RTI/1864/50-03F
                                                                 November 12, 1982
                                        Final Report
                                POLYCHLORINATED BIPHENYLS IN
                           HUMAN ADIPOSE TISSUE AND MOTHER'S MILK
                                              by

                                          R.  M.  Lucas
                                      V.  G.  lannacchione
                                         D.  K.  Melroy
                                  Research Triangle Institute
                                    Research Triangle Park
                                     North Carolina  27709
                               EPA Contract Number:   68-01-5848
                                Project Officer:   Joseph Carra
                                 Task Manager:   Richard Levy
                             U.  S.  Environmental Protection Agency
                                 Exposure Evaluation Division
                                 Design and Development Branch
                                      401 M Street,  S.W.
                                    Washington,  D.C.   20460
RESEARCH  TRIANGLE  PARK,  NORTH   CAROLINA  27709

-------
This report was prepared under contract to an agency of
the United States Government.  Neither the United States
Government nor any of its employees, contractors,
subcontractors, or their employees makes any warranty,
expressed or implied, or assumes any legal liability or
responsibility for any third party's use or the results
of such use of any information, apparatus, product, or
process disclosed in this report, or represents that its
use by such third party would not infringe on privately
owned rights.

Publication of the data in this document does not signify
that the contents necessarily reflect the joint or separate
views and policies of each sponsoring agency.  Mention of
trade names or commercial products does not constitute
endorsement or recommendation for use.

-------
                                                       RTI/1864/50-03F
                                                       November 12, 1982
Approved by:
                              Final Report
                      POLYCHLORINATED BIPHENYLS IN
                 HUMAN ADIPOSE TISSUE AND MOTHER'S MILK
                                    by

                                R. M. Lucas
                            V. G. lannacchione
                               D. K.  Melroy
                        Research Triangle Institute
                          Research Triangle Park
                           North Carolina  27709
                     EPA Contract Number:  68-01-5848
                      Project Officer:   Joseph Carra
                       Task Manager:   Richard Levy
                   U.  S.  Environmental Protection Agency
                       Exposure Evaluation Division
                       Design and Development Branch
                            401 M Street,  S.W.
                          Washington, D.C.  20460
Robert M. Lucas, Task Leader            Stephen R.  Williams, Project Leader
Research Triangle Institute             Research Triangle Institute

-------
                            Table of Contents

                                                                 Page

1.   EXECUTIVE SUMMARY	          1

2.   INTRODUCTION 	          2

3.   HUMAN DATA SUMMARY	          3

     3.1  General Description of the National Adipose
          Tissue Survey 	          3
          3.1.1  Objectives of the NHMP Adipose Tissue
                 Survey 	         3
          3.1.2  Overview of Current Survey Design	         3
          3.1.3  Overview of Weighting	         4
          3.1.4  Summary of Polychlorinated Biphenyls
                 in Human Adipose Tissue	         6
          3.1.5  Limitations of Statistical Inference ...         7

     3.2  Polychlorinated Biphenyls in Human Milk 	        13

          3.2.1  General Description of the Study	        13
          3.2.2  Overview of the PCBs in Human Milk
                 Study Design	        13
          3.2.3  Limitations of Statistical Inferences
                 for PCBs in Human Milk	        18
          3.2.4  Summary of Polychlorinated Biphenyls
                 in Human Milk	        18

4.   REFERENCES	        20

APPENDIX A:  Analysis Weighting Methodology 	      A-22

APPENDIX B:  Statistical Methods Used in Analysis of
             Polychlorinated Biphenyls in Adipose Tissue.  .      B-32

-------
                             List of Tables

Table                                                            Page

  1       Weighted Percentage Distribution of PCB Residue
          Levels in Adipose Tissue for all Fiscal Years ...      8

  2       Significance Levels of Estimated Trends in PCBs
          for Fiscal Years 1972 through 1981	     16

  3       Significance Levels of Estimated Effects of
          Demographic and Geographic Factors	     17

  4       Summary of Polychlorinated Biphenyls in Human
          Milk	     19
                              (11)

-------
                            List of Figures

                                                                Page

         Sample Stages of the National Human Monitoring
         Program 	      5

 2       Estimated Percentage Distribution of U.S.  Popula-
         tion by Adipose Tissue PCB Residue Category for
         Fiscal 1972 through 1981	      9

 3       Estimated Trends for Percent of PCB Residue Levels
         Detected by Age Group for Fiscal 1972 through 1981.     10

 4       Comparison of Estimated and Observed Trends for
         Percent of PCB Residue Levels Detected for Fiscal
         1972 through 1981	     10

 5       Estimated Trends for Percent of PCB Residue Levels
         Above 3 PPM by Age Group for Fiscal 1972 through
         1981	     11

 6       Estimated Trends for Percent of PCB Residue Levels
         Above 3 PPM by Race Group for Fiscal 1972  through
         1981	     11

 7       Comparison of Estimated and Observed Trends for
         Percent of PCB Residue Levels Above 3 PPM  for
         Fiscal 1972 through 1981	     11

 8       Estimated Percentage Distribution of U.S.  Population
         by Adipose Tissue PCB Residue Category for Fiscal
         1976 through 1981	     14

 9       Comparison of Estimated and Observed Trends for
         Percent of PCB Residue Levels Detected for Fiscal
         1976 through 1981	     15

10       Comparison of Estimated and Observed Trends for
         Percent of PCB Residue Levels Above 3 PPM  for
         Fiscal 1976 through 1981	     15
                            (ill)

-------
                            ACKNOWLEDGEMENTS




     The authors would like to thank the Task Manager, Mr. Richard Levy




for his assistance and patience in compiling the materials necessary to




produce this report, the Project Officer, Mr. Joseph Carra and Project



Director, Mr. Stephen Williams for the helpful comments in revising




the manuscript, and Ms. Martha Clegg for her efforts in typing the




manuscript.
                              (iv)

-------
1.   EXECUTIVE SUMMARY

     This report gives a concise summary of the prevalence and levels of
polychlorinated biphenyls  (PCBs) in  human adipose  tissue  and mother's
milk.  Data collected from the National Adipose Tissue Survey are reviewed
and  summarized.   Additional  material  on  PCBs  in  human  mother's  milk
supplied by  the  U.S.  Environmental Protection Agency  is  also included.

     The percent of persons  in the U.S. with detectable levels and with
levels  greater than  3 parts  per  million (ppm)  were investigated  to
ascertain changes among the fiscal years 1972 to 1979 and 1981.  Different
subpopulations defined by  the  factors age, sex, race, Census Region and
PCB industries were investigated to ascertain their association with the
PCB levels.

     The estimated percentage  of U.S. population with detectable levels
of  PCBs  was  found to  be  increased  from  approximately  85  percent  in
fiscal  1972  to  nearly 100  percent in  fiscal  1979.  (The  fiscal  1981
estimates based on a  subsample of 97 specimens indicates  100 percent of
the U.S. population have  detectable levels of PCB).  However, the esti-
mated percentage  of  the  U.S.  population with greater than  3 parts per
million PCB in their tissue has increased from approximately 2.7 percent
in  fiscal  1972 to 8  percent  in  fiscal 1976 and  then has  decreased  to
less than 1 percent in fiscal 1981.

     Age is  the only  factor associated with the direction and amplitude
of trends.    The percentage  of  persons with detectable levels of PCBs  is
increasing  in  all  age  groups but is lower in amplitude in young persons
(0-14 years).  The trends in the percentage of persons with greater than
3 parts per million PCB in the two older age categories (15-44 years and
45+ years)  are similar to the overall trend.   The percentage of persons
in the young  age  category with greater  than  3  parts per million PCB is
nearly constant during the decade and generally lower than the other two
age  groups.    No  other factors  were  found  to  be associated with the
general shape of trends,  but males and nonwhites tended to have a higher
percentage  of  persons  with greater  than  3 ppm  PCBs  than  females and
whites, respectively.

     A special study  that  measured the levels of  PCB residue  in human
mothers'  milk in  1977 was  not  inconsistence  with  adipose tissue  in
percentage  of  persons  with  detectable  levels but  the magnitude  of the
levels was  lower than that found in adipose tissue.
                                 -1-

-------
2.   INTRODUCTION

     This  report  presents  concise  but  comprehensive  summary  of  the
prevalence and  levels  of  polychlorinated biphenyls (PCBs) in humans and
the  environment.   The  primary sources  for  this report  are  previously
prepared preliminary reports on the U.S. Environmental Protection Agency's
(US  EPA)  monitoring program  for  human adipose  tissue  and its computer
accessible data  files.  Additional  material  provided by  the  US  EPA on
PCBs in human mother's milk is also included.

     Chapter three  addresses  PCBs  in humans.   The first section concen-
trates on the National Human Monitoring Program's Adipose Tissue Survey.
That survey  is  an  ongoing program that has been measuring PCBs in human
adipose tissue since fiscal 1972.   The second section summarizes the PCB
data measured in human mother's milk collected in a special study spon-
sored  by the US EPA.   Chapter four includes a  list of  all  documents
referenced in the report.

     In  order  to  limit  the  amount of  material presented, only brief
descriptions of  the  monitoring program,  the  study  of  human mother's
milk,  and  their survey designs are included  in the  text.   Additional
information  is  contained  in  the  appendices.   The  reader  is  advised of
potential  limitations  in  making  inferences  beyond the  sample data and
efforts are  made to assess  the impact of the limitations on the conclu-
sions.  References  are included to guide the  reader  interested in more
detail.

     Several terms  that have  rigorous  statistical  definitions are used
in the report.   Below are generic definitions for these terras.

     Target Population:  The universe to which an investigator wishes to
     make inferences.   Examples are  the civilian population in the U.S.
     or all  rural  soils in the U.S.  to a depth of three inches, as of a
     specific point in time.

     Sampling Frame:  A list or inventory of units in the entire universe
     to be sampled.   Examples are a list of all counties in the U.S. or
     a conceptualized  list  of all 3-inch cubes  of  top-soil  in the U.S.

     Probability Sampling:  A process  by which each  unit  on  a sampling
     frame may  be   selected  for study with a  known and  positive proba-
     bility.
                                 -2-

-------
3.   HUMAN DATA SUMMARY

3.1  General Description of the National Adipose Tissue Survey

     The  National  Human  Monitoring Program  (NHMP) was  established in
1967  to  monitor  levels  and  prevalence  of pesticide  residues  in the
general population of the United States and to assess changes and trends
in these  levels.   The  program was initiated by the United States Public
Health Service  and was  transferred in  1970  to the  then newly created
United States Environmental Protection Agency (EPA).

     The  National  Adipose  Tissue  Survey   (NATS)  is  one  of  the  major
ongoing components  of  NHMP.   Specimens of  adipose  tissue are collected
from surgical patients and autopsied cadavers through the cooperation of
local pathologists  and  medical  examiners.   The adipose tissue specimens
are  chemically  analyzed  for twenty  chlorinated  hydrocarbon compounds
including PCBs.   These  are  listed in Lucas RM et al.  1980.  This report
also  includes  a  description and  evaluation  of the  chemical analysis
method.   This  section  includes a  summary  of  all  PCB  data  currently
available from  the NATS computer accessible data  files.   This includes
all  data  for fiscal  1972 through  1979  and approximately  a 10 percent
subsample of fiscal 1981.

