United States
           Environmental Protection
           Agency
             Office of Research and
             Development
             Washington DC 20460
EPA/600/P-95/002Fa
August 1997
vvEPA
Exposure Factors
Handbook
Volume I
           General Factors

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                                         EPA/600/P-95/002Fa
                                                August 1997
   VOLUME I - GENERAL FACTORS
   EXPOSURE FACTORS HANDBOOK

    Update to Exposure Factors Handbook
       EPA/600/8-89/043 - May 1989
    Office of Research and Development
National Center for Environmental Assessment
   U.S. Environmental Protection Agency
         Washington, DC 20460
                                         Printed on Recycled Paper

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EFH
                                         DISCLAIMER


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

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

recommendation for use.
 Page
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Exposure Factors Handbook
                August 1997


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                                                                        EFH.
                                       CONTENTS
                                                                               Page No.
 VOLUME I
  1.     INTRODUCTION	                                                ,,
        1.1.    PURPOSE	'.'.'.'.'.'.'.		 -
        1.2.    INTENDED AUDIENCE	'.'.'.'.'.'.'.	l"l
        1.3.    BACKGROUND	'.'.'.'.'.'.'.'.'.'.'.'.'.'.'.'.'.'.'.'.'.	\~.\
              1.3.1.   Selection of Studies for the Handbook  	1_1
              1.3.2.   Using the Handbook in an Exposure Assessment	1-3
              1.3.3.   Approach Used to Develop Recommendations for Exposure Factors	1-4
              1.3.4.   Characterizing Variability	                             15
        1.4.    GENERAL EQUATION FOR CALCULATING DOSE	Ill
        1.5.    RESEARCH NEEDS	                 	j 14
        1.6.    ORGANIZATION	       	j 15
        1.7.    REFERENCES FOR CHAPTER 1	          	, ,fi
 APPENDIX i A	I!!.'.'!!.'.'"!!!."	i A-I

 2.      VARIABILITY AND UNCERTAINTY	                        21
        2.1.    VARIABILITY VERSUS UNCERTAINTY 	  	2"l
        2.2.    TYPES OF VARIABILITY  	             	22
        2.3.    CONFRONTING VARIABILITY 	   	2~3
        2.4.    CONCERN ABOUT UNCERTAINTY  	    "	23
        2.5.    TYPES OF UNCERTAINTY AND REDUCING UNCERTAINTY	2-4
        2.6.    ANALYZING VARIABILITY AND UNCERTAINTY	             	2-4
        2.7.    PRESENTING RESULTS OF VARIABILITY AND UNCERTAINTY ANALYSIS	2-6
        2.8.    REFERENCES FOR CHAPTER 2	                  " 2-1

 3.      DRINKING WATER INTAKE	                                       , ,
        3.1.    BACKGROUND	'.'.'.'.'.'.'.'.'.'.'.'.'.'.'.'.'.	'3.1
        3.2.    KEY GENERAL POPULATION STUDIES ON DRINKING WATER INTAKE	3-1
        3.3.    RELEVANT GENERAL POPULATION STUDIES ON DRINKING WATER INTAKE	3-9
        3.4.    PREGNANT AND LACTATING WOMEN 	                            '"317
        3.5.    HIGH ACTIVITY LEVELS/HOT CLIMATES .                	3 20
        3.6.    RECOMMENDATIONS	          	3 23
        3.7.    REFERENCES FOR CHAPTER 3	   3-30

 4.     SOIL INGESTION AND PICA	                                       4 ,
       4.1.    BACKGROUND	 	4"j
       4.2.    KEY STUDIES ON SOIL INTAKE AMONG CHILDREN ".'.'.'.'.	4]]
       4.3.    RELEVANT STUDIES ON SOIL INTAKE AMONG CHILDREN        	4-11
       4.4.    SOIL INTAKE AMONG ADULTS ....                                	4 16
       4.5.    PREVALENCE OF PICA	'.'.'.'.'.'.'.'.	4^7
       4.6.    DELIBERATE SOIL INGESTION AMONG CHILDREN   	418
       4.7.    RECOMMENDATIONS	                    	4 20
       4.8.    REFERENCES FOR CHAPTER 4	          	4"25
Exposure Factors Handbook
August 1997 	
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EFH
                                 CONTENTS (continued)
                                                                               Page No.
5.      INHALATION ROUTE
       5.1.    EXPOSURE EQUATION FOR INHALATION
       5.2.    INHALATION RATE
             5.2.1.   Background
             5.2.2.   Key Inhalation Rate Studies
             5.2.3.   Relevant Inhalation Rate Studies
             5.2.4.   Recommendations ...........
             REFERENCES FOR CHAPTERS
                                                                                    5~\
                                                                                    5-
                                                                                    5~l
                                                                                   5-16
       5.3.
APPENDIX5A
                                                                                   i A— 1
6.     DERMAL ROUTE
       6.1.    EQUATION FOR DERMAL DOSE
       6.2.
              6.2.2.
              6.2.3.
              6.2.4.
              6.2.5.
       6.3.
       6.4.
       6.5.
             SURFACE AREA
             6.2.1.  Background
                    Measurement Techniques
                    Key Body Surface Area Studies
                    Relevant Surface Area Studies
                    Application of Body Surface Area Data
             SOIL ADHERENCE TO SKIN
             6.3.1.  Background
             6.3.2.  Key Soil Adherence to Skin Studies
             6.3.3.  Relevant Soil Adherence to Skin Studies
             RECOMMENDATIONS
             6.4.1.  Body Surface Area
             6.4.2.  Soil Adherence to Skin
             REFERENCES FOR CHAPTER 6
                                                                                    6"2
                                                                                     °-6
                                                                                     °'°
                                                                                     °~°
                                                                                     6~°
       APPENDIX 6A
       BODY WEIGHT STUDIES  . . . .
       7 1.    KEY BODY WEIGHT STUDY
       7.2.    RELEVANT BODY WEIGHT STUDIES
       7.3.    RECOMMENDATIONS
       7.4.    REFERENCES FOR CHAPTER?
                                                                                     7~l
                                                                                     '~l
                                                                                     "-4
                                                                                    7-11
 8.      LIFETIME
        8.1.    KEY STUDY ON LIFETIME
        8.2.    RECOMMENDATIONS
        8.3.    REFERENCES FOR CHAPTER 8
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                                                             Exposure Factors Handbook
                                                             	August 1997

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                                    CONTENTS (continued)
                                                                                    Page No.
 VOLUME II
 9.      INTAKE OF FRUITS AND VEGETABLES	       9-1
        9.1.     BACKGROUND	    9-1
        9.2.     INTAKE STUDIES	'9.2
               9.2.1.   U.S. Department of Agriculture Nationwide Food Consumption Survey and
                      Continuing Survey of Food Intake by Individuals	9-2
               9.2.2.   Key Fruits and Vegetables Intake Study Based on the USDA CSFII	 9-2
               9.2.3.   Relevant Fruits and Vegetables Intake Studies	'..... 9-4
               9.2.4.   Relevant Fruits and Vegetables Serving Size Study Based on the USDA NFCS 	9-6
               9.2.5.   Conversion Between As Consumed and Dry Weight Intake Rates	9-7
        9.3.     RECOMMENDATIONS	         9-7
        9.4.     REFERENCES FOR CHAPTER 9	                    "9.8
 APPENDIX9A	                    9A_1
 APPENDIX9B	 9B-1

 10.     INTAKE OFFISH AND SHELLFISH	.'....	10-1
        10.1.    BACKGROUND	 iQ-l
        10.2.    KEY GENERAL POPULATION STUDIES	'.'.[' 10-2
        10.3.    RELEVANT GENERAL POPULATION STUDIES	 10-6
        10.4.    KEY RECREATIONAL (MARINE FISH STUDIES)	10-8
        10.5.    RELEVANT RECREATIONAL MARINE STUDIES	                   10-10
        10.6.    KEY FRESHWATER RECREATIONAL STUDIES	       ' 10-12
        10.7.    RELEVANT FRESHWATER RECREATIONAL STUDIES  ..;	10-18
        10.8.    NATIVE AMERICAN FRESHWATER STUDIES	:....                10-20
        10.9.    OTHER FACTORS	       ' " ' iQ-24
        10.10.   RECOMMENDATIONS	'.'..•'.'.'.'.'.'. 10-25
               10.10.1. Recommendations - General Population	10-25
               10.10.2. Recommendations - Recreational Marine Anglers	10-26
               10.10.3. Recommendations - Recreational Freshwater Anglers	 10-26
               10.10.4. Recommendations - Native American Subsistence Populations	10-26
        10.11.   REFERENCES FOR CHAPTER 10	                                10-27
 APPENDIX 10A	                  	10A_1
 APPENDIX 10B 	      	 10B_1
 APPENDIX IOC 	.........../......... iqc-l

 11.     INTAKE OF MEAT AND DAIRY PRODUCTS	;.                    11-1
        11.1.    INTAKE STUDIES	! "  11-1
               11.1.1.   U.S. Department of Agriculture Nationwide Food Consumption Survey and
                      Continuing Survey of Food Intake by Individuals		;	11-1
               11.1.2.   Key Meat and Dairy Products Intake Study Based on the CSFII  	11-2
               11.1.3.   Relevant Meat and Dairy Products Intake Studies  	11-3
Exposure Factors Handbook
August 1997       	
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EFH
                                 CONTENTS (continued)
                                                                              Page No.
       11.2.   FAT CONTENT OF MEAT AND DAIRY PRODUCTS	11-6
       11.3.   CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE RATES .... 11-7
       11.4.   RECOMMENDATIONS	n-?
       11.5.   REFERENCES FOR CHAPTER 11 	H'7
APPENDIX 11A 	  11A"1

12.     INTAKE OF GRAIN PRODUCTS	•	• • • I2'1
       12.1.   INTAKE STUDIES	•	I2~l
             12.1.1.  U.S. Department of Agriculture Nationwide Food Consumption Survey and
                    Continuing Survey of Food Intake by Individuals	12-1
             12.1.2.  Key Grain Products Intake Studies Based on the CSFII	12-2
             12.1.3.  Relevant Grain Products Intake Studies  	12-2
             12.1.4.  Key Grain Products Serving Size Study Based on the USDA NFCS 	12-4
       12.2.   CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE RATES .... 12-4
       12.3.   RECOMMENDATIONS	 12-5
       12.4.   REFERENCES FOR CHAPTER 12	12-5
APPENDIX 12A 	  12A-]

13.     INTAKE RATES FOR VARIOUS HOME PRODUCED FOOD ITEMS 	13-1
       13.1.   BACKGROUND	13-J
       13.2.   METHODS 	13'2
       13 3   RESULTS             	13-7
       13A   ADVANTAGES AND LIMITATIONS  	13-9
       13.5.   RECOMMENDATIONS	-	13-10
       13.6.   REFERENCES FOR CHAPTER 13	13-10
APPENDIX 13A 	  13A'1

14.     BREAST MILK INTAKE	14-1
       14.1.   BACKGROUND	14'J
       14.2.   KEY STUDIES ON BREAST MILK INTAKE	14-1
       14.3.   RELEVANT STUDIES ON BREAST MILK INTAKE	14-4
       14.4.   KEY STUDIES ON LIPID CONTENT AND FAT INTAKE FROM BREAST MILK	14-5
       14.5.   OTHER FACTORS ...'	14'6
       14.6.   RECOMMENDATIONS	14-7
       14.7.   REFERENCES FOR CHAPTER 14	14-8
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Exposure Factors Handbook
               August 1997

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                                                                              BFH
                                     CONTENTS (continued)
                                                                                      Page No.
 VOLUME III
 15.     ACTIVITY FACTORS	15.]
        15.1.   ACTIVITY PATTERNS	; 15.1
               15.1.1.  Key Activity Pattern Studies	15-1,
               15.1.2.  Relevant Activity Pattern Studies	 15.7
        15.2.   OCCUPATIONAL MOBILITY	15-11
               15.2.1.  Background	15-11
               15.2.2.  Key Occupational Mobility Studies	 15-11
        15.3.   POPULATION MOBILITY	,	.	 15.12
               15.3.1.  Background	15-12
               15.3.2.  Key Population Mobility Studies	;... 15-13
               15.3.3.  Relevant Population Mobility Studies	15-15
        15.4.   RECOMMENDATIONS	;	•.','.[ 15.15
               15.4.1.  Recommendations for Activity Patterns	 15-15
               15.4.2.  Recommendations: Occupational Mobility	 15-17
               15.4.3.  Recommendations: Population Mobility	15-17
               15.4.4.  Summary of Recommended Activity Factors  	15-18
        15.5.   REFERENCES FOR CHAPTER 15	         15-18
 APPENDIX ISA 	          15A.!
 APPENDIX 15B	'.'.'.'.'.'.  15B-1

 16.     CONSUMER PRODUCTS	16-1
        16.1.   BACKGROUND	•.......-.'.'.'.'.'.'.'.'.'.'.'.'.'. 16-1
        16.2.   KEY CONSUMER PRODUCTS USE STUDIES  	....16-1
        16.3.   RELEVANT CONSUMER PRODUCTS USE STUDY	16-4
        16.4.   RECOMMENDATIONS	16-5
        16.5.   REFERENCES FOR CHAPTER 16	                  16-5
 APPENDIX 16A 	  16A-1


 17.     RESIDENTIAL BUILDING CHARACTERISTICS   	      17-1
        17.1.   INTRODUCTION	'.'.'.'.'.'. 17-1
        17.2.   BUILDING CHARACTERISTICS	 17.2
               17.2.1.  Key Volumes of Residence Studies	17-2
               17.2.2.  Volumes and Surface Areas of Rooms 	17-4
               17.2.3.  Mechanical System Configurations	; 17-6
               17.2.4.  Type of Foundation	17-7
Exposure Factors Handbook
August 1997
Page
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EFH
                                     CONTENTS (continued)
       17.4.
       17.5.
       17.6
       17.7.

GLOSSARY
                                                                                        Page No.
       17.3.   TRANSPORT RATES  [[[ 17-8
              17.3.1.  Background [[[ 17'8
              17.3.2.  Air Exchange Rates .................................................. 17-10
              17.3.3.  Infiltration Models [[[ 17-12
              17.3.4.  Deposition and Filtration ............................................... 17-14
              17.3.5.  Interzonal Airflows .................................................. 17-15
              17.3.6.  Water Uses  [[[ 17-15
              17.3.7.  House Dust and Soil ................................................ .17-19
              SOURCES ......................................... ....................... 17-20
              17.4.1.  Source Descriptions for Airborne Contaminants .............. .............. 17-20
              17.4.2.  Source Descriptions for Waterborne Contaminants  ......................... 17-22
              17.4.3.  Soil and House Dust Sources ........................................... 17-22
              ADVANCED CONCEPTS ..................... . ........... .................. 17-23
              17.5.1.  Uniform Mixing Assumption ....................... .................... 17-23
              17.5.2.  Reversible Sinks  ............... ..................................... 17-23
              RECOMMENDATIONS ..................... .................... • ........... 17-23

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                                                                                     EFH
                                          LIST OF TABLES
                                                                                              Page'No.
VOLUME I

Table 1-1.         Considerations Used to Rate Confidence in Recommended Values	1-6
Table 1-2.         Summary of Exposure Factor Recommendations and Confidence Ratings	1-7
Table 1-3.         Characterization of Variability in Exposure Factors	1-10
Table 1A-1.       Procedures for Modifying IRIS Risk Values for Non-standard Populations	  1A-4

Table 2-1.         Four Strategies for Confronting Variability			2-3
Table 2-2.         Three Types of Uncertainty and Associated Sources and Examples	2-5
Table 2-3.         Approaches to Quantitative Analysis of Uncertainty	2-6

Table 3-1.         Daily Total Tapwater Intake Distribution for Canadians, by Age Group
                  (approx. 0.20 L increments, both  sexes, combined seasons)	3-2
Table 3-2.         Average Daily Tapwater Intake of Canadians (expressed as milliliters per kilogram
                  body weight)	3-3
Table 3-3.         Average Daily Total Tapwater Intake of Canadians, by Age and Season (L/day)	3-3
Table 3-4.         Average Daily Total Tapwater Intake of Canadians as a Function of Level of Physical
                  Activity at Work and in Spare Time (16 years and older, combined seasons, L/day)	3-3
Table 3-5.         Average Daily Tapwater Intake by Canadians, Apportioned Among Various Beverages
                  (both sexes, by age, combined seasons, L/day)	3-4
Table 3-6.         Total Tapwater Intake (mL/day) for Both Sexes Combined	3-5
Table 3-7.         Total Tapwater Intake (mL/kg-day) for Both Sexes Combined  	3-6
Table 3-8.         Summary of Tapwater Intake by Age	.'	3-7
Table 3-9.         Total Tapwater Intake (as percent of total water intake) by Broad Age Category  	3-7
Table 3-10.        General Dietary Sources of Tapwater for Both Sexes	3-8
Table 3-11.        Summary Statistics for Best-Fit Lognormal Distributions for Water Intake Rates	 3-9
Table 3-12.        Estimated Quantiles  and Means for Total Tapwater Intake Rates (mL/day)	3-10
Table 3-13.        Assumed Tapwater Content of Beverages	3-10
Table 3-14.        Intake of Total Liquid, Total Tapwater, and Various Beverages (L/day)	3-11
Table 3-15.        Summary of Total Liquid and Total Tapwater Intake for Males and Females (L/day)	3-12
Table 3-16.        Measured Fluid Intakes (mL/day)	3-13
Table 3-17.        Intake Rates of Total Fluids and Total Tapwater by Age Group	3-14
Table 3-18.        Mean and Standard Error for the  Daily Intake of Beverages and Tapwater by Age ....... 3-14
Table 3-19.        Average Total Tapwater Intake Rate by Sex, Age, and Geographic Area 	3-15
Table 3-20.        Frequency Distribution of Total Tapwater Intake Rates	3-15
Table 3-21.        Mean Per Capita Drinking Water Intake Based on USDA, CSFII Data From 1989-91
                  (mL/day)	3-16
Table 3-22.        Number of Respondents that Consumed Tapwater at a Specified Daily Frequency	3-18
Table 3-23.        Number of Respondents that Consumed Juice Reconstituted with Tapwater
                  at a Specified Daily Frequency	3-19
Table 3-24.        Total Fluid Intake of Women 15-49 Years Old	3-20
Table 3-25.        Total Tapwater Intake of Women 15-49 Years Old  	3-21
Table 3-26.        Total Fluid (mL/Day) Derived from Various Dietary Sources by
                  Women Aged  15-49 Years	3-21
Table 3-27.        Water Intake at Various Activity  Levels (L/hr)	3-22
-Exposure Factors Handbook
August 1997	
Page
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EFH
                                     LIST OF TABLES (continued)
                                                                                              Page No.
Table 3-28.        Planning Factors for Individual Tapwater Consumption	3-23
Table 3-29.        Drinking Water Intake Surveys	3-24
Table 3-30.        Summary of Recommended Drinking Water Intake Rates  	3-26
Table 3-31.        Total Tapwater Consumption Rates From Key Studies 	3-26
Table 3-32.        Daily Tapwater Intake Rates From Relevant Studies  	3-26
Table 3-33.        Key Study Tapwater Intake Rates for Children	3-27
Table 3-34.        Summary of Intake Rates for Children in Relevant Studies		3-27
Table 3-35.        Confidence in Tapwater Intake Recommendations	3-29

Table 4-1.         Estimated Daily Soil Ingestion Based on Aluminum, Silicon, and Titanium Concentrations . 4-2
Table 4-2.         Calculated Soil Ingestion by Nursery School Children	4-3
Table 4-3.         Calculated Soil Ingestion by Hospitalized, Bedridden Children	4-3
Table 4-4.         Mean and Standard Deviation Percentage Recovery of Eight Tracer Elements	4-5
Table 4-5.         Soil and Dust Ingestion Estimates for Children Aged 1-4 Years  	4-5
Table 4-6.         Average Daily Soil Ingestion  Values Based on Aluminum, Silicon, and Titanium as
                  Tracer Elements 	4-6
Table 4-7.         Geometric Mean (GM) and Standard Deviation (GSD) LTM Values for Children at
                  Daycare Centers and Campgrounds  	4-7
Table 4-8.         Estimated Geometric Mean LTM Values of Children Attending Daycare Centers
                  According to Age, Weather Category, and Sampling Period  	4-8
Table 4-9.         Distribution of Average (Mean) Daily Soil Ingestion Estimates Per Child for 64
                  Children (mg/day)	.4-9
Table 4-10.        Estimated Distribution of Individual Mean Daily Soil Ingestion Based on Data for 64
                  Subjects Projected Over 365 Days 	4-10
Table 4-11.        Estimates of Soil Ingestion for Children	4-12
Table 4-12.        Estimated Soil Ingestion Rate Summary Statistics and Parameters for Distributions
                  Using Binder et al.  (1986) Data with Actual Fecal Weights	4-13
Table 4-13.        Tukey's Multiple Comparison of Mean Log Tracer Recovery in Adults Ingesting Known
                  Quantities of Soil	4-14
Table 4-14.        Positive/Negative Error (bias) in Soil Ingestion Estimates in the Calabrese et al. (1989)
                  Mass-balance Study: Effect on Mean Soil Ingestion Estimate (mg/day)	4-15
Table 4-15.        Soil Ingestion Rates for Assessment Purposes	4-16
Table 4-16.        Estimates of Soil Ingestion for Adults	4-17
Table 4-17.        Adult Daily Soil Ingestion by Week and Tracer Element After Subtracting Food and
                  Capsule Ingestion, Based on Median Amherst Soil Concentrations:  Means and
                  Medians Over Subjects (mg)	4-18
Table 4-18.        Daily Soil Ingestion Estimation in a Soil-Pica Child by Tracer and by Week (mg/day)	4-19
Table 4-19.        Ratios of Soil, Dust, and Residual Fecal Samples in the Pica Child	4-19
Table 4-20.        Soil Intake Studies	'.	4-22
Table 4-21.        Confidence in Soil Intake Recommendation	 4-24
Table 4-22.        Summary of Estimates of Soil Ingestion By Children	4-25
Table 4-23.        Summary of Recommended Values for Soil Ingestion	4-25
Page
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 Exposure Factors Handbook
	August 1997

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                                                                                       EFH
                                      LIST OF TABLES (continued)
                                                                                                Page No.
 Table 5-1.         Calibration and Field Protocols for Self-Monitoring of Activities Grouped by Subject
                   Panels 	.-	.......'....	5-4
 Table 5-2.         Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and Self-Estimated
                   Breathing Rates	5,5
 Table«5-3.         Distribution of Predicted IR by Location and Activity Levels for Elementary and
                   High School Students  .'.	5-6
 Table 5-4.         Average Hours Spent Per Day in a Given Location and Activity Level for Elementary (EL)
                   and High School (HS) Students	5-6
 Table 5-5.         Distribution Patterns of Daily Inhalation Rates for Elementary (EL) and High School (HS)
                   Students Grouped by Activity Level	;	 5.7
 Table 5-6.         Summary of Average Inhalation Rates (m3/hr) by Age Group and Activity Levels
                   for Laboratory Protocols	5.3
 Table 5-7.         Summary of Average Inhalation Rates (m3/hr) by Age Group and Activity Levels
                   in Field Protocols	5.9
 Table 5-8.         Distributions of Individual and Group Inhalation/Ventilation Rate for Outdoor Workers .. 5-10
 Table 5-9.         Individual Mean Inhalation Rate (m3/hr) by Self-Estimated Breathing Rate or Job Activity
                   Category for Outdoor Workers	,	5-10
 Table 5-10.        Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-Energy
                   Intakes for Individuals Sampled in the 1977-78 NFCS	 5-12
 Table 5-11.        Daily Inhalation Rates Calculated from Food-Energy Intakes  	5-13
 Table 5-12.        Daily Inhalation Rates Obtained from the Ratios of Total Energy Expenditure to
                   Basal Metabolic Rate (BMR) 	;		 5-14
 Table 5-13.        Daily Inhalation Rates Based on Time-Activity Survey	5-15
 Table 5-14.        Inhalation Rates for Short-Term Exposures 	5-16
 Table 5-15.        Daily'Inhalation Rates Estimated From Daily Activities	5-17
 Table 5-16.        Summary of Human Inhalation Rates for Men, Women, and Children by
                   Activity Level (mVhour)	 5-ig
 Table 5-17.        Activity Pattern Data Aggregated for Three Microenvironments by Activity Level
                   for all Age Groups	5-18
 Table 5-18.        Summary of Daily Inhalation Rates Grouped by Age and Activity Level	5-18
 Table 5-19.        Distribution Pattern of Predicted VR and EVR (equivalent ventilation rate)
                   for 20 Outdoor Workers  	5-20
 Table 5-20.        Distribution Pattern of Inhalation Rate by Location and Activity Type for 20 Outdoor
                   Workers	5_2l
 Table 5-21.        Actual Inhalation Rates Measured at Four Ventilation Levels  	5-22
 Table 5-22.        Confidence in Inhalation Rate Recommendations	5-23
 Table 5-23.        Summary of Recommended Values for Inhalation	5-24
 Table 5-24.        Summary of Inhalation Rate Studies	 5-25
 Table 5-25.        Summary of Adult Inhalation Rates for Short-Term Exposure Studies	5-26
 Table 5-26.        Summary of Children's (18 years old or less) Inhalation Rates for Long-Term
                   Exposure Studies	5-26
 Table 5-27.        Summary of Children's Inhalation Rates for Short-Term Exposure Studies	5-26
 Table 5A-1.        Mean Minute Ventilation (VE, L/min) by Group and Activity for Laboratory Protocols ..  5A-3
 Table 5A-2.        Mean Minute Ventilation (VE> L/min) by Group and Activity for Field Protocols 	  5A-3
Exposure Factors Handbook
August 1997   	
Page
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EFH
                                    LIST OF TABLES (continued)
                                                                                             Page No.
Table 5A-3.        Characteristics of Individual Subjects: Anthropometric Data, Job Categories,
                  Calibration Results	  5A'4
Table 5A-4.        Statistics of the Age/Gender Cohorts Used to Develop Regression Equations for
                  Predicting Basal Metabolic Rates (BMR)	, 5A-4
Table 5A-5.        Selected Ventilation Values During Different Activity Levels Obtained From
                  Various Literature Sources	  5A-5
Table 5A-6.        Estimated Minute Ventilation Associated with Activity Level for Average Male Adult  ..  5A-6
Table 5A-7.        Minute Ventilation Ranges by Age, Sex, and Activity Level 	  5A-7

Table 6-1.         Summary of Equation Parameters for Calculating Adult Body Surface Area	6-12
Table 6-2.         Surface Area of Adult Males in Square Meters	6-13
Table 6-3.         Surface Area of Adult Females in Square Meters	6-13
Table 6-4.         Surface Area of Body Part for Adults (m2)	6-14
Table 6-5.         Percentage of Total Body Surface Area by Part for Adults	6-14
Table 6-6.         Total Body Surface Area of Male Children in Square Meters 		6-15
Table 6-7.         Total Body Surface Area of Female Children in Square Meters	6-15
Table 6-8.         Percentage of Total Body Surface Area by Body Part for Children	6-16
Table 6-9.         Descriptive Statistics for Surface Area/BodyWeight (SA/WB) Ratios (m2/kg)  	6-17
Table 6-10.        Statistical Results for Total Body Surface Area Distributions (m2)  		6-17
Table 6-11.        Summary of Field Studies	6-20
Table 6-12.        Geometric Mean and Geometric Standard Deviations of Soil Adherence by Activity
                  and Body Region	°-22
Table 6-13.        Summary of Surface Area Studies	6-24
Table 6-14.        Summary of Recommended Values for Skin Surface Area	6-25
Table 6-15.        Confidence in Body Surface Area Measurement Recommendations  		6-25
Table 6-16.        Recommendations for Adult Body Surface Area	6-26
Table 6-17.        Summary of Soil Adherence Studies	6-26
Table 6-18.        Confidence in Soil Adherence to Skin Recommendations 	6-27
Table 6-A1.       Estimated Parameter Values for Different Age Intervals	 6-A5
Table 6-A2.       Summary of Surface Area Parameter Values for the DuBois and
                  DuBois Model	 6-A6

Table 7-1.         Smoothed Percentiles of Weight (in kg) by Sex and Age: Statistics from NCHS and Data
                  from Pels Research Institute, Birth to 36 Months	7-1
Table 7-2.         Body Weights of Adults (kilograms)	7-4
Table 7-3.         Body Weights of Children (kilograms)		,	7-4
Table 7-4.      ,   Weight in Kilograms for Males  18-74 Years of Age-Number Examined, Mean, Standard
                   Deviation, and Selected Percentiles, by Race and Age: United States, 1976-1980	.7-5
Table 7-5.         Weight in Kilograms for Females 18-74 Years of Age-Number Examined, Mean, Standard
                  Deviation, and Selected Percentiles, by Race and Age: United States, 1976-1980	7-6
Table 7-6.         Weight in Kilograms for Males  6 Months-19 Years of Age-Number Examined, Mean,
                  Standard Deviation, and Selected Percentiles, by Sex and Age: United States, 1976-1980 . . 7-7
Table 7-7.         Weight in Kilograms for Females 6 Months-19 Years of Age-Number Examined, Mean,
                  Standard Deviation, and Selected Percentiles, by Sex and Age: United States, 1976-1980 .. 7-8
 Page
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 Exposure Factors Handbook
	August 1997

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                                                                                    EFH
                                    LIST OF TABLES (continued)
                                                                                             Page No.
Table 7-8.         Statistics for Probability Plot Regression Analyses Female's Body Weights 6 Months to
                  20 Years of Age	7-9
Table 7-9.         Statistics for Probability Plot Regression Analyses Male's Body Weights 6 Months to
                  20 Years of Age	7-10
Table 7-10.        Summary of Body Weight Studies	 7-11
Table 7-11.        Summary of Recommended Values for Body Weight	7-11
Table 7-12.        Confidence in Body Weight Recommendations	7-12

Table 8-1.         Expectation of Life at Birth, 1970 to 1993, and Projections, 1995 to 2010	8-2
Table 8-2.         Expectation of Life by Race, Sex, and Age: 1992	8-3
Table 8-3.         Confidence in Lifetime Expectancy Recommendations ;	8-5


VOLUME II

Table 9-1.         Sub-category Codes and Definitions Used in the CSFII 1989-91 Analysis	 9-9
Table 9-2.         Weighted and Unweighted Number of Observations for 1989-91 CSFII Data Used in
                  Analysis of Food Intake	9-10
Table 9-3.         Per Capita Intake of Total Fruits (g/kg-day as consumed)  .;....	;	9-11
Table 9-4.         Per Capita Intake of Total Vegetables (g/kg-day as consumed)	 9-12
Table 9-5.         Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed)	 9-13
Table 9-6.         Per Capita Intake of USDA Categories of Fruits and Vegetables (g/kg-day as consumed) .9-19
Table 9-7.         Per Capita Intake of Exposed Fruits (g/kg-day as consumed)	9-20
Table 9-8.         Per Capita Intake of Protected Fruits (g/kg-day as consumed)	9-21
Table 9-9.         Per Capita Intake of Exposed Vegetables (g/kg-day as consumed)	9-22
Table 9-10.        Per Capita Intake of Protected Vegetables (g/kg-day as consumed)	9-23
Table 9-11.        Per Capita Intake of Root Vegetables (g/kg-day as consumed) .	, 9-24
Table 9-12.        Mean Daily Intake of Fruits and Vegetables Per Individual in a Day for USDA 1977-78,
                  87-88, 89-91, 94, and 95 Surveys	•., 9-25
Table 9-13.        Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All
                  Sex/Age/Demographic  Subgroups	9-26
Table 9-14.        Mean Total Fruit Intake (as consumed) in a Day by Sex and Age (1977-1978)	9-33
Table 9-15.        Mean Total Fruit Intake (as consumed) in a Day by Sex an Age (1987-1988)  	9-33
Table 9-16.        Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age (1977-1978)	9-34
Table 9-17.        Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age (1987-1988)	.. 9-34
Table 9-18.        Mean Total Fruit Intake (as consumed) in a Day by Sex and Age (1994 and 1995)	9-35
Table 9-19.        Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age (1994 and 1995)  .. 9-35
Table 9-20.        Mean Per Capita Intake of Fats and Oils (g/day as consumed) in a Day by Sex and
                  Age (1994 and 1995)	9-36
Table 9-21.        Mean and Standard Error for the Per Capita Daily Intake of Food Class and Subclass by
                  Region (g/day as consumed)	9-36
Table 9-22.        Mean and Standard Error for the Daily Intake of Food Subclasses Per Capita by Age
                  (g/day as consumed)	,	9-37
Exposure Factors Handbook
August 1997	
Page
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EFH
                                     LIST OF TABLES (continued)
                                                                                              Page No.
Table 9-23.


Table 9-24.
Table 9-25.
Table 9-26.

Table 9-27.

Table 9-28.
Table 9-29.
Table 9-30.
Table 9 A-1.

Table 9 B.

Table 10-1.
Table 10-2.
Table 10-3.
Table 10-4.
Table 10-5.
Table 10-6.
Table 10-7.

Table 10-8.

Table 10-9.

Table 10-10.

Table 10-11.

Table 10-12.

Table 10-13.

Table 10-14.

Table 10-15.

Table 10-16.

Table 10-17.
Consumption of Foods (g dry weight/day) for Different Age Groups and Estimated
Lifetime Average Daily Food Intakes for a US Citizen (averaged across sex) Calculated
from the FDA Diet Data	9-37
Mean Daily Intake of Foods (grams) Based on the Nutrition Canada Dietary Survey	9-38
Per Capita Consumption of Fresh Fruits and Vegetables in 1991	9-38
Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating Occasion and the
Percentage of Individuals Using These Foods in Three Days	9-39
Mean Moisture Content of Selected Fruits and Vegetables Expressed as Percentages of
Edible Portions	9-40
Summary of Fruit and Vegetable Intake Studies	9-43
Summary of Recommended Values for Per Capita Intake of Fruits and Vegetables  	9-44
Confidence in Fruit and Vegetable Intake Recommendations	9-45
Fraction of Grain and Meat Mixture Intake Represented by
Various Food Items/Groups  	  9A-3
Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data .. .	9 B-3

Total Fish Consumption by Demographic Variables  	10-30
Mean and 95th Percentile of Fish Consumption (g/day) by Sex and Age	10-31
Percent Distribution of Total Fish Consumption for Females by Age	10-32
Percent Distribution of Total Fish Consumption for Males by Age 	10-32
Mean Total Fish Consumption by Species  	10-33
Best Fits of Lognormal Distributions Using the NonLinear Optimization (NLO) Method . 10-33
Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the
U.S. Population (Uncooked Fish Weight)	,	10-34
Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) by Habitat
for Consumers Only (Uncooked Fish Weight)	10-35
Per Capita Distribution of Fish Intake (mg/kg-day) by Habitat and Fish Type for U.S.
Population (Uncooked Fish Weight)	10-36
Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) by Habitat for
Consumers Only (Uncooked Fish Weight)	10-37
Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S.
Population (Cooked Fish Weight - As Consumed))	 10-38
Per Capita Distribution of Fish Intake (g/day) by Habitat for Consumers Only
(Cooked Fish Weight - As Consumed))	10-39
Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the
U.S. Population by Age and Gender - As Consumed (Freshwater and Estuarine) 	10-40
Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the
U.S. Population by Age and Gender - As Consumed (Marine)	10-40
Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the
U.S. Population by Age and Gender - As Consumed (All Fish)	10-41
Per Capita Distribution of Fish (Finfish and Shellfish) Intake (grams/day) for the
U.S. Population Aged 18 Years  and Older by Habitat - As Consumed	10-41
Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the
U.S. Population by Age and Gender - As Consumed (Freshwater and Estuarine) 	10-42
Page
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                                                     Exposure Factors Handbook
                                                    	August 1997

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                                                                                       EFH
                                      LIST OF TABLES (continued)
                                                                                                Page No.
 Table 10-18.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the
                   U.S. Population by Age and Gender - As Consumed (Marine)	10-42
 Table 10-19.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the
                   U.S. Population by Age and Gender - As Consumed (All Fish)	10-43
 Table 10-20.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the
                   U.S. Population Aged 18 Years and Older by Habitat - As Consumed  	10-43
 Table 10-21.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for
                   Consumers Only by Age and Gender - As Consumed (Freshwater and Estuarine)	10-44
 Table 10-22.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for
                   Consumers Only by Age and Gender - As Consumed (Marine)	•	10-44
 Table 10-23.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for
                   Consumers Only by Age and Gender - As Consumed (All Fish)	10-45
 Table 10-24.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for
                   Consumers Only Aged 18 Years and Older by Habitat - As Consumed   	10-45
 Table 10-25.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for
                   Consumers Only by Age and Gender - As Consumed (Freshwater and Estuarine)	10-46
 Table 10-26.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for
                   Consumers Only by Age and Gender - As Consumed (Marine)	10-46
 Table 10-27.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for
                   Consumers Only by Age and Gender - As Consumed (All Fish)  	10-47
 Table 10-28.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for
                   Consumers Only Aged 18 Years and Older by Habitat - As Consumed	.	10-47
 Table 10-29.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for
                   the U.S. Population by Age and Gender - Uncooked Fish Weight
                   (Freshwater and Estuarine)	10-48
 Table 10-30.      . Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for
                   the U.S. Population by Age and Gender - Uncooked Fish Weight (Marine)	  10-48
 Table 10-31.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for
                   the U.S. Population by Age and Gender - Uncooked Fish Weight (All Fish)	10-49
 Table 10-32.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for
                   the U.S. Population Aged 18 Years and Older by Habitat - Uncooked Fish Weight 	10-49
 Table 10-33.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S.
                   Population by Age and Gender - Uncooked Fish Weight (Freshwater and Estuarine)	10-50
 Table 10-34.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for
                   the U.S. Population by Age and Gender - Uncooked Fish Weight (Marine)  	10-50
 Table 10-35.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for
                   the U.S. Population by Age and Gender - Uncooked Fish Weight (All Fish)	10-51
 Table 10-36.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S.
                   Population Aged 18 Years and Older by Habitat - Uncooked Fish Weight	 10-51
 Table 10-37.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers
                   Only by Age and Gender - Uncooked Fish Weight (Freshwater and Estuarine)	10-52
 Table 10-38.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for
                   Consumers Only by Age and Gender - Uncooked Fish Weight (Marine)	 10-52
Exposure Factors Handbook
August 1997          	
Page
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EFH
                                    LIST OF TABLES (continued)
                                                                                             Page No.
Table 10-39.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for
                  Consumers Only by Age and Gender - Uncooked Fish Weight (All Fish)	10-53
Table 10-40.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for
                  Consumers Only Aged 18 Years and Older by Habitat - Uncooked Fish Weight	10-53
Table 10-41.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers
                  Only by Age and Gender - Uncooked Fish Weight (Freshwater and Estuarine)		10-54
Table 10-42.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for
                  Consumers Only by Age and Gender - Uncooked Fish Weight (Marine)	10-54
Table 10-43.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for
                  Consumers Only by Age and Gender - Uncooked Fish Weight (All Fish)	10-55
Table 10-44.       Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for
                  Consumers Only Aged 18 Years and Older by Habitat - Uncooked Fish Weight	10-55
Table 10-45.       Distribution of Quantity of Fish Consumed (in grams) Per Eating Occasion, by
                  Age and Sex  	1Q-56
Table 10-46.       Mean Fish Intake in a Day, by Sex and Age	10-56
Table 10-47.       Percent of Respondents That Responded Yes, No, or Don't Know to Eating
                  Seafood in 1 Month (including shellfish, eels, or squid)	10-57
Table 10-48.       Number of Respondents Reporting Consumption of a Specified Number  of
                  Servings of Seafood in 1  Month  	10-58
Table 10-49.  '     Number of Respondents Reporting Monthly Consumption of Seafood That Was
                  Purchased or Caught by Someone They Knew  	10-59
Table 10-50.       Estimated Number of Participants in Marine Recreational Fishing by State
                  and Subregion	10-60  '
Table 10-51.       Estimated Weight of Fish Caught (Catch Type A and B1) by Marine Recreational
                  Fishermen, by Wave and Subregion	10-61
Table 10-52.       Average Daily Intake (g/day) of Marine Finfish, by Region and Coastal Status	10-62
Table 10-53.       Estimated Weight of Fish Caught (Catch Type A and B1) by Marine
                  Recreational Fishermen by Species Group and Subregion, Atlantic and Gulf	10-62
Table 10-54.       Estimated Weight of Fish Caught (Catch Type A and B1) by Marine
                  Recreational Fishermen by Species Group and Subregion, Pacific	10-63
Table 10-55.       Median Intake Rates Based on Demographic Data of Sport Fishermen and
                  Their Family/Living Group	10-63
Table 10-56.       Cumulative Distribution of Total Fish/Shellfish  Consumption by Surveyed
                  Sport Fishermen in the Metropolitan Los Angeles Area	10-64
Table 10-57.       Catch Information for Primary Fish Species Kept by Sport Fishermen (n=1059)	10-64
Table 10-58.        Percent of Fishing Frequency During the Summer and Fall Seasons in Commencement
                   Bay, Washington	1Q-64
Table 10-59.        Selected Percentile Consumption Estimates (g/day) for the Survey and Total Angler
                   Populations Based on the Reanalysis of the Puffer et al. (1981) and Pierce  et al. (1981)
                   Data	10-65
Table 10-60.        Means  and Standard Deviations of Selected Characteristics by Subpopulation
                   Groups in Everglades, Florida	10-65
Table 10-61.       Mean Fish Intake Among Individuals Who Eat Fish and Reside in Households
                   With Recreational Fish Consumption	10-66
 Page
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Exposure Factors Handbook
                 August 1997

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                                                                                    EFH
                                    LIST OF TABLES (continued)
                                                                                             Page No.
Table 10-62.       Comparison of Seven-Day Recall and Estimated Seasonal Frequency for Fish
                  Consumption	10-66
Table 10-63.       Distribution of Usual Fish Intake Among Survey Main Respondents Who
                  Fished and Consumed Recreationally Caught Fish	10-66
Table 10-64.       Estimates of Fish Intake Rates of Licensed Sport Anglers in Maine During the
                  1989-1990 Ice Fishing or 1990 Open-Water Seasons	:	10-67
Table 10-65.       Analysis of Fish Consumption by Ethnic Groups for "All Waters" (g/day) 	10-67
Table 10-66.       Total Consumption of Freshwater Fish Caught by All Survey Respondents
                  During the 1990 Season	10-68
Table 10-67.     .  Mean Sport-Fish Consumption by Demographic Variables, Michigan Sport
                  Anglers Fish Consumption Study, 1991-1992	10-68
Table 10-68.       Distribution of Fish Intake Rates (from all sources and from sport-caught sources)
                  For 1992 Lake Ontario Anglers	10-69
Table 10-69.       Mean Annual  Fish Consumption (g/day) for Lake Ontario Anglers, 1992, by
                  Sociodemographic Characteristics	10-69
Table 10-70.       Percentile and Mean Intake Rates for Wisconsin Sport Anglers	10-70
Table 10-71.       Sociodemographic Characteristics of Respondents	10-70
Table 10-72.       Number of Grams Per Day of Fish Consumed by All Adult Respondents
                  (Consumers and Non-consumers Combined) - Throughout the Year	10-71
Table 10-73.       Fish Intake Throughout the Year by Sex, Age, and Location by All Adult Respondents  . . 10-71
Table 10-74.       Children's Fish Consumption Rates - Throughout Year	10-72
Table 10-75.       Sociodemographic Factors and Recent Fish Consumption	10-72
Table 10-76.       Number of Local Fish Meals Consumed Per Year by Time Period for All Respondents  . . 10-74
Table 10-77.       Mean Number of Local Fish Meals Consumed Per Year by Time Period for All
                  Respondents and Consumers Only  	10-74
Table 10-78.       Mean Number of Local Fish Meals Consumed Per Year by Time Period and
                  Selected Characteristics for All Respondents (Mohawk, N=97; Control, N=154)	10-75
Table 10-79.       Percentage of Individuals Using Various Cooking Methods at Specified Frequencies .... 10-75
Table 10-80.       Percent Moisture and Fat Content for Selected Species	10-76
Table 10-81.       Recommendations - General Population	10-79
Table 10-82.       Recommendations - General Population - Fish Serving Size  	10-79
Table 10-83.       Recommendations - Recreational Marine Anglers  	10-79
Table 10-84.       Recommendations - Freshwater Anglers	10-79
Table 10-85.       Recommendations - Native American Subsistence Populations	10-80.
Table 10-86.       Summary of Fish Intake Studies	10-81
Table 10-87.       Confidence in Fish Intake Recommendations for General Population 	10-85
Table 10-88.       Confidence in Fish Intake Recommendations for Recreational Marine Anglers	10-86
Table 10-89.       Confidence in Recommendations for Fish Consumption - Recreational Freshwater	10-87
Table 10-90.       Confidence in Recommendations for Native American Subsistence Fish Consumption ... 10-88
Table 10B-1.       Percent of Fish Meals Prepared Using Various Cooking Methods by Residence Size .. .  10B-3
Table 10B-2.       Percent of Fish Meals Prepared Using Various Cooking Methods by Age	  10B-3
Table 10B-3.       Percent of Fish Meals Prepared Using Various Cooking Methods by Ethnicity	  10B-4
Table 10B-4.       Percent of Fish Meals Prepared Using Various Cooking Methods by Education	  10B-4
Table 10B-5.       Percent of Fish Meals Prepared Using Various Cooking Methods by Income	  10B-5
Exposure Factors Handbook
August 1997	
Page
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 EFH
                                    LIST OF TABLES (continued)
                                                                                            Page No.
Table 10B-6.      Percent of Fish Meals Where Fat was Trimmed or Skin was Removed, by Demographic
                  Variables	  10B-6
Table 10B-7.      Method of Cooking of Most Common Species Kept by Sportfishermeri  	  10B-7
Table 10B-8.      Adult Consumption of Fish Parts  	  10B-7
Table 10C-1.      Daily Average Per Capita Estimates of Fish Consumption U.S. Population - Mean
                  Consumption by Species Within Habitat - As Consumed Fish	  10C-3
Table 10C-2.      Daily Average Per Capita Estimates of Fish Consumption U.S. Population - Mean
                  Consumption by Species Within Habitat - Uncooked Fish	  10C-4
Table 10C-3.      Daily Average Per Capita Estimates of Fish Consumption As Consumed Fish - Mean
                  Consumption by Species Within Habitat - U.S. Population  	  10C-5
Table 10C-4.      Daily Average Per Capita Estimates of Fish Consumption Uncooked Fish - Mean
                  Consumption by Species Within Habitat - U.S. Population  	  10C-6

Table 11-1.        Per Capita Intake of Total Meats (g/kg-day as consumed))	11-9
Table 11-2.        Per Capita Intake of Total Dairy Products (g/kg-day as consumed))  	11-10
Table 11-3.        Per Capita Intake of Beef (g/kg-day as consumed))  	11-11
Table 11-4.        Per Capita Intake of Pork (g/kg-day as consumed)	11-12
Table 11-5.        Per Capita Intake of Poultry (g/kg-day as consumed)	11-13
Table 11-6.        Per Capita Intake of Game (g/kg-day as consumed))  	11-14
Table 11-7.        Per Capita Intake of Eggs (g/kg-day as consumed)	 11-15
Table 11-8.        Main Daily Intake of Meat and Dairy Products Per Individual in a Day for USDA
                  1977-78, 87-88, 89-91, 94, and 95 Surveys 	11-16
Table 11-9.        Mean Per Capita Intake Rates for Meat, Poultry, and Dairy Products (g/kg-day as consumed)
                  Based on All Sex/Age/Demographic Subgroups	11-17
Table 11-10.       Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as consumed)
                  for 1977-1978	11-18
Table 11-11.       Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as consumed)
                  for 1987-1988	11-18
Table 11-12.       Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day as
                  consumed) for 1977-1978	11-19
Table 11-13.       Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day as consumed)
                  for 1987-1988	11-19
Table 11-14.       Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as consumed)
                  for 1994 and 1995	11-20
Table 11-15.       Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age
                  (g/day as consumed) for 1994 and 1995	11-20
Table 11-16.       Mean and Standard Error for the Dietary Intake of Food Sub Classes Per Capita by Age
                  (g/day as consumed) 	11-21
Table 11-17.       Mean and Standard Error for the Per Capita Daily Intake of Food Class and
                  Sub Class by Region (g/day as consumed)	11-21
Table 11-18.       Consumption of Meat, Poultry, and Dairy Products for Different Age Groups (averaged
                  across sex), and Estimated Lifetime Average Intakes for 70  Kg Adult Citizens
                  Calculated from the FDA Diet Data 	11-22
Page
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 Exposure Factors Handbook
	August 1997

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                                     LIST OF TABLES (continued)
                                                                                              Page No.
 Table 11-19.       Per Capita Consumption of Meat and Poultry in 1991	.•	11-22
 Table 11-20.       Per Capita Consumption of Dairy Products in 1991	11-23
 Table 11-21.       Adult Mean Daily Intake (as consumed) of Meat and Poultry Grouped by Region and
                   Gender	 11-24
 Table 11-22.       Amount (as consumed) of Meat Consumed by Adults Grouped by Frequency of Eatings  . 11-24
 Table 11-23.       Quantity (as consumed) of Meat, Poultry, and Dairy Products Consumed Per
                   Eating Occasion and the Percentage of Individuals Using These Foods in Three Days ... 11 -25
 Table 11-24.       Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible
                   Portions) of Selected Meat and Dairy Products	11-26
 Table 11-25.       Fat Content of Meat Products	11-27
 Table 11 -26.       Fat Intake, Contribution of Various Food Groups to Fat Intake, and Percentage of the
                   Population in Various Meat Eater Groups of the U.S. Population  	11-28
 Table 11-27.       Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gender	11-28
 Table 11-28.       Percentage Mean Moisture Content (Expressed as Percentages of 100 Grams of
                   Edible Portions)	11-29
 Table 11-29.       Summary of Meat, Poultry, and Dairy Intake Studies	11-30
 Table 11 -30.       Summary of Recommended Values for Per Capita Intake of Meat and Dairy
                   Products and Serving Size	11-31
 Table 11-31.       Confidence in Meats and Dairy  Products Intake Recommendations .. .	 11-32

 Table 12-1.         Per Capita Intake of Total Grains Including Mixtures (g/kg-day as consumed)	12-6
 Table 12-2.         Per Capita Intake of Breads (g/kg-day as consumed))  	12-7
 Table 12-3.         Per Capita Intake of Sweets (g/kg-day as consumed)	12-8
 Table 12-4.         Per Capita Intake of Snacks Containing Grain (g/kg-day as consumed)	12-9
 Table 12-5.         Per Capita Intake of Breakfast Foods (g/kg-day as consumed)	 12-10
 Table 12-6.         Per Capita Intake of Pasta (g/kg-day as consumed)  	12-11
 Table 12-7.         Per Capita Intake of Cooked Cereals (g/kg-day as consumed)	12-12
 Table 12-8.         Per Capita Intake of Rice (g/kg-day as consumed)  .-..-.	:.,.-.		12-13
 Table 12-9.         Per Capita Intake of Ready-to-Eat Cereals  (g/kg-day as consumed))	12-14
 Table 12-10.       Per Capita Intake of Baby Cereals (g/kg-day as consumed)	12-15
 Table 12-11.       Mean Daily Intakes of Grains Per Individual in a Day for USDA 1977-78,
                   87-88, 89-91, 94, and 95 Surveys	12-16
 Table 12-12.       Mean Per Capita Intake Rates for Grains Based on All Sex/Age/Demographic
                   Subgroups	12-16
 Table 12-13.       Mean Grain Intake Per Individual in a Day by Sex and Age (g/day as consumed)
                   for 1977-1978	12-17
 Table 12-14..       Mean Grain Intakes Per Individual in a Day by Sex and Age (g/day as consumed)
                   for 1987-1988	12-17
 Table 12-15.       Mean Grain Intakes Per Individual in a Day by Sex and Age (g/day as consumed)
                   for 1994 and 1995	12-18
 Table 12-16.       Mean and Standard Error for the Daily Per Capita Intake of Grains, by Age
                   (g/day as consumed)	12-18
 Table 12-17.       Mean and Standard Error for the Daily Intake of Grains, by Region (g/day as
                   consumed)	,	12-19
Exposure Factors Handbook
August 1997	
Page
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EFH
                                    LIST OF TABLES (continued)
                                                                                           Page No.
Table 12-18.       Consumption of Grains (g dry weight/day) for Different Age Groups and Estimated
                  Lifetime Average Daily Food Intakes for a U.S. Citizen (averaged across sex) Calculated
                  from the FDA Diet Data	12-19
Table 12-19.       Per Capita Consumption of Flour and Cereal Products in 1991  	12-20
Table 12-20.       Quantity (as consumed) of Grain Products Consumed Per Eating Occasion and the
                  Percentage of Individuals Using These Foods in Three Days	12-20
Table 12-21.       Mean Moisture Content of Selected Grains Expressed as Percentages of Edible Portions . 12-21
Table 12-22.       Summary  of Grain Intake Studies	12-22
Table 12-23.       Summary  of Recommended Values for Per Capita Intake of Grain Products	12-22
Table 12-24.       Confidence in Grain Products Intake Recommendation	12-23
Table 12 A-1.       Food Codes and Definitions Used in the Analysis of the 1989-91 USDA CSFH
                  Grains Data	  12A-3

Table 13-1.        1986 Vegetable Gardening by Demographic Factors	13-1
Table 13-2.        Percentage of Gardening Households Growing Different Vegetables in 1986	13-1
Table 13-3.        Sub-category Codes and Definitions	13-4
Table 13-4.        Weighted and Unweighted Number of Observations (Individuals) for NFCS Data
                  Used in Analysis of Food Intake	13-6
Table 13-5.        Percent Weight Losses from Preparation of Various Meats	13-8
Table 13-6.        Percent Weight Losses from Preparation of Various Fruits 		13-8
Table 13-7.        Percent Weight Losses from Preparation of Various Vegetables 	13-9
Table 13-8.        Consumer Only Intake of Homegrown Fruits (g/kg-day) -  All Regions Combined 	13-12
Table 13-9.        Consumer Only Intake of Homegrown Fruits (g/kg-day) -  Northeast	13-13
Table 13-10.       Consumer Only Intake of Homegrown Fruits (g/kg-day) -  Midwest	13-13
Table 13-11.       Consumer Only Intake of Homegrown Fruits (g/kg-day) -  South	13-14
Table 13-12.       Consumer Only Intake of Homegrown Fruits (g/kg-day) -  West 	13-14
Table 13-13.       Consumer Only Intake of Homegrown Vegetables (g/kg-day) - All Regions  Combined ..  13-15
Table 13-14.       Consumer Only Intake of Homegrown Vegetables (g/kg-day) - Northeast	13-16
Table 13-15.       Consumer Only Intake of Homegrown Vegetables (g/kg-day) - Midwest  	.•	13-16
Table 13-16.       Consumer Only Intake of Homegrown Vegetables (g/kg-day) - South	13-17
Table 13-17.       Consumer Only Intake of Homegrown Vegetables (g/kg-day) - West  	13-17
Table 13-18.       Consumer Only Intake of Home Produced Meats (g/kg-day) - All Regions Combined ...  13-18
Table 13-19.       Consumer Only Intake of Home Produced Meats (g/kg-day) - Northeast	13-19
Table 13-20.       Consumer Only Intake of Home Produced Meats (g/kg-day) - Midwest  	13-19
Table 13-21.       Consumer Only Intake of Home Produced Meats (g/kg-day) - South	13-20
Table 13-22.       Consumer Only Intake of Home Produced Meats (g/kg-day) - West 	13-20
Table 13-23.       Consumer Only Intake of Home Caught Fish (g/kg-day) -  All Regions Combined 	13-21
Table 13-24.       Consumer Only Intake of Home Caught Fish (g/kg-day) -  Northeast	13-22
Table 13-25.       Consumer Only Intake of Home Caught Fish (g/kg-day) -  Midwest	13-22
Table 13-26.       Consumer Only Intake of Home Caught Fish (g/kg-day) -  South	13-23
Table 13-27.       Consumer Only Intake of Home Caught Fish (g/kg-day) -  West	13-23
Table 13-28.       Consumer Only Intake of Home Produced Dairy (g/kg-day) - All Regions 	13-24
Table 13-29.       Consumer Only Intake of Home Produced Dairy (g/kg-day) - Northeast	13-25
Table 13-30.       Consumer Only Intake of Home Produced Dairy (g/kg-day) - Midwest	13-25
 Page
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        	August 1997

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                                                                                  EFH
                                    LIST OF TABLES (continued)
                                                                                           Page No.
 Table 13-31.       Consumer Only Intake of Home Produced Dairy (g/kg-day) - South	13-26
 Table 13-32.       Consumer Only Intake of Home Produced Dairy (g/kg-day) - West	13-26
 Table 13-33.       Seasonally Adjusted Consumer Only Homegrown Intake (g/kg-day)	13-27
 Table 13-34.       Consumer Only Intake of Homegrown Apples (g/kg-day)	13-28
 Table 13-35.       Consumer Only Intake of Homegrown Asparagus (g/kg-day)  	13-29
 Table 13-36.       Consumer Only Intake of Home Produced Beef (g/kg-day)	13-30
 Table 13-37.       Consumer Only Intake of Homegrown Beets (g/kg-day)  	13-31
 Table 13-38.       Consumer Only Intake of Homegrown Broccoli (g/kg-day)	13-32
 Table 13-39.       Consumer Only Intake of Homegrown Cabbage (g/kg-day)	13-33
 Table 13-40.       Consumer Only Intake of Homegrown Carrots (g/kg-day) ... '.	13-34
 Table 13-41.       Consumer Only Intake of Homegrown Corn (g/kg-day)	13-35
 Table 13-42.       Consumer Only Intake of Homegrown Cucumbers (g/kg-day)		13-36
 Table 13-43.       Consumer Only Intake of Home Produced Eggs (g/kg-day)	13-37
 Table 13-44.       Consumer Only Intake of Home Produced Game (g/kg-day)	13-38
 Table 13-45.       Consumer Only Intake of Home Produced Lettuce (g/kg-day)	13-39
 Table 13-46.       Consumer Only Intake of Home Produced Lima Beans (g/kg-day) 	13-40
 Table 13-47.       Consumer Only Intake of Homegrown Okra (g/kg-day)	13-41
 Table 13-48.       Consumer Only Intake of Homegrown Onions (g/kg-day)	13-42
 Table 13-49.       Consumer Only Intake of Homegrown Other Berries (g/kg-day)	13-43
 Table 13-50.       Consumer Only Intake of Homegrown Peaches (g/kg-day)  	13-44
 Table 13-51.       Consumer Only Intake of Homegrown Pears (g/kg-day)  	13-45
 Table 13-52.       Consumer Only Intake of Homegrown Peas (g/kg-day)	  13-46
 Table 13-53.       Consumer Only Intake of Homegrown Peppers (g/kg-day)  	:	13-47
 Table 13-54.       Consumer Only Intake of Home Produced Pork (g/kg-day)	13-48
 Table 13-55.       Consumer Only Intake of Home Produced Poultry (g/kg-day)	13-49
 Table 13-56.       Consumer Only Intake of Homegrown Pumpkins (g/kg-day)	  13-50
 Table 13-57.       Consumer Only Intake of Homegrown Snap Beans (g/kg-day)	13-51
 Table 13-58.       Consumer Only Intake of Homegrown Strawberries  (g/kg-day)	13-52
 Table 13-59.       Consumer Only Intake of Homegrown Tomatoes (g/kg-day)	13-53
 Table 13-60.       Consumer Only Intake of Homegrown White Potatoes (g/kg-day) ..	  13-54
 Table 13-61.       Consumer Only Intake of Homegrown Exposed Fruit (g/kg-day)	13-55
 Table 13-62.       Consumer Only Intake of Homegrown Protected Fruits (g/kg-day) 	13-56
 Table 13-63.       Consumer Only Intake of Homegrown Exposed Vegetables (g/kg-day)	13-57
 Table 13-64.       Consumer Only Intake of Homegrown Protected Vegetables (g/kg-day)	13-58
 Table 13-65.       Consumer Only Intake of Homegrown Root Vegetables (g/kg-day)	'  13-59
 Table 13-66.       Consumer Only Intake of Homegrown Dark Green Vegetables (g/kg-day)	  13-60
 Table 13-67.       Consumer Only Intake of Homegrown Deep Yellow Vegetables (g/kg-day)	13-61
 Table 13-68.       Consumer Only Intake of Homegrown Other Vegetables (g/kg-day)		13-62
 Table 13-69.       Consumer Only Intake of Homegrown Citrus (g/kg-day)	13-63
 Table 13-70.       Consumer Only Intake of Homegrown Other Fruit (g/kg-day)	13-64
 Table 13-71.       Fraction of Food Intake that is Home Produced		13-65
 Table 13-72.       Confidence in Homegrown Food Consumption Recommendations 	13-67
 Table 13A-1.       Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data	 13A-3
Exposure Factors Handbook
August 1997	
Page
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EFH
                                    LIST OF TABLES (continued)
                                                                                             Page No.
Table 14-1.        Daily Intakes of Breast Milk	14'2
Table 14-2.        Breast Milk Intake for Infants Aged 1 to 6 Months	14-2
Table 14-3         Breast Milk Intake Among Exclusively Breast-fed Infants During the First 4 Months
                  of Life	14'3
Table 14-4.        Breat Milk Intake During a 24-Hour Period	14-3
Table 14-5.        Breast Milk Intake Estimated by the DARLING Study	14-4
Table 14-6.        Milk Intake for Bottle- and Breast-fed Infants by Age Group	14-4
Table 14-7.        Milk Intake for Boys and Girls	14-4
Table 14-8.        Intake of Breast Milk and Formula	14-5
Table 14-9         Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively Breast-fed
                  Infants	14'6
Table 14-10.       Predicted Lipid Intakes for Breast-fed Infants Under 12 Months of Age	14-6
Table 14-11.       Number of Meals Per Day	14-7
Table 14-12.       Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants
                  at 5 or 6 Months of Age in the United States in 1989, by Ethnic Background and
                  Selected Demographic Variables 	14-10
Table 14-13.       Breast Milk Intake Studies 	;	14-J l
Table 14-14.       Confidence in Breast Milk Intake Recommendations	14-13
Table 14-15.       Breast Milk Intake Rates Derived From Key Studies	14-14
Table 14-16.       Summary of Recommended Breast Milk and Lipid Intake Rates	14-15


VOLUME III

Table 15-1.        Time Use Table Locator Guide	15-20
Table 15-2.        Mean Time Spent (minutes) Performing Major Activities Grouped by Age, Sex and
                  Type of Day  	•	15'21
Table 15-3.        Mean Time Spent (minutes) in Major Activities Grouped by Type of Day for Five
                  Different Age Groups  	15-22
Table 15-4.        Cumulative Frequency Distribution of Average Shower Duration for 2,550 Households .  15-23
Table 15-5.        Mean Time Spent (minutes/day) in Ten Major Activity Categories Grouped by
                  Total Sample and Gender for the CARB and National Studies (age 18-64 years) 	15-24
Table 15-6.        Total Mean Time Spent at Three Major Locations Grouped by Total Sample and
                  Gender for the CARB  and National Study (ages 18-64 years)  	15-24
Table 15-7.        Mean Time Spent at Three Locations for both CARB and National Studies
                  (ages 12 years and older)	15-25
Table 15-8.        Mean Time Spent (minutes/day) in Various Microenvironments Grouped by Total
                  Population and Gender (12 years and over) in the National and CARB Data	15-26
Table 15-9.        Mean Time Spent (minutes/day) in Various Microenvironments by Type of Day for
                  the California and National Surveys (sample population ages 12 years and older)	15-27
Table 15-10.      Mean Time Spent (minutes/day) in Various Microenvironments by Age Groups
                   for the National and California Surveys 	15-28
Table 15-11.       Mean Time (minutes/day) Children Spent in Ten Major Activity Categories for All
                   Respondents	15-30
 Page
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 Exposure Factors Handbook
	August 1997

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                                                                                    EFH
                                     LIST OF TABLES (continued)
                                                                                            Page No.
 Table 15-12.       Mean Time Children Spent in Ten Major Activity Categories Grouped by Age
                   and Gender	           •,    15-30
 Table 15-13.       Mean Time Children Spent in Ten Major Activity Categories Grouped by Seasons
                   and Regions	.	...........'.,	   15-31
 Table 15-14.       Mean Time Children Spent in Six Major Location Categories for All Respondents
                   (minutes/day)	15.3 j
 Table 15-15.       Mean Time Children Spent in Six Location Categories Grouped by Age and Gender ... 15-32
 Table 15-16.       Mean Time Children Spent in Six Location Categories Grouped by Season and Region .. 15-32
 Table 15-17.'       Mean Time Children Spent in Proximity to Three Potential Exposures Grouped by
                   All Respondents, Age, and Gender		15-33
 Table 15-18.       Range of Recommended Defaults for Dermal Exposure Factors	15-33
 Table 15-19.       Number of Times Taking a Shower at Specified Daily Frequencies by the Number of
                   Respondents	          15-34
 Table 15-20.       Times (minutes) Spent Taking Showers by the Number of Respondents	15-35
 Table 15-21.       Number of Minutes Spent Taking a Shower (minutes/shower)	15-36
 Table 15-22.       Time (minutes) Spent in the Shower Room Immediately After Showering by the
                   Number of Respondents  	15-37
 Table 15-23.       Number of Minutes Spent in the Shower Room Immediately After Showering
                   (minutes/shower)	     15-38
 Table 15-24.       Number of Baths Given or Taken in One Day by Number of Respondents 	15-39
 Table 15-25.       Total Time Spent Taking  or Giving a Bath by the Number of Respondents	15-40
 Table 15-26.       Number of Minutes Spent Giving and Taking the Bath(s) (minutes/bath)  	15-41
 Table 15-27.       Time Spent in the Bathroom Immediately After the Bath(s) by the Number
                   of Respondents  	•  j 5.42
 Table 15-28.       Number of Minutes Spent in the Bathroom Immediately After the Bath(s)
                   (minutes/bath)	          15-43
 Table 15-29.       Total Time Spent Altogether in  the Shower or Bathtub by the Number of Respondents  . . 15-44
 Table 15-30.       Total Number of Minutes  Spent Altogether in the Shower or Bathtub (minutes/bath)	15-45
 Table 15-31.       Time Spent in the Bathroom Immediately Following a Shower or Bath by the
                   Number of Respondents   	15-46
 Table 15-32.       Numbejr.of Minutes Spent in the Bathroom Immediately Following a Shower or  °
                   Bath (minutes/bath)	15-47
 Table 15-33.       Range of Number of Times Washing the Hands at Specified Daily Frequencies by
                   the Number of Respondents	 15.48
 Table 15-34.       Number of Minutes Spent (at home)  Working or Being Near Food While Fried,
                   Grilled, or Barbequed  (minutes/day)	15-49
 Table 15-35.       Number of Minutes Spent (at home)  Working or Being Near Open Flames
                   Including Barbeque Flames (minutes/day)  	15-50
 Table 15-36.      Number of Minutes Spent Working or Being Near Excessive Dust in the Air
                   (minutes/day)	15.5 j
 Table 15-37.      Range of the Number of Times an Automobile or Motor Vehicle was Started in
                  a Garage or Carport at Specified Daily Frequencies by the Number of Respondents	15-52
 Table 15-38.       Range of the Number of Times Motor Vehicle Was Started with Garage Door
                  Closed at Specified Daily  Frequencies by the Number of Respondents	  15-53
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August 1997	
Page
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EFH
                                   LIST OF TABLES (continued)
                                                                                           Page No.
Table 15-39.       Number of Minutes Spent at a Gas Station or Auto Repair Shop (minutes/day)	15-54
Table 15-40.       Number of Minutes Spent at Home While the Windows Were Left Open
                  (minutes/day)	15~55
Table 15-41.       Number of Minutes the Outside Door Was Left Open While at Home (minutes/day) 	15-56
Table 15-42.       Number of Times an Outside Door Was Opened in the Home at Specified Daily
                  Frequencies by the Number of Respondents	15-57
Table 15-43.       Number of Minutes Spent Running, Walking, or Standing Alongside a Road with
                  Heavy Traffic (minutes/day)	•*	15"58
Table 15-44.       Number of Minutes Spent in a Car, Van, Truck, or Bus in Heavy Traffic (minutes/day) .. 15-59
Table 15-45.       Number of Minutes Spent in a Parking Garage or Indoor Parking Lot (minutes/day) 	15-60
Table 15-46.       Number of Minutes Spent Walking Outside to  a Car in the Driveway or Outside
                  Parking Areas (minutes/day)	15-61
Table 15-47.       Number of Minutes Spent Running or Walking Outside Other Than to the Car
                  (minutes/day)	15"62
Table 15-48.       Number of Hours Spent Working for Pay (hours/week)	15-63
Table 15-49.       Number of Hours Spent Working for Pay Between 6PM and 6AM (hours/week)	15-64
Table 15-50.       Number of Hours Worked in a Week That Was Outdoors (hours/week) 	15-65
Table 15-51.       Number of Times Floors Were Swept or Vacuumed at Specified Frequencies by the
                  Number of Respondents	15~66
Table 15-52.       Number of Days Since the Floor Area in the Home Was Swept or Vacuumed by the
                  Number of Respondents 	15-67
Table 15-53.       Number of Loads of Laundry Washed in a Washing Machine at Home by the
                  Number of Respondents 	•	15'68
Table 15-54.       Number of Times Using a Dishwasher at Specified Frequencies by the Number of
                  Respondents 		15-69
Table 15-55.       Number of Times Washing Dishes by Hand at Specified Frequencies by the Number
                  of Respondents 	15-70
Table 15-56.       Number of Times for Washing Clothes in a Washing Machine at Specified Frequencies
                  by the Number of Respondents	15-71
Table 15-57.  '     Number of Minutes Spent Playing on Sand or  Gravel in a Day by the Number of
                  Respondents 	15~72
Table 15-58.       Number of Minutes Spent Playing in Sand or Gravel (minutes/day) 	15-73
Table 15-59.       Number of Minutes Spent Playing in Outdoors on Sand, Gravel, Dirt, or Grass When
                  Fill Dirt Was Present by the Number of Respondents	15-74
Table 15-60.       Number of Minutes Spent Playing on Sand, Gravel, Dirt, or Grass When Fill Dirt
                  Was Present (minutes/day) 	15-75
Table 15-61.       Range of the Time Spent Working in a Garden or Other Circumstances in a Month
                  by the Number of Respondents	15-76
Table 15-62.       Number of Hours Spent Working with Soil in a Garden or Other Circumstances
                  Working (hours/month)	15-77
Table 15-63.       Range of Number of Minutes Spent Playing on Grass in a Day by the Number of
                  Respondents  	15~78
Table 15-64.       Number of Minutes Spent Playing on Grass (minutes/day)	15-79
 Page
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Exposure Factors Handbook
                 August 1997

