

The Urabá subregion is considered one of the geographical locations with the highest sport potential in Colombia however, no study has evaluated young combat athletes. Introduction: The study of anthropometry-based indicators of morphology and maturity status might contribute to the talent identification, sports specialization and early categorization of young athletes.
#3 SITE SKINFOLD BODY FAT CALCULATOR PROFESSIONAL#
This will improve professional practice in health, exercise, and sports sciences ( ID #NCT05450588). The results of this study will not only validate the estimation performance of the current WG-based equations, but they will also develop new equations to estimate body composition in the Colombian population. Using stratified probabilistic sampling, the study population will be adults with different levels of physical activity residing in Medellín and its metropolitan area. This cross-sectional study will be carried out following the guidelines for Strengthening the Reporting of Observational Studies in Epidemiology–Nutritional Epidemiology (STROBE–nut). Considering the lack of validation in the Colombian population, the aim of this research study (the F20 Project) is to externally validate WG-based equations (e.g., relative fat mass), and also to develop and validate new models that include WG to estimate body composition in Colombian adults compared to DXA. Indeed, the use of anthropometry-based equations to estimate body fat and fat-free mass is a frequent strategy. The evaluation of body composition is one of the main components in the assessment of nutritional status. Waist girth (WG) represents a quick, simple, and inexpensive tool that correlates with excess of fat mass in humans however, this measurement does not provide information on body composition. The data from the 17 subjects highlighted BMI has deficiencies in determining a true reflection of a well-trained athlete's body composition. However the data sample is small in determining definitive conclusions, this warrants further data collection to validate the range trend findings. The MS data indicated range trends to link the sum of 8 SKF measures to a prediction range of %BF. The correlation co-efficient relationships for all equations were significant from r = 0.965 tor =0.983 for males and r = 0.961 tor = 0.992 for female. Easton et al (1995) indicated JP & DW over and underestimated %BF, which suggests the mean may reduce the error of calculation. Predicted %BF calculation used was the mean score (MS) of three equation predictors - Durnin and Womersley (DW) 4 Site Skinfold Test (Standard Error of Estimate (SEE) 3.5% for female: 4.0% for male), Jackson and Pollock (JP) 3 site SKF Test (SEE 3.9% for female: 3.4% for male), and Yuhasz SKF Test (Total Error (TE) 3.5% for male). Two test periods were conducted 4 months apart collecting 8 SKF measures from 35 full-time athletes (21 male 26.05 ± 5.07 and 14 female 24 ± 4.15), 17 athletes were tested at both periods. The purpose of this study was to examine if relationship trends between the mean of 3 predicted % body fat (%BF) equations and the sum of 8 skinfold (SKF) measures existed for well-trained athletes as opposed to BMI as an assessment of body composition.
