Care Sports Medicine (2nd Edition) D. McKeag
and J. Moeller (eds.),
Unit 2: Epidemiology of Athletic Injuries
Eric D. Zemper, Ph.D. and Randall W. Dick, FACSM
This unit will introduce some
fundamental concepts of epidemiology, the basic science of preventive medicine,
and its application to sports medicine, specifically the epidemiology of
athletic injuries. The word "epidemiology"
is comprised of three Greek root terms: epi (meaning
"upon"), demos ("people"), and logos
epidemiology is the study of what is upon, or befalls, a people or
population. A more formal definition is
that provided by
"Epidemiology is the study of the distribution and determinants of the varying rates of diseases, injuries, or other health states in human populations."
The basic method of studying and determining these distributions and determinants is comparing groups within a population (the sick and the well; the injured and the non-injured). Doing an epidemiological study is a lot like being a detective, using logic to discover cause and effect relationships for illnesses or other medical conditions in a population. In many ways it is similar to diagnosing an illness, but it is done with a large population rather than with an individual patient.
· Identifying the causes of disease.
· Completing the clinical picture of a disease.
· Allowing identification of syndromes.
· Determining the effectiveness of therapeutic and preventive measures.
· Providing the means to monitor the health of a community or region; i.e., input for rational health planning.
· Quantifying risks (health hazard appraisals).
· Providing an overview of long-term disease trends.
The initial development of the theory and methods of epidemiology focused on applications to communicable diseases. However, in recent years epidemiologic theory and methodologies have been applied to a broader range of subject areas, including athletic injuries. One of the primary tools in applying epidemiologic theory and methods to the study of athletic injuries is the use of the techniques of injury surveillance.
Sports injury surveillance applies the well-established principles of public health surveillance to the problem of athletic injury. Injury surveillance is not the same as injury research, although the two are similar. Injury research involves the slow and thorough accumulation of very precise data and can take years to come to fruition. By contrast, injury surveillance uses methods for the rapid collection and dissemination of data and evolves and develops to meet the ever-changing needs of the sports medicine community in general, and users of the data in particular (57). A thorough review of injury surveillance definitions and guidelines has been developed by the World Health Organization in conjunction with the Centers for Disease Control and Prevention (25).
Meeuwisse and Love (35) suggest that researchers should take the following general recommendations into consideration when collecting and publishing injury data:
The same authors (35) suggest that an “ideal” system for assessing athletic risk would include:
· simplicity and ease of use;
· flexibility to address changing patterns of injury;
· collection of athletic exposure data;
· standardized documentation of injury diagnosis, severity, treatment and associated risk factors;
· data collection by team athletic trainers who work with the team on a daily basis.
The basic tool of epidemiology is the calculation of rates of occurrence of medical cases of interest in a given population. The two most commonly used rates are incidence and prevalence. The prevalence rate includes all cases of the medical condition of interest that exist at the beginning of the study period and all new cases that develop during the study period. Incidence rates include only the newly developed cases. In sports medicine, the incidence rate is predominantly used to study athletic injuries, since it is assumed that all athletes are uninjured at the beginning of the season and it is the incidence of new injuries during the season that is of interest. Therefore, we will deal only with incidence rates here. The incidence rate is a measure of the rate at which new events (illnesses, injuries, etc.) occur during a specified time in a defined population:
Incidence Rate = (# new events during specified time period x k) ÷ # in the population at risk
The numerator is simply a count of the number of new cases that occur during the study period. The denominator is the total number of people in the population under study who are "at risk" or exposed to the possibility of infection, injury, etc. To provide reasonable numbers that are neither extremely large nor extremely small, and to make comparisons easier, this ratio is transformed to a common metric by multiplying by a convenient multiple of 10 (represented by the constant k in the above equation). If k=1,000 the result would be a rate per 1,000 in the population; if k= 100,000 the result would be a rate per 100,000. For example, suppose 24 cases of measles were reported on a college campus of 34,000 students. A moment's thought will show that stating a rate of 24/34,000 is not the most informative way of presenting this information. The probability of an individual having the disease is not readily apparent, and it is not easy to compare the rate with the five cases that occurred in the population of 630 student-athletes on that campus. The base ratio of 24/34,000 is 0.000706, which is the probability that any one individual has measles. But obviously this is not an easy number to work with. Using k=100,000 we transform this rate to 70.6 cases per 100,000, which is a little more manageable. If we make the same calculation for student-athletes, we get a case rate of 793.7 cases per 100,000. Now it is easier to see that student-athletes had a much higher rate of measles, so immediate preventive measures might be in order for this special population.
Determining the numerator of the case rate equation is usually relatively easy. The most critical part of the calculation is determining the denominator, or the "population at risk." This should include everyone in the population who could be affected by the disease or condition of interest, and should exclude those who could not be affected or are not really a member of the population of interest. For instance, in calculating a case rate for pregnancy, males, females past menopause, and females who have not reached menarche should not be used in the denominator. In calculating a case rate for football injuries during games, only those who actually played and were exposed to the possibility of injury, not the whole team, should be included in the denominator.
In sports medicine, case rates generally are used to present epidemiological information about athletic injuries. In the past these rates have been presented most often as injuries per 100 athletes, which is analogous to the rate per 100,000 population used for reporting disease rates. However, there is a difference between the continuous exposure of a population to a disease and the discrete exposure of an athlete to injury, which occurs only during practices or games. The number of practices and games varies considerably from one sport to another, and often varies from one team to another, or even from one year to another in a given sport. In addition, not every player participates in every practice and every game, and the number of participants on a team may change considerably as the season progresses. Thus, the common practice of reporting athletic injuries as a rate per 100 participants can lead to questionable conclusions, particularly when results from different sports, or even from different studies of the same sport, are compared. A more precise method is to report case rates per 1,000 athlete-exposures. An athlete-exposure is defined as one athlete participating in one practice or game where there is the possibility of sustaining an athletic injury. If a football team of 100 players has five practices during the week, there are 500 athlete-exposures to the possibility of being injured in practice during that week. If 40 players get into the game on Saturday, the team has 40 athlete-exposures in the game, and the weekly total is 540 athlete-exposures to the possibility of being injured.
Using athlete-exposures as the denominator allows more accurate and precise comparisons of injury rates between sports and in different years (13). Case rates per 1,000 athlete-exposures are currently used by the NCAA Injury Surveillance System (40) and the Athletic Injury Monitoring System (64). An even more precise approach would base the exposure rate on the amount of time actually spent in practices or games. This might be possible in small local studies but, in most cases, the amount of record keeping required for a national-scale surveillance system would be prohibitive and impractical for those doing the on-site data recording. Case rates per 1,000 athlete-exposures are believed to be a reasonable compromise that gives a more accurate picture of the epidemiology of athletic injuries than the use of simple rates per 100 athletes.
