{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T20:23:22Z","timestamp":1791491002768,"version":"4.3.4"},"reference-count":33,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,7,16]],"date-time":"2025-07-16T00:00:00Z","timestamp":1752624000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Air pollution remains one of the leading environmental risk factors for human health globally, significantly contributing to the burden of disease and premature mortality. The relationship between air pollutants and non-accidental deaths in Guiyang was unclear.<\/jats:p><\/jats:sec><jats:sec><jats:title>Method<\/jats:title><jats:p>Descriptive analysis was conducted to characterize air pollutants and mortality trends during the study period. A time-stratified case-crossover design and a quasi-Poisson regression within a generalized additive model (GAM) framework were employed to examine the association between air pollution and mortality. The models incorporated a 7-day lag structure and adjusted for temporal trends, meteorological factors, and day of the week. Analyses were further stratified by cause-specific mortality, age group, sex, and seasonaty as an endpoint for acute health effects, stratified by cause-specific mortality, age, sex and season.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>SO\u2082 exposure was associated with a 3.18% (95% CI: 1.95 to 4.42%) increase in excess risk (ER) for non-accidental mortality per 10\u202f\u03bcg\/m<jats:sup>3<\/jats:sup> increase, with risks peaking at lag 1 and cumulative effects persisting beyond 7\u202fdays. NO\u2082 exposure resulted in a 2.87% (95% CI: 1.72 to 4.03%) ER increase, peaking at lag 1, with effects extending to lag 7. PM\u2082.\u2085 and PM\u2081\u2080 exposure resulted in ER increases of 1.42% (95% CI: 0.84 to 1.99%) and 0.86% (95% CI: 0.50 to 1.22%), respectively, peaking within 1\u20132\u202fdays. CO exposure was associated with a 1.64% (95% CI: 1.01 to 2.29%) ER increase per 0.1\u202fmg\/m<jats:sup>3<\/jats:sup>, with effects observed at lag 0. Females showed higher susceptibility to SO\u2082 (ER: 3.87, 95% CI: 2.05 to 5.72%), while males were more vulnerable to PM\u2082.\u2085 (ER: 1.80, 95% CI: 1.10 to 2.51%). Individuals aged \u226565\u202fyears exhibited elevated risks across all pollutants, particularly SO\u2082 (ER: 4.16, 95% CI: 2.73 to 5.61%). All pollutants contributed to excess mortality in the cold season.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Different pollutants exhibit different lag durations of excess risks and cumulative excess risks for non-accidental mortality and deaths related to circulatory and respiratory systems. Females showed greater susceptible to SO<jats:sub>2<\/jats:sub>, while males were more vulnerable to other pollutants. The individuals aged 65\u202fyears and older were particularly vulnerable populations.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpubh.2025.1602900","type":"journal-article","created":{"date-parts":[[2025,7,16]],"date-time":"2025-07-16T05:34:44Z","timestamp":1752644084000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Association between air pollution and non-accidental mortality in Guiyang, China: a time-series analysis (2013\u20132023)"],"prefix":"10.3389","volume":"13","author":[{"given":"Xuanhao","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minmin","family":"Su","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minlan","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zihai","family":"Jian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruifang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianhua","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,7,16]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e069487","DOI":"10.1136\/bmj-2021-069487","article-title":"Reducing 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