Mapping default mode connectivity alterations following a single season of subconcussive impact exposure in youth football.

Repetitive head impact (RHI) exposure in collision sports may contribute to adverse neurological outcomes in former players. In contrast to a concussion, or mild traumatic brain injury, "subconcussive" RHIs represent a more frequent and asymptomatic form of exposure. The neural network-level signatures characterizing subconcussive RHIs in youth collision-sport cohorts such as American Football are not known. Here, we used resting-state functional MRI to examine default mode network (DMN) functional connectivity (FC) following a single football season in youth players (n = 50, ages 8-14) without concussion. Football players demonstrated reduced FC across widespread DMN regions compared with non-collision sport controls at postseason but not preseason. In a subsample from the original cohort (n = 17), players revealed a negative change in FC between preseason and postseason and a positive and compensatory change in FC during the offseason across the majority of DMN regions. Lastly, significant FC changes, including between preseason and postseason and between in- and off-season, were specific to players at the upper end of the head impact frequency distribution. These findings represent initial evidence of network-level FC abnormalities following repetitive, non-concussive RHIs in youth football. Furthermore, the number of subconcussive RHIs proved to be a key factor influencing DMN FC.

Neuropsychological Change After a Single Season of Head Impact Exposure in Youth Football.

OBJECTIVES: Head impact exposure (HIE) in youth football is a public health concern. The objective of this study was to determine if one season of HIE in youth football was related to cognitive changes. METHOD: Over 200 participants (ages 9-13) wore instrumented helmets for practices and games to measure the amount of HIE sustained over one season. Pre- and post-season neuropsychological tests were completed. Test score changes were calculated adjusting for practice effects and regression to the mean and used as the dependent variables. Regression models were calculated with HIE variables predicting neuropsychological test score changes. RESULTS: For the full sample, a small effect was found with season average rotational values predicting changes in list-learning such that HIE was related to negative score change: standardized beta (ß) = -.147, t(205) = -2.12, and p = .035. When analyzed by age clusters (9-10, 11-13) and adding participant weight to models, the R2 values increased. Splitting groups by weight (median split), found heavier members of the 9-10 cohort with significantly greater change than lighter members. Additionaly, significantly more participants had clinically meaningful negative changes: X2 = 10.343, p = .001. CONCLUSION: These findings suggest that in the 9-10 age cluster, the average seasonal level of HIE had inverse, negative relationships with cognitive change over one season that was not found in the older group. The mediation effects of age and weight have not been explored previously and appear to contribute to the effects of HIE on cognition in youth football players.

The Effect of Player Contact Characteristics on Head Impact Exposure in Youth Football Games.

To reduce head impact exposure (HIE) in youth football, further understanding of the context in which head impacts occur and the associated biomechanics is needed. The objective of this study was to evaluate the effect of contact characteristics on HIE during player versus player contact scenarios in youth football. Head impact data and time-synchronized video were collected from 4 youth football games over 2 seasons in which opposing teams were instrumented with the Head Impact Telemetry (HIT) System. Coded contact characteristics included the player's role in the contact, player speed and body position, contact height, type, and direction, and head contact surface. Head accelerations were compared among the contact characteristics using mixed-effects models. Among 72 instrumented athletes, 446 contact scenarios (n = 557 impacts) with visible opposing instrumented players were identified. When at least one player had a recorded impact, players who were struck tended to have higher rotational acceleration than players in striking positions. When both players had a recorded impact, lighter players and taller players experienced higher mean head accelerations compared with heavier players and shorter players. Understanding the factors influencing HIE during contact events in football may help inform methods to reduce head injury risk.

Head Impact Exposure in Practices Correlates With Exposure in Games for Youth Football Players.

