r/EPA
United States
Environmental Protection
Agency
Office of
Toxic Substances
Washington, D.C. 20460
EPA 560/13-80-024
November 1980
Office of Toxic Substances
Mirex Residue Levels
in Human Adipose Tissue
*
A Statistical Evaluation
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EPA 560/13-80-024
November, 1980
final Report
RTI/1864/17-OOF
Mirex Residue Levels in Human Adipose Tissue:
A Statistical Evaluation
by
Carol Leininger
Donna Lucas Watts
Charles Sparacino
Stephen Williams
Research Triangle Institute
Research Triangle Park
North Carolina 27709
Contract Number 68-01-5848
Task Manager: Cindy Stroup
Project Officer: Joseph Carra
Design and Development Branch
Exposure Evaluation Division
Office of Toxic Substances
U. S. Environmental Protection Agency
401 M Street, SW
Washington, D.C. 20460
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DISCLAIMER NOTICE
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, nor assumes any legal liability or respon-
sibility for any third party's use or the results of such use of any
information, apparatus, product or process disclosed in this report, nor
represents that its use by such third party would not infringe 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.
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ACKNOWLEDGEMENT
The authors acknowledge the cooperation of Dr. Frederick Kutz,
Ms. Sandra Strassman-Sundy, and Ms. Madeline O'Neill Dean of the U.S.
Environmental Protection Agency, Washington, D.C., in providing informa-
tion on the sample design and data collection for the Mirex Special
Study. The authors appreciate the assistance of Dr. Robert Welch of the
Michigan Department of Public Health in supplying information about the
chemical analysis techniques employed. Special thanks go to Ms. Martha
Clegg and Ms. Pat Parker for an excellent job of typing.
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TABLE OF CONTENTS
1. INTRODUCTION AND CONCLUSIONS 1
1.1 Introduction 1
1.1.1 Foreward 1
1.1.2 Summary of Study 1
1.2 Conclusions 2
1.2.1 Survey Design 2
1.2.2 Chemical Analysis 2
1.2.3 Exploratory Data Analysis 2
1.2.3.1 Introduction 2
1.2.3.2 Unweighted Analysis 3
1.2.3.3 Weighted Analysis 3
2. THE NATIONAL HUMAN MONITORING PROGRAM'S MIREX
SPECIAL STUDY 5
2.1 Detailed Description of Study 5
2.1.1 Introduction 5
2.1.2 Sample Design 5
2.2 National Human Monitoring Program 6
2.2.1 Introduction 6
2.2.2 Strata 8
2.2.3 Eligible Places 8
2.2.4 Pathologists and Medical Examiners 8
2.2.5 Quotas 8
2.3 Selection Weight Construction 9
3. EVALUATION OF CHEMICAL ANALYSIS 13
3.1 Introduction 13
3.2 Discussion 13
4. UNWEIGHTED ANALYSIS 24
4.1 Data Description • . . 24
4.2 Data Analysis 25
4.2.1 Data Distribution 25
4.2.2 Proportions of Positive Values 32
4.2.3 Quantifiable Positive Values 40
4.2.4 Unweighted Analysis Conclusions 40
5. WEIGHTED ANALYSIS 43
5.1 Introduction 43
5.2 Weight Formation 43
5.3 Estimates of Positive Mirex Detection 43
5.4 Estimates of Quantifiable Positive Values 48
5.5 Weighted Analysis Conclusions 49
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TABLE OF CONTENTS (Cont.)
Page
REFERENCES 54
APPENDIX A: State Maps Showing Counties Where Federally
Assisted Mirex was Applied at Some Time During
1965-1974 A-55
APPENDIX B: Counties Where Federally Assisted Mirex was
Applied at Some Time During 1965-1974 B-65
APPENDIX C: Definition of Mirex Treated Areas C-71
APPENDIX D: MSS Sample Site Selection Method D-73
APPENDIX E: List of MSS Collection Sites E-79
APPENDIX F: Quotas for Mirex Special Study Specimens F-82
APPENDIX G: Instructions to Pathologists G-86
APPENDIX H: Modification of Mirex Analysis Protocol -
GC Column Temperature H-95
APPENDIX I: Confirmation Analyses of Mirex in Human Adipose
Tissue Extracts 1-97
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LIST OF TABLES
Table Page
3.1 Comparison of Mirex Peak Heights (mm) and Calculated
Amounts (pg) as Determined by Michigan Department of
Public Health and Quality Control Checks 22
3.2 Interperson Comparison of Mirex Peak Height Measurements . 23
4.1 Specimens Collected for Each Census Division by Age, Race,
and Sex 26
4.2 Detection of Mirex Residue by State: Number of Specimens
with Positive and Zero Detectable Levels 34
4.3 Detection of Mirex Residue by Race and Age: Number of
Specimens with Positive and Zero Detectable Levels .... 35
4.4 Chi-Square Analysis Results for Zero Detectable/Positive
Values: Geographic and Demographic Variables 36
4.5 Regression Model for Race, Age, Sex, and State: Zero
Detectable/Positive Residue Values 38
4.6 Regression Model for Race, Age, Sex, and Census Division:
Zero Detectable/Positive Residue Values 39
4.7 Summary Statistics for Quantifiable Positive Residue
Values: Geometric Means and Standard Errors 41
4.8 Summary Statistics for Quantifiable Positive Residue
Values: Geometric Means and Standard Errors 42
5.1 Weighted Chi-Square Analysis Results for Zero Detectable/
Positive Values: Geographic and Demographic Variables . . 45
5.2 Weighted Regression Model for Race, Age, Sex, and Census
Division: Zero Detectable/Positive Residue Values .... 46
5.3 Weighted Regression Model for Race, Age, Sex, and State:
Zero Detectable/Positive Residue Values 47
5.4 Estimated Summary Statistics for Quantifiable Positive Residue
Values: Weighted Geometric Means and Standard Errors. . . 50
5.5 Estimated Summary Statistics for Quantifiable Residue Values:
Weighted Geometric Means and Standard Errors 51
5.6 Weighted Regression Model for Location, Age, Race, and Sex
Versus Quantifiable Positive Residue Amounts of Mirex. . . 52
5.7 Weighted Regression of Quantifiable Positive Residue
Amounts: Location, Age, Race, and Sex 53
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LIST OF FIGURES
Figure
2.1 Sampling frame and selection procedures for Mirex
Special Study 7
3.1 Gas chromatogram - Aroclor 1260 standard 15
3.2 Gas chromatogram - mirex standard 16
3.3 Gas chromatogram - mixture of Aroclor 1260 and mirex
standards 17
3.4 Gas chromatogram - mirex containing specimen (moderate
level) with interference peak (moderate level). ... 18
3.5 Gas chromatogram - mirex containing specimen (low
level) with interference peak (low level) 19
3.6 Gas chromatogram - mirex containing specimen (moderate
level) with interference (high level) 20
4.1 Frequency Distribution for Raw Values of Residue
Amount 28
4.2 Frequency Distribution for transformed values of
wet weight mirex residue 30
4.3 Frequency Distribution of lipid adjusted mirex
residue amounts and transformed values (n = 123
quantifiable positives) 31
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1. INTRODUCTION AND CONCLUSIONS
1.1. Introduction
1.1.1. Foreword
This report presents a statistical evaluation of data collected
under the Environmental Protection Agency National Human Monitoring
Program's Mirex Special Study, which was begun in 1975. The primary
objectives of this effort were to investigate, document, and assess the
survey design, to verify the chemical analysis results, and to calculate
estimates of the prevalence of mirex residues in human adipose tissues
in a defined section of the southern United States. Several demographic
variables were included in exploratory analyses to determine if there
were any identifiable factors contributing or otherwise related to mirex
residues in humans.
Chapter 2 of this report describes the survey design employed in
the Mirex Special Study and includes a rationale of the statistical
analysis approach. Chapter 3 is a discussion of the chemical analysis.
Chapters 4 and 5 are presentations of unweighted and weighted statistical
analyses, respectively.
1.1.2. Summary of Study
Mirex is an organochlorine insecticide widely used for the control
of the imported fire ant in large areas of the southern United States.
It is persistent, which, in combination with the substance's pharraaco-
dynamics, leads to environmental mobility and potential incorporation
into various food chains.
Mirex residues found in specimens of human adipose tissue led to
the Mirex Special Study (MSS) conducted by the National Human Monitoring
Program (NHMP). The study area, sample design, sample selection, speci-
fication of the procedures for collecting specimens in the field and for
chemical analysis were defined by the NHMP. From October 1975 through
September 1976, a sample of 630 human adipose tissue specimens were
collected from selected surgical patients and cadavers. The sample was
selected within a study area defined as all counties having some feder-
ally assisted application of the insecticide mirex between 1965 and
1974. Mirex residues were found in 141 of the 624 tissue specimens
analyzed (six of the 630 specimens were not analyzed because of the
inadequate amount of extractable lipid). The convention of referring to
a single sampling unit, i.e., adipose tissue from a surgical patient or
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cadaver, as a specimen, and a collection of sampling units or specimens
as a sample is used throughout this report.
1.2. Conclusions
1.2.1. Survey Design
The limitations and assumptions of the MSS survey design are
described in detail in Chapter 2 and in sections 4.1, 4.2, and 5.2. In
brief, the major limitation of this particular survey design is the
method of sample selection. The sample selection did not include prob-
ability sampling at each step of the selection process. Any estimate
for a population made from a small number of people or things selected
from the larger group is based on the assumption that anyone can be
selected and that the probability, or chance, of that selection is
known. Residue levels and other pertinent population values cannot be
accurately estimated with any assurance unless the probabilities with
which a given tissue specimen was chosen for the MSS can be calculated.
This limitation should be recognized in the interpretation and use of
the findings in this report.
1.2.2. Chemical Analysis
Raw mirex analytical data, in the form of gas chromatograms, were
examined in order to assess the reliability of the final results. For
those chromatograms made available for study, good analytical practice
was indicated in virtually all cases. The analytical system remained
stable over the period of study, overall sensitivity was more than
adequate, and peak area measurements were accurate and precise in the
vast majority of cases. The results were thus deemed reliable and
amenable to detailed statistical treatment.
1.2.3. Exploratory Data Analysis
1.2.3.1. Introduction
Two methods of analysis were used for the exploratory analyses:
unweighted and weighted analyses. The unweighted analysis can only be
used to describe the 624 specimens in the MSS sample. The weighted
analysis is an attempt to estimate the patterns influencing prevalence
of mirex residues in the target population. The target population here
consists of all human residents of all counties where mirex was applied
during a ten year period in eight southern States. The process of
adjusting the information contained in the sample so that it represents
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the target population is called weighting; the methodology and justifica-
tion are described in greater detail in section 2.3. Any inferences
about a study population that are based on a sample from that population
need to be based on data that have been adjusted or weighted according
to rules or assumptions of probability.
1.2.3.2 Unweighted Analysis
The results of the unweighted analysis on the sample of 624 speci-
mens indicate that the geographic location of the collection site is the
most important factor studied for explaining the differences in number
of positive detections of mirex in these particular human adipose tissue
specimens. Some results from the unweighted analyses of the entire
sample and of the 123 quantifiable observations are listed below. The
results describe only the specific group of human adipose tissue speci-
mens analyzed.
For all 624 specimens,
the proportion of positive detections is significantly
different (p £ 0.0001) among States and Census Divisions.
there are marginally significant (p £ 0.10) differences related
to the factors age and race.
For the 123 quantifiable observations,
demographic and geographic factors did not show any effect in
degree of mirex concentration in sample specimens.
1.2.3.3. Weighted Analysis
In the weighted analysis, location of the selection site is again
the most significant variable of those studied for explaining variation
in mirex residues. The results of the weighted analyses for the entire
sample and for the quantifiable observations are listed below.
For the total sample,
State is a significant (p < 0.0001) factor in explaining the
variation of positive mirex detection.
Mississippi is the State in which the proportion of mirex
residues is extremely high (51.1 percent).
For the quantifiable residue amounts,
there is a significant interaction between geographic location
and race. This suggests that there is possibly a race effect
for some geographic divisions that is not particularly strong
or consistent throughout the mirex treated area.
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It must be emphasized that the limitations of the sample selection
methodology restrict the interpretation of any results. These findings
can be interpreted only as indications of trends or patterns which may
exist in the population living in the mirex treated region.
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2. THE NATIONAL HUMAN MONITORING PROGRAM'S MIREX SPECIAL STUDY
2.1. Detailed Description of the Study
2.1.1. Introduction
Human adipose tissue specimens for the Mirex Special Study were
collected from October 1, 1975 through September 30, 1976 (FY76). The
target population was the human population of all counties with some
federally assisted application of mirex at any time during the 10-year
period 1965 to 1974 (Kutz and Strassman undated). A list of these
counties was provided to the NHMP by the U.S. Department of Agriculture.
Maps of the eight southern States containing these counties are displayed
in Appendix A. A list of the mirex counties, by State, is given in
Appendix B. The pattern of mirex use can be charted directly to the
areas of infestation of imported fire ants in this country. This infes-
tation pattern does not conform to large-scale geographic or political
boundaries, such as Census Divisions or States, as can be seen by examin-
ing the maps in Appendix A. No information was provided concerning the
amount or frequency of mirex application over the 10-year period. Such
information might be extremely important in determining levels of expect-
ed exposure to this insecticide; for further discussion of this point
see Appendix C.
2.1.2. Sample Design
Mirex residues were found in human adipose tissue specimens submit-
ted to the NHMP, which was designed to provide estimates at the national
level. There were eight cities in mirex areas where established contacts
(hospital. pathologists or medical examiners) were already submitting
adipose tissue specimens for the NHMP. A special study was designed to
increase representation from mirex regions by increasing the number of
sample sites in mirex areas. 32 supplementary sites were selected,
bringing the total number of sites contacted in the MSS to 40.
To select the 32 supplementary areas for the MSS, a listing was
made of all 1974 Ranally Metropolitan Areas (RMA's) in the mirex area:
RMA's were defined on a township and locality basis. All areas with a
total population of 50,000 or more were considered to be RMA's. Other
areas that presently had populations close to 50,000, had populations
greater than 50,000 in the past, or had special significance in their
States were also defined as RMA's (Rand McNally 1974). The complete
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listing of the population from which a sample will be selected is called
a frame. The 8 NHMP sites were on the frame of 68 RMA's located in the
mirex area. These 8 cities were not included as possible selections for
the mirex supplementary sample because they were already included as
part of the MSS sample by virtue of their initial selection into the
NHMP.
Of the 60 RMA's in the mirex supplementary list, 32 were apparently
selected by simple random sampling (SRS). The 60 RMA's were listed in
alphabetical order (not pertinent to the selection process), and then a
SRS was selected from the list. See Appendix D for a discussion of the
site selection methodology employed. Nine additional sites were select-
ed, in the same manner, to be used as alternates in case there were non-
responding sites. These alternates were to be substituted for non-
responding sites in the order in which they were selected. One site was
replaced by an alternate selection. A list of the selected sites and
alternates is given in Appendix E.
The selection of sites within mirex areas produced 40 sample RMA's.
Of these, 5 of the 8 NHMP sites and 23 of the 32 mirex supplementary
sample RMA's responded with valid tissue specimens. The treatment of
nonresponding sites is described in section 2.3. Figure 2.1 outlines
the path of the sample selection procedures for obtaining tissue speci-
mens for the MSS.