CONCERNS REGARDING PUBLISHED LITERATURE ON SPORTS INJURY RATES
A major weakness commonly seen in the published literature on athletic injury rates is that the denominator data for the incidence rate equation is poorly defined or has not been determined. This reduces these articles to simple case series reports that have little or no epidemiological value (60). Unless the calculation of rates is based on the population at risk, it is impossible to generalize the results beyond the specific population used in the study. This highlights a major problem in much of the earlier research literature on athletic injury rates, and even some of the current literature: most authors have little or no training in epidemiology, so these articles often are not of any great use on a broader scale in that the information cannot be generalized to other places and situations. For example, several years ago Powell et al. (46) did a thorough review of the literature on running injuries and found only two published articles and one meeting presentation that met minimal criteria for factors such as definition of injury, selection of subjects, and use of proper denominator data ("population at risk") in calculating injury rates.
Two to three decades ago the research literature on the epidemiology of athletic injuries was very sparse, but since the mid 1960s there has been a slow growth in sports injury rate research as the need for this type of data has become more apparent. Even so, many studies cover only one year (or season), occasionally two (47, 48). Nearly all studies have limitations imposed by sample size, covering one school or one city or one geographic area (47, 48, 52). Some studies (9, 18, 39, 49) are limited to injuries of one anatomical site, such as the knee, or one type of injury, such as fatalities or ankle sprains. Getting a clear national perspective by combining results from different studies are greatly hindered by differences in methodologies, such as dissimilar definitions of a reportable injury or different means of collecting and reporting data. Combining study results would be ill-advised in any case, because of the lack of representativeness of the combined data sources.
Still another problem with many studies is the source used to obtain injury data. Some rely on insurance claim forms (10, 11, 23), which has the disadvantage of not representing the true injury rate since not all athletic injuries result in insurance claims. Also, these records seldom contain much detail on the circumstances and mechanisms of injury. Some studies rely on a coach's assessment or recognition of an injury even though we know that, unless coaches have received specific training, they do a poor job of recognizing most treatable injuries (50). Studies that depend on recall of injuries at the end of a season have the obvious problems of inaccuracy and incompleteness of recall.
One ongoing attempt to collect national injury data is the National Electronic Injury Surveillance System conducted by the Consumer Product Safety Commission. This system collects data on product-related injuries from approximately 100 hospital emergency rooms around the country. Athletic injury records are one part of this project (53). However, athletic injury rates based on these data are questionable because not all athletic injuries are treated in an emergency room. Also, those that are treated in the ER would not be recorded if they were not product-related. Injuries from activities like running or swimming probably would go unrecorded because they do not involve a product. There also is a question of defining the population at risk, because it is not known exactly how large a population each emergency room covers. At best, this data tells us the relative proportions of the more serious types of injuries in certain activities.
It has become evident over the past twenty years that there is a need for accurate, reliable data on injury rates for various sports and exercise activities. In 1985, at a workshop on Epidemiologic and Public Health Aspects of Physical Activity and Exercise, Jeffrey P. Koplan, M.D., made the observation that there was a major lack of data on athletic injuries and on regular physical activity in general (28). With the increase in participation in organized sports and in fitness activities, participation that is encouraged by the medical community as a public health intervention, it often is not realized that even today there still is little or no dependable risk data available for these activities. A great deal of effort is focused on defining the benefits of participation of sports and fitness activities, but little is done to assess risk. This information is needed to make informed decisions about the value of taking part in a particular activity, and to provide information on how injury rates can be reduced. Therefore, it is desirable to collect data for all types of exercise and fitness activities as well as all levels of sports participation. Unfortunately, while there has been improvement in recent years in the data available for some sports activities, little or no data is available at this time for anything other than college and high school sports. A comprehensive compilation and review of the literature on sports injury epidemiology can be found in the recent book by Caine et al. (7).
MODEL SPORTS INJURY DATA COLLECTION SYSTEMS
Several sports injury data collection systems have been developed using the concept of rates discussed earlier. The following examples meet most of the criteria noted earlier for an “ideal” system, and the published reports from these systems avoid the problems noted in the previous section.
In 1931 the
American Football Coaches Association initiated the First Annual Survey of
Football Fatalities and this research has been conducted at the
Due to the success
of these two football projects, the research was expanded to all sports for
both men and women, and a
The decision to expand the research was based on the following factors:
The Center uses consistent, clear injury definitions to create a catastrophic injury database with significant application. Injury definitions include:
Catastrophic Injury - Any severe injury incurred during participation in a school/college sponsored sport involving a fatality, permanent severe functional disability or severe head or neck trauma.
Direct Injury - Those injuries resulting directly from participation in the skills of the sport, such as paralysis resulting from a football tackle.
Indirect Injury - Those injuries caused by systemic failure as a result of exertion while participating in a sport activity or by a complication that was secondary to a non-fatal injury. Catastrophic heat illness or cardiac problems would fit into this category.
Applications: Specific data may be obtained by accessing the Center’s most recent annual report at www.unc.edu/depts/nccsi. It provides data on a variety of sports and is one of the few resources on catastrophic injuries in the activity of cheerleading. Examples of sport-specific applications of this data collection as noted in the annual report are presented later in this chapter.
THE NCAA INJURY SURVEILLANCE SYSTEM (ISS)
in 1982, the NCAA Injury Surveillance System (ISS) (40) is the largest
continuous collegiate injury surveillance system in
Accessibility: The NCAA recognizes the importance of feedback and accessible data in maintaining institutional commitment to injury surveillance and impacting health and safety issues within and beyond college athletics. Participating institutions receive current year individual school, divisional and national data as well as a summary booklet that contains selected information over multiple years. Basic comparative injury information across sports also is available on the NCAA Web site (www.ncaa.org/iss.html) and through annual reports that can be obtained from the NCAA Sports Library. Plans are underway to upgrade the system to a Web-based electronic data transfer system. The goals of the ISS upgrade include:
· Creating a database that is flexible, cost effective, functional and takes advantage of current technology.
· Allowing participation by every NCAA institution, and injury tracking of every NCAA sport and out-of-season athletics activity.
· Broadening the scope of injury surveillance applications.
· Increasing membership, media and public access to ISS information.
· Enhancing the ability to quantify the impact of policy, rules or equipment changes on injury risk.
Medical and research groups should be particularly interested in the expanded breadth (across sports) and depth (increased participation within sports) that this upgrade offers. Other enhancements of interest include an accessible electronic national database that becomes a research tool for the sports medicine profession.
