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Anthropometric profiles and body composition of male runners at different distances

Anthropometric parameters are crucial prerequisite to achieve success in professional running sports. However, it is not clear how these parameters are relevant for athletes performing on a less demanding sport level as academic competitions. To help coaches and selectors working on this level, we h...

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Detalles Bibliográficos
Autores principales: Stachoń, Aleksandra, Pietraszewska, Jadwiga, Burdukiewicz, Anna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10600198/
https://www.ncbi.nlm.nih.gov/pubmed/37880292
http://dx.doi.org/10.1038/s41598-023-45064-9
Descripción
Sumario:Anthropometric parameters are crucial prerequisite to achieve success in professional running sports. However, it is not clear how these parameters are relevant for athletes performing on a less demanding sport level as academic competitions. To help coaches and selectors working on this level, we have explored anthropometric variables and body composition in 68 academic athletes: 26 sprinters, 22 middle distance runners, and 20 long distance runners. Sprinters have a more massive body shape, shorter lower legs in relation to the length of the thigh, broader shoulders and narrower hips, greater musculature and cellular mass. A slender figure, a longer shin, and the greatest subcutaneous fat and extracellular mass characterize long-distance runners. Middle-distance runners are the slimmest, and have a narrow trunk and little subcutaneous fat. Sprinters and long-distance runners are mesomorphic, while middle-distance runners present more mixed mesomorph-ectomorph type. The principal component analysis highlighted the importance of the overall size of the body, limbs musculature and the length of the lower limb together with its segments, and also body fatness. This approach emphasized the morphological distinctiveness of runners at particular distances and allows the use of somatic features as predictors of running performance.