Data collection for the MSS after the selection of first-stage
RMA's follows the methods used in the Adipose Tissue Survey (ATS) of the
NHMP. For the convenience of the readers, a brief discussion of the
NHMP is now included; a more detailed description is contained in a 1979
EPA document (Hartwell et al. 1979).
2.2. National Human Monitoring Program
2.2.1. Introduction
The statistical design used to collect data for the ATS of the NHMP
has two stages. The contiguous 48 states were stratified into several
regions. Sampling sites were selected from a list of eligible places
with probability proportional to population. Within the sampling sites,
the subsampling was performed by cooperating pathologists and medical
examiners.
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23,557,425
17,085,700
13,486,900
unknown
624
Target population*—total population of counties
where mirex has been used.
Purposive exclusions of cities and towns not
defined as RMA's.
1st stage sampling frame and inference population—
the human population of 68 RMA's.
Selection of a subset of 40 of the 68 RMA's.
/ *
1st stage sample of RMA's.
Purposive exclusion of some hospitals, pathologist*
and medical examiners, selection of only
cadavers and surgical patients.
Sampled population—includes a subset of only
surgical patients and persons who died in FY76.
Subsampling of surgical patients and cadavers
by cooperating professionals.
Sample.
Figure 2.1. Sampling frame and selection procedures for Mirex Special Study.
Source: Based on information contained in Kutz and Strassman undated, and Rand McNally and Co., 1974.
'Population values based on 1970 census data.
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2.2.2. Strata
In FY70-FY72, the contiguous 48 states were stratified by Census
Region. Beginning in FY73, the strata were changed to Census Divisions.
In the earlier period, the number of sites selected within each stratum
was determined by its population as given in the 1960 Census. In FY73,
the allocations were revised based on 1970 Census data.
2.2.3. Eligible Places
In FY70-72, the eligible places were cities with populations greater
than 25,000 persons based on the 1960 Census. In FY73-76, the eligible
places were cities greater than 25,000 based on the 1970 Census. Sample
sites were selected in FY73 and followed through FY76. The sample sites
were independently selected from each stratum with probability propor-
tional to size of the city. This was done by listing the sites in
random order along with their cumulative population totals. An interval
for each stratum was calculated by dividing the total population for all
sites listed by the number of sites to be selected in the stratum. A
random number was obtained between zero and the length of the interval
to give a starting point. The sites were selected by matching their
cumulative totals with the starting point or integer multiples of the
interval plus the starting point.
2.2.4. Pathologists and Medical Examiners
The subsampling within each site was done by a cooperating patholo-
gist or medical examiner. When no cooperative pathologist or medical
examiner could be found in a selected site, an alternate site was
selected. Alternate sites were chosen by position in the listing of
eligible sites with respect to the nonrespondent site. The first alter-
nate was the site immediately below the originally selected site, the
second alternate the one immediately above, the third alternate was the
second site following, and so on.
2.2.5. Quotas
Each site was assigned a quota based on the demographic characteris-
tics of age, sex, and race. The ages were grouped into three ranges:
0-14, 15-44, and greater than 44. The races were classified as white
and nonwhite. The quotas for FY70-FY72 were based on the national
demographic characteristics according to the 1960 Census. The quotas
for FY73-FY76 were determined by the appropriate demographic characteris-
tics for each Census Division, based on the 1970 Census. The MSS quotas
are given in Appendix F.
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There was no probability structure below the sample city level for
obtaining the participants in the survey. The hospitals, pathologists,
and medical examiners were selected subjectively. Also, the samples of
cadavers and surgical patients were selected subjectively by the cooper-
ating professionals. Appendix G contains a copy of the EPA letter sent
to each cooperating professional stating the guidelines for screening
specimens and the types of individuals from whom tissue specimens should
not be obtained (for example, suspected victims of pesticide poisoning
and institutionalized patients).
2.3. Selection Weight Construction
In order to use the information obtained in the MSS to estimate the
level of mirex concentration in the population of RMA's in the target
area and to account for disproportionate sampling rates, it is necessary
to weight the original values before analysis. This presents some
problems, for the nature of the selection of sites, which includes at
some points purposive selection (subjective, not based on any known
probability of selection), is incompatible with the formation of statis-
tically valid sampling weights. A method of "quasi" weighting has been
devised and used for the weighted analyses. A simple method of weighting
was chosen to facilitate the weighted analyses, but it is by no means
necessarily the best or only way to weight the data. The method of
weighting chosen and some of that particular method's limitations are
described here.
The first stage selection frame, consisting of 68 1974 RMA's from
the designated mirex counties in eight southern States, was actually
split between two lists, which were considered separately in constructing
weights. One list consisted of eight mirex area cities that were origi-
nally part of the NHMP, and the second list consisted of 60 sites (RMA's),
from which the supplementary MSS sample was drawn. The eight cities
that had been part of the NHMP were included with certainty in the
sample. These eight cities are in RMA's, but were not considered among
the possible selections for the supplementary sample.
Even if one assumes the selection process within sample sites is
approximately random, the sample design of the MSS does not assign equal
"probabilities" of selection to all elements (cadavers and surgical pa-
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tients) in the sample. This introduces the possibility of sampling bias
in calculating population estimates. Bias refers to the difference
between an estimated population value and the true population value. It
can occur as a result of sampling error or measurement error, or a
combination of both. To facilitate bias reduction in this situation, a
sample weight for each observation was calculated that attempts to
reflect its approximate probability of selection. Including weights in
the analysis should reduce bias in estimating means or proportions. For
probability sampling this results in strictly unbiased estimators for
such statistics as means, proportions, and totals. In the following
paragraphs, procedures are given for computing weights for the MSS.
Again, note that true sampling weights cannot be calculated because some
stages of selection involve non-probability sampling.
The population from which tissue specimens might be obtained is not
actually all people residing in a selected RMA; only surgical patients
or individuals who die from certain causes at the selected hospital in
any sample RMA have a chance of being selected. The surgical patients
and cadavers that are available to the selected pathologist may not
necessarily be residents of the RMA that they are purported to represent,
because individuals may travel to another city for medical treatment.
The possibility of medical care migration is particularly problematic
for RMA's that are located on or near the borders of mirex areas (such
as Dallas).
To estimate the probability of a given individual being selected
within a sample site, one might use the number of pathologists and hos-
pitals, so that the probability of selecting any one pathologist at any
hospital in an RMA could be estimated. Then the population of suitable
surgical patients and cadavers to which the pathologist had access would
need to be estimated, so that a probability of selection of a tissue
specimen by that pathologist could be estimated. Even with this type of
information, the estimates of selection probability would be very rough
because the pathologists and tissue specimens in the MSS were not select-
ed in any random or systematic method but by purposive selection. At
this time, there is no reasonable adjustment that can be made to take
the above facts into consideration. Hence, equal probability of selec-
tion is assumed for the within-site stage of sampling. This method
involves dividing the number of specimens received by the population of
the RMA.
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The probability of an RMA being selected in the MSS is dependent
upon the study for which the site was originally selected. The selec-
tion criteria for the sites that were already part of the NHMP were
different from those for the sites that were sampled specifically for
the MSS.
The probability of selection of a site at the first stage is the
number of selections made divided by the number of possible selections;
this is the number of selected RMA's divided by the number of RMA's on
the frame, or
p ( 1st stage } _ number (n) of sample RMA's
(selection/ number (N) of RMA'S on the iist
For each of the eight RMA's that are part of the NHMP, the prob-
ability of selection is equal to 8/8, or a probability of selection of
one. These eight sites were included with certainty in the sample
because data collection systems already existed at these locations. For
RMA's that were selected as part of the supplementary or additional MSS
sample, the probability of selection is 32/60, or 0.53. The supplemen-
tary sites were selected by simple random sampling, which does not
consider the size of the population of the RMA's in the selection process.
When equal selection probability is used at the first stage and approxi-
mately equal sample sizes are selected from each of the primary sampling
units, this can result in oversampling small RMA's and cause underrepre-
sentation of RMA's that have large populations.
Weighting the observations within the sample site is used to adjust
for this. The weight of a given sampling unit is the inverse of the
"quasi" sampling rate. Hence, the weight for a given observation is
c , . . ... number of RMA's on list population of RMA
Selection weight = - r - j - ; — srrn - x — *-r£ - j - : -
° number of sample RMA s number of specimens
selected in RMA
In this study, as noted previously, some of the sample sites
selected did not submit valid tissue samples for analysis. To compen-
sate for this nonresponse, the inverse of the proportion of selected
sample sites that responded was used to adjust the weights. For example,
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data were submitted from five of the eight NHMP sites (5/8 or 62.5 percent
responded), which results in a nonresponse adjustment factor of 1.6 for
NHMP sites. The nonresponse adjustment for supplementary RMA's is 1.23,
the inverse of 26/32. This factor, multiplied by the selection weight
for an observation, produces a weight adjusted for nonresponse at the
first stage level. This technique is designed to reduce bias that might
result from this nonresponse. There was no information upon which to
base any adjustments for the sampling bias which might occur as a result
of the subjective selection of tissue specimens within selected sites.
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3. EVALUATION OF CHEMICAL ANALYSIS
3.1. Introduction
The objective of this portion of the study is to assess the reli-
ability of the results obtained from the chemical analytical procedures
employed in the MSS. The analysis of adipose tissue specimens for mirex
was carried out by the Michigan Department of Public Health (MDPH).
The analytical procedure used for the determination of mirex is de-
scribed in the EPA Pesticides Methods Manual (USEPA 1974). Specific
details regarding the collection, storage, and shipping of specimens
were described in the NHMP study report for mirex (Kutz and Strassman
undated). A number of raw mirex chromatograms, supplied by MDPH, were
examined in sufficient detail to allow for a meaningful assessment of
the quality of reported mirex levels.
3.2. Discussion
The method used for the determination of mirex levels was based on
the use of an external standard. Reference standards were injected
before, during, and at the end of each mirex specimen group. The stan-
dard consisted, usually, of a mixture of known amounts of mirex and
Aroclor 1260. This mixture served not only for purposes of quantitation,
but also provided a constant check on the degree of separation between
mirex and a late-eluting Aroclor peak. This peak represents an inter-
ference found in most tissue specimens due to the ubiquitous nature of
the Aroclors. In an effort to maximize the separation of the two peaks,
the gas chromatographic procedure was modified, and the analysis was
conducted at a temperature slightly below that recommended in the
Pesticides Manual. This procedure was approved by memo (Appendix H)
prior to chemical analysis. Chromatograms of Aroclor 1260, mirex, and a
mixture of 1260/mirex are depicted in Figures 3.1 through 3.3. Baseline
separation was achieved for mirex and the Aroclor 1260 peak, and this
separation was maintained throughout the analysis period covered by the
chromatograms examined (May 1976-November 1977).
The same quantity of Aroclor 1260 and mirex was injected for each
check. Thus, a measure of the reproducibility of injection could be
determined by measuring detector response (peak height) for these stan-
dards. A check of 17 such injections showed acceptably close agreement
(differences < 10 percent) between injections for a given specimen
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group. This agreement and the reproducible retention times observed for
the compounds over a period of several months are indicative of a stable
analytical system.
For a significant number of chromatograms, an interference peak
other than Aroclor 1260 was noted. Of some 50 chromatograms from which
a quantitative assessment of mirex was made, approximately half (26)
showed mirex. peak interference. The degree of interference varied
(Figures 3.4 through 3.6) but was not so severe as to prevent estimation
of levels of target compound.
Of the chromatograms examined, only one blank and two control
specimens were included. These specimens were not described so no
significance could be attached to them, except that the blank chroraato-
gram was "clean" in the area of interest.
To assess the reliability of the chromatographic and, to a limited
extent, the quantitative procedures used, all mirex peaks were measured
(peak heights) and the results compared with the peak height values
denoted on the chromatograms. Comparisons were also made of the amount
of mirex as calculated from the MDPH peak height values and as determined
by the measurements. These data are shown in Table 3.1. As can be
seen, the results are consistent with average absolute errors and stan-
dard errors (A%, see Table 3.1) of 9.2 + 2.1% for peak height measure-
ments, and 8.1 + 1.2% for calculated amounts. A check on the interper-
sonal variability was determined by independent measurements and calcula-
tions of the same parameters, i.e., peak height and amount of mirex.
Some 10 percent of the measured chromatograms were replicated in this
manner. These results are shown in Table 3.2. Again the data are very
consistent, with the average absolute error and standard error calculated
at 3.0 + 1.0 %. Thus, the measurement of mirex peaks and the calculation
of raw mirex amounts were straightforward, and, at least for the chroma-
tograms examined, no gross errors (inaccurate measurement, faulty calcu-
lation, peak assignment error) were evident.
As no completely adequate method exists for the quantitative statis-
tical treatment of "trace" levels of compound, an attempt was made to
ascertain the minimum detectable quantity (MDQ) of mirex as analyzed by
the MDPH. Since the MDQ was not available, an approximation was made
adopting the usual assumption of MDQ = 3 (signal/ noise). Since two
-14-
-------
Figure 3.1. Gas chromatogram - Aroclor 1260 standard.
-------
"(*>
>\
Figure 3.2. Gas chromatograra - tnlrex standard. Conditions as in Figure 3.1.
-------
Figure 3.3. Gas chromatogram - mixture of Aroclor 1260 and mirex
standards. Conditions as in Figure 3.1 except chart
speed is 0.5X.
-17-
-------
oo
Figure 3.4. Gas chromatogram - mirex containing specimen (moderate level)
with interference peak (moderate level). Conditions
as in Figure 3.1.
-------
I
H1
Figure 3.5. Gas chromatogram - mirex containing specimen (low level) with interference peak
(low level). Conditions as in Figure 3.1.
-------
I
to
u~~n
Figure 3.6. Gas chromatogram - mirex containing specimen (moderate level) with
interference (high level). Conditions as in Figure 3.1.
-------
detection systems were used in this study, MDQs were determined for each
at the beginning of the analytical runs (May 1976) and again at the end
(November 1977). For system one, the MDQ's were 16 pg at the beginning
and 20 pg at the end of the study; for system two, the MDQ's were 9 pg
and 12 pg at the beginning and end, respectively. The similarity of
these values bespeaks an extremely stable analytical system, with more
than adequate sensitivity for these types of analyses. Unfortunately,
these values could not be translated into the concentration values (ppm)
reported on the data file. This was due to the inability to relate the
specimen identifiers (specimen numbers) on the sample chromatograms with
the identifiers (patient numbers) reported on the raw data file. In
addition, information was not available regarding the exact analytical
procedures followed (e.g., analyte solution volume, dilution factors);
thus, specimen dilution factors could not be ascertained. The absolute
amounts of mirex, as shown on most of the chroma tograms, could not,
therefore, be converted to ppm fat.
Although a check on the reliability of the final reported mirex
concentration levels could not be made, the raw data indicate that sound
analytical quantitation procedures were followed, and the results are of
acceptable quality. Further assurance of the quality of the data is
provided by independent confirmation of the mirex levels using,
primarily, gas chromatography/mass spectrometry (GC/MS). Results of
analyses of some 23 specimens (Appendix I) showed good agreement between
the values reported by MDPH and those reported by the confirming labora-
tories.
The quality of the raw data, the results of the confirmational
analyses, and the stability of the analytical system are taken as good
indicators of reliable and accurate results. Although every aspect of
the analysis could not be checked (for example, calculations leading to
concentration values), no errors were noted from the available chemical
analytical data. There is no indication that the information as reported
on the raw data file is suspect.
