Final Report

Work Assignment No. B-11/22 (SRA 557-05/14)

Demographic Distribution of 

Sensitive Population Groups

Contract Number 68-C6-0036

U.S. Environmental Protection Agency

Office of Science and Technology

Human and Ecological Effects Division

SRA Project Team: 

Ronald O=Day, M.P.H., Jerry Rench, Ph.D.,

Roger Oen, April Castro

Work Assignment Manager: Joyce Donohue, Ph.D.

GLEC Work Assignment Leader: Greg Smith, Ph.D.

SRA Work Assignment Leader: Ronald O=Day, M.P.H.

February 24, 1998

SRA Technologies, Inc.

8110 Gatehouse Rd

Suite 600, West Tower

Falls Church, VA 22042

TABLE OF CONTENTS
ii

EXECUTIVE SUMMARY .............................................................................................................v

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

2.0 SOURCES OF DATA AND METHOD OF IDENTIFICATION ......................................2

2.1 Data and Literature Search.......................................................................................2

2.2 Sources ....................................................................................................................3

2.2.1 Chronic Disease Subgroup...........................................................................3

2.2.2 Individuals with Compromised Immune Systems.......................................4

2.2.3 Pregnant and Lactating Women...................................................................5

2.2.4 Occupationally At-Risk Subgroup...............................................................6

3.0 SENSITIVE POPULATION DEFINITIONS AND ESTIMATES.....................................7

3.1 Chronic Disease Subgroup.......................................................................................7

3.2 Immunocompromised Individuals.........................................................................10

3.3 Pregnant & Lactating Women ...............................................................................11

3.4 Occupationally At-Risk Groups.............................................................................12

3.4.1 Estimates of Sensitive Occupational Populations......................................12

3.4.2 Workers Experiencing Biological Agent Exposures .................................12

3.4.3 Workers Experiencing Chemical Agent Exposures...................................17

3.5 Demographic Distribution of Sensitive Population Groups ..................................25

4.0 DATA LIMITATIONS......................................................................................................27

4.1 Chronic Disease Subgroup ....................................................................................27

4.2 Immunocompromised Individuals.........................................................................28

4.3 Pregnant and Lactating Women.............................................................................29

4.4 Occupationally At-Risk Groups.............................................................................29

5.0 QUALITY CONTROL (QC).............................................................................................29

6.0 SUMMARY AND CONCLUSIONS ................................................................................30

7.0 REFERENCES ..................................................................................................................31

EXHIBITS

Exhibit 1. Disease Categories and ICD-9 CM Codes.....................................................................8

Exhibit 2. NHIS Pre-Defined Race and Ethnicity Categories Along with Those Categories 

Developed for this Project ..........................................................................................10

Exhibit 3. Microbial Pathogens Found in Drinking Water ..........................................................13

TABLE OF CONTENTS (continued)
iii

Exhibit 4. National Estimates of Workers Potentially Exposed to Biological Disease Agents: 

National Occupational Exposure Survey, 1981-1983 .................................................14

Exhibit 5. Biological Agents, Their Target Organs and Occupational Settings ..........................15

Exhibit 6. Disinfectants and Disinfectant By-Products Used to Identify Sensitive Occupational 

Groups .........................................................................................................................19

Exhibit 7. DBP and Target Organs in Subchronic, Chronic, and Carcinogenicity Assays as 

Reported in 97-Annual HEAST ..................................................................................20

Exhibit 8. Chemical Agents, Their Target Organs, and Occupational Settings ..........................21

Exhibit 9. National Estimates of Workers Potentially Exposed to Disinfectants and DBPs: 

National Occupational Exposure Survey, 1981-1983 .................................................24

Exhibit 10. Total Estimates for Each Population Subgroup .........................................................26

ATTACHMENTS

Attachment A1 Diabetes

Attachment A2 Osteoporosis

Attachment A3 Anemia

Attachment A4 Liver Impairments

Attachment A5 Cardiovascular Disease

Attachment A6 Hypertension

Attachment A7 Renal Disorders

Attachment A8 Alcoholism

Attachment A9 Gastric Hyperacidity

Attachment A10 Thyroid Disorders

Attachment A11 Ulcers

Attachment B1 Acquired Immunodeficiency Syndrome (AIDS)

Attachment B2 Persons Under Treatment for Cancer

Attachment B3 Organ Transplant Recipients

Attachment B4 Immunological Hypersensitivity

Attachment C1 Pregnant Women

Attachment C2 Lactating Women

Attachment D1 Occupationally At-Risk to Biological Agents

TABLE OF CONTENTS (continued)
iv

Attachment D2 Occupationally At-Risk to Chemical Agents

Attachment E Detailed List of ICD-9 Codes from the National Health Interview Survey

Attachment F List of Types of Organ Transplants Used to Develop Estimates of 

Organ Transplant Recipients

Attachment G Statistical Analysis Software (SAS) Programs
v

EXECUTIVE SUMMARY

The U.S. Environmental Protection Agency=s (EPA) Office of Science and Technology is 

considering health impacts that might occur as a result of nationwide changes in drinking water 

regulations. It is believed that persons suffering from certain diseases and/or conditions may be 

more sensitive to the effects from chemicals or microbes present in drinking water than the 

general population. The Agency is considering four major subgroups of people who may be 

sensitive; the chronically ill (including persons with diabetes, osteoporosis, anemia, liver 

impairments, cardiovascular disease, hypertension, renal disorders, alcoholism, gastric 

hyperacidity, thyroid disorders, or ulcers), the immunocompromised (including persons with 

AIDS, persons under treatment for cancer, organ transplant recipients, or the immunologically 

hypersensitive), pregnant and lactating women, and the occupationally at-risk. 

Our objective was to provide EPA with estimates of the number of persons that belong to each of 

the diseases/conditions of interest stratified by age, race, ethnicity, gender, and geographical area 

where available. Following an exhaustive search for relevant data, several national health 

surveys were used to develop estimates of prevalence including the 1994 National Health 

Interview Survey (NHIS), the 1994 National Hospital Discharge Survey (NHDS), and the 1995 

Behavioral Risk Factor Surveillance System (BRFSS). Developing a definition of disease using 

these health surveys was fairly straightforward. Estimates of prevalence were developed and 

compared to existing literature, the results of which reassured us our data are relatively accurate. 

Developing a definition for Aoccupationally at-risk@ groups was more challenging and could be 

considered more subjective in nature. The report includes a description of the rationale used to 

define each of the subgroups of interest. 

** Errata: During an External Review of this report, it was determined that an error was made in 

computing the prevalence data on Acquired Immunodeficiency Syndrome (AIDS). The data in 

the report were not corrected. (EPA, 1999). 
1

1.0 INTRODUCTION

Scientists from the Centers for Disease Control and Prevention (CDC) unofficially have 

estimated that contaminated tap water in the U.S. causes sickness for more than 900,000 people 

each year and results in approximately 900 related deaths (NRDC, 1997). Experts with EPA and 

academic scientists say actual numbers may be substantially higher; they estimate that 7.1 

million waterborne disease cases each year are caused by contaminated tap water. Recent 

studies by academic and government scientists show that chemical contamination of tap water 

also contributes substantially to cancer and other illness rates in the U.S. (NRDC, 1997).

Waterborne pathogens continue to be a source of infectious disease despite the regulatory 

measures that have been instituted to ensure the microbiological safety of drinking water. In 

1993-94, 17 states reported a total of 30 waterborne disease outbreaks which caused an estimated 

405,000 persons to become ill. Twenty-two (73.3%) of the outbreaks were known or suspected 

to be associated with infectious agents (Kramer et al., 1996).

On August 6, 1996, President Clinton signed into law the Safe Drinking Water Act 

(SDWA) Amendments, significantly bolstering the ability of communities to upgrade antiquated 

drinking water filtration and purification systems. One of the 1996 amendments to the SDWA 

charges EPA to provide increased consideration to sensitive populations while performing risk 

assessments. Specifically, EPA is required to conduct a continuing program of studies to 

identify groups within the general population that may be at greater risk than the general 

population for adverse health effects from exposure to contaminants in drinking water. These 

contaminants include biological and chemical agents. 

In order for EPA to provide consideration of these at-risk populations, the Agency 

requires a better understanding of the number of individuals falling into four subgroups: 

individuals suffering from chronic disease, individuals with compromised immune systems, 

pregnant and lactating women, and at-risk occupational groups. The estimates of prevalence 

provided in this report are stratified with respect to age, race, gender, ethnicity, and geographical 

region, when available. The definition for U.S. geographical areas was defined in accordance 

with EPA guidance and are also the same as those used by the U.S. Department of Commerce for 

the 1990 Census of Population (Bureau of the Census, 1991). The four regions are as follows:

Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New 

York, Pennsylvania, Rhode Island, and Vermont. 
2

Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, 

North Dakota, Ohio, South Dakota, and Wisconsin. 

South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky,

Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, 

Tennessee, Texas, Virginia, and West Virginia.

West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New 

Mexico, Oregon, Utah, Washington, and Wyoming. 

Data were obtained from a variety of sources, several of which were employed in 

developing comparable demographic analyses in peer reviewed publications. Demographic data 

on infants, children, and the elderly who are sensitive because of age, are being developed for 

EPA through a separate work assignment. 

2.0 SOURCES OF DATA AND METHOD OF IDENTIFICATION

2.1 Data and Literature Search

Determining the Anumber of persons@ who belong to the four major subgroups of interest 

and their diseases/condition categories, involved the implementation of several key tasks. First 

and foremost, a literature/data search strategy was developed to determine how a search for 

relevant data would take place. The data/literature search strategy was submitted to EPA in 

accordance with Task 1 of the work plan and approved. 

A literature search was conducted following approval of the strategy. The deliverable for 

Tasks 2 and 3 of this work assignment provided a detailed description of the results of our search 

for relevant data sources. At that time, there were two primary sources: (i) data available from 

sources such as peer-reviewed literature or sources accessible through health-related sites on the 

internet, and (ii) data available from a health survey entitled the National Hospital Discharge 

Survey (NHDS), available on Compact Disk-Read Only Memory (CD-ROM) from the National 

Center for Health Statistics (NCHS). However, further research led to the discovery of 

numerous other health surveys, also conducted by the NCHS and available on CD-ROM. A

detailed description of the surveys and the data provided by each one are found below in Section 

2.2. Our search also included telephoning federal agencies and associations for their input 

regarding our objective to obtain/develop national estimates. All of our resources recommended 
3

using the NCHS. We were told numerous times by health associations and agency 

representatives that the origin of their data was from health surveys conducted by the NCHS.

2.2 Sources 

Based on a search for sources of relevant data, SRA obtained several health surveys that 

were postulated to include the information needed for analysis. Much of the hardcopy data 

discovered through the data search was in SRA=s library. Several of the CD-ROMs containing 

health surveys of interest were also in-house. Those CD-ROM=s that were not readily available 

were obtained from either the Government Printing Office (GPO) or the National Technical 

Information Service (NTIS). Listed below are brief descriptions of the data used for each of the 

sensitive subgroups of interest.

2.2.1 Chronic Disease Subgroup

Estimates for persons with diabetes, anemia, liver impairments, cardiovascular disease, 

hypertension, renal disorders, gastric hyperacidity, thyroid disorders, and ulcers were 

developed independently using the 1994 National Health Interview Survey (NHIS) (NCHS, 

1997a). The NHIS annually collects health-related information on the civilian, 

noninstitutionalized population residing in the U.S. Data collected include estimates of acute 

health conditions, episodes of injuries, restricted activity, limitation of activity due to chronic 

conditions, prevalence of selected chronic conditions, respondent-assessed health status, and the 

use of medical services including physician contacts and short-stay hospitalizations. Field 

operations for the survey are conducted by the Bureau of the Census under specifications 

established by NCHS. The Bureau of the Census participates in the survey planning, selects the 

sample, and conducts the interviews. Each year, the NCHS produces a report which provides 

current estimates from the survey. The 1994 NHIS, which is the most recent survey that is 

available to the public, was conducted with a sample composed of 45,705 households containing 

116,179 persons. 

Estimates of alcoholism in the U.S. were derived from the 1995 Behavioral Risk Factor 

Surveillance System (BRFSS) (CDC, 1995). BRFSS contains 12 years of data originating in 

1984, collected by health departments in the states and the District of Columbia. The system is 

administered and supported by CDC=s National Center for Chronic Disease Prevention and 
4

Health Promotion (NCCDPHP). BRFSS is an ongoing data collection program designed to 

measure behavioral risk factors in the U.S. adult, noninstitutionalized, civilian population. The 

objective of the BRFSS is to collect uniform, state-specific data on preventive health practices 

and risk behaviors that are linked to chronic diseases, injuries, and preventable infectious 

diseases. Data are collected from a random sample of adults (one per household) through a 

telephone survey and include information regarding safety-belt use, tobacco and alcohol use, 

physical activity, high-fat and low fiber diet, and use of cancer screening services, among others. 

For this project we are using what the BRFSS refers to as chronic drinking as an index for 

alcoholism. The BRFSS= definition for chronic drinkers is presented later in this report (see 

Section 3.1). A modification during the survey on questions about alcohol use, specifically with 

respect to chronic drinking, resulted in data that were not comparable. Thus, in this report, the 

data from California were excluded for chronic drinking. Also, the District of Columbia did not 

participate in the 1995 BRFSS and as a result, data for the District of Columbia are excluded 

from the estimates provided later in this report.

Estimates of the number of persons with osteoporosis were derived from the third 

National Health and Nutrition Examination Survey (NHANES III) (NCHS, 1997b). Data 

collection for this survey was carried out between October, 1988 and September, 1994. The 

NHANES III sample represents the total civilian, noninstitutionalized population, 2 months of 

age or older, in the 50 states of the U.S. The total sample size includes 39,695 individuals, all of 

whom were interviewed to obtain data regarding physical conditions, health services usage, 

dental care, tobacco use, and vitamin, mineral and medicine use. A subset of that sample 

included 30,818 individuals who were given a physical examination at a mobile examination 

unit. 

2.2.2 Individuals with Compromised Immune Systems

Data obtained from previously published material were used to provide estimates of the 

numbers of persons currently afflicted with acquired immunodeficiency syndrome (AIDS). The

AIDS data were obtained from a 1997 HIV/AIDS Surveillance Report developed by the CDC 

(CDC, 1997). All 50 states, the District of Columbia, U.S. dependencies and possessions, and 

independent nations in free association with the United States report AIDS cases to CDC using a 

uniform surveillance case definition and case report form. Data presented in the CDC report are 
5

provisional. However, each issue of the report includes information received by CDC through 

the last day of the reporting period. AIDS data are tabulated by date of report to CDC. Data for 

U.S. dependencies and possessions and for associated independent nations are included in the 

totals.

Estimates of the number of persons currently under the treatment for cancer were 

developed using the 1992 National Health Interview Survey (NCHS, 1995). Characteristics of 

the data are similar to those described above for the 1994 NHIS. The 1992 NHIS was conducted 

with a sample composed of 49,401 households containing 128,412 persons. In addition, the 

1992 NHIS included several special supplements including questions related to cancer 

epidemiology and control. Estimates of the number of organ transplant recipients were 

derived from the 1994 National Hospital Discharge Survey (NHDS) (NCHS, 1997c). The 

NCHS annually collects medical and demographic information from a sample of discharge 

records selected from a national sample of non-federal, short-stay ( 30 days) hospitals. The 

data serve as a basis for calculating statistics on inpatient hospital utilization. The 1994 sample 

consisted of 525 hospitals, 478 of which responded to the survey. Medical record data included 

age, sex, race, marital status, discharge status, admission and discharge dates, and length of stay

for discharged patients. Diagnostic data include up to seven diagnoses per patient and a 

maximum of four codes for surgical and nonsurgical procedures performed. 

