United States
Environmental Protection
Agency
Office of
Pollution Prevention and Toxics
7404
EPA747-R-94-001
July. 1994
SEMIVOLATILE ORGANIC
COMPOUNDS IN THE
GENERAL U.S. POPULATION
NHATS FY86 RESULTS

VOLUME I

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SEMIVOLATILB ORGANIC  COMPOUNDS IN THE GENERAL U.S. POPULATION:
                       NHATS FY86 RESULTS

                            VOLUME I
                This work was supported by the
             U.S. Environmental Protection Agency
      under EPA contract  numbers 68-02-4294, 68-D8-0115,
        68-DO-0126,  68-D2-0139,  68-02-4252,  68-02-4293,
                        and 68-D9-0174
                          Prepared for
              Khoan Dinh, Work Assignment  Manager
                   Technical Programs Branch
                 Chemical Management Division
           Office of Pollution Prevention  and Toxics
             U.S.  Environmental  Protection Agency
                     Washington, DC  20460
                           July 1994
                           fecyctodfftacyctabto
                           Printed w*h Soy/Curia li
                           comato « KM* 50% recycled few

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The material  in this document has  been subject to
Agency technical and policy review and approved for
publication as  an  EPA  report.   The views expressed
by  individual  authors,  however,  are  their  own and
do  not  necessarily  reflect  those  of  the  U.S.
Environmental Protection Agency.   Mention of trade
names, products,  or services does  not  convey,  and
should not be  interpreted as conveying,  official
EPA approval, endorsement, or recommendation.

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PREFACE


         The determination of  the  levels  of  semivolatile organic
compounds in the general population of the United States
described in this report was achieved through cooperative efforts
of many EPA and contract support staff.  EPA staff participating
in the program included principal investigators from the
Technical Programs Branch  (TPB) of the Chemical Management
Division  (CMD) of the Office of Pollution Prevention and Toxics
(OPPT).  Contract support to OPPT was provided by:

    •    Battelle under EPA Contract Nos. 68-02-4294, 68-D8-0115,
         68-DO-0126,  and  68-D2-0139.

    •    Midwest Research Institute  (MRI) under EPA Contract  No.
         68-02-4252.

    •    Westat, Inc., under EPA Contract Nos. 68-02-4293 and
         68-D9-0174.

The roles and responsibilities of each of these organizations and
key individuals participating in this effort are presented below.


Battelle

         Battelle was responsible  for developing the FY86 NHATS
specimen collection program, creating and maintaining the data
bases on the Patient Summary Reports,  designing the specimen
compositing plan and the statistical methodology for data
analysis, conducting the statistical analysis to develop
estimates of semivolatile. residual levels in the general U.S.
population based on demographic factors,  and producing this final
report.   Key individuals included:  Dr. Robert Lordo,  Dr. John
Orban, Mr. Ying-Liang Chou, Ms. Pamela Hartford,  and Ms. Tamara
Collins.
Midwest Research Institute (MRI)

        MRI was responsible for the coordination of the
collection of the FY86 NHATS specimens, preparation of the NHATS
composites and quality control (QC)  samples, conducting the
HRGC/MS analysis of the composites,  reporting the results, and
contributing to this final report.  Key individuals included:
Dr. John Stanley,  Dr. Stan Spurlin,  Mr. Jack Balsinger, Ms. Hope
Green, and Ms. Patti Aim.
                               iii

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Westat. Inc.

        Westat was responsible for creating and maintaining the
data bases for the Analysis Reports, developing and executing
statistical procedures  for identifying outliers in the reported
concentrations, and writing the  final report on the results of
the outlier analysis.   Key individuals included:  Mr. John Rogers
and Ms. Helen  Powell.


EPA/OPPT

        EPA/OPPT was responsible for oversight in the
development of the study plan, managing and coordinating the
conduct of the overall  study,  and  reviewing, editing  and
finalization of this  report.   Key  individuals  included:  Dr.
Khoan  Dinh, Ms. Janet Remitters, and Mr. John Schwemberger as Work
Assignment Managers and Dr. Joseph Breen, Ms.  Edith Sterrett, Mr.
Gary Grindstaff,  and  Mr. Philip  Robinson as Project Officers.
                                IV

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                        TABLE OF CONTENTS
                                                             Page

EXECUTIVE SUMMARY .....................  xvii

1.0  INTRODUCTION ...................... 1-1

     1 . 1  Background  .................... 1-1
     1.2  Objectives  .................... 1-3
     1.3  Report Organization ................ 1-3

2.0  NHATS FY86 SAMPLE DESIGN .  .  .............. 2-1

     2.1  Sampling Design .................. 2-1

          2.1.1  The NHATS Stratification Scheme  ...... 2-3
          2.1.2  MSA Selection  ............... 2-3
          2.1.3  Specimen Collection Quotas ......... 2-6

     2.2  Sample Collection Procedures  ........... 2-9
     2.3  Specimen Collection Summary ...........  2-11

3.0  NHATS FY86 COMPOSITE DESIGN  .............. 3-1

     3.1  Design Goals and Compositing Criteria ....... 3-1
     3.2  Laboratory Compositing Procedures ......... 3-4
     3.3  Summary of FY86 NHATS  Composite Samples ...... 3-6

4.0  CHEMISTRY  ....................... 4-1

     4.1  Analytical Procedures  ............... 4-1

          4.1.1  Sample Preparation ............. 4-1

                 4.1.1.1  Extraction  ............ 4-3
                 4.1.1.2  Lipid Determination ........ 4-3
                 4.1.1.3  Extract Concentration ....... 4-3

          4.1.2  Cleanup Procedure  ............. 4-4

                 4.1.2.1  Gel Permeation Chromatography .   .  .4-4
                 4.1.2.2  GPC Eluent Concentration  ..... 4-5
                 4.1.2.3  Florisil Column Cleanup ...... 4-5

          4.1.3  Analysis Procedures  ............ 4-7

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                    TABLE OF CONTENTS  (cont.)

                        Volume I   (cont.l

                                                             Page

          4.1.4  Quantitation/Data Reduction   	 4-8

                 4.1.4.1  Qualitative Identification  . .  .  .4-8
                 4.1.4.2  Quantitation   	  4-14
                 4.1.4.3  Recovery of Surrogate Standards  .  4-15
                 4.1.4.4  Data Qualifiers  	  4-15
                 4.1.4.5  Estimating the Method Limit of
                          Detection	4-16

     4.2  QA/QC for Chemical Analysis	4-17

          4.2.1  Demonstrating Achievement of  Instrument
                 Performance Requirements  	  4-17
          4.2.2  Calibration for Quantitative
                 Semivolatile Analysis   	  4-19

                 4.2.2.1  Initial Calibration  	  4-19
                 4.2.2.2  Routine Calibrations  	  4-25

          4.2.3  Spiking Solution Preparation  	  4-25

                 4.2.3.1  Native Standard Spiking
                          Solution	4-25
                 4.2.3.2  Surrogate Standard Spiking
                          Solution	4-25
                 4.2.3.3  Internal Standard Spiking
                          Solution	4-28
                 4.2.3.4  Performance Audit Solutions . .  .  4-28

          4.2.4  QC Samples	4-28

                 4.2.4.1  Method Blanks  	  4-28
                 4.2.4.2  Control Samples  	  4-30
                 4.2.4.3  Spiked Control Samples  	  4-30

     4.3  Overall Data Quality	4-31

5.0  DATA ISSUES	5-1

     5.1  Determining Native Compounds to Include
          in Statistical Analysis 	 5-2

          5.1.1  Detection Status of the Semivolatiles  .  .  . 5-3
          5.1.2  Data Reporting Unique
                 to Dieldrin and p,p-DDE	5-8
                                VI

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                    TABLE  OF  CONTENTS   (cont.)

                        Volume I  (cont.)

                                                             Page

     5.2  Adjusting Concentration Data
          for Surrogate Recoveries  	 5-9

          5.2.1  Data Adjustment Method	5-10

                 5.2.1.1  Composite Data Adjustment ....  5-11
                 5.2.1.2  QC Data Adjustment	5-14

     5.3  Statistical Analysis of Quality Control Data  .   .  5-19

          5.3.1  Descriptive Summary of QC Data	5-22

                 5.3.1.1  Spiked Compounds  	  5-22
                 5.3.1.2  Unspiked Compounds  	  5-30
                 5.3.1.3  Method Blanks 	  5-30

          5.3.2  Statistical Approach
                 to Analyzing the QC Data	5-30

                 5.3.2.1  Spiked Compounds  	  5-30
                 5.3.2.2  Unspiked Compounds  	  5-36

          5.3.3  Results of Statistical Modelling
                 of QC Data	5-36

                 5.3.3.1  Spiked Compounds  	  5-36
                 5.3.3.2  .Unspiked Compounds  	  5-45

          5.3.4  Conclusions	5-48

6.0  STATISTICAL METHODOLOGY  	 6-1

     6.1  The Additive Model	6-2
     6.2  Statistical Analysis of Composite Samples 	 6-7

          6.2.1  Estimation	6-7

                 6.2.1.1  Estimating Native Compound
                          Levels	6-7
                 6.2.1.2  Characterizing PCB Results  ...  6-10

          6.2.2  Hypothesis Testing 	  6-12

7.0  RESULTS	7-1

     7.1  Descriptive Statistics  	 7-2

                               vii

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                    TABLE OP CONTENTS  (cont.)

                         Volume  I   (cont.)

                                                              Page

     7.2  Population Estimates  from Statistical
          Modelling	7-8
     7.3  Hypothesis Testing  	   7-27
     7.4  Outlier Detection 	   7-29
     7.5  Model  Validation  	   7-32

8.0  COMPARISON  WITH RESULTS FROM PREVIOUS  SURVEYS
     IN THE NHATS PROGRAM	8-1

     8 .1  Comparison of  Design  and Analytical
          Procedures	8-2

          8.1.1   Comparison of  Study Designs   	  8-2
          8.1.2   Comparison of  Analytical Procedures   ....  8-6

     8.2  LODs and Percent Detection Summaries	8-10
     8.3  Descriptive Statistics  on Measured
          Concentrations  	   8-15

          8.3.1   Scatterplots of  the Sample
                  Concentrations 	   8-16
          8.3.2   Unweighted National Averages 	   8-17
          8.3.3   Weighted National Averages 	   8-18

     8.4  Statistical Comparison  of
          National Concentration  Estimates   	   8-26

          8.4.1   Semivolatile Compounds  Included in
                  Statistical Comparison  . 	   8-27
          8.4.2   Fitting the Additive Model 	   8-28

                  8.4.2.1  National Estimates   	   8-29
                  8.4.2.2  Marginal Estimates   	   8-31
                  8.4.2.3  Likelihood Ratio  Tests  	   8-34
                  8.4.2.4  Conclusions 	   8-34

9.0  REFERENCES	9-1
                            Volume II


Appendix A:   Listing of NHATS FY86 Composite Data



                               viii

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Appendix B:
Appendix C:
Appendix D:
Appendix E:
Appendix F:
Appendix G:
Appendix H:
Appendix I:
Appendix J:
Appendix K:
                    TABLE OF CONTENTS  (cont.)

                               TT  (cont.)
Listing of NHATS FY86 QC Data For Compounds
Detected in At Least 50% of Composites  (plus
Octachlorobiphenyl )

Plots of Observed vs. Spiked Concentrations for
Spiked Semivolatile Compounds Detected in At Least
50% of Composites (plus Octachlorobiphenyl) .

Plots of Observed Concentration vs. Batch ID
for Unspiked Semivolatile Compounds Detected in
At Least 50% of Composites

Summary of QC Data for the FY86 NHATS Spiked
Semivolatile Compounds Not on the Target List for
Statistical Analysis

Characterizing the Distribution of NHATS FY86
Semivolatile Compound Concentrations (in ng/g,
Unadjusted for Surrogate Recoveries) Based on All
50 Composite Samples

Estimates of Average Concentrations with 95%
Confidence Intervals As Determined by the Additive
Model, for Selected Subpopulations in the FY86
NHATS

Concentrations (ng/g) from the FY82, FY84, and FY86
NHATS, Plotted in Chronological Order with Age
Group as the Plotting Symbol

Surrogate -Ad justed Concentrations  (ng/g) from the
FY82, FY84, and FY86 NHATS, Plotted in
Chronological Order with Age Group as the Plotting
Symbol

Arithmetic Averages  (and Standard Errors) of
Extractable Lipid Concentrations  (ng/g) for
Compounds Analyzed in the FY86 NHATS and Also
Analyzed in the FY82 and/or FY84 NHATS

Comparisons of Predicted Average Concentrations
(ng/g) by Selected Subpopulations for Selected
Semivolatiles over the FY82, FY84, and FY86 NHATS

Plots of Estimates Average Concentrations  (ng/g) by
Census Region and by Age Group, Plus and Minus Two
Standard Errors,  Based on the Additive Model for
the FY82, FY84, and FY86 NHATS
                                IX

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Table ES-1


Table ES-2
                          LIST OF TABLES

                             Volume T
Semivplatile Compounds Detected in At Least
44% of the FY86 NHATS Composite Samples .  .

Estimates of National Average Concentrations
for Selected Semivolatiles,  with 95%
Confidence Intervals, from the FY86 NHATS  . ,
                                                             Page
xx
                                                             XXll
Table ES-3  Estimates of National Average Concentrations
            for Selected Semivolatiles, with 95%
            Confidence Intervals, from the FY82,
            FY84, and FY86 NHATS	  xxvi

Table 2-1   Demographic Categories in Which Subquotas
            Were Established for Collecting
            Adipose Tissue Specimens  	 2-2

Table 2-2   Sampling Strata Definitions for the NHATS  . .  .  .2-4

Table 2-3  .Sample MSAs Selected for the FY86 NHATS	2-7

Table 2-4   FY86 Age and Sex Subquotas, and the Race
            Subquota, for Each NHATS Collection Site
            Within Each Stratum . .  .	  .  2-10

Table 2-5   FY86 NHATS Specimen Collection Summary  ....  2-13

Table 2-6   FY86 NHATS Speciment Collection Summary
            by Demographic Subpopulation  	  2-14

Table 3-1   Distribution of FY86 NHATS Composite Samples
            by Census Division and Age Group	3-7

Table 3-2   Demographic Makeup of FY86 NHATS
            Composite Samples 	 3-8

Table 4-1   Recommended HRGC/MS Operating Procedures   . .  .  .4-8

Table 4-2   Characteristic Masses and Intensities for the
            Qualitative Identification of the Semivolatile
            Target Analytes, Chromatographic Conditions,
            and Estimated Limit of Detection  .  . .  .   . .  .  .4-9

Table 4-3   DFTTP Key Masses and Abundance Criteria ....  4-18

Table 4-4   Calibration Solutions for the 6%
            Florisil Fraction 	  ....  4-20

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                     LIST OF TABLES   (cont.)

                        Volume I   (cont.)
                                                             Page
Table 4-5   Calibration Solutions for the 50%
            Florisil Fraction  	  4-23

Table 4-6   Calibration Solutions for PCB Analysis   ....  4-24

Table 4-7   Proposed QC Spiking Solutions	4-26

Table 4-8   Spike Levels for Surrogate and
            Internal Standards  	  4-29

Table 4-9   Quality Control Samples Included in the
            FY86 NHATS Analytical Procedure 	  4-30

Table 4-10  Data Quality Objectives for the FY86 NHATS,
            Along With Actual Performance	4-32

Table 5-1   Percent of NHATS FY86 Composite Samples
            in Each Detection Level Category  	 5-4

Table 5-2   Matching NHATS FY86 Native Compounds
            with Surrogate Compounds  	  5-12

Table 5-3   Estimates of R and A for Surrogate
            Compounds	5-15

Table 5-4   Spiked Target Compounds for the FY86 NHATS,
            with Spiking Levels	5-21

Table 5-5   Summary of (Surrogate-Adjusted)  QC Data
            for the FY86 NHATS Spiked Target Compounds  .   .  5-23

Table 5-6   Percent Recoveries for Spiked Target
            Compounds,  as Determined from Two
            Calculation Methods 	  5-29

Table 5-7   Means and Standard Errors of Surrogate-
            Adjusted Concentrations (ng/g) of Unspiked
            Target Compounds for QC Samples (by Batch
            and Overall)	  5-31

Table 5-8   Batch Analysis Results on Method Blanks
            and Control Samples for Compounds Detected
            in At Least 50% of Composites, Where the
            Compound Was Detected in the Method Blank  . .   .  5-32
                                XI

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                     LIST OF TABLES   (cont.)

                        Volume I   (cont.)

                                                             Page

Table 5-9   Regression Models Used to Analyze NHATS
            FY86 QC Data for Spiked Compounds	5-34

Table 5-10  Estimated Batch Recoveries and Average
            Recovery for Spiked Compounds with Percent
            Detected At Least 50%  (Adjusted Data)  	  5-37

Table 5-11  Tests  for Significant Differences in
            Batch  Slopes Among Selected Batches
            for Spiked Target Compounds  	  5-39

Table 5-12  Predicted Concentrations and Coefficients
            of Variation at Each Spike Level for
            Spiked Target Compounds Analyzed by the
            Batch  Slopes Model	5-40

Table 5-13  Estimated Batch Background Levels and
            Average Background Level for the Two Methods
            of Reporting p,p-DDE Concentrations, as
            Estimated by the Batch Intercepts Model  ....  5-44

Table 5-14  Results of Statistical Analysis of QC Data
            on Unspiked Target Compounds  	  5-46

Table 5-15  Predicted Concentrations and Coefficients
            of Variation for Unspiked Target Compounds
            at the Control Level	5-47

Table 6-1   NHATS  Analysis Factors and Categories  	 6-3

Table 7-1   Descriptive Statistics of NHATS FY86
            Semivolatile Compound Concentrations
            Based  on All 50 Composite Samples	7-3

Table 7-2   Estimates of Average Concentrations for
            Selected Semivolatiles, with Standard Errors
            and Approximate 95% Confidence Intervals,
            According to Census Region from NHATS FY86
            Composite Samples 	  7-10

Table 7-3   Estimates of Average Concentrations for
            Selected Semivolatiles, with Standard Errors
            and Approximate 95% Confidence Intervals,
            According to Age Group from NHATS FY86
            Composite Samples 	  7-14
                               XI1

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                     LIST OF TABLES   (cont.)

                        Volume I   (cont.)
                                                              Page
Table 7-4   Estimates of Average Concentrations for
            Selected Semivolatiles, with Standard Errors
            and Approximate 95% Confidence Intervals,
            According to Race Group from NHATS FY86
            Composite Samples 	  7-17

Table 7-5   Estimates of Average Concentrations for
            Selected Semivolatiles, with Standard Errors
            and Approximate 95% Confidence Intervals,
            According to Sex Group from NHATS FY86
            Composite Samples 	  7-20

Table 7-6   Estimates of Average Concentrations for
            Selected Semivolatiles, with Standard Errors
            and Approximate 95% Confidence Intervals,
            for the Nation from NHATS FY86
            Composite Samples 	  7-23

Table 7-7   Chlorobiphenyl Distribution Across the
            Five Target PCB Homologs in the
            FY86 NHATS	7-26

Table 7-8   Significance Levels from Hypothesis Tests
            for Differences Between Demographic Groups
            for NHATS FY86 Semivolatiles	7-28

Table 7-9   Measured Concentrations with High Influence
            on Determining the Additive Model Fit	7-34

Table 7-10  R-Squared Correlation Between Observed
            Concentrations and Concentrations Predicted
            by the Additive Model for NHATS FY86
            Semivolatiles 	  7-36

Table 8-1   Number of Specimens and Composites Within
            the FY82, FY84,  and FY86 NHATS According
            to MSA	8-3

Table 8-2   Total Number of Specimens Included in
            Composite Samples Analyzed in the FY82,
            FY84, and FY86 NHATS, by Subpopulation and
            Across the Entire Study 	 8-4
Table 8-3
Total Number of Composite Samples Analyzed
in the FY82, FY84, and FY86 NHATS,
by Subpopulation and Across the Entire Study

                   xiii
                                                             .  8-5

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                     LIST OF TABLES   (cont.)

                        Volume  I   (cont.)
                                                              Page
Table 8-4   Semivolatile  Compounds Quantitated Using
            the Same  Internal  Quantitation  Standards
             (IQS). in  NHATS  FY84  and  FY86	8-8

Table ,8-5   Semivolatile  Compounds Quantitated Using
            Different Internal Quantitation Standards
             (IQS)  in  NHATS  FY84  and  FY86	8-9

Table 8-6   Average Lipid-Adjusted Limit  of Detection
             (LOD,  ng/g) and Percent  of  Composites with
            Detected  Concentrations,  for  Compounds Analyzed
            in the FY86 NHATS  and Also  Analyzed  in the
            FY82  and/or FY84 NHATS	8-11

Table 8-7   Weighted  National  Averages  of Unadjusted
            Concentrations  (ng/g) and Standard Errors
            for Compounds Analyzed in the FY86 NHATS and
            Also  Analyzed in the FY82 and/or FY84 NHATS  .  .   8-20

Table 8-8   Weighted  National  Averages  of Surrogate-
            Adjusted  Concentrations  (ng/g)  and
            Standard  Errors for  Compounds Analyzed in
            the FY86  NHATS  and Also  Analyzed in  the
            FY82  and/or FY84 NHATS	8-23

Table 8-9   Comparisons of  Predicted National Average
            Concentrations  (ng/g) for Selected
            Semivolatiles over the FY82,  FY84, and
            FY86  NHATS	8-30

Table 8-10  Chlorobiphenyl  Distribution Across the
            Five  PCB  Homologs  Considered  for Statistical
            Analysis  in the FY86 NHATS	8-32

Table 8-11  Significance  Levels  from Hypothesis  Tests
            for Differences Between  Demographic  Groups
            for Selected  Semivolatiles  in the FY82,
            FY84,  and FY86  NHATS	8-35
                            Volume  II
Appendix A:   Listing of NHATS  FY86 Composite Data
                               xiv

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Appendix B
Appendix D;
Appendix E;
Appendix I
Appendix J:
       LIST OF TABLES   (cont.)

          Volume  II   (cont.)

Listing of NHATS FY86 QC Data For Compounds
Detected in At Least 50% of Composites  (plus
Octachlorobiphenyl)

Summary of QC Data for the FY86 NHATS Spiked
Semivolatile Compounds Not on the Target List for
Statistical Analysis

Characterizing the Distribution of NHATS FY86
Semivolatile Compound Concentrations (in ng/g,
Unadjusted for Surrogate Recoveries) Based on All
50 Composite Samples

Arithmetic Averages (and Standard Errors) of
Extractable Lipid Concentrations (ng/g)  for
Compounds Analyzed in the FY86 NHATS and Also
Analyzed in the FY82 and/or FY84 NHATS

Comparisons of Predicted Average Concentrations
(ng/g) by Selected Subpopulations for Selected
Semivolatiles over the FY82,  FY84,  and FY86 NHATS
                         LIST OF FIGURES

                            Volume  I
Figure 4-1
Flow Scheme for Analysis of Semivolatile
Compounds in the FY86 NHATS	,
                                                              4-2
Appendix C:
Appendix F
              Volume II

Plots of Observed vs.  Spiked Concentrations for
Spiked Semivolatile Compounds Detected in At Least
50% of Composites (plus Octachlorobiphenyl).  Plots
of Observed Concentration vs. Batch ID for Unspiked
Semivolatile Compounds Detected in At Least 50% of
Composites

Estimates of Average Concentrations with 95%
Confidence Intervals As Determined by the Additive
Model, for Selected Subpopulations in the FY86
NHATS
                                xv

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                     LIST OF FIGURES  (cont.)

                        Volume II   (cont.)

Appendix G    Concentrations  (ng/g)  from the FY82,  FY84,  and FY86
              NHATS,  Plotted  in  Chronological Order with  Age
              Group  as  the  Plotting Symbol

Appendix H    Surrogate-Adjusted Concentrations  (ng/g)  from the
              FY82,  FY84, and FY86  NHATS, Plotted in
              Chronological Order with  Age  Group as the Plotting
              Symbol

Appendix K    Plots  of  Estimates Average Concentrations (ng/g)  by
              Census Region and  by  Age  Group,  Plus and Minus Two
              Standard  Errors, Based on the Additive Model  for
              the  FY82,  FY84,  and FY86  NHATS
                                XVI

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EXECUTIVE SUMMARY

BACKGROUND
         The  National  Human Monitoring  Program  (NHMP),  operated
by the United States Environmental Protection Agency's Office of
Pollution Prevention and Toxics  (USEPA/OPPT), is a national
program to monitor the human body burden of selected chemicals.
The National Human Adipose Tissue Survey (NHATS),  one component
of the NHMP, was performed annually to collect and analyze a
nationwide sample of adipose tissue specimens from autopsied
cadavers and surgical patients.  The purpose of the NHATS was to
identify and quantify the prevalence and levels of selected
chemicals in human adipose tissue.  The analysis results were
used to establish an exposure-based chemicals list, to estimate
baseline body burden levels for selected chemicals, and to
characterize trends in these levels within predefined demographic
groups.   The NHATS was intended to fulfill the human and
environmental monitoring mandates of the Toxic Substances Control
Act and the Federal Insecticide, Fungicide, and Rodenticide Act,
as amended.
        The  EPA/OPPT  earmarked  the FY86 NHATS tissue repository
for the analysis of semivolatile compounds using HRGC/MS methods.
The FY86 NHATS study design was similar.to those used in the FY82
and FY84 NHATS,  where HRGC/MS analyses of semivolatile compounds
were also performed.   This report presents the objectives,
methodology,  and results of the FY86 NHATS, and a comparison of
results with the FY82 and FY84 NHATS.

OBJECTIVES
        The  specific  objectives of the FY86 NHATS  analysis were
to:
        Determine the extent to which semivolatile organic
        compounds are present in human adipose tissue  samples,
                              xvii

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         Estimate the average concentrations  of  semivolatiles  in
         the  adipose tissue of humans  in the  U.S.  population and
         in its  various subpopulations,
         Determine if any key demographic factors  (geographic
         region,  age,  race,  and sex) are associated with the
         average concentrations of semivolatiles in human adipose
         tissue,  and
         Compare the estimated average concentration levels  of
         semivolatiles in the FY86 NHATS with estimates  from the
         FY82 and FY84 NHATS, when similar techniques were used
         to estimate the same semivolatiles.
APPROACH
        One  hundred and eleven (111)  qualitative  and
quantitative semivolatile organic compounds were targeted in the
chemical analysis of human adipose tissue samples in the FY86
NHATS.  For compounds with sufficient detection percentages,
measured concentration  data were statistically analyzed to
estimate average concentration levels in the U.S. population and
to determine if any of  four demographic factors of interest
(geographic region, age, race, and sex) were associated with the
average concentration levels.  Statistical analysis was also used
to compare average  concentration.levels found in the FY82, FY84,
and FY86 NHATS for  selected compounds.
        The  analytical  samples in the FY82, FY84, and  FY86 NHATS
were composites of  individual patient specimens.  Compositing
criteria were established to achieve the study objectives of
estimating and comparing average concentrations in selected
subpopulations, while reducing the number of samples to analyze.
The criteria specified  that composites should only be created
using specimens from donors in the same age group and from the
same U.S. Census division.  This ensured maximum precision for
estimating differences  in body burden levels among populations
from different geographic regions and age groups.
        A total of  50 composite  samples were analyzed  in  the
FY86 NHATS.   These  samples were prepared from 671 individual
                              xviii

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specimens collected from selected metropolitan statistical areas
(MSAs) in the 48 conterminous United States.

SUMMARY OF THE FY86 NHATS RESULTS
        Of  the  111  semivolatiles targeted  for analysis,  23 were
detected in at least half of the FY86 NHATS composite samples.
These compounds and their detection percentages among the FY86
NHATS composite samples are listed in Table ES-1.  For
comparative purposes, this table also includes the detection
percentages for these compounds among the FY82 and FY84 NHATS
composite samples.  Seventeen (17)  of the compounds in Table ES-1
were selected for statistical analysis of measured concentrations
in the FY86 NHATS.
        Concentration estimates for the five PCB homologs
included in Table ES-1 (tetra-,  penta-,  hexa-,  hepta-, and octa-
chlorobiphenyl)  were consolidated to characterize overall PCB
exposures.  The following additional PCB parameters were
calculated from these five homologs and presented with the study
results:

    •   Total concentration of PCBs  (sum of the estimated
        concentrations of the five homologs);
    •   Chlorobiphenyl distribution  (percentage of total PCB
        concentration attributed to a specific homolog);
    •   Chlorination level  (sum of the chlorobiphenyl
        distribution percentages across homologs, each weighted
        by the homolog's chlorine mass fraction).

Note that these PCB parameters should be calculated across all
ten PCB homologs.  However,  since each omitted homolog was
detected in no more than 30% of the FY86 composite samples, the
parameter estimates closely approximate results across all
homologs.

National Average Concentrations
        Table ES-2 contains the model-based estimates of the
FY86 national average concentrations in human adipose tissue for

                               xix

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Table ES-1.  Semivolatile Compounds Detected in at Least 44% of
             the FY86 NHATS Composite Samples
                                           Detection Percentage
Compound
CAS
Number
FY82
FY84
FY86
  p,p-DDE
  p,p-DDT
  Heptachlor epoxide
  Beta-BHC
  Trans-nonachlor
  Oxychlordane
  Dieldrin(1)
  Hexachlorobenzene
  1,4-Dichlorobenzene
  Naphthalene
  Hexachlorobiphenyl
  Pentachlorobiphenyl
  Heptachlorobiphenyl
  Tetrachlorobiphenyl
  Octachlorobiphenyl
   Pesticides

        72-55-9
        50-29-3
       1024-57-3
        319-85-7
      39765-80-5
      26880-48-8
        60-57-1

 Chlorobenzenes

        118-74-1
        106-46-7

      PAHs

        91-20-3

      PCBs

      26601-64-9
      25429-29-2
      28655-71-2
      26914-33-0
      31472-83-0

Phthalate Esters
  Bis  (2-ethylhexyl)
     phthalate(2)
  Di-n-butyl phthalate(2)
  Butyl benzyl  phthalate(2).
        177-81-7
         84-74-2
         85-68-7
100%
 68%
 70%
 93%
 57%

 33%
 79%
 96%
 89%
 80%
 89%
 96%
 83%
 39%
 83%
 42%
 75%
 73%
 52%
 55%
 41%
 24%
 98%
 85%
 84%
 41%
 18%
100%
 96%
 94%
 92%
 92%
 78%
 62%
 98%
 86%
 84%
 94%
 88%
 86%
 66%
 44%
 50%
 74%
  0%
100%
 62%
 78%
 76%
 72%
                               xx

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                     Table  ES-1.   (cont.)
                                            Detection Percentage

                                   CAS
Compound                       Number     FY82    FY84   FY86


                     Other  (Quantitative)

D-limonene(2)                  5898-27-5      --      --     96%
0-cymene(2)                     527-84-4      --      --     80%
Octamethyl-
   cyclotetrasiloxane(2)       556-67-2      --      --     72%

                      Other (Qualitative)

Hexyl  acetate                 142-92-7      --      --     82%
l,2,4-Trimethylbenzene(2)       95-63-6      --      --     62%
1-Nonene                      124-11-8      --      --     50%
(1)  Data qualifier in FY86 determined to reflect the S/N ratio had data
    been above the lowest calibration standard.
(2)  Potential contamination issues with these compounds prevented them
    from being included in FY86 statistical analysis.
                              XXI

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Table ES-2.
Estimates of National Average Concentrations for
Selected Semivolatiles, With 95% Confidence
Intervals, from the FY86 NHATS
   Compound
                 Estimated
                 Avg.  Cone.
                  (ng/g)
95% Confidence
    Interval

p,p-DDT
p,p-DDE
Beta-BHC
Heptachlor epoxide
Oxychlordane
Trans -nonachlor
Dieldrin

1 , 4 -Dichlorobenzene
Hexachlorobenzene

Naphthalene

Tetrachlorobiphenyl
Pentachlorobiphenyl
Hexachlorobiphenyl
Heptachlorobiphenyl
Octachlorobiphenyl
Total PCBs(1)
Level of Chlorination(2)
Pesticides
177.
2340.
157.
57.6
114.
130.
47.0
Chlorobenzenes
90.9
51.3
PAHS
20.7
PCBs
56.4
135.
314.
125.
42.7
672.
58.3%

( 137.,
(1790.,
( 107 .,
( 49.2,
( 98.4,
( 99.6,
( 31.0,

( 60.2,
( 43.3,

( 15.9,

( 46.9,
( 104.,
( 276.,
( 80.7,
( 19.3,
( 603. ,
( 51.2,

217.)
2880.)
207.)
66.1)
129.)
161.)
63.1)

122.)
59.3)

25.4)

65.9)
165.)
351.)
169.)
66.1)
742.)
65.4)
Other (Qualitative)
1-Nonene
Hexyl acetate
124.
123.
( 20.6,
( 79.5,
227.)
166.)
                             XXI1

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                           Table  E8-2.   (cont.)

Notes for Table ES-2

^  The estimate for Total PCBs is the sum of the estimated averages  over  the
    five homologs  included in this table (i.e.,  homologs  detected  in  at  least
    44% of  the NHATS FY86 composite samples).

(2)  Estimated level of chlorination is calculated as  follows:

                                a
   where Aj =  estimate of the percent of total PCBs for homolog i,
   and   BJ =  mass  fraction of chlorine for homolog i.
    (Only the  five PCB homologs included in the  table are considered in
   calculating level of chlorination.)
                                   XXlll

-------
the 17 compounds included in the statistical analysis.
Approximate 95% confidence intervals are included in this table
for each national average.  Relative standard errors of these
estimates ranged from  5.9% for hexachlorobiphenyl to 27.1% for
octachlorobiphenyl.

Age Group Effects
         The  effect of  age  group  on average  concentration  for the
17 compounds in Table  ES-2 was statistically significant for six
of the seven pesticides  (all except dieldrin), five PCB homologs,
and hexachlorobenzene.   In each case, the average concentration
increased with the  age of the donor.  Among the PCB homologs, the
average concentration  for the 45+  age group was from 188%
(pentachlorobiphenyl)  to 706%  (heptachlorobiphenyl) above the
average for the 0-14 age group (an increase from 75.6 to 218 ng/g
for pentachlorobiphenyl, and from  26.9 to 217 ng/g for
heptachlorobiphenyl).  Similar percent increases were observed
with the pesticides.   For example, average concentration of p,p-
DDT was 73 ng/g for the  0-14 age group and 252 ng/g for the 45+
age group --a 245% increase.

Geographic Effects
         Statistically  significant  differences in average
concentration for the  17 compounds in Table ES-2 were observed
between census regions for p,p-DDT, p,p-DDE, heptachlor epoxide,
hexachlorobenzene,  naphthalene, and three of the five PCB
homologs.  Average  concentration of p,p-DDT and the PCBs were
highest in the northeast.  Heptachlor epoxide was highest in the
south, and hexachlorobenzene was highest in the west.  Similar
such patterns were  observed in the FY82 and FY84 NHATS.

Race and Sex Groups
         The  differences  in estimated average concentrations
between race groups (white vs. nonwhite) and between sex groups
                               xxiv

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 (male vs. female) were not statistically significant for any of
the 17 modeled compounds.

SUMMARY OF THE COMPARISON WITH FY82 AND FY84 NHATS RESULTS
         Fifty-four  (54)  of the 111 semivolatiles analyzed  in the
FY86 NHATS were also analyzed in either one or both of the FY82
or FY84 NHATS.  Of these 54 compounds, twelve were detected in at
least 50% of the samples in each of the FY82, FY84, and FY86
surveys.  Statistical comparison of average concentration across
surveys was performed on ten of these twelve compounds (butyl
benzyl phthalate and di-n-butyl phthalate were excluded from
statistical analysis based on FY86 QC data analysis findings).
The estimated national average concentrations within each survey
for these ten compounds, along with approximate 95% confidence
intervals, are listed in Table ES-3.   Statistical analysis
results are also included in Table ES-3 to identify those
compounds whose results for FY82 and FY84 differ significantly
from FY86.
         For the  four PCB homologs considered in the statistical
comparison,  the FY86 average concentration was from 48% to 259%
higher than the FY82 average concentration.  The differences in
these averages for tetra-,  penta-, and hexa-chlorobiphenyl were
statistically significant between these two surveys.   The
observed differences in average concentration for PCB homologs.
between FY84 and FY86 were less apparent; the only statistically
significant difference was a 58% increase from FY84 to FY86 in
average concentration for hexachlorobiphenyl.  Total PCBs in FY82
and FY84 differed significantly from FY86 results,  due to the
larger national average noted in FY86.
         Fewer incidents of significant differences between
surveys were apparent among the five pesticides.  For p,p-DDT and
p,p-DDE, differences of 43% and 101%, respectively, between the
FY84 and FY86 average concentrations were statistically
significant.  Both differences were increases over the FY84
average.  Meanwhile, the only pesticide with a significant
                               XXV

-------
Table ES-3.
Estimates of National Average Concentrations for
Selected Semivolatiles, With 95% Confidence
Intervals, from the FY82, FY84, and FY86 NHATS
Compound
p,p-DDT
p,p-DDE
Beta-BHC
Trans -nonachlor
Heptachlor epoxide
NHATS
Estimated
Avg . Cone .
(ng/g)
Pesticides
FY82 189.
FY84 123 .
FY86 177.
FY82
FY84
FY86
FY82
FY84
FY86
FY82
FY84
FY86
FY82
FY84
FY86
1840
1150
2340
291
199
157
109
105
130
59
68
57
•
•
•.
.4
.3
.6
95%
Confidence
Interval
( 125
( 102
( 137
(1130
( 968
(1790
( 183
( 150
( 107
( 53.
( 94.
( 99.
( 32.
( 53.
( 49.
"
"
"
o,
4,
6,
2,
9,
2,
253.)
145.)
217.)
2550.)
1330.)
2880.)
400.)
248.)
207.)
165.)
115.)
161.)
86.5)
82.6)
66.1)
Diff .
From
FY86
12.
-53.
-498.
-1190.
135.
42.
-21.
-25.
1.
10.
1
4*
*
*
3
3
8
73
6
Chlorobenzenes
Hexachlorobenzene

Tetrachlorobiphenyl
Pentachlorobiphenyl
Hexachlorobiphenyl
FY82
FY84
FY86

FY82
FY84
FY86
FY82
FY84
FY86
FY82
FY84
FY86
118
42
51
PCBs
15
48
56
78
115
135
176
198
314
.9
.3

.7
.8
.4
.3
•
•
( 1.
( 31.
( 43.

( 12.
( 36.
( 46.
( 62.
( 92.
(104.
( 119
( 177
( 276
o,
9,
3,

8,
8,
9,
3,
8,
•'
256.)
53.9)
59.3)

18.6)
60.8)
65.9)
94.4)
137.)
165.)
233.)
220.)
351.)
66.
-8.

-40.
-7.
-56.
-19.
-137-
-115.
9 ,
38

7*
60
2*
8
*
*
                             XXVI

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                        Table  ES-3.   (cont.)

Compound
Estimated
Avg . Cone .
NHATS (ng/g)
95%
Confidence
Interval
Diff .
From
FY86
                            PCBs   (cont.)
Heptachlorobiphenyl


Total PCBs(1)


Chlorination Level^


FY82
FY84
FY86
FY82
FY84
FY86
FY82
FY84
FY86
84
129
125
407
508
672
59
58
58
.6
•
.•
•
•
•
.3%
.1%
.3%
( 50
(107
( 80
(337
(469
(603
( 47
( 53
( 51
.1,
. ,
.7,

/
• /
.1,
.l!
.2,
119.)
149.)
169.)
476.)
547.)
742.)
71.0)
63.1)
65.4)
-40
3

-266
-164

1
-0

.5
.51

, *
^ *

.0
.2

Significantly different from zero at the 0.05  level.
Sum of concentrations for tetra- to octa-chlorobiphenyl.
Overall Chlorination level for PCBs, defined in Section 6.2.1.2.
                                XXVI1

-------
difference in average concentration between the FY82 and FY86
NHATS was beta-BHC; this difference was a 46% decrease from the
FY82 estimate.
        When interpreting  the observed differences  in  the
average concentration levels  between the FY86 NHATS and both the
FY82 and FY84 NHATS, it is important to consider differences in
analytical approach.  For example, differences in the internal
quantitation standards used,  the recovery levels observed, the
analytical laboratories, and  improvements made in the analytical
method over time all may contribute substantially to observed
differences between surveys.
        Additional surveys under  the current  analytical approach
 (HRGC/MS on composite samples) covering a longer time period are
needed to more accurately characterize and interpret trends in
average concentration levels  of semivolatiles.  As has been done
in the past, the designs and  analysis methods for these surveys
should be established to meet the objective of comparing results
across surveys, while minimizing any nuisance effects
contributing to the comparisons.
                              xxvi11

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1.0.  INTRODUCTION

1.1.  BACKGROUND
        The National Human Adipose Tissue Survey  (NHATS) has
been the main operative program of EPA's National Human
Monitoring Program  (NHMP).   The NHATS program has collected and
analyzed human adipose tissue samples on an annual basis to
monitor human exposure to potentially toxic compounds.  The
NHMP/NHATS was established by the U.S. Public Health Service in
1967 and transferred to the EPA in 1970.  Since 1981, the EPA
Office of Pollution Prevention and Toxics (EPA/OPPT) has been
responsible for the NHMP/NHATS.  The NHATS intended to fulfill
the human and environmental monitoring mandates of the Toxic
Substances Control Act and the Federal Insecticide, Fungicide,
and Rodenticide Act, as amended.
        Adipose tissue specimens were collected annually for the
NHATS by cooperating pathologists and medical examiners during
routine post-mortem examinations or elective surgeries.  These
cooperators were selected from a statistical sample of
Metropolitan Statistical Areas  (MSAs)  within the 48 conterminous
United States.   Target quotas specifying the number of specimens
within each donor age,  race,  and sex classification were
established for each collection center.  Sampling plans were
designed for each annual survey to produce statistically unbiased
and precise estimates of the levels and prevalence of compounds
in the U.S. population and in various demographic subpopulations.
        In the 1970s and early  1980s, the NHATS program
characterized the prevalence and levels of 19 organochlorine
pesticides and polychlorobiphenyls (PCBs) in individual human
adipose tissue specimens, using packed column gas chromatography/
electron capture detection (PGC/ECD)  methods.  Recognizing the
need to extend the capabilities of the NHATS program, the
EPA/OPPT initiated a series of programs in 1984 to expand the
utility of the tissue repository.  In order to expand the list of
target compounds monitored by NHATS,  a change to high-resolution
                               1-1

-------
gas chromatography/mass spectrometry  (HRGC/MS) methods was made.
Individual specimens were composited prior to HRGC/MS analysis to
optimize the amount of data which could be generated.  Analysis
on composite samples rather than individual patient samples
necessitated a modified statistical analysis approach to obtain
national and subpopulation estimates at an individual level.
         The  first  study  in  the  NHATS  program  which utilized the
expanded capabilities of the HRGC/MS methodology was the "Broad
Scan Analysis Study"  (Mack and  Panebianco, 1986) .  The FY82 NHATS
specimen repository was selected for this study.  The target
chemicals considered in this broad scan study included 30
semivolatile compounds, 17 volatile organic compounds, and 11
polychlorinated dibenzo-para-dioxins  (PCDDs) and polychlorinated
dibenzo furans  (PCDFs).  The broad scan study demonstrated that
13 of these semivolatile compounds, 11 of the volatile compounds,
and nine of the dioxins and furans were detected in at least half
of the composite samples. Estimated average levels for some
semivolatiles increased significantly with age, while the South
and Northeast census regions tended to have higher levels than
the West and North Central regions.
         The  FY84 NHATS specimen repository was used  in
conducting a comparability study between the PGC/ECD and HRGC/MS
analytical methods (Westat, 1990).  Paired composite samples were
analyzed using both methods.  A total of 58 semivolatile
compounds were analyzed by HRGC/MS, of which 14 were detected in
at least 50% of the samples.  The results of the comparability
study indicated that the PGC/ECD method was generally more
sensitive than the HRGC/MS method in measuring concentrations for
a variety of lipophilic compounds, with the opposite holding true
for PCBs.  Method comparability issues have yet to be resolved
for many of the target semivolatile compounds.
         The  goal of the  study performed on the NHATS FY86
specimen repository was to estimate baseline body burden levels
of semivolatile organic compounds, and to characterize trends in
these levels within predefined  demographic groups (census region,
                                1-2

-------
age group, sex, and race) .   HRGC/MS methods were employed so that

FY86 results could be compared to FY82 and FY84 results.  A total

of 111 semivolatile compounds were analyzed in the FY86 NHATS.-

This report presents the results of the FY86 NHATS analysis on

semivolatiles, along with the comparison to results from the FY82

and FY84 NHATS.


1.2.  OBJECTIVES
        The specific objectives of the FY86 NHATS and analysis

were to:


    •   Determine the extent to which semivolatile organic
        compounds are present in human adipose tissue samples,

    •   Estimate the average concentrations of semivolatiles in
        the adipose tissue of humans in the U.S. population and
        in its various subpopulations,

    •   Determine if any key demographic factors  (geographic
        region, age, race, and sex classification) are
        associated with the average concentrations of
        semivolatiles in human adipose tissue, and

    •   Compare the prevalence and estimated average
        concentration levels of semivolatiles in the FY86 NHATS
        with that from the FY82 and FY84 NHATS, where similar
        sampling and analytical techniques were used.


The results of this study will contribute to EPA's knowledge base

on the prevalence and concentration levels of semivolatiles in

human adipose tissue samples.   Statistical analysis will

determine the extent to which concentrations of these compounds

are changing over a six-year time frame in the 1980s, relative to
analytical effects and trends.


