scholarly journals Practice type effects on head impact in collegiate football

2016 ◽  
Vol 124 (2) ◽  
pp. 501-510 ◽  
Author(s):  
Bryson B. Reynolds ◽  
James Patrie ◽  
Erich J. Henry ◽  
Howard P. Goodkin ◽  
Donna K. Broshek ◽  
...  
Keyword(s):  
National Collegiate Athletic Association ◽  
Collegiate Athletes ◽  
Head Impact ◽  
Football Players ◽  
Rotational Acceleration ◽  
Event Type ◽  
Cumulative Impact ◽  
Head Impacts ◽  
Average Impact ◽  
Collegiate Football

OBJECT This study directly compares the number and severity of subconcussive head impacts sustained during helmet-only practices, shell practices, full-pad practices, and competitive games in a National Collegiate Athletic Association (NCAA) Division I-A football team. The goal of the study was to determine whether subconcussive head impact in collegiate athletes varies with practice type, which is currently unregulated by the NCAA. METHODS Over an entire season, a cohort of 20 collegiate football players wore impact-sensing mastoid patches that measured the linear and rotational acceleration of all head impacts during a total of 890 athletic exposures. Data were analyzed to compare the number of head impacts, head impact burden, and average impact severity during helmet-only, shell, and full-pad practices, and games. RESULTS Helmet-only, shell, and full-pad practices and games all significantly differed from each other (p ≤ 0.05) in the mean number of impacts for each event, with the number of impacts being greatest for games, then full-pad practices, then shell practices, and then helmet-only practices. The cumulative distributions for both linear and rotational acceleration differed between all event types (p < 0.01), with the acceleration distribution being similarly greatest for games, then full-pad practices, then shell practices, and then helmet-only practices. For both linear and rotational acceleration, helmet-only practices had a lower average impact severity when compared with other event types (p < 0.001). However, the average impact severity did not differ between any comparisons of shell and full-pad practices, and games. CONCLUSIONS Helmet-only, shell, and full-pad practices, and games result in distinct head impact profiles per event, with each succeeding event type receiving more impacts than the one before. Both the number of head impacts and cumulative impact burden during practice are categorically less than in games. In practice events, the number and cumulative burden of head impacts per event increases with the amount of equipment worn. The average severity of individual impacts is relatively consistent across event types, with the exception of helmet-only practices. The number of hits experienced during each event type is the main driver of event type differences in impact burden per athletic exposure, rather than the average severity of impacts that occur during the event. These findings suggest that regulation of practice equipment could be a fair and effective way to substantially reduce subconcussive head impact in thousands of collegiate football players.

scholarly journals Magnitude of Head Impact Exposures in Individual Collegiate Football Players

2012 ◽  
Vol 28 (2) ◽  
pp. 174-183 ◽  
Author(s):  
Joseph J. Crisco ◽  
Bethany J. Wilcox ◽  
Jason T. Machan ◽  
Thomas W. McAllister ◽  
Ann-Christine Duhaime ◽  
...  
Keyword(s):  
Cognitive Deficits ◽  
Linear Acceleration ◽  
Head Impact ◽  
Football Players ◽  
Rotational Acceleration ◽  
Head Impacts ◽  
Factors Associated ◽  
Impact Location ◽  
Collegiate Football

The purpose of this study was to quantify the severity of head impacts sustained by individual collegiate football players and to investigate differences between impacts sustained during practice and game sessions, as well as by player position and impact location. Head impacts (N = 184,358) were analyzed for 254 collegiate players at three collegiate institutions. In practice, the 50th and 95th percentile values for individual players were 20.0 g and 49.5 g for peak linear acceleration, 1187 rad/s2 and 3147 rad/s2 for peak rotational acceleration, and 13.4 and 29.9 for HITsp, respectively. Only the 95th percentile HITsp increased significantly in games compared with practices (8.4%, p = .0002). Player position and impact location were the largest factors associated with differences in head impacts. Running backs consistently sustained the greatest impact magnitudes. Peak linear accelerations were greatest for impacts to the top of the helmet, whereas rotational accelerations were greatest for impacts to the front and back. The findings of this study provide essential data for future investigations that aim to establish the correlations between head impact exposure, acute brain injury, and long-term cognitive deficits.

scholarly journals Frequency and Location of Head Impact Exposures in Individual Collegiate Football Players