-21-
-------
Table 3.1. Comparison of Mirex Peak Heights (mm) and Calculated
Amounts (pg) as Determined by Michigan Department of
Public Health and Quality Control Checks
Specimen
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
* A% =
Ht (MDPH)
17
108
19
54
58
43
13
75
75
20
20
78
15
98
28
0
0
0
0
15.5
32.5
118
6.5
22
0
32
12
60
21
71
124
56
107
15
18
12
54
X (QCC)
Ht (QCC)
16.5
113.0
20.5
57.0
77.0
43.5
13.0
76.5
82.0
20.0
20.0
81.5
15.0
99.5
33.0
0
0
0
0
15.0
32.5
119.0
6.5
23.5
0
32.5
16.5
67.0
23.0
80.0
126.5
60.0
120.0
11.0
17.5
17.0
70.5
- X (MDPH)
A%*
-2.9
4.6
7.9
5.6
32.8
1.2
0
2.0
9.3
0
0
4.5
0
1.5
17.9
-
-
-
-
-3.2
0
0.8
0
6.8
-
1.6
37.5
11.7
9.5
12.7
2.0
7.1
12.4
-26.7
- 2.8
41.7
30.6
nnm
Amt (MPDH)
187
2967
284
?
X
X
236
X
986
213
274
829
221
2020
412
0
0
0
0
470
198
2450
198
224
0
327
102
254
244
602
1442
577
973
7
?
120
378
Amt (QCC)
159
2729
271
1326
488
423
236
1855
982
185
240
755
190
2020
418
0
0
0
0
458
198
2466
198
209
0
289
115
205
217
557
1193
517
906
282
280
142
400
A%*
-15.0
- 8.0
- 4.6
-
-
-
0
-
- 0.4
-13.1
-12.4
- 8.9
-14.0
0.5
2.5
-
-
-
-
- 2.6
0
0.7
0
- 6.7
-
-11.6
12.7
-19.5
-11.1
- 7.5
-17.3
-10.4
- 6.9
-
-
18.3
5.8
X (MDPH)
-22-
-------
Table 3.2. Interperson Comparison of Mirex Peak Height
Measurements
Peak height (mm)
Specimen A B A %
1 85.0 82.0 3.7
2 21.0 20.0 5.0
3 20.0 20.0 0
4 79.5 81.5 -2.5
5 22.5 23.0 -2.2
6 25.5 23.5 8.5
7 60.0 60.0 0
8 29.0 29.0 -1.7
-23-
-------
4. UNWEIGHTED ANALYSIS
4.1. Data Description
The MSS data consisted of 664 observations from 31 responding
sites. 40 observations were excluded from analysis: 34 records were of
specimens collected outside the reference time period, and the lipid
extractable amount for 6 observations was less than 10 percent. There
were no data exclusions on the basis of inadequate chemical analysis
confidence codes. After exclusions, there were 624 observations avail-
able for statistical analysis.
In Chapter 2, there is brief mention of desired specimen quotas by
age, race, and sex (Appendix F). These quotas guided the field contact
in submitting specimens from a range of individuals. It should be kept
in mind that representativeness for factors of occupation and length of
residence in an area is not accomplished through balancing on age, race,
and sex information. The quotas were established in an attempt to
obtain information that would reflect the age, race, and sex distribution
of the living population.
Tissue specimens that fit the quota specifications were referred to
as design specimens; tissue specimens received in excess of the quota
guidelines were called surplus specimens. None of the sites filled
their quota of 27 design specimens even though 6 of the 31 responding
sites submitted 27 or more tissue specimens. There were 479 design
specimens and 145 surplus specimens. There is no difference in methodol-
ogy of selection or collection between the design and surplus specimens;
the designation was made in order of date of receipt and processing of a
valid specimen as the study year progressed. There seems to be no
obvious reason to exclude the surplus tissue specimens (23.2 percent of
the data) from weighted analysis and probably not from unweighted analy-
sis because design quotas were never satisfied.
Table 4.1 contains classifications for all tissue specimens within
Census Divisions by age, race, and sex. The desired quotas for racial
representation were met reasonably well within the South Atlantic and
West South Central Census Divisions and almost exactly within the East
South Central Census Division. The Census Division level desired distri-
bution by age group was not met; the 0-14 age group was consistently
underrepresented in all three divisions. This is to be expected because
-24-
-------
children do not die or undergo surgery in proportion to their representa-
tion in the population. The actual distribution of specimens classified
by sex was roughly in keeping with the desired quotas on the Census
Division level.
For the various sample sites the number of valid tissue specimens
submitted ranged from 1 to 37. Dallas, Texas, one of the NHMP sites and
the largest RMA in the MSS (2,455,000 people), was the location that
contributed only one tissue specimen. Dallas presents further analysis
problems because of its location, for it falls on the edge of a mirex
area and part of the defined RMA including Dallas falls outside of the
mirex area boundary. Because Dallas is the largest city in that part of
Texas (see maps, Appendix A), the population that relies on the medical
facilities in Dallas extends far beyond the boundaries of the mirex
counties. Houston and San Antonio are similarly situated in both geogra-
phical and medical terms. The locations of other RMA's are subject to
the same cautions in interpreting the residence of the individuals from
whom adipose tissue specimens were obtained. Some sites, such as those
in Louisiana, are clearly located in a heavily fire ant-infested region,
and for these, little ambiguity exists about the potential mirex exposure
of the population.
In future investigations it would be useful to obtain the zip code
of the home address of the patients from whom the tissue specimens are
obtained so that residence in a mirex area can be verified. However,
this still would not give any indication of the length of time an indivi-
dual resided in an area exposed to mirex. Level of exposure and inten-
sity of application of mirex to an area are also not known but are of
interest.
4.2. Data Analysis
4.2.1. Data Distribution
In the interpretation of estimates and statistical tests in this
section, which are based on unweighted analyses of MSS data, it must be
recognized that at least two categories of individuals are not as preva-
lent (underrepresented) in the sample as in the population. These are
people under age 15 and residents of the larger RMA's. In light of the
correlations between geographic location and mirex positives, the latter
imbalance may cause unweighted analysis to be seriously biased for
-25-
-------
Table 4.1 Specimens Collected for Each Census Division
By Age, Race, and Sex*
East South Central: Alabama and Mississippi
Number of Specimens
Caucasian
Non-Caucasian
Age Group
0-14
15-44
>45
Male
5
22
36
63
Female
7
29
43
79
142
Male
1
6
7
14
Female
2
5
12
19
Total
15
62
98
33
175
desired non-Caucasian quota = 5/27 = 18.5%
actual non-Caucasian representation = 33/175 = 18.9%
South Atlantic: Florida, Georgia, North Carolina, and South Carolina
Number of
Caucasian
Age Group
0-14
15-44
>45
Male
13
35
55
103
Female
8
29
52
89
Specimens
Non-Caucasian
Male
6
25
18
49
Female
10
11
20
41
Total
37
100
145
192
90
282
desired non-Caucasian quota = 6/27 = 22.2%
actual non-Caucasian representation = 90/282 = 31.9%
West South Central: Louisiana and Texas
Number of Specimens
Caucasian
Non-Caucasian
Age Group
0-14
15-44
>45
Male
7
18
28
53
Female
9
34
41
84
Male
2
7
7
16
Female
0
8
6
14
Total
18
67
82
137
30
167
desired non-Caucasian quota = 4/27 = 14.8%
actual non-Caucasian representation = 30/167 = 18.0%
Based on the results of the MSS and information in Appendix F.
-26-
-------
purposes of extending the results to all persons in the study population.
The weighted analyses in the following chapter should reduce this risk
of bias.
In examining the data, it is important to consider the distribution
of mirex levels before choosing summary statistics or conducting descrip-
tive analyses. Of the 624 specimens, 141 (22.6 percent) contained
detectable amounts of mirex. Eighteen (12.8 percent) of the 141 detect-
able values were trace quantities of mirex, present but not in sufficient
quantity to be accurately measured (see discussion in section 3.2).
These trace quantities were included in analyses where presence or
absence of mirex was measured but not included in those statistical
analyses where a specific numerical value was required.
The two histograms in Figure 4.1 illustrate the distribution of the
frequency of mirex residue values (in parts per million) for all 624
specimens and for the 123 specimens for which there were definite measur-
able quantities. It is obvious that the levels of mirex in the sample
do not follow a normal distribution (example at the bottom of Figure
4.1), even when the 501 zero (nondetectable) and trace values are
excluded. The skewing of the distribution to the right indicates that
the residue amounts follow a lognormal or exponential distribution, and
that a transformation of the data might yield a distribution of values
that would be more appropriate for meeting the assumption of normality
underlying many statistical tests. Figure 4.2 contains a histogram of
the result of a natural log (log ) logarithmic transformation of the
measurable positive raw (wet weight) residue amounts. It can be seen
that the distribution of the 123 transformed values in Figure 4.2 is
much closer to normal than the distribution of the same 123 untransformed
values in Figure 4.1. Log is usually used for biological data
transformation.
It should be noted that the actual distribution of mirex levels
contained in human adipose tissues probably consists of fewer true zeros
than current analytical techniques indicate. That is, if it were
possible to analyze the exact same 624 specimens using improved technol-
ogy, there would probably be fewer zeros reported and more positive
detections of some minute amounts of mirex. The skewing to the right
would still exist, but the distribution of values would more closely
-27-
-------
500 -
number of
specimens 400 -
300 -
200 -
100 -
n = 624 sample values:
zeros, traces, and
quantifiable positive
values
zeros and traces ' 0.5 1.0
Residue Amount, ppm
1.5
2.0
2.5
90 •
80 •
70 -
number of
specimens 60 •
50 -
40 •
30 -
20 -
10 -
n = 123 quantifia
positive valu
.A. .
<0.4
0.8 1.6 2.4 3.2
Residue Amount, ppm
4.0
4.8
68% of
values
normal curve
Figure 4.1 Frequency distribution for raw values of residue amount
*Based on results of Mirex Special Study, FY76.
-28-
-------
resemble a true continuous distribution if the presence of mirex in any
quantity, however small, could be measured.
The average minimum detectable quantity (using techniques available
in 1975-1977) estimated for mirex in human adipose tissues is within the
range 0.05 to 0.10 ppm. However, no specific numerical value could
reasonably be substituted or inserted for the 18 trace observations.
The 483 zero values could be transformed to a logarithmic scale if a
constant term was added to all values before transformation. This was
not done for the MSS because there are so many nondetectable values that
means and standard deviations of specific levels of mirex residues for
the entire sample would provide little information. Instead, it was
decided to look at the proportion of detectable versus nondetectable
values and at the quantifiable residue amounts. From this information
estimates can be made of the levels of definitely quantifiable mirex
residues in the proportion of the sample that has some discernible
quantity of mirex in their adipose tissues.
Both the proportion of positive values and the geometric mean of
the transformed quantifiable data were used as summary statistics.
Statistical tests are based on the simple arithmetic mean of the logari-
thmically transformed quantifiable data. Summary statistics are given
in terms of the geometric mean, which is an appropriate summary statis-
tic for logarithmic data. A geometric mean is the antilogarithm of the
arithmetic mean of logarithms. It is a good estimator of the median of
the underlying distribution of this data (Hartwell et al. 1979).
It has been specified by EPA that part of the analysis in this task
is to be carried out on the raw residue amount divided by the proportion
lipid extractable material (LEM) in the specimen. This quantity is
indicated by the term Y in the following pages. The natural log, log ,
was obtained for all 123 quantifiable positive values of Y. The two
histograms in Figure 4.3 are the distributions of Y and log Y. It
should be noted here that the adjustment of wet weight values by the
proportion of LEM does not affect the proportion of positive detections
of mirex residues in the sample. Presence or absence of mirex is inde-
pendent of the LEM adjustment.
-29-
-------
60
50
number of
specimens 40
30
20
10
•
•
•
__, ,__., ^ 1 , _
-4
-3
-2
-1
log mirex residue amounts
Figure 4.2. Frequency distribution for transformed values of wet
*
weight mirex residue
#
Based on results of Mirex Special Study, FY76.
-30-
-------
number of
specimens
80 -
70 -
60 -
50' -
40 -
30 -
20 -
10 -
AAA . . 1 . 1 . 1 i
<0.5 "'123456
Y
50
40
30
number of
Specimens 20
i n
iU
.
•
'
-4
-3
-2 -1 0 123
Y
Y = Mirex Residue Amount (ppm)/% Lipid Extractible Material
Figure 4.3 Frequency distributions of lipid adjusted mirex residue amounts
and transformed values (n=123 quantifiable positives)*
*
Based on results of Mirex Special Study, FY 76.
-31-
-------
4.2.2. Proportions of Positive Values
In Tables 4.2 and 4.3 are some simple classifications of the number
of detectable and nondetectable values by demographic and geographic
categories. In Table 4.2, which is a summary by State, the two States
with the largest percent of detectable mirex levels are Mississippi and
Louisiana, 46.3 and 35.7 percent positive, respectively. Georgia has
the third largest percentage of detectable mirex levels, at 20.9 percent.
The percentage of detectable mirex values drops to less than 8 percent
for the 5 remaining States. There were no positive values for the
specimens submitted from North Carolina and Texas.
This information by State suggests a possible connection between
residence in a widespread mirex-treated area with detectable mirex
levels in human adipose tissue. This is borne out by the highly signifi-
cant results of a chi-square test on the zero detectable/positive values
by State in Table 4.4. The empty cells for positive values for Texas
and North Carolina make the chi-square test results less reliable than
if there were some positive values for these states. However, the test
can still be used to infer that there are significant differences in the
percent of positive mirex residues detected by State.
Census Division was the only other variable investigated that shows
significant results in the chi-square test. Race, age, and sex did not
show significant differences in the percent positive mirex residue
values for the chi-square test results in Table 4.4.
The information in Table 4.3, which is a three-way classification
by race, age, and detectable mirex residues, is less easily summarized
than the data in the two-way classification in Table 4.2. When consider-
ing additional categories, it becomes necessary to consider possible
interactions between variables as well as simple main effects. This can
be done by computing an analysis of variance (ANOVA) or a regression
equation. A model such as the following can be used.
P. .... = |J + A. + S. + R. + L0 + e. ., „
r i j k 8, ijk£m
where
P. .... = mirex level in tissue for the m individual, the
'
3, location, in the (ijk) age-race-sex group;
= mean mirex level;
-32-
-------
A. = age effect for the i age group;
S. = sex effect for the j sex group;
J
R, = race effect for the k race group;
1C
I- = location effect of the & location;
£..,,, = random error.
ijkJtrn
In the above model, testing for age, sex, race, and location effects
corresponds to testing the equality of the A., S., R, , and L0. Standard
1 J K *
statistical computer software was used to carry out these tests for un-
weighted data, and specialized software is available at RTI for carrying
out the analyses for weighted data (see Chapter 5). A model similar to
the above is used for testing the proportion of positive values and the
arithmetic means of the positive values for mirex residues found in
human tissue.
A regression model was tested for the main effects of race, age,
sex, and location, with location being alternately defined as State or
Census Division. Then the model was expanded to include all possible
interaction terms. The dependent variable for this model was presence
or absence of mirex, indicated as 0 or 1 in the model. It is recognized
that log linear models are generally more appropriate than linear regres-
sion models for binomial (0,1) dependent variables. In the case of the
MSS data, there are so few specimens in some of the subgroups (cells)
that it is necessary to combine, or collapse, across subgroups to avoid
the problem of empty cells in the analysis. As illustration, the vari-
able age has three subgroups, which could be collapsed into two sub-
groups or into one group, which would then involve simply dropping age
from the analysis. This collapsing would result in positive proportions
of presence or absence of mirex that could then be analyzed by log
linear analysis. This defeats the purpose of the analysis; the sub-
groups that could be collapsed are the ones for which bias reduction is
sought and for which adjustment is being made.
