There has recently been tremendous growth in the use of movement screening assessments by researchers and clinicians alike to determine functional movement quality within a variety of athlete populations,1 including tactical athletes.2 To date, the movement screen assessment that has been predominantly used within the scientific literature has been the Functional Movement Screen (FMS).3,4 The use of the FMS has arguably been due to the fact that the FBMS has demonstrated an ability to prospectively predict future musculoskeletal injury among various traditional athlete populations,5 as well Bas firefighters6–8 and other tactical athlete populations.9 Within the firefighter population specifically, quantifying functional movement quality is especially important because many of the essential job duties associated with the firefighting occupation require functional movements (eg, stair climb, ladder raise, hose drag, equipment carry, and forced entry).10
Although the test-retest reliability of Composite FMS scores has been established (pooled intraclass correlation coefficient [ICC] = 0.81),11 previous research has also identified statistically significant relationships between obesity, as quantified by body mass index (BMI),12 and Composite FMS scores,13–15 as well as between age and Composite FMS scores.14,16,17 Collectively, these results suggest that performance on the FMS may be influenced by an individual’s obesity level and/or age, and thus it is possible that Composite FMS scores may not be an independent measure of functional movement quality. These influences may also explain the conflicting results regarding the predictive ability of the FMS in the literature,11,18–20 as well as the questions regarding the construct of the Composite FMS score21–24 and, therefore, the clinical utility of the FMS itself.25,26
Recently, a new assessment of functional movement quality, known as the Movement Efficiency (ME) Test, has been presented in the scientific literature.27–30 The ME Test is similar to the FMS in that it also uses seven sub-tests that require an individual to complete various movement patterns, but these sub-tests are graded based on observations of specific movement compensations.27 Similar to the FMS, excellent test-retest reliability of the Overall ME Test scores (ICC = 0.84) and fair-to-excellent test-retest reliability of the sub-test scores (ICC = 0.55 to 0.84) have recently been established in the literature.27 However, due to the use of individual movement compensations in the scoring algorithms, it has recently been hypothesized that ME Test scores may be more sensitive than FMS scores to changes in functional movement quality as a result of various corrective exercise interventions that address the specific movement compensations identified during the sub-tests.27
That said, the relationships between Overall ME Test scores and BMI or age are currently unknown. If BMI and/or age demonstrate different relationships with Composite FMS scores than they do with Overall ME Test scores, it is possible that one measure is less influenced by these confounding influences. In addition, the association between Composite FMS scores and Overall ME Test scores among firefighters also remains unknown. Because both the FMS6–8 and the ME Test31,32 are already being used to quantify the functional movement quality of firefighters, it is important to determine whether these assessments quantify functional movement quality in a similar manner within this population. Therefore, identifying the relationship between these measures of functional movement quality among firefighters, and examining the potential influences of obesity and age on these relationships, is also warranted. Accordingly, the overall aim of the current study was to examine whether the FMS and ME Test measure similar constructs. This was accomplished by: (1) examining the relationships between BMI, age, Composite FMS scores and Overall ME Test scores; (2) determining the unique influence of BMI and age on Composite FMS scores and Overall ME Test scores; and (3) examining the relationship and amount of shared variance between Composite FMS scores and Overall ME Test scores after accounting for BMI and age. Preliminary results of this study have been published in abstract form only.33
Methods
Participants
Forty-nine male career active-duty firefighters volunteered to participate in this study (mean ± standard deviation, age = 40.7 ± 7.9 years; height = 179.2 ± 5.5B cm; body mass = 90.8 ± 9.1 kg). All participants were free of any musculoskeletal injury that required medical attention for at least 3 months prior to participating in the study. All components of this study protocol were approved by the Institutional Review Board at the University of Wisconsin–Milwaukee and all participants provided written informed consent before any data were collected.
Protocol
All data were collected by the same researcher (DJC) across all participants. At the time of data collection, this researcher was a certified strength and conditioning specialist who had more than 2 years of prior experience administering the ME Test and more than 4 years of prior experience administering the FMBS.
Anthropometric Data
Height and body mass data were collected using a stadiometer and mechanical beam scale (Health-o-Meter Professional; Pelstar, LLC). Based on these height and body mass measurements, the BMI of each participant was then calculated (kg/m2) to represent the obesity level of each participant.12 Age data (years) were collected via self-report from each participant.
