Musculoskeletal injury (MSK-I) remains a significant health problem for all active populations (24,37,43) despite it being mostly preventable through primary and secondary prevention strategies. Improving physical fitness, including cardiorespiratory endurance, muscular strength, muscular endurance, and flexibility, power, speed, balance, and agility, shows promise in the ability to affect high rates of MSK-I (1,27,34,40). However, current evidence regarding the relationships among MSK-I and specific components of physical fitness in military and athletic populations is mixed (1,21,22,27,29,32,34,40).
To effectively prevent MSK-I, specific modifiable risk factors must first be understood, and then targeted. Injury prevention programs commonly include exercises that focus on flexibility, power, speed, balance, and agility, and when properly conducted and adhered to, have been shown to reduce injury (35,41,42). However, the ability of such measures to predict risk has yet to be firmly established.
The Consortium for Health and Military Performance conducted a systematic review to evaluate existing scientific literature regarding the association between physical fitness components and MSK-I in military and civilian athletic populations. Although the review was conducted in support of the US Army Training and Doctrine Command’s initiative to develop and validate baseline physical performance assessments for all US Army Soldiers, independent of age and sex, the results should be useful for civilian communities as well. This article is the last in a 3-part series written from this review. In parts 1 and 2 of our series, we focused on cardiorespiratory endurance (31) and muscular strength and endurance (8). Here, the authors review the literature on the relationship of MSK-I in military and active civilian populations to several remaining components of fitness: flexibility, power, speed, balance, and agility.
Experimental Approach to the Problem
After the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (see checklist, Supplemental Digital Content 1, https://links.lww.com/JSCR/A66), we conducted a systematic review of the research literature to evaluate published, peer-reviewed studies, and military technical reports examining the association between components of physical fitness and the risk of sustaining an MSK-I in a military or civilian population between the ages of 18 and 65 (see PRISMA flow diagram, Supplemental Digital Content 2, https://links.lww.com/JSCR/A67). In consultation with a research librarian, the following databases were searched for relevant articles published from 1970 to December 2015: MEDLINE, EBSCO, EMBASE, and the Defense Technical Information Center. A combination of the following search items was used to capture all relevant studies: “injury”, “musculoskeletal diseases,” “musculoskeletal injury,” “sprain,” “strain,” “fracture,” “athletic injury,” “dislocation,” “tendonitis,” “bursitis,” “fasciitis,” “joints,” “risk assessment,” “injury prevention,” “attrition,” “physical fitness,” “exertion,” “physical endurance,” “physical education,” “training,” “exercise intervention,” “physical exercise,” “flexibility,” “muscular strength,” “muscular endurance,” “muscular power,” “aerobic fitness,” “aerobic capacity,” “aerobic power,” “anaerobic fitness,” “anaerobic capacity,” “anaerobic power,” “speed,” “balance,” “agility,” “maximal oxygen consumption,” “maximum oxygen consumption,” “Vo2 Max,” “Vo2 Peak,” “military personnel,” “emergency medical technician,” “athletes,” “dancer,” “emergency responder,” “police,” “firefighter,” “soldier,” “army,” and “navy.” The search was last performed in February 2016. This brief review was approved by Towson University.
Study Inclusion/Exclusion Criteria
Included articles met the following criteria: original research; full-text available; populations aged 18–65; reported measures of physical fitness; study outcomes included acute/traumatic (e.g., dislocation, fracture, sprain/strain, etc.) or overuse (e.g., stress fractures, tendonitis, bursitis, etc.) MSK-I (36); and a reported measure of association with injury (e.g., odds, hazard, risk or rate ratio). Musculoskeletal injury was defined as an event that resulted in damage to the musculoskeletal system for which the subject visited a medical care provider or went to the emergency room (28). Publications were excluded if (a) injury data reported were related to heat or cold injuries, animal bites, or other nonmusculoskeletal MSK-I; (b) injury data were self-report in nature; (c) study populations were composed of children, elderly, or adults with ill health or physically/mentally disabled; or (d) studies were systematic reviews, literature reviews, case studies, or case series in design.
Data extraction was split among the study investigators, with articles evenly divided among the authors. Relevant data were independently extracted using a standardized set of abbreviations and reporting methods and finally compiled in a single database. Data abstraction categories included population characteristics: MSK-I type and assessment, fitness components measured, fitness measurement tests, statistical analysis performed, and the reported odds, risk, or hazard ratios of injury with and without adjustments.
Methodological Quality Assessment
Each study was assessed for methodological quality using one of 2 modified assessments from Bullock et al. (5) (see quality assessments, Supplemental Digital Content 3, https://links.lww.com/JSCR/A68). The assessment tools were composed of 3 sections: (a) problem (1 item); (b) study design and methodology (6 items); and (c) data presentation and statistical analysis (4 items). Each question was scored from 0 to 2, with a maximum total score of 22. After initial scoring, the investigators met to compare scores and a discussion ensued (in cases of disagreement) until consensus was reached.
