EEddiitthh CCoowwaann UUnniivveerrssiittyy RReesseeaarrcchh OOnnlliinnee Theses: Doctorates and Masters Theses 2016 CCoommppaarriissoonn ooff bbooddyy ccoommppoossiittiioonn,, nneeuurroommuussccuullaarr cchhaarraacctteerriissttiiccss aanndd aannaaeerroobbiicc eenndduurraannccee bbeettwweeeenn nnoovviiccee,, sseemmii--pprrooffeessssiioonnaall aanndd pprrooffeessssiioonnaall bbaalllleett ddaanncceerrss Penelope Blanco Ochoa Edith Cowan University Follow this and additional works at: https://ro.ecu.edu.au/theses Part of the Dance Commons, and the Sports Sciences Commons RReeccoommmmeennddeedd CCiittaattiioonn Blanco Ochoa, P. (2016). Comparison of body composition, neuromuscular characteristics and anaerobic endurance between novice, semi-professional and professional ballet dancers. https://ro.ecu.edu.au/ theses/1798 This Thesis is posted at Research Online. https://ro.ecu.edu.au/theses/1798 Edith Cowan University Research Online Theses: Doctorates and Masters Theses 2016 Comparison of body composition, neuromuscular characteristics and anaerobic endurance between novice, semi-professional and professional ballet dancers Penelope Blanco Ochoa Edith Cowan University Recommended Citation Blanco Ochoa, P. (2016).Comparison of body composition, neuromuscular characteristics and anaerobic endurance between novice, semi- professional and professional ballet dancers. Retrieved from http://ro.ecu.edu.au/theses/1798 This Thesis is posted at Research Online. http://ro.ecu.edu.au/theses/1798 Edith Cowan University      Copyright Warning            You may print or download ONE copy of this document for the purpose  of your own research or study.    The University does not authorize you to copy, communicate or  otherwise make available electronically to any other person any  copyright material contained on this site.    You are reminded of the following:     Copyright owners are entitled to take legal action against persons  who infringe their copyright.     A reproduction of material that is protected by copyright may be a  copyright infringement. Where the reproduction of such material is  done without attribution of authorship, with false attribution of  authorship or the authorship is treated in a derogatory manner,  this may be a breach of the author’s moral rights contained in Part  IX of the Copyright Act 1968 (Cth).     Courts have the power to impose a wide range of civil and criminal  sanctions for infringement of copyright, infringement of moral  rights and other offences under the Copyright Act 1968 (Cth).  Higher penalties may apply, and higher damages may be awarded,  for offences and infringements involving the conversion of material  into digital or electronic form . Comparison of body composition, neuromuscular characteristics and anaerobic endurance between novice, semi-professional and professional ballet dancers. PENELOPE BLANCO OCHOA, BSc Submitted in fulfilment of the requirements for the degree of Master of Science (Sports Science) 2016 School of Medical and Health Sciences Edith Cowan University Supervisors: Principal Supervisor: Dr. G. Gregory Haff Co-Principal Supervisor: Dr. Sophia Nimphius USE OF THESIS The Use of Thesis statement is not included in this version of the thesis. ABSTRACTS Study 1 Comparison of body composition, neuromuscular characteristics and anaerobic endurance between novice, semi-professional and professional ballet dancers. The purpose of this study was to compare selected physiological fitness parameters including: body composition, neuromuscular characteristics and aerobic endurance were significantly different between novice, semi-professional and professional ballet dancers. The secondary purpose was to establish which parameters were best discriminators between these dancers. Thirty-five classical ballet dancers (male: n =11 and female: n =24) divided into three different groups according to their dance skill level: novice (n=12) (age: 16.6 ± 1.5 y; height: 1.7 ± 0.1 m; weight: 58.0 ± 13.0 kg), semi-professional (n=13) (age: 20.0 ± 1.6 y; height: 1.7 ± 0.1 m; weight: 64.1 ± 10.5 kg), and professional (n=10) (age: 23.8 ± 3.5 y; height: 1.8 ± 1.2 m; weight: 63.3 ± 14.7 kg) completed one testing session. The testing session, examined dancer’s body composition, neuromuscular characteristics and anaerobic endurance. To examine the differences between groups multivariate analysis of covariance (MANCOVA) was performed with gender and age controlled and a discriminant analysis was performed to determine which variables (grouped into body composition, jumping ability variables, or lower limb isometric strength) were the best predictors of group membership classification. MANCOVA results demonstrated significant differences between the groups in measures of: body fat percentage, lean muscle mass, bone mineral density, countermovement jump peak force, countermovement jump peak power, countermovement jump peak velocity, countermovement jump vertical displacement, drop jump peak force and drop jump vertical displacement (p<0.05). In addition, BMD and the displacement of CoM in a specific ballet leap were found to be the best discriminatory variables for group membership (p= 0.011 and p=0.019 respectively). These findings suggest that many variables differ between different levels of ballet dancers and the best discriminants of performance are BMD and the height achieved during a grand jeté. Further research is need in order to determine if greater jumping displacements in dance performance training is responsible for the higher BMD seen in the professional dancers. iii Study 2: Do relationships exist between a grand jeté leap and two laboratory-based tests: countermovement jump and drop jump? The primary purpose of this study was to investigate the relationship between a grand jeté leap and two laboratory based jumps, such as countermovement jump (CMJ) and drop jump (DJ). The secondary purpose was to establish if the magnitude of the relationship between three different skill levels: novice, semi-professional