PLoS Medicine (Apr 2023)

COVID-19 and mental health in 8 low- and middle-income countries: A prospective cohort study.

  • Nursena Aksunger,
  • Corey Vernot,
  • Rebecca Littman,
  • Maarten Voors,
  • Niccolò F Meriggi,
  • Amanuel Abajobir,
  • Bernd Beber,
  • Katherine Dai,
  • Dennis Egger,
  • Asad Islam,
  • Jocelyn Kelly,
  • Arjun Kharel,
  • Amani Matabaro,
  • Andrés Moya,
  • Pheliciah Mwachofi,
  • Carolyn Nekesa,
  • Eric Ochieng,
  • Tabassum Rahman,
  • Alexandra Scacco,
  • Yvonne van Dalen,
  • Michael Walker,
  • Wendy Janssens,
  • Ahmed Mushfiq Mobarak

DOI
https://doi.org/10.1371/journal.pmed.1004081
Journal volume & issue
Vol. 20, no. 4
p. e1004081

Abstract

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BackgroundThe Coronavirus Disease 2019 (COVID-19) pandemic and associated mitigation policies created a global economic and health crisis of unprecedented depth and scale, raising the estimated prevalence of depression by more than a quarter in high-income countries. Low- and middle-income countries (LMICs) suffered the negative effects on living standards the most severely. However, the consequences of the pandemic for mental health in LMICs have received less attention. Therefore, this study assesses the association between the COVID-19 crisis and mental health in 8 LMICs.Methods and findingsWe conducted a prospective cohort study to examine the correlation between the COVID-19 pandemic and mental health in 10 populations from 8 LMICs in Asia, Africa, and South America. The analysis included 21,162 individuals (mean age 38.01 years, 64% female) who were interviewed at least once pre- as well as post-pandemic. The total number of survey waves ranged from 2 to 17 (mean 7.1). Our individual-level primary outcome measure was based on validated screening tools for depression and a weighted index of depression questions, dependent on the sample. Sample-specific estimates and 95% confidence intervals (CIs) for the association between COVID-19 periods and mental health were estimated using linear regressions with individual fixed effects, controlling for independent time trends and seasonal variation in mental health where possible. In addition, a regression discontinuity design was used for the samples with multiple surveys conducted just before and after the onset of the pandemic. We aggregated sample-specific coefficients using a random-effects model, distinguishing between estimates for the short (0 to 4 months) and longer term (4+ months). The random-effects aggregation showed that depression symptoms are associated with a increase by 0.29 standard deviations (SDs) (95% CI [-.47, -.11], p-value = 0.002) in the 4 months following the onset of the pandemic. This change was equivalent to moving from the 50th to the 63rd percentile in our median sample. Although aggregate depression is correlated with a decline to 0.21 SD (95% CI [-0.07, -.34], p-value = 0.003) in the period thereafter, the average recovery of 0.07 SD (95% CI [-0.09, .22], p-value = 0.41) was not statistically significant. The observed trends were consistent across countries and robust to alternative specifications. Two limitations of our study are that not all samples are representative of the national population, and the mental health measures differ across samples.ConclusionsControlling for seasonality, we documented a large, significant, negative association of the pandemic on mental health, especially during the early months of lockdown. The magnitude is comparable (but opposite) to the effects of cash transfers and multifaceted antipoverty programs on mental health in LMICs. Absent policy interventions, the pandemic could be associated with a lasting legacy of depression, particularly in settings with limited mental health support services, such as in many LMICs. We also demonstrated that mental health fluctuates with agricultural crop cycles, deteriorating during "lean", pre-harvest periods and recovering thereafter. Ignoring such seasonal variations in mental health may lead to unreliable inferences about the association between the pandemic and mental health.