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Musculoskeletal Injuries During U.S. Air Force Special Warfare Training Assessment and Selection, Fiscal Years 2019–2021.

Image of 01_Musculoskeletal Injuries. U.S. Air Force Capt. Hopkins, 351st Special Warfare Training Squadron, Instructor Flight commander and Chief Combat Rescue Officer (CRO) instructor, conducts a military free fall equipment jump from a DHC-4 Caribou aircraft in Coolidge, Arizona, July 17, 2021. Hopkins is recognized as the 2020 USAF Special Warfare Instructor Company Grade Officer of the Year for his outstanding achievement from January 1 to December 31, 2020.


From the inception of the Special Warfare Training Wing in fiscal year 2019 through 2021, 753 male, enlisted candidates attempted at least 1 Assessment and Selection and did not self-eliminate (i.e., quit). Candidates were on aver­age 23 years of age. During candidates’ first attempt, 356 (47.3%) individ­uals experienced a musculoskeletal (MSK) injury. Among the injuries, the most frequent type was nonspecific (n=334/356; 93.8%), and the most com­mon anatomic region of injury was the lower extremity (n=255/356; 71.6%). When included in a multivariable model, older age, slower run times on ini­tial fitness tests, and prior nonspecific injury were associated with both any injury and specifically lower extremity MSK injury.

What are the new findings?

During Assessment and Selection, 356 (47.3%) of candidates suffered an MSK injury. The most frequent type was nonspecific (n=334/356; 93.8%) and the most common anatomic region of injury was the lower extremity (n=255/356;
71.6%). Older age, slower run times, and prior nonspecific injury were associated with injury during the course.

What is the impact on readiness and force health protection?

MSK injuries are costly and continue to be the leading cause of medical visits and disability in the U.S. military and are more prevalent in the special operations community than in conventional military forces. Identifying predictors of injury in this population can inform clinicians and staff regarding the provision of prevention and rehabilitative strategies to reduce this risk.


Musculoskeletal (MSK) injuries are costly and the leading cause of medical visits and disability in the U.S. military.1,2 Within training envi­ronments, MSK injuries may lead to a loss of training, deferment to a future class, or voluntary disenrollment from a training pipeline, all of which are impediments to maintaining full levels of manpower and resources for the Department of Defense. Additionally, injuries sustained during training often lead to chronic conditions or impairments at a later time during a warf­ighter’s career.Previous studies have found that spe­cial operations forces experience higher MSK injury rates than conventional forces,4 and more so in training environ­ments.5 Although previous investigations have studied MSK injury rates in samples of Air Force (AF) special operators,4,6 to date, there are no studies that have explic­itly characterized the incidence of MSK injuries in the AF Special Warfare Training Wing (SWTW) pipeline. 

The AF SWTW was established in fis­cal year 2019 to assess, select, and train individuals to become one of 4 AF Special Warfare (AFSPECWAR) specialties: Tacti­cal Air Control Party (TACP), Pararescue, Combat Control, and Special Reconnais­sance. With the exception of TACP, each of these specialties require a candidate to successfully complete an arduous 16-day Assessment & Selection (A&S) course. Due to the nature of this assessment process, MSK injuries are common. However, no studies have reported the incidence of MSK injuries during A&S. Thus, the purpose of this study was to report the incidence of MSK injury during the 16-day SWTW A&S; and identify factors that were associ­ated with experiencing an MSK injury dur­ing this period.Methods

The cohort included enlisted AFSPEC­WAR candidates who first attempted A&S during fiscal years 2019–2021 and did not voluntarily disenroll (i.e., quit). Officer candidates were excluded from the analysis due to differences in their previous train­ing prior to A&S. Female candidates were excluded due to the small number of candi­dates (n=5), which precluded comparisons by sex. Data for analysis were routinely collected throughout the pipeline lead­ing up to the start of A&S (Figure 1). The Armed Services Vocational Aptitude Bat­tery (ASVAB)7 was administered before the candidates entered Basic Military Training (BMT). Results from baseline fitness tests and body composition factors were col­lected at the start of the Special Warfare Candidate Course (SWCC). The Intelli­gence Quotient (IQ) test was administered at the start of A&S. 