2010 ◽  
Vol 45 (6) ◽  
pp. 549-559 ◽  
Author(s):  
Joseph J. Crisco ◽  
Russell Fiore ◽  
Jonathan G. Beckwith ◽  
Jeffrey J. Chu ◽  
Per Gunnar Brolinson ◽  
...  
Keyword(s):  
National Collegiate Athletic Association ◽  
Median Number ◽  
Head Impact ◽  
Clinical Aspects ◽  
Brain Concussion ◽  
Head Impacts ◽  
Session Type ◽  
Subconcussive Impacts ◽  
Player Positions ◽  
Collegiate Football

Abstract Context: Measuring head impact exposure is a critical step toward understanding the mechanism and prevention of sport-related mild traumatic brain (concussion) injury, as well as the possible effects of repeated subconcussive impacts. Objective: To quantify the frequency and location of head impacts that individual players received in 1 season among 3 collegiate teams, between practice and game sessions, and among player positions. Design: Cohort study. Setting: Collegiate football field. Patients or Other Participants: One hundred eighty-eight players from 3 National Collegiate Athletic Association football teams. Intervention(s): Participants wore football helmets instrumented with an accelerometer-based system during the 2007 fall season. Main Outcome Measure(s): The number of head impacts greater than 10g and location of the impacts on the player's helmet were recorded and analyzed for trends and interactions among teams (A, B, or C), session types, and player positions using Kaplan-Meier survival curves. Results: The total number of impacts players received was nonnormally distributed and varied by team, session type, and player position. The maximum number of head impacts for a single player on each team was 1022 (team A), 1412 (team B), and 1444 (team C). The median number of head impacts on each team was 4.8 (team A), 7.5 (team B), and 6.6 (team C) impacts per practice and 12.1 (team A), 14.6 (team B), and 16.3 (team C) impacts per game. Linemen and linebackers had the largest number of impacts per practice and per game. Offensive linemen had a higher percentage of impacts to the front than to the back of the helmet, whereas quarterbacks had a higher percentage to the back than to the front of the helmet. Conclusions: The frequency of head impacts and the location on the helmet where the impacts occur are functions of player position and session type. These data provide a basis for quantifying specific head impact exposure for studies related to understanding the biomechanics and clinical aspects of concussion injury, as well as the possible effects of repeated subconcussive impacts in football.

scholarly journals Early Results of a Helmetless-Tackling Intervention to Decrease Head Impacts in Football Players

2015 ◽  
Vol 50 (12) ◽  
pp. 1219-1222 ◽  
Author(s):  
Erik E. Swartz ◽  
Steven P. Broglio ◽  
Summer B. Cook ◽  
Robert C. Cantu ◽  
Michael S. Ferrara ◽  
...  
Keyword(s):  
Repeated Measures ◽  
National Collegiate Athletic Association ◽  
Intervention Group ◽  
Control Group ◽  
Controlled Clinical Trial ◽  
Football Players ◽  
Head Impacts ◽  
Early Results ◽  
Division I Football ◽  
Collegiate Football

Objective To test a helmetless-tackling behavioral intervention for reducing head impacts in National Collegiate Athletic Association Division I football players. Design Randomized controlled clinical trial. Setting Football field. Patients or Other Participants Fifty collegiate football players (intervention = 25, control = 25). Intervention(s) The intervention group participated in a 5-minute tackling drill without their helmets and shoulder pads twice per week in the preseason and once per week through the season. During this time, the control group performed noncontact football skills. Main Outcome Measure(s) Frequency of head impacts was recorded by an impact sensor for each athlete-exposure (AE). Data were tested with a 2 × 3 (group and time) repeated-measures analysis of variance. Significant interactions and main effects (P &lt; .05) were followed with t tests. Results Head impacts/AE decreased for the intervention group compared with the control group by the end of the season (9.99 ± 6.10 versus 13.84 ± 7.27, respectively). The intervention group had 30% fewer impacts/AE than the control group by season's end (9.99 ± 6.10 versus 14.32 ± 8.45, respectively). Conclusion A helmetless-tackling training intervention reduced head impacts in collegiate football players within 1 season.

scholarly journals COMPARISON OF HEAD IMPACT BIOMECHANICS BETWEEN TACKLE AND FLAG YOUTH FOOTBALL

2019 ◽  
Vol 7 (3_suppl) ◽  
pp. 2325967119S0000
Author(s):  
Landon B. Lempke ◽  
A. Faith Bartello ◽  
Melissa N. Anderson ◽  
Rachel S. Johnson ◽  
Julianne D. Schmidt ◽  
...  
Keyword(s):  
Linear Acceleration ◽  
Head Impact ◽  
Football Players ◽  
Rotational Acceleration ◽  
Head Impacts ◽  
Head Impact Biomechanics ◽  
Impact Rate ◽  
High Magnitude ◽  
Impact Biomechanics

