## 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 Di vision** 

**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 IN TRODUCTION
................................ ................................ ................................ ............... 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 S ys tems
................................ ....... 4 2.2.3 Pregnant and Lactating Women
................................ ................................ ... 5 2.2.4 Occupationall y At
- Risk Subgroup
................................ ............................... 6 3.0 SENSITIVE POPULATION DEFINITIONS AND ESTIMATES
................................ ..... 7 3.1 Chronic Disease Subgroup ................................ ................................ ....................... 7 3.2 Immunocompromised In dividuals
................................ ................................ ......... 10 3.3 Pregnant & Lactating Women
................................ ................................ ............... 11 3.4 Occupationall y 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 In dividuals
................................ ................................ ......... 28 4.3 Pregnant and Lactating Women
................................ ................................ ............. 29 4.4 Occupationall y At
- Risk Groups
................................ ................................ ............. 2 9 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. NHI S Pre
- Defined Race and Ethnicity Categories Along with Those Categories Developed for this Proj ect
................................ ................................ .......................... 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
- 1 983
................................ ................. 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 Hy pertension Attachment A7 Renal Disorders Attachment A8 Alcoholism Attachment A9 Gastric Hy peracidity Attachment A10 Thy roid Disorders Attachment A11 Ulcers Attachment B1 Acquired Immunodeficiency S yndrome (AIDS) Attachment B2 Persons Under Treatment for Cancer Attachment B3 Organ Transplant Recipients Attachment B4 Immunological Hy persensitivity Attachment C1 Pregnant Women Attachment C2 Lactating Women Attachment D1 Occupationall y At
- Risk to Biological Agents
**TABLE OF CONTENTS (continued)**iv

Attachment D2 Occupationall y At
- Risk to Chemical Agents Attachment E Detailed List of ICD
- 9 Codes from the National Health Interview Survey Attachment F List of T ypes of Organ Transplants Used to Develop Estimates of

Organ Transplant Recipients Attachment G Statistical Analys is Software (SAS) Programsv **EXECUTIVE SUMMARY**
The U.S. Environmental Protection Agenc y= s (EPA) Office of Science and Technology i s 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 b e more sensitive to the effects from chemicals or microbes present in drinking water than the general population. The Agency i s considering four major subgroups of people who may b e sensitive; the chronically i ll (including persons with diabetes, osteoporosis, anemia, liver impairments, cardiovascular disease, hy pertension, renal disorders, alcoholism, gastric hy peracidity, thy

roid disorders, or ulcers), the immunocompromised (including persons with AIDS, persons under treatment for cancer, organ transplant recipients, or the immunologically hy persensitive), pregnant and lactating women, and the occupationall y 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. F ollowing an exhaustive search for relevant data, several national health sur veys were used to develop estimates of prevalence including the 1994 National Health Interview Survey

(NHI S), the 1994 National Hospital Discharge Survey (NHDS), and the 1995 Behavioral Risk Factor Surveillance System (BRFSS). D eveloping a definition of disease using these health surveys was fairly s traightforward. E stimates of prevalence were developed and compared to existing literature, the results of which reassured us our data are relativel y accurate. Developing a definition for Aoccupationall y 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 S yndrome (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) unofficiall y 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 b e substantially

higher; they

e stimate that 7.1 million waterborne disease cases each ye ar are caused by c ontaminated 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., 19 96). On August 6, 1996, President Clinton signed into law the Safe Drinking Water Act (SDWA) Amendments, significantl y bolstering the ability o f 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. S pecifically, EPA is required to conduct a continuing program of studies to identify groups within the general population that may b e 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** : Il linois, 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, M aryl and, 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 o f sources, several of which were employed in developing comparable demographic analyses in peer reviewed publications. D emographic data on infants, children, and the elderl y who are sensitive because of age, are being developed for EP A 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. F irst and foremost, a literature/data search strategy w as developed to determine how a search for relevant data would take place. The data/literature search strategy w as 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 ass ignment provided a detailed description of the results of our search for relevant data sources. At that time, there were two primary s ources: (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 M emory ( CD
- ROM) from the National Center for Health Statistics (NCHS). H owever, further research l ed to the discovery o f 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 e ach 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 recommended3

