Context

Bone-stress injury (BSI) is common in collegiate athletes. Injury rates and health care use in running athletes are not well documented.

Objective

To describe the rate and classification of injury and associated health care use in collegiate cross-country runners with BSI.

Design

Descriptive epidemiology study.

Setting

Sports medicine facilities participating in the Pac-12 Health Analytics Program.

Patients or Other Participants

Pac-12 Conference collegiate cross-country athletes.

Main Outcome Measure(s)

Counts of injury and health care resources used for each injury. Injury rates were calculated based on athlete-seasons.

Results

A total of 168 BSIs were reported over 4 seasons from 80 team-seasons (34 men’s and 46 women’s team-seasons) and 1220 athlete-seasons, resulting in 1764 athletic training services and 117 physician encounters. Bone-stress injuries represented 20% of all injuries reported by cross-country athletes. The average BSI rate was 0.14 per athlete-season. Injury rates were higher in female (0.16) than male (0.10) athletes and higher in the 2019–2020 season (0.20) than the 2020–2021 (0.14), 2018–2019 (0.12), and 2021–2022 (0.10) seasons. Most BSIs occurred in the lower leg (23.8%) and the foot (23.8%). The majority of injuries were classified as overuse and time loss (72.6%) and accounted for most of the athletic training services (75.3%) and physician encounters (72.6%). We found a mean of 10.89 athletic training services per overuse and time-loss injury and 12.20 athletic training services per overuse and non–time-loss injury. Mean occurrence was lower for physician encounters (0.70), prescription medications (0.04), tests (0.75), procedures (0.01), and surgery (0.02) than for athletic training services (10.50).

Conclusions

Bone-stress injuries are common in collegiate cross-country runners and require considerable athletic training resources. Athletic trainers should be appropriately staffed for this population, and suspected BSIs should be confirmed with a medical diagnosis. Future investigators should track treatment codes associated with BSI to determine best-practice patterns.

Key Points
  • Bone-stress injuries were a common overuse and time-loss injury, occurring in up to 14% of collegiate cross-country runners.

  • Athletic training services were used frequently in the management of bone-stress injury.

Running is one of the most popular forms of physical activity in the United States, with approximately 60 million individuals running as their primary source of exercise.1  Cross-country is a competitive form of long-distance running with unique physiologic and biomechanical demands.2  In 2018–2019, cross-country participation was at its greatest at the high school and collegiate levels.3,4  In that year, approximately 488 460 boys and girls participated in high school cross-country and 19 846 men and women participated in National Collegiate Athletic Association (NCAA) cross-country.3  Unfortunately, running is also associated with a high incidence of injury.5  In collegiate cross-country runners, the overall injury rates are estimated to be 3.96 and 4.01 injuries per 1000 athlete-exposures (AEs) in female and male athletes, respectively.2,6  Given the increased participation and the high rate of injury, continued research is necessary to better understand the epidemiology and management of running-related injuries.

One common injury among long-distance runners is bone-stress injury (BSI).7,8  A BSI is commonly classified as an overuse injury that results from an inability of the bone to withstand repetitive loading.9  Bone loading, which commonly occurs with running, without appropriate recovery can result in structural breakdown leading to stress reactions, stress fractures, and, in some cases, complete bone fractures.9,10  Bone-stress injuries have been suggested to occur in >20% of collegiate runners.8  These injuries also have a high recurrence rate and can require prolonged recovery times.8  Approximately 10% to 22% of runners with a history of BSI sustained a second BSI.9,11,12  In addition, runners with a previous BSI were up to 6 times more likely to sustain a subsequent BSI.11  Recovery time for a single BSI can be up to 27 weeks or longer if surgical intervention is required.9,13  Prolonged recovery times and injury recurrence can impair performance and lead to decreased sports participation. Injured runners often do not replace lost running time with other physical activity, and injury is commonly cited as the top reason individuals quit participation altogether.14,15  Reduced participation is not only a concern for the sport of cross-country but also has a broader effect on physical and psychosocial health.16,17  Cross-country runners may be a population at greater risk of sustaining a BSI due to frequent exposure to repetitive loading and conditions known to affect bone health.8,18  Bratsman et al classified BSI rates in NCAA cross-country runners, but the rates reflected injury patterns from 2009–2010 to 2013–2014 and may not be indicative of current injury rates.19  They also primarily focused on differences in injury rates among NCAA divisions in all sports, included only a small sample of Division I institutions (n = 4) per the methods outlined by Kerr et al, and did not investigate differences in sex.19,20  In addition, management patterns may have changed with advancing knowledge of BSI diagnosis and treatment.9,21  Therefore, further research is needed to not only identify the current rate of BSI in this population but also to describe the management strategies used for this condition.

