Association between Ambient Air Pollutants and Pneumonia in Wuhan, China, 2014–2017

Abstract

Objectives: To assess associations between short-time air pollution exposure and outpatient visits for pneumonia by the distributed lag nonlinear model (DLNM). Methods: Daily outpatient visits for pneumonia and air pollutant data were collected from Wuhan Basic Medical Insurance Database in China and 10 national air quality monitoring stations in Wuhan from 2014 to 2017, respectively. Taking the first percentile of the concentration as the reference, DLNM was used to estimate the impact of moderate (50th) and high levels (99th) of pollutants on pneumonia. Results: A total of 133,882 outpatient visits were identified during the period of the study. Moderate-level (P50) fine particulate matter (PM2.5) or sulfur dioxide (SO2) and high-level nitrogen dioxide (NO2) (P99) can increase the risk of pneumonia. The maximum RR was 1.198 (95% CI: 1.094–1.311) at lag0-11, 1.304 (95% CI: 1.166–1.458) at lag0-13, and 1.286 (95% CI: 1.060–1.561) at lag0-14, respectively. Females and children had greater risks. Conclusions: Short-time PM2.5, SO2, and NO2 exposure were associated with outpatient visits for pneumonia in Wuhan, China.

Keywords

• air pollutants
• pneumonia
• outpatient visits
• distributed lag nonlinear model
• time series research