Head Impact Exposure in Youth Football: High School Ages 14 to 18 Years and Cumulative Impact Analysis

Abstract

Sports-related concussion is the most common athletic head injury with football having the highest rate among high school athletes. Traditionally, research on the biomechanics of football-related head impact has been focused at the collegiate level. Less research has been performed at the high school level, despite the incidence of concussion among high school football players. The objective of this study is to twofold: to quantify the head impact exposure in high school football, and to develop a cumulative impact analysis method. Head impact exposure was measured by instrumenting the helmets of 40 high school football players with helmet mounted accelerometer arrays to measure linear and rotational acceleration. A total of 16,502 head impacts were collected over the course of the season. Biomechanical data were analyzed by team and by player. The median impact for each player ranged from 15.2 to 27.0 g with an average value of 21.7 (±2.4) g. The 95th percentile impact for each player ranged from 38.8 to 72.9 g with an average value of 56.4 (±10.5) g. Next, an impact exposure metric utilizing concussion injury risk curves was created to quantify cumulative exposure for each participating player over the course of the season. Impacts were weighted according to the associated risk due to linear acceleration and rotational acceleration alone, as well as the combined probability (CP) of injury associated with both. These risks were summed over the course of a season to generate risk weighted cumulative exposure. The impact frequency was found to be greater during games compared to practices with an average number of impacts per session of 15.5 and 9.4, respectively. However, the median cumulative risk weighted exposure based on combined probability was found to be greater for practices vs. games. These data will provide a metric that may be used to better understand the cumulative effects of repetitive head impacts, injury mechanisms, and head impact exposure of athletes in football.

Head-Impact–Measurement Devices: A Systematic Review

“…Collegiate football athletes sustained 420 to 1177 impacts, 48,55 with 9.4 impacts per session 49 at a median linear magnitude of 19g 50 and average 73 Linear magnitudes averaged 26g, 71 with a median of 22g. 74 Angular magnitudes averaged 71,72 1627 to 1694 rad/s 2 and had a median value 74 of 973 rad/s 2 .…”

Abnormal White Matter Integrity Related to Head Impact Exposure in a Season of High School Varsity Football

“…The biomechanical metric computed from the HITS data for this study was the risk-weighted cumulative exposure (RWE). 31 This metric is defined as the collected risk of concussion over the course of the season. The risk of concussion for each impact for each player was calculated using three different risk functions previously described in the literature.…”

“…5,27,28,30,31 Studies of head impact exposure for high school and youth football populations are only now beginning to emerge. 3,[32][33][34] These demonstrate accelerations, even for the youngest players, approaching those of collegiate athletes.…”

The Influence of Head Impact Threshold for Reporting Data in Contact and Collision Sports: Systematic Review and Original Data Analysis

“…53 The on-field assessment of head impacts has been captured with a head impact telemetry system (HITS) (Simbex, LLC, Lebanon, NH) using helmet mounted accelerometers enabling determination of the head linear and rotational accelerations in American football, 23,24,26,32,80,119 ice hockey 90,112 and in a headband in youth soccer. 45 The data collected through the HITS has enabled analytical risk functions, 88,[92][93][94] concussion risk curves, 94 and risk weighted exposure metrics 107 to be developed further assisting in the identification of sports participants at risk of concussive injuries. More recently, a publication utilized an instrumented mouthguard known as the XGuard (X2biosystems, Inc., Seattle, WA, USA) in rugby union.…”

“…10g 96 10g Y Y Beckwith et al 8 14 13 14.4g Y Y Y Cobb et al 20 14 23 14.4g Y Daniel et al 27 14.4g 94 14.4g Y Talavage et al 103 14.4g Urban et al 107 14 119 14 Total number of impacts and impacts not included for published studies based on the percentage of impacts removed compared with a10g impact threshold using data analysis of New Zealand senior rugby players.…”