Short-Term Effects of Air Pollution on Mortality in the Cities of Rouen and Le Havre, France, 1990–1995

A. Zeghnoun, P. Czernichow, P. Beaudeau, A. Hautemanière, L. Froment, A. Tertre, P. Quénel
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引用次数: 25

Abstract

Abstract In this study, the authors examined the short-term effects of ambient air pollution on mortality across 2 French cities: Rouen and Le Havre. In Poisson regression models, which controlled for day-of-week effects, the authors used nonparametric smoothing to control for temporal trend, weather, and influenza epidemics. In Rouen, an interquartile range increase of 60.5–94.1 μg/m3 of ozone was associated with an increase of 4.1 % (95% confidence interval = 0.6, 7.8) of total mortality. Daily variations in sulfur dioxide (interquartile range increase = 17.6–36.4 μg/m3) were also associated with an 8.2% increase (95% confidence interval = 0.4, 16.6) in respiratory mortality. An increase of 6.1% (95% confidence interval = 1.5, 10.9) of cardiovascular mortality was also observed with an interquartile range increase of nitrogen dioxide (i.e., 25.3–42.2 μg/m3). With respect to Le Havre, an interquartile range increase in daily levels of sulfur dioxide (11.3–35.6 μg/m3) was associated with an increase of approximately 3% (95% confidence interval = 0.8, 5) of cardiovascular mortality. For particulate matter less than or equal to 13 urn in diameter (interquartile increase = 21.5, 45.4 μg/m3), an increase of 6.2% (95% confidence interval = 0.1,12.8) was observed. The estimates of pollutant effects and their standard deviations were slightly affected by the degree of smoothing temporal variations in this study. When low collinearity was present, the 2-pollutant models provided acceptable estimates of pollutant effects. They suggested that the ozone effect was independent of the Black Smoke effect, and that the effects of sulfur dioxide and nitrogen dioxide were unlikely to be confounded by ozone concentrations. However, high collinearity leads to large estimates of the pollutant coefficient variances and, therefore, leads to inaccurate estimates of pollutant effects. The analysis of the contributory effects of different pollutant mixtures requires further investigation in those instances in which high collinearity between pollutants is present.
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1990-1995年法国鲁昂和勒阿弗尔市空气污染对死亡率的短期影响
在这项研究中,作者调查了法国鲁昂和勒阿弗尔两个城市环境空气污染对死亡率的短期影响。在泊松回归模型中,作者使用非参数平滑来控制时间趋势、天气和流感流行。在鲁昂,臭氧浓度每增加60.5-94.1 μg/m3,总死亡率就会增加4.1%(95%可信区间= 0.6,7.8)。二氧化硫的日变化(四分位数范围增加= 17.6-36.4 μg/m3)也与呼吸系统死亡率增加8.2%(95%可信区间= 0.4,16.6)相关。随着二氧化氮浓度(25.3-42.2 μg/m3)的四分位数范围增加,心血管死亡率也增加了6.1%(95%可信区间= 1.5,10.9)。就勒阿弗尔而言,每日二氧化硫水平的四分位数范围(11.3-35.6 μg/m3)增加与心血管死亡率增加约3%(95%置信区间= 0.8,5)相关。对于直径小于或等于13缸的颗粒物(四分位数增幅分别为21.5、45.4 μg/m3),增幅为6.2%(95%可信区间分别为0.1、12.8)。在本研究中,污染物效应的估计及其标准差受到平滑时间变化程度的轻微影响。当存在低共线性时,两种污染物模型提供了可接受的污染物影响估计。他们认为,臭氧效应独立于黑烟效应,二氧化硫和二氧化氮的影响不太可能与臭氧浓度相混淆。然而,高共线性导致对污染物系数方差的估计较大,因此导致对污染物影响的估计不准确。在污染物之间存在高度共线性的情况下,对不同污染物混合物的促成效应的分析需要进一步调查。
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