Functional Movement Quality Data
Before any functional movement quality data were collected, all participants completed a dynamic warm-up that has been previously used within the firefighter poBpulation.15,34 The FMS3,4 and ME Test27 were administered according to previously published methods and all participants completed these B assessments in athletic apparel and without shoes. The FMS consists of the following sub-tests, which were completed in the following order using an FMS test kit (Functional Movement Systems): Deep Squat, Hurdle Step, In-Line Lunge, Shoulder Mobility, Active Straight-Leg Raise, Push-Up, and Rotary Stability.3,4 The ME Test consists of the following sub-tests, completed in the following order: 2-Leg Squat (Figure 1), 2-Leg Squat with Heel Lift (Figure 2), 1-Leg Squat (Figure 3), Push-Up (Figure 4), Shoulder Movements (Figure 5), and Trunk and Cervical Movements (Figure 6).27 Each sub-test of the ME Test was scored in real time in a binomial (yes/no) fashion based on a standard set of 60 potential movement compensations (Table A, available in the online version of this article). Participants were provided three to five trials of each FMS and ME Test sub-test and the most proficient trial of each FMS and ME Test sub-test was used for scoring purposes. No participants reported experiencing pain during any sub-test of the FMS or ME Test and all participants passed the clearing tests associated with the FMS.35 All FMS sub-test scores were summed to calculate a Composite FMS score (0 to 21) for each participant. The ME Test results were subsequently entered into the Fusionetics Performance Health System (Fusionetics) to calculate an Overall ME Test score (0 to 100) for each participant. ME Test scores were generated by the Fusionetics proprietary algorithm based on the number, type, and body region within which an error occurred.27,29,30
 |
Figure 1. 2-Leg Squat sub-test: (A) start position (front view); (B) end position (front view); (C) start position (back view); (D) end position (back view); (E) start position (side view); and (F) end position (side view). |
 |
Figure 2. 2-Leg Squat with Heel Lift sub-test: (A) start position (front view); (B) end position (front view); (C) start position (back view); (D) end position (back view); (E) start position (side view); and (F) end position (side view). |
 |
Figure 3. 1-Leg Squat sub-test: (A) start position and (B) end position. |
 |
Figure 4. Push-Up sub-test: (A) start position and (B) end position. |
 |
Figure 5. Shoulder Movements sub-test: (A) shoulder flexion–start position; (B) shoulder flexion–end position; (C) shoulder internal rotation–start position; (D) shoulder internal rotation–end position; (E) shoulder external rotation–start position; (F) shoulder external rotation–end position; (G) shoulder horizontal abduction–start position; and (H) shoulder horizontal abduction–end position. |
 |
Figure 6. Trunk Movements sub-test: (A) trunk lateral flexion–start position; (B) trunk lateral flexion–end position; (C) trunk rotation–start position; (D) trunk rotation–end position. Cervical Movements sub-test: (E) cervical lateral flexion–start position; (F) cervical lateral flexion–end position; (G) cervical rotation–start position; and (H) cervical rotation–end position. |
  |
Table A: Movement Efficiency (ME) Test Grading Form |
Statistical Analyses
The distribution of each variable was examined for normality by inspecting Q-Q plots and using the Shapiro–Wilk test. The BMI and Composite FMS score distributions were identified as positively skewed (W = 0.929, P = .006; W = 0.942, P = .018, respectively). As such, log10 transformations were applied to the BMI and Composite FMS score variables,36 resulting in a normal distribution for Both variables (W = 0.953, P = .051; W = 0.958, P = .082, respectively). These log10 transformed variables were used in all subsequent statistical analyses.
Bivariate correlations were computed to examine the relationships between the variables of BMI, age, Composite FMS score, and Overall ME Test score. Multiple linear regression analyses were used to test whether BMI and age account for a significant amount of variance in Composite FMS scores after controlling for Overall ME Test scores, and whether BMI and age account for a significant amount of variance in Overall ME Test scores after controlling for Composite FMS scores. Finally, semi-partial correlations were also used to elucidate the relationship and amount of unique variance shared between Composite FMS scores and Overall ME Test scores after accounting for the influence of BMI and age.
