Time‐series analyses and cohort studies to investigate relationships between particulate matter and mortality—two approaches to one endpoint

N. Englert
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引用次数: 6

Abstract

Time‐series analyses and cohort studies provide different methods of looking at the health effects of air pollution. With respect to mortality, the relative risk associated with a defined increase in the concentration of particulate matter is numerically much higher if derived from cohort studies than if based on time‐series analyses. This discrepancy is often explained by arguing that chronic effects of air pollutants can only be assessed in cohort studies. However, with respect to changes in life expectancy, the results of the two study types can be shown to be consistent. In calculations of pollution‐related health costs, mortality plays a dominant role. Applying the relative risk derived from cohort studies directly as a multiplier on daily or annual mortality leads to a considerable overestimation of effects. Copyright © 1999 John Wiley & Sons, Ltd.
时间序列分析和队列研究探讨颗粒物质与死亡率之间的关系-两种方法的一个终点
时间序列分析和队列研究提供了观察空气污染对健康影响的不同方法。就死亡率而言,从队列研究得出的与确定的颗粒物浓度增加相关的相对风险在数值上要比基于时间序列分析得出的高得多。这种差异的解释往往是,空气污染物的慢性影响只能在队列研究中进行评估。然而,就预期寿命的变化而言,两种研究类型的结果是一致的。在污染相关健康成本的计算中,死亡率起着主导作用。直接将从队列研究中得出的相对风险作为每日或每年死亡率的乘数,会导致对效果的严重高估。版权所有©1999 John Wiley & Sons, Ltd
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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