Data on Health and Well-being of American Indians, 

Alaska Natives, And Other Native Americans 

Data Catalog 

Contract No. 233-02-0087

Prepared for: 

U.S. Department of Health and Human Services 

Office of the Assistant Secretary for Planning and Evaluation 

Office of Human Services Policy 

200 Independence Avenue, S.W. 

Washington, D.C. 20201 

Prepared by: 

Westat 

1650 Research Boulevard 

Rockville, MD 20850 

December 2006 

This report was produced under the direction of Alana 

Landey and Peggy Halpern, Task Order Officers, Office of 

the Assistant Secretary for Planning and Evaluation, Office of 

Human Services Policy, Jerry Regier, Principal 

Deputy/Assistant Secretary for Planning and Evaluation. 

This report is available online at: 

http://aspe.hhs.gov/hsp/06/Catalog-AI-AN-NA
Acknowledgments 

 This catalog was prepared by staff from Westat, the American Indian Health 

Research Program of Black Hills State University, and L&M Policy Research, LLC. Peggy 

Halpern and Alana Landey of the Office of the Assistant Secretary of Planning and 

Evaluation (ASPE), United States Department of Health and Human Services (DHHS), 

served as Task Order Officers for this effort and provided input and guidance to the project. 

Canta Pian, director of the Division of Economic Support for Families in ASPE’s Office of 

Human Services Policy, provided review and comment on this report. 

 Three members of the DHHS Data Council’s Racial and Ethnic Data Working 

Group—Audrey Burwell, Dale Hitchcock, and Edna Paisano—served on a project 

workgroup and provided guidance to the project as well as review of this catalog. Several 

members of an American Indian, Alaska Native, and other Native American workgroup also 

provided input and review, including David Wong and Ralph Bryan representing the CDC 

Office of Minority Health and Health Disparities and the IHS Division of Epidemiology and 

Disease Prevention, David Simmons representing the National Indian Child Welfare 

Association, and Lisa Oshiro representing the Council for Native Hawaiian Advancement. 

 We also benefited from input from several external consultants to the project, 

including Gordon Belcourt, Executive Director of the Montana-Wyoming Tribal Leaders 

Council; Carole Anne Heart, Executive Director of the Aberdeen Area Tribal Chairmen’s 

Health Board; Jeff Henderson, President of the Black Hills Center for American Indian 

Health; Lilia Kapunai, Vice President of Council for Native Hawaiian Advancement; and 

Frank Ryan, independent consultant. Numerous knowledgeable individuals at DHHS and 

other federal and non-federal organizations gave generously of their time to ensure that we 

had complete and up-to-date information on existing surveys and databases. We appreciate 

the careful review of the data catalog and data source profiles conducted by all these 

individuals. 
Table of Contents 

Section Page

1. Background.......................................................................................................... 1-1 

2. Catalog Description ............................................................................................. 2-1 

2.1 Catalog Organization ........................................................................................ 2-3 

2.2 Methodology..................................................................................................... 2-5 

2.3 Using These Data Sources ................................................................................ 2-7 

3. Data Sources by Topical Area ............................................................................. 3-1 

4. Data Sources by Subpopulation Coverage........................................................... 4-1 

5. Listing of Data Sources........................................................................................ 5-1 

A Picture of Subsidized Households (1998)............................................................... 5-2 

Adoption and Foster Care Analysis and Reporting System (AFCARS) .................... 5-4 

American Community Survey (ACS)......................................................................... 5-8 

American Housing Survey (2003) ............................................................................ 5-12 

American Housing Survey: Metropolitan Surveys ................................................... 5-15 

Annual Survey of Jails (ASJ).................................................................................... 5-19 

Behavioral Risk Factor Surveillance System (BRFSS) ............................................ 5-22 

CAHPS Health Plan Survey Response Data............................................................. 5-25 

California Health Interview Survey (CHIS) ............................................................. 5-29 

Census 2000 .............................................................................................................. 5-33 

Census 2000 - The American Indian and Alaska Native Summary File .................. 5-38 

Census of Agriculture (2002).................................................................................... 5-41 

Census of Jails........................................................................................................... 5-44 

Census of Tribal Justice Agencies in Indian Country (2002) ................................... 5-47 

Consumer Expenditure Surveys (CE) Interview and Diary Surveys........................ 5-49 

Current Population Survey (CPS)............................................................................. 5-53 

Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) ................................ 5-58 

Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K)... 5-63 

Food Stamp Quality Control Database (FSPQC) ..................................................... 5-67 

Hawaii Health Survey (HHS) ................................................................................... 5-70 

Head Start Program Information Report................................................................... 5-73 

Health and Retirement Study (HRS)......................................................................... 5-75 

Health Behavior in School-aged Children (HBSC) .................................................. 5-78 

Health Information National Trends Survey (HINTS) ............................................. 5-81 

Integrated Postsecondary Education Data System (IPEDS)..................................... 5-83 

Medicaid Analytic Extract (MAX) ........................................................................... 5-85 

Medical Expenditure Panel Survey (MEPS)............................................................. 5-88 

iii
Table of Contents (continued) 

Section Page

Medicare Denominator File ...................................................................................... 5-92 

Medicare Utilization – Standard Analytic Files (SAFs) ........................................... 5-94 

National Aging Program Information Systems (NAPIS) State Program Reports .... 5-96 

National Ambulatory Medical Care Survey (NAMCS)............................................ 5-98 

National Assessment of Adult Literacy (NAAL) ................................................... 5-101 

National Child Abuse and Neglect Data System (NCANDS) ................................ 5-104 

National Crime Victimization Survey (NCVS) ...................................................... 5-108 

National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) . 5-111 

National Health Interview Survey (NHIS) ............................................................. 5-114 

National Hospital Ambulatory Medical Care Survey (NHAMCS) ........................ 5-117 

National Household Education Surveys Program (NHES)..................................... 5-120 

National Household Travel Survey (NHTS)........................................................... 5-125 

National Indian Education Study (NIES)................................................................ 5-130 

National Longitudinal Mortality Study (NLMS).................................................... 5-133 

National Mortality Followback Survey (NMFS).................................................... 5-135 

National Survey of America’s Families (NSAF).................................................... 5-137 

National Survey of Child and Adolescent Well-being (NSCAW) ......................... 5-142 

National Survey of Family Growth (NSFG)........................................................... 5-146 

National Survey of Veterans (NSV) ....................................................................... 5-150 

National Survey on Drug Use and Health (NSDUH) ............................................. 5-153 

National Vital Statistics System: Linked Birth-Infant Death (NVSS-I)................. 5-156 

National Vital Statistics System: Mortality (NVSS-M).......................................... 5-159 

National Vital Statistics System: Natality (NVSS-N) ............................................ 5-162 

Panel Study of Income Dynamics (PSID) .............................................................. 5-164 

Pediatric Nutrition Surveillance System (PedNSS)................................................ 5-167 

Pregnancy Nutrition Surveillance System (PNSS) ................................................. 5-169 

Pregnancy Risk Assessment Monitoring System (PRAMS) .................................. 5-171 

Resource and Patient Management System (RPMS) ............................................. 5-174 

Runaway and Homeless Youth Management Information System (RHYMIS)..... 5-177 

Small Area Income and Poverty Estimates (SAIPE).............................................. 5-180 

Surveillance, Epidemiology, and End Results (SEER) .......................................... 5-183 

Survey of Jails in Indian Country (SJIC)................................................................ 5-186 

Survey of Program Dynamics................................................................................. 5-188 

Temporary Assistance for Needy Families (TANF) and Tribal TANF.................. 5-191 

Tobacco Use Supplement to the Current Population Survey (TUS-CPS).............. 5-194 

Treatment Episode Data Set (TEDS)...................................................................... 5-199 

Uniform Crime Reports (UCR)............................................................................... 5-202 

iv
Table of Contents (continued) 

Section Page

United States Renal Data System (USRDS)........................................................... 5-205 

Washington State Population Survey (WSPS) ....................................................... 5-207 

Youth Gangs in Indian Country.............................................................................. 5-209 

Youth Risk Behavior Surveillance System (YRBSS) ............................................ 5-211 

6. Other Data Sources .............................................................................................. 6-1 

7. Other Reports....................................................................................................... 7-1 

Appendices 

Appendix A: Glossary.................................................................................................. A-1 

Appendix B: Data Set Aggregation ..............................................................................B-1 

Appendix C: Review Protocol ......................................................................................C-1 

Appendix D: List of Sponsoring Agencies .................................................................. D-1 

Figure and Tables 

Figure 1.1 Key Data Catalog Policy Issues..................................................................... 2-2 

Table 1. Data Sources by Policy Issue......................................................................... 3-1 

Table 2. Data Sources by Subpopulation Coverage: American Indian/Alaska 

Native............................................................................................................. 4-1 

Table 3. Data Sources by Subpopulation Coverage: Native Hawaiian/Other 

Pacific Islander............................................................................................... 4-4 

v

Data on Health and Well-being of American Indians, 

Alaska Natives and Other Native Americans: Data Catalog 

1. Background 

 

The Study of Data on Health and Well-being of American Indians, Alaska Natives, and other 

Native Americans (AI/AN/NAs) was funded by the Department of Health and Human Services’ 

(DHHS) Office of the Assistant Secretary for Planning and Evaluation (ASPE) to address the need for 

systematic information about available data sources pertaining to the health and well-being of 

AI/AN/NA populations. This study examined numerous existing databases—federal surveys, research 

survey databases, state and community surveys, and administrative databases—that include 

information on AI/AN/NA population characteristics and measures of health and well-being. The 

study team documented the nature of these databases, including their strengths and limitations, and 

collated the information into this data catalog. In the course of a systematic review, the study also 

shed light on the limitations and gaps in available data on the health and well-being of AI/AN/NA 

populations. The second component of this project, a paper entitled Report on Gaps in Data, 

Initiatives Underway, and Strategies for Improving AI/AN/NA Data for Policy and Research 

describes these limitations and gaps and identifies possible strategies to improve the quality, 

usefulness, and population and geographic coverage of data on AI/AN/NA health and well-being.1

This study continues DHHS’ focus on improving data collection concerning the health and 

well-being of racial and ethnic populations. The current study builds on previous activities, including 

the 1999 Joint Report of the DHHS Data Council’s Working Group on Racial and Ethnic Data and 

the Data Workgroup of the DHHS Initiative to Eliminate Racial and Ethnic Disparities in Health 

entitled Improving the Collection and Use of Racial and Ethnic Data in DHHS. It also expands on the 

activities conducted during an earlier study for ASPE entitled Assessment of Major Federal Data Sets 

for Analyses of Hispanic and Asian Pacific Islander Subgroups and Native Americans. 2

This data catalog focuses on data sources that provide information on the health and wellbeing of AI/AN/NA populations. The catalog is intended for use by a wide variety of users including 

AI/AN/NA communities; researchers from government, academic institutions, and foundations; and 

policy makers. The catalog provides overview information on possible data sources that could be used 

to describe the need for services, analyze trends in well-being and health, or illuminate disparities. 

Some of the data sources profiled in this catalog supply only published tables for the user. Others can 

be used by those with the necessary analytical skills and tools to do analysis on specific questions. 

The profiles of data sets presented in this catalog are not meant to provide instruction for use of the 

data in addressing specific research questions, but instead to serve as a source of general information 

that will help potential users determine if further investigation of a data source is warranted. The 

catalog also provides contact information and data source locations for conducting further in-depth 

reviews of targeted data sources. 

The populations covered by this catalog are American Indians, Alaska Natives, and other 

Native Americans including Native Hawaiians and other Pacific Islanders. While each data source 

profiled here may collect information on the race of the respondents differently, it is helpful to keep 

in mind some generally accepted definitions of the key racial groups included in this catalog. 

 

1

 This paper will be available online in the future. 

2

 Reports from this effort are available at http://aspe.hhs.gov/datacncl/racerpt/ and 

http://aspe.hhs.gov/HSP/minority-db00/task2/index.htm. 

1-1 
American Indians (AI) and Alaska Natives (AN) are defined by the U.S. Census Bureau as “people 

having origins in any of the original peoples of North and South America (including Central 

America), and who maintain tribal affiliation or community attachment.”3

 For purposes of 

measuring, monitoring, and developing approaches to reducing disparities in health and well-being 

and for research on a range of issues related to health and well-being, there may be interest in 

information on the combined AI/AN group for some purposes and in information on specific 

subgroups of the population for other purposes. For this reason, this data catalog includes information 

on the availability of data on the combined AI/AN category as well AI and AN as separate groups and 

AI/AN who are members of federally or state-recognized tribes. The catalog also notes the 

availability of information on those who self report that they are AI/AN alone or AI/AN in 

combination with other races. Finally, because there may be interest in identifying those American 

Indians who live on reservations, the reviewers examined each data source to determine if reservation 

of residence was available in that data source. 

The Native Hawaiian (NH) and other Pacific Islander (PI) population includes those who are 

members of any of the native peoples of Hawaii and native peoples of Pacific Insular Areas that are 

dependent territories of the U.S. (Guam, American Samoa, and the Northern Mariana Islands) or 

Freely Associated States for which the U.S. provides defense, funding grants, and social services to 

its citizens (Micronesia, Palau, and the Marshall Islands). Within the NH/ PI population, there are 

several ethnically distinct categories. Polynesians, including Native Hawaiians, Samoans, Tongans, 

Tahitians, Tuvaluans, and Maori, are the largest group, accounting for 65 percent of all NH/PIs. 

Micronesians, including Guamanians, Marshallese, Palauans, residents of the Northern Mariana 

Islands and of the Federated States of Micronesia, are 13 percent of all NH/PIs. Melanesians, 

including Fijians, New Caledonians, Solomon Islanders, Vanuatuans, and Papua New Guineans, are 2 

percent of this population.4 In 1997, the Office of Management and Budget established a new racial 

category, Native Hawaiian and Pacific Islander (NH/PI), and required that federal agencies collect 

information on this new race category by 2003. The 2000 Census included the NH/PI race category 

and, as a result, provides an initial baseline for assessing socioeconomic status and some limited 

health measures of this group.5

 

3

 U.S. Census Bureau, “The American Indian and Alaska Native Population: 2000.” Census 2000 Brief, 

February 2002, page 2. 

4

 Panapassa, S.V. “The Health of U.S. Pacific Islander Populations: Emerging Directions.” Presentation, May 

2005. 

5 Ibid.

1-2 
2. Catalog Description 

As described above, this catalog is meant to provide overview information on a wide variety 

of data sources that can address health and well-being issues for AI/AN/NA populations. It is not 

meant to be an exhaustive listing of all data available on AI/AN/NA populations concerning health 

and well-being. Time and resource limitations prevented coverage of the entire universe of data 

sources that might be used to address these topics. To ensure that the catalog would provide broad 

coverage of the major topics of health and well-being, as a first step, the project staff, in consultation 

with ASPE, representatives of the DHHS Data Council’s Racial and Ethnic Data Working Group (a 

workgroup for this project), and a small AI/AN/NA workgroup developed a detailed list of policy 

issues within the categories of health and well-being that should be covered in the catalog. The 

purpose of this policy list was to guide decision making about the content of the data sources that 

should be included. The project staff attempted to maximize coverage of the policy issues and avoid 

redundancy in the data sources being reviewed. This list of policy issues is presented in Figure 1. 

Beyond policy parameters, the project team, in consultation with ASPE, members of the 

DHHS workgroup, and the AI/AN/NA workgroup, also established the following technical 

parameters for the data catalog: 

• Data should be from a survey, program reporting system, or registry; 

• Data should be quantitative in nature; 

• Data source must allow user to identify people who are AI/AN/NA or focus on a specific 

geographic region with a large AI/AN/NA population; 

• Data source must be available to researchers (as data or as requested analyses) or have 

extensive published tables and reports available; 

• Contact and location information regarding the data source must be available; 

• Documentation of data collection methods should be available; 

• Data should not have been collected primarily to fill advocacy needs, lobbying purposes, 

or to support corporate interests; 

• Total unweighted AI/AN/NA population in data source should be available, and the 

sample size must be adequate for analyses; 

• Coverage of data source must be either national or focus on a specific AI/AN/NA 

subpopulation only (e.g., single tribe, Pacific Islanders), or consist of a smaller 

geographic area of clear relevance to the AI/AN/NA population; and 

• Timeframe of the data source should be mid-1990s or later (unless a strong argument can 

be made to include older data). 

The review of data sources conducted based on these parameters did not include an 

assessment of the quality of the data source. A careful examination of the actual data to make such an 

assessment was beyond the scope of this effort. Instead, reviewers sought to provide sufficient 

information about the data source to allow users to make an initial assessment of the potential 

usefulness of the data source for their purposes. We strongly recommend that potential users 

thoroughly examine the documentation and data from these sources to make their own assessments of 

the quality of the data. 

2-1 
Figure 1.1 Key Policy Issue Areas Guiding Inclusion of Data Sets 

DEMOGRAPHIC AND ECONOMIC INDICATORS (e.g., age distribution, marital status, household composition) 

HEALTH POLICY ISSUES

1. Measurement of health status (e.g., self-reported health, disability rates, mortality/morbidity rates, trends over time) 

2. Disease-specific measurements (e.g., % with diabetes, TB, STDs, cancer) 

3. Key health disparities of priority interest (e.g., prenatal care/birth outcomes, cancer mortality, substance abuse, alcohol use, mental health, 

suicide) 

4. Factors contributing to measured health disparities (e.g., access to health care, utilization rates, insurance coverage, health care financing, 

socioeconomic factors, preventative measures (such as immunization rates)) 

5. Identification of evidence-based practices and programs that address causes of health disparities, result in positive health outcomes, and 

are generalizable/replicable 

6. Role of traditional medicine in AI/AN/NA communities 

WELL-BEING ISSUES

Economic Well-being

1. Income status (e.g., household income/poverty status, per capita income) 

2. Unemployment rates 

3. Economic assistance program participation rates (e.g., Temporary Assistance for Needy Families/Tribal Temporary Assistance for Needy 

Families, Food Stamps) 

4. Economic opportunity (e.g., number of businesses/jobs, work history) 

5. Measurement of economic/employment disparities between AI/AN/NA and general population 

6. Factors contributing to economic disparities (e.g., lack of child care arrangement, transportation barriers) 

7. Identification of evidence-based practices and programs that reduce economic disparities and are generalizable/replicable 

Education Levels and Opportunities

1. Educational attainment (e.g., last grade completed, literacy/numeracy skills) 

2. Educational opportunities (e.g., Head Start, special education programs, school financing) 

3. Factors contributing to educational disparities (e.g., parents’ education level, average education in city/county, education spending per 

capita, and other socioeconomic factors) 

4. Identification of evidence-based practices and programs that produce positive educational outcomes and are generalizable/replicable 

Family Well-being

1. Measures of well-being for families/households (e.g., families with low income levels, homeless families, teen pregnancy/birthrates, 

household size and composition) 

2. Factors contributing to well-being disparities of families (e.g., socioeconomic factors, education levels of family adults, housing quality, 

public transportation availability) 

3. Identification of evidence-based practices and programs that improve family well-being and are generalizable/replicable 

Child Well-being

1. Measures of well-being for children (e.g., children in foster care, incarcerated children) 

2. Factors contributing to well-being disparities of children (household composition, martial status of parents, foster care placement) 

3. Identification of evidence-based practices and programs that improve child well-being and are generalizable/replicable 

Elder Well-being

1. Measures of well-being for elders (e.g., elders with low income levels, homeless elders, elder abuse) 

2. Factors contributing to well-being disparities of elders (e.g., socioeconomic factors, living arrangements, activities of daily living and 

instrumental activities of daily living (ADL/IADL), family members in proximity, services available/used (such as Meals on Wheels/elder 

transportation) 

3. Identification of evidence-based practices and programs that improve elder well-being and are generalizable/replicable 

Housing Issues

1. Housing quality (e.g., rooms per person, running water, electricity, heat, age of building) 

2. Type of housing 

3. Housing ownership 

4. Rental unit quality and cost 

5. Homelessness 

Transportation Quality and Availability Issues

Justice System Issues

1. Rates of involvement with justice system (e.g., arrest, conviction, probation, parole rates) 

2. Differences in resolution of arrest, by type of court system (e.g., federal, tribal, state, local) 

3. Lifetime probability of being a victim of a violent crime 

4. Lifetime probability of being a victim of a non-violent crime 

5. Domestic violence rates 

6. Child maltreatment rates 

7. Factors contributing to disparities in involvement with justice system and outcomes (e.g., family stability/foster care placement, family 

members’ history of legal system involvement, race/ethnicity, truancy history) 

8. Identification of evidence-based practices or programs that reduce involvement with justice system or reduce recidivism and are

generalizable/replicable 

Military Service/Veterans’ Issues

1. Military service rates (e.g., % served in military, % retired from military with benefits) 

2. Eligibility and use of Veterans Administration health facilities 

3. Eligibility and use of other Veterans Administration benefits (e.g. housing loans, educational benefits) 

2-2 
2.1 Catalog Organization 

The data catalog is organized into six sections beyond this introduction. Each of these 

sections is described in the bullets below: 

• Section 3 provides a listing of the data sources included in the catalog sorted by key 

policy areas. The data sources listed in each section are particularly appropriate for 

answering questions in the topical area but may also contain data in other areas; 

therefore, data sources may be listed under more than one policy area. 

Under each policy topic, data source name and corresponding page number are presented. 

The page number can be used to find the detailed information on the data source in 

Section 5. 

• Section 4 provides a listing of data sources included in the catalog sorted by 

subpopulations identified and analyzable (e.g., all AI/AN/NA, American Indians and 

Alaska Natives, Pacific Islanders, Native Hawaiians, named tribes or communities). Page 

number is also included. 

• Section 5, which is the largest section of this report, provides in depth profiles of all data 

sources presented alphabetically. A more detailed description of topics covered in these 

detailed profiles is presented below. 

• Section 6 includes a list of data sources identified but not reviewed for the catalog. This 

list is also alphabetical and is briefly annotated with reasons the data sources were not 

included in the review and selected information collected about the data set prior to its 

exclusion. 

• Section 7 includes reference information on a set of reports identified during this review 

that ASPE and the project team believe might be of particular interest to catalog users. 

These reports are generally of three types: reports concerning data that are not directly 

available to potential users but on which there are published detailed analytical reports, 

reports that are data compilations covering important issues using multiple data sources, 

and selected reports concerning the profiled data sources identified for review. This list of 

reports is not meant to be exhaustive but represents potentially useful information 

obtained in the course of assembling this catalog. 

• Appendices to this catalog include a glossary of terms, a brief discussion of issues 

related to data aggregation, and the review protocol used to screen and profile the data 

sources. 

 As noted above, Section 5 provides detailed profiles of each data source. Included in the 

detailed profiles are 25 possible elements. If they are not relevant to the data source, elements are 

not included in the profile; for example, if no information on AI/AN/NA subgroups is available, 

this field is not shown in the profile. The 25 possible elements for a data source profile include: 

1. Name of Data Source 

2. Sponsor—documents the agency or funding source for the data collection. 

3. Description—provides a summary description of the purpose of the data collection and 

the general content of the data set. 

4. Data Type(s) — indicates whether the data source is a survey, registry, or program 

reporting database. 

5. Relevant Policy Issues—draws from the list of policy issues described above. 

2-3 
6. Unit of Analysis—describes the level(s) at which the data were collected (e.g., 

individuals, families, households, farms). This information can help users determine the 

type of analysis that can be conducted and the research questions that can be asked. 

7. Identification of AI/AN/NA—provides detailed information on how data about race and 

ethnicity were collected for this data source. Where possible, question or form field text 

is included. 

8. AI/AN/NA Population in Data Set—provides the unweighted count of American Indian, 

Alaska Native, or other Native American persons or families included in the data source. 

This information is provided in as much detail as is available (e.g., for American Indians 

only). 

9. AI/AN/NA subpopulations—provides information on subpopulations for which analysis 

is possible (e.g., American Indian alone, tribal affiliation). 

10. Geographic Scope—indicates the level of geographic analysis possible (e.g., national 

only, state, region). 

11. Date or Frequency—provides information on the date of data collection and how 

frequently, if relevant, the data collections are repeated. 

12. Aggregation— this section is included only where it is necessary or particularly relevant 

to consider combining data collections across years. For example, when the AI/AN/NA 

sample size is extremely small in one year, it may be necessary to combine multiple 

years of data to obtain a sample size appropriate for statistical analysis. Or, when the 

data are collected in segments across several years, it may be desirable to aggregate 

across the years to provide full population coverage. 

13. Data Collection Methodology—provides some detail on how the data are collected (e.g., 

telephone, paper questionnaire.) 

14. Participation—documents whether participation in the data collection effort was 

mandatory or optional, and may provide information on the use of incentives. 

15. Response Rate—documents the response rate or coverage of the data collection. 

Unweighted response rates are provided where possible as these are the most directly 

interpretable. Where only weighted response rates are available, they are reported and, in 

most cases, briefly explained. 

16. Sampling Methodology—provides detail on how individuals, household, or other foci 

were selected to participate in the data collection. This is usually only appropriate for 

surveys and, rarely, program reporting databases. 

17. Oversample of AI/AN/NA Population—addresses the degree to which AI/AN/NA 

persons were purposely selected in excess of what would occur randomly. 

18. Analysis—includes information important to conducting statistical analyses of the data; 

for example, information on the standard errors of any estimates, the effective sample 

size, design effects, and description of the power available to detect differences in the 

data. 

19. Authorization—describes the authorizing legislation for the data collection, where 

appropriate. 

20. Strengths—summarizes the key strengths of the data source for AI/AN/NA research, as 

identified by the reviewers. 

21. Limitations—summarizes the key limitations of the data source identified by the 

reviewers. 

22. Other—contains other important information identified by the reviewer. 

2-4 
23. Access Requirements and Use Restrictions—describes the steps and cost involved in 

accessing, if possible, the data set. 

24. Contact Information—typically provides a name, telephone number, address, and email 

for the office responsible for the data collection. However, in some cases only a name is 

provided, and in other cases, only an email or Internet link is provided. 

25. Reports of Interest—provides a non-exhaustive list of key reports related to the data 

source identified in the course of the project. 

2.2 Methodology 

The approach used to compile the data catalog consisted of four steps: initial listings of data 

sources, screening of data sources, reviewing of the data sources, and developing the catalog profiles. 

Each of these steps is described in more detail in the paragraphs that follow. 

Developing the initial listings of data sources. The project team (in consultation with 

ASPE, our project consultants, and our small AI/AN/NA workgroup) initially developed a substantial 

list of potential data sources drawing from the following sources: 

• Web sites of all federal departments (e.g., Departments of Justice, Defense, Agriculture) 

with information on publicly available data sets and on administrative data sets that could 

be made available from each of these departments; 

• Data repositories including National Library of Medicine, the Interuniversity Consortium 

for Political and Social Research (ICPSR) at the University of Michigan, and the 

University of Virginia to identify additional data sources located in these repositories that 

may be appropriate; 

• Web site developed by the DHHS Data Council that provides a Directory of Health and 

Human Services Data Resources listing available DHHS data resources 

(http://aspe.hhs.gov/datacncl/datadir); 

• Web site developed by DHHS’ Office of Minority Health (OMH) and the Office of the 

Assistance Secretary for Planning and Evaluation (ASPE) under the auspices of the 

DHHS Data Council entitled Health and Human Services Statistics About Minorities 

(http://www.hhs-stat.net/omh/index.htm); 

• Consultation with members of the DHHS Data Council’s Racial and Ethnic Data 

Working Group who served as a workgroup for this project; and 

• Consultation with project consultants and a small AI/AN/NA workgroup representing the 

American Indian and Native Hawaiian communities. 

As the project progressed, data sources were continually added to the review list as they were 

discovered or recommended to the project team. In all, a total of 152 possible data sources were 

considered. 

Screening of data sources. Data sources were initially screened by reviewers to determine 

their appropriateness for inclusion in the catalog. The screening protocol comprised the first few 

pages of the review protocol located in Appendix C to this document. This screening protocol ensured 

that the data sources to be fully profiled and considered for inclusion in the catalog met the technical 

parameters listed in Section 2 above. Specifically, the reviewers provided the following information 

on each data source screened: 

2-5 
• Name of data source being reviewed; 

• Sponsoring agency; 

• Policy issue relevant to data source; 

• Brief description of data set; 

• Whether the data source identified people who are AI/AN/NA; 

• Availability of data set to researchers; 

• Cost associated with use of the data set; 

• Relevant contact and location information regarding this data source; 

• Source of funding for data set; 

• Total unweighted AI/AN/NA population in data source and if unweighted n < 100, 

feasibility of combining across multiple iterations of data collection to increase the size 

of the population; 

• Geographic coverage of the data set; 

• Timeframe of the data set; 

• Nature of data source (i.e., survey, program reporting data, or registry) and availability of 

relevant documentation; and 

• Qualitative or quantitative nature of data. 

Based on this information, the project team and ASPE project officers determined whether 

the data source should be fully profiled and likely included in the catalog, included in the list of nonreviewed data sources (Section 6), or omitted entirely. 

 

Reviewing the data sources. Data sources appropriate for profiling were then researched and 

the data were collected about as many of the 25 elements as possible by the initial reviewers. (See 

Section 2.1 above.) 

For some data sources, not all of this information was available through the Internet, 

published materials, or direct contacts with employees at the agency or data collection facility. After a 

reasonable effort, reviewers were instructed to note that missing information could not be obtained or 

was unavailable. Where the information on any of these categories is not applicable to the data set, 

the category will not appear in the profile (e.g., weighting information for registries) but when 

information important to the assessment of the utility of the data source was not available, the 

category remains in the profile and is duly noted. 

 Initial reviews were evaluated by senior project staff and revisions were made in light of their 

comments and questions. These revised reviews were then converted to the catalog entries presented 

here. In summary, a total of 152 possible data sources were considered. Due to resource issues and 

some early elimination of unusable data sources from the review process, 110 of the 152 data sources 

were screened. From the 110 screened data sources, 686

 data sources met the criteria for inclusion and 

are fully profiled in the catalog. 

 

6

 One data source was not originally considered for inclusion, but was added to the catalog after an agency sent 

in a full profile. 

2-6 
After all data reviews were completed, the data source profiles, where possible, were 

forwarded to the agency or point of contact for that data source for review. Westat received comments 

or approval on 76 percent of the data profiles in this catalog. After agencies and/or points of contact 

completed their review of the data source profiles, we revised many of the profiles in response to their 

comments. Westat then submitted the revised data catalog to members of the project DHHS 

workgroup, the project AI/AN/NA workgroup, the five Westat project consultants, and senior DHHS 

staff for review. Many of their comments and suggestions were incorporated into the final catalog. A 

list of the data sets by the different sponsoring agencies is included in Appendix D. 

2.3 Using These Data Sources 

The data sources described in this catalog fall into four broad categories: publicly available 

data sets, restricted use data sets, published tables (with or without on-line tabulation capability), and 

published tables with special tabulations available. Each of these data source types is described 

briefly below. 

 Publicly available data sets are collections of raw data records, usually in numeric format that 

can be downloaded or transmitted by disk, CD, or email to users for analysis. These may contain one 

record per person, per interaction, or per household. The researcher can access the data in these data 

sets in order to seek answers to specific questions he/she has. However, analysis of these data sets 

requires the appropriate computer equipment, a data analysis program (e.g., SAS, SPSS), and a data 

analyst skilled in handling raw numeric data. Additionally, analysis of some datasets from research 

efforts that used complex sampling procedures to select respondents may require the use of software 

designed to correctly estimate variances, such as WesVar or SUDAAN. These data are termed 

“publicly available” because all identifying information has been removed to allow their use by 

researchers other than those who collected the data. Publicly available data may be free to users or 

there may be a fee for acquiring the data. In some cases, potential users may have to complete a data 

access form and confidentiality agreement. Some examples of publicly available data sets included in 

this catalog are the American Housing Survey, the National Health Interview Survey, and the 

Adoption and Foster Care Analysis and Reporting System. 

 Restricted use data sets are also collections of raw data records that researchers can analyze in 

a way similar to the publicly available data sets. They also require computer equipment and special 

software to analyze. They differ from publicly available data sets in that their use is carefully 

monitored and restricted. Usually, these restrictions are in place to protect confidential information 

stored in the data set (e.g., names, addresses, income). Holders of restricted use data sets always 

require potential secondary users to complete a data access agreement. Some data sources require that 

potential users also submit a proposal for how they will use the data (e.g., research questions to be 

addressed), proof of financial support for the analyses, and personal information on the users. Some 

sources may also require that the users perform their analyses in a designated location. There may or 

may not be a charge for access to these data sets. Some examples of restricted use data sets included 

in this catalog are the National Survey of Family Growth and the American Community Survey (full 

sample).7

 

7 Employees of federal agencies and departments may have access to some restricted use data sources that are 

not available to non-federal employees. These restricted-use data sources may have more identifying 

information than non-restricted use versions of the same data source. In some cases, they may allow 

identification of race of the respondent or participant where the public-use files do not (e.g., the National 

Immunization Survey).

2-7 
 In some cases, data sources that will not permit access to the raw data, or have extremely 

limited access to the raw data, have developed on-line analytical capability that will allow public 

users to conduct some analyses on their own. Users may or may not have full access to the data and 

types of analyses may be restricted. One example of a data source that allows very limited access to 

the data but has on-line analytical capabilities included in this catalog is the American Community 

Survey (full sample). 

 Data sources that supply only published tables will not allow secondary users access to the 

raw data. Once the data are collected and analyses are completed, large tabular volumes containing 

the results from the analyses are published. Potential users can report only the information presented 

in these tables. For this catalog, these data sources are included only if the published tables have been 

determined to be of use to researchers and policy makers interested in issues related to the health and 

well-being of American Indians, Alaska Natives, or other Native Americans. Some examples of data 

sources that supply only published tables included in this catalog are the Pediatric Nutrition 

Surveillance System and the Pregnancy Nutrition Surveillance System. 

 Data sources that both supply published tables and conduct special request tabulations 

typically do not allow users access to the raw data and have large published tabular volumes. They, 

however, also have staff that can perform additional analyses at user request to address questions not 

covered in the tabular volume. The complexity of the additional analyses that can be conducted may 

vary across sources as will the possible charge for these special requests. Two examples of data 

sources included in this catalog that conduct special request tabulations are the Resource Patient and 

Management System, which is the program reporting database for the Indian Health Service, and the 

Census of Agriculture. 

2-8 
3. Data Sources by Topical Area 

The table below groups the 68 data sets included in this catalog by the primary identified policy issue 

related to the data set. The breakdown of the primary policy issues are as follows: 

• Child well-being (4 data sets) 

• Demographic and economic indicators (3 data sets) 

• Economic well-being (6 data sets) 

• Education (7 data sets) 

• Elder well-being (2 data sets) 

• Family well-being (4 data sets) 

• Health policy issues (30 data sets) 

• Housing issues (3 data sets) 

• Justice system issues (7 data sets) 

• Military service/Veterans issues (1 data set) 

• Transportation (1 data set) 

As many of these data sources cover a variety of topics, Table 1 also includes additional policy issues 

that are relevant to the data set. 

Table 1. Data Sources by Policy Issue 

Child Well-being

Additional Relevant 

Policy Issues Page # 

Adoption and Foster Care Analysis and Reporting System 

(AFCARS)

Health policy issues 

Justice system issues 5-4 

National Child Abuse and Neglect Data System (NCANDS) Justice system issues 5-104 

National Survey of Child and Adolescent Well-being 

(NSCAW) 

Family well-being 

Health policy issues 5-142 

Runaway and Homeless Youth Management Information 

System (RHYMIS) 

Housing issues 5-177 

Demographic and Economic Indicators

Additional Relevant 

Policy Issues Page # 

American Community Survey (ACS) Economic well-being 

Family well-being 

Housing issues 

5-8 

Census 2000 Economic well-being 

Education 

Family well-being 

Health policy issues 

Housing issues 

Transportation 

5-33 

Census 2000 - The American Indian and Alaska Native 

Summary File 

Economic well-being 

Education 

Family well-being 

Health policy issues 

Housing issues 

Transportation 

5-38 

3-1 
Table 1 continued. 

Economic Well-being

Additional Relevant 

Policy Issues Page # 

Census of Agriculture (2002) 5-41 

Consumer Expenditure Surveys (CE) Interview and Diary 

Surveys 5-49 

Current Population Survey (CPS) Demographic and 

Economic Indicators 5-53 

Panel Study of Income Dynamics (PSID) Child well-being 

Elder well-being 

Family well-being 

Housing issues

5-164 

Small Area Income and Poverty Estimates (SAIPE) 5-180 

Survey of Program Dynamics (SPD) Child well-being 

Education 

Family well-being 

Health policy issues 

Transportation 

Military service

5-188 

Education

Additional Relevant 

Policy Issues Page # 

Early Childhood Longitudinal Study, Birth Cohort 

(ECLS-B)

Child well-being 

Family well-being 5-58 

Early Childhood Longitudinal Study, Kindergarten Class of 

1998-99 (ECLS-K) 5-63 

Head Start Program Information Report Child well-being 

Family well-being 5-73 

Integrated Postsecondary Education Data System (IPEDS) 5-83 

National Assessment of Adult Literacy (NAAL) 5-101 

National Household Education Surveys Program (NHES) 5-120 

National Indian Education Study (NIES) 5-130 

Elder Well-being

Additional Relevant 

Policy Issues Page # 

Health and Retirement Study (HRS) Economic well-being 

Education 

Health policy issues

5-75 

National Aging Program Information Systems (NAPIS) State 

Performance Reports 5-96 

Family Well-being

Additional Relevant 

Policy Issues Page # 

Food Stamp Program Quality Control Database (FSPQC) Economic well-being 5-67 

National Survey of America’s Families (NSAF) Child well-being 

Economic well-being 

Health policy issues 

Housing issues 

5-137 

National Survey of Family Growth (NSFG) Health policy issues 5-146 

Temporary Assistance for Needy Families (TANF) and Tribal 

TANF 

Economic well-being 5-191 

3-2 
Table 1 continued. 

Health Policy Issues

Additional Relevant 

Policy Issues Page # 

Behavioral Risk Factor Surveillance System (BRFSS) 5-22 

Consumer Assessment of Healthcare Providers and Systems 

(CAHPS) Health Plan Survey Response Data 5-25 

California Health Interview Survey (CHIS) Child well-being 

Elder well-being 5-29 

Hawaii Health Survey (HHS) 5-70 

Health Behavior in School-aged Children (HBSC) Economic well-being 

Education 

Child well-being 

Family well-being 

5-78 

Health Information National Trends Survey (HINTS) 5-81 

Medicaid Analytic Extract (MAX) Child well-being 

Elder well-being 5-85 

Medical Expenditure Panel Survey (MEPS) Child well-being 

Elder well-being 

Family well-being 

5-88 

Medicare Denominator Files Elder well-being 5-92 

Medicare Utilization – Standard Analytic Files (SAFs) 5-94 

National Ambulatory Medical Care Survey (NAMCS) 5-98 

National Epidemiologic Survey on Alcohol and Related 

Conditions (NESARC) 5-111 

National Health Interview Survey (NHIS) Child well-being 

Elder well-being 

Family well-being 

5-114 

National Hospital Ambulatory Medical Care Survey 

(NHAMCS) 5-117 

National Longitudinal Mortality Study (NLMS) 5-133 

National Mortality Followback Survey (NMFS) 5-135 

National Survey on Drug Use and Health (NSDUH) 5-153 

National Vital Statistics System: Linked Birth-Infant Death 

(NVSS-I) 5-156 

National Vital Statistics System: Mortality (NVSS-M) 5-159 

National Vital Statistics System: Natality (NVSS-N) 5-162 

Pediatric Nutrition Surveillance System (PedNSS) Child well-being 5-167 

Pregnancy Nutrition Surveillance System (PNSS) 5-169 

Pregnancy Risk Assessment Monitoring System (PRAMS) Child well-being 5-171 

Resource and Patient Management System (RPMS) and 

National Patient Information Reporting System (NPIRS) 5-174 

Surveillance, Epidemiology, and End Results (SEER) 5-183 

Tobacco Use Supplement to the Current Population Survey 

(TUS-CPS) 5-194 

Treatment Episode Data Set (TEDS) 5-199 

United States Renal Data System (USRDS) 5-205 

Washington State Population Survey (WSPS) Economic well-being 5-207 

Youth Risk Behavior Surveillance Survey (YRBSS) 5-211 

3-3 
Table 1 continued. 

Housing Issues

Additional Relevant 

Policy Issues Page # 

A Picture of Subsidized Households Economic well-being 5-2 

American Housing Survey (AHS) 5-12 

American Housing Survey: Metropolitan Surveys 5-15 

Justice System Issues

Additional Relevant 

Policy Issues Page # 

Annual Survey of Jails (ASJ) 5-19 

Census of Jails 5-44 

Census of Tribal Justice Agencies in Indian Country 5-47 

National Crime Victimization Survey (NCVS) 5-108 

Survey of Jails in Indian Country (SJIC) 5-186 

Uniform Crime Reports 5-202 

Youth Gangs in Indian Country 5-209 

Military Service/Veterans Issues

Additional Relevant 

Policy Issues Page # 

National Survey of Veterans (NSV) 5-150 

Transportation

Additional Relevant 

Policy Issues Page # 

National Household Travel Survey (NHTS) 5-125 

3-4 
4. Data Sources by Subpopulation Coverage 

The 68 data sets included in this catalog vary in the way AI/AN/NA individuals are 

identified. Race is directly self-reported by the respondents or the respondents’ legal guardian (if the 

focal respondent is a minor) in 35 of these studies. Twenty-eight of these studies obtain race 

information from administrative records (e.g., enrollment forms, patient files). Five of the data sets do 

not identify AI/AN/NA individuals. 

Although there is some variation in the categories used to identify AI/AN/NA individuals, the 

majority of the studies in this catalog use the broader categories “American Indian or Alaska Native” 

and “Native Hawaiian or other Pacific Islander.” These broad categories meet the minimum racial 

classification standards set by the Office of Management and Budget (OMB)8

. Table 2 below lists the 

data sets by the subpopulation coverage for the American Indian or Alaska Native racial category, 

while Table 3 lists the data sets by the subpopulation coverage for the Native Hawaiian or other 

Pacific Islander subcategory. 

Table 2. Data Sources by Subpopulation Coverage: American Indian/Alaska Native 

Data Sources that identify Tribal Affiliation Notes Page # 

American Community Survey (ACS) 5-8 

California Health Interview Survey (CHIS) Identifies 10 

federally 

recognized tribes 

5-29 

Census 2000 5-33 

Census 2000 - The American Indian and Alaska Native Summary 

File

Identifies 1,081 

federally 

recognized tribes 

and villages 

5-38 

Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) 5-58 

Pediatric Nutrition Surveillance System (PedNSS) Identifies 7 

federally 

recognized tribes 

5-167 

Pregnancy Nutrition Surveillance System (PNSS) Identifies 6 

federally 

recognized tribes 

5-169 

Resource and Patient Management System (RPMS) and National 

Patient Information Reporting System (NPIRS) 

Analysis by tribe is 

dependent on tribal 

approval 

5-174 

Data sources that include the category American Indian alone 

(AI)

Notes 

Page # 

American Community Survey (ACS) 5-8 

Census 2000 5-33 

Health and Retirement Study (HRS) This category is 

available beginning 

in 2006 

5-75 

Resource and Patient Management System (RPMS) and National 

Patient Information Reporting System (NPIRS) 5-174 

Treatment Episode Data Set (TEDS) 5-199 

 

8

 www.whitehouse.gov.omb/fedreg/1997standards 

4-1 
Table 2 continued. 

Data sources that include the category Alaska Native alone (AN) Notes Page # 

American Community Survey (ACS) 5-8 

Census 2000 5-33 

Health and Retirement Study (HRS) This category is 

available beginning 

in 2006 

5-75 

Resource and Patient Management System (RPMS) and National 

Patient Information Reporting System (NPIRS) 5-174 

Treatment Episode Data Set (TEDS) 5-199 

Data sources that include the combined category American 

Indian/Alaska Native (AI/AN) Notes Page #

A Picture of Subsidized Households Category is “Native 

American” 5-2 

Adoption and Foster Care Analysis and Reporting System 

(AFCARS) 5-4 

American Housing Survey 5-12 

American Housing Survey: Metropolitan Surveys 5-15 

Annual Survey of Jails (ASJ) 5-19 

Behavioral Risk Factor Surveillance System (BRFSS) 5-22 

CAHPS Health Plan Survey Response Data 5-25 

California Health Interview Survey (CHIS) 5-29 

Census of Agriculture (2002) 5-41 

Census of Jails 5-44 

Consumer Expenditure Surveys (CE) Interview and Diary Surveys 5-49 

Current Population Survey (CPS) 5-53 

Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) 5-58 

Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 

(ECLS-K) 5-63 

Food Stamp Program Quality Control Database (FSPQC) 5-67 

Head Start Program Information Report 5-73 

Health Behavior in School-aged Children (HBSC) 5-78 

Health Information National Trends Survey (HINTS) 5-81 

Integrated Postsecondary Education Data System (IPEDS) 5-83 

Medicaid Analytic Extract (MAX) 5-85 

Medical Expenditure Panel Survey (MEPS) 5-88 

Medicare Denominator Files Category is “North 

American Native” 5-92 

Medicare Utilization – Standard Analytic Files (SAFs) Category is “North 

American Native” 5-94 

National Aging Program Information Systems (NAPIS) State 

Performance Reports 5-96 

National Ambulatory Medical Care Survey (NAMCS) 5-98 

National Assessment of Adult Literacy (NAAL) 5-101 

National Child Abuse and Neglect Data System (NCANDS) 5-104 

National Crime Victimization Survey (NCVS) 5-108 

National Epidemiologic Survey on Alcohol and Related Conditions 

(NESARC) 5-111 

National Health Interview Survey (NHIS) 5-114 

4-2 
Table 2 continued.

Data sources that include the combined category American 

Indian/Alaska Native (AI/AN) - Continued Notes Page #

National Hospital Ambulatory Medical Care Survey (NHAMCS) 5-117 

National Household Education Surveys Program (NHES) 5-120 

National Household Travel Survey (NHTS) 5-125 

National Indian Education Study (NIES) 5-130 

National Longitudinal Mortality Study (NLMS) 5-133 

National Mortality Followback Survey (NMFS) Category is 

“American Indian 

(AI), Aleut or 

Eskimo” 

5-135 

National Survey of America’s Families (NSAF) Category is 

“American Indian 

(AI), Aleut or 

Eskimo” 

5-137 

National Survey of Child and Adolescent Well-being (NSCAW) 5-142 

National Survey of Family Growth (NSFG) 5-146 

National Survey of Veterans (NSV) 5-150 

National Survey on Drug Use and Health (NSDUH) 5-153 

National Vital Statistics System: Linked Birth-Infant Death 

(NVSS-I) 5-156 

National Vital Statistics System: Mortality (NVSS-M) 5-159 

National Vital Statistics System: Natality (NVSS-N) 5-162 

Panel Study of Income Dynamics (PSID) Category is “Native 

American” 5-164 

Pediatric Nutrition Surveillance System (PedNSS) 5-167 

Pregnancy Nutrition Surveillance System (PNSS) 5-169 

Pregnancy Risk Assessment Monitoring System (PRAMS) 5-171 

Runaway and Homeless Youth Management Information System 

(RHYMIS) 5-177 

Surveillance, Epidemiology, and End Results (SEER) 5-183 

Survey of Program Dynamics (SPD) Category is 

“American Indian 

(AI), Aleut or 

Eskimo” 

5-188 

Temporary Assistance for Needy Families (TANF) and Tribal 

TANF 5-191 

Tobacco Use Supplement to the Current Population Survey 

(TUS-CPS) 5-194 

Uniform Crime Reports 5-202 

United States Renal Data System (USRDS) Category is “Native 

American” 5-205 

Washington State Population Survey (WSPS) 5-207 

Youth Risk Behavior Surveillance Survey (YRBSS) 5-211 

4-3 
Table 3. Data Sources by Subpopulation Coverage: Native Hawaiian/Other Pacific Islander 

Data sources that include the category Native Hawaiian alone (NH) Notes Page #

American Community Survey (ACS) 5-8 

Census 2000 5-33 

Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) 5-58 

Hawaii Health Survey (HHS) 5-70 

Health and Retirement Study (HRS) This category is 

available beginning 

in 2006 

5-75 

National Survey of Veterans (NSV) 5-150 

National Vital Statistics System: Linked Birth-Infant Death (NVSS-I) Category is not 

available after 2003 5-156 

National Vital Statistics System: Mortality (NVSS-M) 5-159 

National Vital Statistics System: Natality (NVSS-N) Category is not 

available after 2003 5-162 

Pregnancy Risk Assessment Monitoring System (PRAMS) 5-171 

Data sources that include the category Other Pacific Islander alone 

(PI) Notes Page #

American Community Survey (ACS) 5-8 

Census 2000 5-33 

Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) 5-58 

Health and Retirement Study (HRS) This category is 

available beginning 

in 2006 

5-75 

National Survey of Veterans (NSV) 5-150 

National Vital Statistics System: Mortality (NVSS-M) Includes categories 

for Samoan and 

Guamanian 

5-159 

Data sources that include the combined category Native Hawaiian or 

other Pacific Islander (NH/PI) Notes Page #

Adoption and Foster Care Analysis and Reporting System (AFCARS) 5-4 

American Housing Survey 5-12 

American Housing Survey: Metropolitan Surveys 5-15 

Annual Survey of Jails (ASJ) 5-19 

Behavioral Risk Factor Surveillance System (BRFSS) 5-22 

CAHPS Health Plan Survey Response Data 5-25 

California Health Interview Survey (CHIS) 5-29 

Census of Agriculture (2002) 5-41 

Census of Jails 5-44 

Consumer Expenditure Surveys (CE) Interview and Diary Surveys 5-49 

Current Population Survey (CPS) 5-53 

Early Childhood Longitudinal Survey Kindergarten Cohort 

(ECLS-K) 5-63 

Food Stamp Quality Control Database (FSPQC) Category available 

beginning in 2007 5-67 

Head Start Program Information Report 5-73 

Health Behavior in School-aged Children (HBSC) 5-78 

Health Information National Trends Survey (HINTS) 5-81 

Medicaid Analytic Extract (MAX) 5-85 

4-4 
Table 3 continued. 

Data sources that include the combined category Native Hawaiian or 

other Pacific Islander (NH/PI) - Continued Notes Page #

Medical Expenditure Panel Survey (MEPS) 5-88 

National Ambulatory Medical Care Survey (NAMCS) 5-98 

National Assessment of Adult Literacy (NAAL) 5-101 

National Child Abuse and Neglect Data System (NCANDS) 5-104 

National Crime Victimization Survey (NCVS) Category available 

beginning in 2003 5-108 

National Epidemiologic Survey on Alcohol and Related Conditions 

(NESARC) 5-111 

National Hospital Ambulatory Medical Care Survey (NHAMCS) 5-117 

National Household Education Surveys (NHES) Category available 

beginning in 2005 5-120 

National Household Travel Survey (NHTS) 5-125 

National Longitudinal Mortality Study (NLMS) 5-133 

National Survey of Family Growth (NSFG) 5-146 

National Survey on Drug Use and Health (NSDUH) 5-153 

Runaway and Homeless Youth Management Information System 

(RHYMIS) 5-177 

Temporary Assistance for Needy Families (TANF) and Tribal TANF 5-191 

Tobacco Use Supplement to the Current Population Survey 

(TUS-CPS) 5-194 

Washington State Population Survey (WSPS) 5-207 

Youth Risk Behavior Surveillance Survey (YRBSS) 5-211 

4-5 
5. Listing of Data Sources 

The following pages contain detailed descriptions of the 68 data sources included in this catalog. 

5-1 
A Picture of Subsidized Households (1998) 

Sponsor: U.S. Department of Housing and Urban Development (HUD) 

Description: The Picture of Subsidized Households (1998) presents summary information 

reported by subsidized housing programs across the nation. The program data 

included in the data set comes from five different sources: 

 1. Indian Housing 

 2. Public Housing 

 3. Section 8 housing (including Section 8 Certificates and Vouchers, Section 8 

Moderate Rehabilitation, and Section 8 New Construction or Substantial 

Rehabilitation) 

 4. Federal Housing Administration (FHA) (including Section 236 projects and 

other FHA projects with subsidy such as Section 8 Loan Management, 

Rental Assistance Program (RAP), Rent Supplement, Property Disposition, 

etc.) 

 5. Low Income Housing Tax Credit 

The data file and reports cover about four and a half million HUD-subsidized 

housing units, and a third of a million housing units assisted by Low Income 

Housing Tax Credits, for a total of nearly five million subsidized housing units. 

Relevant Policy 

Issues: 

Income Status, Economic Assistance Program Participation Rates, and Housing 

Quality. 

Data Type(s): Program reporting data 

Unit of 

Analysis: 

Housing subsidy program 

Identification 

of AI/AN/NA: 

The 1998 data set includes the percent of Native Americans (defined as American 

Indians and Alaska Natives) living in subsidized housing in 1998. 

AI/AN/NA 

Population in 

Data Set: 

This data set is summary data rather than raw data, and as such, does not provide 

counts of AI/AN/NA persons but does provide the percentage of Native 

Americans living in subsidized housing. Of all those living in subsidized housing 

in 1998, across all types of subsidized housing, 1 percent were Native American. 

Of those living in Indian housing, 89 percent were Native American. 

Geographic 

Scope: 

The geographic scope of the study is national. Geographic indicators available in 

the data include latitude, longitude, zip code, county, MSA, census tract, and 

Congressional district. 

Date or 

Frequency: 

The data used in this report and compiled into the data set are collected 

continuously and only periodically compiled into the report and data sets. A 

Picture of Subsidized Households previously was produced the 1970s and in 

1996, and 1997. A Picture of Subsidized Households: 2000 and A Picture of 

Subsidized Households: 2004 are forthcoming (both are expected by the end of 

5-2 
A Picture of Subsidized Households (1998) 

(continued) 

the 2006 calendar year). These reports will not contain any data on Indian 

Housing but will include information on American Indians, Alaska Natives, and 

other Native Americans living in non-Indian Housing. Tentative plans to release 

A Picture of Subsidized Households reports biennially are under consideration. 

Data Collection 

Methodology: 

Subsidized housing programs submit reports to HUD. 

Participation: Mandatory 

Strengths: Data are collected on key policy issues regarding housing. There are multiple 

years of data available. 

Limitations: These data do not include any information on Native Hawaiians or other Pacific 

Islanders living in subsidized housing. 

Access 

Requirements 

and Use 

Restrictions: 

Data set is available to public at no cost. 

Contact 

Information: 

General user information can be accessed through HUD USER: 

HUD USER 

P.O. Box 23268 

Washington, DC 20026-3268 

Toll Free: (800) 245-2691 

TDD: (800) 927-7589 

Local: (202) 708-3178 

Fax: (202) 708-9981 

email: helpdesk@huduser.org 

More detailed information can be accessed by contacting: 

Robert W. Gray 

U.S. Department of Housing and Urban Development 

451 7th Street S.W., Washington, DC 20410 

Robert_W._Gray@hud.gov 

The 1998 data and documentation are available for download from the following 

website: http://www.huduser.org/datasets/assthsg/statedata98/. 

5-3 
Adoption and Foster Care Analysis and Reporting System (AFCARS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Administration for 

Children and Families (ACF) 

Description: The Adoption and Foster Care Analysis and Reporting System (AFCARS) 

provides child-specific information on all children covered by the protections of 

Title IV-B and Title IV-E of the Social Security Act. On a semi-annual basis, all 

states submit data to the U.S. Children's Bureau concerning each child in foster 

care and each child who has been adopted under the authority of the state's child 

welfare agency. The AFCARS databases have been designed to address policy 

development and program management issues at both the state and federal levels. 

The data are also useful for researchers interested in analyzing aspects of the 

United States' foster care and adoption programs. 

For each year since 1995, there are two AFCARS files, one containing adoption 

data and the other containing foster care data. These annual files are constructed 

from the states' semi-annual data submissions. The adoption file contains 45 data 

elements concerning the adopted child's gender, race, birth date, ethnicity and 

prior relationship with the adoptive parents. The date the adoption was finalized, 

dates parental rights were terminated, characteristics of birth and adoptive 

parents, and whether the child was placed from within the United States or from 

another country are also captured. The foster care file contains 89 elements 

providing information on child demographics including gender, birth date, race, 

and ethnicity. Information about the number of previous stays in foster care, 

service goals, availability for adoption, dates of removal and discharge, funding 

sources, and the biological and foster parents is also included in the foster care 

files. 

Relevant Policy 

Issues: 

Measurement of Health Status, Measures of Well-being for Children, Factors 

Contributing to Well-being Disparities of Children, and Child Maltreatment 

Rates. 

Data Type(s): Registry 

Unit of 

Analysis: 

Individual (child) 

Identification 

of AI/AN/NA: 

Instructions for states reporting race are: "In general, a person’s race is 

determined by how others define them or by how they define themselves. In the 

case of young children, parents determine the race of the child. Data entry staff 

are to indicate all races that apply." 

Definitions of racial categories include: 

American Indian or Alaska Native (AI/AN) is defined as a person having origins 

in any of the original peoples of North America or South America (including 

Central America), and who maintains tribal affiliation or community attachment. 

5-4 
Adoption and Foster Care Analysis and Reporting System (AFCARS) 

(continued) 

Native Hawaiian or other Pacific Islander (NH/PI) is defined as a person having 

origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific 

Islands. 

Asian – A person having origins in any of the original peoples of the Far East, 

Southeast Asia, or the Indian subcontinent including, for example, Cambodia, 

China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, 

and Vietnam. 

Black or African American – A person having origins in any of the black racial 

groups of Africa. 

White – A person having origins in any of the original peoples of Europe, the 

Middle East, or North Africa. 

AI/AN/NA 

Population in 

Data Set: 

For FY 2003, number of children in foster care:

TOTAL: 523,000 

AI/AN non-Hispanic: 10,260 

NH/PI non-Hispanic: 1,540 

For FY 2003, number of children waiting to be adopted:

TOTAL: 119,000 

AI/AN non-Hispanic: 2,190 

NH/PI non-Hispanic: 340 

For FY 2003, number of children who were adopted:

TOTAL: 50,000 

AI/AN non-Hispanic: 700 

NH/PI non-Hispanic: 130 

Geographic 

Scope: 

The geographic scope of the AFCARS is national. A state indicator is available 

for all records on both the adoption and foster care files. For foster care data, the 

geographic Federal Information Processing Standards (FIPS) codes for the local 

county agency responsible for the case are available for all children in counties 

with more than 1,000 records. (If county has less than 1,000 records, FIPS codes 

are excluded for reasons of confidentiality.) Limited geographic analysis is 

possible by state and county. 

Date or 

Frequency: 

States are required to submit AFCARS data semi-annually to ACF. The AFCARS 

reporting periods are October 1 through March 31 and April 1 through September 

30. Data for each reporting period are due no later than May 15 and November 

14, respectively. An annual file is constructed from the two semi-annual files. 

Data collection has been ongoing since 1995, although use of the data prior to 

1998 is discouraged. The period from 1995 to 1997 was a start-up phase for 

AFCARS. Many states were still developing their information systems and were 

unable to submit data. Other states were able to submit data, but the quality was 

5-5 
Adoption and Foster Care Analysis and Reporting System (AFCARS) 

(continued) 

either missing or poor on many of the data elements. Therefore, pre-1998 data 

sets are not as complete or reliable as the data for subsequent years. Since 1998, 

participation by the states has been universal and the data quality has improved 

dramatically. The most recent data available are for FY2004. 

Data Collection 

Methodology: 

States submit case-level reports electronically to AFCARS. 

Participation: Mandatory 

Response Rate: By 1999, all states (plus the District of Columbia (DC) and Puerto Rico) had 

submitted adoption data. By 2001, all states, DC and Puerto Rico had submitted 

foster care data. 

Authorization: Under the final AFCARS’ rule, states are required to collect data on all adopted 

children covered by Title IV-B/E of the Social Security Act. 

Strengths: AFCARS data sets contain a large number of AI/AN/NA respondents. The data 

are collected on key policy issues, including child welfare. There are multiple 

years of data available. The documentation is thorough and clear. Mandatory 

reporting means high compliance among states. 

Limitations: While data collection began in 1995, use of the data prior to 1998 is discouraged. 

Tribal agencies who place children for adoption voluntarily report data to 

AFCARS. Since these adoptions do not involve a state agency, these records are 

not included in the publicly available version of the data. 

A 2003 report issued by the Department of Health and Human Services and 

entitled Adoption and Foster Care Analysis and Reporting System (AFCARS): 

Challenges and Limitations reports there is some inconsistency in the definition 

of data elements, most notably problems with placement and date-of-discharge 

definitions. 

Other: In 2000, technical changes to the race/ethnicity data elements in AFCARS were 

made. Previously, race categories were mutually exclusive, but starting in 2000 

children could be classified as multi-racial. 

