The estimation of body fat percentage (%BF) from anthropometry-related data requires population-specific equations to avoid incorrect interpretations in young athletes. Waist girth (WG) has been described as potential predictor of fat mass (FM) in several populations; however, there are no valid WG-based equations to estimate body composition in young Colombian athletes. The aim of this STandardisierte BerichtsROutine für Sekundärdaten Analysen STROSA-based study was twofold: i) to validate the relative fat mass (RFM) and its pediatric version (RFMp) compared to dual-energy x-ray absorptiometry (DXA) and ii) to develop a new equation (F20_CA) to estimate the fat mass in Colombian children and adolescent elite athletes. A total of 114 young athletes that belong to the ‘Team Medellín’ program (58F, 56M; 51 children, 63 adolescents; 14.85 [2.38] years; 55.09 [12.16] kg; 162.38 [11.53] cm) participated in this cross-sectional study. The statistical analysis revealed a poor correlation, agreement and concordance of RFMp and RFM estimations with DXA measurements. After model specification using both Ordinary Least Square method and Bayesian analysis, the regression output revealed that sex, body mass-to-waist ratio, and waist-to-stature ratio were the statistically significant predictor variables that account for variability in FM. The new F20_CA equation is expressed as FM (kg) = 5.46 ∗ (Sex) + 0.21 ∗ (BM/W [kg/m]) + 81.7 ∗ (W/Stature [cm/cm]) − 41.8 (R² = 0.683; SEE = 2.468 kg), where sex is 0 for males and 1 for females. A moderate-to-high correlation and agreement of the F20_CA was confirmed within the internal validation data set (R² = 0.689; ICC [95%CI] = 0.805 [0.615, 0.904]; RMSE = 2.613 kg). The Bland–Altman analysis corroborated the high concordance between the reference method (DXA) and the F20_CA-estimated FM (bias [95% LoA] = 1.02 [−3.77, 5.81] kg), indicating the two methods could be considered interchangeable. Even though external validation is needed, practitioners are advised to use the F20_CA in young Colombian athletes with similar characteristics to those who participated in this study.

Our study aimed to validate existing equations and develop the new NRG_CO equation to estimate resting energy expenditure (REE) in the Colombian population with moderate-to-high physical activity levels. Upon satisfying the inclusion criteria, a total of 86 (43F, 43M) healthy adults (mean [SD]: 27.5 [7.7] years; 67.0 [13.8] kg) were evaluated for anthropometric variables and REE by indirect calorimetry using wearable gas analyzers (COSMED K4 and K5). Significant positive correlations with REE were found for body mass (r = 0.65), body mass-to-waist (r = 0.58), arm flexed and tensed girth (r = 0.66), corrected thigh girth (r = 0.56), corrected calf girth (r = 0.61), and sum of breadths (∑3D, r = 0.59). As a novelty, this is the first time a significant correlation between REE and the sum of corrected girths (∑3CG, r = 0.63) is reported. Although existing equations such as Harris–Benedict (r = 0.63), Mifflin–St. Jeor (r = 0.67), and WHO (r = 0.64) showed moderate-to-high correlations with REE, the Bland-Altman analysis revealed significant bias (p < 0.05), indicating that these equations may not be valid for the Colombian population. Thus, participants were randomly distributed into either the equation development group (EDG, n = 71) or the validation group (VG, n = 15). A new model was created using body mass, sum of skinfolds (∑8S), corrected thigh, corrected calf, and age as predictors (r = 0.755, R² = 0.570, RMSE = 268.41 kcal). The new NRG_CO equation to estimate REE (kcal) is: 386.256 + (24.309 × BM) − (2.402 × ∑8S) − (21.346 × Corrected Thigh) + (38.629 × Corrected Calf) − (7.417 × Age). Additionally, a simpler model was identified through Bayesian analysis, including only body mass and ∑8S (r = 0.724, R² = 0.525, RMSE = 282.16 kcal). Although external validation is needed, our validation resulted in a moderate correlation and concordance (bias = 91.5 kcal) between measured and estimated REE values using the new NRG_CO equation.

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 evaluation of body composition is one of the main components in the assessment of nutritional status. Indeed, the use of anthropometry-based equations to estimate body fat and fat-free mass is a frequent strategy. 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. This cross-sectional study will be carried out following the guidelines for Strengthening the Reporting of Observational Studies in Epidemiology–Nutritional Epidemiology (STROBE–nut). Using stratified probabilistic sampling, the study population will be adults with different levels of physical activity residing in Medellín and its metropolitan area. 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. This will improve professional practice in health, exercise, and sports sciences (ClinicalTrials.gov ID #NCT05450588).

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Introduction: body composition is key to assessing nutritional status and varies throughout the life course. Fat mass, lean mass, and bone mineral density (BMD) are influenced by age, allowing for the identification of health risks. Objective: to analyze changes in body composition using DXA in a cohort evaluated between 2018-2025, considering variations according to age groups defined by the Ministry of Health and Social Protection for the Colombian population and by ten-year age ranges. Methodology: an observational, retrospective, and cross-sectional study was conducted using records from the Center for Advanced Studies at CES University in Medellín, including 598 individuals aged 10 to 78 years. The variables were analyzed by age group and by decade using the Kruskal-Wallis test to compare age groups and the chi-square test to estimate differences. Results: significant differences were observed in all variables. With aging, BMI, total fat mass, visceral fat, and the android/gynoid ratio increased, while lean mass, bone mineral content, and bone mineral density decreased. Aging may attenuate differences in body composition between the sexes. Discussion: the findings are consistent with evidence describing a redistribution of body composition associated with aging, characterized by muscle loss and bone mass and an increase in adiposity, thereby increasing functional and metabolic risk. The visceral fat increase and the androide/gynoide ratio indicate a redistribution of adipose tissue influenced by hormonal factors. Conclusions: the study demonstrates progressive deterioration in body composition with age, highlighting the importance of promoting preventive and screening strategies to improve quality of life.