A latent class analysis of cognitive impairment in the elderly in China and its influencing factors

LIN Lu; HE Pingping; QIU Sihui; QIU Xiaohui; CHEN Jiangping; WANG Jin

doi:10.16462/j.cnki.zhjbkz.2025.04.003

Volume 29 Issue 4

Apr. 2025

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Article Navigation > CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION > 2025 > 29(4): 386-392

LIN Lu, HE Pingping, QIU Sihui, QIU Xiaohui, CHEN Jiangping, WANG Jin. A latent class analysis of cognitive impairment in the elderly in China and its influencing factors[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2025, 29(4): 386-392. doi: 10.16462/j.cnki.zhjbkz.2025.04.003

Citation:

LIN Lu, HE Pingping, QIU Sihui, QIU Xiaohui, CHEN Jiangping, WANG Jin. A latent class analysis of cognitive impairment in the elderly in China and its influencing factors[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2025, 29(4): 386-392. doi: 10.16462/j.cnki.zhjbkz.2025.04.003

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A latent class analysis of cognitive impairment in the elderly in China and its influencing factors

doi: 10.16462/j.cnki.zhjbkz.2025.04.003

1.
Department of Community Nursing, School of Nursing, Hengyang Medical School, University of South China, Hengyang 421001, China
2.
Department of Community Nursing, School of Nursing, Hunan Normal University, Changsha 410000, China

Funds:

Natural Science Foundation of Hunan Province 2023JJ30426

Key Project of Social Science Achievement Evaluation Committee of Hunan Province XSP20ZDI013

More Information

Corresponding author: HE Pingping, E-mail: 793572859@qq.com
Received Date: 2024-06-26
Rev Recd Date: 2024-12-02
Publish Date: 2025-04-10

Abstract

Abstract

Objective To explore the latent categories of cognitive impairment in the elderly in China and identify its influencing factors, providing a reference for the effective identification of cognitive impairment in older adults. Methods Data from the 2018 Chinese longitudinal healthy longevity survey (CLHLS) released in April 2020 were used, a latent profile analysis was employed to identify the categories of cognitive impairment among the elderly, and multiple logistic regression analysis was used to explore the influencing factors of these categories. Results A total of 8 913 elderly individuals aged 65 years and above were included in the study. Significant heterogeneity in cognitive impairment was observed, and three distinct patterns emerged: no or mild cognitive impairment (85.5%), moderate cognitive impairment (6.5%), and severe cognitive impairment (8.0%). The results of the multivariate logistic regression analysis showed that age (OR=0.128, 95% CI: 0.089-0.184), sleep duration(OR=0.799, 95% CI: 0.667-0.956), years of education(OR=2.132, 95% CI: 1.025-4.434), self-rated health(OR=1.832, 95% CI: 1.449-2.316), physical exercise(OR=2.236, 95% CI: 1.751-2.855), marital status (OR=2.266, 95% CI: 1.772-2.899), depression(OR=0.829, 95% CI: 0.619-1.112), anxiety(OR=0.757, 95% CI: 0.579-0.989), alcohol (OR=1.576, 95% CI: 1.125-2.208), and childhood hunger(OR=0.755, 95% CI: 0.605-0.941) were all influencing factors of cognitive impairment in the elderly, and these were statistically significant (all P<0.05). Conclusions Cognitive impairment among the elderly in China is most severe in terms of reaction time and memory loss, followed by impairments in language, comprehension, and self-coordination abilities. These impairments are influenced by multiple factors, suggesting that healthcare professionals need to adopt more targeted interventions to improve cognitive function in the elderly.
- Elderly,
- Cognitive impairment,
- Latent class analysis

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References(24)

References

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