Obesity. 2013 Jan;21(1):E41-50. doi: 10.1002/oby.20033.

VAT=TAAT-SAAT: innovative anthropometric model to predict visceral adipose tissue without resort to CT-Scan or DXA.

Samouda H, Dutour A, Chaumoitre K, Panuel M, Dutour O, Dadoun F.

Public Health Department, Health Studies Center, Center de Recherche Public-Santé, L-1445 Strassen, Luxembourg. hanene.samouda@crp-sante.lu



OBJECTIVE: To investigate whether a combination of a selected but limited number of anthropometric measurements predicts visceral adipose tissue (VAT) better than other anthropometric measurements, without resort to medical imaging.

HYPOTHESIS: Abdominal anthropometric measurements are total abdominal adipose tissue indicators and global measures of VAT and SAAT (subcutaneous abdominal adipose tissue). Therefore, subtracting the anthropometric measurement the more correlated possible with SAAT while being the least correlated possible with VAT, from the most correlated abdominal anthropometric measurement with VAT while being highly correlated with TAAT, may better predict VAT.

DESIGN AND METHODS: BMI participants’ range was from 16.3 to 52.9 kg m(-2) . Anthropometric and abdominal adipose tissues data by computed tomography (CT-Scan) were available in 253 patients (18-78 years) (CHU Nord, Marseille) and used to develop the anthropometric VAT prediction models.

RESULTS: Subtraction of proximal thigh circumference from waist circumference, adjusted to age and/or BMI, predicts better VAT (Women: VAT = 2.15 × Waist C – 3.63 × Proximal Thigh C + 1.46 × Age + 6.22 × BMI – 92.713; R(2) = 0.836. Men: VAT = 6 × Waist C – 4.41 × proximal thigh C + 1.19 × Age – 213.65; R(2) = 0.803) than the best single anthropometric measurement or the association of two anthropometric measurements highly correlated with VAT. Both multivariate models showed no collinearity problem. Selected models demonstrate high sensitivity (97.7% in women, 100% in men). Similar predictive abilities were observed in the validation sample (Women: R(2) = 76%; Men: R(2) = 70%). Bland and Altman method showed no systematic estimation error of VAT.

CONCLUSION: Validated in a large range of age and BMI, our results suggest the usefulness of the anthropometric selected models to predict VAT in Europides (South of France).

Copyright © 2013 The Obesity Society.

PMID: 23404678



Obesity constitutes an extreme morphology and body composition human variability expression (fat versus fat free mass). Worldwide obesity trends and associated complications are currently epidemic.

Visceral adipose tissue (VAT), a deep fat, constitutes the most dangerous body fat compartment associated with diabetes and heart attack, in particular.

Body Mass Index (BMI), and sometimes some other anthropometric measurements such as waist circumference, waist to hip ratio or skinfold thickness, are traditionally used to describe and diagnose overweight and obesity. However, this kind of measurement does not assess body composition, and in particular visceral fat, with a high level of precision.

Recent developments of biomedical imaging techniques such as DEXA (Dual Energy-X-ray Absorptiometry), CT Scan (Computed Tomography Scan) and/or MRI (Magnetic Resonance Imagery) allow accurate measurements of abdominal and/or visceral adipose tissues, but the use of these tools remains expensive and often limited to a few medical environments.

The objective of our work was to use the CT Scan technology to update the simple anthropometric methods for a more precise, accurate and accessible assessment of visceral adipose tissue excess.

Our method includes a very simple and limited number of anthropometric measurements, which can easily and precisely be used in the medical environment and outside:

In women:

VAT = 2.15 × Waist Circumference – 3.63 × Proximal Thigh Circumference + 1.46 × Age + 6.22 × BMI – 92.713.

In men:

VAT = 6 × Waist Circumference – 4.41 × Proximal Thigh Circumference + 1.19 × Age – 213.65.

As showed in the CT Scan attached figures 1 and 2, abdominal fat or total abdominal adipose tissue (TAAT) containing both visceral adipose tissue and subcutaneous abdominal adipose tissue (SAAT), we based our VAT anthropometric prediction models on the subtraction of the anthropometric measure the more correlated with SAAT from the anthropometric measure the more correlated with TAAT.

The anthropometric visceral adipose prediction models obtained were very strongly correlated with the CT Scan VAT measurements, the gold standard method. Moreover, the combination of 2 simple anthropometric measurements together with age and/or BMI largely improved VAT prediction whereas the VAT prediction using BMI, waist circumference or waist to hip ratio as a single parameter were less accurate. On the other hand, indirect anthropometric surrogates of limb fatness appear to improve substantially VAT prediction, probably because they provide an estimate of SAAT and help differentiate abdominal fat compartments.

 Hanen Samouda-1Figure 1: Cross-sectional abdominal CT-Scan of Total Abdominal Adipose Tissue (TAAT)


 Hanen Samouda-2

Cross-sectional abdominal CT-Scan of:

                  Figure 2a: Visceral Adipose Tissue (VAT)                 Figure 2b: Subcutaneous Abdominal Adipose Tissue (SAAT)

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