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Central European Journal of Sport Sciences and Medicine
Vol. 47, No. 3/2024
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1 077
Publications
412
H-index
12
I10-index
22
Mean citedness (2 years)
0.43
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20174237
20183345
20193556
202038112
202138106
202231146
202330150
202429161
202530132
20261667

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Comparative Analysis of Somatic Parameters and Movement Quality in Novice and Experienced CrossFit Athletes

DOI: 10.18276/cej.2024.3-01
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ISSN:2300-9705
eISSN:2353-2807
Authors: Piotr Sporek ORCID
Faculty of Physical Education and Physiotherapy, Opole University of Technology, Opole, Poland

Mariusz Konieczny ORCID
Faculty of Physical Education and Physiotherapy, Opole University of Technology, Opole, Poland
Keywords: Functional training functional movement screen body fat injury risk
Issue / book publication date:2024
Page range:11 (5-15)
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Abstract

In this study, fifty active CrossFit athletes were divided into beginner (n=25, mean age 24.8±5.2 years) and experienced groups (n=25, mean age 25.1±4.9 years) to assess injury risk, body fat distribution, and functional movement quality at different levels of experience. All participants attended training sessions five times a week and were preparing for competitions, training CrossFit at a competitive level, with the beginner group having up to 2 years of CrossFit training and the experienced group having 4-6 years of training. We involved fifty active CrossFit athletes, divided into beginner and experienced groups, in our study. The athletes in the beginning group (n=25, mean age 24.8±5.2 years) had no more than 2 years of training experience, while the athletes in the experienced group (n=25, mean age 25.1±4.9 years) had between 4-6 years of training experience. All participants attended training sessions five times a week and were preparing for competitions, training CrossFit at a competitive level. Both groups were evaluated for skinfold thickness and body fat percentage using appropriate measurement techniques, while functional movements were assessed separately using the Functional Movement Screen (FMS) Kit system and protocol. The results indicated that the experienced group demonstrated significantly higher overall FMS scores (U = 71.5, p < .001, r = 0.67), suggesting better functional movement patterns and potentially lower injury risk. They also exhibited higher body density and lower body fat percentages (U = 126, p < .001, r = 0.51) compared to the beginner group, which had higher skinfold thickness measurements in the breast, abdominal, and thigh areas. The findings of the study suggest that with increased experience in CrossFit training, athletes tend to have lower body fat, especially in the lower body, and exhibit improved functional movement quality. These improvements in movement efficiency potentially decrease the risk of injury, highlighting the benefits of long-term participation in high-intensity CrossFit training.

