{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T05:06:19Z","timestamp":1789707979634,"version":"4.0.1"},"reference-count":30,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T00:00:00Z","timestamp":1789689600000},"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. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      Low birthweight remains a global public health challenge. While maternal exposure to certain air pollutants is known to adversely affect fetal growth, the association with sulfur dioxide (SO\n                      <jats:sub>2<\/jats:sub>\n                      ) has been inconsistent. The COVID-19 lockdown provided a unique quasi-natural experiment to reassess the relationship under altered emission patterns.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We conducted a retrospective cohort study of 21, 777 term singleton births in Southern Zhejiang Province, East China, from 2020 to 2022. We estimated maternal SO\n                      <jats:sub>2<\/jats:sub>\n                      exposure using a time-activity weighted model based on residential and work addresses. Associations with low and high birthweight risks were evaluated using linear regression and odds ratios. Three machine learning models were used to assess whether incorporating SO\n                      <jats:sub>2<\/jats:sub>\n                      exposure improved birthweight prediction accuracy.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The COVID-19 lockdown was associated with a significant 28% reduction in annual mean atmospheric SO\n                      <jats:sub>2<\/jats:sub>\n                      levels. Maternal SO\n                      <jats:sub>2<\/jats:sub>\n                      exposure during the third trimester showed the most substantial negative association with birthweight, particularly in female neonates, and was associated with increased odds of LBW in both sexes. Feature importance showed SO\n                      <jats:sub>2<\/jats:sub>\n                      played a modest but nonnegligible role. Adding SO\n                      <jats:sub>2<\/jats:sub>\n                      exposure as a predictor improved birthweight prediction, with XGBoost achieving the highest accuracy.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      We found the susceptible windows of maternal SO\n                      <jats:sub>2<\/jats:sub>\n                      exposure for birthweight reduction and LBW risks. Incorporating air pollution exposure into predictive models can enhance the identification of high-risk pregnancies, supporting targeted clinical and environmental interventions.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1954694","type":"journal-article","created":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T04:34:21Z","timestamp":1789706061000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Maternal SO2 exposure and birthweight reduction during COVID-19 lockdown and quarantine in East China"],"prefix":"10.3389","volume":"17","author":[{"given":"Rui","family":"Feng","sequence":"first","affiliation":[{"name":"School of Engineering, Hangzhou Normal University","place":["Hangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengbing","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University","place":["Hangzhou, China"]},{"name":"Zhejiang Key Laboratory of Precise Protection and Promotion of Fertility","place":["Hangzhou, China"]},{"name":"Zhejiang Provincial Clinical Research Center for Reproductive Health and Disease","place":["Hangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinhui","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Public Health, Zhejiang University School of Medicine","place":["Hangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiandong","family":"Shen","sequence":"additional","affiliation":[{"name":"Hangzhou Environmental Monitoring Central Station","place":["Hangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cuiyu","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, School of 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