{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T14:16:53Z","timestamp":1791901013102,"version":"4.3.4"},"reference-count":67,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2021,5,18]],"date-time":"2021-05-18T00:00:00Z","timestamp":1621296000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41925006"],"award-info":[{"award-number":["41925006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Exposure to air pollution has been suggested to be associated with an increased risk of women\u2019s health disorders. However, it remains unknown to what extent changes in ambient air pollution affect gynecological cancer. In our case\u2013control study, the logistic regression model was combined with the restricted cubic spline to examine the association of short-term exposure to air pollution with gynecological cancer events using the clinical data of 35,989 women in Beijing from December 2008 to December 2017. We assessed the women\u2019s exposure to air pollutants using the monitor located nearest to each woman\u2019s residence and working places, adjusting for age, occupation, ambient temperature, and ambient humidity. The adjusted odds ratios (ORs) were examined to evaluate gynecologic cancer risk in six time windows (Phase 1\u2013Phase 6) of women\u2019s exposure to air pollutants (PM2.5, CO, O3, and SO2) and the highest ORs were found in Phase 4 (240 days). Then, the higher adjusted ORs were found associated with the increased concentrations of each pollutant (PM2.5, CO, O3, and SO2) in Phase 4. For instance, the adjusted OR of gynecological cancer risk for a 1.0-mg m\u22123 increase in CO exposures was 1.010 (95% CI: 0.881\u20131.139) below 0.8 mg m\u22123, 1.032 (95% CI: 0.871\u20131.194) at 0.8\u20131.0 mg m\u22123, 1.059 (95% CI: 0.973\u20131.145) at 1.0\u20131.4 mg m\u22123, and 1.120 (95% CI: 0.993\u20131.246) above 1.4 mg m\u22123. The ORs calculated in different air pollution levels accessed us to identify the nonlinear association between women\u2019s exposure to air pollutants (PM2.5, CO, O3, and SO2) and the gynecological cancer risk. This study supports that the gynecologic risks associated with air pollution should be considered in improved public health preventive measures and policymaking to minimize the dangerous effects of air pollution.<\/jats:p>","DOI":"10.3390\/ijerph18105353","type":"journal-article","created":{"date-parts":[[2021,5,18]],"date-time":"2021-05-18T06:01:33Z","timestamp":1621317693000},"page":"5353","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Relationship between Air Pollutant Exposure and Gynecologic Cancer Risk"],"prefix":"10.3390","volume":"18","author":[{"given":"Qiwei","family":"Yu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4175-7590","authenticated-orcid":false,"given":"Liqiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Hou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingwen","family":"Li","sequence":"additional","affiliation":[{"name":"Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suhong","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ke","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8055-3101","authenticated-orcid":false,"given":"Yang","family":"Cheng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,18]]},"reference":[{"key":"ref_1","first-page":"102","article-title":"PM2.5 in Beijing-Temporal Pattern and Its Association with Influenza","volume":"13","author":"Liang","year":"2014","journal-title":"Environ. 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