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Associations and Interaction Effects of Socioeconomic, Lifestyle, and Genetic Factors on Intrinsic Capacity

Beyene, M. B.; Visvanathan, R.; Alemu, R.; Theou, O.; Benyamin, B.; Cesari, M.; Beard, J.; Amare, A. T.

2025-10-07 geriatric medicine
10.1101/2025.10.05.25337351 medRxiv
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BackgroundIntrinsic capacity (IC) is a composite measure, computed from five domains: cognition, psychological well-being, locomotion, vitality, and sensory. IC reflects the overall physiological reserve and functional capacity of an individual, making it a key indicator of healthy ageing. The substantial interindividual variability in IC is likely influenced by genetic (polygenic) as well as socioeconomic status and lifestyle factors. However, the interaction effect of these factors is yet to be explored. ObjectiveThis study examined (1) associations of IC with socio-economic and lifestyle factors and the polygenic scores for IC (PGS-IC) when stratified by age, and (3) the interaction effects of the PGS-IC and socio-economic or lifestyle factors on IC. MethodsOur study included 13,112 participants from the Canadian Longitudinal Study on Aging (CLSA) comprehensive cohort with complete IC variables and genetic data. Composite lifestyle scores, including the Physical Activity Scale for the Elderly (PASE), Prospective Urban Rural Epidemiological study (PURE) diet, and Mediterranean diet scores, were generated following established guidelines. Associations of IC with the socioeconomic and lifestyle factors were assessed using linear regression models adjusted for age and sex. The IC scores and the PGS-IC were developed in CLSA in our previous work, and this study tested age-stratified associations of PGS-IC with IC, and interaction effects of the PGS-IC and socioeconomic or lifestyle factors on IC using linear regression models adjusted for age, sex, and the top five genetic principal components. Statistical significance was defined as a false discovery rate (FDR) adjusted P < 0.05. ResultsThe mean age was 61 (standard deviation 9.6) years, and 50.8% were females. Higher IC was associated with higher education (B = 0.255, 95% CI: 0.180, 0.329), higher income (B = 0.392, CI: 0.322, 0.461), physical activity (PASE score: B = 0.001, CI: 0.0004, 0.001), and healthier diets (PURE diet score: B = 0.024, CI: 0.021, 0.027; Mediterranean diet score: B = 0.018, CI: 0.016, 0.021). IC was lower in previous (B = -0.093, CI: -0.121, -0.064) and current smokers (B = -0.407, CI: -0.459, -0.355) compared to never smokers. Likewise, short (<7h: B = -0.133, CI: -0.161, -0.105) and long (>9h: B = -0.258, CI: -0.392, -0.124) sleep durations were negatively associated with IC compared to those who had optimal sleep. The PGS-IC was positively associated with IC, particularly in younger adults. Significant interaction effects were observed with Mediterranean diet (B = -0.003, CI:-0.006 -, -0.0002) in whole sample, education in younger adults (B = -0.109, CI: -0.211 -, -0.007), and sleep (younger adults: long sleep, B = 0.198, CI:0.023, 0.373; older adults: short sleep, B = -0.095, CI: -0.153 -, -0.036). ConclusionNovel findings confirming the interaction effects of PGS-IC with socioeconomic and lifestyle factors suggest that there is a complex interplay between genetics and the environment in shaping IC and healthy ageing.

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