Application: ISS data has been referenced in a variety of scientific articles and medical texts. The system’s data also has been applied to development or modification of sports rules, policies, and issues by a variety of administrative and sports medicine groups. These efforts have led to collaboration and policy development activities with a variety of agencies, including American Medical Society for Sports Medicine (AMSSM), American College of Sports Medicine (ACSM), American Orthopaedic Society for Sports Medicine (AOSSM), Centers for Disease Control and Prevention (CDC), and the National Athletic Trainers’ Association (NATA). Such efforts have not only benefited collegiate athletics, but also the entire sports medicine community. Some specific examples are noted later.
Table 1. NCAA Injury Surveillance System Methodology
Sports Monitored. Fall -- football, field hockey, men's soccer, women's soccer, women's volleyball. Winter - men's basketball, women's basketball, wrestling, men’s ice hockey, women’s ice hockey, men's gymnastics, women's gymnastics. Spring - spring football, men's lacrosse, women's lacrosse, baseball, softball.
Sampling. Participation in the NCAA Injury Surveillance System is voluntary and limited to the 977 NCAA member institutions (as of September 2001). ISS participants are selected from the population of institutions sponsoring a given sport. Selections are random within the constraints of having an appropriate weighted sample of each NCAA division (I, II, and III) and at least 15 percent of all schools sponsoring the particular sport. It is important to emphasize that this system does not identify every injury that occurs at NCAA institutions in a particular sport. Rather, it collects a sampling that is representative of a national cross-section of NCAA institutions.
Data Reporting. Injury and exposure data are recorded by certified athletic trainers and student athletics trainers from participating institutions. Information is collected from the first official day of pre-season practice to the final tournament contest. Data are submitted weekly on paper forms to the NCAA; this information is then entered into the ISS database by national office staff.
Injuries. A reportable injury in the NCAA Injury Surveillance System is defined as one that:
(1) Occurs as a result of participation in an organized intercollegiate practice or game;
(2) Requires medical attention by a team athletic trainer or physician, and
(3) Results in any restriction of the student-athlete's participation or performance for one or more days beyond the day of injury.
Exposures. An athlete exposure (A-E), the unit of risk in the ISS, is defined as one athlete participating in one practice or game where he or she is exposed to the possibility of athletic injury.
Injury Rate. An injury rate is a ratio of the number of injuries in a particular category to the number of athlete exposures in that category. In the ISS, this value is expressed as injuries per 1,000 athlete exposures. For example, six reportable injuries during 563 practice exposures result in an injury rate of (6/563) x 1,000 or 10.7 injuries/1,000 athlete exposures. In this example, one would anticipate 10.7 injuries if one athlete participated in 1,000 practices, if 50 athletes participated in 20 practices, or if 100 athletes participated in 10 practices.
ATHLETIC INJURY MONITORING SYSTEM (AIMS)
surveillance also has been conducted on a state level, which offers the
possibility for a more specific and controlled data collection. The North
Carolina High School Athletic Injury Study (NCHSAIS) was conducted to delineate
the magnitude and scope of the injury problem among male and female athletes in
SUMMARY OF DATA FROM NATIONAL DATA COLLECTION SYSTEMS
to both ISS and AIMS was the National Athletic Injury/Illness Reporting System
(NAIRS), developed by Kenneth S. Clarke, Ph.D., at
Since NAIRS, ISS and AIMS are basically similar in format and use the same definition of a reportable injury (one occurring in a practice or contest that prevents an athlete from participating for one day or more), with data provided by on-site athletic trainers, and injury rates reported as cases per 1,000 athlete-exposures, it is possible to summarize and compare data from these three collection systems. The one sport for which data is available from all three systems is college football. Table 2 summarizes the overall football injury rates over a total of 25 seasons. The cumulative injury rates for ISS and AIMS are quite similar, whereas the earlier NAIRS rate is higher. There are several possible explanations for this difference. As noted earlier, the NAIRS sample was not as representative as the ISS and AIMS samples. It also appears there has been a general downward trend in college football injury rates over the years (37). This may be due to the major rule changes in the mid to late 1970s that were aimed at reducing the risk of major head and neck injuries (a direct result of data from the ongoing annual football fatality studies that showed an increase in major injuries during the 1960s). Along with the rule changes came shifts in coaching philosophy and technique, which have had a positive impact on injury risk, as have continuing improvements in protective equipment. Any or all of these factors may have contributed to this difference between the NAIRS data from the 1970s and the ISS/AIMS data from more recent years.
Table 2. Injury Rates in College Football
From Three National Data Collection Systems
System per 1,000 athlete-exposures Seasons
NAIRS 10.1 1977-81
ISS 6.6 1982-89
AIMS 6.6 1986-89
Sources: Buckley (1982); NCAA (1990); NCAA (2002); Zemper (1989a,d);
Zemper (2003); Zemper (unpublished data).
Based on these data showing 6.6 injuries per 1,000 athlete-exposures for college football, the average college team of 100 players can expect about two time-loss injuries every three times they take the field for a practice or game. (As we will show later, there can be major differences in injury rates between practices and games, particularly for football.) As would be expected, the body parts injured most often in college football are the knees, ankles, and shoulder, in that order. The most common types of injuries are ligament sprains, muscle strains, and contusions.
NAIRS and ISS have data from other college sports, and AIMS has data from other levels of participation besides college. Table 3 summarizes the male and female injury rates for sports covered by these systems. The data in this table cover from one to fifteen seasons, at least two or three seasons in most cases. Since these are reported in the common metric of rate per 1,000 athlete-exposures, direct comparisons are possible between sports, males and females, and different levels of a sport, as well as the different time periods represented in the table. The exceptions in this table are injury rates for taekwondo (a Korean full-contact martial art form), which are competition data only, unlike the other sports that show injury rates for practice and competition combined.
