1E-01 0.6% 3.6E-01 0.5%
Total Eggs 1.4E+01 2.0% 1.2E+01 1.2% 1.2E+01 0.7% i 1.4E-01 1.9% 4.5E-01 1.4% 5.5E-01 0.8%
Total Grains 1.9E+02 26.3% 2.1E+02 20.9% 2.9E+02 16.3% i 2.0E+00 27.0% 7.0E+00 21.3% 1.1E+01 16.4%
Total Vegetables 1.7E+02 22.8% 1.5E+02 14.9% 1.9E+02 10.9% i 1.9E+00 25.3% 4.8E+00 14.6% 7.7E+00 11.8%
Total Fruits 1.6E+02 22.4% 1.4E+02 14.2% 2.2E+02 12.7% i 1.8E+00 24.2% 5.3E+00 16.0% 7.2E+00 11.0%
Totol^Mฃ^^_^^^Jฃiซl^_^Ji5%_^JJฃiซl^_^Ji0%_^Ji3Eiซl^__0i7%_iji2E;01^_^Ji6%_^^i2E;01^_^Ji0%_^^i7E;01^_^_0i7%_
. Vi^es 12-19 Years (i; day, as consumed) j . Vi^es 12-19 Years (i; ki; day, as consumed)
June 2000
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15
Table 3-26. Per Capita Intake of Total Foods and Major Food Groups, and Percent of Total Food Intake for
Individuals with Low-end, Mid-range, and High-end Total Dairy Intake (continued)
Food
Group
Low-end consumers
Mid-range consumers
High-end consumers
Low-end consumers
Mid-range consumers
High-end consumers
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Intake
Percent
Total Foods
6.9E+02
100.0%
1.1E+03
100.0%
2.1E+03
100.0%
8.9E+00
100.0%
1.8E+01
100.0%
3.8E+01
100.0%
Total Dairy
1.3E+01
2.0%
2.7E+02
23.9%
1.1E+03
51.6%
1.4E-01
1.6%
4.4E+00
24.5%
1.9E+01
50.9%
Total Meats
1.2E+02
17.0%
1.6E+02
13.9%
1.4E+02
6.9%
1.5E+00
17.3%
2.1E+00
11.7%
2.4E+00
6.5%
Total Fish
1.1E+01
1.6%
1.0E+01
0.9%
1.1E+01
0.6%
1.5E-01
1.7%
1.2E-01
0.7%
2.3E-01
0.6%
Total Eggs
1.4E+01
2.1%
1.7E+01
1.5%
2.0E+01
1.0%
2.2E-01
2.4%
3.0E-01
1.7%
3.1E-01
0.8%
Total Grains
2.0E+02
28.4%
2.6E+02
22.8%
3.4E+02
16.4%
2.4E+00
26.7%
4.5E+00
25.2%
6.5E+00
17.2%
Total Vegetables
1.8E+02
26.8%
2.5E+02
22.0%
2.8E+02
13.7%
2.4E+00
26.6%
3.7E+00
20.5%
4.9E+00
13.0%
Total Fruits
1.4E+02
20.8%
1.6E+02
13.8%
1.8E+02
8.9%
2.0E+00
22.3%
2.6E+00
14.5%
3.8E+00
10.0%
Total Fatsa
q 7F+nn
1 4%
1 3F+01
1 7%
7 OF+01
1 0%
1 7F-01
1 4%
7 7F-01
1 7%
3 4F-01
0 9%
a Includes added fats such as butter, margarine, dressings and sauces, vegetable oil, etc.; does not include fats eaten as components of other foods such as meats.
Source: Based on U.S. EPA analysis of 1994-96 CSFII.
June 2000
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8
9
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Table 3-27. 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
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
June 2000
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4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Table 3-28. Consumer Only Intake of Homegrown Foods (g/kg-day)a - All Regions Combined
Nc
Nc
%
Aee (years)
wstd
unwstd
Consuming
Mean
SE
PI
P5
P10
P25
P50
P75
P90
P95
P99
P100
Homegrown Fruits
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
Homegrown Vegetables
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+01
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+01
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+01
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+00
Home Produced Meats
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+01
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+01
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+01
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+00
Home Caught Fish
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+01
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+00
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
* = Less than 20 observations
a Data are not provided for intake of Home Produced Dairy because intake data were not provided for subpopulations for which there were less than 20 observations.
Source: Based on EPA's analyses of the 1987/88 NFCS
June 2000
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Table 3-29. Percent Weight Losses from Food Preparation
4 Mean Net Cooking Loss (%) Mean Net Post Cooking, Paring, or Preparation Loss
(%)
30
11
25
2T_
9
10
11 3 Based on potatoes only.
12
13 Source: U.S. EPA, 1997. (Derived from USDA, 1975.)
14
5 Meat 30
6 Fish 32
7 Fruits 31
8 Vegetables 12
June 2000
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Table 3-30. Quantity (as consumed) of Food Groups Consumed Per Eating Occasion and the Percentage of Individuals Using These Foods in Three Days
Quantity consumed per eating occasion (g)
Food category
Under 1 year
Male and Female
PC Ave. SD
1 -2 years
Male and Female
PC Ave. SD
3-5 years
Male and Female
PC Ave. SD
6-8 years
Male and Female
PC Ave. SD
PC
Male
Ave.
9-1
SD
4 years
PC
Female
Ave.
SD
PC
Male
Ave.
15-18
SD
years
PC
Female
Ave.
SD
Fruits and Vegetables
Raw veaetables
White potatoes
18.1
72
58
74.5
70
56
76.3
86
62
80.7
100
69
81.8
124
87
77.0
112
80
81.2
149
112
77.2
116
86
Cabbage and coleslaw
0
0
0
3.4
33
22
4.9
41
31
8.5
51
31
9.6
60
34
9.3
61
40
9.8
77
51
9.5
66
41
Carrots
0.8
37
12
3.4
28
25
5.4
38
33
9.8
38
41
8.6
39
36
6.5
33
31
4.5
42
39
5.5
39
35
Cucumbers
0.6
63
63
1.6
40
36
3.5
58
50
4.1
68
73
3.2
75
58
4.6
72
82
3.9
76
64
6.3
62
64
Lettuce and tossed salad
0
0
0
16.6
30
29
30.4
34
26
42.8
43
33
45.8
54
47
47.5
51
43
47.7
61
56
49.0
57
49
Mature onions
0
0
0
1.4
22
18
3.1
19
30
3.9
20
19
6.0
27
20
5.3
26
27
9.9
29
29
7.9
25
26
Tomatoes
0.3
21
7
10.6
46
32
15.7
52
44
18.3
55
33
20.1
74
58
21.0
71
49
24.4
75
56
24.3
66
44
Cooked veaetables
Broccoli
1.0
42
27
5.7
55
33
3.8
65
43
5.6
83
50
4.6
96
72
5.1
88
55
4.3
100
48
4.1
106
55
Cabbage
0.4
77
52
3.2
57
48
3.3
77
51
3.8
92
54
3.9
117
79
4.5
121
91
4.5
129
65
4.3
119
81
Carrots
21.7
71
41
11.7
54
38
8.0
49
31
8.7
59
33
8.5
79
48
8.8
75
46
8.5
86
48
7.0
71
46
Corn, whole kernel
3.2
22
17
25.8
56
40
30.1
68
45
34.6
78
41
32.0
95
62
31.0
83
47
28.8
116
70
24.5
94
59
Lima beans
1.0
71
67
2.4
54
38
1.9
49
31
1.9
79
47
1.8
114
133
2.3
86
45
2.6
141
94
1.8
91
78
Mixed vegetables
11.4
81
47
3.7
89
78
3.1
69
40
4.0
82
44
3.7
116
75
3.4
101
50
2.7
107
60
1.8
124
80
Cowpeas, field peas,
0.5
127
64
2.1
63
50
2.5
84
60
2.7
97
57
2.7
109
60
2.3
96
67
3.2
151
63
2.4
163
100
black-eyed peas
Green peas
16.0
61
45
21.8
53
36
20.9
61
42
22.1
72
46
20.9
86
52
19.4
83
46
18.1
112
73
16.9
96
62
Spinach
0.9
26
19
2.8
58
48
3.2
73
53
5.1
93
56
5.2
105
59
3.6
102
62
4.5
127
80
3.0
108
64
String beans
19.7
69
47
25.1
48
33
25.4
51
46
31.6
64
38
31.1
75
54
29.4
74
55
29.5
93
58
24.8
83
51
Summer squash
0.7
26
19
1.3
96
63
1.4
97
91
1.1
136
121
1.2
103
50
1.7
102
56
2.1
155
76
1.2
121
78
Sweet potatoes
10.8
82
47
3.8
97
70
3.1
96
50
3.2
99
62
3.4
144
79
2.1
134
92
3.2
150
75
3.3
166
84
Tomato juice
0
0
0
0.8
147
73
0.9
156
61
0.9
133
48
1.2
159
63
1.0
183
95
2.1
191
94
2.2
194
84
Cucumber pickles
0.2
6
0
4.6
32
26
6.2
38
36
8.1
45
46
8.6
47
50
9.1
50
59
9.9
45
46
8.5
58
71
Fruits
Grapefruit
0
0
0
1.1
145
57
1.0
149
56
1.5
158
64
1.6
160
56
2.4
153
50
2.2
150
68
2.3
159
57
Grapefruit juice
0.6
143
44
1.0
156
66
1.2
174
47
1.6
184
52
1.3
194
73
1.5
173
72
1.7
248
202
2.2
210
66
Oranges
0.9
87
34
8.1
117
45
10.0
134
44
12.6
134
46
10.7
150
51
11.2
137
49
8.9
158
84
9.4
142
51
Orange juice
20.9
122
51
40.9
153
70
41.7
167
73
43.7
178
68
39.4
195
80
41.0
188
77
37.3
228
116
36.6
208
81
Apples
1.7
94
51
23.6
105
44
23.8
124
39
25.8
132
41
22.0
146
55
24.5
140
41
16.7
151
48
19.1
142
46
Applesauce, cooked
35.6
71
49
13.6
104
65
10.4
126
61
14.1
132
76
13.6
151
107
11.1
134
82
10.2
171
125
7.7
146
73
apples
Apple juice
19.2
125
56
13.1
148
64
8.5
170
65
5.5
193
87
3.0
190
69
4.0
204
74
2.7
259
180
3.1
236
139
Cantaloupe
0.2
136
0
1.1
68
35
1.5
125
73
2.2
135
76
2.2
165
85
2.5
152
77
2.0
209
111
2.5
189
113
Raw peaches
1.2
118
39
3.5
129
48
3.8
128
36
4.5
145
68
3.5
170
77
4.9
153
68
4.0
205
111
3.3
142
66
Raw pears
1.2
56
40
2.3
131
43
2.9
150
57
4.0
163
42
2.7
163
46
3.3
161
42
3.2
195
219
1.4
167
57
Raw strawberries
0.2
120
30
1.5
87
41
1.2
69
34
1.6
87
44
1.2
95
53
2.2
91
50
1.6
121
63
1.9
82
45
June 2000
3-64
DRAFT-DO NOT QUOTE OR CITE
-------
Table 3-30. Quantity (as consumed) of Food Groups Consumed Per Eating Occasion and the Percentage of Individuals Using These Foods in Three Days (continued)
Quantity consumed per eating
occasion
(g)
Under 1 year
1 -2 years
3-5 years
6-8 years
9-14 years
15-18
years
Male and Female
Male and Female
Male and Female
Male and Female
Male
Female
Male
Female
Food category
PC
Ave.
SD
PC
Ave.
SD
PC
Ave.
SD
PC
Ave.
SD
PC
Ave.
SD
PC
Ave.
SD
PC
Ave.
SD
PC
Ave.
SD
Grain Products
Yeast Breads
17.6
20
11
88.0
28
16
95.1
36
17
97.2
40
19
96.9
49
28
96.4
44
23
96.2
59
35
93.7
44
21
Pancakes
3.0
39
27
12.2
59
50
12.7
76
52
11.9
96
59
13.5
118
72
10.7
101
89
9.8
161
110
9.8
121
93
Waffles
0.6
30
13
3.4
56
45
5.7
69
41
5.9
69
45
5.2
87
62
4.1
80
68
3.5
125
70
2.4
79
55
Tortillas
0.8
16
7
3.9
26
11
5.1
36
16
4.7
55
29
4.0
74
31
4.3
66
33
3.4
100
48
4.0
69
33
Cakes and Cupcakes
1.6
53
37
17.4
51
38
25.3
61
45
34.4
66
42
36.4
80
56
35.2
77
55
31.0
93
71
26.5
80
59
Cookies
11.9
15
13
46.3
21
15
48.1
25
22
53.2
28
21
44.4
36
36
43.1
32
29
37.9
45
50
34.9
31
26
Pies
0.5
53
30
4.7
88
50
7.1
106
48
8.1
116
58
10.2
133
55
10.6
129
62
13.6
144
66
9.2
126
47
Doughnuts
0.8
36
22
6.6
47
26
8.6
54
28
10.9
60
30
12.0
67
39
12.9
62
36
13.2
91
74
12.9
63
34
Crackers
13.8
10
9
38.1
14
14
32.8
18
20
26.2
20
19
22.1
24
24
22.1
20
16
18.0
32
29
19.6
23
21
Popcorn
0.1
72
0
5.7
9
12
8.5
12
11
9.5
14
9
9.6
18
17
9.1
17
15
6.1
20
20
7.8
18
20
Pretzels
0.7
4
4
3.2
18
18
3.1
21
20
3.3
25
21
4.1
29
25
3.5
30
26
2.9
52
50
3.1
25
16
Corn-based Salty Snacks
0.6
8
2
6.6
24
20
8.6
27
22
10.3
29
26
9.9
33
29
11.3
32
30
8.3
46
44
10.7
34
22
Pasta
3.4
58
42
14.1
82
59
14.7
99
58
14.5
116
74
14.0
162
102
14.5
145
89
11.2
198
133
10.8
158
99
Rice
4.3
53
42
20.9
81
50
22.2
95
58
23.4
120
77
18.9
149
86
22.4
138
77
20.9
195
117
19.0
160
89
Cooked Cereals
16.3
116
82
33.1
149
87
26.0
177
97
21.3
198
104
19.5
223
126
17.3
212
107
14.3
259
132
12.1
229
106
Ready-to-Eat Cereals
68.7
13
11
68.0
23
14
75.8
29
17
76.8
33
19
69.8
41
28
64.0
36
21
50.4
49
31
43.7
37
22
Meat, Poultry, and Dairy Products
Meat3
23.2
58
42
78.2
53
40
82.8
66
46
84.6
82
55
87.1
103
71
84.2
94
69
87.9
123
90
82.6
102
73
Beef
15.6
56
41
60.1
64
38
65.5
79
43
67.2
97
52
69.0
124
66
68.2
111
70
70.3
152
87
65.9
123
73
Pork
10.1
66
44
44.2
37
36
46.0
47
44
46.7
57
49
48.8
68
65
47.0
64
57
56.1
79
75
46.2
68
60
Lamb
2.6
52
29
1.4
72
46
0.6
90
59
0.5
139
86
0.9
171
80
0.7
127
68
0.5
156
81
1.0
112
43
Veal
3.2
54
37
1.2
80
28
1.6
75
33
2.0
115
72
1.5
124
75
1.5
96
46
1.5
170
87
2.1
131
62
Poultry
18.2
60
38
42.2
73
44
42.6
90
50
45.1
103
56
44.3
131
75
44.0
112
58
43.8
153
85
43.7
123
68
Chicken
15.6
62
39
38.8
73
43
39.3
92
50
41.4
106
55
39.8
136
77
39.6
115
57
38.9
160
87
39.5
128
70
Turkey
5.1
53
34
4.4
73
59
4.5
74
39
5.7
74
44
6.5
103
56
6.2
90
54
7.5
120
68
6.2
89
47
Dairv Products
Eggs
17.7
49
30
61.3
59
27
55.2
66
34
48.5
70
37
49.1
85
47
44.3
75
40
52.3
101
49
44.4
79
41
Butter
5.2
6
4
29.2
7
6
28.7
9
10
31.7
10
11
32.4
12
15
30.9
10
9
32.4
14
12
32.0
13
14
Margarine
8.5
5
4
43.8
6
6
46.1
8
8
42.9
9
8
44.8
12
12
40.7
11
12
41.4
16
14
38.6
11
9
Mill?
89.0
170
71
96.9
179
80
97.0
198
83
98.5
227
89
97.4
265
125
95.1
242
103
93.2
314
164
88.0
244
113
Cheesec
6.1
25
21
35.9
31
19
37.0
31
17
35.3
35
23
31.2
39
22
34.9
35
23
39.0
46
30
39.8
37
23
a Meat - beef, pork, lamb, and veal.
b Milk - fluid milk, milk beverages, and milk-based infant formulas.
c Cheese - natural and processed cheese.
Source: Pao et al., 1982 (based on 1977-78 NFCS data).
June 2000
3-65
DRAFT-DO NOT QUOTE OR CITE
-------
1
2
3
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
m
65
66
Table 3-31. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible Portions
Food
Moisture Content (Percent)
Raw Cooked
Comments
Fruit
Apples - dried
Apples 83.93*
Apples - juice
Applesauce
Apricots
Apricots - dried
Bananas
Blackberries
Blueberries
Boysenberries
Cantaloupes - unspecified
Casabas
Cherries - sweet
Crabapples
Cranberries
Cranberries - juice cocktail
Currants (red and white)
Elderberries
Grapefruit
Grapefruit - juice
Grapefruit - unspecified
Grapes - fresh
Grapes - juice
Grapes - raisins
Honeydew melons
Kiwi fruit
Kumquats
Lemons - juice
Lemons - peel
Lemons - pulp
Limes - juice
Limes - unspecified
Loganberries
Mulberries
Nectarines
Oranges - unspecified
Peaches
Pears - dried
Pears - fresh
Pineapple
Pineapple - juice
Plums
Quinces
Raspberries
Strawberries
Tangerine - juice
Tangerines
Watermelon
31.76
84.46**
86.35
31.09
74.26
85.64
84.61
85.90
89.78
91.00
80.76
78.94
86.54
85.00
83.95
79.80
90.89
90.00
90.89
81.30
84.12
15.42
89.66
83.05
81.70
90.73
81.60
88.98
90.21
88.26
84.61
87.68
86.28
86.75
87.66
26.69
83.81
86.50
83.80
86.57
91.57
88.90
87.60
91.51
84.13* sulfured; *without added sugar
*with skin; ** without skin
87.93
88.35*
86.62*
85.56*
86.59*
84.95*
90.10*
92.46*
92.52*
87.49*
64.44*
86.47*
83.51*
85.53
85.20
89.97*
87.00*
89.51*
canned or bottled
*unsweetened
*canned juice pack with skin
sulfured; *without added sugar
*frozen unsweetened
frozen unsweetened
*canned, juice pack
bottled
* canned unsweetened
pink, red, white
American type (slip skin)
canned or bottled
seedless
* canned or bottled
* canned or bottled
all varieties
* canned juice pack
sulfured; *without added sugar
* canned juice pack
* canned juice pack
canned
*frozen unsweetened
* canned sweetened
* canned juice pack
Vegetables
Alfalfa sprouts
Artichokes - globe & French
Artichokes - Jerusalem
91.14
84.38
78.01
86.50
boiled, drained
June 2000
3-66
DRAFT-DO NOT QUOTE OR CITE
-------
1
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
I?
Table 3-31. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible Portions (continued)
Food
Moisture Content (Percent)
Raw Cooked
Comments
Asparagus
Bamboo shoots
Beans - dry
Beans - dry - blackeye peas (cowpeas)
Beans - dry - hyacinth (mature seeds)
Beans - dry - navy (pea)
Beans - dry - pinto
Beans - lima
Beans - snap - Italian - green - yellow
Beets
Beets - tops (greens)
Broccoli
Brussel sprouts
Cabbage - Chinese/celery,
including bok choy
Cabbage - red
Cabbage - savoy
Carrots
Cassava (yucca blanca)
Cauliflower
Celeriac
Celery
Chili peppers
Chives
Cole slaw
Collards
Corn - sweet
Cress - garden - field
Cress - garden
Cucumbers
Dandelion - greens
Eggplant
Endive
Garlic
Kale
Kohlrabi
Lambsquarter
Leeks
Lentils - whole
Lettuce - iceberg
Lettuce - romaine
Mung beans (sprouts)
Mushrooms
Mustard greens
Okra
Onions
Onions - dehydrated or dried
Parsley
Parsley roots
Parsnips
Peas (garden) - mature seeds - dry
Peppers - sweet - garden
Potatoes (white) - peeled
92.25
91.00
66.80
87.87
79.15
81.30
70.24
90.27
87.32
92.15
90.69
86.00
95.32
91.55
91.00
87.79
68.51
92.26
88.00
94.70
87.74
92.00
81.50
93.90
75.96
89.40
89.40
96.05
85.60
91.93
93.79
58.58
84.46
91.00
84.30
83.00
67.34
95.89
94.91
90.40
91.81
90.80
89.58
90.82
3.93
88.31
88.31
79.53
88.89
92.77
78.96
92.04
95.92
71.80
86.90
76.02
93.39
67.17
89.22
90.90
89.13
90.20
87.32
95.55
93.60
92.00
87.38
92.50
92.30
95.00
92.50*
95.72
69.57
92.50
92.50
91.77
91.20
90.30
88.90
90.80
68.70
93.39
91.08
94.46
89.91
92.24
77.72
88.91
94.70
75.42
boil
boil
boil
boil
boil
boil
led, drained
led, drained
boiled,
boiled,
boiled,
boiled,
boiled,
boiled,
boiled,
boiled,
boiled,
boiled,
drained
drained
drained
drained
drained
drained
drained
drained
drained
drained
led, drained
led, drained
led, drained
led, drained
boiled, drained
boiled, drained
boiled, drained
* canned solids & liquid
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
stir-fried
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
baked
June 2000
3-67
DRAFT-DO NOT QUOTE OR CITE
-------
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
Table 3-31. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible Portions (continued)
Food
Moisture Content (Percent)
Raw Cooked
Comments
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
83.29
91.60
94.84
93.61
89.66
77.00
79.80
69.05
91.58
93.68
88.71
72.84
92.66
10.99
85.66
70.64
93.95
93.95
93.85
91.87
91.07
73.46
89.15
71.20
93.69
67.79
90.10
81.00
79.45
91.21
93.70
89.01
71.85
92.65
92.15
63.80
93.90
74.06
87.26
92.40
84.29
93.60
93.20
87.93
baked
boiled, drained
frozen, cooked with added sugar
boiled, drained
boiled, drained
steamed
boiled, drained
all varieties; boiled, drained
all varieties; baked
baked in skin
boiled, drained
dry
steamed
canned
canned
canned
boiled, drained
boiled, drained
boiled, drained
boiled, drained
boiled, drained
Grains
Barley - pearled
Corn - grain - endosperm
Corn - grain - bran
Millet
Oats
Rice - rough - white
Rye - rough
Rye - flour - medium
Sorghum (including milo)
Wheat - rough - hard white
Wheat - germ
Wheat - bran
Wheat - flour - whole grain
10.09
10.37
3.71
3.71
8.22
11.62
10.95
9.85
9.20
9.57
11.12
9.89
10.27
71.41
68.72
crude
crude
crude
Meat
Beef
Beef liver
Chicken (light meat)
Chicken (dark meat)
Duck - domestic
Duck - wild
Goose - domestic
Ham - cured
Horse
Lamb
Lard
Pork
Rabbit - domestic
Turkey
71.60
68.99
74.86
75.99
73.77
75.51
68.30
66.92
72.63
73.42
0.00
70.00
72.81
63.98
69.11
74.16
composite, trimmed, retail cuts
without skin
without skin
roasted
composite, trimmed, retail cuts
roasted
roasted
roasted
June 2000
3-68
DRAFT-DO NOT QUOTE OR CITE
-------
1
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
30
31
32
33
34
Table 3-31. Mean Moisture Content of Selected Food Groups Expressed as Percentages of Edible Portions (continued)
Food
Moisture Content (Percent)
Raw Cooked
Comments
Dairy Products
Butter
Cheese American pasteurized
Cheddar
Swiss
Parmesan, hard
Parmesan, grated
Cream, whipping, heavy
Cottage, lowfat
Colby
Blue
Cream
Yogurt
Plain, lowfat
Plain, with fat
Human milk - estimated from USDA Survey
Human
Skim
Lowfat
74.57
15.87
39.16
36.75
37.21
29.16
17.66
57.71
79.31
38.20
42.41
53.75
85.07
87.90
87.50
90.80
90.80
regular
made from whole milk
whole, mature, fluid
1%
Source: USDA, 1979-1986.
June 2000
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
Table 3-32. Percent Moisture Content for Selected Fish Speciesa
Species
Moisture Content
(%)
Comments
FINFISH
Anchovy, European
73.37
Raw
50.30
Canned in oil, drained solids
Bass
75.66
Freshwater, mixed species, raw
Bass, Striped
79.22
Raw
Bluefish
70.86
Raw
Butterfish
74.13
Raw
Carp
76.31
Raw
69.63
Cooked, dry heat
Catfish
76.39
Channel, raw
58.81
Channel, cooked, breaded and fried
Cod, Atlantic
81.22
Atlantic, raw
75.61
Canned, solids and liquids
75.92
Cooked, dry heat
16.14
Dried and salted
Cod, Pacific
81.28
Raw
Croaker, Atlantic
78.03
Raw
59.76
Cooked, breaded and fried
Dolphinfish, Mahimahi
77.55
Raw
Drum, Freshwater
77.33
Raw
Flatfish, Flounder and Sole
79.06
Raw
73.16
Cooked, dry heat
Grouper
79.22
Raw, mixed species
73.36
Cooked, dry heat
Haddock
79.92
Raw
74.25
Cooked, dry heat
71.48
Smoked
Halibut, Atlantic & Pacific
77.92
Raw
71.69
Cooked, dry heat
Halibut, Greenland
70.27
Raw
Herring, Atlantic & Turbot, domestic species
72.05
Raw
64.16
Cooked, dry heat
59.70
Kippered
55.22
Pickled
Herring, Pacific
71.52
Raw
Mackerel, Atlantic
63.55
Raw
53.27
Cooked, dry heat
Mackerel, Jack
69.17
Canned, drained solids
Mackerel, King
75.85
Raw
Mackerel, Pacific & Jack
70.15
Canned, drained solids
Mackerel, Spanish
71.67
Raw
68.46
Cooked, dry heat
Monkfish
83.24
Raw
Mullet, Striped
77.01
Raw
70.52
Cooked, dry heat
Ocean Perch, Atlantic
78.70
Raw
72.69
Cooked, dry heat
Perch, Mixed species
79.13
Raw
73.25
Cooked, dry heat
Pike, Northern
78.92
Raw
72.97
Cooked, dry heat
Pike. Walleve
79.31
Raw
June 2000
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9
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12
13
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18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
Table 3-32. Percent Moisture Content for Selected Fish Speciesa (continued)
Species
Moisture Content
(%)
Comments
Pollock, Alaska & Walleye
81.56
Raw
74.06
Cooked, dry heat
Pollock, Atlantic
78.18
Raw
Rockfish, Pacific, mixed species
79.26
Raw (Mixed species)
73.41
Cooked, dry heat (mixed species)
Roughy, Orange
75.90
Raw
Salmon, Atlantic
68.50
Raw
Salmon, Chinook
73.17
Raw
72.00
Smoked
Salmon, Chum
75.38
Raw
70.77
Canned, drained solids with bone
Salmon, Coho
72.63
Raw
65.35
Cooked, moist heat
Salmon, Pink
76.35
Raw
68.81
Canned, solids with bone and liquid
Salmon, Red & Sockeye
70.24
Raw
68.72
Canned, drained solids with bone
61.84
Cooked, dry heat
Sardine, Atlantic
59.61
Canned in oil, drained solids with bone
Sardine, Pacific
68.30
Canned in tomato sauce, drained solids with bone
Sea Bass, mixed species
78.27
Cooked, dry heat
72.14
Raw
Seatrout, mixed species
78.09
Raw
Shad, American
68.19
Raw
Shark, mixed species
73.58
Raw
60.09
Cooked, batter-dipped and fried
Snapper, mixed species
76.87
Raw
70.35
Cooked, dry heat
Sole, Spot
75.95
Raw
Sturgeon, mixed species
76.55
Raw
69.94
Cooked, dry heat
62.50
Smoked
Sucker, white
79.71
Raw
Sunfish, Pumpkinseed
79.50
Raw
Swordfish
75.62
Raw
68.75
Cooked, dry heat
Trout, mixed species
71.42
Raw
Trout, Rainbow
71.48
Raw
63.43
Cooked, dry heat
Tuna, light meat
59.83
Canned in oil, drained solids
74.51
Canned in water, drained solids
Tuna, white meat
64.02
Canned in oil
69.48
Canned in water, drained solids
Tuna, Bluefish, fresh
68.09
Raw
59.09
Cooked, dry heat
Turbot, European
76.95
Raw
Whitefish, mixed species
72.77
Raw
70.83
Smoked
Whiting, mixed species
80.27
Raw
74.71
Cooked, dry heat
Yellowtail. mixed species
74.52
Raw
June 2000
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21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Table 3-32. Percent Moisture Content for Selected Fish Speciesa (continued)
Moisture Content
Species
(%)
Comments
SHELLFISH
Crab, Alaska King
79.57
Raw
77.55
Cooked, moist heat
Imitation, made from surimi
Crab, Blue
79.02
Raw
79.16
Canned (dry pack or drained solids of wet pack)
77.43
Cooked, moist heat
71.00
Crab cakes
Crab, Dungeness
79.18
Raw
Crab, Queen
80.58
Raw
Crayfish, mixed species
80.79
Raw
75.37
Cooked, moist heat
Lobster, Northern
76.76
Raw
76.03
Cooked, moist heat
Shrimp, mixed species
75.86
Raw
72.56
Canned (dry pack or drained solids of wet pack)
52.86
Cooked, breaded and fried
77.28
Cooked, moist heat
Spiny Lobster, mixed species
74.07
Imitation made from surimi, raw
Clam, mixed species
81.82
Raw
63.64
Canned, drained solids
97.70
Canned, liquid
61.55
Cooked, breaded and fried
63.64
Cooked, moist heat
Mussel, Blue
80.58
Raw
61.15
Cooked, moist heat
Octopus, common
80.25
Raw
Oyster, Eastern
85.14
Raw
85.14
Canned (solids and liquid based) raw
64.72
Cooked, breaded and fried
70.28
Cooked, moist heat
Oyster, Pacific
82.06
Raw
Scallop, mixed species
78.57
Raw
58.44
Cooked, breaded and fried
73.82
Imitation, made from Surimi
Squid
78.55
Raw
ฃ/1 SA
C^r\r\\^ฃ-A
a Data are reported as in the Handbook
NA = Not available
Source: USDA, 1979-1984 - U.S. Agricultural Handbook No. 8
June 2000
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Table 3-33. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions)
of Selected Meat, Dairy, and Fish Productsa
Product
Fat Percentage
Comment
Meats
Beef
Lean only
Lean and fat, 1/4 in. fat trim
6.16
9.91
Raw
Cooked
Brisket (point half)
Lean and fat
19.24
21.54
Raw
Cooked
Brisket (flat half)
Lean and fat
Lean only
Pork
Lean only
Lean and fat
Cured shoulder, blade roll, lean and fat
Cured ham, lean and fat
Cured ham, lean only
Sausage
Ham
Ham
Lamb
Lean
Veal
Lean and fat
ll
Lean
Lean and fat
Rabbit
Composite of cuts
22.40
4.03
5.88
9.66
14.95
17.18
20.02
12.07
7.57
38.24
4.55
9.55
5.25
9.52
21.59
20.94
2.87
6.58
6.77
11.39
5.55
8.05
Raw
Raw
Raw
Cooked
Raw
Cooked
Unheated
Center slice
Raw, center, country style
Raw, fresh
Cooked, extra lean (5% fat)
Cooked, (11% fat)
Raw
Cooked
Raw
Cooked
Raw
Cooked
Raw
Cooked
Raw
Cooked
Chicken
Meat only
Meat and skin
3.08
7.41
15.06
13.60
Raw
Cooked
Raw
Cooked
Turkey
Meat only
Meat and skin
Ground
2.86
4.97
8.02
9.73
6.66
Raw
Cooked
Raw
Cooked
Raw
Dairy
Milk
Whole
Human
Lowfat (1%)
Lowfat (2%)
Skim
3.16
4.17
0.83
1.83
0.17
3.3% fat, raw or pasteurized
Whole, mature, fluid
Fluid
Fluid
Fluid
Cream
Half and half
Medium
Heavy-whipping
Sour
18.32
23.71
35.09
19.88
Table or coffee, fluid
25% fat, fluid
Fluid
Cultured
June 2000
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19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
Table 3-33. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions)
of Selected Meat, Dairy, and Fish Productsa (continued)
Product
Fat Percentage
Comment
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
FINFISH
Anchovy, European
4.101
Raw
8.535
Canned in oil, drained solids
Bass
3.273
Freshwater, mixed species, raw
Bass, Striped
1.951
Raw
Bluefish
3.768
Raw
Butterfish
NA
Raw
Carp
4.842
Raw
6.208
Cooked, dry heat
Catfish
3.597
Channel, raw
12.224
Channel, cooked, breaded and fried
Cod, Atlantic
0.456
Atlantic, raw
0.582
Canned, solids and liquids
0.584
Cooked, dry heat
1.608
Dried and salted
Cod, Pacific
0.407
Raw
Croaker, Atlantic
2.701
Raw
11.713
Cooked, breaded and fried
Dolphinfish, Mahimahi
0.474
Raw
Drum, Freshwater
4.463
Raw
Flatfish, Flounder and Sole
0.845
Raw
1.084
Cooked, dry heat
Grouper
0.756
Raw, mixed species
0.970
Cooked, dry heat
Haddock
0.489
Raw
0.627
Cooked, dry heat
0.651
Smoked
Halibut, Atlantic & Pacific
1.812
Raw
2.324
Cooked, dry heat
Halibut, Greenland
12.164
Raw
Herring, Atlantic & Turbot, domestic species
7.909
Raw
10.140
Cooked, dry heat
10.822
Kippered
16.007
Pickled
June 2000
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22
23
24
25
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29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
Table 3-33. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions)
of Selected Meat, Dairy, and Fish Productsa (continued)
Product
Fat Percentage
Comment
Herring, Pacific
12.552
Raw
Mackerel, Atlantic
9.076
Raw
15.482
Cooked, dry heat
Mackerel, Jack
4.587
Canned, drained solids
Mackerel, King
1.587
Raw
Mackerel, Pacific & Jack
6.816
Canned, drained solids
Mackerel, Spanish
5.097
Raw
5.745
Cooked, dry heat
Monkfish
NA
Raw
Mullet, Striped
2.909
Raw
3.730
Cooked, dry heat
Ocean Perch, Atlantic
1.296
Raw
1.661
Cooked, dry heat
Perch, Mixed species
0.705
Raw
0.904
Cooked, dry heat
Pike, Northern
0.477
Raw
0.611
Cooked, dry heat
Pike, Walleye
0.990
Raw
Pollock, Alaska & Walleye
0.701
Raw
0.929
Cooked, dry heat
Pollock, Atlantic
0.730
Raw
Rockfish, Pacific, mixed species
1.182
Raw (Mixed species)
1.515
Cooked, dry heat (mixed species)
Roughy, Orange
3.630
Raw
Salmon, Atlantic
5.625
Raw
Salmon, Chinook
9.061
Raw
3.947
Smoked
Salmon, Chum
3.279
Raw
4.922
Canned, drained solids with bone
Salmon, Coho
4.908
Raw
6.213
Cooked, moist heat
Salmon, Pink
2.845
Raw
5.391
Canned, solids with bone and liquid
Salmon, Red & Sockeye
4.560
Raw
6.697
Canned, drained solids with bone
9.616
Cooked, dry heat
Sardine, Atlantic
10.545
Canned in oil, drained solids with bone
Sardine, Pacific
11.054
Canned in tomato sauce, drained solids with bone
Sea Bass, mixed species
1.678
Cooked, dry heat
2.152
Raw
Seatrout, mixed species
2.618
Raw
Shad, American
NA
Raw
Shark, mixed species
3.941
Raw
12.841
Cooked, batter-dipped and fried
Snapper, mixed species
0.995
Raw
1.275
Cooked, dry heat
Sole, Spot
3.870
Raw
Sturgeon, mixed species
3.544
Raw
Sucker, white
4.544
Cooked, dry heat
Sunfish, Pumpkinseed
3.829
Smoked
Swordfish
1.965
Raw
0.502
Raw
Trout, mixed species
3.564
Raw
Trout, Rainbow
4.569
Cooked, dry heat
5.901
Raw
2.883
Raw
3.696
Cooked, dry heat
June 2000
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20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
Table 3-33. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions)
of Selected Meat, Dairy, and Fish Productsa (continued)
Product
Fat Percentage
Comment
Tuna, light meat
7.368
Canned in oil, drained solids
0.730
Canned in water, drained solids
Tuna, white meat
NA
Canned in oil
2.220
Canned in water, drained solids
Tuna, Bluefish, fresh
4.296
Raw
5.509
Cooked, dry heat
Turbot, European
NA
Raw
Whitefish, mixed species
5.051
Raw
0.799
Smoked
Whiting, mixed species
0.948
Raw
1.216
Cooked, dry heat
Yellowtail, mixed species
NA
Raw
SHELLFISH
Crab, Alaska King
NA
Raw
0.854
Cooked, moist heat
Imitation, made from surimi
Crab, Blue
0.801
Raw
0.910
Canned (dry pack or drained solids of wet pack)
1.188
Cooked, moist heat
6.571
Crab cakes
Crab, Dungeness
0.616
Raw
Crab, Queen
0.821
Raw
Crayfish, mixed species
0.732
Raw
0.939
Cooked, moist heat
Lobster, Northern
NA
Raw
0.358
Cooked, moist heat
Shrimp, mixed species
1.250
Raw
1.421
Canned (dry pack or drained solids of wet pack)
10.984
Cooked, breaded and fried
0.926
Cooked, moist heat
Spiny Lobster, mixed species
1.102
Imitation made from surimi, raw
Clam, mixed species
0.456
Raw
0.912
Canned, drained solids
NA
Canned, liquid
10.098
Cooked, breaded and fried
0.912
Cooked, moist heat
Mussel, Blue
1.538
Raw
3.076
Cooked, moist heat
Octopus, common
0.628
Raw
Oyster, Eastern
1.620
Raw
1.620
Canned (solids and liquid based) raw
11.212
Cooked, breaded and fried
3.240
Cooked, moist heat
Oyster, Pacific
1.752
Raw
Scallop, mixed species
0.377
Raw
10.023
Cooked, breaded and fried
NA
Imitation, made from Surimi
Squid
0.989
Raw
ฃ IfTK
NA = Not available
a Based on the lipid content in 100 grams, edible portion. Total Fat Content - saturated, monosaturated and polyunsaturated.
Source: USDA, 1979-1984.
June 2000
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3 Table 3-34. Fat Content of Meat Products
4
5
Meat Product
Total Fat
Percent Fat
6
3-oz cooked serving (85.05 g)
(B)
Content (%)
7
Beef, retail composite, lean only
8.4
9.9
8
Pork, retail composite, lean only
8.0
9.4
9
Lamb, retail composite, lean only
8.1
9.5
10
Veal, retail composite, lean only
5.6
6.6
11
Broiler chicken, flesh only
6.3
7.4
12
Turkey, flesh only
4.2
4.9
13
14 Source: National Livestock and Meat Board, 1993
June 2000
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1
2 Table 3-35. Summary of Recommended Values for Per Capita Intake of Foods, As Consumed
4
5
Age
Mean
95th Percentile
Multiple Percentiles
Study
6
Total Fruit Intake
7
< 1 year
13.2 g/kg-day
41.2 g/kg-day
see Table 3-2
EPA Analysis ofCSFII
8
1-2 years
19.3 g/kg-day
53.9 g/kg-day
1994-96 Data
9
3-5 years
11.0 g/kg-day
32.7 g/kg-day
10
6-11 years
5.4 g/kg-day
18.0 g/kg-day
11
12-19 years
2.8 g/kg-day
11.0 g/kg-day
12
Total Vegetable Intake
13
< 1 year
6.9 g/kg-day
24.2 g/kg-day
see Table 3-2
EPA Analysis ofCSFII
14
1-2 years
9.5 g/kg-day
23.3 g/kg-day
1994-96 Data
15
3-5 years
7.3 g/kg-day
18.3 g/kg-day
16
6-11 years
5.3 g/kg-day
13.5 g/kg-day
17
12-19 years
4.0 g/kg-day
9.3 g/kg-day
18
Total Grain Intake
19
< 1 year
4.1 g/kg-day
20.2 g/kg-day
See Table 3-2
EPA Analysis ofCSFII
20
1-2 years
11.2 g/kg-day
24.7 g/kg-day
1994-96 Data
21
3-5 years
10.3 g/kg-day
21.1 g/kg-day
22
6-11 years
7.2 g/kg-day
15.6 g/kg-day
23
12-19 years
4.4 g/kg-day
9.7 g/kg-day
24
Total Meat Intake
25
< 1 year
1.1 g/kg-day
5.9 g/kg-day
See Table 3-2
EPA Analysis ofCSFII
26
1-2 years
4.4 g/kg-day
10.2 g/kg-day
1994-96 Data
27
3-5 years
4.1 g/kg-day
9.4 g/kg-day
28
6-11 years
2.9 g/kg-day
6.8 g/kg-day
29
12-19 years
2.2 g/kg-day
4.9 g/kg-day
30
Total Dairy Intake
31
< 1 year
111 g/kg-day
235 g/kg-day
See Table 3-2
EPA Analysis ofCSFII
32
1-2 years
37.5 g/kg-day
90.2 g/kg-day
1994-96 Data
33
3-5 years
20.9 g/kg-day
48.8 g/kg-day
34
6-11 years
13.9 g/kg-day
33.5 g/kg-day
35
12-19 years
6.1 g/kg-day
17.8 g/kg-day
36
Total Fish Intake
37
< 1 year
0.11 g/kg-day
0.53 g/kg-day
See Table 3-2
EPA Analysis ofCSFII
38
1-2 years
0.37 g/kg-day
1.79 g/kg-day
1994-96 Data
39
3-5 years
0.32 g/kg-day
1.74 g/kg-day
40
6-11 years
0.26 g/kg-day
1.35 g/kg-day
41
12-19 years
0.20 g/kg-day
1.10 g/kg-day
42
Individual Foods Intake
see Table 3-3
EPA Analysis ofCSFII
1994-96 Data
June 2000
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16
Table 3-35. Summary of Recommended Values for Per Capita Intake of Foods, As Consumed (continued)
95th Percentile
Age Mean Multiple Percentiles Study
Freshwater Total Fish Intake (General Population-)
14 years and under 70.6 mg/kg-day 556 mg/kg-day See Table 3-6 EPA Analysis of CSFII
1989-91 Data
Marine Fish Intake (General Population-)
14 years and under 163 mg/kg-day 894 mg/kg-day See Table 3-6 EPA Analysis of CSFII
1989-91 Data
Recreational Fish Intake - Freshwater
1-5 years 370 mg/kg-day
6-10 years 280 mg/kg-day
Native American Subsistence Fish Intake
<5 years llg/kg-day CRITFC, 1994
Total Fat Intake
See Table 3-15 See Table 3-15 See Table 3-15 Frank et al., 1996
Homeproduced Food Intake
See Table 3-28 See Table 3-28 See Table 3-28 EPA Analysis of
1987/88 NFCS
See Table 3-13 EPA Analysis of West
et al.1989 Data
June 2000
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Table 3-36. Confidence Intake Recommendations for Various Foods, Including Fish (General Population)
Considerations
Rationale
Rating
Study Elements
Level of peer review
Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data collection
period
Validity of approach
Study size
Representativeness of the
population
Characterization of variability
Lack of bias in study design
(high rating is desirable)
Measurement error
Other Elements
Number of studies
Agreement between researchers
Overall Rating
USDA CSFII survey receives high level of peer
review. EPA analysis of these data has been peer
reviewed outside the Agency.
CSFII data are publicly available.
Javitz (1980) is a contractor report to EPA (CSFII)
Enough information is included to reproduce
results.
Analysis is specifically designed to address food
intake.
Data focuses on the U.S. population.
This is new analysis of primary data.
Were the most current data publicly available at the
time the analysis was conducted for the Handbook.
Survey is designed to collect short-term data.
Survey methodology was adequate.
Study size was very large and therefore adequate.
The population studied was the U.S. population.
Survey was not designed to capture long term day-
to-day variability. Short term distributions are
provided.
Response rate was good.
No measurements were taken. The study relied on
survey data.
1 for most foods, 2 for fish; CSFII was the most
recent data set publicly available at the time the
analysis was conducted for the Handbook.
Although the CSFII was the only study classified as
key study for most foods, the results are in good
agreement with earlier data.
The survey is representative of U.S. population.
Although there was only one study considered key,
these data are the most recent and are in 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.
High
High
Medium (Javitz)
High
High
High
High
High
Medium confidence for average values;
Low confidence for long term percentile
distribution
High
High
High
Medium
High
N/A
Low
High
High confidence in the average;
Low confidence in the long-term upper
percentiles
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Table 3-37. Confidence Intake Recommendations for Fish Consumption - Recreational Freshwater Angler Population
Considerations
Rationale
Rating
Study Elements
Level of peer review
Accessibility
Study is in a technical report and has been reviewed High
by the EPA.
The original study analyses are reported in a High
technical report. Subsequent EPA analyses are
detailed in this Handbook.
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data collection
period
Validity of approach
Study size
Representativeness of the
population
Characterization of variability
Lack of bias in study design
(high rating is desirable)
Measurement error
Other Elements
Number of studies
Agreement between researchers
Overall Rating
Enough information is available to reproduce High
results.
Study focused on ingestion of fish by the High
recreational freshwater angler and family.
The study was conducted in the U.S. High
Data are from a primary reference. High
The study was conducted between January and May High
1989.
Data were collected for 1 week. Low
Data presented are from a one week recall of fish Medium
consumption study. Weight of fish consumed was
estimated using approximate weight of fish catch
and edible fraction or approximate weight of fish
meal.
Study population was 621 children. Medium
The study was localized to a single state. Low
Distributions were not generated. High
Response rate was 47 percent. Medium
Weight of fish portions were estimated in one study, Medium
fish weight was estimated from reported fish length
in another study.
There is 1 study. Low
There is only 1 study. EPA performed an analyses Low
using these data.
The study is not nationally representative and not Low
representative of long-term consumption.
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Table 3-38. Confidence Intake Recommendations for Fish Consumption - Native American Subsistence Population
Considerations
Rationale
Rating
Study Elements
Level of peer review
Accessibility
Study is in a technical report. Medium
CRITFC is a technical report, that is publicly Medium
available
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data collection
period
Validity of approach
Study size
Representativeness of the
population
Characterization of variability
Lack of bias in study design
(high rating is desirable)
Measurement error
Other Elements
Number of studies
Agreement between researchers
Overall Rating
The study was adequately detailed and enough
information is available to reproduce results.
Study focused on fish ingestion among Native
American Tribes.
The study was specific in the U.S.
The study used primary data.
Data were from 1991-1992.
Data were collected for 1 study.
Individual intake measured directly, but some
respondents provided in same information for the
children as themselves.
The sample population was 204 children < 5 years
old.
Only one state was represented; population < 5
years old only.
Individual variations were not described.
The response rate was 69 percent in the study..
The weight of the fish was estimated.
There was only one study.
There was only one study.
Study is not nationally representative.
High
High
High
High
High
High
Low confidence for long term percentile
distribution
Low
Medium
Low
Medium
Medium
Medium
Low - Medium
Medium
Low
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1 APPENDIX 3A
2
3 CALCULATIONS USED IN THE 1994-96 CSFII ANALYSIS TO
4 CORRECT FOR MIXTURES
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
APPENDIX 3A
Calculations Used in the 1994-96 CSFII Analysis to Correct for Mixtures
Distributions of intake for various food groups were generated for the food/items groups using the USD A
1994-96 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 3A-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.
IR
meat-adjusted
(IR, mixtures * 'meat/gr
(1Rmeat)
^meatier) + W
* Ft
'mt mixtures meatlmt
) +
where:
-meat-adjusted
-gr mixtures
-mt mixtures
IR,
m,
IR,
TR
^-^meat
Fr
A meat/gr
Fr
Ameat/mt
adjusted individual intake rate for total meat;
individual intake rate for grain mixtures;
individual intake rate for meat mixtures;
individual intake rate for meats;
fraction of grain mixture that is meat; and
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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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
TABLE 3A-1. FRACTION OF GRAIN AND MEAT MIXTURE INTAKE REPRESENTED BY
VARIOUS FOOD ITEMS/GROUPS
Grain Mixtures
total vegetables
0.2584
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
fish
0.0000
eggs
0.0112
fat
0.0225
Meat Mixtures
total vegetables
0.3000
tomatoes
0.1111
white potatoes
0.0333
total meats
0.3111
beef
0.2000
pork
0.0222
poultry
0.0778
dairy
0.0556
total grains
0.1333
fish
0.0444
eggs
0.0111
fats
0.0222
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1 APPENDIX 3B
2
3 FOOD CODES AND DEFINITIONS USED IN
4 ANALYSIS OF THE 1994-96 USDA CSFII DATA
5
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TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA
Food Product
Food Codes
MAJOR FOOD GROUPS
Total Dairy
1- Milk and Milk Products
milk and milk drinks
cream and cream substitutes
milk desserts, sauces, and gravies
cheeses
Includes regular fluid milk, human milk, imitation milk
products, yogurt, milk-based meal replacements, and infant
formulas. Also includes the average portion of grain
mixtures (i.e., 13.48 percent) and the average portion of
meat mixtures (i.e., 5.56 percent) made up by dairy.
Total Meats
20- Meat, type not specified
21- Beef
22- Pork
23- Lamb, veal, game, carcass meat
24- Poultry
25- Organ meats, sausages, lunchmeats, meat spreads
Also includes the average portion of grain mixtures (i.e.,
7.87 percent) and the average portion of meat mixtures (i.e.,
31.11 percent) made up by meats.
Total Fish
26- Fish, all types
Also includes the average portion of meat mixtures (i.e.,
4.44 percent) made up by fish.
Eggs
3- Eggs
eggs
egg mixtures
egg substitutes
eggs baby food
froz. meals with egg as main ingred.
Includes baby foods. Also includes the average portion of
grain mixtures (i.e., 1.12 percent) and the average portion of
meat mixtures (i.e., 1.11 percent) made up by eggs.
Total Grains
50- flour
51- breads
52- tortillas
53- sweets
54- snacks
5 5- 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.,
31.46 percent) and the average portion of meat mixtures
(i.e., 13.33 percent) made up by grain.
Total Fruits
6- Fruits
citrus fruits and juices
dried fruits
other fruits
fruits/juices & nectar
fruit/juices baby food
Includes baby foods.
Total Vegetables
7- Vegetables (all forms)
white potatoes & PR starchy
dark green vegetables
deep yellow vegetables
tomatoes and torn, mixtures
other vegetables
veg. and mixtures/baby food
veg. with meat mixtures
411- Beans/legumes
412- Beans/legumes
413- Beans/legumes
414- Soybeans
415- Bean dinners and soups
416- Bean dinners and soups
418- Meatless items
419- Soyburgers
Includes baby foods; mixtures, mostly vegetables; does not
include nuts and seeds. Also includes the average portion of
grain mixtures (i.e., 25.84 percent) and the average portion
of meat mixtures (i.e., 30.00 percent) made up by
vegetables.
Total Fats
8- Fats (all forms)
Includes butter, margarine, animal fat, sauces, vegetable
oils, dressings, and mayonnaise. Also includes the average
portion of grain mixtures (i.e., 2.25 percent) and the average
portion of meat mixtures (i.e., 2.22 percent) made up by
meats.
June 2000
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TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
Food Product
Food Codes
INDIVIDUAL MEATS
Beef
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
Also includes the average portion of grain mixtures (i.e.,
4.49 percent) and the average portion of meat mixtures (i.e.,
20.0 percent) made up by beef.
