Associations and Interaction Effects of Socioeconomic, Lifestyle, and Genetic Factors on Intrinsic Capacity
Bibliographic record
Abstract
Abstract Background Intrinsic 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. Objective This 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. Methods Our 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. Results The 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). Conclusion Novel 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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".