The robustness of the regression technique should hold up in light
of the overall proportion of positives (22.6%) detected for the MSS
sample. This is based on the tendency of the binomial distribution to
approach approximate normality for measures of central tendency for
-33-
-------
Table 4.2. Detection of Mirex Residue by State: Number of j
Specimens with Positive and Zero Detectable Levels
State/number of responding RMA's
Number of Specimens
Alabama (3)
Florida (6)
Georgia (5)
Louisiana (5)
Mississippi (6)
North Carolina (1)
Texas (3)
South Carolina (2)
Zero
Detectable
36
129
72
83
73
18
38
34
483
Positive
3
8
19
46
63
0
0
2
141
Total
39
137
91
129
136
18
38
36
624
Percent
Positive
7.7
5.8
20.9
35.7
46.3
0.0
0.0
5.6
22.6
Based on results of the Mirex Special Study, FY 76.
-34-
-------
Table 4.3. Detection of Mirex Residue by Race and Age: Number
of Specimens with Positive and Zero Detectable Levels*
Number of Specimens
Race
Caucasian
Non-Caucasian
Age
Group
0-14
15-44
>45
Total
0-14
15-44
>45
Zero
Detectable
42
128
202
372
19
44
48
Positive
7
39
53
151
2
18
22
Total
49
167
255
624
21
62
70
Total
111
42
153
Total over race and age
483
141
624
-35-
-------
Table 4.4 Chi-Square Analysis Results for Zero Detectable/Positive
Values: Geographic and Demographic Variables*
2
Variable Number of % Positive within x df Significance
specimens each level level (p)**
AGE
0-14
15-44
>45
CENSUS DIVISION
East South Central
South Atlantic
West South Central
RACE
Caucasian
Non-Caucasian
SEX
Male
Female
STATE
Alabama
Florida
Georgia
Louisiana
Mississippi
North Carolina
South Carolina
Texas
70
229
325
175
282
167
471
153
298
326
39
137
91
129
136
18
36
38
12.7 4.53 2 0.103
24.5
23.1
37.7 49.65 2 0.0001
10.3
27.5
21.0 2.73 1 0.098
27.5
24.2 0.80 1 0.371
21.2
7.7 105.8 7 0.0001***
5.8
20.9
35 . 7
46.3
0.0
5.6
0.0
Total number of specimens (n) = 624.
VWr o
Probability that a x this large or larger might occur by chance, under
the assumption of no difference among categories.
***
Apparently highly significant, but over 5% of the cells have expected counts
less than 5. Sparse table indicates chi-square may not be a valid test.
-36-
-------
large samples (Snedecor and Cochran 1967). Therefore, the ANOVA, or
regression, model is appropriate in this case for analysis of detection
of mirex residues.
The results of this analysis are summarized in Tables 4.5 and 4.6.
When State was the location factor, the model gave a strong main effect
(p<0.0001) for location, even considering interaction effects. Mississippi
and Louisiana are the States which have significantly different propor-
tions of mirex detections from the remaining six States. When interaction
terms were not considered, race and sex were both significant. After
interaction terms were included in the model, these significant main
effects for race and sex disappeared. When Census Division was used as
the location factor, Census Division was highly significant (p<0.0001)
for the main effects of the all possible interaction terms model. Race
was the only other significant effect in either model involving Census
Division, and there were no significant interaction terms. The East
South Central Census Division (which contains Mississippi) and the West
South Central Census Division (containing Louisiana) have significantly
different proportions of positive mirex detections from the South Atlantic
Census Division.
In addition to examining the significance levels of the individual
F ratios, the fit of the model to the data overall should be considered.
2
The value of R is one indication of the appropriateness of the model to
2
describe the data. In general, the larger the value for R , the better
the model is as a description of the relationship of the dependent
variable (in this case, presence or absence of mirex residue in human
2
tissue) to the independent factors (age, race, sex, and location). R
can range from zero to one; a good fit is generally indicated by values
2 2
for R that are greater than 0.4. The value for R within a series of
models of the same variable will always increase as more interaction or
2
quadratic terms are added. This change in the magnitude of R can be
used to determine the relative contribution of an addition or deletion
2
of a term to the model. In this case, the R values for the 4 models
2
fitted are small; the two models including State have higher R values
than do the models including Census Division as the geographic boundary
of interest. This is logical, as the Census Division boundaries group
States on a proximity basis that does not necessarily reflect concentrated
-37-
-------
Table 4.5 Regression Model for Race, Age, Sex, and State:*
Zero Detectable/Positive Residue Values
Source
df
F Value'
Pr>F
Significance
Model 11
Error 612
Corrected Total 623
State
Race
Age
Sex
7
1
2
1
Model 73
Error 550
Corrected Total 623
12.92
18.89
.48
,45
,64
2.46
0.0001
0.0001
0.006
NS
0.057
0.0001
0.188
0.246
State
Race
Age
Sex
St x R
St x A
St x Sx
R x A
R x Sx
A x Sx
St x R x A
St x R x Sx
St x A x Sx
R x A x Sx
7
1
2
1
7
13
7
2
1
2
10
7
11
2
6.85
1.12
1.18
0.21
0.80
0.37
0.21
0.60
0.00
0.58
1.02
0.89
0.37
0.53
0.0001
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
*
Calculations unweighted and ignoring design effect.
Ratios of sampling variances used to test factor effects follow the F
distribution of the population variances are equal (null hypothesis).
#*
Probability that this might occur by chance under the assumption of
no difference among categories.
-38-
-------
Table 4.6 Regression Model for Race, Age, Sex, and Census
Division: Zero Detectable/Positive Residue Values*
Source
df
F Value1
Pr>F**
Significance
Model 6
Error 617
Corrected Total 623
Census Division 2
Race 1
Age 2
Sex 1
11.45
29.86
8.05
1.74
2.54
0.0001
0.0001
0.005
NS
NS
0.100
Model
Error
Corrected Total
Census Division
Race
Age
Sex
CD x R
CD x A
CD x S
R x A
R x S
A x S
CD x R x A
CD x R x S
CD x A x S
R x A x S
CD x R x A x S
34
589
623
2
1
2
1
2
4
2
2
1
2
4
2
4
2
3
2.73
20.07
6.82
0.46
0.78
1.10
0.89 '
0.59
0.19
0.50
1.11
0.98
0.23
0.35
0.41
1.64
0.0001 0.136
0.0001
0.0009
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
Calculations unweighted and ignoring design effect.
Ratios of sampling variances used to test factor effects follow the F
distribution if the population variances are equal (null hypothesis).
Probability that this might occur by chance under the assumption of
no difference among categories.
-39-
-------
mirex treatment area divisions. If percentage of a State's area treated
by mirex were considered, it would be more reasonable to group Louisiana
and Mississippi together for analysis than the Census Division grouping
of Louisiana and Texas.
4.2.3. Quantifiable Positive Values
The summary statistics for the 123 quantifiable positive values are
displayed in Tables 4.7 and 4.8. The data in these two tables are the
summary statistics for the log of both the raw residue amount and the
lipid extractable material (LEM) adjusted residue amount (Log Y). Both
of these values were analyzed in an unweighted regression analysis. The
model for this analysis is similar to the model used to detect differ-
ences in the presence or absence of mirex in the entire sample (624
observations).
The unweighted regression analysis did not show any significant
differences either in a simple main effects model or in examination of
interaction terms in the model. This indicates that if there are any
statistically significant differences for the level of concentration of
mirex residues among the categories of age, race, sex, and location of
selection sites, these difference do not fit a linear model.
4.2.4. Unweighted Analysis Conclusions
For this section, the results do not generalize to the target
population but reflect only the actual sample selected. Within this
group, it is observed that the most important factor in an individual
showing mirex residues in adipose tissue is the location of the selection
site. There were no significant differences found among any of the
demographic and geographic factors examined, in analysis of the 123
observations in this sample with quantifiable levels of mirex.
-40-
-------
Table 4.7. Summary Statistics for Quantifiable Positive Residue
Values: Geometric Means and Standard Errors*
Factor
All
AGE
CENSUS
RACE
SEX
STATE
Factor
Levels
0-14
15-44
>45
East South Central
South Atlantic
West South Central
Caucasian
Non-Caucasian
Male
Female
Alabama
Florida
Georgia
Louisiana
Mississippi
North Carolina
South Carolina
Texas
n
123
8
47
68
61
23
34
86
37
65
58
3
30
14
39
58
0
1
0
LOG Y**
Geometric Mean (ppm)
0.319
0.226
0.290
0.356
0.278
0.368
0.365
0.299
0.372
0.362
0.278
0.340
0.262
0.419
0.365
0.275
-
0.897
™
Standard Error
0.029
0.084
0.041
0.044
0.035
0.098
0.050
0.032
0.065
0.049
0.033
0.280
0.116
0.148
0.050
0.035
-
-
V
Calculations unweighted and ignoring design effect.
**
LEM adjusted values.
-41-
-------
Table 4.8. Summary Statistics for Quantifiable Positive Residue
Values: Geometric Means and Standard Errors*
Factor
All
AGE
CENSUS
RACE
SEX
STATE
Factor
Levels
0-14
15-44
>45
East South Central
South Atlantic
West South Central
Caucasian
Non-Caucasian
Male
Female
Alabama
Florida
Georgia
Louisiana
Mississippi
North Carolina
South Carolina
Texas
n
123
8
47
68
61
23
34
86
37
65
58
3
30
14
39
58
0
1
0
Log Residue Amount**
e
Geometric Mean (ppm)
0.220
0.117
0.205
0.250
0.190
0.237
0.267
0.211
0.245
0.239
0.201
0.290
0.177
0.269
0.267
0.186
-
0.420
™*
Standard Error
0.011
0.019
0.012
0.013
0.010
0.026
0.016
0.010
0.017
0.013
0.010
0.106
0.033
0.039
0.016
0.010
-
-
™
*
Calculations unweighted and ignoring design effect,
Wet weight residue values.
-42-
-------
5. WEIGHTED ANALYSIS
5.1. Introduction
The analyses presented in this chapter are weighted to offset
disproportionate sampling rates and, hence, to unbiasedly estimate for
the target population. Quasi-selection weights were calculated for each
observation and used to estimate population totals. Several software
programs developed specifically for weighted analysis of sample survey
data were used to obtain the summary statistics and regression analyses
(Holt 1977, Shah 1979).
5.2. Weight Formation
Weights are numerical values that are used to adjust sample data to
estimate information about the target population. Weights were calcu-
lated separately for each (geographic) site, as described in section
2.3. The observations within each site have the same weight, with no
adjustments for age, race, and sex distribution within the site. The
quotas established for each site are intended to create a self-weighting
sample with respect to age, race, and sex distribution. These quotas
were based on the demographic distribution of the living population of
the Census Divisions in which the sample sites were located, rather than
on the distribution of the population within the individual sites.
These quotas were not achieved within geographic site, although on a
Census Division level the desired proportions of race and sex were
approximately met (see Table 4.1). The age distribution was not met,
and this undoubtedly reflects the source of the selection population;
the younger population is not proportionately represented in the segment
of the population that undergoes surgery or dies in a large hospital.
After weights were calculated and added to the data file for each
observation, the weighted analyses were carried out. The estimates of
the proportion of positive mirex detections are presented in section
5.3. The estimates of the quantifiable mirex residues for the target
population are presented in section 5.4.
5.3. Estimates of Positive Mirex Detection
The parameters and statistical tests used are the same for the
weighted and unweighted analyses. The use of weights to produce popula-
tion-based estimates affects the calculation of statistics in a manner
that allows generalization of the statistics to the target population.
-43-
-------
Otherwise, the interpretation of the statistics is similar for the
weighted and unweighted test results.
A weighted chi-square test was used to examine the estimated propor-
tion of the target population with detectable mirex residues. The
weighted chi-squares were produced by a weighted chi-square SAS procedure
(Barr 1979). This produced an inflated (artifically large) statistic.
To adjust for this inflation before evaluating the resulting statistic,
the computed chi-squares were multiplied by the sampling fraction and
then divided by the design effect (Fellegi 1980). The sampling fraction
is the number of specimens in the sample divided by the target population
estimate. In this case, the sampling fraction = 624/23,371,372 = 2.67 x
10 . The design effect (DEFF) is the ratio of the variance for the
design employed to the variance that would be obtained for a simple
random sample. For the MSS, the DEFF was 7.99. This means that the
effective sample size here was equivalent to 78 observations selected by
SRS.
The results of this analysis are shown in Table 5.1. State was the
only significant factor for explaining differences in the proportion of
the target population that has detectable mirex residue in adipose
tissue. Mississippi was the State that had a statistically signifi-
cantly larger proportion of positive mirex detection.
A linearized weighted least squares analysis was used that incorpo-
rates the sampling structure into the regression model calculations
(Shah 1979). This analysis will not compute valid F statistics (for
testing factor effects on a continuous variable) if the number of PSU's
is smaller than the combined levels of the factors in the model. In the
case of a model that included State as the location factor, there are 8
levels for the factor State. When interaction terms are included in
this model, the sum of levels in the analysis rapidly increases beyond
the limits imposed by the sampling structure. Consequently, only main
effects models involving State as the location variable were computed at
this time.
The interpretation of the weighted regression model requires some
caution. The presence of significant main effects can be misleading in
some cases. It is important to consider possible interaction effects in
the model as well. Significant main effects in the presence of signifi-
-44-
-------
Table 5.1 Weighted Chi-Square Analysis Results for Zero Detectable/
Positive Values: Geographic and Demographic Variables*
Variable
Estimates
% Estimated Positive
within each
df
Significance
AGE
0-14
15-44
>45
CENSUS DIVISION
East South Central
South Atlantic
West South Central
RACE
Caucasian
Non-Caucasian
SEX
Male
Female
STATE
Alabama
Florida
Georgia
Louisiana
Mississippi
North Carolina
South Carolina
Texas
of N.
i
6,606,385
7,529,303
9,235,645
1,727,307
9,726,438
11,917,587
18,517,425
4,853,897
8,653,061
14,718,264
503,079
2,477,302
5,642,299
3,229,595
1,224,229
210,692
1,396,152
8,687,994
level
1.6
11.3
15.4
37.6
13.3
3.6
9.8
11.5
16.1
6.7
4.6
5.4
19.6
13.4
51.1
0.0
3.9
0.0
level (p)**
2.72 • 2 0.257
2.6 2 0.273
0.04 1 . 0.844
1.8 1 0.180
32.8 7 0.0001***
Estimate of N = 23,371,332 for the MSS target population.
refers to the subgroup i for a given variable.
The ith subscript
Probability that a X this large or larger might occur by chance, under
the assumption of no difference among categories. Significance is often
considered to be p < 0.05.
***
Apparently highly significant, but over 5% of the original cells have expected
counts less than 5. Sparse table indicates chi-square may not be a valid test.