Estimates of persons with immunological hypersensitivities were developed using the 

1994 NHIS described above in Section 2.2.1.

2.2.3 Pregnant and Lactating Women

Estimates of the number of pregnant women in the U.S. were obtained from the 1996 

Statistical Abstract of the U.S. (Bureau of the Census, 1996). Published since 1878 by the 

Bureau of the Census, the Statistical Abstract of the United States presents statistics on the 

social, political, and economic organization of the U.S. 

Information for lactating women was obtained from the Fertility, Family Planning, and 

Women=s Health: New Data From the 1995 National Survey of Family Growth (NSFG) 

published by the CDC (Abma et al., 1997). The report presents the first results from the 1995 

NSFG. The NSFG is a multipurpose study based on personal interviews with a national sample 
6

of women 15-44 years of age in the civilian, noninstitutionalized population of the Unites States. 

Some of the topics covered in the report include breast-feeding, maternity leave, and child care. 

2.2.4 Occupationally At-Risk Subgroup

Several major sources of data were used to address the occupationally at-risk subgroup. 

Listed below is a brief description of the sources that were used to establish a link between the 

biological and chemical agents of interest, potential occupational exposures and numbers of 

persons employed in those occupations. 

 Physical and Biological Hazards in the Workplace (Wald and Stave, 1994). This 

textbook provided a source from which specific biological agents, such as 

Cryptosporidium, were linked to occupational settings where workers are potentially

at a higher risk of exposure. 

 A Practical Approach to Environmental Medicine, 1994 (McCunney, 1994). This 

textbook served as a source from which specific chemical agents of interest could be 

linked to occupational settings where workers are potentially at an increased risk of 

exposure. 

 Control of Communicable Diseases in Man (Benenson, 1990). This book was written 

to provide an accurate, informative text for public health workers and others who are 

concerned with the control of communicable diseases. 

 1991 National Occupational Exposure Survey (NIOSH, 1991). Conducted by the 

National Institute for Occupational Safety and Health (NIOSH), the NOES was a 

nationwide observational survey conducted in a sample of nearly 5,000 

establishments from 1981-1983. The goal of the NOES was to compile data on the 

types of potential exposure agents found at the workplace, and the kinds of safety and 

health programs which had been implemented at the plant level. The NOES provided 

national estimates of the number of workers exposed to specific chemical and 

biological agents in the workplace. 

 1996 Statistical Abstract of the U.S. (Bureau of Census, 1996). This source cited 

statistics developed by the Bureau of Labor Statistics which were used to develop 

estimates of persons employed in specific job categories. A description of this source 

is provided in Section 2.2.3 above. 

 1997 Health Effects Assessment Summary Tables (HEAST) (U.S. EPA, 1997). The 

HEAST is a comprehensive listing consisting of risk assessment information relative 

to oral and inhalation routes of exposure for chemicals of interest to Superfund, the 

Resource Conservation and Recovery Act (RCRA), and the EPA in general. Material 

in HEAST are presented in a series of tables that contain subchronic and chronic 
7

toxicity, and carcinogenicity information. This information was used in the 

development of estimates of workers exposed to chemical agents.

3.0 SENSITIVE POPULATION DEFINITIONS AND ESTIMATES

This section provides the rationale for developing definitions for each disease/condition 

of interest, and estimates of the prevalence for each of the subgroups under consideration. 

Conditions belonging to three of the four major subgroups (chronic disease, 

immunocompromised, and pregnant and lactating women) were defined using definitions and 

categories provided by the source from which they came and were considered satisfactory for the 

purposes of this study. The fourth subgroup (occupationally at-risk), and perhaps the most 

difficult to characterize, was defined using a variety of resources, the methods for which are 

described below. A more detailed description of the prevalence estimates, i.e., estimates 

stratified by age, race, gender, ethnicity, and geographic region, are provided in Attachments A1 

to A11, B1 to B4, C1 to C2, and D1 to D2. 

3.1 Chronic Disease Subgroup

Estimates of disease prevalence were developed for persons with diabetes, anemia, liver 

impairment, cardiovascular disease, hypertension, renal disorders, gastric hyperacidity, thyroid 

disorders, ulcers, and immunologic hypersensitivities from data provided on the 1994 NHIS. 

These estimates of prevalence are provided in Attachments A1 to A11. 

The data provided by this survey should be regarded as Apoint prevalence@ estimates 

because they represent the number of persons who indicated that at a particular point in time 

(i.e., time of survey) they had a particular condition. The estimate therefore includes old and 

new cases of disease. The data for this survey were obtained from a CD-ROM and contained a 

pre-defined list of disease categories of chronic conditions and impairments. These categories 

are used by the NCHS to produce prevalence estimates of selected chronic conditions and were 

considered to be suitable for this project. Exhibit 1 lists each of the chronic conditions for which 

estimates were developed using the NHIS along with the International Classification of Disease, 

9th Revision, Clinical Modifications (ICD-9-CM) code captured by the NHIS disease category. 

A more detailed illustration of the ICD-9-CM codes captured by the NHIS category is provided 

in Attachment E. In addition to the pre-defined list of disease categories, we used the 

definitions developed for the NHIS for race and ethnicity which corresponded appropriately to 
8

the race and ethnicity categories required by EPA for this report. Exhibit 2 lists the NHIS 

categories for race and ethnicity and the groupings developed for this project.

Exhibit 1. Diseases Categories and ICD-9-CM Codes

Work Plan Disease Category ICD-9-CM Disease 

Category

ICD-9-CM Codes 

Included in 

Corresponding 

NHIS Category

Diabetes Diabetes Mellitus 250.0-9

Anemia Anemia 280.0-1, 8-9, 281.0-4, 8-

9, 282.0-9, 283.0-2, 9, 

284.0, 8-9, 285.0-1, 8-9

Liver Impairment Liver Diseases 

including Cirrhosis

571.0-6, 8-9, 572.0-4, 8, 

573.0, 3-9 

Cardiovascular Disease Ischemic Heart 

Disease

413.0-1, 9, 414.0-1, 8-9 

(NHIS includes 410.0-9, 

411.0-1, 8, 412 and 429.6 

in 414)

Heart Rhythm 

Disorders:

Tachycardia or Rapid 

Heart,

Heart Murmurs,

Other and 

Unspecified Heart 

Rhythm Disorders

427.0-3, 785.0

785.2

427.0, 4-6, 8-9, 785.1

Congenital Heart 

Disease

745.0-9, 746.0-7

Other Selected 

Diseases of the Heart 

(excluding 

Hypertension)

415.0-1, 416.0-1, 8-9, 

417.0-1, 8-9, 420.0, 9, 

421.0, 9, 422.0, 9, 423.0-

2, 8-9, 424.0-3, 9, 425.0-

5, 9, 426.0-9, 428.0-1, 9, 

429.0-5, 8-9

Hypertension High Blood Pressure 401.0-1, 9, 402.0-1, 9, 

403.0-1, 9, 404.0-1, 9, 

405.0-1, 9

Work Plan Disease Category ICD-9-CM Disease 

Category

ICD-9-CM Codes 

Included in 

Corresponding 

NHIS Category

Renal Disorders Kidney Infections 590.0-9
9

Other Kidney 

Trouble, NEC

581.0-3, 8-9, 582.0-2, 4, 

8-9, 583.0-2, 4, 6-9, 

593.0-9

Gastric Hyperacidity Indigestion 

(excluding Ulcers)

536.8

Thyroid Disorders Goiter 240.0, 9, 241.0-1, 9, 

242.0-3

Other Diseases of the 

Thyroid

242.4, 8-9, 243, 244.0-3, 

8-9, 245.0-4, 8-9, 246.0-

3, 8-9

Ulcers Gastric Ulcer 531.0-9

Duodenal Ulcer 532.0-9

Peptic Ulcer 533.0-9

Immunological Hypersensitivity Asthma 493.0-2, 9

Hay Fever/Allergic 

Rhinitis Without 

Asthma

477.0, 8-9 (477.7 NHIS 

code)

Estimates of chronic drinking were developed from the BRFSS; the data from this survey 

were available on CD-ROM. This survey defines a chronic drinker as anyone having 2 drinks 

per day on average, i.e., 60 drinks per month on average. We used the BRFSS definition of 

chronic drinking as a surrogate measure for alcoholism. The BRFSS also contained pre-defined 

race and ethnicity categories which were grouped to develop those requested for the project. For 

the BRFSS, participants were questioned regarding their race/ethnicity, i.e., participants were 

asked- AWhat is your race?@ with the following choices AWhite, Black, Asian/Pacific Islander, 

Native American, Other, and Unknown@ and AAre you of Spanish/Hispanic origin?@ with the 

following choices AYes, No, Don=t know/Not sure, and Refused.@ Responses to Asian/Pacific 

Islander were labeled AAsian@ for this project, persons who were unsure were treated as 

AUnknown@ and persons who refused were not included in our analyses. 

Exhibit 2. NHIS Pre-Defined Race and Ethnicity Categories 

Along with Those Categories Developed for this Project
10

NHIS Race and Ethnicity Categories Project Race/Ethnicity Groups

Race Race

White White

Black Black

Indian, Eskimo, Aleut Native American

Chinese, Filipino, Hawaiian, 

Korean, Vietnamese, Asian Indian

Asian

Samoan, Guamanian, Other API, 

Other Race, Multiple Race

Other

Unknown Unknown

Ethnicity Ethnicity

Multiple Hispanic, Puerto Rican, 

Cuban, Mexican-Mexicano, 

Mexican-American, Chicano, Other 

Latin American, Other Spanish, 

Spanish (DK type), Unknown if 

Spanish origin

Hispanic

Not Spanish origin Non-Hispanic

Estimates for osteoporosis were developed from the NHANES III, which was also 

available on CD-ROM. Survey participants were asked if they had ever been told by a doctor 

that they had osteoporosis. With respect to race, NHANES III had three race categories; white, 

black, and other. For ethnicity, we considered AMexican-American@ and AOther Hispanic@ to 

be AHispanic.@

3.2 Immunocompromised Individuals

Aside from persons considered immunologically hypersensitive for whom estimates of 

prevalence were developed from the 1994 NHIS described above, persons with AIDS, organ 

transplant recipients, and persons under the treatment for cancer are considered 

immunocompromised. Estimates of these immunocompromised individuals are provided in 

Attachments B1 to B4. Listed below are the methods used to define each of these other disease 

categories so that estimates of prevalence could be obtained.
11

 AIDS. Estimates of prevalence for AIDS were not provided in any of the NHIS, NHANES 

III, NHDS, or BRFSS surveys. As a result, we used the number of AIDS cases from July, 

1996- June, 1997, taken from the 1997 HIV/AIDS Surveillance Report developed by CDC. 

This report contains AIDS cases reported to the CDC by state and local health departments. 

According to that report, the original definition was modified in 1985 and 1987, and the case 

definition for adults and adolescents was modified again in 1993 (CDC, 1997). A broader 

range of AIDS-indicator diseases and conditions including the use of HIV diagnostic tests 

were incorporated to increase the specificity and sensitivity of the definition. Included in the 

report cited above are those persons known to be infected with human immunodeficiency

virus type 2 (HIV-2). The HIV/AIDS report defined race and ethnicity as follows: AWhite, 

not Hispanic@ which we considered as AWhite@; ABlack, not Hispanic@ which we 

considered as ABlack@; AAsian/Pacific Islander@ which we considered as AAsian@; 

AAmerican Indian/Alaska Native@ which we considered as ANative American@; and 

AHispanic.@

 Organ Transplant Recipients. We used the 1994 NHDS to search for the number of persons 

in 1994 who had an organ transplant listed as a ICD-9-CM hospital procedure code and 

stratified the data according to the variables of interest. A list of the types of organ 

transplants included in our estimates of organ transplant recipients can be found in 

Attachment F. Our analyses only include those organ transplants involving the 

transplantation of an organ from one person to another. The 1994 NHDS pre-defined 

categories for race were as follows: AWhite@; ABlack@; AAmerican Indian/Eskimo@ which 

we considered as ANative American@; AAsian/Pacific Islander@ which we considered as 

AAsian@; AOther@; and ANot Stated@ which we considered as AUnknown@. The 1994 

NHDS did not provide an indicator for ethnicity.

 Cancer Treatment Patients. Estimates of cancer treatment patients are based on results from 

the 1992 NHIS. One of the supplements for that year=s survey included information on 

cancer control and epidemiology. The supplement included procedures performed to treat 

cancer including chemotherapy and radiation, i.e., in each household, a sample adult 

respondent was randomly selected to complete one of two cancer supplements. Randomly

selected individuals were asked to respond to the following question: What are the types of 

treatment for the only or most recent cancer? Options for a response included surgery, 

chemotherapy, and radiation. We used chemotherapy and radiation responses to develop our 

estimates, and excluded the surgery responses, because we did not consider surgery to be a 

treatment which may compromise an individual=s immune system. With respect to race and 

ethnicity, the definitions provided for the 1992 NHIS are the same as those used in the 1994 

NHIS in Exhibit 2 above.

3.3 Pregnant & Lactating Women

Estimates for pregnant women were obtained from Table No. 110 of the 1996 Statistical 

Abstract of the U.S. (Bureau of the Census, 1996) and are provided in Attachments C1 to C2. 

Data are provided for 1991. The Bureau of the Census= definition of pregnant women includes 
12

live births, induced abortions, and fetal losses. The 1996 Statistical Abstract of the U.S. 

contained the following race/ethnicity groupings: ANon-Hispanic, White@ which we considered 

as AWhite@; ANon-Hispanic, Black@ which we considered as ABlack@; and AHispanic.@ 

For estimating the number of lactating women, the 1995 National Survey of Family 

Growth provides percentages of singleton babies (representing births with only one child) born 

in 1990-1993 who were ever breast-fed (Abma et al., 1997). We were, however, unable to 

obtain estimates of the number of women who breast-fed or the number of singleton babies for 

the 1990-1993 time period. In order to provide a surrogate measure of prevalence, we multiplied 

the number of live births for the same time period by the percentages of lactating women 

provided in the Survey of Family Growth. Numbers of live births were obtained from Table No. 

92 of the 1996 Statistical Abstract of the United States (Bureau of Census, 1996). The race 

categories provided in the 1996 Statistical Abstract of the United States are as follows: AWhite@; 

ABlack@; AAmerican Indian@ which we considered as ANative American@; and AAsian or 

Pacific Islander@ which we considered as AAsian.@ There were no ethnic breakdowns provided.

3.4 Occupationally At-Risk Groups

3.4.1 Estimates of Sensitive Occupational Populations

Identifying sensitive occupational groups was one of the most challenging aspects of this 

work assignment. The goal of EPA risk assessments that evaluate changes in water quality 

regulation is to consider the full range of impacts that could occur. Our development of 

estimates of workers who might be affected by changes in water quality regulations focused on 

two categories of exposure--biological and chemical. 

3.4.2 Workers Experiencing Biological Agent Exposures

Development of the Estimation Method. In the case of the biological agents, we 

assumed that the at-risk groups would be those workers that are already potentially at risk of 

infection from the same microbes as those that are known to cause waterborne illnesses in the 

U.S. The premise of this scenario is that occupational activities routinely or occasionally result 

in exposures and that additional exposure to the microbes through drinking water may produce a 

threshold dose that could lead to an infection. An infection resulting from this scenario 

obviously involves a number of low probability events that must occur simultaneously and 
13

assumes that the occupational and drinking water routes of exposure are the same or 

complementary. We have not taken into account in our development of estimates of at-risk 

workers, those individuals who may have special risk factors due to pre-existing conditions, 

since these have been addressed above.

We defined the microbial pathogens that should be considered in identifying sensitive 

occupational populations as those that are known to occur in drinking water supplies and can 

cause waterborne infections and outbreaks, such as gastroenteritis or meningoencephalitis. 

