title: Correlation of fat distribution in whole body MRI with generally used anthropometric data.
abstract: OBJECTIVE
  : Obesity is a commonly known risk for many diseases such as metabolic syndrome and cardiovascular disease. Especially important is the discrimination of the adipose tissue inside the abdomen and the subcutaneous adipose tissue. Aim of this study was to compare the whole body fat distribution, and the volume of different adipose tissue compartments respectively, with anthropometric data.
  
  
  METHODS
  : Sixty-eight volunteers (20 males, 48 females, 42.3 +/- 15.4 years) were investigated in the context of 2 whole body magnetic resonance imaging (MRI) studies which compared the body fat distribution of depressive and bulimic patients with healthy controls. Unpublished data acquired in these studies were analyzed retrospectively.The sample consisted of 38 healthy volunteers, 17 patients with a depressive syndrome and 13 women suffering from bulimia nervosa. Individual body volume, total adipose tissue (TAT) volume, subcutaneous adipose tissue (SCAT) volume at the trunk, and visceral adipose tissue (VAT) volume were determined, using whole body MRI. Additionally, body fat profiles were standardized and a mean body distribution was calculated. Other modalities to acquire body fat content were: skin fold caliper, body impedance (3 different devices) and simple anthropometric data (Waist to Hip Ratio [WHR], Body Mass Index [BMI], distance of the aponeurosis of the rectus abdominis muscle to the ventral rim of the abdominal aorta (measured in MRI images on umbilical level) (AD) and subcutaneous adipose tissue thickness at the same level). The different modalities were correlated with the MRI data.
  
  
  RESULTS
  : There were highly significant correlations between the skin fold data and TAT (Spearman coefficient 0.668, P >/= 0.0004) and SCAT (0.662, P >/= 0.0004). But there was no correlation with VAT. Impedance data revealed significant correlations of TAT and SCAT (Spearman 0.7, P >/= 0.0004).Simple anthropometric data like waist and hip circumference, WHR, and BMI revealed significant correlations (Spearman coefficient around 0.7-0.4, P < 0.05) with the fat compartments TAT, VAT, and SCAT.The standardized body fat slices and the VAT slices were correlated with the anthropometric data and impedance data to explore specific areas along the body axis where the correlations were higher or weaker. Skinfold data, BMI, and body impedance data yielded significant correlations with TAT along the whole body axis, as well as with VAT in almost the whole analyzed area. However, there was no special body region with locally higher correlations. WHR depicted high correlations with whole VAT, and regional TAT at the abdomen (and not with the other body regions) especially in women. Therefore, it seems to be the best marker for abdominal fat and VAT in this study.
  
  
  CONCLUSIONS
  : We compared different body measures and body fat devices with the whole body fat distribution acquired by MRI. Generally, there were significant correlations of all modalities with body fat content (TAT) and mainly with SCAT. Correlations with VAT compartment were much weaker and an adequate estimation of VAT is, therefore, not possible. Only WHR revealed significant correlations with the fat in the body center, but only in women. If it is important to investigate especially the VAT which is responsible for a higher cardiovascular risk, risk for a metabolic syndrome and that is correlated with the course of different psychiatric diseases, cross sectional techniques such as MRI can not be substituted by simpler methods.
authors.affiliation: Section on Experimental Radiology, Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Tuebingen, Germany. burkhardludescher@web.de
authors.forename: Burkhard
authors.initials: B
authors.lastname: Ludescher
authors.forename: Juergen
authors.initials: J
authors.lastname: Machann
authors.forename: Gerhard W
authors.initials: GW
authors.lastname: Eschweiler
authors.forename: Stefanie
authors.initials: S
authors.lastname: Vanhöfen
authors.forename: Constantin
authors.initials: C
authors.lastname: Maenz
authors.forename: Claus
authors.initials: C
authors.lastname: Thamer
authors.forename: Claus D
authors.initials: CD
authors.lastname: Claussen
authors.forename: Fritz
authors.initials: F
authors.lastname: Schick
mesh_terms: D000328:Adult; D000465:Algorithms; D000886:Anthropometry / Q000379:methods*; D050218:Body Fat Distribution / Q000379:methods*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D051598:Whole Body Imaging / Q000379:methods*