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                                                                                     EFH
                                      LIST OF TABLES (continued)
                                                                                              Page No.
  Table 15-65.       Number of Times Swimming in a Month in Freshwater Swimming Pool by the
                   Number of Respondents 	               15-80
  Table 15-66.       Range of the Average Amount of Time Actually Spent in the Water by Swimmers by
                   the Number of Respondents  	           15-82
  Table 15-67.       Number of Minutes Spent Swimming in a Month in Freshwater Swimming Pool
                   (minutes/month)  	                        15-83
  Table 15-68.       Statistics for 24-Hour Cumulative Number of Minutes Spent Working in a Main Job	15-84
  Table 15-69.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Preparation  ..'.'.'.'.  15-85
  Table 15-70.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Cleanup	'.'.'.'.'.  15-86
  Table 15-71.       Statistics for 24-Hour Cumulative Number of Minutes Spent Cleaning House  	15-87
  Table 15-72.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Cleaning	15-88
  Table 15-73.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Clothes Care	15-89
  Table 15-74.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Car Repair/Maintenance '.  15-90
  Table 15-75.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Other Repairs	15-91
  Table 15-76.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Plant Care	15-92
  Table 15-77.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Animal Care ..........  15-93
 Table 15-78.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Other Household Work  .  15-94
 Table 15-79.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Indoor Playing 	15-95
 Table 15-80.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Playing	15-96
 Table 15-81.       Statistics for 24-Hour Cumulative Number of Minutes Spent for Car Repair Services  ..'.  15-97
 Table 15-82.       Statistics for 24-Hour Cumulative Number of Minutes Spent Washing, etc	15-98
 Table 15-83.       Statistics for 24-Hour Cumulative Number of Minutes Spent Sleeping/Napping	   15-99
 Table 15-84.       Statistics for 24-Hour Cumulative Number of Minutes Spent Attending
                   Full Time School	 .	                      15-100
 Table 15-85.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports	'. 15-101
 Table 15-86.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Recreation  .'.'. 15-102
 Table 15-87.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Exercise  	15-103
 Table 15-88.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Preparation .... .15-104
 Table 15-89.       Statistics for 24-Hour Cumulative Number of Minutes Spent Doing Dishes/Laundry  .'.'. 15-105
 Table 15-90.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Housekeeping	15-106
 Table 15-91.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Bathing	  15-107
 Table 15-92.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Yardwork/Maintenance  15-108
 Table 15-93.       Statistics for 24-Hour Cumulative Number of Minutes Spent in Sports/Exercise	15-109
 Table 15-94.       Statistics for 24-Hour Cumulative Number of Minutes Eating or Drinking  	15-110
 Table 15-95.       Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at an
                   Auto Repair Shop/Gas Station  	      ]5.j j ]
 Table 15-96.       Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a
                   Gym/Health Club  	       15_j 12
 Table 15-97.       Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at the
                   Laundromat	                     j^_j jo
 Table 15-98.       Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at Work
                   (non-specific)  	  	15_j 14
 Table 15-99.       Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at the	
                   Dry Cleaners	                     <_  
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EFH
                                    LIST OF TABLES (continued)
                                                                                            Page No.
Table 15-100.      Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a
                  Bar/Nightclub/Bowling Alley	l5'1 ^
Table 15-101.      Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Restaurant ... 15-117
Table 15-102'.      Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at School 	15-118
Table 15-103.      Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a
                  Plant/Factory/Warehouse 	15
Table 15-104.      Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on a
                  Sidewalk, Street, or in the Neighborhood	15-120
Table 15-105.      Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors in a
                  Parking Lot	?.	15"121
Table 15-106.      Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a
                  Service Station or Gas Station	15~12
Table 15-107.      Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a
                  Construction Site	15-123
Table 15-108.      Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on School
                  Grounds/Playground	15-124
Table 15-109.      Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a
                  Park/Golf Course	15-125
Table 15-110.      Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a
                  Pool/River/Lake 	15~126
Table 15-111.      Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a
                  Restaurant/Picnic	•  ]^']^7
Table 15-112.      Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Farm	15-128
Table 15-113.      Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Kitchen . . .  15-129
Table 15-114      Statistics for 24-Hour Cumulative Number of Minutes Spent in the Bathroom 	15-130
Table 15-115.      Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Bedroom .. 15-131
Table 15-116.      Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Garage  ... 15-132
Table 15-117.      Statistics for 24-Hour Cumulative Number of Minutes Spent in the Basement 	15-133
Table 15-118.      Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the
                  Utility Room or Laundry Room 	'	15-134
Table 15-119.     Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Outdoor
                  Pool or Spa	• • • • 15~135
 Table 15-120.      Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Yard or
                   Other Areas Outside the House	15-136
 Table 15-121.      Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in a Car	15-137
 Table 15-122.      Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in a Truck
                   (Pick-up/Van)  	15'138
 Table 15-123.      Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Motorcycle,
                   Moped, or Scooter	^"l^n
 Table 15-124.      Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in Other Trucks  15-14U
 Table 15-125.      Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Bus	15-141
 Table 15-126.      Statistics for 24-Hour Cumulative Number of Minutes Spent Walking 	15-142
 Table 15-127.      Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a
                   Bicycle/Skateboard/Rollerskate 	15-143
 Page
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                 August 1997

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EFH
Table 15-128.
Table 15-129.
Table 15-130.
Table 15-131.
Table 15-132.
Table 15-133.
Table 15-135.
Table 15-136.
Table 15-137.
Table 15-138.
Table 15-139.
Table 15-140.
Table 15-141.
Table 15-142.
Table 15-143.
Table 15-146.
Table 15-147.
Table 15-148.
Table 15-149.
Table 15-150.
Table 15-151.
Table 15-152.
Table 15-153.
Table 15-154.
LIST OF TABLES (continued)
Statistics for 24-Hour Cumulative Number of Minutes Spent Waiting on a Bus Train
etc., Stop 	
Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a
Train/Subway/Rapid Transit ...
Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on an Airplane
Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors in a Residence
(all rooms) 	
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors (outside the
residence) 	
Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling Inside
a Vehicle 	
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Near a Vehicle
Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Other Than
Near a Residence or Vehicle Such as Parks, Golf Courses, or Farms
Statistics for 24-Hour Cumulative Number of Minutes Spent in an Office or Factory
Statistics for 24-Hour Cumulative Number of Minutes Spent in Malls, Grocery Stores
or Other Stores 	 ,
Statistics for 24-Hour Cumulative Number of Minutes Spent in Schools, Churches
Hospitals, and Public Buildings .
Statistics for 24-Hour Cumulative Number of Minutes Spent in Bars/Nightclubs
Bowling Alleys, and Restaurants . .
Statistics for 24-Hour Cumulative Number of Minutes Spent in Other Outdoors
Such as Auto Repair Shops, Laundromats, Gyms, and at Work (non-specific)
Statistics for 24-Hour Cumulative Number of Minutes Spent with Smokers Present
Range of Time (minutes) Spent Smoking Based on the Number of Respondents
Number of Minutes Spent Smoking (minutes/day)
Range of Time Spent Smoking Cigars or Pipe Tobacco by the Numberof Respondents
Number of Minutes Spent Smoking Cigars or Pipe Tobacco (minutes/day)
Range of Numbers of Cigarettes Smoked Based on the Number of Respondents
Range of Numbers of Cigarettes Smoked by Other People Based on Number
of Respondents 	
Range of Numbers of Cigarettes Smoked While at Home Based on the
Numberof Respondents ...
Differences in Time Use (hours/week) Grouped by Sex, Employment Status,
and Marital Status for the Surveys Conducted in 1965 and 1975
Time Use (hours/week) Differences by Age for the Surveys Conducted in 1 965
and 1975 	
Time Use (hours/week) Differences by Education for the Surveys Conducted in 1965
and 1975 	
Time Use (hours/week) Differences by Race for the Surveys Conducted in 1965
and 1975 	
Mean Time Spent (hours/week) in Ten Major Activity Categories Grouped by Regions
Total Mean Time Spent (minutes/day) in Ten Major Activity Categories Grouped by

Exposure Factors Handbook
August 1997
Page No.
1^1 A A
1 ^ I/IS
. 15-1.46
1 C 1 A*J
. . 1O-14/
1 £ 1 A 0
. . 1J-145
. . ij-14y
. 15-150
15-151
, . 15-152
1 ^ 1 ^3
1< 1C/1
IS 1SS
15-156
. 15-157
, 15-158
15-160
. 15-161
15-162
. 15-163
1 < 1 f*A
. O-104
. 15-165
. 15-166
. 15-167
. 15-168
, 15-169
15-169
15-170
Page
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EFH
                                    LIST OF TABLES (continued)
                                                                                             Page No.
Table 15-155.      Mean Time Spent (minutes/day) in Ten Major Activity Categories During Four Waves   ^^

Table 15-156.      MeSmrSpent (hours/week) in Ten Major Activity Categories Grouped by Gender .  15-171
Table 15-157      Percent Responses of Children's "Play" (activities) Locations m Maryvale, Arizona ...   5-71
Table 15-158.      Occupational Tenure of Employed Individuals by Age and Sex	«-
Table 15-159      Occupational Tenure for Employed Individuals Grouped by Sex and Race	15-172
Table 15-160!      Occupational Tenure for Employed Individuals Grouped by Sex and Employment      ^^

Table 15-161.      Occupational Tenure'of Employed Individuals Grouped by Major Occupational         ^^
                  Groups and Age  	•';	'''''	, ^ 17,
Table 15-162      Voluntary Occupational Mobility Rates for Workers Age 16 Years and Older 	15-173
Table 15-163.      Values and Their Standard Errors for Average Total Residence Time, T, tor           ^^
                  Each Group in Survey	''''''	
Table 15-164.      Total Residence Time, t (years), Corresponding to Selected Values of R(t) by          ^^
                  Housing Category	]5 J75
Table 15-165.      Residence Time of Owner/Renter Occupied Units	
Table 15-166      Percent of Householders Living in Houses for Specified Ranges of Time	  3-/3
Table 15-167.      Descriptive Statistics for Residential Occupancy Period  	"
Table 15-168       Descriptive Statistics for Both Genders by Current Age	^
Table 15-169.      Summary of Residence Time of Recent Home Buyers (1993) 	  »-
Table 15-170.      Tenure in Previous Home (Percentage Distribution)  	
 Table 15-171.      Number of Miles Moved (Percentage Distribution)  	[5  n*
 Table 15-172.      Confidence in Activity Patterns Recommendations  	  '
 Table 15-173.      Confidence in Occupational Mobility Recommendations	15.1%%
 Table 15-174       Recommendations for Population Mobility  	  "
 Table 15-175       Confidence in Population Mobility Recommendations	  ^
 Table 15-176.      Summary of Recommended Values for Activity Factors 	»•>-"
 Table 15A-1       Activity Codes.and Descriptors Used for Adult Time Diaries	
 Table 15A-2       Differences in Average Time Spent in Different Activities Between California
                   and National Studies (minutes per day for age 18-64 years)	  15A-19
 Table 15A-3.       Time Spent in Various Microenvironments  	  15A-21
 Table 15A-4.      Major Time Use Activity Categories	•• • • • • • • • • • • •	     "
 Table 15A-5.      Mean Time Spent (minutes/day) for 87 Activities Grouped by Day of the Week	   5A-22
 Table 15A-6       Weighted Mean Hours Per Week by Gender: 87 Activities  and 10 Subtotals 	  15A-24
 Table 15A-7       Ranking of Occupations by Median Years of Occupational Tenure	
 Table 15B-l"      Annual Geographical Mobility Rates, by Type of Movement for Selected
                    1-Year Periods: 1960-1992 (numbers in thousands)	
 Table 15B-2.      Mobility of the Resident Population by State: 1980	

 Table 16-1         Consumer Products Found in the Typical U.S. Household
 Table 16-2         Frequency of Use for Household Solvent Products (users-only)
 Table 16-3         Exposure Time of Use for Household Solvent Products (users-only)
 Table 16-4'        Amount of Products Used for Household Solvent Products (users-only)	  0- ^
  Table 16-5         Time Exposed After Duration of Use for Household Solvent Products (users-only) 	  6-3
  Table 16-6.        Frequency of Use and Amount of Product Used for Adhesive Removers	io-1«
  Page
  xxviii
Exposure Factors Handbook
                 August 1997

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                                                                                       EFH
                                      LIST OF TABLES (continued)
                                                                                               Pagfe No.

  Table 16-7.        Adhesive Remover Usage by Gender	                16_14
  Table 16-8.        Frequency of Use and Amount of Product Used for Spray Paint !	  	16~15
  Table 16-9.        Spray Paint Usage by Gender	,	]\	j/,-
  Table 16-10.       Frequency of Use and Amount of Product Used for Paint Removers/Strippers	16 16
  Table 16-11.       Paint Stripper Usage by Gender 	           '" 16-16
  Table 16-12.       Total Exposure Time of Performing Task and Product Type Used by Task for	
                    Household Cleaning Products	                          1617
  Table 16-13.       Percentile Rankings for Total Exposure Time in Performing Household Tasks	16-19
  Table 16-14.       Mean Percentile Rankings for Frequency of Performing Household Tasks	        16-20
  Table 16-15.       Mean and Percentile Rankings for Exposure Time Per Event of Performing
                    Household Tasks	                       1621
  Table 16-16.       Total Exposure Time for Ten Product Groups Most Frequently Used for	   "
                    Household Cleaning 	                               \(>2\
  Table 16-17.       Total Exposure Time of Painting Activity of Interior Painters (hours) '.'."	16-22
  Table 16-18.       Exposure Time of Interior Painting Activity/Occasion (hours) and Frequency of      '" '
                    Occasions Spent Painting Per Year	                     1622
  Table 16-19.       Amount of Paint Used  by Interior Painters	'.'.'.'.'.'.'.'.'.'.'.'.	16-22
  Table 16-20.       Number of Respondents Using Cologne, Perfume, Aftershave or Other	
                    Fragrances at Specified Daily Frequencies	            16-23
  Table 16-21.       Number of Respondents Using Any Aerosol Spray Product for Personal Care	
                    Item Such as Deodorant or Hair Spray at Specified Daily Frequencies  	          16-24
  Table 16-22.       Number of Minutes Spent in Activities Working with or Being Near Freshly Applied
                    Paints (minutes/day) 	                         ]6 25
  Table 16-23.        Number of Minutes Spent in Activities Working with or Near Household
                    Cleaning Agents Such as Scouring Powders or Ammonia (minutes/day)	      16-26
 Table 16-24.        Number of Minutes Spent in Activities (at home or elsewhere) Working with
                    or Near Floorwax, Furniture Wax or Shoe Polish (minutes/day)  	            16-27
 Table,16-25.       Number of Minutes Spent in Activities Working with or Being Near Glue  	16 28
 Table 16-26.       Number of Minutes Spent in Activities Working with or Near Solvents, Fumes
                   or Strong Smelling Chemicals (minutes/day)  	        16_29
 Table 16-27.       Number of Minutes Spent in Activities Working with or Near Stain or Spot	
                   Removers (minutes/day)	.,                                    16 30
 Table 16-28.       Number of Minutes  Spent in Activities Working with or Near Gasoline or	
                   Diesel-powered Equipment, Besides Automobiles (minutes/day)	       16-31
 Table 16-29.       Number of Minutes  Spent Using Any Microwave Oven (minutes/day)	16 32
 Table 16-30.       Number of Respondents Using a Humidifier at Home  	..."	" " ' 16.33
 Table 16-31.       Number of Respondents Indicating that Pesticides Were Applied by the Professional  at
                   Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies .           16-34
 1 able 16-32.       Number of Respondents Reporting Pesticides Applied by the Consumer at Home to
                   Eradicate Insects, Rodents, or Other Pests at Specified  Frequencies  	               16-35
 Table 16-33.       Number of Minutes Spent in Activities Working with or Near Pesticides, Including	
                   Bug Sprays or Bug Strips (minutes/day)	            16.36
 Table 16-34.       Amount and Frequency  of Use of Various Cosmetic and Baby Products	16-37
 Table 16-35.       Summary of Consumer Products Use Studies	             	16 40
 Table 16A-1.       Volumes Included in 1992 Simmons Study 	   	,*!  ,
                                                       •'      	*	  10/V- j
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EFH
                                    LIST OF TABLES (continued)
                                                                                              Page No.
                                                                                                 ; 17-3
Table 17-1.        Summary of Residential Volume Distributions	• • •	•	
Tab e 17-2        Average Estimated Volumes of U.S. Residences, by Housing Type and Ownership	  7-4
Table 17-3*.        Residential Volumes in Relation to Household Size and Year of Construction  	17-4
Table 17-4        Dimensional Quantities for Residential Rooms	• • • • -	
Table 17-S'.        Examples of Products and Materials Associated with Floor and Wall Surfaces            ^
                  in Residences	• • •'''';	17 8
Table 17-6        Percent of Residences with Basement, by Census Region and EPA Region	" '  -7~Q
Table 17-?'        Percent of Residences with Certain Foundation Types by Census Region	  /-*
Table 17-8        States Associated with EPA  Regions and Census Regions	- -	
Table 17-9.        Summary of Major Projects  Providing Air Exchange Measurements in the              ^ ^
                  PFTDatabase 		''•'''''' D" '	17 ,9
Table 17-10       Summary Statistics for Air Exchange Rates (air changes per hour-ACH) by Region  ....   /- z
Table 17-11!      Distributions of Residential  Air Exchange Rates by Climate Region and Season	17-13
Table 17-12.      Deposition Rates for Indoor Particles	•	17 15
Table 17-13       Particle Deposition During Normal Activities  	   "
Table 17-14        In-house Water Use Rates (gcd), by Study and Type of Use	   ''
Table 17-15.       Summary of Selected HUD  and Power Authority Water Use Studies	J/-  '
Table 17-16        Showering and Bathing Water Use Characteristics	   '
Table 17-17.       Showering Characteristics for Various Types of Shower Heads	• •  ^^
Table 17-18.       Toilet Water Use Characteristics	•	17_lg
Table 17-19.       Toilet Frequency Use Characteristics	.'' J7"lg
Table 17-20.       Dishwasher Frequency Use Characteristics	^  ^
 Table 17-21.       Dishwasher Water Use Characteristics	
 Table 17-22.       Clothes Washer Frequency  Use Characteristics  	   "
 Table 17-23.       Clothes Washer Water Use  Characteristics	]7_J9
 Table 17-24.       Range of Water Uses for Clothes Washers	^'^
 Table 17-25.       Total Dust Loading for Carpeted Areas  	• •	   "
 Table 17-26       Particle Deposition and Resuspension During Normal Activities	
 Table 17-27.       Dust Mass Loading After One Week Without Vacuum Cleaning	  '-^
 Table 17-28.       Simplified Source Descriptions for Airborne Contaminants	^'^
 Table 17-29.       Volume of Residence Surveys	17_29
 Table 17-30.       Air Exchange Rates Surveys	17]30
 Table 17-31.       Recommendations - Residential Parameters	
 Table 17-32.       Confidence in House Volume Recommendations	   '
 Table 17-33.        Confidence in Air Exchange Rate Recommendations	
                                                                        ^	
                                                                         Exposure Factors Handbook
                                                                                           August1997

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  VOLUME I
                                                                                     EFH
                                           LIST OF FIGURES
                                                                                              Page No.
  Figure 1-1.        Schematic of Dose and Exposure: Oral Route  	                  !  13
  Figure 1-2.        Road Map to Exposure Factor Recommendations ....    	  	i"]7
  Figure 6-1.        Schematic of Dose and Exposure:  Dermal Route	" 6"I2
  Figure 6-2.        SA/BW Distributions for Infants, Adults, and All Ages Combined ".'.'.	6"l 8
  Figure 6-3.        Surface Area Frequency Distribution:  Men and Women                      	6  19
  Figure 7-1.        Weight by Age Percentiles for Boys Aged Birth-36 Months " " '' "	 _
  Figure 7-2.        Weight by Age Percentiles for Girls Aged Birth-36 Months	'.'.'.'.'.'.'.'.'.'.'. 7-3


  VOLUME II

  Figure 10-1.        Seasonal Fish Consumption:  Wisconsin Chippewa, 1990                             1073
  Figure 10-2.        Peak Fish Consumption: Wisconsin Chippewa, 1990  	'.'.'.'.'.'.'.'.'.'.'.'.'"'"' 10-73


  VOLUME HI

  Figure 15-1.        Distribution of Individuals Moving by Type of Move-1991-92                       IS 14
  Figure 17-1.        Elements of Residential Exposure	'.'.'.'.'.'.'.]'.	'  17.1
  Figure 17-2.        Cumulative Frequency Distributions for Residential Volumes from the PFT Data	
                    Base and the U.S. DOE's RECs  	                      173
  Figure 17-3.        Configuration for Residential Forced-air Systems .	17~7
  Figure 17-4.        Idealized Patterns of Particle Deposition Indoors          	17 ,"4
  Figure 17-5.       Air Flows for Multiple-zone Systems                     ""	
Exposure Factors Handbook
August 1997
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EFH
                                              PREFACE
                  The National Center for Environmental Assessment (NCEA) of EPA's Office of Research and
Development (ORD) has prepared this handbook to address factors commonly used in exposure assessments.  This
handbook was first published in 1989 in response to requests from many EPA Program and Regional offices for
additional guidance on how to select values for exposure factors.
                   Several events sparked the efforts to revise the Exposure Factors Handbook. First, since its
publication in 1989, new data have become available.  Second, the Risk Assessment Council issued a memorandum
titled, "Guidance on Risk Characterization for Risk Managers and Risk Assessors," dated February 26, 1992,  which
emphasized the use of multiple descriptors of risk (i.e., measures of central tendency such as average or mean, or
high end), and characterization of individual risk, population risk, important subpopulations.  A new document was
issued titled "Guidance for Risk Characterization," dated February 1995.  This document is an update of the
guidance issued with the 1992 policy. Third, EPA published the revised Guidelines for Exposure Assessment in
 1992.
                   As part of the efforts to revise the handbook, the EPA Risk Assessment Forum sponsored a
 two-day peer involvement workshop which was  conducted during the summer of 1993. The workshop was attended
 by 57  scientists from academia, consulting firms, private industry, the States, and other Federal agencies.  The
 purpose of the workshop was to identify new data sources, to discuss adequacy of the data and the feasibility of
 developing statistical distributions and to establish priorities.
                    As a result of the peer involvement workshop, three new chapters were added to the handbook.
 These chapters are:  Consumer Product Use, Residential Building Characteristics,  and Intake of Grains. This
 document also provides a summary of the available data on consumption of drinking water; consumption of fruits,
 vegetables, beef, dairy products, grain products, and fish;  breast milk intake; soil ingestion; inhalation rates;  skin
 surface area; soil adherence; lifetime; activity patterns;  and body weight.
                    A new draft handbook that incorporated comments from the 1993 workshop was published  for
 peer review in June 1995.  A peer review workshop was held in July 1995 to discuss comments on the draft
 handbook. A new draft of the handbook that addressed comments from the 1995 peer review workshop was
 submitted to the Science Advisory Board (SAB) for review in August 1996. An SAB  workshop meeting was held
  December 19-20, 1996, to discuss the comments of the SAB reviewers.  Comments from the SAB review have been
  incorporated into the current handbook.
  Page
  xxxii
Exposure Factors Handbook
                  August 1997

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                                                                                        EFH
                                               FOREWORD
         The National Center for Environmental Assessment (NCEA) of EPA's Office of Research and Development
 (ORD) has five main functions: (1) providing risk assessment research, methods, and guidelines; (2) performing
 health and ecological assessments; (3) developing, maintaining, and transferring risk assessment information and
 training; (4) helping ORD set research priorities; and (5) developing and maintaining resource support systems for
 NCEA. The activities under each of these functions are supported by and respond to the needs of the various
 program offices.  In relation to the first function, NCEA sponsors projects aimed at developing or refining techniques
 used in exposure assessments.
         This handbook was first published in 1989 to provide statistical data on the various factors used in assessing
 exposure.  This revised version of the handbook provides the up-to-date data on these exposure factors.  The
 recommended values are based solely on our interpretations of the available data. In many situations different values
 may be appropriate to use in consideration of policy, precedent or other factors.
                                                             Michael A. Callahan
                                                             Director
                                                             National Center for Environmental Assessment
                                                             Washington Office
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August 1997        	
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EFH
                         AUTHORS, CONTRIBUTORS, AND REVIEWERS
       The National Center for Environmental Assessment (NCEA), Office of Research and Development was

responsible for the preparation of this handbook.  The original document was prepared by Versar Inc. under EPA
Contract No. 68-02-4254, Work Assignment No. 189. John Schaum, of NCEA-Washington Office, served as the

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

technical assistance and guidance.  Revisions, updates, and additional preparation were provided by Versar Inc.

under Contract Numbers 68-DO-0101, 68-D3-0013, and 68-D5-0051. Russell Kinerson and Greg Kew have served

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

Assignment Manager for the current updated version, providing overall direction, technical assistance, and serving as

contributing author.
AUTHORS

    Patricia Wood
    Linda Phillips
    Aderonke Adenuga
    Mike Koontz
    Harry Rector
    Charles Wilkes
    Maggie Wilson
DESKTOP PUBLISHING

    Susan Perry

WORD PROCESSING

    Valerie Schwartz
GRAPHICS

    Kathy Bowles
    Jennifer Baker
    Exposure Assessment Division
    Versar Inc.
    Springfield, VA
 Page
 xxxiv
                                      Exposure Factors Handbook
                                                       August 1997

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                                                                                      EFH
                                  CONTRIBUTORS AND REVIEWERS
         The following EPA individuals have reviewed and/or have been contributing authors of this document.
         Michael Dellarco
         Robert McGaughy
         Amy Mills
         Jacqueline Moya
         Susan Perl in
 Paul Pinsky
 John Schaum
 Paul White
 Amina Wilkins
 Chieh Wu
         The following individuals were Science Advisory Board Reviewers:

         Members
         Dr. Joan Daisey
         Lawrence Berkley Laboratory
         Berkley, California

         Dr. Paul Bailey
         Mobil Business Resources Corporation
         Paulsboro, New Jersey

         Dr. Robert Hazen
         State of New Jersey Department of
          Environmental Protection and Energy
         Trenton, New Jersey

         Dr. Timothy Larson
         Department of Civil Engineering
         University of Washington
         Seattle, Washington

         Dr. Kai-Shen Liu
         California Department of Health Services
         Berkeley, California
 Dr. Paul Lioy
 Environmental Occupational Health
  Sciences Institute
 Piscataway, New Jersey

 Dr. Maria Morandi
 University of Texas School of Public Health
 Houston, Texas

 Dr. Jonathan M.  Samet
 The Johns Hopkins University
 Baltimore, Maryland

 Mr. Ron White
 American Lung Association
 Washington, D.C.

 Dr. Lauren Zeise
 California Environmental Protection Agency
 Berkeley, California
        Federal Experts

        Dr. Richard Ellis
        U.S. Department of Agriculture
        Washington, D.C.
Ms. Alanna J. Moshfegh
U.S. Department of Agriculture
Washington, D.C.
Exposure Factors Handbook
August 1997	
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EFH
        An earlier draft of this document was peer reviewed by a panel of experts at a peer-review workshop held in
1995. Members of the Peer Review Panel were as follows:
        Edward Avol
        Department of Preventive Medicine
        School of Medicine
        University of Southern California

        James Axley
        School of Architecture
        Yale University

        David Burmaster
        Alceon Corporation

        Steven Colome
        Integrated Environmental Services

        Michael DiNovi
        Chemistry Review Branch
        U.S. Food & Drug Administration

        Dennis Druck
        Environmental Scientist
        Center of Health Promotion & Preventive
          Medicine
        U.S. Army

        J. Mark  Fly
        Department of Forestry, Wildlife, &
          Fisheries
        University of Tennessee

        Larry Gephart
        Exxon Biomedical Sciences, Inc.

        Patricia Guenther
        Beltsville Human Nutrition Research Center
        U.S. Department of Agriculture

        P.J. (Bert) Hakkinen
        Paper Product Development & Paper
          Technology Divisions
        The Proctor & Gamble Company

        Mary Hama
        Beltsville Human Nutrition Research Center
        U.S. Department of Agriculture
Dennis Jones
Agency for Toxic Substances & Disease Registry

John Kissel
Department of Environmental Health
School of Public Health & Community Medicine

Neil Klepeis
Information Systems & Services, Inc.

Andrew Persily
National Institute of Standards & Technologies

Barbara Petersen
Technical Assessment Systems, Inc.

Thomas Phillips
Research Division
California Air Resources Board

Paul Price
ChemRisk

John Risher
Division of Toxicology
The Agency for Toxic Substances & Disease Registry

John Robinson
University of Maryland

Peter Robinson
The Proctor & Gamble Company

P. Barry Ryan
Department of Environmental & Occupational
  Health
Rollins School of Public Health
Emory University

Val Schaeffer
U.S. Consumer Product Safety Commission

Brad Shurdut
 DowElanco

 John Talbott
 Page
 xxxvi
                    Exposure Factors Handbook
                    	August 1997

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                                                                                     EFH
 U.S. Department of Energy
    Frances Vecchio
    Beltsville Human Nutrition Research Center
    U.S. Department of Agriculture
 The following individuals within EPA have reviewed an earlier draft of this document and provided valuable
 comments:
                    OFFICE
      REVIEWERS/CONTRIBUTORS
  Office of Research and Development
  Office of Pollution, Pesticides and Toxic
  Substances
Maurice Berry
Jerry Blancato
Elizabeth Bryan
Curtis Dary
Stan Durkee
Manuel Gomez
Wayne Marchant
Sue Perlin
James Quanckenboss
Glen Rice
Lance Wallace
  Office of Emergency and Remedial Response      Jim Konz
Pat Kennedy
Cathy Fehrenbacker
  Office of Water

  Office of Air Quality Planning and Standards
  EPA Regions
Denis Borum
Helen Jacobs

Warren Peters

Steve Ehlers - Reg. VI
Maria Martinez - Reg. VI
Mike Morton - Reg. VI
Jeffrey Yurk - Reg. VI
Youngmoo Kim - Reg. VI
        In addition, the National Exposure Research Laboratory (NERL) of the Office of Research and
 Development of EPA made an important contribution to this handbook by conducting additional analyses of the
 National Human Activity Pattern Survey (NHAPS) data.  EPA input to the NHAPS data analysis came from Karen
 A. Hammerstrom and Jacqueline Moya from NCEA-Washington Office; William C. Nelson from NERL-RTP, and
 Stephen C. Hern, Joseph V. Behar (retired), and William H. Englemann from NERL-Las Vegas.

        The EPA Office of Water made an important contribution by conducting an analysis of the USDA
 Continuing Survey of Food Intakes by Individual (CSFII) data. They provided fish intake rates for the general
 population. The analysis was conducted under the direction of Helen Jacobs from the Office of Water.
Exposure Factors Handbook
August 1997	
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 Volume I - General Factors

 Chapter 1 - Introduction
                                                        EFH
 1.    INTRODUCTION
 1.1.  PURPOSE
       The purpose of the Exposure Factors Handbook is
 to: (1)  summarize  data on human  behaviors  and
 characteristics which affect exposure to environmental
 contaminants, and (2) recommend values to use for these
 factors.  These recommendations are not legally binding
 on any EPA program  and  should be interpreted as
 suggestions  which  program offices  or  individual
 exposure assessors can consider and modify as needed.
 Most of these factors are best quantified on a site or
 situation-specific  basis.  The handbook has strived to
 include  full  discussions  of the issues which assessors
 should consider hi deciding how to use these data and
 recommendations. The handbook is intended to serve as
 a support document to EPA's Guidelines for Exposure
 Assessment (U.S. EPA, 1992a).  The Guidelines were
 developed to promote consistency  among  the various
 exposure assessment activities that are-carried out by the
 various EPA program offices. This handbook assists in
 this goal by providing a consistent set of exposure factors
 to calculate dose.
 1.2.   INTENDED
       AUDIENCE
       The  Exposure  Factors
 Handbook  is   addressed   to
 exposure assessors inside  the
 Agency as well as outside, who
 need to obtain data on standard
 factors  needed  to   calculate
 human   exposure   to   toxic
 chemicals.
Purpose

• Summarize data on human
  behaviors and characteristics
  affecting exposure

• Recommend exposure factor
  values
 1.3.   BACKGROUND
       This handbook is the update of an earlier version
 prepared in 1989.  Revisions have been made in the
 following areas:

       •  addition of drinking water rates for children;
       •  changes in soil ingestion rates for children;
       •  addition of soil ingestion rates for adults;
       •  addition of tapwater consumption for adults
          and children;
       •  addition of mean daily intake of food class
          and subclass by region, age and per capita
          rates;
                               addition of mean moisture content of selected
                               fruits, vegetables, grains,  fish, meat, and
                               dairy products;
                               addition of food intake by class in dry weight
                               per kg of body weight per day;
                               update of homegrown food intake;
                               expansion of data hi the dermal chapter;
                               update of fish intake data;
                               expansion of data for time spent at residence;
                               update of body weight data;
                               addition of body weight data for infants;
                               update of population mobility data;
                               addition of new data for average time spent in
                               different locations and various microenviron-
                               ments;
                               addition of data for occupational mobility;
                               addition of breast milk ingestion;
                               addition of consumer product use; and
                               addition of reference  residence factors.
Variation Among Studies
      This handbook is a compilation of available data
                       from a  variety  of  different
                       sources.     With  very  few
                       exceptions, the data presented
                       are   the   analyses   of  the
                       individual study authors. Since
                       the  studies  included  in  this
                       handbook varied in terms of
                       their objectives, design, scope,
                       presentation of results, etc., the
                       level  of  detail, statistics,  and
                       terminology  may vary  from
                       study to study and from factor
                      to factor.  For example, some
authors  used geometric means to present  their results,
while others used arithmetic  means or  distributions.
Authors have sometimes used different terms to describe
the same racial populations.  Within the  constraint of
presenting the original material as accurately as possible,
EPA has made  an effort to present discussions  and
results in a consistent manner.  Further, the strengths and
limitations of each study are  discussed  to provide the
reader with a better understanding of the  uncertainties
associated with the values derived from the study.
                     1.3.1.     Selection of Studies for the Handbook
                           Information in this handbook has been summarized
                     from studies documented in the scientific literature and
Exposure Factors Handbook
August 1997	
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                                                                   1-1

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                                                                           Volume I - General Factors
                                                                   Chapter 1 - Introduction
other available sources. Studies were chosen that were
seen as useful and appropriate for estimating exposure
factors.  The handbook contains summaries of selected
studies published through August 30, 1997.

General Considerations
      Many scientific studies were reviewed for possible
inclusion in this handbook.  Studies were selected based
on the following considerations:

      •    Level of peer review:  Studies were selected
           predominantly   from  the  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.

•   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.
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                                                       EFH
       •    Minimal (or defined) bias in study design:
           Studies were sought that were designed with
           minimal bias,  or at least if biases were
           suspected to be present, the direction of the
           bias (i.e., an over or under estimate  of the
           parameter) was either stated or apparent from
           the study design.

       •    Minimal (or defined) uncertainty in the data:
           Studies were sought with minimal uncertainty
           in the data,  which was judged by evaluating
           all the considerations listed above. At least,
           studies  were  preferred  that  identified
           uncertainties, such as those due to inherent
           variability in environmental and exposure-
           related parameters or possible measurement
           error.   Studies  that documented  Quality
           Assurance/Quality Control measures were
           preferable.
 Key versus relevant studies
      Certain studies described
 in this handbook are designated
 as  "key,"  that is,  the  most
 useful for deriving exposure
 factors.   The   recommended
 values for most exposure factors
 are based on the results of the
 key  studies.  Other studies are
 designated "relevant," meaning
 applicable or pertinent, but not
 necessarily the  most important.  This distinction was
 made on the strength of the attributes listed in the
 "General Considerations." For example, in Chapter 14
 of Volume III,  one set  of studies is  deemed to best
 address the attributes listed and is designated as "key."
 Other applicable studies, including foreign data, believed
 to have  value  to handbook users, but having fewer
 attributes, are designated  "relevant."

 1.3.2.    Using the Handbook in an Exposure
          Assessment
      Some of the steps for performing an exposure
 assessment are (1)  determining  the pathways  of
 exposure, (2)  identifying the environmental media which
 transports  the   contaminant,  (3)  determining   the
 contaminant concentration, (4) determining the exposure
 time, frequency, and duration, and (5)  identifying the
 exposed  population.  Many of the issues related to
Key vs. Relevant Studies

• Key studies used to derive
  recommendations

• Relevant studies included to provide
characterizing exposure from selected exposure pathways
have been addressed in a number of existing EPA
guidance documents.  These include, but are not limited
to the following:

      •   Guidelines for Exposure Assessment (U.S.
          EPA 1992a);
      •   Dermal Exposure Assessment:   Principles
          and Applications (U.S. EPA 1992b);
      •   Methodology  for Assessing Health Risks
          Associated with  Indirect  Exposure   to
          Combustor Emissions (U.S. EPA, 1990);
      •   Risk Assessment  Guidance  for Superfund
          (U.S. EPA, 1989);
      •   Estimating  Exposures   to   Dioxin-Like
          Compounds (U.S. EPA, 1994);
      •   Superfund  Exposure  Assessment  Manual
          (U.S. EPA, 1988a);
      •   Selection Criteria for Mathematical Models
          Used hi Exposure Assessments (U.S. EPA
                         1988b);
                         • Selection  Criteria   for
                           Mathematical   Models
                           Used    in    Exposure
                           Assessments (U.S. EPA
                            1987);
                         • Standard Scenarios  for
                           Estimating Exposure to
                           Chemical    Substances
                           During Use of Consumer
                           Products   (U.S.  EPA
                            1986a);
   •  Pesticide Assessment Guidelines, Subdivisions K
      and U (U.S. EPA, 1984, 1986b); and
   •  Methods  for  Assessing Exposure to Chemical
      Substances, Volumes  1-13  (U.S. EPA, 1983-
      1989).

These documents may serve as valuable information
resources to assist in the assessment of exposure.  The
reader is encouraged to refer to them for more  detailed
discussion.
      In addition to the references listed above,  this
handbook discusses the recommendations provided by the
American Industrial Health Council (AIHC) - Exposure
Factors Sourcebook  (May 1994) for some of the major
exposure factors.  The AIHC Sourcebook summarizes
and evaluates statistical data for various exposure factors
used hi risk assessments.  Probability distributions  for
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                                                Volume I - General Factors

                                                   Chapter 1 - Introduction
specific exposure factors were derived from the available
scientific literature using ©Risk simulation software.
Each factor is described by a specific term, such as
lognormal, normal,  cumulative type, or  triangular.
Other distributions included Weibull, beta logistic, and
gamma. Unlike this handbook, however, the Sourcebook
does not provide a description and evaluation of every
study available on each exposure factor.
      Most of the data presented in this handbook are
derived from studies  that  targeted  (1) the  general
population (e.g., USDA food consumptin  surveys); and
(2) a sample population from a specific area or group
(e.g., Calabrese's et al. (1989) soil ingestion study using
children from the Amherst, Massachusetts, area).  Due
to unique activity patterns, preferences,  practices and
biological  differences,  various  segments   of  the
population may experience exposures that are different
from  those  of  the
general    population,
which, in many cases,
may  be  greater. It  is
necessary for risk or
exposure     assessors
characterizing a diverse
population,  to identify
and enumerate  certain
groups    within  the
general population who
are at risk for greater
contaminant  exposures
or exhibit a heightened
sensitivity to particular
chemicals. For  further
guidance  on addressing susceptible populations,  it is
recommended to consult the EPA,  National Center for
Environmental Assessment document Socio-demographic
Data Used for Identifying Potentially Highly Exposed
Subpopulations (to be released as a final document in the
Fall of 1997).
      Most users  of the handbook will  be preparing
estimates of exposure  which are to be combined  with
dose-response factors  to estimate  risk.  Some of the
exposure factors (e.g., life time, body weight) presented
in  this document  are also used hi generating dose-
response relationships.  In order to develop risk estimates
properly, assessors must use dose-response relationships
in  a  manner  consistent with  exposure  conditions.
Although, it is  beyond the  scope of this document to
explain in detail how assessors should address this issue,
                             a discussion (see Appendix A of this chapter) has been
                             included which describes how dose-response factors can
                             be modified to be consistent with the exposure factors for
                             a population of interest. This should serve as a guide for
                             when this issue is a concern.

                             1.3.3.     Approach Used to Develop
                                       Recommendations for Exposure Factors
                                   As  discussed  above, EPA  first  reviewed  all
                             literature pertaining to a factor and determined relevant
                             and key studies. The key studies were used to derive
                             recommendations for the values  of each factor.  The
                             recommended values were derived solely from EPA's
                             interpretation of the available data. Different values may
                             be appropriate for the user to select in consideration of
                             policy, precedent, strategy, or other factors such as site-
                             specific information.  EPA's procedure for developing
                                                           recommendations was
                                                           as follows:
Recommendations and Confidence Ratings

• Recommendations based on data from single or
  multiple key studies

• Variability and limitation of the data evaluated

• Recommendations rated as low, medium, and
  high confidence
1.   Key studies  were
    evaluated in terms
    of  both  quality
    and relevance to
    specific  popula-
    tions (general U.
    S. population, age
    groups,  gender,
    etc.).  The criteria
    for  assessing the
    quality of studies
    is  described  in
    Section 1.3.1.
                             2.  If only one  study  was  classified as key for a
                                 particular factor, the mean value from that study
                                 was selected as the recommended central value for
                                 that population. If there were multiple key studies,
                                 all  with reasonably equal quality,  relevance, and
                                 study design information were available, a weighted
                                 mean (if appropriate, considering sample size and
                                 other statistical factors) of the studies were chosen
                                 as the recommended mean value.  If the key studies
                                 were judged to be unequal in quality, relevance, or
                                 study design, the range of means were presented and
                                 the user of this handbook must employ judgment in
                                 selecting  the most appropriate  value  for  the
                                 population of interest.  In cases where the national
                                 population was  of  interest,  the  mid-point of the
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                                    EFH
     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 hi 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 hi 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 1.3.1.  Clearly this is a continuum
     from low to  high  and judgment was used to
     determine these ratings. Recommendations given in
     this handbook are  accompanied by a discussion of
     the rationale for their rating.

 Table  1-2  summarizes EPA's recommendations  and
 confidence ratings for the various exposure factors.
       It is important to note  that the study elements
 listed  in Table 1-1 do not have the same weight when
 arriving at the overall confidence rating for the various
 exposure factors. The  relative weight of each of these
 elements depend on the exposure factor of interest.
 Also,  the relative weights given to the elements for the
 various factors  were  subjective and  based  on  the
 professional judgement  of the authors of this handbook.
 In general, most studies would rank high with regard to
 "level of peer review," "accessibility,"  "focus  on the
 factor of interest,"  and "data pertinent to the U.S."
 These  elements are important for the study to be included
 in this handbook.   However, a high score of these
 elements does not necessarily translate into a high overall
 score.  Other elements in Table 1-1 were also examined
 to determine the overall score.   For  example,  the
 adequacy  of  data  collection period  may be  more
 important  when determining usual intake of foods in a
 population. On the other hand, it is not as important for
 factors where long-term variability may be small such as
 tapwater intake.  In the case of tapwater intake, the
 currency of the data was a critical element in determining
 the final rating. In addition, some exposure factors are
 more easily measured than others.  For example, soil
 ingestion by children is estimated by measuring,  in the
 feces,  the levels of certain elements found in soil.  Body
 weight,  however, can be measured directly and it is,
 therefore,  a  more reliable  measurement.   This  is
 reflected hi the confidence rating given to both of these
 factors.  In general, the better the methodology used to
 measure the exposure factor, the higher the confidence
 in the value.

 1.3.4.     Characterizing Variability
       This document attempts to characterize variability
 of each of the  factors. Variability is characterized in one
 or  more of three ways:  (1)  as tables  with  various
 percentiles or  ranges  of  values;  (2)  as  analytical
 distributions with  specified parameters; and/or (3) as a
 qualitative discussion.   Analyses to  fit  standard or
 parametric distributions (e.g., normal, lognormal) to the
 exposure data  have not been performed by the authors of
 this handbook, but have  been reproduced  in this
 document  wherever they were found in the literature.
 Recommendations on the use of these distributions are
 made where appropriate based on the adequacy of the
 supporting data.   The list of exposure factors and the
 way  that  variability  has  been  characterized  (i.e.,
 average, upper percentiles,  multiple percentiles,  fitted
 distribution) are presented in Table 1-3.  The term upper
 percentile  is  used 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 hi the Exposure Guidelines
within the context  of risk descriptors and not individual
exopusure factors.  For example,  the Guidelines stated
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                                                 Volume I - General Factors

                                                     Chapter 1 - Introduction
                             Table 1-1.  Considerations Used to Rate Confidence in Recommended Values
 CONSIDERATIONS
                                        HIGH CONFIDENCE
                                                                                    LOW CONFIDENCE
 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 sizes




 Representativeness of the population



 Variability in the population


  Lack of bias in study design
  (a high rating is desirable)

 Response rates
    In-person interviews
    Telephone interviews
    Mail surveys

  Measurement error


  Other Elements

  Number of studies

  Agreement between researchers
                                           The studies received limited peer review.
The studies received high level of peer
review (e.g., they appear in peer review
journals).
The studies are widely available to the public.


The results can be reproduced or
methodology can be followed and evaluated.


The studies focused on the exposure factor of
interest.
The studies focused on die U.S. population.


The studies analyzed primary data.

The data were published after 1990.

The study design  captures the measurement
of interest (e.g., usual consumption patterns
of a population).

The studies used the best methodology
available to capture the measurement of
interest.
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.
                                           The studies are difficult to obtain (e.g., draft
                                           reports, unpublished data).

                                           The results cannot be reproduced, the
                                           methodology is hard to follow, and the
                                           author(s) cannot be located.

                                           The purpose of the studies was to characterize
                                           a related factor.
                                           The studies focused on populations outside the
                                           U.S.
                                           The studies are based on secondary sources.

                                           The data were published before 1980.

                                           The study design does not very accurately
                                           capture the measurement of interest.


                                           There are serious limitations with the approach
                                           used.
The study population is the same as
population of interest.

The studies characterized variability in the
population studied.

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 dian 80 percent.
The respnose rate is greater than 70 percent.

The study design minimizes measurement
errors.
The number of studies is greater than 3.

The results of studies from different
researchers are in agreement.	
                                             The study population is very different from the
                                             population of interest.3

                                             The characterization of variability is limited.


                                             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.

                                             Uncertainties with the data exist due to
                                             measurement error.
                                             The number of studies is 1.

                                             The results of studies from different
                                             researchers are in disagreement.
  " Differences include age, sex, race, income, or other demographic parameters.
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                                                                    EFH
                           Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings
          EXPOSURE FACTOR
                                                      RECOMMENDATION
                                                                                                CONFIDENCE RATING
   Drinking water intake rate




   Total fruit intake rate



   Total vegetable intake rate



   Total meat intake rate



   Total dairy intake rate



   Grain intake


   Breast milk intake rate

   Fish intake rate
 21 ml/kg-day/1.4 L/day (average)
 34 ml/kg-day/2.3 L/day (90th percentile)
 Percentiles and distribution also included
 Means and percentiles also included for pregnant and
 lactating women
 3.4 g/kg-day ( per capita average)
 12.4 g/kg-day (per capita 95th percentile)
 Percentiles also included
 Means presented for individual fruits
 4.3 g/kg-day (per capita average)
 10 g/kg-day (per capita 95th percentile)
 Percentiles also included
 Means presented for individual vegetables
 2.1 g/kg-day (per capita average)
 5.1 g/kg-day (per capita 95th percentile)
 Percentiles also included
 Percentiles also presented for individual meats
 8.0 g/kg-day (per capita average)
 29.7 g/kg-day (per capita 95th percentile)
 Percentiles also included
 Means presented for individual dairy products
 4.1 g/kg-day (per capita average)
 10.8 g/kg-day (per capita 95th percentile)
 Percentiles also included
 742 ml/day (average)
 1,033 ml/day (upper percentile)
 General Population
 20.1 g/day (total fish) average
 14.1 g/day (marine) average
 6.0 g/day (freshwater/estuarine)average
 63 g/day (total fish) 95th percentile long-term
 Percentiles also included
 Serving size
 129 g (average)
 326 g (95th percentile)
 Recreational marine anglers
 2-7 g/day (finfish only)
 Recreational freshwater
 8 g/day (average)
25 g/day (95th percentile)
 Native American Subsistence Population
70 g/day (average)
 170 g/dav (95th percentile)	
            Medium
            Medium
            Medium
             Low
            Medium
             Low
            Medium
             Low
            Medium
             Low
             High
Lowjn long-term upper percentiles

           Medium
           Medium

             High
             High
             High
           Medium

             High
             High

           Medium

           Medium
           Medium

           Medium
             Low
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                                                Volume I - General Factors

                                                    Chapter 1  - Introduction
                    Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings (continued)
         EXPOSURE FACTOR
                                                     RECOMMENDATION
                                                                                               CONFIDENCE RATING
 Home produced food intake
  Inhalation rate
  Surface area
  Soil adherence
  Soil ingestion rate
  Life expectancy
  Body weight for adults

  Body weights for children

  Body weights for infants (birth to 6
Total Fruits
2.7 g/kg-day (consumer only average)
11.1 g/kg-day (consumer only 95th percentile)
Percentiles also included
Total vegetables
2.1 g/kg-day ( consumer only average)
7.5 g/kg-day (consumer only 95th percentile)
Percentiles also included
Total meats
2.2 g/kg-day (consumer only average)
6.8 g/kg-day (consumer only 95th percentile)
Percentiles also included
Total dairy products
14 g/kg-day (consumer only average)
44 g/kg-day (consumer only 95th percentile)
Percentiles also included
Children (<1 year)
4.5 nvVday (average)
Children (1-12 years)
8.7 nrVday (average)
Adult Females
 11.3 m3/day (average)
Adult Males
 15.2 m3/day (average)
Water contact (bathing and swimming)
Use total body surface area for children in Tables 6-6
through 6-8; for adults use Tables 6-2 through 6-4
 (percentiles are included)
Soil contact (outdoor activities)
 Use whole body part area based on Table 6-6 through 6-
 8 for children and 6-2 through 6-4 for adults (percentiles
 are included)
 Use values presented in Table 6-16 depending on activity
 and body part
 (central estimates only)
 Children
 100 mg/day (average)
 400 mg/day (upper percentile)
 Adults
 50 mg/day (average)
 Pica child
 10 g/day
 75 years
 71.8kg
 Percentiles also presented in tables 7-4 and 7-5
 Use values presented in Tables 7-6 and 7-7  (mean and
 percentiles)
 Use values presented in Table 7-1 (percentiles)
Medium (for means and short-term
         distributions)
 Low (for long-term distributions)
             High

             High

             High

             High

             High



             High



              Low


            Medium


              Low

              Low

              High
              High

              High

              High
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Table 1-2.
EXPOSURE FACTOR
Showering/Bathing








Swimming




Time indoors






Time outdoors






Time spent inside vehicle

Occupational tenure
Population mobility

Residence volume
Residential air exchange

Summary of Exposure Factor Recommendations and
RECOMMENDATION
Showering time
10 min/day (average)
35 min/day (95th percentile)
(percentiles are also included)
Bathing rime
20 min/event (median)
45 min/event (90th percentile)
Bathing/showering frequency
1 shower event/day
Frequency
1 event/month
Duration
60 min/event (median)
180 min/event (90th percentile)
Children (ages 3-11)
19 hr/day (weekdays)
17 hr/day (weekends)
Adults (ases 12 and older)
21 hr/day
Residential
16.4 hrs/day
Children (ages 3-11)
5 hr/day (weekdays)
7 hr/day (weekends)
Adults
1.5 hr/day
Residential
2 hrs/day
Adults
1 hr 20 min/day
6.6 years (16 years old and older)
9 years (average)
30 years (95th percentile)
369 m3 (average)
217 m3 (conservative)
0.45 (median)
0.18 (conservative)

CONFIDENCE RATING
High



High


High

High

High


Medium


Medium

High

Medium


Medium

High


Medium
High
Medium
Medium
Medium
Medium
Low
	 	 Low 	
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                                                                             Volume I - General Factors

                                                                                Chapter 1 - Introduction
                               Table 1-3.  Characterization of Variability in Exposure Factors
 xposure Factors
                                    Average
                                                   Upper percentile
                                                                         Multiple Percentiles     Fitted Distributions
 Tinking water intake rate

Total fruits and total vegetables intake rate


 ndividual fruits and individual vegetables
 ntake rate
Total meats and dairy products intake rate



 ndividual meats and dairy products intake
 ate
Grains intake

Breast milk intake rate

 Fish intake rate for general population,
 ecreational marine, recreational
 reshwater, and native american

 Icrving size for fish

 Homeproduced food intake rates

 Soil intake rate
 Inhalation rate
 Surface area
 Soil adherence
 Life expectancy
 Body weight
 Time indoors
 Time outdoors
 Showering time
 Occupational tenure
 Population mobility
 Residence volume
 Residential air exchange
                                             Qualitative discussion for long-
                                             term
                                              Qualitative discussion for long-
                                              term
                                                         /
                                              Qualitative discussion for long-
                                              term
 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
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 Volume I - General Factors
 Chapter 1 - Introduction
                                                                                           EFH
                         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 assump-
           tion 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 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 - examples include: soil
               ingestion by adults;
             ~ data were collected over a short time
               period and may not represent long term
               trends (the respondent usual behavior) -
               examples include:  food consumption
               surveys; activity pattern data;
             — data  are not representative  of  the
               population of interest because  sample
               size was small or the population studied
               was selected from a local area and was
               therefore not representative of the area
               of  interest -  examples  include:  soil
               ingestion by children; and
            — ranges for a key variable are uncertain
               due to  experimental  error  or other
               limitations in the  study  design  or
               methodology - examples include:  soil
               ingestion by children.

1.4.  GENERAL EQUATION FOR
      CALCULATING DOSE
      The definition of exposure as used in the Exposure
Guidelines  (U.S.  EPA,  1992a) is  "condition of a
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                                                                          Volume I - General Factors
                                                                             Chapter 1 - Introduction
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 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 (D^) over body weight and
an averaging time.
  ADD,
      'pot
     Total Potential Dose
Body Weight x Averaging Time
                                          (Eqn. 1-1)
      For cancer effects, where the biological response
is usually described in terms of lifetime probabilities,
even though exposure does not occur over the entire
lifetime, doses are often presented as lifetime average
daily doses (LADDs). The LADD takes the form of the
Equation  1-1  with lifetime  replacing averaging time.
The LADD is a very common term used in carcinogen
risk assessment where linear non-threshold models are
employed.
      The total exposure can be expressed as follows:
    Total Potential Dose = C x IR x ED
                                         (Eqn. 172)
  Where:
          C = Contaminant Concentration
          IR = Intake Rate
          ED = Exposure Duration
      Contaminant concentration is the concentration of
the contaminant in the medium (air,  food, soil, etc.)
contacting the body and has units of mass/volume or
mass/mass.
      The intake rate refers to the rates of inhalation,
ingestion, and dermal contact depending on the route of
exposure.  For ingestion, the intake rate is simply the
amount of food containing the contaminant of interest
that an individual ingests during some specific time
period (units of mass/tune).  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 tune a person lives hi an
area, frequency of bathing, time  spent indoors versus
outdoors, etc. all  affect the exposure duration. The
Activity Factors Chapter (Volume III,  Chapter 15) gives
some examples of population behavior patterns, which
may be useful for estimating exposure durations to be
used in the exposure calculations.
      When the above parameter values remain constant
over time, they are substituted directly into the exposure
equation.  When they change with time,  a summation
approach is needed to calculate exposure.  In either case,
the exposure duration is the length  of time exposure
occurs at the concentration and intake rate specified by
the other parameters in the equation.
      Dose  can be expressed  as  a total amount (with
units of mass,  e.g., mg) or as  a dose rate in terms of
mass/time (e.g.,  mg/day), or  as  a rate normalized to
body mass (e.g., with units of mg of chemical per kg of
body weight per day  (mg/kg-day)).  The LADD  is
usually expressed in  terms  of mg/kg-day or  other
mass/mass-time units.
      In most cases (inhalation and ingestion exposure)
the dose-response parameters for carcinogen risks have
been adjusted for the  difference  hi  absorption across
body barriers between humans and the  experimental
annuals 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
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                                                              Exposure Factors Handbook
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 Volume I - General Factors

 Chapter 1 - Introduction
                                   EFH
                                                                       Biologically
                                                                       Effective
                                                                       Dose
    Exposure
    Chemical
                                                                                        Effect
                 Mouth
                 Intake
  Source: U.S. EPA, 1992a
                                                G.I. Tract
                                                 Uptake

                             Figure 1-1.  Schematic of Dose and Exposure: Oral Route
 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 ingcstion, 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 (hi Equation 1-1) the
average weight of the exposed population during the time
when the exposure actually occurs.  If the exposure
occurs continuously throughout an individual's life or
only during the adult ages, using an adult weight of 71.8
kg  should  provide sufficient accuracy.   If the body
weight of the individuals in the population whose risk is
being evaluated is non-standard in some way, such as for
children or for first-generation immigrants who may be
smaller than the national population, and if reasonable
values are not available in the literature, then a model of
intake as a function of body weight must be used.  One
such model is discussed in Appendix 1A of this chapter.
Some of the parameters (primarily concentrations) used
in estimating exposure are exclusively site specific, and
therefore default recommendations could not be used.
      The  food  ingestion rate  values provided  in this
handbook  are generally  expressed  as  "as consumed"
since this  is the fashion in which data are reported  by
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                                                                           Volume I - General Factors
                                                                              Chapter 1 - Introduction
survey respondents.  This  is of importance  because
concentration data to be used in the dose equation are
generally measured in uncooked food samples.  In most
situations, the only practical choice is to use the "as
consumed"   ingestion   rate   and  the   uncooked
concentration.  However, it should be recognized that
cooking generally results in some reductions in weight
(e.g., loss of moisture), and that if  the mass of the
contaminant  in  the  food remains  constant,  then the
concentration of the contaminant in the cooked food item
will increase. Therefore, if the "as consumed" ingestion
rate and the uncooked concentration are used in the dose
equation,  dose may  be  underestimated.   On the other
hand,  cooking  may cause  a  reduction in  mass  of
contaminant and other ingredients such that the overall
concentration  of  contaminant   does   not   change
significantly.  In this case, combining cooked ingestion
rates  and uncooked concentration will provide  an
appropriate estimate of dose.  Ideally, food concentration
data should be adjusted to  account for  changes after
cooking,  then the  "as  consumed" intake rates  are
appropriate.  In the absence of data, it is reasonable to
assume that  no change in  contaminant  concentration
occurs after cooking. Except for general population fish
consumption and home produced foods, uncooked intake
rate data were not available  for  presention  in  this
handbook.   Data  on  the  general  population fish
consumption have  been presented in this handbook
(Section 10.2) in both  "as  consumed"  and uncooked
basis.  It is important for the assessor to be aware of
these issues and choose intake rate data that best matches
the concentration data that is being used.
      The link between the intake rate  value and the
exposure   duration value  is  a common  source  of
confusion in defining exposure scenarios.  It is important
to define the duration estimate so that it is consistent with
the intake rate:

       •   The intake rate can be based on an individual
          event, such as  129 g of fish eaten per meal
          (U.S. EPA,  1996).  The duration should be
          based on the number of events or, in this
          case, meals.

       •   The intake rate also can be based on a long-
          term average, such as 10 g/day.  In this case
          the duration should be based on the total time
          interval over which the exposure occurs.
      The objective is to define the terms so that when
multiplied, they give the appropriate estimate of mass of
contaminant contacted.  This can be accomplished by
basing the intake rate on either a long-term  average
(chronic exposure) or an event (acute exposure) basis, as
long as the duration value  is selected appropriately.
Consider the case in which a person eats a  129-g fish
meal  approximately  five times per month (long-term
average is 21.5 g/day) for 30 years;  or 21.5 g/day of fish
every day for 30 years.
  (129 g/meal)(5 meals/mo)(mo/30 d)(365 d/yr)(30 yrs) = 235,425 g

  (21.5 g/day)(365 d/yr)(30 yrs) = 235,425 g
Thus, a frequency of either 60 meals/year or a duration
of 365 days/year could be used as long as it is matched
with the appropriate intake rate.

1.5.  RESEARCH NEEDS
      In an earlier draft of this handbook, reviewers
were asked to identify factors or areas where  further
research is needed. The following list is a compilation
of  areas for future research  identified by the  peer
reviewers and authors of this document:

      •  The  data  and information available  with
          respect to occupational exposures are  quite
          limited.   Efforts need  to be directed to
          identify  data or references on occupational
          exposure.

      •  Further  research  is necessary  to refine
          estimates of fish consumption, particularly by
          subpopulations of subsistence fishermen.

      •  Research is needed to  better estimate soil
          intake rates, particularly how to extrapolate
          short-term data to chronic exposures.  Data
          on soil intake rates by adults are very limited.
          Research in this area is also recommended.
          Research is also needed to refine methods to
          calculate soil intake rate (i.e., inconsistencies
          among tracers and input/output misalignment
          errors indicate a fundamental problem with
          the methods).  Research is also needed to
          obtain more  data to better  estimate soil
          adherence.
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 Volume I - General Factors
 Chapter 1 - Introduction
                                                                                        EFH
       •   In cases where several  studies of  equal
           quality and data collection procedures  are
           available for an exposure factor, procedures
           need to be developed to combine the data in
           order to create a single distribution of likely
           values for that factor.

       •   Reviewers recommended that the handbook
           be made available in CD ROM and that the
           data presented be made available in a format
           that will allow the users to conduct their own
           analysis.    The intent  is to  provide a
           comprehensive factors tool with interactive
           menu to guide users to areas of interest, word
           searching features, and data base files.

       •   Reviewers recommended  that EPA derive
           distribution functions using the empirical data
           for the various exposure factors to be used in
           Monte Carlo or other probabilistic analysis.

       •   Research is needed to derive a methodology
           to extrapolate from short-term data to long-
           term or chronic exposures.

       •   Reviewers  recommended that the consumer
           products chapter be expanded to include more
           products. A comprehensive literature search
           needs to be conducted to investigate  other
           sources of data.

       •   Breastmilk intake.

       •   More recent data on tapwater intake.

       •   SAB recommended analysis of 1994 and 1995
           CSFII data.

 1.6.   ORGANIZATION
       The handbook is organized into three volumes as
 follows:

       Volume I - General Factors

       Chapter 1   Provides the overall introduction to
                  the handbook

       Chapter 2   Presents an  analysis of uncertainty
                  and discusses methods that can be
            used  to  evaluate and  present the
            uncertainty associated with exposure
            scenario estimates.

 Chapter 3   Provides  factors  for  estimating
            human exposure through ingestion
            of water.

 Chapter 4   Provides  factors  for  estimating
            exposure through ingestion of soil.

 Chapter 5   Provides  factors  for  estimating
            exposure as a result of inhalation of
            vapors and particulates.

 Chapter 6   Presents   factors  for  estimating
            dermal exposure to environmental
            contaminants that come in  contact
            with the skin.

 Chapter 7   Provides data on body weight.

 Chapter 8   Provides data on life expectancy.

 Volume n - Ingestion Factors
Chapter 9   Provides  factors  for  estimating
            exposure through ingestion of fruits
            and vegetables.

Chapter 10  Provides  factors  for  estimating
            exposure through ingestion of fish.

Chapter 11  Provides  factors  for  estimating
            exposure through ingestion of meats
            and dairy products.

Chapter 12  Presents  data   for   estimating
            exposure through ingestion of grain
            products.

Chapter 13  Presents  factors   for  estimating
            exposure through ingestion of home
            produced food.

Chapter 14  Presents  data   for   estimating
            exposure through ingestion of breast
            milk.
Exposure Factors Handbook
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EFH
                                                                      Volume I - General Factors
                                                                          Chapter 1 - Introduction
      Volume HI - Activity Factors

      Chapter 15  Presents  data  on activity factors
                 (activity    patterns,    population
                 mobility,    and     occupational
                 mobility).

      Chapter 16  Presents data on consumer product
                 use.

      Chapter 17  Presents factors used in estimating
                 residential exposures.

      Figure 1-2 provides a roadmap  to assist users of
this handbook in locating recommended values and
confidence  ratings  for the various exposure factors
presented hi these chapters.  A glossary is provided at
the end of Volume III.

1.7.   REFERENCES FOR CHAPTER 1

A1HC. (1994) Exposure factors sourcebook.
    Washington, DC:  American Industrial Health
    Council.
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:
    Van Nostrand Reirihold.
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.  (1996) Daily-average per capita fish
    consumption estimates based on the combined
    1989, 1990, and 1999 continuing survey of food
    intakes by individuals (CSFII) 1989-91 data.
    Volumes I and II.  Preliminary Draft Report.
    Washington, DC:  Office of Water.
Page
1-16
                 Exposure Factors Handbook
                 	August 1997

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Volume I - General Factors

Appendix 1A	_^
EFH
                                APPENDIX 1A

           RISK CALCULATIONS USING EXPOSURE FACTORS HANDBOOK DATA
                  AND DOSE-RESPONSE INFORMATION FROM THE
                  INTEGRATED RISK INFORMATION SYSTEM (IRIS)
Exposure Factors Handbook
August 1997	
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       1A-1

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Volume I - General Factors

Appendix 1A	
EFH
                                             APPENDIX 1A
                 RISK CALCULATIONS USING EXPOSURE FACTORS HANDBOOK
                      DATA AND DOSE-RESPONSE INFORMATION FROM IRIS
1.  INTRODUCTION
    When calculating risk estimates for a specific population, whether the entire national population or some sub-
population, the exposure information (either from this handbook or from other data) must be combined with dose-
response information. The latter typically comes from the IRIS data base, which summarizes toxicity data for each
agent separately.  Care must be taken that the assumptions about population parameters in the dose-response analysis
are consistent with the population parameters used in the exposure analysis. This Appendix discusses procedures for
insuring this consistency.