using the NCHS. W e were told numerous times by health associations and agency representatives that the origin of the ir 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 anal ys is. Much of the hardcop y data discovered through the data search was in SRA = s library
. S everal 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 In formation 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 u sing the 1994 National Health Interview Survey (NHI S) (NCHS, 1997a). The NHI S annually c ollects health
-related information on the civilian, noninstitutionalized population residing in the U.S. D ata 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 h ospitalizations. F ield operations for the survey are conducted by

the Bureau of the Census under specifications established by

N CHS. The Bureau of the Census participates in the survey planning, selects the sample, and conducts the interviews. E ach ye ar, the NCHS produces a report which provides current estimates from the sur vey . The 1994 NHI S, 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). B RFSS 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 C DC = s National Center for Chronic D isease Prevention and4

Health Promotion (NCCDPHP). B RFSS 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. D ata are collected from a random sample of adults (one per household) through a telephone survey

and inc lude 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 provi ded later in this report. Estimates of the number of persons with **osteoporosis** were derived from the third National Health and Nutrition Ex amination Survey (NHANES III) (NCHS, 1997b). D ata collection for this survey w as 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. As ubset of that sample included 30,818 individuals who were given a physical examination at a mobile examination unit.
**2.2.2 Indivi** **duals 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 sy** **ndrome (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 S tates report AIDS cases to CDC using a uniform surveillance case definition and case report form. D ata presented in the CDC report are5

provisional. H owever, each issue of the report includes information received by C DC through the last day

o f the reporting period. AIDS data are tabulated by date of report to CDC. D ata 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. Inaddition, the 1992 NHI S 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

c ollects 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 inp atient hospital utilization. The 1994 sample consisted of 525 hospitals, 478 of which responded to the survey . M edical record data included age, sex, race, marital status, discharge status, admission and discharge dates, and length of stay for discharged patients. D iagnostic 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 NHI S described ab ove 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. In formation for **lactating women**  was obtained from the Fertility, Family Planning, and Women = s Health: New Data From the 1995 National Survey o f 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 b ased on personal interviews with a n ational sample6

of women 15
- 44 ye ars 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 emplo yed 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

s ource 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 (NI OSH, 1991). C onducted by the National Institute for Occupational Safety and Health (N IOSH), the NOES wa s a nationwide observational survey c onducted in a sample of nearl y 5,000 establishments from 1981
- 1983. The goal of the NOES was to compile data on the ty pes 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 T ables (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 chronic7 toxicity, and carcinogenicity information. This information was used in the development of estimates of workers exposed to chemical agent s. **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 e ach 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 (occupationall y at-risk), and perhaps the most difficult to characterize, was defined using a variety o f resources, the methods for which are described below. Am ore detailed description of the prevalence estimates, i.e., estimates stratified b y 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, hy pertension, renal disorders, gastric hy peracidity, thy

roid disorders, ulcers, and immunologic hy persensitivities from data provided on the 1994 NHI S. 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 h ad a particular condition. The estimate therefore includes old and new cases of disease. The data for this survey w ere 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 NHI S along with the International Classification of Disease, 9th Revision, Clinical Modifications (ICD
- 9
- CM) code captured by the NHI S disease category
. A more detailed illustration of the IC D
- 9
- CM codes captured by the NHIS category

i s 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 appropriatel y to8

the race and ethnicity categories required by E PA for this report. **Exhibit 2**  lists the NHI S 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 Hy pertension) 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 Hy pertension 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 NHI S Category Renal Disorders Kidney Infections 590.0
- 99 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. W e 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. F or 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 anal ys es.