All statistical analyses were conducted using IBM SPSS 25 software (IBM Corporation) and an α-level of 0.05 was used to determine statistical significance for all analyses. Strength of all correlations was interpreted using the following guidelines: weak (r < 0.25); fair (0.25 ≤ r ≤ 0.B49); moderate (0.50 ≤ r ≤ 0.74); and excellent (r ≤ 0.75).37
Results
Non-transformed descriptive data (mean ± standard deviation) for BMI, age, Composite FMS score, and Overall ME Test score are presented in Table 1. A moderate and significant indirect correlation between age and Composite FMS score was identified (r = −0.528, P < B.001), whereas the correlation between BMI and Composite FMS score was weak and non-significant (r = −0.060, P = .683). In addition, weak and non-significant correlations were identified between Overall ME Test score and age (r = −0.203, P = .161), as well as between Overall ME Test score and BMI (r = −0.146, P = .315). These results collectively indicate that age is significantly associated with Composite FMS scores, but not with Overall ME Test scores.
 |
Table 1: Descriptive BMI, Age, and Functional Movement Quality Data |
When examining the relationship between the two measures of functional movement quality, a moderate and significant direct correlation between Overall MEB Test score and Composite FMS score was identified (r = 0.612, P < .001), which indicates that 37.5% of the variance is shared between Overall ME Test scores and Composite FMS scores (R2 = 0.375).
Multiple linear regression analyses indicated that the combination of BMI, age, and Overall ME Test scores was able to significantly predict Composite FMS scores (F3,45 = 17.997, P < .001), and this combination of predictors accounted for 54.5% of the variance in Composite FMS scores (R2 = 0.545). This was a statistically significant increase in the amount of Composite FMS score variance that could be accounted for by Overall ME Test score alone (R2 change = 0.171, F2,45 = 8.454, P < .001).
Multiple linear regression analyses indicated that the combination of BMI, age, and Composite FMS scores was able to significantly predict Overall ME Test scores (F3,45 = 10.096, P < .001), and this combination of predictors accounted for 40.2% of the variance in Overall ME Test scores (R2 = 0.402). However, this was not a statistically significant increase in the amount of Overall ME Test score variance that could be accounted for by Composite FMS score alone (R2 change = 0.028, F2,45 = 1.042, P = .361).
Finally, there was a moderate and significant direct semi-partial correlation between Overall ME Test score and Composite FMS score after accounting for BMI and age (rsp = 0.503, P < .001). Collectively, these results indicate that Overall ME Test scores account for only 25.3% of the variance in Composite FMS scores (R2 = 0.253) after controlling for the effects of BMI and age.
Discussion
The first aim of this study was to examine the relationships between BMI, age, Composite FMS scores, and Overall ME Test scores among active-duty firefighters. Results of the current study indicate that age is significantly and inversely associated with Composite FMS scores, which implies that as age increases the functional movement quality of active-duty firefighters decreases. These findings are in agreement with previous research examining the relationship between age and Composite FMS scores among the non-athlete population of middle-aged adults,14 as well as the athlete population of recreational runners16 and the tactical athlete population of active-duty Army military services members.17
However, results of the current study indicate that BMI is not significantly associated with Composite FMS scores. These findings differ from previous research examining the relationship between BMI and Composite FMS scores among the non-athlete populations of school children13 and middle-aged adults.14 More importantly, these results also differ from literature demonstrating a significant inverse relationship between BMI and Composite FMS scores within the tactical athlete population of firefighter recruits with a similar BMI (28.3 ± 2.8 vs 27.4 ± 3.0 in the current study).15 The contrast in these findings suggests that obesity level may influence the movement quality of firefighter recruits and active-duty firefighters differently. It also is possible that an alternative measure of obesity level, such as body fat percentage, may demonstrate a significant relationship with Composite FMS scores among active-duty firefighters.38 However, it should be noted that although Cornell et al15 identified a significant correlation between Composite FMS scores and BMI, these researchers failed to identify a correlation between Composite FMS scores and body fat percentage. Nevertheless, further examination of the influence of body composition on functional movement quality is warranted.
