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Where People Live and Die Makes a Difference: Individual and Geographic Disparities in Well-Being Progression at the End of Life

Author

Listed:
  • Denis Gerstorf
  • Nilam Ram
  • Jan Goebel
  • Jürgen Schupp
  • Ulman Lindenberger
  • Gert G. Wagner
Abstract
Lifespan psychological research has long been interested in the contextual embeddedness of individual development. To examine if and how regional factors relate to between-person disparities in the progression of late-life well-being, we applied three-level growth curve models to 24-year longitudinal data from deceased participants of the German Socio-Economic Panel Study (N = 3,427; age at death: 18 to 101 years). Results indicate steep declines in well-being with impending death, with some 8% of the between-person differences in both level and decline of well-being reflecting between-county differences. Exploratory analyses revealed that individuals living and dying in less affluent counties reported lower late-life well-being, controlling for key individual predictors including age at death, gender, education, and household income. The regional factors examined did not directly relate to well-being change, but were found to moderate (e.g., amplify) the disparities in change attributed to individual factors. Our results suggest that resource-poor counties provide relatively less fertile grounds for successful aging until the end of life and may serve to exacerbate disparities. We conclude that examinations of how individual and residential characteristics interact can further our understanding of individual psychological outcomes and suggest routes for future inquiry.

Suggested Citation

  • Denis Gerstorf & Nilam Ram & Jan Goebel & Jürgen Schupp & Ulman Lindenberger & Gert G. Wagner, 2010. "Where People Live and Die Makes a Difference: Individual and Geographic Disparities in Well-Being Progression at the End of Life," SOEPpapers on Multidisciplinary Panel Data Research 287, DIW Berlin, The German Socio-Economic Panel (SOEP).
    • Handle: RePEc:diw:diwsop:diw_sp287
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    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.354342.de/diw_sp0287.pdf
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    References listed on IDEAS

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    Cited by:

    1. Jan Goebel & Michael Wurm & Gert G. Wagner, 2010. "Exploring the Linkage of Spatial Indicators from Remote Sensing Data with Survey Data: The Case of the Socio-Economic Panel (SOEP) and 3D City Models," SOEPpapers on Multidisciplinary Panel Data Research 283, DIW Berlin, The German Socio-Economic Panel (SOEP).
    2. Stefano Bartolini & Ennio Bilancini & Francesco Sarracino, 2013. "Predicting the Trend of Well-Being in Germany: How Much Do Comparisons, Adaptation and Sociability Matter?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 114(2), pages 169-191, November.
    3. Denis Gerstorf & Gert G. Wagner, 2010. "Lebenszufriedenheit am Ende des Lebens in Ost- und Westdeutschland: die DDR wirft einen langen Schatten," SOEPpapers on Multidisciplinary Panel Data Research 320, DIW Berlin, The German Socio-Economic Panel (SOEP).
    4. Nina Vogel & Nilam Ram & Jan Goebel & Gert G. Wagner & Denis Gerstorf, 2018. "How does availability of county-level healthcare services shape terminal decline in well-being?," European Journal of Ageing, Springer, vol. 15(2), pages 111-122, June.
    5. Karla Romero Starke & Janice Hegewald & Stefanie Schmauder & Pauline Kaboth & Lena Marie Uhlmann & David Reissig & Kristin Klaudia Kaufmann & Jürgen Wegge & Gesine Marquardt & Andreas Seidler, 2022. "Health and Care Dependency of Older Adults in Dresden, Germany: Results from the LAB60+ Study," IJERPH, MDPI, vol. 19(18), pages 1-18, September.
    6. Brett Smith & Doina Olaru, 2013. "Lifecycle Stages and Residential Location Choice in the Presence of Latent Preference Heterogeneity," Environment and Planning A, , vol. 45(10), pages 2495-2514, October.

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    More about this item

    Keywords

    Neighborhoods; Selective mortality; successful aging; differential aging; psychosocial factors; well-being; longitudinal methods;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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