{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T04:31:55Z","timestamp":1786422715975,"version":"build-2736575974"},"reference-count":57,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T00:00:00Z","timestamp":1786406400000},"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>Objective<\/jats:title>\n                    <jats:p>To examine the correlation among pre-pregnancy body mass index (BMI), BMI increments during different gestational periods, and the occurrence of macrosomia in singleton full-term pregnant women without complications. Additionally, we aimed to assess the predictive performance of these BMI-related indicators for macrosomia, thereby identifying key time windows for targeted gestational weight management.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>An analytical approach was adopted, entailing a retrospective evaluation of clinical data from 4,218 pregnant women without complications who underwent regular prenatal examinations and singleton full-term delivery during the period between January 2019 and December 2025 at the Jinshan Branch of Shanghai Sixth People\u2019s Hospital. Based on neonatal birth weight, a case-control design was employed, selecting 200 cases of macrosomia (macrosomia group) and 250 cases of normal birth weight infants (control group). Data including pre-pregnancy BMI, baseline BMI at the first prenatal visit (10\u201313 weeks), and BMI at various stages of mid- and late-pregnancy (20, 24, 28, 32, 36 weeks, and before delivery) were collected to calculate BMI increments for each stage. The predictive efficacy of individual BMI indicators and a combined model for macrosomia was evaluated using independent sample t-tests, Pearson correlation analysis (PCA), and receiver operating characteristic (ROC) curves.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>(1) Increased pre-pregnancy BMI was significantly and positively correlated with an increased macrosomia risk. Pre-pregnancy overweight (OR\u00a0=\u00a02.63) and obesity (OR\u00a0=\u00a09.06) emerged as independent risk contributors for macrosomia (P &amp;lt; 0.01). (2) Baseline BMI at 10\u201313 weeks, along with BMI increments during the 32\u201336 weeks period and the period from 36 weeks to delivery, exhibited a significant increase in the macrosomia group in comparison to the control group (P &amp;lt; 0.05). (3) The analysis of correlation demonstrated a moderate positive correlation between baseline BMI at 10\u201313 weeks and neonatal birth weight (r = 0.386, P &amp;lt; 0.001). However, no significant correlation was identified between mid-pregnancy BMI increments and birth weight (P &amp;gt; 0.05). (4) Utilising ROC curve analysis, it was ascertained that baseline BMI at 10\u201313 weeks exhibited the most optimal predictive efficacy among the individual indicators (AUC\u00a0=\u00a00.73), with the late-pregnancy increment indicators following in succession. The combined predictive model, integrating early-pregnancy BMI and late-pregnancy BMI increments, achieved a superior AUC of 0.84.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Pre-pregnancy BMI, early-pregnancy (10\u201313 weeks) BMI, and late-pregnancy (32 weeks to delivery) BMI increments are critical predictors of macrosomia in pregnant women without complications. Specifically, baseline BMI at 10\u201313 weeks serves as a core indicator for early risk identification. Clinical interventions should focus on these two critical stages\u2014early and late pregnancy\u2014to implement individualized weight management, thereby effectively reducing the incidence of macrosomia and improving maternal and neonatal outcomes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1875915","type":"journal-article","created":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T04:21:29Z","timestamp":1786422089000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Identifying critical windows for macrosomia prevention: a study on the association between phase-specific dynamic BMI changes and macrosomia risk"],"prefix":"10.3389","volume":"17","author":[{"given":"Huiling","family":"Qu","sequence":"first","affiliation":[{"name":"Department of Obstetrics and Gynecology, Jinshan Branch of Shanghai Sixth People\u2019s Hospital","place":["Shanghai, 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