Are specific players more likely to be involved in high-magnitude head impacts in youth football?

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OBJECTIVE

Youth football attracts approximately 3.5 million participants every year, but concern has recently arisen about the long-term effects of experiencing repetitive head accelerations from a young age due to participation in football. The objective of this study was to quantify total involvement in high-magnitude impacts among individual players in youth football practices. The authors explored the relationship between the total number of high-magnitude accelerations in which players were involved (experienced either by themselves or by other players) during practices and the number of high-magnitude accelerations players experienced.

METHODS

A local cohort of 94 youth football players (mean age 11.9 ± 1.5, mean body mass 50.3 ± 16.4 kg) from 4 different teams were recruited and outfitted with helmet-mounted accelerometer arrays. The teams were followed for one season each for a total of 128 sessions (practices, games, and scrimmages). All players involved in high-magnitude (greater than 40g) head accelerations were subsequently identified through analysis of practice film.

RESULTS

Players who experienced more high-magnitude accelerations were more likely to be involved in impacts associated with high-magnitude accelerations in other players. A small subset of 6 players (6%) were collectively involved in 230 (53%) high-magnitude impacts during practice, were involved in but did not experience a high-magnitude acceleration 78 times (21% of the 370 one-sided high-magnitude impacts), and experienced 152 (30%) of the 502 high-magnitude accelerations measured. Quarterbacks/running backs/linebackers were involved in the greatest number of high-magnitude impacts in practice and experienced the greatest number of high-magnitude accelerations. Which team a player was on was an important factor, as one team showed much greater head impact exposure than all others.

CONCLUSIONS

This study showed that targeting the most impact-prone players for individualized interventions could reduce high-magnitude acceleration exposure for entire teams. These data will help to further quantify elevated head acceleration exposure and enable data-driven interventions that modify exposure for individual players and entire teams.

ABBREVIATIONS HMA = high-magnitude acceleration; HMI = high-magnitude impact.

Article Information

Correspondence Steven Rowson: Virginia Tech, Blacksburg, VA. srowson@vt.edu.

INCLUDE WHEN CITING Published online April 26, 2019; DOI: 10.3171/2019.2.PEDS18176.

Disclosures The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper

© AANS, except where prohibited by US copyright law.

Headings

Figures

  • View in gallery

    Players who experienced more HMAs themselves were more likely to be involved in impacts associated with HMAs in other players. Spearman rank-based methods were used to calculate correlations. Players involved in HMIs could have been the striking (causing) or struck player. Dots represent individual players, line represents the Spearman correlation, and shaded area represents 95% CI for correlation.

  • View in gallery

    Distributions of HMAs received in practices over an entire season by team and position group. The thick black lines within each box represent the median, the boxes represent the interquartile range (IQR) defined as 25th–75th quartiles, and the whiskers represent the fences (1.5 × IQR). Any data points (dots) outside the fences represent outliers.

  • View in gallery

    Bar graphs showing proportion of team’s high-magnitude practice impacts in which players experienced an HMA by position.

  • View in gallery

    Bar graph showing proportion of position’s high-magnitude practice impacts in which players experienced an HMA across all teams.

  • View in gallery

    The number of HMAs experienced in games was correlated with the number of HMAs experienced in practices. Spearman rank-based methods were used to calculate correlations. Dots represent individual players, line represents the Spearman correlation, and shaded area represents 95% CI for correlation.

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