Context: Body mass index (BMI) is widely used as a measure of overweight and obesity, but underestimates the prevalence of both conditions, defined as an excess of body fat. Objective: We assessed the degree of misclassification on the diagnosis of obesity using BMI as compared with direct body fat percentage (BF%) determination and compared the cardiovascular and metabolic risk of non-obese and obese BMI-classified subjects with similar BF%. Design: We performed a cross-sectional study. Subjects: A total of 6123 (924 lean, 1637 overweight and 3562 obese classified according to BMI) Caucasian subjects (69% females), aged 18-80 years. Methods: BMI, BF% determined by air displacement plethysmography and well-established blood markers of insulin sensitivity, lipid profile and cardiovascular risk were measured. Results: We found that 29% of subjects classified as lean and 80% of individuals classified as overweight according to BMI had a BF% within the obesity range. Importantly, the levels of cardiometabolic risk factors, such as C-reactive protein, were higher in lean and overweight BMI-classified subjects with BF% within the obesity range (men 4.3 ± 9.2, women 4.9 ± 19.5 mg l À1 ) as well as in obese BMI-classified individuals (men 4.2 ± 5.5, women 5.1 ± 13.2 mg l À1 ) compared with lean volunteers with normal body fat amounts (men 0.9 ± 0.5, women 2.1 ± 2.6 mg l À1 ; Po0.001 for both genders). Conclusion: Given the elevated concentrations of cardiometabolic risk factors reported herein in non-obese individuals according to BMI but obese based on body fat, the inclusion of body composition measurements together with morbidity evaluation in the routine medical practice both for the diagnosis and the decision-making for instauration of the most appropriate treatment of obesity is desirable.

Our findings show, for the first time, that insulin and leptin regulate the AQP through the phosphatidylinositol 3-kinase/Akt/mammalian target of rapamycin pathway in human visceral adipocytes and hepatocytes. AQP3 and AQP7 may facilitate glycerol efflux from adipose tissue while reducing the glycerol influx into hepatocytes via AQP9 to prevent the excessive lipid accumulation and the subsequent aggravation of hyperglycemia in human obesity.

We conclude that serum betatrophin is decreased in human obesity, being further reduced in obesity-associated insulin resistance. Betatrophin levels are closely related to obesity-associated cardiometabolic risk factors, emerging as a potential biomarker of insulin resistance and T2D.

OBJECTIVETo assess the predictive capacity of a recently described equation that we have termed CUN-BAE (Clínica Universidad de Navarra-Body Adiposity Estimator) based on BMI, sex, and age for estimating body fat percentage (BF%) and to study its clinical usefulness.RESEARCH DESIGN AND METHODSWe conducted a comparison study of the developed equation with many other anthropometric indices regarding its correlation with actual BF% in a large cohort of 6,510 white subjects from both sexes (67% female) representing a wide range of ages (18–80 years) and adiposity. Additionally, a validation study in a separate cohort (n = 1,149) and a further analysis of the clinical usefulness of this prediction equation regarding its association with cardiometabolic risk factors (n = 634) was carried out.RESULTSThe mean BF% in the cohort of 6,510 subjects determined by air displacement plethysmography was 39.9 ± 10.1%, and the mean BF% estimated by the CUN-BAE was 39.3 ± 8.9% (SE of the estimate, 4.66%). In this group, BF% calculated with the CUN-BAE showed the highest correlation with actual BF% (r = 0.89, P < 0.000001) compared with other anthropometric measures or BF% estimators. Similar agreement was found in the validation sample. Moreover, BF% estimated by the CUN-BAE exhibits, in general, better correlations with cardiometabolic risk factors than BMI as well as waist circumference in the subset of 634 subjects.CONCLUSIONSCUN-BAE is an easy-to-apply predictive equation that may be used as a first screening tool in clinical practice. Furthermore, our equation may be a good tool for identifying patients at cardiovascular and type 2 diabetes risk.