Background: There is growing fear among healthcare professionals and parents regarding youth tackle football, likely due to highly publicized concerns about potential long-term physical and cognitive health of professional football players. Parents and advocacy groups are pushing for state legislation to ban youth tackle football in favor of flag football to avoid repetitive head impacts that are potentially associated with late-life cognitive deficits. Although the head impact burden experienced during flag football is likely lower than tackle, no research has compared head impact exposure between youth tackle and flag football. Therefore, our purpose was to examine head impact exposure and magnitudes between youth tackle and flag football players. Methods: Twenty-seven tackle (age=11.0±1.5y, height=145.8±11.9 cm, mass=45.0±14.9 kg) and 29 flag football players (age=8.6±1.1y, height=133.9±8.4 cm, mass=33.9±9.5 kg) were enrolled in this prospective cohort study. Participants were fitted with head impact sensors (Triax Sim-G) worn throughout the entire 2017 season that recorded impact frequency and magnitude (linear [g] and rotational acceleration [rad/s2]). Athlete exposure was defined as one player participating in one session. Impact rates (IR) were calculated as impacts per one athlete exposure. Game, practice, and combined IR were compared between groups using impact rate ratios (IRR). IRR with 95% confidence intervals (CI) not containing 1.0 were considered statistically significant. Acceleration values were binned into low- and high-magnitude categories (linear split at 40 g, rotational split at 4,600rad/s2). Magnitude category frequencies were compared between groups using Chi-square test of association (p<0.05), and 90th percentile acceleration values are presented. Results: One-thousand nine-hundred and eight tackle (735 game, 1173 practice; 70.66 impacts/player) and 169 flag (101 game, 68 practice; 5.83 impacts/player) football head impacts were recorded. Tackle players experienced a higher impact rate during games versus practices (IRR=1.41; 95%CI:1.29 -1.55) while flag players experienced a lower impact rate (IRR=0.60; 95%CI:0.44-0.81). Practice and game head impacts combined resulted in tackle players (IR=3.06) accruing 4.61 times the impact rate (95%CI:3.94-5.40) of flag players (IR=0.66). Tackle players sustained a significantly greater head impact rate than flag players during games (tackle IR=3.83, flag IR=0.55; IRR=6.90; 95%CI:5.60-8.49) and practices (tackle IR=2.72, flag IR=0.93; IRR=2.91; 95%CI:2.28-3.72). Tackle 90th percentile linear acceleration was 53.32 g (median=32.50 g) and flag was 53.32 g (median=32.65 g). Tackle 90th percentile rotational acceleration was 7,000 rad/s2 (median=3,200rad/s2) while flag was 8,300 rad/s2 (median=4,100rad/s2). Tackle experienced a significantly higher frequency of low-magnitude rotational acceleration impacts (71.6% vs. 57.4%) and lower frequency of high-magnitude impacts than flag (28.4% vs 42.6%;?2=15.15, p<0.001). There were no significant associations for linear acceleration (p=0.75). Conclusions/Significance: Our results indicate youth flag football head impact rates are 82%-88% lower compared to tackle. Contrary to general belief, youth flag football players experienced numerous head impacts with a greater tendency for high-magnitude rotational acceleration head impacts. Although fewer head impacts occur during youth flag football, parents and coaches should be aware that head impacts do occur during practices and games. Whether high-magnitude or high-frequency head impacts influence long-term health remains unknown. Our findings provide novel evidence into the head impact exposure occurring during youth tackle and flag football. Longitudinal studies examining head impact biomechanics and advanced neuroimaging in youth tackle and flag football players nationwide is warranted to ensure long term cognitive health.

