Data-driven subgroups of prediabetes and the associations with outcomes in Chinese adults

Abstract

Prediabetes and its pathophysiology remain important issues. We aimed to examine the cluster characteristics of prediabetes and explore their associations with developing diabetes and its complications based on 12 variables representing body fat, glycemic measures, pancreatic β cell function, insulin resistance, blood lipids, and liver enzymes. A total of 55,777 individuals with prediabetes from the China Cardiometabolic Disease and Cancer Cohort (4C) were classified at baseline into six clusters. During a median of 3.1 years of follow-up, significant differences in the risks of diabetes and its complications between clusters were observed. The odds ratios of diabetes stepwisely increase from cluster 1 to cluster 6. Clusters 1, 4, and 6 have increased chronic kidney diseases risks, while the prediabetes in cluster 4, characterized by obesity and insulin resistance, confers higher risks of cardiovascular diseases compared with others. This subcategorization has potential value in developing more precise strategies for targeted prediabetes prevention and treatment.