Data regarding MSK injuries were extracted from the Military Health System (MHS) Management Analysis and Report­ing Tool. The Click to closeDirect CareDirect care refers to military hospitals and clinics, also known as “military treatment facilities” and “MTFs.”direct care outpatient system was searched for encounters within the stated timeframes for the cohort. The 10th Revision of the International Classification of Disease (Clinical Modification) codes were categorized according to a matrix that assigned an injury type and region to each injury using a taxonomy adapted from a previously published work.3,8 Briefly, the matrix broadened the inclusion of non-specific, overuse, and other MSK condi­tions that can also impact completion of training. For the coding of prior MSK injury, the timeframe of 6-months prior to starting A&S was selected to align with the timeframe of a candidate entering BMT, at which point relevant healthcare records are collected within the MHS.Covariates were selected for analysis based on 2 specific rationales; (1) explan­atory covariates including baseline fitness, body composition, and prior injury status that are known from the literature to have an association with risk of injury, and (2) exploratory covariates including anthro­pometric measurements, cognitive factors, and age that are routinely collected by the SWTW and discussed internally as poten­tially related to injury risk.

The injury surveillance period included the 16-day course as well as an additional 7 days following course termination, when students were permitted to rest with little to no formal training conducted. The sur­veillance period was extended in this way because many candidates will not report their injuries until the training concludes. In addition, providers are often unable to document injuries in the electronic medi­cal record system until the course finishes. Chi-square tests and independent samples t-tests were used for bivariate testing of cat­egorical and continuous factors, respec­tively, for differences between candidates with and without MSK injury during A&S. Where appropriate, the Mann-Whitney U, and Fisher’s exact tests were also employed. Binary logistic regression was used to build multivariable models to identify factors associated with MSK injury during A&S. In addition, binary logistic regression was also employed to identify factors associ­ated with lower extremity MSK injury specifically, the most common anatomic site of injury. For multivariable modeling, complete-case analysis was employed. The TRIPOD checklist was followed for model development only (i.e., not validation).9

The presented final binary logistic regres­sion models were exploratory in nature and future validation will be necessary. SAS ver­sion 9.4 (SAS Institute, Cary, NC) was used for all statistical analyses. Odds ratios (ORs) adjusted ORs (AORs), and their associated confidence intervals (CI) are reported with a threshold of p<.05 for univariate signifi­cance and a threshold of p<.10 was used to determine retention of variables in the logistic regression models. The final logistic regression model was selected that obtained optimal goodness of fit and area under the receiver operating curve.


Overall, 753 male enlisted candidates attempted A&S at least once and did not self-eliminate during fiscal years 2019 (4 classes), 2020 (5 classes), or 2021 (6 classes) (Figure 2). Candidates were, on average, 23 years of age at the start of their first A&S attempt. During candidates’ first A&S attempt, 356 (47.3%) experienced an MSK injury; of those can­didates, the most frequent injury type was nonspecific (n=334/356; 93.8%) (Figure 3), and the most common anatomic region of injury was the lower extremity (n=255/356; 71.6%) (Figure 4). 

Any type of MSK injury

Bivariate analyses revealed that initial fitness, age, BMI, and prior MSK injury were statistically significantly associated with injury during candidates' first A&S attempt (Table 1). The only baseline fit­ness measure significantly associated with injury during A&S was slower 1.5 mile run times. Body fat mass, lean body mass, dry lean mass, percent body fat, and skeletal muscle mass, were not significantly higher for candidates who were injured, compared with those who were not injured. Slightly more than one-half of the candidates (n=393; 52.2%) had suffered any prior MSK injury type, and a significant proportion of these candidates also suffered injury during A&S (64.0% vs 41.6%; p<.001). More spe­cifically, prior nonspecific, nerve, sprain or joint damage, strain or tear, and systemic or genetic MSK conditions were all associated with a higher frequency of injury during A&S. Injuries that occurred at all anatomic sites other than the torso were associated with a higher frequency of any type of injury during A&S.

