Estimated glucose disposal rate and risk of metabolic syndrome: A population-based study - Lin Zhang; Nian Cai; Li Mo; Xiaofang Tian; Bohai Yu (PLoS ONE, 2025)
Aims This study aims to explore the association between the estimated glucose disposal rate (eGDR) and the risk of metabolic syndrome (MetS), with a focus on the mediating role of BMI. Methods Data for this study came from the 2011 and 2015 China Health and Retirement Longitudinal Study. We used multivariable logistic regression and restricted cubic splines to assess the relationship between eGDR and MetS, with subgroup and interaction analyses to identify moderating factors. The diagnostic ability of eGDR for MetS was evaluated via receiver operating characteristic curves. Results In total, 3,229 participants were included, with 745 (23.07%) diagnosed with MetS. In the fully adjusted model, each interquartile range increase in eGDR was associated with a 58% reduced MetS risk (odds ratio = 0.42, 95% confidence interval: 0.36–0.49, P < 0.001). A significant nonlinear dose–response relationship between eGDR and MetS risk was observed (P < 0.001, both overall and nonlinear).Spline regression analysis revealed that the protective effect of eGDR was significant up to 11.88 mg/kg/min (standard error = 0.17). Subgroup analysis revealed significant interaction effects of marital status and residential area on the eGDR–MetS relationship (P < 0.05), while BMI mediated 29% of eGDR’s total effect on MetS. Receiver operating characteristic analysis showed eGDR’s good predictive performance for MetS, with an area under the curve of 0.71 (95% confidence interval: 0.69–0.73). Conclusion Higher eGDR levels were linked to a significantly lower MetS risk, with approximately 29% of this association mediated by BMI, suggesting that individuals with low eGDR may benefit from closer monitoring for MetS development.