Do socioeconomic characteristics modify the short term association between air pollution and mortality? Evidence from a zonal time series in Hamilton, Canada
Do socioeconomic characteristics modify the short term association between air pollution and mortality? Evidence from a zonal time series in Hamilton, Canada
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DOI：
10.1136/jech.58.1.31
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发表时间：
2004-01-01
影响因子：
6.3
通讯作者：
Hutchison, B
中科院分区：
文献类型：
--
作者：
Jerrett, M;Burnett, RT;Hutchison, B
研究目的：评估工业城市不同区域空气污染与死亡率之间的短期关系。一个城市内的研究设计是用来检验假设，即社会经济特征修改急性健康影响的环境空气污染exposure.Design：城市的汉密尔顿，加拿大，分为五个区域的基础上接近固定站点的空气污染监测器。在每个区域内，每天的非创伤死亡率和空气污染估计数被结合起来。广义线性模型（GLM）被用来测试死亡率与二氧化硫（SO2）和测量的空气污染的烟雾系数（CoH）。主要结果：增加死亡率与空气污染暴露在全市范围内的模型，在城市内的地区，较低的社会经济特征。低教育程度和高制造业就业的地区显着和积极的修改急性死亡率的影响，空气污染exposition.Discussion：三种可能的解释，提出了观察到的影响修改教育和制造业：（1）那些在制造业接受较高的工作场所暴露，结合联合收割机与环境暴露，以产生更大的健康影响;（2）受教育程度较低的人移动的较少，暴露测量误差较少，这减少了对零值的偏差;或（3）制造业和教育代表了许多代表物质匮乏的社会变量，而恶劣的物质条件增加了对空气污染健康风险的敏感性。
Study objective: To assess the short term association between air pollution and mortality in different zones of an industrial city. An intra- urban study design is used to test the hypothesis that socioeconomic characteristics modify the acute health effects of ambient air pollution exposure.Design: The City of Hamilton, Canada, was divided into five zones based on proximity to fixed site air pollution monitors. Within each zone, daily counts of non- trauma mortality and air pollution estimates were combined. Generalised linear models ( GLMs) were used to test mortality associations with sulphur dioxide ( SO2) and with particulate air pollution measured by the coefficient of haze ( CoH).Main results: Increased mortality was associated with air pollution exposure in a citywide model and in intra- urban zones with lower socioeconomic characteristics. Low educational attainment and high manufacturing employment in the zones significantly and positively modified the acute mortality effects of air pollution exposure.Discussion: Three possible explanations are proposed for the observed effect modification by education and manufacturing: ( 1) those in manufacturing receive higher workplace exposures that combine with ambient exposures to produce larger health effects; ( 2) persons with lower education are less mobile and experience less exposure measurement error, which reduces bias toward the null; or ( 3) manufacturing and education proxy for many social variables representing material deprivation, and poor material conditions increase susceptibility to health risks from air pollution.