Objectives: The orexigenic hormone ghrelin circulates mainly in two forms, acylated and desacyl ghrelin. We evaluated the impact of obesity and obesity-associated type 2 diabetes (T2D) on ghrelin forms and the potential role of acylated and desacyl ghrelin in the control of adipogenesis in humans. Methods: Plasma concentrations of the different ghrelin forms were measured in 80 subjects. The expression of the ghrelin receptor (growth hormone secretagogue receptor, GHS-R) was analyzed in omental adipose tissue using western blot and immunohistochemistry, and the effect of acylated ghrelin and desacyl ghrelin (0.1-1000 pmol l À1 ) on adipogenesis was determined in vitro in omental adipocytes. Results: Circulating concentrations of acylated ghrelin were increased, whereas desacyl ghrelin levels were decreased, in obesity and obesity-associated T2D. Body mass index, waist circumference, insulin and HOMA (homeostasis model assessment) index were positively correlated with acylated ghrelin levels. Obese individuals showed a lower protein expression of GHS-R in omental adipose tissue. In differentiating omental adipocytes, incubation with both acylated and desacyl ghrelin significantly increased PPARg (peroxisome proliferator-activated receptor g) and SREBP1 (sterol-regulatory element binding protein-1) mRNA levels, as well as several fat storage-related proteins, including acetyl-CoA carboxylase, fatty acid synthase, lipoprotein lipase and perilipin. Consequently, both the ghrelin forms stimulated intracytoplasmatic lipid accumulation. Conclusions: Both acylated and desacyl ghrelin stimulate lipid accumulation in human visceral adipocytes. Given the lipogenic effect of acylated ghrelin on visceral adipocytes, the herein-reported elevation of its circulating concentrations in obese individuals may play a role in excessive fat accumulation in obesity.

These findings represent the first observation that plasma OPN and mRNA expression of OPN in omental adipose tissue are increased in overweight/obese patients with the latter being further elevated in obesity-associated diabetes. Moreover, weight loss reduces OPN concentrations, which may contribute to the beneficial effects accompanying weight reduction. Measurement of OPN might be useful for evaluating the outcomes of various clinical interventions for obesity-related cardiovascular diseases.

Obesity is the major risk factor for the development of prediabetes and type 2 diabetes. BMI is widely used as a surrogate measure of obesity, but underestimates the prevalence of obesity, defined as an excess of body fat. We assessed the presence of impaired glucose tolerance or impaired fasting glucose (both considered together as prediabetes) or type 2 diabetes in relation to the criteria used for the diagnosis of obesity using BMI as compared to body fat percentage (BF%). We performed a cross‐sectional study including 4,828 (587 lean, 1,320 overweight, and 2,921 obese classified according to BMI) white subjects (66% females), aged 18–80 years. BMI, BF% determined by air‐displacement plethysmography (ADP) and conventional blood markers of glucose metabolism and lipid profile were measured. We found a higher than expected number of subjects with prediabetes or type 2 diabetes in the obese category according to BF% when the sample was globally analyzed (P < 0.0001) and in the lean BMI‐classified subjects (P < 0.0001), but not in the overweight or obese‐classified individuals. Importantly, BF% was significantly higher in lean (by BMI) women with prediabetes or type 2 diabetes as compared to those with normoglycemia (NG) (35.5 ± 7.0 vs. 30.3 ± 7.7%, P < 0.0001), whereas no differences were observed for BMI. Similarly, increased BF% was found in lean BMI‐classified men with prediabetes or type 2 diabetes (25.2 ± 9.0 vs. 19.9 ± 8.0%, P = 0.008), exhibiting no differences in BMI or waist circumference. In conclusion, assessing BF% may help to diagnose disturbed glucose tolerance beyond information provided by BMI and waist circumference in particular in male subjects with BMI <25 kg/m2 and over the age of 40.

No abstract