Simple anthropometry-based calculations to monitor body composition in athletes: Scoping review and reference values

Abstract

Background: Kinanthropometry offers to exercise and health professionals a standardized procedure of acquiring surface anatomical measurements that might be used to track changes in body composition. Aim: To describe simple anthropometric indices to monitor body composition changes in amateur and elite athletes, and to provide reference values during the competition phase. Methods: A search of articles indexed in PubMed/MEDLINE, ScienceDirect, Cochrane, and SciELO databases using the string body composition AND (anthropometric OR skinfolds OR circumferences OR girth OR estimation equation) AND “body fat”. Inclusion criteria were: quantitative and/or qualitative research published between 2009 and 2020, written in English or Spanish, reporting simple anthropometric indices that included skinfolds, girths, or basic measures in amateur and elite athletes. Results: A total of 51 studies (Price’s index = 66.4%) met all the inclusion criteria and were included in this scoping review. Contrary to the frequent practice, the use of a regression equation might not be accurate to evaluate body composition. To avoid this, anthropometrists should base their analysis on the absolute values of the sum of skinfolds (∑S) and related variables, such as skinfold-corrected girths and lean mass index. While not definitive, because further research is required, the practical recommendations and updated reference values in competition phase provided by this review would contribute to the accurate identification of body composition changes. Conclusions: ∑S and lean mass index have been shown to be valid for monitoring changes in fat mass and fat-free mass, respectively. More research is needed to derive the lean mass index-specific coefficient for each sports population.

Development and Validation of Waist Girth-Based Equations to Evaluate Body Composition in Colombian Adults: Rationale and STROBE–Nut-Based Protocol of the F20 Project

“…Interestingly, scientific evidence supports the predictive potential of WG given the high correlation of WG-based equations with more reference methods (e.g., DXA and CT) for the assessment of body composition. However, these also have limitations that are mainly due to differences with respect to the population on which they have been developed since they are specific and, given the fluctuations that occur in age and sex, further external validation is warranted [ 40 , 55 ]. Development and validation of new models will increase generalizability and scientific soundness at the time of evaluating body composition in the Colombian population with different levels of physical activity.…”

“…The Takai et al, equation [ 35 ] will be used to estimate fat-free mass in athletes. We will also report the sum of skinfolds (∑S) as an absolute variable (expressed in millimeters) which not only gives information about the local distribution of subcutaneous fat tissue, but which also indicates whole-body adiposity since it correlates with whole-body-fat mass [ 40 , 49 ]. As a musculoskeletal index, the skinfold-corrected muscle girths for arm, chest, waist, thigh, and calf will be calculated according to the expression: girth—(π × skinfold) [ 50 ].…”

“…Second, hydrodensitometry as a reference methodology has some disadvantages, including the exclusion of participants who do not complete the underwater weighing test, as well as the fact that it is a methodology for estimating body density but not for estimating fat percentage. Importantly, the use of the Siri equation to estimate body-fat percentage implicates an additional estimation, so the values reported may not be accurate [ 40 ].…”

Development and Validation of a Novel Waist Girth-Based Equation to Estimate Fat Mass in Young Colombian Elite Athletes (F20CA Equation): A STROSA-Based Study

“… Use the sum of skinfolds to accurately detect changes in body composition (i.e., %BF) during a nutrition and/or exercise intervention. The sum of skinfolds has been shown to strongly correlate with %BF measured by DXA in well-trained athletes [ 68 , 69 , 70 ]. Estimate the young athlete’s fat-free mass (kg) according to the expression: Body Mass [kg] − F20 CA -estimated fat mass [kg].…”

Estimation of Stature in Adults: Development and Validation of a New Predictive Formula using the Tibiale Mediale-Sphyrion Tibiale Length.

“…Within the A-anthropometry, B-biochemistry, C-clinical, D-dietary intakes, E-environment and evaluation (ABCDE) model for the assessment of NS 6 , there are several calculations that depend on the stature measurement 7 . One of the best known is the body mass index (BMI), which is calculated from body mass (kg) and stature (m).…”