As all studies received maximum points for clearly identifying the research problem, scores were converted to a 20-point scale and expressed as a percentage. Studies were then ranked according to their methodological quality based on percentage of total possible points, resulting in the following groups: (a) poor (below 70th percentile: ≤13.5 points); (b) fair (70–79th percentile: 14–15.5 points); (c) good (80–89th percentile: 16–17.5 points); or (d) excellent (90th percentile and above: >18 points).
Assessment of Evidence Summary—Strength of the Evidence
Studies that found significant crude or adjusted associations between measures of flexibility, power, speed, balance, and agility were distinguished from those that did not with symbols representing the level and direction of association. Significant associations between low levels of flexibility, power, speed, balance, and agility (less fit), and elevated MSK-I risk with univariate and multivariate analyses were denoted by the symbols “+” and “++,” respectively, whereas associations between high levels of flexibility, power, speed, balance, and agility (more fit), and elevated MSK-I risk were noted with “→” and “→ →”. Next, the overall strength of the evidence was compiled and rated after criteria adapted from previous systematic reviews (5,6,19). The level of evidence for the relationship between flexibility, power, speed, balance, and agility, and MSK-I was ultimately determined to be as follows:
- Strong: three studies of at least good methodological quality or at least 2 studies of excellent methodology with consistent multivariate findings
- Moderate: consistent results from 2 studies of good methodology or one study of excellent methodology with multivariate findings
- Limited: one study of good or fair methodological quality with multivariate findings and multiple studies of good methodology with univariate findings
- Insufficient: results from studies of exclusively poor methodology and no evidence from multivariate analyses in excellent quality studies
The database search yielded 4,229 articles. In addition, 5 potential articles were identified from a manual search and subject matter expert recommendations. After duplicates were removed, the 3,321 remaining articles were divided alphabetically into 4 groups (one group per author). The titles and abstracts were reviewed for inclusion or exclusion, and full-text articles were retrieved if exclusion could not be determined by title and abstract alone, or if the article passed the first eligibility screening. After preliminary review for inclusion, 234 full-text articles were reviewed for associations between MSK-I and one or more fitness components. Ultimately, 27 articles met final inclusion criteria for this systematic review and reported the association between MSK-I and flexibility, power, speed, balance, or agility in military or athletic populations. The primary reasons for exclusion were (a) no objective assessment of fitness; (b) outcome data not specific to MSK-I; and (c) statistical analyses did not include measures of association, such as odds, hazard, or risk ratios.
Characteristics of Included Studies
Sixteen of the 27 studies (59.3%) investigated the association between MSK-I and fitness (flexibility, power, speed, and balance) in athletic populations, 9 (33.3%) were composed of military cohorts, and one each (3.7%) was composed of Federal Bureau of Investigation trainees or foreign physical education students. Of the 16 studies composed of athletic populations, 5 included collegiate athletes, 3 each were composed of Australian football or professional soccer players, 2 each included Australian rugby or professional hockey players, and one study included male volleyball players. Five of the 9 military studies were composed of basic training populations. Of the 27 studies, 25 (92.5%) used a prospective cohort study design, and one each used a retrospective cohort or nonrandomized control study design. Nineteen studies (70.4%) included only male participants, 2 (7.4%) were limited to female participants, and 6 (22.2%) studies included both male and female participants.
Twelve of the 27 articles (44.4%) examined multiple components within the same study. The most commonly investigated components in order were flexibility (18 studies; 67.7%), power (11 studies; 40.7%), speed, and balance (5 studies each; 18.5%). Our search did not yield any studies that investigated the association between agility and MSK-I and met our inclusion criteria.
Musculoskeletal Definitions and Injury Ascertainment
Most studies (15 of 27; 55.6%) used a broad definition of MSK-I and reported “acute/traumatic” and/or “overuse” injury as their outcome variable. Eleven studies (40.7%) specified a particular anatomical site and/or injury of interest, including ankle injuries (n = 4), hamstring (n = 4), or hip adductor/groin strains (n = 2), and Achilles tendon overuse injury (n = 1). Last, one study investigated “contact injury” in Australian professional rugby players. Injury data were obtained directly from health care professionals responsible for the medical care of the athletic teams or military members in 20 studies (74.1%), whereas 6 studies (22.2%) obtained injury data from review of medical records and/or electronic administrative clinical encounter databases. One study obtained injury data using uniform injury-reporting forms filled out by the coaching staff.
