Same-Day Vs Consecutive-Day Precision Error of Dual-Energy X-Ray Absorptiometry for Interpreting Body Composition Change in Resistance-Trained Athletes.

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 does not 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. Twenty-one resistance-trained athletes (age: 30.6 ± 8.2 yr; stature: 174.2 ± 7.2 cm; mass: 74.3 ± 11.6 kg) with at least 12 mo consistent resistance training experience, underwent 2 consecutive DXA scans on 1 d 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. There was high association between whole body (R = 0.98-1.00) and regional measures (R = 0.95-0.99) for same-day (R = 0.98-1.00), and consecutive-day (R = 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 fat mass (1261 g vs 660 g), and over 3 times as large for lean mass (2083 g vs 617 g), 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. 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.