Anthropometric multicompartmental model to predict body composition In Brazilian girls

Machado et al. BMC Sports Science, Medicine and Rehabilitation (2017) 9:23 DOI 10.1186/s13102-017-0088-7 RESEARCH ARTICLE Open Access Anthropometric multicompartmental model to predict body composition In Brazilian girls Dalmo Machado1*, Analiza Silva2, Luis Gobbo3, Paula Elias4, Francisco J. A. de Paula4 and Nilo Ramos5 Abstract Background: Anthropometric models remain appropriate alternatives to estimate body composition of peripubertal populations. However, these traditional models do not consider other body components that undergo major changes during peripubertal growth spurt, with restrictions to a multicompartimental approach as a quantitative growth. DXA has great potential to determine pediatric body composition in more than one component (3-C), but has limited use in field settings. Thus, the aim of this study was to propose and validate an anthropometric model for simultaneous estimation of lean soft tissue (LST), bone mineral content (BMC) and fat mass (FM) in healthy girls, from a multivariate approach of densitometric technique, as the criterion method. Methods: A sample of 84 Brazilian girls (7-17 years) was defined by chronological age and maturity offset. Whole total and regional DXA body scan were performed and, the components were defined (LST, BMC and FM) and considered as dependent variables. Twenty-one anthropometric measures were recorded as independent variables. From a multivariate regression, an anthropometric multicompartmental model was obtained. Results: It was possible to predict DXA body components with only four predictive measurements: body weight (BW); supra-iliac skinfold (SiSk); horizontal abdominal skinfold (HaSk) and contracted arm circumference (CaCi) with high coefficients of determination and low estimation errors (LST = 0.6662657 BW - 0. 2157279 SiSk - 0.2069373 HaSk + 0.3411678 CaCi - 1.8504187; BMC = 0.0222185 BW - 0.1001097 SiSk - 0.0064539 HaSk - 0.0084785 CaCi + 0.3733974 and FM = 0.3645630 BW + 0.1000325 SiSk - 0.2888978 HaSk - 0.4752146 CaCi + 2.8461916). The cross-validation was confirmed through the sum of squares of residuals (PRESS) method, presenting accurate coefficients (Q2PRESS from 0.81 to 0.93) and reduced error reliability (SPRESS from 0.01 to 0.30). Conclusions: When sophisticated instruments are not available, this model provides valid estimates of multicompartmental body composition of girls in healthy Brazilian pediatric populations. Keywords: Multicompartmental analysis, Children, Adolescents, Equation, DXA Background Assessment and monitoring of body composition in children and adolescents have great significance when there is the need to: a) study the prevalence of pediatric obesity, b) improve gender screening of body composition, c) track body composition from healthy childhood to adulthood, d) to assess FM changes over time in a given population [1], e) evaluate sport potential of young * Correspondence: 1 School of Physical Education and Sport of Ribeirao Preto, University of Sao Paulo, Bandeirantes Ave. 3900, Monte Alegre, Ribeirão Preto, SP 14040-900, Brazil Full list of author information is available at the end of the article people, f ) monitor training process, and g) prior knowledge of their physical characteristics [2]. Anthropometric based equations continue to be adequate alternatives to determine the body composition of pediatric populations. However, body composition assessment in children is not easy to measure, since the relationship between body components during growth is not constant as in adults [2]. The progress in the study of the quantitative human two-compartment model (2-C) comprising FM and fat-free mass (FFM) to 3-C template (water, fat and residual mass) and 4-C with the estimation of other components in addition to FM, total-body water © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Machado et al. BMC Sports Science, Medicine and Rehabilitation (2017) 9:23 (TBW), minerals and protein [3], has provided new ways for approaching the traditional body composition, especially when it involves peripubertal people. Several pediatric anthropometric equations were developed using a model of 2-C from the hydrostatic weighing [4, 5] and other densitometric techniques. However, this approach is based on assumptions of stable relationship for FFM density (1.1 g/cm3) and FFM hydration (73.2%). These values are stable in adults, but vary substantially during growth [6, 7]. In fact, from birth to adolescence bone mineral and protein increase whereas TBW decreases thus raising FFM density until reaching the adult value when the chemical maturity profile is reached [6]. Therefore, body composition models have a multicompartmental approach, as the reference method, which accounts for the variability of the main FFM components due to age and maturational changes, resulting in more valid equations [1]. Even using 4-C models, several anthropometric models have been developed to estimate one body component, usually FM for pediatric populations. However, it could be possible to estimate other components such as water, protein, and mineral. In addition to using DXA as the reference method to develop anthropometric models, lean-soft tissue (LST), FM, and bone mineral content (BMC) could also be determined by using a multivariate regression model. When conceived in a multivariate pattern, considering appropriately all important factors, the likelihood to create robust models is attainable, increasing the predictive capacity and reducing errors of estimation [8–10]. Currently, DXA is recognized to have a great potential to determine body composition in pediatric studies [7], due to its ability to provide more than one component (3-C approach). However, the exposition to ionizing radiation, the equipment cost along with the lack of feasibility for large-scale use limits its applicability in field settings (home, school environments, and sport clubs). Consequently, simple solutions to estimate body composition in children from anthropometric techniques including skin folds, bone breadth and circumferences have been widely used and are preferred in different contexts [1]. These alternatives are more convenient due to their low costs, they require low level of personnel training, they are minimally invasive and have good scientific credibility [11]. Although conventional anthropometric methods are scientifically accepted, they do not distingui (...truncated)