Residential proximity to greenness and adverse birth outcomes in urban areas: Findings from a national Canadian population-based study.

BACKGROUND: Over the last decade, several studies have reported that residential proximity to vegetation, or 'greenness', is associated with improved birth outcomes, including for term birth weight (TBW), preterm birth (PTB), and small for gestational age (SGA). However, there remain several uncertainties about these possible benefits including the role of air pollution, and the extent to they are influenced socioeconomic status. METHODS: We addressed these gaps using a national population-based study of 2.2 million singleton live births in Canadian metropolitan areas between 1999 and 2008. Exposures to greenness, fine particulate matter (PM2.5), and nitrogen dioxide (NO2) were assigned to infants using the postal code of their mother's residence at the time of birth. The Normalized Difference Vegetation Index (NDVI) was used to characterize greenness, while estimates of ambient PM2.5 and NO2 were estimated using remote sensing, and a national land-use regression surface, respectively. Multivariable regression analysis was performed to describe associations between residential greenness and the birth outcomes. Stratified analyses explored whether these associations were modified by neighbourhood measures of socioeconomic status. RESULTS: Mothers who lived in greener areas had a lower risk of low TBW, PTB, and SGA babies. These associations persisted after adjustment for ambient NO2 and PM2.5. Specifically, in fully adjusted models, an interquartile range (IQR = 0.16) increase in the NDVI within a residential buffer of 250 m yielded odds ratios of 0.93 (95% confidence interval (CI): 0.92, 0.94), 0.94 (95% CI: 0.92, 0.95), and 0.94 (95% CI: 0.93, 0.95) for the outcomes of PTB, low TBW, and SGA, respectively. Similarly, an IQR increase in greenness was associated with a 16.3 g (95% CI: 15.3, 17.4) increase in TBW. We found inverse associations between greenness and the occurrence of adverse birth outcomes regardless of the socioeconomic status of the neighbourhood. INTERPRETATION: Our findings support the hypothesis that residential greenness contributes to healthier pregnancies, that these associations are independent from exposure to air pollution. , and that proximity to greenness benefits all mothers regardless of socioeconomic status.

Ambient air pollution and the risk of acute myocardial infarction and stroke: A national cohort study.

We used a large national cohort in Canada to assess the incidence of acute myocardial infarction (AMI) and stroke hospitalizations in association with long-term exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3). The study population comprised 2.7 million respondents from the 2006 Canadian Census Health and Environment Cohort (CanCHEC), followed for incident hospitalizations of AMI or stroke between 2006 and 2016. We estimated 10-year moving average estimates of PM2.5, NO2, and O3, annually. We used Cox proportional hazards models to examine the associations adjusting for various covariates. For AMI, each interquartile range (IQR) increase in exposure was found to be associated with a hazard ratio of 1.026 (95% CI: 1.007-1.046) for PM2.5, 1.025 (95% CI: 1.001-1.050) for NO2, and 1.062 (95% CI: 1.041-1.084) for O3, respectively. Similarly, for stroke, an IQR increase in exposure was associated with a hazard ratio of 1.078 (95% CI: 1.052-1.105) for PM2.5, 0.995 (95% CI: 0.965-1.030) for NO2, and 1.055 (95% CI: 1.028-1.082) for O3, respectively. We found consistent evidence of positive associations between long-term exposures to PM2.5, and O3, and to a lesser degree NO2, with incident AMI and stroke hospitalizations.

Residential greenness and indicators of stress and mental well-being in a Canadian national-level survey.

