Association between short-term exposure to ambient air pollution and hospital visits for depression in China

Depression is one of the leading causes of disability, but the etiology remains unclear. Recently, it has been suggested that air pollution is a potential risk factor for depression. However, the results remained inconsistent. So we conducted this study to assess the association between short-term exposure to ambient air pollution and hospital visits for depression in China. Daily hospital visits for depression from January 18, 2013 to June 10, 2018 were extracted from a regional health information system (HIS) covered 1.34 million population in Ningbo, China. We collected daily air pollutant concentrations and meteorological data from environmental air quality monitoring sites and meteorological stations in the study area. Quasi-Poisson regression models with generalized additive models (GAM) were applied to explore the associations between air pollution and hospital visits for depression. Stratified analyses were also conducted by gender, age, and season to examine the effects modification. The results disclosed that air pollutants including PM_2.5, PM₁₀, SO₂, CO, and NO₂ were positively correlated with hospital visits for depression. The strongest effects all occurred on lag0 (the same) day, and the corresponding excess risks (ERs) were 2.59 (95%CI: 0.72, 4.49) for PM_2.5, 3.08 (95%CI: 1.05, 5.16) for PM₁₀, 3.22 (95%CI: 1.16, 5.32) for SO₂, 4.38 (95%CI: 1.83, 6.99) for CO, and 4.94 (95%CI: 2.03, 7.92) for NO₂ per IQR increase, respectively. The associations were found to be stronger in the elderly (≥65 years) and cold season. Furthermore, the effects of CO and NO₂ remained significant in most two-pollutant models, suggesting that traffic-related air pollutants might be more important triggers of depression.