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Dataset: Health and Retirement Study (HRS)

Basic Information
Dataset Full Name Health and Retirement Study
Dataset Acronym HRS
Summary

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 with interviews the respondent and their spouse or partner take 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
Study Design Longitudinal
Data Type(s) Survey
Sponsoring Agency/Entity

National Institutes of Health (NIH):

National Institute on Aging (NIA)

University of Michigan's Institute for Social Research
Health Conditions/Disability Measures
Health Condition(s)

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
Sample Population

Nationally representative sample of adults over the age of 50
Sample Size/Notes

Initial (Wave 1) number of respondents in sample by cohort:

  • 12,652 - HRS: Original R born 1931-1941
  • 8,222 - AHEAD: Original R born in 1923 or earlier
  • 2,320 - CODA (Children of Depression): Original R born 1924-1930
  • 2,529 - WB (War Baby): Original R born 1942-1947
  • 3,330 - EBB (Early Baby Boomers): Original R born 1948-1953
  • Sample size unavailable (as of publication) - MBB (Mid Baby Boomers): Original R born 1954-1959
Unit of Observation Individual
Continent(s) North America
Countries

United States
Geographic Coverage United States
Geographic Specificity National
Special Population(s)

Aging/Older people
Data Collection
Data Collection Mode

Primarily personal interview and phone surveys.

Restricted data linkages available to the following sources:

  • Employer Pension Study
  • National Death Index
  • Social Security Administration
  • Medicare files
Years Collected 1992-ongoing
Data Collection Frequency Biennial
Strengths and Limitations
Strengths

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
Primary Website https://hrs.isr.umich.edu/about
Data Access

Access:

http://hrsonline.isr.umich.edu/index.php?p=reg


Data products:

https://hrs.isr.umich.edu/data-products 
Data Access Requirements Data use agreement, No cost
Summary Tables/Reports

The Health and Retirement Survey: Aging in the 21st Century. Challenges and Opportunities for Americans (2017, January).

http://hrsonline.isr.umich.edu/sitedocs/databook/inc/pdf/HRS-Aging-in-the-21St-Century.pdf 
Data Components Biennial Datasets Longitudinal Datasets Off-Year Studies Restricted data files
Similar/Related Dataset(s)

Other longitudinal ageing studies:
Selected Papers
Other Papers

Bibliography:

https://hrs.isr.umich.edu/publications/biblio/


Servais, Marita A. (2010, June). Overview of HRS Public Data Files for Cross-sectional and Longitudinal Analysis.

http://hrsonline.isr.umich.edu/sitedocs/dmgt/OverviewofHRSPublicData.pdf

Technical https://hrs.isr.umich.edu/documentation/
Related Repositories
Repositories

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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).

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