Table 3. Injury Rates for Various Sports
From Three National Data Collection Systems
Sport NAIRS ISS ISS AIMS
(1976-82) (1985-89) (2001-02)
Baseball - Men’s 1.9 3.3 3.0
Basketball - Men's 7.0 5.1 4.9
Basketball - Women's 7.3 5.0 4.7
Cross Country - Men's 1.6
Cross Country - Women's 6.7
Field Hockey - Women's 5.4 4.9 4.0
Football - Men's 10.1 6.6 6.6 6.6 (1986-90)
Gymnastics - Men's 4.3 5.1 2.1
Gymnastics - Women's 7.0 8.0 6.9
Ice Hockey - Men's 9.1 5.7 6.2
Ice Hockey - Women's 7.6
Lacrosse - Men's 5.7 6.2 4.4
Lacrosse - Women's 4.2 4.1 4.4
Soccer - Men's 9.8 7.7 7.3
Soccer - Women's 8.0 7.5
Softball - Women's 1.7 4.0 2.7
Swimming-Diving - Men's 0.9
Swimming-Diving - Women's 0.6
Tennis - Men's 1.3
Tennis - Women's 3.3
Track & Field - Men's 3.4
Track & Field - Women's 4.1
Ultimate Frisbee - Men's 5.0
Ultimate Frisbee - Women's 3.7
Volleyball - Men's 2.4
Volleyball -Women's 4.8 3.6
Wrestling - Men's 7.7 9.6 7.8
Gymnastics - Women's 3.7
Taekwondo - Men's (competition only) 27.2
Taekwondo - Women's (competition only) 22.2
Youth (6-17 years old)
Football - High School 4.9
Soccer - Boy's 2.7
Soccer - Girl's 2.1
Taekwondo - Boy's (competition only) 25.5
Taekwondo - Girl's (competition only) 28.6
Recreational (45-70 years old)
Running - Men's 11.1
Running - Women's 12.3
Walking - Men's 12.7
Weightlifting - Men's 7.0
Sources: Buckley (1982); Caine et al. (1989); NAIRS (unpublished data); NCAA (1990); NCAA (2002);
Watkins (1990); Zemper (1991); Zemper (2003); Zemper (unpublished data).
From Table 3, we can see that participants in men's wrestling, soccer, and football, and women's ice hockey, soccer and gymnastics currently have the highest overall injury rates. The injury rates for corresponding men's and women's sports generally are similar, the exceptions being the higher rates in cross country and gymnastics for women. Younger female gymnasts in a full-time elite training program are less likely to be injured than older collegiate gymnasts. The injury rates for youth soccer players were considerably lower than those at the collegiate level. Injury rates for middle-aged and older recreational athletes were noticeably higher, although the older recreational athlete presumably does not have as much pressure to participate, and therefore may be more willing to take a few days off when injured at a level of severity that a high school or collegiate athlete would tend to ignore.
Comparing the rates reported by the NCAA ISS for the late 80s and for the more recent 2000-2001 academic year indicates that injury rates for most sports have remained relatively stable, although a few appear to have decreased (e.g., women’s gymnastics, men’s lacrosse, women’s softball and men’s wrestling). The large drop in the men’s gymnastics rate may be more the result of only three teams reporting to the NCAA during 2001. When looking at these data, one should keep in mind that the data from the 80s covers four years, and is probably relatively more stable than the data from the single year represented by the 2000-2001 column. Data for the non-collegiate levels must be considered preliminary because these databases are relatively small in comparison with the amount of collegiate data available, but they do indicate the possibility of some interesting trends.
Data across all the sports show the most frequently injured body part is the ankle, followed by the knee and then the shoulder (7). All are major joints that undergo considerable stress in most sports. Sprains, strains, and contusions are the most frequent types of injuries. Overall, ankle sprains are the most frequently occurring injuries in most sports.
An interesting point that can be highlighted when data are reported in rates per 1,000 athlete-exposures, which is not evident when rates are reported per 100 participants, is the difference in injury risk between practices and competitions. Table 4 breaks down the injury rates for 17 collegiate sports into practice and competition rates, along with their relative rankings within each column. The competition injury rate for Senior (18-30 years old) taekwondo athletes is included for comparison. Also included in the right-hand column of the Table is an indication of the relative risk of injury in practice and in competition; in each case injury risk is higher in competition.
Table 4. Injury Rates in Practices vs Competition
Injury rate/1,000 Athlete-exposures
Sport Practice Competition Risk*
Baseball (M) 2.1 (16) 6.1 (14) 2.9
Basketball (M) 4.4 ( 7) 10.0 ( 9) 2.3
Basketball (W) 4.6 ( 5) 9.2 (10) 2.0
Field Hockey 4.1 ( 9) 8.5 (11) 2.1
Football (M) 4.1 ( 9) 36.0 ( 1) 8.8
Gymnastics (M) 4.4 ( 7) 16.5 ( 7) 3.8
Gymnastics (W) 7.5 ( 1) 18.5 ( 4) 2.5
Ice Hockey (M) 2.2 (15) 17.6 ( 5) 8.0
Lacrosse (M) 3.6 (11) 14.6 ( 8) 4.1
Lacrosse (W) 3.6 (11) 7.5 (12) 2.1
Soccer (M) 4.7 ( 4) 20.2 ( 3) 4.3
Soccer (W) 5.7 ( 3) 17.6 ( 5) 3.1
Softball (W) 3.1 (14) 4.9 (16) 1.5
Ultimate Frisbee (M) 3.5 (13) 7.0 (13) 2.0
Ultimate Frisbee (W) 2.0 (17) 5.6 (15) 2.8
Volleyball (W) 4.5 ( 6) 4.8 (17) 1.1
Wrestling (M) 6.9 ( 2) 29.7 ( 2) 4.3
Taekwondo (M) 27.2
Taekwondo (W) 22.2
* Relative Risk = higher rate divided by lower rate
Example: Men's lacrosse – 14.6 injuries/1,000 athlete-exposures in games divided
by 3.6 injuries/1,000 athlete-exposures in practices equals a relative risk of 4.1; i.e.,
a men's lacrosse player participating in a game is 4.1 times as likely to be injured as
he would be if he were participating in a practice session.
Sources: NCAA (1990); NCAA (2002); Watkins (1990); Zemper (unpublished data).
It often is reported that most injuries occur in practices, giving the impression that practices are at least as risky as competitions. Most injuries in a given sport usually do occur during practices, but the actual risk of an individual athlete being injured is much higher in competition. As an example, in college football nearly 60% of the recorded injuries occur in practice (40, 64). However, while the total number of injuries in college football over a season may be higher in practices, the rate of injuries is considerably higher in games, in this case 8.8 times higher (Table 4). In other words, a college football player is nearly nine times as likely to be injured in a game as he is in a practice session. Bear in mind that there are at least five to six times as many practices as games in a football season, and there usually are more players participating in practices than play in games, which accounts for the fact that the raw numbers of injuries may be higher in practices. The most obvious explanation for the difference in risk between practices and games is the continuously higher intensity of play during games.
Football represents the upper extreme in the difference between practice and competition injury rates. At the other end of the spectrum is women's volleyball, where the risk of injury in games is only slightly higher than in practices (Table 4). This seems reasonable considering that, at the collegiate level, volleyball practices often are as intense as the games. The data presented in Table 4 show that most sports at the collegiate level have a competition injury rate about two to four times higher than for practice.
USES OF SPORTS INJURY RATE DATA
Sports injury databases are important information resources that can be applied to development of sport rules and sport safety equipment, and to sports medicine administration and policy. The major uses of epidemiological data listed at the beginning of this unit can be adapted for our purposes in athletic medicine. Specifically, sports injury epidemiological data can be used to:
· Identify causes of injuries.
