SEARCH

SEARCH BY CITATION

Keywords:

  • American football;
  • pediatrics;
  • injury

Abstract

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References

Objectives:  Limited research exists describing youth football injuries, and many of these are confined to specific regions or communities. The authors describe U.S. pediatric football injury patterns receiving emergency department (ED) evaluation and compare injury patterns between the younger and older youth football participants.

Methods:  A retrospective analysis of ED data on football injuries was performed using the National Electronic Injury Surveillance System–All Injury Program. Injury risk estimates were calculated over a 5-year period (2001–2005) using participation data from the National Sporting Goods Association. Injury types are described for young (7–11 years) and adolescent (12–17 years) male football participants.

Results:  There were an estimated total of 1,060,823 visits to U.S. EDs for males with football-related injuries. The most common diagnoses in the younger group (7–11 years) were fracture/dislocation (29%), sprain/strain (27%), and contusion (27%). In the older group (ages 12–17 years), diagnoses included sprain/strain (31%), fracture/dislocation (29%), and contusion (23%). Older participants had a significantly higher injury risk of injury over the 5-year study period: 11.0 (95% confidence interval [CI] = 9.2 to 12.8) versus 6.1 (95% CI = 4.8 to 7.3) per 1,000 participants/year. Older participants had a higher injury risk across all categories, with the greatest disparity being with traumatic brain injury (TBI), 0.8 (95% CI = 0.6 to 1.0) versus 0.3 (95% CI = 0.2 to 0.4) per 1,000 participants/year.

Conclusions:  National youth football injury patterns are similar to those previously reported in community and cohort studies. Older participants have a significantly higher injury risk, especially with TBI.

American football is a popular sport, with an estimated 11.9 million participants in 2006 and 5 million frequent (40 +  days/year) participants.1 Young and adolescent (ages 7–17 years) football participants comprise an estimated 53.4% of this total, or approximately 6.35 million participants.1 Young athletes, when compared to older athletes, have a higher body surface–to–mass ratio, open physes, and immature motor skills, all of which can contribute to greater injury.2 Injuries in the young athlete can have significant consequences in later life based on the unique physiology of rapidly growing children,3,4 including limb length discrepancies and early osteoarthritis.5

Previously published research on football injuries has been primarily focused on injuries of high school6–11 or collegiate athletes.10,12,13 Several prospective cohort studies have examined injuries in the youth football programs of individual communities over one or two seasons.3,4,14–18 Most of these were smaller studies, with the largest including 5,128 young football participants.3 Currently, there is very limited information about youth football injuries on a national scale. Furthermore, to our knowledge there are no studies that directly compare the youngest participants to adolescent and high school participants. These deficits are compounded by problems with generalizability due to large variations in injury reporting between studies. This is due in part to the challenge of defining what constitutes an injury in this group.9 The classification of “injured participants” in the literature is varied and has been defined in terms of the sport (missed all or a portion of a game or practice), by self-assertion, by testament of an athletic trainer or coach, or by seeking medical treatment. Additionally, the amount of exposure has been calculated in varying manners including any participation, by number of games, by number of game minutes, or by number of plays. Given the increasing levels of participation in football and the lack of nationwide data on youth football injuries, we examined national injury patterns in youth and adolescent football participants who underwent emergency department (ED) evaluation and compared injury patterns of very young participants with those of adolescents.

Methods

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References

Study Design

This was an ecologic study design using data from both the National Electronic Injury Surveillance System–All Injury Program (NEISS-AIP) and National Sporting Goods Association (NSGA) for patients treated in U.S. EDs from January 1, 2001, through December 31, 2005. The Rhode Island Hospital Committee on the Protection of Human Subjects determined the study protocol to be exempt from institutional review board review.

