Aims/Introduction: How to measure insulin resistance (IR) accurately and conveniently is a critical issue for both clinical practice and research. In the present study, we tried to modify the b-cell function, insulin sensitivity, and glucose tolerance test (BIGTT) in patients with normal glucose tolerance (NGT) and abnormal glucose tolerance (AGT) by oral glucose tolerance test (OGTT) and metabolic syndrome (MetS) components. Materials and Methods: There were 327 participants enrolled and divided into NGT or AGT. Data from 75% of the participants were used to build the models, and the remaining 25% were used for external validation. Steady-state plasma glucose (SSPG) concentration derived from the insulin suppression test was regarded as the standard measurement for IR. Five models were built from multiple regression: model 1 (MetS model with sex, age and MetS components); model 2 (simple OGTT model with sex, age, plasma glucose, and insulin concentrations at 0 and 120 min during OGTT); model 3 (full OGTT model with sex, age, and plasma glucose and insulin concentrations at 0, 30, 60, 90, 120, and 180 min during OGTT); model 4 (simple combined model): model 1 and model 2; and model 5 (full model): model 1 and 3. Results: In general, our models had higher r 2 compared with surrogates derived from OGTT, such as homeostasis model assessment-insulin resistance and quantitative insulin sensitivity check index. Among them, model 5 had the highest r 2 (0.505 in NGT, 0.556 in AGT, respectively). Conclusions: Our modified BIGTT models proved to be accurate and easy methods for estimating IR, and can be used in clinical practice and research.

The Increasing prevalence of type 2 diabetes mellitus (T2DM) has been observed in younger adults. Insulin resistance [IR], decreased first-, second-phase insulin secretion, and glucose effectiveness (GE) (IR, first phase insulin secretion [FPIS], second phase insulin secretion [SPIS], and GE), denoted as diabetes factors (DF), are core for developing T2DM. A body of evidence has shown that inflammation contributes to the development of diabetes. In the present study, our goals were first, evaluate the relationships between white blood cell (WBC) count and, second, examine the relative tightness between the 4 DFs to WBC count. Thus, the pathophysiology of T2DM in Chinese young men could be more understood. 21112 non-obese males between 18 to 27 years old were recruited (mean age: 24.3 ± 0.017), including 1745 subjects with metabolic syndrome. DFs were calculated by the published equations by our groups as follows: IR = log (1.439 + 0.018 × sex - 0.003 × age + 0.029 × body mass index [BMI]- 0.001 × systolic blood pressure [SBP] + 0.006 × diastolic blood pressure + 0.049 × triglycerides [TG] - 0.046 × high-density lipoprotein cholesterol [HDLC] - 0.0116 × fasting plasma glucose [FPG]) × 10 3.333 1 FPIS = 10 [1.477 - 0.119 × FPG + 0.079 × BMI - 0.523 × HDLC] 2 SPIS = 10 [-2.4 - 0.088 × FPG + 0.072 × BMI] GE = (29.196 - 0.103 × age - 2.722 × TG - 0.592 × FPG) ×10 −3 3 The association between DFs and WBC count was analyzed using a simple correlation. The r-values of the simple correlation are regarded as the tightness of the relationships. Higher WBC, FPIS, SPIS, IR, age, BMI, blood pressure, FPG, TG, Cholesterol, low-density lipoprotein cholesterol and lower HDL-C and GE were observed in subjects with metabolic syndrome. A similar trend was seen across the quartiles of WBC levels. Among the 4 DFs, GE has the highest r-value ( r = -0.093, P < .001), followed by IR ( r = 0.067, P < .001), SPIS (r = 0.029, P < .001) and FPIS ( r = 0.027, P < .001). Elevated WBC count is significantly associated with all the 4 DFs and the relative order of the tightness, from the highest to the lowest, are GE, IR, SPIS, and FPIS in Chinese young men.

Both decreased insulin sensitivity, and impaired insulin secretion are 2 major pathophyisologies for type 2 diabetes (T2DM). There are two phases of ISEC-the first (1st ISEC) and second phase (2 nd ISEC). In this study, we tried to build an equation to predict 2 nd ISEC.Totally, 82 subjects, including 15 with normal fasting glucose, 26 with pre-diabetes and 41 with T2DM were enrolled. They received a modified low dose graded glucose infusion (M-LDGGI). The M-LDGGI is a simplified version of Polonsky's method. The results were interpreted as the slope of the changes of plasma insulin against the glucose levels. The slopes of these curves were regarded as the 2 nd ISEC.If only metabolic syndrome (MetS) components were analyzed, the equation was built as the following: log (2 nd ISEC) = -2.400-0.088 • (fasting plasma glucose, FPG + 0.072 • (body mass index, BMI). After fasting plasma insulin (FPI) was added , the equation was shown as the following: log (2 nd ISEC) = -2.316-0.093˙FPG + 0.049 • BMI+ 0.434 • log(FPI). The second equation provided a greater accuracy to determine 2nd ISEC than first one in the external validation group (r 2 = 0.545 vs r 2 = 0.423).Using MetS components, 2 nd ISEC could be predicted with good accuracy. After adding FPI into the equation, the predictive power further increases. These equations could be widely used in daily practice and clinical settings.