Evidence map›Paper›PMID 41069966›Full record

ArticleFrontiers in aging neuroscience2025

Latent profiles and correlates factors of cognitive function in older adults: a cross-sectional study.

Jin Xiang, Yan Xiong, Heting Liang, Qingyun Mao, Yumeng Zhang, Yunting Li, Zhixia Jiang, Xiaoli Yuan

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Article in Frontiers in aging neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Jin Xiang *Department of Nursing, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Yan Xiong *Department of Nursing, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Heting LiangDepartment of Nursing, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Qingyun MaoDepartment of Nursing, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Yumeng ZhangDepartment of Nursing, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Yunting LiDepartment of Nursing, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Zhixia JiangGuizhou Nursing Vocational and Technical College, Guizhou, China.
Xiaoli YuanDepartment of Nursing, Affiliated Hospital of Zunyi Medical University, Zunyi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: 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. Methods: 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. Results: 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. Conclusion: 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.

Indexed as

cognitive functioncommunity nursingcorrelates factorslatent profile analysisolder adults

Identifiers

PMID41069966
PMCPMC12504479

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