Quantification of the Exposure–Lag–Response Association Between Air Pollution and Respiratory Disease Morbidity in Chongqing City, China

Abstract

The health effects of air pollution on respiratory disease morbidity and mortality commonly vary with air pollutants’ intensity and latency after exposure. However, the exposure–lag–response association is seldom explored, especially in China, where the smog has led to public displays of dissatisfaction and became a big political issue. In this study, the distributed lag nonlinear model (DLNM) and the generalized additive model (GAM) was used to estimate the relative risk of air pollution exposure history for respiratory disease admission in Chongqing City, China. The results reveals that the health effect of inhalable particulate matter (PM10) can be estimated using a cross-basis by combining two linear functions that respectively model the exposure–response curve and lag–response curve. The risks of sulfur dioxide (SO2) and nitrogen dioxide (NO2) exposure are insignificant. The relative risk of PM10 exposure decreases as time goes by. The greater PM10 intensity, the more quickly the relative risk decreases. The relative risk is higher than 1.0 in 0 to 23 days after exposure. The greater PM10 intensity, the higher the relative risk is. On the contrary, the relative risk is lower than 1.0 after 23 days. The greater PM10 intensity, the lower the relative risk is. This study clarified the health effects of air pollution on respiratory disease admissions and can be used to predict the relative risk of air pollution or the cumulative health effect of a history of air pollution exposure in Chongqing City.