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Gestational diabetes status modifies pre-pregnancy BMI associations with large for gestational age: A prospective
Yuhang Wu1, Jiye Zhang1, Xiaochan Wang2
1Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, Hunan, China.
Objective:
The differential impact of pre-pregnancy body mass index (BMI) on large for gestational age (LGA) risk by gestational diabetes mellitus (GDM) status remains unquantified. We aimed to assess whether GDM modifies the association between pre-pregnancy BMI and LGA to inform precision prevention strategies.
Methods:
In this prospective cohort study, 34 031 pregnant women enrolled at Hunan Provincial Maternal and Child Health Care Hospital (2013-2019) were stratified by GDM status. Multivariable logistic regression and restricted cubic spline (RCS) models adjusted for sociodemographic, behavioral, and clinical covariates evaluated the association between pre-pregnancy BMI and LGA.
Results:
LGA incidence was significantly higher in GDM than non-GDM pregnancies (14.8% vs. 11.9%, P < 0.001). Adjusted models demonstrated a steeper BMI-LGA dose-response gradient in GDM: each 1-unit BMI increase conferred 20% higher odds (adjusted odds ratio [aOR]: 1.20, [95% confidence interval [CI]: 1.17, 1.23]) versus 11% in non-GDM pregnancies (aOR: 1.11, [1.09, 1.12]). Obesity amplified LGA risk more substantially in GDM (aOR: 6.66, [4.27, 10.39]) than non-GDM pregnancies (aOR: 2.78, [2.00, 3.87]). RCS models revealed nonlinear BMI-LGA trajectories in both cohorts (reference level: 21.05 for GDM and 26.18 for non-GDM). Associations remained consistent across demographic subgroups. Notably, significant interaction effects occurred exclusively in non-GDM pregnancies, with multigravida (aOR: 1.13) exhibiting a stronger BMI-LGA association than primigravida (aOR: 1.08).
Conclusion:
GDM status significantly modifies the relationship between pre-pregnancy BMI and LGA risk, identifying a threshold that substantially increases risk in women with GDM and revealing subgroup-specific vulnerabilities. These findings suggest that incorporating pre-pregnancy BMI and estimated risk of developing GDM into early risk stratification can help identify high-risk pregnancies, thereby guiding targeted antenatal monitoring and individualized interventions of varying stringency to prevent LGA.
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