**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 al so available on CD
- ROM. S urvey p articipants were asked if they had ever been told by

a doctor that they h ad osteoporosis. With respect to race, NHANES III had three race categories; white, black, and other. F or ethnicity, we considered AMexican
-American @ and AOther Hispanic @ to be AHispanic. @
**3.2 Immunocompromised Individuals**  Aside from persons considered immunologicall y hy persensitive 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. E stimates 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. A s a result, we used the number of AIDS cases from July, 1996
- June, 1997, taken from the 1997 HIV/AIDS Surveillance Report developed by C DC. This report contains AIDS cases reported to the CDC by s tate and local health departments. According to that report, the original definition was modi fied in 1985 and 1987, and the case definition for adults and adolescents was modified again in 1993 (CDC, 1997). Abroader range of AIDS
- indicator diseases and conditions including the use of HIV diagnostic tests were incorporated to increase the specifi city and sensitivity

of the definition. Included in the report cited above are those persons known to be infected with human immunodeficiency virus ty pe 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 A Native 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 IC D
- 9
- CM hospital procedure code and stratified the data according to the variables of interest. Al ist of the ty pes of organ transplants included in our estimates of organ transplant recipients can be found in **Attachment F** 
. Our anal ys es onl y 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 fol lows: AWhite @ ; ABlack @ ; AAmerican Indian/Eskimo @ which we considered as A

Native American @ ; AAsian/Pacific Islander @ which we considered as AAsian @ ; AOther @ ; and A Not 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 ye ar= s survey included information on cancer control and epidemiology
. The supplement included proc edures performed to treat cancer including chemotherap y and radiation, i.e., in each household, a sample adult respondent was randomly s elected to complete one of two cancer supplements. Randomly selected individuals were asked to respond to the following question: What are the ty pes of treatment for the only

or most recent cancer? Options for a response included surgery, chemotherap y, 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

c ompromise an individual = s immune system. With respect to race and ethnicity, the definitions provided for the 1992 NHI S are the same as those used in the 1994 NHI S 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 includes12

live births, induced abortions, and fetal losses. The 1996 Statistical Abstract of the U.S. contained the following race/ethnicity groupings: A

Non
- Hispanic, White @ which we considered as AWhite @ ; A

Non
- Hispanic, Black @ which we considered as ABlack @ ; and AHispanic. @ For estimating the number of lactating women, the 1995 National Survey o f 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). W e 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 Abs tract 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 In dian @ which we considered as A Native American @ ; and AAsian or Pacific Isl ander @ 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.** Inthe 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 and13

assumes that the occupational and drinking water routes of exposure are the same or complementary
. W e 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 Virus**  **es** 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** 
. U sing 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 NO ES was an observational survey c onducted 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 such14

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 actuall y observed working with an agent. W e believe that the estimates in **Exhibit 4**  are likely to be dominated by

l aboratory

or related personnel, because the surveyor could clearl y document that an agent was being use d or was present at the work site. Potential exposures occurring among health workers, agricultural workers, day c are providers, or other groups which are known to be exposed to pathogens would presumably go unnoticed or unrecorded in this survey.
**Exhibi t 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 aure us 7,685 Yersinia 1,42315 **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 potentiall y 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 Wo rkplace (Wald and Stave, 1994), which specificall y 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 W ald 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 (BL S) (Bureau of the Census, 1996). The estimates of the number of workers potentially expose d 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. E stimates 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 fre sh water, thermal springs, bodies of water warmed by industrial plants, hot tubs, spas or16 inadequately maintained swimming pools a

Cryptosporidium parvum GI tract, respiratory tract b Farmers, 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, l aboratory 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 Pseu domonas 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 and17 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 o ccupations, 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 onl y crude approximations of those that were identified by W ald and Stave (1994) in **Exhibit 5** 
. Age data and regional estimates were also not available in the summary t ables 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. **E xhibit**  **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 anal ys es of the regulatory development process for disinfectants and DBP. Potentially

s ensitive groups were defined as those who might be sensitive by virtue of additivity o f exposure or additivity o f effect. In the case of the former, there are workers involved in occupations that are already exposed to disinfectants or DBP through various ty pes 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 workp lace 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. W e were conf ronted 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. As tarting 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 occupation s 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 o f 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). W e used the FY
- 97 Annual HEAST to identify organ systems that had been affected in subchronic or chronic toxicity a ssays or carcinogenicity a ssays. 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 t ables, usually

onl y 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 f ull range of doses, was important because sources, such as SAX's Dangerous Properties of Industrial Materials (Lewis, 1992) or the NI OSH/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 -**  **Produc ts 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 the20

