Dr. Thomas P. Vogl
FLAW FOR  THE INVESTIGATION ©F SELECTED €0fti!ElATION<
           ftlAL ACTIVITY  AMD COMMUNITY
                          For
           Environment*!  Protection
                 401 M  Street, S.W.
               Washington, D.C. 2064®
                          By
                ENVIRO CONTROL, INC.

                   One Central Plaza
                   H300RockvillePike
                   Rockville, Maryland 20852
E

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PLAN FOR THE  INVESTIGATION OF SELECTED CORRELATIONS

                      BETWEEN

     INDUSTRIAL  ACTIVITY AND COMMUNITY DISEASE
                   VOLUME I - PLAN


                    February 1977
    Prepared  Under Contract No. EPA  68-01-4304

                         For

              Office of Toxic Substances
          Environmental Protection Agency
                 401 M Street, S.W.
               Washington, D.C. 20040
                         By
               ENVIRO CONTROL, INC.

                  One Central Plaza
                  11300 Rockville Pike
                  Rockville, Maryland 20852

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                            TABLE OF CONTENTS
                                                                   Page
      PREFACE                                                       ii
      LIST OF TABLES, FIGURES, AND CHARTS                          iii
  I.   INTRODUCTION                                                  1
 II.   PROGRAM OBJECTIVES                                            2
III.   INDUSTRY/DISEASE ASSOCIATIONS AND TEST SITES                  3
         A.  Sources of Associations                                3
         B.  Selection and Validation Procedure                     3
         C.  Associations Selected for Investigation                6
         D.  Selection of Field Test Sites                          9
 IV.   APPROACH FOR INVESTIGATION OF CAUSAL RELATIONSHIPS           19
         A.  General                                               19
         B.  Hypothesis Development Approach                       19
         C.  Hypothesis Testing Approach                           20
  V.   DATA REQUIREMENTS AND ACQUISITION PROCEDURES                 26
         A.  General                                               26
         B.  Industrial Processes, Emissions, and Effluents        26
         C.  Pathways                                              30
         D.  Health Data Needs and Procedures for Acquisition      33
 VI.   WORK PLAN                                                    45
         A.  Overview                                              45
         B.  Task Description                                      45
         C.  Task Flow and Schedule                                50
         D.  Staffing and Assignments                              51
         E.  Project Organization                                  51

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                                PREFACE
         This document was prepared under EPA Contract No. 68-01-4304,
an 18-month program to investigate correlations between industrial
activities and community disease.  This document, the culmination
of Phase I of the program, presents the detailed plan for Phase II
which is to consist of field studies of the causal relationships
between specific industries and associated diseases identified and
selected in Phase I.  Although the express purpose of this document
is to present the field test plan for the Phase II effort, it reports
on all the work performed in Phase I, in particular:

         1.  Selection of sites for the Phase II field investigations;

         2.  Survey of literature on the selected industries and
             diseases; and

         3.  Preparation of the plan for the field investigation of
             the selected associations.

         The work on Task 1 is reported in the body of this document
in Section III and Task 2 is documented in Appendix A.  The report of
Task 3 constitutes the main body of this document.  A considerable
amount of work, additional to that originally planned, was performed
on the selection and validation of candidate industry/disease associa-
tions.  This work is documented in Section III of the plan and in
Appendices B and C.

         Also, to assist in the preparation of the field test plan,
the Phase I effort included a pilot investigation of one of the
candidate industry/disease associations, i.e., bituminous coal mining
correlated with respiratory/cardiovascular diseases.  This pilot study
served to identify data needs and availabilities.   The results of
the work are described and referenced in the body of the plan to pro-
vide rationale where applicable.

         This document was prepared by the ECI staff with the assis-
tance  of Anne Barton, EPA Project Officer.  The following ECI staff
members contributed substantially to the document:

         John Morton         Project Manager
         Willard Perry       Senior Environmental Systems Analyst
         Robert Goldsmith    Epidemiologist
         Margaret Mattson    Biologist
         Sandra Brown        Physical Chemist
         Bert Berney         Environmental Analyst
         Carl Bailey         Environmental Health Scientist
         Ravi Shukla         Industrial Process Engineer

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                   LIST OF TABLES.  FIGURES, AND CHARTS


                                                                     Page

TABLE I   - VALIDATED INDUSTRY/DISEASE ASSOCIATIONS                    7

TABLE II  - POSSIBLE INDUSTRY ASSOCIATED POLLUTION                    10

TABLE III - CANDIDATE COUNTIES FOR FIELD INVESTIGATION                11

TABLE IV  - POINT SOURCES WITHIN HIGH INDUSTRIAL INDEX COUNTIES
            FOR EACH INDUSTRY/DISEASE CORRELATION                     12

TABLE V   - CRITERIA FOR SELECTION OF STUDY (EXPOSED) AND
            CONTROL (NON-EXPOSED) SITES                               15

TABLE VI  - DISTRIBUTION OF DISCHARGES FROM SHORT-STAY HOSPITALS
            FOR RESIDENTS OF WYOMING COUNTY                           37

TABLE VII - PATIENT ORIGIN DATA & NURSING HOME PLACEMENT SURVEY       38
FIGURE 1 - MORTALITY RATE FOR DISEASE 038 VS INDUSTRIAL
           ACTIVITY FOR BITUMINOUS COAL MINING                         4

FIGURE 2 - MORTALITY RATE FOR DISEASE 040 VS INDUSTRIAL
           INDEX FOR LUGGAGE                                           5

FIGURE 3 - PILOT STUDY COUNTIES (SHADED) & CONTIGUOUS COUNTIES        35
CHART A  - PROJECT MILESTONE SCHEDULE                                 53

CHART B  - SUBTASK SCHEDULE FOR TASKS 1  & 2                           54

CHART C  - TASK FLOW                                                  55

CHART D  - FUNCTIONAL TEAMS                                           56

CHART E  - FUNCTIONAL TEAM RESPONSIBILITY & WORKLOAD                  57

CHART F  - PERSONNEL WORK LOADING (Man-Months)                        58

CHART G  - PROJECT ORGANIZATION                                       59
                                    m

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                            I.  INTRODUCTION
      The Office of Toxic Substances of the Environmental Protection
Agency is investigating the feasibility of identifying disease-causing
pollutants and associated industries by means of a systematic analysis
and exploration of correlations between industrial activities and
community disease.  The investigation is motivated by the desire to
develop an objective methodology for uncovering industries and pollu-
tants which are hazardous to the health of the community and require
regulation and control, and to apply the methodology to selected case
studies.

      The investigation is being conducted in two steps.  The first
step consisted of statistical analyses of county mortality and industry
data for the purpose of identifying suspect associations between indus-
tries and diseases.  The second step will  consist of field studies of
selected associations to investigate the causal relationships between
the suspect industries and associated diseases.  If sufficient evidence
can be found to support the existence of causal relationships between
the industries and diseases, then the methodology under study will
have been shown to be both useful and effective in identifying community
health problems induced by industrial pollutants.

      The first step, which involved both multiple regression analysis
and statistical significance testing of the correlations between county
industrial activity and mortality rates for a broad set of industries
and diseases, is essentially complete.  Systems Sciences, Incorporated
has performed the multiple regression work and Enviro Control, Incorpor-
ated has done the statistical significance testing to screen and vali-
date the large number of potential correlations resulting from the
regression analysis.

      The second step, the field investigation of selected industry/
disease associations for causal relationships, has yet to be performed.
The purpose of this document is to present a detailed plan of field
investigations to be conducted in order to determine whether or not
causal relationships exist between the industrial  pollutants and the
diseases.

      The specific objectives of the program plan are discussed in
Section II of this document.  Section III describes the associations
and sites selected for the field investigations.  It also summarizes
the screening and validation procedures used for selecting the associa-
tions and the methodology for selecting the sites.  Section IV des-
cribes the epidemiological approach for the investigation of the causal
relationships.  Section V describes the data requirements and acquisi-
tion procedures.  Finally, Section VI presents the detailed work plan,
including sub-tasks, schedule, and staffing.

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                         II.  PROGRAM OBJECTIVES
      The program described here is a field investigation of selected
industry/disease associations which have been identified through
statistical  analysis of county industry and mortality data.   The
objectives of the program are twofold.

      The first objective is to gather and examine the evidence of
causality between the suspect industries and associated diseases to
assess whether or not the industry and its hazardous pollutants might
be a cause of disease.  The purpose of these assessments is  to attempt
to provide EPA with documentation of the value and feasibility of iden-
tifying disease-causing industries and pollutants by means of system-
atic and objective statistical analyses of disease and industry corre-
lations.  To satisfy this objective, a thorough program of research
and analysis is planned for the development, testing, and assessment
of causal hypotheses between six specific industries and associated
diseases.

      The second objective is to develop and assess methodology for
the investigation of causal relationships between industry and community
disease.  There are several epidemiological approaches for investigating
the contribution specific industries make to the prevalence  of local
diseases.  The viability of any approach depends upon the nature and
availability of required data.  Only through field studies can the
approaches be evaluated and the detailed methodology developed.  To
accommodate this methodological objective, a flexible program is planned
which is conducive to methodology development by virtue of the sequential
investigation of the six associations.   This allows for learning from
previous investigations and testing of new methods as the program
progresses.

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           III.  INDUSTRY/DISEASE ASSOCIATIONS AND TEST SITES
 A.     Sources  of Associations

       The six  industry/disease  associations  chosen  for  field  investiga-
 tion  were selected  from a  large list  of  potential associations  identified
 by  various means.   The  principal  source  of potential  associations  was  a
 multiple regression analysis* correlating  county  industrial activities
 for over 400 industries with county mortalities for fifty-six disease
 categories.   The multiple  regressions constituted a completely  objective
 source,  providing the  largest number  of  possible  associations in the final
 list.  Other potential  associations were generated  by manual  correlation
 of  county industry  and  mortality  data, through literature  searches, and
 from  observations made  by  state health officials  on state  environmental
 health problems. The  sum  total  of the industry/disease associations iden-
 tified by all  means constituted the so-called "master list" consisting of
 eight hundred  seventy-five associations  of which  eight  hundred  thirty-nine
 were  identified by  the  regression analysis and thirty-six  from  other
 sources.  This master  list is included in  Appendix  B.

      A systematic approach was  taken  to  condensing  this list  to a
workable size.   The regression  data was categorized  into six parts
based on regression coefficients, appearance  in  both subsamples, and
appearance in both sexes.  The  categories believed to contain  the
strongest associations  were chosen (87 associations) and reduced to
57 by elimination of certain broad  industry  categories  which  are not
amenable  to analysis.   Eight groups  of non-regression associations
were  also chosen for further study.  The  list of  associations  remaining
after the final screening process is  termed the  "working list".   This
list  and the details of the screening  process are  presented in Appendix B.


B.    Selection and Validation  Procedure

      To select the final six industry/disease associations for field
study, the working list was subjected  to  a  series  of statistical tests
and analytical  examinations to  identify those associations  which are
strongest and least likely to be spurious.   The  first screening tech-
nique used was graphical display to test  the  strength of the relation-
ship between mortality  rate and  industrial  activity.  Plots were made
for a number of the associations using several  different measures of
industrial activity.  Examples of the  plots for  bituminous  coal/respira-
tory diseases and luggage/acute  interstitial  and  bronchopneumonia are
presented in Figures I  and II. No strong  correlations appeared,  although
some associations showed trends  in a  positive direction.  The  cases
which showe'd promising  trends eventually  were validated  by  another
screening procedure, but the graphical method by  itself  was not a
suitable measure of the strength of association.


*System Sciences, Inc.  provided  the multiple  regression  analysis and data.

                                    3

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 15Q                                                       MORTALITY RATE FOR DISEASE 038
                                                                         VS
                                                   INDUSTRIAL ACTIVITY FOR BITUMINOUS COAL MINING
  100
g
                     G
a!
                     O
                O
   50                            w

              o°   0                                   NATIONAL MEAN MORTALITY  RATE
                                              INDUSTRIAL  INDEX  -  BITUMINOUS COAL MINING  (121R)
      "001000'200030004000

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a
9
                                              MORTALITY  RATE  FOR DISEASE 040
                                                            VS
                                               INDUSTRIAL  INDEX FOR LUGGAGE
    P          O                                                       O

     OO                                   O
        	 NATIONAL MEAN MORTALITY RATE

     33
     o     o                                                             o
     >
       o
                                             INDUSTRIAL INDEX   LUGGAGE (316R)

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      The methods that proved successful for validating the associations
consisted of comparing the aggregated mortality rates of the top 10
counties in industrial activity with:  1) the national mean mortality
rates; and 2) the aggregated mortality rates of matched control coun-
ties not containing the industry.  In selecting the top 10 counties,
those counties with greater than 200,000 population and those counties
with any other suspect industries were eliminated.   The reason that
large population counties were removed from consideration is that
population density appears to be a confounding variable which corre-
lates with many of the diseases of interest.