    In the IRIS derivation of threshold based dose-response relationships (U.S. EPA, 1996), such as the RfD and the
RfCs based on adverse systemic effects, there has generally been no explicit use of human exposure factors. In these
cases the numerical value of the RfD and RfC comes directly from animal dosing experiments (and occasionally from
human studies) and from the application of uncertainty factors to reflect issues such as the duration of the experiment,
the fact that animals are being used to represent humans and the quality of the study. However in developing cancer
dose-response (D-R) assessments, a standard exposure scenario is assumed in calculating the slope factor (i.e., human
cancer risk per unit  dose) on the  basis of either animal bioassay data or human data. This  standard scenario has
traditionally been assumed to be typical of the U.S. population: 1)  body weight = 70 kg;  2) air intake rate = 20
mVday;  3) drinking water intake = 2 liters/day; 4) lifetime = 70 years.  In RfC derivations for cases involving an
adverse effect on the  respiratory tract, the air intake rate of 20 m3/day is assumed.  The use of these specific values
has depended on whether the slope factor was derived' from animal or human epidemiologic data:

    •     Animal Data:  For dose-resopnse (D-R)  studies based on animal data, scale animal doses to  human
          equivalent doses using a human body weight assumption of 70 kg.  No explicit lifetime adjustment is
          necessary  because the assumption is made that events occurring in the lifetime animal bioassay will occur
          with equal probability in a human lifetime, whatever that might happen to be.

    •     Human Data - In the analysis of human studies (either occupational or general population), the Agency has
          usually made no explicit assumption of body weight or human lifetime. For both of these parameters there
          is  an implicit assumption that the population usually of interest has the same descriptive parameters as the
          population analyzed by the Agency.  In the rare situation where  this assumption is known to be wrong, the
          Agency has made appropriate corrections  so that  the dose-response parameters represent the national
          average population.

    When the population of interest is different than the national average (standard) population, the dose-response
parameter needs to be adjusted. In  addition, when the population of interest is different than the population from which
the exposure factors in this handbook were derived, the exposure factor needs to be adjusted. Two generic  examples
of situations where these adjustments are needed are as follows:

    A) Detailed study of recent data, such as are presented in this  handbook, show that EPA's standard assumptions
(i.e., 70 kg body weight, 20 m3/day air inhaled,  and 2 L/day water intake) are inaccurate for the national population
and may be inappropriate for sub-populations under consideration. The handbook addresses most of these  situations
by providing gender-  and age-specific values and by normalizing the intake values to body weight when the data are
available, but it may not have covered all possible situations. An example of a sub-population with a different mean
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                                    	Appendix 1A
body weight would be females, with an average body weight of 60 kg or children with a body weight dependent on
age. Another example of a non-standard sub-population would be a sedentary hospital population with lower than 20
m3/day air intake rates.

    B) The population variability of these parameters is of interest and it is desired to estimate percentile limits of the
population  variation.  Although the detailed methods for estimating percentile limits of exposure  and risk in a
population are beyond the scope of this document, one would treat the body weight and the intake rates discussed in
Sections 2 to 4 of this appendix as distributions, rather than constants.

2.  CORRECTIONS FOR DOSE-RESPONSE PARAMETERS
    The correction factors for the dose-response values tabulated in the IRIS data base for carcinogens are summarized
in Table 1A-1. Use of these correction parameters is necessary to avoid introducing errors into the risk analysis.  The
second column of Table 1A-1 shows the dependencies that have been assumed in the typical situation where the human
dose-response factors have been derived from the administered dose in animal studies.  This table is applicable in most
cases that  will be encountered, but  it is  not  applicable when: a) the effective dose  has been  derived with a
pharmacokinetic model and b) the dose-response data has been derived from human data.  In the former case, the
subpopulation parameters need to be incorporated into the model. In the latter case, the correction factor for the dose-
response parameter must be evaluated on a case-by case basis by examining the specific data and assumptions in the
derivation of the parameter.


                Table 1A-1. Procedures for Modifying IRIS Risk Values for Non-standard Populations3'15
 IRIS Risk Measure
 [Units]
IRIS Risk Measure is Proportional to:b   Correction Factor (CF) for modifying
                                  IRIS Risk Measures:0
Slope Factor
[per mg/(kg/day)]
Water Unit Risk
[per /tg/1]
Air Unit Risk:
(Ws)1/3 = (70)1/3

IWS/[(WS)2/3] = 2/[(70)2/3]

IAS/[(WS)2/3] = 20/[(70)2/3]
(Wp/70)1/3

(Iwp)/2 x [70/(WP)]2/3

(IAP)/20 x [70/(WP)]2/3
   A. Particles or aerosols
      [per jtg/m3], air concentration by
      weight

 Air Unit Risk:
   B.  Gases
      [per parts per million], air
      concentration by volume,
No explicit proportionality to body
weight or air intake is assumed.
1.0
ppm by volume is assumed to be the
effective dose in both animals and
humans.
a W = Body weight (kg)
  Iw « Drinking water intake (liters per day)
  IA = Air intake (cubic meters per day)

b Ws, IwSl, IAS denote standard parameters assumed by IRIS

c Modified risk measure = (CF) x IRIS value
  Wp, Iwp, IAP denote non-standard parameters of the actual population
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Appendix 1A
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     As one example of the use of Table 1 A-l, the recommended value for the average consumption of tapwater for
adults in the U. S. population derived in this document (Chapter 3), is 1.4 liters per day. The drinking water unit risk
for dichlorvos, as given in the IRIS information data base is 8.3 x 10~6 per /tg/1, and was calculated from the slope
factor assuming the standard intake, Iws, of 2 liters per day.  For the United States population drinking 1.4 liters of
tap water per day the corrected drinking water unit risk should be 8.3 x 10"6 x (1.4/2) = 5.8 x 10"6 per ,ug/l. The risk
to the average individual is then estimated by multiplying this by the average concentration in units of jug/1.

    Another example is when the risk for women drinking water contaminated with dichlorvos is to be estimated.
If the  women have  an average body  weight of 60  kg, the correction factor  for the drinking  water unit risk  is
(disregarding the correction discussed in the above paragraph), from Table 1A-1,  is (70/60)273 =  1.11. Here the ratio
of 70 to 60 is raised to the power of 2/3. The corrected water unit risk for dichlorvos is 8.3 x  10"6 x 1.11 = 9.2 x
10"6 per jUg/1.  As before, the risk to the average individual is estimated by multiplying this by the water concentration.

    When human data are  used to derive the risk measure,  there is a large variation in the different data sets
encountered in IRIS, so no generalizations  can be made about global corrections.  However, the typical default
exposure values used for the air intake of an air pollutant over an occupational lifetime are: air intake is 10 m3/day
for an 8-hour shift, 240 days per year with 40 years on the job.  If there is continuous exposure to an ambient air
pollutant, the lifetime dose is usually calculated assuming a 70-year lifetime.

3.  CORRECTIONS FOR INTAKE DATA
    When the body weight, Wp, of the population of interest differs from the body weight, WE, of the population from
which the exposure values in this handbook were derived, the following model  furnishes a  reasonable basis for
estimating the intake of food and air (and probably water also) in the population of interest.  Such a model is needed
in the absence of data on the dependency of intake on body size.  This occurs for inhalation data, where the intake data
are not normalized to body weight, whereas the model is not needed for food and tap water intakes if they are given
hi units of intake per kg body weight.

    The model is based on the dependency of metabolic oxygen consumption on body size.  Oxygen consumption is
directly related to food (calorie) consumption and air intake and indirectly to water intake. For mammals of a wide
range of species sizes (Prosser and Brown,  1961), and also for individuals of various  sizes within a species, the oxygen
consumption and calorie (food) intake varies as the body weight raised to a power  between 0.65 and 0.75. A value
of 0.667 = 2/3 has been used in EPA as the default value for adjusting cross-species intakes, and the same factor has
been used for intra-species intake adjustments.

     [NOTE: Following discussions by an interagency task  force (Federal Register, 1992), the agreement was that a
more accurate and defensible default value would be to choose the power to 3/4 rather than 2/3.  A recent article (West
et al.,  1997) has provided a theoretical basis for the 3/4 power scaling. This will be the standard value to be used in
future assessments, and all equations in this Appendix will be modified in future risk assessments.  However, because
risk assessors now use the current IRIS information, this discussion is presented with the previous default assumption
of 2/3].

     With this model, the relation between the daily air intake in the population of interest, IAP = (m3/day)p, and the
intake in the population described hi this handbook, IAE  =  (m3/day)E is:
                          p _
                              :
                                            \2/3
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 	Appendix 1A
4.  CALCULATION OF RISKS FOR AIR CONTAMINANTS
    The risk is calculated by multiplying the IRIS air unit risk, corrected as described in Table 1A-1, by the air
concentration. But since the correction factor involves the intake in the population of interest (IAP), that quantity must
be included in the equation, as follows:

          (Risk)p = (air unit risk)p x (air concentration)
                  = (air unit risk)8 x (IAP/20) x (70/WP)2/3 x (air concentration)
                  = (air unit risk)8 x [( L.E x (Wp/WE)2/3/20)] x (70/WP)2/3 x (air concentration)
                  = (air unit risk)8 x (IA/20) x (70/WE)2/3 x (air concentration)

    In this equation the air unit risk from the IRIS data base (air unit risk)5, the air intake data hi the handbook for
the populations where it is available (IAE) and the body weight of that population (WE) are included along with the
standard IRIS values of the air intake (20 m3/day) and body weight (70 kg).

    For food ingestion and tap water intake, if body weight-normalized intake values from this handbook are used,
the intake data do not have to be corrected as in Section 3 above. In these cases, corrections to the dose-response
parameters in Table 1A-1 are sufficient.

5.  REFERENCES

Federal Register. (1992) Cross-species scaling factor for carcinogen risk assessments based on equivalence of (mg/kg-
    day)3M.  Draft report. Federal Register, 57(109): 24152-24173, June 5,  1992.

Prosser, C.L.; Brown, F.A. (1961)  Comparative Animal physiology, 2nd edition. WB Saunders Co. p. 161.

U.S. EPA. (1996) Background Documentation. Integrated Risk Information System (IRIS). Online. National Center
    for Environmental Assessment, Cincinnati, Ohio. Background Documentation available from: Risk Information
    Hotline, National Center for Environmental Assessment,  U.S. EPA, 26 W. Martin Luther King Dr. Cincinnati,
    OH 45268. (513) 569-7254

West, G.B.; Brown, J.H.; Enquist, B.J. (1997) A general model of the origin of allometric scaling laws in biology.
    Science 276:122-126.
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Chapter 2 - Variability and Uncertainty
2.    VARIABILITY AND UNCERTAINTY
      The chapters  that follow will  discuss exposure
factors and algorithms for estimating exposure. Exposure
factor values can be  used to obtain a range of exposure
estimates  such  as  average, high-end  and  bounding
estimates.  It is instructive here to return to the general
equation for potential Average Daily Dose (ADDpot) that
was introduced in the opening chapter of this handbook:
  .......  _ Contaminant Concentration x Intake Rale x Exposure Duration
     *"           Body Weight x Averaging Time
(Eqn. 2-1)
      With   the   exception  of   the  contaminant
concentration, all parameters in the above equation are
considered exposure factors and, thus, are treated in fair
detail in other chapters of this handbook. Each of the
exposure factors involves humans, either in terms of their
characteristics (e.g., body weight)  or behaviors (e.g.,
amount of time spent in a specific location, which affects
exposure duration).  While the topics of variability and
uncertainty apply equally to contaminant concentrations
and the rest of the exposure factors  in equation 2-1, the
focus of this chapter is on variability and uncertainty as
they relate to exposure factors. Consequently, examples
provided  in this chapter  relate primarily to exposure
factors, although contaminant concentrations may be used
when they better illustrate the point under discussion.
      This  chapter also  is intended  to acquaint the
exposure assessor with some of the fundamental concepts
and  precepts related  to   variability and  uncertainty,
together with methods and considerations for evaluating
and presenting the uncertainty associated with exposure
estimates. Subsequent sections in this chapter  are devoted
to the following topics:

      •   Distinction between variability and
          uncertainty;
      •   Types of variability;
      •   Methods of confronting variability;
      •   Types of uncertainty and reducing  uncertainty;
      •   Analysis of variability and uncertainty; and
      •   Presenting results  of  variability/uncertainty
          analysis.

      Fairly extensive treatises on the topic of uncertainty
have been provided, for example, by Morgan and Henrion
(1990), the National Research Council (NRC, 1994) and,
to a lesser extent, the U.S. EPA (1992; 1995). The topic
commonly has been treated as it relates to the overall
process of conducting risk assessments; because exposure
assessment is a component of risk-assessment process, the
general concepts apply equally to the exposure-assessment
component.

2.1.   VARIABILITY VERSUS UNCERTAINTY
      While some authors have treated variability as a
       specific type or component of uncertainty, the
       U.S. EPA (1995) has advised the risk assessor
       (and, by  analogy,  the exposure assessor)  to
       distinguish between variability and uncertainty.
       Uncertainty represents a lack of knowledge about
factors affecting exposure or  risk,  whereas variability
arises from true heterogeneity across people, places or
time. In other words, uncertainty can lead to inaccurate or
biased estimates,  whereas  variability  can affect the
precision of the estimates and  the degree to which they
can be generalized.  Most of the data presented in this
handbook concerns variability.
       Variability and uncertainty can complement or
confound one another. An instructive analogy has  been
drawn by the  National Research Council (NRC, 1994:
Chapter  10), based on the objective of estimating the
distance between the earth and the moon. Prior to fairly
recent technology developments, it was difficult to make
accurate measurements  of this distance,  resulting in
measurement uncertainty.  Because the moon's orbit is
elliptical, the distance is a variable quantity. If only a few
measurements were to be taken  without knowledge of the
elliptical pattern, then either of the following incorrect
conclusions might be reached:

       •    That the measurements were faulty,  thereby
           ascribing to uncertainty  what was actually
           caused by variability; or
       •    That the moon's orbit was random, thereby not
           allowing   uncertainty  to  shed  light  on
           seemingly unexplainable differences that are
           in fact variable and predictable.

       A more fundamental error in the above situation
would be  to incorrectly  estimate the true distance,  by
assuming that a few observations were sufficient.  This
latter pitfall - treating a highly variable quantity as if it
were invariant or only uncertain — is probably the  most
relevant to the exposure or risk assessor.
       Now consider a situation that relates to exposure,
such as estimating the average daily dose by one exposure
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 route  —  ingestion  of contaminated drinking water.
 Suppose that it is possible to measure an individual's daily
 water consumption (and concentration of the contaminant)
 exactly, thereby eliminating uncertainty in the measured
 daily dose. The daily dose still has an inherent day-to-day
 variability, however, due to changes  in the  individual's
 daily water intake or the contaminant concentration in
 water.
       It is impractical to measure the individual's dose
 every  day.  For this reason, the exposure assessor may
 estimate the average daily dose (ADD) based on a  finite
 number of measurements, in an attempt to "average out"
 the day-to-day variability. The individual has a true (but
 unknown) ADD, which has now been estimated based on
 a sample of measurements.  Because the individual's true
 average is unknown, it is uncertain how close the estimate
 is to the true value.  Thus, the variability across  daily
 doses  has been translated into uncertainty in the ADD.
 Although the individual's true ADD has no variability, the
 estimate of the ADD has some uncertainty.
       The above discussion pertains to the ADD for one
 person.  Now consider a distribution of ADDs across
 individuals in a defined population (e.g., the general U.S.
 population).  In this case, variability refers to the range
 and distribution of ADDs across individuals  in the
 population.   By comparison,  uncertainty refers to the
 exposure assessor's  state  of knowledge  about that
 distribution,   or  about  parameters  describing  the
 distribution (e.g., mean, standard deviation, general shape,
 various percentiles).
       As noted by the National Research Council (NRC,
 1994),  the realms of variability and uncertainty  have
 fundamentally different ramifications for science and
judgment. For example, uncertainty may force decision-
 makers to judge how probable it is that exposures have
 been overestimated or underestimated for every member
 of the exposed population, whereas variability forces them
 to cope with the certainty that different individuals are
 subject to exposures both above and below any of the
 exposure levels chosen as a reference point.

 2.2.   TYPES OF VARIABILITY
       Variability in exposure is related to an  individual's
 location, activity, and  behavior  or  preferences  at  a
 particular point in time, as well  as pollutant emission rates
 and physical/chemical processes that affect concentrations
 in various media (e.g., air, soil, food and water).  The
 variations in pollutant-specific emissions or processes,
 and in individual locations, activities or behaviors, are not
necessarily independent of one another.  For example,
both personal activities and pollutant concentrations at a
specific  location might  vary in response to weather
conditions, or between weekdays and weekends.
      At a more fundamental level, three types  of
variability can be distinguished:

      •   Variability across locations (Spatial
          Variability);
      •   Variability over time (Temporal Variability);
          and
      •   Variability among individuals (Inter-
          individual Variability).

      Spatial variability  can occur both at regional
(macroscale) and local (microscale) levels. For example,
fish intake rates can vary depending on the region of the
country.    Higher  consumption  may  occur  among
populations located near large bodies of water such as the
Great Lakes or  coastal  areas.   As another example,
outdoor pollutant levels can be affected at  the regional
level by industrial activities  and at the local  level by
activities of individuals. In general, higher exposures tend
to be associated with closer proximity to the pollutant
source, whether it be  an industrial plant or related to a
personal activity such as showering or  gardening. In the
context of exposure to airborne pollutants, the concept of
a "microenvironment"  has been introduced (Duan, 1982)
to denote a specific locality (e.g., a residential lot or a
room in a  specific  building)  where  the  airborne
concentration  can be treated  as  homogeneous (i.e.,
invariant) at a particular point in time.
      Temporal variability refers to variations over
time, whether long- or short-term. Seasonal fluctuations
in weather, pesticide applications, use of woodburning
appliances  and  fraction of  time spent  outdoors  are
examples of longer-term variability. Examples of shorter-
term variability are differences  in industrial or personal
activities on weekdays versus weekends or at different
times of the day.
      Inter-individual variability  can be either of two
types:  (1) human characteristics such as  age or body
weight,  and (2) human behaviors such as  location and
activity patterns.  Each of these variabilities,  in turn, may
be related to several underlying phenomena that vary. For
example, the natural variability in human weight is due to
a combination of genetic, nutritional, and other lifestyle or
environmental   factors.   Variability   arising   from
independent  factors  that  combine   multiplicatively
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generally  will  lead to an  approximately lognormal
distribution   across   the   population,   or   across
spatial/temporal dimensions.

2.3.   CONFRONTING VARIABILITY
      According to the National Research Council (NRC
1994), variability can be confronted in four basic ways
(Table 2-1) when dealing with science-policy questions
surrounding issues such as exposure or risk assessment.
The  first is to ignore the variability and hope for the
best. This strategy tends to work best when the variability
is relatively small. For example, the assumption that all
adults weigh 70 kg is likely to be correct within ±25% for
most adults.
      The second strategy involves disaggregating the
variability  in some  explicit way,  in order to better
understand it or  reduce it.  Mathematical models are
appropriate in some cases, as in fitting a sine wave to the
annual  outdoor  concentration cycle for a particular
pollutant and location.  In other cases, particularly those
involving human characteristics or behaviors, it is easier
to disaggregate the data by considering all the  relevant
subgroups or subpopulations. For example, distributions
of body weight could be developed separately for adults,
adolescents and children, and even for males and females
within each of these subgroups.  Temporal and spatial
analogies for this  concept  involve measurements on
appropriate  time scales  and choosing appropriate
subregions or microenvironments.
      The third strategy is to use the average value of a
quantity that varies. Although this strategy might appear
as tantamount to ignoring variability,  it needs to be based
on a decision that the average value can be estimated
reliably in  light of the  variability (e.g., when  the
variability is known to be relatively small, as in the case
of adult body weight).
      The fourth strategy involves using the maximum
or minimum value for an exposure factor. In this case,
the variability is characterized by the range between the
extreme values and a measure of central tendency.  This
is perhaps  the most common method of dealing  with
variability in exposure or risk assessment — to focus on
one time period (e.g., the period of peak exposure), one
spatial region (e.g., in close proximity  to the  pollutant
source of concern), or one subpopulation  (e.g., exercising
asthmatics). As noted by the U.S. EPA (1992), when an
exposure  assessor  develops  estimates  of  high-end
individual exposure and  dose, care must be taken not to
set all factors to values that maximize exposure or dose —
such  an approach  will-  almost always  lead  to an
overestimate.

2.4.   CONCERN ABOUT UNCERTAINTY
      Why should the exposure  assessor be concerned
with uncertainty?  As noted by  the U.S. EPA (1992),
exposure assessment can  involve  a broad  array of
information sources and analysis techniques.  Even in
situations where actual exposure-related measurements
exist, assumptions  or inferences will still be required
because data are not likely to be available for all aspects
of the exposure assessment. Moreover,  the data that are
available may be of questionable or unknown quality.
Thus, exposure assessors have a responsibility to present
not just numbers, but also a clear and explicit explanation
of the implications and limitations of their analyses.
Table 2-1. Four Strategies for Confronting Variability
Strategy
Ignore variability
Disaggregate the
variability
Use the average value
Use a maximum or
minimum value
Example
Assume that all adults weigh
70kg
Develop distributions of
body weight for age/gender
groups
Use average body weight for
adults
Use a lower-end value from
the weight distribution
Comment
Works best when variability is small
Variability will be smaller in each group
Can the average be estimated reliably given what is
known about the variability?
Conservative approach — can lead to unrealistically
high exposure estimate if taken for all factors
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      Morgan and Henrion (1990) provide an argument
by analogy. When scientists report quantities that they
have measured, they are expected to routinely report an
estimate  of the probable error associated  with  such
measurements.  Because uncertainties inherent in policy
analysis (of which exposure assessment is a part) tend to
be  even greater  than  those  in the natural sciences,
exposure assessors also should be expected to report or
comment  on  the  uncertainties  associated  with  their
estimates.
      Additional reasons for addressing uncertainty in
exposure or risk assessments (U.S. EPA, 1992, Morgan
and Henrion, 1990) include the following:

      •   Uncertain information from different sources
          of different  quality often must be combined
          for the assessment;
      •   Decisions need to be made about whether or
          how to expend resources to acquire additional
          information,;
      •   Biases may result in so-called "best estimates"
          that in actuality are not very accurate; and
      •   Important factors  and potential sources of
          disagreement in a problem can be identified.

      Addressing uncertainty will increase the likelihood
that results of an assessment or analysis will be used in an
appropriate manner.   Problems  rarely are  solved to
everyone's satisfaction, and decisions rarely are reached
on the basis of a single piece of evidence. Results of prior
analyses can  shed  light  on  current   assessments,
particularly if they are couched in  the  context of
prevailing uncertainty at the time of analysis.  Exposure
assessment tends  to be an  iterative process, beginning
with a screening-level assessment that may identify the
need for more in-depth assessment. One of the primary
goals of the more detailed  assessment is  to reduce
uncertainty  in estimated exposures. This objective can be
achieved more efficiently if guided by presentation and
discussion of factors thought to be primarily responsible
for uncertainty in prior estimates.

2.5.   TYPES OF UNCERTAINTY AND
      REDUCING UNCERTAINTY
      The  problem of uncertainty in exposure or risk
assessment is relatively large, and can quickly become too
complex for  facile treatment unless it is  divided  into
smaller and more manageable topics. One method of
division (Bogen,  1990) involves classifying  sources of
uncertainty according to the step in the risk assessment
process (hazard identification, dose-response assessment,
exposure assessment or risk characterization) at which
they can occur. A more abstract and generalized approach
preferred by some scientists is to partition all uncertainties
among the three categories of bias, rand9mness and true
variability.  These  ideas are discussed  later in  some
examples.
      The U.S. EPA (1992) has classified uncertainty in
exposure assessment into three broad categories:

       1.  Uncertainty regarding missing or incomplete
          information  needed to fully define exposure
          and dose (Scenario Uncertainty).
      2.  Uncertainty   regarding  some   parameter
          (Parameter Uncertainty).
      3.  Uncertainty regarding gaps in scientific theory
          required  to make predictions on the basis of
          causal inferences (Model Uncertainty).

Identification of the sources of uncertainty  in an exposure
assessment is the first step in determining how to reduce
that uncertainty. The types of uncertainty listed above can
be further defined by examining their principal causes.
Sources and examples for each type of uncertainty are
summarized in Table 2-2.
      Because uncertainty in exposure  assessments is
fundamentally tied to a lack of knowledge concerning
important  exposure factors, strategies   for  reducing
uncertainty necessarily involve reduction or elimination of
knowledge gaps.  Example strategies to reduce uncertainty
include (1) collection of new data using a larger sample
size,  an  unbiased  sample  design,  a  more  direct
measurement  method  or  a  more  appropriate target
population, and (2)  use of more sophisticated modeling
and analysis tools.

2.6.  ANALYZING VARIABILITY AND
      UNCERTAINTY
      Exposure  assessments often are developed in a
phased approach. The initial phase usually screens out the
exposure scenarios or pathways that  are not expected to
pose much risk,  to eliminate them from  more detailed,
resource-intensive review.  Screening-level assessments
typically examine exposures that would fall on or beyond
the high end of the expected exposure distribution.
Because screening-level analyses usually  are included in
the final exposure assessment, the final document may
contain scenarios that differ quite markedly in
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Table 2-2. Three Types of Uncertainty and Associated Sources and Examples
Type of Uncertainty
Scenario Uncertainty



Parameter Uncertainty



Model Uncertainty

Sources
Descriptive errors
Aggregation errors
Judgment errors
Incomplete analysis
Measurement errors
Sampling errors
Variability
Surrogate data
Relationship errors
Modeling errors
Examples
Incorrect or insufficient information
Spatial or temporal approximations
Selection of an incorrect model
Overlooking an important pathway
Imprecise or biased measurements
Small or unrepresentative samples
In time, space or activities
Structurally-related chemicals
Incorrect inference on the basis for correlations
Excluding relevant variables
sophistication,   data  quality,  and  amenability  to
quantitative expressions of variability or uncertainty.
      According to the U.S. EPA (1992), uncertainty
characterization and uncertainty assessment are two ways
of  describing   uncertainty  at  different  degrees  of
sophistication.    Uncertainty characterization usually
involves a qualitative discussion of the thought processes
used to select or reject specific data, estimates, scenarios,
etc. Uncertainty assessment is a more quantitative process
that may range from simpler measures (e.g., ranges) and
simpler analytical techniques (e.g., sensitivity analysis) to
more complex measures and techniques.  Its goal is to
provide decision makers with information concerning the
quality  of an  assessment,  including  the  potential
variability in the estimated exposures,  major data gaps,
and the effect that these data gaps have on the exposure
estimates developed.
      A distinction between variability and uncertainty
was made  in Section 2.1.   Although the quantitative
process  mentioned above  applies more  directly  to
variability  and  the qualitative approach  more  so  to
uncertainty, there is some degree of overlap. In general,
either method provides the assessor or decision-maker
with  insights to  better evaluate the assessment  in the
context of available data and assumptions. The following
paragraphs  describe  some  of  the  more  common
procedures for analyzing variability and uncertainty in
exposure  assessments.    Principles  that  pertain  to
presenting the results of variability/uncertainty analysis
are discussed in the next section.
      Several approaches can be used to characterize
uncertainty in parameter values.   When uncertainty is
high, the assessor may use order-of-magnitude bounding
estimates of parameter ranges (e.g., from 0.1 to 10 liters
for daily water intake).  Another method  describes the
range for each parameter including the lower and upper
bounds as well as a "best estimate" (e.g., 1.4 liters per
day)  determined  by available  data  or  professional
judgement.
      When sensitivity analysis indicates that a parameter
profoundly influences exposure estimates, the assessor
should develop a probabilistic description of its range. If
there are enough data  to  support their use,  standard
statistical methods  are preferred.   If the data  are
inadequate, expert judgment can  be used  to generate a
subjective probabilistic  representation. Such judgments
should be developed in a consistent, well-documented
manner. Morgan and Henrion (1990) and Rish (1988)
describe techniques to solicit expert judgment.
      Most approaches to quantitative analysis examine
how variability and uncertainty  in values of  specific
parameters translate into the overall uncertainty of the
assessment.  Details may be found  in reviews such as Cox
and Baybutt (1981), Whitmore  (1985), Inman and Helton
(1988), Seller (1987),  and  Rish  and  Marnicio  (1988).
These approaches can generally be described (in order of
increasing complexity and data needs) as:  (1) sensitivity
analysis;   (2)  analytical  uncertainty   propagation;
(3) probabilistic uncertainty  analysis; or  (4) classical
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                                                                                Volume I - General Factors
                                                                  Chapter 2 - Variability and Uncertainty
 statistical methods (U.S. EPA 1992). The four approaches
 are summarized in Table 2-3.
                         medium, or low; and state whether they were based on
                         data,  analogy,  or  professional  judgment.    Where
                                Table 2-3. Approaches to Quantitative Analysis of Uncertainty
 Approach
Description
Example
 Sensitivity Analysis
 Analytical Uncertainty Propagation
 Probabilistic Uncertainty Analysis
 Classical Statistical Methods
Changing one input variable at a time while
leaving others constant, to examine effect on
output

Examining how uncertainty in individual
parameters affects the overall uncertainty of the
exposure assessment

Varying each of the input variables over various
values of their respective probability distributions
                                 Estimating the population exposure distribution
                                 directly, based on measured values from a
                                 representative sample	
Fix each input at lower (then upper) bound
while holding others at nominal values (e.g.,
medians)

Analytically or numerically obtain a partial
derivative of the exposure equation with
respect to each input parameter

Assign probability density function to each
parameter; randomly sample values from each
distribution and insert them in the exposure
equation (Monte Carlo)

Compute confidence interval estimates for
various percentiles of the exposure distribution
 2.7.   PRESENTING RESULTS OF VARIABILITY
       AND UNCERTAINTY ANALYSIS
       Comprehensive qualitative analysis and rigorous
 quantitative analysis  are  of little value for use in the
 decision-making process,  if their results are not clearly
 presented.   In  this chapter, variability (the receipt of
 different levels  of exposure by different individuals) has
 been  distinguished  from  uncertainty  (the  lack  of
 knowledge about the correct value for a specific exposure
 measure or estimate).  Most of the data that are presented
 in this handbook deal with variability directly,  through
 inclusion of statistics  that pertain to the distributions for
 various exposure factors.
       Not all approaches historically used  to construct
 measures or estimates of exposure have attempted to
 distinguish  between  variability and uncertainty.  The
 assessor  is   advised  to  use  a variety of exposure
 descriptors,  and  where  possible,  the full  population
 distribution,  when   presenting  the   results.     This
 information  will  provide risk managers with a better
 understanding of how exposures are distributed over the
 population and  how variability in population activities
 influences this distribution.
       Although  incomplete  analysis  is   essentially
 unquantifiable as a source of uncertainty, it should not be
 ignored. At a minimum, the assessor should  describe the
 rationale for excluding particular  exposure scenarios;
 characterize the uncertainty in these decisions as high,
                         uncertainty is high, a sensitivity analysis can be used to
                         credible upper limits on exposure by way of a series of
                         "what if questions.
                               Although assessors have always used descriptors to
                         communicate the kind  of scenario being addressed, the
                         1992 Exposure Guidelines establish clear  quantitative
                         definitions for these risk descriptors. These definitions
                         were established to ensure that consistent terminology is
                         used throughout the Agency. The risk descriptors defined
                         in the Guidelines include descriptors of individual risk
                         and population  risk.   Individual risk descriptors  are
                         intended to address questions dealing with risks borne by
                         individuals  within a  population, including  not only
                         measures of central tendency (e.g., average or median),
                         but also those risks at  the high  end  of the distribution.
                         Population risk descriptors refer to an assessment of the
                         extent of harm to the population  being addressed. It can
                         be either an estimate of the number of cases of a particular
                         effect that  might occur in a  population (or population
                         segment),  or  a  description  of what fraction of  the
                         population receives exposures, doses, or risks greater than
                         a specified value.  The data presented in the Exposure
                         Factors  Handbook is  one of  the  tools  available  to
                         exposure assessors  to  construct  the  various  risk
                         descriptors.
                               However, it is not sufficient to merely present the
                         results  using  different  exposure  descriptors.   Risk
                         managers should also be presented with an analysis of the
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2-6
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                                                               August 1997

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Volume I - General Factors

Chapter 2 - Variability and Uncertainty
                                        A
uncertainties surrounding these descriptors.  Uncertainty
may be presented using simple or very sophisticated
techniques,  depending  on  the  requirements of  the
assessment and the amount of data available. It is beyond
the scope of this handbook to discuss the mechanics of
uncertainty analysis in detail.  At a minimum, the assessor
should address uncertainty qualitatively by answering
questions such as:

      •   What is  the basis or  rationale for selecting
          these assumptions/parameters, such as data,
          modeling, scientific judgment, Agency policy,
          "what if considerations, etc.?

      •   What is  the range or variability of the  key
          parameters?  How were the parameter values
          selected  for  use  in the assessment?   Were
          average, median, or upper-percentile values
          chosen?  If other choices had been made, how
          would the results have differed?

      •   What is the assessor's confidence (including
          qualitative  confidence aspects)  in the  key
          parameters and the overall assessment?  What
          are  the quality and the extent of the data
          base(s) supporting the selection of the chosen
          values?

      Any exposure estimate developed by an assessor
will have associated  assumptions about the setting,
chemical, population characteristics, and how contact with
the chemical occurs through various exposure routes and
pathways. The exposure assessor will need to examine
many sources of information that bear either directly or
indirectly  on  these   components of the  exposure
assessment. In addition, the assessor will be required to
make  many decisions  regarding  the  use  of existing
information in constructing scenarios and setting up the
exposure equations. In presenting the scenario results, the
assessor  should  strive for  a balanced  and impartial
treatment of the evidence bearing on the conclusions with
the key assumptions  highlighted.   For  these  key
assumptions, one should cite data sources and explain any
adjustments of the data.
       The exposure assessor also should qualitatively
describe the rationale for selection of any conceptual or
mathematical models that may  have been  used.  This
discussion should address their verification and validation
status,  how well they  represent the  situation  being
assessed (e.g., average versus high-end estimates), and
any plausible alternatives in terms of their acceptance by
the scientific community.
      Table  2-2  summarizes  the  three  types  of
uncertainty, associated sources, and examples.  Table 2-3
summarizes four approaches  to analyze uncertainty
quantitatively. These are described further in the 1992
Exposure Guidelines.

2.8.  REFERENCES FOR CHAPTER 2
Bogen, K.T.  (1990) Uncertainty in environmental
    health risk assessment. Garland Publishing, New
    York, NY.
Cox, D.C.;  Baybutt, P.C. (1981) Methods for
    uncertainty analysis.  A comparative survey.  Risk
    Anal. l(4):251-258. •
Duan, N. (1982) Microenvironment types: A model for
    human exposure to air pollution. Environ. Intl.
    8:305-309.
Inman, R.L.; Helton, J.C. (1988)  An investigation of
    uncertainty and sensitivity analysis techniques for
    computer models. Risk Anal. 8(1):71-91.
Morgan, M.G.; Henrion, M. (1990) Uncertainty: A
    guide to dealing with uncertainty in quantitative
    risk and policy analysis.  Cambridge University
    Press, New York, NY.
National Research Council (NRC). (1994) Science and
    judgment in risk assessment. National Academy
    Press, Washington, DC.
Rish, W.R. (1988) Approach to uncertainty in risk
    analysis.  Oak Ridge National Laboratory.
    ORNL/TM-10746.
Rish, W.R.; Marnicio, R.J. (1988) Review of studies
    related to uncertainty in risk analysis. Oak Ridge
    National Laboratory.  ORNL/TM-10776.
Seller, F.A. (1987) Error propagation for large errors.
    Risk Anal. 7(4):509-518.
U.S. EPA (1992) Guidelines for exposure assessment.
    Washington, DC: Office of Research and
    Development, Office of Health and Environmental
    Assessment. EPA/600/2-92/001.
U.S. EPA (1995) Guidance for risk characterization.
    Science Policy Council, Washington, DC.
Whitmore, R.W. (1985) Methodology for
    characterization of uncertainty in exposure
    assessments. EPA/600/8-86/009.
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 Ausust 1997
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Volume I - General Factors
Chapter 3 - Drinking Water Intake
3.    DRINKING WATER INTAKE
3.1.  BACKGROUND
      Drinking water  is a potential source of human
exposure to toxic substances. Contamination of drinking
water may occur by, for example, percolation of toxics
through the soil to ground water that is used as a source
of drinking water; runoff or discharge to surface water
that is used as a source  of drinking water; intentional or
unintentional addition of substances to treat water (e.g.,
chlorination); and leaching of materials from plumbing
systems (e.g., lead).  Estimating the magnitude of the
potential dose of toxics from  drinking water requires
information on the quantity of water  consumed.  The
purpose  of this section is to  describe  key published
studies  that provide information  on drinking water
consumption    (Section    3.2)    and   to   provide
recommendations of consumption rate values that should
be used in exposure assessments (Section 3.6).
      Currently, the U.S.  EPA uses the quantity of 2 L
per day for adults and 1 L per day for infants (individuals
of 10 kg body mass or less) as default drinking water
intake rates (U.S. EPA,   1980; 1991).   These  rates
include drinking water consumed in the form of juices
and other beverages  containing tapwater (e.g., coffee).
The National  Academy  of  Sciences  (NAS,  1977)
estimated that daily consumption of water may vary with
levels of physical activity and fluctuations in temperature
and humidity.   It is reasonable to assume that some
individuals in physically-demanding occupations or living
in warmer regions may have high levels of water intake.
      Numerous  studies  cited in this chapter  have
generated data  on drinking water intake  rates.   In
general, these sources support EPA's use of 2 L/day for
adults and 1  L/day for  children  as  upper-percentile
tapwater intake rates. Many of the studies have reported
fluid  intake rates for  both total fluids  and tapwater.
Total fluid intake is defined as  consumption of all types
of fluids including tapwater, milk, soft drinks, alcoholic
beverages, and water intrinsic to purchased foods. Total
tapwater is defined as water consumed directly from the
tap as a beverage or used in the preparation of foods and
beverages (i.e., coffee, tea, frozen juices,  soups, etc.).
Data for both consumption categories are presented in
the sections that follow.  However, for the purposes of
exposure  assessments    involving   source-specific
contaminated drinking water, intake rates based on  total
tapwater  are  more  representative of source-specific
tapwater intake.  Given the assumption that purchased
foods and beverages are widely distributed and less likely
to contain source-specific water, the use of total fluid
intake rates may overestimate the potential exposure to
toxic substances present only  in local water supplies;
therefore tapwater intake, rather than total fluid intake,
is emphasized in this section.
      All 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 hi 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 Hie data.
      The  available   studies  on  drinking  water
consumption are summarized in the following sections.
They have  been classified as either key  studies  or
relevant studies based on the applicability of their survey
designs to exposure  assessment of the entire United
States population. Recommended intake  rates are based
on the results of key studies, but relevant  studies are also
presented to provide the reader with added perspective
on the current state-of-knowledge pertaining to drinking
water intake.

3.2.  KEY GENERAL POPULATION STUDIES ON
      DRINKING WATER INTAKE
      Canada Department of Health and  Welfare (1981)
-  Tapwater  Consumption in  Canada  - In  a  study
conducted by the Canadian Department of Health and
Welfare, 970 individuals from 295  households were
surveyed to determine the per capita total  tapwater intake
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                                                                          Volume I - General Factors
                                                                  Chapter 3 - Drinking Water Intake
rates  for  various  age/sex  groups during winter and
summer seasons (Canadian Ministry of National Health
and Welfare, 1981).  Intake rate was also evaluated as a
function of physical activity. The population that was
surveyed matched the Canadian 1976 census with respect
to the proportion in different age, regional, community
size and dwelling type groups.  Participants  monitored
tapwater consumed away from home. The survey also did
not attempt to estimate intake rates for fluids other than
tapwater.  Consequently, no intake rates for total fluids
were reported.
      Daily consumption distribution patterns for various
age groups are presented in Table 3-1. For adults (over
18 years of age) only, the average total tapwater intake
Table 3-1 . Daily Total Tapwater Intake Distribution for Canadians, by Age Group
(approx. 0.20 L increments, both sexes, combined seasons)
Amount Consumed3
L/day
0.00 - 0.21
0.22 - 0.43
0.44 - 0.65
0.66 - 0.86
0.87-1.07
1.08 - 1.29
1.30-1.50
1.51 - 1.71
1.72-1.93
1.94-2.14
2.15-2.36
2.37 - 2.57
2.58 - 2.79
2.80 - 3.00
3.01 - 3.21
3.22 - 3.43
3.44 - 3.64
3.65 - 3.86
>3.86
TOTAL
Age Group (years)
5 and under 6-17
%
11.1
17.3
24.8
9.9
11.1
11.1
4.9
6.2
1.2
1.2
1.2
-
-
-
-
-
-
-
-
100.0
Number
9
14
20
8
9
9
4
5
1
1
1
0
0
0
0
0
0
0
0
81
%
2.8
10.0
13.2
13.6
14.4
14.8
9.6
6.8
2.4
1.2
4.0
0.4
2.4
2.4
0.4
-
-
-
1.6
100.0
Number
7
25
33
34
36
37
24
17
6
3
10
1
6
6
1
0
0
0
4
250
18 and over
%
0.5
1.9
5.9
8.5
13.1
14.8
15.3
12.1
6.9
5.6
3.4
3.1
2.7
1.4
1.1
0.9
0.8
_
2.0
100.0
Number
3
12
38
54
84
94
98
77
44
36
22
20
17
9
7
6
5
0
13
639
a Includes tapwater and foods and beverages derived from tapwater.
Source: Canadian Ministry of National Health and Welfare, 1981.
water intake for a 2-day period (1  weekday, and  1
weekend day) in both late summer of 1977 and winter of
1978. All 970 individuals participated in both the summer
and winter surveys. The amount of tapwater consumed
was estimated based on the respondents' identification of
the type and size of beverage container used, compared to
standard sized vessels.   The survey  questionnaires
included a pictorial  guide  to help  participants  in
classifying the sizes of the vessels. For example, a small
glass of water was assumed to be equivalent to 4.0 ounces
of water, and a large glass was assumed to contain 9.0
ounces of water.   The study also accounted for water
derived from ice cubes and popsicles, and water in soups,
infant formula, and juices. The survey did not attempt to
differentiate between tapwater consumed at home and
rate was 1.38 L/day, and the 90th percentile rate was 2.41
L/day  as determined by graphical interpolation.  These
data follow a lognormal distribution. The intake data for
males, females, and both sexes combined as a function of
age and expressed in the units of milliliters (grams) per
kilogram body weight are presented in Table 3-2. The
tapwater survey did  not include body weights  of  the
participants, but the body weight information was taken
from a Canadian health survey dated  1981;  it averaged
65.1 kg for males and 55.6 kg for females.  Intake rates
for specific age groups and seasons are presented in Table
3-3.  The average daily total tapwater intake rates for all
ages and seasons combined was 1.34 L/day, and the 90th
percentile rate was 2.36 L/day. The summer intake rates
are nearly the same as the winter intake rates.  The authors
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Volume I - General Factors
Chapter 3 - Drinking Water Intake
speculate that the reason for the small seasonal variation
here is that in Canada, even in the summer, the ambient
temperature seldom exceeded 20 degrees C and marked
increase in water consumption with high activity levels
has been observed in other studies only when the ambient
temperature has been higher than 20 degrees.  Average
daily total tapwater intake rates as a function of the level
of  physical  activity,  as estimated  subjectively, are
presented  in  Table 3-4.  The  amounts  of  tapwater
consumed  that are derived  from various  foods and
beverages  are presented in Table 3-5.  Note that the
consumption of direct "raw" tapwater is almost constant
across all age groups from school-age children through
the  oldest  ages.   The increase  in total   tapwater
consumption beyond school age is due to coffee and tea
consumption.
Table 3-2. Average Daily Tapwater Intake of Canadians
(expressed as milliliters per kilogram body weight)
Average Daily Intake (mL/kg)
Age Group (years)
<3
3-5
6-17
18-34
35-54
55+
Females
53
49
24
23
25
24
Males Both Sexes
35
48
27
19
19
21
Total Population 24 21
Source: Canadian Ministry of National Health and Welfare,
45
48
26
21
22
22
22
1981.
Table 3-3. Average Daily Total Tapwater Intake of Canadians, by Age and Season (IVday)a
Age (years)

Average
Summer
Winter
Summer/Winter
90th Percentile
Summer/Winter
<3

0.57
0.66
0.61

1.50
3-5

0.86
0.88
0.87

1.50
6-17

1.14
1.13
1.14

2.21
18-34

1.33
1.42
1.38

2.57
35-54

1.52
1.59
1.55

2.57
<55

1.53
1.62
1.57

2.29
All Ages

1.31
1.37
1.34

2.36
a Includes tapwater and foods and beverages derived from tapwater.
Source: Canadian Ministry of National Health and Welfare, 198 1 .
                          Table 3-4. Average Daily Total Tapwater Intake of Canadians as a Function of
                                    Level of Physical Activity at Work and in Spare Time
                                      (16 years and older, combined seasons, L/day)
         Activity
          Level"
Consumption11
   L/day
Work
 Number of Respondents
                                                                                     Spare Time
Consumption
   L/day
Number of Respondents
 Extremely Active
 Very Active
 Somewhat Active
 Not Very Active
 Not At All Active
 Did Not State
 TOTAL
    1.72
    1.47
    1.47
    1.27
    1.30
    1.30
          99
         244
         217
          67
          16
          45
         688
    1.57
    1.51
    1.44
    1.52
    1.35
    1.31
        52
        151
        302
        131
        26
        26
        688
  *   The levels of physical activity listed here were not defined any further by the survey report, and categorization of activity level by survey
     participants is assumed to be subjective.
  b   Includes tapwater and foods and beverages derived from tapwater.
  Source: Canadian Ministry of National Health and Welfare, 1981.	
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                                                                          Volume I- General Factors
                                                                 Chapter 3 - Drinking Water Intake
Table 3-5. Average Daily Tapwater Intake by Canadians, Apportioned Among Various Beverages
(both sexes, by age, combined seasons, L/day)a
Age Group (years)

Total Number in Group 34
Water
Ice/Mix
Tea
Coffee
"Other Type of Drink"
Reconstituted Milk
Soup
Homemade Beer/Wine
Homemade Popsicles
Baby Formula, etc.
TOTAL
Under 3
47
0.14
0.01
*
0.01
0.21
0.10
0.04
*
0.01
0.09
0.61
3-5
250
0.31
0.01
0.01
*
0.34
0.08
0.08
*
0.03
*
0.86
6-17
232
0.42
0.02
0.05
0.06
0.34
0.12
0.07
0.02
0.03
*
1.14
18-34
254
0.39
0.04
0.21
0.37
0.20
0.05
0.06
0.04
0.01
*
1.38
35-54
153
0.38
0.03
0.31
0.50
0.14
0.04
0.08
0.07
*
*
1.55
55 and Over

0.38
0.02
0.42
0.42
0.11
0.08
0.11
0.03
*
*
1.57
* Includes tapwater and foods and beverages derived from tapwater.
* Less than 0.0 1 L/day
Source: Canadian Ministry of National Health and Welfare,
1981.




      Data concerning the source of tapwater (municipal,
well, or lake) was presented in one table of the study.
This  categorization  is  not  appropriate  for  making
conclusions about consumption of ground versus surface
water.
      This survey may be more representative. of total
tapwater   consumption   than   some   other   less
comprehensive surveys because it included data for some
tapwater-containing items not covered by other studies
(i.e., ice cubes, popsicles,  and infant formula).  One
potential source of error in the study is that estimated
intake  rates were  based on identification of standard
vessel sizes; the  accuracy of this type of survey data is not
known. The cooler climate of Canada may have reduced
the importance  of large tapwater intakes resulting from
high activity levels, therefore  making the study less
applicable to the United States. The authors were not able
to explain the  surprisingly large -variations between
regional tapwater intakes; the largest regional difference
was between Ontario (1.18 liters/day) and Quebec (1.55
liters/day).
      Ershow and Cantor (1989) - Total Water and
Tapwater Intake in the United States:  Population-Based
Estimates of Quantities and Sources - Ershow and Cantor
(1989) estimated  water  intake rates  based on data
collected by  the USDA  1977-1978 Nationwide Food
Consumption Survey (NFCS).  Daily intake rates for
tapwater and total water were calculated for various age
groups for males, females, and both sexes combined.
Tapwater was defined as  "all water from the household
tap consumed directly as  a beverage or used to prepare
foods and  beverages."   Total  water was defined as
tapwater plus "water intrinsic to foods and beverages"
(i.e., water contained in purchased food and beverages).
The authors  showed  that the age,  sex, and  racial
distribution of the surveyed population closely matched
the estimated  1977 U. S. population.
      Daily total tapwater intake rates, expressed as mL
(grams) per day by age group are presented in Table 3-6.
These data follow a lognormal distribution. The same
data, expressed as mL (grams) per kg body weight per day
are presented in Table 3-7.  A summary of these tables,
showing the mean, the 10th and 90th percentile intakes,
expressed as both mL/day and mL/kg-day as a function of
age, is presented in Table 3-8. This shows that the mean
and 90th percentile intake rates for adults (ages 20 to 65+)
are approximately 1,410 mL/day and 2,280 mL/day and
for all ages the mean and 90th percentile intake rates are
1,190 mL/day and 2,090 mL/day. Note that older adults
have greater intakes than do adults between age 20 and
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                  Exposure Factors Handbook
                 	August 1997

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 Volume I - General Factors
 Chapter 3 - Drinking Water Intake
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                                                     Exposure Factors Handbook
                                                    	        August 1997

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 Volume I - General Factors
 Chapter 3 - Drinking Water Intake

Age Group

Infants (<1 year)
Children (1-10 years)
Teens (11-19 years)
Adults (20 -64 years)
Adults (65+ years)
All ages


Mean
302
736
965
1,366
1,459
1,193
Table 3-8. Summary of Tapwater Intake by
Intake (mL/day)
10th-90th Percentiles
0-649
286-1,294
353-1,701
559-2,268
751-2,287
423-2,092
Age


43.5
35.5
18.2
19.9
21.8
22.6

Intake (mL/kg-day)
10th-90th Percentiles
0 - 100
12.5 - 64.4
6.5 - 32.3
8.0 - 33.7
10.9-34.7
8.2 - 39.8
Source: Ershow and Cantor (1989)
 65, an observation bearing on the interpretation of the
 Cantor, et al. (1987) study which surveyed a population
 that was older than the national average (see Section 3.3).
       Ershow and Cantor  (1989) also  measured total
 water intake for the same age groups and concluded that
 it averaged 2,070 mL/day for all groups combined and
 that tap water intake (1,190 mL/day) is 55 percent of the
 total water intake. (The detailed intake data for various
 age groups are presented in Table 3-9).  Ershow and
 Cantor (1989)  also concluded that, for all age groups
 combined,  the proportion  of tapwater  consumed as
 drinking water, foods, and beverages  is  54 percent, 10
 percent and 36 percent, respectively. (The detailed data
 on proportion of tapwater  consumed for various age
 groups are presented in Table 3-10). Ershow and Cantor
 (1989) also observed  that males of all age groups had
 higher total water and tapwater consumption rates than
                               females; the variation of each from the combined-sexes
                               mean was about 8 percent.
                                     Ershow and Cantor (1989) also presented data on
                               total water intake and tapwater intake for children of
                               various  ages.   They found, for infants and  children
                               between the ages of 6 months and 15 years, that the total
                               water intake per unit body weight increased smoothly and
                               sharply from 30  mL/kg-day  above age 15  years to 190
                               mL/kg-day for ages less than 6 months. This probably
                               represents metabolic requirements for water as a dietary
                               constituent.  However,  they found that the intake of
                               tapwater alone went up only slightly with decreasing age
                               (from 20 to 45 mL/kg-day as age decreases from 11 years
                               to  less than 6 months).  Ershow and Cantor (1989)
                               attributed this small effect of age on tapwater intake to the
                               large number  of  alternative   water  sources  (besides
                               tapwater) used for the younger age groups.
                    Table 3-9. Total Tapwater Intake (as percent of total water intake) by Broad Age Categorya'b
  Age (years)
Mean
                                                       10
                         Percentile Distribution

                         25       50      75
                                                                                      90
                                                                                               95
                                                                                                       99
  1-10
  11-19
  20-64
  65+
 26
 45
 47
 59
 65
 0
 6
 6
12
25
 0
19
18
27
41
 0
24
24
35
47
12
34
35
49
58
22
45
47
61
67
37
57
59
72
74
55
67
69
79
81
62
72
74
83
84
82
81
83
90
90
     Does not include pregnant women, lactating women, or breast-fed children.
     Total tapwater is defined as "all water from the household tap consumed directly as a beverage or used to prepare foods and beverages."
  0 = Less than 0.5 percent.

  Source: Ershow and Cantor, 1989.	
Exposure Factors Handbook
August 1997
                                                                            Page
                                                                              3-7

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                                                                        Volume I - General Factors

                                                                Chapter 3 - Drinking Water Intake
a b
Table 3-10. General Dietary Sources of Tapwater for Both Sexes '
% of Tapwater
Age
(years)



1-10


11-19


20-64


65+

All


Source
Food0
Drinking Water
Other Beverages
All Sources
Food6
Drinking Water
Other Beverages
All Sources
Food0
Drinking Water
Other Beverages
All Sources
Food0
Drinking Water
Other Beverages
All Sources
Food0
Drinking Water
Other Beverages
All Sources
Food0
Drinking Water
Other Beverages
All Sources
* Does not include pregnant women,

11
69
20
100
15
65
20
100
13
65
22
100
8
47
45
100
8
50
42
100
10
54
36
100
Standard
24
37
33

16
25
21

15
25
23

10
26
26

9
23
23

13
27
27

5
0
0
0

0
0
0

0
0
0

0
0
0

0
0
3

0
0
0

25
0
39
0

5
52
0

3
52
0

2
29
25

2
36
27

2
36
14

50
0
87
0

10
70
15

8
70
16

5
48
44

5
52
40

6
56
34

75
10
100
22

19
84
32

17
85
34

11
67
63

11
66
57

13
75
55

95
70
100
100

44
96
63

38
98
68

25
91
91

23
87
85

31
95
87

99
100
100
100

100
100
93

100
100
96

49
100
100

38
99
100

64
100
100

lactating women, or breast-fed children.
k Individual values may not add to totals due to
rounding.






c Food category includes soups.
0 -
Source:
Less than 0.5 percent.
Ershow and Cantor, 1989.
















      With respect to region of the country, the northeast
states had slightly lower average tap water intake (1,200
mL/day) than the  three  other  regions (which were
approximately equal at 1,400 mL/day).
      This survey has an adequately large size (26,446
individuals) and it is a representative sample of the United
States population with respect to age distribution, sex,
racial composition, and residential location. It is therefore
suitable   as   a   description  of  national   tapwater
consumption. The chief limitation of the study is that the
data  were collected  in 1978 and do  not  reflect the
expected increase in the consumption of soft  drinks and
bottled water or changes in the diet within the last two
decades.  Since the data were collected for only a three-
day  period,  the  extrapolation  to chronic  intake  is
uncertain.
      Roseberry and Burmaster (1992)  - Lognormal
Distributions for Water Intake - Roseberry and Burmaster
(1992) fit lognormal distributions to the water intake data
reported  by Ershow  and  Cantor (1989) and  estimated
population-wide  distributions for total fluid  and total
tapwater  intake based  on proportions of the population in
each age  group. Their publication shows the data and the
fitted log-normal  distributions graphically.  The mean
Page
3-8
                  Exposure Factors Handbook •
                                    August 1997

-------
  Volume I - General Factors
  Chapter 3 - Drinking Water Intake
 was estimated as the zero intercept, and the standard
 deviation was estimated as the slope of the best fit line for
 the natural logarithm of the intake rates plotted against
 their corresponding z-scores (Roseberry and Burmaster,
 1992). Least squares techniques were used  to estimate the
 best fit straight lines for the transformed data.  Summary
 statistics  for the best-fit lognormal distribution  are
 presented in Table 3-11.  In this table,  the  simulated
 balanced population represents an adjustment to account
 for the different age distribution  of the  United States
 population in 1988 from the age distribution in  1978 when
 Ershow and Cantor (1989) collected their data.  Table 3-
 12 summarizes the quantiles and means of tap water intake
 as estimated from the best-fit distributions.  The mean
 total tapwater intake rates for the two adult populations
 (age 20 to 65 years, and 65+ years) were estimated to be
 1.27andl.34L/day.
     Table 3-11. Summary Statistics for Best-Fit Lognormal
     	Distributions for Water Intake Ratesa
  Group
  (age in years)
      In Total Fluid
       Intake Rate
          a       R2
  0 < age < 1
  1 s age <11
  11 s age <20
  20 <; age <65
  65 s age
  All ages
6.979
7.182
7.490
7.563
7.583
7.487
  Simulated balanced population 7.492
0.291     0.996
0.340     0.953
0.347     0.966
0.400     0.977
0.360     0.988
0.405     0.984
0.407     1.000
  Group
  (age in years)
    In Total Tapwater
         Intake
   .       a       R2
  0 < age < 1
  1 <. age <11
  11 <; age <20
  20 <; age <65
  65 <; age
  All ages
5.587
6.429
6.667
7.023
7.088
6.870
  Simulated balanced population  6.864
0.615    0.970
0.498    0.984
0.535    0.986
0.489    0.956
0.476    0.978
0.530    0.978
0.575    0.995
    These values (mL/day) were used in the following equations
    to estimate the quantiles and averages for total tapwater intake
    shown in Tables 3-12.
  97.5 percentile intake rate = exp Cu + (1.96 : a)]
  75 percentile intake rate = exp \]j. + (0.6745 • o)l
  50 percentile intake rate = exp J)u]
  25 percentile intake rate = exp [> - (0.6745 • o)]
  2.5 percentile intake rate = exp [^ - (1.96 • a)]
  Mean intake rate - exp fr/ + 0.5 • o2)]
  Source:    Roseberry and  Burmaster, 1992.
       These intake rates were based on the data originally
 presented by Ershow and Cantor (1989). Consequently,
 the same advantages and disadvantages associated with
 the Ershow and Cantor (1989) study apply to this data set.

 3.3.   RELEVANT   GENERAL    POPULATION
       STUDIES ON DRINKING WATER INTAKE
       National Academy of Sciences (1977) - Drinking
 Water and Health - NAS (1977) calculated the average
 per capita water (liquid) consumption per day to be 1.63
 L. This figure was based on a survey of the following
 literature, sources:    Evans  (1941);  Bourne  and
 Kidder (1953); Walker etal. (1957); Wolf (1958); Guyton
 (1968);  McNall  and Schlegel (1968);  Randall (1973);
 NAS (1974); and Pike and Brown (1975). Although the
 calculated  average intake  rate  was 1.63  L per  day,
 NAS  (1977) adopted a larger rate  (2 L per  day)  to
 represent the intake of the majority of water consumers.
 This value is relatively consistent with the total tapwater
 intakes  rate estimated from the key studies presented
 previously. However, the use of the term "liquid" was not
 clearly defined in this study, and it is not known  whether
 the populations surveyed are representative of the adult
 U.S. population.  Consequently, the results of this study
 are of limited use in recommending total tapwater intake
 rates and this study is not considered a key study.
       Hopkins and Ellis  (1980) -  Drinking Water
 Consumption in Great Britain - A study conducted  in
 Great Britain over a 6-week period during September and
 October  1978, estimated the drinking water consumption
 rates of 3,564 individuals  from  1,320 households  in
 England, Scotland, and Wales (Hopkins and Ellis, 1980).
 The participants were selected randomly and were asked
 to complete a questionnaire and a diary indicating  the type
 and quantity of  beverages consumed  over a  1-week
 period. Total liquid intake included total tapwater taken
 at  home and away from  home; purchased  alcoholic
 beverages; and non-tapwater-based drinks.  Total tapwater
 included water content of tea, coffee, and other hot water
 drinks; homemade alcoholic  beverages;  and tapwater
 consumed directly as a beverage. The assumed tapwater
 contents  for these beverages are presented in Table 3-13.
 Based on responses from 3,564 participants, the mean
 intake  rates and frequency distribution data for  various
beverage categories were estimated by Hopkins and Ellis
(1980).  These data are listed in Table 3-14.  The mean
per capita total liquid intake  rate for all  individuals
surveyed was L59 L/day, and the mean per capita total
tapwater  intake rate was 0.95 L/day, with a 90th percentile
Exposure Factors Handbook
August 1997	
                                                                             Page
                                                                               3-9

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                                                                              Volume I - General Factors
                                                                     Chapter 3 - Drinking Water Intake
Table 3-12. Estimated Quantiles and Means for Total Tapwater Intake Rates (mL/day)d
Age Group
(years)
0
-------
Volume I - General Factors
 Chapter 3 - Drinking Water Intake












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                                                  Chapter 3 - Drinking Water Intake









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-------
Volume I - General Factors
Chapter 3 - Drinking Water Intake
Table 3-16. Measured Fluid Intakes (mL/day)
Subject
Adults ("normal" conditions)6
Adults (high environmental
temperature to 32 °C)
Adults (moderately active)
Children (5-14 yr)
a Includes tea, coffee, soft drinks, beer, cider, wine,
b "Normal" conditions refer to typical environmental
Source: ICRP, 1981.
Total Fluids Milk
1000-2400 120-450
2840-3410
3256 ± ...
SD = 900
3700
1000-1200 330-500
1310-1670 540-650
etc.
temperature and activity levels.
Water-Based
Tapwater Drinks2
45-730 320-1450
ca. 200 ca. 380
540-790

      Gillies and Paulin (1983) - Variability of Mineral
Intakes from Drinking Water - Gillies and Paulin (1983)
conducted a study to evaluate variability of mineral intake
from drinking water.  A study population of 109 adults
(75 females; 34 males) ranging in age from 16 to 80 years
(mean age = 44 years)  in New Zealand was asked to
collect duplicate samples of water consumed directly from
the tap or used in beverage preparation during a 24-hour
period. Participants were asked to collect the samples on
a day when all of the water consumed would be from their
own home. Individuals were selected based on their
willingness to participate and their ability to comprehend
the collection procedures. The mean total tapwater intake
rate for this population was 1.25 (±0.39) L/day, and the
90th percentile rate was 1.90 L/day.  The median total
tapwater intake rate (1.26 L/day) was very similar to the
mean intake rate (Gillies and Paulin, 1983). The reported
range was 0.26 to 2.80 L/day.
      The advantage of these data are that they were
generated using duplicate sampling techniques. Because
this approach is more objective than recall methods, it
may result in more accurate response.  However, these
data are  based on  a short-term survey that may not be
representative  of  long-term behavior, the  population
surveyed is small  and the procedures  for selecting the
survey population were not designed to  be representative
of the New Zealand population, and the results may not be
applicable to the United States.  For these reasons the
study is not regarded as a key study in this document.
      Pennington  (1983)  - Revision of the Total Diet
Study Food List and Diets - Based on data from the U.S.
Food and Drug Administration's  (FDA's)  Total  Diet
Study, Pennington (1983) reported average intake rates
for various foods and beverages for five age groups of the
population. The Total Diet Study  is conducted annually
to monitor the nutrient and contaminant content of the
U.S. food supply and to evaluate trends in consumption.
Representative diets were developed based on 24-hour
recall and 2-day diary data from the  1977-1978 U.S.
Department  of Agriculture (USDA) Nationwide Food
Consumption Survey (NFCS) and 24-hour recall data
from the  Second   National  Health  and  Nutrition
Examination Survey (NHANES II),  The number of
participants in NFCS and NHANES II was approximately
30,000  and  20,000,  respectively.   The diets were
developed to "approximate 90 percent or more of the
weight of the foods usually consumed"  (Pennington,
1983).    The  source  of water  (bottled  water   as
distinguished from tapwater)  was  not stated  in  the
Pennington study.  For the purposes of this report,  the
consumption rates for the  food  categories defined by
Pennington (1983) were used to calculate total fluid and
total water intake rates for five age groups. Total water
includes  water, tea, coffee, soft drinks, and soups and
frozen  juices  that  are   reconstituted  with  water.
Reconstituted soups were assumed to be composed of 50
percent water, and juices were  assumed to contain 75
percent water. Total fluids include total water in addition
to milk, ready-to-use infant formula, milk-based soups,
carbonated soft drinks, alcoholic beverages, and canned
fruit juices.  These intake rates are presented in Table
3-17. Based on the average intake rates for total water for
the two adult age groups, 1.04 and 1.26 L/day, the average
adult intake rate is about 1.15 L/day. These rates should
be more representative of the amount of source-specific
water consumed than are total fluid intake rates. Because
this  study was designed to measure food  intake, and it
used both USDA 1978 data and NHANES II data, there
was  not  necessarily  a  systematic  attempt  to  define
tapwater intake per se, as distinguished  from  bottled
Exposure Factors Handbook
August 1997	
                                             Page
                                              3-13

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                                                                                Volume I - General Factors
                                                                       Chapter 3 - Drinking Water Intake
water. For this reason, it is not considered a key tapwater
study in this document.
   Table 3-17. Intake Rates of Total Fluids and Total Tapwater by
  	Age Group	
           Average Daily Consumption Rate (L/day)
       Age Group	Total Fluids3	Total Tapwaterb
      6-11 months
        2 years
      14-16 years
      25-30 years
      60-65 years
0.80
0.99
1.47
1.76
1.63
0.20
0.50
0.72
1.04
1.26
  a   Includes milk, "ready-to-use" formula, milk-based soup,
      carbonated soda, alcoholic beverages, canned juices, water,
      coffee, tea, reconstituted juices, and reconstituted soups.
      Does not include reconstituted infant formula.
  b   Includes water, coffee, tea, reconstituted juices, and
      reconstituted soups.
  Source: Derived from Pennington. 1983.	
       U.S. EPA (1984) - An Estimation of the Daily
Average Food Intake by Age and Sex for Use in Assessing
the Radionuclide Intake  of the General Population  -
Using data collected by USDA in the 1977-78 NFCS,
U.S.  EPA (1984) determined daily food and beverage
intake levels by age to be used in assessing radionuclide
intake through food consumption. Tapwater, water-based
drinks, and soups were identified  subcategories of the
total beverage category. Daily intake rates for tapwater,
water-based drinks, soup, and total beverage are presented
in Table 3-18. As seen in Table 3-18, mean tapwater
intake for different adult age groups  (age 20 years and
older) ranged from 0.62 to 0.76 L/day,  water-based drinks
intake ranged from 0.34 to 0.69 L/day,  soup intake ranged
from 0.03 to 0.06 L/day, and mean total beverage intake
levels ranged from 1.48 to 1.73 L/day.  Total tapwater
intake rates were estimated by  combining  the average
daily intakes of tapwater, water-based drinks, and soups
for each age group. For adults (ages 20 years and older),
mean total tapwater intake rates range from  1.04 to 1.47
L/day, and for children (ages <1 to 19 years), mean intake
rates range from 0.19 to 0.90 L/day. These intake rates do
not  include  reconstituted  infant formula.    The  total
tapwater  intake  rates,  derived  by  combining  data on
tapwater, water-based drinks, and soup should be more
representative  of source-specific drinking water intake
than the total beverage intake rates reported in this study.
These intake rates are based on  the same USDA NFCS
data used in Ershow and Cantor (1989). Therefore, the
data limitations discussed previously also apply to this
study.
       Cantor et al. (1987) - Bladder Cancer, Drinknig
Water Source, and Tapwater Consumption - The National
Cancer Institute (NCI), in a population-based, case control
study investigating the possible relationship between
bladder  cancer   and   drinking   water,   interviewed
approximately 8,000 adult white individuals, 21 to 84
years of  age (2,805 cases  and 5,258 controls) in their
homes, using a standardized questionnaire (Cantor et al.,
1987).  The cases and  controls resided in one of five
metropolitan areas (Atlanta, Detroit, New Orleans, San
                    Table 3-18. Mean and Standard Error for the Daily Intake of Beverages and Tapwater by Age
  Age (years)
  Tapwater Intake
      (mL)
      Water-Based Drinks
           (mL)a
                  Soups
                  (mL)
Total Beverage Intakeb
       (mL)
  All ages
  Under 1
  Ito4
  5to9
  10 to 14
  15 to 19
  20 to 24
  25 to 29
  30 to 39
  40 to 59
  60 and over
   662.5 ±9.9
   170.7 ±64.5
   434.6 ±31.4
   521.0 ±26.4
   620.2 ±24.7
   664.7 + 26.0
   656.4 ± 33.9
   619.8 ± 34.6
   636.5 ± 27.2
   735.3 ±21.1
   762.5 ±23.7
     457.1 ±6.7
     8.3 ±43.7
     97.9 ±21.5
     116.5 ±18.0
     140.0 ± 16.9
     201.5 ±17.7
     343.1 ±23.1
     441.6 ±23.6
     601.0 ±18.6
     686.5 ± 14.4
     561.1 ± 16.2
                45.9 ± 1.2
                10.1 ±7.9
                43.8 ± 3.9
                36.6 ± 3.2
                35.4 ± 3.0
                34.8 ± 3.2
                38.9 ±4.2
                41.3 ±4.2
                40.6 ± 3.3
                51.6 ±2.6
                59.4 ± 2.9
    1434.0 ± 13.7
    307.0 ± 89.2
    743.0 ± 43.5
    861.0 ±36.5
    1025.0 ± 34.2
    1241.0 ±35.9
    1484.0 ±46.9
    1531.0 ±48.0
    1642.0 ± 37.7
    1732.0 ±29.3
    1547.0 ± 32.8
  *    Includes water-based drinks such as coffee, etc. Reconstituted infant formula does not appear to be included in this group.
  b    Includes tapwater and water-based drinks such as coffee, tea, soups, and other drinks such as soft drinks, fruitades, and alcoholic drinks.

