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Updated: Feb 3, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Cognitive Impairments and Associated Factors in Community-dwelling Elderly in Chengdu, Sichuan]
Zhen-Yan Bo1, Wei-Hong Kuang2, Yang Wang1
1Department of Epidemiology and Biostatistics, West China School of Public Health, Sichuan University, Chengdu 610041, China.
Objective:
To determine the prevalence and associated factors of cognitive impairments in the community-dwelling elderly aged 60 years or older in Chengdu of Sichuan province.
Methods:
A random cluster sampling strategy was adopted to select 621 community-dwelling elderly. Face-to-face interviews were conducted to assess the cognitive status of the participants. 2 tests and logistic regression analyses were performed to identify factors associated with cognitive impairments.
Results:
About 40.9% of the participants had cognitive impairments. Those attended primary schools had a lower risk of cognitive impairments [odds ratio OR)=0.369, P<0.001] compared with the illiterate ones. Older age OR=1.505 for 70-79 years, P=0.042; OR=3.069 for ≥80 years, P<0.001), cerebrovascular disease OR=2.159, P=0.003) and smoking OR=2.388, P<0.001) were risk factors of cognitive impairments. Men had lower risk OR=0.489, P=0.005) of cognitive impairments than women.
Conclusion:
The prevalence of cognitive impairments in community-dwelling elderly in Chengdu is high in comparison with those in other cities. Illiteracy, older age (over 70 years), women, smoking, and cerebrovascular disease are risk factors of cognitive impairments.
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