Several studies have indicated weakly increased risk for kidney cancer among occupational groups exposed to gasoline vapors, engine exhaust, polycyclic aromatic hydrocarbons and other air pollutants, although not consistently. It was the aim to investigate possible associations between outdoor air pollution at the residence and the incidence of kidney parenchyma cancer in the general population. We used data from 14 European cohorts from the ESCAPE study. We geocoded and assessed air pollution concentrations at baseline addresses by land-use regression models for particulate matter (PM10 , PM2.5 , PMcoarse , PM2.5 absorbance (soot)) and nitrogen oxides (NO2 , NOx ), and collected data on traffic. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effects models for meta-analyses to calculate summary hazard ratios (HRs). The 289,002 cohort members contributed 4,111,908 person-years at risk. During follow-up (mean 14.2 years) 697 incident cancers of the kidney parenchyma were diagnosed. The meta-analyses showed higher HRs in association with higher PM concentration, e.g. HR = 1.57 (95%CI: 0.81-3.01) per 5 μg/m3 PM2.5 and HR = 1.36 (95%CI: 0.84-2.19) per 10-5 m-1 PM2.5 absorbance, albeit never statistically significant. The HRs in association with nitrogen oxides and traffic density on the nearest street were slightly above one. Sensitivity analyses among participants who did not change residence during follow-up showed stronger associations, but none were statistically significant. Our study provides suggestive evidence that exposure to outdoor PM at the residence may be associated with higher risk for kidney parenchyma cancer; the results should be interpreted cautiously as associations may be due to chance.

译文

几项研究表明,在暴露于汽油蒸气,发动机废气,多环芳烃和其他空气污染物的职业群体中,患肾癌的风险增加很小,尽管并不一致。目的是调查居住地的室外空气污染与普通人群中肾脏实质癌的发生率之间的可能关联。我们使用了来自ESCAPE研究的14个欧洲队列的数据。我们通过土地利用回归模型对颗粒物 (PM10,PM2.5,pm粗,PM2.5吸光度 (soot)) 和氮氧化物 (NO2,NOx) 的基线地址的空气污染浓度进行了地理编码和评估,并收集了交通数据。我们使用Cox回归模型对队列特异性分析的潜在混杂因素进行校正,并使用随机效应模型进行荟萃分析,以计算汇总风险比 (HRs)。289,002队列成员贡献了4,111,908人年的风险。在随访期间 (平均14.2年),诊断出697例肾实质癌。荟萃分析显示,较高的HRs与较高的PM浓度相关,例如每5 μ g/m3 PM2.5的HR  =   1.57 (95% CI: 0.81-3.01) 和每10-5 m-1 PM2.5的HR  =   1.36 (95% CI: 0.84-2.19),尽管从来没有统计学意义。与最近街道上的氮氧化物和交通密度相关的hr略高于1。在随访期间未改变居住地的参与者中进行的敏感性分析显示,相关性更强,但无统计学意义。我们的研究提供了暗示性证据,表明在住所暴露于室外PM可能与较高的肾实质癌风险相关; 应谨慎解释结果,因为关联可能是偶然的。

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