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. The se 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 liste d substances presented in **Exhibit 7**  represented ingestion routes of exposure. W e 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 Tar get 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
. F or this screening process, Appendix A of the text entitled A Practical Approach to21

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 M cCunney

( 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, explosive s, 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; chemi cal22 **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 f or 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
Dimethyl formamide 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 mo nomethyl 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 wide ly 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 of24 **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 "chemicall y sensitive" workers as were used for estimating the workers with exposures to biological disease agents. Initially, we examined the NOES and found that many o f 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 Disinfecta**  **nts 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 95,77825 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 surv ey 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 BL S 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 o ccupational settings/industries in **Exhibit 8**  and identified categories of workers in the BL S 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. G enerall y, when detailed data summaries were available from the data sources, the data were stratified by variables exactly

l ike those required by

the work assignment. D ata provided on CD
- ROM were organized for Statistical Analysis Software (SAS) use by the NCHS (SAS is a widely u sed computer package that provides epidemiologists and biostatisticians with the ability to analyze data). D ata available on CD
- ROM were manipulated using programs written solely f or the purpose of developing descriptive statistics. In order to anal yz e the data on CD
- ROM using26

SAS, the data were first converted into American Standard Code for In formation 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. U suall y, 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. E stimates 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 **Exhi bit**  **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 7,76 5,981 259,633,000 a 3.0 Osteoporosis 1988
- 94 3,703,302 251,097,002 b 1.5 Anemia 1994 4,664,365 259,633,000 a 1.8 Liver Impairments 1994 594,960 259,633,000 a 0.2 Cardiovascular Disease 1994 22,279,451 259,633,000 a 8.6 Hy pertension 1994 28,236,261 259,633,000 a 10.9 Renal Disorders 1994 2,068,952 259,633,000 a 0.8 Alcoholism (chronic drinking) 1995 5,048,448 not available 2.8 c Gastric Hyperacidity 1994 6,956,917 259,633,000 a 2.7 Thyroid Disorders 1994 4,508,78 0 259,633,000 a 1.7 Ulcers 1994 4,447,035 259,633,000 a 1.727

AIDS 1997 64,966 267,645,000 d 0.02 Cancer Treatment Patients 1992 1,853,795 248,754,000 e 0.8 Organ Transplant Recipients 1994 17,095 258,932,000 f 0.01 Immunological Hyper sensitivity 1994 40,707,827 259,633,000 a 15.7 Pregnant Women 1991 6,272,000 129,187,000 g 4.9 Lactating Women 1990
- 93 2,247,635 129,813,000 h 1.7 Occupationally At
- Risk 1995 13,891,000 263,034,000 i 4.4 (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 occupationall y 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 briefl y 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 siz e. Several diseases/conditions for which a health survey was used to obtain data have unbelievabl y low values, i.e., zero values, for some age groups and race groups. W e believe that the zero values may b e an artifact of the survey and may reflect instanc es in which the survey h ad few or no responses in an age category and therefore scaled
-up estimates for the country c ould not be made. Amore 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, hy pertension, renal disorders, gastric hy peracidity, thy

roid disorders, and ulcers were developed independentl y using the 1994 National Health Interview Survey (NCHS, 1997a). E stimates developed from this survey p ertain onl y 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 ty

pically u sed 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 b e 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 NHI S estimates may not represent a complete measure of any given condition b ecause 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 o r 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 dev eloping estimates were designed to capture information on all health problems being experienced by the interviewed population. Thus, a person could be experiencing hyp ertension and diabetes and be counted in both categories. Estimates developed for oste oporosis 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 b e cost- efficient, eas y to administer and eas y to monitor. However, telephone interviews also might have higher levels of non- coverage than in
-person interviews because a small perc entage 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 b y the CDC (CDC, 1997). This data may b e limited by