This study aimed to compare head impact exposures between practices and games in football players ages 9 to 14 years, who account for approximately 70% of all football players in the United States. Over a period of 2 seasons, 136 players were enrolled from 3 youth programs, and 49,847 head impacts were recorded from 345 practices and 137 games. During the study, individual players sustained a median of 211 impacts per season, with a maximum of 1226 impacts. Players sustained 50th (95th) percentile peak linear acceleration of 18.3 (46.9) g, peak rotational acceleration of 1305.4 (3316.6) rad·s-2, and Head Impact Technology Severity Profile of 13.7 (24.3), respectively. Overall, players with a higher frequency of head impacts at practices recorded a higher frequency of head impacts at games (P < .001, r2 = .52), and players who sustained a greater average magnitude of head impacts during practice also recorded a greater average magnitude of head impacts during games (P < .001). The youth football head impact data quantified in this study provide valuable insight into the player exposure profile, which should serve as a key baseline in efforts to reduce injury.

Relationship between Aggressiveness, Self-Confidence, and Perceived Coach Support and Head Impact Exposure in Youth Football.

This study evaluated head impact exposure (HIE) metrics in relation to individual-level determinants of HIE. Youth (n = 13) and high school (n = 21) football players were instrumented with the Head Impact Telemetry (HIT) system during one season. Players completed the Trait-Robustness of Self-Confidence Inventory (TROSCI), Sports Climate Questionnaire (SCQ), and Competitive Aggressiveness and Anger Scale (CAAS), measuring self-confidence, perceived coach support, and competitive aggressiveness, respectively. Relationships between HIE metrics (number of impacts, median and 95th percentile accelerations, and risk-weighted exposure (RWE)) and survey scores were evaluated using linear regression analysis. For middle school athletes, TROSCI scores were significantly negatively associated with the number of competition impacts and the mean number of impacts per player per competition. SCQ scores were significantly positively associated with median linear acceleration during practice. CAAS scores were not significantly associated with biomechanical metrics at either level of play. Perceived coach support and self-confidence might influence HIE among middle school football players. Football athletes' competitive aggressiveness may have less influence their HIE than other factors.

Head Impact Exposure in Youth and Collegiate American Football.

The relationship between head impact and subsequent brain injury for American football players is not well-defined, especially for youth. The objective of this study is to quantify and assess Head Impact Exposure (HIE) metrics among youth and collegiate football players. This multi-season study enrolled 639 unique athletes (354 collegiate; 285 youth, ages 9-14), recording 476,209 head impacts (367,337 collegiate; 108,872 youth) over 971 sessions (480 collegiate; 491 youth). Youth players experienced 43 and 65% fewer impacts per competition and practice, respectively, and lower impact magnitudes compared to collegiate players (95th percentile peak linear acceleration (PLA, g) competition: 45.6 vs 61.9; 95th percentile PLA practice: 42.6 vs 58.8; 95th percentile peak rotational acceleration (PRA, rad·s-2) competition: 2262 vs 4422; 95th percentile PRA practice: 2081 vs 4052; 95th percentile HITsp competition: 25.4 vs 32.8; 95th percentile HITsp practice: 23.9 vs 30.2). Impacts during competition were more frequent and of greater magnitude than during practice at both levels. Quantified comparisons of head impact frequency and magnitude between youth and collegiate athletes reveal HIE differences as a function of age, and expanded insight better informs the development of age-appropriate guidelines for helmet design, prevention measures, standardized testing, brain injury diagnosis, and recovery management.

Effect of Coach Feedback and Awareness of Head Impact Exposure on Practice Structure in Youth Football.

With the concern of concussion risk and repetitive head impacts in youth football, organizations have adopted rules that limit contact during practice. However, rule changes are not ubiquitous among organizations and are challenging to monitor and enforce. Ultimately, football practice activities are determined by coaches, but it is unknown whether providing objective data to coaches relating activities to their athletes' head impact exposure (HIE) would alter practice structure or help reduce HIE. This study evaluated the effect of coach awareness of HIE on practice structure over time. Head impact data from three intervention (56 players) and three control (38 players) teams were collected over two youth football seasons. Athletes were instrumented with the Head Impact Telemetry (HIT) System and time-synchronized video was recorded for practices and games. Impact frequencies and head accelerations were compiled into weekly HIE practice and game reports and shared with the head coach of each intervention team. Time per drill, impact rate, and impact magnitude were compared across three time frames (pre-season, mid-season, and late-season) using generalized linear models. Control teams had higher impact rates than intervention teams in all drills across time frames. Among all teams, 95th percentile linear and rotational accelerations were highest during mid-season. Among intervention teams, more time was spent on scrimmage and skill development from pre-season to late-season, with less time spent on tackling. This study suggests that receiving objective data informing HIE in practice may contribute to changes in practice structure and help inform intervention efforts to improve head impact safety in football.

