!Background: The prevalence and socioeconomic burden of type 2 diabetes (T2DM) and associated co-morbidities are rising worldwide. Aims: This guideline provides evidence-based recommendations for preventing T2DM. Methods: A European multidisciplinary consortium systematically reviewed the evidence on the effectiveness of screening and interventions for T2DM prevention using SIGN criteria. Results: Obesity and sedentary lifestyle are the main modifiable risk factors. Age and ethnicity are non-modifiable risk factors. Case-finding should follow a step-wise procedure using risk questionnaires and oral glucose tolerance testing. Persons with impaired glucose tolerance and/or fasting glucose are at high-risk and should be prioritized for intensive intervention. Interventions supporting lifestyle changes delay the onset of T2DM in high-risk adults (numberneeded-to-treat: 6.4 over 1.8-4.6 years). These should be supported by inter-sectoral strategies that create health promoting environments. Sustained body weight reduction by ≥ 5% lowers risk. Currently metformin, acarbose and orlistat can be considered as second-line prevention options. The population approach should use organized measures to raise awareness and change lifestyle with specific approaches for adolescents, minorities and disadvantaged people. Interventions promoting lifestyle changes are more effective if they target both diet and physical activity, mobilize social support, involve the planned use of established behaviour change techniques, and provide frequent contacts. Cost-effectiveness analysis should take a societal perspective. Conclusions: Prevention using lifestyle modifications in highrisk individuals is cost-effective and should be embedded in evaluated models of care. Effective prevention plans are predicated upon sustained government initiatives comprising advocacy, community support, fiscal and legislative changes, private sector engagement and continuous media communication.

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Adherence to a MedDiet pattern of eating is associated with lower incidence of GDM and better degree of glucose tolerance, even in women without GDM. The possibility to use MedDiet for the prevention of GDM deserves further testing with intervention studies.

BACKGROUND The triglyceride-to–HDL cholesterol (TG/HDL-C) ratio was introduced as a tool to estimate insulin resistance, because circulating lipid measurements are available in routine settings. Insulin, C-peptide, and free fatty acids are components of other insulin-sensitivity indices but their measurement is expensive. Easier and more affordable tools are of interest for both pediatric and adult patients. METHODS Study participants from the Relationship Between Insulin Sensitivity and Cardiovascular Disease [43.9 (8.3) years, n = 1260] as well as the Beta-Cell Function in Juvenile Diabetes and Obesity study cohorts [15 (1.9) years, n = 29] underwent oral-glucose-tolerance tests and euglycemic clamp tests for estimation of whole-body insulin sensitivity and calculation of insulin sensitivity indices. To refine the TG/HDL ratio, mathematical modeling was applied including body mass index (BMI), fasting TG, and HDL cholesterol and compared to the clamp-derived M-value as an estimate of insulin sensitivity. Each modeling result was scored by identifying insulin resistance and correlation coefficient. The Single Point Insulin Sensitivity Estimator (SPISE) was compared to traditional insulin sensitivity indices using area under the ROC curve (aROC) analysis and χ2 test. RESULTS The novel formula for SPISE was computed as follows: SPISE = 600 × HDL-C0.185/(TG0.2 × BMI1.338), with fasting HDL-C (mg/dL), fasting TG concentrations (mg/dL), and BMI (kg/m2). A cutoff value of 6.61 corresponds to an M-value smaller than 4.7 mg · kg−1 · min−1 (aROC, M:0.797). SPISE showed a significantly better aROC than the TG/HDL-C ratio. SPISE aROC was comparable to the Matsuda ISI (insulin sensitivity index) and equal to the QUICKI (quantitative insulin sensitivity check index) and HOMA-IR (homeostasis model assessment–insulin resistance) when calculated with M-values. CONCLUSIONS The SPISE seems well suited to surrogate whole-body insulin sensitivity from inexpensive fasting single-point blood draw and BMI in white adolescents and adults.