Study Setting and Population

Data were obtained from the NEISS-AIP, which is a collaborative effort between the U.S. Consumer Product Safety Commission and the Centers for Disease Control and Prevention (CDC) National Center for Injury Prevention and Control. Data on injury-related visits are obtained by NEISS-AIP from a national sample of 66 out of 100 NEISS hospitals. This sample is selected by NEISS-AIP as a stratified probability sample of hospitals in the United States and its territories with a minimum of six beds and a 24-hour ED.19–23 The sample includes separate strata for very large, large, medium, and small hospitals and children’s hospitals based on the number of ED visits. NEISS-AIP collects data on initial visits for all categories of injuries treated in U.S. EDs and provides data on nearly 500,000 injury-related ED visits annually. It is intended to provide national incidence estimates of all categories and external causes of nonfatal injuries and poisonings treated in U.S. hospital EDs and cannot be used to provide regional, state, or local estimates.

National Sporting Goods Association’s Sports Participation Program is an annual mailed survey assessing the number of individuals 7 years of age or older who participated in different sports within the previous year. The program has a panel of 300,000 households that is balanced on a number of characteristics, including household size, composition, income, age of household head, and location. From this panel, 20,000 households are selected each year and mailed a self-administered questionnaire. In an effort to return a sample that is representative of the U.S. population, households selected are balanced with oversampling of lower “return rate” segments. Survey response rates average over 70%.1

Measurements

The NEISS-AIP collects information on the date of treatment, patient age, diagnosis, body part injured, patient disposition, locale in which the injury occurred, and type of sport or product associated with the injury. Incident locale is coded by NEISS-AIP as home, farm/ranch, street or highway, other public property (includes store, office building, restaurant, church, hotel, motel, hospital or other medical facility, nightclub, theater, or other public property), mobile home, industrial place, school, place of recreation or sports, or not recorded. Football-related injuries were identified using the NEISS-AIP hierarchical category for sports injuries and were limited to football (nonsoccer)-related injuries. For the present study, only injuries that occurred at school or at a place of recreation or sports were included. Two age groupings were used for analysis: 7–11 years and 12–17 years. These were intended to approximate elementary school age and middle/high school age. Because injury frequencies in female football participants were low, analyses involving NEISS estimates were considered unreliable, and we therefore performed our analyses using only males. Injury diagnoses as provided by NEISS-AIP were used, with the following exceptions: fractures and dislocations were combined into a single category (“fracture/dislocation”); “laceration” was recoded to include the NEISS categories of lacerations, punctures, and avulsions, and “contusions/abrasions” was recoded to include the NEISS categories contusions/abrasions and hematoma. We generated a diagnosis category “traumatic brain injury” (TBI) and recoded into that category NEISS-AIP diagnosis codes for concussion, for internal injury in which “head” was the body part affected and for fracture in which “head” was the body part affected.24 Diagnoses other than the leading five diagnoses were recoded into the “other” category.

Injury rates were calculated using participation data from the Sports Business Research Network1 and are derived from annual reports provided by the NSGA. The NSGA conducts annual mail-based surveys of 20,000 preselected U.S. households, collecting self-reported sports participation data for U.S. residents. Eligible participants include household members ≥7 years of age who report participation in tackle football at least once during the 12-month period. Data collected include age, sex, and sports participated in during the previous 12 months. Participation numbers are grouped into age ranges and include the same age groups: 7–11 and 12–17 years. These data were available for the entire study period. The number of football-related injuries per 1,000 participants during the study period was calculated using these participation data and NEISS-AIP data for 2001–2005.

Data Analysis

Data were analyzed with SAS (Version 9.1.3, SAS Institute, Inc., Cary, NC) using the survey procedures to account for the complex sampling design and the weighting structure utilized by NEISS-AIP. Each case is assigned a sample weight by NEISS-AIP based on the inverse probability of selection. These weights were used to calculate national estimates of nonfatal injuries. Consistent with the NEISS-AIP recommendations,23 we designated estimates as unreliable when computations are based on fewer than 20 NEISS cases (based on unweighted data), individual national estimates are less than 1,200 (based on weighted data), or the coefficient of variation (CV) of the estimate is greater than 30%.

Injury risk for the 5-year study period was calculated using the weighted estimates from NEISS-AIP data and the total participation data in each age group during the study period and then averaged across all years. Confidence intervals (CIs) and CVs were calculated by using a direct variance estimation procedure that accounted for the sample weights.

