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Optimal 24-Hour Sleep Duration and Depression Risk in Chinese Middle-Aged and Elderly: A Machine Learning and RCS
Zhuo Chen1, Taoyang Cai2, S K Kot-Cheung3
1Capital University of Economics and Business, Beijing, China.
Objectives:
To investigate the relationship between sleep (nocturnal sleep and total 24-hour sleep) and depressive symptoms in middle-aged and elderly people using data from the China Health and Retirement Longitudinal Study (CHARLS).
Study Design:
Cross-sectional study.
Methods:
A total of 13,718 middle-aged and elderly people aged 45 and above from the China Health and Retirement Longitudinal Study (CHARLS 2020) were included. A multivariate logistic regression model was used to analyze the correlation between sleep and depressive symptoms, and a random forest model was used to rank the importance of variables. Furthermore, the nonlinear relationship between sleep duration and depressive symptoms risk was fitted using a restricted cubic spline (RCS) model.
Results:
Compared with the group with 24-hour sleep duration of > 7 to ≤ 9 h, the adjusted odds ratio (OR) for depressive symptoms in the group with 24-hour sleep duration of ≤ 7 h (OR = 1.649) and > 9 h (OR = 1.166) was higher. Random forest results showed that total 24-hour sleep ranked above average among variables affecting depressive symptoms. The RCS curve showed that a total 24-hour sleep time of > 7 to ≤ 9 h was associated with the lowest adjusted odds for depressive symptoms.
Conclusions:
There is a significant correlation between sleep duration and depressive symptoms in middle-aged and elderly people. Those who slept > 7 to ≤ 9 h per night had a lower incidence of depressive symptoms, and total 24-hour sleep of > 7 to ≤ 9 h showed a stronger OR value. Life satisfaction also emerged as an important factor influencing depressive symptoms.
