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第一部分. 中国上海环境空气污染与每日死亡率的时间序列研究。

Part 1. A time-series study of ambient air pollution and daily mortality in Shanghai, China.

作者信息

Kan Haidong, Chen Bingheng, Zhao Naiqing, London Stephanie J, Song Guixiang, Chen Guohai, Zhang Yunhui, Jiang Lili

机构信息

Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China.

出版信息

Res Rep Health Eff Inst. 2010 Nov(154):17-78.

Abstract

Although the relation between outdoor air pollution and daily mortality has been examined in several Chinese cities, there are still a number of key scientific issues to be addressed concerning the health effects of air pollution in China. Given the changes over the past decade in concentrations and sources of air pollution (e.g., the change from one predominant source [coal combustion], which was typical of the twentieth century, to a mix of sources [coal combustion and motor-vehicle emissions]) and transition in China, it is worthwhile to investigate the acute effects of outdoor air pollution on mortality outcomes in the country. We conducted a time-series study to investigate the relation between outdoor air pollution and daily mortality in Shanghai using four years of daily data (2001-2004). This study is a part of the Public Health and Air Pollution in Asia (PAPA) program supported by the Health Effects Institute (HEI). We collected data on daily mortality, air pollution, and weather from the Shanghai Municipal Center of Disease Control and Prevention (SMCDCP), Shanghai Environmental Monitoring Center, and Shanghai Meteorologic Bureau. An independent auditing team assigned by HEI validated all the data. Our statistical analysis followed the Common Protocol of the PAPA program (found at the end of this volume). Briefly, a natural-spline model was used to analyze the mortality, air pollution, and covariate data. We first constructed the basic models for various mortality outcomes excluding variables for air pollution, and used the partial autocorrelation function of the residuals to guide the selection of degrees of freedom for time trend and lag days for the autoregression terms. Thereafter, we introduced the pollutant variables and analyzed their effects on mortality outcomes, including both mortality due to all natural (nonaccidental) causes and cause-specific mortality. We fitted single- and multipollutant models to assess the stability of the effects of the pollutants. For mortality due to all natural causes, we also examined the associations stratified by sex and age. Stratified analyses by education level, used as a measure of socioeconomic status, were conducted as well. In addition to an analysis of the entire study period, the effects of air pollution in just the warm season (from April to September) and cool season (from October to March) were analyzed. We also examined the effects of alternative model specifications--such as lag effects of pollutants and temperature, degrees of freedom for time trend and weather conditions, statistical approaches, and averaging methods for pollutant concentrations-on the estimated effects of air pollution. We found significant associations between the air pollutants--particulate matter 10 pm or less in aerodynamic diameter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) -and daily mortality from all natural causes and from cardiopulmonary diseases. The increased mortality risks found in the data from Shanghai were generally similar in magnitude, per concentration of pollutant, to the risks found in research from other parts of the world. An increase of 10 microg/m3 in 2-day moving average concentrations of PM10, SO2, NO2, and O3 corresponded to 0.26% (95% confidence interval [CI], 0.14-0.37), 0.95% (95% CI, 0.62-1.28), 0.97% (95% CI, 0.66-1.27), and 0.31% (95% CI, 0.04-0.58) increases, respectively, in mortality due to all natural causes. Sensitivity analyses suggested that our findings were generally insensitive to alternative model specifications. We found significant effects of the gaseous pollutants SO2 and NO2 on daily mortality after adjustment for PM10. Our analysis also provided preliminary, but not conclusive, evidence that women, older people, and people with a low level of education might be more vulnerable to air pollution than men, younger people, and people with a high level of education. In addition, the associations between air pollution and daily mortality appeared to be more pronounced in the cool season than in the warm. We concluded that short-term exposure to outdoor air pollution (PM10, SO2, NO2, and O3) was associated with daily mortality in Shanghai and that gaseous pollutants might have independent health effects in the city. Overall, the results of the study appeared largely consistent with those reported in other locations worldwide. Further research will be needed to disentangle the effects of the various pollutants and to gain more conclusive insights into the influence of various sociodemographic characteristics (e.g., sex, age, and socioeconomic status) and of season on the associations between air pollution and daily mortality.