Pork
22-
Pork
pork, nfs; ground dehydrated
chops
steaks, cutlets
ham
roasts
Canadian bacon
bacon, salt pork
other pork items
pork baby food
Also includes the average portion of grain mixtures (i.e.,
1.12 percent) and the average portion of meat mixtures (i.e.,
2.22 percent) made up by pork.
Game
233-
Game
Poultry
24-
Poultry
chicken
turkey
duck
other poultry
poultry baby food
Also includes the average portion of grain mixtures (i.e.,
1.12 percent) and the average portion of meat mixtures (i.e.,
7.78 percent) made up by poultry.
INDIVIDUAL GRAINS
Breads
51-
52-
breads, rolls, muffins, bagel, biscuits, corn bread
tortillas
Sweets
53-
cakes, cookies, pies, pastries, doughnuts,
breakfast bars, coffee cakes
Snacks
54-
crackers, salty snacks, popcorn, pretzels
Breakfast Foods
55-
pancakes, waffles, french toast
Pasta
561-
macaroni, noodles, spaghetti
Cooked Cereals
56200-
56201-
56202-
56203-
56206-
56207-
56208-
56209-
56210-
Includes grits, oatmeal, cornmeal mush, millet, etc.
Rice
56204-
56205-
Includes all varieties of rice.
Ready-to-eat Cereals
570-
571-
572-
573-
574-
576-
Includes all varieties of ready-to-eat cereals.
Baby Cereals
578-
baby cereals
June 2000
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TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
Food Product
Food Codes
FRUIT CATEGORIES
Citrus Fruits
61-
Citrus Fruits and Juices
63403150
Lime souffle
6720500
Orange Juice, baby food
6721100
Orange-Apple-Banana Juice, baby food
6723050
Orange/carrot baby juice
Includes some citrus mixtures.
Other Fruits
62-
Dried Fruits
67213-
Baby Juices
63-
Other Fruits
672300
Apple sweet potato juice
64-
Fruit Juices and Nectars Excluding Citrus
6725-
Baby Juice
671-
Fruits, baby
673-
Baby Fruits
67202-
Apple Juice, baby
674-
Baby Fruits
67203-
Baby Juices
675-
Apples with meat
67204-
Baby Juices
Includes some mixtures (i.e., salads, baby foods).
67212-
Baby Juices
Apples
6210110
Apples, dried, uncooked
6410445
Apple-raspberry juice
6210115
Apples, dried, uncooked, low sodium
6410450
Apple-grape juice
6210120
Apples, dried, cooked, NS as to sweetener
6710030
Applesauce, baby toddler
6210122
Apples, dried, cooked, unsweetened
6710100
Apple-raspberry, baby, ns as to strained or
6210123
Apples, dried, cooked, with sugar
junior
6210130
Apple chips
6710101
Apple-raspberry, baby, strained
6310100
Apples, raw
6710102
Apple-raspberry, baby, junior
6310111
Applesauce, NS as to sweetener
6710200
Applesauce baby fd., NS as to str. or jr.
6310112
Applesauce, unsweetened
6710201
Applesauce baby food, strained
6310113
Applesauce with sugar
6710202
Applesauce baby food, junior
6310114
Applesauce with low calorie sweetener
67104-
Applesauce & other fruit, baby
6310115
Applesauce/other fruits
67113-
Apples & pears, baby
6310121
Apples, cooked or canned with syrup
6720200
Apple juice, baby food
6310131
Apple, baked NS as to sweetener
6720300
Apple w/other fruit juice, baby
6310132
Apple, baked, unsweetened
6720320
Apple-banana juice, baby
6310133
Apple, baked with sugar
6720340
Apple-cherry juice, baby
6310141
Apple rings, fried
6720345
Apple-cranberry juice, baby
6310142
Apple, pickled
6720350
Apple-grape juice, baby
6310150
Apple, fried
6720360
Apple-peach juice, baby
634010
Apple/other fruit salad
6720370
Apple-prune juice, baby
6340106
Apple, candied
6723000
Apple-sweet potato juice, baby food
6410101
Apple cider
6725005
Apple juice w/lowfat yogurt, baby food
6410401
Apple juice
67301-
Apples & cranberries w/tapioca, baby
6410405
Apple juice with vitamin C
6740407
Apple yogurt dessert, baby, strained
6410409
Apple juice with calcium
67412-
Dutch apple dessert, baby
6410415
Apple-cherry juice
675-
Apples & meat, baby
6410420
Apple-pear juice
Includes some mixtures.
Bananas
6210710
Banana flakes, dehydrated
6725010
Banana juice with yogurt, baby
6210720
Banana chips
67308-
Banana, baby
63107-
Bananas, various
67309-
Banana, baby
6340199
Banana, chocolate covered
6740411
Banana apple dessert, baby
6340201
Bana whip
6740420
Banana pineapple dessert, baby
6420150
Banana nectar
67408-
Banana, baby
6710503
Banana, baby
674041-
Banana, baby
6711500
Banana, baby
Peaches
62116-
Dried Peaches
67108-
Peaches ,baby
63135-
Peaches
6711450
Peaches, dry, baby
6412203
Peach Juice
67405-
Peach cobbler, baby
6420501
Peach Nectar
67413700
Peach yogurt dessert, baby
Pears
62119-
Dried Pears
6711455
Pears, dry, baby
63137-
Pears
6721200
Pear juice, baby
6341201
Pear salad
6412300
Pear/white grape/passion fruit juice
6421501
Pear Nectar
67114-
Pear/pineapple, baby
67109-
Pears, baby
6725020
Pear/peach juice with yogurt, baby
Strawberries
6322-
Strawberries
6413250
Strawberry Juice
Other Berries
6210910
Cranberries, dried
6410460
Blackberry Juice
6320-
Other Berries
64105-
Cranberry Juice
6321-
Other Berries
6740430
Blueberry yogurt dessert, baby
6322400
Youngberries, raw
6341101
Cranberry salad
June 2000
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TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
1
Food Product
Food Codes
Exposed Fruits
621011-
Apple, dried
6710102
Apple-raspberry, baby, junior
621012-
Apple, dried
67102-
Applesauce, baby
6210130
Apple chips
6710400
Applesauce & apricots, baby, ns as to str or jr
62104-
Apricot, dried
6710401
Applesauce & apricots, baby, strained
62108-
Currants, dried
6710402
Applesauce & apricots, baby, junior
6210910
Cranberries, dried
6710407
Applesauce w/cherries, baby, strained
62110-
Date, dried
6710408
Applesauce w/cherries, baby, junior
62116-
Peaches, dried
6710409
Applesauce w/cherries, baby, ns str/jr
62119-
Pears, dried
67108-
Peaches, baby
62121-
Plum, dried
67109-
Pears, baby
62122-
Prune, dried
6711000
Prunes, baby
62125-
Raisins
6711300
Apples & pears, baby, ns as to str or jr
63101-
Apples/applesauce
6711301
Apples & pears, baby, strained
63102-
Wi-apple
6711302
Apples & pears, baby, junior
63103-
Apricots
6711450
Peaches, baby, dry
63111-
Cherries, maraschino
6711455
Pears, baby, dry
63112-
Acerola
67202-
Apple Juice, baby
63113-
Cherries, sour
6720340
Apple-cherry juice, baby
63115-
Cherries, sweet
6720345
Apple-cranberry juice, baby
63117-
Currants, raw
6720350
Apple-grape juice, baby
63123-
Grapes
6720360
Apple-peach juice, baby
6312601
Juneberry
6720370
Apple-prune juice, baby
63131-
Nectarine
6720380
White Grape Juice, baby
63135-
Peach
67212-
Pear Juice, baby
63137-
Pear
6723000
Apple-sweet potato juice, baby food
63139-
Persimmons
6725005
Apple juice w/lowfat yogurt, baby food
63 MS-
Plum
6725020
Pear-peach juice w/lowfat yogurt, baby food
eS 146-
Quince
6730100
Apples & cranberries w/tapioca, baby, ns str/jr
63147-
Rhubarb/Sapodillo
6730101
Apples & cranberries w/tapioca, baby, strained
632-
Berries
6730102
Apples & cranberries w/tapioca, baby, junior
6340101
Apple salad w/dressing (include waldorf salad)
6730400
Plums w/tapioca, baby, ns as to str/jr
6340102
Apple & cabbage salad w/dressing
6730401
Plums w/tapioca, baby, strained
6340103
Apple & fruit salad w/dressing
6730402
Plums w/tapioca, baby, junior
6340106
Apple, candied (include caramel apples)
6730403
Plums, bananas & rice, baby, strained
6340203
Prune whip
6730450
Prunes w/oatmeal, baby, strained
6341101
Cranberry salad, congealed
6730501
Prunes w/tapioca, baby, strained
6341201
Pear salad w/dressing
6730600
Ciruelas w/tapioca, baby
6341500
Soup, sour cherry
6730700
Apricots w/tapioca, baby, ns as to str/jr
64101-
Apple Cider
6730701
Apricots w/tapioca, baby, strained
64104-
Apple Juice
6730702
Apricots w/tapioca, baby, junior
6410409
Apple juice with calcium
6740407
Apple yogurt dessert, baby, strained
64105-
Cranberry Juice
6740430
Blueberry yogurt dessert, baby, strained
64116-
Grape Juice
6740455
Cherry cobbler, baby, junior
64122-
Peach Juice
6740500
Peach cobbler, baby, ns as to str/jr
6412300
Pear-white-grape-passion fruit juice, w/added Vit.
6740501
Peach cobbler, baby, strained
C
6740502
Peach cobbler, baby, junior
64132-
Prune/Strawberry Juice
6741000
Cherry vanilla pudding, baby
6420101
Apricot Nectar
6741200
Dutch apple dessert, baby, ns as to str/jr
64205-
Peach Nectar
6741201
Dutch apple dessert, baby, strained
64215-
Pear Nectar
6741202
Dutch apple dessert, baby, junior
6710030
Applesauce, baby toddler
6741370
Peach yogurt dessert, baby, strained
6710100
Apple-raspberry, baby, ns as to strained or junior
675-
Apples & meat
6710101
Apple-raspberry, baby, strained
June 2000
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TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
Food Product
Food Codes
Protected Fruits
61-
Citrus Fr., Juices (incl. cit. juice mixtures)
64121-
Passion Fruit Juice
62107-
Bananas, dried
64124-
Pineapple Juice
62113-
Figs, dried
64125-
Pineapple juice
62114-
Lychees/Papayas, dried
64133-
Watermelon Juice
62120-
Pineapple, dried
6420150
Banana Nectar
62126-
Tamarind, dried
64202-
Cantaloupe Nectar
63105-
Avocado, raw
64203-
Guava Nectar
63107-
Bananas
64204-
Mango Nectar
63109-
Cantaloupe, Carambola
64210-
Papaya Nectar
63110-
Cassaba Melon
64213-
Passion Fruit Nectar
63119-
Figs
64221-
Soursop Nectar
63121-
Genip
6710503
Bananas, baby
63125-
Guava/Jackfruit, raw
6711500
Bananas, baby, dry
6312650
Kiwi
6720500
Orange Juice, baby
6312651
Lychee, raw
6721300
Pineapple Juice, baby
6312660
Lychee, cooked
6723050
Orange-carrot juice, baby food
6312665
Loquats, raw
6725010
Banana juice w/lowfat yogurt, baby food
63127-
Honeydew
6730800
Bananas w/tapioca, baby, ns as to str/jr
63129-
Mango
6730801
Bananas w/tapioca, baby, strained
63133-
Papaya
6730802
Bananas w/tapioca, baby, junior
63134-
Passion Fruit
6730900
Bananas & pineapple w/tapioca, baby, ns as to
63141-
Pineapple
str/jr
63 MS-
Pomegranate
6730901
Bananas & pineapple w/tapioca, baby, strained
eS MS-
Sweetsop, Soursop, Tamarind
6730902
Bananas & pineapple w/tapioca, baby, junior
eS 149-
Watermelon
6740411
Banana apple dessert, baby food, strained
6340199
Banana, chocolate-covered, w/nuts
6740420
Banana pineapple dessert, w/tapioca, baby
6340201
Banana whip
6740801
Banana pudding, baby, strained
6340205
Fried dwarf banana w/cheese, puerto rican style
6740850
Banana yogurt dessert, baby, strained
6340315
Lime souffle (include other citrus fruits)
6741400
Pineapple dessert, baby, ns as to str/jr
6340801
Guacamole w/tomatoes
6741401
Pineapple dessert, baby, strained
6340820
Guacamole w/tomatoes & chile peppers
6741402
Pineapple dessert, baby, junior
63490901
Guacamole, nfs
6741410
Mango dessert w/tapioca, baby
64120-
Papaya Juice
VEGETABLE CATEGORIES
Asparagus
7510080
Asparagus, raw
756010
Asparagus soup
75202-
Asparagus, cooked
Does not include vegetables with meat mixtures.
7540101
Asparagus, creamed or with cheese
Beets
72101-
Beet greens
7550021
Beets, pickled
7510250
Beets, raw
7560110
Beet soup
752080-
Beets, cooked
76403-
Beets, baby
752081-
Beets, canned
Does not include vegetable with meat mixtures.
7540501
Beets, Harvard
Broccoli
722-
Broccoli (all forms)
7514050
Broccoli salad w/cauliflower, cheese, bacon, &
7230200
Broccoli soup (include cream of broccoli soup)
dressing
7230210
Broccoli cheese soup, prep w/milk
Does not include vegetable with meat mixtures.
7230200
Broccoli soup (include cream of broccoli soup)
Cabbage
7510300
Cabbage, raw
75211-
Green Cabbage, cooked
7510400
Cabbage, Chinese, raw
75212-
Red Cabbage, cooked
7510500
Cabbage, red, raw
752130-
Savoy Cabbage, cooked
7514100
Cabbage salad or coleslaw
75230-
Sauerkraut, cooked
7514110
Cabbage salad or coleslaw, w/apples, raisins, dress
7540701
Cabbage, creamed
7514120
Cabbage salad or coleslaw, w/pineapple, dressing
755025-
Cabbage, pickled or in relish
7514130
Cabbage, Chinese, salad
7560120
Cabbage soup
75210-
Chinese Cabbage, cooked
7560121
Cabbage w/meat soup
Does not include vegetable with meat mixtures.
Carrots
7310-
Carrots (all forms)
76201-
Carrots, baby
7311140
Carrots in Sauce
7620200
Carrots & peas, baby
7311200
Carrot Chips
Does not include vegetable with meat mixtures.
735-
Carrot soup
June 2000
3B-5
DRAFT-DO NOT QUOTE OR CITE
-------
TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
Food Product
Food Codes
Corn
7510960 Corn, raw
7521600 Corn, cooked, NS as to color/fat added
7521601 Corn, cooked, NS as to color/fat not added
7521602 Corn, cooked, NS as to color/fat added
7521605 Corn, cooked, NS as to color/cream style
7521607 Corn, cooked, dried
7521610 Corn, cooked, yellow/NS as to fat added
7521611 Corn, cooked, yellow/fat not added
7521612 Corn, cooked, yellow/fat added
7521615 Corn, yellow, cream style
7521616 Corn, cooked, yell. & wh./NS as to fat
7521617 Corn, cooked, yell. & wh./fatnot 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
7530301 Corn w/peppers, red or green, cooked, no fat
added
7541101 Corn scalloped or pudding
7541102 Corn fritter
7541103 Corn with cream sauce
7550101 Corn relish
756040- Corn soup
76405- Corn, baby
Does not include vegetable with meat mixtures.
Cucumbers
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
7560451 Cucumber soup, cream of, w/milk
Does not include vegetable with meat mixtures.
Lettuce
75113- Lettuce, raw
75143- Lettuce salad with other veg.
7514410 Lettuce, wilted, with bacon dressing
7522005 Lettuce, cooked
Does not include vegetable with meat mixtures.
Lima Beans
4110300 Lima beans, dry, cooked, ns as to added fat
4110301 Lima beans, dry, cooked, fat added
4110302 Lime beans, dry, cooked, no fat added
4121011 Stewed dry lima beans, p.r.
4130104 Lima bean soup
4160104 Lima bean soup
7510200 Lima beans, raw
752040- Lima beans, cooked
752041- Lima beans, canned
75301- Beans, lima & corn (succotash)
75402- Lima beans with sauce
Does not include vegetable with meat mixtures.
Okra
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 with meat mixtures.
Onions
7510950 Chives, raw
7511150 Garlic, raw
7511250 Leek, raw
7511701 Onions, young green, raw
7511702 Onions, mature
7521550 Chives, dried
7521740 Garlic, cooked
7521840 Leek, cooked
7522100 Onions, mature cooked, NS as to fat added
7522101 Onions, mature cooked, fat not added
7522102 Onions, mature cooked, fat added
7522103 Onions, pearl cooked
7522104 Onions, young green cooked, NS as to fat
7522105 Onions, young green cooked, fat not added
7522106 Onions, young green cooked, fat added
7522110 Onion, dehydrated
7541501 Onions, creamed
7541502 Onion rings
75605- Leek soup
75608- Onion soup
Does not include vegetable with meat mixtures.
June 2000
3B-6
DRAFT-DO NOT QUOTE OR CITE
-------
TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
Food Product
Food Codes
Peas
413010- Cowpeas, dry, cooked
413020- Chickpeas, dry, cooked
41303- Split peas, dry, cooked
413035- Stewed green peas
4130403 Peas, dry, cooked w/pork
4130413 Cowpeas, dry, cooked w/pork
4131010 Stewed pigeon peas, p.r.
4131015 Stewed chickpeas, p.r.
4131016 Stewed chickpeas, w/potatoes, p.r.
4131020 Chickpeas, w/pig's feet, p.r.
4131021 Chickpeas, w/spanish sausage, p.r.
4131022 Fried chickpeas, p.r.
4131031 Stewed cowpeas, p.r.
4160201 Chunky pea & ham soup
4160202 Garbanzo or chickpea soup
4160203 Split pea & ham soup
4160204 Pea soup, instant type
4160205 Split pea soup
4160206 Pigeon pea asopao
4160207 Split pea soup, can, reduced sodium, w/water/rts
4160209 Split pea & ham soup, can, reduced sodium,
w/water/rts
731110-&
731112- Peas & carrots
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
75315- Peas & corn onions, mushrooms, beans, or
potatoes
7541650 Pea salad
7541660 Pea salad with cheese
75417- Peas, with sauce or creamed
75609- Pea soup
76409- Peas, baby
76411- Peas, creamed, baby
7650200 Peas & brown rice, baby
Does not include vegetable with meat mixtures.
Peppers
7512140 Pepper, poblano, raw
7512100 Pepper, hot chili, raw
7512150 Pepper, serrano, raw
7512200 Pepper, raw
7512210 Pepper, sweet green, raw
7512220 Pepper, sweet red, raw
7512400 Pepper, banana, 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
7530700 Green peppers & onions, cooked, fat added in
cooking
7551101 Peppers, hot, sauce
7551102 Peppers, pickled
7551104 Pepper, hot pickled
7551105 Peppers, hot pickled
Does not include vegetable with meat mixtures.
Pumpkin
732- Pumpkin (all forms)
733- Winter squash (all forms)
76205- Squash, baby
Does not include vegetable with meat mixtures.
Snap Beans
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
7530201 Beans, green string w/tomatoes (assume w/o fat)
7530202 Beans, green string w/onions, cooked, no fat added
7530203 Beans, green string w/chickpeas, cooked, no fat
added
7530204 Beans, green string w/almonds, cooked, no fat
added
7530205 Beans, green & potatoes, cooked, no fat added
7530206 Beans, green w/pinto beans, cooked, no fat
added
7530207 Beans, green w/spaetzel, cooked, no fat added
7530208 Bean salad, yellow &/or green string beans
7530220 Beans, green string w/onions, ns as to added fat
7530221 Beans, green string w/onions, fat added
7530250 Beans, green & potatoes, ns as to added fat
7530251 Beans, green & potatoes, fat added
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
7640106 Beans, green string, baby
Does not include vegetable with meat mixtures.
Tomatoes
74- Tomatoes and Tomato Mixtures
raw, cooked, juices, sauces, mixtures, soups,
sandwiches
Also includes the average portion of grain mixtures (i.e.,
16.85 percent) and the average portion of meat mixtures
(i.e., 11.11 percent) made up by tomatoes.
White Potatoes
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
76420000 Potatoes, baby
Also includes the average portion of meat mixtures (i.e.,
3.33 percent) made up by meats.
Dark Green
Vegetables
72- Dark Green Vegetables
all forms
leafy, nonleafy, dk. gr. veg. soups
June 2000
3B-7
DRAFT-DO NOT QUOTE OR CITE
-------
TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
Food Product
Food Codes
Deep Yellow
73-
Deep Yellow Vegetables
Vegetables
all forms
carrots, pumpkin, squash, sweet potatoes, dp. yell,
veg. soups
Other Vegetables
75-
Other Vegetables
all forms
Exposed Vegetables
721-
Dark Green Leafy Veg.
7514800
Cob salad w/dressing
722-
Dark Green Nonleafy Veg.
7520060
Algae, dried
7230200
Broccoli soup (include cream of broccoli soup)
75201-
Artichoke, cooked
7230210
Broccoli cheese soup, prep w/milk
75202-
Asparagus, cooked
7230500
Escarole soup
75203-
Bamboo shoots, cooked
7230600
Watercress broth w/shrimp
752049-
Beans, string, cooked
7230700
Spinach soup
75205-
Beans, green, cooked/canned
7230800
Dark-green leafy vegetable soup w/meat, oriental
75206-
Beans, yellow, cooked/canned
7230850
Dark-green leafy vegetable soup, meatless, oriental
75207-
Bean Sprouts, cooked
74-
Tomatoes and Tomato Mixtures
752085-
Breadfruit
7510050
Alfalfa Sprouts
752087-
Broccoflower, cooked
7510075
Artichoke, Jerusalem, raw
752090-
Brussel Sprouts, cooked
7510080
Asparagus, raw
75210-
Cabbage, Chinese, cooked
75101-
Beans, sprouts and green, raw
75211-
Cabbage, green, cooked
7510260
Broccoflower, raw
75212-
Cabbage, red, cooked
7510275
Brussel Sprouts, raw
752130-
Cabbage, savoy, cooked
7510280
Buckwheat Sprouts, raw
75214-
Cauliflower
7510300
Cabbage, raw
75215-
Celery, Chives, Christophine (chayote)
7510400
Cabbage, Chinese, raw
752167-
Cucumber, cooked
7510500
Cabbage, Red, raw
752170-
Eggplant, cooked
7510700
Cauliflower, raw
752171-
Fern shoots
7510900
Celery, raw
752172-
Fern shoots
7510950
Chives, raw
752173-
Flowers of sesbania, squash or lily
7510955
Cilantro, raw
7521801
Kohlrabi, cooked
7511100
Cucumber, raw
75219-
Mushrooms, cooked
7511120
Eggplant, raw
75220-
Okra/lettuce, cooked
7511200
Kohlrabi, raw
7522116
Palm Hearts, cooked
75113-
Lettuce, raw
7522121
Parsley, cooked
7511500
Mushrooms, raw
75226-
Peppers, pimento, cooked
7511900
Parsley
75230-
Sauerkraut, cooked/canned
7512100
Pepper, hot chili
75231-
Snowpeas, cooked
75122-
Peppers, raw
75232-
Seaweed
7512400
Pepper, banana, raw
75233-
Summer Squash
7512750
Seaweed, raw
7530201
Beans, green string w/tomatoes (assume w/o fat)
7512775
Snowpeas, raw
7530202
Beans, green string w/onions, no fat added
75128-
Summer Squash, raw
7530203
Beans, green string w/chickpeas, cooked, no fat
7513210
Celery Juice
added
7514050
Broccoli salad w/cauliflower, cheese, bacon,
dressing
7530204
Beans, green string w/almonds, cooked, no fat
added
7514100
Cabbage or cole slaw
7530205
Beans, green & potatoes, cooked, no fat added
7514110
Cabbage salad or coleslaw w/apples/raisins,
dressing
7530206
Beans, green w/pinto beans, cooked, no fat
added
7514120
Cabbage salad or coleslaw w/pineapple, dressing
7530207
Beans, green w/spaetzel, cooked, no fat added
7514130
Chinese Cabbage Salad
7530208
Bean salad, yellow &/or green string beans
7514150
Celery with cheese
7530220
Beans, green string w/onions, ns as to added fat
75142-
Cucumber salads
7530221
Beans, green string w/onions, fat added
75143-
Lettuce salads
7530250
Beans, green & potatoes, ns as to added fat
7514410
Lettuce, wilted with bacon dressing
7530251
Beans, green & potatoes, fat added
7514500
Seven-layer salad (lettuce, mayo, cheese, egg,
7530601
Eggplant in torn sauce, cooked, no fat added
peas)
7530700
Green peppers & onions, cooked, fat added in
7514600
Greek salad
cooking
7514700
Spinach salad
June 2000
3B-8
DRAFT-DO NOT QUOTE OR CITE
-------
TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
Food Product
Food Codes
Exposed Vegetables
7531600
Squash, summer & onions, cooked, no fat added
7550314
Cucumber pickles, sweet, reduced salt
(continued)
7531601
Zucchini w/tom sauce, cooked, no fat added in
7550500
Mushrooms, pickled
cooking
7550700
Okra, pickled
7531602
Squash, summer & onions, cooked, fat added
75510-
Olives
7540050
Artichokes, stuffed
7551101
Peppers, hot
7540101
Asparagus, creamed or with cheese
7551102
Peppers, pickled
75403-
Beans, green with sauce
7551104
Peppers, hot pickled
75404-
Beans, yellow with sauce
7551301
Seaweed, pickled
7540601
Brussel Sprouts, creamed
7553500
Zucchini, pickled
7540701
Cabbage, creamed
756010-
Asparagus soup
75409-
Cauliflower, creamed
756012-
Cabbage soup
75410-
Celery/Chiles, creamed
756020-
Cauliflower soup, cream of, w/milk
75412-
Eggplant, fried, with sauce, etc.
756030-
Celery soup
75413-
Kohlrabi, creamed
7560451
Cucumber soup, cream of, w/milk
75414-
Mushrooms, Okra, fried, stuffed, creamed
756046-
Gazpacho
754180-
Squash, baked, fried, creamed, etc.
75607-
Mushroom soup
7541822
Christophine, creamed
7561201
Zucchini soup, cream of, prep w/milk
7550011
Beans, pickled
7564700
Seaweed soup
7550051
Celery, pickled
76102-
Dark Green Veg., baby
7550201
Cauliflower, pickled
76401-
Beans, baby (excl. most soups & mixtures)
755025-
Cabbage, pickled
7660400
Broccoli & chicken, baby, strained
7550301
Cucumber pickles, dill
7661150
Green beans & turkey, baby, strained
7550302
Cucumber pickles, relish
7731601
Stuffed cabbage w/meat, p.r. (repollo relleno
7550303
Cucumber pickles, sour
con carne)
7550304
Cucumber pickles, sweet
7731651
Stuffed cabbage w/meat & rice, Syrian dish,
7550305
Cucumber pickles, fresh
puerto rican style
7550307
Cucumber, Kim Chee
7731660
Eggplant and meat casserole
7550308
Eggplant, pickled
7756301
Puerto rican stew (sancocho)
7550311
Cucumber pickles, dill, reduced salt
Does not include vegetable with meat mixtures.
Protected Veg.
411-, 412-
7531502
Peas & corn, cooked, fat added
413-
Beans and lentils
7531510
Peas & onions, cooked, ns as to added fat
414-
Soy products
7531511
Peas & onions, cooked, fat not added
415-, 416-
Bean meals
7531512
Peas & onions, cooked, fat added
7185-,
7531521
Peas w/mushrooms, cooked, no fat added
7190-
Plantains soups etc.
7531525
Cowpeas w/snap beans, cooked, no fat added in
732-
Pumpkin
cooking
733-
Winter Squash
7531530
Peas & potatoes, cooked, no fat added in
7510200
Lima Beans, raw
cooking
7510550
Cactus, raw
75402-
Lima Beans with sauce
7510960
Corn, raw
75411-
Corn, scalloped, fritter, with cream
7512000
Peas, raw
7541650
Pea salad
7520070
Aloe vera juice
7541660
Pea salad with cheese
752040-
Lima Beans, cooked
75417-
Peas, with sauce or creamed
752041-
Lima Beans, canned
7550101
Corn relish
7520829
Bitter Melon
7560401
Corn soup, cream of, w/milk
752083-
Bitter Melon, cooked
7560402
Corn soup, cream of, prepared w/water
7520950
Burdock
7560900
Pea soup, nfs
752131-
Cactus
7560901
Pea soup, prep w/milk
752160-
Corn, cooked
7560802
Pea soup, prepared w/water
752161-
Corn, yellow, cooked
7560905
Pea soup, prepared w/water, low sodium
752162-
Corn, white, cooked
7560906
Pea soup, prepared w/lowfat milk
752163-
Corn, canned
76205-
Squash, yellow, baby
7521749
Hominy
76405-
Corn, baby
752175-
Hominy
76409-
Peas, baby
75223-
Peas, cowpeas, field or blackeye, cooked
76411-
Peas, creamed, baby
75224-
Peas, green, cooked
7650200
Peas and brown rice, baby
75225-
Peas, pigeon, cooked
7720121
Green plantain w/cracklings, p.r. (Mofongo)
75301-
Succotash
7720511
Ripe plantain fritters, p.r. (Pionono)
7531500
Peas & corn, cooked, ns as to added fat
7720561
Ripe plantainmeat pie, p.r. (Pinon)
7531501
Peas & corn, cooked, no fat added
Does not include vegetable with meat mixtures.
June 2000
3B-9
DRAFT-DO NOT QUOTE OR CITE
-------
TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
Food Product
Food Codes
Root Vegetables
710-, 711-, 712-, 713-, 714-, 715-, 716-, 717-,
7540501
Beets, harvard
7180-, 1793-, 7194-, 7195-, 7196-,
75415-
Onions, creamed, fried
7198-
White Potatoes and Puerto Rican St. Veg.
7541601
Parsnips, creamed
7310-
Carrots
7541810
Turnips, creamed
7311140
Carrots in sauce
7550021
Beets, pickled
7311200
Carrot chips
7550309
Horseradish
734-
Sweet potatoes
7551201
Radishes, pickled
7510250
Beets, raw
7553403
Turnip, pickled
7511150
Garlic, raw
7560110
Beet soup (borscht)
7511180
Jicama (yambean), raw
7560501
Leek soup, cream of, prep w/milk
7511250
Leeks, raw
7560503
Leek soup, made from dry mix
75117-
Onions, raw
7560801
Onion soup, cream of, prep w/milk
7512500
Radish, raw
7560803
Onion soup, cream of, canned, undiluted
7512700
Rutabaga, raw
7560810
Onion soup, french
7512900
Turnip, raw
7560820
Onion soup, made from dry mix
752080-
Beets, cooked
7560830
Onion soup, dry mix, not reconstituted
752081-
Beets, canned
76201-
Carrots, baby
7521362
Cassava
76209-
Sweet potatoes, baby
7521740
Garlic, cooked
76403-
Beets, baby
7521771
Horseradish
7642000
Potatoes, baby
7521840
Leek, cooked
7660200
Carrots & beef, baby, strained
7521850
Lotus root
7712101
Fried stuffed potatoes, p.r. (Rellenos de papas)
752210-
Onions, cooked
7712111
Potato & ham fritters, p.r. (frituras de papa y
7522110
Onions, dehydrated
jamon)
752220-
Parsnips, cooked
7714101
Potato chicken pie, p.r. (Pastelon de polio)
75227-
Radishes, cooked
7723021
Cassava pasteles, p.r. (Pasteles de yuca)
75228-
Rutabaga, cooked
7723051
Cassava pie stuffed w/crab meat, p.r.
75229-
Salsify, cooked
7725011
Stuffed tannier fritters, p.r. (Alcapurrias)
75234-
Turnip, cooked
7725071
Tannier fritters, p.r. (Frituras de yautia)
75235-
Water Chestnut
Does not include vegetable with meat mixtures.
FAT CATEGORIES
Animal Fat
81201-
Bacon grease
81202-
Lard
812032-
Shortening, animal
8133011
Lard
Butter
811005-
Butter
81101-
Butter
81105-
Butter
81204-
Clarified butter
8132200
Honey butter
Dressing
83100-
83202-
83101-
83203-
83102-
83205-
83103-
83206-
83104-
83207-
83105-
83208-
83106-
83209-
8311-
83210-
83200-
83220-
83201-
Margarine
81102-
81103-
81104-
81106-
Mayonnaise
83204-
83107-
83108-
Sauce
81301-
Lemon butter sauce
81302-
Sauces, various
81312-
Tartar sauce
June 2000
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TABLE 3B-1 FOOD CODES AND DEFINITIONS USED IN ANALYSIS OF THE 1994-96 USDA CSFII DATA (CONTINUED)
Food Product
Food Codes
Vegetable Oil
812031-
Shortening, vegetable
82104-
Olive oil
81324-
Lechithin
82105-
Peanut, rapeseed, & canola oil
8133021
Adobo fresco
82106-
Safflower oil
82101-
Vegetable oil
82107-
Sesame oil
82102-
Corn oil
82108-
Soy and sunflower oil
82103-
Cottonseed & flax seed oil
82109-
Wheat serm oil
June 2000
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1 APPENDIX 3C
2
3 SAMPLE CALCULATION OF MEAN DAILY FAT INTAKE BASED
4 ON CDC (1994) DATA
June 2000
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
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.
kcal g- fat g- fat
0.34 x 2,095 - x X = 82
day day day
g-fat
X = 0.12
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:
kcal g-fat g-fat
1,591 x 0.33 x 0.12 =63
day kcal day
June 2000
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1 APPENDIX 3D
2
3 FOOD CODES AND DEFINITIONS USED IN ANALYSIS
4 OF THE 1987-88 USDA NFCS DATA
5
June 2000
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APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA
Food
Product
Household Code/Definition
Individual Code
MAJOR FOOD GROUPS
Total Fruits
Total
Vegetables
Fresh Fruits
citrus
other vitamin-C rich
other fruits
Commercially Canned Fruits
Commercially Frozen Fruits
Canned Fruit Juice
Frozen Fruit Juice
Aseptically Packed Fruit Juice
Fresh Fruit Juice
Dried Fruits
50-
512-
522-
533-
534-
535-
536-
542-
(includes baby foods)
48- Potatoes, Sweetpotatoes
49- Fresh Vegetables
dark green
deep yellow
tomatoes
light green
other
511- Commercially Canned Vegetables
521- Commercially Frozen Vegetables
531- Canned Vegetable Juice
532- Frozen Vegetable Juice
537- Fresh Vegetable Juice
538- Aseptically Packed Vegetable Juice
541- Dried Vegetables
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners; includes baby foods except mixtures/dinners)
Total Meats 44- Meat
beef
pork
veal
lamb
mutton
goat
game
lunch meat
mixtures
451- Poultry
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners; includes baby foods except mixtures)
Total Dairy 40- Milk Equivalent
fresh fluid milk
processed milk
cream and cream substitutes
frozen desserts with milk
cheese
dairy-based dips
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners)
Total Fish 452- Fish, Shellfish
various species
fresh, frozen, commercial, dried
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners)
6- Fruits
citrus fruits and juices
dried fruits
other fruits
fruits/juices & nectar
fruit/juices baby food
(includes baby foods)
7- Vegetables (all forms)
white potatoes & PR starchy
dark green vegetables
deep yellow vegetables
tomatoes and torn, mixtures
other vegetables
veg. and mixtures/baby food
veg. with meat mixtures
(includes baby foods; mixtures, mostly vegetables)
20- Meat, type not specified
21- Beef
22- Pork
23- Lamb, veal, game, carcass meat
24- Poultry
25- Organ meats, sausages, lunchmeats, meat spreads
(excludes meat, poultry, and fish with non-meat items; frozen
plate meals; soups and gravies with meat, poultry and fish
base; and gelatin-based drinks; includes baby foods)
1- Milk and Milk Products
milk and milk drinks
cream and cream substitutes
milk desserts, sauces, and gravies
cheeses
(includes regular fluid milk, human milk, imitation milk
products, yogurt, milk-based meal replacements, and infant
formulas)
26- Fish, Shellfish
various species and forms
(excludes meat, poultry, and fish with non-meat items; frozen
plate meals; soups and gravies with meat, poultry and fish
base; and gelatin-based drinks)
June 2000
3D-1
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Food
Product
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Household Code/Definition
Individual Code
White
Potatoes
Peppers
Onions
INDIVIDUAL FOODS
4811
4821
4831
4841
4851
White Potatoes, fresh
White Potatoes, commercially canned
White Potatoes, commercially frozen
White Potatoes, dehydrated
White Potatoes, chips, sticks, salad
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners)
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)
4953- Onions, Garlic, fresh
onions
chives
garlic
leeks
5114908 Garlic Pulp, raw
5114915 Onions, commercially canned
5213722 Onions, commercially frozen
5213723 Onions with Sauce, commercially frozen
5413103 Chives, dried
5413105 Garlic Flakes, dried
5413110 Onion Flakes, dried
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners)
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)
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)
7510950 Chives, raw
7511150 Garlic, raw
7511250 Leek, raw
7511701 Onions, young green, raw
7511702 Onions, mature
7521550 Chives, dried
7521740 Garlic, cooked
7522100 Onions, mature cooked, NS as to fat added
7522101 Onions, mature cooked, fat not added
7522102 Onions, mature cooked, fat added
7522103 Onions, pearl cooked
7522104 Onions, young green cooked, NS as to fat
7522105 Onions, young green cooked, fat not added
7522106 Onions, young green cooked, fat added
7522110 Onion, dehydrated
7541501 Onions, creamed
7541502 Onion rings
Corn
4956- Corn, fresh 7510960 Corn, raw
5114601 Yellow Corn, commercially canned 7521600 Corn, cooked,
5114602 White Corn, commercially canned 7521601 Corn, cooked,
5114603 Yellow Creamed Corn, commercially canned 7521602 Corn, cooked,
5114604 White Creamed Corn, commercially canned 7521605 Corn, cooked,
5114605 Corn on Cob, commercially canned 7521607 Corn, cooked,
5114607 Hominy, canned 7521610 Corn, cooked,
5115306 Low Sodium Corn, commercially canned 7521611 Corn, cooked,
5115307 Low Sodium Cr. Corn, commercially canned 7521612 Corn, cooked,
5213501 Yellow Corn on Cob, commercially frozen 7521615 Corn, yellow,
5213502 Yellow Corn off Cob, commercially frozen 7521616 Corn, cooked,
5213503 Yell. Corn with Sauce, commercially frozen 7521617 Corn, cooked,
5213504 Corn with other Veg., commercially frozen 7521618 Corn, cooked,
5213505 White Corn on Cob, commercially frozen 7521619 Corn, yellow,
5213506 White Corn off Cob, commercially frozen 7521620 Corn, cooked,
NS as to color/fat added
NS as to color/fat not added
NS as to color/fat added
NS as to color/cream style
dried
yellow/NS as to fat added
yellow/fat not added
yellow/fat added
cream style
yell. & wh./NS as to fat
yell. & wh./fat not added
yell. & wh./fat added
cream style, fat added
white/NS as to fat added
June 2000
3D-2
DRAFT-DO NOT QUOTE OR CITE
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APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Corn (cont.)
Apples
Tomatoes
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)
Apples, fresh
Applesauce with sugar, commercially canned
Applesauce without sugar, comm. canned
Apple Pie Filling, commercially canned
Apples, Applesauce, baby/jr., comm. canned
Apple Pie Filling, Low Cal., comm. canned
Apple Slices, commercially frozen
Apple Juice, canned
Apple Juice, baby, Comm. canned
Apple Juice, comm. frozen
Apple Juice, home frozen
Apple Juice, aseptically packed
Apple Juice, fresh
Apples, dried
5031-
5122101
5122102
5122103
5122104
5122106
5223101
5332101
5332102
5342201
5342202
5352101
5362101
5423101
(includes baby food; except mixtures)
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)
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)
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)
74- Tomatoes and Tomato Mixtures
raw, cooked, juices, sauces, mixtures, soups,
sandwiches
June 2000
3D-3
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APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Snap Beans
Beef
Pork
Game
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)
441-Beef
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners; includes baby foods except mixtures)
442- Pork
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners; includes baby foods except mixtures)
445- Variety Meat, Game
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners; includes baby foods except mixtures)
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)
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)
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)
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)
June 2000
3D-4
DRAFT-DO NOT QUOTE OR CITE
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APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Poultry
Broccoli
Carrots
Pumpkin
Asparagus
Lima Beans
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)
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)
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)
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)
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)
4941- Fresh Asparagus (and home canned/froz.)
5114101 Comm. Canned Asparagus
5115301 Asparagus, Low Sodium, Comm. Canned
5 2131 - Comm. Frozen Asparagus
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners; includes baby foods except mixtures)
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)
egg mixtures
egg substitutes
eggs baby food
froz. meals with egg as main ingred.
(includes baby foods)
722- Broccoli (all forms)
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat 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)
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)
7510080 Asparagus, raw
75202- Asparagus, cooked
7540101 Asparagus, creamed or with cheese
(does not include vegetable soups; vegetables mixtures, or
vegetable with meat mixtures)
7510200 Lima Beans, raw
752040- Lima Beans, cooked
752041- ima Beans, canned
75402- Lima Beans with sauce
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures; does not include succotash)
June 2000
3D-5
DRAFT-DO NOT QUOTE OR CITE
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APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product Household Code/Definition Individual Code
Cabbage
4944- Fresh Cabbage (and home canned/froz.)
7510300 Cabbage, raw
4958601 Sauerkraut, home canned or pkgd
7510400 Cabbage, Chinese, raw
5114801 Sauerkraut, comm. canned
7510500 Cabbage, red, raw
5114904 Comm. Canned Cabbage
7514100 Cabbage salad or coleslaw
5114905 Comm. Canned Cabbage (no sauce; incl. baby)
7514130 Cabbage, Chinese, salad
5115501 Sauerkraut, low sodium., comm. canned
75210- Chinese Cabbage, cooked
5312102 Sauerkraut Juice, comm. canned
75211- Green Cabbage, cooked
(does not include soups, sauces, gravies, mixtures, and ready-to-
75212- Red Cabbage, cooked
eat dinners; includes baby foods except mixtures)
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
75113- Lettuce, raw
canned/froz.)
75143- Lettuce salad with other veg.
(does not include soups, sauces, gravies, mixtures, and ready-to-
7514410 Lettuce, wilted, with bacon dressing
eat dinners; includes baby foods except mixtures)
7522005 Lettuce, cooked
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Okra
4946- Fresh Okra (and home canned/froz.)
7522000 Okra, cooked, NS as to fat
5114914 Comm. Canned Okra
7522001 Okra, cooked, fat not added
5213720 Comm. Frozen Okra
7522002 Okra, cooked, fat added
5213721 Comm. Frozen Okra with Oth. Veg. & Sauce
7522010 Lufita, cooked (Chinese Okra)
(does not include soups, sauces, gravies, mixtures, and ready-to-
7541450 Okra, fried
eat dinners; includes baby foods except mixtures)
7550700 Okra, pickled
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Peas
4947- Fresh Peas (and home canned/froz.)
7512000 Peas, green, raw
51147- Comm Canned Peas (incl. baby)
7512775 Snowpeas, raw
5115310 Low Sodium Green or English Peas (canned)
75223- Peas, cowpeas, field or blackeye, cooked
5115314 Low Sod. Blackeye, Gr. orlmm. Peas (canned)
75224- Peas, green, cooked
5114205 Blackeyed Peas, comm. canned
75225- Peas, pigeon, cooked
52134- Comm. Frozen Peas
75231- Snowpeas, cooked
5412- Dried Peas and Lentils
7541650 Pea salad
(does not include soups, sauces, gravies, mixtures, and ready-to-
7541660 Pea salad with cheese
eat dinners; includes baby foods except mixtures)
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.)
7511100 Cucumbers, raw
(does not include soups, sauces, gravies, mixtures, and ready-to-
75142- Cucumber salads
eat dinners; includes baby foods except mixtures)
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)
June 2000
3D-6
DRAFT-DO NOT QUOTE OR CITE
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APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Beets 4954- Fresh Beets (and home canned/froz.)
51145- Comm. Canned Beets (incl. baby)
5115305 Low Sodium Beets (canned)
5213714 Comm. Frozen Beets
5312104 BeetJuice
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners; includes baby foods except mixtures)
Strawberries 5022- Fresh Strawberries
5122801 Comm. Canned Strawberries with sugar
5122802 Comm. Canned Strawberries without sugar
5122803 Canned Strawberry Pie Filling
5222- Comm. Frozen Strawberries
(does not include ready-to-eat dinners; includes baby foods
except mixtures)
Other Berries 5033- Fresh Berries Other than Strawberries
5122804 Comm. Canned Blackberries with sugar
5122805 Comm. Canned Blackberries without sugar
5122806 Comm. Canned Blueberries with sugar
5122807 Comm. Canned Blueberries without sugar
5122808 Canned Blueberry Pie Filling
5122809 Comm. Canned Gooseberries with sugar
5122810 Comm. Canned Gooseberries without sugar
5122811 Comm. Canned Raspberries with sugar
5122812 Comm. Canned Raspberries without sugar
5122813 Comm. Canned Cranberry Sauce
5122815 Comm. Canned Cranberry-Orange Relish
52233- Comm. Frozen Berries (not strawberries)
5332404 Blackberry Juice (home and comm. canned)
5423114 Dried Berries (not strawberries)
(does not include ready-to-eat dinners; includes baby foods
except mixtures)
Peaches 5036- Fresh Peaches
51224- Comm. Canned Peaches (incl. baby)
5223601 Comm. Frozen Peaches
5332405 Home Canned Peach Juice
5423105 Dried Peaches (baby)
5423106 Dried Peaches
(does not include ready-to-eat dinners; includes baby foods
except mixtures)
Pears 5037- Fresh Pears
51225- Comm. Canned Pears (incl. baby)
5332403 Comm. Canned Pear Juice, baby
5362204 Fresh Pear Juice
5423107 Dried Pears
(does not include ready-to-eat dinners; includes baby foods
except mixtures)
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)
6322- Strawberries
6413250 Strawberry Juice
(includes baby food; except mixtures)
6320-
6321-
6341101
6410460
64105-
Other Berries
Other Berries
Cranberry salad
Blackberry Juice
Cranberry Juice
(includes baby food; except mixtures)
62116-
63135-
6412203
6420501
67108-
6711450
Dried Peaches
Peaches
Peach Juice
Peach Nectar
Peaches,baby
Peaches, dry, baby
(includes baby food; except mixtures)
62119-
63137-
6341201
6421501
67109-
6711455
Dried Pears
Pears
Pear salad
Pear Nectar
Pears, baby
Pears, dry, baby
(includes baby food; except mixtures)
EXPOSED/PROTECTED FRUITS/VEGETABLES, ROOT VEGETABLES
Exposed
5022-
Strawberries, fresh
62101-
Apple, dried
Fruits
5023101
Acerola, fresh
62104-
Apricot, dried
5023401
Currants, fresh
62108-
Currants, dried
5031-
Apples/Applesauce, fresh
62110-
Date, dried
5033-
Berries other than Strawberries, fresh
62116-
Peaches, dried
5034-
Cherries, fresh
62119-
Pears, dried
5036-
Peaches, fresh
62121-
Plum, dried
June 2000
3D-7
DRAFT-DO NOT QUOTE OR CITE
-------
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Exposed
5037-
Pears, fresh
62122-
Prune, dried
Fruits
50381-
Apricots, Nectarines, Loquats, fresh
62125-
Raisins
(cont.)
5038305
Dates, fresh
63101-
Apple s/app le sauc e
50384-
Grapes, fresh
63102-
Wi-apple
50386-
Plums, fresh
63103-
Apricots
50387-
Rhubarb, fresh
63111-
Cherries, maraschino
5038805
Persimmons, fresh
63112-
Acerola
5038901
Sapote, fresh
63113-
Cherries, sour
51221-
Apples/Applesauce, canned
63115-
Cherries, sweet
51222-
Apricots, canned
63117-
Currants, raw
51223-
Cherries, canned
63123-
Grapes
51224-
Peaches, canned
6312601
Juneberry
51225-
Pears, canned
63131-
Nectarine
51228-
Berries, canned
63135-
Peach
5122903
Grapes with sugar, canned
63137-
Pear
5122904
Grapes without sugar, canned
63139-
Persimmons
5122905
Plums with sugar, canned
63143-
Plum
5122906
Plums without sugar, canned
63146-
Quince
5122907
Plums, canned, baby
63147-
Rhubarb/Sapodillo
5122911
Prunes, canned, baby
632- Berries
5122912
Prunes, with sugar, canned
64101-
Apple Cider
5122913
Prunes, without sugar, canned
64104-
Apple Juice
5122914
Raisin Pie Filling
64105-
Cranberry Juice
5222-
Frozen Strawberries
64116-
Grape Juice
52231-
Apples Slices, frozen
64122-
Peach Juice
52233-
Berries, frozen
64132-
Prune/Strawberry Juice
52234-
Cherries, frozen
6420101
Apricot Nectar
52236-
Peaches, frozen
64205-
Peach Nectar
52239-
Rhubarb, frozen
64215-
Pear Nectar
53321-
Canned Apple Juice
67102-
Applesauce, baby
53322-
Canned Grape Juice
67108-
Peaches, baby
5332402
Canned Prune Juice
67109-
Pears, baby
5332403
Canned Pear Juice
6711450
Peaches, baby, dry
5332404
Canned Blackberry Juice
6711455
Pears, baby, dry
5332405
Canned Peach Juice
67202-
Apple Juice, baby
53421-
Frozen Grape Juice
6720380
White Grape Juice, baby
5342201
Frozen Apple Juice, comm. fr.
67212-
Pear Juice, baby
5342202
Frozen Apple Juice, home fr.
(includes baby foods/juices except mixtures; excludes
5352101
Apple Juice, asep. packed
fruit mixtures)
5352201
Grape Juice, asep. packed
5362101
Apple Juice, fresh
5362202
Apricot Juice, fresh
5362203
Grape Juice, fresh
5362204
Pear Juice, fresh
5362205
Prune Juice, fresh
5421-
Dried Prunes
5422-
Raisins, Currants, dried
5423101
Dry Apples
5423102
Dry Apricots
5423103
Dates without pits
5423104
Dates with pits
5423105
Peaches, dry, baby
5423106
Peaches, dry
5423107
Pears, dry
5423114
Berries, dry
5423115
Cherries, dry
(includes baby foods)
Protected
501- Citrus Fruits, fresh
61- Citrus Fr., Juices (incl. cit. juice mixtures)
Fruits
5021-
Cantaloupe, fresh
62107-
Bananas, dried
5023201
Mangoes, fresh
62113-
Figs, dried
5023301
Guava, fresh
62114-
Lychees/Papayas, dried
June 2000
3D-8
DRAFT-DO NOT QUOTE OR CITE
-------
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Protected
5023601
Kiwi, fresh
62120-
Pineapple, dried
Fruits
5023701
Papayas, fresh
62126-
Tamarind, dried
(cont.)