1.3.  REPORT ORGANIZATION

        Volume I of this report presents the methods, results,

and conclusions of the statistical analysis conducted on the FY86
NHATS adipose tissue sample data.   While discussions on sample

design, composite design, and chemistry methods are also included

                               1-3

-------
in this report, these subjects are more fully addressed in other
references  (see Chapter  9).
        Battelle  developed the  sample design and composite
design for  the FY86 NHATS.  The sample and composite designs are
highlighted in Chapters  2  and 3, respectively.
        Chapter  4 discusses the  chemistry procedures  that
Midwest Research  Institute (MRI) used to  analyze the FY86
composite and QC  samples.   Included in this  chapter are
discussions of overall data quality,  analytical procedures, and
QA/QC procedures.
        FY86  data issues and other pre-statistical analysis
results are presented in Chapter 5.   Detection status of the 111
semivolatile compounds are presented, along  with data issues
found to be unique to the  FY86 analysis approach.  For example,
methods were developed in  this effort to  adjust measured
concentrations for surrogate recoveries in order to more
accurately  estimate actual sample concentrations.  The results of
statistical analysis on  QC sample data are presented in Chapter
5; these results  characterize measurement error, recoveries,
background  levels, and the presence of batch effects.
        Chapter  6 contains a discussion of the  statistical
methodologies used by Battelle in estimating average
concentration levels and-associated standard errors for target
compounds.  The results  of applying these statistical
methodologies to  the FY86  NHATS data  are presented in Chapter 7.
Finally, Chapter  8 presents the results of comparing FY86 NHATS
results with those from  the FY82 and  FY84 NHATS for the same
compounds.
        Supporting information on individual sample data,
including data listings  and plots, data summary statistics, QC
data plots, and graphical  display of  the estimated average
concentrations with associated levels of uncertainty, is included
as appendices.  These appendices constitute  Volume II of this
document.
                               1-4

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2.0  NHATS FY86 SAMPLE DESIGN
         The  human adipose  tissue  specimens  in  the  FY86  NHATS
repository were collected from October, 1985, through September,
1986.  The method in which these specimens were supplied to the
NHATS program follows the NHATS Sampling Design.  In each year of
the NHATS program, cooperators (hospital pathologists or medical
examiners) collected approximately 700-1200 adipose tissue
specimens.  Although the NHATS target population is the general,
noninstitutionalized U.S. population, the sampling population was
limited to cadavers and surgical patients due to the invasive
nature of the process required to collect the adipose specimens
from living persons.
         Section 2.1 discusses the NHATS Sampling Design and  its
multistage characteristics.  Methods used to collect specimens
are discussed in Section 2.2.  Finally, a summary of the types of
specimens collected in the FY86 NHATS is presented in Section
2.3.

2.1  SAMPLING DESIGN
         The NHATS program used a multistaged sampling design to
obtain adipose tissue specimens from autopsied cadavers and
surgical patients throughout the United States.  The NHATS
Sampling Design consisted of three components:

    •    The 48 conterminous states were stratified into distinct
         geographical areas.
    •    A sample of Metropolitan Statistical Areas  (MSAs) was
         selected within the strata.  The probability of
         selecting an MSA was proportional to its population
         percentage within the stratum.
    •    One or more cooperators were chosen from each MSA and
         asked to supply a specified quota of tissue specimens to
         the NHATS.  To maintain similarity in  the sampling
         designs across fiscal years, the same MSAs and
         cooperators were retained from year to year to the
         extent possible.
                               2-1

-------
        As  part of the third component  of  the  NHATS  Sampling
Design, the manner  in which  cooperators selected the donors and
tissue specimens was nonprobabilistic, but followed a specific
set of criteria.  Quotas and subquotas for the number of
specimens supplied  to the NHATS were assigned to each cooperator.
The subquotas determined the desired number of specimens coming
from particular combinations of donor age group, race, and sex.
Demographic categories  in which subquotas were defined are
presented in Table  2-1.  The subquotas were proportional to the
1980 U.S. Census population  counts for each sampling stratum.
      Table 2-1.
Demographic Categories in Which Subquotas
Were Established for Collecting
Adipose Tissue Specimens
Subquota
Age group
Race group
Sex group
Categories
0-14 years
15-44 years
45+ years
Caucasian
Non- Caucasian
Female
Male
         Because the survey required some  divergence  from  strict
probabilistic sampling, the validity of the statistical estimates
derived  from the data depended on several assumptions:

    •    The concentrations of  toxic substances  in  the  adipose
         tissue  of  cadavers and surgical patients are assumed to
         be comparable  to  those in the  general population.
    •    The levels of  toxic substances in urban residents are
         approximately  the same as in rural  residents,  and thus
         the selection  of  only  urban hospitals and  medical
         examiners  (i.e.,  those located in MSAs) does not
         introduce  any  significant bias into the estimates of
         average concentration  levels.
                               2-2

-------
    •    No systematic bias  is  introduced by the  fact  that the
         cooperators  are  not randomly selected  and that  the
         donors  and specimens are nonprobabilistically sampled
         according to pre-specified  quotas.

Further discussion of the three components of the NHATS Sampling
Design follow.

2.1.1  The NHATS Stratification Scheme
         Prior to  1985, the  sampling strata  from which MSAs were
randomly selected were the nine U.S. Census divisions.  But in
1985,  EPA wanted the ability to obtain estimates of average
concentration levels in each of the ten EPA regions.   Thus,
beginning with the FY85 NHATS,  the sampling strata were  redefined
as seventeen geographic areas of the country, resulting  from the
intersection of the nine census divisions and the ten EPA
regions.  Selecting the sample under this new stratification
scheme made it possible to make comparisons with previous NHATS
results and also obtain estimates for the EPA regions.  The
states, census divisions, and EPA regions that  define the
seventeen strata are shown in Table 2-2.
        Although  the  FY86 NHATS sampling design specified that
specimens be collected across the seventeen strata, it was not
possible to create composites so that all specimens within a
composite came from the same stratum.  However, the Composite
Design assured that each composite contained specimens
originating from the same census division and age group.  This
was done to ensure that the FY86 and FY82 analysis results could
be compared.  Chapter 3 discusses the Composite Design in greater
detail.

2.1.2   MSA Selection
        The MSAs  were  the primary sampling  units  in the NHATS
sampling plan.  Cooperators were recruited from each selected MSA
to provide tissue samples for the NHATS.
                               2-3

-------
Table 2-2.  Sampling Strata Definitions for the NHATS
Stratum
i
2
3
4
5
6
7
8
9
10
11
Cermus Division
New England
Middle Atlantic
Middle Atlantic
South Atlantic
South Atlantic
East South
Central
East North
Central
West North
Central
West South
Central
West North
Central
West North
Central
I JEPA
Region
1
2
3
3
4
4
5
5
6
7
8
state*
Maine
New Hampshire
Vermont
Massachusetts
Rhode Island
Connecticut
New York
New Jersey
Pennsylvania
Delaware
Maryland
District of Columbia
Virginia
West Virginia
North Carolina
South Carolina
Georgia
Florida
Kentucky
Tennessee
Alabama
Mississippi
Ohio
Indiana
Illinois
Michigan
Wisconsin
Minnesota
Arkansas
Louisiana
Oklahoma
Texas
Iowa
Missouri
Nebraska
Kansas
North Dakota
South Dakota
                         2-4

-------
Table 2-2.  (cont.)
stratum
12
13
14
15
16
, 17
Oeasus Divl^iott
Mountain
Mountain
Pacific
Mountain
Pacific
Mountain
EPA
Region
8
9
9
10
10
6
States
Montana
Wyoming
Colorado
Utah
Arizona
Nevada
California
Idaho
Washington
Oregon
New Mexico
        2-5

-------
         Once the seventeen sampling strata were  identified for
the FY85 NHATS,  a sample of MSAs was selected using a controlled
selection technique, known as the Keyfitz  technique (Kish and
Scott, 1971) .  This sample differed from those MSAs selected
prior to the FY85 NHATS.  However, the Keyfitz technique
maximized the probability of retaining previously selected MSAs,
thus allowing to continue employing existing cooperators  (Mack,
et. al., 1984).  The MSA sample selected in FY85 served as the
base NHATS sample for FY86 through FY91.
         The  FY86 NHATS  sampling design contained 46 MSAs,  of
which two  (St. Louis and Moline) were each split into two primary
sampling units to reflect areas of the MSA falling into different
sampling strata.  All but one of the MSAs  selected for the FY85
NHATS were used  in the FY86 NHATS; the omitted MSA (Medford OR)
was replaced  (Eugene OR) because satisfactory cooperators could
not be found.  The sample MSAs for the FY86 NHATS are listed by
stratum in Table 2-3.  Four MSAs  (Los Angeles, Chicago, Detroit,
and New York) were listed as double collection sites because
their populations were much larger than other MSAs within their
strata.  Strata  13, 15, and 17 had no MSAs selected due to their
small population sizes.

2.1.3  Specimen  Collection Quotas
         Pre-assigned  quotas determined the numbers of  specimens
selected within  each sample MSA.  In addition, demographic
subquotas were assigned to each MSA to ensure that the specimens
collected were representative of the strata with respect to the
three demographic factors in Table 2-1 (age group,  race group,
and sex group).  The subquota assigned to  each MSA was determined
by the demographic makeup of the stratum to which the MSA
belonged and was based on the 1980 U.S. Census population counts.
Each combination of age group and sex was  proportionally
represented in the subquota.  The race categories were also
proportionally represented, but the subquota did not specify that
Caucasians and non-Caucasians were to be proportionally
                               2-6

-------
Table 2-3.  Sample MSAs Selected for the FY86 NHATS
stratum
i
2
3
4
5
6
7
8
9
10
Census Division
New England
Middle Atlantic
Middle Atlantic
South Atlantic
South Atlantic
East South
Central
East North
Central
West North
Central
West South
Central
West North
Central
EPA
^Region
1
2
3
3
4
4
5
5
6
7
Msas
,*
Springfield, MA
Boston, MA
Albany, NY
New York, NY(1)
Binghamton/Elmira, NY
Newark , NJ
Philadelphia, PA
Pittsburgh, PA
Erie, PA
Washington, DC
Norfolk, VA
Tampa , FL
Greenville, SC
Orlando, FL
West Palm Beach/
Boca Raton, FL
Miami , FL
Atlanta, GA
Memphis, TN(2)
Birmingham, AL
Lexington, KY
Dayton, OH
Detroit, MI(1)
Columbus , OH
Cleveland, OH
Akron , OH
Chicago, IL(1)
Madison, WI
Moline, IL(2)
Rochester, MN
El Paso, TX
Lubbock , TX
Houston, TX
San Antonio, TX
Dallas, TX
Omaha , NE
St. Louis, MO(2)
                        2-7

-------
                            Table 2-3.   (cont.)
Stratum
11
12
14
16
Censtfcs r&visioa
West North
Central
Mountain
Pacific
Pacific
EPA
Region
8
8
9
10
MSASJ
Sioux Falls, SD
Salt Lake City, UT
Denver, CO
San Francisco, CA
Sacramento, CA
Los Angeles, CA^
Portland, OR
Spokane , WA
Eugene , OR(3)
Yakima , WA
(1)
(2)
(3)
Indicates a double collection site.  A double collection site is an MSA
whose population relative to its stratum is so large that its proper
representation in the sample requires it to be selected twice.

Indicates a split MSA.  A split MSA is one which covers more than one
stratum.  Only the portion of the stratum in which the MSA is listed is
represented in the sample.

Indicates a replacement MSA.  A replacement MSA is an MSA that was not
selected in the FY85 probability sample, but was chosen to replace an
FY85 sample MSA for which a satisfactory cooperator could not be found.
                                     2-8

-------
represented within each combination of age group and sex.  The
subquotas only specified the total number of Caucasian and non-
Caucasian specimens to be collected from each MSA.
         The  subquotas  for  the  seventeen sampling  strata  for  the
FY86 sample design are presented in Table 2-4.  Each MSA had a
quota of twenty-seven specimens, except for the four MSAs that
were designated as double collection MSAs.   In those MSAs, the
quotas and subquotas were doubled.  Cooperators within an MSA
were assigned quotas and subquotas appropriate to that MSA.
         The  total number of samples specified for the FY86 NHATS
was 1404.  This was based on the quota of twenty-seven specimens
for each of the forty-eight MSAs, plus twenty-seven additional
specimens for each of the four MSAs designated as double
collection MSAs.

2.2  SAMPLE COLLECTION PROCEDURES
         NHATS specimens were adipose tissue samples excised by
pathologists and medical examiners during therapeutic or elective
surgery or during postmortem examinations.   If the specimen was
collected postmortem,  the tissue was obtained from an unembalmed
cadaver which had been dead for less than twenty-four hours and
had been kept under refrigeration during that time.   The death
should have been caused by sudden traumatic injury,  such as
cardiac arrest,  car accident,  or gunshot wound.
         The  following groups were excluded from specimen
collection:

    •    institutionalized individuals;
    •    persons known to be occupationally exposed to toxic
         chemicals;
    •    persons who died of pesticide poisoning; and
    •    persons suffering from cachexia.
                               2-9

-------
 Table  2-4.
FY86  Age and  Sex Subquotas, and  the Race  Subquota,
for Each NHATS  Collection Site Within Each Stratum
Stratum
#
l.
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
: Census
Division
New England
Middle Atlantic
Middle Atlantic
South Atlantic
South Atlantic
East South
Central
East North
Central
West North
Central
West South
Central
West North
Central
West North
Central
Mountain
Mountain
Pacific
Mountain
Pacific
Mountain
EPA
Region
1
2
3
3
4
4
5
5
6
7
8
8
9
9
10
10
6
# n
-------
These guidelines were stipulated so that the levels of substances
detected in the specimens were a result of environmental
exposure.
         Instructions  for the  cooperators stipulated that  at
least five grams of tissue be obtained from each donor.  In
addition, the cooperators were to avoid contamination through
contact with disinfectants, paraffins, plastics, preservatives,
and solvents.  Cooperators placed the collected specimens in
glass jars with Teflon® lids and stored them at -10°  to -20° C.
The jars were packed on dry ice for overnight shipment to MRI,
the contractor responsible for tissue storage.   MRI received the
specimens and checked them for adequacy of  shipping conditions
and level of conformance with cooperator quota.  MRI  determined
an approximate specimen weight and transferred the specimens to
storage at -20° C.  Upon examining the patient summary reports,
MRI forwarded the reports to Battelle for processing.

2.3  SPECIMEN COLLECTION SUMMARY
        In the FY86 NHATS, cooperators provided 739 specimens  in
31 of the sample MSAs.  In preliminary review of the  specimens,
671 were collected in accordance with the quotas and  subquotas.
These specimens were labeled "Design" specimens.  The  remaining
specimens were labeled "Surplus" specimens,  as their  collection
was considered beyond the quotas and subquotas requested.
        The process of labeling specimens as Design or Surplus
followed established guidelines (Orban,  et.  al., 1988).  However,
EPA added a stipulation that the collection dates of  Surplus
specimens be uniformly distributed throughout the fiscal year.
Also, it was necessary to modify Surplus specimen assignment from
the preliminary review,  as one composite contained mostly low
weight specimens.   Surplus specimens were relabeled as Design
specimens and added to this composite in order for the composite
to achieve sufficient tissue mass.  Meanwhile,  the same number of
Design specimens from another amply-represented composite within
the same census division were relabeled Surplus specimens and
                               2-11

-------
removed from the composite.  Thus the total number of Surplus
specimens collected in FY86 did not change following this
adjustment.  The maximum number of specimens from a MSA remained
at the original quota of twentyTseven (or fifty-four from a
double-collection MSA)
        Table  2-5  is  a  summary of  the collection  effort  for  the
FY86 NHATS, detailed by census division.  In FY86, EPA chose not
to make estimates for EPA regions.  Instead, EPA maintained
similarity to the FY82 geographic classifications in order to
compare FY86 results to FY82 results.  All 671 Design specimens
were placed into one of fifty composites, on which laboratory
analysis was performed.
        Table  2-6  shows the number of quota specimens, collected
specimens, and Design specimens in each of the four demographic
subpopulations  (census region, age group, sex, and race)  which
act as analysis factors in  the linear model.  Because the number
of samples in the chemical  analysis was not large enough to
obtain reliable estimates for all nine census divisions,  Battelle
combined the divisions into four census regions for the FY82,
FY84, and FY86 model analyses.
                               2-12

-------
                               Table  2-5.  FY86 NHATS Specimen Collection Summary
Census Division
New England
Middle Atlantic
South Atlantic
East South Central
West South Central
East North Central
West North Central
Mountain
Pacific
Total
Ho. of
Besigtt
MS As
2
7<2)
8
4
5
8<3)
5
2
7<2)
48
No. of Quota
Specimens
54
216
216
108
135
270
135
54
216
1404
HO. Of ;
Cooperating
MSAs
2
4(2)
6
2
1
7<3)
2
2
5(2)
31
No. of
Speci&e&s
Collected.
43
81
173
51
31
209
56
34
61
739
No. Of
Design
Specimens1*'
43
80
128
50
27
194
54
34
61
671
No. of
COR£>OSite
Samples
4
5
8
4
3
11
5
4
6
50
to
I
H
OJ
    (1)   Resulting after the Design/Surplus Indicator was  assigned to each specimen.
    (2)   Includes one double collection quota MSA.
    (3)   Includes two double collection quota MSAs.

-------
Table 2-6.
FY86 NHATS Specimen Collection Summary by
Demographic  Subpopulation
Analysis
Factor .
Census
Region
Age
Group
Sex
Group
Race
Group
Category
Northeast
North Central
South
West
Total
0-14 years
15-44 years
45+ years
Total
Male
Female
Total
White
Nonwhite
Total
No. of Quota
Specimens
270
405
459
270
1404
317
642
445
1404
681
723
1404
1179
225
1404
No. of
Specimens
Collected
124
265
255
95
739
115
248
376
739
354
385
739
564
175
739
No. of
Design
Specimens
123
248
205
95
671
108
221
342
671
315
356
671
529
142
671
                         2-14

-------
3.0  NHATS FY86 COMPOSITE DESIGN
        Battelle assigned the 671 Design specimens in the  FY86
NHATS tissue repository to composite samples using specific
composite design criteria (Orban,  et.  al.  1988).  The necessity
for compositing samples prior to chemical  analysis was to ensure
that at least twenty grams of tissue were  available per sample to
meet the limit of detection goals for the  target compounds.  The
Composite Design resulted in constructing  50 composite samples.

3.1  DESIGN GOALS AND COMPOSITING CRITERIA
        The  five goals of the FY86 NHATS Composite Design,
listed in order of importance,  were to:

    •   maintain similarity to the FY82 Composite Design,
    •   maintain equal weighing of specimens within the
        composite samples,
    •   specify additional numbers of pure sex composite samples
        than in FY82,
    •   control the MSA effect, and
    •   provide the best range of race group percentages across
        the  composite samples.

        Because of the constraints imposed by the sampling and
compositing protocols and the frequency of collection
nonresponse,  it was not always  possible to meet  all the design
goals.  Each of the above goals required a different  mix of
individual specimens within the composite  samples.   Thus,
attempts were made to achieve all goals across the design to the
extent possible.   The five goals are discussed in detail below.

1 •   Similarity to the FY82 Composite Design
        EPA  imposed this criterion to ensure that the results of
FY86 data analysis could be compared with  FY82 results,  where
compositing was performed and the same semivolatile compounds
were analyzed.   The design criterion imposed by this objective is

                               3-1

-------
that each composite sample had to be constructed from individual
specimens collected from  exactly one census division and exactly
one age group category.   Thus there were 27 distinct categories
within which composite samples were formed.
         Once the FY86 Composite  Design was established,  it was
desired to compare results of data analysis on the FY86 samples
with the results obtained from the HRGC/MS analysis on FY84
composite samples.  The FY84 Composite Design closely paralleled
the FY82 Composite Design, allowing the FY86 results to be
compared with the FY84 results as well as the FY82 results.  Of
primary importance, the FY84 design stipulated that all specimens
found in a given composite originate from the same age group and
census division.

2.  Equal weighing of specimens within the composite samples
         This criterion is primarily  for ease of  interpretation.
In attempting to make inferences on individual specimen
concentrations, it is far easier to interpret the observed
composite sample concentrations as the arithmetic average of the
individual specimen concentrations.  Therefore, this design goal
specified that each individual specimen within a composite sample
contribute an equal amount of tissue to the composite sample.
This specification allows the lipid-adjusted concentration of the
composite sample to be interpreted as approximately the
arithmetic average of the lipid-adjusted individual specimen
concentrations, with  equality occurring whenever all specimens in
the composite sample  have the same percentage of lipid material.
         In  the  FY86 analysis, specimens were not labeled as
Surplus as a result of specimen weight, nor was specimen weight
used to determine whether the specimen would be included in a
composite sample.  The specimen weights were evaluated only after
composites were defined based on the other design criteria.
Composites with insufficient tissue mass for chemical analysis
were modified if practical alternatives were available.  This
                               3-2

-------
policy resulted in combining two initial composites and modifying
an additional two composites.
         To ensure  that  equal weighing  of specimens within the
composite  samples was maintained throughout the analysis,
instructions for evaluating individual specimen weights were
based on the ratio of the maximum weight to the minimum weight of
all specimens within the composite sample.   Any low-weight
specimens  causing this ratio to exceed 3.0  was recommended for
removal from the composite.

3.  Construct more pure sex composite samples than in FY82
         Pure sex composites  (composites containing specimens
originating from either all male patients or all female patients)
were constructed when sufficient numbers of specimens were
available within a particular census division/age group category
and more than one composite sample was allocated to this category
by the design.   Pure sex composites were needed to achieve more
precise estimates of sex effects in the population.   This design
strategy was in contrast to the FY82 Composite Design,  which
provided for more balanced sex composite samples (samples with
nearly half male and half female specimens).   Including more pure
sex composites in the FY86 design intended  to reduce the standard
errors for the sex group estimates from that observed for the
FY82 analysis (Draper and Smith, 1981,  pp.  52-55) .

4.  Control the MSA effect
         Controlling the number  of MSAs contributing specimens to
composite samples was intended to reduce the effect of the MSA on
the estimated average concentrations.   This was done because MSAs
are regarded as being major sources of differences in observed
concentrations across the nation due to their varied exposure
scenarios  (Panebianco,  1986).   To avoid confounding the MSA
effect with any of the geographic or demographic effects, the
Composite Design stipulated:
                               3-3

-------
    4a.  to keep the number of MSAs represented in each composite
         sample consistent across the design (targeted at  2-3
         MSAs),  and
    4b.  to maintain approximately the same number of  pure sex
         composite samples within a group of MSAs.

Criterion  4a helped to ensure  a  constant variance of measured
concentrations  across the  sample whenever  the composite sample
concentrations  are  averages over an  equal  number of MSAs.
Criterion  4b was  intended  to prevent  confounding a large MSA
effect with the sex effect.
5.   Control  the  race  group percentages  across the composite
     samples
         The  benefits  for constructing pure race  group  composite
samples paralleled the benefits for constructing pure sex
composite samples.  However, achieving  this design goal was
dependent on the number  of  non-Caucasian specimens collected in
the twenty-seven census  division/age group categories and the
number of composite samples in the design.  At least one pure
Caucasian composite sample  and at least one pure non-Caucasian
composite sample were constructed in four different census
division/age group categories.

3.2  LABORATORY COMPOSITING PROCEDURES
         In the FY86 NHATS Composite Design, specimens  from nine
census divisions and three  age groups were segregated into 50
composites.  Battelle provided MRI with composite sample data
sheets that identified the  specific individual specimens to be
included in each composite  (Appendix A of Orban,  et. al.,  1988).
A composite consisted of  from three to  twenty-four specimens.
The composite  sample data sheets provided sufficient information
(EPA ID number, package  number, sample weight, hospital code,
etc.) such that the individual specimens could be cross-checked
with the study design.   The data sheets were used as work sheets
to record actual laboratory compositing procedures.

                               3-4

-------
         Initially,  the samples  were  grouped into  composites,  and
any samples of insufficient weight (< 1.0 g) or potentially
contaminated samples were reported by MRI to the EPA Work
Assignment Manager  (WAM).   Such samples were omitted from the
analysis.
         The weights of composites  included  in  laboratory
analysis ranged from 1.884g to 22.514g, with three composites
below the target weight of 20g.   The composite with the lowest
weight consisted of only three samples from the 0-14 year age
category.  The other two composites below the target weight had
insufficient samples.
         The composite  samples were placed on dry  ice during the
compositing procedure.   An electronic four-place balance was used
to weigh the samples, and the calibration of the balance was
checked with a Class P set of weights (laboratory grade,
tolerance 1/25,000)  before any weighing was begun and once during
the sample weighings.
         To weigh the samples, a clean culture  tube was  labeled
with the composite number.  This tube was placed on the balance,
and the weight was tared.   A sample was removed from the
composite bag,  the jar opened,  and a portion of the frozen
adipose removed with a clean stainless steel spatula.   The
adipose was placed in the  culture tube and the weight recorded to
three decimal places on the compositing sheets.  Additional
adipose was added if necessary.   A goal of ±10% of the desired
weight was attempted where possible.   The weights of the
individual specimens were  recorded on the composite data sheets.
         The weight  of  the culture, beaker,  and adipose  tissue
was rezeroed,  and the next sample in the composite was weighed.
A new spatula was used between each sample.   This procedure was
repeated for each sample in the composite.  When the composite
was completed,  it was capped and stored in a sample freezer at
-10° C.  All data on the actual compositing procedures  (amount
added, remaining spec,  weight,  date inventoried,  and total weight
of the composite)  were recorded on the data sheets provided by
                               3-5

-------
Battelle.   MRI submitted all data sheets in a separate report
documenting the compositing activity  (MRI, 1988a).

3.3  SUMMARY OF FY86 NHATS COMPOSITE SAMPLES
        The  FY86  NHATS Composite Design resulted in  constructing
50 composite samples using 671 individual specimens collected
from 31 MSAs. Composite samples were formed from specimens
collected exclusively  from the same census division/age group
category.   The numbers of composites within each of these
categories are given in Table 3-1.  Unlike the exclusivity by
census division and age group, the composite samples had specimen
percentages within sex and race groups which varied across the
design depending  on the availability of specimens within specific
demographic subpopulations.  Table 3-2 shows the demographic
makeup of the FY86 NHATS composite samples.
        The  50  composite  samples were randomly  assigned  to  five
laboratory batches of ten samples each.  Within each batch,  the
ten composite samples and three lipid-based QC samples were
placed in random  order for chemical analysis.
                               3-6

-------
Table 3-1.  Distribution of FY86 NHATS Composite Samples by
            Census Division and Age Group
Census Eiviaioa
New England
Middle Atlantic
South Atlantic
East South Central
West South Central
East North Central
West North Central
Mountain
Pacific
Total
# Composites by Age Qroup
0-14
years
i
i
2
1
1
1
1
1
1
10
15-44
years
i
2
3
2
1
3
2
1
1
16
45+
years
2
2
3
1
1
7
2
2
4
24
Total # of
Composites
4
5
8
4
3
1
5
4
6
50
                            3-7

-------
Table 3-2.  Demographic Makeup of FY86 NHATS Composite Samples
Composite
Census Division ID
New England ACS8600261
ACS8600270
ACS8600289
ACS8600298
Middle Atlantic ACS8600172
ACS8600181
ACS8600190
ACS8600207
ACS8600216
U)
i
00 South Atlantic ACS8600369
ACS8600378
ACS8600387
ACS8600396
ACS8600403
ACS8600412
ACS8600421
ACS8600430
East South ACS8600136
Central ACS8600145
ACS8600154
ACS8600163
Age
Group*1*
1
2
3
3
1
2
2
3
3


1
1
2
2
2
3
3
3
1
2
2
3
Number of
Individual
Specimens
9
13
9
12
9
21
16
18
16


15
12
23
16
12
15
20
15
10
9
13
18
Number
of
MS As
2
2
2
2
3
4
3
4
4


6
4
4
5
4
5
6
5
2
2
2
2
Percent
Male
44.4
53.8
100.0
0.0
44.4
100.0
0.0
100.0
0.0


100.0
0.0
100.0
43.8
0.0
100.0
0.0
33.3
50.0
100.0
0.0
44.4
Proportionate
Percent Tissue Amt . ®
Caucasian (g)
88.9
69.2
66.7
100.0
88.9
85.7
75.0
88.9
75.0


46.7
58.3
100.0
0.0
100.0
100.0
100.0
0.0
50.0
77.8
92.2
72.2
2.22
1.54
2.22
1.67
2.22
0.95
1.25
1.11
1.25


1.33
1.67
0.87
1.25
1.67
1.33
1.00
1.33
2.00
2.22
1.54
1.11

-------
                                       Table 3-2.   (cont.)
vo
Census Division
West South
Central

East North
Central









West North
Central



Composite
ID
ACS8600494
ACS8600500
ACS8600519
ACS8600029
ACS8600038
ACS8600047
ACS8600056
ACS8600065
ACS8600074
ACS8600083
ACS8600092
ACS8600109
ACS8600118
ACS8600127
ACS8600449
ACS8600458
ACS8600467
ACS8600476
ACS8600485
Age
Group^
1
2
3
1
2
2
2
3
3
3
3
3
3
3
1
2
2
3
3
Number of
Individual
Specimens
10
9
8
19
17
18
20
16
11
24
19
14
16
20
12
9
11
10
12
Number
of
MSAs
1
1
1
3
3
3
3
3
3
4
2
3
3
1
2
2
2
2
2
Percent
Male
50.0
55.6
50.0
52.6
100.0
38.9
0.0
100.0
36.4
100.0
42.1
0.0
0.6
0.0
58.3
100.0
0.0
100.0
0.0
Proportionate
Percent Tissue Amt.®
Caucasian (g)
70.0
77.8
75.0
68.4
100.0
83.3
80.0
100.0
0.0
100.0
0.0
100.0
100.0
100.0
91.7
77.8
90.9
100.0
100.0
2.00
2.22
2.50
1.05
1.18
1.11
1.00
1.25
1.82
0.83
1.05
1.43
1.25
1.00
1.67
2.22
1.82
2.00
1.67

-------
                                              Table  3-2.   (cont.)
U)


Census Division
Mountain



Pacific






Composite
ID
ACS8600225
ACS8600234
ACS8600243
ACS8600252
ACS8600305
ACS8600314
ACS8600323
ACS8600332
ACS8600341
ACS8600350

Age
Group(1)
1
2
3
3
1
2
3
3
3
3
Number of
Individual
Specimens
3
8
12
11
9
6
16
12
7
11
Number
of
MSAs
1
2
2
2
2
2
3
2
2
2

Percent
Male
0.0
25.0
100.0
0.0
77.8
33.3
100.0
0.0
0.0
0.0

Percent
Caucasian
100.0
87.5
83.3
90.9
66.7
83.3
93.8
100.0
0.0
100.0
Proportionate
Tissue Amt.^
(g)
6.67
2.50
1.67
1.82
2.22
3.33
1.25
1.67
2.86
1.82
        Age groups:  1 = 0-14 years;   2  =  15-44 years;  3 = 45+ years.

        Proportionate Tissue Amount = the  approximate amount of tissue  (g) contributed by each individual
        specimen, where the total composite  weight  is assumed to be 20 g.

-------
4.0  CHEMISTRY
         The 50  composite samples  in the  FY86  NHATS  were  prepared
by MRI in the analysis laboratory for determination of
semivolatile compounds using high-resolution gas chromatography/
mass spectrometry  (HRGC/MS).  The performance of the analysis
effort was demonstrated through recoveries of surrogate compounds
and internal quantitation standards  (IQS), as well as through
analysis on 20 QC samples  (method blanks, control tissue samples,
and spiked control tissue samples).
         Section 4.1  discusses the various steps  in  the
analytical procedure, including how results are quantified.
Section 4.2 presents the QA/QC methods that were implemented.
The presentation of the results for analysis of QC samples is
primarily relegated to Chapter 5.   Section 4.3 presents data
quality objectives established for the laboratory analytical
method and the extent to which these objectives were met.

4.1.  ANALYTICAL PROCEDURES
         The analytical procedures performed in the  FY86 NHATS
included the extraction and cleanup of the composite tissue
samples using Gel Permeation Chromatography (GPC) and Florisil
column fractionation, the analysis by HRGC/MS, and the
quantitation of results.   A flow diagram of these activities is
found in Figure 4-1.   Each of these procedures is described in
detail below.

4.1.1.  Sample Preparation
         The preparation  of  the composited adipose tissue
specimens for determination of semivolatiles required a multistep
procedure.  The stages of this procedure include quantitative
extraction and cleanup through several chromatographic columns.
These stages are described below.
                               4-1

-------
                   Human Adipose Tissue, 20 g
              Add Stable Isotope-Labeled Surrogate
             	  Compounds
                    Extraction = Tissuetnizer
                       Bulk Lipid Removal
                 Gel Permeation  Chromatography
                     Florisil Fractionation

               •  200 mL 6% ethyl ether / hexane
               •  300 mL 50% ethyl ether / hexane
                       HRGC/MS (Scanning)
                         0.01  = 0.1  /ig/g
                  (PCBs, OC1 Pesticides,  etc.)
                  Quantitation / Data Transfer
Figure 4-1,
Flow Scheme for Analysis of Semivolatile Compounds
in the FY86 NHATS
                              4-2

-------
4.1.1.1.  Extraction.  After the compositing stage  (Chapter  3),
the adipose composites were stored at -10°C in 50-mL culture
tubes sealed with aluminum foil.  To begin the sample extraction
procedure, the samples were allowed to come to room temperature
and then fortified with 200 /iL of the surrogate spiking solution.
Spiked control QC samples were fortified with 50 piL and 200 /iL of
the native compound spiking solution for the low- and high-dose
samples, respectively.  Ten milliliters of methylene chloride was
added and the sample homogenized for 1 min with a Tekmar
Tissuemizer.  The mixture was allowed to separate,  and the
methylene chloride was decanted through a funnel of 5 to 10 g of
sodium sulfate into a 200-mL volumetric flask.   The funnel was
rinsed with 10 mL of methylene chloride into the volumetric
flask.  The homogenization was repeated two times with fresh 10-
mL portions of methylene chloride.   The culture tube was rinsed
with additional methylene chloride and the remaining contents of
the tube transferred to the funnel.   Finally,  the funnel was
rinsed with additional methylene chloride until the volumetric
flask was brought up to volume (200 mL).

4.1.1.2.  Lipid Determination.   At this point  the flask was
stoppered, inverted several times to mix the extract,  and 1 mL
was removed with a disposable pipet and placed into a preweighed
(measured to 0.0001 g) 1-dram glass vial.  The methylene chloride
in the vial was reduced under nitrogen until an oily residue
remained.  The weight of the lipid was obtained by difference,
and the percent lipid for the composite was calculated and
recorded.

4.1.1.3.  Extract Concentration.  The remaining portion of the
extract (99 mL)  was quantitatively transferred, with a 30- to 40-
mL rinse, to a 500-mL Kuderna-Danish evaporator equipped with a
20-mL receiver.   One or two clean boiling chips and a three-ball
Snyder column were added to the flask.  The Snyder column was
prewet with 1 mL of methylene chloride and the volume reduced to
                               4-3

-------
15 to 25 mL over a steam bath.  The apparatus was removed from
the steam bath and allowed to cool.  The flask and joint were
rinsed with 5 mL of methylene chloride into the receiver.  The
extract was then quantitatively transferred to a 40-mL sample
vial with a TFE-lined screw cap, adjusting the volume to approxi-
mately 40 mL with methylene chloride.

4.1.2.  Cleanup Procedure

4.1.2.1.  Gel Permeation Chromatography.  GPC columns were packed
with 60 g of Bio-Beads SX-3 that had been allowed to swell
overnight in methylene chloride:cyclohexane (50:50).  The beads
were allowed to settle to form a uniform packing.  Solvent,
methylene chloride:cyclohexane  (50:50), was pumped through the
column at a flow rate of 5 mL/min.  After air had been displaced
from the column, the pressure was adjusted to 5 to 15 psi.
         The GPC column was  then calibrated using a  solution of
approximately 1 mg/mL butyl benzyl phthalate,  1 mg/mL 4-nitro-
phenol, and 390 mg/mL extracted bulk human lipid in methylene
chloride.  The calibration resulted in a GPC program that
provided 135 mL  (27 minutes) of eluent with lipid directed to a
discard fraction, followed by a 225 mL (45 minute)  collection
period.  This was the chrbmatographic pattern established from
the elution of the butyl benzyl phthalate through the elution of
4-nitrophenol.  An additional wash time of 50 mL (10 minutes)  was
included to prevent sample carryover.
         Prior  to loading  the  GPC,  the  sample  collection  tubes
and injector port were rinsed with acetone,  methylene chloride,
toluene, and hexane.  Syringes, beakers,  and filters were washed
with soap and water, rinsed with water, deionized water,  acetone,
methylene chloride, toluene, and hexane.   All extracts were drawn
through a Millipore stainless steel Swinney filter with a 0.5-^im
type FH membrane.  Sample loops were rinsed with 5 mL of methy-
lene chloride:cyclohexane (50:50) and loaded with 2 mL of the
sample extracted followed by 3 mL of solvent.   One loop between
                               4-4

-------
each composite was used as an eluent blank.  The cleaned extracts
were collected in clean 4-L amber solvent bottles.

4.1.2.2.  GPC Eluent Concentration.  The cleaned extracts from
the combined GPC effluent was concentrated, using 500- or 1000-mL
Kuderna-Danish (K-D) evaporators, to approximately 10 mL.  The
Snyder column was prewet with methylene chloride and a new
boiling chip added with addition of eluent.  When all the eluent
was concentrated to 5 to 10 mL,  the apparatus was allowed to
cool.  If the extract remained highly colored or viscous, the
sample was quantitatively loaded onto the GPC and reprocessed in
three to four loops.  Then the extract was reconcentrated and
transferred to Florisil as follows.  If the sample extract
appeared clean, 50 mL of hexane was added.  The Snyder column was
replaced and prewet with 1 mL of hexane.  The volume was reduced
to 10 mL and the flask and lower joint rinsed with 1 to 2 mL of
hexane into the concentrator tube.  The extract was then concen-
trated to approximately 1 mL under a gentle stream of purified
nitrogen.

4.1.2.3.  Florisil Column Cleanup.  A 25- x 300-mm
chromatographic column with solvent reservoir and TFE stopcock
was prepared by packing the bottom with a small wad of silanized
glass wool and rinsing with 20 mL of hexane.  A 100-mL aliquot of
hexane was added to the column.   The precleaned Florisil was
allowed to cool in a desiccator, and 12.5 grams were transferred
to the column.  When the Florisil had settled,  sufficient
anhydrous sodium sulfate was added to achieve a one-half inch
layer on top of the Florisil.  The hexane was drained just to the
top of the anhydrous sodium sulfate layer.  The extract was
transferred to the top of the column.  The extract receptacle was
rinsed with three successive 2- to 3-mL aliquots of hexane,
adding the rinses to the column.
        A  500-mL K-D  flask and  receiver were placed under  the
column, and the sample was drained onto the column until the
                               4-5

-------
anhydrous  sodium sulfate  was  nearly exposed.  The  column was
eluted with  200  inL of  6%  ethyl  ether in  hexane  (v/v)  (Fraction  1)
at a rate  of about 5 mL/min.  The  K-D flask and receiver were
replaced with another  K-D flask and receiver.   The column was
eluted with  300  mL of  50% ethyl ether in hexane (v/v)  (Fraction
2) .
         The fractions were concentrated to approximately 10 mL
using hexane to  prewet the Snyder  column.  The  flask  and lower
joint were rinsed with 1  to 2 mL of hexane.  The receiver was
then placed  under a gentle stream  of purified nitrogen and  the
volume reduced to less than 1 mL.
         If either fraction remained highly colored, viscous,  or
turbid, it was rediluted  in methylene chloride  and loaded again
on the GPC.   If  the sample appeared clean, the  sample was trans-
ferred to  a  clean precalibrated reactivial.  The receiver was
rinsed with  three 1-mL aliquots of hexane, adding  the rinse to
the reactivial.   The volume was reduced  to less than  0.5 mL, the
vials sealed,  and the  samples refrigerated.
         All  6% fractions were reduced to 200  ^iL under a  gentle
stream of  purified nitrogen.  The  6% fractions  were fortified
with 200 /xl  of an internal quantitation  standard (IQS) solution
and the volume returned to 200  /*L  under  a gentle stream of
purified nitrogen.  The IQS solution included naphthalene-d8,
anthracene-d10/ and benzo [a] anthracene-d12.  An aliquot of each
sample was transferred to an  autosampler vial and  submitted for
HRGC/MS analysis.
         The  50%  fractions were  further reduced under a gentle
stream of  purified nitrogen.  The  50% fractions were  further
reduced under a  gentle stream of purified nitrogen.   A white
precipitate  formed in  some samples.   The volume was reduced to
200, 400,  or 600  /zL, depending  upon the  volume  of  precipitate.
An aliquot of  the IQS  solution  equal to  the sample volume was
added, and then  the samples were concentrated to the  same volume
                               4-6

-------
they had prior to addition of the IQS solution.  An aliquot of
each sample.was submitted for HRGC/MS analysis.

4.1.3.  Analysis Procedures
        The quality assurance program plan  for the FY84  and FY86
NHATS analysis of composite samples  (Stanley et. al. ,  1986)
describes in detail the analytical methodology for the HRGC/MS
analysis of semivolatiles in the FY86 NHATS.  Additional
information related to the method can also be found in USEPA
(1986).   Specific differences in the methods between these three
surveys are discussed in Chapter 8.   Sections of these reports
relevant to the FY86 approach are included below.
        At  the beginning of each day that analyses were  per-
formed,  the analyst verified that the instrument was  properly
calibrated through analysis of decafluorotripheylphosphine
(DFTTP,  see Section 4.2.1).  The analyst documented whether the
DFTTP criteria were satisfied.
        Prior to beginning analysis, a hexane  blank was  injected
to document system cleanliness.   If any evidence of system
contamination was found, then another hexane blank was analyzed.
        Two microliters  (determined  to nearest  0.1 /xL) of  the
spiked sample extract were injected into the HRGC/MS  system using
a splitless injection technique.  The syringe was carefully
cleaned between injections by the following procedure to prevent
carryover of contaminants:

    •   Rinse the syringe 10 times with hexane;
    •   Fill the syringe with toluene and sonicate syringe and
        plunger in  toluene for  5 min and repeat  at least twice;
    •   Rinse the syringe 10 times with hexane.

After applying this procedure,  the syringe was ready for use.
        Instrument  performance  was monitored by examining  and
recording the peak areas for the three IQS.   If these areas

                               4-7

-------
decreased to less than 50% of the calibration standard, then
sample analyses were stopped until the problem was found and
corrected.
         The recommended  HRGC/MS operating  conditions  for the
semivolatile organic compounds are listed in Table 4-1:
       Table 4-1.   Recommended HRGC/MS Operating Conditions
Column temperature column
Injector temperature
HRGC/MS interface
Carrier gas
Injector technique
Electron energy
Mass range
60°C (2 min) then 10°C/min to 310°C
(10 min)
250°C
300°C
Helium at 30 cm/sec
2 /iL, splitless with a 45-second
delay, a split flow of 30 mL/min,
and a septum purge of 5 mL/min
70 eV (nominal)
40-550 amu
4.1.4.  Quantitation/Data Reduction
         In this subsection,  the  procedures  for the data reduc-
tion are outlined for the-analysis of data from the HRGC/MS
method for semivolatile compounds.  The data for each sample were
interpreted with computer-assisted quantitation routines.   A mass
spectral library and quantitation list of the target analytes
based on relative retention times and the primary characteristic
ion were used to search each data file.

4.1.4.1.  Qualitative Identification.  The quantitation routine
identified positive responses based on the primary or secondary
characteristic  ion for each of the analytes.  Table 4-2 provides
a list of these analytes  (native compounds,  surrogates, and IQS) ,
along with the primary and secondary quantitation ions used for
compound characterization.
                               4-8

-------
Table 4-2.  Characteristic Masses and Intensities for the Qualitative Identification of the Semivolatile
            Target Analytes, Chromatographic Conditions, and Estimated Limit of Detection
Cotqpotaad
Organochlorine Pesticides
E-B' -DDT
o,E'-DDT
E,E'-DDE
O,E' -DDE
E,E'-DDD
O,E' -ODD
a-BHC
0-BHC
7-BHC (lindane)
6-BHC
Aldrin
Dieldrin
Endrin
Heptachlor
Heptachlor epoxide
Oxychlordane
Mi rex
trans -Nonachlor
Characteristic Masses (nv/z)
vximxy \
secoxKlaxy
: s&con4aaey
Relative
Retention
?ime«> i
Esfc, Mmit
ot Detection
tear/g*W
Internal
QttanMtati0»
Standard

235 (100) <*>
235 (100)
246 (100)
246 (100)
235 (100)
235 (100)
183 (100)
183 (100)
183 (100)
183 (100)
263 (100)
263 (100)
263 (100)
100 (100)
353 (100)
115 (100)
272 (100)
409 (10Q)
237 (72)
237 (66)
248 (58)
248 (64)
237 (66)
237 (66)
181 (96)
181 (96)
181 (96)
181 (96)
265 (67)
265 (58)
265 (66)
272 (35)
355 (83)
185 (35)
274 (82)
407 (91)
165 (48)
165 (59)
176 (41)
176 (38)
165 (58)
165 (58)
219 (68)
219 (81)
219 (66)
219 (81)
261 (63)
279 (58)
279 (38)
274 (30)
351 (56)
187 (30)
270 (51)
411 (65)
1.33-1.39
1.29-1.35
1.23-1.29
1.19-1.25
1.28-1.34
1.24-1.30
0.90-0.96
0.95-1.00
0.95-1.01
0.99-1.05
1.09-1.15
1.23-1.29
1.26-1.44
1.08-1.14
1.16-1.21
--
1.46-1.52
1.21-1.27
0.010
0.010
0.010
0.010
0.010
0.010
0.010
0.010
0.010
0.010
0.010
0.050
0.050
0.010
0.010
0.010
0.010
0.010
Anthracene - d10
Anthracene - d10
Anthracene - d10
Anthracene - d10
Anthracene - dj0
Anthracene -djQ
Anthracene - d10
Anthracene - d10
Anthracene - d 10
Anthracene - dj0
Anthracene - d10
Anthracene - d10
Anthracene - di0
Anthracene - d10
Anthracene - d10
Anthracene - di0
Benzo [a] anthracene-d12
Anthracene - d10

-------
                                               Table 4-2.   (cont.)

