Long-Term Exposure to Low-Level PM2.5 and Mortality: Investigation of Heterogeneity by Harmonizing Analyses in Large Cohort Studies in Canada, United States, and Europe.

BACKGROUND: Studies across the globe generally reported increased mortality risks associated with particulate matter with aerodynamic diameter ≤2.5µm (PM2.5) exposure with large heterogeneity in the magnitude of reported associations and the shape of concentration-response functions (CRFs). We aimed to evaluate the impact of key study design factors (including confounders, applied exposure model, population age, and outcome definition) on PM2.5 effect estimates by harmonizing analyses on three previously published large studies in Canada [Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE), 1991-2016], the United States (Medicare, 2000-2016), and Europe [Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), 2000-2016] as much as possible. METHODS: We harmonized the study populations to individuals 65+ years of age, applied the same satellite-derived PM2.5 exposure estimates, and selected the same sets of potential confounders and the same outcome. We evaluated whether differences in previously published effect estimates across cohorts were reduced after harmonization among these factors. Additional analyses were conducted to assess the influence of key design features on estimated risks, including adjusted covariates and exposure assessment method. A combined CRF was assessed with meta-analysis based on the extended shape-constrained health impact function (eSCHIF). RESULTS: More than 81 million participants were included, contributing 692 million person-years of follow-up. Hazard ratios and 95% confidence intervals (CIs) for all-cause mortality associated with a 5-µg/m3 increase in PM2.5 were 1.039 (1.032, 1.046) in MAPLE, 1.025 (1.021, 1.029) in Medicare, and 1.041 (1.014, 1.069) in ELAPSE. Applying a harmonized analytical approach marginally reduced difference in the observed associations across the three studies. Magnitude of the association was affected by the adjusted covariates, exposure assessment methodology, age of the population, and marginally by outcome definition. Shape of the CRFs differed across cohorts but generally showed associations down to the lowest observed PM2.5 levels. A common CRF suggested a monotonically increased risk down to the lowest exposure level. https://doi.org/10.1289/EHP12141.

Mortality inequalities of Black adults in Canada.

Background: Mortality rates in Canada have been shown to vary by population group (e.g., Indigenous peoples, immigrants) and social economic status (e.g., income levels). Mortality patterns for some groups, including Black individuals, are not as well known. The objective of this study was to assess cause-specific mortality for Black adults living in Canada. Methods: Mortality inequalities between Black and White cohort members were estimated by sex using Cox proportional hazard models, based on data from the 2001, 2006 and 2011 Canadian Census Health and Environment Cohorts (CanCHECs). The CanCHEC cycles were combined and followed for mortality between Census Day and December 31, 2016 or 2019, resulting in a follow-up period of 15.6, 13.6 or 8.6 years, depending on the CanCHEC cycle. Results: Ischemic heart disease mortality was the leading cause of death among adult Black males (12.9%) and females (9.8%), as it is for adult White males (16.4%) and females (12.4%). Despite reduced risk of all-cause mortality among Black males and females, compared with White cohort members, there was notable increased risk for some cause-specific mortality. For instance, in the age-adjusted model, among the 25 causes of death examined, Black males had an increased risk of dying from four causes (HIV/AIDS, prostate cancer, diabetes mellitus and cerebrovascular disease), compared with White males. Similarly, Black females were at an increased risk for 6 causes of death (HIV/AIDS, stomach cancer, corpus uteri cancer, lymphomas and multiple myeloma, diabetes mellitus, and endocrine disorders) out of the 27 causes of death examined. These relative increased risks persisted for most causes of death after adjustment for differences in important social determinants of health. Interpretation: Results showed substantial variability in the risk of dying by cause of death between Black and White cohort members. An important step in reducing health inequities is the routine identification and surveillance of different health outcomes by population groups. This study helps fill that information gap.

Long-term exposure to wildfires and cancer incidence in Canada: a population-based observational cohort study.

