Christine A. Mair, PhD University of Maryland Baltimore County.

Transcription

1 Christine A. Mair, PhD University of Maryland Baltimore County

2 Cross-national (12-20 European nations) Panel (4 waves 04/05, 06/07, 08/09, 11/12) Older adults 50+ (~30,000 individuals) Multidisciplinary in focus Partially harmonized with peer datasets Extensive online documentation *Approved until 2024! (6 addit l waves)* FREE and available to the PUBLIC

3 Source: share-project.org

4 Wave 1 12 nations (Northern, Western, Southern) Wave 2 14 nations (adds Eastern) SHARELIFE 14 nations (life course histories about childhood, family, work, health/health care) Wave 4 19 nations (adds 4 additional EU, social network module, German biomarkers)

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6 Source: share-project.org

7 Probability sampling within each nation Country teams using 27 languages Sample sizes differ by nation Non-institutionalized aged 50+ Coverscreen, core, drop off, vignettes, end-of-life Household response rate (~60%, Wave 1) Individual response rate (~85%, Wave 1) 56% female, 23% aged 75+

8 Multi-sourced funding European Commission National Institute on Aging German Federal Ministry for Education & Research Cross-National Division of Labor Munich Center for the Economics of Aging (Max Planck Institute for Social Law and Social Policy) Italy (weights and imputations) Netherlands (instruments and data distribution)

9 Demographics age, sex, country of origin (when applicable) Health physical and mental health, behavioral risks, cognitive function, health care Economics/Employment employment, pensions, financial transfers, household income, consumption, assets Social Networks children, household structure, social support, activity participation, network composition

10 Generated Variables Weights, imputations Health, Education, Occupations, Housing Mortality status Social support, household composition Social networks (Wave 4) Biomarkers (Germany) Pension insurance data links (Germany)

11 Freedom and opportunity to dig deeper! Individual, cultural, economic, policy differences between countries extensively discussed and continually theorized GAP: Many not empirically documented!

12 My Research Goals with International Data To document empirical cross-national variation in older adults social environments and health To test previously theorized explanations for this variation using empirical measures at the individualand nation-level To ultimately provide a more nuanced and complex understanding of the social environmental processes that shape older adults well-being cross-nationally

13 CULTURE "Cross - National Variation"? POLICY/ ECONOMICS Other?

14 Individual-level data can be linked to country characteristics using publicly available nation-level data sources (aggregated or aggregate-able) World Bank, United Nations, Organisation for Economic Cooperation and Development (OECD), World Values Survey, International Social Survey Programme, etc.!

15 Level 2: Nation-Level Nation A Nation B Person 1 Person 2 Person 3 Person 1 Person 2 Person 3 Level 1: Individual-Level

16 Mair, Christine A European Older Adults Social Activity Networks in National Context: A Cross-National Exploration of National Culture, Policy, and Economic Characteristics. Aging in European Societies (C. Phellas, Ed.). New York, NY: Springer.

17 Mair, Christine A European Older Adults Social Activity Networks in National Context: A Cross-National Exploration of National Culture, Policy, and Economic Characteristics. Aging in European Societies (C. Phellas, Ed.). New York, NY: Springer.

18 Mair, Christine A Family Ties and Health Cross-Nationally: The Contextualizing Role of Familistic Culture and Public Pension Spending in Europe. Journals of Gerontology Series B: Psychological Sciences and Social Sciences 68(6):

19 The aging experience differs cross-nationally. Older adults social environments are theorized to be deeply shaped by national characteristics. We can empirically document this variation using international datasets. Even further, such datasets allow us to pinpoint specific economic and cultural traits at the nation-level that appear to contextualize older adults experiences. With the expansion of longitudinal international datasets (i.e., SHARE and nation-level data sources) the number of unaddressed questions about global aging populations that can now be assessed empirically is (virtually) infinite...

20 SHARE Christine A. Mair