Huang Wei, Tan Jianguo, Kan Haidong, Zhao Ni, Song Weimin, Song Guixiang, Chen Guohai, Jiang Lili, Jiang Cheng, Chen Renjie, Chen Bingheng
Center for Environment and Health, State Key Joint Laboratory of Environmental Simulation and Pollution Control, Peking University, Beijing, China.
Sci Total Environ. 2009 May 1;407(10):3295-300. doi: 10.1016/j.scitotenv.2009.02.019. Epub 2009 Mar 9.
This study was designed to assess the association between visibility and air quality, and to determine whether the variations in daily mortality were associated with fluctuations in visibility levels in Shanghai, China. Mortality data were extracted from the death certificates, provided by Shanghai Municipal Center of Disease Control and Prevention, and visibility data were obtained from Shanghai Municipal Bureau of Meteorology. Air quality data (PM(10), PM(2.5), PM(10-2.5), SO(2), NO(2) and O(3)) were obtained from Shanghai Environmental Monitoring Center. Generalized additive model (GAM) with penalized splines was used to analyze the mortality, visibility, air pollution, and covariate data. Among various pollutants, PM(2.5) showed strongest correlation with visibility. Visibility, together with humidity, was found appropriate in predicting PM(2.5) (R-squared: 0.64) and PM(10) (R-squared: 0.62). Decreased visibility was significantly associated with elevated death rates from all causes and from cardiovascular disease in Shanghai; one inter-quartile range (8 km) decrease in visibility corresponded to 2.17% (95%CI: 0.46%, 3.85%), 3.36% (95%CI: 0.96%, 5.70%), and 3.02% (95%CI: -1.32%, 7.17%) increase of total, cardiovascular and respiratory mortality, respectively. The effect estimates using predicted PM(2.5) and PM(10) concentrations were similar to those assessed using actual concentrations. This is the first study in Mainland China assessing the association between visibility and adverse health outcomes. Our findings suggest the possibility of using visibility as a surrogate of air quality in health research in developing countries where air pollution data might be scarce and not routinely monitored.
本研究旨在评估能见度与空气质量之间的关联,并确定中国上海每日死亡率的变化是否与能见度水平的波动相关。死亡率数据取自上海市疾病预防控制中心提供的死亡证明,能见度数据则来自上海市气象局。空气质量数据(PM(10)、PM(2.5)、PM(10 - 2.5)、SO(2)、NO(2)和O(3))来自上海市环境监测中心。采用带惩罚样条的广义相加模型(GAM)分析死亡率、能见度、空气污染及协变量数据。在各种污染物中,PM(2.5)与能见度的相关性最强。研究发现,能见度与湿度一起,在预测PM(2.5)(决定系数:0.64)和PM(10)(决定系数:0.62)方面较为合适。能见度降低与上海所有原因及心血管疾病死亡率升高显著相关;能见度每降低一个四分位数间距(8公里),总死亡率、心血管疾病死亡率和呼吸系统疾病死亡率分别升高2.17%(95%置信区间:0.46%,3.85%)、3.36%(95%置信区间:0.96%,5.70%)和3.02%(95%置信区间:-1.32%,7.17%)。使用预测的PM(2.5)和PM(10)浓度得出的效应估计值与使用实际浓度评估的结果相似。这是中国大陆第一项评估能见度与不良健康结局之间关联的研究。我们的研究结果表明,在空气污染数据可能稀缺且未进行常规监测的发展中国家,在健康研究中使用能见度作为空气质量替代指标具有可能性。