5023801
Passion Fruit, fresh
63105-
Avocado, raw
5032-
Bananas, Plantains, fresh
63107-
Bananas
5035-
Melons other than Cantaloupe, fresh
63109-
Cantaloupe, Carambola
50382-
Avocados, fresh
63110-
Cassaba Melon
5038301
Figs, fresh
63119-
Figs
5038302
Figs, cooked
63121-
Genip
5038303
Figs, home canned
63125-
Guava/Jackfruit, raw
5038304
Figs, home frozen
6312650
Kiwi
50385-
Pineapple, fresh
6312651
Lychee, raw
5038801
Pomegranates, fresh
6312660
Lychee, cooked
5038902
Cherimoya, fresh
63127-
Honeydew
5038903
Jackfruit, fresh
63129-
Mango
5038904
Breadfruit, fresh
63133-
Papaya
5038905
Tamarind, fresh
63134-
Passion Fruit
5038906
Carambola, fresh
63141-
Pineapple
5038907
Longan, fresh
63145-
Pomegranate
5121-
Citrus, canned
63148-
Sweetsop, Soursop, Tamarind
51226-
Pineapple, canned
63149-
Watermelon
5122901
Figs with sugar, canned
64120-
Papaya Juice
5122902
Figs without sugar, canned
64121-
Passion Fruit Juice
5122909
Bananas, canned, baby
64124-
Pineapple Juice
5122910
Bananas and Pineapple, canned, baby
64133-
Watermelon Juice
5122915
Litchis, canned
6420150 Banana Nectar
5122916
Mangos with sugar, canned
64202-
Cantaloupe Nectar
5122917
Mangos without sugar, canned
64203-
Guava Nectar
5122918
Mangos, canned, baby
64204-
Mango Nectar
5122920
Guava with sugar, canned
64210-
Papaya Nectar
5122921
Guava without sugar, canned
64213-
Passion Fruit Nectar
5122923
Papaya with sugar, canned
64221-
Soursop Nectar
5122924
Papaya without sugar, canned
6710503
Bananas, baby
52232-
Bananas, frozen
6711500
Bananas, baby, dry
52235-
Melon, frozen
6720500
Orange Juice, baby
52237-
Pineapple, frozen
6721300
Pineapple Juice, baby
5331-
Canned Citrus Juices
(includes baby foods/juices except mixtures; excludes fruit
53323-
Canned Pineapple Juice
mixtures)
5332408
Canned Papaya Juice
5332410
Canned Mango Juice
5332501
Canned Papaya Concentrate
5341-
Frozen Citrus Juice
5342203
Frozen Pineapple Juice
5351-
Citrus and Citrus Blend Juices, asep. packed
5352302
Pineapple Juice, asep. packed
5361-
Fresh Citrus and Citrus Blend Juices
5362206
Papaya Juice, fresh
5362207
Pineapple-Coconut Juice, fresh
5362208
Mango Juice, fresh
5362209
Pineapple Juice, fresh
5423108
Pineapple, dry
5423109
Papaya, dry
5423110
Bananas, dry
5423111
Mangos, dry
5423117
Litchis, dry
5423118
Tamarind, dry
5423119
Plantain, dry
(includes baby foods)
Exposed
491- Fresh Dark Green Vegetables
721- Dark Green Leafy Veg.
Vegetable
493- Fresh Tomatoes
722- Dark Green Nonleafy Veg.
4941-
Fresh Asparagus
74- Tomatoes and Tomato Mixtures
4943-
Fresh Beans, Snap or Wax
7510050
Alfalfa Sprouts
June 2000
3D-9
DRAFT-DO NOT QUOTE OR CITE
-------
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Exposed
4944- Fresh Cabbage
7510075
Artichoke, Jerusalem, raw
Vegetable
4945- Fresh Lettuce
7510080
Asparagus, raw
(cont.)
4946- Fresh Okra
75101-
Beans, sprouts and green, raw
49481-
Fresh Artichokes
7510275
Brussel Sprouts, raw
49483-
Fresh Brussel Sprouts
7510280
Buckwheat Sprouts, raw
4951- Fresh Celery
7510300
Cabbage, raw
4952- Fresh Cucumbers
7510400
Cabbage, Chinese, raw
4955- Fresh Cauliflower
7510500
Cabbage, Red, raw
4958103
Fresh Kohlrabi
7510700
Cauliflower, raw
4958111
Fresh Jerusalem Artichokes
7510900
Celery, raw
4958112
Fresh Mushrooms
7510950
Chives, raw
4958113
Mushrooms, home canned
7511100
Cucumber, raw
4958114
Mushrooms, home frozen
7511120
Eggplant, raw
4958118
Fresh Eggplant
7511200
Kohlrabi, raw
4958119
Eggplant, cooked
75113-
Lettuce, raw
4958120
Eggplant, home frozen
7511500
Mushrooms, raw
4958200
Fresh Summer Squash
7511900
Parsley
4958201
Summer Squash, cooked
7512100
Pepper, hot chili
4958202
Summer Squash, home canned
75122-
Peppers, raw
4958203
Summer Squash, home frozen
7512750
Seaweed, raw
4958402
Fresh Bean Sprouts
7512775
Snowpeas, raw
4958403
Fresh Alfalfa Sprouts
75128-
Summer Squash, raw
4958504
Bamboo Shoots
7513210
Celery Juice
4958506
Seaweed
7514100
Cabbage or cole slaw
4958508
Tree Fern, fresh
7514130
Chinese Cabbage Salad
4958601
Sauerkraut
7514150
Celery with cheese
5111- Dark Green Vegetables (all are exposed)
75142-
Cucumber salads
5113- Tomatoes
75143-
Lettuce salads
5114101
Asparagus, comm. canned
7514410
Lettuce, wilted with bacon dressing
51144-
Beans, green, snap, yellow, comm. canned
7514600
Greek salad
5114704
Snow Peas, comm. canned
7514700
Spinach salad
5114801
Sauerkraut, comm. canned
7520600
Algae, dried
5114901
Artichokes, comm. canned
75201-
Artichoke, cooked
5114902
Bamboo Shoots, comm. canned
75202-
Asparagus, cooked
5114903
Bean Sprouts, comm. canned
75203-
Bamboo shoots, cooked
5114904
Cabbage, comm. canned
752049-
Beans, string, cooked
5114905
Cabbage, comm. canned, no sauce
75205-
Beans, green, cooked/canned
5114906
Cauliflower, comm. canned, no sauce
75206-
Beans, yellow, cooked/canned
5114907
Eggplant, comm. canned, no sauce
75207-
Bean Sprouts, cooked
5114913
Mushrooms, comm. canned
752085-
Breadfruit
5114914
Okra, comm. canned
752090-
Brussel Sprouts, cooked
5114918
Seaweeds, comm. canned
75210-
Cabbage, Chinese, cooked
5114920
Summer Squash, comm. canned
75211-
Cabbage, green, cooked
5114923
Chinese or Celery Cabbage, comm. canned
75212-
Cabbage, red, cooked
51152-
Tomatoes, canned, low sod.
752130-
Cabbage, savoy, cooked
5115301
Asparagus, canned, low sod.
75214-
Cauliflower
5115302
Beans, Green, canned, low sod.
75215-
Celery, Chives, Christophine (chayote)
5115303
Beans, Yellow, canned, low sod.
752167-
Cucumber, cooked
5115309
Mushrooms, canned, low sod.
752170-
Eggplant, cooked
51154-
Greens, canned, low sod.
752171-
Fern shoots
5115501
Sauerkraut, low sodium
752172-
Fern shoots
5211- Dark Gr. Veg., comm. frozen (all exp.)
752173-
Flowers of sesbania, squash or lily
52131-
Asparagus, comm. froz.
7521801
Kohlrabi, cooked
52133-
Beans, snap, green, yellow, comm. froz.
75219-
Mushrooms, cooked
5213407
Peapods, comm froz.
75220-
Okra/lettuce, cooked
5213408
Peapods, with sauce, comm froz.
7522116
Palm Hearts, cooked
5213409
Peapods, with other veg., comm froz.
7522121
Parsley, cooked
5213701
Brussel Sprouts, comm. froz.
75226-
Peppers, pimento, cooked
5213702
Brussel Sprouts, comm. froz. with cheese
75230-
Sauerkraut, cooked/canned
5213703
Brussel Sprouts, comm. froz. with other veg.
75231-
Snowpeas, cooked
5213705
Cauliflower, comm. froz.
75232-
Seaweed
June 2000
3D-10
DRAFT-DO NOT QUOTE OR CITE
-------
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Exposed
5213706
Cauliflower, comm. froz. with sauce
75233-
Summer Squash
Vegetable
5213707
Cauliflower, comm. froz. with other veg.
7540050
Artichokes, stuffed
(cont.)
5213708
Caul., comm. froz. with other veg. & sauce
7540101
Asparagus, creamed or with cheese
5213709
Summer Squash, comm. froz.
75403-
Beans, green with sauce
5213710
Summer Squash, comm. froz. with other veg.
75404-
Beans, yellow with sauce
5213716
Eggplant, comm. froz.
7540601
Brussel Sprouts, creamed
5213718
Mushrooms with sauce, comm. froz.
7540701
Cabbage, creamed
5213719
Mushrooms, comm. froz.
75409-
Cauliflower, creamed
5213720
Okra, comm. froz.
75410-
Celery/Chiles, creamed
5213721
Okra, comm. froz., with sauce
75412-
Eggplant, fried, with sauce, etc.
5311-
Canned Tomato Juice and Tomato Mixtures
75413-
Kohlrabi, creamed
5312102
Canned Sauerkraut Juice
75414-
Mushrooms, Okra, fried, stuffed, creamed
5321-
Frozen Tomato Juice
754180-
Squash, baked, fried, creamed, etc.
5371-
Fresh Tomato Juice
7541822
Christophine, creamed
5381102
Aseptically Packed Tomato Juice
7550011
Beans, pickled
5413101
Dry Algae
7550051
Celery, pickled
5413102
Dry Celery
7550201
Cauliflower, pickled
5413103
Dry Chives
755025-
Cabbage, pickled
5413109
Dry Mushrooms
7550301
Cucumber pickles, dill
5413111
Dry Parsley
7550302
Cucumber pickles, relish
5413112
Dry Green Peppers
7550303
Cucumber pickles, sour
5413113
Dry Red Peppers
7550304
Cucumber pickles, sweet
5413114
Dry Seaweed
7550305
Cucumber pickles, fresh
5413115
Dry Tomatoes
7550307
Cucumber, Kim Chee
(does not include soups, sauces, gravies, mixtures, and ready-to-
7550308
Eggplant, pickled
eat dinners; includes baby foods except mixtures)
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)
Protected
4922-
Fresh Pumpkin, Winter Squash
732-
Pumpkin
Vegetable
4942-
Fresh Lima Beans
733-
Winter Squash
4947-
Fresh Peas
7510200
Lima Beans, raw
49482-
Fresh Soy Beans
7510550
Cactus, raw
4956-
Fresh Corn
7510960
Corn, raw
4958303
Succotash, home canned
7512000
Peas, raw
4958304
Succotash, home frozen
7520070
Aloe vera juice
4958401
Fresh Cactus (prickly pear)
752040-
Lima Beans, cooked
4958503
Burdock
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)
7520950 Burdock
51142-
Beans, comm. canned
752131-
Cactus
51143-
Beans, lima and soy, comm. canned
752160-
Corn, cooked
51146-
Corn, comm. canned
752161-
Corn, yellow, cooked
5114701
Peas, green, comm. canned
752162-
Corn, white, cooked
5114702
Peas, baby, comm. canned
752163-
Corn, canned
5114703
Peas, blackeye, comm. canned
7521749
Hominy
5114705
Pigeon Peas, comm. canned
752175-
Hominy
5114919
Succotash, comm. canned
75223-
Peas, cowpeas, field or blackeye, cooked
5115304
Lima Beans, canned, low sod.
75224-
Peas, green, cooked
5115306
Corn, canned, low sod.
75225-
Peas, pigeon, cooked
5115307
Creamed Corn, canned, low sod.
75301-
Succotash
511531-
Peas and Beans, canned, low sod.
75402-
Lima Beans with sauce
June 2000
3D-11
DRAFT-DO NOT QUOTE OR CITE
-------
APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Protected
52122-
Winter Squash, comm. froz.
75411-
Corn, scalloped, fritter, with cream
Vegetable
52132-
Lima Beans, comm. froz.
7541650
Pea salad
(cont.)
5213401
Peas, gr., comm. froz.
7541660
Pea salad with cheese
5213402
Peas, gr., with sauce, comm. froz.
75417-
Peas, with sauce or creamed
5213403
Peas, gr., with other veg., comm. froz.
7550101
Corn relish
5213404
Peas, gr., with other veg., comm. froz.
76205-
Squash, yellow, baby
5213405
Peas, blackeye, comm froz.
76405-
Corn, baby
5213406
Peas, blackeye, with sauce, comm froz.
76409-
Peas, baby
52135-
Corn, comm. froz.
76411-
Peas, creamed, baby
5213712
Artichoke Hearts, comm. froz.
(does not include vegetable soups; vegetable mixtures; or
5213713
Baked Beans, comm. froz.
vegetable with meat mixtures)
5213717
Kidney Beans, comm. froz.
5213724
Succotash, comm. froz.
5411-
Dried Beans
5412-
Dried Peas and Lentils
5413104
Dry Corn
5413106
Dry Hominy
5413504
Dry Squash, baby
5413603
Dry Creamed Corn, baby
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners; includes baby foods except mixtures)
Rooted
48-
Potatoes, Sweetpotatoes
71-
White Potatoes and Puerto Rican St. Veg.
Vegetable
4921-
Fresh Carrots
7310-
Carrots
4953-
Fresh Onions, Garlic
7311140
Carrots in sauce
4954-
Fresh Beets
7311200
Carrot chips
4957-
Fresh Turnips
734-
Sweetpotatoes
4958101
Fresh Celeriac
7510250
Beets, raw
4958102
Fresh Horseradish
7511150
Garlic, raw
4958104
Fresh Radishes, no greens
7511180
Jicama (yambean), raw
4958105
Radishes, home canned
7511250
Leeks, raw
4958106
Radishes, home frozen
75117-
Onions, raw
4958107
Fresh Radishes, with greens
7512500
Radish, raw
4958108
Fresh Salsify
7512700
Rutabaga, raw
4958109
Fresh Rutabagas
7512900
Turnip, raw
4958110
Rutabagas, home frozen
752080-
Beets, cooked
4958115
Fresh Parsnips
752081-
Beets, canned
4958116
Parsnips, home canned
7521362
Cassava
4958117
Parsnips, home frozen
7521740
Garlic, cooked
4958502
Fresh Lotus Root
7521771
Horseradish
4958509
Ginger Root
7521850
Lotus root
4958510
Jicama, including yambean
752210-
Onions, cooked
51121-
Carrots, comm. canned
7522110
Onions, dehydrated
51145-
Beets, comm. canned
752220-
Parsnips, cooked
5114908
Garlic Pulp, comm. canned
75227-
Radishes, cooked
5114910
Horseradish, comm. prep.
75228-
Rutabaga, cooked
5114915
Onions, comm. canned
75229-
Salsify, cooked
5114916
Rutabagas, comm. canned
75234-
Turnip, cooked
5114917
Salsify, comm. canned
75235-
Water Chestnut
5114921
Turnips, comm. canned
7540501
Beets, harvard
5114922
Water Chestnuts, comm. canned
75415-
Onions, creamed, fried
51151-
Carrots, canned, low sod.
7541601
Parsnips, creamed
5115305
Beets, canned, low sod.
7541810
Turnips, creamed
5115502
Turnips, low sod.
7550021
Beets, pickled
52121-
Carrots, comm. froz.
7550309
Horseradish
5213714
Beets, comm. froz.
7551201
Radishes, pickled
5213722
Onions, comm. froz.
7553403
Turnip, pickled
5213723
Onions, comm. froz., with sauce
76201-
Carrots, baby
5213725
Turnips, comm. froz.
76209-
Sweetpotatoes, baby
5312103
Canned Carrot Juice
76403-
Beets, baby
5312104
Canned Beet Juice
(does not include vegetable soups; vegetable mixtures; or
5372102
Fresh Carrot Juice
vegetable with meat mixtures)
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APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Root
5413105 Dry Garlic
Vegetables
5413110 Dry Onion
(cont.)
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)
USDA SUBCATEGORIES
Dark Green
491 - Fresh Dark Green Vegetables
72-
Dark Green Vegetables
Vegetables
5111- Comm. Canned Dark Green Veg.
all forms
51154- Low Sodium Dark Green Veg.
leafy, nonleafy, dk. gr. veg. soups
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)
Deep Yellow
492- Fresh Deep Yellow Vegetables
73-
Deep Yellow Vegetables
Vegetables
5112- Comm. Canned Deep Yellow Veg.
all forms
51151 - Low Sodium Carrots
carrots, pumpkin, squash, sweetpotatoes, dp. yell.
5212- Comm. Frozen Deep Yellow Veg.
veg. soups
5312103 Carrot Juice
54135- Dry Carrots, Squash, Sw. Potatoes
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners; includes baby foods except mixtures/dinners;
excludes vegetable juices and dried vegetables)
Other
494- Fresh Light Green Vegetables
75-
Other Vegetables
Vegetables
495- Fresh Other Vegetables
all forms
5114- Comm. Canned Other Veg.
51153- Low Sodium Other Veg.
51155- Low Sodium Other Veg.
5 213 - Comm. Frozen Other Veg.
5312102- Sauerkraut Juice
5312104- BeetJuice
5411- Dried Beans
5412- Dried Peas, Lentils
541310- Dried Other Veg.
5413114- Dry Seaweed
5413603- Dry Cr. Corn, baby
(does not include soups, sauces, gravies, mixtures, and ready-to-
eat dinners; includes baby foods except mixtures/dinners;
excludes vegetable juices and dried vegetables)
Citrus Fruits
501- Fresh Citrus Fruits
61-
Citrus Fruits and Juices
5121 Comm. Canned Citrus Fruits
6720500
Orange Juice, baby food
5331 Canned Citrus and Citrus Blend Juice
6720600
Orange-Apricot Juice, baby food
5341 Frozen Citrus and Citrus Blend Juice
6720700
Orange-Pineapple Juice, baby food
5351 Aseptically Packed Citrus and Citr. Blend Juice
672110
Orange-Apple-Banana Juice, baby food
5361 Fresh Citrus and Citrus Blend Juice
(excludes dried fruits)
(includes baby foods; excludes dried fruits)
Other
62- Fresh Other Vitamin C-Rich Fruits
5353-
Dried Fruits
Fruits
503- Fresh Other Fruits
63
Other Fruits
5122- Comm. Canned Fruits Other than Citrus
64
Fruit Juices and Nectars Excluding Citrus
5222- Frozen Strawberries
671
Fruits, baby
5332- Frozen Other than Citr. or Vitamin C-Rich Fr.
67202
Apple Juice, baby
5333- Canned Fruit Juice Other than Citrus
67203
Baby Juices
5352- Frozen Juices Other than Citrus
67204
Baby Juices
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1 APPENDIX 3D. FOOD CODES AND DEFINITIONS USED IN ANALYSIS
2 OF THE 1987-88 USDA NFCS DATA (cont'd)
Food
Product
Household Code/Definition
Individual Code
Other Fruits
5362- Aseptically Packed Fruit Juice Other than Citr.
67212
Baby Juices
(cont.)
542- Fresh Fruit Juice Other than Citrus Dry Fruits
67213
Baby Juices
(includes baby foods; excludes dried fruits)
673
Baby Fruits
674
Rahv Fruits
7
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4. DRINKING WATER INTAKE 4-1
4.1 INTRODUCTION 4-1
4.2 DRINKING WATER INTAKE STUDIES 4-2
4.3. PREGNANT AND LACTATING WOMEN 4-7
4.4 RECOMMENDATIONS 4-8
4.5 REFERENCES FOR CHAPTER 4 4-9
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Table 4-1. Estimated Direct and Indirect Community Total Water Ingestion By Source for U.S.
Population 4-10
Table 4-2. Estimate of Total Direct and Indirect Water Ingestion, All Sources By Broad Age
Category for U.S. Children 4-11
Table 4-3. Estimate of Direct and Indirect Community Water Ingestion By Fine Age Category
for U.S. Children 4-12
Table 4-4. Estimate of Direct and Indirect Community Water Ingestion By Broad Age Category
for U.S. Children 4-13
Table 4-5. Estimate of Direct and Indirect Bottled Water Ingestion By Fine Age Category for
U.S. Children 4-14
Table 4-6. Estimate of Direct and Indirect Bottled Water Ingestion By Broad Age Category for
U.S. Children 4-15
Table 4-7. Estimate of Direct and Indirect Other Water Ingestion By Fine Age Category for U.S.
Children 4-16
Table 4-8. Estimate of Direct and Indirect Other Water Ingestion By Broad Age Category for
U.S. Children 4-17
Table 4-9. Chi-square GOF statistics for 12 Models, Tapwater Data, Based on Maximum
Likelihood Method of Parameter Estimation 4-18
Table 4-10. P-Values for Chi-Square GOF Tests of 12 Models, Tapwater Data 4-18
Table 4-11. Results of Statistical Modeling of Tapwater Data (intake Rates in dL/kg-day) Using
5-Parameter Generalized F and 2-Parameter Gamma, Lognormal and Weibull
Modles 4-19
Table 4-12. Total Fluid Intake of Women 15-49 Years Old 4-20
Table 4-13. Total Tapwater Intake of Women 15-49 Years Old 4-20
Table 4-14. Total Fluid (mL/Day) Derived from Various Dietary Sources by Women Aged
15-49 Years3 4-21
Table 4-15. Summary of Recommended Community Drinking Water Intake Rates 4-22
Table 4-16. Confidence in Tapwater Intake Recommendations 4-23
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4. DRINKING WATER INTAKE
4.1 INTRODUCTION
Drinking water is a potential source of human exposure to toxic substances among
children. 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 4.2) among
children and to provide recommendations of consumption rate values that should be used in
exposure assessments (Section 4.3).
Currently, the U.S. EPA uses the quantity 1 L per day for infants (individuals of 10 kg
body mass or less) and children as a default drinking water intake rates (U.S. EPA, 1980; 1991).
This rate includes drinking water consumed in the form of juices and other beverages containing
tapwater. The National Academy of Sciences (NAS, 1977) estimated that daily consumption of
water may vary with levels of physical activity and fluctuations in temperature and humidity. It is
reasonable to assume that children engaging in physically-demanding activities or living in warmer
regions may have higher levels of water intake.
Two studies cited in this chapter have generated data on drinking water intake rates. In
general, these sources support EPA's use of 1 L/day as an upper-percentile tapwater intake rate
for children under 10 years of age. The studies have reported intake rates for direct and indirect
ingestion of water. Direct intake is defined as direct consumption of water as a beverage, while
indirect intake includes water added during food preparation, but not water intrinsic to purchased
foods. Data for consumption of various sources (i.e., the community water supply, bottled water,
and other sources) are also presented. For the purposes of exposure assessments involving site-
specific contaminated drinking water, intake rates based on the community supply are most
appropriate. Given the assumption that bottled water, and other purchased foods and beverages
are widely distributed and less likely to contain source-specific water, the use of total water intake
rates may overestimate the potential exposure to toxic substances present only in local water
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supplies; therefore, tapwater intake of community water, rather than total water intake, is
emphasized in this section.
The studies on drinking water intake that are currently available are based on short-term
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, upper-percentile 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.
Other studies based on older data were presented in the Exposure Factors Handbook
(U.S. EPA, 1997a).
4.2 DRINKING WATER INTAKE STUDIES
U.S. EPA Office of Water (2000) - Estimated Per Capita Water Ingestion in the United
States - The U.S. EPA used data from a U.S. Department of Agriculture (USDA) survey from
1994 through 1996 to estimate drinking water ingestion rates by the U.S. population. The
Continuous Study of Food Intakes by Individuals (CSFII) is a continuing survey of food
consumption habits in the U.S. Over 15,000 persons responded to the study conducted between
1994 and 1996 on what they ate and drank over two non-consecutive days (USDA, 1998). The
U.S. EPA used the drinking water ingestion data to derive estimates of consumption rates by age
groups, gender, water source, vulnerable subsets of the population (i.e., lactating and pregnant
women) (U.S. EPA, 2000). The ingestion rates are expressed in both volume (milliliters [ml]) per
day per person and volume per kilogram (kg) body weight (BW) per day. The purpose of the
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report was to provide data to assist in estimating human health risks from the ingestion of
contaminated or potentially-contaminated drinking water (U.S. EPA, 2000).
In the study, the U.S. EPA reported that community water (i.e., tapwater-public water
supply) accounts for approximately 75 percent of the mean ingested water (U.S. EPA, 2000).
The total water consumption consists of community water supply, bottled water, other sources,
and missing sources. Other sources include household wells or cisterns or a spring, either
household or community. In addition to these sources, the data also distinguish between direct
and indirect water consumption. Direct consumption is water consumed directly from the tap
while indirect consumption is water added during final food or beverage preparation in the home
or food establishment (e.g., restaurants, school cafeterias). Indirect water does not include water
added by the food manufacturer during food processing. Table 4-1 provides the estimates for the
mean total direct and indirect water consumption by water source for 1994 to 1996 per person
combined for all ages. The estimates also include consumption rates for the 90th percentile and
the 95th percentile plus the upper and lower bounds for each percentile. Table 4-2 shows the
estimated total direct and indirect water ingestion by all sources by broad age groups (i.e., <1
year, 1-10 years, 11-19 years) and percentiles.
The data are broken down into multiple population subsets including children's age
groups: less than 1 year, 1 to 10 years, and 11 to 19 years. The data show that although the
quantity of water ingested decreases with age, the quantity consumed per unit mass of body
weight (BW) increases (U.S. EPA, 2000). For instance, the mean community water consumption
is 342 ml per child per day for under 1 year, 400 ml/child/day for 1 to 10 years, and 683
ml/child/day for 11 to 19 years. The consumption as a function of unit mass, however, is 46
ml/kilogram (kg) BW/day for under 1 year, 19 ml/kg BW/day for 1 to 10 years, and 12 ml/kg
BW/day for 11 to 19 years. The significance of this finding is that although children may be
encounter lower overall doses, the younger, vulnerable ages (i.e., infants) have significantly higher
dose rates per unit of BW. Tables 4-3 and 4-4 show the daily community water consumption rate
estimates by fine and broad age groups in units of mL/day and mL per mass of BW per day.
Tables 4-5 and 4-6 present the data for bottled water ingestion.
Water consumption rates for other sources of water are compiled in Tables 4-7 and 4-8.
These two sources comprise nearly one-quarter of total water consumption. The trend in the data
is similar to that shown for community water consumption; that is, the younger ages consume less
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of these sources of water, but the quantity consumed per unit mass of BW increases as the age
decreases. Missing water sources have not been included in the summary of water sources
because of its negligible quantity. Missing water sources comprise only about one percent of
water consumption.
The data collected from the CSFII study for the USD A have both strengths and
limitations. The strengths lie in the design of the survey in that it was intended to collect a
statistically representative sample of the U.S. population (i.e., obtain data from a sufficiently large
sample set) and the survey was sufficiently specific in detailing types of food and drink. The large
size of the sample population (> 15,000) total and 6,000 children enhances the precision and
accuracy of the estimates for the overall population and population subsets. The survey was
conducted on non-consecutive days which improves the variance over consecutive days of
consumption. In addition, the survey was administered such that an interviewer went through the
data collection process for the initial day to show the participants the proper response
methodology. The second day of the survey was reported by the participant. The survey also
represents the most up-to-date on water consumption and incorporated sufficient parameters to
differentiate sources of water, ages, gender, weight, and vulnerable populations. The limitations
of the survey involve the short duration of the study and some of the data reporting methods. The
short duration (i.e., 2 non-consecutive days), although an advantage over 2 consecutive days,
diminishes the precision of an individual's water ingestion rate. The mean for an individual can
easily be skewed for numerous reasons. The large number of the sample population would
hopefully contribute to greater accuracy, but the precision may still be low. The data reporting
did not always support variance estimation for some reported population subsets. As such, the
means differences could not always be statistically tested except for the larger population subsets.
Therefore, the reported differences were derived empirically instead of statistically.
Myers et al. (1999) - Options for Development of Parametric Probability Distributions
for Exposure Factors - Myers et al. (1999) presented a system of procedures to fit distributions
to selected data from the draft Exposure Factors Handbook (EFH) (U.S. EPA, 1996). The
system was based on EPA's Guiding Principles for Monte Carlo Analysis (U.S. EPA, 1997b).
The system was applied to the dataset of total tapwater intake reported in Table 3-7 (Ershow and
Cantor, 1989) of the EFH. EFH Table 3-7 data summaries analyzed by Myers et al. (1999)
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consist of nine estimated percentiles for total daily tapwater intake in mL/kg-day. Only the values
for infants, children, and teens are reported here.
The statistical methodology recommended by Myers et al. (1999) incorporates the
following elements:
1. a dataset and its underlying experimental design.
2. a family of models, and
3. an approach to inference (e.g., estimation, assessment of fit, and uncertainty analysis).
The system utilizes a twelve-model hierarchy with the most general model being a five-parameter
generalized F distribution with a point mass at zero. The point mass at zero represents the
proportion of nonconsuming or nonexposed individuals. As described in Myers et al. (1999), the
12 models of the generalized F hierarchy were fit to each of the three tapwater datasets (i.e., three
age groups of children) using three different estimation criteria, maximum likelihood estimation
(MLE), minimum chi-square estimation (MCS), and weighted least squares (WLS). The Pearson
chi-square tests and likelihood ratio tests of goodness-of-fit (GOF) were used. Tables 4-9 and 4-
10 present chi-square values and associated p-values for chi-square GOF tests, respectively. As
stated in Myers et al. (1999), "In each case the null hypothesis tested is that the data arose from
the given type of model. A low p-value casts doubt on the null hypothesis. Clearly, the only
model that appears to fit most of the datasets is the five-parameter generalized F distribution with
a point mass at zero, referred to as GenF5. According to Table 4-9, the gamma model provides
the best fit (smallest chi-square) of the two-parameter models to the data for each individual age
groups."
Table 4-11 is shown in Myers et al. (1999) and is described there as follows:
"[This table] summarizes several additional aspects of interest for the tapwater
populations. For each age group shown, the first row (SOURCE=data) is basically
a data summary. Within the first row, the columns labeled N, MEAN, and SDEV
contain the sample size, the sample mean, and the sample standard deviation.
Within the first row, the columns labeled P01, P05, ..., P99 contain the nominal
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probabilities .01, .05, ..., .99. The values in the first row for MEAN, SDEV, and
the nine nominal probabilities can be thought of as 11 targets that the models are
trying to hit.
The other rows (2nd through 6th rows) within each age group contain results from
fitting four models, including gamma, lognormal and Weibull, using selected
estimation criteria. The model and estimation criterion are indicated by the
variable SOURCE. For instance, SOURCE = gammle indicates the two-parameter
gamma model fit using maximum likelihood estimation. The model gf5 is the five-
parameter generalized F with a point mass at zero. The infants group does not
contain results from the five-parameter generalized F because the selected model
had infinite variance. For the gamma and Weibull models, there was little
difference between the three estimation criteria, and the MLE performed best
overall. For the lognormal model, results from the WLS estimation criterion are
shown in addition to the MLE.
The last three columns contain summary GOF measures. CHIDF is the value of the
chi-square statistic divided by its degrees of freedom. The methods are ordered
with respect to this CHIDF measure. CHIDF is more comparable across cases
involving different degrees of freedom than is the chi-square statistic. PGOF is the
p-value for model goodness-of-fit based on the chi-square test. Low-values of
PGOF, such as PGOF <0.05, cast doubt on the null hypothesis that the given type
of model is correct. Note that maximum likelihood estimation performed much
worse for the lognormal model than the WLS method of estimation, as determined
by CHIDF and PGOF measures.
If a two-parameter model must be used for tapwater consumption, then the gamma
model with parameters estimated by maximum likelihood is recommended. The
five-parameter generalized F distribution could be used for sensitivity analyses.
The age effect seems sufficiently strong to justify the use of separate age groups in
risk assessment."
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4.3. 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 non-tapwater sources, including water contained in food.
Estimated total fluid and total tapwater intake rates for the three groups are presented in Tables
4-12 and 4-13, 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=l,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 4-13).
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 4-14). All other
beverages combined accounted for approximately 46 percent, 43 percent, and 45 percent of the
total water intake for control, pregnant, and lactating women, respectively. Food accounted for
the remaining portion of total water intake.
This survey has an adequately large size (6,201 individuals) and it is representative of the
United States population with respect to age distribution, racial composition, and residential
location. 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
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diet within the last two decades. Since the data were collected for only a three-day period, the
extrapolation to chronic intake is uncertain.
4.4 RECOMMENDATIONS
The studies described in this section were used in selecting recommended drinking water
(tapwater) consumption rates for children. The mean and upper-percentile estimates reported in
these studies are reasonably similar. 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 4-15.
The intake rates, as expressed as liters per day, generally increase with age, and the data are
consistent across ages for the studies.
A characterization of the overall confidence in the accuracy and appropriateness of the
recommendations for drinking water is presented in Table 4-16. The Exposure Factors Handbook
(U.S. EPA, 1997a) gave this factor a medium confidence rating. However, the confidence score
of the overall recommendations has been increased to high for this report because of the addition
of the newer U.S. EPA (2000) study.
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4.5 REFERENCES FOR CHAPTER 4
Cantor, K.P.; Hoover, R.; Hartge, P.; Mason, T.J.; Silverman, D.T.; et al. (1987) Bladder cancer, drinking water
source, and tapwater consumption. A case-control study. J. Natl. Cancer Inst. 79(6): 1269-1270.
Ershow, A.G.; Cantor, K.P. (1989) Total water and tapwater intake in the United States: population-based
estimates of quantities and sources. Life Sciences Research Office, Federation of American Societies for
Experimental Biology.
Erschow, A.G.; Brown, L.M.; Cantor, K.P. (1991) Intake of tapwater and total water by pregnant and lactating
women. American Journal of Public Health. 81:328-334.
Myers, L., J. Lashley, and R. Whitmore. (1999) Options for Development of Parametric Probability Distributions
for Exposure Factors, submitted to U.S. Environmental Protection Agency, Office of Research and
Development, Washington, D.C., September 30.
National Academy of Sciences (NAS). (1977) Drinking water and health. Vol. 1. Washington, DC: National
Academy of Sciences-National Research Council.
USDA. (1998) 1994-1996 Continuing survey of food intakes and 1994-1996 diet and health survey.
U.S. EPA. (1980) U.S. Environmental Protection Agency. Water quality criteria documents; availability. Federal
Register, (November 28) 45(231):79318-79379.
U.S. EPA. (1991) National primary drinking water regulations; final rule. Federal Register. 56(20):3526-3597.
January 30, 1991.
U.S. EPA. (1996) Exposure Factors Handbook. Washington, DC: Office of Research and Development, National
Center for Environmental Assessment. SAB Review Draft (EPA/600/P-95/002Ba).
U.S. EPA. (1997a) Exposure Factors Handbook. Washington, DC: Office of Research and Development,
(EPA/600/P-95/002F).
U.S. EPA. (1997b) Risk Assessment Forum. Guiding Principles for Monte Carlo Analysis, (EPA/630/R-97/001).
U.S. EPA. (2000) Estimated per capita water ingestion in the United States. Washington, DC: Office of Science
and Technology, Office of Water.
June 2000
4-9
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Table 4-1. Estimated Direct and Indirect Community Total Water Ingestion By Source for U.S. Population
Mean (ml/person/day) 90th Percentile (ml/person/day) 95th Percentile (ml/person/day)
90% CI 90% CI 90% CI
Source
Sample
Size
Estimate
Lower
Bound
Upper
Bound
Estimate
Lower
Bound
Upper
Bound
Estimate
Lower
Bound
Upper
Bound
Community
Water Supply
15,303
927
902
951
2,016
1,991
2,047
2,544
2,485
2,576
Bottled Water
15,303
161
147
176
591
591
632
1,036
1,006
1,065
Other Sources
15,303
128
101
155
343
305
360
1,007
947
1,074
Missing Sources
15,303
16
13
20
-
-
-
-
-
-
All Sources
15,303
1,232
1,199
1,265
2,341
2,308
2,366
2,908
2,840
2,960
- Denotes zero.
(1) Source of Data - USDA Continuing Survey of Food Intakes by Individuals (1994-1996)
(2) Estimates are based on 2-day averages for non-consecutive days.
Source: U.S. EPA (2000)
June 2000
4-10
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1
2
Table 4-2. Estimate of Total Direct and Indirect Water Ingestion, All Sources By Broad Age Category for U.S. Children
3 Quantity, Percentiles (ml/person-day)
4
Age (years)
Sample Size
Mean
1th
5th
10th
25th
50th
75th
90th
95th
99th
5
< 1
359
484
-
-
-
124
449
747
949
1,182
l,645a
6
1 - 10
3,980
528
4
75
133
254
444
710
1,001
1,242
1,891
7
11 - 19
1,641
907
-
118
219
395
715
1,188
1,780
2,185
3,805
8 Quantity, Percentiles (ml/kg-day)
9
< 1
359
67
-
-
16
57
101
156
170
218a
10
1 - 10
3,980
25
4
6
12
21
33
49
64
98
11
11 -19
1,641
16
2
4
7
13
20
30
39
64
12
13 Source of Data: 1994-96 USDA Survey of Food Intakes by Individuals (CSFII)
14 - Denotes zero.
15 a - Sample size was insufficient for minimum reporting requirements according to "Third Report on Nutritional Monitoring in the U.S. (1994-96)"
16
17 Source: U.S. EPA (2000)
18
19
20
June 2000
4-11
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Table 4-3. Estimate of Direct and Indirect Community Water Ingestion By Fine Age Category for U.S. Children
Quantity, Percentile (ml/person-day)
Age (years)
Sample Size
Mean
1th
5th
10th
25th
50th
75th
90th
95th
99th
<0.5
199
280
-
-
-
-
35
552
861
945a
l,286a
0.5-0.9
160
412
-
-
-
36
322
712
884
l,101a
l,645a
1 -3
1,834
313
-
-
-
74
236
469
691
942
1,358
4-6
1,203
420
-
-
22
133
330
591
917
1,165
l,902a
7 - 10
943
453
-
-
29
139
355
671
978
1,219
1,914a
11 - 14
816
594
-
-
27
181
435
801
1,365
1,722
2,541a
15 - 19
825
760
-
-
25
201
540
1,030
1,610
2,062
3,830a
Quantity, Percentile (ml/kg-day)
<0.5
191
47
-
-
-
-
5
90
139
170a
217a
0.5-0.9
153
45
-
-
-
4
36
79
103
122a
169a
1 -3
1,752
23
-
-
1
6
17
33
51
67
109a
4-6
1,113
21
-
-
1
6
16
29
44
64
91a
7 - 10
879
15
-
-
1
5
11
21
32
39
60a
11 - 14
790
12
-
-
1
4
9
17
26
34
54a
15 -19
816
12
-
-
-
3
9
16
25
32
61a
Source of Data: 1994-96 USDA Survey of Food Intakes by Individuals (CSFII)
- Denotes zero.
a - Sample size was insufficient for minimum reporting requirements according to "Third Report on Nutritional Monitoring in the U.S. (1994-96)"
Source: U.S. EPA (2000)
June 2000
4-12
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1
2 Table 4-4. Estimate of Direct and Indirect Community Water Ingestion By Broad Age Category for U.S. Children
3
4
Quantity, Percentile (ml/person-day)
5
Age (years)
Sample Size
Mean
1th
5th
10th
25th
50th
75th
90th
95th
99th
6
< 1
344
342
-
-
-
-
173
652
878
1,040
l,438a
7
1 - 10
3,744
400
-
-
12
118
302
571
905
1,118
1,731
8
11 - 19
1,606
683
-
-
26
191
473
937
1,533
1,946
3,671
9 Quantity, Percentile (ml/kg-day)
10 < 1 344 46 19
11 1 - 10 3,744 19 5 15
12 11 - 19 1,606 12 1 3 9
13
14 Source of Data: 1994-96 USDA Survey of Food Intakes by Individuals (CSFII)
15 - Denotes zero.
16 a - Sample size was insufficient for minimum reporting requirements according to "Third Report on Nutritional Monitoring in the U.S. (1994-96)."
17 Source: U.S. EPA (2000)
18
19
20
82 127 156 205
27 42 56 91
16 26 33 59
June 2000
4-13
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Table 4-5. Estimate of Direct and Indirect Bottled Water Ingestion By Fine Age Category for U.S. Children
Quantity, Percentile (ml/person-day)
Age (years)
Sample Size
Mean
1th
5th
10th 25 th 50th
75th
90th
95th
99th
<0.5
199
110
-
-
-
38
519
809
l,045a
0.5-0.9
160
113
-
-
-
5
496
12T
l,006a
1 -3
1,834
62
-
-
-
-
235
411
820
4-6
1,203
73
-
-
-
-
279
521
915a
7 - 10
943
76
-
-
-
-
271
497
917a
11 - 14
816
100
-
-
-
-
344
679
1,415a
15 - 19
825
130
-
-
-
-
468
867
l,775a
Quantity, Percentile (ml/kg-day)
<0.5
191
20 ...
6 81
152a
170a
0.5-0.9
153
14 ...
2 51
92a
125a
1 -3
1,752
5 ...
17
30
61
4-6
1,113
4 ...
13
24
49a
7 - 10
879
2 ...
8
14
26a
11 - 14
790
2 ...
7
13
27a
15 -19
816
2 ...
7
12
28a
Source of Data: 1994-96 USDA Survey of Food Intakes by Individuals (CSFII)
- Denotes zero.
a - Sample size was insufficient for minimum reporting requirements according to "Third Report on Nutritional Monitoring in the U.S. (1994-96)"
Source: U.S. EPA (2000)
June 2000
4-14
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1 Table 4-6. Estimate of Direct and Indirect Bottled Water Ingestion By Broad Age Category for U.S. Children
3 Quantity, Percentile (ml/person-day)
4 Age (years) Sample Size Mean 1th 5th 10th 25th 50th 75th 90th 95th 99th
5 < 1 359 111 - - - - - 23 522 793 l,083a
6 1 - 10 3,980 71 ...... 264 472 906
7 11-19 1,641 116 ...... 414 764 1,648
8 Quantity, Percentile (ml/kg-day)
9 < 1 344 17 ..... 5 76 123 169a
10 1 - 10 3,744 3 ...... 12 22 49
11 11 - 19 1,606 2 ..ฆฆฆฆ 7 13 28
12
13 Source of Data: 1994-96 USDA Survey of Food Intakes by Individuals (CSFII)
14 - Denotes zero.
15 a - Sample size was insufficient for minimum reporting requirements according to "Third Report on Nutritional Monitoring in the U.S. (1994-96)."
16 Source: U.S. EPA (2000)
17
18
19
20
21
June 2000
4-15
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Table 4-7. Estimate of Direct and Indirect Other Water Ingestion By Fine Age Category for U.S. Children
Quantity, Percentile (ml/person-day)
Age (years)
Sample Size
Mean
1th 5th 10th 25th 50th 75th
90th
95th
99th
<0.5
199
18
-
-
86a
468a
0.5-0.9
160
30
-
23
202a
554a
1 -3
1,834
35
-
8
295
710
4-6
1,203
43
-
32
322
830a
7 - 10
943
67
-
206
554
l,049a
11 - 14
816
106
-
341
800
1,81 la
15 - 19
825
77
-
234
552
1,41 la
Quantity, Percentile (ml/kg-day)
<0.5
191
3
-
-
15a
86a
0.5-0.9
153
3
-
5
24a
63a
1 -3
1,752
3
-
2
21
48
4-6
1,113
2
-
2
15
42a
7 - 10
879
2
-
7
18
37a
11 - 14
790
2
-
7
16
36a
15 -19
816
1
-
4
9
21a
Source of Data: 1994-96 USDA Survey of Food Intakes by Individuals (CSFII)
- Denotes zero.
a - Sample size was insufficient for minimum reporting requirements according to "Third Report on Nutritional Monitoring in the U.S. (1994-96)"
Source: U.S. EPA (2000)
June 2000
4-16
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Table 4-8. Estimate of Direct and Indirect Other Water Ingestion By Broad Age Category for U.S. Children
Quantity, Percentile (ml/person-day)
Age (years)
Sample Size
Mean
1th
5th
10th 25 th 50th 75 th
90th
95th
99th
< 1
359
23
-
-
-
-
148
556a
1 - 10
3,980
50
-
-
-
103
405
920
11 - 19
1,641
90
-
-
-
286
666
1,710
Quantity, Percentile (ml/kg-day)
< 1
344
3
-
-
-
-
21
66a
1 - 10
3,744
2
-
-
-
5
18
43
11 - 19
1,606
2
-
-
-
5
11
29
Source of Data: 1994-96 USDA Survey of Food Intakes by Individuals (CSFII)
- Denotes zero.
a - Sample size was insufficient for minimum reporting requirements according to "Third Report on Nutritional Monitoring in the U.S. (1994-96)."
Source: U.S. EPA (2000)
June 2000
4-17
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1
2
Table 4-9. Chi-square GOF statistics for 12 Models, Tapwater Data, Based on Maximum Likelihood Method of Parameter Estimation
3
4
5
Age
Group
(years)
CHI
Gam2
CHI
Log2
CHI
Tic2
CHI
Wei2
CHI
Ggam3
CHI
GenF4
CHI
Gam3
CHI
Log3
CHI
Tic3
CHI
Wei3
CHI
Ggam4
CHI
GenF5
6
7
Infants
(<1)
19.8
26.6
39.4
20.6
18.1
10.6
19.8
13.7
10.8
20.6
18.1
8.10
8
9
Children
(1-10)
84.5
315
295
198
84.7
40.3
46.6
129
195
198
27.5
15.2
10
11
Teens
(11-19)
89.5
606
557
125
81.4
38.4
23.4
286
377
110
23.1
7.88
12
13
14
15
Legend: Prefix indicates model type, Gam = gamma, Log = lognormal, Tic
= log-logistic, Wei =
Weibull, Ggam
= generalized gamma, GenF = generalized F.
Model suffix indicates number of free or adjustable parameters.
16
17
18
Table 4-10
. P-Values for Chi-Square GOF Tests of 12 Models, Tapwater Data
19
20
21
Age
Group
(years)
PGOF
Gam2
PGOF
Log2
PGOF
Tic2
PGOF
Wei2
PGOF
Ggam3
PGOF
GenF4
PGOF
Gam3
PGOF
Log3
PGOF
Tic3
PGOF
Wei3
PGOF
Ggam4
PGOF
GenF5
22
23
Infants
(<1)
0.001
0.000
0.000
0.000
0.000
0.005
0.000
0.003
0.013
0.000
0.000
0.013
24
25
Children
(1-10)
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.004
26
27
Teens
(11-19)
0.000
0.000
0.000
0.000
0.000
0.000
0.001
0.000
0.000
0.000
0.000
0.096
28
29
30
Legend: Prefix indicates model type, Gam = gamma, Log = lognormal, Tic
= log-logistic, Wei =
Weibull, Ggam
= generalized gamma, GenF = generalized F.
Model suffix indicates number of free or adjustable parameters.
4-18
-------
1
2
3
Table 4-11. Results of Statistical Modeling of Tapwater Data (intake Rates in dL/kg-day) Using 5-Parameter Generalized F and
2-Parameter Gamma, Lognormal and Weibull Modles
4
Source
N P01
P05
P10
P25
P50
P75
P90
P95
P99
MEAN
SDEV
CHIDF
PGOF
5
INFANTS (Age <1)
6
data
403 0.010
0.050
0.100
0.250
0.500
0.750
0.900
0.950
0.990
0.435
0.425
7
gammle
0.252
0.526
0.702
0.908
0.951
0.996
0.448
0.410
40.945
0.0006
8
weimle
0.260
0.526
0.699
0.906
0.950
0.996
0.447
0.412
50.145
0.0004
9
logmle
0.227
0.561
0.735
0.903
0.937
0.984
0.470
0.548
60.660
0.0000
10
logwls
0.216
0.559
0.738
0.908
0.942
0.986
0.462
0.512
60.974
0.0000
11
CHILDREN (Ages 1-10)
12
data
5605 0.010
0.050
0.100
0.250
0.500
0.750
0.900
0.950
0.990
0.355
0.229
13
gammle
0.010
0.047
0.106
0.250
0.495
0.752
0.900
0.952
0.989
0.356
0.234
30.792
0.0044
14
gf5mle
0.004
0.052
0.118
0.263
0.492
0.738
0.895
0.953
0.993
0.355
0.224
120.07
0.0000
15
weimle
0.000
0.024
0.091
0.266
0.529
0.765
0.895
0.943
0.984
0.356
0.250
270.18
0.0000
16
logmle
0.011
0.070
0.134
0.264
0.474
0.721
0.894
0.959
0.997
0.355
0.218
280.34
0.0000
17
logwls
0.000
0.036
0.113
0.288
0.532
0.750
0.878
0.929
0.977
0.366
0.286
450.07
0.0000
18
TEENS (Ages 11-19)
19
data
5801 0.010
0.050
0.100
0.250
0.500
0.750
0.900
0.950
0.990
0.182
0.108
20
gf5mle
0.010
0.048
0.103
0.253
0.498
0.747
0.953
0.953
0.989
0.182
0.110
10.969
0.0962
21
gammle
0.002
0.046
0.110
0.274
0.511
0.740
0.947
0.947
0.989
0.182
0.111
120.79
0.0000
22
weimle
0.006
0.061
0.122
0.267
0.487
0.725
0.957
0.957
0.995
0.182
0.106
170.86
0.0000
23
logmle
0.000
0.017
0.076
0.270
0.544
0.768
0.942
0.942
0.981
0.182
0.119
450.35
0.0000
24
logwls
0.000
0.032
0.108
0.303
0.548
0.747
0.920
0.920
0.968
0.189
0.144
860.56
0.0000
25
26
4-19
-------
1
2
Table 4-12.
Total Fluid Intake of Women 15-49 Years Old
3
Percentile Distribution
4
Reproductive
Standard
5
Status3
Mean
Deviation
5
10
25
50
75
90
95
6
mL/dav
7
Control
1940
686
995
1172
1467
1835
2305
2831
3186
8
Pregnant
2076
743
1085
1236
1553
1928
2444
3028
3475
9
Lactating
2242
658
1185
1434
1833
2164
2658
3169
3353
10
mL/ke/dav
11
Control
32.3
12.3
15.8
18.5
23.8
30.5
38.7
48.4
55.4
12
Pregnant
32.1
11.8
16.4
17.8
17.8
30.5
40.4
48.9
53.5
13
Lactating
37.0
11.6
19.6
21.8
21.8
35.1
45.0
53.7
59.2
14
15
" Number of observations: nonpregnant, nonlactating controls (n =
6,201); pregnant (n =
188); lactating
16
t"-
II
17
Source: Ershow etal., 1991
18
19
20
Table 4-13. Total Tapwater Intake of Women 15-49 Years Old
21
22
Percentile Distribution
23
Reproductive Statusa
Mean
Standard
Deviation
5
10
25
50
75
90
95
24
mL/dav
25
Control
1157
635
310
453
709
1065
1503
1983
2310
26
Pregnant
1189
699
274
419
713
1063
1501
2191
2424
27
Lactating
1310
591
430
612
855
1330
1693
1945
2191
28
mL/kg/dav
29
Control
19.1
10.8
5.2
7.5
11.7
17.3
24.4
33.1
39.1
30
Pregnant
18.3
10.4
4.9
5.9
10.7
16.4
23.8
34.5
39.6
31
Lactating
21.4
9.8
7.4
9.8
14.8
20.5
26.8
35.1
37.4
32
Fraction of dailv fluid intake that is
tapwater (%)
33
Control
57.2
18.0
24.6
32.2
45.9
59.0
70.7
79.0
83.2
34
Pregnant
54.1
18.2
21.2
27.9
42.9
54.8
67.6
76.6
83.2
35
Lactating
57 0
158
27 4
38 0
49 5
58 1
65 9
76 4
80 5
36
37 a Number of observations: nonpregnant, nonlactating controls (n = 6,201); pregnant (n = 188); lactating (n = 77).
38 Source: Ershow et al., 1991.
39
4-20
-------
Table 4-14. Total Fluid (mL/Day) Derived from Various Dietary Sources by Women Aged 15-49 Years3
Sources
Control Women
Pregnant
Women
Lactating
Women
Meanb
Percentile
Percentile
Percentile
50
95
Meanb
50
95
Meanb
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 Drinks1
174
110
590
130
73
464
117
57
440
Noncarbonated Soft Drinks1
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, nonlactatmg controls (n = 6,201); pregnant (n = 188); lactating (n = 77).
b Individual means may not add to all-sources total due to rounding.
c 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.
