Association of estimated glucose disposal rate and body mass index with stroke risk in middle-aged and elderly populations: evidence from two cohort studies

Estimated Glucose Disposal Rate (eGDR) is one of the markers of insulin resistance (IR). However, current literature lacks robust evidence to clarify the correlation between eGDR-Body Mass Index (eGDR-BMI) and stroke incidence. Therefore, this study aims to explore the potential relationship between eGDR-BMI and stroke risk. This study analyzed data from the National Health and Nutrition Examination Survey (NHANES) and the China Health and Retirement Longitudinal Study (CHARLS). A multivariable logistic regression model was applied to examine the association between eGDR-BMI and stroke risk. Restricted cubic splines (RCS) were employed to explore the dose-response relationship and non-linear association between eGDR-BMI and stroke risk. The predictive performance of the models was evaluated using Receiver Operating Characteristic (ROC) curves and Decision Curve Analysis (DCA). A total of 18,837 participants were included (CHARLS: 9,202; NHANES: 9,635). Multivariable-adjusted analyses demonstrated that eGDR-BMI was independently associated with reduced stroke risk. Each 1-SD increase in eGDR-BMI corresponded to an 8.7% risk reduction (HR = 0.913; 95% CI: 0.786–0.990; p < 0.001) in the CHARLS cohort, with consistent results in NHANES. RCS analysis also indicated a significant linear relationship between eGDR-BMI and stroke. Subgroup analysis revealed that eGDR-BMI was significantly predictive of stroke across different age groups and genders. Finally, both the ROC curve and DCA results demonstrated that eGDR-BMI has substantial predictive potential for stroke (AUC = 0.699). eGDR-BMI is significantly associated with a reduced risk of stroke, and there exists a specific non-linear relationship between eGDR-BMI and stroke. Moreover, eGDR-BMI demonstrates substantial predictive potential for stroke.