Access 

Requirements 

and Use 

Restrictions: 

Researchers need to complete and submit a Terms of Use Agreement. 

5-6 
Adoption and Foster Care Analysis and Reporting System (AFCARS) 

(continued) 

Contact 

Information: 

The data set is available through the National Data Archive on Child Abuse and 

Neglect at Cornell University: http://www.ndacan.cornell.edu. 

National Data Archive on Child Abuse and Neglect 

Beebe Hall - FLDC 

Cornell University 

Ithaca NY 14853 

Phone: (607) 255-7799 

Fax: (607) 255-8562 

E-Mail: NDACAN@cornell.edu 

5-7 
American Community Survey (ACS) 

Sponsor: U.S. Department of Commerce/U.S. Census Bureau 

Description: The American Community Survey (ACS) was designed to provide current 

estimates of community change, and intended to replace the decennial Census 

long form by collecting and producing updated population and housing 

information every year instead of every 10 years. About three million households 

are to be surveyed each year. The ACS collects information from U.S. households 

similar to what was collected on the Census 2000 long form, such as income and 

employment, commute time to work, home value and expenses, type of housing, 

household composition, health status, and veteran status. The ACS began testing 

in 1996 and expanded to a national demonstration design from 2000 through 

2004. Full implementation into all counties began in 2005. 

Each year, a subsample of the ACS is selected to construct the Public Use 

Microdata (PUMS). This data set is available online for all researchers. Use of the 

full sample of the ACS is restricted and access is difficult to obtain. However, the 

full sample data are used to create the published population estimates from the 

ACS. Both the PUMS data and the restricted-access full ACS sample are 

discussed in this profile. 

Relevant Policy 

Issues: 

Demographic and Economic Indicators, Income Disparities, Unemployment 

Rates, Economic Assistance Program Participation Rates, Measures of Wellbeing for Families/Households, Housing Quality, Type of Housing, Housing 

Ownership, and Rental Unit Quality and Cost. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual and Household. 

Identification 

of AI/AN/NA: 

Race is self-reported. One household member fills out the ACS questionnaire and 

reports race for himself/herself and all other members of the household. 

Instructions in the ACS survey for reporting race are: “What is this person’s race? 

Mark one or more races to indicate what this person considered himself/herself to 

be.” Response categories include: 

• White 

• Black or African American 

• American Indian or Alaska Native – Print name of enrolled or principal 

tribe (AI/AN) 

• Asian Indian 

• Chinese 

• Filipino 

• Japanese 

• Korean 

• Vietnamese 

• Other Asian – Print race 

5-8 
American Community Survey (ACS) 

(continued) 

• Native Hawaiian (NH) 

• Guamanian or Chamorro 

• Samoan 

• Other Pacific Islander – Print race below (OPI) 

• Some other race – Print race below 

Additionally, the questionnaire contains several questions that either require or 

permit respondents to write-in their responses. The write-in fields cover the 

following topics: race, Hispanic origin, place of birth, ancestry, migration, 

language, place of work, industry and occupation. These write-in responses are 

then coded. Using these coded responses, further race classification of the data is 

possible, such as separating “American Indian” from “Alaska Native.” 

AI/AN/NA 

Population in 

Data Set: 

As noted earlier, there is both the restricted-access full sample of the ACS and the 

Public Use Microdata set (PUMS). The restricted-access sample provides race 

categories in greater detail than the PUMS data, while the race categories for the 

PUMS data are combined into fewer categories. 

At the time of this publication, the data from the 2005 full implementation of the 

ACS are not yet available. The PUMS data will contain about 40 percent of the 

full ACS sample and represent 1 percent of the population. Based on information 

from the pilot testing, the PUMS data should contain an adequate number of 

AI/AN/NA individuals to support analysis targeting this population. 

AI/AN/NA 

Subpopulations: 

The ACS questionnaire asks for AI/AN individuals to give the name of their 

enrolled or principal tribe. Total population estimates are provided for the 

following tribal groupings: Cherokee, Chippewa, Navajo and Sioux. Tribal 

affiliation is not available in the PUMS data set, but is present in the full 

restricted ACS data. 

The Native Hawaiian/Other Pacific Islander race category is broken out into the 

following subcategories and total population estimates are reported separately: 

Native Hawaiian, Guamanian or Chamorro, Samoan, Other Pacific Islander. 

Again, this level of detail is only available in the restricted use ACS data. The 

PUMS data only reports the combined category Native Hawaiian/Other Pacific 

Islander. 

Geographic 

Scope: 

The geographic scope of the ACS is national. The ACS identifies the following 

individual geographic areas: nation, state, county, county subdivision, placecounty, place, metropolitan statistical area (MSA)/consolidated metro statistical 

area (CMSA)/primary metropolitan statistical area (PMSA), and Congressional 

district. The list of geographic identifiers will expand with the release of the 2005 

data. 

Data from the 2004 ACS are available for over 800 geographic areas, including 

244 counties, 203 Congressional districts, most metropolitan areas of 250,000 

population or more, all 50 states, and the District of Columbia. From the mid 

5-9 
American Community Survey (ACS) 

(continued) 

1990s to 2004, the ACS survey was administered to selected sites. The ACS data 

collection effort was fully implemented in 2005. The Census Bureau plans to 

begin releasing the 2005 survey estimates in the summer of 2006, but only for 

areas with populations of 65,000 or more. For areas with populations of 20,000 or 

more, data release is planned for the summer of 2008, with estimates for all 

areas–down to census tract/block group level–by the summer of 2010. 

Date or 

Frequency: 

Data collection is conducted on a monthly basis. Results are compiled and 

published annually. At the time of this reporting, the most current available data 

are for 2004. Release dates are noted in the Geographic Scope section above. 

Data Collection 

Methodology: 

Surveys are mailed every month to a random sample of addresses in each county. 

The self-enumeration procedure uses several mailing pieces, including a 

prenotification letter, the American Community Survey questionnaire, a reminder 

card, and a replacement questionnaire if the original questionnaire is not returned 

in a timely manner. If a household does not respond in 6 weeks, Census Bureau 

staff will attempt to contact the respondent by telephone to complete the survey. 

If that, too, fails, about one in every three addresses remaining will be visited by 

Census Bureau staff for an in-person interview. 

Participation: Mandatory 

Response Rate: The ACS does not report an unweighted response rate. Weighting is used because 

not all housing units have the same probability of selection. The weighted 

response rate for the 2004 ACS is reported as 93.1 percent, due to a special 

budget issue. From 2001 to 2003, response rates ranged from 96.7 percent to 97.7 

percent. 

Sampling 

Methodology: 

The 2004 ACS used a two-stage stratified annual sample of approximately 

830,000 housing units. Step one of the sampling design was to divide the U.S. 

into primary sampling units (PSUs); step two was grouping the PSUs into strata 

based on independent information. After that, one pair of PSUs from each stratum 

was selected. The 2004 population estimates were derived from 568,966 final 

interviews. Beginning in 2005, the first stage of sample was no longer used, as all 

counties will be included in the sample. 

Oversample of 

AI/AN/NA 

Population: 

A larger proportion of addresses are sampled for small governmental units 

including American Indian reservations. The monthly sample size is designed to 

approximate the sampling ratio of Census 2000 Long Form, including the 

oversampling of small governmental units. 

Analysis: The ACS is a weighted data set. The PUMS methodology report gives a detailed 

explanation on how to apply appropriate weights when conducting analysis and 

how to calculate standard errors for the survey variable(s) of interest. Each 

variable in the ACS data set has an associated design effect. The design effects 

for the race categories in the ACS are listed as: 

5-10 
American Community Survey (ACS) 

(continued) 

• White alone = 2.5 

• Black or African American alone = 3.1 

• AI/AN alone, Asian alone, NH/PI alone, some other race alone = 3.0 

Authorization: The American Community Survey is part of the 10-year Census. As such, its legal 

authority derives from the same statutes that authorize the Census: Title 13 of the 

U.S. Code, Sections 141 and 193. 

Strengths: The data set contains a large number of AI/AN/NA respondents. The data are 

collected on key policy issues, including housing and economic well-being. There 

are multiple years of data available. 

The AI/AN/NA population is oversampled in the ACS, thereby improving the 

reliability of estimates for this population by reducing the variance. Coverage 

rates for the 2004 ACS for AI/AN are reported as 100 percent and as 90 percent 

for Native Hawaiian and other Pacific Islanders. 

Limitations: The tabulations prepared from the PUMS are based on a subset of the 2004 

American Community Survey (ACS) sample. Estimates from the ACS PUMS file 

are expected to be different from the previously released ACS estimates because 

they are subject to additional sampling error and further data processing 

operations. The full data set is difficult to obtain (see below). 

Access 

Requirements 

and Use 

Restrictions: 

The ACS PUMS data are available for download at no cost at the Census 

Bureau's American FactFinder website: 

http://factfinder.census.gov/home/saff/main.html?_lang=en. 

It may be possible for researchers to access the full ACS survey data set, but 

obtaining permission for this is difficult. Interested researchers can send an 

application to the Center of Economic Studies. If approved, researchers will need 

to work with the data at a Census Bureau data site, or at research centers located 

in various cities. 

Contact 

Information: 

For general information about the scope and content of the American Community 

Survey, call 1 (888) 456-7215 or email cmo.acs@census.gov. 

Additional information can be found online at: 

http://www.census.gov/acs/www/index.html 

5-11 
American Housing Survey (2003) 

Sponsor: U.S. Department of Housing and Urban Development (HUD) 

Description: The American Housing Survey (AHS) collects data on the Nation's housing, 

including apartments, single-family homes, mobile homes, vacant housing units, 

household characteristics, income, housing and neighborhood quality, housing 

costs, equipment and fuels, size of housing unit, and recent movers. The AHS is 

conducted by field representatives who obtain information from occupants of 

homes or from informed people such as landlords, rental agents, or 

knowledgeable neighbors about vacant homes. Interviewing occurs from May 30 

through September 8 and is conducted every other year. The 2003 national survey 

is a sample of about 61,050 designated housing units. 

Relevant Policy 

Issues: 

Housing Quality, Type of Housing, Housing Ownership, and Rental Unit Quality 

and Cost. 

Data Type(s): Survey 

Unit of 

Analysis: 

Household. A household consists of all people who occupy a particular housing 

unit as their usual residence, or who live there at the time of the interview and 

have no usual residence elsewhere. The usual residence is the place where the 

person lives and sleeps most of the time. This place is not necessarily the same as 

a legal residence, voting residence, or domicile. Households include not only 

occupants related to the householder but also any lodgers, roomers, boarders, 

partners, wards, foster children, and resident employees who share the living 

quarters of the householder. It includes people temporarily away for reasons such 

as visiting, traveling in connection with their jobs, attending school, in general 

hospitals, and in other temporary relocations. By definition, the count of 

households is the same as the count of occupied housing units. 

Identification 

of AI/AN/NA: 

Race is self-reported. Interviewees were asked to respond to the question on race 

by indicating one or more of six race categories. The six race categories included: 

• White 

• Black or African American 

• American Indian or Alaska Native (AI/AN) 

• Asian 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• Some Other Race (this category is not read or displayed to the respondent) 

AI/AN/NA 

Population in 

Data Set: 

The total number of completed surveys for the AHS 2003 was 71,170. Responses 

to the race item were recoded into the multiple race categories. The following 

categories reflect the unweighted counts for the AI/AN/NA respondents in the 

2003 AHS: 

5-12 
American Housing Survey (2003) 

(continued) 

AI/AN Only: 300 

NH/PI Only: 139 

White/AI/AN: 291 

White/NH/PI: 11 

Black/AI/AN: 49 

Black/NH/PI: 2 

AI/AN/Asian: 3 

Asian/NH/PI: 10 

White/Black/AI/AN: 27 

White/Asian/NH/PI: 5 

White/AI/AN/Asian: 1 

Geographic 

Scope: 

The geographic scope of the AHS is national. Geographic analysis is possible by 

county. 

Date or 

Frequency: 

From 1973 to 1981, the AHS collected national data every year and was called 

the Annual Housing Survey. Since 1981, the AHS has been conducted biannually 

in odd-numbered years. 

Data Collection 

Methodology: 

In-person interviews and telephone interviews are conducted by field 

interviewers. 

Participation: Optional, without incentives 

Response Rate: For 2003, the unweighted overall response rate was 91 percent. 

Sampling 

Methodology: 

The sample for AHS is spread over 394 primary sampling units (PSUs), counties 

or groups of counties or independent cities. These PSUs include 878 counties and 

independent cities with coverage in all 50 states and the District of Columbia. If 

there were over 100,000 housing units in a PSU at the time of selection, the PSU 

is known as a self-representing PSU because it was removed from the probability 

sampling operation and was in the sample with certainty. There are 170 selfrepresenting PSUs. The Census Bureau grouped the remaining PSUs and selected 

one PSU per group, proportional to the number of housing units in the PSU, to 

represent all PSUs in the group. These selected PSUs are referred to as nonselfrepresenting PSUs. After this, a sample of housing units was chosen within the 

selected PSUs. 

Authorization: Title 12, Sections 1701Z-1 and 1701Z-2g of the U.S. Code authorize the 

Secretary of HUD to collect data from public and private agencies and protect the 

confidentiality of the data. Title 12, Section 1701Z-10 mandates the collection of 

the data for the AHS. 

Strengths: Data are collected on key policy issues, including issues related to housing. There 

are multiple years of data available. 

Limitations: No major limitations were identified. 

5-13 
American Housing Survey (2003) 

(continued) 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to public at no cost. 

Contact 

Information: 

The American Housing Survey Branch can be contacted by email at 

ahsn@census.gov or by phone at (301) 763-3235. 

Tables, reports and the actual data can be downloaded from 

http://www.census.gov/hhes/www/housing/ahs/nationaldata.html. 

5-14 
American Housing Survey: Metropolitan Surveys 

Sponsor: U.S. Department of Housing and Urban Development (HUD) 

Description: The Metropolitan Area Surveys portion of the American Housing Survey (AHS 

Metro Survey) collects data on housing, including apartments, single-family 

homes, mobile homes, vacant housing units, household characteristics, income, 

housing and neighborhood quality, housing costs, equipment and fuels, size of 

housing unit, and recent movers in a selection of metropolitan areas across the 

country. Data are gathered for about 14 metropolitan areas in even-numbered 

years until a total of 47 metropolitan areas have been covered. That is, 

householders in selected areas are interviewed every 6 years until all 47 

metropolitan areas have been surveyed. The cycle begins again 6 years later. 

Since 1984, each metropolitan area has been represented by a sample of at least 

3,200 designated housing units. The units are divided between the central city and 

the rest of the metropolitan area. 

Relevant Policy 

Issues: 

Housing Quality, Type of Housing, and Housing Ownership. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individuals, Households, and Metropolitan areas. 

A household consists of all people who occupy a particular housing unit as their 

usual residence, or who live there at the time of the interview and have no usual 

residence elsewhere. The usual residence is the place where the person lives and 

sleeps most of the time. This place is not necessarily the same as a legal 

residence, voting residence, or domicile. Households include not only occupants 

related to the householder but also any lodgers, roomers, boarders, partners, 

wards, foster children, and resident employees who share the living quarters of 

the householder. It includes people temporarily away for reasons such as visiting, 

traveling in connection with their jobs, attending school, in general hospitals, and 

in other temporary locations. By definition, the count of households is the same as 

the count of occupied housing units. 

Identification 

of AI/AN/NA: 

Race is self-reported. Participants were asked to respond to the question on race 

by indicating one or more of six race categories. The six race categories were: 

 

• White 

• Black or African American 

• American Indian or Alaska Native (AI/AN) 

• Asian 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• Some Other Race (this category is not read or displayed to the respondent) 

5-15 
American Housing Survey: Metropolitan Surveys 

(continued) 

AI/AN/NA 

Population in 

Data Set: 

The following categories reflect the unweighted counts for the recoded 

AI/AN/NA relevant response categories in the 2004 AHS Metro Survey: 

TOTAL: 62,005 

AI/AN: 350 

NH/PI: 122 

White/AI/AN: 555 

White/NH/PI: 27 

Black/AI/AN: 74 

Black/NH/PI: 6 

AI/AN/Asian: 1 

Asian/NH/PI: 11 

White/Black/AI, AN: 40 

White/AI/AN/Asian: 1 

White/Asian/NH/PI: 1 

White/AI/AN/Asian: 5 

Geographic 

Scope: 

The geographic scope of the AHS Metro Survey is national. Geographic analysis 

is possible by Metropolitan Statistical Area (MSA) in the following groupings or 

in a combined data set: 

The 2004 AHS Metro Survey covered 13 metropolitan areas: Atlanta, Cleveland, 

Denver, Hartford, Indianapolis, Memphis, New Orleans, Oklahoma, 

Pittsburgh, St. Louis, Sacramento, San Antonio, Seattle-Everett. 

The 2002 AHS Metro Survey covered 13 metropolitan areas: Anaheim-Santa 

Ana, Buffalo, Charlotte, Columbus, Dallas, Fort Worth-Arlington, Kansas City, 

Miami-Ft. Lauderdale, Milwaukee, Phoenix, Portland, Riverside-San BernardinoOntario, San Diego. 

The 1998 AHS Metro Survey covered 15 metropolitan areas: Baltimore, 

Birmingham, Boston, Cincinnati, Houston, Minneapolis, Norfolk/Newport News, 

Oakland, Providence, Rochester, Salt Lake City, San Francisco, San Jose, Tampa, 

Washington, DC. 

Date or 

Frequency: 

The AHS Metro Survey was conducted annually between 1974 and 1996, and has 

been conducted biannually since 1998 with the exception of 2000 (a census year). 

Aggregation: No specific guidance regarding aggregation of the data exists in the extensive 

documentation on the AHS Metro Survey. The numbers of AI/AN/NA 

represented in each survey are sufficiently large to permit analyses for the specific 

metropolitan areas sampled in that year’s data collection effort, so aggregation to 

compensate for small Ns is not necessary. If, however, the analyst wished to 

aggregate across data collection years to expand the number of MSAs in the data 

set, it would be advisable to use the AHS National data set (also, included in this 

catalog) rather than the Metro data set. 

5-16 
American Housing Survey: Metropolitan Surveys 

(continued) 

Data Collection 

Methodology: 

In-person interviews and telephone interviews are conducted by field 

interviewers. 

Participation: Optional, without incentives 

Response Rate: For 2004, the overall weighted response rate was 91 percent. 

Sampling 

Methodology: 

To draw the AHS Metro Survey sample, the Census Bureau initially grouped the 

housing units enumerated in the 1990 Census of Population and Housing into 

census blocks and assigned these blocks to either the unit/group quarters frame or 

the area frame. Blocks located in an area that issued permits for new construction 

were assigned to the unit/group quarters frame. All other blocks were assigned to 

the area frame. 

The unit/group quarters frame was then split into the unit frame and the group 

quarters frame by removing all group quarters and placing them in a separate 

frame. All housing units that were built after the 1990 census in areas where 

construction of new homes was monitored by building permits were placed into a 

separate frame, called the permit frame. 

Sampling operations for all frames were performed separately within a designated 

group of counties in each state. Prior to the AHS Metro Survey sample selection, 

records selected by other Census Bureau surveys were removed from each of the 

frames to avoid having the same housing unit in sample for more than one survey. 

The Census Bureau selected the AHS Metro Survey sample from the remaining 

records. 

Authorization: The U.S. Census Bureau conducts the American Housing Survey (AHS) to obtain 

up-to-date housing statistics for the Department of Housing and Urban 

Development (HUD). Title 12, Sections 1701Z-1 and 1701Z-2g of the U.S. Code 

authorize the Secretary of HUD to collect data from public and private agencies 

and protect the confidentiality of the data. Title 12, Section 1701Z-10 mandates 

the collection of the data for the AHS. This mandate covers the collection of data 

for the 2004 AHS Metro Survey. 

Strengths: Data are collected on key policy issues, including housing. There are multiple 

years of data available. There are a large number of AI/ANs in the sample. 

Limitations: Each data collection round of the AHS Metro Survey is limited to a relatively 

small number of metropolitan areas across the nation. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to the public at no cost. 

5-17 
American Housing Survey: Metropolitan Surveys 

(continued) 

Contact 

Information: 

The American Housing Survey Branch can be contacted by email at 

ahsn@census.gov or by phone at (301) 763-3235. 

Older AHS Metro Survey data sets can be requested via HUDUSER (see 

http://www.huduser.org/datasets/ahs/ahsprev.html for list of specific datasets 

available). 

Tables, reports and the actual data for 1998, 2002, and 2004 can be downloaded 

from: http://www.census.gov/hhes/www/housing/ahs/nationaldata.html. 

5-18 
Annual Survey of Jails (ASJ) 

Sponsor: U.S. Department of Justice (DoJ)/Bureau of Justice Statistics (BJS) 

Description: The Annual Survey of Jails (ASJ) provides an annual source of data on local jails 

and jail inmates. Data on the size of the jail population and selected inmate 

characteristics are obtained every five to six years from the Census of Jails (also 

profiled in this catalog). In each of the years between the full censuses, a sample 

survey of jails, the ASJ, is conducted to estimate baseline characteristics of the 

nation's jails and inmates housed in these jails. Data are supplied on inmate 

characteristics, admissions and releases, growth in the number of jail facilities, 

changes in their capacities and level of occupancy, growth in the population 

supervised in the community, changes in methods of community supervision, and 

crowding issues in local jails. 

Relevant Policy 

Issues: 

Rates of Involvement with Justice System. 

Data Type(s): Survey 

Unit of 

Analysis: 

Jails 

Identification 

of AI/AN/NA: 

On June 28, 2002, how many persons CONFINED in your jail facilities were: 

• White, not of Hispanic origin 

• Black or African American, not of Hispanic origin 

• American Indian/Alaska Native (AI/AN) 

• Asian 

• Hispanic or Latino 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• Other categories in your information system (Specify) 

AI/AN/NA 

Population in 

Data Set: 

The nationally-representative sample included all public and private jails in 

selected jail jurisdictions and 50 regional jails. Each of these facilities reports on 

the number of AI/AN and NH/PI confined in their facility at midyear. 

Geographic 

Scope: 

The geographic scope of the data is national. All 50 states and the District of 

Columbia are included. Analysis may be possible by state, county, and city 

depending on sample size within each subgroup. 

Date or 

Frequency: 

The survey has been conducted annually since 1982, except every 5th year when 

the National Jail Census is conducted. 

Data Collection 

Methodology: 

Data are collected primarily by mail with a web-based reporting option and 

telephone follow-up for nonrespondents. 

Participation: Optional, without incentives 

5-19 
Annual Survey of Jails (ASJ) 

(continued) 

Response Rate: After follow-up phone calls, 100 percent of the jails provided data on key 

variables such as number of confined persons, number of male and female 

inmates by adult and juvenile, number of inmates by race and Hispanic origin, 

average daily population (ADP), and total rated capacity of jails. Data were not 

imputed for any items. 

Sampling 

Methodology: 

Using information from the 1999 Census of Jails, a sample of jail jurisdictions 

was selected for the 2002 survey. The sample included all jail facilities (948) in 

878 jurisdictions. Large jails and regional jails were in the sample with certainty. 

The remaining jurisdictions were stratified into two groups: jurisdictions with at 

least one juvenile inmate and jurisdictions holding adults only. Using stratified 

probability sampling, 474 jurisdictions were then selected from 10 strata based on 

the average daily population in the 1999 census. The sample selection was 

designed to precisely estimate the average daily population and one-day inmate 

population (i.e., highest population in the preceding month) for the entire nation. 

Analysis: Standard errors are included in the documentation for some estimates but not for 

AI/AN or NH/PI estimates. These are included in an “other” category. 

Strengths: Data are collected on a key policy issue, involvement with the justice system. 

There are multiple years of data available. The 2002 Annual Survey of Jails had a 

very high response rate (100 percent of jails provided data on critical items). The 

documentation is very detailed and readily accessible through the Internet. 

Limitations: This is a facility-level rather than an individual-level data set. Counts of AI/AN or 

NH/PI persons being confined are available for the facilities, by state, and 

nationally. This information cannot be associated with individual characteristics 

for additional analysis. 

Other: Researchers also may be interested in the Annual Survey of Jails in Indian 

Country (also described in this catalog). 

Access 

Requirements 

and Use 

Restrictions: 

Data set is available to the public at no cost. 

Contact 

Information: 

2002 data and documentation can be downloaded at: 

http://webapp.icpsr.umich.edu/cocoon/NACJD-STUDY/04428.xml. 

Data archive information: 

National Archive of Criminal Justice Data 

ICPSR 

University of Michigan 

Institute for Social Research 

P.O. Box 1248 

Ann Arbor, MI 48106-1248 

5-20 
Annual Survey of Jails (ASJ) 

(continued) 

(800) 999-0960 

(313) 763-5011 

nacjd@icpsr.umich.edu 

http://webapp.icpsr.umich.edu/cocoon/NACJD-SERIES/00007.xml 

Questions for the Bureau of Justice Statistics should be addressed to: 

James Stephan 

Statistician 

Bureau of Justice Statistics 

810 Seventh Street, NW 

Washington, DC 20531 

USA 

(202) 616-3289 

James.Stephan@usdoj.gov or 

askbjs@usdoj.gov 

5-21 
Behavioral Risk Factor Surveillance System (BRFSS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC) 

Description: The objective of the Behavioral Risk Factor Surveillance System (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 in the adult population. Factors assessed by the BRFSS include tobacco 

use, health care coverage, HIV/AIDS knowledge and prevention, and physical 

activity. 

Relevant Policy 

Issues: 

Measurement of Health Status. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Question: Which one or more of the following would you say is your race? 

• White 

• Black/African American 

• Asian 

• Native Hawaiian/Pacific Islander (NH/PI) 

• American Indian or Alaska Native (AI/AN) 

• Other 

If more than one response is given, the following question is asked for 

clarification: Which of these groups best represent your race? 

• White 

• Black/African American 

• Asian 

• Native Hawaiian/Pacific Islander (NH/PI) 

• American Indian or Alaska Native (AI/AN) 

• Other 

AI/AN/NA 

Population in 

Data Set: 

In 2005, out of 356,112 total records, 6,904 respondents reported AI/AN as the 

race that best described them and 1,503 reported NH/PI as the race that best 

described them. 

Geographic 

Scope: 

The geographic scope of the study is national. Over time, the number of states 

participating in the survey has increased, so that by 1994, 50 states, the District of 

Columbia, Puerto Rico, Guam, and the Virgin Islands were participating in the 

BRFSS. 

5-22 
Behavioral Risk Factor Surveillance System (BRFSS) 

(continued) 

The following geographic indicators are available on the public use file for 

analysis: state, county, zip code, indicator of residence within or outside a 

metropolitan statistical area. 

Date or 

Frequency: 

Data collection has been conducted yearly since 1984. 

Data Collection 

Methodology: 

BRFSS field operations are managed by state health departments, which follow 

guidelines provided by the CDC. These health departments participate in 

developing the survey instrument and conduct the interviews either in-house or 

through use of contractors. The data are transmitted to the CDC's National Center 

for Chronic Disease Prevention and Health Promotion's Behavioral Surveillance 

Branch for editing, processing, weighting, and analysis. 

In 2005, all 53 states and territories used computer-assisted telephone 

interviewing (CATI). The core portion of the questionnaire lasts an average of 10 

minutes. Interview time for modules and state-added questions is dependent upon 

the number of questions asked, but generally extend the interview period by an 

additional 5 to 10 minutes. 

Participation: Optional, without incentives 

Response Rate: Across the 53 states and territories, the median overall response rate in 2004 was 

41.2 percent (minimum was 22.0 percent and maximum was 63.4 percent). The 

overall response rate assumes that all likely households are households and that 

98 percent of known or probable households contain an adult who uses the phone 

number. 

Sampling 

Methodology: 

In a telephone survey such as the BRFSS, a sample record is one telephone 

number in the list of all telephone numbers selected for dialing. In order to meet 

the BRFSS standard for participating states’ sample designs, sample records must 

be justifiable as a probability sample of all households with telephones in the 

state. All participating areas met this criterion in 2004. Fifty–one projects used a 

disproportionate stratified sample design. Puerto Rico, Guam and the Virgin 

Islands used a simple random sample design. 

Analysis: Overall approximately 95 percent of U.S. households have telephones, but 

coverage ranges from 87 to 98 percent across states and also varies for subgroups. 

People living in the South, minorities, and those in lower socioeconomic groups 

typically have lower telephone coverage. No direct method of compensating for 

non-telephone coverage is employed by the BRFSS; however, weighting 

adjustments for differences in probability of selection and non-response may 

compensate to some degree for non-telephone coverage. 

Strengths: Data are collected on a key policy issue, health. Multiple years of data are 

available. Large sample sizes are available for AI/ANs and NH/PIs. 

5-23 
Behavioral Risk Factor Surveillance System (BRFSS) 

(continued) 

Limitations: Many states included in the study have significant AI/AN/NA populations that 

may not be reached through phone interviews because they do not have 

telephones. 

Other: An edited and weighted data file is provided to each participating health 

department for each year of data collection, and summary reports of state-specific 

data are prepared by CDC. Health departments use the data for a variety of 

purposes, including identifying demographic variations in health related 

behaviors, targeting services, addressing emergent and critical health issues, 

proposing legislation for health initiatives, and measuring progress toward state 

and national health objectives. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to public at no cost. 

Contact 

Information: 

Suzianne Ellington Garner, MPA 

Deputy Chief, Behavioral Surveillance Branch 

Division of Adult and Community Health 

CDC 

4770 Buford Hwy, MS K-66 

Atlanta, GA 30341 

(770) 488-6005 

suzianne.garner@cdc.hhs.gov 

Data can be accessed at http://www.cdc.gov/brfss. 

5-24 
Consumer Assessment of Healthcare Providers and Systems (CAHPS) 

Health Plan Survey Response Data 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Agency for Healthcare 

Research and Quality (AHRQ) 

Description: The Consumer Assessment of Healthcare Providers and Systems (CAHPS) 

program develops and supports the use of a family of standardized surveys that 

ask consumers and patients to report on and evaluate their experiences with health 

care. CAHPS surveys include ratings of personal doctors and other health care 

staff, as well as an overall rating of the health plan and ask patients and 

consumers to report on their experiences with health care services. CAHPS 

sponsors include various public and private organizations that fund the 

administration of a CAHPS survey by collecting data from consumers and 

patients of a particular health plan. 

There are two data sets available to researchers. The core database consists of 

responses to the CAHPS Health Plan Survey. Participating sponsors submit these 

data at the individual respondent level in accordance with specifications provided 

by the CAHPS Database. All health plan identifiers are removed from the public 

use database. Respondent records contain a unique health plan ID so responses 

from each health plan can be grouped together, but health plans can not be 

identified. The data also do not include respondent names, addresses, telephone 

numbers, and member ID numbers. Certain survey administration data (e.g., 

mode of administration, survey language) and descriptive information (e.g., state) 

may also be included in this data set. The second database is the Survey 

Administration and Health Plan Characteristics Data. This data set includes 

information regarding survey administration, such as mode of administration, 

response rates, and dates of survey completion, as well as descriptive information 

relating to each of the sampled units (e.g., health plan products), such as type of 

organization, size of enrollment, tax status and ownership, and location. 

Relevant Policy 

Issues: 

Measurement of Health Status and Factors Contributing to Measured Health 

Disparities. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Race is self-reported, using the following question: 

What is your race? Please mark one or more. 

• White 

• Black or African-American 

• Asian 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• American Indian or Alaska Native (AI/AN) 

• Other 

5-25 
Consumer Assessment of Healthcare Providers and Systems (CAHPS) 

Health Plan Survey Response Data 

(continued) 

AI/AN/NA 

Population in 

Data Set: 

Number of Records per Year by Type of Plan 

Adult Commercial Plans:

2005: Out of 123,272 records, 1,745 are AI/AN and 1,006 are NH/PI 

2004: Out of 111,680 records, 1,745 are AI/AN and 942 are NH/PI 

2003: Out of 114,063 records, 1,390 are AI/AN and 888 are NH/PI 

2002: Out of 94,546 records, 1,286 are AI/AN and 744 are NH/PI 

2001: Out of 165,500 records, 2,732 are AI/AN and 1,294 are NH/PI 

Child Commercial Plans:

2005: Out of 2,661 records, 28 are AI/AN and 9 are NH/PI 

2004: Out of 7,024 records, 77 are AI/AN and 29 are NH/PI 

2003: Out of 1,866 records, 30 are AI/AN and 2 are NH/PI 

2002: Out of 5,600 records, 106 are AI/AN and 22 are NH/PI 

2001: Out of 9,913 records, 153 are AI/AN and 118 are NH/PI 

Adult Medicaid Plans:

2005: Out of 32,115 records, 1,011 are AI/AN and 194 are NH/PI 

2004: Out of 59,515 records, 1,982 are AI/AN and 1,188 are NH/PI 

2003: Out of 39,275 records, 1,143 are AI/AN and 211 are NH/PI 

2002: Out of 48,109 records, 1,942 are AI/AN and 1,681 are NH/PI 

2001: Out of 45,127 records, 1,596 are AI/AN and 1,875 are NH/PI 

Child Medicaid Plans:

2005: Out of 40,204 records, 1,184 are AI/AN and 1,354 are NH/PI 

2004: Out of 86,159 records, 2,291 are AI/AN and 806 are NH/PI 

2003: Out of 31,082 records, 1,153 are AI/AN and 1,079 are NH/PI 

2002: Out of 60,534 records, 2,018 are AI/AN and 472 are NH/PI 

2001: Out of 36,940 records, 1,322 are AI/AN and 268 are NH/PI 

State Children's Health Insurance Program (SCHIP):

2005: Out of 1,252 records, 5 are AI/AN and 4 are NH/PI 

2004: Out of 16,657 records, 359 are AI/AN and 143 are NH/PI 

2003: Out of 19,061 records, 402 are AI/AN and 132 are NH/PI 

2002: Out of 18,910 records, 349 are AI/AN and 203 are NH/PI 

(SCHIP data were not collected in 2001.) 

Geographic 

Scope: 

The geographic scope of CAHPS is national. The data files also include a state 

indicator. Some state-level analysis may be possible, but will depend on the 

number of records available for each state. State coverage varies from year to 

year, depending on which providers submit data for inclusion in the CAHPS 

Database. Details of the number of records per state are available in the CAHPS 

Health Plan Survey Chartbook, which is released on an annual basis and can be 

accessed at: 

https://www.cahps.ahrq.gov/content/NCBD/Chartbook/2005_Chartbook.pdf 

5-26 
Consumer Assessment of Healthcare Providers and Systems (CAHPS) 

Health Plan Survey Response Data 

(continued) 

Date or 

Frequency: 

Schedules for collecting CAHPS data vary by sponsor. The CAHPS Database is 

compiled every year, collecting data from health plans that have completed data 

collection in the past 12 months. Data are currently available from 2001 to 2005 

(SCHIP data are available from 2002 to 2005). Data from 1998 to 2000 also exist 

in the CAHPS Database, but the quality of the data cannot be assured, and the 

CAHPS staff advises against using these data. 

Beginning in 2006, the CAHPS Database will be expanded to include CAHPS 

Hospital Survey data, and will eventually be further expanded to include CAHPS 

Clinician and Group Survey Data. These survey data will all include unique 

respondent identifiers as well. 

Aggregation: Researchers who are interested in combining multiple years of data for 

aggregation should consider that the basic reporting unit for CAHPS is the 

provider, even though the survey is at the individual respondent level. Across 

multiple years there will be differences in the providers submitting data; for 

example, in one year more large providers may submit and in another more 

Western providers. An aggregated data set will not necessarily be representative 

of the population by year or in combination. These differences in providers by 

year cannot be described, as the provider-level unique ID number is not 

consistently assigned from year to year. Also, each year, the data from the 

CAHPS surveys are case-mix adjusted in order to create the CAHPS benchmark. 

Researchers should consider re-running the case-mix adjustment (called the 

CAHPS Macro) on data aggregated across multiple years. 

Data Collection 

Methodology: 

Data collection methodology varies by the CAHPS sponsor or vendor 

administering the CAHPS survey. Some information on the mode of data 

collection is included in the public use data set (e.g., each completed survey is 

coded either M = mail complete, T = telephone complete, or I = Internet 

complete). 

Additionally, the CAHPS Program provides the following guidelines for sponsors 

concerning data collection: "A mixed-mode data collection protocol involving 

both mail and telephone is more likely to achieve a desired response rate than will 

either mode alone. Research conducted by the CAHPS grantees shows that 

differences in the types of responses collected by these different modes are 

minimal (these differences are called “mode effects”), so telephone and mail can 

be used together with confidence." 

Participation: Optional, without incentives 

Response Rate: Response rates are calculated and provided by the different CAHPS survey 

vendors and sponsors who submit data to the CAHPS Database. The 2005 

CAHPS Database self-reported response rates vary by sponsor and range from 14 

percent to 71 percent. The breakdown of response rates by population type are as 

follows: 

5-27 
Consumer Assessment of Healthcare Providers and Systems (CAHPS) 

Health Plan Survey Response Data 

(continued) 

Adult Commercial: 19% - 71% 

Adult Medicaid: 17% - 59% 

Child Medicaid: 14% - 50% 

Sampling 

Methodology: 

Sampling methods for CAHPS vary by sponsor. CAHPS provides guidelines for 

selecting a sample, including determining eligibility, calculating the estimated 

sample size needed for general reporting, and creating a frame of all covered lives 

or sampling policyholders only. 

Strengths: Some CAHPS data sets contain a large number of AI/AN/NA respondents. Data 

are collected on key policy issues, including self-reported health status. There are 

multiple years of data available. 

Limitations: The CAHPS survey is not administered in a consistent fashion. Instead, the 

CAHPS Database is a collection of surveys administered at the level of health 

plans. As such, not all health plans participate each year, so the mix of plans will 

vary across years. Additionally, sampling and data collection methods vary by 

plan, as plans hire vendors to administer the survey and these methods will vary 

by vendor. 

Access 

Requirements 

and Use 

Restrictions: 

To access these data, researchers must submit a data release agreement and a 

description of the proposed research, as well as IRB clearance documentation. 

Contact 

Information: 

Contact Dale Shaller, Managing Director, with any questions about the CAHPS 

Database and data requests. 

Email: d.shaller@comcast.net 

Phone: (651) 430-0759 

Send proposals for data access and signed Data Use Agreements to: 

CAHPS Project Staff 

Westat 

1650 Research Boulevard 

RA1159 

Rockville, MD 20850 

Fax: (301) 251-1500 

The CAHPS Database website is located at: 

https://www.cahps.ahrq.gov/content/ncbd/ncbd_Intro.asp?p=105&s=5 

Research Brief: Racial and Ethnic Disparities in the Experiences of Health Care 

Consumers. Published in November 2005 by the National CAHPS Benchmarking 

Database, under AHRQ Contract Number 290-0I-0003. Written by Karen Onstad. 

Reports of 

Interest: 

5-28 
California Health Interview Survey (CHIS) 

Sponsor: UCLA Center for Health Policy Research 

Description: The California Health Interview Survey (CHIS) is a biennial telephone survey 

that began in 2001. CHIS collects information on California children (0-11 yrs), 

adolescents (12-17 yrs), and adults (18 and older) about their health and health 

care access. Specific topics addressed by the survey include health status, health 

conditions, health-related behaviors, health insurance coverage, access to and use 

of health care services, and the health and development of children and 

adolescents. CHIS data are used to produce population-based estimates for most 

California counties, all major ethnic groups, and several ethnic subgroups within 

California. The overall sample is representative of the state’s non-institutionalized 

population. 

Relevant Policy 

Issues: 

Measurement of Health Status, Disease-specific Measurements, Key Health 

Disparities, Factors Contributing to Measured Health Disparities, Measures of 

Well-being for Children, and Measures of Well-being for Elders. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

The CHIS interview asks several questions about race. Below are those relevant 

to the identification of AI/AN/NA in this data source. 

1. Would you describe yourself as Native Hawaiian, Other Pacific Islander, 

American Indian, Alaska Native, Asian, Black, African American, or White? 

(Interviewers are instructed to code all that apply.) 

 

• White 

• Black or African American 

• Asian 

• American Indian or Alaska Native (AI/AN) 

• Other Pacific Islander (OPI) 

• Native Hawaiian (NH) 

• Other (Specify) 

2. You said, American Indian or Alaska Native, and what is your tribal 

heritage? If you have more than one tribe, tell me all of them. 

3. Are you an enrolled member in a federally or state recognized tribe? 

4. Which tribe are you enrolled in? 

5. You said you are Pacific Islander. What specific ethnic group are you, such 

as Samoan, Tongan, or Guamanian? If you are more than one, tell me all of 

them. 

5-29 
California Health Interview Survey (CHIS) 

(continued) 

AI/AN/NA 

Population in 

Data Set: 

The CHIS 2003 Random Digit Dial (RDD) sample is representative of 

California’s non-institutionalized population. The numbers below are based on 

any mention of a specific race or ethnicity (rather than the single-race categories): 

Adults

Total number of records: 42,044 

AI/AN, Hispanic: 740 

AI/AN, Non-Hispanic: 1,157 

NH/PI, Hispanic: 61 

NH/PI, Non-Hispanic: 199 

Adolescents (ages 12-17) 

Total number of records: 4,010 

AI/AN, Hispanic: 212 

AI/AN, Non-Hispanic: 153 

NH/PI, Hispanic: 27 

NH/PI, Non-Hispanic: 39 

Children (ages 0-11) 

Total number of records: 8,156 

AI/AN, Hispanic: 195 

AI/AN, Non-Hispanic: 175 

NH/PI, Hispanic: 34 

NH/PI, Non-Hispanic: 57 

AI/AN/NA 

Subpopulations: 

Data source allows identification of federally recognized tribes: Apache, 

Blackfeet, Cherokee, Choctaw, Mexican American Indian, Navajo, Pomo, 

Pueblo, Sioux, Yaqui. 

Additional subpopulation categories include Native Hawaiian alone, Pacific 

Islander alone, and a breakdown by Pacific Island (i.e., Samoan/American, 

Samoan, Guamanian, Tongan, Fijian, Polynesian, and Other Pacific Islander). 

Sample size for some Tribes or Islands may be too small for analysis. 

Geographic 

Scope: 

The geographic scope of the study is the state of California. Additional 

geographic identifiers include counties, zip codes, and exact longitudes and 

latitudes of the residence for about 80 percent of the sample. 

Date or 

Frequency: 

The CHIS survey began in 2001 and is fielded every 2 years. Data from 2003 are 

the most recent data that are publicly available. 

Data Collection 

Methodology: 

Data are collected using a computer assisted telephone interviewing (CATI) 

system, with respondents selected through a geographically stratified random 

digit dialing approach. One adult in a household is selected and responds for 

him/herself and one sampled child (0-11 yrs) if there are any in the household. 

Adolescents respond for themselves, after approval is given from their guardian. 

Up to three individuals in any given household may be sampled (adult, 

5-30 
California Health Interview Survey (CHIS) 

(continued) 

adolescent, child). In addition to English, the survey is fielded in five additional 

languages (Spanish, Mandarin, Cantonese, Korean and Vietnamese). 

Participation: Optional, without incentives 

Response Rate: Most recent response rate was 33.5 percent (composite of screener and interview 

completion rates). 

Sampling 

Methodology: 

CHIS employs a multi-stage sample design in which the state of California is 

divided into 41 geographic sampling strata (primarily counties) and within each 

geographic stratum, households were selected through random-digit dialing. 

Within each household, an adult (age 18 and over) respondent was randomly 

selected, and for those households with adolescents (ages 12-17) and children 

(under age 12), one of each was randomly selected for interview. 

Analysis: The complex survey design of the CHIS requires that adjustments to weighting 

and standard error calculations be made in order to produce robust estimates. 

Failure to make these adjustments can yield estimates where the standard error 

appears smaller than it actually should be, suggesting the accuracy of the estimate 

is better than it actually is. The technique used to address this adjustment process 

in the CHIS Public Use Files is replication, and the data set includes the set of 

replicate weights for users to apply in the calculation of standard errors. Special 

software is required to conduct statistical analyses using replicate weights. 

Strengths: The CHIS data sets contain a large number of AI/AN/NA respondents. The data 

are collected on key policy issues, including health and child welfare. There are 

multiple years of data available. The sample size of the overall survey is of 

sufficient size to allow for analyses of racial/ethnic subgroups of interest, which 

includes a breakout of Native Hawaiian from Pacific Islander as well as specific 

tribal affiliations. While sample sizes for certain tribes are small, some tribes do 

have sufficient sample size to permit at least basic descriptive statistical analyses. 

Furthermore, many of the questions fielded in the CHIS are taken from the 

National Health Interview Survey, which can provide a national benchmark for 

many variables. 

Limitations: While a very large survey, results are only generalizable to the state of California. 

The sample does not include an institutionalized population or people without 

telephones. Some tribes and other subpopulations have very small sample size 

that will allow only minimal analyses. The response rate is low. 

Access 

Requirements 

and Use 

Restrictions: 

CHIS Public Use Files are available through a data use agreement at no cost. 

5-31 
California Health Interview Survey (CHIS) 

(continued) 

Contact 

Information: 

The main website for the survey is located at http://www.chis.ucla.edu/. Data can 

be downloaded at this site. There is also an on-line analysis query system named 

"AskCHIS." In addition, potential users can link to a wide variety of other CHISrelated information at this site. 

California Health Interview Survey 

UCLA Center for Health Policy Research 

10960 Wilshire Blvd, Suite 1550 

Los Angeles, CA 90024 

Toll free: (866) 275-2447 

E-mail: chis@ucla.edu 

5-32 
Census 2000

Sponsor: U.S. Department of Commerce/U.S. Census Bureau 

Description: The Decennial Census occurs every 10 years to count the population and housing 

units for the entire United States. Its primary purpose is to provide the population 

counts that determine how seats in the U.S. House of Representatives are 

apportioned. The U.S. Census Bureau provides three types of data products that 

may be useful to the interested researcher: 

• Tabular data in the form of summary files, 

• Raw data in the form of Public Use Microdata Sample files (PUMS 

files), and 

• Census briefs and special reports. 

Tabular data: Summary files

The U.S. Census Bureau has released a series of summary files that present 

Census 2000 data in tabular form. The primary summary files are: 

1. Summary File 1: This file contains 286 detailed tables focusing on age, 

sex, households, families, and housing units. These tables provide indepth figures by race and Hispanic origin. Counts are also provided for 

over 40 American Indian and Alaska Native tribes and for groups within 

race categories. The race categories also include 12 Native Hawaiian and 

other Pacific Islander groups. 

2. Summary File 2: This file contains 47 detailed tables focusing on age, 

sex, households, families, and occupied housing units for the total 

population. These tables are repeated for 249 detailed population groups, 

including American Indian, Alaskan Native, 9 Native Hawaiian or other 

Pacific Islander groups, and 40 American Indian and Alaska Native 

tribes. For each of these groups, data are provided for that group alone 

and in combination with one or more other races.

3. Summary File 3: This file consists of 813 detailed tables of Census 2000 

social, economic and housing characteristics compiled from a sample of 

approximately 19 million housing units (about 1 in 6 households) that 

received the Census 2000 long-form questionnaire. Fifty-one tables are 

repeated for 9 major race categories including American Indian/Alaska 

Native and Native Hawaiian/Other Pacific Islander.

4. Summary File 4: This file consists of 213 population tables and 110 

housing tables. Each table is repeated for 336 population groups: the 

total population, 132 race groups, 78 American Indian and Alaska Native 

tribe categories (reflecting 39 individual tribes), and 9 Native Hawaiian 

or other Pacific Islander groups. 

5. The American Indian and Alaska Native Summary File (AIANSF):

These sample data are presented in 213 population tables and 110 

housing tables. The tables are repeated for the total population, the total

5-33 
Census 2000 

(continued)

 American Indian and Alaska Native population, the total American 

Indian population, the total Alaska Native population, and for 1,081 

additional self-reported American Indian and Alaska Native tribes and 

villages without consideration of any designation of federal or state 

recognition. (Please note that the AIANSF is profiled separately in 

this data catalog.)

Raw data: 1 percent and 5 percent PUMS files

The PUMS files contain records of households, people, or housing units with 

identifying information removed and other precautions taken to prevent the 

violation of confidentiality. PUMS files often show data only for identified 

geographic areas (such as states) that meet a certain population threshold. The 1 

percent PUMS files have state-level Census 2000 data containing individual 

records of the characteristics for a 1 percent sample of people and housing units. 

The 5 percent PUMS files contain similar information for a 5 percent sample of 

people and housing units. 

Census briefs and special reports

The Census 2000 Brief series focus on discussing key topics covered by the 

Census and exploring the geographic distribution of the topics. The Census 2000 

Special Report series provides an in-depth analysis of Census 2000 population 

and housing topics. 

Examples of census briefs and special reports of particular interest include: 

• The American Indian and Alaska Native Population: 2000 (C2KBR/01-

15) 

• American Indian and Alaska Native Tribes for the United States, 

Regions, Divisions, and States (PHC-T-18) 

• We the People: American Indians and Alaska Natives in the United 

States (CENSR-28) 

• The Native Hawaiian and other Pacific Islander Population: 2000

(C2KBR/01-14) 

Relevant Policy 

Issues: 

Demographic and Economic Indicators, Measurement of Health Status, Income 

Status, Unemployment Rates, Economic Assistance Program Participation Rates, 

Educational Attainment, Measures of Well-being for Families/Households, 

Factors Contributing to Well-being Disparities of Families, Housing Quality, 

Type of Housing, Housing Ownership, Rental Unit Quality and Cost, and 

Transportation Availability. 

Data Type(s): Census survey 

Unit of Analysis: Individual 

Identification 

of AI/AN/NA: 

As described above, identification of the AI/AN/NA population differs across the 

many Census 2000 data products. Some data products present the AI/AN/NA 

population into 2 groups: American Indian/Alaskan Native and Native 

Hawaiian/Other Pacific Islander while other data products provide more detailed 

5-34 
Census 2000 

(continued)

breakdowns (e.g., distinction between American Indians and Alaska Native, 

distinction between Native Hawaiian and other Pacific Islanders). Some data 

products provide detailed breakdowns of these groups presenting data for 

different tribal affiliations and different Pacific Islander groups. For example, the 

PUMS files, the AIANSF file, and Summary Files 2 and 4 present tribal 

affiliation data. 

Please note that the tribal affiliation data reflect the written entries by 

respondents, who identified themselves as AI/AN, and provided an entry for their 

enrolled or principal tribe or village. Some of the responses (for example, 

Colorado River and Village of Alakanuk) represent reservations or native 

villages. The information on tribe or village is based on self-identification 

without consideration of any designation of federal or state recognition. 

AI/AN/NA 

Population in 

Data Set: 

The following counts are reported in Profiles of General Demographic 

Characteristics: 2000 Census of Population and Housing. These data are based 

on 100 percent counts derived from the Census 2000 short form: 

Total population: 281,421,906 

American Indian and Alaska Native: 2,475,956 

Native Hawaiian: 140,652 

Guamanian or Chamorro: 58,240 

Samoan: 91,029 

Other Pacific Islander: 108,914 

AI/AN/NA 

Subpopulations: 

As described in detail above, some data products provide detailed breakdowns 

(e.g., distinction between American Indians and Alaska Native, distinction 

between Native Hawaiian and other Pacific Islanders) and some present data for 

different tribal affiliations and different Pacific Islander groups. 

Geographic 

Scope: 

The geographic scope of the study is national. Geographic areas covered by the 

data in the Census 2000 summary files include: 

• Region (e.g., Midwest, Northeast, South, West) 

• Division (e.g., East North Central, East South Central, Middle Atlantic, 

Mountain, New England) 

• State 

• County (county subdivision, census tract) 

• Place (cities, towns, municipalities) 

• Consolidated cities 

• American Indian Area/Alaska Native Area/Hawaiian Homeland (including 

reservations or statistical entities, off-reservation trust lands, Hawaiian 

homelands, tribal census tracts, tribal subdivisions and remainders) 

• Alaska Native Regional Corporation (e.g., Ahtna Alaska Native Regional 

Corporation, Aleut Alaska Native Regional Corporation, Arctic Slope 

Alaska Native Regional Corporation) 

• Metropolitan Statistical Area, Primary Metropolitan Statistical Area 

• New England County Metropolitan Area 

5-35 
Census 2000 

(continued)

• Urban areas 

Geographic areas covered by the Census 2000 PUMS data include: 

• Region (e.g., Midwest, Northeast, South, West) 

• Division (e.g., East North Central, East South Central, Middle Atlantic, 

Mountain, New England) 

• State 

• Public Use Microdata Area Code (PUMA) 

• Super Public Use Microdata Area Code (SuperPUMA) 

• Metropolitan Area (MA): MSA/CMSA for PUMA and SuperPUMA 

Date or 

Frequency: 

The Census is conducted every 10 years in years ending in zero. The next census 

is scheduled for 2010. Data are available for each year since 1790. American 

Indians were first enumerated as a separate group in the 1860 Census. The 1890 

census was the first to count American Indians, including some tribes, 

throughout the country. 

Data Collection 

Methodology: 

Census 2000 data were collected by mail, telephone, personal interview, and 

Internet. 

Participation: Mandatory 

Response Rate: The national final response rate for Census 2000 was 67 percent and represents 

responses received by mail, telephone or over the Internet through September 7, 

2000. The final response rates for 117 American Indian Areas are listed at the 

following website: http://www.census.gov/dmd/www/response/disp-fro-res.txt. 

Sampling 

Methodology: 

Basic demographic and housing questions (for example, race, age, and 

relationship to householder) were asked for every person in all housing units in 

the United States. A sample of housing units was also selected to receive more 

detailed questions in the long form of Census 2000, containing items such as 

income, occupation, and housing costs. The sampling unit for the long form 

Census 2000 was the housing unit, including all occupants. There were four 

different housing unit sampling rates: 1-in-8, 1-in-6, 1-in-4, and 1-in-2 (designed 

for an overall average of about 1-in-6). The Census Bureau assigned these 

varying rates based on precensus occupied housing unit estimates of various 

geographic and statistical entities, such as incorporated places and interim census 

tracts. For people living in group quarters or those enumerated at long-formeligible service sites (shelters and soup kitchens), the sampling unit was the 

person and the sampling rate was 1-in-6. 

Analysis: Detailed information regarding the design effects and standard errors for each of 

the 2000 Census PUMS files and the summary files is available for download 

from online links on the Census 2000 website. 

Authorization: The Census is mandated by the U.S. Constitution, Article I, Section 2. 

Participation in the Census is required by law set forth in Sections 141 and 193 

of Title 13 of the United States Code. 

5-36 
Census 2000 

(continued)

Strengths: The Census 2000 PUMS files and summary files contain a representative sample 

of the AI/AN population and selected tribes and villages. The Census 2000 

PUMS files and summary files also contain a representative sample of the NH/PI 

population with some data products providing information on select OPI groups. 

Data are collected on key policy issues. The U.S. Census Bureau's website 

provides extremely comprehensive documentation on the methodology, results, 

and interpretation of census data. 

Limitations: The Census 2000 PUMS files are a very large set of complex files. Considerable 

expertise in working with data of these types will likely be required. The 

summary files are less complex but more numerous, thus finding the particular 

table(s) of interest may be challenging. 

Access 

Requirements and 

Use Restrictions: 

Both the PUMS data and the summary files are available to the public at no cost. 

Contact 

Information: 

A U.S. Census Bureau list of contacts by subject area is available at the 

following website: http://www.census.gov/contacts/www/c-census2000.html. 

The Census 2000 summary files as well as supporting documentation are 

available at the U.S. 2000 Census website: 

http://factfinder.census.gov/servlet/DatasetMainPageServlet?_program=DEC&_s

ubmenuId=datasets_1&_lang=en. 

5-37 
Census 2000 - The American Indian and Alaska Native Summary File 

Sponsor: U.S. Department of Commerce/U.S. Census Bureau 

Description: As mandated by the U.S. Constitution, the Decennial Census is conducted every 

10 years to count the population and housing units for the entire United States. 

The American Indian and Alaska Native Summary File (AIANSF) is based on 

Census 2000 data. Data from Census 2000 on the American Indian and Alaska 

Native population (AI/AN) are derived from a limited number of basic questions 

asked of the entire American Indian and Alaska Native population and every 

corresponding housing unit (referred to as the 100-percent questions found on the 

“short form”), and from additional questions asked of a sample of the population 

and housing units (referred to as the sample questions, found on the “long 

form”). The AIANSF provides sample data based on both the 100-percent and 

the sample questions. 

Data in the AIANSF include, for example, age, Hispanic or Latino origin, 

household relationship, sex, educational attainment, veteran status, income and 

poverty status, housing tenure (owner-or renter-occupied), physical housing 

characteristics, and mortgage and rental cost characteristics. These data are 

available for the total AI/AN population, the total American Indian population, 

the total Alaska Native population, and for 1,081 self-reported AI/AN tribes or 

villages without consideration of any designation of federal or state recognition. 

Relevant Policy 

Issues: 

Demographic and Economic Indicators, Measurement of Health Status, Income 

Status, Unemployment Rates, Economic Assistance Program Participation Rates, 

Educational Attainment, Measures of Well-being for Families/Households, 

Factors Contributing to Well-being Disparities of Families, Housing Quality, 

Type of Housing, Housing Ownership, Rental Unit Quality and Cost, 

Transportation Availability. 

Data Type(s): Census survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Tribal data provided in the AIANSF reflect the written entries by respondents, 

who identified themselves as AI/AN, and provided an entry for their enrolled or 

principal tribe or village. Some of the responses (for example, Colorado River 

and Village of Alakanuk) represent reservations or native villages. The 

information on tribe or village is based on self-identification without 

consideration of any designation of federal or state recognition. 

The listing of American Indian and Alaska Native tribes and villages is derived 

from the American Indian Tribal Detailed Classification List for the 1990 census, 

which was expanded to include individual Alaska Native villages, when provided 

as a written response to the question on race. The list was updated based on a 

December 1997 Federal Register Notice, entitled Indian Entities Recognized and 

5-38 
Census 2000 - The American Indian and Alaska Native Summary File 

(continued) 

Eligible to Receive Service From the United States Department of Interior, 

Bureau of Indian Affairs, issued by the Office of Management and Budget. The 

list of 1,081 tribes or villages for which summary tables are available can be 

found in the technical report for the AIANSF sample file available at: 

http://www.census.gov/prod/cen2000/doc/aiansf.pdf. 

AI/AN/NA 

Population in 

Data Set: 

Unweighted counts of AI/AN/NA in the AIANSF are not available, but given the 

scope of the Census, the counts are expected to be sufficiently high to support 

most analyses. 

AI/AN/NA 

Subpopulations: 

The AIANSF allows identification of members of federally and state-recognized 

tribes and villages by tribe or village. Subpopulations are identified by specific 

affiliation. 

Geographic 

Scope: 

The geographic scope of the study is national. Geographic areas covered by the 

data in the AIANSF include: 

• Region (e.g., Midwest, Northeast, South, West); 

• Division (e.g., East North Central, East South Central, Middle Atlantic, 

Mountain, New England); 

• State; 

• American Indian Area/Alaska Native Area/Hawaiian Homeland (e.g., 

Acoma Pueblo and Off-Reservation Trust Land, and Agua Caliente 

Reservation); 

• Alaska Native Regional Corporation (e.g., Ahtna Alaska Native Regional 

Corporation, Aleut Alaska Native Regional Corporation); 

• Metropolitan Statistical Area/Consolidated Metropolitan Statistical Area; 

• Primary Metropolitan Statistical Area; and 

• New England County Metropolitan Area. 

Date or 

Frequency: 

The Census is conducted every ten years in years ending in zero. The next census 

is scheduled for 2010. Data are available for each year since 1790. American 

Indians were first enumerated as a separate group in the 1860 Census. The 1890 

census was the first to count American Indians, including some tribes, 

throughout the country. 

Data Collection 

Methodology: 

Census 2000 data were collected by mail, telephone, personal interview, and 

Internet. 

Participation: Mandatory 

Response Rate: The national final response rate for Census 2000 was 67 percent and represents 

responses received by mail, telephone or over the Internet through September 7, 

2000. The final response rates for 117 American Indian Areas are listed at the 

following website: http://www.census.gov/dmd/www/response/disp-fro-res.txt. 

5-39 
Census 2000 - The American Indian and Alaska Native Summary File 

(continued) 

Sampling 

Methodology: 

Every person and housing unit in the United States was asked basic demographic 

and housing questions (for example, race, age, and relationship to householder). 

A sample of these people and housing units was asked more detailed questions 

about items such as income, occupation, and housing costs. The sampling unit 

for Census 2000 was the housing unit, including all occupants. There were four 

different housing unit sampling rates: 1-in-8, 1-in-6, 1-in-4, and 1-in-2 (designed 

for an overall average of about 1-in-6). The Census Bureau assigned these 

varying rates based on precensus occupied housing unit estimates of various 

geographic and statistical entities, such as incorporated places and interim census 

tracts. For people living in group quarters or those enumerated at long-formeligible service sites (shelters and soup kitchens), the sampling unit was the 

person and the sampling rate was 1-in-6. 

