Insulin resistance is a heterogenous condition with high prevalence in medical practice. As diabesity reaches epidemic levels worldwide, the role of insulin resistance is getting great importance. Contribution of risk factors like sedentary lifestyle, diets high in saturated fats and refined carbohydrates leads to this state with significant consequences. Besides its role in diabetes, insulin resistance is also associated with other several endocrine diseases, having not only a role in their development, but also to their treatment approach, evolution and even prognosis. The present review summarizes the current literature on the clinical significance of insulin resistance, as well as the possible underlying mechanisms and treatment options in order to achieve a high quality of life of these categories of patients. Deepening the role of inflammatory cytokines involved in insulin resistance paves the way for future research findings in this continuously evolving field.
Introduction: Worldwide, childhood obesity is on the rise. A lot of debate exists within the scientific community regarding the best way to define overweight and obesity in different populations. Currently, three sets of growth references are in use internationally: the 2007 World Health Organization (WHO) growth standards, the International Obesity Task Force (IOTF) reference, and the 2000 Center for Disease Control and Prevention (CDC) growth charts. We examined the impact of using these international growth references on diagnosing obesity in a group of overweight and obese Romanian children. Afterwards, we evaluated the relationship between diagnosed obesity and insulin resistance status.
Material and method: We studied retrospectively the observation charts of children who had their insulin levels tested in our hospital’s laboratory between January 1st 2008 and December 31st 2009. The study population consisted of 76 children. We analyzed: age, gender, body mass index (BMI), the homeostatic model assessment: insulin resistance (HOMA-IR). We divided the children into two categories according to their HOMA-IR values. We used each of the standards and grouped the study population into two BMI groups: overweight and obese. We used One-Way ANOVA to evaluate the differences between the three definitions.
Results: We found significant differences between the WHO and the IOTF and CDC references. The WHO standards identified the least overweight children with insulin resistance.
Conclusions: Our study shows that using WHO growth standards may be the proper method to diagnose obese children. A large populational study is needed to establish the proper growth references for our population.
Background: Hepatitis C virus infection seems to induce insulin resistance and type 2 diabetes by direct viral involvement. The prevalence of glucose metabolism disorders is higher in C virus infected non-cirrhotic patients in comparation with patients with other etiology liver diseases.
Material and method: Two-hundred seventy patients with chronic C hepatitis were compared to 163 patients with chronic B hepatitis, regarding glucose metabolism before and after antiviral therapy and regarding the risk factors of diabetes.
Results: The prevalence of insulin resistance was 19% in hepatitis C and 6.7% in hepatitis B patients (p<0.0001). 90.2% of insulin resistant patients with C hepatitis had viraemia ≥800,000UI/ml. After viral eradication plasma glucose and insulin levels decreased significantly (p<0.0001). In this group of patients, eradication was obtained less (66.7%) than in the non-insulin resistent C hepatitis (84.4%) or insulin resistant B hepatitis group (80.0%).
Conclusions: Hepatitis C virus infection increases the risk of diabetes compared with hepatitis B virus, irrespectively of classic diabetes risk factors, but dependent on viraemia. Insulin resistance decreases therapeutic response only in hepatitis C, but viral eradication improves glucose metabolism in these patients.
Objective: Insulin resistance has been shown to be a risk factor for type 2 diabetes and cardiovascular disease. The assessment of insulin sensitivity in the clinical practice, however, faces several difficulties. The study proposes to analyze surrogate measures of insulin resistance based on fasting insulin levels in central Romania, and check whether the diagnosis of the metabolic syndrome is an adequate strategy to identify middle-aged persons with reduced insulin sensitivity.
Methods: Anthropometric measurements, metabolic profile, and surrogates measures of insulin sensitivity (GIR, HOMA, QUICKI, FIRI, Belfiore, Bennett, Raynaud, McAuley index) based on fasting insulin levels were assessed in 233 non-diabetic middle aged subjects.
Results: Cutoff values, determined as the lowest quartile of insulin sensitivity for fasting insulin, HOMA, IRI (1/QUICKI), FIRI and Belfiore’s, Bennett’s, Raynaud’s and McAuley’s insulin sensitivity indices were 10.49 mU/L, 2.1, 3.01, 2.32, and 0.03, 1.34, 3.81, 6.29, 5.82. Components of the metabolic syndrome showed moderate but significant correlations with the surrogate measures of insulin resistance (r = 0.22–0.56, p <0.05). HOMA-IR and McAuley indices were the best predictors of clustered cardiometabolic risk factors (AUC – 0.83, 0.81 and 0.82). The metabolic syndrome diagnosis performed well in identifying patients with reduced insulin sensitivity (McAuley 2: sensitivity – 0.78, specificity – 0.84).
Conclusion: Fasting insulin derived insulin sensitivity indices may help the recognittion of insulin resistant states predicting cardiometabolic disorders. Actively looking for insulin resistance by these simple indices, or by diagnosing the metabolic syndrome, those at increased risk can be recognized.