  Source:     U.S. EPA, 1984.
Page
3-14
                                                   Exposure Factors Handbook
                                                  	August 1997

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Volume I - General Factors
Chapter 3 - Drinking Water Intake
Francisco, and Seattle) and five States (Connecticut, Iowa,
New Jersey, New Mexico, and Utah).  The individuals
interviewed were asked to recall the level of intake of
tapwater and other beverages in a typical week during the
winter prior to the interview. Total beverage intake was
divided into the following two components:  1) beverages
derived from tapwater; and 2) beverages from other
sources. Tapwater used in cooking foods and in ice cubes
was apparently not considered.  Participants also supplied
information on the primary source of the water consumed
(i.e., private well, community supply, bottled water, etc.).
The control population was randomly selected from the
general population and frequency matched to the bladder
cancer  case  population in terms of  age,  sex,  and
geographic location of residence.  The case population
consisted of Whites only, had no people under the age of
21 years and 57 percent were  over the age of 65 years.
The fluid intake rates for the bladder cancer cases were
not used because their participation in the study was based
on selection factors that could bias the intake estimates for
the general population.  Based on responses from 5,258
White controls  (3,892 males;  1,366 females), average
tapwater intake rates for a "typical" week were compiled
by sex, age group, and geographic region.  These rates are
listed in Table 3-19.  The average total fluid intake rate
was 2.01 L/day  for men of which 70 percent (1.4 L/day)
was derived from tapwater, and 1.72 L/day for women of
which 79 percent (1.35 L/day) was derived from tapwater.
Frequency distribution data for the 5,081  controls, for
which the authors had information on  both tapwater
consumption and cigarette smoking habits, are presented
in Table 3-20. These data follow a lognormal distribution
having an average value of 1.30 L/day and an upper 90th
percentile  value of approximately 2.40  L/day.  These
values were determined by graphically interpolating the
data of Table 3-20 after plotting it on log probability
graph paper.  These values represent the usual level of
intake for this population of adults in the winter.
       A limitation associated with this data set is that the
population surveyed was older than the general population
and consisted exclusively of Whites. Also, the intake data
are based on recall of behavior from the winter previous
to the interview.  Extrapolation to other seasons and
intake durations is difficult.
       The authors presented  data on person-years of
residence  with  various  types  of water supply sources
(municipal   versus    private,   chlorinated   versus
nonchlorinated,  and  surface  versus  well  water).
Unfortunately,  these  data  can  not  be  used to  draw
conclusions about the National average apportionment of
surface versus groundwater since a large fraction (24
percent) of municipal water intake in this survey could not
be  specifically  attributed to either ground or surface
water.
     Table 3-19. Average Total Tapwater Intake Rate by Sex
     	Age, and Geographic Area	
 Group/Subgroup
  Number of
 Respondents
  Average Total
Tapwater Intake,a'b
     L/day
 Total group
 Sex
   Males
   Females
 Age, years
   21-44
   45-64
   65-84
 Geographic area
   Atlanta
   Connecticut
   Detroit
   Iowa
   New Jersey
   New Mexico
   New Orleans
   San Francisco
   Seattle
   Utah
    5,258

    3,892
    1,366

     291
    1,991
    2,976

     207
     844
     429
     743
    1,542
     165
     112
     621
     316
     279
      1.39

      1.40
      1.35.

      1.30
      1.48
      1.33

      1.39
      1.37
      1.33
      1.61
      1.27
      1.49
      1.61
      1.36
      1.44
      1.35
  a   Standard deviations not reported in Cantor et al. (1987).
  b   Total tapwater defined as all water and beverages derived
     from tapwater.
  Source: Cantor et al.. 1987.	
          Table 3-20.  Frequency Distribution of Total
                  Tapwater Intake Rates3
    Consumption
    Rate (L/day)
Frequency15 (%)
   Cumulative
 Frequency1" (%)
       <;0.80
     0.81-1.12
     1.13-1.44
     1.45-1.95
       a 1.96
    20.6
    21.3
    20.5
    19.5
    18.1
     20.6
     '41.9
     62.4
     81.9
     100.0
  a  Represents consumption of tapwater and beverages derived
    from tapwater in a "typical" winter week.
  b  Extracted from Table 3 in Cantor etal. (1987).

  Source:  Cantor, etal., 1987.
      AIHC (1994) - Exposure Factors Handbook- The
Exposure Factors Sourcebook (AIHC, 1994) presented
Exposure Factors Handbook
August 1997	
                                               Page
                                                3-15

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                                                                          Volume I - General Factors
                                                                  Chapter 3 - Drinking Water Intake
drinking water intake rate recommendations for adults.
Although AIHC (1994) provided little information on the
studies used to derive mean and upper percentile recom-
mendations, the references indicate that several of the
studies used were the same as ones categorized as relevant
studies in this handbook. The mean adult drinking water
recommendations in AIHC (1994) and this handbook are
in agreement.  However, the upper percentile value
recommended by AIHC (1994) (2.0  L/day) is slightly
lower than that recommended by this  handbook  (2.4
L/day). Based on data provided by Ershow and Cantor
(1989), 2.0 L/day corresponds to only approximately the
84th  percentile of  the  drinking water  intake  rate
distribution. Thus, a slightly higher value is appropriate
for representing the  upper percentile (i.e., 90 to 95th
percentile) of the distribution. AIHC (1994)  also presents
simulated distributions of drinking water intake based on
Roseberry and Burmaster (1992). These distributions are
also described in detail in Section 3.2 of this handbook.
AIHC (1994) has been classified as a relevant rather than
a key study because  it is not the primary source for the
data used to make recommendations for this document.
      USDA  (1995) -  Food and Nutrient Intakes  by
Individuals in the United States, 1 Day, 1989-91. - USDA
(1995) collected data on the quantity of "plain drinking
water" and  various other beverages  consumed  by
individuals in  1 day during 1989 through 1991. The data
were collected as part of USDA's Continuing Survey of
Food Intakes  by Individuals (CSFII).  The data used to
estimate mean per capita intake rates combined one-day
dietary recall  data from 3 survey years: 1989, 1990, and
1991 during which 15,128 individuals supplied one-day
intake data. Individuals from all income levels in the 48
conterminous  states and Washington D.C. were included
in the sample.  A complex three-stage sampling design
was employed and the overall response rate for the study
was 58 percent.  To minimize the biasing effects of the
low response  rate and adjust for the seasonality, a series
of weighting factors was incorporated into the data
analysis.   The intake  rates  based on  this study are
presented in Table 3-21. Table 3-21 includes data for: a)
"plain drinking water", which might be assumed to mean
Table 3-21 Mean Per Capita Drinking Water Intake Based on USDA, CSFII Data From
Sex and Age
(years)
Males and Females:
Under 1
1-2
3-5
5 & Under
Males:
6-11
12-19
20-29
30-39
40-49
50-59
60-69
70-79
80 and over
20 and over
Females:
6-11
12-19
20-29
30-39
40-49
50-59
60-69
70-79
80 and over
20 and over
AH individuals
a Includes regular and
Plain Drinking
Water

194
333
409
359

537
725
842
793
745
755
946
824
747 .
809

476
604
739
732
781
819
829
772
856
774
711
low calorie fruit drinks,
1989-91
(mL/day)
Fruit Drinks
Coffee Tea and Adesa

0
<0.5
2
1

2
12
168
407
534
551
506
430
326
408

1
21
154
317
412
438
429
324
275
327
260
punches, and ades,

<0.5
9
26
17

44
95
136
136
149
168
115
115
165
139

40
87
120
136
174
137
124
161
149
141
114
including those made from powdered

17
85
100
86

114
104
101
50
53
51
34
45
57
60

86
87
61
59
36
37
36
34
28
46
65
mix and
Total

211.5
427.5
537
463

697
936
,247
,386
,481
,525
,601
,414
,295
,416

603
799
1,074
1,244
1,403
1,431
1,418
1,291
1,308
1,288
1,150
frozen concentrate.
Excludes fruit juices and carbonated drinks.
Source: USDA, 1995.





Page
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                  Exposure Factors Handbook
                 	August 1997

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Volume I - General Factors
Chapter 3 - Drinking Water Intake
tapwater directly consumed rather than bottled water; b)
coffee and tea, which might be assumed to be constituted
from tapwater; and 3) fruit drinks and ades, which might
be assumed to be reconstituted from tapwater rather than
canned products; and 4) the total of the three sources.
With these assumptions, the mean per capita total intake
of water is estimated to be 1,416 mL/day for adult males
(i.e., 20 years of age and older), 1,288 mL/day for adult
females  (i.e., 20 years of age and older) and 1,150
mL/day for all ages and both sexes combined.  Although
these assumptions appear reasonable, a close reading of
the definitions used by USDA (1995) reveals that the
word "tapwater" does not  occur, and this uncertainty
prevents the use of this study as a key study of tapwater
intake.
     The  advantages of using these data are that; 1) the
survey had a large sample size; 2) the authors attempted
to represent  the general United  States population  by
oversampling low-income groups and by weighting the
data to compensate for  low response rates;  and 3) it
reflects more recent intake data than the key studies. The
disadvantages are that: 1) the response rate was low; 2)
the word "tapwater" was not defined and the assumptions
that must be used in order to compare the data with the
other tapwater  studies might not be valid; 3) the data
collection period reflects only a  one-day intake period,
and  may  not reflect long-term drinking water intake
patterns; and 4) data on the percentiles of the distribution
of intakes were riot given.
     Tsang and Klepeis (1996) - National  Human
Activity Pattern Survey (NHAPS) -  The U.S. EPA
collected information on the number of glasses of drinking
water and juice reconstituted with tapwater consumed by
the general population as part of the National Human
Activity Pattern  Survey (Tsang and Klepeis,  1996).
NHAPS was  conducted between  October 1992 and
September 1994.   Over 9,000 individuals in the  48
contiguous United States provided data on the duration
and frequency of selected activities and the time spent in
selected microenvironments via 24-hour diaries.  Over
4,000 NHAPS respondents also provided information of
the number of 8-ounce glasses of water and the number of
8-ounce glasses of juice reconstituted with water than they
drank during the 24-hour survey period (Tables 3-22 and
3-23).  The median number  of glasses  of tapwater
consumed was 1-2 and the median number of glasses of
juice with tapwater consumed was 1-2.
      For both  individuals  who  drank tapwater  and
individuals who drank juices reconstituted with tapwater,
the number of glasses ranged from 1 to 20. The highest
percentage of the population (37.1 percent) who drank
tapwater consumed 3-5 glasses and the highest percentage
of the population (51.5 percent) who consumed juice
reconstituted with tapwater drank 1-2 glasses.  Based on
the assumption that each glass  contained 8 ounces of
water (226.4 mL), the total volume of tapwater and juice
with tapwater  consumed would range from 0.23 L/day (1
glass) to 4.5 L/day (20 glasses) for respondents who drank
tapwater.  Using the same assumption, the volume of
tapwater consumed for the population who consumed 3-5
glasses would be 0.68 L/day to 1.13 L/day and the volume
of juice with tapwater consumed for the  population  who
consumed 1-2 glasses would be 0.23 L/day to 0.46  L/day.
Assuming that the  average  individual consumes  3-5
glasses of tapwater plus 1-2 glasses of juice with tapwater,
the range of total tapwater intake for this individual would
range from 0.9 L/day to 1.64 L/day.  These values are
consistent with the average intake rates observed in other
studies.
      The advantages of NHAPS is that the data were
collected for  a large number of individuals and that the
data are representative of the U.S. population.  However,
evaluation of drinking water intake rates was not the
primary purpose of the study and the data do not reflect
the total volume of tapwater consumed.  However, using
the assumptions described above, the estimated drinking
water intake  rates from this  study are within the same
ranges observed for other drinking water studies.

3.4.   PREGNANT AND LACTATING WOMEN
      Ershow et al.  (1991) - Intake of Tapwater and
Total Water by Pregnant and Lactating Women - Ershow
et al.  (1991) used data from the 1977-78  USDA MFCS 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
Exposure Factors Handbook
August 1997            	
                                             Page
                                              3-17

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                                                         Volume I - General Factors
                                                   Chapter 3 - Drinking Water Intake
Table 3-22. Number of Respondents that Consumed Tapwater at a Specified Daily Frequency

Population Group
Overall
Gender
Male
Female
Refused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
"NO" —
Yes
DK
Refused
Employment
Full-time
Part-time
Not Employed
Refused
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Rceion
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
No
Yes
DK
NOTE: "•"» Missing Data
"DK" » Don't know
N » sample size
Number of Glasses in a Day
Total N
4,663

2,163
2,498
2

263
348
326
2,972
670

3,774
463
77
96
193
60

4,244
347
26
46

2,017
379
1,309
32
399
1,253
895
650
445

1,048
1,036
1,601
978

3,156
1,507

1,264
1,181
1,275
943

4,287
341
35

4,500
125
38

4,424
203
36



None
1,334

604
728
2

114
90
86
908
117

1,048
147
25
36
63
15

1,202
116
5
11

637
90
313
6
89
364
258
195
127

351
243
450
290

864
470

398
337
352
247

1,232
96
6

1,308
18
8

1,280
48
6



1-2
1,225

582
643
•

96
127
109
751
127

1,024
113
18
18
42
10

1,134
80
6
5

525
94
275
4
95
315
197
157
109

262
285
437
241

840
385

321
282
323
299

1,137
83
5

1,195
25
5

1,161
55
9



3-5
1,253

569
684
•

40
86
88
769
243

1,026
129
23
22
40
13

1,162
73
7
11

497
120
413
11
118
330
275
181
113

266
308
408
271

862
391

336
339
344
234

1,155
91
7

1,206
40
7

1,189
58
6



6-9
500

216
284
•

7
15
22
334
112

416
38
6
6
28
6

451
41
4
4

218
50
188
1
51
132
118
82
62

95
127
165
113

334
166

128
127
155
90

459
40
1

470
27
3

474
24
2



10-19
151

87
64
•

1
7
7-
115
20

123
9
1
7
10
1

129
18
3
1

72
13
49
2
14
52
31
19
16

32
26
62
31

96
55

45
33
41
32

134
16
1

143
6
2

142
9
•



20+
31

25
6
•

0
2
• •
26
2

25
1
•
2
2
1

26
4
•
1

18
7
3
1
2
13
5
4
3

7
9
11
4

27
4

5
10
9
7

29
1
1

29
1
1

29
1
1



DK
138

65
73
•

5
20
11
54
42

92
21
4
5
7
9

116
13
1
8

40
5
54
4
28
37
9
6
12

28
33
, 57
20

106
32

26
40
40
32

115
13
10

123
6
9

124
5
9



Refused = respondent refused to answer
Source: Tsang and Kleipeis,
1996







Page
3-18
 Exposure Factors Handbook
	August 1997

-------
 Volume I - General Factors
 Chapter 3 - Drinking Water Intake
Table 3-23. Number of Respondents that Consumed Juice Reconstituted with Tapwater at a Specified Daily Frequency
Number of Glasses in a Day
Population Group
Overall
Gender
Male
Female
Refused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
Full-time
Part-time
Not Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
No •
Yes
DK
NOTE: "•" = Missing Data
"DK" = Don't know
N = sample size
Total N
4,663

2,163
2,498
2

263
348
326
2,972
670

3,774
463
77
96
193
60

4,244
347
26
46

2,017
379
1,309
32

399
1,253
895
650
445

1,048
1,036
1,601
978

3,156
1,507

1,264
1,181
1,275
943

4,287
341
35

4,500
125
38

4,424
203
36



None
1,877

897
980
•

126
123
112
1,277
206

1,479
200
33
46
95
24

1,681
165
11
20

871
156
479
15

146
520
367
274
182

440
396
593
448

1,261
616

529
473
490
385

1,734
130
13

1,834
31
12

1,782
84
11



1-2 '"
1,418

590
• 826
2

71
140
118
817
252

1,168
142
27
19
51
11

1,318
87
6
7

559
102
426
4

131
355
253
, 201
130

297
337
516
268

969
449

382
382
389
265

1,313
102
3

1,362
53
3

1,361
53
4



3-5
933

451
482
«

48
58
63
614
133

774
83
15
24
30
7

863
61
5
4

412
88
265
4

82
254
192
125
92

220
200
332
181

616
307

245
215
263
210

853
74
6

900
25
8

882
44
7



6-9
241

124
117
*

11
12
18
155
43

216
15
1
2
5
2

226
14
•
1

103
19
75
2

25
68
47
31
26

51
63
84
43

162
79

66
54
68
53

216
25
•

231
7
3

230
10
1



10-19
73

35
38
•

4
2
7
46
12

57
9
•
1
5
1

64
7
1
1

32
7
20
1

7
21
18
7
5

13
17
26
17

51
22

23
19
18
13

69
3
1

67
5
1

65
6
2



20+
21

17
4
•

1
1
1
16
2

16
1
•
3
1
•

17
4
•
•

9
2
7
•

2
7
5
1
3

4
4
10
3

11
10

4
8
6
3

20
1
•

20
1
•

21
•
•



DK
66

33
33
•

2
11
4
30
14

44
7
0
1
5
9

49
7
3
7

20
5
21
3 .

4
17
11
5
4

15
14
28
9

46
20

10.
17
28
11

55
5
6

59
1
6

57
3
6



Refused = Respondent refused to answer
Source: Tsang and Klepeis,
1996







.Exposure Factors Handbook
August 1997	
Page
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                                                                          Volume I - General Factors
                                                                  Chapter 3 - Drinking Water Intake
presented in  Tables  3-24  and  3-25,  respectively.
Lactating women had the highest mean total fluid intake
rate (2.24 L/day) compared with both pregnant women
(2.08 L/day) and control women (1.94 L/day). Lactating
women also had a higher mean total tapwater intake rate
(1.31  L/day) than  pregnant women  (1.19 L/day) and
control women (1.16 L/day). The tapwater distributions
are neither normal  nor lognormal, but lactating women
had a higher mean tapwater intake than controls and
pregnant women. Ershow et al. (1991) also reported that
rural women (n=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
these data sets (Section 3.2). A further advantage of this
study is that it provides information on estimates of total
waterand tapwater intake rates for pregnant and lactating
women.  This topic has rarely  been addressed in the
literature.

3.5.   HIGH ACTIVITY LEVELS/HOT CLIMATES
      McNall and Schlegel (1968)  -  Practical Thermal
Environmental Limits for Young Adult Males Working in
Hot, Humid Environments - McNall and Schlegel (1968)
conducted  a study  that evaluated  the physiological
tolerance of adult males working under varying degrees of
physical activity. Subjects were required to pedal pedal-
driven propeller  fans for 8-hour work cycles under
varying environmental conditions. The activity pattern for
each individual was: cycled at 15 minute pedalling and  15
miute rest for each 8-hour period.  Two  groups of eight
subjects each were used.  Work rates were divided into
three categories as follows:   high activity level [0.15
horsepower (hp) per person], medium activity level (0.1
Table 3-24. Total Fluid Intake of Women 15-49 Years Old
Percentile Distribution
Reproductive
Status"
mLAlav
Control
Pregnant
Lactating
rnL/kg/dav
Control
Pregnant
Lactating
Mean
1940
2076
2242
32.3
32.1
37.0
Standard
Deviation
686
743
658
12.3
11.8
11.6
5
995
1085
1185
15.8
16.4
19.6
10
1172
1236
1434
18.5
17.8
21.8
a Number of observations: nonpregnant, nonlactating controls (n = 6,201);
Source: Ershow etal., 1991.
25
1467
1553
1833
23.8
17.8
21.8
pregnant (n =
50
1835
1928
2164
30.5
30.5
35.1
188); lactating (n
75
2305
2444
2658
38.7
40.4
45.0
= 77).
90
2831
3028
3169
48.4
48.9
53.7

95
3186
3475
3353
55.4
53.5
59.2

three groups of women (Table 3-25).  Drinking water
accounted for the largest single proportion of the total
fluid  intake  for  control  (30 percent), pregnant  (34
percent), and lactating women (30 percent) (Table 3-26).
All   other   beverages   combined   accounted   for
approximately 46 percent, 43 percent, and 45 percent of
the total water intake for control, pregnant, and lactating
women, respectively. Food accounted for the remaining
portion of total water intake.
      The same advantages and limitations associated
with the Ershow and Cantor (1989) data also apply to
hp  per  person), and  low activity level (0.05 hp  per
person). Evidence of physical stress (i.e., increased body
temperature,  blood pressure, etc.) was  recorded, and
individuals were eliminated from further testing if certain
stress criteria were met. The amount of water consumed
by  the test subjects during the work cycles was also
recorded.   Water  was provided  to the individuals on
request.  The water intake rates obtained  at the three
different activity levels and the various  environmental
temperatures  are  presented in Table 3-27.  The data
Page
3-20
                  Exposure Factors Handbook
                  	August 1997

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Volume I - General Factors
Chapter 3 - Drinking Water Intake
Table 3-25. Total Tapwater Intake of Women 15-49 Years Old
Reproductive
Status"
mL/day
Control
Pregnant
Lactating
mL/kg/day
Control
Pregnant
Lactating
Fraction of daily fluid
Control
Pregnant
Lactating
Percentile Distribution
Mean
1157
1189
1310
19.1
18.3
21.4
Standard
Deviation
635
699
591
10.8
10.4
9.8
5
310
274
430
5.2
4.9
7.4
10
453
419
612
7.5
5.9
9.8
25
709
713
855
11.7
10.7
14.8
50
1065
1063
1330
17.3
16.4
20.5
75
1503
1501
1693
24.4
23.8
26.8
90
1983
2191
1945
33.1
34.5
35.1
95
2310
2424
2191
39.1
39.6
37.4
intake that is tapwater (%)
57.2
54.1
57.0
18.0
18.2
15.8
24.6
21.2
27.4
32.2
27.9
38.0
a Number of observations: nonpregnant, nonlactating controls (n = 6,201);
Source: Ershowetal., 1991.
45.9
42.9
49.5
pregnant (n
59.0
54.8
58.1
= 188);
70.7
67.6
65.9
lactating (n
79.0
76.6
76.4
= 77).
83.2
83.2
80.5

Table 3-26. Total Fluid (mL/Day) Derived from Various Dietary Sources by Women Aged 15-49 Years3
Control Women


Sources
Drinking Water
Milk and Milk Drinks
Other Dairy Products
Meats, Poultry, Fish, Eggs
Legumes, Nuts, and Seeds
Grains and Grain Products
Citrus and Noncitrus Fruit Juices
Fruits, Potatoes, Vegetables, Tomatoes
Fats, Oils, Dressings, Sugars, Sweets
Tea
Coffee and Coffee Substitutes
Carbonated Soft Drinks0
Noncarbonated Soft Drinks0
Beer
Wine Spirits, Liqueurs, Mixed Drinks
All Sources
a Number of observations: nonpregnant,

Mean5

583
162
23
126
13
90
57
198
9
148
291
174
38
17
10
1940
Percentile

50
480
107
8
114
0
65
0
171
3
0
159
no
0
0
0
NA
nonlactating controls (n =

95
1440
523
93
263
77
257
234
459
41
630
1045
590
222
110
66
NA
Pregnant Women

Meanb

695
308
24
121
18
98
69
212
9
132
197
130
48
7
5
2076
6,201); pregnant (n = 188);
Percentile

50
640
273
9
104
0
69
0
185
3
0
0
73
0
0
0
NA

95
1760'
749,
93
252
88
246
280
486
40
617
955
464 '
257
0
25
NA.

Mean"

677
306
36
133
15
!l9
64
245
10
253
205
117
38
17
6
2242
Lactating Women
Percentile

50
560
285
27
117
0
82
0
197
6
77
80
57
0
0
0
NA

95
1600
820
113
256
72
387
219
582
50
848
955
440
222
147
59
NA
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 .









fxposure Factors Handbook
August 1997	
Page
3-21

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                                                                          Volume I - General Factors
                                                                  Chapter 3 - Drinking Water Intake
Table 3-27. Water Intake at Various Activity Levels (L/hr)a
Room
Temperature1* (°F)
Activity Level
High_(QJ.5 hp/man)c Medium (0.10 hp/man)c
No.d
100
95 18
90 7
85 7
80 16
Intake No. Intake
„
0.540 12 0.345
(0.31) (0.59)
0.286 7 0.385
(0.26) (0.26)
0.218 16 0.213
(0.36) (0.20)
0.222
(0.14)

Low (0.05 hp/man)c
No. Intake
15 0.653
(0.75)
6 0.50
(0.31)
16 0.23
(0.20)
—
-
* Data expressed as mean intake with standard deviation in parentheses.
b Humidity = 80 percent; air velocity = 60 ft/min.
c The symbol "hp" refers to horsepower.
d Number of subjects with continuous data.
Source: McNall and Schlegel, 1968.
presented are for test subjects with continuous data only
(i.e., those test subjects who were not eliminated at any
stage of the study as a result of stress conditions).  Water
intake was  the highest at  all activity  levels when
environmental temperatures  were increased. The highest
intake rate was observed at the low activity level at 100° F
(0.65 L/hour) however, there were no data for  higher
activity levels at 100°F. It should be noted that this study
estimated intake on an hourly basis during various levels
of physical activity. These hourly intake rates cannot be
converted to daily intake  rates by multiplying  by 24
hours/day because they are  only representative of intake
during the specified activity levels and the intake rates for
the rest of the day are not known. Therefore, comparison
of intake rate values from this study cannot be made with
values from the previously described studies on drinking
water intake.
       United States Army (1983) - Water Consumption
Planning Factors Study - The U.S. Army has developed
water consumption planning factors to enable them to
transport an adequate amount of water to soldiers in the
field under various conditions (U.S. Army, 1983). Both
climate and activity levels were used to determine the
appropriate  water consumption  needs.   Consumption
factors have been established for the following uses:
1) drinking,  2)  heat  treatment, 3) personal hygiene,
4) centralized hygiene, 5) food preparation, 6) laundry,
7) medical treatment, 8) vehicle and aircraft maintenance,
9) graves  registration, and  10) construction.   Only
personal drinking water consumption factors are described
here.
      Drinking water consumption planning factors are
based on the estimated amount of water needed to replace
fluids lost by urination, perspiration, and respiration. It
assumes that water lost to urinary output averages one
quart/day (0.9 L/day) and perspiration losses range from
almost  nothing  in a  controlled environment  to  1.5
quarts/day  (1.4  L/day) in  a very hot  climate where
individuals are performing strenuous work. Water losses
to respiration are typically very  low except in extreme
cold where water losses can range from 1  to 3 quarts/day
(0.9 to 2.8 L/day). This occurs when the humidity of
inhaled air is near zero, but expired air is 98 percent
saturated  at body temperature  (U.S.  Army,  1983).
Page
3-22
                   Exposure Factors Handbook
                  	August 1997

-------
 Volume I - General Factors
 Chapter 3 - Drinking Water Intake
 Drinking water is defined by the U.S. Army (1983) as "all
 fluids consumed by individuals to satisfy body needs for
 internal water."  This includes soups, hot and cold drinks,
 and tapwater. Planning factors have been established for
 hot, temperate, and cold climates based on the following
 mixture of activities among the work force: 15 percent of
 the force performing light work, 65 percent of the force
 performing medium work, and 20 percent of the force
 performing heavy work.  Hot climates are defined as
 tropical and arid areas where the temperature is greater
 than 80°F. Temperate climates are defined as areas where
 the mean daily  temperature ranges  from 32°F to 80°F.
 Cold regions are areas where the mean daily temperature
 is less than 32 °F. Drinking water consumption factors for
 these three climates are presented in Table 3-28. These
 factors are based on research on individuals and small unit
 training exercises.   The estimates are assumed to be
 conservative because they are rounded up to account for
 the subjective nature of the activity mix and minor water
 losses that are not considered (U.S. Army, 1983).  The
 advantage of using  these data  is that they provide  a
 conservative estimate of drinking water  intake among
 individuals performing at various levels of physical
 activity in hot, temperate, and cold climates. However,
 the planning factors  described  here are  based on
 assumptions about water loss from urination, perspiration,
 and respiration, and are not based on survey data or actual
 measurements.

 3.6. RECOMMENDATIONS
     The key studies described in this section were  used
 in  selecting recommended  drinking water  (tapwater)
     consumption rates for adults and children. The studies on
     other subpopulations were not classified as key versus
     relevant.    Although  different  survey  designs  and
     populations were utilized  by key and relevant studies
     described in this report, the mean and upper-percentile
     estimates reported in these studies are reasonably similar.
     The general design of both key and relevant studies and
     their limitations are summarized in Table 3-29.  It should
     be noted that studies that surveyed large representative
     samples of the population provide more reliable estimates
     of intake rates for the general population.  Most  of the
     surveys described here are based on short-term  recall
     which may  be biased toward  excess  intake  rates.
     However, Cantor et al. (1987) noted that retrospective
     dietary   assessments   generally  produce  moderate
     correlations with "reference data from the past."  A
     summary of the recommended values for drinking water
     intake rates is presented in Table 3-30.
           Adults - The total tapwater consumption rates for
     adults (older than 18 or 20 years) that have been reported
     in the key surveys can be summarized in Table 3-31.  For
     comparison,  values  for daily tapwater intake for the
     relevant studies are shown in Table 3-32.
           Note  that both  Ershow and Cantor (1989)  and
     Pennington (1983) found that adults above 60 years of age
     had larger intakes than younger adults. This is difficult to
     reconcile with the Cantor et al. (1987) study because the
     latter, older population had a smaller average intake.
     Because of these results, combined with the fact that the
     Cantor et al.  (1987)  study was not  intended  to be
     representative of the U. S. population, it is not included
     here in the determination of the recommended value. The
                          Table 3-28. Planning Factors for Individual Tapwater Consumption
         Environmental Condition
                                       Recommended Planning Factor (gal/day)a
                       Recommended Planning Factor (L/day)a'b
                 Hot
              Temperate
                Cold
3.0C
1.5"
2.0e
11.4
5.7
7.6
  a  Based on a mix of activities among the work force as follows:  15% light work; 65% medium work; 20% heavy work. These factors
    apply to the conventional battlefield where no nuclear, biological, or chemical weapons are used.
  b  Converted from gal/day to L/day.
  c  This assumes 1 quart/12-hour rest period/man for perspiration losses and 1 quart/day/man for urination plus 6 quarts/12-hours light
    work/man, 9 quarts/12-hours moderate work/man, and 12 quarts/12-hours heavy work/man.
    This assumes 1 quart/12-hour rest period/man for perspiration losses and 1 quart/day/man for urination plus 1 quart/12-hours light
    work/man, 3 quarts/12-hours moderate work/man, and 6 quarts/12-hours heavy work/man.
  e  This assumes 1 quart/12-hour rest period/man for perspiration losses, 1 quart/day/man for urination, and 2 quarts/day/man for respiration
    losses plus 1 quart/12-hours light work/man, 3 quarts/12-hours moderate work/man, and 6 quarts/6-hours heavy work/man.

  Source: U.S. Army, 1983.		
Exposure Factors Handbook
August 1997	
                                                    Page
                                                    3-23

-------
                                                       Volume I - General Factors
                                                 Chapter 3 - Drinking Water Intake
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Page
                    Exposure Factors Handbook
                     	August 1997

-------
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 Chapter 3 - Drinking Water Intake













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Exposure Factors Handbook
August 1997	
Page
3-25

-------
                                                                               Volume I - General Factors

                                                                      Chapter 3 - Drinking Water Intake
                             Table 3-30.  Summary of Recommended Drinking Water Intake Rates
                                                               'Percentiles
Age Group/
   mlation
     Mean
                       50th
                                       ,90th
                                                       95th
                                                   Multiple
                                                                                  Fitted
                                                                               ^Distributions
<3 years0
3-5 years'
I-10 years*

11-19 years"

Adults"

Pregnant Women'd

Lactating Women4

Adults in High
Activity/Hot Climate
Conditions*
 Active Adultsf
   0.30 L/day
  44 mL/kg-day
   0.61 L/day
   0.87 L/day
   0.74 L/day
  35 mL/kg-day
   0.97 L/day
  18 mL/kg-day
    1.4 L/day
  21 mL/kg-day
    1.2 L/day
  18.3 mL/kg-day
    1.3 L/day
  21.4 mL/kg-day
0.21 to 0.65 L/hour,
                                          0.24 L/day
                                        35 mL/kg-day
    0.66 L/day
   31 mL/kg-day
    0.87 L/day
   16 mL/kg-day
     1.3 L/day
   19 mL/kg-day
     1.1 L/day
   16 mL/kg-day
     1.3 L/day
   21 mL/fcg-day
  0.65 L/day
 102 mL/kg-day
   1.5 L/day
   1.5 L/day
   1.3 L/day
 64niL/kg-day
   1.7 L/day   '
* 32 mL/kg-day
   2.3 L/day
 34 mL/kg-day
 , 2.2 L/day
 35 mL/kg-day
 - 1.9 L/day
 35 mL/kg-day
                                     0.76 L/day
                                   127 mL/kg-day
  1.5 L/day
  2.0 L/day -
40 mL/kg-day
  2.4 L/day
40 mL/kg-day
 '2.2 L/day
"37 mL/kg-day
depending on ambient temperature and activity level; see Table 3
 Tables 3-6, '
 3-7, and 3-8
  Table3-3   ,
  Table3-3 -
 Tables 3-6,
 3-7, and 3-8 '
 Tables 3-6,
 3-7, and 3-8
 Tables 3-6,
 3-7, and 3-8
 Table 3-25  ,

 Table 3-25  '

i-27.
Table 3-llb




Table 3-1 lh

Table 3-1 lb

Table 3-1 lb
6 L/day (temperate climate) to 11 L/day (hot climate); see Table 3-28.
 a   Source: Ershow and Cantor, 1989
 b   Source: Roseberry and Burmaster, 1992
 c   Source: Canadian Ministry of Health and Welfare, 1981
 d   Ershow et a!. (1991) presented data for pregnant women, lactating women, and control women.
 c   Source: McNall and Schlegal, 1968
              . Armv. 1983	
Table 3-31. Total Tapwater Consumption Rates From Key Studies
Mean
cL/dav)
1.38
1.41
90th
Percentile
(Udav)
2.41
2.28
Number in
Survey
639
11,731
Reference
Canadian Ministry of Health
and Welfare, 1981
Ershow and Cantor, 1989
Table 3-32. Daily Tapwater Intake Rates From Relevant Studies
Mean (LMay)
1.30s
1.63 (calculated)
1.25
1.04 (25 to 30 yrs)
1,26 (60(o 65 yrs)
1.04-1 .47 (ages 20+)
1.37 (20 to 64 yrs)
1.46 (65+ yrs)
1.15
107
" Age of the Cantor et al.
average.
90th
Percentile
2.40
1.90
2.27
2.29
1.87
Reference
Cantor etal., 1987
NAS, 1977
Gillies and Paulin, 1983
Pennington, 1983
Pennington, 1983
U.S. EPA, 1984
Ershow and Cantor, 1989
Ershow and Cantor, 1989
USDA, 1995
Hopkins and Ellis. 1980
(1987) population was higher than the U.S.
                                                           USDA (1995) data are not included because tapwater was
                                                           not defined in the survey and because the response rate
                                                           was low, although the results (showing lower intakes than
                                                           the studies based on older  data)  may be  accurately
                                                           reflecting an expected lower use of tapwater (compared to
                                                           1978) because of increasing use of bottled water and soft
                                                           drinks in recent years.
                                                                  A value  of 1.41 L/day, which is the population-
                                                           weighted mean of the two  national studies (Ershow and
                                                           Cantor,  1989 and  Canadian Ministry of Health and
                                                           Welfare, 1981) is the recommended average tapwater
                                                           intake rate.
                                                                  The average of the 90th percentile values from the
                                                           same two studies (2.35  L/day)  is recommended as the
                                                           appropriate upper limit.  (The commonly-used 2.0 L/day
                                                           intake rate corresponds to the 84th percentile of the intake
                                                           rate distribution among the adults in the Ershow and
                                                           Cantor  (1989)  study).   In keeping with the  desire to
                                                           incorporate body weight  into  exposure assessments
                                                           without introducing extraneous errors, the values from the
Page
3-26
                                                          Exposure Factors Handbook
                                                                              August 1997

-------
Volume I - General Factors
Chapter 3 - Drinking Water Intake
Ershow and Cantor (1989) study (Tables 3-7 and 3-8)
expressed as mL/kg-day are recommended in preference
to the liters/day units.  For adults, the mean and 90th
percentile values are 21  mL/kg-day and 34.2 mL/kg/day,
respectively.
     In the absence of actual data on chronic intake, the
values in the previous  paragraph are recommended as
chronic values, although the chronic 90th upper percentile
may  very well be  larger  than  2.35  L/day.    If  a
mathematical description of the intake distribution is
needed, the parameters of lognormal fit to the Ershow and
Cantor (1989) data (Tables 3-11 and 3-12) generated by
Roseberry and Burmaster (1992) may be  used.  The
simulated balanced population distribution of intakes
generated  by   Roseberry  and  Burmaster  is  not
recommended for use in the post-1997 time frame, since
it corrects the 1978 data  only for the differences in the age
structure  of the U. S. population between 1978 and 1988.
     These recommended values are different than the 2
liters/day commonly assumed in EPA risk assessments.
Assessors are encouraged  to  use  values  which most
accurately reflect the exposed population.  When using
values other  than 2 liters/day, however, the  assessors
should consider if the dose estimate will  be used to
estimate   risk  by  combining  with a dose-response
relationship which was derived assuming a tap  water
intake of 2 liters/day. If such an inconsistency exists, the
assessor  should adjust the dose-response relationship as
described in Appendix 1 of Chapter 1. IRIS does not use
a tap water intake assumption in the derivation of RfCs
and RfDs, but does make the 2 liter/day assumption in the
derivation of cancer slope factors and unit risks.
     Children - The tapwater  intake rates for children
reported in the key studies are summarized in Table 3-33.
     The intake rates,  as  expressed as liters per day,
generally increase with age, and the data are consistent
across ages for the two  key  studies  except for the
Canadian Ministry of Health and Welfare (1981) data for
ages 6 to 17 years; it is recommended that any  of the
liters/day values that match the age range of interest
except the Canada  data for ages 6 to 17 years be used.
The mL/kg-day intake values show a consistent downward
trend with increasing ages; using the Ershow and Cantor
(1989) data in preference  to the Canadian  Ministry of
National  Health and Welfare (1981) data is recommended
where the age ranges overlap.
     The intakes for children as reported in the relevant
studies are shown in Table 3-34.
Table 3-33. Key Study Tapwater Intake Rates for Children
Age
(years)
<1
<3
3-5
1-10
6-17
11-19
Mean
(L/day)
0.30
0.61
0.87
0.74
1.14
0.97
90th
Percentile
(L/day)
0.65
1.50
1.50
1.29
2.21
1.70
f-
Reference
Ershow and Cantor, 1989
Canadian Ministry of
National Health and
Welfare, 1981
Canadian Ministry of
National Health and
Welfare, 1981
Ershow arid Cantor, 1989
Canadian Ministry of
National Health and
Welfare, 1981 .
Ershow and Cantor, 1989
Table 3-34. Summary of Intake Rates for
Children in Relevant Studies

Age
6-11 months
<1 yr
<1 yr
2yrs
1-4 yrs
5-9 yrs
1-10 yrs
10-14 yrs
14-16 yrs
15-19 yrs
11-19 yrs
Mean
(L/day)
0.20
0.19
0.32
0.50
0.58
0.67
0.70
0.80
0.72
0.90
0.91

Reference
Pennington, 1983
U.S. EPA, 1984
Roseberry and Burmaster, 1992
Pennington, 1983
U.S. EPA, 1984
U.S. EPA, 1984
Roseberry and Burmaster, 1992
U.S. EPA, 1984
Pennington, 1983
U.S. EPA, 1984
Roseberry and Burmaster, 1992
      Disregarding the Roseberry and Burmaster study,
which is a recalculation of the Ershow and Cantor (1989)
study, the non-key studies generally  have lower  mean
intake values than the Ershow and Cantor (1899) study.
The reason is not known, but the results are not persuasive
enough  to discount the recommendations based on the
latter study.  Intake rates for specific percentiles of the
distribution  may  be  selected using  the lognormal
distribution data generated by Roseberry and Burmaster
(1992) (Tables 3-11 and 3-12).
      Pregnant and Lactating Women -The data on
tapwater intakes for control,  pregnant,  and  lactating
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                                                                         Volume I - General Factors
                                                                 Chapter 3 - Drinking Water Intake
women are presented in Table 3-25. The recommended
intake values are presented in Table 3-30.
     High Activity/Hot Climates - Data on intake rates for
individuals performing strenuous activities under various
environmental conditions are limited.  None of these is
classed as a key study because the populations in these
studies  are  not representative  of the  general  U.S.
population. However, the data presented by McNall and
Schlegel (1968) and U.S. Army (1983) provide bounding
intake values for these individuals. According to McNall
and Schlegel (1968), hourly intake can range from 0.21 to
0.65 L/hour depending on the temperature and activity
level.  Intake  among physically active individuals can
range from 6 L/day in temperate climates to 11  L/day in
hot climates (U.S. Army, 1983).
      A characterization of the overall confidence in the
accuracy and appropriateness of the recommendations for
drinking water is presented in Table 3-35. Although the
study of Ershow and Cantor (1989) is of high quality and
consistent with the other surveys, the low currency of the
information (1978 data collection), in the presence of
anecdotal  information (not  presented here) that the
consumption of bottled water and beverages has increased
since 1980  was the  main  reason  for lowering the
confidence score of the overall recommendations  from
high to medium.
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                 	August 1997

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Volume I - General Factors
Chapters - Drinking Water Intake
Table 3-35. Confidence in Tapwater Intake Recommendations
Considerations
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
Rationale

The study of Ershow and Cantor (1989) had a 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 sponsoring agencies;
the others are library-accessible.
Methods are well-described.
The studies are directly relevant to tapwater.
See "representativeness" below.
The two monographs used recent primary data (less than one week)
on recall of intake.
Data were all collected in the 1978 era. Tapwater use may have
changed since that time period.
These are one- to three-day intake data. However, long term
variability may be small. Their use as a chronic intake measure can
be assumed.
The approach was competently executed.
This study was the largest monograph that had data for 1 1,000
individuals.
The Ershow and Cantor (1989) and Canadian surveys were
validated as demographically representative.
The full distributions were given in the main studies.
Bias was not apparent.
No physical measurements were taken. The method relied on
, recent recall of standardized volumes of drinking water containers,
and was not validated.

There were two key studies for the adult and child
recommendations. There were six other studies for adults, one
study for pregnant and lactating women, and two studies for high
activity/hot climates.
This agreement was good.
The data are excellent, but are not current.
Rating

High
High
High
High
NA
High
Low
Medium
High
High
High
High
High
Medium

High for adult and
children.
Low for the other
recommended
subpopulation values.
High
Medium
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                                                                        Volume I - General Factors
                                                                Chapter 3 - Drinking Water Intake
3.7.  REFERENCES FOR CHAPTER 3

American Industrial Health Council (AIHC). (1994)
  Exposure factors sourcebook. AIHC, Washington,
  DC.
Bourne, G.H.; Kidder, G.W., eds.  (1953) Biochemistry
  and physiology of nutrition.  Vol.1.  New York, NY:
  Academic Press.
Canadian Ministry of National Health and Welfare
  (1981) Tapwater consumption in Canada. Document
  number 82-EHD-80. Public Affairs Directorate,
  Department of National Health and Welfare, Ottawa,
  Canada.
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): 1269-1279.
Ershow, 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.
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.
Evans, C.L., ed. (1941) Starling's principles of human
  physiology, 8th ed. Philadelphia, PA: Lea and
  Febiger.
Gillies, M.E.; Paulin, H.V.  (1983) Variability of
  mineral intakes from drinking water: A possible
  explanation for the controversy over the relationship
  of water quality to cardiovascular disease. Int. J.
  Epid.  12(1):45-50.
Guyton, A.C.  (1968) Textbook of medical physiology,
  3rd ed. Philadelphia, PA: W.B. Saunders Co.
Hopkins, S.M.; Ellis, J.C. (1980)  Drinking water
  consumption in Great Britain: a survey of drinking
  habits with special reference to tap-water-based
  beverages.  Technical Report 137, Water Research
  Centre, Wiltshire Great Britain.
ICRP. (1981) International Commission on
  Radiological Protection.  Report of the task group on
  reference man. New York: Pergammon Press.
McNall, P.E.; Schlegel, J.C. (1968) Practical thermal
  environmental limits for young adult males working
  in hot, humid environments. American Society of
  Heating, Refrigerating and Air-Conditioning
  Engineers (ASHRAE) Transactions 74:225-235.
National Academy of Sciences (NAS). (1974)
  Recommended dietary allowances, 8th ed.
  Washington, DC: National Academy of Sciences-
  National Research Council.
National Academy of Sciences (NAS). (1977)
  Drinking water and health. Vol. 1.  Washington, DC:
  National Academy of Sciences-National Research
  Council.
Pennington, J.A.T.  (1983) Revision of the total diet
  study food list and diets. J. Am. Diet. Assoc.
  82:166-173.
Pike, R.L.; Brown, M.  (1975) Minerals and water in
  nutrition~an integrated approach, 2nd ed. New York,
  NY: John Wiley.
Randall, H.T., (1973) Water, electrolytes and  acid base
  balance.  In: Goodhart RS, Shils ME, eds. Modern
  nutrition in health and disease. Philadelphia, PA: Lea
  and Febiger.
Roseberry, A.M.; Burmaster, D.E. (1992)  Lognormal
  distribution for water intake by children  and adults.
  Risk Analysis 12:99-104.
Tsang, A.M.; Klepeis, N.E. (1996) Results tables from
  a detailed analysis of the National Human Activity
  Pattern Survey (NHAPS) responses. Draft Report
  prepared for the U.S. Environmental Protection
  Agency by Lockheed Martin, Contract No. 68-W6-
  001, Delivery Order No. 13.
U.S. Army. (1983) Water Consumption Planning
  Factors Study. Directorate of Combat Developments,
  United States Army Quartermaster School, Fort Lee,
  Virginia.
USDA. (1995) Food and nutrient intakes  by
  individuals in the United States, 1 day, 1989-91.
  United States Department of Agriculture, Agricultural
  Research Service. NFS Report No. 91-2.
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.  (1984)  An estimation of the daily average
  food intake by age and sex for use in assessing the
  radionuclide intake of individuals in the  general
  population. EPA-520/1-84-021.
U.S. EPA.  (1991)  U.S. Environmental Protection
  Agency.  National Primary Drinking Water
  Regulation; Final Rule. Federal Register
  56(20):3526-3597. January 30, 1991.
Page
3-30
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Volume I - General Factors
Chapter 3 - Drinking Water Intake
Walker, B.S.; Boyd, W.C.; Asimov, I.  (1957)
  Biochemistry and human metabolism, 2nd ed.
  Baltimore, MD: Williams & Wilkins Co.
Wolf, A.V. (1958) Body water. Sci. Am. 99:125.
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Volume I - General Factors
Chapter 4 - Soil Ingestion and Pica
4.    SOIL INGESTION AND PICA
4.1.   BACKGROUND
      The ingestion of soil is a potential source of human
exposure  to toxicants.  The  potential for exposure  to
contaminants  via  this source is greater for  children
because they are more  likely to ingest more soil than
adults as a result of behavioral patterns present during
childhood. Inadvertent soil ingestion among children may
occur  through  the  mouthing  of  objects  or hands.
Mouthing behavior is considered to be a normal phase of
childhood development.  Adults may also ingest soil  or
dust particles that adhere  to food, cigarettes,  or their
hands. Deliberate soil ingestion is defined as pica and is
considered to be relatively uncommon. Because normal,
inadvertent soil ingestion is more prevalent and data for
individuals with pica behavior are limited, this section
focuses primarily on normal soil ingestion that occurs as
a result  of mouthing or unintentional hand-to-mouth
activity.
      Several studies have been conducted to estimate the
amount of soil ingested  by children.  Most of the early
studies attempted to estimate the amount of soil ingested
by measuring the  amount of dirt present on children's
hands and making generalizations based on behavior.
More recently, soil intake studies have been conducted
using a methodology that measures trace elements in feces
and soil that are believed to be poorly absorbed in the gut.
These measurements are used to estimate the amount of
soil ingested over a specified time period. The available
studies on soil intake are summarized in the following
sections.  Studies on soil intake among children have been
classified as either key studies or relevant studies based on
their  applicability  to  exposure  assessment needs.
Recommended intake rates are based on the results of key
studies, but relevant studies are also presented to provide
the reader with added perspective on the current state-of-
knowledge pertaining to soil intake.  Information on soil
ingestion among adults is presented based on available
data from a limited number of studies.  This is an area
where more data and more research are needed. Relevant
information on the prevalence of pica and intake among
individuals exhibiting pica behavior is  also presented.

4.2.   KEY STUDIES ON SOIL INTAKE AMONG
      CHILDREN
      Binder et al. (1986) - Estimating Soil Ingestion:
Use of Tracer Elements in Estimating the Amount of Soil
Ingested by Young Children - Binder et al. (1986) studied
the ingestion of soil among children 1 to 3 years of age
who wore diapers using a tracer technique modified from
a method previously used to measure soil ingestion among
grazing animals.  The children were studied during the
summer of 1984 as part of a  larger study of residents
living  near a lead smelter  in East Helena, Montana.
Soiled diapers were collected over a 3-day period from
65 children (42 males and 23 females), and composited
samples of soil were obtained from the children's yards.
Both  excreta and soil  samples  were  analyzed for
aluminum, silicon, and titanium.  These elements were
found in soil, but were thought to be poorly absorbed in
the gut and to have been present in the diet only in limited
quantities. This made them useful tracers for estimating
soil intake. Excreta measurements were obtained for 59
of the  children.  Soil ingestion  by  each  child was
estimated based on each of the three tracer elements using
a standard assumed fecal dry weight of 15 g/day, and the
following equation:
                                        (Eqn. 4-1)
  where:
    Ti,e  =
    fi,e  =


    F!   =
    Si,e  =
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).
      The analysis conducted by Binder et al. (1986)
assumed that: (1) the tracer elements were neither lost nor
introduced during sample processing; (2) the soil ingested
by children originates primarily from their own yards; and
(3) that absorption of the tracer elements  by children
occurred  in only small amounts.   The study did not
distinguish between ingestion of soil and housedust nor
did it account for the presence of the tracer elements in
ingested foods or medicines.
      The arithmetic mean quantity of soil ingested by
the children in the Binder  et  al.  (1986) study  was
estimated to be 181 mg/day (range 25 to 1,324) based on
the aluminum tracer; 184 mg/day (range 31 to 799) based
on the silicon  tracer;  and 1,834 mg/day (range 4 to
17,076) based on the titanium tracer (Table 4-1). The
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                                                                          Volume I - General Factors
                                                                 Chapter 4 - Soil Ingestion and Pica
Table 4-1. Estimated Daily Soil Ingestion Based on Aluminum, Silicon, and Titanium Concentrations
Estimation
Method
Aluminum
Silicon
Titanium
Minimum
Source: Binder etal
Mean
(mg/day)
181
184
1,834
108
, 1986.
Median
(mg/day)
121
136
618
88

Standard
Deviation
(mg/day)
203
175
3,091
121

Range
(mg/day)
25-1,324
31-799
4-17,076
4-708

95th Percentile
(mg/day)
584
5,78
9,590
386

Geometric
Mean
(mg/day)
128
130
401
65

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
pcrcentile values for aluminum, silicon, and titanium were
584 mg/day, 578 mg/day, and 9,590 mg/day, respectively.
The  95th percentile value based on the minimum of the
three individual tracer estimates for each child was  386
mg/day.
      The authors were not able to explain the difference
between the results for titanium and for the other  two
elements, but speculated that unrecognized sources of
titanium in the diet or in the laboratory processing of stool
samples may have accounted for the increased levels.  The
frequency distribution graph of soil ingestion estimates
based on titanium shows that a group of 21 children had
particularly high titanium values (i.e., >1,000 mg/day).
The remainder of the children showed titanium ingestion
estimates at  lower levels,  with a  distribution more
comparable to that of the other elements.
      The advantages  of this study are that a relatively
large number of children were studied and tracer elements
were used to estimate soil ingestion.   However, the
children studied may not be representative of the U.S.
population and the study did not account for  tracers
ingested via foods  or medicines.  Also, the use of an
assumed fecal weight instead of actual fecal weights may
have biased the results  of this study. Finally, because of
the short-term nature of the survey, soil  intake estimates
may not be entirely representative of long-term behavior,
especially at the upper-end of the distribution of intake.
      Clausing et al. (1987) - A Method for Estimating
Soil Ingestion by  Children  - Clausing et al.  (1987)
conducted a soil ingestion study with Dutch children using
a tracer element methodology similar to that of Binder et
al.  (1986).   Aluminum,  titanium,  and acid-insoluble
residue (AIR) contents were determined for fecal samples
from children, aged  2  to 4 years,  attending a nursery
school, and for samples of playground dirt at that school.
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 4-2). As in the Binder
et al. (1986) study,  a  fraction of the children (6/19)
showed titanium values well above 1,000 mg/day, with
most  of the remaining children showing  substantially
lower values.  Based on the Limiting Tracer Method
(LTM), mean soil intake was estimated to  be 105 mg/day
with a population standard deviation of 67 mg/day (range
23 to 362 mg/day). Use of the LTM assumed that "the
maximum amount of soil ingested corresponded with the
lowest estimate from the three tracers" (Clausing et al.,
1987).  Geometric mean soil intake was estimated to be
90 mg/day.  This  assumes that the maximum amount of
soil ingested cannot be higher than the lowest estimate for
the individual tracers.
      Mean soil intake for the hospitalized children was
estimated to be 56 mg/day based on aluminum (Table 4-
3). For titanium, three of the children had estimates well
in excess of 1,000 mg/day,  with the remaining three
children in the range of 28 to 58 mg/day.  Using the LTM
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Volume I - General Factors
Chapter 4 - Soil Ingestion and Pica
Table 4-2, Calculated Soil Ingestion by Nursery School Children


Child
1


2


3

4

5

6

7

8
9
10
11
12
13
14
15
16
17
18
Arithmetic Mean
Source: Adapted fron

Sample
Number
L3
L14
L25
L5
L13
L27
L2
L17
L4
Lll
L8
L21
L12
L16
LI 8
L22
LI
L6
L7
L9
L10
L15
L19
L20
L23
L24
L26

ft Clausing et al.
Soil Ingestion as
Calculated from Ti
(mg/dav)
103
154
130
131
184
142
124
670
246
2,990
293
313
1,110
176
11,620
11,320
3,060
624
600
133
354
2,400
124
269
1,130
64
184
1,431
1987.
Soil Ingestion as
Calculated from Al
(ma/day)
300
211
23
_
103
81
42
566
62
65
_
-
693
-
_
.77
82
979
200
_
195
-
71
212
51
566
56
232

Soil Ingestion as
Calculated from AIR
(mg/dav)
107
172
-
71 '
82
84
84
174
145
139
108
152
362
145-
120
-
96
111
124
95
106
48
93
274
84
-
-'
129


Limiting Tracer
(mg/day)
103
154
23
71
82
81
42
174
62
65
108
152
362
145
120
77
82
111
124
95
106
48
71
212
51
64
56
105




Child
1

2
3

4
5
6
Arithmetic Mean
Table 4-3.


Sample
G5
G6
Gl
G2
G8
G3
G4
G7

Calculated Soil Ingestion by Hospitalized, Bedridden Children
Soil Ingestion as Calculated
from Ti
(mg/dav)
3,290
4,790
28
6,570
2,480
28
1,100
58'
2,293
Soil Ingestion as Calculated
from Al
(mg/dav)
57
71
26
94
57
77
30
38
56

Limiting Tracer
(mg/dav)
57
71
26
84
57
28
30
38
49
Source: Adapted from Clausing et al. 1987.
 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
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                                                                           Volume I - General Factors
                                                                  Chapter 4 - Soil Ingestion and Pica
source of aluminum.  However, conditions specific to
hospitalization (e.g., medications) were not considered.
AIR measurements were not reported for the hospitalized
children.  Assuming that the tracer-based soil ingestion
rates observed in hospitalized children actually represent
background tracer intake from dietary and other nonsoil
sources, mean soil ingestion by nursery school children
was estimated to be 56 mg/day, based on the LTM (i.e.,
105 mg/day for nursery school children minus 49 mg/day
for hospitalized children) (Clausing et al. 1987).
      The advantages of this study are that Clausing et al.
(1987) evaluated soil ingestion among two populations of
children  that had differences  in  access  to  soil,  and
corrected soil intake rates based on background estimates
derived from the hospitalized group.  However, a smaller
number of children were used in this study than in the
Binder et al. (1986) study and these children may not be
representative of the U.S. population.  Tracer elements in
foods or medicines were not evaluated. Also, intake rates
derived from this study may not be representative of soil
intake over the long-term because of the short-term nature
of the study. In addition, one of the factors that could
affect soil  intake rates is hygiene (e.g., hand washing
frequency). Hygienic practices can vary across countries
and cultures and may be more stringently emphasized in
a more structured environment such as child care centers
in The Netherlands and other European countries than in
child  care centers in the United States.
      Calabrese et al. (1989) - How Much Soil do Young
Children Ingest: An  Epidemiologic Study - Calabrese et
al. (1989) studied soil ingestion among children using the
basic tracer design developed by Binder et al. (1986).
However, in contrast to the Binder et al. (1986) study,
eight tracer elements (i.e.,  aluminum, barium, manganese,
silicon, titanium, vanadium, yttrium, and zirconium) were
analyzed instead of only three (i.e., aluminum, silicon, and
titanium).   A total of 64 children between the ages of 1
and 4 years old were included in the study.  These
children were all  selected from the greater  Amherst,
Massachusetts area and were predominantly from two-
parent households  where the parents were  highly
educated.    The  Calabrese et al.  (1989) study  was
conducted over eight days during a two week period and
included the use of a mass-balance methodology in which
duplicate samples of food, medicines, vitamins, and others
were collected and analyzed on a daily basis, in addition
to soil and dust samples collected from the child's home
and play  area.   Fecal and urine samples  were also
collected and analyzed for tracer elements. Toothpaste,
low in tracer content, was provided to all participants.
      In order to validate the mass-balance methodology
used to estimate soil ingestion rates among children and
to determine  which tracer elements provided the most
reliable data on soil ingestion, known amounts of soil (i.e.,
300 mg over three days and 1,500 mg over three days)
containing eight tracers  were administered to six adult
volunteers (i.e., three males and  three females).  Soil
samples and feces samples from these adults and duplicate
food  samples  were  analyzed for tracer  elements to
calculate recovery rates of tracer elements in soil. Based
on the adult  validation  study, Calabrese et al. (1989)
confirmed that the tracer methodology could adequately
detect tracer  elements in feces at levels  expected to
correspond with soil intake rates in children.  Calabrese et
al. (1989)  also found that aluminum, silicon, and yttrium
were  the  most reliable  of the eight  tracer elements
analyzed.   The standard deviation of recovery of these
three  tracers  was  the lowest and  the percentage of
recovery was closest to  100 percent  (Calabrese,  et al.,
1989). The recovery of these three tracers ranged from
120 to 153 percent when 300 mg of soil had been ingested
over a three-day period and from 88 to 94 percent when
1,500 mg  soil had been ingested over a three-day period
(Table 4-4).
      Using the three most reliable tracer elements, the
mean soil intake rate for children, adjusted to account for
the amount of tracer found in food and medicines, was
estimated  to be 153 mg/day based on aluminum, 154
mg/day based on silicon,  and 85 mg/day based on yttrium
(Table 4-5). Median intake rates were somewhat lower
(29 mg/day for aluminum, 40 mg/day for silicon, and 9
mg/day for yttrium). Upper-percentile (i.e., 95th) values
were 223 mg/day for aluminum, 276 mg/day for silicon,
and  106  mg/day  for yttrium.    Similar results  were
observed  when soil and dust ingestion was combined
(Table 4-5). Intake of soil and dust was estimated using
a weighted average of tracer  concentration  in dust
composite samples and in soil composite samples based
on the timechildren spent at home and away from home,
and  indoors  and outdoors.  Calabrese et al.  (1989)
suggested that the  use of titanium as a tracer in earlier
studies  that  lacked  food  ingestion  data may  have
significantly overestimated soil intake because of the high
levels of titanium in food.  Using  the median values of
aluminum and silicon, Calabrese et al. (1989) estimated
the quantity of  soil ingested daily  to be 29 mg/day and
40 mg/day, respectively. It should be  noted that soil
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Volume I - General Factors
Chapter 4 - Soil Ingestion and Pica
Table 4-4. Mean and Standard Deviation Percentage Recovery of Eight Tracer Elements

Tracer Element
Al
Ba
Mn
Si
Ti
V
Y
Zr
300 mg
Mean
152.8
2304.3
1177.2
139.3
251.5
345.0
120.5
80.6
Soil Ingested
SD
107.5
4533.0
1341.0
149.6
316.0
247.0
42.4
43.7
1500
Mean
93.5
149.8
248.3
91.8
286.3
147.6
87.5
54.6
mg Soil Ingested
SD
15.5
69.5
183.6
16.6
380.0
66.8
12.6
33.4
Source: Adapted from Calabrese et al., 1989.
Table 4-5. Soil and Dust Ingestion Estimates for Children Aged 1-4 Years

Tracer Element
Aluminum
soil
dust
soil/dust combined
Silicon
soil
dust
soil/dust combined
Yttrium
soil
dust
soil/dust combined ,
Titanium
soil
dust


N

64
64
64

64
64
64

62
64
62

64
64
64

Mean

153
317
154

154
964
483

85
62
65

218
163
170

Median

29
31
30

40
49
49

9
15
11

55
28
30
Intake (mg/day)a
SD

852
1,272
629

693
6,848
3,105

890
687
717

1,150
659
691
95th Percentile

223
506
478

276
692
653

106
169
159

1,432 .
1,266
1.059
Maximum

6,837
8,462
4,929

5,549
54,870
24,900
•
6,736
5,096
5,269

6,707
3,354
3.597
a Corrected for Tracer Concentrations in Foods
Source: Adapted from Calabrese et al.
1989.





 ingestion for one  child  in  the  study ranged  from
 approximately 10 to 14 grams/day during the second week
 of observation.  Average soil ingestion for this child was
 5 to 7 mg/day, based on the entire study period.
      The advantages of this study are that intake rates
 were corrected for  tracer  concentrations in foods and
 medicines and that the methodology was validated using
 adults.  Also, intake was observed over a  longer time
period in this study than in earlier studies and the number
of tracers  used was larger than for other studies.   A
relatively large population was studied, but they may not
be entirely representative of the U.S. population because
they were selected from a single location.
      Davis et al. (1990) - Quantitative Estimates of Soil
Ingestion in Normal Children Between the ages of 2 and
7 years: Population-Based Estimates Using Aluminum,
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                                                                   Chapter 4 - Soil Ingestion and Pica
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:
         (DWr * DWp
  where:
      sie
      DWf
      DWp
      Ef

      DWfd
      Efd
      Esoi!
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 (Mg/g);
tracer amount in urine (A
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Volume I - General Factors
Chapter 4 - Soil Ingestion and Pica
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 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 Wijnen et  al.  (1990) also
reported geometric mean LTM values because soil intake
rates were found to  be skewed and the log  transformed
data were approximately normally distributed. Geometric
mean LTM values were estimated to be 111 mg/day for
children  in  daycare  centers,  174 mg/day  for children
vacationing at campgrounds (Table 4-7) and 74 mg/day
for hospitalized children (70-120 mg/day based on the 95
percent confidence  limits  of  the mean). AIR was  the
limiting tracer in about 80 percent of the samples. Among
children attending daycare centers, soil intake was also
found to be higher when the weather was good (i.e., <2
days/week precipitation) than  when the weather was bad
(i.e., >4 days/week precipitation (Table 4-8).  Van Wijnen
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.
Table 4-7. Geometric Mean (GM) and Standard Deviation (GSD) LTM Values
* for Children at Daycare Centers and Campgrounds
Daycare Centers
Age (yrs) Sex

<1

l-<2

2-<3

3-4

4-<5

All girls
All boys
Total

Girls
Boys
Girls
Boys
Girls
Boys
Girls
Boys
Girls
Boys


n

3
1
20
17
34
17
26
29
1
4
86
72
162a
GMLTM
(mg/day)
81
75
124
114
118
96
111
110
180
99
117
104
111
GSD LTM
(mg/day)
1.09
-
1.87
1.47
1.74
1.53
1.57
1.32
-
1.62
1.70
1.46
1.60
n

-
-
3
5
4
8
6
8
19
18
36
42
78b
Campgrounds
GM LTM.
(mg/day)
'
-
207
312
367
232
164
148
164
136
179
169
174

GSD LTM
(mg/day)
-
-
1.99
2.58
2.44
2.15
1-27 ,
1.42
1.48
1.30
1.67
1.79
1.73
a Age and/or sex not registered for eight children.
b Age not registered for seven children.
Source:
Adapted from Van Wijnen et al., 1990.
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 August 1997
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                                                                           Volume I - General Factors
                                                                  Chapter 4 - Soil Ingestion and Pica
Table 4-8. Estimated Geometric Mean LTM Values of Children Attending Daycare Centers
According to Age, Weather Category, and Sampling Period
First Sampling Period
Weather Category
Bad
(>4 days/week precipitation)


Reasonable
(2-3 days/week precipitation)



Good
(<2 days/week precipitation)



Age (years)
<1
l-<2
2-<3
4-<5
<1
l-<2
2-<3
3-<4
4-<5
<1
l-<2
2-<3
3-<4
4-<5
Second Sampling Period
Estimated Geometric Mean Estimated Geometric Mean
LTM Value LTM Value
n (me/day) n (mg/dav)
3
18
33
5





4
42
65
67
10
94
103
109
124





102
229
166
138
132
3
33
48
6
1
10
13
19
1





, 67
80
91
109
61
96
99
94
61





Source: Van Wiinen et al., 1990.
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 Wijnen 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 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
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Volume I - General Factors
Chapter 4 - Soil Ingestion and Pica
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 4-9 presents the estimates of mean daily soil
ingestion intake  per child (mg/day)  for  the 64 study
participants. (The authors also presented estimates of the
median values of daily intake for each child. For most
risk assessment purposes the child mean values, which are
proportional to the cumulative soil intake by the child, are
needed instead of the median  values.)  The approach
adopted in this paper led to changes in ingestion estimates
from those presented in Calabrese et al. (1989).
                                    Specifically, among elements that may be more useful for
                                    estimation of ingestion, the mean estimates decreased for
                                    Al (153  mg/d to 122 mg/d) and Si ( 154 mg/d to 139
                                    mg/d), but increased for Ti (218 mg/d to 271 mg/d) and Y
                                    (85 mg/d to 165 mg/d). The "overall" mean estimate from
                                    this reanalysis  was 179 mg/d.  Table 4-9 presents the
                                    empirical distribution of the  the "overall" mean daily soil
                                    ingestion estimates for the 8-day study period (not based
                                    on lognormal modeling). The estimated intake based on
                                    the "overall" estimates is 45 mg/day or less for 50 percent
                                    of the children and 208 mg/day or less for 95  percent of
                                    the children. The upper percentile values for most of the
                                    individual trace elements are somewhat higher.  Next,
                                    estimates of the respondents soil intake averaged over a
                                    period of 365  days were  presented based  upon the
                                    lognormal models fit to the daily ingestion estimates
                                    (Table 4-10).  The estimated median value  of the 64
                                    respondents' daily soil ingestion averaged over a year is
                                    75 mg/day, while the 95th percentile is 1,751 mg/day.
                                          A strength of this study is that it attempts to make
                                    full use of the collected data through estimation of daily
                                    ingestion rates for children. The data are then screened to
                                    remove less consistent tracer estimates and the remaining
                                    values are aggregated.   Individual  daily estimates of
                                    ingestion will be subject to larger errors than are weekly
                                    average  values, particularly since  the assumption of a
                                    constant lag time between food intake and fecal output
                                    may  be  not  be correct for many subject days.  The
                                    aggregation approach used to arrive at the "overall"
                                    ingestion estimates rests on the assumption that the mean
               Table 4-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates Per Child for 64 Children (mg/day)
    Type of Estimate
   Number of Samples
 Overall
  (64)
  Al
  (64)
  Ba
  (33)
  Mn
  (19)
   Si
  (63)
   Ti
  (56)
 V
(52)
  Y
 (61)
 Zr
(62)
  Mean
  25th Percentile
  50th Percentile
  75th Percentile
  90th Percentile
  95th Percentile
  Maximum
  179
   10
   45
   88
  186
  208
7,703
  122
   10
   19
   73
  131
  254
4,692
 655
  28
  65
 260
 470
 518
17,991
1,053
  35
  121
  319
  478
17,374
17,374
 139
   5
  32
  94
 206
 224
4,975
  271
    8.
   31
   93
  '154
  279
12,055
112
  8
 47
177
340
398
845
 165
   0
  15
  47
 105
 144
8,976
 23
  0
 15
 41
 87
117
208
  a  For each child, estimates of soil ingestion were formed on days 4-8 and the mean of these estimates was then evaluated for each child. The
     values in the column "overall" correspond to percentiles of the distribution of these means over the 64 children. When specific trace elements
     were not excluded via the relative standard deviation criteria, estimates of soil ingestion based on the specific trace element were formed for
     108 days for each subject. The mean soil ingestion estimate was again evaluated. The distribution of these means for specific trace elements is
     shown.
  Source: Stanek and Calabrese, 1995a.	
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August 1997
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                                                                             Volume I - General Factors
                                                                    Chapter 4 - Soil Ingestion and Pica
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.
  Table 4-10. Estimated Distribution of Individual Mean Daily Soil
           Ingestion Based on Data for 64 Subjects
 	Projected Over 365 Days"	
  Range
  50th Pcrcentile (median)
  90th Percemile
  95th Pereentile	
1 - 2,268 mg/db
75mg/d
l,190mg/d
1.751 mg/d
  " Based on fitting a log-normal distribution to model daily soil
   ingestion values.
  b Subject with pica excluded.
  Source: Slanek and Calabrese. 1995a.	
      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
ingestion, such as the study mean estimates presented  in
Table 4-9, are substantially more   reliable than  any
available distributional estimates.
      Stanek and Calabrese (1995b) - Soil Ingestion
Estimates for Use in Site Evaluations Based on the Best
Tracer Method -  Stanek  and Calabrese  (1995b)
recalculated ingestion rates that were estimated in three
previous mass-balance studies (Calabrese et al., 1989 and
Davis et al.,  1990 for  children's  soil  ingestion,  and
Calabrese et al., 1990 for adult soil ingestion) using the
Best Tracer Method (BTM). This method allows for the
selection of the most recoverable tracer for a particular
subject or  group of subjects.  The selection process
involves ordering trace elements for each subject based on
food/soil (F/S) ratios.  These ratios are estimated by
dividing the total amount  of  the tracer in food by the
tracer concentration in soil. The F/S ratio is small when
the tracer  concentration in food is  almost zero when
compared to the tracer concentration in soil. A small F/S
ratio is desirable because it lessens the impact of transit
time error (the error that occurs when fecal output does
not  reflect  food  ingestion,  due  to  fluctuation  in
gastrointestinal  transit  time)  in  the  soil   ingestion
calculation. Because the recoverability of tracers can vary
within any group of individuals, the BTM uses a ranking
scheme of F/S ratios to determine the best tracers for use
in the ingestion rate calculation.  To reduce biases that
may occur as a result of sources of fecal tracers other than
food or soil, the median of soil ingestion estimates based
on the four lowest F/S ratios was used to represent soil
ingestion among individuals.
      For adults, Stanek and Calabrese (1995b) used data
for 8 tracers from the Calabrese  et al. (1990) study to
estimate soil ingestion by the BTM. The lowest F/S ratios
were Zr and Al and the element with the highest'F/S ratio
was Mn.  For soil ingestion estimates based on the median
of the lowest four F/S ratios, the tracers contributing most
often to the soil ingestion estimates were Al, Si, Ti, Y, V,
and Zr. Using the median of the soil ingestion rates based
on the best four tracer elements,  the average  adult soil
ingestion rate was  estimated to be 64 rng/day with a
median of 87 mg/day.  The 90th percentile soil ingestion
estimate was 142 mg/day. These estimates are based on
18 subject weeks for the six adult volunteers described in
Calabrese et al. (1990).
      For children, Stanek and Calabrese (1995b) used
data on 8 tracers from Calabrese et al., 1989 and data on
3  tracers  from Davis  et al. (1990) to  estimate soil
ingestion rates.  The median of the soil ingestion estimates
from the lowest four F/S ratios from the Calabrese et al.
(1989) study most often included Al, Si, Ti, Y,  and Zr.
Based on the median of soil ingestion estimates from the
best four tracers, the mean soil ingestion rate was 132
mg/day and  the median  was  33 mg/day.  The 95th
percentile value was 154 mg/day. These estimates are
based on data for 128 subject weeks for the 64 children in
the Calabrese et al. (1989) study. For the 101 children in
the Davis et al. (1990) study, the mean soil ingestion rate
was 69 mg/day and the median soil ingestion rate was 44
mg/day.  The 95th percentile estimate was 246 mg/day.
These data are based on the three tracers (i.e., Al, Si, and
Ti) from the Davis et al.  (1990) study.  When  the
Calabrese et al. (1989) and Davis et al.  (1990) studies
were  combined, soil ingestion was estimated to be 113
mg/day (mean); 37 mg/day (median); and 217  mg/day
(95th percentile), using the BTM.
      This  study provides a reevaluation of previous
studies. Its advantages are that it combines data from 2
studies for children, one from California and  one from
Massachusetts,   which  increases  the   number   of
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Volume I - General Factors
Chapter 4 - Soil Ingestion and Pica
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
etal. (1990) studies.

