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

• DOI: 10.3389/fpsyt.2022.838907
• Publication Date: 2022-04-13T04:44:47Z
• Authors: Bin Yan; Binbin Zhao; Xiaoying Jin; Wenyu Xi; Jian Yang; Lihong Yang; Xiancang Ma
• Keywords: Depression

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