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

Christidis T, Erickson AC, Pappin AJ, Crouse DL, Pinault LL, Weichenthal SA, Brook JR, van Donkelaar A, Hystad P, Martin RV, Tjepkema M, Burnett RT, Brauer M.

Environ Health. 2019 Oct 10;18(1):84. doi: 10.1186/s12940-019-0518-y

Abstract

BACKGROUND:

Approximately 2.9 million deaths are attributed to ambient fine particle air pollution around the world each year (PM_2.5). In general, cohort studies of mortality and outdoor PM_2.5 concentrations have limited information on individuals exposed to low levels of PM_2.5 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 PM_2.5 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 PM_2.5.

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 PM_2.5 exposure estimates, and mortality incidence to 2016. Cox proportional hazard models were used to estimate the relationship between non-accidental mortality and ambient PM_2.5 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 PM_2.5 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 PM_2.5 were increased for males, those under age 65, and non-immigrants. Hazard ratios for PM_2.5 and mortality were attenuated when gaseous pollutants were included in models.

CONCLUSIONS:

Outdoor PM_2.5 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 PM_2.5 concentrations.

Disproportionately higher exposure to urban heat in lower-income neighborhoods: a multi-city perspective.

T Chakraborty, A Hsu, D Manya and G Sheriff.

Environmental Research Letters, Volume 14, Number 10
Focus on Sustainable Cities: Urban Solutions Towards Desired Outcomes Published 30 September 2019 • © 2019 The Author(s). Published by IOP Publishing Ltd

DOI https://doi.org/10.1088/1748-9326/ab3b99

Abstract

A growing literature documents the effects of heat stress on premature mortality and other adverse health outcomes. Urban heat islands (UHI) can exacerbate these adverse impacts in cities by amplifying heat exposure during the day and inhibiting the body’s ability to recover at night. Since the UHI intensity varies not only across, but also within cities, intra-city variation may lead to differential impact of urban heat stress on different demographic groups. To examine these differential impacts, we combine satellite observations with census data to evaluate the relationship between distributions of both UHI and income at the neighborhood scale for 25 cities around the world. We find that in most (72%) cases, poorer neighborhoods experience elevated heat exposure, an incidental consequence of the intra-city distribution of income in cities. This finding suggests that policymakers should consider designing city-specific UHI reduction strategies to mitigate its impacts on the most socioeconomically vulnerable populations who may be less equipped to adapt to environmental stressors. Since the strongest contributor of intra-urban UHI variability among the physical characteristics considered in this study is a neighborhood’s vegetation density, increasing green space in lower income neighborhoods is one strategy urban policymakers can adopt to ameliorate some of UHI’s inequitable burden on economically disadvantaged residents.

Ambient black carbon particles reach the fetal side of human placenta.

Hannelore Bové, Eva Bongaerts, Eli Slenders, Esmée M. Bijnens, Nelly D. Saenen, Wilfried Gyselaers, Peter Van Eyken, Michelle Plusquin, Maarten B. J. Roeffaers, Marcel Ameloot & Tim S. Nawrot.

Nature Communications volume 10, Article number: 3866 (2019) | Published: 17 September 2019  DOI doi.org/10.1038/s41467-019-11654-3

Abstract

Particle transfer across the placenta has been suggested but to date, no direct evidence in real-life, human context exists. Here we report the presence of black carbon (BC) particles as part of combustion-derived particulate matter in human placentae using white-light generation under femtosecond pulsed illumination. BC is identified in all screened placentae, with an average (SD) particle count of 0.95 × 10⁴ (0.66 × 10⁴) and 2.09 × 10⁴ (0.9 × 10⁴) particles per mm³ for low and high exposed mothers, respectively. Furthermore, the placental BC load is positively associated with mothers’ residential BC exposure during pregnancy (0.63–2.42 µg per m³). Our finding that BC particles accumulate on the fetal side of the placenta suggests that ambient particulates could be transported towards the fetus and represents a potential mechanism explaining the detrimental health effects of pollution from early life onwards.

Prenatal exposure to traffic-related air pollution, the gestational epigenetic clock and risk of early-life allergic sensitization.

Sbihi H, Jones MJ, MacIsaac JL, Brauer M, Allen RW, Sears MR, Subbarao P, Mandhane PJ, Moraes TJ, Azad MB, Becker AB, Brook JR, Kobor MS, Turvey SE. 

J Allergy Clin Immunol. 2019 Aug 27. pii: S0091-6749(19)31101-7. [Epub ahead of print] DOI: 10.1016/j.jaci.2019.07.047

Abstract

Prenatal exposure to traffic-related air pollution is associated with an increased risk of allergic sensitization by modifying in utero development and altering the gestational epigenetic clock.

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

Erickson AC, Brauer M, Christidis T, Pinault L, Crouse DL, van Donkelaar A, Weichenthal S, Pappin A, Tjepkema M, Martin RV, Brook JR, Hystad P, Burnett RT.

Environ Res. 2019 Aug;175:108-116. doi: 10.1016/j.envres.2019.05.010 Epub 2019 May 11.

Abstract

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 (PM_2.5) 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 PM_2.5 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 PM_2.5 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.