In contrast, neither BMI nor age was significantly associated with Overall ME Test scores. Although this is the first study to examine the relationship between Overall ME Test scores and BMI and age, these findings suggest that obesity level and age may not influence ME Test performance. This discrepancy in the influence of obesity and age on functional movement quality assessment may also explain why an excellent correlation (ie, r ≥ 0.75) between Overall ME Test score and Composite FMS score was not identified and that only 37.5% of the variance is shared between Overall ME Test scores and Composite FMS scores. Therefore, despite the fact that these two movement screens are measuring directly related constructs, the results of the current study suggest that the FMS and the ME Test may quantify the functional movement quality of firefighters differently.
Accordingly, the second aim of the current study was to further elucidate these potential discrepancies by determining the unique influence of obesity and age on Composite FMS scores and Overall ME Test scores. Results indicate that BMI and age additionally account for a significant amount of the variance in Composite FMS scores, above and beyond that accounted for by Overall ME Test scores alone. In contrast, BMI and age did not additionally account for a significant amount of the variance in Overall ME Test scores above and beyond what was accounted for by Composite FMS scores alone. When taken together, these results indicate that BMI and age did not influence Overall ME Test scores to the same extent that they influenced Composite FMS scores, which implies that changes in Overall ME Test scores may be more indicative of true changes in overall functional movement quality, and not potentially due to concomitant changes and/or differences in BMI or age among individuals.
Finally, the third aim of the current study was to examine the relationship and the amount of shared variance between Composite FMS scores and Overall ME Test scores among active-duty firefighters after controlling for BMI and age. Although a moderate and direct semi-partial correlation between Overall ME Test score and Composite FMS score was identified, after controlling for the influence of BMI and age, this semi-partial correlation was considerably smaller than the bivariate correlation between Composite FMS scores and Overall ME Test scores (rsp = 0.503 vs r = 0.612, respectively). That is, after controlling for the known influences of obesity13–15 and age14,16,17 on Composite FMS scores, Overall ME Test scores uniquely account for 25.3% of the variance in this measure of functional movement quality. Collectively, these results suggest that although both the FMS and the ME Test attempt to quantify the overall functional movement quality of an individual, there is not concurrent validity between the FMS and ME Test, because a relatively small proportion of the variance in Composite FMS scores was accounted for by the Overall ME Test scores.
The results of the current study also provide potential mechanistic rationale supporting previous research that has questioned the construct of the Composite FMS score,21–24 as well as the predictive ability11,18–20 and clinical utility of the FMS when examining changes before and after intervention.25,26 In particular, if age and/or obesity level significantly impact the scoring of the FMS, then such variables should be accounted for when examining the ability of the FMS to predict future musculoskeletal injury and/or examining the responsiveness of the FMS to changes as a result of corrective exercise interventions. Therefore, it is possible that these influences could potentially explain the discrepancies in musculoskeletal injury prediction ability and/or responsiveness of FMS scores noted within the literature. Further, given the apparent lack of influence of obesity and age on Overall ME Test scores, it is possible that the ME Test may respond differently to changes in functional movement quality and future research should examine the responsiveness ME Test scores to post-intervention.
Several limitations of the current study should be noted. This study used a small sample size of male active-duty career firefighters from the same geographic area in the United States. Therefore, replication of this study using larger sample sizes of both male and female firefighters, different types of firefighters (recruit vs active-duty; career vs volunteer; structural vs wildland), and firefighters recruited from different types of departments (urban vs suburban vs rural) and geographical regions, should be conducted. In addition, due to differing results regarding the relationship between BMI and Composite FMS scores observed among firefighters in the current study compared to other previous research,15 future research should examine the influence of other measures of body composition on functional movement quality among different types of firefighters. Similarly, because all participants in the current study were firefighters, these results are not generalizable to other athlete populations, and future research within additional athlete populations is needed. Finally, given the relationship between previous musculoskeletal injury and FMS score outcomes among tactical athletes identified in the literature,39 determining the influence of previous injury history on both FMS and ME Test scores within the firefighter population is warranted.
Implications for Clinical Practice
The results of the current study suggest that discrepancies in overall functional movement quality may exist between the two assessments and, thus, the FMS and ME Test assessments should not be used interchangeably. Furthermore, the results of the current study provide further rationale that age, and potentially BMI, influence the scoring of the FMS. In contrast, the ME Test did not demonstrate the same associations with BMI and age, and thus the lack of concurrent validity between the FMS and ME Test could simply be due to the fact that obesity and age may not influence Overall ME Test scores in the same manner as Composite FMS scores. Given the large variability in BMI and age that exists in the fire service, these collective results suggest that it is possible that Overall ME Test scores may be more independent of their influences, and thus represent a more appropriate measure when assessing the overall functional movement quality of firefighters.