      The test of the significance of the difference in mortality
rates between the aggregated top ten industrial counties and the
national mean was a quick statistical test which was effective in
eliminating about half of the working list of associations as being
invalid.  The remainder were tested by examining the significance
of the difference between the aggregated mortality rates for the top
10 and those of a set of control counties with socioeconomic charac-
teristics matched to the top 10.  Ten industries with their associa-
ted diseases survived this matched control test.  The final selection
of 6 industries and associated diseases was made on a subjective
basis simply to restrict the number to be investigated to fit time
and budget constraints.

      The details and results of these screening and validation
operations are presented in Appendix C.
C.    Associations Selected for Investigation

      The final list of associations selected for investigation
appears in Table I.  It contains 10 industries with 23 associated
diseases.  Except for 1 association involving cirrhosis, the diseases
fit into 3 main categories: cardiovascular diseases (5 industries),
respiratory diseases (3 industries), and digestive cancer (2 industries).
A number of the industries involve metal, primarily copper, and obviously
dirty operations such as smelting and coal mining.  The list thus has
some intuitive credibility, encompassing diseases that are among the
leading causes of death  and industries that have potential for re-
leasing toxicants to the community.  There are obviously some strong
associations and others that seem much less plausible.  For objectivity,
all associations which met our selection criteria were retained.  A
literature search was conducted for each association in order to de-
termine what, if any, research has been done on the relationship.  The
results are reported in detail in Appendix A and are summarized here.

      Bituminous coal mining is the industry with the strongest associa-
tion with disease.  It has stood out from the beginning of the study
and is a good candidate for study because the industrial indices are
exceedingly high and contributions from other industrial sources should

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                                  TABLE I
                  VALIDATED INDUSTRY/DISEASE ASSOCIATIONS
 SIC
Industry
3357 - Non-Ferrous Wire Drawing*


102R - Copper Ore Mining*

121R - Bituminous Coal Mining*
3312 - Blast Furnaces*

2321 - Men's Shirts & Nightwear*


3331 - Primary Copper


3421 - Cutlery

34RR - Fabricated Metal Products

2879 - Pesticides & Agricultural
       Chemicals

2823 - Viscose Rayon*
             Disease

06 - Neoplasm, Digestive Organs
08 - Neoplasm, Intestine

31 - Acute Myocardial  Infarction

38 - Respiratory Diseases
39 - Acute Interstitial &
     Bronchopneumonia
40 - Bronchitis, Emphysema, & Asthma
42 - Emphysema
43 - Asthma
45 - Other Respiratory Diseases
27 - Major Cardiovascular Disease
30 - Ischemic Heart Disease
31 - Acute Myocardial  Infarction
32 - Chronic Ischemic Heart Disease,
     Angina Pectoris
37 - Disease of Veins, Lymphatics
     & Circulatory System

06 - Neoplasm, Digestive Organs

27 - Major Cardiovascular Disease
30 - Ischemic Heart Disease

48 - Alcoholic Cirrhosis of Liver
46 - Digestive Diseases

38 - Respiratory Disease

29 - Hypertensive Disease

38 - Respiratory Diseases
                          32 - Chronic Ischemic Heart Disease,
                               Angina Pectoris
*Associations selected for field investigation

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be minimal.  Association with respiratory disease may be related  to
the high level of airborne participate matter in the vicinity of  mining
operation.  There is no obvious reason for the high rate for heart
disease, but leaching of heavy metals and acidic materials from coal
mines may contribute.  A complication in this study may be the use of
coal furnaces  in home heating.  Examination of the literature indica-
ted that there appear to have been few studies on the effects of
mining on community health.  Three studies were identified in which
respiratory symptoms in the wives of coal miners were analyzed.   They
were found to  have an excess of respiratory symptoms, when compared
to wives of men in other occupations.  The difference was not ade-
quately accounted for by the various studies.  Socioeconomic or physio-
logical variables were alluded to in some cases, but in general there
was no reference to the possiblity of environmental pollution from
mining as a causal factor  in the women's symptoms.

      Blast furnaces have  the potential for releasing a multitude of
compounds into the atmosphere.  The health impact of the steel industry
upon the community has been studied by previous workers.  Research at
one site in Canada indicated higher death rates from respiratory,
gastrointestinal and genitourinary cancer among residents living  near
a steel mill.  High levels of fluoride (a known carcinogen) were  found
in  the area's  vegetation and cancer patients exhibited skeletal fluorosis.
This effect has not been shown at other sites nor has the role of other
agents  involved in the steel process been considered.  Coke ovens are
known to produce polycyclic aromatic compounds that are linked to cancer.
There is also  a possibility of trace metal contaminants.

      There is already an established occupational  link between the
viscose rayon  industry and coronary heart disease.   The appearance of
high rates in  both sexes, however, raises the possiblity of a community-
wide effect.  The agent responsible is  believed to  be carbon disulfide.
The presence of viscose rayon plants has  not been  associated with
community disease.   However,  one documentation  of carbon disulfide
pollution in the area surrounding rayon plants  was  found.   No human
effects were reported,  although the elevated carbon  disulfide levels
produced toxic vascular effects in laboratory rats.

      Copper smelting is  of interest because  of trace metals contained
in the ore (i.e.,  arsenic,  beryllium).   The  correlation  with cirrhosis,
particularly alcoholic  cirrhosis,  is  not  what might  be  expected;  but
the possibility of agents being potentiating  rather  than  causative
must be considered in this  case.   The literature  indicates  that copper
smelting  activity has  been associated  with  adverse  health  effects,
both among workers  and  in the community.   Contaminants  from the indus-
try which have appeared in  the  community  and  have  been  linked to
disease are arsenic (respiratory system cancer);  cadmium (cancer,
liver disease); and sulfur  dioxide (liver disease).   No  links between
copper smelters and digestive diseases  were  found  in  the  published
literature.

      Some  of the  other associations  appear weaker  and  may  or may not
be borne  out by further investigation.  The  category  of fabricated

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                                 TABLE II
                  POSSIBLE INDUSTRY-ASSOCIATED POLLUTANTS
          Industry

Non-Ferrous Wire Drawing



Copper Ore Mining

Bituminous Coal Mining
Blast Furnaces



Men's Shirts & Nightwear


Copper Smelting

Cutlery


Fabricated Metal Products
Pesticides & Agricultural
  Chemicals

Viscose Rayon
     Possible Harmful Emissions

Metal fines - Copper, Aluminum; Arsenic
Plasticizers
Cutting Oils & Lubricants (amines)

Metal dusts - Copper; Arsenic

Coal dust particulates
Materials leached from coal  piles

Carbon monoxide
Polycyclic aromatic compounds
Trace metal contaminants

Fine fibers
Minute starch particles

Trace elements - Arsenic, Beryllium, Uranium

Metal fines
Nuisance dusts

Metal fines
Cutting oils & lubricants

Compounds designed for physiological action
Carbon Disulfide
                                    10

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TABLE  III
CANDIDATE COUNTIES FOR FIELD INVESTIGATION
INDUSTRY
Bituminous Coal Mining
Primary Copper Smelting
Cutlery
Non-Ferrous Wire Drawing
Blast Furnaces
Men's Shirt's 4 Nightwear
Viscose Rayon
Pesticides 4 Agricultural
Chemicals
Fabricated Metal Products
STATE
Virginia
Kentucky
Ohio
Pennsylvania
West Virginia
Arizona
flew Mexico
Tennessee
Michigan
Nevada
Montana
Massachusetts
Arkansas
Rhode Island
Arkansas
Illinois
Vermont
Indiana
Michigan
Pennsylvania
Indiana
West Virginia
Colorado
Ohio
Indiana
Georgia
Kentucky
Alabama
Tennessee
Mississippi
North Carolina
Tennessee
Virginia
Colorado
Missouri
Texas
Georgia
Alabama
Michigan
Indiana
Georgia
Massachusetts
Kentucky
COUNTIES
Buchanan
Dickenson
Floyd
Harlan
Letcher
Harrison
Greene
Logan
McDowel 1
Wyoming
Cochise
Gil a
Green! ae
Mohave
Yavapai
Grant
Polk
Keewenaw
Lyon
White Pine
Deer Lodge
Hampshire
Howard
Bristol
Dallas
DeKalb
Grand Isle
Grant
Tuscola
Cambria
Mercer
Fountain
Parker
Hancock
Pueblo
Scioto
Whites ids
Bleckley
Clinton
Covinaton
DeKalb
Fen tress
Itwamba
Newton
Buncombe
Carter
Hamblen
Warren
Adams
Buchanan
Hidalgo
Peach
Terrell
Washington
Antrium
Baraga
Cass'
Coweta
Franklin
Oldham
  11

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                                                     TABLE IV
             POINT SOURCES WITHIN HIGH INDUSTRIAL INDEX COUNTIES FOR EACH INDUSTRY/DISEASE CORRELATION
     County
                   Plant Name & Address
Adjacent County (Country)
Comments
 *Association:   Primary Copper Smelting - Alcoholic liver cirrhosis and digestive diseases
 Cochise, Az.
 Gila, Az.
 Greenlee, Az.

 Deerlodge, Mont.
 White Pine, Nev.
 Grant, N. Hex.
 Polk, Tenn.
                   Phelps-Dodge Corp.,  Douglas,  Az.  85607             Mexico
                   ASARCO,  Inc., Hayden,  Az.  85235                    Pinal  Co., Az.

                   Kennecott Copper Corp.,  Hayden, Az.  85235
                   Phelps-Dodge Corp.,  Morenci,  Az.  85540

                   The Anaconda Co., Anaconda, Mont.  59711
                   Kennecott Copper Corp.,  McGill, Nev.  89445
                   Kennecott Copper Corp.,  Hurley, N.  Mex.  88043
                   Cities Service Co.,  Copperhill,  Tenn.  37317        Fannin Co.,  Ga.
 *Association:   Copper Ore Mining (Without Smelting)  -  Acute  Myocardial Infarction

                                                                       Haughton  Co.,  Mich.
Keewenaw, Mich.     Homestake Copper Co.,  Box 386,  Calumet,  Mich.
Lyon, Nev.          The Anaconda Co., Box  1000
                     Weed Heights,  Nev. 89443
Monave, Az.         Duval  Corp., Box 1271, Kingman, Az.  86501
Yavapai, Az.        Cyprus-Bagdad Copper Co., Bagdad,  Az.  86321
                   McAlester Fuel  Co.,  Kirkland, Az.
                   Phelps-Dodge Corp.,  Box 125,  Jerome, Az.  86331
                   Cyprus Sruce Copper &  Zinc Co.
                     Box  457, Bagdad, Az. 86321
                                                                       Mohave Co.,  Az.
                                                                       Mohave Co.,  Az.
                             Bordertown
                             Gila is surrounded
                             on 3 sides by Pinal

                             Greenlee is long
                             and narrow
                             Hurley is located
                             in an eastern sect-
                             ion of the county
                             Odd-shaped county

                             Long, narrow county



                             Underground mine
 * Association:  Non-Ferrous Wire Drawing - Digestive  & Intestinal  Neoplasms
 Dallas, Ark.

 Bristol, R.I.


 Grand  Isle, Vt.
 Grant,  Ind.

 Tuscola,  Mich.

 DeKalb,  111.
                   Phelps-Dodge Communications,  300 S.  Edgar St.,
                     Fordyce,  Ark.
                   Carol  Cable, Warren,  R.I.


                   Pheonix Wire, South Hero, Vt.
                   Anaconda, E.  8th St., Marion,  Ind.
                   Essex  Int'1., 2601 S. Adams St., Marion,  Inc.
                   General Cable, 6285 Garfield,  Cass City,  Mich.

                   Plant  not yet located
     Plant has recently moved across river to
     Newport Co., R.I.
                             Employment  800
                             Employment  600
                             Plant  is  in NE
                             corner of county
*Association:  Blast  Furnaces - Digestive Neoplasms

Pueblo, Colo.      CF&I Steel Corp., 325 Canal St., Pueblo, Colo.
Whiteside, 111.    Northwestern Steel a Wire, 121 Wallace St.
                      Sterling, 111.
Fountain, Ind.     Harrisons Steel Foundry,  Attica, Ind.
                   Veedersburg Foundry, Veedersburg, Ind.
Parker, Ind.        Bethlehem Steel, Rt. 12, Burns Harbor, Ind.
                   Midwest, Rt. 12, Portage, Ind.
Scioto, 0.         Empire Steel, 3879 Rhodes Ave., New Boston, 0.
Cambria, Pa.        Bethlehem Steel, Johnstown, Pa.

                   U.S. Steel, Johnstown, Pa.
Mercer, Pa.         Sharon Steel, Farrell, Pa.
                   Sharon Tube, Sharon, Pa.
                   Sanhill Tubular, Wheatland, Pa.
                   Wheatland Tube Co., Wheatland, Pa.
Hancock,  W.Va.     Plant not yet identified
                                                                     Lee Co., 111.
                                                                     (Approx. 5 miles)
                                                                     Warren Co.,  Ind.
                                                                     Greenup Co., Ky.
                                                                     Somerset Co., Pa.
                                                                     (5 miles)
                                                                            H
                                                                     Trumbull Co., 0.
                             Employment  9100
                             Employment  4350
                                                        12

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    County
Plant Name & Address
Adjacent County
Comments
* Association:   Men's Shirts & Nightwear - Cardiovascular Disease
Covington, Ala.

