淮安市城区大气污染与呼吸系统疾病门诊量的时间序列分析

目的 探讨淮安市城区大气污染物对日呼吸系统疾病发生的急性影响,为呼吸系统疾病的早期预防提供科学依据。方法 收集淮安地区2015全年气象,环保及城区部分医疗机构呼吸系统疾病门诊量数据,采用Poisson分布广义相加模型(GAM)分析主要大气污染物(PM2.5、PM10、SO2、NO2)与呼吸系统疾病门诊量的关系。结果 (1)Spearman等级相关分析发现PM2.5、PM10、SO2和NO2与日呼吸系统疾病门诊量发生成正相关(P<0.01)；(2)单污染物模型分析显示:PM2.5、NO2对日呼吸系统疾病门诊量的影响效应均在当日达到最大值,PM10、SO2对日呼吸系统疾病门诊量的影响效应分别在滞后第4天、滞后第3天达到最大值,且日浓度每升高10 μg/m3,对呼吸系统门诊量风险增加分别为0.26%(0.076%~0.44%),2.90%(2.20%~3.60%),0.26%(0.15%~0.38%)和2.40%(1.80%~3.00%)；(3)多污染物模型分析显示:SO2与NO2在引入其他污染物时对日呼吸系统疾病门诊量影响均有所下降,且均具有统计学意义。结论 淮安市城区大气污染物(PM2.5、PM10、SO2、NO2)与呼吸系统疾病门诊量密切相关,并且SO2、NO2浓度增加更易增加呼吸系统疾病的发病风险。

A time-series study of air pollution and hospital outpatients with respiratory diseases

Objective To explore the acute effect of air pollutants on respiratory diseases in urban area of Huai′an,and to provide scientific strategies for respiratory disease prevention and control. Methods The data of meteorology,environment and the hospital outpatients with respiratory diseases were collected during 2015 in Huai′an.A generalized additive model with Poisson distribution were used to analyze the relationship between main air pollutants（PM2.5、PM10、SO2、NO2） and hospital outpatients with respiratory diseases. Results Spearman′s rank correlation analysis showed that PM2.5,PM10,SO2 and NO2 had positive relationship with hospital outpatients with respiratory diseases (P≤0.01).The uni-pollutant model showed that an increase of 10 μg/m3 of PM2.5 (lag0),NO2 (lag0),PM10 (lag4) and SO2 (lag3) were significantly related to hospital outpatients with respiratory diseases and could increase the excess risk of 0.26（0.076%~0.44%）,2.90%（2.20%~3.60%）,0.26（0.15%~0.38%） and 2.40%（1.80%~3.00%),respectively.The multi-pollutants model indicated that SO2 and NO2 slowly affect the decline of hospital outpatients with respiratory diseases,when other pollutants were brought into model. Conclusion The air pollutants (PM2.5,PM10,SO2 and NO2) have significantly positive relation with hospital outpatients with respiratory diseases,and SO2 and NO2 are more likely to increase the risk of incidence of respiratory diseases in urban area of Huai′an.