Review ArticleInterpretation of Dual-Energy X-Ray Absorptiometry-Derived Body Composition Change in Athletes: A Review and Recommendations for Best Practice
Introduction
Dual-energy X-ray absorptiometry (DXA) is a medical imaging technology that uses 2 X-ray beams of different energies that are diversely attenuated by bone and soft tissue. Although the primary application of DXA has historically been for osteoporosis assessment using bone mineral density (1), there has been a rapid growth in its application for the measurement of fat and lean soft tissues over the last 2 decades. This largely followed the introduction of fan beam densitometers with quicker scan acquisition times, better image resolution and quality, and lower radiation exposure. The radiation dose from a total body scan is now relatively small, facilitating its application in longitudinal monitoring of physique traits. As an example, the effective dose from 1 standard mode total body scan on the GE Lunar iDXA is around 2 µSv, and 1 d of natural background radiation in the United Kingdom is around 5–8 µSy (2).
Of all fields, sports science and medicine has witnessed a considerable rise in the number of published research studies utilizing DXA for the assessment of total and regional body composition. These studies have included the body composition profiling of competitive athletes 3, 4, in relation to bone density 5, 6, 7 and nutritional status 8, 9. Serial DXA measurements are increasingly being used to explore the effects of training and diet on athlete body composition changes 10, 11, 12, 13, 14, 15, 16, 17. DXA is regarded as the preferred method for measuring absolute body composition by the International Olympic Committee (18) and is gaining popularity across elite sport centers of excellence, professional sports clubs, and the wider public commercially.
There are a number of alternative imaging modalities for the assessment of body composition, including magnetic resonance imaging, which offers an accurate and reliable alternative to DXA but is limited because of expense and longer scanning times. The reproducibility of DXA is excellent 19, 20, 21 and is frequently used as the criterion method, from which other measurement methods are validated. Nonetheless, it is also now known to be impacted by a number of factors that can affect results and the repeatability of the measurement. Furthermore, knowledge of measurement precision is required for interpreting what constitutes a true and meaningful change—defined as a change that is biological and not arising from technical error. This is particularly pertinent when monitoring body composition in highly trained athletic populations because of their reduced potential for adaptation over a defined period (16). Once the precision error of a device is established, the least significant change (LSC) value can be calculated and applied as follows:
The LSC is the change between 2 DXA measurements that is required for 95% confidence that an actual change has occurred 22, 23. The International Society for Clinical Densitometry (ISCD) official position stand recommends the application of LSC for interpreting longitudinal body composition measurements (23).
It is important to note that the precision of DXA is influenced by both technical and biological factors. Technical factors include instrument model, reference database (24) and scan mode 25, 26, 27, adjustment of regions of interest, and subject positioning, whereas biological factors include subject preparation (28), age (29), sex (21), and body size 21, 30, 31, 32, which can vary greatly between athletes from different sports. In the largest DXA longitudinal precision study to date, Powers and colleagues demonstrated differences in precision error of tissue measurements across the body mass index categories (21). In addition, we have previously found that athleticism is an important factor for precision, with increased precision error for body composition measurements in rugby players (31) compared to precision errors reported for a heterogeneous study sample (20). The distribution of lean and bone tissues are different between athletes according to sport, and differences in body sizes and thickness may affect total and regional X-ray attenuation characteristics. For example, a larger fat free mass (FFM) might predispose an individual to greater error in FFM estimates, given the range of factors influencing FFM such as a larger total body water flux. As such, knowledge of precision error that is population-specific is particularly important for body composition studies of athletic groups.
The purpose of this review was to evaluate the methodologies of all published athlete longitudinal DXA-based body composition studies between 1996 and 2016, according to the assessment of body composition change. On the basis of this review and that of others (33), plus the ISCD official position (23), we provide a guide for consistency and best practice in the interpretation and presentation of DXA-derived body composition change in sports science research and practice.
Section snippets
Study Selection
Before commencing the review, a search of PROSPERO was conducted to confirm that there were no similar reviews registered. Following this confirmation, a literature search was performed (in English) to identify the studies relevant to this review. Specifically, the aim of the literature search was to identify all available longitudinal studies of body composition change in athletic populations published from 1980 to November 2016. To achieve this aim, 3 authors performed independent
Results
The Preferred Reporting Items for Systematic Reviews and Meta-analyses flow diagram for the selection of the 25 studies included in the review is presented in Fig. 3. Table 1 summarizes the key outcomes of the review for each eligible manuscript based on the assessment rubric (Fig. 2). Most studies used fan beam systems (Lunar iDXA, Prodigy or Hologic Discovery, Hologic Explorer) and 4 studies used pencil beam technology (Lunar DPX-L, and Norland XR800, Swissray, NJ) 10, 12, 15, 34. Fourteen
Discussion
The main findings of this review were not only of an improvement from 1980 to 2016 in the number of studies providing information on precision error (62% in 1980–2013; 83% in 2014–2016), but also of apparent limitations in precision error methodologies and a lack of consistency between studies in terms of athlete pre-scan preparation and the level of information provided in manuscripts. We also found that around the same number of athlete longitudinal DXA body composition studies were published
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2022, Journal of Clinical DensitometryFood and fluid intake and hydration status does not affect ultrasound measurements of subcutaneous adipose tissue in active adults
2022, Journal of Science and Medicine in SportToo Tall for the DXA Scan? Contributions of the Feet and Head to Overall Body Composition
2022, Journal of Clinical DensitometryCitation Excerpt :Regardless of the choice to remove the head or feet when performing whole-body composition scans on tall individuals, the key to accurate measurement is consistency. Best practice guidelines recommend that participants be scanned after an overnight fast, in a euhydrated state, and refrain from intense exercise 24-h prior to scanning (7,33). However, most inaccuracies seen when best practice protocols are impractical will be reflected in lean mass compartmental shifts of water following acute exercise bouts (33,34) or food/fluid intakes (35).
Measures of body composition via Dual-energy X-ray absorptiometry, ultrasound and skinfolds are not impacted by the menstrual cycle in active eumenorrheic females
2022, Journal of Science and Medicine in SportCitation Excerpt :Another limitation of this study was that we were unable to include all the body composition estimates for all of the 30 participants at each of the intended phases of their cycle due to either participant availability, inaccuracies in cycle phase prediction or technical error during hormonal analysis. We were however able to collect body composition data from all 30 participants in duplicates at baseline (EF1), which enabled us to calculate the precision error and LSC-95% CIs of DXA body composition estimates as recommended,19 to verify true changes between MC phases. Should the monitoring of longitudinal changes in body composition be required however, calculating precision error and LSC-95% CIs values from analysis of consecutive-day rather than same-day DXA scans may be even more advantageous since both technical error and biological variation will be accounted for when interpreting accuracy and meaning.28
Conflicts of interest: Authors KH, GS, ML, ST, MB, and BO declare no conflict of interest. JS is a former President of the International Society for Clinical Densitometry.
Funding: This study was not externally funded.