and professional ballet dancers. Thirty-five classical ballet dancers (male: n=11 and female: n=24) divided into three different groups according to their dance skill level: novice (n=12) (age: 16.6 ± 1.5 y; height: 1.7 ± 0.1 m; weight: 58.0 ± 13.0 kg), semi- professional (n=13) (age: 20.0 ± 1.6 y; height: 1.7 ± 0.1 m; weight: 64.1 ± 10.5 kg), and professional (n=10) (age: 23.8 ± 3.5 y; height: 1.8 ± 1.2 m; weight: 63.3 ± 14.7 kg) completed a single testing session. The participants performed three types of jumps. The first jump constituted of a specific ballet leap (grand jeté) and the difference between standing the centre of mass (CoM) height and displacement of CoM at the peak of the ballet jump was determined by three-dimensional motion capture. Next, the CMJ was executed standing on a force plate and the DJ was performed from a 40cm height box onto a force plate. Vertical displacement in both jumps (CMJ and DJ ) was calculated from flight time. The relationship between VD VD the displacement of CoM and CMJ and DJ was assessed by Pearson product- VD VD moment correlation coefficient. Significant relationships were found between the grand jeté and CMJ (r=0.77, p=0.001) and DJ (r=0.76, p=0.001). Further, when the groups were analysed individually (CMJ: novice r=0.64, p=0.025; semi-professional r= 0.75, p=0.003 and professionals r=0.91, p= 0.001; DJ: novice r=0.70, p=0.001; semi-professional r=0.80, p=0.001; professionals r=0.86, p=0.001) the magnitude of the relationship improved with increasing skill level. In addition, results indicated that a grand jeté leap could be predicted utilising a regression equation from the CMJ VD and DJ (p<0.05). In conclusion displacement of CoM in a grand jeté leap showed VD large to very large correlations in two laboratory based tests: CMJ and DJ. Correlations became stronger as group skill level increased, suggesting that with superior specific ballet skills dancers may be better able to utilise their physical capacity to jump higher within the context of ballet specific jumping. Moreover, ballet experts and instructors may be able to predict ballet specific jump ability from faster and less costly laboratory based tests such as CMJ and DJ. iv COPYRIGHT AND ACCESS DECLARATION I certify that this thesis does not, to the best of my knowledge and belief: (i) incorporate without acknowledgement any material previously submitted for a degree or diploma in any institution of higher education; (ii) contain any material previously published or written by another person except where due reference is made in the text; or (iii) contain any defamatory material. Signed (signature not included in this version of thethesis) Date………………………………………. ACKNOWLEDGEMENTS I would like to express my sincere gratitude to everyone who helped me and supported me through this journey. To my dearest supervisor Dr. Greg Haff, you have been a remarkable mentor for me. Thank you for your patience, commitment and dedication to my project and also for allowing me to grow not only as a research scientist but also as a person. Your advice and kind words when most needed have made a huge difference not only in my research but also in my career. To my co- supervisor Dr. Sophia Nimphius I would like to thank you for your invaluable guidance and support during the past three years. Your illuminating knowledge and constructive criticism made me challenge myself and thrive for excellence. Thank you so much to all the dancers that participated in this study. I am very grateful for your cooperation and professionalism. Your efforts will hopefully assist and motivate young dancers. Special thanks to the WA Conservatoire of Classical Ballet, to WA Academy of performing arts and to the WA ballet for kindly agree to use the dancers for this study. To all the members of the technical staff at ECU: Nadija Vrdoljak, Elisabeth Depetro and Helen Alexander that kindly helped me and facilitated all the equipment and laboratories for the data collection, thank you so much for your assistance. There were many colleagues that helped me in all the stages of my thesis, but I would like to particularly point out a few. To Tania Spiteri, thank you so much for all your hard work and enthusiasm over this time. Your knowledge and ability to solve problems are outstanding, I only hope some day I could help you the same way you help me. To Laurent Seitz I am so grateful that you made long days fun and difficult times tolerable. Your humour and your attitude towards work are really worth admiration. To my dear friend Chantelle du Plessis, I am so lucky to have met you and even more fortunate to study with you. In all these years you have really gone out of your way to help me and support me, thank you so much. To “Professor Andy Govus” without you the statistics session in this thesis would not have been completed. Thank you for taking the time and devotion to teach me I hope I did not let you down. To Ryan Lin, I am very grateful for all your assistance and expertise. To all my peers that some how helped with data collection, or just simply gave me a vi word of encouragement when I most needed it: James Tufano, Jenny Conlon, Vincent, Gabriel Trajano and Nicholas Hart. I would like to acknowledge and thank my outstanding husband Christopher Bishop. Not only you are the brightest mind that I have ever seen but also you are the best companion anybody can wish for. Your love, support and encouragement over the years have allowed me to complete my research journey. I will always be in debt to you. A would like to recognise my beautiful mother Dr. Mariangel Ochoa who possesses more than thirty years of experience as an academic. Thank you for helping me complete and polish my thesis. With your example, I learnt that with discipline and hard work anyone could accomplish great things. Lastly, I would like to dedicate this thesis to my daughter Larissa, who came into my life after data collection. You are the soul of this project, thank you for giving me strength everyday. vii