The description of health care use can quantify injury and treatment burden in specific populations.22,23  Clarifying the number and types of services sought for an injury is useful in determining medical workload and the need for better prevention and treatment programs.22  To our knowledge, health care use for BSI has not been documented in the literature. Considering the prolonged recovery times and high recurrence rate associated with BSI, identification of appropriate intervention strategies is needed. Improved outcomes in this population may be possible through a better understanding of services being provided for individuals with BSI. For example, athletic departments can determine whether athletic training services are adequately supplied for this population for prevention and treatment and whether greater attention needs to be paid to the medical diagnosis and management of this condition. Therefore, our purpose was to describe the epidemiology of individuals diagnosed with BSI in NCAA Division I cross-country runners. Specifically, we sought to identify the rate and location of injury stratified by injury mechanism (acute versus overuse) and time-loss status in all documented BSI cases. Associated health care use, including athletic training services, physician encounters, and other medical services, is also described.

Participants

This project was approved by the Pac-12 Student-Athlete Health and Well-Being Initiative, which oversees the Pac-12 Health Analytics Program (HAP) injury registry.24,25  Eleven institutions provided data over the first 2 collection years (July 2018 through June 2019 and July 2019 through June 2020), and 12 institutions participated in the final 2 years (July 2020 through June 2021 and July 2021 through June 2022).22  National Collegiate Athletic Association activities were suspended from March 2020 through June 2020 due to COVID-19. As a result, the cross-country season, usually taking place in the fall, was moved to spring 2021. Student-athletes at participating institutions provided authorization for their injury data to be used in the HAP.

Procedures

Injury and health care use data were collected during the 2018–2019 through 2021–2022 competitive seasons in male and female cross-country athletes. Data quality, including null data analysis and logic checks, was evaluated and managed by the HAP as further described by Robell et al.25  Throughout the observation period, athletic trainers (ATs) at participating institutions documented injuries and associated health care use in Presagia Sports (Kitman Labs), a web-based electronic medical record documentation system integrated into the HAP and stored via Amazon Web Services.22  Before participation, clinicians were trained in the documentation system and followed common data elements documentation and definitions.24  Participant data were deidentified with a unique numeric code, and only injury, sex, and health care use were linked to each student-athlete’s case.22 

All injuries sustained during an organized practice or competition were recorded by participating ATs.24  Clinicians documented the body part injured and the associated Orchard Sports Injury Classification System (OSICS) code.22,26  For this study, only OSICS codes associated with a BSI (bone stress injury or stress reaction or stress fracture) of the lumbar spine, pelvis, or lower extremity were obtained because the spine and lower extremity are the primary locations of injury in collegiate running populations.2,6  Cases of medial tibial stress syndrome were excluded from analysis because researchers have recently suggested that this should be considered a distinct clinical diagnosis27  separate from BSI and have its own OSICS code. Injuries were classified as acute or overuse. Acute injuries were defined as symptoms presenting within 24 hours after the initial onset of injury with a specific precipitating event, whereas overuse injuries were defined as presenting with a gradual onset with no clear precipitating event.22  This definition of overuse injury is consistent with a “mechanism of gradual onset, and … underlying pathogenesis of repetitive microtrauma.”28  Injuries were also classified as time loss (TL) or non–time loss (NTL) and defined as restricting participation for ≥24 hours or <24 hours, respectively.22  In some overuse cases, the injury was not specified as resulting in TL or NTL. Given the small population sample, these cases were retained for analysis and classified as unspecified. To provide a comprehensive description of BSI in this population, we included all cases with an associated BSI OSICS code, regardless of injury definition or classification.

Health care use associated with each injury was obtained from clinician documentation collected by the HAP as discussed by Robell et al.25  Health care use measures included athletic training services, physician encounters, prescription medications, tests (any associated diagnostic imaging or tests), procedures (performed in a clinic without general anesthesia or the need for a preoperative visit), and surgery (performed in a hospital or surgery center with patients under general anesthesia and attending preoperative and postoperative visits).22  Athletic training services were recorded as the number of sessions, or visits, associated with each injury case and could include any type of evaluation, manual therapy, modality, therapeutic exercise, or testing or skill session. Physician encounters, prescription medications, tests, procedures, and surgery were recorded as present or absent for each case.22 Present indicated athletes had at least 1 physician encounter, prescription medication, test, procedure, or surgery associated with their BSI case.