Results

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References

From 2001 to 2005, there were an estimated 1,111,917 ED visits for children aged 7 through 17 years for football-related injuries occurring at school or sport/recreation (Table 1). Males represented the large majority of these injuries (n = 1,060,823). The number of injuries in male 12- to 17-year-old participants was approximately four times that of younger participants during the study period. The overall male injury risk over the 5-year study period for ages 7–17 was approximately 9.5 per 1,000 participants/year (95% CI = 7.9 to 11.1). The annual injury risk during the study years for the older participants group (12–17 years) and the younger participants (7–11 years) is depicted in Figure 1.

Table 1.   Demographics of Football Injuries in Athletes Presenting to EDs, United States, 2001–2005
CharacteristicNNational Estimate*%
  1. ED = emergency department.

  2. *Based on National Electronic Injury Surveillance System–All Injury Program (NEISS-AIP) weights.

Total21,2511,111,917
7–11 years old
 Male4,654206,14994.3
 Female28014,6505.7
 Total4,934220,799100.0
12–17 years old
 Male15,688854,67496.1
 Female62936,4443.9
 Total16,317891,118100.0
image

Figure 1.  Annual injury risk for male football participants presenting to emergency departments (EDs), by age group, United States, 2001–2005.

Download figure to PowerPoint

The younger male participants had an injury risk of approximately 6.1 per 1,000 participants/year (95% CI = 4.8 to 7.3; Table 2). Fracture was the most common diagnosis, followed closely by sprain/strain and contusion. Commonly injured body parts in the younger participants included arm/hand (43.0%), followed by leg/foot (23.7%) and head/neck (19.0%).

Table 2.   Football Injury Characteristics of Male Participants Presenting to EDs by Age Group, United States, 2001–2005
CharacteristicMalesInjury Risk Ratio‡
Age 7–11 yearsAge 12–17 years
n*Injury Risk† (95% CI)n*Injury Risk† (95% CI)
  1. ED = emergency department; TBI = traumatic brain injury.

  2. *Based on National Electronic Injury Surveillance System-All Injury Program (NEISS-AIP) weights.

  3. †Injury risk expressed per 1,000 participants/year.

  4. ‡Injury risk ratio = age 12–17 injury risk/age 7–11 injury risk.

Total injuries206,1496.1 (4.8, 7.3)854,67411.0 (9.2, 12.8)1.8
Injuries by diagnosis
 Fracture/dislocation60,4111.8 (1.4, 2.2)248,9403.2 (2.6, 3.8)1.8
 Sprain/strain56,4991.7 (1.3, 2.5)261,0843.3 (2.8, 3.9)1.9
 Contusion55,8331.7 (1.3, 2.5)196,5692.5 (2.1, 3.0)1.5
 Laceration13,3930.4 (0.3, 0.5)47,1390.6 (0.5, 0.7)1.5
 TBI10,9770.3 (0.2, 0.4)64,4580.8 (0.6, 1.0)2.7
 Other8,9770.3 (0.1, 0.4)36,2900.5 (0.3, 0.7)1.7
Injuries by mechanism
 Struck by/against100,4143.0 (2.3, 3.6)410,4385.3 (4.3, 6.2)1.8
 Overexertion35,5831.1 (0.8, 1.3)184,2662.4 (2.0, 2.2)2.2
 Fall37,2721.1 (0.8, 1.4)112,2091.4 (1.1, 1.8)1.3
 Unknown/unspecified/other32,8811.0 (0.7, 1.3)147,7621.9 (1.5, 2.3)1.9

The overall injury risk over the 5-year study period for the older male participants’ group was 11.0 per 1,000 participants/year (95% CI = 9.2 to 12.8; Table 2). The most common diagnoses were sprain/strain, fracture, and contusion. The most common body part injured was arm/hand, with 37.4% of all injuries. Other common sites of injury included leg/foot (27.4%) and head/neck (17.4%).

