Clinical Usefulness of a New Equation for Estimating Body Fat

  1. Gema Frühbeck, MD, PHD1,2,3
  1. 1Metabolic Research Laboratory, Clínica Universidad de Navarra, Pamplona, Spain
  2. 2Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ICSCIII), Girona, Spain
  3. 3Department of Endocrinology and Nutrition, Clínica Universidad de Navarra, Pamplona, Spain
  1. Corresponding author: Javier Gómez-Ambrosi, jagomez{at}unav.es.

Abstract

OBJECTIVE To assess the predictive capacity of a recently described equation that we have termed CUN-BAE (Clínica Universidad de Navarra-Body Adiposity Estimator) based on BMI, sex, and age for estimating body fat percentage (BF%) and to study its clinical usefulness.

RESEARCH DESIGN AND METHODS We conducted a comparison study of the developed equation with many other anthropometric indices regarding its correlation with actual BF% in a large cohort of 6,510 white subjects from both sexes (67% female) representing a wide range of ages (18–80 years) and adiposity. Additionally, a validation study in a separate cohort (n = 1,149) and a further analysis of the clinical usefulness of this prediction equation regarding its association with cardiometabolic risk factors (n = 634) was carried out.

RESULTS The mean BF% in the cohort of 6,510 subjects determined by air displacement plethysmography was 39.9 ± 10.1%, and the mean BF% estimated by the CUN-BAE was 39.3 ± 8.9% (SE of the estimate, 4.66%). In this group, BF% calculated with the CUN-BAE showed the highest correlation with actual BF% (r = 0.89, P < 0.000001) compared with other anthropometric measures or BF% estimators. Similar agreement was found in the validation sample. Moreover, BF% estimated by the CUN-BAE exhibits, in general, better correlations with cardiometabolic risk factors than BMI as well as waist circumference in the subset of 634 subjects.

CONCLUSIONS CUN-BAE is an easy-to-apply predictive equation that may be used as a first screening tool in clinical practice. Furthermore, our equation may be a good tool for identifying patients at cardiovascular and type 2 diabetes risk.

  • Received July 15, 2011.
  • Accepted October 24, 2011.

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