Four studies were categorized as “excellent,” 14 were classified as “good,” 8 were categorized as “fair,” and one had “poor” methodological quality. The mean quality score ± SD of the studies was 16.1 ± 1.6, ranging from 14 to 19. Strengths of most studies were noted in the 4 items categorized in the data presentation and statistical analysis section. By contrast, weaknesses of some studies were noted in the study design and methodology category. The most common items receiving either partial or no credit in order were (a) failure to state whether a power analysis was conducted, (a) inadequate description of the source of subjects including inclusion and exclusion criteria, and (c) insufficient inclusion of relevant confounders in the data collection. Table 1 provides a summary of the study characteristics, quality ratings and scores, and outcomes and directions of associations for all studies of “excellent” and “good” methodological quality that investigated the association between flexibility and MSK-I. Table 2 presents these results for all studies of “excellent” and “good” methodological quality that investigated the association between MSK-I and power, speed, and balance. Supplemental Digital Content 4 (see Table, https://links.lww.com/JSCR/A69) presents results for all studies of “fair” and “poor” methodological quality that investigated the association between flexibility and MSK-I while Supplemental Digital Content 5 (see Table, https://links.lww.com/JSCR/A70) presents these results for studies that examined the association between MSK-I and power, speed, and balance. Studies were grouped into tables by physical fitness measures; therefore, studies that investigated the association between several measures of fitness and MSK-I are listed more than once.
Evidence Summary—Strength of Evidence
Hip and Quadriceps Flexibility
Seven studies investigated the association between hip or quadriceps flexibility and MSK-I in athletic populations (2,9,11,12,25,48,50), 2 of which were composed of women only (25,50). Assessments of hip flexibility consisted primarily of active range of motion measured with goniometry in any of the 6 possible directions for the hip (2,9,11,12,25,48,50), whereas quadriceps (namely rectus femoris) flexibility was assessed with either the modified (11,12) or standard Thomas test (2,48). One additional study used a prone knee flexion measure to assess quadriceps flexibility (2). In one study of good methodological quality, greater quadriceps flexibility, as determined by a modified Thomas test, was found to be an independent risk factor for hamstring injury occurrence in Australian rules football players; players with greater flexibility were 70% less likely to suffer a hamstring injury than those with poor flexibility (12). An additional study of good methodological quality reported a significant univariate association between active hip extension asymmetry (right-to-left, >15%) and MSK-I in female collegiate athletes (25). Overall, the evidence supporting the association between hip and/or quadriceps flexibility and MSK-I is limited.
Ten studies investigated the association between hamstring flexibility and MSK-I; of these, 6 included athletic populations (2,11,12,20,25,52), whereas 4 were composed of military cohorts (4,7,28,38) and 3 of which were basic training populations (4,7,28). Four studies specifically looked at hamstring injury risk (11,12,20,52), whereas the remaining 6 studies used any acute/traumatic or overuse injury as their outcome of interest (2,4,7,25,28,38). Assessments of hamstring flexibility included a sit-and-reach test (6 studies) (4,7,11,12,28,38), active (2 studies) (11,12) or passive knee extension (1 study) (2), and active (2 studies) (20,25) or passive (3 studies) (12,20,52) straight leg raise (SLR) tests. One study of good methodological quality reported a multivariate association between performance on a sit-and-reach test and incidence of MSK-I in male US Army basic trainees; recruits with the highest and lowest hamstring flexibility were 2.9 and 3.3 times more likely to suffer a hamstring injury compared with those with average flexibility (7). Another study of good methodological quality reported that poor hamstring flexibility, as determined performance on a SLR test measured with a goniometer, was an independent risk factor for hamstring injury in English professional soccer players; athletes with lower flexibility had roughly a 30% greater risk of injury than those with higher flexibility measurements (20). Finally, an additional study of good methodological quality reported a univariate association between poor hamstring flexibility and elevated MSK-I risk in male but not female US Army basic trainees (28). Collectively, there is moderate evidence supporting the association between hamstring flexibility and MSK-I risk, although the exact direction of the association cannot be stated.
Eight studies investigated the association between ankle flexibility and MSK-I. Five of the 8 studies were composed of athletic populations (10–12,18,25), 2 were military cohorts (33,45), and one included college physical education students (50). The most commonly performed ankle flexibility assessment was non–weight-bearing active dorsiflexion (DF) (5 studies) (10,18,25,33,50) and plantarflexion (PF) (4 studies) (10,18,33,50) measured with a goniometer. One of these studies (33) obtained both DF and PF measurements with the knee in 2 positions, 45° of flexion and extended, while another measured DF in both knee positions and included a measurement of subtalar inversion and eversion (50). Three additional studies used a weight-bearing measure of DF, which was obtained during a forward lunge (11,12,45). Injury outcomes for these studies included ankle sprains (3 studies) (10,18,50), hamstring injury (2 studies) (11,12), Achilles tendon overuse injury (1 study) (33), and any MSK-I (2 studies) (25,45). One study of excellent methodological quality reported a multivariate association between ankle DF asymmetry and incidence of MSK-I in male US Army Rangers; Rangers with asymmetry ≥6.5° were 4.0 and 5.1 times more likely to suffer any and overuse MSK-Is, respectively, than those without asymmetry (45). Another study of good methodological quality reported that increased passive DF ROM was an independent risk factor for overuse Achilles tendon injuries; Belgian Army basic trainees with increased DF ROM were 1.2 times more likely to suffer an injury than those with less ROM (33). Overall, there is moderate evidence supporting the association between ankle flexibility and MSK-I risk, although the exact direction of the association cannot be stated.
