Inequities in ambient fine particulate matter: A spatiotemporal analysis in Canadian communities

Megan Kirby-McGregor; Chen Chen; Hong Chen; Tarik Benmarhnia; Jay S Kaufman

doi:10.1016/j.scitotenv.2022.159766

Inequities in ambient fine particulate matter: A spatiotemporal analysis in Canadian communities

Sci Total Environ. 2023 Feb 1;858(Pt 1):159766. doi: 10.1016/j.scitotenv.2022.159766. Epub 2022 Oct 26.

Authors

Megan Kirby-McGregor¹, Chen Chen², Hong Chen³, Tarik Benmarhnia⁴, Jay S Kaufman¹

Affiliations

¹ Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Canada.
² Scripps Institution of Oceanography, University of California, San Diego, USA. Electronic address: chc048@ucsd.edu.
³ Environmental Health Science and Research Bureau, Health Canada, Canada.
⁴ Scripps Institution of Oceanography, University of California, San Diego, USA.

PMID: 36309259
DOI: 10.1016/j.scitotenv.2022.159766

Abstract

Background: Exposure to fine particulate matter (PM_2.5) is associated with adverse health outcomes but communities are not randomly exposed to PM_2.5. Previous cross-sectional environmental injustice analyses in Canada found disproportionately higher exposure to PM_2.5 in low-income populations, visible minorities and immigrants. Beyond static surveillance, it is also important to evaluate how changes in PM_2.5 exposure over time may differentially impact disadvantaged communities. We examine whether communities with different sociodemographic characteristics benefited equitably from the overall decreases in ambient concentrations of PM_2.5 from 2001 to 2016 in Canada.

Methods: We derived census tract level estimates of average annual PM_2.5 using validated satellite-based estimations of annual average PM_2.5 concentration surfaces. We investigated how the spatial distribution of PM_2.5 has evolved over 15 years (2001-2016) by comparing absolute values and rank percentiles of census tract level annual average PM_2.5 concentrations in 2001 and 2016. Using decennial census data and multivariable linear regression, we determined if sociodemographic characteristics are associated with changes in exposure to PM_2.5, accounting for geographic boundary changes between census periods.

Results: Overall, ambient PM_2.5 concentrations decreased from 2001 (median of 9.1 μg/m³) to 2016 (median of 6.4 μg/m³), with varying provincial patterns. Across communities, ranked census tract specific PM_2.5 in 2001 and in 2016 are highly correlated (Spearman's rho = 0.75). We found that, on average and accounting for provincial differences and baseline PM_2.5, communities with greater density of aboriginal population, lower education, higher shelter-cost-to-income ratio, unemployment or lower income experienced smaller absolute decreases in PM_2.5 from 2001 to 2016.

Conclusions: Identifying sociodemographic groups that benefit least from decreasing exposure to PM_2.5 highlights the need to consider environmental injustice when designing or revising air pollution policies.

Keywords: Air pollution; Canada; Environmental justice; Inequity; Social determinants of health; Social disadvantage.

MeSH terms

Air Pollutants* / analysis
Air Pollution* / analysis
Canada / epidemiology
Cross-Sectional Studies
Environmental Exposure / analysis
Particulate Matter / analysis
Spatio-Temporal Analysis

Substances

Particulate Matter
Air Pollutants