摘要

尽管中国的多个城市已对室外空气污染与每日死亡率之间的关系进行了研究,但在中国,空气污染对健康的影响仍存在一些关键科学问题有待解决。鉴于过去十年间空气污染浓度及其来源发生了变化(例如,从20世纪典型的单一主要来源[煤炭燃烧]转变为多种来源[煤炭燃烧和机动车排放]的混合)以及中国的转型情况,研究室外空气污染对该国死亡率的急性影响很有必要。我们开展了一项时间序列研究,利用四年的每日数据(2001 - 2004年)调查上海室外空气污染与每日死亡率之间的关系。本研究是由健康影响研究所(HEI)支持的亚洲公共卫生与空气污染(PAPA)项目的一部分。我们从上海市疾病预防控制中心(SMCDCP)、上海环境监测中心和上海市气象局收集了每日死亡率、空气污染和天气数据。HEI指派的一个独立审核团队对所有数据进行了验证。我们的统计分析遵循PAPA项目的通用方案(见本书末尾)。简而言之,使用自然样条模型分析死亡率、空气污染和协变量数据。我们首先构建了各种死亡率结果的基本模型,排除空气污染变量,并利用残差的偏自相关函数来指导时间趋势自由度和自回归项滞后天数的选择。此后,我们引入污染物变量并分析它们对死亡率结果的影响,包括所有自然(非意外)原因导致的死亡率以及特定病因死亡率。我们拟合了单污染物和多污染物模型以评估污染物影响的稳定性。对于所有自然原因导致的死亡率,我们还按性别和年龄进行了分层分析。此外,还按教育水平进行了分层分析,将教育水平用作社会经济地位的衡量指标。除了对整个研究期进行分析外,还分析了仅在暖季(4月至9月)和冷季(10月至3月)空气污染的影响。我们还研究了替代模型规格(如污染物和温度的滞后效应、时间趋势自由度和天气条件、统计方法以及污染物浓度的平均方法)对空气污染估计影响的作用。我们发现空气污染物——空气动力学直径小于或等于10微米的颗粒物(PM10)、二氧化硫(SO₂)、二氧化氮(NO₂)和臭氧(O₃)——与所有自然原因以及心肺疾病导致的每日死亡率之间存在显著关联。上海数据中发现的死亡率风险增加幅度,按每单位污染物浓度计算,总体上与世界其他地区研究中发现的风险相似。PM10、SO₂、NO₂和O₃的2天移动平均浓度每增加10微克/立方米,分别对应所有自然原因导致的死亡率增加0.26%(95%置信区间[CI],0.14 - 0.37)、0.95%(95%CI,0.62 - 1.28)、0.97%(95%CI,0.66 - 1.27)和0.31%(95%CI,0.04 - 0.58)。敏感性分析表明,我们的研究结果总体上对替代模型规格不敏感。我们发现,在对PM10进行调整后,气态污染物SO₂和NO₂对每日死亡率有显著影响。我们的分析还提供了初步但非结论性的证据,表明女性、老年人和低教育水平人群可能比男性、年轻人和高教育水平人群更容易受到空气污染的影响。此外,空气污染与每日死亡率之间的关联在冷季似乎比暖季更明显。我们得出结论,短期暴露于室外空气污染(PM10、SO₂、NO₂和O₃)与上海的每日死亡率相关,并且气态污染物在该市可能具有独立的健康影响。总体而言,该研究结果在很大程度上与世界其他地区报告的结果一致。需要进一步研究以厘清各种污染物的影响,并更确凿地了解各种社会人口学特征(如性别、年龄和社会经济地位)以及季节对空气污染与每日死亡率之间关联的影响。

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