4.3.  RELEVANT STUDIES ON SOIL INTAKE
      AMONG CHILDREN
      Lepow et al. (1975) - Investigations Into Sources
of Lead in the Environment of Urban Children - Lepow et
al. (1975) used data from a previous study (Lepow et al.,
1974) to estimate daily soil ingestion rates of children.
Lepow et al.' (1974) estimated ingestion of airborne lead
fallout among urban children by: (1) analyzing surface
dirt and • dust  samples from locations where children
played; (2) measuring hand dirt by applying preweighed
adhesive labels  to the hands and weighing the amount of
dirt that was removed;  and (3) observing "mouthing"
behavior over 3 to 6 hours of normal play.  Twenty-two
children from an urban area of Connecticut were included
in the study. Lepow et al. (1975) used data from the 1974
study and found that the mean weight of soil/dust on the
hands was 11  mg.   Assuming that a child would put
fingers or other "dirty" objects into his mouth about 10
times a day ingesting  11 mg of dirt each time, Lepow et
al. (1975) estimated  that the  daily soil ingestion  rate
would be about 100 mg/day. According to Lepow et al.
(1975),  the amount of hand  dirt measured with  this
technique  is probably  an underestimate because  dirt
trapped  in  skin folds and creases was probably not
removed by the adhesive label. Consequently, mean soil
ingestion rates  may be somewhat higher  than the values
estimated in this study.
       Day et al. (1975) - Lead in Urban Street Dust -
Day et al. (1975) evaluated the contribution of incidental
ingestion of lead-contaminated street dust and soil to
children's  total daily intake of lead by measuring the
 amount of lead in street dust and soil and estimating the
 amount of dirt  ingested by children. The amount of soil
that might be ingested was estimated by measuring the
 amount of dirt that was transferred to a "sticky sweet"
 during 30 minutes of play and assuming that a child might
 eat from 2 to 20 such sweets per day. Based on "a small
 number of direct measurements," Day et al. (1975) found
 that 5 to 50 mg of dirt  from a child's hands may be
 transferred to  a  "sticky  sweet" during  30 minutes of
 "normal playground activity. Assuming that all of the dirt
 is  ingested with the 2 to  20 "sticky sweets," Day  et al.
(1975) estimated that intake of soil among children could
range from 10 to 1000 mg/day.
      Duggan and Williams (1977) - Lead in Dust in City
Streets - Duggan and Williams (1977) assessed the risks
associated with lead in street dust by analyzing street dust
from areas in and around London for lead, and estimating
the amount of hand dirt that a child might ingest. Duggan
and Williams (1977) estimated the amount of dust that
would be retained  on the forefinger  and thumb  by
removing a small amount of dust from a weighed amount,
rubbing  the forefinger  and  thumb  together,  and
reweighing to determine the amount retained on the finger
and thumb. The results of "a number of tests with several
different people" indicated that the mean amount of dust
retained on the finger and thumb was approximately 4 mg
with a range of 2 to 7 mg (Duggan and Williams, 1977).
Assuming that a child would suck his/her finger or thumb
10 times a day and that all of the dirt is removed each time
and replaced with new dirt prior to subsequent mouthing
behavior, Duggan and Williams (1977) estimated that 20
mg of dust would be ingested per day.
      Hawley et al (1985) - Assessment of Health Risk
from Exposure to Contaminated  Soil - Using  existing
literature,  Hawley  (1985)  developed  scenarios  for
estimating exposure of young children, older children, and
adults to contaminated soil. Annual soil ingestion rates
were estimated based on assumed intake rates  of soil  and
housedust for  indoor   and   outdoor activities   and
assumptions about  the duration  and frequency of the
activities.  These soil ingestion rates were based on the
assumption that the contaminated area is in a region
having a winter season.  Housedust was assumed to be
comprised of 80 percent soil.
       Outdoor exposure to contaminated soil among
young children (i.e., 2.5 years old) was assumed to occur
5 days per week during only 6 months of the year (i.e.,
mid-April through mid-October). Children were assumed
to ingest 250 mg soil/day while playing outdoors based on
data presented in Lepow et al. (1974; 1975) and Roels et
al. (1980). Indoor exposures among this population were
based on the assumption that young children ingest 100
 mg of housedust per day while spending all of their time
 indoors during the winter months, and 50 mg of housedust
 per day during the warmer months when only a portion of
 their time is spent indoors. Based on these assumptions,
 Hawley (1985)  estimated that the annual average soil
 intake rate for young children is 150 mg/day (Table 4-11).
 Older children (i.e., 6 year olds) were assumed to ingest
 50 mg of soil per day from an area equal to the area of the
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 August 1997
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                                                                           Volume I - General Factors
                                                                   Chapter 4 - Soil Ingestion and Pica

Scenarios
Youne Child (2.5 Years Old)
Outdoor Activities (Summer)
Indoor Activities (Summer)
Indoor Activities (Winter
TOTAL SOIL INTAKE
Older Child (6 Years Old)
Outdoor Activities (Summer)
Indoor Activities (Year-Round)
TOTAL SOIL INTAKE
Table 4-11.
Media
Soil
Dust
Dust
Soil
Dust
Estimates of Soil Ingestion for Children
Exposure
(mg/day)
250
50
100
50
3
Days/Year
Activity
130
182
182
152
365
Fraction Soil
Content
1
0.8
0.8
1
0.8
Annual Average Soil
Intake
(mg/day)
90
20
40
150
21
2.4
23.4
Source: Hawley, 1985.
 fingers on one hand while playing outdoors.  This
 assumption was based on data from Lepow et al. (1975).
 Outdoor activities were assumed to occur each day over
 5 months of the year (i.e., during May through October).
 These children were also assumed to ingest 3  mg/day of
 housedust from the indoor surfaces of the hands during
 indoor activities occurring over the entire year.  Using
 these data, Hawley (1985) estimated  the annual average
 soil intake rate for  older children to be 23.4 mg/day
 (Table 4-11).
       Thompson and Burmaster (1991) - Parametric
 Distributions for Soil Ingestion by Children - Thompson
 and  Burmaster   (1991)   developed   parameterized
 distributions of soil ingestion rates for children  based on
 areanalysis of the data collected by Binder et al. (1986).
 In  the original Binder et al. (1986)  study, an  assumed
 fecal weight of 15  g/day  was used.  Thompson and
 Burmaster reestimated the soil  ingestion rates  from the
 Binder et al. (1986) study using the actual stool weights of
 the  study participants instead of  the  assumed  stool
 weights. Because the actual stool weights averaged only
 7.5  g/day, the soil  ingestion  estimates presented by
 Thompson and Burmaster (1991) are approximately one-
 half of those reported by Binder et al. (1986). Table 4-12
 presents the distribution of estimated  soil ingestion rates
 calculated by Thompson and Burmaster (1991) based on
 the three  tracers elements (i.e., aluminum, silicon, and
 titanium),  and on the arithmetic average of soil ingestion
 based on  aluminum and silicon. The mean  soil intake
 rates were 97  mg/day for aluminum,  85 mg/day for
 silicon, and  1,004  mg/day  for titanium.  The  90th
 percentile  estimates were 197 mg/day  for aluminum, 166
 mg/day for silicon, and 2,105 mg/day for titanium. Based
 on the arithmetic average of aluminum and silicon for
 each child, mean soil intake was estimated  to be 91
 mg/day and 90th percentile intake was estimated to be 143
 mg/day.
      Thompson  and  Burmaster (1991)  tested  the
 hypothesis that soil ingestion rates based on the adjusted
 Binder et al. (1986) data for  aluminum, silicon and the
 average of these two tracers were lognormally distributed.
 The distribution of soil intake based on titanium was not
 tested for lognormality because titanium may be present
 in food in high concentrations and the Binder et al. (1986)
 study did not correct for  food  sources of titanium
 (Thompson and  Burmaster,  1991).   Although visual
 inspection of the distributions for aluminum,  silicon, and
 the average of these tracers all indicated that they may be
 lognormally distributed, statistical tests indicated that only
 silicon and the average of the silicon and aluminum
 tracers were lognormally distributed.  Soil intake rates
 based on aluminum were not lognormally  distributed.
 Table 4-12 also  presents the lognormal distribution
 parameters and underlying normal distribution parameters
 (i.e., the  natural logarithms of the data) for aluminum,
 silicon, and the average of these two tracers.  According
 to  the authors,  "the  parameters  estimated from  the
 underlying normal distribution are much more reliable and
 robust" (Thompson and Burmaster, 1991).
      The advantages  of this study are that it provides
percentile data and defines  the shape of  soil  intake
distributions. However, the number of data points used to
fit the distribution was limited. In addition, the study did
not generate "new" data. Instead, it provided a reanalysis
of previously-reported data using actual fecal weights. No
corrections were made for tracer intake from  food or
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Volume I - General Factors
Chapter 4 - Soil Ingestion and Pica
Table 4-12. Estimated Soil Ingestion Rate Summary Statistics and Parameters for Distributions
Using Binder et al. (1986) Data with Actual Fecal Weights
Soil Intake (mg/day)
Trace Element Basis

Mean
Min
10th
20th
30th
40th
Med
60th
70th
80th
90th
Max

Al
97
11
21
33
39
43
45
55
73
104
197
1,201

Si
85
10
19
23
36
52
60
65
79
106
166
642

Ti
1,004
1
3
22
47
172
293
475
724
1,071
2,105
14,061

MEAN3
91
13
22
34
43
49
59
69
92
100
143
921
Lognormal Distribution Parameters
Median
Standard Deviation
Arithmetic Mean
45
169
97
60
95
85
__
—
-
. 59
126
91
Underlying Normal Distribution Parameters
Mean
Standard Deviation
4.06
0.88
4.07
0.85
„

4.13
0.80
a MEAN = arithmetic average of soil ingestion based on aluminum and silicon.
Source: Thompson and Burmaster, 1991.




me'dicine and the results may not be representative of
long-term intake rates b.ecause the data were derived from
a short-term study.
       Sedman and Mahmood (1994) - Soil Ingestion by
Children and Adults Reconsidered Using the Results of
Recent Tracer Studies - Sedman and Mahmood (1994)
used the results of two recent children's (Calabrese et al.
1989; Davis et al. 1990)  tracer  studies to determine
estimates of average daily soil ingestion in young children
and for over a lifetime.  In the two studies, the intake and
excretion of a variety of tracers  were  monitored, and
concentrations of tracers in soil adjacent to the children's
dwellings  were determined (Sedman and Mahmood,
1994). From a mass balance approach, estimates of soil
ingestion in these children were determined by dividing
the excess tracer intake (i.e., quantity of tracer recovered
in the feces  in excess of the measured intake) by the
average concentration of tracer in soil samples from each
child's dwelling. Sedman and Mahmood (1994) adjusted
the mean estimates of soil ingestion in children for each
tracer (Y) from both studies to reflect that of a 2-year old
child using the following equation:
             Y. = x e("°-112*yr)
(Eqn. 4-3)
 where:
         YJ = adjusted mean soil ingestion (mg/day)
         x = a constant
         yr = average age (2 years)
In addition  to  the  study  in  young children, a study
(Calabrese et  al.,  1989) in adults  was conducted to
evaluate the tracer methodology.  In the adult studies,
percent recoveries of tracers were determined in six adults
who ingested known quantities of tracers in  1.5 or 0.3
grams of soil. The distribution of tracer recoveries from
adults  was  evaluated using  data analysis  techniques
involving  visualization  and exploratory data analysis
(Sedman and Mahmood, 1994). From the results obtained
in these studies, the distribution of tracer recoveries from
adults  were determined.  In addition, an analysis of
variance (ANOVA) and Tukey's multiple comparison
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                                                                         Volume I - General Factors
                                                                 Chapter 4 - Soil Ingestion and Pica
methodologies were employed to identify differences in
the recoveries  of the various tracers  (Sedman  and
Mahmood, 1994).
      From the adult studies, the ANOVA of the natural
logarithm of the recoveries of tracers from 0.3 or 1.5 g of
ingested soil showed a significant difference (« =0.05)
among the estimates of recovery of the tracers regardless
of whether the  recoveries were combined or analyzed
separately (Sedman and Mahmood, 1994). Sedman and
Mahmood (1994) also reported that barium, manganese,
and zirconium yielded significantly different estimates of
soil ingestion than the other tracers (aluminum, silicon,
yttrium, titanium, and vanadium). Table 4-13 presents the
Tukey's multiple comparison of mean log tracer recovery
in adults ingesting known quantities of soil.
      The average ages of children  in the two  recent
studies were 2.4 years in Calabrese, et al. (1989) and 4.7
years in Davis et al. (1990). The mean of the adjusted
levels of soil ingestion for a two year  old child was 220
mg/kg for the Calabrese et al. (1989) study and 170 mg/kg
for the Davis et al. (1990) study (Sedman and Mahmood,
1994). From the adjusted soil ingestion estimates, based
on a normal distribution of means, the mean estimate for
a 2-year old child was 195 mg/day and the overall mean
of soil ingestion and the standard error of the mean was 53
mg/day (Sedman  and  Mahmood, 1994).   Based on
uncertainties  associated  with  the method  employed,
Sedman  and   Mahmood  (1994)   recommended  a
conservative estimate of soil ingestion in young children
of 250 mg/day.  Based on the 250 mg/day ingestion rate
in a 2-year old child, an average daily soil ingestion over
a lifetime was estimated to be 70 mg/day.  The lifetime
estimates were derived using the equation presented above
that describes changes in soil ingestion with age (Sedman
and Mahmood, 1994).
      AIHC Exposure Factors Sourcebook (1994) - The
Exposure Factors Sourcebook (AIHC, 1994) uses data
from the Calabrese et al.  (1990)  study to derive soil
ingestion rates using zirconium as the tracer. More recent
papers indicate that  zirconium  is  not  a  good tracer.
Therefore,  the values recommended  in  the  AIHC
Sourcebook are not appropriate. Furthermore, because
individuals were only studied for a short period of time,
deriving a distribution of usual intake is not possible and
is inappropriate.
      Calabrese  and  Stanek  (1995)  -  Resolving
Intertracer Inconsistencies in Soil Ingestion Estimation -
Calabrese and  Stanek (1995)  explored  sources and
magnitude of positive and negative errors in soil ingestion
estimates for children on a subject-week and trace element
basis.  Calabrese and Stanek (1995) identified possible
sources of positive errors to be the following:

      •  Ingestion of high levels  of tracers before the
         study starts and low  ingestion during study
         period may result in over estimation of soil
         ingestion; and

      •  Ingestion of element tracers from a non-food or
         non-soil source during the study period.
Table 4-13. Tukey's Multiple Comparison of Mean Log Tracer Recovery in Adults Ingesting Known Quantities of Soil
Tracer
•
Aluminum
Silicon
Titanium
Vanadium
Yttrium

Aluminum
Silicon
Titanium
Reported Mean Age Adjusted Mean
(mg/day) (mg/day)
Calabrese et al., 1989 Study
153
154
218
459
85
Davis et al., 1990 Study
39
81
246

160
161
228
480
89

53
111
333
" Age adjusted mean estimates of soil ingestion in young children. Mean estimates of soil ingestion for each tracer in each study were
adjusted using the following equation:
Y = x e*""'1 12 * ^, where Y = adjusted mean soil ingestion (mg/day), x = a constant, and yr = age in years.
Source: Sedman and Mahmood, 1994.
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 Volume I - General Factors
 Chapter 4 - Soil Ingestion and Pica
 Possible sources of negative bias identified by Calabrese
 and Stanek (1995) are the following:

       •  Ingestion of tracers in food, but the tracers are
          not captured in the fecal sample either due to
          slow lag  time or not having a  fecal sample
          available on the final study day; and

       •  Sample measurement errors which result in
          diminished detection of fecal tracers, but not in
          soil tracer levels.

 The authors developed an approach which attempted to
 reduce the magnitude  of error in the individual  trace
 element ingestion estimates.   Results from a previous
 study conducted by Calabrese et al. (1989) were used to
 quantify these errors based  on the following criteria: (1)
 a lag period of 28 hours was assumed for the passage of
 tracers ingested in  food to the feces (this value was
 applied  to all  subject-day estimates);  (2) daily soil
 ingestion rate was estimated  for each tracer for each 24-hr
 day a fecal sample was obtained; (3) the median tracer-
 based soil ingestion  rate  for  each subject-day  was
 determined. Also, upper and lower bound estimates were
 determined based on criteria formed using an assumption
 of the magnitude of the relative standard deviation (RSD)
 presented  in another  study conducted  by Stanek and
 Calabrese (1995a). Daily soil ingestion rates for tracers
 that fell beyond the upper and lower ranges were excluded
 from  subsequent calculations,  and  the median  soil
 ingestion rates of the remaining tracer elements were
considered the best estimate for that particular day. The
magnitude of positive or negative error for a specific
tracer per day was derived by determining the difference
between the value for the tracer and the median value; (4)
negative errors due to missing fecal samples at the end of
the study period were also determined  (Calabrese and
Stanek, 1995).
      Table  4-14 presents the estimated magnitude of
positive and negative error for six tracer elements in the
children's study (i.e., conducted by Calabrese et al., 1989).
The original mean soil ingestion rates ranged from a low
of 21 mg/day based on zirconium to a high of 459 mg/day
based on titanium (Table 4-14). The  adjusted  mean soil
ingestion rate after correcting for negative and p&sitive
errors ranged from 97 mg/day based on yttrium  to 208
mg/day based on titanium (Table 4-14). Calabrese and
Stanek (1995) concluded that correcting for errors at the
individual level for each tracer element provides more
reliable estimates of soil ingestion.
      This report is valuable in providing additional
understanding of the nature of potential errors in trace
element specific estimates of soil ingestion. However, the
operational definition used for estimating the  error in a
trace element estimate was the observed difference of that
tracer from a median tracer value.  Specific identificatio"h
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
          Table 4-14. Positive/Negative Error (bias) in Soil Ingestion Estimates in the Calabrese et al. (1989) Mass-balance Study:
          	Effect on Mean Soil Ingestion Estimate (mg/day)a	
                                                        Negative Error



Aluminum
Silicon
Titanium
Vanadium
Yttrium
Zirconium
Lack of Fecal
Sample on Final
Study Day
14
15
82
66
8
6

Other Causes'"

11
6
187
55
26
91

Total Negative
Error
25
21
269
121
34
97

Total Positive
Error
43
41
282
432
22
. 5


Net Error
+18
+20
+13
+311
-12
-92

Original
Mean
153
154
218
459
85
21

Adjusted
Mean
136
133
208
148
97
113
  a  How to read table: for example, aluminum as a soil tracer displayed both negative and positive error. The cumulative total negative error is
    estimated to bias the mean estimate by 25 mg/day downward. However, aluminum has positive error biasing the original mean upward by
    43 mg/day. The net bias in the original mean was 18 mg/day positive bias. Thus, the original 156 mg/day mean for aluminum should be
    corrected downward to 136 mg/day.
  b  Values indicate impact on mean of 128-subject-weeks in milligrams of soil ingested per day.
  Source: Calabrese and Stanek. 1995.	
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                                                                          Volume I - General Factors
                                                                 Chapter 4 - Soil Ingestion and Pica
accurate estimate of soil ingestion, and the validity of this
assumption depends on the specific set of tracers used in
the study and need not be correct. The approach used for
the estimation of daily tracer intake is the same as in
Stanek and Calabrese (1995a), and some limitations of
that approach are mentioned in the review of that study.
      Sheppard (1995) - Parameter Values to Model the
Soil Ingestion Pathway - Sheppard (1995) summarized
the available literature on soil ingestion to estimate the
amount of soil ingestion in humans for the purposes of
risk assessment.   Sheppard (1995) categorized  the
available  soil  ingestion studies   into  two  general
approaches:  (1) those that measured the soil intake rate
with the use of tracers  in the soil, and (2) those that
estimated   soil  ingestion  based  on  activity  (e.g.,
hand-to-mouth) and exposure duration. Sheppard (1995)
provided estimates  of soil intake based on previously
published tracer studies. The data from these studies were
assumed to be lognormally distributed due to the broad
range, the concept that soil ingestion is never zero, and the
possibility of very high values.  In  order to account for
skewness  in  the data,  geometric means rather than
arithmetic means, were calculated by age, excluding pica
and geophagy values.  The  geometric mean for soil
ingestion rate for children under six was estimated to be
100 mg/day.   For children  over  six  and adults, the
geometric mean intake  rate  was  estimated to be  20
mg/day. Sheppard (1995) also provided soil ingestion
estimates for indoor and outdoor activities based on data
from Hawley (1985) and assumptions regarding duration
of exposure (Table 4-15).
      Sheppard's (1995) estimates, based on activity and
exposure duration, are quite similar to the mean values
from intake rate estimates described in previous sections.
The advantages of this study are that the model can be
used to calculate the ingestion rate from non-food sources
with variability in exposure ingestion rates and exposure
durations. The limitation of this study is that it does not
introduce new data; previous data are re-evaluated. In
addition, because the model is based on previous data, the
same advantages and limitations of those studies apply.

4.4.   SOIL INTAKE AMONG ADULTS
      Hawley 1985  - Assessment of Health  Risk from
Exposure to  Contaminated Soil - Information on soil
ingestion among adults is very limited. Hawley (1985)
estimated  soil  ingestion  among  adults   based  on
assumptions regarding activity patterns and corresponding
ingestion amounts.  Hawley (1985) assumed  that adults
ingest outdoor soil at a rate of 480 mg/day while engaged
in yardwork or other physical activity.  These outdoor
exposures were assumed  to occur 2 days/week during 5
months of the year (i.e., May through October).  The
ingestion estimate was based on the assumption that a 50
/^m/thick layer of soil is ingested from the inside surfaces
of the thumb and fingers of one hand. Ingestion of indoor
housedust was assumed to occur from typical living space
activities such as eating and smoking, and work in attics
or other uncleaned areas of the house. Hawley (1985)
assumed that adults ingest  an average  of 0.56  mg
housedust/day during typical living space activities and
 110 mg housedust/day while working in attics.  Attic work
Table 4-15. Soil Ingestion Rates for Assessment Purposes
Receptor Age
Pica Child
2.5 yrs
6yrs

Adult

Setting

Outdoor
Indoor
Outdoor
Indoor
Gardening
Indoor
Soil Load on
Hands
(mg/cm2)
—
0.5
0.4
0.5
0.04
1.0
0.04
a Hawley (1985) assumed the child spent all the time at home,
Source: Sheppard, 1995
Soil Exposure Ingestion
Rate
(mg/hr)
1,000
20
3
10
0.15
20
0.03
Suggested Exposure
Durations
(hr/yr)
200
1,000
Remaining3
700
5,000
300
5,000
Average Daily Soil
Ingestion
(mg/day)
500
50
60
20
2
20
0.4
so that the indoor time was 8,760 hours/year minus the outdoor time.
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 Volume I - General Factors
 Chapter 4 - Soil Ingestion and Pica
 was assumed to occur 12 days/year. Hawley (1985) also
 assumed that soil comprises 80 percent of household dust.
 Based on these assumptions about soil intake and the
 frequency of indoor and outdoor activities, Hawley (1985)
 estimated the annual average soil intake rate for adults to
 be 60.5 mg/day (Table 4-16).
 of 500  mg of soil  per  day) during the three  days.
 Duplicate  meal  samples  (food  and  beverage)  were
 collected from the six adults. The sample included all
 foods ingested  from  breakfast Monday,  through  the
 evening meal Wednesday during each of the 3 weeks. In
 addition, all medications  and vitamins ingested by the
Table 4-16. Estimates of Soil Ingestion for Adults
Scenarios
Adult
Work in attic (year-round)
Living Space (year-round)
Outdoor Work (summer)
TOTAL SOIL INTAKE
Exposure
Media (mg/day)
Dust 110
Dust 0.56
Soil 480

Days/Year
Activity
12
365
43

Annual Average Soil
Fraction Soil Intake
Content (mg/day)
0.8 3
0.8 0.5
1 57
60.5
Source: Hawley, 1985.
       The soil intake value estimated by Hawley (1985)
 is consistent with adult soil intake rates suggested by other
 researchers.  Calabrese et al. (1987) suggested that soil
 intake  among adults  ranges  from  1  to  100  mg/day.
 According to Calabrese et al.  (1987), these values "are
 conjectural and based on fractional estimates"  of earlier
 Center for Disease Control  (CDC) estimates.   In  an
 evaluation of the scientific literature concerning soil
 ingestion rates for children and adults (Krablin, 1989),,
 Arco Coal Company suggested  that 10 mg/day may be an
 appropriate value for adult soil ingestion.  This value is
 based   on    "extrapolation   from  urine    arsenic
 epidemiological studies and information  on  mouthing
 behavior and time activity patterns" (Krablin, 1989).
       Calabrese et al.  (1990) - Preliminary Adult Soil
 Ingestion Estimates: Results of a Pilot Study- Calabrese
 et al. (1990) studied six adults to evaluate the  extent to
 which they ingest soil. This adult study was originally part
 of the  children soil  ingestion  study conducted by
 Calabrese and was used to validate part of the analytical
 methodology used in the children study.  The participants
 were six healthy adults, three males and three females, 25-
 41 years old. Each volunteer ingested one empty gelatin
 capsule at breakfast and one at dinner Monday, Tuesday,
 and Wednesday during the first week of the study. During
 the second week, they ingested 50 mg of sterilized soil
 within a gelatin capsule at breakfast and at dinner (a total
 of 100 mg of sterilized soil per day) for 3 days. For the
 third week, the participants ingested 250 mg of sterilized
 soil in a gelatin capsule at breakfast and at dinner (a total
 adults were  collected.   Total excretory output were
 collected from Monday noon through Friday midnight
 over 3 consecutive weeks. Table 4-17 provides the mean
 and median values of soil ingestion for each element by
 week. Data  obtained from the first week, when empty
 gelatin capsules were ingested, may be used to derive an
 estimate of soil intake by adults.  The mean intake rates
 for the eight  tracers are: Al, 110 mg; Ba, -232 mg; Mn,
 330 mg; Si, 30 mg; Ti, 71 mg; V, 1,288 mg; Y, 63 mg;
 andZr, 134mg.
       The advantage of this study is that it provides
 quantitative estimates of soil ingestion for adults. The
 study also corrected for tracer concentrations in foods and
 medicines. However, a limitation of this study is that a
 limited number of subjects were studied. In addition, the
 subjects  were only studied for  one week before soil
 capsules were ingested.

 4.5.   PREVALENCE OF PICA
       The scientific literature define pica as "the repeated
 eating of non-nutritive substances" (Feldman, 1986). For
 the purposes  of this handbook,  pica is defined as  an
 deliberately high soil ingestion rate. Numerous  articles
 have been published that report on the incidence of pica
 among various populations.  However,  most of these
papers describe pica for substances other than soil
 including sand, clay,  paint, plaster, hair, string, cloth,
 glass, matches, paper, feces, and various other items.
These  papers  indicate  that  the   pica  occurs  in
approximately half of all children between the ages of 1
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                                                                         Volume I - General Factors
                                                                 Chapter 4 - Soil Ingestion and Pica
Table 4-17. Adult Daily Soil Ingestion Estimates by Week and Tracer Element After Subtracting Food and Capsule Ingestion,
Based on Median Amherst Soil Concentrations: Means and Medians Over Subjects (mg)a
Week
Means
1
2
3
Medians
1
2
3
Al
110
98
28
60
85
66
Ba
-232
12,265
201
-71
597
386
a Data were converted to milligrams
Negative values occur because of correction for food
Source: Calabreseetal.. 1990 	
Mn
330
1,306
790
388
1,368
831
and capsule ingestion.
Si
30
14
-23
31
15
-27

Ti
71
25
896
102
112
156

V
1,288
43
532
1,192
150
047

Y
63
21
67
44
35
60

Zr
134
58
-74
124
65
-144

and 3 years (Sayetta, 1986). The incidence of deliberate
ingestion behavior in children has been shown to differ for
different subpopulations.  The incidence rate appears to
be higher for black children than for white  children.
Approximately 30 percent of black children aged 1 to 6
years are reported to have deliberate ingestion behavior,
compared with 10 to 18 percent of white children in the
same age group (Danford, 1982).  There does not appear
to be any sex differences in the incidence rates for males
or females (Kaplan and Sadock,  1985).  Lourie et  al.
(1963) states that the incidence of pica is higher among
children in lower socioeconomic groups (i.e.,  50 to  60
percent) than in higher income families (i.e.,  about  30
percent). Deliberate soil ingestion behavior appears to be
more common in rural areas (Vermeer and Frate, 1979).
A higher rate of pica has also been reported for pregnant
women and  individuals with poor nutritional  status
(Danford,  1982). In general, deliberate ingestion behavior
is more frequent and more severe in mentally retarded
children than in children in the  general population
(Behrman and Vaughan 1983, Danford 1982, Forfar and
Arneil 1984, Illingworth 1983, Sayetta 1986).
       It should be noted that the pica statistics cited
above  apply to the incidence of general pica and not soil
pica. Information on the incidence of soil pica is limited,
but it appears that soil pica is less common. A study by
Vermeer and Frate (1979) showed that the incidence of
geophagia (i.e., earth-eating) was about 16 percent among
children from a rural black community in Mississippi.
However, geophagia was described as a cultural practice
among the  community  surveyed  and  may not  be
representative of the general population. Average daily
consumption of soil was estimated to  be 50 g/day. Bruhn
and Pangborn (1971) reported the incidence of pica  for
"dirt" to be 19 percent in children, 14 percent in pregnant
women, and 3 percent in nonpregnant women.  However,
"dirt" was not clearly defined.  The Bruhn and Pangborn
(1971) study was conducted among 91  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
Wijnen 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.

4.6.    DELIBERATE SOIL INGESTION AMONG
       CHILDREN
       Information on the amount of soil  ingested  by
children with abnormal soil ingestion behavior is limited.
However, some evidence suggests that a rate on the order
of 10 g/day may not be unreasonable.
       Calabrese  et al. (1991) - Evidence of Soil Pica
Behavior and Quantification of Soil Ingestion - Calabrese
et al. (1991) estimated that upper range soil ingestion
values  may range from approximately 5-7 grams/day.
This estimate was based on observations of one pica child
among the 64 children who participated in the study.  In
the study, a 3.5-year old female exhibited extremely high
soil  ingestion behavior during one of the two weeks of
observation.  Intake ranged from 74 mg/day to 2.2 g/day
Page
4-18
                   Exposure Factors Handbook
                                     August 1997

-------
 Volume I - General Factors
 Chapter 4 - Soil Ingestion and Pica
 during the first week of observation and 10.1 to 13.6
 g/day  during  the   second  week  of  observation
 (Table 4-18). These results are based on mass-balance
 analyses for seven (i.e., aluminum, barium, manganese,
 silicon, titanium,  vanadium, and yttrium) of the eight
 tracer elements used. Intake rates based on zirconium was
 significantly lower but Calabrese et al. (1991) indicated
 that this may have  "resulted from  a limitation in the
 analytical protocol."
Table 4-18. Daily Soil Ingestion Estimation in a Soil-Pica Child by
Tracer and by Week (mg/day)
Tracer
Al
Ba
Mn
Si
Ti
V
Y
Zr
Source:
Weekl
Estimated Soil Ingestion
74
458
2,221
142
1,543
1,269
147
86
Calabrese et al.. 1991
Week 2
Estimated Soil Ingestion
13,600
12,088
12,341
10,955
11,870
10,071
13,325
2695

       Calabrese and Stanek (1992) - Distinguishing
 Outdoor Soil Ingestion from Indoor Dust Ingestion in a
 Soil  Pica  Child  -  Calabrese  and  Stanek (1992)
 quantitatively distinguished the amount of outdoor soil
 ingestion from indoor dust ingestion in a soil pica child.
 This study was based on a previous mass-balance study
 (conducted in 1991) in which a 3-1/2 year old child
ingested 10-13 grams of soil per day  over the second
week of a 2-week soil ingestion study. Also, the previous
study  utilized a soil tracer methodology with  eight
different tracers  (Al, Ba, Mn, Si,  Ti, V,  Y, Zr).  The
reader is referred to Calabrese et al. (1989) for a detailed
description and  results of  the soil ingestion  study.
Calabrese and Stanek (1992) distinguished indoor dust
from outdoor soil  in ingested soil based on a methodology
which compared differential element ratios.
       Table 4-19 presents tracer ratios of soil, dust, and
residual fecal samples in the  soil pica child. Calabrese
and Stanek (1992) reported that there was a maximum
total of 28 pairs of tracer ratios  based on eight tracers.
However, only 19 pairs of tracer ratios were available for
quantitative evaluation as shown in Table 4-19.  Of these
19 pairs, 9 fecal tracer ratios fell within the boundaries for
soil and dust (Table 4-19). For  these 9 tracer soils, an
interpolation  was performed to estimate the relative
contribution of soil and dust to the residual fecal tracer
ratio. The other 10 fecal tracer ratios that fell outside the
soil and dust boundaries were  concluded to be  100
percent of the  fecal tracer ratios from soil  origin
(Calabrese and Stanek, 1992). Also, the 9 residual fecal
samples within  the  boundaries  revealed that a high
percentage (71-99 percent) of the residual fecal tracers
were estimated to be of soil origin. Therefore, Calabrese
and Stanek  (1992)  concluded  that the  predominant
proportion of the fecal tracers  was from outdoor soil and
not from indoor dust origin.
Table 4-19. Ratios of Soil, Dust, and Residual Fecal Samples in the Soil Pica Child
Tracer Ratio Pairs
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
Source
Mn/Ti
Ba/Ti
Si/Ti
V/Ti
Ai/Ti
Y/Ti
Mn/Y
Ba/Y
Si/Y
V/Y
Al/Y
Mn/Al
Ba/Al
Si/Al
V/A1
Si/V
Mn/Si
Ba/Si
Mn/Ba
: Calabrese and Stanek,
Soil
208.368
187.448
148.117
14.603
18.410
8.577
24.293
21.854
17.268
1.702
2.146
11.318
10.182
8.045
0.793
10.143
1.407
1.266
1.112
1992.
Fecal
215.241
206.191
136.662
10.261
21.087
9.621
22.373
21.432
14.205
1.067
2.192
10.207
9.778
6.481
0.487
13.318
1.575
1.509
1.044

Estimated % of Residual Fecal Tracers of Soil
Dust Origin as Predicted by Specific Tracer Ratios
260.126
115.837 '
7.490
17.887
13.326
5.669
45.882
20.432
1.321
3.155 •
2.351
19.520
8.692
0.562
1.342
0.419
34.732
15.466
2.246

87
100
92
100
100
100
100
71
81
100
88
100
73
81 '
100
100
99
83
100

Exposure Factors Handbook
August 1997
                                             Page
                                              4-19

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                                                                           Volume I - General Factors
                                                                  Chapter 4 - Soil Ingestion and Pica
     In conducting a risk assessment for TCDD, U.S.
EPA (1984) used 5 g/day to represent the soil intake rate
for pica children. The Centers for Disease Control (CDC)
also investigated  the potential for exposure to TCDD
through the soil ingestion route. CDC used a value of 10
g/day to represent the amount of soil that a child with
deliberate  soil  ingestion   behavior  might   ingest
(Kimbrough et al.,  1984). These values are consistent
with those observed by Calabrese et al. (1991).

4.7. RECOMMENDATIONS
     The key studies described in this section were used
to recommend values for soil  intake among children. The
key and relevant studies used  different survey designs and
study populations. These studies are summarized in Table
4-20. For example, some of the studies considered food
and nonfood sources of trace elements, while others did
not.  In other studies, soil ingestion  estimates were
adjusted to account for the contribution of house dust to
this estimate.  Despite these differences, the mean and
upper-percentile estimates reported for these studies are
relatively consistent. The confidence rating for soil intake
recommendations is presented in Table 4-21.
     It is important, however, to understand the various
uncertainties  associated  with  these  values.    First,
individuals were not studied for sufficient periods of time
to get a good estimate of the usual intake. Therefore, the
values presented in this section may not be representative
of long term exposures.  Second, the experimental error in
measuring soil ingestion values for individual children is
also a source of uncertainty. For example, incomplete
sample collection of both input (i.e., food and nonfood
sources) and output (i.e., urine and feces) is a limitation
for  some  of the  studies  conducted.  In addition, an
individual's soil ingestion value may be artificially high or
low depending on the extent to which a mismatch between
input and output occurs due to individual variation in the
gastrointestinal transit time.  Third, the degree to which
the tracer elements used in these studies are absorbed in
the human body is uncertain.   Accuracy of the soil
ingestion estimates depends on how good this assumption
is.  Fourth, there  is uncertainty  with regard  to  the
homogeneity of soil samples and the accuracy of parent's
knowledge about their child's playing areas.  Fifth, all the
soil ingestion studies presented in this section with the
exception  of Calabrese et  al.  (1989) were conducted
during the summer when soil contact is more likely.
     Although the recommendations presented below are
derived from studies which were mostly conducted in the
summer, exposure during the winter months when the
ground  is  frozen or  snow  covered  should  not be
considered as zero.   Exposure  during these  months,
although lower than in the summer months, would not be
zero because some portion of the house dust comes from
outdoor soil.
     Soil Ingestion Among Children - Estimates of the
amount of soil ingested by children are summarized in
Table 4-22. The mean values ranged from 39 mg/day to
271  mg/day  with an average  of 146 mg/day for  soil
ingestion and 191 mg/day for soil and dust ingestion.
Results obtained using titanium as a tracer in the Binder
et al. (1986) and Clausing et al. (1987) studies were not
considered in the derivation  of this recommendation
because these studies  did not take into consideration other
sources of the element in the diet which for  titanium
seems to be  significant. Therefore, these values  may
overestimate the soil intake.  One can note that this group
of mean values is consistent with the 200 mg/day value
that EPA programs  have used as a conservative mean
estimate.   Taking into consideration that the highest
values were seen with titanium,  which may exhibit greater
variability than the other tracers, and the fact that the
Calabrese et  al. (1989) study included a pica child, 100
mg/day is the best estimate of the mean for children under
6 years of age. However, since the children were studied
for short periods of time and the prevalence of  pica
behavior is not known,  excluding the pica child from the
calculations may underestimate soil intake rates.   It is
plausible that many children may exhibit some  pica
behavior if studied for longer periods of time.  Over the
period of study, upper percentile values ranged from 106
mg/day to 1,432 mg/day with an average of 383 mg/day
for soil ingestion and  587 mg/day for soil and  dust
ingestion.    Rounding  to  one significant figure, the
recommended upper percentile  soil ingestion rate for
children is 400  mg/day. However, since  the period  of
study was short,  these  values are not estimates of usual
intake.  The recommended values for soil ingestion among
children and  adults are summarized in Table 4-23.
      Data on soil  ingestion  rates for children  who
deliberately ingest soil are also limited. An  ingestion rate
of 10 g/day is a reasonable value for use in acute exposure
assessments,  based on the available information.  It should
be noted, however,  that this value is based on only one
pica child observed in the Calabrese et al. (1989) study.
      Soil Ingestion  Among Adults  - Only three studies
have attempted to estimate adult soil ingestion. Hawley
(1985)  suggested a value  of 480  mg/day for adults
 Page
 4-20
                   Exposure Factors Handbook
                  	          August 1997

-------
 Volume I -General Factors
 Chapter 4 - Soil Ingestion and Pica
 engaged in outdoor activities and a range of 0.56 to 110
 mg/day of house dust during indoor activities.  These
 estimates were derived from assumptions about soil/dust
 levels on hands and mouthing behavior; no supporting
 measurements were made.  Making further assumptions
 about  frequencies  of indoor and outdoor  activities,
 Hawley (1985) derived an annual average of 60.5 mg/day.
 Given  the lack of  supporting  measurements, these
 estimates must be considered conjectural. Krablin (1989)
 used arsenic  levels  in urine (n=26)  combined with
 information on mouthing behavior and activity patterns to
 suggest an estimate for adult soil ingestion of 10 mg/day.
 The study protocols are not well described and has not
 been formally published. Finally, Calabrese et al. (1990)
 conducted a tracer study on 6 adults and found a range of
 30 to  100 mg/day.   This  study is probably the most
 reliable of the three, but  still has  two  significant
 uncertainties: (1)
representativeness of the general population is unknown
due   to   the   small   study   size   (n=6);  and   (2)
representativeness of long-term  behavior  is unknown
since the study was conducted over only 2 weeks. In the
past, many EPA risk assessments have assumed an adult
soil ingestion rate of 50 mg/day for industrial settings and
100  mg/day for residential and agricultural  scenarios.
These values are within the range of estimates from the
studies discussed above. Thus, 50 mg/day still represents
a reasonable central estimate of adult soil ingestion and is
the  recommended  value  in  this  handbook.     This
recommendation is clearly highly uncertain; however, and
as indicated in Table 4-21, is  given  a low confidence
rating.  Considering  the uncertainties in the  central
estimate, a recommendation for an  upper percentile value
would be  inappropriate.  Table 4-23 summarizes soil
ingestion recommendations for adults.
Exposure Factors Handbook
August 1997
                                            Page
                                             4-21

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       Volume I - General Factors
Chapter 4 - Soil Ingestion and Pica









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 Volume I - General Factors
 Chapter 4 - Soil Ingestion and Pica








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Exposure Factors Handbook
August 1997     	
Page
4-23

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                                                                                          Volume I - General Factors
                                                                               Chapter 4 -Soil In^estion and Pica
                                       Table 4-21.  Confidence in Soil Intake Recommendation
                                                                     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)	
Page
4-24
                                              Exposure Factors Handbook

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 Volume I - General Factors
 Chapter 4 - Soil Ingestion and Pica
Table 4-22. Summary of Estimates of Soil Ingestion by Children
Mean (mg/day)
Al Si AIRa Ti Y
181 184
230 129
39 . 82 245.5
64.5b 160b 268.4b
153 154 218 85
154b 483b 170b 65b
122 139 - 271 165
133C
69-120d
Average = 146 mg/day soil
191 mg/day soil and dust
combined
a AIR = Acid Insoluble Residue
b Soil and dust combined
c BTM
d LTM; corrected value

Al
584



223
478b
254
217C
Si Ti Y
578



276 1,432 106
653b l,059b 159b
224 279 144



Binder etal. 1986
Clausing et al. 1987
Davis etal. 1990

Calabrese et al. 1989

Stanek and Calabrese,
Stanek and Calabrese.








1995a
1995b
Van Wljnen et al. 1990
383 mg/day soil
587 mg/day soil and dust combined




















Table 4-23. Summary of Recommended Values for Soil Ingestion
Population Mean
Children , IQQ mg/daya
Adults 50 mg/day
Pica child lOe/dav^
Upper Percentile
400 mg/dayb
r% '
, 200 mg/day may be used as a conservative estimate of the mean (see text).
Study period was short; therefore, these values are not estimates of usual intake.
To be used in acute exposure assessments. Based on only one pica child (Calabrese et al 1989)
4.8.    REFERENCES FOR CHAPTER 4

American Industrial Health Council (AIHC). (1994)
    Exposure factors sourcebook. AIHC, Washington,
    DC.
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.; Kostecki, P.T.; Gilbert, C.E. (1987)
    How much soil do children eat?  An emerging
    consideration for environmental health risk
    assessment. In press (Comments in Toxicology).
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.; Barnes,
    R.M.  (1990) Preliminary adult soil ingestion
    estimates; results of a pilot study. Regul. Toxicol.
    Pharmacol. 12:88-95.
Calabrese, E.J.; Stanek, E.J.; Gilbert, C.E. (1991)
    Evidence of soil-pica behavior and quantification
Exposure Factors Handbook
August 1997
                                           Page
                                            4-25

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                                                                         Volume I - General Factors
                                                                 Chapter 4 - Soil Ingestion and Pica
        of soil ingested. Hum. Exp. Toxicol. 10:245-
        249.
Calabrese, E.J.; Stanek, EJ. (1992)  Distinguishing
    outdoor soil ingestion from indoor dust ingestion in
    a soil pica child. Regul. Toxicol. Pharmacol.
    15:83-85.
Calabrese, E.J.; Stanek, EJ. (1995)  Resolving
    intertracer inconsistencies in soil ingestion
    estimation. Environ. Health Perspect. 103(5):454-
    456.
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.
Day,  J.P.; Hart, M.; Robinson, M.S. (1975)  Lead in
    urban street dust. Nature 253:343-345.
Duggan, M.J.; Williams, S. (1977) Lead in dust in city
    streets. Sci. Total Environ. 7:91-97.
Feldman, M.D. (1986) Pica: current perspectives.
    Psychosomatics (USA) 27(7):519-523.
Forfar, J.O.; Arneil, G.C., eds. (1984) Textbook of
    Paediatrics. 3rd ed. London: Churchill
    Livingstone.
 Hawley, J.K.  (1985) Assessment of health risk from
     exposure to contaminated soil. Risk Anal. 5:289-
     302.
 Illingworth, R.S.  (1983) The normal child. New York:
     Churchill Livingstone.
 Kaplan, H.I.; Sadock, B.J. (1985)  Comprehensive
     textbook of psychiatry/TV. 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.
 Krablin, R. (1989) [Letter to Jonathan Z. Cannon
     concerning soil ingestion rates.]  Denver, CO:
      Arco Coal Co.; October  13, 1989.
Lepow, M.L.; Bruckman, L.; Robino, R.A.; Markowitz,
    S.; Gillette, M.; et al.  (1974) Role of airborne lead
    in increased body burden of lead in Hartford
    children. Environ. Health Perspect. 6:99-101.
Lepow, M.L.; Buckman, L.; Gillette, M.; Markowitz,
    S.; Robino, R.; et al. (1975) Investigations into
    sources of lead in the environment of urban
    children. Environ. Res. 10:415-426.
Lourie, R.S.; Layman, E.M.; Millican, F.K.  (1963)
    Why children eat things that are not food. Children
     10:143-146.
Reels, H.; Buchet, J.P.; Lauwerys, R.R. (1980)
    Exposure to lead by the oral and pulminary route of
    children living in the vicinity of a primary lead
    smelter. Environ. Res. 22:81-94.
Sayetta, R.B. (1986)  Pica: An overview. American
    Family Physician 33(5):181-185.
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.
Sheppard, S.C. (1995) Parameter values to model the
     soil ingestion pathway. Environmental Monitoring
     and Assessment 34:27-44.
 Stanek, E.J.; Calabrese, EJ.  (1995a) Daily estimates
     of soil ingestion in children. Environ. Health
     Perspect. 103(3):276-285.
 Stanek, EJ.; Calabrese, EJ. (1995b) Soil ingestion
     estimates for use in site evaluations based on the
     best tracer method. Human and Ecological Risk
     Assessment. 1:133-156.
 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.
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Chapter 5 - Inhalation
5.    INHALATION ROUTE
      This chapter presents data and recommendations
for inhalation rates that can be used to assess exposure to
contaminants in air. The studies discussed in this chapter
have been classified as key or relevant. Key studies are
used as the basis for deriving recommendations and the
relevant studies  are included to  provide additional
background  and  perspective.    The  recommended
inhalation rates are summarized in Section 5.2.4 and cover
adults, children, and outdoor workers/athletes.
      Inclusion of this chapter in the Exposure Factors
Handbook does not imply that assessors will always need
to select and use  inhalation rates  when  evaluating
exposure to air contaminants. In fact, it is unnecessary to
calculate inhaled dose when using dose-response factors
from  Integrated Risk Information System (IRIS) (U.S.
EPA,  1994).     This  is  due to  the fact that IRIS
methodology  accounts  for  inhalation  rates  in   the
development of "dose-response"  relationships.  When
using  IRIS  for  inhalation  risk assessments,  "dose-
response"  relationships require  only an  average air
concentration to evaluate health concerns:

       •  For non-carcinogens, IRIS  uses Reference
         Concentrations (RfC) which are expressed in
         concentration units. Hazard is  evaluated by
         comparing the inspired air concentration to the
         RfC.

       •  For carcinogens, IRIS  uses unit risk values
         which are  expressed in inverse concentration
         units. Risk is evaluated by multiplying the unit
         risk by the inspired air concentration.

Detailed descriptions  of  the  IRIS  methodology for
derivation of inhalation reference concentrations can be
found in two methods manuals produced by the Agency
(U.S. EPA,  1992; 1994).
       IRIS employs a default inhalation rate of 20
m3/day. This is greater than the recommendated value in
this chapter.  When using IRIS, adjustments of dose-
response relationships using inhalation rates other than the
default, 20 m3/day,  are not currently recommended.
There  are  instances where the inhalation  rate  data
presented in this  chapter  may be  used for estimating
average daily dose. For example, the inhalatino average
daily dose is often estimated in cases where a compative
pathway analysis is desired or to determine a total dose by
adding across pathways in cases where RfCs and unit risk
factors are not available.

5.1.   EXPOSURE EQUATION FOR INHALATION
      For  those  cases where the average daily dose
(ADD) needs to be estimated, the general equation is:
  ADD = [[C x IR x ED] / [BW x AT]]

  where:
(Eqn. 5-1)
    ADD =  average daily dose (mg/kg-day);
    C    =  contaminant concentration in inhaled air (/ug/m3);
    IR   =  inhalation rate (m3/day);
    ED   =  exposure duration (days);
    BW  =  body weight (kg); and
    AT   =  averaging time (days), for non-carcinogenic effects
            AT = ED, for carcinogenic or chronic effects AT =
            70 years or 25,550 days (lifetime).
      The average daily dose is the dose rate averaged
over a pathway-specific period of exposure expressed as
a daily dose on a per-unit-body-weight basis. The ADD
is used for exposure to chemicals with non-carcinogenic
non-chronic effects. For compounds with carcinogenic or
chronic effects, the lifetime average daily dose (LADD)
is used.  The LADD is  the dose rate averaged  over a
lifetime.  The contaminant concentration refers to the
concentration of the contaminant in inhaled air. Exposure
duration refers to the total time an individual is exposed
to an air pollutant.

5.2.  INHALATION RATE
5.2.1. Background
      The Agency defines exposure as the chemical
concentration at the boundary of the body (U.S. EPA,
1992).   In  the  case of inhalation, the  situation is
complicated by the fact that oxygen exchange with carbon
dioxide takes place in the distal portion of the lung.  The
anatomy  and  physiology  of  the  respiratory  system
diminishes  the pollutant concentration  in  inspired air
(potential dose) such that the amount of a pollutant that
actually enters the body through the lung (internal dose)
is less than that measured at the boundary of the body
(Figure 5-1).  When constructing risk assessments that
concern the inhalation route  of exposure, one must be
aware if any adjustments have been employed in the
estimation of the pollutant concentration to account for
this reduction in potential dose.
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                                                                                 Chapter 5 - Inhalation
                                                                       Biologically
                                                                       Effective
                                                                       Dose
   Exposure
    Chemical
                                                                                        Effect
              Mouth / Nose
                 Intake
                                                Lung
Uptake
                       Figure 5-1. Schematic of Dose and Exposure: Respiratory Route
Source: U.S. EPA, 1992.
      The respiratory  system is comprised  of three
regions:    nasopharyngeal,   tracheobronchial,   and
pulmonary. The nasopharyngeal region extends from the
nose to the larynx. The tracheobronchial region forms the
conducting airways  between nasopharynx and alveoli
where gas exchange occurs.  It consists of the trachea,
bronchi, and bronchioles. The pulmonary regions consists
of the acinus which is the site where gas exchange occurs;
it is comprised of respiratory bronchioles, alveolar ducts
and sacs, and alveoli. A  detailed discussion of pulmonary
anatomy and physiology can  be found in:  Benjamin
(1988) and U.S. EPA (1989 and 1994).
      Each region in  the respiratory system can be
involved with removing pollutants from inspired air. The
nasopharyngeal region filters out large inhaled particles,
moderates the temperature, and increases the humidity of
the air.   The surface of the tracheobronchial region is
covered with ciliated mucous secreting cells which forms
a mucociliary escalator  that moves particles from deep
regions of the lung to the oral cavity where they may be
swallowed and then excreted. The branching pattern and
physical dimensions  of  the these airways determine the
pattern of deposition of airborne particles and absorption
of gases  by  the respiratory tract.   They decrease in
       diameter as they divide into  a bifurcated  branching
       network dilutes gases by axial diffusion of gases along the
       streamline of airways and radial diffusion of gases due to
       an increase in cross sectional area of the lungs.  The
       velocity of the airstream in this decreasing  branching
       network creates a turbulent force such  that airborne
       particles can be deposited along the walls of these airways
       by impaction, interception,  sedimentation, or diffusion
       depending on their size. The pulmonary region contains
       macrophages which engulf particles and pathogens that
       enter this portion of the lung.
             Notwithstanding these removal mechanisms, both
       gaseous and particulate pollutants can deposit  in various
       regions of the lung. Both the physiology of the lung and
       the  chemistry  of the  pollutant  influences where  the
       pollutant tends to deposit.
             Gaseous pollutants are evenly dispersed in the air
       stream.  They come into contact with a large  portion of
       the  lung.   Generally, their solubility and  reactivity
       determines where they deposit in the lung. Water soluble
       and chemically reactive gases tend to deposit in the upper
       respiratory  tract.  Lipid soluble  or non-reactive gases
       usually are not removed in the upper airways and tend to
       deposit in the distal portions of the lung..  Gases can be
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Volume I - General Factors
Chapter 5 - Inhalation
absorbed into the blood stream or react with lung tissue.
Gases can be removed from the lung by reaction with
tissues or by expiration.  The amount of gas retained in
the lung or other parts of the body is mainly due to their
solubility in blood.
      Chemically, particles are quite heterogenous. They
range from aqueous soluble particles to solid insoluble
particles.  Their size,  chemical composition, and  the
physical forces of breathing dictate where they tend to
deposit in the lung. Large particles, those with a diameter
of greater than 0.5 micrometers (um), not filtered out in
the nasopharynx, tend to deposit in the upper respiratory
tract at  airway branching points due to impaction.  The
momentum of these particles in the air stream is such that
they tend to collide with the airway wall at branching
points in the tracheobronchial region of the lung. Those
particles not removed  from the airstream by impaction
will likely be deposited in small bronchi and bronchioles
by sedimentation, a process where by particles settle out
of the airstream due to the decrease in airstream velocity
and the gravitational  force  on the particles.  Small
particles, less than 0.2 um, acquire a random motion due
to bombardment by air molecules.  This movement can
cause particles to be deposited on the wall of an air way
throughout the lungs.
      A special case exists for fibers. Fibers can deposit
along  the  wall  of  an airway by a process known as
interception. This occurs when a fiber makes contact with
an airway wall. The likelihood of interception increases
as airway diminish  in diameter. Fiber shape influences
deposition too.  Long, thin, straight fibers tend to deposit
in the deep region of the lung compared to thick or curved
fibers.
      The health risk associated with human exposure to
airborne toxics is  a  function  of concentration of  air
pollutants, chemical species, duration of exposure, and
inhalation rate.  The  dose delivered  to target organs
(including the lungs) , the biologically  effective dose, is
dependent on the potentail dose, the  applied dose and the
internal dose (Figure 5-1) A detailed discussion of this
concept can  be found  in  Guidelines  for  Exposure
Assessment (U.S. EPA, 1992).
       The  estimation of applied dose for  a given  air
pollutant is dependent  on  inhalation rate, commonly
described as ventilation rate (VR) or breathing rate. VR
is usually measured as minute volume, the volume in liters
of air exhaled per minute(VE).  VE is the product of the
number of respiratory cycles in a minute and the volume
of air respired during each respiratory cycle, the tidal
volume( VT).
      When interested in calculating internal dose,
assessors must consider the alveolar ventilation rate. This
is the amount of air available for exchange with alveoli
per unit time. It is equivalent to the tidal volume( VT)
minus the anatomic dead space of the lungs (the space
containing air that does not come into contact with the
alveoli).  Alveolar ventilation is approximately 70 percent
of total ventilation; tidal volume is approximately 500
milliliters (ml) and the amount of anatomic dead space in
the lungs is approximately 150 ml, approximately 30% of
the amount of air inhaled (Menzel and Amdur, 1986).
      Breathing rates are affected by numerous individual
characteristics, including  age, gender, weight, health
status, and levels of activity (running, walking, jogging,
etc.). VRs are either measured directly using a spirometer
and a collection system or indirectly from heart rate (HR)
measurements. In many of the studies described in the
following  sections,  HR  measurements   are usually
correlated with VR  in  simple and multiple  regression
analysis.
      The  available studies  on  inhalation rates  are
summarized in the following sections. Inhalation rates are
reported for adults and  children (including infants)
performing   various  activities  and  outdoor  workers/
athletes. The activity levels have been categorized as
resting, sedentary, light, moderate, and heavy.  In most
studies, the sample population kept diaries to record their
physical  activities,  locations,  and  breathing  rates.
Ventilation rates were either measured, self-estimated or
predicted  from   equations   derived  using  VR-HR
calibration relationships.