changes in the definition of AIDS over time. H owever, 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 immunologicall y hy persensitive are subject to the same limitations as those described above for the NHI S. Persons under treatment for cancer were obtained from the NHI S 1992 supplement. These estimates may

also be subject to limitations like those described above for the 1994 NHIS. Also, the 1992 NHI S ended the second week in the third quarter of that ye ar because of budgetary constraints; this may

have resulted in an underestimate of persons being treated for cancer.
**4.3 Pregnant a**  **nd Lactating Women** A surrogate measure for pregnancies was used b y the 1996 Statistical Abstract of the U.S. (Bureau of the Census, 1996) and includes live births, stillbirths, and abortions. Asurrogate measure f or 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 Famil y 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 QUALIT**  **Y CONTROL (QC)** Inherent in the development of any project is the requirement to perform a review of the data presented. W e have conducted a thorough review of the data presented in this report to ensure the information w e obtained is well represented. One of the sources of relevant data discovered earl y in our search for information included a report by

Adams and Marano (1995). These authors use the 1994 NHI S to develop estimates of prevalence for selected chronic con ditions. 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 favorabl y with estimates developed by Adams and Marano (1995). F or example, their estimate for hy pertension in the U.S. in 1994 of 28,236,000 persons matches the total estimate we provide of 28,236,261 person s. 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 correctl y abstracted. The Statistical Abstract of the United States (Burea u of Census, 1996) estimates that 28,236,000 persons suffered from hy pertension nationwide in 1994. They c ite the report developed b y 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. H owever, estimates for the number of persons currentl y under the treatment for cancer and for persons considered occupationally atrisk persons were not discovered. A s 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 speci fic subgroups that may b e at increased risk of adverse health impacts when substantive changes in water quality o ccur. Currently

EPA is considering changes in the31

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

f rom microbial food borne and waterborne disease (Gerba et al., 1996). G erba 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 A sensitive @ are considered in this report including immunocompromised individuals, AIDS p atients, and transplant organ patients. The results of this project are descriptive in nature. M any of the estimates of chronic disease categories provided in this report are estimates of prevalence. C ompared to incidence which measures the probability that otherwise healthy

p eople 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. P oint 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 previousl y, we successfull y generated very s imilar estimates using the same sources of data. In situations in which we chose an alternative source of data (a more recent survey f or example), we continued to make comparisons with estimates from previous research and developed similar results. F or 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, P iccinino L. 1 997. Fertility, family p lanning, and women = s health: New data from the 1995 National Survey o f Famil y 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 Abs tract of the United States: 1996. 1 16th 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 Surveilla nce Report, 1997;9(No.1):[5,8
- 12]. Centers for Disease Control and Prevention. 1 995. N ational Center for Chronic Disease Prevention and Health Promotion, Behavioral Surveillance Branch: 1984
- 1995 Behavioral Risk Factor Surveillance S ys tem [database on C D
- ROM]. CD
- ROM Series 1, No. 1. Collins, JG. 1 997. Prevalence of selected chronic conditions: United States, 1990
- 1992. NCHS. Vital Health Stat 10(194). Gerba CP, Rose JB, and Haas CN. 1 996. S ensitive populations: who is at the greatest risk? I nternat J Food Microbiol 30: 113
- 123. Kramer MH, Herwaldt BL, et al. 1 996. S urveillance for waterborne
- disease outbreaks
- United States, 1993
- 1994. Morbidity and Mortality W eekly Report 45 (SS
- 1): 1
- 33. Lewis RJ. 1992. SAX's Dangerous Properties of Industrial Materials. E ighth edition. V an Nostrand Reinhold, New York. Marshall MM, Naumovitz, et al. 1 997. W aterborne protozoan pathogens. Clin Microbiol Rev 10: 67
- 85. McCunney

RJ. 1 994. A Practical Approach to Occupational and Environmental Medicine. Appendix A. S econd 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 (N IOSH). 1991. National Occupational Exposure S urvey

(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
. S tate - 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
. 1 997. H ealth Effects Assessment Summary T ables. EPA/540/R
- 97/036. National Center for Environmental Assessment, Cincinnati, Ohio. U.S. Environmental Protection Agency
. 1 988. C omparative Health Effects of Drinking Water Treatment Te chnologies. EPA 570/9
- 88
- 009. Office of Drinking Water, Washington, D.C. Wald PH, and Stave GM. 1 994. Physical and Biological Hazards of the Workplace
. V an Nostrand Reinhold, New York.