BACKGROUND: Wildfires emit many carcinogenic pollutants that contaminate air, water, terrestrial, and indoor environments. However, little is known about the relationship between exposure to wildfires and cancer risk. We aimed to assess the associations between residential exposure to wildfires and the incidence of several cancer outcomes (lung cancer, brain cancer, non-Hodgkin lymphoma, multiple myeloma, and leukaemia) in Canada. METHODS: We did a population-based observational cohort study of participants in the 1996 Canadian Census Health and Environment Cohort. The 1996 Canadian Census Health and Environment Cohort is a nationally representative sample of Canadian adults, followed up for cancer incidence and mortality from 1996 to 2015. For this analysis, we excluded participants who lived in major Canadian cities (with a population size greater than 1·5 million people), recent immigrants, and individuals younger than 25 years or 90 years of age or older at baseline. Exposures to wildfires were assigned on the basis of area burned within a 20 km or 50 km radius of residential locations and updated for annual residential mobility. Multivariable Cox proportional hazards models were used to estimate associations between exposure to wildfires and specific cancers associated with carcinogenic compounds released by wildfires, including lung and brain cancer, non-Hodgkin lymphoma, multiple myeloma, and leukaemia, adjusted for many personal and neighbourhood-level covariates. FINDINGS: Our analyses included more than 2 million people followed up for a median of 20 years, for a total of 34 million person-years. Wildfire exposure was associated with slightly increased incidence of lung cancer and brain tumours. For example, cohort members exposed to a wildfire within 50 km of residential locations in the past 10 years had a 4·9% relatively higher incidence (adjusted hazard ratio [HR] 1·049, 95% CI 1·028-1·071) of lung cancer than unexposed populations, and a 10% relatively higher incidence (adjusted HR 1·100, 1·026-1·179) of brain tumours. Similar associations were observed for the 20 km buffer size. Wildfires were not associated with haematological cancers in this study, and concentration-response trends were not readily apparent when area burned was modelled as a continuous variable. INTERPRETATION: Long-term exposure to wildfires might increase the risk of lung cancer and brain tumours. Further work is needed to develop long-term estimates of wildfire exposures that capture the complex mixture of environmental pollutants released during these events. FUNDING: Canadian Institute for Health Research and Fonds de recherche du Quebec.

Disease assimilation: The mortality impacts of fine particulate matter on immigrants to Canada.

BACKGROUND: Immigrants make up 20% of the Canadian population; however, little is known about the mortality impacts of fine particulate matter (PM2.5) air pollution on immigrants compared with non-immigrants, or about how impacts may change with duration in Canada. DATA AND METHODS: This study used the 2001 Canadian Census Health and Environment Cohort, a longitudinal cohort of 3.5 million individuals, of which 764,000 were classified as immigrants (foreign-born). Postal codes from annual income tax files were used to account for mobility among respondents and to assign annual PM2.5 concentrations from 1998 to 2016. Exposures were estimated as a three-year moving average prior to the follow-up year. Cox survival models were used to determine hazard ratios (HRs) for cause-specific mortality, comparing the Canadian and foreign-born populations, with further stratification by year of immigration grouped into 10-year cohorts. RESULTS: Differences in urban-rural settlement patterns resulted in greater exposure to PM2.5 for immigrants compared with non-immigrants (mean = 9.3 vs. 7.5 µg/m3), with higher exposures among more recent immigrants. In fully adjusted models, immigrants had higher HRs per 10 µg/m3 increase in PM2.5 concentration compared with Canadian-born individuals for cardiovascular mortality (HR [95% confidence interval] = 1.22 [1.12 to 1.34] vs. 1.12 [1.07 to 1.18]) and cerebrovascular mortality (HR = 1.25 [1.03 to 1.52] vs. 1.03 [0.93 to 1.15]), respectively. However, tests for differences between the two groups were not significant when Cochran's Q test was used. No significant associations were found for respiratory outcomes, except for lung cancer in non-immigrants (HR = 1.10 [1.02 to 1.18]). When stratified by year of immigration, differences in HRs across varied by cause of death. DISCUSSION: In Canada, PM2.5 is an equal-opportunity risk factor, with immigrants experiencing similar if not higher mortality risks compared with non-immigrants for cardiovascular-related causes of death. Some notable differences also existed with cerebrovascular and lung cancer deaths. Continued reductions in air pollution, particularly in urban areas, will improve the health of the Canadian population as a whole.

Within-city Spatial Variations in Ambient Ultrafine Particle Concentrations and Incident Brain Tumors in Adults.