5.2.2.  Key Inhalation Rate Studies
       Linn  et al. (1992) - Documentation of Activity
Patterns in "High-Risk" Groups Exposed to Ozone in the
Los Angeles Area - Linn et al. (1992) conducted a study
that  estimated the inhalation  rates for  "high-risk"
subpopulation groups exposed to  ozone (O3) in their daily
activities in the Los  Angeles  area.  The population
surveyed consisted of seven subject panels: Panel 1: 20
healthy outdoor workers (15 males, 5 females, ages 19-50
years); Panel 2: 17 healthy elementary school students (5
males, 12 females, ages 10-12 years); Panel 3: 19 healthy
high school students (7 males,  12 females, ages 13-17
years); Panel  4: 49 asthmatic  adults (clinically mild,
moderate, and severe, 15 males, 34 females, ages 18-50
years); Panel 5:24 asthmatic adults from 2 neighborhoods
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                                                                                         Chapter 5 - Inhalation
 of contrasting O3 air quality (10 males, 14 females, ages
 19-46 years); Panel 6: 13 young asthmatics (7 males, 6
 females, ages 11-16 years); Panel 7: construction workers
 (7 males, ages 26-34 years).
       Initially, a calibration test was conducted, followed
 by a training session. Finally, a field study was conducted
 which involved subjects' collecting their own heart rate
 and diary data.  During the calibration tests, VR and HR
 were  measured simultaneously at each  exercise level.
 From the calibration data  an  equation was developed
 using linear regression  analysis  to predict  VR from
 measured HR (Linn et al., 1992).
       In the field study, each subject (except construction
 workers) recorded in diaries: their daily activities, change
 in locations (indoors, outdoors, or in a vehicle), self-
 estimated breathing rates during each  activity/location,
 and time spent at each activity/location.  Healthy subjects
 recorded their HR once every  60 seconds,  Asthmatic
 subjects recorded their diary information once every hour
 using a Heart Watch. Construction workers dictated their
 diary information to a technician accompanying them on
 the job. Subjective breathing rates were defined as slow
 (walking at their normal  pace);  medium  (faster than
 normal walking); and fast (running or similarly strenuous
                         exercise).  Table 5-1 presents the calibration and field
                         protocols for self-monitoring of activities for each subject
                         panel.
                               Table  5-2  presents the  mean  VR,  the  99th
                         percentile  VR, and  the mean VR at  each subjective
                         activity level (slow, medium,  fast). The mean VR and
                         99th percentile VR were derived from all HR recordings
                         (that appeared to be valid) without considering the diary
                         data.  Each of the three activity  levels  was determined
                         from both the concurrent diary data and HR recordings by
                         direct calculation or regression (Linn et al.,  1992). The
                         mean VR for healthy adults was 0.78  m3/hr while the
                         mean VR for asthmatic adults was 1.02 m3/hr (Table 5-2).
                         The preliminary data for construction workers indicated
                         that during a  10-hr work  shift, their mean  VR (1.50 nrVhr)
                         exceeded the VRs of all other subject panels (Table 5-2).
                         Linn et al. (1992) reported that the diary data showed that
                         most individuals except construction workers spent most
                         of their time (in a typical day) indoors  at slow activity
                         level.  During slow activity, asthmatic subjects had higher
                         VRs than healthy subjects, except construction workers
                         (Table 5-2).   Also, Linn et al. (1992)  reported that in
                         every panel, the predicted VR correlated significantly with
                         the subjective estimates  of activity levels.
                  Table 5-1. Calibration and Field Protocols for Self-Monitoring of Activities Grouped by Subject Panels
                Panel
                                               Calibration Protocol
                                                                                          Field Protocol
  Panel 1 - Healthy Outdoor Workers -15
  female, 5 male, age 19-50
  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 4 - Adult Asthmatics, clinically
  mild, moderate, and severe - 15 male,
  34 female, age 18-50
  Panel 5 - Adult Asthmatics from 2
  neighborhoods of contrasting O3 air
  quality - 10 male, 14 female, age 19-46

  Panel 6 - Young Asthmatics - 7 male, 6
  female, age 11-16
  Pane! 7 - Construction Workers - 7
  male, age 26-34
Laboratory treadmill exercise tests, indoor
hallway walking tests at different self-chosen
speeds, 2 outdoor tests consisted of 1-hour
cycles each of rest» walking, and jogging.
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
Treadmill and hallway exercise tests
Treadmill and hallway exercise tests
Laboratory exercise tests on bicycles and
treadmills
Performed similar exercises as Panel 2 and 3,
and also performed job-related tests including
lifting and carrying a 9-kg pipe.
3 days in 1 typical summer week (included most
active workday and most active day off); HR
recordings and activity diary during waking
hours.
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.
1 typical summer week, 1 typical winter week;
hourly activity/health diary during waking hours;
lung function tests 3 times daily; HR recordings
during waking hours on at least 3 days (including
most active work day and day off).
Similar to Panel 4, personal NO, and acid
exposure monitoring included. (Panels 4 and 5
were studied in different years, and had 10
subjects in common).
Similar to Panel 4, summer monitoring for 2
successive weeks, including 2 controlled
exposure studies with few or no observable
respiratory effects.
HR recordings and diary information during 1
typical summer work day.
  Source:  Linnet al.. 1992
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Volume I - General Factors
Chapter 5 - Inhalation
              Table 5-2.  Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and Self-Estimated Breathing Rates
                                                                      Inhalation Rates (m /hr)
                Panel
                                                MeanVR
                                                 fm3/hr)
  99th Percentile
      VR
    Mean VR at Activity Levels
   	On3/hrtb	
                                                                              Slow
                                                                                         Medium'
                                              Fast0
  Healthy
   1-Adults                              20        0,78
   2 - Elementary School Students              17        0.90
   3 - High School Students                   19        0.84
   7 - Construction Workers0                   7        1.50
  Asthmatics                                           ;
   4-Adults                              49        1.02
   5-Adultsd                             24        1.20
   6 - Elementary and High School Students      13  	1.20
      2.46
      1.98
      2.22
      4.26

      1.92
      2.40
      2.40
0.72
0.84
0.78
1.26

1.02
1.20
1.20
1.02
0.96
1.14
1.50

1.68
2.04
1.20
3.06
1.14
1.62
1.68

2.46
4.02
1.50
        Number of individuals in each survey panel.
        Some subjects did not report medium and/or fast activity. Group means were calculated from individual means (i.e., give equal weight
        to each individual who recorded any time at the indicated activity level).
        Construction workers recorded only on 1 day, mostly during work, while others recorded on a 1 work or school day and a 1 day off.
        Excluding subjects also in Panel 4.
  Source:  Linn etal., 1992.
      A limitation of this study is that calibration data
may overestimate  the predictive power of HR  during
actual field monitoring. The wide variety of exercises in
everyday activities may result in greater variation of the
VR-HR relationship than calibrated. Another limitation
of this  study is  the  small  sample  size  of  each
subpopulation surveyed.  An advantage of this study is
that diary data can provide rough estimates of ventilation
patterns  which are useful in  exposure  assessments.
Another advantage is that inhalation rates were presented
for various subpopulations  (i.e., healthy  outdoor adult
workers,  healthy children, asthmatics, and construction
workers).
      Spier   et al.  (1992)  -   Activity  Patterns  in
Elementary  and  High School Students  Exposed To
Oxidant Pollution  -   Spier et  al. (1992) investigated
activity patterns of 17  elementary school students (10-12
years old) and 19 high school students (13-17 years old)
in suburban Los Angeles from late September to October
(oxidant  pollution season).   Calibration  tests  were
conducted in supervised outdoor exercise sessions. The
exercise sessions consisted  of 5 minutes for each: rest,
slow walking, jogging, and fast walking.  HR and VR
were measured during the last 2 minutes of each exercise.
Individual VR and HR relationships for each individual
were determined by fitting a regression line to HR values
and log VR values.  Each subject recorded their  daily
activities, change in location,  and breathing rates in
diaries for 3 consecutive days.  Self-estimated breathing
rates were recorded as slow (slow walking), medium
(walking faster than normal), and fast (running). HR was
recorded during the 3 days once per minute by wearing a
Heart Watch VR values for each self-estimated breathing
rate and activity type  were estimated from the HR
recordings  by employing the  VR  and  HR equation
obtained from the calibration tests.
      The data presented in Table .5-3  represent HR
distribution patterns and corresponding predicted VR for
each age group during hours spent awake. At the same
self-reported  activity  levels   for both  age. groups,
inhalation rates were higher for outdoor activities than for
indoor activities. The total hours spent indoors by high
school students  (21.2  hours) were higher than  for
elementary school students (19.6 hours).  The converse
was true for outdoor activities; 2.7 hours for high school
students, and 4.4 hours for elementary school students
(Table 5-4). Based on the data presented in Tables 5-3
and 5-4, the average activity-specific inhalation rates for
elementary (10-12 years) and high school (13-17 years)
students were calculated in Table 5-5.  For elementary
school students, the average daily inhalation rates (based
on indoor and outdoor locations) are  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 5-5).
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1 Volume I - General Factors
PHUri Chapter 5 - Inhalation

Table 5-3. Distribution of Predicted IR by Location and Activity Levels for Elementary and High School Students
Inhalation Rates (nrVhr)
Age
(yrs)
Student
Location Activity Level
% Recorded
Time2
Percentile Rankings1"
Mean ± SD
10-12

13-17

ELC
(nd=17)

HSC
(nd=19)

Indoors
Outdoors
Indoors
Outdoors
slow
medium
. fast
slow
medium
fast
slow
medium
fast
slow
medium
fast
49.6
23.6
2.4
8.9
11.2
4.3
70.7
10.9
1.4
8.2
7.4
1.4
0.84
0.96
1.02
0.96
1.08
1.14
0.78
0.96
1.26
0.96
1.26
1.44
±
±
+
±
±
±
±
+
±
±
±
+
0.36
0.42
0.60
0.54
0.48
0.60
0.36
0.42
0.66
0.48
0.78
1.08
a Recorded time averaged about 23 hr per elementary school student and 33 hr. per high school
b Geometric means closely approximated 50th percentiles; geometric standard deviations were 1
e EL — elementary school student; HS = high school student.
d N = number of students that participated in survey.
e Highest single value.
1st
0.18
0.24
0.24
0.36
0.24
0.48
0.30
0.42
0.54
0.42
0.48
0.48
50th
0.78
0.84
0.84
0.78
0.96
0.96
0.72
0.84
1.08
0.90
1.08
1.02
99
.9th
2.34
2.58
3.42
4.32
3.36
3.60
3.24
4.02
6.84C
5.28
5.70
5.94
student, over 72-hr, periods.
.2-1.3 forHR, 1.5-1.8'for VR.
Source: Spier et al., 1992.
Table 5-4. Average Hours Spent Per Day in a Given Location and Activity Level for Elementary (EL) and High School (HS) Students
Student
(EL?, nc= 17; HSb, Nc= 19) Location




a
b
c
EL Indoor
EL Outdoor
HS Indoor
HS Outdoor
Elementary school (EL) students were between 10-12 years
High school (HS) students were between 13-17 years old.
N corresponds to number of school students.
Slow
16.3
2.2
19.5
1.2
old.
Activity Level
Medium
2.9
1.7
1.5
1.3

Fast
0.4
0.5
0.2
0.2

Total Time Spent
(hrs/dav)
19.6
4.4
21.2
2.7

Source: Spier et al., 1992.
Page
5-6
 Exposure Factors Handbook
	August 1997

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Volume I - General Factors
Chapter 5 - Inhalation
Students
Age
(yrs) Location
Activity type"
Mean IRb
(m3/day)
Percentile Rankings
1st 50th
99.9th
    Table 5-5. Distribution Patterns of Daily Inhalation Rates for Elementary (EL) and High School (HS) Students Grouped by Activity Level
  EL(nc=17)     10-12      Indoor
     EL
                        Outdoor
  HS (n=19)     13-17      Indoor
 Light
Moderate
 Heavy

 Light
Moderate
 Heavy

 Light
Moderate
 Heavy
13.7
2.8
0.4

2.1
1.84
0.57

15.2
1.4
0.25
2.93
0.70
0.096

0.79
0.41
0.24

5.85
0.63
0.11
12.71
2.44
0.34

1.72
1.63
0.48

14.04
1.26
0.22
38.14
7.48
1.37 .

9.50
5.71
1.80

63.18
6.03
1.37
HS Outdoor

Light
Moderate
Heavy
1.15
1.64
0.29
0.50
0.62
0.096
1.08
1.40
0.20
6.34
7.41
1.19
  a    For this report, activity type presented in Table 5-2 was redefined as light activity for slow, moderate activity for medium, and heavy
      activity for fast.
  b    Daily inhalation rate was calculated by multiplying the hours spent at each activity level (Table 5-4) by the corresponding inhalation rate
      (Table 5-3).                                                             .
  0    Number of elementary (EL) and high school students (HS).

  Source: Adapted from Spier et al., 1992 (Generated using data from Tables 5-3 and 5-4).	
       A limitation of this study is the small sample size.
The results may not be representative of all children in
these age groups. Another limitation is that  the accuracy
of the self-estimated breathing rates reported by younger
age groups is uncertain. This may affect the validity of
the data set generated. An advantage of this study is that
inhalation  rates  were  determined  for children  and
adolescents.  These data are useful in estimating exposure
for the younger population.
       Adams (1993) - Measurement of Breathing Rate
and Volume in Routinely Performed Daily Activities -
Adams  (1993) conducted research to accomplish two
main objectives: (1) identification of mean and ranges of
inhalation rates for  various age/gender  cohorts  and
specific activities; and (2) derivation of simple linear and
multiple regression equations used to predict inhalation
rates through other measured variables:  heart rate (HR),
breathing frequency (fB), and oxygen consumption (VO2).
A total of 160 subjects participated in the primary study.
There were four age dependent groups: (1) children 6 to
12.9 years old, (2) adolescents between 13 and 18.9 years
old, (3) adults  between 19 and 59.9 years old, and (4)
seniors >60 years old (Adams, 1993).  An additional 40
children from 6 to 12 years old and 12 young children
                   from 3 to 5 years old were identified as subjects for pilot
                   testing purposes in this age group (Adams, 1993).
                          Resting protocols conducted in the laboratory for
                   all age groups consisted of three phases (25 minutes each)
                   of lying, sitting, and standing.  They were categorized as
                   resting and sedentary activities.   Two  active protocols,
                   moderate (walking) and heavy (jogging/ running) phases,
                   were performed  on  a treadmill over a  progressive
                   continuum of intensities made up  of 6 minute intervals, at
                   3 speeds, ranging from  slow to moderately fast.  All
                   protocols involved measuring VR,  HR, fB (breathing
                   frequency),    and    VO2   (oxygen    consumption).
                   Measurements were taken in the last 5 minutes of each
                   phase of the resting protocol, and the last 3 minutes of the
                   6 minute intervals at each speed  designated in the active
                   protocols.
                          In the field,  all children  completed spontaneous
                   play protocols, while the older adolescent population (16-
                    18  years)  completed  car  driving  and  riding,  car
                   maintenance (males), and housework (females) protocols.
                   All  adult females (19-60  years)  and most of the senior
                   (60-77 years) females completed housework, yardwork,
                   and car driving and riding protocols.  Adult and senior
                   males completed car  driving and riding, yardwork, and
 Exposure Factors Handbook
 August 1997
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                                                                     5-7

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                                                                                Volume I - General Factors
                                                                                      Chapter 5 - Inhalation
 mowing protocols. HR, VR, and fB were measured during
 each protocol.  Most protocols were conducted  for 30
 minutes. All  the active  field protocols were conducted
 twice.
       During all activities in either the laboratory or field
 protocols,  IR for the  children's group revealed  no
 significant gender differences,  but those for the adult
 groups demonstrated gender differences. Therefore, IR
 data presented in Appendix Tables 5A-1 and 5A-2 were
 categorized as young children, children (no gender),and
 for adult female, and adult male by activity levels (resting,
 sedentary, light, moderate, and heavy).  These categorized
 data from the Appendix tables are summarized as IR in
 m3/hr in Tables 5-6 and 5-7. The laboratory protocols are
 shown in  Table 5-6.   Table  5-7 presents the mean
 inhalation  rates  by  group  and  activity  levels  (light,
 sedentary,   and  moderate)   in  field protocols.    A
 comparison of the data shown in Tables 5-6 and 5-7
 suggest that during  light and  sedentary activities  in
 laboratory  and field  protocols,  similar inhalation rates
 were  obtained  for  adult  females  and  adult  males.
 Accurate predictions  of IR across all population groups
 and activity types were obtained  by including body
 surface area (BSA), HR, and fB in multiple regression
 analysis (Adams, 1993).  Adams (1993) calculated BSA
 from measured height and weight using the equation:
                                   BSA = Height<°-725> x Weight(a425> x 71.84.
                                                         (Eqn. 5-2)
                                       A limitation associated with this study is that the
                                 population does not represent the general U.S. population.
                                 Also, the classification of activity types (i.e., laboratory
                                 and field protocols)  into activity  levels may bias the
                                 inhalation rates obtained for various age/gender cohorts.
                                 The estimated rates were based on short-term data and
                                 may not reflect long-term patterns.  An advantage of this
                                 study is that it provides inhalation data for all age groups.
                                       Linn et al.  (1993) -  Activity patterns in Ozone
                                 Exposed Construction Workers  -   Linn et al.  (1993)
                                 estimated the inhalation rates of 19 construction workers
                                 who  perform heavy outdoor labor before and during a
                                 typical work  shift.  The workers (laborers, iron workers,
                                 and carpenters)  were employed at a site on a hospital
                                 campus in suburban Los  Angeles.  The construction site
                                 included a new hospital building and a separate medical
                                 office complex.  The study was conducted between mid-
                                 July and early November, 1991. During this period, ozone
                                 (O3) levels were typically high. Initially, each subject was
                                 calibrated with a 25-minute exercise test that included
                                 slow walking, fast walking, jogging, lifting, and carrying.
                                 All calibration tests were conducted in the mornings. VR
            Table 5-6. Summary of Average Inhalation Rates (m3/hr) by Age Group and Activity Levels for Laboratory Protocols
      Age Group
Resting
Sedentaryb
Lightc
                                                                                 Moderate
                 Heavy6
  Young Children*

  Children11

  Adult Females'

  Adult Males*
  0.37

  0.45

  0.43

  0.54
  0.40

  0.47

  0.48

  0.60
 0.65

 0.95

 1.33

 1.45
DNPg

 1.74

 2.76

 1.93
DNP

2.23

2.96*

3.63
  f   Resting defined as lying (see Appendix Table 5A-1 for original data).
     Sedentary defined as sitting and standing (see Appendix Table 5A-1 for original data).
  jj   Light defined as walking at speed level 1.5 - 3.0 mph (see Appendix Table 5A-1 for original data).
     Moderate defined as fast walking (3.3 - 4.0 mph) and slow running (3.5 - 4.0 mph) (see Appendix Table 5A-1 for original data).
     Heavy defined as fast running (4.5 - 6.0 mph) (see Appendix Table 5A-1 for original data).
     Young children (both genders) 3 - 5.9 yrs old.
  •   DNP. Group did not perform this protocol or N was too small for appropriate mean comparisons. All young children did not run.
  I1   Children (both genders) 6 - 12.9 yrs old.
     Adult females defined as adolescent, young to middle aged, and older adult females.
  *   Older adults not included in mean value since they did not perform running protocols at particular speeds.
     Adult males defined as adolescent, young to middle aged, and older adult males.
  Source:  Adapted from Adams. 1993.	
Page
5-8
                                                    Exposure Factors Handbook
                                                                       August 1997

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Volume I -General Factors
Chanter 5 - Inhalation
  Table 5-7.  Summary of Average Inhalation Rates (m3/hr) by Age
          Group and Activity Levels in Field Protocols	
     Age Group
Light"
Sedentary
                                            Moderate
  Young Children0

  Childrenf

  Adult Females8

  Adult Males'
DNPe

DNP

1.10h

 1.40
  DNP

  DNP

  0.51

  0.62
0.68

1.07

DNP

1.78j
  a  Light activity was defined as car maintenance (males),
    housework (females), and yard work (females) (see Appendix
    Table 5A-2 for original data).
  b  Sedentary activity was defined as car driving and riding (both
    genders) (see Appendix Table 5A-2 for original data).
  c  Moderate activity was defined as mowing (males); wood
    working (males); yard work (males); and play (children) (see
    Appendix Table 5A-2 for original data).
  d  Young children (both genders) = 3-5.9 yrs old.
  c  DNP. Group did not perform this protocol or N was too small
    for appropriate mean comparisons.
  f  Children (both genders) = 6 -12.9 yrs old.
  8  Adult females defined as adolescent, young to middle aged, and
    older adult females.
  h  Older adults not included in mean value since they did not
    perform this activity.
  '  Adult males defined as adolescent,  young to middle aged, and
    older adult males.
  •>  Adolescents not included in mean value since they did not
    perform this activity.
  Source: Adams, 1993.	
 and HR were measured simultaneously during the test.
 The data were analyzed using least squares regression to
 derive an equation for predicting VR at a given HR.
 Following the calibration tests, each subject recorded the
 type of activities to be performed during their work shift
 (i.e.,  sitting/standing,  walking,  lifting/carrying,  and
 "working  at trade" -  defined as tasks specific  to  the
 individual's job classification).   Location, and self-
 estimated breathing rates ("slow" similar to slow walking,
 "medium" similar to fast walking, and "fast" similar to
 running) were also recorded in the diary. During work, an
 investigator recorded the diary information dictated by the
 subjects.  HR was recorded minute by minute for each
 subject before work and  during  the  entire work shift.
 Thus,  VR  ranges for each breathing rate and activity
 category were  estimated  from the HR recordings by
 employing the relationship between VR and HR obtained
 from the calibration tests.
      A total of 182 hours  of HR  recordings were
obtained during the survey from the 19 volunteers; 144
hours reflected actual working time according to the diary
records. The lowest actual working hours recorded was
6.6 hours and the highest recorded for a complete work
shift  was  11.6  hours (Linn et al., 1993).   Summary
statistics for predicted VR distributions for all subjects,
and for job  or site  defined  subgroups are presented in
Table 5-8.  The data reflect all recordings before and
during  work, and at break times.  For all subjects, the
mean IR was 1.68  m3/hr with a standard deviation of
±0.72 (Table 5-8).  Also,  for most subjects, the 1st and
99th percentiles of HR were outside of the calibration
range (calibration ranges are presented in Appendix Table
5A-3).  Therefore, corresponding  IR percentiles were
extrapolated using the calibration data (Linn et al., 1993).
       The  data presented in  Table  5-9  represent
distribution patterns of IR for each subject, total subjects,
and job  or site defined  subgroups by  self-estimated
breathing  rates (slow, medium, fast) or by type of job
activity. All data include working and non-working hours.
The mean inhalation rates for most individuals showed
statistically  significant  increases   with  higher  self-
estimated  breathing rates or with increasingly strenuous
job activity (Linn et  al.,  1993). Inhalation rates were
higher in hospital site workers when  compared with office
site workers (Table 5-9). In spite of their higher predicted
VR workers at the  hospital site reported  a higher
percentage  of slow breathing time (31  percent) than
workers at  the  office site (20 percent),  and  a lower
percentage of fast breathing time, 3 percent and 5 percent,
respectively (Linn et al.,  1993).  Therefore, individuals
whose work was objectively heavier than average (from
VR predictions) tended to describe their work as lighter
than  average (Linn et al.,  1993). Linn et al. (1993) also
concluded  that during   an   O3   pollution   episode,
construction  workers   should   experience   similar
microenvironmental O3 exposure concentrations as other
healthy outdoor workers, but with approximately twice as
high a VR.  Therefore, the inhaled  dose of O3 should be
almost two times higher  for typical heavy-construction
workers than for typical healthy adults performing less
strenuous outdoor jobs.
        A limitation associated with this study is the small
sample size.  Another limitation  of  this study is that
calibration data were not obtained at extreme conditions.
 Exposure Factors Handbook
 August 1997
                                                                                     Page
                                                                                        5-9

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Volume I - General Factors
    Chapter 5 - Inhalation
Table 5-8. Distributions of Individual and Group Inhalation/Ventilation Rate for Outdoor Workers

Population Group and Subgroup3
All Subjects (nb = 19)
Job
GCWVLaborers (n=5)
Iron Workers (n=3)
Carpenters (n=l 1)
Site
Medical Office Site (n=7)
Hospital Site (n=12)

Mean ± SD
1.68 ±0.72

1.44 ±0.66
1.62 ±0.66
1.86 + 0.78

1.38 + 0.66
1.86 ±0.78
Ventilation Rate (VR) (nrVhr)

1
0.66

0.48
0.60
0.78

0.60 '
0.72
Percentile
50 99
1.62 3.90

1.32 3.66
1.56 3.24
1.74 4.14

1.20 3.72
1.80 3.96
" Each group or subgroup mean was calculated from individual means, not from pooled data.
n = number of individuals performing specific jobs or number of individuals at survey sites.
0 GCW - general construction worker.
Source: Linn et a!., 1993.



Table 5-9. Individual Mean Inhalation Rate (m3/hr) by Self-Estimated Breathing Rate or Job Activity Category for Outdoor Workers
Self-Estimated Job Activity Category (m3/hr)
Breathing Rate (m3/hr)
Population Group and Subgroup Slow Med Fast Sit/Std Walk Carry Tradeb
All Subjects (n=19) 1.44 1.86
Job
GCW'/Laborers (n=5) 1.20 1.56
Iron Workers (n=3) 1.38 1.86
Carpenters (n= 11) 1.62 2.04
Site
Office Site (n=7) 1 . 14 1 .44
Hospital Site (n= 12) 1.62 2.16
° GCW - general construction worker
b Trade - "Working at Trade" (i.e., tasks specific to the individual
Source: Linn etal., 1993
Therefore, it was necessary to predict IR values that were
outside the calibration range. This may introduce an
>
Page
5-10
2.04 1.56 1.80 2.10 1.92
1.68 1.26 1.44 1.74 1.56
2.10 1.62 1.74 1.98 1.92
2.28 1.62 1.92 2.28 2.04
1.62 1.14 1.38 1.68 1.44
2.40 1.80 2.04 2.34 2.16
s job classification)
unknown amount of uncertainty to the data set
Subjective self-estimated breathing rates may be anothei
Exposure Factors Handbook
August 1997

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Volume I - General Factors
Chapter 5 - Inhalation
source of uncertainty in the inhalation rates estimated. An
advantage is that this study provides empirical data useful
in exposure assessments for a subpopulation thought to be
the most  highly exposed common occupational group
(outdoor workers).
      Layton  (1993)   -  Metabolically   Consistent
Breathing Rates for Use in Dose Assessments - Layton
(1993)  presented  a  new  method  for  estimating
metabolically consistent  inhalation  rates  for use  in
quantitative dose assessments of airborne radionuclides.
Generally, the approach for estimating the breathing rate
for a specified time frame was to calculate  a  time-
weighted-average of  ventilation rates associated  with
physical activities of  varying durations (Layton, 1993).
However, in this  study, breathing rates, were calculated
based on oxygen consumption associated  with energy
expenditures for short (hours)  and long  (weeks and
months) periods  of time, using the following general
equation to calculate energy-dependent inhalation rates:
  VE = E x H x VQ
(Eqn. 5-3)
  where:
     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/KJorm3/MJ)];and
     VQ  =   ventilatory equivalent (ratio  of minute  volume
             (L/min) to oxygen uptake (L/min)) unitless.
      Three alternative approaches were used to estimate
daily chronic (long term) inhalation rates for different
age/gender  cohorts of the U.S.  population using  this
methodology.
      First Approach
      Inhalation rates were estimated by  multiplying
average daily food energy intakes for different age/gender
cohorts, volume of oxygen (H), and ventilatory equivalent
(VQ), as shown in the equation above.  The average food
energy   intake  data  (Table  5-10)  -are  based   on
approximately 30,000 individuals and were obtained from
the  USD A  1977-78  Nationwide Food Consumption
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 O2/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 5-11. Table 5-11 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).   Estimated average  lifetime
inhalation rates for males and females are  14 m3/day and
10 m3/day, respectively (Table 5-11). Inhalation rates
were also calculated for active and inactive periods for the
various age/gender cohorts.
      The inhalation rate for inactive  periods  was
estimated by multiplying the basal metabolic rate (BMR)
times the oxygen uptake (H) times the VQ.  BMR was
defined as "the minimum amount of energy required to
support basic cellular respiration while at rest and not
actively digesting food"(Layton, 1993). The inhalation
rate for active periods was calculated by multiplying the
inactive inhalation rate by the ratio of the rate of energy
expenditure during active hours to the estimated BMR.
This ratio is presented as F in Table 5-11.  These data for
active and inactive  inhalation rates are also presented in
Table 5-11.  For children, inactive and active inhalation
rates ranged between 2.35 and 5.95  mVday and 6.35 to
13.09 m3/day, respectively.  For adult males (19-64 years
old), the average inactive and active inhalation rates  were
approximately 10 and 19 m3/day, respectively.  Also, the
average  inactive  and active inhalation rates  for adult
females (19-64 years old) were approximately 8 and 12
mVday, respectively.
      Second Approach
      Inhalation rates were calculated by multiplying the
BMR of the population cohorts times A (ratio of total
daily energy expenditure to daily BMR) times H times
VQ.   The  BMR data obtained from literature  were
statistically analyzed and regression equations  were
developed to predict BMR from body weights of various
age/gender cohorts (Layton, 1993).  The statistical data
used to develop the regression equations are presented in
Appendix Table 5A-4. The data obtained from the second
Exposure Factors Handbook
August 1997     	
                                                            Page
                                                            5-11

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                                                         Volume I - General Factors

                                                             Chapter 5 - Inhalation
Table 5-10. Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-Energy Intakes for
Individuals Sampled in the 1977-78 NFCS
Cohort/Age Body Weight
(years)
Children
Under 1
Ito2
3to5
6 to 8
Males
9toll
12 to 14
IS to 18
19 to 22
23 to 34
35to50
51 to 64
65 to 74
75 +
Females
9toll
12 to 14
15 to 18
19 to 22
23 to 34
35 to 50
51 to 64
65 to 74
75 +
kg

7.6
13
18
26

36
50
66
74
79
82
80
76
71

36
49
56
59
62
66
67
66
62
BMRa
MJ d'lb

1.74
3.08
3.69
4.41

5.42
6.45
7.64
7.56
7.87
7.59
7.49
6.18
5.94

4.91
5.64
6.03
5.69
5.88
5.78
5.82
5.26
5.11
kcal d'lc

416
734
881
1053

1293
1540
1823
1804
1879
1811
1788
1476
1417

1173
1347
1440
1359
1403
1380
1388
1256
1220
Energy Intake (EFD)
MJd'1

3.32
5.07
6.14
7.43

8.55
9.54
10.8
10.0
10.1
9.51
9.04
8.02
7.82

7.75
7.72
7.32
6.71
6.72
6.34
6.40
5.99
5.94
kcal d"1

793
1209
1466
1774

2040
2276
2568
2395
2418
2270
2158
1913
1866

1849
1842
1748
1601
1603
1514
1528
1430
1417
Ratio
EFD/BMR

1.90
1.65
1.66
1.68

1.58
1.48
1.41
1.33
1.29
1.25
1.21
1.30
1.32

1.58
1.37
1.21
1.18
1.14
1.10
1.10
1.14
1.16
* Calculated from the appropriate age and gender-based BMR equations given in Appendix Table 5A-4.
MJd'1 -mega joules/day
c kcal d"' - kilo calories/day
Source: Layton, 1993.
Page
5-12
 Exposure Factors Handbook
	        August 1997

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Volume I -  General Factors
Chanter 5 - Inhalation
                                      Table 5-11. Daily Inhalation Rates Calculated from Food-Energy Intakes
                                     Daily Inhalation
                                         Rate*
                                                          Sleep
                                                     MET" Value
                                                                     Inhalation Rates
                                                                Inactive0	Active"
  Cohort/Age (years)
                                        (nvVdav)
       Children
         <1
         I -2
         3-5
         6-8

        Males
        9-11
        12-14
        15-18
        19-22
        23-34
        35-50
        51-64
        65-74
         75+
   Lifetime average &

       Females
3
3
4
4
11
16
14
10
1
               4.5
               6.8
               8.3
                10
14
15
17
16
16
15
15
13
12
14
                 11
                 11
                 10
                 10
1.9
1.6
1.7
1.7
1.9
1.8
1.7
1.6
1.5
1.5
1.4
1.6
1.6
2.7
2.2
2.2
2.2
2.5
2.2
2.1
1.9
1.8
1.8
1.7
1.8
1.9
2.35     •        6.35
4.16             9.15
4.98             10.96
5.95             13.09
7.32
8.71
10.31
10.21
10.62
10.25
10.11
8.34
8.02
 18.3
19.16
21.65
 19.4
19.12
18.45
17.19
15.01
15.24
9-11
12-14
15-18
19-22
23-34
35-50
51 -64
65-74
75+

3
3
4
4
11
16
14
10
1

13
12
12
11
11
10
10
• 9.7
M
	 10 	
9 1.9
9 1.6
8 1.5
8 1.4
8 1.4
8 1.3
8 1.3
8 1.4
8 1.4

2.5
2.0
1.7
1.6
1.6
1.5
1.5
1.5
1.6

6.63
7.61
8.14
7.68
7.94
7.80
7.86
7.10
6.90

16.58
15.20
13.84
12.29
12.7
11.7
11.8
10.65
11.04

  a    Daily inhalation rate was calculated by multiplying the EFD values (see Table 5-10) by H x VQ x (m3 1,000 L'1) for subjects under 9 years of age and by
       1.2xHxVQ 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 LO2/KJ or 0.21 LO2/Kcal
       VQ   = Ventilation equivalent = 27 = geometric mean of VQs (unitless)

  b    MET  = Metabolic equivalent

  c    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 5-10.
       Where:
       BMR  = Basal metabolic rate (MJ/day) or (kg/hr)

  d    L is the number of years for each age cohort.

  c    For individuals 9 years of age and older, A was calculated by multiplying the ratio for EFD/BMR (unitless) (Table 5-10) by the factor 1.2 (see text for
       explanation).                                                                                                     .  •

  f    F     = (24A - S)/(24 - S) (unitless), ratio of the rate of energy expenditure during active hours to the estimated BMR (unitless)
       Where:
       S     = Number of hours spent sleeping each day (hrs)

  g    Lifetime average was calculated by multiplying individual  inhalation rate by corresponding L values summing the products across cohorts and dividing the
       result by 75, the total of the cohort age spans.

  Source:  Lavton. 1993.	;	,——	
 Exposure Factors Handbook
 August 1997
                                                                                                      Page
                                                                                                       5-13

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                                                                               Volume I - General Factors
                                                                                    Chapter 5 - Inhalation
 approach are presented in Table 5-12.  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
 (10-18 years) was 15 m3/day for males and 12 nvVday for
 females.  Adult females (18 years and older) ranged from
 9.9-11 nvVday and  adult  males (18 years  and older)
 ranged from 13-17 m3/day.  These rates are similar to the
 daily inhalation rates obtained using the first approach.
 Also, the inactive inhalation rates obtained from the first
 approach  are  lower than the inhalation rates obtained
 using the second approach.  This may be attributed to the
 BMR multiplier employed in the equation of the second
 approach to calculate inhalation rates.
       Third Approach
       Inhalation  rates were calculated  by multiplying
 estimated energy expenditures associated with different
 levels of physical activity engaged in over the course of an
 average day by VQ and H for each age/gender cohort.
 The energy expenditure associated with each level of
 activity was estimated by multiplying BMRs of  each
 activity level by the metabolic equivalent (MET) and by
 the  time spent per day performing each activity for each
 age/gender population. The time-activity data used in this
 approach were obtained from a survey conducted by Sallis
 et al. (1985) (Layton, 1993). In that survey, the physical-
 activity categories and associated MET values used were
                                  sleep,   MET=1;  light-activity,  MET=1.5;  moderate
                                  activity, MET=4; hard activity, MET=6; and very hard
                                  activity, MET=10. The physical activities were based on
                                  recall by the test subject (Layton, 1993).  The survey
                                  sample was 2,126 individuals (1,120 women and 1,006
                                  men) ages 20-74 years that were randomly selected from
                                  four communities in California.    The  BMRs were
                                  estimated using the metabolic equations presented in
                                  Appendix Table 5A-4. The body weights were obtained
                                  from a study conducted by Najjar and Rowland (1987)
                                  which  randomly  sampled  individuals  from the  U.S.
                                  population (Layton,  1993).  Ta6le  5-13 presents the
                                  inhalation rates (VE) in m3/day and m3/hr for adult males
                                  and  females aged 20-74 years at five physical  activity
                                  levels.  The total daily inhalation rates ranged from 13-17
                                  m3/day  for adult males  and  11-15  mVday for adult
                                  females.
                                        The rates for  adult  females were higher when
                                  compared with the other two approaches. Layton (1993)
                                  reported that the  estimated inhalation rates obtained from
                                  the third approach were particularly sensitive to the MET
                                  value that represented the energy expenditures for light
                                  activities. Layton (1993) stated further that in the  original
                                  time-activity survey (i.e., conducted by Sallis et al., 1985),
                                  time spent performing light activities was not presented.
                                  Therefore, the time spent at light activities was estimated
  Male
  0.5-<3
  3-<10
  10-<18
  I8-<30
  30-<60
  60+
  Female
                                 Table 5-12. Daily Inhalation Rates Obtained from the Ratios
Gender/Age
(yrs)
Body Weight8
(kg)
BMRb
(MJ/day)
VQ
Ac
H
(m3O,/MJ)
Inhalation Rate, VE
(m3/day)d
14
23
53
76
80
75
3.4
4.3
6.7
7.7
7.5
6.1
27
27
27
27
27
27
1.6
1.6
1.7
1.59
1.59
1.59
0.05
0.05
0.05
0.05
0.05
0.05
7.3
9.3
15
17
16
13
0.5 - <3
3-<10
10-<18
I8-<30
30-<60
60+
11
23
50
62
68
67
2.6
4.0
5.7
5.9
5.8
5.3
27
27
27
27
27
27
1.6
1.6
1.5
1.38
1.38
1.38
0.05
0.05
0.05
0.05
0.05
0.05
5.6
8.6
12
11
11
9.9
   Body weight was based on the average weights for age/gender cohorts in the U.S. population.
  b The BMRs (basal metabolic rate) are calculated using the respective body weights and BMR equations (see Appendix Table 5A-4).
  c The values of the BMR multiplier (EFD/BMR) for those 18 years and older were derived from the Basiotis et al. (1989) study: Male = 1.59,
   Female= 1.38. For males and females under 10 years old, the mean BMR multiplier used was 1.6. For males and females aged 10to< 18
   years, the mean values for A given in Table 5-11 for 12-14 years and 15-18 years, age brackets for males and females were used:  male = 1.7
   and female= 1.5.
   Inhalation rate = BMR x A x H x VQ; VQ = ventilation equivalent and H = oxygen uptake.
  Source: Lavton.  1993.	
Page
5-14
                                                    Exposure Factors Handbook
                                                                       August 1997

-------
Volume I - General Factors
Chapter 5 - Inhalation














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 Exposure Factors Handbook
 August 1997
Page
5-15

-------
                                                                            Volume I - General Factors
                                                                                 Chapter 5 - Inhalation
 by subtracting the total time spent at sleep, moderate,
 heavy, and very heavy activities from 24 hours (Layton,
 1993). The range of inhalation rates for adult females
 were 9.6 to  11 m3/day, 9.9 to 11 m3/day, and 11 to 15
 m3/day,  for  the  first, second, and  third  approach,
 respectively. The inhalation rates for adult males ranged
 from 13 to 16 m3/day for the first approach, and 13 to 17
 nrVday for the second and third approaches.
       Inhalation rates were also obtained for short-term
 exposures for various age/gender cohorts and five energy-
 expenditure categories (rest, sedentary, light, moderate,
 and heavy).   BMRs were multiplied by the product of
 MET, H,  and VQ.  The  data  obtained for short term
 exposures are presented in Table 5-14.
       The major strengths of the Layton (1993) study are
 that  it obtains similar  results using three  different
 approaches to estimate inhalation rates in different  age
 groups and that the populations are large, consisting of
 men, women, and children. Explanations for differences
 in results due to metabolic measurements, reported diet,
 or activity patterns are supported by observations reported
 by other investigators in other studies.  Major limitations
 of this study are that activity pattern levels estimated in
this study are somewhat subjective, the explanation that
activity pattern differences is responsible for the lower
level obtained with the metabolic approach (25 percent)
compared to the activity pattern  approach is  not well
supported by the data, and different populations were used
in each approach which may introduce error.

5.2.3.     Relevant Inhalation Rate Studies
  International Commission on Radiological Protection
(ICRP) (1981) -  Report of the Task Group on Reference
Man -  The International Commission of Radiological
Protection (ICRP) estimated  daily inhalation rates for
reference adult males, adult females,  children (10 years
old), infant (1  year old), and newborn babies by using a
time-activity-ventilation approach.  This approach for
estimating inhalation rate over a specified period of time
was based on calculating a time  weighted average of
inhalation rates associated with physical  activities of
varying durations.  ICRP  (1981) compiled reference
values   (Appendix   Table   5A-5)   of  minute
volume/inhalation rates from various literature  sources.
ICRP  (1981)  assumed that  the  daily  activities of  a
reference man and woman, and child (10 yrs) consisted of
Table 5-14. Inhalation Rates for Short-Term Exposures
Gender/Age (yrs)
Weight
(kg)"
BMRb
(MJ/day)
Activity Type
Rest Sedentary Light Moderate
MET (BMR Multiplier)
1 1.2 2C 4d
Heavy
10C
Inhalation Rate (m'/hr/'8
Mate
0,5 -<3
3-<10
!0-<18
18-<30
30-<60
60+
Female
0.5 -<3
3-<10
10-<18
18-<30
30-<60
60+
14
23
53
76
80
75
11
23
50
62
68
67
3.40
4.30
6.70
7.70
7.50
6.10
2.60
4.00
5.70
5.90
5.80
5.30
0.19
0.24
0.38
0.43
0.42
0.34
0.14
0.23
0.32
0.33
0.32
0.30
0.23
0.29
0.45
0.52
0.50
0.41
0.17
0.27
0.38
0.40
0.39
0.36
0.38
0.49
0.78
0.84
0.84
0.66
0.29
0.45
0.66
0.66
0.66
0.59
0.78
0.96
1.50
1.74
1.68
1.38
0.60
0.90
1.26
1.32
1.32
1.20
1.92
2.40
3.78
4.32
4.20
3.42
1.44
2.28
3.18
3.30
3.24
3.00
f Body weights were based on average weights for age/gender cohorts of the U.S. population
The BMRs for the age/gender cohorts were calculated using the respective body weights and the BMR equations (Appendix Table 5A-4).
" Rangcofl .5 -2.5.
" Range of 3 -5.
" Range of >5 - 20.
The inhalation rate was calculated by multiplying BMR (MJ/day) x H (0.05 L/KJ) x MET x VQ (27) x (d/1 ,440 min)
* Original data were presented in L/min. Conversion to m3/hr was obtained as follows:
60 min m3 L
Source: Lavton. 1993.
hr ' 1000L
mm


Page
5-16
                  Exposure Factors Handbook
                                    August 1997

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Volume I - General Factors
Chapter 5 - Inhalation
8 hours of rest and 16 hours of light activities. It was also
assumed  that 16  hours were  divided evenly between
occupational  and nonoccupational  activities.   It was
assumed that a day consisted of 14 hours resting and 10
hours light activity for an infant (1 yr).  A newborn's daily
activities consisted of 23 hours resting and 1 hour light
activity.  Table 5-15 presents  the daily inhalation rates
obtained  for all ages/genders.  The estimated inhalation
rates were 22.8 m3/day for adult males, 21.1 m3/day for
adult females, 14.8 m3/day for children (age 10 years),
3.76 mVday for infants (age 1 year), and 0.78 m3/day for
newborns.
    Table 5-15. Daily Inhalation Rates Estimated From Daily Activities"
                    Inhalation Rate (IR)
  Subject            Resting       Light      Daily Inhalation
                   (m3/hr)
          Activity
          (m3/hr)
          Rate (DIR)1
            (nrVday)
  Adult Man
  Adult Woman
  Child (10 yrs)
  Infant(1 yr)
  Newborn
0.45
0.36
0.29
0.09
0.03
 1.2
1.14
0.78
0.25
0.09
22.8
21.1
14.8
3.76
0.78
  a Assumptions made were based on 8 hours resting and 16 hours light
    activity for adults and children (10 yrs); 14 hours resting and 10 hours
    light activity for infants (1 yr); 23 hours resting and 1 hour light activity
    for newborns.
  b
     DIR = 1 £ IRA
          T 1,1
   IR,  = Corresponding inhalation rate at im activity
   t!   = Hours spent during the i"1 activity
   k   = Number of activity periods
   T   = Total time of the exposure period (i.e., a day)

   Source:  ICRP, 1981	__^_
        A limitation associated with this study is that the
 validity and accuracy of the inhalation rates data used in
 the compilation were not specified.  This may introduce
 some degree of uncertainty in the results obtained. Also,
 the approach used  involved assuming hours spent by
 various age/gender cohorts in specific activities.  These
 assumptions may over/under-estimate the inhalation rates
 obtained.
        U.S. EPA (1985) - Development of Statistical
 Distributions or Ranges of Standard Factors Used in
 Exposure Assessments - Due to a paucity of information
 in  the literature regarding  equations used to develop
 statistical distributions of minute ventilation/ventilation
 rate at all activity levels for male and female children and
 adults, the U.S. EPA (1985) compiled measured values of
 minute ventilation for various age/gender cohorts from
early studies.   In more recent investigations,  minute
ventilations have been measured more as background
information  than as research objective itself and the
available studies have been for specific subpopulations
such as obese, asthmatics, or marathon runners. The data
compiled by the U.S. EPA (1985)  for each age/gender
cohorts were obtained at various activity levels.  These
.levels were  categorized as light,  moderate,  or heavy
according to the criteria developed by the EPA Office of
Environmental  Criteria and Assessment for the  Ozone
Criteria Document. These criteria were developed for a
reference male adult with a body weight of 70 kg (U.S.
EPA, 1985). The minute ventilation rates for adult males
based on these activity level  categories are detailed in
Appendix Table 5A-6.
       Table 5-16 presents a summary of inhalation rates
 by  age,  gender, and activity level  (detailed data are
 presented in Appendix Table 5A-7).  A  description of
 activities included in each activity level is also presented
 in Table 5-16.   Table 5-16  indicates that at rest, the
 average  adult inhalation  rate is 0.5  m3/hr.   The mean
 inhalation rate for children at rest, ages 6 and 10 years, is
 0.4 m3/hr.   Table 5-17  presents  activity  pattern data
 aggregated for three microenvironments by activity level
 for all age groups. The total average hours spent indoors
 was 20.4, outdoors was 1.77, and in transportation vehicle
 was 1.77. Based on the data presented in Tables 5-16 and
 5-17, a daily inhalation rate was calculated for adults and
 children by using a time-activity-ventilation approach.
 These data are presented in Table  5-18. The calculated
 average daily inhalation rate is 16 m3/day for adults. The
 average daily inhalation rate for children (6 and 10 yrs) is
 18.9 nvVday ([16.74 + 21.02]/2).
        A limitation associated with this study is that many
 of the values used in the data compilation were from early
 studies. The accuracy and/or validity of the values used
 and data collection method were not presented in U.S.
 EPA (1985).  This introduces uncertainty  in the results
 obtained. An advantage of this study is that the data are
 actual measurement data for  a large number of subjects
 and the data are presented for both adults and children.
        Shamoo et al. (1990) - Improved Quantitation of
 Air Pollution Dose Rates by  Improved Estimation of
  Ventilation Rate-  Shamoo et al. (1990) conducted  this
  study  to develop and validate new  methods to accurately
  estimate ventilation rates for typical individuals during
  their normal activities.  Two practical approaches were
  tested for  estimating ventilation rates indirectly:  (1)
  volunteers  were trained  to  estimate their own VR at
  Exposure Factors Handbook
  August 1997
                                                                                      Page
                                                                                       5-17

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                                                                                                    Volume I - General Factors
                                                                                                           Chapter 5 - Inhalation

Adult male
Adult female
Average adult'
Child, age 6 years
Child, age 10 years
n"
454
595

8
10
Resting0
0.7
0.3
0.5
0.4
0.4
n
102
786

16
40
Light"
0.8
0.5
0.6
0.8
1.0

102
106

4
29

2.5
1.6
2.1
2.0


267
211

5
43
Heavy'
4.8
2.9
3.9
2.3
3.9
         Values of inhalation rates for males, females, and children (male and female) presented in this table represent the mean of values reported for each
         activity level in 1985. (See Appendix Table 5A-7 for a detailed listing of the data from U.S. EPA, 1985.)
         n = number of observations at each activity level.
         Includes watching television, reading, and sleeping.
         Includes most domestic work, attending to personal needs and care, hobbies, and conducting minor indoor repairs and home improvements
         Includes heavy indoor cleanup, performance of major indoor repairs and alterations, and climbing stairs.
         Includes vigorous physical exercise and climbing stairs carrying a load.
         Derived by taking the mean of the adult male and adult female values for each activity level.

    Source: Adapted from U.S. EPA. 1985.	
Table 5-17. Activity Pattern Data Aggregated for Three
Microenvironments by Activity Level for all Age Groups
Microenvironment

Indoors




Outdoors




In Transportation
Vehicle



Source: Adapted from
Average Hours Per Day in
Activity Each Microenvironment at
Level
Resting
Light
Moderate
Heavy
TOTAL
Resting
Light
Moderate
Heavy
TOTAL
Resting
Light
Moderate
Heavy
TOTAL
U.S. EPA. 1985.
Each Activity Level
9.82
9.82
0.71
0.098
20.4
0.505
0.505
0.65
0.12
1.77
0.86
0.86
0.05
0.0012
1.77

                                                                                 Table 5-18. Summary of Daily Inhalation Rates Grouped by
                                                                                                 Age and Activity level	
                                                                                             Daily Inhalation Rate (m3/day)a
                                                                           Subject
                                                                                                                                   Total
                                                                                                                                 Daily IRb
   Light    Moderate    Heavy    (nvVday)
Adult Male     7.83      8.95       3.53

Adult          3.35      5.59       2.26
Female

Adult          5.60      6.71       2.96
Average0'

Child          4.47      8.95       2.82
(age 6)

Child          4.47      11.19       4.51
(age 10)	
                                                                                                                        1.05

                                                                                                                        0.64
                                   21.4

                                   11.8
                                                                                                                        0.85         16


                                                                                                                        0.50       16.74


                                                                                                                        0.85       21.02
                                                                              Daily inhalation rate was calculated using the following equation:
                                                                              !R!    =     inhalation rate at i"1 activity (Table 5-18)
                                                                              I,     =     hours spent per day during i™ activity (Table 5-19)
                                                                              k     =     number of activity periods
                                                                              T     =     total time of the exposure period (e.g., a day)

                                                                              Total daily inhalation rate was calculated by summing the specific
                                                                              activity (resting, light, moderate, heavy) daily inhalation rate.
                                                                          Source:
                                                                                    Generated using the data from U.S. EPA (1985) as shown in
                                                                                    Tables 5-16 and 5-17.   _
Page
5-18
Exposure Factors Handbook
                        August 1997

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Volume I - General Factors
Chapter 5 - Inhalation
various controlled levels of exercise; and (2) individual
VR and HR relationships were determined in another set
of  volunteers  during  supervised  exercise  sessions
(Shamoo et al., 1990).  In the first approach, the training
session involved  9 volunteers (3 females and  6  males)
from 21 to 37 years old.  Initially the subjects were trained
on  a treadmill with  regularly increasing  speeds. VR
measurements were recorded during the last minute of the
3-minute interval at each speed.  VR was reported to the
subjects as low  (1.4 m3/hr), medium (1.5-2.3  m3/hr),
heavy (2.4-3.8 m3/hr), and  very  heavy (3.8  m3/hr  or
higher) (Shamoo  et al., 1990).
       Following the initial test, treadmill training sessions
were conducted on a different day in which 7 different
speeds were presented, each for 3 minutes in arbitrary
order.  VR was measured and the subjects were given
feedback with the  four ventilation ranges  provided
previously. After resting, a treadmill testing session was
conducted in which  seven  speeds  were presented  in
different arbitrary order from the training session. VR
was measured and each subject estimated their own
ventilation level at each speed. The correct level was then
revealed  to  each subject after  his/her own  estimate.
Subsequently, two 3-hour outdoor supervised exercise
sessions  were  conducted  in  the  summer  on two
consecutive days. Each hour consisted of 15  minutes each
of rest, slow walking, jogging,  and fast walking.  The
subjects'  ventilation  level  and  VR were recorded;
however,  no  feedback  was  given to the  subjects.
Electrocardiograms were recorded via direct connection
or telemetry and HR was measured concurrently with
ventilation measurement for all treadmill sessions.
       The second approach consisted of two protocol
phases  (indoor/outdoor  exercise  sessions  and  field
testing).  Twenty outdoor adult workers between 19-50
years old were recruited. Indoor and outdoor supervised
exercises similar to the protocols in the first approach
were conducted; however, there were no feedbacks.  Also,
in this approach, electrocardiograms were recorded and
HR was measured concurrently with VR. During the field
testing phase, subjects were trained  to  record  their
activities during three different 24-hour periods during
one week.   These periods  included their most active
working and non-working days. HR was measured quasi-
continuously during the 24-hour periods that activities
were  recorded.   The subjects recorded in a diary all
changes in physical activity, location, and exercise levels
 during  waking  hours.   Self-estimated  activities   in
 supervised exercises and field studies were categorized as
slow (resting, slow walking or equivalent), medium (fast
walking or equivalent), and fast (jogging or equivalent).
      Inhalation rates were not presented in this study. In
the first approach, about 68 percent of all self-estimates
were correct for the 9 subjects sampled (Shamoo et al.,
1990). Inaccurate self-estimates occurred in the younger
male population who were highly physically fit and were
competitive aerobic trainers.   This subset of sample
population tended to underestimate their own physical
activity levels at higher VR ranges. Shamoo et al. (1990)
attributed this  to a "macho  effect."   In  the second
approach, a regression analysis was conducted that related
the logarithm of VR  to  HR.   The  logarithm of VR
correlated better with HR  than VR itself (Shamoo et al.,
1990).
      A limitation associated with this study is that the
population sampled is  not representative of the general
U.S.  population.   Also,  ventilation rates  were not
presented. Training individuals to estimate their VR may
contribute to uncertainty in  the  results because the
estimates are subjective.   Another  limitation is that
calibration data were not obtained at extreme conditions;
therefore, the  VR/HR relationship obtained may be
biased. An additional limitation is that training subjects
may be too labor-intensive for widespread use in exposure
assessment studies. An advantage of this study is that HR
recordings are useful in predicting ventilation rates which
in turn are useful  in estimating exposure.
       Shamoo etal. (1991) - Activity Patterns in a Panel
of Outdoor Workers Exposed to  Oxidant  Pollution -
Shamoo  et  al.  (1991)  investigated  summer activity
patterns in  20 adult volunteers with potentially high
exposure to ambient oxidant pollution.  The  selected
volunteer subjects were 15 men and 5 women ages 19-50
years from the Los Angeles area. All volunteers worked
outdoors at least 10 hours per week.  The experimental
approach involved  two  stages: (1)  indirect objective
estimation of VR from HR measurements; and (2) self
estimation  of inhalation/ventilation rates recorded by
subjects in diaries during their normal activities.
       The   approach   consisted   of calibrating  the
relationship between VR and HR for each test subject in
controlled exercise; monitoring by subjects of their own
normal activities with diaries and electronic HR recorders;
and then relating VR with the activities described in the
diaries (Shamoo et al.,  1991).  Calibration tests were
conducted for indoor and outdoor supervised exercises to
determine individual relationships between VR and HR.
Indoors, each subject was tested on a treadmill at rest and
sExposure Factors Handbook
 August 1997
                                               Page
                                               5-19

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                                                                           Volume I - General Factors
                                                                                 Chapter 5 - Inhalation
 at increasing speeds. HR and VR were measured at the
 third minute at each 3-minute interval speed. In addition,
 subjects were tested while walking a 90-meter course in a
 corridor at 3  self-selected speeds (normal, slower than
 normal, and faster than normal) for 3 minutes.
       Two outdoor testing sessions (one hour each) were
 conducted for each subject,  7 days  apart.   Subjects
 exercised  on  a 260-meter asphalt  course.  A session
 involved 15 minutes each of rest, slow walking, jogging,
 and fast walking during the first hour. The sequence was
 also repeated during the second hour.   HR and VR
 measurements were recorded starting at the 8th minute of
 each 15-minute segment.  Following the calibration tests,
 a field study was conducted in which  subject's self-
 monitored their activities by  filling out activity diary
 booklets, self-estimated their breathing rates,  and their
 HR. Breathing rates  were defined as sleep, slow (slow or
 normal  walking);  medium (fast walking);  and fast
 (running) (Shamoo et al., 1991).  Changes in location,
 activity, or breathing rates during three 24-hr periods
 within a week were recorded.  These periods included
 their most active working and non-working days. Each
subject wore Heart Watches which recorded their HR
once per minute during the field study. Ventilation rates
were estimated for the following categories: sleep, slow,
medium, and fast.
      Calibration data were fit to the equation log (VR)
= intercept + (slope x HR), each individual's intercept and
slope were determined separately to  provide a specific
equation that predicts each subject's VR from measured
HR (Shamoo et al., 1991). The average measured VRs
were 0.48,0.9,1.68, and 4.02 m3/hr for rest, slow walking
or normal walking, fast walking and jogging, respectively
(Shamoo et al., 1991).  Collectively, the diary recordings
showed that sleep  occupied about 33 percent of the
subject's time; slow activity 59 percent; medium activity
7 percent; and fast activity 1 percent.  The  diary data
covered an average of 69 hours per subject (Shamoo et
al., 1991).  Table 5-19 presents the distribution pattern of
predicted ventilation rates and equivalent ventilation rates
(EVR) obtained at  the four activity  levels.  EVR was
defined as the VR per square meter of body surface area,
and also as a percentage of the subjects average VR over
the entire field monitoring period (Shamoo et al., 1991).
Table 5-19. Distribution Pattern of Predicted VR and EVR (equivalent ventilation rate) for 20 Outdoor Workers
VR (m3/hr)a
Self-Reported Arithmetic Geometric
Activity Level Nc Mean ± SD Mean ± SD
Sleep
Slow
Medium
Fast
18,597 0.42 ±0.16
41,745 0.71+0.4
3,898 0.84 ±0.47
572 2.63 ±2. 16
0.39 ± 0.08
0.65 ±0.09
0.76 ±0.09
1.87-1-0.14
EVRb (m3/hr/m2 body surface)
Arithmetic Geometric
Mean ± SD Mean + SD
0.23 ±0.08
0.38 ±0.20
0.48 ±0.24
1.42 + 1.20
0.22 ± 0.08
0.35 ± 0.09
0.44 ±0.09
1.00 + 0.14
Percentile Rankings, VR
Sleep
Slow
Medium
Fast
1 5
0.18 0.18
0.30 0.36
0.36 0.42
0.42 0.54
10
0.24
0.36
0.48
0.60
50
0.36
0.66
0.72
1.74
90
0.66
1.08
1.32
5.70
95
0.72
1.32
1.68
684
99
0.90
1.98
2.64
9 18
99.9
1.20
4.38
3.84
1026
Percentile Rankings, EVR
Sleep
Slow
Medium
Fast
1 5
0.12 0.12
0.18 0.18
0.18 0.24
0.24 0.30
10
0.12
0.24
0.30
0.36
50
0.24
0.36
0.42
0.90
90
0.36
0.54
0.72
3.24
95
0.36
0.66
0.90
3.72
99
0.48
1.08
1.38
4.86
99.9
0.60
2.40
2.28
5.52
" Data presented by Shamoo et al. (1991) in liters/minute were converted to m3/hr.
b EVR = VR per square meter of body surface area.
0 Number of minutes with valid .appearing heart rate records and corresponding daily records of breathing rate.
Source: Shamoo et al., 1991
Page
5-20
                  Exposure Factors Handbook
                                    August 1997

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 Volume I - General Factors
 Chapter 5 - Inhalation
 The overall mean predicted VR was 0.42 m3/hr for sleep;
 0.71 mVhr  for  slow activity; 0.84  m3/hr for medium
 activity; and 2.63 m3/hr for fast activity.
     The mean predicted VR and standard deviation, and
 the percentage of time spent in each combination of VR,
 activity type (essential  and non-essential), and location
 (indoor and outdoor)  are presented in  Table 5-20.
 Essential   activities   include   income-related  work,
 household chores,  child  care, study and  other school
 activities, personal care and destination-oriented travel.
 Non-essential activities  include sports and active leisure,
 passive leisure, some travel, and social or civic activities
 (Shamoo et al., 1991). Table 5-20 shows that inhalation
 rates were higher outdoors than indoors at slow, medium,
 and fast activity levels. Also, inhalation rates were higher
 for outdoor non-essential activities than for indoor non-
 essential activity levels at slow, medium, and fast self-
 reported breathing rates (Table 5-20).
     An advantage of this  study is that subjective activity
 diary data can provide exposure modelers with useful
 rough  estimates of VR for groups of generally healthy
 people.  A limitation of this study  is that  the results
 obtained show high within-person and between-person
 variability in VR at each diary-recorded level, indicating
 that VR estimates from diary reports could potentially be
                         substantially  misleading in individual  cases.  Another
                         limitation of this study is that elevated HR data of slow
                         activity at the second hour of the exercise session reflect
                         persistent  effects  of  exercise  and/or  heat  stress.
                         Therefore, predictions  of  VR  from  the  VR/HR
                         relationship may be biased.
                             Shamoo et al. (1992)  -  Effectiveness of Training
                         Subjects to Estimate Their Level of Ventilation - Shamoo
                         et al. (1992) conducted a study where nine non-sedentary
                         subjects in good health were trained on a treadmill to
                         estimate their own ventilation rates at four activity levels:
                         low, medium, heavy, and very heavy. The purpose of the
                         study  was  to  train the  subjects self-estimation  of
                         ventilation in the field and assess the effectiveness of the
                         training (Shamoo et al., 1992).  The subjects included 3
                         females and 6 males between 21 to 37 years of age. The
                         tests were conducted in four stages.  First, an  initial
                         treadmill pretest was conducted indoors at various speeds
                         until the four ventilation  levels were experienced by each
                         subject; VR was measured and feedback was given to the
                         subjects.  Second, two treadmill training sessions which
                         involved seven 3-minute segments of  varying  speeds
                         based on initial tests were conducted; VR was measured
                         and feedback was given to the subjects. Another similar
                         session was conducted; however, the subjects estimated
                Table 5-20. Distribution Pattern of Inhalation Rate by Location and Activity Type for 20 Outdoor Workers
  Location
   Indoor
   Outdoor
                Activity Type
Self-reported
Activity Level
                                                     % of Time
                                                                    Inhalation rate (m3/hr)b
                                                                          ±SD
                Non-essential
             .  Essential
Slow .
Medium
Fast

Slow
Medium
Fast
20.4
 0.9
 0.2

11.3
 1.8
 0
0.66 ± 0.36
0.78 ± 0.30
1.86 ±0.96

0.78 ± 0.36
0.84 ±0.54
    0
                                           %of Avg.c
Indoor Essential



Sleep
Slow
Medium
Fast
28.7
29.5
2.4
0
0.42 ±0.12
0.72 ± 0.36
0.72 ± 0.30
0
69 ±15
106 ±43
129 ±38
0
 98 ±36
 120 ±50
278 ±124

 117 ±42
 130 ± 56
   0
Outdoor


Non-essential


Slow
Medium
Fast
3.2
0.8
0.7
0.90 ± 0.66
1.26 ±0.60
2.82 ± 2.28
136 ± 90
213 ±91
362 ± 275
   a  Essential activities include income-related, work, household chores, child care, study and other school activities, personal care, and
     destination-oriented travel; Non-essential activities include sports and active leisure, passive leisure, some travel, and social or civic
     activities.
     Data presented by Shamoo et al. (1991) in liters/mintue were converted to m3/hr.
   0  Statistic was calculated by converting each VR for a given subject to a percentage of her/his overall average.
   Source: Adapted from Shamoo et al.. (1991).	
^Exposure Factors Handbook
 August 1997   	
                                                                        Page
                                                                         5-21

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                                                                            Volume I - General Factors
                                                                                 Chapter 5 - Inhalation
their own ventilation level during the last 20 seconds of
each segment and VR was  measured  during  the  last
minute of each segment.  Immediate feedback was given
to the subject's estimate; and the third and fourth stages
involved 2 outdoor sessions of 3 hours each. Each hour
comprised 15 minutes each of rest, slow walking, jogging,
and fast  walking.  The subjects estimated their own
ventilation level at the middle of each segment.  The
subject's estimate was  verified by a respirometer which
measured VR in the middle of each  15-minute activity.
No  feedback was given to the  subject.   The overall
percent correct score obtained for all ventilation levels
was 68 percent (Shamoo et ah, 1992).  Therefore, Shamoo
et al.  (1992) concluded that this training protocol was
effective in training subjects to correctly estimate their
minute ventilation levels.
       For this handbook, inhalation rates were analyzed
from the  raw data provided  by Shamoo et al. (1992).
Table 5-21 presents the mean inhalation rates obtained
from  this analysis at four  ventilation  levels in two
microenvironments (i.e., indoors and outdoors) for  all
subjects. The mean inhalation rates for all subjects were
0.93, 1.92,3.01,4.80 m3/hr for low, medium, heavy, and
very heavy activities, respectively.
        Table 5-21. Actual Inhalation Rates Measured at
                 Four Ventilation Levels
                         Mean Inhalation Rate0 (m3/hr)a
  Subject    Location
                      Low   Medium
                                   Very
                           Heavy   Heavy
  All
  subjects
Indoor       1.23
(Treadmill
post)
Outdoor      0.88
Total        0.93
1.83
                              1.96
                              1.92
        3.13     4.13
        2.93     4.90
        3.01     4.80
  " Original data were presented in L/min. Conversion to m3/hr was
   obtained as follows:
                    hr   1000L   min
  Source: Adapted from Shamoo et al., 1992
      The population sample size used in this study was
small and was not selected to represent the general U.S.
population. The training approach employed may not be
cost effective because it was labor intensive; therefore,
this approach may not be viable in field studies especially
for field studies within large sample sizes.
      AIHC(1994) - The Exposure Factors Sourcebook -
AIHC (1994) recommends an average adult inhalation
rate  of 18 mVday and presents values for children of
various ages.  These recommendations were derived from
data presented in U.S. EPA (1989). The newer study by
Layton (1993) was  not considered.  In addition, the
Sourcebook presents probability distributions derived by
Brorby and Finley (1993).  For each distribution, the
@Risk formula is provided for direct use in the @Risk
simulation software (Palisade, 1992). The organization of
this document makes it very convenient to use in support
of Monte Carlo analysis.  The reviews of the supporting
studies are very brief with little analysis of their strengths
and weaknesses. The Sourcebook has been classified as
a relevant rather than key study because it is not the
primary   source   for  the   data   used   to  make
recommendations in this document. The Sourcebook is
very  similar to this document  in  the  sense that  it
summarizes exposure factor data and recommends values.
As such, it is clearly relevant as an alternative information
source on  inhalation rates as  well as other exposure
factors.

5.2.4.  Recommendations
      In the  Ozone Criteria Document prepared by the
U.S.  EPA  Office  of  Environmental  Criteria  and
Assessment, the EPA identified the collapsed  range of
activities and its corresponding  VR as follows: light
exercise (VE < 23 L/min or 1.4 m3/hr); moderate/ medium
exercise (VE= 24-43 L/min or 1.4-2.6 m3/hr);  heavy
exercise (VE= 43-63 L/min or 2.6-3.8 m3/hr); and very
heavy exercise (VE>  64 L/min or 3.8 nrVhr),  (Adams,
1993).
      Recent peer reviewed scientific papers and an EPA
report comprise the studies that were evaluated in this
Chapter.  These studies were  conducted  in the United
States among both men and  women of different age
groups. All are widely available.  The confidence ratings
in the inhalation rate recommendations are shown in Table
5-22.
      Each study focused on ventilation rates and factors
that  may affect them.  Studies were conducted among
randomly selected volunteers.   Efforts were  made to
include men,  women, different age groups, and  different
kinds of activities. Measurement methods are  indirect,
but reproducible. Methods are well described (except for
questionnaires) and experimental error is well
Page
5-22
                                                               Exposure Factors Handbook
                                                              	August 1997

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Volume I - General Factors
 Chapter 5 - Inhalation
                                 Table 5-22. Confidence in Inhalation Rate Recommendations
               Considerations
                                                                    Rationale
                                                                                                         Ratine
  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 EPA peer reviewed       High
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 provided.             Medium
Studies focused on ventilation rates and factors influencing them.              High
Studies conducted in the U.S.                                          High
Both data collection and re-analysis of existing data occurred.               Medium
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 not systematically.    Medium
An effort has been made to address age and gender, but not systematically.       High
Subjects were selected randomly from volunteers and measured in the same      High
way-
Measurement error is well documented by statistics, but procedures           Medium
measure factor indirectly.

Five key studies and six relevant studies were evaluated.
There is general agreement among researchers using different experimental      High
methods.
Several studies exist that attempt to estimate inhalation rates according to        High
age, gender and activity.
documented.  There is general agreement with these
estimates among researchers.
       The recommended inhalation rates for  adults,
children, and outdoor workers/athletes are based on the
key studies described  in this  chapter (Table  5-23).
Different survey designs and populations were utilized in
the studies described in this Chapter. A summary of these
designs, data generated, and their limitations/advantages
are presented  in Table 5-24,  Excluding  the study by
Layton (1993), the population surveyed in all of the key
studies described in this report were limited to the Los
Angeles area. This regional population may not represent
the general  U.S. population and may result in biases.
However, based on other aspects of the study design,
these studies were selected as the basis for recommended
inhalation rates.
       The selection of inhalation rates  to be  used for
exposure assessments depends on the age of the exposed
population  and the  specific   activity  levels  of this
population during  various exposure  scenarios.   The
recommended values  for adults, children (including
infants), and outdoor workers/athletes for use in various
exposure scenarios are discussed below. These rates were
calculated by  averaging  the inhalation  rates for each
activity level from the various key studies (see Table 5-
25).
                       Adults   (19-65+   yrs)  -     Adults   in  this
                 recommendation include young to middle age adults (19-
                 64 yrs), and older adults (65+ yrs).  The daily average
                 inhalation rates for long term exposure for adults are: 11.3
                 m3/day for women and  15.2 m3/day for men.   These
                 values are averages of the inhalation rates provided for
                 males and females in each of the three approaches  of
                 Layton (1993)  (Tables 5-11 through 5-14).  An upper
                 percentile is not recommended. Additional research and
                 analysis of activity pattern data and dietary data in the
                 future  is  necessary  to  attempt  to  calculate  upper
                 percentiles.
                       The recommended value for the general population
                 average inhalation rate, 11.3 m3/day for women and 15.2
                 m3/day for men, is different than the 20 m3/day which has
                 commonly been assumed in past EPA risk assessments.
                 In addition, recommendations are presented for various
                 ages and special populations (athletes, outdoor workers)
                 which  also  differ  from  20  m3/day.   Assessors are
                 encouraged to use values which most accurately reflect
                 the exposed population.
                       For exposure scenarios where the distribution  of
                 activity  patterns  is  known,  the  following results,
                 calculated from the studies referenced are shown in Table
                 5-25.   Based  on  these  key studies, the following
                 recommendations are made: for short term exposures in
Exposure Factors Handbook
August 1997	
                                                                 Page
                                                                  5-23

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                                                                            Volume I - General Factors
                                                                                 Chapter 5 - Inhalation
Table 5-23. Summary of Recommended Values for Inhalation
Population
Lonp-term Exposures
Infants
<1 year
Children
1-2 years
3-5 years
6-8 years
9-1 1 years
males
females
12-14 years
males
females
15-18 years
males
females
Adults (19-65+ yrs)
females
males
Short-term Exposures
Adults
Rest
Sedentary Activities
Light Activities
Moderate Activities
Heavy Activities
Children
Rest
Sedentary Activities
Light Activities
Moderate Activities
Heavy Activities
Outdoor Workers
Hourly Average
Slow Activities
Moderate Activities
Heavy Activities
Note: See Tables 5-25. 5-26.
Mean Upper Percentile


4.5mVday — -

6.8m3/day — ;_
8.3 m3/day —
lOmVday —

14m3/day —
13 nrVday

15m3/day — •?:
12m3/day

17m3/day
12m3/day — .

