Latent profile analysis of cognitive function among the rural elderly
10.19485/j.cnki.issn2096-5087.2026.10.002
- Author:
CHEN Ying
;
CHE Yajie
;
WANG Lang
;
MIAO Miao
;
WANG Mengyao
;
TONG Yihui
;
WANG Siyu
;
YAN Ping
- Publication Type:Journal Article
- Keywords:
cognitive function;
latent profile analysis;
influencing factor;
the elderly;
rural areas
- From:
Journal of Preventive Medicine
2026;38(10):977-983
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the types of cognitive function and influencing factors among the rural elderly, so as to provide evidence for the prevention and control of cognitive impairment among the rural elderly.
Methods:From July to August 2025, a multi-stage stratified cluster random sampling method was used to recruit the elderly aged ≥60 years from eight administrative villages in the Xinjiang Uygur Autonomous Region. Data on basic information, physical health status and mental health status were collected through questionnaire surveys. Cognitive function was assessed using the Chinese version of the Mini-Mental State Examination. Latent profile analysis was used to identify the types of cognitive function among the rural elderly, and a multinomial logistic regression model was used to analyze influencing factors of cognitive function among the rural elderly.
Results:A total of 549 participants were surveyed, including 301 males (54.83%) and 248 females (45.17%). The median age was 67.00 (interquartile range, 9.00) years. Latent profile analysis classified cognitive function into three types: the normal cognitive function group, the attention and calculation impairment group, and the multi-domain cognitive impairment group, accounting for 33.33%, 41.35% and 25.32%, respectively. Multinomial logistic regression analysis showed that, with the normal cognitive function group as the reference, males, education level of primary school and above were statistically associated with a lower risk of attention and calculation impairment (both P<0.05); age 71 to <81 years, hearing decline, obesity, poor sleep quality and social frailty were statistically associated with a higher risk of attention and calculation impairment (all P<0.05). Education level of primary school and above and good self-rated health status were statistically associated with a lower risk of multi-domain cognitive impairment (all P<0.05), while age ≥71 years, hearing decline, underweight or obesity, poor sleep quality and depressive symptoms were statistically associated with a higher risk of multi-domain cognitive impairment (all P<0.05).
Conclusion:Cognitive function among the rural elderly can be classified into three types: normal cognitive function, attention and calculation impairment, and multi-domain cognitive impairment, and was associated with demographic characteristics, physical health status and mental health status.
- Full text:2026111218000885013农村老年人认知功能潜在剖面分析.pdf
