S Weichenthal, M Lloyd, A Ganji, L Simon, J Xu, A Venuta, A Schmidt, J Apte, H Chen, E Lavigne, P Villeneuve, T Olaniyan, M Tjepkema, R T Burnett, M Hatzopoulou
{"title":"加拿大蒙特利尔和多伦多长期暴露于室外超细粒子和黑碳以及对死亡率的影响。","authors":"S Weichenthal, M Lloyd, A Ganji, L Simon, J Xu, A Venuta, A Schmidt, J Apte, H Chen, E Lavigne, P Villeneuve, T Olaniyan, M Tjepkema, R T Burnett, M Hatzopoulou","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Numerous studies support an important relationship between long-term exposure to outdoor fine particulate air pollution (PM<sub>2.5</sub>) and both nonaccidental and cause-specific mortality. Less is known about the long-term health consequences of other traffic pollutants, including ultrafine particles (UFPs, <0.1 μm) and black carbon (BC), which are often present at elevated concentrations in urban areas but are not currently regulated. Knowledge is lacking largely because these pollutants generally are not monitored by governments and vary greatly over small spatial scales, hindering the evaluation of long-term exposures in population-based studies.</p><p><strong>Methods: </strong>We aimed to estimate associations between long-term exposures to outdoor UFPs and BC and nonaccidental and cause-specific mortality in Canada's two largest cities, Montreal and Toronto. We considered several approaches to exposure assessment: (1) land use regression (LUR) models based on large-scale year-long mobile monitoring campaigns combined with detailed land use and traffic information; (2) machine learning (i.e., convolutional neural networks [CNN]) models trained by combining mobile monitoring data with aerial images; and (3) the combined use of these two approaches. We also examined exposure models with and without backcasting based on historical trends in vehicle emissions (to capture potential trends in pollutant concentrations over time) and with and without accounting for neighborhood-level mobility patterns (based on travel demand surveys). These exposure models were linked to members of the Canadian Census Health and Environment Cohorts (CanCHEC) residing in Montreal or Toronto (including census years 1991, 1996, 2001, and 2006) with mortality follow-up from 2001 (or cohort entry for the 2006 cohort) to 2016. Cox proportional hazard models were used to estimate associations between long-term exposures to outdoor UFPs and BC, adjusting for sociodemographic factors and co-pollutants identified as potential confounding factors. Concentration-response relationships for outdoor UFPs and BC were also examined for nonaccidental and cause-specific mortality using smoothing splines.</p><p><strong>Results: </strong>Our cohort study included approximately 1.5 million people with 174,200 nonaccidental deaths observed during the follow-up period. Combined LUR and machine learning model predictions performed slightly better than LUR models alone and were used as the main exposure models in all epidemiological analyses. Long-term exposures to outdoor UFP number concentrations were consistently positively associated with nonaccidental and cause-specific mortality. Importantly, hazard ratios (HRs) for outdoor UFP number concentrations were sensitive to adjustment for UFP size: UFP size was inversely related to number concentrations and independently associated with mortality, resulting in underestimation of mortality risk for outdoor UFP number concentrations when UFP size was excluded. HRs for outdoor UFP number concentrations were robust to backcasting and mobility weighting but varied slightly in analyses using LUR and machine learning models alone, with stronger associations typically observed for the machine learning models. Associations between outdoor BC concentrations and mortality were generally weak or null, but a positive association was observed for cardiovascular mortality.</p><p><strong>Conclusions: </strong>Outdoor UFP number concentrations were consistently associated with increased risks of nonaccidental and cause-specific mortality in Montreal and Toronto. Our results suggest that UFP size should be considered in epidemiological analyses of outdoor UFP number concentrations, as excluding size can lead to an underestimation of health risks. Our results suggest that outdoor UFP number concentrations are positively associated with mortality independent of other outdoor air pollutants, including PM<sub>2.5</sub> mass concentrations and oxidant gases (i.e., nitrogen dioxide [NO<sub>2</sub>] and ozone [O<sub>3</sub>]). As outdoor UFPs are currently unregulated, interventions targeting these pollutants could significantly affect population health.</p>","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 217","pages":"1-63"},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11480997/pdf/","citationCount":"0","resultStr":"{\"title\":\"Long-Term Exposure to Outdoor Ultrafine Particles and Black Carbon and Effects on Mortality in Montreal and Toronto, Canada.