INTRODUCTION: Numerous studies support an important relationship between long-term exposure to outdoor fine particulate air pollution (PM) 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. 2.5
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 PMmass concentrations and oxidant gases (i.e., nitrogen dioxide [NO] and ozone [O]). As outdoor UFPs are currently unregulated, interventions targeting these pollutants could significantly affect population health. 2.5 2 3
