title: Relationship between the Bertin index to estimate visceral adipose tissue from dual-energy X-ray absorptiometry and cardiometabolic risk factors before and after weight loss.
abstract: The purpose of this study was to investigate the relationship between visceral adipose tissue (VAT), estimated with the Bertin index obtained from dual-energy X-ray absorptiometry (DXA), with cardiometabolic risk factors before and after a weight loss program and compare it with VAT measured with computed tomography (CT) scan. The study population for this analysis included 92 nondiabetic overweight and obese sedentary postmenopausal women (age: 58.1 ± 4.7 years, BMI: 31.8 ± 4.2 kg/m(2)) participating in a weight loss intervention that consisted of a caloric restricted diet with and without resistance training (RT). We measured (i) VAT using CT scan, (ii) body composition (using DXA) from which the Bertin index was calculated, (iii) cardiometabolic risk factors such as insulin sensitivity (using the hyperinsulinenic-euglycemic clamp technique), peak oxygen consumption, blood pressure, plasma lipids, C-reactive protein as well as fasting glucose and insulin. VAT levels for both methods significantly decreased after the weight loss intervention. Furthermore, no differences in VAT levels between both methods were observed before (88.0 ± 25.5 vs. 83.8 ± 22.0 cm(2)) and after (76.8 ± 27.8 vs. 73.6 ± 23.2 cm(2)) the weight loss intervention. In addition, the percent change in VAT levels after the weight loss intervention was similar between both methods (-13.0 ± 16.5 vs. -12.5 ± 12.6%). Moreover, similar relationships were observed between both measures of VAT with cardiometabolic risk factors before and after the weight loss intervention. Finally, results from the logistic regression analysis consistently showed that fat mass and lean body mass were independent predictors of pre- and post-VAT levels for both methods in our cohort. In conclusion, estimated visceral fat levels using the Bertin index may be able to trace variations of VAT after weight loss. This index also shows comparable relationships with cardiometabolic risk factors when compared to VAT measured using CT scan.
authors.affiliation: Department of Kinanthropology, Université du Québec à Montréal, Montreal, Quebec, Canada. Karelis.antony@uqam.ca
authors.forename: Antony D
authors.initials: AD
authors.lastname: Karelis
authors.forename: Rémi
authors.initials: R
authors.lastname: Rabasa-Lhoret
authors.forename: Roseline
authors.initials: R
authors.lastname: Pompilus
authors.forename: Virginie
authors.initials: V
authors.lastname: Messier
authors.forename: Irene
authors.initials: I
authors.lastname: Strychar
authors.forename: Martin
authors.initials: M
authors.lastname: Brochu
authors.forename: Mylene
authors.initials: M
authors.lastname: Aubertin-Leheudre
mesh_terms: D015502:Absorptiometry, Photon / Q000379:methods*; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000378:metabolism / Q000473:pathology* / Q000517:prevention & control; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D050152:Intra-Abdominal Fat / Q000473:pathology*; D008659:Metabolic Diseases / Q000378:metabolism / Q000473:pathology* / Q000517:prevention & control; D008875:Middle Aged; D009765:Obesity / Q000378:metabolism / Q000473:pathology*; D011237:Predictive Value of Tests; D012307:Risk Factors; D014057:Tomography, X-Ray Computed; D015431:Weight Loss; D061217:Weight Reduction Programs