Estimated glucose disposal rate outperforms inflammation surrogate markers in predicting cardiometabolic...

Both estimated glucose disposal rate (eGDR) and inflammation surrogate (high-sensitivity C-reactive protein [hs-CRP]) have emerged as potential markers reflecting metabolic health. However, their comparative predictive value for cardiometabolic multimorbidity remains unclear, particularly in middled-aged and older populations where both metabolic dysfunction and low-grade inflammation are highly prevalent.

This prospective cohort study included 7,589 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study (CHARLS) with complete baseline data. The primary outcome was incident cardiometabolic multimorbidity, defined as the co-occurrence of two or more cardiometabolic conditions, including diabetes, heart disease, and stroke. Cox proportional hazards models were employed to assess separate and joint associations. Concordance index (C-index) was used to evaluate the predictive capacity.

Over a 9-year follow-up period, 2,263 participants developed cardiometabolic multimorbidity. In models adjusting for traditional risk factors, lower eGDR (lowest vs. highest quartile: hazard ratio [HR] 2.07, 95% CI 1.80-2.38) remained significantly associated with increased risk of cardiometabolic multimorbidity. In joint associations, participants with low eGDR exhibited consistently elevated cardiometabolic multimorbidity risk regardless of inflammation surrogate status (HR 1.52 (95% CI 1.33-1.74) in those with low inflammation and HR 1.80 (95% CI 1.58-2.04) in those with high inflammation). Addition of eGDR to the basic model (which included covariates) yielded a significantly higher C-index (0.676) compared to hs-CRP (0.643, P < 0.001).

Among middle-aged and older adults, eGDR is significantly associated with incident cardiometabolic multimorbidity regardless of inflammation status. Low eGDR demonstrates superior discriminative ability compared to hs-CRP. These findings suggest that eGDR may serve as a more comprehensive biomarker for cardiometabolic risk stratification by capturing insulin resistance and metabolic dysfunction.