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Diabetes Technology & Therapeutics
Correlation Between Anthropometric Parameters and Abdominal Fat Volumes Assessed by a Magnetic Resonance Imaging Method in Patients with Diabetes

To cite this article:
Ludger Wilhelm Poll, Hans-Jörg Wittsack, Reinhart Willers, Ulrich Mödder, Lutz Heinemann, Christoph Kapitza, Klaus Rave. Diabetes Technology & Therapeutics. December 2004, 6(6): 844-849. doi:10.1089/dia.2004.6.844.

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Dr. Ludger Wilhelm Poll, M.D.
Institute of Diagnostic Radiology, Heinrich-Heine-University, Düsseldorf, Germany.
Hans-Jörg Wittsack, Ph.D.
Institute of Diagnostic Radiology, Heinrich-Heine-University, Düsseldorf, Germany.
Reinhart Willers, Ph.D.
Statistical Department, Heinrich-Heine-University, Düsseldorf, Germany.
Ulrich Mödder, M.D.
Institute of Diagnostic Radiology, Heinrich-Heine-University, Düsseldorf, Germany.
Lutz Heinemann, Ph.D.
Profil Institute for Metabolic Research GmbH, Neuss, Germany.
Christoph Kapitza, M.D.
Profil Institute for Metabolic Research GmbH, Neuss, Germany.
Klaus Rave, M.D.
Profil Institute for Metabolic Research GmbH, Neuss, Germany.

Background: Anthropometric measurements such as body mass index (BMI), waist-to-hip ratio, or waist circumference are used in clinical settings as a rough estimation of abdominal fat volumes. In contrast, abdominal magnetic resonance imaging (MRI) allows a precise and noninvasive imaging modality to measure the whole abdominal fat volumes. The main difference between the two methods is that only MRI provides detailed anatomical information about fat distribution in terms of a three-dimensional volumetric model. The aim of this study was to evaluate the relationship between selected anthropometric parameters and MRI-estimated abdominal fat volumes in patients with diabetes.

Methods: Total fat volume coverage of the abdomen was obtained in a total of 37 patients with diabetes (mean ± SD age, 48 ± 13 years) with a BMI of 27.9 ± 3.6 kg/m2 and a waist-tohip ratio of 0.94 ± 0.01 using T1-weighted magnetic resonance images. Quantification of intraabdominal, subcutaneous, and total abdominal fat volumes was performed using a semiautomated computer-assisted analysis of the images. Anthropometric parameters (height, weight, BMI, circumference hip, waist circumference, and waist-to-hip ratio) of all patients and abdominal fat volumes estimated by the MRI method proposed were correlated.

Results: The volumes estimated were as follows: intraabdominal fat, 10.5 ± 5.0 L; subcutaneous fat, 15.2 ± 7.3 L; and total abdominal fat, 25.7 ± 11.5 L. The correlation coefficients between BMI and the three different fat volumes were, respectively, r = 0.38, r = 0.31, and r = 0.36. For the waist-to-hip ratio the respective correlation coefficients were r = 0.46, r = 0.14, and r = 0.29.

Conclusions: Correlation in patients with diabetes of abdominal fat volumes estimated with a reliable MRI method with conventionally applied anthropometric parameters revealed poor correlation coefficients. In contrast, the fat volume determination by means of the novel MRI analysis method is rapid and reliable. Therefore, this method has the potential to be of high value in studies in patients with diabetes.

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