Does socio-economic status predict grip strength in older Europeans? Results from the SHARE study in non-institutionalised men and women aged 50+
- 1 November 2009
- journal article
- research article
- Published by BMJ in Journal of Epidemiology and Community Health
- Vol. 64 (9), 829-837
- https://doi.org/10.1136/jech.2009.088476
Abstract
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.Keywords
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