Body composition is a powerful mediator of athletic ability and health amongst elite athletes. Having read Part I, you already appreciate this. So, how do we discern which is the best method to assess body composition in elite athletes?
The gold standard for complete accuracy in assessing an individual’s body composition is dissection (Wells and Fewtrell, 2006). Understandably, this is not desirable for athletes, as being a cadaver hugely impairs performance. Therefore, other indirect methods of assessing BC have been developed.
A commonly used method of assessing bodyfat percentage (BF%) is skinfold thickness. This involves going around with a callipers and pinching the jaysus out of the athlete at several anatomical sites. This is used to give an estimate of overall bodyfat, and has the advantages of being user-friendly, low cost and readily available (Hume and Marfell-Jones, 2008).
Sounds like a dream.
Except for the glaring lack of inter-assessor consistency. Anatomical landmarks appear to be subjective to the individual. Your interpretation of below the scapula could be different to mine. This has led to a big old yikes of 70% skinfold measurements being taken from the wrong anatomical landmark (Hume and Marfell-Jones, 2008). This means that athletes get two completely different body fat results from the different assessors.
In addition, skinfold measurements only assess subcutaneous fat (unless you’re highly invasive with your callipers), and don’t assess visceral (around organs) fat or fat-free mass status.
Inaccurate measurements, high variability between assessors even with experienced users make it difficult to recommend this method for elite athletes. At an elite level, every variable affecting performance needs to be accurately assessed.
Bioelectrical Impedance (BIA)
BIA passes an electrical current through the body and then measures the rate it travels at. Body fat slows the current, and it flows faster through water and FFM (Kyle et al., 2004). This is not always advantageous, as it means that BIA is affected by hydration status.
As the current passes quicker through water, a hydrated individual may exhibit a lower BF% reading. The opposite holds true for the dehydrated athlete (Ackland et al., 2012). This highlights the need for a standardised testing protocol (hydration levels etc.), which at present is not well-developed.
BIA is advantageous in that it is non-invasive, fast and widely available. However, the lack of standardisation and influence of hydration on accuracy makes It different to recommend for elite athletes.
Oh you already know those four years in college weren’t wasted on me. Join me as we destroy the hopes of researchers with the crushing reality of radiology and access to same.
Modalities such as computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound are all being touted as the next big body composition assessment method.
CT uses x-ray to generate multi-planar scans of anatomy, that we can reconstruct, window and analyse. By assessing how much each tissue attenuates the x-ray beam, we can assess the tissue density and type (muscle, bone etc.) (Ackland et al., 2012). Sounds good, until we get to the glaring issue of radiation safety. CT uses ionising radiation to generate images, which carries a risk to the athlete. Radiology 101 dictates that to justify the issue of radiation, the benefit of the scan must outweigh the risk of harm from radiation exposure (Ravikanth, 2017). Accurately assessing body composition is important, but so is not increasing cancer risk to the patient. It is very hard to justify regular CT scans for assessing body composition, from a radiation safety perspective and a practical standpoint. As a slave to the public healthcare system, it’s hard to imagine CT replacing other BC methods.
Magnetic Resonance Imaging
Enter MRI. She’s offering better assessment of soft tissue structures (heyi muscle) and she doesn’t use ionising radiation (Ackland et al., 2012). However, much like CT, it’s hard to imagine the practicalities of this translating to the sporting world. An MRI scanner is expensive to purchase and run. And the waiting lists for sick patients are huge, let alone for elite athletes looking to assess their body fat. In addition, it will be a huge challenge for claustrophobic athletes to tolerate. Current MRI software is geared toward diagnostic imaging, and not on assessing or quantifying tissue. MRI has promise for the future, but in the absence of a complete overhaul of the health system and suitable software, she’s relegated back to the sideline for the time being.
Then, we have ultrasound. Ultrasound, as the name suggests, uses pulses of sound to image the body. She’s non-invasive, portable and quick (Wagner, 2013). Ultrasound has been deemed as accurate as CT and MRI in assessing fat patterns and distributions and measuring the thickness of tissues (Wagner, 2013). However, ultrasound is incredibly user-dependent. It’s incredibly difficult to standardise, considering interpretation of images differ between users. It’s also very hard to examine patients with increased body habitus. You can imagine the challenge imaging rugby players would pose. In addition, unless you plan on getting really personal, imaging internal/deep musculature can be a challenge. Much like MRI, she has promise, but it’s just not established enough yet.
And finally, DEXA. DEXA (or Dual-Energy X-ray Absorbptiometry if you’re trying to up the word count in a radiography essay) works by passing a low-energy x-ray beam over the athlete. Not unlike CT, we use the degree of attenuation to assess the density of tissues. We can separate tissues into bone, fat and fat-free mass (Ackland, 2012). DXA is highly popular in assessing BC in elite athletes (Zemski et al., 2019).
It’s fast and convenient, and is unaffected by clothing or moisture in the way other methods are. It offers similar results to skinfold measurements in elite rugby players (Zemski et al., 2019). It’s also as reliable as BodPod in assessing BF% and FFM (Smith-Ryan et al., 2017). We will touch on the BodPod a bit more below.
DXA is limited by a few constraints, most notably athlete habitus and my favourite, radiation safety. Athletes taller than 192cm might be too tall for the scanner (but not not too tall for my DMs, hit me up). In addition, most scanners have a weight limit of 120kg. This can be an issue for certain athletes, particularly male rugby players. Forwards typically average around 110kg (Brazier et al., 2012), which pushes the limits. Other modalities have no height or weight limits, which can be advantageous.