Bleckley, Ga.
Clinton, Ky.
Itwamba, Miss.

Newton, Miss.

DeKalb, Tenn.


DeKalb, Tenn.

Fentress, Tenn.
Franklin-Ferguson Co., 410 S. 4th St.,
  Florala, Ala.
L&H Shirt Co., Dohl St., Cochran, Ga.
Kellwood Co., 810 Tennessee Rd., Albany, Ky.
Sutton Shirt Corp., 510 Columbia St. & Highway 127
  Albany, Ky.
Itwamba Mfg., Co., Ltd., 1000 Rex Ave.,
  Fulton, Miss. 38843
Midland Shirts, Union, Miss.
Oecatur Corp., Decatur, Miss.
Alexandria Ind. Garment Co., Alexandria, Tenn.
DeKalb Industries, Inc., Smithville, Tenn.
Dowelltown Mfg., Co., Dowel 1 town, Tenn.
Liberty Mfg., Corp., Liberty, Tenn.
Smithville Mfg. Corp., Smithville, Tenn.
Jamestown Mfg. Corp., Jamestown, Tenn.
Fentress  Industries, Jamestown, Tenn.
Sharp Mfg. Corp., Jamestown, Tenn.
Clarkrange Mfg. Corp., Clarkrange, Tenn.
Walton Co., Fla.
                        Employment 450

Neshoba Co., Miss.

Smi th & Wi1 son Co., Tenn.
                                                                      Cumberland Co., Tenn.
*Association:  Viscose Rayon -  Cardiovascular Disease
Warren, Va.
Carten, Tenn.
Buncombe, N.C.
Hamblen, Tenn.
  Green, Tenn.
Avtex Fibers, Inc., Front Royal, Va.
Beaunit Corp., Elizabethton, Tenn.
Akzona.i.Enka, N.C.
Akzona, Lowland, Tenn.
Lowland is in Hamblen Co.
but borders on Greene Co.
*Association:  Pesticides & Agricultural Chemicals - Respiratory Diseases

Washington, Ala.   Plants not identified
Adams, Colo.
Peach, Ga.
Terrell, Ga.
Buchanan, Mo.
Hidalgo, Tex.

* Association:  Fabricated Metal Products - Hypertensive Disease

Coweta, Ga.        Plants not identified
Cass,  Ind.
Oldham, Ky.
Franklin, Mass.            "
Antrium, Mich.
Baraga, Mich.              "
                                                       13

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      The criteria for selection  of the specific test sites are listed
in Table V.   The criteria are listed under three categories:  1) required
characteristics of industrial emissions and processes; 2) population at
risk; and 3) the transport pathway.   Criteria for selection of control
areas are included under similar categories in the right-hand column of
the table.

      The selection process and the  specific sites selected for the first
two investigations to be conducted,  i.e., bituminous coal mining and
copper smelting, are described in the following procedures.  Sites for
subsequent investigations will be selected as the final  step in the
investigation.
      Bituminous Coal Mining

      The selection process for coal  mining sites is more difficult than
for other industries because the coal mines constitute a multitude of
point sources of air pollution as well  as an area source of water pollu-
tion.  Bituminous and lignite coal mining with associated preparation
plants constitute SIC 1211.  The mines  are not located in one specific
region of the candidate counties but, in general, are spread throughout
the county.   This is true for two of the counties with the highest bitu-
minous production, Wyoming County, West Virginia and Buchanan County,
Virginia.  As part of a pilot study to  examine the problems associated
with the field investigation, the site  selection process for these two
counties was examined in detail.

      Topographic maps (1:24,000) which display locations of mines,
preparation plants, houses, etc. were purchased from the U.S. Geological
Survey for each of the study counties.   Close inspection of these maps,
along with detailed process information described in Section V, dis-
closed two good study areas in Wyoming  County.  These areas, when aggre-
gated, will  represent one study site.

      While performing the pilot study  on Buchanan County, the presence
of a coke oven in the middle of the county was noted which had not been
listed in the initial industrial data.   Information from NEDS* indicated
that the coke oven was responsible for  94% of the particulate and all of
the SO , NO , CO, and hydrocarbon emissions from industrial processes in
Buchanan County.  For these reasons,  Buchanan County was determined not
to meet the selection criteria (Table V), and has been excluded from
further consideration as a potential  study site.

      Based on the site selection criteria, Kopperston and the Mullens-
Allen Junction-Bud-Itmann-Stephanson  area of Wyoming County have been
determined as appropriate study sites.   There is high activity of mining
of Pocohontas #3 and #12 coal and of coal preparation in these areas.
The two largest coal preparation plants (tipples) in the county are loca-
ted in these areas.  They have been there for at least fifteen years.
Recent atmospheric emission data from the preparation plant has been
obtained from NEDS.*
* National Emissions Data System, Condensed Point Source Listing for
  Buchanan County.

                                    14

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                                     TABLE  V

       CRITERIA FOR SELECTION  OF STUDY  (EXPOSED)  AND CONTROL  (NON-EXPOSED)  SITES
                            STUDY
                                              CONTROL
INDUSTRIAL
EMISSIONS AND
PROCESSES
POPULATION
AT RISK
PATHWAY
High activity of industry
under study.
Little local industrial
clutter.
Appropriate plant history
(time factor).
Plant emission and effluent
data available.

Low migration.
Small likelihood of
occupational origin.
Health data available.
Suitable population
density characteristics.
Availability of medical
facilities.

Tractable pathways.
No industry suspected of
emitting hazardous agents
exists.
Located in same or adjacent
county.
Match control variables (see
Section IV-C).
Population is not potentially
at risk from an emission or
effluent from a candidate
industry.
                                        15

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      Appalachian migration patterns are relatively stable and migration
has generally been out of the area rather than into it.  The availability
of health data for Wyoming County is described in Section V-D.  Finally,
a population at risk can be identified which is downstream and downwind
from the plants in question.

      The second study site is in Harrison County, Ohio.  Harrison County
is on the border of the Appalachian coal mining region.  It contains areas
of heavy strip mining in the southeastern portion of the county and an
area of no coal mining the northwest.   The Georgetown Coal  Preparation
Plant, the largest in the country, is  located in Harrison County.   Our
sources indicate that an earthenware factory is the only major manufactur-
ing plant in the county.  Strip mining of Pittsburgh #8 coal  has been
carried out for decades in Harrison County.   The Georgetown plant is
located three miles southeast of Cadiz.   Cadiz, a town of about 3,000
is surrounded on all sides by miles of strip mines.  Thus,  mine runoff
and water-borne toxicants would put the population of Cadiz at risk via
a water route.  Airborne contaminants  from the Georgetown plant and other
tipples to the south and east of Cadiz  would not be expected to put
Cadiz's population at risk, since general air patterns over the region
flow northeast to southwest.   Further  micrometeorology will have to be
done in the field studies.

      The third study site selected for testing hypotheses, relating to
environmental induction of diseases from coal mining operations, is
Floyd County, Kentucky.  Many underground mines are located along various
branches or tributaries to the Levisa  Fork.   Few preparation  plants are
present and there is almost no strip mining of the Elkhorn  #3 coal  which
is prevalent in the county.  Fifty-three percent of the working population
in Floyd County is employed in bituminous coal  mining and cleaning.  There
are no other major industries in the county.  Floyd County, like the rest
of Appalachia, has seen a negative net migration.  There are  hospitals in
Martin, McDowell, and Prestonburg from which morbidity data is obtainable.
Floyd County appears to be especially  good for obtaining tractable path-
ways.  Tributaries to the Levisa Fork  begin at the southern boundary of
Floyd County and flow northward.  Populations at risk from  water-borne
exposure to potential toxic agents are located all along the  waterways.
Airborne contaminants do not appear to be the hazard that they would be
in Wyoming County because of the relatively low number of tipples  in the
county.

      Harrison County and Floyd County were selected for study because
of their ideal applicability to this study.   Harrison County, on the
border of the coal mining region, has  a highly exposed population  and a
non-exposed population.  Underground mining is the sole type  of mining
practiced in Floyd County.

      The three areas which have been  selected for the epidemologic field
study of potentially hazardous community health effects of  bituminous
coal  mining represent a cross section  of the eastern bituminous coal
mining region.  Bituminous coal mining in the Appalachian basin was
selected in preference to lignite mining because lignite mining did not
constitute a major portion of the employment data on which  the regression

                                    16

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analysis was done.  The Appalachian coal mining district allows testing
of hypotheses based on acid mine drainage since this is the primary area
where it occurs.

      Each of the three study sites overlies a different type of coal
and each coal has its own characteristics.  It should be noted that the
counties with the highest industrial activity were not necessarily the
best areas to study.  Control areas are difficult to find in counties
which mine coal throughout the county.

      Our hypotheses development will  be able to test potential effects
of different mining methods.  Harrison  County uses strip mining exclusive-
ly while Floyd County is solely an underground mining county.  Wyoming
County contains both types of mining.   Exposure of community residents
to emissions from coal preparation plants is another testable hypothesis
with the counties selected.  The study  sites in Wyoming County, being
downwind and downstream from large tipples, would be at risk, while only
a few small isolated plants are located in Floyd County.
      Copper Smelting

      The site selection process for copper smelting was considerably
easier than that just described for coal mining.  Copper smelters re-
present point souces of pollution.   Populations are usually congregated
around the smelters which are generally located in isolated areas.
Although isolation means that occupational exposure may dominate the
situation, our analysis will recognize that possibility and attempt to
correct for it by looking at mortality and disease incidence among the
female and non-occupationally exposed male population.

      The sites selected are Anaconda's smelter in Anaconda, Montana,
the Kennecott Plant in McGill, Nevada, and the Kennecott operation in
Hurley, New Mexico.  Anaconda, Montana appeared to be the best situation
to study.  The town is large (population 10,000) and is located within a
mile of the largest smelter operation in America and its associated
tailings ponds.  In addition, the town is located in a pass between two
mountains which would tend to increase pollution levels under stable
atmospheric conditions.  The ore mines which supply the Anaconda smelter
are at least ten miles distant and should contribute no confounding
variable.

      McGill, Nevada is a small town which pratically surrounds the
Kennecott smelter.  Population and plant output are both small, but this
plant has been in operation since 1908.  Molybdenum is also processed
as a byproduct of the smelting operation.

      Hurley, New Mexico is the final site chosen for study.  The plant
is just east of the town, but the close proximity indicates that community
exposure would have occurred.
                                    17

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      Hopefully, this selection of plants will  enable the ECI Team to
test hypotheses regarding the health impact on  the community of copper
smelter emissions and effluents.  Copper mining is not carried out in
the immediate vicinity (5 mile radius)  of any of these plants and should
not confound the results.  Recently, gases from the converter have been
contained and sent to an acid plant in  two of the three sites.  Particu-
late matter is trapped by use of electrostatic  precipitators on all  of
the smelters to be studied.   The Kennecott operation in McGill appears
to have the best pollution control  devices, as  a settling flue and multi-
clones are used in conjunction with the electrostatic precipitator.   The
epidemiology of chronic diseases relies on the  long-term exposure of
populations to toxic agents.   Extremely large tailings ponds are associa-
ted with each of the smelters and may be associated with exposure via a
water route.

      Site selection for the  remaining  four associations will  follow a
procedure similar to that described above.   It  is anticipated that the
process will be somewhat easier because the other industries constitute
well-defined point sources within the county of interest.   Picking the
population at risk will  also  be much easier.
                                    18

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          IV.  APPROACH FOR INVESTIGATION OF CAUSAL RELATIONSHIPS
A.    General
      Our basic approach for the investigation consists of two sequential
tasks.  The first is the formulation of plausible hypotheses linking dis-
semination of industrial pollutants to pathophsiology  in the
community residing near an industrial plant.   These hypotheses wili
consider specific pollutants, routes by which a human population might
be exposed, and the likely effect of such exposure in the etiology of
certain diseases.  The second task, which follows the first, is the
testing of these hypotheses.   This will involve comparing mortality
(and morbidity) experience of persons exposed to industrial  pollutants
with that of an unexposed population.


