2018年广州市空气污染物对居民日急救人数影响的短期效应  

Short-term effects of ambient air pollutants on daily number of emergency department visits of Guangzhou City in 2018

作　　者：步犁[1] 范淑君 蒋琴琴[1] 吕嘉韵 石同幸[1] 江思力[1] BU Li;FAN Shu-jun;JIANG Qin-qin;LYU Jia-yun;SHI Tong-xing;JIANG Si-li(Environmental Health Division,Guangzhou Center for Disease Control and Prevention,Guangzhou Guangdong,510440,China)

机构地区：[1]广州市疾病预防控制中心环境卫生部,广东广州510440

出　　处：《职业与健康》2021年第3期379-382,387,共5页Occupation and Health

基　　金：广州市卫生健康科技项目(20191A010041)。

摘　　要：目的探讨广州市空气污染物与日急救人次之间的关系,为制定治理大气污染相关政策提供数据支持。方法收集2018年广州市空气污染物SO2、NO2、CO、细颗粒物(PM2.5)、可吸入颗粒(PM10)、O3日最大1 h平均值(O3-1 h)、O3日最大8 h平均值(O3-8 h),结合日均气温、相对湿度和日总急救人数、循环系统日急救人数及呼吸系统日急救人数等数据,采用广义相加模型(GAM)控制长期趋势、星期几效应及气象因素的影响后,分析SO2、NO2、CO、PM2.5、PM10、O3-1 h、O3-8 h日均浓度与日总急救人数、呼吸系统日急救人数和循环系统日急救人数的关系。结果 SO2、NO2、CO、PM2.5、PM10、O3-1 h、O3-8 h的日平均浓度为9.93μg/m3、47.52μg/m3、0.89 mg/m3、35.09μg/m3、52.84μg/m3、128.56μg/m3和99.49μg/m3。日总急救人次与SO2呈正相关,呼吸系统日急救人次与SO2、NO2、CO、PM2.5呈正相关,循环系统日急救人次与SO2呈正相关,差异均有统计学意义(均P<0.05)。时间序列分析结果显示,SO2、NO2、PM2.5和PM10浓度与日总急救人次呈正相关并滞后一定时间,SO2和NO2浓度分别对滞后3天(lag3)和滞后4天(lag4)效果最为显著,PM2.5和PM10浓度均对滞后当天(lag0)效果最为显著。NO2、O3-1 h、O3-8 h、PM2.5和PM10浓度与呼吸系统日急救人次呈正相关,NO2浓度对lag4效果最为显著;O3-1 h和O3-8 h浓度分别对lag3和滞后5天(lag5)效果最为显著;PM2.5和PM10浓度均以滞后1天(lag1)效果最为显著。结论 PM2.5和PM10浓度的升高可能增加居民日总急救人次和呼吸系统日急救人次的风险,SO2和NO2浓度的升高可能增加居民日总急救人次的风险,应采取相关措施降低PM2.5、PM10、SO2和NO2浓度。Objective To evaluate the association between air pollutants and daily number of emergency department visits of Guangzhou City, provide the data support for the formulation of air pollution control policies. Methods The concentrations of sulfur dioxide(SO2), nitrogen dioxide(NO2), carbon monoxide(CO), Fine particulate matter(PM2.5), inhalable particulate matter(PM10), as well as daily maximum 1-hour concentrations of O3(O3-1 h), daily maximum 8-hour concentrations of O3(O3-8 h) in Guangzhou City in 2018 were collected. Combined with the data of daily average temperature, relative humidity, total daily number of emergency department visits, daily number of circulatory system emergency department visits and daily number of respiratory diseases emergency department visits, the generalized additive model(GAM) was used to analyze the association between daily concentrations of SO2, NO2, CO, PM2.5, PM10, O3-1 h, O3-8 h and total daily number of emergency department visits, daily number of circulatory system emergency department visits, daily number of respiratory diseases emergency department visits after adjustment for long-term trend, day of week(DOW) and meteorological factors. Results The average daily concentrations of SO2,NO2, CO, PM2.5, PM10, O3-1 h, O3-8 h was 9.93 μg/m3, 47.52 μg/m3, 0.89 mg/m3, 35.09 μg/m3, 52.84 μg/m3, 128.56 μg/m3 and 99.49 μg/m3, respectively. The total daily number of emergency department visits was positively correlated with the concentration of SO2, the daily number of respiratory diseases emergency department visits was positively correlated with the concentrations of SO2, NO2, CO and PM2.5, the daily number of circulatory system emergency visits was positively correlated with the concentration of SO2, and the differences were statistically significant(all P <0.05). Time series analysis showed that the concentrations of SO2, NO2, PM2.5 and PM10 were positively correlated with the total daily number of emergency department visits,and had lag effect. The concentrations of SO2 and N

关 键 词：大气污染 急救 时间序列 广义相加模型 

分 类 号：R181.34[医药卫生—流行病学]