Correlates and determinants of physical activity among older adults of lower versus higher socio-economic status: a systematic review and meta-analysis
Malkowski OS., Harvey J., Townsend NP., Kelson MJ., Foster CEM., Western MJ., Physical Activity Inequalities in Later Life consortium None., Westgarth C., Thøgersen-Ntoumani C., Strain T., Stevinson C., Stephan Y., Stamatakis E., Solomon-Moore E., Smith LG., Scholes S., Rowlands AV., Pina I., Pasanen TP., Oliveira D., Ogilvie D., Mosca I., Marques A., Maddock J., Macdonald L., Lemanska A., Lakerveld J., Hillsdon M., Hanson CL., Hampshire A., Garrett JK., Dudman K., Creese B., Cox SR., Corley J., Corbett A., Cook S., Cajita M., Burnett H., Bourassa KJ., Alkhatib A.
Background: Understanding socio-economic differences in the factors influencing physical activity among older adults is essential for developing comprehensive interventions. We aimed to quantify the associations of modifiable correlates and determinants on physical activity among older adults of lower versus higher socio-economic status in the United Kingdom. Methods: In this systematic review and meta-analysis, we searched MEDLINE, Embase, Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), and Scopus from inception to December 2023, for peer-reviewed studies published in English, investigating associations between a modifiable factor as an independent variable and physical activity as a dependent variable, by socio-economic status (defined according to various area- and individual-level indicators, including neighbourhood deprivation, wealth or income, education, and occupational class), in samples of community-dwelling older adults aged 60+ years in the United Kingdom. Hospitalised and institutionalised populations were excluded. Random effects meta-analyses were performed separately for people of lower and higher socio-economic status. Risk of bias was assessed with the Mixed Methods Appraisal Tool. This study was registered with the International prospective register of systematic reviews (PROSPERO; CRD42022351708). Results: Searches identified 11,472 references; seventy-seven studies met the selection criteria, of which fifty-one contributed to meta-analyses (N range = 134–29,280). Of the exposures positively associated with physical activity, physical function, social participation, and perception of general health had the largest effect sizes (standardised mean difference [SMD] range = 0.53–0.81; I2 range = 54.81–91.00%). Estimates were comparable among older adults of lower and higher socio-economic status, except for the presence of built physical activity facilities, access to walking and cycling infrastructure, and less smoking, which were positively associated with physical activity only among individuals of lower socio-economic status. Conclusions: Our results suggest researchers need to better understand discrepancies in the prevalence of the assessed correlates (e.g., fewer participants of lower socio-economic status reported good physical function) to inform policies that reduce inequalities in older adults’ physical activity levels. However, most studies were cross-sectional. Future longitudinal and experimental research should gauge the suitability of these correlates as intervention targets.