Association between the plasma atherogenic index and type 2 diabetes in Chinese population: prospective cohort study based on 4C study - Zhang, Yue-Yang; Cao, Rui; Wan, Qin (Frontiers in Endocrinology, 2025)
BackgroundCurrently, the plasma atherogenic index (AIP) is mainly used to predict atherosclerosis and cardiovascular diseases. Therefore, we aim to investigate the potential association between AIP and type 2 diabetes through a prospective cohort study.MethodsThe 4C study, a multicenter prospective cohort investigation, targets the Chinese population and initially enrolled 10,008 participants. Baseline data encompassing lifestyle, metabolic status, and various other factors were collected in 2011. A 10-year follow-up survey was subsequently conducted, ultimately including 9,092 participants. AIP, defined as the logarithmic transformation of the triglycerides to high-density lipoprotein ratio, was divided into quartiles. To explore the potential association between AIP and the risk of type 2 diabetes, Cox regression, restricted cubic spline, receiver operating characteristic curve(ROC), and subgroup analysis were employed.ResultsOver a 10-year follow-up period, 693 new cases of type 2 diabetes were identified. In a fully adjusted model, AIP demonstrated a positive association with type 2 diabetes (HR: 4.40; 95% CI: 3.21, 6.04). Compared to the Q1 group, the risk of type 2 diabetes increased progressively across the Q2, Q3, and Q4 groups, with a significant trend (p-value < 0.05). Restricted cubic spline (RCS) analysis revealed an inverse L-shaped association between AIP and the risk of type 2 diabetes, with a turning point at 0.45. The ROC analysis indicates that incorporating the AIP into the base model enhances its diagnostic performance for type 2 diabetes. Furthermore, similar patterns were observed in the subgroup analyses.ConclusionsAmong the Chinese population, elevated AIP levels are positively correlated with an increased risk of type 2 diabetes, indicating that AIP could potentially serve as a biomarker for assessing the risk of developing type 2 diabetes.