title: Sagittal abdominal diameter as a marker for epicardial adipose tissue in premenopausal women.
abstract: OBJECTIVE
  Accumulation of epicardial (EAT) adipose tissue is associated with the development of an unfavorable metabolic risk profile. Gold standard methods used to assess this fat depot are not routinely applicable in the clinic. Anthropometric measures, including the sagittal abdominal diameter (SAD), have emerged as surrogate markers of visceral obesity. We determined the relationship between EAT measurement and cardiometabolic risk parameters and the potential use of the SAD, compared with other anthropometric parameters, as a practical estimation of EAT.
  
  
  METHODS
  Sixty-seven premenopausal women were evaluated. The anthropometric parameters that were measured included waist circumference, SAD, body mass index and waist-to-hip ratio. EAT was determined by echocardiogram. Visceral adipose tissue (VAT) was determined by abdominal ultrasound. Insulin sensitivity was assessed by the hyperglycemic clamp.
  
  
  RESULTS
  The accumulation of EAT was correlated with impaired insulin sensitivity and decreased adiponectin. All of the anthropometric measurements were correlated with EAT. Interestingly, EAT was most significantly correlated with the SAD. From the ROC analysis, we found that the SAD measurements were very accurate, presenting the highest area under the curve for EAT (0.81; p<0.01) when compared with the other measurements. In the multiple linear regression analysis, EAT was moderately predicted by the SAD (R²=0.25; p<0.001).
  
  
  CONCLUSIONS
  SAD, a simple anthropometric measure, accurately estimated EAT and thus represents a clinically useful non-invasive marker that can identify patients with EAT accumulation.
authors.affiliation: Department of Internal Medicine, Laboratory of Investigation on Metabolism and Diabetes LIMED, School of Medicine, State University of Campinas, Campinas, Brazil. anacarolinavasques@yahoo.com.br
authors.forename: Ana Carolina Junqueira
authors.initials: AC
authors.lastname: Vasques
authors.forename: José Roberto Matos
authors.initials: JR
authors.lastname: Souza
authors.forename: Ademar
authors.initials: A
authors.lastname: Yamanaka
authors.forename: Maria da Saúde
authors.initials: Mda S
authors.lastname: de Oliveira
authors.forename: Fernanda Satake
authors.initials: FS
authors.lastname: Novaes
authors.forename: José Carlos
authors.initials: JC
authors.lastname: Pareja
authors.forename: Bruno
authors.initials: B
authors.lastname: Geloneze
mesh_terms: D000005:Abdomen / Q000000981:diagnostic imaging / Q000473:pathology*; D052242:Adiponectin / Q000097:blood; D052436:Adipose Tissue, White / Q000000981:diagnostic imaging / Q000473:pathology*; D050154:Adiposity; D000328:Adult; D015415:Biomarkers; D015992:Body Mass Index; D049628:Body Size; D003430:Cross-Sectional Studies; D004452:Echocardiography; D005260:Female; D006801:Humans; D007333:Insulin Resistance; D050152:Intra-Abdominal Fat / Q000000981:diagnostic imaging / Q000473:pathology; D009765:Obesity / Q000097:blood / Q000175:diagnosis / Q000000981:diagnostic imaging / Q000473:pathology*; D056128:Obesity, Abdominal / Q000097:blood / Q000175:diagnosis / Q000000981:diagnostic imaging / Q000473:pathology; D010496:Pericardium / Q000000981:diagnostic imaging / Q000473:pathology*; D011237:Predictive Value of Tests; D017697:Premenopause; D012372:ROC Curve
chemical_list: C499918:ADIPOQ protein, human; D052242:Adiponectin; D015415:Biomarkers