Association of the CUN-BAE index with glycemic outcomes in individuals with impaired fasting glucose: a retrospective multicenter Chinese cohort study.

BACKGROUND: Diabetes mellitus (DM) poses a significant global public health challenge, with impaired fasting glucose (IFG) representing a critical prediabetic state. The Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) index, a body fat estimator integrating body mass index (BMI), age, and gender, has shown promise in assessing cardiometabolic risk. However, its longitudinal association with bidirectional glycemic transitions, specifically reversion to normoglycemia and progression to DM, in individuals with IFG remains unclear. This study aimed to evaluate the association between baseline CUN-BAE index and glycemic outcomes in a Chinese IFG population. METHODS: This retrospective multicenter cohort study included 26,247 adults with baseline IFG from a health screening program. The CUN-BAE index was calculated using a standardized formula. Cox proportional hazards regression, restricted cubic spline models, and threshold effect analyses were employed to assess associations between the CUN-BAE index and glycemic outcomes, with adjustments for confounders. Subgroup and sensitivity analyses were conducted to verify robustness. RESULTS: Higher CUN-BAE index levels were independently associated with a reduced probability of reversion to normoglycemia (adjusted HR 0.99 per unit increase; 95% CI 0.98-0.99) and an increased risk of DM progression (adjusted HR 1.04; 95% CI 1.03-1.04). Nonlinear relationships were identified, with threshold effects at CUN-BAE index = 24.53 for reversion and CUN-BAE index = 22.51 for progression. The CUN-BAE index quartile analysis demonstrated a graded association, with the highest CUN-BAE index quartile showing a significantly elevated risk of diabetes and a reduced rate of reversion to normoglycemia. CONCLUSION: Higher CUN-BAE index levels are strongly and independently associated with adverse glycemic transitions in IFG individuals, with higher values indicating poorer outcomes. Its nonlinear associations and threshold effects support its utility for risk stratification and personalized intervention strategies in prediabetes management.