11.3m3/day
15.2m3/day ~-


0.4m3/hr —
0.5 m3/hr —
1.0 m3/hr — '•-'
1.6 m3/hr —
3.2 m3/hr

0.3m3/hr — 'i+
0.4m3/hr —
1.0m3/hr — .;',..,-.
1.2m3/hr —
1.9m3/hr — ;v: \\

1.3m3/hr 3.3m3/hr
1.1 m3/hr
1.5m3/hr
2.5m3/hr "V: '- ^
and 5-27 for reference studies.
which distribution of activity patterns are specified, the
recommended average rates are 0.4 m3/hr during rest; 0.5
m3/hr  for sedentary  activities;  1.0  m3/hr for  light
activities; 1.6 irrVhr for moderate activities; and 3.2 m3/hr
for heavy activities.
      Children (18 yrs old or less including infants) - For
the purpose of this recommendation, children are defined
as males and females between the ages of 1-18 years old,
while infants are individuals less than 1  year old. The
inhalation rates for  children  are  presented   below
according to different exposure scenarios.  The daily
inhalation rates for long-term dose assessments, are based
on the first approach of Layton (1993) (Table 5-11) and
are summarized in Table 5-26.
      Based on the key study results (i.e., Layton, 1993),
the recommended  daily  inhalation  rate  for infants
(children  less  than  1  yr),  during  long-term dose
assessments is 4.5 mVday.  For children 1-2 years old, 3-
5 years  old, and 6-8 years old, the recommended daily
inhalation  rates are 6.8  m3/day,  8.3  mVday,  and  10
mVday,  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 5-23.
      For short-term exposures for children aged 18 years
and under, in which activity patterns are known, the data
are summarized in Table 5-27. For short term exposures,
the recommended average hourly inhalation rates  are
based on these key studies. They are averaged over each
activity held 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).  These  values
represent averages  of the activity  level data from key
studies (Table 5-27).
      Outdoor Worker - Inhalation rate data for outdoor
workers/athlete are limited. However, based on the key
studies  (Linn et al., 1992  and 1993), the recommended
average hourly inhalation rate for outdoor workers is
1.3 m3/hr and the upper-percentile  rate is 3.3 m3/hr (see
Tables 5-5 and 5-8).  This is  calculated as the weighted
mean of the 99th  percentile values reported for  the
individuals on Panels 1 and 7 in Tables 5-5 and the  19
subjects in Table  5-8.   The recommended average
inhalation rates for outdoor workers based on the activity
levels categorized as  slow  (light activities), medium
(moderate activities), and fast (heavy activities) are 1.1
m3/hr, 1.5  m3/hr, and 2.5 m3/nr,  respectively.  These
values are based  on the data from Linn et al. (1992 and
1993) and are the weighted mean  of the values  for the
individuals on Panels 1 and 7 in Table 5-5 and the  19
outdoor workers  in Table 5-9.  Inhalation rates may be
higher among outdoor workers/athletes because levels of
activity  outdoors may  be  higher.   Therefore, this
subpopulation  group may be more susceptible to  air
pollutants and  are  considered a "high-risk" subgroup
(Shamoo et al., 1991; Linn et al., 1992).
Page
5-24
                   Exposure Factors Handbook
                  	August 1997

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 Volume I - General Factors
 Chapter 5 - Inhalation











































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Exposure Factors Handbook
August 1997
5-25

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                                                       Volume I - General Factors
                                                            Chapter 5 - Inhalation

Table 5-25.
Summary of Adult Inhalation Rates for Short-Term Exposure Studies
Arithmetic Mean (m3/hr)
Activity Level
Rest
0.5
..
0.4
0.4
--
Sedentary
0.5
0.6
0.4
—
--
Light
1.4
1.2
0.7
0.6
1.0
Moderate
2.4
1.8
1.4
1.5
1.6
High
3.3
--
3.6
3.0
3.0
Reference
Adams, 1993 (Lab protocols)
Adams, 1993 (Field protocols)
Layton, 1993 (Short-term
exposure)
Layton, 1993 (3rd approach)
Linn et al., 1992
Table 5-26. Summary of Children's (18 years old or less) Inhalation Rates for Long-Term Exposure Studies"

Age Males
less than 1 yr
1-2 years
3-5 years
6-8 years
9-11 years 14
12-14 years 15
15-18 years 17
Arithmetic Mean (m3/day)
Males and
Females Females
4.5
6.8
8.3
10
13
12
12

Reference
Layton, 1993
Layton, 1993
Layton, 1993
Layton, 1993
Layton, 1993
Layton, 1993
Layton, 1993
* Layton, 1993 1st approach.
Table 5-27. Summary of Children's Inhalation Rates for Short-Term Exposure Studies
Arithmetic Mean
(nvVhr)


Activity Level
Rest Sedentary
0.4 0.4
~
0.2 0.3
..
„
Light
0.8
—
0.5
1.8
0.8
Moderate
-
0.9
1.0
2.0
1.0
High
-
-
2.5
2.2
11
Reference
Adams, 1993 (Lab protocols)
Adams, 1993 (Field protocols)
Layton, 1993 (Short-term data)
Spier etal., 1992 (10-12 yrs)
Linn etal., 1992 (10-12 yrs)
Page
5-26
Exposure Factors Handbook
              August 1997

-------
 Volume 1 - General Factors
 Chapter 5 - Inhalation
 5.3. REFERENCES FOR CHAPTER 5

 Adams, W.C. (1993) Measurement of breathing rate
    and volume in routinely performed daily activities,
    Final Report. California Air Resources Board
    (GARB) Contract No. A033-205. June 1993. 185
    Pgs-
 American Industrial Health Council (AIHC). (1994)
    Exposure factors sourcebook. AIHC, Washington,
    DC.
 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.
 Benjamin, G.S. (1988) "The lungs." In:
    Fundamentals of Industrial Hygiene, Third Edition,
    Plog, B.A., ed. Chicago, IL: National Safety
    Council, p. 31-45.
 Brorby, G.; Finley, B.  (1993)  Standard probability
    density functions for routine use in environmental
    health risk assessment. Presented at the Society of
    Risk Analysis Meeting, December 1993, Savannah,
    GA.
 ICRP. (1981) International Commission on
    Radiological Protection. Report of the task group
    on reference man. New York: Pergammon Press.
 Layton, D.W. (1993) Metabolically consistent
    breathing rates for use in dose assessments. Health
    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.
 Linn, W.S.; Spier, C.E.; Hackney, J.D. (1993) Activity
    patterns in ozone-exposed construction workers. J.
    Occ. Med. Tox. 2(1):1-14.
 Menzel, D.B.; Amdur, M.O. (1986) Toxic responses of
    the respiratory system. In: Klaassen, C.; Amdur,
    M.O.; Doull, J., eds. Toxicology, The Basic Science
    of Poisons. 3rd edition. New York: MacMillan
    Publishing Company.
 Najjar, M.F.; Rowland, M. (1987) Anthropometric
    reference data and prevalence of overweight: United
    States. 1976-80. Hyattsville, MD: National Center
    for Health Statistics. U.S. Department of Health and
   Human Services: DHHS Publication No. (PHS)87-1688.
Palisade.  (1992)  ©Risk User Guide.  Newfield, NY:
   Palisade Corporation.
Sallis, J.F.; Haskell, W.L.; Wood, P.O.; Fortmann, S.P.;
   Rogers, T.; Blair, S.N.; Paffenbarger, Jr., R.S.
   (1985) Physical activity assessment methodology in
   the Five-City project. Am. J. Epidemiol. 121:91-
   106.
Shamoo, D.A.; Trim, S.C.; Little, D.E.; Linn, W.S.;
   Hackney, J.D. (1990) Improved quantitation of air
   pollution dose rates by improved estimation of
   ventilation rate. In:  Total Exposure Assessment
   Methodology:  A New Horizon, pp. 553-564. Air
   and Waste Management Assoc., Pittsburgh, PA.
Shamoo, D.A.; Johnson, T.R.; Trim, S.C.; Little, D.E.;
   Linn, W.S.; Hackney, J.D.  (1991) Activity patterns
   in a panel of outdoor workers exposed to oxidant
   pollution. J. Expos. Anal. Environ. Epidem.
   l(4):423-438.
Shamoo, D.A.; Trim, S.C.; Little, D.E.; Whynot, J.D.;
   Linn, W.S. (1992) Effectiveness of training subjects
   to estimate their level of ventilation. J. Occ. Med.
   Tox. l(l):55-62.
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.
U.S. EPA. (1985) Development of statistical
   distributions or ranges of standard factors used in
   exposure assessments. Washington, DC: Office of
   Health and Environmental Assessment; EPA report
   No. EPA 600/8-85-010.  Available from: NTIS,
   Springfield, VA; PB85-242667.
U.S. EPA. (1989) Exposure factors handbook.
   Washington, DC: Office of Research and
   Development, Office of Health and Environmental
   Assessment.  EPA/600/18-89/043.
U.S. EPA. (1992) Guidelines for exposure assessment.
   Washington, DC: Office of Research and
   Development, Office of Health and  Environmental
   Assessments. EPA/600/Z-92/001.
U.S. EPA. (1994) Methods for derivation of inhalation
   reference concentrations and application of
   inhalation dosimetry. Washington, DC: Office of
   Health and Environmental Assessment. EPA/600/8-
   90/066F.
Exposure Factors Handbook
August 1997
                                            Page
                                            5-27

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-------
 Volume I- General Factors

 Appendix 5A
                                 APPENDIX 5A
                               VENTILATION DATA
Exposure Factors Handbook
August 1997	
Page
5A-1

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  Volume I - General Factors

  Appendix 5A
              Table 5A-1. Mean Minute Ventilation (VF. L/min) by Group and Activity for Laboratory Protocols
       Activity
                  Young Children3
                                                             Children
                                                                            Adult Females
                                                                          Adult Male
   Lying
   Sitting
   Standing

   Walking
   Running
1.5 mph
1.875 mph
2.0 mph
2.25 mph
2.5 mph
3.0 mph
3.3 mph
4.0 mph

3.5 mph
4.0 mph
4.5 mph
5.0 mph
6.0 mph
 6.19
 6.48
 6.76

10.25
10.53
DNP
11.68
DNP
DNP
DNP
DNP

DNP
DNP
DNP
DNP
DNP
 7.51
 7.28
 8.49

 DNP
 DNP
 14.13
 DNP
 15.58
 17.79
 DNP
 DNP

26.77
31.35
37.22
 DNP
 DNP
 7.12
 7.72
 8.36

 DNP
 DNP
 DNP
 DNP
 20.32
 24.20
 DNP
 DNP

 DNP
46.03b
47.86b
50.78b
 DNP
 8.93
 9.30
 10.65

 DNP
 DNP
 DNP
 DNP
 24.13
 DNP
 27.90
 36.53

 DNP
 DNP
 57.30
 58.45
65.66b
       Young Children, male and female 3-5.9 yr olds; Children, male and female 6-12.9 yr olds; Adult Females, adolescent,
       young to middle-aged, and older adult females; Adult Males, adolescent, young to middle-aged, and older adult males';
  b    DNP, group did not perform this protocol or N was too small for appropriate mean comparisons
       Older adults not included in the mean value since they did not perform running protocol at particular speeds
  Source:   Adams. 1993.           	
                Table 5A-2. Mean Minute Ventilation (VK, L/min) by Group and Activity for Field Protocols
              Activity
              Young Children
                                                        Children
Play
Car Driving
Car Riding
Yardwork
Housework
Car Maintenance
Mowing
Woodworking
11.31
DNP
DNP
DNP
DNP
DNP
DNP
DNP
17.89
DNP
DNP
DNP
DNP
DNP
DNP
DNP
DNP
8.95
8.19
19.23e
17.38
DNP
DNP
	 DNP
DNP
10.79
9.83
26.07b/31.89c
DNP
23.21d
36.55e
	 24.42e
       Young Children, male and female 3-5.9 yr olds; Children, male and female 6-12.9 yr olds; Adult Females, adolescent,
       young to middle-aged, and older adult females; Adult Males, adolescent, young to middle-aged, and older adult males;
       DNP, group did not perform this protocol or N was too small for appropriate mean comparisons;
       Mean value for young to middle-aged adults only
       Mean value for older adults only
       Older adults not included in the mean value since they did not perform this activity.
       Adolescents not included in mean value since they did not perform this activity
  Source:   Adams. 1993.
Exposure Factors Handbook
August 1997	
                                                                                 Page
                                                                                 5A-3

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                                                       Volume I - General Factors

                                                      	Appendix 5A























a

b
c
d
c



Subj. #
1761
1763
1764
1765
1766
1767
1768
1769
1770
1771
1772
1773
1774
1775
1776
1778
1779
1780
1781
Mean
SD 	 	


Anthropometric Data, Job Categories, Calibration Results

Age (years) Ht. (in.) Wt. (Ib.) Ethnic Group3
26
29
32
30
31
34
32
32
26
39
32
39
23
42
29
35
40
37
38
33
71 180
63 135
71 165
73 145
67 170
74 220
69 155
77 230
70 180
66 150
71 260
69 170
68 150
67 150
70 180
76 220
70 175
75 242
65 165
70 181
4 36 	
Abbreviations are interpreted as follows. Ethnic Group: Asn =
White
Job: Car =

carpenter,

GCW = general construction worker, Irn
Site: Hosp = hospital buidling, Ofc = medical office complex.
Wht
Asn
Elk
Wht
His
Wht
Blk
Wht
Wht
Wht
Wht
Wht
His
Wht
His
Ind
Wht
His
His


Jobb
GCW
GCW
Car
GCW
Car
Car
GCW
Car
Car
Car
Car
Irn
Car
Irn
Car
Car
Car
Irn
Lab

Asian-Pacific, Blk = Black, His

= ironworker, Lab
Calibration data

= laborer


Sitec
Ofc
Ofc
Ofc
Ofc
Ofc
Ofc
Ofc
Hosp
Hosp
Hosp
Hosp
Hosp
Hosp
Hosp
Hosp
Hosp
Hosp
Hosp
Hosp

Calibration
HR Ranged
69-108
80-112
56-87
66-126
75-112
59-114
62-152
69-132
63-106
88-118
83-130
77-128
68-139
76-118
68-152
70-129
72-140
68-120
66-121
70-123
8-16
r20
.91
.95
.95
.97
.89
.98
.95
.99
.89
.91
.97
.95
.98
.88
.99
.94
.99
.98
.89
.94
.04
= Hispanic, Ind = American Indian, Wht =









H R range = range of heart rates in calibration study
r2 = coefficient of determination (proportion of ventilation rate variability explainable by heart rate variability under calibration-study
conditions.
ource: Linnet
using quadratic prediction equation).
al.. 1993.






Table 5A-4
Gerider/Age
(y)
Males
Under 3
3 to < 10
10 to < 18
18 to < 30
30 to < 60
60 +
Female^
Under 3
3 to < 10
10to< 18
18 to < 30
30 to < 60
60+ 	
Statistics of the Age/Gender Cohorts Used to Develop Regression Equations for Predicting Basal Metabolic Rates (BMR)
BMR
MJd'1 	

1.51
4.14
5.86
6.87
6.75
5.59

1.54
3.85
5.04
5.33
5.62
4.85

tSD

0.918
0.498
1.171
0.843
0.872
0.928

0.915
0.493
0.780
0.721
0.630
0.605

cva

0.61
0.12
0.20
' 0.12
0.13
0.17

0.59
0.13
0.15
0.14
0.11
0.12
Body Weight
(kg)

6.6
21
42
63
64
62

6.9
21
38
53
61
56

Nb

162
338
734
2879
646
50

137
413
575
829
372
38

BMR Equation0

0.249 bw- 0.127
0.095 bw + 2. 110
0.074 bw + 2.754
0.063 bw + 2.896
0.048 bw + 3.653
0.049 bw + 2.459

0.244 bw- 0.130
0.085 bw + 2.033
0.056 bw + 2.898
0.062 bw + 2.036
0.034 bw + 3.538
0.038 bw + 2.755

rd

0.95
0.83
0.93
0.65
0.6
0.71

0.96
0.81
0.8
0.73
0.68
0.68
a Coefficient of variation (SD/mean)
N = number of subjects
0 Body weight (bw) in kg
d coefficient of correlation
Source: Lavton. 1993. 	 ___ 	 — 	 — 	 '
Page
5A-4
 Exposure Factors Handbook
	August 1997

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Volume I - General Factors 	 I,
Appendix 5A -=:-BlE





























































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Exposure Factors Handbook Page
August 1997 5A-5

-------
                                                        Volume I - General Factors
                                                                    Appendix 5A
f%
Table 5A-6. Estimated Minute Ventilation Associated with Activity Level for Average Male Adult
Level of work L/min
Light 13
Light 19
Light 25
Moderate 30
Moderate 35
Moderate 40
Heavy 55
Heavy 63
Very heavy 72
Very heavy 85
Severe 100+
Representative activities
Level walking at 2 mph; washing clothes
Level walking at 3 mph; bowling; scrubbing floors
Dancing; pushing wheelbarrow with 15-kg load; simple construction;



stacking firewood
Easy cycling; pushing wheelbarrow with 75-kg load; using sledgehammer
Climbing stairs; playing tennis; digging with spade
Cycling at 13 mph; walking on snow; digging trenches
Cross-country skiing; rock climbing; stair climbing
with load; playing squash or handball; chopping
with axe
Level running at 10 mph; competitive cycling
Competitive long distance running; cross-country skiing





a Average adult assumed to weigh 70 kg.
Source: Adapted from U.S. EPA, 1985
Page
5A-6
 Exposure Factors Handbook
	August 1997

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Volume I- General Factors
Appendix 5A












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Exposure Factors Handbook
August 1997 	
Page
5A-7

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-------
Volume I - General Factors
Chapter 6 - Dermal
6.    DERMAL ROUTE
      Dermal exposure can occur during a variety of
activities   in   different   environmental  media  and
microenvironments (U.S. EPA, 1992). These include:

      •   Water (e.g., bathing, washing, swimming);
      •   Soil  (e.g.,  outdoor recreation,  gardening,
          construction);
      •   Sediment (e.g., wading, fishing);
      •   Liquids (e.g., use of commercial products);
      •   Vapors/fumes  (e.g.,   use  of  commercial
          products); and
      •   Indoors (e.g., carpets, floors, countertops).

The  major factors that  must  be  considered  when
estimating  dermal  exposure   are:   the  chemical
concentration in contact with the skin, the potential dose,
the extent of skin surface  area exposed, the duration of
exposure, the absorption of the chemical through the skin,
the internal dose, and the amount of chemical that can be
delivered to a target  organ (i.e., biologically effective
dose) (see Figure 6-1). A detailed discussion of these
factors  can be  found in  Guidelines  for  Exposure
Assessment (U.S. EPA, 1992a).
      This chapter focuses on measurements of body
surface areas and  various factors needed to estimate
dermal  exposure  to  chemicals in  water  and- soil.
Information concerning dermal exposure to pollutants in
indoor  environments  is  limited.  Useful information
concerning estimates of body surface area can be found in
"Development of Statistical Distributions or Ranges of
Standard  Factors Used in  Exposure Assessments" (U.S.
EPA, 1985). "Dermal Exposure Assessment:  Principles
and Applications (U.S. EPA, 1992b), provides detailed
information concerning dermal exposure using a stepwise
guide in the exposure assessment process.
      The available studies have been classified as either
key or relevant based on  their applicability to exposure
assessment needs and are summarized in  this chapter.
Recommended values are  based on the results of the key
studies.   Relevant  studies are presented to provide an
added perspective on the state-of-knowledge pertaining to
dermal exposure factors. All tables and figures presenting
data from these studies are shown  at the end  of this
chapter.

6.1.   EQUATION FOR DERMAL DOSE
       The  average daily  dose (ADD)  is the dose rate
averaged over a pathway-specific  period of exposure
expressed as a daily dose on a per-unit-body-weight basis.
The ADD is used for exposure to chemicals with non-
carcinogenic non-chronic effects. For compounds with
carcinogenic or chronic effects, the lifetime average daily
dose  (LADD) is used.  The LADD is the dose rate
averaged over a lifetime.
      For dermal contact with chemicals in soil or water,
dermally absorbed average daily dose can be estimated by
(U.S. EPA, 1992b):
    ADD
                 BW x AT
                        (Eqn. 6-1)
  where:
     ADD
     DAeve
     EV
     ED
     EF
     SA
     BW
     AT
average daily dose (mg/kg-day);
absorbed dose per event (mg/cm2-event);
event frequency (events/day);
exposure duration (years);
exposure frequency (days/year);
skin surface area available for contact (cm2);
body weight (kg);, and
averaging  time (days) for noncarcinogenic
effects, AT = ED and for carcinogenic effects,
AT = 70 years or 25,550 days.
This method is to be used to calculate the absorbed dose
of a chemical.  Total body surface area (SA) is assumed
to be exposed for a period of time (ED).
       For dermal contact with water, the DAevent is
estimated  with  consideration  for the  permeability
coefficient from water,  the chemical  concentration in
water, and the event duration.  The approach to estimate
DAevent is different for inorganic and organic compounds.
The nonsteady-state approach to estimate the dermally
absorbed dose from  water is recommended  as the
preferred approach for organics which exhibit octanol-
water partitioning  (U.S.  EPA,   1992b).   First,  this
approach more accurately reflects normal human exposure
conditions since the short contact  times associated with
bathing and  swimming generally mean that steady state
will not occur.  Second, the approach accounts for uptake
that can occur  after the actual exposure event due to
absorption of residual chemical trapped in  skin tissue.
Use  of the nonsteady-state  model for  organics has
implications for selecting permeability coefficient (Kp)
values (U.S. EPA, 1992b). It is recommended that the
traditional steady-state  approach be applied to inorganics
(U.S. EPA, 1992b). Detailed information concerning how
to estimate  absorbed dose per event (DAevent) and Kp
 Exposure Factors Handbook
 August 1997
                                               Page
                                                 6-1

-------
                                                                          Volume I - General Factors
                                                                                   Chapter 6 - Dermal
 values can be found in Section 5.3.1 of "Dermal Exposure
 Assessment:  Principles and Applications" (U.S. EPA,
 I992b).
       For  dermal  contact  with contaminated  soil,
 estimation of the DAevem is different from the estimation
 for dermal contact with chemicals in water. It is based on
 the concentration of the chemical in soil, the adherence
 factor  of soil to skin,  and the absorption fraction.
 Information for DAevent estimation from soil contact can
 be found in U.S. EPA (I992b), Section 6.4.
       The apparent simplicity of the absorption fraction
 (percent  absorbed)  makes  this  approach  appealing.
 However, it is not practical to apply it to water contact
 scenarios, such as swimming, because of the difficulty in
 estimating the total material contacted (U.S. EPA, I992b).
 It is assumed that there is essentially an infinite amount of
 material available, and that the chemical will be replaced
 continuously,  thereby increasing the amount of material
 (containing  the  chemical)  available by  some  large
 unknown amount. Therefore, the permeability coefficient
 -based  approach  is recommended over  the absorption
 fraction approach for determining the dermally absorbed
 dose of chemicals in aqueous media.
       Before  the absorption fraction approach can be
 used   in  soil contact  scenarios,  the  contaminant
 concentration  in soil must be established. Not all of the
 chemical  in  a layer of dirt applied  to skin may  be
 bioavailable, nor is it assumed to be an internal dose.
 Because of the lack of Kp data for compounds bound to
 soil, and reduced uncertainty in defining an applied dose,
 the absorption fraction-based approach is suggested for
 determining the internal dose of chemicals in soil.  More
 detailed explanation of the equations, assumptions,  and
 approaches  can  be  found  in   "Dermal Exposure
 Assessment:  Principles and Applications"  (U.S.  EPA.
 I992b).

 6.2.  SURFACE AREA
 6.2.1. Background
      The total  surface area  of skin  exposed to a
 contaminant must be determined using measurement or
 estimation techniques   before  conducting  a  dermal
 exposure  assessment.   Depending  on  the exposure
 scenario, estimation of the surface area for the total body
 or a specific body part can be used to calculate the contact
 rate for the pollutant.  This section presents estimates for
 total body surface area and for body parts and presents
 information on the application of body surface area data.
6.2.2. Measurement Techniques
      Coating, triangulation, and surface integration are
direct measurement techniques that have been used to
measure total body surface area and the surface area of
specific body parts.  Consideration has been given for
differences due to age, gender, and race.  The results of
the  various  techniques  have  been  summarized  in
"Development of Statistical Distributions or Ranges of
Standard Factors Used in Exposure Assessments" (U.S.
EPA, 1985).  The coating method  consists of coating
either the whole body or  specific body regions with a
substance of known  or  measured area.  Triangulation
consists of marking the area of the body into geometric
figures, then calculating the figure areas from their linear
dimensions.  Surface  integration is performed by using a
planimeter and adding the areas.
      The   triangulation   measurement  technique
developed by Boyd (1935) has been found to be highly
reliable.  It estimates the surface area of the body using
geometric approximations  that assume parts of the body
resemble geometric solids (Boyd,  1935). More recently,
Popendorf and Leffingwell (1976), and Haycock et al.
(1978) have developed similar geometric methods that
assume body parts correspond to geometric solids, such as
the sphere and cylinder.  A linear method proposed by
DuBois and DuBois (1916) is based on the principle that
the surface areas of the parts of the body are proportional,
rather than equal to the  surface area of the solids they
resemble.
      In  addition  to direct measurement techniques,
several formulae have been proposed to  estimate body
surface area from  measurements of other  major body
dimensions (i.e., height and weight) (U.S. EPA, 1985).
Generally, the formulae are based on the principles that
body density and shape are  roughly the same and that the
relationship  of surface area to any  dimension  may be
represented  by the curve  of central tendency  of their
plotted values or by the algebraic expression for the curve.
A discussion and comparison of formulae to determine
total body surface area are presented in Appendix 6A.

6.2.3. Key Body Surface Area Studies
      U.S. EPA (1985) -  Development of Statistical
Distributions or Ranges of Standard Factors  Used in
Exposure Assessments -  U.S. EPA (1985) analyzed  the
direct surface area measurement data of Gehan and
George (1970)  using the Statistical Processing System
(SPS) software package of Buhyoff et al. (1982). Gehan
and George (1970) selected 401 measurements made by
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Boyd (1935) that were complete for surface area, height,
weight, and age for their analysis.  Boyd (1935) had
reported surface area estimates for 1,114 individuals using
coating, triangulation,  or surface  integration methods
(U.S. EPA, 1985).
      U.S. EPA (1985) used SPS to generate equations
to calculate surface  area as a function of height and
weight. These equations were then used to calculate body
surface area distributions of the U.S. population using the
height and weight data obtained from the National Health
and Nutrition Examination Survey (NHANES) II and the
computer program QNTLS of Rochon and Kalsbeek
(1983).
      The equation proposed by Gehan and George
(1970) was determined by U.S. EPA (1985) to be the best
choice for estimating total body surface area. However,
the paper by Gehan and George (1970) gave insufficient
information to estimate  the standard  error about the
regression.  Therefore, U.S. EPA  (1985) used the 401
direct measurements of children and adults and reanalyzed
the data using the formula of Dubois and Dubois (1916)
and SPS to obtain the standard error (U.S. EPA, 1985).
       Regression equations were developed for specific
body parts using the Dubois and Dubois (1916) formula
and using the surface area of various body parts provided
by Boyd (1935) and Van Graan (1969) in conjunction
with  SPS.   Regression  equations for  adults were
developed for the head, trunk (including the neck),-upper
extremities (arms and hands, upper arms, and forearms)
and lower extremities (legs and feet, thighs, and lower
legs) (U.S. EPA, 1985). Table 6-1 presents a summary of
the equation parameters developed by U.S. EPA (1985)
for calculating surface area of adult body parts. Equations
to estimate the body part surface area of children were not
developed because of insufficient data.
       Percentile estimates of  total surface area  and
surface area of body parts developed by U.S. EPA (1985)
using the regression equations and NHANES II height and
weight data are presented in Tables 6-2  artd 6-3 for adult
males  and adult females, respectively.  The calculated
mean surface areas of body parts for men and women are
presented  in Table  6-4.   The standard  deviation,  the
minimum value, and the maximum value for each body
part are included. The median total body surface area for
men and women and the corresponding standard errors
about the regressions are also given. It has been assumed
that errors  associated  with  height  and weight  are
negligible (U.S. EPA, 1985).  The data in Table 6-5
present the percentage of total body surface by body part
for men and women.
      Percentile estimates for total surface area of male
and female children presented in Tables 6-6 and 6-7 were
calculated using the total surface area regression equation,
NHANES II height and weight data, and using QNTLS.
Estimates are not included for children younger than 2
years old because NHANES height data are not available
for this age group. For children, the error associated with
height and weight cannot be assumed to be zero because
of their relatively small sizes.  Therefore, the standard
errors of the percentile estimates cannot be estimated,
since it cannot be assumed that the errors associated with
the  exogenous variables (height  and weight)  are
independent of that associated with the model; there are
insufficient data to determine the relationship between
these errors.
      Measurements of the surface area of children's
body parts are summarized as a percentage of total surface
area in Table 6-8.  Because of the small sample size, the
data  cannot be  assumed to  represent the  average
percentage of surface area by body part for all children.
Note that  the  percent  of total body surface area
contributed by the head decreases from childhood  to
adult, while the percent contributed by the leg increases.
      Phillips et al.  (1993) - Distributions of Total Skin
Surface Area to Body Weight Ratios  - Phillips et al.
(1993)  observed a strong  correlation (0.986) between
body surface area and body weight and studied the effect
of using these factors, as  independent  variables in the
LADD equation. Phillips et al.  (1993) concluded that,
because of the correlation between these two  variables,
the use of body surface area to body weight  (SA/BW)
ratios in human exposure assessments is more appropriate
than  treating  these  factors as  independent  variables.
Direct measurement (coating, triangulation, and surface
integration) data from the scientific  literature were used
to calculate body surface area to body weight (SA/BW)
ratios for three age  groups (infants aged 0 to 2 years,
children aged 2.1 to 17.9 years, and adults 18 years and
older).  These ratios were calculated by dividing body
surface areas by corresponding body weights for the 401
individuals analyzed by Gehan and George (1970) and
summarized  by U.S.  EPA (1985).   Distributions  of
SA/BW ratios were developed  and summary statistics
were calculated for each of the three age groups and the
combined  data  set.   Summary  statistics  for  these
populations are presented  in Table  6-9.  The shapes of
these  SA/BW  distributions  were  determined using
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 D'Agostino's test.  The results indicate that the SA/BW
 ratios for infants  are lognormally distributed and the
 SA/BW ratios for adults and all ages combined are
 normally distributed (Figure 6-2).  SA/BW ratios for
 children  were  neither  normally  nor  lognormally
 distributed.  According to Phillips et al. (1993), SA/BW
 ratios should be used to calculate LADDs by replacing the
 body surface area  factor in the numerator of the LADD
 equation with the SA/BW ratio and eliminating the body
 weight factor in the denominator of the LADD equation.
       The  effect  of gender and  age  on  SA/BW
 distribution was also analyzed by classifying the 401
 observations by gender and age.  Statistical analyses
 indicated no  significant differences between SA/BW
 ratios for males and females.  SA/BW ratios were found
 to decrease with increasing age.

 6.2.4. Relevant Surface Area Studies
       Murray  and Burmaster  (1992)  -  Estimated
 Distributions for Total Body Surface Area of Men and
 Women in the United States - In this study, distributions
 of total body surface area for men and women ages 18 to
 74 years were estimated using Monte Carlo simulations
 based on height  and weight distribution data.  Four
 different formulae  for estimating body surface area as a
 function of height  and weight were employed: Dubois
 and Dubois (1916); Boyd (1935); U.S. EPA (1985); and
 Costeff (1966).  The formulae of  Dubois and Dubois
 (1916); Boyd (1935); and U.S. EPA (1985) are based on
 height and weight.  They are discussed in Appendix 6A.
 The formula developed by Costeff (1966) is based on 220
 observations that estimate body surface area  based on
 weight only. This formula is:
      4W+7/W+90
                                          (Eqn. 6-2)
  where:
          SA = Surface Area (m2); and
          W = Weight (kg).
Formulae were compared and the effect of the correlation
between height and weight on the body surface area
distribution was analyzed.
      Monte  Carlo simulations  were  conducted  to
estimate body surface area distributions. They were based
on the bivariate distributions estimated by Brainard and
Burmaster (1992)  for height and natural logarithm  of
weight and the formulae described  above.  A total of
5,000 random samples each for men and women were
selected from the two correlated bivariate distributions.
Body surface area calculations  were  made  for each
sample, and for each formula, resulting in body surface
area distributions.  Murray and Burmaster (1992), found
that the body surface area frequency distributions were
similar for the four models (Table 6-10).  Using the U.S.
EPA (1985) formula, the median surface area values were
calculated to be 1.96 m2 for men and 1.69 m2 for women.
The median value for women is identical to that generated
by U.S. EPA (1985) but differs for men by approximately
1  percent.    Body surface  area  was  found  to have
lognormal distributions for both men and women (Figure
6-3). It was also found that assuming correlation between
height and weight influences the final distribution by less
than 1 percent.
      AIHC (1994) - Exposure Factors Sourcebook - The
Exposure Factors  Sourcebook (AIHC,  1994)  provides
similar  body surface  area data as  presented  here.
Consistent with this document, average and percentile
values are presented on the basis  of age and gender.  In
addition, the Sourcebook presents  point estimates  of
exposed skin surface areas for various scenarios on the
basis of several published studies. Finally, the Sourcebook
presents  probability distributions based on U.S. EPA
(1989) and  as  derived  by Thompson  and Burmaster
(1991); Versar (1991); and Brorby and  Finley (1993).
For each distribution, the ©Risk formula is provided for
direct use in  the ©Risk simulation software (Palisade,
1992).  The organization of this document, makes it very
convenient to use  in support of Monte Carlo  analysis.
The reviews of the supporting studies are very brief with
little analysis of  their  strengths  and weaknesses.  The
Sourcebook has been classified as a relevant rather than
key study because it is not the primary source for the data
used to make recommendations in this document.  The
Sourcebook is very similar to this document in the sense
that it summarizes exposure factor data and recommends
values. As such,  it is clearly relevant as an alternative
information source on body surface area as well as other
exposure factors.

6.2.5. Application of Body Surface Area Data
      In many settings, it is likely that only certain parts
of the body are exposed.  All body  parts that come in
contact with  a chemical must be considered to estimate
the total surface area of the body exposed.  The data in
Table 6-4 may be used to estimate the total surface area of
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the particular body  part(s).  For example, to assess
exposure to a chemical in a cleaning product for which
only the hands are exposed, surface area values for hands
from Table 6-4 can be used. For exposure to both hands
and arms, mean surface areas for these parts from Table
6-4 may be summed to estimate the  total  surface area
exposed. The mean surface area of these body parts for
men and women is as follows:

                                 Surface Area (m )
                                 Men     Women
Arms (includes upper arms and forearms)  0.228    0.210
Hands                           0.084    0.075
Total area                         0.312    0.285
Therefore, the total body part surface area that may be in
contact with the chemical in the cleaning product in this
example is 0.312 m2 for men and 0.285 m2 for women.
      A  common  assumption is that clothing prevents
dermal   contact   and  subsequent   absorption   of
contaminants. This assumption may be false in cases
where the chemical may be able to penetrate clothing,
such as in a fine dust or liquid suspension.  Studies using
personal  patch monitors  placed  beneath clothing  of
pesticide workers exposed to fine mists and vapors show
that a significant proportion of dermal exposure may
occur at anatomical sites covered by clothing (U.S. EPA,
1992b).  In  addition, it has been demonstrated that a
"pumping" effect  can  occur which causes  material to
move  under loose  clothing  (U.S.  EPA,  1992b).
Furthermore, studies have demonstrated that hands cannot
be  considered to be protected from exposure even if
waterproof gloves are worn (U.S. EPA, 1992b). This may
be  due to contamination to the interior surface of the
gloves when donning  or removing them during work
activities (U.S. EPA,  1992b).  Depending on the task,
pesticide workers  have been shown to experience  12
percent to 43 percent of their total exposure through their
hands, approximately 20 percent to  23 percent through
their heads and necks, and 36 percent to  64 percent
through their torsos and arms, despite the use of protective
gloves and clothing (U.S. EPA, 1992b).
      For swimming and bathing scenarios, past exposure
assessments have assumed that 75 percent to  100 percent
of the skin surface is  exposed (U.S. EPA, 1992b). As
shown in Table 6-4, total adult body surface areas can
vary from about 17,000 cm2 to 23,000 cm2. The mean is
reported as approximately 20,000 cm2.
      For default purposes, adult body surface areas of
20,000 cm2 (central estimate) to 23,000 cm2 (upper
percentile) are recommended  in  U.S. EPA (1992b).
Tables 6-2 and 6-3 can also be used when the default
values are not preferred. Central  and upper-percentile
values for children should be derived from Table 6-6 or
6-7.
      Unlike exposure to liquids,  clothing may or may
not be effective in limiting the extent of exposure to soil.
The  1989 Exposure Factors Handbook presented two
adult clothing scenarios for outdoor activities (U.S. EPA,
1989):

      Central tendency mid range: Individual wears
      long sleeve shirt, pants, and shoes.  The exposed
      skin surface is limited to the head and hands (2,000
      cm2).
      Upper percentile: Individual wears a short sleeve
      shirt, shorts, and shoes. The exposed skin surface
      is limited to the head, hands, forearms, and lower
      legs (5,300 cm2).

The  clothing  scenarios presented above,  suggest that
roughly 10 percent to 25 percent of the skin area may be
exposed to soil.  Since some studies have suggested that
exposure can occur under clothing, the upper end of this
range was selected in Dermal Exposure Assessment:
Principles and Applications (U.S. EPA,  1992b) for
deriving defaults.  Thus, taking 25 percent of the total
body surface area results in defaults for adults of 5,000
cm2 to 5,800 cm2. These values were obtained from the
body surface areas in Table 6-2 after rounding to 20,000
cm2 and 23,000 cm2, respectively.  The range of defaults
for children can be derived by multiplying the 50th and
95th percentiles by 0.25 for the ages of interest.
       When addressing soil contact exposures, assessors
may want to refine estimates of surface area exposed on
the basis of  seasonal  conditions.   For  example,  in
moderate climates, it may be reasonable to assume that 5
percent of the skin is exposed during the winter, 10
percent during the spring and fall, and 25 percent during
the summer.
       The previous discussion, has presented information
about the area of skin exposed to soil. These estimates of
exposed skin area should be useful to assessors using the
traditional approach of multiplying the soil adherence
factor by exposed skin area to estimate the total amount of
soil on skin. The next section presents soil adherence data
specific to activity and body part  and is designed to be
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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 6-4
to obtain total surface areas of specific body parts. See
detailed discussion below.

6.3.   SOIL ADHERENCE TO SKIN
6.3.1. Background
      Soil adherence to  the surface of the skin is a
required parameter to calculate dermal dose when the
exposure scenario  involves dermal   contact  with  a
chemical in soil.  A number of studies have attempted to
determine the magnitude of dermal soil adherence. These
studies are described in detail in U.S. EPA (1992b). This
section  summarizes recent  studies that estimate soil
adherence to skin for use as exposure factors.

6.3.2. Key Soil Adherence to Skin Studies
      Kissel et al.  (1996a) -  Factors Affecting Soil
Adherence to Skin in Hand-Press Trials: Investigation of
Soil Contact and Skin Coverage - Kissel et al. (1996a)
conducted soil adherence experiments  using five soil
types  (descriptor)  obtained locally   in  the  Seattle,
Washington, area: sand  (211), loamy sand (CP), loamy
sand (85), sandy loam (228), and silt loam (72). All soils
were analyzed  by hydrometer  (settling velocity) to
determine composition. Clay contents ranged from 0.5 to
7.0 percent.   Organic carbon content, determined by
combustion, ranged from 0.7 to 4.6 percent.  Soils were
dry sieved to obtain particle size ranges of <150,150-250,
and >250 yum.  For each  soil type, the amount of soil
adhering to an adult female hand, using both sieved and
unsieved  soils,   was determined  by  measuring the
difference in soil sample weight before and after the hand
was pressed into a pan containing the test soil. Loadings
were estimated by dividing the recovered soil mass by
total hand area, although loading occurred primarily on
only one side of the hand. Results showed that generally,
soil adherence to hands could be directly correlated with
moisture content, inversely correlated with particle size,
and  independent of  clay content or organic  carbon
content.
      Kissel et  al. (1996b) - Field  Measurement of
Dermal Soil Loading Attributable to Various Activities:
Implications  for Exposure  Assessment   -  Further
experiments were conducted by Kissel et al.  (1996b) to
estimate soil adherence associated with various indoor and
outdoor activities: greenhouse gardening, tae kwon do
karate,  soccer,  rugby,  reed  gathering,   irrigation
installation,  truck farming,  and playing in mud.   A
summary of field studies by activity, gender, age, field
conditions, and clothing worn is presented in Table 6-11.
Subjects' body surfaces (forearms, hands, lower legs in all
cases, faces, and/or feet; pairs in some cases) were washed
before and after monitored activities.  Paired samples
were  pooled into single ones.  Mass recovered was
converted to loading using allometric models of surface
area.  These data are presented in Table 6-12. Results
presented are based on direct measurement of soil loading
on the surfaces of skin before and after occupational and
recreational activities that may be expected to have soil
contact (Kissel et al., 1996b).

6.3.3. Relevant Soil Adherence to Skin Studies
      Lepow etal. (1975) - Investigations into Sources of
Lead in the Environment of Urban Children - This study
was   conducted  to   identify   the   behavioral  and
environmental factors contributing to elevated lead levels
in ten preschool children.  The study was performed over
6 to 25 months.   Samples of dirt from the  hands  of
subjects were collected during the course of play around
the areas where they lived.   Preweighed self-adhesive
labels were used to sample a standard area on the palm of
the hands of 16 male and female children. The  labels
were pressed on a single area, often pressed several times,
to obtain an adequate sample. In the laboratory,  labels
were  equilibrated in a desiccant cabinet for  24  hours
(comparable to the preweighed desiccation), then the total
weight was recorded. The mean weight of dirt from the 22
hand sample labels was 11 mg. This corresponds to 0.51
mg/cm2.  Lepow et al. (1975) reported that this amount
(11 mg) represented only a small fraction (percent not
specified) of the total amount of surface dirt present on
the hands, because much of the dirt may be trapped in skin
folds and creases or there may be a patchy distribution of
dirt on hands.
      Roels et al. (1980) - Exposure to Lead by the Oral
and the Pulmonary Routes of Children Living  in  the
Vicinity of a Primary Lead Smelter - Roels et al. (1980)
examined blood lead levels among 661 children, 9 to 14
years old, who lived in the vicinity of a large lead smelter
in Brussels, Belgium. During five different study periods,
lead levels were assessed by rinsing the childrens'  hands
in 500 mL dilute nitric acid.  The amount of lead on the
hands was divided by the concentration of lead in soil to
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estimate the amount of soil adhering to the hands.  The
mean soil amount adhering to the hands was 0.159 grams.
      Que Hee et al.  (1985)  - Evolution of Efficient
Methods to Sample Lead Sources, Such as House Dust
and Hand Dust, in the Homes of Children - Que Hee et al.
(1985) used soil haying particle sizes ranging from <. 44
to 833 urn diameters, fractionated into six size ranges, to
estimate the amount that adhered to the palm of the hand
that  are assumed to be approximately  160 cm2  (test
subject with an average total body surface area of 16,000
cm2  and a total hand surface  area of 400  cm2).  The
amount of soil that adhered to skin was determined by
applying approximately 5 g of soil for each size fraction,
removing  excess  soil by shaking the  hands, and  then
measuring  the difference  in  weight before and after
application.  Several assumptions were made to apply
these results to other soil types and exposure scenarios:
(a)  the  soil is composed  of particles  of the indicated
diameters;  (b) all soil types and particle sizes adhere to
the skin to the degree observed in this study; and  an
equivalent weight of particles  of any diameter adhere to
the same surface area of skin. On average, 31.2 mg of soil
adhered to the palm of the  hand.
      Driver et al. (1989) - Soil Adherence to Human
Skin - Driver et al.  (1989) conducted soil adherence
experiments using various  soil types collected from sites
in Virginia.  A total of five soil types were collected:
Hyde,  Chapanoke, Panorama,  Jackland, and Montalto.
Both top soils and subsoils were collected for each soil
type.   The  soils were also  characterized by cation
exchange capacity, organic content, clay mineralogy, and
particle size distribution.  The soils were dry sieved to
obtain particle sizes of ^250 urn and < 150 [am. For each
soil type, the amount of soil adhering to adult male hands,
using both sieved and unsieved soils, was determined
gravimetrically (i.e., measuring the difference in soil
sample weight before  and after soil application to the
hands).
      An attempt was made to measure only the minimal
or "monolayer" of soil adhering to the hands. This was
done by mixing a pre-weighed amount of soil  over the
entire surface area of  the   hands  for a period  of
approximately 30 seconds,  followed by removal of excess
soil by gently rubbing the hands together after contact
with the soil.  Excess soil that was removed from the
hands was collected,  weighed, and compared to the
original soil  sample weight.   The authors measured
average adherence of 1.40 mg/cm2 for particle sizes less
than 150 um, 0.95 mg/cm2 for particle sizes less than 250
um, and 0.58 mg/cm2 for unsieved soils.  Analysis of
variance statistics showed that the most important factor
affecting adherence variability was  particle  size (p <
0.001).  The next most important factor is soil type and
subtype (p < 0.001).  The interaction of soil type and
particle  size was  also  significant,  but  at  a lower
significance level (p < 0.01).
      Driver et al. (1989) found statistically significant
increases in soil adherence with decreasing particle size;
whereas, Que Hee et  al.  (1985) found  relatively small
changes with changes in particle size. The amount of soil
adherence found by Driver et al. (1989) was greater than
that reported by Que Hee et al. (1985).
      Sedman  (1989) -  The Development of Applied
Action  Levels for Soil  Contact: A  Scenario for the
Exposure of Humans to  Soil in a  Residential Setting -
Sedman (1989) used the estimate from Roels et al. (1980),
0.159 g, and the average surface area of the hand of an 11
year old, 307 cm2 to estimate the amount of soil adhering
per unit area of skin to be 0.9 mg/cm2.  This assumed that
approximately 60 percent (185 cm2) of the lead on the
hands was recovered by the method employed by Roels et
al. (1980).
      Sedman (1989) used estimates from Lepow et al.
(1975), Roels et al. (1980), and Que Hee et al. (1985) to
develop a maximum soil load that could occur on the skin.
A rounded arithmetic mean of 0.5 mg/cm2 was calculated
from these three studies.  According to Sedman (1989),
this was near the maximum load of soil that could occur
on the skin but it is unlikely that most skin surfaces would
be covered with this amount of soil (Sedman, 1989).
       Yang  et  al.  (1989)   - In  vitro  and  In  vivo
Percutaneous  Absorption  of Benzo[a]pyrene from
Petroleum Crude - Fortified Soil in the Rat - Yang et al.
(1989)   evaluated  the   percutaneous   absorption  of
benzo[a]pyrene (BAP) in petroleum crude oil sorbed on
soil using a modified in vitro technique. This method was
used  in  preliminary experiments  to  determine   the
minimum amount of soil adhering to the skin of rats.
Based  on  these  results,   percutaneous   absorption
experiments with the  crude-sorbed soil were conducted
with soil particles of <150 ^m only. This particle size
was intended to represent the composition of the soil
adhering to the skin surface. Approximately 9 mg/cm2 of
soil was found to be the minimum amount required for a
"monolayer" coverage of the skin surface in both in vitro
and in vivo experiments.  This value is larger than reports
for human skin in the studies of Kissel et al.,  1996a,b;
Lepow et al., 1975; Roels et al., 1980; and Que Hee et al.,
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 1985.  Differences between  the  rat and human soil
 adhesion findings may be the result of differences in rat
 and human skin texture, the  types of soils used, soil
 moisture content or possibly the methods of measuring
 soil adhesion (Yang et al., 1989).

 6.4.   RECOMMENDATIONS
 6.4.1. Body Surface Area
       Body surface area estimates are based on direct
 measurements.  Re-analysis of data collected by  Boyd
 (1935) by several investigators (Gehan and George,  1970;
 U.S. EPA, 1985; Murray and Burmaster, 1992; Phillips et
 al., 1993) constitutes much of this literature. Methods are
 highly reproducible and the results are widely accepted.
 The  representativeness  of  these  data to the  general
 population is somewhat limited since variability due  to
 race or gender have not been systematically addressed.
       Individual  body  surface   area   studies  are
 summarized in Table 6-13 and the recommendations for
 body surface area are summarized in Table 6-14. Table
 6-15 presents the confidence ratings for various aspects  of
 the recommendations for body surface area.  The U.S.
 EPA  (1985)  study is based  on generally  accepted
 measurements that enjoy widespread usage, summarizes
 and compares previous reports in the literature, provides
 statistical distributions for adults, and provides data for
 total  body surface  area and body parts by gender for
 adults and children. However, the results are based on
 401 selected measurements from the original 1,114  made
 by Boyd (1935). More than half of the measurements are
 from children. Therefore, these estimates may be subject
 to selection bias and  may not be representative of the
 general population nor specific ethnic groups. Phillips et
 al. (1993) analyses are based  on direct measurement data
 that provide  distributions of body surface area to calculate
 LADD. The results are consistent with previous efforts  to
 estimate body surface area.  Analyses are based on 401
 measurements  selected  from  the   original   1,114
 measurements made by Boyd (1935) and data were not
 analyzed for specific body parts. The study by Murray
 and Burmaster (1992) provides frequency distributions for
 body surface area for men  and women  and  produces
 results that are similar to those obtained by the U.S. EPA
 (1985), but  do not provide data for body parts nor can
 results be applied to children.
      For most dermal exposure scenarios concerning
 adults, it is  recommended that the body surface  areas
 presented in Table 6-4 be used after determining which
 body parts  will be exposed.  Table 6-4  was selected
because these data are straightforward determinations for
most  scenarios.    However,  for  others,  additional
considerations may need to be addressed. For example,
(1) the type of clothing worn could have a significant
effect on the surface  area  exposed,  and (2)  climatic
conditions will also affect the type of clothing worn and,
thus, the skin surface area exposed.
       Frequency, event, and exposure duration for water
activities and soil contact  are  presented  in  Activity
Patterns, Volume III, Chapter 15 of this report. For each
parameter, recommended values were derived for average
and upper percentile values. Each of these considerations
are also  discussed in more detail in U.S. EPA (1992b).
Data in Tables 6-2 and 6-3 can be used when surface area
distributions  are  preferred.  A range  of recommended
values for estimates of the skin surface area of children
may be taken from Tables 6-6 and 6-7 using the 50th and
95th percentile  values for age(s)  of concern.   The
recommended 50th and 95th percentile values for adult
skin surface  area provided in U.S.  EPA (1992b) are
presented in Table 6-16.

6.4.2.  Soil Adherence to Skin
       Table 6-17 summarizes the relevant and key studies
addressing soil adherence to skin.  Both Lepow et al.
(1975) and  Roels et  al.  (1980)  monitored  typical
exposures in children. They attempted to estimate typical
exposure by recovery of accumulated soil from hands at
specific  time intervals.  The efficiency of their sample
collection methods is not known and may be subject to
error.   Only children  were studied which  may limit
generalizing these results to adults. Later studies (Que
Hee et al., 1985  and Driver et  al., 1989) attempted to
characterize both soil properties and sample collection
efficiency to estimate adherence of soil to skin. However,
the experimental conditions used to expose skin to  soil
may not reflect typical dermal exposure situations. This
provides useful information about the influence of soil
characteristics on skin adherence, but the intimate contact
of  skin   with  soil  required  under  the  controlled
experimental conditions in the studies by Driver et al.
(1989) and Que Hee et al. (1985) may have exaggerated
the amount of adherence over what typically occurs.
      More recently, Kissel et al. (1996a;  1996b) have
related dermal adherence to soil characteristics and to
specific activities. In all cases, experimental design and
measurement   methods   are   straightforward   and
reproducible, but application of results is limited. Both
controlled experiments and field studies  are based on a
Page
6-8
                  Exposure Factors Handbook
                                    Augustl997

-------
Volume I - General Factors
Chapter 6 - Dermal
limited number of measurements. Specific situations have
been  selected   to  assess  soil  adherence  to  skin.
Consequently, variation due to individuals, protective
clothing, temporal, or seasonal factors remain to be
studied in more detail.  Therefore, caution is required in
interpretation and application of these results for exposure
assessments.
      These studies are  based on  limited  data, but
suggest:

      • Soil properties influence adherence. Adherence
        increases with moisture content, decreases with
        particle size, but is relatively unaffected by clay
        or organic carbon content.

      • Adherence  levels  vary  considerably  across
        different parts of the body. The highest levels
        were found on common contact points such as
        hands, knees, and elbows; the least was detected
        on the face.

      • Adherence levels vary with activity. In general,
        the highest levels of soil adherence were seen in
        outdoor workers such as farmers and irrigation
        system   installers,   followed  by   outdoor
        recreation, and gardening activities. Very high
        adherence  levels  were  seen  in  individuals
        contacting wet soils such as might occur during
        wading  or  other  shore   area   recreational
        activities.

      In consideration, of these general observations and
the recent data from Kissel et al. (1996a, 1996b), changes
are needed from past EPA recommendations which used
one adherence value to represent all soils, body parts, and
activities. One approach would be to select the activity
from  Table 6-11 which best represents the exposure
scenario of concern and use the corresponding adherence
value from Table 6-12. Although this approach represents
an improvement, it still has shortcomings. For example,
it is difficult to  decide which activity in Table 6-12 is
most  representative of  a  typical  residential setting
involving a variety of activities.  It may  be useful to
combine these  activities into general  classes of low,
moderate, and high contact.  In the future, it may be
possible  to combine  activity-specific  soil adherence
estimates with survey-specific soil adherence estimates
with  survey-derived data  on activity  frequency  and
duration to develop overall average  soil contact rates.
EPA is sponsoring research to develop such an approach.
As  this   information   becomes   availble,  updated
recommendations will be issued.
      Table 6-12 provides the best estimates available on
activity-specific adherence  values, but are based on
limited  data.  Therefore, they have a high degree of
uncertainty such that considerable judgment must be used
when selecting them for an assessment. The confidence
ratings  for various aspects of this  recommendation are
summarized in Table 6-18. Insufficient data are available
to develop a distribution or a probability function for soil
loadings.
      Past EPA guidance has recommended assuming
that soil exposure  occurs primarily to exposed body
surfaces and used typical clothing scenarios to  derive
estimates  of exposed   skin  area.    The  approach
recommended  above for  estimating soil adherence
addresses this issue in a different manner.  This change
was motivated by two developments.  First, increased
acceptance that soil and dust particles can get under
clothing and be deposited on skin. Second, recent studies
of soil adherence have measured soil on entire body parts
(whether or  not  they were  covered  by clothing)  and
averaged the amount of soil adhering to skin over the  area
of entire body part. The soil adherence levels resulting
from these new studies must be combined with the surface
area of the entire body part (not merely unclothed surface
area) to estimate the amount of contaminant on skin. An
important caveat, however, is that this approach assumes
that clothing in the exposure scenario of interest matches
the clothing in the studies used to derive these adherence
levels such that the same degree of protection provided by
clothing can be assumed in both cases.  If clothing differs
significantly  between the studies reported here and the
exposure  scenarios  under investigation,  considerable
judgment is needed to adjust either the adherence level or
surface  area assumption.
      The dermal adherence  value represents the amount
of soil on the  skin at the time of measurement. Assuming
that the amount  measured  on the skin represents its
accumulation between washings and that people wash at
least  once per day,  these  adherence Values can be
interpreted as daily contact rates  (U.S. EPA, 1992b).
However, this is not recommended because  the residence
time of soils  on skin has not been studied.  Instead, it is
recommended that these adherence  values be interpreted
on an event basis (U.S. EPA, 1992b).
Exposure Factors Handbook
August 1997	
                                              Page
                                                6-9

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                                                                         Volume I - General Factors
                                                                                  Chapter 6 - Dermal
6.5.   REFERENCES FOR CHAPTER 6

American Industrial Health Council (AIHC). (1994)
      Exposure factors sourcebook. Washington, DC:
      AIHC.
Boyd, E. (1935) The growth of the surface area of the
      human body. Minneapolis, Minnesota:
      University of Minnesota Press.
Brainard, J.B.; Burmaster, D.E. (1992) Bivariate
      distributions for height and weight, men and
      women in the United States. Risk Anal.
      12(2):267-275.
Brorby, G.; Finley B. (1993) Standard probability
      density functions for routine use in
      environmental  health risk assessment. Presented
      at the Society of Risk Analysis Annual Meeting,
      December 1993, Savannah, GA.
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.
Costeff, H. (1966) A simple empirical formula for
      calculating approximate surface area in children.
      Arch. Dis. Childh. 41:681-683.
Driver, J.H.; Konz, J.J.; Whitmyre, O.K. (1989) Soil
      adherence to human skin.  Bull. Environ.
      Contam. Toxicol. 43:814-820.
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.
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.
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.
Lepow, M.L.; Bruckman, L.; Gillette, M.; Markowitz,
    S.; Rubino, R.; Kapish, J.  (1975)  Investigations
    into sources of lead in the environment of urban
    children. Environ. Res. 10:415-426.
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.
Palisade. (1992) @Risk users guide. Palisade
    Corporation, Newfield, NY.
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.
Que Hee, S.S.; Peace, B.; Clark, C.S.; Boyle, J.R.;
    Bornschein, R.L.; Hammond, P.B. (1985)
    Evolution of efficient methods to sample lead
    sources, such as house dust and hand dust, in the
    homes of children.  Environ. Res. 38: 77-95.
Rochon, J.; Kalsbeek, W.D. (1983)  Variance
    estimation from multi-stage sample survey data:
    the jackknife repeated replicate approach.
    Presented at 1983 SAS Users Group Conference,
    New Orleans, Louisiania, January  1983.
Roels, H.A.; Buchet, J.P.; Lauwenys, R.R.; Branx, P.;
    Claeys-Thoreau, F.; Lafontaine, A.; Verduyn, G.
    (1980) Exposure to lead  by oral and pulmonary
    routes of children living in the vicinity of a primary
    lead smelter. Environ. Res. 22:81-94.
Sedman, R.M. (1989)  The development of applied
    action levels for soil contact: a scenario for the
    exposure of humans to soil in a residential setting.
    Environ. Health Perspect. 79:291-313.
Page
6-10
                  Exposure Factors Handbook
                 	August 1997

-------
Volume I - General Factors
Chapter 6 - Dermal
Sendroy, J.; Cecchini, L.P. (1954) Determination of
      human body surface area from height and weight.
      J. Appl. Physiol. 7(1):3-12.
Thompson, K.M.; Burmaster, D.E. (1991) Parametric
      distributions for soil ingestion by children. Risk .
      Anal.  ll(2):339-342.
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. (1989) Exposure factors handbook.
      Washington, DC: Office of Research and
      Development, Office of Health and
      Environmental Assessment. EPA/600/18-
      89/043.
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.
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.
Versar, Inc.  (1991) Analysis of the impact of exposure
    assumptions on risk assessment of chemicals in the
    environment, phase II: uncertainty analyses of
    existing  exposure assessment methods. Draft
    Report.  Prepared for Exposure Assessment Task
    Group, Chemical Manufacturers Association,
    Washington,  DC.
Yang, J.J.; Roy, T.A.; Krueger, A.J.; Neil, W.;
    Mackerer, C.R.  (1989) In vitro and in vivo
    percutaneous absorption of benzo[a]pyrene from
    petroleum crude-fortified soil in the rat. Bull.
    Environ. Contam. Toxicol. 43: 207-214.
Exposure Factors Handbook
August 1997	 '
                                           Page
                                            6-11

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Volume 1 - General Factors
       Chapter 6 - Dermal





Exposure ^^
^***«^
**«i_ * * ^s"~






Potential
Dose








Applied »
	 ^- Dose ^s.
^^
^-


Sk



Internal
Dose
^*
Metabolism
in
Biologically
Effective
Dose

\
Organ








^
P**" Effect









Uptake
Figure 6-1. Schematic of Dose and Exposure: Dermal Route
Source: U.S. EPA, 1992a.

Table 6-1. Summary of Equation Parameters for Calculating Adult Body Surface Area
Equation for surface areas (m2)
Body Part
Head
Female
Male
Trunk
Female
Male
Upper Extremities
Female
Male
Arms
Female
Male
Upper Arms
Mole
Forearms
Male
Hands
Female
Mole
Lower Extremities'1
Legs
Thighs
Lower legs
Feet
8 SA =a0 Wal Ha2
N

57
32

57
32

57
48

13
32

6

6

12b
32
105
45
45
45
45

BO

0.0256
0.0492

0.188
0.0240

0.0288
0.00329

0.00223
0.00111

8.70

0.326

0.0131
0.0257
0.00286
0.00240
0.00352
0.000276
0.000618 ,

Wal H112

0.124 0.189
0.339 -0.0950

0.647 -0.304
0.808 -0.0131

0.341 0.175
0.466 0.524

0.201 0.748
0.616 0.561

0.741 -1.40

0.858 -0.895

0.412 0.0274
0.573 -0.218
0.458 0.696
0.542 0.626
0.629 0.379
0.416 0.973
0.372 0.725

p

0.01
0.01

R2

0.302
0.222

0.001 0.877
0.001 0.894


0.001 0.526
0.001 0.821

0.01

0.731
0.001 0.892

0.25

0.05

0.1

0.576

0.897

0.447
0.001 0.575
0.001 0.802
0.001 0.780
0.001 0.739
0.001 0.727
0.001 0.651


S.E.

• 0.00678
0.0202

0.00567
. 0.0118

0.00833
0.0101

0.00996
0.0177

0.0387

0.0207

0.0172
0.0187
0.00633
' 0.0130
0.0149
0.0149
0.0147

W - Weight in kilograms; H = Height in centimeters; P = Level of significance; R2 = Coefficient of determination;
S A ~ Surface Area; S.E. = Standard error; N = Number of observations
b One observation for a female whose body weight exceeded the 95 percentile was not used.
c Although two separate regressions were marginally indicated by the F test, pooling was done for consistency with individual components
of lower extremities.
Source: U.S. EPA. 1985.













Page
6-12
Exposure Factors Handbook





August 199?

-------
Volume I - General Factors
Chapter 6 - Dermal
Table 6-2. Surface Area of Adult Males in Square Meters
Percentile ;
Body Dart 5
Total 1.66
Head 0.119
Trunkb 6.591
Upper extremities 0.321
Arms 0.241
Forearms 0.106
Hands 0.085
Lower extremities 0.653
Legs 0.539
Thighs 0.318
Lower legs 0.218
Feet 0.114
10
1.72
0.121
0.622
0.332
0.252
0.111
0.088
0.676
0.561
0.331
0.226
0.118
15 25
1.76 1.82
0.123 0.124
0.643 0.674
0.340 0.350
0.259 0.270
0.115 0.121
0.090 0.093
0.692 0.715
0.576 0.597
0.341 0.354
0.232 0.240
0.120 0.124
50
1.94
0.130
0.739
0.372
0.291
0.131
0.099
0.761
0.640
0.382
0.256
0.131
75
2.07
0.135
0.807
0.395
0.314C
0.144C
0.105
0.810
0.686°
0.41 lc
0.272
0.138
85
2.14
0.138
0.851
0.408
0.328C
0.151C
0.109
0.838
0.714°
0.429°
0.282
0.142
90
- 2.20
0.140
0.883
0.418
0.339°
0.157°
0.112
0.858
0.734°
0.443°
0.288
0.145
95
2.28
0.143
0.935°
0.432°
0.354°
0.166°
0.117
0.888°
0.762°
0.463°
0.299
0.149
S.E.a
0.00374
0.0202
0.0118
0.00101
0.00387
0.0207
0.0187
0.00633
0.0130
0.0149
0.0149
0.0147
a Standard error for the 5-95 percentile of each body part.
b Trunk includes neck.







'
c Percentile estimates exceed the maximum measured values upon which the equations are based.
Source: U.S. EPA. 1985.








Table 6-3. Surface Area of Adult Females in Square Meters
Percentile
Body part
Total
Head
Trunk"
Upper extremities
Arms
Hands
Lower extremities
Legs
Thighs
Lower legs
Feet
5
1.45
0.106
0.490
0.260
0.210
0.0730
0.564
0.460
0.271
0.186
0.100
10
1.49
0.107
0.507
0.265
0.214
0.0746
0.582
0.477
0.281
0.192
0.103
15
1.53
0.108
0.518
0.269
0.217
0.0757
0.595
0.488
0.289
0,197
0.105
25
1.58
0.109
0.538
0.274
0.221
0.0777
0.615
0.507
0.300
0.204
0.108
50
1.69°
0.111
0.579
0.287
0.230
0.0817
0.657
0.546
0.326
0.218
0.114
75
1.82
0.113
0.636
0.301
0.238°
0.0868°
0.704
0.592
0.357
0.233
0.121
85
1.91
0.114
0.677
0.311
0.243°
0.0903°
0.736
0.623
0.379
0.243
0.126
90
1.9S
0.115
0.704
0.318
0.247°
0.0927°
0.757
0.645
0.394
0.249
0.129
95
2.09
0.117
0.752
0.329
0.253°
0.0966°
0.796
0.683°
0.421°
0.261
0.134
S.E.a
0.00374
0.00678
0.00567
0.00833
0.00996
0.0172
0.00633
0.0130
0.0149
0.0149
0.0147
a Standard error for the 5-95 percentile of each body part.
b Trunk includes neck. ;
° Percentile estimates exceed the maximum measured values upon which the equations are based.
Source: U.S. EPA,
1985.









