A Prediction Model for Prediabetes Risk in Middle-Aged and Elderly Populations: A Prospective Cohort Study in China

Abstract

Background. To investigate indicators for prediabetes risk and construct a prediction model for prediabetes incidences in China. Methods. In this study, 551 adults aged 40–70 years had normal glucose tolerance (NGT) and normal hemoglobin A1c (HbA1c) levels at baseline. Baseline data including demographic information, anthropometric measurements, and metabolic profile measurements were collected. The associations between possible indicators and prediabetes were assessed by the Cox proportional-hazards model. The predictive values were evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). Results. During an average of 3.35 years of follow-up, the incidence of prediabetes was found to be 19.96% (n = 110). In the univariate analyses, fasting plasma glucose (FPG), fasting serum insulin (FINS), 2 h plasma glucose (2hPG), HbA1c, serum uric acid (SUA), waist circumference (WC), smoking, and family history of diabetes (FHD) were found to be significantly correlated with prediabetes. In the multivariable analyses, WC (hazard ratio (HR): 1.032; 95% confidence interval (CI): 1.010, 1.053; p=0.003), FHD (HR: 1.824; 95% CI: 1.250, 2.661; p=0.002), HbA1c (HR: 1.825; 95% CI: 1.227, 2.714; p=0.003), and FPG (HR: 2.284; 95% CI: 1.556, 3.352; p<0.001) were found to be independent risk factors for prediabetes. A model that encompassed WC, FHD, HbA1c, and FPG for predicting prediabetes exhibited the largest discriminative ability (AUC: 0.702). Conclusions. WC, FHD, HbA1c, and FPG are independently correlated with the risk of prediabetes. Furthermore, the combination of these predictors enhances the predictive accuracy of prediabetes.