In examining the injury risk ratios of the two groups (Table 2), the overall injury risk ratio for the 5-year period between groups was 1.8, with the older age group demonstrating a higher risk of injury across all types of injuries. When examining the injuries by ED diagnosis, older participants were 2.7 times more likely to have a TBI, almost twice as likely to suffer a strain or sprain (1.9), and 1.8 times more likely to experience a fracture when compared with the younger participants. Fracture, which was the leading diagnosis in the younger group, was replaced by sprain/strain as the leading diagnosis in the older group. Younger participants had a higher proportion of arm/hand injuries (43.0% vs. 37.4%), but injury site distribution was fairly similar in both groups (Table 3).

Table 3.   Proportions for Body Parts by Age Group of Football Injuries Presenting to U.S. EDs, 2001–2005
Injuries by Body PartAge 7–11 YearsAge 12–17 Years
National Estimate*% of Total 95% CINational Estimate*% of Total 95% CI
  1. ED = emergency department.

  2. *Based on National Electronic Injury Surveillance System–All Injury Program (NEISS-AIP) weights.

  3. †National estimates less than 1,200 cases are considered unreliable by NEISS.

Head/neck39,22519.016.8, 21.3148,95517.416.1, 18.8
Arm/hand88,50943.040.6, 45.3319,07437.436.2, 38.5
Upper trunk21,19410.38.7, 11.9117,56113.813.0, 14.5
Lower trunk8,0153.93.0, 4.830,7913.63.1, 4.1
Leg/foot48,74523.721.9, 25.4233,59927.326.1, 28.6
Other   316†0.10.0, 0.44,2940.50.3, 0.7

Discussion

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References

Previous research describing football injuries has been largely confined to examining cohorts over one or two seasons, usually from a single community or region. To our knowledge, our study is the first to use a nationally representative data set to describe injuries to young football participants that require ED evaluation and then compare them to older adolescent football participants.

Previous research has identified that many injuries incurred by football participants are minor.3,16 Our finding that fractures are the most common injury diagnosis in the younger age group and second most common in the older age group most likely reflects the increased level of acuity with this database of injuries receiving ED evaluation. It should be noted, however, that using ED-treated injuries does create some difficulty in comparing our findings with previous research on youth football injuries.

Over the 5-year study period, we found that older youths (ages 12–17 years) appear to have an increasing annual injury risk, while the younger participants had a relatively constant injury risk. We do not have an explanation for this, but can speculate that over this 5-year period, adolescent football participants may have been at increasing risk of injury due to less conditioning, increased weight resulting in more force, increased length of playing seasons, or playing more aggressively or because of adolescent football rule modifications. This worrisome trend in the older age group encompasses high school football programs, programs that already have been reported to have the highest injury rate for high school athletics.25 Additional research will be needed to determine if this trend continues and whether more focused analysis for its causative factors is warranted.

In comparing injury diagnoses in the older group with the younger group, we found that TBI, sprain/strain, and fracture/dislocation were significantly more common in the older age group. This is troublesome given that TBI and fracture/dislocation are two of the most serious injury diagnoses. Others have also reported that increasing age is associated with increasing risk of fracture,17,18 and Shankar et al.10 have noted that injured high school football participants have a greater proportion of fractures and concussions than collegiate football athletes. Furthermore, this is consistent with Powell and Barber-Foss,26 who found that high school football accounts for the majority (63%) of mild TBI in all high school athletics.

Arm/hand was the location with the highest proportion of injuries in our study in both age groups. This is consistent with previous studies of younger participants,3,14,18,27 but conflicts with the findings of several high school football studies that reported the lower extremity to be the most common site.6,7,9–11 Again, this may reflect the difference in our data set, which includes only injuries resulting in an ED evaluation, so does not include injuries treated only on the field.

Our findings support the need for continued efforts in injury prevention and control directed at youth football. Radelet et al.27 asserted that “youth football should be a priority for injury studies,” and we concur. Furthermore, these findings suggest the need to direct further prevention efforts within the sport. Others have made recommendations regarding mechanisms for reducing sports injuries including preparticipation physicals, sporting event medical coverage, adequate training of coaches, adequate hydration, enforcement of game rules, and proper equipment.2,28 Although these approaches have already been used with some success in football,25,28 these interventions need to be continually modified and then tested specifically within this age group to further reduce injury risk in young athletes.

