Exposure to Head Impacts and Cognitive and Behavioral Outcomes in Youth Tackle Football Players Across 4 Seasons

Key Points

Question  Are repetitive head impacts in youth tackle football across 4 years of play associated with cognitive and behavioral difficulties?

Findings  In this cohort study including 70 male participants aged 9 to 12 years, few associations were found between cumulative head impacts and cognitive and behavioral outcomes, and no associations were seen consistently or became more prominent over the years.

Meaning  Because head impacts were not associated with measured outcomes, these findings suggest that other factors, including premorbid medical conditions, should be further explored.

Importance  Repetitive head impacts have been posited to contribute to neurocognitive and behavioral difficulties in contact sport athletes.

Objective  To identify associations between cognitive and behavioral outcomes and head impacts measured in youth tackle football players over 4 seasons of play.

Design, Setting, and Participants  This prospective cohort study was conducted from July 2016 through January 2020, spanning 4 football seasons. The setting was a youth tackle football program and outpatient medical clinic. Players were recruited from 4 football teams composed of fifth and sixth graders, and all interested players who volunteered to participate were enrolled. Data analysis was performed from March 2020 to June 2021.

Exposures  Impacts were measured using helmet-based sensors during practices and games throughout 4 consecutive seasons of play. Impacts were summed to yield cumulative head impact gravitational force equivalents per season.

Main Outcomes and Measures  Ten cognitive and behavioral measures were completed before and after each football season.

Results  There were 70 male participants aged 9 to 12 years (mean [SD] age, 10.6 [0.64] years), with 18 completing all 4 years of the study. At the post–season 1 time point, higher cumulative impacts were associated with lower self-reported symptom burden (β = −0.6; 95% CI, −1.0 to −0.2; P = .004). After correcting for multiple comparisons, no other associations were found between impacts and outcome measures. At multiple times throughout the study, premorbid attention-deficit/hyperactivity disorder, anxiety, and depression were associated with worse cognitive or behavioral scores, whereas a premorbid headache disorder or history of concussion was less often associated with outcomes.

Conclusions and Relevance  In this cohort of youth tackle football players, premorbid conditions, including attention-deficit/hyperactivity disorder, anxiety, and depression, were associated with cognitive and behavioral outcomes more often than cumulative impact.

Repetitive subconcussive head impacts during childhood have been implicated in the development of chronic cognitive and behavioral problems. However, both retrospective^1-7 and prospective^8-12 research studies have yielded conflicting results regarding the association between repetitive head impacts and cognitive and behavioral outcomes.

Previous studies^8-10,13 in pre–high school athletes have generally examined 1 year of head impact exposure. We conducted a 4-year prospective study in youth tackle football players. We previously reported few associations between measured head impacts and neurobehavioral outcomes over the course of 3 seasons of play.¹¹ The current study sought to identify associations between cognitive and behavioral outcomes and head impacts measured in youth tackle football players over 4 seasons of play.

This cohort study was approved by the IntegReview institutional review board. Written consent and assent were obtained from a parent and all participants, respectively. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

A local youth tackle football program was identified through community engagement; the program leadership and coaches expressed interest in participating in research examining the safety of youth tackle football. The fifth and sixth grade teams were selected for this study at the recommendation of the coaches to prioritize young age but also large team size. Players entering the fifth and sixth grades were enrolled in the summer of 2016 and followed through the fall football seasons of 2016 (season 1), 2017 (season 2), 2018 (season 3), and 2019 (season 4). Players dropped out of the study if they stopped playing football or if they did not attend preseason or postseason testing visits.

Head impacts were monitored using helmet-based Riddell InSite sensors during practices and games. InSite sensors were first developed to quantify blunt force trauma and overpressurization from military blast injuries.¹⁴ They characterize linear acceleration using ferroelectret films that produce an electrical charge that is proportional to the deformation of the sensor during an impact event. The relationship between sensor deformation and head acceleration is based on direct comparison testing showing a strong correlation between InSite sensors and accelerometers embedded in Hybrid III head forms (r², 0.900-0.963).¹⁵ In the current study, a head impact was defined as any impact detected by the InSite sensor. During season 1, the sensors detected impacts greater than or equal to 10 gravitational force equivalents (g). As a result of a change in the manufacturer’s software to account for changes in the manufacturing process of the ferroelectret film, during seasons 2 to 4 the sensors detected impacts greater than or equal to 15g. The cumulative impact for each player for each season was calculated according to previously reported methods.^11,12

Before and after each football season, players completed several cognitive and behavioral assessments (Table 1). The Medical Symptom Validity Test was used at each visit to screen for response validity.