Analysis: Detailed information regarding the design effects and standard errors for the 

2000 Census long form is available from the following publication: Summary 

File 4- 2000 Census of Population and Housing: Technical Documentation 

(Chapter 8) and American Indian and Alaska Native Summary File Technical 

Documentation (Chapter 8). 

Authorization: The Census is mandated by the U.S. Constitution, Article I, Section 2. 

Participation in the Census is required by law set forth in Sections 141 and 193 

of Title 13 of the United States Code. 

Strengths: The AIANSF data set contains a representative sample of the AI/AN population 

and selected tribes and villages. Data are collected on key policy issues. The U.S. 

Census Bureau's website provides extremely comprehensive documentation on 

the methodology, results, and interpretation of census data. 

Limitations: The AIANSF is a very large set of complex files. Considerable expertise in 

working with data of this type will likely be required. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to the public at no cost. 

Contact 

Information: 

No specific contact information regarding the AIANSF is given, however a U.S. 

Census Bureau list of contacts by subject area is available at the following 

website: http://www.census.gov/contacts/www/c-census2000.html. 

The AIANSF data as well as supporting documentation are available at the U.S. 

2000 Census website: 

http://factfinder.census.gov/servlet/DatasetMainPageServlet?_program=DEC&_s

ubmenuId=datasets_1&_lang=en. 

5-40 
Census of Agriculture (2002) 

Sponsor: U.S. Department of Agriculture/National Agriculture Statistics Service 

Description: The Census of Agriculture provides periodic and comprehensive statistics about 

agricultural operations, production, operators and land use for 1992, 1997, and 

2002. Agricultural statistics are used by government, businesses, and other 

institutions. Federal, state, and local agencies use data for planning rural 

development, extension work, and agricultural research. The census is the only 

source of detailed, complete, consistent agricultural data for each county; it also 

includes such data for the states and the United States. 

Relevant Policy 

Issues: 

Economic Opportunity and Measurement of Economic/Employment Disparities 

between AI/AN/NA and General Population. 

Data Type(s): Census survey 

Unit of 

Analysis: 

Principal Operator, Farm, and Ranch 

Identification The race categories collected for the Census of Agriculture are: 

• White 

• Black or African American 

• American Indian or Alaska Native - specify tribe (AI/AN) 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• Asian 

of AI/AN/NA: 

AI/AN/NA 

Population in 

Data Set: 

Total number of farm operators: Approximately 2,464,000 

AI/AN principal farm operators: Approximately 5,268 

NH/PI principal farm operators: Approximately 280 

Note: These “unweighted” counts were calculated by taking the values reported in 

Operators by Race, Special Reports Part 1, 2002 Census of Agriculture and 

dividing them by the approximate weights for nonresponse adjustment and 

coverage adjustment (0.34 for AI/AN and 0.285 for NH/PI). 

Although self-reported tribal affiliation is collected on the Census of Agriculture, 

the data set is not available to the public and it is not clear whether analyses 

employing that information could be made available via a "Special Tabulations" 

request to the National Agricultural Statistics Service. 

Geographic 

Scope: 

The geographic scope of the Census of Agriculture is national. Geographic 

analysis also is possible by state and county. 

Date or 

Frequency: 

The Census of Agriculture is planned for every 5 years. It was conducted in 1992, 

1997, and 2002. Reports and tabulations are available for each of these data 

collection efforts. 

5-41 
Census of Agriculture (2002) 

(continued) 

Data Collection 

Methodology: 

The Census of Agriculture is a mail survey with telephone and face-to-face 

interviewing follow-up for nonrespondents. 

Participation: Mandatory 

Response Rate: Multiple response rates were calculated, but these have not been published. 

Appendix A of the 2002 Census of Agriculture Volume 1 Chapter 1: U.S. 

National Level Data report lists a minimal response rate of 75 percent. 

Appendix C of the 2002 Census of Agriculture Volume 1 Chapter 1: U.S. 

National Level Data report states that “all name and address records on the final 

[Census Mail List] received a 2002 Census of Agriculture report form." 

Sampling 

Methodology: 

Authorization: Title 7, Chapter 55, 2204g. Authority of Secretary of Agriculture to conduct 

Census of Agriculture. 

Strengths: Strengths of the data source include sufficient numbers of members of the 

AI/AN/NA population. Moreover, special efforts were undertaken in the 2002 

Census of Agriculture to address representation of AI/AN/NA farm operators. In 

addition, there are multiple years of data available. 

Limitations: The Census of Agriculture only provides indirect measures of economic wellbeing (e.g., measures of size of farms, productivity of farms, type of produce, 

livestock, etc. produced by the farm). 

Other: The U.S. Department of Agriculture also conducted a pilot project in conjunction 

with the 2002 Census of Agriculture to collect agricultural census data for farms 

and ranches on American Indian reservations in Montana, North Dakota, and 

South Dakota. This is the first time agricultural census data for American Indian 

reservations based on individual farm and ranch reports have ever been published 

by the National Agricultural Statistics Service (NASS) of the U.S. Department of 

Agriculture. The results of this pilot project have been published in American 

Indian Reservations: Montana, North Dakota, and South Dakota. Pilot Project. 

Specialty Products, Part 1. AC-02-SP-1. This report is available at 

http://www.nass.usda.gov/census/amindian.pdf. 

It is important to note that the methodology used to account for AI/AN/NA farm 

operators in this pilot project differs from that used in the overall Census of 

Agriculture. The pilot project emphasized individual-level reports while the 

overall Census uses both individual-level reports as well as aggregated 

information obtained from reservation-level reports. 

Access 

Requirements 

and Use 

Restrictions: 

Data set is not available to the public, but interested parties can request analyses. 

Also, published tables and reports are available. 

Special Tabulations are publishable, resummarized data tables from the Census of 

Agriculture or NASS surveys. Requests for Special Tabulations are considered 

5-42 
Census of Agriculture (2002) 

(continued) 

when the requested data are not published elsewhere. Depending on the 

complexity of the request, specialized analyses may be done for no or minimal 

cost. More complex requests are chargeable and the minimum charge is $500 for 

a Special Tabulation. 

Contact 

Information: 

Agriculture Statistics Hotline (800) 727-9540 

National Agricultural Statistics Service 

U.S. Department of Agriculture 

USDA-NASS 

1400 Independence Ave, SW 

Washington, DC 20250 

5-43 
Census of Jails 

Sponsor: U.S. Department of Justice (DoJ)/Bureau of Justice Statistics (BJS) 

Description: The 1999 Census of Jails is the seventh in a series of data collection efforts aimed 

at studying the nation's locally administered jails. The 1999 census enumerated 

3,365 locally administered confinement facilities that held inmates beyond 

arraignment and were staffed by municipal or county employees and 11 facilities 

maintained by the Federal Bureau of Prisons that functioned as jails. Variables 

include information on jail population by legal status (i.e., convicted or not 

convicted), age and sex of prisoners, maximum sentence, admissions and releases, 

available services and programs, structure and capacity, facility age and use of 

space, expenditure (i.e., per diem fees charged/paid for confining inmates), 

employment, staff information, and inmate health issues, which includes statistics 

on drugs, AIDS, and tuberculosis. 

Relevant Policy 

Issues: 

Rates of Involvement with Justice System. 

Data Type(s): Census survey 

Unit of 

Analysis: 

Correctional facility 

Identification 

of AI/AN/NA: 

On June 30, 1999, how many persons CONFINED in your jail facilities were: 

• White, not of Hispanic origin 

• Black or African American, not of Hispanic origin 

• American Indian/Alaska Native (AI/AN) 

• Asian 

• Hispanic or Latino 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• Other 

On June 30, 1999, how many staff employed by your jail facility were: 

• White, not of Hispanic origin 

• Black or African American, not of Hispanic origin 

• American Indian/Alaska Native (AI/AN) 

• Asian 

• Hispanic or Latino 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• Other 

•

5-44 
Census of Jails 

(continued) 

Of all CORRECTIONAL OFFICERS reported in item 23b [staff count item], 

how many were: 

• White, not of Hispanic origin 

• Black or African American, not of Hispanic origin 

• American Indian/Alaska Native (AI/AN) 

• Asian 

• Hispanic or Latino 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• Other 

AI/AN/NA 

Population in 

Data Set: 

The 1999 Census includes information on 3,084 jail jurisdictions. Each of these 

jurisdictions reports on the number of AI/AN and NH/PI confined in their 

facility(s) at mid-year. 

Geographic 

Scope: 

The geographic scope is national. This is a census of jail facilities in 46 states and 

the District of Columbia. Connecticut, Delaware, Hawaii, Rhode Island, and 

Vermont are excluded because they operate combined jail-prison facilities. 

Analysis is possible by state, county, census area, zip code or groups of zip codes, 

and individual jail jurisdictions. 

Date or 

Frequency: 

The Census of Jails, previously known as the National Jail Census, is conducted 

every 5 to 6 years for the U.S. Department of Justice, Bureau of Justice Statistics 

(BJS) by the U.S. Census Bureau. Censuses have been conducted in 1970, 1972, 

1978, 1983, 1988, 1993 and 1999. Data collection for the next census was 

conducted in 2005 and 2006. These data should be available in 2007 or early 

2008. 

Data Collection 

Methodology: 

The mailing list used for the Census of Jails is derived from a facility list 

maintained by the Census Bureau for BJS, correctional association directories, 

and other secondary sources. Census forms were mailed to facilities. In addition 

to a paper form, BJS offered respondents in large jurisdictions an electronic 

version via the Internet, which allowed them to complete and submit their 

questionnaire on-line. Follow-up included additional mail and fax requests and 

repeated telephone contacts. 

Participation: Optional, without incentives 

Response Rate: Data were obtained by mailed and web-based survey questionnaires. After 

followup phone calls, nearly 100 percent of jails provided critical data items such 

as gender of inmates held and number of inmates on June 30, 1999. 

Analysis: Because there was nonresponse and incomplete data from a small number of 

facilities on non-critical items, survey staff estimated totals for their reporting and 

imputed data for some missing non-critical items. Full documentation of these 

procedures can be found in the report located at: 

http://www.ojp.usdoj.gov/bjs/abstract/cj99.htm. 

5-45 
Census of Jails 

(continued) 

Strengths: Data are collected on a key policy issue, involvement with the justice system. 

There are multiple years of data available. 

Limitations: This data set contains facility-level rather than individual-level data. Researchers 

will have counts by facility of those being confined, staff, or corrections officers 

who have been identified as AI/AN or NH/PI. Additional analysis related to the 

characteristics or experiences of these individuals is not possible using these data. 

Access 

Requirements 

and Use 

Restrictions: 

Data sets are available to the public at no cost. 

Contact 

Information: 

1999 Census of Jails data can be downloaded at: 

http://webapp.icpsr.umich.edu/cocoon/NACJD-STUDY/03318.xml. 

Data archive information: 

National Archive of Criminal Justice Data 

ICPSR 

University of Michigan 

Institute for Social Research 

P.O. Box 1248 

Ann Arbor, MI 48106-1248 

(800) 999-0960 

(313) 763-5011 

nacjd@icpsr.umich.edu 

http://webapp.icpsr.umich.edu/cocoon/NACJD-SERIES/00068.xml 

Questions for the Bureau of Justice Statistics should be addressed to: 

James Stephan 

Statistician 

Bureau of Justice Statistics 

810 Seventh Street, NW 

Washington, DC 20531 

USA 

(202) 616-3289 

James.Stephan@usdoj.gov 

askbjs@usdoj.gov

5-46 
Census of Tribal Justice Agencies in Indian Country (2002) 

Sponsor: U.S. Department of Justice/Bureau of Justice Statistics 

Description: The Census of Tribal Justice Agencies is the first comprehensive effort to identify 

which justice agencies operate in tribal jurisdictions, what services those agencies 

provide, and what information they collect and keep. The data describe the 

characteristics of tribal law enforcement, courts and administration, corrections 

and intermediate sanctions, criminal history records, and justice statistics. The 

data also describe the criminal justice system in Indian Country including which 

tribes have sworn law enforcement personnel and the source of their authority, the 

number and types of tribal court systems, who performs the tribal detention 

function and what types of sanctions are imposed, and tribal access to state and 

national criminal record systems. 

Relevant Policy 

Issues: 

Differences in Resolution of Arrest by Type of Court System, and Factors 

Contributing to Disparities in Involvement with Justice System and Outcomes. 

Data Type(s): Census survey 

Unit of 

Analysis: 

The tribal justice agency is the unit of analysis. 

Identification 

of AI/AN/NA: 

AI/AN/NA individuals are not identified in the data set. 

AI/AN/NA 

Population in 

Data Set: 

Ninety-two percent (314 of 341) of tribal justice agencies responded to the 

survey. Participation by Alaska Native communities was not sufficient to allow 

them to be included in the final data. 

Geographic 

Scope: 

The geographic area covered by the study is national. The data set includes 314 

tribal justice agencies out of 341. The state and name of the tribe is identified for 

each justice agency. While the state of the agency's location is available, national 

analysis is recommended as there may be some states with very few agencies. 

Date or 

Frequency: 

Data were collected once. 

Data Collection 

Methodology: 

The questionnaires were distributed by mail and participants could respond by 

mail, fax, telephone, or online. 

Participation: Optional, without incentives. 

Response Rate: For tribal agencies, it was 92 percent. Responses were very poor for Alaska 

Native communities, but the rate is not reported. 

5-47 
Census of Tribal Justice Agencies in Indian Country (2002) 

(continued) 

Strengths: The key strength of this data collection is its uniqueness. This is the only 

comprehensive description of the justice system in Indian Country available. The 

response rate for AI tribes was very high (92 percent). The data are available 

online in spreadsheet format for additional analysis. 

Limitations: The key weakness was the very poor response rate by AN communities. Response 

was so low that they could not be included in the final reported data. 

Access 

Requirements 

and Use 

Restrictions: 

The data set is available to the public at no cost. 

Contact 

Information: 

The data and reports can be downloaded at: 

http://www.ojp.usdoj.gov/bjs/abstract/ctjaic02.htm. 

Questions for the Bureau of Justice Statistics should be addressed to: 

Steven W. Perry, Statistician 

Bureau of Justice Statistics 

810 Seventh Street, NW 

Washington, DC 20531 

USA 

(202) 307-0765 

askbjs@usdoj.gov

Reports of 

Interest: 

Location for final report: http://www.ojp.usdoj.gov/bjs/abstract/ctjaic02.htm. 

5-48 
Consumer Expenditure Surveys (CE) Interview and Diary Surveys 

Sponsor: U.S. Department of Labor (DoL)/Bureau of Labor Statistics (BLS) 

Description: The Consumer Expenditure Survey (CE) consists of two surveys—the quarterly 

Interview survey and the Diary survey—that provide information on the buying 

habits of American consumers, including data on their expenditures, income, and 

consumer unit (families and single consumers) characteristics. The Diary survey 

asks consumers to track their expenditures over a two-week period. The Interview 

survey gathers similar data in a series of quarterly computer-assisted interviews. 

The CE is a basic source of data for revising the items and weights in the market 

basket of consumer purchases to be priced for the Consumer Price Index. It is also 

used to construct statistical measures of consumption, for analysis of expenditure 

patterns by individual and family characteristics, in market research studies, in 

economic research, and to develop consumer guidance materials. 

Relevant Policy 

Issues: 

Measurement of Economic/Employment Disparities, Income Status, 

Unemployment Rates, and Economic Assistance Program Participation Rates. 

Data Type(s): Survey 

Unit of 

Analysis: 

Consumer Unit. A consumer unit consists of any of the following: (1) all 

members of a particular household who are related by blood, marriage, adoption, 

or other legal arrangements; (2) a person living alone or sharing a household with 

others or living as a roomer in a private home or lodging house or in permanent 

living quarters in a hotel or motel, but who is financially independent; or (3) two 

or more persons living together who use their incomes to make joint expenditure 

decisions. The terms consumer unit, family, and household are often used 

interchangeably for convenience. However, the proper technical term for 

purposes of the Consumer Expenditure Survey is consumer unit. 

Identification 

of AI/AN/NA: 

Race is self-reported. There are no specific instructions given for selfidentification. Respondents are permitted to check all that apply. The categories 

available: 

• White 

• Black or African American 

• American Indian or Alaska Native (AI/AN) 

• Asian 

• Hawaiian or Other Pacific Islander (NH/PI) 

AI/AN/NA 

Population in 

Data Set: 

The (unweighted) numbers of AI/AN/NA represented in the CE Diary 2004 are: 

TOTAL: 14,917 

AI/AN: 80 

NH/PI: 55 

5-49 
Consumer Expenditure Surveys (CE) Interview and Diary Surveys 

(continued) 

The (unweighted) numbers of AI/AN/NA represented in the CE Interview 2004 

are: 

TOTAL: 38,844 

AI/AN: 204 

NH/PI: 118 

Geographic 

Scope: 

The geographic scope of the CE is national. The microdata includes the following 

geographic identifiers that would support analyses: some states, city population 

size, and rural vs. urban areas. 

The Bureau of Labor Statistics makes state identifiers available for use with the 

public-use CD-ROMs, although some states are not identified because the sample 

size for each state is very small. Further information about geographic identifiers 

can be obtained from the Bureau’s Division of Consumer Expenditure Surveys, 

by e-mail at cexinfo@bls.gov or by telephone at (202) 691-6900. 

Consumer expenditure data for selected Metropolitan Statistical Areas (MSAs) 

also are published in the biennial reports. For confidentiality reasons, MSA 

identifiers are not included on the public-use microdata on CD-ROMs. 

Date or 

Frequency: 

The CE has been conducted annually since 1984 and will continue to be 

conducted annually. Data are available for all years the CE has been conducted. 

Aggregation: BLS sells microdata for the 1984-2004 CE on CD-ROM. These data can be 

integrated if careful attention is paid to differences across the forms from 

collection to collection as well as differences in sampling design from collection 

to collection. BLS recommends that to represent the covered population in 

aggregating the data, the quarterly weights should be used for each consumer unit. 

See the following link for what is available and price lists: 

http://www.bls.gov/cex/csxmicro.htm 

If the 2003 and 2004 data were aggregated, the resulting (unweighted) Ns would 

be: 

Diary data 

TOTAL: 30,744 

AI/AN: 176 

NH/PI: 109 

Interview data 

TOTAL: 79,218 

AI/AN: 417 

NH/PI: 196 

5-50 
Consumer Expenditure Surveys (CE) Interview and Diary Surveys 

(continued) 

Data Collection 

Methodology: 

The diary component uses a self-administered paper-and-pencil diary that is 

returned to BLS. The interview component is conducted in person using a 

computer-assisted personal interview protocol or a laptop computer. 

Participation: Optional, without incentives 

Response Rate: The following table represents response rate information for the 2001, 2002 and 

2003 CE: 

 Interview Diary

2001- Percent of eligible units interviewed 78.0 74.9 

2002- Percent of eligible units interviewed 78.0 74.1 

2003- Percent of eligible units interviewed 78.6 73.4 

Sampling 

Methodology: 

The CE is a national probability sample of households designed to represent the 

total U.S. civilian noninstitutional population. The selection of households begins 

with the definition and selection of primary sampling units (PSUs), which consist 

of counties (or parts thereof), groups of counties, or independent cities. Within 

these PSUs, the sampling frame (that is, the list from which housing units are 

chosen) for the Consumer Expenditure Survey is generated from the 2000 Census 

100-percent detail file. The frame is augmented by a sample drawn from new 

construction permits and extra housing units identified through improvements in 

coverage techniques. 

The Census Bureau selects a sample of approximately 12,500 addresses for 

participation in the Diary survey each year. The Interview survey is a rotating 

panel survey in which approximately 15,000 addresses are contacted in each 

calendar quarter of the year. One-fifth of the addresses contacted each quarter are 

new to the survey and provide the bounding interviews that afford baseline data, 

but are not used to compute the survey’s published expenditure estimates. After a 

housing unit has been in the sample for five consecutive quarters, it is dropped 

from the panel and a new housing unit is selected to replace it. 

Analysis: Beginning with year 2000 data, the Consumer Expenditure Survey program made 

available standard error tables using integrated data from both surveys. These 

standard error tables correspond to the program’s standard tables, except for the 

classification by region, population size of area of residence, and selected age. 

Selected standard error tables are available at 

http://www.bls.gov/cex/csxstnderror.htm. 

Detailed information on how to use the standard error tables is provided at 

http://www.bls.gov/cex/anthology/csxanth5.pdf. 

Authorization: The Bureau of Labor Statistics conducts the Consumer Expenditure Diary Survey 

under the authority of Title 29 of the U.S. Code. Congress authorizes the financial 

support for the survey through Public Laws 94-439 and 95-205. 

5-51 
Consumer Expenditure Surveys (CE) Interview and Diary Surveys 

(continued) 

Strengths: The CE is a very well-documented series of studies; much of this documentation 

is available on-line. Multiple years of data are available. 

Limitations: There are a very small number of AI/AN/NA respondents in the data from the CE 

Diary 2004 and only a moderate number in the CE Interview 2004. For maximum 

utility, CE data should be aggregated across multiple years to increase the 

numbers of AI/AN/NA respondents represented in the sample. Aggregation of the 

data, however, may require sophisticated programming and statistical skills. 

Access 

Requirements 

and Use 

Restrictions: 

Microdata are available to the public. Cost per annual CD is $145. 

Contact 

Information: 

Bureau of Labor Statistics 

Consumer Expenditure Surveys -- Branch of Information and Analysis 

Postal Square Building, Room 3985 

2 Massachusetts Avenue, N.E. 

Washington, DC 20212-0001 

Telephone- (202) 691-6900 

FAX- (202) 691-7006 

E Mail- CEXINFO@bls.gov 

For information on how to obtain the actual data, please contact BLS officials 

using the contact information given above. There is also an online table generator 

available at the CE homepage at: http://www.bls.gov/cex/. 

5-52 
Current Population Survey (CPS) 

Sponsor: U.S. Department of Labor (DoL)/Bureau of Labor Statistics and U.S. Department 

of Commerce/Bureau of the Census 

Description: The Current Population Survey (CPS) is the primary source of information on the 

labor force characteristics of the U.S. population. The sample is selected to 

represent the civilian noninstitutional population. Respondents are interviewed to 

obtain information about the employment status of each member of the household 

15 years of age and older. Data collected include employment; unemployment; 

earnings; hours of work; a variety of demographic characteristics including age, 

sex, race, marital status, and educational attainment; occupation, industry, and 

class of worker. Supplemental questions are often asked on a variety of topics 

including school enrollment, income, previous work experience, health, employee 

benefits, and work schedules. 

Relevant Policy 

Issues: 

Income Status, Unemployment Rates, Economic Opportunity, and Demographic 

and Economic Indicators. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Participants were asked to respond to the question on race by indicating one or 

more of six race categories. The six race categories are: 

• White 

• Black or African American 

• American Indian/Alaska Native (AI/AN) 

• Asian 

• Native Hawaiian/Other Pacific Islander (NH/PI) 

• Some Other Race (this category is not read/displayed to the respondent) 

Responses to the race item are recoded into multiple race categories for analytic 

purposes. Those categories that include AI/AN or NH/PI are listed below: 

• AI/AN Only 

• NH/PI Only 

• White/AI/AN 

• White/NH/PI 

• Black/AI/AN 

• Black/NH/PI 

• AI/AN/Asian 

• Asian/NH/PI 

• White/Black/AI/AN 

• White/AI/AN/Asian 

• White/Asian/NH/PI 

• White/Black/AI/AN/Asian 

5-53 
Current Population Survey (CPS) 

(continued) 

AI/AN/NA 

Population in 

Data Set: 

Responses to the race item were recoded into the multiple race categories. The 

following categories reflect the unweighted counts for AI/AN/NA respondents in 

the April, March, and February 2006 CPS: 

February 2006 (N = 136,294)

AI/AN Only: 1,510 

NH/PI Only: 462 

White/AI/AN: 1,357 

White/NH/PI: 149 

Black/AI/AN: 143 

Black/NH/PI: 22 

AI/AN/Asian: 4 

Asian/NH/PI: 124 

White/Black/AI/AN: 102 

White/AI/AN/Asian: 17 

White/Asian/NH/PI: 156 

White/Black/AI/AN/Asian: 5 

March 2006 (N = 135,028)

AI/AN Only: 1,447 

NH/PI Only: 472 

White/AI/AN: 1,345 

White/NH/PI: 155 

Black/AI/AN: 146 

Black/NH/PI: 23 

AI/AN/Asian: 6 

Asian/NH/PI: 128 

White/Black/AI/AN: 95 

White/AI/AN/Asian: 19 

White/Asian/NH/PI: 171 

White/Black/AI/AN/Asian: 3 

April 2006 (N = 136,405)

AI/AN Only: 1,486 

NH/PI Only: 486 

White/AI/AN: 1,351 

White/NH/PI: 165 

Black/AI/AN: 150 

Black/NH/PI: 20 

AI/AN/Asian: 6 

Asian/NH/PI: 110 

White/Black/AI/AN: 91 

White/AI/AN/Asian: 21 

White/Asian/NH/PI: 188 

White/Black/AI/AN/Asian: 4 

5-54 
Current Population Survey (CPS) 

(continued) 

Geographic 

Scope: 

The geographic scope of the study is national. 

There are several geographic variables on the data sets that could be useful for 

analysis. They include: 

• Region (Northeast, Midwest, South, and West); 

• State Census Code (state names); 

• Combined Statistical Area Federal Information Processing Standards Code 

(FIPS) (e.g., Appleton-Oshkosh-Neenah,WI; Chicago-NapervilleMichigan City, IL- IN-WI; Cincinnati-Middletown-Wilmington, OHKY-IN; Cleveland-Akron-Elyria, OH); 

• Metropolitan Statistical Area FIPS Code (e.g., Appleton-Oshkosh-Neenah, 

WI, MSA; Grand Rapids-Muskegon-Holland, MI MSA; GreenvilleSpartanburg-Anderson, SC MSA); 

• Principal City/Balance Status (Principal City, Balance Metropolitan, 

Nonmetropolitan, Not Identified); 

• Metropolitan Status (Metropolitan, Nonmetropolitan, Not Identified); 

• Individual Central City Code (specific city code); and 

• Metropolitan Statistical Area Size (100,000 - 249,999, 250,000 - 499,999, 

500,000 - 999,999, 1,000,000 - 2,499,999, 2,500,000 - 4,999,999, 

5,000,000+). 

Date or 

Frequency: 

The CPS is a rotating panel survey that has been conducted monthly for over 50 

years. A panel survey is a survey in which similar measurements are made on the 

same sample at different points in time, and in a rotating panel survey, part of the 

sample is changed each month. For the CPS, each monthly sample is divided into 

eight representative subsamples or rotation groups. A given rotation group is 

interviewed for a total of 8 months, divided into two equal periods. It is in the 

sample for 4 consecutive months, leaves the sample during the following 8 

months, and then returns for another 4 consecutive months. In each monthly 

sample, one of the eight rotation groups is in the first month of enumeration, 

another rotation group is in the second month, and so on. Under this system, 75 

percent of the sample is common from month to month and 50 percent is common 

from year to year for the same month. This procedure provides a substantial 

amount of month-to-month and year-to-year overlap in the sample, thus providing 

better estimates of change and reducing discontinuities in the data series without 

burdening any specific group of households with an unduly long period of 

inquiry. 

Aggregation: Public release cross-sectional data are available for each month of data collection 

and smaller scope cross-wave tables of data are also publicly available. It is 

possible to combine the cross-sectional data sets to obtain cross-wave data sets 

that would contain information not available in the cross-wave data sets that are 

currently provided. The overall count of members of the AI/AN/NA population in 

an aggregated data set, however, would not increase dramatically as the CPS is a 

panel survey with about 75 percent overlap between samples from month to 

month. 

5-55 
Current Population Survey (CPS) 

(continued) 

Data Collection 

Methodology: 

The mode of data collection for the CPS is both telephone and in-person 

interviewing. 

Participation: Optional, without incentives 

Response Rate: Nonresponse rates are less than 9 percent for the monthly CPS for September 

2003 through September 2004. 

Sampling 

Methodology: 

The CPS sample is a multistage stratified sample of approximately 72,000 

households. Of these households, approximately 56,000 housing units from 792 

sample areas were interviewed. The CPS samples housing units from lists of 

addresses obtained from the 1990 Decennial Census of Population and Housing. 

These lists are updated continuously for new housing built after the 1990 census. 

The first stage of sampling involves dividing the United States into primary 

sampling units (PSUs)—most of which comprise a metropolitan area, a large 

county, or a group of smaller counties. Every PSU falls within the boundary of a 

state. The PSUs are then grouped into strata. 

Analysis: Effective sample size, design effects, and standard errors for estimates are 

discussed in detail in the following publication: Technical Paper 63RV: Current 

Population Survey - Design and Methodology 

(http://www.census.gov/prod/2002pubs/tp63rv.pdf). 

Authorization: The information collected in the CPS is authorized by the following: 

Title 13, U.S. Code, Section 182 (Authorizes the Census Bureau to collect 

statistical information); Title 29, U.S. Code, Sections 1-9 (Authorizes the Bureau 

of Labor Statistics to collect labor force statistics); Title 38, U.S. Code, Section 

219 (Authorizes the Census Bureau to collect information for the Department of 

Veterans' Affairs); and Public Laws 89-10, 92-318, 93-380 (Authorizes the 

Census Bureau to collect information on education). 

Strengths: The CPS data sets contain a large number of AI/AN/NA respondents. They 

include information on key policy issues. There are multiple years of data 

available. 

Limitations: Aggregation of the monthly data to obtain a longitudinal data set would require 

the expertise of a skilled statistician. 

Access 

Requirements 

and Use 

Restrictions: 

CPS data are available to the public at no cost. 

5-56 
Current Population Survey (CPS) 

(continued) 

Contact 

Information: 

Information on the CPS is available at http://www.bls.census.gov/cps/. 

Email inquiries can be submitted via the “Ask a Question” tab on the 

ask.census.gov webpage. (https://ask.census.gov/cgibin/askcensus.cfg/php/enduser/std_alp.php). 

Telephone inquiries can be made at (301) 763-3806. 

Basic monthly data for May 2004 through April 2006 are currently available from 

DataFerrett. DataFerrett is a data mining tool that accesses data stored in 

TheDataWeb (a network of online data libraries) through the Internet. DataFerrett 

must be installed as an application on a personal computer or used as a java applet 

with an Internet browser (http://dataferrett.census.gov/). Older data are available 

via file transfer protocol (ftp) from the CPS website: 

http://www.bls.census.gov/ferretftp.htm. 

5-57 
Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) 

Sponsor: U.S. Department of Education (DoE)/National Center for Educational Statistics 

(NCES) 

Description: The Early Childhood Longitudinal Study is designed to provide decision-makers, 

researchers, child care providers, teachers, and parents with detailed information 

about children's early life experiences. The Early Childhood Longitudinal Study, 

Birth Cohort (ECLS-B) looks at children's health, development, care, and 

education during the formative years from birth through kindergarten entry. The 

ECLS-B selected a nationally representative sample of children born in the year 

2001 to follow from birth through kindergarten. 

Relevant Policy 

Issues: 

Educational Attainment, Measures of Well-being for Families/Households, and 

Measures of Well-being for Children. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

The ECLS-B collects information on race and ethnicity in two places: the parent 

interview and the birth certificate. Race/ethnicity information from the birth 

certificate was used for sampling purposes only. For analytic purposes, ECLS-B 

recommends using the information provided in the parent interview. 

In the parent interview, children’s race/ethnicity is defined by a series of 

variables. Parents were asked whether their child was of Spanish, Hispanic, or 

Latino origin. The parents were then shown a card with race response options and 

asked to choose from a number of options. 

The restricted-use ECLS-B data files identify the following race categories: 

• White 

• Black 

• American Indian 

• Asian Indian 

• Chinese 

• Filipino 

• Japanese 

• Korean 

• Vietnamese 

• Other Asian 

• Native Hawaiian 

• Guamanian 

• Chamorro 

• Samoan 

• Other Pacific Islander 

5-58 
Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) 

(continued) 

The data set allows for children to be identified as more than one race. 

In the second data collection wave, parents of children who were identified as 

AI/AN in the first data collection wave were asked to confirm that they/their 

children were AI/AN. If confirmed, interviewers asked “[Are you/Is [the child]] 

formally enrolled in that (tribe/Alaska Regional Corporation)?” and “[Do 

you/Does [the child]] currently live on tribal lands or a reservation?” 

AI/AN/NA 

Population in 

Data Set: 

During the first wave of the study, parents of approximately 10,700 children 

completed interviews, and approximately 10,200 children were directly assessed. 

The count of AI/AN individuals in the 2001-2002 base year of the ECLS-B study 

(data were first collected when the children were approximately 9 months old) are 

provided below: 

Total AI/AN population = 750* 

AI/AN and Hispanic = 150* 

AI/AN, non-Hispanic = 300* 

AI/AN, non-Hispanic, more than one race = 300* 

When appropriately weighted to be nationally representative, this sample of 

AI/AN children represents approximately 2 percent of all children born in the 

United States in 2001. 

For the second year (children approximately 2 years old) collected in 2003: 

Total AI/AN population = 700* 

*Please note: These counts have been rounded according to NCES rounding 

rules, as the ECLS-B data are currently only available in a restricted format. 

Although "Native Hawaiian” and “Other Pacific Islander” are provided as 

separate racial categories in the data files, reports present data for these groups 

rolled up into a single category: “Other Asian/Pacific Islander.” 

AI/AN/NA 

Subpopulations: 

The restricted-use data files contain all the detailed race/ethnicity information 

colleted in the parent interview. Relevant subpopulations in the ECLS-B data 

include Native Hawaiians, Guamanians, Chamorros, Samoans, and Other Pacific 

Islanders. The restricted-use data file also includes information about whether the 

child is formally affiliated with a tribe and lives on a reservation. 

Geographic 

Scope: 

The geographical scope of the ECLS-B is national. The sample is designed also to 

support regional estimates. It is not designed to estimate characteristics at the 

state level. 

Date or 

Frequency: 

Wave 1: Data collection in the first wave took place between fall 2001 and fall 

2002, at which time most of the sampled children were about 9 months of age (65 

percent of AIAN children were 8 to 10 months of age). 

5-59 
Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) 

(continued) 

Wave 2: Children were about 2-year-olds (collected in 2003) 

Wave 3: Children were preschool-aged (e.g., age 4) (collected in 2005) 

Wave 4: Children will be in kindergarten (to be collected 2006-2007) 

Wave 5: Includes children who were not yet enrolled in kindergarten during the 

Wave 4 field period (to be collected in fall 2007) 

Data Collection 

Methodology: 

ECLS-B data collection in the first wave (when the children were about 9 months 

old) involved three parts: 

Child assessment: Children participated in a variety of activities to assess their 

early mental, physical, and socioemotional development. A trained staff member 

measured the child’s mental and physical skills through an untimed one-on-one 

assessment in the child’s home. Assessment tools included the Bayley Short 

Form-Research Edition (BSF-R) (a variation of the Bayley Scales of Infant 

Development-Second Edition that was developed specifically for use in the 

ECLS-B), the Nursing Child Assessment Teaching Scale (NCATS), and physical 

measurements. 

Parent interview: Parents/guardians were asked to provide key information about 

their children and themselves. The parent interview included two instruments: the 

parent interview instrument and the parent self-administered questionnaire 

(PSAQ). The first was conducted in person by trained field interviewers using 

computer-assisted personal interviewing (CAPI) as part of the home visit. The 

PSAQ was a paper and pencil instrument, presented during the parent CAPI 

instrument for the respondent to complete and return in a provided envelope, and 

contained 23 questions on topics some people might prefer to answer privately. 

Father questionnaires: The ECLS–B also collected data from fathers through two 

separate father questionnaires: the resident father questionnaire and the 

nonresident father questionnaire. The nonresident father questionnaire was only 

administered in cases where the child did not live in the same household as his or 

her biological father and a minimum contact frequency was met. Both father 

questionnaires were self-administered with telephone follow-up. 

Participation: Optional, with incentives. For the first round, parent participants received $50 and 

a book for their child. For the second round, parents received $30 and a children’s 

book. 

Response Rate: NCES reported the response rate for Wave 1 as 74.1 percent overall while the 

AI/AN response rate was reported as 79.3 percent (based on weighted data). The 

response rate is calculated as the weighted number of completed parent interviews 

divided by the total eligible sample. To be considered complete, the first three 

sections of the parent interview needed to be completed. 

5-60 
Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) 

(continued) 

Sampling 

Methodology: 

The sample for ECLS-B was selected using a clustered, list frame sampling 

design. The list frame was registered births in the National Center for Health 

Statistics’ (NCHS) vital statistics system (from lists provided by state registrars). 

Births were sampled from 96 core primary sampling units (PSUs) representing all 

infants born in the United States in the year 2001. The PSUs were counties and 

county groups. 

Sampling was based on occurrence of the birth as listed on the birth certificate. 

Sampled children subsequently identified by the state registrars as having died or 

who had been adopted after the issuance of the birth certificate were excluded 

from the sample. Also, infants whose birth mothers were younger than 15 years at 

the time of the child’s birth were excluded. 

Oversample of 

AI/AN/NA 

Population: 

Eighteen additional PSUs were selected from a supplemental frame consisting of 

areas where the population has a higher proportion of AI/AN births. The PSUs in 

the AI/AN PSU sampling frame were counties or groups of counties that had at 

least an expected 50 AI/AN sample births based on 1994-1996 National Center 

for Health Statistics natality detail files and that had relatively large proportions 

of AI/AN births. 

Analysis: The effective sample size based on the number of complete cases in wave 1 for 

the AI/AN population is 1,190. 

Design effects (weighting effect) = 1.0500 

Strengths: Documentation is extremely detailed and very clear. The study includes some 

oversamples of American Indian/Native Americans. An extensive nonresponse 

bias analysis was conducted, and findings from these analyses suggest that there 

is not a bias due to nonresponse. Details on the nonresponse bias analysis are 

available in the study’s documentation. 

Limitations: The Institutional Review Board of the Navajo Nation reservations did not approve 

participation in the study. Where cases were drawn from persons residing on a 

Navajo Nation reservation, those cases were treated as nonresponse. Navajos not 

living on reservations were included in the sample. 

Access 

Requirements 

and Use 

Restrictions: 

The data are available to researchers with an NCES restricted-use license. The 

steps for obtaining a license are detailed here: 

http://nces.ed.gov/pubsearch/licenses.asp. 

Contact 

Information: 

The ECLS-B staff can be contacted by sending an email to: ecls@ed.gov. 

Questions about NCES restricted-use licenses can be addressed to: 

Cynthia L. Barton 

Data Security Assistant 

Phone: (202) 502-7307 

E-mail: Cynthia.Barton@ed.gov

5-61 
Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) 

(continued) 

Flanagan, K., and Park, J. (2005). American Indian and Alaska Native Children: 

Findings From the Base Year of the Early Childhood Longitudinal Study, Birth 

Cohort (ECLS-B) (NCES 2005–116). U.S. Department of Education. 

Washington, DC: National Center for Education Statistics 

Reports of 

Interest: 

5-62 
Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K) 

Sponsor: U.S. Department of Education (DoE)/National Center for Educational Statistics 

(NCES) 

Description: The Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLSK) is an ongoing study that focuses on children's early school experiences 

beginning with kindergarten and following children through 12th grade. In the 

fall of 1998, ECLS-K began following a nationally representative sample of 

kindergarteners. The ECLS-K provides descriptive information on children's 

status at entry to school, their transition into school, and their progression through 

8th grade. (Initially, the ECLS-K was designed to follow children through their 

fifth grade year in school – however plans have been made to extend the study to 

follow the ECLS-K children through their eighth grade of school. The study will 

end with the data collection scheduled for school year 2006-2007.) 

The longitudinal nature of the ECLS-K data enables researchers to study how a 

wide range of family, school, community, and individual factors are associated 

with school performance. Researchers can request the child-level files for each 

year of data collection, as well as the longitudinal kindergarten to fifth grade data 

file. Data are collected from a direct child assessment, from parent interviews, 

from school administrators and teachers, and from student records and a school 

facilities checklist. 

Relevant Policy 

Issues: 

Educational Attainment, Educational Opportunities, Factors Contributing to 

Educational Disparities, and Identification of Evidence-based Practices and 

Programs that Produce Positive Educational Outcomes and are 

Generalizable/replicable. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual child 

Identification 

of AI/AN/NA: 

Race information is obtained during the parent interviews using the following 

question: What is your race? (The same question is asked concerning the child: 

“What is [NAME OF CHILD’S] race?”) 

Categories include: 

• American Indian or Alaska Native (AI/AN) 

• Asian 

• Black or African American 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• White 

• Another race (specify) 

When the parent interview is not completed, race information is obtained from 

school records. The parent interview is considered the best source of information 

regarding race/ethnicity. 

5-63 
Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K) 

(continued) 

AI/AN/NA 

Population in 

Data Set: 

Completed interviews with AI/AN/NA children, parents, and school informants 

by type of data collection for the school year 2003-2004 (fifth-grade): 

Child assessment

Total completed interviews: 11,260 

AI/AN: 210 

NH/PI: 144 

Parent interview

Total completed interviews: 10,913 

AI/AN: 222 

NH/PI: 136 

School administrator questionnaires

Total completed interviews: 10,937 

AI/AN: 191 

NH/PI: 145 

School facilities checklist

Total completed interviews: 11,154 

AI/AN: 208 

NH/PI: 146 

Student records abstract

Total completed interviews: 10,015 

AI/AN: 197 

NH/PI: 125 

Teacher-level questionnaires

Total completed interviews: 10,872 

AI/AN: 206 

NH/PI: 138 

Geographic 

Scope: 

The geographic scope of the study is national. The ECLS-K public-use data also 

contain information on the regional location of the child’s school (i.e., Northeast, 

Midwest, South, and West.) The ECLS-K sample was designed to support 

national and regional estimates. It was not designed to estimate characteristics of 

children, teachers, families and schools at the state level. Variables such as the 

child’s home and school zip code are suppressed on the public use files to ensure 

respondent confidentiality. 

Date or 

Frequency: 

The ECLS-K is a longitudinal study. The same children are followed periodically 

from kindergarten through the 8th grade. Information was collected in the fall and 

the spring of kindergarten (1998-99), the fall and spring of first grade (1999-

2000), the spring of third grade (2002) and the spring of 5th (2004). Future data 

collections will include 8th grade (2007). 

5-64 
Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K) 

(continued) 

Data Collection 

Methodology: 

To collect information from children, a trained assessor visits the children in their 

schools. Children are assessed, un-timed, one-on-one within their school. The 

direct child assessment collects information about children's reading and 

mathematics skills, their general knowledge (i.e., science and social studies) in 

kindergarten and first grade, and their science knowledge in third and fifth grade. 

In addition, the assessment includes height/weight measurements, and in fall 

kindergarten only, children's psychomotor skills (e.g., hopping, skipping, 

jumping, manipulating blocks, drawing figures) are assessed. The direct child 

assessments are administered using computer assisted personal interviews 

(CAPI). 

To collect information from parents, a trained interviewer phones the parent at 

their home and administers a 45-50 minute interview. Computer assisted 

telephone interviewing (CATI) methods are used to record the parent's answers. If 

the child's family does not have a telephone, the interview is conducted in person. 

To collect information from schools, teachers and school administrators complete 

paper and pencil surveys and retrieve information from school records. 

Participation: Optional, with incentives 

Response Rate: Overall unweighted response rates for the fifth grade cohort (school year 2003-

2004): 

Child assessments: 93.6% 

Parent interview: 90.7% 

School administrator questionnaire: 89.6% 

Facilities checklist: 91.4% 

Student records abstract: 82.1% 

Teacher level-questionnaire: 90.6% 

There are also some differences in response rates by race. For example, in the 

spring-fifth grade data collection, the AI/ANs had the lowest child assessment 

weighted completion rate (78.3 percent) and the highest parent interview 

weighted completion rate (95.2 percent). 

Sampling 

Methodology: 

The ECLS-K study uses a multistage probability sample design. Primary 

sampling units (PSUs) consist of counties and groups of counties. The second 

stage units are schools within the sampled PSUs. In the base year of the ECLS-K, 

a total of 1,277 schools were selected for the sample. The third and final stage is 

students within the selected schools. In the base year of the ECLS-K, a total of 

22,666 students were selected. The children in ECLS-K attended both public and 

private schools, including both full-day and part-day kindergarten programs. 

Oversample of 

AI/AN/NA 

Population: 

Asians and Pacific Islanders were oversampled for the ECLS-K study. To create 

this oversample, two independent sampling strata were formed within each 

school. One stratum consisted of Asian/Pacific Islander children, while the 

second stratum consisted of the remaining children. 

5-65 
Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K) 

(continued) 

Analysis: The ECLS-K data are weighted to compensate for differential probabilities of 

selection at each sampling stage and to adjust for the effects of nonresponse. The 

User’s Manual provides a detailed description of how weights were calculated 

and how they should be applied to the data set. 

Each survey item in the ECLS-K has its own design effect that can be estimated 

from the survey data. The median design effects, as reported in the ECLS-K 5th 

Grade User's Manual, for the race/ethnicity variable for all six rounds of data 

collection are: 

• White: 2.920 

• Black : 2.532 

• Hispanic: 2.456 

• Asian: 3.106 

• Native Hawaiian or other Pacific Islander: 4.186 

• American Indian or Alaska Native: 7.058 

• Other: 2.423 

Strengths: Data are collected on a key policy issue, education. There are multiple years of 

data available. The study includes some oversampling of Pacific Islanders. 

Limitations: There are a limited number of AI/AN/NA in these data sets. 

Other: While the ECLS-K study includes children that attend Bureau of Indian Affairs 

(BIA) schools, the number of children attending these schools is suppressed to 

protect respondent confidentiality. Additionally, attendance at BIA schools is not 

included as an identifier in the data files. 

Access 

Requirements 

and Use 

Restrictions: 

Unlike the Early Childhood Longitudinal Study Birth Cohort data, the ECLS-K 

data has a public use data file. There is also a restricted ECLS-K data set 

available to researchers with a National Center for Education Statistics (NCES) 

license. The restricted data set contains a few values and variables that are 

suppressed on the public use data set. For most research, the ECLS-K public use 

data set should suffice. For researchers who feel they need the restricted use data 

set, the steps for obtaining an NCES license are detailed here: 

http://nces.ed.gov/pubsearch/licenses.asp. There is no cost associated with use of 

the data. 

Contact 

Information: 

Public use data file can be ordered on CD-ROM from www.edpubs.org. 

Elvira Germino Hausken 

Project Officer, ECLS-K 

U.S. Department of Education 

National Center for Education Statistics 

(202) 502-7352 

ECLS@ed.gov 

Web Site: http://nces.ed.gov/ecls/ 

5-66 
Food Stamp Program Quality Control Database (FSPQC) 

Sponsor: U.S. Department of Agriculture (USDA) 

Description: The Food Stamp Program Quality Control Database contains detailed 

demographic, economic, and Food Stamp Program (FSP) eligibility information 

for a nationally representative sample of approximately 50,000 participating 

households. The FSPQC data are generated from monthly quality control (QC) 

reviews of FSP cases that are conducted by state FSP agencies to assess the 

accuracy of eligibility determinations and benefit calculations for the state's FSP 

caseload. These data, which are produced annually, are suitable for tabulations of 

characteristics of food stamp units and for simulating the impact of various FSP 

policy changes on households and persons currently receiving food stamps. The 

FSPQC Database is an edited version of the raw datafile generated by the Food 

Stamp Program’s Quality Control (QC) System. 

Relevant Policy 

Issues: 

Economic Assistance Program Participation Rates, Measures of Well-being for 

Families/Households, and Factors Contributing to Well-being Disparities of 

Families. 

Data Type(s): Program enrollment data 

Unit of 

Analysis: 

Analysis is possible at the individual and household levels. The FSPQC lists 

characteristics for 1-16 members of a household. Individuals included in the 

database as household members are those eligible for participation in the FSP as 

well as those who would be considered part of the FSP household but are 

ineligible to participate because of a variety of reasons. In many of these cases, 

the income of an ineligible household member is factored into determining the 

benefit for the eligible portion of the household. Not included in this database are 

those individuals that are living under “the same roof” who can be considered a 

separate FSP household. Examples of these are the elderly or disabled (who have 

special household status rules) as well as unrelated housemates who purchase and 

prepare their meals separately. 

Identification 

of AI/AN/NA: 

Race/ethnicity is self-reported on the application for Food Stamp benefits. The 

QC reviewer takes this information and incorporates it into the FSPQC database. 

The reporting categories in the current database are: 

• White, not of Hispanic origin 

• Black, not of Hispanic origin 

• Hispanic 

• Asian or Pacific Islander 

• American Indian or Alaskan Native (AI/AN) 

USDA recently announced that these categories are being changed. States have 

until April 1, 2007 to implement this change. The new categories will capture the 

following: 

5-67 
Food Stamp Program Quality Control Database (FSPQC) 

(continued) 

• American Indian or Alaskan Native 

• Asian 

• Black or African-American 

• Native Hawaiian or other Pacific Islander 

• White 

• American Indian or Alaska Native and White 

• Asian and White 

• Black or African American and White 

• American Indian or Alaska Native and Black or African-American 

Additionally, separate categories will be included for each of the race categories 

above to designate Hispanic origin (e.g., White/Hispanic, White/Non-Hispanic.) 

The FSPQC database will be revised to reflect these new reporting requirements 

for FY 2007. 

AI/AN/NA 

Population in 

Data Set: 

Out of the total 48,806 household-level records in the FSPQC, there are 117,456 

individuals identified across 16 person-level variables. Of these, 4,050 individuals 

are coded as AI/AN in 1,371 households. Of the 4,050 AI/AN individuals, 4,013 

of them participate in the Food Stamp Program. 

Geographic 

Scope: 

The geographic scope of the FSPQC is national. A county Federal Information 

Processing Standards (FIPS) code is assigned to each unit on the FSPQC file. 

However, the sample size does not allow analyses at the county level. The sample 

size is sufficient to allow analyses at the state level. 

Date or 

Frequency: 

The FSPQC is compiled on a yearly basis. The most recent version of the FSPQC 

available to researchers is from FY 2004. The FSPQC data are typically released 

in late summer or early fall. 

Data Collection 

Methodology: 

State FSP agencies conduct monthly case reviews to assess the accuracy of 

eligibility determinations and benefit calculations for the state’s FSP caseload. 

The public use FSPQC database contains all case reviews except those removed 

from the file because there is too little information. These include those coded as 

not subject to review, those whose review was incomplete, those who are 

ineligible, and a few households dropped due to inconsistencies in the data. 

Participation: Mandatory. States must report data to Food and Nutrition Service (FNS). 

Sampling 

Methodology: 

All state agencies (including the District of Columbia, Guam and the Virgin 

Islands) are required to select monthly a statistically random sample from a 

universe of all households receiving Food Stamp benefits for that given month. 

Most state agencies draw the samples systematically (i.e. using a constant 

sampling interval), though there are some state agencies which employ simple 

random and/or stratified sampling techniques. All sampling plans must be 

approved by FNS. Required annual sample sizes range from 300 for state 

agencies with small Food Stamp caseloads (e.g. Wyoming and Guam), to over 

5-68 
Food Stamp Program Quality Control Database (FSPQC) 

(continued) 

1000 for larger states, with the average being around 950 per state. State agencies 

are required to complete reviews for at least 98 percent of those selected cases 

which are deemed to be part of the desired Food Stamp universe. The review 

findings and data for each state are reported to FNS when the review is 

completed. These data form the basis for the public FSPQC database. 

Strengths: The FSPQC database contains a large number of AI/AN/NA respondents. The 

data are collected on key policy issues, including family well-being. There are 

multiple years of data available with little missing data (less than 1 percent 

missing data for the race variable in 48 states). The documentation is very 

detailed. 

Limitations: The Food Distribution Program on Indian Reservations (FDPIR) is administered 

at the federal level by the FNS in cooperation with 98 tribal organizations and 6 

state agencies. Many Native Americans actually participate in the FDPIR rather 

than the Food Stamp Program because of rural isolation and the lack of easy 

access to food stores. Therefore, the FSPQC underrepresents American Indians 

who live on reservations and receive nutrition assistance. 

Additionally, the FSPQC data are limited regarding the asset and vehicle holdings 

of FSP participants, and there are no data available for eligible non-participants. 

There are also no data available for those receiving disaster benefits, as these 

cases are not subject to review. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to the public at no cost. 

Contact 

Information: 

The contact for obtaining FSPQC data is as follows: 

Office of Analysis, Nutrition, and Evaluation 

USDA Food and Nutrition Service 

3101 Park Center Drive, Room 1014 

Alexandria, Virginia 22302 

703-305-2017 

Additionally, a restricted version of the FSPQC data can be downloaded from the 

following website: 

http://host4.mathematica-mpr.com/fns/fnsqcdata/download.htm. 

Reports of 

Interest: 

Background Report on the Use and Impact of Food Assistance Programs on 

Indian Reservations. January 2005. Finegold, K., Pindus, N., Wherry, L., Nelson, 

S., Triplett, T., Capps, R. The Urban Institute. 

Characteristics of Food Stamp Households: Fiscal Year 2004. September 2005. 

Anni Poikolainen. Mathematica Policy Research, Inc. 

5-69 
Hawaii Health Survey (HHS) 

Sponsor: State of Hawaii Department of Health (DOH)/Office of Health Status Monitoring 

(OHSM) 

Description: The Hawaii Health Survey (HHS) is a continuous statewide household survey of 

health and socio-demographic conditions. The HHS was modeled after the 

National Health Information Survey (NHIS). The HHS was initiated in 1968, and 

in 1996 it became a telephone survey. The survey is conducted for the purpose of 

providing Hawaii Department of Health (DOH) programs, other agencies, and the 

public with statistics for planning and evaluation of health services, programs, 

and problems. Sample data are adjusted and weighted to generate estimates of the 

population in Hawaii. The survey provides demographic information for 

observing population changes during the intercensal decade. The survey provides 

information on health and demographic characteristics of the people of Hawaii 

(e.g., income, race, education, marital status, employment, household size, 

insurance status, health status, morbidity, food security, and physical and mental 

health). However, many of the items unrelated to health are added by private 

agencies. For this reason, the Hawaii DOH can only run customized data analysis 

on the core survey items related to health issues. 

Relevant Policy 

Issues: 

Measurement of Health Status. 

Data Type(s): Survey 

Unit of 

Analysis: 

The unit of analysis is the household or family unit, with each household's 

individuals identified as separate data elements. A household is defined as all 

persons who occupy a housing unit (e.g., house, apartment), whether or not they 

are related to each other. 

Identification 

of AI/AN/NA: 

Race is self-reported by the respondent. Race and ethnicity are gathered 

according to two independent procedures in the HHS file. First, a set of variables 

is used to collect respondent-reported ethnicity of the parents of each household 

member. The respondent can list up to four ethnic categories for each member’s 

mother and father, resulting in up to eight indicators of ethnicity for household 

members. Response categories include: 

• White/Caucasian 

• Hawaiian 

• Chinese 

• Filipino 

• Japanese 

• Korean 

• Vietnamese 

• Asian Indian 

• Other Asian 

• Samoan/Tongan 

• Black/African American 

5-70 
Hawaii Health Survey (HHS) 

(continued) 

• Native American/Aleut/Eskimo/Inuit 

• Puerto Rican 

• Mexican 

• Portuguese 

• Guamanian/Chamorro 

• Other Pacific Islander 

Additionally, the interviewer can mark an “other” category and record an ethnic 

background not included in the above list. Interviewers can also record responses 

of “don’t know” (respondent may not know all ethnic background classifications 

of all household members) or “refused.” Data are stored in the file as eight or 

more (8 responses and also other) ethnic indicators for every household member, 

and can support classification of ethnicity or race according to any classification 

scheme including single and multiple class schemes. 

OHSM then codes the eight possible choices for each individual to one ethnic 

indicator based on parents' race/ethnicity according to a system consistent with 

U.S. Census rules for coding race/ethnicity. Specifically, if Hawaiian is listed for 

either the mother or father, ethnicity for that person is coded as Hawaiian. 

The Hawaii Department of Health publishes figures for the following race groups: 

Caucasian, Hawaiian, Chinese, Filipino, Japanese, and Other. 

AI/AN/NA 

Population in 

Data Set: 

In 2004, 6,769 households (6,769 respondents who were aged 18 years of age or 

older answered questions about their household and its members) were surveyed. 

The total number of household members described was 19,699. A breakdown of 

unweighted respondent groups by race is not available. 

AI/AN/NA 

Subpopulations: 

Native Hawaiian (NH) alone is identified. 

Geographic 

Scope: 

The geographic scope of the study is the state of Hawaii. Geographic indicators 

include county, island, zip code as reported by the respondent, and telephone 

prefix. Geographic analysis by any of these variables would not be appropriate 

given the small sample size. 

Date or 

Frequency: 

The HHS began in 1968 and is conducted on an annual basis. 

Data Collection 

Methodology: 

The HHS is administered by telephone using computer assisted telephone 

interviewing (CATI). Data are collected on all members of sampled households. 

Participation: Optional, without incentives 

Response Rate: The response rate for this study is not available. 

5-71 
Hawaii Health Survey (HHS) 

(continued) 

Sampling 

Methodology: 

The target population for the HHS is all Hawaiian residents in the state of Hawaii 

in non-institutionalized housing units with working telephone service at the time 

of the survey. Results exclude residents of the island of Niihau, households 

without phones, the homeless, and persons in group quarters. The HHS uses a 

disproportionate stratified random-digit dialing (RDD) sample that randomizes 

selection within strata. The sample is disproportionately selected by island 

(slightly larger proportions of interviews are conducted on islands with smaller 

populations). The sample population is statistically adjusted to represent the 

population of Hawaii. The respondent is an adult 18 years of age or older who is 

knowledgeable about their household, rather than a randomized adult. 

Strengths: Data sets contain information on individuals identified or coded as Native 

Hawaiian. 

Limitations: Technical documentation is very limited. Researchers cannot obtain the data file, 

and can only request analysis on the core survey items related to health policy 

issues. 

Access 

Requirements 

and Use 

Restrictions: 

OHSM will run customized data analysis for researchers upon request (there may 

be a charge depending on the nature of the request). Additionally, some data 

items are added on to the HHS by different agencies. These data are not available 

through OHSM. Researchers would need to contact the different agencies 

regarding the availability of these additional items. 

Contact 

Information: 

Office of Health Status Monitoring 

Hawaii Department of Health 

1250 Punchbowl Street, Room 104 

Honolulu, Hawaii 96813 

Phone (808) 586-4600 

Fax (808) 586-4606 

5-72 
Head Start Program Information Report 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Administration for 

Children and Families (ACF)/Office of Head Start 

Description: The Head Start Program Information Report (PIR) collects comprehensive data 

on the services, staff, children and families served by more than 2,700 Head Start 

and Early Head Start (EHS) programs nationwide (including American Indian 

and Alaska Native Head Start Programs.) All programs (grantees and delegates) 

are required to submit a PIR for each year in which they provide services to 

children and families. The PIR is the primary source of programmatic data for the 

Head Start community, their partners, Congress, and the general public. 

Staffing, enrollment, and service trend information is collected through the PIR 

and compiled each year for use at federal, regional, and local levels. The PIR 

enrollment report describes the program options provided by Head Start and Early 

Head Start programs and provides demographic information on the children and 

pregnant women served. Additional information collected in the PIR enrollment 

report includes funded and actual enrollment, eligibility, and turnover of 

enrollees. The PIR family services report provides information on Head Start and 

Early Head Start family characteristics, including the number and types of 

families served, employment status, education level, and the types of services the 

programs provide in response to family needs. 

Relevant Policy 

Issues: 

Educational Opportunities and Child/Family Well-being. 

Data Type(s): Program reporting data 

Unit of 

Analysis: 

The unit of analysis is the individual Head Start programs. A program identifier 

variable allows for separate counts to be generated for AI/AN Head Start 

Programs. 

Identification 

of AI/AN/NA: 

Head Start programs report the number of participants per race category based on 

enrollment records. The instructions for reporting race are as follows: 

Report the total number of children (and pregnant women in EHS programs) by 

race: 

• American Indian or Alaska Native (AI/AN). A person having origins in 

any of the original peoples of North, South, or Central America, and who 

maintains tribal affiliation or community attachment. 

• Asian. A person having origins in any of the original peoples of the Far 

East, Southeast Asia, or the Indian subcontinent. 

• Black or African American. A person having origins in any of the Black 

racial groups of Africa. 

• Native Hawaiian or other Pacific Islander (NH/PI). A person having 

origins in any of the original peoples of Hawaii, Guam, Samoa, or other 

Pacific Islands. 

5-73 
Head Start Program Information Report 

(continued) 

• White. A person having origins in any of the original peoples of Europe, 

the Middle East, or North Africa. 

• Biracial or Multi-Racial. A person of two or more races. 