Analysis of longitudinal head impact exposure and white matter integrity in returning youth football players.

OBJECTIVE: The objective of this study was to characterize changes in head impact exposure (HIE) across multiple football seasons and to determine whether changes in HIE correlate with changes in imaging metrics in youth football players. METHODS: On-field head impact data and pre- and postseason imaging data, including those produced by diffusion tensor imaging (DTI), were collected from youth football athletes with at least two consecutive seasons of data. ANCOVA was used to evaluate HIE variations (number of impacts, peak linear and rotational accelerations, and risk-weighted cumulative exposure) by season number. DTI scalar metrics, including fractional anisotropy, mean diffusivity, and linear, planar, and spherical anisotropy coefficients, were evaluated. A control group was used to determine the number of abnormal white matter voxels, which were defined as 2 standard deviations above or below the control group mean. The difference in the number of abnormal voxels between consecutive seasons was computed for each scalar metric and athlete. Linear regression analyses were performed to evaluate relationships between changes in HIE metrics and changes in DTI scalar metrics. RESULTS: There were 47 athletes with multiple consecutive seasons of HIE, and corresponding imaging data were available in a subsample (n = 19) of these. Increases and decreases in HIE metrics were observed among individual athletes from one season to the next, and no significant differences (all p > 0.05) in HIE metrics were observed by season number. Changes in the number of practice impacts, 50th percentile impacts per practice session, and 50th percentile impacts per session were significantly positively correlated with changes in abnormal voxels for all DTI metrics. CONCLUSIONS: These results demonstrate a significant positive association between changes in HIE metrics and changes in the numbers of abnormal voxels between consecutive seasons of youth football. Reducing the number and frequency of head impacts, especially during practice sessions, may decrease the number of abnormal imaging findings from one season to the next in youth football.

Psychometric properties of the standardized assessment of concussion in youth football: Validity, reliability, and demographic factors.

The objective of this study was to determine the psychometrics (reliability, validity) of the original Standardized Assessment of Concussion (SAC) in a youth sample (ages 11 to 13). Demographic factors of race, level of vocabulary knowledge, mother's level of education were also considered. Over 150 youth football athletes completed the SAC and a brief battery of NIH Toolbox cognitive tests as part of a larger study on biomechanical factors in youth sport concussion. This was a within-subjects design (pre-season, post-season assessments), and correlational analysis of convergent and discriminant validity. Between groups analysis based on demographic differences was also employed. The pre-season SAC scores were not different by age; however, SAC scores were statistically different by race: t(155) = 3.162, p = .002, d = .519. Maternal level of education and participant vocabulary scores were related to racial group membership. Convergent and discriminant validity were established compared to NIH Toolbox tests of memory and speed. Pre-post-season tests for 108 participants established marginally acceptable test-retest reliability (ICC = .692). These data support the use of the original SAC in youth football although clinicians must be aware of racial differences in scores.

Physical Performance Measures Correlate with Head Impact Exposure in Youth Football.