The average age of candidates injured during A&S was significantly higher (24.2 years, SD=4.1) compared with those who were not injured (23.0 years, SD=3.8). Other tested cognitive factors, including highest academic level, overall IQ, and ASVAB test scores were not significantly associated with injury during A&S in bivar­iate analyses.Multivariable analysis

In an adjusted binary logistic regres­sion model, factors that were retained as associated with injury during A&S included age at A&S start (AOR=1.09; 95% CI: 1.04–1.14; p<.001), 1.5 mile run time on initial fitness test (AOR=1.53; 95% CI: 1.15–2.05; p=.004), and prior nonspe­cific injury (AOR=2.25; 95% CI: 1.64–3.10; p<.001) (Table 2). 
In an adjusted  model, factors that were retained as associated with lower extrem­ity injury during A&S included age at A&S start (AOR=1.05; 95% CI: 1.01–1.10; p=.018), 1.5 mile run time on initial fitness test (AOR=1.41; 95% CI: 1.05–1.90; p=.023), and prior nonspecific injury (AOR=1.91; 95% CI: 1.37–2.67; p<.001) (Table 3).

Editorial Comment

The purpose of this study was to report the incidence of MSK injuries in a 16-day rigorous SWTW A&S, and to identify fac­tors associated with suffering an MSK injury. This is the first characterization of MSK injury in a SWTW A&S population, finding 47.3% of candidates suffered an MSK injury, with the most frequent type as nonspecific (93.8%; of those injured). Knapik et al pre­viously described medical encounters dur­ing a U.S. Army Special Forces A&S course, reporting 38% of the candidates experi­enced one or more injuries during the 19-20 day period.10 The high percentage of injury among both cohorts is an indication of the rigorous requirements incurred by trainees in short periods of times under extremely challenging circumstances.

The lower extremity was identified as the most common anatomic region of injury during A&S (71.6%; of those injured). This finding is consistent with Lovalekar et al, who also reported lower extremity MSK injury as the most common region in Navy Sea, Air, and Land (SEAL) Qualification Training Students.11 However, both find­ings should be interpreted with caution, as these values may be underestimates due to potential under-reporting.12

When put into a multivariable model, older age, slower run times on initial fitness tests and prior nonspecific injury increased the likelihood of any musculoskeletal injury and, more specifically, lower extremity MSK injury. Although BMI was significant on the univariate analysis, the variable did not meet the criteria for retention in the final adjusted model. These findings are similar to previ­ous studies of similar populations that have found low levels of physical fitness, slower run time or history of a previous injury13–15 were all associated with sustaining MSK injury. Age, poor muscular endurance, and slower run times have also been observed to be reliable indicators of future acute injuries in U.S. Army Infantry, Armor, and Cavalry basic trainees during initial entry training (IET),16 but only performance deficits in running tests were correlated with ‘overuse’ MSK injuries in their cohort. Several addi­tional observations of military IET samples have reported similarities in MSK injury risk associated with poor aerobic capacity test performances, which does indicate a distinct and historical association between aerobic fitness and MSK incidence early in military service.17–19 

A novel aspect of this manuscript ana­lyzed IQ and ASVAB scores for association with MSK injury. These potential covari­ates were selected a priori based on litera­ture demonstrating relationships between neurocognition, biomechanics20 and early screening21 to detect MSK injury. Addi­tionally, literature documents components of ASVAB scores as a reliable predictor for graduation in an Army course,22 supporting the current study hypothesis to investigate an association between ASVAB scores and MSK injury during A&S. However, no sig­nificant relationship was found for either IQ or ASVAB scores.