     3.1.1  Objectives of the NHMP Adipose Tissue Survey

            The defined  primary objectives  of the adipose tissue survey
are:

     (i)       to measure average concentration of pesticides and
               other toxic substances in the general U.S. population;

     (ii)      to measure time trends of these concentrations; and

     (iii)     to assess the effects of regulatory actions.

As a secondary objective, the adipose tissue survey

     (iv)      provides baseline data.

The  baseline data  may  help in detecting and evaluating suspected pesti-
cide poisonings.   Besides achieving the above  objectives  on a national
basis, several subpopulations or domains are of interest.  These domains
are  sex, race, age subgroups, and geographic regions.

     Based  on  these objectives,  the  following  definition  seems appro-
priate as a target population.

     Target Population:  All non-institutionalized persons in the
                         United States.

     3.1.2  Overview of Current Survey Design

            A brief description of the current  NATS  survey design that
was  implemented  in  fiscal  1977 is given below.  The  survey design was
                                 -3-

-------
modified  twice  in the  past.   A description  of all  survey designs and
their  time  periods  is given  in Hartwell  et  al.   (1979).   The modifi-
cations have  had little  impact on the  inferential capabilities of the
network or  the  ability  to  make  comparisons  among  the  fiscal years.

     The  specimens  of adipose  tissue are  collected through cooperation
of  local  pathologists and  medical  examiners.   The  complex  process,
involving several stages  of  selection,  is illustrated in Figure 1.  The
48  conterminous  States   are  stratified  into  nine  geographic regions
coinciding with  the  Census Divisions.  The  stratification ensures that
the  sample  is dispersed across  Census  Divisions,  potentially  improving
the  ability   to  make  regional  estimates  and  the   accuracy  of  national
estimates.  Standard  Metropolitan  Statistical  Areas  (SMSAs) within each
Census Division are the primary sampling units (PSUs), and a total of 40
are  selected  with probability  proportional to their population based on
the  1970  Census.  The number of SMSAs  selected  in each Census Division
(given  in Appendix  A)  is  proportional  to  the total  population of the
Census Division.  Within each SMSA, a cooperating pathologist or medical
examiner  is   solicited  for cooperation  and asked to  select   specimens
according to  EPA  guidelines  (described  in Lucas et  al.  1980).   The
guidelines include a  quota for each pathologist based  on the  age, sex,
and  race distribution of the Census Division; instructions for exclusion
of  "unrepresentative"  patients such  as  ones  suspected  of  pesticide
poisoning or   exhibiting   cachexia;  and  instructions  on  shipping  and
storage.

     The  sample  SMSAs  are  a  valid  probability sample  of SMSAs.  Hence,
it  is  defensible to  present  inferences  about  all   SMSAs  in  the U.S.  if
one has accurate information for sample  SMSAs.   The accuracy and precision
of  these  inferences,  however,  also  depend on  the sampling methodology
within  each SMSA.  Within each SMSA, the  hospitals,  medical examiners'
offices and specimens are selected in a  non-probabilistic manner based
on  the  EPA  guidelines  and judgement of  the  cooperating professionals.
Useful  interpretation of  the  statistical  analysis,  requires   that  we
assume  that all the  tissue  specimens within  each SMSA,  although they
come largely from cadavers, are "representative" of the target population
of  non-institutionalized   persons  living  in  the   corresponding  Census
Division.   All  statements of  significance  included  in  the statistical
analysis  below are based  on  this and other assumption.  Other necessary
assumptions  are stated in the following  sections as appropriate.

     3.1.3  Overview of Weighting

            Because the  PSUs  constitute  a  valid  probability  sample  of
SMSAs,  a  weight  is  assigned  to each specimen  based on  the  selection
protocol  (see Appendix  A).   Adjustments to each weight  for fiscal 1972
through 1979  were then performed to assure that the  sum of all weights
within each  age (0-14, 15-44, 45+), sex  (male,  female), and race (white,
nonwhite)  category  equaled  the appropriate  population  count   for  the
Census  Region according  to  the  U.S. Census.   The  fiscal  1972 survey
design was based  on  the 1960 Census  data,  also, the  weight adjustments
were  based  on  1960  Census  data.   The  survey  designs  for  fiscal 1973
through  1979  were based   on  1970  Census  data.   Because only  a  small
subsample of   fiscal   1981  data is  currently  available,  an  aggregate
                                 -4-

-------
Figure 1.      Sample Stages of the National Human Monitoring Program
        Geographic
        Stratification
        Select Primary
        Sampling Unit
           (PSD)
        Select Secondary
         Sampling Unit
        (SSU) within PSU
        Select Specimen
        within  SSU for
        Specific Age/
        Sex/Race Group
 Group the 48 conterminous States
 into nine geographic areas which
 coincide with the nine Census
 Divisions.
Select from two  to seven SMSAs from
each Census Division for a total of
40.
Select one  (or more) hospitals from
each SUSA.
Select adipose tissue specimen from
cadavers or sugical patients.
                                          -5-

-------
adjustment, which  did  not take into account the age, sex and race cate-
gories, was performed  on the basis of  1980  Census data.  The subsample
of fiscal 1981 tissue specimens was controlled to assure that the propor-
tions  of  specimens in  the  sample  in each category  were similar to the
proportions of persons  in each category given in the 1980 Census.  When
these  adjustments  were  completed,  the weights for each  fiscal year were
inspected to detect extremely large weights.   Large weights were reduced.
The  reduction in  large weights  (trimming)  is  felt to result  in more
accurate population estimates.  A  detailed description of the weighting
procedure is given in Appendix A.

     3.1.4  Summary of Polycnlorinated Biphenyls in Human Adipose Tissue

            PCB levels  in  adipose  tissue are classified into four cate-
gories by the chemical analysis laboratory:  (i) not detected (ND), (ii)
detected but  less  than  1 part per million (ppm) (DLT1), (iii) between 1
and 3 ppm (1-3) and (iv) greater than 3 ppm (GT3).   Because the data are
categorized  in the  above  manner,  it  is  not  possible to  express  the
individual  concentrations   on  a percent  lipid  basis.   However,  it  is
possible to adjust statistically the estimates of the percent of persons
in each  category.   The adjustment is statistically  significant  but the
magnitude of the adjustment is in consequenital.  Hence, all data summar-
ies are on  a  whole specimen (wet weight) basis, not on a lipid adjusted
basis and exclude specimens with less than 10 percent extractable lipid.
The data are first summarized for all years by three demographic factors:
age,   sex,  and race and by  two  geographic factors:   Census  Region and
industry.    The  PCB industry  factor  was defined by  grouping  the tissue
specimens  into  three  categories:   (i) those collected  from  States  con-
taining no  PCB industries,  (ii) those collected from  States  containing
one PCB industry,  and  (iii) those collected from  States containing two
or more PCB industries.   A list of the States in each Census Region and
industry category  is  given  in Appendix B.   Table 1 summarizes the esti-
mated  percentage  of persons  falling  in the four  residue  categories  by
the three  demographic  factors,  the two geographic factors and  over all
factors.   Appendix B  contains  the  same summaries  for  each  fiscal year.

     Inspection of the tables in Appendix B revealed apparent changes in
the percentage of the U.S. population in each residue category by fiscal
year.  Figure 2 presents a chart of the estimated percentage of the U.S.
population  falling  in the  residue categories ND,  DLE3, (DLT1  and  1-3
combined) and  GTS  for  fiscal years 1972 through 1979 and 1981.   Several
trends become apparent:

     (  i)     the  estimated percent  of  persons  in  the  U.S.  without
               detectable  levels  of  PCBs  decreased (the percent  with
               detectable levels increased);

     ( ii)     the estimated percent of persons in the U.S.  with
               detectable levels less  than or equal to 3 ppm increased;
               and

     (iii)     the estimated percent of persons in the U.S.  with
               PCB levels greater than 3 ppm increased until fiscal 1977
               and then began to decrease.
                                 -6-

-------
(The  reader is  cautioned to  note that  the  fiscal  1981  estimates are
based on a  small  subsample of 97 tissue specimens that have been chemi-
cally analyzed at this time.)

     To quantify  the apparent changes over time,  trends  were estimated
for percent  in  the  GT3 category and for percent detected (PD), which  is
the sum of DLT1, 1-3, and GT3.  The trends included a linear term (fiscal
year) and a quadratic term (fiscal year squared).  In addition to inves-
tigating trends, the statistical analysis (see Appendix B) allows one  to
compare the  subpopulations  for each factor and their changes over  time.
The estimated  trends are  descriptive  in nature and  intended  to give a
smoothed picture of the underlying trends, which may be obscured by year
to year fluctuations in the estimates.

     Figures 3  and  4  illustrate  the estimated trends  in  PD.   Figure 3
illustrates  the  trends^, for  the  three  age  groups.   These  trends  were
found to be significant  and increasing but different.  The youngest age
group had  the  lowest PD  in  fiscal 1972 but  increased  more  quickly and
approached the two  older  age groups by  fiscal  1981.   The trends in the
subpopulations  of J:he  other  factors were statistically tested and  found
to be  significant , increasing,  and equal in  both  rate  of change and
amplitude.   Hence, the trend illustrated in Figure 4 adequately describes
the trends  for  both sexes,  both racial groups,  the four Census Regions,
and the three industrial categories.

     Figures 5,  6, and 7 illustrate the estimated trends in GT3.  Figure
5  illustrates  the treads  for the three age  groups.   These  trends  were
found to be significant  but different.  The two older age groups increase
from fiscal  1972  to 1976  and decrease from fiscal 1976 to 1981 with the
oldest group highest.  The youngest age group remains relatively constant.
Figure  6  illustrates  the trends  for  the two.  racial groups.   The two
racial groups were  found  to have significant   trends  of  the same shape
but differing  in  amplitude.   The  trends in  the  subpopulations  for. the
factors sex  and Census Region were also  found to  be  significant   but
differing in amplitude  like  the racial groups.   The^trends in the three
industrial  categories  were found  to be significant  also but equal  in
amplitude when adjusted for  the factor Census Region.  Because there  is
overlap between the two geographic factors,  the amplitudes of the trends
for  the industrial  subpopulations  were  also  tested and  found to  be
different when  not  adjusted  for  the factor  Census Region.   Figure  7
illustrates the overall trend for GT3.