PURPOSE: Head impact exposure (HIE) (i.e., magnitude and frequency of impacts) can vary considerably among individuals within a single football team. To better understand individual-specific factors that may explain variation in head impact biomechanics, this study aimed to evaluate the relationship between physical performance measures and HIE metrics in youth football players. METHODS: Head impact data were collected from youth football players using the Head Impact Telemetry System. Head impact exposure was quantified in terms of impact frequency, linear and rotational head acceleration, and risk-weighted cumulative exposure metrics (RWELinear, RWERotational, and RWECP). Study participants completed four physical performance tests: vertical jump, shuttle run, three-cone, and 40-yard sprint. The relationships between performance measures, and HIE metrics were evaluated using linear regression analyses. RESULTS: A total of 51 youth football athletes (ages, 9-13 yr) completed performance testing and received combined 13,770 head impacts measured with the Head Impact Telemetry System for a full season. All performance measures were significantly correlated with total number of impacts in a season, RWELinear-Season, and all RWE-Game metrics. The strongest relationships were between 40-yard sprint speed and all RWE-Game metrics (all P ≤ 0.0001 and partial R > 0.3). The only significant relationships among HIE metrics in practice were between shuttle run speed and total practice impacts and RWELinear-Practices, 40 yard sprint speed and total number of practice impacts, and three-cone speed and 95th percentile number of impacts/practice. CONCLUSIONS: Generally, higher vertical jump height and faster times in speed and agility drills were associated with higher HIE, especially in games. Physical performance explained less variation in HIE in practices, where drills and other factors, such as coaching style, may have a larger influence on HIE.

Development of a Concussion Risk Function for a Youth Population Using Head Linear and Rotational Acceleration.

Physical differences between youth and adults, which include incomplete myelination, limited neck muscle development, and a higher head-body ratio in the youth population, likely contribute towards the increased susceptibility of youth to concussion. Previous research efforts have considered the biomechanics of concussion for adult populations, but these known age-related differences highlight the necessity of quantifying the risk of concussion for a youth population. This study adapted the previously developed Generalized Acceleration Model for Brian Injury Threshold (GAMBIT) that combines linear and rotational head acceleration to model the risk of concussion for a youth population with the Generalized Acceleration Model for Concussion in Youth (GAM-CY). Survival analysis was used in conjunction with head impact data collected during participation in youth football to model risk between individuals who sustained medically-diagnosed concussions (n = 15). Receiver operator characteristic curves were generated for peak linear acceleration, peak rotational acceleration, and GAM-CY, all of which were observed to be better injury predictors than random guessing. GAM-CY was associated with an area under the curve of 0.89 (95% confidence interval: 0.82-0.95) when all head impacts experienced by the concussed players were considered. Concussion tolerance was observed to be lower for youth athletes, with average peak linear head acceleration of 62.4 ± 29.7 g compared to 102.5 ± 32.7 g for adults and average peak rotational head acceleration of 2609 ± 1591 rad/s2 compared to 4412 ± 2326 rad/s2. These data provide further evidence of age-related differences in concussion tolerance and may be used for the development of youth-specific protective designs.

Associations between upper extremity injury patterns in side impact motor vehicle collisions with occupant and crash characteristics.

INTRODUCTION: Side impact motor vehicle collisions (MVC) represent a significant burden of mortality and morbidity caused by automotive injury within the United States. The objective of this study was to evaluate the relationship between upper extremity (UE) injury patterns and contact sources in side impact MVC with occupant and crash variables. METHODS: Crash Injury Research and Engineering Network data obtained from 1998 to 2012 were used to evaluate UE injuries in side impact crashes. First row drivers and passengers that were at least 16 years old with complete crash information were included. Side impact crashes were defined to have an area of deformation to the side of the vehicle and a principal direction of force between 60° and 120° or 240° and 300°. Injuries were stratified by type, anatomic location, and Abbreviated Injury Scale (AIS) severity. Occupant variables included age, sex, height, weight, body mass index, and Injury Severity Score. Vehicle and crash variables included in the analysis were change in vehicle velocity at the time of impact, maximum door intrusion, maximum B-pillar intrusion, seat track position, belt use, vehicle type, impact type, and injury source. Statistical analysis of the UE injury data included descriptive statistics, linear regression analyses with occupant variables, and logistic regression analyses with vehicle and crash variables. RESULTS: There were 903 UE injuries among 408 case occupants. The most common injury type was soft tissue injury (72.5%). The majority of fractures were proximal to and including the humerus (70.3%) with the clavicle being the most common fracture location (N = 89). AIS 2+ UE injuries were associated with a significantly higher mean occupant Injury Severity Score than AIS 1 UE injuries (p = 0.01). Contact with the door was the leading cause of UE injury (34.2%). The odds (OR [95% confidence interval], p-value) of an AIS 2+ UE injury due to contact with the B-pillar (5.3 [3.1, 9.1], <0.0001), door (1.9 [1.3, 2.7], 0.0006), and steering wheel/assembly (2.7 [1.1, 6.3], 0.03) were significantly higher than all other injury sources combined. Scapula fractures were significantly associated with rearward seat track positions (1.46 [1.04, 2.05], 0.03). CONCLUSIONS: This study provides insight into UE injury patterns in side impact MVC. The clavicle was the most common UE fracture location. Contact with the door resulted in the highest number of UE injuries and the B-pillar resulted in the most severe injuries. Additionally, exposure to greater B-pillar intrusion was associated with increased odds of scapula and clavicle fractures in side impacts.