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Table 4-15. Summary of Recommended Community Drinking Water Intake Rates
Percentiles
Age Group/
Population
Mean
50th
90th
95th
Multiple
Fitted
Distributions
<1 year"
0.34 L/day
46 mL/kg-day
0.17 L/day
19 mL/kg-day
0.88 L/day
127 mL/kg-day
1.0 L/day
156 mL/kg-day
Tables 4-4
Table 4-11ฐ
1-3 years"
0.31 L/day
23 mL/kg-day
0.24
17 mL/kg-day
0.69 L/day
51 mL/kg-day
0.94 L/day
67 mL/kg-day
Table 4-3
1-10 years"
0.40 L/day
19 mL/kg-day
0.30 L/day
15 mL/kg-day
0.90 L/day
42 mL/kg-day
1.1 L/day
56 mL/kg-day
Table 4-4
Table 4-11ฐ
11-19 years"
0.68 L/day
12 mL/kg-day
0.47 L/day
9 mL/kg-day
1.5 L/day
26 mL/kg-day
1.9 L/day
33 mL/kg-day
Tables 4-4
Table 4-11ฐ
Pregnantb
Women
1.2 L/day
18.3 mL/kg-day
1.1 L/day
16 mL/kg-day
2.2 L/day
35 mL/kg-day
2.4 L/day
40 mL/kg-day
Table 3-25
Lactatingb
Women
1.3 L/day
21.4 mL/kg-day
1.3 L/day
21 mL/kg-day
1.9 L/day
35 mL/kg-day
2.2 L/day
37 mL/kg-day
Table 3-25
"Source: U.S. EPA (2000).
bSource: Ershow et al. (1991).
'Source: Myers et al. (1999).
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Table 4-16. Confidence in Tapwater Intake Recommendations
Considerations
Rationale
Rating
Study Elements
Level of peer review
Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data
collection period
Validity of approach
Study size
Representativeness of the
population
Characterization of
variability
Lack of bias in study design
(high rating is desirable)
Measurement error
The U.S. EPA (2000) and Ershow and Cantor (1989) High
studies had thorough expert panel review. Review
procedures were not reported in the Canadian study; it
was a government report. Other reports presented are
published in scientific journals.
The two monographs are available from the High
sponsoring agencies; the others are library-accessible.
Methods are well-described. High
The studies are directly relevant to tapwater. In High
addition, for U.S. EPA (2000) study included
consumption for other drinking water sources
See "representativeness" below. NA
The three monographs used recent primary data (less High
than one week) on recall of intake.
Data collected for USDA (1998) used by U.S. EPA High
(2000) are current. The Ershow and Cantor (1989)
and Canadian surveys used data from 1978 era.
These are one- to three-day intake data. However, Medium
long term variability may be small. Their use as a
chronic intake measure can be assumed.
The approach was competently executed. High
The two U.S. monographs (U.S. EPA, 2000; Ershow High
and Cantor, 1989) each sufficiently sample
populations (i.e., 6,000 and 11,000, respectively) for
their studies
The U.S. EPA (2000), Ershow and Cantor (1989), and High
Canadian surveys were validated as demographically
representative.
The full distributions were given in the main studies. High
Bias was not apparent. High
No physical measurements were taken. The method Medium
relied on recent recall of standardized volumes of
drinking water containers, and was not validated.
Other Elements
Number of studies
Agreement between
researchers
There were three key studies for the child
recommendations.
This agreement was good.
High for adult and
children.
Medium for the other
recommended
subpopulation values.
High
Overall Rating
The data are excellent and current.
High
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TABLE OF CONTENTS
5. SOIL INGESTION AND PICA 5-1
5.1 INTRODUCTION 5-1
5.2 SOIL INTAKE STUDIES 5-1
5.3 PREVALENCE OF PICA 5-18
5.4 DELIBERATE SOIL INGESTION AMONG CHILDREN 5-19
5.5 RECOMMENDATIONS 5-25
5.6 REFERENCES FOR CHAPTER 5 5-27
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LIST OF TABLES
Table 5-1. Estimated Daily Soil Ingestion Based on Aluminum, Silicon, and Titanium
Concentrations 5-29
Table 5-2. Calculated Soil Ingestion by Nursery School Children 5-30
Table 5-3. Calculated Soil Ingestion by Hospitalized, Bedridden Children 5-31
Table 5-4. Mean and Standard Deviation Percentage Recovery of Eight Tracer Elements .. 5-31
Table 5-5. Soil and Dust Ingestion Estimates for Children Ages 1-4 Years 5-32
Table 5-6. Average Daily Soil Ingestion Values Based on Aluminum, Silicon, and Titanium as
Tracer Elements 5-32
Table 5-7. Geometric Mean (Gm) and Standard Deviation (Gsd) Ltm Values for Children at
Daycare Centers and Campgrounds 5-33
Table 5-8. Estimated Geometric Mean Ltm Values of Children Attending Daycare Centers
According to Age, Weather Category, and Sampling Period 5-34
Table 5-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates per Child for 64
Children (Mg/day) 5-35
Table 5-10. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on
Data for 64 Subjects Projected over 365 Days 5-35
Table 5-11. Estimated Soil Ingestion Rate Summary Statistics And Parameters for Distributions
Using Binder et Al. (1986) Data with Actual Fecal Weights 5-36
Table 5-12. 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) .... 5-37
Table 5-13. Soil Ingestion Estimates for Median and Best Four Trace Elements Based on
Food/Soil Ratios for 64 Anaconda Children (mg/day) Using Al, Si, Ti, Y, and Zr . . . 5-38
Table 5-14. Dust Ingestion Estimates for Median and Best Four Trace Elements Based
on Food/Soil Ratios for 64 Anaconda Children (mg/day) Using Al, Si, Ti, Y, and Zr 5-39
Table 5-15. Daily Soil Ingestion Estimation in a Soil-pica Child by Tracer and by Week (mg/dป$P
Table 5-16. Ratios of Soil, Dust, and Residual Fecal Samples in the Soil Pica Child 5-41
Table 5-17. Daily variation of Soil Ingestion by Children Displaying Soil Pica in
Wong (1988) 5-42
Table 5-18. Prevalence of Non-Food Ingestion Mouthing Behaviors by Child's Age:
Percent of Children Whose Parents Reports the Behavior in the Past Month . 5-43
Table 5-19. Average Outdoor Object Mouthing Scores for Children by Age, Frequency of
Sand/Dirt Play, and General Mouthing Quartiles 5-46
Table 5-20. Summary of Estimates of Soil Ingestion by Children 5-47
Table 5-21. Summary of Recommended Values for Soil Ingestion 5-47
Table 5-22. Confidence in Soil Intake Recommendation 5-48
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5. SOIL INGESTION AND PICA
5.1 INTRODUCTION
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. 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. Recommended intake rates are
based on the results of key studies presented in the Exposure Factors Handbook and summarized
here. Relevant information on the prevalence of pica and intake among individuals exhibiting pica
behavior is also presented.
5.2 SOIL INTAKE STUDIES
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 soil were obtained from the children's
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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:
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 5-1). 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
T
(5-1)
where:
estimated soil ingestion for child i based on element e (g/day);
concentration of element e in fecal sample of child i (mg/g);
fecal dry weight (g/day); and
concentration of element e in child i's yard soil (mg/g).
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the laboratory processing of stool samples may have accounted for the increased levels. The
frequency distribution graph of soil ingestion estimates based on titanium shows that a group of
21 children had particularly high titanium values (i.e., >1,000 mg/day). The remainder of the
children showed titanium ingestion estimates at lower levels, with a distribution more comparable
to that of the other elements.
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 Methodfor 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. Twenty-seven 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 5-2). 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
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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 5-3). 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 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
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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 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 5-4).
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 5-5). 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 5-5). Intake of soil and dust was estimated
using a weighted ingestion for one child in the study ranged from approximately 10 to
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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 mass-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:
(5-2)
where:
soil ingested for child i based on tracer e (g);
feces dry weight (g);
feces dry weight on toilet paper (g);
tracer amount in feces (//g/g);
tracer amount in urine (//g/g);
food dry weight (g);
tracer amount in food (//g/g); and
tracer concentration in soil (//g/g).
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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 5-6). 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, 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 one-week period during the summer and may not be
representative of long-term (i.e., annual) patterns of intake.
Van Wijnen et al. (1990) - Estimated Soil Ingestion by Children - In a study by Van
Wijnen 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 Wijnen 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
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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 W'ijnen
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 5-7) 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 5-8). Van W'ijnen 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 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 W'ijnen 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-by-element 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
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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. 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 5-9 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.)
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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 5-9 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 5-10). 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 representative of the U.S. population. Study mean estimates of soil
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ingestion, such as the study mean estimates presented in Table 5-9, 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 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. 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.
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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.
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 key study 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 one-half of those reported by Binder et al.
(1986). Table 5-11 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 5-11 also presents the
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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 representative of long-term intake rates because
the data were derived from a short-term study.
Sedman andMahmood (1994) - Soil Ingestion by Children and Adults Reconsidered
Using the Results of Recent Tracer Studies - Sedman and Mahmood (1994) used the results of
two of the key children's tracer studies (Calabrese et al. 1989; Davis et al. 1990) 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:
Y^xe^0112*^ (5-3)
where:
Y; = adjusted mean soil ingestion (mg/day)
x = a constant
yr = average age (2 years)
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The average ages of children in the two key 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).
Calabrese and Stanek (1995) - Resolving Inter tracer 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.
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
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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 5-12 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 5-12). 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 5-12). 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 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.
Calabrese etal. (1997) - Soil Ingestion for Children Residing on a Superfund Site -
Calabrese et al. (1997) estimated soil ingestion rates for children residing on a Superfund site
using a mass-balance methodology in which eight tracer elements (i.e., aluminum, barium,
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manganese, silicon, titanium, vanadium, yttrium, and zirconium) were analyzed. The
methodology used in this study is very similar to the one conducted in Calabrese et al. (1989). As
in Calabrese et al. (1989), 64 children ages 1-4 years were selected for this study and were
predominantly from two-parent households. This stratified simple random sample of children was
selected from the Anoconda, Montana area. Thirty-six of the 64 children were male, and the
children ranged in age from 1 to 3 years with approximately an equal number of children in each
age group. The Calabrese et al. (1997) study was conducted for seven consecutive days during a
two week period in the month of September. Duplicate samples of meals, beverages, and over-
the-counter medicines and vitamins were collected over the seven day period, along with fecal
samples. In addition, soil and dust samples were collected from the children's home and play
areas. Toothpaste containing nondetectable levels of the tracer elements, with the exception of
silica, was provided to all of the children. Infants were provided with baby cornstarch, diaper rash
cream, and soap which were found to contain low levels of tracer elements.
As in Calabrese et al. (1989), an additional study was conducted in which the identical
mass-balance methodology used to estimate soil ingestion rates among children was used on
adults in order to validate that soil ingestion could be detected. Known amounts of soil were
administered to ten adults (5 males, 5 females) from Western Massachusetts over a period of 28
days. Each adult ingested for 7 consecutive days 1) no soil during Week 1, 2) 20 mg of sterilized
soil during Week 2, 3) 100 mg of sterilized soil during Week 3, and 4) 500 mg of sterilized soil
during Week 4. Soil samples were previously characterized and were of sufficient concentration
to be detected in the analysis of fecal samples. Duplicate food and fecal samples were collected
every day during each study week and analyzed for the eight tracer elements (Al, Si, Ti, Ce, La,
Nd, Y, and Zr). It was found that ingestion of soil from 20 to 500 mg/day could be detected in a
reliable manner.
Calabrese et al. (1997) estimated soil ingestion by each tracer element using the Best
Tracer Method (BTM) which allows for the selection of the most recoverable tracer for a
particular group of subjects (Stanek and Calabrese, 1995b). In this case BA, Mn, and V were
dropped as they were found to be poor performing tracers. The median soil ingestion estimates
for the four best trace elements based on Food/Soil ratios for the 64 children using Al, Si, Ti, Y,
and Zr were presented (Table 5-13). Based on the soil ingestion estimate for the best tracer, the
mean soil ingestion rate was 66 mg/day and the median was 20 mg/day. The 95th percentile value
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was 280 mg/day. Using the median of the 4 best tracers, the mean was 7 mg/day and the 95th
percentile was 160 mg/day. These results are lower than the soil ingestion estimates obtained by
Stanek and Calabrese (1995a). Calabrese et al. (1997) believe this may be due to the fact that the
families of the children who participated in this study were aware that they lived on an EPA
Superfund site and this knowledge might have resulted in reduced exposure. There was no
statistically significant difference found in soil ingestion estimates by gender or age. There was
also no significant difference in soil ingestion by housing or yard characteristics (i.e., porch, deck,
door mat, etc.), or between children with or without pets.
The median dust ingestion estimates for the four best tracer elements using Al, Si, Ti, Y,
and Zr were also presented (Table 5-14). The mean dust ingestion rate based on the best tracer
was 130 mg/day and the 95th percentile rate was 614 mg/day.
The advantages of this study were the use of a longer 7 consecutive day study period
rather than two periods of 3 and 4 days (Stanek and Calabrese, 1995a), the use of the BTM, the
use of an expanded adult validation study which used 10 volunteers rather than 6 (Calabrese et al.,
1989), and the use of a dietary education program to reduce food tracer input and variability.
However, the data presented in this study are from a single 7-day period during September which
may not reflect soil ingestion rates for other months or time-periods. In addition, the study
displayed a net residual negative error, which may have resulted in underestimated soil ingestion
rates. Calabrese et al. (1997) believe that this error is not likely to affect the median by more than
40 mg/day.
5.3 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
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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 non-black, 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 W'ijnen et 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.
5.4 DELIBERATE SOIL INGESTION AMONG CHILDREN
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12
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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 5-15). 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 5-16 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 5-16. Of these 19 pairs, 9 fecal tracer ratios fell within
the boundaries for soil and dust (Table 5-16). 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
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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).
Calabrese, E. J. and E. J. Stanek (1993) - Soil Pica: Not a Rare Event - Calabrese and
Stanek critiqued a study by Wong (1988) that attempted to estimate the amount of soil ingested
by two groups of children. Wong (1988) studied a total of 52 children who were in two separate
government institutions in Jamaica. The children had an average age of 3.1 years (ranging from
0.3 to 7.6 years) and 7.2 years (ranging from 1.8 to 14 years). The younger group (from the
Glenhope Place of Safety) contained 24 children and the older group (from the Reddies Place of
Safety) had 28 children. Fecal samples were obtained from the subject children and the amount of
silicon, a soil tracer, in dry feces was measured in order to quantify soil ingestion.
Using a hospital control group of 30 children with an average age of 4.8 years (ranging
from 0.3 to 12 years), the authors of the study collected an unspecified number of daily fecal
samples. Based on these samples, dry feces were observed as containing 1.45 percent silicon or
14.5 mg of silicon per 1 g of dry feces. The authors assumed that this amount of silicon in dry
feces was representative of the typical background amount of silicon from dietary sources only.
Observed quantities of silicon greater than 1.45 percent were then assumed to be from soil
ingestion.
Wong (1988) calculated the amount of soil ingested by using the standard soil ingestion
estimation formula (Binder et al. 1986). One fecal sample was collected from each subject per
month over the four month study period.
For the 28 children in the older group (average age 7.2 years), soil ingestion was
estimated to be 58 mg/day based on the mean minus one outlier and 1,520 mg/day based on the
mean of all the children. The group contained one outlier, a child with an estimated average soil
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ingestion rate of 41 g/day over the four months. Some of the observed soil ingestion results for
this group of children included:
7 of 28 had average soil ingestion of >100 mg/day,
4 of 28 had average soil ingestion of >200 mg/day,
1 of 28 had average soil ingestion of >300 mg/day, and
8 of 28 showed no indication of soil ingestion for any month.
Estimated average soil ingestion in the younger group of children (average age 3.1 years)
was higher. The mean soil ingestion of all the children was 470 ฑ 370 mg/day. Due to some
sample losses, of the 24 children studied, only 15 subjects had samples for each of the four
months. Observed soil ingestion estimates for this group included:
14 of 24 had average soil ingestion of <100 mg/day,
10 of 24 had average soil ingestion of >100 mg/day,
5 of 24 had average soil ingestion of >600 mg/day,
4 of 24 had average soil ingestion of >1,000 mg/day, and
5 of 24 showed no indication of soil ingestion for any month.
Over the entire 4 month study duration, 9 of 84 total samples (or 10.5%) showed soil
ingestion estimates of >1 g/day (pica behavior). Of the 52 children studied by Wong (1988), six
children displayed soil pica behavior. The estimated soil ingestion for each of these subjects is
shown in Table 5-17. For the younger group of children (Glenhope Place of Safety), 5 of 24 (or
20.8%) displayed soil pica behavior on at least one occasion. A high degree of daily variability in
soil ingestion was observed among the 6 children exhibiting pica behavior. As shown in Table 5-
17, 3 of 6 children (#11, 12, and 22) showed soil pica on only 1 of 4 days. The other 3 children
(#14, 18, and 27) ingested >1.0 g/d on 2 of 4, on 3 of 4, and 4 of 4 days, respectively. Subject
#27 displayed a high degree of soil pica, ranging from 3.7 to 60.6 g/d of soil ingestion; however,
it was indicated that this child was mentally retarded while the other pica children were considered
to have normal mental capabilities.
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Sources of uncertainty or error in this study include differences between the hospital (i.e.,
control) study group (the background control) and the 2 study groups; lack of information on the
dietary intake of silicon for the studied children; use of a single fecal sample; and loss of fecal
samples. The use of a single soil tracer may also introduce error since there may be other sources
from which the tracer could originate. For example, some toothpastes have extremely high
concentrations of silicon and children could ingest significant quantities of toothpaste.
Additionally, tracers could be found in indoor dust that children may ingest. However, given
these uncertainties, the results are important in that they indicate that soil pica is not a rare
occurrence in younger children.
Stanek et al. (1998) - Prevalence of Soil Mouthing/Inge stion among Healthy Children
Aged 1 to 6 - Stanek et al. (1998) presented a methodology that links mouthing behavior among
children to the prevalence of ingestion of non-food items. Soil ingestion data were collected via
face-to-face interviews over a period of 3 months from parents or guardians of 533 children ages
1 to 6 years old attending well-visits in Western Massachusetts. Three clinics participated in this
study during the months of August, September, and October, 1992: Kaiser Permanente's clinic in
Amherst, a private clinic associated with the Cooley Dickinson Hospital in Northampton, and the
BayState Medical Center clinic in Springfield. Stanek et al. (1998) questioned the participants
about the frequency of 28 mouthing behaviors of the children over the past month in addition to
exposure time (e.g., time outdoors, play in sand or dirt) and children's characteristics (e.g.,
teething). Response categories of the clinic questionnaire corresponded to daily, at least weekly,
at least monthly, and never. Stanek et al. (1998) expressed the mouthing rate for each child as the
sum of rates for responses to four questions on mouthing specific outdoor objects. Regression
models with variables in a step-wise manner identified factors related to high outdoor mouthing
rates. Stanek et al. (1998) first considered variables that indicated opportunity for exposure, then
subjects' characteristics (e.g., teething) and environmental factors, and finally, concurrent
reported behaviors.
Table 5-18 presents the prevalence of non-ingestion/mouthing behaviors by child's age as
the percent of children whose parents reported the behavior in the past month. Stanek et al.
(1998) found that outdoor soil mouthing behavior prevalence was higher than indoor dust
mouthing prevalence, but both behaviors had highest prevalence among 1-year-old children, and
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dropped quickly among children 2 years old and older. Stanek et al. (1998) conducted principal
component analyses on response to four questions relating to ingestion of outdoor objects
(Table 5-18) in an attempt to characterize variability. Responses were converted to mouthing
rates per week, using values of 0, 0.25, 1, and 7 for responses of never, monthly, weekly, and
daily ingestion. Stanek et al. (1998) found outdoor ingestion/mouthing rates for children 1 years
of age to be 4.73 per week and 0.44 per week for children 2-6 years of age. Stanek et al. (1998)
estimated the frequency of children playing in sand/dirt as a measure of potential exposure, and
found that 71 percent of the children were reported to play in sand or dirt at least weekly, and 45
percent were reported as playing in the sand or dirt daily. The authors found that children who
played in the sand or dirt had higher outdoor object ingestion/mouthing rates. Thus, children with
higher direct exposure to sand or dirt were more likely to ingest or mouth on outdoor objects.
Stanek et al. (1998) found similar results when comparing the time spent outdoors to reported
outdoor ingestion and mouthing rates. Sixty-five percent of one-year old children were reported
to spend less than 3 hour per day outdoors, while 42 percent of children 2-6 years old spend less
than 3 hours per day outdoors.
Table 5-19 presents average outdoor mouthing rates by age and sand/dirt play frequency.
Stanek et al. (1998) presented the data for children by quartiles according to their general
mouthing rates and applied linear regression models fit to general mouthing rates. The authors
found a significant slope for all groups but one, and thus demonstrated that outdoor mouthing
behavior increased with higher quartiles and that rates of increase depended on age and sand/soil
play exposure.
A strength of this study is that it focuses on the prevalence of specific behaviors to
quantify soil mouthing or ingestion among healthy children. The results of this study might have
important health implications as it showed that one-year-old children with high general levels of
mouthing behavior have the potential for high risk soil ingestion.
A limitation associated with this study is that the data are based on recall behavior from
the summer previous to the interview. Extrapolation to other seasons may be difficult. In
addition, data were collected for children in Western Massachusetts and data were only available
for the healthy children who were present for well-visits.
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5.5 RECOMMENDATIONS
The studies described in this section were used to recommend values for soil intake among
children. Estimates of the amount of soil ingested by children are summarized in Table 5-20 and
the recommended values are presented in Table 5-21. The mean values ranged from 39 mg/day to
271 mg/day with an average of 138 mg/day for soil ingestion and 193 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 358 mg/day for
soil ingestion and 790 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.
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.
It should be noted that these recommendations are based on studies that used different
survey designs and populations. 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 5-22. It is important,
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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 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.
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5.6 REFERENCES FOR CHAPTER 5
Binder, S.; Sokal, D.; Maughan, D. (1986) Estimating soil ingestion: the use of tracer elements in estimating the
amount of soil ingested by young children. Arch. Environ. Health. 41(6):341-345.
Behrman, L.E.; Vaughan, V.C., III. (1983) Textbook of Pediatrics. Philadelphia, PA: W.B. Saunders Company.
Bruhn, C.M.; Pangborn, R.M. (1971) Reported incidence of pica among migrant families. J. of the Am. Diet.
Assoc. 58:417-420.
Calabrese, E.J.; Stanek, E.J. (1992) Distinguishing outdoor soil ingestion from indoor dust ingestion in a soil pica
child. Regul. Toxicol. Pharmacol. 15:83-85.
Calabrese, E.J.; Stanek, E.J. (1993) Soil pica: not a rare event. J. Environ. Sci. Health. A28(2):373-384.
Calabrese, E.J.; Stanek, E.J. (1995) Resolving intertracer inconsistencies in soil ingestion estimation. Environ.
Health Perspect. 103(5):454-456.
Calabrese, E.J.; Pastides, H.; Barnes, R.; Edwards, C.; Kostecki, P.T.; et al. (1989) How much soil do young
children ingest: an epidemiologic study. In: Petroleum Contaminated Soils, Lewis Publishers, Chelsea, MI.
pp. 363-397.
Calabrese, E.J.; Stanek, E.J.; Gilbert, C.E. (1991) Evidence of soil-pica behavior and quantification of soil
ingested. Hum. Exp. Toxicol. 10:245-249.
Calabrese, E.J.; Stanek, E.J.; Pekow, P.; Barnes, R.M. (1997) Soil ingestion estimates for children residing on a
Superfund site. Ecotoxicology and Environmental Safety. 36:258-268.
Clausing, P.; Brunekreef, B.; Van Wijnen, J.H. (1987) A method for estimating soil ingestion by children. Int.
Arch. Occup. Environ. Health (W. Germany) 59(l):73-82.
Danford, D.C. (1982) Pica and nutrition. Annual Review of Nutrition. 2:303-322.
Davis, S.; Waller, P.; Buschbon, R.; Ballou, J.; White, P. (1990) Quantitative estimates of soil ingestion in
normal children between the ages of 2 and 7 years: population based estimates using aluminum, silicon, and
titanium as soil tracer elements. Arch. Environ. Hlth. 45:112-122.
Feldman, M.D. (1986) Pica: current perspectives. Psychosomatics (USA) 27(7):519-523.
Forfar, J.O.; Arneil, G.C., eds. (1984) Textbook of Paediatrics. 3rded. London: Churchill Livingstone.
Illingworth, R.S. (1983) The normal child. New York: Churchill Livingstone.
Kaplan, H.I.; Sadock, B.J. (1985) Comprehensive textbook of psychiatry/IV. Baltimore, MD: Williams and
Wilkins.
Kimbrough, R.; Falk, H.; Stemr, P.; Fries, G. (1984) Health implications of 2,3,7,8-tetrachlorodibenzo-p-dioxin
(TCDD) contamination of residential soil. J. Toxicol. Environ. Health 14:47-93.
Lourie, R.S.; Layman, E.M.; Millican, F.K. (1963) Why children eat things that are not food. Children
10:143-146.
Sayetta, R.B. (1986) Pica: An overview. American Family Physician 33(5): 181-185.
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Sedman, R.; Mahmood, R.S. (1994) Soil ingestion by children and adults reconsidered using the results of recent
tracer studies. Air and Waste, 44:141-144.
Stanek, E.J.; Calabrese, E.J. (1995a) Daily estimates of soil ingestion in children. Environ. Health Perspect.
103(3):276-285.
Stanek, E.J.; Calabrese, E.J. (1995b) Soil ingestion estimates for use in site evaluations based on the best tracer
method. Human and Ecological Risk Assessment. 1:133-156.
Stanek, E.J.; Calabrese, E.J.; Mundt, K.; Pekow, P.; Yeatts, K.B. (1998) Prevalence of soil mouthing/ingestion
among healthy children aged 1 to 6. Journal of Soil Contamination. 7(2):227-242.
Thompson, K.M.; Burmaster, D.E. (1991) Parametric distributions for soil ingestion by children. Risk Analysis.
11:339-342.
U.S. EPA. (1984) Risk analysis of TCDD contaminated soil. Washington, DC: U.S. Environmental Protection
Agency, Office of Health and Environmental Assessment. EPA 600/8-84-031.
Van Wijnen, J.H.; Clausing, P.; Brunekreff, B. (1990) Estimated soil ingestion by children. Environ. Res.
51:147-162.
Vermeer, D.E.; Frate, D.A. (1979) Geophagia in rural Mississippi: environmental and cultural contexts and
nutritional implications. Am. J. Clin. Nutr. 32:2129-2135.
Wong, M.S. (1988) The Role of Environmental and Host Behavioural Factors in Determining Exposure to
Infection with Ascaris lumbricoldes and Trichuris trichlura. Ph.D. Thesis, Faculty of Natural Sciences,
University of the West Indies. 1988.
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Table 5-1. Estimated Daily Soil Ingestion Based on Aluminum,
Silicon, and Titanium Concentrations
4
Standard
95th
Geometric
5
Estimation
Mean
Median
Deviation
Range
Percentile
Mean
6
Method
(mg/day)
(mg/day)
(mg/day)
(mg/day)
(mg/day)
(mg/day)
7
Aluminum
181
121
203
25-1,324
584
128
8
Silicon
184
136
175
31-799
5,78
130
9
Titanium
1,834
618
3,091
4-17,076
9,590
401
10
Minimum
108
88
121
4-708
386
65
11 Source: Binder et al. (1986).
12
13
14
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Table 5-2. Calculated Soil Ingestion by Nursery School Children
3
4
5
Child
Sample
Number
Soil Ingestion as
Calculated from Ti
(mg/day)
Soil Ingestion as
Calculated from Al
(mg/day)
Soil Ingestion as
Calculated from AIR
(mg/day)
Limiting
Tracer
(mg/day)
6
1
L3
103
300
107
103
L14
154
211
172
154
L25
130
23
-
23
7
2
L5
131
-
71
71
L13
184
103
82
82
L27
142
81
84
81
8
3
L2
124
42
84
42
L17
670
566
174
174
9
4
L4
246
62
145
62
Lll
2,990
65
139
65
10
5
L8
293
-
108
108
L21
313
-
152
152
11
6
L12
1,110
693
362
362
L16
176
-
145
145
12
7
L18
11,620
-
120
120
L22
11,320
77
-
77
13
8
LI
3,060
82
96
82
14
9
L6
624
979
111
111
15
10
L7
600
200
124
124
16
11
L9
133
-
95
95
17
12
L10
354
195
106
106
18
13
L15
2,400
-
48
48
19
14
L19
124
71
93
71
20
15
L20
269
212
274
212
21
16
L23
1,130
51
84
51
22
17
L24
64
566
-
64
23
18
L26
184
56
-
56
24
Arithmetic
1,431
232
129
105
25
Mean
26 Source: Adapted from Clausing et al. (1987).
27
28
29
30
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Table 5-3. Calculated Soil Ingestion by Hospitalized,
Bedridden Children
4
Soil Ingestion as
Soil Ingestion as
5
Calculated from Ti
Calculated from Al
Limiting Tracer
6
Child Sample
(mg/day)
(mg/day)
(mg/day)
7
1 G5
3,290
57
57
G6
4,790
71
71
8
2 G1
28
26
26
9
3 G2
6,570
94
84
G8
2,480
57
57
10
4 G3
28
77
28
11
5 G4
1,100
30
30
12
6 G7
58
38
38
13
Arithmetic Mean
2,293
56
49
14
Source: Adapted from Clausing et al. (1987).
15
16
17
18
19
Table 5-4. Mean and Standard Deviation Percentage Recovery of Eight Tracer Elements
20
21
300 mg Soil Ingested
1,500 mg Soil Ingested
22
23
Tracer Element Mean
SD
Mean
SD
24
Al 152.8
107.5
93.5
15.5
25
Ba 2304.3
4533.0
149.8
69.5
26
Mn 1177.2
1341.0
248.3
183.6
27
Si 139.3
149.6
91.8
16.6
28
Ti 251.5
316.0
286.3
380.0
29
V 345.0
247.0
147.6
66.8
30
Y 120.5
42.4
87.5
12.6
31
Zr 80.6
43.7
54.6
33.4
32 Source: Adapted from Calabrese et al. (1989).
33
34
35
36
June 2000
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3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Table 5-5. Soil and Dust Ingestion Estimates for
Children Ages 1-4 Years
Intake (mg/day)a
95th
Tracer Element N Mean Median SD Percentile Maximum
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
Corrected for Tracer Concentrations in Foods
Source: Adapted from Calabrese et al. (1989).
Table 5-6. Average Daily Soil Ingestion Values Based on
Aluminum, Silicon, and Titanium as Tracer Elements21
Standard Error of
Element
Mean
Median
the Mean
Range
(mg/d)
(mg/d)
(mg/d)
(mg/d)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).
bNegative values occurred as a result of correction for nonsoil sources of the tracer elements.
Source: Adapted from Davis et al. (1990).
June 2000
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4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Table 5-7. 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
(mg/day)
GSD LTM
(mg/day)
n
GM LTM
(mg/day)
GSD LTM
(mg/day)
<1
Girls
3
81
1.09
_
_
_
Boys
1
75
-
-
-
-
l-<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
00
r-
174
1.73
"Age and/or sex not registered for eight children.
bAge not registered for seven children.
Source: Adapted from Van Wijnen et al. (1990).
June 2000
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4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Table 5-8. 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
Bad
(>4 days/week
precipitation)
Age
(years)
<1
1-<2
2-<3
4-<5
3
18
33
5
Estimated
Geometric Mean
LTM Value
(mg/day)
94
103
109
124
3
33
48
6
Estimated Geometric
Mean
LTM Value
(mg/day)
67
80
91
109
Reasonable
(2-3 days/week
precipitation)
<1
1-<2
2-<3
3-<4
4-<5
1
10
13
19
1
61
96
99
94
61
Good
(<2 days/week
precipitation)
<1
1-<2
2-<3
3-<4
4-<5
4
42
65
67
10
102
229
166
138
132
Source: Van Wijnenetal. (1990).
June 2000 5-33 DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Table 5-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates
per Child for 64 Children21 (Mg/day)
Type of Estimate
Number of
Overall
A1
Ba
Mn
Si
Ti
V
Y
Zr
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
75 th 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
Tor each child, estimates of soil ingestion were formed on days 4-8 and the mean of these estimates was then
evaluated for each child. The values in the column "overall" correspond to percentiles of the distribution of
these means over the 64 children. When specific trace elements were not excluded via the relative standard
deviation criteria, estimates of soil ingestion based on the specific trace element were formed for 108 days for
each subject. The mean soil ingestion estimate was again evaluated. The distribution of these means for
specific trace elements is shown.
Source: Stanek and Calabrese (1995a).
Table 5-10. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on
Data for 64 Subjects Projected over 365 Days3
Range 1 - 2,268 mg/db
50th Percentile (median) 75 mg/d
90th Percentile 1,190 mg/d
95th Percentile 1,751 mg/d
" Based on fitting a log-normal distribution to model daily soil ingestion values.
b Subject with pica excluded.
Source: Stanek and Calabrese (1995a).
June 2000
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2
3
4
5
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7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Table 5-11. 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
Al
Si
Ti
MEAN3
Mean
97
85
1,004
91
Min
11
10
1
13
10th
21
19
3
22
20th
33
23
22
34
30th
39
36
47
43
40th
43
52
172
49
Med
45
60
293
59
60th
55
65
475
69
70th
73
79
724
92
80th
104
106
1,071
100
90th
197
166
2,105
143
Max
1,201
642
14,061
921
Lognormal Distribution Parameters
Median
45
60
59
Standard Deviation
169
95
--
126
Arithmetic Mean
97
85
--
91
Underlying Normal Distribution Parameters
Mean
4.06
4.07
4.13
Standard Deviation
0.88
0.85
--
0.80
" MEAN = arithmetic average of soil ingestion based on aluminum and silicon.
Source: Thompson and Burmaster (1991).
June 2000
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Table 5-12. 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)3
Negative Error
Lack of Fecal
Total
Total
Sample on
Other
Negative
Positive
Original
Adjusted
Final Study Day
Causesb
Error
Error
Net Error
Mean
Mean
Aluminum
14
11
25
43
+18
153
136
Silicon
15
6
21
41
+20
154
133
Titanium
82
187
269
282
+13
218
208
Vanadium
66
55
121
432
+311
459
148
Yttrium
8
26
34
22
-12
85
97
Zirconium
6
91
97
5
-92
21
113
How to read table: for example, aluminum as a soil tracer displayed both negative and positive error. The
cumulative total negative error is estimated to bias the mean estimate by 25 mg/day downward. However,
aluminum has positive error biasing the original mean upward by 43 mg/day. The net bias in the original
mean was 18 mg/day positive bias. Thus, the original 156 mg/day mean for aluminum should be corrected
downward to 136 mg/day.
bValues indicate impact on mean of 128-subject-weeks in milligrams of soil ingested per day.
Source: Calabrese and Stanek (1995).
June 2000
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2
3
Table 5-13. Soil Ingestion Estimates for Median and Best Four Trace Elements Based on Food/Soil
Ratios for 64 Anaconda Children (mg/day) Using Al, Si, Ti, Y, and Zr
4
Min
P5
P10
SP25
P50
SP75
P90
P95
Max
Mean
SD
5
Median of best 4
-101.3
-91.0
-53.8
-38.0
-2.4
26.8
73.1
159.8
380.2
6.8
74.5
6
Best tracer
-53.4
-24.4
-14.4
2.2
20.1
68.9
223.6
282.4
609.9
65.5
120.3
7
2nd best
-115.9
-62.1
-48.6
-26.6
1.5
38.4
119.5
262.3
928.5
33.2
144.8
8
3rd best
-170.5
-88.9
-67.0
-52.0
-18.8
25.6
154.7
376.1
1293.5
31.2
199.6
9
4th best
-298.3
-171.0
-131.9
-74.7
-29.3
0.2
74.8
116.8
139.1
-34.6
79.7
10
11
12 Source: Calabrese et al. (1997).
13
14
15
5-37
-------
Table 5-14. Dust Ingestion Estimates for Median and Best Four Trace Elements Based
on Food/Soil Ratios for 64 Anaconda Children (mg/day)
Using Al, Si, Ti, Y, and Zr
5
Min
P5
P10
SP25
P50
SP75
P90
P95
Max
Mean
SD
6
Median of best 4
-261.5
-186.2
-152.7
-69.5
-5.5
62.8
209.2
353.0
683.9
16.5
160.9
7
Best tracer
-377.0
-193.8
-91.0
-20.8
26.8
198.1
558.6
613.6
1499.4
127.2
299.1
8
2nd best
-239.8
-147.2
-137.1
-59.1
7.6
153.1
356.4
409.5
1685.1
82.7
283.6
9
3rd best
-375.7
-247.5
-203.1
-81.7
-14.4
49.4
406.5
500.5
913.2
25.5
235.9
10
4th best
-542.7
-365.6
-277.7
-161.5
-55.1
52.4
277.3
248.8
6120.5
81.8
840.3
11
12
13 Source: Calabrese et al. (1997).
14
15
16
5-38
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Table 5-15. Daily Soil Ingestion Estimation in a Soil-pica
Child by Tracer and by Week (mg/day)
Tracer
Week 1
Estimated Soil Ingestion
Week 2
Estimated Soil 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).
June 2000
5-39
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Table 5-16. Ratios of Soil, Dust, and Residual Fecal
Samples in the Soil Pica Child
Tracer Ratio
Pairs
Soil
Fecal
Dust
Estimated % of Residual Fecal Tracers
of Soil Origin as Predicted by Specific
Tracer 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).
June 2000
5-40
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Table 5-17. Daily variation of Soil Ingestion by Children Displaying Soil Pica in Wong (1988)
Child subject number
Month
Estimated soil ingestion
(mg/day)
Glenhope Place of Study
Number 11
1
55
2
1,447
3
22
4
40
Number 12
1
0
2
0
3
7,924
4
192
Number 14
1
1,016
2
464
3
2,690
4
898
Number 18
1
30
2
10,343
3
4,222
4
1,404
Number 22
1
0
2
--
3
5,341
4
0
Reddles Place of Study
Number 27
1
48,314
2
60,692
3
51,422
4
3,782
Source: Calabrese and Stanek (1993).
June 2000
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Table 5-18. Prevalence of Non-Food Ingestion/Mouthing Behaviors by Child's Age:
Percent of Children Whose Parents Reports the Behavior in the Past Month
Child's Age (years)
Non-Food Ingestion/mouthing prevalence
1
2
3
4
5
6
All
N
171
70
93
82
90
22
528
Outdoor "soil" mouthing/Ingestion
Sand, stones
% > Monthly
54
26
19
9
7
9
27
% > Weekly
36
10
6
2
4
5
16
% Daily
17
0
2
1
1
5
6
Grass, leaves, flowers
% > Monthly
48
16
24
13
9
5
26
% > Weekly
34
7
14
4
6
0
16
% Daily
16
0
2
1
1
0
6
Twigs, sticks, woodchips
% > Monthly
42
23
13
13
11
5
23
% > Weekly
29
7
9
5
7
0
14
% Daily
12
0
0
1
0
0
4
Soil, dirt
% > Monthly
38
21
5
7
3
9
18
% > Weekly
24
7
3
2
1
9
10
% Daily
11
0
1
0
1
0
4
Dust, lint, dustballs
% > Monthly
14
4
2
0
0
5
6
% > Weekly
7
1
1
0
0
0
3
% Daily
2
0
0
0
0
0
1
Plaster, chalk
% > Monthly
8
10
3
2
3
5
5
% > Weekly
5
3
0
1
0
0
2
% Daily
2
0
0
1
0
0
1
Paintchips, splinters
% > Monthly
6
0
0
4
1
0
3
% > Weekly
2
0
0
1
0
0
1
% Daily
0
0
0
0
0
0
0
General mouthing of objects
Other toys
% > Monthly
88
53
64
44
42
23
62
% > Weekly
82
44
42
26
28
9
49
% Daily
63
27
20
9
7
5
30
Paper, cardboard, tissues
% > Monthly
71
37
32
23
18
14
41
% > Weekly
54
23
20
12
7
9
28
% Daily
28
9
8
5
2
5
13
Teething toys
% > Monthly
65
29
15
4
3
9
29
% > Weekly
55
16
9
1
1
9
22
% Daily
44
6
6
0
0
9
17
June 2000
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3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Table 5-18. Prevalence of Non-Food Ingestion/Mouthing Behaviors by Child's Age:
Percent of Children Whose Parents Reports the Behavior in the Past Month (continued)
Crayons, pencils, erasers
% > Monthly
56
54
46
50
41
36
50
% > Weekly
41
37
25
27
26
27
32
% Daily
19
17
4
6
4
18
12
Blankets, cloth
% > Monthly
51
21
26
22
22
14
32
% > Weekly
42
17
17
18
14
14
25
% Daily
29
11
9
13
7
5
16
Shoes, Footware
% > Monthly
50
23
8
7
2
5
22
% > Weekly
42
10
3
2
1
5
16
% Daily
20
1
0
0
0
0
7
Clothing
% > Monthly
49
34
37
43
26
27
39
% > Weekly
39
24
23
28
16
14
27
% Daily
25
7
11
9
6
14
14
Other items
% > Monthly
41
30
30
23
21
27
31
% > Weekly
35
26
24
15
10
14
23
% Daily
22
11
15
7
6
5
14
Crib, chairs, furniture
% > Monthly
37
11
8
10
4
5
17
% > Weekly
26
9
3
5
2
0
11
% Daily
13
3
1
1
0
0
5
Sucking of fingers, etc
Suck fingers/thumb
% > Monthly
67
41
43
57
39
41
52
% > Weekly
60
27
31
43
31
18
41
% Daily
44
21
22
26
24
14
30
Suck feet or toes
% > Monthly
37
14
12
11
3
0
18
% > Weekly
23
4
3
2
1
0
9
% Daily
8
1
0
1
0
0
3
Use pacifier
% > Monthly
24
9
6
2
2
5
11
% > Weekly
22
9
5
2
2
0
10
% Daily
20
6
5
1
1
0
9
Suck hair
% > Monthly
1
3
8
9
10
5
5
% > Weekly
1
3
2
2
4
5
2
% Daily
1
1
1
0
2
0
1
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Table 5-18. Prevalence of Non-Food Ingestion/Mouthing Behaviors by Child's Age:
Percent of Children Whose Parents Reports the Behavior in the Past Month (continued)
"Disgusting" object mouthing/ingestion
Soap, detergent, shampoo
% > Monthly
48
34
24
17
9
9
29
% > Weekly
37
27
14
11
6
9
21
% Daily
15
14
3
2
0
0
8
Plastic, plastic wrap
% > Monthly
32
19
8
7
9
0
17
% > Weekly
22
11
3
4
4
0
10
% Daily
7
4
1
0
1
0
3
Cigarette butts, tobacco
% > Monthly
16
6
5
4
3
5
8
% > Weekly
10
4
4
1
2
5
5
% Daily
4
0
1
1
1
0
2
Matches
% > Monthly
6
4
1
4
1
0
4
% > Weekly
2
3
1
1
1
0
2
% Daily
1
0
0
0
0
0
0
Insect
% > Monthly
5
1
2
4
2
0
3
% > Weekly
2
0
1
4
2
0
2
% Daily
0
0
1
2
2
0
1
Other ingestion and behaviors
Toothpaste
% > Monthly
63
97
92
94
93
86
84
% > Weekly
60
94
91
93
92
86
82
% Daily
52
87
86
93
89
82
77
Chew gum
% > Monthly
18
56
76
76
91
100
58
% > Weekly
10
40
60
60
69
68
43
% Daily
3
17
18
13
21
36
14
Bite nails
% > Monthly
8
26
31
29
33
59
24
% > Weekly
5
23
24
20
26
45
18
% Daily
2
7
12
9
10
14
7
Suck hair
% > Monthly
62
76
85
96
88
73
78
% > Weekly
57
64
77
88
81
68
71
% Daily
42
39
43
55
52
45
45
Source: Stanek et al. (1998).
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Table 5-19. Average Outdoor Object Mouthing Scores for Children by
2
3
Age, Frequency of Sand/Dirt Play, and General Mouthing Quartiles
4
1 Year old
Age 2 to 6 years
5
/T
Sand/dirt play?
Sand/dirt play?
O
7
Outdoor object
>Daily
Daily
>Daily
Daily
8
mouthing scores
Mean N
Mean N
Mean N
Mean N
9
General mouthing
10
Score quartiles (Mean)
11
1st Quartile (1.5)
0.1 19
2.8 16
0.1 139
0.5 117
12
2nd Quartile (9.7)
0.7 14
3.9 11
0.3 27
0.8 28
13
3rd Quartile (19.6)
1.3 33
10.5 22
0.2 19
1.8 21
14
4th Quartile (35.6)
3.6 35
14 23
0.5 2
1.5 4
15
Slope based on general
16
mouthing quartile
0.11
0.34
0.007
0.054
17
score
18
SE
0.052
0.060
0.021
0.019
19
20
21
Source: Stanek et al. (1998).
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Table 5-20. Summary of Estimates of Soil Ingestion by Children
Mean (mg/day) Upper Percentile (mg/day) References
Al
Si
AIRa
Ti
Y
Al
Si
Ti
Y
181
184
584
578
Binder etal. 1986
230
129
Clausing et al. 1987
39
82
245.5
Davis et al. 1990
64.5b
160b
268.4b
153
154
218
85
223
276
1,432
106
Calabrese et al. 1989
154b
483b
170b
65b
478b
653b
l,059b
159b
122
139
-
271
165
254
224
279
144
Stanek and Calabrese, 1995a
133ฐ
217c
Stanek and Calabrese, 1995b
69-120d
Van Wijnen et al. 1990
66c
280c
Calabrese et al. 1997
196b
994b
Average =138 mg/day soil
193 mg/day soil and dust combined
"AIR = Acid Insoluble Residue
bSoil and dust combined
CBTM
dLTM; corrected value
358 mg/day soil
790 mg/day soil and dust combined
Table 5-21. Summary of Recommended Values for Soil Ingestion
Population Mean Upper Percentile
a b
Children (age 1-6 years) 100 mg/day 400 mg/day
Pica child 10 g/day
"200 mg/day may be used as a conservative estimate of the mean (see text).
bStudy period was short; therefore, these values are not estimates of usual intake.
cTo be used in acute exposure assessments. Based on only one pica child (Calabrese et al., 1989).
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Table 5-22. Confidence in Soil Intake Recommendation
Considerations
Rationale
Rating
Study Elements
Level of peer review
Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data collection period
Validity of approach
Study size
Representativeness of the
population
Characterization of variability
Lack of bias in study design (high
rating is desirable)
Measurement error
Other Elements
Number of studies
Agreement between researchers
Overall Rating
All key studies are from peer review literature.
Papers are widely available from peer review journals.
Methodology used was presented, but results are difficult
to reproduce.
The focus of the studies was on estimating soil intake rate
by children; studies did not focus on intake rate by adults.
Two of the key studies focused on Dutch children; other
studies used children from specific areas of the U.S.
All the studies were based on primary data.
Studies were conducted after 1980.
Children were not studied long enough to fully
characterize day to day variability.
The basic approach is the only practical way to study soil
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.
The sample sizes used in the key studies were adequate
for children. However, only few adults have been studied.
The study population may not be representative of the
U.S. in terms of race, socio-economics, and geographical
location; Studies focused on specific areas; two of the
studies used Dutch children.
Day-to-day variability was not very well characterized.
The selection of the population studied may introduce
some bias in the results (i.e., children near a smelter site,
volunteers in nursery school, Dutch children).
Errors may result due to problems with absorption of the
tracers in the body and mismatching inputs and outputs.
There are 7 key studies.
Despite the variability, there is general agreement among
researchers on central estimates of daily intake for
children.
Studies were well designed; results were fairly consistent;
sample size was adequate for children and very small for
adults; accuracy of methodology is uncertain; variability
cannot be characterized due to limitations in data
collection period. Insufficient data to recommend upper
percentile estimates for both children and adults.
High
High
Medium
High (for children)
Low (for adults)
Medium
High
High
Medium
Medium
Medium (for
children)
Low (for adults)
Low
Low
Medium
Medium
High
Medium
Medium (for
children - long-term
central estimate)
Low (for adults)
Low (for upper
percentile)
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TABLE OF CONTENTS
6. OTHER NON-DIETARY INGESTION FACTORS 6-1
6.1 INTRODUCTION 6-1
6.2 STUDIES RELATED TO NON-DIETARY INGESTION 6-2
6.3 RECOMMENDATIONS 6-9
6.4 REFERENCES FOR CHAPTER 6 6-11
-------
LIST OF TABLES
Table 6-1. Extrapolated Total Mouthing Times Minutes per Day (time awake) 6-12
Table 6-2. Frequency of Contact, by Contact Variable Contacts per Hour 6-13
Table 6-3. Summary of Studies on Mouthing Behavior 6-14
Table 6-4. Summary of Mouthing Frequency Data 6-15
Table 6-5. Confidence in Mouthing Behavior Recommendations 6-16
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6. OTHER NON-DIETARY INGESTION FACTORS
6.1 INTRODUCTION
Young children (i.e., ages 6 months through approximately 4 years) also have the potential
for exposure to toxic substances through non-dietary ingestion pathways other than soil ingestion
(e.g., ingesting pesticide residues that have been transferred from treated surfaces to the hands or
objects that are mouthed). These children have an urge to mouth objects or their fingers in
exploring their environment, as a sucking reflex, and as a habit (Groot et al., 1998). This route of
exposure may exceed other routes ingestion (i.e., food, pica, drinking water, breast milk) and
dermal exposure because non-dietary ingestion may result in higher ingestion rates of
contaminated material (Weaver et al., 1998). This exposure route is also a difficult route to
model because there is little literature or research that has been performed on mouthing behavior
(Reed et al., 1998) and little information on the susceptibility of children to toxic substances
(Weaver et al., 1998).
Mouthing behavior includes all activities in which objects, including fingers, are touched
by the mouth or put into the mouth except for eating and drinking, and includes licking, sucking,
chewing, and biting (Groot et al., 1998). This exposure route becomes difficult to model because
contact with surfaces is intermittent and nonuniform over different parts of the body. The
intermittent and nonuniform nature of the mouthing itself also makes this pathway difficult to
model (Zartarian et al., 1997).
Children exhibit large differences in mouthing behavior (Groot et al., 1998). Infants are
born with a sucking reflex for breast feeding, and within a few months, children begin to use
sucking or mouthing as a means to explore their surroundings. Children will use both sucking and
licking to explore their environment. Sucking also becomes a means of comforting a child when
they are tired or upset. In addition, teething normally causes substantial mouthing behavior,
sucking or chewing, to alleviate discomfort in their gums. Each child is different, and large
differences occur between children, even within the same family.
Where mouthing becomes critical in exposure to potentially toxic substances is the
proximity and behavior of a small child around potentially contaminated sources. Children play
close to the ground and are constantly licking their fingers or mouthing toys or objects. As a
result, this becomes a potentially significant exposure route for children. They can ingest more
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toxic constituents through this behavior than from dietary ingestion or inhalation because the
children could place wet, sticky fingers on potentially-contaminated surfaces where more toxic
constituents may adhere to the fingers than if the fingers were dry (Gurunathan et al., 1998).
Gurunathan et al. (1998) estimate that young children spend as much as 90 percent of
their days inside, so exposure to contaminants that may infiltrate the home (i.e., volatile and semi-
volatile organic constituents [VOCs and SVOCs]) through the vapor phase may be of concern.
This may be a significant pathway of exposure to SVOCs because these compounds can be
deposited on surfaces in the home or become absorbed onto plastic toys or in stuffed animals
where they can serve as reservoirs for toxic constituents (Gurunathan et al., 1998).
There have been few studies investigating this potential exposure route. The shortage of
research and data may be due to the difficulty in observing very young children and the labor-
intensive effort in gathering the data (U.S. EPA, 1999). The applicable research efforts use two
general approaches to gather data: real-time hand recording in which trained persons observe a
child and manually record information on a survey sheet or score sheet; or, videotaping in which
trained videographers tape a child's activities and subsequently extract the pertinent data manually
or with computer software (U.S. EPA, 1999).
Some researchers express mouthing behavior in terms of frequency of occurrence (e.g.,
contacts/hour, contacts/minute). Others, express mouthing behavior as a rate in units of minutes
per hour of mouthing time. Both approaches have their use in exposure assessments. The former
approach is more appropriate when studying children's behavior during various microactivities.
The latter, however, is more useful when studying children's behavior during macroactivities.
