Qin-Wei Qiu1, Sheng Qian1, Jia-Yu Li1, Rui-Xia Jia1, Ying-Quan Wang1, Yong Xu2. 1. Department of Social Medicine, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Soochow University, Suzhou, PR China. 2. Department of Social Medicine, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Soochow University, Suzhou, PR China. Electronic address: xuchildhealth@163.com.
Abstract
BACKGROUND: The study aims to explore the risk factors for depressive symptoms among older Chinese adults. METHODS: PubMed, PsycINFO, Cochrane Library, EMbase, Google Scholar, Chinese National Knowledge Infrastructure (CNKI), Chinese BioMedical Literature Database, and Wanfang data were searched for potentially relevant articles published before September 1st, 2019. Stata/IC 15 was used to perform a meta-analysis and subgroup analysis to compute the pooled odds ratio. RESULTS: The retrieve strategy yielded 11 studies that met the inclusion criteria. The total sample size was 31528 across seven districts, including Mainland China, Hong Kong, and Taiwan. Patients with depression were included in the sample size. Fourteen risk factors were extracted for at least having two or more relative studies. The combined odds ratio ranged from 0.70 to 4.75. Female, poor self-perceived financial condition, single, average and poor self-perceived health status, diabetes, adverse life events, poor social support, two or more numbers of cardiovascular diseases, and functional disability are risk factors of depressive symptoms among older Chinese adults. Fair or good social support is a protective factor. LIMITATIONS: These findings may be somewhat limited by (i) quality of studies included, (ii) a finite number of studies met inclusion criteria. CONCLUSIONS: Despite the methodological limitations of the studies and this meta-analysis, average or poor self-perceived health status, functional disability, poor social support, poor self-perceived financial condition, negative life events, and diabetes appear to be significant risk factors for depressive symptoms among the aged population in China. Social support can mitigate depressive symptoms.
BACKGROUND: The study aims to explore the risk factors for depressive symptoms among older Chinese adults. METHODS: PubMed, PsycINFO, Cochrane Library, EMbase, Google Scholar, Chinese National Knowledge Infrastructure (CNKI), Chinese BioMedical Literature Database, and Wanfang data were searched for potentially relevant articles published before September 1st, 2019. Stata/IC 15 was used to perform a meta-analysis and subgroup analysis to compute the pooled odds ratio. RESULTS: The retrieve strategy yielded 11 studies that met the inclusion criteria. The total sample size was 31528 across seven districts, including Mainland China, Hong Kong, and Taiwan. Patients with depression were included in the sample size. Fourteen risk factors were extracted for at least having two or more relative studies. The combined odds ratio ranged from 0.70 to 4.75. Female, poor self-perceived financial condition, single, average and poor self-perceived health status, diabetes, adverse life events, poor social support, two or more numbers of cardiovascular diseases, and functional disability are risk factors of depressive symptoms among older Chinese adults. Fair or good social support is a protective factor. LIMITATIONS: These findings may be somewhat limited by (i) quality of studies included, (ii) a finite number of studies met inclusion criteria. CONCLUSIONS: Despite the methodological limitations of the studies and this meta-analysis, average or poor self-perceived health status, functional disability, poor social support, poor self-perceived financial condition, negative life events, and diabetes appear to be significant risk factors for depressive symptoms among the aged population in China. Social support can mitigate depressive symptoms.
Authors: Gianluca Ciuffreda; Sara Cabanillas-Barea; Andoni Carrasco-Uribarren; María Isabel Albarova-Corral; María Irache Argüello-Espinosa; Yolanda Marcén-Román Journal: Int J Environ Res Public Health Date: 2021-11-12 Impact factor: 3.390
Authors: Chin-Chen Liu; Yi-Tung Lin; Kung-Chuan Cheng; Hsueh-Hsing Pan; Chou-Ping Chiou Journal: Int J Environ Res Public Health Date: 2022-08-01 Impact factor: 4.614