横断面研究
认知
认知老化
心理学
老年学
医学
临床心理学
发展心理学
精神科
病理
作者
Xiang Jin,Yan Xiong,Heting Liang,Qingyun Mao,Yumeng Zhang,Yunting Li,Zhixia Jiang,Xiaoli Yuan
标识
DOI:10.3389/fnagi.2025.1622804
摘要
This study aimed to identify the latent profiles of cognitive function among community-dwelling and institutionalized older adults, and to examine their associated influencing factors, in order to inform the development of targeted interventions. A convenience sampling method was used to select 6,708 elderly people aged 60 years and older from six communities and nine long-term care institutions across China, who were assessed using a general information questionnaire, Mini-Mental State Examination (MMSE), the Frailty Scale, the Anxiety Scale, the Depression Scale, and the Pittsburgh Sleep Quality Index. Latent profile analysis (LPA) was performed based on the MMSE scores, and multiple logistic regression was used to analyse the influencing factors of cognitive function categories. A total of three cognitive function profiles were identified: High cognitive Function group (41.2%), Moderate Cognitive Function Group (48.2%) and Low cognitive Function group (10.7%). Higher Frailty [odds ratio (ORs) = 1.070-1.246], higher depressive symptom scores (OR = 1.059-1.191) and poorer sleep quality (higher PSQI; OR = 1.088) were associated with higher odds of belonging to the Moderate/Low cognitive profiles, whereas adequate social support (Yes vs. No; OR = 0.530-0.696), selected middle-income categories versus ≥¥6,000 in per-capita monthly household income (OR = 0.462-0.735) and male sex (OR = 0.556-0.876) were associated with lower odds. Cognitive function among older adults can be classified into three distinct latent profiles, each associated with different influencing factors. These findings underscore the need for stratified and personalized interventions at the community level to support stratified screening and tailored community programs; given the cross-sectional design, these associations do not establish causality or intervention effects.
科研通智能强力驱动
Strongly Powered by AbleSci AI