Other Measures of Flexibility
Three studies investigated additional measures of flexibility not previously discussed, including lumbar spine extension ROM from standing (12), metatarsal phalangeal joint flexion and extension ROM (50), and the TIGHT score (30), which assessed overall muscle tightness by combining measures of flexibility for the iliopsoas, iliotibial band, hamstring, rectus femoris, and gastroc-soleus muscles. In one study of fair methodological quality, collegiate athletes with a higher TIGHT score, which signified greater muscular tightness, were 1.2 times more likely to suffer a MSK-I that those with lower scores (30). Based on this study alone, the evidence supporting the association between other measures of flexibility and MSK-I is limited.
Eleven studies investigated the association between power and MSK-I (2,13–15,17,20,28,33,39,44,45). Five of the 11 studies were conducted in military populations (28,33,39,44,45), with 3 during basic training (28,33,39). The most commonly performed power assessment was the countermovement vertical jump (CMJ) (6 studies) (2,13,14,17,20,28); other assessments of lower body power included the standing broad jump (3 studies) (33,39,44), vertical jump without countermovement (2 studies) (2,20), weighted jump squat (2 studies) (14,15), single-leg CMJ (2), weighted squat (2), and triple cross-over hop for distance (45) (1 study each). Upper body power assessments included the bench press throw (14) and seated shot (39) put (1 study each) while total body power was assessed with the Olympic clean (17) and power clean (14) (1 study each). Two studies of good methodological quality reported that lower body power, as measured by a standing broad jump or vertical jump with no countermovement, was an independent risk factor for injury when considered in the multivariate models (20,44). Finnish conscripts with shorter standing broad jump distances were 2.8 and 1.8 times more likely to suffer severe acute and overuse injuries, respectively, than those with longer jump distances (44). By contrast, professional soccer players who jumped higher during a vertical jump with no countermovement test were 1.5 times more likely to suffer a hamstring injury than those with lower jump heights (20). Collectively, moderate evidence supports the association between lower body power and MSK-I risk, although the exact direction of the association cannot be stated.
Five studies investigated the association between speed and risk of MSK-I (13–15,26,49); only one study included women (26) or was comprised of a military population (49). Speed assessments included sprints of varying length—from 10 to 300 m. In one study of excellent methodological quality, slower sprint speeds on 10- and 40-m sprints were both found to be independent risk factors for MSK-I in Australian rugby players; athletes with low 10- and 40-m speeds were 10.3 and 9.9 times more likely to be injured than those with faster speeds (13). Similarly, a study of good methodological quality reported a multivariate association between slower speed on a 300-m sprint and incidence of injury in male FBI trainees and a univariate association in female trainees (26). Consequently, there is moderate evidence that slower sprint speed is associated with increased MSK-I risk.
Five studies investigated the association between balance and MSK-I, with 2 each composed of athletic (18,47) or military populations (39,45) and one collegiate physical education students (50). Three studies investigated ankle sprains as their sole injury outcome (18,47,50). Two studies used instrumented measures of balance (i.e., stability limits as assessed by the Neurocom Balance Master or force plate measures) (18,50), whereas 3 others used clinical assessments, such as the single-leg balance test (39,47), which measured static balance, and the Y-balance test (45), an assessment of dynamic balance. One study of excellent methodological quality reported a multivariate association between single-leg balance test performance and incidence of ankle sprains in male and female collegiate athletes; athletes who failed the test, as determined by an inability to maintain single-leg balance without error on both legs for 10 seconds, were 2.5 times more likely to suffer an ankle sprain vs. those who passed (47). Consequently, there is moderate evidence supporting an association between poor balance and eventual ankle sprain injury.
Physical fitness is a broad concept that includes many different components. This paper specifically focused on 5 important but often neglected components that might be associated with MSK-I: flexibility, power, speed, balance, and agility. Based on our synthesis of the evidence, our primary findings were that there is (a) moderate evidence that hamstring flexibility, as measured by performance on a sit-and-reach test or active straight leg raise test assessed with goniometry, and ankle flexibility, assessed with goniometry, are associated with MSK-I risk; (b) moderate evidence that lower body power, as measured by performance on a standing broad jump or vertical jump with no countermovement, is associated with MSK-I risk; (c) moderate evidence that slow sprint speed is associated with risk for MSK-I; (d) moderate evidence that poor performance on a single-leg balance test is associated with increased risk for ankle sprain; and (e) insufficient evidence that agility is associated with MSK-I risk. Notably, our search did not yield any studies that investigated the association between agility and MSK-I and met our inclusion criteria.
Our examination of the scientific literature led to several interesting findings. First, slower sprint speed was positively associated with increased risk for injury in both rugby players (13) and FBI trainees (26). Notably, sprint speeds were measured across both short (10 and 40 m) and long (300 m) distances. The reason that slower times were associated with increased risk is unclear, but speed may be a surrogate for aerobic fitness, and the evidence for associations between MSK-I risk and aerobic fitness is strong (31). In FBI trainees, Cox regression analyses determined the slowest 2 quartile-sustained MSK-I at greater rates compared with the fastest. Those with slower 1.5-mile run times and lower overall physical fitness test scores were also at increased risk (26), which again is consistent with the findings for our systematic review on cardiorespiratory endurance (31).