Limitations

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References

Our estimates of injury involve some potential biases associated with the use of NEISS-AIP for injury frequency and NSGA’s participation data. By examining NEISS-AIP ED data, we underestimate minor football injuries that are not treated in an ED setting. Although these minor injuries have less serious medical consequences, they still may restrict participation, as well as cause pain. Similarly, other significant injuries might be evaluated primarily by a specialist or in an office-based practice or by an on-field physician and not be evaluated in the ED.

The NEISS-AIP allows for only the most severe injury to be coded in the case of multiple injuries and thus may underreport less serious injuries. Conversely, extreme injuries resulting in fatalities are not fully captured in NEISS-AIP (patients who were dead on arrival or died in the ED are excluded) and were excluded from our analysis. Thus, we cannot make any inference from our data on the incidence of fatal injury occurrence in the study population. All of these factors would lead to an underestimation of the frequency of injuries and injury rate.

By restricting location codes to school and place of recreation or sport, we attempted to minimize the potential for including injuries not occurring in organized football settings. While it is likely that we nevertheless included some nonorganized football injuries, and this would lead to overestimation of the problem, it is also possible that we missed organized football injuries that were not coded as football related. This possibility could offset any overestimation, although we cannot be sure where the balance lies.

The participation data are a self-reported mail survey of a nationally representative sample. A participant was included if reporting participation at least one time over the past 12 months. Thus, the numbers may overestimate the number of participants, causing a bias of underreporting rates. In addition, using the NSGA’s data for participation for participants 7–17 years in calculating injury rates has the limitation of not accounting for sampling error. Our denominator was not considered a random variable; it was assumed that the denominator was our population parameter or, simply, our sample size. We recognize that this is an assumption of utilizing an ecologic study design, but currently there is no better way to estimate the number of adolescents playing football in the United States. All of our analyses were done using visits to an ED by young and adolescent male football participants and are not necessarily extrapolated to female participants in these age groups.

Conclusions

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References

Our analysis of nationally representative data of football injuries treated in EDs is similar to previously reported findings in communities and cohorts, with older participants having a significantly higher injury risk. We found this relationship of increased injury risk with increasing age to be especially true for the potentially more serious injury diagnoses of TBI and fractures. These results and future research in this area should be used to guide subsequent injury reduction measures in this age group.

