Background and Objectives: The key pathogenetic mechanism of glucose metabolism disorders, insulin resistance (IR), can be assessed using the Homeostasis Model Assessment of IR (HOMA-IR). However, its application in clinical practice is limited due to the absence of cut-offs. In this study, we aimed to define the cut-offs for the Czech population. Methods: After undergoing anthropometric and biochemical studies, the sample of 3539 individuals was divided into either nondiabetics, including both subjects with normal glucose tolerance (NGT, n = 1947) and prediabetics (n = 1459), or diabetics (n = 133). The optimal HOMA-IR cut-offs between subgroups were determined to maximize the sum of the sensitivity and specificity for diagnosing type 2 diabetes mellitus (T2DM) or prediabetes. The predictive accuracy was illustrated using receiver operating characteristic (ROC) curves. Logistic regression was performed to assess the association between a target variable (presence/absence of T2DM) depending on the HOMA-IR score as well as on the age and sex. Results: The HOMA-IR cut-off between nondiabetics and diabetics for both sexes together was 3.63, with a sensitivity of 0.56 and a specificity of 0.86. The area under the ROC curve was 0.73 for T2DM diagnosing in both sexes. The HOMA-IR cut-off between the NGT subjects and prediabetics was 1.82, with a sensitivity of 0.60 and a specificity of 0.66. Logistic regression showed that increased HOMA-IR is a risk factor for the presence of T2DM (odds ratio (OR) 1.2, 95% confidence interval (CI) 1.14–1.28, p < 0.0001). The predictive ability of HOMA-IR in diagnosing T2DM is statistically significantly lower in females (OR 0.66, 95% CI 0.44–0.98). The results are valid for middle-aged European adults. Conclusions: The results suggest the existence of HOMA-IR cut-offs signaling established IR. Introduction of the instrument into common clinical practice, together with the known cut-offs, may contribute to preventing T2DM.

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Diabetes mellitus type 1 disease changes the activity of fatty acid degradation as compared to healthy animals. Supplementation in vitro with microelements chromium Cr 3+ and selenium Se 4+ and Se 2in non-toxic ([96.15 μmol (5 ppm) for chromium and 6.33 μmol (0.5 ppm) for selenium] concentrations strongly stimulates the activity of this process in diabetic rats. In healthy animals only chromium Cr 3+ in concentration of 96.15 μmol (5 ppm) stimulated β-oxidation activity in lymphocytes. It may indicate the beneficial effect of supplementation of the diet with microelements, chromium Cr 3+ and selenium Se 4+ or Se 2at concentrations as low as 100 μmol for chromium and 6 μmol for selenium, respectively.

Background and Objectives: The mechanism of the relationship between glycemia and lipid metabolism has not been completely clarified, and slight differences may be found between authors and the kinds of evaluated parameters. Therefore, this study focused on possible changes of lipoprotein profile with regards to HOMA IR (Homeostatic Model Assessment for Insulin Resistance) cut-off 3.63, considered a signal of glucose metabolism alterations. Materials and Methods: The metabolic profiles of 3051 individuals were divided by HOMA IR values into two groups below cut-off 3.63, including (n = 2627) and above cut-off (n = 424). Patients taking medication or supplements to affect lipid, insulin, or glucose metabolism were excluded. Fasting glucose levels, insulin, and lipoproteins (total, HDL—high density and LDL—low density lipoprotein cholesterol) were compared between the groups with different HOMA IR. After analysis of data distribution, F-test and t-test were provided to compare variances and mean values. Results: The evaluation shows that the kind of cholesterol is crucial for a possible relationship with glucose metabolism and consequently confirms the changes of lipoproteins (HDL and LDL) by HOMA IR cut-off 3.63. Conclusions: The results of patients divided by HOMA IR cut-off 3.63 also suggest possible changes in the regulation of glucose metabolism and lipoprotein concentrations (HDL and LDL).

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