B.    Hypothesis Development Approach

      For each suspect industry, it will  be necessary to determine which
processes are involved, what potentially hazardous pollutants are assoc-
iated with these processes, how toxic substances might escape into the
environment, and how they could be disseminated so as to affect the
health of human beings.  Data pertaining to a specific plant or industry,
or knowledge of emissions or effluents from common industrial practices,
such as drying or distillation, can be used to identify suspected pollu-
tants.  If these pollutants could possibly escape into the environment,
it will be necessary to hypothesize a route by which  they could contamin-
ate populated areas.  Here it will be necessary to postulate only the
conditions necessary for pollutant transport into the subpopulation.
Finally, the physiologic mechanism leading to a pathological  response
in an exposed population must be determined.   In this determination,
the proposed entry of the toxic substance must be considered.  Addi-
tionally, the demographic characteristics of the population  must be
taken into account as well  as incubation  or latency periods  (lag time)
between exposure and appearance of symptoms or death.   In summary, the
hypothesis development approach will  result in the generation of specific
hypotheses to include the following:

      1.   Specific pollutants resulting  from suspect industrial
           processes at dosages large enough  to cause disease.

      2.   Plausible pathways for transmission of these pollutants
           to a population at risk.

      3.   Physiological  mechanisms  which explain how these  pollutants
           could cause the specific disease in the population at risk
           as determined by their location and demographic charac-
           teristics.

      4.   Approximate lag time between exposure and  appearance of
           pathophysiological  death.
                                    19

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C.    Hypothesis Testing Approach

      In testing an epidemiologic hypothesis, as in other experimental
efforts,  several  approaches are usually available to the investigator.
Each has particular merits and disadvantages and usually must be judged
in the context of time and cost constraints, as well as design efficiency
and applicability of the results.  For our investigations, we have con-
sidered the following directionalities in study designs:

      1.   Retrospective Follow-Up

           We would identify all members of a cohort living in an area
      suspected of being exposed to industrial pollutants and a cohort
      living in an area not exposed at some designated time in the past.
      All persons would be followed over a period of time (until the
      present) and their morbidity and mortality experience would be
      compared.

      2.   Prospective Follow-Up Study

           In this design, we would identify all people living in
      exposed and non-exposed areas; follow them for a period of time;
      and compare their mortality and morbidity experience.

      3.   Retrospective Case-Control Study

           Cases of the disease being investigated and controls (of
      another disease not related to environmental exposure to indus-
      trial pollutants), determined either from death certificates or
      hospital records on file, would be compared as to their place
      of residence in exposed or non-exposed areas.

      4.   Prospective Case-Control Study

           This is similar to 3 but would involve only "incident"
      cases, i.e., deaths or hospitalizations occuring since the
      beginning of the study.

      5.   Cross-Sectional Study

           For every death or hospitalization from a selected disease,
      we would determine the last known place of residence as either
      in an exposed or non-exposed area, and compare the rates of
      both groups.


      It is apparent that no simple approach is totally acceptable in
relation to the constraints mentioned above.  Some of the reasons for
this are as follows:  Designs 1 and 2 require total enumeration of a
population and complete follow-up of all persons, tasks which are very
expensive and time consuming; 3 and 4 require the selection of control


                                    20

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diseases which are unrelated to exposure to industrial contaminants and
without knowledge of all  emitted compounds, the potential for bias in
selection of controls is  high; 5 provides little indication of tempo-
rality in an association  since both independent and dependent variables
are determined at the same time.

      Although the particular study location will  determine which general
design to use, it must be realized that an investigation with as broad
a scope as this can only  serve as an indication of potential  industry/
disease relationships.  Therefore, an expensive and time-consuming follow-
up approach is not indicated (unless the period of follow-up is relatively
short, as it might be for some diseases).  Neither is a case-control
approach appropriate without well-founded suspicion of an etiologic
agent.  Therefore, we have chosen, at least for our initial investiga-
tions, to employ the cross-sectional study design  with modifications
such as using a "matched  control" population to improve causal  inference.
As the entire investigation progresses, we may be  able to adopt elements
of the other approaches into our study design.

      Using the cross-sectional approach, we will  compare the mortality
(and morbidity) experience of populations exposed  to industrial pollut-
ants with that of "matched control" populations, i.e., demographically
similar but unexposed to  emissions, effluents, or  solid materials.   The
alternative approach of comparing morbidity and mortality experience  of
exposed populations to that of a "standard" population and adjusting
statistically for the effects of uncontrolled variables is inappropriate
because adjustments deal  only with the adjusted factors while controls
may also cover unmeasured factors.  That is, the differential effects
of uncontrolled variables are lessened when comparisons are made between
similar populations.  This method attempts to hold constant other possi-
ble etiologic factors, much the same as randomization, so that the only
difference in the populations being studied is the factor being investi-
gated.

      This design offers  the following advantages:

      1.  The effect of industrial activity on mortality and morbidity
          can be judged in a relatively homogenous population in refer-
          ence to a specific industrial entity, thereby decreasing the
          potential for confounding.

      2.  The effect of several similar industrial entities can be
          examined in several different settings in order to elucidate
          a causal relationship in an entire industry or a large part
          thereof.

      3.  Differentials in health effects from similar industries in
          different settings may indicate that appropriate pollution
          control procedures can ameliorate disease-causality potential.


                                    21

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      4.   Estimates of relative and attributable risk are readily
          obtainable.

      The unexposed population chosen for comparison will  be one which
is matched as closely  as  possible, demographically, to the exposed popu-
lation.   A set of enumeration districts to be used as controls will  be
chosen by matching the distributions of the following variables in the
control  aggregate to those in the study aggregate:

      1.   Age
      2.   Race
      3.   Sex
      4.   Nativity
      5.   Education
      6.   Residence in 1965
      7-   Income
      8.   Persons per  room
      9.   Heating fuel used

      We have, at present, no defined range for a particular variable to
be considered "matched".   Nor can the relative importance of the matching
variables be judged in the context of the entire investigation.  Rather,
we will  examine the distribution of the matching variables in the exposed
and non-exposed areas  and, depending on the particular location, choose
those variables which  are critical in that study site.  For example, in
Appalachia we will not be too concerned with nativity in our matching,
while in Arizona we must pay particular heed to this variable because of
the highly heterogenous population.  We will, however, choose the best
set of enumeration districts in the unexposed area whose collective
demographic characteristics most closely match those of the exposed
population.

      Conjunction of two variables or mere statistical association be-
tween them is insufficient for judging causality.  Obviously, data
collection procedures  must be sound, but beyond that, the following
criteria must be judged in evaluating causality in an association:
strength, consistency, temporality, specificity, coherent explanation.*

      The design of this study, which will allow comparisons between
exposed and non-exposed population  groups, both within and among indus-
trial areas, provides  a basis for evaluating these criteria.

      Criteria  for  Establishing Causality

      Strength  of association:  The stronger an association, the more
likely it  is to be  causal.*  Therefore, we will examine, within each
study location, the differences in morbidity and mortality of  an exposed
*Causal Thinking in the Health Sciences, M.W. Susser (1973)
                                    22

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population and a demographically similar non-exposed control population
in the same general area.  The ratio of mortality (or morbidity) rates
would indicate the effect of exposure on health.  We will also compare
the rates of people living nearby a plant with those of people living at
varying distances from the industry.  Likewise, we will examine differen-
tials in duration of residence among the exposed population.  It is hoped
that in this way a dose-response relationship can be demonstrated in
relation to proximity or potential duration of exposure to industrial
emissions.  Furthermore, industries of different size, in separate loca-
tions, can be compared for their effect on their respective surrounding
communities.  As disease relates to an industry as a whole, exposed
populations from similar industrial sites will be compared as a single
group to all non-exposed populations to test the strength of the associa-
tion on this broader basis.

      Consistency of association upon repetition:   By conducting our
investigations in several areas, each containing a common industry, the
consistency of the association can be tested.  Within each area, exposed
and non-exposed populations will be compared in relation to their mortality
(and morbidity) experience.  Should exposed populations in several  areas
exhibit higher death (or illness) rates, the concept of causality would
be greatly enhanced.  Alternatively, lack of consistency may indicate
differences in pollution dissemination and control,  medical care or
diagnosis, and therefore will not necessarily negate the association.

      Temporality - time sequence of variables:  This criterion will,
perhaps, be the most difficult to fulfill due to the necessity of obtain-
ing past exposure data.  With a cross-sectional design, it is quite diffi-
cult to determine whether exposure or disease occured first.  To amelio-
rate this problem, we will attempt to' determine place of residence,
meteorologic phenomena, and industrial processes and emissions as they
occurred years ago.  Where this is impossible, it may be necessary to
make certain assumptions which relate current estimates to past condi-
tions; assumptions that will  undoubtably affect the  precision and cer-
tainty of a relationship.

      Specificity:  Ideally,  one manifestation resulting from one cause
is the desired result.  A causal relationship is enhanced by specificity
but lack of specificity does  not rule out causality.  We have identified
industries which appear to be related to several diseases, but we expect
to enhance specificity by correlating health effects with specific
emissions.  It is recognized, however, that etiologically similar diseases
may result from exposure to the same industrial pollutants.  Certainly,
the ability to observe the presence of a suspected pollutant in the ex-
posed area would be desired.   The validity of the proposed pathway would
be somewhat suspect without this additional proof.

      Coherent explanation:  Coherence refers to concordance of an explana-
tion with known facts about the disease and causal  factor being investiga-
ted.  A coherent explanation  supports existing theory.   Incoherence re-
quires the formulation of a new theory.  We will base our hypotheses on
the ability to postulate a coherent explanation for  linkage of industrial
pollutants via environment to health effects in the  community.   If the
                                    23

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results of this study conflict with our hypothesis, another explanation
must be proposed and, if possible, studied.


      Study Protocol

      We will locate death certificates (and hospital records) for persons
deceased or hospitalized from certain diseases.  Data on morbidity and
mortality for a designated period of time will be abstracted to standard
forms for all residents of each study area,  regardless of their eventual
designation as exposed or non-exposed.  This methodology will  eliminate
any systematic bias on the part of the investigators.  Bias may be intro-
duced in relation to obtaining morbidity data if availability of medical
care and medical facility usage varies systematically with exposure status.
Only complete attainment of morbidity data for all persons will minimize
selection bias in this type of health data.   After health-related data is
collected and abstracted, exposed and non-exposed groups will  be designated
primarily by place of residence.   Duration of residence in the exposed
area will be estimated from voting registration or tax records, property
deeds, and other available sources.  If this information is unavailable,
potential dose-response relationships can only be examined relative to
distance from the pollution source.  Furthermore, lack of this information
for a highly mobile population will diminish the precision of estimated
relative risk.

      The demography of the affected population will  be determined from
death (or hospital) records.  Demographic data on persons not identified
through health records (i.e., denominators of rates)  will be obtained
from census tabulations on enumeration districts.  Industrial  emission
data, not available from known process information, will be obtained from
industries and agencies and may be supplemented by on-site measurements
of air, water, and soil.  We will determine  if the suggested emission is
of a magnitude large enough to be a potential health  hazard.  Our analysis
will also consider the possible confounding  effect of migration, occupa-
tional exposure, duration of residence, and  age.  Section V details data
requirements and acquisition procedures.

      The acknowledged limitations of the proposed study design in its
ability to uncover causal relationships are  superseded by elements in
the design which will allow judgement of an  entire body of evidence,
each piece of which may not be convincing in a statistical sence by it-
self.  Dr. M. W. Susser recently commented:

      "Clinicians, epidemiologists, and applied statisticians often
      experience a tension between the formal requirements of a
      statistical test of a result on the one hand, and the practical
      requirements of a judgment about the application of the result
      on the other.  Formal statistical tests are framed to give
      mathematical answers to structured questions leading to judg-
      ments, whereas in any field practitioners must give answers
      to unstructured questions leading from judgment to decision
      and implementation.  These questions of decision generally
      hinge around judgments about causality and prediction. . .


                                    24

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      (One should) recognize that the difference between types of evidence
      is relative and not absolute, and apply all  available criteria of
      judgment to any particular instance.   Perhaps we may advance beyond
      our present limitations by systematizing our criteria of judgment,
      and by expanding the number and type  of available criteria"*

      One type of criteria mentioned previously is consistency upon
repetion.  This is true even though we will  not have "the apparatus for
exact replication which enables the physical  scientist to demonstrate
consistency".  The hypothesis testing approach does, however,  offer the
advantage that the

      "most powerful  alternative to exact replication is
      consistency of a finding on repeated  tests.   The strength
      of the arguments rests on the fact that diverse approaches
      produce similar results"-*
*Judgment and Causal  Inference:   Criteria in  Epidemiologic  Studies,
 M.  W. Susser, American Journal  of Epidemiology,  105:1-15  (1977)
                                    25

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           V.   DATA REQUIREMENTS AND ACQUISITION PROCEDURES
A.    General
      Collection of retrospective data is in general a difficult
process.  In this study, the difficulties are augmented by the
probable lack of assistance on the part of industry.  Further
problems arise when one must rely on death certificates, entities
notoriously known for their inadequacies and lack of reliability.
However, death certificates are gathered systematically and at least
can be expected to represent an almost complete accounting of all
deaths in a particular area.  This cannot be said for morbidity
data, although the proposed study design attempts to randomize the
errors associated with them.  Following is a discussion of our data
requirements and proposed acquisition procedures, subject to vagaries
not yet known prior to the field investigations.


