Same-day versus consecutive-day precision error of dual-energy X-ray absorptiometry for interpreting body composition change in resistance trained athletes

Abstract

Introduction: The application of dual-energy X-ray absorptiometry (DXA) in sport science settings is gaining popularity due to its ability to assess body composition. The International Society for Clinical Densitometry (ISCD) recommends application of the least significant change (LSC) to interpret meaningful and true change. This is calculated from same-day consecutive scans, thus accounting for technical error. However, this approach doesn't capture biological variation which is pertinent when interpreting longitudinal measurements, and could be captured from consecutive-day scans. The aims of this study were to investigate the impact short-term biological variation has on LSC measures, and establish if there is a difference in precision based on gender in a resistance trained population. Methodology: Twenty-one resistance trained athletes (age 30.6 ± 8.2 years; stature 174.2 ± 7.2cm; mass 74.3 ± 11.6kg) with at least 12 months consistent resistance training experience, underwent two consecutive DXA scans on one day of testing, and a third scan the day before or after. ISCD recommended techniques were used to calculate same-day and consecutive-day precision error and LSC values. Results: There was high association between whole body (R2=0.98–1.00) and regional measures (R2=0.95–0.99) for same-day (R2=0.98–1.00) and consecutive-day (R2=0.95–0.98) measurements. The consecutive-day precision error, in comparison to same-day precision error, was significantly different (p<0.05), and almost twice as large for FM (1261g vs 660g), and over three times as large for LM (2083g vs 617g), yet still remained within the ISCD minimum acceptable limits for DXA precision error. No whole body differences in precision error were observed based on gender. Conclusion: When tracking changes in body composition, the use of precision error and LSC values calculated from consecutive-day analysis is advocated, given this takes into account both technical error and biological variation, thus providing a more accurate indication of true and meaningful change.