title: Dual energy X-ray absorptiometry assessment of fat mass distribution and its association with the insulin resistance syndrome.
abstract: OBJECTIVE
  To determine which dual energy X-ray absorptiometry (DXA)-derived indices of fat mass distribution are the most informative to predict the various parameters of the metabolic syndrome.
  
  
  METHODS
  A total of 87 healthy men, 63 lean (% fat < or =26) and 24 obese (% fat >26), underwent DXA scanning to evaluate body composition with respect to the whole body and the trunk, leg, and abdominal regions from L1 to L4 and from L3 to L4. These regions were correlated with insulin sensitivity determined by the euglycemic-hyperinsulinemic clamp, insulin area under the curve after oral glucose tolerance test (AUC I); triglyceride; total, HDL, and LDL cholesterol; free fatty acids; and blood pressure. The analyses were performed in all subjects, as well as in lean and obese groups separately.
  
  
  RESULTS
  Among the various indices of body fat, DXA-determined adiposity in the abdominal cut at L1-4 level was the most predictive of the metabolic variables, showing significant relationships with glucose infusion rate ([GIR], mg kg(-1) lean body mass x min(-1)), triglyceride, and cholesterol, independent of total-body mass (r = -0.267, P<0.05; r = 0.316, P<0.005; and r = 0.319, P<0.005, respectively). Upon subanalysis, these correlations remained significant in lean men, whereas in obese men, only BMI and the amount of leg fat (negative relationship) showed significant correlations with triglyceride and cholesterol (r = 0.438, P<0.05; r = 0.458, P<0.05; r = -0.439, P<0.05; and r = -0.414, P<0.05, respectively). The results of a multiple regression analysis revealed that 47% of the variance in GIR among all study subjects was predicted by AUC I, fat L1-4, diastolic blood pressure (dBP), HDL, and triglyceride as independent variables. In the lean group, fat L1-4 alone accounted for 33% of the variance of GIR, whereas in obese men, AUC I and dBP explained 68% of the variance in GIR.
  
  
  CONCLUSIONS
  The DXA technique applied for the evaluation of fat distribution can provide useful information regarding various aspects of the insulin resistance syndrome in healthy subjects. DXA can be a valid, accurate, relatively inexpensive, and safer alternative compared with other methods to investigate the role of abdominal body fat distribution on cardiovascular risk factors.
authors.affiliation: Indiana University Medical Center and the Richard L. Roudebush Veterans Affairs Medical Center, Indianapolis, USA.
authors.forename: G
authors.initials: G
authors.lastname: Paradisi
authors.forename: L
authors.initials: L
authors.lastname: Smith
authors.forename: C
authors.initials: C
authors.lastname: Burtner
authors.forename: R
authors.initials: R
authors.lastname: Leaming
authors.forename: W T
authors.initials: WT
authors.lastname: Garvey
authors.forename: G
authors.initials: G
authors.lastname: Hook
authors.forename: A
authors.initials: A
authors.lastname: Johnson
authors.forename: J
authors.initials: J
authors.lastname: Cronin
authors.forename: H O
authors.initials: HO
authors.lastname: Steinberg
authors.forename: A D
authors.initials: AD
authors.lastname: Baron
mesh_terms: D015502:Absorptiometry, Photon; D000273:Adipose Tissue / Q000502:physiology*; D000328:Adult; D001794:Blood Pressure / Q000502:physiology; D001823:Body Composition / Q000502:physiology*; D002241:Carbohydrates / Q000097:blood; D005069:Evaluation Studies as Topic; D015309:Glucose Clamp Technique; D006801:Humans; D007333:Insulin Resistance; D016014:Linear Models; D008055:Lipids / Q000097:blood; D008297:Male; D011237:Predictive Value of Tests; D012044:Regression Analysis; D013577:Syndrome
chemical_list: D002241:Carbohydrates; D008055:Lipids