The functional movement screen (FMS™) is a noninvasive screening method developed to identify movement deficiencies in individuals using fundamental exercises (Cook et al., 2006a; Cook et al., 2006b). FMS™ testing has expanded from the clinical setting to athletic settings with the aim of preventing injury and predicting athletic performance (Kiesel et al., 2007). However, the usefulness of the FMS™ testing to predict injury or performance has been debated (Kiesel et al., 2007; Kiesel et al., 2014; O’Connor et al., 2011; Bushman et al., 2015: Bushman et al., 2016).
The FMS™ is comprised of seven movements including the deep squat (DS), active straight-leg raise (ASLR), in-line lunge (IL), hurdle step (HS), shoulder mobility (SM), trunk stability push-up (TSP), and rotary stability (RS). These movements place the individual in different positions, with the idea that these positions will allow imbalances and strength asymmetries to be identified when proper stability and mobility are not utilized. A score of 14 or less out of a composite score of 21 on the FMS™ has been reported as a cutoff score that may predict those at high risk of musculoskeletal injury.
Previous studies have demonstrated a relationship between body mass index (BMI) (Duncan et al., 2013: Perry & Koehle, 2013) as well as percent body fat (Nicolozakes et al., 2018) and FMS™ composite scores. Recently, Nicolozakes et al. (2018) examined FMS™ and percent body fat in collegiate football players. In a sample of 38 male freshman National Collegiate Athletic Association Division I football players, the authors reported that percent body fat determined using dual X-ray absorptiometry was negatively associated with the FMS™ composite score. Given these results, we decided to examine FMS™ scores in 227 players in the National Football League (NFL) who had also undergone determination of body composition using DXA. We categorized the NFL players into position groups (Linemen = offensive and defensive linemen; LB/TE/RB = linebackers, tight ends, and running backs; QB/PK = quarterbacks and placekickers, and WR/DB = wide receivers and defensive backs). The descriptive statistics for the NFL players can be found in Table 1.
The boxplots for FMS composite scores by position group are displayed in Figure 1. The Linemen’s FMS Composite score (13.3±2.5) was significantly (p<0.01) lower than the FMS composite scores for LB/RB/TE (14.5±1.9), QB/PK (15.7±1.8), and WR/DB (15.5±1.7) (Figure 1). There were no significant differences between the FMS composite scores for the other position groups. Similar to what Nicolozakes et al. (2018) reported in collegiate football players, there was a negative correlation between both BMI (r = -0.464, p<0.01) and percent body fat (r = -0.449, p<0.01) in the NFL players.
What is interesting is the correlation between BMI and percent body fat in Table 2 shows that only the Lineman position group had a significant relationship between the FMS™ composite score and BMI and percent body fat. For the other position groups there was no significant relationship between the FMS composite score and BMI or percent body fat.
Looking at the FMS™ composite score in greater detail table 3 presents the FMS™ scores for the seven specific tests. Examining the table you will notice that only the ASLR, TSP and the RS-specific tests discovered differences among the position groups. On average, the Lineman position group was significantly lower than the other position groups.
TAKE-HOME MESSAGE
A relationship between body mass index as well as percent body fat and the FMS™ composite score was observed in these NFL players. This relationship was driven by those individuals that made up the Lineman position group (i.e., offensive lineman, defensive lineman). The question one has to ask is whether the lower score observed in the Lineman position group is an indicator of a greater risk of injury or simply due to the fact that these individuals are limited in performing the FMS™ specific tests due to their size. Finally, it is possible that the FMS™ is not sensitive enough in this population to discern differences among the other position groups.
REFERENCES
Cook G, Burton L, Hoogenboom B. Pre-participation screening: the use of fundamental movements as an assessment of function— part 1. N Am J Sports Phys Ther. 2006a;1(2):62–72.
Cook G, Burton L, Hoogenboom B. Pre-participation screening: the use of fundamental movements as an assessment of function— part 2. N Am J Sports Phys Ther. 2006b;1(3):132–139.
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;5-11. doi: 10.1186/2052-1847-5-11.
Kiesel K, Plisky PJ, Voight ML. Can serious injury in professional football be predicted by a preseason functional movement screen? N Am J Sports Phys Ther. 2007;2(3):147–158.
Kiesel KB, Butler RJ, Plisky PJ. Prediction of injury by limited and asymmetrical fundamental movement patterns in American football players. J Sport Rehabil. 2014;23(2):88–94.
O’Connor FG, Deuster PA, Davis J, Pappas CG, Knapik JJ. Functional movement screening: predicting injuries in officer candidates. Med Sci Sports Exerc. 2011;43(12):2224–2230.
Bushman TT, Grier TL, Canham-Chervak MC, Anderson MK, North WJ, Jones BH. Pain on functional movement screen tests and injury risk. J Strength Cond Res. 2015;29(suppl 11):S65–S70.
Bushman TT, Grier TL, Canham-Chervak M, Anderson MK, North WJ, Jones BH. The functional movement screen and injury risk: association and predictive value in active men. Am J Sports Med. 2016;44(2):297–304.
Perry FT, Koehle MS. Normative data for the functional movement screen in middle-aged adults. J Strength Cond Res. 2013;27(2):458–462.
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;27:431-437.
About the Author
Donald Dengel, Ph.D., is a Professor in the School of Kinesiology at the University of Minnesota and is a co-founder of Dexalytics. He serves as the Director of the Laboratory of Integrative Human Physiology, which provides clinical vascular, metabolic, exercise and body composition testing for researchers across the University of Minnesota.