ArticleJournal of translational medicine2026
Association between estimated glucose disposal rate and heart disease events in adults with overweight or obesity: a prospective cohort study.
Article in Journal of translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundRecent research indicates that insulin resistance (IR) plays a role in the progression of cardiovascular diseases (CVD), with the estimated glucose disposal rate (eGDR) recognized as a dependable proxy for measuring IR. Nonetheless, there is a scarcity of studies concentrating on overweight and obese populations. Consequently, this study aims to explore the correlation between eGDR and the risk of developing CVD among individuals who are overweight or obese.
methodsIn the cohort study, participants were selected from the China Health and Retirement Longitudinal Study (CHARLS), encompassing those without a history of heart disease and possessing complete baseline data on the estimated glucose disposal rate (eGDR). Participants were stratified into three groups based on the tertiles (T) of eGDR values. Cox proportional hazards models were used to evaluate the association between eGDR and the incidence of heart disease. Furthermore, a multivariate adjusted restricted cubic spline (RCS) model was utilized to assess the linearity of the association. Robustness of the results was examined through subgroup and sensitivity analyses.
resultsA cohort of 2,217 participants were enrolled, with a mean age of 56.9 ± 8.0 years, including 839 males (37.8%). Throughout a follow-up duration of up to 9 years, 600 participants (27.1%) developed heart disease events. After controlling for all covariates (Model 4), the association between eGDR and incidence heart disease persisted as significant (adjusted HR: 0.90; 95% CI: 0.86–0.94; P < 0.001). When analyzed as a categorical variable, eGDR tertiles 2 and 3 demonstrated a significant reduction in the risk of heart disease compared to tertile 1, with adjusted HRs of 0.76 (95% CI: 0.62–0.92) and 0.56 (95% CI: 0.44–0.71), respectively, in Model 4. RCS analysis indicated an inverse linear relationship was observed between eGDR and the occurrence of heart disease. Subgroups and sensitivity analysis both verify the robustness of the findings.
conclusionseGDR is a practical and informative marker for identifying individuals with overweight or obesity who are at higher risk of heart disease. Incorporating eGDR into routine risk assessment may help improve early prevention strategies. Further validation in external cohorts is warranted.
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