Ambient concentrations of particulate matter and hospitalization for depression in 26 Chinese cities: A case-crossover study

Abstract

ObjectiveAir pollution with high ambient concentrations of particulate matter (PM) has been frequently reported in China. However, no Chinese study has looked into the short-term effect of PM on hospitalization for depression. We used a time-stratified case-crossover design to identify possible links between ambient PM levels and hospital admissions for depression in 26 Chinese cities. MethodsElectronic hospitalization summary reports (January 1, 2014–December 31, 2015) were used to identify hospital admissions related to depression. Conditional logistic regression was applied to determine the association between PM levels and hospitalizations for depression, with stratification by sex, age, and comorbidities. ResultsBoth PM2.5 and PM10 levels were positively associated with the number of hospital admissions for depression. The strongest effect was observed on the day of exposure (lag day 0) for PM10, with an interquartile range increase in PM10 associated with a 3.55% (95% confidence interval: 1.69–5.45) increase in admissions for depression. For PM2.5, the risks of hospitalization peaked on lag day 0 (2.92; 1.37–4.50) and lag day 5 (3.65; 2.09–5.24). The elderly (>65) were more sensitive to PM2.5 exposure (9.23; 5.09–13.53) and PM10 exposure (6.35; 3.31–9.49) on lag day 0, and patients with cardiovascular disease were likely to be hospitalized for depression following exposure to high levels of PM10 (4.47; 2.13–6.85). ConclusionsShort-term elevations in PM may increase the risk of hospitalization for depression, particularly in the elderly and in patients with cardiovascular disease.