Several resources were used to develop a list of pathogens including an EPA report to Congress 

(U.S. EPA, 1988), the most recent CDC surveillance summary on waterborne disease outbreaks 

(Kramer et al., 1996), and two recent review articles, one on sensitive populations (Gerba et al., 

1996) and the other on waterborne protozoan pathogens (Marshall et al., 1997). Exhibit 3

presents the list of microorganisms that were selected.

Exhibit 3. Microbial Pathogens Found in Drinking Water

Protozoa/Parasites Bacteria Viruses

Acanthamoeba spp. Campylobacter jejuni Astro

Cyclospora cayetanensis Escherichia coli 0157:H7 Coxsackie B

Cryptosporidium parvum Leptospira spp. Echo

Entamoeba histolytica Pseudomonas spp. Hepatitis A

Giardia lamblia Salmonella spp. Hepatitis E

Isospora belli Shigella spp. Norwalk

Microsporidia Staphylococcus spp. Polio

Naegleria fowleri Vibrio cholera Rota

Schistosoma spp. Yersinia spp.

Estimates of the Number of Workers. Using the list in Exhibit 3, information was 

sought on the occupations that potentially have exposures to these microbes. Two approaches 

were considered for estimating the number of workers. The first approach involved a review of 

the results of the National Occupational Exposure Survey. The NOES was an observational 

survey conducted by the National Institute for Occupational Safety and Health (NIOSH), which 

had surveyors visit work sites during 1981 to 1983 (NIOSH, 1991). The survey involved a 

sample of 4,490 businesses employing approximately 1,800,000 workers. The survey examined 

worker exposures to chemical and biological hazards, including waterborne disease agents such 
14

as Giardia, Salmonella, E. coli, and Shigella, and developed national estimates of the number of 

potentially exposed workers. Exhibit 4 presents the NOES estimates for these agents, which 

incidentally, NIOSH considers to be "unpublished provisional data as of July 1, 1990."

We concluded that the NOES data may provide a gross underestimation of the actual 

number of workers potentially at risk of infection and may not be appropriate for assessing the 

impact of any contemplated changes in water quality regulations. We recognized that the NEOS 

was an observational survey in which surveyors noted on the survey instrument only those 

instances in which a worker was actually observed working with an agent. We believe that the 

estimates in Exhibit 4 are likely to be dominated by laboratory or related personnel, because the 

surveyor could clearly document that an agent was being used or was present at the work site. 

Potential exposures occurring among health workers, agricultural workers, day care providers, or 

other groups which are known to be exposed to pathogens would presumably go unnoticed or 

unrecorded in this survey.

Exhibit 4. National Estimates of Workers Potentially Exposed to Biological Disease 

Agents: National Occupational Exposure Survey, 1981-1983

Microorganism Number of Workers

Protozoa/Parasites

 Entamoeba histolytica 1,246

 Giardia lamblia 69

Bacteria

 Campylobacter jejuni 185

 Escherichia coli 8,385

 Leptospira 562

 Pseudomonas 1,197

 Salmonella 2,641

 Shigella 1,941

 Staphylococcus aureus 7,685

 Yersinia 1,423
15

Viruses 

 Polio 33

 Rota 1,000

Other Related Categories

 Animal metabolic waste-cow 12,066

 Animal metabolic waste-sheep 3,765

The second approach, which we used for estimating the number of workers potentially 

exposed to agents causing waterborne illnesses, involved two steps that consisted of first 

identifying the occupational categories with workers at risk and then obtaining estimates of the 

number of workers in those categories. The occupational groups were identified using the text 

entitled Physical and Biological Hazards of the Workplace (Wald and Stave, 1994), which 

specifically addressed a few of the protozoans and viruses and most of the bacteria listed in 

Exhibit 5. Exhibit 5 also presents the occupations that could be linked with the disease agents 

of interest and, as one would expect, agricultural and health care workers represent the broad 

categories with the individuals at risk of infection.

The information provided by Wald and Stave (1994) indicated to us that, with a few 

exceptions, the same categories of workers appear to be at risk regardless of the waterborne 

disease agent being considered. Therefore, we elected to develop a list of non-military 

occupational categories for which estimates of the number of workers could be made using 

summary tables compiled by the U.S. Bureau of Labor Statistics (BLS) (Bureau of the Census, 

1996). The estimates of the number of workers potentially exposed and at risk to infections by

the disease agents listed in Exhibit 5 were classified into four broad categories -- agricultural 

workers, food handlers, health care providers and child care providers. Estimates for each of the 

categories are presented in Attachment D1.

Exhibit 5. Biological Agents, Their Target Organs and Occupational Settings

Agent Target Organ(s) Occupation(s) and/or Occupational Setting(s)

Acanthamoeba spp. Brain, meninges a Occupations associated with swimming or diving 

in fresh water, thermal springs, bodies of water 

warmed by industrial plants, hot tubs, spas or 
16

inadequately maintained swimming pools a

Cryptosporidium parvum GI tract, respiratory tract bFarmers, animal handlers, veterinarians, 

laboratory personnel, health care workers, day 

care workers b

Agent Target Organ(s) Occupation(s) and/or Occupational Setting(s)

Entamoeba histolytica GI tract, skin, eyes a Mental institution personnel, farmers, food 

handlers, personnel of institutions with limited 

sanitary facilities a

Giardia lambia GI tract a Day care workers, personnel of institutions with 

limited sanitary facilities a

Campylobacter jejuni GI tract,

vascular system b

Abattoir workers, butchers, veterinarians, 

farmers, laboratory animal personnel, animal 

handlers, day care and health care personnel b

Escherichia coli GI tract b Day care workers, employees in chronic care 

facilities, jobs requiring travel to less developed 

countries, animal handlers, workers eating in 

institutional cafeterias, laboratory workers b

Leptospira spp. Respiratory system, GI 

tract b

Farmers, esp. dairy farmers, sanitation and 

sewage workers, rodent control workers, zoo 

workers, veterinarians, slaughterhouse and other 

meat workers, fishing industry workers b

Pseudomonas spp. GI tract, respiratory tract b Health care workers, metal workers, workers in 

swine and poultry processing plants b

Salmonella spp. GI tract, respiratory tract, 

CNS b

Occupations with animal contact, food handlers, 

health care workers, laboratory workers, business 

travelers to undeveloped countries b

Shigella spp. GI tract b Military personnel, seafarers, day care, nursery 

personnel, health care personnel, medical 

laboratory workers, workers who handle 

contaminated materials or wastes b

Vibrio cholerae GI tract b Travelers to areas where cholera is endemic and 
17

where exposure to contaminated water and food 

is possible, handlers of shellfish b

Yersinia spp. GI tract b Abattoir workers, butchers, meat handlers, and 

meat packers b

Agent Target Organ(s) Occupation(s) and/or Occupational Setting(s)

Hepatitis A Virus Liver b Occupations associated with foreign travel, day 

care centers, food handlers, institutional, some 

military and hospital settings, primate handling, 

and dentistry b

Norwalk virus GI tract b Health care settings (nursing and military) in 

areas with limited sanitary facilities b

Rotavirus GI tract a Occupations associated with hospital/health care 

and day care settings a

a

 Benenson, 1990

b

 Wald and Stave, 1994

Limitations of this approach include the fact that some of the categories may have 

inflated numbers of workers at risk. For example, the agricultural worker categories are believed 

to include both crop and animal husbandry occupations, and greater infection risks would be 

expected among those individuals who work with livestock. Another disadvantage is the 

absence of some of the categories of interest; these include veterinarians, animal handlers/zoo 

keepers, traveling workers, and others. Also, some of the listed categories may represent only 

crude approximations of those that were identified by Wald and Stave (1994) in Exhibit 5. Age 

data and regional estimates were also not available in the summary tables we used; however, 

with further investigation, some of the weaknesses of this data source might be overcome. 

Advantages of the BLS data include the fact that the estimates are nationally-based, are 

up to date (1995 estimates have been presented), and provide demographic breakouts for race 

and gender. The categories are also believed to be mutually exclusive allowing summations of 

the total number of workers potentially at-risk across several categories.
18

3.4.3 Workers Experiencing Chemical Agent Exposures

Development of the Estimation Method. We have used the proposed disinfectant and 

disinfectant by-products (DBP) rule as a model for identifying workers that are potentially

sensitive from a chemical exposure perspective. Exhibit 6 presents a list of the chemicals that 

we used as an initial working list for this effort and includes key chemicals being considered in 

health analyses of the regulatory development process for disinfectants and DBP.

Potentially sensitive groups were defined as those who might be sensitive by virtue of 

additivity of exposure or additivity of effect. In the case of the former, there are workers 

involved in occupations that are already exposed to disinfectants or DBP through various types 

of occupations and that the exposures occurring through consumption of drinking water adds to 

the exposure occurring in the workplace. There is also another set of workers who are 

potentially impacted by disinfectants and DBP because they are exposed in their workplace to 

other categories of chemicals that have toxic effects on the same target organs as those affected 

by the disinfectants and DBP.

Our goal was to obtain estimates of the number of workers who could be affected by

disinfectants and DBP. We were confronted with two challenges in meeting this goal. The first 

was the development of a list of chemicals (and their associated occupations) that meet the 

criteria of having effect additivity to the disinfectants and DBP. A starting point for identifying 

occupations in which there would be exposure additivity to disinfectants and DBP was 

straightforward, because a list of these substances was available (Exhibit 6). The second 

challenge was identifying reliable estimates of the number of workers in occupations in which 

exposure to these substances can occur.

In order to identify the organ systems of interest in this effort, we identified the affected 

target organs for as many of the chemicals in Exhibit 6 as possible using the Health Effects 

Assessment Summary Tables (HEAST) that are derived from the Integrated Risk Information 

System (IRIS) prepared by EPA's National Center for Environmental Assessment in Cincinnati 

(U.S. EPA, 1997). We used the FY-97 Annual HEAST to identify organ systems that had been 

affected in subchronic or chronic toxicity assays or carcinogenicity assays. This approach 

offered several advantages including the fact that the data source is well-recognized for being 

peer-reviewed. 
19

Another important aspect of the HEAST approach was that the affected organ systems 

are identified in the tables and in the case of the subchronic/chronic toxicity tables, usually only 

one or two systems are noted that are believed to be the most sensitive organ systems, based on 

the available information. Identifying a data source that focused upon the most sensitive target 

organ, rather than all of the organs that can be affected by a full range of doses, was important 

because sources, such as SAX's Dangerous Properties of Industrial Materials (Lewis, 1992) or

the NIOSH/OSHA Pocket Guide to Chemical Hazards (NIOSH/OSHA, 1978), identify many if 

not all of the organ systems that can be affected by the wide range of exposures that can occur in 

the workplace. 

Exhibit 6. Disinfectants and Disinfectant By-Products Used to 

Identify Sensitive Occupational Groups

Chemical Chemical Abstracts Service No.

Bromoacetic acid 79-08-3

Bromodichloromethane 75-27-4

Bromoform 75-25-2

Chloral 75-87-6

Chloramine 127-52-6

Chlorine 7782-50-5

Chlorine dioxide 10049-04-4

Chloroform 67-66-3

Dibromoacetic acid none found

Dibromochloromethane 124-48-1

Dichloroacetic acid 79-43-6

Trichloracetic acid 76-03-9

We recognized that there were weaknesses in the HEAST approach including the fact 

that the data are based on animal testing rather than epidemiologic or occupational medicine 

studies and that not all of the substances of interest in Exhibit 6 were included in the HEAST 

data set. Nevertheless, the HEAST data provided an efficient approach to the problem, given the 
20

resources that were available for this aspect of the project, which was just one of four categories 

for which estimates of sensitive populations were developed.

There were five substances in Exhibit 6 that appeared in the HEAST. These substances 

and the target organs that they were found to affect are presented in Exhibit 7. Also included in 

the exhibit are several additional chemicals that are structurally-related to the DBPs. Information 

on these chemicals and their target organs are provided, because they provide additional insight 

into the possible effects of DBPs in humans. With the exception of the carcinogenicity assays 

for dibromomethane which involved inhalation exposures, all of the other health effects data for 

the listed substances presented in Exhibit 7 represented ingestion routes of exposure. We 

selected the kidney, liver, heart, and gonads (sperm) as representative of the organ systems most 

sensitive to the effects of disinfectants and DBPs.

Exhibit 7. DBP and Target Organs in Subchronic, Chronic, and 

Carcinogenicity Assays as Reported in 97-Annual HEAST

Chemical

Target Organ

Subchronic/Chronic

Toxicity Carcinogenicity

Disinfectant By-Products:

Bromodichloromethane Kidney --

Bromoform Liver Large intestine

Chloral Liver --

Chloroform Liver Liver

Dibromochloromethane Liver --

Related Chemicals:

Chloroacetic acid Heart --

1,2-Dibromoethane Sperm (gonad) Nasal cavity

With the target organs of interest selected above, additional chemicals that are commonly 

found in the workplace were identified that also have similar target organs when exerting 

toxicity. For this screening process, Appendix A of the text entitled A Practical Approach to 
21

Occupational and Environmental Medicine (McCunney, 1994) was used to identify the 

substances. This resource also listed the industries and occupations in which these substances 

are used or manufactured. Exhibit 8 presents the chemicals that were found. This exhibit also 

includes the disinfectants and DBPs from Exhibit 7 that were addressed by McCunney (1994). 

From this exhibit it is apparent that there are a wide variety of chemical production, mining, 

petroleum, and other manufacturing industries where exposures to these substances can 

potentially occur.

Exhibit 8. Chemical Agents, Their Target Organs, and Occupational Settings 

Agent Target Organ Occupational Exposure

Antimony Pulmonary

Gastrointestinal

Skin cardiac

Exposure maximal during mining 

and smelting; used in the 

semiconductor industry, battery 

grids, type castings, bearings and 

cable sheaths, munitions, glass, 

pottery, paints, and lacquers, 

rubber, solder

Cadmium Pulmonary

Renal

Electroplating; solder for 

aluminum; metal alloys; process 

engraving; nickel-cadmium 

batteries

Carbon disulfide CNS

PNS

Renal

Cardiovascular

Skin reproductive

Solvent for lipids, sulfur, halogens, 

rubber, phosphorus, oils, waxes, 

and resins; manufacturing of 

organic chemicals, paints, fuels, 

explosives, viscose rayon

Carbon tetrachloride Hepatic

Renal

CNS

Skin

Solvent for oils, fats, lacquers, 

resins, varnishes, etc.; used as a 

degreasing and cleaning agent

Chlorine Middle respiratory tract Paper and textile bleaching; water 

disinfection; chemical 
22

Agent Target Organ Occupational Exposure

manufacturing; metal fluxing; 

detinning and dezincing iron

Chlorofluorocarbons Cardiac

Pulmonary

CNS

Skin

Aerosol propellants, refrigerants, 

intermediate process product

Chloroform CNS

Liver

Renal

Cardiovascular

Manufacturing of fluorocarbons for 

refrigerants, aerosol propellants, 

plastics, purifying antibiotics, 

solvents, photographic processing, 

and dry cleaning

Chloromethyl Eyes, skin

Pulmonary

Used in the manufacture of ion 

exchange resins, bactericides, 

pesticides, dispersing agents, water 

repellents, and solvents for 

industrial polymerization

Dibromochloropropane CNS

Eye, nose, throat

Reproductive

Pulmonary

Nematocide

Dichlorobenzene Eye and nose, skin

Pulmonary

Liver

Used as a deodorant, disinfectant, 

and insecticide

Dimethylformamide Liver

Skin

CVS

Laboratory and industrial solvent

Dioxane CNS

Renal

Liver

Used as a solvent for a variety of 

materials, including cellulose 

acetate, dyes, fats, greases, resins, 

polyvinyl polymers, varnishes, and 

waxes

Ethylbenzene Eyes and nose, skin

CNS

Liver

Solvent, fuel additive, chemical 

intermediate in the production of 

styrene

Ethylene glycol ethers

Ethylene glycol monoethyl ether 

(cellosolve)

Ethylene glycol monoethyl ether 

acetate (cellosolve acetate)

Methyl- and butyl-substituted 

compounds such as ethylene glycol 

monomethyl ether (methyl 

CNS

Renal

Liver

Hematopoietic

Reproductive

The ethers are used as solvents for 

resins, paints, lacquers, varnishes, 

gum, perfume, dyes, and inks; the 

acetate derivatives are widely used 

solvents and ingredients of 

lacquers, enamels, and adhesives. 