References
- McCunn R, Aus der Fünten K, Fullagar HH, McKeown I, Meyer T. Reliability and association with injury of movement screens: a critical review. Sports Med. 2016;46(6):763–781. doi:10.1007/s40279-015-0453-1 [CrossRef]
- Teyhen D, Bergeron MF, Deuster P, et al. Consortium for Health and Military Performance and American College of Sports Medicine Summit: utility of functional movement assessment in identifying musculoskeletal injury risk. Curr Sports Med Rep. 2014;13(1):52–63. doi:10.1249/JSR.0000000000000023 [CrossRef]
- Cook G, Burton L, Hoogenboom BJ, Voight M. Functional movement screening: the use of fundamental movements as an assessment of function—part 1. Int J Sports Phys Ther. 2014;9(3):396–409.
- Cook G, Burton L, Hoogenboom BJ, Voight M. Functional movement screening: the use of fundamental movements as an assessment of function-part 2. Int J Sports Phys Ther. 2014;9(4):549–563.
- Chimera NJ, Warren M. Use of clinical movement screening tests to predict injury in sport. World J Orthop. 2016;7(4):202–217. doi:10.5312/wjo.v7.i4.202 [CrossRef]
- Butler RJ, Contreras M, Burton LC, Plisky PJ, Goode A, Kiesel K. Modifiable risk factors predict injuries in firefighters during training academies. Work. 2013;46(1):11–17.
- Manton C, Garibaldi S, Harrell K. The association of the Functional Movement Screen and physical fitness measures with musculoskeletal injury in firefighter recruits. J Orthop Sports Phys Ther. 2016;46(1):A188.
- Peate WF, Bates G, Lunda K, Francis S, Bellamy K. Core strength: a new model for injury prediction and prevention. J Occup Med Toxicol. 2007;2(1):3. doi:10.1186/1745-6673-2-3 [CrossRef]
- Bock C, Orr RM. Use of the Functional Movement Screen in a tactical population: a review. J Mil Veterans Health. 2015;23(2):33–42.
- National Fire Protection Association. NFPA 1582: Standard on Comprehensive Occupational Medical Program for Fire Departments. 2018 Edition. National Fire Protection Association; 2017.
- Bonazza NA, Smuin D, Onks CA, Silvis ML, Dhawan A. Reliability, validity, and injury predictive value of the Functional Movement Screen: a systematic review and meta-analysis. Am J Sports Med. 2017;45(3):725–732. doi:10.1177/0363546516641937 [CrossRef]
- World Health Organization. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser. 2000;894:i–xii, 1–253.
- Duncan MJ, Stanley M, Leddington Wright S. The association between functional movement and overweight and obesity in British primary school children. BMC Sports Sci Med Rehabil. 2013;5(1):11. doi:10.1186/2052-1847-5-11 [CrossRef]
- Perry FT, Koehle MS. Normative data for the functional movement screen in middle-aged adults. J Strength Cond Res. 2013;27(2):458–462. doi:10.1519/JSC.0b013e3182576fa6 [CrossRef]
- Cornell DJ, Gnacinski SL, Zamzow A, Mims J, Ebersole KT. Influence of body mass index on movement efficiency among firefighter recruits. Work. 2016;54(3):679–687. doi:10.3233/WOR-162306 [CrossRef]
- Loudon JK, Parkerson-Mitchell AJ, Hildebrand LD, Teague C. Functional movement screen scores in a group of running athletes. J Strength Cond Res. 2014;28(4):909–913. doi:10.1097/JSC.0000000000000233 [CrossRef]
- Teyhen DS, Riebel MA, McArthur DR, et al. Normative data and the influence of age and gender on power, balance, flexibility, and functional movement in healthy service members. Mil Med. 2014;179(4):413–420. doi:10.7205/MILMED-D-13-00362 [CrossRef]
- Dorrel BS, Long T, Shaffer S, Myer GD. Evaluation of the Functional Movement Screen as an injury prediction tool among active adult populations: a systematic review and meta-analysis. Sports Health. 2015;7(6):532–537. doi:10.1177/1941738115607445 [CrossRef]
