Environmental Health Perspectives ( IF 10.1 ) Pub Date : 2021-4-12 , DOI: 10.1289/ehp8368 Jie Chen 1 , Sophia Rodopoulou 2 , Kees de Hoogh 3, 4 , Maciej Strak 1, 5 , Zorana J Andersen 6 , Richard Atkinson 7 , Mariska Bauwelinck 8 , Tom Bellander 9, 10 , Jørgen Brandt 11 , Giulia Cesaroni 12 , Hans Concin 13 , Daniela Fecht 14 , Francesco Forastiere 12, 15 , John Gulliver 14, 16 , Ole Hertel 11 , Barbara Hoffmann 17 , Ulla Arthur Hvidtfeldt 18 , Nicole A H Janssen 5 , Karl-Heinz Jöckel 19 , Jeanette Jørgensen 6 , Klea Katsouyanni 2, 15 , Matthias Ketzel 11, 20 , Jochem O Klompmaker 5, 21 , Anton Lager 22 , Karin Leander 9 , Shuo Liu 6 , Petter Ljungman 9, 23 , Conor J MacDonald 24, 25 , Patrik K E Magnusson 26 , Amar Mehta 27 , Gabriele Nagel 28 , Bente Oftedal 29 , Göran Pershagen 9, 10 , Annette Peters 30, 31 , Ole Raaschou-Nielsen 18 , Matteo Renzi 12 , Debora Rizzuto 32, 33 , Evangelia Samoli 2 , Yvonne T van der Schouw 34 , Sara Schramm 19 , Per Schwarze 29 , Torben Sigsgaard 35 , Mette Sørensen 18 , Massimo Stafoggia 9, 12 , Anne Tjønneland 18 , Danielle Vienneau 3, 4 , Gudrun Weinmayr 28 , Kathrin Wolf 30 , Bert Brunekreef 1 , Gerard Hoek 1
Abstract
Background:
Inconsistent associations between long-term exposure to particles with an aerodynamic diameter [fine particulate matter ()] components and mortality have been reported, partly related to challenges in exposure assessment.
Objectives:
We investigated the associations between long-term exposure to elemental components and mortality in a large pooled European cohort; to compare health effects of components estimated with two exposure modeling approaches, namely, supervised linear regression (SLR) and random forest (RF) algorithms.
Methods:
We pooled data from eight European cohorts with 323,782 participants, average age 49 y at baseline (1985–2005). Residential exposure to 2010 annual average concentration of eight components [copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)] was estimated with Europe-wide SLR and RF models at a scale. We applied Cox proportional hazards models to investigate the associations between components and natural and cause-specific mortality. In addition, two-pollutant analyses were conducted by adjusting each component for mass and nitrogen dioxide () separately.
Results:
We observed 46,640 natural-cause deaths with 6,317,235 person-years and an average follow-up of 19.5 y. All SLR-modeled components were statistically significantly associated with natural-cause mortality in single-pollutant models with hazard ratios (HRs) from 1.05 to 1.27. Similar HRs were observed for RF-modeled Cu, Fe, K, S, V, and Zn with wider confidence intervals (CIs). HRs for SLR-modeled Ni, S, Si, V, and Zn remained above unity and (almost) significant after adjustment for both and . HRs only remained (almost) significant for RF-modeled K and V in two-pollutant models. The HRs for V were 1.03 (95% CI: 1.02, 1.05) and 1.06 (95% CI: 1.02, 1.10) for SLR- and RF-modeled exposures, respectively, per , adjusting for mass. Associations with cause-specific mortality were less consistent in two-pollutant models.
Conclusion:
Long-term exposure to V in was most consistently associated with increased mortality. Associations for the other components were weaker for exposure modeled with RF than SLR in two-pollutant models. https://doi.org/10.1289/EHP8368
中文翻译:
长期接触细颗粒元素成分与自然死亡率和特定原因死亡率——对 ELAPSE 项目中八个欧洲队列的汇总分析
抽象的
背景:
长期接触颗粒物与空气动力学直径之间的关联不一致[细颗粒物( )] 已报道成分和死亡率,部分与暴露评估中的挑战有关。
目标:
我们调查了长期暴露于大型欧洲队列中的元素成分和死亡率;比较对健康的影响使用两种曝光建模方法估计的成分,即监督线性回归(SLR)和随机森林(RF)算法。
方法:
我们汇集了 8 个欧洲队列的数据,共有 323,782 名参与者,基线时(1985-2005 年)平均年龄为 49 岁。住宅暴露2010年平均集中度为8成分[铜 (Cu)、铁 (Fe)、钾 (K)、镍 (Ni)、硫 (S)、硅 (Si)、钒 (V) 和锌 (Zn)] 使用欧洲范围的 SLR 估算和射频模型规模。我们应用 Cox 比例风险模型来研究成分与自然死亡率和特定原因死亡率之间的关联。此外,通过调整各成分进行双污染物分析质量和二氧化氮( ) 分别地。
结果:
我们观察到 46,640 例自然原因死亡,涉及 6,317,235 人年,平均随访时间为 19.5 年。所有 SLR 模型组成部分均与单一污染物模型中的自然原因死亡率显着相关,风险比 (HR) 为 1.05 至 1.27。 RF 模型的 Cu、Fe、K、S、V 和 Zn 也观察到类似的 HR,且置信区间 (CI) 更宽。 SLR 模型的 Ni、S、Si、V 和 Zn 的 HR 仍然高于统一值,并且在对两者进行调整后(几乎)显着和 。在两种污染物模型中,HR 仅对 RF 建模的 K 和 V 保持(几乎)显着性。对于每个 SLR 和 RF 模型暴露,V 的 HR 分别为 1.03 (95% CI: 1.02, 1.05) 和 1.06 (95% CI: 1.02, 1.10)。 ,调整为大量的。在两种污染物模型中,与特定原因死亡率的关联不太一致。