Recent epidemiological studies pointed out that air pollution has a significant impact on pediatric asthma. Shanghai is one of the biggest cities in China, and the short-term effect of atmospheric particulate matter on the incidence of pediatric asthma has become a hot topic. From January 1, 2009, to December 31, 2010, we used daily measurements of pollutant concentrations, daily weather data, and daily records of pediatric asthma hospital visits from local authorities to evaluate the short-term effect of air pollution on pediatric asthma incidence in Shanghai, China. We used a generalized additive model (GAM) in the analysis, and the controlled confounding factors include long-term trends, day-of-the-week effects, and weather elements. We divided the entire study group into different age-subgroups. In addition, we took a variety of lag models into consideration. The results showed a strong connection between concentrations of fine particulate matter (PM2.5) and pediatric asthma hospital visits from 2009 to 2010 in Shanghai, China. For the entire study group, the greatest relative risk (RR) of PM2.5 on pediatric asthma hospital visits was 1.060 on a lag of 4 days. As for the three different age-subgroups, the greatest RR of PM2.5 on pediatric asthma hospital visits was 1.061 (at a lag of 5 days), 1.071 (at a lag of 4 days), and 1.052 (at a lag of 2 days), for the under-2-year-olds, 3-to-5-year-olds, and the 6-to-18-year-olds, respectively. The overall short-term effect of PM2.5 on pediatric asthma hospital visits was relatively stronger in younger children. Within the year, we detected the strongest seasonal effect of PM2.5 on pediatric asthma hospital visits in Summer. When adding other air pollutants in the analysis model, RR of PM2.5 on pediatric asthma hospital visits would be increased.
Keywords: Generalized additive model; Hospital visits; PM2.5; Pediatric asthma; Relative risk.