\",\"authors\":\"S Weichenthal, M Lloyd, A Ganji, L Simon, J Xu, A Venuta, A Schmidt, J Apte, H Chen, E Lavigne, P Villeneuve, T Olaniyan, M Tjepkema, R T Burnett, M Hatzopoulou\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Numerous studies support an important relationship between long-term exposure to outdoor fine particulate air pollution (PM<sub>2.5</sub>) and both nonaccidental and cause-specific mortality. Less is known about the long-term health consequences of other traffic pollutants, including ultrafine particles (UFPs, <0.1 μm) and black carbon (BC), which are often present at elevated concentrations in urban areas but are not currently regulated. Knowledge is lacking largely because these pollutants generally are not monitored by governments and vary greatly over small spatial scales, hindering the evaluation of long-term exposures in population-based studies.</p><p><strong>Methods: </strong>We aimed to estimate associations between long-term exposures to outdoor UFPs and BC and nonaccidental and cause-specific mortality in Canada's two largest cities, Montreal and Toronto. We considered several approaches to exposure assessment: (1) land use regression (LUR) models based on large-scale year-long mobile monitoring campaigns combined with detailed land use and traffic information; (2) machine learning (i.e., convolutional neural networks [CNN]) models trained by combining mobile monitoring data with aerial images; and (3) the combined use of these two approaches. We also examined exposure models with and without backcasting based on historical trends in vehicle emissions (to capture potential trends in pollutant concentrations over time) and with and without accounting for neighborhood-level mobility patterns (based on travel demand surveys). These exposure models were linked to members of the Canadian Census Health and Environment Cohorts (CanCHEC) residing in Montreal or Toronto (including census years 1991, 1996, 2001, and 2006) with mortality follow-up from 2001 (or cohort entry for the 2006 cohort) to 2016. Cox proportional hazard models were used to estimate associations between long-term exposures to outdoor UFPs and BC, adjusting for sociodemographic factors and co-pollutants identified as potential confounding factors. Concentration-response relationships for outdoor UFPs and BC were also examined for nonaccidental and cause-specific mortality using smoothing splines.</p><p><strong>Results: </strong>Our cohort study included approximately 1.5 million people with 174,200 nonaccidental deaths observed during the follow-up period. Combined LUR and machine learning model predictions performed slightly better than LUR models alone and were used as the main exposure models in all epidemiological analyses. Long-term exposures to outdoor UFP number concentrations were consistently positively associated with nonaccidental and cause-specific mortality. Importantly, hazard ratios (HRs) for outdoor UFP number concentrations were sensitive to adjustment for UFP size: UFP size was inversely related to number concentrations and independently associated with mortality, resulting in underestimation of mortality risk for outdoor UFP number concentrations when UFP size was excluded. HRs for outdoor UFP number concentrations were robust to backcasting and mobility weighting but varied slightly in analyses using LUR and machine learning models alone, with stronger associations typically observed for the machine learning models. Associations between outdoor BC concentrations and mortality were generally weak or null, but a positive association was observed for cardiovascular mortality.</p><p><strong>Conclusions: </strong>Outdoor UFP number concentrations were consistently associated with increased risks of nonaccidental and cause-specific mortality in Montreal and Toronto. Our results suggest that UFP size should be considered in epidemiological analyses of outdoor UFP number concentrations, as excluding size can lead to an underestimation of health risks. Our results suggest that outdoor UFP number concentrations are positively associated with mortality independent of other outdoor air pollutants, including PM<sub>2.5</sub> mass concentrations and oxidant gases (i.e., nitrogen dioxide [NO<sub>2</sub>] and ozone [O<sub>3</sub>]). 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引用次数: 0
摘要