-45-
V
-------
Table 5.2 Weighted Regression Model for Race, Age, Sex, and
Census Division: Zero Detectable/Positive Residue
Values*
Degrees of u. Pr>F**
Source freedom F Value Significance
Overall Model 6 9.30 0.0001
Census Division 2 3.53 0.042
Race 1 0.14 NS
Age 2 1.93 0.162
Sex 1 3.03 0.092
Overall Model 19 46.41 0.0001
Census Division
Race
Age
Sex
CD x R
CD x A
CD x S
R x A
R x S
A x S
2
1
2
1
2
4
2
2
1
2
/*/>/*
0~UJL
t\ t\ 4\
***
***
0.26
1.13
3.45
0.28
0.11
1.22
NS
NS
0.044
NS
NS
NS
Based on the results of the MSS FY76.
JLJU
Probability that this might occur by chance under the assumption of
no difference among categories.
Not testable in the presence of interactions.
Ratios of sampling variances used to test factor effects follow the F
distribution if the population variances are equal (null hypothesis).
-46-
-------
Table 5.3 Weighted Regression Model for Race, Age, Sex,
and State: Zero Detectable/Positive Residue
Values*
Source
Overall Model
Total
State
Race
Age
Sex
Degrees of
freedom
11
30
7
1
2
1
f
F Value1
11.38
16.11
0.23
0.91
2.72
Pr>F**
Significance
0.0001
0.0001
NS
NS
0.109
*
Based on the results of the MSS FY76.
j-jf
Probability that this might occur by chance under the assumption of
no difference among categories. Significance is often considered to be
p < 0.05.
Ratios of sampling variances used to test factor effects follow the
F distribution if the population variances are equal (null hypothesis).
-47-
-------
cant interaction terms involving the same factors that are in the main
effects can not be interpreted independently of the interaction terms.
The results for a weighted regression analysis for the estimated
presence or absence of mirex when Census Division is the location of
interest are in Table 5.2. A model containing all possible two-way
interactions produced a significant sex and Census Division interaction
relating to percent positive (p<0.017). In this interaction, there are
no significant differences in the East South Central or West South
Central Census Divisions between the proportion of males and females who
have detectable mirex residues, but there is a significantly higher
proportion of males than females with positive mirex detection in the
South Atlantic Census Division.
The model containing State was limited to a simple main effects
model, due to the restrictions noted above. Results for this model are
shown in Table 5.3. The significant main effect for State (p<0.0001) in
this analysis confirms the results of the weighted chi-square, which
also shows that the States have significantly different proportions of
their population with positive mirex residues. Mississippi is the State
that has a significantly greater proportion of positive mirex detections
than the seven other States. The main effect for sex in this model is
marginally significant (p£0.109). There may be some interaction between
sex and State; however, this could not be tested within the limits of
the software program used.
5.4. Estimates of Quantifiable Positive Values
The estimates of the geometric means and standard errors for the
log of the lipid extractable material (LEM) adjusted residue amounts
and the the log raw residue amount are in Tables 5.4 and 5.5. These
variables are also analyzed by the weighted regression technique
described in section 5.2.
The variable of most interest is the LEM adjusted residue amount;
three models involving this variable are listed in Table 5.6. The first
two models in the table are main effects models, one with State as the
location factor and one with Census Division. Neither model has any
significant main effects. The third model in Table 5.6 contains all
possible second order interactions. There are marginally significant
interactions for Census Division by age group (p<0.069) and for Census
-48-
-------
Division by race (p<0.0106). This indicates that there may be differ-
ences in levels of mirex concentraction among subgroups of the target
population. However, these differences are not straight-forward in the
sense that it can be assumed that the same subgroup had the highest
mirex levels in every Census Division. For example, Caucasians in the
East South Central and West South Central Census Divisions have higher
levels of mirex concentrations than do non-Caucasians. In the South
Atlantic Census Division non-Caucasians have higher mirex residue levels
than do Caucasians.
The same three models were analyzed for the unadjusted (wet weight
or raw) residue amount values. These results are in Table 5.7. There
is a significant effect for State (p<0.0027) and for age group (p<0.0138)
when State is the location tested. In the second order interaction
model, with Census Division as the location factor, the interactions are
similar to those obtained when the LEM adjusted residue amount is the
dependent variable in the same model.
5.5 Weighted Analysis Conclusions
The two weighted analyses are presented so that inferences can be
made about the population of the mirex treated areas. The use of two
different analyses provides a check on the test results.
The chi-square statistic is relatively assumption-free, but it is
less sensitive to differences than regression analysis. Regression
analysis, in turn, requires more assumptions to be met about the under-
lying structure of the data before it can be considered an appropriate
test.
It appears that geographic location is an important variable for
explaining percentage presence or absence of mirex in human adipose
tissue. Mississippi is the State that shows the largest proportion of
presence of mirex in human adipose tissue. There is less clear cut
evidence that there are any large differences in level of residue amount
in any particular category studied, although marginally statistically
significant results are found for several categories.
-49-
-------
Table 5.4 Estimated Summary Statistics for Quantifiable Positive Residue Values:
Weighted Geometric Means and Standard Errors*
Factor
All
AGE
CENSUS
RACE
SEX
STATE
Estimate of
population
Factor positives,
Levels N**
1
0-14
15-44
>45 1
East South Central
South Atlantic .
West South Central
Caucasian
Non-Caucasian
Male
Female
Alabama
Florida
Georgia
Louisiana
Mississippi
North Carolina
South Carolina
Texas
,919,220
88,474
504,045
,326,701
621,846
924,120
373,254
1,427,135
492,085
1,033,219
886,001
23,193
132,962
764,235
373,254
598,654
***
26,923
T^rA*
LOG Y - LEM adjusted Standard
Geometric Mean (ppm) Error
0.286
0.172
0.283
0.297
0.292
0.266
0.331
0.252
0.406
0.322
0.249
0.340
0.298
0.250
0.331
0.290
***
0.897
***
0.048
0.037
0.039
0.077
0.018
0.083
0.049
0.030
0.102
0.085
0.023
JUJt«JU
/\ f\ n
0.105
0.085
0.049
0.019
Jl~l~£.
***
***
***
Based on the results of the MSS FY76.
IL
'*
Estimate of total population for the mirex region = 23,371,372.
No information in sample on which to base estimate.
-50-
-------
Table 5.5 Estimated Summary Statistics for Quantifiable Positive Residue Values:
Weighted Geometric Means and Standard Errors*
Factor
All
AGE
CENSUS
RACE
SEX
STATE
Estimate of
Population
Factor positives Log Residue Amount
Levels N** Geometric Mean (ppm)
0-14
15-44
>45
East South Central
South Atlantic
West South Central
Caucasian
Non-Caucasian
Male
Female
Alabama
Florida
Georgia
Louisiana
Mississippi
North Carolina
South Carolina
Texas
1,919,220
88,474
504,045
1,326,701
621,846
924,120
373,254
1,427,135
492,085
1,033,219
886,001
23,193
132,962
764,235
373,254
598,654
***
26,923
***
0.197
0.095
0.192
0.209
0.189
0.187
0 . 244
0.184
0.240
0.208
0.186
0.290
0.190
0.181
0.244
0.185
***
0.420
***
Standard Error
0.010
0.009
0.012
0.017
0.003
0.017
0.014
0.011
0.020
0.018
0.006
-Hr*
0.030
0.018
0.014
0.003
***
***
***
***
Based on the results of the MSS FY76.
i_
Estimate of total population for the mirex region = 23,371,372.
c
No information in sample on which to base estimate.
-51-
-------
Table 5.6 Weighted Regression Model for Location, Age, Race, and
Sex Versus Quantifiable Positive Residue Amounts of Mirex*
Source
Degrees of
freedom
F Value1
Pr>F**
Significance
Overall Model***
7.42
0.0001
State
Age
Race
Sex
Overall Model
5
1
1
2
1.34
0.66
1.65
2.22
6.25
NS
NS
NS
0.1322
0.006
Census Division
Age
Race
Sex
2
2
1
1
0.85
2.02
2.25
0.77
NS
0.1561
0.1481
NS
Overall Model***
18
129409
0.0001
Census Division
Age
Race
Sex
CD X A
CD X R
CD X S
A X R
A X S
R X S
2
2
1
1
3
2
2
2
2
1
Not Testable
Not Testable
Not Testable
Not Testable
2.72
5.63
0.43
0.55
0.50
2.17
0.0690
0.0106
NS
NS
NS
0.155
Dependent variable in model is the log LEM adjusted mirex residue amount.
Ratios of sampling variances used to test factor effects follow the F
distribution if the population variances are equal (null hypothesis).
**•
Probability that this might occur by chance under the assumption of
no difference among categories. Significance is often considered to be
represented by p £ 0.05.
***
Full higher order interaction models not estimable.
-52-
-------
Table 5.7 Weighted Regression of Quantifiable Positive
Residue Amounts: Location, Age, Race, and Sex*
Source
Degrees of
freedom
F Value1
Pr>F**
Significance
Overall Model*** 9
State 5
Age 1
Race 1
Sex 2
Overall Model 6
Census Division 2
Age 2
Race 1
Sex 1
Overall Model***
34.18
5.20
5.24
1.34
0.01
13.70
1.31
4.
1.
83
70
0.02
0.0001
0.0027
0.0138
NS
NS
0.001
NS
0.0182
NS
NS
Census Division
Age
Race
Sex
CD X A
CD X R
CD X S
A X R
A X S
R X S
3
2
2
2
2
1
Not Testable
Not Testable
Not Testable
Not Testable
4.03
6.59
0.84
1.34
0.43
1.70
0.020
0.0057
NS-
NS
NS
NS
Variable log raw residue amount.
Ratios of sampling variances used to test factor effects follow the F
distribution if the population variances are equal (null hypothesis).
**
Probability that this might occur by chance under the assumption of
no difference among categories. Significance is often considered to be
represented by p £ 0.05.
***Models containing higher level interactions not computed.
-53-
-------
References
Barr AJ et al. 1979. A User's Guide to SAS-79. North Carolina: SAS
Institute, Inc.
BC. 1972. Bureau of the Census. 1970 Census of Population.
Characteristics of the Population (Volume I, Part A, Sections 1 and
2). Washington, DC: U.S. Department of Commerce.
Fellegi IP. 1980. Approximate tests of independence and goodness of
fit based on stratified multistage samples. JASA 75(370):261-268.
Hartwell T, Piserchia P, White SB et al. 1979. Analysis of EPA
Pesticides Monitoring Networks. Washington, DC: U.S. Environmental
Protection Agency. EPA-560/13-79-014.
Hartwell T, Piserchia P, White SB et al. 1979. Analysis of EPA
Pesticides Monitoring Networks. ADDENDA. Washington, DC: U.S.
Environmental Protection Agency. EPA-560/13-79-014.
Holt MM. May 1977. SURREGR: Standard Errors of Regression Coefficients
From Sample Survey Data. Research Triangle Park, NC: Research
Triangle Institute.
Kutz FW and Strassman SC. Undated. National Human Monitoring Program
Study Plan for Mirex Special Project. Internal document. Washington,
DC: Office of Pesticides and Toxic Substances, U.S. Environmental
Protection Agency.
Rand McNally and Co. 1974. Commercial Atlas and Marketing Guide. New
York, New York: Rand McNally and Co. Shah BV. June 1979. SESUDAAN:
Standard Errors Program for Computing
of Standardized Rates from Sample Survey Data. Research Triangle
Park, NC: Research Triangle Institute. RTI/1789/00-01F.
Snedecor GW and Cochran WG. 1967. Statistical Methods. Ames, Iowa:
Iowa Press.
Thompson JF, ed. 1974. Analysis of Pesticide Residues in Human and
Environmental Samples. Section 5A. Research Triangle Park, NC:
U.S. Environmental Protection Agency.
-54-
-------
APPENDIX A
State Maps Showing Counties Where Federally Assisted
Mirex Was Applied At Some Time During 1965-1974
A-55-
-------
Shaded areas had some application of mirex during the
period 1965-1974
-------
AfcBAMA
Counties, Standard Metropolitan Statistical Areas, and Selected Places
I
COLUMBUS
KUtCOGCC
OIUMBUS
LEGEND
® Places of 100,000 or more'inhabitants
• Places of 50,000 to 100.000 inhabitants
O Places of 25,000 to 50,000 inhabitants outside SMSA's
Standard Metropolitan
Statistical Areas (SMSA's)
M
A-57
-------
14
OO
IS
LEGEND
(•) PUces ol 100.000 01 more inhabitants
• Places ol 50.000 to 100.000 inhabitants
O Places ol 25.000 to 50.000 inhabitants outside SMSA's
•:*ri Slandatd Metropolitan
Statistical Areas ISMSA's)
FORT LAUDERDALE HOLL'
WEST PALM BEACH
p? V^..^rr|
.YWOOD »,,..„ ./
10
0>
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a
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2.
s
T3
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05
CO
Q>
3
Q.
C/)
-------
1
I
EORGIA
unties, Standard Metropolitan Statistical Areas, and Selected Places
i
-,'; CHATTANOOGA
' »
, ©CHATTANOOGA
LEGEND
® Places of 100,000 or more inhabitants
• Places of 50.000 to 100,000 inhabitants
O Places of 25.000 to 50.000 inhabitants outside SMSA's
J—1 Standard Metropolitan
Statistical Areas (SMSA's)
KS^S^;&V%s*'^&Jf£&K^-Vi&i\';;'"i^?T*~~"(*
^%ve>«
-------
10
11
12
13
LEGEND
® Places ol 100.000 or more inhabitants
• Places of SO.OOO to 100.000 inhabitants
O Places ol 25.000 to SO.OOO inhabitants outside SMSA's
PI Standard Metropolitan
Statistical Areas I SMSA's)
CD
3-
Q.
Q>
CD
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T3
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=1
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S
(D
0)
in
&)
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W
ro_
(D
a
8.
0)
O
(D
(A
CO
-------
*
SISSIPPI
Counties, Standard Metropolitan Statistical Areas, and Selected Places
LEGEND
® Places of 100,000 or more inhabitants
Q Central cities of SMSA's with fewer than 50,000 inhabitants
O Places of 25,000 to 50,000 inhabitants outside SMSA's
Standard Metropolitan
Statistical Areas (SMSA's)
H
Mi
10
A-61
-------
10 11 12 13 14
15
16 17 18
STOMS | 1KXHINCMAM I CASWIU I KRSON
WIN^Tpf^SALEM-HIGHl POINT
»»i«u«i \ WIL« » Kz^vvmym
H
LEGEND
® Places of 100,000 or more inhabitants
• Places of 50,000 to 100,000 inhabitants
D Central cities of SMSA's with fewer than 50,000 inhabitants
O Places of 25,000 to 50,000 inhabitants outside SMSA's
Standard Metropolitan
Statistical Areas (SMSA's)
H
a
s
3
C/J
sr
o
(D
0)
Q)
Q.
ay
CD.
(t)
Jl
8.
33
Q)
O IO 2O 3O 40 9O MILCS
I • I I I I —<
10 11 12 13 14 15 16 17
18
-------
10
11
12
13
to
LEGEND
® Places of 100,000 or more inhabitants
• Places of 50.000 to 100.000 inhabitants
O Places of 25.000 to 50,000 inhabitants outside SMSA's
Standard Metropolitan
Statistical Areas (SMSA's)
CHARLESTON
IO O IO «O *O 4O Mil
CO
f-+
Q)
3
Q.
CO
2-
3
T3
Q)
3
Q>
o
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(D
Q)
Q)
Q.