BACKGROUND: Residential proximity to greenness in urban areas has been shown to confer a number of health benefits, including improved mental health. We investigated whether greenness was associated with self-reported stress, distress, and mental health among adult participants of multiple cycles of a national Canadian health survey, and whether these associations varied by sex, age, income, and neighbourhood characteristics. METHODS: Our study population included 397,900 participants of the Canadian Community Health Survey, 18 years of age or older, who lived in census metropolitan areas between 2000 and 2015. We used the Normalized Difference Vegetation Index (NDVI) to characterize participants' exposure to greenness within 250 m, 500 m, and 1 km buffers from a representative location of their postal code. Health outcomes included: self-reported perceptions of life stress, psychological distress, and self-rated mental health. We used multiple regression models, adjusted for relevant individual and neighbourhood-level variables to estimate associations (and 95% confidence intervals) between each outcome and exposure to greenness. FINDINGS: In models with all participants, we observed 6% lower odds of poor self-rated mental health per increase in the interquartile range (i.e., 0.12) of NDVI within a 500 m buffer. Across the three outcomes, we found substantial heterogeneity in effect size across categories of sex, age, and community-level indicators of deprivation and urban form. For example, each incremental increase in greenness exposure was associated with a reduction of 0.61 (95% CI: 0.81 to -0.51) on the K10 psychological distress score among those living in the active core of cities, and with an increase of 0.07 (95% CI: 0.03-0.12) on this score among those living in the most suburban areas. CONCLUSIONS: Our results indicate that the potential benefits of residential greenness on mental health vary across personal and neighbourhood-level characteristics and are sensitive to how the outcome is measured. Additional research is needed to understand which features of greenness are most relevant to different sub-groups of the population to maximize these health benefits.

Does exposure to air pollution increase the risk of acute care in young children with asthma? An Ontario, Canada study.

Owing to their greater outdoor activity and ongoing lung development, children are particularly vulnerable to the harmful effects of exposure to fine particulate matter (PM2.5). However, the effects of PM2.5 components are poorly understood. This study aimed to use a longitudinal birth cohort of children with physician-diagnosed incident asthma to investigate the effect of PM2.5 components at birth on morbidity measured by health services utilization. Of 1277 Toronto Child Health Evaluation Questionnaire (T-CHEQ) participants, the study population included 362 children diagnosed with asthma who were followed for a mean of 13 years from birth until March 31, 2016, or loss-to-follow-up. Concentrations of PM2.5 and its components were assigned based on participants' postal codes at birth. Study outcomes included counts of asthma, asthma-related, and all-cause health services use. Poisson regression in single-, two-, and multi-pollutant models was used to estimate rate ratios (RR) per interquartile range (IQR) increase of exposures. Covariates were included in all models to further adjust for potential confounding. The adjusted RR for sulfate (SO4) and all-cause hospitalizations was statistically significant with RR = 2.23 (95% confidence interval [CI]: 1.25-3.96) in a multi-pollutant model with nitrogen dioxide (NO2) and ozone (O3). In multi-pollutant models with oxidants, the adjusted RRs for SO4 of all-cause hospitalizations and emergency department (ED) visits were also statistically significant with RR = 2.31 (95% CI: 1.32-4.03) and RR = 1.39 (95% CI: 1.02-1.90), respectively. While unadjusted single-pollutant RRs for asthma-specific and asthma-related health services use with the SO4 component of PM2.5 were above one, none were statistically significant. This study found significant associations with exposure to SO4 in PM2.5 and all-cause acute care, chiefly for hospitalizations, in children with asthma.

Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter.

Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.

Ethnocultural and socioeconomic disparities in exposure to residential greenness within urban Canada.

BACKGROUND: Residential greenness has been associated with health benefits, such as lower risk of mortality, cardiovascular disease, obesity, adverse birth outcomes and asthma and better psychological health. However, the variation in greenness across socioeconomic and demographic characteristics in urban areas of Canada has not been well documented. DATA AND METHODS: Respondents to the 2016 Census long-form questionnaire were assigned estimates of exposure to residential greenness based on the mean Normalized Difference Vegetation Index (NDVI) (from 2012 or the most recent year available) within a 500 m buffer around their home, based on postal code. Census weights were used to determine differences in average exposure to greenness according to selected demographic and socioeconomic characteristics. RESULTS: Mean residential greenness among the 5.3 million census respondents in urban Canada was 0.44 units of the NDVI (standard deviation = 0.18 units). Greenness was lower among immigrants (particularly recent immigrants), some groups designated as visible minorities (particularly people of Filipino ancestry), lower-income households and tenants (i.e., NDVI values ranging from 0.40 to 0.43 units). Greenness values were highest among White non-immigrants and higher-income households (i.e., NDVI values ranging from 0.46 to 0.47 units). DISCUSSION: Given the potentially multifaceted role that greenness plays in health outcomes, the inequalities in residential greenness described here may contribute to producing or exacerbating existing health inequalities in the Canadian population.