Compound
•y-Chlordane
Characteristic Masses (m/z)
Primary
373 (100)
Secondary
375 (99)
Secondary
377 (50)
Relative
Retention
TitW^>
1.19-1.24
Est « Limit
of Detection
(t*3/&m
0.010
:•:
:, Internal
: Quantitation . »
Standard
Anthracene - d10
Polychlorinated Biphenyls (PCBs)
Monochloro- (3-isomers)
Dichloro- (12-isomers)
Trichloro- (24-isomers)
Tetrachloro- (42-isomers)
Pentachloro- (46-isomers)
Hexachloro- (42-isomers)
Heptachloro- (24-isomers)
Octachloro- (12-isomers)
Nonachloro - ( 3 - isomers )
Decachloro- (1-isomer)
188 (100)
222 (100)
256 (100)
292 (100)
326 (100)
360 (100)
394 (100)
430 (100)
464 (100)
498 (100)
190 (33)
224 (66)
258 (99)
290 (76)
328 (66)
362 (82)
396 (98)
428 (87)
462 (76)
500 (87)
--
226 (11)
260 (33)
294 (49)
324 (61)
358 (51)
392 (44)
432 (66)
466 (76)
496 (68)
0.63-0.86
0.81-0.95
0.81-1.10
0.90.1.30
1.05-1.40
1.25-1.49
1.30-1.61
1.40-1.55
1.49-1.61
1.61-1.67
0.010
0.010
0.010
0.010
0.020
0.020
0.020
0.020
0.020
0.050
Chlorobenzenes
Trichloro- (3-isomers)
Tetrachloro- (3-isomers)
Pentachlor-
Hexachloro-
180 (100)
216 (100)
250 (100)
284 (100)
182 (98)
214 (77)
252 (65)
286 (82)
184 (32)
218 (49)
248 (61)
282 (51)
0.36-0.60
0.55-0.80
0.76-0.82
0.91-1.00
0.010
0.010
0.010
0.010
Anthracene - djo
Anthracene - d10
Anthracene - d10
Anthracene - d10
Anthracene - d10
Benzo [a] anthracene -d12
Benzo [a] anthracene -d12
Benzo [a] anthracene-d12
Benzo [a] anthracene -d12
Benzo [a] anthracene -d12

Naphthal ene - d8
Naphthalene- d8
Anthracene - dw
Anthracene - d10
I
M
O

-------
Table 4-2.  (cont.)
i • •
: Compound .,
Phthalate Esters
Dimethyl phthalate
Diethyl phthalate
Di-n-butyl phthalate
Butyl benzyl phthalate
Di-n-octyl phthalate
Bis(2-ethylhexyl) phthalate
Characteristic Masses (m/z)
Primary •

163 (100)
149 (100)
149 (100)
149 (100)
149 (100)
149 (100)
>
Secondary
Secondary
Relative
Retention
Tirne^
Est, Mmlt
of Detection
^sr/0)^
Internal
Quantitation
Standard

194 (11)
177 (31)
150 (19)
167 (38)
167 (41)
167 (35)
164 (10)
150 (12)
104 (9)
279 (-)
--
279 (11)
0.70-0.76
0.82-0.87
1.08-1.14
1.33-1.38
1.43-1.48
1.50-1.60
0.010
0.010
0.010
0.010
0.010
0.010
Anthracene - dlQ
Anthracene - d10
Anthracene - d10
Benzo [a] anthracene -d12
Benzo [a] anthracene -d12
Benzo [a] anthracene -d12
Phosphate Triesters
Tributyl phosphate
tris(2-Chloroethyl) phosphate
tris (Dichloropropyl) phosphate
Tributoxyethyl phosphate
Tritolyl phosphate
Triphenyl phosphate
99 (100)
143 (100)
99 (100)
101 (100)
91 (100)
326 (100)
155 (27)
249 (95)
191 (65)
325 (99)
165 (80)
325 (65)
211 (16)
251 (60)
209 (45)
170 (32)
368 (77)
170 (24)
0.86-0.92
0.95-1.00
1.32-1.38
1.36-1.46
1.46-1.57
1.31-1.37
0.050
0.040
0.050
0.020
0.020
0.020
Anthracene - dj0
Anthracene - d 10
Benzo [a] anthracene -d12
Benzo [a] anthracene -d^
Benzo [a] anthracene -d12
Benzo [a] anthracene -d12
Polynuclear Aromatic Hydrocarbons (PAH)
Naphthalene
Acenaphthylene
Acenaphthene
Fluorene
129 (100)
152 (100)
154 (100)
166 (100)
129 (12)
151 (17)
153 (86)
165 (83)
127 (11)
153 (16)
152 (43)
167 (14)
0.46-0.52
0.70-0.76
0.73-0.79
0.81-0.87
0.010
0.010
0.010
0.010
Naphthalene - d8
Anthracene - d10
Anthracene - d10
Anthracene - di0

-------
                                                Table  4-2.   (eont.)

Compound
Phenanthrene
Fluoranthene
Pyrene
Chrysene
Characteristic Masses (m/z)
Primary
178 (100)
202 (100)
202 (100)
228 (100)
Secondary
179 (16)
101 (23)
101 (26)
226 (22)
Secondary
176 (18)
100 (14)
100 (17)
229 (22)
Surrogate Compounds
1, 2, 4-Trichlorobenzene-d3
Chrysene -d12
13C6-1, 2 ,4, 5-tetrachlorobenzene
13C6-hexachlorobenzene
13C6- 4 - chlorobiphenyl
13Ci2-3 , 3 ' , 4 , 4 ' -tetrachlorobiphenyl
13pi 9 9' •» •»» A A'*i 5' -
^"12 *»« » -5 / -S I*/* ->|3
octachlorobiphenyl
13C12-decachlorobiphenyl
Diethyl phthalate-3,4, 5,6-d4
Di-n-butyl phthalate-2,4, 5,6-d4
Butyl benzyl phthalate-3 , 4,5, 6-d4
183 (100)
240 (100)
222 (100)
292 (100)
194 (100)
304 (100)
442 (100)
510 (100)
153 (100)
153 (100)
153 (100)
185 (98)
238 (22)
220 (77)
292 (82)
196 (33)
302 (76)
440 (87)
512 (87)
181 (31)
154 (19)
171 (38)
187 (32)
241 (22)
224 (49)
288 (51)
--
306 (49)
444 (66)
508 (68)
154 (12)
108 (13)
283 (-)
Relative
Retention
Time(l)
0.97-1.02
1.16-1.22
1.20-1.25
1.40-1.46
Est. Limit
of Detection
<*s/«r>»
0.010
0.010
0.010
0.010
Internal
Quantitation
Stam4a*rd
Anthracene - d10
Anthracene - di0
Anthracene - d10
Benzo [a] anthracene -d12

0.36-0.60
1.40-1.46
0.55-0.80
0.91-1.00
0.63-0.86
0.90-1.30
1.40-1.55
1.61-1.67
0.82-0.87
1.08-1.14
1.33-1.38
0.010
0.010
0.010
0.010
0.010
0.010
0.020
0.050
0.010
0.010
0.010
--
Benzo [a] anthracene -d12
Naphthalene-dg
Naphthalene - dg
Anthracene - d10
Anthracene - d10
Benzo [a] anthracene-d12
Benzo [a] anthracene-d12
Anthracene - dj0
Anthracene - d10
Benzo [a] anthracene-d12
I
H

-------
                                                   Table 4-2.   (cent.)
Compound
Character is tic Masses (m/zj
Primary
Internal Standards
Naphthalene - d8
Anthracene - d10
Benzo [a] anthracene-d12
136 (100)
188 (100)
240 (100)
Secondary

137 (12)
189 (16)
238 (22)
Secondary

135 (11)
186 (17)
241 (22)
Relative
Retention
Tto»P>

0.46-0.52
1.00
1.40-1.67
Est. Limit
of Detection
<*sr/0)a
Internal
Quantitation
&tand&g4

0.010
0.010
0.010
Anthracene - d10
--
--
Relative retention times  (RRT) calculated versus the internal standard anthracene-d10 with chromatographic conditions as
specified in Section 12.1.  For napthalene-d10 and benzo [a] anthracene-d12 relative to anthracene-d10 are estimated to be
within the range of 0.36-0.60 and 1.40-1.65,  respectively.

Estimated detection level for 20 g sample assuming 100% recovery of  analyte.  The estimate detection level for the
chlorobenzenes and PCBs reflect the sensitivity for a single isomer.

Values in parentheses represent the relative  abundances of the characteristic masses.
    i
   H
   U)

-------
         The following criteria based on Table 4-2 must have been
met in order to make  a qualitative identification:


    •    The characteristic masses of each parameter of interest
         must maximize in the same scan or within one scan of
         each other.

    •    The retention time must fall within ±10 seconds of the
         retention time of the authentic compound.

    •    The relative peak heights of the three characteristic
         masses in the EICPs must fall within ±30% of the
         relative intensities of these masses in a reference mass
         spectrum.  The reference mass spectrum can be obtained
         from a standard analyzed in  the GC/MS system or from a
         reference library.

    •    The response for each of the characteristic ions must be
         at least 2.5 times the background signal-to-noise ratio.


4.1.4.2.   Quantitation.   Data  were quant it at ed on the  internal

standard method.   IQS were paired with  each analyte  for  quantita-

tion purposes; these  pairings  are displayed in Table 4-2.

Relative response factors (RRFs)  for  native  "quantitative"

semivolatile compounds were calculated  from the data obtained

during the  analysis of calibration solutions  using the following

formula :

                                 A   • c
                          RRF  =   STD
                                                             (4-1)
where Agm  =  The area of the primary quantitation ion for the
             analyte in question,
      AIS   =  The area of the primary quantitation ion for the
             labeled IQS paired with the given analyte,
      CSTD  =  Concentration (ng//iL) of the analyte,
 and  CIS   =  Concentration (ng//xL) of the IQS.


        Once the RRF values were obtained,  the lipid-adjusted

concentration of  a semivolatile  analyte within an adipose tissue

sample  (C^fe)  was calculated as follows:
                               4-14

-------
                 C
                 i-
                                 AIS ' RRF ' WAT - LC             (4-2)


where RRF was determined from the calibration,
             The area of the primary quant it at ion ion for the
             analyte in question within the sample,
     AIS =    The area of the primary quantitation ion for the
             labeled IQS paired with the analyte,
      QK =   The amount (total ng)  of the labeled IQS added to
             the sample prior to extraction,
      WAT  =   Weight (g)  of  the original adipose tissue sample,
 and  LC =   Percent extractable lipid from the sample.


4.1.4.3.  Recovery of Surrogate Standards.  Recoveries of the

labelled surrogate standards measured in the final extract were

calculated using the following formula:
                % Recovery  =  	—	 • 100%
                              Ais ' Qss ' RRFss                  (4-3)

where AIS and QIS are defined above,
      Ass =   Area  of the primary quantitation  ion determined for
             the surrogate standard,
      QSS =   Amount (ng)  of the  surrogate standard added to the
             sample prior to extraction,
and RRFSs =   RRF for the surrogate  standard relative to its IQS,
             as determined from  the initial calibration.


4.1.4.4.  Data Qualifiers.  Quantitative data were classified  to

indicate the intensity of the signal response.  For quantitative

compounds,  the qualifiers were defined as follows:


    •   Not  Detected  (ND):   S/N ratio  less  than 2.5.
    •   Trace  (TR):   S/N ratio  at  2.5  or above,  but less than
        10.
    •   Positive  Quantifiable  (PQ):   S/N ratio  at 10  or above.


The semivolatile compounds described as  "qualitative analytes"  in

the FY86 NHATS were not quantitated beyond a one-significant-


                              4-15

-------
figure estimate.  A  "positive detect"  (PD) was reported for
analytes that met the qualitative criteria.

4.1.4.5.  Estimating the Method Limit of Detection.  A method
limit of detection  (LOD) was estimated for a given sample in the
following situations for a  specific analyte:

     •    no  response was noted for the  analyte;
     •    a response  was  noted but  the  ion ratios  were incorrect;
     •    a response  was  noted but  was below the calibration
         range;  or
     •    the reported response was quantitated as a  trace value.

         If  no response  was  noted,  the  LOD was reported  as the
lower end of the established calibration range.   The LOD value
was reported as total ng/injection such that the LOD could be
extrapolated for each individual sample.
         For samples for which a response at  the  compound's
retention time was noted but the qualitative criteria for ion
ratios were outside  an acceptable range, the estimated LOD was
calculated as the response  of the interference,  and the
concentration value  was regarded as not detected  (ND).
         If  a response was noted at  the  correct retention time
and met the qualitative criteria of ion ratio agreement for
identification, but  the calculated response was below the
calibration curve, then the value was identified as not detected.
         If  a response was qualified as  a trace value, then the
analyst also provided an estimated LOD.  This was accomplished by
using the observed signal-to-noise ratio on either side of the
response or the lower calibration limit, whichever was higher.
                               4-16

-------
4.2.  OA/QC FOR CHEMICAL ANALYSIS

4.2.1.  Demonstrating Achievement of Instrument Performance
        Requirements
        Achievement of  the instrument  performance  requirements
were demonstrated in the following stages:

         (1)   HRGC  Column  Performance    A 30-m HRGC column,  DB-5,
film thickness = 0.2 pun, was used for analysis of all samples  and
standards for the 6% fraction extracts, and a 30-m DB-1301, film
thickness = 0.2 pirn, was used for all 50% fraction extracts.  The
column performance was initially demonstrated using a Grob
hydrocarbon mixture.  The retention times should be within ±30%
of the values supplied by the manufacturer with the column when
chromatographed under similar conditions.  If during the course
of the analysis it became necessary to install a new column, this
column was verified in a similar manner.

         (2)   Tuning and Mass Calibration.  The mass spectrometer
was tuned at least daily to yield optimum sensitivity using
decafluorotripheylphosphine (DFTTP).   The criteria that must be
met are listed in Table 4-3.  Corrective actions were implemented
whenever the resolving power did not meet the requirement.
Examples of these corrective actions are recalibrating the mass
spectrometer,  changing the GC column,  or maintenance of the
instrument. - Corrective actions were determined by consultation
between the analyst, the work assignment leader(s), and the mass
spectrometry facility staff.

         (3)   RRF Check and  Instrument Sensitivity  Check.  As
part of the initial and routine instrument performance checks, a
single calibration standard was analyzed and RRF values of the
respective analytes were compared to specific internal standards.
The initial and routine calibration criteria require that the
                               4-17

-------
       Table 4-3.   DFTTP Key Masses  and Abundance Criteria*1*
Mass
51
68
69
70
127
198
199
275
441
442
443
Intensity Required
8%-82% of mass 198
<2% of mass 69
11%-91% of mass 198
<2% of mass 69
32%-59% of mass 198
base peak, 100% abundance
4%-9% of mass 198
11%-30% of mass 198
44%-110% of mass 443
30%-86% of mass 198
14%-24% of mass 442
^  EPA Method 1625 Revision B:   Semivolatile Organic Compounds by Isotope
Dilution GC/MS, January 1985.
                                  4-18

-------
precision of the RRF measurements are ±30% for the target
analytes.
        Sensitivity of  the  MS  was documented  through  the
responses noted for the first calibration standard of each
analysis day.  The method requires that a low level standard be
analyzed to document sufficient instrumental response to support
instrumental detection limits.
        Routine checks  on the  instrumental sensitivity were
achieved by monitoring the response for the IQS from injection to
injection and documenting the responses in the MS log book.  If
the response for the IQS was noted to drop by greater than 50% of
the response noted in the previous calibration standard,  the
analyst verified instrumental performance through the analysis of
an additional calibration standard.
        The  qualitative analytes in the FY86 NHATS were
identified by relative retention times and characteristic mass
peaks.  These met the same qualitative identification factors as
the quantitative targets but were not quantitated beyond a one-
significant-figure estimate.  The RRFs for the compounds were not
a required factor in the initial calibration and daily
performance checks.  A "positive detect"  (PD)  was reported for
analytes that met the qualitative criteria in Section 4.1.4.

4.2.2.  Calibration for Quantitative Semivolatile Analysis

4.2.2.1.  Initial Calibration.   Initial calibration was required
before any samples were analyzed,  or when any routine calibration
did not meet the required criteria for the consistency of RRFs
(±30% for quantitative targets  and internal standards).   An
initial calibration was conducted by performing the following
steps:

     (1) Tuning and calibrating  the instrument with PFK and
        DFTTP.
                               4-19

-------
Table 4-4.  Calibration Solutions for the 6% Florieil Fraction
Compound
Lindane (-y-BHC)
Mirex
Chlordane
Oxychlordane
Aldrin
or-BHC
A-BHC
/3-BHC
Heptachlor epoxide
Heptachlor
p,p'-DDT
o,p' -DDT
p,p' -DDE
o,p' -DDE
o,p' -ODD
p,p'-DDD
t-Nonachlor
1 , 3 -Dichlorobenzene
1 , 4 -Dichlorobenzene
1 , 2 -Dichlorobenzene
1,2, 4-Trichlorobenzene
1,2, 3 -Trichlorobenzene
1,3, 5 -Trichlorobenzene
1,2, 3,4-Tetrachlorobenzene
1,2,3, 5-Tetrachlorobenzene
1,2,4, 5-Tetrachlorobenzene
Pentachlorobenzene
Hexachlorobenzene
Naphthalene
Phenanthrene
Approximate Concentration {ncf/fiL)
in Calibration solutions
CS1
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100

100
100
100
100
100
100
100
100
100
100
100
100
100
100
CS2
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50

50
50
50
50
50
50
50
50
50
50
50
50
50
50
CS3
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10

10
10
10
10
10
10
10
10
10
10
10
10
10
10
CS4
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5

5
5
5
5
5
5
5
5
5
5
5
5
5
5
CSS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

1
1
1
1
1
1
. 1
1
1
1
1
1
1
1
                            4-20

-------
Table 4-4.   (cont.)
Compound
Fluoranthene
Chrysene
Benzo [a] pyrene
Acenaphthylene
Acenaphthene
Fluorene
Pyrene
Biphenyl
1 , 2 -Dibromo- 3 - chloropropane
Hexachlorobutadiene (HCBD)
Hexachlorocyclopentadiene
Octachlorostyrene
Tetrabromobiphenyl
o-Cymene
m-Cymene
p-Cymene
D-Limonene
D, L- Isoborneol
l-Indanone
2 - Inadanone
Butylated hydroxytoluene
Coumarin
Octamethylcyclotetrasiloxane
'*'' '
Approximate Concentration (»g/#L)
in Calibration solutions
CS1 [ CS2
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50,
50
50
50
50
50
50
CS3
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
CS4
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
" 5
5
5
CSS
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
       4-21

-------
     (2)  Analyzing the five concentration calibration solutions
         for the 6% fracton eluates listed in Table 4-4.   The low
         concentration solution,  CS5,  was used to demonstrate the
         lower limit of detection provided by the available
         instrument.

     (3)  Computing the RRFs for each analyte in the concentration
         calibration solution using the criteria for positive
         identification of semivolatile analytes and the
         computational methods given in Section 4.1.4.

     (4)  Computing the means and their respective relative
         standard deviations (RSD,  expressed as a percentage)  for
         the RRFs for each analyte in the standard.  The  RSD was
         calculated as the standard deviation to all measurements
         of a particular RRF value divided by the average RRF
         value and multiplied by 100%.  These samples were
         identified in the individual batch reports.

     (5)  Repeating the above process for the 50% Florisil
         fraction eluates (Table 4-5)  and PCB calibration
         solution (Table 4-6).

         The above fractionation was based on the previous broad

scan analysis of  adipose  tissue.   In  the  case  of quantitative

analytes not previously determined, comparisons  to similar

compounds  have  been made  for the purpose  of  determining  in which

Florisil fraction the  analyte was  most  likely  to appear.

         To declare an acceptable initial calibration,  the RSD

for the response  factors  for the analysis of analytes across the

calibration range must have been less than  ±30%.   If this

criterion  held, then the  RRF was assumed  to  be nonvariant and  the

average RRF could be used for calculating a  RSD value.  Alter-

natively,  the results  were used to plot a calibration curve of

response ratios,  A3/AiS versus RRF.

         An acceptable initial calibration also required  the

traces for all  ions used  for quantitation to present a signal-to-

noise  (S/N) ratio of at least 2.5.  This  included  analytes and

isotopically labeled standards.  Isotopic ratios must have been

within ±30% of  the  theoretical values.
                               4-22

-------
Table 4-5.  Calibration Solutions  for  the 50% Florisil Fraction
compound
Dimethyl phthalate
Dibutyl phthalate
Butylbenzyl phthalate
Di-n-octyl phthalate
Diethyl phthalate
Di-n-butyl phthalate
Tributyl phthalate
Diethylhexylphthalate (DEHP)
Tributylphosphate
Triphenylphosphate
Tris (2 -chloroethyl) phosphate
Tributoxyethyl phosphate
Tritolylphosphate
Tris (dichloropropyl) phosphate
Dieldrin
Endrin
Endrin ketone
Tris (2 , 3-dibromopropyl) -
phosphate
2 - Phenylphenol
Trichloro-o-terphenyl
Tetrachloro-o-terphenyl
4-Chloro-o-terphenyl
Pentachlorodiphenyl ether
2 -Methoxy- 3 -methylpyrazine
Ethyl hydrocinnamate
:-:
Approximate Concentration, (ng//tl»j
i& Calibration Solutions
CS1
100
100
100
100
100
100
100
100
500
200
500
200
200
500
500
500
500
500
100
200
200
200
200
200
200
CS2
50
50
50
50
50
50
50
50
250
100
250
100
100
250
250
250
250
250
50
100
100
100
100
100
100
CS3
10
10
10
10
10
10
10
10
50
20
50
20
20
50
50
50
50
50
10
20
20
20
20
20
20
CS4
5
5
5
5
5
5
5
5
25
10
25
10
10
25
25
25
25
25
5
10
10
10
10
10
10
CSS
1
1
1
1
1
1
1
1
5
2
5
2
2
5
5
5
5
5
1
2
2
2
2
2
2
                             4-23

-------
Table 4-6.  Calibration Solutions for PCB Analysis
Compound
Monochlorobiphenyl
Dichlorobiphenyl
Trichlorobiphenyl
Tetrachlorobiphenyl
Pentachlorobiphenyl
Hexachl or ob ipheny 1
Heptachlorobiphenyl
Octachlorobiphenyl
Nonachlorobiphenyl
Decachlorobiphenyl
'•;• • '
Approximate concentration {ng/^L}
in calibration solutions
C83,
100
100
100
100
200
200
200
200
200
500
CS2
50
50
50
50
100
100
100
100 .
100
250
c&a
10
10
10
10
20
20
20
20
20
50
GS4
5
5
5
5
10
10
10
10
10
25
CSS
1
1
1
1
2
2
2
2
2
5
                       4-24

-------
4.2.2.2.  Routine Calibrations.  Routine calibrations were
performed at the beginning of every day before actual sample
analyses were performed and as the last injection of every day.
Routine calibrations involved the following steps:
    (1) Injecting 2 /zL of  the concentration calibration
        solutions CSS for  the 6%  fraction as the initial
        calibration check  on each analysis day and as the  final
        check on each analysis day.
    (2) Computing the RRFs for each analyte in the concentration
        calibration solution using the criteria for positive
        identification of  semivolatiles given in Section 4.1.4.

        To declare an acceptable  routine calibration, the
measured RRF for all analytes must have been within ±30% of the
mean values established by initial calibration of the calibration
concentraton solutions.   Also,  isotopic ratios must have been
within ±30% of the theoretical value for each analyte and isoto-
pically labeled standard.

4.2.3.  Spiking Solution Preparation

4.2.3.1.  Native Standard Spiking Solution.   A native standard
spiking solution was prepared in dichloromethane from the
individual stock standards.  This solution was used for preparing
laboratory spikes of adipose tissue.   For example,  if the
anticipated spike level is 0.10 /ig/g in a 20-g sample,  the target
analyte should be added to the spiking solution to achieve a
final  concentration of 10 /ig/mL.   The specific PCB isomers used
for preparing calibration solutions were also included in the
target spiking solution.   The spiking solution and proposed
levels are listed in Table 4-7.

4.2.3.2.  Surrogate Standard Spiking Solution.  A mixed surrogate
standard spike solution was prepared in dichloromethane from the
individual stock standards.  The surrogate standard spike

                              4-25

-------
Table 4-7.   Proposed QC Spiking Solutions
cot^oxmd
P_,E' -DDE
E,E'-DDT
Dieldrin
Heptachlor epoxide
£-Nonachlor
Mi rex
y-Chlordane
Hexachlorobenzene
1,2,4, 5-Tetrachlorobenzene
2. , 4 -Dichlorobenzene
1 , 2 , 4-Trichlorobenzene
Diethyl phthalate
Butylbenzyl phthalate
Triphenyl phosphate
Tris (dichloroethyl) phosphate
Benzo [a] pyrene
Phenanthrene
Chrysene
Hexachloro- 1 , 3 -butadiene
R-Limonene
2-Phenyl phenol
Coumarin
o-Cymene
2 - Indanone
DL- Isoborneol
Ethyl hydrocinnamate
Octamethylcyclotetrasiloxane
Monochlorobiphenyl
Dichlorobiphenyl
Trichlorobiphenyl
Approximate
Spike Solution
coae i»0/£&J
29.5
28.4
21.9
14.3
21.9
21.7
22.3
19.5
28.8
124
20.7
23.0
22.6
19.2
372
24.1
23.6
5.07
19.6
23.4
20.7
25.2
28.0
17.3
26.7
32.7
21.1
25.3
27.9
24.6
Ftnal spike volume
few
$1
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
200
S2
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
                 4-26

-------
                              Table  4-7.   (cont.)
cotapoxmd.
Tetrachlorobiphenyl
Pentachlorobiphenyl
Hexachlorobiphenyl
Heptachlorobiphenyl
Octachlorobiphenyl
Nonachlorobiphenyl
Decachlorobiphenyl
Approximate
Spike Solution
Cone {ng/nii}
56.2
65.0
52.6
130
137
154
96.1
Final Spike Volume
&&>»
S3,
200
200
200
200
200
200
200
S2
50
50
50
50
50
50
50
W  Final spike level is based on ng of analyte/g of adipose (20 g sample).
The actual  reported value would be based on ng of analyte/g of extractable
lipid.

W  From EPA Method 680 list except for the nonachlorbiphenyl which is not
included in Method 680.
                                    4-27

-------
solution were prepared  to  deliver the surrogates at the amounts
specified in Table  4-8  in  a  200-/zL volume.  This requires that
the stock solution  contain the surrogates at concentrations
ranging from 10  to  50 /ig/mL.

4.2.3.3.  Internal  Standard  Spiking Solution.  The internal
standard spiking stock  solution concentrations are also listed in
Table 4-8 for each  of the  deuterated internal standards.

4.2.3.4.  Performance Audit  Solutions.  Included among the
samples in  at least two sample batches was a solution provided by
the quality control coordinator containing known amounts of
specific target  analytes representing each major compound class
to be determined.   The  accuracy of measurements for performance
evaluation  samples  was  in  the range of 70-130%.

4.2.4.  QC  Samples
         Samples included for QC  purposes  within each batch  of
composite samples are summarized in Table 4-9.  The order of
preparation and  analysis with respect to the FY86 NHATS compos-
ites was specified  in the  sample design.  This section discusses
each of these QC sample types.  Discussion of the findings and
conclusions from QC sample analyses are presented in Section 5.3.

4.2.4.1.  Method Blanks.   One method blank was generated within
each batch  of samples.   A  method blank was generated by perform-
ing all steps detailed  in  the analytical procedure using all
reagents, standards, equipment, apparatus, glassware,  and
solvents that were  used for  a sample analysis, but not adding any
adipose tissue.  The method  blank contained the same amounts of
labeled surrogate standards  that were added to samples before
bulk lipid  cleanup.
        Protocol dictated  that if the levels  detected  in the
method blank were greater  than 10% of the levels seen in the
                               4-28

-------
        Table 4-8.  Spike Levels for Surrogate and Internal Standards*1*
Analybe
•: • -• • .....-.-.
Spike Levels (Msf}^
Surrogate Compounds
1, 2, 4-Trichlorobenzene-dg
Chrysene-d^
13C6-1, 2,4, 5-Tetrachlorobenzene
13C6-Hexachlorobenzene
13Cg- 4 - Chlorobiphenyl
13C12-3 , 3 ' , 4 , 4 ' -Tetrachlorobiphenyl
13C12-2 , 2' ,3,3' ,5,5' ,6,6' -Octachlorobiphenyl
l3Ci2-Decachlorobiphenyl
Diethyl phthalate-3,4, 5,6-d4(3)
Di-n-butyl phthalate-3,4,5,6-d4(3)
Lindane 13C6/d^
Heptachlor 13C
3.428
2.808
2.470
1.932
2.222
4.016
6.852
12.20
2.252
1.800
1.672
2.030
Internal Standards
Napht hal ene - d8
Anthracene-d10
Benzo [a] anthracene-d12
1.901
1.910
2.102
^  Refer to EPA Method  1625, Revision B--Semivolatile Organic Compounds by
Isotope Dilution GC/MS,  Federal Register 1984, 49 (209), pp. 184-197.

®  Concentration calculated  for a  solution of 200-piL final  volume.

(3)  were not reported  in most samples.
                                     4-29

-------
 Table  4-9.
Quality Control Samples Included in the PY86 NHATS
Analytical  Procedure
Type
Method blank
Spiked control adipose
tissue sample
Unspiked control
adipose tissue sample
Frequency
One per batch
Two per batch (two
different spike levels)
One per batch
!#pUc^!£af ..-.,
Assess laboratory
background
contribution.
Evaluate method
performance (accuracy
and precision)
Evaluate method
performance (accuracy
and precision)
tissue samples, then the solvents, reagents, spiking solutions,
apparatus, and glassware were checked to locate and eliminate the
source of contamination before any further samples were extracted
and analyzed.

4.2.4.2.  Control Samples.  Control samples were prepared from a
bulk sample of approximately 2 kg of human adipose tissue.  This
material was prepared by blending the tissue with methylene
chloride, drying the extract by eluting through anhydrous sodium
sulfate, and removing the methylene chloride using rotoevapora-
tion at elevated temperatures  (80°C).  The evaporation process
was extended to ensure all traces of the extraction solvent have
been removed.  The resulting oily matrix (lipid) was subdivided
into 20-g aliquots which were analyzed with each sample batch.

4.2.4.3.  Spiked Control Samples.  Spiked lipid samples were
prepared by using a portion of the homogenized lipid.  Sufficient
spiked lipid matrix was prepared to provide a minimum of two
spiked samples per sample batch:  one sample spiked at a low
concentration and one at a high concentration.  Method
performance was addressed in this study by calculating recoveries
for each spiked sample as follows:
                               4-30

-------
 Recovery(%) = conc- (spiked sample)  - cone, (control sample)  ^
                               Spike level                  (4_4)
This method to calculating percent recovery leads to a test of
ruggedness of the method with respect to detecting finite
differences in concentration.  Note that an equally-accepted
approach to calculating percent recovery is given by the formula
    Recovery^)  =  	 cone, (spiked sample)    	 „ 1Q(J%
                    conc. (control sample)  + spike level       (4-5)
Formula (4-5)  can lead to larger percentages than formula (4-4)
applied in this study.  This fact should be considered when
interpreting observed recovery percentages in this study.
        Analytical  results  of the QC samples are statistically
summarized in Chapter 5.  This chapter also presents conclusions
and issues resulting from the QC sample analysis.

4.3  OVERALL DATA QUALITY
        At the outset of  the analysis effort for the FY86 NHATS,
specific data quality objectives were defined for the quantita-
tive and qualitative analyses of the target semivolatile com-
pounds.  Data quality objectives were established for calibration
criteria (relative response factors [RRPs])  for each analyte and
internal standard, internal standard response area, and method
performance based on the recoveries of labeled surrogate com-
pounds and native compounds spiked into a spiked internal QC
sample.  The data generated with respect to these criteria are
presented within this report.  Further details were provided in
the original data reports.
        Table  4-10  summarizes the performance  achieved versus
the specific criteria and data quality objectives for the
analysis of the FY86 NHATS composites.
                               4-31

-------
Table 4-10.
Data Quality Objectives for the FY86 NHATS,
Along With Actual  Performance
Criteria
RRF calibration
Labeled surrogate stan-
dards
Spiked internal QC sam-
ples
Internal standard re-
sponse areas
Objective ;
±30% all quantitative
analytes
40%-160%
50%-150%
50%-150% of initial
daily calibration stan-
dard
Actual Performance
>90% of all RRF factors
within DDQs .
>84% for all labeled
surrogate spikes; 12%
of the deviation due to
50% fraction
surrogates .
70% of all measurements
within criteria; 22% of
all deviations due to
50% fraction compounds.
>90% of all
measurements within
criteria.
                          4-32

-------
5.0  DATA ISSUES
          The NHATS FY86 sampling effort resulted in a total of
50 composites of adipose tissue specimens for chemical analysis
(see Chapter 3).  In the analytic laboratory, these 50 composites
were partitioned into five groups, or batches, of ten composites
each.  Each batch also included the following four laboratory QC
samples:

     •    One method blank
     •    Three samples prepared from a homogeneous bulk lipid
          extract; two of these samples spiked at differing
          levels by selected native compounds.

Thus, the NHATS FY86 chemical analysis was performed on five
batches each containing fourteen analytical samples,  for a total
of 70 analytical samples.  Samples within a batch were chemically
analyzed as a group under similar laboratory conditions.
          Prior to chemical analysis,  all non-blank analytical
samples were spiked with a set of twelve surrogate compounds.
These labelled compounds do not exist in the natural environment
and were selected to represent the native compounds of interest.
Analysis of surrogate recovery data was performed to evaluate
method performance and overall recovery levels.
          This chapter addresses a series of preliminary data
issues which include a summary of the composite data and
statistical analysis on the QC data.  The information gathered
from this preliminary data investigation was essential for the
statistical analysis and interpretation of sample results.  The
objectives of the preliminary data analysis included the
following:

     •    Identify those compounds having a sufficiently large
          percentage of composite samples with detected results.
          Results for these compounds will likely reflect more
          accurate estimates of average concentration levels and
          variability.

                               5-1

-------
          Identify the extent that systematic errors in measured
          concentrations are present over time by considering
          surrogate recovery data.  If necessary, adjust the
          measured concentrations for these errors.

          Characterize method performance through analysis of QC
          sample data, identifying sources of variability and the
          extent of batch effects in the  (adjusted) measured
          concentrations.
Each of these efforts  is documented in separate subsections which
follow.


5.1  DETERMINING NATIVE COMPOUNDS TO INCLUDE IN STATISTICAL
     ANALYSIS

          A total of 111 semivolatile compounds were considered

in the FY86 NHATS.  These compounds fall into several chemical

classes:


               Pesticides  (19 compounds)
               Chlorobenzenes  (11 compounds)
               Phthalate esters  (5 compounds)
               Phosphate triesters  (5 compounds)
               PAHs  (9 compounds)
               PCBs  (10 compounds)
               Other quantitative compounds  (19 compounds)
               Qualitative pesticides  (9 compounds)
               Qualitative chlorinated aromatics  (9 compounds)
               Qualitative PAHs  (4 compounds)
               Other qualitative compounds  (11 compounds)

                                                     %
Section 5.1.1 identifies the compounds analyzed within each

chemical class and the detection percentages for each compound as

observed within the NHATS FY86 composite samples.  Statistical

analysis was performed only on compounds with sufficiently high

detection percentages.  Section  5.1.2 discusses unique data

reporting for two pesticides which have been historically

prevalent in the NHATS program.
                               5-2

-------
5.1.1  Detection Status of the Semivolatilea
          When reporting a measured concentration for a given
semivolatile compound in a laboratory sample, the NHATS FY86
analytical method determined whether the compound was
successfully detected in the sample.  For quantitative compounds,
the method classified each result into one of three possible data
qualifier categories, indicating the intensity of the signal
response:

     •    Not detected -- Result is less than 2.5 times the
          signal-to-noise ratio.
     •    Trace -- Result is between 2.5 and 10 times the signal-
          to-noise ratio.
     •    Positive quantifiable -- Result is greater than 10
          times the signal-to-noise ratio.

If a result was categorized as trace or positive quantifiable,
the compound was considered detected in the sample.   For
qualitative compounds, only detected and not detected results
were reported.
          Estimated method detection limits were reported when
not detected or trace results occurred for a sample.  When a
compound was not detected in a sample,  it was assumed that the
sample's true compound concentration was at some level below the
detection limit.  For the statistical analysis, one half of the
detection limit was used as the estimated concentration level for
not detected samples.
          Table 5-1 reports the percentage of FY86 composite
samples occurring in each of the data qualifier categories for
the 111 semivolatile compounds.  The percent of composite samples
with detected results are also reported.
          Of the 111 compounds, 23 were detected in at least 50%
of the 50 composite samples, and one compound nearly met the 50%
threshold (octachlorobiphenyl, detected in 44% of the samples).
These 24 compounds are identified as target compounds for

                               5-3

-------
Table 5-1.
Percent of NHATS FY86 Composite Samples in Each
Detection Level Category
Compound Number
and Name

*

*
*



*




*
*
*



*



1
2
3
3
4
5
6
7
8
9
10
11
12
13
14
15
16
60
60
61
62

P,P-DDT
O,P-DDT
P,P-DDE (M/Z=288)
P,P-DDE (M/Z=316)
O,P-DDE
O,P-DDD
ALPHA- BHC
BETA-BHC
DELTA- BHC
GAMMA-BHC (LINDANE)
ALDRIN
HEPTACHLOR
HEPTACHLOR EPOXIDE
OXYCHLORDANE
TRANS - NONACHLOR
GAMMA- CHLORDANE
MIREX
DIELDRIN
DIELDRIN (CORRECTED)
ENDRIN
ENDRIN KETONE
CAS %
Number Detected
PESTICIDES
50-29-3
789-02-6
72-55-9
72-55-9
3424-82-6
53-19-0
319-84-6
319-85-7
319-86-8
58-89-9
309-00-2
76-44-8
1024-57-3
26880-48-8
39765-80-5
57-74-9
2385-85-5
60-57-1
60-57-1
7221-93-4


96
0
100
100
0
0
0
92
0
4
0
0
94
78
92
0
32
12
62
0
2
% Not %
Detected Trace

4
100
0
0
100
100
100
8
100
96
100
100
6
22
8
100
68
88
38
100
98

0
0
0
0
0
0
0
2
0
0
0
0
0
2
0
0
2
0
22
0
2
% Pos.
Quant.

96
0
100
100
0
0
0
90
0
4
0
0
94
76
92
0
30
12
40
0
0
CHLOROBENZBNHS

*








*

+








17
18
19
20
21
22
23
24
25
26
27

41
42
43
44
45
46
47
48
49
1 , 3 -DICHLOROBENZENE
1 , 4 -DICHLOROBENZENE
1 , 2 -DICHLOROBENZENE
1,2, 3 -TRICHLOROBENZENE
1,2, 4 -TRICHLOROBENZENE
1,3, 5 -TRICHLOROBENZENE-
1,2,3, 4 -TETRACHLOROBENZENE
1,2,3,5- TETRACHLOROBENZENE
1,2,4, 5 -TETRACHLOROBENZENE
PENTACHLOROBENZENE
HEXACHLOROBENZENE

NAPHTHALENE
ACENAPHTHALENE
ACENAPHTHENE
FLUORENE
PHENANTHRENE
FLUORANTHENE
PYRENE
CHRYSENE
BENZO (A) PYRENE
541-73-1
106-46-7
95-50-1
87-61-6
120-82-1
108-70-3
634-66-2
634-90-2
95-44-3
608-93-5
118-74-1
PAHs
91-20-3
208-96-8
83-32-9
86-73-7
85-01-8
206-44-0
129-00-0
218-01-9
50-32-8
0
86
0
0
0
0
0
0
0
0
98

84
0
0
0
8
2
0
4
0
100
14
100
100
100
100
100
100
100
100
2

16
100
100
100
92
98
100
96
100
0
0
0
0
0
0
0
0
0
0
4

8
0
0
0
8
2
0
0
0
0
86
0
0
0
0
0
0
0
0
94

76
0
0
0
0
0
0
4
0
                            5-4

-------
                          Table 5-1.   (cont.)
 Compound Number
    and Name
  CAS        %      % Not     %    % Pos.
Number    Detected Detected  Trace  Quant.
                                  PCBs
   50  MONOCHLOROBIPHENYL
   51  DICHLOROBIPHENYL
   52  TRICHLOROBIPHENYL
*  53  TETRACHLOROBIPHENYL
*  54  PENTACHLOROBIPHENYL
*  55  HEXACHLOROBIPHENYL
*  56  HEPTACHLOROBIPHENYL
*  57  OCTACHLOROBIPHENYL
   58  NONACHLOROBIPHENYL
   59  DECACHLOROBIPHENYL
63  DIMETHYL PHTHALATE
64  DIETHYL PHTHALATE
65  Dl-N-BUTYL PHTHALATE
66  BUTYL BENZYL PHTHALATE
67  BIS (2-ETHYLHBXYL)
       PHTHALATE
68  TRIBUTYL PHOSPHATE
69  TRIS (2-CHLOROETHYL)
       PHOSPHATE
70  TRIS (2,3-DIBROMOPROPYL)
       PHOSPHATE
71  TRIPHENYL PHOSPHATE
72  TRITOLYL PHOSPHATE
28  BIPHENYL
29  1.2-DIBROMO-3-CHLORO
       PROPANE
30  HEXACHLORO BUTADIENE
31  HEXACHLORO CYCLOPENTADIENE
32  2,2',4',5-TETRABROMO
       BIPHENYL
33  O-CYMENE
34  D-LIMONENE
35  D,L-ISOBORNEOL
36  1-INDANONE
37  2-INDANONE
38  BUTYLATED HYDROXYTOLUENE
39  COUMARIN
40  OCTAMETHYL-
       CYCLOTETRASILOXANE
73  ETHYL HYDROCINNAMATE
74  2-METHOXY-3-METHYLPYRAZINE
2732-18-8
25512-42-9
25323-68-6
26914-33-0
25429-29-2
26601-64-9
28655-71-2
31472-83-0
53742-07-7
2051-24-3
PHTHALATB ESTERS
131-11-3
84-66-2
84-74-2
85-68-7
177-81-7
PHOSPHATE TRIBSTERS
126-73-8
115-96-8
ti)
126-72-7
115-86-6
1330-78-5
OTHER
92-52-4
96-12-8
87-68-3
IENE 77-47-4

527-84-4
5898-27-5
124-76-5
83-33-0
615-13-4
HE 128-37-0
91-64-5
556-67-2
2021-28-5
ZINE 2847-30-5
0
0
30
66
88
94
86
44
26
28

0
10
76
72
78

0
0
0
4
2

0
0
0
0
0
80
96
0
0
0
18
0
72
2
0
                                                      100
                                                      100
                                                       70
                                                       34
                                                       12
                                                        6
                                                       14
                                                       56
                                                       74
                                                       72
                    100
                     90
                     24
                     28

                     22
                    100

                    100

                    100
                     96
                     98
                    100

                    100
                    100
                    100

                    100
                     20
                      4
                    100
                    100
                    100
                     82
                    100

                     28
                     98
                    100
                              0
                              0
                              2
                              0
                              0
                              0
                              0
                              0
                              0
                              0
0
2
6
4
0

0

0
0
2
0
0
0

0
4
2
0
0
0
4
0

4
2
0
         0
         0
        28
        66
        88
        94
        86
        44
        26
        28
                                                                           0
                                                                           8
                                                                          70
                                                                          68

                                                                          78
                                                                           0

                                                                           0

                                                                           0
                                                                           4
                                                                           0
                                                                           0
                                                                           0
                                                                           0

                                                                           0
                                                                          76
                                                                          94
                                                                           0
                                                                           0
                                                                           0
                                                                          14
                                                                           0

                                                                          68
                                                                           0
                                                                           0
                                  5-5

-------
Table 5-1.   (cont.)
Compound Number
and Name
CAS % % Not %
Number Detected Detected Trace
% Pos.
Quant.
OTHER (cont.)
75

76
77
78
2 , 2 ' , 4 , 4 ' , 5-PENTACHLORO
DIPHENYL ETHER
4 - CHLORO - P - TERPHENYL
TRI CHLORO - P - TERPHENYL
2-PHENYL PHENOL




90-43-7
PESTICIDES (QUALITATIVE)
85
86
98
99
100
101
102
106
107
ISOPHORONE
DICHLOROVOS
CHLORPYRIFOS
ISOPROPALIN
BUTACHLOR
NITROFEN
PERTHANE
DICOFOL
P . P ' -METHOXYCHLOR
78-59-1
62-73-7
2921-88-2
33820-53-0
23184-66-9
1836-75-5
72-56-0
115-32-2
72-43-5

0
0
0
24
(a)
16
2
28
10
12
8
0
6
0
CHLORINATED AROMATICS (QUALITATIVE)
88
89
90
91
92
95
96
97
110

105
108
109
111

* 79
80
* 81
* 82
83
84
87
93
94
2,4, 6 -TRICHLOROANISOLE
2,4,6 -TRICHLOROPHENOL
2,4, 5 -TRICHLOROPHENOL
2,3, 6 -TRICHLOROANISOLE
2,3, 6 -TRICHLOROPHENOL
PENTACHLOROANI SOLE
PENTACHLORONITROBENZENE
2 , 3 , 4 -TRICHLOROANISOLE
OCTACHLORONAPHTHALENE
PAHS
BENZO (A) ANTHRACENE
BENZO (B) FLUORANTHENE
BENZO (K) FLUORANTHENE
DIBENZO (A,H) ANTHRACENE
OTHER
1-NONENE
CUMENE
1,2, 4 -TRIMETHYLBENZENE
HEXYL ACETATE
1 , 3 - DIETHYLBENZENE
1 , 4 -DIETHYLBENZENE
QUINOLINE
DIBENZOFURAN
CHLORDANE
87-40-1
88-06-2
95-95-4
50375-10-5
933-75-5

82-68-8
54135-80-7
2234-13-1
(QUALITATIVE) (a)
56-55-3

207-08-9
53-70-3
(QUALITATIVE) (a)
124-11-8
98-82-8
95-63-6
142-92-7
141-93-5
105-05-5
91-22-5
132-64-9

0
0
0
0
0
2
0
4
2

26
10
4
0

50
34
62
82
8
0
8
0
2

100 0
100 0
100 0
76 2

84
98
72
90
88
92
100
94
100
(a)
100
100
100
100
100
98
100
96
98

74
90
96
100

50
66
38
18
92
100
92
100
98

0
0
0
22

_
_

-
-
_


-

_
-
-
-
-
-
-
-
-

_
-
-
-

_
-
-
-
-
-
-
-
-
       5-6

-------
                              Table  5-1.   (cont.)
    Compound Number                    CAS         %      % Not      %    % Pos.
       and Name                      Number   Detected Detected  Trace  Quant.


