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. 2024 May 3;8(1):765-776.
doi: 10.3233/ADR-230192. eCollection 2024.

Latent Class Analysis of Sleep in Mild Cognitive Impairment Patients and its Influencing Factors

Yamei Bai  1 , Meng Tian  1 , Yuqing Chen  1 , Yulei Song  1 , Xueqing Zhang  1 , Haiyan Yin  1 , Dan Luo  1 , Guihua Xu  1
Affiliations

Latent Class Analysis of Sleep in Mild Cognitive Impairment Patients and its Influencing Factors

Yamei Bai et al. J Alzheimers Dis Rep. .

Abstract

Background: Individuals with mild cognitive impairment (MCI) frequently experience sleep disorders, which may elevate the risk of developing Alzheimer's disease. Yet, sleep types in MCI patients and the factors influencing them have not been sufficiently investigated.

Objective: The objective of this study was to explore potential sleep typing and its influencing factors in patients with MCI using latent class analysis.

Methods: A cross-sectional survey was conducted in Jiangsu Province, China. Cognitive function in older adults was assessed using neuropsychological tests, including the Montreal Cognitive Assessment Scale-Beijing version (MoCA), the Mini-Mental State Examination (MMSE), the Activities of Daily Living Scale (ADL), and the Clinical Dementia Rating Scale (CDR). Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). Latent class analysis based on PSQI scores and multinomial logistic regression analyses were employed to explore the influencing factors of sleep typing.

Results: The study included a total of 611 patients with MCI. Latent class analysis identified three latent classes to categorize the sleep patterns of MCI patients: the good sleep type (56.6%), the insufficient sleep type (29.6%), and the difficulty falling asleep type (13.7%). Potential sleep typing is influenced by gender, chronic disease, physical exercise, social activity, brain exercise, smoking, frailty, subjective cognitive status, and global cognitive function.

Conclusions: The findings of this study underscore the notable heterogeneity in the sleep patterns of patients with MCI. Future research may provide targeted prevention and interventions to address the characteristics and influencing factors of patients with different subtypes of sleep MCI.

Keywords: Alzheimer’s disease; latent class analysis; mild cognitive impairment; risk factors; sleep.

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Conflict of interest statement

The authors have no conflict of interest to report.

Figures

Fig. 1
Fig. 1
Characteristics of each potential sleep typing in patients with MCI. Class 1, Good sleep type; Class 2, Insufficient sleep type; Class 3, Difficulty falling asleep type.
See this image and copyright information in PMC

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