• Other. A person reporting a race other than those listed above. 

• Unspecified. Race not reported and/or unknown. 

AI/AN/NA 

Population in 

Data Set: 

Enrollment for Program Year 2004-2005 (reported by 2,695 programs): 

Total enrollment: 1,065,225 

AI/AN: 55,733 (of these individuals, 21,161 are serviced by AI/AN Head Start 

Programs) 

NH/PI: 8,448 

Geographic 

Scope: 

Geographic areas are identified by the location of the Head Start program. The 

PIR provides summary data at the national, regional, state, city and zip code 

levels. 

Date or 

Frequency: 

The Head Start PIR is compiled on an annual basis. The most recent available 

data are for the 2004-2005 program year. 

Data Collection 

Methodology: 

Head Start programs can submit data to the PIR through an online reporting 

application or using the desktop PIR reporting software. 

Participation: Mandatory 

Authorization: According to federal mandates, all Head Start and Early Head Start programs are 

required to complete a PIR on an annual basis. Head Start Performance Standards 

are under the authority for the final rule in sections 641(a) and (d), 642(b) and (d), 

644(a) and (c), and 645(h)(2) of the Head Start Act, as amended (42 U.S.C. 9801 

et. Seq.). 

Strengths: Data sets contain a large number of AI/AN/NA respondents. Researchers can 

disaggregate the data to look at children served by AI/AN Head Start programs. 

Data address the key policy issues of education and child and family well-being. 

There are multiple years of data available. 

Limitations: Data are only available at the aggregate level. 

Access 

Requirements 

and Use 

Restrictions: 

A request to use the data should be emailed to the Office of Head Start, where it 

will be reviewed and approved before data access is granted. There is no charge. 

Contact 

Information: 

Office of Head Start 

Office of Program Management and Operations 

370 L'Enfant Plaza SW 

Washington, D.C. 20447 

(202) 205-8396 

5-74 
Health and Retirement Study (HRS) 

 

Sponsor: U.S. Department of Health and Human Services (DHHS)/National Institutes of 

Health (NIH)/National Institute on Aging (NIA) 

Description: The University of Michigan Health and Retirement Study (HRS) is a national 

panel study of more than 22,000 Americans over the age of 50. Sponsored by the 

National Institute on Aging, the study is conducted every two years (1992-2006) 

and includes core interviews with the sampled respondents and proxy interviews 

when the sampled respondents have died. The study collects data on physical and 

mental health, insurance coverage, financial status, family support systems, labor 

market status, and retirement planning. 

Relevant Policy 

Issues: 

Measurement of Health Status, Disease-specific Measurements, Income Status, 

Educational Attainment, Measures of Well-being for Elders, and Factors 

Contributing to Well-being Disparities of Elders. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification The questionnaire item on race is phrased as follows: “Do you consider yourself 

primarily White or Caucasian, Black or African American, American Indian, or 

Asian, or something else?” 

of AI/AN/NA: 

If the respondent indicated either American Indian or Alaska Native (even though 

the option “Alaska Native” is not stated in the question), then these two 

categories are collapsed into a single category. Asians and Pacific Islanders are 

also collapsed into a single category. 

Beginning in 2006, the HRS adopted the more exhaustive Census race item that 

separates American Indians, Alaska Natives, Native Hawaiians and Pacific 

Islanders. 

AI/AN/NA 

Population in 

Data Set: 

For the 1992 Core interview: 

Total: 12,521 

American Indian/Alaska Native: 162 

Counts for later waves of the HRS are available from codebooks that can be 

accessed at no cost from the HRS website. Since the HRS adds new refresher 

cohorts every six years (most recently in 2004), the count for AI/AN persons may 

increase, but could also decrease as a result of attrition or death. The overall 

numbers, however, will not change drastically. 

Geographic 

Scope: 

The geographic scope of this study is national. Geographic areas are also 

identified by Census region. 

Date or 

Frequency: 

The HRS is a longitudinal study. Baseline interviews were conducted in-home 

and face-to-face beginning in 1992 for the 1931-1941 birth cohort (and their 

5-75 
Health and Retirement Study (HRS) 

(continued) 

spouses, if married, regardless of age); and in 1998 for newly added 1924-1930 

and 1942-1947 birth cohorts. The HRS includes follow-ups by telephone every 

second year, with proxy interviews after death. Data are publicly available for 

each wave of data collection. Data collection for the 2006 wave was underway at 

the time this catalog was prepared. Also, beginning in 2006, one half of the 

follow-ups will be conducted face-to-face to permit collection of biological 

samples and physical performance measures. 

Aggregation: The HRS is a longitudinal panel survey (conducted every two years since 1992). 

Public release cross-sectional data are available for each year of data collection 

and smaller-scope cross-wave data sets are also publicly available. It is possible 

to combine the cross-sectional data sets to obtain cross-wave data sets that would 

contain information not available in the cross-wave data sets that are currently 

provided. The overall count of members of the AI/AN population, however, will 

not increase as the same respondents are represented in each wave of data 

collection, but it may decrease because of attrition or death. 

Data Collection 

Methodology: 

Most of the interviews are done by telephone, although exceptions are made 

when respondents have health limitations that would make an hour-long session 

on the telephone difficult or impossible or when there is no telephone in the 

household. The preferred mode of data collection was face-to-face for the first 

wave of data collection and by telephone for subsequent waves. 

Participation: Optional, with incentives 

Response Rate: The overall unweighted response rate reported for the 2004 wave of data 

collection was 86.2 percent. Given the complexity of the HRS design, 

considerable detail on the calculation of response rates across waves is available 

from 

http://hrsonline.isr.umich.edu/intro/sho_uinfo.php?hfyle=sample_new_v2&xtyp=

2#rates. 

Sampling 

Methodology: 

The HRS sample is selected using a multi-stage area probability sample design. 

The sample includes four distinct selection stages. The primary stage of sampling 

involves probability proportionate to size (PPS) selection of U.S. Metropolitan 

Statistical Areas (MSAs) and non-MSA counties. This stage is followed by a 

second stage sampling of area segments (secondary sampling units or SSUs) 

within sampled primary sampling units (PSUs). The third stage of sample 

selection is preceded by a complete listing (enumeration) of all housing units 

(HUs) that are physically located within the bounds of the selected SSU. The 

third sampling stage is a systematic selection of housing units from the HU 

listings for the sample SSUs. The fourth and final stage in the multi-stage design 

is the selection of an age-eligible person within a sample HU. 

Analysis: Methodological details regarding the survey design of the HRS are available from 

http://hrsonline.isr.umich.edu/docs/sho_refs.php?hfyle=design&xtyp=2. 

5-76 
Health and Retirement Study (HRS) 

(continued) 

Strengths: Data are collected on key policy issues including health and the well-being of 

elders. There are multiple years of data available. Comprehensive documentation 

is available. There is a low sample attrition rate. 

Limitations: There are a small number of AI/AN respondents and NH/PI respondents cannot 

be separated from Asian respondents. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to the public at no cost. Detailed race data are only available 

as restricted-use data. Researchers will need to obtain special permission to 

access these files, in order to protect confidentiality. 

Contact 

Information: 

Data can be accessed at: http://hrsonline.isr.umich.edu. 

Health and Retirement Study 

Survey Research Center 

Institute for Social Research 

University of Michigan 

426 Thompson Street 

Ann Arbor, MI 48104 

Phone: (734) 936-0314 

Fax: (734) 647-1186 

Email: hrsquest@isr.umich.edu

5-77 
Health Behavior in School-aged Children (HBSC) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/National Institutes of 

Health (NIH)/National Institute of Child Health and Human Development 

(NICHD) and the Health Resources and Services Administration (HRSA) (The 

World Health Organization (WHO) collaborates to disseminate results.) 

Description: The Health Behavior in School-aged Children (HBSC) survey is a cross-national 

survey intended to help researchers better understand the well-being, health 

behaviors and social context of children aged 11, 13 and 15, who are attending 

school. Specifically, the survey seeks to monitor health-risk behaviors and 

attitudes in youth throughout the adolescent school age years to provide 

background and identify targets for health promotion initiatives. In addition, the 

survey offers insight in the development of health attitudes and behaviors through 

early adolescence. Although cross-national comparisons can only be made with 

children aged 11, 13, and 15, the U.S. surveys also includes larger, nationally 

representative samples of ages 11 through 15 with an over-sampling of AfricanAmerican and Hispanic children. The sample size in 2001-2002 is approximately 

14,800. 

Questions in the survey address type of drug use (e.g., tobacco, alcohol, 

marijuana, cocaine, inhalants, hallucinogens, and a number of other substances), 

ease of obtaining drugs, frequency of drug usage, and other health behaviors and 

personal history such as eating habits, family make-up, depression, stealing, 

fighting, bringing weapons to school, anger management, attention span at school, 

and opinions about school itself. The U.S. study also includes a survey of school 

administrators and health educators to provide contextual information about the 

school and health education programs in the school. The HBSC began in 1983 

and has been conducted approximately every 4 years. The most recently available 

data for the United States are the 2001-2002 survey year data. 

Relevant Policy 

Issues: 

Measurement of Health Status, Health Disparities, Income Status, Measurement 

of Economic/Employment Disparities between AI/AN/NA and General 

Population, Factors Contributing to Educational Disparities, Factors Contributing 

to Well-being Disparities of Families, and Measures of Well-being for Children. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

The survey question is phrased as follows: What is your race? (Mark one or more 

races to indicate what you consider yourself to be.) 

• American Indian or Alaska Native (AI/AN) 

• Asian 

• Black or African American 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• White 

5-78 
Health Behavior in School-aged Children (HBSC) 

(continued) 

AI/AN/NA 

Population in 

Data Set: 

In 2001-2002 survey data: 

Total number of records: 14,818 

AI/AN: 572 

NH/PI: 116 

Geographic 

Scope: 

The survey is cross-national and country of residence is the only geographic area 

identified. The U.S. portion of the data set does not provide any finer geographic 

detail. 

Date or 

Frequency: 

The survey has been conducted approximately every 4 years beginning in 1983-

1984. 

Data Collection 

Methodology: 

Data are collected via self-completed questionnaires administered to children 

aged 11, 13, and 15 attending sampled schools. 

Participation: Optional, without incentives 

Response Rate: Of the 548 schools were selected to participate for the 2001-2002 survey year, 

340 (62.5 percent) responded yielding 18,593 eligible students. Of the eligible 

students (after eliminating 637 absent on day of survey, 600 not providing 

consent when required, 518 parents declining their child permission, and 1,620 

students declining to participate), 15,245 (82 percent) completed questionnaires. 

Of this sample, 62 students who had missing data on a significant number of key 

items and 365 students who were outliers (+1 percent) for age in grade were 

dropped, leaving a sample of 14,818 for further analyses. 

Sampling 

Methodology: 

The HBSC utilizes a three-stage cluster design where school counties are the 

primary sampling unit (PSU) or first stage, schools are the second stage, and 

classrooms are the third stage. 

Analysis: A SAS macro file, made available with the downloaded data set, enables the end 

user to calculate appropriate standard errors that adjust for design effects. 

Strengths: The 1997-1998 survey data include a large number of AI/AN/NA respondents. 

Limitations: The 58 percent school participation rate may impact the external validity 

(generalizability) of study findings to the overall population of school-aged 

children aged 11-17 in the U.S. 

Access 

Requirements 

and Use 

Restrictions: 

The data set is available to the public at no cost. 

5-79 
Health Behavior in School-aged Children (HBSC) 

(continued) 

Contact 

Information: 

The data for the United States and documentation can be downloaded through the 

University of Michigan’s Inter-University Consortium for Political and Social 

Research: 

http://webapp.icpsr.umich.edu/cocoon/SAMHDA-SERIES/00195.xml. 

Reports of 

Interest: 

Summary Report Download: 

http://www.euro.who.int/Document/e82923.pdf. 

To obtain research protocol: 

http://www.hbsc.org/publications/research_protocols.html. 

5-80 
Health Information National Trends Survey (HINTS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/National Cancer 

Institute (NCI)/Health Communication and Informatics Research Branch 

(HCIRB)/Division of Cancer Control and Population Sciences (DCCPS) 

Description: The Health Information National Trends Survey (HINTS) data collection program 

was created to monitor changes in the rapidly evolving field of health 

communication. Questions on the HINTS survey include topics such as health 

communication with doctors, obtaining information from the media, knowledge 

of cancer and screening behavior, primary cancer risk behaviors, and respondent 

characteristics. HINTS data were collected in 2003 and 2005. Uses of the data 

include: (a) extending cancer communication research from the laboratory to the 

population, (b) monitoring the population’s use of new media (e.g., and 

specifically the Internet), (c) documenting the public’s progress in accurate 

knowledge related to cancer and chronic disease prevention, and (d) stimulating 

cross-branch cooperation. 

Relevant Policy 

Issues: 

Identification of Evidence-based Practices and Programs that Address Causes of 

Health Disparities, Result in Positive Health Outcomes, and are 

Generalizable/replicable. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification Which one or more of the following would you say is your race? Are you 

American Indian or Alaska Native (AI/AN), Asian, Black or African American, 

Native Hawaiian or other Pacific Islander (NH/PI), or White? (Interviewers are 

instructed to code all that apply. If the respondent says “Hispanic,” they are to 

probe for one of the listed race categories.) 

of AI/AN/NA: 

AI/AN/NA 

Population in 

Data Set: 

In 2003, data were collected from 6,369 respondents. Of these 6,369 respondents, 

203 were AI/AN and 32 were NH/PI. In 2005, data were collected from 5,586 

respondents. Of these 5,586 respondents, 141 were AI/AN and 17 were NH/PI. 

Geographic 

Scope: 

The geographic scope of the study is national. No additional geographic 

breakdowns of the data are available. 

Date or 

Frequency: 

HINTS data were collected in 2003 and 2005. The third administration of the 

survey was funded in 2006 and will go into the field in 2007. 

Data Collection 

Methodology: 

Telephone data collection was conducted using computer-assisted telephone 

interviewing (CATI) by trained telephone interviewers over a period of 25 weeks. 

In 2005, some respondents were offered a web-based option for completing the 

survey using the Internet. 

Participation: Optional, with incentives 

5-81 
Health Information National Trends Survey (HINTS) 

(continued) 

Response Rate: The 2005 overall response rate is reported as 20.83 percent. 

Sampling 

Methodology: 

The sample design for both the 2003 and 2005 HINTS was a list-assisted, random 

digit dialing (RDD) sample of all telephone exchanges in the United States. This 

approach resulted in a nationally representative sample of households. During the 

household screener, one adult was sampled within each household and recruited 

for the extended interview. The respondent selection process was the same for the 

2003 and 2005 HINTS with a minor modification for three-person households. 

Analysis: The HINTS data set is weighted. Base weights were assigned to both sampled 

households and sampled adults within households. Standard errors were 

computed for HINTS 2005 estimates. The HINTS 2005 Final Report contains 

detailed information regarding the computation of these weights. 

Strengths: Data are collected on health policy issues including health communication and 

information. There are multiple years of data available. 

Limitations: There are a very limited number of AI/AN/NA individuals in this study. The 

response rate for the 2005 HINTS study is very low. 

Access 

Requirements 

and Use 

Restrictions: 

Data can be downloaded directly from the HINTS website at no cost (after 

registering). 

Contact 

Information: 

Data can be downloaded at http://hints.matthewsgroup.com/register.asp. 

NCI Division of Cancer Control and Population Sciences 

6130 Executive Boulevard, Suite 6134 

Bethesda, Maryland 20892 

http://hints.cancer.gov 

http://cancercontrol.cancer.gov/hints/ 

5-82 
Integrated Postsecondary Education Data System (IPEDS) 

Sponsor: U.S. Department of Education (DoE)/National Center for Educational Statistics 

(NCES) 

Description: The Integrated Postsecondary Education Data System (IPEDS), established as the 

core postsecondary education data collection program for NCES, is a system of 

surveys designed to collect data from all primary providers of postsecondary 

education. For IPEDS, a postsecondary institution is defined as an organization 

open to the public that has as its primary mission the provision of postsecondary 

education (defined as formal instructional programs with a curriculum designed 

primarily for students who are beyond the compulsory age for high school). The 

IPEDS system is built around a series of interrelated surveys designed to collect 

institution-level data in such areas as enrollment, program completion, faculty, 

staff, and finances. IPEDS surveys postsecondary institutions, including 

universities and colleges, as well as institutions offering technical and vocational 

education beyond the high school level. All institutions that participate in any 

federal student financial assistance program authorized by Title IV must submit 

data to IPEDS. 

Relevant Policy 

Issues: 

Educational Attainment. 

Data Type(s): Program reporting data 

Unit of 

Analysis: 

Educational institution 

Identification 

of AI/AN/NA: 

Institutions report data on American Indians/Alaska Natives (AI/AN) students in 

three areas: enrollment, completers by program studied, and graduation rates. 

AI/AN/NA 

Population in 

Data Set: 

Enrollment at Title IV institutions in the U.S., Fall 2004: 

Total: 17,710,798 

AI/AN population = 170,919 

Using IPEDS, it is also possible to disaggregate the data by tribal colleges. 

Thirty-two tribal colleges submitted data to IPEDS in 2004. Enrollment at tribal 

colleges in the U.S., Fall 2004: 

Total enrollment at tribal colleges: 17,599 

AI/AN enrollment at tribal colleges = 14,067 

Geographic 

Scope: 

The geographic scope of IPEDS is national. Institutions can be grouped by state 

for state-level analysis. Additional information on the state of residence of firsttime freshmen is collected in even years. 

Date or 

Frequency: 

IPEDS surveys are collected on an annual basis. IPEDS began in 1986, replacing 

the Higher Education General Education Information Survey (HEGIS) which 

began in 1966. 

5-83 
Integrated Postsecondary Education Data System (IPEDS) 

(continued) 

Data Collection 

Methodology: 

IPEDS uses a web-based data collection system. Each institution designates a 

person or several persons who are responsible for ensuring that survey data 

submitted for the institution are correct. Non-response follow-up is conducted 

with CEOs, coordinators, and data entry staff via mail, e-mail, and telephone. 

Participation: Participation is mandatory for Title IV institutions. Institutions that do not 

participate in Title IV programs may participate in the IPEDS data collection on a 

voluntary basis. 

Response Rate: As data collection is mandatory for Title IV institutions, response rates are very 

high. Response rates calculated by type of institution for all IPEDS survey 

components are above 95 percent. Response rates for non-Title IV institutions are 

not provided. 

Authorization: The completion of the surveys by all institutions that participate in or are 

applicants for participation in any federal financial assistance program authorized 

by Title IV of the Higher Education Act of 1965, as amended, is mandated by 20 

U.S.C. 1094, Section 487(a)(17). 

Strengths: The data sets contain a large number of AI/AN respondents. It is possible to 

disaggregate the data to examine counts by tribal colleges. Data are collected on a 

key policy issue, education. There are multiple years of data available. 

Limitations: Data are only available at the institutional level. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available on the Internet at no charge. 

Contact 

Information: 

IPEDS data are available online. The online table generator for IPEDS is located 

at http://nces.ed.gov/dasol/tables/. Additionally, researchers can download IPEDS 

data to their PC using the IPEDS Peer Analysis and Data Cutting Tool at 

http://nces.ed.gov/ipedspas/. 

National Center for Education Statistics 

Institute of Education Sciences 

1990 K Street, NW 

8th & 9th Floors 

Washington, DC 20006, USA 

Telephone: (202) 502-7300 

5-84 
Medicaid Analytic Extract (MAX) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Medicare 

and Medicaid Services (CMS) 

Description: The Medicaid Analytic Extract (MAX) files (formerly State Medicaid Research 

Files) are comprised of the Personal Summary, Inpatient, Long-Term Care, Drug, 

and Other Therapy data sets, and contain eligibility and utilization records. The 

Personal Summary File contains one record for every individual enrolled in 

Medicaid for at least one day during the year. These files include demographic 

data (e.g., date of birth, gender, race); basis of eligibility; maintenance assistance 

status; monthly enrollment status; utilization summary; complete inpatient stay 

records; claims for long term care services provided by Nursing Facilities, Skilled 

Nursing Facilities (SNFs), Intermediate Care Facilities (ICFs), and independent 

psychiatric facilities; drug claims; and claim records for all non-institutional 

Medicaid services, including physician services, lab/X-ray, clinic services and 

premium payments. 

Relevant Policy 

Issues: 

Measurement of Health Status, Disease-specific Measurements, Health 

Disparities, Factors Contributing to Measured Health Disparities, Measures of 

Well-being for Children, and Measures of Well-being for Elders. 

Data Type(s): Program reporting data 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Racial/ethnic categories available: 

• White (was “White, not of Hispanic origin” through September 1998) 

• Black or African American (was “Black, not of Hispanic origin” through 

September 1998) 

• American Indian or Alaska Native (AI/AN) 

• Asian (was “Asian or Pacific Islander” through September 1998) 

• Hispanic or Latino – No Race information available (was “Hispanic" 

[without race annotation] through October 1998) 

• Native Hawaiian or other Pacific Islander (NH/PI) (new code beginning 

October 1998) 

• Hispanic or Latino and one or more Races (new code beginning October 

1998) 

• More than one Race (new code beginning October 1998) 

• Unknown 

AI/AN/NA 

Population in 

Data Set: 

Unweighted population in data source from 2003 files: 

TOTAL: 55,157,775 

AI/AN: 806,211 

NH/PI: 508,106 

5-85 
Medicaid Analytic Extract (MAX) 

(continued) 

Geographic 

Scope: 

The geographic scope of the MAX files is national. State, county, and zipcode also 

are available for analyses. Files for the District of Columbia are available 

beginning with the MAX 1999. 

Date or 

Frequency: 

Data are submitted quarterly, with data files made available on an annual basis 

from 1992 to the present. 

Data Collection 

Methodology: 

States submit data via the Medicaid Statistical Information System (MSIS), 

meeting standardized specifications. MSIS data are cleaned and reconciled and 

become the MAX files. 

Participation: Mandatory 

Response Rate: As the submission of these data are mandatory, it is assumed that the response is a 

near census of all states. This assumption is only valid for reporting of eligibles 

and Fee for Service utilization. Reporting of encounter data for services provided 

under a capitated managed care plan was mandated beginning with FY 1999. The 

data are still viewed as largely incomplete for utilization. 

Authorization: The Balanced Budget Act of 1997 mandated that all states submit Medicaid-paid 

claims data to CMS. Prior to this, states submitted data on a voluntary basis. 

Strengths: These data files contain a very large number of AI/AN/NA respondents. Data 

contain indicators concerning key policy issues including health, child well-being, 

and elder well-being. There are multiple years of data available. Because these 

data represent a census of Medicaid data, response rates and sample sizes are not 

an issue in using the data. States submit data on standardized forms and all data 

are available in electronic form making the data relatively easy to access and use. 

Limitations: The data files are quite large and cumbersome to use. Potential users must also be 

extremely familiar with the data documentation to ensure that they are interpreting 

results obtained from this data set correctly. For example, the variation in 

procedures and practices across states (e.g., one state tracks or defines a certain 

service differently) means that there are numerous exceptions or variations on the 

data standardization requirements. The extensive documentation tracking these 

data anomalies that should be examined by potential users of these data. 

Access 

Requirements 

and Use 

Restrictions: 

Researchers must submit a proposal and comply with multiple criteria of the data 

use agreement. Note that only approved academic research projects and certain 

government agencies are entitled to a data use agreement to obtain MAX data. 

Detailed information can be found at: 

http://www.resdac.umn.edu/Medicaid/requesting_data.asp. 

Cost of the data set is dependent on the number of states, years, and file types 

requested. 

5-86 
Medicaid Analytic Extract (MAX) 

(continued) 

Contact 

Information: 

Contact Information: 

E-Mail: resdac@umn.edu 

Phone: (888) 9-ResDAC or (888) 973-7322 

Data documentation: 

http://www.resdac.umn.edu/Medicaid/data_documentation.asp. 

http://www.cms.hhs.gov/MedicaidDataSourcesGenInfo/07_MAXGeneralInformation.asp

5-87 
Medical Expenditure Panel Survey (MEPS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Agency for Health Care 

Research and Quality (AHRQ) and National Center for Health Statistics (NCHS) 

Description: The Medical Expenditure Panel Survey (MEPS) is conducted to provide 

nationally representative estimates of health care use, health care expenditures, 

sources of payment, health insurance coverage and health status for the U.S. 

civilian noninstitutionalized population. MEPS data can be used to estimate the 

impact of changes in sources of payment and insurance coverage on different 

economic groups or special populations of interest, such as the poor, elderly, 

families, veterans, the uninsured, and racial and ethnic minorities. 

MEPS is comprised of three component surveys: the Household Component 

(HC), the Medical Provider Component (MPC), and the Insurance Component 

(IC). The HC is the core survey, and it forms the basis of the MPC sample. 

Together these surveys yield comprehensive data that provide national estimates 

of the level and distribution of health care use and expenditures, support health 

services research, and can be used to assess health care policy implications. 

Relevant Policy 

Issues: 

Measurement of Health Status, Disease-specific Measurements, Health 

Disparities, Factors Contributing to Measured Health Disparities, Measures of 

Well-being for Families/Households, Factors Contributing to Well-being 

Disparities of Families, Measures of Well-being for Children, Measures of Wellbeing for Elders, and Factors Contributing to Well-being Disparities of Elders. 

Data Type(s): Survey 

Unit of 

Analysis: 

Data can be analyzed at the person level, the event level, the family level, or the 

health insurance unit level. 

Identification 

of AI/AN/NA: 

Race categories include (2002 and beyond): 

• White alone 

• Black alone 

• American Indian or Alaska Native (AI/AN) alone 

• Asian alone 

• Native Hawaiian or Pacific Islander (NH/PI) alone 

• Multiple Race 

AI/AN/NA 

Population in 

Data Set: 

Based on 2004 MEPS data, out of 34,403 total records, 293 are coded AI/AN 

alone and 150 are coded NH/PI alone. Multiple years of data can be pooled to 

increase the sample size. Aggregation requires at least 100 unweighted cases to 

support national estimates. 

Geographic 

Scope: 

The geographic scope of the MEPS is national. The MEPS is designed to support 

national and regional estimates. Due to small sample sizes, state estimates of the 

AI/AN/NA population are not possible. 

5-88 
Medical Expenditure Panel Survey (MEPS) 

(continued) 

Date or 

Frequency: 

MEPS was initiated in 1996 and is a continuous ongoing survey. MEPS 

predecessor surveys were conducted in 1987 and 1977. 

Data Collection 

Methodology: 

The MEPS HC uses an overlapping panel design in which data are collected 

through a series of five rounds of interviews over a 2-1/2 year period using 

computer-assisted personal interviewing technology to collect information on all 

household members. This series of data collection rounds is launched each 

subsequent year on a new sample of households to provide overlapping panels of 

survey data that, when combined, will provide continuous and current estimates 

of health care expenditures. In 2000, an annual fielding of a self-administered 

questionnaire (SAQ) was introduced into the process as well. 

For the MPC, a sample of medical providers are contacted by telephone to 

provide information that the household respondents cannot accurately provide 

(after obtaining permission from the HC respondents). The IC is an annual panel 

survey that collects data on health insurance plans obtained through employers, 

unions, and other sources of private health insurance. Data are collected by the 

Census Bureau from the sampled organizations through a prescreening telephone 

interview, a mailed questionnaire, and a telephone follow-up for non-respondents. 

Participation: Optional, with incentives ($25.00) for each of the five rounds of interviews 

completed and $5.00 for each self-administered or child questionnaire completed. 

Response Rate: The full-year HC response rate has generally ranged from about 65 to 71 percent. 

Conditional response rates for Rounds 2-5 are always over 90 percent. 

Sampling 

Methodology: 

The MEPS-HC uses the National Health Interview Survey (NHIS) conducted by 

the National Center for Health Statistics as its sampling frame. The NHIS 

sampling frame provides a nationally representative sample of the U.S. civilian 

non-institutionalized population and reflects an over-sampling of Blacks and 

Hispanics. In certain years MEPS over samples additional policy relevant subgroups. This design allows linkage back to the previous year’s NHIS for analytic 

purposes. 

Analysis: As with most surveys, participating individuals represent only a fraction of the 

overall population the survey is intended to reflect. In order to calculate estimates 

representing the overall population, responses from surveyed individuals must be 

weighted by the proportion of the population they represent. In addition, 

adjustments must be made to account for non-response. Each MEPS file contains 

appropriate weight variables that can be applied to the data to generate national 

estimates of the civilian non-institutionalized population. A detailed description 

of the weighting process and how weights are applied to estimates can be found in 

the weighting and estimation section of the online workbook under the workshop 

and events section of the MEPS web site. 

Because MEPS relies on a complex sampling design rather than simple random 

sampling, it is important to take into account reductions in the accuracy of 

5-89 
Medical Expenditure Panel Survey (MEPS) 

(continued) 

calculated estimates (size of standard errors). Statistical software programs such 

as SAS (version 8.2 or higher), SUDAAN, STATA, and SPSS (version 12.0 or 

higher), are available to accommodate the complex design and calculate robust 

standard errors. A full description of how to compute standard errors for MEPS 

can be found on the MEPS web site 

(http://www.meps.ahrq.gov/FactSheets/FS_StandardErrors.HTM). 

Strengths: MEPS facilitates research on relationships between individual characteristics and 

health care utilization. It provides national and regional estimates of health care 

use and expenditures. It contains two full years’ worth of data for each panel. 

Each panel also can be linked to the previous year’s NHIS for a third point in 

time. This design facilitates analysis of change over time. MEPS data can be used 

to estimate the impact of changes in sources of payment and insurance coverage 

on different populations of interest such as the AI/AN/NA population, or to 

evaluate the impact of an intervention or treatment on health status over time. It is 

the only source of actual sources of payments and amounts paid including out-ofpocket expenditures for health care visits. 

Limitations: The MEPS was not designed to produce state-level estimates. While aggregate 

estimates for a selected number of large states may be possible, small sample 

sizes preclude making such estimates for the AI/AN/NA populations. Even after 

pooling several years of MEPS data, sample size limitations and confidentiality 

restrictions make MEPS data unsuitable for certain types of analysis. For 

example, the MEPS data do not support research on rare conditions. Moreover, 

information on conditions is household reported and not verified by clinical 

records. All MEPS data are reported by one designated household respondent. 

Reporting detailed information on other household members can sometimes be 

problematic. 

Access 

Requirements 

and Use 

Restrictions: 

MEPS HC data releases, including documentation and codebooks, are available 

free to the public on the Internet (via the MEPS web site). MEPS IC data are 

published in tabular format on a yearly schedule. MEPS data (HC and IC data) are 

also available via MEPSnet, an on-line, interactive, statistical tool developed to 

give users the ability to analyze MEPS data in real-time. Access to the MEPS IC 

full data set is only available in a Census Bureau Research Data Center. 

Many of the MEPS databases include considerably more data than can be made 

available to the general public because of the constraints of confidentiality 

guidelines. In order to facilitate the use of such data, while maintaining the 

confidentiality, AHRQ developed a Data Center (a physical space at AHRQ in 

Rockville, Maryland) where researchers with approved projects can access data 

files not available for public dissemination. See the MEPS web site for details. 

5-90 
Medical Expenditure Panel Survey (MEPS) 

(continued) 

Contact 

Information: 

The MEPS website is http://www.meps.ahrq.gov/. 

By e-mail: mepspd@ahrq.gov 

By phone/fax: MEPS Information Coordinator (301) 427-1656 

CFACT General Information: (301) 427-1406 

CFACT Fax: (301) 427-1276 

By mail: Project Director 

Center for Financing, Access and Cost Trends 

Medical Expenditure Panel Survey 

Agency for Healthcare Research and Quality 

540 Gaither Road 

Rockville, MD 20850 

Telephone: (301) 427-1656 

E-mail: mepspd@ahrq.gov 

Reports of 

Interest 

For copies of data products and reports, see the MEPS web site. Selected MEPS 

data products are available from: 

AHRQ Publications Clearinghouse 

P.O. Box 8547 

Silver Spring, MD 20907 

(1-800) 358-9295 

(703) 437-2078 outside the U.S. 

TDD for the hearing impaired, toll free: (888) 586-6340 

5-91 
Medicare Denominator File 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Medicare 

and Medicaid Services (CMS) 

Description: The Medicare Denominator File contains demographic and enrollment 

information about each beneficiary enrolled in Medicare during a calendar year. 

The information in the Denominator File is finalized in March of the following 

calendar year. Some of the information contained in the file includes the 

beneficiary unique identifier, state and county codes, zipcode, date of birth, date 

of death, sex, race, age, monthly entitlement indicators (Part A/B/Both), reasons 

for entitlement, state buy-in indicators, and monthly managed care indicators 

(yes/no). The Denominator File is used to determine beneficiary demographic 

characteristics, entitlement, and beneficiary participation in Medicare Managed 

Care Organizations. 

Relevant Policy 

Issues: 

Factors Contributing to Measured Health Disparities and Measures of Well-being 

for Elders. 

Data Type(s): Program enrollment, eligibility, and demographic data 

Unit of 

Analysis: 

Individual 

Identification Race is provided by the Social Security Administration and is found within the 

Denominator file. CMS receives a quarterly update file from Indian Health 

Services on individuals deemed by IHS to be Native American and uses it to 

update the race code found in the Denominator file. The information from the IHS 

will override any other code which may have been on file. 

of AI/AN/NA: 

Race/ethnic categories included in the data are: 

• Unknown 

• White 

• Black 

• Other 

• Asian/Pacific Islander 

• Hispanic 

• North American Native 

AI/AN/NA 

Population in 

Data Set: 

Population size is not available in documentation, however, this file is a census of 

the Medicare population and should have more than sufficient sample size for 

research purposes. The Native American population from the administrative 

records in 2002, for example, was over 141,000. 

Geographic 

Scope: 

The geographic scope of the file is national. State, county, and zip code are 

available in the file. 

5-92 
Medicare Denominator File 

(continued) 

Date or 

Frequency: 

Data are collected on an ongoing basis with the files constructed on an annual 

basis. 

Data Collection 

Methodology: 

The Medicare Denominator Files are populated using the Medicare enrollment 

database, an administrative data source completed when individuals become 

eligible for and enroll in the Medicare program. An update in March of each year 

is included for the previous year’s data file (e.g., March 1995 update is used to 

finalize the 1994 denominator file). 

Participation: Mandatory 

Strengths: The Medicare Denominator File can be combined with other data sources (e.g., 

Standard Analytic File/Claims data) using the beneficiary’s unique identifier, and 

therefore can be a very powerful analytic data source. On their own, these files 

offer a census of Medicare enrollment, type of coverage and basic demographics. 

They contain a large number of AI/AN/NA respondents and there are multiple 

years of data available. 

Limitations: The Pacific Islander population is not separated from the Asian racial/ethnic 

category. The AI/AN/NA populations are also not divided into more refined 

categories. Given the size of the Medicare population, cell size concerns should 

not be an issue, yet only these broader race/ethnic categories are available. This is 

due in large part to how the data are collected. 

Other: In addition to the data sets profiled in this catalog, a full listing of all available 

CMS data sets is presented at this website: 

http://www.cms.hhs.gov/FilesForOrderGenInfo/ 

Access 

Requirements 

and Use 

Restrictions: 

The data request process involves multiple components including a proposal of 

how the data will be used, evidence of funding for the research, data use 

agreement, Institutional Review Board clearance/waiver, and some administrative 

forms. 

There is a cost associated with use of this data set. Researchers will need 

to contact ResDAC in order to receive pricing information. The steps and forms 

are described in detail at the following website: 

http://www.resdac.umn.edu/medicare/requesting_data.asp. 

Contact 

Information: 

The University of Minnesota, CMS contractor for managing and supporting CMS 

data, can be contacted via the Internet at: 

https://resdac.oit.umn.edu/ 

Via e-mail: resdac@umn.edu 

Via telephone: (888) 973-7322 

Denominator File Record Layout 

http://www.resdac.umn.edu/ddde/dd_de.asp 

5-93 
Medicare Utilization – Standard Analytic Files (SAFs) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Medicare 

and Medicaid Services (CMS) 

Description: The Standard Analytical Files (SAFs) comprise seven data sets containing 

detailed claims information about health care services rendered to Medicare 

beneficiaries in fee-for-service Medicare. SAFs are available for each institutional 

(inpatient, outpatient, skilled nursing facility, hospice, or home health agency) 

and non-institutional (physician and durable medical equipment providers) claim 

types. Data are organized at the claim level and include basic beneficiary 

demographic information, date of service, diagnosis and procedure code, provider 

number, and reimbursement amount. 

Relevant Policy 

Issues: 

Disease-specific Measurements, Health Disparities, and Factors Contributing to 

Measured Health Disparities. 

Data Type(s): Program claims data 

Unit of 

Analysis: 

Final action claims, which are associated with an individual. 

Identification 

of AI/AN/NA: 

Race is provided by the Social Security Administration and is found within the 

Denominator file. CMS receives a quarterly update file from Indian Health 

Services on individuals deemed by IHS to be Native American and uses it to 

update the race code found in the Denominator file. The information from the IHS 

will override any other code which may have been on file. 

The following categories are used in the SAFs: 

• White 

• Black 

• Other 

• Asian 

• Hispanic 

• North American Native 

• Unknown 

AI/AN/NA 

Population in 

Data Set: 

Population size is not available in documentation, however, the data reflect all 

Medicare beneficiaries and therefore should have more than adequate sample size 

to address research needs. 

Geographic 

Scope: 

The geographic scope of the SAFs is national. Zip code is the lowest level of 

geographic detail available in the file. 

Date or 

Frequency: 

Data are submitted continually from the Fiscal Intermediary (FI) and Carriers to 

CMS, but SAFs are produced by calendar year, available from 1991 through the 

present, with 2004 data the most recently available. 

5-94 
Medicare Utilization – Standard Analytic Files (SAFs) 

(continued) 

Data Collection 

Methodology: 

Providers submit claims to the FI or Carrier for processing and payment. The FI 

or Carrier forwards all claims to CMS. CMS creates the SAFs six months 

following the end of the calendar year. 

Participation: Mandatory 

Strengths: This data source offers a near-census (does not include the small number of 

beneficiaries enrolled in managed care organizations) of utilization, expenditure 

and diagnosis data for Medicare beneficiaries. 

CMS updates race information based on a quarterly update file from Indian 

Health Services identifying individuals deemed by IHS to be Native American. 

Limitations: Only very broad racial categories are available (White, Black, Hispanic, Asian, 

Other, North American Native). Claims data are very difficult to work with and 

also consist of very large files, often millions of records large, and therefore are 

not a suitable resource for the average researcher with limited programming 

skills. 

Other: In addition to the data sets profiled in this catalog, a full listing of all available 

CMS data sets is presented at this website: 

http://www.cms.hhs.gov/FilesForOrderGenInfo/ 

Access 

Requirements 

and Use 

Restrictions: 

The data request process involves multiple components including a proposal of 

how the data will be used, evidence of funding for the research, data use 

agreement, Institutional Review Board clearance/waiver, and some administrative 

forms. There is a cost associated with use of this data set. Researchers will need 

to contact ResDAC in order to receive pricing information. The steps and forms 

are described in detail at the following website: 

http://www.resdac.umn.edu/medicare/requesting_data.asp. 

Contact 

Information: 

The University of Minnesota, CMS contractor for managing and supporting CMS 

data, can be contacted via the Internet at: https://resdac.oit.umn.edu/ 

Via e-mail: resdac@umn.edu 

Via telephone: (888) 973-7322 

Please see this website for a further description of the SAFs: 

http://www.resdac.umn.edu/Medicare/data_file_descriptions.asp#rif 

Data Dictionaries are available at: 

http://www.resdac.umn.edu/ddvh/index.asp#RIF 

5-95 
National Aging Program Information Systems (NAPIS) State Program Reports 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Administration on 

Aging (AoA) 

Description: The National Aging Program Information Systems (NAPIS) State Program 

Reports are completed by the states to comply with AoA reporting requirements 

for submission of annual performance reports. Three principal types of data are 

included in the NAPIS design: (1) performance data on programs and services 

funded by the Older Americans Act (OAA); (2) demographic/descriptive data on 

the elderly population obtained from the U.S. Census Bureau and other sources; 

and (3) descriptive data on the infrastructure of home- and community-based 

services in place to assist older persons, based on AoA studies and related 

reviews. 

Relevant Policy 

Issues: 

Factors Contributing to Well-being Disparities of Elders. 

Data Type(s): Program reporting data 

Unit of 

Analysis: 

Primarily aggregated state-level data. Under Title VI of the Older Americans Act, 

grant awards are made directly to tribal and native organizations representing 

older American Indians, Alaska Natives, and Native Hawaiians. Title VI data will 

be available by individual grantee. 

Identification 

of AI/AN/NA: 

On the reporting form entitled General Characteristics of Elderly Clients 

Receiving Registered Services and Those Receiving Cluster 2 Registered Services, 

respondents are given the following options for reporting clients by race or 

ethnicity: 

• White (Alone) – Non-Hispanic 

• White (Alone) - Hispanic 

• American Indian or Alaska Native (AI/AN) (Alone) 

• Asian (Alone) 

• Black or African American (Alone) 

• Native Hawaiian or other Pacific Islander (NH/PI) (Alone) 

• Persons Reporting Some Other Race 

• Persons Reporting Two or More Races 

• Race Missing 

AI/AN/NA 

Population in 

Data Set: 

The total number of persons served under Title III of the OAA for FY 2004 is 

8,651,974. Of these, the total number of AI/AN individuals in the FY 2004 data is 

56,606. NH/PI is combined with Asians in all published reports. 

Geographic 

Scope: 

The geographic scope of the study is national. The identified geographic areas are 

states. 

Date or 

Frequency: 

States submit performance reports annually. 

5-96 
National Aging Program Information Systems (NAPIS) State Program Reports 

(continued) 

Data Collection 

Methodology: 

States submit data to NAPIS through an online reporting application. 

Participation: Mandatory 

Authorization: The 1992 reauthorization of the Older Americans Act (OAA) directed the AoA to 

improve performance reporting on programs and services funded by the OAA. 

This impetus caused AoA to reconsider reporting requirements for all Titles of the 

Act under the direction of AoA. The concept of the National Aging Program 

Information System (NAPIS) arose from this review and the related review of 

AoA's internal information needs. 

Strengths: State information contains a large number of AI/AN/NA respondents. Data are 

collected on the key policy issue of elder well-being. There are multiple years of 

data available. 

Limitations: Most data are only available at the state level. 

Access 

Requirements 

and Use 

Restrictions: 

Data set is available to public at no cost. 

Contact 

Information: 

The general website for the NAPIS program is: 

http://www.aoa.gov/prof/agingnet/NAPIS/napis.asp 

Questions regarding NAPIS should be addressed to: 

Saadia Greenberg 

email: saadia.greenberg@aoa.gov 

or 

Steve Cordasco 

email: steve.cordasco@aoa.gov 

To obtain the NAPIS data, contact: 

Robert Hornyak 

email: robert.hornyak@aoa.hhs.gov 

5-97 
National Ambulatory Medical Care Survey (NAMCS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC)/National Center for Health Statistics (NCHS) 

Description: The National Ambulatory Medical Care Survey (NAMCS) collects information 

about the provision and use of ambulatory medical care services in the United 

States. Non-federally employed office-based physicians complete a one-page 

questionnaire for each patient visit sampled during a one-week reporting period. 

Collected data include physician characteristics (obtained during a survey 

induction interview), patient demographic characteristics (age, sex, race, 

ethnicity), and visit characteristics (patients' symptoms, complaints or other 

reasons for the visit, physicians' diagnoses, diagnostic and therapeutic services 

ordered or provided at the visit including medications, expected sources of 

payment, visit disposition, time spent with physician, etc.). Participating 

physicians must be primarily involved in office-based direct patient care, with 

anesthesiologists, pathologists and radiologists excluded. 

Relevant Policy 

Issues: 

Measurement of Health Status, Key Health Disparities, and Factors Contributing 

to Measured Health Disparities. 

Data Type(s): Survey 

Unit of 

Analysis: 

Patient visit 

Identification 

of AI/AN/NA: 

Physicians are asked to report one or more races (up to 5) for each sampled visit. 

The public use data file includes five single race categories and an aggregated 

category for visits with more than one race checked. 

• White 

• Black/African American 

• Asian 

• Native Hawaiian/Other Pacific Islander (NH/PI) 

• American Indian/Alaska Native (AI/AN) 

• More than one race reported 

AI/AN/NA 

Population in 

Data Set: 

Total number of records in 2004 data set: 25,286 

AI/AN: 93 

NH/PI: 70 

Geographic 

Scope: 

The geographic scope of the study is national. Analysis is possible for the 

following regions: Northeast, Midwest, South, West. 

Date or 

Frequency: 

Data are available annually from 1973 to 1981, in 1985, and annually since 1989. 

5-98 
National Ambulatory Medical Care Survey (NAMCS) 

(continued) 

Aggregation: Each year of data, on average, has 50-90 visits by persons reported as AI/AN only 

and 60-100 visits by persons reported as NH/PI only. According to the NCHS, 

researchers frequently combine years of data for analysis in order to achieve 

reliable estimates. Researchers considering aggregation should take special note 

of changes in sample design variables across the years, as these will affect 

variance estimation. They should also be particularly aware of any possible 

clustering by race that may affect sample estimates. The format and content of the 

survey questionnaires has also changed across the years. Data must be weighted 

to produce national estimates, and researchers may wish to seek guidance about 

the use of weights with aggregated files. 

Data Collection 

Methodology: 

The U.S. Census Bureau acts as the data collection agent for the NAMCS. The 

physician, or his/her staff, is trained by Census field representatives to sample 

patients and to complete the 1-page reporting form for each sampled visit. 

Participation: Optional, without incentives 

Response Rate: In the 2004 survey, the response rate for participating physicians was 64.7 

percent. 

Sampling 

Methodology: 

NAMCS utilizes a multistage probability sample design where geographic 

primary sampling units (PSUs) are selected in the first stage, physician practices 

within PSUs in the second stage (using the American Medical Association and 

American Osteopathic Association directories as the sampling frame), and a 

random sample of patient visits to selected physicians in the third stage. 

Analysis: The weighting procedure produces essentially unbiased national estimates and has 

basically four components: 1) inflation by reciprocals of the probabilities of 

selection, 2) adjustment for nonresponse, 3) a ratio adjustment to fixed totals, and 

4) weight smoothing. Patient visit weights are provided in the data set to produce 

accurate national estimates. 

Strengths: Data are collected on key policy issues pertaining to health. There are multiple 

years of data available. 

Limitations: In the 2004 survey, the item nonresponse rate is low overall; however this rate for 

the variables measuring ethnicity and race is 20.9 percent and 19.2 percent, 

respectively. Race and ethnicity are imputed from records with similar 

characteristics based on physician specialty, geographic region (in the case of 

ethnicity, state is used rather than region), and primary diagnosis. There are also 

few visits by patients categorized as AI/AN or NH/PI. Finally, NAMCS does not 

include physicians from Indian Health Service (IHS) in the sample frame. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to the public at no cost. Restricted files which contain 

additional variables and non-masked data can be accessed by applying to the 

NCHS Research Data Center and paying a fee. 

5-99 
National Ambulatory Medical Care Survey (NAMCS) 

(continued) 

Contact 

Information: 

Main website for NAMCS 

http://www.cdc.gov/nchs/namcs.htm 

Data Download: 

http://www.cdc.gov/nchs/about/major/ahcd/ahcd1.htm#Micro-data 

Contact Information: 

National Center for Health Statistics 

Ambulatory Care Statistics Branch 

3311 Toledo Road, Rm. 3409 

Hyattsville, MD 20782 

(301) 458-4600 

5-100 
National Assessment of Adult Literacy (NAAL) 

Sponsor: U.S. Department of Education (DoE)/National Center for Education Statistics 

(NCES) 

Description: The National Assessment of Adult Literacy (NAAL) is a nationally representative 

assessment of English literacy among American adults age 16 and older. Results 

from the study cover the status and progress of literacy in the nation, the literacy 

skill level of American adults (including the least-literate adults), various factors 

associated with literacy, and the application of literacy skills to health-related 

materials. NAAL also provides the results of state-level assessments of six 

participating states and a national study on literacy among the state and federal 

prison population (local jails and other types of institutions are not included). 

Additionally, one important goal of the 2003 NAAL was to provide trend data in 

adult literacy performance since 1992. At this time, the 2003 NAAL full data set 

and accompanying technical documentation are not ready for public release. 

Relevant Policy 

Issues: 

Educational Attainment. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

During the in-person interview, respondents are asked “Which of the groups on 

this card best describes you? Choose one or more.” and then given a handcard 

with the following response options: 

• White 

• Black or African American 

• Asian 

• American Indian or Alaska Native (AI/AN) 

• Native Hawaiian or other Pacific Islander (NH/PI) 

AI/AN/NA 

Population in 

Data Set: 

Of the 19,714 adults who made up the 2003 NAAL sample, 18,541 were from the 

household sample and 1,173 were from the prison sample. The total number of 

AI/AN respondents included in the full 2003 NAAL sample is 167. The total 

number of NH/PI respondents included is 26. An upcoming NAAL report will 

include separate estimates for AI/ANs. 

Geographic 

Scope: 

The geographic scope of the study is national. In addition to allowing for national 

estimates, both the 1992 and 2003 NAAL allow estimates for state-level 

assessments for those states that choose to participate. In 2003, the following 

states participated in state-level assessments: Kentucky, Maryland, 

Massachusetts, Missouri, New York, and Oklahoma. 

5-101 
National Assessment of Adult Literacy (NAAL) 

(continued) 

Date or 

Frequency: 

The NAAL was conducted in 1992 and 2003. In order to provide trend data on 

adult literacy in the future, NCES plans to conduct additional periodic 

assessments. 

Aggregation: The 1992 and 2003 NAAL used the same sampling and data collection 

procedures to ensure that comparable populations were assessed in both years. 

However, there are differences in how race information was collected between the 

two administrations. In 2003, respondents were not offered an “Other” category 

to describe their race and they could select one or more racial categories, while in 

1992 respondents were limited to choosing one race or ethnicity. Additionally, 

there is an eleven year gap between the two data collection efforts, which may 

contribute to the variability in responses. For these reasons caution should be 

exercised if combining the 1992 and 2003 results for analysis by race/ethnicity. 

Data Collection 

Methodology: 

NAAL is administered in person. Participants are first administered a set of 

background questions using computer assisted personal interviewing (CAPI) and 

a set of basic screening tasks to determine whether they should be given the main 

NAAL or the Adult Literacy Supplemental Assessment (ALSA). The least-literate 

participants are given the ALSA. Main NAAL participants read assessment 

questions from printed booklets and write their answers using a pencil. ALSA 

participants give oral responses to oral questions, but refer to printed materials to 

find the answers. At the end of the interview, all participants take the Fluency 

Addition to NAAL (FAN), which requires them to read lists and passages aloud 

from printed booklets. Participants’ responses to FAN are recorded using CAPI 

software. 

Participation: Optional, with incentives. Respondents were paid $30 to participate. 

Response Rate: Cases are considered complete if the respondent completed the background 

questionnaire and at least one question on each of the three scales of literacy 

assessment, or if the respondent was unable to answer questions due to language 

issues or mental disabilities. The overall weighted response rate for the household 

sample was 60.1 percent. The overall weighted response rate for the prison 

sample was 87.2 percent. 

Sampling 

Methodology: 

NAAL uses a multi-stage probability sampling design. The NAAL sample is 

designed to represent all U.S. adults who live in households and prisons. For the 

2003 NAAL, a national sample of the adult household population was combined 

with samples for the six states that participated in the NAAL state-level 

assessment. Stage 1 of the sample design involved dividing the U.S. into 1,900 

primary sampling units (PSUs) and selecting 160 PSUs total among the national 

and state samples combined. Stage 2 involved selecting area segments within 

each selected PSU. Stage 3 was the selection of sampled households, and stage 4 

was the selection of individual participants within the households. 

5-102 
National Assessment of Adult Literacy (NAAL) 

(continued) 

The NAAL prison sample was independently selected using a two-stage design. 

The first stage involved selecting more than 100 federal and state prisons. The 

second stage involved selecting individual inmates from the selected prisons. 

Strengths: Data are collected on a key policy issue, adult literacy. There are multiple years of 

data available. 

Limitations: There are a small number of AI/AN/NA respondents. Differences in how race 

was assessed in 1992 and 2003, as well as the length of time between the two data 

collection efforts, will affect the ability to aggregate the data. Although currently 

there is a public use data set containing a limited number of variables available on 

the NAAL website, this limited data set does not identify AI/AN individuals 

(available race categories in the public use data set include White, Black, 

Hispanic, and Other.) 

The full NAAL public-use and restricted-use data sets are not ready for 

dissemination at this time. However, once they are released, only the restricted 

use NAAL data set will identify AI/AN individuals. As there are less than 45 

NH/PI cases in the data set, these values will be suppressed according to NAAL 

rules. 

Access 

Requirements 

and Use 

Restrictions: 

To access the NAAL restricted-use data set, individuals will have to obtain an 

NCES license. NAAL staff currently will respond to special requests for analysis 

of NAAL data. Users who want to request that service need to complete a request 

form and submit it to NAAL. There is no cost for these analyses. 

Contact 

Information: 

National Center for Education Statistics 

1990 K Street, NW 

Room 8087 

Washington, DC 20006 

http://nces.ed.gov/NAAL/ 

5-103 
National Child Abuse and Neglect Data System (NCANDS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Administration on 

Children and Families (ACF)/Children's Bureau 

Description: The National Child Abuse and Neglect Data System (NCANDS) is a federally 

sponsored national data collection effort created for the purpose of tracking the 

volume and nature of child maltreatment reporting each year within the United 

States. The NCANDS Child File consists of child-specific data of all investigated 

reports of maltreatment to state child protective service agencies. Child File data 

are collected annually through the voluntary participation of states. Participating 

states submit their data after going through a process in which the state's 

administrative data system is mapped to the NCANDS data structure. Data 

elements include the demographics of children and their perpetrators, types of 

maltreatment, investigation or assessment dispositions, risk factors, and services 

provided as a result of the investigation or assessment. 

Relevant Policy 

Issues: 

Measures of Well-being for Children, Child Maltreatment Rates. 

Data Type(s): Registry 

Unit of 

Analysis: 

The unit of observation in the Child File includes report-level data for all children 

who have received a disposition of an investigation or assessment of allegations 

of maltreatment during the reporting year. Each child on a report gets a separate 

data record, referred to as a "report-child pair." As a child may be in the data file 

multiple times, there is a unique identifier assigned to each child. 

Identification 

of AI/AN/NA: 

Race is coded by the state agency submitting the data to NCANDS. Beginning 

with the year 2000, the agency was allowed to select more than one race for a 

child. Each of the five race variables are independent (White, African American, 

American Indian or Alaska Native (AI/AN), Native Hawaiian or other Pacific 

Islander (NH/PI), and Asian), so an individual may have more than one race 

variable coded as true. 

The directions for coding a child as American Indian or Alaska Native are: A 

child having origins in any of the original peoples of North and South America 

(including Central America) and who maintains tribal affiliation or community 

attachment. 

The directions for coding a child as Native Hawaiian or other Pacific Islander are: 

A child having origins in any of the original peoples of Hawaii, Guam, Samoa, or 

other Pacific Islands. 

If there are a very small number of records at the county level for a particular 

race, the race information is recoded to unknown. 

5-104 
National Child Abuse and Neglect Data System (NCANDS) 

(continued) 

AI/AN/NA 

Population in 

Data Set: 

The 2004 data set consists of 3,134,026 total records (report-child pairs) from 44 

states and the District of Columbia (DC). 

Counts of distinct children by race in the 2004 NCANDS data file:

AI/AN: 46,708 

NH/PI: 11,700 

Counts of distinct perpetrators by race in the 2004 NCANDS data file:

AI/AN: 6,294 

NH/PI: 2,091 

The 2003 data set consists of 1,216,626 total records (report-child pairs) from 22 

states and DC. 

Counts of distinct children by race in the 2003 NCANDS data file:

AI/AN: 22,228 

NH/PI: 3,400 

Counts of distinct perpetrators by race in the 2003 NCANDS data file:

AI/AN: 3,740 

NH/PI: 653 

Geographic 

Scope: 

Forty-four states and DC voluntarily submitted data to the NCANDS Child File 

for 2004. States that did not submit data for 2004 are Alaska, Alabama, Georgia, 

North Dakota, Oregon, and Wisconsin. 

In 2003, only twenty-two states and DC agreed to archive their NCANDS Child 

File data with the National Data Archive on Child Abuse and Neglect 

(NDACAN). States that submitted data in 2003 are Arkansas, Delaware, Florida, 

Kansas, Kentucky, Louisiana, Massachusetts, Maine, Minnesota, Missouri, 

Montana, North Carolina, Nebraska, Ohio, Oklahoma, Pennsylvania, Rhode 

Island, Texas, Utah, Vermont, Washington, and Wyoming. 

In addition to the state indicator, the child data file also includes the Federal FIPS 

Code for the county where the report was made for counties with more than 1,000 

records in the data file. For all records, the child’s county of residence is removed 

from the data file because of confidentiality concerns. 

Date or 

Frequency: 

The most recent available data are for Federal Fiscal Year 2004. NCANDS data 

have been collected annually since 1990. For 1990 through 2002, annual data sets 

are for calendar years. Beginning with the 2003 data set, the collection period is 

Federal Fiscal Year. 

Data Collection 

Methodology: 

Reports of child maltreatment are received by state agencies that administer social 

services. A single report may contain information about multiple children, 

multiple abuse types (e.g., physical, sexual, neglect), and multiple perpetrators. 

The agency investigates the report and a decision is made regarding each 

5-105 
National Child Abuse and Neglect Data System (NCANDS) 

(continued) 

report/child/instance. If the abuse is corroborated by evidence, the 

report/child/instance is coded as "substantiated" (states vary as to what word they 

use for this concept). If there is not sufficient corroboration, the instance is not 

coded as substantiated. Both substantiated and unsubstantiated cases are included 

in NCANDS. For unsubstantiated cases, no information is collected about the 

perpetrator. For substantiated cases, the gender, race, relationship to child, and 

other information is collected about the perpetrator or perpetrators. 

State participation in the detailed case data collection consists of mapping each 

requested data element into the Child File record layout, extracting the state data 

into the Child File record layout, and submitting the case level data to NCANDS. 

Participation: Optional without incentives. 

Sampling 

Methodology: 

The NCANDS Child File represents a census of all child protective services 

investigations or assessments conducted in the states that participated in the 

NCANDS. 

Authorization: The Child Abuse Prevention and Treatment Act (CAPTA) was amended in 1988 

to direct the Secretary of the Department of Health and Human Services (DHHS) 

to establish a national data collection and analysis program that would make 

available state child abuse and neglect reporting information (42 U.S.C. 5101 et 

seq.; 42 U.S.C. 5116 et seq., Public Law 100-294 passed April 25, 1988). DHHS 

responded by establishing NCANDS as a voluntary, national reporting system. 

Strengths: Data sets contain a large number of AI/AN/NA respondents. Data are collected on 

a key policy issue, child welfare. There are multiple years of data available. 

Limitations: As states are not required to submit data to NCANDS, some states do not 

participate. Coverage has improved from 2003 (22 states and DC submitting) to 

2004 (44 states and DC submitting). 

When conducting analyses with NCANDS data, it is important to keep in mind 

that state-to-state variation in child maltreatment laws and information systems 

may affect the interpretation of the data. Users are encouraged to refer to the state 

mapping documents included on the data CD for information about how the 

state’s system codes its data. 

Access 

Requirements 

and Use 

Restrictions: 

Restricted usage files of state report-level data are available for researchers from 

the National Data Archive on Child Abuse and Neglect at 

www.ndacan.cornell.edu. Researchers who would like to use the data must fulfill 

eligibility criteria, submit an application for approval to the Archive, and enter 

into a legally-binding data license that outlines the requirements for appropriate 

use of the data. Only individuals holding a faculty appointment or research 

position at an institution of higher education, a research organization, or a 

government agency are eligible to obtain the Child File. There is no cost for 

access to these data. 

5-106 
National Child Abuse and Neglect Data System (NCANDS) 

(continued) 

Contact 

Information: 

National Data Archive on Child Abuse and Neglect 

Beebe Hall – FLDC 

Cornell University 

Ithaca, New York 14853-4401 

(607) 255-7799 

ndacan@cornell.edu 

www.ndacan.cornell.edu

5-107 
National Crime Victimization Survey (NCVS) 

Sponsor: U.S. Department of Justice (DoJ)/Bureau of Justice Statistics (BJS) 

Description: The National Crime Victimization Surveys (NCVS) series, previously called the 

National Crime Surveys (NCS), has been collecting data on personal and 

household victimization through an ongoing survey of a nationally representative 

sample of residential addresses since 1973. The four primary objectives of the 

effort include: 1) to develop detailed information about the victims and 

consequences of crime; 2) to estimate the number and types of crimes not 

reported to the police; 3) to provide uniform measures of selected types of 

crimes; and 4) to permit comparisons over time and geographic areas. Basic 

demographic information such as age, race, gender, and income is also collected 

to enable analysis of crime by various subpopulations. 