                         OTHER (QUALITATIVE)   (cont.)

  103  CHLOROBENZYLATE               510-15-6      0     100
  104  BIS  (2-ETHYLHEXYL) ADIPATE    103-23-1     10      90       -


*  Detected in at least 44% of the FY86 composite samples.

W Qualitative compounds were only monitored for detection versus non-detection.
                                      5-7

-------
statistical  analysis  and are  noted with  asterisks in Table 5-1.
Statistical  analysis  of  QC  and composite data was restricted to
these target compounds.   For  the  other 87 compounds, each having
no more  than a  34%  detection  rate, results were summarized
through  descriptive statistics only.

5.1.2  Data  Reporting Unique  to Dieldrin and p.p-DDE
           For two pesticides  analyzed in the NHATS FY86 program,
two  sets of  measured  concentrations were obtained from different
protocols.   The two sets of results for  these compounds, dieldrin
and  p,p-DDE,  were each treated as two distinct entities in data
analysis.  The  procedures unique  to these compounds to obtain
measured concentrations  are discussed in this subsection.
           According to Table  5-1, dieldrin had only a 12%
detection rate  among  the FY86 composite  samples.  In Batches 1,
3, 4, and 5,  the reported concentration  levels for 29 samples
(including 4 QC samples)  were below the  lowest calibration
standard.  According  to  the QAPP  for laboratory analysis  (MRI,
1988b),  if the  calculated laboratory response was below the range
of calibration  standards while satisfying criteria for retention
time and ion ratio  agreement,, the value  was to be identified as a
"not detected"  result.   While this approach was followed for the
initial  set  of  reported  dieldrin  results, the HRGC/MS results
indicated that  dieldrin  was indeed present in some samples whose
measured concentrations  were  below the calibration standards.
Thus the data qualifier  classification of dieldrin data was
redetermined to reflect  the signal-to-noise ratio that would have
been applied if the data were above the  lowest calibration
standard.  The  quantifiable concentrations for these samples were
recalculated using  the signal-to-noise ratio to define the
detection  limit.  This second classification of the dieldrin data
resulted in  a 62% detection rate  among the composite samples,
classifying  dieldrin  as  a target  compound for statistical
analysis.  Thus statistical analysis for dieldrin was performed
only on  the  recalculated results.
                                5-8

-------
          Historically, the compound p,p-DDE has been detected in
a majority of NHATS samples.  However, in the FY86 analysis, the
primary quantitation ion used to calculate the p,p-DDE
concentrations (m/z=288) was saturated at the mass spectrometry
detector.  It is expected that using an ion for quantitation at
or near saturation would result in an underestimate of the true
concentration.  To help remedy this situation, a second set of
p,p-DDE concentrations was calculated based on a lower response
ion (m/z=316).  The modified p,p-DDE data were obtained based on
recalculated calibration curves.  Unless interferences were
present under the lower response ion,  most of the modified data
were higher than the original data based on the primary
quantitation ion.  Although the modified p,p-DDE data values are
likely more accurate estimates of the true sample concentrations,
most of these values were higher than the highest calibration
standard.  This caveat should accompany any conclusions made on
the reported p,p-DDE data from the FY86 NHATS.

5.2  ADJUSTING CONCENTRATION DATA FOR SURROGATE RECOVERIES
          Measured compound concentrations in NHATS composite
samples are generally contaminated by systematic and random
errors.  A potential source of systematic error in the NHATS FY86
data has been identified by the recoveries of surrogate compounds
spiked into the composite samples.  These recoveries were much
higher in FY86 compared with previous surveys.  This type of
systematic error can lead to the conclusion that measured
concentrations for a compound are increasing over time, when in
fact the true concentration has remained constant during the
period.
          Statistical methods for characterizing trend in
compound concentrations should focus on how the true
concentration changes over time rather than how the average
measured concentration changes.  Dinh  (1991) has developed a
statistical technique to estimate true concentration levels in
the NHATS.  This technique used the recoveries of surrogate
                               5-9

-------
compounds to adjust  the measured concentration data of native
compounds.  The  result is  a more accurate representation of the
true concentration of native  compounds over time.  The NHATS
statistical analyses summarized in this report, including trends
analyses, were conducted on FY82, FY84, and FY86 data that were
first adjusted by applying this technique.  A discussion of this
technique follows.

5.2.1  Data Adjustment Method
          The statistical  technique developed by Dinh (1991) for
adjusting native compound  concentrations was based on fitting a
systematic errors-in-variables model to the NHATS data  (see
Sections 5.2.1.1 and 5.2.1.2).  This model predicted the measured
concentration as a linear  function of the unknown true
concentration.   In turn, the  expected value of the unknown true
concentration given  the measured concentration was estimated from
the model fit.   This latter result was considered an "adjustment"
to the measured  concentration and provided a more accurate
estimate of the  unknown actual concentration.
          To estimate the  expected value of an unknown true
concentration in a composite  sample, it was necessary to obtain
accurate characterizations of recoveries and true concentrations
for the native compounds.  This information was best represented
by analysis results  on surrogate compounds.  As part of the daily
QC procedure, several surrogate compounds were injected at known
concentrations into  each NHATS composite sample.  Surrogate
compounds do not naturally exist in composite samples; thus the
actual concentration of a  surrogate compound in a sample is known
to equal to the  amount spiked into the sample.  As a result, the
recovery levels  for  surrogate compounds provided information on
overall method performance and accuracy.
          While  recovery data were available for native compounds
as well as surrogate compounds, only recoveries for surrogate
compounds were used  to adjust the measured concentrations of
native compounds.  Native  compound recoveries were excluded for
                               5-10

-------
the following reasons:

     •    native compound recoveries can be affected by
          contamination and interferences of unknown magnitude,
     •    native compound recoveries were available only for the
          15 spiked QC samples, while surrogate recoveries were
          available for all NHATS samples.

          Each surrogate compound spiked into an NHATS composite
sample represented a class of one or more native compounds of
interest.  The surrogate compounds and the native compounds
represented by each surrogate are listed in Table 5-2.  When
possible, a native compound was linked directly to its surrogate
counterpart, such as lindane and chrysene.  However, most native
compounds did not have a direct surrogate counterpart included in
the spiking.  These compounds were associated with an average
result across multiple surrogates in the relevant chemical group.
          The methods used to adjust the measured concentrations
of composite and QC samples are now discussed.

5.2.1.1  Composite Data Adjustment.  In this procedure,  the
measured concentration of a compound is assumed to be linearly
related to the actual compound concentration in a composite
sample.  Let C be the number of NHATS composite samples analyzed,
let Yj be a measured concentration of a compound in  the i* NHATS
composite sample (i=l,...,C), and let /ij be the compound's
unknown true concentration in the sample.   Then
                         *i  =  Rfii + e± ,                     (5_1}

where R is the unknown recovery of the compound by the analytical
method, and e{ is random  error  having  mean zero.  Assume that ptj
and 6j  are normally distributed and are uncorrelated across  the
composites.   Then the expectation of /^ given Yj is  given by
                               5-11

-------
      Table  5-2.  Matching  NHATS  FY86 Native Compounds with
                     Surrogate Compounds
Surrogate Compound**)
Chrysene-d12
1, 2,4-Trichlorobenzene-d3
13C6 - 1, 2,4, 5-Tetrachlorobenzene
13C6 - Hexachlorobenzene
Mean of above three surrogates
13C6 -4-Chlorobiphenyl
13C12 - 3 , 3 ' , 4 , 4 ' -
Tetrachlorobiphenyl
2,2' ,3,3' ,5,5' ,6,6' -
Octachlorobiphenyl
13C12 - Decachlorobiphenyl
Mean of above four surrogates
Mean of tetra- and octa-
chlorobiphenyl surrogates
13C - Heptachlor
Lindane-d6
Mean of above two surrogates
Mean of all ten surrogates above
13} Kumbers of .Native
compounds Mnked with This !
Surrogate™
41-49
20-22
23-25
27
'17-19, 26
50
53
57

59
51, 52, 58
54-56
12
9
1-8, 10-11, 13-16, 6,0-62,
85-86, 98-102, 106-107
28-40, 63-84, 87-97,
103-105, 108-111
(1)  Two additional surrogates (Diethyl phthalate-d^  and Di-N-Butyl Phthalate-d4)
were included in the FY86 NHATS, but measured concentrations were missing for the
majority of the  composite samples.

(2*  See Table 5-1 to identify native compounds  from these codes.
                                   5-12

-------
                  \  Yj  =  [(1 - A)E(Yi)  + A*YJ  I R  ,
                                                             \ D — 
-------
          Table  5-3  lists  the estimates of R and A for all
compounds in  the FY82,  FY84, and  FY86 NHATS for semivolatiles.
For FY86, these  estimates  are based on only those composite
samples with  a wet weight  of at least ten grams.  This table
shows the relatively high  recoveries in FY86 for most surrogate
compounds  (values of R  greater than one) compared with the other
fiscal years.  Meanwhile,  the estimated recoveries were similar
for FY82 and  FY84.
          Among  the  three  fiscal  years in Table 5-3, spiked and
measured concentrations for surrogate compound data were only
available for the FY84  and FY86 NHATS.  Thus only for the FY84
and FY86 NHATS could the parameters R and A could be estimated by
fitting the linear regression model in equation (5-1) .  In
contrast, only recovery data were available for surrogate
compounds in  the FY82 NHATS.  As  a result, an estimate of R for a
given surrogate  compound in the FY82 NHATS was calculated by
averaging the observed  sample recoveries.  Because an estimate of
A could not be determined  from the available FY82 surrogate data,
the corresponding estimates of A  from the FY84 data were applied
to FY82.

5.2.1.2  QC Data Adjustment.  A slight modification to the
approach in 5.2.1.1  was needed to adjust the measured
concentration of a native  compound in an analytical sample when a
portion of the concentration in the sample was known.  This
situation occurred when the sample was spiked with a known amount
of the compound.  For example, ten of the FY86 NHATS QC samples
were spiked with 36  native compounds prior to analysis.  The
known portion of the concentration must be considered when
estimating the entire actual compound concentration in the
sample.
          Suppose that  the 1th QC  sample was spiked with a native
compound at a known  concentration Ss.  Let the unknown
concentration of the native compound in this sample be /Zj before
                               5-14

-------
Table 5-3.  Estimates of R and A for Surrogate Compounds
Native
Compound (or
group of
compounds )"'
UHATS FY82^
^
R
^
A
NHATS FY84
^
R
^t f
A
NH&TS FY8€^
: A
R
<"%
A
Pesticide group^
Heptachlor
epoxide
Lindane
All other
pesticides^
0.5764
0.5764
0.5764
0.9558
0.9558
0.9558
0.6069
0.6069
0.6069
0.9725
0.9725
0.9725
1.2761
0.9704
1.1381
0.9082
0.9120
0.9292
Chlorobenzene group
Trichloro-
benzene
Tetrachloro-
benzene
Hexachloro-
benzene
Other
Chloro-
benzenes^
0.5089
0.4374
0.5788
0.5089
0.8697
0.9301
0.9716
0.9514
0.2915
0.4400
0.5658
0.4325
0.8697
0.9301
0.9716
0.9514
0.6203
0.7666
0.9940
0.7586
0.9100
0.9290
0.9413
0.9315
PAH group
Chrysene and
other PAH
compounds
0.5858
0.9805
0.6500
0.9805
1.0088
0.9743
PCBs group
Monochloro-
biphenyl
Tetrachloro-
biphenyl
Penta-,
Hexa- , and
Heptachloro-
biphenyl^
Octachloro-
biphenyl
0.6223
0.6798
0.5089
0.4968
0.9584
0.9552
0.9696
0.9662
0.6580
0.6452
0.6455
0.6456
0.9584
0.9552
0.9696
0.9662
1.0252
1.2569
1.2018
1.1694
0.9453
0.9306
0.9154
0.8975
                            5-15

-------
                           Table  5-3.   (oont.)
Native
Compound (or
group of
compounds )u'
NHATS PY82^
R
A
NHATS FY84
R ';';|
F A
NHATS FY86W
MM^MMMMMMMI
R
A
A
PCB* group (oont.)
Decachloro-
biphenyl
Di-, Tri-,
and
Nonachloro-
biphenyl(8)
0.6272
0.6078
0.9022
0.9679
0.6414
0.6448
0.9022
0.9679
1.0467
1.1117
0.8618
0.9120
Phthalate Eater* group^
Diethyl
phthlate
Di-n-butyl
phthalate
Butyl benzyl
phthalate
Other
phthalates
0.5764
0.5764
0.5764
0.5764
0.9032
0.7850
0.6145
0.8235
0.6313
0.4472
0.4059
0.4948
0.9032
0.7850
0.6145
0.8235
1.0369
1.0369
1.0369
1.0369
0.9340
0.9340
0.9340
0.9340
All compound* not represented in the above row*(10)
Other
compounds
0.5764
0.9558 I 0.6637
II 	
0.9558 1.0369
0.9340
Notes for Table  5-3

(l)   Grouping  of compounds  without direct surrogate  counterparts  for FY86  is
documented in Table 5-2.

m   Estimates  of A  for PY82  are  taken  from FY84 estimates.

0)  Composite samples having ten  or more grams wet weight were used in determining
estimates for R and A.

(4)   Surrogates for  pesticides were not analyzed in FY82 or FY84.   Estimates for
these two years  are based on the linear regression in (5-1)  where Y( and Ml ar«
substituted by  the average  of  the spiked and found  concentrations  across all
surrogates.

(5)  The estimates of R and A  for  FY86 are obtained by the linear regression in (5-
1)   where  Y,  and Mi ar«  substituted  by the  average  of  the  found and  spiked
concentrations, respectively, of surrogate heptachlor and lindane.
                                     5-16

-------
                           Table  5-3.   (oont.)

(6)  The estimates of R and A are obtained by the  linear regression in  (5-1) where
Y, and MI  are substituted by the average of the found and spiked concentrations,
respectively, of surrogate tri-, tetra-, and hexa-chlorobenzene.

W  The estimates of R and A are obtained by the  linear regression in  (5-1) where
Y| and Mi  are substituted by the average of the found and spiked concentrations,
respectively, of surrogate tetra- and octa-chlorobiphenyl.

(8)  The estimates of R and A are obtained by the  linear regression in  (5-1) where
Y| and Mi  are substituted by the average of  the found and spiked
concentrations,  respectively,   of  surrogate  mono-,  tetra-,  octa-,   and deca-
chlorobiphenyl.

W  Surrogates  corresponding to phthalates were not analyzed in FY82.  Surrogate
phthalate data in FY86 were not analyzed due to the prevalence of missing values.
Estimates of R and A for  phthalates  in FY82  and FY86 are  based on the linear
regression in  (5-1) where  Yt and Mi ar« substituted by the average of the spiked
and found concentrations across all surrogates.

C°)  Estimates of R and A for all compounds  not represented on other rows of this
table are baaed on the linear  regression in (5-1)  where  Y( and MI are substituted
by the average of the spiked and found concentrations across all surrogates.
                                     5-17

-------
spiking and  /ij*  =  ^ + Sj after spiking.  Note that a portion of
the unknown  concentration ^* is known.   Similar to  equation
(5-1) , the measured concentration Yj* of the i* QC sample can  be
expressed as

                 Yi  =  R\il +  ei  =  R (jii + SJ + e^  ,            (5_4)

          As in equation  (5-2), the expectation of  p* given Yj*  is
given by
\  Yi)  =  [(1 -A)E(Y-)  + A*YJ]  I R  ,
                                                             (5_5)
where A and  R are as in equation (5-2) .   Thus the adjusted
measured  concentration for spiked samples is given by the
following estimate of E([JL* \  Yj*) :
                  p!  =  [(l-A) (B + RSJ + AY±] I R
                                                             (5-6)

where B is an  estimate of the background concentration (discussed
                                  A     A
in the following paragraph) ,  and A and R are as in formula (5-3) .
The last two columns  of Table 5-3 contain the estimates A and R
that were substituted in equation (5-6)  for each compound.
          The  background sample concentration,  represented by B
in equation  (5-6) ,  was estimated by fitting a linear regression
model.  This model, labeled the full batch effects model in
Section 5.3.2,  estimates the linear relationship between the
spiked concentration  and the measured concentration in a spiked
sample.  This  relationship was allowed to change according to the
batch in which the  sample was analyzed.   This model has the
following form:
                                 Pi
                                                             (5_7)
                               5-18

-------
where YJJ* is the measured  concentration  for  the  j* QC  sample

(j=l,2,3)  in the 1th batch  (i=l,...,5), Sj  is the spike level  of

the j* QC sample,  and ey represents random error.  The parameters

oij and /3j (1=1,..., 5)  represent batch intercepts  and slopes,

respectively.   These parameters were estimated by fitting the

model to the QC data.  The average of the estimates for the  five

batch intercepts a{  (1=1,..., 5) was  taken  as the value of B in

formula (5-6).

          Note that the modification presented in this subsection

to adjust measured concentrations was relevant only when a native
compound was spiked into the given sample.  No modification was

necessary for adjusting measured concentrations for unspiked

native compounds in these samples.


5.3  STATISTICAL ANALYSIS OF QUALITY CONTROL DATA

          The statistical analysis of quality control  (QC)  data

was performed to meet a number of study objectives prior to

composite data analysis.  These objectives include:

            >
     •    estimating the percent recovery of the analytical
          method for spiked compounds,

     •    determining if any significant differences exist in the
          analytical performance among the five batches,

     •    characterizing the precision of the analytical method,

     •    identifying estimates of measurement error present in
          the data within a batch,

     •    establishing the relationship in spiked compounds
          between the precision of the analytical method and the
          level of the spiked concentration,

     •    identifying anomalous results that suggest potential
          problems in the analytical measurements and which may
          cause removal of some of all data for a compound in
          further statistical analysis.
                               5-19

-------
          Of the seventy samples analyzed in the FY86
semivolatiles study, fifteen were QC samples, and five were
method blanks.  Each of the five analysis batches contained one
method blank, one unspiked control sample, and two spiked samples
(one sample spiked at a lower concentration than the other).   The
QC samples were prepared from a homogenized bulk lipid sample,
allowing for comparisons in method quality to be made between
batches.
          Within a batch, the three lipid-based QC samples were
randomized with the ten composite samples in determining the
order of sample testing.  The randomization ensured that no
systematic trends due to changes in laboratory procedures were
introduced into the analysis results.  The method blank was the
first sample analyzed within each batch.
          A total of 36 compounds were spiked into the two spiked
QC samples for each batch.  The spiking levels and compounds were
determined by MRI in consultation with the EPA/OPPT WAM.  Sixteen
of these compounds were identified in Section 5.1 as target
compounds for statistical analysis.  They are listed in Table 5-4
with their spike levels.  These levels were multiplied by 200
(solutions were spiked in a 200 /xL aliquot),  then divided by the
percent lipid weight  (in grams) of the sample to obtain spike
concentrations  (ng/g) for the sample.  QC analysis was performed
on these spiked target compounds.
          Eight additional compounds were identified in Section
5.1 as target compounds for statistical analysis, but they were
not spiked into the QC samples.  These compounds were identified
as unspiked target compounds.  The eight unspiked target
compounds were:

•    Beta-BHC                 •    Bis  (2-Ethylhexyl) phthalate
•    Oxychlordane             •    1-Nonene
•    Naphthalene              •    1,2,4-Trimethylbenzene
•    Di-N-Butyl phthalate     •    Hexyl acetate
                               5-20

-------
      Table 5-4.  Spiked Target Compounds for the FY86 NHATS,
                    With  Spiking Levels
Compound
(ID and Nams}^
Low Spike
Level (ng/#L)
High Spike
Level ; (ng/^L)
Pesticides
1
3
12
14
60
p,p-DDT
p,p-DDE
Heptachlor Epoxide
Trans -nonachlor
Dieldrin(2)
5.28
7.38
3.58
5.48
5.48
21.1
29.5
14.3
21.9
21.9
Chlorobenzenes
18
27
1 , 4 -Dichlorobenzene
Hexachlorobenzene
31.0
4.88
124.
19.5
PCBs
53
54
55
56
57
Tetrachlorobiphenyl
Pentachlorobiphenyl
Hexachlorobiphenyl
Heptachlorobiphenyl
Octachlorobiphenyl
14.1
16.3
13.2
32.5
34.3
56.2
65.0
52.6
130.
137.
Phthalate Esters
66
Butyl Benzyl Phthalate
5.65
22.6
Other
33
34
40
O-cymene
D-limonene
Octamethyl
Cyclotetrasiloxane
7.00
5.98
5.28
28.0
23.9
21.1
(1)  All listed compounds except Octachlorobiphenyl were detected in at least 50%
of the NHATS FY86 composite samples.  Octachlorobiphenyl  was detected in 44% of
the samples.
(2)  Detected in > 50% of the NHATS FY86 composite samples when S/N calculation
is used  (see Section  5.1.2).
  Spike level  (ng/g)   =   Spike level (na/^tL)  * 200 uiL
                               Percent lipid weight  (g)
Source:   Table  9 of MRI  Batch Reports  (updated 8/10/90)
                                  5-21

-------
QC data analysis for these target compounds was limited to
identifying effects due to batch and to QC sample type.  Thus QC
analysis was performed on a total of 24 of the FY86 semivolatile
compounds.
          If a compound was not detected in a QC sample, the
measured concentration was computed as one-half of the detection
limit.  This same approach was used in the statistical analysis
of the composite samples.
          A listing of the QC data, both unadjusted and adjusted
for surrogate recoveries, is found in Appendix B.  All QC
analysis was performed on data adjusted for surrogate recoveries.

5.3.1  Descriptive Summary of QC Data

5.3.1.1.  Spiked Compounds.  Table 5-5 contains a summary of the
QC data for the 16 spiked target compounds.   The data are
corrected for surrogate recoveries as discussed in Section 5.2.
Presented for each target compound and each of the four QC sample
types are the following statistics:

          •    the number of samples with reported results,
          •    the number of detected results,
          •    the average and standard deviation of the observed
               concentrations  (ng/g),
          •    the coefficient of variation (%), equal to the
               standard deviation divided by the average.

For the spiked samples, the following recovery information is
also presented:

          •    the average spike level (ng/g),
          •    the background average recovery (%), calculated as
               the average (across batches)  of the following
               ratio:
                               5-22

-------
Table 5-5.
Summary of (Surrogate-Adjusted)  QC Data for the FY86 NHATS
Spiked Target Compounds
Compound
p,p-DDT



p,p-DDE
(m/z=288)


in
^ p,p-DDE
w (m/z=316)


Heptachlor
epoxide

•
Trans -
nonachlor


Avg.
Spike
Spike # # Level
Level Samples Detected (ng/g)
MB
Control
Low
High
MB
Control
Low
High

MB
Control
Low
High
MB
Control
Low
High
MB
Control
Low
High
5
5
5
5
5
5
5
5

0
5
5
5
5
5
5
5
5
5
5
5
0
5
5
5
0
5
5
5

0
5
5
5
0
5
5
5
0
5
5
5

0
53
212

0
74
296


0
74
296

0
36
143

0
55
220
—
.00
.32
.27
-
.00
.53
.77

-
.00
.53
.77
-
.00
.15
.86
_
.00
.34
.32
Avg.
Observed
Cone.
(ng/g)
3
211
262
470
3
2979
2721
2877


2735
2606
2667
3
92
135
221
3
238
236
350
.33
.09
.38
.24
.57
.26
.64
.80

-
.68
.68
.58
.42
.59
.53
.71
.50
.12
.32
.87
Background
Adjusted Std. Dev.
Recovery of Cone.
(%) (ng/g)
_
-
95.91
122.24
-
-
-343.59
-33.97

-
-
-174.00
-22.63
-
-
118.31
89.75
_
-
-1.94
51.15
1
17
34
71
1
1183
1371
1627


1356
1364
1688
1
21
25
45
1
125
70
164
.43
.56
.44
.75
.40
.27
.98
.77

-
.11
.86
.32
.34
.34
.28
.83
.37
.99
.05
.24
C.V.
42.85
8.32
13.12
15.26
39.23
39.72
50.41
56.56

-
49.57
52.36
63.29
39.12
23.05
18.65
20.67
39.12
52.91
29.64
46.81

-------
Table 5-5.   (cont.)
Avg.
Spike
Spike # # Level
Compound Level Samples Detected (ng/g)
Dieldrin
(corrected)


1 , 4 -Dichlorobenzene



Ul
to Hexachlorobenzene
**


Tetrachlorobiphenyl


Pentachlorobiphenyl


MB
Control
Low
High
MB
Control
Low
High

MB
Control
Low
High
MB
Control
Low
High
MB
Control
Low
High
0
4
4
5
5
5
5
5

5
5
5
5
5
5
5
5
5
5
5
5
0
5
5
5
0
5
' 5
5.

0
5
5
5
0
4
5
5
0
5
5
5

0.
55.
220.
_
0.
313.
1247

-
0.
49.
196.
0.
142.
565.
0.
164.
653.

00
34
32

00
06
.5


00
28
17
00
39
38
00
61
91
Avg.
Observed
Cone.
(ng/g)

56.
103.
164.
3.
177.
266.
875.

3.
71.
118.
284.
4.
85.
208.
580.
8.
194.
321.
702.

19
41
33
01
05
77
60

43
51
76
30
00
59
41
71
60
01
57
98
Background
Adjusted Std. Dev.
Recovery of Cone.
(%) (ng/g)

-
85.34
49.18
_
-
29.10
56.03

-
-
95.78
108.49
-
86.30
87.67
-
77.38
78.01

47
84
102
1
63
130
256

1
4
21
22
0
28
55
132
0
92
165
260

.78
.31
.60
.17
.57
.45
.10

.34
.04
.91
.98
.00
.23
.16
.29
.00
.02
.68
.33
c.v.

85.04
81.53
62.44
39.06
35.90
48.90
29.25

39.07
5.66
18.45
8.08
0.00
32.98
26.47
22.78
0.00
47.43
51.52
37.03

-------
Table 5-5.  (cont.)
Compound
Hexachlorobiphenyl



Heptachlorobiphenyl



ui
eo Octachlorobiphenyl
Ul


Butyl benzyl
phthalate


O-cymene



Avg.
Spike
Spike # # Level
Level Samples Detected (ng/g)
MB
Control
Low
High
MB
Control
Low
High

MB
Control
Low
High
MB
Control
Low
High
MB
Control
Low
High
5
5
5
5
5
5
5
5

5
5
5
5
4
5
5
5
5
5
5
5
0
5
5
5
0
5
5
5

0
5
5
5
2
3
4
5
0
3
3
5
_
0.00
133.31
529.16
-
0.00
328.21
1307.8

-
0.00
346.39
1378.2
-
0.00
57.06
227.36
-
0.00
70.69
281.68
Avg.
Observed
Cone.
(ng/g)
8
1042
1044
1282
9
679
976
1743

8
142
531
1537
13
36
104
180
3
11
12
59
.90
.11
.40
.64
.15
.24
.65
.22

.90
.68
.73
.61
.30
.63
.33
.83
.57
.04
.82
.59
Background
Adjusted Std. Dev.
Recovery of Cone.
(%) (ng/g)


1
45


90
81



111
101


119
63


2
17
>_r
-
.43
.40
—
-
.56
.49

-
-
.94
.36
-
-
.06
.55
-
-
.63
.26
0
78
61
70
0
147
110
362

0
64
130
468
11
29
53
110
1
6
4
38
.00
.08
.89
.49
.00
.79
.02
.28

.00
.48
.41
.91
.35
.38
.64
.33
.40
.09
.00
.76
C.V.
(%)
0.00
7.49
5.93
5.50
0.00
21.76
11.27
20.78

0.00
45.19
24.53
30.50
85.31
80.20
51.42
61.02
39.12
55.15
31.18
65.05

-------
                                         Table 5-5.   (cont.)



Spike #
Compound
D-limonene



Octamethyl-
cyclotetrasiloxane


Level Samples
MB
Control
Low
High
MB
Control
Low
High
5
5
5
5
5
5
5
5

ft
Detected
2
5
5
5
1
2
2
4
Avg.
Spike
Level
(ng/g)

0.00
60.39
240.44
_
0.00
53.32
212.27
Avg.
Observed
Cone.
(ng/g)
11.52
122.24
108.62
223.09
34.59
8.03
10.28
66.84
Background
Adjusted
Recovery
(%)

-
-21.45
41.94
-
-
4.30
27.73
Std. Dev
of Cone.
(ng/g)
11.55
40.19
52.65
53.90
67.89
6.15
4.17
38.34

C.V.
(%)
100.24
32.88
48.48
24.16
196.27
76.62
40.61
57.35
to

-------
 Recovery(%) = conc- (spiked sample) - cone, (control sample)  ^ 1(J(J.
                               Spike level                   (5_8)
          Table 5-5 shows that the higher spike level for p,p-DDE
was approximately ten percent of the average background level
given by the control sample.  The laboratory analysis was unable
to estimate recoveries for p,p-DDE due to the high background
level relative to the spiking levels.  As a result, estimated
background-adjusted recoveries (BARs) for p,p-DDE were negative.
BARs near zero were observed at low spike levels for trans-
nonachlor,  hexachlorobenzene, and D-limonene, all as a result of
high background levels.
          BARs of less than 50% were observed for o-cymene, D-
limonene, and octamethyl-cyclotetrasiloxane, despite spike levels
generally above observed background.  Thus these three compounds
may have recovery problems.  The BAR for 1,4-Dichlorobenzene was
less than 60%, reflecting the higher volatility in this compound
compared to the other target compounds.  Except for
hexachlorobiphenyl (which had low recoveries) ,  the BARs for PCBs
ranged from 77 to 112 percent.  For p,p-DDT, heptachlor epoxide,
hexachlorobenzene, and butyl benzyl phthalate,  the BARs ranged
from 64 to 122 percent.
          The "BAR" approach to calculating percent recoveries
given in equation (5-8) has been recommended for use through the
NHATS program.  However, an alternative approach to calculating
percent recoveries does not place as much emphasis on the ability
to detect finite differences in concentration.   This approach
considers the formula
    Recovery^  =  	cone, (spiked sample)   	  „ 10Q%
           -^  /     conc, (control sample)  + spike level       (5-9)
                               5-27

-------
Note that the percentages  calculated from  (5-9) are always
positive and are equal  to  100% when the observed concentration
equals the sum of  the spike  level and the  control sample
concentration within the batch.  Table 5-6 presents the percent
recoveries under both approaches  (5-8) and (5-9) for the spiked
target compounds.   In this setting, approach  (5-9) generally
leads to improved  percent  recovery values  over approach  (5-8).
This is especially apparent  with p,p-DDE,  where the spike levels
were much smaller  than  the observed levels in the control
samples.  While approach  (5-8) has been recommended for the NHATS
program, both approaches evaluate method performance differently,
and thus both sets of results should enter into performance
evaluation.
          Coefficients  of  variation were widely varied among the
samples and compounds  (Table 5-5).  Only p,p-DDT, heptachlor
epoxide, hexachlorobenzene,  hexachlorobiphenyl, and
heptachlorobiphenyl had coefficients of variation which were at
25% or smaller for all  samples.  For the other spiked target
compounds, the variation in  the QC results at a given spike level
was as high as 80% of the  observed average level across the
batches.
          For dieldrin, butyl benzyl phthalate, o-cymene, and
octamethyl-cyclotetrasiloxane, at least one QC sample result was
not detected at the low spike level.
          Appendix C contains plots of the measured
concentrations versus the  spike levels for all study compounds.
Although some plots indicate a linear increasing relationship,
most plots show highly  variable results among the batches at a
given spike level.  Several  of the plots suggest that
concentrations were higher for Batches 4 and 5 than for the other
three batches, such as  with  p,p-DDT, p,p-DDE, and some of the
PCBs.  This was especially evident at high spike levels.
          Appendix D contains summaries like those in Table 5-5
for spiked compounds not on  the target list.
                               5-28

-------
   Table 5-6.  Percent Recoveries  for  Spiked Target  Compounds,
             as Determined from Two Calculation Methods
Compound
•.* •*•*
p,p-DDT
p,p-DDE (m/z=288)
p,p-DDE (m/z=316)
Heptachlor epoxide
Trans -nonachlor
Dieldrin (corrected)
1 , 4 -Dichlorobenzene
Hexachlorobenzene
Te t r achl orobipheny 1
Pent achl orobipheny 1
Hexachlorobiphenyl
Heptachlorobiphenyl
Octachlorobiphenyl
Butyl benzyl phthalate
O-cymene
D-limonene
Octamethyl-
cyclotetrasiloxane
% Recovery Using
SkpatlOtt (5-8}
Low - High
spike spike
95.91
-343.59
-174.00
118.31
-1.94
85.34
29.10
95.78
86.30
77.38
1.43
90.56
111.94
119.06
2.63
-21.45
4.30
122.24
-33.97
-22.63
89.75
51.15
49.18
56.03
108.49
87.67
78.01
45.40
81.49
101.36
63.55
17.26
41.94
27.73
% Recovery
Using Equation
(5-9) .
Low High
spike spike
98.95
88.27
97.32
105.38
84.27
84.99
55.81
98.60
91.50
98.01
89.04
97.43
109.92
110.52
15.81
64.29
17.02
110.86
82.30
80.57
93.66
79.83
56.90
61.26
106.33
89.00
83.27
81.71
88.14
101.17
66.72
20.35
61.94
30.11
Two methods  to  calculating
adjusted data:
percent  recovery on  the  surrogate-
 Recoverv(%) = cone, (spiked sample) - cone, (control sample)  + 1QO%
        y                      Spike level                    (5-8)
     Recovery (%)   =
                            cone, (spiked sample)
                    cone, (control sample) + spike level
                          * 100%
                                                              (5-9)
                               5-29

-------
5.3.1.2  Unspiked Compounds.  Table 5-7 contains descriptive
summaries 'of eight target compound concentrations that were not
spiked in the control samples.  The descriptive statistics were
calculated for each batch and across all batches.

5.3.1.3.  Method Blanks.  Method blanks were used to assess
laboratory background contribution to concentration levels within
the composite samples.  Eight of the target compounds were
detected in the method blanks.  When detectable concentrations
were measured in method blanks, the results are presented in
Table 5-8.  Detection in the method blanks suggests a potential
bias in the reported concentration levels within the affected
batches for the given compound.
          The method blanks for Batches 1 and 5 had detectable
levels for the three target phthalates.  The bis (2-ethylhexyl)
phthalate was also detected in the method blank for Batch 3.   The
method blank for Batch 4 was not analyzed for phthalates.  In
most cases, the method blank concentration was at or above the
control  (unspiked) sample, suggesting laboratory background
contribution to the measured concentration.

5.3.2  Statistical Approach to Analyzing the QC Data
          To address the statistical objectives presented at the
beginning of Section 5.3, the QC data were statistically analyzed
using linear models fitted to the surrogate-adjusted
concentrations for each compound.  A linear regression model was
applied to concentration data for spiked compounds.  This model
included effects for batch and spike level.  A similar analysis
of variance application determined whether batch and sample type
effects were statistically significant on concentrations for
unspiked compounds.  The statistical methods and results are
described in this subsection.

5.3.2.1  Spiked Compounds.  Two types of linear regression models
were fit to the QC data for spiked target compounds.  One model,
                               5-30

-------
     Table 5-7.   Means and Standard Errors of Surrogate-Adjusted Concentrations (ng/g)
                 of Unspiked Target Compounds for QC Samples (By Batch and Overall)

Compound
Beta-BHC
Oxychl ordane
Naphthalene
Di-n-butyl phthalate
en
00
H Bis (2-ethylhexyl)
phthalate
1-Nonene
1,2,4
-Trimethylbenzene
Hexyl acetate

1
147.04
( 66.01)
12.43
( 0.02)
11.40
( 3.22)
23.70
( 10.18)
414.00
(330.21)
360.11
( 79.44)
18.14
( 10.32)
68.01
( 15.01)

2
261.88
(121.63)
94.07
( 40.89)
8.63
( 1.93)
44.36
( 17.06)
231.36
(147.34)
218.99
(175.67)
62.43
( 21.65)
158.83
(107.74)
Da+-/~iVi
3
126.33
(108.90)
132.41
( 9.57)
6.24
( 3.62)
12.28
( 1.37)
191.66
( 63.43)
513.24
(237.20)
21.14
( 8.26)
137.82
(115.44)

4
310.39
( 8.11)
146.56
( 11.32)
11.71
( 0.61)
62.32
( 5.69)
78.96
( 39.24)
720.42
(108.26)
63.18
( 29.27)
179.10
( 94.90)

5
221.18
( 89.94)
143.84
( 7.79)
10.68
( 0.59)
56.31
( 21.91)
629.34
(456.20)
447.18
(247.80)
15.14
( 7.39)
59.00
( 3.00)
all
A±L
Batches
213.364
( 38.198)
105.864
( 15.389)
9.731
( 1.048)
39.795
( 7.205)
309.065
(111.818)
451.988
( 82.086)
36.005
( 8.882)
120.552
( 33.826)
Standard errors are in parentheses beneath the means.

These statistics represent three lipid-based QC samples  (C, SI, S2)  per batch.   All act as
control samples for unspiked compounds.

-------
  Table 5-8.
Batch Analysis Results on Method Blanks and Control
 Samples  for  Compounds Detected  in At Least 50% of
 Composites,  where  the Compound  Was Detected in the
 Method Blank
Compound
Batch
Lab f
Cone.
of
Method
Blank
(ng/g)
1 Gone.,
i of
Control
sample
(ng/g)
% Of
Control:
Qatto. \t
<>•,
<•
Phthalate Esters
Di-n-butyl
phthalate
Butyl benzyl
phthalate
Bis (2-ethylhexyl)
phthalate
1
5
1
5
1
2
3
5
17901
17957
17901
17957
17901
17915
17929
17957
44.9
13.7
29.1
14.0
205.
581.
288.
15.4
12.05
20.2
10.55
13.7
57.8
560.
222.
348.
373.
67.8
276.
102.
355.
104.
130.
4.4
Other
D-limonene
Oc tame thy 1-
cyclotetrasiloxane
2
5
3
17915
17957
17929
27.9
19.5
156.
85.4
164.
20.3
32.7
11.9
768.
Other (qualitative)
1-nonene
1,2,4-
trimethylbenzene
Hexyl acetate
1
2
3
1
3
17901
17915
17929
17901
17929
600.
1000.
40.0
20.0
400.
200.
600.
30.0
50.0
2.50
300.
167.
133.
40.0
16000
Note:  Concentrations are unad-iusted for surrogate recoveries.
                               5-32

-------
known as the batch slopes model, provided estimates of batch
recoveries and tests for equality of these estimates across
batches.  The other model, called the batch intercepts model, was
considered when spiked sample results were not sufficiently above
background to allow for batch recovery estimates to be made.  The
batch intercepts model provided for separate background levels to
be estimated for each batch.  These models are summarized in
Table 5-9 and satisfactorily characterize the FY86 QC data for
all compounds.
          The full batch effects model introduced in Section
5.2.1 and presented in (5-7) was also considered in this
application.  The full batch effects model,  a composite of the
batch slopes and batch intercepts models, contains ten parameters
which represent separate slopes and intercepts for the five
batches.  This is a large number of parameters compared with the
number of data points (15),  leading to overparametrization
problems.  When either constant batch backgrounds or constant
batch slopes cannot be assumed, a simple linear regression model,
with constant background and slope across batches, was
considered.
          The batch slopes model tested for significant
differences in batch recoveries for the spiked compound.  This
model also estimated the batch recoveries and the average
recovery across all batches, and calculates predicted
concentrations at each spike level.  The average recovery was
tested for significant difference from 100%,  thus determining the
accuracy of the analytical method.  The estimated intercept term
was interpreted as the estimate of background (or systematic
error)  across all batches.  Batch effects were present when at
least one of the estimated slopes was found to be significantly
different from the others.
          According to the descriptive results presented earlier
in this section, the spike levels for some compounds were low
relative to background.  Thus the reported concentrations for
spiked samples were at the background level.   This outcome was
                               5-33

-------
       Table  5-9.   Regression Models Used to Analyze NHATS FY86 QC  Data for Spiked  Compounds
        Model
                    Equation1
(1)
Model interpretation
    Batch  Slopes Model
                  ECy = a + /3j*SCj
Ul

00
    Batch Intercepts Model    ECy  =  a} + j8*SCj
           Intercept  (a)  represents  the background  level
           across all batches.

           Slopes  (ft,  i=l,2,...,5)  represent  the  batch
           recoveries.    When  data  are  balanced®,  the
           average of the estimated batch recoveries from
           this model  equals the  slope  which would have
           been fitted if batch was not represented in the
           model.

           Intercepts (c^, i=l,2,...,5) represent the batch
           background levels.   When data are balanced®,
           the average  of the estimated batch background
           levels  from this  model  equals  the  intercept
           which would  have  been fitted if  batch was  not
           represented  in the model.

           Slope  (j8)  represents the estimated recovery
           across all batches.
    ^ ECy = Expected compound concentration  (ng/g)  in the jth QC sample of batch i
               (i=l,2,...,5; j=l (Control),2  (low spike),  3(high spike))
        so
         •j
Spike levels of. the jth QC sample
   (jsl (Control), 2 (low spike), 3 (high spike))
    ® In this application,  the data are balanced whenever there are equal numbers of control, low spike, and high
    spike samples with reported data.

-------
observed for p,p-DDE.  A batch slopes model was not appropriate
in this situation, as batch recoveries cannot be estimated from
the observed data.  Affected compounds were analyzed using the
batch intercepts model or simple linear regression model to note
overall differences among batches.
          The statistical analysis of QC data established that
significant batch effects existed in the data for virtually all
spiked target compounds.  Specifically, estimated recoveries for
Batches 4 and 5 tended to differ from the first three batches.
As a result, all statistical analyses on composite samples
included a "batch class" effect  (Batches 1-3 versus 4-5).   Any
batch effects existing beyond the "batch class" effect were
treated as random effects.
          The NHATS additive model assumes that the standard
deviation of the measured concentration in composite samples has
two components:

     •    a component associated with the within-batch
          measurement error, estimated by the mean-squared error
          (MSE) from the batch slopes model,
     •    a random component associated with the random-batch
          effects within each batch "class".

For a spiked target compound, the predicted average concentration
at the j* spiked concentration SCj  (j = 1, 2) is given by

                       
-------
                   SD(Cj)   =  /  MSE + SCj*SD(/3) ,             (5-11)

where MSE  is  the  mean-squared  error from  the batch  slopes model,
and SD(/3)  is  the  sample  standard deviation  of the estimated batch
recoveries.   Thus the  standard deviation  increases  with the
concentration of  the sample; however,  it  is not necessarily
proportional  to the concentration.   If the  batch slopes model
indicated  that a  significant batch  effect existed,  only
recoveries from Batches  1-3 were used  to  estimate the parameters
/|vg and SD(/3) .  Otherwise all five batches were used.

5.3.2.2  Unspiked Compounds.   Although batch recoveries could not
be estimated  for  the eight unspiked target  compounds, batch
effects and method contamination could still be characterized for
these compounds.   A two-way analysis of variance approach was
applied to these  compounds containing  effects representing the
batch and  the  sample type  (control,  low spike, high spike).  The
batch effect  provided  a  test for significant differences in
concentrations between batches.   The effect for sample type
allowed for tests between  samples containing different spiking
solutions.  This  latter  test was a  means  of determining the
presence of method contamination.

