Background Reduced hand-grip strength predicts disability, morbidity and mortality, but whether it is shaped by socio-economic experiences is yet unknown. The authors examined the association of education, occupation, income and wealth with grip strength in older Europeans.
Methods Data came from the Survey of Health, Ageing and Retirement in Europe comprising 27 351 participants ages 50+ in 11 countries. Grip strength was objectively measured using a handheld dynamometer. Estimates were obtained based on multivariate linear regression controlling for a wide set of confounders, demographics, health and disability measures, and behavioural risk factors.
Results In the total sample, education, occupational class, income and wealth predicted grip strength among men, whereas only education and wealth predicted grip strength among women. While education and income effects were inconsistent in most countries, wealth consistently predicted grip strength in each country. A one-point increase in the log of wealth was associated with 0.38 kg (95% CI 0.31 to 0.45) higher grip strength in men and 0.18 kg (95% CI 0.15 to 0.21) higher grip strength in women. While education, income and occupation effects disappeared after adjustment for health measures, log of wealth effects remained significant in both men (0.22, 95% CI 0.15 to 0.29) and women (0.08, 95% CI 0.05 to 0.11). Wealth effects were particularly evident in the two lowest quintiles.
Conclusion Old-age socio-economic and financial circumstances as measured by wealth are associated with grip strength, particularly among the least wealthy, while circumstances defined earlier in life as measured by education, income and occupation do not consistently predict grip strength.
- Hand strength
- socio-economic factors
- health status disparities
- international collaboration
- Public Health Europe
- social epidemiology
- social inequalities
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Funding FMH was sponsored by a scholarship from the University of Malaya, Kuala Lumpur. MA was supported by a grant from The Netherlands Organisation for Scientific Research (NWO, grant no 451-07-001), a Fellowship from the Erasmus University, and a David E Bell fellowship from the Harvard Center for Population and Development studies. This paper uses data from release 2 of SHARE 2004. The SHARE data collection has been primarily funded by the European Commission through the 5th framework programme (project QLK6-CT-2001-00360 in the thematic programme Quality of Life). Additional funding came from the US National Institute on Ageing (U01 AG09740-13S2, P01 AG005842, P01 AG08291, P30 AG12815, Y1-AG-4553-01 and OGHA 04-064). Data collection in Austria (through the Austrian Science Foundation, FWF), Belgium (through the Belgian Science Policy Office) and Switzerland (through BBW/OFES/UFES) was nationally funded. The SHARE data collection in Israel was funded by the US National Institute on Aging (R21 AG025169), by the German–Israeli Foundation for Scientific Research and Development (GIF), and by the National Insurance Institute of Israel. Further support by the European Commission through the 6th framework programme (projects SHARE-I3, RII-CT-2006-062193 and COMPARE, CIT5-CT-2005-028857) is gratefully acknowledged.
Competing interests None.
Ethics approval Ethics approval was provided by the institutional review board at the University of Mannheim, Germany.
Provenance and peer review Not commissioned; externally peer reviewed.