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Equation Córdoba: A Simplified Method for Estimation of Body Fat (ECORE-BF)

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Author
Molina Luque, Rafael
Romero Saldaña, Manuel
Álvarez-Fernández, Carlos
Bennasar-Veny, Miquel
Álvarez-López, Álvaro
Molina Recio, Guillermo
Publisher
MDPI
Date
2019
Subject
Adults
Anthropometry
Body fat
Obesity
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Abstract
Background: Many methods for measuring body fat have been developed, but applications in clinical settings are limited. For this reason, researchers have tried to identify different formulas for its estimation but most of are hard to incorporate into daily work due to the variability in population and difficulty of use. The aim of this study was to develop and validate a new equation for the simplified estimation of body fat using the Clínica Universidad de Navarra – Body Adiposity Estimator (CUN-BAE) as a reference. Methods: This research was conducted in two phases. In the first, the new body fat estimation equation was developed. The developed equation was validated in the second phase. Pearson’s linear correlation, raw and adjusted linear regressions, the intraclass correlation coefficient, and Bland–Altman graphs were used. Results: The variables that best adjusted the body fat percentage were age, sex, and the Napierian logarithm of Body Mass Index (LnBMI), forming the Equation Córdoba for Estimation of Body Fat (ECORE-BF) model. In its validation, the model presented correlation values of 0.994, an intraclass correlation coefficient of 0.960, with the Bland–Altman graph indicating means differences of 1.82 with respect to the estimation with the CUN-BAE. Nevertheless, although the aim was to simplify the CUN-BAE, the main limitation of this study is that a gold standard, such as air displacement plethysmography (ADP) or dual-energy X-ray absorptiometry (DXA), was not used. Conclusions: The proposed equation (ECORE-BF) simplified the CUN-BAE and provided a precise method, respecting the principle of parsimony, for the calculation of body fat.
URI
http://hdl.handle.net/10396/19128
Fuente
International Journal of Environmental Research and Public Health 16(22), 4529 (2019)
Versión del Editor
http://dx.doi.org/10.3390/ijerph16224529
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