There are inherent limitations to the collected data and analysis. First, this work is retrospective, and as such is subject to selec­tion bias. Additionally, there was no delin­eation between injuries and training loss for the candidates, and therefore the results should be interpreted with caution. Also, the vast majority of candidates who voluntarily disenrolled during A&S did so within the first 2 days of A&S (internal data), and since this would potentially significantly impact the injury exposure, these candidates were excluded from analysis. However, as some of these candidates may have disenrolled due to an unspecified injury, this would impact the findings of this study.

Finally, all candidates were cleared med­ically to transition from BMT to SWCC, and again from SWCC to A&S. It is assumed at the start of SWCC and A&S that MSK inju­ries have been resolved, and candidates have a ‘clean bill of health’. However, due to the inherent nature of MSK injuries, challenges with diagnosis, and candidates’ propen­sity to not report injuries that could delay the completion of their training, it is pos­sible that some MSK injuries prior to A&S are indistinguishable from new injuries dur­ing A&S. Regardless, increased surveillance of candidates who had prior injuries is still warranted for injury prevention during A&S whether they are new or persistent. Future work is planned to examine the detailed timing and severity of MSK injuries, as well as elimination rates and types, throughout the training pipeline.

In conclusion, MSK injuries continue to be costly and the leading cause of medi­cal visits and disability in the U.S. military and are more prevalent in the special opera­tions community than in conventional mili­tary forces. To increase the readiness and longevity of operators, continued efforts are required to reduce MSK injury risk. The findings from this project highlight the increased risk of MSK injury in this popu­lation and provide further evidence for the scientific community to continue to develop appropriate prevention, screening, and reha­bilitative strategies to reduce that risk and increase the health and readiness of mem­bers in the Special Warfare community.

Author Affiliations

Special Warfare Human Performance Squadron, Lackland Air Force Base, San Antonio TX.


 The views expressed are solely those of the authors and do not reflect the official policy or position of the U.S. Army, U.S. Navy, U.S. Air Force, the Department of Defense, or the U.S. Government.


The authors acknowl­edge Dr. William C Scott PhD for his contri­butions in data retrieval and management.


