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大气PM10与心血管疾病就诊人次的时间序列分析
引用本文:王宛怡,王洪源,张志刚,王旗.大气PM10与心血管疾病就诊人次的时间序列分析[J].环境与健康杂志,2009,26(12).
作者姓名:王宛怡  王洪源  张志刚  王旗
作者单位:1. 北京大学公共卫生学院,北京,100191
2. 国家气象中心天气预报室,北京,100081
基金项目:国家科技支撑计划重大项目
摘    要:目的 研究大气PM10污染对居民心血管系统疾病日就诊人次的影响.方法 采用广义相加Poisson回归模型的时间序列分析,在控制长期趋势、星期几效应、气象因素等混杂因素的影响后,对2002年1月1日-2002年12月31日北京市大气PM10日均浓度与居民心血管系统疾病日就诊人次进行定量回归分析,并考虑滞后效应和其他空气污染物的影响.结果 大气PM10浓度每上升10μg/m~3,当天的心血管系统疾病日就诊人次增加O.380%(95%CI:0.326%~0.433%);滞后4 d PM10的健康效应最强,超额危险度为1.166%(95%CI:1.121%~1.212%);考虑CO、NO_2、SO_2:的影响均使PM10的健康效应估计值增高.结论 北京城区大气PM10污染与居民心血管系统疾病日就诊人次之间存在正相关.
Abstract:
Objective To estimate quantitatively the impact of the ambient PM10 on the hospital outpatients for cardiovascular diseases of local residents. Methods Time serial analysis using generalized addictive model (GAM) was applied. After controlling for those confounding factors such as long-term trend, weekly pattern and meteorological factors, considering lag effect and the influence of other air pollutants, excess relative risks (ER) of daily hospital visits associated with increasing PM10 level were estimated by fitting a Poisson regression model. Results A 10 μ.g/m~3 increase in PM10 levels was associated with an ER of 0.380% (95%CI: 0.326%~0.433%) for hospital visits for cardiovascular diseases. Lag effect of 4 days with an ER of 1.166% (95%C/:1.121%~1.212%) were observed. The ER value increased when CO, NO_2, SO_2 concentrations were introduced. Conclusion The ambient PM10 concentration is positively associated with daily hospital visits for cardiovascular diseases in Beijing.

关 键 词:空气污染  可吸入颗粒物  心血管疾病  广义相加模型  时间序列分析  日就诊人次

Association between Ambient PM10 and Daily Hospital Visits: a Time-Series Analysis
Abstract:Objective To estimate quantitatively the impact of the ambient PM10 on the hospital outpatients for cardiovascular diseases of local residents. Methods Time serial analysis using generalized addictive model (GAM) was applied. After controlling for those confounding factors such as long-term trend, weekly pattern and meteorological factors, considering lag effect and the influence of other air pollutants, excess relative risks (ER) of daily hospital visits associated with increasing PM10 level were estimated by fitting a Poisson regression model. Results A 10 μ.g/m~3 increase in PM10 levels was associated with an ER of 0.380% (95%CI: 0.326%~0.433%) for hospital visits for cardiovascular diseases. Lag effect of 4 days with an ER of 1.166% (95%C/:1.121%~1.212%) were observed. The ER value increased when CO, NO_2, SO_2 concentrations were introduced. Conclusion The ambient PM10 concentration is positively associated with daily hospital visits for cardiovascular diseases in Beijing.
Keywords:Air pollution  Inhalable particulates  Cardiovascular diseases  Generalized addictive model  Time series analysis  Daily hospital visit
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