References

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitations
  7. Conclusions
  8. References
  • 1
    Sports Business Research Network. Football-Tackle Market Research Results: Participation. 2007. Available at: http://www.sbrnet.com/research.asp?subRID=150. Accessed Apr 15, 2008.
  • 2
    Adirim TA, Cheng TL. Overview of injuries in the young athlete. Sports Med. 2003; 33:7581.
  • 3
    Goldberg B, Rosenthal PP, Robertson LS, Nicholas JA. Injuries in youth football. Pediatrics. 1988; 81:25561.
  • 4
    Roser LA, Clawson DK. Football injuries in the very young athlete. Clin Orthop Relat Res. 1970; 69:21923.
  • 5
    Marshall SW, Golightly YM. Sports injury and arthritis. N C Med J. 2007; 68:4303.
  • 6
    DeLee JC, Farney WC. Incidence of injury in Texas high school football. Am J Sports Med. 1992; 20:57580.
  • 7
    Powell JW, Barber-Foss KD. Injury patterns in selected high school sports: a review of the 1995–1997 seasons. J Athl Train. 1999; 34:27784.
  • 8
    Prager BI, Fitton WL, Cahill BR, Olson GH. High school football injuries: a prospective study and pitfalls of data collection. Am J Sports Med. 1989; 17:6815.
  • 9
    Ramirez M, Schaffer KB, Shen H, Kashani S, Kraus JF. Injuries to high school football athletes in California. Am J Sports Med. 2006; 34:114758.
  • 10
    Shankar PR, Fields SK, Collins CL, Dick RW, Comstock RD. Epidemiology of high school and collegiate football injuries in the United States, 2005–2006. Am J Sports Med. 2007; 35:1295303.
  • 11
    Turbeville SD, Cowan LD, Owen WL, Asal NR, Anderson MA. Risk factors for injury in high school football players. Am J Sports Med. 2003; 31:97480.
  • 12
    Boden BP, Tacchetti RL, Cantu RC, Knowles SB, Mueller FO. Catastrophic head injuries in high school and college football players. Am J Sports Med. 2007; 35:107581.
  • 13
    Dick R, Ferrara MS, Agel J, et al. Descriptive epidemiology of collegiate men’s football injuries: National Collegiate Athletic Association Injury Surveillance System, 1988–1989 through 2003–2004. J Athl Train. 2007; 42:22133.
  • 14
    Dompier TP, Powell JW, Barron MJ, Moore MT. Time-loss and non-time-loss injuries in youth football players. J Athl Train. 2007; 42:395402.
  • 15
    Linder MM, Townsend DJ, Jones JC, Balkcom IL, Anthony CR. Incidence of adolescent injuries in junior high school football and its relationship to sexual maturity. Clin J Sport Med. 1995; 5:16770.
  • 16
    Malina RM, Morano PJ, Barron M, Miller SJ, Cumming SP, Kontos AP. Incidence and player risk factors for injury in youth football. Clin J Sport Med. 2006; 16:21422.
  • 17
    Stuart MJ, Morrey MA, Smith AM, Meis JK, Ortiguera CJ. Injuries in youth football: a prospective observational cohort analysis among players aged 9 to 13 years. Mayo Clin Proc. 2002; 77:31722.
  • 18
    Turbeville SD, Cowan LD, Asal NR, Owen WL, Anderson MA. Risk factors for injury in middle school football players. Am J Sports Med. 2003; 31:27681.
  • 19
    U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, et al. National Electronic Injury Surveillance System All Injury Program, 2001 [computer file]. ICPSR version: ICPSR03817-v1. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Injury Prevention and Control [producer], 2003. Ann Arbor MI: Inter-university Consortium for Political and Social Research [distributor]; Nov 3, 2003.
  • 20
    U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, et al. National Electronic Injury Surveillance System All Injury Program, 2002 [computer file]. ICPSR version: ICPSR04085-v1. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Injury Prevention and Control [producer], 2004. Ann Arbor MI: Inter-university Consortium for Political and Social Research [distributor]; Oct 1, 2004.
  • 21
    U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, et al. National Electronic Injury Surveillance System All Injury Program, 2003 [computer file]. ICPSR version: ICPSR04352-v1. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Injury Prevention and Control [producer], 2005. Ann Arbor MI: Inter-university Consortium for Political and Social Research [distributor]; Nov 14, 2005.
  • 22
    U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, et al. National Electronic Injury Surveillance System All Injury Program, 2004 [computer file]. ICPSR version: ICPSR04598-v1. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Injury Prevention and Control [producer], 2006. Ann Arbor MI: Inter-university Consortium for Political and Social Research [distributor]; Nov 21, 2006.
  • 23
    U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, et al. National Electronic Injury Surveillance System All Injury Program, 2005 [computer file]. ICPSR version: ICPSR21280-v1. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Injury Prevention and Control [producer], 2007. Ann Arbor MI: Inter-university Consortium for Political and Social Research [distributor]; Nov 12, 2007.
  • 24
    Xiang H, Sinclair SA, Yu S, Smith GA, Kelleher K. Case ascertainment in pediatric traumatic brain injury: challenges in using the NEISS. Brain Inj. 2007; 21:2939.
  • 25
    Comstock RD, Knox CL, Yard EE. Sports-related injuries among high school athletes-United States. 2005–2006 School year. MMWR Morb Mortal Wkly Rep. 2006; 55:103740.
  • 26
    Powell JW, Barber-Foss KD. Traumatic brain injury in high school athletes. JAMA. 1999; 282:95863.
  • 27
    Radelet MA, Lephart SM, Rubinstein EN, Myers JB. Survey of the injury rate for children in community sports. Pediatrics. 2002; 110:e28.
  • 28
    Hergenroeder AC. Prevention of sports injuries. Pediatrics. 1998; 101:105763.