### Attachments A1
- A11 Chronic Disease Subgroup34 **Attachmen t A1**  

### Chronic Disease Subgroup 

### D **IABETES**
Data Source Description: Diabetes prevalence data are for the ye ar 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 b y 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**  **P revalence**  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 Prevalenc**  **e** Hispanic 742,658 Non
- Hispanic 7,023,32335 **Attachment A2** 

### Chronic Disease Subgroup 

### O **STEOPOROSIS**

Data Source Description: The data provided below were derived from the third National Health and Nutrition Examination Survey

(NHANES III) conducted between 1988
- 1994. D ata were not available (n/a) for Asians, and Native Americans, several of the age categories, and geographical areas of the U.S. Z ero 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 b y 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 3,578,01536 **Att achment A3**  

### Chronic Disease Subgroup 

### A**NEMIA**
Data Source Description: Prevalence data for anemia are for the ye ar 1994 and were obtained from the National Health Interview Survey

(NHIS).
Prevalence Estimates b y Selected Variables:

**Age Groups Pre** **valence 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 4,011,07937 **Attachment A4** 

### Chronic Disease Subgroup 

### L **IVER** 

### I **MPAIRMENTS**

Data Source Description: Prevalence data for liver impairments are for the ye ar 1994 and were obtained from the National Health Interview Survey (NHIS). Z ero values may represent an artifact of the survey and may reflect instances in which the survey h ad few or no responses in an age category and therefore scaled
-up estimates for the country could not be made.
Prevalence Estimates b y 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 67,2 31 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 499,2 59 West 194,296 Unknown 0 Other 0 **Ethnicity Prevalence**  Hispanic 47,742 Non
- Hispanic 547,21838 **Attachment A5** 

### Chronic Disease Subgroup 

### C **ARDIOVASCULAR** 

### D **ISEASE**

Data Source Description: Cardiovascular disease prevalence data are for the year 1994 and were obtained from the National Health Interview Survey (NHI S).
Prevalence Estimates b y 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**  **Preva lence**  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 20,871,26139 **Attachment A6** 

### Chronic Disease Subgroup 

### H**YPERTENSION**

Data Source Description: Hy pertension prevalence data are for the year 1994 and were obtained from the National Health Interview Survey

(NHIS).

Prevalence Estimates b y 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 28 3,562 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 26,488,19340 **Attachment A7** 

### Chronic Disease Subgro **up** 

### R**ENAL** 

### D **ISORDERS**

Data Source Description: Prevalence data for renal disorders are for the year 1994 and were obtained from the National Health Interview Survey (NHIS). Z ero values may represent an artifact of the survey and may reflect instances in which the survey h ad few or no responses in an age category and therefore scaled
-up estimates for the country could not be made.
Prevalence Estimates b y 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 1,834,55141 **Attachment A8** 

### Chronic Disease Subgroup 

### A**LCOHOLISM** 

### ( **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. D ata were not available (n/a) for persons under 18 ye ars of age and for the State of California and the District of Co lumbia.

Prevalence Estimates b y 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 ** Doe s not include California42 **Attachment A9** 

### Chronic Disease Subgroup 

### G**ASTRIC** 

### H**YPERACIDITY**

Data Source Description: Prevalence data for gastric hy peracidity

are for the ye ar 1994 and were obtained from the National Health Interview Survey (NHIS). G astric hy

peracidity

does not include ulcers, which is considered a separate disease subgroup of interest. Z ero 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 c ould not be made.