     3.1.5  Limitations of Statistical Inference

            The NATS  survey samples a surrogate  population  of surgical
patients and autopsied  cadavers  instead  of the general U.S.  population.
This is done for sound ethical reasons.  By obtaining specimens from the
sample population no  additional  risk is assigned to persons selected  in
the sample.  However,  because the sampled population  is  different  from
the target population, one must be willing to assume that the prevalence
*
 Assuming no measurement or sampling bias exist.
                                 -7-

-------
                          Table 1  Weighted Percentage Distribution of PCS Residue Levels
oo
in Adipose Tissues for all

Domain


Sample
Size





Population
Estimate
(in thous . )
Age (years):
0 -14
15-44
45+
Sex:
Male
Female
Race:
White
Non-white
Census Region:
Northeast
North Central
South
West
Number of PCB
Industries per
State:
0
1
2+
Overall

1554
2894
4145

4403
4190

7165
1428

2124
2364
2969
1136



2332
2408
3853
8593

56
85
60

101
101

176
27

48
56
63
34



57
58
86
203

,942
,718
,487

,665
,482

,141
,006

,567
,276
,321
,983



,912
,386
,849
,147

Fiscal

Years








•
PCB Residue Levels
Detected
Not but Less Between I...
Detected Than 1 PPM and 3 PPM"
percent (standard error)

10.5
3.0
3.6

5.1
5.5

4.9
7.7

5.8
5.0
5.5
4.4



5.1
4.4
6.0
5.3

(
(
(

(
(

(
(

(
(
(
(



(
(
(
(

1-6)
0.6)
0.7)

0.8)
0.7)

0.6)
1.9)

1.5)
1.2)
1.1)
1.2)



1.1)
1.1)
1.0)
0.6)

76.7 1
59.0 1
51.11

57.4 1
65.8 1

63.3 1
50.4 1

51.6 1
65.8 1
63.2 1
65.8 1



66.4 I
67.7 1
54.3 1
61.6 1

[ 2.6)
[ 2.2)
( 2.3)

[ 2.3)
[ 2.1)

[ 1.8)
[ 3.9)

( 3.5)
[ 3.1)
[ 3.5)
[ 4.2)



( 3.8)
[ 3.0)
[ 2.6)
[ 1.8)

11.3
31.9
36.1

30.8
24.0

26.5
33.3

33.3
24.7
25.9
26.0



23.8
23.7
32.2
27.4

(
(
(

(
(

(
(

(
(
(
(



(
(
(
(

1.7)
2.0)
2.0)

1-9)
1.8)

1.5)
4.1)

3.3)
2.7)
3.0)
4.1)



3.1)
2.7)
2.4)
1.6)
Greater than
3 PPM»

1.4 1
6.2 1
9.3 1

6.8 I
4.7 1

5.3 1
8.7 1

9.2 1
4.5 1
5.3 1
3.7 1



4.7 1
4.2 1
7.5 1
5.8 1

; 0.5)
; 0.7)
: i.o)

: 0.7)
: 0.6)

[ 0.5)
[ 1.3)

( i.o)
[ 0.9)
( 1.0)
: i.D



[ i.o)
[ 0.8)
[ 0.9)
[ 0.5)
   Source:  Calculated by the Research Triangle Institute from the NATS computer accessible data files.




         *    PPM denote parts per million.

-------
Figure 2.
       Estimated Percentage Distribution of U. S. Population
by Adipose Tissue PCB Residue  Category for Fiscal 1972 Through 1981
                                                                                       * 1981  Is a sub-sample of 97 observations.
               LEGEND: ND •=  Not Detected  DLE3 - Detected and Less Than or Equal to 3 PPM  GT3 « Above 3 PPM

-------
 Figure 3.
   133-
 Q
 t
 e
 c
 t
 e
    95-1
P
e
r
c

n   90
t
    85-
    80-
    75-
                      Eatimoted Trends for Percent of PCS Residua Levels Detected
                             by Ago Group for Fiscal 1972 Through  1981
       72       73       74
           LEGEND:  AGE
                                 75
                76       77       78       79       80

               F i sea I  Year

            0-14	15-44      	45-1-
Flgure 4.   Comparison of Estimated and Observed Trends for Percent of PCS Residue Levels Detected
                                  for Fiscal 1972 Through 1981
                                 75
                                                            78
                76       77
              F I sea I  Y
-------
rigur« 5.
    15-
    a-
Ljtimotia  Trtnoi lor Pircinl of PCS R.irtuo Urtil *boy» 1 FPU
        by Ago Croup lor Fiscal 1972 Througn 1981
                                                                               \
     72
              73
                       7<
         LEGEND.  AGE
                               75
                                        76      77
                                      Fi.col  Y.or
                                                         78       79      88       81
  Ftguri 6.
                   ClHmotM Tr.noi lor P«r«nt of PCS R.rtu. Lonli *bo». 3 PPU
                           by Roe* Croup for Tbcfll 1972 Througn 1981



                                                                      \



              73
                               7S
               LEGEND.  RACE
                                        78      77
                                      F i .en I  Y.
-------
and  levels  of  the substances of  interest  (chlorinated hydrocarbon com-
pounds)  are  the  same  in both populations  (age,  sex,  race adjusted) to
make  inferences  from the  sampled population  to  the target population.

     -Other limitations result from the survey design and its implementa-
tion.   Because  cities with  populations  greater  than  25,000 persons or
SMSAs  form  the sampling  frame,  areas that are  rural  in  character are
excluded  from  the  sample.   A  sizable  percent  (38.3  percent  in 1970
(Lucas  RM  et al.  1980)  of  the  U.S.  population  resides  in these rural
areas.   The  real percentage  of  omission is most likely  less, however,
because  the  service areas  of hospitals  in cities -or  SMSAs extend into
neighboring  rural areas.   Obviously, the  urban  nature   of  the  sample
results in an under coverage of the population of interest.

     Limitations also result from the purposeful  selection of cooperating
professionals  and the  lack  of  probability  sampling  used  by  them  in
selecting tissue  specimens within  the  PSUs.    The  purposeful selection
methods may  result  in biases in estimates  derived  from  the sample.  In
an effort to minimize potential biases,  the data  collected in the  network
were  assigned  weights  to be  used  in  the  statistical  analysis.  The
weights can be thought of as the number of persons in the target popula-
tion that each sample specimen represents.  The reader is cautioned that
even  though  the weighting  is felt to  reduce bias; due to  the  lack of
probability  sampling within  the SMSAs,  this  bias is not necessarily
overcome by  the weighting  procedure.   Even the  estimates  based on the
weights may be substantially biased.

     The chemical analysis methods are another potential source of bias.
A detailed description of the current chemical analysis methods for PCBs
is given in Lucas R M et al. (1980).  The report also gives a comprehen-
sive evaluation of the current analytical method which includes extraction
according  to the  modified  Mills-Olney-Gaither procedures  (USEPA 1974
Section 5A[1])  and  analyzed  by gas chromatography with electron capture
detection (GC/ECD) on  two columns.   The report  (Lucas R  M et al. 1980)
also  contains  a brief  assessment of the analytical method,  thin layer
chromatography  (TLC)  (USEPA  1977 and Mulhern et al. 1971) used prior to
November  1974.   The  measurement errors  for  the techniques  are quite
large.   For the  TLC  method the  error  is  estimated  to  be  ±50  percent
(Lucas  R M  et  al. 1980) and  for the  GC/ECD method ±  50 percent is the
best-case estimate and  ±100  percent is felt to be a reasonable estimate
of the measurement error in this particular application.   The measurement
errors  can  be partitioned  into  two  components,  systematic errors that
bias estimates and random errors that affect the precision of estimates.
The  statistical  analysis  techniques  properly  incorporate  the   random
component in the estimates of precision.   However, any systematic  errors
that may exist could not be accounted for in the analysis.

     To  obtain  some  insight into how biases may  affect  the conclusions
with  regard  to trends  and differences  among  demographic  or geographic
groups,  additional  material  is  presented below.   First  the trends are
investigated  for  fiscal  1976  through 1981  to  assess  the  effect of the
change  in chemical analysis.
                                 -12-

-------
     To  investigate  the  impact  on trends  resulting  from the change  in
chemical  analysis  methods,  trends were  estimated  for the categories  PD
and GT3 using only fiscal 1976 to  1978 and  the  1981 subsample.  Figure 8
presents  the  estimated  percentage of the U.S.  population  falling  in  the
three residue categories ND, DLT3  and GT3.

     Figures  9  and  10  present  the  estimated  trends  for  the  residue
categories  PD and  GTS   respectively.  The  trends  illustrated  in  these
figures are  consistent  with the trends  estimated  using  all nine  fiscal
years of  data.   Hence,  the change in chemical  analysis  method does  not
have a  noticable  impact on the estimated trends for  fiscal  1976 through
1981.   Because the  analytical  technique  did not  change  during the last
six years, the minimal detectable  level should  not substantially change,
and thus, should have little effect on the PD trend.
                                       J.
     The  trends are  highly  significant   (the probability of no trend  iSj.
very small) and the two  racial groups and sexes are highly significantly
different for GTS.   Tables  2 and  3 summarize the results of the statis-
tical  tests.   Because  of  the  relatively  high levels  of significance
here,  it  is  unlikely  that actual biases  in  the  population estimates
would change  the  conclusion about trends or  race  and sex group differ-
ences.   Biases are more  likely to  have an effect on the conclusion about
the different trends  for the age  groups  in PD  and for differences among
the  Census  Regions.   A  table  is  given  in Appendix  B  illustrating  the
effect of bias on the significance level  of statistical test.

     The  potential  for   bias  is  a two-edged  sword.   Biases  may mislead
the  investigator into making  false conclusions, but  biases  in the data
may also hide real differences in  the population and mislead the investi-
gator into believing that no differences  exist when in fact they do.   It
is  impossible  to  estimate  the  magnitude or direction of  biases  in  the
present situation,  if they exist, with the available information.

3.2  Polychlorinated Biphenyls in Human Milk

     3.2.1  General Description of the Study

            This  section summarizes  the  data present in  a special pro-
ject  report  on PCBs  in human milk  (SPR 1977).   The survey  design   is
described in  Savage  et  al.  (1981) and  was originally targeted  at five
chlorinated hydrocarbon  insecticide  residues.   Approximately 72 percent
of  the  milk  specimens  had sufficient volume to permit a  second chemical
analysis  for  PCBs.   The  chemical  analysis method  is described  in SPR
1977.

     3.2.2  Overview of the PCBs in Human Milk Study Design

            A total  of  163  hospitals  was randomly  selected  from  a list
of approximately 7,000 general care hospitals in the United States.  The
hospitals  were  grouped  into five geographic  regions:   (i)  Northeast,
(ii) Southeast, (iii) Midwest,  (iv)  Southwest, and (v) Northwest.   From
the  selected  hospitals, a  subsample  of  nursing  mothers who  had  given
*
 Assuming no measurement or sampling bias.
                                 -13-

-------
     Figure 8.            Estimated Percentage Distribution of U.S.  Population
                by Adipose Tissue PCB Residue Category for Fiscal 1976 Through 1981
                                     BLOCK CHART OF PERCENT
                              Fiscal Y«or

                                      *
                                   1981
                                              £17
                                               a
                            1878
                     1878
              1977
       1976
                                                             99
                                                90
                                         89
                                                       ie
                                  90
                NO
   PLE3           6T3

L.v.l of PCB
                                                              * 1981 Is a sub-sample of 97  observations.
LEGEND: ND ~ Not Detected   DLE3 •» Detected and Less Than or Equal to 3 PPM   GT3 - Above 3 PPM

-------
 Figure 9.  Comparison of Estimated  and Observed Trends for Percent of PCS Residue Levels Defected
                                      for Fiscal 1976 Through 1981
          I 00.0-
                              77            78             79             80

                                               FI sea I  Year

                               LEGEND:   •  Observed    	  Estimated
                                                           81
Figure 10. Comparison  of Estimated and Observed Trends for Percent of PCB Residue Levels Above 3 PPM
                                          for Fiscal  1976 Through  1981
         10.0-J
              76
77
             78            79

               F I sea I  Year

LEGEND:   • Observed    - Estimated

             -15-
80

-------
       Table 2.   Significance Levels  of Estimated Trends in PCBs
                 for Fiscal Years 1972 through 1981**
                                          Probability  of No Trend
Trend                              Percent             Percent Greater
                                   Detected              Than 3 ppm

Linear Term                         .0000                   .9519

Quadratic Terra                      .0017                   .0000


                                              *
                                   Probability  of Equal Trends
                                   	Among Age Groups	

Linear Terra                         .0307                   .3753

Quadratic Term                      .0857                   .0000


*    Assuming no measurement or sampling bias.

