Ambient air pollution and depression: A systematic review with meta-analysis up to 2019.

ABSTRACT

Although epidemiological studies have evaluated the associations of ambient air pollution with depression, the results remained mixed. To clarify the nature of the association, we performed a comprehensive systematic review and meta-analysis with the Inverse Variance Heterogeneity (IVhet) model to estimate the effect of ambient air pollution on depression. Three English and four Chinese databases were searched for epidemiologic studies investigating associations of ambient particulate (diameter ≤ 2.5 µm (PM2.5), ≤10 µm (PM10)) and gaseous (nitric oxide (NO), nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2) and ozone (O3)) air pollutants with depression. Odds ratios (OR) and corresponding 95% confidence intervals (CI) were calculated to evaluate the strength of the associations. We identified 22 eligible studies from 10 countries of the world. Under the IVhet model, per 10 µg/m3 increase in long-term exposure to PM2.5 (OR 1.12, 95% CI 0.97-1.29, I2 51.6), PM10 (OR 1.04, 95% CI 0.88-1.25, I2 85.7), and NO2 (OR 1.05, 95% CI 0.83-1.34, I2 83.6), as well as short-term exposure to PM2.5 (OR 1.01, 95% CI 0.99-1.04, I2 51.6), PM10 (OR 1.01, 95% CI 0.98-1.04, I2 86.7), SO2 (OR 1.03, 95% CI 0.99-1.07, I2 71.2), and O3 (OR 1.01, 95% CI 0.99-1.03, I2 82.2) was not significantly associated with depression. However, we observed significant association between short-term NO2 exposure (per 10 µg/m3 increase) and depression (OR 1.02, 95% CI 1.00-1.04, I2 65.4). However, the heterogeneity was high for all of the pooled estimates, which reduced credibility of the cumulative evidence. Additionally, publication bias was detected for six of eight meta-estimates. In conclusion, short-term exposure to NO2, but not other air pollutants, was significantly associated with depression. Given the limitations, a larger meta-analysis incorporating future well-designed longitudinal studies, and investigations into potential biologic mechanisms, will be necessary for a more definitive result.