Exposure occurs in dry cleaning, 

plastic, ink, and lacquer 

manufacturing, and textile dying, 
23

Agent Target Organ Occupational Exposure

cellosolve) among other places 

Semiconductor industry

Hexachlorobenzene Skin Used as a fungicide in control of 

smut diseases in seed wheat

Isopropanol Eyes, nose, throat

Skin

CNS

CVS

Renal

Hematologic

Industrial and laboratory chemical

Lead Hematologic

Renal

Gastrointestinal

Neuromuscular

CNS

Reproductive

Storage batteries; manufacturing of 

paint, enamel, ink, glass, rubber, 

ceramics; chemical industry

Mercury (Hg)

 Elemental

 Inorganic

 Organic

Pulmonary

CNS

Pulmonary

Renal

CNS

Skin

Electronic equipment; paint, metal 

and textile production; catalyst in 

chemical manufacturing; 

pharmaceutical production

Agricultural and industrial poisons

Nitrosamines Liver

Pulmonary

Renal

Used in rubber industry; as a 

solvent, organic accelerator, 

retardant, antioxidant; used in 

leather tanning, synthetic cutting 

fluid, and as a meat preservative; 

present in cigarette smoke

Paraquat Skin, nose, eye

Pulmonary

Liver

Gastrointestinal

Herbicide

Perchloroethylene

 (Tetrachloroethylene)

Skin

Liver

CNS

Dry cleaning; chemical 

intermediate, degreaser

Phenol CNS

Skin

Liver

Renal

Cleaning agent, paint, stripper, 

disinfectant, chemical intermediate 

for epoxy resins and drugs

Styrene CNS

Liver

Eyes

Chemical intermediate, solvent 

used in the manufacturing of 
24

Agent Target Organ Occupational Exposure

Skin plastics

1,1,1-Trichloroethane Skin

Liver

CNS

Degreaser, propellant

Trichloroethylene (TCE) CNS

PNS

Skin 

Cardiovascular

Solvent in metal degreasing, dry 

cleaning, food extraction; 

ingredient of paints, adhesives, 

varnishes, inks

Uranium Pulmonary

Immune system

Renal

Processing of uranium ore for 

nuclear fuel

Vinyl chloride Pulmonary

CNS

Liver

Skin

Intermediate in the synthesis of 

polyvinyl chloride resins for plastic 

piping, floor coverings, upholstery, 

appliances, and packaging

Estimates of the Number of Workers. We considered the same data sources for 

estimating the number of "chemically sensitive" workers as were used for estimating the workers 

with exposures to biological disease agents. Initially, we examined the NOES and found that 

many of the disinfectants and DBPs were listed and had been considered in the survey. Exhibit 

9 presents these chemicals and the estimated number of workers; however, the chemicals with 

potentially additive effects to disinfectants and DBPs are not included.

Exhibit 9. National Estimates of Workers Potentially Exposed 

to Disinfectants and DBPs: National Occupational Exposure Survey, 1981-1983

Chemical Number of Workers

Bromoacetic acid n.l.

Bromodichloromethane n.l.

Bromoform 1,473

Chloral hydrate 11,281

Chloramine 562

Chlorine 178,113

Chlorine dioxide 7,889

Chloroform 95,778
25

Dibromoacetic acid n.l.

Dibromochloromethane n.l.

Dichloroacetic acid 1,592

Trichloracetic acid 35,125

n.l. : not listed

While the information in Exhibit 9 is informative, the category estimates are not believed 

to be mutually exclusive, as discussed previously, and do not allow summations of all of the 

potentially exposed workers. Underestimation may be another concern with the NOES data, if a 

surveyor did not observe the chemical being used at the time of the survey or if unsuspected and 

unmeasured exposures were taking place. It was concluded that the NOES data would not be the 

most suitable data source for estimating the number of workers for these reasons. Therefore, we 

chose the BLS data for estimating the number of workers. This approach also provided 

continuity with the estimates developed for workers exposed to biological disease agents. 

Recognizing that not all workers in a category are going to be exposed to the agents of interest, 

we used the list of occupational settings/industries in Exhibit 8 and identified categories of 

workers in the BLS summary in which these exposures are likely to occur. Three broad 

industrial categories were identified: mining, manufacturing of durable goods (e.g., nonferrous 

foundries), and manufacturing of non-durable goods (e.g., organic chemicals). In Attachment 

D2 we provide estimates of the number of workers in these occupational categories.

3.5 Demographic Distribution of Sensitive Population Groups

Estimates of prevalence were developed using the methods described above. Generally, 

when detailed data summaries were available from the data sources, the data were stratified by

variables exactly like those required by the work assignment. Data provided on CD-ROM were 

organized for Statistical Analysis Software (SAS) use by the NCHS (SAS is a widely used 

computer package that provides epidemiologists and biostatisticians with the ability to analyze 

data). Data available on CD-ROM were manipulated using programs written solely for the 

purpose of developing descriptive statistics. In order to analyze the data on CD-ROM using 
26

SAS, the data were first converted into American Standard Code for Information Interchange 

(ASCII) format. The SAS programs developed for this project are available in Attachment G.

When we were not able to obtain information from a national survey on CD-ROM, we 

were forced to use alternative sources and variable definitions. Usually, in these situations we 

were able to provide estimates that closely matched those specified in the work assignment. 

Estimates of the total number of individuals in the categories of interest can be found in Exhibit 

10. Included in Exhibit 10 are estimates of people belonging to each of the subgroups expressed 

as a percentage of the population. Estimates of percent population were developed by dividing 

the estimates of prevalence by the estimates of the U.S. population. The footnotes at the end of 

Exhibit 10 provide the reader with the source of the U.S. population estimates. In most cases, 

the survey used to develop the estimates of prevalence also provided the U.S. population used by

the survey to perform the extrapolations. The estimate for percent of population for chronic 

drinking was obtained from 

a report based on the BRFSS and developed by the CDC. The estimates of percent population 

for persons with AIDS, pregnant women, lactating women, and the occupationally at-risk were 

developed from estimates and projections of the U.S. population provided by the Census Bureau. 

Exhibit 10. Total Estimates for Each Population Subgroup

Disease/Condition

Year(s) 

Covered

Annual

Prevalence Population

Percentage of 

Population

Diabetes 1994 7,765,981 259,633,000a3.0

Osteoporosis 1988-94 3,703,302 251,097,002b1.5

Anemia 1994 4,664,365 259,633,000a1.8

Liver Impairments 1994 594,960 259,633,000a0.2

Cardiovascular Disease 1994 22,279,451 259,633,000a8.6

Hypertension 1994 28,236,261 259,633,000a10.9

Renal Disorders 1994 2,068,952 259,633,000a0.8

Alcoholism (chronic drinking) 1995 5,048,448 not available 2.8c

Gastric Hyperacidity 1994 6,956,917 259,633,000a2.7

Thyroid Disorders 1994 4,508,780 259,633,000a1.7

Ulcers 1994 4,447,035 259,633,000a1.7
27

AIDS 1997 64,966 267,645,000d0.02

Cancer Treatment Patients 1992 1,853,795 248,754,000e0.8

Organ Transplant Recipients 1994 17,095 258,932,000f0.01

Immunological Hypersensitivity 1994 40,707,827 259,633,000a15.7

Pregnant Women 1991 6,272,000 129,187,000g4.9

Lactating Women 1990-93 2,247,635 129,813,000h1.7

Occupationally At-Risk 1995 13,891,000 263,034,000i4.4 (biological) 

0.8 (chemical) 

a NCHS, 1997a. Note on Rates, Table 1.

b NCHS, 1997b. 

c

Powell-Griner et al., 1997. Table 4, p8.

d Bureau of the Census, 1996. Table No. 3, p9. Middle series resident population projection for 1997.

e Collins, 1997. Table 45, p63. 

f NCHS, 1997c. Appendix C, Population Files.

g Bureau of the Census, 1996. Table No. 12, p14. Female population in the U.S. for the year 1991. 

h Bureau of the Census, 1996. Table No. 12, p14. Annualized female population in the U.S. for the years 1990-

1993.

i Bureau of the Census, 1996. Table No. 2, p8.

A more detailed demographic characterization of the chronic disease subgroup, the 

immunocompromised individuals subgroup, the pregnant and lactating women subgroup, and the 

occupationally at-risk subgroup are presented in Attachments A1 to A11, B1 to B4, C1 to C2, 

and D1 to D2, respectively. In each of these attachments we restate the source of data and 

include a brief description of the prevalence estimates provided. 

4.0 DATA LIMITATIONS

The estimates provided in Section 3.5 above are subject to limitations that are briefly 

described below. In some cases, the data are limited by the methods used to conduct the health 

surveys themselves, including the population sampled and population size. Several 

diseases/conditions for which a health survey was used to obtain data have unbelievably low 

values, i.e., zero values, for some age groups and race groups. We believe that the zero values 

may be an artifact of the survey and may reflect instances in which the survey had few or no 

responses in an age category and therefore scaled-up estimates for the country could not be 

made. A more in-depth examination of the survey methodology may help resolve this issue. In 

places where an An/a@ exists, the data were not available for that survey. 
28

4.1 Chronic Disease Subgroup

Estimates for persons with diabetes, anemia, liver impairments, cardiovascular disease, 

hypertension, renal disorders, gastric hyperacidity, thyroid disorders, and ulcers were developed 

independently using the 1994 National Health Interview Survey (NCHS, 1997a). Estimates 

developed from this survey pertain only to the resident, civilian, noninstitutionalized population 

of the U.S. living at the time of the interview and are based on a 12-month reference period. The 

sample does not include persons residing in nursing homes, members of the Armed Forces, 

institutionalized persons, or U.S. nationals living abroad. In order to develop estimates on a 

national level, some of the data provided in the chronic disease subgroup categories needed 

extrapolation using the application of weighting factors that were developed by the survey 

investigators and were dependent upon the design of the survey. The purpose of weighting the 

sample was to permit analysts to produce national estimates that would not have been obtained 

otherwise unless the entire sampling frame had been surveyed. It should be noted that due to the 

form of estimators typically used with data from complex samples, extreme variability in the 

weights may result in reduced reliability of the estimates. 

In addition, information obtained from surveys based on self-reporting and interviewing 

may be less accurate than information based on physical measurements or medical records, 

because respondents may have forgotten the event, may not want to disclose the information, or 

misunderstood the question. The NHIS estimates may not represent a complete measure of any 

given condition because data were not collected for those who became institutionalized or who 

died during the interviewing period. Furthermore, proxy responses were used for family 

members who are mentally or physically incapable of responding for themselves, for family 

members not at home and for children.

An important caveat regarding the chronic disease categories and the other sensitive 

population estimates provided in this report is that the categories are not mutually exclusive. The 

surveys that provided the data used for developing estimates were designed to capture 

information on all health problems being experienced by the interviewed population. Thus, a 

person could be experiencing hypertension and diabetes and be counted in both categories. 

Estimates developed for osteoporosis came from NHANES III and were based on 

participants responses in an interview. These estimates may suffer from limitations similar to 

those described above for the NHIS with respect to self-reported illnesses.
29

Estimates developed for alcoholism came from BRFSS. This survey was based on 

telephone interviews which may be cost-efficient, easy to administer and easy to monitor. 

However, telephone interviews also might have higher levels of non-coverage than in-person 

interviews because a small percentage of the U.S. households could not be reached by telephone. 

Data for the State of California were not included in this report due to survey methodology

changes for 1995 and the District of Columbia did not participate in the 1995 BRFSS. The 

BRFSS may also be subject to limitations like those discussed for the NHIS.

4.2 Immunocompromised Individuals

Estimates for AIDS were developed using a report by the CDC (CDC, 1997). This data 

may be limited by changes in the definition of AIDS over time. However, the HIV/AIDS 

surveillance system continually adapts to changes in the diagnosis and clinical management of 

HIV-related diseases. 

Estimates of persons with organ transplants were developed using the NHDS. Results 

from these surveys are subject to nonsampling or measurement errors, which include errors due 

to hospital nonresponse, missing abstracts, information incompletely or inaccurately recorded on 

abstract forms, and processing errors. The estimates for persons considered immunologically 

hypersensitive are subject to the same limitations as those described above for the NHIS. 

Persons under treatment for cancer were obtained from the NHIS 1992 supplement. These 

estimates may also be subject to limitations like those described above for the 1994 NHIS. Also, 

the 1992 NHIS ended the second week in the third quarter of that year because of budgetary

constraints; this may have resulted in an underestimate of persons being treated for cancer. 

4.3 Pregnant and Lactating Women

A surrogate measure for pregnancies was used by the 1996 Statistical Abstract of the U.S. 

(Bureau of the Census, 1996) and includes live births, stillbirths, and abortions. A surrogate 

measure for lactating women was used as well. The number of live births provided by the 1996 

Statistical Abstract of the U.S. (Bureau of the Census, 1996) was multiplied by the percentage of 

lactating women provided by the National Survey of Family Growth (NSFG) (Abma et al., 1997) 

to develop an annual estimate of lactating women.
30

4.4 Occupationally At-Risk Groups

Refer to the methods in Sections 3.4.2 and 3.4.3 above for a description of the data 

limitations.

5.0 QUALITY CONTROL (QC)

Inherent in the development of any project is the requirement to perform a review of the 

data presented. We have conducted a thorough review of the data presented in this report to 

ensure the information we obtained is well represented. 

One of the sources of relevant data discovered early in our search for information 

included a report by Adams and Marano (1995). These authors use the 1994 NHIS to develop 

estimates of prevalence for selected chronic conditions. Although the age groups for which 

Adams and Marano (1995) developed estimates differ from those used for this project, we 

developed estimates for the same age groups used by Adams and Marano (1995) as a source for 

comparison and validation of our methods. The estimates we developed compared favorably 

with estimates developed by Adams and Marano (1995). For example, their estimate for 

hypertension in the U.S. in 1994 of 28,236,000 persons matches the total estimate we provide of 

28,236,261 persons. In addition, estimates published by the Bureau of the Census provided 

additional validation that: (i) an appropriate source for our estimates was used and, (ii) the source 

was correctly abstracted. The Statistical Abstract of the United States (Bureau of Census, 1996) 

estimates that 28,236,000 persons suffered from hypertension nationwide in 1994. They cite the 

report developed by Adams and Marano (1995) as their source of data. 

For most of the conditions under consideration, national estimates from independent 

sources were discovered and used for comparison. However, estimates for the number of 

persons currently under the treatment for cancer and for persons considered occupationally atrisk persons were not discovered. As a result, our estimates for these two groups could not be 

compared with an independent source. 

6.0 SUMMARY AND CONCLUSIONS

Our goal in conducting this project was to develop estimates of the number of persons in 

the U.S. belonging to specific subgroups that may be at increased risk of adverse health impacts 

when substantive changes in water quality occur. Currently EPA is considering changes in the 
31

rules for treating drinking water; adequate treatment and removal of microbial pathogens is an 

important consideration. Previous studies have shown that certain segments of our population 

are at increased risk of morbidity and mortality from microbial food borne and waterborne 

disease (Gerba et al., 1996). Gerba et al. (1996) reviewed existing literature to define those 

groups of individuals who would be at greatest risk of serious illness from enteric organisms. 