CO
O>
O
CO
o
(D
8
10
11
12
13
-------
10
II
12
13
14
16
17
TEXARKANA
.BEAUMONT-
PORT.ARTHUR
ORANGE
OUNCf
I AITNUI
GALVESTON TEXAS CITY
LEGEND
(•) Places ol 100.000 ot more inhabitants
• Places of 50.000 to 100.000 inhabitants
O Central Cities ol SMSA's with fewer than 50000 inhabitants
O Places of 25.000 to 50.000 inhabitants outside SMSA's
"—i Standard Metropolitan
Statistical Areas ISMSA's)
BROWNSVILLE HARLINGEN SAN BENITO
15 16 17
C
i-f
(D*
tn
Q)
=1
Q.
0)
(D
!-*•
s
T3
D)
=1
O)
<-^
Q)
>
0>
-------
APPENDIX B
Counties Where Federally Assisted Mirex was Applied at Some
Time During 1965-1974
Note: Population values based on 1970 Census Data
B-65
-------
Alabama
Total Population 3,444,165
All counties except
Colbert
Lauderdale
Lawrence
Limestone
Madison
Morgan
Marshall
Jackson
DeKalb
Cherokee
Mirex Area Popultation
Population
49,632
68,111
27,281
41,699
186,540
77,306
54,211
39,202
41,981
15,606
601,569
2.842.596
Florida
Total Population 6,789,443
All counties except
Monroe
Dade
Collier
Broward
Hendry
Palm Beach
Glades
Martin
St. Lucie
Indian River
Mirex Area Population
Population
52,586
1,267,792
38,040
620,100
11,859
348,753
3,669
28,035
50,836
35.992
2,457,662
4,331,781
B-66
-------
Georgia
Total Population 4,589,575
All counties except
Dade
Walker
Catoosa
Whitfield
Murray
Fannin
Gilmer
Union
Towns
Rabun
Habersham
White
Lumpkin
Dawson
Pickens
Gordon
Chattooga
Floyd
Polk
Haralson
Carroll
Douglas
Paulding
Bartow
Cherokee
Forsyth
Hall
Banks
Stephens
Franklin
Hart
Elbert
Madison
Jackson
Barrow
Walton
Morgan
Oconee
Clarke
Oglethorpe
Wilkes
Lincoln
Columbia
McDuffie
Warren
Taliaferro
Greene
Hancock
Glascock
Population
9,910
50,691
28,271
55,108
12,986
13,257
8,956
6,811
4,565
8,327
20,691
7,742
8,728
3,639
9,620
23,570
20,541
73,742
29,656
15,927
45,404
28,659
17,520
32,663
31,059
16,928
59,405
6,833
20,331
12,784
15,814
17,262
13,517
21,093
16,859
23,404
9,904
7,915
61,177
7,598
10,184
5,895
22,327
15,276
6,669
2,423
10,212
9,019
2,280
Jefferson
Burke
Jenkins
Emanuel
Candler
Mirex Area
Population
Population
17,174
18,255
8,332
18,189
6.412
1,031,614
3.557.961
B-67
-------
Louisiana
Total Population 3,641,306
All counties mirex treated
Population
3,641,306
Mississippi
Total Population 2,216,912
All counties except
Sunflower
Leflore
Humphreys
Sharkey
Issaquena
Bolivar
Coahoma
Quitman
Tallahatchie
Tunica
Panola
Tate
DeSoto
Marshall
Benton
Tippah
Alcorn
Prentiss
Tishomingo
Carroll
Holmes
Attala
Clarke
George
Stone
Pearl River
Hancock
Mirex Area Population
Population
37,047
42,111
14,601
8,937
2,737
49,409
40,447
15,888
19,338
11,854
26,829
18,544
35,885
24,027
7,505
15,852
27,179
20,133
14,940
9,397
23,120
19,570
15,049
12,459
8,101
27,802
17,387
566,148
1,650,764
B-68
-------
North Carolina
Total Population 5,082,059
New Hanover
Brunswick
Columbus
Robeson
Bladen
Duplin
Onslow
Lenoir
Jones
Craven
Pamlico
Cateret
Population
82,996
24,223
46,937
84,342
26,477
38,015
103,126
55,204
9,779
65,554
9,467
31,603
Mirex Area Population 578,223
South Carolina
Total Population 2,590,516
Marlboro
Dillon
Marion
Horry
Georgetown
Williamsburg
Florence
Clarendon
Sumter
Kershaw
Fairfield
Richland
Calhoun
Orangeburg
Berkeley
Charleston
Dorchester
Colleton
Bamberg
Barnwell
Aiken
Allendale
Edgefield
Lexington
Hampton
Jasper
Beaufort Point
Population
27,151
28,838
30,270
69,992
33,500
34,243
89,636
25,604
79,425
34,727
19,999
233,868
10,780
69,789
56,199
247,650
32,276
27,622
15,950
17,176
91,023
9,692
15,692
89,012
15,878
11,885
51,136
Mirex Area Population 1,469.023
B-69
-------
Texas
Total Population 11,196,730
Denton
Collin
Dallas
Bowie
Harrison
Smith
Orange
Jefferson
Polk
San Jacinto
Walker
Madison
Grimes
Harris
Galveston
Brazoria
Fort Bend
Waller
Austin
Washington
Wharton
Lavaca
DeWitt
Victoria
Bexar
Nueces
Montgomery
Brazos
Population
75,633
66,920
1,327,321
67,813
44,841
97,096
71,170
244,733
14,457
6,702
27,680
7,693
11,855
1,741,912
169,812
108,312
52,314
14,285
13,831
18,842
36,729
17,903
18,660
53,766
830,460
237,544
49,479
57,978
Mirex Area Population 5,485,781
B-70
-------
APPENDIX C
Definition of Mirex Treated Areas
C-71
-------
Definition of Mirex-Treated Areas
For purposes of the MSS, a mirex treated county is a county includ-
ing an area having any application of mirex during a 10-year period.
This definition does not take into consideration factors of repeated
applications, amount of active substance displaced, or land area covered.
Before being banned from sale and use in 1977, mirex was sold over
the counter to private individuals and applied by both State action
agencies and the States and Federal Government working together. It may
be possible to obtain mirex use information from individual State action
agencies and from the United States Department of Agriculture's Animal
and Plant Health Inspection Service (USDA, APHIS) that would help answer
some of the above questions about the frequency and intensity of mirex
application. For example, this kind of historical information about
mirex application in the State of North Carolina can be gathered from
existing records in the North Carolina Department of Agriculture's Pest
Control Division.- Information from the APHIS of USDA concerning the
number of mirex-treated acres by State is available; this only includes
those acres treated from 1964 to 1973 by the Federal Government in
21
connection with the individual States.- Additional mirex treatment
must have varied from State to State, dependent upon the magnitude of
the fire ant problem and the resources of the State.
It would be inconclusive, however, to attempt to correlate detailed
information about mirex use with this human adipose tissue data.
Specific residence information was not obtained about the individuals
from whom specimens were collected. In an epidemiological study such as
this, it is more important to verify the residence of study individuals
than to form a better definition of the area in which the individuals
can only be assumed to reside.
- Singletary HM. May 8, 1980. Personal communication, C. Leininger.
Raleigh, North Carolina: Pesticide Division, North Carolina State
Department of Agriculture.
2/
-Table of Aggregate Acres Treated, provided to EPA by APHIS.
Revised date 8/1/73.
C-72
-------
APPENDIX D
MSS Sample Site Selection Method
D-73
-------
MSS Sample Site Selection Method
D.I. Introduction
In order to calculate appropriate weights that can be used in
making population estimates from sample data, the method used to select
the sample must be known. This appendix is a discussion of the method
used to select the sample RMA's for the MSS. For the NHMP, the method
used to select sites involved selection with probability proportional to
the size of the site's population (PPS) and with replacement. The NHMP
study plan for the MSS- is not clear as to the method used to select
sites for the MSS. The selection procedure for the MSS was checked by
calculating the expected outcome of selecting 32 out of 60 RMA's by both
PPS and simple random sampling (SRS). It was concluded that SRS was the
method used.
D.2. The NHMP and Probability Proportional to Size
The method of sample selection used in the NHMP was systematic
selection with probability proportional to size (PPS) from a stratified
sampling frame. This means that the population of a city was a factor
in the possibility of the city being selected in a sample. When n areas
are to be selected systematically with PPS, the selection probability
for a given area is calculated by dividing n times the population of
that area by the total population of all the areas in the sampling
frame. This is expressed as
i
, .. , v-i -4. /T.T.OA c -i n x population of area i
selection probability (PPS) of area i' = - *-*• - ,
N
I population of area i
where N is the number of areas in the sampling frame. If some units
have a size measure greater than the sampling interval, this expression
should be termed expected number of hits as opposed to selection
probabilities.
NHMP cities were selected by PPS, within strata defined by Census
Divisions. As discussed in Chapter 2, the 8 NHMP cities located in the
mirex area were included in the MSS. This was an effort to use the
D-74
-------
existing tissue collection network. The MSS supplementary sample was
selected from 60 RMA's not in the NHMP. The majority of the existing
documentation of the MSS indicates that SRS was used to select the 32
MSS sites.
D.3. Simple Random Sampling
In SRS, any RMA has the same chance of being selected as any other
RMA in the list of 60 RMA's in the mirex area. A listing of the eligible
sites might be made and a consecutive number assigned to each site. A
sample of sites can then be selected by drawing numbers (sites) from the
list using a table of random numbers.
If SRS was used to choose the 32 RMA's, then any one RMA was as
likely as any other to be chosen. To test this, the 60 RMA's were first
ordered by population size, and then divided into 4 groups, each with 15
RMA's. There were 32 RMA's actually selected. Under SRS it would be
expected that approximately the same number of RMA's would be selected
from each of the 4 divisions that have been arbitrarily made in the
ordered listing. This can be seen more easily in the line chart below,
where the 4 segments or groups are indicated by Roman numerals, with a
subscript "s" or "f" to indicate membership in the sample or in the
frame.
1
1
I
s
:f
8
15
II
s
Hf
16
30
III
III
s
f
24
45
IV
s
IVf
32 =
60 =
sample
frame
RMA's
RMA's
In repeated sampling, the average proportion of selected RMA's from
a segment of the frame will be one-fourth. Since it is a random process,
there will be some variation in the number of selected RMA's from a
segment of the frame. A 95 percent confidence interval (C.I.) will
give the range of values that will be encountered 95 out of 100 times a
given sample selection procedure is used. The expected number of sites
selected by SRS in any of the 4 segments of the frame is one-fourth of
32, or 8. To find a 95 percent confidence interval for the number of
sites chosen from each segment, computations were based on the variance
of the number of sites selected per segment and the properties of the
normal curve. These calculations are given in detail in section D.6.
For this case, where 8 is the expected number of sites selected from a
segment, the 95 percent C.I. is 8 + 1.96V 6 = 8 ± 4.8.
D-75
-------
The number of sites selected under SRS can range from 3.2 to 12.8
sites within a 95 percent C.I. This agrees with the actual distribution
of sites among the arbitrary segments, as indicated in the chart below.
I II III IV
s s s s
Expected number
of sites (SRS) 8 ± 4.8 8+4.8 8 ± 4.8 8 + 4.8
and the 95% C.I, .
Number of sites 8 5 8 11
actually in the MSS
Another method that can be used to check the observed number of
sites selected against the number of sites expected under SRS is the
2
chi-square (x ) test. This test compares the expected results (F) to
the actual results (f) under the hypothesis of no significant difference
2
between expected and observed result. The value of the x statistic is
computed using the following formula.
, *
X
F.
i
2
where x = chi-square statistic ,
f. = observed number of sites for the ith segment ,
and F. = expected number of sites for the ith segment .
Any standard statistical text will contain a more detailed description
of this simple test. A thorough explanation is given in Chapter 3 of
Statistical Methods by Snedecor and Cochran (1967).
2
For these data, the value of x under the assumption of SRS is
2.25, which with 3 degrees of freedom (number of segments (4) minus 1 =
3) has a p-value of 0.522. This is not at all significant; the test
hypothesis of no difference between the expected results under SRS and
the observed results cannot be rejected as false.
D.4 Probability Proportional to Size
The same arbitrary segments were created, and 95 percent C.I.'s for
the number of sites selected from each segment were calculated, assuming
selection PPS. The selection rates varied from segment to segment,
D-76
-------
because the combined population of the areas within a segment determined
the sampling rate for that segment. The combined population for each of
the four divisions varied considerably: I_ = 730.600, II,, = 1,159,800,
r r
IIIF = 2,124,100, and IVp = 6,779,200, for a frame total of 10,793,700.
The selection probabilities also varied accordingly, from Pr(I ) =0.07
s
to Pr(IV ) = 0.63. C.I.'s for the number of selected sites from each
S
segment under PPS were computed and are displayed in the chart below.
Expected number
of sites (PPS)
and the 95% C.I.
Actually selected 8 5 8 11
for MSS
s
2.2 ± 2.8
II
s
3.4 ± 3.5
III
s
6.3 ± 4.4
IV
s
20.1 ± 5.4
The number of sites actually selected in 2 of the 4 segments falls
outside the 95% C.I. for number of selected sites from the segment when
selection is PPS. The result is in agreement with the results of a
chi-square test for expected number of sites under PPS to the observed
2
number of sites selected for the sample. The x in this case is 20.6,
which with 3 degrees of freedom has a p value of 0.0001. This is highly
significant and indicates that the hypothesis of no difference cannot be
accepted as true.
D.5. Conclusions
Based on the computations described in Section D.3 and D.4, it
appears that the MSS sample sites were selected by simple random sampling.
Therefore, the selection rates used in computing the quasi selection
weights were calculated under the assumption of SRS.
D.6. Calculations
This section contains a detailed description of the calculation of
confidence intervals for the number of sites selected per segment when
selecting 32 of 60 RMA's by SRS. The method used to determine C.I.'s
when using PPS sampling is similar to that used in SRS, and will be
described briefly.
Confidence intervals are calculated using the properties of the
normal curve and the variance of a random variable. In this case, the
D-77
-------
random variable, which can be called y, is the number of sites that will
be selected from a given segment. The distribution of y is binomial.
Variances are calculated for binomial random variables (in this case,
the Bernoulli event is that a site is selected in a given segment or it
is not selected in that segment) by multiplying the total number of
sites selected by the probability (p) that the selected site is in the
segment by the probability (q) that it is not. Thus, the variance of y
can be expressed as V(y) = npq.
The probability that a selected site falls in a given segment is
8/32 = 1/4 = p. The value of q is then 24/32 or 3/4. The variance will
be the same for the number of sites selected in each segment:
32(l/4)(3/4)=6. To find the 95 percent C.I. for y (where y is the
number of sites selected for a segment) requires multiplying the square
root of the variance (this is the standard deviation) by 1.96. The
constant 1.96 is a value (called a z score) which corresponds to 95
percent of the area under the normal curve. Other constants, which
correspond to different percentages of the area under the normal curve,
can be found in a table of z scores in any standard statistical text.
In this case, where the probability that a selected site falls in the
given segment is the same for all segments, the 95 percent
C.I. is 8 ± 1.96V~1T~ = 8 ± 4.8 for each segment.
To find the 95% confidence interval for number of selected sites
falling in a given segment, assuming PPS, the same procedure is followed
as for SRS, except that the probability of a selected site falling in a
given segment is different for each segment. This reflects the differ-
ence in the population size of the sites in the frame. To calculate the
expected number of sites in a segment, the probability of selection for
a segment is multiplied by the number of sites desired in the final
sample. As an example, for segment If, with Pr(selection) = 730,600/
10,793,700 = 0.07, the expected value of y = (0.07)(32) =2.2. The
variance of y was calculated separately for each segment, and the C.I.'s
computed for each segment as was done when assuming SRS.