Exposure Factors Handbook
August 1997    	
Page
 6-13

-------
                                                        Volume I - General Factors
                                                               Chapter 6 - Dermal
Table 6-4. Surface Area by Body Part for Adults (m2)
Men
Body part

Head
Trunk
(Incl. Neck)
Upper extremities
Arms
Upper arms
Forearms
Hands
Lower extremities
Legs
Thighs
Lower legs
Feet
TOTAL

N"
32
32

48
32
6
6
32
48
32
32
32
32


Mean
0.118
0.569

0.319
0.228
0.143
0.114
0.084
0.636
0.505
0.198
0.207
0.112
1.94C

(sd)b
(0.0160)
(0.104)

(0.0461)
(0.0374)
(0.0143)
(0.0127)
(0.0127)
(0.0994)
(0.0885)
(0.1470)
(0.0379)
(0.0177)
(0.00374)d

Min.
0.090
0.306

0.169
0.109
0.122
0.0945 -
0.0596 -
0.283
0.221
0.128
0.093
0.0611 -
1.66

Max.
0.161
0.893

0.429
0.292
0.156
0.136
0.113
0.868
0.656
0.403
0.296
0.156
2.28°

N
57
57

57
13
-
-
12
57
13
13
13
13


Mean
0.110
0.542

0.276
0.210
-
-
0.0746
0.626
0.488
0.258
0.194
0.0975
1.69C
Women

(sd)
(0.00625)
(0.0712)

(0.0241)
(0.0129)
-
-
(0.00510)
(0.0675)
(0.0515)
(0.0333)
(0.0240)
(0.00903)
(0.00374)d

Min.
0.0953
0.437

0.215
0.193
-
-
0.0639
0.492
0.423
0.258
0.165
0.0834
1.45

Max.
0.127
0.867

0.333
0.235
-
-
0.0824
0.809
0.585
0.360
0.229
0.115
2.09e
a number of observations.
b standard deviation.
c median (see Table 6-2).
d standard error.
c percentiles (5th -

95th).


















Source: Adapted from U.S. EPA, 1985.
Table 6-5. Percentage of Total Body Surface Area by Part for Adults
Men
Body part
Head
Trunk
Upper extremities
Arms
Upper arms
Forearms
Hands
Lower extremities
Legs
Thighs
Lower legs
Feet
Na
32
32
48
32
6
6
32
48
32
32
32
32
Mean
7.8
35.9
18.8
14.1
7.4
5.9
5.2
37.5
31.2
18.4
12.8
7.0
(s.d.)b
(1.0)
(2.1)
(1.1)
(0.9)
(0.5)
(0.3)
(0.5)
(1.9)
(1.6)
(1.2)
(1.0)
(0.5)
Min.
6.1
30.5
16.4
12.5
6.7
5.4
4.6
33.3
26.1
15.2
11.0
6.0
Max.
10.6
41.4
21.0
15.5
8.1
6.3
7.0
41.2
33.4
20.2
15.8
7.9
N
57
57
57
13
- -
-
12
57
13
13
13
13
Mean
7.1
34.8
17.9
14.0
-
-
5.1
40.3
32.4
19.5
12.8
6.5
Women
(s.d.)
(0.6)
(1-9)
(0.9)
(0.6)
-
-
(0.3)
(1.6)
(1.6)
(1.1)
(1.0)
(0.3)
Min.
5.6
32.8
15.6
12.4
-
-
4.4
36.0
29.8
18.0
11.4
6.0
Max.
8.1
41.7
19.9
14.8
-
-
5.4
43.2
35.3
21.7
14.9
7.0
" Number of observations.
b Standard deviation.

Source: Adapted from U.S

EPA, 1985.
















Page
6-14
 Exposure Factors Handbook
	August 1997

-------
 Volume I - General Factors
  Chapter 6 - Dermal
Table 6-6. Total Body Surface Area of Male Children in Square Metersa
1-
Age (yr)b
2<3
3<4
4<5
5<6
6<7
7<8
8<9
9<10
10<11
11<12
12<13
13<14
14<15
15<16
16<17
17<18
3<6
6<9
9<12
12<15
15<18

5
0.527
0.585
0.633
0.692
0.757
0.794
0.836
0.932
1.01
1.00
1.11
1.20
1.33
1.45
1.55 '
1.54
0.616
0.787
0.972
1.19
1.50

10
0.544
6.606
0.658
0.721
0.788
0.832
0.897
0.966
1.04
1.06
1.13
1.24
1.39
1.49
1.59
1.56
0.636
0.814
1.00
1.24
1.55

15
0.552
0.620
0.673
0.732
0.809
0.848
0.914
0.988
1.06
1.12
1.20
1.27
1.45
1.52
1.61
1.62
0.649
0.834
1.02
1.27
1.59 '

25
0.569
0.636
0.689
0.746
0.821
0.877
0.932
.00
.10
.16
.25
.30
.51
.60
.66
.69
0.673
0.866
1.07
1.32
1.65
Percentile
50
0.603
0.664
0.731
0.793
0.866
0.936
1.00
1.07
1.18
1.23
1.34
1.47
1.61
1.70
1.76
1.80
0.728
0.931
1.16
1.49
1.75

75
0.629
0.700
0.771
0.840
0.915
0.993
1.06
1.13
1.28
1.40
1.47
1.62
1.73
1.79
1.87
1.91
0.785
1.01
1.28
1.64
1.86
* Lack of height measurements for children <2 years in NHANES II precluded calculation of surface areas for this

85
0.643
0.719
0,796
0.864
0.957
.01
.12
.16
.35
.47
.52
.67
.78
.84
.98
.96
0817
.05
.36
.73
.94
age group.

90
0.661
0.729
0.809
0.895
1.01
1.06
1.17
1.25
1.40
1.53
1.62
1.75
1.84
1.90
2.03
2.03
0.842
1.09
1.42
1.77
•2.01 '


95
0.682
0.764
0.845
0.918
.06
.11
.24
.29
.48
.60
.76
1.81
1.91
2.02
2.16
2.09
0.876
1.14
1.52
1.85
2.11

Estimated values calculated using NHANES II data.
Source: U.S
EPA. 1985.








Table 6-7. Total Body Surface Area of Female Children in Square Meters"
Percentile
Age (yr)b
2<3
3<4
4<5
5<6
6<7
7<8
8<9
9<10
10<11
11 <12
12<13
13<14
14<15
15<16
16<17
17<18
3<6
6<9
9<12
12<15
15<18 '
5
0.516
0.555
0.627
0.675
0.723
0.792
0.863
0.897
0.981
1.06
1.13
1.21
1.31
1.38
1.40
1.42
0.585
0.754
0.957
1.21
1.40
10
0.532
0.570
0.639
0.700
0.748
0.808
0.888
0.948
1.01
1.09
1.19
1.28
1.34
1.49
1.46
1.49
0.610
0.790
0.990
1.27 ..
1.44
15
0.544
0.589
0.649
0.714
0.770
0.819
0.913
0.969
1.05
.12
.24
.32
.39
.43
.48
.51
0.630
0.804
1.03
1.30
1.47
25 50 75
0.557 0.579 0.610
0.607 0.649 0.688
0.666 0.706 0.758
0.735 0.779 0.830
0.791 0.843 0.914
0.854 0.917 0.977
0.932
1.01
1.10
1.16
1.27
1.38
1.45
1.47
1.53
1.56
.00 1.05
.06 .14
.17 .29
.30 .40
.40 .51
.48 .59
.55 .66
.57 .67
.60 .69
.63 .73
0.654 0.711 0.770
0.845 0.919 1.00
1.06
1.37
1.51
.16 1.31
.48 1.61
.60 1.70
85
0.623
0.707
0.777
b.870
0.961
' .02
.08
.22
.34
.50
.62
.67
.74
- .72
1.79
1.80
0.808
1.04
1.38
1.68
1.76 '
90
0.637
0.721
0.794
0.902
0.989
1.06
1.11
1.31
1.37
1.56
1.64
1.75
1.76
1.76
1.84
1.84
0.831
1.07
1.43
1.74
1.82
95
0.653
0.737
0.820
0.952
1.03
1.13
1.18
1.41
1.43
1.62
1.70
1.86
1.88
1.83
1.91
1.94
0.879
1.13
1.56
1.82
1.92
" Lack of height measurements for children <2 years in NHANES n precluded calculation of surface areas for this age group.
Estimated values calculated using NHANES II data.
Source: U.S. EPA.
1985.







 Exposure Factors Handbook
^August 1997	
Page
 6-15

-------
                                                       Volume I - General Factors
                                                              Chapter 6 - Dermal












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Page
6-16
Exposure Factors Handbook
  	August 1997

-------
 Volume I - General Factors
 Chapter 6 - Dermal

Age fvrs.1
0-2
2.1 - 17.9
s 18
All aees

Mean
0.0641
0.0423
0.0284
0.0489
Table 6-9.
Range
Min-Max
0.0421-0.1142
0.0268-0.0670
0.0200-0.0351
0.0200-0.1 142
a Standard deviation.
b Standard error of the mean.
Source: Phillies et al.. 1993.
Descriptive Statistics for Surface Area/Body Weight (SA/BW) Ratios (nvVkg)
SD"
0.0114
0.0076
0.0028
0.0187

SEb
7.84e-4
1.05e-3
7.68e-6
9.33e-4

5
0.0470
0.0291
0.0238
0.0253

10
0.0507
0.0328
0.0244
0.0272

25
0.0563
0.0376
0.0270
00299

Percentiles
50
0.0617
0.0422
0.0286
- 0.0495

75
0.0719
0.0454
0.0302
0.0631

90
0.0784
0.0501
0.0316
0.0740

95
0.0846
0.0594
0.0329
0.0788

Table 6-1 0. Statistical Results for Total Body Surface Area Distributions (m2)


Mean
Median
Mode
Standard Deviation
Skewness
Kurtosis


Mean
Median
Mode
Standard Deviation
Skewness
Kurtosis
Source: Murray and Burmaste

U.S. EPA
1.97
1.96
1.96
0.19
0.27
3.08

U.S. EPA
1.73
1.69
1.68
0.21
0.92
4.30
tr, 1992

Bovd
1.95
1.94
1.91
0.18
0.26
3.06

Bovd
1.71
1.68
1.62
0.20
0.88
4.21

Men

1.94
1.94
1.90
0.17
0.23
3.02
Women

1.69
1.67
1.60
0.18
0.77
4.01



1.89
1.89
1.90
0.16
0.04
292

Costeff
1.71
1.68
1.66
0.21
0.69
3.52

Exposure Factors Handbook
August 1997	
Page
 6-17

-------
                                                                   Volume I - General Factors
                                                                           Chapter 6 - Dermal
             0.25
             0.25 r
                            Infant SA/BW Ratios:  Lognonm(O.OB41,0.0114)
                                                             Expected Value*
                                                               6.410E-02
                                                                 13
                                                                         is
                            All Ages SA/BW Ratios:  Normal(0.0489.0.0187)
                                                               Expected Value«
                                                                 4.890E-02
                                                                           14
                             Adult SA/BW Ratios: NormaHO.0284,0.0028)
                                                             Expected Value •
                                                                2.840E-02
                                                                                 17
                                                                             42
               Figure 6-2.  SA/BW Distributions for Infants, Adults, and All Ages Combined
  Source: Phillips et al., 1993.
Page
6-18
Exposure Factors Handbook
                August 1996

-------
 Volume I - General Factors
 Chapter 6 - Dermal
           .08
          .00
              1.00
          .00
             1.00
                             Surface Area: Men
                              Frequency Distribution
1.50
2.00
2.50
                              Area in m2, n=5,000, LHS


                          Surface Area: Women
                              Frequency Distribution
                          1.50
            2.00
                        2.50
                                          424
                                                                   318
                                                                        (D

                                                                        O
3.00
                        3.00
                              Area in m2. n=5.000. LHS
             Figure 6-3. Frequency Distributions for the Surface Area of Men and Women
  Source: Murray and Burmaster, 1992.
 Exposure Factors Handbook
^August 1996	
                                                  Page
                                                   6-19

-------
                                                       Volume I - General Factors
                                                              Chapter 6 - Dermal
Table 6-11. Summary of Field Studies
Activity
ndoor
'ae Kwon Do


Greenhouse Workers

Indoor Kids No. 1

Indoor Kids No. 2

Month

Feb.


Mar.

Jan.

Feb.

Event"
(hrs)

1.5


5.25

2

2

Nb

7


2

4

6

Indoor Totals
Outdoor
Jaycare Kids No. la


Daycare Kids No. Ib


Daycare Kids No.2c
Daycare Kids No. 3

Soccer No. 1

Soccer No. 2

Soccer No. 3

Groundskeepers No. 1

Groundskeepers No. 2

Groundskeepers No. 3

Groundskeepers No. 4
Groundskeepers No. 5
Landscape/Rockery

Irrigattonlnstallers

Gardeners No. 1



Aug.


Aug.


Sept.
Nov.

Nov.

Mar.

Nov.

Mar.

Mar.

Mar.

Aug.
Aug.
June

Oct.

Aug.



3.5


4


8
8

0.67

1.5

1.5

1.5

4.25

8

4.25
8
9

3

4



6


6


5
4

8

8

7

2

5

7

7
8
4

6

8


M

6


1

3

4

19

5


5


4
3

8

0

0

1

3

5

4
6
3

6

1


F

1


1

1

2

Age Conditions Clothing

8-42 Carpeted floor All in longsleeve-long pants martial
arts uniform, sleeves rolled back,
barefoot
37-39 Plant watering.spraying, soil Long pants, elbow length short sleeve
blending, sterilization shirt, no gloves
6- 1 3 Playing on carpeted floor 3 of 4 short pants, 2 of 4 short sleeves,
socks, no shoes
3-13 Playing on carpeted floor 5of 6 long pants, 5 of 6 long sleeves,
socks, no shoes
14 5

1


1


1
1

0

8

7

1

2

2

3
2
1

0

7



1-6.5 Indoors: linoleum surface; 4 of 6 in long pants, 4 of 6 short
outdoors: grass, bare earth, barked sleeves, shoes
area
1-6.5 Indoors: linoleum surface; 4 of 6 in long pants, 4 of 6 short
outdoors: grass, bare earth, barked sleeves, no shoes
area
1 -4 Indoors, low napped carpeting, 4 of 5 long pants, 3of 5 long sleeves,
linoleum surfaces all barefoot for part of the day
1-4.5 Indoors: linoleum surface, outside: All long pants, 3 of 4 long sleeves,
grass, bare earth, barked area socks and shoes
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
24-34 All-weather field (sand-ground All in short sleeve shirts, shorts, knee
tires) socks, shin guards
24-34 All-weather field (sand-ground All in short sleeve shirts, shorts, knee
tires) socks, shin guards
29-52 Campus grounds, urban All in long pants, intermittent use of
horticulture center, arboretum gloves
22-37 Campus grounds.urban All in long pants, intermittent use of
horticulture center, arboretum gloves
30-62 Campus grounds,urban All in long pants, intermittent use of
horticulture center, arboretum gloves
22-38 Campus grounds.urban 5 of 7 in short sleeve shirts,
horticulture center, arboretum intermittent use of gloves
19-64 Campus grounds.urban 5 of 8 in short sleeve shirts,
horticulture center, arboretum intermittent use of gloves
27-43 Digging (manual andmechanical), All long pants, 2 long sleeves, all
rock moving socks and boots
23-41 Landscaping.surface restoration All in long pants, 3 of 6 short sleeve or
sleeveless shirts
16-35 Weeding, pruning.digging a trench 6 of 8 long pants, 7 of 8 short sleeves,
1 sleeveless, socks, shoes, intermittent
use of gloves
Page
6-20
Exposure Factors Handbook
              August 1997

-------
  Volume I - General Factors

  Chapter 6 - Dermal


Activity
Gardeners No. 2

Rugby No. 1

Rugby No. 2


Rugby No. 3

Archeologists

Construction Workers

Utility Workers No.l

Utility Workers No.2

Equip. Operators No.l

Equip. Operators No.2

'armers No. 1

Farmers No. 2

Reed Gatherers

Kids-in-mud No. 1

Kids-in-mud No. 2


Month
Aug.

Mar.

July


Sept.

July

Sept.

July

Aug.

Aug.

Aug.

May

July

Aug.

Sept.

Sept.


(hrs)
4

1.75

2


2.75

11.5

8

9.5

9.5

8

8

2

2

2 '

0.17

0.33


Nb
7

8

8


7

7

8

5

6

4

4

4

6

4

6

6

Outdoor Totals

i Number of subject







M
2

8

8


7

3

8

5

6

4

4

2

4

0

5

5

7S^



F
5

0

0


0

4

0

0

0

0

0

2

2

4

1

1


Age
26-52

20-22

23-33


24-30

16-35

21-30

24-45

23-44

21-54

21-54

39-44

18-43

42-67

9-14

9-14




Weeding, pruning, digging a
trench, picking fruit, cleaning
Mixed grass-barewet field

Grass field (80% oftime) and all-
weather field (mix of gravel, sand,
and clay) (20% oftime)
Compacted mixedgrass and bare
earth field
Digging withtrowel, screening dirt,
sorting
Mixed bare earth and concrete
surfaces, dust and debris
Cleaning, fixing mains, excavation
(backhoe and shovel)
Cleaning, fixing mains, excavation
(backhoe and shovel)
Earth scraping withheavy
machinery, dusty conditions
Earth scraping withheavy
machinery, dusty conditions
Manual weeding,mechanical
cultivation
Manual weeding.mechanical
cultivation
Tidal flats
,
ILake shoreline

J.-ake shoreline



	 Clothing 	
3 of 7 long pants, 5of 7 short sleeves,
1 sleeveless, socks, shoes, no gloves
All in short sleeve shirts, shorts,
variable sock lengths
All in shorts, 7 of 8 in short sleeve
shirts, 6 of 8 in low socks

All short pants, 7 of 8 short or rolled
up sleeves, socks, shoes
6 of 7 short pants.all short sleeves, 3
no shoes or socks, 2 sandals
5 of 8 pants,? of 8 short sleeves, all
socks and shoes
All long pants,short sleeves, socks,
boots, gloves sometimes
All long pants, 5 of 6 short sleeves,
socks, boots, gloves sometimes
All long pants, 3 of 4 short sleeves,
socks, boots, 2 of 4 gloves
All long pants, 3 of 4 short sleeves,
socks, boots, 1 gloves
All in long pants, heavy shoes, short
sleeve shirts, no gloves
2 of 6 short, 4 of 61ong pants, 1 of 6
long sleeve shirt, no gloves
2 of 4 shortsleeve shirts/knee length
pants, all wore shoes
All in short sleeve T-shirts, shorts,
barefoot
All in short sleeveT-shirts, shorts,
barefoot
725 5
-------
^T Chapter 6 - Dermal

Table 6-12. Geometric Mean and Geometric Standard Deviations of
Soil Adherence by Activity and Body Region 	 : 	 	 	
Post-activity Dermal Soil Loadings (mg/cm2)























Activity Na
ndoor
Fae Kwon Do 7
3reenhouseWorkers 2
Indoor Kids No. 1 4
Indoor Kids No. 2 6
Daycare Kids No. la 6
Daycare Kids No. Ib 6
Daycare Kids No. 2 5
Daycare Kids No. 3 4
Outdoor
Soccer No. 1 8
Soccer No. 2 8
Soccer No. 3 7
Groundskeepers No. 1 , 2
Groundskeepers No. 2 5
Groundskeepers No. 3 7
Groundskeepers No. 4 7
Groundskeepers No. 5 8
Landscape/Rockery 4
Irrigation Installers 6
Gardeners No. 1 8
Hands

0.0063
1.9
0.043
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
0.035
3.9
0.019
1.5
0.15
0.098
2.1
0.030
2.3
0.045
1.9
0.032
1.7
0.072
2.1
0.19
1.6
0.20
1.9
Arms

0.0019
- 4.1
0,0064
0.0042 .
, 1.9
0.0041
2.0
0.026
1.9
0.031 .
1.8
0.023V
1.4
0.012

0.011
2.0
0.0043
2.2
0.0029
2.2
0.005
0.0021
2.6
0.0022 '
1.9
0.014
1.8
0.022
2.8
0.030
2.1
0.018
3.2
0.050
2.1
Legs

0.0020
2.0
0.0015
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
0.014
5.3
0.0081
1.6

0.0010 ,
; i .5
0.0009
• 1.8
0.0008
1.9
0.0010
1.4

0.0054
1.8
0.072
Faces


0.0050







0.012
1.5
0.016
1.5
0.012
1.6
0.0021
0.010
2.0
0.0044
2.6
0.0026
1.6
0.0039
2.1
0.0057
1.9
0.0063
1.3
0.058
1.6
Feet

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




0.018

0.0040
0.018



0.17

Page
6-22

Exposure Factors Handbook
August 1997






-------
  Volume I - General Factors

  Chapter 6 - Dermal
Table 6-12. Geometric Mean and Geometric Standard Deviations of
Soil Adherence by Activity and Body Region (continued) -

Activity
Gardeners No. 2

Rugby No. 1

Rugby No. 2

iugby No. 3

Archeologists

Construction Workers

Utility Workers No. 1

Utility Workers No. 2

Equip. Operators No. 1

Equip. Operators No. 2

Farmers No. 1

'armers No. 2

Reed Gatherers

Kids-in-mud No. 1

Kids-in-mud No. 2

a Number of subjects.
Sources: Kissel et al.. 1996b;

Na
7

8

8

7

7

8

5

6

4

4

4

6

4

6

6


Holmes et
Post-activity Dermal Soil Loadings fmp/cm2'>

0.18
3.4
0.40
1,7
0.14
1.4
0.049
1.7
0.14
1.3
0.24
1.5
0.32
1.7
0.27
2.1
0.26
2.5
0.32
1.6
0.41
1.6
0.47
1.4
0.66
1.8
35
2.3
58
2.3

al., 1996
Arms
0.054
2.9
0.27
1.6
0.11
1.6
0.031
1.3
0.041
1.9
0.098
1.5
0.20
2.7
0.30
1.8
0.089
1.6
0.27
1.4
0.059
'•'3.2
0.13
;...'• 2.2 ' ,
.0.036
2.1
....-." 11
r 6.1
11
3.8

(submitted for publication).
Legs
0.022
2.0
0.36
1.7
0.15
1.6
0.057
1.2
0.028
4.1
. 0.066
1.4




-



0.0058
2.7
0.037
3.9
0.16
9.2
36
2.0
9.5
2.3



0.047 0.26
1,6 ...:;\ - . ;
0.059 . '
2.7 •
0.046
1.4
0.020
1.5
0.050 0.24
1.8 1.4 :
0.029
1.6
0.10
1.5
0.10
1.5
0.10
1.4
0.23
1.7
0.018
1.4
0.041
3.0 ";
0.63
.7.1... .
24
3.6 ' , '
6.7 '
• 12.4

'
Exposure Factors Handbook
August 1997	'
Page
 6-23

-------
                                                      Volume I - General Factors

                                                      	Chapter 6 - Dermal












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Page
 Exposure Factors Handbook
	     August 1997

-------
  Volume I - General Factors

  Chapter 6 - Dermal
                           Table'6-14.  Summary of Recommended Values for Skin Surface Area
      ildren
   Whole body
   Body gaits-
                  "&:   >    ^ *<    '   **'*•    <
         '"<.„''•% ^Tables6-6~and%-7J •• *4'^'
                       Table 6-15. Confidence in Body Surface Area Measurement Recommendations
  	Considerations
   Study Elements
                       Rationale
                                                             Rating
    • 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
 EPA report was peer reviewed before distribution.
 The journals used have wide circulation.
 EPA report available from National Technical Information
 Service.
 Experimental methods are well-described.
 Experiments measured skin area directly.
 Experiments conducted in the U.S.
 Re-analysis of primary data in more detail by two different
 investigators.
 Neither rapidly  changing nor controversial area; estimates
 made in 1935 deemed to be accurate and subsequently
 used by others.                                 J
 Not relevant to exposure factor; parameter not time
 dependent.
 Approach used by other investigators; not challenged in
 other studies.
 Not statistically representative of U.S. population.

 Individual variability due to age, race, or gender not
 studied.
 Objective subject selection and measurement methods
 used; results reproduced by others with different methods.
 Measurement variations are low; adequately described by
 normal statistics.                                  J
1 experiment; two independent re-analyses of this data set.
Consistent results obtained with different analyses; but
from a single set of measurements.
This factor can be directly measured. It is not subject to
dispute. Influence of age, race, or gender have not been
detailed adequately in these studies.
     High

     High

     High
     High
     High
     Low

     Low

     NA

    High

  Medium

    Low

    High

Low/Medium


  Medium
  Medium

    High
Exposure Factors Handbook
August 1997  	
                                                                   Page
                                                                    6-25

-------
                                                                 Volume I - General Factors
                                                                         Chapter 6 - Dermal
                        Table 6-16. Recommendations for Adult Body Surface Area
Bathing and Swimming
Water Contact
     50th
     20,000 cm2 '
 Soil Contact
     50th
     5,000 cm2
95th   - __
23,000 cm2

95th,, >-";
5,800 cm2
Source: U.S. EPA, 1992.

Study
KEY STUDIES
Kissel etal., 1995a
Kisselletal., 1996b
RELEVANT STUDIES
Driver etal., 1989
Lcpowct al., 1975
Que Hee et al., 1985
Roels etal., 1980
Sedman, 1989
Yang et al., 1989
Table 6- 17. Summary of Soil
Size Soil
Fraction Adherence
(^m) (mg/cm2)
<150, 150- Various
200, >250
Various
<150 1.40
<250 0.95
unsieved 0.58
0.5
1.5
0.9-1.5
*
0.9; 0.5
<150 9
Adherence Studies
Population
Surveyed
28 adults
24 children
12 children
89 adults
Adults
Adults
Adults
10 children
1 adult
661 children
Children
Rats
Comments
Data presented for soil loadings by
body part. See Table 6-11.
Data presented by activity and body
part.
Used 5 soil types and 2-3 soil horizons
(top soils and subsoils); placed soil
over entire hand of test subject, excess
removed by shaking the hands.
Dirt from hands collected during play.
Represents only fraction of total
present, some dirt may be trapped in
skin folds.
Assumed exposed area = 20 cm2. Test
subject was 14 years old.
Subjects lived near smelter in
Brussels, Belgium. Mean amount
adhering to soil was 0.159 g.
Used estimate of Roels et al. (1980)
and average surface of hand of an 11
year old; used estimates of Lepow et
al. (1975), Roels et al. (1980), and
Que Hee et al. (1985) to develop
mean of 0.5 mg/cm2.
Rat skin "monolayer" (i.e., minimal
amount of soil covering the skin); in
vitro and in vivo experiments.
Page
6-26
                         Exposure Factors Handbook
                                          August

-------
  Volume I - General Factors

  Chapter 6 - Dermal
                            Table 6-18. 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.                   High

 Articles were published in widely circulated journals.               High

 Reports clearly describe experimental method.                      High

 The goal of the studies was to determine soil adherence to            High
 skin.

 Experiments were conducted in the U.S.                           High

 Experiments were directly measure soil adherence to skin;            High
 exposure and dose of chemicals in soil were measured
 indirectly or estimated from soil contact.

 New studies were presented.                                     High

 Seasonal factors may be important, but have not been             Medium
 studied adequately.                               '

 Skin rinsing technique is a widely employed procedure.             High

 Studies were limited to the State of Washington and may             Low
 not be representative  of other locales.

 Variability in soil adherence is affected by many factors     ,    -    Low
 including soil properties, activity and individual behavior
 patterns.

 The studies attempted to measure soil adherence in                 High
 selected activities and conditions to identify important
 activities and groups.

 The experimental error is low and well controlled, but            Low/High
 application of results to other similar activities may be
 subject to variation.
The experiments were controlled as they were conducted          Medium
by a few laboratories; activity patterns were studied by
only one laboratory.

Results from key study were consistent with earlier               Medium
estimates from relevant studies and assumptions, but are
limited to hand data.

Data are limited, therefore it is difficult to extrapolate               Low
from experiments and field observations to general
conditions.
Exposure Factors Handbook
August 1997	
                                                                    Page
                                                                     6-27

-------

-------
Volume I - General Factors
Appendix 6A
                                 APPENDIX 6A
                    FORMULAE FOR TOTAL BODY SURFACE AREA
Exposure Factors Handbook
August 1997	
Page
6A-1

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-------
Volume I - General Factors
Appendix 6A
                                            APPENDIX 6A

                          FORMULAE FOR TOTAL BODY SURFACE AREA
      Most formulae for estimating surface area (SA), relate height to weight to surface area. The following formula
was proposed by Gehan and George (1970):
                                                 = KW2/3
  (Eqn. 6A-1)
where:
      SA  =   surface area in square meters;
      W  =   weight in kg; and
      K   =   constant.

        While the above equation has been criticized because human bodies have different specific gravities and because
the surface area per unit volume differs for individuals with different body builds, it gives a reasonably good estimate
of surface area.

        A formula published in 1916 that still finds wide acceptance and use  is that of DuBois and DuBois. Their
model can be written:
                          SA = an H  ' W
                                     ai w "2
(Eqn. 6A-2)
where:
      SA  =   surface area in square meters;
      H   =   height in centimeters; and
      W   =   weight in kg.

        The values of ag (0.007182), al (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 a$ = 0.01787, at = 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.
Exposure Factors Handbook
August 1997      	
       Page
       6A-3

-------
                                                                         Volume I - General Factors
                                                                                         Appendix 6A
        Gehan and George (1970) proposed another set of constants for the DuBois and DuBois model. The constants
were based on a total of 401 direct measurements of surface area, height, and weight of all postnatal subjects listed in
Boyd (1935). The methods used to measure these subjects were coating (163 cases), surface integration (222 cases),
and triangulation (16 cases).

        Gehan and George (1970) used a least-squares method to identify the values of the constants. The values of
the constants chosen are those that minimize the sum of the squared percentage errors of the predicted values of surface
area. This approach was used because the importance of an error of 0.1 square meter depends on the surface area of the
individual. Gehan and George (1970) used the 401 observations summarized in Boyd (1935) in the least-squares method.
The following estimates of the constants were obtained: ag = 0.02350, a! = 0.42246, and ^ = 0.51456.  Hence, their
equation for predicting surface area (SA) is:
                                      SA = 0.02350 H0-42246 W°-51456
                                                                                       (Eqn. 6A-3)
or in logarithmic form:
                              In SA= -3.75080 + 0.42246 In H + 0.51456 In W
                                                                                       (Eqn. 6A-4)
where:
     SA  =   surface area in square meters;
     H   =   height in centimeters; and
     W  =   weight in kg.

     This prediction explains more than 99 percent of the variations in surface area among the 401 individuals measured
(Gehan and George, 1970).

        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:
or in logarithmic form:
where:
Sai
Hi
Wi
30, alt  and
                           In (SA); = In ao + a, In H; + ^ In Wt + In e;
                        surface area of the i-th individual (m2);
                        height of the i-th individual (cm);
                        weight of the i-th individual (kg);
                        parameters to be estimated; and
                        a random error term with mean zero and constant variance.
                                                                                             (Eqn. 6A-5)
                                                                                             (Eqn. 6A-6)
Page
6A-4
                                                                  Exposure Factors Handbook
                                                                  	August 1997

-------
Volume I - General Factors
Appendix 6A
      Using the least squares procedure for the 401 observations, the following parameter estimates and their standard
errors were obtained:
The model is then:
or in logarithmic form:
                              =-3.73 (0.18), aj =0.417 (0.054), 83 = 0.517 (0.022)
                                         SA = 0.0239 H°-417 W°-517
                                   In SA = -3.73 + 0.417 In H + 0.517 In W
(Eqn. 6A-7)
(Eqn. 6A-8)
with a standard error about the regression of 0.00374. This model explains more than 99 percent of the total variation
in surface area among the observations, and is identical to two significant figures with the model developed by Gehan
and George (1970).

        When natural logarithms of the measured surface areas are plotted against natural logarithms of the surface
predicted by the equation, the observed surface areas are symmetrically distributed around a line of perfect fit, with only
a few large percentage deviations. Only five subjects differed from the measured value by 25 percent or more.  Because
each of the five subjects weighed less than 13 pounds, the amount of difference was small. Eighteen estimates differed
from measurements by 15 to 24 percent. Of these, 12 weighed less than 15 pounds each, 1 was overweight  (5 feet 7
inches, 172 pounds), 1 was very thin (4 feet 11 inches, 78 pounds), and 4 were of average build.  Since the same observer
measured surface area for these 4 subjects, the possibility of some bias in measured values cannot be discounted (Gehan
and George 1970).

      Gehan and George (1970) also considered separate constants for different age groups: less than 5 years old, 5 years
old to less than 20 years old, and greater than 20 years old. The different values for the constants are presented below:
                      Table 6A-1. Estimated Parameter Values for Different Age Intervals
Age
group
All ages
<5 years old
;> 5 - <20 years old
^ 20 years oldl
Number
of persons
401
229
42
30
ao
0.02350
0.02667
0.03050
0.01545
ai
0.42246
0.38217
0.35129
0.54468
a2
0.51456
0.53937
0.54375
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 a^ a^
and a2 by age interval.
Exposure Factors Handbook
August 1997	
     Page
     6A-5

-------
                                                                         Volume I - General Factors
                                                                                         Appendix 6A
        Haycock et al. (1978) without knowledge of the work by Gehan and George (1970), developed values for the
parameters a^, aj, 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: ag = 0.024265, a! = 0.3964, and a2 = 0.5378.  The result was the following equation for estimating
surface area:
expressed logarithmically as:
                                      SA = 0.024265 H°-3964 Wa5378
                              In SA = In 0.024265 + 0.3964 In H + 0.5378 In W
                      (Eqn. 6A-9)
                     (Eqn. 6A-10)
        The coefficients for this equation agree remarkably with those obtained by Gehan and George (1970) for 401
measurements.

        George et al. (1979) agree that a model more complex than the model of DuBois and DuBois for estimating
surface area is unnecessary. Based on samples of direct measurements by Boyd (1935) and Gehan and George (1970),
and samples of geometric estimates by Haycock et al. (1978), these authors have obtained parameters for the DuBois
and DuBois model that are different than those originally postulated in 1916. The DuBois and DuBois model can be
written logarithmically as:

                                     lnSA = lna0 + a1lnH + a2lnW                         (Eqn. 6A-11)

        The values for ag, a,, and a% obtained by the various authors discussed in this section are presented to follow:

           Table 6A-2.  Summary of Surface Area Parameter Values for the DuBois and DuBois Model
Author
(year)
DuBois and DuBois (1916)
Boyd (1935)
Gehan and George (1970)
Haycock etal. (1978)
Number
of persons
9
231
401
81
ao
0.007184
0.01787
0.02350
0.024265
ai
0.725
0.500
0.42246
0.3964
a2
0.425
0.4838
0.51456
0.5378
        The agreement between the model parameters estimated by Gehan and George (1970) and Haycock et al. (1978)
is remarkable in view of the fact that Haycock et al. (1978) were unaware of the previous work. Haycock et al. (1978)
used an entirely different set of subjects, and used geometric estimates of surface area rather than direct measurements.
Page
6A.-6
 Exposure Factors Handbook
	August 1997

-------
Volume I - General Factors
Appendix 6A
It has been determined that the Gehan and George model is the formula of choice for estimating total surface area of the
body since it is based on the largest number of direct measurements.

Nomograms                      ,                 '

        Sendroy and Cecchini (1954) proposed a graphical method whereby surface area could be read from a diagram
relating height and weight to surface area. However, they do not give an explicit model for calculating surface area. The
graph was developed empirically based on 252 cases, 127 of which were from the 401 direct measurements reported by
Boyd (1935).  In the other 125 cases the surface area was estimated using the linear method of DuBois and DuBois
(1916). Because the Sendroy and Cecchini method is graphical, it is inherently less precise and less accurate than the
formulae of other authors discussed above.
Exposure Factors Handbook
August 1997	
Page
6A-7

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-------
Volume I - General Factors
Chapter 7 - Body Weight Studies
7.    BODY WEIGHT STUDIES
      There are several physiological factors needed to
calculate potential exposures. These include skin surface
area (see Volume I,  Section  6), inhalation rate (see
Volume I, Section 5)  life  expectancy (see Volume I,
Section 8), and body weight. The average daily dose is
typically normalized to the average body weight of the
exposed  population,  If exposure occurs only during
childhood years, the average child body weight during the
exposure  period should be used to estimate risk (U.S.
EPA, 1989).  Conversely, if adult exposures are  being
evaluated, an adult body weight value should be used.
      The purpose of this section is to describe published
studies on body weight for the general U.S. population.
The studies have been classified as either key or relevant
studies, based on the  criteria  described  in Volume I,
Section 1.3.1.  Recommended values are based on the
results of key studies, but relevant studies are also
presented to provide the reader with added perspective on
the current state of knowledge pertaining to body weight.

7.1.  KEY BODY WEIGHT STUDY
      Hamill et al. (1979) - Physical Growth: National
Center for Health Statistics Percentiles - A National
Center for Health Statistics (NCHS) Task Force that
included academic investigators and representatives from
CDC Nutrition Surveillance Program selected, collated,
integrated, and defined appropriate data sets to generate
growth curves for the age interval:   birth to 36 months
developed (Hamill et al., 1979).  The percentile curves
were for assessing the physical growth of children in the
U.S. They are based on accurate measurements made on
large  nationally  representative  samples  of children
(Hamill et al., 1979).  Smoothed percentile curves were
derived for body weight by age  (Hamill et al., 1979).
Curves were developed for boys and for girls.  The data
used to construct the curves were provided by the Pels
Research  Institute, Yellow Springs, Ohio.   These data
were  from  an  ongoing  longitudinal  study  where
anthromopetric   data  from  direct   measurements  are
collected regularly from participants (-1,000) in various
areas of the U.S. The NCHS used advanced statistical
and computer technology to generate the growth curves.
Table 7-1  presents the percentiles of weight by sex and
age.   Figures  7-1  and 7-2 present weight  by age
percentiles for boys and for girls aged birth to 36 months,
respectively. Limitations of this study are that mean body
weight values were not reported and the data are more
Table 7-1. Smoothed Percentiles of Weight (in kg) by Sex and Age:
Statistics from NCHS and Data from Pels Research Institute, Birth to 36 Months
Smoothed" Percentile

Sex and Age
Male
Birth
1 Month
3 Months
6 Months
9 Months
12 Months
18 Months
24 Months
30 Months
36 Months
Female
Birth
1 Month
3 Months
6 Months
9 Months
12 Months
18 Months
24 Months
30 Months
36 Months
5th


2.54
3.16
4.43
6.20
7.52
8.43
9.59
10.54
11.44
12.26

2.36
2.97
4.18
5.79
7.00
7.84
8.92
9.87
10.78
11.60
10th


2.78
3.43
4.78
6.61
7.95
8.84
9.92
10.85
11.80
12.69

2.58
3.22
4.47
6.12
7.34
8.19
9.30
10.26
11.21
12.07
25th


3.00
3.82
5.32
7.20
8.56
9.49
10.67
11.65
12.63
13.58

2.93
3.59
4.88
6.60
7.89
8.81
10.04
11.10
12.11
12.99
50th
Weight in Kilograms

3.27
4.29
5.98
7.85
9.18
10.15
11.47
12.59
13.67
14.69

3.23
3.98
5.40
7.21
8.56
9.53
10.82
11.90 .
12.93
13.93
75th


3.64
4.75
6.56
8.49
9.88
10.91
12.31
13.44
14.51
15.59

3.52
4.36
5.90
7.83
9.24
10.23
11.55
12.74
13.93
15.03
90th


3.82
5.14
7.14
9.10
10.49
11.54
13.05
14.29
15.47
16.66

3.64
4.65
6.39
8.38
9.83
10.87
12.30
13.57
14.81
15.97
95th


4.15
5.38
7.37
9.46
10.93
11.99
13.44
14.70
15.97
17.28

3.81
4.92
6.74
8.73
10.17
11.24
12.76
14.08
15.35
16.54
a Smoothed by cubic-spline approximation.
Source: Hamill etal., 1979.







Exposure Factors Handbook
August 1997	
                                             Page
                                               7-1

-------
    Volume I - General Factors




Chapter 7 - Body Weight Studies

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imill et al., 1979.
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7-2 . August 1996

-------
Volume I - General Factors
Chapter 7 - Body Weight Studies
                                  12   15   18   21  24   27   30   33   36


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

 Source: Hamill etal., 1979
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Exposure Factors Handbook

August 1996
Page

  7-3

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                                                                               Volume I - General Factors
                                                                         Chapter 7 - Body Weight Studies
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
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 of adults, by  age, and their  standard
deviations are presented  in Table  7-2 for men,  women,
and  both sexes combined.   Mean body weights and
standard deviations for children,  ages  6 months to 19
years, are presented in Table 7-3 for boys, girls, and boys
and  girls combined. Percentile distributions of the body
weights of adults by age and race for males are presented
in Table 7-4, and  for females in  Table 7-5. Data for
children by age are presented in Table 7-6 for males, and
for females in Table 7-7.
       Results shown in Tables 7-4 and 7-5 indicate that
the mean weight for adult males is 78.1 kg and for adult
females, 65.4 kg. It also shows that the mean weight for
White males (78.5 kg) is greater  than for Black males
(77.9 kg).  Additionally, mean  weights are  greater for
Black females (71.2 kg) than for White females (64.8 kg).
From Table 7-3, the mean body weights for girls and boys
are approximately  the same from ages 6 months to 14
years.  Starting at years  15-19, the difference in mean
body weight ranges from 6 to 11 kg.
           Table 7-2. Body Weights of Adults" (kilograms)
                 Men
                                Women
                                              Men and
                                              Women
  Age (years)
             Mean
              (kg)
        Std.
        Dev.
       Mean
        (kg)
        Std.
        Dev.
       Mean (kg)
  18<25
  25<35
  35<45
  4S<55
  55<65
  65<7S
  18<75
73.8
78.7
80.9
80.9
78.8
74.8
78.1
12.7
13.7
13.4
13.6
12.8
12.8
13.5
60.6
64.2
67.1
68.0
67.9
66.6
65.4
11.9
15.0
15.2
15.3
14.7
13.8
14.6
67.2
71.5
74.0
74.5
73.4
70.7
71.8
  Note: 1 kg = 2.2046 pounds.
  a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.
  Source: Adapted from National Center for Health Statistics (NCHS), 1987.
          Table 7-3. Body Weights of Children" (kilograms)
                   Boys
                                  Girls
                                             Boys and
                                               Girls
     Age
  Mean
  (kg)
 Std.
 Dev.
 Mean
 (kg)
 Std.
 Dev.
Mean
(kg)
  6-11 months
  1 year
  2 years
  3 years
  4 years
  5 years
  6 years
  7 years
  8 years
  9 years
  10 years
  11 years
  12 years
  13 years
  14 years
  15 years
  16 years
  17 years
  18 years
  19 years
  9.4
  11.8
  13.6
  15.7
  17.8
  19.8
  23.0
  25.1
  28.2
  31.1
  36.4
  40.3
  44.2
  49.9
  57.1
  61.0
  67.1
  66.7
  71.1
  71.7
  1.3
  1.9
  1.7
  2.0
  2.5
  3.0
  4.0
  3.9
  6.2
  6.3
  7.7
 10.1
 10.1
 12.3
 11.0
 11.0
 12.4
 11.5
 12.7
 11.6
  8.8
 10.8
 13.0
 14.9
 17.0
 19.6
 22.1
 24.7
 27.9
 31.9
 36.1
 41.8
 46.4
 50.9
 54.8
 55.1
 58.1
 59.6
 59.0
 60.2
 1.2
 1.4
 1.5
 2.1
 2.4
 3.3
 4.0
 5.0
 5.7
 8.4
 8.0
 10.9
 10.1
 11.8
 11.1
 9.8
 10.1
 11.4
 11.1
 11.0
 9.1
 11.3
 13.3
 15.3
 17.4
 19.7
 22.6
 24.9
 28.1
 31.5
 36.3
 41.1
 45.3
 50.4
 56.0
 58.1
 62.6
 63.2
 65.1
 66.0
  Note: 1 kg = 2.2046 pounds.
  a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.
  Source: Adapted from National Center for Health Statistics (NCHS). 1987.
7.2.  RELEVANT BODY WEIGHT STUDIES
      Brainard and  Burmaster  (1992)  -  Bivariate
Distributions for Height and Weight of Men and Women
in the United  States - Brainard and Burmaster (1992)
examined  data on the height  and  weight  of  adults
published  by the U.S. Public Health Service and fit
bivariate distributions to the tabulated values for men and
women, separately.
Page
7-4
                   Exposure Factors Handbook
                  	August 1997

-------
Volume I - General Factors
Chapter 7 - Body Weight Studies


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                                                         Volume I - General Factors
                                                     Chapter 7 - Body Weight Studies

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Chapter? - Body Weight Studies
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-------
Volume I - General Factors
Chapter 7 - Body Weight Studies
      Height and weight of 5,916 men and 6,588 women
in the age range of 18 to 74 years were taken from the
NHANES II study and statistically adjusted to represent
the U.S. population aged 18 to 74 years with regard to age
structure, sex, and race. Estimation techniques were used
to fit normal distributions to the cumulative marginal data
and goodness-of-fit tests were used to test the hypothesis
that height  and lognormal weight follow  a normal
distribution for each sex.  It was found that the marginal
distributions of height and lognormal weight for both men
and women are Gaussian  (normal)  in form.   This
conclusion was reached by visual observation and the high
R2  values  for best-fit  lines  obtained  using   linear
regression. The R2 values for men's height and lognormal
weight  are reported  to be 0.999.  The R2 values for
women's height and lognormal  weight are 0.999  and
0.985, respectively.
      Brainard and Burmaster  (1992)  fit  bivariate
distributions to estimated numbers of men and women
aged 18 to 74 years  in cells representing 1 inch height
intervals and 1-0 pound weight intervals. Adjusted height
and lognormal weight data for men were fit to a  single
bivariate normal distribution with  an estimated  mean
height of 1.75 meters (69.2 inches) and an estimated mean
weight of 78.6 kg (173.2 pounds). For women, height and
lognormal weight data were fit to a pair of superimposed
bivariate normal distributions (Brainard and Burmaster,
 1992).  The average  height and weight for women were
estimated from the combined bivariate analyses.  Mean
height for women was estimated to be  1.62 meters (63.8
inches)  and  mean  weight was estimated to be 65.8 kg
(145.0 pounds). For women, a calculation using a single
bivarite normal distribution gave poor results (Brainard
and Burmaster, 1992).   According  to Brainard  and
Burmaster, the distributions are suitable for use in Monte
Carlo simulation.
       Burmaster et al. (1994) (Submitted 2/19/94 to Risk
Analysis for Publication) - Lognormal Distributions of
Body Weight as a Function of Age for Female and Male
 Children in the United States - Burmaster et al. (1994),
 performed data analysis  to fit normal and  lognormal
 distributions to the body weights of female and male
 children at age 6 months to 20 years  (Burmaster et al.,
 1994).
       Data used in this analysis  were from the second
 survey  of the  National Center  for  Health Statistics,
 NHANES II, which included responses from 4,079
females and 4,379 males 6 months to 20 years of age in
the U.S. (Burmaster et al., 1994). The NHANES II data
had  been statistically adjusted for  non-response and
probability of selection, and stratified by age, sex, and
race to reflect the entire U.S. population prior to reporting
(Burmaster  et al.,  1994).   Burmaster et al.  (1994)
conducted exploratory and quantitative data analyses, and
fit normal and lognormal distributions to percentiles of
body  weight  for children.   Cumulative  distribution
functions (CDFs) were plotted for female and male body
weights on both linear and logarithmic scales.
     Two models  were used to assess the probability
density functions (PDFs)  of  children's  body weight.
Linear and quadratic regression lines were fitted to the
data.   A number of goodness-of-fit measures  were
conducted on  data  generated  by  the  two  models.
Burmaster et al. (1994) found that lognormal distributions
give strong fits  to the body weights of children, ages 6
months to  20  years.    Statistics  for  the  lognormal
probability plots are presented in Tables 7-8 and 7-9.
These data  can be used for further analyses of body
weight distribution (i.e., application of Monte  Carlo
analysis).
      Table 7-8. Statistics for Probability Plot Regression Analyses
         Female's Body Weights 6 Months to 20 Years of Age
        Age
                           Lognormal Probability Plots
                               Linear Curve
                                                 0V
     6 months to 1 year
          1 to 2 years
          2 to 3 years
          3 to 4 years
          4 to 5 years
          5 to 6 years
          6 to 7 years
          7 to 8 years
          8 to 9 years
         9 to 10 years
        10 to 11 years
        11 to 12 years
        12 to 13 years
        13 to 14 years
        14 to 15 years
        15 to 16 years
        16 to 17 years
        17 to 18 years
        18 to 19 years
        19 to 20 years
2.16
2.38
2.56
2.69
2.83
2.98
3.10
3.19
3.31
3.46
3.57
3.71
3.82
3.92
3.99
4.00
4.06
4.08
4.07
4.10
0.145
0.128
0.112
0.137
0.133
0.163
0.174
0.174
0.156
0.214
0.199
0.226
0.213
0.216
0.187
0.156
0.167
0.165
0.147
0.149
  a ^2> °2 " correspond to the mean and standard deviation, respectively, of
    the lognormal distribution of body weight (kg).
  Source: Burmaster et al.. 1994.	
 Exposure Factors Handbook
 August 1997
                                               Page
                                                 7-9

-------
                                                                             Volume I - General Factors
                                                                       Chapter 7 - Body Weight Studies
       Table 7-9. Statistics for Probability Plot Regression Analyses
          Male's Body Weights 6 Months to 20 Years of Age
        Age
                          Lognormal Probability Plots
                               Linear Curve
   6 months to 1 year
        1 to 2 years
        2 to 3 years
        3 to 4 years
        4 to 5 years
        5 to 6 years
        6 to 7 years
        7 to 8 years
        8 to 9 years
       9 to  10 years
      10 to  11 years
      11 to  12 years
      12 to  13 years
      13 to  14 years
      14 to  15 years
      IS to  16 years
      16 to  17 years
      17 to  18 years
      18 to  19 years
      19 to  20 years
2.23
2.46
2.60
2.75
2.87
2.99
3.13
3.21
3.33
3.43
3.59
3.69
3.78
3.88
4.02
4.09
4.20
4.19
4.25
4.26
0.132
0.119
0.120
0.114
0.133
0.138
0.145
0.151
0.181
0.165
0.195
0.252
0.224
0.215
0.181
0.159
0.168
0.167
0.159
0.154
  *  ju2, O2 - correspond to the mean and standard deviation,
    respectively, of the lognormal distribution of body weight (kg).
  Source; Burmasteret al... 1994.  	
    AIHC  -  Exposure  Factors Sourcebook  -  The
Exposure Factors Sourcebook (AIHC, 1994) provides
similar body weight data as presented here.  Consistent
with this document, an average adult body weight of 72 kg
is recommended on the basis of the NHANES II  data
(NCHS, 1987).   These data are also used to derive
probability  distributions  for adults and  children.   In
addition,    the    Sourcebook   presents   probability
distributions derived by Brainard and Burmaster (1992),
Versar (1991) and Brorby and Finley (1993). For each
distribution, the ©Risk formula is provided for direct use
in the ©Risk simulation software (Palisade, 1992).  The
organization of this document, makes it very convenient
to use in support of Monte Carlo analysis. The reviews of
the supporting studies are very brief with little analysis of
their strengths and weaknesses. The Sourcebook has been
classified as a relevant rather than key study because it is
not  the  primary  source for the data used to make
recommendations in this document.  The Sourcebook is
very  similar  to  this  document in the  sense  that  it
summarizes exposure factor data and recommends values.
As such, it is clearly relevant as an alternative information
source on body weights as well as other exposure factors.
7.3.   RECOMMENDATIONS
      The key studies described in this section was used
in selecting recommended values for body weight. The
general description of both the key and relevant studies
are summarized in Table 7-10.  The recommendations for
body weight are summarized in Table 7-11.  Table 7-12
presents   the  confidence  ratings  for  body  weight
recommendations. The mean body weight for all .adults
(male and female, all age groups) combined is 71.8 kg as
shown in Table 7-2. The mean values for each age group
in Table 7-2 were derived by adding the body weights for
men and women  and dividing by  2. If age and sex
distribution of the exposed population is known, the mean
body weight values in Table 7-2 can be used. If percentile
data are needed or if race is a factor, Tables 7-4 and 7-5
can be used to select the appropriate data for percentiles
or mean values.
      For infants (birth to 6 months), appropriate values
for body weight may be selected from Table 7-1. These
data (percentile only) are presented for male and female
infants.
      For children, appropriate mean values for weights
may be selected from Table 7-3. If percentile values are
needed, these data are presented in Table 7-6 for  male
children and in Table 7-7 for female children.
      Body weight is a function of age, gender, and race
and populations of many geographic regions may vary
from the general population across geographic regions.
Therefore, the user should make appropriate adjustments
when applying the percentiles to other geographic regions.
      The mean recommended value for adults (71.8 kg)
is different than the 70 kg commonly assumed in EPA risk
assessments.  Assessors are encouraged to use values
which most accurately  reflect  the exposed population.
When using  values other than 70 kg, however, the
assessors should consider if the dose estimate will be used
to estimate  risk by combining with a  dose-response
relationship which was derived assuming a body weight of
70 kg. If such an inconsistency exists, the assessor should
adjust the dose-response relationship as described  in the
appendix to Chapter 1. The Integrated Risk Information
System (IRIS) does  not  use a 70 kg body weight
assumption in the derivation of RfCs and RfDs, but does
make this assumption in the derivation of cancer slope
factors and unit risks.
Page
7-10
                                           Exposure Factors Handbook
                                                             August 199:7

-------
 Volume I - General Factors
 Chapter 7 - Body Weight Studies
Table 7-10. Summary of Body Weight Studies
Study
KEY STUDIES
Hamilletal. (1979)
NCHS, 1987
(NHANES II)
RELEVANT STUDIES
Braihard and Burmaster, 1992
Burmaster et al., 1994
Number of Subjects
-1,000
20,322
12,501 (5,916 men and 6,588
women)
8,458 (4,079 females and
4,379 males)
Population
U.S. general
population
U.S. general
population
U.S. general
population
U.S. general
population
Comments
Authors noted that data are accurate measurements from a
large nationally representative sample of children.
Based on civilian non-institutionalized population aged 6
months to 74 years. Response rate was 73.1 percent.
Used data from NHANES II to fit bivarite distributions to
women and men age 18 to 74 years.
Used data from NHANES II to develop fitted distributions
for children aged 6 to 20 years old. Adjusted for non-
response by age, gender, and race.
                           ._ xabte 7-41. >Sumraarrof Recommenaed Values for Body Weight
        "Populaion
                                   "Mea
   s 'Uooerl'ercentile -"f
         ^v
  Children ,/>  •
  \»  ^ //>3'^
  Infants  *    *
s 71.8 kg (Se4 fable 7-2)'   ^   **    Se^I.able&7-4andi7-5  "*N-  '  ;_;

\See^ile7-3  '  -^ '? ^ ,''  "SeeTabIes7-6and7^7 ^

 Nor Available^  ?    -   '*" **  S
                         See, Tables 7-6 ''ta&'TZf

                         See Table 7-f
  7.4.  REFERENCES FOR CHAPTER 7

 American Industrial Health Council (AIHC).  (1994)
     Exposure factors sourcebook. AIHC, Washington,
     DC.
 Brainard, J.; Burmaster, D. (1992) Bivariate
     distributions for height and weight of men and
     women in the United States. Risk Anal. 12(2):267-
     275.
 Brorby, G.; Finley, G. (1993) Standard probability
     density functions for routine use in environmental
     health risk assessment. Presented at the Society of
     Risk Analysis Annual Meeting, December 1993,
     Savannah, GA.
 Burmaster, D.E.; Lloyd, K.J.; Crouch, E.A.C. (1994)
     Lognormal distributions of body weight as a
     function of age for female and male children in the
     United States. Submitted 2/19/94 to Risk Analysis
     for publication.
 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.
Palisade. (1992) ©Risk Users Guide. Palisade
    Corporation, Newfield, NY.
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.
Versar, Inc. (1991) Analysis of the impact of exposure
    assumptions on risk assessment of chemicals in the
    environment, phase II: uncertainty analyses of
    existing exposure assessment methods. Draft
    Report. Prepared for Exposure Assessment Task
    Group, Chemical Manufacturers Association,
    Washington, DC.
; Exposure Factors Handbook
^August 1997	
                                            Page
                                             7-11

-------
                                                                                         Volume I - General Factors

                                                                                  Chapter 7 - Body Weight Studies
                                      Table 7-12.  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
    1 Characterization of
     variability

    1 Lack of bias in study design
     (high rating is desirable)

    1 Measurement error
  Other Elements
   • Number of studies
   • Agreement between researchers
  Overall Rating	
NHANES H was the major source of data for NCHS (1987). This is a
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.

Results can be reproduced by analyzing NHANES II data and the Pels
Research Institute data.

The studies focused on body weight, the exposure factor of interest.

The data represent the U.S. population.

The primary data were generated from NHANES II data and Pels studies,
thus these data are secondary.

The data were collected between 1976-1980.

The NHANES II study included data collected over a period of 4 years.
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,
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 Pels 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
noted in Hamill et al. (1979) that the data set was large.

Data collected focused on the U.S. population for both studies.
Both studies characterized variability regarding age and sex. Additionally
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
study design for collecting the Pels data was not provided.

For NHANES II, measurement error should be low since body weights
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 etal.  (1979) report that study data
are based on accurate direct measurements from an ongoing longitudinal
study.
There are two studies.

There is consistency among the two studies.
  High


  High
  High

  High

  High

Medium

  Low

  High


  High
  High

  High

  High
Medium-
  High

  High
  Low

  High

  High
Page
7-12
                                         Exposure Factors Handbook
                                                              August 1997

-------
 Volume I - General Factors
 Chapter 8 - Lifetime
                                            .rf
 8.     LIFETIME
       The length of an individual's life is an important
 factor to consider when evaluating cancer risk because the
 dose estimate is averaged over an individual's lifetime.
 Since the averaging time is found in the denominator of
 the dose equation, a shorter lifetime would result in a
 higher potential risk estimate, and conversely, a longer life
 expectancy would produce a lower potential risk estimate.

 8.1.   KEY STUDY ON LIFETIME
       Statistical  data on life expectancy are published
 annually by the U.S. Department of Commerce in the
 publication:  "Statistical Abstract of the United States."
 The latest year for which statistics are available is 1993.
 Available  data  on   life   expectancies  for various
 subpopulations born  in the years  1970  to.  1993 are
 presented in Table 8-1. Data for 1993 show that the life
 expectancy for an average  person born in the United
 States in 1993 is 75.5 years (U.S. Bureau of the Census,
 1995).  The table shows that the overall life expectancy
 has averaged approximately 75 years since 1982.  The
 average life expectancy for males in 1993 was 72.1 years,
 and 78.9 years for females. The data consistently show an
 approximate  7 years difference  in life expectancy for
 males and females from 1970 to present. Table 8-1 also
 indicates that life expectancy for white males (73.0 years)
 is consistently longer than for Black males (64.7 years).
 Additionally, it indicates that life expectancy for White
 females  (79.5 years) is longer than for Black females
 (73.7), a difference of almost 6 years. Table 8-2 presents
 data for expectation of life for persons who were at a
 specific  age in year 1990.  These data are available by
 age, gender,  and race  and may be useful for deriving
 exposure estimates based on the  age of  a specific
 subpopulation. The data show that expectation of life is
 longer for females and for Whites.
8.2.  RECOMMENDATIONS
      Current data suggest that 75 years would be an
appropriate value to reflect the average life expectancy of
the general population and is the recommended value. If
gender is a factor considered in the assessment, note that
the average life expectancy value for females is higher
than for males.  It is recommended  that the assessor use
the appropriate value of 72.1 years for males or 78.9 years
for females.   If race is a consideration in assessing
exposure  for male individuals,  note  that the  life
expectancy is about 8 years longer for Whites than for
Blacks.  It is recommended that the  assessor use the
values of 73  years and 64.7 years for White males and
Black  males, respectively.   Table 8-3 presents the
confidence rating for life expectancy recommendations.
      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.

8.3.  REFERENCES FOR CHAPTER 8

U.S. Bureau of the Census. (1995) Statistical abstracts of
      the United States.
Exposure Factors Handbook
August 1997     	
                                             Page
                                               8-1

-------
                                                       Volume I - General Factors

                                                              Chapter 8 - Lifetime
Table 8-1. Expectation of Life at Birth, 1970 to 1993, and Projections, 1995 to 2010 (years)a
TOTAL
YEAR
1970
1975
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
Total Male
70.8 67.1
72.6 68.8
73.7 70.0
74.1 70.4
74.5 70.8
74.6 71.0
74.7 71.1
74.7 71.1
74.7 71.2
74.9 71.4
74.9 71.4
75.1 71.7
75.4 71.8
75.5 71.0
75.8 72.3
75.5 72.1
Projections0 1995 76.3 72.8



a
b
c
Source:
2000 76.7 73.2
2005 77.3 73.8
2010 77.9 74.5

Female Total
74.7
76.6
77.4
77.8
78.1
78.1
78.2
78.2
78.2
78.3
78.3
78.5
78.8
78.9
79.1
78.9
79.7
80.2
80.7
81.3
71.7
73.4
74.4
74.8
75.1
75.2
75.3
75.3
75.4
75.6
75.6
75.9
76.1
76.3
76.5
76.3
77.0
77.6
78.2
78.8
WHITE
Male Female
68.0
69.5
70.7
71.1
71.5
71.6
71.8
71.8
71.9
72.1
72.2
72.5
72.7
72.9
73.2
73.0
73.7
74.3
74.9
75.6
Excludes deaths of nonresidents of the United States.
Racial descriptions were not provided in the data source.
Based on middle mortality assumptions; for details, see U.S.
Bureau of the Census, 1995.



75.6
77.3
78.1
78.4
78.7
78.7
78.7
78.7
78.8
78.9
78.9
79.2
79.4
79.6
79.8
79.5
80.3
'80.9
81.4
81.0
BLACK AND OTHERb
Total
65.3
68.0
69.5
70.3
70.9
70.9
71.1
71.0
70.9
71.0
70.8
70.9
71.2
71.5
71.8
71.5
72.5
•72.9
73.6
74.3
Bureau of the Census,


Male
61.3
63.7
65.3
66.2
66.8
67.0
67.2
67.0
66.8
66.9
66.7
66.7
67.0
67.3
67.7
67.4
68.2
68.3
69.1
69.9
Female
69.4
72.4
73.6
74.4
74.9
74.7
74.9
74.8
74.9
75.0
74.8
74.9
75.2
75.5
75.7
75.5
76.8
77.5
78.1
78.7
Total
64.1
66.8
68.1
68.9
69.4
69.4
69.5
69.3
69.1
69.1
68.9
68.8
69.1
69.3
69.6
69.3
70.3
70.2
70.7
71.3
BLACK
Male
60.0
62.4
63.8
64.5
65.1
65.2
65.3
65.0
64.8
64.7
64.4
64.3
64.5
64.6
65.0
64.7
65.8
65.3
65.9
66.5
Current Population Reports, Series P-25, No.





Female
68.3
71.3
72.5
73.2
73.6
73.5
73.6
73.4
73.4
73.4
73.2
73.3
73.6
73.8
73.9
73.7
74.8
75.1
75.5
76.0
1104.

Page
8-2
 Exposure Factors Handbook
	August 1997

-------
 Volume I - General Factors

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

Expectation of Life in Years
Age in 1990
(years)
At birth
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
Total
75.8
75.4
74.5
73.5
72.5
71.6
70.6
69.6
68.6
67.6
66.6
65.6
64.6
63.7
62.7
61.7
60.7
59.8
58.8
57.9
56.9
56.0
55.1
54.1
53.2
52.2
51.3
50.4
49.4
48.5
47.5
46.6
45.7
44.7
43.8
42.9
42.0
41.0
40.1
39.2
38.3
37.4
36.5
35.6
34.7
33.8
32.9
32.0 '
31.1
30.2
Male
73.2
72.8
71.8
70.9
69.9
68.9
67.9
66.9
65.9
65.0
64.0
63.0
62.0
61.0
60.0
59.1
58.1
57.2
56.2
55.3
54.3
53.4
52.5
51.6
50.6
49.7
48.8
47.8
46.9
46.0
45.1
44.1
43.2
42.3
41.4
40.5
39.6
38.7
37.8
36.9
36.0
35.1
34.2
33.3
32.4
31.5
30.6
29.7
28.8
28.0
White
Female
79.8
79.3
78.3
77.3
76.3
75.4
74.4
73.4
72.4
71.4
70.4
69.4
68.4
67.4
66.5
65.5
64.5
63.5
62.5
61.6
60.6
59.6
58.7
57.7
56.7
55.7
54.8
53.8
52.8
51.8
50.9
49.9
48.9
48.0
47.0
46.0
45.1
44.1
43.2 .
42.2
41.2
40.3
39.3
38.4
37.5
36.5
35.6
34.7
33.7
32.8
Male
65.0
65.2
64.3
63.4
62.4
61.4
60.5
59.5
58.5
57.5
56.5
55.5
54.6
53.6
52.6
51.7
50.7
49.8
48.9
48.1
47.2
46.3
45.5
44.6
43.8
42.9
42.1
41.2
40.4
39.5
38.7
37.8
37.0
36.2
35.3
34.5
33.7
32.9
32.1
31.3
30.5
29.7
28.9
28.2
27.4
. 26.7
25.9
25.2
24.4
23.7
Black
Female
73.9
74.1
' - 73.1
72.2
71.2
70.3
69.3
68.3
67.3
66.3
65.4
64.4 •
63.4
62.4
61.4
60.4
59.5
58.5
57.5
56.6
55.6
54.6
53.7
52.7
• 51.8
50.8
49.9
48.9
48.0
47.1
46.1
45.2
44.3
43.4
42.4
41.5
40.6
39.7
38.8
37.9
37.1
36.2
35.3
. . 34.4
33.6
32.7
31.9
31.0
30.2
29.3
.Exposure Factors Handbook
August 1997	.
Page
  8-3

-------
                                                        Volume I - General Factors

                                                          	Chapter 8~ Lifetime
Table 8-2. Expectation of Life by Race, Sex, and Age: 1992 (continued)
Expectation of Life in Years
White
Age in 1990
(years)
SO
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
70
75
80
85 and over
Source: U.S. Bureau of Census,
Total
29.3
28.5
27.6
26.8
25.9
25.1
24.3
23.5
22.7
21.9
21.1
20.4
19.7
18.9
18.2
17.5
14.2
11.2
8.5
6.2
1995.
Male
27.1
26.3
25.4
24.6 •
23.7
22.9
22.1
21.3
20.6
19.8
19.1
18.3
17.6
16.9
16.2
15.5
12.4
9.6
7.2
5.3

Female
31.9
31.0
30.1
29.2
28.3
27.5
26.6
25.7
24.9
24.1
23.2
22.4
21.6
20.8
20.0
19.3
15.6
12.2
9.2
6.6

Black
Male
23.0
22.3
21.5
20.8
20.1
19.5
18.8
18.2
17.6
16.9
16.3
15.8
15.2
14.6
14.1
13.5
11.0
8.9
6.8
5.1

Female
28.5
27.7
26.8
26.0
25.3
24.5
23.7
23.0
22.2
21.5
20.8
20.1
19.4
18.7
18.0
17.4
14.3
11.4
8.6
6.3

Page
8-4
Exposure Factors Handbook
 	August 1997

-------
  Volume I - General Factors

  Chapter 8 - Lifetime	
                                                                        •rf
                                     Table 8-3. Confidence in Lifetime Expectancy 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

  Overall Rating
 Data are published and have received extensive peer review.

 The study was widely available to the public (Census data).

 Results can be reproduced by analyzing Census data.

 Statistical data on life expectancy were published in this study.

 The study focused on the U.S. population.

 Primary data were analyzed.

 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.

 The data analyzed were collected over a period of years.

 Census data is collected and analyzed over a period of years.

 This study was based on U.S. Census data, thus the population study size
 is expected to be greater than 100.

 The data are representative of the U.S. population.

 Data were averaged by gender and race but only for Blacks and Whites; no
 other nationalities were represented within the section.

There are no apparent biases.
                                                Measurement error may be attributed to portions of the population that
                                                avoid or provide misleading information on census surveys.
Data presented in the section are from the U.S. Bureau of the Census
publication.

Recommendation was based on only one study, but it is widely accepted.
  High

  High

  High

  High

  High

  High

  High



  High

  High

  High


  High

Medium


  High


Medium




  Low


 High

HIGH
Exposure Factors Handbook
August 1997	
                                                                       Page
                                                                         8-5
AU.S GOVERNMENT PRINTING OFFICE: 1998 650-001/80172

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