B.    Industrial Processes, Emissions and Effluents

      For each suspect industry a list of emissions and effluents will
be developed from existing data sources and from an analysis of the
industry's materials and processes.   Specific information needed, how
it will be obtained and anticipated  problems are discussed here with
examples from the pilot study on bituminous coal mining.

      Existing emissions and effluents will be collected for each
suspect industry.  Sources of data are federal  and state agencies,
industry, and other private groups.   A specific example of a federal
source is the Environmental Protection Agency publication EPA-450/2-
74-021a, October 1974, Background Information for Standards of
Performance:  Coal Preparation Plants.  The book Groundwater Pollution,
edited by the Editorial Board, Underwater Research Institute, is an
example from the private sector.

      Anticipated problems in locating emissions and effluents data
for a period from approximately 1925 to 1970 are significant.
Complicating monitoring factors in finding prior emissions and effluents
data, if they exist for the suspect plant, are the following:

      •  precise monitoring location

      •  time distribution of monitoring

      •  changes in monitoring over  time

The pollutants regularly monitored are only general such as particulates,
SOX, pH, and hardness.  A particular heavy metal from a coal slack dump
would not have been monitored.  Consequently, existing historical data
may at best show general trends.


                                    26

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      Details of the processes in the suspect industries will be
needed to identify sources of emissions and effluents.  When a source
is located, the materials being handled at that point can be
identified.  The chemical composition, concentration, physical state,
and pathway of the emissions and effluents to the environment will
be determined.  The plant processes are categorized into the
following:

      t  storing

      •  handling

      t  processing

      t  work practices

      •  accidents

      •  disposal

The term "work practices" includes ooerations such as purging of lines,
cleaning of equipment, maintaining equipment, repairing equipment,
etc.  Materials at a plant will be categorized into the following:

      •  raw

      •  intermediate

      t  final

      t  by-product

      •  waste

      t  process
      •  power generation

The process materials include any catalysts or reaction media.   Power
materials include all fuels and often the plant's own wastes.  All of
the materials may release toxic agents to the environment.

      Material and process descriptions will  be collected from experts
in industry, government agencies, literature, the private sector,
and direct observations.  For example, specific process equipment is
listed by name for coal preparation plants in the Keystone Coal  Buyers
Manual.  A site visit to a preparation plant will show the methods
used to store and move the thousands of tons  of coal  a day that are
handled.  J. M. Evans, a chemical engineer at Enviro  Control  with
20 years experience in the coal industry, has described how water is
used to separate coal from dirt and rock.  The wet coal may be dried
in the flue gas of a coal furnace (thermal drying process); consequently,
the coal combustion materials are an important component of the emissions,
No one data source is expected to completely describe each industry,
but the combination of information from several  sources will  describe
industrial processes and materials.
                                    27

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      Historical changes and their dates will be needed for plant
materials and processes that have changed the emissions and effluents.
This includes the date of construction, process changes, and installation
of any pollution control devices.  Technical advances, changing
economics, and pollution control laws have had effects on emissions
and effluents chemical composition and concentrations.  The information
of a change in a plant process may be documented in government agencies,
plant records, and the literature.  For example, the installation of
control devices by type and date for point sources is documented by
the National Emissions Data Systems in the EPA.

      Problems are anticipated in obtaining plant process and material
data.  Because the SIC codes are by final product and not by industrial
process, one code can include several diverse processes.  The SIC code
for the pilot study industry is as follows:
      Group No. 121 - Industry No. 1211 - Bituminous Coal and Lignite

      Establishments primarily engaged in producing bituminous coal or
lignite or in developing bituminous coal or lignite mines.  This industry
includes underground mining, auger mining, strip mining, culm bank mining.
and coal cleaning, crushing, screening, and sizing plants, whether or not
operated in conjunction with the mines served.
              •  Brown coal mining
              •  Cleaning plants, bituminous coal
              •  Coal mining, bituminous
              •  Crushing plants, bituminous coal
              •  Culm bank recover, bituminous coal
                 or lignite: except on a contract basis
              •  Hard coal mining, except Pennsylvanis
                 anthracite
              •  Lignite mining
              •  Screening plants, bituminous coal
              •  Semi anthracite mining
              t  Semi bituminous coal mining
              t  Strip mining, bituminous coal: except
                 on a contract basis
              •  Subbituminous coal mining
              t  Washeries, bituminous coal
                                    28

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      Industry No. 1213 - Bituminous Coal and Lignite Mining Services^

      Establishments primarily engaged in performing bituminous coal and
lignite mining services for others on a contract fee, or similar basis.
Establishments which have complete responsibility for operating mines
for others on a contract, fee, or similar basis are classified according
to the product mined rather than as bituminous coal and lignite mining
services.
              0  Auger mining services, bituminous coal or
                 lignite: on a contract basis

              •  Bituminous coal mining services: on a
                 contract basis

              t  Culm bank recovery, bituminous coal or
                 lignite: on a contract basis

              •  Draining or pumping bituminous coal and
                 lignite mines: on a contract basis

              •  Drilling for bituminous coal and lignite
                 mining: on a contract basis

              •  Lignite mining services: on a contract
                 basis

              •  Lignite strip mining: on a contract basis

              •  Overburden removal for bituminous coal:
                 on a contract basis
              •  Sinking shafts for bituminous coal and
                 lignite mining: on a contract basis

              •  Strip mining, bituminous coal: on a
                 contract basis

              •  Stripping services, bituminous coal and
                 lignite: on a contract basis

              t  Tunneling, bituminous coal and lignite
                 mining: on a contract basis

The bituminous coal cleaning plant division alone can have either dry
or wet separation processes or both.  A wet process may include a
thermal drying process.  In addition to the number and variety of
processes in a SIC code, the processes and materials may be proprietary.
Often materials have complex chemical components such as bituminous
coal which varies from sample to sample, seam to seam, and basin to
basin.  Different coal mining methods and coal washing methods under
the same SIC code and in close proximity to each other complicate the
emissions and effluents analysis.
                                    29

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      In conclusion, there are two sources of emissions and effluents
data -- existing data and information from analysis of industry
processes and materials.  Both private and governmental organizations
at all  levels may have specific emissions and effluents data.  Historical
changes in emissions and effluents can be estimated by changes in
existing data and changes in industry.  Problems in obtaining reliable
data on both historical  changes and individual pollutants is expected.
Plants  in the same industry, that are close to each other and have
different processes, complicate defining particular emissions and
effluents.  Specific processes and materials may be proprietary and
have complex chemical compositions.
C.    Pathways
          1.   Introduction

              The human health effects of specific pollutants, both
          known and postulated, can be inferred only where a mechanism
          exists for transport of a known industrial emission or
          effluent from the source to the human receptors.  Once
          industrial activity has been shown to emit a pollutant which
          is  hypothesized to have an adverse health effect it is
          necessary to demonstrate that the emission could get to
          the population at risk.  In discussing the source-receptor
          linkage, we must characterize the emission, consider possible
          chemical and biological transformations and determine the
          method and route of transport.   The basic format will  be used
          for air, water and land routes.

          2.   Atmospheric Emissions

              In addition to emissions from stacks, pollutants may be
          emitted from ventilation systems, fugitive sources and spills.
          Chemical transformations of primary pollutants  occur as they
          travel through the atmosphere.   The route that  a pollutant
          travels to the receptor is a complex combination of local
          geography, meteorology and climatic conditions.

              Data which would be required on the state of discharge
          from a particular plant should  not be too difficult to obtain.
          If  the industry, local authorities or regional  EPA has not
          already made atmospheric measurements with high-vol samplers,
          impingers, sulfation plates and analytical instruments, the
          ECI team will investigate the presence and concentration of
          the suspect compound(s).  The specific compounds to be
          monitored would be determined by the process, chemical and
          industrial hygiene engineers.

              The ECI team will use its experience to postulate possible
          biological and chemical transformations once reliable information
                                    30

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          on chemicals utilized and produced in the plant and on poten-
          tial by-products from plant operations has been obtained.

              A method of approaching the ground-level  dosage problem
          is by studying the prevailing wind patterns during times when
          the atmosphere is in different Pasquill  stability categories.
          The three basic Pasquill stability categories which are of
          concern are the stable, neutral, and unstable atmospheric
          conditions.  Since polluting conditions  prevail in a stable
          atmosphere, the prevailing wind direction during stable
          conditions is a tool to determine the population at risk from
          airborne toxic substances.  The National  Weather Service in
          Asheville, North Carolina has developed  a STability ARray
          (STAR) computer program.  Meteorologic input  required for
          the STAR program is simply wind speed and cloud conditions.
          The output is frequency and percent frequency of wind
          direction by speed classes for each stability category.
          By running STAR programs for atmospheric  observing stations
          in the vicinity (100 miles) of the study  site, ECI
          meteorologists will have a tool to determine  which
          population should be at the highest risk  from airborne
          pollutants.  Confounding effects of local  geography and
          topography will be included in the analysis once the
          survey team visits the study site.

              Historic information on ambient air quality in the vicinity
          of coal mining and cleaning operations is crucial  in
          attempting to estimate chronic exposures  of populations to
          pollutants which may be hypothesized as hazardous.  This
          information is available from the Storage and Retrieval of
          Aerometric Data branch of the AEROS Data  System of EPA.
          Their data banks contain air quality information dating back
          to the 1950's.  More historic data may be obtainable from
          individual state air pollution control boards since they are
          the source of AEROS data.

              Transport of airborne materials for  the set of pilot
          study plants is not easy to estimate. As a first order
          approximation of wind speed and direction of  the air mass
          which lies above the study region of Southern West Virginia
          and Western Virginia, a STAR program should be run on wind
          data from Pikeville, Kentucky.  On the local  level, the
          Appalachian region has a distinctive "hollows-and-ridges"
          topography.  The effect of the mountainous terrain on
          atmospheric diffusion is described by Pasquill*.

             "For the case of generally rugged terrain  a
              survey of the air-flow in relation to dispersion
              processes was carried out at the United States
*Pasquill, F., Atmospheric Diffusion, John Wiley & Sons, 1974.
                                   31

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    Atomic Energy Commission at Oak Ridge, Tennessee
    (Holland, 1953).  This site is located in a large
    valley running roughly NE-SW in the Southern
    Appalachians.  The observations display typical
    regimes of valley and drainage winds, and include
    some interesting data on the vertical motions, as
    derived from double-theodolite observations on
    neutral balloons.  A special analysis was made of
    flights with trajectories either down-valley or
    across-valley, in the latter case over a ridge
    rising 100 m above the release station to a
    parallel  valley some 2 km to the north-west.
    During the day, and especially in very unstable
    conditions, the ridge appeared not to have any
    mechanical effect comparable with the thermal
    eddies of large vertical extent, which alone
    would quickly disperse any material released in
    the valley.  At the other extreme, on clear
    nights with light winds, vertical flow within
    the valley was obviously dominated by the
    circulations generated by cooling of the valley
    slopes, and was virtually isolated from the general
    airflow above the ridge."


3.  Water Routes

    Toxic effluents may be introduced directly into waterways
via untreated plant waste materials.  Another method of intro-
ducing potential etiologic agents into the aqueous environment
is by way of sewage.  Sewage construction may allow chemicals
to seep into the environment.  Mine drainage and agricultural
runoff are other methods by which toxic agents can enter the
ground and/or surface matter.

    In order for the ECI Team to get some indication of the
water quality in the study regions, we will contact EPA region-
al and state water resources boards.  These agencies are en-
gaged in ground and surface water monitoring, and  will  be able
to give us data-on water quality in the region being surveyed.

    If we are working with a waterborne agent, it  will  be
important to estimate watersheds of the area surrounding the
suspect plant so that we may be sure that a control population
selected in a nearby area will not be at risk from the  same
pollutants.  Hydrological maps of watersheds, ground water,
and surface water are available from the Geological Survey.

    Waterbourne transport of a pollutant from a given source
can be measured directly.  Water samples may be taken from the
plant effluent and downstream from where the effluent enters
the local stream.  Quality of underground water in the  pertinent
watershed can be measured by taking well samples.
                          32

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              Samples which are taken in conjunction with this study
          do not necessarily reflect conditions 10-20 years ago.
          Therefore, some sort of historical  perspective of the
          quality of water is desirable.  This information is avail-
          able from the EPA's data coordinators for effluent guide-
          lines.

              Almost all  water in Buchanan County drains into the
          Levisa Fork, part of the Big Sandy  River Basin which runs
          through the middle of the county and drains into the Ohio.
          Water quality data has been obtained from the Geological
          Survey of Virginia for this river basin.

              Two well-documented problems associated with coal  mining
          which are seen  in practically all underground bituminous
          coal mining regions are mine drainage and leaching from
          overburden and  open coal piles.   These related problems
          lower the pH of the ground water, mobilize soil  and coal
          minerals, and increase the hardness of the water.   Although
          acid mine drainage is a preventable problem,  the adult
          Appalachian population has been  exposed to several  decades
          of potentially  hazardous drainage and minerals.   Data  on
          exposure levels will  be obtained through  the  literature and
          through EPA resources.


