Back

Trajectories and correlates of poor mental health in India over the course of the COVID-19 pandemic: a nation-wide survey

Nichols, E.; Petrosyan, S.; Khobragade, P.; Banerjee, J.; Angrisani, M.; Dey, S.; Bloom, D.; Schaner, S.; Dey, A.; Lee, J.

2023-09-14 public and global health
10.1101/2023.09.13.23295513 medRxiv
Show abstract

IntroductionThe COVID-19 pandemic had large impacts on mental health; however, most existing evidence is focused on the initial lockdown period and high-income contexts. By assessing trajectories of mental health symptoms in India over two years, we aim to understand the effect of later time periods and pandemic characteristics on mental health in a lower-middle income context. MethodsWe used data from the Real-Time Insights of COVID-19 in India (RTI COVID-India) cohort study (N=3,662). We used covariate-adjusted linear regression models with generalized estimating equations to assess associations between mental health (PHQ-4 score) and pandemic periods as well as pandemic characteristics (COVID-19 cases and deaths, government stringency, self-reported financial impact, COVID-19 infection in the household) and explored effect modification by age, gender, and rural/urban residence. ResultsMental health symptoms dropped immediately following the lockdown period but rose again during the delta and omicron waves. Associations between mental health and later pandemic stages were stronger for adults 45 years of age and older (p<0.001). PHQ-4 scores were significantly and independently associated with all pandemic characteristics considered, including estimated COVID-19 deaths (PHQ-4 difference of 0.041 SD units; 95% Confidence Interval 0.030 - 0.053), government stringency index (0.060 SD units; 0.048 - 0.072), self-reported major financial impacts (0.45 SD units; 0.41-0.49), and COVID-19 infection in the household (0.11 SD units; 0.07-0.16). ConclusionWhile the lockdown period and associated financial stress had the largest mental health impacts on Indian adults, the effects of the pandemic on mental health persisted over time, especially among middle-age and older adults. Results highlight the importance of investments in mental health supports and services to address the consequences of cyclical waves of infections and disease burden due to COVID-19 or other emerging pandemics.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.