Association of the triglyceride-cholesterol-body weight index (TCBI) with incident diabetes in Chinese adults: a population-based cohort study with non-linear and threshold analyses

BACKGROUND: The triglyceride-cholesterol-body weight index (TCBI) is a simple composite nutritional marker. However, its association with incident diabetes remains unclear. We examined this association in Chinese adults, focusing on non-linear and threshold effects. METHODS: This retrospective cohort study included 206,085 adults without baseline diabetes. TCBI was calculated as (TG × TC × body weight) / 1,000. We used Cox regression, restricted cubic splines, and segmented regression for analysis. RESULTS: During follow-up, 4,093 participants developed incident diabetes. Higher TCBI was consistently associated with an increased risk of incident diabetes. In the fully adjusted model, each 1-SD increase in TCBI was associated with a 13% higher risk of incident diabetes (HR = 1.13, 95% CI: 1.12-1.14; P < 0.001), while each 1-unit increase in ln-TCBI was associated with a 94% higher risk (HR = 1.94, 95% CI: 1.86-2.03; P < 0.001). Compared with participants in the lowest TCBI quartile (Q1), the fully adjusted HRs were 2.18 (95% CI: 1.83-2.59), 3.49 (95% CI: 2.95-4.12), and 6.53 (95% CI: 5.53-7.72) for Q2, Q3, and Q4, respectively (P for trend < 0.001). Restricted cubic spline analysis indicated a non-linear association between ln-TCBI and incident diabetes (P for non-linearity < 0.001). Segmented regression identified a potential threshold at ln-TCBI = 6.828 (original TCBI ≈ 923), with positive associations observed both below (HR = 2.223, 95% CI: 1.613-3.062) and above (HR = 1.901, 95% CI: 1.787-2.022) the threshold. CONCLUSIONS: These findings suggest that TCBI may represent an accessible composite metabolic indicator associated with diabetes risk; however, whether TCBI provides additional information beyond established metabolic indicators and whether the identified threshold has clinical relevance require further validation in diverse populations.