      4.   Other Routes

              Other methods of transport of pollutants  from source  to
          receptor in the community include solid waste disposal,
          employee clothing, bioconcentration in the food  chain  and
          transportation  of raw intermediary  or finished products.   In
          the example of  coal mining, transport in  clothing and  trans-
          portation are of major concern.   Although miners wear
          coveralls in the mines, coal  dust can lodge in the outer
          layer of the clothing and expose the home environment.
          Conveyors, rail cars, and trucks are all  involved in getting coa'
          from the mine to the preparation plant and primary user.
          Substantial agitation during these  operations gives rise
          to significant  amounts of coal fines.
D.     Health Data Needs and Procedures  for Acquisition
          1.   Introduction

              In order to determine if there is  a causal  relationship
          between industrial  activity in selected counties  and the
          occurrence of health problems among community residents,
          detailed information on health and death patterns of the
          involved populations is needed.   Specifically,  we need data
          on  death rates and  disease prevalence  for individuals living
          in  areas which are  contaminated  with pollution  from the
          industrial operations and for control  groups not  affected by


                                    33

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          the environmental hazard.  We will also need information on
          the occupation of the individuals studied since we wish to
          distinguish environmentally mediated diseases from occupation-
          ally induced ones.  Finally, in order to establish a
          meaningful dose-response hypothesis, we must also determine
          the residence of the individual in relation to the source of
          the pollution and how long he or she lived there.  The
          following pages summarize a plan  to acquire this data
          which was developed using the bituminous coal mining
          association as a model.

          2.  Mortality Data Acquisition

              Although records of death are registered at the county
          level, the release of individual death records for research
          purposes is determined at the state level.   In order to
          determine the feasibility and cost of obtaining death
          certificate data, we telephoned officials in Virginia and
          West Virginia.  Contacted in this preliminary inquiry were
          the Director of Registration and Health Statistics for
          West Virginia and the Virginia State Registrar.   Conversa-
          tions with these two officials indicated that the mortality
          data we need can be obtained in a relatively straightforward
          manner.

              The agencies  require that  we furnish  evidence of  our  affi-
         liation  with  EPA,  a brief description  of the  scope and purpose
         of  the research project,  a promise  of  confidentiality  and  a  list
         of  our data requirements.   Upon  receipt  of this  information,  they
         will  search their  records for deaths  from  the  specified  disease
         in  the county and  mail  the death certificates  to  us.   The  fee
         involved in approximately $1.00  per certificate.

              Using this method we can obtain the following relevant
          information on individuals who died from a  specified
          disease: street address  at the time of death, occupation,
          age, cause of death, plus underlying and other significant
          conditions.   A U.S. standard death certificate and the
          information one can expect to find on a properly completed
          form is shown in Appendix E.  Although it is generally
          acknowledged that death  certificates are sometimes incomplete
          and nonspecific*, the health and personal data which can  be
          obtained from them will  provide a valuable  basis for the
          identification of epidemiological  patterns.

              With a few exceptions, most states have policies similar
          to those outlined above  regarding the release of death
*For instance, some attending physicians do not provide all  of the
 information called for on the form and sometimes the occupation listed
 is too general  (e.g., "laborer").

                                    34

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          certificates.  Therefore, we have drafted a three-part
          document which will be sent out in the full scale
          mortality data collection after preliminary contact is made
          with the proper official by telephone.  As is shown in
          Appendix E, the document consists of a personalized letter
          to the official, a project fact sheet and a data requirement
          sheet, which will, or course, vary depending upon the
          association being studied.  Some states (for example, West
          Virginia) have a separate confidentiality agreement which
          must also be completed and signed (see Appendix E).  The
          names, titles and telephone numbers of the appropriate
          state health officers can be easily located by using the
          1976 Director of Registration Areas for the United States
          and Canada published by the Department of Health, Education
          and Welfare.  Prior to negotiation with any state officer
          for actual data acquisition, the EPA project officer will
          be notified and clearance obtained.

          3.  Morbidity Data Acquisition

              Sources of morbidity data are less centralized than are
          death records.  Figures such as those compiled by the
          National Center for Health Statistics are aggregated
          statistics and thus cannot be analyzed on the level of
          detail which we require.  In order to obtain the type of
          individual health information we need, it will  be necessary
          to examine the records of hospitals* or health insurance
          organizations in the various study sites.

              Again using the bituminous coal  mining association as a
          model, we identified the health care facilities in the two
          study counties (Buchanan,  Virginia, and Wyoming, West
          Virginia) and also in the adjacent counties, since it is
          likely that individuals may go out of their home county to
          seek medical care; see Figure 3.  A list of potential  sources
          of health care and/or local health information for the ten
          counties involved was compiled using the 1976 edition  of the
          American Hospital Association Guide to the Health Care Field
          (see Appendix E).The list includes hospitals, clinics,
          nursing homes, health care planning facilities  and medical
          insurance organizations.

              Since the list was rather lengthy, we attempted to locate
          actual statistics on where individuals in the two counties go
          for medical treatment.  With this type of information, we
          can determine the number of health care facilities necessary to
          contact in order to obtain the health records of the study and
          control populations.
*Physicians are possible sources of morbidity data,  but the cost of
 obtaining data from this source is prohibitive for  this investigation.
                                    35

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                                                                    WEST VIRGINIA

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-------
    The Director of the West Virginia State Department of
Health furnished the patient flow data given in Table VI.
This shows that in order to acquire data on all of the
patients from Wyoming County, it would be necessary to
deal with 18 hospitals (Table VI Part A).   This number
of hospitals could be reduced depending upon the degree of
sampling completeness required.   For instance, collection
of data on 76% of those hospitalized would involve only
7 hospitals  (i.e., hospitals in Wyoming, McDowell and
Raleigh counties)   (Table VI  Part B).  Similar patient
flow data shown in Table VII was obtained from the Executive
Director of South Western Virginia Health Systems Agency.
To acquire data on all of the patients from Buchanan
County, it would be necessary to deal with 10 hospitals.
(Part A)  However, some hospitals had only a few admissions
from Buchanan  County.  A more realistic figure is that
97% of the patients were treated in 3 hospitals (i.e.,
Cinch Valley Clinic and Mattie Williams  Hospital  both in
Tazewell County, and Grundy Hospital in Buchanan County).
Nursing home data was also furnished for Buchanan County.
Table VII. Part B shows the patient distribution  for
nursing homes is much more broad than for short term
facilities.   For instance, the 14 patients tabulated went
to 8 different homes.  The highest percent going  to any one
home was 28%.

4.  Contact with Local Hospital  Administrators

    In order to determine the regulations concerning access
to hospital  records, we contacted the administrators of
Wyoming General Hospital in Mullens, West Virginia and
Grundy Hospital in Grundy, Virginia.  The reactions of the
two administrators to questions  about the availability of
hospital records for research purposes were similar.  They
had not received requests of this type previously stated
that they needed more detailed written information before
they could make a decision.   In  the case of Wyoming General,
review of our request would be made by the hospital president
and attorney, in addition to the administrator.  Both
hospitals requested in writing (1) a statement  of our
relationship to EPA, (2) a summary of the scope and purposes
of the project and (3) the specifics of  our data  requirements.
The concerns they expressed regarding the release of the
information were also similar.  They are sensitive to outsiders
viewing the records and to any possibility of physician
performance review.  They are committed  to protecting the
privacy of their patients and insist on  concealment of the
identity of individual cases.  Both hospitals felt that the
task of sorting and abstracting  records  would impose a burden
on the record room personnel.
                          37

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                                TABLE VI


PART A:
                     DISTRIBUTION OF DISCHARGES FROM
          SHORT-STAY HOSPITALS FOR RESIDENTS OF WYOMING COUNTY

                                              Percentage of Discharges
                                               Who Are Wyoming County
Location of Hospital      Name of Hospital     	Residents	

Logan	Logan General	2.4%
McDowell	Doctor's Memorial	8.7%
                          Man Appl.  Reg	15.3%
                          Stevens Clinic	14.5%
                          Welch Emergency	10.1%
Mercer	Bluefield	2.1%
                          St. Luke's	3.1%
                          Princeton	4.1%
Raleigh	Beckley A.R.H	10.7%
                          Beckley	10.4%
Wyoming	Wyoming General	92.0%
Kanawha	Charleston Memorial	0.4%
                          Eye & Ear	2.2%
                          Charleston General  	 0.2%
Cabell	Cabell-Hunt	0.2%
                          St. Mary's	0.5%
Nichols	Summers vi lie	0.2%
Monongalia	W.V.U	0.2%
PART B:
Wyoming County has only one hospital, it is situated in Mullens and
contains 39 beds, or 1 bed for 1,000 residents.  It is therefore
necessary for patients to utilize hospitals outside of Wyoming County.
Residents of Wyoming County seek treatment at hospitals within the 9
county southern region.  No resident discharges originated from out-
of-state facilities.

Of the 262 Wyoming County patients discharged from area hospitals for a
given period, the distribution by county of hospitalization was as
follows:
                                        Percentage of Wyoming County
               Hospital Location        Patients Treated at the Facility

               Wyoming County	33%
               McDowell County	22%
               Raleigh County	21%
               Mercer County	8%
               Logan County	10%
               Charleston. Summersville or
               West Virginia University 	 6%
Data furnished by West Virginia State Department of Health.


                                    38

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PART A:
                      TABLE VII
                  PATIENT ORIGIN  DATA

            January  15 - February 13,  1975

                     Buchanan  County
          Clinch Valley Clinic	141
          Bristol Memorial  	   7
          Johnson Memorial  	   4
          Grundy	311
          Mattie Williams	65
          Lebanon General.  .
          Norton Community  .
          Tazewell Community
          Roanoke Memorial  .
          Montgomery County.
1
1
1
2
1
                                     TOTAL  534
PART B:
             NURSING HOME PLACEMENT SURVEY

              HSA III, February 15, 1975

                    Buchanan County
             Washington County	4
             Bristol	2
             Montgomery County	1
             Roanoke County  	 1
             Roanoke City	2
             Salem	2
             Bedford	1
             Henrico County	_J_
                                  TOTAL  14
Data supplied by Southwestern Virginia Health Systems  Agency
                          39

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    The draft of a three part morbidity data request very
similar to the mortality document is in Appendix E.
Included is a personalized cover letter, emphasizing our
mutual concern about safe-guarding patient privacy and our
readiness to provide personnel and/or financial support
for the abstracting task.  The same project fact sheet is
used.  The specifics of the health data needed have been
listed in the morbidity data requirements sheet.  To
facilitate the actual abstracting from hospital charts an
appropriate data form  will be designed for the abstractors
to use.  The information contained in the three-part
morbidity document incorporates the requirements and concern
expressed by the Virginia and West Virginia administrators
and also by the assistant administrator of a local  hospital
contacted with the same type of trial inquiry.   From these
three sources, as well  as from conversations with an American
Health Foundation representative, we ascertained that the
requirements of many hospitals are likely to be similar.
As with the mortality collection effort, a document of this
type will be sent out to the administrators involved after
initial communication is established by telephone.   Because
of the more sensitive nature of the morbidity data  collection,
the possible need for local personnel recruitment and the
greater complexity of the data desired, on-site consultations
with the officials involved may be necessary.

5.  Medical Insurance Organizations

    We inquired about the policy of medical insurance organi-
zations regarding release of health information for research
purposes.  This approach appeared to be an alternative to the
cost and effort which would be involved in abstracting a
large volume of individual  medical  records from hospital
charts..  It was felt that if insurance companies would
cooperate by providing printouts of patient diagnoses
sorted by residence zip code, we would need to  use  the more
involved method of abstracting hospital records only in very
special cases.

    Officials from Blue Cross of Virginia reacted positively
to our questions about use of patient health data for this
project.   They asked for some written material  on the project
and also wished to confer with their corporate  lawyer, but
in general, expressed a desire to cooperate with us.   If we
provide them with a list of ICDA code numbers for the counties
and zip codes desired,  they will write a program to retrieve
the data from their tape files.  We must, of course,  cover
the costs of such a procedure, but we anticipate it will
probably be less expensive and more efficient than  manual
abstraction.   The Virginia Blue Cross representative said that
although the policies of the various state Blue Cross officials
                          40

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is individually determined, the overall attitude of the
organization is to cooperate with researchers whenever
feasible.

    Results from the Blue Cross of West Virginia were less
favorable.  In general, the Blue Cross facility in this state
is rather limited with regard to what they could provide for
our study.  Much of their system is manual and hence difficult
to  access  quickly and easily.  The information which they
do have on tape is too limited for our needs.  For example,
they could provide us with figures on the number
of a specific disease treated at any hospital.  This,
however, will not tell us the essential point - where the
patient in question resides.  Finally, for certain counties
(like Wyoming) where much of the workforce is involved in
mining, residents are covered by United Mine Workers benefits
rather than Blue Cross.  Officials from the UMW Regional
Office in Beckley were contacted to determine accessibility
of the patient data.  They reported that they are presently
developing a computer system of patient records which will
be retrievable on several identifiers  including zip code.
Unfortunately for our purposes, the system will not be operable
for about six months and then will be equipped to handle only
present health data.  They do not plan to enter retrospective
health data into the system.