Early life exposure to air pollution and incidence of childhood asthma, allergic rhinitis and eczema.

RATIONALE: There is growing evidence that air pollution may contribute to the development of childhood asthma and other allergic diseases. In this follow-up of the Toronto Child Health Evaluation Questionnaire (T-CHEQ) study, we examined associations between early life exposures to air pollution and incidence of asthma, allergic rhinitis and eczema from birth through adolescence. METHODS: 1286 T-CHEQ participants were followed from birth until outcome (March 31, 2016) or loss to follow-up, with a mean of 17 years of follow-up. Concentrations of nitrogen dioxide (NO2), ozone (O3) and particulate matter with a 50% cut-off aerodynamic diameter of 2.5 µm (PM2.5) from January 1, 1999 to December 31, 2012 were assigned to participants based on their postal codes at birth using ground observations, chemical/meteorological models, remote sensing and land-use regression models. Study outcomes included incidence of physician-diagnosed asthma, allergic rhinitis and eczema. Cox proportional hazard regression models were used to estimate hazard ratios per interquartile range of exposures and outcomes, adjusting for potential confounders. RESULTS: Hazard ratios of 1.17 (95% CI 1.05-1.31) for asthma and 1.07 (95% CI 0.99-1.15) for eczema were observed for total oxidants (O3 and NO2) at birth. No significant increase in risk was found for PM2.5. CONCLUSIONS: Exposures to oxidant air pollutants (O3 and NO2) but not PM2.5 were associated with an increased risk of incident asthma and eczema in children. This suggests that improving air quality may contribute to the prevention of asthma and other allergic disease in childhood and adolescence.

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.

Self-rated stress, distress, mental health, and health as modifiers of the association between long-term exposure to ambient pollutants and mortality.

BACKGROUND: Individual and neighbourhood-scale socioeconomic characteristics modify associations between exposure to air pollution and mortality. The role of stress, which may integrate effects of social and environmental exposures on health, is unknown. We examined whether an individual's perspective on their own well-being, as assessed using self-rated measures of stress and health, modifies the pollutant-mortality relationship. METHODS: The Canadian Community Health Survey (CCHS)-mortality cohort includes respondents from surveys administered between 2001 and 2012 linked to vital statistics and postal codes from 1981 until 2016. Annual fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) exposure estimates were attached to a sample of cohort members aged 30-89 years (n = 398,300 respondents/3,848,400 person-years). We examined whether self-rated stress, distress, mental health, and general health modified associations between long-term exposure to each pollutant (three-year moving average with one-year lag) and non-accidental mortality using Cox survival models, adjusted for individual- (i.e. socioeconomic and behavioural) and neighbourhood-scale covariates. RESULTS: In fully-adjusted models, the relationship between exposure to pollutants and mortality was stronger among those with poor self-rated mental health, including a significant difference for NO2 (hazard ratio (HR) = 1.15, 95% CI 1.06-1.25 per IQR) compared to those with very good/excellent mental health (HR = 1.05, 95% CI 1.01-1.08; Cochran's Q = 4.01; p < 0.05). Poor self-rated health was similarly associated with higher pollutant-associated HRs, but only in unadjusted models. Stress and distress did not modify pollutant-mortality associations. CONCLUSIONS: Poor self-rated mental and general health were associated with increased mortality attributed to exposure to ambient pollutants.

Accuracy of matching residential postal codes to census geography.