**   Source:  Calculated by the Research Triangle Institute from the
              National Adipose Tissue Survey sponsored by the U.S.
              Environmental Protection Agency.
                    "V
NS   Not significant , probability > .05.
                                 -16-

-------
                                      -.V
         Table 3.  Significance Levels  of Estimated Effects of
                   Demographic and Geographic Factors**
*
Probability that the Subpopulations within
Each Factor are Equal
Factor
Age Group
Race
Sex
Census Region
Industry
Percent Detected
NA
.1362
.8267
.8725
.1157
Percent Greater than 3 ppm
NA
.0005
.0003
.0397
.4373
*    Assuming no measurement or sampling bias and adjusted for the o.ther
     factors.

**   Source:  Calculated by the Research Triangle Institute from the
              National Adipose Tissue Survey sponsored by the U.S.
              Environmental Protection Agency.

NA   Because the difference among age groups changes by fiscal year, it
     is not appropriate to test for this effect.
                                  -17-

-------
birth  in  the selected  hospitals  were  solicited  for cooperation.  Milk
specimens were collected from 1,436 participants.

     3.2.3  Limitations of Statistical Inferences for PCBs in Human Milk

            The available material is not sufficiently detailed to fully
evaluate the survey design or to incorporate the design into the  statis-
tical analysis.  Also,  the  statistical method used to summarize  the PCB
data presented in  SPR 1977  are not described.  Hence, there is insuffi-
cient information to fully evaluate the limitations of making inferences
from the sample  data  to the target population of nursing mothers giving
birth in U.S.  general care  hospitals during the study period.  However,
one  important  limiting factor  is  the  fact  that a  nonrandom subsample
(only specimens with sufficient volume for the second chemical analysis)
of  1,033 milk  specimens were analyzed for PCBs from the original 1,436.
This  admits  the  possibility of  biases  which might  result  in  making
inferences to  the  intended  target  population.  Hence,  statements that
the levels measured in the sample are indicative of those one would find
in the target population may be misleading.

     3.2.4  Summary of Polychlorinated Biphenyls in Human Milk Data

            To summarize  the  levels  of PCBs in human milk, the measured
values are  grouped into  the  three categories:  (i)  not  detected (NTJ),
(ii)  trace  (detected  but less  than 0.05 parts per  million  (ppm)),  and
(iii) positive (greater than  0.05  ppm).  Table 4 contains these  summar-
ies  by  the  five geographic  regions  (not  Census Regions)  and overall.
The Northeast and  Southeast  have  the highest percent positive (38.2 and
37.7  percent respectively)  and the  Southwest  region the  lowest (21.5
percent).  The maximum positive value  (not  adjusted  for  percent lipid)
was 0.563 ppm in Texas in the Southwest region.  In comparing this human
milk data with the adipose tissue data, both similarities and differences
are  noticable.   The percent  of specimens containing  detectable^ levels
(99.1 percent) are  similar,  but the  levels  in  milk  are much lower than
the levels in adipose tissue.

     The data  given  in  SPR  (1977) also  included  the  positive   amounts
adjusted  for percent lipid.  These  adjusted data were  not  included in
this  report  because  of noncomparability with  the adipose  tissue  data
that could not be directly adjusted for percent lipid.
                                 -18-

-------
        Table 4.  Summary of Polychlorinated Biphenyls in Human Milk
Region
Levels
(parts per
million)
Not Detected
Trace
Positive
Sample Size
Northeast
percent
2.2
59.7
38.2
186
Southeast
percent
0.0
62.3
37.7
159
Midwest
percent
1.0
70.6
28.4
289
Southwest
percent
0.7
78.5
20.9
297
Northwest
percent
0.0
67.6
32.4
102
Total
0.9
69.3
29.8
1033
  Source:  Calculated by the Research Triangle Institute from data provided
           by the U.S. EPA (SPR 1977).
_i_i_
  Greater than the minimum quantifiable level of 0.05 parts per million
in whole milk.
                                  -19-

-------
4.    REFERENCES
Hartwell T,  Piserchia  P,  White SB et  al.  1979.   Analysis of EPA Pesti-
cides Monitoring Networks.   Prepared by the Research Triangle Institute
for  the  Office of  Toxic  Substances.   U.S.  Environmental  Protection
Agency.  Washington, DC 20460.  EPA-560/13-79-014.

Inglis A  1982.   Personal  communication with Anthony Inglis of the Expo-
sure Evaluation Division,  Office of Toxic Substances, U.S. Environmental
Protection Agency.   Washington, DC  20460.

Lucas  D,  Mason RE,  Rosenzweig M et al.  1980.   Recommendations  for the
National  Surface  Water  Monitoring  Program  for Pesticides.   Research
Triangle    Institute,     Research    Triangle    Park,    NC     27709.
RTI/1864/14/01-01I.

Lucas  RM,  Rosenzweig MS,  Williams  SR  et  al.  1980.   Evaluation of and
Alternate Designs  for  the  National  Human Monitoring  Program's  Adipose
Tissue Survey.  Research Triangle  Institute,  Research Triangle Park, NC
27709.  RTI/1864/14/02-02I.

Lucas, RM, Erickson, MD  and Williams, SR  1980B.  PCB Residue Levels in
Human  Adipose  Tissue:   A  Statistical Evaluation  By Racial  Grouping.
Prepared  by   the Research   Triangle  Institute for  the Office of  Toxic
Substances,   U.   S.   Environmental  Protection  Agency.   Washington,  DC.
EPA/13-79-015.

McDonald M,  Hardy M, Drummond D  1981.  National  Soil Monitoring Program:
Urban  Soils  Monitoring Network.  Research Triangle  Park,  NC:   Research
Triangle Institute.  RTI/1864/14/03-02I.

Mulhern  BM,   Cromartie E,   Riechel  WE,  Belisle  AM.   1971.   JAOAC  54:
548-550.

SPR  1977.   Special Project Report:  Polychlorinated  Biphenyls  in  Human
Milk.  (Unpublished document describing analysis  of PCB from a subsample
of the milk  specimens  collected in Savage et al. 1981)  Provided to the
Research Triangle Institute by the U.S. Environmental Protection Agency.

Savage EP, Keefe TJ, Tessari JTJ et al. 1981.   National Study of  Chlori-
nated  Hydrocarbon   Insecticide Residues  in Human  Milk,  U.S.A.   Am  J
Epidemiol 1981; 113:1413-22.

Schmitt, CJ,  Ludke,  JI and Walsh,  D (1981).   Organochlorine residues in
fish,  1970-1974, National  Pesticide  Monitoring Program.   Pestic. Monit.
J. 14(4): 136-206.

USDA 1966.  National Handbook for Updating the Conservation Needs Inven-
tory United States  Department of Agriculture.

USEPA  1977.  U.S.  Environmental  Protection  Agency.  Analysis of pesti-
cide  residue  in human  and  environmental  samples, section 9D.   Research
Triangle Park, NC.   U.S.  Environmental Protection Agency.
                                 -20-

-------
USEPA  1974.  U.S. Environmental Protection Agency.  Analysis of pesticide
residue in human and environmental samples.  Research Triangle Park, NC:
U.S. Environmental Protection Agency.

USGA  1980.    National  Water  Data  Exchange.   U.S.  Geological  Survey.
Reston, Virginia.

Whitmore R, Rosenzweig M,  and Hines J   1981.   National  Soil Monitoring
Program.   Research  Triangle  Park,  NC:   Research Triangle  Institute.
RTI/1864/14/03-01I.
                                 -21-

-------
          Appendix A




Sampling Weighting Methodology

-------
                               Appendix A.

                      Sample Weighting Methodology

A.1  Introduction

     The  true  probability of  selection for  specimens  collected in the

adipose  tissue  network could  not be calculated  because  some stages of

the  sample  selection  involved   nonprobability  sampling.  Even  if the

selection probabilities of  a  specimen within sample cities were assumed

to be  equal, the  sample  design  of the NHMP  adipose  tissue network did

not  give  a  self-weighting  sample with regard to  the living population

because  of  discrepancies  between samples and the  quotas.   Therefore,  a

weight was  calculated  for  each  specimen that  reflects  its approximate
                        •(V
probability  of  selection  .   Including these weights in the analysis may

reduce bias in  estimating  means  or  proportions.   The  following para-

graphs describe  the procedures  used  for computing  approximate weights

for the NHMP data.

A.2  Initial Sample Weights

     The calculation of the initial sample weights considered two stages

of selection. In the  first stage, primarily  sampling units (PSUs)  were

selected within each stratum with probability approximately proportional

to their  population.   Table A.I  gives  the number of PSUs  specified by

the survey design for the fiscal years.   In the second stage, samples of

cadavers  and  surgical patients  were  selected  in  a  nonprobabilistic

manner from  a hospital(s) or other facility located in the sample cities.
                                 *
Equal  probabilities  of selection  were assumed  for  this  stage.  Table

A.2  gives  the number  of  tissue  specimens  included in  the statistical
                                   •
analysis by  fiscal year.
 Probabilities of  selection  at the final stage are  with reference to a
sampling rate  for  the living population rather than for the population
of cadavers and surgical patients.
                                 A-23

-------
        Table A.I.  Number of Primary Sampling Units  Per Stratum
                    by Fiscal Year as Specified by Survey Design*""
Fiscal 1972

Census Region

Northeast
North Central
South
Westt

Total

Fiscal 1973-1981


Census Division
     Number

       11
       12
        9
       _7

       39
Fiscal 1973-1976
Number
Percent
                         Percent

                          28.2
                          30.8
                          23.1
                          17.9

                         100.0
                  Fiscal 1977-1981
Number
Percent
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific!
Total
4
14
15
6
11
5
7
3
10
75
5.3
18.7
20.0
8.0
14.7
6.7
9.3
4.0
13.3
100.0
2
7
8
3
6
3
4
2
5
40
5.0
17.5
20.0
7.5
15.0
7.5
10.0
5.0
12.5
100.0
 *   For fiscal years 1972 through 1976 the primary sampling units were
     cities with populations over 25,000 persons and from fiscal 1977
     to 1981 the PSUs were Standard Metropolitan Statistical Areas
     (SMSAs).

**   Source:  Hartwell et al, 1979.

t    Excludes Alaska and Hawaii.
                                 A-24

-------
             Table A.2.  Number of Tissue Specimens Used in
                         Statistical Analysis by Fiscal Year
          Fiscal Year                        Number

             1972                             1826

             1973                             1183

             1974                             1025

             1975                              895

             1976                              779

             1977                              927

             1978                              951

             1979                              910

             1981                               97

             Total                            8593
 Source:  Calculated by the Research Triangle Institute from the
National Adipose Tissue Survey's computer accessible data files
sponsored by the U.S. Environmental Protection Agency.
                                 A-25

-------
     The initial  sample  weight for specimen  (j)  in PSU (i) and stratum

(h) was calculated as the inverse product of  the approximate probabilities
            *
of selection  for each stage and is expressed as

          W1(hiJ)= [PhiPj|hir1'
where P   denotes  the probability of selecting the i-th PSU in the h-th

stratum (for  large  PSUs  selected with probability  1  this  is more accu-

rately described  as  the  expected number of times the PSU is selected in

the  sample);  and P.i. .  denotes  the  sampling rate of  specimens  to the

living population given PSU (i) in stratum (h).

