AUTHOR=López-Plaza Bricia , Larrad-Sainz Angélica , Valerio Johanna , O’Connor Rocío Martín , del Valle Laura , Ramos-Levi Ana M. , Barabash Ana , Marcuello Clara , Jiménez-Varas Inés , Rubio-Herrera Miguel A. , Matía-Martín Pilar , Calle-Pascual Alfonso L. 

TITLE=Body composition as a complementary tool for detection of metabolic syndrome 6 years postpartum: a St. Carlos Cohort follow-up

JOURNAL=Frontiers in Nutrition

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2025.1689658

DOI=10.3389/fnut.2025.1689658

ISSN=2296-861X

ABSTRACT=Background and aimsGestational diabetes mellitus (GDM) is a prevalent pregnancy complication associated with long-term cardiometabolic risk, including metabolic syndrome (MetS). This study aimed to assess differences in body composition and metabolic health 6 years postpartum based on prior GDM diagnosis and to identify body composition cut-off values predictive of MetS.MethodsThis cross-sectional analysis included 604 women from the prospective St. Carlos Cohort in Spain, who had no subsequent pregnancies and complete body composition data 6 years postpartum. Body composition was assessed using bioelectrical impedance analysis (BIA), and MetS was diagnosed per harmonized criteria. Statistical analyses included ROC curves to establish diagnostic accuracy and optimal cut-off points.ResultsWomen with prior GDM had a twofold increased risk of developing MetS (26.6 vs. 14.6%). However, waist circumference or elevated BMI and waist-to-height ratio were not significantly different between groups. ROC analysis identified that body composition parameters, particularly fat mass (FM), visceral fat, and FM/Fat Free Mass ratio, as having high predictive value for MetS, regardless of GDM history (AUC ≥ 0.8). Women with MetS showed significantly higher FM and lower relative muscle mass and function. Diagnostic models showed high negative predictive values (≥90%) for most body composition parameters making them effective for excluding MetS.ConclusionGDM is a significant predictor of MetS. However, body composition, especially increased adiposity and reduced relative muscle mass, provides valuable clinical insights beyond traditional anthropometric measures in postpartum women. The proposed cut-off values for body composition parameters may serve as effective, non-invasive tools for early MetS detection in postpartum care.