Increased body weight as well as type 2 diabetes (T2D) are found to be associated with increased incidence of hypertension, although the mechanisms facilitating hypertension in T2D or nondiabetic individuals are not clear. Therefore, in this study we compared the levels of insulin resistance (IR:OGIS), plasma insulin (PI:RIA) levels, and pro-inflammatory cytokines (IL-6 and TNF-α: ELISA), being risk factors previously found to be associated with hypertension, in T2D patients showing increased body weight (obese and overweight, BMI ≥ 25 kg/m2) with hypertension (group A, N = 30), or without hypertension (group B, N = 30), and in nonobese (BMI < 25 kg/m2), normotensive controls (group C, N = 15). We found that OGIS index was the lowest (A: 267 ± 35.42 vs. B: 342.89 ± 32.0, p < 0.01) and PI levels were the highest (A: 31.05 ± 8.24 vs. B: 17.23 ± 3.23, p < 0.01) in group A. In addition, IL-6 levels were higher in group A (A: 15.46 ± 5.15 vs. B: 11.77 ± 6.09; p < 0.05) while there was no difference in TNF-α levels. Our results have shown that appearance of hypertension in T2D patients with increased body weight was dependent on further increase in IR which was associated with the rise in pro-inflammatory IL-6 cytokine. The results imply that lifestyle intervention aimed to decrease IR might be beneficial in reducing the risk for hypertension in those T2D individuals.

This study aimed to analyse the impact of obesity in type 2 diabetes (T2D) on adipocytokines (adiponectin, leptin and resistin) and inflammatory markers (TNF-α, IL-6 and hsCRP) as cardiovascular risk factors. A cross-sectional study comparing the basal levels of adipocytokines and inflammatory markers was done in 18 obese (BMI ≥ 30 kg/m2) (group A), 21 overweight (25 kg/m2 ≤ BMI < 30 kg/m2) (group B), 25 non-obese T2D patients (group C) and 15 non-obese controls (group D). The lowest levels of adiponectin and the highest levels of leptin, resistin, TNF-α, IL-6 and hsCRP were found in group A. Adiponectin levels were significantly lower, and resistin, TNF-α, and hsCRP levels were elevated in group C vs. D. However, leptin and IL-6 levels differed significantly between groups A and B, but not between groups C and D. Moreover, we found a significant negative correlation between adiponectin and TNF-α, but not with other markers, which was independent of the presence of obesity. In contrast, leptin and resistin correlated with the inflammatory markers, and this correlation was obesity-dependent. Our results suggest that obesity influences cardiovascular risk primarily through changes in leptin and resistin and less efficiently at the level of adiponectin.

Background: Patients with Huntington disease (HD) develop diabetes mellitus more often than do matched healthy controls. Recent studies in neurodegenerative diseases suggested that insulin resistance constitutes a metabolic stressor that interacts with a preexisting neurobiological template to induce a given disorder.Objective: To investigate possible changes in insulin sensitivity and secretion, major determinants of glucose homeostasis, in a group of consecutive normoglycemic patients with HD.Design: Metabolic investigations.Participants: Twenty-nine untreated, nondiabetic patients with HD and 22 control participants matched by age, sex, and socioeconomic background.Main Outcome Measures: Glucose tolerance, assessed by means of the glucose curve during oral glucose challenge; insulin sensitivity, assessed using homeostasis model assessment and minimal model analysis based on frequent sampling of plasma glucose and plasma insulin during the intravenous glucose tolerance test; and insulin secretion, determined by means of the acute insulin response and the insulinogenic index.Results: The evaluation of insulin sensitivity using homeostasis model assessment demonstrated higher homeostasis model assessment insulin resistance indices, and a lower sensitivity index when the minimal model approach was used, in patients with HD compared with controls (P=.03 and P=.003, respectively). In the assessment of early-phase insulin secretion, the acute insulin response and the insulinogenic index were lower in patients with HD compared with controls (P=.02). The number of CAG repeats correlated significantly only with acute insulin response (P =.003).Conclusions: Besides impairment in insulin secretion capacity, a simultaneous decrease in insulin sensitivity, with an increase in the insulin resistance level, was found in normoglycemic patients with HD compared with controls. These data imply that progression of the insulin secretion defect in HD may lead to a failure to compensate for insulin resistance.

It appears that ghrelin might be involved in the negative control of insulin secretion and glucose consumption in gastrectomized patients, at least after acute administration.