Macroactivities can be described by a child's general activities such as sleeping, watching
television, playing, and eating. Microactivities refer to the specific behavior a child is engaged in
such as hand-to-surface contacts and hand-to-mouth behavior (Hubal, 2000). Time spent in
various macroactivities in several microenvironments (e.g., indoors at home) are presented in
Chapter 9).
6.2 STUDIES RELATED TO NON-DIETARY INGESTION
Groot et al. (1998) - Mouthing Behavior of Young Children - In this study, Groot et al.
(1998) examined the mouthing behavior of infants and young children between the ages of 3 and
36 months in the Netherlands. The study was actually part of a larger effort to determine if PVC
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toys softened with phthalates could pose health risks to children from mouthing. As part of the
effort, Groot et al. (1998) asked parents to observe their children and gather information which
could be used to estimate how often children engage in mouthing and the duration spent mouthing
during a day. Parents were asked to observe their children ten times per day for 15-minute
intervals (i.e., 150 minutes total per day) for two days and measure mouthing with a stopwatch.
In total, 36 parents participated in the study and 42 children were observed by their
parents. For the study, a distinction was made to differentiate between toys meant for mouthing
(e.g., pacifiers, teething rings) and those not meant for mouthing. The time a child spent
mouthing a dummy (e.g., pacifier) was not included in the time recorded. Although the sample
size was relatively small, the results provide a first-order estimate on mouthing times during a day.
Table 6-1 compiles the mouthing times from the Groot et al. (1998) effort. The results show
wide variation. The standard deviation in all four age categories except the 3- to 6-month old
children exceeds the mean time estimated mouthing during a day. The large standard deviations is
not unexpected given the vast behavioral differences from child to child and the small sample size
of the study. The overall trend of the data, however, may be accurate in that it shows that as the
children age, the time spent mouthing decreases. The 3- to 6-month children were estimated to
mouth 37 minutes per day and the 6- to 12-month children 44 minutes per day. After 12 months,
the estimated mouthing time drops quickly to 16 minutes per day for 12- to 18-month children
and 9 minutes per day for 18- to 36-month children.
The study has several limitations that have an impact on the usability of the data. The
initial drawback concerns the small size of the study. Groot et al. (1998) acknowledge this
shortcoming and recommend further study using a larger sample population. In addition, the
study also incorporated mostly higher-educated persons. The area where the study was
performed consisted primarily of parents with higher education. The study had recruited persons
of lower education and socioeconomic levels, but these persons chose not to participate in the
study after recruitment (Groot et al., 1998). Therefore, the results do not reflect data from the
full spectrum of the population. The study also recorded only the time spent mouthing and not
the number of times that mouthing occurred and did not differentiate the types of objects
mouthed. In addition, children were observed for a period of two consecutive days and may not
reflect long-term behavior. The study may not be representative of the U.S. population.
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Reed et al. (1999) - Quantification of Children's Hand and Mouthing Activities through
a Videotaping Methodology - In this study, Reed et al. (1999) used videotaping to quantify the
frequency and type of contacts children have during the course of an hour. The contacts included
numerous categories: hand to clothing, hand to dirt, hand to hand, hand to mouth, hand to object,
object to mouth, hand to smooth surface (e.g., counter tops, table tops), hand to textured surface
(e.g., stuffed animal) (Reed et al., 1999). A total of 30 children were observed in this study.
Children were observed in both day care (20 children 3-6 years old) and residential (10 children 2-
5 years old) settings. Parents and day-care providers were also asked to complete questionnaires
describing the behavior of their children. In addition, the study also differentiated between the
usage of right and left hands.
Over the course of the research, Reed et al. (1999) found that the behavior of children was
similar between the day and residential settings except for the contact rate of hand to smooth
surfaces. Children in residential settings had higher contact rates with smooth surfaces than
children in day care centers. The results of the study are compiled in Table 6-2. The highest
contacts were with object (123 contacts/hr), smooth surfaces (84 contacts/hr), and other (83
contacts/hr). The two lowest contact rates were the hand-to-mouth (9.5 contacts/hr) and object-
to-mouth (16.3 contacts/hr) (Reed et al., 1999). Because the contact rates of hand-to-objects and
smooth surfaces are high, these results indicate that the fingers would appear to provide a
continual dose per hand-to-mouth contact because of constant touching of potentially
contaminated surfaces. Pesticides and other SVOCs are partitioned between the vapor and
deposited phases (e.g., on dust or absorbed on a plastic toy or stuffed animal) such that a child's
fingers, especially if wet from mouthing, will continually be acquiring doses of these types of
constituents (Gurunathan et al., 1998). Reed et al. (1999) also noted that children acted equally
on their environment with both hands with the exception of object-to-mouth behavior. Therefore,
the compiled data are reported as combined right and left hand data. The object-to-mouth
behavior showed a strong preference for the right hand over the left hand for nearly all children
(Reed et al., 1999). The preference ratio for the right hand over the left hand for this category
was 6.8 to 1 (Reed et al., 1999).
The advantages of the Reed et al. (1999) study is that it incorporates a wide variety of
contacts that small children have, not just the hand-to-mouth or object-to-mouth. This
information allows assessors to identify areas or surfaces that may serve as sources for toxic
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constituent transfer. This is especially important for exposure to SVOCs such as pesticides (e.g.,
chlorpyrifos) that have an affinity for absorption onto dust particles, plastic toys, and into the
polyurethane foam (PUF) that is used in many stuffed animals (Gurunathan et al., 1998). Another
strength of this study is the agreement it shows with earlier work by Zartarian et al. (1998) for the
hand to mouth contacts. Some of the shortcomings are the small sample size of the study and the
lack of comment as to the representativeness of the sample population to the U.S. population.
Reed et al. (1999) acknowledge the weakness in regard to the sample size and recommend further
work with a larger population. The study makes no mention of the representativeness of the
sample population or addresses the need for a representative population for any additional study.
Zartarian et al. (1997) - Quantified Dermal Activity Data from a Four-Child Pilot Field
Study - Zartarian et al. (1997) conducted a pilot study of four children of farm workers to
investigate the applicability of using videotaping for gathering information related to children's
interaction with their environment. The evaluation of the videotaping included observation of the
children's contact frequency and duration with objects in their environment, duration spent in
different locations, activity levels, and frequency distributions (Zartarian et al., 1997). As such,
the research was not specifically intended to gather data for non-dietary ingestion; however, the
activities used to evaluate the use of videotaping provide data were for dermal and non-dietary
exposure.
Four Mexican-American farm worker children between the ages of 2.5 and 4.2 years were
videotaped for 33 hours using hand-held cameras over the course of a single day in 1993
(Zartarian et al., 1997). Two girls and two boys were the subject of the videotaping. The
videotaping gathered information on detailed micro-activity patterns of children to be used to
evaluate software for videotaped activities and translation training methods (Zartarian et al.,
1997). The data were also reported by type of object/surface and by hand (i.e., left or right).
Zartarian et al. (1997) present the data for their observations on a per child and per hand
basis. The data suggest that the U.S. EPA (1997) estimate of hand to mouth contact of 1.56
contacts/hr may significantly underestimate the contacts per hour for young children. None of the
children had average contact frequencies for either hand, individually, lower than 3 contacts/hr for
hand to mouth contact, and Zartarian et al. (1997) estimated the average as 9 contacts/hr. As was
reported by Reed et al. (1999), the most frequently contacted objects were toys and hard (i.e.,
smooth) surfaces (Zartarian et al., 1997). Zartarian et al. (1997) report that the average contact
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time with objects is only 2 to 3 seconds and that questionnaires and diaries, therefore, would be
insufficient in gathering that level of activity.
The Zartarian et al. (1997) study has several weaknesses. The sample population is very
small, only four children; however, the work was reported as a pilot study completely
acknowledging that further work was necessary. The effort was intended to evaluate the
methodology of collecting observations, not the contact data itself. So the data are not presented
in a format that can be used to support other research or supply recommended estimates for
contact frequency. This study may not reflect long-term behavior. In addition, the sample
population is not representative of the U.S. population in general because the sample population
consists of only four Mexican-American farm worker children.
Davis (1995), Soil Ingestion in Children with Pica (Final Report), EPA Cooperative
Agreement CR 816334-01 - In 1992, the Fred Hutchinson Cancer Research Center under
Cooperative Agreement with EPA conducted a study to estimate soil intake rates and collect
mouthing behavior data. Originally, the study was designed with two primary purposes: 1) to
describe and quantify the distribution of soil ingestion values in a group of children under the age
of five who exhibit behaviors that would be likely to result in the ingestion of larger than normal
amounts of soil; and 2) to assess and quantify the degree to which soil ingestion varies among
children according to season of the year (summer vs. winter). The study was conducted during
the first four months of 1992 and included 92 children from the Tri-Cities area in Washington
State. These children were volunteers among a group selected through random digit dialing and
their ages ranged between 0 and 48 months. The study was conducted during a period of 7 days.
Since there was no standard methodology to study mouthing behavior, a pretest and a
series of pilot studies were conducted to examine various aspects of the methodology. As a
result of the pilot studies, it was determined that although parents could be taught to conduct
observations using the instrument, the resulting ranking of children according to degree of
mouthing behavior did not correspond very well to the rankings based on observations of the
same children by trained staff observers. Therefore, using parents' observations to select a group
with high mouthing activity was not deemed appropriate. Funding constraints made it impractical
to continue with the original design of screening a large number of children and conducting field
work during two different times of the year.
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The Davis (1995) research recognizes that mouthing behavior is intermittent. Therefore, a
method called "interval method" of observation was used. This method measures both frequency
and duration of the behavior. Under this method, children were observed during 15 second
intervals, during which the mouthing behavior was recorded. Based on the types of behaviors
observed in the testing of the instrument, two mouthing behaviors were selected for the full study.
These included: 1) tongue contacts object; 2) object in mouth. In addition four other behaviors
were included in an attempt to better describe the types of behaviors that would likely result in
soil ingestion: 1) hand touches ground; 2) child repulsed by object in mouth - tries to get it out; 3)
other person stops child's contact with object; and 4) child out of sight or view. In addition to
further characterize potential exposures to soil associated with the three types of mouthing
behaviors, six object categories were included to be used along with the three mouthing
behaviors. These were: 1) hand, finger, or thumb; 2) other body parts, including toes, feet, arms;
3) natural materials, including dirt, sand, rocks, leaves; 4) toys and other objects, including books,
utensils, keys; 5) surfaces, including, window sills, floor, furniture, carpet; and 6) food or drink.
An additional code was added to indicate whether an object was swallowed by the child. The
type of activity the child was engaged in during the observation period was also recorded. In
addition to mouthing behavior data, Davis (1995) collected information about how long the child
spent indoors and outdoors each day, and the general types of outdoor settings in which the child
played.
Mouthing behavior data were collected during a 4-day period. Both trained observers and
one parent observed the children to record mouthing behavior data. Trained observers recorded
mouthing behavior data for 1 hour during active play time, while the parent recorded mouthing
behavior data for the first 15 minutes of that hour.
The basic measure of each type of mouthing activity derived from the observation form
was the percent of time spent in that activity. This measure was defined as the percentage of the
total number of intervals observed that indicate such an activity took place. If there was no
activity in an interval, that interval was excluded. For tabulating the object categories, multiple
instances of the same object in a single interval were counted only once in that interval. Multiple
instances of different objects in a single interval were counted separately under each object
category.
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Based on the mouthing behavior data collected in this study, EPA calculated that during
the period of observation (assumed to be 1 hour) the average mouthing activity was 6.2 minutes
and the average tongue activity was 0.70 minutes. It is important to note that this is based on one
hour of observation. In order to estimate the overall mouthing activity in a day, one would have
to make some assumptions about the amount of time a child is involved in active play time in a
day. These values may also be underestimates because they assume that all the children in the
study were observed for one hour on each of the four days. If this were true, each child would
have a total of 960 intervals of observations (i.e., 3,600 seconds x intervals/15 seconds x 4 days).
The data show that the number of intervals of observation ranged from 80 to 840. It can be
concluded that some children were either observed for less than one hour or less than 4 days.
In order to compare the values estimated by Groot et al. (1998) whose work also used
time as a basis for measuring mouthing activity, it is necessary to multiply the Davis (1995) hourly
estimate by an estimate of how long the children are awake during the day. According to Davis
(1995) small children are awake approximately 8.9 hours per day for ages 0 to 48 months. Based
upon this estimate, the Davis (1995) findings translate into about 55 minutes per day of mouthing
activity and 6 minutes per day of tongue activity. The 55 minutes compares favorably to the 37
minutes and 44 minutes estimated by Groot et al. (1998) for 3- to 6-month and 6- to 12-month
old children, respectively, but is significantly above the 16.4 minutes and 9.3 minutes estimated
for the 12- to 18-month and 18- to 36-month old children, respectively.
EPA also analyzed the mouthing behavior data for 86 children (43 males/43 females)
from the Davis (1995) study. Six children from the original sample size of 92 were excluded from
the analysis because no age information was provided. Total mouthing behavior included both
mouth and tongue contacts with hands, other body parts, surfaces, natural objects, and toys.
Eating events were excluded from the analysis. Statistical analysis was undertaken to determine if
significant differences existed between age and gender. Model results showed that there were no
associations between mouthing frequency and gender. However, a clear relationship was
observed between mouthing frequency and age. Two distinct groups could be identified:
male/female <24 months and male/female > 24 months. Children <24 months exhibited the
highest frequency of mouthing behavior with 76 ฑ 5 contacts/hr (n= 30 subjects; 106
observations). On the other hand, children > 24 months exhibited a lower frequency of mouthing
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behavior with 38 ฑ 3 contacts/hr (n= 56 subjects; 192 observations). These results suggest that as
children grow older, they are less likely to place objects into their mouths.
The Davis (1995) work has both strengths and weaknesses. The strengths of this work
are that it incorporates more children (e.g., 92) in the sample population than any of the other
literature reviewed. In addition, the research is very detailed in defining the parameters and
variables associated with mouthing behavior. The research also gathered information over four
days whereas most of the literature involved only one or two days of observation. Although the
research included the largest sample population of the reviewed literature, 92 sample points is still
a small number considering the wide variability associated with mouthing in children. The random
nature in which the population was selected probably provides a representative population of the
northwest U.S., but not the national population in general. The interval time of 15 seconds would
also appear to be small and potentially easily skewed for those children observed less than an
hour. In addition, most other studies used observation times of 15 minutes to continuous
observation throughout waking hours.
6.3 RECOMMENDATIONS
Due to the paucity of the available research data, it is difficult to recommend with any
degree of certainty estimates for non-dietary ingestion. Table 6-3 summarizes the studies on
mouthing behavior that were described in this chapter. Table 6-4 summarizes the results of these
studies. As mentioned earlier, the studies presented use different units of reporting mouthing
behavior. If the assessor is interested in estimating exposures during macroactivities, then the
total amount of time engaged in mouthing behavior may be the unit of interest. Groot et al.
(1998) is the only study thus far that presents data for infants. These data, as well as the Davis
(1995) study, show that mouthing behavior decreases as children age. Data from both Groot et
al. (1998) and Davis (1995) for children between 3 to 60 months ranged from 9 min/day to 55
min/day with a weighted average of 46 min/day. If the assessor is interested in estimating
exposures to various microactivities, then the number of contacts with hands or objects per unit of
time may be the unit of interest. Reed et al. (1999) and Zartarian (1997) both studied hand-to-
mouth behavior. Although there are uncertainties with the results of these two studies due to
sample size, they are fairly consistent in their results. Based on these two studies, a value of 9
contacts/hour seems to be a reasonable estimate of hand-to-mouth behavior. Reed et al. (1999)
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also studied object-to-mouth frequency. Based on the Reed et al. (1999) and the analysis of the
Davis (1995) data, total mouthing behavior, including hand-to-mouth as well as objects, ranged
from 26 contacts/hour (i.e., 9.5 (hand-to-mouth)+ 16.3 (object-to-mouth)) to 76 contacts/hour
with a weighted average of 45 contacts/hour.
The frequency of contact of finger-to-mouth (9.5 contacts/hr) greatly exceeds the 1.56
contacts/hr for fingers to mouth suggested by the U.S. EPA (1997) in their guidance for
calculating exposure to pesticides. The estimate of 9.5 contacts/hr is close to the 9 contacts/hr
estimated by Zartarian et al. (1997) for a study conducted using video taping as reported by Reed
et al. (1999). The agreement of the two studies suggests that the U.S. EPA (1997) value of 1.56
contacts/hr may significantly underestimate the non-dietary exposure route. Table 6-5 presents
the confidence ratings for the recommended values.
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6.4
REFERENCES FOR CHAPTER 6
Davis (1995). Soil Ingestion in Children with Pica (Final Report), EPA Cooperative Agreement CR 816334-01
Groot M., Lekkerkerk M., Steenbekkers L. (1998) Mouthing behavior of young children - an
observational study. H&C onderzoeksraport 3.
Gurunathan S., Robson M., Freeman N., Buckley B., Roy A., Meyer R., Bukowski J., and Lioy P. (1998)
Accumulation of chloropyrifos on residential surfaces and toys accessible to children. Environ. Health
Pers. 106( 1) :9-16.
Hubal, E.A.; Sheldon, L.S.; Burke, J.M.; McCurdy, T.R.; Berry, M.R.; Rigas, M.L.; Zartarian, V.G.
(2000) Children's exposure assessment: A review of factors influencing children's exposure, and the
data available to characterize and assess that exposure. Prepared by U.S. Environmental Protection
Agency, National Exposure Research Laboratory, RTP, NC.
Reed K., Jimenez M., Freeman N., and Lioy P. (1999) Quantification of children's hand and mouthing
activities through a videotaping methodology. JEAEE. 9:513-520.
U.S. EPA (1997) Standard operating procedures (SOPs) for residential exposure assessment. Washington,
DC: Office of Pesticide Programs.
U.S. EPA, National Exposure Research Laboratory. (1999) Children's exposure assessment: A review of
factors influencing children's exposure, and the data available to characterize and assess that exposure.
Weaver V., Buckley T., and Groopman J. (1998) Approaches to environmental exposure assessment in
children. Environ. Health Pers. 106(3):827-831
Zartarian V., Ferguson A., and Leckie J. (1997) Quantified dermal activity data from a four-child pilot
field study. JEAEE 7(4):543-553.
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1 Table 6-1. Extrapolated Total Mouthing Times Minutes per Day (time awake)
2
3
4 Age (months) No. Children Mean Standard Dev. Minimum Maximum
5 3 - 6 5 36.9 19.1 14.5 67
6 6- 12 14 44 44.7 2.4 171.5
7 12 - 18 12 16.4 18.2 0 53.2
8 18-36 U 93 9_8 0 30.9
9
10 Note: The object most mouthed in all age groups in the fingers except for the 6 - 12 month group which
11 mostly mouthed on toys.
12
13 Source: Groot et al. (1998)
14
15
16
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Table 6-2. Frequency of Contact, by Contact Variable Contacts per Hour
Variable
Mean
Median
Minimum
Maximum
90th Percentile
Clothing
66.6
65
22.8
129.2
103.3
Dirt
11.4
0.3
0
146.3
56.4
Hand
21.1
14.2
6.3
116.4
43.5
Hand to mouth
9.5
8.5
0.4
25.7
20.1
Object
122.9
118.7
56.2
312
175.8
Object to mouth
16.3
3.6
0
86.2
77.1
Other
82.9
64.3
8.3
243.6
199.6
Smooth surface
83.7
80.2
13.6
190.4
136.9
Textured surface
22.1
16.3
0.2
68.7
52.2
Source: Reed et al. (1999)
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Table 6-3. Summary of Studies on Mouthing Behavior
3 Study Population Size Population Studies
4
Grootetal. 1998
42
3-36 months in Netherlands
children from well educated
parents
5
Reed et al. 1999
30
20 children 3-6 years
10 children 2-5 years
Day care and residential settings
6
Zartarian 1997
4
2.5-4.2 years
children of farm workers
7
Davis 1995
92
10-60 months
Washington State
8
9
10
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Table 6-4. Summary of Mouthing Frequency Data
Age (months)
Mouthing Frequency/Time
Population Size
Reference
3-6
6-12
12-18
18-36
2-6 years
2.5-4.2 years
10-60
<24
>24
1 min/day 5
44 min/day 14
16 min/day 12
9 min/day 11
9.5 contacts/hr (hand to mouth) 30
16.3 contacts/hr (object to mouth)
9 contacts/hr 4
55 min/day 92
76 ฑ5 contacts/hr 30
38 ฑ3 contacts/hr 56
Groot et al. 1998
Reedetal. 1999
Zartarian 1997
EPA analysis of
Davis 1995
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Table 6-5. Confidence in Mouthing Behavior Recommendations
Considerations
Rationale
Rating
Study Elements
Peer Review
Three of the studies are from peer review journals, one
from a contractor's report to EPA
Medium
Accessibility
Studies in journals have wide circulation.
Contractor's report only available through EPA
Medium
Reproducibility
Cannot reproduce the data unless raw data are provided.
Medium
Focus on factor of Interest
Studies focused on mouthing behavior as well as other
hand contacts.
High
Data pertinent to U.S.
Studies were conducted in the U.S.
High
Primary data
Analyses were done on primary data. EPA did the
analysis of the raw data from David et al. 1995.
High
Currency
Recent studies were evaluated
High
Adequacy of data collection
period
Data were collected for a period of several days, not
enough to represent seasonal variations.
Medium
Validity of Approach
Measurements were made by observation methods. Both
surveys and videotaping were used. Videotaping
techniques may be more reliable, but resource intensive.
Medium
Representativeness of the
population
An effort was made to consider age and gender (in the
Davis study), but sample size was too small.
Low
Characterization of variability
An effort was made to consider age and gender, data for
infants is fairly limited.
Low
Lack of bias in study design
Subjects were selected from volunteers.
Medium
Measurement error
Measuring children's behavior is difficult and somewhat
subjective and depends on the experience of the observer.
Medium
Other Elements
Number of studies
Four studies were evaluated
Medium
Agreement between researchers
There is general agreement among the researchers.
High
Overall Rating
Although there are four studies, they have very small
sample size, variability in the population cannot be
assessed. Variation in behavior due to seasons cannot be
evaluated. Measuring children's behavior is difficult.
Low/Medium
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TABLE OF CONTENTS
7. INHALATION ROUTE 7-1
7.1 INTRODUCTION 7-1
7.2 INHALATION RATE STUDIES 7-1
7.3 RECOMMENDATIONS 7-7
7.4 REFERENCES FOR CHAPTER 7 7-9
APPENDIX 7A VENTILATION DATA 7A-1
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LIST OF TABLES
Table 7-1. Calibration And Field Protocols For Self-monitoring of Activities
Grouped by Subject Panels 7-10
Table 7-2. Subject Panel Inhalation Rates by Mean VR, Upper
Percentiles, And Self-estimated Breathing Rates 7-10
Table 7-3. Distribution of Predicted Intake Rates by Location And Activity Levels
For Elementary And High School Students 7-11
Table 7-4. Average Hours Spent Per Day in a Given Location and Activity
Level For Elementary (EL) and High School (HS) Students 7-11
Table 7-5. Distribution Patterns of Daily Inhalation
Rates For Elementary (EL) And High School (HS)
Students Grouped by Activity Level 7-12
Table 7-6. Summary of Average Inhalation Rates (M3/hr) by Age Group And Activity Levels
For Laboratory Protocols 7-13
Table 7-7. Summary of Average Inhalation Rates (M3/hr) by
Age Group And Activity Levels in Field Protocols 7-14
Table 7-8. Comparisons of Estimated Basal Metabolic Rates (BMR) With Average Food-energy
Intakes For Individuals Sampled in The 1977-78 NFCS 7-15
Table 7-9. Daily Inhalation Rates Calculated From
Food-energy Intakes 7-16
Table 7-10. Daily Inhalation Rates Obtained From The Ratios
Of Total Energy Expenditure to Basal Metabolic Rate (BMR) 7-17
Table 7-11. Inhalation Rates For Short-term Exposures 7-18
Table 7-12. Confidence in Inhalation Rate Recommendations 7-19
Table 7-13. Summary of Recommended Values For Inhalation 7-20
Table 7-14. Summary of Children's Inhalation Rates
For Short-Term Exposure Studies 7-21
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7. INHALATION ROUTE
7.1 INTRODUCTION
This chapter presents data and recommendations for inhalation rates that can be used to
assess children's exposure to contaminants in air. Children may be more highly exposed to
environmental toxicants through inhalation routes than adults. Infants and young children have a
higher resting metabolic rate and rate of oxygen consumption per unit body weight than adults
because they have a larger cooling surface per unit body weight and because they are growing
rapidly. The oxygen consumption of a resting infant aged between one week and one year is 7
ml/kg body weight per minute. The rate for an adult under the same conditions is 3-5 ml/kg per
minute (WHO 1996). Thus, the volume of air passing through the lungs of a resting infant is
twice that of a resting adult under the same conditions and therefore twice as much of any
chemical in the atmosphere could reach the lungs of an infant. The recommended inhalation rates
for children are summarized in Section 7.3.
7.2 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 (03) in their daily
activities in the Los Angeles area. The population surveyed consisted of several panels of both
adults and children. The panels consisting of children included: 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 6: 13 young asthmatics (7 males, 6 females, ages
11-16 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, ventilation rate (VR), breathing rate, and heart rate (HR) were
measured simultaneously at each exercise level. From the calibration data an equation was
developed using linear regression analysis to predict VR from measured HR (Linn et al., 1992).
In the field study, each subject recorded in diaries: their daily activities, change in
locations (indoors, outdoors, or in a vehicle), self-estimated breathing rates during each
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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. 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 7-1 presents the calibration and field protocols for self-monitoring of activities for each
subject panel.
Table 7-2 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 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). Linn et al. (1992) reported that the diary data
showed that most individuals 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, (Table 7-2).
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 both healthy and asthmatic children.
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
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(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 7-3 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 (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 7-4). Based on the
data presented in Tables 7-3 and 7-4, the average activity-specific inhalation rates for elementary
(10-12 years) and high school (13-17 years) students were calculated in Table 7-5. For
elementary school students, the average daily inhalation rates (based on indoor and outdoor
locations) are 15.8 m3/day for light activities, 4.62 m3/day for moderate activities, and
0.98 m3/day for heavy activities. For high school students the daily inhalation rates for light,
moderate, and heavy activities are estimated to be 16.4 m3/day, 3.1 m3/day, and 0.54 m3/day,
respectively (Table 7-5).
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: breathing frequency (fB) and oxygen
consumption (VQ2). A total of 160 subjects participated in the primary study. For children, there
were two age dependent groups: (1) children 6 to 12.9 years old, (2) adolescents between 13 and
18.9 years old, (Adams, 1993). An additional 40 children from 6 to 12 years old and 12 young
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children from 3 to 5 years old were identified as subjects for pilot testing purposes (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 V02 (oxygen consumption). Measurements were taken in
the last 5 minutes of each phase of the resting protocol, and the last 3 minutes of the 6 minute
intervals at each speed designated in the active protocols.
In the field, all children completed spontaneous play protocols, while the older adolescent
population (16-18 years) completed car driving and riding, car maintenance (males), and
housework (females) protocols.
During all activities in either the laboratory or field protocols, IR for the children's group
revealed no significant gender differences. Therefore, IR data presented in Appendix Tables 7A-1
and 7A-2 were categorized as young children, children (no gender) by activity levels (resting,
sedentary, light, moderate, and heavy). These categorized data from the Appendix tables are
summarized as IR in m3/hr in Tables 7-6 and 7-7. The laboratory protocols are shown in
Table 7-6. Table 7-7 presents the mean inhalation rates by group and activity levels (light,
sedentary, and moderate) in field protocols. 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:
BSA = Height^0425) x Weight^0425) x 71.84 (7-1)
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
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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.
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:
Vg = E x H x VQ (7-2)
where:
VE = ventilation rate (L/min or m3/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 production of 1 kilojoule (KJ) of energy
expended (L/KJ or m3/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 7-8) are based on approximately
30,000 individuals and were obtained from the USDA 1977-78 Nationwide Food Consumption
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Survey (USDA-NFCS). The food energy intakes were 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 02/KJ
which was determined 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 7-9.
Table 7-9 presents the daily inhalation rate for each age/gender cohort. The highest daily
inhalation rates were reported for children between the ages of 6-8 years (10 m3/day), for males
between 15-18 years (17 m3/day), and females between 9-11 years (13 m3/day). 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 7-9. These data for active and
inactive inhalation rates are also presented in Table 7-9. For children, inactive and active
inhalation rates ranged between 2.35 and 5.95 m3/day and 6.35 to 13.09 m3/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 the 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 7A-3. The data
obtained from the second approach are presented in Table 7-10. Inhalation rates for children
(6 months - 10 years) ranged from 7.3-9.3 m3/day for male and 5.6 to 8.6 m3/day for female
children, and for older children (10-18 years), inhalation rates were 15 m3/day for males and 12
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m3/day for females. These rates are similar to the daily inhalation rates obtained using the first
approach. Also, the inactive inhalation rates obtained from the first approach are lower than the
inhalation rates obtained using the second approach. This may be attributed to the BMR
multiplier employed in the equation of the second approach to calculate inhalation rates.
Inhalation rates were also obtained for 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 7-11.
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.
7.3 RECOMMENDATIONS
The recommended inhalation rates for children are based on the studies described in this
chapter. Different survey designs and populations were utilized in the studies described in this
Chapter. Excluding the study by Layton (1993), the population surveyed in all of the 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 confidence ratings and recommended inhalation rates are presented in
Tables 7-12 and 7-13, respectively. Based on the study results from Layton (1993), the
recommended daily inhalation rate for infants (children less than 1 yr), during long-term dose
assessments is 4.5 m3/day. For children 1-2 years old, 3-5 years old, and 6-8 years old, the
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recommended daily inhalation rates are 6.8 m3/day, 8.3 m3/day, and 10 m3/day, respectively.
Recommended values for children aged 9-11 years are 14 m3/day for males and 13 m3/day for
females. For children aged 12-14 years and 15-18 years, the recommended values are shown in
Table 7-13.
Recommended short-term inhalation rates for children aged 18 years and under are also
summarized in Table 7-13. The short-term inhalation rates were calculated by averaging the
inhalation rates for each activity level from the various key studies (Table 7-14). The
recommended average hourly inhalation rates are as follows: 0.3 m3/hr during rest; 0.4 m3/hr for
sedentary activities; 1.0 m3/hr for light activities; 1.2 m3/hr for moderate activities; and 1.9 m3/hr
for heavy activities. The recommended short-term exposure data also include infants (less than
1 yr).
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7.4 REFERENCES FOR CHAPTER 7
Adams, W.C. (1993) Measurement of breathing rate and volume in routinely performed daily activities, Final
Report. California Air Resources Board (CARB) Contract No. A033-205. June 1993. 185 pgs.
Basiotis, P.P.; Thomas, R.G.; Kelsay, J.L.; Mertz, W. (1989) Sources of variation in energy intake by men and
women as determined from one year's daily dietary records. Am. J. Clin. Nutr. 50:448-453.
Layton, D.W. (1993) Metabolically consistent breathing rates for use in dose assessments. Health Physics
64(l):23-36.
Linn, W.S.; Shamoo, D.A.; Hackney, J.D. (1992) Documentation of activity patterns in "high-risk" groups exposed
to ozone in the Los Angeles area. In: Proceedings of the Second EPA/AWMA Conference on
Tropospheric Ozone, Atlanta, Nov. 1991. pp. 701-712. Air and Waste Management Assoc., Pittsburgh,
PA.
Spier, C.E.; Little, D.E.; Trim, S.C.; Johnson, T.R.; Linn, W.S.; Hackney, J.D. (1992) Activity patterns in
elementary and high school students exposed to oxidant pollution. J. Exp. Anal. Environ. Epid. 2(3):277-
293.
WHO (1986) Principles for evaluating health risks from chemicals during infancy and early childhood: the need
for a special approach. Environmental Health Criteria 59, World Health Organization, International
Programme on Chemical Safety.
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33
34
35
Table 7-1. Calibration And Field Protocols For Self-monitoring of Activities
Grouped by Subject Panels
Panel
Calibration Protocol
Field Protocol
Panel 2 - Healthy Elementary
School Students - 5 male,
12 female, age 10-12
Panel 3 - Healthy High School
Students - 7 male, 12 female,
age 13-17
Panel 6 - Young Asthmatics -
7 male, 6 female, age 11-16
Outdoor exercises each consisted of
20 minute rest, slow walking,
jogging and fast walking
Outdoor exercises each consisted of
20 minute rest, slow walking,
jogging and fast walking
Laboratory exercise tests on bicycles
and treadmills
Saturday, Sunday and Monday (school
day) in early autumn; HR recordings
and activity diary during waking
hours and during sleep.
Same as Panel 2, however, no HR
recordings during sleep for most
subjects.
Similar to Panel 4, summer
monitoring for 2 successive weeks,
including 2 controlled exposure
studies with few or no observable
respiratory effects.
Source: Linn et al., 1992
Table 7-2. Subject Panel Inhalation Rates by Mean VR, Upper
Percentiles, And Self-estimated Breathing Rates
Inhalation Rates (m3/hr)
N1' Mean VR 99th Mean VR at Activity Levels
(m3/hr) Percentile VR (m3/hr)b
Panel Slow Medium Fast
Healthy
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
Asthmatics
6 - Elementary and High School 13 1.20 2.40 1.20 1.20 1.50
Students
"Number of individuals in each survey panel.
bSome 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).
Source: Linn et al. (1992).
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23
24
25
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32
33
34
35
Table 7-3. Distribution of Predicted Intake Rates by Location And Activity Levels
For Elementary And High School Students
Inhalation Rates (m3/hr)
Percentile Rankingsb
Age (yrs)
Student
Location
Activity
Level
% Recorded
Time1
Mean ฑ SD
pt
50th
99.9th
10-12
Elc
(nd=17)
Indoors
slow
medium
fast
49.6
23.6
2.4
0.84 ฑ0.36
0.96 ฑ0.42
1.02 ฑ0.60
0.18
0.24
0.24
0.78
0.84
0.84
2.34
2.58
3.42
Outdoors
slow
medium
fast
8.9
11.2
4.3
0.96 ฑ0.54
1.08 ฑ0.48
1.14 ฑ0.60
0.36
0.24
0.48
0.78
0.96
0.96
4.32
3.36
3.60
13-17
HSC
(nd=19)
Indoors
slow
medium
fast
70.7
10.9
1.4
0.78 ฑ0.36
0.96 ฑ0.42
1.26 ฑ0.66
0.30
0.42
0.54
0.72
0.84
1.08
3.24
4.02
6.84c
Outdoors
slow
medium
fast
8.2
7.4
1.4
0.96 ฑ0.48
1.26 ฑ0.78
1.44 ฑ 1.08
0.42
0.48
0.48
0.90
1.08
1.02
5.28
5.70
5.94
Recorded time averaged about 23 hr per elementary school student and 33 hr. per high school student,
over 72-hr. periods.
bGeometric means closely approximated 50th percentiles; geometric standard deviations were 1.2-1.3 forHR,
1.5-1.8 for VR.
CEL = elementary school student; HS = high school student.
dN = number of students that participated in survey.
eHighest single value.
Source: Spier et al. (1992).
Table 7-4. Average Hours Spent Per Day in a Given Location and Activity
Level For Elementary (EL) and High School (HS) Students
Student
(EL\ nc=17; HSb,
Nc=19)
Location
Activity Level
Slow Medium
Fast
Total Time Spent
(hrs/day)
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.
bHigh school (HS) students were between 13-17 years old.
CN corresponds to number of school students.
Source: Spier et al. (1992).
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22
Table 7-5. Distribution Patterns of Daily Inhalation
Rates For Elementary (EL) And High School (HS)
Students Grouped by Activity Level
Percentile Rankings
Students
Age
(yrs)
Location
Activity type"
Mean IRb
(m3/day)
1st
50th
99.9th
EL
10-12
Indoor
Light
13.7
2.93
12.71
38.14
(nc=17)
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
13-17
Indoor
Light
15.2
5.85
14.04
63.18
(n=19)
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
Tor this report, activity type presented in Table 7-2 was redefined as light activity for slow, moderate activity
for medium, and heavy activity for fast.
bDaily inhalation rate was calculated by multiplying the hours spent at each activity level (Table 7-4) by the
corresponding inhalation rate (Table 7-3).
cNumber of elementary (EL) and high school students (HS).
Source: Adapted from Spier et al. (1992) (Generated using data from Tables 7-3 and 7-4).
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Table 7-6. Summary of Average Inhalation Rates (M3/hr) by Age Group And Activity Levels
For Laboratory Protocols
Age Group
Restingฎ
Sedentaryb
Light0
Moderated
Heavy6
Young Childrenf
0.37
0.40
0.65
DNPg
DNP
Children11
0.45
0.47
0.95
1.74
2.23
"Resting defined as lying (see Appendix Table 7A-1 for original data).
bSedentary defined as sitting and standing (see Appendix Table 7A-1 for original data).
cLight defined as walking at speed level 1.5 - 3.0 mph (see Appendix Table 7A-1 for original data).
dModerate defined as fast walking (3.3 - 4.0 mph) and slow running (3.5 - 4.0 mph) (see Appendix Table 7A-1
for original data).
eHeavy defined as fast running (4.5 - 6.0 mph) (see Appendix Table 7A-1 for original data).
'Young children (both genders) 3 - 5.9 yrs old.
BDNP. Group did not perform this protocol or N was too small for appropriate mean comparisons. All young
children did not run.
hChildren (both genders) 6 - 12.9 yrs old.
Source: Adapted from Adams (1993).
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21
Table 7-7. Summary of Average Inhalation Rates (M3/hr) by
Age Group And Activity Levels in Field Protocols
Age Group
Light"
Sedentaryb
Moderate'
Young Childrend
Childrenf
DNPe
DNP
DNP
DNP
0.68
1.07
"Light activity was defined as car maintenance (males), housework (females), and yard work (females) (see
Appendix Table 7A-2 for original data).
bSedentary activity was defined as car driving and riding (both genders) (see Appendix Table 7A-2 for original
data).
cModerate activity was defined as mowing (males); wood working (males); yard work (males); and play
(children) (see Appendix Table 7A-2 for original data).
dYoung children (both genders) = 3 - 5.9 yrs old.
eDNP. Group did not perform this protocol or N was too small for appropriate mean comparisons.
fChildren (both genders) = 6 - 12.9 yrs old.
Source: Adams (1993).
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Table 7-8.
Comparisons of Estimated Basal Metabolic Rates (BMR) With Average Food-energy Intakes For
2
3
Individuals Sampled in The 1977-78 NFCS
4
BMRa
Energy Intake (EFD)
5
Cohort/Age
Body Weight
MJ d"lb
kcal d"lc
MJd"1
kcal d"1
Ratio
6
(years)
kg
EFD/BMR
7
Children
8
Under 1
7.6
1.74
416
3.32
793
1.90
9
1 to 2
13
3.08
734
5.07
1209
1.65
10
3 to 5
18
3.69
881
6.14
1466
1.66
11
6 to 8
26
4.41
1053
7.43
1774
1.68
12
Males
13
9 to 11
36
5.42
1293
8.55
2040
1.58
14
12 to 14
50
6.45
1540
9.54
2276
1.48
15
15 to 18
66
7.64
1823
10.8
2568
1.41
16
Females
17
9 to 11
36
4.91
1173
7.75
1849
1.58
18
12 to 14
49
5.64
1347
7.72
1842
1.37
19
15 to 18
56
6.03
1440
7.32
1748
1.21
20
Calculated from the appropriate age and gender-based BMR equations given in
Appendix Table 7A-3.
21
bMJ d"1 - mega joules/day
22
Ckcal d"1 - kilo calories/day
23
24
Source: Layton (1993).
25
26
27
28
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36
37
38
39
40
41
42
43
44
Table 7-9. Daily Inhalation Rates Calculated From
Food-energy Intakes
METb
Value
Inhalation Rates
Cohort/Age
Daily Inhalation Ratea
(h) Sleep
Inactive0
Active0
(years)
Ld
(m3/day)
(h)
Ae
Ff
(m3/day)
(m3/day)
Children
<1
1
4.5
11
1.9
2.7
2.35
6.35
1 -2
2
6.8
11
1.6
2.2
4.16
9.15
3 -5
3
8.3
10
1.7
2.2
4.98
10.96
00
1
3
10
10
1.7
2.2
5.95
13.09
Males
9 - 11
3
14
9
1.9
2.5
7.32
18.3
12 - 14
3
15
9
1.8
2.2
8.71
19.16
15 - 18
4
17
8
1.7
2.1
10.31
21.65
Females
9 - 11
3
13
9
1.9
2.5
6.63
16.58
12 - 14
3
12
9
1.6
2.0
7.61
15.20
15 - 18
4
12
8
1.5
1.7
8.14
13.84
Daily inhalation rate was calculated by multiplying the EFD values (see Table 7-10) by H x VQ x
(m3 1,000 L"1) for subjects under 9 years of age and by 1.2 x H x VQ x (m3 1,000 L"1) (for subjects 9 years of
age and older (see text for explanation).
Where:
EFD = Food energy intake (Kcal/day) or (MJ/day)
H = Oxygen uptake = 0.05 L02/KJ or 0.21 L02/Kcal
VQ = Ventilation equivalent = 21 = geometric mean of VQs (unitless)
bMET = Metabolic equivalent
Inhalation rate for inactive periods was calculated as BMR x H x VQ x (d 1,440 min"1) and for active periods by
multiplying inactive inhalation rate by F (See footnote f); BMR values are from Table 7-10.
Where:
BMR = Basal metabolic rate (MJ/day) or (kg/hr)
dL is the number of years for each age cohort.
Tor individuals 9 years of age and older, A was calculated by multiplying the ratio for EFD/BMR (unitless)
(Table 7-10) by the factor 1.2 (see text for explanation).
rF = (24A - S)/(24 - S) (unitless), ratio of the rate of energy expenditure during active hours to the estimated
BMR (unitless)
Where:
S = Number of hours spent sleeping each day (hrs)
Source: Layton (1993).
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8
9
10
11
12
13
14
15
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17
18
19
20
21
22
23
24
25
26
27
28
Table 7-10. Daily Inhalation Rates Obtained From The Ratios
Of Total Energy Expenditure to Basal Metabolic Rate (BMR)
Gender/Age
Body Weighf
BMRb
H
Inhalation Rate, VE
(yrs)
(kg)
(MJ/day)
VQ
Ac
(m302/MJ)
(m3/day)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
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
Body weight was based on the average weights for age/gender cohorts in the U.S. population.
bThe BMRs (basal metabolic rate) are calculated using the respective body weights and BMR equations (see
Appendix Table 7A-3).
The values of the BMR multiplier (EFD/BMR) for those 18 years and older were derived from the Basiotis
et al. (1989) study: Male = 1.59, Female = 1.38. For males and females under 10 years old, the mean BMR
multiplier used was 1.6. For males and females aged 10 to < 18 years, the mean values for A given in
Table 7-11 for 12-14 years and 15-18 years, age brackets for males and females were used: male = 1.7 and
female =1.5.
dInhalation rate = BMR x A x H x VQ; VQ = ventilation equivalent and H = oxygen uptake.
Source: Layton (1993).
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20
21
22
23
24
25
26
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30
Table 7-11. Inhalation Rates For Short-term Exposures
Activity Type
Rest
Sedentary
Light
Moderate
Heaw
MET (BMR Multiplier)
1
1.2
2C
4d
10e
Gender/Age
(yrs)
Weight
(kg)a
BMRb
(MJ/day)
Inhalation Rate (m3/hr)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
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 3?
0 38
0 66
1 96
3 18
Body weights were based on average weights for age/gender cohorts of the U.S. population
bThe BMRs for the age/gender cohorts were calculated using the respective body weights and the BMR
equations (Appendix Table 7A-3).
cRange of 1.5 - 2.5.
dRange of 3 - 5.
eRange of >5 - 20.
fThe 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)
gOriginal data were presented in L/min. Conversion to mVhr was obtained as follows:
Source: Layton (1993).
60 min
hr
m
1000L
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27
Table 7-12. Confidence in Inhalation Rate Recommendations
Considerations
Rationale
Rating
Study Elements
Peer Review
Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data collection
period
Validity of approach
Representativeness of the
population
Characterization of variability
Lack of bias in study design
Measurement error
Other Elements
Number of studies
Agreement between researchers
Overall Rating
Studies are from peer reviewed journal articles and an High
EPA peer reviewed report.
Studies in journals have wide circulation. High
EPA reports are available from the National Technical
Information Service.
Information on questionnaires and interviews were not Medium
provided.
Studies focused on ventilation rates and factors High
influencing them.
Studies conducted in the U. S. High
Both data collection and re-analysis of existing data Medium
occurred.
Recent studies were evaluated. High
Effort was made to collect data over time. High
Measurements were made by indirect methods. Medium
An effort has been made to consider age and gender, but Medium
not systematically. Sample size was too small.
An effort has been made to address age and gender, but High
not systematically.
Subjects were selected randomly from volunteers and High
measured in the same way.
Measurement error is well documented by statistics, but Medium
procedures measure factor indirectly.
Five key studies and six relevant studies were evaluated.
There is general agreement among researchers using High
different experimental methods.
Several studies exist that attempt to estimate inhalation Medium
rates according to age, gender and activity.
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2
Table 7-13. Summary of Recommended Values For Inhalation
3
Population
Mean
Upper Percentile
4
Long-term Exposures
5
Infants
6
<1 year
4.5 m3/day
7
8
Children
9
1-2 years
6.8 m3/day
10
3-5 years
8.3 m3/day
...
11
6-8 years
10 m3/day
...
12
9-11 years
13
males
14 m3/day
14
females
13 m3/day
15
12-14 years
16
males
15 m3/day
17
females
12 m3/day
18
15-18 years
19
males
17 m3/day
20
females
12 m3/day
...
21
Short-term Exposures
22
Children (18 years and under)
23
Rest
0.3 m3/hr
24
Sedentary Activities
0.4 m3/hr
25
Light Activities
1.0 m3/hr
26
Moderate Activities
1.2 m3/hr
27
Heavy Activities
1.9 m3/hr
...
28
29
30
31
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Table 7-14. Summary of Children's Inhalation Rates
For Short-Term Exposure Studies
Arithmetic Mean (m3/hr)
Activity Level
Rest
Sedentary
Light
Moderate
High
Reference
0.4
0.4
0.8
0.9
--
Adams, 1993 (Lab protocols)
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)
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1 APPENDIX 7A
2
3
4 VENTILATION DATA
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1 TABLE 7A-1. Mean Minute Ventilation (Ve, L/min) by Group
2 And Activity for Laboratory Protocols
3
Activity
Young Childrenฎ
Children
4
Lying
6.19
7.51
5
Sitting
6.48
7.28
6
Standing
6.76
8.49
7
Walking
1.5 mph
10.25
DNP
1.875 mph
10.53
DNP
2.0 mph
DNP
14.13
2.25 mph
11.68
DNP
2.5 mph
DNP
15.58
3.0 mph
DNP
17.79
3.3 mph
DNP
DNP
4.0 mph
DNP
DNP
8
Running
3.5 mph
DNP
26.77
4.0 mph
DNP
31.35
4.5 mph
DNP
37.22
5.0 mph
DNP
DNP
6.0 mph
DNP
DNP
9 "Young Children, male and female 3-5.9 yr olds; Children, male and female 6-12.9 yr olds; Adult Females,
10 adolescent, young to middle-aged, and older adult females; Adult Males, adolescent, young to middle-aged,
11 and older adult males; DNP, group did not perform this protocol or N was too small for appropriate mean
12 comparisons
13
14 Source: Adams (1993).
15
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TABLE 7A-2.
Mean Minute Ventilation (Ve, L/min) by Group
2
and Activity for Field Protocols
3
Activity
Young Childrenฎ
Children
4
Play
11.31
17.89
5
Car Driving
DNP
DNP
6
Car Riding
DNP
DNP
7
Yardwork
DNP
DNP
8
Housework
DNP
DNP
9
Car Maintenance
DNP
DNP
10
Mowing
DNP
DNP
11
Woodworking
DNP
DNP
12
"Young Children, male and female 3-5.9 yr olds; Children, male and female 6-12.9 yr olds; Adult Females,
13
adolescent, young to middle-aged, and older adult females; Adult Males, adolescent, young to middle-aged,
14
and older adult males; DNP, group did not perform this protocol or N was too small for appropriate mean
15
comparisons;
16
17
Source: Adams (1993).
18
TABLE 7A-3. Statistics of the Age/gender Cohorts Used
19
To Develop Regression Equations for Predicting
20
Basal Metabolic Rates (BMR)
21
Body
22
Gender/Age
BMR
Weight
23
(y)
MJd"1
ฑSD
CVa (kg)
Nb
BMR Equation0
rd
24
Males
25
Under 3
1.51
0.918
0.61 6.6
162
0.249 bw-0.127
0.95
26
3 to < 10
4.14
0.498
0.12 21
338
0.095 bw +2.110
0.83
27
10 to < 18
5.86
1.171
0.20 42
734
0.074 bw + 2.754
0.93
28
Females
29
Under 3
1.54
0.915
0.59 6.9
137
0.244 bw-0.130
0.96
30
3 to < 10
3.85
0.493
0.13 21
413
0.085 bw + 2.033
0.81
31
10 to < 18
5.04
0.780
0.15 38
575
0.056 bw +2.898
0.8
32
Coefficient of variation (SD/mean)
33
bN = number of subjects
34
cBody weight (bw) in kg
35
Coefficient of correlation
36
37
Source: Layton (1993).
38
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TABLE OF CONTENTS
8. DERMAL ROUTE 8-1
8.1 INTRODUCTION 8-1
8.2 SURFACE AREA 8-2
8.2.1 Background 8-2
8.2.2 Measurement Techniques 8-2
8.2.3 Body Surface Area Studies 8-3
8.2.4 Application of Body Surface Area Data 8-7
8.3 SOIL ADHERENCE TO SKIN 8-8
8.3.1 Background 8-8
8.3.2 Soil Adherence to Skin Studies 8-9
8.4 RECOMMENDATIONS 8-12
8.4.1 Body Surface Area 8-12
8.4.2 Soil Adherence to Skin 8-13
8.5 REFERENCES FOR CHAPTER 8 8-15
APPENDIX 8A - Formulae for Total Body Surface Area 8A-1
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LIST OF TABLES
Table 8-1. Total Body Surface Area of Male
Children in Square Metersฎ 8-17
Table 8-2. Total Body Surface Area of Female
Children in Square Metersฎ 8-18
Table 8-3. Percentage of Total Body Surface Area by Body Part For Children 8-19
Table 8-4. Descriptive Statistics For Surface Area/body Weight (Sa/bw) Ratios (M2/kg) . . . 8-20
Table 8-5. Clothing choices and assumed body surface areas exposed 8-21
Table 8-6. Estimated skin surface exposed during warm weather outdoor play for children
under age 5 (based on SCS-I data) 8-21
Table 8-7. Number and percentage of respondents with children and those reporting outdoor
playa activities in both warm and cold weather 8-22
Table 8-8. Play frequency and duration for all child players (from SCS-II data) 8-22
Table 8-9. Hand washing and bathing frequency for all child players (from SCS-II data) . . . 8-23
Table 8-10. NHAPS and SCS-II play durationฎ comparison 8-23
Table 8-11. NHAPS and SCS-II hand wash frequency comparison 8-24
Table 8-12. Summary of Field Studies 8-25
Table 8-13. Geometric Mean And Geometric Standard Deviations of
Soil Adherence by Activity And Body Region 8-26
Table 8-14. Summary of Groups Assayed in Round 2 of Field Measurements 8-27
Table 8-15. Attire for Individuals within Children's Groups Studied 8-28
Table 8-16. Geometric Means (Geometric Standard Deviations) of Round 2 Post-activity
Loadings 8-29
Table 8-17. Summary of Controlled Green House Trials - Children Playing 8-30
Table 8-18. Preactivity Loadings Recovered from Greenhouse Trial Children Volunteers .. 8-31
Table 8-19. Summary of Recommended Values For Skin Surface Area 8-33
Table 8-20. Confidence in Body Surface Area Measurement Recommendations 8-34
Table 8-21. Confidence in Soil Adherence to Skin Recommendations 8-35
LIST OF FIGURES
Figure 8-1. Schematic of Dose and Exposure: Dermal Route 8-2
Figure 8-2. Skin Coverage as Determined by Fluorescence vs. Body Part for Adults
Transplanting Plants and for Children Playing in Wet Soils 8-32
Figure 8-3. Gravimetric Loading vs. Body Part for Adult Transplanting Plants in Wet Soil
and for Children Playing in Wet and Dry Soils 8-32
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8. DERMAL ROUTE
8.1 INTRODUCTION
Children may be more highly exposed to environmental toxicants through dermal routes
than adults. For instance, children often play and crawl on contaminated surfaces and are more
likely to wear less clothing than adults. These factors result in higher dermal contact with
contaminated media. In addition, children have a higher surface area relative to body weight. In
fact, the surface-area-to-body weight ratio for newborn infants is more then two times greater
then that for adults (Cohen-Hubal et al., 1999).
