摘要
目的探讨淄博市大气污染物[SO_2、NO_2、细颗粒物(PM_(2.5))]浓度对急救人次的影响。方法收集2016年1月1日至2017年12月31日淄博市的急救医疗数据,按照WHO国际疾病分类(ICD-10)统计每日因非意外总急救及呼吸系统疾病急救的人次,结合同期逐日空气污染数据和气象数据,利用广义相加模型(GAM)控制长期趋势、季节趋势、星期几效应及气象因素的影响后,分析SO_2、NO_2、PM_(2.5)日均浓度与非意外、呼吸系统疾病急救人次的关系。结果淄博市2016年至2017年SO_2日均浓度52. 6μg/m^3,NO_2日平均浓度57. 0μg/m^3,PM_(2.5)日平均浓度70. 4μg/m^3。2016年至2017年日平均急救366. 78人次,其中日均非意外急救63. 98人次,日均呼吸系统急救8. 04人次。相关性分析表明,日均非意外急救及呼吸系统急救人次均与PM_(2.5)、SO_2、NO_2、CO浓度呈正相关。时间序列分析单污染物模型显示,SO_2和NO_2浓度均对非意外急救人次的影响存在滞后效应,滞后1 d健康效应最强,其中SO_2浓度每增加10μg/m^3,非意外急救人次增加0. 423%(95%CI:0. 253%~0. 601%),NO_2浓度每增加10μg/m^3,非意外急救人次增加0. 412%(95%CI:0. 218%~0. 621%); PM_(2.5)浓度均对呼吸系统疾病急救人次的影响存在滞后效应,滞后3 d健康效应最强,其中PM_(2.5)浓度每增加10μg/m^3,呼吸系统疾病急救人次增加0.314%(95%CI:0. 178%~0. 533%)。双污染物模型中,在分别引入PM_(2.5)和O3后,SO_2浓度每升高10μg/m^3,非意外总急救人次的超额危险度(ER)分别为0. 286%(95%CI:0. 061%~0. 519%)、0. 389%(95%CI:0. 229%~0.671%),NO_2浓度每升高10μg/m^3,非意外总急救人次的ER分别为0. 176%(95%CI:0. 117%~0. 561%)、0.427%(95%CI:0. 287%~0. 663%)。双污染物模型中,分别引入SO_2和NO_2后,PM_(2.5)浓度每升高10μg/m^3,呼吸系统疾病急救人次的ER分别为0. 219%(95%CI:0. 128%~0. 456%)、0. 193%(95%CI:0. 101%~0. 429%)。结论大气中SO_2或NO_2浓度的升高可能增加居民�
Objective To explore the association between SO2,NO2,fine particulate matter（ PM2.5） pollution and daily emergency room visits in Zibo City. Methods The data of emergency room visits during 2016 and 2017 were collected. The number of non-accidental emergencies and respiratory diseases emergencies were statistically analyzed according to the WHO International Classification of Diseases（ ICD-10）. After the confounding factors including timetrends,seasonal trends,day of week（ DOW） and meteorological factors were controlled,the excess risk（ ER） of daily emergency room visits associated with increased SO2,NO2,PM2.5 levels were analyzed with generalized addictive model（ GAM） with Poisson regression. Results During 2016 and 2017,the average daily concentrations of SO2,NO2 and PM2.5 were 52. 6 μg/m3,57. 0 μg/m3 and 70. 4 μg/m3,respectively. The daily emergency room visits was 366.78,of which 63. 98 and 8. 04 were due to non-accidents and respiratory diseases. The correlation analysis showed that the number of daily emergency room visits was positively correlated with the concentrations of PM2.5,SO2,NO2 and CO. In the single-pollutant model,the SO2 and NO2 concentrations had lag effect on the number of non-accidental emergency visits,and lag1 factor had the most significant impact： a 10 μg/m3 increase of SO2 concentration was associated with a 0. 423% ER（ 95% CI： 0. 253%-0. 601%）,and a 10 μg/m3 increase of NO2 was associated with 0. 412%ER（ 95% CI： 0. 218%-0. 621%）. The PM2.5 concentration had lag effect on the number of respiratory diseases emergency visits,and lag3 factor had the most significant impact： a 10 μg/m3 increase of PM2.5 concentration was associated with a 0. 314% ER（ 95% CI： 0. 178%-0. 533%）. The dual-pollutant model indicated that for every 10 μg/m3 rise in SO2 concentration,the ER of non-accidental emergency visits was 0. 286%（ 95% CI： 0. 061%-0. 519%） and 0. 389%（ 95% CI： 0. 229%-0. 671%） when PM2.5 and O3 were introduced separately; and for ev
作者
刘晓利
刘芳盈
孟超
李平
张殿平
殷茂荣
翟慎永
LIU Xiaoli;LIU Fangying;MENG Chao;LI Ping;ZHANG Dianping;YIN Maorong;ZHAI Shenyong(Zibo Center for Disease Control and Prevention,Zibo 255026,Shandong,China)
出处
《山东大学学报（医学版）》
CAS
北大核心
2018年第11期42-47,共6页
Journal of Shandong University:Health Sciences
基金
山东省医药卫生科技发展计划(2014WS0231)
淄博市科技发展计划(2017kj010092)
关键词
SO2
NO2
细颗粒物
急救
时间序列分析
SO2
NO2
fine particulate matter
Emergency visit
Time-series analysis
