The product of waist-to-height ratio and glycated hemoglobin, a novel predictor of diabetes in East Asian populations: insights from two large East Asian cohort studies - Li Wang; Weijian Wang; Yanjing Ji; Gangjun Zong (Diabetology & Metabolic Syndrome)
Abstract Background The global incidence of diabetes is increasing annually, with a notable rise in East Asia. This study aimed to develop a novel clinical indicator for predicting the onset of diabetes, based on two longitudinal East Asian cohorts. The clinical utility of the proposed indicator was evaluated by comparing its predictive performance against established metabolic markers. Methods A total of 14,468 participants from the NAFLD (Non-Alcoholic Fatty Liver Disease) in the Gifu Area Longitudinal Analysis (NAGALA) cohort and 8,977 from the China Health and Retirement Longitudinal Study (CHARLS) were enrolled for health screenings. The novel Waist-to-Height-Hemoglobin A1c (WHH) indicator was calculated using the formula: waist circumference (cm)/height (cm) × HbA1c × 100. The association between WHH and diabetes incidence was analyzed across the entire population and subgroups via Kaplan-Meier curves and multivariate Cox regression models. Generalized Additive Models (GAM) were used to explore potential non-linear relationships between WHH and diabetes risk. Time-dependent receiver operating characteristic (ROC) curves and area under the ROC (AUC) analysis were employed to compare the predictive power of WHH with other clinical metabolic indicators. Results Over a maximum 13-year follow-up, the cumulative risk of diabetes increased with higher WHH quartiles. Following covariate adjustment, multivariable Cox regression showed a significant positive correlation between WHH and diabetes incidence in the total population (hazard ratio [HR]: 9.71; 95% confidence interval [CI]: 7.03–13.41) and subgroups. GAM analysis confirmed a non-linear relationship between WHH and diabetes risk (P < 0.001). Time-dependent ROC analysis demonstrated that WHH effectively predicted future diabetes risk (AUC > 80%) over medium-to-long-term periods (5–12 years). Baseline WHH outperformed established indicators—including WHtR, HbA1c, BMI, METS-IR, TyG, AIP, and LAP—in predicting diabetes risk. Conclusions WHH is positively associated with diabetes risk in East Asian populations. Compared to other clinical metabolic indicators, baseline WHH demonstrates superior predictive performance for future diabetes risk, especially over medium-to-long-term periods. We recommend maintaining WHH below 2.489 through dietary calorie control and waist circumference management to reduce diabetes risk in healthy individuals.