Previous medical diagnoses, including headaches, migraines, attention-deficit/hyperactivity disorder (ADHD), anxiety, depression, and number of prior concussions, were recorded at the pre–season 1 visit. Interval concussions were documented at follow-up visits. At the final post–season 4 visit, players reported whether they played other contact sports (defined as wrestling, ice hockey, soccer, lacrosse, or rugby).

Three players were excluded from statistical analyses at the corresponding assessment time point because of Medical Symptom Validity Test failure (2 players before season 1 and 1 player after season 1). Because of missing impact data, additional players were excluded from statistical analyses involving the corresponding season’s cumulative impact (9 players in season 1 and 3 players in season 4).

In previous reports,^9,11,12 we found several outcome measures suggesting a potential association with cumulative impact. On the basis of these results and associations found in other studies,^8,16 we narrowed the list of outcome measures in the current analysis to the 10 most likely to be affected by repetitive head impacts (Table 1).

To examine the potential for attrition bias, independent-samples 2-sided t tests and χ² tests were used to compare the players who were included in the final post–season 4 analysis and the players who contributed data to fewer time points. Linear mixed models were used to examine change in outcome measures over time. Linear mixed models with fixed-effect factors of premorbid medical diagnoses assessed whether outcome trends varied by diagnoses over time. The Wald χ² statistic was used to determine the effect of time as a discrete measure and then analyzed as a series of pairwise comparisons among the estimated marginal means. Multivariable linear regressions were used to determine the association of cumulative head impact with each outcome measure, controlling for premorbid medical diagnoses. Each analysis accounted for the changing sample size over time and the cumulative nature of the head impact data with each subsequent season. These models included all head impacts measured prior to any given time point.

Significance was defined as α < .05. All statistical analyses were performed using SPSS statistical software for Mac version 24.0 (IBM Corporation) and R statistical software version 4.0.3 (R Project for Statistical Computing). Data analysis was performed from March 2020 to June 2021.

Seventy male players aged 9 to 12 years (mean [SD] age, 10.6 [0.64] years) from a single youth tackle football program enrolled and completed the pre–season 1 assessment; 18 players completed all 4 years of the study. Age, mean cumulative impact per season, and preenrollment medical diagnoses are shown in Table 2. During each of the 4 seasons, 1 player received a diagnosis of concussion, with the same player sustaining a concussion in seasons 2 and 3. For each diagnosed concussion, symptoms had resolved and the player was medically cleared before completing their postseason assessment. Premorbid diagnoses, pre–season 1 outcome measures, and cumulative impacts in season 1 did not differ between players who completed all 4 years of the study and those who dropped out (eTable 1 in the Supplement).

Most outcome measures improved over time except for Test of Variables of Attention Response Time Variability (Wald χ²₇ = 4.86; P = .68) and Sport Concussion Assessment Tool–3 Total (Wald χ²₇ = 6.08; P = .53), which did not change over time. The Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Rating Scale Total fluctuated over time (Wald χ²₇ = 15.57; P = .03). The CogState Processing Speed worsened over time (Wald χ²₇ = 79.02; P < .001).

When assessing the association of cumulative impact measured in all previous years up to each assessment time point, few associations were significant (Table 3). Higher cumulative impact was associated with lower Sport Concussion Assessment Tool–3 symptom scores after season 1 and before season 2, but higher scores before season 3. At the pre–season 3 time point, higher cumulative impact was also associated with worse concentration on Test of Variables of Attention. Once a Bonferroni correction was applied (P < .05/10 or .005), only the association with the post–season 1 Sport Concussion Assessment Tool–3 score remained significant (β = −0.6; 95% CI, −1.0 to −0.2; P = .004). When playing other contact sports was added to the model as a covariate, a few specific associations were identified only at pre–season 2, but no other statistically significant associations were detected between cumulative impact and outcome measures or between playing other contact sports and outcome measures.

Players with premorbid medical conditions performed worse on several outcome measures during the study period (eTable 2 in the Supplement). For example, players with a history of ADHD performed worse on Wechsler Abbreviated Scale of Intelligence Full-Scale Intelligence Quotient–2, Wechsler Intelligence Scale for Children 5th Edition Digits, Test of Variables of Attention Response Time Variability, CogState Processing Speed, Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Rating Scale Total, and Strengths and Difficulties Questionnaire Total Difficulties, with the between-group difference often becoming more prominent as the study progressed. Players with a history of anxiety or depression had worse scores on the Wechsler Abbreviated Scale of Intelligence Full-Scale Intelligence Quotient–2 or Strengths and Difficulties Questionnaire Total Difficulties at 6 of 8 and 5 of 8 time points, respectively.