- Kutz F W and Strassman S C. undated. National Human Monitoring
Program Study Plan for Mirex Special Project. EPA internal document.
Washington, DC: Office of Pesticides and Toxic Substances, U.S.
Environmental Protection Agency.
D-78
-------
APPENDIX E
List of MSS Collection Sites
E-79
-------
COLLECTION SITES
Alabama
Anniston
0 Birmingham
Dothan
°*Mobile
0 Montgomery
* Tuscaloosa
Florida
Fort Myers
Fort Walton Beach
Lakeland
Orlando
°*Panama City
Sarasota
0 St. Petersburg
Tallahassee
°*Tampa
Georgia
Atlanta
0 Brunswick
Columbus
Ma con
Savannah
x Valdosta
Louisiana
Alexandria
0 Lafayette
Lake Charles
Monroe
* New Orleans
Shreveport
Albany, Georgia
Opelika, Alabama
Melbourne, Florida
Bryan, Texas
RMA Population-'
93,100
679,000
51,200
312,500
201,000
106,300
83,500
76,500
97,000
473,000
72,000
222,000 '
625,000
121,500
495,000
1,720,000
54,300
226,700
219,500
184,000
50,100
97,500
128,800
128,500
110,800
1,126,000
282,000
Mississippi RMA Population-
Columbus 43,200
0 Greenville 51,100
Hattiesburg 57,200
Jackson 258,000
Laurel 41,000
Meridian 56,200
Pascagoula 74,900
North Carolina
Wilmington 91,300
South Carolina
Charleston 290,000
Columbia 315,000
Texas
* Dallas 2,455,000
* Houston 2,085,000
* San Antonio 890,000
••'-'.-"
ALTERNATE COLLECTION SITES -/
94,800
46,700
100,000
60,700
Gadsden, Alabama 79,000
Jacksonville, Florida 585,000
Baton Rouge, Louisiana 361,000
Pensacola, Florida .217,000
Gulfport, Mississippi 173,500
*
X
o
1
2
National Human Monitoring Site
Replaced by Albany, Georgia, in survey
Nonresponding Site
1974 Rand McNally Population Estimates
Listed in Order of Selection
E-80
-------
RMA Remainder Frame After Selection of
Collection Sites and Alternates
Florida
Cocoa
Daytona Beach
Gainesville
Titusville
Winter Haven
Georgia
Augusta
Louisiana
Houma
New Iberia
North Carolina
Jacksonville
South Carolina
Florence
Sumter
RMA
Population —
Texas
RMA Population -'
I/
87,000
117,000
97,000
39,000
64,800
215,500
53,000
40,500
71,000
49,600
69,600
Beaumont-Port Arthur 226,000
Corpus Christi 257,000
Freeport-Lake Jackson 58,700
Galveston-Texas City 135,000
Orange 51,600
Texarkana 75,000
Tyler • 79,200
Victoria 45,400
1974 Rand McNally Population Estimates
Remainder Frame: The sites remaining .after sample selection has been
made from the frame of target sites.
E-81
-------
APPENDIX F
Quotas for Mirex Special Study Specimens
-------
NATIONAL HUMAN MONITORING PROGRAM
U. S. ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, D. C. 20460
QUOTA FOR MIREX SPECIAL PROJECT
Each collection site in the states of Alabama and Mississippi is
requested to collect human adipose tissue from the following
age/sex/race groups:
QUOTA AGE GROUP SEX
4 0-14 Male
4 0-14" Female
5 15-44 Male
6 15-44 Female
4 45 and above Male
4 45 and above Female
Quota of 27 samples should include 5 non-Caucasian specimens.
Proportional distribution of these non-Caucasian specimens
among the age/sex groups is preferable but not required.
F-83
-------
NATIONAL HUMAN MONITORING PROGRAM
U. S. ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, D. C. 20460
QUOTA FOR MIREX SPECIAL PROJECT
Each collection site in the states of Louisiana and Texas
is requested to collect human adipose tissue from the following
age/sex/race groups:
QUOTA AGE GROUP SEX
4 0-14 Male
4 0-14 Female
6 15-44 Male
6 15-44 Female
3 45 and above Male
4 45 and above Female
Quota of 27 samples should include 4 Non-Caucasian specimens.
Proportional distribution of these non-Caucasian soecimens aroono
the age/sex groups is preferable but not required.
F-84
-------
NATIONAL HUMAN MONITORING PROGRAM
U. S. ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, D. C. 20460
QUOTA FOR MIREX SPECIAL PROJECT
Each collection site in the states of North Carolina, South Carolina,
Georgia and Florida is requested to collect human adipose tissue from
the following age/sex/race groups:
QUOTA AGE GROUP SEX
4 0-14 Male
4 0-14 Female
5 15-44~ Male
6 15-44 Female
4 45 and above Male
4 45 and above Female
Quota of 27 samples should include 6 non-Caucasian specimens. Proportional
distribution of these non-Caucasian specimens among the age/sex groups
is preferable but not required.
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APPENDIX G
Instructions to Pathologists
G-86
-------
Dear :
has been selected as one of 40
representative cities in which the U. S. Environmental-Protection
Agency would like to conduct a special research study to determine
the frequency of finding residues of the insecticide, mi rex in
humans. This letter is an invitation to you to participate
in this study. This project is an activity of the National
Human Monitoring Program for Pesticides and will be ongoing for
the next 6 to 9 months.
Mirex is an organochlorine insecticide which has been used
for the control of the imported fire ant in large areas of the
southern United States. Our information indicates that over
14 million acres have been treated to date. Mirex is extremely
resistant to chemical degradation and thus its persistence enables
it to accumulate in certain organisms in the food chain. As you
will note from the enclosed reprint, mirex has been found in
humans. We now need to make a more precise estimate of the
epidemiology of this chemical.
As a mechanism for estimating exposure to mirex, samples of
human adipose tissue will be chemically analyzed in our laboratories.
Reports of findings will be furnished to each participating physician.
Data from these analyses are useful in evaluating various factors
and conditions pertaining to human health and pesticide regulation.
G-87
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We will need samples of human adipose tissue from previously
excised surgical specimens and/or postmortem examinations. The
samples should be collected in accordance with the enclosed
guidelines. Each participant is being asked to collect specimens
according to the enclosed age/sex/race quota form. We furnish
all supplies (mailers, forms, bottles, postage-paid address cards,
etc.) and are able to remunerate you or your designee for professional
services at the rate of $10.00 per acceptable sample.
We hope that you will help in this study by providing selected
adipose tissues obtained during routine pathology. We will telephone
you about this in a few days.
Sincerely yours,
Frederick W. Kutz, Ph.D.
Project Officer
National Human Monitoring Program (WH-569)
Enclosures
G-88
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INSTRUCTIONS FOR THE COLLECTION OF
HUMAN ADIPOSE TISSUE FOR MIREX
ANALYSIS
Mi rex is an organochlorine insecticide used for the control
of the imported fire ant in large areas of southern United States.
The chemical is extremely resistant to degradation and this
persistence and its chemical characteristics enable it to
accumulate in certain organisms in the food chain.
The objective of this special environmental study is to
determine the incidence and levels of mi rex in human adipose
tissue collected from areas which have been treated with this
chemical. The results from the program are used in evaluating
various factors and conditions pertaining to human health and effective
pesticide regulation.
The adipose tissue for this project is secured through the
cooperation of participating pathologists located throughout
southern United States. The tissue is obtained from surgical
specimens previously excised for pathological examination and from
postmortem examinations. The specimens are sent to the program
office in Washington, D. C., from which they are then forwarded to
contract laboratories for chemical analysis. Periodic reports of
the laboratory results are sent to each participating pathologist
for the tissues which were submitted under his auspices. Summaries
comparing results with other regions are also provided as they become
available.
-------
In order to develop precise epidemiologic data, collections
must be made according to an experimental design which dictates
the number of samples required according to the demographic
distribution of the population of your area. You should have a
copy of the quota of samples expected to be collected from your
location on a fiscal year basis. All collections should be made
according to this age/sex/race distribution. You should be able
to collect the number of samples required in each category in the
next 6 months. If you feel that you will be unable to collect the
number of samples required, please let us know.
Criteria for Selection of Patients to be Sampled
Since the program objective is to reflect pesticide incidences
and levels in the general (man-on-the-street) population, a few
suggestions are listed here for your guidance:
. The highest priority should be given to satis-
fying the number and demographic distribution
of your quota. This quota should be completed
as soon as possible after the start of the project.
. Patients having known or suspected pesticide
poisoning should not be sampled. If you are
involved with a potential pesticide poisoning,
we would like to assist you in any way possible.
However, samples should not be taken for the
National Human Monitoring Program.
fSr-fO
-------
. Patients with cachexia or who have been institu-
tionalized for long periods should not be sampled
for the national program.
Collection of Surgical Adipose Tissue
Collect samples of adipose tissue from living patients from
unfixed specimens which have been surgically excised for therapeutic
reasons. Take special care to keep samples from different patients
separate and correctly and securely labeled and to avoid their con-
tact with other chemicals such as paraffin, disinfectants or plastics.
At least five grams of good quality (subcutaneous, perl renal,
mesenteric) adipose tissue should be collected from any part of the
specimen; avoid fibrous or connective tissue, I.e., omentum. Place
the fat, without any fixatives or preservatives, Into the chemically-
cleaned container that you have been given and legibly complete, in
ball-point pen or pencil, and attach the self-adhesive label. The
bottle labels should be affixed before freezing. Store the specimens
up-right in a freezer at -4°F (-20°C) until shipment.
Collection of Postmortem Adipose Tissue
Adipose tissue samples must be obtained only from unembalmed
cadavers. The interval between death and the collection of tissue
should be as short as possible and must not exceed 24 hours,
assuming refrigeration during the interval. Samples of adipose
tissue must weigh at least five grams and should be placed in the
(3-91
•v
-------
supplied chemically-clean container with a completed label affixed.
Specimens should be stored at -4°F (-20°C) without any fixative or
preservative until shipment. Submit only good quality fat; do not
submit omentum as it contains too much connective tissue for satis-
factory analysis.
Adipose should be taken dry, and should not be rinsed before
placing in the containers provided. Many water supplies contain
materials which would interfere with chemical analysis.
Instruments should be well-rinsed with distilled water and
dried before taking the adipose sample.
Completion of the Patient Summary Report
A Patient Summary Report should be completed for each patient
from whom a sample was taken. Special attention should be given to
the completeness of the information. First and last Initials, in
that order, should be used instead of the complete name to insure
that confidentiality is maintained. The Initials, along with the
date of birth, sex, and race, are used 1n this office to compose the
AMA identification number. The patient's Identification number and/or
the pathology department's accession number are for your Information
in referring back to the individual patient when you receive the
results of the pesticide analysis.
Confirmed diagnosis should be detailed in the spaces provided.
Only the major ones should be supplied.
-------
Other information required should be completed as accurately
as possible. The completed forms should be held and sent under the
lid of the insulated container when shipment is made.
Packing and Shipping
Tighten all lids on the specimen bottles carefully. This is
important since we are required to use special aluminum foil cap
liners which make tightening a little difficult. Be certain that
a completed bottle label is firmly attached to each specimen bottle.
Wrap each bottle in gauze or paper to prevent breakage during ship-
ment and to keep the label on the container. Place the specimen
bottles in the insulated mailer and fill it wi.th dry ice. If you
have difficulty obtaining dry ice, please call us and we can arrange
alternative methods of refrigeration for you.
.A franked addressed label is on the reverse side of the address
card. This card is marked AIR MAIL - SPECIAL DELIVERY. (Do not
send Air Express, please). There is no cost to the sender because
of the franked label. All insulated mailers should have a PERISHABLE
PACKED IN DRY ICE label visible from all sides on the outside.
i
Specimens should be mailed on a Monday or Tuesday of a week with
no federal holidays. This assures that they will arrive before the
end of the work week on Friday.
G-93
-------
Patient Summary Reports should be sent in the carton with
the specimens when possible. They can be folded and placed on
the top of the styrofoam lid.
Only samples which meet our criteria and are handled according
to the guidelines can be accepted. No substitute containers will
be accepted.
For Further Information
If you have any questions or comments, please contact us.
Telephone (collect): 202-755-8060.
Frederick W. Kutz, Ph.D.
Sandra C. Strassman
National Human Monitoring Program
..G-94
-------
APPENDIX H
Modification of Mirex Analysis Protocol
GC Column Temperature
H-95
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ENVIRONMENTAL TOXICOLOGY DIVISION
HEALTH EFFECTS RESEARCH LABORATORY
UNITED STATES ENVIRONMENTALPROTECTION AGENCY
Research Triangle Park, North Carolina 27711
SUBJECT-. Multiresidue Analysis of Adipose Tissue with DATE: March 1, 1976
Emphasis on Mi rex and Chlordane/HeptacJilor Derivatives
FROM:
TO:
Chief, Quality Assurance Section, ETD, EPA, HERL,
Research Triangle Park, N.C.
Michigan Project, Mr. R. L. Welch
After receiving a copy of Bob Welch's letter to Dr..Kutz (2/11/76)
we cranked up a straight 5% OV-210 and a mixture column of 1.5/1.95,
OV-17/OV-210 and ran some chromatograms in the appropriate concentration
ranges incorporating the derivatives of heptachlor/chlordane, mirex, and
Aroclor 1260.
V
Frankly, we were not overjoyed by the elution patterns produced
by Aroclor 1260 and Mirex. As Bob commented in his letter, at 200°C
Mirex overlaps nearly completely with the next to last Aroclor peak
(a major one). However, at 195°, although the separation is slightly
better, we could not agree that it was anything remarkable on our
column. Our separation was not nearly as good as the separation
in Bob's chromatogram. We dropped the column temp, to 190°, and while
the mirex peak was clearly visible on the early side of the Aroclor, it
was not a quantifiable separation.
Undoubtedly, the relative efficiency of his column vs. ours was a
factor. We estimated his column to be yielding about 3,200 T.P. with
his carrier flow obviously cranked down. To compensate for the exces-
sive time consumption at 190°, we raised the flow to 80 ml with a - .
resulting EFF. of about 2,700 T.P. Undoubtedly, our resolution
characteristics suffered accordingly.
Just so long as Bob's column holds up and he can continue to
obtain the separations shown in his sample chromatograms, we see no
objection at all to making temperature and/or carrier flow adjustments
in any way that it will best get the job done. There is nothing
sanctified in the recommended parameters in the manual. They were
written for a shotgun approach to general multiresidue work, but if
some other combination is more suitable for special purposes, then by
all means, appropriate modifications should be made.
Even with our poor separation, I believe the chromatographer would
be alerted to the possible presence of mirex, then by further confirmation
via ECD and GC/MS the final answers can be obtained.