    From the information given above, the following morbidity
data collection procedures seem feasible.  Acquisition of
Blue Cross diagnostic information, sorted by zip code will be
a practical way to get data for counties where (i) a
suitable number of residents subscribe to the plan; (ii) the
data base is automated and contains the information we need;
and (iii) the officials agreed to cooperate.  For cases
where the three requirements are not met, morbidity data can
be collected by abstracting hospital records.

6.  Applicability of the Federal Reports Act and the Privacy
    Act to the Health Data Collection Plan

    Form 83-A of the Office of Management and Budget indicated
that the proposed data collection might be regulated by the
Federal  Reports Act.   In order to determine our legal  obliga-
tions  under this law,  the OMB Clearance Officer was contacted.
The conversation is summarized in the letter shown in Appendix
E.  According to the Officer, we are not obligated by law, as
long as  the transfer of information is accomplished officially
between  the hospital  and a non-federal  agency (viz. Enviro
Control).

    The Office of General Counsel of the EPA Grants, Contracts,
and General Administration was contacted with regard to
                          41

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          implementation guidelines for the Privacy Act.   The office's
          legal spokesperson confirmed that the proposed data collection
          activity requires no special clearance under the guidelines.
          The final  published report, however, must be presented in a
          manner which conceals personal  identity and prevents the
          identification of an individual.

          7.   Residential  Data:  Address  of the Subject

              The mortality and morbidity data must be collected
          and analyzed so  that the residence of the individual can be
          located in relation to the source of contamination.   The
          procedure  involves accurately locating on an appropriate
          map a specific address obtained from either a death
          certificate or a hospital.

              This is a simple matter in  the case of larger communities
          having numbered  streets and roads.  However, in smaller areas,
          such as Wyoming  and Buchanan  counties, addresses are usually
          in  the form of P.O. Box number  or rural route numbers.
          Individuals using box numbers pick up their mail  at the
          post office, which usually (but not always) is  the closest
          one to their actual place of residence.  Post Office per-
          sonnel deliver rural route mail to boxes located  near the
          recipients' homes.  Since we will have the actual address
          on  the death certificate data,  it will be relatively straight-
          forward to locate the residence of the decedent on an
          appropriate map.*

              If the hospitals will  not release patient addresses,  we
          need a plan  to  aggregate patients into cells large  enough
          to  satisfy hospital privacy concerns, but small  enough  to
          allow us to study potential  pathways.  It is possible that an
          analysis of the  mortality distribution may suggest a size
          for such a system.  To make a hypothetical  case,  excess
          mortality  might  occur in clusters of 1 square mile in areas
          surrounding a particular point  of industrial impact.   In  this
          case, a cell size of 5 square miles would be too  large  to
          permit adequate  resolution on the morbidity data.  We would
          want to select a grid size closer to 1 mile square.   In this
          approach,  we would construct by hand a grid system of the
          appropriate size using a map of the area.  An address coding
          key would  be devised so that the  medical record abstractor
          could assign each patient to the  proper cell.
*We have obtained a number of maps for the study counties  which illustrate
 topographical  features*  roads,  structures such as dwellings,  farms and
 public buildings, local  boundries, zip code areas, post office locations,
 and mine sites.
                                    42

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              An alternative is the use of census divisions called
          enumeration districts.  These are small divisions of several
          hundred people devised for non-metropolitan areas which the
          Census Bureau uses as primary data units.  Enumeration
          maps ( ee Appendix E) have street and road patterns but
          no street numbers.  These would have to be filled in manually.*
          The use of these standard grids to gather and plot morbidity
          data has the important advantage of allowing us to use census
          statistical  data to characterize the populations.  Included in
          the information available for enumeration districts are
          various socioeconomic indicators and housing information
          such as year moved into unit and type of home heating fuel
          used.   This  type of data is not available for all residents
          of the district, but rather for a sample of from 5 to 20% of
          the households interviewed,  (see Appendix E for the
          description  of the census data involved.)

          8.  Residential Data:  Duration of Residence in the Area

              In order to determine the effect of duration of residency,
          we need to know how long an individual  lived in the area of
          contamination.   This must be determined for two different data
          sets.   In the case of data for which residence address  is
          known  (i.e., death certificates, and hospital  records if indivi-
          dual address is released), duration of residence can be traced
          through one  or more sources:  1) city residential directories,
          2) tax records, such as state, local, and property taxes, 3)
          records of voting registration, and 4)  county deed registration
          offices.   If, however, the individual addresses are not re-
          leased by the hospital and cells or aggregates are used, we
          will have to rely on the figures given by the Census (see
          Section III  and Appendix E.)  If residential  history was
          obtained at  the time of hospitalization, we will, of course,
          be able to use this.

          9.  Conclusion

              The basic health data needs and acquisition procedures for
          the field studies have been identified  and discussed above.
          Details of the  operation will  need to be evaluated and  handled
          on an  individual  basis for the various  associations.   For
          instance, it is to be expected that unique features  of  the
          particular industrial  activity will  influence the type  and
          amount of health data needed to best evaluate the hypotheses.
*For larger areas of 500,000 (or SMSAs)  the Census Bureau has a computerized
 address coding guide  which may be purchased on tape.   One can then
 automate the procedure of going from a  street address  to a census
 geographic area.


                                    43

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For example, the length of time a factory has been operating
and occurrence of significant process changes will influence
the time span of health data needed.   The number of plant
sites in a county will  determine the  size of the populations
on whom data is needed.  Other factors which can affect the
health data gathering operation are:  size and population of
the area, cooperation of local officials and administrators,
and completeness of the mortality and morbidity data available
                          44

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                              VI.  WORK PLAN
A.      Overview

       We have planned to investigate six industries, their emissions and
effluents, and their relationship to specific diseases in the nearby
community.  Industries will  be examined sequentially, each in three
different locations.

       For each investigation, a site visit to obtain an overview of
the location and to ensure that there are no obvious problems will be the
first order of business.  The visit will also pave the way for eventual
data-collection procedures.

       Each investigation consists of two major tasks:  hypothesis deve-
lopment and hypothesis testing.  The development of a hypothesis entails
a characterization of the industry and its relevant pollutants, research
into the etiology of the disease to identify possible environmental causes,
pathway research to determine plausible routes by which pollutants could
affect the community, and a  final synthesis of a causal hypothesis.

       The hypothesis testing phase involves verification of the presence
of such pollutants at the test site, detailed pathway analysis to estimate
the populations exposed and  non-exposed to pollutants, analysis of morta-
lity and morbidity data and  the related demographic characteristics of
the population, and interpretation of the results leading to acceptance  or
rejection of the causal hypothesis.

       The sequence of the investigations will be:  1) bituminous coal
mining; 2) copper smelting;  3) blast furnaces; 4) non-ferrous wire drawing;
5) men's shirts and nightwear; and 6) viscose rayon.

       Specific sites have been selected for the first two investigations.
For the remaining industries, sites will be selected from candidate
counties just prior to the investigation.

       The plan, as presented in this section, details how our investiga-
tion will start.  As we proceed, we expect to develop and enhance the
plan.   It is expected that alterations will occur and that its metamor-
phosis will reflect experience gained through each investigation.


B.      Task Description

       1.  Investigation of  Bituminous Coal Mining

           a.  Characterize  the mining operations for the selected mines
               by determining the nature and magnitude of:
                                     45

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       materials used
       products and byproducts produced
       processes involved
       modes of transportation of materials (input and output)
       waste material and disposal methods
       ventilation systems
       employment and production history

    Information is to be obtained from:

       mining experts
       mining literature
       State and County officials
       Chamber of Commerce
       plant officers
       other

b.  Characterize the emissions and effluents directly or
    indirectly related to the mining operations by determining
    the amount and chemical  nature of materials released into
    the surrounding community through:

    •  air route
    t  water route
    •  indirect routes (transportation system, home burning
       of coal, leaching through coal  waste, etc.)
    •  chemical transformations (en route)

    Information to be obtained from EPA data bases (e.g.,
    NEDS) and by analysis of mining processes, operations,
    and materials.

c.  Research the etiology of respiratory and cardiovascular
    diseases to identify possible causes related to the
    emissions and effluents  of coal mining operations and
    associated processes.  Research to be conducted by:

    •  thorough literature review
    •  review by a team of experts

d.  Identify plausible pathways from mining operations to
    community by:

    •  characterization of transport phenomenology for each
       site (meteorology, hydrology, topography)
    •  identification of possible transport routes through
       examination of transport phenomenology
    t  determination of population distribution with
       respect to the mines  and to the transport routes
    •  examination of population distribution and transport
       phenomenology to assess the plausibility of the
       various pathways identified.
                          46

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e.  Formulate plausible causal  hypotheses relating respiratory
    and cardiovascular diseases to mining operations and
    associated activities.   Hypotheses will  be derived by the
    examination and integration of the results of the previous
    tasks in which emissions and possible routes were charac-
    terized and physiological mechanisms were hypothesized.

f.  Verify the presence of suspected pollutants at the study
    site:

       from available data
       from on-site monitoring
       for each site, estimate  the source strength of the
       hypothesized disease-causing agents
       estimate ambient levels  of exposure for the agent
       estimate (i) the level of exposure required for any
       possibility of contracting the disease and (ii) the
       safe level  of exposure

g.  Determine exposed and non-exposed populations:

    •  by means of transport analysis, determine general
       areas for each site corresponding to  the risk and
       safe levels of exposure  estimated above

h.  Acquire demographic data and select control areas:

    •  determine the characteristics of the  exposed popula-
       tion including race, sex, critical socioeconomic
       characteristics, duration of residence, and age
       distribution
    •  select a population not  exposed with  demographic
       characteristics matched  to the exposed population
       (for each site)
    •  matching criteria to include (i) age,  (ii) race, (iii)
       sex, (iv) nativity,  (v)  education, (vi) residence in
       1965, (vii) income,  (viii) persons per room, (ix)
       heating fuel used

i.  Determine the location and  duration of residence for
    mortalities with respect to exposed and  non-exposed areas:

    •  acquire and validate death certificates for the past
       20 years
    0  locate mortalities with  respect to exposed and non-
       exposed areas
    •  determine duration of residence at reported location
       by examination of tax or voting registration records
       or property deeds.
                          47

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j.  Determine residence of morbidities with respect to
    exposed and non-exposed areas:

    *  examine hospital records or data provided by third
       party payment plans relating to a specific period
       of time
    *  locate morbidities with respect to exposed and
       non-exposed areas

k.  Analyze data on mortalities and morbidities  for deter-
    mination of effect of industry-related pollutants,  examining
    both sexes and occupationally related cases  separately:

    *   determine epidemological  characteristics  of
       affected population
    •   examine possible confounding effects  of age,
       duration of residence,  migration,  self-selection,
       and occupation
    •   review industry production and  migration  trends
    •   examine,  if possible,  the effect of cigarette  and
       alcohol  consumption
    *   show temporal  distribution of mortalities  (and
       morbidities) in the exposed and non-exposed areas
    •   prepare spot maps showing distribution of mortalities
       (and morbidities) in the exposed and  non-exposed areas
    *   calculate mortality (and morbidity)  rates  for  study
       period for exposed and  non-exposed populations -

       R  = # deaths  or illnesses during specified time period
            population-at-risk in exposed area
       Rn  = # deaths  or illnesses  during  specified  time  period
            population-at-risk in  non-exposed  area

       calculate  ratio  of mortality  (and  morbidity)  rates  as  a
       point estimate of relative  risk, and test-based
       confidence interval  around  the  point estimate.

             R                             + 1.65
       RR  =  -n^                CI -Q,= RR1     x
             n                    -30
      calculate difference between mortality (and morbidity)
      rates as a point estimate of attributable risk, and
      test-based confidence interval around the point estimate.

      AR= Re-Rn             CI   = AR  (1±1^5)
                        48

-------
        •  calculate measure of correlation
                                   2
                   2         ,     Y  = Mantel-Haenszel Chi-square
             * = _jL        where *  =     ^   .
                   n

        *  calculate mortality (and morbidity) rates for an
           exposed population sub-groups located at different
           distances from pollution source.  Compare rates in
           each sub-group with each other and with rates in
           non-exposed population.


         •  calculate  mortality (and morbidity)  rates  for exposed
            and non-exposed  populations in  relation to  duration
            of residence in  each  area.   This  will  be done only
            for mortalities  (and  morbidities) occuring  since  1970,
            as  population residence  data is available  only for
            persons alive at the  time of the  1970  census.

     1.   Review the entire body of data and analyses pertinent to
         each hypothesis to  make  a case either for or  against the
         hypothesis.   Review the  strength of  each  case  and present
         documentation.

