BACKGROUND: Visceral adipose tissue (VAT) is widely recognized as conveying the highest health risk in humans among the currently measurable adipose tissue compartments. A recent study indicated that the traditionally measured VAT area at L(4)-L(5) is not the VAT area with the highest correlation with total VAT volume. At present, it is unknown whether the area with the highest correlation is also the most strongly associated with obesity-related health risk. OBJECTIVE: The study aim was to establish which VAT slice area(s) are most strongly associated with obesity-related health risk indicators. DESIGN: The subjects were a convenience sample of healthy adults who completed whole-body magnetic resonance imaging (MRI) scans. The correlations, with appropriate adjustments, were examined between individual MRI slice VAT areas and fasting serum/plasma triglycerides (TG), high-density lipoprotein cholesterol (HDL), glucose, insulin and blood pressure. RESULTS: The sample consisted of 283 healthy men (age (mean+/-s.d.) 41.9+/-15.8 years; BMI, 26.0+/-3.2 kg/m(2); VAT, 2.7+/-1.8 L) and 411 women (age, 48.1+/-18.7 years; BMI 27.0+/-5.4 kg/m(2); VAT, 1.7+/-1.2 L). After adjusting for age, race, menopause status, scan position and specific blood analysis laboratory, VAT area at L(4)-L(5) had lower correlations with most metabolic risk factors including serum/plasma TG, HDL, glucose, insulin and blood pressure than VAT volume in both men and women. The VAT areas 10 and 15 cm above L(4)-L(5) in men had higher or equal correlations with health risk measures than VAT volume. In women, the VAT area 5 cm above or below L(4)-L(5) and total VAT volume had similar correlations with health risk measures. CONCLUSIONS: An appropriately selected single slice VAT area is an equally reliable phenotypic marker of obesity-related health risk as total VAT volume. However, in both men and women the VAT slice area at the traditional L(4)-L(5) level is not the best marker of obesity-related health risk.
BACKGROUND: Visceral adipose tissue (VAT) is widely recognized as conveying the highest health risk in humans among the currently measurable adipose tissue compartments. A recent study indicated that the traditionally measured VAT area at L(4)-L(5) is not the VAT area with the highest correlation with total VAT volume. At present, it is unknown whether the area with the highest correlation is also the most strongly associated with obesity-related health risk. OBJECTIVE: The study aim was to establish which VAT slice area(s) are most strongly associated with obesity-related health risk indicators. DESIGN: The subjects were a convenience sample of healthy adults who completed whole-body magnetic resonance imaging (MRI) scans. The correlations, with appropriate adjustments, were examined between individual MRI slice VAT areas and fasting serum/plasma triglycerides (TG), high-density lipoprotein cholesterol (HDL), glucose, insulin and blood pressure. RESULTS: The sample consisted of 283 healthy men (age (mean+/-s.d.) 41.9+/-15.8 years; BMI, 26.0+/-3.2 kg/m(2); VAT, 2.7+/-1.8 L) and 411 women (age, 48.1+/-18.7 years; BMI 27.0+/-5.4 kg/m(2); VAT, 1.7+/-1.2 L). After adjusting for age, race, menopause status, scan position and specific blood analysis laboratory, VAT area at L(4)-L(5) had lower correlations with most metabolic risk factors including serum/plasma TG, HDL, glucose, insulin and blood pressure than VAT volume in both men and women. The VAT areas 10 and 15 cm above L(4)-L(5) in men had higher or equal correlations with health risk measures than VAT volume. In women, the VAT area 5 cm above or below L(4)-L(5) and total VAT volume had similar correlations with health risk measures. CONCLUSIONS: An appropriately selected single slice VAT area is an equally reliable phenotypic marker of obesity-related health risk as total VAT volume. However, in both men and women the VAT slice area at the traditional L(4)-L(5) level is not the best marker of obesity-related health risk.
Authors: Wei Shen; ZiMian Wang; Mark Punyanita; Jianbo Lei; Ahmet Sinav; John G Kral; Celina Imielinska; Robert Ross; Steven B Heymsfield Journal: Obes Res Date: 2003-01
Authors: Jack Wang; John C Thornton; Salina Bari; Bennett Williamson; Dympna Gallagher; Steven B Heymsfield; Mary Horlick; Donald Kotler; Blandine Laferrère; Laurel Mayer; F Xavier Pi-Sunyer; Richard N Pierson Journal: Am J Clin Nutr Date: 2003-02 Impact factor: 7.045
Authors: J C Seidell; A Oosterlee; M A Thijssen; J Burema; P Deurenberg; J G Hautvast; J H Ruijs Journal: Am J Clin Nutr Date: 1987-01 Impact factor: 7.045
Authors: Marshall K Tulloch-Reid; Robert L Hanson; Nancy G Sebring; James C Reynolds; Ahalya Premkumar; David J Genovese; Anne E Sumner Journal: Obes Res Date: 2004-08
Authors: Barbara J Nicklas; Brenda W J H Penninx; Matteo Cesari; Stephen B Kritchevsky; Anne B Newman; Alka M Kanaya; Marco Pahor; Ding Jingzhong; Tamara B Harris Journal: Am J Epidemiol Date: 2004-10-15 Impact factor: 4.897
Authors: Cristina Palacios; Cynthia M Pérez; Manuel Guzmán; Ana P Ortiz; Alelí Ayala; Erick Suárez Journal: Public Health Nutr Date: 2011-05-24 Impact factor: 4.022
Authors: Ellen W Demerath; Derek Reed; Nikki Rogers; Shumei S Sun; Miryoung Lee; Audrey C Choh; William Couch; Stefan A Czerwinski; W Cameron Chumlea; Roger M Siervogel; Bradford Towne Journal: Am J Clin Nutr Date: 2008-11 Impact factor: 7.045