METHODS: Three hundred individuals aged 18-55 years of both sexes were selected for this cross-sectional study. VF was evaluated as a part of body composition analysis using BIA. The body composition variables for the prediction of prediabetes were examined using backward logistic regression. Optimal cut-off levels of VF to predict prediabetes were identified using receiver operator characteristic curve (ROC) analysis.
RESULTS: VF, total fat, and age were found to be associated with prediabetes (p ≤ 0.05). In females, the cut-off value of VF for predicting prediabetes was identified as 8 with 77.8% sensitivity and 69.3% specificity; in males, it was 11 with 84% sensitivity and 62.9% specificity.
CONCLUSION: This study contributes to the sex-specific cut-off values of VF level on BIA that can be used for predicting prediabetes in the Indian population.