The finding with balance is also of interest, but the specific measures used seem to be important as well: clinical performance measures which are noninstrumented and require little or no equipment vs. those instrumented requiring specialized equipment. A meta-analysis by Arnold et al. (3) found poorer noninstrumented balance (foot lifts during a static balance task and the Star Excursion Balance Test) and instrumented measures (time to stabilization and other force plate measures) to be highly associated with chronic ankle instability, but no study outside of the current review has systematically examined balance in nonpathologic populations within our search and inclusion criteria. For the purposes of this study, poor balance as measured by noninstrumented tasks in collegiate athletes was associated with greater risk of ankle sprain (47), whereas no such association was noted for the instrumented tests investigating ankle sprain (18,50). Performance-based noninstrumented measures of balance are widely used and easy to implement but do not identify the underlying mechanisms of balance impairments, meaning instrumented assessments still remain relevant. The expediency and ease of use of clinical balance measures, together with the moderate level of evidence, make for an attractive assessment in prospectively examining ankle sprain risk. However, as all balance studies looked at ankle sprain outcomes, we cannot generalize these findings to other types of MSK-I.
The moderate yet conflicting evidence for hamstring and ankle flexibility and injury also warrants further discussion. More than half (6 of 10; 60%) of the studies on hamstring flexibility used a broad MSK-I definition as their outcome (2,4,7,25,28,38), whereas 4 specifically studied hamstring injury (11,12,20,52). Only one of these was significant, albeit in a small sample of male professional soccer players, with results revealing an association between greater hamstring flexibility as measured by performance on an active SLR test and decreased injury risk (20). By contrast, one study reported a bimodal association between hamstring flexibility, as measured by sit-and-reach test performance and injury risk (acute or overuse injury) in male basic trainees (7). Similar findings of conflicting directions of association were found with regard to ankle ROM and risk of injury in military populations (33,45). For ankle flexibility, ankle dorsiflexion active ROM asymmetry was found to be a significant predictor of MSK-I risk in US Army Rangers (45), whereas greater DF-passive ROM was associated with elevated risk of overuse Achilles tendon injuries in Belgian basic trainees (33). Although it is routinely accepted that poor flexibility is related to increased injury risk and stretching is widely recommended as an injury prevention practice, the evidence remains equivocal on the influence of flexibility on training and sport-related injury (16,23,46,51). Authors have suggested that muscles with less compliant musculo-tendinous units (low level of flexibility) are more susceptible to strains during stretch-shortening cycles (16,51), which are especially potent and frequent during sport- and training-related jumping and sprinting activities. By contrast, proposed explanations for studies relating high levels of flexibility to increased injury risk include the potential effects ROM has on decreasing overall joint stability and positioning joints in positions where static (ligaments) and dynamic (muscle) stabilizing tissues are more prone to sprain or strain when loaded (46). Given the findings for both hamstring and ankle flexibility/ROM, it is clear that future research investigating the potential link between flexibility and injury is warranted.
Similar to flexibility, results from this review revealed inconsistent findings related to the association between power and injury risk (2,13,17,20,28,33,39,44,45). Professional soccer players who demonstrated increased vertical jump height were at greater risk for hamstring injury (20). As most hamstring injuries occur with explosive movements within this sport, this finding is not wholly surprising. It is reasonable to suggest that athletes who generated greater explosive force production, as measured by performance on a non-countermovement jump test, were more likely to achieve greater limb accelerations and decelerations during play, which may have increased their risk for hamstring injury. By contrast, Taanila et al. (44) reported that lower levels of lower body power, as measured by standing broad jump performance, were predictive of acute and chronic injury in a large cohort of Finnish military conscripts. Given this test requires both vertical and horizontal displacement during performance, higher levels of both power and motor control are needed for successful jump completion. These factors, in addition to the population tested and use of a broad injury definition (all acute and overuse injuries), may help explain the relationship found. Conscripts with lower levels of lower body power and motor control may have perceived formal physical and field training exercises, such as obstacle courses and runs/marches over various terrains, as more difficult and thus had an increased likelihood for injury. Given these collective findings, future studies may want to further investigate associations between various measures of power and injury across a multitude of populations.
This systematic review has several limitations, many of which have been presented in parts 1 and 2 of this series (8,31). For instance, an important limitation is that some studies may have been missed from the current literature search. Our search strategy used broad injury search terms (e.g., “injury,” “musculoskeletal injury,” “sprain,” “strain,” etc.) and thus may not have captured all relevant literature measuring the association between fitness components (flexibility, power, speed, balance, and agility) and a specific injury and/or injury to a particular anatomical location. Consequently, future systematic reviews and meta-analyses that use search terms specific to particular injuries and/or anatomical locations are warranted to investigate these potential associations. Furthermore, we excluded all studies with injury data that were self-report in nature due to the potential variance in both validity and reliability of self-reported injury outcome measures across studies. Investigators may also want to include self-report measures of injury in future systematic reviews albeit taking into consideration the reliability and validity characteristics of self-report injury assessments.
