| BackgroundWith the development of global industrialization,the situation of air pollution has become increasingly serious,and extreme weather events have occurred frequently in recent years.Environmental issues are receiving increasing attention.As a developing country,China has not been able to strike a balance between economic development and environmental protection in the current development stage.A large number of previous epidemiological studies have found that air pollutants and extreme temperatures associated with the mortality and morbidity of cardiovascular disease,but the results were still very different in diverse regions and populations.In addition,most of the researches were carried out in developed countries.There are few related studies in China,most of which are about cardiovascular mortality rather than morbidity.Moreover,even the few incidence studies have many problems,for example,short study period,insufficient number of cardiovascular events,no screening of residential address information,insufficient exposure indicators.Beijing has four distinct seasons and serious condition of air pollution.The unique environmental and socioeconomic characteristics make it more meaningful to conduct research here.In addition,Beijing has a disease reporting system,which provides the data foundation of acute myocardial infarction(AMI)hospitalizations for this study.ObjectiveThis study aimed to evaluated effects of particulate matter less than 2.5?m in aerodynamic diameter(PM2.5),particulate matter less than 10?m in aerodynamic diameter(PM10),sulfur dioxide(SO2),nitrogen dioxide(NO2),carbon monoxide(CO),ozone(O3)and temperature on AMI hospital admissions during 2013-2016 in Beijing.The details are as follows:(1)To assess the relationship between short-term air pollution exposure and admission to AMI,explore possible susceptible populations and establish exposure-response relationship consistenting with the characteristics of pollution exposure in China.(2)To evaluate the exposure-response relationship between different temperature indicators and the risk of AMI hospital admissions in different populations.(4)To assess the impact of extreme temperatures on AMI hospital admissions and explore possible susceptible populations.MethodsTime-serise method was adopted.AMI hospitalization data from January 1,2013 to December 31,2016 derived from the public health information center of Beijing,which collected hospitalization data from all level II and III hospitals in Beijing.Then permanent residents in Beijing were selected according to their address,and the daily number of AMI inpatients was calculated according to admission date.Daily air pollutant data(PM2.5,PM10,SO2,NO2,CO and O3)of 12 national controlled air quality monitoring stations,air quality index(AQI),relative humidity(RH),air pressure(AP)and wind speed(WS)in Beijing during the same period were also collected.A generalized additive model(GAM)was used to evaluate the effects of six kinds of pollutants on AMI hospitalizations,and stratified analysis by gender and age were carried out.In addition,the colinearity of 6 pollutants was treated by principal component analysis,and the exposure-response relationship curve between pollutants and AMI hospitalization risk was fitted.Moreover,the assessment of population attributable risk(PAR)was also included in the study to provide a better insight into how many AMI hospital admissions are attributable to excess pollutant levels.Regarding the relationship between temperature and AMI hospital admissions,a distributed lag nonlinear model(DLNM)was adopted.The temperature was divided into 6 indicators,including daily mean temperature(Tmean),daily minimum temperature(Tmin),daily maximum temperature(Tmax),daily mean apparent temperature(ATmean),daily minimum apparent temperature(ATmin),and daily maximum apparent temperature(ATmax).The impact of each indicator on AMI hospital admissions under different lag time was estimated.Furthermore,the effects of each indicator in extremely cold interval(1st vs 10th),moderate cold interval(10th vs 25th),extremely hot interval(99th vs 90th)and moderate hot interval(90th vs 75th)were also compared.ResultsAir pollution and AMI hospital admissions:for an interquartile range(IQR)increase of PM2.5,PM10,SO2,NO2 and CO concentrations,the percentage increase in AMI hospital admissions were 2.33%(95CI%:1.55%,3.88%),2.67%(95CI%:1.78%,3.56%),2.09%(95CI%:1.04%,2.78%),2.55%(95CI%:1.42%,3.97%)and 1.50%(95CI%:0.51%,2.49%)respectively in single air pollution model.The elderly was vulnerable.In addition,after adjusting the colinearity of pollutants by principal component analysis,the effects decreased slightly,but still had statistical significance.Exposure-response relationship curves were almost linear without any thresholds.No effect was found in O3.Using WHO air quality guidelines(PM2.5:25?g/m3,PM10:50?g/m3)as reference concentration,about 1.63%and 1.69%AMI hospital admissions were attributable to PM2.5 and PM10 respectively.Temperature and AMI hospital admissions:The exposure-response relationship between temperature and the risk of AMI hospital admissions is a "J"type curve(the risk is increased only at low temperatures).Compared with 10th percentile temperature,the cumulative relative risks(CRR)at 1st percentile of Tmean,Tmin and ATmin for AMI hospital admissions were 1.15(95%CI:1.02,1.30),1.24(95%CI:1.11,1.38)and 1.41(95%CI;1.18,1.68),respectively.Moderate low temperature(10th vs 25th)also had adverse impact on AMI events,while the effects were smaller than extremely low temperature(1st vs 10th).Moreover,the effects of extremely low temperature(1st vs 10th)measured by ATmin were greater than that measured by Tmin and Tmean.The lag effects of low temperature on AMI could last at least 3 weeks.The susceptive groups were males and people 65 years and older.No associations were found between high temperature and AMI risk.ConclusionThe findings of this study suggested,PM2.5,PM10,SO2,NO2,CO and low temperature were significantly associated with AMI hospital admissions in Beijing.In addition,the exposure-response relationship curves between air pollution and the risk of AMI hospital admissions were almost linear without any thresholds.The elderly was more sensitive to air pollutants,while males and the elderly were more sensitive to low temperatures.Compared with measured temperature,apparent temperature should deserve more attention.No statistically significant correlations were found between O3,high temperature and AMI hospital admissions. |
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