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      Prevalence of Depression among Chinese University Students: A Meta-Analysis

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      PLoS ONE
      Public Library of Science

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          Abstract

          Background

          Depression is a major mental health issue worldwide, and university students with heavy burdens of study are at a high risk for depression. While a number of studies have been conducted regarding depression among university students in China, there is a lack of information regarding the national prevalence of depression among Chinese university students. Therefore, we performed a meta-analysis to statistically pool the prevalence of depression among Chinese university students.

          Methods

          A systematic search of scientific databases was conducted, including Chinese Web of Knowledge, Embase, PubMed, Wanfang (a Chinese database) and Weipu (a Chinese database) to find relevant publications published between 1995 and December 2015. This was supplemented by a secondary review of the reference lists of all retrieved papers to find additional relevant citations. Studies published in either English or Chinese that provided prevalence estimates of depression in Chinese university students were considered. Prevalence estimates of each eligible study were extracted and pooled in our meta-analysis using a random-effects model.

          Results

          A total of 39 studies conducted between 1997 and 2015 including 32,694 university students were analyzed. Our results indicate that the overall prevalence of depression among Chinese university students is 23.8% (95% CI: 19.9%–28.5%). Substantial heterogeneity in prevalence estimates was noted. Subgroup analysis revealed that the prevalence of depression among medical students is higher than among other students.

          Conclusions

          Overall, the prevalence of depression among Chinese university students is exceedingly high. This suggests that it is imperative that more attention be given to the development of appropriate mental healthcare strategies for university students in China.

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          Most cited references26

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          A SELF-RATING DEPRESSION SCALE.

          W W Zung (1965)
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            A systematic review of studies of depression prevalence in university students.

            Depression is a common health problem, ranking third after cardiac and respiratory diseases as a major cause of disability. There is evidence to suggest that university students are at higher risk of depression, despite being a socially advantaged population, but the reported rates have shown wide variability across settings. To explore the prevalence of depression in university students. PubMed, PsycINFO, BioMed Central and Medline were searched to identify studies published between 1990 and 2010 reporting on depression prevalence among university students. Searches used a combination of the terms depression, depressive symptoms, depressive disorders, prevalence, university students, college students, undergraduate students, adolescents and/or young adults. Studies were evaluated with a quality rating. Twenty-four articles were identified that met the inclusion and exclusion criteria. Reported prevalence rates ranged from 10% to 85% with a weighted mean prevalence of 30.6%. The results suggest that university students experience rates of depression that are substantially higher than those found in the general population. Study quality has not improved since 1990. Copyright © 2012 Elsevier Ltd. All rights reserved.
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              Associations of Physical Activity, Screen Time with Depression, Anxiety and Sleep Quality among Chinese College Freshmen

              Objectives To investigate the independent and interactive associations of physical activity (PA) and screen time (ST) with depression, anxiety and sleep quality among Chinese college students. Methods A cross-sectional study was conducted in Wuhan University, China from November to December 2011. The students reported their PA, ST and socio-economic characteristics using self-administered questionnaires. Sleep quality was measured by the Pittsburgh Sleep Quality Index (PSQI). Depression and anxiety were assessed using the Self-rating Depression Scale (SDS) and Self-rating Anxiety Scale (SAS), respectively. Multivariate logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of the independent and interactive relationships of PA and ST with depression, anxiety and sleep quality. Results A total of 1106 freshmen (471 females and 635 males) aged 18.9±0.9 years were included in the study. After adjustment for potential confounders, high PA and low ST were independently associated with significantly lower risks for poor sleep quality (OR: 0.48, 95% CI: 0.30–0.78) and depression (OR: 0.67, 95%CI: 0.44–0.89), respectively. An interactive inverse association was observed for combined effects of PA and low ST on depression (OR: 0.62, 95%CI: 0.40–0.92) and sleep quality (OR: 0.51, 95%CI: 0.27–0.91). No statistically significant associations were found between PA, ST and anxiety among the participants. Conclusions These findings suggest an independent and interactive relationship of high PA and low ST with significantly reduced prevalence of depressive problems and favorable sleep quality among Chinese college freshmen.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                12 April 2016
                2016
                : 11
                : 4
                : e0153454
                Affiliations
                [1 ]The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
                [2 ]Office of the President, Central South University, Changsha, Hunan Province, China
                [3 ]Xiangya Nursing School, Central South University, Changsha, Hunan Province, China
                Universitat Wien, AUSTRIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: YML XYL. Performed the experiments: LMX YNL. Analyzed the data: LMX YNL. Contributed reagents/materials/analysis tools: XYL. Wrote the paper: XYL YML.

                Article
                PONE-D-15-45857
                10.1371/journal.pone.0153454
                4829172
                27070790
                1e2dc0db-71e6-48f9-85e1-15597d306103
                © 2016 Lei et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 19 October 2015
                : 30 March 2016
                Page count
                Figures: 4, Tables: 2, Pages: 14
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mood Disorders
                Depression
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Meta-Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Meta-Analysis
                People and Places
                Geographical Locations
                Asia
                China
                Research and Analysis Methods
                Database and Informatics Methods
                Database Searching
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Research and Analysis Methods
                Database and Informatics Methods
                People and Places
                Population Groupings
                Ethnicities
                Chinese People
                Research and Analysis Methods
                Research Design
                Survey Research
                Questionnaires
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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                Uncategorized

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