     The PSUs were selected independently within each stratum.  For each

stratum, the cumulative total population of eligible PSUs was divided by

the number of PSUs to be selected in the h-th stratum.  This calculation

gave  the  sample  selection  interval.   A  random  start was  obtained  by

selecting a  random number  between  "1" and  the value  of  the selection

interval.    The  method  then involved  listing  the  cities  in  a  random

order, calculating the cumulative totals and selecting cities by matching

the cumulative totals  to  the random start and  integer multiples  of the

selection interval plus the random start (USEPA 1973).

     The above can be expressed algebraically  in  the following manner.

For each stratum, the selection interval is

          :h = Vv
where  I, ,  N, ,  and m,  denote the  selection interval,  cumulative  pop-
        h    h         h
ulation total, and  number  of PSUs to be  selected  for the h-th stratum,

respectively.  The  PSUs  selected  in the sample are  those  for which the

cumulative totals  match  r   + K x I  for K=0,	mh~1( wnere rh is tne

random start for the h-th stratum.
y-
 Probabilities of  selection  at the final stage  are  with reference to a
sampling rate for the living population rather than for the population of
cadavers and surgical patients.
                                 A-26

-------
     This method  assigned  a probability of  selection  to each PSU equal



to  the  population of  the  PSU divided by  the  selection interval.  This



can be expressed algebraically as



          P.. = N../L.
           hi    hi  h'


where N, . denotes  the  population of the PSU (i) in stratum  (h)  and P..



and I,  are defined above.
     h


     Under the  assumption  made  above for  selection  of samples within a



PSU,  the calculation  is  straightforward.  The  pseudo  probability  of



selection is  given by  dividing  the number of specimens  selected  in each



PSU by  the population  of the PSU.   This  can be expressed algebraically



as



          P .  ., .   = n, . /N, .
           j|hi     hi   hi


for j=l,  ..., n, ., were n,  . denotes the  number of samples collected in



the i-th  city in the  h-th  stratra and  P.,, .  and N, .  are defined above.
             3                          jI hi       hi


     The initial weight can be written as



          Wl(hij) = [N^xn^/N^r1,



which simplifies to



          Wl(hij) = yn^



Hence,  the  approximate initial  sampling  weight for the PSU  (i)  in the



stratum  (h)  is  the  same  for all  samples  collected in  the  city  and is



calculated by  dividing the  selection  interval  for  the  h-th  stratum by



the number of specimens collected in the city.



     The  method  described  above  does  yield   selection  probabilities



proportional to  the  population  of the PSUs when certain precautions are



followed.  Adequate methods  for  selecting alternate (substitute) cities



were not  taken.   Hence,  the procedures followed in  the study alter the



probability  of selection for some PSUs, but the degree,  although probably
                                 A-27

-------
minor,  is undetermined.   For  the  purpose  of calculating  approximate

weights,  these  special  situations  were treated the  same  as  all others.

A.3  Missing Data Adjustments and Poststratification

     Survey estimates of means and proportions may be biased if specimens

that  were identified  for  selection,   but  not collected,  had  different

levels  of PCB   residue  than  those  actually collected.   Furthermore,

estimates of population totals will be underestimated unless some allow-

ance is made  for the loss  of the missing  data.   Therefore,  the initial

sample weights  were  adjusted  by stratum so  that  the sum of the weights

equaled national Census population counts in each stratum.  This included

only those data  that were  suitable for  statistical  analysis.   Data was

classified as suitable  for  analysis by percent extractable  lipid  (> 10

percent) and valid chemical  analysis confidence codes.

     The missing data  adjustment  process began with the definition of a

response indicator for specimen (k)  of the form
          RESP(k) =
1  if specimen (k) had data suitable
for analysis
                           0  otherwise.

     Missing data occurred at different rates among demographic domains.

Therefore,  ratio adjustments  to  the  initial  weights  were made  within

demographic domains  referred to  as  poststrata.   These  poststrata were

formed by crossing some  or all  of  the  following  classification  vari-

ables :

          Fiscal year: 1972,...,1979,1981

          Census Region:  North East, North Central,  South, West

          Age Group: 0-14,  15-44,  45+

          Race: White, Non-White

          Sex: Male, Female


                                 A-28

-------
Once a poststratum (£) was formed, N(£), the Census population count  for

that poststratum, was  obtained.   The Census counts used depended on  the

fiscal year the sample data were obtained.  Fiscal 1972 used 1960 Census

data (US  Census  1960),  while fiscal  1973  through  fiscal  1979 used 1970

Census data  (US Census  1970).   The  fiscal  1981  sample was partitioned

into poststrata formed by the nine Census Divisions and used 1980 Census

data (US Census 1980).

     The Census counts for each poststratum were divided by the weighted

number of tissue  specimens   to  form  a  poststratum  adjustment  factor:

          ADJU) = N (2) / [I Wl(k) • RESP(k)],
                            ke£

where ke£  indicates  that the summation is  over  all  specimens belonging

to poststratum (£).

     Each  responding  specimen (k)  received an  adjusted  sample  weight,

W2 (k),  which  was its  poststratum adjustment factor  times its  initial

sample weight:

          W2(k) = ADJ(£) ' Wl(k).

Hence,  within  a  poststratum, the  sum of  the adjusted  sample  weights

equaled the corresponding Census population count.

     Excessive sampling variances may be caused by unequal weighting ef-

fects.  Therefore, a  maximum  increase of fifty percent over the standard

deviation of an  equally weighted sample was imposed on each of the nine

fiscal year samples.   Because fiscal  1972, 1973,  and 1976 had unacceptable

unequal weighting  effects under  this rule, the  following calculations

were undertaken to reduce the extreme values among the weights for these

fiscal years.

     First,  the  poststratum  containing  the largest adjusted  weight in

the  fiscal years  was found.   Next, this largest adjusted weight was set


                                 A-29

-------
equal  to  the  second largest  adjusted  weight  within  the  poststratum.




Then, the difference between these two largest weights was spread equally




over  the  remaining  adjusted  weights  in  the poststratum.   This  weight




trimming process  reduced the  unequal  weighting effect  for  fiscal 1973




and  1976  to below  50  percent.  The unequal  weighting  effect for fiscal




1972 was still 57  percent after trimming, but was considered acceptable




since  there  were  several  large  weights.  The adjusted  weight  sums for




the affected poststrata remained equal to their Census population counts




and  the  resulting  mean  square  errors of  estimation should  be  reduced




using the trimmed weights.
                                 A-30

-------
A. 4  References


USCENSUS.  1980.  U.S.  Census  of  Population,  Supplementary  Reports.
PC80-51-1, Table 2.

USCENSUS. 1970. U.S. Census of Population, U.S. Summary PC(1) IB, Table 57.

USCENSUS. 1960. US Census of Population, U.S. Summary PC (1) IB, Table 52.

USEPA. 1973. U.S.  Environmental  Protection Agency.  Listing of eligible
cities  with cumulative  populations,  selection  intervals, and  random
start  numbers.  Washington,  D.C.:  Office  of  Pesticides and Toxic  Sub-
stances, U.S. Environmental Protection Agency.
                                 A-31

-------
                      APPENDIX B

Statistical Methods Used in Analysis of Polychlorinated
              Biphenyls in Adipose Tissue

-------
                               Appendix B

           Statistical Methods in Analysis of Polychlorinated
                       Biphenyls in Adipose Tissue
B.1  Statistical Analysis of Polycfalorinated Biphenyls in Human
     Adipose Tissue

     The  statistical  analysis  that was performed  on  PCB residue levels

used  the  NATS  computer accessible  data  files  and  software  that  was

specifically developed to take into account the survey design and weights.

Estimates of  the percentage  of  the U.S.  population  in  the PCB residue

categories  for  geographic,  demographic,   and overall  categories  are

produced.   These estimates were computed using a software package called

SESUDAAN  (Shah  1979).   Tables  B.I through B.9 summarize these estimates

by  fiscal  year.  Table  2  in  chapter  three summarizes  these estimates

over all fiscal years.

     To investigate differences  among  the  categories for PD and percent

GTS and their changes over time,  statistical models were developed using

a  software  package called  SURREGR (Holt 1977).   Before  the models  are

discussed,  it  is important  to note that because  of  the limitations of

the survey  design,  implementation and  chemical analysis, all statements

of  statistical  significance are  asterisked.   The purpose  is to remind

the  reader  that  unverified assumptions  about  the   survey  design  were

required  to assign weights  to the specimens  collected  in  NATS and to

estimate  the precision  of  the estimates.   Additional reservations about

the statistical significance result from the potential bias in population

estimates that may result from the chemical analysis  limitations.
                                B-33

-------
                   Table B.I   Weighted Percentage Distribution of PCB Residue Levels
in Adipose

Domain


Sample
Size


Tissues

for Fiscal Year 1972


Population





PCB Residue Levels
Estimate
(in thous . )
Age (years):
0 -14
15-44
45+
Sex:
Male
Female
Race:
White
Nonwhite
Census Region:
Northeast
North Central
South
West
Number of PCB
Industries per
State:
0
1
2+
Overall

223
446
1157

1029
797

1501
325

630
476
486
234



462
419
945
1826

55
70
52

89
89

159
20

44
51
54
28



69
32
77
179

,786
,920
,626

,990
,342

,081
,252

,678
,628
,973
,053



,863
,337
,133
,332
Not Less than
Detected 1 PPMt
percent (standard

11.7
7.0
9.8

8.0
10.6

9.0
11.5

11.2
13.1
6.1
5.3



6.2
10.4
11.6
9.3

( 3.3)
( 2.1)
( 2.7)

( 1.5)
( 2.0)

( 1.6)
( 3.9)

( 3.5)
( 3.6)
( 2.5)
( 1.7)



( 2.4)
( 3.0)
( 2.5)
( 1-6)

42.2
24.6
22.0

27.6
31.0

29.5
27.4

15.9
35.8
28.0
41.3



33.8
30.0
24.9
29.3

( 6.6)
( 4.1)
( 3.2)

( 4.3)
( 3.5)

( 3.2)
( 6.3)

( 6.1)
( 6.0)
( 5.0)
(12.4)



( 5.0)
( 9.4)
( 5.0)
( 3.3)
Between 1
and 3 PPMt
error)

44.2
63.3
63.4

58.3
56.5

57.6
55.8

67.7
48.1
60.1
52.8



55.4
55.9
59.8
57.4

( 4.9)
( 4.0)
( 3.8)

( 3.6)
( 3.9)

( 3.1)
( 6.1)

( 8.0)
( 3.0)
( 3.4)
(12.6)



( 3.0)
( 7.8)
( 6.0)
( 3.1)
Greater than
3 PPMt

2.0 I
5.1 1
4.8 {

6.2 1
1.9 I

3.9 1
5.3 1

5.3 1
2.9 1
5.8 1
.6 1



4.6 1
3.8 1
3.6 1
4.0 I

[ 1-4)
[ 1.7)
[ 0.9)

[ 1-9)
[ 0.6)

[ 1-1)
[ 2.0)

[ 2.8)
[ 1.2)
[ 2.4)
[ 0.3)



[ 2.0)
[ 1.5)
[ 1.7)
( l.D
t parts per million
^Standard error not estimable.
Source:  Calculated by the Research Triangle Institute from the National Adipose
         Tissue Survey's computer accessible data files.