BACKGROUND: Postal codes are often the only geographic identifier available to match subjects in a health dataset to census geography. This paper describes the characteristics of postal codes reported by the Canadian population on the census and, as an indicator of geocoding accuracy, the proportion that are linked to a single dissemination area (DA). DATA AND METHODS: Postal codes reported on the 2016 Census questionnaire were matched to a combination of the Postal Code Conversion File (PCCF) and the Postal Code Conversion File Plus (PCCF+ version 7B) (reference date November 2018) to calculate population-weighted counts and the number of matches to DAs by province or territory, delivery mode type (DMT), population centre or rural area size, and census metropolitan area. The number of single matches to census tracts (CTs), census subdivisions (CSDs) and census divisions (CDs) was also calculated. RESULTS: In Canada, 72.6% of the population reported postal codes that matched to a single DA. This proportion was higher in urban cores (87.1%) and among postal codes for an urban street address (DMT=A) (85.3%) or apartment building (DMT=B) (95.3%), and was lower in rural areas (26.2% to 38.1%) and among rural postal codes (13.9%). In comparison, 89.3% and 95.4% of the population reported postal codes matching to a single CSD or CD, respectively, while 92.1% of the population that live within CT boundaries were matched to a single CT. DISCUSSION: Matching postal codes to census geography is relatively accurate and frequently one to one in urban centres. In rural areas and for some types of postal code DMTs, alternative approaches to using the PCCF and PCCF+ for attaching census geography might be explored.

The association between ambient air pollution concentrations and psychological distress.

BACKGROUND: A growing number of epidemiological studies have linked air pollution exposure to psychological conditions. Laboratory studies indicate that air pollutants can activate the neuroendocrine stress axis and modulate stress hormone levels, which could contribute to the development or exacerbation of psychological distress. The present study examined the spatial associations between air pollutants (fine particulate matter [PM2.5], nitrogen dioxide [NO2] and ground-level ozone [O3]) and psychological distress among subjects in the most populous provinces in Canada. DATA AND METHODS: Subjects were sampled from the Canadian Community Health Survey in three regions (Quebec in 2005 [n=25,800], British Columbia and Alberta in 2005 [n=23,000], and Ontario in 2011 [n=36,000]), and were assigned estimates of annual exposure to three ambient air pollutants (PM2.5, NO2 and O3) for the same years. Individual psychological distress was assessed using the Kessler Psychological Distress Scale (K10), based on anxiety and depressive symptoms in the past month. Regression models (both ordinary least squares and simultaneous autoregressive models) were applied to estimate associations between K10 distress scores and each air pollutant, after adjusting for individual (demographic, socioeconomic and behavioural) and neighbourhood covariates.. RESULTS: Psychological distress was positively associated with PM2.5 and NO2 in all three regions, and with O3 in Quebec. However, after further adjusting for individual and neighbourhood covariates, the associations between distress and air pollution remained statistically significant only in Quebec. DISCUSSION: Some evidence for positive associations between psychological distress and ambient air pollution after adjusting for spatial autocorrelation was found.

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.

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.

Air pollution in the week prior to delivery and preterm birth in 24 Canadian cities: a time to event analysis.

BACKGROUND: Numerous studies have examined the association between air pollution and preterm birth (< 37 weeks gestation) but findings have been inconsistent. These associations may be more difficult to detect than associations with other adverse birth outcomes because of the different duration of exposure in preterm vs. term births, and the existence of seasonal cycles in incidence of preterm birth. METHODS: We analyzed data pertaining to 1,001,700 singleton births occurring between 1999 and 2008 in 24 Canadian cities where daily air pollution data were available from government monitoring sites. In the first stage, data were analyzed in each city employing Cox proportional hazards models using gestational age in days as the time scale, obtaining city-specific hazard ratios (HRs) with their 95% confidence intervals (CIs) expressed per interquartile range (IQR) of each air pollutant. Effects were examined using distributed lag functions for lags of 0-6 days prior to delivery, as well as cumulative lags from two to six days. We accounted for the potential nonlinear effect of daily mean ambient temperature using a cubic B-spline with three internal knots. In the second stage, we pooled the estimated city-specific hazard ratios using a random effects model. RESULTS: Pooled estimates across 24 cities indicated that an IQR increase in ozone (O3, 13.3 ppb) 0-3 days prior to delivery was associated with a hazard ratio of 1.036 (95% CI 1.005, 1.067) for preterm birth, adjusting for infant sex, maternal age, marital status and country of birth, neighbourhood socioeconomic status (SES) and visible minority, temperature, year and season of birth, and a natural spline function of day of year. There was some evidence of effect modification by gestational age and season. Associations with carbon monoxide, nitrogen dioxide, particulate matter, and sulphur dioxide were inconsistent. CONCLUSIONS: We observed associations between daily O3 in the week before delivery and preterm birth in an analysis of approximately 1 million births in 24 Canadian cities between 1999 and 2008. Our analysis is one of a limited number which have examined these short term associations employing Cox proportional hazards models to account for the different exposure durations of preterm vs. term births.