BACKGROUND: Ambient ultrafine particles (UFPs, <0.1 µm) can reach the human brain, but to our knowledge, epidemiologic studies have yet to evaluate the relation between UFPs and incident brain tumors. METHODS: We conducted a cohort study of within-city spatial variations in ambient UFPs across Montreal and Toronto, Canada, among 1.9 million adults included in multiple cycles of the Canadian Census Health and Environment Cohorts (1991, 1996, 2001, and 2006). UFP exposures (3-year moving averages) were assigned to residential locations using land-use regression models with exposures updated to account for residential mobility within and between cities. We followed cohort members for malignant brain tumors (ICD-10 codes C71.0-C71.9) between 2001 and 2016; Cox proportional hazards models (stratified by age, sex, immigration status, and census cycle) were used to estimate hazard ratios (HRs) adjusting for fine particle mass concentrations (PM2.5), nitrogen dioxide (NO2), and various sociodemographic factors. RESULTS: In total, we identified 1,400 incident brain tumors during the follow-up period. Each 10,000/cm increase in UFPs was positively associated with brain tumor incidence (HR = 1.112, 95% CI = 1.042, 1.188) after adjusting for PM2.5, NO2, and sociodemographic factors. Applying an indirect adjustment for cigarette smoking and body mass index strengthened this relation (HR = 1.133, 95% CI = 1.032, 1.245). PM2.5 and NO2 were not associated with an increased incidence of brain tumors. CONCLUSIONS: Ambient UFPs may represent a previously unrecognized risk factor for incident brain tumors in adults. Future studies should aim to replicate these results given the high prevalence of UFP exposures in urban areas.

Evaluating the Sensitivity of PM2.5-Mortality Associations to the Spatial and Temporal Scale of Exposure Assessment.

BACKGROUND: The temporal and spatial scales of exposure assessment may influence observed associations between fine particulate air pollution (PM2.5) and mortality, but few studies have systematically examined this question. METHODS: We followed 2.4 million adults in the 2001 Canadian Census Health and Environment Cohort for nonaccidental and cause-specific mortality between 2001 and 2011. We assigned PM2.5 exposures to residential locations using satellite-based estimates and compared three different temporal moving averages (1, 3, and 8 years) and three spatial scales (1, 5, and 10 km) of exposure assignment. In addition, we examined different spatial scales based on age, employment status, and urban/rural location, and adjustment for O3, NO2, or their combined oxidant capacity (Ox). RESULTS: In general, longer moving averages resulted in stronger associations between PM2.5 and mortality. For nonaccidental mortality, we observed a hazard ratio of 1.11 (95% CI = 1.08, 1.13) for the 1-year moving average compared with 1.23 (95% CI = 1.20, 1.27) for the 8-year moving average. Respiratory and lung cancer mortality were most sensitive to the spatial scale of exposure assessment with stronger associations observed at smaller spatial scales. Adjustment for oxidant gases attenuated associations between PM2.5 and cardiovascular mortality and strengthened associations with lung cancer. Despite these variations, PM2.5 was associated with increased mortality in nearly all of the models examined. CONCLUSIONS: These findings support a relationship between outdoor PM2.5 and mortality at low concentrations and highlight the importance of longer-exposure windows, more spatially resolved exposure metrics, and adjustment for oxidant gases in characterizing this relationship.

Cohort profile: The Canadian Census Health and Environment Cohorts (CanCHECs).

The Canadian Census Health and Environment Cohorts (CanCHECs) are population-based linked datasets of the household population at the time of census collection. The CanCHECs combine data from respondents to the long-form census or the National Household Survey between 1991 and 2011 with administrative health data (e.g., mortality, cancer incidence, hospitalizations, emergency ambulatory care) and annual mailing address postal codes. The CanCHEC datasets are rich national data resources that can be used to measure and examine health inequalities across socioeconomic and ethnocultural dimensions for different periods and locations. These datasets can also be used to examine the effects of exposure to environmental factors on human health. Because of their large size, the CanCHECs are an excellent resource for examining rare health outcomes and small population groups. They are ideally suited for environmental health research because of their geographic coverage across all regions of Canada, their long follow-up periods and their linkage to annual postal code history.

Low concentrations of fine particle air pollution and mortality in the Canadian Community Health Survey cohort.

