{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T15:21:01Z","timestamp":1783092061987,"version":"3.54.6"},"reference-count":42,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T00:00:00Z","timestamp":1783036800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100014895","name":"Southwest Medical University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100014895","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Pediatr."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aims to systematically evaluate the primary influencing factors of birth defects in China from 2019 to 2025, providing evidence for decision-making and intervention measures in the prevention of birth defects.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A comprehensive search was conducted in various databases, including CNKI, Wanfang, VIP, China Biomedical Literature Database, PubMed, Web of Science, Embase, Elsevier Science Direct, and CINAHL, covering literature published from January 2019 to December 2025. Two researchers independently performed literature screening, quality assessment, and data extraction. Meta-analysis was conducted using Stata 17.0 software. For factors exhibiting high heterogeneity (\n                      <jats:italic>I<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u2009\u2265\u200950%) and with at least four included studies, subgroup analyses were carried out based on the types of birth defects, study regions, or study quality. This review adhered to the PRISMA 2020 guidelines.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 25 studies were included in this analysis, comprising 26,019 cases of birth defects. Seventeen influencing factors were identified. Maternal physiological factors included maternal age \u226535 years (OR\u2009=\u20091.26, 95% CI: 1.05\u20131.47), maternal BMI\u2009&amp;gt;\u200930\u2005kg\/m\n                      <jats:sup>2<\/jats:sup>\n                      (OR\u2009=\u20091.42, 95% CI: 1.25\u20131.58), and maternal drug use (OR\u2009=\u20091.06, 95% CI: 0.58\u20131.54). Healthcare service factors encompassed premarital examinations (OR\u2009=\u20090.36, 95% CI: 0.30\u20130.43), pregnancy examinations (OR\u2009=\u20090.41, 95% CI: 0.21\u20130.62), and birth examinations (OR\u2009=\u20090.45, 95% CI: 0.28\u20130.62). Nutritional and behavioral factors included irregular folic acid supplementation (OR\u2009=\u20091.32, 95% CI: 0.09\u20132.55; for neural tube defects: OR\u2009=\u20092.34, 95% CI: 2.01\u20132.72,\n                      <jats:italic>I<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u2009=\u20090%), a history of medication in early pregnancy (OR\u2009=\u20091.17, 95% CI: 0.65\u20131.69), a history of fever in early pregnancy (OR\u2009=\u20091.19, 95% CI: 0.86\u20131.52), adverse mood during pregnancy (OR\u2009=\u20091.09, 95% CI: 0.17\u20132.01), exposure to harmful substances (OR\u2009=\u20091.45, 95% CI: 1.04\u20131.87), and contraceptive use within 6 months prior to pregnancy (OR\u2009=\u20091.36, 95% CI: 1.29\u20131.44). Other factors included income &amp;lt;5,000 yuan (OR\u2009=\u20091.41, 95% CI: 0.90\u20131.93), preterm birth (OR\u2009=\u20091.07, 95% CI: 0.04\u20132.10; stronger for congenital heart disease: OR\u2009=\u20091.82, 95% CI: 1.64\u20132.02), being small for gestational age (OR\u2009=\u20091.38, 95% CI: 0.74\u20132.01), adverse pregnancy history (OR\u2009=\u20091.03, 95% CI: 0.58\u20131.48), and a family history of genetic disorders (OR\u2009=\u20091.10, 95% CI: 0.81\u20131.39). Subgroup analyses indicated that after categorizing by types of birth defects, the heterogeneity of factors such as adverse pregnancy history, preterm birth, history of fever in early pregnancy, and irregular folic acid supplementation was significantly reduced, resulting in more stable pooled effect sizes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Numerous factors influence the occurrence of birth defects. Medical professionals should prioritize addressing irregular folic acid supplementation, low rates of premarital examinations, and regional disparities in prenatal care as key intervention targets in China. It is essential to implement targeted interventions on controllable factors to prevent and reduce the incidence of birth defects.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fped.2026.1842814","type":"journal-article","created":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T14:54:09Z","timestamp":1783090449000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Maternal, healthcare, and nutritional factors influencing birth defects in China from 2019 to 2025: a systematic review and meta-analysis"],"prefix":"10.3389","volume":"14","author":[{"given":"Min","family":"Yang","sequence":"first","affiliation":[{"name":"School of Nursing, Southwest Medical University","place":["Luzhou, Sichuan, China"]},{"name":"Department of Obstetrics, Affiliated Hospital of Southwest Medical University","place":["Luzhou, Sichuan, 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