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Dataset: Survey of Health, Ageing and Retirement in Europe (SHARE)

Basic Information
Dataset Full Name Survey of Health, Ageing and Retirement in Europe
Dataset Acronym SHARE

SHARE is a multidisciplinary, cross-national, longitudinal study of the European  population over 50 years old. 28 European countries plus Israel participate in the SHARE study. The study covers the interplay between economic, health, and social factors in shaping older people’s living conditions. It also aims to address these issues cross-nationally. The wave 3 SHARELIFE survey collected life history calendars designed to identify prominent events in each participant's life. Health measurements include self-reports as well as four physical performance measurements: grip strength (GS), walking speed (WS), peak-flow (PF) and chair stand (CS). Six waves of data have been released with wave 7 data (collected in 2017) expected to be released in spring 2019.

Blood spot samples were collected for 24,000 individuals across 12 SHARE countries in wave 6 Blood spot analysis will focus on markers related to diseases and conditions typical for older people and/or are influenced by lifestyle,including cardiovascular diseases (CVD), diabetes, and markers for stress and cognition. Biomarker data may be available sometime in 2018.

Key Terms

Aging, Longitudinal, Cross-country data, National variation, Socio-economic status, Health care utilization, Health care quality, Health care expenditures, Chronic conditions, Biomarkers, Work, Retirement

Study Design Longitudinal
Data Type(s) Clinical
Sponsoring Agency/Entity
  • European Commission
  • U.S. National Institute of Aging 
  • Funding from participating countries
Health Conditions/Disability Measures
Health Condition(s)

Allergies, Arthritis, Body mass index (BMI)/obesity, Cancer, Cardiovascular conditions, Depression (EURO-D depression scale), Diabetes, Heart attack, Migraine or frequent headaches, Osteoporosis, Stroke

Disability Measures

Functional limitations (ADLs and/or IADLs), Hearing disability, Mental health disability, Special equipment use/assistive technology, Visual disability, Work limitation

Grip strength, Walking speed, Peak flow, Memory recall

Measures/Outcomes of Interest
  • Health behavioral risks, Diet/nutrition, Health trajectories, Trends in disability
  • National level variations of social & economic support 
  • Retirement, Wealth, Work quality, Financial transfers, Disability insurance
  • Social support, Social networks, Family structure, Volunteering
  • Periods and causes of disability/periods of ill health over life course
  • Consequences of illness/disability on life and work
Sample Population

Households (Adults ages 50 and older residing in one of the participating countries)

Sample Size/Notes
31,115 at baseline (2004)
Refresher samples have been recruited to account for attrition

Sample distribution waves 1-6:
Unit of Observation





Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland

Geographic Coverage

Cross - National

Country data available:

  • Wave 1 (2004-5): Austria, Belgium, Denmark, France, Germany, Greece, Italy, Israel, the Netherlands, Spain, Switzerland, and Sweden
  • Wave 2 (2006-7) added: Czech Republic, Ireland, and Poland
  • Wave 4 (2010-11) added: Estonia, Hungary, Portugal, and Slovenia
  • Wave 5 (2013) added: Luxembourg
  • Wave 6 (2015) added: Croatia
  • Wave 7 (2017) added: Bulgaria, Cyprus, Finland, Latvia, Lithuania, Malta, Romania, and Slovakia
Geographic Specificity


Special Population(s)

Aging/Older people

Data Collection
Data Collection Mode
  • Computer assisted personal interviews (CAPI)
  • Self-completed questionnaires 
  • Physical examination and blood draws (starting at Wave 6) at home
  • End-of–life interviews with proxy
Years Collected

2004-present (ongoing)

Data Collection Frequency

Every 2 years

Strengths and Limitations
  • Large sample size across 28 countries allowing for comparisons of health, social and economic trends over time and across nations.
  • Objective markers of health are also included (biomarkers and physical examination). 
  • Outcome measures have been harmonized with other ongoing studies, such as the UK ELSA and US HRS study, allowing for comparisons of trends among different countries.
  • A simplified version of the data is available for student training and teaching purposes:
  • Attrition and loss to follow up.
  • Information on earlier life medical history is self-reported and collected retrospectively.
  • Imputed variables may have limited use in longitudinal analyses, as the underlying information may not be comparable.
Data Details
Primary Website


Data Access


Data Access Requirements

Data Use agreement, No cost

Summary Tables/Reports

First Results from the Survey of Health, Ageing and Retirement in Europe


Data Components
Main SHARE datasets:

  • Wave 1
  • Wave 2
  • Wave 3 (SHARELIFE)
  • Wave 4
  • Wave 5
  • Wave 6
  • Job Episodes Panel
  • Longitudinal Weights
  • All Waves 

Special SHARE datasets:

  • easySHARE
    • Simplified data for teaching & student training purposes)
  • SHARE-RV (German SHARE subsample)
    • German SHARE data linked with administrative records of the German Pension Insurance (DRV)
  • REGLINK-SHAREDK: (Danish subsample)
    • Links Danish SHARE Survey Data with data from Danish national registers
    • Access requires special application & permission
Similar/Related Dataset(s)

Other longitudinal ageing studies:

Selected Papers
Other Papers

Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE)


Health, Ageing and Retirement in Europe: First Results from the Survey of Health, Ageing and Retirement in Europe


Publications based on SHARE data:



Data Documentation:


The Survey of Health, Aging, and Retirement in Europe – Methodology


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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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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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