United States
                   Environmental Protection
                   Agency
Office of Health and
Environmental Assessment
Washington DC 20460
                   Research and Development
 EPA/600/S8-85/010  Mar. 1989
&EPA         Project  Summary

                   Development of Statistical
                   Distributions  or  Ranges  of
                   Standard  Factors  Used  in
                   Exposure Assessments
                   E. Anderson, N. Browne, S. Duletsky, J. Ramig, and T. Warn
                    This summary provides information
                   on how to calculate human exposure
                   to toxic substances and  ranges  of
                   values for body weight, skin surface
                   area, and ventilation rates.
                    Percentile distribution of body
                   weight were computed  from the
                   Second National Health and Nutrition
                   Examination Survey (NHANES II) data
                   base  computer program. Distribu-
                   tions  of  skin  surface areas were
                   similarly  calculated from NHANES
                   height and weight data by applying
                   regression equations.
                    Insufficient data precluded the
                   development of distributions  of
                   ventilation rates.  Activity  pattern
                   information  is  presented  to permit
                   the calculation of time-weighted
                   average ventilation  rates.
                    This Project Summary was devel-
                   oped  by EPA's Office of Health and
                   Environmental  Assessment, Wash-
                   ington, DC, to announce key findings
                   of the research project that is fully
                   documented  in a separate report  of
                   the same title  (See Project  Report
                   ordering information at back).

                   Introduction
                    Using standard factors in exposure
                   assessments  promotes consistency
                   among various  exposure assessment
                   activities in which the Environmental
                   Protection Agency (EPA) is involved.
                   Consistency with respect to common
                   physical,  chemical,  and  biological
                   factors, to assumptions about typical
                   exposure situations, and to the  presen-
tation of the possible ranges of estimates,
enhances the comparability of results and
encourages gains in state-of-the-art
exposure assessment techniques.
  Current practice for estimating human
exposures  typically  involves the
assumption of average values for  such
factors  as  body weight,  liquid  con-
sumption, and respiration rates. The full
report presents statistical distributions or
ranges of values for these factors.
  Where sufficient data are  available,
percentile  distributions are developed.
Where insufficient  data precluded the
development of  statistical distributions,
ranges of  values were compiled  from
measurements reported in the literature.
In a  few instances, unpublished  data
obtained through correspondence with
researchers have been used to develop
ranges or distributions. All data, including
these unpublished data, are presented in
the Appendices of the full report.  A
glossary of terms is also presented.

Body Weight
  Published percentile  distributions for
body weight for  men and  women and
male and  female  children are based
primarily on  data gathered in the first
National Health and Nutrition Examination
Survey  during 1970 and 1974.  The
source of data used in this study is the
more recent, second National Health and
Nutrition Examination Survey , NHANES
II, for which published percentiles are not
yet available.
  NHANES II was conducted  on  a
nationwide  probability sample  of ap-

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proximately 28,000  persons,  aged 6
months  to  74 years, from  the  civilian,
noninstitutionalized  population  of  the
United States.  The  survey started  in
February 1976  and  was  completed  in
February 1980. The sample was selected
so that certain population groups thought
to be at high risk of malnutrition (persons
with low incomes, preschool children and
the  elderly)  were  oversampled.
NHANES  II  provides  information  on
20,322 interviewed and examined indi-
viduals.
  Weight was measured with a scale that
mechanically  prints  weight to  quarter-
pound  intervals directly onto  the
permanent record.
  In the full report, percentiles (and their
standard errors) of  the distribution  of
body weight have been computed from
the NHANES  II data  using the computer
program QNTLS.