-------
                       Table B.2  Weighted Percentage  Distribution  of PCB Residue Levels
at
I
u>
Ul
in Adipose

Domain


Sample
Size


Ti ssues

for Fiscal Year 1973

Population






PCB Residue Levels
Estimate
(in thous . )
Age (years):
0 -14
15-44
45+
Sex:
Male
Female
Race:
White
Nonwhite
Census Region:
Northeast
North Central
South
West
Number of PCB
Industries per
State:
0
1
2+
Overall

188
419
576

549
634

1026
157

204
359
439
181



282
390
511
1183

57
83
61

101
102

176
26

49
56
62
34



52
61
89
203

,900
,A37
,875

,12A
,088

,3A5
,867

,041
,572
,795
,804



,AA8
,080
,684
,212
Not Less than Between 1
Detected 1 PPMt and 3 PPMt
percent (standard error)

26.8
13.6
15.4

18.0
17.9

15.8
31.8

19.0
11.1
24.1
16.5



21.5
13.2
19.1
17.9

( 5.9)
( 3.7)
( 3.8)

( 4.0)
( 3.7)

( 2.9)
(10.3)

(11.1)
( 3.7)
( 5.8)
( 7.3)



( 6.7)
( 3.5)
( 6.6)
( 3.6)

61.3
45.9
33.6

38.7
54.3

49.1
29.7

34.5
51.9
47.4
53.2



49:5
53.2
40.3
46.5

( 6.4)
( 4.3)
( 3.8)

( 3.9)
( 4.1)

( 3.6)
( 7.0)

(11.2)
( 5.7)
( 4.7)
( 6.0)



( 6.7)
( A. 3)
( 6.3)
( 3.5)

9.7
36.4
41.8

37.1
23.8

30.8
27.7

39.7
32.1
23.6
27.0



26.2
28.1
34.5
30.4

( 2.8)
( A. 2)
( 3.7)

( A.I)
( 2.9)

( 3.2)
( 5.3)

( 9.2)
( 6.3)
( 3.0)
( A. 6)



( A. A)
( 5.5)
( 5.2)
( 3.0)
Greater than
3 PPMt

2.1 1
A.I {
9.2 1

6.2 1
A.O (

A. 2 I
10.8 (

6.8 I
5.0 1
A. 9 1
3.3 1



2.9 1
5.5 1
6.1 1
5.1 1

: 1.4)
: 1.3)
: 1.6)

: 1.3)
: i.o)

: 0.9)
: 2.8)

: 2. A)
: 2.3)
; i.D
: 2.1)



: I.D
: 2.1)
[ 1.5)
( 1.0)
    t parts per million
    "•^Standard error not estimable.
    Source:  Calculated by the Research Triangle  Institute  from the National Adipose
             Tissue Survey's computer accessible  data  files.

-------
                       Table B.3  Weighted Percentage Pi stribut ion of PCB Residue Levels
td
I
a.
in Adipose Tissue

Domain


Sample
Size



for Fiscal Year 1974

Population






PCB Residue Levels
Estimate
(in thous.)
Age (years):
0 -14
15-44
45+
Sex:
Male
Female
Race:
White
Nonwhite
Census Region:
Northeast
North Central
South
West
Number of PCB
Industries per
State:
0
1
2+
Overall

207
362
456

521
504

868
157

225
304
374
122



242
306
477
1025

57
83
61

98
104

177
26

49
56
62
34



49
64
89
203

,900
,437
,875

,912
,300

,066
,146

,041
,572
,795
,804



,439
,057
,716
,212
Not Less than Between 1
Detected 1 PPM t and 3 PPM t
percent (standard error)

19.1 I
5.5 I
6.3 1

9.8 1
9.5 1

9.2 1
12.8 1

13.5 1
13.4 1
6.5 1
3.9 1



12.0 1
8.0 I
9.5 I
9.6 I

( 5.6)
[ 1.9)
[ 2.6)

[ 2.9)
( 2.7)

[ 2.2)
[ 5.0)

[ 5.4)
[ 5.3)
( 2.4)
( 2.2)



( 5.3)
( 2.9)
( 3.4)
( 2.2)

72.9
50.7
41.7

49.3
59.1

55.5
46.0

40.7
55.0
57.4
66.7



60.3
57.2
48.9
54.3

( 6.5)
( 4.2)
( 4.3)

( 3.5)
( 3.3)

( 2.8)
( 7.3)

( 4.9)
( 4.8)
( 3.6)
( 8.9)



( 6.7)
( 2.9)
( 4.5)
( 2.6)

8.0
38.6
43.8

36.9
26.3

30.9
35.4

37.8
28.7
31.2
27.4



22. 4
32.3
35.8
31.4

(1.9)
(4.2)
(3.9)

(4.1)
(2.9)

(2.9)
(5.7)

(6.5)
(4.5)
(3.5)
(9.2)



(4.3)
(3.9)
(5.1)
(2.8)
Greater than
3 PPMT

0.0
5.2
8.1

4.0
5.2

4.5
5.7

8.0
3.0
4.9
2.0



5.3
2.4
5.8
4.6

( * )
( 1-6)
( 2.5)

( 1.0)
( 1.9)

( 1-3)
( 2.0)

( 4.1)
( 1.4)
( 1.7)
( 1.1)



( 2.3)
( 0.8)
( 2.3)
( 1.2)
    t parts per million
    "'Standard error not estimable.
    Source:  Calculated by the Research Triangle Institute from the National Adipose
             Tissue Survey's computer accessible data files.

-------
                   Table B.5  Weighted Percentage Distribution of PCB Residue Levels
in Adipose Tissue

Domain


Sample
Size



for Fiscal Year 1976


Population






PCB Residue Levels
Estimate
(in thous.)
Age (years):
0 -14
15-44
45+
Sex:
Male
Female
Race:
White
Non-white
Census Region:
Northeast
North Central
South
West
Number of PCB
Industries per
State:
0
1
2+
Overall

165
248
366

397
382

642
137

229
205
254
91



181
216
382
779

57
83
61

97
105

177
25

49
56
62
34



42
63
96
203

,900
,437
,875

,391
,821

,887
,325

,041
,572
,795
,804



,997
,566
,649
,212
Not Less than Between 1
Detected 1 PPMt and 3 PPMt
percent (standard error)

4.5
0.5
0.0

1.8
1.3

1.2
3.7

0.1
2.1
1.4
2.6



0.3
1.7
1.9
1.5

(
(
(

(
(

(
(

(
(
(
(



(
(
(
(

1.8)
0.5)
* )

0.8)
0.8)

0.7)
2.5)

0.1)
1.9)
1.0)
1.0)



0.3)
1.0)
1.1)
0.6)

86.6
56.3
52.4

56.5
70.4

64.2
60.3

47.4
77. 1
62.5
67.2



81.8
69.3
52.0
63.7

( 3.4)
( 2.6)
( 5.1)

( 4.2)
( 3.7)

( 2.8)
( 6.5)

( 3.0)
( 6.1)
( 5.4)
(10.1)



( 3.6)
( 6.1)
( 3.4)
( 2.8)

7.7
35.7
34.1

32.4
22.5

27.8
23.4

37.0
19.5
29.5
22.2



15.5
25.2
33.9
27.3

( 2.6)
( 2.9)
( 4.7)

( 3.6)
( 3.6)

( 2.6)
( 5.1)

( 5.0)
( 5.7)
( 4.6)
( 5.6)



( 3.2)
( 5.3)
( 3.4)
( 2.5)
Greater than
3 PPMt

1.2
7.4
13.4

9.3
5.8

6.8
12.6

15.5
1.3
6.5
8.0



2.4
3.8
12.1
7.5

( 0.8)
( 2.2)
( 3.0)

( 2.1)
( 2.0)

( 1.5)
( 3.6)

( 3.4)
( 0.6)
( 2.5)
( 5.2)



( 1.8)
( 2.2)
( 2.5)
( 1.5)
t parts per million
"^Standard error not estimable.
Source:  Calculated by the Research Triangle Institute from the National Adipose
         Tissue Survey's computer accessible data files.

-------
                         Table  B.4   Weighted  Percentage  Distribution of  PCB Residue Levels
w
u>
00
in Adipose Tissue

Domain


Sample
Size



for Fiscal Year 1975

Population






PCB Residue Levels
Estimate
(in thous . )
Not
Detected
Less than
1 PPM t
Between 1
and 3 PPM T
Greater than
3 PPMt
percent (standard error)
Age (years):
0 -14
15-44
45+
Sex:
Male '
Female
Race:
White
Nonwhite
Census Region:
Northeast
North Central
South
West
Number of PCB
Industries per
State:
0
1
2+
Overall
163
304
428

445
450

747
148
206
339
231
119


222
256
417
895
57
83
61

98
104

177
26
49
56
62
34


46
69
86
203
,900
,437
,875

,912
,300

,067
,145
,041
,572
,795
,804


,815
,481
,916
,212
19.7 1
1.5 1
0.7 1

6.9 1
6.0 1

6.5 1
6.0 1
7.0 I
4.6 1
7.1 1
7.5 1


3.5 1
6.8 1
7.7 1
6.4 1
[ 6.8)
[ 0.7)
; o.4)

[ 3.1)
[ 2.0)

[ 2.6)
[ 2.3)
[ 3.9)
[ 2.2)
[ 6.1)
[ 3.4)


: 1.8)
[ 5.4)
( 2.6)
[ 2.3)
71.1
59.5
57.0

63.0
61.1

62.9
56.4
54.9
62.6
63.0
69.4


66.2
66.3
56.3
62.0
( 7.9)
( 4.1)
( 5.0)

( 4.4)
( 4.7)

( 4.1)
( 6.8)
(10.6)
( 6.9)
( 6.1)
( 9.0)


( 7.4)
( 5.6)
( 7.0)
( 4.0)
8.6
30.6
26.9

21.4
25.0

22.9
25.2
21.9
25.1
23.8
21.1


21.7
22.9
24.3
23.2
(2.6)
(3.8)
(3.4)

(3.2)
(3.3)

(2.6)
(4.8)
(5.9)
(4.6)
(4.2)
(6.3)


(5.1)
(4.0)
(4.3)
(2.6)
0.5
8.4
15.4

8.7
7.9

7.7
12.4
16.3
7.8
6.1
2.0


8.6
4.0
11.6
8.3
( 0.4)
( 1.9)
( 3.6)

( 2.3)
( 1.6)

( 1-4)
( 3.3)
( 3.0)
( 2.9)
( 3.1)
( 2.1)


( 3.4)
( 2.4)
( 2.2)
( 1.5)
      t  parts  per  million
      '-Standard  error  not  estimable.
      Source:  Calculated  by  the  Research  Triangle  Institute  from the National Adipose
              Tissue  Survey's  computer  accessible  data  files.

