研究颗粒物与死亡率之间关系的时间序列分析和队列研究——一个终点的两种方法

Norbert Englert
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引用次数: 6

摘要

时间序列分析和队列研究提供了不同的方法来观察空气污染对健康的影响。关于死亡率,如果从队列研究中得出,则与颗粒物浓度增加相关的相对风险在数字上要比基于时间序列分析的风险高得多。这种差异的解释通常是认为空气污染物的长期影响只能在队列研究中进行评估。然而,关于预期寿命的变化,这两种研究类型的结果可以证明是一致的。在计算与污染相关的健康成本时,死亡率起着主导作用。将来自队列研究的相对风险直接用作每日或年度死亡率的乘数,会导致对影响的高估。版权所有©1999 John Wiley&;有限公司。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time-series analyses and cohort studies to investigate relationships between particulate matter and mortality—two approaches to one endpoint

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.

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