CUN-BAE adiposity index prediction of incident type 2 diabetes: the Seguimiento Universidad de Navarra prospective cohort

Background: Obesity is currently a pandemic and a cardinal risk factor for incident diabetes, a parallel growing pandemic. Measures commonly used to define obesity, i.e., BMI and waist circumference, do not accurately reflect body fatness. Methods: We examined the prognostic value of body fatness assessed with the ‘Clínica Universidad de Navarra-Body Adiposity Estimator’ (CUN-BAE, range: 18.4–65.0 %) in 18,594 participants of the “Seguimiento Universidad de Navarra” prospective longitudinal cohort (60.5% women) without diabetes at baseline. Participants were followed-up with biennial questionnaires and multivariable-adjusted Cox models were used to estimate incident diabetes. Results: During 13.7 years of median follow-up, 209 participants developed diabetes. Progressively ascending quartiles of CUN-BAE were significantly associated with incident diabetes in multivariable-adjusted models, even after adjusting for BMI > 30 kg/m2. For each 2-unit increment in the CUN-BAE index, diabetes risk relatively increased by 46% in men and women (95% CI: 33%–62%). When comparing ROC AUC for CUN-BAE and BMI the association was stronger for CUN-BAE (p < 0.001). Conclusions: CUN-BAE index, an easy equation that can be used in any clinical setting, predicted better the risk of incident diabetes compared to BMI. Our results emphasize the importance of reducing and maintaining a low adiposity in order to prevent diabetes.