Relevant Policy 

Issues: 

Rates of Involvement with Justice System, Lifetime Probability of Being a 

Victim of a Violent Crime, Lifetime Probability of Being a Victim of a Nonviolent Crime, Domestic Violence Rates, Child Maltreatment Rates, Factors 

Contributing to Disparities in Involvement with Justice System and Outcomes. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individuals, Households, Crime Incidents 

Identification Respondents are allowed to select all race categories that apply from the 

of AI/AN/NA: following: 

• White 

• Black/African American 

• American Indian/Alaska Native (AI/AN) 

• Native Hawaiian/Other Pacific Islander (NH/PI) 

• Asian 

• Other – Specify 

AI/AN/NA 

Population in 

Data Set: 

In the combined incident-level file for 1992-2004, there are 162,736 incidents of 

which 1,621 are incidents where the informant for the household in which there 

had been an incident is AI/AN (alone or as part of a multiple race designation). 

Native Hawaiians and Other Pacific Islanders cannot be distinguished from 

Asians in most of the concatenated incident-level file; however, beginning in 

2003, a new race categorization was adopted that allows NH/PI persons to be 

identified from that time forward. In this incident-level file, there are 71 

incidents where the informant was NH/PI (alone or as part of a multiple race 

designation). 

AI/AN/NA 

Subpopulations: 

It is possible to isolate individuals who identify themselves as American Indian 

or Alaska Native and indicate that they reside on Indian lands. (Question 12 asks 

“Are your living quarters located on an American Indian reservation or on Indian 

lands?” ) 

5-108 
National Crime Victimization Survey (NCVS) 

(continued) 

Geographic 

Scope: 

The geographic scope of the study is national. Geographic identifiers include 

urban or rural; region; and central city of a Metropolitan Statistical Area (MSA), 

MSA but not in central city, or not MSA. Geographic analysis is possible for all 

of these. Also, as noted previously, it is also possible to identify individuals 

reporting that their residence is on Indian lands. 

Date or 

Frequency: 

The NCVS is a semiannual study with data available beginning 1973. 

Respondents are interviewed every 6 months for a total of seven interviews over 

a 3-year period. After the seventh interview the household leaves the panel and a 

new household is rotated in to the sample. 

Data Collection 

Methodology: 

The first and fifth interviews are face-to-face; the rest are by telephone. 

Participation: Optional, without incentives 

Response Rate: Survey documentation states that the NCS and NCVS have consistently obtained 

a response rate of about 95 percent. 

Sampling 

Methodology: 

The NCVS sample consists of approximately 50,000 sample housing units 

selected with a stratified, multi-stage cluster design. The first stage consists of 

selecting a sample of Enumeration Districts (ED's) from designated Primary 

Sampling Units (counties, groups of counties, or large metropolitan areas). (ED's 

are established for each decennial Census and are geographic areas ranging in 

size from a city block to several hundred square miles, and usually encompassing 

a population of 750 to 1,500 persons.) In the second stage, each selected ED is 

divided into segments (clusters of about four housing units each), and a sample 

of segments is selected. The sample of housing units is divided into six rotation 

groups, and each group is interviewed every six months for a period of threeand-a-half years. 

Analysis: Use of standard statistical tests with these data would not be accurate because 

these tests assume independence among observations and a simple, random 

sample design. The NCVS uses a complex, clustered sampling design in which 

observations are not independent. Survey documentation presents instructions for 

two methods to calculate variances for NCVS data that avoid these problems, 

computing generalized variances and using direct variance calculation methods 

designed for complex survey design. 

Strengths: Data are collected on key policy issues, primarily justice system issues. There are 

multiple years of data available. Documention is strong and there is a userfriendly on-line analytical tool for the incident-level data. 

Limitations: The full NVS data set is hierarchical. It is not a flat individual-level data set as 

are most survey data sources. The file is organized into a hierarchical format 

which corresponds to variations in household composition and in the occurrence 

of incidents of victimization. Hierarchical data sets have varying record lengths, 

5-109 
National Crime Victimization Survey (NCVS) 

(continued) 

and each record is stored sequentially in the data file. Hierarchical storage is a 

benefit as it greatly reduces the size and space needed to store and process the 

data; however, stronger programming skills may be required to correctly analyze 

a file of this type compared to the traditional file. 

Other: Data are available on-line in aggregated form. Data for 1992-2004 are available 

for downloading. Data for 1992-2003 can be analyzed on-line (incident-level 

file) or downloaded. 

A series of changes has occurred recently with modifications to the questions, 

placing more emphasis on “hot topics” of crime, which may provide challenges 

for multi-year comparisons. Some topics included in 2004 were identity theft, 

credit card theft and multiple crime situations involving personal information. 

Access 

Requirements 

and Use 

Restrictions: 

The data are available to the public at no cost. 

Contact 

Information: 

For data and documentation:

National Archive of Criminal Justice Data 

ICPSR 

Institute for Social Research 

P.O. Box 1248 

Ann Arbor, MI 48106 

USA 

(800) 999-0960 

(734) 998-9825 

Data can be accessed at 

http://webapp.icpsr.umich.edu/cocoon/NACJD-STUDY/04276.xml. 

General information:

Bureau of Justice Statistics 

810 Seventh Street, NW 

Washington, DC 20531 

USA 

(202) 307-0765 

askbjs@usdoj.gov

Reports of 

Interest: 

The National Archive of Criminal Justice Data provides lists of publications 

from the NVS data. A list of publications for the 1992-2003 data can be found at 

http://www.icpsr.umich.edu/cgibin/CITATIONS/search?study=3995&method=study&path=NACJD. 

A list of publications for the 1992-2004 data can be found at 

http://www.icpsr.umich.edu/cgi/CITATIONS/search?study=4276&method=stud

y&path=NACJD. 

5-110 
National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/National Institutes of 

Health/National Institute on Alcohol Abuse and Alcoholism (NIAAA) 

Description: The National Epidemiologic Survey on Alcohol and Related Conditions 

(NESARC) was designed to determine the magnitude of alcohol use disorders and 

their associated disabilities in the general population and in subgroups of the 

population and to examine changes over time in alcohol use disorders and their 

associated disabilities. It is a longitudinal survey with its first wave of interviews 

fielded in 2001-2002 and second wave in 2004-2005. The NESARC is a 

representative sample of the non-institutionalized U.S. population 18 years of age 

and older. 

The NESARC collects data on background, alcohol consumption, alcohol abuse 

and dependence, alcohol treatment utilization, family history of alcoholism, 

tobacco use and dependence, medicine use, drug abuse and dependence, drug 

treatment utilization, family history of drug abuse, major depression, family 

history of major depression, dysthymia, mania and hypomania, panic disorder and 

agoraphobia, social phobia, specific phobia, anxiety disorder, personality 

disorders, antisocial personality disorder, family history of antisocial personality 

disorder, pathological gambling, medical conditions, and victimization. Public use 

data are currently available for the first wave of data collection. 

Relevant Policy 

Issues: 

Key Health Disparities, Factors Contributing to Measured Health Disparities. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

The interviewer presents a flashcard with racial categories listed and says, "Please 

select 1 or more categories to describe your race." 

The respondent chooses one or more from the following categories: 

• American Indian or Alaska Native (AI/AN) 

• Asian 

• Black or African American 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• White 

AI/AN/NA 

Population in 

Data Set: 

In the first wave of data collection (2001-2002), there were 43,093 respondents. 

The unweighted frequencies for selected racial categories were as follows: 

AI/AN: 1,304 

NH/PI: 363 

Note that respondents could select more than one category. 

5-111 
National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) 

(continued) 

For analytical purposes, the Census Bureau imputed race for individuals for 

whom that information was missing. The Bureau also used an algorithm to code a 

single race category for those individuals who identified themselves as multiracial. These computations and imputations resulted in a constructed variable 

where the unweighted count of American Indians or Alaska Natives (not 

Hispanic) was 701. Native Hawaiians or other Pacific Islanders are combined 

with Asians as one category of the constructed variable. 

Geographic 

Scope: 

The geographic scope of the survey is national. Geographic indicators are 

available for Census region, Census division, central city vs. not central city, and 

state. These geographic factors can be incorporated as variables in analyses. 

However, valid analyses cannot be conducted within these geographic areas 

because the NESARC was designed to be a representative sample of the U.S. 

Date or 

Frequency: 

This is a longitudinal study. The first wave of data collection occurred in 2001-

2002 and the second wave occurred in 2004-2005. 

Data Collection 

Methodology: 

Data are collected through computer-assisted personal interviews (CAPI). 

Participation: Optional, with incentives. Participants who completed the survey were given $80. 

Response Rate: The overall survey response rate for the NESARC was 81 percent. 

Sampling 

Methodology: 

The NESARC used a three-stage sampling design. The sampling frame for the 

NESARC sample of housing units is the Census 2000/2001 Supplementary 

Survey (C2SS), a national survey of 78,300 households per month. A group 

quarters frame was also used. Stage 1 was primary sampling unit (PSU) selection 

using the C2SS PSUs. Stage 2 was household selection from the sampled PSUs. 

In Stage 3, one sample person was selected from each household. 

Strengths: Data are collected on key policy issues including alcohol and substance use as 

well as health. When available, the longitudinal data will provide significant 

opportunities for examining patterns of alcohol use and disability by individuals. 

Limitations: Change in sample size for the AI/AN/NA population related to attrition from the 

study across the two waves of data collection is unknown at this time. 

Other: The second wave of data collected in 2004 and 2005 are expected to be ready for 

use in the summer of 2007. 

Access 

Requirements 

and Use 

Restrictions: 

First wave data are available to public at no cost. 

5-112 
National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) 

(continued) 

Contact 

Information: 

Public use data file and documentation are available at http://niaaa.census.gov/. 

Ms. Nekisha Lakins 

CSR, Incorporated 

Phone: (703) 741-7157 

Fax: (703) 312-5230 

Email: nlakins@csrincorporated.com 

Reports of 

Interest: 

The link below provides a list of more than 30 publications using the NESARC 

data: http://niaaa.census.gov/publications.html 

5-113 
National Health Interview Survey (NHIS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC)/National Center for Health Statistics (NCHS) 

Description: The National Health Interview Survey is a household survey that serves as the 

primary source of information on the health of the U.S., non-institutionalized, 

civilian population. Though it has undergone various changes since its inception 

in 1957, the NHIS has remained largely unchanged since 1997 and comprises the 

Basic Core Questionnaire (Family, Sample Adult and Sample Child surveys) as 

well as topic-focused supplements. The Basic Core collects information on 

household composition and sociodemographic characteristics, tracking 

information, information for matches to administrative data bases, and basic 

indicators of health status, activity limitations, injuries, health insurance coverage, 

and access to and utilization of health care services. Supplement topics are often 

selected to coincide with monitoring areas of public health interest and to help in 

the monitoring of national health goals (e.g., Healthy People 2010). Examples of 

supplement topics include cancer, diabetes, mental health and complementary and 

alternative medicine. 

Relevant Policy 

Issues: 

Measurement of Health Status, Disease-specific Measurements, Factors 

Contributing to Measured Health Disparities, Measures of Well-being for 

Families/Households, Factors Contributing to Well-being Disparities of Families, 

Measures of Well-being for Children, Measures of Well-being for Elders, and 

Factors Contributing to Well-being Disparities of Elders. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual, Family, and Household 

Identification 

of AI/AN/NA: 

The race categories available in the public use data set are: 

• White only 

• Black/African American only 

• American Indian/Alaska Native only (AI/AN) 

• Asian only 

• Race group not releasable 

• Multiple race 

AI/AN/NA 

Population in 

Data Set: 

AI/AN only: 670 

Geographic 

Scope: 

The geographic scope of the NHIS is national. Geographic analysis also is 

possible at the regional level. 

5-114 
National Health Interview Survey (NHIS) 

(continued) 

Date or 

Frequency: 

These data have been collected since 1969, though only data from 1982 through 

the present are currently available for download from the Internet. The most 

recent, complete file available is from 2005. 

Data Collection 

Methodology: 

NHIS is currently conducted via a personal household interview with a 

knowledgeable adult household representative using computer-assisted personal 

interviewing (CAPI) technology. 

Participation: Optional, without incentives 

Response Rate: For 2003, the overall response rate was 89.2 percent for a sample of 35,921 

households (92,148 individuals). The Sample Adult subsample had a response 

rate of 74.2 percent, while the Sample Child subsample had a response rate of 

81.1 percent. 

Sampling 

Methodology: 

NHIS utilizes a stratified, multi-stage probability design to reflect the overall 

noninstitutionalized U.S. population. The sample is drawn from a geographic 

frame designated using the most recent decennial Census. Names and addresses 

are derived in a separate listing activities conducted specifically for NHIS. From 

1995 through 2005, African American and Hispanic households were 

oversampled in order to facilitate better estimates for these populations. 

Beginning in 2006, households with at least one Asian member are also 

oversampled. 

Analysis: Equations calculating standard errors can be found in the Survey Description 

document on page: 

www.cdc.gov/nchs/about/major/nhis/quest_data_related_1997_forward.htm. 

Strengths: Data set contains a large number of AI/AN/NA respondents. Data are collected on 

key policy issues, including health and child welfare. There are multiple years of 

data available. Certain years can be linked to the Medical Expenditure Panel 

Survey (MEPS) to produce a very rich database that includes medical care 

utilization data. 

Limitations: The NHIS data conform to the revised OMB guidelines, which mean that data for 

the Asian population is collected separately from that of the Native Hawaiian and 

other Pacific Islander (NH/PI) population. NCHS data confidentiality standards 

do not permit the release the population counts for the NH/PI population 

separately because of the small size of this population. This group is combined 

with other small population groups into an aggregated group labeled "Race group 

not releasable" on the public use data file. Researchers wishing to do analysis on 

the NH/PI population can submit a proposal to the NCHS Research Data Center; 

however there is a charge which depends on the amount of time and help needed. 

Information on this process can be found at: 

http://www.cdc.gov/nchs/r&d/rdc.htm 

5-115 
National Health Interview Survey (NHIS) 

(continued) 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to the public at no cost. 

Contact 

Information: 

National Center for Health Statistics, Hyattsville, MD 20782 

(301) 458-4000 or (866) 441-NCHS 

http://www.cdc.gov/nchs/nhis.htm 

5-116 
National Hospital Ambulatory Medical Care Survey (NHAMCS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC)/National Center for Health Statistics (NCHS) 

Description: The National Hospital Ambulatory Medical Care Survey (NHAMCS) collects 

data on the utilization and provision of ambulatory care services in the emergency 

and outpatient departments of noninstitutional general and short-stay hospitals in 

the United States. Hospital staff complete a one-page questionnaire for each 

patient visit sampled during a 4-week reporting period. Collected data include 

hospital characteristics, patient demographic characteristics (age, sex, race, 

ethnicity), and visit characteristics (patients' symptoms, complaints or other 

reasons for the visit, physicians' diagnoses, diagnostic and therapeutic services 

ordered or provided at the visit including medications, expected sources of 

payment, visit disposition). Excluded from the sample are federal, military, and 

Veterans Administration hospitals. Sample data must be weighted to produce 

national estimates. 

Relevant Policy 

Issues: 

Measurement of Health Status, Key Health Disparities, and Factors Contributing 

to Measured Health Disparities. 

Data Type(s): Survey 

Unit of 

Analysis: 

Patient visit 

Identification 

of AI/AN/NA: 

Hospital staff are asked to report one or more races (up to 5) for each sampled 

visit. The public use data files include five single race categories and an 

aggregated category for visits with more than one race checked. 

• White 

• Black/African American 

• Asian 

• Native Hawaiian/Other Pacific Islander (NH/PI) 

• American Indian/Alaska Native (AI/AN) 

• More than one race reported 

AI/AN/NA 

Population in 

Data Set: 

Total number of records in 2004 Emergency Department data set: 36,589 

Total number of records in 2004 Outpatient Department data set: 31,783 

AI/AN: 209 in 2004 Emergency Department data set; 149 in 2004 Outpatient 

Department data set 

• NH/PI: 213 in 2004 Emergency Department data set; 305 in 2004 

Outpatient Department data set 

Geographic 

Scope: 

The geographic scope of the study is national. Analysis is possible for the 

following regions: Northeast, Midwest, South, West. 

Date or 

Frequency: 

Data are available annually from 1992. 

5-117 
National Hospital Ambulatory Medical Care Survey (NHAMCS) 

(continued) 

Aggregation: Each year of data has, on average, 120-170 outpatient department visits and 160-

240 emergency department visits by persons reported as AI/AN only. In addition, 

each year has, on average, 140-300 outpatient department visits and 200-240 

emergency department visits by persons reported as NH/PI only. According to the 

NCHS, researchers frequently combine years of data for analysis in order to 

achieve reliable estimates. Researchers considering aggregation should take 

special note of changes in sample design variables across the years, as these will 

affect variance estimation. They should also be particularly aware of any possible 

clustering by race that may affect sample estimates. The format and content of the 

survey questionnaires has also changed across the years. Data must be weighted 

to produce national estimates, and researchers may wish to seek guidance about 

the use of weights with aggregated files. 

Data Collection 

Methodology: 

The U.S. Census Bureau acts as the data collection agent for the NHAMCS. 

Hospital staff are trained by Census field representatives to sample patients and to 

complete the 1-page reporting form for each sampled visit. 

Participation: Optional, without incentives. 

Response Rate: In the 2004 survey, the response rate for participating hospitals was 91 percent. 

Sampling 

Methodology: 

NHAMCS utilizes a multistage probability sample design where geographic 

primary sampling units (PSUs) are selected in the first stage; a fixed panel of 600 

hospitals, developed from the SMG Hospital Market Database in 1991 and 

updated using data products from Verispan, LLC, comprises the second stage; the 

selection of outpatient department clinics and emergency service areas (ESAs) 

from the outpatient and emergency departments of the sampled hospitals 

constitutes the third stage; and the selection of patient visits within sampled 

clinics and ESAs during a randomly selected 4-week reporting period is the fourth 

stage. 

Analysis: The weighting procedure produces essentially unbiased national estimates and has 

three components: 1) inflation by reciprocals of the probabilities of selection, 2) 

adjustment for nonresponse, and 3) a population weighting ratio adjustment. Two 

data sets are produced – one for outpatient department visits and one for 

emergency department visits. Patient visit weights are provided on each file to 

produce accurate national estimates. 

Strengths: Data are collected on key policy issues pertaining to health. There are multiple 

years of data available. 

Limitations: In the 2004 survey, the overall item nonresponse rate is low; however it is 20.9 

percent for ethnicity and 19.2 percent for race. On the outpatient department file, 

race and ethnicity were missing on 11.9 percent and 11.8 percent of records 

respectively. On the emergency department file, race and ethnicity were missing 

for 10.6 percent and 15.1 percent of records respectively. Race and ethnicity are 

imputed in both files by randomly assigning a value from another sampled visit 

5-118 
National Hospital Ambulatory Medical Care Survey (NHAMCS) 

(continued) 

with similar characteristics. There are also relatively few visits by patients 

categorized as AI/AN or NH/PI. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to the public at no cost. Restricted files which contain 

additional variables and non-masked data can be accessed by applying to the 

NCHS Research Data Center and paying a fee. 

Contact 

Information: 

Main website for NHAMCS 

http://www.cdc.gov/nchs/nhamcs.htm 

Data Download: 

http://www.cdc.gov/nchs/about/major/ahcd/ahcd1.htm#Micro-data 

Contact Information: 

National Center for Health Statistics 

Ambulatory Care Statistics Branch 

3311 Toledo Road, Rm. 3409 

Hyattsville, MD 20782 

(301) 458-4600 

5-119 
National Household Education Surveys Program (NHES) 

Sponsor: U.S. Department of Education (DoE)/National Center for Education Statistics 

(NCES) 

Description: The National Household Education Surveys Program (NHES) provides 

descriptive data on the educational activities of the U.S. population and offers 

researchers, educators, and policymakers a variety of statistics on the condition of 

education in the United States. The NHES surveys cover learning at all ages, from 

early childhood to school age to adulthood. The NHES uses a repeating crosssectional design that allows for the study of trends related to educationally 

important topics. 

While there are many surveys included in this system, this profile includes only 

the surveys that have more than 100 AI/AN/NA individuals across multiple years, 

and that were administered in 1995 or later (note that the first NHES survey was 

fielded in 1991). Surveys that are included in this profile are the Parent and 

Family Involvement in Education Survey (PFI-NHES), the Early Childhood 

Program Participation Survey (ECPP-NHES), the Adult Education Survey (AENHES) (also called the Adult Education and Lifelong Learning Survey (AELLNHES)), the Before- and After-School Programs and Activities Survey (ASPANHES), and the 1999 Parent Survey (Parent-NHES, which includes some items 

from the PFI-NHES, ECPP-NHES, and ASPA-NHES). 

Relevant Policy 

Issues: 

Educational Attainment, Educational Opportunities, and Factors Contributing to 

Educational Disparities. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Race is self-reported on all the surveys. The questions asking about race were 

changed between the 2003 and 2005 collections in order to meet new OMB 

requirements for collecting this information. Specifically, the questions were 

changed to allow respondents to be classified as more than one specific race (e.g., 

as both White and Black). In previous years (i.e., 1995-2003), respondents were 

classified as either belonging to only one racial group or as being multiracial 

without those specific races being identified. For example, the 2005 Adult 

Education Survey included the following race question: 

Which of the following races do you consider yourself to be? You may name 

more than one. 

• White 

• Black 

• American Indian or Alaska Native (AI/AN) 

• Asian 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• Other specify 

5-120 
National Household Education Surveys Program (NHES) 

(continued) 

In 2001, the AE-NHES race questions was: 

Are you... 

• White 

• Black 

• American Indian or Alaska Native 

• Asian or Pacific Islander 

• Some other race? (Interviewers are instructed to use this category if no race 

is selected or if more than one race is selected.) 

The race question in all surveys prior to 2005 was structured the same way as this 

question from the 2001 AE-NHES Survey. Note that also prior to 2005, the 

categories "Asian" and "Native Hawaiian or other Pacific Islander" were 

combined into a single category: "Asian or Other Pacific Islander." 

For all NHES surveys, information about Hispanic ethnicity is collected in a 

separate question. 

AI/AN/NA 

Population in 

Data Set: 

PFI-NHES

1996: Out of 20,792 records, 231 are AI/AN 

2003: Out of 12,426 records, 108 are AI/AN 

ECPP-NHES

1995: Out of 14,064 records, 113 are AI/AN 

2001: Out of 6,749 records, 51 are AI/AN 

2005: Out of 7,209 records, 233 are AI/AN and 66 were NH/PI 

AE-NHES and AELL-NHES

1995: Out of 19,722 records, 160 are AI/AN 

1999: Out of 6,697 records, 51 are AI/AN 

2001: Out of 10,873 records, 84 are AI/AN 

2005: Out of 8,904 records, 355 are AI/AN and 51 were NH/PI 

ASPA-NHES

2001: Out of 9,583 records, 79 were AI/AN 

2005: Out of 11,684 records, 374 were AI/AN and 79 were NH/PI 

Parent-NHES: 

1999: Out of 24,600 records, 193 were AI/AN 

Geographic 

Scope: 

The geographic scope of NHES is national. While zip code was collected on the 

surveys, it is not included in the public use data files. The files do contain the 

variable ZIPURBAN, which identifies records as being inside or outside an urban 

region. Additionally, records contain a Census region with the four values: 

Northeast, South, Midwest, West. 

5-121 
National Household Education Surveys Program (NHES) 

(continued) 

Date or 

Frequency: 

The PFI-NHES survey was conducted in 1996 and 2003. The ECPP-NHES 

survey was conducted in 1995, 2001, and 2005. The AE-NHES survey was 

conducted in 1995, 1999, 2001 and 2005. In 2001, the AE-NHES survey was 

called the Adult Education and Lifelong Learning Survey (AELL-NHES). The 

ASPA-NHES survey was conducted in 2001 and 2005. The Parent-NHES was 

conducted in 1999. For all years of administration, the NHES data collection 

period runs from January to April. 

The NHES will continue to be conducted regularly in the future, covering the 

same topics investigated in earlier collections. In 2007, surveys will cover Adult 

Education for Work-Related Reasons, School Readiness, and Parent and Family 

Involvement in Education. 

Aggregation: It is possible to combine multiple years of data for the NHES surveys, but 

researchers should be aware that there is a sizable time difference between the 

administrations of some of the surveys (for example, the PFI-NHES survey was 

conducted in 1996 and 2003). In addition, in 1995, the NHES surveys switched 

the way in which they selected their sample (from using a modified MitofskyWaksberg method to a list-assisted method). For this reason, it is recommended 

that the samples from NHES surveys conducted prior to 1995 not be combined 

with samples later than 1995. As the NHES is weighted data, new weights would 

need to be developed in order to combine survey data across multiple years. 

 

Researchers also should review any survey questions of interest before combining 

them to ensure the question text and response categories are comparable. Change 

in the race question text between 2003 and 2005 may affect the ability to 

aggregate 2005 data with data from previous years. 

If researchers choose to combine data sets across multiple years, the end results 

would be: 

PFI-NHES surveys from 1996 and 2003: Total AI/AN : 339 

ECPP-NHES surveys from 1995, 2001 and 2005: Total AI/AN : 397 

AE-NHES surveys from 1995, 1999, 2001 and 2005: Total AI/AN: 650 

ASPA-NHES surveys from 2001 and 2005: Total AI/AN: 453 

Data Collection 

Methodology: 

NHES is conducted as a random digit dial (RDD) telephone survey using 

computer-assisted telephone interviewing (CATI). Each household contact begins 

with a screener to obtain information used to sample adults and children for 

extended interviews (the topical surveys). Since 1996, in order to introduce the 

survey, advance letters have been sent out to all sample households where an 

address was obtained through a commercial address matching service. 

Participation: Optional, with incentives 

5-122 
National Household Education Surveys Program (NHES) 

(continued) 

Response Rate: Response rates:

1996 PFI-NHES: Weighted response rate of 62.5% 

2003 PFI-NHES: Weighted response rate of 53.8% 

1995 ECPP-NHES: Weighted response rate of 66.3% 

2001 ECPP-NHES: Weighted response rate of 59.9% 

2005 ECPP-NHES: Weighted response rate of 56.4% 

1995 AE-NHES: Weighted response rate of 58.6% 

1999 AE-NHES: Weighted response rate of 62.3% 

2001 AELL-NHES: Weighted response rate of 53.4% 

2005 AE-NHES: Weighted response rate of 47.6% 

2001 ASPA-NHES: Weighted response rate of 59.7% 

2005 ASPA-NHES: Weighted response rate of 56.3% 

1999 Parent-NHES: Weighted response rate of 66.7% 

The NHES data user manuals provide weighted response rates as these rates give 

a better description of the success of the survey with respect to the population of 

interest. The response rate indicates the percentage of possible interviews that 

have been completed, taking all sampling stages into account. The weighted 

response rate is similar to the unweighted response rate unless the probabilities of 

selection vary considerably. 

Sampling 

Methodology: 

Beginning in 1995, the NHES surveys began using a list-assisted method to select 

the random digit dial (RDD) sample. With the list-assisted method, an equal 

probability random sample of telephone numbers is selected from all telephone 

numbers that are in 100-banks (numbers in a 100-bank have the same first 8 digits 

of the 10-digit telephone number) in which there is at least one residential 

telephone number listed in the white pages directory (the listed stratum). Both 

listed and unlisted telephone numbers are included in the listed stratum. 

Telephone numbers in 100-banks with no listed telephone numbers (the zerolisted stratum) were not sampled. 

Additionally, a within-household sampling scheme was developed to limit the 

number of persons sampled for extended interviews in each household in order to 

reduce respondent burden. 

Analysis: Design effects (deff): 

1996 PFI-NHES survey deff = 1.3 for the Full Sample 

2003 PFI-NHES survey deffs = 1.3 for the Full Sample, and 1.4 for the 

race/ethnicity subgroups 

1995 ECPP-NHES survey deff = 1.2 for the Full Sample 

2001 ECPP-NHES survey deff = 1.2 for the Full Sample 

2005 ECPP-NHES survey = 1.4 for the Full Sample, 1.3 for Preschoolers 

5-123 
National Household Education Surveys Program (NHES) 

(continued) 

1995 AE-NHES survey deff = 1.3 for the Full Sample 

1999 AE-NHES survey deff = 1.3 for the Full Sample, 1.4 for Participants 

2001 AELL-NHES survey deff = 1.3 for the Full Sample 

2005 AE-NHES survey deff= 1.6 for the Full Sample 

2001 ASPA-NHES survey deff = 1.3 for the Full Sample 

2005 ASPA-NHES survey deff = 1.3 for the Full Sample 

1999 Parent-NHES survey deff = 1.3 for the Full Sample 

Strengths: Multiple years of data are available. Documentation is detailed and 

comprehensive. 

Limitations: Most of these studies contain a relatively small number of AI/AN/NA 

respondents. While it may be possible to combine the samples from multiple 

years of the surveys, this is a complicated procedure. One of the biggest issues 

related to aggregation is the variation in the race questions over the years. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available online at no cost. 

Contact 

Information: 

The NHES data can be downloaded via the Internet at: 

http://nces.ed.gov/nhes/dataproducts.asp 

The NHES staff can be contacted by sending an email to: nhes@ed.gov. 

5-124 
National Household Travel Survey (NHTS) 

Sponsor: U.S. Department of Transportation/Federal Highway Administration, Bureau of 

Transportation Statistics, and National Highway Traffic Safety Administration 

Description: The 2001 National Household Travel Survey (NHTS) was developed to gather 

comprehensive data on travel and transportation patterns in the United States. 

Data were collected on daily trips taken in a 24-hour period, as well as long 

distance trips collected for the 4-week period prior to the travel day. Data 

collected for the daily trips include the purpose of the trip, the means of 

transportation used, how long the trip took, when the trip took place, and 

characteristics of private vehicle ownership. The survey measured personal travel, 

which excluded travel made as part of the respondent's job (i.e., business trips). 

The NHTS data are used primarily for gaining a better understanding of travel 

behavior. For example, NHTS data are used to quantify travel behavior, analyze 

changes in travel characteristics over time, relate travel behavior to the 

demographics of the traveler, and study the relationship of demographics and 

travel over time. Additionally, people in fields outside of transportation use the 

NHTS data. For example, social service agencies may use the data to learn more 

about how low-income households currently meet their travel needs. 

In addition to the national sample, planning organizations could purchase add-on 

surveys in their state or specific county so that reliable estimates could be made 

for that geographic area. The nine add-on samples include the following areas: 

• State of Wisconsin 

• State of New York 

• State of Texas 

• Hawaii (state-wide, excluding Oahu) 

• Oahu, Hawaii 

• Baltimore, Maryland 

• Des Moines, Iowa 

• Lancaster, Pennsylvania 

• Edmonson, Carter, Pulaski, and Scott Counties, Kentucky 

Relevant Policy 

Issues: 

Transportation Availability. 

Data Type(s): Survey 

Unit of 

Analysis: 

The NHTS data are organized into five different data files and contain data on the 

26,038 households from the national sample, and the 43,779 completed add-on 

households. There were over 160,000 person interviews from the national sample 

and add-on households, with about 100,000 of them from the add-on sample. 

Records from each data file can be linked to one another using the Household ID 

number. Descriptions for each data file are as follows: 

5-125 
National Household Travel Survey (NHTS) 

(continued) 

Household file: Contains one record per sampled household. Variables include 

the number of vehicles, type of residence, household income, and information on 

the primary household respondent. 

Person file: Contains one record per person who completed a person interview. 

Variables include information on traveling to work; the number of miles driven; 

customer satisfaction with transportation arrangements; and person demographics 

such as age, race, driver status, and medical condition. 

Vehicle File: Contains one record per each vehicle owned, leased, or available for 

regular use by the household members in each sample household. Variables 

include type of vehicle, vehicle ownership, mileage, and housing characteristics. 

Travel day trip file: Contains one record per each trip taken by an interviewed 

person in a sampled household, for the household’s randomly- assigned travel 

day. 

Long trip file: Contains one record per each trip of 50 miles or more away from 

home. The long distance trip data were collected in the national sample and NY 

and WI add-on samples only. 

For the NHTS study, household members include all people who think of the 

sampled household as their primary place of residence. It includes persons who 

usually stay in the household but are temporarily away on business, vacation, or 

in a hospital. It does not include people just visiting, such as college students who 

normally live away at school. 

Identification 

of AI/AN/NA: 

Race is self-reported, using the following survey item: 

I’m going to read a list of races. Please tell me which best describes your race. 

Are you... 

(Interviewers are instructed to code all that apply.) 

• White 

• African American, Black 

• Asian 

• American Indian, Alaskan Native (AI/AN) 

• Native Hawaiian, or other Pacific Islander (NH/PI) 

The following categories are not asked but are coded in the data files: 

• Multiracial 

• Hispanic/Mexican 

• Other 

• Refused 

• Don't Know 

5-126 
National Household Travel Survey (NHTS) 

(continued) 

AI/AN/NA 

Population in 

Data Set: 

2001 NHTS Household File

Total number of records: 69,817 households 

AI/AN primary household respondent: 401 

NH/PI primary household respondent: 370 

White/AI primary household respondent: 547 

AI/Hispanic primary household respondent: 44 

2001 NHTS Person File

Total number of records: 160,758 completed interviews 

AI/AN person in household: 882 

NH/PI person in household: 1,027 

White/AI person in household: 1,275 

AI/Hispanic person in household: 115 

2001 NHTS Vehicle File 

Total number of vehicles: 139,382 

AI/AN primary driver: 697 

NH/PI primary driver: 720 

White/AI primary driver: 1,189 

AI/Hispanic primary driver: 62 

2001 NHTS Day Trip File

Total number of day trips: 642,292 

AI/AN traveler: 3,383 

NH/PI traveler: 3,794 

White/AI traveler: 4,834 

AI/Hispanic traveler: 413 

2001 NHTS Long Trip File

Total number of long trips: 45,165 

AI/AN traveler: 277 

NH/PI traveler: 127 

White/AI traveler: 609 

AI/Hispanid traveler: 24 

Geographic 

Scope: 

The geographic scope of the study is national. Geographic indicators included are 

state, Census division, Census region, and Metropolitan Statistical Area (MSA) or 

Consolidated Metropolitan Statistical Area (CMSA). 

The NHTS data are supplemented with tract and block group data that are derived 

from the 2000 Census data. These data are used to describe the characteristics of 

the areas where the NHTS respondents live, including descriptors such as housing 

units per square mile, an urban/rural code, and population density per square mile. 

Date or 

Frequency: 

The NHTS interviews were conducted from April 2001 through May 2002. 

5-127 
National Household Travel Survey (NHTS) 

(continued) 

The NHTS resulted from integrating two national travel surveys: the Federal 

Highway Administration-sponsored Nationwide Personal Transportation Survey 

(NPTS) and the Bureau of Transportation Statistics-sponsored American Travel 

Survey (ATS). The NPTS collected detailed information on personal travel 

patterns using daily travel surveys, and was conducted in 1969, 1977, 1983, 1990 

and 1995. The ATS obtained information about long-distance travel of persons 

living in the United States and was collected in 1977 and 1995. 

Data Collection 

Methodology: 

Data collection consisted of three main phases. First, a household interview was 

conducted using computer assisted telephone interviewing (CATI) technology. 

The household interview was designed to collect information about the 

household, household members, and vehicles available to the household, and to 

elicit participation in the travel diary task. Next, travel diaries were mailed to the 

households. Each household in the sample was assigned a specific 24-hour 

“Travel Day” and kept diaries to record all travel by all household members for 

the assigned day. Respondents were also asked to document a 28-day “Travel 

Period” in order to collect longer-distance travel (over 50 miles from home) for 

each household member, including information on long commutes, airport access, 

and overnight stays. The assigned travel day was the last day of the assigned 

travel period. For a household to be included in any of the data sets, interviews 

had to be completed with at least half of the household adults. Finally, for the 

national sample and the New York and Wisconsin add-on samples, odometer 

readings from the household vehicles were collected from the respondent. 

Participation: Optional, with incentives. 

Response Rate: Overall weighted response rates were 41.2 percent for the national sample and 

38.9 percent for the full sample (includes national sample and 9 add-on samples). 

These response rates were an improvement from the previous 1995 survey 

response rates, and are considered high for travel surveys of this type. 

Sampling 

Methodology: 

NHTS collected travel data from the civilian, non-institutionalized population of 

the United States. Sampling was done by creating a random-digit dialing (RDD) 

list of telephone numbers. The sampling frame consisted of all telephone numbers 

in "100-banks" of numbers in which there was at least one listed residential 

number. (Each 100-bank contains the 100 telephone numbers with the same area 

code, exchange, and first two of the last four digits of the telephone number.) 

Analysis: The NHTS is a weighted data set. The weights reflect the selection probabilities 

and adjustments to account for nonresponse, undercoverage, and multiple 

telephones in a household. To obtain estimates that are minimally biased, weights 

must be used. Tabulations without weights may be significantly different than 

weighted estimates and may be subject to large bias. There are separate sets of 

weights for the full sample and for the national sample. For each set, there are 

household weights, person weights, travel day and travel period weights. The 

NHTS methodology report describes the process for applying the weights 

appropriately. 

5-128 
National Household Travel Survey (NHTS) 

(continued) 

Strengths: There are multiple years of data available. Documentation for the NHTS is 

readily available, very detailed, and extremely clear. 

Limitations: During the 2001 NHTS data collection period, the September 11th terrorist 

attacks occurred and severely disrupted travel in the United States for months. 

These attacks altered the amount and modes of travel that were being documented 

during this data collection. 

Although there are multiple years of data available for comparison purposes, 

aggregation of the data is not recommended. The sample design varied across 

administrations of the survey. Also, there were changes in national travel 

behavior across the years of data collection due to the state of the economy, the 

price of oil, and the terrorist attacks of September 11, 2001. Some significant 

variations can be expected in travel trend analysis, but the nature of these 

variations is such that aggregation of the data across multiple years is 

discouraged. 

As the data from the NHTS study is organized into four separate files, it may 

require strong programming skills to merge the files together if this is required for 

a specific research questions. 

Access 

Requirements 

and Use 

Restrictions: 

The public use data are available to the public at no cost. 

Contact 

Information: 

Federal Highway Administration/DOT 

The Office of Highway Policy Information (HPPI) 

Rm 3306 

Washington, DC 20590 

Phone: (202) 366-5021 

Fax: (202) 366-7742 

The NHTS public use database can be downloaded directly from: 

http://nhts.ornl.gov/2001/html_files/download_directory.shtml. 

5-129 
National Indian Education Study (NIES) 

Sponsor: U.S. Department of Education (ED)/National Center for Education Statistics 

(NCES)/Office of Indian Education (OIE) 

Description: The National Indian Education Study (NIES) focuses on both the academic 

achievement and educational experiences of fourth and eight grade students 

across the country. This activity is a collaborative effort among Indian tribes and 

organizations, the Bureau of Indian Affairs (BIA), and state and local education 

agencies. Part One of the NIES is an augmentation of the National Assessment of 

Educational Progress (NAEP) 2005 reading and mathematics assessment to 

increase the representation of Bureau of Indian Affairs schools in the NAEP data 

and allow for separate analyses. Part Two is a separate survey focusing on issues 

of Indian education, such as the role of Indian culture in education. At the time 

this catalog was being compiled, further information concerning Part Two of the 

NIES had not been released. The results of the NIES are intended to assist 

policymakers, educators, and community members in making informed decisions 

to improve education of all American Indian and Alaska Native students. 

Relevant Policy 

Issues: 

Educational Attainment. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Race/ethnicity is collected from two sources: school records and student selfreports. The primary source of race/ethnicity data is based on the race reported by 

the school. Schools that are sampled for the study are asked to provide lists of all 

students in grades 4 and 8, along with basic demographic information, including 

race/ethnicity. 

When school-recorded information is missing, student-reported data are used to 

determine race/ethnicity. All students who complete an assessment are asked 

some general student background questions, including questions about their 

race/ethnicity. Separate questions are asked about students’ Hispanic ethnic 

background and about students’ race. 

Based on the school records and self-reports, students are categorized into one of 

the following mutually exclusive categories: 

• White (non-Hispanic) 

• Black (non-Hispanic) 

• Hispanic 

• Asian/Pacific Islander 

• American Indian (including Alaska Native) (AI/AN) 

• Unclassified 

5-130 
National Indian Education Study (NIES) 

(continued) 

Unclassified students are those whose school-reported race was recorded as 

“other” or “unavailable” or was missing, or who self-reported more than one race 

category (i.e., “multi-racial”) or none. Hispanic students may be of any race. 

AI/AN/NA 

Population in 

Data Set: 

In the full 2005 NAEP reading assessment, a sample of about 166,000 fourthgrade and 159,000 eighth-grade students participated in the study. Of these, 

approximately 3,800 AI/AN students in grade 4 and approximately 3,400 AI/AN 

students in grade 8 are included in the NIES study. These numbers have been 

rounded to the nearest 100. 

In the full 2005 NAEP mathematics assessment, a sample of about 172,000 

fourth-grade and 162,000 eighth-grade students participated in the study. Of 

these, approximately 3,900 AI/AN students in grade 4 and approximately 3,500 

AI/AN students in grade 8 are included in the NIES study. These numbers have 

been rounded to the nearest 100. 

Geographic 

Scope: 

The geographic scope of the study is national. In addition to the national sample, 

data for American Indian/Alaska Native students can be analyzed for five regions 

of the country. These regions are Atlantic, North Central, South Central, 

Mountain, and Pacific. Furthermore, NIES focused on states with relatively high 

proportions of American Indian and Alaska Native students. The seven states 

included are Alaska, Arizona, Montana, New Mexico, North Dakota, Oklahoma, 

and South Dakota. Data concerning AI/AN students can be analyzed separately 

for each of these states, but comparisons between AI/AN students and students 

who are not AI/AN cannot be made at the state level. 

Date or 

Frequency: 

NIES data were collected for the first time in 2005. Future administrations of the 

study are planned. 

Data Collection 

Methodology: 

The reading and mathematics assessments are administered to participating 

students at the school location in paper and pencil format. 

Participation: Optional, without incentives 

Response Rate: The NIES student-weighted response rates are below: 

Grade 4 reading: 93% 

Grade 4 mathematics: 93% 

Grade 8 reading: 91% 

Grade 8 mathematics: 88% 

Sampling 

Methodology: 

The NIES sample was designed as an augmentation of the 2005 NAEP reading 

and mathematics assessment samples of AI/AN students in the fourth and eighth 

grades. In past NAEP samples, BIA schools were identified as part of the national 

sample, and the resulting number of participating schools was usually small, 

fewer than five per grade. In order to create the NIES study in 2005, BIA schools 

were sampled as a part of each state sample, at the same rate as public schools in 

a given state. Therefore a BIA student had the same probability of selection as a 

5-131 
National Indian Education Study (NIES) 

(continued) 

public school student in the same state. As a result, about 30 BIA schools were 

included per grade, thereby increasing the number of AI/AN students in the 

sample. 

The national and regional results of the NIES include AI/AN students in all 

schools (public, private, Department of Defense, and BIA), while the state results 

are based on samples of AI/AN students in public and BIA schools only; 

however, the percentage of AI/AN students who are enrolled in schools other than 

public and BIA schools nationally is very small (between 1 and 2 percent, 

unweighted). 

Authorization: Authorization for this study falls under the Executive Order 13336: American 

Indian and Alaska Native Education. This Executive Order is a follow-up to the 

No Child Left Behind Act. 

Strengths: Data sets contain a large number of AI/AN/NA respondents. Data are collected on 

a key policy issue, education. 

Limitations: No major limitations were identified with Part One of the study. Details from Part 

Two were not available at the time this catalog was compiled and thus cannot be 

included in this profile. 

Access 

Requirements 

and Use 

Restrictions: 

The data will be made available to researchers with NCES license. There is no 

cost. The steps for obtaining a license are detailed at the following website: 

http://nces.ed.gov/pubsearch/licenses.asp. 

Contact 

Information: 

Office of Indian Education 

U.S. Department of Education 

400 Maryland Avenue SW 5C132 

Washington, DC 20202-6335 

Phone: (202) 260-7485 

Fax: (202) 260-7779 

E-mail: indian.education@ed.gov 

Specific questions about the NIES to can be directed to Jeff Johnson 

(jeff.johnson@ed.gov) or Taslima Rahman (taslima.rahman@ed.gov). 

5-132 
National Longitudinal Mortality Study (NLMS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/National Institutes of 

Health/National Cancer Institute (NCI); National Heart, Lung, and Blood Institute 

(NHLBI); National Institute on Aging (NIA); National Center for Health 

Statistics (NCHS); and the U.S. Census Bureau 

Description: The National Longitudinal Mortality Study (NLMS) examines the effects of 

demographic and socio-economic characteristics on differentials in mortality. The 

NLMS is a unique research database in that it is based on a random sample of the 

non-institutionalized population of the United States. Records from the Annual 

Social and Economic Supplement, and the Census Current Population Surveys 

(CPS) are matched to mortality information from death certificates available for 

deceased persons through NCHS. Extensive demographic, social, economic, and 

occupation information is collected in the CPS. The study currently consists of 

approximately 2.3 million records with over 250,000 identified mortality cases. 

Relevant Policy 

Issues: 

Measurement of Health Status, Key Health Disparities, and Factors Contributing 

to Measured Health Disparities. 

Data Type(s): Registry 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Most of the race information in the NLMS is based on the CPS. 

AI/AN/NA 

Population in 

Data Set: 

Based on frequencies provided for each file (for years 1979 through 1998) in the 

public use data file reference manual, there are 19,779 American Indians/Alaska 

Natives (AI/AN) and 1,504 Native Hawaiians/Other Pacific Islanders (NH/PI) in 

this file. For years 1992 through 1998, the average number of AI/AN in the data 

files are 848 and 220 for NH/PI persons. 

Geographic 

Scope: 

The geographic scope of the study is national. Geographic indicators available for 

analysis include region, state, county, urban status, and SMA status. 

Date or 

Frequency: 

Data files linking Census data to death certificate information are available for 

1973-2002. 

Data Collection 

Methodology: 

Census data are linked to mortality information obtained from death certificates 

available for deceased persons through the NCHS. 

Participation: This is a secondary data linkage and does not require participation by individual 

respondents. 

Strengths: Data are collected on key policy issues, including health. There are multiple years 

of data available. The linkage of the individual social and economic data with the 

mortality outcomes provides the resource for extensive analysis. 

5-133 
National Longitudinal Mortality Study (NLMS) 

(continued) 

Limitations: The study is based on specific survey months of the CPS, the Annual Social and 

Economic Supplement, and a subset of the 1980 Census. These are one-time data 

collection processes with no subsequent data collection. Therefore, one limitation 

of NLMS data is that they provide a one-time only baseline measurement of 

subjects in a long-term follow-up situation. Another limitation of these data is 

that, although the CPS and Census instruments provide extensive data collection 

capabilities in specific subject matter areas, desirable general or specific health 

information is not collected and smoking status is available only on a limited 

number of records. 

Access 

Requirements 

and Use 

Restrictions: 

A public use data file is available. Potential users must submit a data use 

agreement to the NHLBI. Data use agreement form can be found at: 

http://www.census.gov/nlms/docs/form.doc. 

Research access to the entire NLMS database may be arranged through the 

principal investigators of the NLMS sponsoring agencies. 

Contact 

Information: 

Project Main Website: http://www.census.gov/nlms/index.html 

Norman J. Johnson 

U.S. Census Bureau 

4700 Silver Hill Road 

DSMD, Room 3725-3 

Suitland, MD 20746 

Ph: (301) 763-4270 

FAX: (301) 457-3766 

email: norman.j.johnson@census.gov 

Reports of 

Interest: 

The NLMS website provides a list of published articles based all or in part on 

either the full NLMS database or the NLMS public-use file. The URL for this 

bibliography is: http://www.census.gov/nlms/bibliography.html. 

5-134 
National Mortality Followback Survey (NMFS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC)/National Center for Health Statistics (NCHS) 

Description: The National Mortality Followback Survey Program (NMFS), begun in the 1960s 

by NCHS, draws a sample of U.S. residents who die in a given year and 

supplements their death certificate information with information from the next of 

kin or another person familiar with the decedent’s life history. This information, 

sometimes enhanced by administrative records, provides a unique opportunity to 

study the etiology of disease, demographic trends in mortality, and other health 

issues. 

Relevant Policy 

Issues: 

Measurement of Health Status and Key Health Disparities. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification In the 1993 data, death certificate information is coded into the following 

of AI/AN/NA: categories: 

• White 

• Black 

• American Indian, Eskimo, Aleut (AI/AN) 

• Asian and Pacific Islander 

• Could not match 

AI/AN/NA 

Population in 

Data Set: 

In the 1993 NMFS data, out of 22,957 total unweighted cases, 205 unweighted 

cases are identified as AI/AN. 

Geographic 

Scope: 

The geographic scope of the study is national. (South Dakota did not participate 

in 1993.) Analysis (in the 1993 data) is also possible by region and by size of 

county. 

Date or 

Frequency: 

The 1993 NMFS is the sixth in a series of surveys, first initiated by NCHS in the 

early 1960's. Data are available for both the 1993 NMFS and the 1986 NMFS. 

Data Collection 

Methodology: 

The sampling frame for the 1993 NMFS is the 1993 Current Mortality Sample 

(CMS). The CMS is a 10 percent systematic random sample of states' death 

certificates. The proxy respondent questionnaire is completed through a telephone 

or in-person interview. 

Participation: Optional, without incentives 

Response Rate: The overall response rate was 83 percent. 

5-135 
National Mortality Followback Survey (NMFS) 

(continued) 

Sampling 

Methodology: 

The sampling frame for the 1993 NMFS is the 1993 Current Mortality Sample 

(CMS). The CMS is a 10 percent systematic random sample of states' death 

certificates. A sample of 22,957 death certificates from the Current Mortality 

Sample was drawn. The sample was selected by broad age groups (15 years or 

older), two racial groups (black vs. nonblack), and gender within 12 causes of 

death (suicide; homicide; injuries to motor vehicle drivers, pedestrians, and 

motorcycle owner operators; other motor vehicle injuries; non-motor vehicle 

injuries; HIV; cancer; chronic obstructive pulmonary disease; heart disease; 

alcohol abuse; drug abuse; and all other causes). In order to produce more robust 

analysis, black decedents, certain causes of death, and certain age groups were 

oversampled (45.5 percent of all cases). 

Analysis: To produce national estimates, researchers must use weights and adjust for the 

complex sampling design for all analyses. 

Authorization: The 1993 NMFS was conducted under the authorization of the Public Health 

Service Act (Title 42, United States code, Section 242k). 

Strengths: Data are collected on key policy issues including health status and health 

disparities. Documentation is thorough and available online. 

Limitations: The sample size for AI/AN is small. 

Access 

Requirements 

and Use 

Restrictions: 

The 1986 and 1993 data from the NMFS are available on CD-ROM at no charge. 

The 1993 NMFS data are also available by directly downloading from the CDC 

website. 

Contact 

Information: 

For questions concerning the 1993 National Mortality Followback Survey 

or to obtain a CD-ROM, contact: 

Mortality Statistics Branch 

Division of Vital Statistics 

National Center for Health Statistics 

Centers for Disease Control and Prevention 

3311 Toledo Road, Room 7318 

Hyattsville, Maryland 20782 

(301) 458-4666 

The data can be directly downloaded from: 

http://www.cdc.gov/nchs/about/major/nmfs/nmfs.htm. 

Documentation for the 1993 survey is also available at this website. 

5-136 
National Survey of America’s Families (NSAF) 

Sponsor: The Urban Institute 

Description: The National Survey of America's Families (NSAF) is part of The Urban 

Institute’s Assessing the New Federalism project. Its purpose is to track the 

effects of recent federal policy changes decentralizing many social programs, and 

to provide a comprehensive look at the well-being of children and non-elderly 

adults. The survey provides quantitative measures of child, adult and family wellbeing in America, with an emphasis on persons in low-income families. The 

survey gathers data on economic, health and social characteristics of children and 

families in order to estimate well-being. Specific topics include: participation in 

government programs; employment; earnings and income; economic hardship; 

educational attainment; training; family structure; housing arrangements; health 

insurance coverage; access to and use of health services; health status; 

psychological well-being; participation in religious and volunteer activities; 

knowledge of social services; and attitudes about work, welfare, health care and 

childbearing. In 2002, interviews were conducted with more than 40,000 families, 

yielding information on more than 100,000 people. Earlier rounds of the survey 

were conducted in 1997 and 1999. 

Relevant Policy 

Issues: 

Measurement of Health Status, Factors Contributing to Measured Health 

Disparities, Income Status, Economic Assistance Program Participation Rates, 

Economic Opportunity, Housing Quality, and Measure of Child Well Being and 

Child Care arrangements. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual or family level. 

Identification 

of AI/AN/NA: 

What is (your/NAME’s) race? 

(Interviewers are instructed to probe by reading categories if necessary and if the 

respondent says “Native American,” to verify by asking: “I am recording this as 

‘American Indian’—is that right?”) 

• White 

• Black 

• American Indian, Aleutian, or Eskimo (AI/AN) 

• Asian/Pacific Islander 

• Other (Specify) 

The race question was identical in the 1999 study. In 1997, the race question did 

not include the follow-up probe for “Native American." 

AI/AN/NA 

Population in 

Data Set: 

There are four person-level data files available for public use. These files include 

the Adult Pair, Random Adult, Childless Adult, and Focal Child. Additionally, 

there are two family-level files that do not contain race information, but can be 

merged with the individual-level data files. 

5-137 
National Survey of America’s Families (NSAF) 

(continued) 

The 2002 Focal Child File contains one record for each child (ages 0 – 17) 

included in the NSAF study. Out of 34,332 completed interviews in this file, 491 

respondents are identified as American Indian/Native American/Aleutian or 

Eskimo. 

There are also three data files for the adult respondents included in the NSAF. In 

the survey, some questions are asked about both the respondent and his or her 

spouse or partner (if one exists), others are asked about either the respondent or 

his or her spouse or partner (randomly chosen), and still others are asked about 

only the respondent. 

The 2002 Adult Pair File contains records for both the respondent and his/her 

spouse or partner. Out of 70,577 completed interviews in this file, 1,018 

individuals are identified as American Indian/Native American/Aleutian or 

Eskimo. 

The 2002 Random Adult File contains data elements from the extended interview 

that are specific to a randomly selected adult (this is a subset of the Adult Pair 

File). The random adult data set contains variables based on questions asked 

during the extended interview that were specific to a randomly selected adult 

(either the respondent or the spouse/partner). This situation occurs only in 

sections E (Past Year Health Insurance Coverage) and F (Health Care use and 

Access) of the NSAF questionnaire. Out of 49,507 completed interviews in this 

file, 752 respondents are identified as American Indian/Native American/Aleutian 

or Eskimo. 

The 2002 Childless Adult File contains data elements representing households 

without children, where up to two childless adults between the ages of 18 and 64 

were selected for interviewing. Out of 15,279 completed interviews, 248 

respondents are identified as being American Indian/Native American/Aleutian or 

Eskimo. This file is not available on the NSAF Online Statistical Analysis 

webpage, but can be downloaded seperately at: 

http://anfdata.urban.org/drsurvey/login.cfm 

Geographic 

Scope: 

Geographic indicator variables on the public use data files include a state 

indicator (including D.C.), the 5-digit Federal Information Processing Standards 

(FIPS) county code for counties with more than 250,000 persons in the 13 NSAF 

focal states, and the 4 Census regions of Northeast, Midwest (formerly North 

Central), West, and South. 

The NSAF was designed to produce national estimates of the population under 

65. Additionally, state estimates are possible for the 13 states that contained 

oversamples: Alabama, California, Colorado, Florida, Massachusetts, Michigan, 

Minnesota, Mississippi, New Jersey, New York, Texas, Washington, and 

Wisconsin. There is also a public use NSAF data set available for the California 

NSAF, conducted in 1997, 1999, and 2002 (containing 113 AI/AN individuals). 

5-138 
National Survey of America’s Families (NSAF) 

(continued) 

Date or 

Frequency: 

The 2002 study was conducted from February to November. Previous rounds of 

data collection include the 1997 and 1999 study. At this time there are no plans 

for future rounds of data collection. 

Aggregation: Researchers who wish to aggregate data across the three years of data collection 

for the NSAF study should first examine all survey items of interest to make 

certain the question text and the response options are identical. Although every 

effort was made to keep question wording unchanged between the rounds, there 

were some improvements made to some questions. Researchers should also 

examine the design of each wave very carefully. Changes were made in each 

wave that could affect survey weights and estimation; for example, in the third 

round of data collection, the sample size for nontelephone households in the study 

areas was reduced. 

The number of AI/AN respondents for the 1997 and 1999 NSAF that could be 

included in an aggregation are below: 

AI/AN Respondents in 1999:

Child file: 488 

Adult pair file: 1,001 

Random adult file: 721 

AI/AN Respondents in 1997:

Child file: 529 

Adult pair file: 971 

Random adult file: 738 

Data Collection 

Methodology: 

All interviews were conducted on the telephone by interviewers working in 

central interviewing facilities, using computer-assisted telephone interviewing 

(CATI) technology. In-person interviewers used cellular telephones to connect 

respondents in nontelephone households to the interviewing centers for the CATI 

interview. 

Participation: Optional, with incentives 

Response Rate: 2002: overall child response rate = 55.1% 

2002: overall adult response rate = 51.9% 

1999: overall child response rate = 62.4% 

1999: overall adult response rate = 59.4% 

1997: overall child response rate = 65.1% 

1997: overall adult response rate = 61.8% 

Sampling 

Methodology: 

The sample is representative of the civilian, non-institutionalized population 

under age 65. As with the prior two rounds of data collection (conducted in 1997 

and 1999), the 2002 survey included oversize samples drawn in 13 states (listed 

5-139 
National Survey of America’s Families (NSAF) 

(continued) 

under Geographic Scope) to allow for the production of reliable estimates at the 

state level. The oversize state samples are supplemented with a balance of the 

United States sample to allow the creation of estimates at the national level as 

well. 

The sampling frame consisted of a list-assisted, random-digit dialing (RDD) 

sample of telephone numbers supplemented by an area probability sample of 

nontelephone households. A short screening interview was used to identify and 

sample households based on age composition and household income. Once 

household eligibility was sampled, subsequent questions were asked to identify 

the children (age 0 to 17) or adults (age 18 to 64) in the household. Once this list 

was compiled, the CATI program sampled up to two children or up to two adults 

for subjects on the extended interview. If children were sampled, a series of 

questions was asked to determine the name and relationship of the person most 

knowledgeable about the selected child or children (the most knowledgeable 

adult). 

Analysis: There are a series of methodology reports that accompany the NSAF public use 

data. Detailed information on calculating design effects (DEFF) and standard 

errors can be found in the following reports in the 2002 NSAF Variance 

Estimation, Report No. 4, located at 

http://www.urban.org/UploadedPDF/900716_2002_Methodology_4.pdf; and the 

NSAF Public Use File User’s Guide, Report No. 11, located at 

http://www.urban.org/UploadedPDF/900760_2002_Methodology_11.pdf. 

Child, all races: DEFF = 1.77, effective sample size = 10,828 

Adult, all races: DEFF = 2.13, effective sample size = 15,015 

(Separate design effects and effective sample sizes were calculated for the Black 

and Hispanic populations, but not the AI/AN population.) 

Strengths: Data are collected on many key policy issues, including family well-being 

measures such as assistance receipt, socioeconomic status and education. There 

are multiple years of data available. 

For most survey questions the item nonresponse rates were very low, often less 

than 1 percent. For survey items with significantly higher levels of item 

nonresponse (such as income), missing responses were imputed using a standard 

“hot deck” method, for all three rounds of data collection. 

Low-income families were oversampled. Even with this oversampling method, 

the NSAF contains a relatively small average margin of error for state-level 

estimates of low-income children and adults. 

Limitations: No major limitations were identified. 

5-140 
National Survey of America’s Families (NSAF) 

(continued) 

Access 

Requirements 

and Use 

Restrictions: 

To access the public use data, researchers must register with the Urban Institute’s 

website and agree to their terms of confidentiality. The data are available at no 

cost. 

Contact 

Information: 

The Urban Institute 

Assessing the New Federalism Policy Center 

2100 M Street, NW 

Washington DC 20037 

(202) 261-5377 

nsaf@ui.urban.org 

The public use data can be accessed: http://anfdata.urban.org/drsurvey/login.cfm. 

Additionally, researchers can perform web-based analysis of the NSAF survey 

data using the online analysis tool at: 

http://www.urban.org/center/anf/analysisprelogin.cfm. 