         Present alternative explanations for hypotheses  not  found
         to be  acceptable.   Make  recommendations  for new  investi-
         gations.
2.  Investigation of Copper Smelting

    Repeat of subtasks 1  (a) through 1  (1)  for copper smelting  and
digestive diseases instead of bituminous coal  mining and respira-
tory/cardiovascular diseases.
3.  Investigation of Blast Furnaces

    a.   Selection of three specific sites from candidate sites

    b.   Hypothesis development:   repeat of subtasks 1  (a) through
        1  (e) for blast furnaces and neoplasm of digestive organs
        instead of bituminous coal  mining and its associated
        diseases.

    c.   Hypothesis test:  repeat of subtasks 1 (f) through 1 (1):

        *  for blast furnaces and neoplasms of digestive organs
        •  using modifications to hypothesis test methods
           suggested by previous investigations


4.  Investigation of Non-Ferrous Wire Drawing

    Repeat subtasks in Task 3 for non-ferrous wire drawing and
neoplasm of the digestive organs.


                              49

-------
      5.   Investigation of Men's Shirts and Nightwear

          Repeat subtasks in Task   for men's shirts and nightwear and
      cardiovascular disease.
      6.  Investigation of Viscose Rayon

          Repeat subtasks in Task 3 for viscose rayon and chronic
      ischemic heart diseases and angina pectoris.
C.    Task Flow and Schedule

      The milestone schedule for the major tasks and study outputs is
presented in Chart A.   There are six major tasks corresponding to the
six industry/disease associations to be investigated.  Each major task
is divided into three consecutive subtask groups:  (i) site selection,
(ii) hypothesis development, and (iii) hypothesis testing.  The purpose
of the site selection task is to review the industry and population
characteristics of the several  candidate locations under consideration
for each investigation and select the three specific sites to be investi-
gated.  The specific sites have already been selected for the Task 1  and
Task 2 investigations; i.e., bituminous coal mining and copper smelting.

      The time duration for each investigation is approximately five
months, consisting of 1/2 month for site selection, 1 1/2 to 2 months
for hypothesis development, and 3 months for hypothesis testing.  The
starting dates for the investigations are staggered in such a way to
allow members of the staff responsible for particular types of activities
to be applied to all investigations.

      All investigations are to be completed by January 1, 1978, at which
time the Draft Final Report is  to be submitted to EPA for review.  The
Final Report is to be published by March 30, 1978.  An Interim Technical
Report is scheduled for delivery on May 15, 1977.  At that time the work
plan will be revised to include modifications which experience will have
shown to be needed or advisable.

      Chart B gives the detailed subtask schedule for Task 1 (Bituminous
Coal Mining) and Task 2 (Copper Smelting).  The subtask schedule for  the
remaining four investigations is identical to copper smelting except  that
the start of each successive investigation is delayed one month from  the
previous one and 'includes 1/2 month for final site selection.

      The schedule for hypothesis development deserves a comment:  During
the first month of an investigation, the industry, disease, and environ-
ment are examined in detail to  develop a basis for hypothesis formulation.
At this point a first attempt is made at assembling the information into
a plausible hypothesis.  This attempt is expected to generate the require-
ment for further information on the disease, the industry, or the environ-
ment.  This data will  then be collected and fed back into the formulation
process.  The first hypothesis  will not be formulated until one month
after the initial attempt, due  to this iterative procedure, even though
the formulation process itself  is only a two or three-day effort once
the data is available.

                                    50

-------
      It is observed that, due to the staggering of start times, staff
members working on a particular kind of activity in bituminous coal can
perform the same type of job for the copper smelting investigation.  Thus,
an industrial  process engineer who characterizes the mining operations
can finish his task in time to characterize copper smelting.

      The task and information flow for the bituminous coal mining inves-
tigation is schematically depicted in Chart C.  The flows for the other
five investigations will be similar,
D.    Staffing and Assignments

      The work outlined in the previous sections will be performed by
six functional teams.  Chart D lists the functional teams and gives their
composition.  Each team has a team leader, as shown, who is responsible
for assignments and scheduling of the team members to ensure that all
assigned tasks are performed as required.  The members of each team are
of two classifications; core personnel and consultative personnel.  The
core personnel are the workers, so to speak, who will devote a substantial
amount of their time to the project, i.e., near full time.   The consul-
tants will provide expertise that is needed on an intermittent basis -
either to help solve problems of the moment or to contribute to scheduled,
short-duration efforts such as hypothesis formulation.

      All subtasks are to be performed by these functional  teams.  Chart
E gives the subtask responsibilities, showing the man-months each team
is allowed for each assigned task.  The assigned effort is  presented for
the first task only (i.e., bituminous coal mining investigation).

      There are basically two reasons the subtasks are assigned to teams
rather than to individuals.  The first is that the team approach helps
to bring to bear, on each subtask, expertise that is needed but does not
reside in one individual.  Both the core personnel and the  consultants
are aware of their overall responsibilities and, consequently, are ready
and willing to contribute when required.  The second reason is that the
six investigations are heavily overlapping and require similar efforts
to be performed in close proximity to each other.  The functional team
approach is the only realistic way to do this, wherein the  team leader
makes and schedules assignments depending upon up-to-date information
on progress and requirements.

      Chart F gives the man-months of effort planned for each individual
assigned to the project.  The effort is broken down into the various
subtasks involved in an investigation.  The man-months shown are the
cumulative effort of the specified subtasks for all six investigations.


E.    Project Organization

      The project organization is depicted in Chart G.  John Morton  is


                                    51

-------
the Project Manager, Willard Perry is his Deputy and responsible for
day-to-day technical direction and operations.  The Functional Team
Leaders, as previously described, are shown.
                                   52

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CHART A:   PROJECT MILESTONE SCHEDULE
TASKS and MILESTONES

1. BITUMINOUS COAL
2. COPPER SMELTING
3. BLAST FURNACES
4. NONFERROUS WIRE DRAWING


5. MEN'S SHIRTS & NIGHTWEAR

6. VISCOSE RAYON
MONTHLY LETTER REPORTS
INTERIM TECHNICAL SUMMARY REPORT
DRAFT FINAL REPORT
FINAL REPORT

M









A




A









A




M
mis

n






A
A




fl
i

M





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IP
&
—






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1 9
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^




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9 7
F













8
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A
                                 CODE:




                                 {%%%%  Site Selection




                                 [   J  Hypothesis Development




                                       Hypothesis Testing
                53

-------
                                                          CHART B:  SUBTASK SCHEDULE  FOR TASKS  1 & 2
en

TASK 1. BITUMINOUS COAL
Characterize Mining Operation
Characterize Emissions & Effluents
Research Disease Etiology
Identify Plausible Pathways
Formulate Causal Hypotheses
Pollutant Verification
Determine Exposed & Non-Exposed Areas
Acquire Demographic Data & Match Study Areas
Determine Location of Morbidities
Determine Location of Mortalities
Analyze Data
Interpret & Document Results
TASK 2. COPPER SMELTING
Characterize Smelting Operation
Characterize Emissions & Effluents
Research Disease Etiology
Identify Plausible Pathways
Formulate Causal Hypotheses
Pollutant Verification
Determine Exposed & Non-Exposed Areas
Acquire Demographic Data & Match Study Areas
Determine Location of Morbidities
Determine Location of Mortalities
Analyze Data
Interpret & Document Results
March













-

-


April



4-












H-

-
-
•»
••
IM«

"
May
UUm
mmm
mmm


-
—














-
am
mm*
ma


June

-
OH
mm
mm


— •



•••



-




-




July















August













-------
                           Industry/
                           Disease
                           ssociatio
                              Formulate Causal Hypotheses
Determine  Exposed
 and Non-Exposed

      Areas
                                Determine Location and
                            Duration of Residence for Cases
    Analyze Data for Effect,  Confounding, Epidemiology,  Dose-Response, and Clustering
                                    Interpretation,
                                    Documentation,
                                 and Recommendations
                            CHART  C:    TASK FLOW
                                         55

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                        CHART D:  FUNCTIONAL TEAMS
      DIVISION
CORE STAFF   CONSULTATIVE STAFF
Industrial Processes & Pollutants
K. Schoultz*
C. Bailey
R. Shukla
J. Bochinski
D. Cubit
J. Evans
Etiology Research
M. Mattson*
R. Goldsmith
R. Thomas
S. Pi rages
H. Sassoon
Site Selection & Pathway Determination
B. Berney*
J. Morton
W. Perry
A. Rausch
Hypothesis Formulation
R. Thomas*
R. Goldsmith
A. Hayward
M. Mattson
J. Morton
J. Bochinski
C. Lynch
Data Collection & Handling
C. Bailey*
M. Mattson
Research Assistant
Research Assistant
Epidemiologic Analysis
* = Team Leader
R. Goldsmith*
W. Perry  ^
M. Rowley
R. Thomas
C.  Lynch
                                  56

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 CHART E:  FUNCTIONAL TEAM RESPONSIBILITY & WORKLOAD

                      (Man-Months)
Industrial                  Site Selection              Data
Processes      Etiology     & Pathway      Hypotheses   Collection
Epidemologic  TOTAL BY
              SUBTASK
SUB-TASK
Site Selection
Characterize Industry Operation
Characterize Emissions & Effluents
Research Disease Etiology
Identify Plausible Pathways
Formulate Causal Hypotheses
Pollutant Verification
Determine Exposed & Non-Exposed Areas
Acquire Demographic Data & Match Study Areas
Determine Location of Morbidities
Determine Location of Mortalities
Analyze Data
Interpret & Document Results
TOTAL BY FUNCTIONAL TEAM
Bit.
Coal

2
1 1/2



1/2






4
Total
Proj.

8
9



3






20
Bit.
Coal



1









1
Total
Proj.



4









4
Bit.
Coal
-



2


2





4
Total
Proj .
2



6


8





16
Bit.
Coal





1







1
Total
Proj.





4







4 I
Bit.
Coal









3
2


5
Total
Proj.









10
8


18
Bit.
Coal








1


2
2
5
Total
Proj.








4


10
7
21
Bit.
Coal
0
2
1 1/2
1
2
1
1/2
2
1
3
2
2
2
20
Total
Proj.
2
a
9
4
6
4 '
3
8
4
10
8
10
7
83

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CHART F:   PERSONNEL WORK LOADING (Man-Months)

C. Bailey
B. Berney
J. Bochinski
D. Cubit
J. Evans
R. Goldsmith
A. Hayward
C. Lynch
M. Mattson
J. Morton
W. Perry
S. Pirages
A. Rausch
R. Rowley
H. Sassoon
R. Shukla
K. Schoultz
R. Thomas
Research Assistant
Research Assistant
TOTALS
Percent
of Effort
75%
70%
5%
10%
5%
80%
5%
10%
70%
45%
60%
5%
5%
30%
5%
50%
50%
25%
40%
40%

E
o
0
0)
CD
O>
•i—
IS)

2


















2
Characterize
Industry Operation
2 1/2

1/2
1/2
1/2










2
2



8
Characterize
Emissions & Effluents
3 1/2


1/2











3
2



9
Research Disease
Etiology





1/2


2 1/2


1/2


1/2





4
0)
JD
in
to
Q-
•r- tO
E -E
CD 4->
"O tO
>— i Q-

2







2
1 1/2

1/2







6
to
13
in
to
O
10
0) T-
4-> m
to  4-J
tO O
3 C
O O)
D- >















1
2



3
Determine Exposed &
Non-Exposed Areas

5







3










8
o
Q- r!
<~ IS)
CD
O -E
E 0
OJ 4->
Q ro
0) *~
S- c>3
•r- in
13 rO rd
CT4-> O)
O n3 S-





2




1


1






4
Determine Location
of Morbidities
2







3









2 1/2
2 1/2
10
Determine Location
of Mortalities
1 1/2







2 1/2









2
2
8
(O
0)
M
1o
<=c





4

1/2


3


2



1/2


10
Interpret &
Document Results





3

1/2


2


1



1/2


7
TOTAL
MAN-MONTHS
FOR ENTIRE
PROJECT
9 1/2
9
1/2
1
1/2
10
1/2
1
9
5
7 1/2
1/2
1/2
4
1/2
6
6
3
4 1/2
4 1/2
83

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                                                                 PROGRAM MANAGER

                                                                    J.  Morton
                                                                     DEPUTY
                                                                 PROGRAM MANAGER
                                                                    W. Perry
tn
              INDUSTRIAL
              PROCESSES &
              POLLUTANTS

              K. Schoultz
 ETIOLOGY
 RESEARCH

M. Mattson
SITE SELECTION
  & PATHWAY
   ANALYSIS
  0. Berney
HYPOTHESIS
FORMULATION

 R. Thomas
   DATA
COLLECTION
& HANDLING

 C. Bailey
EPIDEMIOLOGIC
  ANALYSIS

R. Goldsmith
                                                    CHART  G:   PROJECT ORGANIZATION

-------