Determining the threshold effect of ozone on daily mortality: an analysis of ozone and mortality in Seoul, Korea, 1995-1999
Determining the threshold effect of ozone on daily mortality: an analysis of ozone and mortality in Seoul, Korea, 1995-1999
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DOI：
10.1016/j.envres.2003.09.006
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发表时间：
2004-02-01
影响因子：
8.3
通讯作者：
Kim, H
中科院分区：
文献类型：
--
作者：
Kim, SY;Lee, JT;Kim, H
许多研究表明，环境臭氧水平与死亡率之间存在正相关关系。通常情况下，这些研究结果是基于模型，假设木材死亡率和臭氧水平之间的线性关系。在这项研究中，我们适应广义添加剂模型，其中臭氧的影响被假定为发生在三种不同的方式：作为一个简单的线性项，作为一个三次自然样条项，并作为两个线性项的组合（阈值模型）。我们将这些模型应用于1995-1999年韩国首尔的日常时间序列数据，发现阈值模型总是最适合这三个。通过线性泊松回归观察到，与滞后于I天的每日I-h最大臭氧增加21.5 ppb相关的总死亡率的估计相对风险（RR）增加2.6%（95%CI：1.7-3.5）。然而，使用阈值模型观察到估计RR增加3.4%（95% CI：2.3-4.4）。对其他环境污染物的调整对这些结果的影响很小;线性模型为2.4-2.5%，阈值模型为3.2-3.4%。此外，在夏季观察到线性模型和阈值模型估计RR的最大差异：线性模型为1.9%（95% CI：0.5-3.3），阈值模型为3.8%（95% CI：2.0-5.7）。这些结果表明，传统的时间序列泊松回归模型，不考虑阈值，可能会低估臭氧对每日死亡率的影响的真实风险。(C)2003年爱思唯尔公司All rights reserved.
Many studies have shown a positive association between ambient ozone levels and mortality. Typically, these findings are based on models that assume a linear relationship between log mortality and ozone level. In this study, we adapted generalized additive models in which ozone effects are presumed to occur in three different ways: as a simple linear term, as a cubic natural spline term, and as a combination of two linear terms (a threshold model). We applied these models to daily time-series data for Seoul, Korea for the years 1995-1999 and found that the threshold model always fits best among the three. A 2.6% (95% CI: 1.7-3.5) increase of estimated relative risk (RR) in the total mortality associated with a 21.5 ppb increase of daily I-h maximum ozone lagged by I day was observed by linear Poisson's regression. However, a 3.4% (95% CI: 2.3-4.4) increase in the estimated RR was observed using the threshold model. Adjustments for other ambient pollutants caused little changes to these results; 2.4-2.5% in the linear models and 3.2-3.4% in the threshold models. In addition, the largest difference in the estimated RRs of the linear and threshold models was observed in the summer: 1.9% (95% CI: 0.5-3.3) by the linear model and 3.8% (95% CI: 2.0-5.7) by the threshold model. These findings indicate that the conventional time-series Poisson regression model, which dose not take threshold into consideration, could underestimate the true risk of the ozone effect on daily mortality. (C) 2003 Elsevier Inc. All rights reserved.