CUN‑BAE predicts risk of metabolic dysfunction–associated steatotic liver disease: A prospective cohort study in non‑obese Chinese adults

While metabolic dysfunction-associated steatotic liver disease (MASLD) increasingly affects non-obese individuals, current screening approaches show poor performance in this population. We investigated whether the Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) could better identify MASLD risk than traditional measures in non-obese adults, and examined how the triglyceride-glucose (TyG) index might mediate this relationship. Using data from the Dryad public database, we followed 16,173 Chinese non-obese adults (BMI < 25 kg/m²) without baseline MASLD for 5 years. MASLD diagnosis relied on abdominal ultrasonography. We applied multivariable logistic regression to assess cross-sectional associations and Cox models for incident disease risk. Restricted cubic splines revealed dose-response patterns in sex-stratified analyses, while structural equation modeling quantified TyG index mediation effects. Our cohort included 8,483 men and 7,690 women. After full adjustment, each standard deviation increased in CUN-BAE linked to 35% higher MASLD risk (HR = 1.35, 95% CI: 1.29-1.41, P < 0.001). Comparing top versus bottom tertiles showed 95% increased risk (HR = 1.95, 95% CI: 1.74-2.18, P < 0.001). Five-year cumulative incidence rose from 8.4% (lowest tertile) to 15.8% (middle) to 18.9% (highest tertile, Log-rank P < 0.0001). Cubic spline analysis uncovered sex differences: women showed a sharp risk increase above CUN-BAE 31.2, while men displayed more gradual, linear patterns. The TyG index accounted for 24.7% of the CUN-BAE-MASLD association (P < 0.001). CUN-BAE effectively predicts MASLD development in Chinese non-obese adults through clear dose-response relationships that differ by sex. Since TyG index only partially explains this association, insulin resistance appears important but insufficient to account for the full relationship. CUN-BAE could serve as a practical screening tool to identify high-risk individuals missed by conventional BMI-based approaches, enabling more precise risk stratification in non-obese populations.