To examine the rate of injury by sport season, we divided each team’s year into the following periods: preseason, in-season, postseason, and off-season. The periods were defined as in a previous study.22 

Statistical Analysis

We reported injury rates per athlete-season (AS) because individual AEs (in which an individual athlete participates in 1 exposure event: practice or competition) were not tracked for this study.22 Athlete-season was defined as the number of athletes on the roster for each participating team before the start of the season. Approximately 86% of student-athletes across institutions provided authorization to use their information for research.24  Therefore, AS reflects 86% participation. Injury rate ratios (IRRs) with associated 95% CIs were calculated to examine differences in injury rates between sexes and years. Given that injury rates were greatest in the 2019–2020 season, IRRs were referenced to this season for analysis.

Associated health care use was reported for athletic training services, including the number of BSIs that did not receive any services, as well as physician encounters, prescription medications, tests, procedures, and surgery. All services were reported in count and mean per BSI. Injury rates and health care use were reported for all athletes, as well as separately for male and female athletes.

Although it was not part of the original analysis, we completed a post hoc analysis of the data with the 13 acute cases removed.

Statistical analyses were performed using MedCalc for Windows (version 22.016; MedCalc Software). The α level was set at .05.

Over the 4 seasons of observation, 80 participating teams (34 men’s and 46 women’s teams) and 1220 ASs (86% participation rate) were recorded. Overall, 837 total injuries were reported, and 20% (168 of 837) had OSICS codes consistent with BSI (Figure 1). This resulted in a BSI injury rate of 0.14 per AS between 2018–2019 and 2021–2022 (Table 1). Overall, injury rates were higher in female (0.16) than male (0.10) athletes (IRR = 1.58; 95% CI = 1.13, 2.24; P = .005). When comparing years, injury rates were higher in the 2019–2020 season (0.20) than the 2018–2019 (0.12; IRR = 1.58; 95% CI = 1.03, 2.44; P = .03) and 2021–2022 (0.10; IRR = 1.99; 95% CI = 1.28, 3.17; P = .001) seasons (Table 2). Injury rates were greater in the 2019–2020 (0.20) than the 2020–2021 (0.14) season but were not different (IRR = 1.43; 95% CI = 0.95, 2.19; P = .08). Most injuries were diagnosed in-season (48.81%), followed by off-season (23.21%), preseason (18.45%), and postseason (9.52%; Table 3). Of the 82 BSIs that occurred in-season, 10 occurred between days 1 and 28, 27 between days 29 and 56, 20 between days 57 and 84, and 9 between days 85 and 112. The remaining 16 BSIs occurred during the 2020–2021 season, which was moved to spring 2021. Therefore, these 16 were classified as in-season but occurred outside the traditional 112-day season.

Figure 1

Flow diagram for the selection of study participants. a Present in the database, with authorization for research use provided and injury resolved. b Filtered for sport-related injury. c Filtered for years of inclusion (July 2018–June 2022). d Filtered for bone-stress injury, stress fracture, stress reaction, fracture injury type, and lower extremity and trunk-spine injury location and Orchard Sports Injury Classification System (OSICS) code related to bone-stress injury. eComplete cases defined as having demographic information (sex, sport), onset (acute versus overuse), and time-loss status (time-loss versus non–time-loss versus unspecified). Student-athletes may have had >1 injury case included in the data set. Abbreviation: HAP, Health Analytics Program.

Figure 1

Flow diagram for the selection of study participants. a Present in the database, with authorization for research use provided and injury resolved. b Filtered for sport-related injury. c Filtered for years of inclusion (July 2018–June 2022). d Filtered for bone-stress injury, stress fracture, stress reaction, fracture injury type, and lower extremity and trunk-spine injury location and Orchard Sports Injury Classification System (OSICS) code related to bone-stress injury. eComplete cases defined as having demographic information (sex, sport), onset (acute versus overuse), and time-loss status (time-loss versus non–time-loss versus unspecified). Student-athletes may have had >1 injury case included in the data set. Abbreviation: HAP, Health Analytics Program.

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Table 1.

Bone-Stress Injury Rate in Pac-12 Cross-Country Runners, 2018–2019 Through 2021–2022

Bone-Stress Injury Rate in Pac-12 Cross-Country Runners, 2018–2019 Through 2021–2022
Bone-Stress Injury Rate in Pac-12 Cross-Country Runners, 2018–2019 Through 2021–2022
Table 2.

Bone-Stress Injury Rate per Athlete-Season in Pac-12 Cross-Country Runners, 2018–2019 Through 2021–2022

Bone-Stress Injury Rate per Athlete-Season in Pac-12 Cross-Country Runners, 2018–2019 Through 2021–2022
Bone-Stress Injury Rate per Athlete-Season in Pac-12 Cross-Country Runners, 2018–2019 Through 2021–2022
Table 3.