5.3.3  Results of Statistical  Modelling of  QC Data

5.3.3.1  Spiked Compounds.  The  results of  fitting  the batch
slopes model  in Table  5-9  to the QC data  for spiked target
compounds  are  summarized in Tables  5-10 through 5-12.  Table 5-10
contains the estimated batch recoveries for each spiked target
compound,  as well as the estimated  average  recovery across all
batches.   Table 5-11 reports significance levels for tests of
equal recoveries  among sets of batches.   Table 5-12 provides
information on observed  precision.
                               5-36

-------
              Table 5-10  Estimated Batch Recoveries and Average Recovery for Spiked
                          Compounds with Percent Detected At Least 50%  (Adjusted Data)
in
Estimated
Average
Recovery
Compound (%)
p,p-DDT
p,p-DDE (m/z=288)
p,p-DDE (m/z=316)
Heptachlor epoxide
Trans - nonachl or
Dieldrin (modified)
1 , 4 -Dichlorobenzene
Hexachlorobenzene
Tetrachlorobiphenyl
Pentachlorobiphenyl
Hexachlorobiphenyl
Hep t achl orob ipheny 1
Octachlorobiphenyl
Butyl benzyl phthalate
O-cymene
124*
-6.60
-7.83
87.8*
56.0*
46.2*
58.1*
110*
87.8*
78.1*
48.7*
80.8*
101
59.1*
18.4*
S.E.<2>
5.4
213
229
9.08
27.4
14.3
4.83
3.91
2.81
9.27
8.89
6.64
3.33
9.53
2.51
Estd
1
108
	
	
63.2
58.9
-15.9
32.0
95.6
64.2
34.8
40.2
51.4
51.2
10.3
27.5
.mated Batch Recoveries (%)^
2
90.2
	
	
71.8
-53.1
42.5
59.7
111
73.7
42.1
60.7
64.4
97.0
75.1
9.54
3
97.8
	
	
58.7
40.0
60.8
43.5
97.3
72.1
69.3
53.3
72.3
89.4
4.01
36.2
4
170
	
	
122
121
19.4
72.1
127
113
112
33.7
102
131
123
9.14
5
156
	
	
123
117
124
83.1
117
116
131
55.8
113
134
83.8
9.50
Sig.
Batch
Slope
Effect?
Yes
	
	
Yes
No
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes

-------
Table 5-10.   (cont.)
in
u>
00
Estimated
Averacre Estimated Batch Recoveries (%)^
Recovery
Compound (%) S.E.(2) 1 2 3 4 5
D-limonene 46.9* 11.9 16.6 53.0 27.5 73.7 63.6
Octamethyl-
cyclotetrasiloxane 29.5* 3.23 8.28 40.8 50.8 19.1 28.7
^ These are estimates of the parameters ft (i=l,...,5) in the batch slopes model in
Table 5-9.
® Standard error in the estimated average recovery.
* Significantly different from 100% at the 0.05 level.
Note; 'Larcre dif f erenees in batch intercenta for n.n-DDE nrohibit calculatino internretable bate
Sig.
Batch
Slope
Effect?
No
Yes
h recovers

-------
  Table  5-11.  Tests  for Significant  Differences in  Batch Slopes
                Among  Selected Batches for Spiked Target Compounds

£* £& Compound/ '

:":-:--:: . .':::;::




Significance Levels
Test of
Equal Batch
Recoveries
Among
Batches 1-5
Test of
Equal Batch
Recoveries
Among
Batches 1-3
Only
Test of
Differences
in
Recoveries
between
Batches 1-3
and Batches
4-5
Pesticides
p,p-DDT
Heptachlor epoxide
Trans -nonachlor
Dieldrin
0.0003*
0.023*
0.101
0.0018*
0.389
0.812
0.210
0.094
0.0001*
0.0018*
0.027*
0.071
Chlorobenzenes
1 , 4 -Dichlorobenzene
Hexachlorobenzene
0.0067*
0.031*
0.083
0.205
0.0013*
0.0059*
PCBs
Tetrachlorobiphenyl
Pentachlorobiphenyl
Hexachlorobiphenyl
Heptachlorobiphenyl
Octachlorobiphenyl
0.0001*
0.0042*
0.650
0.012*
0.0001*
0.316
0.273
0.598
0.407
0.0004*
0.0001*
0.0004*
0.620
0.0012*
0.0001*
Phthalate Esters
Butyl benzyl
phthalate
0.0016*
0.016*
0.0005*
Other
0-cymene
D-limonene
Octamethyl
cyclotetrasiloxane
0.023*
0.254
0.0018*
0.0032*
0.410
0.0006*
0.0026*
0.066
0.077
0)
   p,p-DDE not included in this table  (see discussion)

  Significance occurs at the 0.05 level.
                                  5-39

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                 Table 5-12.
Predicted Concentrations and Coefficients of Variation
at Each Spike Level for Spiked Target  Compounds  Analyzed
by the  Batch Slopes Model
ui

£»
O
Control
Compound
P.P-DDT(*>
Heptachlor epoxide^
Trans -nonachlor
Dieldrin (corrected) ^
1 , 4 -Dichlorobenzene^
Hexachlorobenzene^
Tetrachlorobiphenyls^
Pentachlorobiphenyls^
Hexachlorobipheny 1 s
Kept achlorobiphenyl s^
Butyl benzyl phthalate^
O-cymene^
D-limonene
Oct amethyl - cyclo . ^
Pred.
Cone.
(ng/g)
2 04.. 59
97.32
223.84
65.50
137.87
68.59
84.66
193.54
1015.34
693.02
51.31
6.22
104.37
2.25
C.V.
9.2
22.1
44.4
79.1
71.9
18.4
30.8
51.5
7.6
20.6
69.4
186.9
45.1
501.4
Average Low
Soike Level
Pred.
Cone.
(ng/g)
257.15
120.67
254.84
81.61
278.94
118.55
184.36
273.77
1080.30
898.93
68.31
23.50
132.68
20.02
C.V.
7.5
17.9
42.0
69.0
38.8
11.2
14.7
38.0
7.3
16.4
61.7
64.2
37.1
81.9
Average High
Spike Level
Pred.
Cone.
(ng/g)
413.82
190.22
347.25
129.66
699.99
267.45
480.51
512.27
1273.22
1513.50
119.06
75.06
217.10
72.97
C.V.
6.4
12.4
53.5
78.9
28.6
7.8
8.1
30.3
7.7
13.1
80.9
53.4
34.4
66.6
    All compounds but O-cymene and Octamethyl-cyclotetrasiloxane have predicted control concentrations which are
    significantly different from zero at the 0.05 level.
       Average recoveries only from batches 1-3 used in calculations.

-------
          For all but p,p-DDE, the batch slopes model provided a
good fit to the surrogate-adjusted data.  The estimate of average
recovery for p,p-DDE was outside of valid ranges, emphasizing the
inappropriateness of estimating batch recoveries for this
compound.  Batch recoveries were not interpretable for p,p-DDE
due to large differences in batch intercepts.  Thus no estimated
batch recoveries were reported for p,p-DDE in Table 5-10.
          For the other compounds, a t-test was performed at the
0.05 significance level to determine if the average recovery was
significantly different from 100%.  All compounds except p,p-DDE
and octachlorobiphenyl had average recoveries significantly
greater than 100%.  For twelve of the compounds, the average
recovery was significantly less than 100%.   Five compounds had
average recoveries less than 50%:  o-cymene (18.4%), octamethyl-
cyclotetrasiloxane (29.5%), dieldrin (46.2%),  D-limonene (46.9%),
and hexachlorobiphenyl (48.7%).  Two compounds had average
recoveries significantly greater than 100%:  hexachlorobenzene
(110%)  and p,p-DDT (124%).
          Estimates of the individual batch recoveries from the
batch slopes model are shown in the remaining columns of Table
5-10.  Also present are the results of an F-test to determine if
significant differences exist among the batch recoveries at the
0.05 significance level.   This test determines the presence of
batch effects.
          Significant differences among the five batch recoveries
were observed for twelve compounds.  For virtually all of these
compounds, the differences seem to arise from the large
recoveries in Batches 4 and 5 relative to the first three
batches.  For p,p-DDT, the estimated recoveries in Batches 4 and
5 average a 65% increase over the first three batches.  Similar
results are observed for PCBs and other pesticides.
          F-tests on linear combinations of the estimated batch
recoveries were performed to determine significant differences
among these recoveries.  The significance levels for the test of
equal recoveries among the five batches are listed in Table 5-10
                               5-41

-------
for each spiked target compound except p,p-DDE, where batch
recoveries could not be accurately estimated.  Because of the
apparent difference in estimated batch recoveries between Batches
1-3 and Batches 4-5, Table  5-10 also contains significance levels
for testing differences between these two groups of batches, as
well as among the first three batches only.  For eleven of the
fifteen spiked target compounds in Table 5-10, the estimated
recoveries in Batches 1-3 differ significantly (at the 0.05
level) from the estimated recoveries in Batches 4-5.  However,
only three of these compounds have significant differences in
estimated recoveries among  Batches 1-3 only.  Thus the following
conclusions can be made from Table 5-10:

     •    The systematic difference in recoveries between Batches
          1-3 and Batches 4-5 appears real,
     •    There appear to be no additional systematic batch
          effects beyond that observed in Batches 1-3 versus
          Batches 4-5.

The first conclusion states that it is not suitable to treat all
batch effects as random as  was done in the FY87 analysis of
dioxins and furans.  The presence of a systematic batch effect
indicates that some batch correction is necessary when analyzing
the composite data.  However, any additional batch effects beyond
the Batches 1-3 versus Batches 4-5 effect can be treated as
random.
          For spiked target compounds, Table 5-12 presents the
predicted average concentration and estimated coefficient of
variation (CV) for each compound and spike level, as derived by
the batch slopes model.  These results were used to characterize
the precision of the analytical method.   Except for o-cymene and
octamethyl-cyclotetrasiloxane (which had very low recoveries),
all predicted concentrations at the zero spike level were
significantly greater than  zero at the 0.05 significance level.
                               5-42

-------
This is consistent with the fact that the target compounds were
detected in nearly all of the QC control samples (Table 5-5).
          Whenever the batch slopes model indicated a significant
batch effect present, average recoveries from only the first
three batches were used to calculate predicted concentrations and
CVs for the compound.  This reflects the assumption that the
primary trend in batch effects is due to Batches 4 and 5 having
higher recoveries compared to the first three batches, leading to
biases in the results from Batches 4 and 5.
          From Table 5-12, the relative precision of measured
concentrations tends to be better for pesticides and PCBs
compared with other groups of compounds.  At the control level,
the CVs for pesticides and PCBs range from 7.6% to 51.5%,  with a
CV of 71.9% for the more volatile 1,4-Dichlorobenzene.  The CVs
for all of the pesticides and PCBs are below 79% in the spiked
samples.  Meanwhile, except for D-limonene (whose CVs rival the
pesticides and PCBs), the CVs for phthalates and other compounds
are above 50% for control and spiked samples.
          Because batch recoveries could not be estimated for
p,p-DDE (m/z=288 and m/z=316)  based on the observed results and
spike levels, the batch intercepts model was fit to this
compound.   The batch intercepts model provides for background
levels to be estimated for each batch.  Thus batch effects were
determined by testing for equality of the batch background
levels.  Table 5-13 contains the results of fitting the batch
intercepts model to p,p-DDE.  For both sets of p,p-DDE results,
the test for batch effects is highly significant.  As apparent in
the QC data plots, the estimated background levels for Batches 4
and 5 are over twice the level of the first three batches.  This
extreme difference in background levels contributes to the
inability to estimate batch recoveries.  Thus the results of the
batch intercepts model fitting for p,p-DDE indicate that
differences between the two "batch classes"  (Batches 1-3 versus
4-5) are highly significant, as was seen for most of the spiked
target compounds.
                               5-43

-------
            Table 5-13.  Estimated Batch  Background Levels and Average Background Level
                          for  the Two Methods of Reporting p,p-DDE Concentrations, as Estimated by
                          the  Batch Intercepts Model



Compound
P,P-DDE (m/z=288)
P,P-DDE (m/z=316)
Est. Avg.
Background
Level
(ng/g) S.E.<2>
2872 157
2684 158

Estimated Batch

1 2
2162 1896
2098 1796

Background

3
1615
1149

Level

4
4473
4476

(na/cr) (1)

5
4215
3900
    (i)
       These are estimates of the parameters a-t (i=l,...,5)  in the batch intercepts model in Table 5-9.
01   ®  Standard error of the estimated average background level.

-------
5.3.3.2  Unspiked Compounds.  Results of statistical analysis of
unspiked target compound concentrations in QC samples are
presented in Table 5-14. This table presents significance levels
for differences between batches and between sample types.  Batch
effects were significant at the 0.05 level for oxychlordane and
Di-n-butyl phthalate.  Significant batch effects for oxychlordane
are attributed to the large number of not detected readings in
Batch 1.   A very high percentage of not detected readings for
oxychlordane in Batch 1 is also present among the composite
samples.   Since the frequency of not detected oxychlordane
readings substantially decreases after Batch 1,  the Batch 1
oxychlordane results tend to be suspect.
          None of the unspiked target compounds showed a
significant effect due to the sample type.  Thus these data can
be considered as control sample results for the unspiked
compounds.  All of these samples are used to determine within-
batch measurement error.
          Precision was estimated for the unspiked compounds at
the control level based on the above analysis of variance model.
The precision summary is presented in Table 5-15.  The predicted
control level reflects all QC samples,  as it was determined that
no sample type effect existed.  Because data exist for all sample
types within each batch, the predicted concentration is equal to
the average concentration across the 15 QC samples.  The standard
deviation of the predicted concentration is equal to the mean-
squared error estimated by the model.
          The precision summary in Table 5-15 indicates that two
compounds (Bis (2-ethylhexyl) phthalate and hexyl acetate) have
CVs above 100%.  These compounds have one extreme observation in
at least one batch, at levels up to four times the value of the
other results within the batch.  Other compounds also show high
variability in the data within each batch, especially between not
detected results and detected results.
                               5-45

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Table 5-14.  Results of Statistical Analysis of QC Data
             on Unspiked Target  Compounds
Compound
Significance
Level of Batch
Effect
'Significance *-
Xt&ft& of Sample
Type Effect
Pesticides
Beta-BHC
Oxychl ordane
0.626
0.009
0.643
0.634
PAHs
Naphthalene
0.545
0.698
Phthalate Esters
Di-n-butyl phthalate
Bis (2-ethylhexyl) phthalate
0.050
0.496
0.073
0.119
Other (qualitative)
1-nonene
1,2, 4 -Trimethylbenzene
Hexyl acetate
0.488
0.144
0.771
0.613
0.199
0.342
                          5-46

-------
    Table  5-15.   Predicted Concentrations  and Coefficients  of
                 Variation for Unspiked Target Compounds
                 at the Control Level
Compound
... ......... M . -•:•-•-- - :•. .• • •-• 	 :•: :• : :•: x .«*•: .-. ..-..•:..•.:• 	 • 	 	
Predicted
Control
Concentration
.(ns/sr).'
Coefficient
of Variation
(%}
Pesticides
Beta-BHC
Oxychlordane (all batches)
Oxychlordane (Batch 1 removed)
213.4
105.9
129.2
76.0
34.1
31.8
PAHs
Naphthalene
9.731
44.9
Phthalate Esters
Di-N-Butyl phthalate
Bis (2-ethylhexyl) phthalate
39.79
309.1
47.3
126.0
Other (qualitative)
1-nonene
1,2,4 - t rimethylbenzene
Hexyl acetate
452.0
36.00
120.6
73.6
77.5
116.1
Note:  These statistics reflect results for all QC samples.

Coefficient of variation  =  Square root of mean-squared error
                                  Predicted concentration
                               5-47

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5.3.4  Conclusions

          The following summarizes the conclusions and findings

of the QC data analysis  (courses of action formulated from these
conclusions are underlined):


     1.   Significant batch effects appear among the 16 spiked
          target compound concentrations.  The primary batch
          effect is due to the high recovery and background in
          Batches 4 and 5 compared to the other three batches.
          Because this difference between "batch classes" is
          prevalent in nearly all of the spiked target compounds,
          it is necessary to include an effect for Batches 4-5
          versus Batches 1-3 in the model used to analyze the
          composite samples.  Any other batch effects were
          assumed to be random and thus were not considered in
          model adjustments.

     2.   The difference between "batch classes" was not as
          significant among the eight unspiked target compounds.
          However, differences in control level concentrations
          between batches were noted for oxychlordane and di-n-
          butyl phthalate.  In particular, nearly every QC and
          composite sample indicated a not-detected result for
          oxychlordane in Batch 1.  As a result, all Batch 1
          concentrations for oxvchlordane will be deleted prior
          to composite data analysis.

     3.   Seven of the target compounds were detected among the
          five method blanks.  All three target phthalates were
          included among these seven compounds.  In particular,
          bis (2-ethylhexyl) phthalate was detected in all four
          method blanks which were analyzed for phthalates.  D-
          limonene and octamethyl-cyclotetrasiloxane, also
          detected in the method blanks, were among those
          compounds with relatively low recoveries.

     4.   High background levels relative to the spiking levels
          were observed for a few spiked target compounds.  In
          particular, the spike levels for p,p-DDE were no more
          than 10% of the observed background level.  For this
          reason, and because of large differences in background
          level among the batches, batch recoveries could not be
          estimated for p,p-DDE.  Other compounds with high
          background levels relative to spiking levels were p,p-
          DDT, heptachlor epoxide, trans-nonachlor,
          hexachlorobenzene, and D-limonene.

     5.   Estimated average recoveries for spiked target
          compounds were significantly below 100% for all but
          p,p-DDT and hexachlorobenzene, where they were
          significantly above 100%.  O-cymene, D-limonene,


                               5-48

-------
          octamethyl-cyclotetrasiloxane, dieldrin, and
          hexachlorobiphenyl had average recoveries below 50%.
          Most estimated batch recoveries for all compounds were
          less than 100% for Batches 1-3, while many compounds
          had estimated batch recoveries above 100% for Batches 4
          and 5.

     6.    Characterization of measurement precision for spiked
          target compounds indicated that better precision was
          observed for pesticides and PCBs.  Precision was worse
          for phthalates and "other" compounds, with coefficients
          of variation  (CVs) exceeding 50%.  For unspiked target
          compounds, CVs ranged from 32 to 126 percent.

     7.    Except for o-cymene and octamethyl-cyclotetrasiloxane
          (which had very low recoveries),  all predicted
          concentrations at the zero spike level were greater
          than zero at the 0.05 significance level.

     8.    The relationship between measured and spiked
          concentrations for spiked target compounds was
          generally linear over the range of spiked
          concentrations, but the variability within each batch
          was high.


          The above findings in the QC data were used to
reevaluate the status of each target compound prior to composite

data analysis.  Several compounds had recovery and contamination
problems as summarized above.  As a result of findings from the
statistical analysis on QC data, the following compounds have

been removed from the list of target compounds on which
statistical analysis of composite data is performed:
Bis (2-ethylhexvl) phthalate

     •  detected  in  all  method blanks analyzed for this
        compound.

     •  low precision results.

Di-n-butvl phthalate

     •  detected  in  two  of  the four analyzed method blanks.

     •  high  levels  of not-detected results among the composite
        samples in Batches  3  and 5 make these batch results
        suspect.
                               5-49

-------
Butyl benzyl phthalate

     •   detected in two of  the  four method blanks analyzed for
         this  compound.

     •   the low-spiked result in Batch  3 was not detected,
         although spiked amounts were  not below  estimated
         background.

1.2,4-Trimethvlbenzene

     •   detected in the method  blank  for Batch  3.

     •   percent detected among  composite samples in Batches 4
         and 5 is very low compared to the other three batches,
         making these batch results suspect.

O-cymene

     •   recoveries extremely low for  all spiked QC samples, even
         though the spiked amounts were  above estimated
         background.   All results for  spiked sampled failed to
         meet  DQOs.

     •   percent detected among  composite samples in Batch 1 is
         low compared to the other batches.

D-limonene

     •   detected in two of the  five method blanks.

     •   recoveries extremely low for  spiked QC  compounds.

Octamethyl-cvclotetrasiloxane

     •   detected in the method  blank  for Batch  3.

     •   recoveries extremely low for  all spiked QC samples, even
         though the spiked amounts were  above estimated
         background.   All results for  spiked samples failed to
         meet  DQOs.

     •   percent detected among  composite samples in Batch 1 is
         low compared to the other batches.  The percentage of
         detected results increased with the batch ID number.


A total of 17  compounds  remained classified as  target compounds

for statistical  analysis following analysis of  the QC data.

However, only  limited analyses  were performed on the qualitative

compounds hexyl  acetate  and 1-nonene.
                               5-50

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6.0  STATISTICAL METHODOLOGY
        This  section discusses  the  statistical methodology
applied in the PY86 NHATS composite sample data analysis.  The  '
statistical analysis of FY86 NHATS data had three objectives:

    •   Estimate  average  concentration levels of target
        semivolatile compounds  in the adipose tissue of
        individuals  in the  U.S. population as well as in various
        demographic  subpopulations.
    •   Estimate  standard errors and construct confidence
        intervals for these average levels.
    •   Perform statistical hypothesis tests to determine if
        average concentration levels of target semivolatiles in
        the U.S.  population differ  significantly by any of four
        demographic  factors (geographic region, age group, race
        group, and sex group).

        The "additive model", a statistical model developed
to estimate average concentration levels in individual specimens
by analyzing NHATS composite data,  was fit to the FY86 data to
address each of the above objectives.   The additive model
involves an iterative weighted generalized least squares method
to estimate model parameters representing demographic effects.
The resulting parameter estimates are approximately normally
distributed for large samples.  This approximate normality is
used to construct confidence intervals and hypothesis tests.
Derivation and validation of the additive model is presented in
Orban and Lordo (1989).
        Section 6.1  briefly presents the additive model and  its
necessary modifications in  analyzing the FY86 data.  The methods
used to obtain estimates of average concentrations for target
compounds, standard errors  for these estimates,  and hypothesis
tests for the significance  of demographic effects on the
concentrations are presented in Section 6.2.
                               6-1

-------
6.1  THE ADDITIVE MODEL
         In order to expand the NHATS to address  a broader range
of compounds, it was necessary to develop mass spectrometry-based
analytical methods  that provided detailed chemical information
and supported method specificity.  These analytical methods
required larger tissue samples than  the available samples from
individual patients.  As a  result, the  individual adipose tissue
specimens were composited prior to chemical analysis.  The
additive model was  developed to achieve the NHATS statistical
objectives under the sample compositing scenario.
         The additive model was used  to  analyze the FY87  NHATS
dioxin and furan concentrations in composite samples  (USEPA,
1991) .  The  FY86 NHATS was  the first  study in which the additive
model was applied to semivolatile composite data.  Orban and
Lordo  (1989) have shown that the additive model has the following
attractive features:

    •    Under very general assumptions,  the  additive  model
         produces asymptotically unbiased estimates of average
         concentration levels  in the  population.
    •    The additive model establishes  a more tractable
         relationship between  the distribution of analyte
         concentrations in. individuals and the distribution of
         measured concentrations from the composite samples.

The latter feature  is particularly important because  individual
specimens are collected, but the chemical analysis is performed
on composite samples.
         Table 6-1  lists  the categories  of the four analysis
factors of interest to the  NHATS.  The additive model assumes
that the four analysis factors have  fixed additive effects on the
average concentrations in specimens.  This assumption subdivides
the population into 48 "subpopulations" defined by the 4x3x2x2=48
unique combinations of categories for the four factors.
                               6-2

-------
        Table 6-1.  NHATS Analysis Factors and Categories
Analysis Factor
Census region
Age group
Race group
Sex group
Category
Northeast
North Central
South
West
0-14 years
15-44 years
45+ years
Caucasian
Noncaucasian
Male
Female
Total Number of Subpopulations
(combinations of the four analysis factors) :
Number of
Categories
4
3
2
2
48
        In addition  to  the  four analysis factors, there are
three ancillary factors that have random effects on NHATS data.
Two of these factors have random effects on the actual
concentration in individual specimens.  They are:

    •   effect of MSA sampling
    •   effect of sampling  individuals within MSAs  (and
        selecting specimens from  individual donors)

The third has a random effect on the measured composite
concentrations:

    •   measurement  error of  compound concentrations  in the
        composite samples.

        A fourth ancillary  factor applied  specifically to the
FY86 composite data  is the  fixed effect of laboratory batches 4
and 5 on the measured composite concentrations.  Analysis of FY86
                               6-3

-------
QC sample data  (Section 5.3)  found significant  differences  for a
majority of  target  compounds  in the measured concentrations for
Batches 4 and 5 versus  those  in the first  three batches.  Thus a
"batch class" factor has been included in  the additive model for
analysis of  FY86  NHATS  semivolatile data on composite samples.
         From these assumptions, the actual concentration C^j^^
in a specimen from  the  ith donor in MSA  j,  census region k,  age
group I, sex m, and race group n,  is represented by
         Cijk
-------
              M
and variance a \ and  is  independent from the distribution of MSAj .
Data analysis results through the history of the NHATS program
have concluded that variation in specimen concentrations is
proportional to the average concentration level.  This finding is
generally true in most  environmental monitoring programs where
chemical concentrations are measured.  Thus if fj.g is the average
concentration level in  subpopulation s, then it is assumed that
for subpopulation s  (s=l, . . . ,48) , there exists a positive number
b such that :
For notational simplicity we let

                  M   =    + CR  + A  + s
                                        m
where the combination of indices k, I, m, and n define
subpopulation s .
        Equation (6-1)  defines  the model for the actual
concentration in a specimen collected in the FY86 NHATS.
However, as specimens are composited prior to chemical analysis,
measured specimen concentrations C^j^^ are not observed.
Instead, data are obtained from the chemical analysis of
composite samples.  Assuming data exist for C composites, and
letting Yh represent the measured concentration of  composite h
(h=l,...,C), the natural additive effects of compositing imply
that

where   C±^g is the actual concentration in specimen i from MSA j
              and subpopulation s,
        Ch(i,j,s) is  equal to  1 if specimen i from MSA j and
              subpopulation s  is in composite h, and is equal to
                               6-5

-------
               zero otherwise,
         Mh is the number of specimens in composite h,
         B45 is the fixed effect of analysis in Batches 4 and 5
               on the composite concentration,
         Ih is equal to 1 if composite h was analyzed in
               Batches 4 or 5,  and is equal to zero otherwise,  and
         yh is random measurement error associated with composite
               h,  assumed to have mean zero and variance a*.

Because  C^s is associated with demographic effects as  specified
in equation (6-1),  equation (6-2)  relates the measured composite
concentrations with the demographic effects in Table  6-1.   Note
that the term B45 has been placed  in the  model  in  (6-2)  as  a
result of the QC data analysis on FY86 NHATS data.  It is  not  a
standard term in the additive  model for all NHATS  applications.
         The statistical analysis performed on the additive model
in  (6-2)  will be explained in  terms of matrix notation. Matrices
are denoted by capital  letters.   Matrices and vectors are  denoted
in bold.   Let

            j8   =  (/z,  CR-L, CR2, CR3,  A-L, A2, S-L, R1,  B45) '

be the 9x1 vector of fixed effects from equations  (6-1) and (6-2)
on the vector of composite concentrations y = (Ylf  Y2,  ..., Yc) ' .
Fixed effects omitted from /8 can be specified as a linear
combination of the  effects in  /8.   Let /* = (/ilf . . . ,/z48) ' be a 48x1
vector containing the unknown  average concentrations  from  the  48
subpopulations.   Then \i is calculated as   \L = X/8  for some 48x9
design matrix X.
         If the QC data analysis (Section 5.3) found the average
concentration in Batches 4-5 to be significantly different from
that for the  first  three batches,  the matrix X is  constructed  so
that \L will depend  on the  effect  B45.   In this  situation, two
average  concentrations  will  be associated with each

                                6-6

-------
subpopulation, one for Batches 4-5 and one for Batches 1-3.  This
is due to potential biases attributed to the results in Batches 4
and 5.
        The  expected value  of the  composite concentrations y is
given by

                  E(y)  =  Zp  =  ZX0  =  D0  ,               (6-3)

where Z is a Cx48 composite design matrix.  Thus, according to
the additive model, both the actual concentrations of the
individual specimens and the measured concentrations of the
composite samples have expected values that are linear
combinations of the additive effects of the fixed analysis
factors in /8.
        Orban  and Lordo  (1989) also show that the variance-
covariance matrix of y (denoted by V )  is a block diagonal matrix
that depends on a2m,  a2f, and o2^.

6.2  STATISTICAL ANALYSIS OF COMPOSITE SAMPLES
        This section describes the specific methods used  to
achieve the statistical objectives.  The estimation methods are
discussed in Section 6.2.1,  and the hypothesis testing procedures
are presented in Section 6.2.2.  This section refers to terms and
symbols presented in Section 6.1.

6.2.1  Estimation

6.2.1.1  Estimating Native Compound Levels.  The specific
quantities estimated for the FY86 NHATS are the average
concentrations in the adipose tissue of the U.S. population and
the average concentrations for each of the eleven "marginal"
demographic populations defined by the categories listed in Table
6-1.  These estimates were calculated in three steps:
                               6-7

-------
    1.   The additive model parameters (vector ft in Section 6.1)
         were estimated using a method called iterative weighted
         generalized least squares (IWGLS) .
    2.   Estimates of average concentration levels in the 48
         subpopulations defined by the four analysis factors
         (vector n in Section 6.1)  were calculated from the
         parameter estimates.
    3 .   National and marginal population estimates were obtained
         by taking weighted averages of the appropriate
         subpopulation estimates in /*.  Weights were proportional
         to the population counts from the 1980 U.S. Census.

         To obtain asymptotically unbiased estimates of the fixed
effects  in /8,  it  is  not  necessary  to  make any assumptions  about
the form of the distributions of the  random  effects in equation
(6-2) .   If the variance -covariance matrix V   of the vector  of
measured composite sample  concentrations y were known,  the  method
of generalized least squares (GLS) produces  estimates  of ft  that
are unbiased and  have minimum variance among all  unbiased
estimates.   Furthermore, if  the errors are normally distributed,
the GLS  estimates are equivalent to the maximum likelihood
estimates.   The GLS  estimate of |8  is  given by

                     J8  =  (D'Vy^-Dj^D'Vy^-y   ,                (6-4)
                                                                 A
where D  is defined in (6-3) .   The  variance -covariance  matrix of  |8
is given by
Unfortunately, V  depends on three unknown variance components
  and aV  from *6~1) and <6~2) '  as wel1 as on the vector
ft.  Therefore, Orban and Lordo  (1989) proposed a method  involving
iterative weighting.  Thus  the method is  called iterative
weighted generalized least  squares  (IWGLS) .
         The IWGLS procedure requires starting values for the
unknown parameters.  These  starting  values were calculated using
                               6-8

-------
the P3V program of the BMDP™ software package.  This program uses
a maximum likelihood procedure in fitting a mixed model.  The
resulting estimate of Vy was then used in the GLS formula to
produce a revised estimate of j8.  The IWGLS procedure provided
continual updating of the estimates for Vy,  continuing until
convergence criteria on the estimate of ft and the error sum or
squares were met.  Orban and Lordo  (1989) discuss this method in
more detail and describe special computer programs in the SAS®
System for implementing IWGLS.  They also provide formulas for
calculating the standard errors of the estimates.
           A
         If ft denotes the final estimate of j8 from the IWGLS
procedure, then an estimate of the average concentration level in
each of the 48 subpopulations is calculated by
                            A      A
                            M   =  X/3 ,
                                                               A
where X is a design matrix.  The variance-covariance matrix of \n
is given by

                EM  =  XE0X'  =  XfD'Vy^-D)'^'

The estimates in ft are affected whenever batch class effects are
present.
        Weighted averages  of  the appropriate subpopulation
concentrations £s are calculated to  estimate  "marginal"  averages
for the categories of each analysis factor.   For example, if the
set of 12 of the 48 subpopulations found in the Northeast census
region is represented by NE, then the estimated average
concentration in the Northeast census region is given by
                                                             (6-5)

where ws is the proportion of total population in the Northeast
census region that is found in subpopulation s  (as determined by
                               6-9

-------
1980 U.S. Census figures).  Marginal estimates were calculated
for four census regions,  three age groups, two race groups, and
two sex groups.  The U.S. population estimate was calculated  in
the same way, with weights corresponding to the proportion of the
U.S. population in each  subpopulation.
         Standard  errors  for the  marginal  estimates  were
calculated based on the  standard errors of the subpopulation
          A           A                                       A
estimates \LB.  If Var(/ig)  indicates  the estimated  variance of  fjL8,
then the standard error  of the marginal estimate of MNE in (6-5)
is given by
                                                             (6-6)

where NE and ws are as defined in  (6-5).  An approximate 95%
confidence interval for each estimate was calculated by adding
and subtracting two times the standard  error of the estimates.

6.2.1.2  Characterizing PCB Results.  Laboratory analysis in the
FY86 NHATS measured the concentrations  of each of the ten PCB
homologs in the composite samples.  These concentration estimates
were integrated to characterize the nature of PCBs detected in
adipose tissue.
         If n±  is  the  average concentration level  (ng/g) of the
ith PCB homolog (only /i4 through HQ were estimated  in  the
statistical analysis), then the characterization considered the
following three sets  of information:

    •    Total  PCB concentration (nq/q)  --  the  sum  of  the
         estimated concentrations  for  each  homolog:

                                     10
                        total  PCB =
                                     •*• -* » •
                                                             (6-7)
                               6-10

-------
        Chlorobiphenvl distribution across homoloaa (%)  -- the
        percentage of the total PCB concentration attributed to
        the  icn homolog  (1=1, ... ,10) :
         chlorobiphenyl    distribution    ,=     f1 p,^* 100%    (6  8)
        Chlorination level (%)  -- the sum of the chlorobiphenyl
        distribution percentages, each weighted by the homolog' s
        chlorine mass fraction (C1MF) :

                                 10
        level  of Chlorination     =  T CIMFf*(   f h^0*10Q04
                                           total  PCB         (6-9)
        These  PCB parameters were estimated by substituting
estimates of the homolog concentrations ni in the above
equations, as obtained from  the statistical analysis  (Section
6.2.1.1).   However, statistical analysis was performed only on
five of the ten PCB homologs  (tetra- through octa-CB) .  The
remaining five homologs were each detected in no more than  30%  of
the FY86 NHATS composite samples.  Thus in estimating the above
PCB parameters, it is assumed that ^1=° f°r 1=1/2,3,9,10.   While
this approach may lead to an underestimate of total PCB
concentration, the extent of underestimation is expected to be
very low.   To estimate the level of Chlorination, the value of
the C1MF is 0.4856 for tetra-CB, 0.5430 for penta-CB, 0.5893-for
hexa-CB, 0.6277 for hepta-CB, and 0.6598 for octa-CB.
        The standard errors  of  the above  PCB parameters  were
calculated from the variability estimates in the average
concentration levels for the individual PCB homologs  (Section
6.2.1.1) .   If ^ is the estimate of fi± as  obtained from the
statistical analysis, then standard error estimates are given as:
                                                            (6-10)
standard error of total PCB;
                                                            (6-11)
standard error of chlorobiphenyl distribution percentages;
                               6-11

-------
SEcn  =
                    100
                 total
                                 >
                          5SE( M
                                               total
standard error of  level of  chlorination
                             \

Approximate 95% confidence bounds  for  the  PCB parameters were
taken as plus and minus  two  standard errors.

6.2.2  Hypothesis Testing
         Hypothesis  tests were performed to determine if average
concentration levels differ  significantly  by any of  the
geographic or demographic factors.  The  specific hypotheses
tested were
H
H
H
H
H
CR:
AGE:
SEX:
RACE:
         CRi  =  CR2 = CR3
         Al = A2 = A3 =
         Sl = S2 = ° '
                                 " CR
                    = R2 = 0
 B45:
                 B
                  45
The hypothesis HCR, for example, states that there are no
differences in average concentration  levels among  the  four  census
regions.  Each hypothesis was  two-tailed;  that  is, each
alternative was that at least  one effect was nonzero and
different from the others.
         In  order to test  these hypotheses, it  was necessary to
make specific distribution  assumptions  for the  random  effects.
It was assumed that the errors associated  with  sampling MSAs,
                               6-12

-------
sampling individuals within MSAs, and measuring concentrations
were independent and normally distributed.  The additive effect
of compositing specimens suggests that the normality assumption
is reasonable because specimen sampling errors are averaged in
the composite sample.  Statistical theory states that averages
and sums are approximately normally distributed.  Distributional
assumptions were tested for all target compounds using
probability plots and residual analysis.
        The  likelihood  ratio method was used to test the above
hypotheses.  In this process,  the additive model is fit to the
observed data both including and excluding the effects to be
tested.  According to asymptotic theory, the log of the ratio of
the likelihood functions from these two fits has approximately a
chi-squared distribution, with degrees of freedom equal to the
number of independent parameters constrained under the null
hypothesis.  Orban and Lordo (1989) developed programs in the
SAS® System to perform these tests.
                               6-13

-------
7.0  RESULTS
         This  section contains the  results of  the statistical
analysis of the FY86 NHATS for semivolatiles in human adipose
tissue.  The applied statistical methods were discussed in
Chapter 6.  The objectives of the statistical analysis were as
follows:

    •    Estimate  average concentration  levels of target
         compounds for individuals  in  the U.S. population and  in
         various subpopulations;
    •    Calculate standard errors  and confidence bounds on these
         average levels;
    •    Perform statistical  hypothesis  tests  to determine if
         average levels differ significantly between various
         levels of demographic factors of interest.

Statistical analysis was performed on data obtained from
laboratory analysis of 50 composite samples.   The composites were
prepared using a total of 671 adipose tissue specimens from
sampled cadavers and surgical patients.   Each composite contained
from three to 24 specimens, with an average of 13.4 specimens per
composite.  The specimens within each sample originated from a
common census division and age group but may have differed among
sex and race groups.  Additional information on sample and
composite design is presented in Chapters 2 and 3.
        A descriptive  summary of the  observed concentrations  for
the 111 semivolatiles is provided in Section 7.1.   Statistical
analysis  was performed only on "target"  semivolatiles (identified
in Chapter 5)  that were detected in a majority of the 50
composite samples and which met specific data quality objectives.
Resulting from this statistical analysis,  estimates of average
subpopulation concentrations are presented in Section 7.2,  along
with standard errors and confidence bounds on these estimates.
Section 7.3 presents the results of statistical hypothesis
testing to identify significant effects of demographic factors on
average concentration levels.  Section 7.4 describes the outlier
                               7-1

-------
detection procedures that  identified potential data errors to be
corrected prior to conducting the statistical analysis.  Finally,
as part of the commitment  to overall data quality in this
program, procedures were implemented to demonstrate the validity
of the statistical methodology applied to the FY86 NHATS data.
The results of this data validation procedure are presented in
Section 7.5.
         Unless otherwise specified,  all  statistical  analyses
were performed on composite concentrations adjusted for
recoveries of surrogate compounds.  This adjustment, discussed in
Section 5.2, corrected for systematic error identifiable through
the surrogate recovery data.

7.1  DESCRIPTIVE STATISTICS
         Prior to statistical  modelling of  target  compounds,
simple descriptive statistics were generated on the measured
concentrations for all 111 semivolatiles analyzed in the NHATS
FY86 campaign.  These statistics summarized the laboratory
results across all 50 FY86 composite samples and consisted of the
following:

    •    arithmetic  average;
    •    standard deviation;
    •    standard error  of  the average;
    •    percent  of  samples with detected results  (duplicated
         from Table  5-1);
    •    average  level of detection  (LOD).

Table 7-1 presents these statistics across the 111 semivolatiles
for measured concentrations adjusted for surrogate recoveries, as
well as on the unadjusted  concentrations.
        A compound  is detected within a  composite sample  if the
result is classified as either a trace or positive quantifiable
reading.  Prior to summarizing the data for a given compound,  the
measured concentrations for all samples with not-detected
outcomes were replaced by  one-half of the reported LOD.  While
the LOD itself was not adjusted for surrogate recoveries,  the
                               7-2

-------
                Table 7-1.  Descriptive Statistics of NHATS FY86 Semivolatile Compound Concentrations
                            Based on All  50 Composite Sanples(1)
u>
Unadjusted Cone.® (ncr/a)
Compound ID Number Percent
and Name Detected
Avg.
LOD
(ng/g)
Avg.
Cone.
Std.
Dev.
Std.
Error
of Avg.
Adiusted Cone.®
,Avg .
Cone.
Std.
Dev.
(ncr/cr)
Std.
Error
of Avg.
PESTICIDES
1
2
3
3
4
S
6
7
8
9
10
11
12
13
14
15
16
60
60
61
62
P,P-DDT
O,P-DDT
P,P-DDE (M/Z=288)
P,P-DDE (M/Z=316)
O,P-DDE
O,P-DDD
ALPHA- BHC
BETA-BHC
DELTA-BHC
GAMMA- BHC (LINDANE)
ALDRIN
HEPTACHLOR
HEPTACHLOR EPOXIDE
OXYCHLORDANE
TRANS -NONACHLOR
GAMMA- CHLORDANE
MIREX
DIELDRIN
DIELDRIN (CORRECTED)
ENDRIN
ENDRIN KETONE
96
0
100
100
0
0
0
92
0
4
0
0
94
78
92
0
32
12
62
0
2
9.
10.


13.
13.
11.
30.
12.
11.
11.
35.
31.
20.
26.
10.
10.
123.