Surface Area of  the Human
Body
  Two approaches  can  be used  to
determine the surface area (SA) of  the
body: direct  measurement  of the  skin
area or estimating the SA by geometrical
approximation.
  Several direct  measurement tech-
niques have been used to measure  SA,
including direct coating, triangulation,
and surface integration.
  The  coating methods  consist  of
coating either the whole body or specific
regions  with  a  substance  of  known  or
measured area. In some instances  the
pieces of coating were placed on cross-
section paper and the area measured by
counting the squares covered. In others,
the areas of the pieces of coating were
calculated by weighing the coating  or
weighing duplicates cut from a substance
of uniform thickness. Triangulation
consists of marking the  area of the body
into geometric  figures  then calculating
the figure areas from their linear dimen-
sions. Surface  integration  is performed
by running a planimeter over the body in
parallel  strips of equal width. The SA is
calculated by adding the areas of all the
strips measured.    Directly measuring
body SA by any  method described
above is a difficult and time consuming
task.  Consequently,  existing  direct
measurement data are limited.
   Body  SA  can  be estimated using
geometric  methods by  assuming  the
parts  of the  body  resemble  geometric
solids, then calculating  the  surface area
of  the  solids  based  on  a  few
measurements  of  length  and  circum-
ference. For example, the SA of the trunk
may be  estimated  by  measuring  the
length from the groove of the neck to the
tip  of the coccyx  and  taking circum-
ferences just under the arms, at the level
of the pubis.
  A linear method has been proposed in
which  estimates are made on  the
principle  that the surface area of  the
parts of the body are proportional, rather
than equal, to the surface area  of  the
solids they resemble,  so that estimates
of SA  made  from  lengths and  circum-
ferences  need to  be corrected by con-
stants obtained  from direct  measure-
ments of SA.
  Several  formulae have been proposed
for  estimating body SA from measure-
ments of other major  body dimensions.
Generally, the formulae are based on the
principles  that body density  and shape
are roughly  the  same  and that the
relation of SA to  any dimension may be
represented  by  the curve  of  central
tendency of their  plotted values or by the
algebraic expression for the curve. Most
formulae  for estimating SA relate height
to weight. The first such equation derived
can be expressed by:

             SA  = KW 2/3

where  SA is  surface  area in  square
meters, W is  weight in kilograms, and K
is a constant. While the  equation has
been  criticized  because  the specific
gravities of human bodies are not equal
and because the surface  area per unit
volume  differs  for individuals with
different body   builds,  it  gives a
reasonably good estimate of SA.
  A  formula that   has  found  wide
acceptance and use is:

          SA = a0 H3-, Wa2

where  SA is surface area in  square
meters, H is  height in  centimeters, and
W is weight in kilograms. The value of an
(0.007182), a, (0.725), and  a2  (0.425)
were estimated from a  sample  of  only
nine individuals for which SA was directly
measured.
  More recently,  values  of  the  model
parameters were solved  for the rela-
tionship  between SA  and height and
weight by multiple  regression analysis.
The least squares best fit for  this
equation  yielded  the following values for
the three coefficients: an = 0.024265, a-|
 = 0.3964, and 82 =0.5378. The result is
this equation for estimating surface area:

     SA = 0.024265 H° 3964 W° 5378
expressed logarithmically as:

  In SA = In 0.024265 + 0.3964 In H
          0.5378 In W.

The coefficients for this equation  agr
remarkably with those obtained in  earl
measurements.
  A graphical method has been propos
whereby  SA could be  read  from
diagram  relating height and  weight
surface areas. However, it does not gi
an explicit model for calculating SA. T
graph was developed empirically  bas
on 252  cases, 127  of  which  were fr(
401  direct measurements  report
earlier. In the other 125 cases the SA w
estimated using the linear method.
  Several investigators who have work
in  determining body surface  area ha
reported  their results in terms of surfa
areas  (SA) of different parts of the bo
as  well  as  total   surface  area. T
literature contains SA of body parts b(
as  direct  measurements  and
estimates.  Data on  body part SA ha
been reported for both sexes,  for seve
ethnic groups, and for ages ranging frc
newborn  to elderly.
  This study presents the largest  sint
group of direct  measurements made
any SA investigator, involving a balanc
sample  of  individuals   according to s
age group, and compares the results
Japanese measurements with Germa
and Americans, however, only averag
for each  age  group and sex  a
presented, which limits  the usefulness
the data for determining  ranges
percentages for each body part or regie
  Our recent study proposed a  hum
skin surface model  based on a geomet
method of estimating SA. Various bo
dimensions for a "50th percentile ma
were used with a mensuration  formula
geometric solids to calculate  the  SA
the geometric solid  most closely relat
to the body part.   The results were
ported  as a percentage of total !
associated with each body  part,  whi
shows the author's comparison  of I
model  with three earlier   publish
methods.
  Available direct  measurement d«
were  analyzed using the  Statistic
Processing  System  (SPS) softwe
package  to  generate  equations tt
calculate SA as a function of  height a
weight. These equations were then us
to calculate SA distributions of the U
population with NHANES II  height  a
weight data using the computer progn
QNTLS.