Specific to this study, an important limitation was the number of various assessments used to measure each component of fitness, which made comparing fitness components across studies difficult. Ultimately, this limitation led to numerous additional questions. For example—hamstring flexibility can be measured in different ways—are the ones used assessing flexibility or range of motion? What is the best assessment for upper and lower body power? Should a standardized noninstrumented measure of balance be used? As suggested, a major limitation was that we made a number of assumptions to try to bring the literature into a coherent framework, and our assumptions could be challenged. However, this is an attempt to help develop a scientific approach to synthesizing the vast and diverse literature, so the results can be applied in practical ways. Finally, we modified previous methodological scoring rubrics and developed our own level of evidence determinations for this study. Both these metrics were modified from previously published systematic reviews and both were made specific to our questions of interest However, as these are new measures, the measurement properties of each could be questioned.
This is the last in a 3-part series of articles that systematically reviewed the evidence and assessed the quality of relevant scientific literature published on physical fitness and MSK-I among military and civilian populations. Findings from this article indicate that several measures of flexibility, power, speed, and balance are moderately associated with increased risk for MSK-I. Notably, our results also revealed conflicting directions of association for the relationships between both flexibility and power, and injury risk. When results from this entire series of reviews are considered, several important findings emerge. First, it is important to note that this review was conducted in support of the US Army Training and Doctrine Command’s initiative to develop and validate baseline physical performance assessments for all US Army Soldiers, independent of age and sex. Given that most studies were conducted in military populations, many of the assessments used to measure components of physical fitness were specific to military training, particularly branch-specific physical fitness tests. Consequently, the most frequently reported fitness components were cardiorespiratory endurance and muscular endurance, which were commonly assessed with set distances run for time, and push-up and sit-up tests. Our review also revealed that studies assessing the relationship between muscular strength, flexibility, power, speed, and agility, and MSK-I were more scarce, and in the case of agility, non-existent. It is clear that further study on these associations and their implications for injury prevention programming is warranted. Despite this disparity in the quantity of reviewed studies examining the various components of fitness, we believe our results can still be of use for military, first responder, and athletic communities who are seeking evidence-based metrics for assessing or risk-stratifying populations or individuals for risk of MSK-I. Second, our results indicate that the scientific literature supports the association between low levels of cardiorespiratory endurance and muscular endurance, especially of the upper body, and increased MSK-I risk. The evidence is particularly strong because it pertains to the relationship between low CRE and injury; therefore, including an assessment of CRE when stratifying these populations for injury risk is advised. Finally, although much work remains with regard to prioritizing what measures would be most useful in various situations and across multiple populations, selected tests presented in this series of articles could be used now to help mitigate injury risk by providing countermeasures to improve functional limitations.
The authors report no conflicts of interest. The opinions or assertions contained herein are the private ones of the author(s) and are not to be construed as official or reflecting the views of the Uniformed Services University, Department of the Army, Department of the Air Force, Department of the Navy or the United States Department of Defense.
1. Almeida SA, Maxwell WK, Shaffer RA, Luz JT, Badong KE, Brodine SK. A physical training training program to reduce musculoskeletal injuries in U.S. Marine Corps recruits. San Diego, CA: Center NHR, 1997.
2. Arnason A, Sigurdsson SB, Gudmundsson A, Holme I, Engebretsen L, Bahr R. Risk factors for injuries in football. Am J Sports Med 32: 5S–16S, 2004.
3. Arnold BL, De La Motte S, Linens S, Ross SE. Ankle instability is associated with balance impairments: A meta-analysis. Med Sci Sports Exerc 41: 1048–1062, 2009.
4. Bell N, Amoroso P, Hemenway D, Mangione T, Jones B. Race and Injury
Among Army Basic Trainees. Natick, MA: Defense Technical Information Center, 1994. Available at: http://www.dtic.mil/docs/citations/ADA306072
. Accessed March 1, 2014.
5. Bullock SH, Jones BH, Gilchrist J, Marshall SW. Prevention of physical training- related injuries recommendations for the military and other active populations based on expedited systematic reviews. Am J Prev Med 38: S156–S181, 2010.
6. Bulzacchelli MT, Sulsky SI, Rodriguez-Monguio R, Karlsson LH, Hill MO. Injury
during U.S. Army basic combat training: A systematic review of risk factor studies. Am J Prev Med 47: 813–822, 2014.
7. Cowan D, Jones B, Tomlinson P, Robinson J, Polly D, Frykman P, Reynolds K. The Epidemiology of Physical Training Injuries in U.S. Army Infantry Trainees: Methodology, Population, and Risk Factors. Natick, MA: Defense Technical Information Center, 1988. Available at: http://www.dtic.mil/dtic/tr/fulltext/u2/a206551.pdf
. Accessed March 1, 2014.
8. de la Motte SJ, Gribbin TC, Lisman P, Murphy K, Deuster PA. A systematic review of the association between physical fitness and musculoskeletal injury
risk: Part 2-muscular endurance and muscular strength. J Strength Cond Res 31: 3218–3234, 2017.
