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. 2022 Apr 13:13:838907.
doi: 10.3389/fpsyt.2022.838907. eCollection 2022.

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

Bin Yan  1   2 , Binbin Zhao  2 , Xiaoying Jin  2 , Wenyu Xi  2 , Jian Yang  1   2 , Lihong Yang  1 , Xiancang Ma  2
Affiliations

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

Bin Yan et al. Front Psychiatry. .

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 (P interaction < 0.05).

Conclusions: SE and WASO may be markers for the incidence of depression. The association between SE and depression was intensified in men.

Keywords: SHHS; depression; men; polysomnography; sleep efficiency.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The distribution of incident depression in different SE categories.
See this image and copyright information in PMC

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