Association between different obesity indices and carotid intima-media thickness in patients with type 2 diabetes assessed by a decision tree model and logistic regression: A cross-sectional study

Objective To explore the relationship between different obesity indicators and carotid intima-media thickness (CIMT), so as to provide a scientific basis for the selection of early warning indicators for CIMT thickening. Methods The samples were collected from patients with type 2 diabetes (T2DM) who visited the department of endocrinology of two Grade A tertiary hospitals in Jiangsu Province from 2019 to 2022. A decision tree model combined with logistic regression analysis were used to compare the effects of different obesity indicators on CIMT thickening in T2DM. And subgroup analysis was performed by patient age to explore the association between obesity indicators and CIMT in the young, middle-aged, and elderly groups. Results A total of 2676 patients with T2DM were enrolled, and 900 cases of CIMT thickening were detected. The CHAID decision tree model screened 7 significant factors influencing CIMT thickening, the most significant one was age. Binary Logistic regression showed that after adjusting for confounding variables, VFA [OR = 1.023, 95%CI (1.011,1.036)], NC [OR = 1.231, 95%CI (1.074,1.411)] and VAI [OR = 2.500, 95%CI (1.392,4.488)] in the young group, High CAVI [OR = 1.041, 95%CI (1.024,1.059)] and low SFA [OR = 0.994, 95%CI (0.989,0.999)] in the middle-aged group, and high NC [OR = 1.041, 95% CI (1.024,1.059)] in the elderly group had a statistically effect on CIMT thickening. Conclusion The traditional obesity indicators are not good predictors of CIMT thickening. VFA, NC and VAI in the youth, CAVI and SFA in the middle-aged, and NC in the elderly T2DM patients independently influenced CIMT.