-------
                       Table B.6  Weighted Percentage Distribution  ot  PCB  Residue  Levels
U)
VO
in Adipose Tissue for Fiscal Year 1977

Domain


Sample
Size




Population






PCB Residue Levels
Estimate
(in thous . )
Age (years):
0 -14
15-44
45+
Sex:
Male
Female
Race:
White
Nonwhi te
Census Region:
Northeast
North Central
South
West
Number of PCB
Industries per
State:
0
1
2+
Overall

174
357
396

457
470

794
133

206
257
341
123



312
262
353
927

57
83
61

98
104

178
24

49
56
62
34



59
60
83
203

,900
,437
,875

,912
,300

,972
,240

,041
,572
,795
,804



,410
,641
,161
,212
Not Less than Between 1
Detected 1 PPMt and 3 PPMt
percent (standard error)

2.0 {
0.0 (
0.0 {

0.3 1
0.8 I

0.7 1
0.0 1

0.7 1
0.0 I
1.3 1
0.0 1



0.0 1
0.0 {
1.4 1
0.6 1

: 1-6)
: * )
: * )

; 0.3)
: o.s)

: 0.5)
: * )

[ 0.7)
r ,•. \
^ ** /
: 1.3)
[ * )



[ * )
[ * )
[ 1.0)
[ 0.4)

90.1 I
66.8 I
59.8 I

66.7 1
75.6 I

71.5 1
69.7 1

69.5 1
68.6 I
75.2 I
71.2 1



77.6 1
67.9 1
69.3 I
71.3 I

[ 2.9)
: 3.6)
[ A.I)

[ 3.4)
[ 2.6)

[ 2.3)
: 5.1)

[ 3.4)
[ 4.8)
[ 5.2)
[ A. 2)



( A.O)
( A. 8)
[ 2.7)
[ 2.4)

3.7
24.9
23.6

22.4
14.7

18.8
15.9

19.2
21.7
13.8
20.6



14. A
21.6
19.1
18.5

(1.6)
(2.8)
(2.6)

(2.3)
(1.9)

(1.6)-
(A. 2)

(3.3)
(3.1)
(2. A)
(3.6)



(2.6)
(2.8)
(2.1)
(1.5)
Greater than
3 PPMt

A. 2
8.3
16.6

10.5
8.9

9.0
1A.A

10.7
9.7
9.6
8.2



8.0
10.5
10.3
9.7

( 2.3)
( 2.1)
( 3.5)

( 2.5)
( 1.8)

( 1-7)
( A. 6)

( A. 5)
( 2.4)
( 3.2)
( 3.7)



( 2.0)
( 3.5)
( 3.0)
( 1.7)
    t parts per million
    "'Standard error not estimable.
    Source:  Calculated by the Research Triangle  Institute  from the  National  Adipose
             Tissue Survey's computer accessible  data  files.

-------
                       Table B.7  Weighted Percentage Distribution of PCB Residue Levels
CO
in Adipose Tissue

Doma i n


Sample
Size



for Fiscal Year 1978

Population







PCB Residue Levels
Estimate
(in thous . )
Age (years):
0 -14
15-44
45+
Sex:
Male
Female
Race:
White
Non-white
Census Region:
Northeast
North Central
South
West
Number of PCB
Industries per
State:
0
1
2+
Overall

205
365
381

475
476

771
180

216
211
372
152



316
270
365
951

57
83
61

98
104

177
25

49
56
62
34



74
48
80
203

,900
,437
,875

,912
,300

,749
,463

,041
,572
,795
,804



,356
,062
,794
,212
Not Less than Between 1
Detected 1 PPM t and 3 PPM t
percent (standard error)

5.7
0.3
0.3

1.0
2.6

1.5
4.4

0.6
2.0
1.6
3.6



2.4
0.8
1.9
1.8

(1-7)
(0.3)
(0.2)

(0.5)
(0.9)

(0.6)
(3.0)

(0.5)
(1.1)
(1.1)
(2.0)



(1.1)
(0.6)
(0.9)
(0.6)

85.1 1
67.9 I
64.7 1

67.0 1
76.4 1

72.8 1
65.2 I

69.4 I
70.9 1
74.0 I
72.8 I



77.5 1
74.5 I
65.0 1
71.8 I

[ 4.3)
( 4.4)
[ 5.1)

[ 3.9)
[ 3.6)

[ 3.8)
( 5.6)

[ 8.9)
[ 5.4)
[ 7.5)
[ 3.9)



[ 5.2)
[ 4.4)
C 6.2)
( 3.5)

6.5
19.6
27.0

20.3
16.0

17.8
20.3

22.6
19.6
13.8
17.2



12.9
17.9
23.1
18.1

(2.4)
(2.9)
(4.4)

(2.9)
(2.9)

(2.7)
(4.3)

(7.0)
(5.0)
(3.7)
(3.5)



(3.5)
(3.9)
(4.3)
(2.5)
Greater than
3 PPMt

2.7
12.2
8.0

11.7
5.0

8.0
10.1

7.4
7.5
10.6
6.4



7.2
6.9
10.0
8.2

(
(
(

(
(

(
(

(
(
(
(



(
(
(
(

1.6)
2.8)
2.5)

2.8)
1.5)

2.0)
3.4)

3.3)
3.4)
4.3)
3.6)



2-7)
2.8)
3.6)
1.9)
    t parts per million
    ^Standard error not estimable.
    Source:  Calculated by the Research Triangle Institute from the National Adipose
             Tissue Survey's computer accessible data files.

-------
                        Table B.8  Weighted Percentage Distribution of PCB Residue  Levels
CO
in Adipose Tissue

Domain


Sample
Size



for Fiscal Year 1979

Population






PCB Residue Levels
Estimate
(in thous. )
Age (years):
0 -14
15-44
45+
Sex:
Male
Female
Race:
White
Non-white
Census Region:
Northeast
North Central
South
West
Number of PCB
Industries per
State:
0
1
2+
Overall

203
346
361

477
433

740
170

189
189
438
94



281
259
370
910

57
84
61

104
99

178
24

49
56
62
34



57
60
85
203

,900
,167
,145

,131
,081

,897
,315

,041
,572
,795
,804



,160
,086
,966
,212
Not Less than Between 1
Detected 1 PPM t and 3 PPM 1
percent (standard error)

4.1
0.0
0.2

1.3
1.2

1.0
3.1

0.9
0.0
2.7
1.1



2.3
0.8
0.9
1.2

(2.2)
( * )
(0.2)

(0.6)
(0.8)

(0.4)
(2.3)

(0.7)
( * )
(1.5)
(1.3)



(1.6)
(0.8)
(0.5)
(0.6)

89.0
80.3
66.6

76.5
80.9

79.5
72.7

55.7
93.0
81.4
82.9



85.6
92.2
64.6
78.7

( 3.5)
( 4.2)
( 3.9)

( 3.5)
( 3.5)

( 3.2)
( 6.1)

(11.7)
( 2.8)
( 4.4)
( 5.7)



( 5.2)
( 1-9)
( 6.8)
( 3.3)

6.9
15.0
26.5

17.7
14.6

15.9
18.4

30.5
6.9
15.4
12.4



11.2
5.5
26.9
16.2

(3.1)
(2.8)
(3.9)

(3.1)
(2.3)

(2.6)
(3.8)

(6.7)
(2.8)
(3.3)
(6.5)



(3.6)
(1.8)
(4.0)
(2.4)
Greater than
3 PPMt

0.0
4.7
6.6

4.5
3.3

3.7
5.8

12.9
0.1
0.6
3.5



0.8
1.5
7.7
3.9

( * )
( 2.9)
( 4.3)

( 1.9)
( 3.2)

( 2.5)
( 2.8)

(10.5)
( 0.1)
( 0.4)
( 2.1)



( 0.6)
( 1.3)
( 6.0)
( 2.5)
     t parts per million
     ""Standard error not estimable.
     Source:  Calculated by the Research Triangle Institute from  the National Adipose
              Tissue Survey's computer accessible data  files.

-------
                   Table B.9  Weighted Percentage Distribution of PCB Residue Levels


Domain


Age (years):
0 -14
15-44
45+
Sex:
Male
Female
Race:
White
Nonwhite
Census Region:
Northeast
North Central
South
West
Number of PCB
Industries per
State:
0
1
2+
Overall


Sample
Size


26
47
24

53
44

76
21

19
24
• 34
20



34
30
33
97
in

Adipose

Tissues for Fiscal Year 1981



Population





PCB Residue Levels
Estimate
(in

51,
115,
59,

126,
99,

182,
44,

49,
58,
75,
43,



68,
66,
91,
226
thous . )

390
750
365

700
805

205
299

137
854
349
165



718
161
626
,505
Not Less than Between 1
Detected 1 PPMt and 3 PPMt
percent (standard error)

0.0 (
0.0 (
0.0 (

0.0 (
0.0 (

0.0 (
0.0 (

0.0 (
0.0 (
0.0 (
0.0 (



0.0 (
0.0 (
0.0 (
0.0 (

* )
* )
* )

•/t ^
* )

* )
* )

* )
* )
**» ^
* )



* )
* )
J. \
* )

92.8
69.5
58.4

65.9
79.4

80.7
35.4

73.5
74.0
73.8
63.6



69.2
82.5
66.1
71.8

( 5.3)
(10.6)
(12.8)

(10.8)
( 9.3)

( 6.8)
(13.3)

(15.9)
(13-4)
(16.4)
(22.6)



( 1-7)
(10.6)
(13.0)
( 8.5)

7.2
29.0
41.6

32.7
20.6

19.3
60.7

26.5
23.0
26.2
36.4



28.3
17.5
33.9
27.4

( 5.3)
(10.5)
(12.8)

(10.4)
( 9.3)

( 6.8)
(14.0)

(15.9)
(12.2)
(16.4)
(22.6)



(16.0)
(10.6)
(13.0)
( 8.4)
Greater than
3 PPMt

0.0 (
1.5 (
0.0 (

1.4 (
0.0 (

0.0 (
3.9 (

0.0 (
3.0 (
0.0 (
0.0 (



2.5 (
0.0 (
0.0 (
0.8 (

* )
1.5)
* )

1.4)
* )

"A" ^
4.0)

* )
3.0)
* )
j- \



2.5)
* )
* )
0.8)
t parts per million
^Standard error not estimable.
Source:  Calculated by the Research Triangle Institute from the National Adipose
         Tissue Survey's computer accessible data files.

-------
B.2  Statistical Models for Trends

     To  estimate  the trends  in PD  and  percent  GTS  for the U.S. Popu-

lation, the regression model:


     Y(i)  =  B(0) + B(l) (FY-FY) + B(2) (FY-FY)2                 (B.2.1)

was used where Y(i), i=l,2, is the dependent variable, FY denotes fiscal


year, FY denotes the mean of the fiscal years.  Y is an  indicator random

variable taking on the values:

            (  0 if PCB = 0
     Y(l) = <
            (  1 if PCB > 0

when  PD is being investigated and

            (   0 if PCB < 3 ppm
     Y(2) = I
            (   1 if PCB > 3 ppm

when percent GTS is being investigated.

     For  the  dependent  variable Y(l),  both  the linear  and quadratic
                      "V                                            *£
terms were  significant  .   Only the quadratic  term was  significant  for

Y(2).  Hence,  the estimated trend equations are

          PD = 96.0 + 1.80 (FY - 76.11) - .189 (FY-76.11)2

and

          GTS  = 8.15 - .31 (FY-76.11)2.

These equations are plotted in Figures 4 and 7 in Chapter 3.