Again, we run into the ethical dilemma of using ionising radiation for non-diagnostic or therapeutic purposes. We spoke about the Hippocratic Oath for radiographers – justify the risk for the exposure. I would call into question the need to irradiate athletes repeatedly for the sake of body composition analysis. DXA is a far lower radiation exposure than CT (Wells and Fewtrell, 2006). It would hurt me and my CORU registration to see widespread use of DEXA when we can avail of non-ionising modalities with equal accuracy (see BodPod spiel below).
Densitometry: Hydrostatic Weighting & Air Plethysmography
Densitometry splits the body into FFM and BF, and assigns each a constant density. This is then correlated with the individuals’ measured body density, which gives an indication of BF% and FFM (Ackland et al., 2012). Hydrostatic weighting submerges the athlete underwater, and then they exhale. Using the Archimedes principle (so well-known ofc you know what this is), BC is assessed by dividing bodyweight by volume of weight lost underwater.
Air plethysmography (BodPod) acts similarly, but measures volume in a sealed air capsule instead of water. The athlete can breathe normally throughout, and at the end a breathing technique is performed to calculate remaining gas (Ackland et al., 2012). However, excessive clothing, moisture on the skin and altered breathing patterns alter the accuracy of the readings (Fields, Goran and McCrory, 2002). These errors are easily corrected, by ensuring athlete is prepared, instructed and dressed appropriately. The athlete’s intestinal gas may affect the validity of these results, which is non-preventable (Smith-Ryan et al., 2017).
Densitometry is non-invasive and does not use ionising radiation. However, it assumes FFM density is constant, which may lead to in accuracy in assessing very lean athletes (Ackland et al., 2012). This may not be a limiting factor for the elite rugby athlete. The lowest average BF% for elite males is 11% (Brazier et al., 2012) and 22% for females (Jones et al., 2016). Neither average BF% approaches the minimum leanness standards outlined for their respective gender. Densitometry is generally considered more accurate at determining BC of heavier adults (Wells and Fewtrell, 2006).
Densitometry may be a viable method in assessing BC of elite athletes, but the sport and typical anthropometric features of athletes in that sport/position must be carefully considered.
There is no perfect method of body composition assessment, unless you want a murder charge on your hands. The biggest barrier to many assessment methods lies in their poor consistency or else their glaring lack of radiation safety.
Big ups to BodPod, and perhaps the future shall see the advent of MRI scanning for body composition assessments in elite athletes.
- Ackland, T.R., Lohman, T.G., Sundgot-Borgen, J., Maughan, R.J., Meyer, N.L., Stewart, A.D., Muller, W. (2012) ‘Current Status of Body Composition Assessment in Sport’, Sports Medicine, 42, pp. 227-249.
- Brazier, J., Antrobus, M., Stebbings, G.K., Day, S.H., Callus, P., Erskine, R.M., Bennett, M.A., Kilduff, L.P., Williams, A.G. (2020) ‘Anthropometric and Physiological Characteristics of Elite Male Rugby Athletes’, 34(6), pp. 1790-1801.
- Fields, D.A., Goran, M.I., McCrory (2002) ‘Body-composition assessment via air-displacement plethysmography in adults and children: a review’, The American Journal of Clinical Nutrition, 75(3), pp. 453-467.
- Hume, P., Marfell-Jones, M. (2008) ‘The importance of accurate site location for skinfold measurement’, Journal of Sports Sciences, 26(12), pp. 1333-1340.
- Jones, B., Emmonds, S., Hind, K., Nicholson, G., Rutherford, Z., Till, K. (2016) ‘Physical Qualities of International Female Rugby League Players by Playing Position’, Journal of Strength and Conditioning Research, 30(5), pp. 1333-1340.
- Kyle, U.G., Bosaeus, I., De Lorenzo, A.D., Deurenberg, P., Elia, M., Gómez, J.M., Lilienthal-Heitmann, B., Kent-Smith, L., Melchior, J.C., Pirlich, M., Scharfetter, H., Schols, A., Pichard, C. (2004) ‘Bioelectrical impedance analysis – part I: review of principles and methods’, Clinical Nutrition, 23(5), pp. 1226-1243.
- Ravikanth, R. (2017) ‘Effective Radiological Imaging for the Good of Patients: Weighing Benefits and Risks’, World Journal of Nuclear Medicine, 16(2), pp. 85-87.
- Smith-Ryan, A.E., Mock, M.G., Ryan, E.D., Gerstner, G.R., Trexler, E.T., Hirsch, K.R. (2017) ‘Validity and reliability of a 4-compartment body composition model using dual energy x-ray absorptiometry-derived body volume’, Clinical Nutrition, 36(3), pp. 825-830.
- Wells, J.C., Fewtrell, M.S. (2006) ‘Measuring body composition’, Archives of Disease in Childhood, 91(7), pp. 612-617.
- Zemski, A.J., Keating, S.E., Broad, E.M., Slater, G.J. (2019) ‘Longitudinal Changes in Body Composition Assessed Using DXA and Surface Anthropometry Show Good Agreement in Elite Rugby Athletes’, International Journal of Sport Nutrition and Exercise Metabolism¸ 29(1).