Triglyceride glucose-weight adjusted waist index as a promising predictive marker for incident diabetes: a large-scale retrospective cohort study

The triglyceride-glucose (TyG) index and weight-adjusted waist index (WWI) are separately associated with diabetes mellitus (DM). However, the longitudinal relationship of their combination (TyG‑WWI) with incident diabetes remains unclear. We aimed to investigate the association between TyG‑WWI and new‑onset DM and to evaluate its predictive performance. This retrospective cohort study included 15,453 non‑diabetic Japanese adults. Cox proportional hazards models were used to estimate hazard ratios (HRs) for TyG‑WWI as both continuous and quartile variables. Restricted cubic spline analysis was applied to examine the dose‑response relationship. Time‑dependent receiver operating characteristic (ROC) curves were constructed to compare the predictive performance of TyG‑WWI, TyG, WWI, and body mass index (BMI) at 5, 10, and 12 years of follow‑up. Over a median follow‑up of 5.75 years for men and 5.13 years for women, 373 participants developed diabetes. After full adjustment, each one‑unit increase in TyG‑WWI was associated with a 5% higher risk (HR = 1.05, 95% confidence interval (CI): 1.03–1.06). Compared with the lowest quartile, the highest quartile had a 2‑fold increased risk (HR = 2.02, 95% CI: 1.13–3.62). Restricted cubic spline analysis revealed a positive, approximately linear dose‑response relationship between TyG‑WWI and incident diabetes ( P for non‑linearity > 0.05). TyG‑WWI showed superior predictive accuracy at 5 years (area under the curve (AUC) = 0.7693), 10 years (AUC = 0.7706), and 12 years (AUC = 0.7793) compared with TyG, WWI, or BMI alone (all P < 0.05 except for BMI at 5 and 10 years, but significant at 12 years, P = 0.002). Higher TyG‑WWI is independently associated with an increased risk of incident DM and demonstrates better and more stable predictive performance than TyG, WWI, or BMI over long-term follow-up. This simple, low‑cost index may serve as a practical long‑term risk stratification tool for identifying high‑risk individuals in primary care.