PM2.5和PM10对银川市呼吸系统疾病影响分析OA

Using daily meteorological data,atmospheric pollutant concentrations,and outpatient visits for respiratory diseases in Yinchuan City from 2015 to 2022,this study quantitatively assessed the lagged and cumulative effects of PM2.5 and PM10 on respiratory outpatient visits.A Generalized Additive Model(GAM)and the Distributed Lag Nonlinear Model(DLNM)were employed,with PM2.5 and PM10 concentrations in Yinchuan City as the primary influencing factors,while NO2,SO2,CO,wind speed,mean temperature,and maximum temperature as covariate factors.The results indicate that:(1)From 2015 to 2022,the daily number of outpatient visits for respiratory diseases showed a fluctuating upward trend with significant seasonal variations,peaking in winter and spring.(2)Both PM2.5 and PM10 concentrations exhibited a slight downward trend from 2015 to 2022.The proportion of days with PM2.5 concentrations reaching light pollution levels and above ranged from 10%to 40%,mainly occurring in spring and winter,while that for PM10 ranged between 10%and 30%.(3)Exposure to PM2.5 and PM10 exerted significant lagged and cumulative effects on respiratory disease visits.On the day of onset,the risk of respiratory disease increased with rising PM10 concentrations,and remained elevated(Relative Risk>1)for up to 2 lag days.(4)The exposure-response relationships between PM2.5/PM10 concentrations and the number of respiratory outpatient visits were generally similar across genders.For different age groups,sensitivity and lag effects varied:the elderly and children were more sensitive to particulate matter concentrations.Therefore,it is recommended that relevant departments,such as hospitals,implement appropriate health interventions for elderly and child populations following episodes of high PM2.5 and PM10 concentrations.