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Cited by 420

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The Incidence and Distribution of Stress Fractures in Competitive Track and Field Athletes: A Twelve-Month Prospective Study

Bennell, Kim L., Malcolm, Susan A., Thomas, Shane A., Wark, John D., Brukner, Peter D.·1996·The American Journal of Sports Medicine

Abstract

The incidence and distribution of stress fractures were evaluated prospectively over 12 months in 53 female and 58 male competitive track and field athletes (age range, 17 to 26 years). Twenty athletes sustained 26 stress fractures for an overall incidence rate of 21.1%. The incidence was 0.70 for the number of stress frac tures per 1000 hours of training. No differences were observed between male and female rates ( P > 0.05). Twenty-six stress fractures composed 20% of the 130 musculoskeletal injuries sustained during the study. Although there was no difference in stress fracture incidence among athletes competing in different events ( P > 0.05), sprints, hurdles, and jumps were associated with a significantly greater number of foot fractures; middle- and long-distance running were as sociated with a greater number of long bone and pelvic fractures ( P < 0.05). Overall, the most common sites of bone injuries were the tibia with 12 injuries (46%), followed by the navicular with 4 injuries (15%), and the fibula with 3 injuries (12%). The high incidence of stress fractures in our study suggests that risk factors in track and field athletes should be identified.

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Metadata

Authors
Bennell, K. L., Malcolm, S. A., Thomas, S. A., Wark, J. D., & Brukner, P. D.
Venue
The American Journal of Sports Medicine
Published
1996-03
Volume
24
Issue
2
Pages
211-217
ISSN
  • 0363-5465 (ISSN-L)
  • 1552-3365
OpenAlex
W2046584535
Cited by
420
References
0
FWCI
6.50
Type
journal article
Language
en
Open access
closed

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.