title: Visceral adiposity and its anatomical distribution as predictors of the metabolic syndrome and cardiometabolic risk factor levels.
abstract: BACKGROUND
  Despite the recognition that central obesity plays a critical role in chronic disease, few large-scale imaging studies have documented human variation in abdominal adipose tissue patterning.
  
  
  OBJECTIVE
  We aimed to compare the associations between abdominal subcutaneous adipose tissue (ASAT) and visceral abdominal tissue (VAT), which were measured at different locations across the abdomen, and the presence of the metabolic syndrome (MS; National Cholesterol Education Program Adult Treatment Panel III definition) and individual cardiometabolic risk factors.
  
  
  METHODS
  This study included 713 non-Hispanic whites aged 18-86 y, in whom VAT and ASAT were assessed by using multiple-image magnetic resonance imaging. The anatomical position of the magnetic resonance image containing the maximum VAT area for each subject was used as a measure of VAT patterning. Multivariate linear and logistic regression analyses were used to examine the relation of VAT, ASAT, and VAT patterning to cardiometabolic risk.
  
  
  RESULTS
  VAT mass was a stronger predictor of the MS than was ASAT mass, but ASAT mass (and other measures of subcutaneous adiposity) had signification interactions with VAT mass, whereby elevated ASAT reduced the probability of MS among men with high VAT (P = 0.0008). There was variation across image locations in the association of VAT area with the MS in men, and magnetic resonance images located 4-8 cm above L4-L5 provided the strongest correlations between VAT area and cardiometabolic risk factors. Subjects whose maximum VAT area was higher in the abdomen had higher LDL-cholesterol concentrations (R(2) = 0.07, P < 0.0001), independent of age and adiposity.
  
  
  CONCLUSIONS
  Further studies are needed to confirm the effects of VAT patterning on cardiometabolic risk.
authors.affiliation: Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN 55454-1015, USA. ewd@umn.edu
authors.forename: Ellen W
authors.initials: EW
authors.lastname: Demerath
authors.forename: Derek
authors.initials: D
authors.lastname: Reed
authors.forename: Nikki
authors.initials: N
authors.lastname: Rogers
authors.forename: Shumei S
authors.initials: SS
authors.lastname: Sun
authors.forename: Miryoung
authors.initials: M
authors.lastname: Lee
authors.forename: Audrey C
authors.initials: AC
authors.lastname: Choh
authors.forename: William
authors.initials: W
authors.lastname: Couch
authors.forename: Stefan A
authors.initials: SA
authors.lastname: Czerwinski
authors.forename: W Cameron
authors.initials: WC
authors.lastname: Chumlea
authors.forename: Roger M
authors.initials: RM
authors.lastname: Siervogel
authors.forename: Bradford
authors.initials: B
authors.lastname: Towne
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001823:Body Composition / Q000502:physiology*; D002318:Cardiovascular Diseases / Q000453:epidemiology* / Q000209:etiology / Q000378:metabolism; D005260:Female; D006801:Humans; D050152:Intra-Abdominal Fat / Q000378:metabolism / Q000503:physiopathology*; D016014:Linear Models; D016015:Logistic Models; D008279:Magnetic Resonance Imaging; D008297:Male; D024821:Metabolic Syndrome / Q000453:epidemiology* / Q000209:etiology / Q000378:metabolism; D008875:Middle Aged; D015999:Multivariate Analysis; D009765:Obesity / Q000378:metabolism*; D011237:Predictive Value of Tests; D012307:Risk Factors; D050151:Subcutaneous Fat / Q000378:metabolism / Q000503:physiopathology