Background: Few cohort studies have evaluated the risk of mortality associated with long-term exposure to fine particulate matter [≤ 2.5 μm in aerodynamic diameter (PM2.5)]. This is the first national-level cohort study to investigate these risks in Canada. Objective: We investigated the association between long-term exposure to ambient PM2.5 and cardiovascular mortality in nonimmigrant Canadian adults. Methods: We assigned estimates of exposure to ambient PM2.5 derived from satellite observations to a cohort of 2.1 million Canadian adults who in 1991 were among the 20% of the population mandated to provide detailed census data. We identified deaths occurring between 1991 and 2001 through record linkage. We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) adjusted for available individual-level and contextual covariates using both standard Cox proportional survival models and nested, spatial random-effects survival models. Results: Using standard Cox models, we calculated HRs of 1.15 (95% CI: 1.13, 1.16) from nonaccidental causes and 1.31 (95% CI: 1.27, 1.35) from ischemic heart disease for each 10-μg/m3 increase in concentrations of PM2.5. Using spatial random-effects models controlling for the same variables, we calculated HRs of 1.10 (95% CI: 1.05, 1.15) and 1.30 (95% CI: 1.18, 1.43), respectively. We found similar associations between nonaccidental mortality and PM2.5 based on satellite-derived estimates and ground-based measurements in a subanalysis of subjects in 11 cities. Conclusions: In this large national cohort of nonimmigrant Canadians, mortality was associated with long-term exposure to PM2.5. Associations were observed with exposures to PM2.5 at concentrations that were predominantly lower (mean, 8.7 μg/m3; interquartile range, 6.2 μg/m3) than those reported previously.

A peer-reviewed open access journal published by the National Institute of Environmental Health Sciences

OBJECTIVE Recent studies suggest that chronic exposure to air pollution can promote the development of diabetes. However, whether this relationship actually translates into an increased risk of mortality attributable to diabetes is uncertain. RESEARCH DESIGN AND METHODS We evaluated the association between long-term exposure to ambient fine particulate matter (PM_2.5) and diabetes-related mortality in a prospective cohort analysis of 2.1 million adults from the 1991 Canadian census mortality follow-up study. Mortality information, including ∼5,200 deaths coded as diabetes being the underlying cause, was ascertained by linkage to the Canadian Mortality Database from 1991 to 2001. Subject-level estimates of long-term exposure to PM_2.5 were derived from satellite observations. The hazard ratios (HRs) for diabetes-related mortality were related to PM_2.5 and adjusted for individual-level and contextual variables using Cox proportional hazards survival models. RESULTS Mean PM_2.5 exposure levels for the entire population were low (8.7 µg/m³; SD, 3.9 µg/m³; interquartile range, 6.2 µg/m³). In fully adjusted models, a 10-µg/m³ elevation in PM_2.5 exposure was associated with an increase in risk for diabetes-related mortality (HR, 1.49; 95% CI, 1.37–1.62). The monotonic change in risk to the population persisted to PM_2.5 concentration <5 µg/m³. CONCLUSIONS Long-term exposure to PM_2.5, even at low levels, is related to an increased risk of mortality attributable to diabetes. These findings have considerable public health importance given the billions of people exposed to air pollution and the worldwide growing epidemic of diabetes.

Develop statistical methods for survival models to indirectly adjust hazard ratios of environmental exposures for missing risk factors. A partitioned regression approach for linear models is applied to time to event survival analyses of cohort study data. Information on the correlation between observed and missing risk factors is obtained from ancillary data sources such as national health surveys. The relationship between the missing risk factors and survival is obtained from previously published studies. We first evaluated the methodology using simulations, by considering the Weibull survival distribution for a proportional hazards regression model with varied baseline functions, correlations between an adjusted variable and an adjustment variable as well as selected censoring rates. Then we illustrate the method in a large, representative Canadian cohort of the association between concentrations of ambient fine particulate matter and mortality from ischemic heart disease. Indirect adjustment for cigarette smoking habits and obesity increased the fine particulate matter-ischemic heart disease association by 3%-123%, depending on the number of variables considered in the adjustment model due to the negative correlation between these two risk factors and ambient air pollution concentrations in Canada. The simulations suggested that the method yielded small relative bias (<40%) for most cohort designs encountered in environmental epidemiology. This method can accommodate adjustment for multiple missing risk factors simultaneously while accounting for the associations between observed and missing risk factors and between missing risk factors and health endpoints.

Most studies on the association between exposure to fine particulate matter (PM_2.5) and mortality have considered only total concentration of PM_2.5 or individual components of PM_2.5 and not the combined effects of concentration and particulate composition. We sought to develop a method to estimate the risk of death from long-term exposure to PM_2.5 and the distribution of its components, namely: sulphate, nitrate, ammonium, organic mass, black carbon and mineral dust. We decomposed PM_2.5 exposure into the sum of total concentration and the proportion of each component. We estimated the risk of death due to exposure using a cohort of ~2.4 million Canadians who were followed for vital status over 16 years. Modelling the concentration of PM_2.5 with the distribution of the proportions of components together was a superior predictor for mortality than either total PM_2.5 concentration alone, or all component concentrations modelled together. Our new approach has the advantage of characterizing the toxicity of the atmosphere in its entirety. This is required to fully understand the health benefits associated with strategies to improve air quality that may result in complex changes not only in PM_2.5 concentration, but also in the distribution of particle components.

The independent and joint effects of within- and between-city contrasts in air pollution on mortality have been investigated rarely. To examine the differential effects of between- versus within-city contrasts in pollution exposure, we used both ambient measurements and land use regression models to assess associations with mortality and exposure to nitrogen dioxide (NO₂) among ~735,600 adults in 10 of the largest Canadian cities. We estimated exposure contrasts partitioned into within- and between-city contrasts, and the sum of these as overall exposures, for every year from 1984 to 2006. Residential histories allowed us to follow subjects annually during the study period. We calculated hazard ratios (HRs) adjusted for many personal and contextual variables. In fully-adjusted, random-effects models, we found positive associations between overall NO₂ exposures and mortality from non-accidental causes (HR per 5 p.p.b.: 1.05; 95% confidence interval (CI): 1.03–1.07), cardiovascular disease (HR per 5 p.p.b.: 1.04; 95% CI: 1.01–1.06), ischaemic heart disease (HR per 5 p.p.b.: 1.05; 95% CI: 1.02–1.08) and respiratory disease (HR per 5 p.p.b.: 1.04; 95% CI: 0.99–1.08), but not from cerebrovascular disease (HR per 5 p.p.b.: 1.01; 95% CI: 0.96–1.06). We found that most of these associations were determined by within-city contrasts, as opposed to by between-city contrasts in NO₂. Our results suggest that variation in NO₂ concentrations within a city may represent a more toxic mixture of pollution than variation between cities.