Bone-Stress Injury Rate in Pac-12 Cross-Country Runners by Season Segment, 2018–2019 Through 2021–2022, No. (%)

Bone-Stress Injury Rate in Pac-12 Cross-Country Runners by Season Segment, 2018–2019 Through 2021–2022, No. (%)
Bone-Stress Injury Rate in Pac-12 Cross-Country Runners by Season Segment, 2018–2019 Through 2021–2022, No. (%)

Of all the BSIs reported between 2018–2019 and 2021–2022, 72.6% (122 of 168) were classified as overuse-TL. The remainder were classified as acute-TL (12 of 168), acute-NTL (1 of 168), overuse-TL (15 of 168), or overuse-unspecified (18 of 168). The lower leg (40 of 168) and the foot (40 of 168) were the most common injury locations. The ankle (9 of 168), knee (6 of 168), and lumbar spine (1 of 168) were the least frequently involved. Male runners had a higher proportion of injuries located in the foot (31% of all BSIs in men), whereas female runners sustained more injuries in the lower leg (25% of all BSIs in women). Figure 2 illustrates BSI by sex, classification, and location.

Figure 2

Distribution of bone-stress injuries in Pac-12 cross-country runners by sex (men/women), 2018–2019 through 2021–2022. Injury counts indicated for both classification (acute-time-loss [TL], acute-non–time-loss [NTL], overuse-TL, overuse-NTL, or overuse-unspecified) and location (foot, lower leg, pelvis, thigh, groin/hip, ankle, knee, or lumbar spine). Red represents men’s injuries, and blue represents women’s injuries.

Figure 2

Distribution of bone-stress injuries in Pac-12 cross-country runners by sex (men/women), 2018–2019 through 2021–2022. Injury counts indicated for both classification (acute-time-loss [TL], acute-non–time-loss [NTL], overuse-TL, overuse-NTL, or overuse-unspecified) and location (foot, lower leg, pelvis, thigh, groin/hip, ankle, knee, or lumbar spine). Red represents men’s injuries, and blue represents women’s injuries.

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Associated health care use is reported in Table 4. A total of 1764 athletic training services were provided for these injuries, resulting in a mean of 10.50 services per BSI. Approximately 21% (36 cases) of all BSIs received no athletic training services. Most athletic training services (n = 1329) were associated with overuse-TL injuries. On a per-case basis, the mean athletic training services per BSI was slightly larger in overuse-NTL (12.20) than overuse-TL (10.89) injuries (Table 5). The presence of service use per BSI was lower for physician encounters (0.70), prescription medications (0.04), tests (0.75), procedures (0.01), and surgery (0.02) than for athletic training services.

Table 4.

Associated Health Care Use for Collegiate Cross-Country Runners With a Bone-Stress Injury, 2018–2019 Through 2021–2022

Associated Health Care Use for Collegiate Cross-Country Runners With a Bone-Stress Injury, 2018–2019 Through 2021–2022
Associated Health Care Use for Collegiate Cross-Country Runners With a Bone-Stress Injury, 2018–2019 Through 2021–2022
Table 5.

Mean Athletic Training Services per Bone-Stress Injury by Injury Classification

Mean Athletic Training Services per Bone-Stress Injury by Injury Classification
Mean Athletic Training Services per Bone-Stress Injury by Injury Classification

Results of the post hoc analysis completed with the 13 acute cases removed are provided in the Supplemental Table, available online at https://dx.doi.org/10.4085/1062-6050-0089.23.S1.

The purpose of our study was to describe the rate and location of BSI stratified by injury mechanism (acute versus overuse) and TL status, as well as the associated health care use for each BSI, in a sample of NCAA Division I cross-country runners. Bone-stress injuries occurred frequently and were commonly classified as overuse-TL injuries. Fewer injuries were classified as acute or resulted in no loss in participation. Athletic training services were frequently sought for management of this condition, but other health care resources were less frequently used.