Several of the groups that were labeled as Asensitive@ are considered in this report including 

immunocompromised individuals, AIDS patients, and transplant organ patients.

The results of this project are descriptive in nature. Many of the estimates of chronic 

disease categories provided in this report are estimates of prevalence. Compared to incidence 

which measures the probability that otherwise healthy people will develop a disease during a 

specified period of time, prevalence is a measure of the number of people in a population who 

have the disease at a given time. Point prevalence estimates of disease at one point in time are 

provided for many of the disease categories and period prevalence (for pregnant and lactating 

women) estimates were available in other cases.

The estimates of prevalence we provide are consistent with estimates developed by other 

researchers. In situations where numbers were developed previously, we successfully generated 

very similar estimates using the same sources of data. In situations in which we chose an 

alternative source of data (a more recent survey for example), we continued to make 

comparisons with estimates from previous research and developed similar results. For each of 

the subgroups of interest, we provide the rationale used when developing the estimates. 

7.0 REFERENCES

Abma J, Chandra A, Mosher W, Peterson L, Piccinino L. 1997. Fertility, family planning, and 

women=s health: New data from the 1995 National Survey of Family Growth. National Center 

for Health Statistics. Vital Health Stat 23(19). 

Adams, PF, Marano, MA. 1995. Current estimates from the National Health Interview Survey, 

1994. National Center for Health Statistics. Vital Health Stat 10(193).

Benenson, AS. 1990. Control of Communicable Diseases in Man. Fifteenth edition. American 

Public Health Association. 

Bureau of the Census. 1996. Statistical Abstract of the United States: 1996. 116th Edition. 

Washington, DC.
32

Bureau of the Census. 1991. Statistical Abstract of the United States: 1991. The National Data 

Book. Washington, DC.

Centers for Disease Control and Prevention. 1997. HIV/AIDS Surveillance Report,

1997;9(No.1):[5,8-12].

Centers for Disease Control and Prevention. 1995. National Center for Chronic Disease 

Prevention and Health Promotion, Behavioral Surveillance Branch: 1984-1995 Behavioral Risk 

Factor Surveillance System [database on CD-ROM]. CD-ROM Series 1, No. 1. 

Collins, JG. 1997. Prevalence of selected chronic conditions: United States, 1990-1992. 

NCHS. Vital Health Stat 10(194). 

Gerba CP, Rose JB, and Haas CN. 1996. Sensitive populations: who is at the greatest risk? 

Internat J Food Microbiol 30: 113-123.

Kramer MH, Herwaldt BL, et al. 1996. Surveillance for waterborne-disease outbreaks - United 

States, 1993-1994. Morbidity and Mortality Weekly Report 45 (SS-1): 1- 33.

Lewis RJ. 1992. SAX's Dangerous Properties of Industrial Materials. Eighth edition. Van 

Nostrand Reinhold, New York.

Marshall MM, Naumovitz, et al. 1997. Waterborne protozoan pathogens. Clin Microbiol Rev

10: 67-85.

McCunney RJ. 1994. A Practical Approach to Occupational and Environmental Medicine. 

Appendix A. Second Edition. (Appendix A Authors: Frumkin H, McCunney RJ, and Barbanel 

C). American Occupational Medical Association.

National Center for Health Statistics. 1997a. 1994 National Health Interview Survey [database 

on CDROM]. CD-ROM Series 10, No. 9. SETS Version 1.21a. Washington: US Government 

Printing Office.

National Center for Health Statistics. 1997b. 1988-1994 National Health and Nutrition 

Examination Survey [database on CDROM]. CD-ROM Series 11, No. 1. Washington: US 

Government Printing Office.

National Center for Health Statistics. 1997c. 1994 National Hospital Discharge Survey [database 

on CDROM]. CD-ROM Series 13, No. 12. SETS Version 1.22a. Washington: US Government 

Printing Office.

National Center for Health Statistics. 1995. 1992 National Health Interview Survey [database on 

CDROM]. CD-ROM Series 10, No. 6. SETS Version 1.22. Washington: US Government 

Printing Office.

National Institute for Occupational Safety and Health (NIOSH). 1991. National Occupational 

Exposure Survey (1981-83). Unpublished provisional data as of 7/1/90. Cincinnati, OH.
33

National Institute for Occupational Safety and Health/Occupational Safety and Health 

Administration (NIOSH/OSHA). 1978. Pocket Guide to Chemical Hazards. Editors: Mackison 

FW, Stricoff RS, and Partridge LJ. Centers for Disease Control, Atlanta Georgia.

Natural Resources Defense Council. 1997. Safe Drinking Water Act Amendments of 1996, 

internet website: http://www.nrdc.org/bkgrd/dwsdwa96.html, last revised 1.23.97.

Powell-Griner E, Anderson J, Murphy W. State- and sex-specific prevalence of selected 

characteristics-- behavioral risk factor surveillance system, 1994 and 1995. In: CDC 

Surveillance Summaries, August 1, 1997. MMWR 1997; 46(No. SS-3): 1-40.

U.S. Environmental Protection Agency. 1997. Health Effects Assessment Summary Tables. 

EPA/540/R-97/036. National Center for Environmental Assessment, Cincinnati, Ohio.

U.S. Environmental Protection Agency. 1988. Comparative Health Effects of Drinking Water 

Treatment Technologies. EPA 570/9-88-009. Office of Drinking Water, Washington, D.C.

Wald PH, and Stave GM. 1994. Physical and Biological Hazards of the Workplace. Van 

Nostrand Reinhold, New York.

Attachments A1-A11

Chronic Disease Subgroup
34

Attachment A1

Chronic Disease Subgroup

DIABETES

Data Source Description:

Diabetes prevalence data are for the year 1994 and were obtained from the National 

Health Interview Survey (NHIS). Zero values may represent an artifact of the survey and 

may reflect instances in which the survey had few or no responses in an age category and 

therefore scaled-up estimates for the country could not be made.

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<1 0 Female 4,186,574

1-5 14,958 Male 3,579,407

6-10 12,577

11-19 112,860

20-45 1,500,578

46-55 1,396,387

56-64 1,587,147

65+ 3,141,474

Total 7,765,981

Race Prevalence Geographic 

Area Prevalence

Asian 219,770 Northeast 1,573,185

Black 1,405,471 Midwest 1,936,920

Native American 91,780 South 3,021,883

White 5,791,080 West 1,233,993

Unknown 67,576

Other 190,304

Ethnicity Prevalence

Hispanic 742,658

Non-Hispanic 7,023,323
35

Attachment A2

Chronic Disease Subgroup

OSTEOPOROSIS

Data Source Description:

The data provided below were derived from the third National Health and Nutrition 

Examination Survey (NHANES III) conducted between 1988-1994. Data were not 

available (n/a) for Asians, and Native Americans, several of the age categories, and 

geographical areas of the U.S. Zero values may represent an artifact of the survey and 

may reflect instances in which the survey had few or no responses in an age category and 

therefore scaled-up estimates for the country could not be made.

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<1 n/a Female 3,438,546

1-5 n/a Male 264,756

6-10 n/a

11-19 0

20-45 415,580

46-55 471,598

56-64 728,131

65+ 2,087,993

Total 3,703,302

Race Prevalence Geographic 

Area Prevalence

Asian n/a Northeast n/a

Black 131,194 Midwest n/a

Native American n/a South n/a

White 3,527,849 West n/a

Unknown n/a

Other 44,259

Ethnicity Prevalence

Hispanic 125,288

Non-Hispanic 3,578,015
36

Attachment A3

Chronic Disease Subgroup

ANEMIA

Data Source Description:

Prevalence data for anemia are for the year 1994 and were obtained from the National 

Health Interview Survey (NHIS). 

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<1 61,361 Female 3,873,201

1-5 418,626 Male 791,164

6-10 225,226

11-19 300,831

20-45 2,189,400

46-55 495,728

56-64 340,431

65+ 632,762

Total 4,664,365

Race Prevalence Geographic 

Area Prevalence

Asian 38,020 Northeast 1,014,562

Black 1,218,941 Midwest 1,277,277

Native American 97,972 South 1,446,565

White 3,028,825 West 925,962

Unknown 40,694

Other 239,912

Ethnicity Prevalence

Hispanic 653,286

Non-Hispanic 4,011,079
37

Attachment A4

Chronic Disease Subgroup

LIVER IMPAIRMENTS

Data Source Description:

Prevalence data for liver impairments are for the year 1994 and were obtained from the 

National Health Interview Survey (NHIS). Zero values may represent an artifact of the 

survey and may reflect instances in which the survey had few or no responses in an age 

category and therefore scaled-up estimates for the country could not be made.

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<1 0 Female 167,201

1-5 29,879 Male 427,759

6-10 0

11-19 0

20-45 269,239

46-55 67,231

56-64 91,998

65+ 136,613

Total 594,960

Race Prevalence Geographic 

Area Prevalence

Asian 0 Northeast 81,648

Black 95,701 Midwest 77,095

Native American 0 South 241,921

White 499,259 West 194,296

Unknown 0

Other 0

Ethnicity Prevalence

Hispanic 47,742

Non-Hispanic 547,218
38

Attachment A5

Chronic Disease Subgroup

CARDIOVASCULAR DISEASE

Data Source Description:

Cardiovascular disease prevalence data are for the year 1994 and were obtained from the 

National Health Interview Survey (NHIS). 

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<1 85,440 Female 11,260,582

1-5 392,405 Male 11,018,869

6-10 323,084

11-19 703,155

20-45 4,202,730

46-55 2,859,809

56-64 3,633,114

65+ 10,079,714

Total 22,279,451

Race Prevalence Geographic 

Area Prevalence

Asian 206,545 Northeast 4,069,268

Black 1,861,914 Midwest 5,432,053

Native American 318,290 South 8,315,194

White 19,389,086 West 4,462,936

Unknown 177,927

Other 325,689

Ethnicity Prevalence

Hispanic 1,408,190

Non-Hispanic 20,871,261
39

Attachment A6

Chronic Disease Subgroup

HYPERTENSION

Data Source Description:

Hypertension prevalence data are for the year 1994 and were obtained from the National 

Health Interview Survey (NHIS). 

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<1 n/a Female 15,898,911

1-5 43,084 Male 12,337,350

6-10 73,112

11-19 221,347

20-45 5,822,261

46-55 5,312,742

56-64 5,471,139

65+ 11,292,576

Total 28,236,261

Race Prevalence Geographic 

Area Prevalence

Asian 614,895 Northeast 5,198,902

Black 4,134,469 Midwest 7,138,637

Native American 283,562 South 10,617,882

White 22,579,800 West 5,280,840

Unknown 186,895

Other 463,640

Ethnicity Prevalence

Hispanic 1,748,068

Non-Hispanic 26,488,193
40

Attachment A7

Chronic Disease Subgroup

RENAL DISORDERS

Data Source Description:

Prevalence data for renal disorders are for the year 1994 and were obtained from the 

National Health Interview Survey (NHIS). Zero values may represent an artifact of the 

survey and may reflect instances in which the survey had few or no responses in an age 

category and therefore scaled-up estimates for the country could not be made.

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<1 0 Female 1,673,470

1-5 60,858 Male 395,482

6-10 50,012

11-19 185,652

20-45 924,319

46-55 214,012

56-64 145,532

65+ 488,567

Total 2,068,952

Race Prevalence Geographic 

Area Prevalence

Asian 27,961 Northeast 181,816

Black 184,211 Midwest 565,372

Native American 59,009 South 875,777

White 1,753,332 West 445,988

Unknown 26,541

Other 17,898

Ethnicity Prevalence

Hispanic 234,401

Non-Hispanic 1,834,551
41

Attachment A8

Chronic Disease Subgroup

ALCOHOLISM

(CHRONIC DRINKING)

Data Source Description:

Chronic drinking, which is being used as a surrogate for alcoholism, was provided on the 

1995 BRFSS developed by the CDC. An individual was considered a chronic drinker if 

they indicated the consumption of 2 drinks per day, i.e., 60 drinks per month. Data 

were not available (n/a) for persons under 18 years of age and for the State of California 

and the District of Columbia.

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<1 n/a Female 703,639

1-5 n/a Male 4,353,677

6-10 n/a

11-17 n/a

18-19 169,470

20-45 3,231,751

46-55 706,172

56-64 385,740

65+ 555,315

Total*,** 5,048,448

Race Prevalence Geographic 

Area Prevalence

Asian 51,243 Northeast 1,225,809

Black 353,893 Midwest 1,251,722

Native American 82,111 South* 1,982,217

White 4,380,245 West** 597,567

Unknown 5,093

Other 160,034

Ethnicity Prevalence

Hispanic 372,546

Non-Hispanic 4,655,946

* Does not include the District of Columbia

** Does not include California
42

Attachment A9

Chronic Disease Subgroup

GASTRIC HYPERACIDITY

Data Source Description:

Prevalence data for gastric hyperacidity are for the year 1994 and were obtained from the 

National Health Interview Survey (NHIS). Gastric hyperacidity does not include ulcers, 

which is considered a separate disease subgroup of interest. Zero values may represent 

an artifact of the survey and may reflect instances in which the survey had few or no 

responses in an age category and therefore scaled-up estimates for the country could not 

be made.

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<1 0 Female 3,478,567

1-5 14,032 Male 3,478,350

6-10 11,556

11-19 247,311

20-45 3,360,810

46-55 11,096,034

56-64 842,070

65+ 1,385,104

Total 6,956,917

Race Prevalence Geographic 

Distribution Prevalence

Asian 69,631 Northeast 927,350

Black 453,104 Midwest 1,799,540

Native American 71,516 South 2,875,685

White 6,158,942 West 1,354,342

Unknown 48,704

Other 155,020

Ethnicity Prevalence

Hispanic 534,397

Non-Hispanic 6,442,520
Attachment A10

Chronic Disease Subgroup

THYROID DISORDERS

Data Source Description:

Prevalence data for thyroid disorders are for the year 1994 and were obtained from the 

National Health Interview Survey (NHIS). Zero values may represent an artifact of the 

survey and may reflect instances in which the survey had few or no responses in an age 

category and therefore scaled-up estimates for the country could not be made.

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<1 0 Female 3,819,745

1-5 14,037 Male 689,034

6-10 0

11-19 11,488

20-45 1,584,147

46-55 854,766

56-64 553,529

65+ 1,490,813

Total 4,508,780

Race Prevalence Geographic 

Area Prevalence

Asian 165,684 Northeast 961,117

Black 250,337 Midwest 1,131,619

Native American 40,672 South 1,418,758

White 3,959,271 West 997,286

Unknown 27,961

Other 64,854

Ethnicity Prevalence

Hispanic 246,658

Non-Hispanic 4,262,122
Attachment A11

Chronic Disease Subgroup

ULCERS

Data Source Description:

Prevalence data for ulcers are for the year 1994 and were obtained from the National 

Health Interview Survey (NHIS). Zero values may represent an artifact of the survey and 

may reflect instances in which the survey had few or no responses in an age category and 

therefore scaled-up estimates for the country could not be made.