导言:大量研究证实,长期暴露于室外细颗粒空气污染(PM2.5)与非意外死亡和特定原因死亡之间存在重要关系。关于其他交通污染物(包括超细颗粒物)对健康的长期影响,目前还知之甚少:我们的目标是估算加拿大最大的两个城市--蒙特利尔和多伦多--长期暴露于室外超细粒子和 BC 与非意外死亡率和特定原因死亡率之间的关系。我们考虑了几种暴露评估方法:(1)基于长达一年的大规模移动监测活动并结合详细的土地利用和交通信息的土地利用回归(LUR)模型;(2)结合移动监测数据和航空图像训练的机器学习(即卷积神经网络 [CNN])模型;以及(3)这两种方法的结合使用。我们还研究了是否根据车辆排放的历史趋势(以捕捉污染物浓度随时间变化的潜在趋势)进行了反向预测的暴露模型,以及是否考虑了邻里层面的流动模式(基于出行需求调查)的暴露模型。这些暴露模型与居住在蒙特利尔或多伦多(包括人口普查年份 1991、1996、2001 和 2006)的加拿大人口普查健康与环境队列(CanCHEC)成员相关联,并从 2001 年(或 2006 年队列的队列入口)至 2016 年进行死亡率跟踪。采用 Cox 比例危险模型来估计长期暴露于室外 UFP 与 BC 之间的关系,并对社会人口因素和被确定为潜在混杂因素的共污染物进行调整。此外,还使用平滑样条检验了室外 UFP 与 BC 的浓度-反应关系,以及非事故死亡率和特定原因死亡率:我们的队列研究包括约 150 万人,在随访期间观察到 17.42 万例非意外死亡。综合 LUR 和机器学习模型的预测结果略优于单独的 LUR 模型,在所有流行病学分析中被用作主要暴露模型。长期暴露于室外的 UFP 数量浓度与非事故死亡率和特定原因死亡率一直呈正相关。重要的是,室外UFP数量浓度的危险比(HRs)对UFP大小的调整很敏感:UFP大小与UFP数量浓度成反比,与死亡率独立相关,当排除UFP大小时,室外UFP数量浓度的死亡风险被低估。室外 UFP 数量浓度的 HR 值对反向预测和流动性加权是稳健的,但在单独使用 LUR 和机器学习模型进行分析时略有不同,通常在机器学习模型中观察到更强的相关性。室外 BC 浓度与死亡率之间的关系一般较弱或不相关,但在心血管死亡率方面观察到了正相关:结论:在蒙特利尔和多伦多,室外 UFP 数量浓度一直与非意外死亡和特定原因死亡风险的增加有关。我们的研究结果表明,在对室外 UFP 数量浓度进行流行病学分析时,应考虑 UFP 的大小,因为不考虑 UFP 的大小会导致低估健康风险。我们的研究结果表明,室外UFP数量浓度与死亡率呈正相关,与其他室外空气污染物无关,包括PM2.5质量浓度和氧化剂气体(即二氧化氮[NO2]和臭氧[O3])。由于室外 UFPs 目前不受管制,针对这些污染物的干预措施可能会对人口健康产生重大影响。
Long-Term Exposure to Outdoor Ultrafine Particles and Black Carbon and Effects on Mortality in Montreal and Toronto, Canada.
Introduction: Numerous studies support an important relationship between long-term exposure to outdoor fine particulate air pollution (PM2.5) and both nonaccidental and cause-specific mortality. Less is known about the long-term health consequences of other traffic pollutants, including ultrafine particles (UFPs, <0.1 μm) and black carbon (BC), which are often present at elevated concentrations in urban areas but are not currently regulated. Knowledge is lacking largely because these pollutants generally are not monitored by governments and vary greatly over small spatial scales, hindering the evaluation of long-term exposures in population-based studies.
Methods: We aimed to estimate associations between long-term exposures to outdoor UFPs and BC and nonaccidental and cause-specific mortality in Canada's two largest cities, Montreal and Toronto. We considered several approaches to exposure assessment: (1) land use regression (LUR) models based on large-scale year-long mobile monitoring campaigns combined with detailed land use and traffic information; (2) machine learning (i.e., convolutional neural networks [CNN]) models trained by combining mobile monitoring data with aerial images; and (3) the combined use of these two approaches. We also examined exposure models with and without backcasting based on historical trends in vehicle emissions (to capture potential trends in pollutant concentrations over time) and with and without accounting for neighborhood-level mobility patterns (based on travel demand surveys). These exposure models were linked to members of the Canadian Census Health and Environment Cohorts (CanCHEC) residing in Montreal or Toronto (including census years 1991, 1996, 2001, and 2006) with mortality follow-up from 2001 (or cohort entry for the 2006 cohort) to 2016. Cox proportional hazard models were used to estimate associations between long-term exposures to outdoor UFPs and BC, adjusting for sociodemographic factors and co-pollutants identified as potential confounding factors. Concentration-response relationships for outdoor UFPs and BC were also examined for nonaccidental and cause-specific mortality using smoothing splines.
Results: Our cohort study included approximately 1.5 million people with 174,200 nonaccidental deaths observed during the follow-up period. Combined LUR and machine learning model predictions performed slightly better than LUR models alone and were used as the main exposure models in all epidemiological analyses. Long-term exposures to outdoor UFP number concentrations were consistently positively associated with nonaccidental and cause-specific mortality. Importantly, hazard ratios (HRs) for outdoor UFP number concentrations were sensitive to adjustment for UFP size: UFP size was inversely related to number concentrations and independently associated with mortality, resulting in underestimation of mortality risk for outdoor UFP number concentrations when UFP size was excluded. HRs for outdoor UFP number concentrations were robust to backcasting and mobility weighting but varied slightly in analyses using LUR and machine learning models alone, with stronger associations typically observed for the machine learning models. Associations between outdoor BC concentrations and mortality were generally weak or null, but a positive association was observed for cardiovascular mortality.
Conclusions: Outdoor UFP number concentrations were consistently associated with increased risks of nonaccidental and cause-specific mortality in Montreal and Toronto. Our results suggest that UFP size should be considered in epidemiological analyses of outdoor UFP number concentrations, as excluding size can lead to an underestimation of health risks. Our results suggest that outdoor UFP number concentrations are positively associated with mortality independent of other outdoor air pollutants, including PM2.5 mass concentrations and oxidant gases (i.e., nitrogen dioxide [NO2] and ozone [O3]). As outdoor UFPs are currently unregulated, interventions targeting these pollutants could significantly affect population health.