Insomnia as a predictor of depression: A meta-analytic evaluation of longitudinal epidemiological studies

荟萃分析 萧条(经济学) 优势比 失眠症 精神科 流行病学 置信区间 医学 临床心理学 人口 心理学 内科学 环境卫生 宏观经济学 经济
作者
Chiara Baglioni,Gemma Battagliese,Bernd Feige,Kai Spiegelhalder,Christoph Nissen,Ulrich Voderholzer,Caterina Lombardo,Dieter Riemann
出处
期刊:Journal of Affective Disorders [Elsevier BV]
卷期号:135 (1-3): 10-19 被引量:2632
标识
DOI:10.1016/j.jad.2011.01.011
摘要

In many patients with depression, symptoms of insomnia herald the onset of the disorder and may persist into remission or recovery, even after adequate treatment. Several studies have raised the question whether insomniac symptoms may constitute an independent clinical predictor of depression. This meta-analysis is aimed at evaluating quantitatively if insomnia constitutes a predictor of depression. PubMed, Medline, PsycInfo, and PsycArticles databases were searched from 1980 until 2010 to identify longitudinal epidemiological studies simultaneously investigating insomniac complaints and depressed psychopathology. Effects were summarized using the logarithms of the odds ratios for insomnia at baseline to predict depression at follow-up. Studies were pooled with both fixed- and random-effects meta-analytic models in order to evaluate the concordance. Heterogeneity test and sensitivity analysis were computed. Twenty-one studies met inclusion criteria. Considering all studies together, heterogeneity was found. The random-effects model showed an overall odds ratio for insomnia to predict depression of 2.60 (confidence interval [CI]: 1.98–3.42). When the analysis was adjusted for outliers, the studies were not longer heterogeneous. The fixed-effects model showed an overall odds ratio of 2.10 (CI: 1.86–2.38). The main limit is that included studies did not always consider the role of other intervening variables. Non-depressed people with insomnia have a twofold risk to develop depression, compared to people with no sleep difficulties. Thus, early treatment programs for insomnia might reduce the risk for developing depression in the general population and be considered a helpful general preventive strategy in the area of mental health care.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Bobo发布了新的文献求助10
刚刚
外向烨磊完成签到,获得积分20
1秒前
Twonej举报yiwen求助涉嫌违规
1秒前
2秒前
充电宝应助无限莫言采纳,获得10
3秒前
4秒前
4秒前
暴龙战士完成签到 ,获得积分10
4秒前
隐形曼青应助冷静的石头采纳,获得10
4秒前
5秒前
5秒前
chy完成签到 ,获得积分10
6秒前
7秒前
猴子完成签到,获得积分10
7秒前
可爱的函函应助超厉害的采纳,获得10
8秒前
和谐面包完成签到 ,获得积分10
8秒前
mirror应助QQQ采纳,获得10
8秒前
8秒前
邪恶银渐层关注了科研通微信公众号
9秒前
KEQIN发布了新的文献求助50
9秒前
专注的雪发布了新的文献求助10
9秒前
小石头完成签到,获得积分10
10秒前
Hello应助艺_采纳,获得30
10秒前
搜集达人应助张萌采纳,获得30
10秒前
SciGPT应助淡然沛儿采纳,获得10
10秒前
小刘小刘发布了新的文献求助10
11秒前
11秒前
Orange应助高国豪采纳,获得10
12秒前
1821977451发布了新的文献求助10
12秒前
三九完成签到,获得积分10
12秒前
xxxgoldxsx完成签到,获得积分10
12秒前
12秒前
FashionBoy应助tangxinhebaodan采纳,获得10
14秒前
CodeCraft应助tangxinhebaodan采纳,获得10
14秒前
14秒前
Owen应助小石头采纳,获得10
14秒前
李健应助tangxinhebaodan采纳,获得10
14秒前
英姑应助tangxinhebaodan采纳,获得10
14秒前
打打应助tangxinhebaodan采纳,获得10
14秒前
汉堡包应助顾阿秀采纳,获得10
14秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Lewis’s Child and Adolescent Psychiatry: A Comprehensive Textbook Sixth Edition 2000
Continuing Syntax 1000
Encyclopedia of Quaternary Science Reference Work • Third edition • 2025 800
Signals, Systems, and Signal Processing 510
Pharma R&D Annual Review 2026 500
荧光膀胱镜诊治膀胱癌 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6216674
求助须知:如何正确求助?哪些是违规求助? 8041996
关于积分的说明 16762775
捐赠科研通 5304152
什么是DOI,文献DOI怎么找? 2825891
邀请新用户注册赠送积分活动 1804083
关于科研通互助平台的介绍 1664168