Air pollution exposure has been related with mental disorders, especially depression; however, the available evidence on these associations in Low and Middle-Income Countries (LMICs) is scarce. Therefore, we aimed to assess the relationship between particulate matter (PM) exposure and indicators of traffic with depressive symptoms in women of Sabzevar, Iran. This cross-sectional study was based on 741 women aged 15-45 years (adults) in 2019. The annual average of PM10, PM2.5 and PM1 at home was estimated using land use regression (LUR) models. Street map of Sabzevar was used to calculate the indicators of traffic, i.e., the proximity to major roads and total street length buffers with 100, 300 and 500 m radii around the participants' homes. We used the Center for Epidemiological Studies- Depression (CESD-20) Scale in the general population to measure depression scores. Quasi-Poisson models and logistic regression were used to examine the association and odds ratios of exposure to air pollution and depression scores adjusted for relevant covariates. Exposure to PM10, PM2.5 and PM1 and total street length in 100 m buffer were significantly associated with higher depression scores. In fully adjusted model, an interquartile range (IQR) increase in PM10, PM2.5 and PM1 concentration as well as total street length in 100 m buffer was associated with 1.25 (95% CI:1.03, 1.52, P-value = 0.02), 1.16 (95% CI: 1.06, 1.26, P-value< 0.01), 1.16 (95% CI: 1.03, 1.29, P-Value = 0.01) and 1.15 (95% CI: 1.06, 1.25, P-value< 0.01) odds of clinical depression, respectively. For street length in 300 and 500 m buffers and proximity to major roads, no statistically significant increased risk of clinical depression were observed. Overall, our findings recommended that air pollution exposure has increased the risk of clinical depression in women.
Keywords: Air pollution; Depression; Middle-income country; Traffic.
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