Head Impact Biomechanics in Youth Flag Football: A Prospective Cohort Study

2021 ◽  
pp. 036354652110266
Author(s):  
Landon B. Lempke ◽  
Rachel S. Johnson ◽  
Rachel K. Le ◽  
Melissa N. Anderson ◽  
Julianne D. Schmidt ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Acceleration ◽  
Cross Sectional Study ◽  
Head Impact ◽  
Rotational Acceleration ◽  
Event Type ◽  
Level Of Evidence ◽  
Cross Sectional ◽  
Head Impact Biomechanics ◽  
Impact Biomechanics

Background: Youth flag football participation has rapidly grown and is a potentially safer alternative to tackle football. However, limited research has quantitatively assessed youth flag football head impact biomechanics. Purpose: To describe head impact biomechanics outcomes in youth flag football and explore factors associated with head impact magnitudes. Study Design: Cross-sectional study; Level of evidence, 3. Methods: We monitored 52 player-seasons among 48 male flag football players (mean ± SD; age, 9.4 ± 1.1 years; height, 138.6 ± 9.5 cm; mass, 34.7 ± 9.2 kg) across 3 seasons using head impact sensors during practices and games. Sensors recorded head impact frequencies, peak linear ( g) and rotational (rad/s2) acceleration, and estimated impact location. Impact rates (IRs) were calculated as 1 impact per 10 player-exposures; IR ratios (IRRs) were used to compare season, event type, and age group IRs; and 95% CIs were calculated for IRs and IRRs. Weekly and seasonal cumulative head impact frequencies and magnitudes were calculated. Mixed-model regression models examined the association between player characteristics, event type, and seasons and peak linear and rotational accelerations. Results: A total of 429 head impacts from 604 exposures occurred across the study period (IR, 7.10; 95% CI, 4.81-10.50). Weekly and seasonal cumulative median head impact frequencies were 1.00 (range, 0-2.63) and 7.50 (range, 0-21.00), respectively. The most frequent estimated head impact locations were the skull base (n = 96; 22.4%), top of the head (n = 74; 17.2%), and back of the head (n = 66; 15.4%). The combined event type IRs differed among the 3 seasons (IRR range, 1.45-2.68). Games produced greater IRs (IRR, 1.24; 95% CI, 1.01-1.53) and peak linear acceleration (mean difference, 5.69 g; P = .008) than did practices. Older players demonstrated greater combined event–type IRs (IRR, 1.46; 95% CI, 1.12-1.90) and increased head impact magnitudes than did younger players, with every 1-year age increase associated with a 3.78 g and 602.81-rad/s2 increase in peak linear and rotational acceleration magnitude, respectively ( P≤ .005). Conclusion: Head IRs and magnitudes varied across seasons, thus highlighting multiple season and cohort data are valuable when providing estimates. Head IRs were relatively low across seasons, while linear and rotational acceleration magnitudes were relatively high.

scholarly journals Can helmet design reduce the risk of concussion in football?

2014 ◽  
Vol 120 (4) ◽  
pp. 919-922 ◽  
Author(s):  
Steven Rowson ◽  
Stefan M. Duma ◽  
Richard M. Greenwald ◽  
Jonathan G. Beckwith ◽  
Jeffrey J. Chu ◽  
...  
Keyword(s):  
Head Impact ◽  
Dartmouth College ◽  
University Of Minnesota ◽  
Head Impacts ◽  
University Of Oklahoma ◽  
Significant Difference ◽  
Rule Changes ◽  
Impact Data ◽  
Collegiate Football ◽  
Helmet Design

Of all sports, football accounts for the highest incidence of concussion in the US due to the large number of athletes participating and the nature of the sport. While there is general agreement that concussion incidence can be reduced through rule changes and teaching proper tackling technique, there remains debate as to whether helmet design may also reduce the incidence of concussion. A retrospective analysis was performed of head impact data collected from 1833 collegiate football players who were instrumented with helmet-mounted accelerometer arrays for games and practices. Data were collected between 2005 and 2010 from 8 collegiate football teams: Virginia Tech, University of North Carolina, University of Oklahoma, Dartmouth College, Brown University, University of Minnesota, Indiana University, and University of Illinois. Concussion rates were compared between players wearing Riddell VSR4 and Riddell Revolution helmets while controlling for the head impact exposure of each player. A total of 1,281,444 head impacts were recorded, from which 64 concussions were diagnosed. The relative risk of sustaining a concussion in a Revolution helmet compared with a VSR4 helmet was 46.1% (95% CI 28.1%–75.8%). When controlling for each player's exposure to head impact, a significant difference was found between concussion rates for players in VSR4 and Revolution helmets (χ2 = 4.68, p = 0.0305). This study illustrates that differences in the ability to reduce concussion risk exist between helmet models in football. Although helmet design may never prevent all concussions from occurring in football, evidence illustrates that it can reduce the incidence of this injury.

scholarly journals Effect of Head Impact Exposures on Changes in Cognitive Testing