146.
85.
14
9


7
5
0
8
3
7
6
2
9
0
9
8
9



3
227
5
3010
2950
6
6
5
209
6
8
5
17
81
123
161
5
12
70
54
72
43
m
.46
.
.
.87
.75
.50
.
.15
.74
.79
.6
.3
.
.
.41
.1
.0
.3
.8
.4
264.
4.99
2570.
2990.
6.29
6.17
5.04
142.
5.63
17.3
5.26
84.2
46.5
86.
122.
4.95
12.2
54.6
58.8
56.6
33.2
37.
0.71
360.
420.
0.89
0.87
0.71
20.
0.80
2.45
0.74
11.9
6.6
12.
17.
0.70
1.7
7.7
8.3
8.0
4.7
200.
4.79
2650.
2590.
6.03
5.93
4.83
184.
5.40
9.01
5.08
15.5
63.7
108.
141.
4.75
10.6
61.5
47.7
64.0
38.2
216.
4.08
2100.
2440.
5.13
5.04
4.11
116.
4.60
16.3
4.30
68.7
33.1
70.
99.
4.04
10.0
44.6
48.0
46.2
27.1
31.
0.58
300.
350.
0.73
0.71
0.58
16.
0.65
2.30
0.61
9.7
4.7
10.
14.
0.57
1.4
6.3
6.8
6.5
3.8
CHLOROBENZBNBS
17
18
19
20
21
22
23
1 , 3 -DICHLOROBENZENE
1 , 4 -DICHLOROBENZENE
1 , 2 -DICHLOROBENZENE
1,2, 3 -TRICHLOROBENZENE
1 , 2 , 4 -TRICHLOROBENZENE
1,3, 5 -TRICHLOROBENZENE
1,2,3,4- TETRACHLOROBENZENE
0
86
0
0
0
0
0
10.
16.
10.
11.
10.
11.
11.
1
7
3
8
2
1
7
5
78
5
5
5
5
5
.04
.4
.14
.88
.08
.53
.84
4.62
75.6
4.63
5.38
4.65
5.06
5.35
0.65
10.7
0.66
0.76
0.66
0.72
0.76
6.65
103.
6.77
9.48
8.19
8.92
7.62
5.67
93.
5.69
7.89
6.82
7.43
6.48
0.80
13.
0.80
1.12
0.96
1.05
0.92

-------
Table 7-1.  (cont.)
Unadjusted Conc.^ (na/a)
Compound ID Number Percent
and Name Detected
Avg.
LOD
(ng/g)
Avg.
Cone.
CHLOROBENZENES
24
25
26
27

41
42
43
44
45
46
47
48
49

50
51
52
53
54
55
56
57
58
59
1,2,3, 5-TETRACHLOROBENZENE
1,2,4, 5-TETRACHLOROBENZENE
PENTACHLOROBENZENE
HEXACHLOROBENZENE

NAPHTHALENE
ACENAPHTHALENE
ACENAPHTHENE
FLUORENE
PHENANTHRENE
FLUORANTHENE
PYRENE
CHRYSENE
BENZO (A) PYRENE

MONOCHLOROBIPHENYLS
DICHLOROBIPHENYLS
TRICHLOROBIPHENYLS
TETRACHLOROBIPHENYLS
PENTACHLOROBIPHENYLS
HEXACHLOROB I PHENYLS
HEPTACHLOROBIPHENYLS
OCTACHLOROBIPHENYLS
NONACHLOROBIPHENYLS
DECACHLOROBIPHENYL
0
0
0
98

84
0
0
0
8
2
0
4
0

0
0
30
66
88
94
86
44
26
28
11.6
10.8
10.1
33.0

13.6
11.0
10". 7
12.2
11.1
10.7
10.2
10.7
9.81

12.8
13.0
20.2
69.6
65.0
110.
65.8
33.9
32.3
43.7
5
5
5
54
PAHs
20
5
5
6
5
5
5
5
4
PCBS
6
6
16
88
188
422
176
60
25
32
Std.
Dev.
Std.
Error
of Avg.
Adi us ted Cone.*3*
Avg.
Cone.
(na/cr)
Std.
Std. Error
Dev. of Avg.
(cont. )
.79
.38
.04
.7

.5
.51
.36
.09
.92
.44
.11
.61
.91

.41
.49
.5
.1
f
.
.
.7
.7
.6
5.30
4.93
4.62
36.5

17.9
5.04
4.90
5.58
5.14
4.90
4.68
4.99
4.49

7.42
7.48
14.7
75.8
151.
296.
188.
78.7
29.2
30.3
0.75
0.70
0.65
5.2

2.5
0.71
0.69
0.79
0.73
0.69
0.66
0.71
0.63

1.05
1.06
2.1
10.7
21.
42.
27.
11.1
4.1
4.3
7
7
6
55

20
5
5
6
5
5
5
5
4

6
5
14
70
157
351
146
51
23
31
.56
.02
.65
.1

.3
.46
.31
.04
.87
.39
.06
.56
.86

.25
.84
.8
.1
•
.
.
.9
.1
.1
6.42
5.97
5.67
34.6

17.3
4.87
4.74
5.39
4.97
4.73
4.52
4.82
4.34

6.84
6.14
12.0
56.1
115.
226.
143.
60.4
24.0
25.0
0.91
0.84
0.80
4.9

2.4
0.69
0.67
0.76
0.70
0.67
0.64
0.68
0.61

0.97
0.87
1.7
7.9
16.
32.
20.
8.5
3.4
3.5

-------
                                                 Table 7-1.   (cont.)
                                                            Unadjusted Cone.*2*  (ng/g)
                                                                                     Adiusted Cone.*3*  (ng/g)

Confound ID Number
and Name

Percent
Detected
Avg.
LOD
(ng/g)
Std.
Avg . Std . Error
Cone. Dev. of Avg.
Std.
Avg. Std. Error
Cone. Dev. of Avg.
Ul
                                                   PHTHALATB ESTERS
     63  DIMETHYL  PHTHALATE
     64  DIETHYL PHTHALATE
     65  DI-N-BUTYL PHTHALATE
     66  BUTYL BENZYL PHTHALATE
     67  BIS  (2-ETHYLHEXYL)  PHTHALATE
68  TRIBUTYL PHOSPHATE                0
69  TRIS (2-CHLOROETHYL) PHOSPHATE    0
70  TRIS (2,3-DIBROMOPROPYL)
       PHOSPHATE                      0
71  TRIPHENYL PHOSPHATE               4
72  TRITOLYL PHOSPHATE                2
      28  BIPHENYL                         0
      29  l,2-DIBROMO-3-CHLORO PROPANE     0
      30  HEXACHLORO BUTADIENE             0
      31  HEXACHLORO CYCLOPENTADIENE       0
      32  2,2',4',5-TETRABROMO BIPHENYL    0
      33  O-CYMENE                        80
      34  D-LIMONENE                      96
      35  D,L-ISOBORNEOL                   0
      36  1-INDANONE                       0
      37  2-INDANONE                       0
      38  BUTYLATED HYDROXYTOLUENE        18
      39  COUMARIN                         0
      40  OCTAMETHYL-CYCLOTETRASILOXANE   72
      73  ETHYL HYDROCINNAMATE             2
27.1
27.9
23.6
26.6
27.4
13.6
17.9
63.0
58.0
1010.
10.5
19.1
117
52.4
3930.
PHOSPHATE TRIESTBRS
115.
139.
137.
50.7
48.0

9.68
11.7
12.0
10.3
12.4
17.7
11.7
11.3
11.2
10.7
11.3
10.7
17.8
57.3
57.7
69.4
68.5
30.4
24.3
OTHER
4.84
5.83
5.98
5.16
6.22
21.0
264.
5.66
5.59
5.34
11.8
5.34
46.7
29.1
44.8
54.0
53.2
40.3
18.6

4.43
5.34
5.48
4.73
5.70
14.9
174.
5.18
5.12
4.89
24.5
4.89
56.5
22.2
6.3
7.6

7.5
5.7
2.6
                                                                          0.63
                                                                          0.75
                                                                          0.77
                                                                          0.67
                                                                          0.81
                                                                          2.1
                                                                         25.
                                                                          0.73
                                                                          0.72
                                                                          0.69
                                                                          3.5
                                                                          0.69
                                                                          8.0
                                                                          3.1
13.1
17.2
60.8
55.9
975.
55.6
67.0
66.0
29.3
23.5
4.67
5.62
5.76
4.98
6.00
20.3
254.
5.45
5.39
5.15
11.4
5.15
45.1
28.0
9.5
17.2
105
47.2
4E3.
40.4
48.6
48.0
36.3
16.8
3.99
4.81
4.93
4.26
5.13
13.4
157.
4.66
4.61
4.40
22.1
4.41
50.9
20.0
1.3
2.4
14.9
6.7
500.
5.7
6.9
6.8
5.1
2.4
0.56
0.68
0.70
0.60
0.73
1.9
22.
0.66
0.65
0.62
3.1
0.62
7.2
2.8

-------
Table 7-1.  (cont.)
Unadiusted Cone.®
Avg.
Compound ID Number Percent LOD
and Name Detected (ng/g)

74
75

76
77
78

2 -METHOXY- 3 -METHYLPYRAZINE
2,2' ,4,4' ,5-PENTACHLORO
DIPHENYL ETHER
4 - CHLORO- P - TERPHENYL
TRICHLORO - P - TERPHENYL
2-PHENYL PHENOL

0

0
0
0
24

50.

5.
40.
62.
24.
OTHER
5

97
8
3
0
PESTICIDES
85
86
98
99
100
101
102
106
107
ISOPHORONE
DICHLOROVOS
CHLORPYRIFOS
ISOPROPALIN
BUTACHLOR
NITROFEN
PERTHANE
DICOFOL
P . P ' -METHOXYCHLOR
16
2
28
10
12
8
0
6
0
5.
5.
5.
10.
5.
5.
10.
5.
10.
CHLORINATED
88
89
90
91
92
95
96
97
110
2,4,6 -TRICHLOROANISOLE
2,4,6 -TRICHLOROPHENOL
2,4, 5 -TRICHLOROPHENOL
2,3, 6 -TRICHLOROANISOLE
2,3, 6 -TRICHLOROPHENOL
PENTACHLOROANISOLE
PENTACHLORONITROBENZENE
2 , 3 , 4 -TRICHLOROANISOLE
OCTACHLORONAPHTHALENE
0
0
0
0
0
2
0
4
2
10.
10.
10.
10.
10.
10.
5.
10.
10.
00
00
00
0
00
00
0
00
0
Avg.
Cone.
(cont.)
25.3

2.99
20.4
31.1
93.7
(nq/q)
Std.
Std. Error
Dev. of Avg.

19.6

2.32
15.8
24.2
295

2.8

0.33
2.2
3.4
41.7
Adi us ted Cone.*3*
Avg.
Cone.

24

2
19
30
90

.4

.88
.7
.0
.4
(nq/q)
Std.
Std. Error
Dev. of Avg.

17.7

2.09
14.3
21.8
265

2.5

0.30
2.0
3.1
37.5
(QUALITATIVE) w
5.50
3.65
7.00
5.50
9.60
16.1
5.00
11.2
5.00
13.9
8.13
9.01
1.52
31.2
59.1
0.00
44.2
0.00
1.96
1.15
1.27
0.21
4.41
8.4
0.0
6.2
0.0
4
3
6
4
8
14
4
9
4
.83
.21
.15
.83
.44
.1
.39
.80
.39
11.3
6.64
7.35
1.24
25.4
48.3
0.00
36.1
0.00
1.60
0:94
1.04
0.17
3.60
6.8
0.0
5.10
0.0
AROMATICS (QUALITATIVE) (4)
0
0
0
0
0
0
00
0
0
5.00
5.00
5.00
5.00
5.00
5.10
2.50
10.0
5.30
0.00
0.00
0.00
0.00
0.00
0.71
0.00
28.5
2.12
0.0
0.0
0.0
0.0
0.0
0.10
0.0
4.0
0.30
4
4
4
4
4
4
2
9
5
.82
.82
.82
.82
.82
.92
.41
.64
.11
0.00
0.00
0.00
0.00
0.00
0.64
0.00
25.7
1.91
0.0
0.0
0.0
0.0
0.0
0.09
0.0
3.63
0.27

-------
                                                  Table 7-1.   (cont.)
-J
 i
-o
Unadjusted Cone.® (ncr/cr)
Compound ID Number Percent
and Name Detected

105
108
109
111

79
80
81
82
83
84
87
93
94
103
104

BENZO (A) ANTHRACENE
BENZO (B) FLUORANTHENE
BENZO (K) FLUORANTHENE
DIBENZO (A,H) ANTHRACENE

1-NONENE
CUMENE
1,2, 4 -TRIMETHYLBENZENE
HEXYL ACETATE
1 , 3 -DIETHYLBENZENE
1 , 4 -DIETHYLBENZENE
QUINOLINE
DIBENZOFURAN
CHLORDANE
CHLOROBENZYLATE
BIS (2-ETHYLHEXYL) ADIPATE

26
10
4
0

50
34
62
82
8
0
8
0
2
0
10
Avg.
LOD
(ng/g)
PAH'S
5.00
5.00
5.00
5.00
OTHER
20.0
5.00
5.00
5.00
10.0
10.0
10.0
20.0
10.0
10.0
9.89
Avg.
Cone.
(QUALITATIVE)
4
3
8
2
.45
.79
.60
.50
(QUALITATIVE)
112
11
39
132
6
5
15
10
6
5
11
.
.9
.5
.
.20
.00
.6
.0
.90
.00
.9
Std.
Dev.
(4)
3.32
4.76
42.1
0.00
(4)
173.
28.7
43.7
166.
4.11
0.00
57.2
0.0
13.4
0.00
22.0
Std.
Error
of Avg.

0.47
0.67
5.95
0.0

24.
4.1
6.2
23.
0.58
0.0
8.1
0.0
1.90
0.0
3.1
Adjusted Cone.0)
Avg.
Cone.

4
3
8
2

108
11
38
128
5
4
15
9
6
4
11

.29
.66
.29
.41

.
.4
.1
.
.98
.82
.0
.64
.65
.82
.4
(nq/cr)
Std.
Std. Error
Dev. of Avg.

2.99
4.29
37.9
0.00

156.
25.9
39.4
149.
3.70
0.00
51.5
0.00
12.1
0.00
19.8

0.42
0.61
5.36
0.0

22.
3.7
5.6
21.
0.52
0.0
7.3
0.0
1.71
0.0
2.8
     (1)  Descriptive statistics are  simple  averages,  standard deviations,  and standard errors of the average
     using standard statistical formulas.  Concentration statistics expressed in ng/g.  Concentrations for not
     detected results are replaced by one-half of the detection limit  (LOD) prior to calculating statistics.
     Data for all 50 composite samples are included in the statistics for all compounds.
     (2)
Concentrations as reported by the laboratory, without adjustment for surrogate recoveries  (Section  5.2)
     0)  Concentrations are adjusted  for  surrogate  recoveries  (Section 5.2).   These  adjusted concentrations are
     used in further statistical analyses for 17 target compounds  (Sections 7.2 through 7.3).
     (4)
Qualitative compounds were only monitored for detection versus non-detection.

-------
modified measured concentration was  adjusted.  No LOD was
reported for detected compounds within a  sample.  The percentage
of  samples  in each of three qualifier  classifications  (not
detected, trace,  and positive  quantifiable) was summarized in
Table  5-1 of Chapter 5.
         Appendix E contains the minimum,  median,  and maximum
reported concentrations  across the 50  composite samples for  each
of  the 111  compounds.  These statistics are based on
concentrations which are unadjusted  for surrogate recoveries.
         The descriptive statistics in Table 7-1  are based on
simple averages of the measured concentrations within the 50
composite samples.   As such they only  summarize the observed
data.   They should not be used to estimate concentration levels
within the  population.   Statistical  analyses were implemented to
obtain population average estimates  for seventeen target
semivolatiles meeting specific data  quality objectives.  The
results of  these  analyses are  presented in the following
section^.

7.2  POPULATION ESTIMATES FROM STATISTICAL MODELLING
         The statistical  modelling techniques  presented  in
Chapter 6 were used to determine estimates of average
concentrations for selected semivolatiles within subpopulations
as well as  for the entire nation, to obtain estimates of
uncertainty inherent  in  these  estimates, and to identify where
significant differences  in average concentration were present
among  subpopulations.  These techniques centered around the
additive model, which  was used to estimate average concentration
for individuals as  a  function  of several demographic factors.
The results from  fitting the additive  model to the NHATS FY86
composite data are  presented in this section.
         Not all of the compounds analyzed in  the  FY86 NHATS
analysis provided sufficient composite  concentration data to
warrant a meaningful statistical analysis.  Seventeen of the 111
compounds were  identified as containing a sufficient number of
                                7-8

-------
detected samples and whose analytical measurements were deemed
accurate in reflecting the true concentration level.  Having a
sufficient number of composite samples with detected results
ensured that only minimal bias was generated by substituting one-
half of the detection limit for the measured concentration
whenever the compound was not detected by the analytical method.
Method performance was determined from analysis of the QC data
(Section 5.3), which indicated the presence of batch effects and
the extent that anomalous analytical results were reported.  The
compounds selected for statistical modelling, as well as the
criteria used to select them, were identified in Chapter 5.
        Fitting the  additive  model to the NHATS FY86 data  for 17
semivolatiles resulted in average concentration estimates for the
entire U.S. population, as well as "marginal" estimates for each
of the categories defined by the four analysis factors presented
in Table 6-1  (census region, age group,  race group, and sex
group).   The formula for calculating marginal estimates was given
in equation (6-5) of Section 6.2.1.  The estimates are presented
in Table 7-2 for the four census regions, Table 7-3 for the three
age groups, Table 7-4 for the two race groups, and Table 7-5 for
the two sex groups.  Table 7-6 presents estimated concentration
estimates for the entire nation.  The estimates are
asymptotically unbiased and were adjusted for the presence of
laboratory batch effects  (Batches 1-3 versus 4-5)  and for
population percentages based on the 1980 U.S. Census.
        Accompanying the  marginal  estimates  based  on the
additive model, standard errors and approximate 95% confidence
intervals of these estimates are displayed in Tables 7-2 through
7-6.  The standard errors were calculated using equation (6-6)  of
Section 6.2.1 and are used to characterize the statistical
uncertainty in the estimated average concentrations.  The
standard errors are presented in both absolute and relative
terms.  The confidence intervals represent the marginal estimate,
plus and minus approximately  two standard errors.  The actual
                                7-9

-------
Table 7-2.  Estimates of Average Concentrations^  for Selected Semivolatiles, with Standard Errors
            and Approximate 95% Confidence Intervals, According  to Census Region
            from HEATS PT86 Composite Samples
Compound Census Region

p.p-DDT North Central
North East
South
West
p.p-DDE® North Central
North East
South
West
Beta-BHC North Central
North East
South
West
Heptachlor epoxide North Central
North East
South
West
Oxychlordane^ North Central
North East
South
West
Trans -nonachlor North Central
North East
South
West
Estimated
Average
Cone.
(ng/g)
Pesticides
136.
273.
132.
202.
1820.
2310.
2240.
3240.
151.
157.
177.
130.
63.5
48.4
70.5
37.7
104.
107.
126.
113.
89.2
156.
154.
116.
Absolute
Standard
Error of
Estimate
(ng/g) .

23.7
56.6
23.1
50.7
307.
491.
358.
938.
42.7
54.6
42.8
55.2
7.37
9.14
7.34
9.37
13.0
15.3
13.9
15.0
26.2
33.5
26.2
33.8
Relative
Standard
Error of
Estimate
(%)

17.5
20.7
17.5
25.1
16.8
21.3
16.0
28.9
28.2
34.7
24.2
42.6
11.6
18.9
10.4
24.8
12.5
14.3
11.1
13.3
29.4
21.5
17.0
29.2
95% Confidence
Interval (ng/g)

( 87.8,
( 159.,
( 85.2,
( 99.5,
(1202.,
(1314.,
(1521.,
(1346.,
( 65.0,
( 47.2,
( 90.4,
( 18.2,
( 48.6,
( 30.0,
( 55.6,
( 18.8,
( 77.8,
( 75.9,
( 97.5.
( 82.2.
( 36.3,
( 88.1,
( 102.,
( 47.4,

184.)
388.)
178.)
304.)
2440.)
3299.)
2968.)
5134.)
237.)
268.)
263.)
241.)
78.3)
66.9)
85.3)
•56.6)
131.)
138.)
154.)
143.)
142.)
223.)
207.)
184.)

-------
                                          Table 7-2.  (cant.)



Compound

Estimated
Average
Cone.
Census Region (ng/g)
Absolute
Standard
Error of
Estimate
(ng/g)
Relative
Standard
Error of
Estimate
(%)


95% Confidence
Interval (ng/g)
Dieldrinw
1,4-Dichlorobenzene
Hexachlorobenzene
Naphtha!ene
 Tetrachlorobiphenyl
North Central
North Bast
South
West
North Central
North East
South
West

North Central
North East
South
West
North Central
North East
South
West
North Central
North East
South
West
Pesticides  (cant.)

       57.3
       42.7
       37.3
       54.8
       PAH*

       12.7
       18.8
       27.3
       22.1

       PCBs

       66.2
       78.8
       46.9
       34.0
13.6
17.4
13.7
17.6
98.1
77.4
126.
35.7
41.2
57.6
41.7
74.7
26.1
33.4
26.2
33.7
5.40
8.81
5.50
13.6
 2.49
 4.47
 4.80
 6.07
 8.59
11.6
 7.91
10.6
23.8
40.8
36.6
32.2
                                  26.6
                                  43.1
                                  20.8
                                  94.5

                                  13.1
                                  15.3
                                  13.2
                                  18.2
19.6
23.8
17.6
27.5
13.0
14.7
16.9
31.2
(  29.8,   84.8)
(   7.54,  77.9)
(   9.74,  64.9)
(  19.2,   90.4)
                           (  45.4,   151.)
                           {    9.98,  145.)
                           (  72.9,   179.)
                           (    0.0,   104.)

                           (  30.3,    52.1)
                           (  39.8,    75.4)
                           (  30.6,    52.9)
                           (  47.2,   102.)
(    7.68,   17.7)
(    9.74,   27.8)
{   17.6,    37.0)
(    9.85,   34.4)
(   48.9,    83.6)
(   55.4,   102.)
(   30.9,    62.9)
(   12.6,    55.4)

-------
                                                 Table 7-2.   (cont.)
to
Compound
Census Region
Estimated
Average
Cone.
(ng/g)
Absolute
Standard
Error of
Estimate
(ng/g)
Relative
Standard
Error of
Estimate
95% Confidence
Interval (ng/g)
PCBs (cont.)
Pentachlorobiphenyl



Hexachlorobiphenyl



Heptachlorobiphenyl



Octachlorobiphenyl



Total PCBs(5)



Level of Chlorination(6)



North Central
North East
South
West
North Central-
North East
South
West
North Central
North East
South
West
North Central
North East
South
West
North Central
North East
South
West
North Central
North East
South
West
165.
202.
107.
64.2
282.
430.
299.
250.
101.
213.
109.
85.5
33.7
75.3
33.4
33.9
648.
998.
595.
468.
57.7%
. 58.5%
58.4%
58.8%
26.2
33.5
26.3
33.9
29.8
47.0
30.1
40.6
37.6
48.1
37.7
48.6
19.9
25.4
19.9
25.7
58.8
80.2
59.0
77.0
6.17%
5.44%
6.84%
11.5%
15.9
16.6
24.6
52.8
10.6
10.9
10.1
16.2
37.2
22.6
34.6
56.8
58.9
33.7
59.6
75.6
9.07
8.03
9.91
16.5
10.7
9.32
11.7
19.5
( 112.,
( 134.,
( 54.0,
( 0.0,
( 221.,
( 335.,
( 238.,
( 168.,
( 25.2,
( 116.,
( 32.8,
( o.o,
( o.o,
( 24.1,
( 0.0,
( 0.0,
( 531.,
( 838.,
( 477.,
( 314.,
( 45.3%,
( 47.6%,
( 44.7%,
( 35.8%,
218.)
269.)
160.)
133.)
342.)
525.)
360.)
332.)
177.)
310.)
185.)
184.)
73.9)
127.)
73.6)
85.8)
766.)
1160.)
713.)
622.)
70.0%)
69.4%)
72.1%)
81.7%)

-------
                                                  Table 7-2.  (cont.)
i
M
U)

Compound
Census Region
Absolute Relative
Estimated Standard Standard
Average Error of Error of
Cone. Estimate Estimate 95% Confidence
(ng/g) (ng/g) (%) Interval (ng/g)
Other (qualitative)








(i)

(2)
(3)
(4)
(5)

(6)

1-Nonene



Hexyl acetate



North
North
South
West
North
North
South
West
Central
East


Central
East


92.2
214.
118.
73.9
80.0
142.
171.
76.0
Data adjusted for surrogate recoveries (see Section 5.
Estimates are based on
1980 U.S. Census
p,p-DDE concentrations use the
Data results from Batch
Corrected (see Section 5
figures .
following response ion:
1 not included in
.1.2) .
The estimate for Total PCBs is
table (i.e., homologs detected
Estimated percent level


the sum of
calculations

87.
112.
87.
113.
36.
47.
37.
47.
2).

m/z=316.
m

5

7

9
2
1
7





the estimated averages
in at least 44% of the
of chlorination is calculated


8
NHATS FY86
as follows :


94.
52.
74.
153
46.
33.
21.
62.





9 (
3 (
4 (
(
1 (
2 (
7 (
8 (





over the five homologs
0.
0.
0.
0.
5.
47.
96.
0.





0,
0,
0,
0,
45,
0,
0,
o,





included
269.)
440.)
295.)
302.)
154.)
238.)
246.)
172.)





in this
composite samples) .










         where A; = estimate of the percent of total PCBs for homolog i,
         and   Bj = mass fraction of chlorine for homolog i.
         (Only the five PCB homologs included in the table are considered in calculating level of chlorination.)

-------
         Table 7-3.   Estimates of Average Concentrations^ for Selected Semivolatiles, with Standard Errors
                     and Approximate 95%  Confidence Intervals, According to Age Group
                     from NHATS FY86 Composite Samples
i
H
Compound Age Group

p,p-DDT 0-14 years
15-44 years
45+ years
p,p-DDE® 0-14 years
15-44 years
45+ years
Beta-BHC 0-14 years
15-44 years
45+ years
Heptachlor epoxide 0-14 years
15-44 years
45+ years
Oxychlordane^ 0-14 years
15-44 years
45+ years
Trans -nonachlor 0-14 years
15-44 years
45+ years
Dieldrin(4) 0-14 years
15-44 years
45+ years
Estimated
Average
Cone.
(ng/g)
Pesticides
73.0
177.
252.
1710.
2150.
3080.
100.
124.
247.
32.6
51.8
84.7
52.7
119.
150.
62.5
115.
203.
67.9
41.9
39.4
Absolute
Standard
Error of
Estimate
(ng/g)

26.6
29.2
32.9
380.
360.
412.
52.4
41.0
35.9
7.57
6.11
5.48
16.0
12.2
11.1
32.1
25.2
22.0
16.7
13.1
11.5
Relative
Standard
Error of
Estimate
(%)

36.4
16.5
13.1
22.1
16.8
13.4
52.3
33.0
14.5
23.2
11.8
6.5
30.5
10.2
7.4
51.4
21.8
10.8
24.6
31.3
29.1
95% Confidence
Interval (ng/g)

( 19.4,
( 118.,
( 186.,
( 948.,
(1420.,
(2247. ,
( o.o,
( 41.5,
( 175.,
( 17.3,
( 39.4,
( 73.6,
( 19.9,
( 94.3,
( 128.,
( o.o,
( 64.4,
( 158.,
( 34.1,
( 15.4,
( 16 . 2 ,

127.)
236.)
319.)
2481.)
2876.)
3911.)
206.)
207.)
320.)
47.9)
64.1)
95.7)
85.4)
144.)
173.)
127.)
166.)
247.)
102.)
68.4)
62.5)

-------
                                                  Table 7-3.   (cont.)
-J
 i
H
in
Compound
Age Group
Estimated
Average
Cone.
(ng/g)
Absolute
Standard
Error of
Estimate
(ng/g)
Relative
Standard
Error of
Estimate
(%)
95% Confidence
Interval (ng/g)
Chlorobenzenes
1 , 4 -Dichlorobenzene
Hexachlorobenzene

Naphthalene

Tetrachlorobiphenyl
Pentachlorobiphenyl
Hexachlorobiphenyl
Heptachlorobiphenyl
0-14 years
15-44 years
45+ years
0-14 years
15-44 years
45+ years

0-14 years
15-44 years
45+ years

0-14 years
15-44 years
45+ years
0-14 years
15-44 years
45+ years
0-14 years
15-44 years
45+ years
0-14 years
15-44 years
45+ years
101.
66.2
120.
35.0
47.0
69.8
PAHS
24.5
18.8
20.7
PCBs
19.4
41.8
105.
75.6
107.
218.
101.
306.
481.
26.9
112.
217.
32.1
25.1
21.9
6.64
5.83
6.45

5.59
3.19
2.96

9.00
7.41
8.31
32.2
25.2
22.1
29.2
30.0
32.5
46.2
36.2
31.6
31.6
37.9
18.2
19.0
12.4
9.3

22.9
16.9
14.3

46.3
17.7
7.9
42.6
23.5
10.1
29.0
9.8
6.8
171
32.4
14.6
( 36.7,
( 15.6,
( 76.0,
( 21.5,
( 35.2,
( 56.7,

( 13.2,
( 12.4,
( 14.7,

( 1.27,
( 26.9,
( 88.5,
( 10.5,
( 56.5,
( 174.,
( 41.8,
( 245.,
( 415.,
( 0.0,
( 38.5,
( 153.,
166.)
117.)
165.)
48.4)
58.8)
82.8)

35.7)
25.3)
26.6)

37.6)
56.8)
122.)
141.)
158.)
263.)
160.)
367.)
546.)
120.)
185.)
281.)

-------
                                                  Table 7-3.   (cont.)
i
H
0\















Compound

Octachlorobiphenyl


Total PCBs(5)


Level of Chlorination(6)




Age Group

0-14 years
15-44 years
45+ years
0-14 years
15-44 years
45+ years
0-14 years
15-44 years
45+ years
Estimated
Average
Cone.
(ng/g)
PCBs (cont.
20.9
28.8
79.5
244.
596.
1100.
57.7%
58.4%
58.3%
Absolute Relative
Standard Standard
Error of Error of
Estimate Estimate 95% Confidence
(ng/g)
)
24.
19.
16.
68.
57.
53.
19.
6.
3.

4
1
7
5
1
8
2%
65%
31%
(%)

117
66.
21.
28.
9.
4.
33.
11.
5.
Interval

(
3 (
0 (
1 (
59 (
89 (
2 (
4 (
67 (

0.
0.
45.
107.
481.
993.
19.
45.
51.

o,
0,
7,
,
,
/
4%,
1%,
7%,
(ng/g)

70
67
113
381
710
1210
96
71
64

.2)
.4)
•)
.)
. )
•)
.0%)
.7%)
.9%)
Other (qualitative)






(1)

(2)
(3)
(4)
(5)

(6)
i-Honene


Hexyl acetate


0-14 years
15-44 years
45+ years
0-14 years
15-44 years
45+ years
Data adjusted for surrogate recoveries
Estimates are based on
111.
162.
75.5
106.
121.
139.
(see Section 5.2)
107.
84.
73.
45.
35.
31.
•

1
5
3
5
0

97.
51.
97.
42.
29.
22.

1 (
9 (
4 (
9 (
5 (
3 (

0.
0.
0.
14.
48.
76.

0,
0,
0,
1,
9,
5,

328
332
224
197
192
202

.)
.)
•)
.)
. )
J

1980 U.S. Census figures.
p,p-DDE concentrations use the following response ion:
Data results from Batch
Corrected (see Section 5
1 not included
.1.2) .
The estimate for Total PCBs is the sum
in calculations.

of the estimated
m/z=316


.


averages over the
table (i.e., homologs detected in at least 44% of the NHATS FY86 composite
Estimated percent level
of chlorination is calculated as given






five homologs









included in



this
samples) .
in the footnotes to Table
7-2
.



-------
Table 7-4.  Estimates of Average Concentrations*1*  for Selected Semivolatiles,  with Standard Errors
            and Approximate 95% Confidence Intervals, According to Race Group
            from MEATS FY86 Composite Samples
Compound

p,p-DDT
p,p-DDE®
Beta-BHC
.j Heptachlor epoxide
i
H
Oxychlordane^
Trans -nonachlor
Dieldrin(4)

1 , 4 -Dichlorobenzene
Hexachlorobenzene
Race Group

White
Nonwhite
White
Nonwhite
White
Nonwhite
White
Nonwhite
White
Nonwhite
White
Nonwhite
White
Nonwhite

White
Nonwhite
White
Nonwhite
Estimated
Average
Cone.
(ng/g)
Pesticides
152.
301.
2250.
2780.
146.
212.
58.8
51.6
116.
103.
130.
131.
45.6
54.1
Chlorobenzenes
76.6
162.
51.9
48.2
Absolute
Standard
Error of
Estimate
(ng/g)

22.6
74.7
300.
687.
30.0
68.8
4.81
9.74
9.40
23.2
18.4
42.2
9.57
22.0

18.3
42.1
4.71
10.5
Relative
Standard
Error of
Estimate
(%)

14.9
24.8
13.3
24.7
20.6
32.4
8.2
18.9
8.1
22.5
14.1
32.3
21.0
40.6

23.9
26.0
9.1
21.8
95% Confidence
Interval (ng/g)

( 106.,
( 150.,
(1642.,
(1396.,
( 85.2,
( 73.3,
( 49.1,
( 32.0,
( 96.7,
( 56.0,
( 93.2,
( 45.6,
( 26.3,
( 9.72,

( 39.6,
( 76.7,
( 42.4,
( 27.0,

197.)
452.)
2852.)
4173.)
206.)
351.)
68.5)
71.3)
135.)
151.)
167.)
216.)
64.9)
98.5)

114.)
247.)
61.5)
69.4)

-------
                                                  Table 7-4.   (cont.)
i
H
00
Compound

Naphthalene

Te t rachlorobipheny 1
Pen t achl orob ipheny 1
Hexachlorobiphenyl
Heptachlorobiphenyl
Octachlorobiphenyl
Total PCBs^
Level of chlorination®
Race Group

White
Nonwhite

White
Nonwhite
White
Nonwhite
White
Nonwhite
White
Nonwhite
White
Nonwhite
White
Nonwhite
White
Nonwhite
Estimated
Average
Cone.
(ng/g)
PAHs
19.6
25.9
PCBs
53.0
73.0
133.
141.
289.
435.
111.
195.
37.5
68.2
623.
913.
58.2%
58.7%
Absolute
Standard
Error of
Estimate
(ng/g)

2.64
6.27

5.99
16.0
18.4
42.3
22.9
65.2
26.4
60.6
13.9
32.0
42.3
105.
4.63%
7.86%
Relative
Standard
Error of
Estimate
(%)

13.5
24.2

11.3
21.9
13.8
30.0
7.9
15.0
23.8
31.1
37.2
46.9
6.78
11.5
7.97
13.4
95% Confidence
Interval (ng/g)

( 14 . 3 ,
( 13.2,

( 40.9,
( 40.7,
( 96.0,
( 55.7,
( 243.,
( 304.,
( 57.5,
( 72.8,
( 9.36,
( 3.56,
( 539.,
( 703.,
( 48.9%,
( 43.0%,

24.9)
38.6)

65.1)
105.)
170.)
226.)
335.)
567.)
164.)
318.)
65.6)
133.)
708.)
1120.)
67.4%)
74.5%)

-------
Table 7-4.  (cont.)
Compound Race Group
l-Nonene White
Nonwhite
Hexyl acetate White
Nonwhite
Estimated
Average
Cone.
(ng/g)
Absolute
Standard
Error of
Estimate
(ng/g)
Other (qualitative)
109. 61.4
196. 141.
108. 25.9
195. 59.6
Relative
Standard
Error of
Estimate
56.3
72.1
23.9
30.5
95% Confidence
Interval (ng/g)
( 0.0,
( 0.0,
( 56.0,
( 74.8,
(n Data adjusted for surrogate recoveries (see Section 5.2) .
Estimates are based on 1980 U.S. Census figures.
^ W p.p-DDE concentrations use the following response ion: m/«-3l6.
K <*) Data results from Batch l not included in calculations.
vo (4) corrected (see Section 5.1.2).
(S) The estimate for Total PCBs is the sum of the estimated averages over the five homologs included
table (i.e., homologs detected in at least 44% of the NHATS FY86 composite samples).

-------
         Table 7-5.  Estimates of Average Concentrations^  for  Selected  Semivolatiles, with  Standard Errors
                     and Approximate 95% Confidence Intervals,  According to Sex Group
                     from NHATS FY86 Composite Samples
to
Compound Sex Group

p,p-DDT Male
Female
p,p-DDE(2) Male
Female
Beta-BHC Male
Female
Heptachlor epoxide Male
Female
Oxychlordane^ Male
Female
Trans -nonachlor Male
Female
Dieldrin(4) Male
Female

1 , 4 -Dichlorobenzene Male
Female
Hexachlorobenzene Male
Female
Absolute
Estimated Standard
Average Error of
Cone . Estimate
(ng/g) (ng/g)
Pesticides
172.
181.
2240.
2430.
133.
179.
59.9
55.5
122.
106.
160.
102.
45.2
48.7
Chlorobenzenes
108.
75.0
52.3
50.4

27.7
27.6
369.
358.
40.2
36.1
5.99
5.46
11.8
11.1
24.6
22.1
12.8
11.5

24.6
22.1
6.10
5.58
Relative
Standard
Error of
Estimate

16.1
15.2
16.5
14.7
30.1
20.2
10.0
9.8
9.7
10.4
15.4
21.7
28.4
23.7

22.8
29.4
11.7
11.1
95% Confidence
Interval (ng/g)

( 116.,
( 126.,
(1490.,
(1710.,
( 52.3,
( 106.,
( 47.8,
( 44.5,
( 97.5,
( 83.7,
( HI-,
( 57.3,
( 19.3,
( 25.4,

( 58.1,
( 30.5,
( 40.0,
( 39.1,

228.)
237.)
2983.)
3157.)
215.)
252.)
72.0)
66.5)
146.)
129.)
210.)
147.)
71.2)
72.0)

157.)
120.)
64.6)
61.6)

-------
Table 7-5.   (cont.)
Compound

Naphthalene

Tetrachlorobiphenyl
Pentachlorobiphenyl
i
w Hexachlorobiphenyl
Heptachlorobiphenyl
Octachlorobiphenyl
Total PCBs(5)
Level of chlorination®
Sex Group

Male
Female

Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Estimated
Average
Cone.
(ng/g)
PAHa
20.1
21.2
PCBs
40.7
71.2
115.
153.
294.
332.
148.
104.
52.5
33.4
651.
692.
58.9%
57.8%
Absolute
Standard
Error of
Estimate
(ng/g)

3.20
3.13

7.57
7.37
24.7
22.2
29.5
27.5
35.4
31.8
18.7
16.8
56.0
51.0
5.89%
5.04%
Relative
Standard
Error of
Estimate

15.9
14.8

18.6
10.3
21.4
14.5
10.0
8.3
24.0
30.7
35.6
50.3
8.61
7.36
10.0
8.73
95% Confidence
Interval (ng/g)

( 13.6,
( 14.9,

( 25.4,
( 56.4,
( 65.6,
( 108.,
( 235.,
( 276.,
( 76.3,
( 39.3,
( 14.8,
( 0.0,
( 539.,
( 591.,
( 47.1%,
( 43.0%,

26.6)
27.5)

56.0)
86.1)
165.)
197.)
354.)
387.)
219.)
168.)
90.3)
67.3)
763.)
794.)
70.7%)
74.5%)

-------
                                             Table 7-5.   (cont.)
     Compound
                         Race Group
Estimated
 Average
  Cone.
 (ng/g)
Absolute
Standard
Error of
Estimate
  (ng/g)
                                                                            Relative
                                                                            Standard
                                                                            Error of
                                                                            Estimate
95% Confidence
Interval (ng/g)
                                             Other (qualitative)
1-Monene
Hexyl acetate
Male
Female
Male
Female
148.
101.
107.
138.
82.4
74.0
34.8
31.2
55.7
73.5
32.4
22.7
( o.o,
( o.o,
( 37.1,
( 74.7,
314.)
250.)
177.)
201.)
(4)

(5)


(6)
Data adjusted for surrogate recoveries  (see Section  5.2).
  Estimates are based on 1980 U.S. Census figures.
p.p-DDE concentrations use the  following response ion:   m/z»3l6.
Data results from Batch 1 not included  in calculations.
Corrected  (see Section 5.1.2).
The estimate for Total PCBs  is  the sum  of the estimated averages over the five homologs included in this
table  (i.e., homologs detected  in at least  44% of the NHATS FY86 composite samples).
Estimated  percent  level of chlorination is  calculated as given in the footnotes to Table 7-2.

-------
Table 7-6.  Estimates of Average Concentrations*1*  for Selected
           Semivolatiles, With Standard Errors and Approximate
           95% Confidence Intervals, for the Nation  from MEATS
           FY86 Composite Samples
'•W/ <'/ •/% •„• W','/t
'& m- S?/ ^ ^:
'"'* -^""^ Z
•'•\«&t
Compound
Estimate
of Avg. *
I^Conc. *®
* (ng/g) *
'Absolute
Standard
Error of
Est, (ng/g)
Relative
Standard
Error ? of
Est. (%)?
$m i. ^-;
%^.™^ '•'
^95% Confidence
^' ?•* Interval
Pesticides
p,p-DDT
p,p-DDE(2)
Beta-BHC
Heptachlor epoxide
Oxychlordane^
Trans -nonachlor
Dieldrin(4)
177.
2340.
157.
57.6
114.
130.
47.0
19.7
270.
24.9
4.19
7.52
15.3
7.95
11.2
11.6
15.9
7.3
6.6
11.7
16.9
( 137., 217.)
(1792., 2884.)
( 107., 207.)
( 49.2, 66.1)
( 98.4, 129.)
( 99.6, 161.)
( 31.0, 63.1)
Chlorobenzenes
1 , 4 -Dichlorobenzene
Hexachlorobenzene
90.9
51.3
15.2
3.97
16.7
7.7
( 60.2, 122.)
( 43.3, 59.3)
PAHs
Naphthalene
20.7
2.37
11.4
( 15.9, 25.4)
PCBs
Tetrachlorobiphenyl
Pentachlorobiphenyl
Hexachlorobiphenyl
Heptachlorobiphenyl
Octachlorobiphenyl
Total PCBs(5)
Level of
Chlorination(6)
56.4
135.
314.
125.
42.7
672.
58.3%
4.70
15.3
18.4
21.9
11.6
34.6
3.54
8.3
11.4
5.9
17.5
27.1
5.2
6.1
( 46.9, 65.9)
( 104., 165.)
( 276., 351.)
( 80.7, 169.)
( 19.3, 66.1)
( 603., 742.)
( 51.2, 65.4)
Other (qualitative)
1-Nonene
Hexyl acetate
124.
123.
51.0
21.5
41.3
17.5
( 20.6, 227.)
( 79.5, 166.)
                             7-23

-------
                            Table  7-6.   (cont.)

Notes for Table 7-6;
^  Data  adjusted  for  surrogate recoveries (see Section 5.2) .
     Estimates are based on 1980 U.S.  Census figures.
®  p,p-DDE concentrations use the  following response ion:  m/z=316.
^  Data  results from  Batch  1 not included in calculations .
W  Corrected  (see Section 5.1.2).
®  The estimate for Total PCBs is the sum of the estimated averages over the
   five homologs  included in this table (i.e.,  homologs  detected in at least
   44% of the NHATS FY86 composite samples) .
w  Estimated percent level of chlorination is calculated as follows:
 where Aj = estimate of  the percent of total PCBs for homolog i,
 and   B; = mass fraction of  chlorine for homolog i.
  (Only the five  PCB homologs included in the table are considered in
 calculating level  of chlorination.)
                                     7-24

-------
number of standard errors in the confidence interval is
determined by the Student-t distribution.
        The  17 target compounds for statistical analysis
included five PCB homologs (tetra- through octa-chlorobiphenyl) .
Using the average estimates for these five homologs, estimates of
total PCBs and level of chlorination were  calculated based on the
approach documented in Section 6.2.1.2.  The estimates of these
two PCB parameters are also included in Tables 7-2 through 7-6.
In addition,  the chlorobiphenyl distribution across the five PCB
homologs,  corresponding to the percentage  of the total PCB
concentration represented within each homolog, is presented in
Table 7-7.  This table illustrates that the penta-, hexa-, and
hepta-chlorobiphenyls represent over 80% of the national average
PCB concentration across the five homologs, with
hexachlorobiphenyl representing 47% of the total.   As will be
seen in Chapter 8, similar distributions were observed in
previous NHATS campaigns.
        Appendix  F contains plots of the estimated average
concentrations and their associated 95% confidence intervals for
the 17 target compounds, as documented in  Tables 7-2 through 7-6.
One plot exists for each compound and contains statistics for
each of the four analysis factors and the  entire nation.  These
plots illustrate the trends observed in the average
concentrations across the subpopulations and the variability
associated with .these trends.   Considerable overlapping of the
confidence intervals indicate that while average concentrations
may differ between subpopulations, they may not differ
statistically.  The chlorobiphenyl distributions presented in
Table 7-7 are also plotted in Appendix F.
        Estimates of the average  concentrations in the
population categories defined by the four  demographic factors are
presented in Tables 7-2 through 7-6 even if the effects of those
factors were not found to be statistically significant through
hypothesis testing.  For example, regional estimates of average
concentration for Beta-BHC range from 151  ng/g in  the North
                               7-25

-------
         Table  7-7.  Chlorobiphenyl Distribution Across the
                    Five Target PCB Homologs in  the FY86 NHATS
Demographic
Group
North Central
North East
South
West
0-14 years
15-44 years
45+ years
White
Nonwhite
Male
Female
Nation
Percentage of Total Concentration Across the
.<-.:;•*•,. Five Homologs
Tetra-
10.2%
7.9%
7.9%
7.3%
8.0%
7.0%
9.6%
8.5%
8.0%
6.3%
10.3%
8.4%
Pent a -
25.5%
20.2%
18.0%
13.7%
31.0%
18.0%
19.8%
21.4%
15.5%
17.7%
22.0%
20.0%
Hexa-
43.4%
43.1%
50.2%
53.5%
41.3%
51.4%
43.7%
46.3%
47.7%
45.2%
47.9%
46.6%
Rept
-------
Central census region to 177 ng/g in the South census region.
However, as further documented in Section 7.3, this difference
was not found to be statistically significant.
        Table 7-6 indicates that the standard errors of the
national estimates among the 17 semivolatiles ranged from 5.9 to
41.3 percent of the estimates.  The highest relative standard
error was observed with 1-Nonene,  which is a qualitative
semivolatile compound.  Among the four analysis factors,  higher
relative standard errors were generally noted among subfactors
associated with fewer composites,  such as the West census region,
the 0-14 year age group, and the non-Caucasian race group.
        The estimated concentrations for most of the 17
semivolatile compounds appear to increase with age group
according to Table 7-3.   This result has been observed in data
analyses on other NHATS datasets (e.g.,  FY82 and FY87).   Similar
trends consistent across the analyzed compounds are not  as
apparent among census regions, race groups,  and sex groups.
Statistical conclusions on these effects are based on the
hypothesis tests in the next section.

7.3  HYPOTHESIS TESTING
        Statistical hypothesis tests were conducted for each  of
the 17 semivolatile compounds included in the statistical
analysis to determine if there are statistically significant
differences in average concentrations between individuals from
different geographic regions,  age groups,  race groups,  and sex
groups.   The tests were based on likelihood ratio tests  using the
additive model analysis and were described in Section 6.2.2.
        Table 7-8 lists the attained significance  levels  for  the
tests associated with the four analysis factors.  In addition, a
test was performed to note significance of the effect that being
in Batches 4 and 5 has on the measured concentration; this factor
was significant among the QC sample data.  The attained
significance level is the smallest level at which the test can
result in rejection of the hypothesis that no differences are
                               7-27

-------
     Table 7-8.   Significance  Levels  from Hypothesis Tests  for
                   Differences Between  Demographic Groups for
                   NHATS  FY86 Semivolatiles™
Compo*m4
• If f sets due to ...
•€&ns&$ ;
H&glon$*
Age
Group(3* ;
Sex
Groupt4*
Race
<3raup*4J
Pesticides
p,p-DDT
p,p-DDE(5)
Beta-BHC
Heptachlor epoxide
Oxychlordane^
Trans -nonachlor
Dieldrin^
<0.001**
0.001**
0.947
0.031*
0.616
0.187
0.711
<0.001**
0.009**
0.015*
<0.001**
<0.001**
<0.001**
0.359
0.966
0.814
0.623
0.565
0.483
0.321
0.858
0.286
0.569
0.501
0.846
0.853
0.879
0.808
Chlorobenzenes
1 , 4 -Dichlorobenzene
Hexachlorobenzene
0.133
<0.001**
0.182
<0.001**
0.500
0.777
0.327
0.936
PAHs
Naphthalene
0.011*
0.142
0.830
0.641
PCBs
Tetrachlorobiphenyl
Pentachlorobiphenyl
Hexachlorobiphenyl
Heptachlorobiphenyl
Octachlorobiphenyl
0.037*
0.009**
0.047*
0.140
0.535
<0.001**
<0.001**
<0.001**
<0.001**
0.036*
0.260
0.549
0.693 .
0.490
0.561
0.337
0.619
0.244
0.368
0.484
Other (qualitative)
1-Nonene
Hexyl acetate
0.782
0.301
0.751
0.826
0.764
0.672
0.695
0.445
(1)
(2)
(3)
(4)
(5)
(6)
(7)
Data adjusted for surrogate recoveries  (see Section 5.2).
Likelihood ratio tests based on the Xm distribution.
Likelihood ratio tests based on the xh) distribution.
Likelihood ratio tests based on the XH) distribution.
p,p-DDE concentrations use the following response ion:   m/z=316
Data results from Batch 1 not included.
Corrected (see Section 5.1.2).
*   Significant  at  the 0.05 level.
*.*  Significant  at  the 0.01 level.
                                   7-28

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present between the population averages.  For example, the
differences among estimated averages of Beta-BHC in the four
census regions could only be considered significant at the 0.947
(94.7%) level of significance, while the differences in age group
average is significant at the 0.015 (1.5%) level.  A significance
level of less than 0.05  (5%) is generally required to declare
statistical significance.
        An apparent  conclusion from Table 7-8 is the presence  of
significantly different estimated average concentrations among
the age groups for pesticides, hexachlorobenzene, and PCBs.  From
Table 7-3, the older age group (45+ years) had the highest
estimated average concentration for these compounds, and the
youngest age group (0-14 years)  had the lowest estimate.  The
disparity between the older age group and the others is more
apparent for the PCBs.
        Statistical  significance was also observed  among census
regions for three pesticides, hexachlorobenzene, naphthalene, and
three PCB congeners.   Levels of p,p-DDT and hexachlorobenzene
were highest in the West census region, while for some PCB
congeners, levels were lowest in the West census region.
However, a consistent trend across the compounds was not observed
with census region as was observed with age groups.
        The difference  in estimated average  concentration
between Caucasian and non-Caucasian and between male and female
donors were not statistically significant for any of the modelled
compounds.  The effect of Batches 1-3 versus 4-5 on the measured
concentrations in composite samples was also not significant for
any of the compounds.