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.

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.

Diabetes Status and Susceptibility to the Effects of PM2.5 Exposure on Cardiovascular Mortality in a National Canadian Cohort.

BACKGROUND: Diabetes is infrequently coded as the primary cause of death but may contribute to cardiovascular disease (CVD) mortality in response to fine particulate matter (PM2.5) exposure. We analyzed all contributing causes of death to examine susceptibility of diabetics to CVD mortality from long-term exposure. METHODS: We linked a subset of the 2001 Canadian Census Health and Environment Cohort (CanCHEC) with 10 years of follow-up to all causes of death listed on death certificates. We used survival models to examine the association between CVD deaths (n = 123,500) and exposure to PM2.5 among deaths that co-occurred with diabetes (n = 20,600) on the death certificate. More detailed information on behavioral covariates and diabetes status at baseline available in the Canadian Community Health Survey (CCHS)-mortality cohort (n = 12,400 CVD deaths, with 2,800 diabetes deaths) complemented the CanCHEC analysis. RESULTS: Among CanCHEC subjects, comention of diabetes on the death certificate increased the magnitude of association between CVD mortality and PM2.5 (HR = 1.51 [1.39-1.65] per 10 µg/m) versus all CVD deaths (HR = 1.25 [1.21-1.29]) or CVD deaths without diabetes (HR = 1.20 [1.16-1.25]). Among CCHS subjects, diabetics who used insulin or medication (included as proxies for severity) had higher HR estimates for CVD deaths from PM2.5 (HR = 1.51 [1.08-2.12]) relative to the CVD death estimate for all respondents (HR = 1.31 [1.16-1.47]). CONCLUSIONS: Mention of diabetes on the death certificate resulted in higher magnitude associations between PM2.5 and CVD mortality, specifically among those who manage their diabetes with insulin or medication. Analyses restricted to the primary cause of death likely underestimate the role of diabetes in air pollution-related mortality. See video abstract at, http://links.lww.com/EDE/B408.

Positional accuracy of geocoding from residential postal codes versus full street addresses.

BACKGROUND: Postal codes are often the only geographic identifier available for assigning contextual or environmental information to a study population. This analysis assesses the influence of three factors-delivery mode type (mode of postal delivery), representative point type (source of latitude-longitude coordinates), and community size-on the accuracy of postal code spatial assignment. DATA AND METHODS: PCCF+ (Postal Code Conversion File Plus) was used to assign delivery mode type, representative point type and community size to each individual in the 2011 Census of Canada. A sample (n = 1,004) was randomly selected with a minimum of 90 observations for each category of those three factors. Based on the address information of individuals in the sample, measures of positional accuracy for geocoding from residential postal codes (PCCF+) versus reference locations as determined by full street addresses (Google Maps) were calculated using a geographic information system. Accuracy was measured as the distance that the geocoded position differed from the full street address. RESULTS: Positional accuracy was related primarily to mode of postal delivery. Rural and mixed (partly urban, partly rural) modes had much higher geocoding error than did urban modes. Rural and small-town Canada and latitude and longitude based on dissemination area centroids had low accuracy, largely because of their close relationship to rural and mixed modes of delivery. DISCUSSION: The accuracy of geocoding from postal codes can vary. Geocoding imprecision may result in misclassification, depending on the spatial resolution of the environmental or contextual measures. The spatial resolution required for a study helps to identify subpopulations that should be excluded because of inadequate positional accuracy.