In this sample, BSI represented 20% of all injuries reported over the 4-year observation period and occurred in approximately 14% of the total sample on average. This sample of collegiate cross-country runners from 1 athletic conference may not represent the entire collegiate population, but if the rate holds true across the NCAA, it would equate to nearly 4000 BSIs each year. This rate of injury is consistent with previous findings that cross-country runners were at high risk of BSI.18,19  In a study examining BSI rates across collegiate athletes, Bratsman et al found that cross-country runners across 3 NCAA divisions had a BSI injury rate of 73.8 per 100 000 AEs.19  Similarly, in a study examining risk factors associated with BSI at a single university, Tenforde et al found that the highest proportion of injured athletes participated in cross-country.18  We found that the rate of BSI was greater in female than male athletes and is consistent with the rate reported in the literature.8  Although we found that injury rates were higher in the 2019–2020 season, no data are currently collected in the HAP to indicate why this might be the case, as individual athletic training and competition exposures are not recorded. Future epidemiologic studies should be done to collect individual exposure characteristics to investigate reasons for year-to-year fluctuations in injury rate, as changes in training and competition volume may be reasons for this difference. We also found that a large proportion of injuries took place during the season, with more than half of all in-season BSIs (n = 47) occurring between days 29 and 84 (weeks 5 to 12). This finding of increased BSIs occurring after week 4 in the season is consistent with a previous finding of BSIs occurring several weeks after the initiation of a new training program or change in training intensity.29  A change in training intensity after the start of the season, the addition of competition, or both might increase the susceptibility to BSI development in this population. Considering the continued high rate of injury and the proportion of runners sustaining a BSI, further research is needed to identify risk factors associated with injury. Biomechanical factors, training, genetics, diet, and nutrition have been associated with BSI, but to date, no consensus exists on the weight of any specific factor, or combination of factors, in relation to the probability that a runner will sustain an injury.9,18  Identification of risk would help clinicians plan future prevention strategies and ultimately minimize the occurrence of BSI in this population.

Return to sport after BSI has been reported to take up to 6 to 27 weeks, and runners with BSI have a high risk of reinjury.8,9,13  To minimize future risk and ensure an efficient return to sport, adequate access to care and appropriate intervention are needed. We found that cross-country runners in the Pac-12 Conference received a mean of 10.50 athletic training services per BSI. This is the first study to report on athletic training services used for BSI in collegiate cross-country runners. Our findings indicate a high demand on ATs tasked with managing BSI in this sample of collegiate runners. Considering the prevention and treatment requirements for all athletes under their care, the ATs working with this sample of runners are spending an extended period with each athlete at approximately 11 athletic training services, or visits, per BSI. This value is considerably larger than that reported in other studies investigating athletic training service use in other populations. Using data from the Athletic Training Practice-Based Research Network, Marshall et al found that injured high school cross-country runners received approximately 7 athletic training services per injury.30  The number of visits reported by Marshall et al is also consistent with values reported for high school cross-country athletes in other studies in which daily patient encounters were investigated.23,30,31  Specifically, Lam et al found that athletes received a mean of 7.5 visits per injury across all sports, whereas another study by Lam et al showed that cross-country athletes had approximately 4 services per injury.23,31  One reason for this difference may be the type and classification of injuries between high school runners and this sample of collegiate runners. Most injuries in high school runners tended to be NLT (69.3%), and BSI only accounted for 4.7% of the total injury cases. However, when Marshall et al further investigated visits per diagnosis type, they still found that individuals with a BSI received only 3.8 ± 1.3 athletic training services over 2.8 ± 4.7 visits.30 

High school athletes may receive care for their BSIs outside of their school-based ATs, whereas collegiate athletes may seek treatment only from practitioners at their universities, and this may account for the differences. Pryor et al reported that <40% of high school athletic departments employed full-time ATs, often citing budgetary restrictions, hiring power, and misconceptions about the role of ATs in the high school setting as barriers to hiring.32,33  Limited access to an AT may result in high school athletes seeking care from outside providers, whereas collegiate athletes possibly have daily access to ATs because they are often provided by the university’s athletic department.33  Fewer visits may also reflect a less intensive course of care. High school athletes possibly have less access to care due to staffing issues previously mentioned or an increased demand on high school ATs with the management of NTL injuries, which results in a lower frequency of visits and less treatment provided.30,31  Even athletes with an overuse-NTL BSI in this sample received 12.2 athletic training services per injury, indicating a high need for treatment despite being able to continue sport participation. Regardless, collegiate cross-country runners with a diagnosis of BSI receive a considerable amount of athletic training services. Athletic trainers should expect to frequently see cross-country athletes with a BSI, and athletic departments at NCAA institutions should provide adequate staffing to support the athletic training needs of these individuals.