Dermal exposure can occur during a variety of activities in different environmental media
and microenvironments (U.S. EPA, 1992a; 1992b). 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 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 8-1). 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
dermal adherence of soil to the skin. Dermal Exposure Assessment: Principles and Applications
(U.S. EPA, 1992b), provides detailed information concerning dermal exposure assessment using a
stepwise guide in the exposure assessment process.
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Biologically
Effective
Dose
Skin
Uptake
Figure 8-1. Schematic of Dose and Exposure: Dermal Route
Source: U.S. Environmental Protection Agency (1992a).
8.2 SURFACE AREA
8.2.1 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.
8.2.2 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
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measured area. Triangulation consists of marking the area of the body into geometric figures,
then calculating the figure areas from their linear dimensions. Surface integration is performed by
using a planimeter and adding the areas.
The 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 8A.
8.2.3 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
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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 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 specific body parts using the Dubois and Dubois
(1916) formula and using the surface area of various body pars provided by Boyd (1935) and Van
Graan (1969) in conjunction with SPS. Equations to estimate the body part surface area of
children were not developed because of insufficient data.
Percentile estimates for total surface area of male and female children presented in
Tables 8-1 and 8-2 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 8-3. 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.
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
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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 two age groups of
children (infants aged 0 to 2 years and children aged 2.1 to 17.9 years). These ratios were
calculated by dividing body surface areas by corresponding body weights for the 401 individuals
analyzed by Gehan and George (1970) and summarized by U.S. EPA (1985). Distributions of
SA/BW ratios were developed and summary statistics were calculated for the two age groups and
the combined data set. Summary statistics for the two children's age groups are presented in
Table 8-4. 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. 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.
Wong et al. (2000) - Adult Proxy Responses to a Survey of Children's Dermal Soil
Contact Activities - Wong et al. (2000) conducted telephone surveys to gather information on
children's activity patterns as related to dermal contact with soil during outdoor play on bare dirt
or mixed grass and dirt surfaces. This study, the second Soil Contact Survey (SCS-II), was a
follow-up to the initial Soil Contact Survey (SCS-I), conducted in 1996, that primarily focused on
assessing adult behavior related to dermal contact with soil and dust (Garlock et al., 1999). As
part of SCS-I, information was gathered on the behavior of children under the age of 18 years,
however, the questions were limited to clothing choices and the length of time after soil contact to
hand washing. Results obtained for children from SCS-I were not reported in Garlock et al.
(1999), but some of the collected information is summarized in Wong et al (2000). Questions
were posed for SCS-II to further define children's outdoor activities and hand washing and
bathing frequency. For both soil contact surveys households were randomly phoned in order to
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obtain nationally representative results. The adult respondents were questioned as surrogates for
one randomly chosen child under the age of 18 residing within the household.
For SCS-I, the population size of children sampled was 211. Older children (those
between the ages of 5 and 17) were questioned regarding participation in "gardening and
yardwork," "outdoor sports," and "outdoor play activities." For children less than 5 years old,
"outdoor play activities" occurring on a playground or yard with "bare dirt or mixed grass and
dirt" surfaces were noted. The clothing worn during these play activities during warm weather
months (April though October) also was questioned. For both groups of children, information
was gathered concerning hand washing, bathing, and clothes changing habits after soil contact
activities, but these results are not reported in Wong et al. (2000).
Results of SCS-I indicate that most children wore short pants, a dress or skirt, short sleeve
shirts, no socks, and leather or canvas shoes during the outdoor play activities of interest. Using
data from Anderson et al. (1985) percentages of total body surface area associated with specific
body parts were estimated (Table 8-5). Then exposed skin surface areas for children under age 5
were estimated per clothing item as well as for all clothing items worn together during warm
weather outdoor play (Table 8-6). Faces and hands were assumed to be exposed under all
conditions with the face having a constant surface area fraction of 5 percent and the hands 6
percent.
In the SCS-II, of 680 total adult respondents with a child in their household, 500 (73.5%)
reported that their child played outdoors on bare dirt or mixed grass and dirt surfaces (identified
as "players"). Those children that reportedly did not play outdoors ("non-players") were
typically very young (< 1 year) or relatively older (> 14 years). Of the 500 children that played
outdoors, 497 played outdoors in warm weather months (April through October) and 390 were
reported to play outdoors during cold weather months (November through March). These results
are presented in Table 8-7. The frequency (days/week), duration (hours/day), and total hours per
week spent playing outdoors was determined for those children identified as "players"
(Table 8-8). The responses indicated that during the warmer months children spend a relatively
high percentage of time outdoor and a lesser amount of time in cold weather. The median play
frequency reported was 7 days/week in warm weather and 3 days/week in cold weather. Median
play duration was 3 hours/day in warm weather and 1 hour/day during cold weather months.
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Adult respondents were then questioned as to how many times per day their child washed
his/her hands and how many times the child bathed or showered per week during both warm and
cold weather months. This information provided an estimate of the time between skin contact
with soil and removal of soil by washing (i.e., exposure time). Hand washing and bathing
frequencies for child players are reported in Table 8-9. Based on these results, hand washing
occurred a median of 4 times per day during both warm and cold weather months. The median
frequency for baths and showers was estimated to be 7 times per week for both warm and cold
weather.
Based on reported household incomes, the respondents sampled in SCS-II tended to have
higher incomes than that of the general population. This may be explained by the fact that phone
surveys cannot sample those households without telephones. Additional uncertainty or error in
the study results may be presented by the use of surrogate respondents. Adult respondents were
questioned regarding child activities that may have occurred in prior seasons, introducing the
chance of recall error. In some instances, a respondent did not know the answer to a question or
refused to answer. In Tables 8-10 and 8-11 iformation extracted from the National Human
Activity Pattern Survey (NHAPS) (U.S. EPA, 1996). Table 8-10 compares mean play duration
data from SCS-II to similar activities identified in NHAPS. The number of times per day a child
washed his or her hands was presented in both SCS-II and NHAPS follow-up survey B and are
shown in Table 8-11. Corresponding information for bathing frequency data collected from SCS-
II was not collected in NHAPS. As indicated in Tables 8-10 and 8-11, where comparison is
possible, NHAPS and SCS-II results showed similarities in observed behaviors.
8.2.4 Application of Body Surface Area Data
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). Central and upper-
percentile values for children should be derived from Table 8-1 or 8-2.
Unlike exposure to liquids, clothing may or may not be effective in limiting the extent of
exposure to soil. The children clothing scenarios are presented below.
Central tendency mid range: Child wears long sleeve shirt, pants, and shoes. The
exposed skin surface is limited to the head and hands. Table 8-3 can be used to determine
the skin surface area depending on the age group of interest.
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Upper percentile: Child wears a short sleeve shirt, shorts, and shoes. The exposed skin
surface is limited to the head, hands, forearms, and lower legs. Table 8-3 can be used to
determine the skin surface area depending on the age group of interest.
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. Default values for children can be
derived by multiplying the 50th and 95th percentiles of the total surface area 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 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 8-3 to estimate surface areas of specific body parts.
8.3 SOIL ADHERENCE TO SKIN
8.3.1 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.
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8.3.2 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 //m.
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. Several of the activities studied by Kissel (1996b)
involved children, as shown in Table 8-12. A summary of field studies by activity, gender, age,
field conditions, and clothing worn is presented in Table 8-12. 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 using allometric models of surface area. These data are presented in Table
8-13. Results presented are based on direct measurement of soil loading on the surfaces of skin
before and after activities that may be expected to have soil contact (Kissel et al., 1996b). The
results indicate that the rate of soil adherence to the hands is higher than for other parts of the
body.
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Holmes, Jr., K.K., J.H. Shirai, K.Y. Richter, andJ.C. Kissel (1999) - Field Measurement
of Dermal Soil Loadings in Occupational and Recreational Activities - Holmes et al. (1999)
collected pre- and post-activity soil loadings on various body parts of individuals within groups
engaged in various occupational and recreational activities. These groups included children at a
daycare center and playing indoors in a residential setting. This study was conducted as a follow
up to previous field sampling of soil adherence on individuals participating in various activities
(Kissel et al., 1996). For this round of sampling, soil loading data were collected utilizing the
same methods used and described in Kissel et al. (1996). Information regarding the groups of
children studied and their observed activities are presented in Table 8-14.
The daycare children studied were all at one location and measurements were taken on
three different days. The children freely played both indoors in the house and outdoors in the
backyard. The backyard was described as having a grass lawn, shed, sand box, and wood chip
box. In this setting, the children engaged in typical activities including: playing with toys and
each other, wrestling, sleeping, and eating. The number of children within each day's group and
the clothing worn is described in Table 8-15.
The five children measured on the first day were washed first thing in the morning to
establish a preactivity level. They were next washed at noon to determine the postactivity soil
loading for the morning (Daycare kids No. la). The same children were washed once again at the
close of the day for measurement of soil adherence from the afternoon play activities (Daycare
kids No. lb).
For the second observation day (Daycare kids No. 2), postactivity data were collected for
five children. All the activities on this day occurred indoors. For the third daycare group
(Daycare kids No. 3), four children were studied.
On two separate days, children playing indoors in a home environment were monitored.
The first group (Indoor kids No. 1) had four children while the second group (Indoor kids No. 2)
had six children. The play area was described by Holmes et al. (1999) as being primarily carpeted.
The clothing worn by the children within each day's group is described in Table 8-15.
The geometric means and standard deviations of the postactivity soil adherence for each
group of children and for each body part are summarized in Table 8-16. According to Holmes et
al. (1999), variations in the soil loading data from the daycare participants reflect differences in
the weather and access to the outdoors.
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An advantage of this study is that it provides a supplement to soil loading data collected in
a previous round of studies (Kissel et al., 1996b). Also, the data support the assumption that
hand loading can be used as a conservative estimate of soil loading on other body surfaces for the
same activity. The activities studied represent normal child play both indoors and outdoors, as
well as for different combinations of clothing. The small number of participants (//) is a
disadvantage of this study. Also, the children studied and the activity setting may not be
representative of the U.S. population.
Kissel et al. (1998) - Investigation of Dermal Contact with Soil in Controlled Trials - In
this study, Kissel et al.(1998) measured dermal exposure to soil from staged activities conducted
in a greenhouse. A fluorescent marker was mixed in soil so that soil contact for a particular skin
surface area could be identified. As described in Kissel et al.(1998), the subjects, which included
a group of children, were video imaged under a long-wave ultraviolet (UV) light before and after
soil contact. In this manner, soil contact on hands, forearms, lower legs, and faces was assessed
by presence of fluorescence. In addition to fluorometric data, gravimetric measurements for
preactivity and postactivity were obtained from the different body parts examined.
The studied group of children played for 20 minutes in a soil bed of varying moisture
content representing wet and dry soils. For wet soils, both combinations of long sleeves and long
pants and short sleeves and short pants were tested. Children only wore short sleeves and short
pants during play in the dry soil. Clothing was laundered after each trail. Thus, a total of three
trials with children were conducted. The parameters describing each of these trials are
summarized in Table 8-17.
Before each trial, each child was washed in order to obtain a preactivity or background
gravimetric measurement. Preactivity data are shown in Table 8-18. Body part surface areas
were calculated using Anderson et al. (1985) for the range of heights and weights of the study
participants.
For wet soil, postactivity fluorescence results indicated that the hand had a much higher
fractional coverage than other body surfaces (see Figure 8-2). No fluorescence was detected on
the forearms or lower legs of children dressed in long sleeves and pants.
As shown in Figure 8-3, postactivity gravimetric measurements showed higher soil loading
on hands and much lower amounts on other body surfaces, as was observed with fluorescence
data. According to Kissel et al. (1998), the relatively low loadings observed on non-hand body
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parts may be a result of the limited area of contact rather than lower localized loadings. A
geometric mean dermal loading of 0.7 mg/cm2 was found on children's hands following play in
wet soil. Mean loadings were lower on hands in the dry soil trial and on lower legs, forearms, and
faces in both the wet and dry soil trials. Higher loadings were observed for all body surfaces with
the higher moisture content soils.
This report is valuable in showing soil loadings from soils of different moisture content
and providing evidence that dermal exposure to soil is not uniform for various body surfaces.
There is also some evidence from this study demonstrating the protective effect of clothing.
Disadvantages of the study include a small number of study participants and a short activity
duration. Also, no information is provided on the ages of the children involved in the study.
8.4 RECOMMENDATIONS
8.4.1 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.
The recommendations for body surface area for children are summarized in Table 8-19.
These recommendations are based on U.S. EPA (1985) and Phillips et al. (1993). Table 8-20
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
children. The results are based on selected measurements from the original data collected by
Boyd (1935). 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 previous
efforts to estimate body surface area. Analyses are also based on measurements selected from the
original measurements made by Boyd (1935) and data were not analyzed for specific body parts.
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8.4.2 Soil Adherence to Skin
Recommendations for the rate of soil adherence to the skin are based on data collected by
Kissel et al. (1996a; 1996b) for specific activities. The experimental design and measurement
methods used by Kissel et al. (1996a; 1996b) are straightforward and reproducible, but it should
be noted that the controlled experiments and field studies are based on a limited number of
measurements and specific situations were 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.
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 8-12 which best represents the exposure scenario of concern and use the
corresponding adherence value from Table 8-13. Although this approach represents an
improvement, it still has shortcomings. For example, it is difficult to decide which activity in
Table 8-13 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 available, updated recommendations will be issued.
Table 8-13 provides the best estimates available on activity-specific adherence values, but
are based on limited data. Therefore, they have a high degree of uncertainty 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 8-21. 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
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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).
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8.5 REFERENCES FOR CHAPTER 8
Anderson E., Browne N., Duletsky S., Ramig J. and Warn T. (1985) Development of Statistical Distributions or
Ranges of Standard Factors Used in Exposure Assessments. U. S. EPA Office of Health and
Environmental Assessment, Washington, D.C. NTIS PB85-242667.
Boyd, E. (1935) The growth of the surface area of the human body. Minneapolis, Minnesota: University of
Minnesota Press.
Buhyoff, G.J.; Rauscher, H.M.; Hull, R.B.; Killeen, K.; Kirk, R.C. (1982) User's Manual for Statistical Processing
System (version 3C. 1). Southeast Technical Associates, Inc.
Cohen-Hubal, E.A.; Sheldon, L.S.; Burke, J.M.; McLundy, T.R.; Berry, M.R.; Rigas, M.L.; Zartarian, V.G.;
Freeman, N.C.G. (1999) Children's exposure assessment: A review of factors influencing children's
exposure, and the data available to characterize and assess that exposure. Research Triangle Park, NC:
U.S. Environmental Protection Agency, National Exposure Research Laboratory.
Dubois, D.; Dubois, E.F. (1916) A formula to estimate the approximate surface area if height and weight be
known. Arch, of Intern. Med. 17:863-871.
Gehan, E.; George, G.L. (1970) Estimation of human body surface area from height and weight. Cancer
Chemother. Rep. 54(4):225-235.
Garlock T.J., Shirai, J.H. and Kissel, J.C. (1999) Adult responses to a survey of soil contact related behaviors. J.
Exposure Anal. Environ. Epid. 1999: 9: 134-142.
Geigy Scientific Tables (1981) Nomograms for determination of body surface area from height and mass. Lentner,
C. (ed.). CIBA-Geigy Corporation, West Caldwell, NJ. pp. 226-227.
George, S.L.; Gehan, E.A.; Haycock, G.B.; Schwartz, G.J. (1979) Letters to the editor. J. Ped. 94(2):342.
Haycock, G.B.; Schwartz, G.J.; Wisotsky, D.H. (1978) Geometric method for measuring body surface area:
A height-weight formula validated in infants, children, and adults. J. Ped. 93(l):62-66.
Holmes, K.K.; Kissel, J.C.; Richter, K.Y. (1996) Investigation of the influence of oil on soil adherence to skin. J.
Soil. Contam. 5(4):301-308.
Holmes, Jr., K.K., J.H. Shirai, K.Y. Richter, and J. C. Kissel (1999) Field Measurement of Dermal Loadings in
Occupational and Recreational Activities, Environmental Research, Section A, 80, 148-157.
Kissel, J.; Richter, K.; Duff, R.; Fenske, R. (1996a) Factors Affecting Soil Adherence to Skin in Hand-Press Trials.
Bull. Environ. Contamin. Toxicol. 56:722-728.
Kissel, J.; Richter, K.; Fenske, R. (1996b) Field measurements of dermal soil loading attributable to various
activities: Implications for exposure assessment. Risk Anal. 16(1): 116-125.
Kissel, J.C., Shirai, J. H., Richter, K.Y., and R.A. Fenske (1998) Investigation of Dermal Contact with Soil in
Controlled Trials, Journal of Soil Contamination, 7(6): 737-752.
Murray, D.M.; Burmaster, D.E. (1992) Estimated distributions for total surface area of men and women in the
United States. J. Expos. Anal. Environ. Epidemiol. 3(4):451-462.
June 2000
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Phillips, L.J.; Fares, R.J.; Schweer, L.G. (1993) Distributions of total skin surface area to body weight ratios for
use in dermal exposure assessments. J. Expos. Anal. Environ. Epidemiol. 3(3):331-338.
Popendorf, W.J.; Leffingwell, J.T. (1976) Regulating OP pesticide residues for farmworker protection.
In: Residue Review 82. New York, NY: Springer-Verlag New York, Inc., 1982. pp. 125-201.
Rochon, J.; Kalsbeek, W.D. (1983) Variance estimation from multi-stage sample survey data: thejackknife
repeated replicate approach. Presented at 1983 SAS Users Group Conference, New Orleans, Louisiania,
January 1983.
Sendroy, J.; Cecchini, L.P. (1954) Determination of human body surface area from height and weight. J. Appl.
Physiol. 7(1):3-12.
U.S. EPA. (1985) Development of statistical distributions or ranges of standard factors used in exposure
assessments. Washington, DC: Office of Research and Development, Office of Health and
Environmental Assessment. EPA 600/8-85-010. Available from: NTIS, Springfield, VA.
PB85-242667.
U.S. EPA. (1992a) Guidelines for exposure assessment. Federal Register. FR 57:104:22888-22938. May 29,
1992.
U.S. EPA. (1992b) Dermal exposure assessment: principles and applications. Washington, DC: Office of
Research and Development, Office of Health and Environmental Assessment/OHEA. U.S.
EPA/600/8-9-91.
U. S. Environmental Protection Agency (U.S. EPA) (1996) Analysis of the National Human Activity Pattern
Survey (NHAPS) Respondents from a Standpoint of Exposure assessment. Office of Research and
Development, Washington, D.C., EPA/600/R-96/074.
Van Graan, C.H. (1969) The determination of body surface area. Supplement to the South African J. of Lab. and
Clin. Med. 8-2-69.
Wong E. Y., Shirai, J.H, Garlock, T. J., and Kissel, J.C. (2000) Adult Proxy Responses to a Survey of Children's
Dermal Soil Contact Activities, Submitted for publication.
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Table 8-1. Total Body Surface Area of Male
Children in Square Meters3
Percentile
Age
(yr)b
5
10
15
25
50
75
85
90
95
2 < 3
0.527
0.544
0.552
0.569
0.603
0.629
0.643
0.661
0.682
3 <4
0.585
0.606
0.620
0.636
0.664
0.700
0.719
0.729
0.764
4 < 5
0.633
0.658
0.673
0.689
0.731
0.771
0,796
0.809
0.845
5 <6
0.692
0.721
0.732
0.746
0.793
0.840
0.864
0.895
0.918
6 < 7
0.757
0.788
0.809
0.821
0.866
0.915
0.957
1.01
1.06
7 < 8
0.794
0.832
0.848
0.877
0.936
0.993
1.01
1.06
1.11
8 < 9
0.836
0.897
0.914
0.932
1.00
1.06
1.12
1.17
1.24
9< 10
0.932
0.966
0.988
1.00
1.07
1.13
1.16
1.25
1.29
10 < 11
1.01
1.04
1.06
1.10
1.18
1.28
1.35
1.40
1.48
11 < 12
1.00
1.06
1.12
1.16
1.23
1.40
1.47
1.53
1.60
12 < 13
1.11
1.13
1.20
1.25
1.34
1.47
1.52
1.62
1.76
13 < 14
1.20
1.24
1.27
1.30
1.47
1.62
1.67
1.75
1.81
14 < 15
1.33
1.39
1.45
1.51
1.61
1.73
1.78
1.84
1.91
15 < 16
1.45
1.49
1.52
1.60
1.70
1.79
1.84
1.90
2.02
16 < 17
1.55
1.59
1.61
1.66
1.76
1.87
1.98
2.03
2.16
17 < 18
1.54
1.56
1.62
1.69
1.80
1.91
1.96
2.03
2.09
3 <6
0.616
0.636
0.649
0.673
0.728
0.785
0.817
0.842
0.876
6 < 9
0.787
0.814
0.834
0.866
0.931
1.01
1.05
1.09
1.14
9< 12
0.972
1.00
1.02
1.07
1.16
1.28
1.36
1.42
1.52
12 < 15
1.19
1.24
1.27
1.32
1.49
1.64
1.73
1.77
1.85
15 < 18
1.50
1.55
1.59
1.65
1.75
1.86
1.94
2.01
2.11
"Lack of height measurements for children <2 years in NHANES II precluded calculation of surface areas for this
age group.
bEstimated values calculated using NHANES II data.
Source: U.S. Environmental Protection Agency (1985).
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Table 8-2. Total Body Surface Area of Female
Children in Square Meters3
Percentile
Age (yr)b
5
10
15
25
50
75
85
90
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.
bEstimated values calculated using NHANES II data.
Source: U.S. EPA (1985).
June 2000
8-18
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Table 8-3. Percentage of Total Body Surface Area by Body Part For Children
Percent of Total
Head
Trunk
Arms
Hands
Legs
Age
(yr)
N
M:F
Mean
Min-Max
Mean
Min-Max
Mean
Min-Max
Mean
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
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
2 < 3
1:0
14.2
38.5
11.8
5.30
23.2
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
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
5 <6
6 < 7
1:0
13.1
35.1
13.1
4.71
27.1
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
10 < 11
11 < 12
12 < 13
1:0
8.74
34.7
13.7
5.39
30.5
13 <14
1:0
9.97
32.7
12.1
5.11
32.0
14 < 15
15 < 16
16 < 17
1:0
7.96
32.7
13.1
5.68
33.6
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).
8-19
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1
2
3
4
5
6
7
8
9
10
11
Table 8-4. Descriptive Statistics For Surface Area/body Weight (SA/BW) Ratios (m2/kg)
Range
Age (yrs.) Mean Min-Max
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
Standard deviation.
bStandard error of the mean.
Source: Phillips et al. (1993).
SDa SE
Percentiles
10 25 50 75 90 95
8-20
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Table 8-5. Clothing choices and assumed body surface areas exposed
Clothing response
Area assumed exposed
% of total body surface area"
M F
Long pants
0
0
Short pants
lower '/? of thigh and upper '/? of lower leg
13
13
Long sleeves
0
0
Short sleeves
forearms
6
6
No shirt (males)
3/4 trunk and arms
38
n/a
Halter (females)
Vi trunk and arms
n/a
30
High socks
0
0
Low socks
1/4 lower leg
3
3
No socks
bottom half lower leg
6
6
Shoes
0
0
No shoes or sandals
feet
7
7
Gloves
0
0
No gloves
hands
6
6
Hat or no hat
1/3 head for face
5
5
Maximum exposure
75
67
a After Anderson et. al (1985).
Table 8-6. Estimated skin surface exposed during warm weather outdoor play for children
under age 5 (based on SCS-I data).
Skin area exposed (% of total) based on expressed choice of
pants shirt sleeves socks shoes haf all clothing
n
41
43
42
43
43
41
Mean
12.8
6.6
4.4
3.0
5.0
32.0
Median
13.0
6.0
5.3
3.5
5.0
30.5
S.D.
1.0
2.7
1.7
3.2
0.0
6.0
a Face was assumed to always be exposed.
June 2000
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1
2
Table 8-7. Number and percentage of respondents with children and those reporting outdoor play1 activities in both warm and cold weather
3
Respondents
with children
Child players3
Child non players
Warm
weather
palyerb
Cold weather
player
Player in both
seasons
4
n
n
%
n
%
n
n
%
5
SCS-II base
197
128
65.0
69
35.0
127
100
50.8
6
SCS-II oversample
483
372
77.0
111
23.0
370
290
60.0
7
Total
680
500
73.5
180
26.5
497
390
57.4
8
9
10
11
12
13
a "Play" and "player" refer specifically to participation in outdoor play on bare dirt or mixed grass and dirt,
b Does not include three "Don't know/refused" responses regarding warm weather play.
Table 8-8. Play frequency and duration for all child players (from SCS-II data)
14
Cold weather
Warm weather
15
Frequency
(d/wk)
Duration
(hrs/d)
Total
(hrs/wk)
Frequency
(d/wk)
Duration
(hrs/d)
Total
(hrs/wk)
16
n
372
374
373
488
479
480
17
5th Percentile
1
1
1
2
1
4
18
50th Percentile
3
1
5
7
3
20
19
95th Percentile
7
4
20
7
8
50
20
21
8-22
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Table 8-9. Hand washing and bathing frequency for all child players (from SCS-II data)
Cold weather Warm weather
Hand washing Bathing Hand washing
(times/d) (times/wk) (times/d)
n
5th Percentile
50th Percentile
95th Percentile
329
2
4
10
388
2
7
10
433
2
4
12
Table 8-10. NHAPS and SCS-II play duration3 comparison
Mean play duration
(min/d)
Cold weather Warm weather Total
NHAPS 114 109 223
SCS-II 102 206 308
a. Selected previous day activities in NHAPS, average day outdoor play on bare dirt or mixed grass and dirt in SCS-II.
b. 2x2 Chi-square test for contingency between NHAPS and SCS-II.
8-23
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1
2
Table 8-11. NHAPS and SCS-II hand wash frequency comparison
3 Percent reporting frequency (times/d) of:
4 Season 0 1-2 3-5 6-9 10-19 20-29 30+ "Don't X2testc
know"
5 NHAPS cold 3 18 51 17 7 1 1 3
6 SCS-II cold 1 16 50 11 7 1 0 15 p = 0.06
7 NHAPS warm 3 18 51 15 7 2 14
8 SCS-II warm 0 12 46 16 10 1 0 13 p = 0.001
9
8-24
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Table 8-12. Summary of Field Studies
Evenf Age
Activity Month (hrs) Nb M F (yrs) Conditions Clothing
Indoor
TaeKwonDo Feb. 1.5 7 6 1 8-42 Carpeted floor All in longsleeve-long pants
martial arts uniform, sleeves
rolled back, barefoot
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
Daycare Kids No. la Aug. 3.5 6
Daycare Kids No. lb Aug. 4 6
Daycare Kids No.2c Sept. 8 5
Daycare Kids No. 3 Nov. 8 4
5 1 1-6.5 Indoors: linoleum surface; 4 of 6 in long pants, 4 of 6
outdoors: grass, bare earth, short sleeves, shoes
barked area
5 1 1-6.5 Indoors: linoleum surface; 4 of 6 in long pants, 4 of 6
outdoors: grass, bare earth, short sleeves, no shoes
barked area
4 1 1-4 Indoors, low napped
carpeting, linoleum
surfaces
Outdoor
Soccer No. 1
Nov. 0.67
Gardeners No. 1 Aug. 4
4 of 5 long pants, 3 of 5 long
sleeves, all barefoot for part of
the day
3 1 1-4.5 Indoors: linoleum surface, All long pants, 3 of 4 long
outside: grass, bare earth, sleeves, socks and shoes
barked area
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
1 7 16-35 Weeding, pruning,digging 6 of 8 long pants, 7 of 8 short
Archeologists
July 11.5 7
a trench
4 16-35 Digging withtrowel,
screening dirt, sorting
Kids-in-mud No. 1 Sept. 0.17 6 5 1 9-14 Lake shoreline
Kids-in-mud No. 2 Sept. 0.33 6 5 1 9-14 Lake shoreline
sleeves, 1 sleeveless, socks,
shoes, intermittent use of
gloves
6 of 7 short pants,all short
sleeves, 3 no shoes or socks,
2 sandals
All in short sleeve T-shirts,
shorts, barefoot
All in short sleeve T-shirts,
shnrts hnrpfnnt
"Event duration
bNumber of subject
cActivities were confined to the house
Sources: Kissel et al. (1996b); Holmes et al. (1996).
June 2000
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1
2
3
4
5
6
Table 8-13. Geometric Mean And Geometric Standard Deviations of
Soil Adherence by Activity And Body Region
Activity
Post-activity Dermal Soil Loadings (mg/cm2)
Na
Hands
Arms
Legs
Faces
Feet
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Indoor
Tae Kwon Do
Indoor Kids No. 1
Indoor Kids No. 2
Daycare Kids No. la
Daycare Kids No. lb
Daycare Kids No. 2
Daycare Kids No. 3
Outdoor
Soccer No. 1
Gardeners No. 1
Archeologists
Kids-in-mudNo. 1
Kids-in-mud No. 2
0.0063
1.9
0.0073
1.9
0.014
1.5
0.11
1.9
0.15
2.1
0.073
1.6
0.036
1.3
0.11
1.8
0.20
1.9
0.14
1.3
35
2.3
58
2.3
0.0019
4.1
0.0042
1.9
0.0041
2.0
0.026
1.9
0.031
1.8
0.023
1.4
0.012
1.2
0.011
2.0
0.050
2.1
0.041
1.9
11
6.1
11
3.8
0.0020
2.0
0.0041
2.3
0.0031
1.5
0.030
1.7
0.023
1.2
0.011
1.4
0.014
3.0
0.031
3.8
0.072
0.028
4.1
36
2.0
9.5
2.3
0.012
1.5
0.058
1.6
0.050
1.8
0.0022
2.1
0.012
1.4
0.0091
1.7
0.079
2.4
0.13
1.4
0.044
1.3
0.0053
5.1
0.17
0.24
1.4
24
3.6
6.7
12.4
"Number of subjects.
Sources: Kissel et al. (1996b); Holmes et al. (1996).
June 2000
8-26
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1
2
Table 8-14. Summary of Groups Assayed in Round 2 of Field Measurements
3
Activity
Month
Event3 (hrs)
nb
Males
Females
Ages
4
Daycare kids No. la
Aug.
3.5
6
5
1
1 -6.5
5
Daycare kids No. lb
Aug.
4
6
5
1
1 -6.5
6
Daycare kids No. 2
Sept.
8
5
4
1
1 - 4
7
Daycare kids No. 3
Nov.
8
4
3
1
1 -4.5
8
Indoor kids No. 1
Jan.
2
4
3
1
6 - 13
9
Indoor kids No. 2
Feb.
2
6
4
2
3 - 13
10
11
a Event duration,
b Number of subjects.
June 2000
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2
Table 8-15. Attire for Individuals within Children's Groups Studied
3 Pants Sleeves Socks Shoes
4
Activity
rf
Long
Short
Long
Short
High
Low
5
Daycare kids No. la
6
4
2
1
5
1
5
low leather or canvas
shoes - 6
6
Daycare kids No. lb
6
4
2
1
5
1
5
barefoot - 3
low leather or canvas
shoes - 3
7
Daycare kids No. 2
5
4
1
2
3
NA
NA
barefoot - 2
shoes/socks Vi day and
barefoot Vi day - 3
8
Daycare kids No. 3b
4
4
0
3
1
0
4
low shoes - 4
9
Indoor kids No. 1
4
1
3
2
2
0
4
no shoes (socks only) - 4
10
Indoor kids No. 2
6
5
1
5
1
0
6
no shoes (socks only) - 6
11
12
13 a Number of subjects.
14 b All children wore jackets when engaged in outdoor activities.
15 NA - "Not Available": 3 children wore socks for Vi day in the morning but no specific information is provided on the type of
16 socks worn.
17
June 2000
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
Table 8-16. Geometric Means (Geometric Standard Deviations) of Round 2 Post-activity Loadings
Postactivity Dermal Soil Loadings (mg/cm2)
Activity
na
Hands
Forearms
Lower legs
Facesb Feet
Daycare kids No. la
4
0.11 (1.9)
0.026 (1.9)
0.030 (1.7)
0.079 (2.4)
Daycare kids No. lb
6
0.15 (2.1)
0.031 (1.8)
0.023 (1.2)
0.13 (1.4)
Daycare kids No. 2
6
0.073 (1.6)
0.023 (1.4)
0.011 (1.4)
0.044 (1.3)
Daycare kids No. 3
6
0.036 (1.3)
0.012 (1.2)
0.014 (3.0)
0.0053 (5.1)
Indoor kids No. 1
5
0.0073 (1.9)
0.0042 (1.9)
0.0041 (2.3)
0.012 (1.4)
Indoor kids No. 2
4
0.014 (1.5)
0.0041 (2.0)
0.0031 (1.5)
0.0091 (1.7)
a Number of subjects (number of data points for specific non-hand body parts may deviate slightly),
b Children's feet rather than faces were washed in order to reduce the chance of a child's refusal to participate.
June 2000
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2
Table 8-17. Summary of Controlled Green House Trials - Children Playing
3 Activity Ages Duration Soil moisture Clothing3 n Male Female
(min) (%)
4 Playing 8-12 20 17-18 L 4 3 1
16-18 S 9 5 4
3-4 S 5 3 2
5
6 a L, long sleeves and long pants; S, short sleeves and short pants.
7
8
June 2000
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1
2 Table 8-18. Preactivity Loadings Recovered from Greenhouse Trial Children Volunteers
3
4 Body part surface area (cm2) Geometric mean
5 Area n (95% C.I.) ((ig/cm2)
6 Hands 12 420-798 9.4
(5.4 - 15.8)
7 Forearms 12 584-932 3.4
(2.3-5.2)
8 Lower legs 12 1,206-2,166 1.0
(0.7 - 1.5)
9 Face 12 388-602 0.8
(0.5 - 1.5)
10
11
June 2000
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
Percent Fluorescing
Figure 8-2. Skin Coverage as Determined by Fluorescence vs. Body Part for Adults
Transplanting Plants and for Children Playing in Wet Soils
10 -j
-------
1
2
3
4
5
6
7
8
9
10
11
12
Table 8-19. Summary of Recommended Values For Skin Surface Area
Surface Area
Central Tendency
Upper Percentile
Multiple Percentiles
Whole body
Body parts
see Tables 8-1, 8-2, and 8- see Tables 8-1, 8-2, and
4 8-4
see Table 8-3
see Table 8-3
June 2000
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3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Table 8-20. Confidence in Body Surface Area Measurement Recommendations
Considerations
Rationale
Rating
Study Elements
Level of Peer Review
Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data collection
period
Validity of approach
Representativeness of the
population
Characterization of variability
Lack of bias in study design
Measurement error
Other Elements
Number of studies
Agreement among researchers
Overall Rating
Studies were from peer reviewed journal articles. High
EPA report was peer reviewed before distribution.
The journals used have wide circulation. High
EPA report available from National Technical
Information Service.
Experimental methods are well-described. High
Experiments measured skin area directly. High
Experiments conducted in the U.S. High
Re-analysis of primary data in more detail by two Low
different investigators .
Neither rapidly changing nor controversial area; Low
estimates made in 1935 deemed to be accurate and
subsequently used by others.
Not relevant to exposure factor; parameter not time NA
dependent.
Approach used by other investigators; not High
challenged in other studies.
Not statistically representative of U.S. population. Medium
Individual variability due to age, race, or gender not Low
studied.
Objective subject selection and measurement High
methods used; results reproduced by others with
different methods.
Measurement variations are low; adequately Low/Medium
described by normal statistics.
1 experiment; two independent re-analyses of this Medium
data set.
Consistent results obtained with different analyses; Medium
but from a single set of measurements.
This factor can be directly measured. It is not Medium
subject to dispute. Influence of age, race, or gender
have not been detailed adequately in these studies.
June 2000
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Table 8-21. Confidence in Soil Adherence to Skin Recommendations
Considerations
Rationale
Rating
Study Elements
Level of Peer Review
Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data collection
period
Validity of approach
Representativeness of the
population
Characterization of variability
Lack of bias in study design
Measurement error
Other Elements
Number of studies
Agreement among researchers
Overall Rating
Studies were from peer reviewed journal articles.
Articles were published in widely circulated
journals.
Reports clearly describe experimental method.
The goal of the studies was to determine soil
adherence to skin.
Experiments were conducted in the U.S.
Experiments were directly measure soil adherence to
skin; exposure and dose of chemicals in soil were
measured indirectly or estimated from soil contact.
New studies were presented.
Seasonal factors may be important, but have not
been studied adequately.
Skin rinsing technique is a widely employed
procedure.
Studies were limited to the State of Washington and
may not be representative of other locales.
Variability in soil adherence is affected by many
factors including soil properties, activity and
individual behavior patterns.
The studies attempted to measure soil adherence in
selected activities and conditions to identify
important activities and groups.
The experimental error is low and well controlled,
but application of results to other similar activities
may be subject to variation.
The experiments were controlled as they were
conducted by a few laboratories; activity patterns
were studied by only one laboratory.
Results from key study were consistent with earlier
estimates from relevant studies and assumptions, but
are limited to hand data.
Data are limited, therefore it is difficult to
extrapolate from experiments and field observations
to general conditions .
High
High
High
High
High
High
High
Medium
High
Low
Low
High
Low/High
Medium
Medium
Low
June 2000
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1 APPENDIX 8A
2
3 FORMULAE FOR TOTAL BODY SURFACE AREA
June 2000
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
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APPENDIX 8A
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 = KW273 (8A-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 = a0Halwa2 (8A-2)
where:
SA = surface area in square meters;
H = height in centimeters; and
W = weight in kg.
The values of a0 (0.007182), ax (0.725), and a2 (0.425) were estimated from a sample of
only nine individuals for whom surface area was directly measured. Boyd (1935) stated that the
Dubois formula was considered a reasonably adequate substitute for measuring surface area.
Nomograms for determining surface area from height and mass presented in Volume I of the
Geigy Scientific Tables (1981) are based on the DuBois and DuBois formula. In addition, a
computerized literature search conducted for this report identified several articles written in the
last 10 years in which the DuBois and DuBois formula was used to estimate body surface area.
Boyd (1935) developed new constants for the DuBois and DuBois model based on
231 direct measurements of body surface area found in the literature. These data were limited to
measurements of surface area by coating methods (122 cases), surface integration (93 cases), and
triangulation (16 cases). The subjects were Caucasians of normal body build for whom data on
weight, height, and age (except for exact age of adults) were complete. Resulting values for the
constants in the DuBois and DuBois model were a0 = 0.01787, ax = 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,
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and weight of all postnatal subjects listed in Boyd (1935). The methods used to measure these
subjects were coating (163 cases), surface integration (222 cases), and triangulation (16 cases).
Gehan and George (1970) used a least-squares method to identify the values of the
constants. The values of the constants chosen are those that minimize the sum of the squared
percentage errors of the predicted values of surface area. This approach was used because the
importance of an error of 0.1 square meter depends on the surface area of the individual. Gehan
and George (1970) used the 401 observations summarized in Boyd (1935) in the least-squares
method. The following estimates of the constants were obtained: a0 = 0.02350, a, = 0.42246,
and a2 = 0.51456. Hence, their equation for predicting SA is:
SA = 0.02350 h042246W0-51456 (8A"3)
or in logarithmic form:
lnSA= -3.75080 = 0.422461nH = 0.514561nW (8A-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).
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:
SAi=a0HialWia2ei (8A-5)
or in logarithmic form:
ln(SA)- = InaQ +a^lnH- + a2lnW- +lne- (8A-6)
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where:
Sai = surface area of the i-th individual (m2);
Hi = height of the i-th individual (cm);
Wi = weight of the i-th individual (kg);
a0, al3 and a2 = parameters to be estimated; and
e; = 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),ai = 0.417(0.054),a2 = 0.517(0.022)
The model is then:
SA = 0.0239Hฐ-417W0-517 (8A"7)
or in logarithmic form:
In SA =-3.73+ 0.417 In H +0.517 In W (8A-8)
with a standard error about the regression of 0.00374. This model explains more than 99 percent
of the total variation in surface area among the observations, and is identical to two significant
figures with the model developed by Gehan and George (1970).
When natural logarithms of the measured surface areas are plotted against natural
logarithms of the surface predicted by the equation, the observed surface areas are symmetrically
distributed around a line of perfect fit, with only a few large percentage deviations. Only five
subjects differed from the measured value by 25 percent or more. Because each of the five
subjects weighed less than 13 pounds, the amount of difference was small. Eighteen estimates
differed from measurements by 15 to 24 percent. Of these, 12 weighed less than 15 pounds each,
1 was overweight (5 feet 7 inches, 172 pounds), 1 was very thin (4 feet 11 inches, 78 pounds),
and 4 were of average build. Since the same observer measured surface area for these 4 subjects,
the possibility of some bias in measured values cannot be discounted (Gehan and George 1970).
Gehan and George (1970) also considered separate constants for different age groups:
less than 5 years old, 5 years old to less than 20 years old, and greater than 20 years old. The
different values for the constants are presented below:
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Table 8A-1. Estimated Parameter Values for Different Age Intervals
Age
Number
group
of persons
ao
ai
a2
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 old
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 was 0.03 m2 for an 18-year-old at the
97th percentile. The authors concluded that there is no advantage in using separate values of a0,
aj, and a2 by age interval.
Haycock et al. (1978) without knowledge of the work by Gehan and George (1970),
developed values for the parameters a0, ab and a2 for the DuBois and DuBois model. Their
interest in making the DuBois and DuBois model more accurate resulted from their work in
pediatrics and the fact that DuBois and DuBois (1916) included only one child in their study
group, a severely undernourished girl who weighed only 13.8 pounds at age 21 months. Haycock
et al. (1978) used their own geometric method for estimating surface area from 34 body
measurements for 81 subjects. Their study included newborn infants (10 cases), infants
(12 cases), children (40 cases), and adult members of the medical and secretarial staffs of
2 hospitals (19 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, ax = 0.3964, and a2 = 0.5378. The result was the following equation for estimating
surface area:
SA = 0.024265Hฐ-3964W0-5378 (8A-9)
expressed logarithmically as:
In SA = In 0.024265 + 0.3964 In H + 0.5378 In W (8A-10)
The coefficients for this equation agree remarkably with those obtained by Gehan and George
(1970) for 401 measurements.
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1 George et al. (1979) agree that a model more complex than the model of DuBois and
2 DuBois for estimating surface area is unnecessary. Based on samples of direct measurements by
3 Boyd (1935) and Gehan and George (1970), and samples of geometric estimates by Haycock
4 et al. (1978), these authors have obtained parameters for the DuBois and DuBois model that are
5 different than those originally postulated in 1916. The DuBois and DuBois model can be written
6 logarithmically as:
In SA = In aQ = lnH + a2 InW (8A-11)
7
8
9 The values for a0, ab and a2 obtained by the various authors discussed in this section are
10 presented to follow:
11
12 Table 8A-2. Summary of Surface Area Parameter Values for the Dubois and Dubois Model
13
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15
Author
(year)
Number
of persons
ao
ai
a2
16
17
DuBois and DuBois
(1916)
9
0.007184
0.725
0.425
18
Boyd (1935)
231
0.01787
0.500
0.4838
19
20
Gehan and George
(1970)
401
0.02350
0.42246
0.51456
21
Haycock et al. (1978)
81
0.024265
0.3964
0.5378
22
23
24 The agreement between the model parameters estimated by Gehan and George (1970) and
25 Haycock et al. (1978) is remarkable in view of the fact that Haycock et al. (1978) were unaware
26 of the previous work. Haycock et al. (1978) used an entirely different set of subjects, and used
27 geometric estimates of surface area rather than direct measurements. It has been determined that
28 the Gehan and George model is the formula of choice for estimating total surface area of the body
29 since it is based on the largest number of direct measurements.
30
31 Nomograms
32 Sendroy and Cecchini (1954) proposed a graphical method whereby surface area could be
33 read from a diagram relating height and weight to surface area. However, they do not give an
34 explicit model for calculating surface area. The graph was developed empirically based on
35 252 cases, 127 of which were from the 401 direct measurements reported by Boyd (1935). In the
36 other 125 cases the surface area was estimated using the linear method of DuBois and DuBois
37 (1916). Because the Sendroy and Cecchini method is graphical, it is inherently less precise and
38 less accurate than the formulae of other authors discussed above.
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TABLE OF CONTENTS
9. ACTIVITY FACTORS 9-1
9.1 INTRODUCTION 9-1
9.2 ACTIVITY PATTERNS 9-1
9.3 RECOMMENDATIONS 9-11
9.3.1 Recommendations for Activity Patterns 9-11
9.3.2 Summary of Recommended Activity Factors 9-13
9.4 REFERENCES FOR CHAPTER 9 9-14
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LIST OF TABLES
Table 9-1. Mean Time Spent (minutes) Performing Major Activities Grouped by Age, Sex and
Type of Day 9-15
Table 9-2. Mean Time Spent (minutes) in Major Activities Grouped by Type of Day for Five
Different Age Groups 9-16
Table 9-3. Mean Time Spent Indoors and Outdoors Grouped by Age and Day of the
Week 9-17
Table 9-4. Mean Time Spent at Three Locations for both CARB and
National Studies (ages 12 years and older) 9-18
Table 9-5. Mean Time Spent (minutes/day) in Various Microenvironments Grouped by Total Population
and Gender (12 years and over) in the National and CARB Data 9-19
Table 9-6. Mean Time Spent (minutes/day) in Various Microenvironments by Type
of Day for the California and National Surveys 9-20
Table 9-7. Mean Time Spent (minutes/day) in Various Microenvironments by Age Groups for the
National and California Surveys 9-21
Table 9-8. Mean Time (minutes/day) Children Ages 12 Years and Under Spent in Ten Major
Activity Categories for All Respondents 9-22
Table 9-9. Mean Time Children Spent in Ten Major Activity Categories Grouped by Age and
Gender 9-23
Table 9-10. Mean Time Children Ages 12 Years and Under Spent in Ten Major Activity Categories
Grouped by Seasons and Regions 9-24
Table 9-11. Mean Time Children Ages 12 Years and Under Spent in Six Major Location
Categories for All Respondents (minutes/day) 9-25
Table 9-12. Mean Time Children Spent in Six Location Categories Grouped by Age and
Gender 9-25
Table 9-13. Mean Time Children Spent in Six Location Categories Grouped by Season and
Region 9-26
Table 9-14. Mean Time Children Spent in Proximity to Three Potential Exposures Grouped by
All Respondents, Age, and Gender 9-26
Table 9-15. Mean Time Spent Indoors and Outdoors Grouped by Age 9-31
Table 9-16. Range of Recommended Defaults for Dermal Exposure Factors 9-32
Table 9-17. Number of Times Taking a Shower at Specified Daily Frequencies by the Number of
Respondents 9-32
Table 9-18. Time (minutes) Spent Taking a Shower and Spent in the Shower Room
After Taking a Shower by the Number of Respondents 9-32
Table 9-19. Time (minutes) Spent Taking a Shower and Spent in the Shower Immediately After
Showering 9-33
Table 9-20. Total Time Spent Altogether in the Shower or Bathtub and Time Spent
in the Bathroom Immediately After by Number of Respondents 9-33
Table 9-21. Total Number of Minutes Spent Altogether in the Shower or Bathtub and Spent
in the Bathroom Immediately Following a Shower or Bath 9-34
Table 9-22. Range of Number of Times Washing the Hands at Specified Daily Frequencies by the
Number of Respondents 9-34
Table 9-23. Number of Minutes Spent Working or Being Near Excessive Dust in the Air
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(minutes/day) 9-34
Table 9-24. Range of Number of Times per Day a Motor Vehicle was Started in a Garage or Carport
and Started with the Garage Door Closed 9-35
Table 9-25. Number of Minutes Spent Playing on Sand, Gravel, Dirt, or Grass 9-35
Table 9-26. Number of Minutes Spent Playing in Sand, Gravel, Dirt or Grass
(minutes/day) 9-36
Table 9-27. Range of Number of Minutes Spent Playing on Grass in a Day by the Number of
Respondents 9-36
Table 9-28. Number of Minutes Spent Playing on Grass (minutes/day) 9-36
Table 9-29. Number of Times Swimming in a Month in Freshwater Swimming Pool by the
Number of Respondents 9-37
Table 9-30. Number of Minutes Spent Swimming in a Month in Freshwater Swimming Pool
(minutes/month) 9-37
Table 9-31. Range of the Average Amount of Time Actually Spent in the Water by Swimmers by
the Number of Respondents 9-37
Table 9-32. Statistics for 24-Hour Cumulative Number of Minutes Spent Playing Indoors and
Outdoors 9-38
Table 9-33. Statistics for 24-Hour Cumulative Number of Minutes Spent
Sleeping/Napping 9-38
Table 9-34. Statistics for 24-Hour Cumulative Number of Minutes Spent Attending Full Time
School 9-38
Table 9-35. Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports
and for Time Spent in Sports/Exercise 9-39
Table 9-36. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Recreation
and Spent Walking 9-39
Table 9-37. Statistics for 24-Hour Cumulative Number of Minutes Spent in Bathing 9-40
Table 9-38. Statistics for 24-Hour Cumulative Number of Minutes Eating or Drinking .... 9-40
Table 9-39. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at School and
Indoors at a Restaurant 9-40
Table 9-40. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on School Grounds/Play^
at a Park/Golf Course, and at a Pool/River/Lake 9-41
Table 9-41. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Kitchen
Bathroom, Bedroom, and in a Residence (All Rooms) 9-42
Table 9-42. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling Inside a
Vehicle 9-43
Table 9-43. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors (outside the
residence) and Outdoors Other Than Near a Residence or Vehicle, Such as Parks, Golf
Courses, or Farms 9-43
Table 9-44. Statistics for 24-Hour Cumulative Number of Minutes Spent in Malls, Grocery
Stores, or Other Stores 9-43
Table 9-45. Statistics for 24-hour Cumulative Number of Minutes Spent with Smokers
Present 9-44
Table 9-46. Range of Time (minutes) Spent Smoking Based on the Number of
Respondents 9-45
Table 9-47. Number of Minutes Spent Smoking (minutes/day) 9-45
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Table 9-48. Gender and Age Groups 9-46
Table 9-49. Assignment of At-Home Activities to Ventilation Levels for Children 9-47
Table 9-50. Aggregate Time Spent (minutes/day) At-Home in Activity Groups
by Adolescents and Children 9-48
Table 9-51. Comparison of Mean Time (minutes/day) Spent At-Home by Gender
(Adolescents) 9-48
Table 9-52. Comparison of Mean Time (minutes/day) Spent At-Home by Gender and Age for
Children 9-48
Table 9-53. Number of Person-Days/Individualsa for Children in CHAD Database 9-49
Table 9-54. Number of Hours Per Day Children Spend in Various Microenvironments by Age
Average ฑ Std. Dev. (Percent of Children Reporting >0 Hours in
Microenvironment) 9-50
Table 9-55. Average Number of Hours Per Day Children Spend Doing Various
Macroactivities While Indoors at Home by Age 9-51
Table 9-56. Confidence in Activity Patterns Recommendations 9-52
Table 9-57. Summary of Activity Pattern Studies 9-59
Table 9-58. Summary of Mean Time Spent Indoors and Outdoors from Several Studies . . . 9-60
Table 9-59. Summary of Recommended Values for Activity Factors 9-61
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LIST OF FIGURES
Figure 9-1. Distribution of the Number of Hours per Day Study Children Spent Indoors at Home
9-27
Figure 9-2. Distribution of the Number of Hours per Day Study Children Spent Indoors Away
from Home 9-28
Figure 9-3. Distribution of the Number of Hours per Day Study Children Spent Outdoors at
Home 9-29
Figure 9-4. Distribution of the Number of Hours per Day Study Children Spent Outdoors Away
from Home 9-30
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9. ACTIVITY FACTORS
9.1 INTRODUCTION
As a consequence of a child's immaturity and small stature, certain activities and behaviors
specific to children place them at higher risk to certain environmental agents (Chance and
Harmsen, 1998). Individual or group activities are important determinants of potential exposure
because toxic chemicals introduced into the environment may not cause harm a child until an
activity is performed subjecting the child to contact with those contaminants. An activity or time
spent will vary based on, for example, culture, hobbies, location, gender, age, and personal
preferences. It is difficult to accurately collect/record data for a child's activity patterns (Hubal et
al., 1999). Children engage in more contact activities than adults, therefore, a much wider
distribution of activities need to be considered when assessing exposure (Hubal et al., 2000).