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<1 0 Female 2,399,639

1-5 0 Male 2,047,396

6-10 11,464

11-19 115,991

20-45 2,131,495

46-55 554,498

56-64 654,389

65+ 979,197

Total 4,447,035

Race Prevalence Geographic 

Area Prevalence

Asian 54,243 Northeast 516,391

Black 694,269 Midwest 1,278,927

Native American 149,618 South 1,773,694

White 3,394,009 West 878,023

Unknown 18,406

Other 136,489

Ethnicity Prevalence

Hispanic 375,517

Non-Hispanic 4,071,518
Attachments B1-B4

Immunocompromised Individuals
Attachment B1

Immunocompromised Subgroup

ACQUIRED IMMUNODEFICIENCY SYNDROME (AIDS)

Data Source Description:

Data on AIDS was abstracted from an 1997 HIV/AIDS Surveillance Report developed by 

the CDC and included AIDS cases reported to CDC by state and territorial health 

departments from July, 1996 to June, 1997. The report did not provide the age 

breakdowns of interest. As a result, the data obtained were categorized in similar groups 

as those requested in the work assignment. 

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<13 609 Female 14,003

13-19 390 Male 50,963

20-24 2,096

25+ 61,871

Total 64,966

Race Prevalence Geographic 

Area Prevalence

Asian 526 Northeast 21,070

Black 28,156 Midwest 5,801

Native American 223 South 24,371

White 23,139 West 11,407

Unknown 727

Other n/a

Ethnicity Prevalence

Hispanic 12,691

Non-Hispanic 40,080
Attachment B2

Immunocompromised Subgroup

PERSONS UNDER TREATMENT FOR CANCER

Data Source Description:

Data on persons being treated for cancer was obtained from the 1992 National Health 

Interview Survey Cancer Supplement. No data existed for persons under the age of 11.

Estimates by Selected Variables:

Age Groups Number Gender Number

<1 n/a Female 1,090,751

1-5 n/a Male 763,044

6-10 n/a

11-19 14,593

20-45 384,213

46-55 190,170

56-64 329,921

65+ 934,899

Total 1,853,795

Race Number Geographic 

Area Number

Asian 18,241 Northeast 385,429

Black 140,953 Midwest 498,672

Native American 4,078 South 570,920

White 1,688,337 West 398,744

Unknown 0

Other 2,187

Ethnicity Number

Hispanic 85,572

Non-Hispanic 1,768,223
Attachment B3

Immunocompromised Subgroup

ORGAN TRANSPLANT RECIPIENTS

Data Source Description:

Data provided on organ transplant recipients were obtained from the 1994 National 

Hospital Discharge Survey. This survey provided information on procedures performed 

while in the hospital. Data on children <1 year of age and on ethnicity could not be 

obtained (n/a).

Estimates by Selected Variables:

Age Groups Number Gender Number

<1 n/a Female 7,116

1-5 590 Male 9,979

6-10 587

11-19 994

20-45 5,912

46-55 5,665

56-64 1,762

65+ 1,585

Total 17,095

Race Number

Geographic 

Area Number

Asian 821 Northeast 2,426

Black 3,591 Midwest 1,871

Native American 296 South 9,614

White 10,475 West 3,184

Unknown 1,516

Other 396

Ethnicity Number

Hispanic n/a

Non-Hispanic n/a
Attachment B4

Immunocompromised Subgroup

IMMUNOLOGICAL HYPERSENSITIVITY

Data Source Description:

Prevalence data for immunological hypersensitivities are for the year 1994 and were 

obtained from the National Health Interview Survey (NHIS). 

Prevalence Estimates by Selected Variables:

Age Groups Prevalence Gender Prevalence

<1 81,385 Female 21,889,938

1-5 1,778,374 Male 18,817,889

6-10 2,795,838

11-19 5,759,388

20-45 18,260,033

46-55 4,942,181

56-64 3,043,325

65+ 4,047,303

Total 40,707,827

Race Prevalence Geographic 

Area Prevalence

Asian 1,116,726 Northeast 7,561,815

Black 4,352,170 Midwest 8,689,292

Native American 482,343 South 14,206,918

White 33,441,850 West 10,249,802

Unknown 517,222

Other 797,517

Ethnicity Prevalence

Hispanic 3,518,287

Non-Hispanic 37,189,540
Attachments C1-C2

Pregnant and Lactating Women
Attachment C1

PREGNANT WOMEN 

Data Source Description:

Data on the number of pregnant women were obtained from the Bureau of the Census=

1996 Statistical Abstract of the U.S. Pregnancy estimates are provided for 1991 and 

include stillbirths and abortions. Information was not available (n/a) for Asians, Native 

Americans, or the geographic areas of interest. The age breakdowns do not match those 

requested by the work assignment. As a result, similar age categories are provided.

Estimates by Selected Variables:

Age Groups Number

15 27,000

15-19 938,000

20-24 1,752,000

25-29 1,715,000

30-34 1,235,000

35-39 513,000

40+ 92,000

Total 6,272,000

Race Number Geographic 

Area Number

Asian n/a Northeast n/a

Black 1,344,000 Midwest n/a

Native American n/a South n/a

White 3,964,000 West n/a

Unknown n/a

Other n/a

Ethnicity Number

Hispanic 965,000

Non-Hispanic 5,307,000

Attachment C2
LACTATING WOMEN

Data Source Description:

Data for lactating women were not provided in terms of Anumbers of women lactating@. 

However, percentages of women with singleton births occurring between 1990-1993 

were obtained and are provided below. We used those percentages and numbers of live 

births for the same time period to develop annualized estimates of women who breast-fed 

during the time period. 

Numbers by Selected Variables:

Age Groups

Number of 

Live Births 

(1990-1993)

Number of 

Live Births 

(annualized)

Percent

Lactating

Estimated Number of 

Lactating Women 

(annualized)

<20 2,084,000 521,000 36.0 187,560

20-24 4,292,000 1,073,000 46.4 493,580

25+ 9,946,000 2,486,500 63.0 1,566,495

Total 16,322,000 4,080,500 55.2 2,247,635

Race Groups

Asian n/a n/a n/a n/a

Black 2,700,000 675,000 25.1 169,425

Native 

American

n/a n/a n/a n/a

White 12,883,000 3,220,750 59.1 1,903,020

Unknown n/a n/a n/a n/a

Other n/a n/a n/a n/a
Attachments D1-D2

Occupationally At-Risk Subgroup
Attachment D1

OCCUPATIONALLY AT-RISK 

TO BIOLOGICAL AGENTS

Data Source Description:

Numbers of workers were obtained from the 1996 Statistical Abstract of the U.S. The 

estimates are for the year 1995. Refer to Section 3.4.2 of this report for a more detailed 

description of the sources used to develop the estimates below.

Number of Workers

Occupational Category Total Males Females White Black

Agricultural Workers:

Farm operators and managers 1,446,000 1,080,162 365,838 1,440,216 5,784

Other agricultural and related 

occupations including farm 

workers 2,010,000 1,660,260 349,740 1,873,320 136,680

Subtotal 3,456,000 2,740,422 715,578 3,313,536 142,464

Food Handlers:

Cooks 2,001,000 1,110,555 890,445 1,648,824 352,176

Kitchen workers, food preparers 280,000 82,040 197,960 250,040 29,960

Meat product workers 467,000 n/a n/a n/a n/a

Subtotal 2,748,000 1,192,595* 1,088,405* 1,898,864* 382,136*

Health Care Providers:

Health service including dental 

assistants, and health and 

nursing aids 2,315,000 273,170 2,041,830 1,676,060 638,940

Clinical laboratory technologists 

and technicians 374,000 105,842 268,158 323,136 50,864

Licensed practical nurses 399,000 18,354 380,646 320,796 78,204

Physician assistants 55,000 25,740 29,260 50,820 4,180

Physicians 693,000 523,908 169,092 659,043 33,957

Dentists 155,000 134,230 20,770 152,055 2,945

Subtotal 3,991,000 1,081,244 2,909,756 3,181,910 809,090
Child Care Providers:

Teachers, prekindergarten and 

kindergarten 498,000 8,964 489,036 428,778 69,222

Family child care providers 486,000 10,206 475,794 436,914 49,086

Early childhood teacher=s 

assistants 396,000 16,632 379,368 330,660 65,340

Subtotal 1,380,000 35,802 1,344,198 1,196,352 183,648

Total 11,575,000 5,050,063* 6,057,937* 9,590,662* 1,517,338*

* Does not include meat product workers
Attachment D2

OCCUPATIONALLY AT-RISK 

TO CHEMICAL AGENTS

Data Source Description:

Numbers of workers were obtained from the 1996 Statistical Abstract of the U.S. The 

estimates are for the year 1995 and include production workers only. Data are not 

available for the gender and race groups requested in the work assignment. Refer to 

Section 3.4.3 of this report for a more detailed description of the sources used to develop 

the estimates below.

Occupational Category Number of Workers

Mining: 424,000

Manufacturing, Durable Goods:

 Stone, clay and glass products

 flat glass 12,000

 glass and glassware pressed and blown 62,000

 Primary metal industries

 nonferrous foundries (castings) 71,000

 Electronic and other electrical equipment

 electrical industrial apparatus 112,000

 electronic components and accessories 349,000

Subtotal 1,030,000

Manufacturing, Nondurable Goods:

 Chemicals and Allied Products

 industrial inorganic chemicals 54,000

 plastics materials and synthetics 105,000

 drugs 127,000

 soap, cleaners and toilet goods 94,000

 paints and allied products 30,000

 industrial organic chemicals 83,000

 agricultural chemicals 31,000
 Petroleum and Coal Products

 petroleum refining 66,000

 Rubber and Miscellaneous Plastic Products 696,000

Subtotal 1,286,000

Total 2,316,000
Attachment E

Detailed List of ICD-9-CM Codes Included in the 

National Health Interview Survey
Work Plan Disease 

Category

ICD-9-CM Disease 

Category

ICD-9-CM Codes 

Included in 

Corresponding NHIS 

Category

Condition for Each ICD-9-CM Code

Diabetes Diabetes Mellitus 250

250.0

250.1

250.2

250.3

250.4

250.5

250.6

250.7

250.8

250.9

Diabetes mellitus

Diabetes mellitus without mention of 

complication

Diabetes with ketoacidosis

Diabetes with hyperosmolarity

Diabetes with other coma

Diabetes with renal manifestations

Diabetes with ophthalmic manifestations

Diabetes with neurological manifestations

Diabetes with peripheral circulatory 

disorders

Diabetes with other specified manifestations

Diabetes with unspecified complication

Anemia Anemia 280

280.0

280.1

280.8

280.9

281

281.0

281.1

281.2

281.3

281.4

281.8

281.9

282

282.0

282.1

282.2

282.3

282.4

282.5

282.6

282.7

282.8

282.9

283

283.0

283.1

283.2

283.9

284

284.0

284.8

284.9

285

285.0

285.1

285.8

285.9

Iron deficiency anemias

Secondary to blood loss (chronic)

Secondary to inadequate dietary iron intake

Other specified iron deficiency anemias

Iron deficiency anemia, unspecified

Other deficiency anemias

Pernicious anemia

Other vitamin B12 deficiency anemia

Folate-deficiency anemia

Other specified megaloblastic anemias, not 

elsewhere classified

Protein-deficiency anemia

Anemia associated with other specified 

nutritional deficiency

Unspecified deficiency anemia

Hereditary hemolytic anemias

Hereditary spherocytosis

Hereditary elliptocytosis

Anemias due to disorders of glutathione 

metabolism

Other hemolytic anemias due to enzyme 

deficiency

Thalassemias

Sickle-cell trait

Sickle-cell anemia

Other hemoglobinopathies

Other specified hereditary hemolytic 

anemias

Hereditary hemolytic anemia, unspecified

Acquired hemolytic anemias

Autoimmune hemolytic anemias

Non-autoimmune hemolytic anemias

Hemoglobinuria due to hemolysis from 

external causes

Acquired hemolytic anemia, unspecified

Aplastic anemia

Constitutional aplastic anemia

Other specified aplastic anemias

Aplastic anemia, unspecified

Other and unspecified anemias

Sideroblastic anemia

Acute posthemorrhagic anemia

Other specified anemias

Anemia, unspecified
Work Plan Disease 

Category

ICD-9-CM Disease 

Category

ICD-9-CM Codes 

Included in 

Corresponding NHIS 

Category

Condition for Each ICD-9-CM Code

Liver Impairment Liver Diseases Including 

Cirrhosis

571

571.0

571.1

571.2

571.3

571.4

571.5

571.6

571.8

571.9

572

572.0

572.1

572.2

572.3

572.4

572.8

573

573.0

573.3

573.4

573.8

573.9

Chronic liver disease and cirrhosis

Alcoholic fatty liver

Acute alcoholic hepatitis

Alcoholic cirrhosis of liver

Alcoholic liver damage, unspecified

Chronic hepatitis

Cirrhosis of liver without mention of alcohol

Biliary cirrhosis

Other chronic nonalcoholic liver disease

Unspecified chronic liver disease without 

mention of alcohol

Liver abscess and sequelae of chronic liver 

disease

Abscess of liver

Portal pyemia

Hepatic coma

Portal hypertension

Hepatorenal syndrome

Other sequelae of chronic liver disease

Other disorders of liver

Chronic passive congestion of liver

Hepatitis, unspecified

Hepatic infarction

Other specified disorders of liver

Unspecified disorder of liver

Cardiovascular Disease Ischemic Heart Disease 413

413.0

413.1

413.9

414

414.0

414.1

414.8

414.9

410

410.0

410.1

410.2

410.3

410.4

410.5

410.6

410.7

410.8

410.9

411

411.0

411.1

411.8

412

429.6

Angina pectoris

Angina decubitus

Prinzmetal angina

Other and unspecified angina pectoris

Other forms of chronic ischemic heart disease

Coronary atherosclerosis

Aneurysm of heart

Other specified forms of chronic ischemic 

heart disease

Chronic ischemic heart disease, unspecified

Acute myocardial infarction

Of anterolateral wall

Of other anterior wall

Of inferolateral wall

Of inferoposterior wall

Of other inferior wall

Of other lateral wall

True posterior wall infarction

Subendocardial infarction

Of other specified sites

Unspecified site

Other acute and subacute forms of ischemic 

heart disease

Postmyocardial infarction syndrome

Intermediate coronary syndrome

Other

Old myocardial infarction

Rupture of papillary muscle

Cardiovascular Disease

(continued)

Heart Rhythm Disorders:

Tachycardia or Rapid 

Heart,

Heart Murmurs,

Other and Unspecified 

427

427.0

427.1

427.2

427.3

Cardiac dysrhythmias

Paroxysmal supraventricular tachycardia

Paroxysmal ventricular tachycardia

Paroxysmal tachycardia, unspecified

Atrial fibrillation and flutter
Work Plan Disease 

Category

ICD-9-CM Disease 

Category

ICD-9-CM Codes 

Included in 

Corresponding NHIS 

Category

Condition for Each ICD-9-CM Code

Heart Rhythm Disorders 785

785.0

785.2

427.4

427.5

427.6

427.8

427.9

785.1

Symptoms involving cardiovascular system

Tachycardia, unspecified

Undiagnosed cardiac murmurs

Ventricular fibrillation and flutter

Cardiac arrest

Premature beats

Other specified cardiac dysrhythmias

Cardiac dysrhythmia, unspecified

Palpitations

Congenital Heart 

Disease

745

745.0

745.1

745.2

745.3

745.4

745.5

745.6

745.7

745.8

745.9

746

746.0

746.1

746.2

746.3

746.4

746.5

746.6

746.7

Bulbus cordis anomalies and anomalies of 

cardiac septal closure

Common truncus

Transposition of great vessels

Tetralogy of Fallot

Common ventricle

Ventricular septal defect

Ostium secundum type atrial septal defect

Endocardial cushion defects

Cor biloculare

Other

Unspecified defect of septal closure

Other congenital anomalies of heart

Anomalies of pulmonary valve

Tricuspid atresia and stenosis, congenital

Ebstein=s anomaly

Congenital stenosis of aortic valve

Congenital insufficiency of aortic valve

Congenital mitral stenosis

Congenital mitral insufficiency

Hypoplastic left heart syndrome

Other Selected Diseases 

of Heart (Excludes 

Hypertension)

