Sleep Efficiency May Predict Depression in a Large Population-Based Study

5Citations
Citations of this article
15Readers
Mendeley users who have this article in their library.

Abstract

Objectives: The purpose of our study was to investigate the effect of objective sleep characteristics on the incidence of depression. Methods: The participants of our study (1,595 men and 1,780 women with 63.1 ± 10.7 years) were selected from the Sleep Heart Health Study (SHHS) datasets. Depression was defined as the first occurrence between SHHS visit 1 and visit 2. Objective sleep characteristics, including sleep efficiency (SE), wake after sleep onset (WASO), sleep fragmentation index (SFI) and arousal index (ArI), were monitored by polysomnography. Multivariable logistic regression was used to explore the relationship between sleep characteristics and depression. Results: A total of 248 patients with depression (7.3%) were observed between SHHS visits 1 and 2. After adjusting for covariates, SE (odds ratio [OR], 0.891; 95% confidence interval [CI] 0.811–0.978; P = 0.016) and WASO (OR, 1.021; 95% CI 1.002–1.039; P = 0.026) were associated with the incidence of depression. Moreover, the relationship between SE and depression was more pronounced in men (OR, 0.820; 95% CI 0.711–0.946; P = 0.007) than in women (OR, 0.950; 95% CI 0.838–1.078; P = 0.429) in subgroup analysis (Pinteraction < 0.05). Conclusions: SE and WASO may be markers for the incidence of depression. The association between SE and depression was intensified in men.

Cite

CITATION STYLE

APA

Yan, B., Zhao, B., Jin, X., Xi, W., Yang, J., Yang, L., & Ma, X. (2022). Sleep Efficiency May Predict Depression in a Large Population-Based Study. Frontiers in Psychiatry, 13. https://doi.org/10.3389/fpsyt.2022.838907

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free