In-Season Variations in Head Impact Exposure among Youth Football Players.

Head impact exposure (HIE) is often summarized by the total exposure measured during the season and does not indicate how the exposure was accumulated, or how it varied during the season. Therefore, the objective of this study was to compare HIE during pre-season, the first and second halves of the regular season, and playoffs in a sample of youth football players (n = 119, aged 9-13 years). Athletes were divided into one of four exposure groups based on quartiles computed from the distribution of risk-weighted cumulative exposure (RWECP). Mean impacts per session and mean 95th percentile linear and rotational acceleration in practices and games were compared across the four exposure groups and time frames using mixed effects models. Within games, the mean 95th percentile accelerations for the entire sample ranged from 47.2g and 2331.3 rad/sec2 during pre-season to 52.1g and 2533.4 rad/sec2 during the second half of regular season. Mean impacts per practice increased from pre-season to the second half of regular season and declined into playoffs among all exposure groups; however, the variation between time frames was not greater than two impacts per practice. Time of season had a significant relationship with mean 95th percentile linear and rotational acceleration in games (both, p = 0.01) but not with practice accelerations or impacts per session. The in-practice mean levels of 95th percentile linear and rotational acceleration remained fairly constant across the four time frames, but in games these changed over time depending on exposure group (interactions, p ≤ 0.05). The results of this study improve our understanding of in-season variations in HIE in youth football and may inform important opportunities for future interventions.

Evaluation of Brain Response during Head Impact in Youth Athletes Using an Anatomically Accurate Finite Element Model.

During normal participation in football, players are exposed to repetitive subconcussive head impacts, or impacts that do not result in signs and symptoms of concussion. To better understand the effects of repetitive subconcussive impacts, the biomechanics of on-field head impacts and resulting brain deformation need to be well characterized. The current study evaluates local brain response to typical youth football head impacts using the atlas-based brain model (ABM), an anatomically accurate brain finite element (FE) model. Head impact kinematic data were collected from three local youth football teams using the Head Impact Telemetry (HIT) System. The azimuth and elevation angles were used to identify impacts near six locations of interest, and low, moderate, and high acceleration magnitudes (5th, 50th, and 95th percentiles, respectively) were calculated from the grouped impacts for FE simulation. Strain response in the brain was evaluated by examining the range and peak maximum principal strain (MPS) values in each element. A total of 40,538 impacts from 119 individual athletes were analyzed. Impacts to the facemask resulted in 0.18 MPS for the high magnitude impact category. This was 1.5 times greater than the oblique impact location, which resulted in the lowest strain value of 0.12 for high magnitude impacts. Overall, higher strains resulted from a 95th percentile lateral impact (41.0g, 2556 rad/sec2) with two predominant axes of rotation than from a 95th percentile frontal impact (67.6g, 2641 rad/sec2) with a single predominant axis of rotation. These findings highlight the importance of accounting for directional dependence and relative contribution of axes of rotation when evaluating head impact response.

Evaluation of head impact exposure measured from youth football game plays.

