Abstract
BACKGROUND AND OBJECTIVE: While the creatinine-to-body weight ratio (Cre/BW) has emerged as a promising biomarker for muscle mass assessment, its relationship with prediabetes remains unclear. This study aimed to investigate the association between Cre/BW ratio and incident prediabetes in Chinese adults. METHODS: We conducted a large-scale retrospective cohort study involving 173,476 participants from health check-up programs across 11 Chinese cities. Cox proportional hazards models were employed to evaluate the association between baseline Cre/BW ratio and incident prediabetes. To address potential non-linear relationships, we applied Cox proportional hazards regression with cubic spline functions and smooth curve fitting, using a recursive algorithm to calculate inflection points. Multiple imputation was used for missing data, and comprehensive sensitivity analyses were performed to assess result robustness. RESULTS: During a median follow-up of 3.0 years, 18,506 participants (10.67%) developed prediabetes. A lower Cre/BW ratio was associated with an increased risk of prediabetes (adjusted HR = 0.869, 95%CI: 0.806-0.973). Exploratory threshold effect analysis suggested a potential inflection point at 0.96(95% CI 0.90-1.01)μmol/L/kg, below which the association might be stronger (HR = 0.407, 95%CI: 0.328-0.506). The association remained stable in sensitivity analyses excluding participants with smoking history, drinking history, or family history of diabetes. Subgroup analyses revealed more pronounced associations among individuals aged 30-40 years (HR = 0.614, 95%CI: 0.532-0.708), females (HR = 0.726, 95%CI: 0.640-0.824), and those with normal blood pressure (systolic blood pressure <140 mmHg, HR = 0.816, 95%CI: 0.752-0.886). CONCLUSION: A lower Cre/BW ratio is associated with an increased risk of prediabetes in Chinese adults. Exploratory threshold effect analysis suggested a potential inflection point at 0.96(95% CI 0.90-1.01) μmol/L/kg. These findings suggest that the Cre/BW ratio could serve as a simple, cost-effective tool for prediabetes risk stratification in clinical practice.