To study the short-term effects of air pollution on asthma visits and differences in susceptibility to various groups of people, data for asthma visits from January 1, 2013 to December 31, 2015 were obtained from a Hangzhou hospital. Considering the nonlinear relationships among concentration of air pollutants, respiratory hospital outpatient visits and meteorological factors, Generalized Additive Models (GAM) and stratification analysis were used to explore the lag effects and differences in people stratifications. The natural cubic spline function was used for smoothing the average temperature, the average relative humidity and the long-term trend, using dummy variables to control the effect of the day of the week and of holidays. Correlation of PM2.5, NO2 and SO2 daily mean concentrations were significant (under 0.01) in Spearman correlation analysis, while the correlations of daily mean temperature and 3 pollutants were significantly negative. The lag effects of PM2.5 concentration on outpatient visits of asthma peaked at 3-5 days. The relative risk of asthma reached maximum at lag day 5 as 1.0056 (95% CI:1.0021-1.0091), with per 10 μg·m-3 increment of PM2.5 concentration. The relative risk of asthma outpatient visits of all groups of patients were statistically significant (P<0.05). The relative risk of asthma outpatient visits of males and young and middle-aged group were statistically significant at lag days 3-5, and for females and the elderly, were statistically significant at lag day 5. With the introduction of the effects of NO2, the relative risk of asthma outpatient visits increased at lag 5 day in co-pollutant models. The authors concluded that the increase of PM2.5 may be related to the increase of asthma hospital outpatient visits within 3-5 days in Hangzhou, and the effects on male group and elderly group were more definite.
Keywords: air pollution; asthma; hospital outpatient visits; short-term effects; time-series analysis.