7.4  OUTLIER DETECTION
        Prior to conducting the statistical  analysis  of the  FY86
NHATS data,  outlier detection procedures were performed to
identify possible data entry errors and errors associated with
the analytical method.  The outlier detection process was
performed in multiple stages by Westat, Battelle, and EPA.  MRI
                               7-29

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 reviewed all findings of this process,  identified a  list of
 changes  to data values resulting from their review,  and notified
 the  NHATS project team of these changes.   Battelle corrected  the
 database according to MRI's review prior  to performing the final
 statistical analysis.
         Westat performed statistical outlier analysis on the
 following types of data:

     •   measured concentrations of native analytes,
     •   internal quantitation standard recoveries,
     •   LODs, and
     •   percent lipid values for composite and QC samples.

 The  methods and findings of these analyses are presented in
 Rogers  (1991).   The procedure consisted of three  approaches:
 logic checks,  formal outlier identification procedures, and
 informal outlier identification procedures.
         Logic checks were performed prior to database
 completion,  to  identify obvious data  inconsistencies  or coding
 errors.   For example,  by printing records with inconsistent
 entries,  the logic check procedure would  reveal records having
 recorded concentrations but a data qualifier of "not  detected".
         The formal approach to outlier identification in Rogers
 (1991) assumed  that the concentrations  and recovery data followed
 a lognormal  distribution,  and the percent lipid data  followed a
 normal distribution.   A mathematical  model was fit to the data,
 and  the  extreme  studentized deviate (BSD)  test was applied to the
 residuals  of the  model.   This test considered the  ratio of the
maximum  residual  to the standard deviation of the  residuals.
Outliers were identified if this ratio  exceeded the appropriate
critical value given the significance level  (1% or 5%).  The  form
of the simple linear regression models  varied.among the different
types of data  (see  Table 2  in Rogers  (1991)).
         Once formal outlier identification procedures were
completed, informal  identification procedures noted any
                               7-30

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additional data which may be in question.  These procedures
included normality tests on residuals for individual compounds,
multivariate tests across multiple compounds (identifying data •
points which do not conform with a multivariate normal
distribution),  boxplots to compare measurements of different
types, and special outlier comparison tests for the LODs.
         In addition to the approach documented in Rogers  (1991)
to identify outliers among native compound concentrations in
composite samples, Battelle identified additional potential
outliers by fitting the additive model (Chapter 6)  to the
preliminary FY86 semivolatile data.  Residuals  exceeding two
standard deviations from zero were reported.
         To illustrate patterns due to analysis order and batch,
time series plots of the FY86 data were produced.  Any outliers
and questionable data points were highlighted in these plots.
These data plots and listings of statistical outliers were
delivered to EPA and to MRI for review.
         A total of 50 data points were identified as outliers
from the procedures in Rogers (1991).   These data points included
24 quantitative concentrations,  6 qualitative concentrations, and
20 recoveries.   Of these points,  eight were changed as a result
of review by MRI.   The findings of the outlier analysis
identified unusually low surrogate recoveries for two samples,
implying that the reported concentrations were suspect for these
samples.  The outlier report also noted that recoveries in Batch
1 were lower than in later batches, apparently due to changes in
lab procedures.   These findings supported the need to consider
effects of batch in statistical analyses and to correct data for
surrogate recoveries.
         Forty-four additional data points were identified  as
potential statistical outliers as a result of fitting the
additive model to target compound data.  Review of these data by
MRI resulted in changes to 16 of the data points.
         Battelle  made all data corrections  to the master
database before proceeding with the statistical analysis.
                               7-31

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 However,  as a result of the data review,  some  of  the  data points
 identified in the outlier detection procedure  either  did not
 require modification or remained influential after  modification.
 Thus  these data points contributed to increased error in fitting
 the additive model and to inflated variability in parameter
 estimation and hypothesis testing.   The most influential data
 points are documented in the following section.

 7.5 MODEL VALIDATION
         As part of the commitment to overall data quality,  three
 types of analyses were performed to evaluate the  adequacy of the
 additive model for use on the FY86  NHATS  semivolatile data on the
 seventeen target compounds.   All three analyses were  based on
 comparisons of the observed (i.e.,  measured) and  predicted
 concentrations for the composite samples.   Predicted
 concentrations were calculated using the  IWGLS method applied to
 the additive model (Chapter 6).   Residuals, which were also used
 in the model validation analysis, were calculated by  taking the
 differences between the observed and predicted concentrations.
         Model validation analyses included:
    •   residual plots,
    •   normal probability plots, and
    •   R-squared analysis.
 The use  of  Shapiro-Wilk tests for normality was also  considered.
 However,  in this application,  the Shapiro-Wilk test was not
 appropriate because the data were correlated and  variances
 increased with increasing concentrations.
         In several of the target compounds, the residual plots
 (residuals  versus  predicted  concentration)  confirmed  the model
 assumption  that  the variance of  the  measured concentrations
 increases with the average concentration.   In  addition, these
plots  showed  that  the  distribution of  residuals tended to be
 symmetric about  zero across  all  predicted concentrations.  For
 some compounds,  the extent to which  residuals  were symmetric
about  zero  was  less evident  at low concentrations, where
                               7-32

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predicted levels tended to be larger than the observed level.
This finding indicates that the relationship between measured
concentration and the model predictors may not be as linear in  '
low concentration ranges relative to larger concentration ranges.
Also, the low concentration range can include a substantial
number of measured concentrations at or below the detection
limit.  For compounds whose non-detect percentage approached 50%
(such as octachlorobiphenyl,  1-nonene, dieldrin,  and
tetrachlorobiphenyl), the predicted concentrations in areas close
to the detection limit may be more biased in portraying the true
concentration than predicted concentrations in higher detectable
ranges.
        The presence of unusually high or low data points also
contributed to an overall lack of fit of the model to the
observed data.  The data points observed to be among the most
"influential" to the model fitting are presented in Table 7-9.
The result of fitting the model while including the influential
data points is either an underestimate or overestimate by the
fitted model in certain concentration ranges.
        Normal probability plots for most target compounds
resembled a linear pattern,  supporting the normality assumption
for the errors.   However,  the linearity assumption for some
compounds did not hold in areas of extremely large or small
concentrations.   This is explained by the larger variances
associated with these concentrations,  and by the presence of
influential data points with large positive or negative
residuals.
        Table 7-10 lists the R-squared correlations between the
observed and predicted concentrations calculated for each target
compound.   R-squared can be interpreted as the percent of the
total variability in the observed concentrations that can be
explained by the additive model.  The correlations range from 12%
(naphthalene)  to 65% (tetrachlorobiphenyl).  The qualitative
compounds have low R-squared values, indicating that their
categorical concentrations are not highly correlated with
                               7-33

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Table 7-9.  Measured Concentrations with High Influence
            on Determining the Additive Model Pit
Sample ID
Lab. ID
Measured Conc.^
(ng/g)
-„. Predicted
Cone, (ng/o;}
p/p-DDT
ACS8600270
17922
1214
886
Oxychlordane^
ACS8600065
ACS8600163
17942
17946
39.2
306
148.7
139
Trans -nonachlor
ACS8600163
17946
510
264
Hexachlorobenzene
ACS8600314
ACS8600207
ACS8600350
17986
17968
17948
123
176
192
67.5
81.1
96.5
Naphthalene
ACS8600332
ACS8600225
ACS8600421
17965
17939
17924
66.9
99.0
70.5
23.5
24.6
26.3
Tetrachlorobiphenyl
ACS8600127
ACS8600092
17959
17909
249
217
124
146
Hexachlorobiphenyl
ACS8600092
17909
1123
493
Heptachlorobiphenyl
ACS8600289
17919
888
376
Octachlorobiphenyl
ACS8600289
17919
322
142
                          7-34

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                            Table  7-9.   (cont.)
"'//'"'W%,,:'^'/''' -
' '% 4-^41^ ''•£'' 'I :
S&&jjiie$.' ;$&

Lab, ID

ACS8600181
17960
flteasured Coae*^
(ng/g)
3red&4sg£/' ;
Cone. 
-------
        Table 7-10.   R-Squared  Correlation Between Observed
                      Concentrations and Concentrations  Predicted
                      by the Additive Model  for NHATS  PY86
                      Semivolatiles(1)
Coraptsrnwl
i s^&£i*g**d[ ,
Pesticides
p,p-DDT
p,p-DDE
Beta-BHC
Heptachlor epoxide
Oxychlordane
Trans -nonachlor
Dieldrin
31
49
43
55
43
55
13
Chlorobenzenes
1 , 4 -Dichlorobenzene
Hexachlorobenzene
29
46
PAHs
Naphthalene
12
PCBs
Tetrachlorobiphenyl
Pentachl or ob ipheny 1
Hexachldrobiphenyl
Heptachlorobiphenyl
Octachlorobiphenyl
65
54
61
47
37
Other (qualitative)
1-Nonene
Hexyl acetate
23
14
(1)  R-squared is the square of the Pearson correlation coefficient.  It
represents the percent of variability in the data that is explained by the
additive model.  Data adjusted for surrogate recoveries (see Section 5.2).
                                  7-36

-------
predicted values.  Note that these R-squared values are not as
high as seen with dioxins and furans in the FY87 NHATS (USEPA,
1991).   This does not necessarily imply, however, that the
additive model is an inadequate fit to the semivolatile compound
data.  Instead, low R-squared values may indicate that the
estimated model effects are small relative to the random error
observed in the measured concentrations.  The random error is
increased by the presence of influential observations such as
those in Table 7-9.
                               7-37

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8.0 COMPARISON WITH RESULTS FROM PREVIOUS SURVEYS IN THE NHATS
    PROGRAM

        The FY86 NHATS  is one of three surveys in the NHATS
program to use HRGC/MS analytical methods in measuring the
prevalence and levels of semivolatile organic compounds in
composited adipose tissue samples.   Prior to the FY86 survey, the
FY82 and FY84 surveys also performed analysis of semivolatiles on
composite samples using HRGC/MS methods.   The NHATS FY86 sampling
and data analysis approach was designed to allow valid
statistical comparisons to be made between the FY86 results and
the results from these two surveys.
        The NHATS FY82  Broadscan Analysis Study  (Mack and
Panebianco, 1986)  was the first NHATS campaign to employ the
HRGC/MS method in characterizing an expanded chemicals list.   The
objective of the FY82 NHATS was to identify and characterize
additional compounds that persist in human adipose tissue but
could not be measured with less selective analytical techniques.
The FY84 NHATS was designed to establish the comparability of the
HRGC/MS and PGC/ECD analytical methods (Westat,  1990).  The FY84
NHATS revealed that issues in method comparability were not
totally resolved for many of the target semivolatile compounds.
This chapter presents comparison of the FY86 NHATS results with
the results from the NHATS FY82 and FY84 semivolatile analyses.
        There are several differences in the designs and
analytical procedures used in these three surveys.  These
differences are documented in Section 8.1.   Only the semivolatile
compounds analyzed in the FY86 NHATS and in at least one of the
FY82 and FY84 NHATS are included in comparisons.  For each of
these compounds within each survey, Section 8.2 presents average
limits of detection (LODs)  and the percentages of detected
results among the samples.   Statistical procedures were used to
compare these detection percentages across surveys.  Section 8.3
presents two approaches to calculating descriptive statistics  in
summarizing measured concentration data within each of the three

                               8-1

-------
surveys at the national  level.  Finally, statistical comparisons
were performed on only those  compounds detected in at least 50%
of the composite samples within each survey.  Section 8.4
presents results of  fitting the additive model to these compounds
within each  survey.

8.1  COMPARISON OF DESIGN AND ANALYTICAL PROCEDURES

8.1.1  Comparison of Study Designs
         Similar sampling designs  were  used for  collecting tissue
specimens in the FY82, FY84,  and  FY86 NHATS.  A discussion of the
FY86 sampling design is  found in  Chapter 2 of this report.  The
primary difference in sampling designs between these three
surveys is the method of stratification.  Prior to the FY85
NHATS, MSAs  were selected from strata defined by the nine U.S.
Census divisions.  Beginning  with the FY85 NHATS, sampling strata
were redefined to be the seventeen geographic areas that resulted
from the intersection of the  Census divisions and the ten EPA
regions  (Table 2-2).
         A controlled selection  technique  (Mack  et.  al./  1984)
was used to  maximize the probability of retaining MSAs from one
survey design to another.  Table  8-1 displays the number of
specimens and composites associated with each MSA for each
survey.  Except for  double-collection MSAs, no MSA contributed
more than the quota  of 27 specimens to the FY86 NHATS design.
This was not true for the FY82 and FY84 surveys, where as many as
72 specimens originated  from  a single-collection MSA.  Only five
MSAs sampled in the  FY82 and  FY84 NHATS were not represented in
the FY86 NHATS, while only four MSAs were sampled in the FY86
NHATS but not in the other two surveys.  It is expected that
differences  in MSA sampling across the three surveys contribute
to only minor differences in  concentration estimates.
         For  each  census  region, age  group,  sex  group,  and race
group, Tables 8-2 and 8-3 present summaries of the number of
specimens and composites, respectively, originating within these
                               8-2

-------
        Table 8-1.   Number of Specimens  and Composites Within the  FY82,
                    FY84, and FY86 NHATS According to MSA
Number of
Specimens
MSA (code and location)
800
5200
10000
11200
16000
16800
18400
19200
19600
20000
20800
21600
23350
31600
42800
44800
46000
47200
49200
50000
56000
57200
59200
59600
61600
62800
64400
68200
69200
71600
72400
73600
78400
80000
82800
88400

AKRON, OH
ATLANTA, GA
BIRMINGHAM, AL
BOSTON, MA
CHICAGO, IL
CLEVELAND, OH
COLUMBUS, OH
DALLAS -FORT WORTH, TX
DAVENPORT- ROCK ISLAND-MOLINE, IA-IL
DAYTON, OH
DENVER-BOULDER, CO
DETROIT, MI
ELMIRA, NY
GREENVILLE- SPARTANBURG, SC
LEXINGTON- FAYETTE, KY
LOS ANGELES -LONG BEACH, CA
LUBBOCK, TX
MADISON, WI
MEMPHIS, TN-AR-MS
MIAMI, FL
NEW YORK, NY-NJ
NORFOLK- VA BEACH- PORTSMOUTH, VA-NC
OMAHA, NE-IA
ORLANDO, FL
PHILADELPHIA, PA-NJ
PITTSBURGH, PA
PORTLAND, OR-WA
ROCHESTER, MN
SACRAMENTO, CA
SALT LAKE CITY-OGDEN, UT
SAN ANTONIO, TX
SAN FRANCISCO-OAKLAND, CA
SPOKANE, WA
SPRINGFIELD-CHICOPEE-HOLYOKE, MA-CT
TAMPA- ST PETERSBURG, FL
WASHINGTON, DC-MD-VA
Totals :
FY82
0
0
40
0
17
44
0
38
12
24
10
9
0
14
45
0
35
40
0
26
76
72
19
43
5
28
27
41
4
19
0
0
0
56
0
19
763
FY84
6
0
27
0
37
40
0
26
9
24
10
15
17
39
38
8
12
29
0
16
0
43
60
33
7
25
15
29
0
22
27
0
15
37
7
16
689
FY86
18
27
0
25
45
27
14
27
0
9
10
54
27
27
27
4
0
27
23
27
25
27
27
0
7
21
16
27
2
24
0
27
12
18
8
12
671
Number of
Composites*1)
FY82
0
0
5
0
8
8
0
4
5
7
2
3
0
9
5
0
4
8
0
9
6
10
4
9
2
4
3
4
1
3
0
0
0
3
0
8
46
FY84
1
0
4
0
6
6
0
4
2
6
3
2
4
10
4
2
4
6
0
8
0
9
5
8
1
4
4
4
0
3
4
0
3
4
4
6
46
FY86
5
8
0
4
6
6
3
3
0
3
3
4
5
7
4
2
0
4
4
8
5
8
5
0
4
4
3
5
2
4
0
5
3
4
3
5
50
(1)  Column entries indicate the number of composites having at  least  one
specimen from the given MSA.   The total at the bottom of each column indicates
the total number of analyzed composites in the survey.  Since specimens within
a composite can originate from more than one MSA, this total is not equal to
the sum of the column entries.
                                      8-3

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  Table 8-2.
Total Number of Specimens Included in Composite
Samples Analyzed in the FY82, FY84, and FY86
NHATS, by Subpopulation and Across the
Entire Study
Subpopulation
                   Number  of  Specimens  (%  of Total)
      FY82
      FY84
                                                           1980
                                                          Census
   FY86
                          Census  Region
Northeast
North Central
South
West
0-14 years
15-44 years
45+ years
Male
Female
White
Nonwhite
   166  ( 22%)
   206  ( 27%)
   331  ( 43%)
    60  (  8%)
   178  ( 23%)
   312  ( 41%)
   273  ( 36%)
   412 ( 54%)
   351 ( 46%)
   632 ( 83%)
   131 ( 17%)
    86 ( 12%)
   249 ( 36%)
   284 ( 41%)
    70 ( 10%)

Age Group

   142 ( 21%)
   266 ( 39%)
   281 ( 41%)

   Sex

   352 ( 51%)
   337 ( 49%)

   Race

   579 ( 84%)
   110 ( 16%)
123 ( 18%)
248 ( 37%)
205 ( 31%)
 95 ( 14%)
108 ( 16%)
221 ( 33%)
342 ( 51%)
315 ( 47%)
356 ( 53%)
526 ( 78%)
145 ( 22%)
26%
22%
33%
19%
23%
46%
31%
49%
51%
83%
17%
Total # of
Specimens
   763
   689
671
                               8-4

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  Table 8-3.
Total Number of Composite Samples Analyzed in  the
FY82, FY84,  and FY86 NHATS, by Subpopulation and
Across  the Entire Survey
 Subpopulation
                      Number of Composites (% of  Total)
        FY82
  FY84
                                                                1980
                                                              Census
  FY86
 Northeast
 North  Central
 South
 West
 0-14 years
 15-44 years
 45+ years
 Mixed(3)
 Male only
 Female  only
 Mixed(3)
 White  only
 Nonwhite  only
                           Census  Region1
                          (l)
       9  (  20%)
     12  (  26%)
     19  (  41%)
       6  (  13%)
 8  ( 17%)
13  ( 28%)
18  ( 39%)
 7  ( 15%)
                             Age  Group1
                        (1)
     12  (  26%)
     17  (  37%)
     17  (  37%)
     35
       6  (  55%)
       5  (  45%)
     29
     11  (  65%)
      6  (  35%)
10  ( 22%)
19  ( 41%)
17  ( 37%)
                                 Sex1
                     (2)
29
 8  ( 47%)
 9  ( 53%)
                                Race
                                    (2)
25
16  ( 76%)
 5  ( 24%)
 9  ( 18%)
16  ( 32%)
15  ( 30%)
10  ( 20%)
10  ( 20%)
16  ( 32%)
24  ( 48%)
18
14  ( 44%)
18  ( 56%)
29
16  ( 76%)
 5  ( 24%)
26%
22%
33%
19%
23%
46%
31%
49%
51%
83%
17%
 Total  #  Of
 Composites
     46
46
50
(1)  All specimens within a given composite originated from the same  census
region and age group.

®  The percentages for sex and race groups are  calculated as the total number
of pure composites within each study design.  For example,  6 of  the 11 (55%)
pure sex composites in the FY82 study design were composed of specimens from
males  only.
0)
   Composites containing specimens from both sex  (or race) groups.
                                  8-5

-------
groups.   The distributions of  specimens  among  the  geographic  and
demographic  groups were relatively similar across  the  three
surveys.   The FY86 survey had  higher percentages of  specimens
from  the  West census region and the nonwhite race  group:   two
groups  in which specimens are  generally  less procurable than
other groups.
         The FY82, FY84, and FY86 NHATS also had comparable
composite designs (Table 8-3).   One of the design  criteria for
compositing  FY84 and FY86 specimens was  to maintain  similarity to
the FY82  design (see Section 3.1).   However, the FY86  design
stipulated more pure sex composites (i.e.,  all male  or all
female) than the FY82 and FY84  designs in  order to more
accurately estimate differences in concentrations  among the
sexes.  Sixty-four percent of  the  FY86 composites  were pure sex
composites,  compared to less than  forty  percent of the composites
in the  FY82  and FY84 surveys.   Overall,  the percentages of
composites within each population  group  were similar across the
three surveys and with the 1980 Census percentages.

8.1.2  Comparison of Analytical Procedures
         To interpret differences in estimated  concentrations
between the  three surveys,  it  is necessary to  consider
differences  in their analytical methods.   While some major
differences  do exist,  the methods  were otherwise similar between
the three surveys.
         One  analytical factor  having a large potential effect on
data  comparability between the  three surveys is the  type and
number  of internal  quantitation standards  (IQS) and  how these
standards are  assigned to semivolatile compounds.  Native
compound  concentrations were quantified  relative to  the IQS
findings.  Only one IQS was  used to quantify the semivolatiles in
FY82:   anthracene-d10.   The FY84 and FY86 surveys included  three
IQS for quantification of semivolatiles:   anthracene-d10,
benzo (a) anthracene-d12,  and naphthalene-d8.   In  addition to
                               8-6

-------
differences caused by the number and type of IQS assigned to each
survey, the method of assigning an IQS to each semivolatile
differed between the FY84 and FY86 NHATS.  Table 8-4 lists those-
semivolatiles analyzed in both FY84 and FY86 for which the same
IQS was assigned in both surveys.  Table 8-5 lists the
semivolatiles with differing IQS between FY84 and FY86.
Differing IQS assignments between surveys must be considered when
interpreting differences observed in results from one survey to
another.
        Average concentration estimates  in the FY86 NHATS were
based on measured concentrations adjusted for surrogate
recoveries (Chapter 7).   The adjusted concentrations are more
likely to resemble actual concentrations in the sample than
unadjusted measured concentrations.  Thus for comparison
purposes,  it was necessary to obtain average concentration
estimates in the FY82 and FY84 surveys based on surrogate-
adjusted concentrations.  Like the IQS, surrogate compounds were
matched to specific semivolatile compounds within each survey
(Table 5-2)  for adjustment purposes.  However, the types of
surrogate compounds included in each survey also differed.  Thus
in conducting the comparison, it is noted when surrogate
compounds differed among the surveys.
        Another issue to consider  is that the FY82 and FY86
analyses  were conducted at Midwest Research Institute, while the
FY84 analysis was performed at Colorado State University.  Thus
interlaboratory variation is also introduced when comparing FY84
results with the other two surveys.
        Other than the  differences  noted above,  the techniques
in the analytical methods for semivolatile analyses were
essentially equivalent between the three surveys.  The flow
diagram in Figure 4-1 (Chapter 4) illustrates the order of
activities in each campaign.  Each procedure required
fortification with IQS and surrogate compounds, extraction,
removal of bulk lipid,  separation, cleanup, and quantification.
Extraction was achieved with methylene chloride using a Tekmar
                               8-7

-------
  Table 8-4.
Semivolatile Compounds Quantitated Using  the  Same
Internal Quantisation Standards  (IQS)  in  NHATS  PY84
and FY86.
                    IQS t   Benzo(a)anthracene-d^
                              p,p-DDT
                              0,p-DDT
                              p,p-DDE
                              o,p-DDD
                          TRANS-NONACHLOR
                               MIREX
                              CHRYSENE
                        HEXACHLOROBIPHENYL
                        HEPTACHLOROBIPHENYL
                        OCTACHLOROBIPHENYL
                        NONACHLOROBIPHENYL
                        DECACHLOROBIPHENYL
                        IQSt   Anthracene-d10
                             ALPHA-BHC
                              BETA-BHC
                             DELTA-BHC
                        GAMMA-BHC(LINDANE)
                              ALDRIN
                            HEPTACHLOR
                        HEPTACHLOR EPOXIDE
                           OXYCHLORDANE
                          GAMMA-CHLORDANE
                        PENTACHLOROBENZENE
                         HEXACHLOROBENZENE
                          ACENAPHTHALENE
                              FLUORENE
                           PHENANTHRENE
                           FLUORANTHENE
                        MONOCHLOROBIPHENYL
                         DICHLOROBIPHENYL
                         TRICHLOROBIPHENYL
                        TETRACHLOROBIPHENYL
                       IQS;  Naphthalene-dg
                      1,2,3-TRICHLOROBENZENE
                      1,2,4-TRICHLOROBENZENE
                      1,3,5-TRICHLOROBENZENE
                           NAPHTHALENE
Note:  Anthracene-d10 was the only IQS used in the FY82 NHATS.
                                8-8

-------
Table  8-5.  Semivolatile Compounds Quarttitated Using Different
             Internal Quantitation  Standards  (IQS) in NHATS FY84
             and FY86.
    (i)
       Legend:  A = Anthracene-dto
               B = Benzo (a) anthracene -d12
               N = Naphthalene-dg
Compound
o,p-DDE
1,2,3, 4 -TETRACHLOROBENZENE
1,2,3, 5 -TETRACHLOROBENZENE
1,2,4, 5 -TETRACHLOROBENZENE
ACENAPHTHENE
PYRENE
PENTACHLOROB I PHENYL
IQSW
PY84
B
N
N
N
N
B
B
FY86
A
A
A
A
A
A
A
    Note:  Anthracene-d10 was the only IQS used in the FY82 NHATS,
                                8-9

-------
 Tissuemizer to promote thorough extraction of lipids.   Extracts
 were filtered through anhydrous sodium sulfate.   Gel permeation
 chromatography was applied to separate target analytes  from lipid
 material.   Interference separation was achieved  through Florisil
 column fraction procedures.

 8.2.  LODs AND PERCENT DETECTION SUMMARIES
         A total of 54 quantitative semivolatile compounds were
 analyzed in the FY86  NHATS and also analyzed in  one or  both of
 the  FY82 and FY84  NHATS.   These compounds  form the basis of the
 descriptive and statistical  comparisons in measured
 concentrations of  target  compounds across  the three surveys.
 This subsection summarizes the LODs and the percentages of
 detected results for  these compounds in the FY82, FY84,  and FY86
 NHATS.
         An LOD was reported for a compound whenever a  trace or
 not-detected reading  was  reported for the  sample.  These LODs
 (ng/g lipid weight) are averaged and presented in Table 8-6 for
 the  54  semivolatile compounds.   The LODs were not adjusted  for
 surrogate  recoveries  prior to averaging.   Table  8-6 also
 documents  the percent of  composite samples with  detected readings
 within  each survey for the 54 compounds.   Only compounds with at
 least 50%  detected readings  within each of the three surveys were
 considered for further statistical comparisons.
         For most compounds,  the percentage of samples  with
 detected results was  consistent across the surveys.  Low
 detection  percentages were reported for most  chlorobenzenes (with
 the  exception of hexachlorobenzene),  phosphate triesters, and
 PAHs, while  some pesticides  (such as  p,p-DDE  and beta-BHC)  had
 very high  detection percentages.
         To identify those compounds in Table 8-6 where
 significant  differences were  present  (at the  0.05 level)  in the
percent  detected value between  the three surveys, a chi-square
 test  for homogeneity  was  used.   Among pesticides, significant
differences  in  the percent detected value  were present  for  p,p-
                               8-10

-------
         Table 8-6.  Average Iiipid-Adjusted Limit of Detection (LOD,  ng/g)  and Percent of Composites
                      with Detected Concentrations, for Compounds Analyzed in the FY86 NHATS
                      and Also Analyzed in the FY82 and/or FY84 NHATS(1*
                                              FY82
FY84
FY86
00
I
Compound

p,p-DDT*
O,p-DDT
p,p-DDE
o,p-DDE
o,p-DDD
ALPHA-BHC
BETA-BHC
GAMMA- BHC (LINDANE)
DELTA-BHC
ALDRIN
DIELDRIN*

ENDRIN
TRANS -NONACHLOR*
OXYCHLORDANE
HEPTACHLOR EPOXIDE
HEPTACHLOR
MIREX*
GAMMA- CHLORDANE

1, 2-DICHLOROBENZENE*
1,2,3- TRICHLOROBENZENE
1,2, 4 -TRICHLOROBENZENE
1,3, 5 -TRICHLOROBENZENE
1,2,3, 4 -TETRACHLOROBENZENE
1,2,3, 5 -TETRACHLOROBENZENE
1,2,4, 5 -TETRACHLOROBENZENE
PENTACHLOROBENZENE
HEXACHLOROBENZENE*
Mean

31.

13.



34.



117.


45.

21.

22.


26.

25.




25.
18.
LOD

2

7



0






8

4

6


3

4




9
5
(% det.)
PESTICIDES
( 67.6%)

(100.0%)



( 93.0%)



( 32.6%)


( 57.1%)

( 69.8%)

( 14.0%)

CHLOROBENZENES
( 11.6%)

( 4.4%)




( 0.0%)
( 79.1%)
Mean

48.
13.
352.
13.
125.
19.
212.
18.
18.
13.
19.

38.
14.
16.
15.
19.
13.
13.


13.
13.
13.
13.
13.
13.
13.
15.
LOD

7
5

2

9

5
2
1
4

7
2
5
2
1
1
0


0
1
0
0
0
0
0
2
(% det.)

( 88
( 0
( 95
( 4
( o
( o
( 89
( 2
( o
( o
( 38

( o
( 95
( 82
( 80
( o
( 4
( o


( o
( 4
( o
( o
( o
( o
( 0
( 82

.9%)
.0%)
.5%)
.3%)
.0%)
.0%)
.1%)
.2%)
.0%)
.0%)
.5%)

.0%)
.6%)
.6%)
.4%)
.0%)
.3%)
.0%)


.0%)
.3%)
.0%)
.0%)
.0%)
.0%)
.0%)
.6%)
Mean

9.
10.
LOD

14
9
(%

(
(
det.)

96.0%)
0.0%)
(100. 0%)(2>
13.
13.
11.
30.
11.
12.
11.
123.

146.
26.
20.
31.
35.
10.
10.

10.
11.
10.
11.
11.
11.
10.
10.
33.
7
5
0
8
7
3
6



9
0
9
2
9
8

3
8
2
1
7
6
8
1
0
(
(
(
(
(
(
(
(
(
(
(
(
(
(
(
(

(
(
(
(
(
(
(
(
(
0.0%)
0.0%)
0.0%)
92.0%)
4.0%)
0.0%)
0.0%)
12.0%)
62.0%)^
0.0%)
92.0%)
78.0%)
94.0%)
0.0%)
32.0%)
0.0%)

0.0%)
0.0%)
0.0%)
0.0%)
0.0%)
0.0%)
0.0%)
0.0%)
98.0%)

-------
                                              Table  8-6.   (cont.)
                                               FY82
                                FY84
                               FY86
        Compound
Mean LOD   (% det.)
Mean LOD   (% det.)
Mean LOD   (% det.)
oo

H
to

DIMETHYL PHTHALATE
DIETHYL PHTHALATE*
DI-N-BUTYL PHTHALATE*
BUTYL BENZYL PHTHALATE
BIS (2-ETHYLHEXYL) PHTHALATE*

TRIBUTYL PHOSPHATE
TRIPHENYL PHOSPHATE*
TRIS (2-CHLOROETHYL) PHOSPHATE
TRITOLYL PHOSPHATE

NAPHTHALENE*
PHENANTHRENE
FLUORANTHENE
CHRYSENE
ACENAPHTHENE
ACENAPHTHALENE
FLUORENE
PYRENE

MONOCHLOROBIPHENYL
DICHLOROBIPHENYL
TRICHLOROBIPHENYL
TETRACHLOROBIPHENYL
PENTACHLOROBIPHENYL
HEXACHLOROBIPHENYL
HEPTACHLOROBIPHENYL*


47.7
299.
240.


108.
333.
89.7


19.3
21.6





22.6



20.3
17.8
42.6
48.4
50.6
PHTHALATE ESTERS

( 47.6%)
( 50.0%)
( 73.8%)

PHOSPHATE TRIESTERS
( 2.3%)
( 38.1%)
( 2.2%)

PAHS
( 41.9%)
( 14.0%)





( 0.0%)
PCBs


{ 22.7%)
( 54.5%)
( 72.7%)
( 75.0%)
( 52.3%)

14.2
14.3

24.0
38.7

14.2
13.5
38.7
48.7

13.1
13.0
14.1
16.4
13.0
13.1
14.0
12.9

13.0
13.0
14.2
31.5
16.4
13.1
15.0

( 0.0%)
( 7.7%)
(100.0%)
( 61.5%)
( 0.0%)

( 0.0%)
( 61.5%)
( 0.0%)
( 0.0%)

( 23.9%)
( 21.7%)
( 2.2%)
( 4.3%)
( 0.0%)
( 0.0%)
( 2.2%)
( 4.3%)

( 0.0%)
( 0.0%)
( 39.1%)
( 41.3%)
( 84.8%)
( 97.8%)
( 84.4%)

27.1
27.9
23.6
26.6
27.4

115.
50.7
139.
48.0

13.6
11.1
10.7
10.7
10.7
11.0
12.2
10.2

12.8
13.0
20.2
69.6
65.0
110.
65.8

< 0.0%)
( 10.0%)
( 76.0%)
( 72.0%)
( 78.0%)

( 0.0%)
( 4.0%)
( 0.0%)
( 2.0%)

( 84.0%)
( 8.0%)
( 2.0%)
( 4.0%)
( 0.0%)
( 0.0%)
( 0.0%)
( 0.0%)

( 0.0%)
( 0.0%)
( 30.0%)
( 66.0%)
( 88.0%)
( 94.0%)
( 86.0%)

-------
                                             Table 8-6.   (cent.)
                                              FY82                     FY84                   FY86
       Compound                       Mean  LOD   (%  det.)       Mean LOD  (% det.)      Mean LOD  (% det.)

OCTACKLOROBIPHENYL*
NONACHLOROBIPHENYL
DECACHLOROBIPHENYL*

48.8
42.3
104.
PCBs (cont.i
( 40.9%)
( 13.6%)
( 6.8%)
>
13.2
19.1
20.7

( 17.8%)
( 22.2%)
( 35.6%)

33.9
32.3
43.7

( 44.0%)
( 26.0%)
( 28.0%)
     *  Percent detection differs signficantly across surveys at the 0.05 level, based on a chi-square test
     of homogeneity.
     (1)  LODs were obtained in each survey only for composites having not-detected or trace results.  LCDs
     were not adjusted  for  surrogate  recoveries.   Statistics are presented only for those compounds analyzed
     within  a given survey.
oo    p)  The detection percentage was 100% under both quantitation ions used in FY86  (see Section 5.1.2).
£)    ®  Detection percentage based on redefined quantitation methods in FY86  (see Section 5.1.2).

-------
DDT, dieldrin, trans-nonachlor, heptachlor epoxide, and mirex.
For each of these pesticides, significance was primarily the
result of low detection percentages observed in the FY82 survey.
For p,p-DDT, the detection percentage increased from 67.6% in
FY82 to 96% in FY86.  This increase may be partially explained by
a substantial reduction in the average LOD for p,p-DDT in the
FY86 survey.  Percent detection also increased in FY86 for mirex,
from below 15% in both FY82 and FY84 to 32% in FY86, while
accompanied by a gradual reduction in the average LOD across
these surveys.
         Percent  detection  of  hexachlorobenzene  increased  across
the FY82 to FY86 surveys, from 79.1% to 98%.  These differences
across surveys were statistically significant, but were not
accompanied by corresponding reductions in the average LOD,  The
average percent detection declined in FY86 to 4% for triphenyl
phosphate from above 38% in the other two surveys; this decline
was statistically significant.   Naphthalene was the only PAH
with a high percent detection in FY86 (84%), leading to
statistically significant differences in the percentages across
surveys.
         Significant differences  in percent detection were  also
observed for diethyl phthalate (where the average percentage
dropped substantially from the FY82 value of 47.6%), di-n-butyl
phthalate  (where the average percentage increased from 50% in
FY82 to 100% in FY84), and bis (2-ethylhexyl)  phthalate (0% in
FY84 to 78% in FY86).  However for di-ethyl phthalate,  the
decreasing percentages were accompanied by decreases in the
average LOD.  This  indicates that overall measured concentrations
have decreased across the surveys for this compound, despite
potential contaminations in the phthalates for the FY86 survey as
suggested by the QC data analysis.  The contamination issue was
more evident for bis (2-ethylhexyl)  phthalate, which was detected
in  all method blanks in the FY86 analysis.
         Significant differences  in percent detection across
surveys were also observed in the higher-order PCB homologs.
                               8-14

-------
Average percent detection was  low  in FY82 compared  to  the  other
two surveys for hexa-, hepta-, and deca-chlorobiphenyls, leading
to statistically significant differences in percent detection
across the surveys.  However,  a corresponding reduction  in the
average LOD from FY82 to FY84  did  not hold for FY86.   In fact,
the average detection limit in FY86 for these homologs exceeded
that for FY82 in hexa- and hepta-chlorobiphenyls.  This  result
appears to agree with other findings indicating unusually  high
concentrations for these homologs  in FY86, which may derive from
analytical sources rather than environmental sources.
        Thus  while  average percent detection  in  FY86  remained at
levels consistent with earlier surveys, occasional increases were
observed for some compounds.   However,  the differences in
analytical methods and recoveries observed from one survey to
another imply that the differences may be the result of
analytical rather than environmental effects.

8.3  DESCRIPTIVE STATISTICS ON MEASURED CONCENTRATIONS
        A  total of  54 semivolatile organic compounds were
analyzed in the FY86 NHATS and in at least one of the FY82 and
FY84 NHATS.  The extent to which statistical comparison of
measured concentrations was appropriate among these 54 compounds
was determined by initially summarizing the analytical results
within each survey through simple descriptive statistics.  Some
basic differences in the results across surveys were apparent
when reviewing summary statistics.   The summaries also assisted
in interpreting comparison findings.
        Initially,  scatterplots were produced for each of  these
compounds in order to identify any large differences or
patternistic behavior in the  measured concentrations between and
within the three surveys.  Then,  two approaches to calculating
descriptive statistics were applied to the concentrations.   In
the first approach,  simple arithmetic averages and standard
errors of the measured concentrations were calculated.   While
these statistics summarize the measured concentrations across
                               8-15

-------
analytical samples, they are not necessarily good estimates of
the national average concentration.  A better approximation of
national average concentration can result by taking weighted
averages of the observed concentrations.  Thus the second
approach was to partition the nation into subpopulations,
calculate average concentrations within each subpopulation, and
weight each average by the 1980 Census population percentage for
its respective subpopulation.  The second approach can lead to a
improved estimate of national average concentration for each
compound, regardless of whether further statistical analysis was
warranted on the compound concentrations.
         In the descriptive summaries  from both approaches,
measured concentrations were defined as the total mass detected,
divided by the sample lipid weight.  Whenever a compound was not
detected within a sample, measured concentrations were taken to
be one-half of the LOD  (as was done in the statistical analyses) .
The percent detected values in Table 8-6 indicate the frequency
with which not-detected results were observed within each
compound.  The descriptive statistics presented in the following
subsections were calculated on measured concentration both
adjusted and unadjusted for surrogate recoveries.

8.3.1.  Scatterplota of the Sample Concentrations
         Prior to  calculating descriptive statistics,
scatterplots of measured concentrations were generated for all
compounds detected in at least 50% of the FY86 samples and which
were analyzed  in the FY82 NHATS and/or the FY84 NHATS.  The
scatterplots illustrate any general differences or trends in the
concentrations between surveys and between batches within
surveys.  Plots were generated for concentrations both unadjusted
and adjusted for surrogate recoveries.  These plots are located
in Appendices G and H, respectively.
         The  concentrations are plotted  as a  function  of  the
analysis date in these scatterplots.  Therefore any trends in the
concentrations over time or batches are highlighted in these
                               8-16

-------
plots.  In addition, the plotting symbols indicate the age group
represented by the result  (1 = 0-14 years, 2 = 15-44 years, 3  =
45+ years).  Results in Chapter 7 indicated that age group had a
significant effect on the values of the measured concentrations.
        These  plots  illustrate  the  large  extent  to which
increasing concentrations were associated with increasing age  for
most compounds.  Also, the unadjusted concentrations for the FY86
NHATS appeared to be more variable than in the previous surveys,
excluding the effects of occasional outliers.   This is
especially apparent in plots of PCBs and some pesticides.
However, variability appears to be more consistent across surveys
when considering surrogate-adjusted concentrations.   The plots
suggest that this is the result of an increase in variability
associated with the surrogate-adjusted concentrations across all
surveys.
        These  scatterplots also illustrate apparent trends from
batch to batch within a survey.   For example, unadjusted
concentrations of beta-BHC tend to decrease in later batches in
the FY84 analysis.  The difference between Batch 1 and the other
batches in FY86 oxychlordane concentrations is also evident
(recall that Batch 1 data were excluded from statistical analysis
for oxychlordane).
        The primary purpose of reviewing scatterplots prior to
further statistical summaries or analyses  was to depict any
obvious differences in results across surveys.   Extreme
differences in the values of the concentrations between surveys
would indicate that statistical  techniques may not be  necessary
in making such conclusions.  Extreme differences from one survey
to another were not apparent for these compounds based on the
scatterplots.

8.3.2.  Unweighted National Averages
        Appendix  I presents simple arithmetic averages  (with
their standard errors)  of the measured concentrations  among the
54 compounds for each of the three surveys.   The averages were
                              8-17

-------
 calculated across all composite samples in Table 8-3  where
 measured concentrations were reported for the given compound.
 Averages were calculated for two endpoints:   on measured
 concentrations adjusted for surrogate recoveries (Table  1-1),  and
 on unadjusted concentrations (i.e.,  the recorded concentrations)
 (Table 1-2) .   The adjustment for surrogate recoveries was
 performed to more accurately estimate actual concentrations
 within each sample.  The adjustment  was described in  Section 5.2.
         With some  exceptions, concentrations or LCDs were
 reported for all composites for a given compound analyzed  within
 a  survey-   However in the FY84  survey,  results for dieldrin,
 endrin,  the phthalate esters, and the phosphate triesters  were
 reported in only 13 of the 46 composite samples.
         The descriptive statistics in Appendix I were calculated
 only to summarize the results of the three surveys.   Because
 these summaries ignore demographic effects which were determined
 to be significantly associated  with  measured concentration,  the
 descriptive statistics do not necessarily estimate national
 average concentrations in the respective surveys.   Such  estimates
 were obtained from statistical  modelling techniques for  a  limited
 number of  compounds.

 8.3.3.   Weighted National Averages
         Estimates of the national average concentration
 estimates  were  obtained in this study through statistical
 modelling  procedures  rather than from simple descriptive
 statistics as discussed above.   However,  statistical  modelling
 was  reserved only for those compounds with sufficiently  high
 detection  percentages within each survey.  Thus an approach  was
 necessary  for calculating more  accurate national  estimates than
 the  simple descriptive statistics, regardless of  detection
 percentages.  To do this,  averages of composite concentrations
 were  calculated within each of  the three age groups (0-14  years,
 15-44 years, 45+ years)  and were weighted by the  population
proportions within  each group.   Age  group was selected for the
                               8-18

-------
weighting criterion because its effect on measured concentrations
was most commonly significant across the demographic groups
within each survey.  In addition, sufficient numbers of sample
results existed to provide sufficient accuracy in averages within
each age group.
        Calculating the weighted national averages was a
multistage process.  First, unweighted arithmetic averages were
calculated for each of the three age groups.  Then each age-group
average was multiplied by the population proportion in that age
group (based on the 1980 Census).  These three results were then
summed to obtain the final estimate.
        Tables  8-7 and 8-8 present  the weighted national
averages for the 54 compounds analyzed in the FY86 and in the
FY82 and/or FY84 NHATS.   The results in Table 8-7 are based on
the actual measured concentrations,  while the results in Table
8-8 are calculated from concentrations adjusted for surrogate
recoveries.
        Results from these two  tables indicate that for some
compounds, the values of descriptive statistics differ greatly
between surveys.  Some of these differences may be more likely
due to differences in laboratory methods and instrumentation than
to differences rooted in environmental effects.  For example, the
LODs for some of the phthalate esters and phosphate triesters
were found to average much higher in the FY82 NHATS than in the
other surveys (Table 8-6), leading to higher average measured
concentrations among the FY82 composites for these compounds.
The largest difference in average concentration occurred with
triphenyl phosphate,  where the FY82 weighted average was two
orders of magnitude higher than in the other two surveys.  Most
FY82 composite samples report high concentrations for this
compound relative to the other surveys.
        The weighted average  concentration  for bis  (2-
ethylhexyl)  phthalate also increased nearly two orders of
magnitude from FY84 to FY86,  primarily due to the presence of
samples with detected results in FY86 (78%, versus no detected
                               8-19

-------
        Table 8-7.  Weighted National Averages  of  Unadjusted Concentrations (ng/g)  and Standard Errors
                    for Compounds Analyzed  in the  FY86  NHATS and Also Analyzed in the FY82 and/or
                    FY84 NHATS(1)
O>
 i
10
O
FY82
Compound®

p,p-DDT
o,p-DDT
p,p-DDE
o,p-DDE
o,p-DDD
ALPHA-BHC
BETA-BHC
GAMMA-BHC (LINDANE)
DELTA-BHC
ALDRIN
DIELDRIN
ENDRIN
TRANS -NONACHLOR
OXYCHLORDANB
HEPTACHLOR EPOXIDE
HEPTACHLOR
MIREX
GAMMA- CHLORDANE

1 , 2-DICHLOROBENZENE
1,2,3 -TRICHLOROBENZENE
1,2,4 -TRICHLOROBENZENE
1,3, 5 -TRICHLOROBENZENE
1,2,3,4- TETRACHLOROBENZENE
1,2,3, 5 -TETRACHLOROBENZENE
1,2,4, 5 -TETRACHLOROBENZENE
PENTACHLOROBENZENE
HEXACHLOROBENZENE
Weighted
Avg.

