BMI-C as a Predictor of Type 2 Diabetes: Validation in Two Independent NHANES Cohorts (2015-16 and 2017-18)

Objective: To validate BMI-C (Body Morphometric Index – Corrected) as a predictor of Type 2 Diabetes (T2D) in two independent cohorts of the North American population, and to compare its performance with that of traditional body mass index (BMI). Methods: Cross-sectional study using NHANES 2015-16 (N=6,321) and 2017-18 (N=6,015) data. BMI-C was calculated using the proprietary algorithm available at bmi-c.com, using waist circumference (cm), height (cm), weight (kg), age (years), and sex as inputs. T2D was defined by self-reported diagnosis, use of insulin or oral hypoglycemic agents, HbA1c ≥ 6.5%, or fasting glucose ≥ 126 mg/dL. ROC curves, age- and sex-adjusted logistic regression, and relative risk by category were calculated. BMI was calculated as weight/height² for comparison. The 95% CI of AUCs was estimated by bootstrap (2,000 resamples). Results: T2D prevalence was 15.0% (2015-16) and 13.3% (2017-18). BMI-C showed an AUC of 0.738 (95% CI: 0.723–0.755) and 0.719 (95% CI: 0.702–0.736), respectively. BMI showed an AUC of 0.687 (95% CI: 0.670–0.704) and 0.662 (95% CI: 0.642–0.681). The AUC difference was +0.051 and +0.057. The optimal BMI-C cut-off was 1.32 and 1.29; the optimal BMI cut-off was 26.7 and 27.8 kg/m². The age- and sex-adjusted odds ratio for BMI-C was 12.48 (95% CI: 7.85–19.86) and 18.58 (95% CI: 11.47–30.09). The dose-response relationship was consistent across cohorts: T2D risk ranged from 2.1% (BMI-C 0.8–0.9) to 42.9% (BMI-C 1.8–1.9) in 2015-16, and from 0.0% to 33.0% in 2017-18. Conclusion: BMI-C is a robust and replicable predictor of T2D, with performance consistently superior to BMI across two independent cohorts. Its low cost and simplicity make it viable for initial screening in primary care, complementing — not replacing — laboratory-based diagnostic tests.