5-141 
National Survey of Child and Adolescent Well-being (NSCAW) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Administration for 

Children and Families (ACF) 

Description: The National Survey of Child and Adolescent Well-being (NSCAW) provides 

nationally representative longitudinal data concerning children who are at risk of 

abuse or neglect or are in the child welfare system. Two samples of children were 

selected for NSCAW: children who were the subject of child abuse or neglect 

investigations conducted by Child Protective Service agencies (CPS sample) and 

children who had been in out-of-home or foster care for approximately one year 

and whose placement had been preceded by an investigation of child abuse or 

neglect (LTFC sample). The information comes from first-hand reports from 

children, parents, and other caregivers, as well as reports from caseworkers, 

teachers, and data from administrative records. The data include information on 

child and family functioning and well-being, service needs and utilization, and 

agency- and system-level factors that are likely to be related to child and family 

outcomes. Child outcomes of interest include health and physical well-being, 

cognitive and school performance, mental health, behavior problems, and social 

functioning and relationships. 

Relevant Policy 

Issues: 

Measurement of Health Status, Measures of Well-being for Families/households, 

and Measures of Well-being for Children. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

What race are you? (Interviewers are instructed to code all that apply.) 

• American Indian or Alaska Native (AI/AN) 

• Asian 

• Black or African American 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• White 

This format is used to ascertain race of child, caretaker, and caseworker. 

AI/AN/NA 

Population in 

Data Set: 

In Wave 1, there are a total of 5,504 children in the CPS study group. Of these, 

341 are identified as AI/AN. In addition, there are a total of 727 in the LTFC 

study group; 47 are identified as AI/AN. 

Asians, Native Hawaiians and Pacific Islanders are combined into a single 

category in the data set and can not be analyzed separately. 

Geographic 

Scope: 

The geographic scope of the study is national. The type of county residence (rural 

vs. urban) is identified in the sampling frame. (Counties with greater than 50 

percent urban area are classified as urban. Remaining counties are classified as 

5-142 
National Survey of Child and Adolescent Well-being (NSCAW) 

(continued) 

rural.) Address is collected for follow-up purposes but does not appear to be 

recoded into geographic variables. Based on the documentation available, 

researchers should be able to conduct analyses by rural vs. urban county. 

Date or 

Frequency: 

This is a longitudinal study with four waves of data collection. Baseline data 

collection began in Fall 1999 and was completed in April 2001. After the 

baseline, three additional waves of data collection occurred at 12 months, 18 

months, and 36 months post-baseline. 

Data Collection 

Methodology: 

Interviews with parents or caregivers and children were conducted in-person 

using computerized personal interviewing techniques (CAPI) in private settings 

(e.g., the home). Field personnel collected physical measurements and 

observation data for infants and toddlers. Caseworker and agency interviews were 

also conducted in-person. 

The CAPI instrument guided the child interview and prompted the field 

representative to administer the required developmental assessments in the 

designated order. When prompted, the field representative retrieved the 

assessment materials and administered the various activities appropriate for the 

child’s age. 

Participation: Optional, with incentives 

Response Rate: Child Interview Response Rates: 

 CPS Sample LTFC Sample

Wave 1 64.2% 73.4% 

Wave 2 86.7% 92.5% 

Wave 3 86.6% 94.0% 

Wave 4 85.3% 88.5% 

Sampling 

Methodology: 

The children in the NSCAW CPS and LTFC samples were selected using a twostage stratified sample design. At the first stage, the U. S. was divided into nine 

sampling strata. Within each of these nine strata, primary sampling units (PSUs), 

geographic areas that encompass the population served by a single child 

protective services agency, were randomly selected using a probabilityproportionate-to-size procedure that gave a higher chance of selection to PSUs 

having larger caseloads. The same numbers of children were then sampled within 

each PSU. 

Analysis: Because the NSCAW sample design is complex (e.g., unequally weighted, 

stratified, and clustered), standard errors computed using standard statistical 

procedures that assume a simple random sample will generally be too small. 

Special software that accounts for the complex sample design is needed in order 

to correctly estimate the standard errors. The User’s Manual provides detailed 

guidance on the use of commercially available software packages such as 

SUDAAN, Stata, WesVar, and the SAS procedures SURVEYMEANS and 

5-143 
National Survey of Child and Adolescent Well-being (NSCAW) 

(continued) 

SURVEYREG to correctly estimate the standard errors taking into account the 

complex sample design. 

Authorization: In the Personal Responsibility and Work Opportunities Reconciliation Act of 

1996, Congress directed the Secretary of the Department of Health and Human 

Services to conduct a national study of children who are at risk of abuse or 

neglect or are in the child welfare system. Congress directed that the study 

include a longitudinal component that follows cases for a period of several years; 

collects data on the types of abuse or neglect involved, agency contacts and 

services, and out-of-home placements. 

Strengths: Data are collected on key policy issues, including health and child welfare. There 

are multiple years of data available. The unique content of the data will be 

extremely useful to researchers and policy makers. The documentation is 

comprehensive. Extensive nonresponse analysis has been conducted to identify 

potential sources of bias in the collected data. Because of the complexity of this 

data source, ACF and its contractor have developed the NSCAW Data Delivery 

System to aid analysts and other data users, support the reduction of the data set 

to a manageable level, support various programming environments, and provide 

an electronic codebook including frequency distributions for the variables in the 

CPS and LTFC cohorts. 

Limitations: Data access is strictly controlled and is not available to employees at child 

welfare agencies. In the LTFC, the number of AI/AN is very small. Because of 

their longitudinal nature, weighted analyses of these data will be complex. 

Access 

Requirements 

and Use 

Restrictions: 

Two different versions of the NSCAW data are available. The General Use Data 

has identifying information and geographic detail removed and variables posing a 

risk of respondent disclosure have been recoded. The Restricted Release version 

has geographic detail and fewer variables have been recoded, but this version 

presents a higher risk to respondent confidentiality. It is, therefore, only made 

available to researchers who can justify a need for high level access and who are 

willing to follow additional application requirements. 

 

For both versions of NSCAW, access is limited to researchers who agree to the 

terms and conditions contained in the Data Use License. Only faculty and nonstudent research personnel at institutions that have an Institutional Review 

Board/Human Subjects Review Committee are eligible to order the data. 

While access to both versions of the NSCAW data require approval by an 

Institutional Review Board at the researcher's institution and close oversight by 

NDACAN in the form of a legally-binding licensing agreement, access to the 

Restricted Release Data also requires preparation of an application and data 

protection plan as well as willingness to cooperate with unannounced on-site 

inspections of the research facility. 

University students may gain access to the NSCAW only as research staff who 

have been added to the project, but a faculty advisor must serve as the 

5-144 
National Survey of Child and Adolescent Well-being (NSCAW) 

(continued) 

investigator. Employees at child welfare agencies are not presently eligible to 

obtain any version of the NSCAW data. 

Contact 

Information: 

Data are available to researchers who meet the requirements described in the 

Access Requirements and Use Restrictions section of this profile through the 

National Data Archive on Child Abuse and Neglect (NDACAN) at 

http://www.ndacan.cornell.edu/index.html. 

Data Archive information: 

National Data Archive on Child Abuse and Neglect 

Beebe Hall - FLDC 

Cornell University 

Ithaca, NY 14853 

NDACAN General E-mail: NDACAN@cornell.edu 

NDACAN Technical Support: NDACANSupport@cornell.edu 

Federal Project Officer: 

Mary Bruce Webb, Ph.D. 

Administration for Children and Families 

370 L'Enfant Promenade, S.W. 

Washington, D.C. 20201 

Phone: (202) 205-8628 

mary.webb@acf.hhs.gov

5-145 
National Survey of Family Growth (NSFG) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC)/National Center for Health Statistics (NCHS) 

Description: The National Survey of Family Growth (NSFG) is a periodic survey initiated to 

provide current information on fertility and infertility, family planning, 

childbearing, contraceptive practice, and other aspects of maternal and child 

health and to gauge the effects of these processes on population growth. The 

NSFG Cycle 6 interviews, conducted in 2002, covered the respondent's pregnancy 

history, past and current use of contraception, ability to bear children, use of 

medical services for family planning, infertility, prenatal care, marital history, and 

associated cohabiting unions. Data on occupation and labor force participation 

and on a wide range of social, economic, and demographic characteristics are also 

presented. In addition, Cycle 6 adds detailed questions on HIV risk behaviors and 

fatherhood and father involvement. 

Relevant Policy 

Issues: 

Health Disparities, Measures of Well-being for Families/Households, and 

Identification of Evidence-based Practices and Programs that Improve Family 

Well-being. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Race is self-reported to the interviewer (during the face-to-face interview), using 

the following CAPI instructions: 

Which of the groups on Card 2 describe your racial background? Please select 

one or more groups. 

[Interviewers are instructed to enter all that apply. They are to enter all groups 

that are part of the mixture if the respondent reports a mixture of several races 

(biracial, mixed, mulatto, etc.).] 

• American Indian or Alaska Native (AI/AN) 

• Asian 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• Black or African American 

• White 

[If respondent selected multiple race groups, interviewer asks this question.] 

Which of these groups, that is (Race groups selected) would you say best 

describes your racial background? 

AI/AN/NA 

Population in 

Data Set: 

It is not possible to identify AI/AN/NA persons in the public use file. However, in 

the restricted Cycle 6 data set (2002), the following cases are available: 

5-146 
National Survey of Family Growth (NSFG) 

(continued) 

AI/AN, Non-Hispanic: 368 (159 men and 209 women) 

AI/AN, Hispanic: 579 men and women (most identified themselves as Mexican 

and South American) 

NH/PI: 91 (45 men and 46 women) 

Geographic 

Scope: 

The geographic scope of the study is national. Detailed geographic identifiers are 

available on the restricted access contextual data file. These variables include the 

state code, the county code, census tract, block group, metropolitan status, 

urban/rural identifiers, and information regarding the land area and population 

count for the county, tract, and block group. 

Analysis can be done for the four major census regions (Northeast, Midwest, 

South, West) and for metropolitan and nonmetropolitan areas. Estimates cannot 

be made for individual states or for smaller areas. 

Date or 

Frequency: 

This is a periodic survey. Previous cycles of data collection for all races include: 

Cycle 6: 2002 [7,643 women, 4,928 men (the first time NSFG included a sample 

of men)] 

Cycle 5: 1995 (10,847 women) 

Cycle 4: 1988 (8,450 women) 

Cycle 3: 1982 (7,969 women) 

Cycle 2: 1976 (8,611 women) 

Cycle 1: 1973 (9,797 women) 

Aggregation: Researchers may wish to pool data from the different cycles of the NSFG to 

increase the numbers within rare subgroups (such as Native Hawaiians and Other 

Pacific Islanders). Details on the way race information was collected in earlier 

cycles of the NSFG are provided below: 

Cycle 3 (1982): Question F-47: 

“Which of the groups on this card best describes your racial background?” 

Alaskan Native or American Indian has 83 cases (out of 7,969 women). 

Only one race was coded in Cycle 3. 

Cycle 4 (1988): Question F-9: 

“Which of the groups on card 30 best describe your racial background?” (Code all 

that apply) 

Alaskan Native or American Indian has 238 cases out of 8,450, allowing multiple 

mentions. The standard “RACE” recode is shown only as black, white, and other, 

but the original variable contains more detail. 

Cycle 5 (1995): Question IC-3 and 4: 

“Which of the groups on Card I-1best describes your racial background?” 

First mention= 344 “Alaskan Native or American Indian.” 

2nd mention = 9 “Alaskan Native or American Indian.” 

3rd mention = 3 “Alaskan Native or American Indian.” 

5-147 
National Survey of Family Growth (NSFG) 

(continued) 

CDC does not recommend using the AI/AN/NA race identifiers on the Cycle 1 

(1973) and Cycle 2 (1976) data sets, as this information was collected differently 

and should not be combined with later cycles. 

While there are no CDC-specific guidelines for pooling data, the agency provides 

the following suggestions for combining the data: 

Researchers can append the data from each cycle of interest and use the year of 

the survey as an independent variable. For obtaining unbiased standard errors for 

each cycle: 

• For the 2002 and 1995 surveys (Cycles 6 and 5) researchers can use 

SUDAAN or STATA software. 

• For 1988 (Cycle 4) there are Balanced Repeated Replicate (BRR) 

weights available. STATA version 9 does BRR variance estimation. The 

command and the column locations of the weights can be obtained from 

CDC. 

• For 1982 (Cycle 3): Replicate weights to allow calculation of valid 

standard errors for complex sampling were not included on public use 

files. Instead, generalized variance estimates were developed and 

published for estimated numbers and percentages. 

Additionally, researchers should examine the sampling methodology and question 

text and response options across the different cycles to decide whether pooling 

data across the different cycles is feasible. 

Data Collection 

Methodology: 

Data are collected through in-person face-to-face interviews conducted by trained 

female interviewers. Interviewers use computer assisted personal interviewing 

(CAPI) to record responses, except for the last section of the questionnaire, which 

uses audio computer assisted self-interviewing (ACASI) for sensitive questions. 

Participation: Optional, with incentives. For Cycle 6, an incentive of $40 was given for 

completed surveys. 

Response Rate: For 2002, the response rate is reported as 80 percent for women and 78 percent 

for men. 

Sampling 

Methodology: 

The NSFG employed a multistage national area probability sample design. The 

target population consisted of women 15-44 years of age in all 50 states and the 

District of Columbia. The first stage of sampling involved combining all counties 

in the U.S. to form 2,402 primary sampling units (PSUs). From this, 121 national 

and Hispanic sample PSUs were selected. Stage 2 divided the sample PSUs into 

four domains based on estimated key characteristics of the population within a 

block. From this, a total of 783 segments were selected from the initial sample of 

1,414 segments for fieldwork. For stage 3, trained household listers visited each 

of the sample segments to list housing units on the blocks in the segments. 

Sampled housing units were drawn from these housing unit lists. The fourth stage 

consisted of selecting eligible persons from within the sampled households. 

5-148 
National Survey of Family Growth (NSFG) 

(continued) 

Analysis: The CDC website includes several examples of programs used to create variance 

estimation for Cycle 6 data of the NSFG. There is not a report that publishes 

specific design effects for the variables of interest, but the examples included on 

this website may be very useful to researchers: 

http://www.cdc.gov/nchs/about/major/nsfg/nsfgvar.htm. 

Strengths: Data are collected on key policy issues, including health and family well-being. 

Limitations: Since AI/AN/NA persons are not identified in the most recent (2002) public use 

file, researchers will have to analyze the data through the NCHS Research Data 

Center. In addition, to increase sample size, researchers may wish to combine the 

data for 2002 with data from one or more of the previous surveys that collected 

AI/AN/NA race, conducted in 1995, 1988 and 1982. Researchers are also 

encouraged to cross-tabulate the data on AI/AN race by Hispanic origin. 

In the full sample data, the number of NH/PI is very small. 

Access 

Requirements 

and Use 

Restrictions: 

The AI/AN race categories were included in an "other" category on the public use 

file due to disclosure risk. To do analysis using these categories separately, a 

researcher may use the Research Data Center (RDC) at NCHS, which is a 

physical space located within the NCHS facilities in Hyattsville, Maryland, where 

researchers are allowed access to NCHS restricted data files not released to the 

public. These data files do not contain direct identifiers such as name or social 

security number, but may contain identifiers for small geographic units such as 

block or census tract. 

There are 3 ways to access data through the RDC once a project has been 

approved: 

(1) “remote access,” in which the user submits a SAS program electronically and 

the output is screened and returned electronically; 

(2) by physically going to the RDC at NCHS, and doing the research there, using 

any software the researcher wants to use; and 

(3) staff-assisted access, in which the researcher submits a program to an RDC 

staff member who submits and screens it and returns the output. 

There are fees for each type of access. 

Contact 

Information: 

National Survey of Family Growth Staff 

Division of Vital Statistics 

National Center for Health Statistics 

Centers for Disease Control and Prevention 

3311 Toledo Road, Floor 7 

Hyattsville, Maryland 20782 

(301) 458-4222 

nsfg@cdc.gov 

Research Data Center: (301) 458-4277 or e-mail rdca@cdc.gov 

5-149 
National Survey of Veterans (NSV) 

Sponsor: U.S. Department of Veterans Affairs 

Description: The 2001 National Survey of Veterans (NSV) is the fifth in a series of 

comprehensive nationwide surveys designed to help the Department of Veterans 

Affairs (VA) plan its future programs and services for veterans. The information 

gathered through these surveys will help VA to identify the needs of veterans and 

then allocate resources in ways that will ensure these needs can be met. It also 

provides a snapshot profile of the veteran population. Data collected through the 

NSV enables VA to: (1) follow changing trends in the veteran population; (2) 

compare characteristics of veterans who use VA services with those of veterans 

who do not; (3) study VA’s role in the delivery of all benefits that veterans 

receive; and (4) update information about veterans to help the VA develop its 

policies. 

Relevant Policy 

Issues: 

Eligibility and Use of Veterans Administration Health Facilities and Eligibility 

and Use of Other Veterans Administration Benefits. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification The instructions for reporting race were as follows: 

I’m going to read a list of racial categories. Please select one or more to describe 

your race. Are you... 

of AI/AN/NA: 

• White 

• Black or African American 

• American Indian or Alaska Native (AI/AN) 

• Asian 

• Native Hawaiian (NH) 

• Other Pacific Islander (OPI) 

• Hispanic/Mexican 

• Other 

Respondents could choose up to 8 response categories for this item. 

AI/AN/NA 

Population in 

Data Set: 

The counts reported below represent the number of respondents who mentioned 

the listed race as their race either with or without mentioning any other race(s). 

TOTAL: 20,048 

AI/AN: 897 

NH: 34 

OPI: 48 

5-150 
National Survey of Veterans (NSV) 

(continued) 

AI/AN/NA 

Subpopulations: 

AI/AN/NA subpopulations identified are: 

• Native Hawaiian alone 

• Pacific Islander alone 

Geographic 

Scope: 

The geographical scope is national. No additional geographic areas were identified 

in the data. 

Date or 

Frequency: 

The National Survey of Veterans was first conducted in the late 1970s, again in 

1987, again in 1993, and most recently in 2001. The content of the questionnaires 

changed between data collection efforts. 

Data Collection 

Methodology: 

The 2001 NSV was a computer-assisted telephone interview (CATI). 

Participation: Optional, without incentives 

Response Rate: There were two types of samples: random-digit dialing (RDD) and list. Overall 

response rate was 51.6 percent for the RDD sample. The overall list sample 

response rate was not presented in the methodology report. 

Sampling 

Methodology: 

The sample design for the 2001 NSV was a dual frame design consisting of an 

RDD sample and a list sample. The list sample design used the Veterans Health 

Administration Healthcare enrollment file and the Veterans Benefits 

Administration Compensation and Pension (C&P) file to construct the sampling 

frame. 

Analysis: Appendix C of the final report includes a discussion of standard errors for 

estimates. Information on the NSV is available online at: 

http://www.virec.research.va.gov/DataSourcesName/NationalSurveyVeterans/200

1NationalSurveyofVeterans.htm

Authorization: The NSV is conducted under the general authorization of U.S. Code Title 38, 

Section 527. This section authorizes the VA Secretary to gather data for the 

purposes of planning and evaluating VA programs. 

Strengths: Data are collected on key policy issues. There are multiple years of data available. 

The NSV is one of the few national data sets that covers veterans’ issues. Also, 

comprehensive documentation of the study is available online. 

Limitations: There are only a small number of NH/PI respondents. Although the NSV has been 

conducted in previous years, there are significant differences in the survey content 

across the administrations. Aggregation of the data to increase the number of 

NH/PI represented in the database would require a skilled statistician. 

5-151 
National Survey of Veterans (NSV) 

(continued) 

Access 

Requirements 

and Use 

Restrictions: 

Current data are available to the public at no cost; this could change if demand is 

high. Data from these earlier efforts may be available depending on demand. 

Contact 

Information: 

In order to obtain this file, researchers should contact the Office of Policy, 

Planning and Prepardness Office, Office of Policy, Department of Veterans 

Affairs, and the 2001 National Survey of Veterans Project Officer, Susan 

Krumhaus at (202) 273-5108, or Wayne Johnson at (202) 273-8972, and briefly 

explain how you would like to use these data. 

5-152 
National Survey on Drug Use and Health (NSDUH) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Substance Abuse and 

Mental Health Services Administration (SAMHSA)/Office of Applied Studies 

(OAS) 

Description: The National Survey on Drug Use and Health (NSDUH), formerly called the 

National Household Survey on Drug Abuse or NHSDA, is designed to produce 

drug and alcohol use incidence and prevalence estimates and report the 

consequences and patterns of use and abuse in the general U.S. civilian 

population aged 12 and older. Questions include age at first use, as well as 

lifetime, annual, and past-month usage for many drugs. The survey also covers 

substance abuse treatment history and perceived need for treatment, and includes 

questions from the Diagnostic and Statistical Manual (DSM) of Mental Disorders 

that allow diagnostic criteria to be applied. Respondents are also asked about 

personal and family income sources and amounts, health care access and 

coverage, illegal activities and arrest record, problems resulting from the use of 

drugs, perceptions of risks, and needle-sharing. Demographic data include gender, 

race, age, ethnicity, educational level, job status, income level, veteran status, 

household composition, and population density. 

Relevant Policy 

Issues: 

Key Health Disparities. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Which of these groups describes you? (The interviewer gives the respondent a 

handcard with race categories and instructs respondent to provide one or more 

races.) 

• White 

• Black/African American 

• American Indian or Alaska Native (AI/AN) (American Indian includes 

North American, Central American, and South American Indians) 

• Native Hawaiian (NH) 

• Other Pacific Islander (OPI) 

• Asian (for example, Asian Indian, Chinese, Filipino, Japanese, Korean, and 

Vietnamese) 

• Other 

In the public use data, NH and OPI are combined into a single category. 

AI/AN/NA 

Population in 

Data Set: 

The achieved sample for the 2004 NSDUH was 67,760 persons. The public use 

file contains 55,602 records due to a subsampling step used in the disclosure 

protection procedures. 

5-153 
National Survey on Drug Use and Health (NSDUH) 

(continued) 

From the public use 2004 data: 

AI/AN (coded as Non-Hispanic Native American/Alaska Native): 784 

NH/PI (coded as Non-Hispanic NH/PI): 218 

Geographic 

Scope: 

The geographic scope of the study is national. Geographic indicators available on 

the public-use file include Metropolitan Statistical Area (MSA) with 1 million or 

more people, MSA with less than 1 million people, and not in MSA. 

Date or 

Frequency: 

This is an annual study that has been collected from 1971 to the present. The most 

recent year of available data is 2004. Data from the previous year's collection are 

typically released in September of the following year. Data from 2005 are 

expected to be released in September 2006. 

Data Collection 

Methodology: 

The NSDUH is administered in-person by field interviewers at respondents' 

residences. 

Participation: Optional, with incentives 

Response Rate: The study yielded a weighted screening response rate of 91 percent and a 

weighted interview response rate for the computer assisted personal interview 

(CAPI) of 77 percent. 

Sampling 

Methodology: 

The NSDUH uses a multistage area probability sample for each of the 50 states 

and the District of Columbia. The 2004 sample design is a continuation of the 

coordinated five-year sample design that increases the precision of estimates in 

year-to-year trend analysis. The sample is stratified on multiple levels, beginning 

with states. The second level of stratification divides states into field interviewer 

(FI) regions. For the first stage of sampling, each FI region is partitioned into 

small geographic areas composed of adjacent census blocks (segments). 

Systematic sampling is then used to select the allocated sample of addresses from 

each segment. The sample design includes approximately equal numbers of 

persons in the following age groups: 12-17, 18-25, and 26 and older. 

Analysis: There are three different analysis weights available with the 2004 NSDUH data. 

One weight is used when analyzing variables asked of all respondents. The others 

are used when analyzing data asked only of a subgroup of respondents (resulting 

from a complex split-sample design). Detailed instructions for applying these 

weights for analysis can be found at 

http://www.icpsr.umich.edu/SDA/SAMHDA/04373-

0001/CODEBOOK/4373.htm. 

Strengths: Data are collected on a key policy issue, health. There are multiple years of data 

available. The 2004 NSDUH is specifically designed to facilitate precise trend 

analysis using prior years of the survey data. 

5-154 
National Survey on Drug Use and Health (NSDUH) 

(continued) 

Limitations: The NSDUH does not collect data from persons who are homeless who do not 

stay at shelters, active duty military personnel, and persons housed in jails or 

hospitals. 

Access 

Requirements 

and Use 

Restrictions: 

Data sets are available to the public at no cost. 

Contact 

Information: 

Data and documentation can be downloaded at: 

http://webapp.icpsr.umich.edu/cocoon/SAMHDA-STUDY/04373.xml 

Data Archive Information: 

Substance Abuse and Mental Health Data Archive (SAMHDA) 

SAMHDA Helpline: (888) 741-7242 

Local: (734) 615-9524 

Fax: (734) 647-8200 

e-mail: samhda-support@icpsr.umich.edu 

SAMHDA/ICPSR 

The University of Michigan 

P.O. Box 1248 

Ann Arbor, MI 48106-1248 

U.S.A. 

General Inquiries should be addressed to: 

Joe Gustin 

Assistant Project Officer 

DHHS/SAMHSA/OAS 

1 Choke Cherry Road, Room 7-1020 

Rockville, MD 20857 

e-mail: Joe.Gustin@samhsa.hhs.gov 

http://www.oas.samhsa.gov/nsduh.htm 

5-155 
National Vital Statistics System: Linked Birth-Infant Death (NVSS-I) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC)/National Center for Health Statistics (NCHS) 

Description: The National Vital Statistics System Linked Birth-Infant Death (NVSS-I) 

research data set is comprised of linked birth and death certificates for infants 

born in the United States, Puerto Rico, the Virgin Islands, and Guam who died 

before reaching 1 year of age. In this data set, information from the death 

certificate is linked with information from the birth certificate for each infant. The 

purpose of this linkage is to use the many additional variables available from the 

birth certificate in infant mortality analysis. The birth certificate is the primary 

source of demographic information, such as age, race, and Hispanic origin of the 

parents; maternal education; live birth order; and mother’s marital status; and of 

maternal and infant health information, such as birthweight, period of gestation, 

plurality, prenatal care usage, and maternal smoking, etc. Analysis of this 

information can provide insight into the major factors influencing infant mortality 

in the United States. This system of linked records was established in 1983. 

Relevant Policy 

Issues: 

Measurement of Health Status, Health Disparities. 

Data Type(s): Registry 

Unit of 

Analysis: 

Individual 

Identification The majority of the demographic information is obtained from the birth 

certificate. Below is an example of the race question as it appears on the U.S. 

Standard Certificate of Live Birth: 

of AI/AN/NA: 

MOTHER’S RACE (Check one or more races to indicate what the mother 

considers herself) 

• White 

• Black or African American 

• American Indian or Alaska Native (AI/AN) and (Name of the enrolled or 

principal tribe) 

• Asian Indian 

• Chinese 

• Filipino 

• Japanese 

• Korean 

• Vietnamese 

• Other Asian (Specify) 

• Native Hawaiian (NH) 

• Guamanian or Chamorro 

• Samoan 

5-156 
National Vital Statistics System: Linked Birth-Infant Death (NVSS-I) 

(continued) 

• Other Pacific Islander (OPI) (Specify) 

• Other (Specify) 

Beginning in 2003, the number of births for any of the Asian /Pacific Islander 

subgroups is no longer available. Please see the NVSS report entitled Births: 

Final Data for 2003 for an explanation: 

http://www.cdc.gov/nchs/data/nvsr/nvsr54/nvsr54_02.pdf 

AI/AN/NA 

Population in 

Data Set: 

From the 2003 linked file (National Vital Statistics Report, Volume 54, Number 

16): 

Race of Mother is American Indian (AI) 

Births: 43,054 (N=4,090,007) 

Infant deaths: 376* (N=27,995) 

Neonatal deaths: 196 (N=18,935) 

Post-neonatal deaths: 180 (N=9,060) 

*Infant deaths are weighted, so numbers may not exactly add to totals due to 

rounding. 

From the 2002 linked file (National Vital Statistics Report, Volume 53, Number 

10): 

Race of Mother is Hawaiian (NH) 

Births: 6,772 (N=4,021,825) 

Infant deaths: 65* (N=27,970) 

Neonatal deaths: 38 (N=18,791) 

Post-neonatal deaths: 27 (N=9,179) 

*Infant deaths are weighted, so numbers may not exactly add to totals due to 

rounding. 

AI/AN/NA 

Subpopulations: 

Based on available reports, identification for Native Hawaiians is possible for 

some years of data linkage (e.g., 2002). 

Geographic 

Scope: 

Geographic scope of the data is national. Place of birth and place of death are 

classified by state and county. In residence classification of the birth, all births are 

allocated to the usual place of residence of the mother as reported on the birth 

certificate and are classified by state, county, and city. In residence classification 

of the death, all deaths are allocated to the usual place of residence of the 

decedent as reported on the death certificate and are classified by state, county, 

and city. Counties and cities of 250,000 persons or more are identified in the 

linked data set. Geographic classification for the linked data set is based on the 

1980 census enumeration. 

Date or 

Frequency: 

Linked files are available for the data years 1983-91 and 1995-2002. Linked file 

data were not produced for the 1992-94 data years. Future data years will be 

available annually. 

Data Collection 

Methodology: 

Vital statistics are provided through state-operated registration systems. 

Administrative records pertaining to death certificates are completed by 

5-157 
National Vital Statistics System: Linked Birth-Infant Death (NVSS-I) 

(continued) 

physicians, coroners, medical examiners, and funeral directors. Administrative 

records pertaining to birth certificates are completed by physicians and midwives. 

These records are filed with state vital statistics offices and selected statistical 

information is forwarded to NCHS to be merged into a national statistical file. 

Participation: Mandatory 

Strengths: Data sets contain a moderate number of AI/AN/NA respondents. There are 

multiple years of data available. 

Limitations: There is limited documentation available for this study, so it is difficult to know 

which subpopulations of key interest can be examined separately using the data 

files. For example, in the 2002 report, Hawaiians are reported separately, but they 

are not reported separately in the 2003 report. 

Access 

Requirements 

and Use 

Restrictions: 

Linked Birth and Infant Death public use data are available for the years 1983-91 

and 1995-98 on CD-ROM. The Linked Birth and Infant Death CD-ROM can be 

purchased through the National Technical Information Service (NTIS) and/or the 

Government Printing Office (GPO). As prices vary, contact NTIS or GPO for 

current pricing. 

Contact 

Information: 

Reproductive Statistics Branch 

Division of Vital Statistics 

National Center for Health Statistics 

Centers for Disease Control and Prevention 

3311 Toledo Road, Room 7417 

Hyattsville, Maryland 20782 

(301) 458-4356 

5-158 
National Vital Statistics System: Mortality (NVSS-M) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC)/Coordinating Center for Health Information and 

Service (CCHIS)/National Center for Health Statistics (NCHS) 

Description: The National Vital Statistics System Mortality (NVSS-M) data set is generated 

from death certificate information collected through the National Vital Statistics 

System, an inter-governmental collaboration between NCHS and the 50 states, 

two cities, and five territories. The NVSS-M data serve as the primary source of 

information on demographic, geographic, and cause-of-death information among 

persons dying in a given year. Data are available on an annual basis. Variables 

include the following: year, month, and day of week of death; place of death; 

residence of decedent (state, county, city, population size, standard metropolitan 

statistical area, metropolitan and nonmetropolitan counties); state and county of 

occurrence; demographic information on decedent (e.g., age at death, education, 

Hispanic origin, marital status, race, sex, state of birth); underlying cause of 

death; and multiple causes of death. 

Relevant Policy 

Issues: 

Measurement of Health Status, Key Health Disparities. 

Data Type(s): Registry 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Races available on public use data sets: 

• White 

• Black 

• American Indian (includes Aleuts and Eskimos) 

• Chinese 

• Japanese 

• Hawaiian (includes Part-Hawaiian) 

• Filipino 

• Asian Indian 

• Korean 

• Samoan 

• Vietnamese 

• Guamanian 

• Other Asian or Pacific Islander* 

• Combined other Asian or Pacific Islander** 

* Other Asian or Pacific Islander includes any Asian or Pacific Islander (API) 

group that is not included and does not easily fall into one of the API categories 

listed above. 

5-159 
National Vital Statistics System: Mortality (NVSS-M) 

(continued) 

** The "Combined Other Asian or Pacific Islander" category are death records in 

which more than one API category was listed under "race" on the death certificate 

(multiple race deaths). This category was introduced with the 2003 data. Most of 

the deaths in this category come from California and Hawaii (98.3 percent of the 

category). 

AI/AN/NA 

Population in 

Data Set: 

The numbers below represent the 2003 NVSS-M public use data set: 

Total number of records: 2,452,154 

White: 2,106,697 

Black: 291,706 

American Indian: 13,160 

Chinese: 8,831 

Japanese: 5,920 

Hawaiian: 594 

Filipino: 7,557 

Asian Indian: 2,542 

Korean: 2,548 

Samoan: 404 

Vietnamese: 2,024 

Guamanian: 159 

Other Asian or Pacific Islander: 8,438 

Combined other Asian or Pacific Islander: 1,574 

AI/AN/NA 

Subpopulations: 

AI/AN/NA subpopulations identified are: 

• Native Hawaiian alone (in detailed data only) 

• Samoan (in detailed data only) 

• Guamanian (in detailed data only) 

Geographic 

Scope: 

The geographic scope of the data includes national, region, state and counties 

with population of 100,000 or more. 

Date or 

Frequency: 

Public use data sets from 1968 through 2003 are available. 

Data Collection 

Methodology: 

Data from all death certificates filed in the United States are compiled into an 

annual file, except for 1972 when only a 50 percent sample was compiled. 

Participation: Mandatory 

Strengths: Data sets may contain a large number of AI/AN/NA respondents. There are 

multiple years of data available. 

Limitations: The primary weaknesses of these data sources are the quality of the race/ethnicity 

data. Because data are extracted from death certificates, the race/ethnicity 

category is not self-reported and is often completed by a funeral director based on 

5-160 
National Vital Statistics System: Mortality (NVSS-M) 

(continued) 

information received from a family member/proxy on the race/ethnicity of the 

deceased individual. According to the NCHS, these data are particularly poor for 

the American Indian/Alaska Native category, as data quality checks of the 

racial/ethnic distribution of the deceased in this category are lower than the 

distribution represented in Census estimates. 

The Indian Health Service (IHS) conducted a study on racial misclassification of 

mortality data and produced adjustments to apply to the rates to compensate for 

the misreporting of AI/AN race on the state death certificates. This study found 

that misidentification varies substantially among states and the IHS service areas. 

IHS now adjusts the NVSS-M data to correct this misidentification and presents 

both adjusted and unadjusted data in two major IHS publications entitled: 

Regional Differences in Indian Health and Trends in Indian Health. (The reports 

are currently being updated to include the latest adjustment factors.) 

Access 

Requirements 

and Use 

Restrictions: 

Public use data sets are available at no cost. Potential users are advised to contact 

the Mortality Statistics Branch at (301) 458-4666. 

Data on injury deaths for the race categories “American Indian/Alaskan Native” 

and “Asian/Pacific Islander” are available from CDC’s web-based Injury 

Statistics Query and Reporting System (WISQARS) at: 

http://www.cdc.gov/ncipc/wisqars/ 

Contact 

Information: 

General Contact for Mortality statistics data: 

Robert N. Anderson, Ph.D. 

Branch Chief, Mortality Statistics Branch 

Division of Vital Statistics 

National Center for Health Statistics 

Centers for Disease Control and Prevention 

3311 Toledo Rd., Room 7318 

Hyattsville, Maryland 20782 

(301) 458-4073 

For information on accessing mortality files, contact: Ken Kochanek (301) 458-

4319 

5-161 
National Vital Statistics System: Natality (NVSS-N) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC)/National Center for Health Statistics (NCHS) 

Description: The National Vital Statistics System Natality (NVSS-N) public-use data file 

comprises records of all documented births occurring within the United States. 

Data from all birth certificates filed in each state are included in this file. 

Specifically, these data cover the following information: residence of mother 

(e.g., population size of residence community, standard metropolitan statistical 

area, metropolitan and nonmetropolitan counties); demographic information about 

parents (e.g., race of parents, age of parents, education of mother and father, 

pregnancy/childbearing history of mother, marital status of mother); information 

on the infant (e.g., race, sex, Apgar scores at 5 minutes after birth, total-birth 

order); and information on the birth [e.g., place of birth, place of delivery, birth 

date (month/day), birth weight (in grams), gestation period, and prenatal care]. 

Relevant Policy 

Issues: 

Measurement of Health Status, Key Health Disparities, and Factors Contributing 

to Measured Health Disparities. 

Data Type(s): Registry 

Unit of 

Analysis: 

Individual 

Identification Data are coded into the following categories: 

of AI/AN/NA: 

• White 

• Black 

• American Indian/Alaska Native (AI/AN) 

• Asian/Pacific Islander (microdata early than 2003 are subdivided into: 

Chinese, Japanese, Filipino, Hawaiian, Other API) 

There are no detailed breakdowns for any of the Asian/Pacific Islander subgroups 

after 2002. Please see the NVSS Report "Births: Final Data for 2003" for an 

explanation: http://www.cdc.gov/nchs/data/nvsr/nvsr54/nvsr54_02.pdf 

Beginning 2003, data are available for selected states for multiple race reporting 

for the mother and the father. As of the 2004 data year, 15 states reported multiple 

race responses to NCHS. Because most states do not report multiple race, it is 

necessary to “bridge” the multiple race responses to single race, following a 

special algorithm developed by NCHS in cooperation with the Census Bureau and 

with support from the National Cancer Institute. A large proportion of births to 

American Indian and Hawaiian women in particular are to women reporting more 

than one race. Detailed verbatim and checkbox entries for multiple race persons 

are available on the natality files by request. 

5-162 
National Vital Statistics System: Natality (NVSS-N) 

(continued) 

AI/AN/NA 

Population in 

Data Set: 

Total number of births registered in the United States in 2004: 4,112,052 

AI/AN registered births in 2004: 43,927 

Geographic 

Scope: 

The geographic scope of the data is national. Geographic areas identified are 

state, county, city (if more than 100,000 population), standard metropolitan 

statistical area (SMSA), and metropolitan/nonmetropolitan counties. Additional 

analyses are possible by state, county, city (if more than 100,000 population), 

standard metropolitan statistical area (SMSA), metropolitan/nonmetropolitan 

counties. 

Date or 

Frequency: 

Data from all birth certificates are compiled into an annual file, except for the 

files for 1951-54, 1956-66, and 1968-71, when only a 50 percent sample was 

compiled, and 1967 when a 20- to 50-percent sample was compiled. Data for 

1972-84 are based on 100 percent of births for selected states and a 50 percent 

sample for all other states. 

Data Collection 

Methodology: 

Data from all birth certificates are compiled into an annual file, except for the 

files 1972, 1981 and 1982 when only a 50 percent sample was compiled. 

Participation: Mandatory for NCHS to compile a national data set; state participation is based 

on the Vital Statistics Cooperative Program of the National Vital Statistics 

System. 

Strengths: Data sets contain a large number of AI/AN respondents. Data are collected on key 

health issues. There are multiple years of data available. 

Limitations: Of the Pacific Islander population groups, only Native Hawaiians as either a 

single- or multiple-race category can be separately identified in the microdata. 

Access 

Requirements 

and Use 

Restrictions: 

The data set is available to the public on CD-ROM at no charge from 

births@cdc.gov or by contacting the office listed below. 

Contact 

Information: 

Information on the Public Use Files and instructions for obtaining files can be 

located at http://www.cdc.gov/nchs/products/elec_prods/subject/natality.htm, or 

by contacting births@cdc.gov. 

For custom data requests, contact: 

Reproductive Statistics Branch Division of Vital Statistics 

National Center for Health Statistics 

Centers for Disease Control and Prevention 

3311 Toledo Road, Floor 7318 

Hyattsville, Maryland 20782 

(301) 458-4111 

births@cdc.gov 

5-163 
Panel Study of Income Dynamics (PSID) 

Sponsor: The Panel Study of Income Dynamics (PSID)'s original funding agency was the 

Office of Economic Opportunity of the United States Department of Commerce. 

The study's major funding source is now the National Science Foundation. 

Substantial additional funding has been provided by: the National Institute on 

Aging, the National Institute of Child Health and Human Development and the 

Office of the Assistant Secretary for Planning and Evaluation of the United States 

Department of Health and Human Services; the Economic Research Service of 

the United States Department of Agriculture; the United States Department of 

Housing and Urban Development; the United States Department of Labor; and 

the Center on Philanthropy at the Indiana University-Purdue University. 

Description: The PSID, begun in 1968, is a longitudinal study of a representative sample of 

U.S. individuals (men, women, and children) and the family units in which they 

reside. Its emphasis is on economics, but it also includes sociological and 

psychological measures. 

Relevant Policy 

Issues: 

Income Status, Unemployment Rates, Economic Assistance Program 

Participation Rates, Economic Opportunity, Measures of Well-being for 

Families/households, Measures of Well-being for Children, Measures of Wellbeing for Elders, and Housing Ownership. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Instructions for reporting race are as follows: “In order to get an idea of the 

different races and ethnic groups that participate in the study, I would like to ask 

you about your background. Are you: 

• White 

• Black 

• Native American (NA) 

• Asian 

• Pacific Islander 

• Another race 

Up to four choices were recorded. 

AI/AN/NA 

Population in 

Data Set: 

There are 7,822 families in the full 2003 data set. The unweighted count for NA 

male heads of households of these families is 136 (41 are NA alone and 95 are 

NA and other races). The unweighted count for wives of heads of households in 

the 2003 wave of the PSID is 39 (24 are NA alone and 15 are NA and other 

races). 

(Pacific Islanders are combined with Asians into a single group, so no separate 

count of this group is possible.) 

5-164 
Panel Study of Income Dynamics (PSID) 

(continued) 

Geographic 

Scope: 

The geographic scope of the study is national. The public release files contain 

geographic information such as region, state of residence, size of largest city in 

the county of residence, and the Beale rural-urban code. The Beale rural-urban 

code includes the following categories: 

• Fringe counties of metropolitan areas of 1 million population or more 

• Counties in metropolitan areas of 250,000 to 1 million population 

• Counties in metropolitan areas of less than 250,000 population 

• Urban population of 20,000 or more, adjacent to metropolitan area 

• Urban population of 20,000 or more, not adjacent to a metropolitan area 

• Urban population of less than 20,000, adjacent to a metropolitan area 

• Urban population of less than 20,000, not adjacent to a metropolitan area 

• Completely rural, adjacent to a metropolitan area 

• Completely rural, not adjacent to a metropolitan area 

The data allow geographic analysis at all these levels. 

Date or 

Frequency: 

Between 1968 and 1997, PSID data were collected every year. Starting in 1999, 

the PSID collected data biennially (i.e., every other year). All waves of data 1968-

2003 are available on the website. The 2005 data will be released by December 

31, 2006. The next wave of the PSID will be conducted in 2007. 

Data Collection 

Methodology: 

The PSID was collected in face-to-face interviews using paper and pencil 

questionnaires between 1968 and 1972. Thereafter, the majority of interviews 

were conducted over the telephone. In 1993, the PSID introduced the use of 

computer assisted telephone interviewing. In the 1999 wave, 97.5 percent of the 

interviews were conducted over the phone, and all interviews were conducted 

using computer-based instruments. 

Participation: Optional, with incentives 

Response Rate: Since 1969, annual response rates have ranged between 96.9 and 98.5 percent. 

Sampling 

Methodology: 

The initial sample for the PSID consisted of two independent samples: a crosssectional, national sample (based on stratified multistage selection of the civilian 

noninstitutional population of the U.S.) and a national sample of low-income 

families. Both samples are probability samples. However, when the two samples 

are combined the result is a sample with unequal selection probabilities, and as a 

result compensatory weighting is needed in estimation. 

Strengths: Data are collected on key policy issues, including economic status and child wellbeing. There are multiple years of data available. Documentation of the content 

and implementation of the PSID is comprehensive and available on-line. 

Limitations: There are a very small number of AI/AN/NA respondents. Asians and Pacific 

Islanders are collapsed into a single result category in all PSID data sets. 

5-165 
Panel Study of Income Dynamics (PSID) 

(continued) 

Access 

Requirements 

and Use 

Restrictions: 

Data set is available to the public at no cost. 

Contact 

Information: 

The data set is available from the following website: http://simba.isr.umich.edu/. 

For general assistance, contact: 

PSID Staff 

The Panel Study of Income Dynamics 

Institute for Social Research 

PO Box 1248 

Ann Arbor, MI 48106-1248 

psidhelp@isr.umich.edu

5-166 
Pediatric Nutrition Surveillance System (PedNSS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC)/National Center for Chronic Disease Prevention 

and Health Promotion/Division of Nutrition and Physical Activity/Maternal and 

Child Nutrition Branch 

Description: The Pediatric Nutrition Surveillance System (PedNSS) is a child-based public 

health surveillance system that monitors the nutritional status of low-income 

children in federally funded maternal and child health programs. Data on 

birthweight, breastfeeding, anemia, short stature, underweight, and overweight 

are collected for children who attend public health clinics for routine care, 

nutrition education, and supplemental food. Data are collected at the clinic level 

then aggregated at the state level and submitted to CDC for analysis. Online 

national PedNSS data are available as published tables. State-level online tables 

are also available for both California and West Virginia in addition to online 

national-level tables. 

Relevant Policy 

Issues: 

Measurement of Health Status, Disease-specific Measurements, Health 

Disparities, and Measures of Well-being for Children. 

Data Type(s): Program reporting data. Data are collected from children enrolled in federally 

funded programs that serve low-income children, including the Special 

Supplemental Nutrition Program for Women, Infants, and Children (WIC) and 

non-WIC programs that include the Early and Periodic Screening, Diagnosis, and 

Treatment (EPSDT) Program and the Title V Maternal and Child Health 

Program. 

Unit of 

Analysis: 

Individual (unique child records) 

Identification 

of AI/AN/NA: 

Data include the following racial/ethnic categories: 

 

• White, not Hispanic 

• Black, not Hispanic 

• Hispanic 

• American Indian/Alaska Native (AI/AN) 

• Asian/Pacific Islander 

• All Other 

AI/AN/NA 

Population in 

Data Set: 

For 2004, the total number of individual children was 6,822,769. Of these, 77,915 

were identified as AI/AN. 

AI/AN/NA 

Subpopulations: 

State data are broken out by race and include some tribe identifiers: Cheyenne 

River Sioux (SD), InterTribal Council of Arizona, Rosebud Sioux Tribe (SD), 

Chickasaw Nation (OK), Wichita-Caddo-Delaware (OK), Navajo Nation (AZ), 

Standing Rock Sioux Tribe (ND). 

5-167 
Pediatric Nutrition Surveillance System (PedNSS) 

(continued) 

Geographic 

Scope: 

PedNSS is a national surveillance system. PedNSS Surveillance data are reported 

from contributors (defined as a state, U.S. territory, or tribal government). In 

2004, a total of 48 contributors, including 40 states, the District of Columbia, 

Puerto Rico, and 7 tribal governments, participated in PedNSS. PedNSS is a 

voluntary surveillance system. 

Online geographic analysis is possible through review of published tables of 

national data and for two states at the websites listed below: 

California has its data available at the following website: 

http://www.dhs.ca.gov/pcfh/cms/onlinearchive/pdf/chdp/informationnotices/2003

/chdpin03q/contents.htm. 

West Virginia provides state-specific data from 1996 - present 

http://www.wvdhhr.org/ons/surveillance.asp. 

Date or 

Frequency: 

Trend data tables present data from 1995 – 2004. 

Data Collection 

Methodology: 

Federally funded health clinics serving low-income children participate on a 

voluntary basis and report data to state-level agencies, which in turn submit data 

to the CDC. These data are combined for annual reporting. 

Participation: Optional, without incentives 

Strengths: Registry contains a large number of AI/AN/NA respondents. Data are collected 

on key policy issues, including health and child welfare. There are multiple years 

of data available. 

Limitations: Pacific Islanders are not separated from Asians. Not all states, or federally funded 

clinics within states, participate in this surveillance system; therefore, data are not 

representative of all children served by programs such as the Special 

Supplemental Nutrition Program for Women, Infants, and Children (WIC); Early 

and Periodic Screening, Diagnostic, and Treatment Services (EPSDT); and other 

Maternal and Child Health Bureau programs. 

Access 

Requirements 

and Use 

Restrictions: 

National data set is not available to the public, but published tables and reports 

are available. 

Contact 

Information: 

National PedNSS data tables can be accessed through the following website: 

http://www.cdc.gov/pednss. State-level data for California and West Virginia are 

available. See above for information on Internet locations of these data. 

5-168 
Pregnancy Nutrition Surveillance System (PNSS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC) 

Description: PNSS is a program-based public health surveillance system that monitors risk 

factors associated with infant mortality and poor birth outcomes among lowincome pregnant women who participate in federally funded public health 

programs including Special Supplemental Nutrition Program for Women, Infants, 

and Children (WIC), and Title V, the Maternal and Child Health Program 

(MCH). Data include indicators of maternal health and maternal health behavior 

including pre-pregnancy weight status, parity, and diabetes. National PNSS data 

are available as published tables. States have the option of making the data 

publicly available. North Carolina, California, and West Virginia make state data 

available for download through the Internet. 

Relevant Policy 

Issues: 

Measurement of Health Status, Disease-specific Measurements, and Health 

Disparities. 

Data Type(s): Program reporting data 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

The racial/ethnic categories used in this data set include the following: 

• White, not Hispanic 

• Black, not Hispanic 

• Hispanic 

• American Indian/Alaska Native (AI/AN) 

• Asian/Pacific Islander 

• All Other 

AI/AN/NA 

Population in 

Data Set: 

Of the 856,123 total records in 2004, 11,686 were identified as AI/AN. 

AI/AN/NA 

Subpopulations: 

State data are broken out by race and include some tribe identifiers: Cheyenne 

River Sioux (SD), InterTribal Council of Arizona, Rosebud Sioux Tribe (SD), 

Chickasaw Nation (OK), Navajo Nation (AZ), Standing Rock Sioux Tribe (ND). 

Geographic 

Scope: 

PNSS is a national surveillance system. Other geographic identifiers include 

states (all except for Washington, Alaska, New Mexico, Oklahoma, Texas, 

Virginia, North Carolina, Connecticut, Massachusetts, Mississippi, Arizona) and 

selected tribes (see above). 

5-169 
Pregnancy Nutrition Surveillance System (PNSS) 

(continued) 

Geographic analysis is possible at the national level through review of the 

published tables. Additionally, California has its data available at the following 

website: 

http://www.dhs.ca.gov/pcfh/cms/onlinearchive/pdf/chdp/informationnotices/2003

/chdpin03q/contents.htm. 

North Carolina provides state-specific data from 1997 - present 

http://www.nutritionnc.com/nutrsurv.htm. 

West Virginia provides state-specific data from 1998 - present 

http://www.wvdhhr.org/ons/surveillance.asp. 

Date or 

Frequency: 

Trend tables present data from 1994 – 2003. 

Data Collection 

Methodology: 

Federally funded health clinics serving pregnant women participate on a 

voluntary basis and report data to state-level agencies, which in turn submit the 

data to the CDC. These data are combined for annual reporting. 

Participation: Optional, without incentives 

Strengths: Registry contains a large number of AI/AN/NA respondents. Data are collected 

on key policy issues, including health, particularly maternal risk factors 

associated with infant mortality and peer birth outcomes. There are multiple years 

of data available. 

Limitations: Pacific Islanders are not separated from Asians. Not all states, or federally funded 

clinics within states, participate in this surveillance system; therefore, data are not 

representative of pregnant women served by programs such as the Special 

Supplemental Nutrition Program for Women, Infants, and Children (WIC); Early 

and Periodic Screening, Diagnostic, and Treatment Services (EPSDT); and other 

Maternal and Child Health Bureau programs. 

The racial/ethnic distribution of individuals served by contributing clinics is 

presented by state and for some tribes; however, there is no such geographic 

breakdown for any of the health indicators collected in the data source in the 

published tables. 

Access 

Requirements 

and Use 

Restrictions: 

National data set is not available to the public, but published tables and reports 

are available. 

Contact 

Information: 

Data tables can be accessed through the following website: 

http://www.cdc.gov/pednss/pnss_tables/index.htm 

State-level data are available from North Carolina, California, and West Virginia. 

See above for Internet locations of these data. 

5-170 
Pregnancy Risk Assessment Monitoring System (PRAMS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC) 

Description: The Pregnancy Risk Assessment Monitoring System (PRAMS) was initiated in 

1987 to monitor maternal experiences and attitudes before, during, and shortly 

after pregnancy to better understand adverse outcomes of mothers and infants. 

PRAMS collects the following data: state, most core birth certificate variables 

(not included are birth certificate number; specific date of the month in the 

infant's date of birth, mother's date of birth, and mother's date of last menses; 

county of residence; and hospital of birth). On a monthly basis, a sample of 

women (approximately 1,300-3,400 women per state) who are state residents and 

have delivered a live-born infant during the preceding 2-4 months are randomly 

selected (with an oversample of women at higher risk for adverse pregnancy 

outcomes) from a file of birth certificate records and mailed a questionnaire. Core 

questions in this instrument include: 

• Attitudes and feelings about the most recent pregnancy, 

• Content and source of prenatal care, 

• Maternal alcohol and tobacco consumption, 

• Physical abuse before and during pregnancy, 

• Pregnancy-related morbidity, 

• Infant health care, 

• Contraceptive use, and 

• Mother's knowledge of pregnancy-related health issues, such as adverse 

effects of tobacco and alcohol; benefits of folic acid; and risks of HIV. 

Thirty–seven states, New York City, and Yankton Sioux Tribe of South Dakota 

currently participate in PRAMS. 

Relevant Policy 

Issues: 

Measurement of Health Status, Disease-specific Measurements, Key Health 

Disparities, and Factors Contributing to Well-being Disparities of Children. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Race is identified in the data set in the following categories: 

• White 

• Black 

• American Indian or Alaska Native (AI/AN) 

• Asian/Pacific Islander (subdivided into: Chinese, Japanese, Filipino, 

Hawaiian, Other API) 

5-171 
Pregnancy Risk Assessment Monitoring System (PRAMS) 

(continued) 

AI/AN/NA 

Population in 

Data Set: 

An overall total number of AI/AN/NA respondents in the data sets was not 

available. However, an analysis of 8 PRAMS participating states (see link below) 

indicated that several states have a sample of 30 or greater American 

Indian/Alaska Native respondents. This suggests that for analyses aggregated to 

the national level, there is sufficient sample size for analyses by AI/AN. 

http://www.cdc.gov/mmwr/preview/mmwrhtml/ss5304a1.htm. 

Geographic 

Scope: 

Thirty–seven states, New York City, and the Yankton Sioux Tribe of South 

Dakota currently participate in PRAMS. Six other states previously participated. 

The currently participating states are Alabama, Alaska, Arkansas, Colorado, 

Delaware, Florida, Georgia, Hawaii, Illinois, Louisiana, Maine, Maryland, 

Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Nebraska, New 

Jersey, New Mexico, New York, North Carolina, Ohio, Oklahoma, Oregon, 

Pennsylvania, Rhode Island, South Carolina, Tennessee, Texas, Utah, Vermont, 

Virginia, Washington, West Virginia, Wisconsin, and Wyoming. 

Date or 

Frequency: 

PRAMS data are available in annual files by individual participating state. The 

availability of years 1988 to 2004 varies. The 2004 data are the most recently 

available data set. Data availability by state and year can be reviewed at 

http://www.cdc.gov/prams/index.htm. 

Data Collection 

Methodology: 

PRAMS utilizes two sequential modes of data collection; a mailed questionnaire 

survey with multiple follow-up attempts to encourage response was followed by a 

telephone survey. 

Participation: Optional, without incentives. 

Response Rate: The following reference notes that the median response rate across participating 

states was 76 percent among surveyed mothers: The Pregnancy Risk Assessment 

Monitoring System (PRAMS): Current Methods and Evaluation of 2001 Response 

Rates. Public Health Rep. 2006 Jan-Feb;121(1):74-83. 

Sampling 

Methodology: 

Each participating state draws a stratified systematic sample of 100 to 250 new 

mothers every month from a frame of eligible birth certificates (mother recently 

gave live birth), with most states oversampling low birth weights. 

Analysis: The PRAMS data set includes weights to adjust for non-response bias and to help 

generate accurate standard errors for estimates. Because PRAMS data also 

contains information from birth certificate data, there is basic information on 

women who did not respond to the survey, which allowed the research team to 

further refine the weights. A discussion of the methods can be accessed at 

http://www.cdc.gov/prams/methodology.htm. 

Strengths: There are multiple years of data available. Sample size appears to be sufficient for 

AI/AN analyses. 

5-172 
Pregnancy Risk Assessment Monitoring System (PRAMS) 

(continued) 

Limitations: Only 37 states plus New York City and 1 tribe participate in the PRAMS data 

collection effort, thus impacting the generalizability of estimates to the national 

level. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to the public through a data use agreement at no cost. A 

research proposal must be mailed or sent electronically to: 

 

Denise D’Angelo, MPH 

Applied Sciences Branch MS-K22, Division of Reproductive Health, 

Centers for Disease Control and Prevention 

4770 Buford Hwy, NE 

Atlanta GA 30341-3724 

DDAngelo@cdc.gov 

Proposal guidelines and review processes are available at: 

http://www.cdc.gov/prams/. 

Contact 

Information: 

PRAMS website: http://www.cdc.gov/prams. 

CDC/Division of Reproductive Health 

4770 Buford Hwy, NE 

MS K-20 

Atlanta, GA 30341-3717 

(770) 488-5200 

5-173 
Resource and Patient Management System (RPMS) and 

National Patient Information Reporting System (NPIRS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Indian Health Service 

(IHS) 

Description: The Resource and Patient Management System (RPMS) is an IHS-wide system 

designed to provide detailed and comprehensive clinical and administrative 

information to providers and managers at all levels of the Indian health system in 

order to allow them to better manage individual patients, local facilities, regional 

and national programs. It has several components for reporting detailed 

information on patient characteristics, diagnoses, and specific services provided 

to those patients. RPMS is a decentralized automated information system of over 

50 integrated software applications with separate, individual databases at local 

sites. RPMS software modules fall into three major categories: (1) administrative 

applications that perform patient registration, scheduling, billing, and linkage 

functions; (2) clinical applications that support various healthcare programs 

within IHS; and (3) infrastructure applications. It has the capability to produce 

special reports, by individual provider, clinic, outpatient versus inpatient services, 

in addition to other output generated from patient-level records. Taken together, 

the RPMS components collect, store, and then display an extensive abstract of 

clinical and administrative information gathered during patient contacts. 

A smaller subset of this abstracted information is exported to the National Patient 

Information Reporting System (NPIRS), a national data warehouse designed to 

allow IHS to aggregate RPMS data from all their local sites to track clinical 

practice patterns and episodes of care, provide measures of quality of care and 

clinical outcomes, perform epidemiological studies, report on patient 

demographics and healthcare utilization patterns and provide data from which 

health care costs can be estimated. Data elements exported to NPIRS include 

certain patient demographics; encounter-based information such as the date, 

location of a visit (facility), provider, the “Purpose(s) of Encounter” using 

International Classification of Disease (ICD-9) codes, medications, and certain 

laboratory test data; and specific patient related clinical data such as health 

factors. 

Relevant Policy 

Issues: 

Measurement of Health Status, Disease-specific Measurements, and Factors 

Contributing to Measured Health Disparities. 

Data Type(s): Program enrollment data 

Unit of 

Analysis: 

Individual 

Identification In the reports that are requested from NPIRS, one can select only AI/AN 

individuals. The data also permit analyses of a variety of subpopulations, selected 

by geographic and other variables such as state, reservation, community, facility, 

tribal affiliation, gender, age group, etc. Tribes have the right to disapprove the 

release of data that would allow the identification of their tribe. 

of AI/AN/NA: 

5-174 
Resource and Patient Management System (RPMS) and 

National Patient Information Reporting System (NPIRS) 

(continued) 

AI/AN/NA 

Population in 

Data Set: 

RPMS system is in use at essentially all Indian Health Service facilities and at 

many tribal and some urban program sites, and therefore these local databases 

should have more than sufficient observations to facilitate detailed analyses. Most 

data pertains to AI/AN patients, although some is about non-AI/AN who obtain 

care at IHS, tribal, or urban sites for various reasons. NPIRS contains data on all 

RPMS registered patients and their encounters, but only for a specified subset of 

their RPMS data. NPIRS also contains similar data from a handful of tribal and/or 

urban sites who export data to NPIRS in an appropriate format. 

AI/AN/NA 

Subpopulations: 

Tribes have the right to approve data release with detailed subpopulation 

identifiers. Given tribal approval, one could examine the following 

subpopulations: American Indian alone, Alaska Native alone, or specific tribes 

and villages. 

