The Relationship Between Anthropometric Variables and Race Performance
Dessalew GW, Open Access Journal of Sports Medicine 27 December 2019 Volume 2019:10 Pages 209—216
The key elements of success in a given sports competition have become an area of interest for researchers. The reason for the success of Ethiopian runners was not proved scientifically. This study aimed at documenting the anthropometric parameters of 10,000 meter runners and to find out the association between such parameters and performances.
Methods: A descriptive field study was conducted. 32 elite 10,000 meter runners participated.
The data were collected while the athletics team was preparing for the world athletics championship. The procedure was repeated three times for each individual. Statistical analysis was performed using SPSS version 18. All the data were presented as mean ± S.D. The Pearson product-moment test was used to determine the correlation between the variables and finishing time. The level of significance for all statistical tests was set at p < 0.05.
Results: The experience of male and female athletes showed a negative association with finishing time. However, there was no statistically significant correlation between the age and running time in both sexes. A significant positive association of body weight to running time was observed in both sexes. Body height correlates positively to running time in males (p<0.05), but not in females. The length of the arm, the forearm, the leg in both sexes and length of the thigh in women had no significant association with finishing time. A smaller arm and calf circumferences have a positive effect on the performance of both sexes. Smaller thigh circumference showed a positive association with the performance of men.
Conclusion: The age of the runners did not correlate with their performance. The anthropometric variables displayed significantly higher values in men than in women. Experienced athletes performed better in both sexes. Anthropometric parameters may be useful for selection, prediction, improving running performance besides for preventing injuries and health risk assessment.