The role of financial stress, food insecurity, and COVID-19-related illness concerns shaping mental health in five South Asian countries during the pandemic (2020-2022): A secondary analysis of the online COVID-19 Trends and Impact Survey (CTIS) data

Abstract

The COVID-19 pandemic has substantially impacted mental health worldwide, yet little attention has been given to its acute and long-term effects on mental health in low- and middle-income countries (LMICs). This study investigates how a triad of pandemic-related worries-financial stress, food insecurity, and COVID-19-related illness concerns-are associated with depression and anxiety across five South Asian LMICs: Bangladesh, India, Nepal, Pakistan, and Sri Lanka. Using data from the COVID-19 Trends and Impact Survey (CTIS), we analyzed responses from over 3.6 million participants collected between June 27, 2020 and June 25, 2022. We employed survey-weighted logistic regression models based on the complete cases (N = 1,062,786), adjusting for demographics and calendar time. Due to a substantial change in the survey design on May 20, 2021, our analysis was divided into two distinct periods: Period 1 (pre-change) and Period 2 (post-change). Our main findings reveal that all three types of pandemic-related worries were significantly associated with increased levels of depression and anxiety across the studied countries. In Period 1, a random-effects meta-analysis showed financial stress had the highest pooled adjusted odds ratio (OR) for depression at 2.41 (95% confidence interval, CI: [2.26, 2.58]), followed by COVID-19-related illness concerns at 1.58 (95% CI: [1.43, 1.75]), and food insecurity at 1.52 (95% CI: [1.40, 1.67]). In Period 2, the pooled adjusted OR for depression increased to 2.74 (95% CI: [2.38, 3.12]) for financial stress, while food insecurity showed a notable rise to 2.42 (95% CI: [2.23, 2.62]). Heterogeneity across countries was substantial ([Formula: see text] ranged from 60.33% to 86.68%), except for the association between food insecurity and depression in Period 2. Country-specific analyses further confirmed these results. Additionally, calendar time, vaccination status, gender, education, and rural-urban residential status modified these associations. These results underscore the need for targeted interventions to address socioeconomic stressors and improve mental health resilience in LMICs.

Fig 1. Unpooled (circles) and pooled (triangles) effects of pandemic-related worries on mental health across five South Asian countries in Period 1 (N = 827,472) and Period 2 (N = 235,314), post-weighting.

Abbreviations: Period 1, June 27, 2020, to May 19, 2021; Period 2, May 20, 2021, to June 25, 2022; OR, odds ratio; CI, confidence interval. COVID-19-related health concerns were excluded from the surveys during Period 2. Separate weighted logistic regression models were fitted for complete cases stratified by each period and country, including pandemic-related worries (financial stress, food insecurity, and COVID-19-related illness concerns), demographics (gender, age, education, rural-urban residential status, and occupation), and calendar time (categorized by month and year) as covariates. The pooled estimates were obtained by a random-effects meta-analysis. The results present odds ratios with their corresponding 95% Wald confidence intervals. Robust sandwich estimators were applied for variance estimation. The vertical solid black lines represent an odds ratio of 1.

Fig 2. Effects of pandemic-related worries on mental health over time in Bangladesh during Period 1 (N = 69,047) and Period 2 (N = 34,004), post-weighting.

Abbreviations: Period 1, June 27, 2020, to May 19, 2021; Period 2, May 20, 2021, to June 25, 2022; OR, odds ratio; CI, confidence interval. COVID-19-related health concerns were excluded from the surveys during Period 2. Separate weighted logistic regression models were fitted for complete cases from each period, including pandemic-related worries (financial stress, food insecurity, and COVID-19-related illness concerns), demographics (gender, age, education, rural-urban residential status, and occupation), and calendar time (categorized by month and year) as covariates. Interaction terms between time and one worry variable were included in each model. The results present odds ratios with their corresponding 95% Wald confidence intervals. Robust sandwich estimators were applied for variance estimation. The y-axis is displayed on a logarithmic scale to improve visualization. The horizontal dashed black lines represent an odds ratio of 1.

Fig 3. Effects of pandemic-related worries on mental health between vaccination statuses across five South Asian countries during Period 2 (N = 234,149), post-weighting.

Abbreviations: Period 2, May 20, 2021, to June 25, 2022; OR, odds ratio; CI, confidence interval. COVID-19-related health concerns were excluded from the surveys during Period 2. Separate weighted logistic regression models were fitted for complete cases from each period, including pandemic-related worries (financial stress, food insecurity, and COVID-19-related illness concerns), demographics (gender, age, education, rural-urban residential status, occupation, and vaccination status), and calendar time (categorized by month and year) as covariates. Interaction terms between vaccination status and one worry variable were included in each model. The results present odds ratios with their corresponding 95% Wald confidence intervals. Robust sandwich estimators were applied for variance estimation. The x-axis is presented on a logarithmic scale to improve visualization. The vertical black lines at an odds ratio of 1 represent the null.