PREDICTORS OF LOWER EXTREMITY INJURIES IN VARSITY ATHLETES
Timothy A. Burkhart1,2, Alison Schinkel-Ivy1, David M. Andrews1,2
Department of Kinesiology, University of Windsor, Windsor, ON, Canada
2
Department of Industrial and Manufacturing Systems Engineering, University of Windsor
1
INTRODUCTION
The magnitude of tibial shock has been shown to affect the risk
of injury in athletes [1]. The mass of shank tissues (muscle, fat,
bone) have also been shown to have a significant effect on
properties of the shock after traveling through the leg [2].
However, the effect that the tissue masses have on lower
extremity injuries and whether they have any interacting effects
with other previously determined risk factors such as race,
physical activity level and sport, has not been considered to
date. Therefore, the purpose of this study was to determine the
significant predictors of lower extremity injury in varsity
athletes with emphasis on leg tissue masses and tissue mass
ratios.
METHODS
Male and female basketball (BB) (M=18, F=9), volleyball (VB)
(F=10), soccer (S) (M=29 F=7) and cross-country (CC) (M=18,
F=13) varsity athletes participated in this study. Data were
collected on 86 variables, including demographics, physical
activity history, medication use, footwear (categorized as
wearing different footwear in games and practices), playing
surface and injury history, over the course of their respective
seasons. Tissue mass prediction equations [3] were used to
calculate the lean mass (LM), fat mass (FM), wobbling mass
(WM) and bone mineral content (BMC) of the lower
extremities. Injuries were reported by athletes and confirmed by
two certified athletic therapists. Stress fractures were also
confirmed by an orthopedic surgeon. Injuries were first
categorized generally (left and right leg separately) and then
divided into bone and soft tissue injuries. Logistic regression
analysis was used to determine the multivariate predictors of
lower extremity bone and soft tissue injuries.
RESULTS
Overall, 36% of the athletes reported an injury, of which, 15%
were considered bone injuries. In general, sport and playing
surface were significant injury predictors, with BB athletes
(OR=0.11) and athletes who play on hardwood (OR=0.13) at a
lower risk of sustaining any type of injury (Table 1). With
respect to tissue mass ratios, left leg LM:BMC (OR=0.028) was
the best predictor, suggesting that as the ratio of LM to BMC
increased, the risk of injury decreased. The best predictors of
injuries to bone were leg FM:BMC (OR=1.80) and left foot
LM:FM (OR=0.63). Interestingly, athletes who reported
wearing different footwear in games and practices were 4 times
more likely to sustain an injury to the bone (OR=4.02).
DISCUSSION
The influence of sport on lower extremity injuries could be
indicative of the different loading patterns across sports. For
example, BB players are subjected to impacts from both
running and jumping whereas S players and CC athletes are
subjected to forces strictly from running. This suggests that
variation in loading patterns may be beneficial to athletes.
However, the type of playing surface may also explain why BB
and VB players are at a decrease risk of injury as they compete
and practice exclusively on the more compliant hardwood
surfaces. The results also suggest that inconsistent use of
footwear may have implications for the leg in terms of how it
can adequately adapt its protective muscle tuning effects [4].
This may lead to increases in the magnitude of shock that travels
through the leg, which has been implicated in lower extremity
injuries [1]. Finally, it appears that an optimal level of BMC
exists and that a leg with more muscle than fat surrounding the
bone is better suited to increasing the attenuation of shock
waves as they progress proximally through the leg after impact.
REFERENCES
[1] Milner, C.E. et al. (2006). Med. Sci. Sport Exer., 38, 323328.
[2] Schinkel, A. et al. (2009). Proceedings of the 22nd ISB
Congress, Cape Town, South Africa.
[3] Holmes, J. et al. (2005). J. Appl. Biomech., 21, 371-382.
[4] Wakeling J. M. et al. (2002). Med. Sci. Sport Exer. 34,
1529-1532.
ACKNOWLEDGEMENT
Thanks to NSERC for funding this project.
Table 1: Summary of lower extremity injury predictors (OR=Odds ratio; CI=Confidence interval) (* X 2<0.05; † p<0.05).
Variable
Category
n
Uninjured
Injured
95% CI
Sport*
BB /CC
31/27
85.1%/41.9%
14.2%/ 58.1%
0.1
0.1-0.7
Different Footwear*
No/Yes
52/51
73.1% / 49.0%
26.9% / 51.0%
2.0
0.5-9.0
Playing surface*
Hardwood/Mondo
39/25
82.1% / 40.0%
17.9 % / 60.0%
0.13
0.0-0.8
Left leg LM:BMC†
106
11.9
12.0
0.03
0.0-0.8
Left leg FM:BMC
106
2.0
2.7
1.9
1.1-3.1
Left foot LM:BMC
106
3.9
3.7
0.9
0.8-0.9