OBJECTIVE: There is a growing body of literature informing efforts to improve the safety of football; however, research relating on-field activity to head impacts in youth football is limited. Therefore, the objective of this study was to compare head impact exposure (HIE) measured in game plays among 3 youth football teams. METHODS: Head impact and video data were collected from athletes (ages 10-13 years) participating on 3 youth football teams. Video analysis was performed to verify head impacts and assign each to a specific play type. Each play was categorized as a down, punt, kickoff, field goal, or false start. Kickoffs and punts were classified as special teams. Downs were classified as running, passing, or other. HIE was quantified by play type in terms of mean, median, and 95th percentile linear and rotational acceleration. Mixed-effects models were used to assess differences in acceleration among play types. Contact occurring on special teams plays was evaluated using a standardized video abstraction form. RESULTS: A total of 3003 head impacts over 27.5 games were analyzed and paired with detailed video coding of plays. Most head impacts were attributed to running (79.6%), followed by passing (14.0%), and special teams (6.4%) plays. The 95th percentile linear acceleration measured during each play type was 52.6g, 50.7g, and 65.5g, respectively. Special teams had significantly greater mean linear acceleration than running and passing plays (both p = 0.03). The most common kick result on special teams was a deep kick, of which 85% were attempted to be returned. No special teams plays resulted in a touchback, and one resulted in a fair catch. One-third of all special teams plays and 92% of all nonreturned kicks resulted in athletes diving toward the ball. CONCLUSIONS: The results demonstrate a trend toward higher head impact magnitudes on special teams than for running and passing plays, but a greater number of impacts were measured during running plays. Deep kicks were most common on special teams, and many returned and nonreturned kicks resulted in athletes diving toward the ball. These results support policy changes to youth special teams plays, including modifying the yard line the ball is kicked from and coaching proper return technique. Further investigation into biomechanical exposure measured during game impact scenarios is needed to inform policy relevant to the youth level.

Comparison of head impact exposure in practice drills among multiple youth football teams.

Objective: Limiting contact in football practice can reduce the number of head impacts a player receives, but further research is needed to inform the modification of optimal drills that mitigate head impact exposure (HIE) while the player develops the skills needed to safely play the game. This study aimed to compare HIE in practice drills among 6 youth football teams and to evaluate the effect of a team on HIE. Methods: On-field head impact data were collected from athletes (ages 10­13 years) playing on 6 local youth football teams (teams A­F) during all practices using the Head Impact Telemetry System. Video was recorded and analyzed to verify and assign impacts to a specific drill. Drills were identified as follows: dummy/sled tackling, half install, install, install walk through, multiplayer tackle, Oklahoma, one-on-one, open field tackling, other, passing, position skill work, scrimmage, special teams, tackling drill stations, and technique. HIE was quantified in terms of impacts per player per minute (ppm) and peak linear and rotational head acceleration. Generalized linear models were used to assess differences in head impact magnitude and frequency among drills as well as among teams within the most common drills. Results: Among 67 athlete-seasons, a total of 14,718 impacts during contact practices were collected and evaluated in this study. Among all 6 teams, the mean linear (p < 0.0001) and rotational (p < 0.0001) acceleration varied significantly among all drills. Open field tackling had significantly (p < 0.001) higher mean linear acceleration than all other drills. Multiplayer tackle had the highest mean impact rate (0.35 ppm). Significant variations in linear acceleration and impact rate were observed among teams within specific drills. Team A had the highest mean linear acceleration in install, one-on-one, and open field tackling and the highest mean impact rate in Oklahoma and position skill work. Although team A spent the greatest proportion of their practice on minimal- or no-player versus player contact drills (27%) compared to other teams, they had the highest median (20.2g) and 95th percentile (56.4g) linear acceleration in practice. Conclusions: Full-speed tackling and blocking drills resulted in the highest HIE. Reducing time spent on contact drills relative to minimal or no contact drills may not lower overall HIE. Instead, interventions such as reducing the speed of players engaged in contact, correcting tackling technique, and progressing to contact may reduce HIE more effectively.

Numerical investigation of driver lower extremity injuries in finite element frontal crash reconstruction.

