AUTHOR=Qiao Chunhong , Zhang Hui , Song Qi , Wang Xi , Wang Xiaofeng , Yao Yin
TITLE=Sleep Disturbances Are Associated With Depressive Symptoms in a Chinese Population: The Rugao Longevity and Aging Cohort
JOURNAL=Frontiers in Psychiatry
VOLUME=12
YEAR=2021
URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2021.731371
DOI=10.3389/fpsyt.2021.731371
ISSN=1664-0640
ABSTRACT=Objective: To investigate the cross-sectional and longitudinal relationships between sleep disturbances and depressive symptoms in older Chinese adults.
Methods: This study included baseline and 3.5-year follow-up data of 1,631 Chinese men and women aged 70 years or older from the aging arm of the Rugao Longevity and Aging Study. Depressive symptoms were assessed by the 15-item Geriatric Depression Scale (GDS). Sleep disturbances were assessed by using the Pittsburgh Sleep Quality Index (PSQI). Logistic regression models were used to estimate the odds ratios (ORs) of the associations.
Results: In the cross-sectional analysis, individuals with greater total PSQI scores exhibited significantly higher risk of “depressive symptoms” (OR: 1.31, 95% CI: 1.21–1.41) and “some depressive symptoms” (OR: 1.22, 95% CI: 1.17–1.28). Specifically, higher scores on the sleep efficiency PSQI subscale were associated with greater odds for “depressive symptoms” (OR: 1.54, 95% CI: 1.30–1.84) and “some depressive symptoms” (OR: 1.42, 95% CI: 1.29–1.57). Our longitudinal analyses indicated an association between greater PSQI total scores at baseline and greater odds of having “some depressive symptoms” at follow-up (OR: 1.07, 95% CI: 1.00–1.14). Additionally, higher scores on the sleep efficiency PSQI subscale had an association with higher odds for “some depressive symptoms” (OR: 1.21, 95% CI: 1.04–1.41).
Conclusions: Poor self-reported global sleep quality and sleep efficiency PSQI subscale scores were associated with levels of depressive symptoms in an older Chinese population, indicating that global sleep quality and sleep efficiency may be risk factors for depression and can possibly predict the levels of depressive symptoms.