- Moran RW, Schneiders AG, Mason J, Sullivan SJ. Do Functional Movement Screen (FMS) composite scores predict subsequent injury? A systematic review with meta-analysis. Br J Sports Med. 2017;51(23):1661–1669. doi:10.1136/bjsports-2016-096938 [CrossRef]
- Warren M, Lininger MR, Chimera NJ, Smith CA. Utility of FMS to understand injury incidence in sports: current perspectives. Open Access J Sports Med. 2018;9:171–182. doi:10.2147/OAJSM.S149139 [CrossRef]
- Gnacinski SL, Cornell DJ, Meyer BB, Arvinen-Barrow M, Earl-Boehm JE. Functional Movement Screen factorial validity and measurement invariance across sex among collegiate student-athletes. J Strength Cond Res. 2016;30(12):3388–3395. doi:10.1519/JSC.0000000000001448 [CrossRef]
- Kazman JB, Galecki JM, Lisman P, Deuster PA, O’Connor FG. Factor structure of the functional movement screen in marine officer candidates. J Strength Cond Res. 2014;28(3):672–678. doi:10.1519/JSC.0b013e3182a6dd83 [CrossRef]
- Koehle MS, Saffer BY, Sinnen NM, MacInnis MJ. Factor structure and internal validity of the Functional Movement Screen in adults. J Strength Cond Res. 2016;30(2):540–546. doi:10.1519/JSC.0000000000001092 [CrossRef]
- Li Y, Wang X, Chen X, Dai B. Exploratory factor analysis of the functional movement screen in elite athletes. J Sports Sci. 2015;33(11):1166–1172. doi:10.1080/02640414.2014.986505 [CrossRef]
- Minthorn LM, Fayson SD, Stobierski LM, Welch CE, Anderson BE. The Functional Movement Screen’s ability to detect changes in movement patterns after a training intervention. J Sport Rehabil. 2015;24(3):322–326. doi:10.1123/jsr.2013-0146 [CrossRef]
- Wright AA, Stern B, Hegedus EJ, Tarara DT, Taylor JB, Dischiavi SL. Potential limitations of the functional movement screen: a clinical commentary. Br J Sports Med. 2016;50(13):770–771. doi:10.1136/bjsports-2015-095796 [CrossRef]
- Corndell DJ, Ebersole KT. Intra-rater test-retest reliability and response stability of the Fusionetics Movement Efficiency Test. Int J Sports Phys Ther. 2018;13(4):618–632. doi:10.26603/ijspt20180618 [CrossRef]
- Bagherian S, Rahnama N, Wikstrom EA. Corrective exercises improve movement efficiency and sensorimotor function but not fatigue sensitivitsy in chronic ankle instability patients: a randomized controlled trial. Clin J Sport Med. 2019;29(3):193–202. doi:10.1097/JSM.0000000000000511 [CrossRef]
- Bagherian S, Rahnama N, Wikstrom EA, Clark MA, Faroogh R. Characterizing lower extremity movement scores before and after fatigue in collegiate athletes with chronic ankle instability. Int J Athl Ther Train. 2018;28(1):27–32. doi:10.1123/ijatt.2017-0029 [CrossRef]
- Harriss J, Khan A, Song K, Register-Mihalik JK, Wikstrom EA. Clinical movement assessments do not differ between collegiate athletes with and without chronic ankle instability. Phys Ther Sport. 2019;36:22–27. doi:10.1016/j.ptsp.2018.12.009 [CrossRef]
- Cornell DJ, Ebersole KT. Inter-rater reliability of a movement efficiency test among the firefighter cadet population. Med Sci Sports Exerc. 2016;48(5)(suppl 1):97. doi:10.1249/01.mss.0000485295.94060.8d [CrossRef]
- Ebersole KT, Cornell DJ. Inter-rater response stability of a movement efficiency test among the firefighter cadet population. Med Sci Sports Exerc. 2016;48(5)(suppl 1):98. doi:10.1249/01.mss.0000485298.39802.1d [CrossRef]
- Cornell DJ, Ebersole KT, Azen R, Earl-Boehm JEZ, Alt C. Criterion validity of the Fusionetics Movement Efficiency Test in reference to the Functional Movement Screen among active-duty firefighters. J Orthop Sports Phys Ther. 2017;47(1):A173–A174.