118. (

FY84
Weighted
(S.E.) Avg.
PBSTXCXDBS
27. )

1070. (160. )



176. (



105. (

85.0 (

48.9 (

9.91 (


9.67 (

7.01 (




6.46 (
80.6 (



24. )



23. )

22.0 )

11.2 )

1.45)

CHLOROBBNZBNBS
1.48)

0.54)




0.29)
39.9 )

88
6
796
7
65
10
130
9
9
6
22
18
72
45
47
9
7
6


6
7
6
6
6
6
6
23

.1 1
.73 i

.19
.0 i
.2

.61 '
.26
.58
.2
.1
.3
.7
.1
.56
.35
.55


.55
.29
.55
.55
.55
.55
.55
.3
(S.E.)

( 12
( 0
( 66
( 0
( 16
( 3
( 17
( 2
( 1
( 0
( 6
( 3
( 4
( 3
( 4
( 1
( 0
( 0


( o
( 0
( 0
( 0
( 0
( 0
( 0
( 2

.2 )
.24)
)
.51)
.7 )
.6 )
)
.67)
.92)
.17)
.8 )
.7 )
.8 )
.9 )
.6 )
.55)
.62)
.17)


.17)
.54)
.17)
.17)
.17)
.17)
.17)
.8 )
FY86
Weighted
Avg. (S.

205.
5.
2530.
7.
6.
5.
183.
9.
6.
5.
55.
71.
142.
112.
73.
13.
12.
5.

5.
6.
5.
5.
6.
5.
5.
5.
49.


61

07
95
66

99
33
98
2
6


6
6
5
56

30
05
23
69
01
96
54
19
3

( 42
( o
(280
( 0
( 0
( o
( 16
( 3
( o
( o
( 10
( 9
( 12
( 10
( 4
( 7
( 1
( o

( o
( o
( o
( o
( o
( o
( o
( o
( 3
E.)

. )
.75)
. )
.94)
.92)
.75)
. )
.42)
.84)
.80)
.0 )
.0 )
. )
. )
.6 )
.7 )
.8 )
.74)

.68)
.81)
.70)
.76)
.80)
.79)
.74)
.69)
.8 )

-------
                                             Table  8-7.   (cont.)
                                              FY82
                                FY84
       Compound®
Weighted
  Avg.    (S.E.)
Weighted
  Avg.    (S.E.)
00

to
                              FY86
Weighted
  Avg.    (S.E.)
PHTHALATE ESTERS
DIMETHYL PHTHALATE
DIETHYL PHTHALATE
DI-N-BUTYL PHTHALATE
BUTYL BENZYL PHTHALATE
BIS (2-ETHYLHEXYL) PHTHALATE

75
351
237


.2 ( 25.4 )
(123. )
(56. )

7.22
8.04
202.
62.6
18.1
( 0.64)
( 0.85)
(44. )
( 21.3 )
( 3.7 )
13.3
17.6
59.9
62.8
869.
( 1.7 )
( 2.5 )
( 11.6 )
( 8.1 )
(396. )
PHOSPHATE TRIESTERS
TRIBUTYL PHOSPHATE
TRIPHENYL PHOSPHATE
TRIS (2-CHLOROETHYL) PHOSPHATE
TRITOLYL PHOSPHATE

NAPHTHALENE
PHENANTHRENE
FLUORANTHENE
CHRYSENE
ACENAPHTHENE
ACENAPHTHALENE
FLUORENE
PYRENE

MONOCHLOROBIPHENYL
DICHLOROBIPHENYL
TRICHLOROBIPHENYL
TETRACHLOROB I PHENYL
PENTACHLOROBIPHENYL
HEXACHLOROBIPHENYL
32
1630
28


14
8





6



8
20
68
122
.9 ( 2.1 )
(1520. )
.9 ( 3.6 )

PAHs
.2 ( 2.1 )
.24 ( 0.76)





.50 ( 0.30)
PCBs


.86 ( 0.73)
.9 ( 2.5 )
.2 ( 9.2 )
(18. )
7.22
57.0
18.1
23.3

9.67
21.3
7.25
10.3
6.55
6.60
8.42
20.8

6.55
6.55
10.4
32.5
74.3
132.
( 0.64)
( 39.1 )
( 3.7 )
( 3.7 )

( 0.94)
( 7.7 )
( 0.44)
( 1.7 )
( 0.17)
( 0.18)
( 1.41)
( 12.1 )

( 0.17)
( 0.17)
( 0.6 )
( 3.9 )
( 8.7 )
( 11. )
56.7
30.9
68.3
24.1

20.1
6.14
5.63
5.73
5.52
5.67
6.27
5.26

6.62
6.70
14.2
72.2
162.
373.
( 7.1 )
( 6.3 )
( 8.5 )
( 3.0 )

( 2.4 )
( 0.76)
( 0.74)
( 0.71)
( 0.73)
( 0.76)
( 0.84)
( 0.70)

( 1.16)
( 1.17)
( 1.8 )
( 6.3 )
(15. ) .
( 25. )

-------
                                        Table 8-7.   (cont.)
                                        FY82
                                                                     FY84
FY86
Compound*2*
Weighted
Avg. (S.E
.)
FCBs (cont
HEPTACHLOROBIPHENYL
OCTACHLOROBIPHENYL
NONACHLOROBIPHENYL
DECACHLOROBIPHENYL
59
41
21
37
.6
.7
.0
.4
( 9-
( 8.
( 5.
( 3.
5 )
8 )
5 )
3 )
Weighted
Avg. (S.E.)
.)
90
12
13
15

.6
.3
.8
.7

( 11.
( 2.
( 1.
( 1.

2 )
6 )
9 )
9 )
Weighted
Avg.

149.
49.0
22.7
28.2
(S.E.)

( 17.
( 7.6
( 3.4
( 3.7
i

)
)
)
)
10
W  Weighted averages  are the sum of the arithmetic averages of the unadjusted concentrations within
each of the three age groups  (0-14 years, 15-44 years, 45+ years) , each multiplied by the proportion of
the national population  in that age group according to the 1980 Census  (0.23, 0.46, and 0.31,
respectively) .  Statistics are presented only for  those compounds  analyzed within a given survey.

®  Concentrations  of  p,p-DDE and dieldrin for FY86 originated from the alternative approaches
documented  in Section 5.1.2.

-------
   Table  8-8.   Weighted National Averages of Surrogate-Adjusted Concentrations  (ng/g) and Standard Errors
                for Compounds Analyzed in the FY86 HHATS and Also Analyzed in the FY82 and/or FY84 NHATS(1)
oo
i
to
CO
FY82
Compound®
p,p-DDT
0,p-DDT
p,p-DDE
0,p-DDE
o,p-DDD
ALPHA- BHC
BETA- BHC
GAMMA- BHC (LINDANE)
DELTA- BHC
ALDRIN
DIELDRIN
ENDRIN
TRANS -NONACHLOR
OXYCHLORDANE
HEPTACHLOR EPOXIDE
HEPTACHLOR
MIREX
GAMMA- CHLORDANE
Weighted
Avg.
203.
1850.
305.

182.

147.

84.5

17.2

(S.E.)
i
PESTICIDES
( 45. )
(260. )
( 40. )

(

(

(

(


38.

36.

18.5

2.4


)

)

)

)

FY84
Weighted
Avg.
133. (
10.1 (
1200. (
10.8 (
97.8 (
15.3 (
196. (
14.5 (
13.9 (
9.91 (
33.7 (
27.3 (
109. (
68.9 (
71.0 (
14.4 (
11.1 (
9.86 (
(S.E.)
18
0
90
0
24
5
24
3
2
0
9
5
7
5
6
2
0
0
'3 )
.1 )
.1 )
.2 )
'.B )
.8 )
.24)
.8 )
.4 )
)
.6 )
.6 )
.2 )
.9 )
.24)
FY86
Weighted
Avg.
181
4
2250
6
6
4
162
10
5
5
48
63
126
98
58
12
10
4
(S.E.)
( 35
.92 ( 0
(230
.20 ( 0
.09 ( 0
.96 ( 0
( 13
.2 ( 3
.55 ( 0
.24 <
.4 I
.0 i

.8 i
.3 i
.2 i
.9 i
.88 i
[ 0
( 8
( 7
( 10
( 8
( 3
( 6
( 1
( 0
!ei)
[77)
.75)
.62)
.2 )
.69)
.65)
.2 )
.3 )
)
.1 )
.3 )
.3 )
.5 )
.61)
CHLOROBENZENES
1 , 2 -DICHLOROBENZENE
1,2,3 -TRICHLOROBENZENE
1,2, 4 -TRICHLOROBENZENE
1,3, 5 -TRICHLOROBENZENE
1,2,3, 4 -TETRACHLOROBENZENE
1,2,3, 5 -TETRACHLOROBENZENE
1,2,4, 5 -TETRACHLOROBENZENE
PENTACHLOROBENZENE
HEXACHLOROBENZENE
19.1

13.8




12.7
139.
(

(




(
(
2.8

0.9




0.6
67.
)

)




)
)

22.4 (
25.0 (
22.4 (
14.9 (
14.9 (
14.9 (
15.1 (
41.2 (

0
1
0
0
0
0
0
4

.5 )
.6 )
.5 )
.4 )
.4 )
.4 )
.4 )
.8 )
6
9
8
9
7
7
7
6
49
.97
.73
.40
.15
.83
.76
.21
.83
.9
( 0
( 1
( 1
( 1
( 0
( 0
( 0
( 0
( 3
.83)
.18)
.02)
.11)
.97)
.96)
.89)
.85)
.6 )

-------
                                              Table 8-8.   (cent.)
CO
t
to
FY82
Compound®
Weighted
Avg.
(S.E.)
FY84
Weighted
Avg.
(S.E.)
FY86
Weighted
Avg.
(S.E.)
PHTHALATE ESTERS
DIMETHYL PHTHALATE
DIETHYL PHTHALATE
DI-N-BDTYL PHTHALATE
BUTYL BENZYL PHTHALATE
BIS (2-ETHYLHEXYL) PHTHALATE

131.
608.
418.


( 40. )
(168. )
( 59. )

14.6 (
12.7 I
454. I
149. I
37.0 1
; 1.1 )
: 1.2 )
; 76. )
; 32. )
[ 6.2 )
12.9
17.0
58.0
60.2
847.
( 1.5 )
( 2.3 )
( 10.4 )
( 7.3 )
(356. )
PHOSPHATE TRIESTERS
TRIBUTYL PHOSPHATE
TRIPHENYL PHOSPHATE
TRIS (2-CHLOROETHYL) PHOSPHATE
TRITOLYL PHOSPHATE

NAPHTHALENE
PHENANTHRENE
FLUORANTHENE
CHRYSENE
ACENAPHTHENE
ACENAPHTHALENE
FLUORENE
PYRENE

MONOCHLOROBIPHENYL
DICHLOROBIPHENYL
TRICHLOROBIPHENYL
TETRACHLOROBIPHENYL
PENTACHLOROBIPHENYL
HEXACHLOROBIPHENYL
57.1
2840.
50.2


24.3
14.1





11.1



14.6
30.8
134.
239.
( 3.5 )
(2520. )
( 6.0 )

PAHs
( 3.5 )
( 1.3 )





( 0.5 )
PCBS


( 1.2 )
( 3.5 )
(18. )
( 34. )
10.9 <
86.5 1
27.3 1
35.2 1

14.9 1
32.7 1
11.2 1
15.8 1
10.1 1
10.1 1
13.0 1
31.9 1

9.95 1
10.1 i
16.2 i
50.5 i
115. <
204. i
; 0.9 )
[ 56.3 )
[ 5.4 )
[ 5.4 )

[ 1.4 )
[ 11.6 )
[ 0.7 )
[ 2.6 )
[ 0.3 )
[ 0.3 )
( 2.1 )
( 18.2 )

( 0.25)
( 0.3 )
( 1.0 )
( 5.8 )
(13. )
(16. )
54.7
29.8
65.9
23.2

20.0
6.08
5.58
5.68
5.46
5.62
6.21
5.21

6.44
6.01
13.0
58.3
137.
314.
( 6.4 )
( 5.7 )
( 7.7 )
( 2.7 )

( 2.3 )
( 0.73)
( 0.71)
( 0.69)
( 0.71)
( 0.73)
( 0.81)
( 0.68)

( 1.07)
( 0.96)
( 1.5 )
( 4.7 )
( 11. )
( 19. )

-------
                                            Table  8-8.   (cont.)
FY82
Compound®

HEPTACHLOROBIPHENYL
OCTACHLOROBIPHENYL
NONACHLOROBIPHENYL
DECACHLOROBIPHENYL
Weighted
Avg.

117.
84.1
34.6
59.8
(S.E.)
PCBs (cont.)
(18. )
( 17.2 )
( 8.7 )
( 4.8 )
FY84
Weighted
Avg.

140.
19.0
21.5
24.6
(S.E.)

( 17. )
( 3.9 )
( 2.9 )
( 2.7 )
FY86
Weighted
Avg.

126.
42.9
20.6
27.5
(S.E.)

(13. )
( 5.9 )
( 2.8 )
( 3.1 )
     (1)  Weighted averages are the sum of the arithmetic averages of the  surrogate-adjusted concentrations
     within each of the three age groups (0-14 years, 15-44 years,  45+ years),  each multiplied by the
     proportion of the national population in that age group according to the 1980 Census (0.23, 0.46, and
     0.31,  respectively).   Statistics are presented only for those compounds analyzed within a given survey.

?    ®  Concentrations of p,p-DDE and dieldrin for FY86 originated from  the  alternative approaches
*2    documented in Section 5.1.2.

-------
 results  in FY84).   However,  bis (2-ethylhexyl) phthalate  also was
 detected in all method blanks in FY86  and was  associated  with low
 precision results,  removing it from consideration  for  statistical
 analysis in the FY86 NHATS.
         For p,p-DDE, the national average concentration based on
 weighted averages  was higher in FY86 than in previous  surveys.
 However,  the QC data analysis for the  FY86 NHATS suggested that
 background levels  were high for this compound, preventing
 recovery estimates from being interpretable.
         The findings in this subsection imply that differences
 between  the surveys may not be environmental in nature but may
 result from analytical differences (such  as possible
 contamination or interferences,  as seen with the phthalates in
 the  FY86 analysis).   However,  other results are not so easily
 explained.   Weighted averages for hexachlorobenzene were  reduced
 from FY82  levels,  despite  higher percentages of detected  results
 compared to FY82.   Similarly,  average  concentrations for
 naphthalene in FY86 did not increase at the level  suggested by
 the  large  increase in detected results from previous surveys.
 The  effect  of  adjusting for surrogate  recoveries is seen  for
 heptachlorobiphenyl,  where a large increase in the weighted
 average  of  unadjusted concentrations for  FY86  (Table 8-7) was not
 matched  when considering adjusted concentrations (Table 8-8).
 The  results in Table 8-8 are more likely  to estimate actual
 concentrations across the  composite samples than the unadjusted
 data  results in Table 8-7.
         One should remember that no general  conclusions  on  true
 national concentrations should be made from these tables  of
 descriptive statistics  unless  results  of  QC data analysis and
 statistical modelling agree  with the findings.

 8.4   STATISTICAL COMPARISON OF NATIONAL CONCENTRATION ESTIMATES
         The results from the FY82, FY84,  and FY86  NHATS  for
semivolatiles  in composite  samples were statistically compared by
fitting the  additive  model  (Chapter 6) on data for each survey
                               8-26

-------
separately, calculating marginal estimates and standard errors,
and comparing these estimates across surveys through approximate
95% confidence intervals.  In order to compensate for differences
in recoveries existing across the three surveys,  the additive
model was fit to the surrogate-adjusted concentrations within
each survey (see Section 5.2 on the adjustment method).
Previously published results from the FY82 and FY84 NHATS may
differ from those presented in this section as the additive model
and the adjustment for surrogate recoveries were not previously
considered in these surveys.  While adjusting for surrogate
recoveries attempted to remove effects of differing recoveries
across surveys and to better estimate actual sample
concentrations, other differences in analytical method and design
(documented in Section 8.1) may contribute greatly toward overall
differences in the marginal estimates between the surveys.

8.4.1.  Semivolatile Compounds Included in Statistical Comparison
        Statistical comparisons yield useful conclusions  only
when sufficient numbers of detectable results are available from
each survey.  Specifically, statistical analyses were performed
on only those compounds detected in at least 50% of the
composites within each survey.  In addition, comparisons were
made only on compounds which were not removed from consideration
for statistical analysis in FY86 as a result of the QC data
analysis (Section 5.3); thus no phthalates were considered in. the
statistical comparison.  Based on these criteria, the compounds
considered for statistical analysis across surveys were the
following:

        p,p-DDT
        p,p-DDE
        Beta-BHC
        Trans-nonachlor
        Heptachlor epoxide
        Hexachlorobenzene
        Te t rachlorobiphenyl
        Pentachlorobiphenyl

                               8-27

-------
     •    Hexachlorobiphenyl
     •    Heptachlorobiphenyl.

Thus the statistical comparisons were limited to only ten of the
most prevalent pesticides,  PCB homologs, and chlorobenzenes found
in the NHATS over the years.
         In addition,  the PCB  parameters introduced in Section
6.2.1.2  (total PCB concentration, chlorobiphenyl distribution
across homologs, and chlorination level) were estimated for FY82,
FY84, and  FY86 from the  estimated average concentration levels
for  five PCB homologs resulting from fitting the additive model.
The  additive model was fitted to data for each of these five
homologs (tetra- through octa-CB) since these homologs had high
detection  percentages in FY86.  The method for estimating these
parameters and their standard errors was documented in Section
6.2.1.2.

8.4.2.  Fitting the Additive Model
         The method  for  fitting  the  additive model,  as well as
the form of the model itself,  was essentially similar between the
three surveys.  The primary differences in the model fitting
approaches across surveys were as follows:

     •    The FY86 model  fitting  included an effect  for Batches
         1-3 versus  4-5  (Section 6.1).   This effect  was not
         included in the  model for either FY82 or FY84.
     •    For FY82 and FY84,  the  errors attributable  to
         measurement error  and specimen  sampling error were
         combined into one  error term, rather than  individually
         estimated as in  the FY86 analysis.  An estimate of
         measurement error  was not determined for these two
         surveys because  FY82 QC data were not readily available,
         and FY84 QC data were not statistically analyzed.
         Preliminary analyses indicated  that measurement error
         from the FY86 QC data analysis  was not appropriate for
         use in the  FY82  or FY84  analyses.
                               8-28

-------
         One note  should be  made  in  reporting  standard  errors
resulting from the additive model fitting to the FY84 NHATS data.
Large absolute error attributable to MSA sampling was observed
for p,p-DDE, beta-BHC, pentachlorobiphenyl,  and
hexachlorobiphenyl in this survey.  When this error was included
in the formulas for calculating standard errors in the marginal
estimates, these standard errors were inflated by two to three
orders of magnitude relative to the marginal estimates.  Because
these errors were likely not an accurate portrayal of the true
error, the MSA error was not considered in the additive model
fitting in this survey.  Thus the calculated standard errors may
be somewhat underestimated for these four compounds in FY84.

8.4.2.1.  National Estimates.  For the above ten semivolatiles
and total PCB concentration, Table 8-9 presents the estimated
national average concentrations  (and standard errors) for each of
the three surveys, based on fitting the additive model to
surrogate-adjusted concentrations within each survey.  This table
also contains the estimated overall chlorination percentage for
PCBs within each survey.  Along with these estimates, Table 8-9
includes the estimated difference from the FY86 estimate for both
the FY82 and FY84 surveys and the significance level for testing
that this difference differs from zero.  The test was based on
the approximate t-statistic of the form
(i=82, 84), where NAgj, NA^,  and NHgg are the FY82,  FY84,  and FY86
national average estimates and SEg2, SE^,  and SE86 are their
standard errors, respectively.  Approximate significance levels
were calculated using the standard normal distribution.  More
exact significance levels based on the Student-t distribution
(with degrees of freedom obtained through Satterthwaite's
approximation) was deemed too complex to use in this application;

                               8-29

-------
  Table 8-9.  Comparisons  of Predicted National Average Concentrations  (ng/g) for Selected Semivolatiles
              over  the  FY82, PY84,  and PY86 NHATS(1)
FY82
Compound
P,P-DDT
P.P-DDE^
BETA-BHC
TRANS -NONACHLOR
HEPTACHLOR EPOXIDE
HEXACHLOROBENZENE
f TETRACHLOROBIPHENYL
U)
0 PENTACHLOROBIPHENYL
HEXACHLOROBIPHENYL
HEPTACHLOROBIPHENYL
TOTAL PCBS(4)
CHLOR. LEVEL (%)(5)
Mean
189.
1840.
291.
109.
59.4
118.
15.7
78.3
176.
84.6
407.
59.3
(S.E.)
(31.)
(350.)
(54.)
(28.)
(13.4)
(68.)
( 1.4)
( 7.9)
(28.)
(17.0)
(34.9)
( 5.8)
FY84®
Mean
123.
1150.
199.
105.
68.3
42.9
48.8
115.
198.
129.
508.
58.1
(S.E.)
(11.)
(90.)
(24.)
(5.)
(7.1)
(5.4)
(5.9)
(11.)
(11.)
(10.)
(19.5)
( 2.5)
FY86
Mean
177.
2340.
157.
130.
57.6
51.3
56.4
135.
314.
125.
672.
58.3
(S.E.)
(20.)
(270.)
(25.)
(15.)
(4.2)
(4.0)
(4.7)
(15.)
(18.)
(22.)
(34.8)
( 3.5)
FY86-FY82
Diff .
-12.1
498.
-135.'
21.3
-1.73
-66.9
40.7*
56.2*
137.*
40.5
266.*
-1.0 (
(S.E.)
(36.8)
(441.)
(59.)
(31.5)
(14.0)
(68.2)
(4.9)
(17.2)
(34.)
(27.7)
(49.2)
6.8)
P
0.74
0.26
0.02
0.50
0.90
0.33
<0.01
<0.01
<0.01
0.15
<0.01
0.88
Diff.
53.4*
1190.
-42.3
25.8
-10.6
8.38
7.60
19.8
115.*
-3.51
164.*
0.2
FY86-FY84
(S.E.)
(22.4)
*(280.)
(34.7)
(16.1)
(8.2)
(6.73)
(7.58)
(18.7)
(21.)
(24.2)
(39.8)
( 4.3)
P
0.02
<0.01
0.22
0.11
0.20
0.21
0.32
0.29
<0.01
0.88
<0.01
0.96
   Difference is significant at the 0.05 level.

(1)  Estimates originate  from fitting the additive model on surrogate-adjusted concentrations.
®  Error  due to MSA sampling is not included in the standard error estimates.
(3)  m/z  =  316 in FY86 NHATS  (see Section 5.1.2).
(4)  Sum  of concentrations  for tetra- to octa-chlorobiphenyl.
(5)  Overall chlorination level for PCBs,  defined in Section 6.2.1.2.

-------
these significance levels are well approximated by the standard
normal distribution with the sample sizes observed in each
survey.
         Significant differences  from the FY86 national estimate
were observed at the 0.05 level for both the FY82 and PY84
surveys  (Table 8-9).  In the FY82 survey,  the national estimates
for the PCB homologs and total PCBs were lower than in the FY86
survey; the difference was highly significant for tetra-, penta-,
and hexa-chlorobiphenyls, as well as for total PCBs.   However,
except for tetrachlorobiphenyl,  different IQS were used between
the FY82 and FY86 surveys for the PCB homologs.   A significant
difference in the national estimates for beta-BHC was also
observed between FY82 and FY86;  the FY86 estimate was 135 ng/g
lower than the FY82 estimate.  Both surveys used the same IQS for
quantitating beta-BHC.
         In the FY84 survey,  the  national estimate for only one
of the analyzed PCB homologs differed significantly from the FY86
estimate.  The 115 ng/g increase in hexachlorobiphenyl for FY86
relative to FY84 was highly significant.  An increase of 164 ng/g
in total PCBs for FY86 relative to FY84 was also highly
significant.   Increases in the FY86 national estimates for p,p-
DDT and p,p-DDE relative to the FY84 estimates were also
significant at the 0.05 level.  All three of these compounds were
quantitated using the same IQS in the FY84 and FY86 NHATS.
         Table 8-10 presents  the  estimated chlorobiphenyl
distribution across the five prevalent PCB homologs for the FY82,
FY84, and FY86 surveys.  It is clear that the dominance of
hexachlorobiphenyl observed in the FY86 analysis was present in
the FY82 and FY84 surveys as well.

8.4.2.2.  Marginal Estimates.  Marginal estimates for the four
census regions,  three age groups, two sex groups, and two race
groups are presented  (with their standard errors) in Tables J-3
through J-6 (Appendix J) for the ten analyzed semivolatiles,
total PCBs, and overall chlorination level across the three
                              8-31

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        Table  8-10.  Chlorobiphenyl  Distribution Across the
                      Five PCB Homologs Considered for Statistical
                      Analysis in the FY86 NHATS
. /
* v""
t '
, PCB Homolog
Tetrachlorobiphenyl
Pent achl orobiphenyl
Hexachlorobiphenyl
Heptachlorobiphenyl
Octachlorobiphenyl
V Chlorobiphenyl Distribution^
F1T82 SHUTS FYS4 mH&TS FfBV.MHKXS
3.86%
19.3%
43.4%
20.8%
12.7%
9.60%
22.6%
39.1%
25.3%
3.46%
8.39%
20.0%
46.6%
18.6%
6.35%
(1) Chlorobiphenyl distribution for homolog i (i=4,5,6,7,8)  is calculated as
follows:

         average concentration estimate for Homolog i + 10o%
         average concentration estimate for Total PCB


where "Total PCB" is  the sum of  the average concentration estimates across the
five homologs in the  above table.  Each homolog omitted  from the table was
detected in no more than 30% of  the NHATS FY86 composite samples.
                                  8-32

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surveys.  The estimates for census regions and age groups are

plotted for each survey in Appendix K with plus and minus two

standard error bars.  The tables also contain estimates of the

difference in the marginal estimates between the FY86 survey and

each previous survey.
        The  following results are suggested from the marginal

estimates in Tables J-3 through J-6 (references to significant

differences between surveys are made at the 0.05 level using the

t-test described above):


    •   Large differences  in the estimates of PCB homologs and
        of total PCB concentration were evident between FY86 and
        FY82 for many of the subpopulations.  These differences,
        often several times larger than their standard errors,
        were generally significant for the northcentral and
        northeast census regions, the 15-44 and 45+ age groups,
        whites, and both sexes.  In each case, the FY86 estimate
        was higher  than the FY82 estimate.

    •   Among PCB homologs, significant differences in the
        marginal estimates between FY86 and FY84 were primarily
        relegated to hexachlorobiphenyl.  All subpopulations
        except the  0-14 age group observed significant
        differences in the marginal estimate for this homolog
        between the two surveys.  For total PCBs, significant
        differences between surveys were observed for the
        northcentral and northeast census regions, the 45+ age
        group, both race groups, and females.  In each case, the
        FY86 estimate was  higher than the FY84 estimate.

    •   Excluding the PCB  homologs, few significant differences
        in marginal estimates were observed between FY82 and
        FY86 among  the subpopulations.

    •   Excluding the PCB  homologs, there is some evidence that
        significant differences exist in marginal estimates for
        p,p-DDT and p,p-DDE between the FY86 and FY84 surveys.
        Differences in p,p-DDE were significant across all age
        groups, sex groups, and race groups; the FY86 estimate
        was larger  than the FY84 estimate in each instance.  For
        p,p-DDT, significant differences were observed for the
        45+ age group, northeast census region, and males as a
        result of larger marginal estimates in the FY86 survey.
                               8-33

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 Thus Tables J-3 through J-6 indicate that  whenever  significant
 differences occurred in the marginal estimates  between  surveys,
 higher estimates were associated with the  FY86  survey.   In  FY82,
 most differences occurred with PCBs; these differences  were
 primarily observed for the two highest age groups and the
 northeast and northcentral census regions.   In  FY84, most
 differences were observed for hexachlorobiphenyl, p,p-DDE,  and
 p,p-DDT;  these differences tended to be consistent  across all
 subpopulations.

 8.4.2.3.   Likelihood Ratio Tests.  For the ten  compounds analyzed
 within each survey using the additive model,  statistical
 hypothesis tests were conducted within each survey  to determine
 if  there  were statistically significant differences in  average
 concentration between individuals between  different geographic
 regions,  age groups,  race groups, and sex  groups.   Likelihood
 ratio principles were used to conduct these tests  (Section
 6.2.2).   For the FY86 survey,  these tests  were  performed in
 Section 7.3.
         Table 8-11 lists the significance  levels obtained  from
 performing the likelihood ratio tests on the  FY82,  FY84, and FY86
 data.   These results  show a relative consistency across all
 surveys.   No significant differences were  noted across  age  groups
 or  sex groups in either survey.   Significant  effects due to
 census region and age groups were observed in each  survey for
 most  of the  PCB homologs,  hexachlorobenzene,  and pesticides.
 Specifically,  the importance of both the census region  and  age
 group effects on the  concentration values  remains evident in the
 FY86  NHATS as in the  prior surveys.

 8.4.2.4.   Conclusions.   The conclusions of  statistical  analysis
on surrogate-adjusted concentrations for semivolatile organic
compounds  are similar between  the three surveys.  Age group and
census region appear  to be  the  most  significant demographic
effects on many of  these concentrations within  each survey.
                               8-34,

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Table 8-11.  Significance Levels from Hypothesis Tests  for
             Differences  Between Demographic Groups for
             Selected Semivolatiles in the FY82,  FY84,  and
             FY86  NHATS(1)
Significance Levels
Compound^
Effect of
p,p-DDT
p,p-DDE
BETA-BHC
HEPTACHLOR EPOXIDE
TRANS -NONACHLOR
HEXACHLOROBENZENE
TETRACHLOROB I PHENYL
PENTACHLOROB I PHENYL
HEXACHLOROB I PHENYL
HEPTACHLOROB I PHENYL
Effect
p,p-DDT
p,p-DDE
BETA-BHC
HEPTACHLOR EPOXIDE
TRANS -NONACHLOR
HEXACHLOROBENZENE
TETRACHLOROB I PHENYL
PENTACHLOROB I PHENYL
HEXACHLOROB I PHENYL
HEPTACHLOROB I PHENYL
Effect
p,p-DDT
p,p-DDE
BETA-BHC
HEPTACHLOR EPOXIDE
TRANS -NONACHLOR
HEXACHLOROBENZENE
TETRACHLOROB I PHENYL
PENTACHLOROB IPHENYL
HEXACHLOROB I PHENYL
HEPTACHLOROB I PHENYL
FY82
Census Region
<0.001*
0.005*
0.011*
0.442
<0.001*
<0.001*
>0.50
0.001*
<0.001*
0.001*
of Age Group
>0.50
0.001*
0.001*
0.117
0.022*
<0.001*
0.057
<0.001*
0.005*
0.811
of Sex Group
0.952
0.946
0.994
0.534
0.771
0.974
0.379
0.675
0.562
0.203
FY84

<0.001*
<0.001*
0.141
<0.001*
<0.001*
<0.001*
0.216
<0.001*
<0.001*
0.408

<0.001*
>0.50
>0.50
<0.001*
<0.001*
<0.001*
<0.001*
<0.001*
>0.50
<0.001*

0.379
0.694
0.353
0.551
0.233
0.971
0.543
0.617
0.381
0.243
FY86

<0.001*
0.001*
0.947
0.031*
0.187
<0.001*
0.036*
0.009*
0.047*
0.140

<0.001*
0.009*
0.015*
<0.001*
<0.001*
<0.001*
<0.001*
<0.001*
<0.001*
0.001*

0.966
0.814
0.623
0.565
0.321
0.777
0.260
0.549
0.693
0.490
                           8-35

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                   Table  8-11.   (cont.)
                                     Significance Levels
Compound®
FY82
FY84
FY86
                   Effect of Race Oroup
p,p-DDT
p,p-DDE
BETA-BHC
HEPTACHLOR EPOXIDE
TRANS -NONACHLOR
HEXACHLOROBENZENE
TETRACHLOROB I PHENYL
PENTACHLOROB I PHENYL
HEXACHLOROB I PHENYL
HEPTACHLOROB I PHENYL
0.433
0.805
0.259
0.495
0.484
0.890
0.383
0.605
0.389
0.280
0.259
0.808
0.452
0.786
0.711
0.802
0.908
0.228
0.245
0.289
0.286
0.569
0.501
0.846
0.879
0.936
0.337
0.619
0.244
0.368
 Significance declared at the 0.05 level.

  Data adjusted for surrogate recoveries  (see Section 5.2).
   Likelihood ratio tests are based on the  chi-square distribution.

  p,p-DDE concentrations for FY86 use m/z«=316 (see Section 5.1.2) .
                            8-36

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         Despite  the  similarities between surveys, differences  in
estimated subpopulation concentrations were significant for some
PCB homologs and pesticides between the FY82/FY84 surveys and the
FY86 survey.  In most cases, these differences indicated that
FY86 estimates were higher than in the previous surveys.  These
results are contrary to the downward trends concluded in previous
trends analyses  (Robinson, et. al., 1990).   These results are
more likely due,  however, to analytical effects rather than
environmental effects.  Since a period of only four years exist
between the collection of specimens for these three surveys, it
is unlikely that major changes in the actual concentration levels
in human adipose tissue will be observed over this time period
under normal exposure conditions.   In making generalizations
across the surveys, such analytical factors as differences in IQS
and surrogate compounds between surveys,  and differences in
design factors, must also be considered as attributable toward
observed differences.
         The national  average  estimates from the  statistical
modelling on ten semivolatiles tend to agree with the estimates
obtained from the weighted average calculations  (Section 8.3.2).
Thus the weighted averages in Table 8-8 may provide useful
estimates in national average concentrations which are relatively
similar to what would be achieved through statistical modelling.
                               8-37

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9.0  REFERENCES


Dinh, K.  1991.  USEPA.  Guideline for adjusting concentrations
   in NHATS data.  Draft Final Report.  Washington, DC:  Office
   of Pollution Prevention and Toxics (formerly the Office of
   Toxic Substances), U.S. Environmental Protection Agency.

Draper NR, and Smith H.  1981.  Applied regression analysis,
   Second Edition.  New York:  John Wiley and Sons.

Kish, L, and Scott, A.  1971.  Retaining units after changing
   strata and probabilities.  Journal of the American Statistical
   Association.  66(335):  pp. 461-470.

Mack GA, Leczynski B, Chu A, and Mohadjer L.  1984.  Battelle
   Columbus Division and Westat, Inc.  Survey design for the
   national adipose tissue survey.  Draft Final Report.
   Washington, DC:  Office of Pollution Prevention and Toxics
   (formerly the Office of Toxic Substances), U.S. Environmental
   Protection Agency.  Contract No. 68-01-6721.

Mack, GA, and Panebianco, DL.  1986.  Battelle Columbus Division.
   Statistical Analysis of the FY82 NHATS Broad Scan Analysis
   Data.  Draft Final Report.  Washington,  DC:  Office of
   Pollution Prevention and Toxics  (formerly the Office of Toxic
   Substances), U.S. Environmental Protection Agency.  Document
   No. NHATS-SS-04.  Contract No. 68-02-4243.

MRI.   1988a.  Analysis of adipose tissue for semivolatile
   analytes:  adipose tissue sample compositing.  Interim Report
   #1.  Washington, DC:  Office of Pollution Prevention and
   Toxics (formerly the Office of Toxic Substances),  U.S.
   Environmental Protection Agency.  Contract No. 68-02-4252.

MRI.   1988b.   Quality assurance project plan for WA-28: broad
   scan analysis of adipose tissue from the FY 1986 EPA NHATS
   repository.  Washington, DC:  Office of Pollution Prevention
   and Toxics  (formerly the Office of Toxic Substances), U.S.
   Environmental Protection Agency.  Contract No. 68-02-4252.

MRI.   17 March,1989.  Analysis of adipose tissue for semivolatile
   organic compounds -- FY 1986 NHATS composites, batch 1 interim
   data report.  Washington, DC:  Office of Pollution Prevention
   and Toxics  (formerly the Office of Toxic Substances), U.S.
   Environmental Protection Agency.  Contract No. 68-02-4252.

MRI.   19 May 1989.  Analysis of adipose tissue for semivolatile
   organic compounds -- FY 1986 NHATS composites, batch 2 interim
   data report.  Washington, DC:  Office of Pollution Prevention
   and Toxics  (formerly the Office of Toxic Substances), U.S.
   .Environmental Protection Agency.  Contract No. 68-02-4252.

                               9-1

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MRI.   21  July 1989.   Analysis  of  adipose  tissue  for  semivolatile
   organic  compounds --  FY 1986 NHATS  composites, batch  3 interim
   data report.   Washington, DC:   Office  of  Pollution Prevention
   and Toxics (formerly  the Office of  Toxic  Substances), U.S.
   Environmental  Protection Agency.  Contract No. 68-02-4252.

MRI.   21  July 1989.   Analysis  of  adipose  tissue  for  semivolatile
   organic  compounds --  FY 1986 NHATS  composites, batch  4 interim
   data report.   Washington, DC:   Office  of  Pollution Prevention
   and Toxics (formerly  the Office of  Toxic  Substances), U.S.
   Environmental  Protection Agency.  Contract No. 68-02-4252.

MRI.   22  September 1989.   Analysis of  adipose tissue for
   semivolatile organic  compounds -- FY 1986 NHATS composites,
   batch  3  revised tables  and  analysis report forms.  Washington,
   DC:  Office of Pollution Prevention and Toxics  (formerly the
   Office of  Toxic Substances), U.S. Environmental Protection
   Agency.  Contract No. 68-02-4252.

MRI.   25  September 1989.   Analysis of  adipose tissue for
   semivolatile organic  compounds -- FY 1986 NHATS composites,
   batch  5  interim data  report.   Washington, DC:  Office of
   Pollution  Prevention  and Toxics (formerly the Office  of Toxic
   Substances), U.S.  Environmental Protection Agency.  Contract
   No. 68-02-4252.

MRI.   28  September 1989.   Analysis of  adipose tissue for
   semivolatile organic  compounds -- FY 1986 NHATS composites,
   batch  5  revised tables  and  analysis report forms.  Washington,
   DC:  Office of Pollution Prevention and Toxics  (formerly the
   Office of  Toxic Substances), U.S. Environmental Protection
   Agency.  Contract No. 68-02-4252.

MRI.   13  July 1990.   Analysis  of  adipose  tissue  for  semivolatile
   organic  compounds --  FY 1986 NHATS  composites, revised PCB
   data batches 1-5.  Washington,  DC:  Office of Pollution
   Prevention and Toxics (formerly the Office of Toxic
   Substances), U.S.  Environmental Protection Agency.  Contract
   No. 68-02-4252.

Orban JE,  Leczynski  B, Collins TJ,  and Sasso NR.  1988.  Battelle
   Columbus Division.  FY86 NHATS composite design.  Final
   Report.  Washington,  DC:  Office of Pollution Prevention and
   Toxics (formerly  the  Office of Toxic Substances), U.S.
   Environmental  Protection Agency.  Contract No. 68-02-4294.
                               9-2

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Orban JE, and Lordo, RA.  1989.  Battelle Columbus Division.
   Statistical methods for analyzing NHATS composite sample
   data -- evaluation of multiplicative and additive model -
   methodologies.  Draft Final Report.  Washington, DC:  Office
   of Pollution Prevention and Toxics (formerly the Office of
   Toxic Substances), U.S. Environmental Protection Agency.
   Contract No. 68-02-4294.

Panebianco DL.  1986.  Battelle Columbus Division.  A review of
   hospital nonresponse and its effect on standard errors of
   sample estimates in NHATS.  Draft Final Report.  Washington,
   DC:  Office of Pollution Prevention and Toxics  (formerly the
   Office of Toxic Substances), U.S. Environmental Protection
   Agency.  Contract No. 68-02-4243.

Robinson, PE, Mack, GA, Remmers, J, Levy, R, and Mohadjer, L.
   1990.  Trends of PCB, hexachlorobenzene, and /8-benzene
   hexachloride levels in the adipose tissue of the U.S.
   population.  .Environmental Research.   53:  pp. 175-192.

Rogers, J.  1991.  Westat, Inc.  FY86 NHATS Semi-Volatile Organic
   Compounds:  Outlier Analysis.  Final Report.  Washington, DC:
   Office of Pollution Prevention and Toxics (formerly the Office
   of Toxic Substances), U.S. Environmental Protection Agency.
   Contract No. 68-D9-0174.

Stanley, JS, Balsinger, J, Mack, GA, and Tessari, JD.  1986.
   Midwest Research Institute, Battelle Columbus Division, and
   Colorado State University.  Comparability study of analytical
   methodology for TSCA chemicals in human adipose tissue.
   Quality Assurance Program Plan.  Washington, DC:  Office of
   Pollution Prevention and Toxics  (formerly the Office of Toxic
   Substances), U.S. Environmental Protection Agency.  Contracts
   No. 68-02-3938 and 68-02-4243.

Westat, 1990.  NHATS Comparability Study, Draft 3.0.  Washington,
   DC:  Office of Pollution Prevention and Toxics  (formerly the
   Office of Toxic Substances), U.S. Environmental Protection
   Agency.  Contract No. 68-DO-0174.

USEPA.  1986.  Broad scan analysis of the FY82 NHATS specimens.
   Volume III:  Semi-volatile organic compounds.  EPA Publication
   No. EPA-560/5-86-037.

USEPA.  1991.  Chlorinated dioxins and furans  in the general U.S.
   population:  NHATS FY87 results.  EPA Publication No.
   EPA-560/5-91-003.
                               9-3

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   50272-101	

   REPORT DOCUMENTATION
           PAGE
l._ REPORT NO.
   4. Title and Subtitle
                           EPA 747-R-QA-Qnj
     Semivolatile Organic Compounds in the General  U.S. Population:
     NHATS FY86 Results - Volume  I
   7. Authors)
                                                3. Recipient's Accession No.
   9. Performing Organization Name and Address
   12. Sponsoring Organization Nam* and Address
     Chemical Management Division
     Office of Pollution Prevention and Toxics
     U.S.  Environmental  Protection Agency
     Washington.  DC   20460
   15. Supplementary Notes
                                                                          8. Performing Organization Rept. No.
                                                                          10. Project/Task/Work Unit No.
                                                                          11. Contract(C) or Grant(G) No.

                                                                          (0

                                                                          (G)
                                               13. Type of Report & Period Covered
                                               14.
      Khoan T. Dinh,  Work Assignment Manager
      Technical Programs Branch
   16. Abstract (Limit: 200 words)
          The Environmental Protection Agency's  National Human Adipose Tissue  Survey
           (NHATS) was  performed annually to quantify the levels of selected  chemicals in
          the adipose  tissue of humans in the U.S.  population.   Specimens collected in
          fiscal year  1986 were earmarked for an analysis to estimate national average
          concentrations of 111 semivolatile compounds in adipose tissue, to identify
          differences  in average  concentrations  among subpopulations, and to compare
          results with previous surveys in the NHATS.  For 17  semivolatiles  detected in
          at  least half of the 50 analytical samples, statistical modeling techniques
          were conducted to address  these objectives.

          Among demographic effects  on average concentration,  the a.ge group  effect was
          most often statistically significant,  with higher concentrations associated
          with higher  ages.  Among PCS homologs,  the 45+ year  age group had  from 188% to
          706% higher  average concentrations than the 0-14 year age group, with similar
          increases observed for  pesticides.  Geographic effects were only occasionally
          significant,  and no significant race or sex effects  were observed.

          Statistically significant  increases in concentration (generally less than
          100%)  from the FY82 NHATS  were observed for three PCB homologs, while
          increases of 50% to 100% from the FY84 NHATS were significant for  p,p-DDT and
          p,p-DDE.  Mixed findings were observed for other semivplatiles analyzed in all
          three surveys.	^	
  17. Document Analysis  a. Descriptors
    b. Identifiers/Open-Ended Terms
   c. COSATI Field/Group
 18. Availability Statement

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