Climate-related shocks and other stressors associated with depression and anxiety in Bangladesh: a nationally representative panel study

Abstract

Background: Climate change has major implications for common mental disorders including depression and anxiety in vulnerable nations such as Bangladesh. However, knowledge gaps exist around national estimations of depression and anxiety, and the associations between the prevalence of these disorders with climate-related and sociodemographic risk factors. To address these gaps, this study analysed data from a nationally representative panel study in Bangladesh that examined climate-related and sociodemographic correlates of depression and anxiety.

Methods: Two rounds of nationally representative household panel data were collected from urban and rural areas between August and September, 2019, and January and February, 2020. Households were selected for inclusion across 150 enumeration areas as the primary sampling units with use of a two-stage stratified random sampling design, and survey instruments were administered to the available adult member of the household. Depression and anxiety were measured with the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 scales, respectively, and weighted prevalence estimates were calculated on the basis of the 2011 national population census. Data on temperature and humidity were collected from 43 weather stations and constructed as mean values for the 2-month period preceding each round of the survey. Self-reported exposure to flooding was collected for a 12-month recall period. We applied a weighted population average logistic model on the pooled sample of both surveys to analyse the associations between ambient temperature, humidity, exposure to flooding, seasonality, sociodemographic variables, and three outcome conditions (depression, anxiety, and co-occurring depression and anxiety; at the level of p<0·1). The models accounted for temporal and spatial heterogeneity. Standard errors were clustered at the level of each primary sampling unit.

Findings: 3606 individuals were included with 3·5% dropout in the second survey round (pooled sample n=7086; age range 15-90 years; 2898 [40·9%] men and 4188 [59·1%] women). National weighted prevalence estimates were 16·3% (95% CI 14·7-17·8) for depression, 6·0% (4·7-7·3) for anxiety, and 4·8% (3·7-5·9) for co-occurring depression and anxiety. We observed no significant associations between overall seasonality (summer vs winter) and the odds of depression (adjusted odds ratio 3·14 [95% CI 0·52-19·13], p=0·22), anxiety (0·16 [0·02-1·41], p=0·10), or co-occurring depression and anxiety (0·13 [0·01-1·49], p=0·10). An increase in mean temperature of 1°C within the 2 months preceding the surveys was associated with increased odds of anxiety (1·21 [1·00-1·47], p=0·046) and increased odds of co-occurring depression and anxiety (1·24 [1·00-1·53], p=0·045), whereas increased temperature was not associated with depression (0·90 [0·77-1·04], p=0·15). An increase in mean humidity of 1 g/m³ was not associated with depression (0·99 [0·96-1·02], p=0·60) or anxiety (1·04 [0·99-1·09], p=0·13), but was associated with co-occurring depression and anxiety (1·06 [1·00-1·12], p=0·064). Exposure to flooding within the 12 months preceding the survey rounds was associated with increased odds of all outcome conditions (depression, 1·31 [1·00-1·70], p=0·047; anxiety, 1·69 [1·21-2·36], p=0·0020; and co-occurring depression and anxiety, 1·87 [1·31-2·68], p=0·0006).

Interpretation: Climate-related shocks and other stressors have an important association with the burden of depression and anxiety in Bangladesh. Community-level interventions for common mental disorders need to be developed and assessed for safety, feasibility, and effectiveness in a Bangladeshi context. Further research on climate-related stressors is needed over different timespans and time intervals.

Funding: The World Bank.