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We used a multivariable Cox proportional hazards regression model to analyze data from UK Biobank to determine the relationship between long-term exposure to air pollutants\u2013nitric oxide (NO), nitrogen dioxide (NO<jats:sub>2<\/jats:sub>), and 2.5-<jats:italic>\u00b5<\/jats:italic>m and 10-<jats:italic>\u00b5<\/jats:italic>m particulate matter (PM<jats:sub>2.5<\/jats:sub> and PM<jats:sub>10<\/jats:sub>) and the risk of laryngeal cancer. In multivariable-adjusted models, in model 3 and compared with the participants with lower quintile scores for air pollution, the participants with the highest quintile scores for air pollution had a higher laryngeal cancer risk. The observed association was more pronounced among the participants who were female, were smokers, had a systolic blood pressure equal to or greater than 120\u00a0mmHg, and had diabetes. Compared with the participants with a low GRS and the lowest quintile score for air pollution exposure, those with an intermediate GRS and the highest quintile score for air pollution exposure had a higher risk of laryngeal cancer. Long-term exposure to NO<jats:sub>2<\/jats:sub>, NO, or PM<jats:sub>2.5<\/jats:sub>, individually or jointly, was associated with a risk of incident laryngeal cancer, especially in the participants with an intermediate GRS.<\/jats:p>","DOI":"10.1007\/s11356-023-26519-y","type":"journal-article","created":{"date-parts":[[2023,3,28]],"date-time":"2023-03-28T17:02:52Z","timestamp":1680022972000},"page":"58295-58303","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Association between long-term exposure to air pollution and the risk of incident laryngeal cancer: a\u00a0longitudinal UK Biobank-based study"],"prefix":"10.1007","volume":"30","author":[{"given":"Jiada","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yidian","family":"Chu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongxia","family":"Deng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhisen","family":"Shen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,3,28]]},"reference":[{"issue":"7726","key":"26519_CR1","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41586-018-0579-z","volume":"562","author":"C Bycroft","year":"2018","unstructured":"Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K et al (2018) The UK Biobank resource with deep phenotyping and genomic data. 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