GDM increases maternal and fetal complication risks. Fat distribution may predict risk better than total adiposity. While BMI is common, indices like BAI, ABSI, and adiposity percentage may add predictive value. This study compares these indices for GDM prediction and tests whether BMI remains the strongest predictor. To compare body fat indices in predicting gestational diabetes mellitus (GDM). This prospective study was conducted at a tertiary hospital between March 2024 and November 2024. Pregnant patients presenting during the first trimester were included. Clinical and demographic data, waist and hip circumferences, height, weight, high-density lipoprotein, and triglyceride levels were recorded for each participant. Body mass index (BMI), body adiposity index (BAI), a-type body shape index (ABSI), and adiposity percentage were calculated. Between the 24th and 28th gestational weeks, a 75-gram oral glucose tolerance test was administered. Based on the results, the patients were grouped as GDM-positive or GDM-negative. Clinical and demographic characteristics, as well as height measurements, were similar between the two groups. However, there were statistically significant differences in relation to weight, hip circumference, waist circumference, BMI, BAI, ABSI, and adiposity percentage (p < 0.005). The ROC analysis revealed that the optimal cut-off value for BMI in predicting GDM was 25.5, with 78% sensitivity and 60% specificity. For BAI, the optimal cut-off value was 30.45, with 72% sensitivity and 64% specificity. The optimal cut-off value for ABSI was 0.069 with61% sensitivity and 48% specificity. Adiposity percentage had an optimal cut-off value of 14.47, with 72% sensitivity and 74% specificity. BMI, BAI, ABSI, and adiposity percentage are effective formulas for predicting GDM. Among these, BMI remains the most effective predictor.
Özdal et al. (Tue,) studied this question.