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Cited by 210

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Spine injuries in gymnasts and swimmers: An epidemiologic investigation

Goldstein, Jack D., Berger, Paul E., Windler, Gary E., Jackson, Douglas W.·1991·The American Journal of Sports Medicine

Abstract

Three groups of top level female gymnasts of preelite, elite, national and Olympic caliber were studied without regard to back pain or injury. These athletes were compared to a similar group of national caliber female swimmers. Magnetic resonance imaging scans of each participant were used to document disk or bony abnor malities. The relationship between magnetic resonance imaging findings and age, height, weight, previous in juries, back symptoms, and hours of training per week each year was examined. Nine percent of preelite (1/11), 43% of elite (6/14), and 63% of Olympic level (5/8) gymnasts had spine abnormalities; 15.8% of all swimmers had spine abnor malities. Average hours of training per week and age were found to be associated with abnormalities seen on magnetic resonance imaging. Increased intensity and length of training correlated with previous data that suggests the female gymnast is prone to spine injuries.

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Metadata

Authors
Goldstein, J. D., Berger, P. E., Windler, G. E., & Jackson, D. W.
Venue
The American Journal of Sports Medicine
Published
1991-09
Volume
19
Issue
5
Pages
463-468
ISSN
  • 0363-5465 (ISSN-L)
  • 1552-3365
OpenAlex
W2021820566
Cited by
210
References
0
FWCI
2.43
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Spine injuries in gymnasts and swimmers: An epidemiologic investigation. https://app.cochat.ai/papers/10.1177/036354659101900507
The paper
Goldstein, J. D., Berger, P. E., Windler, G. E., & Jackson, D. W. (1991). Spine injuries in gymnasts and swimmers: An epidemiologic investigation. The American Journal of Sports Medicine. https://doi.org/10.1177/036354659101900507

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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.