Use of other health care resources (physician encounters, prescription medications, tests, etc) was limited in comparison with the use of athletic training services. Specifically, physician encounters and tests were limited to a mean of <1 per BSI. This was surprising, as we expected that each BSI would be accompanied by at least 1 visit to the team physician and diagnostic imaging. Bone-stress injury is a general term encompassing both stress-reaction and stress-fracture diagnoses.21  Many researchers use imaging to confirm the presence of a BSI, and in many cases, this is needed to make a definitive diagnosis of stress reaction versus stress fracture.9,13,21,34  Although a suspected diagnosis of a low-risk stress fracture can be made based on history and clinical presentation, confirmation of a BSI with imaging, preferably magnetic resonance imaging (MRI) because of its high sensitivity and specificity, is recommended in the early management of this condition.34  Prognosis, including time frames for bone healing and return to sport participation, has been shown to be associated with MRI grading and should be considered in treatment planning for this population.9,13,21  The presence of BSI in this population could have been overrepresented or underrepresented based on the limited use of physician follow-up and ordering of diagnostic imaging. The grade of BSI could have affected the frequency of athletic training service use. Knowing the type of BSI may provide greater insight into the health care needs of athletes with a stress reaction or stress fracture. All cases associated with an OSICS code indicating a BSI were kept for analysis despite this limitation to determine rates and health care use associated with all runners classified as having a BSI. In future studies, researchers may consider including only athletes with confirmed BSIs in their analysis. In addition, clinicians working with cross-country runners with a history suggestive of BSI should consider follow-up with medical imaging to confirm the diagnosis and plan treatment.9,21,34,35  Other health care resources may also need to be considered in the management of these athletes. Presence of a BSI may indicate bone-density changes and underlying relative energy-deficiency syndrome and female or male athlete triad syndrome.8,18,36,37  Individuals with these conditions have been shown to be at greater risk for BSI and may be at greater risk for long-term bone-health issues.18,36  Clinicians working with individuals with BSI should consider a multidisciplinary approach to diagnosis and management to optimize outcomes.

This study had limitations. Data represented only cross-country athletes from 1 athletic conference and 168 BSIs. This sample may not be representative of the entire population of cross-country athletes, and the rate of BSI may be overrepresented or underrepresented. Injury rates were reported per AS based on an 86% participation rate and not as individual AEs. However, rates of BSI were similar to those found in other investigations of cross-country runners.2,19,30  As mentioned, not all cases of BSI were associated with diagnostic imaging. Lack of diagnostic imaging may indicate an overrepresentation of BSI. For this study, all cases associated with an OSICS code consistent with a BSI were kept for analysis to investigate health care use for cases treated as BSI. In addition, clinical presentation can be indicative of BSI, and imaging modalities other than MRI, such as plain-film radiographs, have a high false-negative rate and may delay diagnosis.9  We assumed that competing diagnoses were ruled out, but clinicians should consider obtaining MRI confirmation of suspected BSI. A total of 13 cases were associated with an acute mechanism of injury, which does not fit the classification commonly used to describe BSI.9  Although the number of cases was limited, the classification of acute injury may represent a lack of consistency in clinician documentation and adherence to surveillance program definitions.22,38  Athletes presenting with an onset of symptoms within the past 24 hours may have been classified as having an acute injury despite having no clear mechanism of injury. Current information provided by the HAP does not provide data to support this hypothesis, but an analysis completed with the removed 13 acute cases demonstrated similar findings when comparing rates between sexes and years (Supplemental Table). In future injury surveillance programs investigating BSI, researchers should ensure consistent use of injury definitions in addition to obtaining imaging confirmation for this specific diagnosis. Regarding athletic training services used in the management of BSI, we reported only on visits to the AT and not specific interventions used with each case. Therefore, treatment strategies associated with BSI and whether best practices were followed cannot be determined. Future epidemiology studies on health care use for BSI should be done to track treatment codes used in each case.

We examined the rate of BSIs in collegiate cross-country athletes and are the first to investigate associated health care use in this population. We found a high rate of overuse-TL BSIs in this population that required considerable health care resources. Specifically, the frequency of services provided by ATs was higher than that previously reported in other populations. The need for athletic training services in this population should be considered in the staffing and training of ATs working in collegiate athletic departments. Future research should be done to track treatment codes associated with BSI management to determine whether best-practice patterns are being followed. A suspected BSI should be followed up with diagnostic imaging to confirm diagnosis and grade of injury, and other members of the health care team should be consulted in the management of this condition.

