We examined the relationships of visceral fat area (VFA), subcutaneous fat area, and waist circumference, determined using computed tomography (CT), and BMI with metabolic risk factors in a large Japanese population.

Study subjects comprised 6,292 men and women who participated in the Hitachi Health Study and received CT examinations in 2007 and 2008.

Regarding the clustering of metabolic risk factors, the odds ratios (ORs) for the VFA quintiles were 1.0 (ref.), 2.4, 3.4, 5.0, and 9.7 for men and 1.0 (ref.), 1.5, 2.6, 4.6, and 10.0 for women (P < 0.001 for trends in both sexes). For the highest quintiles, the OR for VFA was 1.5 to 2 times higher than those of the other anthropometric indexes in both sexes.

We demonstrated a superior performance of VFA to predict the clustering of metabolic risk factors compared with other anthropometric indexes.

To compare fenofibric acid (FA) + statin to respective monotherapies on the prevalence of metabolic syndrome and its diagnostic components in patients with mixed dyslipidemia.

Post hoc analysis of over 2,000 metabolic syndrome patients administered either FA + low- or moderate-dose statin; FA alone; or low-, moderate-, or high-dose statin alone.

FA + low- or moderate-dose statin combination therapy reduced the presence of metabolic syndrome (35.7 or 35.9%, respectively) more than low-, moderate-, or high-dose statin monotherapy (15.5, 16.6, or 13.8%, respectively), mostly due to improvements in triglycerides and HDL cholesterol levels. Mean glucose levels slightly decreased with FA monotherapy, slightly increased with statin monotherapy, and were essentially unchanged with FA + statin. FA with or without statin also reduced non-HDL cholesterol, apolipoprotein B, total cholesterol, VLDL cholesterol, and high-sensitivity C-reactive protein.

FA + statin in patients with mixed dyslipidemia reduces the prevalence of metabolic syndrome.

A1C is an optional method for diagnosing diabetes and also for detecting individuals at increased risk of the disease. However, how A1C compares with fasting (FPG) and 2-h plasma glucose for detecting at-risk individuals is not well known.

A 2-h glucose tolerance test, frequently sampled intravenous glucose tolerance test, and A1C were obtained at the follow-up examination in 855 participants in the Insulin Resistance Atherosclerosis Study (IRAS). For this report, 385 individuals were at increased risk of diabetes as defined by A1C between 5.7 and 6.4%, impaired glucose tolerance (IGT), and/or impaired fasting glucose (IFG).

IFG and IGT identified 69.1 and 59.5% of all individuals at increased risk of diabetes, respectively. A1C 5.7–6.4% detected 23.6% of all at-risk individuals, although more African Americans (31.4%) and Hispanics (35.2%) than non-Hispanic whites (9.9%). Relative to A1C, FPG was more strongly related to fasting insulin (r = 0.38 vs. 0.26; P < 0.01), acute insulin response (r = – 0.20 vs. – 0.09; P < 0.01), and waist circumference (r = 0.43 vs. 0.25; P < 0.001) by the Spearman correlation test. Similarly, 2-h plasma glucose was more strongly related to Si (r = – 0.40 vs. – 0.27; P < 0.01) and triglycerides (r = 0.30 vs. 0.08; P < 0.001).

A1C 5.7–6.4% is less sensitive for detecting at-risk individuals than IFG and IGT, particularly among non-Hispanic whites. Single determinations of FPG and 2-h plasma glucose seem to be more precise correlates of insulin resistance and secretion than A1C and, in general, better for other metabolic disorders.

Some individuals with normal glucose tolerance (NGT) exhibit a 1-h excursion of plasma glucose during oral glucose tolerance testing as high as that of individuals with impaired glucose tolerance (IGT). The aim of this study was to characterize their metabolic phenotype.

A total of 1,205 healthy volunteers (aged 29–61 years) underwent assessment of 1) oral glucose tolerance and 2) insulin sensitivity (standardized euglycemic-hyperinsulinemic clamp), as part of the Relationship between Insulin Sensitivity and Cardiovascular Risk (RISC) study.

One-hour plasma glucose correlated better than 2-h plasma glucose with total insulin secretion (r = 0.43), β-cell glucose sensitivity (r = –0.46), and β-cell rate sensitivity (r = –0.18). Receiver operating characteristic analysis identified 8.95 mmol/l as the best cutoff value for prediction of IGT from 1-h plasma glucose (sensitivity 77% and specificity 80%). Participants with NGT with 1-h plasma glucose >8.95 mmol/l had larger waist circumference, higher BMI, lower insulin sensitivity, higher fasting glucose, and higher insulin secretion than their counterparts with 1-h plasma glucose ≤8.95 mmol/l (P < 0.001 for all comparisons). Moreover, they exhibited lower β-cell glucose sensitivity (P < 0.001), β-cell rate sensitivity (P < 0.001), and potentiation factor (P = 0.026). When compared with conventionally defined IGT, they were not different in waist circumference and BMI, hepatic insulin extraction, β-cell glucose sensitivity, β-cell rate sensitivity, and potentiation factor but did have greater insulin sensitivity along with reduced basal (P = 0.001) and total insulin secretion (P = 0.002).

Higher values of 1-h plasma glucose may identify an intermediate condition between NGT and IGT characterized by greater insulin resistance, reduced β-cell glucose sensitivity, and reduced β-cell rate sensitivity.

Diabetes is a predictor of both coronary artery disease (CAD) and heart failure. It is unknown to what extent the association between diabetes and heart failure is influenced by other risk factors for heart failure.

We evaluated the association of diabetes and A1C with incident heart failure in outpatients with stable CAD and no history of heart failure (average follow-up 4.1 years).

Of 839 participants, 200 had diabetes (23.8%). Compared with patients who did not have diabetes, those with diabetes had an increased risk of heart failure (hazard ratio [HR] 2.17 [95% CI 1.37–3.44]). Adjustment for risk factors for CAD (age, sex, race, smoking, physical inactivity, obesity, blood pressure, and LDL cholesterol), interim myocardial infarction, and myocardial ischemia did not alter the strength of the association between diabetes and heart failure. After inclusion also of other risk factors for heart failure (left ventricular ejection fraction, diastolic dysfunction, and C-reactive protein) and medication use, diabetes remained an independent predictor of heart failure (HR 3.34 [95% CI 1.65–6.76]; P = 0.001). Each 1% increase in A1C concentration was associated with a 36% increased HR of heart failure hospitalization (HR 1.36 [95% CI 1.17–1.58]).

In patients with stable CAD who are free from heart failure at baseline, diabetes and glycemic control are independent risk factors for new-onset heart failure. The mechanisms by which diabetes and hyperglycemia lead to heart failure deserve further study, as the association is independent of baseline functional assessment of ischemia, systolic and diastolic function, and interim myocardial infarction.