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.
Highlights
Obesity is defined as being an excess of adipose tissue that may cause health problems [1] and is considered a key risk factor in the development of several chronic diseases such as ischemic heart disease, arterial hypertension, the onset and recovery difficulties of osteo-articular problems, some types of cancer, alterations in the fecundity capacity of men and women, and all-cause mortality [2,3,4,5,6].The prevalence of being overweight and obesity is continuously increasing, having increased up to39% and 13%, respectively in 2016 worldwide [7].Int
The prevalence of obesity following body mass index (BMI) criteria (≥30 kg/m2 ) was 17.5%, reaching 19.9% in men, and 13.5% in women
The prevalence of overweight (41.7%) and obesity (17.5%) found in sample n1 according to BMI criteria was higher than that presented by the World Health Organization (WHO) in its latest report [7]
Summary
Obesity is defined as being an excess of adipose tissue that may cause health problems [1] and is considered a key risk factor in the development of several chronic diseases such as ischemic heart disease, arterial hypertension, the onset and recovery difficulties of osteo-articular problems, some types of cancer, alterations in the fecundity capacity of men and women, and all-cause mortality [2,3,4,5,6].The prevalence of being overweight and obesity is continuously increasing, having increased up to39% and 13%, respectively in 2016 worldwide [7].Int. 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. The new body fat estimation equation was developed. The developed equation was validated in the second phase. 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. The model presented correlation values of 0.994, an intraclass correlation coefficient of 0.960, with the
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