Lipfert F W, Wyzga R E
Electric Power Research Institute, Palo Alto, California.
J Air Waste Manag Assoc. 1995 Dec;45(12):949-66. doi: 10.1080/10473289.1995.10467427.
Results from 31 epidemiology studies linking air pollution with premature mortality are compared and synthesized. Consistent positive associations between mortality and various measures of air pollution have been shown within each of two fundamentally different types of regression studies and in many variations within these basic types; this is extremely unlikely to have occurred by chance. In this paper, the measure of risk used is the elasticity, which is a dimensionless regression coefficient defined as the percentage change in the dependent variable associated with a 1% change in an independent variable, evaluated at the means. This metric has the advantage of independence from measurement units and averaging times, and is thus suitable for comparisons within and between studies involving different pollutants. Two basic types of studies are considered: time-series studies involving daily perturbations, and cross-sectional studies involving longer-term spatial gradients. The latter include prospective studies of differences in individual survival rates in different locations and studies of the differences in annual mortality rates for various communities. For a given data set, time-series regression results will vary according to the seasonal adjustment method used, the covariates included, and the lag structure assumed. The results from both types of cross-sectional regressions are highly dependent on the methods used to control for socioeconomic and personal lifestyle factors and on data quality. A major issue for all of these studies is that of partitioning the response among collinear pollution and weather variables. Previous studies showed that the variable with the least exposure measurement error may be favored in multiple regressions; assigning precise numerical results to a single pollutant is not possible under these circumstances. We found that the mean overall elasticity as obtained from time-series studies for mortality with respect to various air pollutants entered jointly was about 0.048, with a range from 0.01 to 0.12. This implies that about 5% of daily mortality is associated with air pollution, on average. The corresponding values from population-based cross-sectional studies were similar in magnitude, but the results from the three recent prospective studies varied from zero to about five times as much. Long-term responses in excess of short-term responses might be interpreted as showing the existence of chronic effects, but the uncertainties inherent in both types of studies make such an interpretation problematic.
对31项将空气污染与过早死亡联系起来的流行病学研究结果进行了比较和综合分析。在两种根本不同类型的回归研究中的每一种以及这些基本类型中的许多变体中，都显示出死亡率与各种空气污染指标之间存在一致的正相关关系；这种情况极不可能是偶然发生的。在本文中，所使用的风险度量是弹性，它是一个无量纲的回归系数，定义为因变量的百分比变化与自变量1%变化相关联，在均值处进行评估。这个指标具有不受测量单位和平均时间影响的优点，因此适合在涉及不同污染物的研究内部和之间进行比较。考虑了两种基本类型的研究：涉及每日扰动的时间序列研究和涉及长期空间梯度的横断面研究。后者包括对不同地点个体生存率差异的前瞻性研究以及对不同社区年死亡率差异的研究。对于给定的数据集，时间序列回归结果会因所使用的季节性调整方法、所包含的协变量以及所假设的滞后结构而有所不同。两种横断面回归的结果都高度依赖于用于控制社会经济和个人生活方式因素的方法以及数据质量。所有这些研究的一个主要问题是在共线的污染和天气变量之间划分响应。先前的研究表明，在多元回归中，暴露测量误差最小的变量可能更受青睐；在这种情况下，不可能将精确的数值结果归因于单一污染物。我们发现，从时间序列研究中得出的关于死亡率相对于共同纳入的各种空气污染物的平均总体弹性约为0.048，范围从0.01到0.12。这意味着平均而言，约5%的每日死亡率与空气污染有关。基于人群的横断面研究的相应值在数量上相似，但最近三项前瞻性研究的结果从零到大约五倍不等。长期反应超过短期反应可能被解释为表明存在慢性影响，但这两种研究中固有的不确定性使得这种解释存在问题。
