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As compared with placebo, pioglitazone reduced the risk of conversion of impaired glucose tolerance to type 2 diabetes mellitus by 72% but was associated with significant weight gain and edema. (Funded by Takeda Pharmaceuticals and others; ClinicalTrials.gov number, NCT00220961.).

OBJECTIVE -The oral glucose tolerance test identifies high-risk subjects for diabetes, but it is costly and inconvenient. To find better predictors of type 2 diabetes, we evaluated two different definitions of the metabolic syndrome because insulin resistance, which is commonly associated with this clustering of metabolic factors, frequently precedes the onset of type 2 diabetes. RESEARCH DESIGN AND METHODS-We compared the ability of the National Cholesterol Education Program (NCEP) definition, a modified version of the 1999 World Health Organization (WHO) definition that excludes the 2-h glucose requirement, and impaired glucose tolerance (IGT) to predict incident type 2 diabetes. In the San Antonio Heart Study, 1,734 participants completed a 7-to 8-year follow-up examination.RESULTS -IGT and the NCEP definition had higher sensitivity than the modified WHO definition (51.9, 52.8, and 42.8%, respectively). IGT had a higher positive predictive value than the NCEP and modified WHO definitions (43.0, 30.8, and 30.4%, respectively). The combination of the IGT and NCEP definitions increased the sensitivity to 70.8% with an acceptable positive predictive value of 29.7%. Risk for incidence of type 2 diabetes using the NCEP definition was independent of other risk factors, including IGT and fasting insulin (odds ratio 3.30, 95% CI 2.27-4.80). The NCEP definition performed better with fasting glucose Ն5.4 mmol/l (sensitivity 62.0% and positive predictive value 30.9%). The OGTT is the standard method for identifying subjects at increased risk for developing type 2 diabetes in clinical research. However, OGTT is not widely used in clinical practice because it is inconvenient and costly. Identifying subjects at risk for diabetes has become more relevant because of the positive results seen with lifestyle modification and medication in the prevention (or delay) of type 2 diabetes (5-9). CONCLUSIONSIn seeking better predictors of type 2 diabetes, we evaluated two different definitions of the metabolic syndrome because insulin resistance, which is commonly associated with this clustering of metabolic factors, frequently precedes the onset of type 2 diabetes. We compared the ability of the NCEP definition, a modified version of the 1999 WHO definition of the metabolic syndrome, and IGT to predict the incidence of type 2 diabetes. RESEARCH DESIGN AND METHODS SubjectsThe San Antonio Heart Study (SAHS) is a population-based, epidemiological study of type 2 diabetes and cardiovascular disease (initial response rate 65.3%). A total of 2,941 Mexican Americans and nonHispanic whites aged 25-68 years were enrolled in phase 2 (10,11). We excluded participants in phase 1 (waist circumference was not measured) and those in phase 2 with diabetes at baseline (baseline prevalence of type 2 diabetes 10.6%). From a total of 2,569 eligible participants, 1,734 subjects completed a 7-to 8-year follow-up examination. Survey protocols at baseline and follow-up were identical and were approved by the Institutional Review Board of the University of T...

OBJECTIVE:To study the relation of fibrinogen and C-reactive protein (CRP) to various measures of body fat and body fat distribution and to investigate whether these relations were explained by differences in insulin sensitivity. DESIGN AND SUBJECTS: Cross-sectional analysis of the IRAS (Insulin Resistance Atherosclerosis Study), a large (n ¼ 1559) triethnic population (non-Hispanic whites, African-Americans and Mexican-Americans) across different states of glucose tolerance. MEASUREMENTS: Glucose tolerance (oral glucose tolerance test), insulin sensitivity (frequently sampled intravenous glucose tolerance test and minimal model analysis), assessment of body fat mass and distribution (weight, girths, bioelectrical impedance), subclinical atherosclerosis (B-mode ultrasonography of carotid artery intima-media thickness, IMT), CRP (highly sensitive immunoassay), fibrinogen (standard assay). RESULTS: Both CRP and fibrinogen were related to all measures of body fat. Strong correlations (correlation coefficient r ! 0.35) were found between CRP and body mass index (BMI), waist circumference and adipose body mass, respectively. The associations were consistent in non-diabetic and type-2 diabetic subjects, were generally stronger in women, and were only moderately attenuated by the prevailing insulin sensitivity (S I ). In a multivariate linear regression model waist circumference explained 14.5% of the variability of circulating CRP levels (P ¼ 0.0001), BMI 0.4% (P ¼ 0.0067), and S I 1.7% (P ¼ 0.0001). Common carotid artery IMT was related to CRP and fibrinogen in men, but not in women, and was attenuated after adjusting for BMI or waist. CONCLUSION: Our findings show that measures of body fat are strongly associated with circulating levels of CRP and fibrinogen. These associations were not explained by lower S I in obese subjects. Chronic, subclinical inflammation may be one pathophysiological mechanism explaining the increased risk of atherosclerotic disease associated with adiposity.