· Provide a more accurate picture of clinical reality. Clusters of injuries (and the resulting media attention they often generate) give a distorted view of reality; on the other hand, data may reveal a previously unsuspected injury problem.
· Determine the effectiveness of preventive measures (on a local or national scale), whether they are rule changes, new or modified equipment, or modifications of training techniques.
· Monitor the health of athletes, which will assist in rational medical planning.
Examples of each of these applications are discussed in the following sections, primarily referencing the model databases noted earlier.
1. Identify Causes of Injuries.
Pole vaulting - NCCSIR. The pole vault was associated with a majority of the fatal track and field injuries, and on an injury rate basis is the most dangerous activity monitored by the NCCSIR. There have been fifteen high school pole-vaulting fatalities from 1983 to 2000 (4, 39). This does not include the coach who was demonstrating in 1998, bounced out of the pit, struck his head on concrete, and died. In addition to the fatalities there also were seven permanent disability injuries and six serious injuries. All 28 of these accidents involved the vaulter bouncing out of or landing out of the pit area. Requiring a common cover or pad to extend over all sections of the pit and expanding the size of the pit have been policy modifications resulting from this data collection.
Swim pool starts – NCCSIR. Catastrophic injuries in swimming were all directly related to the racing dive in the shallow end of pools (39). There has been a major effort by both schools and colleges to make the racing dive safer and the catastrophic injury data support that effort. These efforts have involved increasing the minimum depth of water in the starting end and reducing the height of the starting blocks.
Men’s basketball – ISS. At an August 2002 sports medicine conference held in conjunction with the Men’s World Basketball Championships, NCAA ISS data on the epidemiology of collegiate basketball injuries were presented (16). Five-year within-sport analysis revealed that a majority of the men’s collegiate basketball game injuries occurred from player contact when within the lane. Ankles (29%) and knees (11%) also were reported to be the top two types of game injuries. However, more detailed analysis revealed that a majority of the ankle injuries resulted from rebounding and player contact, and the majority of knee injuries occurred from rebounding and non-contact defending. With the additional specific cause of injury information, preventive measures ranging from rules modifications (possible wider lanes) and officials’ points of emphasis (enforcing player contact), to shoe design (addressing non-contact issues) and focused practice techniques are possible.
2. Provide a more accurate picture of clinical reality.
HIV, Bleeding and Sports (ISS). As concern about HIV in intercollegiate and professional athletics grew in the early 1990’s following the revelations of Magic Johnson, athletic organization responses ranged from indifference to overreaction. Science scrambled to provide a fact-based recommendation in response to the range of reactionary proposals. Using data from a modified ISS form (frequency of bleeding injuries) and information from the Centers for Disease Control and Prevention (risk of HIV transmission in a hospital setting), a study was performed to determine the risk of HIV transmission in college athletics (17). Results indicated that the risk of HIV transmission during participation in NCAA sport was less than one chance in one million exposures. Similar results were found in an analysis of professional football players (5). Subsequently, policies were developed in all NCAA activities to address bleeding on the field of play in a reasonable and medically sound fashion.
Anterior cruciate ligament (ACL) injuries (ISS). Anterior cruciate ligament injuries pose a significant threat to a student-athlete, not only in the time away from the sport, but also in the economic cost to repair and rehabilitate the injury. Early studies had suggested that the risk of such an injury in females might be greater than their male counterparts. In 1995, Sports Illustrated (34) noted “Knee injuries of the most serious kind – tears of the anterior cruciate ligament, one of the two central ligaments that support the knee – are virtually epidemic in women’s college basketball.” Such statements led some to question whether participation in sports was worth the risk, especially for female athletes. Yet most medical research has focused on the repair of this injury rather than preventive efforts.
A five-year study of NCAA ISS data (2) showed a two to three-fold increased risk of ACL injury to female collegiate soccer and basketball student-athletes relative to their male counterparts. With its large national sample over a five-year period, this study validated the anecdotal evidence that women were at higher risk of such an injury, at least in certain sports. However, by quantifying the risk, the authors also were able to show that while the risk was higher in females, it was still relatively infrequent (estimated one ACL injury every 247 female basketball practices or games with 15 participants per event). Subsequent studies (1, 24) reported similar results. Further presentation and discussion of these findings noted the many benefits of participating in physical activities (58) that far outweighed the risk of ACL injury portrayed in the media. Once the increased risk was identified, researchers began discussion of identifying the causative factors involved in ACL injuries (21).
Head injuries in taekwondo – AIMS. The previous example illustrated a case where data showed a perceived problem was not as severe as thought. In the case of head injuries in the sport of taekwondo, there was a belief that the sport had no injury problems, until there was an effort to collect injury data. AIMS collected injury data at national taekwondo competitions for the U.S. Olympic Committee and the U.S. Taekwondo Union, the national governing body for this sport (42-45, 74-77). The major result was to draw immediate attention and concern to the high rate of cerebral concussions recorded during taekwondo competitions (42, 44, 75, 77). The cerebral concussion rate over a two-year period for taekwondo compared with AIMS data for college football showed the rate for taekwondo competition (5.45 cerebral concussions per 1,000 athlete-exposures) is 3.2 times as high as the rate seen in college football games (1.69 cerebral concussions per 1,000 athlete-exposures). Based on time of exposure, taekwondo (1.2 per 1,000 minutes of exposure) has a cerebral concussion rate 9.2 times that of college football games (0.13 per 1,000 minutes of exposure). These rates are essentially the same for Junior (6-17 years old) and Senior (18 and older) taekwondo competitors. The data uncovered a previously unsuspected problem with head injuries in this sport. The primary suggestions for addressing the problem include working with the manufacturers of the helmet used in taekwondo to develop a more protective product; changing the rules to require mouthguards, rather than just recommending their use; establishing and enforcing standards for competition mats; and adopting rules similar to those of amateur boxing, which require a minimum time period before an athlete is allowed to return to participation after a loss of consciousness from a blow during a bout.
Commotio cordis – NCCSIR. Sudden death from cardiac arrest in primarily young individuals may occur in athletics following a blow to the chest in the absence of structural cardiovascular disease or traumatic injury. Incidents have been reported in the sports of baseball, men’s lacrosse and ice hockey (39). Maron and colleagues (31) have used the NCCSIR and other injury registries to better understand the mechanism of commotio cordis, and to begin discussion on development of preventive measures.
