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Binary Logistic Regression Analysis of Prevalence of Depression and Anxiety among University Students in India during COVID-19 Pandemic

Covid 19 has posed grave challenges and caused serious disruptions and distress across the world. On one hand the imposition of nationwide lockdowns has helped to curb the virus on the other hand it has resulted in significant damage to public mental health. The aim of this study was to investigate the prevalence of depression and anxiety among students of various universities in India during the COVID-19 pandemic. It also aimed at identifying the factors and determinants of depression and anxiety. A total of 138 university students living in various parts of India, accepted to participate in this cross- sectional web-based survey. A standardized e-questionnaire was generated using the Google Form, and the link was shared through social media, mainly via WhatsApp. The information was analysed in three consecutive levels, such as, univariate, bivariate, and multivariate analysis. Around 14.4% of the students reportedly had moderately severe depression, whereas 18.1% were severely suffering from anxiety. The binary logistic regression suggests that students in the age range 21-23 have greater depression (OR = 3.009, 95% CI = 1.072–8.446). It is also evident that students who were not provided with tuition in the pre-pandemic period had depression (OR =0.699, 95% CI =0.250-1.957). Key Words: Covid-19, Binary Logistic Regression, Anxiety, Depression.