BACKGROUND: Approximately 2.9 million deaths are attributed to ambient fine particle air pollution around the world each year (PM2.5). In general, cohort studies of mortality and outdoor PM2.5 concentrations have limited information on individuals exposed to low levels of PM2.5 as well as covariates such as smoking behaviours, alcohol consumption, and diet which may confound relationships with mortality. This study provides an updated and extended analysis of the Canadian Community Health Survey-Mortality cohort: a population-based cohort with detailed PM2.5 exposure data and information on a number of important individual-level behavioural risk factors. We also used this rich dataset to provide insight into the shape of the concentration-response curve for mortality at low levels of PM2.5. METHODS: Respondents to the Canadian Community Health Survey from 2000 to 2012 were linked by postal code history from 1981 to 2016 to high resolution PM2.5 exposure estimates, and mortality incidence to 2016. Cox proportional hazard models were used to estimate the relationship between non-accidental mortality and ambient PM2.5 concentrations (measured as a three-year average with a one-year lag) adjusted for socio-economic, behavioural, and time-varying contextual covariates. RESULTS: In total, 50,700 deaths from non-accidental causes occurred in the cohort over the follow-up period. Annual average ambient PM2.5 concentrations were low (i.e. 5.9 µg/m3, s.d. 2.0) and each 10 µg/m3 increase in exposure was associated with an increase in non-accidental mortality (HR = 1.11; 95% CI 1.04-1.18). Adjustment for behavioural covariates did not materially change this relationship. We estimated a supra-linear concentration-response curve extending to concentrations below 2 µg/m3 using a shape constrained health impact function. Mortality risks associated with exposure to PM2.5 were increased for males, those under age 65, and non-immigrants. Hazard ratios for PM2.5 and mortality were attenuated when gaseous pollutants were included in models. CONCLUSIONS: Outdoor PM2.5 concentrations were associated with non-accidental mortality and adjusting for individual-level behavioural covariates did not materially change this relationship. The concentration-response curve was supra-linear with increased mortality risks extending to low outdoor PM2.5 concentrations.

Evaluation of a method to indirectly adjust for unmeasured covariates in the association between fine particulate matter and mortality.

BACKGROUND: Indirect adjustment via partitioned regression is a promising technique to control for unmeasured confounding in large epidemiological studies. The method uses a representative ancillary dataset to estimate the association between variables missing in a primary dataset with the complete set of variables of the ancillary dataset to produce an adjusted risk estimate for the variable in question. The objective of this paper is threefold: 1) evaluate the method for non-linear survival models, 2) formalize an empirical process to evaluate the suitability of the required ancillary matching dataset, and 3) test modifications to the method to incorporate time-varying exposure data, and proportional weighting of datasets. METHODS: We used the association between fine particle air pollution (PM2.5) with mortality in the 2001 Canadian Census Health and Environment Cohort (CanCHEC, N = 2.4 million, 10-years follow-up) as our primary dataset, and the 2001 cycle of the Canadian Community Health Survey (CCHS, N = 80,630) as the ancillary matching dataset that contained confounding risk factor information not available in CanCHEC (e.g., smoking). The main evaluation process used a gold-standard approach wherein two variables (education and income) available in both datasets were excluded, indirectly adjusted for, and compared to true models with education and income included to assess the amount of bias correction. An internal validation for objective 1 used only CanCHEC data, whereas an external validation for objective 2 replaced CanCHEC with the CCHS. The two proposed modifications were applied as part of the validation tests, as well as in a final indirect adjustment of four missing risk factor variables (smoking, alcohol use, diet, and exercise) in which adjustment direction and magnitude was compared to models using an equivalent longitudinal cohort with direct adjustment for the same variables. RESULTS: At baseline (2001) both cohorts had very similar PM2.5 distributions across population characteristics, although levels for CCHS participants were consistently 1.8-2.0 µg/m3 lower. Applying sample-weighting largely corrected for this discrepancy. The internal validation tests showed minimal downward bias in PM2.5 mortality hazard ratios of 0.4-0.6% using a static exposure, and 1.7-3% when a time-varying exposure was used. The external validation of the CCHS as the ancillary dataset showed slight upward bias of -0.7 to -1.1% and downward bias of 1.3-2.3% using the static and time-varying approaches respectively. CONCLUSIONS: The CCHS was found to be fairly well representative of CanCHEC and its use in Canada for indirect adjustment is warranted. Indirect adjustment methods can be used with survival models to correct hazard ratio point estimates and standard errors in models missing key covariates when a representative matching dataset is available. The results of this formal evaluation should encourage other cohorts to assess the suitability of ancillary datasets for the application of the indirect adjustment methodology to address potential residual confounding.