Behavioral patterns and preferred activities results in different exposures than for adults, but also
for children of different developmental stages (Chance and Harmsen, 1998).
The purpose of this section is to provide information on various activities, length of time
spent performing these activities, and locations and length of time spent by individuals within
those various microenvironments. This section summarizes data on how much time children
spend participating in various activities, in various microenvironments, and on the frequency of
performing various activities. These data cover a wide scope of activities and populations
arranged by age group, when available.
9.2 ACTIVITY PATTERNS
The purpose of this section is to describe published time use studies that provide
information on time-activity patterns of children in the U.S. These studies are briefly described
below. For a detailed description of the studies, the reader is referred to the Exposure Factors
Handbook, Volume III (U.S. EPA, 1997).
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. A total of 922
children participated in the survey. The children surveyed were between the ages of 3 and 17
years using a time diary and a standardized interview. The time diary involved children reporting
their activities beginning at 12.00 a.m. the previous night; the duration and location of each
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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.
The mean time spent performing major activities on weekdays and weekends by age and
sex, and type of day is presented in Table 9-1. 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 9-1 indicate that girls spend
more time than boys performing household work and personal care activities, and less time
playing sports. Also, children spend most of their free time watching television. Table 9-2
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 9-2. 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 it was conducted in 1981 and there is a
potential that activity patterns in children may have changed significantly from 1981 to the
present. Thus, application of these data for current exposure assessment may bias exposure
assessment results. Another limitation is that the data do not provide overall annual estimates of
children's time use since data were collected only during the time of the year when children attend
school and not during school vacation.
EPA estimated the total time indoors and outdoors using the Timmer data. Activities
performed indoors were assumed to include household work, personal care, eating, sleeping,
school, studying, attending church, watching television, and engaging in household conversations.
The average times spent in these indoor activities, and half the time spent in each activity which
could have occurred indoors or outdoors (i.e., market work, sports, hobbies, art activities,
playing, reading, and other passive leisure) were summed. Table 9-3 summarizes the results of
this analysis by age groups and day of the week.
Robinson and Thomas (1991) - Time Spent in Activities, Locations, and
Microenvironments: A California-National Comparison - Robinson and Thomas (1991)
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reviewed and compared data from the 1987-88 California Air Resources Board (CARB) time
activity study for California residents and from a similar 1985 national study, American's Use of
Time. Both studies used the diary approach data. Time use patterns were collected for
individuals 12 years and older. Telephone interviews based on the random-digit-dialing procedure
were conducted for approximately 1,762 respondents. Data categorized for children 0-18 years
old were not provided in the study. In addition, Robinson and Thomas (1991) defined a set of 16
microenvironments based on the activity and location codes employed in both studies. The mean
duration of time spent for the total sample population, 12 years and older in three location
categories is presented in Table 9-4 for both studies. Based on the data shown in Table 9-4,
respondents spent most of their time indoors, 1255 and 1279 minutes/day for the CARB and
national study, respectively.
Table 9-5 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 9-5
shows that in both studies males spend more time in work locations, automobiles and other
vehicles, autoplaces (garages), and physical outdoor activities, outdoor sites. In contrast, females
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 9-6 shows the mean time spent in various microenvironments grouped by type of
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 9-7.
Limitations associated with the Robinson and Thomas (1991) study are that the CARB
survey was performed in California only. Therefore, if applied to other populations, the data set
may be biased. In addition, the studies were conducted in 1980s and may bias exposure
assessment results when used for current exposure assessments. Another limitation is that time
distribution patterns were not provided for both studies and the data are based on short-term
studies.
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
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activities and locations (microenvironments) on a typical day (Wiley et al., 1991). A total of
1,200 children were included in the study. The average time respondents spent during the 10
activity categories for all children are presented in Table 9-8. 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 (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 9-9 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 9-10 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 9-11 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 9-12 and 9-13 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 9-12). 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 9-13). Table 9-14 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).
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EPA estimated the total time indoors and outdoors using the data from the Wiley study.
Activities performed indoors, were assumed to include household, childcare, personal needs and
care, education, and communication and passive leisure. The average times spent in these indoor
activities, and half the time spent in each activity which could have occurred indoors or outdoors
(i.e., work-related, goods/services, organizational activities, entertainment/social, don't know/not
coded) were summed. Table 9-15 summarizes the results of this analysis by age groups.
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 9-16. Limitations of this study are
that the values are based on small data sets and a limited number of studies. These data are not
representative for children in specific age group categories. An advantage is that it presents
default values for frequency and duration for use in exposure assessments when specific data are
not available.
Davis (1995), Soil Ingestion in Children with Pica (Final Report), EPA Cooperative
Agreement CR 816334-01 - In 1992, the Fred Hutchinson Cancer Research Center under
Cooperative Agreement with EPA conducted a study to estimate soil intake rates and collect
mouthing behavior data. Originally, the study was designed with two primary purposes: 1) to
describe and quantify the distribution of soil ingestion values in a group of children under the age
of five who exhibit behaviors that would be likely to result in the ingestion of larger than normal
amounts of soil; and 2) to assess and quantify the degree to which soil ingestion varies among
children according to season of the year (summer vs. winter).
The study was conducted during the first four months of 1992 and included 92 children
from the Tri-Cities area in Washington State. Children ranged in age from 10 to 60 months.
These children were volunteers among a group selected through random digit dialing. The study
was conducted during a period of 7 days.
In addition to mouthing behavior data, information was collected about how long the child
spent indoors and outdoors each day, and the general types of outdoor settings the child played
in. Figure 9-1 presents the distribution of the number of hours per day study children spent
indoors at home. Values were: the mean was 8.9 hours, the median was 9 hours, and the range
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was 30 minutes to 1.5 hours. Figure 9-2 presents the distribution of the number of hours per day
study children spent indoors away from home. The mean number of hours spent indoors away
from home was 1.8, the median was 1, and the range was 0-15 hours. Figure 9-3 presents the
distribution of number of hours per day study children spent outdoors at home. The mean number
of hours spent outdoors at home was 1.4, the median was 45 minutes, and the range was 0-9
hours. Figure 9-4 presents the number of hours per day study children spent outdoors away from
home. The mean number of hours spent was approximately 30 minutes, the median was less than
15 minutes, and the range was 0-8 hours.
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 were collected 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.
Tables 9-17 through 9-47 provide data from the NHAPS study. Tables 9-17 through 9-31
present data on the amount of time spent in selected activities and/or the corresponding
distribution data, when available.
Table 9-17 presents number of times taking a shower at specified daily frequencies by
number of respondents. The data shows that the majority of respondents take a
shower one or two times a day.
Table 9-18 provides time spent taking a shower and time spent in the shower room
immediately after showering. Most of the respondents spent 10-20 minutes taking a
shower and in the shower room after showering.
Table 9-19 provides the percentile data for the same activity shown in Table 9-16.
The 50th percentile value is 10 minutes for showering and 5 minutes for time spent
after showering was complete. The 90th percentile values vary across age groups and
range from 30-35 minutes and 10-15 minutes for time spent showering and in the
bathroom after showering, respectively.
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Table 9-20 presents total time (minutes) spent in the shower or bathtub and in the
bathroom immediately after a shower or bath. The majority of respondents spent from
10-20 minutes in the shower or bathtub and approximately 10 minutes in the bathroom
afterwards.
Table 9-21 presents the percentile data for the same activity shown in Table 9-18.
The 50th percentile values range from 15-20 minutes and 2-5 minutes for taking a
shower or bath and time spent in the bathroom after the bath, respectively.
Table 9-22 provides a range of number of times washing the hands in a day. Most
respondents washed their hands 3-5 times a day.
Table 9-23 presents statistics data for the number of minutes per day spent working or
being near excessive dust in the air. For age groups 1-11 years old, the 50th percentile
data indicates that approximately 75 minutes/day is spent in air with excessive dust.
Table 9-24 provides data for the frequency of starting a motor vehicle in a garage or
carport and started with the garage door closed.
Table 9-25 provides data for the range of minutes/day spent playing on sand, gravel,
dirt, or grass and playing when fill dirt was present.
Table 9-26 provides the percentile data for the same activity shown in Table 9-25.
Table 9-27 presents data for time (minutes/day) spent playing on the grass by number
of respondents. The majority of respondents spent more than 120 minutes/day in this
activity.
Table 9-28 presents percentile data for the same activity shown in Table 9-27. The
50th percentile rate is 60 minutes/day for all age groups.
Table 9-29 provides number of times/month swimming in a freshwater swimming pool
by number of respondents. The majority of respondents swim in freshwater pools 1 or
2 times/month.
Table 9-30 provides percentile data for the same activity shown in Table 9-29. The
50th percentile values are 42.5 minutes/month for age group 1-4 years and 60
minutes/month for age gropus 5-11 and 12-17 years.
Table 9-31 presents the range of the average amount of time (minutes/month) actually
spent in the water by swimmers. The majority of swimmers spent an average of 50-60
minutes/month in the water.
Tables 9-32 through 9-44 provide statistics for 24-hour cumulative time (minimum, mean,
maximum) spent in selected activities. The minimum is the minimum number of minutes spent in
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the activity. The mean is the mean 24-hour cumulative number of minutes spent by doers. The
maximum is the maximum number of minutes spent in the activity. The percentiles are the
percentage of doers below or equal to the given number of minutes.
Table 9-32 provides number of minutes spent playing indoors and playing outdoors.
Table 9-33 provides number of minutes spent sleeping/napping in a day.
Table 9-34 presents data for time spent attending full-time school.
Table 9-35 provides data for time spent in active sports and for time spent in
sports/exercise.
Table 9-36 presents data for time spent in outdoor recreation and for walking.
Table 9-37 provides data for time spent bathing.
Table 9-38 presents statistics for minutes eating or drinking.
Table 9-39 provides data for time spent indoors at school and in a restaurant.
Table 9-40 provides information for time spent outdoors on school
grounds/playgrounds and at a pool/river/lake.
Table 9-41 provides information on time spent at home in the kitchen, bathroom, and
bedroom, and indoors in a residence (all rooms).
Table 9-42 presents data for time spent traveling inside a vehicle.
Table 9-43 provides data for time spent outdoors (outside the residence) and outdoor
other than near a residence such as parks, golf courses, or farms.
Table 9-44 provides information for time spent in malls, grocery stores, and other
stores.
Table 9-45 presents data for minutes spent with smokers present.
Table 9-46 provides data for time (minutes) spent smoking by number of respondents.
Table 9-47 provides percentile data for the same activity shown in Table 9-44.
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
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representative of all ages, gender, and is race specific. A disadvantage of the study is that for ages
1-17, the "N" is small for most activities. In addition, 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.
Funk et al. (1998) - Quantifying the Distribution of Inhalation Exposure in Human
Populations - Funk et al. (1997) used the data from the California Air Resources Board (CARB)
study to determine distributions of exposure time by tracking the time spent participating in daily
at home and at school activities for male and female children and adolescents. CARB performed
two studies from 1987 to 1990; the first was focused on adults and adolescents (12-17 years old),
while the second focused on children (6-11 years old) (Funk et al., 1998). The targeted groups
were noninstitutionalized English speaking Californians with a telephone in their residence.
Individuals were contacted by telephone and asked to account for every minute within the
previous 24 hours, including the amount of time spent on an activity and the location of the
activity. The surveys varied from day to day and season to season.
All the activities that were documented were separated into two groups, "at home" (any
activity at principal residence), or "away." Each activity was assigned to one of three ventilation
levels (Ve), low, moderate, or high. Resting activities were placed in the low Ve, and moderate
exertion activities were assigned to moderate Ve. Activities requiring high levels of physical
exertion were placed in the high Ve group. Ambiguous activities that were encountered were
assigned to moderate ventilation levels. Among the adolescents and children studied, means were
determined for the aggregate age groups, as shown in Table 9-48.
Several statistical methods, such as Chi-quare, Kolmogorov,-Smirnov, and Anderson-
Darling, were used to determine whether the time spent in an activity group had a known
distribution (Funk et al., 1998). All the activities that were identified in the CARB study were
assigned to the three ventilation levels. Most of the activities performed by children were low to
moderate Ve as shown in Table 9-49.
The aggregate time periods spent at home in each activity are shown in Table 9-50.
Aggregate time spent at home performing different activities was compared between genders.
There were no significant differences between adolescent male and females in any of the activity
groups (Funk et al., 1998) (Table 9-51). In children ages 6-11 years there were differences found
between gender and age at the low ventilation levels. In the moderate ventilation level there were
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significant differences between two age groups (6-8 years, and 9-11 years) and gender (Funk et
al., 1998) (Table 9-52).
Large proportions of the respondents in the study did not participate in high ventilation
activities; discrete distributions were used to characterize high ventilation activity groups (Funk et
al., 1998). Lognormal distribution best described the time spent by children at high ventilation
levels.
Hubal et al. (2000) - Children's Exposure Assessment: A Review of Factors Influencing
Children's Exposure, and the Data Available to Characterize and Assess that Exposure - Hubal
et al. (2000) reviewed available data to characterize and assess environmental exposures to
children. As part of that review, available activity patterns data were evaluated. Hubal reviewed
the EPA National Exposure Research Laboratory's Consolidated Human Activity Database
(CHAD), which contains data from several studies on human activities. For children and
adolescents younger than 18 years, CHAD contains 4,300 person-days of information and 3,009
person-days of microactivity data for 2,640 children less than 12 years old (Hubal et al., 2000)
(Table 9-53). Specific examples of the type of microactivity data available in CHAD for children
are shown in Tables 9-54 and 9-55. The number of hours spent in various microenvironments are
shown in Table 9-54 and time spent in various activities indoors at home in Table 9-55.
The authors noted that CHAD contains approximately "140 activity codes and 110
location codes, but the data generally are not available for all activity locations for any single
respondent. In fact, not all of the codes were used for most of the studies. Even though many
codes are used in macroactivity studies, many of the activity codes do not adequately capture the
richness of what children actually do. They are much too broadly defined and ignore many child-
oriented behaviors. Thus, there is a need for more and better-focused research into children's
activities." CHAD is available on the EPA Intranet (Hubal et al., 2000).
9.3 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 in the recommendations for activity patterns is presented in
Table 9-56.
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9.3.1 Recommendations for Activity Patterns
This chapter presents several studies that provide data on activity patterns. Table 9-57
summarizes information on the various studies. Recommendations for selected activities
commonly used in exposure assessments and known to increase exposure to certain chemicals are
provided to follow. These activities are time spent indoors versus outdoors, showering,
swimming, residential time spent indoors and outdoors, time spent playing on sand and gravel,
and time spent playing on grass.
Time Spent Indoors Versus Outdoors - 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.
Activities can vary significantly with differences in age. Table 9-58 summarizes the
studies that present information on time indoors and outdoors. Of these studies, Timmer et al.
(1985) in addition to being a national study, presents the data for a more comprehensive set of
age groupings for children. Timmer et al. (1985) presented data on time spent in various activities
for boys and girls ages 3-17 years. This national 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
activity, and half the times spent in each activity which could have occurred indoors or outdoors,
were summed. The results are presented in Table 9-59 For various age groups. Although there is
good agreement between the Robinson Thomas 1991 and Timmer 1985 studies, the
recommendations are based on the Timmer study because it provides data for younger children.
The recommendations are based on the Timmer data shown in Table 9-58.
Showering - The recommended shower frequency of one shower per day is based on the
NHAPS data summarized in Table 9-17. This table showed that 341 of the 451 total participants
indicated taking at least one shower the previous day.
Recommendations for showering duration are based on the study of Tsang and Klepeis
(1996). A recommended value for average showering time is 10 minutes (Table 9-18) based on
professional judgement.
Swimming - Data for swimming frequency is taken from the NHAPS Study (Tsang and
Klepeis, 1996). Of the 653 participants, who answered yes to the question "in the past month, did
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you swim in a freshwater pool?", 241 were ages 1-17 years. The results to this question are
summarized in Table 9-29. The recorded number of times respondents swam in the past month
ranged from 1 to 60 with the greatest number of respondents reporting they swam one time per
month. Thus, the recommended swimming frequency is one event/ month. The recommended
swimming duration, 60 minutes per swimming event, is based on the NHAPS distribution shown
on Table 9-30. Sixty minutes is based on an average of the 50th percentile values. 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.
Residential Time Spent Indoors and Outdoors - The recommendations for time spent
indoors at one's residence for children 1-17 years old is 18 hours/day. This is based on the
NHAPS data summarized in Table 9-41 for number of minutes spent indoors in a residence (all
rooms). The average of the 50th percentile values for all age groups is 1,061 minutes per day
(17.7 hours/day); and a 90th percentile value of 1,361 minutes per day (22.6 hours/day).
The recommended value for time spent outdoors outside one's residence is 2 hours per
day based on NHAPS data shown on Table 9-43 for time spent outdoors (outside the residence).
The 50th percentile values range from 100-150 minutes/day and the 90th percentile values range
from 300-400 minutes/day as shown in Table 9-43.
Playing on Sand or Gravel, and on Grass - The recommended value for time spent
playing on sand or gravel is 60 minutes/day. This value is based on NHAPS data shown in Table
9-25. This recommendation is based on professional judgement. The data in Table 9-25, show
that the majority of respondents are captured in the 0-0 minutes/day category. However, for the
other time categories, the majority of respondents are captured in the 50-60 minutes/day category.
The recommended value for time spent playing on grass is 60 minutes/day based on the
50th percentile data shown in Table 9-28 and the 50-60 minutes/day category data in Table 9-27.
9.3.2 Summary of Recommended Activity Factors
Table 9-59 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, taking a shower, swimming, time spent playing on
sand or gravel, and time spent playing on grass.
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9.4 REFERENCES FOR CHAPTER 9
Chance, W.G.; Harmsen, E. (1998) Children are different: environmental contaminants and children's health.
Canadian Journal of Public Health, Vol. 89, Supplement, pp. 59-513.
Davis, S. (1995) Soil ingestion in children with pica. Final Report. EPA Cooperative Agreement. CR816334.01.
Funk, L.; Sedman, R.; Beals, J.A.J.; Fountain, R. (1998) Quantifying the distribution of inhalation exposure in
human populations: distributions of time spent by adults, adolescents, and children at home, at work, and at
school. Risk Analysis. 18(l):47-56.
Hubal, E.A.; Sheldon, L.S.; Burke, J.M.; McCurdy, T.R.; Berry, M.R.; Rigas, M.L.; Zartarian, V.G.; Freeman,
N.G. (2000) Children's exposure assessment: a review of factors influencing children's exposure and the data
available to characterize and assess that exposure. Research Triangle Park, NC: U.S. Environmental Protection
Agency, National Exposure Research Laboratory.
Robinson, J.P; Thomas, J. (1991) Time spent in activities, locations, and microenvironments: a California-
National Comparison Project report. Las Vegas, NV: U.S. Environmental Protection Agency, Environmental
Monitoring Systems Laboratory.
Timmer, S.G.; Eccles, J.; O'Brien, K. (1985) How children use time. In: Juster, F.T.; Stafford, F.P.; eds. Time,
goods, and well-being. Ann Arbor, MI: University of Michigan, Survey Research Center, Institute for Social
Research, pp. 353-380.
Tsang, A.M.; Klepeis, N.E. (1996) Results tables from a detailed analysis of the National Human Activity Pattern
Survey (NHAPS) response. Draft Report prepared for the U.S. Environmental Protection Agency by Lockheed
Martin, Contract No. 68-W6-001, Delivery Order No. 13.
U.S. EPA. (1992) Dermal exposure assessment: principles and applications. Washington, DC: Office of Health
and Environmental Assessment. EPA No. 600/8-91-01 IB. Interim Report.
U.S. EPA. (1997) Exposure Factors Handbook. Washington, DC: National Center for Environmental Assessment,
Office of Research and Development. EPA/600/P-95/002Fa,b,c.
Wiley, J.A.; Robinson, J.P.; Cheng, Y.; Piazza, T.; Stork, L.; Plasden, K. (1991) Study of children's activity
patterns. California Environmental Protection Agency, Air Resources Board Research Division. Sacramento,
CA.
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Table 9-1. 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
(n=118)
Girls
(n=lll)
Boys
(n=118)
Girls
(n=lll)
Boys
(n=77)
Girls
(n=83)
Boys
(n=77)
Girls
(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
NAa
22
25
20
29
14
17
10
4
Percent of Time Accounted for
by Activities Above
94%
92%
93%
89%
93%
92%
88%
89%
a NA = Unknown
Source: Timmer et al., 1985.
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Table 9-2. 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
-
4
10
29
48
Personal Care
41
49
40
56
60
47
45
44
60
51
A,S,AxS (F>M)
Household Work
14
15
18
27
34
17
27
51
72
60
A,S, AxS (F>M)
Eating
82
81
73
69
67
81
80
78
68
65
A
Sleeping
630
595
548
473
499
634
641
596
604
562
A
School
137
292
315
344
314
-
-
-
-
-
Studying
2
8
29
33
33
1
2
12
15
30
A
Church
4
9
9
9
3
55
56
53
32
37
A
Visiting
14
15
10
21
20
10
8
13
22
56
A (Weekend only)
Sports
5
24
21
40
46
3
30
42
51
37
A,S (M>F)
Outdoor activities
4
9
8
7
11
8
23
39
25
26
Hobbies
0
2
2
4
6
1
5
3
8
3
Art Activities
5
4
3
3
12
4
4
4
7
10
Other Passive Leisure
9
1
2
6
4
6
10
7
10
18
A
Playing
218
111
65
31
14
267
180
92
35
21
A,S (M>F)
TV
111
99
146
142
108
122
136
185
169
157
A,S, AxS (M>F)
Reading
5
5
9
10
12
4
9
10
10
18
A
Being read to
2
2
0
0
0
3
2
0
0
0
A
NA
30
14
23
25
7
52
7
14
4
9
A
a Effects are significant for weekdays and weekends, unless otherwise specified A = age effect, P<0.05, for both weekdays and weekend activities; S
= sex effect P<0.05, F>M, M>F = females spend more time than males, or vice versa; and AxS = age by sex interaction, P<0.05.
Source: Timmer et al., 1985.
June 2000
9-15
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1
2
Table 9-3. Mean Time Spent Indoors and Outdoors Grouped by Age and Day of the Week
3
Age Group
Time Indoors
Time Indoors
Time Outdoors
Time Outdoors
4
(yrs)
Weekday
Weekend
Weekday
Weekend
(hrs/day)
(hrs/day)
(hrs/day)
(hrs/day)
5
3-5
1.94
18.9
2.5
3.1
6
6-8
20.7
18.6
1.8
2.5
7
9-11
20.8
18.6
1.3
2.3
8
12-14
20.7
18.5
1.6
1.9
9
15-17
19.9
17.9
1.4
2.3
10
11 Source: Adapted from Timmer et al. (1985).
June 2000
9-16
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1 Table 9-4. Mean Time Spent at Three Locations for both CARB and
2 National Studies (ages 12 years and older)
3
4 Mean duration (mins/day)
5 Location Category CARB National
(n= 1762)" ST^ (n = 2762)" Sii_
6 Indoor 1255c 28 1279c 21
7 Outdoor 86d 5 74d 4
8 In-Vehicle 98f 4 87^ 2
9 Total Time Spent 1440 1440
10
11 a S.E. = Standard Error of Mean
12 b Weighted Number - National sample population was weighted to obtain a ratio of 46.5 males and 53.5 females, in equal
13 proportion for each day of the week, and for each quarter of the year.
14 c Difference between the mean values for the CARB and national studies is not statistically significant.
15 d Difference between the mean values for the CARB and national studies is statistically significant at the 0.05 level.
16 Source: Robinson and Thomas, 1991.
June 2000
9-17
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Table 9-5. 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
Microenvironment
N =1284b
Male
"Doer"c
Male
N =1478b
Female
"Doer"
Female
N = 2762b
Total
"Doer"
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
W ork/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
491CI 41
492
496 (11)
497
494 (9)
495
CARB Data
Mean Duration (mins/day) (standard
error)"
Microenvironment
N = 867b
Male
"Doer"c
Male
N = 895b
Female
"Doer"
Female
N =1762b
Total
"Doer"
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
W ork/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
c Doer = Respondents who reported participating in each activity/location spent in microenvironments.
Source: Robinson and Thomas, 1991.
June 2000
9-18
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
Table 9-6. 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)3
Mean Duration for
"Doer"b
Microenvironment
(mins/day)
(mins/day)
CARB
NAT
(n=1259)c
(n=1973)c
CARB
NAT
1 Autoplaces
21(5)
3(1)
108
73
2 Restaurant/Bar
29 (3)
20 (2)
83
73
3 In-Vehicle/Internal Combustion
90 (5)
85 (2)
104
95
4 In-Vehicle/Other
3(1)
1(0)
71
116
5 Physical/Outdoors
14(2)
15(2)
106
118
6 Physical/Indoors
7(1)
8(1)
64
68
7 Work/Study-Residence
14(2)
16(2)
116
147
8 Work/Study-Other
228 (11)
225 (8)
401
415
9 Cooking
27 (2)
35(2)
58
57
10 Other Activities/Kitchen
51(3)
73 (3)
76
87
11 Chores/Child
99 (5)
124 (4)
108
125
12 Shop/Errand
30 (2)
30 (2)
67
63
13 Other/Outdoors
67 (6)
51(4)
117
107
14 Social/Cultural
42 (3)
62 (3)
99
101
15 Leisure-Eat/Indoors
230 (9)
211(6)
244
218
16 Sleep/Indoors
490 (14)
481(10)
495
483
Weekend Mean Duration (standard error)3 Mean Duration for "Doer"b
Microenvironment (mins/day) (mins/day)
CARB
(n=503)c
NAT
(n=789)c
CARB
NAT
1 Autoplaces
19(4)
3(1)
82
62
2 Restaurant/Bar
55(6)
23 (2)
127
84
3 In-Vehicle/Internal Combustion
108 (8)
91(6)
125
100
4 In-Vehicle/Other
5(3)
0(0)
130
30
5 Physical/Outdoors
23 (3)
23 (4)
134
132
6 Physical/Indoors
7(1)
9(2)
72
80
7 Work/Study-Residence
10(2)
15(3)
155
165
8 Work/Study-Other
74(11)
64 (6)
328
361
9 Cooking
27 (2)
34 (2)
60
55
10 Other Activities/Kitchen
44 (3)
73 (4)
71
90
11 Chores/Child
103 (7)
120 (5)
114
121
12 Shop/Errand
35(4)
35(3)
81
75
13 Other/Outdoors
74(7)
67 (7)
126
132
14 Social/Cultural
79 (7)
99 (6)
140
141
15 Leisure-Eat/Indoors
256 (12)
257(11)
273
268
16 Sleep/Indoors
520 (20)
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.
June 2000
9-19
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
Table 9-7. 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 years
N=340b
"Doer"
Age 18-24 years
N=340
"Doer"
Autoplaces
2(1)
73
7(2)
137
Restaurant/bar
9(2)
60
28(3)
70
In-vehicle/internal combustion
79 (7)
88
103 (8)
109
In-vehicle/other
0(0)
12
1(1)
160
Physical/outdoors
32(8)
130
17(4)
110
Physical/indoors
15(3)
87
8(2)
76
Work/study-residence
22 (4)
82
19(6)
185
Work/study-other
159(14)
354
207 (20)
391
Cooking
11(3)
40
18(2)
39
Other activities/kitchen
53 (4)
64
42 (3)
55
Chores/child
91(7)
92
124 (9)
125
Shop/errands
26 (4)
68
31(4)
65
Other/outdoors
70(13)
129
34(4)
84
Social/cultural
87(10)
120
100(12)
141
Leisure-eat/indoors
237(16)
242
181 (11)
189
Sleep/indoors
548 (31)
551
511 (26)
512
CARB Data
Microenvironment
Mean Duration (Standard Error)"
Age 12-17 years
Age 18-24 years
N=183b
"Doer"
N=250
"Doer"
Autoplaces
16(8)
124
16(4)
71
Restaurant/bar
16(4)
44
40 (8)
98
In-vehicle/internal combustion
78(11)
89
111 (13)
122
In-vehicle/other
1(0)
19
3(1)
60
Physical/outdoors
32(7)
110
13(3)
88
Physical/indoors
20 (4)
65
5(2)
77
Work/study-residence
25 (5)
76
30(11)
161
Work/study-other
196 (30)
339
201 (24)
344
Cooking
3(1)
19
14(2)
40
Other activities/kitchen
31(4)
51
31(5)
55
Chores/child
72(11)
77
79 (8)
85
Shop/errands
14(3)
50
35(7)
71
Other/outdoors
58(8)
78
80(15)
130
Social/cultural
63 (14)
109
65(10)
110
Leisure-eat/indoors
260 (27)
270
211(19)
234
Sleep/indoors
557(44)
560
506 (30)
510
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.
June 2000
9-20
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Table 9-8. Mean Time (minutes/day) Children Ages 12 Years and Under Spent in Ten Major
Activity Categories for All Respondents
Activity Category
Mean
Duration
(mills dav)
%
Doina
Mean
Duration
for Doersb
(mills dav)
Median
Duration
for Doer
(mills dav)
Maximum
Duration
for Doers
(mills dav)
Detailed Activity with
Highest Avg. Minutes
("code")
Work-related"
10
25
39
30
405
Eating at work/school/daycare (06)
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 Care0
794
100
794
770
1440
Night sleep (45)
Education11
110
35
316
335
790
School classes (50)
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
Leisure
192
93
205
180
898
TV use (91)
Don't know/Not coded
2
4
41
15
600
All Activities6 1441
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.
June 2000
9-21
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Table 9-9. Mean Time Children Spent in Ten Major Activity Categories Grouped by Age and Gender
Mean Duration (minutes/day)
Activity
Category
0-2 yrs
3-5 yrs
Boys
6-8 yrs
9-11 yrs
0-11
yrs
0-2 yrs
3-5 yrs
Girls
6-8 yrs
9-11 yrs
0-11
yrs
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 Care"
914
799
736
690
792
906
816
766
701
797
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 Activities0
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.
c The column totals may differ from 1440 due to rounding error.
Source: Wiley et al., 1991.
June 2000
9-22
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Table 9-10. Mean Time Children Ages 12 Years and Under Spent in Ten Major Activity Categories
Grouped by Seasons and Regions
Mean Duration (minutes/day)
Activity Category Season Region of California
Winter Spring Summer Fall All So. Bay Rest of All
(Jan-Mar) (Apr-June) (July-Sept) (Oct-Dec) Seasons Coast Area State Regions
Work-related
10
10
6
13
10
10
10
8
10
Household
47
58
53
52
53
45
62
55
53
Childcare
<1
1
<1
<1
<1
<1
<1
1
<1
Goods/Services
19
17
26
23
21
20
21
23
21
Personal Needs and
Care"
799
774
815
789
794
799
785
794
794
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/Passi
ve 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 Activities0
1442
1439
1441
1441
1441
1440
1442
1439
1441
Sample Sizes
(Unweighted)
318
204
407
271
1200
224
263
713
1200
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.
c The column totals may not be equal to 1440 due to rounding error.
Source: Wiley et al., 1991.
June 2000
9-23
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Table 9-11. Mean Time Children Ages 12 Years and Under Spent in Six Major Location Categories for All Respondents (minutes/day)
Location Category
Mean
Duration
(mins)
%
Doing
Mean
Duration
for Doers
(mins)
Median
Duration
for Doers
(mins)
Maximum
Duration for
Doers
(mins)
Detailed Location with Highest Avg.
Time
Home
1,078
99
1,086
1,110
1,440
Home - bedroom
School/Childcare
109
33
330
325
1,260
School or daycare facility
Friend's/Other's House
80
32
251
144
1,440
Friend's/other's house - bedroom
Stores, Restaurants, Shopping
Places
24
35
69
50
475
Shopping mall
In-transit
69
83
83
60
1,111
Traveling in car
Other Locations
79
57
139
105
1,440
Park, playground
Don't Know/Not Coded
<1
1
37
30
90
-
All Locations
1,440
Source: Wiley et al., 1991.
Table 9-12. Mean Time Children Spent in Six Location Categories Grouped by Age and Gender
Mean Duration (minutes/day)
Boys Girls
Location Category
0-2 yrs
3-5 yrs
6-8 yrs
9-11 yrs
All
Boys
0-2 yrs
3-5 yrs
6-8 yrs
9-11 yrs
All
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,
Shopping Places
21
25
22
15
21
23
35
27
26
28
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 Locations"
1,439
1,440
1,439
1,440
1,439
1,438
1,440
1,440
1,440
1,440
Sample Sizes
(Unweighted)
172
151
145
156
624
141
151
124
160
576
a The column totals may not sum to 1,440 due to rounding error.
Source: Wiley et al., 1991.
June 2000
9-24
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Table 9-13. Mean Time Children Spent in Six Location Categories Grouped by Season and Region
Mean Duration (minutes/day)
Season Region of California
Location Category
Winter
(Jan-Mar)
Spring
(Apr-June)
Summer
(July-Sept)
Fall
(Oct-Dec)
All
Seasons
So.
Coast
Bay
Area
Rest of
State
All
Regions
Home
1,091
1,042
1,097
1,081
1,078
1,078
1,078
1,078
1,078
School/Childcare
119
141
52
124
109
113
103
108
109
Friend's/Other's House
69
75
108
69
80
73
86
86
80
Stores, Restaurants,
Shopping Places
22
21
30
24
24
26
23
23
24
In-transit
75
75
60
65
69
71
73
63
69
Other Locations
63
85
93
76
79
79
76
81
79
Don't Know/Not Coded
<1
<1
<1
<1
<1
<1
<1
<1
<1
All Locations"
1,439
1,439
1,440
1,439
1,439
1,439
1,440
1,440
1,439
Sample Sizes
(Unweighted N's)
318
204
407
271
1,200
224
263
713
1,200
a The column totals may not sum to 1,440 due to rounding error.
Source: Wiley et al., 1991.
Table 9-14. Mean Time Children Spent in Proximity to Three Potential Exposures Grouped by All Respondents, Age, and Gender
Mean Duration (minutes/day)
Boys Girls
Potential
Exposures
All
Children
0-2 yrs
3-5 yrs
6-8 yrs
9-11 yrs
All
Boys
0-2 yrs
3-5 yrs
6-8 yrs
9-11 yrs
All
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
(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.
June 2000
9-25
DRAFT-DO NOT QUOTE OR CITE
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Child-Days.
.
i
ฆ
I
I
3
i
uix
|
i
|
|
9
il i
<2.23 3 3-5 * A3 5 SlS 6 U 7 . M ซ 15 . 3 .15 10 .10J 11 11J5-12 IZIi 13 JXS M >14
Hours Indoors At Home
Figure 9-1. Distribution of the Number of Hours per Day Study Children Spent Indoors at Home
Source: Davis 1995.
June 2000
9-27
DRAFT-DO NOT QUOTE OR CITE
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Figure 9-2. Distribution of the Number of Hours per Day Study Children Spent Indoors Away from Home
Source: Davis 1995.
9-28 DRAFT-DO NOT QUOTE OR CITE
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Number of
Child-Days
140fl
a ซJ- 1 IS 2 2Jป 3 3.5 4 ' 4.5
5- 45- . S .. ปs
Hours Outdoors At Home
Figure 9-3. Distribution of the Number of Hours per Day Study Children Spent Outdoors at Home
Source: Davis 1995.
June 2000 9-29 DRAFT-DO NOT QUOTE OR CITE
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Number of
Child-Days
Hours Outdoors Away From Home
Figure 9-4, Distribution of the Number of Hours per Day Study Children Spent Outdoors Away at Home
Source; Davis 1995.
June 2000
9-30 DRAFT-DO NOT -QUOTE OR OTt
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1 Table 9-15. Mean Time Spent Indoors and Outdoors Grouped by Age
2
3
4
Age Groups
Time Indoors
(hours/day)
Time Outdoors
(hours/day)
5
0-2
20
4
6
3-5
18.8
5.2
7
6-8
19.7
4.4
8
9-11
19.9
4.1
9
10
11
June 2000
9-30
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
Table 9-16. Range of Recommended Defaults for Dermal Exposure Factors
Water Contact
Soil Contact
Bathing
Swimming
Central
Upper
Central
Upper
Central
Upper
Event time
10 min/event
15 min/event
0.5 hr/event
1.0 hr/event
40 events/yr
350 events/yr
and
1 event/day
1 event/day
1 event/day
1 event/day
frequency3
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
" Bathing event time is presented to be representative of baths as well as showers.
Source: U.S. EPA 1992.
Table 9-17. Number of Times Taking a Shower at Specified Daily Frequencies by the Number of Respondents
Total N
Times/Day
10 11:1-0+ DK
Age (years)
1-4
5-11
12-17
41
140
270
30
112
199
9
26
65
Note: * Signifies missing data; Dk= don't know; N = sample size.
Source: Tsang and Klepeis, 1996
Table 9-18. Time (minutes) Spent Taking a Shower and Spent in the Shower Room
After Taking a Shower by the Number of Respondents
Minutes/Shower
Total N
0-10
10-20
20-30
30-40
40-50
50-60
60-61
Times (minutes) Spent Taking Showers by the Number of Respondents
Age
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
Time (minutes) Spent in the Shower Room Immediately After Showering by the Number of Respondents
Age (years)
1-4
41
*
5
31
3
1
*
1
*
5-11
140
3
9
110
14
3
*
*
1
17-17
770
1
17
706
79
10
3
7
1
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 9-19. Time (minutes) Spent Taking a Shower and Spent in the Shower Immediately After Showering
June 2000
9-31
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Table 9-19. Time (minutes) Spent Taking a Shower and Spent in the Shower Immediately After Showering
Percentiles
Category
Population Group
N
1
2
5
10
25
50
75
91
95
98
99
100
Number of Minutes Spent Taking
a
Shower (minutes/shower)
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
Number of Minutes Spent in the Shower Room Immediately After Showering (minutes/shower)
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
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 9-20. Total Time Spent Altogether in the Shower or Bathtub and Time Spent
in the Bathroom Immediately After by 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- 110- 121-
N 100 110 120 121
Total Time Spent Altogether in the Shower or Bathtub by the Number of Respondents
Age (years)
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
*
Time Spent in the Bathroom Immediately Following a Shower or Bath by the Number of Respondents
Age (years)
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
*
*
*
*
*
*
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
June 2000
9-32
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Table 9-21. Total Number of Minutes Spent Altogether in the Shower or Bathtub and Spent
in the Bathroom Immediately Following a Shower or Bath
Percentiles
Category Population Group
N 1 2 5 10 25 50 75 90 95 98 99 100
Total Number of Minutes Spent Altogether in the Shower or Bathtub (minutes/bath)
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
Number of Minutes Spent
in the Bathroom Immediately Following a Shower or Bath (minutes/bath)
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
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 9-22. 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
Age (years)
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
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 9-23. 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
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
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.
June 2000
9-33
DRAFT-DO NOT QUOTE OR CITE
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Table 9-24. Range of Number of Times per Day a Motor Vehicle was Started in a Garage or Carport
and Started with the Garage Door Closed
Times/day
Total N 1-2 3-5 6-9
10+
Dk
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
Age(years)
1-4
5-11
12-17
111 68 39 2
150 93 49 6
145 86 42 12
2
*
1
*
2
4
Range of the Number of Times Motor Vehicle Was Started with Garage Door Closed
at Specified Daily Frequencies by the Number of Respondents
Age (years)
1-4
5-11
12-17
111 99 8 2
150 141 6 *
145 127 9 4
*
*
1
2
3
4
Note: Signifies missing data; "DK" = respondent answered don't know; Refused - the respondent refused to answer; N =
Source: Tsang and Klepeis, 1996
= doer sample size.
Table 9-25. Number of Minutes Spent Playing on Sand, Gravel, Dirt, or Grass
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
Number of Minutes Spent Playing on Sand or Gravel in a Day by the Number of Respondents
Age (years)
1-4
5-11
12-17
216 13 115 15 9 15 2 3 15 1 5
200 7 96 11 12 14 * 5 25 1 2
41 1 23 124**3**
*
1
1
7
6
3
16
20
3
Number of Minutes Spent Playing in Outdoors on Sand, Gravel, Dirt, or Grass
When Fill Dirt Was Present by the Number of Respondents
Age (years)
*
1-4
5-11
12-17
18-64
>64
^ **J****J**
216 11 118 14 10 13 1 4 18 4 *
200 15 103 14 8 15 * 1 17 1 *
41 3 19 3 2 7 * * 4 1 *
237 23 138 19 9 13 * 1 20 1 1
3 12 * * * *****
*
7
9
2
3
*
1
16
17
*
9
*
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.
June 2000
9-34
DRAFT-DO NOT QUOTE OR CITE
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Table 9-26. Number of Minutes Spent Playing in Sand, Gravel, Dirt or Grass (minutes/day)
Percentiles
Category
Population Group
N
1
2
5
10
25
50
75 90 95
98
99
100
Number of Minutes Spent Playing on
Sand or Gravel (minutes/day)
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
Number of Minutes Spent Playing on
Sand, Gravel, Dirt, or Grass When Fill Dirt Was Present (minutes/day)
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
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 9-27. 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
Age (years)
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
NOTE: signifies missing data. 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 9-28. 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
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
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
June 2000
9-35
DRAFT-DO NOT QUOTE OR CITE
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Table 9-29. 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
Age (years)
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
*
Times/Month
18
20
23
24
25
26
28
29
30
31
32
40
42
45
50
60
DK
Age (years)
1-4
*
2
*
*
*
*
*
1
2
*
1
*
*
*
*
*
*
5-11
*
3
*
1
2
*
*
*
5
*
*
*
*
*
1
*
*
12-17
1
4
*
*
*
1
*
*
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 9-30. 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
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
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 9-31. Range of the Average Amount of Time Actually Spent in the Water by Swimmers by the Number of Respondents
Minutes/Month
Total 90-100 110- 150- 180- 181-
N *-* 0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 120 150 180 181
Age (years)
1-4 63 3 5 12 12 1 4 8 * * 2 * 7 1 3 5
5-11 100 5 3 2 12 5 4 25 * * 7 * 16 2 11 8
12-17 84 1 3 7 10 2 6 15 * 1 8 1 14 4 6 6
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.
June 2000
9-36
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Table 9-32. Statistics for 24-Hour Cumulative Number of Minutes Spent Playing Indoors and Outdoors
Percentiles
Category Population Group
N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99
Statistics for 24-Hour Cumulative Number of Minutes Spent in Indoor Playing
Age (years) 1-4 11 130 80.2 24.2 15 270 15 60 115 180 255 270 270 270
Age (years) 5-11 11 93.6 64.3 19.4 30 195 30 30 60 175 180 195 195 195
Age (years) 12-17 4 82.5 45 22.5 30 120 30 45 90 120 120 120 120 120
Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Playing
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
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 9-33. 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
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
Note: "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 9-34. 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
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
Note: "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.
June 2000
9-37
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Table 9-35. Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports
and for Time Spent in Sports/Exercise
Percentiles
Category
Population Group N
Mean
Stdev
Stderr
Min
Max
5
25
50
75
90
95
98
99
Statistics for 24-Hour Cumulative Number of Minutes Spent
in Active Sports
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
Statistics for 24-Hour Cumulative Number of Minutes Spent in
Sports/Exercise (a)
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
a Includes active sports, exercise, hobbies.
Note: "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 9-36. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Recreation and Spent Walking
Percentiles
Category
Population Group
N Mean Stdev
Stderr
Min
Max
5
25
50
75
90
95
98
99
Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Recreation
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
Statistics for 24-Hour Cumulative Number of Minutes Spent Walking
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
Note: "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.
June 2000
9-38
DRAFT-DO NOT QUOTE OR CITE
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Table 9-37. 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
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
a Includes baby and child care, personal care services, washing and personal hygiene (bathing, showering, etc.)
Note: "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 9-38. 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
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
Note: "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 9-39. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at School and Indoors at a Restaurant
Percentiles
Category
Population Group N
Mean
Stdev
Stderr
Min
Max
5
25
50
75
90
95
98
99
Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at School
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
Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors
at a Restaurant
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
Note: "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.
June 2000
9-39
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Table 9-40. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on School Grounds/Playground,
at a Park/Golf Course, and at a Pool/River/Lake
Percentiles
Category
Population Group
N
Mean
Stdev Stderr
Min
Max
5
25
50
75
90
95
98
99
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on School Grounds/Playground
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
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors a
a Park/Golf Course
Age (years)
1-4
21
149.857
176.25 38.4609
21
755
25
50
85
150
360
425
755
755
Age (years)
5-11
54
207.556
184.496 25.1068
25
665
35
70
125
275
555
635
660
665
Age (years)
12-17
52
238.462
242.198 33.5869
15
1065
15
60
147.5
337.5
590
840
915
1065
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Pool/River/Lake
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
Note: "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.
June 2000
9-40
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Table 9-41. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Kitchen
Bathroom, Bedroom, and in a Residence (All Rooms)
Percentiles
Category
Population Group N Mean Stdev
Stderr
Min
Max
5
25
50
75
90
95
98
99
Statistics for 24-Hour Cumulative Number of Minutes Spent a
Home in the Kitchen
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
Statistics for 24-Hour Cumulative Number of Minutes Spent in the Bathroom
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
Statistics for 24-Hour Cumulative Number of Minutes Spent at
Home in the Bedroom
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
Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors in a Residence (all rooms)
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
Note: "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.
June 2000
9-41
DRAFT-DO NOT QUOTE OR CITE
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Table 9-42. 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
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
Note: "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 9-43. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors (outside the residence) and 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
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors (outside the residence)
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
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Other Than
Near a Residence or Vehicle Such as Parks, Golf Courses, or Farms
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
Note: "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 9-44. 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
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
Note: "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.
June 2000
9-42
DRAFT-DO NOT QUOTE OR CITE
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Table 9-45. 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
Age (years)
1-4
155
366.56
324.46
26.062
5
1440
30
90
273
570
825
1010
1140
1305
Age (years)
5-11
224
318.07
314.02
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
9-43
-------
Table 9-46. Range of Time (minutes) Spent Smoking Based on the Number of Respondents
Number of Minutes
Total N
*_*
0-60
60-
120-
180-
240-
300-
360-
420-
480-
540-
600-
120
180
240
300
360
420
480
540
600
660
Age (years)
1-4
499
344
29
23
14
8
10
7
8
7
8
7
5
5-11
703
479
40
38
32
23
10
9
6
12
6
11
6
12-17
589
333
75
31
30
20
22
15
13
7
13
5
3
Number of Minutes
660-
720
720-
780
780-
840
840-
900
900-
960
960- 1020- 1080-
1020 1080 1140
1140-
1200
1200-
1260
1260-
1320
1320-
1380
1380-
1440
Age (years)
1-4
5-11
12-17
1 *
2 3
* 2
Note: * = Missing Data; DK =Don't know; N = Number of Respondents; Refused = Respondent Refused to Answer.
Source: Tsang And Klepeis, 1996.
Table 9-47. Number of Minutes Spent Smoking (minutes/day)
Percentiles
Category
Population Group
N
1
2
5
10
25
50
75
90
95
98
99
100
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
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.
June 2000
9-44
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
Table 9-48.
Gender and Age Groups
4
Gender-Age Group
Subgroup
n
Age Range
5
Adolescents
Males
98
12-17 years
6
Females
85
12-17 years
7
Children3
Young males
145
6-8 years
8
Young females
124
6-8 years
9
Old males
156
9-11 years
10
Old females
160
9-11 years
11
12 a Children under the age of 6 are excluded for the present study (too few responses in CARB study).
13
14 Source: Funk et al., 1998.
15
16
17
June 2000
9-45
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Table 9-49. Assignment of At-Home Activities to Ventilation Levels for Children
Low
Moderate
Watching child care
Outdoor cleaning
Night sleep
Food Preparation
Watch Personal care
Metal clean-up
Homework
Cleaning house
Radio use
Clothes care
TV use
Car/boat repair
Records/tapes
Home repair
Reading books
Plant care
Reading magazines
Other household
Reading newspapers
Pet care
Letters/writing
Baby care
Other leisure
Child care
Homework/watch TV
Helping/teaching
Reading/TV
Talking/reading
Reading/listen music
Indoor playing
Paperwork
Oudoor playing
Medical child care
Washing, hygiene
Medical care
Help and care
Meals at home
Dressing
Visiting at home
Hobbies
Domestic crafts
Art
Music/dance/drama
Indoor dance
Conservations
Painting room/home
Building fire
Washing/dressing
Outdoor play
Playing/eating
Playing/talking
Playing/watch TV
TV/eating
TV/something else
Reading book/eating
Read magazine/eat
Read newspaper/eat
Source: Funketal., 1998.
June 2000
9-46
DRAFT-DO NOT QUOTE OR CITE
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1
2
3
Table 9-50. Aggregate Time Spent (minutes/day) At-Home
by Adolescents and Children3
in Activity Groups
4
Adolescents
Children
5
Activity Group
Mean SD
Mean
SD
6
Low
789 230
823
153
7
8
Moderate
High
197 131
1 11
241b
3
136
17
9
I Ii^lin;nl ul n;UIK
43 72
58
47
10
11
12
13
14
15
16
17
18
19
20
a Time spent engaging in all activities embodied by Ve category (minutes/day),
b Significantly differ from adolescents (p <0.05).
c Represents time spent at-home by individuals participating in high ventilation levels.
Source: Funketal., 1998.
Table 9-51. Comparison of Mean Time (minutes/day) Spent At-Home by Gender3 (Adolescents)
21
22
Male
Female
Activity Group
Mean SD
Mean
SD
23
Low
775 206
804
253
24
Moderate
181 126
241
134
25
High
2 16
0
0
26
27
28
29
30
31
Source: Funketal., 1998.
Table 9-52. Comparison of Mean Time (minutes/day) Spent At-Home by Gender and Age for Children3
32
33
Activity
Males
Females
Group
6-
8 Years 9-11 Years
6-8
Years
9-11 Years
Mean
SD Mean SD
Mean
SD
Mean
SD
34
Low 806
134 860 157
828
155
803
162
35
Moderate 259
135 198 111
256
141
247
146
36
High 3
17 7 27
1
9
2
10
37
f h~h|);m U l I);1NI- 77
59 70 54
68
11
30
23
38
39
40
41
42
43
a Time spent engaging in all activities embodied by Ve category (minutes/day)
b Participants in high Ve activities
Source: Funketal., 1998.
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Table 9-53. Number of Person-Day s/Individuals3 for Children in CHADa Database
Age Group
All Studies
Californiab
Cincinnati0
NHAPS-Air
NHAPS-Water
0 year
223/199
104
36/12
39
44
0-6 months
50
15/5
6-12 months
54
21/7
1 year
259/238
97
31/11
64
67
12-18 months
57
18-24 months
40
2 years
317/264
112
81/28
57
67
3 years
278/242
113
54/18
51
60
4 years
259/232
91
41/14
64
63
5 years
254/227
98
40/14
52
64
6 years
237/199
81
57/19
59
40
7 years
243/213
85
45/15
57
56
8 years
259/226
103
49/17
51
55
9 years
229/195
90
51/17
42
46
10 years
224/199
105
38/13
39
42
11 years
227/206
121
32/11
44
30
Total
3009/2640
1200
556/187
619
634
a CHAD - Consolidated Human Activity Database is available on U.S. EPA Intranet.
b The California study referred to in this table is the Wiley 1991 study.
c The Cincinnati study referred to in this table is the Johnson 1989 study.
