BACKGROUND/ OBJECTIVE: Knowing the distribution of lean soft tissue (LST) among the body segments is of relevance for optimizing athletic performance, monitoring response to training, and for evaluating injury risk. Bioelectrical impedance (BIA) is a portable, low cost, and easy technique to assess body composition. However, most equations used by BIA to predict LST are not specific for the athlete population. The aim of this investigation was to develop and validate equations to estimate dual-energy X-ray absorptiometry (DXA) appendicular LST of the arms and legs based on whole-body BIA in athletes. METHODS: Arms and legs LST were assessed by DXA and whole-body reactance (Xc) and resistance (R) were measured by BIA in athletes from various sports. Using measures of height, the resistance index (RI) (RI = height2/R) was calculated. Prediction equations were established using a cross-validation method where 177 athletes (2/3 of sample) were used for equation development and the remaining 88 athletes (1/3 of sample) were used for equation validation. RESULTS: The developed prediction equations were as follows: arm LST = 0.940 × sex (0 = male; 1 = female) + 0.042 × total body weight (kg) + 0.080 × RI + 0.024 × Xc - 3.927; leg LST = 1.983 × sex (0 = male; 1 = female) + 0.154 × total body weight (kg) + 0.127 × RI - 1.147. Both equations validated well for the arms (mean difference = 0.11 kg, R2 = 0.89, pure error (PE) = 0.61) and for the legs (mean difference = 0.05 kg, R2 = 0.81, PE = 1.93 kg). There were no differences (p > 0.05) in the mean observed and predicted LST for the arms and legs. CONCLUSION: The developed BIA-based prediction equations provide a valid estimation of upper and lower body LST in athletes.
BACKGROUND/ OBJECTIVE: Knowing the distribution of lean soft tissue (LST) among the body segments is of relevance for optimizing athletic performance, monitoring response to training, and for evaluating injury risk. Bioelectrical impedance (BIA) is a portable, low cost, and easy technique to assess body composition. However, most equations used by BIA to predict LST are not specific for the athlete population. The aim of this investigation was to develop and validate equations to estimate dual-energy X-ray absorptiometry (DXA) appendicular LST of the arms and legs based on whole-body BIA in athletes. METHODS: Arms and legs LST were assessed by DXA and whole-body reactance (Xc) and resistance (R) were measured by BIA in athletes from various sports. Using measures of height, the resistance index (RI) (RI = height2/R) was calculated. Prediction equations were established using a cross-validation method where 177 athletes (2/3 of sample) were used for equation development and the remaining 88 athletes (1/3 of sample) were used for equation validation. RESULTS: The developed prediction equations were as follows: arm LST = 0.940 × sex (0 = male; 1 = female) + 0.042 × total body weight (kg) + 0.080 × RI + 0.024 × Xc - 3.927; leg LST = 1.983 × sex (0 = male; 1 = female) + 0.154 × total body weight (kg) + 0.127 × RI - 1.147. Both equations validated well for the arms (mean difference = 0.11 kg, R2 = 0.89, pure error (PE) = 0.61) and for the legs (mean difference = 0.05 kg, R2 = 0.81, PE = 1.93 kg). There were no differences (p > 0.05) in the mean observed and predicted LST for the arms and legs. CONCLUSION: The developed BIA-based prediction equations provide a valid estimation of upper and lower body LST in athletes.
Authors: Luís B Sardinha; Gil B Rosa; Megan Hetherington-Rauth; Inês R Correia; João P Magalhães; Analiza M Silva; Henry Lukaski Journal: Eur J Clin Nutr Date: 2022-10-17 Impact factor: 4.884
Authors: Francesco Campa; Catarina N Matias; Pantelis T Nikolaidis; Henry Lukaski; Jacopo Talluri; Stefania Toselli Journal: Int J Environ Res Public Health Date: 2020-11-05 Impact factor: 3.390
Authors: Giada Ballarin; Luca Scalfi; Fabiana Monfrecola; Paola Alicante; Alessandro Bianco; Maurizio Marra; Anna Maria Sacco Journal: Int J Environ Res Public Health Date: 2021-11-30 Impact factor: 3.390