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      Gender Difference in the Prevalence of Insomnia: A Meta-Analysis of Observational Studies

      systematic-review

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          Abstract

          Objective: Insomnia is a major health challenge in the general population, but the results of the gender differences in the epidemiology of insomnia have been mixed. This is a meta-analysis to examine the gender difference in the prevalence of insomnia among the general population.

          Methods:Two reviewers independently searched relevant publications in PubMed, EMBASE, PsycINFO, Web of Science from their inception to 16 April 2019. Studies that reported the gender-based prevalence of insomnia according to the international diagnostic criteria were included for analyses using the random-effects model.

          Results:Eventually 13 articles were included in the meta-analysis. The pooled prevalence of insomnia in the general population was 22.0% [ n = 22,980, 95% confidence interval (CI): 17.0–28.0%], and females had a significantly higher prevalence of insomnia compared with males (OR = 1.58, 95% CI: 1.35, 1.85, Z = 5.63, p < 0.0001). Subgroup analyses showed that greater gender difference was associated with the use of case-control study design and consecutive sampling method. Meta-regression analyses also revealed that higher proportion of females and better study quality were significantly associated with greater gender difference.

          Conclusions:This meta-analysis found that the prevalence of insomnia in females was significantly higher than males in the included studies. Due to the negative effects of insomnia on health, regular screening, and effective interventions should be implemented in the general population particularly for females.

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          Most cited references54

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          Measuring inconsistency in meta-analyses.

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            Bias in meta-analysis detected by a simple, graphical test

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              Quantifying heterogeneity in a meta-analysis.

              The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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                Author and article information

                Contributors
                Journal
                Front Psychiatry
                Front Psychiatry
                Front. Psychiatry
                Frontiers in Psychiatry
                Frontiers Media S.A.
                1664-0640
                20 November 2020
                2020
                : 11
                : 577429
                Affiliations
                [1] 1Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University , Luzhou, China
                [2] 2Neurosurgery Clinical Medical Research Center of Sichuan Province, Academician (Expert) Workstation of Sichuan Province , Luzhou, China
                [3] 3Unit of Psychiatry, Faculty of Health Sciences, Institute of Translational Medicine, University of Macau , Macao, China
                [4] 4Center for Cognition and Brain Sciences, University of Macau , Macao, China
                [5] 5Institute of Advanced Studies in Humanities and Social Sciences, University of Macau , Macao SAR, China
                [6] 6The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University , Beijing, China
                [7] 7Pui Ching Middle School Macau , Macao, China
                [8] 8Department of Psychiatry, The Melbourne Clinic and St. Vincent's Hospital, University of Melbourne , Melbourne, VIC, Australia
                Author notes

                Edited by: Maurice M. Ohayon, Stanford University, United States

                Reviewed by: Masaya Takahashi, National Institute of Occupational Safety and Health, Japan; Mikhail G. Poluektov, I.M. Sechenov First Moscow State Medical University, Russia

                *Correspondence: Li-Gang Chen chengligang.cool@ 123456163.com

                This article was submitted to Sleep Disorders, a section of the journal Frontiers in Psychiatry

                †These authors have contributed equally to this work

                Article
                10.3389/fpsyt.2020.577429
                7714764
                33329116
                0ecfa9f7-0246-4fdb-a192-4e9f868bf368
                Copyright © 2020 Zeng, Zong, Yang, Zhang, Xiang, Ng, Chen and Xiang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 29 June 2020
                : 06 October 2020
                Page count
                Figures: 3, Tables: 2, Equations: 0, References: 54, Pages: 9, Words: 4744
                Categories
                Psychiatry
                Systematic Review

                Clinical Psychology & Psychiatry
                insomnia,prevalence,gender difference,meta-analysis,observational studies

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