The number of person-days of data are the same as the number of individuals for all studies except for the Cincinnati study.
Since up to three days of activity pattern data were obtained from each participant in this study, the number of person-days of
data is approximately three times the number of individuals.
Source: Hubal et al., 2000.
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1 Table 9-54. Number of Hours Per Day Children Spend in Various Microenvironments by Age
2 Average ฑ Std. Dev. (Percent of Children Reporting >0 Hours in Microenvironment)
4
Age (years)
Indoors at Home
Outdoors at Home
Indoors at School
Outdoors at Park
In Vehicle
5
0
19.6 ฑ 4.3 (99%)
1.4 ฑ 1.5 (20%)
3.5 ฑ 3.7 (2%)
1.6 ฑ 1.5 (9%)
1.2 ฑ 1.0 (65%)
6
i
19.5 ฑ4.1 (99)
1.6 ฑ 1.3 (35)
3.4 ฑ 3.8 (5)
1.9 ฑ2.7 (10)
1.1 ฑ0.9 (66)
7
2
17.8 ฑ4.3 (100)
2.0 ฑ 1.7 (46)
6.2 ฑ 3.3 (9)
2.0 ฑ 1.7 (17)
1.2 ฑ 1.5 (76)
8
3
18.0 ฑ4.2 (100)
2.1 ฑ 1.8 (48)
5.7 ฑ2.8 (14)
1.5 ฑ0.9 (17)
1.4 ฑ 1.9 (73)
9
4
17.3 ฑ4.3 (100)
2.4 ฑ 1.8 (42)
4.9 ฑ 3.2 (16)
2.3 ฑ 1.9 (20)
1.1 ฑ0.8 (78)
10
5
16.3 ฑ4.0 (99)
2.5 ฑ2.1 (52)
5.4 ฑ2.5 (39)
1.6 ฑ 1.5 (28)
1.3 ฑ 1.8 (80)
11
6
16.0 ฑ4.2 (98)
2.6 ฑ 2.2 (48)
5.8 ฑ2.2 (34)
2.1 ฑ2.4 (32)
1.1 ฑ0.8 (79)
12
7
15.5 ฑ3.9 (99)
2.6 ฑ 2.0 (48)
6.3 ฑ 1.3 (40)
1.5 ฑ 1.0 (28)
1.1 ฑ 1.1 (77)
13
8
15.6 ฑ4.1 (99)
2.1 ฑ2.5 (44)
6.2 ฑ 1.1 (41)
2.2 ฑ2.4 (37)
1.3 ฑ2.1 (82)
14
9
15.2 ฑ4.3 (99)
2.3 ฑ 2.8 (49)
6.0 ฑ 1.5 (39)
1.7 ฑ 1.5 (34)
1.2 ฑ 1.2 (76)
15
10
16.0 ฑ4.4 (96)
1.7 ฑ 1.9 (40)
5.9 ฑ 1.5 (39)
2.2 ฑ 2.3 (40)
1.1 ฑ 1.1 (82)
16
11
14.9 ฑ4.6 (98)
1.9 ฑ2.3 (45)
5.9 ฑ 1.5 (41)
2.0 ฑ 1.7 (44)
1.6 ฑ 1.9 (74)
17
18 Source: Hubal et al., 2000.
19
20
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6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Table 9-55. Average Number of Hours Per Day Children Spend Doing Various
Macroactivities While Indoors at Home by Age
(Percent of Children Reporting >0 Hours for Microenvironment/macroactivity)
Age
Eat
Sleep or Nap
Shower or
Play
Watch TV or
Read, Write,
Think, Relax,
(year)
Bathe
Games
Listen to Radio
Homework
Passive
0
1.9(96%)
12.6 (99%)
0.4 (44%)
4.3 (29%)
1.1 (9%)
0.4 (4%)
3.3 (62%)
1
1.5 (97)
12.1 (99)
0.5 (56)
3.9 (68)
1.8 (41)
0.6 (19)
2.3 (20)
2
1.3 (92)
11.5 (100)
0.5 (53)
2.5 (59)
2.1 (69)
0.6 (27)
1.4 (18)
3
1.2 (95)
11.3 (99)
0.4 (53)
2.6 (59)
2.6 (81)
0.8 (27)
1.0 (19)
4
1.1 (93)
10.9 (100)
0.5 (52)
2.6 (54)
2.5 (82)
0.7 (31)
1.1 (17)
5
1.1 (95)
10.5 (98)
0.5 (54)
2.0 (49)
2.3 (85)
0.8 (31)
1.2 (19)
6
1.1 (94)
10.4 (98)
0.4 (49)
1.9 (35)
2.3 (82)
0.9 (38)
1.1 (14)
7
1.0 (93)
9.9 (99)
0.4 (56)
2.1 (38)
2.5 (84)
0.9 (40)
0.6 (10)
8
0.9 (91)
10.0 (96)
0.4 (51)
2.0 (35)
2.7 (83)
1.0 (45)
0.7 (7)
9
0.9 (90)
9.7 (96)
0.5 (43)
1.7 (28)
3.1 (83)
1.0 (44)
0.9 (17)
10
1.0 (86)
9.6 (94)
0.4 (43)
1.7 (38)
3.5 (79)
1.5 (47)
0.6 (10)
11
0.9 (89)
9.3 (94)
0.4 (45)
1.9 (27)
3.1 (85)
1.1 (47)
0.6 (10)
Source: Hubal et al., 2000.
June 2000
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2
Table 9-56. Confidence in Activity Patterns Recommendations
Considerations
Rationale
Rating
3
TIME SPENT INDOORS VS. OUTDOORS
4
Studv Elements
5
Level of peer review
The study received high level of peer review.
High
6
Accessibility
The study is widely available to the public.
High
7
Reproducibility
The reproducibility of these studies is left to question. Evidence has
Medium
shown that activities have tended to shift over the past decade since the
study was 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.
8
Focus on factor of
The study focused on general activity patterns.
High
9
interest
10
Data pertinent to US
The study focused on the U.S. population.
High
11
Primary data
Data were collected via questionnaires and interviews.
High
12
Currency
The studies were published in 1985 (data were collected 1981-1982).
Medium
13
Adequacy of data
Households were sampled 4 times during 3 month intervals from
High
14
collection period
February to December, 1981.
15
Validity of approach
A 24 hour recall time diary method was used to collect data.
High
16
Study size
The sample population was 922 children between the ages of 3-17 years
old.
High
17
Representativeness of
The study focused on activities of children.
High
18
the population
19
Characterization of
Variability was characterized by age, gender, and day of the week;
Medium
20
variability
location of activities and various age categories for children.
21
Lack of bias in study
Biases noted were sampled during time when children were in school
Medium
22
design (high rating is
(activities during vacation time are not represented); activities in the
23
desirable)
1980's may be different than they are now;
24
Measurement error
Measurement or recording error may occur since the diaries were based
Medium
on recall (in most cases a 24 hour recall).
25
Other Elements
26
Number of studies
Two
High
27
Agreement between
Difficult to compare due to varying categories of activities and the
Not
28
researchers
unique age distributions found within each study.
Ranked
29
Overall Rating
Medium
30
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Table 9-56. Confidence in Activity Patterns Recommendations (cont'd)
Considerations
Rationale
Rating
TIME SPENT SHOWERING
Study Elements
Level of peer review
Accessibility
Reproducibility
Focus on factor of
interest
Data pertinent to US
Primary data
Currency
Adequacy of data
collection period
Validity of approach
Study size
Representativeness of
the population
Characterization of
variability
Lack of bias in study
design (high rating is
desirable)
Measurement error
Other Elements
Number of studies
Agreement between
researchers
The study received high level of peer review.
Currently, raw data are available to only EPA. It is not known when data
will be publicly available.
Results are reproducible.
The study focused specifically focused on time spent showering.
The study focused on the U.S. general population.
The study was based on primary data.
The study was published in 1996.
The data were collected between October 1992 and September 1994.
The study used a valid methodology and approach which, in addition to
24-hour diaries, collected information on temporal conditions and
demographic data such as geographic location and socioeconomic status
for various U.S. subgroups.
Study consisted of 9,386 total participants consisting of all ages.
The data were representative of the U.S. population.
The study provides a distribution on showering duration.
The study includes distributions for showering duration. Study is based
on short-term data.
Measurement or recording error may occur because diaries are based on
24-hour recall.
One; the study was a national study.
Recommendation is based on only one study but it is a widely accepted
study and average value is comparable to a second key study.
High
Low
High
High
High
High
High
High
High
High
High
High
High
Medium
Low
High
Overall Rating
High
June 2000
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1 Table 9-56. Confidence in Activity Patterns Recommendations (cont'd)
2 Considerations Rationale Rating
3 SHOWER FREQUENCY
4 Study Elements
5 Level of peer review The study received high level of peer review. High
6 Accessibility Currently, raw data is available to only EPA. It is not known when data Low
will be publicly available.
7 Reproducibility Results can be reproduced or methodology can be followed and evaluated High
provided comparable economic and social conditions exists.
8 Focus on factor of The survey collected information on duration and frequency of selected High
9 interest activities and time spent in selected micro-environments.
10 Data pertinent to US The data represents the U.S. population High
11 Primary data The study was based on primary data. High
12 Currency The study was published in 1996. High
13 Adequacy of data The data were collected between October 1992 and September 1994. High
14 collection period
15 Validity of approach The study used a valid methodology and approach which, in addition to High
24-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.
16 Study size The study consisted of 9,386 total participants consisting of all age High
groups
17 Representativeness of Studies were based on the U.S. population. High
18 the population
19 Characterization of The study provided data that varied across geographic region, race, High
20 variability gender, employment status, educational level, day of the week, seasonal
conditions, and medical conditions of respondent..
21 Lack of bias in study Study is based on short term data.. Medium
22 design (high rating is
23 desirable)
24 Measurement error Measurement or recording error may occur because diaries were based Medium
on 24-hour recall.
25 Other Elements
26 Number of studies One; the study was based on one, primary, national study. Low
27 Agreement between Recommendation was based on only one study. Not
28 researchers Ranked
29 Overall Rating High
June 2000
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1 Table 9-56. Confidence in Activity Patterns Recommendations (cont'd)
2 Considerations Rationale Rating
3 TIME SPENT SWIMMING
4 Study Elements
5 Level of peer review Study received high level of peer review. High
6 Accessibility Currently, raw data is available to only EPA. It is not known when data Low
will be publicly available.
7 Reproducibility Results can be reproduced or methodology can be followed and High
evaluated provided comparable economic and social conditions exists.
8 Focus on factor of The survey collected information on duration and frequency of selected High
9 interest activities and time spent in selected micro-environments.
10 Data pertinent to US The data represents the U.S. population High
11 Primary data The study was based on primary data. High
12 Currency The study was published in 1996. High
13 Adequacy of data The data were collected between October 1992 and September 1994. High
14 collection period
15 Validity of approach The study used a valid methodology and approach which, in addition to High
24-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.
16 Study size The study consisted of 9,386 total participants consisting of all age High
groups
17 Representativeness of Studies were based on the U.S. population. High
18 the population
19 Characterization of The study provided data that varied across geographic region, race, High
20 variability gender, employment status, educational level, day of the week, seasonal
conditions, and medical conditions of respondent..
21 Lack of bias in study The study includes distributions for swimming duration. Study is based Medium
22 design (high rating is on short term data.
23 desirable)
24 Measurement error Measurement or recording error may occur because diaries were based Medium
on 24-hour recall.
25 Other Elements
26 Number of studies One; the study was based on one, primary, national study. Low
27 Agreement between Recommendation was based on only one study. Not
28 researchers Ranked
29 Overall Rating High
June 2000
9-54
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1 Table 9-56. Confidence in Activity Patterns Recommendations (cont'd)
2 Considerations Rationale Rating
3 RESIDENTIAL TIME SPENT INDOORS AND OUTDOORS
4 Study Elements
5 Level of peer review The study received high level of peer review. High
6 Accessibility Currently, raw data is available to only EPA. It is not known when data Low
will be publicly available.
7 Reproducibility Results can be reproduced or methodology can be followed and evaluated High
provided comparable economic and social conditions exists.
8 Focus on factor of The survey collected information on duration and frequency of selected High
9 interest activities and time spent in selected micro-environments.
10 Data pertinent to US The data represents the U.S. population High
11 Primary data The study was based on primary data. High
12 Currency The study was published in 1996. High
13 Adequacy of data Data were collected between October 1992 and September 1994. High
14 collection period
15 Validity of approach The study used a valid methodology and approach which, in addition to High
24-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.
16 Study size The study consisted of 9,386 total participants consisting of all age High
groups
17 Representativeness of The studies were based on the U.S. population. High
18 the population
19 Characterization of The study provided data that varied across geographic region, race, High
20 variability gender, employment status, educational level, day of the week, seasonal
conditions, and medical conditions of respondent..
21 Lack of bias in study The study includes distribitions for time spent indoors and outdoors at Medium
22 design (high rating is ones residence. Study is based on short term data.
23 desirable)
24 Measurement error Measurement or recording error may occur because diaries were based Medium
on 24-hour recall.
25 Other Elements
26 Number of studies One; the study was based on one, primary, national study. Low
27 Agreement between Recommendation was based on only one study. Not
28 researchers Ranked
29 Overall Rating High
June 2000
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1 Table 9-56. Confidence in Activity Patterns Recommendations (cont'd)
2 Considerations Rationale Rating
3 TIME SPENT PLAYING ON GRASS
4 Study Elements
5 Level of peer review The study received high level of peer review. High
6 Accessibility Currently, raw data are available to only EPA. It is not known when Low
data will be publicly available.
7 Reproducibility Results can be reproduced or methodology can be followed and evaluated High
provided comparable economic and social conditions exists.
8 Focus on factor of The survey collected information on duration and frequency of selected High
9 interest activities and time spent in selected micro-environments.
10 Data pertinent to US The data represents the U.S. population. High
11 Primary data The study was based on primary data. High
12 Currency The study was published in 1996. High
13 Adequacy of data The data were collected between October 1992 and September 1994. High
14 collection period
15 Validity of approach The study used a valid methodology and approach which, in addition to High
24-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.
16 Study size The study consisted of 9,386 total participants consisting of all age High
groups.
17 Representativeness of The studies were based on the U.S. population. High
18 the population
19 Characterization of The study provided data that varied across geographic region, race, High
20 variability gender, employment status, educational level, day of the week, seasonal
conditions, and medical conditions of respondent..
21 Lack of bias in study The study includes distributions for bathing duration. Study is based on Medium
22 design (high rating is short-term data.
23 desirable)
24 Measurement error Measurement or recording error may occur because diaries were based Medium
on 24-hour recall.
25 Other Elements
26 Number of studies One; the study was based on one, primary, national study. Low
27 Agreement between Recommendation was based on only one study. Not
28 researchers Ranked
29 Overall Rating High
30
June 2000
9-57
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1 Table 9-56. Confidence in Activity Patterns Recommendations (cont'd)
2 Considerations Rationale Rating
3 TIME SPENT PLAYING ON GRASS
4 Study Elements
5 Level of peer review The study received high level of peer review. High
6 Accessibility Currently, raw data are available to only EPA. It is not known when Low
data will be publicly available.
7 Reproducibility Results can be reproduced or methodology can be followed and evaluated High
provided comparable economic and social conditions exists.
8 Focus on factor of The survey collected information on duration and frequency of selected High
9 interest activities and time spent in selected micro-environments.
10 Data pertinent to US The data represents the U.S. population. High
11 Primary data The study was based on primary data. High
12 Currency The study was published in 1996. High
13 Adequacy of data The data were collected between October 1992 and September 1994. High
14 collection period
15 Validity of approach The study used a valid methodology and approach which, in addition to High
24-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.
16 Study size The study consisted of 9,386 total participants consisting of all age High
groups.
17 Representativeness of The studies were based on the U.S. population. High
18 the population
19 Characterization of The study provided data that varied across geographic region, race, High
20 variability gender, employment status, educational level, day of the week, seasonal
conditions, and medical conditions of respondent..
21 Lack of bias in study The study includes distributions for bathing duration. Study is based on Medium
22 design (high rating is short-term data.
23 desirable)
24 Measurement error Measurement or recording error may occur because diaries were based Medium
on 24-hour recall.
25 Other Elements
26 Number of studies One; the study was based on one, primary, national study. Low
27 Agreement between Recommendation was based on only one study. Not
28 researchers Ranked
29 Overall Rating High
30
June 2000
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1
2
Table 9-57. Summary of Activity Pattern Studies
3 Summary of Activity Patterns Studies
4
Study
Age Groups
(yrs)
Sample Size
Population
Activities
5
Timmer (1985)
3-5, 6-8, 9-11, 12-
14, 15-17
922
National
18 microenvironments
6
Robinson & Thomas (1991)
12-adults
1,762
(California)
2,762 (national)
California and
national
16 microenvironments
7
Wiley (1991)
0-2, 3-5,6-8, 9-11
1,200
California
10 microenvironments
8
Davis (1995)
10-60 (months)
92
Washington State
Activities grouped
into indoors and
outdoors
9
Tsang & Kleipeis (1996)
1-4, 5-11, 12-17
Varies with age
groups and
activities
U.S. national
23 microenvironments
10
Funk (1998)
6-11, 12-17
768
California
Activities grouped
into low, medium, and
high ventilation levels
11
Hubal (2000)
0, 1,2,3,4,5,6, 7,
8, 9, 10, 11
2,640
Based on Wiley
(1991), Johnson
(1989), and Tsang
& Kleipeis (1996)
Activities grouped
into indoors at home,
indoors at school,
outdoors at home,
outdoors at part, and
in vehicle
12
June 2000
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2
Table 9-58. Summary of Mean Time Spent Indoors and Outdoors from Several Studies
3
Age (years)
Time Indoors
(hours/day)1
Time Outdoors
(hours/day)1
Study
4
3-5
19
2.8
Timmer 1985
5
6-8
20
2.2
6
9-11
20
1.8
7
12-14
20
1.8
8
15-17
19
1.9
9
12 and older
21 (national)
1.2 (national
Robinson and Thomas 1991
21 (California)
1.4 (California)
10
0-2
20
4
Wiley 1991
11
3-5
18.8
5.2
12
6-8
19.7
4.4
13
9-11
19.9
4.1
14
15 1 Mean of weekday and weekend rounded up to two significant figures.
June 2000
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1
2
Table 9-59. Summary of Recommended Values for Activity Factors
3 Type Value Study
4
Time Indoors
Ages 3-5 years (19 hours/day)
Ages 6-14 years (20 hours/day)
Ages 12-17 years (19 hours/day)
Timmeretal., 1985
5
Time Outdoors
Ages 3-5 years (2.8 hours/day)
Ages 6-8 years (2.2 hours/day)
Ages 9-14 years (1.8 hours/day)
Ages 15-17 years (1.9 hours/day)
6
Taking Showers
10 min/day shower duration
1 shower event/day
Tsang and Klepeis,
Tsang and Klepeis,
1996
1996
7
Swimming
1 event/month
60 minutes/event
Tsang and Klepeis,
1996
8
9
10
Residential
Indoors
Outdoors
18 hr/day
2 hr/day
Tsang and Klepeis,
1996
11
Playing on Sand or Gravel
60 min/day
Tsang and Klepeis,
1996
12
Playing on Grass
60 min/day
Tsang and Klepeis,
1996
13
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TABLE OF CONTENTS
10. CONSUMER PRODUCTS 10-1
10.1 BACKGROUND 10-1
10.2 CONSUMER PRODUCTS USE STUDIES 10-1
10.3 RECOMMENDATIONS 10-2
10.4 REFERENCES FOR CHAPTER 10 10-3
-------
LIST OF TABLES
Table 10-1. Consumer Products Found in the Typical U.S. Household 10-4
Table 10-2. Number of Minutes Spent in Activities Working with or Near Household Cleaning
Agents Such as Scouring Powders or Ammonia (minutes/day) 10-7
Table 10-3 Number of Minutes Spent Using Any Microwave Oven (minutes/day) 10-7
Table 10-4. Number of Respondents Using a Humidifier at Home 10-7
Table 10-5. Number of Respondents Indicating that Pesticides Were Applied by the Professional
at Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies .... 10-8
Table 10-6. Number of Respondents Reporting Pesticides Applied by the Consumer at Home
To Eradicate Insects, Rodents, or Other Pests at Specified Frequencies 10-8
-------
10. CONSUMER PRODUCTS
10.1 BACKGROUND
Consumer products may contain toxic or potentially toxic chemical constituents to which
children 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 health concerns. Potential
pathways of exposure to consumer products or chemicals released from consumer products
during use can occur via ingestion, inhalation, and dermal contact.
This chapter presents information on the amount of product used, frequency of use, and
duration of use for various consumer products typically found in households. There are limited
data available on consumer product use for the general population and especially for children.
Children can be in environments where household consumer products (Table 10-1) such as
cleaners, solvents, and paints are used. As such, children can be passively exposed to chemicals in
these products. 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 reader is referred to the Exposure
Factors Handbook (U.S. EPA, 1997) for a more detailed presentation for use of consumer
products for the general population.
10.2 CONSUMER PRODUCTS USE STUDIES
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 all age groups in 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 (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).
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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 10-2 through 10-6 for age
groups 1-4, 5-11, and 12-17 years. 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.
The advantages of NHAPS is that the data were collected for a large number of
individuals, representative of the U.S. general population. However, 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.
10.3 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 had been done in other
chapters of this handbook. The user is referred to the contents and references in Chapter 16 of
the Exposure Factors Handbook to derive appropriate exposure factors and review its associated
recommendations.
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10.4 REFERENCES FOR CHAPTER 10
Tsang, A.M.; Klepeis, N.E. (1996) Results tables from a detailed analysis of the National Human Activity Pattern
Survey (NHAPS) response. Draft Report prepared for the U.S. Environmental Protection Agency by
Lockheed Martin, Contract No. 68-W6-001, Delivery Order No. 13.
U.S. EPA (1987) Methods for assessing exposure to chemical substances - Volume 7 - Methods for assessing
consumer exposure to chemical substances. Washington, DC: Office of Toxic Substances. EPA Report
No. 560/5-85-007.
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Table 10-1. 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
Garment Conditioning Products
Household Maintenance Products
Carpeting
Draperies/curtains
Rugs (area)
Shower curtains
Vinyl upholstery, furniture
Anti-static spray (aerosol)
Leather treatment (liquid and wax)
Shoe polish
Spray starch (aerosol)
Suede cleaner/polish (liquid and aerosol)
Textile water-proofing (aerosol)
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')
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Table 10-1. Consumer Products Found in the Typical U.S. Householda (continued)
Consumer Product Category
Consumer Product
Household Maintenance Products
(continued)
Fabric rinse/softener (powder)
Fertilizer (garden) (liquid)
Fertilizer (garden) (powder)
Fire extinguishers (aerosol)
Floor polish/wax (liquid)
Food packaging and packaged food
Furniture polish (liquid)
Furniture polish (aerosol)
General cleaner/disinfectant (liquid)
General cleaner (powder)
General cleaner/disinfectant (aerosol and pump)
General spot/stain remover (liquid)
General spot/stain remover (aerosol and pump)
Herbicide (garden-patio) (Liquid and aerosol)
Insecticide (home and garden) (powder)
Insecticide (home and garden) (aerosol and pump)
Insect repellent (liquid and aerosol)
Laundry detergent/bleach (liquid)
Laundry detergent (powder)
Laundry pre-wash/soak (powder)
Laundry pre-wash/soak (liquid)
Laundry pre-wash/soak (aerosol and pump)
Lubricant oil (liquid)
Lubricant (aerosol)
Matches
Metal polish
Oven cleaner (aerosol)
Pesticide (home) (solid)
Pesticide (pet dip) (liquid)
Pesticide (pet) (powder)
Pesticide (pet) (aerosol)
Pesticide (pet) (collar)
Petroleum fuels (home( (liquid and aerosol)
Rug cleaner/shampoo (liquid and aerosol)
Rug deodorizer/freshener (powder)
Room deodorizer (solid)
Room deodorizer (aerosol)
Scouring pad
Toilet bowl cleaner
Toiler bowl deodorant (solid)
Water-treating chemicals (swimming pools)
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')
Home Building/Improvement Products (DIY)b
Adhesives, specialty (liquid)
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Table 10-1. Consumer Products Found in the Typical U.S. Householda (continued)
Consumer Product Category
Consumer Product
Home Building/Improvement Products (DIY)b
(Continued)
Automobile-related Products
Paint/varnish removers
Paint thinner/brush cleaners
Patching/ceiling plaster
Roofing
Refinishing products (polyurethane, varnishes, etc.)
Spray paints (home) (aerosol)
Wall paneling
Wall paper
Wall paper glue
Antifreeze
Car polish/wax
Fuel/lubricant additives
Gasoline/diesel fuel
Interior upholstery/components, synthetic
Motor oil
Radiator flush/cleaner
Automotive touch-up paint (aerosol)
Windshield washer solvents
Personal Materials
Clothes/shoes
Diapers/vinyl pants
Jewelry
Printed material (colorprint, newsprint, photographs)
Sheets/towels
Toys (intended to be placed in mouths)
a A subjective listing based on consumer use profiles.
b DIY = Do It Yourself.
Source: U.S. EPA, 1987.
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Table 10-2. 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
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
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 10-3 Number of Minutes Spent Using Any Microwave Oven (minutes/day)
Cateaorv
Population Grout)
Percentiles
N
1
2
5
10
25
50
75
90
95
98
99
100
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
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 10-4. Number of Respondents Using a Humidifier at Home
Total N
Almost
Every
Day
3-5 Times a
Week
Frequency
1-2 Times a
Week
1-2 Times a
Month
DK
Age (years)
1-4
5-11
12-17
111
88
83
33
18
21
16
10
7
7
12
5
53
46
49
Note: DK= Don't Know; Refused =
Source: Tsang and Klepeis, 1996.
Respondent Refused to Answer; N = Number of Respondents
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Table 10-5. 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
Age (years)
1-4
5-11
12-17
113
150
143
60
84
90
35
37
40
11
10
5
6
18
6
Note: * = Missing Data; DK= Don't know; Refused = Respondent Refused to Answer; N = Number of Respondents
Source: Tsang and Klepeis, 1996.
Table 10-6. 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
Age (years)
1-4
113
46
46
15
3
3
*
5-11
150
50
70
24
1
4
1
12-17
143
45
64
21
5
8
*
Note: * = Missing Data; DK= Don't know; Refused = Respondent Refused to Answer; N = Number of Respondents
Source: Tsang and Klepeis, 1996.
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TABLE OF CONTENTS
11. BODY WEIGHT STUDIES 11-1
11.1 INTRODUCTION 11-1
11.2 BODY WEIGHT STUDIES 11-1
11.3 RECOMMENDATIONS 11-3
11.4 REFERENCES FOR CHAPTER 11 11-5
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LIST OF TABLES
Table 11-1. Smoothed Percentiles of Weight (In Kg) by Sex And Age:
Statistics From NCHS And Data From Fels Research Institute, Birth to 36 Months . 11-6
Table 11-2. Body Weights of Childrenฎ (Kilograms) 11-9
Table 11-3. Weight in Kilograms For Males 6 Months-19 Years of Age-number Examine, Mean,
Standard Deviation,
and Selected Percentiles, by Sex and Age: United States, 1976-1980a 11-10
Table 11-4. Weight in Kilograms For Females 6 Months-19 Years of Age - Number
Examine, Mean, Standard Deviation, And Selected Percentiles,
By Sex And Age: United States, 1976-1980a 11-11
Table 11-5. Best-fit Parameters for Lognormal Distributions 11-12
Table 11-6. Statistics for Probability Plot Regression Analyses
Male's Body Weights 6 Months to 20 Years of Age 11-13
Table 11-7. Body Weight Estimates (in kilograms) by Age and Gender, U.S. Population 1988-94
11-14
Table 11-8. Body Weight Estimates (in kilograms) by Age, U.S. Population 1988-94 .... 11-15
Table 11-9. Summary of Recommended Values for Body Weight 11-16
Table 11-10. Confidence in Body Weight Recommendations 11-17
LIST OF FIGURES
Figure 11-1. Weight by Age percentiles for Girls Aged Birth-36 Months 11-7
Figure 11-2: Weight by Age Percentiles for Boys Aged Birth-36 Months 11-8
Figure 11-3. Mean Body Weights Estimates, U.S. Population, 1988-94 11-18
Figure 11-4. Median Body Weights Estimates, U.S. Population, 1988-94 11-19
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7
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9
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23
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31
11. BODY WEIGHT STUDIES
11.1 INTRODUCTION
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).
The purpose of this section is to describe key published studies on body weight for
children in the general U.S. population, as described in the Exposure Factors Handbook (U.S.
EPA, 1997). Recommended values are based on the results of these studies.
11.2 BODY WEIGHT STUDIES
Hamill etal. (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 11-1 presents the percentiles of weight by sex and age.
Figures 11-1 and 11-2 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 that 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
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2
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5
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7
8
9
10
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16
17
18
19
20
21
22
23
24
25
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27
28
29
30
31
Examination Survey (NHANES II). NHANES II was conducted on a nationwide 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 and standard deviations for children, ages 6 months to 19 years, are presented in
Table 11-2 for boys, girls, and boys and girls combined. Percentile data for children, by age, are
presented in Table 11-3 for males, and in Table 11-4 for females. From Table 11-2, 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.
Burmaster et al. (1997)- Lognormal Distributions for Body Weight as a Function of Age
for Males and Females in the United States, 1976-1980 - Burmaster et al. (1997) performed data
analysis to fit normal and lognormal distributions to the body weights of females and males at age
9 months to 70 years (Burmaster et al., 1997). The 1997 Exposure Factors Handbook used a
pre-published version of this paper (U.S. EPA, 1997). The numbers reported in Tables 11-5 and
11-6 vary slightly from those reported in the Exposure Factors Handbook (U.S. EPA, 1997).
Data used in this analysis were from the second survey of the National Center for Health
Statistics, NHANES II, which included 27,801 persons 6 months to 74 years of age in the U.S.
(Burmaster et al., 1997). The NHANES II data had been statistically adjusted for non-response
and probability of selection, and stratified by age, sex, and race to reflect the entire U.S.
population prior to reporting (Burmaster et al., 1997). Burmaster et al. (1997) conducted
exploratory and quantitative data analyses, and fit normal and lognormal distributions to
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19
20
21
22
23
24
25
26
27
28
29
30
percentiles of body weights of children, teens, and adults as a function of age. 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.
(1997) found that lognormal distributions give strong fits to the data for each sex across all age
groups. Statistics for the lognormal probability plots for children, ages 9 months to 20 years, are
presented in Tables 11-5 and 11-6. These data can be used for further analyses of body weight
distribution (i.e., application of Monte Carlo analysis).
U.S. EPA, 2000 - Body Weight Estimates Based on NHANES III Data - The EPA Office
of Water has estimated body weights for children, in kilograms, by age and gender using data
collected during National Health and Nutrition Examination Survey III (NHANES III), 1988-
1994. NHANES III collected body weight data for approximately 15,000 children between the
ages of 2 months and 17 years. Table 11-7 Presents the body weight estimates in kilograms by
age and gender. Table 11-8 shows the body weight estimates for the infants under the age of 3
months and/or younger, while Figures 11-3 and 11-4 compare the body weights (mean and
median) between male and female among various age groups, respectively.
The limitations of these data are (1) the data were not available for infants under 2 months
old, and (2) the data are roughly 6-12 years old. With the upward trends in body weight from
NHANES II (1976-1980) to NHANES III which may still be valid, the data in Tables 11-7 and
11-8 may underestimate current body weights. Adjustment factors may be needed to update the
estimates from 1988-1994 data to 2000. However, the data are national in scope and represent
the general children's population.
11.3 RECOMMENDATIONS
The recommended values for body weight are summarized in Table 11-9. Table 11-10
presents the confidence ratings for body weight recommendations.
For infants (birth to 6 months), appropriate values for body weight may be selected from
Table 11-1. These data (percentile only) are presented for male and female infants.
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1 For children, appropriate mean values for weights may be selected from Table 11-2.
2 If percentile values are needed, these data are presented in Table 11-3 for male children and in
3 Table 11-4 for female children.
4
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11.4 REFERENCES FOR CHAPTER 11
Burmaster, D.E.; Lloyd, K.J.; Crouch, E.A.C. (1997) Lognormal distributions for body weight as a function of age
for males and females in the United States, 1976-1980. Risk Anal. 17(4):499-505.
Hamill, P.V.V.; Drizd, T.A.; Johnson, C.L.; Reed, R.B.; Roche, A.F.; Moore, W.M. (1979) Physical growth:
National Center for Health Statistics Percentiles. American J. Clin. Nutr. 32:607-609.
National Center for Health Statistics (NCHS) (1987) Anthropometric reference data and prevalence of overweight,
United States, 1976-80. Data from the National Health and Nutrition Examination Survey, Series 11,
No. 238. Hyattsville, MD: U.S. Department of Health and Human Services, Public Health Service,
National Center for Health Statistics. DHHS Publication No. (PHS) 87-1688.
U.S. EPA (1989) Risk assessment guidance for Superfund, Volume I: Human health evaluation manual.
Washington, DC: U.S. Environmental Protection Agency, Office of Emergency and Remedial Response.
EPA/540/1-89/002.
U.S. EPA (1997) Exposure Factors Handbook. Washington, DC: Office of Research and Development. EPA/600-
P-95/002F.
U.S. EPA (2000) Memorandum entitled: Bodyweight estimates on NHANES III data, revised, Contract 68-C-
99-242, Work Assignment 0-1 from Bob Clickner, Westat Inc. to Helen Jacobs, U.S. EPA dated
March 3, 2000.
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32
33
Table 11-1. Smoothed Percentiles of Weight (In Kg) by Sex And Age:
Statistics From NCHS And Data From Fels Research Institute, Birth to 36 Months
Smoothed3 Percentile
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
aSmoothed by cubic-spline approximation.
Source: Hamill et al. (1979).
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0
9 12 15 18 21 24 27 30 33 36
Age In Months
Figure 11-1. Weight by Age percentiles for Girls Aged Birth-36 Months
Source: Hamill et al. (1979).
June 2000 11-7
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0 3 6 9 12 15 18 21 24 27 30 33 36
Age in Months
Figure 11-2: Weight by Age Percentiles for Boys Aged Birth-36 Months
Source: Hamill et al. (1979).
June 2000
11-8
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Figure 11-3. Mean Hotly Wcighls K.slimales, U.S. Population, 1988-94
ฆmala female
Aflป
Source: U.S. I:.I'A (2000).
June 2000
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Figure 11-4. Median Body Weights lislimatcs, U.S. Population, 1988-94
lmala ฆfemalB
Age
Source: U.S. ITA (2000).
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Table 11-2. Body Weights of Childrenฎ (Kilograms)
Boys Girls Boys and Girls
Age
Mean (kg)
Std. Dev.
Mean (kg)
Std. Dev.
Mean
(kg)
6-11 months
9.4
1.3
OO
OO
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
58.1
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.
includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.
Source: Adapted from National Center for Health Statistics (NCHS) (1987).
June 2000
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Table 11-3. Weight in Kilograms For Males 6 Months-19 Years of Age-number Examine, Mean, Standard Deviation,
and Selected Percentiles, by Sex and Age: United States, 1976-1980"
Percentile
Age
Number of
Persons
Examined
Mean
(kg)
Standard
Deviation
5th
10th
15th
25th
50th
75th
85th
90th
95th
6-11 months
179
9.4
1.3
7.5
7.6
8.2
8.6
9.4
10.1
10.7
10.9
11.4
1 years
370
11.8
1.9
9.6
10.0
10.3
10.8
11.7
12.6
13.1
13.6
14.4
2 years
375
13.6
1.7
11.1
11.6
11.8
12.6
13.5
14.5
15.2
15.8
16.5
3 years
418
15.7
2.0
12.9
13.5
13.9
14.4
15.4
16.8
17.4
17.9
19.1
4 years
404
17.8
2.5
14.1
15.0
15.3
16.0
17.6
19.0
19.9
20.9
22.2
5 years
397
19.8
3.0
16.0
16.8
17.1
17.7
19.4
21.3
22.9
23.7
25.4
6 years
133
23.0
4.0
18.6
19.2
19.8
20.3
22.0
24.1
26.4
28.3
30.1
7 years
148
25.1
3.9
19.7
20.8
21.2
22.2
24.8
26.9
28.2
29.6
33.9
8 years
147
28.2
6.2
20.4
22.7
23.6
24.6
27.5
29.9
33.0
35.5
39.1
9 years
145
31.1
6.3
24.0
25.6
26.0
27.1
30.2
33.0
35.4
38.6
43.1
10 years
157
36.4
7.7
27.2
28.2
29.6
31.4
34.8
39.2
43.5
46.3
53.4
11 years
155
40.3
10.1
26.8
28.8
31.8
33.5
37.3
46.4
52.0
57.0
61.0
12 years
145
44.2
10.1
30.7
32.5
35.4
37.8
42.5
48.8
52.6
58.9
67.5
13 years
173
49.9
12.3
35.4
37.0
38.3
40.1
48.4
56.3
59.8
64.2
69.9
14 years
186
57.1
11.0
41.0
44.5
46.4
49.8
56.4
63.3
66.1
68.9
77.0
15 years
184
61.0
11.0
46.2
49.1
50.6
54.2
60.1
64.9
68.7
72.8
81.3
16 years
178
67.1
12.4
51.4
54.3
56.1
57.6
64.4
73.6
78.1
82.2
91.2
17 years
173
66.7
11.5
50.7
53.4
54.8
58.8
65.8
72.0
76.8
82.3
88.9
18 years
164
71.1
12.7
54.1
56.6
60.3
61.9
70.4
76.6
80.0
83.5
95.3
19 years
148
71.7
11.6
55.9
57.9
60.5
63.8
69.5
77.9
84.3
86.8
82.1
Note: 1 kg = 2.2046 pounds.
^Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.
Source: National Center for Health Statistics (1987).
11-10
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Table 11-4. Weight in Kilograms For Females 6 Months-19 Years of Age - Number
Examine, Mean, Standard Deviation, And Selected Percentiles,
By Sex And Age: United States, 1976-19803
5
Percentile
6
7
8
Age
Number of
Persons
Examined
Mean
(kg)
Standard
Deviation
5th
10th
15th
25th
50th
75th
85th
90th
95th
9
10
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
11
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
12
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
13
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
14
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
15
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
16
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
17
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
18
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
19
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
20
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
21
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
22
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
23
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
24
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
25
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
26
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
27
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
28
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
29
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
30
31
32
33
34
Note: 1 kg = 2.2046 pounds.
" Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.
Source: National Center for Health Statistics (1987).
11-11
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Table 11-5. Best-fit Parameters for Lognormal Distributions
Lognormal Probability Plots
Linear Curve
Age Midpoint (yr)
^ 2
ฐ2
0.75
2.16
0.145
1.5
2.38
0.129
2.5
2.56
0.112
3.5
2.69
0.136
4.5
2.83
0.134
5.5
2.98
0.164
6.5
3.10
0.174
7.5
3.19
0.174
8.5
3.31
0.156
9.5
3.46
0.214
10.5
3.57
0.199
11.5
3.71
0.226
12.5
3.82
0.213
13.5
3.92
0.215
14.5
3.99
0.187
15.5
4.00
0.156
16.5
4.05
0.167
17.5
4.08
0.165
18.5
4.07
0.147
19.5
4.10
0.149
V;. o2 - correspond to the mean and standard deviation, respectively, of the lognormal distribution of body
weight (kg).
Source: Burmaster et al. (1997).
June 2000
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Table 11-6. Statistics for Probability Plot Regression Analyses
Male's Body Weights 6 Months to 20 Years of Age
Lognormal Probability Plots
Age Midpoint (yrs) Linear Curve
^ 2
ฐ2
0.75
2.23
0.132
1.5
2.46
0.119
2.5
2.60
0.120
3.5
2.75
0.114
4.5
2.87
0.133
5.5
2.98
0.138
6.5
3.13
0.145
7.5
3.21
0.151
8.5
3.33
0.181
9.5
3.43
0.165
10.5
3.59
0.195
11.5
3.69
0.252
12.5
3.78
0.224
13.5
3.88
0.215
14.5
4.02
0.181
15.5
4.09
0.159
16.5
4.20
0.168
17.5
4.19
0.167
18.5
4.25
0.159
19.5
4.26
0.154
V;. o2 - correspond to the mean and standard deviation, respectively, of the lognormal distribution of body
weight (kg).
Source: Burmaster et al. (1997).
June 2000
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Table 11-7. Body Weight Estimates (in kilograms) by Age and Gender, U.S. Population 1988-94
Age
Sample Size
Population
Male and Pemaie
Male
Pemaie
Median
Mean
Median
Mean
Median
Mean
2-6 months
1,020
1,732,702
7.4
7.4
7.6
7.7
7.0
7.0
7-12 months
1,072
1,925,573
9.4
9.4
9.7
9.7
9.1
9.1
1 year
1,258
3,935,114
11.3
11.4
11.7
11.7
10.9
11.0
2 years
1,513
4,459,167
13.2
12.9
13.5
13.1
13.0
12.5
3 years
1,309
4,317,234
15.3
15.1
15.5
15.2
15.1
14.9
4 years
1,284
4,008,079
17.2
17.1
17.2
17.0
17.3
17.2
5 years
1,234
4,298,097
19.6
19.4
19.7
19.3
19.6
19.4
6 years
750
3,942,457
21.3
21.7
21.5
22.1
20.9
21.3
7 years
736
4,064,397
25.0
25.5
25.4
25.5
24.1
25.6
8 years
711
3,863,515
27.4
28.1
27.2
28.4
27.9
27.9
9 years
770
4,385,199
31.8
32.7
32.0
32.3
31.1
33.0
10 years
751
3,991,345
35.2
35.6
35.9
36.0
34.3
35.2
11 years
754
4,270,211
40.6
41.5
38.8
40.0
43.4
42.8
12 years
431
3,497,661
47.2
46.9
48.1
49.1
45.7
48.6
13 years
428
3,567,181
53.0
55.1
52.6
54.5
53.7
55.9
14 years
415
4,054,117
56.9
61.1
61.3
64.5
53.7
57.9
15 years
378
3,269,777
59.6
62.8
62.6
66.9
57.1
59.2
16 years
427
3,652,041
63.2
65.8
66.6
69.4
56.3
61.6
17 years
410
3,719,690
65.1
67.5
70.0
72.4
60.7
62.2
1 and older
31,311
251,097,002
66.5
64.5
73.9
89.0
80.8
80.3
1-3 years
4,080
12,711,515
13.2
13.1
13.4
13.4
13.0
12.9
1-14 years
12,344
56,653,796
24.9
29.9
25.1
30.0
24.7
29.7
15-44 years
10,393
118,430,653
70.8
73.5
77.5
80.2
63.2
67.3
Source: U.S. EPA, 2000.
June 2000
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1 Table 11-8. Body Weight Estimates (in kilograms) by Age, U.S. Population 1988-94
2
3
4
Male and Female
5
Age
Sample Size
Population
Median
Mean
95% CI
6
Newborn
NA
NA
NA
NA
NA
7
1 Month
NA
NA
NA
NA
NA
8
2 Months
243
408,837
6.3
6.3
6.1-6.4
9
3 Months
190
332,823
7.0
6.9
6.7-7.1
10
11
3 Months and
Younger
433
741,660
6.6
6.6
6.4-6.7
12
13 NA = Not available.
14 CI = Confidence Intervals.
15
16 Source: U.S. EPA (2000).
June 2000
11-15
DRAF
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Table 11-9. Summary of Recommended Values for Body Weight
5
Population
Mean
Upper Percentile
Multiple Percentiles
6
Children
See Table 11-2
See Tables 11-3 and 11-4
See Tables 11-3 and 11-4
7
Infants
Not Available
See Table 11-1
See Table 11-1
8
June 2000
11-16
DRAF
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1
2
Table 11-10. Confidence in Body Weight Recommendations
Considerations
Rationale
Rating
Study Elements
Level of peer review
Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to US
Primary data
Currency
Adequacy of data collection
period
Validity of approach
Study size
Representativeness of the
population
Characterization of variability
Lack of bias in study design
(high rating is desirable)
Measurement error
Other Elements
Number of studies
Agreement between
researchers
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.
Both studies are available to the public. High
Results can be reproduced by analyzing NHANES II data and the Fels High
Research Institute data.
The studies focused on body weight, the exposure factor of interest. High
The data represent the U.S. population. High
The primary data were generated from NHANES II data and Fels studies, Medium
thus these data are secondary.
The data were collected between 1976-1980. Low
The NHANES II study included data collected over a period of 4 years. High
Body weight measurements were taken at various times of the day and at
different seasons of the year.
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.
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.
Data collected focused on the U.S. population for both studies. High
Both studies characterized variability regarding age and sex. Additionally High
NHANES II characterized race (for Blacks, Whites and total populations)
and sampled persons with low income.
There are no apparent biases in the study designs for NHANES II. The Medium-
study design for collecting the Fels data was not provided. High
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.
There are two studies. Low
There is consistency among the two studies. High
Overall Rating
High
June 2000
11-17
DRAF
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Figure 11-3. Mean Hotly Wcighls K.slimales, U.S. Population, 1988-94
ฆmala female
Aflป
Source: U.S. I:.I'A (2000).
June 2000
11-18
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Figure 11-4. Median Body Weights lislimatcs, U.S. Population, 1988-94
[ฆrnalfl ฆfeniaii)]
Age
Source: U.S. H'A (201)0).
June 2000 11-19 DRAFT-DO NOT QUOTE OR CITE
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TABLE OF CONTENTS
12. LIFETIME 12-1
12.1 INTRODUCTION 12-1
12.2 DATA ON LIFETIME 12-1
12.3 RECOMMENDATIONS 12-2
12.4 REFERENCES FOR CHAPTER 12 12-3
March 2000
12-1
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LIST OF TABLES
Table 12-1. Expectation of Life at Birth, 1980 to 1993,
And Projections, 1995 to 2010 (Years) 12-4
Table 12-2. Expectation of Life by Race, Sex, And Age: 1996 12-5
Table 12-3. Confidence in Lifetime Expectancy Recommendations 12-6
March 2000
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
12. LIFETIME
12.1 INTRODUCTION
The length of an individual's life is an important factor to consider when evaluating cancer
risk because the dose estimate is averaged over an individual's lifetime. 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. Children have more years of future life than adults. Therefore, they have more time
to develop any chronic diseases that might be triggered by early environmental exposures.
Diseases initiated by chemical hazards require several decades to develop, and early childhood
exposure to certain carcinogens or toxicants is more likely to lead to disease than the same
exposures later in life (NRDC, 1997).
12.2 DATA 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 1980 to 1993 are presented in Table 12-1. 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, 1999). The table shows that the overall life expectancy has averaged
approximately 75 years since 1982. The average life expectancy for males in 1993 was
72.2 years, and 78.8 years for females. The data consistently show an approximate 7 years
difference in life expectancy for males and females from 1980 to present. Table 12-1 also
indicates that the 1993 life expectancy for white males (73.1 years) is consistently longer than for
Black males (64.6 years). Additionally, it indicates that the 1993 life expectancy for White
females (79.5 years) is longer than for Black females (73.7), a difference of almost 6 years. Table
12-1 also shows that the projected life expectancy for children born in the year 2000 (76.4 years)
is longer than for those born in the 1980s (73.7 years). Table 12-2 presents data for expectation
of life for persons who were at a specific age in year 1996. 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.
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12.3 RECOMMENDATIONS
Current data suggest that 75 years would be an appropriate value to reflect the average
life expectancy of children in the current 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 1993 value of 72.2
years for males or 78.8 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 1993 values of 73.1 years and 64.6 years for White males
and Black males, respectively. Table 12-3 presents the confidence rating for life expectancy
recommendations.
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.
March 2000
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12.4 REFERENCES FOR CHAPTER 12
Natural Resources Defense Council. (1997) Our children at risk: the 5 worst environmental threats to their health.
U.S. Bureau of the Census. (1999) Statistical abstracts of the United States.
March 2000
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Table 12-1. Expectation of Life at Birth, 1980 to 1993,
And Projections, 1995 to 2010 (Years)a
TOTAL
WHITE
BLACK AND OTHERb
BLACK
YEAR
Total
Male
Female
Total
Male
Female
Total
Male
Female
Total
Male
Female
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
72.2
78.8
76.3
73.1
79.5
71.5
67.3
75.5
69.2
64.6
73.7
Projections0
1995
75.8
72.5
78.9
76.5
73.4
79.6
71.9
67.9
75.7
69.6
65.2
73.9
2000
76.4
73.0
79.7
77.4
74.2
80.5
NA
NA
NA
69.7
64.6
74.7
2005
76.9
73.8
80.2
77.9
74.7
81.0
NA
NA
NA
69.9
64.5
75.0
2010
77.4
74.1
80.6
78.6
75.5
81.6
NA
NA
NA
70.4
65.1
75.5
^Excludes deaths of nonresidents of the United States.
bRacial descriptions were not provided in the data source.
cBased on middle mortality assumptions; for details, see U.S. Bureau of the Census, Current Population Reports,
Series P-25, No. 1130.
Source: Bureau of the Census (1999).
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Table 12-2.
Expectation of Life by Race, Sex, And Age: 1996
3
Expectation of Life in Years
4
White
Black
5
Age in 1990
6
(years)
Total
Male
Female
Male
Female
7
At birth
76.1
73.9
79.7
66.1
74.2
8
1
75.7
73.4
79.1
66.2
74.2
9
2
74.7
72.4
78.1
65.2
73.2
10
3
73.7
71.4
77.1
64.3
72.3
11
4
72.8
70.5
76.2
63.3
71.3
12
5
71.8
69.5
75.2
62.4
70.3
13
6
70.8
68.5
75.2
61.4
69.4
14
7
69.8
67.5
73.2
60.4
68.4
15
8
68.8
66.5
72.2
59.4
67.4
16
9
67.8
65.5
71.2
58.4
66.4
17
10
66.9
64.5
70.2
57.5
65.4
18
11
65.9
63.5
69.2
56.5
64.4
19
12
64.9
62.6
68.3
55.5
63.4
20
13
63.9
61.6
67.3
54.5
62.5
21
14
62.9
60.6
66.3
53.5
61.5
22
15
61.9
59.6
65.3
52.6
60.5
23
16
61.0
58.8
64.3
51.6
59.5
24
17
60.0
57.7
63.3
50.7
58.6
25
18
59.1
56.8
62.4
49.8
57.6
26
19
58.1
55.8
61.4
48.9
56.6
27
28 Source: U.S. Bureau of Census (1999).
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1 Table 12-3. Confidence in Lifetime Expectancy Recommendations
2
3
Considerations
Rationale
Rating
4
Study Elements
5
Level of peer review
Data are published and have received extensive peer
review.
High
6
Accessibility
The study was widely available to the public (Census
data).
High
7
Reproducibility
Results can be reproduced by analyzing Census data.
High
8
Focus on factor of interest
Statistical data on life expectancy were published in this
study.
High
9
Data pertinent to US
The study focused on the U.S. population.
High
10
Primary data
Primary data were analyzed.
High
11
Currency
The study was published in 1995 and discusses life
expectancy trends from 1970 to 1993. The study has also
made projections for 1995 until the year 2010.
High
12
Adequacy of data collection period
The data analyzed were collected over a period of years.
High
13
Validity of approach
Census data is collected and analyzed over a period of
years.
High
14
Study size
This study was based on U.S. Census data, thus the
population study size is expected to be greater than 100.
High
15
Representativeness of the population
The data are representative of the U.S. population.
High
16
Characterization of variability
Data were averaged by gender and race but only for
Blacks and Whites; no other nationalities were
represented within the section.
Medium
17
18
Lack of bias in study design (High
rating is desirable)
There are no apparent biases.
High
19
Measurement error
Measurement error may be attributed to portions of the
population that avoid or provide misleading information
on census surveys.
Medium
20
Other Elements
21
Number of studies
Data presented in the section are from the U.S. Bureau of
the Census publication.
Low
22
Agreement between researchers
Recommendation was based on only one study, but it is
widely accepted.
High
23
Overall Rating
High
24
25
26
27
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