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在一项基于大规模人群的研究中,睡眠效率可能预示着抑郁症。

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

作者信息

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

机构信息

Department of Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.

Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.

出版信息

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

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; = 0.016) and WASO (OR, 1.021; 95% CI 1.002-1.039; = 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; = 0.007) than in women (OR, 0.950; 95% CI 0.838-1.078; = 0.429) in subgroup analysis ( < 0.05).

CONCLUSIONS

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

摘要

目的

本研究旨在探讨客观睡眠特征对抑郁症发病率的影响。

方法

本研究的参与者(1595名男性和1780名女性,年龄63.1±10.7岁)选自睡眠心脏健康研究(SHHS)数据集。抑郁症定义为在SHHS第1次访视和第2次访视之间首次出现。通过多导睡眠图监测客观睡眠特征,包括睡眠效率(SE)、睡眠开始后觉醒时间(WASO)、睡眠片段化指数(SFI)和觉醒指数(ArI)。采用多变量逻辑回归分析来探讨睡眠特征与抑郁症之间的关系。

结果

在SHHS第1次和第2次访视之间共观察到248例抑郁症患者(7.3%)。在调整协变量后,SE(比值比[OR],0.891;95%置信区间[CI]0.811 - 0.978;P = 0.016)和WASO(OR,1.021;95%CI 1.002 - 1.039;P = 0.026)与抑郁症发病率相关。此外,在亚组分析中,SE与抑郁症之间的关系在男性中(OR,0.820;95%CI 0.711 - 0.946;P = 0.007)比在女性中(OR,0.950;95%CI 0.838 - 1.078;P = 0.429)更显著(P < 0.05)。

结论

SE和WASO可能是抑郁症发病率的标志物。SE与抑郁症之间的关联在男性中更为明显。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/412d/9043133/d15971c00eb5/fpsyt-13-838907-g0001.jpg

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