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2013—2018年北京市大气PM2.5持续高暴露对居民因病入院的急性影响
引用本文:陈晨,仲宇,刘园园,路凤,郭默宁,方建龙,李湉湉,施小明.2013—2018年北京市大气PM2.5持续高暴露对居民因病入院的急性影响[J].环境科学研究,2021,34(1):213-219.
作者姓名:陈晨  仲宇  刘园园  路凤  郭默宁  方建龙  李湉湉  施小明
作者单位:1.中国疾病预防控制中心环境与人群健康重点实验室, 中国疾病预防控制中心环境与健康相关产品安全所, 北京 100021
基金项目:大气重污染成因与治理攻关项目(No.DQGG0401)
摘    要:为探讨以细颗粒物(PM2.5)持续高浓度暴露为特征的大气污染事件对于人群因病入院的急性影响,收集2013—2018年北京市大气PM2.5浓度、气象因素数据和人群因病入院数据,以PM2.5浓度〔75.0 μg/m3、150.0 μg/m3、第95百分位数(205.8 μg/m3)〕和持续时间(≥2 d、≥3 d)联合定义6种持续高暴露情景,采用基于quasi-Poisson回归的广义相加模型开展时间序列分析,获得不同情景下PM2.5对人群因病入院的急性影响.结果表明:①对于全人群研究发现,相较于非持续高暴露情景,持续2 d及以上的重污染(PM2.5浓度>150.0 μg/m3)情景引起非意外总疾病和心脑血管系统疾病的发病风险均显著增加,增幅分别为5.0%(95% CI,1.2%~9.0%)和5.6%(95% CI,1.8%~9.5%).②亚组人群分层分析发现,持续2 d及以上的重污染情景下,男性、女性、0~64岁、65~74岁、75岁及以上等亚组人群的非意外总疾病和心脑血管系统疾病的发病风险均显著增加;当出现极端PM2.5暴露浓度(>205.8 μg/m3)且持续3 d以及上时,女性和0~64岁、65~74岁人群的非意外总疾病和心脑血管系统疾病的发病风险均显著增加.③因呼吸系统疾病入院分析发现,仅在PM2.5浓度>150 μg/m3且持续时间≥2 d的情景下,观察到0~64岁人群的发病风险显著增加,增幅为3.4%(95% CI,0.2%~6.6%).研究显示,以PM2.5持续高暴露为特征的大气污染事件对人群因病入院有显著影响. 

关 键 词:细颗粒物(PM2.5)    重污染    因病入院    时间序列研究
收稿时间:2020/8/28 0:00:00
修稿时间:2020/11/9 0:00:00

Impact of Persistent High Ambient Fine Particulate Matters Exposures on Hospitalization in Beijing from 2013 to 2018
CHEN Chen,ZHONG Yu,LIU Yuanyuan,LU Feng,GUO Moning,FANG Jianlong,LI Tiantian,SHI Xiaoming.Impact of Persistent High Ambient Fine Particulate Matters Exposures on Hospitalization in Beijing from 2013 to 2018[J].Research of Environmental Sciences,2021,34(1):213-219.
Authors:CHEN Chen  ZHONG Yu  LIU Yuanyuan  LU Feng  GUO Moning  FANG Jianlong  LI Tiantian  SHI Xiaoming
Institution:1.China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China2.Beijing Municipal Health Commission Policy Research Center, Beijing 100021, China
Abstract:In order to investigate the impact of air pollution episode characterized by persistent high PM2.5 exposure on people's hospitalization in Beijing, we collected data of air pollutants, meteorological factors and hospital admissions in Beijing from 2013 to 2018. Under six persistent PM2.5-polluted scenarios defined by PM2.5 concentration (75.0 μg/m3, 150.0 μg/m3, P95 (205.8 μg/m3)) and duration (≥2 d, ≥3 d), generalized additive models (GAM) based on quasi-Poisson regression were used to carry out time series analyses to obtain the impact of air pollution episode characterized by persistent high exposure to PM2.5 on hospitalizations of the entire population and subgroups. The results showed that: (1) For the entire population, relative to non-specified pollution scenarios, when the PM2.5 exposure concentration was >150 μg/m3 and lasted for two days or more, the hospitalization risk for non-accidental diseases and cardio-cerebrovascular diseases increased by 5.0% (95%CI, 1.2% to 9.0%) and 5.6% (95%CI, 1.8% to 9.5%), respectively. (2) A stratified analysis of subgroup populations found that under heavy PM2.5-pollution scenarios that lasted for two days or more, non-accidental and cardio-cerebrovascular hospitalizations significantly increased in the subgroups of men, women, people 0-64 years old, people 65-74 years old, and people 75 years or older. In the extreme PM2.5-pollution concentration (>205.8 μg/m3) that lasted for three days or more, non-accidental and cardio-cerebrovascular hospitalizations significantly increased in only the subgroups of women, people 0-64 years old and people 65-74 years old. (3) For respiratory admissions, we only detected statistical significance when PM2.5 exposure concentration was greater than 150.0 μg/m3 and lasted for two days or more in the 0-64 years old population, and the risk increased by 3.4% (95%CI, 0.2% to 6.6%). This study shows that air pollution episode characterized by persistent high exposure to PM2.5 had a significant impact on hospital admissions. 
Keywords:fine particulate matter (PM2  5)  pollution episode  hospitalization  time series
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