Abstract
Objective:: The novel coronavirus (n COVID-19) has affected every walk of life across the world including India. Several studies have been available on the COVID-19-related anxiety and depressive symptoms in the public health context. However, there is a dearth of evidence of a meta-analysis regarding the pooled estimates of anxiety and depressive symptoms related to this pandemic based on the existing studies conducted among the general population of India. The aim of the study was to estimate the pooled prevalence of COVID-19-related anxiety and depressive symptoms among the general population in India. Material and Methods:: We searched the following electronic bibliographic databases: PubMed, Ovid, Science Direct, and Wiley online library for studies conducted from the onset of the COVID-19 pandemic and until September 25, 2021. We separately analyzed the outcome measures based on the risk of bias assessment. The publication bias was evaluated by funnel plots and Eggers test. Results:: We used a random-effect model due to the significant heterogeneity between the studies (Anxiety symptoms I2 = 99.40% and Depressive symptoms I2 = 95.3%). According to the index meta-analysis, the pooled estimates of anxiety and depressive symptoms among general population of India during COVID-19 pandemic are 23.5% (95% CI: 17.429.6%; n = 21 studies) and 20.2% (95% CI: 17.223.2%; n = 17 studies), respectively. In subgroup analyses, good-quality studies (Score 7/9) had a significant effect on the pooled prevalence. Conclusion:: About one-fifth of the general population of India reported having anxiety and depressive symptoms during the COVID-19 pandemic. The pooled estimates varied with the methodological quality of included studies. The present study provides a comprehensive picture of the overall magnitude of anxiety and depressive symptoms due to the COVID-19 outbreak which will guide the policy makers to measure the burden of similar pandemics more judiciously in the future.
Copyright
Association for Helping Neurosurgical Sick People. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-Non Derivative-Non Commercial License, permitting copying and reproduction so long as the original work is given appropriate credit.
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This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.
