Endocrine Abstracts

There are a wide range of tests to measure insulin sensitivity. Alternative techniques for estimating insulin sensitivity include measurements made during the oral glucose tolerance test (OGTT). We aimed to describe the weekly intraindividual daily variability of measures of insulin sensitivity indexes (HOMA-IR, QUICKI, Matsuda’s insulin sensitivity index (ISIM), Insulinogenic Index, Early C Peptide, Stumvoll’s Insulin Sensitivity Index (ISIS), OGIS_{_120}) and the impact of body composition, physical activity behaviour, and dietary intake, when using OGTT. Twenty-six healthy, weight stable, young males that visited QUT on 3 occasions over a 3-week period, completed the study. At 1-wk participants had a DXA scan to assess body composition, and received an accelerometer (ActiGraph- GT3X) which they wore during 14 days. Over the next 2-wks, participants undertaken repeated OGTTs, scheduled 7 days apart. Glucose, insulin and C-peptide were measured to assess each participant insulin sensitivity using OGTT at 0, 30, 60, 90 and 120 minutes. Dietary interviews were conducted by phone during a 3-week period, using a multiple-day, multiple-pass, 24-h recall and dietary intakes were assessed using FoodWorks 7 software. Despite of being one of the simplest and largely used surrogate measures of insulin sensitivity, the dailyvariability for HOMA (CV32%) was markedly higher compared with QUICKI (CV5%). The lowest variability was demonstrated by the ISIS (CV2%) and the highest reproducibility (ICC.927). The OGIS 120 also showed a low variability (CV4%). The fat trunk % was negative correlated with fasting insulin (r = −.433, P < .05), confirming relationship between abdominal fat, hyperinsulinemia and the clinical risk of diabetes. Significant correlation was found between OGIS120 and the length of vigorous physical activity spent a day (r = 573, P = .001). These findings reinforce that reduction of daily physical activity resulted in negative impact on insulin sensitivity in young healthy men. The Fiber_intake had a significant negative correlation between OGIS_{120 Day 2} (P = 0.013; r = .478). However, the Fiber_intake explained only 0.03% of the variance of OGTT by OGIS_{120 Day 2}. A significant negative correlation (P = .013;r = −.481) was observed between percentage of body fat and Fiber_intake, suggesting higher Fiber_intake predicted lower body fatness. In conclusion, the insulin sensitivity evaluation obtained from OGTT in apparently healthy individuals is quite consistent and produced reliable results using ISIS. We suggest the use of QUICKI when only fasting measures are available to measure insulin sensitivity.