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Bibliography (29)
  1. Ballesta-García, I., Martínez-González-moro, I., Rubio-Arias, J., & Carrasco-Poyatos, M. (2019). High-intensity interval circuit training versus moderate-intensity continuous training on functional ability and body mass index in middle-aged and older women: A randomized controlled trial. International Journal of Environmental Research and Public Health, 16(21), Article 4205. https://doi.org/10.3390/ijerph16214205
  2. Bond, D., Goodson, L., Oxford, S. W., Nevill, A. M., & Duncan, M. J. (2015). The association between anthropometric variables, functional movement screen scores and 100 m freestyle swimming performance in youth swimmers. Sports, 3(1), 1–11. https://doi.org/10.3390/sports3010001
  3. Campa, F., Piras, A., Raffi, M., & Toselli, S. (2019). Functional movement patterns and body composition of high-level volleyball, soccer, and rugby players. Journal of Sport Rehabilitation, 28(7), 740–745. https://doi.org/10.1123/jsr.2018-0087
  4. Cook, G., Burton, L., & Hoogenboom, B. (2006a). Pre-participation screening: the use of fundamental movements as an assessment of function - part 1. North American Journal of Sports Physical Therapy : NAJSPT, 1(2), 62–72.
  5. Cook, G., Burton, L., & Hoogenboom, B. (2006b). Pre-participation screening: the use of fundamental movements as an assessment of function - part 2. North American Journal of Sports Physical Therapy : NAJSPT, 1(3), 132–139.
  6. Cook, G. (2010). Movement: Functional movement systems: Screening, assessment and corrective strategies (2nd ed.). On Target Publications.
  7. Davis, J. D., Orr, R., Knapik, J. J., & Harris, D. (2020). Functional Movement Screen (FMSTM) Scores and Demographics of US Army Pre-Ranger Candidates. Military Medicine, 185(5–6), e718–e724. https://doi.org/10.1093/milmed/usz373
  8. Dawson, M. C. (2017). CrossFit: Fitness cult or reinventive institution? International Review for the Sociology of Sport, 52(3), 361–379. https://doi.org/10.1177/1012690215591793
  9. Domingos, C., Matias, C. N., Cyrino, E. S., Sardinha, L. B., & Silva, A. M. (2019). The usefulness of Tanita TBF-310 for body composition assessment in Judo athletes using a four-compartment molecular model as the reference method. Revista Da Associacao Medica Brasileira, 65(10), 1283–1290 https://doi.org/10.1590/1806-9282.65.10.1283
  10. Hamdouni, H., Kliszczewicz, B., Zouhal, H., Rhibi, F., Ben Salah, F. Z., & Ben Abderrahman, A. (2022). Effect of three fitness programs on strength, speed, flexibility and muscle power on sedentary subjects. Journal of Sports Medicine and Physical Fitness, 62(1), 132–139. https://doi.org/10.23736/S0022-4707.21.12086-9
  11. Herz, J. C., Morais, D. G., & Todd, J. (2015). Learning to Breathe Fire: The Rise of CrossFit and the Primal Future of Fitness. Sport Management Review, 18(4), 491–493. https://doi.org/10.1016/j.smr.2014.11.007
  12. Kaczorowska, A., Noworyta, K., Mroczek, A., & Lepsy, E. (2020). Effect of the mobilityWOD training program on functional movement patterns related to the risk of injury in crossfit practitioners. Acta Gymnica, 50(1), 1–10. https://doi.org/10.5507/ag.2020.002
  13. Kiesel, K., Plisky, P. J., & Voight, M. L. (2007). Can Serious Injury in Professional Football be Predicted by a Preseason Functional Movement Screen? North American Journal of Sports Physical Therapy : NAJSPT, 2(3), 147–158.
  14. Klimek, C., Ashbeck, C., Brook, A. J., & Durall, C. (2018). Are injuries more common with CrossFit training than other forms of exercise? Journal of Sport Rehabilitation, 27(3), 295–299. https://doi.org/10.1123/jsr.2016-0040
  15. Kuhn, S. (2013). The culture of CrossFit: A lifestyle prescription for optimal health and fitness (Senior thesis, Illinois State University). Illinois State University. https://ir.library.illinoisstate.edu/sta/1
  16. Kuzuhara, K., Shibata, M., Iguchi, J., & Uchida, R. (2018). Functional Movements in Japanese Mini-Basketball Players. Journal of Human Kinetics, 61(1), 135–142. https://doi.org/10.1515/hukin-2017-0128
  17. Leitão, L., Dias, M., Campos, Y., Vieira, J. G., Sant’ana, L., Telles, L. G., Tavares, C., Mazini, M., Novaes, J., & Vianna, J. (2021). Physical and physiological predictors of fran crossfit® wod athlete’s performance. International Journal of Environmental Research and Public Health, 18(8), Article 4070. https://doi.org/10.3390/ijerph18084070
  18. Magyari, N., Szakács, V., Bartha, C., Szilágyi, B., Galamb, K., Magyar, M. O., Hortobágyi, T., Kiss, R. M., Tihanyi, J., & Négyesi, J. (2017). Gender may have an influence on the relationship between Functional Movement Screen scores and gait parameters in elite junior athletes – A pilot study. Physiology International, 104(3), 231–242. https://doi.org/10.1556/2060.104.2017.3.1
  19. Menargues-Ramírez, R., Sospedra, I., Holway, F., Hurtado-Sánchez, J. A., & Martínez-Sanz, J. M. (2022). Evaluation of body composition in CrossFit® athletes and the relation with their results in official training. International Journal of Environmental Research and Public Health, 19(17), Article 11003. https://doi.org/10.3390/ijerph191711003
  20. Moghimi Sarani, A. (2020). CrossFit training improves blood lipid profile in overweight men: A randomized controlled trial. Journal of Physical Activity and Hormones , 4(1), 17–28.
  21. Montalvo, A. M., Shaefer, H., Rodriguez, B., Li, T., Epnere, K., & Myer, G. D. (2017). Retrospective injury epidemiology and risk factors for injury in CrossFit. Journal of Sports Science and Medicine, 16(1), 53–59.
  22. Moore, E., Chalmers, S., Milanese, S., & Fuller, J. T. (2019). Factors Influencing the Relationship Between the Functional Movement Screen and Injury Risk in Sporting Populations: A Systematic Review and Meta-analysis. In Sports Medicine, 49(9), 1449–1463. https://doi.org/10.1007/s40279-019-01126-5
  23. Perna, S., Bologna, C., Agosti, I. D., & Rondanelli, M. (2018). High intensity crossfit training compared to high intensity swimming: A pre-post trial to assess the impact on body composition, muscle strength and resting energy expenditure. Asian Journal of Sports Medicine, 9(1), Article e13843– https://doi.org/10.5812/asjsm.13843
  24. Schneiders, A. G., Davidsson, A., Hörman, E., & Sullivan, S. J. (2011). Functional movement screen normative values in a young, active population. International Journal of Sports Physical Therapy, 6(2), 75–82.
  25. Smith, M. M., Sommer, A. J., Starkoff, B. E., & Devor, S. T. (2013). Crossfit-based high-intensity power training improves maximal aerobic fitness and body composition. In Journal of Strength and Conditioning Research, 27(11), 3159–3172. https://doi.org/10.1519/JSC.0b013e318289e59f
  26. Tafuri, S., Notarnicola, A., Monno, A., Ferretti, F., & Moretti, B. (2016). Crossfit athletes exhibit high symmetry of fundamental movement patterns. A cross-sectional study. Muscles, Ligaments and Tendons Journal, 6(1), 157–160. https://doi.org/10.11138/mltj/2016.6.1.157
  27. Weisenthal, B. M., Beck, C. A., Maloney, M. D., DeHaven, K. E., & Giordano, B. D. (2014). Injury rate and patterns among crossfit athletes. Orthopaedic Journal of Sports Medicine, 2(4), Article 2325967114531177. https://doi.org/10.1177/2325967114531177
  28. Westerterp K. R., & Skowrońska U. (2007). Skład ciała i jego pomiary, red. Sobotka L., Podstawy żywienia klinicznego,: Vol. PZWL.
  29. Wright, M. D., & Chesterton, P. (2018). Functional Movement ScreenTM total score does not present a gestalt measure of movement quality in youth athletes. Journal of Sports Sciences, 36(22), 2521–2527. https://doi.org/10.1080/02640414.2018.1465724