9. Emery CA, Meeuwisse WH. Risk factors for groin injuries in hockey. Med Sci Sports Exerc 33: 1423–1433, 2001.
10. Fousekis K, Tsepis E, Vagenas G. Intrinsic risk factors of noncontact ankle sprains in soccer: A prospective study on 100 professional players. Am J Sports Med 40: 1842–1850, 2012.
11. Gabbe BJ, Bennell KL, Finch CF. Why are older Australian football players at greater risk of hamstring injury
?. J Sci Med Sport 9: 327–333, 2006.
12. Gabbe BJ, Finch CF, Bennell KL, Wajswelner H. Risk factors for hamstring injuries in community level Australian football. Br J Sports Med 39: 106–110, 2005.
13. Gabbett TJ, Domrow N. Risk factors for injury
in subelite rugby league players. Am J Sports Med 33: 428–434, 2005.
14. Gabbett TJ, Ullah S, Finch CF. Identifying risk factors for contact injury
in professional rugby league players—application of a frailty model for recurrent injury
. J Sci Med Sport 15: 496–504, 2012.
15. Gastin PB, Meyer D, Huntsman E, Cook J. Increase in injury
risk with low body mass and aerobic-running fitness in elite Australian football. Int J Sports Physiol Perform 10: 458–463, 2015.
16. Gleim GW, McHugh MP. Flexibility and its effects on sports injury
and performance. Sports Med 24: 289–299, 1997.
17. Grant JA, Bedi A, Kurz J, Bancroft R, Gagnier JJ, Miller BS. Ability of preseason body composition and physical fitness to predict the risk of injury
in male collegiate hockey players. Sports Health 7: 45–51, 2015.
18. Hadzic V, Sattler T, Topole E, Jarnovic Z, Burger H, Dervisevic E. Risk factors for ankle sprain in volleyball players: A preliminary analysis. Isokinet Exerc Sci 17: 155–160, 2009.
19. Hegedus EJ, McDonough S, Bleakley C, Cook CE, Baxter GD. Clinician-friendly lower extremity physical performance measures in athletes: A systematic review of measurement properties and correlation with injury
, part 1. The tests for knee function including the hop tests. Br J Sports Med 49: 642–648, 2015.
20. Henderson G, Barnes CA, Portas MD. Factors associated with increased propensity for hamstring injury
in English Premier League soccer players. J Sci Sport Med 13: 397–402, 2010.
21. Hootman JM, Macera CA, Ainsworth BE, Martin M, Addy CL, Blair SN. Association among physical activity level, cardiorespiratory fitness, and risk of musculoskeletal injury
. Am J Epidemiol 154: 251–258, 2001.
22. Hootman JM, Macera CA, Ainsworth BE, Martin M, Addy CL, Blair SN. Predictors of lower extremity injury
among recreationally active adults. Clin J Sport Med 12: 99–106, 2002.
23. Jones BH, Knapik JJ. Physical training and exercise-related injuries. Surveillance, research and injury
prevention in military populations. Sports Med 27: 111–125, 1999.
24. Kerr ZY, Marshall SW, Dompier TP, Corlette J, Klossner DA, Gilchrist J. College sports-related injuries—United States, 2009–10 through 2013–14 academic years. MMWR Morb Mortal Wkly Rep 64: 1330–1336, 2015.
25. Knapik JJ, Bauman CL, Jones BH, Harris JM, Vaughan L. Preseason strength and flexibility imbalances associated with athletic injuries in female collegiate athletes. Am J Sports Med 19: 76–81, 1991.
26. Knapik JJ, Grier T, Spiess A, Swedler DI, Hauret KG, Graham B, Yoder J, Jones BH. Injury
rates and injury
risk factors among Federal Bureau of Investigation new agent trainees. BMC Public Health 11: 920, 2011.
27. Knapik JJ, Scott SJ, Sharp MA, Hauret KG, Darakjy S, Rieger WR, Palkoska FA, VanCamp SE, Jones BH. The basis for prescribed ability group run speeds and distances in U.S. Army basic combat training. Mil Med 171: 669–677, 2006.
28. Knapik JJ, Sharp MA, Canham-Chervak M, Hauret K, Patton JF, Jones BH. Risk factors for training-related injuries among men and women in basic combat training. Med Sci Sports Exerc 33: 946–954, 2001.
29. Knapik JJ, Swedler DI, Grier TL, Hauret KG, Bullock SH, Williams KW, Darakjy SS, Lester ME, Tobler SK, Jones BH. Injury
reduction effectiveness of selecting running shoes based on plantar shape. J Strength Cond Res 23: 685–697, 2009.
30. Krivickas LS, Feinberg JH. Lower extremity injuries in college athletes: Relation between ligamentous laxity and lower extremity muscle tightness. Arch Phys Med Rehabil 77: 1139–1143, 1996.