2018 ◽  
Vol 6 (3) ◽  
pp. 232596711876103 ◽  
Author(s):  
Eleni Diakogeorgiou ◽  
Theresa L. Miyashita
Keyword(s):  
Reaction Time ◽  
National Collegiate Athletic Association ◽  
Assessment Tool ◽  
Vital Signs ◽  
Head Impact ◽  
Cognitive Testing ◽  
Repeated Impact ◽  
Level Of Evidence ◽  
Head Impacts ◽  
Significant Difference

Background: Gaining a better understanding of head impact exposures may lead to better comprehension of the possible effects of repeated impact exposures not associated with clinical concussion. Purpose: To assess the correlation between head impacts and any differences associated with cognitive testing measurements pre- and postseason. Study Design: Case-control study; Level of evidence, 3. Methods: A total of 34 National Collegiate Athletic Association Division I men’s lacrosse players wore lacrosse helmets instrumented with an accelerometer during the 2014 competitive season and were tested pre- and postseason with the Sport Concussion Assessment Tool (SCAT 3) and Concussion Vital Signs (CVS) computer-based neurocognitive tests. The number of head impacts >20 g and results from the 2 cognitive tests were analyzed for differences and correlation. Results: There was no significant difference between pre- and postseason SCAT 3 scores, although a significant correlation between pre- and postseason cognitive scores on the SCAT 3 and total number of impacts sustained was noted ( r = –0.362, P = .035). Statistically significant improvements on half of the CVS testing components included visual reaction time ( P = .037, d = 0.37), reaction time ( P = .001, d = 0.65), and simple reaction time ( P = .043, d = 0.37), but no correlation with head impacts was noted. Conclusion: This study did not find declines in SCAT 3 or CVS scores over the course of a season among athletes who sustained multiple head impacts but no clinical concussion. Thus, it could not be determined whether there was no cognitive decline among these athletes or whether there may have been subtle declines that could not be measured by the SCAT 3 or CVS.

scholarly journals Concussion BASICS II

Neurology ◽  
2018 ◽  
Vol 91 (23) ◽  
pp. e2123-e2132 ◽  
Author(s):  
Breton M. Asken ◽  
Russell M. Bauer ◽  
Steven T. DeKosky ◽  
Zachary M. Houck ◽  
Charles C. Moreno ◽  
...  
Keyword(s):  
Collegiate Athletes ◽  
Head Impact ◽  
Amyloid Peptide ◽  
Serum Biomarker ◽  
Cumulative Exposure ◽  
Head Impacts ◽  
Clinical Assessments ◽  
Recent Exposure ◽  
Impact Index ◽  
Concussion History

ObjectiveTo examine the effect of concussion history and cumulative exposure to collision sports on baseline serum biomarker concentrations, as well as associations between biomarker concentrations and clinical assessments.MethodsIn this observational cohort study, β-amyloid peptide 42 (Aβ42), total tau, S100 calcium binding protein B (S100B), ubiquitin carboxy-terminal hydrolyzing enzyme L1 (UCH-L1), glial fibrillary acidic protein, microtubule associated protein 2, and 2′,3′-cyclic-nucleotide 3′-phosphodiesterase serum concentrations were measured in 415 (61% male, 40% white, aged 19.0 ± 1.2 years) nonconcussed collegiate athletes without recent exposure to head impacts. Regression analyses were used to evaluate the relationship between self-reported history of concussion(s), cumulative years playing collision sports, clinical assessments, and baseline biomarker concentrations. Football-specific analyses were performed using a modified Cumulative Head Impact Index. Clinical assessments included symptom, cognitive, balance, and oculomotor tests.ResultsAthletes with a greater number of concussions had a higher baseline Aβ42 concentration only (ρ = 0.140, p = 0.005, small effect size). No biomarker concentrations correlated with cumulative exposure to collision sports. Race status fully mediated the correlations of S100B, UCH-L1, and Aβ42 with cognitive scores. Football exposure, specifically, was not associated with serum biomarker concentrations or clinical assessment scores based on the modified Cumulative Head Impact Index.ConclusionConcussion-related serum biomarkers showed no consistent association with concussion history, cumulative exposure to collision sports, or clinical assessments in a sample of healthy collegiate athletes. Serum Aβ42 concentrations could increase following multiple previous concussions. Considering race status is essential when investigating links between biomarkers and cognition. The biomarkers studied may not detect residual effects of concussion or repetitive head impact exposure in otherwise asymptomatic collegiate athletes without recent exposure to head impacts. Much more research is needed for identifying reliable and valid blood biomarkers of brain trauma history.

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