3. Determine the effectiveness of preventive measures.
Adding protective equipment. Epidemiological studies can be used to evaluate the effectiveness of a rule or equipment change. Having baseline data prior to a change allows for the possibility of evaluating the impact of the intervention, if other possible confounding variables can be controlled. Specific applications of this analysis could assist in the evaluation of protective equipment effectiveness on the nature of competition in sport. A model example of such a study was the work by Benson et al., in evaluating head and neck injuries among ice hockey players wearing full and half shields (3). This prospective cohort study evaluated injuries on college hockey players playing in the same hockey league over one season. Eleven teams wore full face shields while another eleven wore half shields. Results showed that the use of full face shields was associated with a significantly reduced risk of sustaining facial and dental injuries without an increase in the risk of neck injuries, concussions, or other injuries. This study should be considered a template to follow when evaluating the possible effect of protective equipment on injuries. Laprade and colleagues had similar findings in an ice hockey face mask evaluation (30), while Marshall et al. (33) studied protective equipment and injury in North American college football and club level New Zealand Rugby Union.
Spring Football – ISS. In 1997, spring football practice injuries at NCAA Division I and II football programs were more than double regular season practice rates (15, 40). The football and sports medicine communities collaborated to develop policy that would allow coaches to teach the skills of the game while reducing the threat of serious injury. Such policy included allowing for initial acclimatization and providing opportunities for contact practice while reducing full tackle activities. Since the resulting NCAA legislation was enacted in 1998, the injury rate in spring football has decreased 27%, from 11.2 to 8.1 injuries per 1000 athlete exposures (Figure 1).
Figure 1. Football Spring and Fall Season Practice Injury Rates – 1997-2001
Anterior Cruciate Ligament (ACL) injuries (ISS). The 1999 Hunt Valley Consensus Conference on Prevention of Noncontact ACL Injuries, funded by the Orthopedic Research and Education Foundation, American Orthopaedic Society for Sports Medicine, National Athletic Trainers’ Association Research and Education Foundation, and the NCAA, was a landmark meeting that began the integration of ACL incidence and causative information into prevention efforts. Prior to that time, Garrick and Requa (20) noted that only 133 of 3572 MedLine citations under the ACL topic heading were subheaded “prevention” and less than 10 of the citations actually dealt with injury prevention rather than prevention of some surgical complication. The meeting resulted in a consensus publication that identified risk factors and offered prevention strategies (21). A special issue of the Journal of Athletic Training devoted to anterior cruciate ligament injury in the female athlete provides further epidemiology and causative research on this subject (26). Current ongoing prevention studies will use several epidemiology and surveillance techniques to assess the effectiveness of these programs.
Assessing protective equipment – football helmets – AIMS. Epidemiological studies of sports injuries may be used to evaluate new protective equipment or monitor the performance of existing equipment, if the study is properly designed to collect the necessary data. An example of this use for existing equipment is the AIMS monitoring of concussion rates in various brands and models of football helmets (65, 71). By collecting enough detail about helmets in use and concussions during general data collection on football injuries, AIMS is able to assess whether specific brands and models of football helmets are performing within expectations with regard to the occurrence of concussions. When this data was first analyzed, there was one older model of helmet that had a higher than expected rate of concussions, but it was no longer manufactured by the time the report was released. Since then, all helmet models have been performing within expectations, through the 1998 season (Zemper, unpublished data).
Assessing protective equipment – preventive knee braces – AIMS. Another example, evaluating new protective equipment, is a study of preventive knee braces in college football conducted by AIMS (66, 68, 72) as a part of general data collection on football injuries. Braces designed to prevent medial collateral ligament injuries from lateral blows to the knee came into widespread use in the 1980s before any studies were performed to see if they actually worked. The only “data” available were a lot of anecdotes and a few one- or two-season, one-team studies. There are many variables that could have an impact on the results of any study like this, such as brand or type of brace, position played, proper placement of brace, whether it was actually being worn at the time of injury, previous history of knee injury, intensity of practices, condition of playing surface, or weather, to name a few.
From an epidemiological perspective, the only way to "control" these numerous variables is to do a large-scale, long-term study with as many teams as possible so that the impact of the uncontrollable and essentially unrecordable variables (proper brace placement, practice intensity, condition of playing surface, weather) will "wash out" in the data collection process. At the same time, the more easily recordable variables (position played, whether the brace was worn at the time of injury, brand or type of brace, previous history) will be recorded in sufficient numbers to provide more reliable results than could ever be possible with a study of a single team or a small number of teams. The results of earlier, small-scale studies were mixed, with some showing that braces reduced the number of MCL injuries and others showing they did not. However, the later large-scale studies, such as those of Teitz (55) and the AIMS study (66, 68, 72), show that wearing preventive knee braces appears to have no effect on reducing the number or severity of MCL injuries, or on the time lost due to injury.
A well-controlled smaller-scale study done at the U.S. Military Academy (54) does show some positive effect in reducing MCL injuries by wearing preventive knee braces, but only with defensive players. This indicates that position played may be an important factor. There was no effect on the severity of knee injuries. However, the subjects were cadets playing intramural football rather than larger and heavier intercollegiate players, so the study may indicate a possible size/weight and, therefore, a force threshold involvement. Obviously, much more data must be collected from large-scale epidemiological studies, as well as biomechanical studies, before complex issues such as this can be resolved.
Catastrophic Football Injuries – NCCSIR. Football is associated with the greatest number of catastrophic injuries of all sports, but the total incidence of injury per 100,000 participants is higher in both gymnastics and ice hockey. In 1968 there were 36 fatalities associated with football. There have been dramatic reductions in the number of football fatalities and non-fatal catastrophic injuries since 1976 and the 1990 data illustrated an historic decrease in football fatalities to zero (39). This dramatic reduction, particularly in head and neck neurological problems, can be directly related to data collection and subsequent recommendations based on that data, including the 1976 rules change that prohibited initial contact with the head and face when blocking and tackling, the NOCSAE helmet standard that went into effect in colleges in 1978 and high schools in 1980, better coaching in the techniques of blocking and tackling, and improved medical care.
4. Monitor the health of athletes, which will assist in rational medical planning.
Nontraumatic cardiac deaths –NCCSIR. Data from the NCCSIR report have been further analyzed to assist the sports medicine community in more effectively addressing preventive issues (38). An example of this is the 1995 work by Van Camp and colleagues (59) on nontraumatic deaths in high school and college athletes. The authors noted that the study provides information that may assist in three important sport medicine issues: 1) appropriate athletic preparticipation exams, 2) eligibility recommendations for athletic participation, and 3) evaluation and medical treatment of athletes. Maron et al. (32) also have published on this subject, with the principal cause of sudden death in young competitive athletes being cardiovascular disease, most commonly hypertrophic cardiomyopathy.
populations – ISS. Since the
incorporation of women’s athletics into the NCAA in 1982, participation has
increased from approximately 80,000 to over 150,000 in 1999, an 88% increase
(41). Women’s soccer participation alone
has increased 563% in this time frame, with softball, volleyball, lacrosse and
basketball also showing large gains. Although these participants should reap
health benefits that extend beyond collegiate athletics, increased
participation brings with it issues such as sports injuries, which have not
been well-documented. As part of the
1999 Women’s Health in Sport and Exercise Workshop, co-sponsored by the
· Medical issues unique to women will continue to develop with increased participation. Research efforts that are able to identify, isolate and affect such issues are needed now and in the future.
