The predictive value of estimated pulse wave velocity combined with BMI for newly diagnosed diabetes

Abstract Purpose ePWV and BMI are closely related to the prediction of new-onset diabetes. The aim of this study was to evaluate the impact and predictive value of the combination of estimate pulse wave velocity (ePWV) and body mass index (BMI) on new-onset diabetic patients. Methods A secondary analysis of a cohort study conducted by rich health care was performed with a total of 211833 eligible subjects enrolled. Logistic regression analysis was used to identify factors influencing the occurrence of diabetes, and ROC curve analysis was used to evaluate the predictive value of ePWV, BMI, and their combination on new-onset diabetes. Results During a mean follow-up period of 3.12 years, 3000 men (1.41%) and 1174 women (0.55%) were diagnosed with diabetes. Logistic regression analysis showed that BMI, triglycerides, alanine aminotransferase, blood urea nitrogen, creatinine clearance rate, ePWV, and history of diabetes in the family were high-risk factors for new-onset diabetes. Compared with using ePWV or BMI alone, the combined ePWV and BMI had a higher area under the receiver operating characteristic curve of 0.822. Conclusion The elevation of ePWV and BMI levels is an independent risk factor for new-onset diabetes, and the combination of ePWV and BMI can better predict new-onset diabetes compared to using either indicator alone.