Injury prediction in aerobic gymnastics based on anthropometric variables
Objective: Use logistic regression to determine a mathematical model which is able to predict injuries in aerobic gymnastics (AG) athletes, according to certain anthropometric characteristics.
Subjects and methods: In total, 73 athletes were recruited, of whom 51 were gymnasts and 22 were athletes from other sports. The independent variables were anthropometric characteristics of both lower extremities. The dependent variable was injury at the end of the season.
Results: The statistical model indicated that the effect of the Q angle on the likelihood of injury varies depending on the weight of the gymnast. An excessive Q angle is an anthropometric factor that may predispose to injury, especially the left Q angle.
Conclusion: Studies that analyze anthropometric characteristics can contribute to understanding what variables or parameters may cause injuries in athletes. Thus, in the future, intervention strategies could be developed and the onset of certain injuries could be prevented.
© Copyright 2018 Science & Sports. Elsevier. All rights reserved.
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| Notations: | technical sports biological and medical sciences |
| Published in: | Science & Sports |
| Language: | English |
| Published: |
2018
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| Online Access: | https://doi.org/10.1016/j.scispo.2018.02.002 |
| Volume: | 33 |
| Issue: | 4 |
| Pages: | 228-236 |
| Document types: | article |
| Level: | advanced |