· Identify causative factors for injuries that may have gender as a risk variable. Develop controlled studies to verify the effect of any proposed modifications. Reflect the significant benefits of athletic participation in any reports or educational efforts associated with specific injury issues.
Appropriate Medical Coverage for Intercollegiate Athletics (AMCIA). In February 1998, the National Athletic Trainers’ Association (NATA) (38) created the Task Force to Establish Appropriate Medical Coverage for Intercollegiate Athletics (AMCIA) to systematically determine the appropriate level of medical coverage for each sport. This was achieved by devising a rating system utilizing injury rates (primarily from the NCAA ISS), the potential for catastrophic injury (primarily from NCCSIR), and treatment/rehabilitation demands for both time loss and non-time loss injuries per sport. In addition to these indices, other related factors, such as prolonged season exposure, squad size, travel requirements, and health care administrative duties, were used to determine health care loads and medical staffing needs. To form the basis for the recommendations and indices, the task force conducted an extensive review of existing literature and evaluated past research, injury rate data, position statements and legal cases. Other relevant data obtained from informal conference and national surveys, and conference injury tracking data, also were reviewed.
The base health care unit system utilized indices of injury rates (IRE), catastrophic injury risk (CI) and treatment demands/injury (Tx/I) as the means to determine the level of appropriate medical care for each sport. To equate differing data, each index was converted to a 4-point scale, with 1 representing the lowest risk/demand and 4 representing the highest risk/demand. Each factor was considered to be equally important. By adding the three indices together and dividing that total by 3, the base health care unit for each sport was determined:
This formula was developed with the professional expertise of the NATA task force members, although the process of combining these factors into a formula for “optimal” athletic trainer staffing has not been scientifically validated. Nonetheless, this is an innovative application of epidemiology data, primarily from the NCAA ISS and NCCSIR, that has been developed to assist colleges and universities in evaluating their health care coverage needs.
5. Quantify the risks of various types, frequencies and intensities of exercise activities
Sports sponsorship / athletics health care and coverage – ISS. Because the ISS uses identical exposure and injury definitions for each sport, it is easy to compare injury rates across different activities (40). Such information can be applied by administrators in:
· Evaluating the potential comparative medical costs associated with adding new sports or athletics-related activities, and
· Considering delegation of athletics health care and coverage resources. Medical or athletic administrators can use injury rates to make an information-based decision on where to assign limited resources when numerous simultaneous athletics activities are occurring.
Specific injury risk and return to play – ISS. Evaluation and return to play decision sometimes involve a medical risk assessment of repeat or further damage to a particular area. In situations where the absence or nonfunction of a set of paired organs is a concern, the probability of injury to the remaining organ should be considered. The ISS can provide definitive injury risk data on organs such as eyes and kidneys to assist the student-athlete and the team physician in assessing the overall risks and benefits of athletics participation.
Relative risk of a second concussion – AIMS. Return to play decisions following a concussion are another area where protocols are still evolving. One element in formulating these recommendations is information about the risk of a second concussion following an initial concussion. For many years it was believed that there is an increased risk following an initial injury, but solid evidence for this increased risk and its magnitude was not available. As part of its process of monitoring the effectiveness of football helmets, AIMS has been able to provide data demonstrating that there indeed is an increased risk of a second concussion following an initial one, and the increased risk is about six times greater. Factors not related to previous history of concussion, such as player position, do not appear to impact this added risk. This level of increased risk was first noted in an AIMS published report on college injury data from the 1988-1990 seasons (71), and recently was replicated with high school and college football injury data from the 1997-1998 seasons (73).
Heat illness and injury in preseason football practice – ISS. In 2001, the NCAA began developing a preseason practice model for college football that had several health and safety components. If adopted, the model will be implemented at the start of the 2003 fall football season. The model included a five-day single-practice acclimatization period at the start of fall practice. This time would focus on acclimating the student-athletes to environmental conditions, exercise intensity and equipment. During the first two days, helmets would be the only allowable piece of protective equipment. The second two days would allow helmets and shoulder pads, while the fifth day would be a single practice in full equipment. Subsequent practices could have multiple practices on one day, but these “double sessions” could not occur on consecutive days. ISS data (Table 5) was used to justify this model (40).
Table 5. NCAA Football – Heat Illness During Early Fall Practice (2001)
Number of Number of Rate/ First Three
Division Schools Heat Illnesses 1000 A-E * Days
I 53 88 0.22 Shoulder Pads
II 29 58 0.33 Shoulder Pads
III 46 19 0.08 Helmets only
* A-E = athlete-exposures
Source: NCAA (2002).
As Table 5 indicates, NCAA 2001 ISS data showed that Division I and II institutions averaged 1.5 to 2 heat illnesses per school. These events restricted participation for at least one day. By legislation, these institutions were allowed to initiate their fall preseason practice in helmets and shoulder pads. Division III institutions reported time loss heat illnesses at a rate one-third to one-fourth that of Division I and II schools. By legislation, the Division III schools were required to practice with helmets as the only piece of protective equipment for the first three days. These data, as well as the findings of Kulka and Kenney (29) show the importance of acclimating to protective equipment as well as the environment.
In addition, ISS data showed that in 2002, a student-athlete was almost four times as likely to receive a time loss injury in preseason as opposed to the regular season. Eighty-seven percent of all reported time-loss heat illnesses and 49% of ANY time-loss practice injury for the entire season occurred on the 10-12 preseason days in which a school conducted a multiple session practice. These findings provided the rationale for alternating double and single practice days after the five-day acclimatization period to emphasize recovery and rehydration.
6. Provide an overview of long-term injury trends.
Trend analysis for administrative decisions – ISS. Historically, the role of the physician has been to address an injury after it occurs. The ISS data allows the entire medical community to critically evaluate the injury trends in college athletics and to respond proactively. ISS final reports allow physicians and athletic trainers at participating schools to annually evaluate individual school injury patterns and discuss results with the coaching staff. The ability to compare an individual school injury rate to conference, division or national values can be a convincing tool in modifying practice techniques.