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Ventilation Rates
  Pulmonary ventilation data and activity
pattern  data permit  the calculation  of
time-weighted  average ventilation rates.
  Pulmonary  ventilation  is  the mass
movement of gas in and out of the lungs.
The  volumes of inhaled and exhaled air
usually are not exactly equal; the volume
of inspired oxygen  is  typically larger than
the volume of expired  carbon  dioxide.
Pulmonary ventilation  is  generally
represented by the minute volume (^e),
the volume  of gas expired in liters per
minute at BTPS (gas volume at normal
body  temperature  and  ambient
barometric pressure,  saturated with water
vapor). Minute volume is the product  of
tidal  volume (the volume of gas moved
during  each  respiratory cycle) and
respiratory frequency.
  Minute volume  is  usually  measured
accurately  with a water-filled  spirom-
eter.  The  spirometer  uses  one-way
valves to funnel expired air into a col-
lection system or  alternatively,  directly
into a spirometer.
  There  have  been  several formulae
proposed in the literature to  calculate
minute ventilation of humans at rest from
anthropometric data.
  Resting ventilation  is directly related  to
the resting  metabolic rate.  With exercise,
minute volume increases in response  to
the increase in metabolic demand. There
is an abrupt increase in ventilation with
the onset of  exercise, followed by  a
further,  more gradual  increase.  With
moderate exercise, the  increase is  due
primarily to  an increase in tidal volume;
this  is accompanied  by an increase in
respiratory  frequency when the exercise
becomes more strenuous.  When exer-
cise ceases, there is an abrupt decrease
in ventilation, followed by a more gradual
decline to preexercise values.
  Review  of  the  literature  failed to
identify  equations that  would enable the
development of statistical distributions of
minute  ventila-tion at  all activity  levels
for male and female children and adults.
Therefore,  ranges  of  measured values
were compiled from the  available  data,
which are  tabulated in the  full report.
Many of these measurements are from
early studies.
  Most of the available  minute ventilation
measurements are from  studies  ex-
pressing the associated activity levels in
terms of kilogrammeters  per minute. In
other studies, the activity level was given
qualitatively by the type of activity (e.g.,
walking  at  3 miles per hour);  the asso-
ciated breathing rates  were  categorized
based on representative activities.
  For  each  age-sex-activity  level
category for which  data were  available,
minimum, maximum, and  mean minute
volumes were  determined. These values
were  derived from   both  individual
measurements and   reported  mean
values, for  which the raw data were not
presented.  Weighted means were  cal-
culated  by assigning  each individual
measurement a weight of one  and each
mean value a  weight  corresponding to
the number of subjects the mean  repre-
sented;  the weighted  data were  then
summed and divided by the total number
of  subjects. The standard deviations for
the age-sex-activity level groups were
not calculated because  many of  the
mean values used were reported without
any measure of distribution variance. In
addition, many groups had very few data
points, making  standard  statistical sum-
maries  difficult to interpret.  In some
cases, means were presented without the
minimum  and maximum values  of  the
original data sets; therefore, the minima
and  maxima  for  age-sex-activity level
groups are representative only  of  the
available individual measurements.
  Activity  pattern data may be  used in
conjunction with  minute  volume data to
estimate ventilation rates.   In addition to
providing information on exercise levels,
available  activity  pattern  studies  also
describe  the  amount  of  time  spent in
different microenvironments. Such  de-
tailed information is desirable  if  the
ambient  concentration  of  a  pollutant
differs significantly from  one microenvi-
ronment to another, as may happen with
particulate filtration from  the outdoor to
the indoor microenvironment.
  More detailed activity pattern data are
available in the Appendices of the  full
report which  presents in  its entirety  a
document describing activity patterns for
56 population subgroups. This document
is  a  supplement to  a  report  on  the
application of  the National Ambient Air
Quality  Standard Exposure Model  to
carbon monoxide. Hourly  assignments to
locations,  microenvironments, and activ-
ity levels  are presented for each popu-
lation subgroup.

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£ Anderson,  N.  Browne, S. Duletsky,  J. Ramig,  and  T. Warn are with  GCA
   Corporation, Chapel Hill, NC 27514,
Tom McLaughlin is the EPA Project Officer (see below).
The complete  report, entitled, "Development of Statistical Distributions or Ranges
   of Standard Factors Used in Exposure Assessments," (Order No.  PB 85-242
   667/AS; Cost: $21.95, subject to change) will be available only from:
    National Technical Information Service
    5285 Port Royal Road
    Springfield, VA 22161
    Telephone:  703-487-4650
The EPA Project Officer can be contacted at:
    Office of Health and Environmental Assessment
    U.S. Environmental Protection Agency
    Washington, DC 20460
United States                  Center for •Environm.&ntat Research
Environmental Protection        Information     '         Vs,:>,":"'Yi
Agency                        CincinnatTOH 4$268^5 \-&  VrXAT^i
                                                         1J^£  jl'-j
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Official Business
Penalty for Private Use $300

EPA/600/S8-85/010
                   CHICAGO

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