Clinical usefulness of a new equation for estimating body fat

Javier Gómez-Ambrosi, Camilo Silva, Victoria Catalán, Amaia Rodríguez, Juan Carlos Galofré, Javier Escalada, Victor Valentí, Fernando Rotellar, Sonia Romero, Beatriz Ramírez, Javier Salvador, Gema Frühbeck, Javier Gómez-Ambrosi, Camilo Silva, Victoria Catalán, Amaia Rodríguez, Juan Carlos Galofré, Javier Escalada, Victor Valentí, Fernando Rotellar, Sonia Romero, Beatriz Ramírez, Javier Salvador, Gema Frühbeck

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.

Trial registration: ClinicalTrials.gov NCT01055626.

Figures

Figure 1
Figure 1
Bland-Altman plot shows the limits of agreement between BF% estimated using CUN-BAE and BF% measured by ADP in the comparison sample of 6,510 subjects. The middle red line represents the mean difference between the estimated and the measured BF%. The dotted lines indicate ± 2 SDs from the mean.
Figure 2
Figure 2
Correlation stratified by sex between BF% measured by ADP and BMI (A) and BF% estimated using CUN-BAE (B) in the validation sample of 1,149 subjects (366 men and 783 women). Pearson correlation coefficients and associated P values are shown for the whole sample and stratified by sex. Tendency lines are shown for men and women in panel A and for the whole sample in panel B.

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Source: PubMed

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