VAT=TAAT‐SAAT: Innovative anthropometric model to predict visceral adipose tissue without resort to CT‐Scan or DXA |
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| Authors: | Hanen Samouda Anne Dutour Kathia Chaumoitre Michel Panuel Olivier Dutour Frédéric Dadoun |
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| Institution: | 1. Public Health Department, Health Studies Center, Center de Recherche Public‐Santé, L‐1445 Strassen, Luxembourg;2. Endocrinology and Nutrition Department, H?pital Nord, AP‐HM, F‐13915 Marseille Cedex 20, France;3. INSERM Department Université de la Méditerranée, Faculté de Médecine Timone, F‐13385 Marseille, France;4. Medical Imaging Department, H?pital Nord, AP‐HM, F‐13915 Marseille Cedex 20, France;5. Research Unit Department 6578 ? Adaptabilité bioculturelle ?—CNRS/Université de la Méditerranée. Faculté de Médecine—Secteur Nord, F‐ 13916 Marseille Cedex 20, France;6. Department of Anthropology, University of Toronto, 19 Russel Street, Toronto, ON, Canada |
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| Abstract: | 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; R2 = 0.836. Men: VAT = 6 × Waist C ? 4.41 × proximal thigh C + 1.19 × Age ? 213.65; R2 = 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: R2 = 76%; Men: R2 = 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). |
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