OBJECTIVE: Lower extremity injuries are the most frequent Abbreviated Injury Scale (AIS) 2 injury for drivers in frontal crashes. The objective was to reconstruct 11 real-world motor vehicle crashes (2 with AIS 2+ distal lower extremity injury and 9 without lower extremity injury) and to analyze the vehicle parameters and driver attributes that affect injury risk. METHODS: Eleven frontal crashes were reconstructed with a finite element simplified vehicle model (SVM) using a semi-automated optimization method. The SVM was tuned to each corresponding vehicle and the Total HUman Model for Safety (THUMS) Ver 4.01 was scaled and positioned in a baseline configuration to mimic the documented precrash driver posture. The event data recorder crash pulse was applied as the boundary condition for each case. Additionally, for the 2 cases with lower extremity injury, 120 simulations to quantify the uncertainty and response variation were performed varying the following parameters using a Latin hypercube design of experiment (DOE): seat track position, seatback angle, steering column angle, steering column position, and D-ring height. Injury metrics implemented within THUMS were calculated from the femur, tibia, and ankle and cross-compared among the 11 baseline cases using tibia index and multiple injury risk functions. Kinetic and kinematic data from the 120-simulation DOE were analyzed and fit to regression models to examine any causal relationship between occupant positioning and lower extremity injury risk. RESULTS: Of the 11 real-world crashes, both cases with lower extremity injuries resulted in elevated tibia axial forces and resultant bending moments, compared to the 9 cases without lower extremity injury. The average tibia index of the 2 cases with distal lower extremity injury (left: 1.79; right: 1.19) was higher than that in the 9 cases without lower extremity injury (left: 1.16, P =.024; right: 0.82, P =.024). An increased risk of AIS 2+ tibia shaft (33.6%), distal tibia and hindfoot (20.0%), as well as ankle malleolar (14.5%) fracture was also observed for the injured compared to the noninjured cases. Rearward seat track position, reclined seat back angle, and reduced seat height were correlated with elevated tibia axial force and increased tibia index, imposing additional lower extremity injury risk. CONCLUSIONS: This study provides a computational framework for assessing lower extremity injuries and elucidates the effect of precrash driver posture on lower extremity injury risk while accounting for vehicle parameters and driver attributes. Results from the study aid in the evaluation of real-world injury data, the understanding of factors contributing to injury risk, and the prevention of lower extremity injuries.

Head Impact Exposure in Youth Football: Comparing Age- and Weight-Based Levels of Play.

Approximately 5,000,000 athletes play organized football in the United States, and youth athletes constitute the largest proportion with ∼3,500,000 participants. Investigations of head impact exposure (HIE) in youth football have been limited in size and duration. The objective of this study was to evaluate HIE of athletes participating in three age- and weight-based levels of play within a single youth football organization over four seasons. Head impact data were collected using the Head Impact Telemetry (HIT) System. Mixed effects linear models were fitted, and Wald tests were used to assess differences in head accelerations and number of impacts among levels and session type (competitions vs. practices). The three levels studied were levels A (n = 39, age = 10.8 ± 0.7 years, weight = 97.5 ± 11.8 lb), B (n = 48, age = 11.9 ± 0.5 years, weight = 106.1 ± 13.8 lb), and C (n = 32, age = 13.0 ± 0.5 years, weight = 126.5 ± 18.6 lb). A total of 40,538 head impacts were measured. The median/95th percentile linear head acceleration for levels A, B, and C was 19.8/49.4g, 20.6/51.0g, and 22.0/57.9g, respectively. Level C had significantly greater mean linear acceleration than both levels A (p = 0.005) and B (p = 0.02). There were a significantly greater number of impacts per player in a competition than in a practice session for all levels (A, p = 0.0005, B, p = 0.0019, and C, p < 0.0001). Athletes at lower levels experienced a greater percentage of their high magnitude impacts (≥ 80g) in practice, whereas those at the highest level experienced a greater percentage of their high magnitude impacts in competition. These data improve our understanding of HIE within youth football and are an important step in making evidence-based decisions to reduce HIE.

