Importance of Standardized DXA Protocol for Assessing Physique Changes in Athletes

• Autores: Alisa Nana, Gary J. Slater, Will G. Hopkins, Shona L. Halson, David T. Martin, Nicholas P. West, Louise M. Burke
• Localización: International journal of sport nutrition and exercise metabolism, ISSN 1526-484X, ISSN-e 1543-2742, Vol. 26, Nº. 3, 2016, págs. 259-267
• Idioma: inglés
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• Dialnet Métricas: 1 Cita
• Resumen

  • The implications of undertaking DXA scans using best practice protocols (subjects fasted and rested) or a less precise but more practical protocol in assessing chronic changes in body composition following training and a specialized recovery technique were investigated. Twenty-one male cyclists completed an overload training program, in which they were randomized to four sessions per week of either cold water immersion therapy or control groups. Whole-body DXA scans were undertaken with best practice protocol (Best) or random activity protocol (Random) at baseline, after 3 weeks of overload training, and after a 2-week taper. Magnitudes of changes in total, lean and fat mass from baseline-overload, overload-taper and baselinetaper were assessed by standardization (?mean/SD). The standard deviations of change scores for total and fat-free soft tissue mass (FFST) from Random scans (2�3%) were approximately double those observed in the Best (1�2%), owing to extra random errors associated with Random scans at baseline. There was little difference in change scores for fat mass. The effect of cold water immersion therapy on baseline-taper changes in FFST was possibly harmful (-0.7%; 90% confidence limits ±1.2%) with Best scans but unclear with Random scans (0.9%; ±2.0%). Both protocols gave similar possibly harmful effects of cold water immersion therapy on changes in fat mass (6.9%; ±13.5% and 5.5%; ±14.3%, respectively). An interesting effect of cold water immersion therapy on training-induced changes in body composition might have been missed with a less precise scanning protocol. DXA scans should be undertaken with Best.