  1. Grimm PD, Mauntel TC, Potter BK. Combat and noncombat musculoskeletal injuries in the US military. Sports Med Arthrosc. 2019;27(3):84–91.
  2. Teyhen DS, Shaffer SW, Goffar SL, et al. Identi­fication of risk factors prospectively associated with musculoskeletal injury in a warrior athlete popula­tion. Sports Health. 2020;12(6):564–572.
  3. Molloy JM, Pendergrass TL, Lee IE, Chervak MC, Hauret KG, Rhon DI. Musculoskeletal injuries and United States Army readiness Part I: over­view of injuries and their strategic impact. Mil Med. 2020;185(9-10):e1461–e1471.
  4. Warha D, Webb T, Wells T. Illness and injury risk and healthcare utilization, United States Air Force battlefield airmen and security forces, 2000-2005. Mil Med. 2009;174(9):892–898.
  5. Stannard J, Fortington L. Musculoskeletal inju­ry in military Special Operations Forces: a system­atic review. BMJ Mil Health. 2021;167(4):255–265.
  6. Lovalekar M, Johnson CD, Eagle S, et al. Epi­demiology of musculoskeletal injuries among US Air Force Special Tactics Operators: an economic cost perspective. BMJ Open Sport Exerc Med. 2018;4(1): e000471.
  7. Cudeck R. A structural comparison of conven­tional and adaptive versions of the ASVAB. Multi­variate Behav Res. 1985;20(3):305–322.
  8. Hauschild V, Hauret K, Richardson M, Jones BH, Lee T. A Taxonomy of Injuries for Public Health Monitoring and Reporting. Army Public Health Command. 2018.
  9. Collins GS, Reitsma JB, Altman DG, Moons KGM. Transparent reporting of a multivariable prediction model for individual prognosis or diag­nosis (TRIPOD): the TRIPOD statement. BJOG. 2015;122(3):434–443.
  10. Knapik JJ, Farina EK, Ramirez CB, Pasiakos SM, McClung JP, Lieberman HR. Medical encoun­ters during the United States Army Special Forc­es Assessment and Selection Course. Mil Med. 2019;184(7-8):e337–e343.
  11. Lovalekar M, Perlsweig KA, Keenan KA, et al. Epidemiology of musculoskeletal injuries sustained by Naval Special Forces Operators and students. J Sci Med Sport. 2017;20 Suppl 4:S51–S56.
  12. Hotaling B, Theiss J, Cohen B, Wilburn K, Emberton J, Westrick R. Self-reported musculo­skeletal injury healthcare-seeking behaviors in US Air Force Special Warfare personnel. J Spec Oper Med. 2021;21(3):72–77.
  13. Kaufman KR, Brodine S, Shaffer R. Military training-related injuries: surveillance, research, and prevention. Am J Prev Med. 2000;18(3 Sup­pl):54–63.
  14. Shwayhat AF, Linenger JM, Hofherr LK, Sly­men DJ, Johnson CW. Profiles of exercise history and overuse injuries among United States Navy Sea, Air, and Land (SEAL) recruits. Am J Sports Med. 1994;22(6):835–840.
  15. Teyhen DS, Shaffer SW, Butler RJ, et al. What risk factors are associated with musculoskeletal in­jury in US Army Rangers? A Prospective prognostic study. Clin Orthop Relat Res. 2015;473(9):2948–2958.
  16. Sefton JM, Lohse KR, McAdam JS. Predic­tion of injuries and injury types in Army basic training, infantry, armor, and cavalry trainees Using a Common Fitness Screen. J Athl Train. 2016;51(11):849–857.
  17. Psaila M, Ranson C. Risk factors for lower leg, ankle and foot injuries during basic military train­ing in the Maltese Armed Forces. Phys Ther Sport. 2017;24:7–12.
  18. Wentz L, Liu PY, Haymes E, Ilich JZ. Females have a greater incidence of stress fractures than males in both military and athletic populations: a systemic review. Mil Med. 2011;176(4):420–430.
  19. Knapik J, Ang P, Reynolds K, Jones B. Physi­cal fitness, age, and injury incidence in infantry sol­diers. J Occup Med. 1993;35(6):598–603.
  20. Porter Ke’la, Quintana C, Hoch M. The relation­ship between neurocognitive function and biome­chanics: a critically appraised topic. J Sport Reha­bil. 2020;30(2):327–332.
  21. Berg Rice VJ, Connolly VL, Pritchard A, Bergeron A, Mays MZ. Effectiveness of a screen­ing tool to detect injuries during Army Health Care Specialist training. Work. 2007;29(3):177–188.
  22. Grant J, Vargas AL, Holcek RA, Watson CH, Grant JA, Kim FS. Is the ASVAB ST composite score a reliable predictor of first-attempt gradu­ation for the U.S. Army operating room specialist course? Mil Med. 2012;177(11):1352–1358.


FIGURE 1. Schematic of training pipeline through Assessment and Selection, and time points of data collection for analysis

 Candidate inclusion and exclusion criteria for analysis


Frequency of musculoskeletal injuries by type, fiscal years 2019–2021


Frequency of musculoskeletal injury by anatomic site, fiscal years 2019–2021

Baseline demographic, fitness, and cognitive factors, by musculoskeletal status, fiscal years 2019–2021

Multivariable assessment of predictors of any musculoskeletal injury during Assessment and Selection (n=665)

Multivariable assessment of predictors of lower extremity musculoskeletal injury during Assessment and Selection (n=665)

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Last Updated: November 02, 2022
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