Associations between fine particulate matter and mortality in the 2001 Canadian Census Health and Environment Cohort.

BACKGROUND: Large cohort studies have been used to characterise the association between long-term exposure to fine particulate matter (PM2.5) air pollution with non-accidental, and cause-specific mortality. However, there has been no consensus as to the shape of the association between concentration and response. METHODS: To examine the shape of this association, we developed a new cohort based on respondents to the 2001 Canadian census long-form. We applied new annual PM2.5 concentration estimates based on remote sensing and ground measurements for Canada at a 1km spatial scale from 1998 to 2011. We followed 2.4 million respondents who were non-immigrants aged 25-90 years and did not reside in an institution over a 10 year period for mortality. Exposures were assigned as a 3-year mean prior to the follow-up year. Income tax files were used to account for residential mobility among respondents using postal codes, with probabilistic imputation used for missing postal codes in the tax data. We used Cox survival models to determine hazard ratios (HRs) for cause-specific mortality. We also estimated Shape Constrained Health Impact Functions (a concentration-response function) for selected causes of death. RESULTS: In models stratified by age, sex, airshed, and population centre size, and adjusted for individual and neighbourhood socioeconomic variables, HR estimates for non-accidental mortality were HR = 1.18 (95% CI: 1.15-1.21) per 10µg/m3 increase in concentration. We observed higher HRs for cardiovascular disease (HR=1.25; 95% CI: 1.19-1.31), cardio-metabolic disease (HR = 1.27; 95% CI: 1.21-1.33), ischemic heart disease (HR = 1.36; 95% CI: 1.28-1.44) and chronic obstructive pulmonary disease (COPD) mortality (HR = 1.24; 95% CI: 1.11-1.39) compared to HR for all non-accidental causes of death. For non-accidental, cardio-metabolic, ischemic heart disease, respiratory and COPD mortality, the shape of the concentration-response curve was supra-linear, with larger differences in relative risk for lower concentrations. For both pneumonia and lung cancer, there was some suggestion that the curves were sub-linear. CONCLUSIONS: Associations between ambient concentrations of fine particulate matter and several causes of death were non-linear for each cause of death examined.

Sun exposure, sun protection and sunburn among Canadian adults.

BACKGROUND: Ultraviolet radiation (UVR) exposure and a history of sunburn are important risk factors for skin cancer. Sunburn is more common among men, younger age groups, and people in higher income households. Sun protection measures also vary by sex, age, and socioeconomic characteristics. Associations between ambient UVR and sunburn and sun safety measures have not been quantified. DATA AND METHODS: A total of 53,130 respondents aged 18 or older answered a Canadian Community Health Survey (CCHS) module on sun safety, which was administered in six provinces from 2005 to 2014. The module contained questions about sunburn, time in the sun, and sun protection. These respondents were linked to an ambient erythemal UVR dataset representing the June-to-August mean. Descriptive statistics and logistic regression were used to examine associations between population characteristics, sunburn, sun safety, time in the sun, and ambient UVR. RESULTS: Sunburn was reported by 33% of respondents and was more common among men, younger age groups, people who were not members of visible minorities, residents of higher income households, and individuals who were employed. On a typical summer day, a larger percentage of women than men sought shade and wore sunscreen, whereas a larger percentage of men wore a hat or long pants. As ambient summer UVR increased, women were more likely to apply sunscreen to their face, seek shade, or wear a hat (OR~1.02 to 1.09 per increase of 187 J/m² of erythemally-weighted UVR, or 5.4% of the mean); these associations were not observed among men. INTERPRETATION: Findings related to sunburn and sun protection were similar to those of previous studies. The association between ambient UVR and women's precautionary measures suggests that information about UVR may influence their decision to protect their skin.