1.
2021 Participation report
.
Physical Activity Council
. Accessed June 21, 2021. http://www.physicalactivitycouncil.com/
2.
Chandran
A,
Morris
SN,
Boltz
AJ,
Robison
HJ,
Collins
CL.
Epidemiology of injuries in National Collegiate Athletic Association women’s cross-country: 2014–2015 through 2018–2019
.
J Athl Train
.
2021
;
56
(
7
):
622
628
.
3.
NCAA sports sponsorship and participation rates report. 1956–57 through 2020–21
.
National Collegiate Athletic Association
. Published December 1, 2021. Revised January 1, 2022. Accessed July 29, 2022. https://ncaaorg.s3.amazonaws.com/research/sportpart/2021RES_SportsSponsorshipParticipationRatesReport.pdf
4.
2018–19 High school athletics participation survey.
National Federation of State High School Associations
. Accessed September 13, 2021. https://www.nfhs.org/media/1020412/2018-19_participation_survey.pdf
5.
Videbæk
S,
Bueno
AM,
Nielsen
RO,
Rasmussen
S.
Incidence of running-related injuries per 1000 h of running in different types of runners: a systematic review and meta-analysis
.
Sports Med
.
2015
;
45
(
7
):
1017
1026
.
6.
Chandran
A,
Morris
SN,
Boltz
AJ,
Robison
HJ,
Collins
CL.
Epidemiology of injuries in National Collegiate Athletic Association men’s cross-country: 2014–2015 through 2018–2019
.
J Athl Train
.
2021
;
56
(
7
):
629
635
.
7.
Rizzone
KH,
Ackerman
KE,
Roos
KG,
Dompier
TP,
Kerr
ZY.
The epidemiology of stress fractures in collegiate student-athletes, 2004–2005 through 2013–2014 academic years
.
J Athl Train
.
2017
;
52
(
10
):
966
975
.
8.
Tenforde
AS,
Kraus
E,
Fredericson
M.
Bone stress injuries in runners
.
Phys Med Rehabil Clin N Am
.
2016
;
27
(
1
):
139
149
.
9.
Warden
SJ,
Davis
IS,
Fredericson
M.
Management and prevention of bone stress injuries in long-distance runners
.
J Orthop Sports Phys Ther
.
2014
;
44
(
10
):
749
765
.
10.
Meardon
SA,
Derrick
TR,
Willson
JD,
et al.
Peak and per-step tibial bone stress during walking and running in female and male recreational runners
.
Am J Sports Med
.
2021
;
49
(
8
):
2227
2237
.
11.
Kelsey
JL,
Bachrach
LK,
Procter-Gray
E,
et al.
Risk factors for stress fracture among young female cross-country runners
.
Med Sci Sports Exerc
.
2007
;
39
(
9
):
1457
1463
.
12.
Bennell
KL,
Malcolm
SA,
Thomas
SA,
Wark
JD,
Brukner
PD.
The incidence and distribution of stress fractures in competitive track and field athletes: a twelve-month prospective study
.
Am J Sports Med
.
1996
;
24
(
2
):
211
217
.
13.
Miller
TL,
Jamieson
M,
Everson
S,
Siegel
C.
Expected time to return to athletic participation after stress fracture in Division I collegiate athletes
.
Sports Health
.
2018
;
10
(
4
):
340
344
.
14.
Davis
JJ IV,
Gruber
AH.
Injured runners do not replace lost running time with other physical activity
.
Med Sci Sports Exerc
.
2020
;
52
(
5
):
1163
1168
.
15.
Fokkema
T,
Hartgens
F,
Kluitenberg
B,
et al.
Reasons and predictors of discontinuation of running after a running program for novice runners
.
J Sci Med Sport
.
2019
;
22
(
1
):
106
111
.
16.
Rowe
GC,
Safdar
A,
Arany
Z.
Running forward: new frontiers in endurance exercise biology
.
Circulation
.
2014
;
129
(
7
):
798
810
.
17.
Oswald
F,
Campbell
J,
Williamson
C,
Richards
J,
Kelly
P.
A scoping review of the relationship between running and mental health
.
Int J Environ Res Public Health
.
2020
;
17
(
21
):
8059
.
18.
Tenforde
AS,
Carlson
JL,
Chang
A,
et al.
Association of the female athlete triad risk assessment stratification to the development of bone stress injuries in collegiate athletes
.
Am J Sports Med
.
2017
;
45
(
2
):
302
310
.
19.
Bratsman
A,
Wassef
A,
Wassef
CR,
Jayaram
P,
Mosely
JB,
Shybut
TB.
Epidemiology of NCAA bone stress injuries: a comparison of athletes in Divisions I, II, and III
.
Orthop J Sports Med
.
2021
;
9
(
7
):
23259671211014496
.
20.
Kerr
ZY,
Dompier
TP,
Snook
EM,
et al.
National Collegiate Athletic Association Injury Surveillance System: review of methods for 2004–2005 through 2013–2014 data collection
.
J Athl Train
.
2014
;
49
(
4
):
552
560
.
21.
Warden
SJ,
Hoenig
T,
Sventeckis
AM,
Ackerman