OBJECTIVE -The metabolic syndrome has been promoted as a method for identifying high-risk individuals for type 2 diabetes and cardiovascular disease (CVD). We therefore sought to compare this syndrome, as defined by the National Cholesterol Education Program, to the Diabetes Predicting Model and the Framingham Risk Score as predictors of type 2 diabetes and CVD, respectively. RESEARCH DESIGN AND METHODS -A population-based sample of 1,709 initially nondiabetic San Antonio Heart Study (SAHS) participants were followed for 7.5 years, 195 of whom developed type 2 diabetes. Over the same time interval, 156 of 2,570 SAHS participants experienced a cardiovascular event. A population-based sample of 1,353 initially nondiabetic Mexico City Diabetes Study (MCDS) participants were followed for 6.5 years, 125 of whom developed type 2 diabetes. Baseline measurements included medical history, age, sex, ethnicity, smoking status, BMI, blood pressure, fasting and 2-h plasma glucose levels, and fasting serum total and HDL cholesterol and triglycerides.RESULTS -The sensitivities for predicting diabetes with the metabolic syndrome were 66.2 and 62.4% in the SAHS and the MCDS, respectively, and the false-positive rates were 27.8 and 38.7%, respectively. The sensitivity and false-positive rates for predicting CVD with the metabolic syndrome in the SAHS were 67.3 and 34.2%, respectively. At corresponding false-positive rates, the two predicting models had significantly higher sensitivities and, at corresponding sensitivities, significantly lower false-positive rates than the metabolic syndrome for both end points. Combining the metabolic syndrome with either predicting model did not improve the prediction of either end point.CONCLUSIONS -The metabolic syndrome is inferior to established predicting models for either type 2 diabetes or CVD. Diabetes Care 27:2676 -2681, 2004T he metabolic syndrome has been promoted recently as a method of identifying individuals at increased risk of both type 2 diabetes and cardiovascular disease (CVD). This syndrome, first described in 1988 by Reaven (1), who called it Syndrome X, consists of obesity (especially abdominal obesity), insulin resistance, impaired glucose metabolism, dyslipidemia of the high triglyceride/low HDL cholesterol type, and elevated blood pressure. Although the syndrome is of considerable importance in understanding the pathophysiology and biochemistry of an interrelated cluster of diabetes and cardiovascular risk factors, recent attempts to inject it into clinical practice may be premature. The metabolic syndrome is an asymptomatic disorder. Thus, its clinical significance is presumably due to its ability to identify individuals for preventive treatments that they might otherwise not receive. The question then arises whether the metabolic syndrome represents an improvement over currently available methods of identifying such individuals.Recently, two definitions of the metabolic syndrome have been proposed, one by the National Cholesterol Education Program Adult Treatment Panel...

Persons at high risk for diabetes mellitus are better identified by using a simple prediction model than by relying exclusively on the results of a 2-hour oral glucose tolerance test. Although adding the 2-hour glucose variable to the model enhanced prediction, the resulting slight improvement entails greater cost and inconvenience.

Background-To assess the utility of clinical definitions of the metabolic syndrome (MetS) to identify individuals with increased cardiovascular risk, we examined the relation between the MetS, using both the National Cholesterol Education Program (NCEP) and the World Health Organization definitions, and all-cause and cardiovascular mortality in San Antonio Heart Study participants enrolled between 1984 and 1988. Methods and Results-Among 2815 participants, 25 to 64 years of age at enrollment, 509 met both criteria, 197 met NCEP criteria only, and 199 met WHO criteria only. Over an average of 12.7 years, 229 deaths occurred (117 from cardiovascular disease). Moreover, in the primary prevention population of 2372 participants (ie, those without diabetes or cardiovascular disease at baseline), 132 deaths occurred (50 from cardiovascular disease). In the primary prevention population, the only significant association adjusted for age, gender, and ethnic group was between NCEP-MetS and cardiovascular mortality (hazard ratio [HR], 2.01; 95% CI, 1.13-3.57). In the general population, all-cause mortality HRs were 1.47 (95% CI, 1.13-1.92) for NCEP-MetS and 1.27 (95% CI, 0.97-1.66) for WHO-MetS. Furthermore, for cardiovascular mortality, there was evidence that gender modified the predictive ability of the MetS. For women and men, respectively, HRs for NCEP-MetS were 4.65 (95% CI, 2.35-9.21) and 1.82 (95% CI, 1.14 -2.91), whereas HRs for WHO-MetS were 2.83 (95% CI, 1.55-5.17) and 1.15 (95% CI, 0.72-1.86). Conclusions-In summary, although both definitions were predictive in the general population, the simpler NCEP definition tended to be more predictive in lower-risk subjects.