To explore the effects of different air pollutants on the outpatient quantity of respiratory diseases, with the city of xi′an as the research object.

collected relevant data, including the daily data of six kinds of air pollutants in Xi′an from 2015 to 2016 (PM_2.5 and PM₁₀, CO, SO₂, NO₂ and O₃), the daily meteorological data in Xi′an from 2015 to 2016 (average temperature, daily average relative humidity and daily average air pressure, wind speed), and the daily outpatient and emergency data of respiratory departments of two comprehensive 3A grade hospitals in Xi′an during the same period. Spearman′s rank correlation test was used to evaluate the correlation between air pollutants and meteorological factors during the same period. A smooth spline function was used to control the influence of daily mean temperature, relative humidity, air pressure and long-term trend on the outpatient volume of respiratory diseases. The Day of the Week effect (DOW) was incorporated into the multivariate regression model as a dummy variable. Considering the lag effect of 0 to 7 days, this paper adopted the Generalized Additive Model (GAM) taking Poisson distribution as the connection function.Through the construction of single pollutant models and the analysis of age and disease subgroups, the influence of air pollutants on the number of outpatient and emergency visits of respiratory diseases were studied. This paper explained the specific effect of air pollutants on population health in Xi′an.

This study showed that for every 10 μg/m³ increase in the concentration of PM_2.5 in xi′an, the emergency department volume of respiratory diseases increased by 0.39% (ER=0.39, 95%CI: 0.37~0.41, P<0.05), and the strongest effect was achieved on the 6th day. For every 10 μg/m³ increase in concentration of PM₁₀, the emergency department volume of respiratory diseases in xi′an increased by 0.34% (ER=0.34, 95%CI: 0.32~0.35, P<0.05). For every 10 mg/m³ increase in concentration of CO, e emergency department volume of respiratory diseases increased by 48.53%(ER=48.53, 95%CI: 46.07~51.03, P<0.05), and the strongest effect was at day 6.For every 10 μg/m³ increase in concentration of NO₂, the emergency department volume of respiratory diseases in xi′an increased by 0.96% (ER=0.96, 95%CI: 0.9~1.02, P<0.05). For every 10 μg/m³ increase in the concentration of SO₂, the emergency department volume of respiratory system in xi′an increased by 2.13% (ER=2.13, 95%CI: 2.04~2.23, P<0.05). For every 10 μg/m³ increase in the concentration of O₃, the emergency department volume of respiratory diseases in xi′an increased by 0.07% (ER=0.07, 95%CI: 0.04~0.10, P<0.05). The increase of the concentrations of PM_2.5, PM₁₀, CO, SO₂, NO₂ and O₃ will all cause an increase in the outpatient volume of respiratory diseases, and the effect is the biggest on the 6th day of lag. The effect of CO on the outpatient volume of respiratory system is particularly obvious.

The results of this study showed that exposure to the concentration of six major air pollutants in xi′an would increase the number of outpatient visits for respiratory diseases, among which pollutant CO had the greatest impact on the number of outpatient visits.