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Training load characteristics and injury and illness risk identification in elite youth ski racing: A prospective study

PURPOSE: The study aimed to investigate the role of training load characteristics and injury and illness risk in youth ski racing. METHODS: The training load characteristics as well as traumatic injuries, overuse injuries, and illnesses of 91 elite youth ski racers (age = 12.1 ± 1.3 years, mean ± SD...

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Detalles Bibliográficos
Autores principales: Hildebrandt, Carolin, Oberhoffer, Renate, Raschner, Christian, Müller, Erich, Fink, Christian, Steidl-Müller, Lisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Shanghai University of Sport 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7987564/
https://www.ncbi.nlm.nih.gov/pubmed/32428673
http://dx.doi.org/10.1016/j.jshs.2020.03.009
Descripción
Sumario:PURPOSE: The study aimed to investigate the role of training load characteristics and injury and illness risk in youth ski racing. METHODS: The training load characteristics as well as traumatic injuries, overuse injuries, and illnesses of 91 elite youth ski racers (age = 12.1 ± 1.3 years, mean ± SD) were prospectively recorded over a period of 1 season by using a sport-specific online database. Multiple linear regression analyses were performed to monitor the influence of training load on injuries and illnesses. Differences in mean training load characteristics between preseason, in-season, and post-season were calculated using multivariate analyses of variance. RESULTS: Differences were discovered in the number of weekly training sessions (p = 0.005) between pre-season (4.97 ± 1.57) and post-season (3.24 ± 0.71), in the mean training volume (p = 0.022) between in-season (865.8 ± 197.8 min) and post-season (497.0 ± 225.5 min) and in the mean weekly training intensity (Index) (p = 0.012) between in-season (11.7 ± 1.8) and post-season (8.9 ± 1.7). A total of 185 medical problems were reported (41 traumatic injuries, 12 overuse injuries, and 132 illnesses). The weekly training volume and training intensity was not a significant risk factor for injuries (p > 0.05). Training intensity was found to be a significant risk factor for illnesses in the same week (β = 0.348; p = 0.044; R² = 0.121) and training volume represents a risk factor for illnesses in the following week (β = 0.397; p = 0.027; R² = 0.157). CONCLUSION: A higher training intensity and volume were associated with increased illnesses, but not with a higher risk of injury. Monitoring training and ensuring appropriate progression of training load between weeks may decrease incidents of illness in-season.