Head impact exposure measured in a single youth football team during practice drills.

OBJECTIVE This study evaluated the frequency, magnitude, and location of head impacts in practice drills within a youth football team to determine how head impact exposure varies among different types of drills. METHODS On-field head impact data were collected from athletes participating in a youth football team for a single season. Each athlete wore a helmet instrumented with a Head Impact Telemetry (HIT) System head acceleration measurement device during all preseason, regular season, and playoff practices. Video was recorded for all practices, and video analysis was performed to verify head impacts and assign each head impact to a specific drill. Eleven drills were identified: dummy/sled tackling, install, special teams, Oklahoma, one-on-one, open-field tackling, passing, position skill work, multiplayer tackle, scrimmage, and tackling drill stations. Generalized linear models were fitted to log-transformed data, and Wald tests were used to assess differences in head accelerations and impact rates. RESULTS A total of 2125 impacts were measured during 30 contact practices in 9 athletes (mean age 11.1 ± 0.6 years, mean mass 44.9 ± 4.1 kg). Open-field tackling had the highest median and 95th percentile linear accelerations (24.7 g and 97.8 g, respectively) and resulted in significantly higher mean head accelerations than several other drills. The multiplayer tackle drill resulted in the highest head impact frequency, with an average of 0.59 impacts per minute per athlete, but the lowest 95th percentile linear accelerations of all drills. The front of the head was the most common impact location for all drills except dummy/sled tackling. CONCLUSIONS Head impact exposure varies significantly in youth football practice drills, with several drills exposing athletes to high-magnitude and/or high-frequency head impacts. These data suggest that further study of practice drills is an important step in developing evidence-based recommendations for modifying or eliminating certain high-intensity drills to reduce head impact exposure and injury risk for all levels of play.

Lumbar vertebrae fracture injury risk in finite element reconstruction of CIREN and NASS frontal motor vehicle crashes.

INTRODUCTION: The objective of this study was to reconstruct 4 real-world motor vehicle crashes (MVCs), 2 with lumbar vertebral fractures and 2 without vertebral fractures in order to elucidate the MVC and/or restraint variables that increase this injury risk. METHODS: A finite element (FE) simplified vehicle model (SVM) was used in conjunction with a previously developed semi-automated tuning method to arrive at 4 SVMs that were tuned to mimic frontal crash responses of a 2006 Chevrolet Cobalt, 2012 Ford Escape, 2007 Hummer H3, and 2002 Chevrolet Cavalier. Real-world crashes in the first 2 vehicles resulted in lumbar vertebrae fractures, whereas the latter 2 did not. Once each SVM was tuned to its corresponding vehicle, the Total HUman Model for Safety (THUMS) v4.01 was positioned in 120 precrash configurations in each SVM by varying 5 parameters using a Latin hypercube design (LHD) of experiments: seat track position, seatback angle, steering column angle, steering column telescoping position, and d-ring height. For each case, the event data recorder (EDR) crash pulse was used to apply kinematic boundary conditions to the model. By analyzing cross-sectional vertebral loads, vertebral bending moments, and maximum principal strain and stress in both cortical and trabecular bone, injury metric response as a function of posture and restraint parameters was computed. RESULTS: Tuning the SVM to specific vehicle models produced close matches between the simulated and experimental crash test responses for head, T6, and pelvis resultant acceleration; left and right femur loads; and shoulder and lap belt loads. Though vertebral load in the THUMS simulations was highly similar between injury cases and noninjury cases, the amount of bending moment was much higher for the injury cases. Seatback angle had a large effect on the maximum compressive load and bending moment in the lumbar spine, indicating the upward tilt of the seat pan in conjunction with precrash positioning may increase the likelihood of suffering lumbar injury even in frontal, planar MVCs. CONCLUSION: In conclusion, precrash positioning has a large effect on lumbar injury metrics. The lack of lumbar injury criteria in regulatory crash tests may have led to inadvertent design of seat pans that work to apply axial force to the spinal column during frontal crashes.