415

415.0

415.1

416

416.0

416.1

417

417.0

417.1

417.8

417.9

420

420.0

420.9

421

421.0

421.9

Acute pulmonary heart disease

Acute cor pulmonale

Pulmonary embolism and infarction

Chronic pulmonary heart disease

Primary pulmonary hypertension

Kyphoscoliotic heart disease

Other diseases of pulmonary circulation

Arteriovenous fistula of pulmonary vessels

Aneurysm of pulmonary artery

Other specified diseases of pulmonary 

circulation

Unspecified disease of pulmonary 

circulation

Acute pericarditis

Acute pericarditis in diseases classified 

elsewhere

Other and unspecified acute pericarditis

Acute and subacute endocarditis

Acute and subacute bacterial endocarditis

Acute endocarditis, unspecified

Cardiovascular

Disease

(continued)

Other Selected Diseases 

of Heart (Excludes 

Hypertension)

(continued)

422

422.0

422.9

423

423.0

423.1

Acute myocarditis

Acute myocarditis in diseases classified 

elsewhere

Other and unspecified acute myocarditis

Other diseases of pericardium

Hemopericardium

Adhesive pericarditis
Work Plan Disease 

Category

ICD-9-CM Disease 

Category

ICD-9-CM Codes 

Included in 

Corresponding NHIS 

Category

Condition for Each ICD-9-CM Code

423.2

423.8

423.9

424

424.0

424.1

424.2

424.3

424.9

425

425.0

425.1

425.2

425.3

425.4

425.5

425.9

426

426.0

426.1

426.2

426.3

426.4

426.5

426.6

426.7

426.8

426.9

428

428.0

428.1

428.9

429

429.0

429.1

429.2

429.3

429.4

429.5

429.8

429.9

Constrictive pericarditis

Other specified diseases of pericardium

Unspecified disease of pericardium

Other diseases of endocardium

Mitral valve disorders

Aortic valve disorders

Tricuspid valve disorders, specified as 

nonrheumatic

Pulmonary valve disorders

Endocarditis, valve unspecified

Cardiomyopathy

Endomyocardial fibrosis

Hypertrophic obstructive cardiomyopathy

Obscure cardiomyopathy of Africa

Endocardial fibroelastosis

Other primary cardiomyopathies

Alcoholic cardiomyopathy

Secondary cardiomyopathy, unspecified

Conduction disorders

Atrioventricular block, complete

Atrioventricular block, other and 

unspecified

Left bundle branch hemiblock

Other left bundle branch block

Right bundle branch block

Bundle branch block, other and unspecified

Other heart block

Anomalous atrioventricular excitation

Other specified conduction disorders

Conduction disorder, unspecified

Heart failure

Congestive heart failure

Left heart failure

Heart failure, unspecified

Ill-defined descriptions and complications

of heart disease

Myocarditis, unspecified

Myocardial degeneration

Cardiovascular disease, unspecified

Cardiomegaly

Functional disturbances following cardiac 

surgery

Rupture of chordae tendineae

Other ill-defined heart diseases

Heart disease, unspecified

Hypertension High Blood Pressure 401

401.0

401.1

401.9

402

402.0

402.1

402.9

403

403.0

403.1

403.9

404

404.0

Essential hypertension

Malignant

Benign

Unspecified

Hypertensive heart disease

Malignant

Benign

Unspecified

Hypertensive renal disease

Malignant

Benign

Unspecified

Hypertensive heart and renal disease

Malignant
Work Plan Disease 

Category

ICD-9-CM Disease 

Category

ICD-9-CM Codes 

Included in 

Corresponding NHIS 

Category

Condition for Each ICD-9-CM Code

404.1

404.9

405

405.0

405.1

405.9

Benign

Unspecified

Secondary hypertension

Malignant

Benign

Unspecified

Renal Disorders Kidney Infections 590

590.0

590.1

590.2

590.3

590.8

590.9

Infections of kidney

Chronic pyelonephritis

Acute pyelonephritis

Renal and perinephric abscess

Pyeloureteritis cystica

Other pyelonephritis or pyonephrosis, not 

specified as acute or chronic

Infection of kidney, unspecified

Other Kidney Trouble, 

NEC

581

581.0

581.1

581.2

581.3

581.8

581.9

582

582.0

582.1

582.2

582.4

582.8

582.9

Nephrotic syndrome

With lesion of proliferative 

glomerulonephritis

With lesion of membranous 

glomerulonephritis

With lesion of membranoproliferative

With lesion of minimal change 

glomerulonephritis

With other specified pathological lesion in 

kidney

Nephrotic syndrome with unspecified 

pathological lesion in kidney

Chronic glomerulonephritis

With lesion of proliferative 

glomerulonephritis

With lesion of membranous 

glomerulonephritis

With lesion of membranoproliferative 

glomerulonephritis

With lesion of rapidly progressive 

glomerulonephritis

With other specified pathological lesion in 

kidney

Chronic glomerulonephritis with 

unspecified pathological lesion in kidney

Renal Disorders

(continued)

Other Kidney Trouble,

NEC

(continued)

583

583.0

583.1

583.2

583.4

583.6

583.7

583.8

583.9

593

593.0

Nephritis and nephropathy, not specified as 

acute or chronic

With lesion of proliferative 

glomerulonephritis

With lesion of membranous 

glomerulonephritis

With lesion of membranoproliferative 

glomerulonephritis

With lesion of rapidly progressive 

glomerulonephritis

With lesion of renal cortical necrosis

With lesion of renal medullary necrosis

With other specified pathological lesion in 

kidney

With unspecified pathological lesion in 

kidney

Other disorders of kidney and ureter

Nephroptosis
Work Plan Disease 

Category

ICD-9-CM Disease 

Category

ICD-9-CM Codes 

Included in 

Corresponding NHIS 

Category

Condition for Each ICD-9-CM Code

593.1

593.2

593.3

593.4

593.5

593.6

593.7

593.8

593.9

Hypertrophy of kidney

Cyst of kidney, acquired

Stricture or kinking of ureter

Other ureteric obstruction

Hydroureter

Postural proteinuria

Vesicoureteral reflux

Other specified disorders of kidney and 

ureter

Unspecified disorder of kidney and ureter

Gastric Hyperacidity Indigestion 536.8 Dyspepsia and other specified disorders of 

function of stomach

Thyroid Disorders Goiter 240

240.0

240.9

241

241.0

241.1

241.9

242

242.0

242.1

242.2

242.3

Simple and unspecified goiter

Goiter, specified as simple

Goiter, unspecified

Nontoxic nodular goiter

Nontoxic uninodular goiter

Nontoxic multinodular goiter

Unspecified nontoxic nodular goiter

Thyrotoxicosis with or without goiter

Toxic diffuse goiter

Toxic uninodular goiter

Toxic multinodular goiter

Toxic nodular goiter, unspecified

Thyroid Disorders

(continued)

Other Diseases of the 

Thyroid

242.4

242.8

242.9

243

244

244.0

244.1

244.2

244.3

244.8

244.9

245

245.0

245.1

245.2

245.3

245.4

245.8

245.9

246

246.0

246.1

246.2

246.3

246.8

246.9

Thyrotoxicosis from ectopic thyroid nodule

Thyrotoxicosis of other specified origin

Thyrotoxicosis without mention of goiter or 

other cause

Congenital hypothyroidism

Acquired hypothyroidism

Postsurgical hypothyroidism

Other postablative hypothyroidism

Iodine hypothyroidism

Other iatrogenic hypothyroidism

Other specified acquired hypothyroidism

Unspecified hypothyroidism

Thyroiditis

Acute thyroiditis

Subacute thyroiditis

Chronic lymphocytic thyroiditis

Chronic fibrous thyroiditis

Iatrogenic thyroiditis

Other and unspecified chronic thyroiditis

Thyroiditis, unspecified

Other disorders of thyroid

Disorders of thyrocalcitonin secretion

Dyshormonogenic goiter

Cyst of thyroid

Hemorrhage and infarction of thyroid

Other specified disorders of thyroid

Unspecified disorder of thyroid

Ulcers Gastric Ulcer 531

531.0

531.1

531.2

531.3

Gastric ulcer

Acute with hemorrhage

Acute with perforation

Acute with hemorrhage and perforation

Acute without mention of hemorrhage or 
Work Plan Disease 

Category

ICD-9-CM Disease 

Category

ICD-9-CM Codes 

Included in 

Corresponding NHIS 

Category

Condition for Each ICD-9-CM Code

531.4

531.5

531.6

531.7

531.9

perforation

Chronic or unspecified with hemorrhage

Chronic or unspecified with perforation

Chronic or unspecified with hemorrhage 

and perforation

Chronic without mention of hemorrhage or 

perforation

Unspecified as acute or chronic, without 

mention of hemorrhage or perforation

Duodenal Ulcer 532

532.0

532.1

532.2

532.3

532.4

532.5

532.6

532.7

532.9

Duodenal ulcer

Acute with hemorrhage

Acute with perforation

Acute with hemorrhage and perforation

Acute without mention of hemorrhage or 

perforation

Chronic or unspecified with hemorrhage

Chronic or unspecified with perforation

Chronic or unspecified with hemorrhage 

and perforation

Chronic without mention of hemorrhage or 

perforation

Unspecified as acute or chronic, without 

mention of hemorrhage or perforation

Ulcers 

(continued)

Peptic Ulcer 533

533.0

533.1

533.2

533.3

533.4

533.5

533.6

533.7

533.9

Peptic ulcer, site unspecified

Acute with hemorrhage

Acute with perforation

Acute with hemorrhage and perforation

Acute without mention of hemorrhage and 

perforation

Chronic or unspecified with hemorrhage

Chronic or unspecified with perforation

Chronic or unspecified with hemorrhage 

and perforation

Chronic without mention of hemorrhage or 

perforation

Unspecified as acute or chronic, without 

mention of hemorrhage or perforation

Immunological 

Hypersensitivity

Asthma 493

493.0

493.1

493.2

493.9

Asthma

Extrinsic asthma

Intrinsic asthma

Chronic obstructive asthma

Asthma, unspecified

Hay Fever/Allergic 

Rhinitis Without Asthma

477

477.0

477.8

477.9

Allergic rhinitis

Due to pollen

Due to other allergen

Cause unspecified
Attachment F

List of Types of Organ Transplants Used to Develop 

Prevalence Estimates of Organ Transplant Recipients
ICD-9 CM Procedure Codes and Corresponding Transplantations

ICD-9 CM 

Procedure Codes Transplantation

07.94 Transplantation of thymus

33.5 Lung transplantation

33.50 Lung transplantation, not otherwise specified

33.51 Unilateral lung transplantation

33.52 Bilateral lung transplantation

33.6 Combined heart-lung transplantation

37.5 Heart transplantation

41.0 Bone marrow or hematopoietic stem cell transplant

41.00 Bone marrow transplant, not otherwise specified

41.02 Allogeneic bone marrow transplant with purging

41.03 Allogeneic bone marrow transplant without purging

41.94 Transplantation of spleen

50.5 Liver transplant

50.51 Auxiliary liver transplant

50.59 Other transplant of liver

52.8 Transplant of pancreas

52.80 Pancreatic transplant, not otherwise specified

55.6 Transplant of kidney

55.69 Other kidney transplantation
Attachment G

Statistical Analysis Software (SAS) Programs
*--------------------------------------------------------------

Program Name: osteop.sas

Author: Roger Oen, SRA Technologies, Inc. 703-205-8500

Date: 2/2/98

Input file(s): adult.dat (NHANES III)

Output file(s): none

This SAS program develops U.S. prevalence estimates, stratified

by age, race, ethnicity, gender, and geographic area, for 

osteoporosis (chronic disease subgroup).

*--------------------------------------------------------------

OPTIONS LS=78;

 FILENAME ADULT 'external-file' LRECL=3348;

 *** LRECL includes 2 positions for CRLF, assuming use of PC SAS;

proc format;

value yesnof 1='Yes' 2='No' 3='Blank but app.'

9='Refused';

value age 1='Under 1 Year'

2='1-5 Years'

3='6-10 Years'

4='11-19 Years'

5='20-45 Years'

6='46-55 Years'

7='56-64 Years'

8='Over 65 Years';

value dmarethn 1='Non-Hispanic White'

2='Non-Hispanic Black'

3='Mexican-American'

4='Other';

value dmaracer 1='White'

2='Black'

3='Other'

8='Mexican-American of unknown race';

value dmaethnr 1='Mexican-American'

2='Other Hispanic'

3='Not Hispanic';

value hssex 1='Male'

2='Female';

va

lue dmpcregn 1='Northeast'

2='Midwest'

3='South'

4='West';
 DATA WORK;

 INFILE ADULT MISSOVER;

*NHANES III variable names and positions have been omitted here due to length. They can 

be found on the CD-ROM.** 

LENGTH

 ;

*-------------------

Osteoporosis Recoded

--------------------;

if hag11=1 then hag11a=1;

else if hag11=2 or hag11=8 then hag11a=2;

else if hag11=3 then hag11a=3;

else if hag11=9 then hag11a=9;

*----------

Age Recoded

-----------;

if hsageir < 1 then age=1;

else if 1 <= hsageir <= 5 then age=2;

else if 6 <= hsageir <= 10 then age=3;

else if 11 <= hsageir <= 19 then age=4;

else if 20 <= hsageir <= 45 then age=5;

else if 46 <= hsageir <= 55 then age=6;

else if 56 <= hsageir <= 64 then age=7;

else if 65 <= hsageir <= 99 then age=8;

run;

%MACRO ANALYSIS;

%DO I=1 %TO 5;

%LET J=%SCAN(age@dmarethn@dmaracer@hssex@dmaethnr@dmpcregn,&I,@);

PROC FREQ DATA=WORK;

WEIGHT WTPFQX6;

TABLES HAG11A*&J;

FORMAT HAG11A YESNOF. age age. dmarethn dmarethn. 

hssex hssex. dmaracer dmaracer. dmaethnr dmaethnr. dmpcregn dmpcregn.

;

RUN;

%END;

%MEND;

%ANALYSIS;

*-------------
END OF PROGRAM

--------------;
*---------------------------------------------------------------

Program Name: organ.sas

Author: Roger Oen, SRA Technologies, Inc. 703-205-8500

Date: 2/2/98

Input file(s): nonnewborn.exp (1994 National Hospital Discharge

Survey)

Output file(s): none

This SAS program develops U.S. prevalence estimates, stratified

by age, race, ethnicity, gender, and geographic area, for

persons who undergo organ transplants (immunocompromised

subgroup).

