PM2.5 and Emergency Calls for Health with Respiratory Diseases in Chengdu in 2017

Abstract

To determine the association between daily particulate matter 2.5 (PM2.5) mass and emergency calls for help with respiratory diseases.  Methods  Semi-parametric generalized additive model was established to determine the association between daily PM2.5 and emergency calls for help with respiratory diseases in 2017 in Chengdu, after adjustments for time trend and variations in the days of the week and weather conditions.  Results  In 2017, a total of 9,309 emergency calls for help with respiratory diseases were recorded in Chengdu: on average 26 calls a day. Over the year, Chengdu reported a mean PM2.5 mass concentration of 53.6 μg/m3, an average temperature of 16.6 ℃, and an average relative humidity of 81.2%. The single pollutant model with lag time effect showed that a 10 μg/m3 increase in PM2.5 was associated with an increase of 1.26% ［95% confidence interval (CI) 0.56%-1.97%］ emergency calls for help with respiratory diseases. The exposure-response was almost in a direct line. The dual pollutant model found that O3 8-hour sliding average (O3-8h) enhanced the effect of PM2.5 on emergency calls for help with respiratory diseases.  Conclusion  Outdoor PM2.5 is a significant predictor of emergency calls for help with respiratory diseases in Chengdu.

Keywords: Particulate matter2.5, Emergency call, Time series analysis