Latent profile analysis of impaired cognitive function and attribution among community-dwelling older adults with mild cognitive impairment
10.3760/cma.j.cn371468-20230811-00051
- VernacularTitle:社区轻度认知障碍老年人群认知功能受损及其归因的潜在剖面分析
- Author:
Liming SU
1
;
Chen ZHANG
;
Xiaoyan WANG
;
Cheng HUANG
;
Zhuqin WEI
;
Xinhua SHEN
;
Lina WANG
Author Information
1. 湖州师范学院医学院，湖州 313000
- Keywords:
Mild cognitive impairment;
Older adults;
Latent profile analysis;
Community;
Categories
- From:
Chinese Journal of Behavioral Medicine and Brain Science
2024;33(6):519-526
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the potential categories and associated factors of mild cognitive impairment (MCI) in community-dwelling older adults.Methods:A total of 393 community-dwelling older adults with MCI in Huzhou City were selected through multistage random sampling from January to July 2022.The survey was conducted by the general information questionnaire, Montreal cognitive assessment (MoCA), Pittsburgh sleep quality index (PSQI) and 15-item geriatric depression scale(GDS-15). Latent profile analysis (LAP) was applied to explore latent categories based on the characteristics of cognitive impairment, and Logistic regression analysis was performed to examine the factors associated with these MCI categories. The statistical software was SPSS 26.0.Results:The community-dwelling older adults with MCI was categorized into four subgroups: generalized mildly impaired subgroup, mixed impaired with visuospatial executive dysfunction subgroup, narrative memory dysfunction impaired subgroup, and high-risk severely impaired subgroup, with corresponding MoCA scores of (23.10±0.96), (21.87±0.92), (20.43±0.93), (19.00±0.00), PSQI scores of (6.00 (4.00)), (7.00 (6.00)), (7.00 (6.00)), (10.00 (3.00)), and GDS-15 scores of (4.00 (4.00)), (4.00(5.00)), (6.00(5.00)), (8.00 (3.00)), respectively. Logistic regression analysis revealed that compared to generalized mildly impaired subgroup, gender, age, exercise habits, sleep quality, depressive symptoms, chronic disease count, and medication count significantly affected other three subgroups, with female, older age, and never/irregular exercise as common risk factors. Poor sleep quality and depressive symptoms could positively predict mixed impaired with visuospatial executive dysfunction subgroup and narrative memory dysfunction impaired subgroup( B=0.82, OR=2.27, 95% CI=1.26-4.08; B=1.12, OR=3.06, 95% CI=1.36-6.91).Additionally, poor sleep quality, depressive symptoms, chronic disease and medication count could significantly predict high-risk severely impaired subgroup ( B=4.13, OR=62.32, 95% CI= 1.71->999.99; B=3.31, OR=27.49, 95% CI=1.37-549.99; B=1.20, OR=3.32, 95% CI= 1.06-10.41 and B=0.80, OR=2.22, 95% CI=1.04-4.71). Conclusion:Four latent MCI categories are identified among community-dwelling older adults, and each category was characterized by unique cognitive impairment features and factors. Healthcare professionals are advised to customize assessments and management strategies according to these specific characteristics to effectively slow cognitive decline.