Some previous retrospective studies^3,4 have suggested that exposure to repetitive head impacts in tackle football before the age of 12 years is associated with neurobehavioral and cognitive problems later in life. However, other studies^1,2,6,7 have found no association between earlier age of exposure to tackle football or other contact sports and deleterious outcomes. Additionally, current high school and collegiate athletes with head impact exposure before age 12 years have not been shown to have worse neurocognitive performance than those with exposure after age 12 years.¹⁷

Here we contribute evidence from children who were aged 9 to 12 years at enrollment that repetitive head impacts in youth tackle football were not found to be associated with neurocognitive performance or behavioral outcomes. Although outcomes on a computerized measure of processing speed (CogState) declined over the course of this study, a well-validated measure of processing speed (Wechsler Intelligence Scale for Children 5th Edition coding) improved over time, and neither change was associated with head impacts. To our knowledge, this is the longest prospective study to date to measure head impacts and neurocognitive outcomes in youth contact sport athletes. Consistent with the first 3 years of this study, our findings from 4 seasons of play did not identify an association between cumulative head impact and neurocognitive outcomes.

This study has limitations that should be considered. First, premorbid medical diagnoses were reported by the player and a parent, but formal diagnostic criteria were not verified. Second, the attrition of players over time limited the statistical power in the final years of the study. To reduce the effect of the decreasing sample size over time and to reduce the likelihood of type I error associated with multiple comparisons, we analyzed only the 10 outcome measures conceptually associated with repetitive head impacts. In addition, players who dropped out of the study did not differ from those who continued through all 4 years. Third, all impact sensors have limitations, and we have previously described the characteristics of the Riddell InSite sensors.^9,11,12 We did not confirm each helmet impact with video recordings of practices and games. Fourth, although this was a prospective study spanning 4 years, we were unable to determine long-term neurocognitive outcomes in our participants. Future prospective studies could measure head impacts and monitor outcomes throughout life.

In conclusion, we did not find compelling evidence that cumulative head impacts across 4 years of play are associated with neurocognitive function in youth tackle football players. Rather, self-reported medical diagnoses, especially ADHD, anxiety, and depression, were consistently associated with worse neurocognitive outcomes. Over time, neurocognitive performance appears to be influenced by comorbid medical diagnoses more than by repetitive head impacts.

Accepted for Publication: October 29, 2021.

Published: December 30, 2021. doi:10.1001/jamanetworkopen.2021.40359

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Rose SC et al. JAMA Network Open.

Corresponding Author: Sean C. Rose, MD, Child Neurology, Nationwide Children’s Hospital, The Ohio State University, 700 Children’s Dr, Columbus, OH, 43205 (sean.rose@nationwidechildrens.org).

Author Contributions: Dr Rose had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Rose, Yeates, McCarthy.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Rose, Nguyen.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Nguyen, Ercole.

Obtained funding: Rose.

Administrative, technical, or material support: Pizzimenti, McCarthy.

Supervision: Rose, Ercole, McCarthy.

Conflict of Interest Disclosures: This study was investigator-initiated, and no authors have a financial interest in Riddell. Dr Yeates reported receiving grants from Canadian Institutes of Health Research outside the submitted work. Ms Pizzimenti reported holding shares in Reven and having a patent (20200390743) issued outside the submitted work. No other disclosures were reported.

Funding/Support: MORE Foundation funded the study and provided staff and administrative support. Riddell and ElMindA provided grants and equipment to MORE Foundation.

Role of the Funder/Sponsor: ElMindA did not have a role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Riddell manufactures the helmet impact sensors used in this study. Riddell did not have a role in the design and conduct of the study; management, analysis, and interpretation of the data; preparation or approval of the manuscript; and decision to submit the manuscript for publication. Riddell aided in data collection only by maintaining and servicing the helmet sensors used. Riddell reviewed the manuscript only to ensure the accuracy of terminology related to the helmet sensors.

Additional Contributions: The Sports Neurology Clinic/Kutcher Clinic helped obtain funding and provided clinic space, equipment, and staff to support data collection. Brighton High School and Brighton Bulldogs Football and Cheer and their football coaches and staff assisted with data collection. Andrew Cavey, ATC (Brighton High School), helped with data collection. The following individuals from The Sports Neurology Clinic/Kutcher Clinic helped with data collection: Jacob Greer, ATC, Erik Beltran, MD, Anthony Savino, MD, Ashley Dunn, MA, Shirley King, Kate Essad, MD, Sandro Corti, MD, Stephanie Alessi, MD, Rebecca Kahn, PA, and Miesty Woodburn, MD. Taylour Aungst, BS (Nationwide Children’s Hospital), helped with table creation. These individuals were not compensated for this work beyond their normal salaries.