Short-term health impacts of air pollution in Canada: a nonlinear multi-pollutant Bayesian case-crossover framework

Background: Most short-term air pollution studies rely on linear, single-pollutant models that cannot adequately describe the nonlinear and interdependent nature of pollutant-health associations. Methods: We developed a nonlinear multi-pollutant Bayesian case-crossover model to jointly evaluate short-term health effects of PM(Formula presented), NO2, and O3. The model accommodates overdispersion, propagates exposure uncertainty from imputed monitoring data, and pools Census Division (CD)-specific exposure-response functions through a Bayesian hierarchical framework. We applied this approach to cause-specific daily mortality (2001–2015) and hospitalization (2001–2018) data across 20 Canadian CDs, covering more than half of the national population. Results: The estimated exposure-response relationships varied by pollutant and health outcome. The combined PM(Formula presented) +NO2 metric showed the clearest positive associations with all non-accidental mortality and hospitalization. Respiratory hospitalization estimates were higher among seniors, but evidence of an age difference remained uncertain. An approximate 10-unit contrast in combined PM(Formula presented) +NO2 corresponded to an estimated 1.5% (95% credible interval [CrI]: 0.3, 2.2) increase in all non-accidental mortality and a 0.6% (95% CrI: 0.0, 1.3) increase in all non-accidental hospitalization, while the corresponding estimate for senior respiratory hospitalization was 2.7% (95% CrI: 0.9, 4.5). Several PM(Formula presented) and NO2 curves were nonlinear, whereas O3 associations were closer to linear over much of the observed range. Conclusion: Our study introduces a flexible epidemiologic modelling framework for quantifying the short-term health impacts of correlated pollutants. The results highlight the value of accounting for nonlinear and joint exposure patterns in multi-pollutant settings, while uncertainty remains substantial for several cause- and age-specific estimates. © The Author(s) 2026. Published by Oxford University Press on behalf of the International Epidemiological Association. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.