- Corcnell DJ, Gnacinski SL, Langford MH, Mims J, Ebersole KT. Backwards overhead medicine ball throw and countermovement jump performance among firefighter candidates. J Trainol. 2015;4(1):11–14. doi:10.17338/trainology.4.1_11 [CrossRef]
- Cook G. Movement: Functional Movement Systems: Screening, Assessment and Corrective Strategies. On Target Publications; 2010.
- Cohen J, Cohen P, West SG, Aiken LS. Quantitative scales, curvilinear relationships, and transformations. In: Cohen J, Cohen P, West SG, Aiken LS, eds. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences, 3rd ed. Routledge; 2003:193–254.
- Portney LG, Watkins MP. Correlation. In: Portney LG, Watkins MP, eds. Foundations of Clinical Research: Applications to Practice, 3rd ed. Pearson Education; 2009:523–538.
- Nicolozakes CP, Schneider DK, Roewer BD, Borchers JR, Hewett TE. Influence of body composition on Functional Movement Screen scores in college football players. J Sport Rehabil. 2018;27(5):431–437. doi:10.1123/jsr.2015-0080 [CrossRef]
- de la Motte SJ, Lisman P, Sabatino M, Beutler AI, O’Connor FG, Deuster PA. The relationship between functional movement, balance deficits, and previous injury history in deploying Marine warfighters. J Strength Cond Res. 2016;30(6):1619–1625. doi:10.1519/JSC.0000000000000850 [CrossRef]
Descriptive BMI, Age, and Functional Movement Quality Data
| BMI (kg/m2) | 28.3 ± 2.8 | 23.8 to 35.6 |
| Age (y) | 40.7 ± 7.9 | 27.0 to 59.0 |
| Composite FMS Score (0 to 21) | 12.2 ± 3.0 | 8.0 to 19.0 |
| Overall ME Test Score (0 to 100) | 44.8 ± 12.5 | 19.7 to 72.3 |
| Foot/Ankle | Foot Turns Out | |||
| Foot Flattens | ||||
| Knee | Knee Moves In (Valgus) | |||
| Knee Moves Out (Varus) | ||||
| L-P-H-C | Excessive Forward Lean | |||
| Low Back Arches | ||||
| Low Back Rounds | ||||
| Shoulder | Arms Fall Forward | |||
| Foot/Ankle | Heel of Foot Lifts | |||
| L-P-H-C | Asymmetrical Weight Shift | |||
| Foot/Ankle | Foot Turns Out | |||
| Foot Flattens | ||||
| Knee | Knee Moves In (Valgus) | |||
| Knee Moves Out (Varus) | ||||
| L-P-H-C | Excessive Forward Lean | |||
| Low Back Arches | ||||
| Low Back Rounds | ||||
| Shoulder | Arms Fall Forward | |||
| L-P-H-C | Asymmetrical Weight Shift | |||
| Foot/Ankle | Foot Flattens | |||
| Knee | Knee Moves In (Valgus) | |||
| Knee Moves Out (Varus) | ||||
| L-P-H-C | Uncontrolled Trunk: Flexion, Rotation, and/or Hip Shift | |||
| Loss of Balance | ||||
| Spine | Head Moves Forward | |||
| Scapular Dyskinesis | ||||
| L-P-H-C | Low Back Arches / Stomach Protrudes | |||
| Knees | Knees Bend | |||
| Shoulder | Flexion: Compensation during movement / Unable to bring hand to wall | |||
| Internal Rotation: Compensation during movement / Unable to bring hand to mid-line of trunk | ||||
| External Rotation: Compensation during movement / Unable to bring hand to wall | ||||
| Horizontal Abduction: Compensation during movement / Unable to bring hand to wall | ||||
| Spine | Trunk Lateral Flexion: Compensation during movement / Unable to touch lateral joint line of knee with fingers | |||
| Trunk Rotation: Compensation during movement / Unable to rotate lateral aspect of shoulder to mid-line of sternum | ||||
| Spine | Cervical Lateral Flexion: Compensation during movement / Unable to side-bend neck so that ear is approximately half the distance to shoulder | |||
| Cervical Rotation: Compensation during movement / Unable to rotate chin to acromion of shoulder | ||||