KE,
Tenforde
AS.
Not all bone overuse injuries are stress fractures: it is time for updated terminology
.
Br J Sports Med
.
2023
;
57
(
2
):
76
77
.
22.
Brown
CN,
Bovbjerg
VE,
Soucy
MT,
Choe
S,
Fredericson
M,
Simon
JE.
Acute and overuse, time-loss and non-time-loss lateral ankle sprains and health care utilization in collegiate student-athletes
.
J Sport Rehabil
.
2023
;
32
(
2
):
133
144
.
23.
Lam
KC,
Valier
AR,
Anderson
BE,
McLeod
TC.
Athletic training services during daily patient encounters: a report from the Athletic Training Practice-Based Research Network
.
J Athl Train
.
2016
;
51
(
6
):
435
441
.
24.
Bohr
AD,
Aukerman
DF,
Harmon
KG,
et al.
Pac-12 CARE-Affiliated Program: structure, methods and initial results
.
BMJ Open Sport Exerc Med
.
2021
;
7
(
2
):
e001055
.
25.
Robell
KC,
Norcross
MF,
Bohr
AD,
Harmon
KG.
Pac-12 Health Analytics Program (HAP): an innovative approach to health care operations, data analytics and clinical research in intercollegiate athletics
.
J Athl Train
.
2023
;
58
(
7–8
):
655
663
.
26.
Rae
K,
Orchard
J.
The Orchard Sports Injury Classification System (OSICS) version 10
.
Clin J Sport Med
.
2007
;
17
(
3
):
201
204
.
27.
Milgrom
C,
Zloczower
E,
Fleischmann
C,
et al.
Medial tibial stress fracture diagnosis and treatment guidelines
.
J Sci Med Sport
.
2021
;
24
(
6
):
526
530
.
28.
Roos
KG,
Marshall
SW.
Definition and usage of the term “overuse injury” in the US high school and collegiate sport epidemiology literature: a systematic review
.
Sports Med
.
2014
;
44
(
3
):
405
421
.
29.
Kardouni
JR,
McKinnon
CJ,
Taylor
KM,
Hughes
JM.
Timing of stress fractures in soldiers during the first 6 career months: a retrospective cohort study
.
J Athl Train
.
2021
;
56
(
12
):
1278
1284
.
30.
Marshall
AN,
Valovich McLeod
TC,
Lam
KC.
Characteristics of injuries occurring during cross-country: a report from the Athletic Training Practice-Based Research Network
.
J Athl Train
.
2020
;
55
(
12
):
1230
1238
.
31.
Lam
KC,
Snyder Valier
AR,
Valovich McLeod
TC.
Injury and treatment characteristics of sport-specific injuries sustained in interscholastic athletics: a report from the Athletic Training Practice-Based Research Network
.
Sports Health
.
2015
;
7
(
1
):
67
74
.
32.
Pryor
RR,
Casa
DJ,
Vandermark
LW,
et al.
Athletic training services in public secondary schools: a benchmark study
.
J Athl Train
.
2015
;
50
(
2
):
156
162
.
33.
Mazerolle
SM,
Raso
SR,
Pagnotta
KD,
Stearns
RL,
Casa
DJ.
Athletic directors’ barriers to hiring athletic trainers in high schools
.
J Athl Train
.
2015
;
50
(
10
):
1059
1068
.
34.
Wright
AA,
Hegedus
EJ,
Lenchik
L,
Kuhn
KJ,
Santiago
L,
Smoliga
JM.
Diagnostic accuracy of various imaging modalities for suspected lower extremity stress fractures: a systematic review with evidence-based recommendations for clinical practice
.
Am J Sports Med
.
2016
;
44
(
1
):
255
263
.
35.
Expert Panel on Musculoskeletal Imaging
;
Bencardino
JT,
Stone
TJ,
Roberts
CC,
et al.
ACR Appropriateness criteria stress (fatigue/insufficiency) fracture, including sacrum, excluding other vertebrae
.
J Am Coll Radiol
.
2017
;
14
(
5
):
S293
S306
.
36.
Mountjoy
M,
Sundgot-Borgen
J,
Burke
L,
et al.
International Olympic Committee (IOC) consensus statement on relative energy deficiency in sport (RED-S): 2018 update
.
Int J Sport Nutr Exerc Metab
.
2018
;
28
(
4
):
316
331
.
37.
Nattiv
A,
De Souza
MJ,
Koltun
KJ,
et al.
The male athlete triad—a consensus statement from the Female and Male Athlete Triad Coalition part 1: definition and scientific basis
.
Clin J Sport Med
.
2021
;
31
(
4
):
335
348
.
38.
Roos
KG,
Kucera
KL,
Golightly
YM,
Myers
JB,
Rosamond
WD,
Marshall
SW.
Variability in the identification and reporting of overuse injuries among sports injury surveillance data collectors
.
Athl Train Sports Health Care
.
2019
;
11
(
3
):
143
–146.

Supplemental Table. Bone-Stress Injuries Classified as Overuse by Season in Pac-12 Cross-Country Runners, 2018–2019 Through 2021–2022.

Found at DOI: https://dx.doi.org/10.4085/1062-6050-0089.23.S1

Supplementary data