I'm sure we will want to get together for further discussions
of this topic the week of the chemists' meeting.
cc: Dr. F. W. Kutz, Washington
Dr. H. F. Enos, Athens
EPA Form 1320-6 (Rav. £.72)
,#-96
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APPENDIX I
Confirmation Analyses of Mirex Human Adipose Tissue Extracts
1-97
-------
Analytical Results
Confirmational Analyses for
Mirex in Human Adipose Tissue Extracts
Analytical Chemistry Branch
Environmental Toxicology Division
Health Effects Research Laboratory
Research Triangle Park, North Carolina 27711
Date: 30 November 1976
1-98
-------
Health Effects Research Laboratory
Research Triangle Park, North Carolina 27711
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
DATE: November 30, 1976
SUBJECT: Confirmational Analyses for Mirex in Human Adipose Tissue Extracts
FROM: Dr. Edward 0. Oswald, Chief
Analytical Chemistry Branch, ETD (MD-69)
TO: Dr. Frederick W. Kutz
Ecological Monitoring Branch (WH-569)
OPP, Headquarters
THRU: Director, HERL (MD-51)
Attached you will find the results of confirmational analyses for
Mirex as generated by members of the Analytical Chemistry Branch, ETD,
HERL, RTP on extracts of human adipose tissue which were received from
the Michigan OPP lab on the 2 September 1976. Three (3) separate mass
spectrometry groups analyzed selected extracts by gas liquid chroma-
tography interfaced either with low resolution or with high resolution
mass spectrometry in the electron impact mode.
The results of the present report confirm both the qualitative and.
the comparable quantitative presence of Mirex in human adipose tissue as
indicated by the electron capture results from the Michigan lab.
As indicated to you in a similar report of the 23 June 1976, the
GC/EC results agree quite favorably with the confirmational analyses by
GC/MS. . . '
If additional GC/MS confirmational analyses are needed by OPP for
Mirex in human adipose tissue, then I would suggest that only about 10%
of the total extracts be analyzed.
If I or other members of the Branch can be of assistance on this or
other matters, please feel free to contact me.
Enclosure
EPA Form 1320-t (Rc». 3-76)
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Mirex in Human Adipose Tissue Extracts
(Concentrations expressed in parts per million—ppm)
Sample
Identification
*GC/EC Analyses
(Michigan)
Confirmational GC/MS Analyses
Research Triangle Park, N. C.
0.10
0.20
0.39
0.16
0.20
0.07
Negative
0.09
^) 0.09
i Negative
LU 0.12
ijj 0.22
^ 1.10
0.11
0.15
0.12
1.13
0.16
.
-------
Analytical Methodology
Confintiational Analyses for
Mirex in Human Adipose Tissue Extracts
Analytical Chemistry Branch
Environmental Toxicology Division
Health Effects Research Laboratory
Research Triangle Park, North Carolina 27711
Date: 30 November 1976
I-K31L
-------
Methods
Extracts of human adipose tissue were received in.sealed glass
ampules. At the time that the sample vial was opened, aliquots of each
selected sample extract were prepared for analysis by the various mass
spectrometry groups. All samples were analyzed by.at least two (2)
of the analytical teams which generated multiple analyses. All
quantitative results are expressed as mean concentrations in parts per
million (ppm) for each analytical team. The three (3) mass spectrometry
teams were coordinated by: (a) Mr. Robert Harless; (b) Dr. Wayne Sovocool
and (c) Dr. Lynn Wright.
Below are listed the detailed analytical conditions utilized for
the GC/MS confirmational analyses of Mirex in extracts of human adipose
tissue.
1-102
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Group A.
Low Resolution GC/MS
Instrument: Hewlett Packard 5930A Mass Spectrometer equipped with a
Hewlett Packard 5700 gas chromatograph
GC Column: 183 cm x 2 mm (i.d.) glass column packed with 3% OV-17 on
100/120 mesh Gas Chrom Q.
Column temperature: 235°C
Injector temperature: 235°C
Transfer line temperature: 250°C
Membrane separator temperature: 235°C
Carrier gas: Helium
Flow rate: 42 ml/min
lonization voltage: 70 eV
Criteria for Analyses:
These low resolution mass spectrometric analyses (GC-LRMS) are
based upon: (a) correct absolute retention time as compared to Mirex;
(b) presence of intense fragments at m/e 270 with a 6-chlorine isotope
cluster and at m/e 235 with a 5-chlorine cluster (corresponding to the
main electron impact ion fragments of Mirex); and (c) the proper ratios
of the m/e 270 and m/e 235 ion clusters.
Quantitative GC-LRMS measurements were accomplished by single ion
monitoring of the m/e 272 ion in comparison to an external Mirex standard
and to internal spiked samples. All samples were analyzed in at least
duplicates.
I-.1Q3
-------
Group B.
Low Resolution GC/MS
Instrument: Finnigan 3200 Mass Spectrometer equipped with a Finnigan
6100 data system and Finnigan 9500 gas chromatograph
GC Column: 122 cm x 2 mm (i.d.) glass column packed with 3% OV-17
on 100/120 mesh Gas Chrom Q
Column temperature: 240°C
Injector temperature: 240°C
Transfer line temperature: 240°C
Glass jet separator temperature: 240°C .
Carrier gas: Helium
Flow rate: 20 ml/min
lonization voltage: 70eV
Criteria for Analyses:
These low resolution mass spectrometric analyses (GC-LEMS) are
based upon: (a) correct absolute retention time as compared to Mirex;
and (b) presence of intense fragments in the m/e 270 region representing
the most prominent ions of the C_C1 cluster.
5 o
The mass spectrometer was operated in the multiple ion detection
mode monitoring the three (3) most prominent ions of the C^Cl. cluster—
m/e 270, m/e 272, and m/e 274. A fourth ion m/e 405—not present in the
spectrum of Mirex—was monitored to provide a background. Any sample
which gave a negative or trace response upon the initial dilution
conditions was then further reduced in volume to approximately 1/10 of
its original volume. The sample was then reanalyzed. Negative responses
to the latter conditions were reported as negative.
Samples were quantitated by summating the areas the mass chromato-
grams for m/e 270, 272, and 274 and comparisons of these values with the
average response obtained for an external Mirex standard which was
injected either before or after each residue sample.
High Resolution GC/MS
Instrument: Varian MAT 311A Mass Spectrometer equipped with a Varian
2700 gas chromatograph and a Varian C-1024 time averaging
computer (CAT).
GC Column: 91 cm x 2 mm (i.d.) glass column packed with 2% Dexil 410
on 90/100 mesh Anakrom Q.
I-104-,
-------
Column temperature: 243°C
Injector port temperature: 255°C
Transfer line temperature: 255°C
Slit separator temperature: 2559C
Carrier gas: Helium
Flow rate: 10-12 ml/min
lonization voltage: 70eV
Criteria for Analyses:
The high resolution mass spectrometric analyses (GC-HRMS) are based
upon: (a) correct absolute retention time as compared to Mirex; (b)
isotope ratios of two fragments of the molecular ion cluster—m/e 539.6262
•jt *3 C ^/
(C1Q C112) and m/e 543.6203 (C1Q CllQ Cl.); and (c) analysis with
internal and external standards of Mirex.
The mass spectrometer was operated at a high sensitivity in order
to observe the molecular ion .m/e 543.6203 (C CLm c^ with a mass
resolution capability of 7200-8500. Using the time averaging computer
(CAT) system, the mass spectrometer was operated in a double ion moni-
toring mode for the molecular ion m/e 539.6262 and m/e 543.6203. The
quantitative analyses were accomplished by the use of internal and
external standards of Mirex combined with the double ion monitoring of
two specific ion fragments in the molecular cluster of Mirex in the high
resolution GC/MS mode.
I-
-------
Health Effects Research Laboratory
Environmental Research Center
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
Research Triangle Park, North Carolina
SUBJECT: Confirmation of Mirex in Human Adipose Tissue DATE: June 23, 1976
Extracts
FROM: Dr. Robert G. Lewis, Chief
Chemical Characterization Section, ACB/ETD (MD-69)
TO: Dr. Frederick W. Kutz
Ecological Monitoring Branch (WH-569)
OPP, Headquarters
This is to confirm my telephone transmittals to you of the results
of our confirmatory analysis of mirex in human adipose tissue extracts
received from the Michigan project on June 15, 1976. Mirex was confirmed
qualitatively and determined quantitatively in all five samples by each
of three independent methods; i.e. , photochemical, GC-low resolution
mass spectrometry (GC-LRMS) and GC-high resolution mass spectrometry
(GC-HRMS) . Data are presented below:
GC-ECD Mirex Concentration, ppm
Sample I.D. (Michigan) Photochem. GC-ECD GC-LRMS GC-HRMS
0.5 0.4 0.5 0.7
^ 1.3 0.8 0.7 0.9
A
jU 1.3 - 1.3 1.2 1.6
j 0.4 0.3 0.2 0.4
ui
<3 . 1.2 0.4 0.8 1.2
Samples were received in .glass vials sealed with Teflon- lined caps.
Volumes ranged from 3.6 to 14.6 ml. Aliquots of 1 to 4.5 ml were with-
drawn for photochemical confirmation. In this procedure, the aliquot
was added to 10% diethylamine in hexane sufficient to make a total
volume of 5 ml. These solutions were analyzed for GC-ECD before and
after 100 min. exposure in quartz tubes to a 275W sunlamp. Analytical
conditions were as follows:
Instrument — Tracer 222 - Ni ECD
Column — 183-cm x 4-mm (i.d.) glass, packed with 1.5% OV-17/1.95%
OV-210 on 80/100 mesh Gas Chrom Q
2
Attenuation — 10 x 8
Carrier Gas — Ar/CH , 95:5
Carrier Flow — 75 ml/min
Column temp — 200°C
Detector temp — 270°C
Inlet temp — 225°C
EPA Form 1320-6 (Rev. 6-72)
1-106
-------
B.C. Current — 46% f.s.d. @ 102 x 128 D.C.
Voltage — 50v
Pulse Width — 5 ysec
Pulse Rate — 150 usec
Photochemical confirmation work was performed by R. C. Hanisch.
Portions of each sample were taken for GC-LRMS analysis. These
were concentrated to 100 pi by evaporation under a gentle stream of
nitrogen at room temperature. Portions corresponding to ca. 50 ng of
mirex were injected into the GC-LRMS for determination of mass spectra
over the 195 to 560 amu range. GC-LRMS confirmation was based on (1)
correct absolute retention time; (2) presence of intense fragments at
270 m/e with 6-chlorine isotope cluster and at 235 m/e with 5-chlorine
isotope cluster (corresponded to the main electron impact fragments of
mirex); (3) presence of other fragments derivable from mirex; (4) absence
of possible interferring compounds; and (5) proper ratios of the 270 and
235 m/e clusters. Quantitative GC-LRMS measurements were accomplished
through single ion monitoring of the 272 m/e peak and the use of an
external mirex standard. All samples were analyzed in duplicate or
better. Precision with standards was +10 to 15%. GC-LRMS parameters
were as follows:
Instrument: Hewlett Packard 5930A quadrapole focusing mass spec-
trometer equipped with an HP 5700A gas chromatograph and an HP
5932A data system. _
Column: 183-cm x 2-mm (i.d.) glass, packed with 3% OV-17 on 100/120
mesh Gas Chrom Q.
Carrier Gas: Helium
Flow rate: 41 ml/min
Injection port temperature: 200°C
Column temperature: 230°C
Transfer line temperature: 250°C
Membrane separator temperature: 230°C
Ion source temperature: 190°C
Mass filter temperature: 120°C
lonization voltage: 70eV
Filament emission: 160 yamp
Ion source pressure: 2 x 10 mm Hg
-------
Scan rate: 360 amu/sec
GC-LRMS measurements were performed by G. W. Sovocool and M.
Simpson.
The same concentrated samples used for GC-LRMS were also used for
GC-HRMS. The mass spectrometer was operated at extreme sensitivity in
order to observe the molecular ion at 543.6203 m/e (corresponding to
C1035C11037C12). Qualitative and quantitative analyses were performed
by double ion monitoring of the 539.6262 and molecular ions. GC retention
times and internal standards were used for identification and quantifi-
cation. GC-HRMS parameters are given below:
Instrument: Varian MAT 311A double focusing mass spectrometer
equipped with a Varian gas cnromatograph and a Varian data system.
Column: 91-cm x 2-mm (i.d.) glass, packed with 5% OV-101 on Gas
Chrom Q.
Carrier gas: Helium
Flow rate: 15 ml/min
Column temperature: 235°C
•Injection port, transfer line and separator temperatures: 250°C
Ion source temperature: 220°C
Ion source pressure: 5 x 10 mm Hg
GC-HRMS measurements were performed by R. L. Harless.
I trust that you will find these data useful. If we can be of
further assistance, please call on us.
1-108
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA 560/13-80-024
2.
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
Mirex Residue Levels in Human Adipose Tissue:
Statistical Evaluation
5. REPORT DATE
November,
198$
ate of
Pfepara-
r.on;
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
Carol Leininger, Donna Lucas Watts, Charles Sparacino,
and Stephen^Williams
8. PERFORMING ORGANIZATION REPORT NO.
RTI/1864/17-01I
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Research Triangle Institute
P. 0. Box 12194
Research Triangle Park, NC 27709
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
EPA contract 68-01-5848
12. SPONSORING AGENCY NAME AND ADDRESS
Design and Development Branch
Exposure Evaluation Division, Office of
Toxic Substances, U.S. Environmental Protection Agencj
401 M Street, SW, Washington, DC 20460
13. TYPE OF REPORT AND PERIOD COVERED
Final Report
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
Mirex is an insecticide which has a specific geographic region of application
in the United States. The Mirex Special Study was undertaken in 1975 by the
National Human Monitoring Program in an attempt to obtain information about the
prevalence and levels of mirex in human adipose tissues in areas in mirex application.
A sample of human adipose tissue specimens was selected from mirex treated areas in
eight southern States. Detectable levels of mirex were found in 141 of 624 human
adipose tissue specimens in the sample. The data were analyzed with respect to three
demographic variables (race, age, and sex) and two geographic variables (Census
Division and State). Geographic divisions appear to be the most salient factors in
levels of concentration of mirex in the sample studied.
7.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
mirex
fire ant control pesticides
human adipose tissues
sample design
gas chromatography
regression analysis
chi square analysis
unweighted
statistical
analysis
weighted
statistical
analysis
18. DISTRIBUTION STATEMENT
19. SECURITY CLASS (This Report)
unclassified
21. NO. OF PAGES
20. SECURITY CLASS (This page)
unclassified
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EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDITION is OBSOLETE
-------
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17. KEY WORDS AND DOCUMENT ANALYSIS '
(a) DESCRIPTORS - Select from the Thesaurus of Engineering and Scientific Terms the proper authorized terms that identify the major
concept of the research and are sufficiently specific and precise to be used as index entries for cataloging.
(b) IDENTIFIERS AND OPEN-ENDED TERMS - Use identifiers for project names, code names, equipment designators, etc. Use open-
ended terms written in descriptor form for those subjects for which no descriptor exists.
(c) COS ATI FIELD GROUP - Field and group assignments are to be taken from the 1965 COS ATI Subject Category List. Since the ma-
jority of documents are multidisciplinary in nature, the Primary Field/Group assignment(s) will be specific discipline, area of human
endeavor, or type of physical object. The application(s) will be cross-referenced with secondary Field/Group assignments that will follow
the primary posting(s).
18. DISTRIBUTION STATEMENT
Denote releasability to the public or limitation for reasons other than security for example "Release Unlimited." Cite any availability to
the public, with address and price.
19. &20. SECURITY CLASSIFICATION
DO NOT submit classified reports to the National Technical Information service.
21. NUMBER OF PAGES
Insert the total number of pages, including this one and unnumbered pages, but exclude distribution list, if any.
22. PRICE
Insert the price set by the National Technical Information Service or the Government Printing Office, if known.
EPA Form 2220-1 (Rev. 4-77) (Reverse)
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