How to transform a metabolic syndrome score into an insulin sensitivity value?

BACKGROUND: The metabolic syndrome (MetS) predicts cardiovascular risk and incident type 2 diabetes mellitus. The presence of a MetS is defined by the clustering of ≥3 out of 5 cardiometabolic criteria (hyperglycemia; hypertension; enlarged waist; low high-density lipoprotein-cholesterol; and hypertriglyceridemia), each of which is connected with insulin resistance. It is not known whether the severity of MetS, ranked from the sextet of scores range [0/5 to 5/5], is linearly related to reduced insulin sensitivity (IS) and/or lesser hyperbolic product across the glycemic spectrum.

PATIENTS AND METHODS: A total of 839 adults (54 normoglycemic; 785 with abnormal glucose homeostasis, among whom 711 type 2 diabetes mellitus) had insulin sensitivity assessed together with their cardiometabolic phenotype.

RESULTS: There was a significant gradient according to interval-scale MetS score in insulinemia; body mass index; (visceral) fat; hepatic steatosis; and macroangiopathy. There was an inverse linear relationship between increasing MetS scores and decreased insulin sensitivity, allowing to define an insulin resistance-predicting linear equation: IS (%) = [-15.1 × MetS score] + 109.4 (R(2)  = 0.221). For each MetS category, mean IS values did not significantly differ between groups of patients across the glycemic spectrum. The hyperbolic product (β-cell function × IS) and/or its loss rate were inversely related to MetS severity.

CONCLUSION: Insulin sensitivity is linearly and inversely related to MetS severity across the 6 scores. This novel way to exploit information intrinsic to the MetS criteria provides an easy and low cost means to quantify insulin sensitivity across the glycemic spectrum. Moreover, a higher MetS score is associated with lesser residual insulin secretion, and faster B-cell function loss. Copyright © 2015 John Wiley & Sons, Ltd.