Prevalence Estimates b y 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 

### T **HYROID** 

### D **ISORDERS**

Data Source Description: Prevalence data for thy

roid disorders are for the ye ar 1994 and were obtained from the National Health Interview Survey (NHIS). Z ero values may represent an artifact of the surv ey and may reflect instances in which the survey h ad few or no responses in an age category and therefore scaled
-up estimates for the country could not be made.
Prevalence Estimates b y 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**  **Geograp hic**  **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 Preva** **lence** Hispanic 246,658 Non
- Hispanic 4,262,122**Attachment A11** 

### Chronic Disease Subgroup 

### U**LCERS**
Data Source Description: Prevalence data for ulcers are for the ye ar 1994 and were obtained from the National Health Interview Sur

vey (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 b y Selecte d 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 1 8,406 Other 136,489 **Ethnicity Prevalence**  Hispanic 375,517 Non
- Hispanic 4,071,518

### Attachments B1
- B4 Immunocompromised Individuals**Attachment B1** 

### Im **mu nocom** 

**prom ised Subgroup**  

### A **CQUIRED** 

### I **MMUNODE FICIENCY**  

### S **YNDROME** 

### (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 s tate and territorial health departments from July, 1996 to June, 1 997. The report did not provide the age breakdowns of interest. A s a result, the data obtained were categorized in similar groups as those requested in the work assignment.

Prevalence Estimates b y Selected Variables:

**Age Groups Prevalence**  **Gend er**  **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** 

### Im **mu nocom** 

**prom ised Sub** 

**group** 

### P **ERSONS** 

### U**NDER** 

### T **REATMENT** 

### F **OR** 

### C **ANCER**

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 2,1 87 **Ethnicity Number**  Hispanic 85,572 Non
- Hispanic 1,768,223**Attachment B3** 

### Im **mu nocom** 

**prom ised Subgroup**  

### O **RGAN** 

### T **RANSPLANT** 

### R**ECIPIENTS**

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. D ata on children <1 ye ar of age and on ethnicity c ould 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 Numb**  **er 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** 

### Im **mu nocom** 

**prom ised Subgroup**  

### I **MMUNOLOGICAL** 

### H**YPERSENSITIVITY**

Data Source Description: Prevalence data for immunological hy persensitivities are for the year 1994 and were obtained from the National He alth Interview Survey (NHIS).
Prevalence Estimates b y 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 1 8,260,033 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**A ttachment**  **C1** 

### P **REGNANT** 

### W **OMEN**

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 b y the work assignment. As a result, simi lar 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** 

### L **ACTATING** 

### W **OMEN**

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. W e 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 b y Selected Variables:

**Age Groups Number of** 

**Live Births (1990**  **- 1993)**  **Number of**

**Live Births (annualized)**  **Percent**

**Lactating Estimated Number of** 

**Lactating Wom en**  **(annualized)** <20 2,084,000 521,000 36.0 187,56 0 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** 

### O **CCUPATIONALLY** 

### A **T** 

### - **R ISK**  

### T **O** 

### B **IOL OGICAL**  

### A **GENTS** Data Source Description: Numbers of workers were obtained from the 1996 Statistical Abstract of the U.S. The estimates are for the ye ar 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**  **Fem ales**  **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 Kitche n 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 16,6 32 379,368 330,660 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** 

