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Impact of socioeconomic position on frailty trajectories in 10 European countries: evidence from the Survey of Health, Ageing and Retirement in Europe (2004–2013)
  1. Erwin Stolz,
  2. Hannes Mayerl,
  3. Anja Waxenegger,
  4. Éva Rásky,
  5. Wolfgang Freidl
  1. Institute of Social Medicine and Epidemiology, Medical University of Graz, Graz, Austria
  1. Correspondence to Dr Erwin Stolz, Institute of Social Medicine and Epidemiology, Medical University of Graz, Universitätsstraße 6, 8010 Graz, Austria; erwin.stolz{at}medunigraz.at

Abstract

Background Whether or not, and how, health inequalities change throughout older age is currently under debate. The goal of this study was to assess the net impact of education, occupational class, income and wealth on frailty trajectories among older adults in Continental Europe.

Methods We modelled frailty index trajectories within a repeated cohort design among the community-dwelling population (50+) in 10 countries, using growth curve models based on 54 036 observations from 20 965 respondents in 4 waves (2004–2013) of the Survey of Health, Ageing and Retirement in Europe.

Results Gaps in frailty due to education, occupational class and wealth continued throughout old age, while the gap due to income, smaller in comparison, converged. Frailty levels were higher and trajectories steeper in later birth cohorts, and the impact of education increased over time. Frailty levels and growth curves were higher in Southern European countries, and results were consistent across countries regarding the continuous effect of education and occupation and more mixed regarding wealth and income.

Conclusions Health inequalities due to education, occupational class and wealth tend to persist throughout old age, whereas the negligible effect of income declines with age, which, substantially, highlights the importance of social conditions on the pace of physiological decline in older Europeans and, methodologically, highlights the need to assess multiple measures of socioeconomic position.

  • Epidemiology of ageing
  • Health inequalities
  • LONGITUDINAL STUDIES
  • MULTILEVEL MODELLING
  • Social and life-course epidemiology

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Footnotes

  • Contributors ES led the design of the study, conducted the literature review and analysis, and wrote the paper. HM, AW, ÉR and WF contributed to the literature review and the analysis, and reviewed the paper carefully.

  • Funding This work was supported by no specific institution but only the Medical University of Graz. This paper uses data from SHARE Waves 1, 2, 3 (SHARELIFE), 4 and 5 (DOIs: 10.6103/SHARE.w1.260, 10.6103/SHARE.w2.260, 10.6103/SHARE.w3.100, 10.6103/SHARE.w4.111, 10.6103/SHARE.w5.100). The SHARE data collection has been primarily funded by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812) and FP7 (SHARE-PREP: N211909, SHARE-LEAP: N227822, SHARE M4: N261982). Additional funding from the German Ministry of Education and Research, the U.S. National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064) and from various national funding sources is gratefully acknowledged (see http://www.share-project.org).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement This study uses data from the Survey of Health, Ageing and Retirement in Europe, which is freely available to academic researchers.

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