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The fraction of lung cancer incidence attributable to fine particulate air pollution in France: Impact of spatial resolution of air pollution models

机译:法国可归因于微粒空气污染的肺癌发病率:空气污染模型的空间分辨率的影响

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Outdoor air pollution is a leading environmental cause of death and cancer incidence in humans. We aimed to estimate the fraction of lung cancer incidence attributable to fine particulate matter (PM2.5) exposure in France, and secondarily to illustrate the influence of the input data and the spatial resolution of information on air pollution levels on this estimate. The population attributable fraction (PAF) was estimated using a nationwide spatially refined chemistry-transport model with a 2-km spatial resolution, neighbourhood-scale population density data, and a relative risk from a published meta-analysis. We used the WHO guideline value for PM2.5 exposure (10 mu g/m(3)) as reference. Sensitivity analyses consisted in attributing the nation-wide median exposure to all areas and using alternative input data such as reference of PM2.5 exposure level and relative risk. Population-weighted median PM2.(5) level in 2005 was 13.8 mu g/m(3); 87% of the population was exposed above the guideline value. The burden of lung cancer attributable to PM2.5 exposure corresponded to 1466 cases, or 3.6% of all cases diagnosed in 2015. Sensitivity analyses showed that the use of a national median of PM2.5 exposure would have led to an underestimation of the PAF by 11% (population-weighted median) and by 72% (median of raw concentration), suggesting that our estimates would have been higher with even more finely spatially-resolved models. When the PM2.5 reference level was replaced by the 5th percentile of country-scale exposure (4.9 mu g/m(3)), PAF increased to 7.6%. Other sensitivity analyses resulted in even higher PAFs. Improvements in air pollution are crucial for quantitative health impacts assessment studies. Actions to reduce PM2.5 levels could substantially reduce the burden of lung cancer in France.
机译:室外空气污染是导致人类死亡和癌症发病率的主要环境原因。我们的目的是估计法国细颗粒物(PM2.5)暴露所致肺癌的发病率,其次要说明输入数据的影响以及信息对空气污染水平的空间分辨率对这一估计的影响。人口归因分数(PAF)是使用具有2 km空间分辨率,邻居规模人口密度数据以及已发表的荟萃分析的相对风险的全国范围的空间精细化学运输模型估算的。我们以WHO的PM2.5暴露指导值(10μg / m(3))作为参考。敏感性分析包括将全国范围的中位暴露水平归因于所有区域,并使用替代输入数据,例如PM2.5暴露水平参考值和相对风险。 2005年按人口加权的PM2中位数。(5)为13.8克/平方米(3); 87%的人口暴露于指导值以上。由PM2.5暴露引起的肺癌负担相当于1466例病例,占2015年诊断出的所有病例的3.6%。敏感性分析表明,使用全国PM2.5暴露中位数会导致PAF的低估分别增加了11%(人口加权中位数)和72%(原始浓度的中位数),这表明我们使用更精细的空间分辨模型可以得出更高的估计值。当PM2.5参考水平被国家暴露水平的第五个百分数(4.9μg / m(3))取代时,PAF增至7.6%。其他敏感性分析导致更高的PAF。空气污染的改善对于定量健康影响评估研究至关重要。降低PM2.5水平的措施可以在法国大大减轻肺癌的负担。

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