Geographic 

Scope: 

IHS and tribally operated health care facilities are located in 35 states, while a 

handful of other states host urban Indian health programs. Geographic areas are 

identified by state and community. Geographic analysis is available by state, or 

each individual’s tribal affiliation (pending approval by tribe during data request). 

Date or 

Frequency: 

Data are continually fed into the RPMS system as patients are served. At sites 

where data entry into RPMS is performed by clerks from paper encounter forms 

that providers complete, there can be delays in this data entry that range from 

days to months. Data from the local RPMS systems are periodically exported to 

NPIRS. The frequency of these exports from local sites can vary from daily at the 

largest sites to once a year from a few smaller sites. 

Data Collection 

Methodology: 

Participating IHS facilities and providers implement the RPMS software system 

and input data into the system. Data are then linked into the broader IHS database 

which can be tapped for research purposes. 

Participation: Optional, with incentives for programs (technical support provided) 

Strengths: Data sets contain a large number of AI/AN/NA respondents. Data are collected on 

key policy issues including health. There are multiple years of data available. The 

RPMS data source is a very powerful tool for examining detailed health and 

utilization information for individuals using the IHS system over time. It contains 

comprehensive encounter data not otherwise collected through surveys and 

includes most IHS providers. 

Limitations: RPMS can only report on patients who use IHS facilities and providers and 

therefore may have some gaps in the overall health experience and utilization of 

AI/AN patients. 

Access 

Requirements 

and Use 

Restrictions: 

The data are not available to those outside the agency in raw form, but users can 

request special data analyses. NPIRS is almost entirely outsourced (provided by a 

contractor under a contract with IHS), so depending on the scope and complexity 

of the request the user may or may not have to pay any associated costs. Users 

5-175 
Resource and Patient Management System (RPMS) and 

National Patient Information Reporting System (NPIRS) 

(continued) 

can send data request forms to the Statistics Program at the Office of Program 

Support at the Indian Health Service (see address below). 

Contact 

Information: 

Statistics Program 

Office of Program Support 

Office of Public Health 

Indian Health Service 

12300 Twinbrook Parkway, Suite 450 

Rockville, Maryland 20852 

Telephone: (301) 443-1180 

Fax: (301) 443-4087 

The RPMS help desk for technical support with the RPMS system has staff who 

may be able to direct researchers to documents on the website and provide 

general information about RPMS data. However, the primary purpose of this help 

desk is for those who are implementing the RPMS system in their facility. 

The help desk can be contacted by telephone at (505) 248-4371 or (888) 830-

7280, or by email to support@ihs.gov. 

Main Website, geared primarily towards those who are implementing the RPMS 

system: 

http://www.ihs.gov/Cio/RPMS/index.cfm?module=home&option=index. 

5-176 
Runaway and Homeless Youth Management Information System (RHYMIS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Administration for 

Children and Families (ACF) 

Description: The Runaway and Homeless Youth Management Information System (RHYMIS) 

was designed to provide comprehensive information on youth served, issues that 

affect them and services provided for Runaway and Homeless Youth programs 

funded by the Family and Youth Services Bureau (FYSB). FYSB mandates that 

certain data be regularly collected and reported by its grantees. Current grantees 

must report on the profile of the youth and families they serve, and provide an 

overview of the services which they deliver under their grant programs. In order 

to assist grantees in their reporting responsibilities, FYSB funded the 

development of a Runaway and Homeless Youth Management Information 

System (RHYMIS). 

Relevant Policy 

Issues: 

Measures of Well-being for Children, Factors Contributing to Well-being 

Disparities of Children, Identification of Evidence-based Practices and Programs 

that Improve Child Well-being and are Generalizable/Replicable, and 

Homelessness. 

Data Type(s): Program reporting data 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Race and ethnicity are self reported by the youth. This sometimes results in 

multiple indications or "not provided" as responses. Below are the instructions 

provided to program staff on the data collection forms: 

"How does the youth describe himself/herself using these census categories? On 

the basis of the youth's self-perception, select one or more codes indicating the 

young person's race category and one code indicating their ethnicity category." 

The race categories are:

American Indian or Alaska Native (AI/AN): A person having origins in any of the 

original peoples of North and South America (including Central America) and 

who maintains tribal affiliation or community attachment. 

Asian: A person having origins in any of the original peoples of the Far East, 

Southeast Asia, or the Indian subcontinent including, for example, Cambodia, 

China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, 

and Vietnam. 

Black or African American: A person having origins in any of the black racial 

groups of Africa. 

Native Hawaiian or other Pacific Islander (NH/PI): A person having origins in 

any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands. 

5-177 
Runaway and Homeless Youth Management Information System (RHYMIS) 

(continued) 

White: A person having origins in any of the original peoples of Europe, the 

Middle East, or North Africa. 

AI/AN/NA 

Population in 

Data Set: 

For FY 2004:

TOTAL number of records in data set: 56,677 

AI/AN: 1,922 

NH/PI: 338 

AI/AN and some other race(s): 398 

NH/PI and some other race(s): 47 

For FY 2003:

TOTAL number of records in data set: 74,290 

AI/AN: 2,497 

NH/PI: 581 

AI/AN and some other race(s): 481 

NH/PI and some other race(s): 78 

Geographic 

Scope: 

The geographic scope of RHYMIS is national. State and regional identifiers are 

included in the data; therefore geographic analysis is possible at the state and 

regional levels. Although federally funded programs within all states submit data 

to RHYMIS, the data should not be used to produce state-wide estimates of 

runaway and homeless youth. RHYMIS data are only collected on youth who 

utilize federally funded programs under the Runaway and Homeless Youth Act. 

However, the data can be used to create state-level estimates of youth who use 

federally funded programs. 

Date or 

Frequency: 

RHYMIS is collected on a semi-annual basis. Due dates are listed as April 15th 

and October 15th. Data are released for a full fiscal year. Prior to FY 2002, 

sometimes fewer than 45-55 percent of participating programs reported fully to 

RHYMIS. For this reason, use of data prior to FY 2002 is discouraged by 

RHYMIS staff. RHYMIS was re-designed during FY 2001; as a result, all data 

beginning in FY 2002 is based on virtually a 100 percent response rate. 

Data Collection 

Methodology: 

Program staff utilize desktop software provided by FYSB to complete an intake 

and exit form for each youth serviced by the program. 

Participation: Mandatory 

Authorization: Authorization for RHYMIS falls under the Runaway and Homeless Youth Act as 

Reauthorized (2003) by 42 U.S.C. 5701. 

Strengths: This data set contains a large number of AI/AN/NA respondents. Data are 

collected on key policy issues, including (after 2004) history of involvement in 

the child welfare system (e.g., foster care experiences). Multiple years of 

complete data are available. Starting with the date range October 1, 2001 to the 

end of the most recent fiscal year (September 30, 2005), the data are virtually a 

100 percent complete report on all youth served by all FYSB-funded runaway and 

5-178 
Runaway and Homeless Youth Management Information System (RHYMIS) 

(continued) 

homeless youth agencies. Generally less than 1 percent of the grantees fail to 

report at all by the time the database is closed for a six-month reporting period. 

Limitations: There is little documentation available on the RHYMIS data. Studies that have 

used the RHYMIS data may discuss issues related to data quality, but ACF does 

not release a methodology report for data users. 

RHYMIS data should not be used to generate estimates for all runaway and 

homeless youth. RHYMIS data focus on youth who are served by federally 

funded programs under the Runaway and Homeless Youth Act. 

Access 

Requirements 

and Use 

Restrictions: 

NEO-RHYMIS is an online reporting system that contains complete data at the 

FYSB grantee level. Researchers interested in detailed RHYMIS research should 

contact the RHYMIS Hotline at (888) 749-6474. There are some limitations on 

use involving privacy issues. 

Contact 

Information: 

Director, Division of Research and Evaluation 

Family and Youth Services Bureau 

www.acf.hhs.gov/programs/fysb 

phone: (202) 205-8496; fax: (202) 690-5600 

Arlene Calabro, RHYMIS Support 

acalabro@csc.com 

(954) 472-4122 

Computer Sciences Corporation 

15245 Shady Grove Road 

Rockville, MD 20850 

5-179 
Small Area Income and Poverty Estimates (SAIPE) 

Sponsor: U.S. Department of Commerce/U.S. Census Bureau 

Description: The U.S. Census Bureau, with support from other federal agencies, created the 

Small Area Income and Poverty Estimates (SAIPE) program to provide more 

current estimates of selected income and poverty statistics than the most recent 

decennial census. Estimates are created for states, counties, and school districts. 

The main objective of this program is to provide updated estimates of income and 

poverty statistics for the administration of federal programs and the allocation of 

federal funds to local jurisdictions. 

The estimates are not direct counts from enumerations or administrative records, 

nor direct estimates from sample surveys. Data from those sources are not 

adequate to provide intercensal estimates for all counties. Instead, the relationship 

between income or poverty and tax and program data for the states and a subset of 

counties are modeled using estimates of income or poverty from the Annual 

Social and Economic Supplement (ASEC) to the Current Population Survey 

(CPS). The modeled relationships are then used to develop estimates for all states 

and counties. For school districts, the model-based county estimates and the 

decennial census distribution of the population in poverty of each county across 

its constituent school districts are used to create the estimates. 

Relevant Policy 

Issues: 

Income status. 

Data Type(s): Statistical database 

Unit of 

Analysis: 

Estimates developed for the SAIPE program are not at the individual level, 

therefore counts of the AI/AN/NA population in the data set are not available. 

The estimates, however, are available by county and school district (geographical 

units that may be of interest). Researchers could use other data sources to identify 

geographic areas with large concentrations of AI/AN/NA and then use SAIPE 

data to do analyses of these areas. 

Identification 

of AI/AN/NA: 

AI/AN/NA individuals are not identified in the data set. 

Geographic 

Scope: 

The geographic scope of the study is national. Geographic analysis is possible by 

state, county, and school district. 

Date or 

Frequency: 

State and county data are available for 1989, 1993, and 1995 – 2003. 

School district data are available for 1995, 1997, and 1999 – 2003. 

Data Collection 

Methodology: 

No data are collected. Models are developed on a periodic basis and then used to 

generate estimates. 

Authorization: The SAIPE program was developed when Congress called for authorization 

legislation requiring the Secretary of Commerce to develop the methodology to 

5-180 
Small Area Income and Poverty Estimates (SAIPE) 

(continued) 

produce "intercensal data relating to the incidence of poverty for each state, 

county, and local jurisdiction." The legislation further called for estimates of the 

number of children impovered age 5 to 17, for local education agencies (school 

districts) and of the number of impovered people age 65 and over for states and 

counties. In September 1994, the Congress passed the Improving America's 

Schools Act and signed it into law (PL 103-382). It reauthorized and amended the 

Elementary and Secondary Education Act. Authorization for SAIPE falls under 

this legislation. The No Child Left Behind Act of 2001 further amended the 

ESEA and required annual production of estimates for school districts. 

Strengths: The SAIPE program data provides estimates of income and poverty statistics 

based on more current data than other sources of information. 

Limitations: The type of information available from SAIPE is not diverse; it concerns only the 

number in poverty, poverty rates, and median household income information. 

SAIPE estimates are based on statistical models and are subject to modeling error. 

Other: The Small Area Health Insurance Estimates (SAHIE) program builds on the work 

of the SAIPE program. SAHIE was created to develop model-based estimates of 

health insurance coverage by age for counties and states. The SAHIE program has 

developed experimental estimates for counties and states for 2000 for the total 

population with and without health insurance coverage; children under age 18 

with and without health insurance coverage; and measures of uncertainty of the 

estimates. This type of county-level data on health insurance coverage are not 

available elsewhere because neither the decennial census nor the American 

Community Survey contain questions on this topic. More information about the 

SAHIE program can be found at: 

http://www.census.gov/hhes/www/sahie/index.html 

Access 

Requirements 

and Use 

Restrictions: 

These estimates are available to the public at no cost. 

Contact 

Information: 

Mail address: 

U.S. Census Bureau 

4700 Silver Hill Road 

Washington DC 20233-0001 

Telephone: 

For general questions about SAIPE, contact the Statistical Information Staff of the 

Data Integration Division at this phone number: (301) 763-3242. 

Location of the actual data: 

The data are available at the following website: 

http://www.census.gov/hhes/www/saipe/tables.html 

These data are also available via DataFerrett 

5-181 
Small Area Income and Poverty Estimates (SAIPE) 

(continued) 

Reports of 

Interest: 

Detailed information on SAIPE estimates and limitations concerning the use of 

these data are provided in three recent publications: 

1. Evaluation of School District Poverty Estimates: Predictive Models using IRS 

Income Tax Data. Jerry J. Maples and William R. Bell, Bureau of the Census, 

Washington DC 20233. 

(http://www.census.gov/hhes/www/saipe/asapaper/asa05finalmaples.pdf) 

2. Using Medicaid Participant Data in the Estimation of County Poverty Levels.

David S. Powers, U.S. Census Bureau, Small Area Estimates Branch, Housing 

and Household Economic Statistics Division, Room 1451, Building 3. 

(http://www.census.gov/hhes/www/saipe/asapaper/asa2005dpowers.pdf) 

3. Estimating School District Poverty with Free and Reduced Lunch Data. Craig 

Cruse and David Powers, U.S. Census Bureau, Small Area Estimates Branch, 

Room 1451-3. 

http://www.census.gov/hhes/www/saipe/publications.html. 

5-182 
Surveillance, Epidemiology, and End Results (SEER) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/National Institutes of 

Health (NIH)/National Cancer Institute (NCI) 

Description: The Surveillance, Epidemiology, and End Results (SEER) Program of the 

National Cancer Institute is responsible for the collection and reporting of cancer 

incidence and survival data from 15 population-based central cancer registries 

that cover 26 percent of the U.S. population. The U.S. racial/ethnic population 

coverage in SEER includes 23 percent of African Americans, 40 percent of 

Hispanics, 42 percent of American Indians and Alaska Natives, 53 percent of 

Asians, and 70 percent of Native Hawaiian and other Pacific Islanders. SEER 

data include patient demographic information as well as primary tumor site, 

tumor morphology and stage at diagnosis, first course of cancer treatment, and 

follow-up for vital status. SEER began collecting data on cancers diagnosed on 

January 1, 1973, which enables the analysis of longitudinal trends as well as 

current patterns of cancer. 

Relevant Policy 

Issues: 

Disease-specific Measurements and Health Disparities. 

Data Type(s): Registry 

Unit of 

Analysis: 

Cancer case (may be more that one cancer diagnosis per person in the database). 

Identification 

of AI/AN/NA: 

Detailed racial/ethnic information is collected for over 30 different racial/ethnic 

categories including, but not limited to: 

• White 

• Black 

• American Indian/Alaska Native (AI/AN) 

• Asian or Pacific Islander (e.g., Chinese, Japanese, Filipino, Native 

Hawaiian, Korean, ...others). 

• Hispanic/Latino 

AI/AN/NA 

Population in 

Data Set: 

The SEER database includes information on over six million in situ and invasive 

cancer cases with more than 350,000 cases being added each year. Of these, over 

28,000 cases are among AI/ANs. Geographic regions with large AI/AN 

populations in the publicly available SEER data include New Mexico, Alaska, 

California and the Seattle/Puget Sound area. 

AI/AN/NA 

Subpopulations: 

Tribal affiliation is not reported in SEER data, but geographic-specific data 

analyses may better characterize cancer patterns in specific AI/AN 

subpopulations. 

Geographic 

Scope: 

SEER covers geographically and demographically diverse populations in the U.S. 

including all residents of the states of CA, CT, HI, IA, KY, LA, NJ, NM, and UT; 

metropolitan areas of Atlanta, Detroit, Seattle; selected rural Georgia counties; 

5-183 
Surveillance, Epidemiology, and End Results (SEER) 

(continued) 

and AI/AN populations in AK and AZ. Available geographic identifiers within 

the database include registry (which covers either a state or a group of counties) 

and county. 

Date or 

Frequency: 

Data are available on an annual basis from 1973 to the present. 

Data Collection 

Methodology: 

Population-based cancer registries from state or metropolitan area or rural county 

grouping submit data to the National Cancer Institute for inclusion in the SEER 

database. The cancer patient data are collected from health providers such as 

hospitals, clinics, pathology labs, and physician offices as well as from autopsy 

reports and death certificates. The data are subjected to rigorous data quality edits 

and investigations and must meet data quality standards. The SEER Program data 

are considered the international standard for cancer registry data quality. 

Participation: Optional, without incentives. The population-based registries report their data 

through contracts or interagency agreements with the NCI. 

Strengths: Registries contain a large number of AI/AN/NA respondents including a region 

that is predominantly Alaska Native. Data are collected on key policy issues 

including health; for example, detailed data are collected on cancer type, stage, 

morphology, first course of treatment, survival, cause of death and patient 

demographics. There are multiple years of data available. 

Limitations: The SEER data are a definitive source of cancer incidence and survival data in the 

U.S., but coverage is limited to about 26 percent of the total U.S. population. 

Minority racial/ethnic groups, foreign-born, and urban populations are groups of 

special interest to the SEER program and are therefore somewhat overrepresented 

in the database. Although frequency distributions of tumor characteristics and 

observed survival may be generated for over 30 detailed racial/ethnic groups, 

incidence rate calculations are limited to the racial/ethnic groups for which 

population denominators are available from the Census Bureau. Incidence rates 

for AI/AN can be calculated for diagnoses in 1992 and later. 

Although AI/AN are well-represented in the database, the three states (AZ, CA, 

and AK) for which data for AI/AN are primarily collected are not necessarily 

representative of all AI/AN, since there is evidence that cancer incidence may be 

different in geographically distinct AI/AN populations. 

Other: Since 1994, the National Program of Cancer Registries (NPCR) has been funding 

state cancer registries to collect population-based cancer incidence data. Starting 

in 2001, NPCR began receiving data annually from funded programs with the 

goals of establishing the quality of the data and eventually releasing the data for 

use in public health planning. Currently, the United States Cancer Statistics on 

the NPCR website (www.cdc.gov/cancer/npcr/uscs) provides aggregate rates for 

states by race. Information on AI/AN cancer incidence is available for some 

states that meet the 100,000 population criteria through this analysis system. 

5-184 
Surveillance, Epidemiology, and End Results (SEER) 

(continued) 

NPCR plans to have a restricted use dataset available for use by researchers who 

meet specified criteria. Some NPCR registries provide county-level data on 

AI/AN to State Cancer Profiles (http://statecancerprofiles.cancer.gov). 

Access 

Requirements 

and Use 

Restrictions: 

Potential users must sign a data use agreement 

(http://seer.cancer.gov/publicdata/access.html). Data tables are available without 

any data use agreement requirements. 

Contact 

Information: 

Cancer Statistics Branch 

Surveillance Research Program 

Division of Cancer Control and Population Sciences 

National Cancer Institute 

Suite 504, MSC 8316 

6116 Executive Boulevard 

Bethesda, MD 20892-8316 

(301) 496-8510 

Information on SEER public use data is available at the following website: 

http://seer.cancer.gov/publicdata/ 

Questions can be addressed to seerweb@imsweb.com. 

5-185 
Survey of Jails in Indian Country (SJIC) 

Sponsor: U.S. Department of Justice/Bureau of Justice Statistics 

Description: The Survey of Jails in Indian Country (SJIC), a component of the Annual Survey 

of Jails, gathers data on all adult and juvenile jail facilities and detention centers 

in Indian Country, which is defined as reservations, pueblos, rancherias, and other 

Native American and Alaska Native communities throughout the United States. 

The survey, conducted yearly between 1998 and 2004, is a complete enumeration 

of all confinement facilities operated by tribal authorities or the Bureau of Indian 

Affairs (BIA) and provides data on number of inmates and facility characteristics 

and needs. 

Variables describe each facility, including capacity, number of adult inmates, 

number of juveniles held, number of inmates held by sex and conviction status, 

number of admissions and discharges in the last 30 days, number of inmate 

deaths, the peak population during June, facility crowding, and renovation and 

building plans. The 2004 survey also collected information on inmate health 

services and programs available to inmates including information on four 

infectious diseases, including HIV, hepatitis B and C, and tuberculosis. 

Additional new information included inmate medical and mental health services, 

suicide prevention, substance dependency programs, domestic violence 

counseling, sex offender treatment, educational programs, and inmate work 

assignments. 

Relevant Policy 

Issues: 

Justice System Issues. 

Data Type(s): Survey 

Unit of 

Analysis: 

Correctional facility 

Identification 

of AI/AN/NA: 

American Indian and Alaska Native (AI/AN) individuals are not identified in this 

study. Instead, this study is a complete enumeration of all jails and correctional 

facilities in Indian Country. 

AI/AN/NA 

Population in 

Data Set: 

In 2001, this study included 68 facilities. In 2002 and 2003, this study included 70 

facilities. 

Geographic 

Scope: 

The geographic scope of the study includes AI/AN communities. All identifiers 

for the 70 respondent facilities are included in the data file (i.e., facility name, 

tribal affiliation, city, state, zip code). While facilities from 19 different states and 

55 different tribes participate, geographic analysis would not be appropriate given 

the small number of facilities in any one tribe or state. 

Date or 

Frequency: 

Data were collected annually from 1998-2004. 

5-186 
Survey of Jails in Indian Country (SJIC) 

(continued) 

Data Collection 

Methodology: 

The survey was conducted by mail. Surveys were mailed to each facility and 

facility-identified staff completed the surveys. Data were returned by mail, fax, or 

telephone. 

Participation: Optional, without incentives. 

Response Rate: Through follow-up phone calls and facsimiles, the 2002 survey achieved an 86 

percent response rate. Older data for non-responding facilities is included in 

reports released by Bureau of Justice Statistics. 

Strengths: There are multiple years of data available providing institutional-level 

descriptions of the conditions of confinement in Indian Country. 

Limitations: These are not individual-level data; they are a description of facilities. Moreover, 

in this survey, race of persons being confined is not asked so it is not possible to 

determine how many persons described in the data are AI/AN. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to public at no cost. 

Contact 

Information: 

Data archive information: 

National Archive of Criminal Justice Data 

ICPSR 

University of Michigan 

Institute for Social Research 

P.O. Box 1248 

Ann Arbor, MI 48106-1248 

(800) 999-0960 

(313) 763-5011 

nacjd@icpsr.umich.edu 

Questions for the Bureau of Justice Statistics should be mailed to: 

Todd Minton 

Statistician 

Corrections Statistics Program 

Bureau of Justice Statistics 

810 Seventh St, NW 

Washington, DC 20531 

(202) 305-9630 

Data for 1998-2001 can be downloaded at 

http://webapp.icpsr.umich.edu/cocoon/NACJD-SERIES/00158.xml. Data for 

2002, 2003, and 2004 were not yet available as this catalog was being prepared. 

5-187 
Survey of Program Dynamics (SPD) 

Sponsor: U.S. Department of Commerce/U.S. Census Bureau 

Description: The Survey of Program Dynamics (SPD) is a longitudinal database drawn from a 

study designed to collect data on the economic, household, and social 

characteristics of a nationally representative sample of the U.S. population over 

time. Core data include employment, income, welfare program participation, 

health insurance and utilization, child well-being, marital relationships, and 

parents' depression. The SPD also had topical modules that vary by year. The 

primary goals of the SPD were to provide information on spells of actual and 

potential welfare program participation (over a ten-year period), to examine the 

causes of program participation and its long-term consequences (on recipients and 

their families), and to monitor the possible long-term changes (for individuals) 

that result from implementing welfare reform. 

Relevant Policy 

Issues: 

Measurement of Health Status, Income Status, Unemployment Rates, Economic 

Assistance Program Participation Rates, Economic Opportunity, Educational 

Attainment, Factors Contributing to Educational Disparities, Measures of Wellbeing for Families/households, Factors Contributing to Well-being Disparities of 

Families, Measures of Well-being for Children, Factors Contributing to Wellbeing Disparities of Children, Transportation Availability, Eligibility and Use of 

Other Veterans Administration Benefits. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

The race item on all versions of the SPD questionnaire reads: “Which of these 

categories best describes (your/name's) race?” 

• White 

• Black 

• American Indian (AI), Aleut or Eskimo 

• Asian or Pacific Islander 

AI/AN/NA 

Population in 

Data Set: 

In the 1992 - 2002 longitudinal file with a total of 129,013 records, there are 

1,100 unique American Indian, Aleut or Eskimo respondents. 

Geographic 

Scope: 

The geographic scope of the study is national. Geographic areas identified are 

regions (i.e., Northeast, Midwest, South, West), and states. Geographic analysis is 

possible by region and by state. 

Date or 

Frequency: 

The SPD is a longitudinal database. Data were collected annually from 1997 - 

2002. There are no plans for future administrations of the SPD. 

5-188 
Survey of Program Dynamics (SPD) 

(continued) 

Data Collection 

Methodology: 

Data are collected in person using computer-assisted personal interviewing 

(CAPI). The original pool of respondents for the SPD were households that were 

previously interviewed in the 1992 and 1993 Survey of Income and Program 

Participation (SIPP) panels. The first round of SPD data collection was conducted 

in 1997 using a modified version of the March Current Population Survey. After 

the 1997 wave of data collection, the SPD questionnaire was developed and 

administered from 1998 through 2002. 

Participation: Optional, with incentives 

Response Rate: Unweighted response rates are reported for the 1997-2002 administrations of the 

SPD as follows: 

• 1997 SPD: 81.7% 

• 1998 SPD: 85.0% 

• 1999 SPD: 85.2% 

• 2000 SPD: 79.7% (Including non-interviewed households from the 1997 

list) 

• 2001 SPD: 74.1% (Including non-interviewed households from the 1997 

list and the 1992-1993 SIPP) 

• 2002 SPD: 65.1% 

Sampling 

Methodology: 

The 1997 SPD recontacted the sample members who were interviewed for the 

1992 and 1993 SIPP panels. The SIPP samples were multistage, stratified samples 

of the U.S. civilian noninstitutionalized population. 

 

The sample size for the 1997 SPD was 34,609 households. Census field 

representatives interviewed 30,125 households. At any given point in time, a 

household was eligible to be interviewed if it contained an original sample 

member (age 15 or older). The number of eligible households fluctuated from 

round to round of interviewing because of household formation and dissolution—

and because original sample members move from one (previously eligible) 

household to another (previously ineligible) household. 

Strengths: Data are collected on key policy issues, including health and child welfare. There 

are multiple years of data available. The documentation of the content and 

implementation of the SPD is comprehensive and available on-line. 

Limitations: Asians and Pacific Islanders are collapsed into a single response category in all 

versions of the SPD. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to the public at no cost. Data are publicly available for each 

wave of data collection as well as a longitudinal file across all years of data 

collection. 

5-189 
Survey of Program Dynamics (SPD) 

(continued) 

Contact 

Information: 

The actual data are available for download from the following website: 

http://www.bls.census.gov/spd/access.html. 

Questions about the SPD should be addressed to: 

dsd.survey.program.dynamics@census.gov 

5-190 
Temporary Assistance for Needy Families (TANF) and Tribal TANF 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Administration for 

Children and Families (ACF) 

Description: The Temporary Assistance for Needy Families (TANF) and Tribal TANF 

database contains demographic characteristics for families receiving assistance 

under the TANF program. TANF case record information is reported to the 

national TANF database by states and territories on a quarterly basis. The 

database consists of active cases (families who were receiving assistance for the 

reporting month by the end of the sample month) and closed cases (families 

whose assistance was terminated for the reporting month, but received assistance 

in the prior month). States have the option of submitting all active and closed 

cases or a sample of these cases. 

Since 1996, federally recognized American Indian Tribes and Alaska Native 

organizations have been allowed to operate their own TANF programs and serve 

tribal members who would otherwise be served by the state in which they live. As 

of Fiscal Year (FY) 2005 year's end, 51 Tribal TANF plans were approved to 

operate on behalf of 237 tribes and Alaska Native villages. American Indian and 

Alaska Native families not served by Tribal TANF programs continue to be 

served by state TANF programs. The Tribal TANF database includes 

demographic characteristics of families receiving assistance under Tribal TANF. 

Relevant Policy 

Issues: 

Income Status, Unemployment Rates, Economic Assistance Program 

Participation Rates, and Measures of Well-being for Families/Households. 

Data Type(s): Program reporting data 

Unit of 

Analysis: 

Analysis can be conducted at the individual level and family level. 

For reporting purposes, the TANF family means a) all individuals receiving 

assistance as part of a family under the state’s TANF Program; and b) the 

following additional persons living in the household, if not included under a) 

above: 1) parent(s) or caretaker relative(s) of any minor child receiving 

assistance; 2) minor siblings of any child receiving assistance; and 3) any person 

whose income or resources would be counted in determining the family’s 

eligibility for or amount of assistance. 

For Tribal TANF, tribes administering their own TANF program have great 

flexibility in program design and implementation. They can define such elements 

of their programs as the service area; service population, including the definition 

of “family”; time limits; benefits and services; and work activities. 

Identification 

of AI/AN/NA: 

The State TANF agencies or Tribal TANF grantees collect and report data for 

each person receiving TANF assistance. The instructions for reporting 

race/ethnicity on TANF recipients are as follows: 

5-191 
Temporary Assistance for Needy Families (TANF) and Tribal TANF 

(continued) 

The intent of this data element is to capture the multiplicity of race and ethnicity 

characteristics applicable to each person. States/tribes should code at least one of 

the race categories “YES” in addition to coding ethnicity. 

The provided race/ethnicity categories include: 

Ethnicity: 

• Hispanic or Latino 

Race: 

• American Indian or Alaska Native (AI/AN) 

• Asian 

• Black or African American 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• White 

AI/AN/NA 

Population in 

Data Set: 

Researchers can receive a sample of the FY 2004 state TANF database for 

research. This database contains 205,119 records for active cases, and 58,453 

records for closed cases. Breakdowns of the AI/AN/NA population are below: 

Active Cases

AI/AN: 9,718 

NH/PI: 1,711 

Closed Cases

AI/AN: 3,001 

NH/PI: 653 

In 2002 there were 9,983 families receiving Tribal TANF assistance in total. The 

numbers for the 2004 database have not been released yet. 

AI/AN/NA 

Subpopulations: 

Researchers can request analyses of Tribal TANF data by tribal affiliation. 

Because the numbers in the data set are very small, extreme limitations will be 

put on such requests. 

Geographic 

Scope: 

The geographic scope of the state and Tribal TANF databases is national. In the 

state TANF database, analysis by state is possible. Also, in the state TANF 

database, the 3-digit county Federal Information Processing Standards (FIPS) 

code is provided. County-level analysis may be possible. Tribal TANF grantees 

do not report the FIPS code, but they do report the 3-digit tribal identification 

code instead. Tribal-level special tabulations may be available, but due to the 

small numbers in the data, extreme limitations will be put on requests. 

Date or 

Frequency: 

Data is collected on a monthly basis and submitted quarterly to the national 

TANF databases. Research databases are compiled for an entire fiscal year. The 

most current fiscal year data available is FY 2004. 

5-192 
Temporary Assistance for Needy Families (TANF) and Tribal TANF 

(continued) 

Data Collection 

Methodology: 

State and Tribal TANF agencies complete a TANF data collection form for all 

families receiving assistance under the TANF program. 

Participation: Mandatory 

Sampling 

Methodology: 

There is no single sampling method applied across the board for all states 

submitting data to the national TANF database. Twenty-nine states submitted 

records on all active and closed cases, while the remaining 24 states submitted 

sample data. If states do not meet the annual minimal sample size requirements, 

they must report data for all active and closed cases. No tribe has a caseload large 

enough to warrant sampling. 

Authorization: The Personal Responsibility and Work Opportunity Reconciliation Act of 1996 

requires states, territories, and tribes to collect on a monthly basis and report to 

the Secretary of the Department of Health and Human Services on a quarterly 

basis disaggregated case record information on families receiving assistance, 

families no longer receiving assistance, and families newly-approved for 

assistance from programs funded under TANF. 

Strengths: Data sets contain a large number of AI/AN/NA respondents though Tribal TANF 

data are not currently available. Multiple years of TANF data are available. 

Limitations: There is limited documentation available for researchers who wish to use the 

TANF public use database. 

Access 

Requirements 

and Use 

Restrictions: 

Tribal TANF is still relatively new. Processes to provide researchers with direct 

access to the data files may be developed in the future. For the time being, the 

office is concerned about the confidentiality of the data, but is willing to run 

analyses for researchers. Also, it may be possible to request the data with tribal 

affiliation removed, although detail would be lost. 

Contact 

Information: 

Researchers interested in receiving the sample FY 2004 state TANF public use 

database should contact: 

Andrew Yoo 

(202) 401-5098 

AYoo@acf.hhs.gov 

Researchers interested in working with Tribal TANF data should contact the 

Tribal TANF acting director Bob Shelbourne at (202) 401-5150; Raymond 

Apodaca, Tribal TANF Team Leader at (202) 401-5150; Ann Bowker, Native 

Employment Works (NEW) Program at (202) 401-5308; or Gerald Joireman, 

TANF Data at (202) 401-5097, email: gjoireman@acf.hhs.gov. 

Reports of 

Interest: 

The 2004 TANF/TTANF Annual Report to Congress can be located at: 

http://www.acf.hhs.gov/programs/ofa/indexar.htm 

5-193 
Tobacco Use Supplement to the Current Population Survey (TUS-CPS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/National Institutes of 

Health/National Cancer Institute (NCI) and The Centers for Disease Control and 

Prevention (CDC) 

Description: The Tobacco Use Supplement to the Current Population Survey (TUS-CPS) is a 

survey of tobacco use that serves as a key source of national and state level data 

on smoking and other tobacco use in the U.S. household population. The TUSCPS uses a large, nationally representative sample that contains information on 

about 240,000 individuals within a given survey period. Although the TUS-CPS 

has changed slightly between 1992 and 2003, it has generally contained about 40 

items concerning cigarette smoking prevalence including smoking history, current 

and past cigarette consumption; cigarette smoking quit attempts and intentions to 

quit; medical and dental advice to quit smoking; cigar, pipe, chewing tobacco, 

and snuff use; workplace smoking policies; smoking rules in the home; attitudes 

toward smoking in public places; opinions about the degree of youth access to 

tobacco in the community; and attitudes toward advertising and promotion of 

tobacco. These data can be used by researchers to monitor progress in the control 

of tobacco use, conduct tobacco-related research, and evaluate tobacco control 

programs. 

Relevant Policy 

Issues: 

Key Health Disparities of Priority Interest. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

The race/ethnicity of the TUS-CPS respondents is taken from the CPS data. In the 

CPS, participants are asked to respond to the question on race by indicating one 

or more of six race categories. The six race categories are: 

• White 

• Black or African American 

• American Indian/Alaska Native (AI/AN) 

• Asian 

• Native Hawaiian/Other Pacific Islander (NH/PI) 

• Some Other Race (this category is not read or displayed to the respondent) 

Responses to the race item are recoded into multiple race categories for analytic 

purposes: 

• AI/AN Only 

• NH/PI Only 

• White/AI/AN 

• White/NH/PI 

• Black/AI/AN Black/NH/PI 

5-194 
Tobacco Use Supplement to the Current Population Survey (TUS-CPS) 

(continued) 

• AI/AN/Asian 

• Asian/NH/PI 

• White/Black/AI/AN 

• White/AI/AN/Asian 

• White/Asian/NH/PI 

• White/Black/AI/AN/Asian 

AI/AN/NA 

Population in 

Data Set: 

For the TUS-CPS, some surveys are completed with proxy respondents when the 

original sampled respondent is unavailable. Self-respondents are eligible for the 

entire TUS-CPS questionnaire, whereas proxy respondents are only eligible for 

certain items. Additionally, responses to the race item are recoded into the 

multiple race categories. The following categories reflect the unweighted counts 

for AI/AN/NA respondents, including all surveys completed by the sampled 

respondents and proxies, and all surveys completed by only the sampled 

respondent, in the February, June, and November 2003 CPS: 

February 2003 (N = 68,954) 

AI/AN Only: 786 self & proxy, 582 self only 

NH/PI Only: 218 self & proxy, 152 self only 

White/AI/AN: 660 self & proxy, 552 self only 

White/NH: 52 self & proxy, 34 self only 

Black/AI/AN: 71 self & proxy, 59 self only 

Black/NH/PI: 3 self & proxy, 2 self only 

AI/AN/Asian: 8 self & proxy, 3 self only 

Asian/NH/PI: 36 self & proxy, 23 self only 

White/Black/AI/AN: 29 self & proxy, 21 self only 

White/AI/AN/Asian: 1 self & proxy, 1 self only 

White/Asian/NH/PI: 1 self & proxy, 1 self only 

White/Black/AI/AN/Asian: 2 self & proxy, 2 self only 

June 2003 (N = 89,864)

AI/AN Only: 963 self & proxy, 739 self only 

NH/PI Only: 254 self & proxy,164 self only 

White/AI/AN: 784 self & proxy, 629 self only 

White/NH: 72 self & proxy, 46 self only 

Black/AI/AN: 59 self & proxy, 46 self only 

Black/NH/PI: 3 self & proxy, 1 self only 

AI/AN/Asian: 3 self & proxy, 3 self only 

Asian/NH/PI: 72 self & proxy, 36 self only 

White/Black/AI/AN: 40 self & proxy, 34 self only 

White/AI/AN/Asian: 5 self & proxy, 4 self only 

White/Asian/NH/PI: 6 self & proxy, 3 self only 

White/Black/AI/AN/Asian: 0 respondents 

5-195 
Tobacco Use Supplement to the Current Population Survey (TUS-CPS) 

(continued) 

November 2003 (N = 90,802)

AI/AN Only: 931 self & proxy, 672 self only 

NH/PI Only: 222 self & proxy, 142 self only 

White/AI/AN: 827 self & proxy, 629 self only 

White/NH: 58 self & proxy, 28 self only 

Black/AI/AN: 72 self & proxy, 55 self only 

Black/NH/PI: 3 self & proxy, 2 self only 

AI/AN/Asian: 5 self & proxy, 2 self only 

Asian/NH/PI: 90 self & proxy, 54 self only 

White/Black/AI/AN: 36 self & proxy, 24 self only 

White/AI/AN/Asian: 3 self & proxy, 1 self only 

White/Asian/NH/PI: 7 self & proxy, 5 self only 

White/Black/AI/AN/Asian: 0 respondents 

Geographic 

Scope: 

The geographic scope of the study is national. Due to the large sample size for 

most survey items, analyses can be done at either the national or state levels, and 

in some cases, for areas smaller than the state level. State sample sizes range from 

2,100 for the District of Columbia to 18,700 for California. State data for any year 

is considered most reliable when using data from all 3 months of data collection. 

Date or 

Frequency: 

The TUS-CPS was administered as part of the CPS in 1992-1993, 1995-1996, 

1998-1999, 2000, 2001-2002, and 2003. For these time periods, the TUS-CPS 

was administered for 3 months throughout the year. 

Over the next 10 years, NCI plans to conduct the TUS-CPS triennially, alternating 

between a core questionnaire intended for monitoring purposes (similar to the 

questionnaire used throughout the 1990s) and more specific Special Topics 

questionnaires that target tobacco-related issues of particular interest to 

researchers. NCI and CDC will be co-sponsoring the supplements. The next 

round of core TUS-CPS supplements is being fielded in May 2006, August 2006, 

and January 2007. 

Aggregation: It is recommended that when analyzing the TUS-CPS data, researchers should 

aggregate the data across the months of the data collection effort for a single year. 

For example, when using the 2003 data researchers should combine the data 

collected in the months of February, June, and November. 

Although multiple years of TUS-CPS data are available, in 2003 significant 

changes were made to the race/ethnicity questions in the CPS. In 2003, 

respondents were able to select more than one race when answering the survey. 

This change in wording does not impact smoking estimates and trends calculated 

for the entire nation from the TUS-CPS, but it could potentially impact smoking 

estimates and trends calculated by race/ethnicity. NCI has developed a method to 

construct single-race estimates using data from the post-2003 TUS-CPS. The 

method is useful when trends over time are being examined for single race groups 

using both pre-2003 and post-2003 data. More information is available in the 

report Bridging Estimates by Race for the Tobacco Use Supplement to the 

5-196 
Tobacco Use Supplement to the Current Population Survey (TUS-CPS) 

(continued) 

Current Population Survey – (TUS-CPS) (http://riskfactor.cancer.gov/studies/tuscps/race_bridging.pdf) which describes the method and gives an initial 

assessment of the usefulness of the race adjustment. 

Data Collection 

Methodology: 

The mode of data collection is both telephone and in-person interviewing. NCI 

estimates that 75 percent of the respondents reply to the survey by telephone and 

25 percent of the respondents reply during personal home visits. Additionally, 

about 20 percent of the completed surveys are completed by a proxy for the 

sampled respondent. When a proxy is providing the information, only a few 

measures of use are collected. 

Participation: Optional, without incentives 

Response Rate: Nonresponse rates are less than 9 percent for the monthly CPS for September 

2003 through September 2004. 

Sampling 

Methodology: 

The TUS-CPS was conducted as a supplemental study with the core CPS. The 

CPS sample is a multistage stratified sample of approximately 56,000 housing 

units from 792 sample areas. The CPS samples housing units from lists of 

addresses obtained from the 1990 Decennial Census of Population and Housing. 

These lists are updated continuously for new housing built after the 1990 census. 

The first stage of sampling involves dividing the United States into primary 

sampling units (PSUs)—most of which comprise a metropolitan area, a large 

county, or a group of smaller counties. Every PSU falls within the boundary of a 

state. The PSUs are then grouped into strata. 

Analysis: Effective sample size, design effects, and standard errors for estimates are 

discussed in detail in the following publication: Technical Document CPS03: 

Current Population Survey, February, June, and November 2003: Tobacco Use 

Supplement File 

(http://riskfactor.cancer.gov/studies/tus-cps/surveys/cps03_tech_doc.pdf). 

Strengths: There are a large number of AI/AN/NA respondents. There is relevance to a key 

health policy issue, tobacco use. Multiple years of data are available. 

Limitations: While multiple years of data are available, in 2003 significant changes were made 

to the race/ethnicity questions in the CPS that may affect the ability to look at 

tobacco use by AI/AN/NA persons over time. 

Access 

Requirements 

and Use 

Restrictions: 

TUS-CPS data are available to the public. The data may be purchased through the 

Census Bureau's online catalog. Prices for the data may vary; the cost of 

purchasing the 2003 data on CD-ROM is $55.00. 

5-197 
Tobacco Use Supplement to the Current Population Survey (TUS-CPS) 

(continued) 

Contact 

Information: 

Risk Factor Monitoring and Methods Branch 

Applied Research Program 

Division of Cancer Control and Population Sciences 

National Cancer Institute, EPN 4005 

6130 Executive Blvd-MSC 7344 

Bethesda, MD 20892-7344 

(301) 496-8500 

Instructions for ordering the TUS-CPS data files are available on the NCI website 

at: http://riskfactor.cancer.gov/studies/tus-cps/info.html 

U.S. Department of Health and Human Services. Tobacco Use Among U.S. 

Racial/Ethnic Minority Groups—African Americans, American Indians and 

Alaska Natives, Asian Americans and Pacific Islanders, and Hispanics: A Report 

of the Surgeon General. Atlanta, Georgia: U.S. Department of Health and Human 

Services, Centers for Disease Control and Prevention, National Center for 

Chronic Disease Prevention and Health Promotion, Office on Smoking and 

Health, 1998. 

http://www.cdc.gov/TOBACCO/sgr/sgr_1998/index.htm 

Reports of 

Interest: 

5-198 
Treatment Episode Data Set (TEDS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Substance Abuse and 

Mental Health Services Administration (SAMHSA) 

Description: The Treatment Episode Data Set (TEDS) is an administrative data system 

providing descriptive information about the national flow of admissions to 

providers of substance abuse treatment. The TEDS series was designed to provide 

annual data on the number and characteristics of persons admitted to public and 

private substance abuse treatment programs receiving public funding. Data 

collected include client demographics, client substance abuse problems, client 

mental health information, information on treatments received and source of 

client referral to treatment, and sources of payment for treatment. Admission data 

have been collected since 1989. In 2000, a discharge data set was added to allow 

TEDS to collect information on entire treatment episodes. TEDS is comprised of 

data that are routinely collected by states in monitoring substance abuse treatment 

facilities. In general, TEDS data cover those facilities that receive state funds for 

substance abuse treatment. 

Relevant Policy 

Issues: 

Health Disparities and Differences in Patterns in Drug and Alcohol Use. 

Data Type(s): Program reporting data 

Unit of 

Analysis: 

Admissions at publicly funded substance abuse treatment facilities 

Identification 

of AI/AN/NA: 

Data are reported in the following categories: 

• Alaska Native (Aleut, Eskimo, Indian) (AN) 

• American Indian (Other than Alaskan Natives) (AI) 

• Asian or Pacific Islander 

• Black 

• White 

• Other Single Race 

• Two or More Races 

AI/AN/NA 

Population in 

Data Set: 

In 2004 the entire TEDS data include 1,875,026 cases. Counts for AI/AN cases 

are: 

AN: 5,186 

AI: 38,785 

AI/AN/NA 

Subpopulations: 

American Indian alone and Alaska Native alone are available. 

Geographic 

Scope: 

The geographic scope of TEDS is national. Geographic indicators include state, 

primary metropolitan statistical area (PMSA), metropolitan statistical area 

(MSA), and core-based statistical area (CBSA). 

5-199 
Treatment Episode Data Set (TEDS) 

(continued) 

Date or 

Frequency: 

TEDS data are compiled yearly. Data for 1992-2004 are available online. New 

files will continue to be released approximately 18 months after the end of each 

year (e.g., the 2004 file was released in June 2006.) 

Data Collection 

Methodology: 

TEDS data are routinely collected by state administrative systems and then 

submitted to SAMHSA in a standard format. 

Participation: Participation is mandatory for publicly-funded clients. Other clients participate on 

an optional basis. 

Response Rate: TEDS is designed to include client-level data from all facilities that receive state 

funds for substance abuse treatment. In 1997, the most recent information 

available, TEDS was estimated to represent 83 percent of all admissions to these 

facilities. Also in 1997, TEDS was estimated to cover 67 percent of all known 

substance abuse treatment admissions, regardless of the source of funding for the 

treatment. The scope of admissions included in TEDS is affected by differences 

in state reporting practices, varying definitions of treatment admission, 

availability of public funds, and public funding constraints. 

Authorization: In 1988, the Comprehensive Alcohol Abuse, Drug Abuse, and Mental Health 

Amendments (P.L. 100-690) established a revised Substance Abuse Prevention 

and Treatment (SAPT) Block Grant and mandated federal data collection on 

clients receiving treatment for either alcohol or drug abuse. The TEDS data 

collection effort represents the federal response to this mandate. 

Strengths: TEDS contains a large number of AI/AN respondents. The data are collected on a 

key policy issue, substance abuse. Key demographic indicators are included for 

each state. One can identify by state, the number of admissions by race, age, 

gender, and education. There are multiple years of data available, and in addition 

to the annual files, there is a multi-year file available. Online analysis and 

subsetting, as well as "Quick Tables" online table generation, are available. 

Limitations: Several limitations are identified in the TEDS documentation that should be 

considered: 

• The way an admission is defined may vary from state to state such that the 

absolute number of admissions is not a valid measure for comparing 

states. 

• The number and client mix of TEDS records depends, to some extent, on 

external factors, including the availability of public funds. In states with 

higher funding levels, a larger percentage of the substance-abusing 

population may be admitted to publicly-funded treatment, including the 

less severely impaired and the less economically disadvantaged. 

• Public funding constraints may direct states to selectively target special 

populations. For example, pregnant women or adolescents may be more 

likely to receive treatment. The representations of these populations in 

the data may vary accordingly. 

5-200 
Treatment Episode Data Set (TEDS) 

(continued) 

• States vary in the extent to which coercion plays a role in referral to 

treatment. This variation derives from criminal justice practices and 

differing concentrations of abuser subpopulations. 

• TEDS consists of treatment admissions, and therefore may include multiple 

admissions for the same client. Thus, any statistics derived from the data 

will represent admissions, not clients. It is possible for clients to have 

multiple initial admissions within a state and even within providers that 

have multiple treatment sites within the state. TEDS provides a national 

snapshot of what is seen at admission for treatment, but is currently not 

designed to follow individual clients through a sequence of treatment 

episodes. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to the public at no cost. 

Contact 

Information: 

SAMHDA User Support 

Substance Abuse and Mental Health Data Archive 

Inter-University Consortium for Political and Social Research (ICPSR) 

P.O. Box 1248 

Ann Arbor, Michigan 48106 

(1-888) 741-7242 

samhda-support@icpsr.umich.edu 

www.icpsr.umich.edu 

Data can be accessed at: http://webapp.icpsr.umich.edu/cocoon/SAMHDASERIES/00056.xml

5-201 
Uniform Crime Reports (UCR) 

Sponsor: U.S. Department of Justice (DoJ)/Federal Bureau of Investigation (FBI) 

Description: The Uniform Crime Reporting (UCR) Program is a nationwide, cooperative 

summary statistical effort of more than 17,000 city, university and college, 

county, state, tribal, and federal law enforcement agencies voluntarily reporting 

data on crimes brought to their attention. The UCR Program collects offense 

information for murder and nonnegligent manslaughter, forcible rape, robbery, 

aggravated assault, burglary, larceny-theft, motor vehicle theft, and arson. It also 

collects information on the characteristics of persons arrested, victims and 

offenders in homicides and nonnegligent manslaughter, and offenders in hate 

crimes. 

Relevant Policy 

Issues: 

Rates of Involvement with Justice System. 

Data Type(s): Registry 

Unit of 

Analysis: 

The unit of analysis is arrests. One person may be arrested multiple times during 

the year; as a result, the arrest tabulations cannot be considered as a total number 

of individuals arrested. 

Identification 

of AI/AN/NA: 

According to the UCR Handbook, revised in 2004, the racial categories used in 

the UCR Program were adopted from the Statistical Policy Handbook (1978)

published by the Office of Federal Statistical Policy and Standards, U.S. 

Department of Commerce. The racial designations are defined as follows: 

• White. A person having origins in any of the original peoples of Europe, 

North Africa, or the Middle East. 

• Black. A person having origins in any of the black racial groups of Africa. 

• American Indian or Alaskan Native (AI/AN). A person having origins in 

any of the original peoples of North America and who maintains cultural 

identification through tribal affiliation or community recognition. 

• Asian or Pacific Islander. A person having origins in any of the original 

peoples of the Far East, Southeast Asia, the Indian subcontinent, or the 

Pacific Islands. This area includes, for example, China, India, Japan, 

Korea, the Philippine Islands, and Samoa. 

AI/AN/NA 

Population in 

Data Set: 

The total number of arrests of AI/ANs in 2004 was 135,479 for all ages. Of this 

total, 20,391 AI/AN arrests involved individuals who were under 18 years of age. 

Total arrests of AI/AN offenders in hate crimes was 41. Information was not 

available on offenders or victims of homicide because in the published tables, 

AI/AN is combined with other races into an "other" race category. However, this 

information is available in the raw data sets, which are available from the UCR 

Program. 

5-202 
Uniform Crime Reports (UCR) 

(continued) 

Geographic 

Scope: 

The geographic scope of the reporting system is national. Analyses are presented 

for principal cities in metropolitan statistical areas (MSAs), metropolitan counties 

(counties within an MSA), nonmetropolitan counties (counties outside an MSA), 

and suburban areas (counties within an MSA but excluding principal city). 

Breakdowns of the data are also available regionally and by population group as 

well. 

Date or 

Frequency: 

Law enforcement agencies submit data on a monthly basis and the data are 

compiled into annual files. Data are published in annual reports. 

Data Collection 

Methodology: 

Law enforcement agencies contribute crime data through their respective state 

UCR Program. For those states that do not have a state program, local agencies 

submit crime statistics directly to the FBI. 

Participation: Optional, without incentives 

Response Rate: During 2004, law enforcement agencies active in the UCR Program represented 

94.2 percent of the total number of law enforcement agencies. 

Strengths: The data source contains a large AI/AN population. Data are collected on a key 

policy issue, involvement with the justice system. There are multiple years of data 

available. This data source is a vast compilation of published tables that are 

widely used for tracking crime trends across the nation. Additionally, an archive 

of master files (final data, not estimates) are available upon request. 

Limitations: These are summary data that do not allow analyses beyond simple tabulations by 

geographic unit, race, and broad age groupings. Moreover, these are primarily 

tabulations of arrests and, in some cases victim information, so these data cannot 

be used to determine the number of unique individuals who have been arrested 

within a year. Some offense data for each year are estimated (arrest data are not 

estimated) because not all law enforcement agencies are able to provide data for 

complete reporting periods. The estimates are computed by using the known 

offense figures of similar areas within a state and assigning the same proportion 

of crime volumes to nonreporting agencies or agencies with missing data. The 

estimation process considers the following: population size of agency, type of 

jurisdiction (e.g., police department versus sheriff’s office), and geographic 

location. 

Other: The National Incident-Based Reporting System (NIBRS), which is compiled in 

addition to the UCR as summary reporting, covers 80 percent of the nation's 

reporting. The NIBRS collects data on each single incident and arrest within 22 

crime categories. For each offense known to police within these categories, 

incident, victim, property, offender, and arrestee information are gathered when 

available. The goal of the redesign is to modernize crime information by 

collecting data currently maintained in law enforcement records while 

maintaining the integrity of UCR’s long-running statistical series. Implementation 

of the NIBRS is occurring at a pace commensurate with the resources, abilities, 

5-203 
Uniform Crime Reports (UCR) 

(continued) 

and limitations of the contributing law enforcement agencies. In, 2004, 29 state 

programs had been certified for NIBRS participation. For current UCR reporting, 

NIBRS data are summarized in order to be combined with the UCR data. Contact 

information for the NIBRS is the same as for the UCR. 

Contact 

Information: 

The general website for the UCR is http://www.fbi.gov/ucr/ucr.htm. At this 

website, reports and statistical tables are available for 1995-2005 (provisional 

data). 

For more information regarding the FBI's UCR data, you may contact a member 

of the Communications Unit staff by telephone at (304) 625-4995; by facsimile at 

(304) 625-5394; or by Internet at cjis_comm@leo.gov. (E-mail data requests 

cannot be processed unless requesters include their full name, a mailing address, 

and a contact telephone number.) 

Reports of 

Interest: 

http://www.fbi.gov/ucr/cius_04/documents/CIUS2004.pdf 

http://www.fbi.gov/ucr/cius_04/appendices/appendix_06.html 

5-204 
United States Renal Data System (USRDS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)National Institutes of 

Health (NIH)/National Institute of Diabetes and Digestive and Kidney Diseases 

(NIDDK) 

Description: The United States Renal Data System (USRDS) is a national data system that 

collects, analyzes, and distributes information about end-stage renal disease 

(ESRD) and chronic kidney disease (CKD) in the United States. The USRDS is 

funded directly by NIDDK in collaboration with the Centers for Medicare & 

Medicaid Services (CMS). The United Network for Organ Sharing (UNOS) is 

also providing transplant and wait-list data, under the inter-agency agreement, to 

this data collection effort in order to improve the accuracy of ESRD patient 

information. 

Relevant Policy 

Issues: 

Measurement of Health Status and Disease-specific Measurements. 

Data Type(s): Registry 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Native American (includes American Indians and Alaska Natives.) The combined 

category Asian/Pacific Islander is used in USRDS reports. 

AI/AN/NA 

Population in 

Data Set: 

The population size by race is available in Reference Section M of the 2005 

USRDS Annual Data Report (ADR). ESRD incidence and prevalence rates by 

year for Native Americans (NA) are available in Reference Sections A and B. For 

example, the incident count and adjusted incident rate per million population for 

NA in 2003 was 1,097 and 503.9 respectively. 

Geographic 

Scope: 

The geographic scope of the study is national. Further geographic analysis is 

possible by state, county, zipcode, and HSA (CDC Health Service Area). 

Date or 

Frequency: 

Data have been compiled annually since 1988, with the 2004 data being the most 

recently available for analysis. 

Data Collection 

Methodology: 

Data for the USRDS Database are compiled from existing data sources including 

the Centers for Medicare and Medicaid Services (CMS) Renal Management 

Information System (REMIS), CMS claims data, Facility survey data, CDC 

survey data, Standard Information Management System (SIMS), Medicare 

Evidence Form (CMS-2728), ESRD Death Notification Form (CMS-2746), and 

UNOS transplant and wait-list data. The CMS data files are supplemented by 

CMS with enrollment, payer history, and other administrative data to provide 

utilization and demographic information on ESRD patients. 

Participation: Mandatory 

5-205 
United States Renal Data System (USRDS) 

(continued) 

Response Rate: Response or coverage rates are 100 percent since May of 1995 because the 

amended ESRD entitlement policy requires a Medicare Evidence form to be 

submitted for all ESRD patients regardless of their insurance and eligibility 

status. However, the payment data for non-Medicare ESRD patients maybe absent 

during the 30-month coordination period. 

Strengths: Data set contains information on all Native American patients with ESRD. There 

are multiple years of data available starting from 1978. 

Limitations: Payment data of non-Medicare or MSP patients during the first 30-month 

coordination period is not available. 

Access 

Requirements 

and Use 

Restrictions: 

The data are available to the public through a data use agreement (DUA). The 

cost associated with use of the data set is $600 for the core data file and $100-

$400 for each supplemental file. Researchers completing a data use agreement 

can access the limited data set directly. To submit a DUA request, contact the 

Coordinating Center at (888) 99USRDS. Statistical reports providing frequencies 

and basic tabulations are available through the Renal Data Extraction and 

Referencing System (RenDER) on the USRDS website: www.usrds.org. 

Contact 

Information: 

Annual Data Reports can be accessed through: 

http://www.usrds.org/adr.htm. 

Data requests and publications: 

USRDS Coordinating Center 

914 South 8th Street 

Suite D-206 

Minneapolis, MN 55404 

(612) 347-7776 

(888) 99USRDS 

Fax: (612) 347-5878 

usrds@usrds.org 

Data file contact: Shu Chen, MS, schen@usrds.org. 

5-206 
Washington State Population Survey (WSPS) 

Sponsor: State of Washington/Office of Financial Management 

Description: The Washington State Population Survey (WSPS) is a source of information 

about the health and welfare of Washington families. The survey focuses 

primarily on issues of employment, family poverty, migration into the state, 

health, and health insurance coverage. 

Relevant Policy 

Issues: 

Measurement of Health Status, Factors Contributing to Measured Health 

Disparities, Income Status, Unemployment Rates, Economic Assistance Program 

Participation Rates, and Economic Opportunity. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification Instructions for reporting race are as follows: “What racial group or groups best 

of AI/AN/NA: describes you?" 

• White 

• Black 

• American Indian or Alaska Native (AI/AN) 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• Asian 

Respondents could select more than one race. 

AI/AN/NA 

Population in 

Data Set: 

The 2004 WSPS gathered data on 17,788 individuals from 7,097 households. 

The unweighted counts for AI/AN respondents to the 2004 WSPS are as follows: 

AI/AN alone: 265 

AI/AN and other races: 225 

Unweighted counts of NH/PI respondents for the 2004 WSPS are as follows: 

NH/PI alone: 119 

NH/PI and other races: 54 

Geographic 

Scope: 

The geographic scope of the study is the state of Washington. Geographic areas 

are identified by regions of the state (e.g., North Puget, West Balance, King, 

Other Puget Metro, Clark, East Balance, Spokane, Tri-cities). The level of 

geographical analysis possible is state-wide or regional. However, regional 

analysis is not recommended for AI/AN/NA subgroups because of very small 

sample sizes. 

Date or 

Frequency: 

The WSPS has been conducted biennially since 1998. The 2006 administration of 

the survey was underway at the time of preparation of this catalog. 

5-207 
Washington State Population Survey (WSPS) 

(continued) 

Data Collection 

Methodology: 

The WSPS is a telephone survey. 

Participation: Optional, without incentives 

Response Rate: WSPS survey contacts indicated that the response rate for the 2004 study was 

low. 

Sampling 

Methodology: 

For the WSPS, a stratified sample by region was selected from all households in 

state of Washington with an activated telephone line, either listed or unlisted. A 

target of 750 households was planned for each of the eight regions with the 

exception of King County where a target of 1,800 households was planned. More 

households were selected in King County to insure sufficient information on 

racial minority groups for statistical analyses. Households were selected in each 

of the regions using random digit dialing (RDD) technique. 

Analysis: There are two weights for use in analysis. A population weight is available that 

weights the survey responses to represent the state population based on Census 

Bureau population counts. There is also a weight based on administrative records 

for Medicaid that, when used, will yield improved estimates for uninsured 

persons. 

Strengths: Data are collected on key policy issues including health and economic status. 

There are multiple years of data available. 

Limitations: There are limited AI/AN/NA respondents in this data source. This study has a low 

response rate. 

Access 

Requirements 

and Use 

Restrictions: 

Data are available to the public at no cost. 

Contact 

Information: 

The data and documentation are available for download from the following 

website: http://www.ofm.wa.gov/sps/2004/default.asp. 

