Associations and Interaction Effects of Socioeconomic, Lifestyle, and Genetic Factors on Intrinsic Capacity
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».