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Healthier over time? Period effects in health among older Europeans in a step-wise approach to identification

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  • Myck, Michał
  • Oczkowska, Monika

Abstract

We examine changes in the level of physical health using longitudinal data on people aged 50+ from nine European countries covering the years from 2004 to 2017. For this purpose we develop a novel approach to identify age, period and cohort effects, which, in contrast to methods relying on mechanical restrictions, uses a step-wise estimation combining information on physical health with data on cognitive abilities. The approach relies on two important assumptions. First, we estimate relative differences between cohorts in cognitive abilities assuming that only age and cohort effects are responsible for their evolution. We then use the estimated proportional cohort differences to restrict the differences between cohorts in health development. The method is applied to the dynamics of four measures of poor health: weak grip strength, limitations in mobility, in activities of daily living (ADL) and in instrumental activities of daily living (IADL). Our results suggest insignificant or adverse period effects for the evolution of physical health. For example, the difference in likelihood of poor health as measured through weak grip strength between 2004 and 2017 is 2.1 percentage points, p.p., (95% CI -4.3, 8.4), and the corresponding numbers for the other three measures are respectively: 2.0 p.p. (CI -1.6, 5.6); 2.2 p.p. (CI -0.2, 4.7) and 3.0 p.p. (CI 0.3, 5.8). These estimates, which reflect the implications of time over the period of 14 years, are relatively low, but they highlight the surprising fact that any improvements in health in the examined period have been driven essentially by cohort effects. Our evidence is consistent with some earlier studies and sheds new light on recent (pre-pandemic) trends in life expectancy. It also raises questions concerning efficacy of healthcare and equal access to high quality care – the factors one would consider as important determinants of period effects in health.

Suggested Citation

  • Myck, Michał & Oczkowska, Monika, 2022. "Healthier over time? Period effects in health among older Europeans in a step-wise approach to identification," Social Science & Medicine, Elsevier, vol. 297(C).
  • Handle: RePEc:eee:socmed:v:297:y:2022:i:c:s0277953622000971
    DOI: 10.1016/j.socscimed.2022.114791
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    1. Blanchflower, David G. & Oswald, Andrew J., 2008. "Is well-being U-shaped over the life cycle?," Social Science & Medicine, Elsevier, vol. 66(8), pages 1733-1749, April.
    2. Alberto Abadie & Susan Athey & Guido W Imbens & Jeffrey M Wooldridge, 2023. "When Should You Adjust Standard Errors for Clustering?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 1-35.
    3. Kitty S. Chan & Judith D. Kasper & Jason Brandt & Liliana E. Pezzin, 2012. "Measurement Equivalence in ADL and IADL Difficulty Across International Surveys of Aging: Findings From the HRS, SHARE, and ELSA," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 67(1), pages 121-132.
    4. Andrew Bell & Kelvyn Jones, 2018. "The hierarchical age–period–cohort model: Why does it find the results that it finds?," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(2), pages 783-799, March.
    5. Cameron, A. Colin & Gelbach, Jonah B. & Miller, Douglas L., 2011. "Robust Inference With Multiway Clustering," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(2), pages 238-249.
    6. Deaton, Angus & Paxson, Christina, 1994. "Intertemporal Choice and Inequality," Journal of Political Economy, University of Chicago Press, vol. 102(3), pages 437-467, June.
    7. Orazio P. Attanasio, 1998. "Cohort Analysis of Saving Behavior by U.S. Households," Journal of Human Resources, University of Wisconsin Press, vol. 33(3), pages 575-609.
    8. Reither, Eric N. & Hauser, Robert M. & Yang, Yang, 2009. "Do birth cohorts matter? Age-period-cohort analyses of the obesity epidemic in the United States," Social Science & Medicine, Elsevier, vol. 69(10), pages 1439-1448, November.
    9. David Autor & David Figlio & Krzysztof Karbownik & Jeffrey Roth & Melanie Wasserman, 2019. "Family Disadvantage and the Gender Gap in Behavioral and Educational Outcomes," American Economic Journal: Applied Economics, American Economic Association, vol. 11(3), pages 338-381, July.
    10. Delaruelle, Katrijn & Buffel, Veerle & Bracke, Piet, 2015. "Educational expansion and the education gradient in health: A hierarchical age-period-cohort analysis," Social Science & Medicine, Elsevier, vol. 145(C), pages 79-88.
    11. Ottar Hellevik, 2009. "Linear versus logistic regression when the dependent variable is a dichotomy," Quality & Quantity: International Journal of Methodology, Springer, vol. 43(1), pages 59-74, January.
    12. Keyes, Katherine M. & Utz, Rebecca L. & Robinson, Whitney & Li, Guohua, 2010. "What is a cohort effect? Comparison of three statistical methods for modeling cohort effects in obesity prevalence in the United States, 1971-2006," Social Science & Medicine, Elsevier, vol. 70(7), pages 1100-1108, April.
    13. Yu-Kang Tu & George Davey Smith & Mark S Gilthorpe, 2011. "A New Approach to Age-Period-Cohort Analysis Using Partial Least Squares Regression: The Trend in Blood Pressure in the Glasgow Alumni Cohort," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-9, April.
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    Cited by:

    1. Robert M. O’Brien, 2023. "Setting bounds on age, period, and cohort effects using observed data," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2841-2857, June.

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    More about this item

    Keywords

    Age-period-cohort; Health dynamics; Grip strength; Ageing;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

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