Erica Gardner 

Forecasting Division 

Washington State Office of Financial Management 

P.O. Box 43113 

Olympia, WA 98504-3113 

(360) 902-0599 

5-208 
Youth Gangs in Indian Country 

Sponsor: U.S. Department of Justice (DOJ)/Office of Juvenile Justice and Delinquency 

Prevention (OJJDP) and the National Youth Gang Center (NYGC) 

Description: In 2001, OJJP and NYGC developed and implemented the 2000 Survey of Youth 

Gangs in Indian Country. All federally recognized Indian communities were 

surveyed to measure the presence, size, and criminal behavior of youth gangs in 

Indian Country. This survey collected data regarding the presence and effect of 

youth gang activity in Indian Country as well as programmatic responses to the 

problem. The survey was mailed to tribal leaders or tribal representatives in 577 

Indian communities comprising 561 federally recognized tribes. 

Relevant Policy 

Issues: 

Rates of Involvement with Justice System. 

Data Type(s): Survey 

Unit of 

Analysis: 

Federally recognized Indian communities 

Identification 

of AI/AN/NA: 

AI/AN/NA individuals are not identified in the data set. Instead, data are 

organized by Indian community. The survey defines an Indian “community” as 

persons of American Indian, Alaska Native, or Aleut heritage who reside within 

the limits of Indian reservations, pueblos, rancherias, villages, dependent Indian 

communities, or Indian allotments, and who together comprise a federally 

recognized tribe or community. Communities also include people who have been 

recognized by the United States government as a tribe or tribal community, but 

who do not occupy tribal trust, tribally owned, or Indian allotment lands. 

Communities are the people and land together or tribal community viewed as a 

group. Land without the people is not considered a community for the purpose of 

this survey. The data source does not allow identification of members of a state 

recognized tribe. 

AI/AN/NA 

Population in 

Data Set: 

Race data on the respondents was not gathered in the survey. Communities that 

reported gang activity in 2000, however, were asked to estimate demographic 

characteristics of gang members, including race or ethnicity. Survey respondents 

reported that the majority (78 percent) of youth gang members in their 

communities were American Indian, Alaska Native, or Aleut. In fact, 

approximately one-half of responding communities indicated almost all gang 

members (more than 90 percent) were of this race. 

Geographic 

Scope: 

The geographic scope of the study is national. Information on additional 

geographic indicators was not available. 

Date or 

Frequency: 

This study was a one-time effort. Data were collected in 2001. 

5-209 
Youth Gangs in Indian Country 

(continued) 

Data Collection 

Methodology: 

Mail and telephone survey 

Response Rate: Overall, 52 percent (n=300) of the communities responded to the survey. 

Sampling 

Methodology: 

At the time the survey was developed, there were 577 Indian communities in the 

United States, comprising 561 federally recognized tribes. NYGC and the 

advisory group chose to survey the entire Indian country population to provide a 

broad assessment. 

Strengths: Data are collected on the key policy issue of justice system involvement. For 

those interested in youth gang activity, this data set is the only assessment of such 

activity across all Indian Country. 

Limitations: The data are very difficult to obtain and the documentation available online does 

not include information on statistical topics such as error estimates or weighting. 

There is a low response rate. 

Access 

Requirements 

and Use 

Restrictions: 

The data set, held by the NYGC, is only available on a very limited basis. It is not 

intended for release, but release has occurred in a few exceptional situations. 

There is no cost should access be granted. 

Contact 

Information: 

National Youth Gang Center 

Institute for Intergovernmental Research 

Post Office Box 12729 

Tallahassee, FL 32317 

Tel: (850) 385-0600 

Fax: (850) 386-5356 

5-210 
Youth Risk Behavior Surveillance System (YRBSS) 

Sponsor: U.S. Department of Health and Human Services (DHHS)/Centers for Disease 

Control and Prevention (CDC) 

Description: The Youth Risk Behavior Surveillance System (YRBSS) is an epidemiologic 

survey system established by CDC to monitor the prevalence of youth behavior 

that most influences health. The priority health risk behaviors that contribute 

markedly to the leading causes of death, disability, and social problems among 

youth and adults in the United States include tobacco use; unhealthy dietary 

behaviors; inadequate physical activity; alcohol and other drug use; sexual 

behaviors that contribute to unintended pregnancy and sexually transmitted 

diseases including HIV infection; and behaviors that contribute to unintentional 

injuries and violence. 

Relevant Policy 

Issues: 

Measurement of Health Status, Key Health Disparities, and Factors that 

Contribute to Health Disparities. 

Data Type(s): Survey 

Unit of 

Analysis: 

Individual 

Identification 

of AI/AN/NA: 

Race/ethnicity are ascertained by the following two questions: 

Are you Hispanic or Latino? 

• Yes 

• No 

What is your race? (Select one or more responses.) 

• American Indian or Alaska Native (AI/AN) 

• Asian 

• Black or African American 

• Native Hawaiian or other Pacific Islander (NH/PI) 

• White 

AI/AN/NA 

Population in 

Data Set: 

For 2005, there are 13,917 records for the National Youth Risk Survey; of these 

147 are identified as AI/AN and 90 as NH/PI. 

Geographic 

Scope: 

The geographic scope of the study is national. Geographic identifiers available for 

analysis include geographic region (Northeast, Midwest, South, or West). Prior to 

2005, metropolitan status (urban, suburban, or rural) is available, but will not be 

made available in data sets beginning in 2005. 

Date or 

Frequency: 

School-based data have been collected in odd years since 1991. The 2005 

National School-based Youth Risk Behavior Survey is available for public use. 

5-211 
Youth Risk Behavior Surveillance System (YRBSS) 

(continued) 

National Alternative High School YRBSS was conducted in 1998 and the 

National College Health Risk Behavior Survey was conducted in 1995. 

Data Collection 

Methodology: 

Students complete the self-administered questionnaire in their classrooms during 

a regular class period, and record their responses directly on a computerscannable booklet or answer sheet. 

Participation: Optional, without incentives to students. 

Response Rate: In 2005, the school response rate was 78 percent and the student response rate 

was 86 percent. When these response rates are combined, the overall response 

rate equaled 67 percent. 

Sampling 

Methodology: 

The 2005 national school-based survey employed a three-stage cluster sample 

designed to produce a nationally representative sample of students in grades 9-12. 

The first stage sampling frame contained primary sampling units (PSUs) 

consisting of large counties, sub-areas of very large counties, or groups of small, 

adjacent counties. The PSUs were selected with probability proportional to school 

enrollment size. At the second sampling stage, 195 schools were also selected 

with probability proportional to school enrollment size. To enable separate 

analysis of data for black and Hispanic students, schools with substantial numbers 

of black and Hispanic students were sampled at higher rates than all other 

schools. The third stage of sampling consisted of randomly selecting one or two 

intact classes of a required subject (e.g., English or social studies) from grades 9-

12 at each chosen school. All students in the selected classes were eligible to 

participate in the survey. 

Strengths: Data are collected on key policy issues, including health status, health disparities, 

and factors that contribute to key health disparities. Multiple years of data are 

available for trend analysis. 

Limitations: There are few AI/AN/NA respondents in each year. These low numbers will 

make complex analyses on these populations difficult. 

Other: The Bureau of Indian Affairs (BIA) and the Navajo Nation also conduct the 

YRBS on about a 3-year cycle. These data are owned by the BIA and the Navajo 

Nation. Potential users can contact BIA and the Navajo Nation for information 

about accessing these data. 

For access to the YRBSS data for the Navajo Nation, it is probable that the 

Nation will need to approve the use of data by outside researchers through the 

Navajo Nation Health and Human Research Review Board. The proposing party 

would be required to submit a proposal to the Navajo Nation with supporting 

documents on the purpose and use of the data, and benefits of outcome for the 

Navajos. A report summarizing the results of the Navajo Nation's YRBSS in 

1997, 2000, and 2003 is available for public dissemination at the following 

website: www.yrbs.navajo.org. 

5-212 
Youth Risk Behavior Surveillance System (YRBSS) 

(continued) 

Contact information concerning these data follows: 

BIA: 

Jack Edmo at JEdmo@bia.edu or (505) 248-6964 

Navajo Nation: 

Christine J. Benally, Ph.D. 

Lead Epidemiologist, Community Health Services 

CDR USPHS, Director Support Scientist Officer 

P. O. Box 160, N. U.S. Hwy 491 

Shiprock, NM 87420 

(505) 368-7427 desk 

(505) 368-6324 fax 

(505) 368-6300 office 

christine.benally@ihs.gov@ 

Access 

Requirements 

and Use 

Restrictions: 

YRBSS data are available to the public at no cost. 

Contact 

Information: 

Dr. Laura Kann 

Division of Adolescent and School Health 

National Center for Chronic Disease Prevention and Health Promotion 

Centers for Disease Control and Prevention 

Mailstop K-33 

4770 Buford Highway, NE 

Atlanta, GA 30341-3717 

(770) 488-6181 

LKK1@cdc.gov 

 

Or: healthyyouth@cdc.gov 

(770) 488-6161 

Data can be accessed at www.cdc.gov/yrbs. 

5-213 
6. Other Data Sources 

The following list describes data sources that were considered but not profiled for the catalog. 

Reasons for excluding data sources include the inability to identify AI/AN/NA individuals in the data 

source; a very limited number of AI/AN/NA individuals in the data source; lack of relevance to the 

identified key policy issues; extended length of time since the study was conducted; or data 

unavailable in any form for independent research. This list describes some basic information about 

these data sources and includes the reason(s) for excluding each data set. 

Alcohol and Drug Services Study 

This study involves a drug treatment facility and client sample survey, in which data are collected 

to estimate the length of a patient's stay, the cost of treatment, and to describe post-treatment 

status of clients. This study is excluded from the catalog as there are only 59 AI/AN individuals 

identified in the data set. 

Additional information about this study can be found at: 

http://www.oas.samhsa.gov/ADSS/ADSS2ClientCB.pdf 

Drug Abuse Treatment Outcome Study: Adolescent (DATOS-A) 

The study was designed to determine the outcomes of drug abuse treatment delivered in typical 

community-based programs by examining the role of treatment outcomes and program type, 

client characteristics, treatment received, therapeutic approaches, and provision of aftercare. 

Information was collected on a small number of AI/AN individuals, but these individuals cannot 

be identified in the data set. 

For more information about this study, contact: 

SAMHDA/ICPSR 

The University of Michigan 

P.O. Box 1248 

Ann Arbor, MI 48106-1248 

SAMHDA Helpline: 1-888-741-7242 

e-mail: samhda-support@icpsr.umich.edu 

Drug and Alcohol Services Information System (DASIS) 

This system is part of the National Directory of Drug and Alcohol Abuse Treatment Programs 

and the online Substance Abuse Treatment Facility Locator. It was excluded from this catalog 

because of its focus on facilities rather than individuals or families. 

Additional information about the DASIS can be found at: 

http://oas.samhsa.gov/dasis.htm#DASISinfo 

6-1 
Evaluation of the Tribal Strategies Against Violence (TSAV) Initiative in Four Tribal Sites in 

the United States, 1995 

This study was designed to develop comprehensive strategies in tribal communities to reduce 

crime, violence, and substance abuse. Approximately 90 interviews were conducted in four 

locations. Due to the limited number of sites and respondents and extremely limited access to the 

data, this study is excluded from the catalog. 

Questions regarding this study can be addressed to: 

Director 

National Archive of Criminal Justice Data 

Inter-University Consortium for Political and Social Research 

Institute for Social Research 

P.O. Box 1248 

University of Michigan 

Ann Arbor, MI 48106-1248 

Family Data on Public and Indian Housing 

This study of public and Indian housing projects and their tenants is 13 years old. The records are 

summaries for housing projects that do not provide individual-level information. Also, there is 

little documentation. 

Questions regarding this study can be addressed to: 

Information Services Division of Public and Indian Housing 

(202) 708-1445 

Gambling Impact and Behavior Study, 1997-1999 

This study on the gambling behavior of American adults and youth and the impact of gambling 

facilities on local economies is excluded because it does not identify people who are AI/AN/NA, 

nor does it focus on a specific geographic region with a large AI/AN/NA population. 

The data, codebooks, and other documentation are available at: http://www.icpsr.umich.edu/cgibin/bob/newark?study=2778&path=SAMHDA 

Hawaii Student Alcohol, Tobacco and other Drug Use Survey 

The purpose of this study is to assess the incidence and prevalence of alcohol, tobacco, and other 

drug use among students in grades 6 through 12 throughout the State of Hawaii. Results are based 

on student responses from public, private, and charter schools. The 2003 data set contains 

answers from 4,912 Native Hawaiian students. However, the Alcohol and Drug Abuse Division 

(ADAD) of the Hawaii Department of Health does not release this data for use by researchers. 

6-2 
Additional information about this study can be found at: 

Alcohol and Drug Abuse Division 

601 Kamokila Blvd. 

Kapolei, Hawai‘i, 96707 

(808) 692-7506 

http://www.hawaii.gov/health/substance-abuse/prevention-treatment/survey/adsurv.htm 

Hawaiian Community Survey 

This is an annual survey of households in the state of Hawaii in which at least one member is 

identified as Hawaiian. The survey was conducted from 2001 to 2005 as part of an effort to assess 

the true educational needs in Hawaii. The survey contains information on family well-being, 

childcare arrangements for preschool-age children, obstacles and achievements among school-age 

children, and continuing educational pathways among adults. At this time, there is no public use 

data file available for researchers, although the data may become available in the future. 

More information about this study can be found at: 

http://www.ksbe.edu/pase/researchproj-hicomsrvy.php 

Head Start Family and Child Experiences Survey (FACES) 

This study provides longitudinal information on a periodic basis on the characteristics, 

experiences, and outcomes for children and families served by Head Start. The study does not 

include American Indian/Alaska Native Head Start Programs and does not identify AI/AN/NA as 

one or more separate race categories. 

More information about this study can be found at: 

http://www.acf.hhs.gov/programs/opre/hs/faces/index.html 

Health and Diet Survey 

This periodic telephone survey measures and monitors public awareness, knowledge, attitudes, 

and reported behavior related to food and nutrition. Although the survey includes a race category 

for American Indians/Alaskan Natives, the number in this category is so small (n<100) that it is 

combined with other small categories into “other” for the public use data set. The survey also 

does not lend itself to analysis of a specific geographic region relevant to the AI/AN/NA 

population because of its small size (N=1,798). 

Additional information regarding this study can be found at: 

http://www.cfsan.fda.gov/~comm/crnutri3.html#demog 

6-3 
Medicare Current Beneficiary Survey 

This survey of Medicare beneficiaries residing in the United States and Puerto Rico contains very 

few AI/AN/NA cases in the sample (n=36 for the last round of data collection) and aggregation 

across years is not recommended. 

Additional information on this study can be found at: http://www.cms.hhs.gov/apps/mcbs/ 

Monitoring the Future: A continuing study of American youth 

This ongoing study of the behaviors, attitudes, and values of American youths contains very few 

American Indian (AI) respondents (i.e., approximately 1 percent of the grade 12 samples). For 

this reason, the public use data sets and restricted-access data sets do not contain an indicator for 

AI in the data set. 

Additional information regarding this study can be found at: 

http://www.monitoringthefuture.org/ 

National Health and Nutrition Examination Survey (NHANES) 

This survey collects data on the health and nutritional status of children and adults in the U.S. 

Because there is no oversample for Native American/Alaskan Natives in the NHANES, the 

sample of AI/AN/NA is very small and is grouped into the "other" category in the public use 

files. 

Additional information regarding this study can be found at: 

http://www.cdc.gov/nchs/nhanes.htm 

National Immunization Survey (NIS) 

Data from the NIS are used to produce timely estimates of vaccination coverage rates. The data 

do not identify the AI/AN/NA populations of interest for this catalog, as the public-use data files 

do not identify AI/AN/NA individuals. 

Additional information regarding this study can be found at: 

http://www.cdc.gov/nis/ 

National Longitudinal Survey of Youth 

This study focuses on the labor market experiences of American youth. The study included an 

oversample of blacks, Hispanics, and disadvantaged whites. However, the sample of AI/AN/NA 

individuals is too small to identify as a separate racial category in the data set. 

Additional information regarding this study can be found at: 

http://www.bls.gov/nls/nlsy97.htm 

6-4 
National Survey of Substance Abuse Treatment Services 

This study is a compilation of data collected from facilities and is used to update the National 

Directory of Drug and Alcohol Abuse Treatment Programs and the online Substance Abuse 

Treatment Facility Locator. This study was excluded from this catalog because its focus on 

facilities rather than individuals or families. 

Additional information regarding this study can be found at: 

http://oas.samhsa.gov/dasis.htm#nssats2 

Native Hawaiian Children and Families - Provider Survey and Consumer Survey 

The goal of the Consumer Survey was to gather information on consumers' perceptions of the 

services they receive from programs located in their communities, while the goal of the Service 

Provider Survey was to gather information from community agencies about their programs and 

the services they provide to Native Hawaiian children and families. It could not be ascertained 

whether the data from this study are publicly available. 

Additional information regarding this study can be found at: 

http://uhfamilydata.hawaii.edu/hi_child_ed/hi_child_ed.asp 

Navajo Health and Nutrition Survey 

The Navajo Health and Nutrition Survey was conducted from 1991 to 1992 to assess the health 

and nutritional status of Navajo Reservation residents using a population-based sample. The data 

do not appear to be available in any format. 

Property Owners and Managers Survey (POMS) 

The Property Owners and Managers Survey (POMS) was designed to learn more about rental 

housing and the providers of rental housing. A nationwide sample of approximately 16,300 

housing units that were rented or vacant-for-rent in the 1993 American Housing Survey National 

Sample (AHS-N) was selected, and a questionnaire was mailed to the property owner, manager, 

or other agent of the owner of each property containing a selected unit. This study is excluded 

because there are very few AI/AN/NA respondents in the data set and the data cannot be 

combined with other data to increase the number of AI/AN/NAs. In addition, the survey content 

focuses on the characteristics of the rental properties that the respondents own or manage, not the 

personal dwellings of the respondents. 

Contact the Financial and Market Characteristics Branch at (301) 763-3199 or visit 

ask.census.gov for further information on Property Owners & Managers Survey (POMS) Data. 

The actual data are hosted on-line by HUDUSER and are available for downloading from the 

following site: http://www.huduser.org/datasets/poms.html 

6-5 
Social Security Administration Benefits and Earnings Public Use File 

The 2004 Benefits and Earnings Public-Use File consists of a 1 percent random, representative 

sample of records of Old-Age, Survivors, and Disability Insurance beneficiaries who were 

entitled to receive a Social Security (OASDI) benefit for December 2004, and all benefit 

information is as of December 2004. This file does not contain any racial indicators. 

More information about this study can be found at: 

http://www.socialsecurity.gov/policy/docs/microdata/earn/index.html 

Study of Tribal and Alaska Native Juvenile Justice Systems in the United States, 1990 

This congressionally-mandated analysis of tribal juvenile justice systems was conducted in 1990-

1992. We could not find any indication that these data are available to researchers. 

Suicide and Risk Behaviors in an Incarcerated American Indian Population in the Northern 

Plains [United States], 1999-2000 

This multi-part study was an evaluation of five intake screening protocols in a county jail in the 

Northern Plains. The study is being excluded from the catalog because it was designed only to 

evaluate and compare the five protocols and the data collected cannot be combined to facilitate 

other analyses. 

Questions regarding this study can be addressed to: 

Director 

National Archive of Criminal Justice Data 

Inter-university Consortium for Political and Social Research 

Institute for Social Research 

P.O. Box 1248 

University of Michigan 

Ann Arbor, MI 48106-1248 

Survey of Active Duty Personnel 

This study focuses on the experiences, attitudes, and demographic characteristics of all Army, 

Navy, Marine Corps, Air Force, and Coast Guard active-duty members. Although there is a 

public use data file available for this study, AI/AN individuals can not be identified and 

geographic analysis of regions specific to this population is not possible. 

For more information concerning this study, contact Dr. Jim Caplan at 703-696-5848. 

6-6 
Survey of American Indians and Alaska Natives (SAIAN) 

The National Medical Expenditure Survey (NMES) series provides information on health 

expenditures by or on behalf of families and individuals, the financing of these expenditures, and 

each person's use of services. Conducted in 1987, the Survey of American Indians and Alaska 

Natives (SAIAN) was designed in collaboration with the Indian Health Service (IHS), and used 

the same data collection instruments, interview procedures, and time frame as the NMES 

Household Survey component. However, the SAIAN differed from the Household Survey in 

several respects. The SAIAN sample was interviewed only three times and was not given the 

supplements on long-term care, caregiving, and care-receiving. Also, SAIAN respondents were 

asked additional questions on topics such as use of IHS facilities and traditional medicine, and 

were given a modified self-administered questionnaire with separate versions for adults and 

children. Interviewers for the SAIAN were mainly American Indians or Alaska Natives, and 

about 20 percent of the interviews were not conducted entirely in English. Of these, 

approximately 40 percent were conducted entirely in the native language of the respondent. Data 

were collected on 7,071 AI/AN persons in the eligible dwelling units. 

Although the topic of this study is of clear relevance to the AI/AN population, this study is 

excluded from this catalog as these data are nearly 20 years old and cannot be combined with 

other data. 

For more information about this study, contact ICPSR User Support at netmail@icpsr.umich.edu 

or call (734) 647-2200 for information about accessing ICPSR data. 

Survey of Health Related Behaviors among Military Personnel 

This study provides comprehensive and detailed estimates of the prevalence of alcohol, illicit 

drug, and tobacco use and the negative effects of alcohol use among active-duty personnel. 

Although there is a public use data file available for this study, AI/AN individuals can not be 

identified and geographic analysis of regions specific to this population is not possible. 

Questions regarding this study can be addressed to: 

LTC Lorraine Babeu, Ph. D., CCC-A 

Office of the Assistant Secretary of Defense (Health Affairs) 

Tricare Management Activity 

Health Program Analysis & Evaluation 

5111 Leesburg Pike, Skyline 5, Suite 510 

Falls Church, VA 22041-3206 

Office: (703) 681-3636 DSN: 761-3636 

Fax: (703) 681-3682 

6-7 
Survey of Income and Program Participation (SIPP) 

The purpose of this study is to collect source and amount of income, labor force information, 

program participation and eligibility data, and general demographic characteristics to measure the 

effectiveness of existing federal, state, and local programs; to estimate future costs and coverage 

for government programs, such as food stamps; and to provide improved statistics on the 

distribution of income and measures of economic well-being in the country. However, the data 

files use the following race categories: White alone, Black alone, Asian alone, and Other. There is 

no way to identify AI/AN/NA individuals in the data set. 

More information about SIPP can be found at: http://www.bls.census.gov/sipp/ 

6-8 
7. Other Reports 

During the course of constructing the data catalog, the project team identified a number of useful 

reports that are listed below. This section is not meant to serve as a comprehensive listing of reports 

relevant to the topic of this catalog, but rather to serve as a potentially useful resource for users of the 

catalog. 

1. American Indian and Alaska NativeChildren: Findings From the Base Year of the 

Early Childhood Longitudinal Study, Birth Cohort (ECLS-B). 2005. Flanagan, K., and 

Park, J. (NCES 2005–116). U.S. Department of Education. Washington, DC: National Center 

for Education Statistics 

2. American Indian and Alaska Native Roundtable on Long Term Care: Final Report 

2002. Roundtable Report Prepared by: Jo Ann Kauffman, Kauffman and Associates, 

Incorporated, 425 West First Avenue, Spokane, WA. 

3. American Indians and Crime. Lawrence A. Greenfeld and Steven K. Smith, BJS 

Statisticians. February 1999, NCJ 173386 

http://www.ojp.usdoj.gov/bjs/abstract/aic.htm 

4. American Indian Reservations: Montana, North Dakota, and South Dakota. Pilot 

Project. Specialty Products, Part 1. AC-02-SP-1. October 2004. U.S. Department of 

Agriculture. http://www.nass.usda.gov/census/amindian.pdf 

5. American Indians on Reservations: A Databook of Socioeconomic Change between the 

1990 and 2000 Census. Jonathan B. Taylor and Joseph P. Kalt. January 2005. The Harvard 

Project on American Indian Economic Development. 

http://www.ksg.harvard.edu/hpaied/pubs/pub_151.htm 

6. Background Report on the Use and Impact of Food Assistance Programs on Indian 

Reservations. K. Finegold, N. Pindus, L. Wherry, S. Nelson, T. Triplett, R. Capps. January 

2005. The Urban Institute. 

7. Characteristics of Food Stamp Households: Fiscal Year 2004. Anni Poikolainen. 

September 2005. Mathematica Policy Research, Inc. 

8. Family Violence and American Indians/Alaska Natives: A Report to the Indian Health 

Service Office of Women’s Health. Principal Investigator: Laura A. Williams. 

http://www.ihs.gov/PublicInfo/PublicAffairs/PressReleases/Press_Release_2002/Compendiu

m_Part_I_and_II.pdf 

9. HIV/AIDS Surveillance Report, 2004. Centers for Disease Control and Prevention. Vol. 16. 

Atlanta: US Department of Health and Human Services, Centers for Disease Control and 

Prevention; 2005. http://www.cdc.gov/hiv/stats/hasrlink.htm. 

10. Indian Health Service Population Estimates and Projections 

http://www.ihs.gov/NonMedicalPrograms/IHS_Stats/Statistical_Databases.asp 

11. Ka huaka’i: 2005 Native Hawaiian Educational Assessment. S.K. Kana’iaupuni, N. 

Malone, and K. Ishibashi. Honolulu, HI: Kamehameha Schools, Pauahi Publications. 

7-1 
12. Longitudinal Study of the Indian Vocational Rehabilitation Services Program. May 

2003. Final Report was submitted to Rehabilitation Services Administration, U.S. 

Department of Education, in partial fulfillment of requirements under ED Contract No. 

HR92022001.

http://www.ilr.cornell.edu/ped/lsvrsp/PublishedResearchFiles/RTI_1stFINAL_Report.pdf 

13. Office of Indian Education Programs Annual School Report Card 

http://www.oiep.bia.edu/Report%20Cards/Annual%20Report%20Card%2004-05.htm 

14. Racial and Ethnic Disparities in the Experiences of Health Care Consumers. Karen 

Onstad. A research brief published in November 2005 by the National Consumer Assessment 

of Health Care Providers and Systems (CAHPS) Benchmarking Database, under AHRQ 

Contract Number 290-0I-0003. 

15. Regional Differences in Indian Health. Rockville, MD: Indian Health Service, 1998-99. 

http://www.ihs.gov/PublicInfo/Publications/trends98/region98.asp 

16. Sexually Transmitted Disease Surveillance, 2004. Centers for Disease Control and 

Prevention. Atlanta, GA: U.S. Department of Health and Human Services, September 2005. 

17. State Tobacco Activities Tracking and Evaluation (STATE) System. Centers for Disease 

Control and Prevention. Available at: http://www.cdc.gov/tobacco/statesystem. 

18. Status and Trends in the Education of American Indians and Alaska Natives. C.

Freeman and M. Fox. (2005). U.S. Department of Education, National Center for Education 

Statistics. Washington, DC: U.S. Government Printing Office, NCES 2005-108. 

19. Strong Heart Study Data Book: A Report to American Indian Communities. November 

2001. National Institutes of Health, National Heart, Lungs and Blood Institute, Division of 

Epidemiology and Clinical Applications. NIH Publication No. 01-3285. 

http:www.nhlbi.nih.gov/resources/docs/shs_db.htm 

20. Summary of Notifiable Diseases – United States, 2004. Centers for Disease Control and 

Prevention. Published June 16, 2006, for MMWR 2004: 53 (No. 53). 

http://www.cdc.gov/mmwr/summary.html 

21. Tobacco Use Among U.S. Racial/Ethnic Minority Groups—African Americans, 

American Indians and Alaska Natives, Asian Americans and Pacific Islanders, and 

Hispanics: A Report of the Surgeon General. U.S. Department of Health and Human 

Services, Centers for Disease Control and Prevention, National Center for Chronic Disease 

Prevention and Health Promotion, Office on Smoking and Health. 

1998http://www.cdc.gov/TOBACCO/sgr/sgr_1998/index.htm 

22. Trends in Indian Health, 2000-2001. Rockville, MD: Indian Health Service, 2000. 

http://www.ihs.gov/NonMedicalPrograms/IHS_Stats/Trends00.asp 

7-2 
Appendices 

Appendix A: Glossary 

Term Definition 

Census Division Census divisions are groupings of states and the District of 

Columbia that are subdivisions of the four census regions. There 

are nine census divisions, which the U.S. Census Bureau 

established in 1910 for the presentation of census data.

Census Region Census regions are grouping of states and the District of 

Columbia. The four regions (Northeast, Midwest, South and West) 

represent areas that were relatively homogeneous when they were 

established in 1910 and revised in 1950. 

Computer Assisted Personal 

Interviewing (CAPI) 

A method of data collection where the interviewer and respondent 

conduct an interview face-to-face. The survey questions are 

displayed on the screen of a computer. The interviewer reads the 

questions to the respondent and then enters the respondent’s 

answers into a database on the computer. 

Computer Assisted Telephone 

Interviewing (CATI) 

A method of data collection where the interviewer and respondent 

conduct an interview over the telephone. The survey questions are 

displayed on the screen of a computer. The interviewer reads the 

questions to the respondent and then enters the respondent’s 

answers into a database on the computer. 

Consolidated Metropolitan 

Statistical Area (CMSA) 

A metropolitan area is identified as a CMSA when it has a 

population of one million or more and also has separate 

component areas [Primary Metropolitan Statistical Areas 

(PMSAs)] that meet statistical criteria and are supported by local 

opinion. 

Core Based Statistical Area 

(CBSA) 

The term core based statistical area (CBSA) became effective in 

2000 and refers collectively to metropolitan and micropolitan 

statistical areas. The 2000 standards provide that each CBSA must 

contain at least one urban area of with a population of 10,000 or 

more. 

Cluster sampling When the basic sampling unit in the population is to be found in 

groups or clusters (e.g., individual respondents in households), the 

sampling is sometimes carried out by first selecting a sample of 

clusters (e.g., households) and then collecting data from all or a 

sample of the members of each selected cluster. 

Equal Probability Sample An equal probability sample is derived from a random sampling 

method in which all units on the sampling frame have an equal 

probability of being selected. 

Design Effect The design effect is the ratio of the actual variance of a sample to 

the variance of a simple random sample with the same number of 

elements. The size of the design effect helps researchers 

understand the extent to which the data collection approach affects 

the results. 

A-1 
Term Definition 

Disproportionate Stratified Sample A disproportionate stratified sample is a sampling method where 

particular units within a stratum have a higher probability of 

selection than other units. This method is often used when a 

sample design calls for an oversample of a particular group (i.e., 

AI/AN population). 

Federal Information Procession 

Standards (FIPS) code 

FIPS codes are a standardized set of numeric or alphabetic codes 

issued by the National Institute of Standards and Technology 

(NIST) to ensure uniform identification of geographic entities 

through all federal government agencies. The entities covered 

include states and statistically equivalent entities, counties and 

statistically equivalent entities, named populated and related 

location entities (such as, places and county subdivisions), and 

American Indian and Alaska Native areas. 

Field Period The field period denotes the start and end date of a data collection 

effort. 

Metropolitan Statistical Area 

(MSA) 

MSAs are metropolitan areas (MAs) that are not closely 

associated with other MAs. These areas typically are surrounded 

by nonmetropolitan counties (or county subdivisions in New 

England). 

Mitofsky-Waksberg sample design The Mitofsky-Waksberg sample design is a multi-stage sampling 

design method developed to maximize the efficiency of random 

digit dialing. Telephone numbers that are assigned to residential 

households tend to be grouped in banks of consecutive telephone 

numbers. The Mitofsky-Waksberg method groups telephone 

numbers into banks of 100 consecutive numbers using the area 

code, the 3-digit prefix, and the first 2 digits of the suffix. In the 

first stage of sampling, telephone numbers within the 100-banks 

are selected at random with replacement to determine if the 

number comes from a bank of residential numbers. If the 

telephone number is residential, the 100-bank is retained for the 

second stage of sampling. 

Multi-stage sample A multi-stage sample is derived from a sampling method that uses 

more than one stage of selection to draw the sample. The first 

stage of selection involves selecting the largest sampling unit [also 

called the primary sampling unit (PSU)], while the final stage of 

sampling involves selecting the smallest sample unit (for example, 

an individual or household). 

Panel survey/study A panel survey or study is a type of longitudinal study in which a 

group of subjects are surveyed on more than one occasion. 

Primary Metropolitan Statistical 

Area (PMSA) 

Each Primary Metropolitan Statistical Area (PMSA) consists of a 

large urbanized county or cluster of counties (or cities and towns 

in New England) that demonstrate very strong internal economic 

and social links, in addition to close ties to other portions of the 

larger area. If an area that qualifies as a metropolitan area (MA) 

has 1 million people or more, two or more PMSAs may be defined 

within it. 

Primary Sampling Unit (PSU) A primary sampling unit (PSU) is the first sample entity drawn in 

a multi-stage sample (in a single stage sample, the primary 

sampling unit is the first and only sampling unit drawn). 

A-2 
Term Definition 

Random Digit Dialing (RDD) Random Digit Dialing (RDD) is an automated method of dialing 

telephone numbers at random in a targeted area. Unlisted 

telephone numbers are included in the sample frame. 

Simple Random Sampling (SRS) Simple Random Sampling (SRS) is a method of sampling that 

gives all units in the sample frame an equal chance of being 

selected for inclusion in the sample, and an equal chance for 

selection for each of all possible samples of the same size. 

Standard error The standard error is a measure of the variation that might be 

expected to occur merely by chance in the characteristics of 

samples drawn equally randomly from the same population. It is 

the standard deviation of the sampling distribution of a statistic. 

The smaller the standard error, the better the sample statistic is as 

an estimate of the population parameter. 

Stratified Sample In stratified sampling, an independent sample is selected from 

each strata of the population. Strata are divisions of the 

populations into relevant subsets (e.g., race, location). 

Two-stage sampling A two-stage sample is a simple case of a multi-stage sample. The 

population to be sampled is first classified into primary sampling 

units (PSUs) (e.g., census tracts) each of which consists of a 

number of the basic sampling units or the secondary sampling 

units (SSUs) (e.g., households within the census tract). A sample 

of these PSUs is taken, constituting the first stage, and then a 

sample of the SSUs is taken, constituting the second stage. 

Wave Wave is a term used to describe a single field period for a study 

that involves collecting data more than once (such as in a panel 

study). 

Sources

Kish, L. Survey Sampling. 1965. John Wiley & Sons, Inc., New York, NY. 

Pocket Dictionary of Statistics. 2002. The McGraw-Hill Companies, Inc., New York, NY. 

U.S. Census Bureau online glossary: http://www.census.gov/main/www/glossary.html 

OECD Glossary of Statistical Terms: http://stats.oecd.org/glossary/index.htm 

A-3 
Appendix B: Data Set Aggregation 

Researchers may want to combine survey data from two or more data collection efforts (e.g., 

combining data across years for a particular study) in order to construct an analytic data set 

containing more respondents than the individual data sets themselves. This combined data set could 

have greater statistical power and precision to answer research questions. As an example, consider 

two data sets, one with 400 respondents and the other with 600 respondents. The confidence interval 

for an estimate of 40 percent is ± 4.8 percent for the smaller survey and ± 3.9 percent for the larger 

survey.9

 If the surveys are combined, yielding a total of 1,000 respondents, the confidence interval 

drops to ± 3.0 percent. The combined confidence interval is 38 percent less than that for the smaller 

survey and 23 percent less than that for the larger survey. Combining the surveys has substantially 

increased the precision of survey estimates over those for each of the surveys individually. 

Combining data from multiple surveys is often considered when the research focus is upon relatively 

rare or under-sampled populations. 

Many of the issues involved in determining if survey data can be combined and how they 

should be combined are substantive and require consideration by subject-matter experts rather than 

statistical consultation. Moreover, these substantive issues should be resolved before any statistical 

consultation can take place. This appendix focuses primarily on the substantive issues that need to be 

addressed in order to decide if two or more data sets can be successfully aggregated. The appendix 

only briefly touches on the statistical operations that may be required to aggregate multiple data sets. 

Further analytical and statistical consulting may be required before such an aggregation can be 

accomplished correctly. 

Combining Survey Data Sets: Substantive Questions to Address 

The following four questions can serve as a guide to determining the advisability of 

combining data from multiple survey efforts. Each of these questions is discussed in more detail in 

the paragraphs that follow: 

1. Are the populations the same for the different data collection efforts? 

2. Do survey questions and response categories match? 

3. Might differences in survey administration dates affect survey results? 

4. What were the survey sample designs? 

 

9 In this example we assume simple random sampling and are using the formula ± 1.96*√((p*q)/N) for calculating the 

confidence interval of a proportion. 

B-1 
Are the populations the same for the different data collection efforts? First, we must 

determine if the surveyed populations match. Are there age, geographic, or other definitions that 

differ among the surveys? If one survey defines its adult population as 18 to 65 years-of-age and the 

other as 16 to 85 years-of-age, the differences between the populations may make the meaning of 

responses somewhat different. If this is so, combining the data sets would not be reasonable. 

Similarly, the geographic areas sampled may differ between surveys. For example, does it make sense 

to combine Oregon respondents with those from Wyoming? The determination of matching 

populations is essentially a substantive, not statistical, issue. The researcher must determine if the 

differences between the populations will make a substantive difference in the meaning of their 

responses or if some reconciliation could be made that would correct for those differences in 

response. In the case of the age difference between the two survey populations presented earlier, the 

reconciliation may be to either restrict the age range to the most limited or expand it to the most 

inclusive. In either case, the researcher should be able to clearly justify his/her rationale for deciding 

to combine the two populations or changing one population to match another should he/she decide to 

combine data sets where the populations differ. 

Do survey questions and response categories match? If the survey populations (frames) 

are considered comparable, the next question concerns the survey content and question presentation. 

Here the survey questions of research interest, the response and reporting categories offered, and the 

context of the questions must be compared. Is the wording of questions of interest in the surveys 

exactly the same? Or, if not exactly the same, are the wordings close enough to be considered the 

same? Are the response categories the same or can they be recoded into the same categories? If 

response categories cannot be altered to match, combining the data is not feasible. 

A similar review must be made of the variables that will be used to form subgroups for 

reporting purposes. Often these reporting subgroups are defined by demographic characteristics such 

as age, race/ethnicity, or geographic location. Are the subgroups that can be formed for the surveys 

comparable? Again, if comparable subgroups cannot be formed for the reporting of survey data, it 

makes no sense to combine survey data. 

Finally, does the placement of the questions of interest in the respective questionnaires differ? 

If so, could this difference influence responses? Stated slightly differently, does the placement of 

questions in the flow of the questionnaires predispose respondents to respond differently? As with the 

B-2 
judgments that must be made regarding population comparability and survey content difference, this 

decision will be based on the judgment of the researcher and should be carefully documented. 

Might differences in survey administration dates affect survey results? Combining 

surveys with different administration dates assumes that survey results are not time-dependent. This 

assumption presumes that survey results for an earlier survey and a later survey are independent and 

do not differ in a way that relates to the date of survey administration (i.e., no intervening events or 

changes in circumstances occurred that may influence survey responses). The question for the 

researcher is whether this assumption is appropriate. As was the case with the previous issues, 

determination of whether it is reasonable to combine surveys given the time difference between their 

administrations is an issue that should be carefully considered. 

What were the survey sample designs? Unlike the previous considerations, consideration of 

sample designs does not lead to a clear yes or no decision regarding the combining of surveys. 

Sample design considerations provide information that helps to inform and structure the combining of 

survey data. Presumably, researchers will first consider issues related to the sample frame, survey 

data, and survey administration time differences before considering the sample design, and thus have 

some indication about the possibility of combining data from multiple surveys. In reviewing survey 

sample designs it is desirable to know the mechanics of sample selection (e.g., a random digit dialing 

(RDD) telephone survey, a multistage sample beginning with selection of a geographic area then 

selection of housing units then selection of respondents, or a sample selected from a preexisting list). 

This knowledge along with the rates of selection used for each survey provides an indication 

regarding the similarity of sample designs. Generally, the more similar the sample designs, the more 

defensible the decision to combine. This is not to say that surveys with very different sample designs 

cannot be combined, only that the case for combining may be more difficult to justify. 

Combining Survey Data Sets: Technical Issues 

This section addresses the mechanics of constructing weights when combining multiple 

weighted surveys that cover a common population. Rather than enumerating the range of possible 

combining strategies, this section presents a general strategy of scaling the weights that optimizes the 

precision of combined survey estimates overall. This strategy is meant as an example of statistical 

manipulation that will be required when weighted data sets are combined. It is not meant to serve as a 

guide for use with every set of data sources. Additional statistical consulting should be sought before 

data are combined and analysis begins. 

B-3 
Scaling Weights. It is possible, in some configurations of sample and weighting designs, that 

estimates for combined data sets may have less precision than those for each of the surveys being 

combined.10 This condition is clearly at odds with the common reason for combining surveys – to 

increase the statistical power and precision of combined survey estimates over those for the individual 

surveys. This may occur because different sample designs and survey weighting strategies can affect 

the precision of combined survey estimates. Consider the circumstance of combining two surveys of a 

common population. Each survey was weighted to reflect the survey population. If the data are simply 

combined with no adjustment to weights, the combined weighted data set would yield population 

counts twice that of the population. Furthermore, this combined data set would not take into account 

response rates or survey design effects resulting from the sampling strategies. The result of combining 

these data sets could lead to less statistical power and less precise survey estimates rather than more 

power and more precise survey estimates. 

Combining survey data sets covering a common population requires an adjustment or scaling 

of the survey weights to reflect the population of interest as well as the precision of the individual 

surveys. In general terms, for two surveys, the scaled weights for common domains are: 

 αw1i if w1i is the weight from Survey 1, and

wci = 

 ((1-α)w2i if w2i is the weight from Survey 2

where wci is the combined weight and α is the scaling factor subject to the restriction 0 ≤ α ≥ 1. As a 

result of the boundaries for α, (α + (1-α)) = 1, so the combined weighted estimate will equal the 

population total. Where the domains of the two surveys are not common, for example, the weight for 

each survey can be used without scaling. 

There are several ways to select values for α. Among the most common are setting α as a 

function of each survey’s sample size or setting α so that combined survey estimates have the 

smallest possible variance. The method recommended here minimizes the variance of combined 

survey estimates. In this method, α is set as a function of the variability of weights for the two 

surveys. Basically, the survey with the greatest precision is given greater relative influence in the 

scaling of weights. The formula used for calculating α is: 

 

10 See, for example, Cervantes, Jones, and Wilson (2005), 2005 Workplace and Equal Opportunity Survey of Active Duty 

Members: Statistical Methodology Report. 

B-4 
)()(

)( 1

1 2

1

i i

i

wDEFF wDEFF

wDEFF

+

α −=

where DEFF(w1i) and DEFF(w2i) are the respective design effects due to unequal weighting for 

Survey 1 and Survey 2 (it makes no difference which DEFF is used in the numerator). Calculation of 

the design effect due to unequal weighting for a survey is accomplished using the following formula: 

2

1 1 )100/)((1)(wDEFF i += wCV i

where CV(w1i) is the coefficient of variation (CV) for the weights in Survey 1. The CV is calculated 

by dividing the standard deviation of the weights by the mean of the weights. This measure of relative 

dispersion is usually expressed as a percentage so the standard deviation divided by the mean is 

usually multiplied by 100. 

Summary 

 The determination of whether to combine surveys for the construction of a more robust 

combined database is initially a substantive, not statistical, question. Answers to these questions, 

however, require considerable content familiarity. The initial questions presented in this appendix 

regard nuances of sample frame construction, questionnaire characteristics (question wording, 

response categories, and question placement context), dates of survey administration, and sample 

design. These issues are best evaluated by persons familiar with the research questions at hand and 

the population(s) of interest. The second section of the appendix presents an example of an approach 

for adjusting the combined weight when two weighted surveys covering the same population are 

combined. This example provides information for a general approach that will ensure that 

combination results in increased precision of the survey estimates and, more importantly, 

demonstrates the level of statistical expertise that may be required to correctly aggregate two data 

weighted data sources. 

B-5 
Appendix C: Review Protocol 

Reviewer: 

Name of Data Source being Reviewed: 

Sponsoring Agency: 

Policy issue relevant to data source (reference to policy document): 

Brief description of data set: (Include brief statement of purpose, common uses, and 

all major topics covered in the data set.) 

1. Determine if data source should be included in catalog. 

A. Does the data source allow you to identify people who are AI/AN/NA? 

□ Yes 

□ No (See below) 

If not, can you focus on a specific geographic region with a large AI/AN/NA 

population? 

□ Yes 

□ No (Exclusion Criteria)

B. Is a data set available to researchers? 

□ Yes, available to public 

□ Yes, available through data use agreement (please 

explain process): 

 

□ Data are only available for government employees 

and contractors 

□ Aggregate program report is available on paper 

only (Exclusion Criteria) 

□ Data set is not available, but can request analyses 

□ Data set is not available, but published tables and 

reports are available

□ Data set is not available at all (Exclusion Criteria)

□ Other, explain: 

Is there a cost associated 

with use of the data set? 

□ Yes (Cost: $_____no 

cost) 

□ No 

C-1 
Reviewer: 

Name of Data Source being Reviewed: 

C. Please list the relevant contact and location information regarding this data 

source. Please include contact information for any required data use agreements 

and the location of the actual data. 

D. If data collection was privately funded, were the data collected primarily to fill 

advocacy needs, lobbying purposes, or to support corporate interests? 

□ Yes (Exclusion Criteria), explain below: 

□ No 

□ Data are publicly funded 

E. Total unweighted AI/AN/NA population in data source (please include all possible 

breakdowns): 

If unweighted n < 100, would it be possible to combine this data source across 

multiple iterations of data collection to increase the size of the population? 

□ Yes , explain below: 

□ No (Exclusion Criteria)

F. What is the coverage of the data set? (Check only one)

□ National 

□ Smaller geographic area of clear relevance to AI/AN/NA population 

□ A specific AI/AN/NA subpopulation only (e.g., single tribe, Pacific Islanders) 

□ None of the above (Exclusion Criteria) 

G. What is the timeframe of the data set? 

□ Mid-1990s or later (can be series that began earlier as long as continues past 

mid-1990s) 

□ Earlier than mid-1990s 

 If earlier than mid-1990s, can a strong argument be made to include this data 

set? 

□ Yes Explain: 

□ No (Exclusion Criteria) 

C-2 
Reviewer: 

Name of Data Source being Reviewed: 

H. Is this a 

survey? 

□ Yes 

For survey data, is detailed documentation available (either 

hard-copy or electronically) for: 

Instruments used for data collection (examples of question 

□ No phrasing)? 

□ Yes 

□ No (Exclusion Criteria)

Data limitations (e.g., coverage, data completeness, 

response rates)? 

□ Yes 

□ No (Exclusion Criteria)

Sampling design techniques? 

□ Yes 

□ No (Exclusion Criteria)

□ Not Applicable (e.g., Census) 

Weighting methods? 

□ Yes 

□ No (Exclusion Criteria)

□ Not Applicable (data were not weighted) 

Contact information for program officials? 

□ Yes 

□ No (Exclusion Criteria)

I. Is this program 

reporting data? 

(Include 

program 

enrollment)

□ Yes 

□ No 

For program-level data, is detailed documentation available 

(either hard-copy or electronically) for: 

Contact information for program officials (e.g., primary and 

secondary contacts, telephone numbers and email 

addresses)? 

□ Yes 

□ No (Exclusion Criteria) 

Data limitations (e.g., coverage, data completeness)? 

□ Yes 

□ No 

J. Is this a registry (e.g., vital statistics, state cancer registry, etc.)? 

□ Yes 

□ No 

K. Is this a qualitative study (e.g., case studies, focus groups, cognitive interviews)? 

□ Yes (Exclusion Criteria)

□ No 

C-3 
STOP AND DETERMINE WHETHER THE DATA SET WILL BE INCLUDED IN 

THE CATALOG BEFORE CONTINUING 

Based on initial review, is this data source being profiled for possible inclusion in the 

catalog? 

□ Yes 

□ No, explain: 

If not in the data catalog, do you recommend that this data source be included in the 

list of unreviewed data sources? (Possible exclusions include qualitative, 

experimental, or methodological studies or studies with a significant lack of 

documentation.) 

□ Yes, explain: 

□ No, explain: 

C-4 
Reviewer: 

Name of Data Source being Reviewed:

2. Describe data source to be included in the catalog.

A. How are AI/AN/NA individuals identified in the data set? (Please note if separate 

multi-racial categories exist (such as American Indian and other vs. American 

Indian alone.) Also, if instructions for self-reporting are available, please include 

them here.)

B. Does the data source allow you to identify members of a federally recognized

tribe? 

□ Yes (Please explain how they are distinguished:) 

□ No 

Does the data source allow you to identify members of a state-recognized tribe? 

□ Yes (Please explain how they are distinguished:) 

□ No 

C. What geographic area(s) does the study cover? 

□ National 

□ State(s), specify: 

□ County(ies), specify: 

□ Reservation(s), specify: 

□ Other region(s), specify: 

D. What is the unit of analysis? 

□ Individual 

□ Geographical area (please specify:) 

□ Household or family unit (please specify definition of household:) 

□ Other, specify: 

E. How are geographic areas identified? (e.g., zip codes, census tracts, counties, 

county subdivisions, reservations, frontier areas)

C-5 
Reviewer: 

Name of Data Source being Reviewed:

F. What level of geographic analysis is possible? 

G. What AI/AN/NA subpopulations are identified? 

□ American Indian alone 

□ Alaska Native alone 

□ Native Hawaiian alone 

□ Pacific Islander alone 

□ Specific tribal affiliation: __________________________ 

H. Is participation in this data collection mandatory or optional? 

□ Mandatory 

□ Optional, with incentives 

□ Optional, without incentives 

I. Using the checklist below, please indicate all policy issues that are covered in 

this data source: 

Health Status and Health Policy Issues

□ Measurement of health status (e.g., self-reported, % with disability, mortality/morbidity 

rates, trends over time) 

□ Disease-specific measurements (e.g., % with diabetes, TB, STDs, cancer, etc.) 

□ Key health disparities of priority interest (e.g., prenatal care/birth outcomes, cancer 

mortality, substance abuse/alcohol use/mental health/suicide) 

□ Factors contributing to measured health disparities (e.g., access to health care, 

insurance coverage, utilization rates, health care financing, socioeconomic factors, 

preventative measures (i.e., immunization rates) 

□ Identification of evidence-based practices and programs that address causes of health 

disparities, result in positive health outcomes, and are generalizable/replicable 

□ Role of traditional medicine in AI/AN/NA communities 

Economic Well-being

□ Income status (e.g., household income/poverty status, per capita income) 

□ Unemployment rates 

□ Economic assistance program participation rates (e.g., TANF/TTANF, food stamps) 

□ Economic opportunity (e.g., number of businesses/jobs, work history) 

□ Measurement of economic/employment disparities between AI/AN/NA and general 

population 

□ Factors contributing to economic disparities (e.g. lack of child care arrangement, 

transportation barriers) 

□ Identification of evidence-based practices and programs for reducing economic 

disparities and are generalizable/replicable 

C-6 
Reviewer: 

Name of Data Source being Reviewed:

(Policy Issues Checklist continued) 

Education Levels and Opportunities

□ Educational attainment (e.g., last grade completed, literacy/numeracy skills) 

□ Educational opportunities (e.g., Head Start, special education programs, school 

financing) 

□ Factors contributing to educational disparities (e.g., parents’ education level, average 

education in city/county, education spending per capita, and other socioeconomic 

factors) 

□ Identification of evidence-based practices and programs that produce positive 

educational outcomes and are generalizable/replicable 

Family Well-being

□ Measures of well-being for families/households (e.g., families with low income levels, 

homeless families, teen pregnancy/birthrates, household size and composition) 

□ Factors contributing to well-being disparities of families (e.g., socioeconomic factors, 

education levels of family adults, housing quality, public transportation availability) 

□ Identification of evidence-based practices and programs that improve family well-being 

and are generalizable/replicable 

Child Well-being

□ Measures of well-being for children (e.g., children in foster care, incarcerated children) 

□ Factors contributing to well-being disparities of children (household composition, 

martial status of parents, foster care placement) 

□ Identification of evidence-based practices and programs that improve child well-being 

and are generalizable/replicable 

Elder Well-being

□ Measures of well-being for elders (e.g., elders with low income levels, homeless 

elders, elder abuse) 

□ Factors contributing to well-being disparities of elders (e.g., socioeconomic factors, 

living arrangements, ADL/IADL, family members in proximity, services available/used 

(Meals on Wheels/elder transportation) 

□ Identification of evidence-based practices and programs that improve elder well-being 

and are generalizable/replicable 

Housing Issues

□ Housing quality (e.g., rooms per person, running water, electricity, heat, age of 

building) 

□ Type of housing 

□ Housing ownership 

□ Rental unit quality and cost 

□ Homelessness 

Demographic and Economic Indicators (e.g., age distribution, marital status, 

household composition) 

C-7 
Reviewer: 

Name of Data Source being Reviewed:

(Policy Issues Checklist continued) 

Transportation Quality and Availability Issues

□ Transportation quality (e.g., maintenance of roads, availability of paved roads, child 

restraint laws) 

□ Transportation availability (e.g., availability of public transit, vehicle ownership per 

household) 

Justice System Issues

□ Rates of involvement with justice system (e.g., arrest/conviction/probation/parole 

rates) 

□ Differences in resolution of arrest, by type of court system (e.g., federal, tribal, state, 

local) 

□ Lifetime probability of being a victim of a violent crime 

□ Lifetime probability of being a victim of a non-violent crime 

□ Domestic violence rates 

□ Child maltreatment rates 

□ Factors contributing to disparities in involvement with justice system and outcomes 

(e.g., family stability/foster care placement, family members’ history of legal system 

involvement, race/ethnicity, truancy history) 

□ Identification of evidence-based practices or programs to reduce involvement with 

justice system, reduce recidivism, and are generalizable/replicable

Military Service/Veterans’ Issues

□ Military service rates (e.g., % served in military, % retired from military with benefits) 

□ Eligibility and use of veterans administration health facilities 

□ Eligibility and use of other veterans administration benefits (e.g. housing loans, 

educational benefits) 

J. Describe data collection methodology (e.g., mode).

K. What is the response rate for this study? (If possible, please provide any details 

on how the response rate was calculated). 

L. How frequently are the data collected? 

□ One-time effort 

Year of data collection: 

□ More than once (e.g., annual study, semi-annual study, longitudinal study, 

irregular points of data collection)

 Please describe (include the years the data are available for and any plans 

for future data collections): 

C-8 
Reviewer: 

Name of Data Source being Reviewed: SURVEYS ONLY 

M. Describe sampling method, if any. (e.g., simple random sample, two-stage 

stratified sample)

N. Was the AI/AN/NA population oversampled? 

□ No 

□ Yes (Please describe:) 

O. Does the methodology report include any of the following (please provide as 

much information as possible): 

□ Effective sample size (n=_____________) 

□ Design effects (deff): ___________ 

□ Standard errors for estimates: _______________ 

□ Description of available power to detect differences (This may be found in 

the sample section of a methodology report. Please specify variables used 

for calculation and for which groups differences are to be detected)

P. If multiple years of data are available and are suitable for aggregation, what 

would be the result of the aggregation (e.g., sample size)? 

Q. Summarize the strengths of the data source. (Include areas such as coverage in 

terms of sample size and content about AI/AN/NA population, relevance to policy 

areas, amount of missing data, response rate, weighting, quality of 

documentation, psychometric assessments) 

Key Issues

□ Large number of AI/AN/NA respondents 

□ Relevance to key policy issues, including: 

□ Health 

□ Child welfare 

□ Multiple years of data are available 

Additional Strengths:

C-9 
Reviewer: 

Name of Data Source being Reviewed:

R. Summarize the limitations of the data source. (Include areas such as coverage of 

AI/AN/NA population, content pertaining to the target population, relevance to 

policy areas, amount of missing data, response rate, weighting, quality of 

documentation) 

Key Issues

□ Small number of AI/AN/NA respondents 

□ Lack of relevance to key policy issues 

□ Multiple years of data are not available 

Additional Limitations:

S. Was this data collection effort authorized by any specific legislation? (Answer yes 

if Congress created a mandate to authorize this specific data collection effort.)

□ Yes (Explain:) 

□ No 

T. Other comments? 

U. Document materials in project files related to this data source, or related web 

links. 

C-10 
Appendix D: List of Sponsoring Agencies 

Sponsor Data Set 

National Science Foundation • Panel Study of Income Dynamics (PSID) 

State of Hawaii Department of Health 

(DOH) 

• Hawaii Health Survey (HHS) 

State of Washington • Washington State Population Survey (WSPS) 

The Urban Institute • National Survey of America’s Families (NSAF) 

U.S. Department of Agriculture (USDA) • Census of Agriculture (2002) 

 • Food Stamp Quality Control Database (FSPQC) 

U.S. Department of Commerce • American Community Survey (ACS) 

 

 

• Census 2000 

• Census 2000 – American Indian and Alaska Native Summary 

File 

 

 • Current Population Survey (CPS)* 

• National Longitudinal Mortality Study (NLMS)* 

• Small Area Income and Poverty Estimates (SAIPE) 

• Survey of Program Dynamics 

U.S. Department of Education (DoE) 

 

 

 

 

 

• Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) 

• Early Childhood Longitudinal Study, Kindergarten Class of 

1998-99 (ECLS-K) 

• Integrated Postsecondary Education Data System (IPEDS) 

• National Assessment of Adult Literacy (NAAL) 

• National Household Education Surveys Program (NHES) 

• National Indian Education Study (NIES) 

U.S. Department of Justice (DoJ) 

 

 

 

 

 

 

• Annual Survey of Jails (ASJ) 

• Census of Jails 

• Census of Tribal Justice Agencies in Indian Country (2002) 

• National Crime Victimization Survey (NCVS) 

• Survey of Jails in Indian Country (SJIC) 

• Uniform Crime Reports 

• Youth Gangs in Indian Country 

U.S. Department of Labor (DoL) 

 

• Consumer Expenditure Surveys (CE) Interview and Diary 

Surveys 

• Current Population Survey (CPS)* 

U.S. Department of Transportation • National Household Travel Survey (NHTS) 

U.S. Department of Veterans Affairs • National Survey of Veterans (NSV) 

UCLA Center for Health Policy Research • California Health Interview Survey (CHIS) 

U.S. Department of Housing and Urban 

Development (HUD) 

 

• A Picture of Subsidized Households (1998) 

• American Housing Survey (2003) 

 • American Housing Survey: Metropolitan Surveys 

D-1 
Sponsor Data Set 

U.S. Department of Health and Human 

Services (DHHS) 

 

 

 

 

• Adoption and Foster Care Analysis and Reporting System 

(AFCARS) 

• Behavioral Risk Factor Surveillance System (BRFSS) 

• CAHPS Health Plan Survey Response Data 

• Head Start Program Information Report 

• Health Behavior in School-aged Children (HBSC) • Health Information National Trends Survey (HINTS) • Health and Retirement Study (HRS) • Medicaid Analytic Extract (MAX) • Medical Expenditure Panel Survey (MEPS) • Medicare Denominator File • Medicare Utilization – Standard Analytic Files (SAFs) • National Aging Program Information Systems (NAPIS) State 

Performance Reports 

 • National Ambulatory Medical Care Survey (NAMCS) 

• National Child Abuse and Neglect Data System (NCANDS) 

• National Epidemiologic Survey on Alcohol and Related 

Conditions (NESARC) 

 

 

 • National Health Interview Survey (NHIS) 

 • National Hospital Ambulatory Medical Care Survey 

 (NHAMCS) 

 • National Longitudinal Mortality Study (NLMS)* 

 • National Mortality Followback Survey (NMFS) • National Survey of Child and Adolescent Well-being 

(NSCAW) 

 • National Survey on Drug Use and Health (NSDUH) • National Survey of Family Growth (NSFG) • National Vital Statistics System: Linked Birth-Infant Death 

(NVSS-I) 

 • National Vital Statistics System: Mortality (NVSS-M) • National Vital Statistics System: Natality (NVSS-N) • Pediatric Nutrition Surveillance System (PedNSS) • Pregnancy Nutrition Surveillance System (PNSS) • Pregnancy Risk Assessment Monitoring System (PRAMS) • Resource and Patient Management System (RPMS) and 

National Patient Information Reporting System (NPIRS) 

• Runaway and Homeless Youth Management Information 

System (RHYMIS) 

• Surveillance, Epidemiology, and End Results (SEER) 

• Temporary Assistance for Needy Families (TANF) and Tribal 

TANF 

• Tobacco Use Supplement to the Current Population Survey 

(TUS-CPS) 

• Treatment Episode Data Set (TEDS) 

• United States Renal Data System (USRDS) 

• Youth Risk Behavior Surveillance System (YRBSS) 

* Denotes data sets that have more than one sponsor. 

D-2