31. Lisman PJ, de la Motte SJ, Gribbin TC, Jaffin DP, Murphy K, Deuster PA. A systematic review of the association between physical fitness and musculoskeletal injury
risk: Part 1-cardiorespiratory endurance. J Strength Cond Res 31: 1744–1757, 2017.
32. Macera CA, Jackson KL, Hagenmaier GW, Kronenfeld JJ, Kohl HW, Blair SN. Age, physical activity, physical fitness, body composition, and incidence of orthopedic problems. Res Q Exerc Sport 60: 225–233, 1989.
33. Mahieu NN, Witvrouw E, Stevens V, Van Tiggelen D, Roget P. Intrinsic risk factors for the development of Achilles tendon overuse injury
: A prospective study. Am J Sports Med 34: 226–235, 2006.
34. Nindl BC, Williams TJ, Deuster PA, Butler NL, Jones BH. Strategies for optimizing military physical readiness and preventing musculoskeletal injuries in the 21st century. US Army Med Dep J: 5–23, 2013.
35. Noyes FR, Barber Westin SD. Anterior cruciate ligament injury
prevention training in female athletes: A systematic review of injury
reduction and results of athletic performance tests. Sports Health 4: 36–46, 2012.
36. O’Connor FG, Deuster PA, Davis J, Pappas CG, Knapik JJ. Functional movement screening: Predicting injuries in officer candidates. Med Sci Sports Exerc 43: 2224–2230, 2011.
37. Pitts SR, Niska RW, Xu J, Burt CW. National Hospital Ambulatory Medical Care Survey: 2006 emergency department summary. Natl Health Stat Report: 1–38, 2008.
38. Reynolds KL, Heckel HA, Witt CE, Martin JW, Pollard JA, Knapik JJ, Jones BH. Cigarette smoking, physical fitness, and injuries in infantry soldiers. Am J Prev Med 10: 145–150, 1994.
39. Roos L, Boesch M, Sefidan S, Frey F, Mader U, Annen H, Wyss T. Adapted marching distances and physical training decrease recruits’ injuries and attrition. Mil Med 180: 329–336, 2015.
40. Schwellnus MP, Jordaan G, Noakes TD. Prevention of common overuse injuries by the use of shock absorbing insoles. A prospective study. Am J Sports Med 18: 636–641, 1990.
41. Steffen K, Emery CA, Romiti M, Kang J, Bizzini M, Dvorak J, Finch CF, Meeuwisse WH. High adherence to a neuromuscular injury
prevention programme (FIFA 11+) improves functional balance and reduces injury
risk in Canadian youth female football players: A cluster randomised trial. Br J Sports Med 47: 794–802, 2013.
42. Sugimoto D, Myer GD, Bush HM, Klugman MF, Medina McKeon JM, Hewett TE. Compliance with neuromuscular training and anterior cruciate ligament injury
risk reduction in female athletes: A meta-analysis. J Athl Train 47: 714–723, 2012.
43. Swenson DM, Yard EE, Fields SK, Comstock RD. Patterns of recurrent injuries among US high school athletes, 2005–2008. Am J Sports Med 37: 1586–1593, 2009.
44. Taanila H, Suni JH, Kannus P, Pihlajamaki H, Ruohola JP, Viskari J, Parkkari J. Risk factors of acute and overuse musculoskeletal injuries among young conscripts: A population-based cohort study. BMC Musculoskelet Disord 16: 104, 2015.
45. Teyhen DS, Shaffer SW, Butler RJ, Goffar SL, Kiesel KB, Rhon DI, Williamson JN, Plisky PJ. What risk factors are associated with musculoskeletal injury
in US Army rangers? A prospective prognostic study. Clin Orthop Relat Res 473: 2948–2958, 2015.
46. Thacker SB, Gilchrist J, Stroup DF, Kimsey CD Jr. The impact of stretching on sports injury
risk: A systematic review of the literature. Med Sci Sports Exerc 36: 371–378, 2004.
47. Trojian TH, McKeag DB. Single leg balance test to identify risk of ankle sprains. Br J Sports Med 40: 610–613, 2006.
48. Tyler TF, Nicholas SJ, Campbell RJ, McHugh MP. The association of hip strength and flexibility with the incidence of adductor muscle strains in professional ice hockey players. Am J Sports Med 29: 124–128, 2001.
49. Wang X, Wang PS, Zhou W. Risk factors of military training-related injuries in recruits of Chinese People’s Armed Police Forces. Chin J Traumatol 6: 12–17, 2003.
50. Willems TM, Witvrouw E, Delbaere K, Philippaerts R, De Bourdeaudhuij I, De Clercq D. Intrinsic risk factors for inversion ankle sprains in females–a prospective study. Scand J Med Sci Sports 15: 336–345, 2005.
51. Witvrouw E, Mahieu N, Danneels L, McNair P. Stretching and injury
prevention: An obscure relationship. Sports Med 34: 443–449, 2004.
52. Yeung SS, Suen AMY, Yeung EW. A prospective cohort study of hamstring injuries in competitive sprinters: Preseason muscle imbalance as a possible risk factor. Br J Sports Med 43: 589–594, 2009.