Association of metabolic score for insulin resistance with gestational diabetes mellitus: a multicenter cohort study.

Background: The metabolic score for insulin resistance (METS-IR) is a novel and effective indicator for assessing insulin resistance. Previous studies have shown that METS-IR is positively associated with the risk of type 2 diabetes. However, the association between METS-IR and gestational diabetes mellitus (GDM) has not yet been clearly clarified. This study aims to investigate the association between METS-IR and GDM as well as its related adverse pregnancy outcomes and to evaluate its predictive value. Methods: A total of 37,770 singleton pregnant women from three hospitals in China between January 2018 and June 2024 were included in the study. METS-IR was calculated using the formula: ln ([high-density lipoprotein cholesterol (HDL-C) (mg/dL)] × [2 × fasting glucose (mg/dL)] + TG (mg/dL) × BMI (kg/m2)). Participants were divided into four groups according to METS-IR quartiles. Multivariable logistic regression models, smoothed curve fitting, and subgroup analyses were conducted to assess the associations between METS-IR and GDM as well as related adverse pregnancy outcomes. The receiver operating characteristic (ROC) curves were used to evaluate the predictive performance. Results: After adjusting for potential confounders, higher METS-IR levels were significantly associated with an increased risk of GDM. Compared with the lowest quartile group (Q1), the risks of GDM in the Q2, Q3, and Q4 groups increased by 13% (OR = 1.13, 95% CI: 1.02-1.25), 59% (OR = 1.59, 95% CI: 1.44-1.75), and 165% (OR = 2.65, 95% CI: 2.42-2.91), respectively. Similar associations were also observed between METS-IR and preterm birth, macrosomia, gestational diabetes mellitus (GDM) complicated with preeclampsia (GDM&PE), and pharmacologically treated GDM class A2 (GDMA2). Smoothed curve fitting suggested an approximately linear dose-response relationship between METS-IR and GDM. Subgroup analysis indicated that the association between METS-IR and GDM remained consistent across different age groups (interaction p > 0.05), with a higher GDM risk observed among women aged ≥35 years. The ROC analysis showed that the areas under the curve (AUCs) of METS-IR for predicting GDM, preterm birth, macrosomia, GDM&PE, and GDMA2 were 0.623, 0.532, 0.640, 0.741, and 0.712, respectively. Conclusion: This study demonstrated that METS-IR is positively associated with GDM risk and its related adverse pregnancy outcomes. METS-IR may serve as a useful tool for risk stratification and early intervention in clinical practice for GDM.