     Besides the overall model, the complex design model


     Y(i) = AGEG+RACE+SEX+CR+IND+(FY-FY)+(FY-FY)2+


            (FY-FY) * (AGEG+RACE+SEX+CR+IND)


            +(FY-FY)2 * (AGEG+RACE+SEX+CR+IND)                    (B.2.2)
*
 Assuming no sampling or measurement bias.

                                B-43

-------
was tested  using  SURREGR (Holt 1977) where  was  Y(i),  i=l,2, is defined

as in equation (B.2.1),

AGEG           denotes the age effect for the three levels 0-14,
               15-44 and 45+,

RACE           denotes the race effect for the two levels white
               and nonwhite,

SEX            denotes the sex effect for the two levels male
               and female,

CR             denotes the Census Region effect for the four levels
               Northeast, North Central, South and West,

IND            denotes the PCB industry effect for the three levels
               none (0), one (1) and more than one (2+),
FY-FY          denotes the difference between the fiscal year and
               the mean of the fiscal years,
(FY-FY)"(AGEG+RACE+SEX+CR+IND) denotes the linear interactions of
               fiscal year with the main effects, and


(FY-FY) *(AGEG+RACE+SEX+CR+IND) denotes the quadratic interactions
               of fiscal year with the main effects.

The  categories  CR and  IND  are defined in Tables B.10  and B.ll respec-

tively.   Each observation  is assigned to  the appropriate  category by

using the State in which the tissue specimen was collected.
                                                        *
     The statistical test indicated only one significant  second order
                                                 	 2
interaction (significance level (SL) < .05), (FY-FY) *AGEG for GT3 and

none for PD.  The model in equation (B.2.2) was simplified by dropping
                                                     	 2
all second order terms with the exception of the (FY-FY) *AGEG for GT3.

The statistical test on the first order interactions indicated no
           .A.                        	
significant" interactions among (FY-FY) and RACE, SEX, CR or IND.  The

model was again simplified yielding the two models:
*
 Assuming no sampling or measurement bias.
                                B-44

-------
                        Table  B.10   List  of  States by Census Region and Census Division Within Region
Region
North East
Division
New England
                  Middle Atlantic
South
 South Atlantic
                  East South
                  Central
                  West South
                  Central
States
Connecticut
Maine
Massachusetts
New Hampshire
Rhode Island
Vermont

New Jersey
New York
Pennsylvania
Region
North Central
Division
East North
Central
                                                                   West  North
                                                                   Central
Delaware
District of Columbia
Florida
Georgia
Maryland
North Carolina
South Carolina
Virginia
West Virginia

Alabama
Kentucky
Mississippi
Tennessee
                     Arkansas
                     Louisiana
                     Oklahoma
                     Texas
West
Mountain
                                                                   Pacific
States
Illinois
Indiana
Michigan
Ohio
Wisconsin
Iowa
Kansas
Minnesota
Missouri
Nebraska
North Dakota
South Dakota

Arizona
Colorado
Idaho
Montana
Nevada
New Mexico
Utah
Wyoming
                                         Alaska
                                         California
                                         Hawaii
                                         Oregon
                                         Washington

-------
             Table B.ll  List of States By PCB Industry Category

  No PCB Industries                                 One PCB Industry
  Alaska
  Arkansas
  Connecticut
3 Delaware
y Florida
  Hawaii
  Idaho
  Iowa
  Kansas
  Louisiana
  Maine
5 Michigan
<; Minnesota
  Missouri
  Montana
  Nebraska
  Nevada
  New Hampshire
  New Mexico
  North Dakota
  Oklahoma
  Rhode Island
  South Dakota
  Utah
  Washington
J West Virginia
^ Wisconsin
  Wyoming
  Arizona
  Colorado
 "^Georgia
 ^Indiana
^ Mississippi
 u North Carolina
 5 Ohio
  Oregon
y Tennessee
  Texas
  Vermont

  Two or more PCB Industries

 S- Alabama
  California
 5" Illinois                 ,
  Massachusetts         £~/
  New Jersey             /^
  New York
 3 Pennsylvania
Ij South Carolina
  Virginia
  Source:   Compiled by the Research Triangle Institute from lists of
            U.S. transformer and capacitor manufacturing industries
            using PCBs provided by the U.S. Environmental Protection
            Agency.
                                  B-46

-------
Y(l) =  AGEG+RACE+SEX+CR+IND+(FY-FY)+(FY-FY)2+(FY-FY)*AGEG


and


Y(2) =  AGEG+RACE+SEX+CR+IND+(FY-FY)+(FY-FY)2+(FY-FY)*AGEG+(FY-FY)2*AGEG

                                                                  (B.2.3)


for PD and  GTS  respectively.   The above models was used to test  for the


main effects with  the  exception of AGEG.   The  results  of this test are


summarized in Chapter 3.


     To illustrate  the  trends  in the three age groups,  the coefficients


for two simple models were estimated.   The equations for PD are


     PD = 91.0 + 2.58 (FY-76.11) - .189(FY-76.II)2


for the 0-14 age group,


     PD = 98.2 + 1.35(FY-76.11) - .189(FY-76.II)2


for the 15-44 age group, and


     PD = 97.8 + 1.60(FY-76.11) - .l89(FY-76.II)2


for the 45+ age group.   These equations were used to calculate the


trends illustrated in Figure 3.  The equations for percent GT3 are


     GT3 = 1.83 - .055  (FY-76.11)2


for the 0-14 age group,


     GT3 = 8.55 - .293  (FY-76.11)2


for the 15-44 age group, and


     GT3 = 13.6 - .585  (FY-76.11)2


for the  45+ age group.  The linear terra in FY was  excluded  because it

                                 *
did not contribute  significantly  to  explaining the changes in GT3 over


time.   These  equations were used  to  calculate the  trends  in Figure 5.


     To  illustrate  the  trends  in  the  race  groups, the  equations  for


percent GT3 are



          GT3 = 7.8  -  .34(FY-FY)2
*
 Assuming no sampling or measurement bias.
                                B-47

-------
for whites and




          GT3 = 11.5 - .34(FY-FY)2


for nonwhites were  plotted in Figure 6.   Trends  for the two sex groups


and the  Census  Regions  would have essentially the same coefficients for


the fiscal year  terms  but would have different  intercepts.   Table B.12


summarizes the  intercepts  for the factors race,  sex,  Census Region and


industry.


B.3  Assessing Limitations of the Data


     In  an  attempt to  ascertain the impact  of  the  change  in chemical


analysis  on  the estimated trends, overall trends were calculated using


data collected  during  fiscal 1976 to 1979 and  1981.   The overall trend


equation for PD is:


          PD = 98.98 + .24 (FY-78.2),


and the overall trend equation for percent GTS is:


          GT3 = 6.00 - 1.66  (FY-78.2).


The trends  for PD and GT3 are  illustrated in Figures  9  and 10 respec-

                                                JL
tively.  The slopes of the lines are significant  , with the slope for PD

                             JL
having  a  significance level  of .0199  and  the  slope  for GT3  having a

                  *
significance level  of .0000.


     To  compare  the slopes  in  the  above  equations with  the  estimated


trend  using  all  fiscal  years, one can  calculate  the average change per


year from fiscal 1976 to 1981.  Using the equations:


     PD(FY) = 96.0 + 1.80  (FY-76.11) -  .189 (FY-76.11)2
and
     GT3(FY) = 8.15 - .31 (FY-76.11)2,
 Assuming no measurement of sampling bias.



                                B-48

-------
     Table B.12.  Intercepts for Trends of Percent Greater
                  Than 3 PPM* by Factors —
Factor Subpopulation
Race White
Nonwhite
Sex Male
Female
Census Region Northeast
North Central
South
West
Industry 0
1
2+
Intercept
(Percent)
7.7
11.4
9.3
7.1
11.6
6.8
7.7
6.2
7.4
6.4
9.9
PPM denotes parts per million.

Source:  Calculated by the Research Triangle Institute from the
National Adipose Tissue Survey computer accessible data file.
                           B-49

-------
the average change for PD is (PD(81) - PD(76))/(81-76) = .90 and the




average change for GT3 is (GT3(8l) - GT3(76)) / (81-76) = -1.48.  The




average changes per year are consistent in direction.  The two estimated




rates of  change  for  GTS are comparable for the time period.  The magni-




tudes for PD are  not as comparable  but this  can be explained  by the




relatively  low  value in PD  for  fiscal 1973 which pulls  down the trend




equation  for  all  years.   Hence,  the change  in  chemical  analysis  method




does not appear to consequentially affect the estimated trends.




     To develop an understanding of the impact of bias on the significance




level of trends and subpopulation differences, Table B.13 was calculated.




The  table  illustrates  the   true  significance  of  a  two sided test  of




hypothesis when no bias  exists and for  levels  of  bias ranging from one




fourth  the  standard  error  (SE)  to four times  the  SE.   For simplicity,




the significance levels are calculated using the normal density function.




Even though the tests discussed in the report were based on the F distri-




bution,  the  table  is  not misleading because  the degrees  of freedom for




the  denominator  were  large (69  for  fiscal  1976-1981  and 103 for  all




fiscal  years)  and the  degrees of freedom for  the  numerator  were often




only 1  (at most 3).




     Using  the  table, one  can estimate the  magnitude of  the  relative




bias that may mislead the investigator into drawing erroneous conclusions.




For  example,  if  a test  was  calculated to have a  significance  level  of




.0001,  then a bias of more than twice the size of the SE would be  required




to  raise  the true significance  level above  the traditional  .05  level.




Hence,  because the significance  level of trends were generally .0001 or




lower,  it is unlikely  that magnitude  of  the  bias  is large  enough  to
                                B-50

-------
          Table B.13.  Impact of Bias on the Significnace Level
                       of Statistical Test of Hypothesis'-
BIAS/SE
0.00
0.25
0.50
1.00
1.50
2.00
3.00
4.00
Significance Level
.0500
.0572
.0791
.1701
.3230
.5160
.8508
.9793
.0250
.0297
.0440
.1081
.2297
.4052
.7764
.9608
.0100
.0124
.0190
.0578
.1412
.2826
.6646
.9229
.0010
.0012
.0028
.0113
.0375
.1003
.3897
.7642
.0001
.0001
.0003
.0019
.0084
.0294
.1867
.5438
.00001
.00002
.00004
.00032
.00177
.00782
.07825
.33834
 Calculated by the Research Triangle Institute using the equation:

                    z(a) + BIAS/SE
          SL
exp(-x /2)/V2n dx
                   -z(a) + BIAS/SE
where z(.0500) = 1.960, z(.0250) = 2.24, z(.0100) = 2.576, z(.0010) =
3.291, z(.OOOl) = 3.891, z(.00001) = 4.417 and SE denotes the standard
error.
                                B-51

-------
affect the conclusions  about  trends.   Similar reasoning can  be  used to




allow the reader to evaluate the conclusions about race, sex,  or geogra-




phic differences.
                                B-52

-------
B.4  References
Holt MM  1977   SURREGR:   Standard  errors of regression coefficients from
sample  survey  data.   Research  Triangle  Institute,  Research  Triangle
Park, NC 27709.

Shah DV  1979   SESUDAAN:   Standard errors program for computing of stan-
dardized rates  from sample  survey  data.  Research  Triangle  Institute,
Research Triangle Park,  NC 27709,  RTI/1789/00-01F.
                                B-53

-------