FIND Disability Statistics
American Community Survey (ACS)
- Employment Rate
- Not Working but Actively Looking for Work
- Full-Time / Full-Year Employment
- Annual Earnings
- Annual Household Income
- Supplemental Security Income (SSI)
- Educational Attainment
- Veterans Service-Connected Disability
- Health Insurance Coverage (and Type)
Current Population Survey (CPS)
EEOC Charge Data
Rehabilitation Dataset Directory: Dataset Profile
Dataset: Health and Retirement Study (HRS)
|Dataset Full Name||Health and Retirement Study|
The Health and Retirement Study (HRS) is a nationally representative longitudinal panel survey conducted biennially. The study follows a cohort(s) of adults ages 50 years or older in the United States. The purpose of the HRS is to understand the health shifts in older adults and demographic changes in labor force participation at the end of their service. It provides detailed information on demographic characteristics, income, work, assets, housing, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, and health care expenditures. The original study began in 1992 and follows up onreinterviews the respondent and their spouse or partner every two years through using an in-depth interview questionnaires. A new cohort is added to the sample every six years.
In 1998, the original HRS was merged with Asset and Health Dynamics Among the Oldest-Old (AHEAD, born before 1923). In 1998, the HRS also included a Children of the Depression cohort (CODA, born 1923-1930) and a War Baby cohort (WB, born 1942-1947). In 2004, an Early Baby Boomer cohort (EBB, born 1948-1953) was added, and in 2010 a Mid Baby Boomers cohort (MBB, born 1954-1959) was added in 2010, and a Late Baby Boomers cohort (LBB, born 1960-1965) was added in 2016.
Off-year questionnaires are also submitted to a subset of HRS respondents. These include: the Consumption and Activities Mail Survey (originating in 2001), the Disability Vignette Survey (2007), the Health Care and Nutrition Study (2013), the Human Capital and Educational Expenses Mail Survey (2001), the Life History Mail Survey (2015), the Internet Survey (originating in 2003), and the Veterans Mail Survey (2013).
|Key Terms||Aging, Longitudinal, Health, Income, Retirement, Disability, Housing, Pension, Family characteristics|
National Institutes of Health (NIH):
National Institute on Aging (NIA)
University of Michigan's Institute for Social Research
|Health Conditions/Disability Measures|
Alzheimer's/dementia, Arthritis, Body mass index (BMI)/obesity, Cancer, Cardiovascular conditions, Chronic pain, Depression, Diabetes, Eye diseases, Orthopedic conditions, Pulmonary disorders, Stroke,
|Disability Measures||Ambulatory disability, Cognitive disability, Communication impairment, Functional limitations (ADLs and/or IADLs), Hearing disability, Independent living disability, Mental health disability, Physical disability, Self-care disability, Special equipment use/assistive technology, Visual Disability, Work limitation||Measures/Outcomes of Interest|
|Topics||Income, Education, Internet use, Housing, Employment, Employer accommodations, Assets, Pension plans, Health insurance, Health care expenditures, Assistive Technology use||Sample|
Nationally representative sample of adults over the age of 50
Initial (Wave 1) number of respondents in sample by cohort:
|Unit of Observation||Individual|
|Geographic Coverage||United States|
|Data Collection Mode||
Primarily personal interview and phone surveys.
Restricted data linkages available to the following sources:
|Data Collection Frequency||Biennial||Strengths and Limitations|
Nationally-representative, multi-stage area probability sample. Excellent re-interview response rates of 90% or higher. Wide range of questions asked including: functional status, disability, economic factors, retirement, health services utilization, social security disability benefits, veterans’ benefits and workers’ compensation. The majority (80%) of HRS participants allow Medicare record based disease history data to be linked to their HRS data.
**NOTE Medicare data access requires a Data Use Agreement (DUA) from the Centers for Medicare & Medicaid Services (CMS)
** Restricted data linkages include: biometric and biological information to the online genetics database of the National Institutes of Health (20,000 participants), National Death Index, Social Security benefit and Medicare files.
|Limitations||Information on chronic disease and health-care utilization are based on self-reports. Proxy responses used in about 20% of the 2008 core interviews for the oldest cohort (born 1890-1923) . Some question wording has been altered over time making some comparisons problematic. Questionnaire skip patterns and survey wave design can be difficult to follow.||Data Details|
|Data Access Requirements||Data use agreement, No cost|
The Health and Retirement Survey: Aging in the 21st Century. Challenges and Opportunities for Americans (2017, January).
|Data Components||Biennial Datasets Longitudinal Datasets Off-Year Studies Restricted data files|
Other longitudinal ageing studies:
Servais, Marita A. (2010, June). Overview of HRS Public Data Files for Cross-sectional and Longitudinal Analysis.
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The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).
Other CLDR supported resources and collaborative opportunities:
- Archive of Data on Disability to Enable Policy and research (ADDEP)
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- Pilot Project Program
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Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.
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