The body composition of elite wheelchair basketball players

2012-07-26T14:21:07Z (GMT) by Mhairi Keil
The assessment of body composition is a commonly used monitoring tool in elite sports, to assess changes as a result of either a training and/or dietary intervention. Theoretically, excess body fat, above levels required for health and sporting performance, constitutes additional load that is non-functional. In most sports, the movement of this additional weight will increase energy expenditures and muscle glycogen utilisation and could contribute to premature muscle fatigue. In addition, non-functional mass has also been shown to have an impact on performance factors such as speed, acceleration and drag/rolling resistance (e.g. in cycling or wheelchair sports). For these reasons, body composition is often an important performance measure that requires attention. Individuals who are wheelchair bound experience substantial muscle atrophy of the lower extremities and have a greater tendency to store fat mass. It is of importance from both a health and performance perspective to understand the body composition of athletes with a disability. There are numerous techniques available to estimate body composition; therefore it is also important to determine the most suitable for use in elite wheelchair athletes, and whether they are sensitive enough to detect small yet significant changes. The first study, Chapter 4 was designed to assess the reproducibility of dual energy X-ray absorptiometry within a cohort of elite wheelchair basketball players. In addition, this chapter sought to establish measurement error and determine the least significant change that would need to be observed, to be certain of a change in body composition. The findings demonstrated good reproducibility with coefficient of variation values for all whole body measurements being <2.0%, with the exception of arm fat mass (kg) (7.8%). All segmental coefficient of variation values ranged between 0.1-3.7% for bone mass, fat mass and lean mass. The least significant change for fat mass, lean mass and bone mass were determined to be at least 1kg, 1.1kg and 120g, respectively. This information concluded that dual energy X-ray absorptiometry was an appropriate reference technique for use in this specific cohort and helped to identify meaningful changes in body composition in Study3, Chapter 6. Chapter 5 compared body composition data obtained from three techniques (skinfold measurements and associated skinfold prediction equations, bioelectrical impedance and air displacement plethysmography), to the reference data obtained from DXA, in order to establish the agreement, accuracy and validity between the methods employed. These findings demonstrated that whilst skinfold prediction equations, bioelectrical impedance and air displacement plethysmography showed a good agreement with DXA, neither were accurate or valid techniques for the assessment of body composition in elite wheelchair athletes. The final study (Chapter 6) documented the seasonal changes that occurred throughout a 15 month training period. In addition this chapter examined how well skinfold measurements could track changes in body composition, and how sensitive this technique was to changes in fat mass, as identified using DXA. The results demonstrated that the sum of skinfold measurements could track small (0.34 standard deviations) to moderate (0.4 standard deviations) changes in fat mass. In absolute terms the least significant change for sum of 8, 6 and 4 skinfolds were 14mm, 13mm and 10mm. In relative terms, a ratio of 1.13, 1.17 and 1.28 could be applied to sum of 8, 6 and 4 skinfolds to establish the smallest meaningful change. In addition, a skinfold prediction equation was proposed that could determine percentage body fat from sum of skinfolds in elite wheelchair athletes. The results of this thesis add to the current literature by describing the physical characteristics of elite wheelchair athletes, and demonstrating that DXA and skinfold measurements are appropriate techniques for use in this population. These findings also provide some useful guidelines to determine meaningful change and present a skinfold prediction equation that is specific to this cohort.