### O **CCUPATIONALLY** 

### A **T** 

### - **R ISK**  

### T **O** 

### C **HE MICAL**  

### A **GENTS** Data Source Description: Numbers of workers were obtained from the 1996 Statistical Abstract of the U.S. The estimates are for the ye ar 1995 and include production workers onl y. D ata are not available for the gender and race groups reques ted 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 equip me nt 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 31,000Petroleum 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 SurveyWork 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 28 0.1 280.8 280.9 281 281.0 281.1 281.2 281.3 281.4 281.8 281.9 282 282.0 282.1 282.2 282.3 282.4 282.5 282.6 282.7 282.8 282.9 283 283.0 283.1 283.2 283.9 284 284.0 284.8 284.9 285 285.0 285.1 285.8 285.9 Iron deficiency anemias Secondary to blood lo ss (chronic) Secondary to inadequate dietary iron intake Other specified iron deficiency anemias Iron deficiency anemia, unspecified Other deficiency anemias Pernicious anemia Other vitamin B 12 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 Apl astic anemia, unspecified Other and unspecified anemias Sideroblastic anemia Acute posthemorrhagic anemia Other specified anemias Anemia, unspecifiedWork 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, unspecifi ed Atrial fibrillation and flutterWork 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 Tran sposition 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 Hy poplastic left heart syndrome Other Selected Diseases of Heart (Excludes Hy pertension) 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 pulmon ary heart disease Primary pulmonary hypertension Ky phoscoliotic heart disease Other diseases of pulmonary circulation Arteriovenous fistula of pulmonary vessels Aneurysm of pulmonary artery Other specified diseases of pulmonary circulation Unspecified dise ase 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 Hy pertension) (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 pericarditisWork 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 Hy pertrophic 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
- defin ed 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 dise ases Heart disease, unspecified Hy pertension 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 Hy pertensive heart disea se Malignant Benign Unspecified Hy pertensive renal disease Malignant Benign Unspecified Hy pertensive heart and renal disease MalignantWork 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 59 0.1 590.2 590.3 590.8 590.9 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 membranop roliferative 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 specifie d 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 n ecrosis 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 NephroptosisWork 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 Hy pertrophy 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 sp ecified 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 uninodul ar 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 ori gin 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 orWork 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 unspecifi ed 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 Hy persensitivity 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

L ist 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 Com bined 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 (NHANE S 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 L S=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
- 1 0 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 M ISSOVER; *NHANES III variable names and positions have been omitted here due to length. They c an 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 i f 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 FRE Q 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) Out put 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 procf 1='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', '50 5
- ', '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 anal ys is; %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; %anal ys is;*
----- ----------------------------------------------------------

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, thy

roid disorder, anemias, renal disorders, liver impairment, gastric hypersensitivities, ulcers, cardiovascular di sease, 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 Hy pers.' 3='Ulcers'; value disfmtc 1='Cardiovascular Dis.'

2='Hy pertension'; value disfmtd 1='Immuno. Hy persen.'; 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

- 2 7 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 andGeographic Region

-------------------------------------------------- ; %macro anal ys is; %do i=1 %to 5; %let j=%scan(age1@racef@gender@hispan@region1,&i,@); proc freq data=cond1; weight wgt; table s disease*&j; format age1 agefmt. racef racefmt. gender $genderf. hispan hispanf. region1 regfmt. disease disfmta.; run; %end; %mend; %anal ys is; 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 anal ys is; %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; %anal ys is; 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 dise ase=2; %macro anal ys is; %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; %anal ys is; data cond4; set cond;
*
--------- Subsetting

---------- ; if cacode='1' and condlist='6';
*
------------------------ Chronic Condition Recoded

------------------------- ; if c1condrc in('602','603') then dis ease=1; %macro anal ys is; %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; %anal ys is; data cond5; set cond;
*
--------- Subsetting

---------- ; if cacode='1' and condlist='1';
*
------------------------- Chronic Condition Recoded

-------------------------- ; if c1condrc='107' then disease=1 ; %macro anal ys is; %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. dise ase disfmte.; run; %end; %mend; %anal ys is;*
---------------------------------------------------------------

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 anal ys is; %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; %anal ys is;*
--------------------------------------------------- ------------

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='H isp, 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' 3 7='North Carolina' 38='North Dakota' 39='Ohio' 40='Oklahoma' 41='Oregon' 42='Penns ylvania' 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='Wiscon sin' 56='Wyoming'; value regionf 1='Northeast'

2='Midwest' 3='South' 4='West'; run; data anal ys is; 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=anal ys is; by statex; run; %macro anal ys is;%do i=1 %to 6;

%let j=%scan(sext@hispanic@oraceu@race@ag e@region1,&i,@); proc freq data=anal ys is; 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; %anal ys is;