*---------------------------------------------------------------

options ls=78;

filename info 'external-file';

proc format;

 value genderf 1='Male'

 2='Female';

 value racef 1='White'

 2='Black'

 3='American Indian/Eskimo'

 4='Asian/PI'

 5='Other'

 9='Not Stated';

 value regionf 1='Northeast'

 2='Midwest'

 3='South'

 4='West';

value procf1='Organ Transplantation';

value agef 1='Under 1 Year'

 2='1-5 Years'

 3='6-10 Years'

 4='11-19 Years'

 5='20-45 Years'

 6='46-55 Years'

 7='56-64 Years'

 8='Over 65 Years';

data nhds;

infile info missover;

input agenum 7-8 gender 9 race 10 region 20 wgt 23-27 diagnos1 $ 30-34

diagnos2 $ 38-42 diagnos3 $ 46-50 diagnos4 $ 54-58 diagnos5 $ 62-66

diagnos6 $ 70-74 diagnos7 $ 78-82 proced1 $ 86-89 proced2 $ 92-95 proced3
$ 98-101 proced4 $ 104-107;

*----------

Age Recoded

-----------;

if agenum < 01 then age=1;

else if 01 <= agenum <= 05 then age=2;

else if 06 <= agenum <= 10 then age=3;

else if 11 <= agenum <= 19 then age=4;

else if 20 <= agenum <= 45 then age=5;

else if 46 <= agenum <= 55 then age=6;

else if 56 <= agenum <= 64 then age=7;

else if 65 <= agenum <= 99 then age=8;

*-----------------

Procedures Recoded

------------------;

if proced1

in('335-','410-','4100','4102','4103',

'505-','5051','5059','528-','5280','556-','0794',

'3350','3351','3352','336-','375-','4194','5569') or proced2

in('335-','410-','4100','4102','4103',

'505-','5051','5059','528-','5280','556-','0794',

'3350','3351','3352','336-','375-','4194','5569') or proced3

in('335-','410-','4100','4102','4103',

'505-','5051','5059','528-','5280','556-','0794',

'3350','3351','3352','336-','375-','4194','5569') or proced4

in('335-','410-','4100','4102','4103',

'505-','5051','5059','528-','5280','556-','0794',

'3350','3351','3352','336-','375-','4194','5569')

then proc1=1;

*--------------------------------------------------

Analysis by Age, Race, Gender and Geographic Region

---------------------------------------------------;

%macro analysis;

%do i=1 %to 4;

%let j=%scan(age@race@gender@region,&i,@); 

proc freq data=nhds;

weight wgt;

tables proc1*&j;

format proc1 procf. age agef. race racef. gender genderf. 

region regionf.;

run;

%end;

%mend;

%analysis;
*---------------------------------------------------------------

Program Name: chronic.sas

Author: Roger Oen, SRA Technologies, Inc. 703-205-8500

Date: 2/2/98

Input file(s): nhis1994 (1994 National Health Interview Survey) 

Output file(s): none

This SAS program develops U.S. prevalence estimates, stratified

by age, race, ethnicity, gender, and geographic area, for

diabetes, thyroid disorder, anemias, renal disorders, liver

impairment, gastric hypersensitivities, ulcers, cardiovascular

disease, hypertension, immunological hypersensitivities, and

disorders of the bone or cartilage. (chronic disease subgroup).

*---------------------------------------------------------------

options ls=78 mprint;

filename data 'external-file';

*------

Formats

-------;

proc format;

value racefmt 1='White'

2='Black'

3='Native American'

4='Asian'

5='Other'

6='Unknown';

value hispanf 1='Hispanic'

2='Non-Hispanic';

value agefmt 1='Under 1 Year'

2='1-5 Years'

3='6-10 Years'

4='11-19 Years'

5='20-45 Years'

6='46-55 Years'

7='56-64 Years'

8='Over 65 Years';

value disfmta 1='Diabetes'

2='Thyroid Disor.'

3='Anemias'

4='Renal Disor.';

value disfmtb 1='Liver Impairment'
2='Gastric Hypers.'

3='Ulcers';

value disfmtc 1='Cardiovascular Dis.'

2='Hypertension';

value disfmtd 1='Immuno. Hypersen.';

value disfmte 1='Disorder of bone or cartilage';

value $genderf '1'='Male'

'2'='Female';

value regfmt 1='Northeast'

2='Midwest'

3='South'

4='West';

data cond;

infile data missover lrecl=500;

input quarter $ 5 gender $ 25 age 26-27 race $ 45-46 hispanic $ 50-51

condlist $ 96 icdnhis $ 97-100 c1condrc $ 108-110 cacode $ 111 region $

155 ccfact 162-172 wtfa 191-199;

*-----------

Race Recoded

------------;

if race='01' then racef=1;

else if race='02' then racef=2;

else if race='03' or race='04' or race='05' then racef=3;

else if race='06' or race='07' or race='08' or race='09' or

race='10' or race='11' or race='12' then racef=4;

else if race='13' or race='14' or race='15' or race='16' or

race='17' then racef=5;

else if race='99' then racef=6;

*----------------------

Hispanic Origin Recoded

-----------------------;

if hispanic NE '10' then hispan=1;

else if hispanic EQ '10' then hispan=2;

*----------

Age Recoded

-----------;

if age=00 then age1=1;

else if 1 <= age <= 5 then age1=2;

else if 6 <= age <= 10 then age1=3;

else if 11 <= age <= 19 then age1=4;

else if 20 <= age <= 45 then age1=5;

else if 46 <= age <= 55 then age1=6;
else if 56 <= age <= 64 then age1=7;

else if 65 <= age <= 99 then age1=8;

*------------------------

Geographic Region Recoded

-------------------------;

if region='1' then region1=1;

else if region='2' then region1=2;

else if region='3' then region1=3;

else if region='4' then region1=4;

*-----

Weight

------;

wgt=wtfa*ccfact/1000000000;

*-----

Labels

------;

label disease='Disease'

age1='Age'

racef='Race'

gender='Gender'

hispan='Hispanic Origin'

region1='Geographic Region';

data cond1;

set cond; 

*---------

Subsetting

----------;

if cacode='1' and condlist='4';

*-------------------------

Chronic Conditions Recoded

--------------------------;

if c1condrc='403' then disease=1;

else if c1condrc in('401','402') then disease=2;

else if c1condrc='404' then disease=3;

else if c1condrc in('410','411') then disease=4;

*-------------------------------------------------

Analysis by Age, Gender, Race, Hispanic Origin and
Geographic Region

--------------------------------------------------;

%macro analysis;

%do i=1 %to 5;

%let j=%scan(age1@racef@gender@hispan@region1,&i,@);

proc freq data=cond1;

weight wgt;

tables disease*&j;

format age1 agefmt. racef racefmt. gender $genderf. hispan

hispanf. region1 regfmt. disease disfmta.;

run;

%end;

%mend;

%analysis;

data cond2;

set cond;

*---------

Subsetting

----------;

if cacode='1' and condlist='3';

*-------------------------

Chronic Conditions Recoded

--------------------------;

if c1condrc='302' then disease=1;

else if c1condrc='309' then disease=2;

else if c1condrc in('303','304','305') then disease=3;

%macro analysis;

%do i=1 %to 5;

%let j=%scan(age1@racef@gender@hispan@region1,&i,@);

proc freq data=cond2;

 weight wgt;

 tables disease*&j;

 format age1 agefmt. racef racefmt. gender $genderf. hispan

hispanf. region1 regfmt. disease disfmtb.;

run;

%end;

%mend;

%analysis;

data cond3;

set cond;
*---------

Subsetting

----------;

if cacode='1' and condlist='5';

*-------------------------

Chronic Conditions Recoded

--------------------------;

if c1condrc in('502','503','504','505','506','507') then disease=1;

else if c1condrc='508' then disease=2;

%macro analysis;

%do i=1 %to 5;

%let j=%scan(age1@racef@gender@hispan@region1,&i,@);

proc freq data=cond3;

 weight wgt;

 tables disease*&j;

 format age1 agefmt. racef racefmt. gender $genderf. hispan

hispanf. region1 regfmt. disease disfmtc.;

run;

%end;

%mend;

%analysis;

data cond4;

set cond;

*---------

Subsetting

----------;

if cacode='1' and condlist='6';

*------------------------

Chronic Condition Recoded

-------------------------;

if c1condrc in('602','603') then disease=1;

%macro analysis;

%do i=1 %to 5;

%let j=%scan(age1@racef@gender@hispan@region1,&i,@);

proc freq data=cond4;

 weight wgt;

 tables disease*&j;

 format age1 agefmt. racef racefmt. gender $genderf. hispan

hispanf. region1 regfmt. disease disfmtd.;
run;

%end;

%mend;

%analysis;

data cond5;

set cond;

*---------

Subsetting

----------;

if cacode='1' and condlist='1';

*-------------------------

Chronic Condition Recoded

--------------------------;

if c1condrc='107' then disease=1;

%macro analysis;

%do i=1 %to 5;

%let j=%scan(age1@racef@gender@hispan@region1,&i,@);

proc freq data=cond5;

 weight wgt;

 tables disease*&j;

 format age1 agefmt. racef racefmt. gender $genderf. hispan

hispanf. region1 regfmt. disease disfmte.;

run;

%end;

%mend;

%analysis;
*---------------------------------------------------------------

Program Name: cancer.sas

Author: Roger Oen, SRA Technologies, Inc. 703-205-8500

Date: 2/2/98

Input file(s): control.exp, epi.exp (1992 National Health

Interview Survey, Cancer Supplement)

Output file(s): none

This SAS program develops U.S. prevalence estimates, stratified

by age, race, ethnicity, gender, and geographic area, for

persons under treatment for cancer (immunocompromised subgroup).

*---------------------------------------------------------------

options ls=78 mprint;

filename data1 'external-file1';

filename data2 'external-file2';

*------

Formats

-------;

proc format;

value racefmt 1='White'

 2='Black'

 3='Native American'

 4='Asian'

 5='Other'

 6='Unknown';

value hispanf 1='Hispanic'

2='Non-Hispanic';

value agefmt 1='Under 1 Year'

2='1-5 Years'

3='6-10 Years'

4='11-19 Years'

5='20-45 Years'

6='46-55 Years'

7='56-64 Years'

8='Over 65 Years';

value disfmt 1='Mentioned'

2='Not mentioned'

3='N/A';

value $genderf '1'='Male'

'2'='Female';

value regfmt 1='Northeast'
2='Midwest'

3='South'

4='West';

data control;

infile data1 missover;

input gender $ 1 age 2-3 race $ 4-5 hispanic $ 6-7 region $ 8 intbaswt 

9-14 fanbaswt 15-20 radiatio $ 21 chemothe $ 22;

run;

data epi;

infile data2 missover;

input gender $ 1 age 2-3 race $ 4-5 hispanic $ 6-7 region $ 8 intbaswt

9-14 fanbaswt 15-20 radiatio $ 21 chemothe $ 22;

run;

data all;

set control epi;

*----------

Age Recoded

-----------;

if age=00 then age1=1;

else if 01 <= age <= 05 then age1=2;

else if 06 <= age <= 10 then age1=3;

else if 11 <= age <= 19 then age1=4;

else if 20 <= age <= 45 then age1=5;

else if 46 <= age <= 55 then age1=6;

else if 56 <= age <= 64 then age1=7;

else if 65 <= age <= 99 then age1=8;

*----------------------

Hispanic Origin Recoded

-----------------------;

if hispanic NE '10' then hispan=1;

else if hispanic EQ '10' then hispan=2;

*------------------------

Geographic Region Recoded

-------------------------;

if region='1' then region1=1;

else if region='2' then region1=2;

else if region='3' then region1=3;

else if region='4' then region1=4;

*-----------
Race Recoded

------------;

if race='01' then racef=1;

else if race='02' then racef=2;

else if race='03' or race='04' or race='05' then racef=3;

else if race='06' or race='07' or race='08' or race='09' or

race='10' or race='11' or race='12' then racef=4;

else if race='13' or race='14' or race='15' or race='16' or

race='17' then racef=5;

else if race='99' then racef=6;

*-----------------

Treatments Recoded

------------------;

if radiatio='1' or chemothe='1' then tx=1;

else if radiatio='2' or chemothe='2' then tx=2;

else if radiatio=' ' or chemothe=' ' then tx=3;

*-----

Labels

------;

label tx='Treatment for Cancer'

age1='Age'

racef='Race'

gender='Gender'

hispan='Hispanic Origin'

region1='Geographic Region';

*-----

Weight

------;

wgt=fanbaswt/2;

run;

*-------------------------------------------------

Analysis by Age, Gender, Race, Hispanic Origin and 

Grographic Region

--------------------------------------------------;

%macro analysis;

%do i=1 %to 5;

%let j=%scan(age1@racef@gender@hispan@region1,&i,@);

proc freq data=all;

weight wgt;

tables tx*&j;

format tx disfmt. age1 agefmt. racef racefmt. 
gender $genderf. hispan hispanf. region1 regfmt.;

run;

%end;

%mend;

%analysis;
*---------------------------------------------------------------

Program Name: alcohol.sas

Author: Roger Oen, SRA Technologies, Inc. 703-205-8500

Date: 2/2/98

Input file(s): dbf file; use proc dbf to convert to a SAS data

file (Behavioral Risk Factor Surveillance

System)

Output file(s): none

This SAS program develops U.S. prevalence estimates, stratified

by age, race, ethnicity, gender, and geographic area, for

alcoholism (chronic disease subgroup).

*---------------------------------------------------------------

options ls=78;

libname info 'SAS-data-library';

proc format;

value yesnof 1='Yes'

2='No'

7='DK/NS'

9='Refused';

value oraceuf 1='White'

2='Black'

3='Asian/PI'

4='Native American'

5='Other'

7='Unknown'

9='Refused';

value racef 01='White, non-Hisp'

02='Black, non-Hisp'

03='Hisp, White'

04='Hisp, Black'

05='Other Hisp'

06='Asian/PI'

07='Native American'

08='Other'

09='Unknown/Refused';

value drinkf 1='Not at risk'

2='At risk'

9='Refused';

value agef 1='18-19 Years'

2='20-45 Years'

3='46-55 Years'

4='56-64 Years'
5='Over 65 Years';

value sextf 1='Male'

2='Female';

value statexf 01='Alabama'

02='Alaska'

04='Arizona'

05='Arkansas'

06='California'

08='Colorado'

09='Connecticut'

10='Delaware'

11='DC'

12='Florida'

13='Georgia'

15='Hawaii'

16='Idaho'

17='Illnois'

18='Indiana'

19='Iowa'

20='Kansas'

21='Kentucky'

22='Louisiana'

23='Maine'

24='Maryland'

25='Massachusetts'

26='Michigan'

27='Minnesota'

28='Mississippi'

29='Missouri'

30='Montana'

31='Nebraska'

32='Nevada'

33='New Hampshire'

34='New Jersey'

35='New Mexico'

36='New York'

37='North Carolina'

38='North Dakota'

39='Ohio'

40='Oklahoma'

41='Oregon'

42='Pennsylvania'

44='Rhode Island'

45='South Carolina'

46='South Dakota'

47='Tennessee'

48='Texas'

49='Utah'

50='Vermont'
51='Virginia'

53='Washington'

54='West Virginia'

55='Wisconsin'

56='Wyoming';

value regionf 1='Northeast'

 2='Midwest'

 3='South'

 4='West';

run;

data analysis;

set info.data-set-name;

label

hispanic='Hispanic Origin'

oraceu='Race'

race='Race/Ethnicity'

sext='Gender'

age='Age'

rfdrchrx='Chronic Drinking';

*----------

Age Recoded

-----------;

if 18 <= ageu <= 19 then age=1;

else if 20 <= ageu <= 45 then age=2;

else if 46 <= ageu <= 55 then age=3;

else if 56 <= ageu <= 64 then age=4;

else if 65 <= ageu <= 99 then age=5;

*------------------------

Geographic Region Recoded

-------------------------;

if statex in(09,23,25,33,34,36,42,44,50) then region1=1;

else if statex in(17,18,19,20,26,27,29,31,38,39,46,55) then region1=2;

else if statex in(01,05,10,12,13,21,22,24,28,37,40,45,47,48,51,54)

then region1=3;

else if statex in(02,04,08,15,16,30,32,35,41,49,53,56) then

region1=4;

run;

proc sort data=analysis;

by statex;

run;

%macro analysis;
%do i=1 %to 6;

%let j=%scan(sext@hispanic@oraceu@race@age@region1,&i,@);

proc freq data=analysis;

weight finalwtx;

tables rfdrchrx*&j / out=&j noprint;

format rfdrchrx drinkf. hispanic yesnof. oraceu oraceuf.

race racef. sext sextf. statex statexf. age agef. region1 regionf.;

by statex;

run;

proc sort data=&j;

by rfdrchrx;

run;

proc means data=&j sum;

by rfdrchrx;

var count;

class &j;

run;

%end;

%mend;

%analysis;