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Background The metabolic syndrome (MS) based on insulin resistance (IR) is a cluster of conditions indicating an increased risk of cardiometabolic diseases. This study aimed to define valid cut-off values for surrogate measures for IR to predicting the risk for the development of MS in the Hungarian general (HG) and Roma (HR) populations. Methods This study included 397 HG and 368 HR subjects aged 20-64 years from a complex health survey in 2018/2019. Four surrogate measures, namely the homeostasis model assessment-IR (HOMA-IR), McAuley index (McA), TG to HDL-cholesterol ratio (TG/HDL-C) and TG and glucose index (TyG) were calculated for all participants. The cut-off values were determined as the value with the highest Youden index (YI) on the basis of results obtained by receiver operating characteristic (ROC) curve analysis for the development of MS on separate and combined populations. Results Since no significant difference could be detected between the results obtained on separate populations, cut-off values defined on the combined one are proposed to use for risk prediction. The area under the ROC curve was 0.753 (95%CI: 0.718-0.787) for HOMA-IR, 0.827 (95%CI: 0.797-0.856) for McA, 0.843 (95%CI: 0.814-0.872) for TG/HDL-C ratio and 0.862 (95%CI: 0.835-0.889) for TyG. The cut-off value was 2.32 (sensitivity (sens.) 70.9%; specificity (spec.) 69.0%; YI: 0.399) for HOMA-IR, 5.989 (sens. 69.7%; spec. 82.7%; YI: 0.524) for McA, 1.274 (sens. 73.4; spec. 84.3%; YI: 0.574) for TG/HDL-C ratio and 4.694 (sens. 77.2%; spec. 84.3%; YI: 0.615) for TyG. Concerning the fact, that the TyG has the best indicative power for predicting IR to the estimation of MS risk in both populations the IR/MS prevalence was defined by using TyG and found to be as high as 42.3% and 40.5% in the HG and HR populations, respectively. Conclusions Based on our results the TyG index could be a useful supplementary method for identifying individuals at risk for MS. Key messages The optimal cut-off points’ four surrogate indices of insulin resistance for the prediction of metabolic syndrome did not differ significantly between the Hungarian general and Roma populations. The triglyceride and glucose index proved to be the strongest predictor for the risk of metabolic syndrome in the Hungarian general and Roma populations.

Cut-off values of surrogate indices of insulin resistance as risk predictors for metabolic syndrome