Shao Jiaxian, Yu Yuncong, Cheng Cheng, Gao Min, Li Xiaona, Ma Dongping, Yin Wenqiang, Chen Zhongming
School of Management, Shandong Second Medical University, Weifang, Shandong, China.
WeiFang Mental Health Center, Weifang, Shandong, China.
Iran J Public Health. 2024 Apr;53(4):785-798. doi: 10.18502/ijph.v53i4.15555.
We aimed to analyze the prevalence of depression among the global public during COVID-19, identify its influencing factors in order to provide reference, and help safeguard public mental health.
A comprehensive literature on global public depression in various countries during the COVID-19 pandemic was obtained through electronic searches of PubMed, Web of Science, and other databases, combined with literature tracing from Dec 2019 to Mar 2023. Then a meta-analysis was conducted using the random effects model by Stata 16.0. The heterogeneity was evaluated by . Subgroup analysis, sensitivity analysis, and meta-regression analysis were used to explore the sources of heterogeneity and the factors influencing public depression. Egger's test was used to test publication bias.
Overall, 68 articles with 234,678 samples were included in the study. Analysis revealed that the overall prevalence of depression among the population during COVID-19 was 32.0% (95% CI: 29.0%-35.0%). Of these, marital status (OR=0.65, 95% CI: 0.47-0.87), presence of infected cases (OR=2.45, 95% CI: 1.82-3.30), and fear of being infected by the virus (OR=9.31, 95% CI: 6.03-14.37) were the main factors influencing people's depression and the main source of heterogeneity.
The prevalence of depression among the global public is at a high level during COVID-19. The prevalence of depression among people unmarried, divorced, or widowed, surrounded by infected cases, contact infection cases, and worried about being were higher than others.
我们旨在分析新冠疫情期间全球公众中抑郁症的患病率,确定其影响因素以提供参考,并帮助保障公众心理健康。
通过对PubMed、Web of Science等数据库进行电子检索,并结合2019年12月至2023年3月的文献追溯,获取了关于新冠疫情期间各国全球公众抑郁症的综合文献。然后使用Stata 16.0的随机效应模型进行荟萃分析。通过 评估异质性。采用亚组分析、敏感性分析和荟萃回归分析来探索异质性来源和影响公众抑郁症的因素。使用Egger检验来检验发表偏倚。
总体而言,该研究纳入了68篇文章,共234,678个样本。分析显示,新冠疫情期间人群中抑郁症的总体患病率为32.0%(95%置信区间:29.0%-35.0%)。其中,婚姻状况(OR=0.65,95%置信区间:0.47-0.87)、有感染病例(OR=2.45,95%置信区间:1.82-3.30)以及担心感染病毒(OR=9.31,95%置信区间:6.03-14.37)是影响人们抑郁症的主要因素和异质性的主要来源。
新冠疫情期间全球公众中抑郁症的患病率处于较高水平。未婚、离异或丧偶、周围有感染病例、接触过感染病例以及担心被感染的人群中抑郁症的患病率高于其他人。