{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T07:03:57Z","timestamp":1790233437860,"version":"4.1.0"},"reference-count":21,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:00:00Z","timestamp":1790035200000},"content-version":"vor","delay-in-days":35,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Health Canada through the federal Air Quality Program","award":["AQP-810666"],"award-info":[{"award-number":["AQP-810666"]}],"id":[{"id":"https:\/\/ror.org\/05p8nb362","id-type":"ROR","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPIN-2022\u201305164"],"award-info":[{"award-number":["RGPIN-2022\u201305164"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPIN-2025\u201306302"],"award-info":[{"award-number":["RGPIN-2025\u201306302"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We developed a nonlinear multi-pollutant Bayesian case-crossover model to jointly evaluate short-term health effects of PM\u00a02.5, 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\u20132015) and hospitalization (2001\u20132018) data across 20 Canadian CDs, covering more than half of the national population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The estimated exposure-response relationships varied by pollutant and health outcome. The combined PM\u00a02.5+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\u00a02.5+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\u00a02.5 and NO2 curves were nonlinear, whereas O3 associations were closer to linear over much of the observed range.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ije\/dyag194","type":"journal-article","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T11:40:00Z","timestamp":1787658000000},"source":"Crossref","is-referenced-by-count":0,"title":["Short-term health impacts of air pollution in Canada: a nonlinear multi-pollutant Bayesian case-crossover framework"],"prefix":"10.1093","volume":"55","author":[{"given":"Guowen","family":"Huang","sequence":"first","affiliation":[{"name":"Department of Statistical and Actuarial Sciences, Western University , London, Ontario,","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick E","family":"Brown","sequence":"additional","affiliation":[{"name":"Centre for Global Health Research, St Michael\u2019s Hospital , Toronto, Ontario,","place":["Canada"]},{"name":"Department of Statistical Sciences, University of Toronto , Toronto, Ontario,","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hwashin Hyun","family":"Shin","sequence":"additional","affiliation":[{"name":"Environmental Health Science and Research Bureau, Health Canada , Ottawa, Ontario,","place":["Canada"]},{"name":"Department of Mathematics and Statistics, Queen\u2019s University , Kingston, Ontario,","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,9,22]]},"reference":[{"key":"2026092402425767500_dyag194-B1","author":"World Health Organization"},{"key":"2026092402425767500_dyag194-B2","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1186\/1476-069X-12-43","article-title":"Long-term air pollution exposure and cardio-respiratory mortality: a 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