Concussions in Men’s Collegiate Ice Hockey – ISS. The game-concussion injury rate in men’s collegiate ice hockey has doubled since 1990 (Figure 2). Based on these data, the NCAA Ice Hockey Rules Committee has created stricter penalties associated with noncompliance with the mouthpiece rule, hitting from behind and checking into the boards. In addition, a mechanism for re-certification of the hockey helmet and the addition of a four-point chinstrap were considered. Officials were educated that the helmet is not designed to prevent concussion and that any contact to the head should be penalized. The ISS will be used as an evaluation tool to assess the effectiveness of these rules and equipment modifications on injury rates. Concussions in many sports have become a research focus in sports medicine. The July-September 2001 issue of the Journal of Athletic Training (27) is devoted to concussions in athletes, and includes concussion injury trends in several other athletic activities.
Figure 2. Ice Hockey Game Concussion Injury Rates – 1986-1999
Unusual events. National or international multi-sport events provide a good opportunity to conduct injury surveillance on hard-to-find activities. The 1994 Australian Universities Games is such an event that featured over 5000 participants competing in nineteen sports, including events such as squash, taekwondo, water polo and rugby. Injury surveillance was conducted by means of an injury surveillance form that recorded time, mechanism, site, type and severity of injury (12).
LOCAL SPORTS INJURY DATA COLLECTION
Although the importance of longitudinal, national-scale epidemiologic data collection to adequately address major sports injury issues has been emphasized here, the small-scale local data collection effort also has a place in sports medicine. A primary care physician who is responsible for medical care of a high school or other local sports program, or who is part of a local sports medicine network (see Chapter 19), is in a good position to track local injury patterns. At a minimum this will require some form of centralized records of all sports injuries treated. Forms like those suggested in Chapter 19 for the records of a local sports medicine network would serve this purpose very well.
An alternative to normal patient files, which would make data compilation much easier, is a brief check-off form describing the athlete, injury, and circumstances. This would be similar to those used by larger data collection systems. These forms could be filled out by the physician, nurse, or athletic trainer at the high school for every sports injury treated, and kept in a single file. As mentioned earlier, this data is only a case series and cannot be used to make comparisons across sports or with data from other sources. However, they might alert the physician if an unexpected number of injuries of a certain type or injuries that happen under specific circumstances are noted.
If comparisons are desired, some form of exposure or "denominator" data is required to calculate injury rates, as discussed earlier. The simplest denominator data to obtain are the number of athletes on the team, so injury rates per 100 athletes can be calculated. The fact that many teams have more athletes at the beginning of the season than at the end presents a problem. The most reasonable solution is to use an average number of athletes if the rate of attrition is fairly stable over the season, or use the number of athletes on the team during the majority of the season if the drop-outs tend to occur at the beginning of the season and then the numbers stabilize as the season progresses.
For reasons presented previously, rates per 100 athletes are not the most accurate way to calculate sports injury rates. With some extra effort and on-site assistance from a student athletic trainer or coach, it is feasible to get data at the local level on the number of athletes participating in practices and competitions, or possibly even the amount of time of participation, so that rates per 1,000 athlete-exposures or rates per 100 hours or 1,000 minutes can be calculated.
In some team sports, the time of exposure in games is relatively easy to estimate, because the games last a specified length of time and involve a specified number of players at any one time. A high school football game will involve four quarters of twelve minutes each, and eleven players from a team are on the field at any given time. Therefore, the amount of exposure time for a single team in a single game will be 528 player-minutes per game (4 quarters/game x 12 minutes/quarter x 11 players). It is more difficult to get data on time of exposure in practices, but it basically means keeping track of the number of players participating in each practice and the length of the practices. When collecting athlete-exposure data, the time element is ignored, and data are recorded only on the number of players at each practice and the number who actually get into the games and are exposed, however briefly, to the possibility of injury (not the number who dress for the game).
Once appropriate denominator data on the population at risk are available, the rate equation presented earlier can be used to calculate injury rates that can be used in comparisons across local sports teams or with data from other sources that are calculated in a similar manner. When comparing local data with injury data from other sources (or for that matter when comparing injury data from any sources), always note any differences in methodologies used (data sources and collection procedures, definition of an injury, type of rate calculated, etc.). If there are any major differences, conclusions drawn from the comparisons may not be valid. Of particular importance are the type of rate calculated and the definition of an injury. Obviously, trying to compare injury rates per 100 athletes with rates per 1,000 athlete-exposures would be meaningless. Less obvious is the need to ensure that the same definition of a reportable injury is being used. If one set of data includes everything seen by the medical staff and another includes only injuries that cause three or more days of time lost from participation, comparisons would be meaningless. The most commonly used definition of a reportable injury is based on time-loss:
A reportable injury is any injury a) occurring in a scheduled practice or competition, b) requiring medical attention, and c) resulting in the athlete being restricted from further normal participation for the remainder of that practice or competition or for the following day or more.
This is essentially the basic definition of a reportable time-loss injury used by ISS and AIMS, and we recommend its use in local data collection systems. By basing the definition on time-loss of one day or more before a return to unrestricted participation, all minor scrapes, bumps, and bruises that do not cause time-loss are eliminated, so they do not overburden the data collection system. (The only exception to this in AIMS is that any mild concussion is reported, even though it may not cause time-loss.).
Rates for specific types of injuries or body parts also can be calculated for local injury data. For example, the total number of knee injuries could be the numerator rather than the total number of all injuries. If game and practice exposure data are available, separate game and practice injury rates can be calculated. Make sure the appropriate denominator is matched with the numerator. If a game injury rate is being calculated, be sure to divide the number of game injuries by the number of game exposures. As with large-scale sports injury data collection systems, the more local data collected over time, the more useful and valuable the information becomes.
Applying the principles of epidemiology to sports injuries is a relatively recent development, and national-scale data collection systems such as NCCSIR, ISS, and AIMS are making important contributions to current sports medicine issues. As Mueller (36) notes, “injury data collection plays an important role in the prevention of (catastrophic football) injuries… There is no question that the beneficial changes are the result of reliable data collection and the publication of the results in the athletic and medical literature. Persistent surveillance of sports injury data is mandatory if progress is to continue in the prevention of fatalities. Continuous data are needed to observe the development of specific trends, to implement in-depth investigation into areas of concern, and to carry out preventive measures. If continued progress in sports injury prevention is to be made, reliable data is a must.”
There will be ample opportunity for contributions from others as well, such as the primary care physician working with a local sports program. Understanding the basic principles of epidemiology presented in this chapter will allow the primary care physician to be more discriminating in reading the literature, and also will be useful in setting up a system for keeping track of local injury patterns. These efforts on the part of the primary care physician can play an important role in reducing the number and severity of injuries in the local community.
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