Athletic Training

Bone stress injuries (BSI) occur frequently in runners and females. However, their occurrence in other sports, time-lost (TL) status, and associated healthcare utilization is unclear.

PURPOSE

To describe bone stress injuries and associated healthcare utilization in a population of collegiate student athletes.

METHODS

A descriptive epidemiology design utilizing de-identified electronic medical records from all sponsoring institutions in one NCAA conference was used. Injury occurrences were collected from August 2017 - March 2020, representing 810 team-seasons (351 men’s and 459 women’s). Injuries were identified by onset (acute or overuse) and stratified as TL or non-time-loss (NTL). Lower extremity injury location and injury type were identified. Associated healthcare utilization, including athletic training services (ATS) provided, and injuries resulting in one or more physician encounters (PE), prescribed medication, diagnostic test, procedure, or surgery were determined. Mean BSI per team per season were calculated.

RESULTS

A total of 501 BSI were captured, representing 2.5% of all injuries/illnesses in the time period (n = 20080). The majority (n = 341, 68.1%) were in women’s teams. Overuse-NTL BSI comprised 13.8% of the sample (n = 69). The foot was the most frequent location (n = 164, 68.3%). Women’s track and field (n = 106, 21.2%, 2.9) and women’s cross country (n = 86, 17.2%, 2.4) reported the highest occurrence of BSI by sport and highest occurrence per team per season. BSI necessitated 13907 ATS, and 462 BSI required PE, resulting in medications prescribed in 54, tests in 458, procedures in 8, and surgeries in 74 cases. Of ATS, 65% (n = 9056) were for overuse injuries, with women utilizing 77.7% (n = 7037) of them.

CONCLUSIONS

Women experienced the majority of BSI, concentrated in running sports. Most BSI in men and women were designated as overuse and resulted in TL, but almost 14% were managed as overuse-NTL. BSI required substantial AT and physician services, and prevention may be possible with data-driven programs. This project was supported by the Pac-12 Conference’s Student-Athlete Health and Well-Being Initiative. The content of this abstract is solely the responsibility of the authors and does not necessarily represent the official views of the Pac-12 Conference, or its members