Introduction: : Concussions are a common sports-related injury, with an estimated 1.6 to 3.8 million sports-related concussions occurring each year in the United States [1]. Concussion risk functions have the potential to reduce concussion incidence by aiding in helmet design and the development of new injury prevention methods. Given the variations in concussion tolerance between different age groups and sexes, concussion risk functions should be population-based to allow for the creation of targeted interventions. While concussion risk functions have been previously developed for youth and collegiate male football players, there are currently no risk functions using injury data from female athletes. Although sex differences in concussions are widely documented, with female athletes having higher concussion injury rates across matched sports such as hockey, softball/baseball, basketball, and soccer [2], there is limited biomechanical data collected from concussive head impacts in female athletes. Therefore, the objective of this study was to estimate a concussion risk function for female athletes by scaling a concussion risk function previously developed for male collegiate football players using published concussion biomechanical data collected from female athletes. The male concussion risk function was developed using head acceleration data collected with the Head Impact Telemetry (HIT) System, and a logistic regression was used to model concussion risk as a function of peak linear acceleration (PLA) and peak rotational acceleration (PRA) (Eq. 1) [3].
Materials and
Methods: : The female concussion risk function was developed by scaling the male concussion risk function using acceleration data from four concussions in female hockey players collected with the HIT System by Wilcox et. al [4]. First, the tolerance ratio for concussion between male and female athletes was calculated by dividing the average PLA and PRA for concussions in male athletes by the average PLA and PRA for concussions in female athletes. The male concussion risk function was then scaled by multiplying the PLA coefficient, PRA coefficient, and interaction coefficient by the corresponding tolerance ratios (Eq. 2). This method of scaling assumes that the shape of the concussion risk function is similar between male and female athletes.
The scaled female concussion risk function was used to assess concussion risk in 3 equestrian helmet models: the Champion Revolve X-Air MIPS Peaked, Charles Owen Halo MIPS, and Kask Kooki. Helmets were impacted on the front, back, and side at 4.0 m/s on a pendulum impactor, and the front boss and rear boss at 6.56 m/s on an oblique drop tower (Figure 1). Each impact configuration was tested twice, and their resulting accelerations were averaged. The same location was never impacted twice on the same helmet. Both testing systems used a NOCSAE headform instrumented with a six-degree-of-freedom sensor package. Within testing systems, the resultant PLAs and PRAs from all impact tests were averaged for each helmet, then male-specific and female-specific concussion risk was estimated using the risk functions.
Results, Conclusions, and Discussions:: The tolerance ratio between male and female concussions was 2.4 for PLA and 1.8 for PRA, showing that male athletes sustain concussions at much higher PLAs and PRAs than female athletes on average. Concussion risk was estimated to be much higher in female athletes for the three tested equestrian helmet models (Figure 2). For example, the Charles Owens Halo MIPS had a concussion risk of 4% for male athletes and 98% for female athletes for pendulum impacts at 4.0 m/s and a concussion of risk of 72% for male athletes and 100% for female athletes for oblique impacts at 6.56 m/s. These data suggest a need for sex-specific helmet designs.
Although the female concussion risk function was based on data from a small number of concussive head impacts collected by Wilcox et. al., these head impacts were similar in severity to concussive head impacts measured by Kieffer et. al in female collegiate rugby players [5]. Kieffer et. al. used sensor-instrumented mouthguards to monitor head impacts during four seasons of rugby and collected data from three concussion events. Concussions in female rugby players had PLAs ranging from 24.0 g to 57.5 g, which is similar to the 30.4 g to 53.3 g range measured by Wilcox et. al. in female hockey players.
Acknowledgements and/or References (Optional):: References [1] Langlois, J. A., W. Rutland-Brown, and M. M. Wald. The epidemiology and impact of traumatic brain injury: A brief overview. The Journal of head trauma rehabilitation 21: 375-378, 2006. [2] Covassin, T., R. Moran, and R. Elbin. Sex differences in reported concussion injury rates and time loss from participation: An update of the national collegiate athletic association injury surveillance program from 2004–2005 through 2008–2009. Journal of athletic training 51: 189-194, 2016. [3] Rowson, S., S. M. Duma, J. G. Beckwith, J. J. Chu, R. M. Greenwald, J. J. Crisco, P. G. Brolinson, A. C. Duhaime, T. W. McAllister, and A. C. Maerlender. Rotational head kinematics in football impacts: An injury risk function for concussion. Ann Biomed Eng 40: 1-13, 2012. https://doi.org/10.1007/s10439-011-0392-4 [4] Wilcox, B. J., J. G. Beckwith, R. M. Greenwald, J. J. Chu, T. W. McAllister, L. A. Flashman, A. C. Maerlender, A. C. Duhaime, and J. J. Crisco. Head impact exposure in male and female collegiate ice hockey players. J Biomech 47: 109-14, 2014. https://doi.org/10.1016/j.jbiomech.2013.10.004 [5] Kieffer, E. E. and S. Rowson. Implementing head impact sensors in collegiate men’s and women’s rugby: Successes and challenges in characterizing concussion. 2022.
