Association between Marital Status, Social Support and Lifestyle with Cognitive Impairment among Community-dwelling Older Adults: Based on the Baseline Survey of Hubei Memory and Aging Cohort Study
Notice bibliographique
Résumé
Background The accelerated aging process, combined with the increase in widowhood and social isolation, has led to a rise in chronic diseases, further increasing the social burden. Objective To explore the association between the marital status of older adults and the prevalence of cognitive impairment, as well as the impact of social support and lifestyle on this association. Methods A total of 9 466 older adults aged 65 years and above from Wuhan and Xiaogan, Hubei Province, were included in this study from 2018 to 2023. Participants were categorized into a married group (n=7 055) and an unmarried group (n=2 411) based on their marital status. Baseline information was collected through structured questionnaires, and cognitive function was assessed using the Mini-mental State Examnation and the Montreal Cognitive Assessment-basic China (MoCA-BC). A multivariable Logistic regression model was employed to analyze the association between marital status and cognitive impairment in the overall population as well as in subgroups stratified by age and sex. Further analyses explored the independent and combined effects of marital status, social support, and lifestyle habits on cognitive impairment risk. Results Compared with the elderly with spouses, no spouse was an independent risk factor for cognitive impairment (OR=1.299, 95%CI=1.227-1.376, P<0.001). Further subgroup analysis showed that never married (OR=1.679, 95%CI=1.448-1.947, P<0.001) and widowed (OR=1.282, 95%CI=1.206-1.362, P<0.001) were independent risk factors for cognitive impairment in the elderly. Gender and age stratified analysis showed that never married (OR=2.316, 95%CI=1.680-3.193, P<0.001) and widowed (OR=1.731, 95%CI=1.405-2.131, P<0.001) were independent risk factors for cognitive impairment in elderly men. Widowed was an independent risk factor for cognitive impairment in elderly women (OR=1.163, 95%CI=1.002-1.351, P=0.047). In the 65-74 years old group, never married (OR=1.953, 95%CI=1.390-2.746, P<0.001) and widowed (OR=1.315, 95%CI=1.120-1.545, P=0.001) were independent risk factors for cognitive impairment. In the ≥75 years old group, widowed was an independent risk factor for cognitive impairment (OR=1.470, 95%CI=1.238-1.747, P<0.001). Multivariate Logistic regression analysis on marital status, social support and living habits associated with cognitive impairment showed that compared with the elderly with spouse and social support and healthy living habits, the elderly with spouse and social support but unhealthy living habits (OR=1.262, 95%CI=1.169-1.363, P=0.002), spouse and no social support but healthy lifestyle (OR=1.650, 95%CI=1.479-1.841, P<0.001), spouse and no social support but unhealthy lifestyle (OR=1.777, 95%CI=1.575-2.005, P<0.001), no spouse and social support with healthy lifestyle (OR=1.284, 95%CI=1.189-1.397, P<0.001), no spouse and social support with unhealthy lifestyle (OR=1.999, 95%CI=1.768-2.260, P<0.001), no spouse and social support with unhealthy lifestyle (OR=1.999, 95%CI=1.768-2.260, P<0.001), no spouse and no social support but healthy lifestyle (OR=1.680, 95%CI=1.500-1.882, P<0.001), no spouse and no social support but unhealthy lifestyle (OR=2.422, 95%CI=2.141-2.740, P<0.001), no spouse and no social support but healthy lifestyle (OR=2.422, 95%CI=2.141-2.740, P<0.001) were at increased risk for cognitive impairment. Conclusion The prevalence of cognitive impairment, especially among older adults without spouses, notably increases, particularly for those who have never married or are widowed. Regardless of marital status, the lack of social support and unhealthy lifestyle are risk factors for cognitive impairment. This study highlights the importance of paying attention to marital status, social support, and lifestyle in the health management of older adults.
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».