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| The bidirectional relationship between nighttime sleep duration and depression among Chinese older adults : evidence from the CHARLS |
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| English keywords:Chinese older adults Nighttime sleep duration Depression Cross-lagged path analysis Bidirectional relationship |
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| Background Depression and sleep problems are prevalent among older adults and are prone to form a vicious cycle that seriously affects their quality of life and health. However, most of the existing studies adopt cross-sectional design, which makes it difficult to clarify the mutual predictive relationship and direction of action between the two. Objective To explore the longitudinal association between nighttime sleep duration and depression among older adults in China over a 10-year period, providing scientific evidence for developing sleep intervention and depression prevention strategies tailored to the elderly. Methods Based on data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2011 to 2020, this study selected 5 954 older adults who completed the 2011 baseline survey and at least one follow-up survey as participants. Depression was assessed using the 10-Item Center for Epidemiological Studies-Depression Scale (CESD-10), and a self-designed questionnaire was used to collect basic information such as nighttime sleep duration among the elderly. Cross-lagged path analysis (CLPA) was employed to analyze the bidirectional relationship between nighttime sleep duration and depression in Chinese older adults. Results The nighttime sleep duration was negatively correlated with CESD-10 scores at baseline and last follow-up (r=-0.299, -0.247, P<0.01). CLPA model results indicated that the baseline CESD-10 scores predicted nighttime sleep duration at the last follow-up (β=-0.100, P<0.001), and the baseline nighttime sleep duration predicted CESD-10 scores at the last follow-up (β=-0.041, P<0.001). Conclusion Depression in older adults is longitudinally associated with nighttime sleep duration, and there is a bidirectional negative predictive relationship between them. |
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