1 Department of Epidemiology and Biostatistics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada.
2 Department of Community Health Sciences, Faculty of Medicine, University of Calgary, Calgary, Alberta, Canada.
3 University of Calgary Sport Medicine Centre, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada.
Received for publication December 28, 2001; accepted for publication November 5, 2002.
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ABSTRACT |
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athletic injuries; cohort studies; football
Abbreviations: Abbreviations: CI, confidence interval; GEE, generalized estimating equations; RR, rate ratio.
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INTRODUCTION |
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Because of the size and speed of the players engaged in this type of football, extreme collision forces can produce severe, even life-threatening injuries. Many factors have been implicated as contributing to the occurrence of football injuries. Factors such as the type of field surface (13), field conditions (4), session type (2, 512), and history of injury (4, 7, 1315) have all been studied to determine which affects injury risk, either independently or in combination with others. However, there are shortcomings identifiable with past investigations of football injury risk, primarily concerning the assessment of athlete participation (1618). Therefore, we conducted an investigation among members of the Canada West Universities Athletic Association to determine which risk factors best predict injury incidence and severity in specific body regions, either alone or in combination, for intercollegiate football players. Once identified, risk factors can be eliminated or modified for injury prevention.
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MATERIALS AND METHODS |
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If an injury occurred at the end of the season or occurred in-season but caused the player to miss playing time up to the end of the season, time loss was based on the greater of the measured time loss (from the athlete participation log) or the therapist/physician assessment of time loss (from the injury report form).
The rate of injury to a particular body region was used as the outcome or dependent variable. This was done to determine the specificity of particular risk factors in relation to the part of the body affected. The three primary regions of injury analyzed were the head and neck (injuries to the head or neck, concussions, and neck neurologic injuries), the upper extremities (shoulder to hand), and the lower extremities (hip to foot). Thoracic spine-chest and lumbar spine-pelvis injuries were also examined in the indicated analyses.
Predictor variables included type of playing session (game vs. practice), field type (artificial turf vs. natural turf), field conditions (wet vs. dry), year of varsity sport participation (assessed both as a continuous variable and as a categorical variable where indicated), university (British Columbia, Alberta, Calgary, Manitoba, or Saskatchewan), and history of injury (present vs. absent). Any injury to a particular body region noted on the preseason medical form was considered to constitute a positive history for that region in the analysis. However, an injury that occurred during the season was only categorized as a past injury (from that point in the season onward) if the injury resulted in partial or complete time loss.
We estimated unadjusted incidence density ratios by specifying the number of injuries per 1,000 athlete exposures for each of the conditions being compared. However, because outcomes were not all independentthat is, because many players sustained multiple injuriesPoisson regression models were fitted using generalized estimating equations (GEE). The GEE approach accounts for correlation in individuals with multiple injuries, which is the case in these data. The beta coefficients from this model estimate the injury incidence density ratio (i.e., rate ratio) accounting for the nonindependence of the data (20). These ratios were compared with the unadjusted rate ratios obtained from simply expressing the number of injuries per 1,000 athlete exposures under the presence versus absence of the risk factor of interest, an approach that does not take into account correlated outcomes. This analysis was completed using Stata statistical software (21).
We conducted a sensitivity analysis of the potential for bias related to differential (across the exposure contrast) underreporting of injury. This analysis proceeded according to the method described by Rothman and Greenland (22) for person-time follow-up data with the tenable assumptions of no false-positive injury reporting (i.e., perfect specificity) and negligible alteration of person-time.
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RESULTS |
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Table 4 suggested an increasing risk of head and neck and lower extremity injuries with each additional year of participation in varsity football when data were controlled for past injury. The Poisson regression equation predicted that the rate in any given year was 19 percent (95 percent CI: 9, 31) higher than the rate in the previous year for the head and neck. Lower extremity injury rates were estimated to increase 15 percent (95 percent CI: 9, 23) per additional year of participation. Upper extremity injury rates were estimated to increase 10 percent (95 percent CI: 1, 21) per additional year of participation, although the confidence limits crossed the null value.
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For the lower extremity, the GEE Poisson regression rate ratio estimates for specific body parts ranged from 1.47 for the left foot (95 percent CI: 0.28, 7.83) to 7.21 for the right hip (95 percent CI: 2.70, 19.27), after controlling for year of varsity sport.
We conducted a sensitivity analysis to examine the effect of underreporting of neck injury among those with no past neck injury (unadjusted RR = 5.81 (table 5)), assuming that no underreporting occurred among those with a past neck injury. With 90 percent of the neck injury cases captured in the no-past-neck-injury category, the unadjusted rate ratio would change to 5.23. At 70 percent case capture in the no-past-neck-injury group, the unadjusted rate ratio would decrease to 4.1. Under the extreme condition of 50 percent case capture in the no-past-neck-injury group, the rate ratio would fall to 2.9. Neck injury capture would have to be 20 percent in the no-past-neck-injury group in order for the unadjusted rate ratio to fall to a practically and statistically insignificant value of 1.16.
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DISCUSSION |
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Artificial turf versus natural turf
Although artificial turf has advantages over natural grass in terms of maintenance costs and durability (23), there has been considerable debate and research to determine whether a synthetic playing field increases athletes risk of injury. In this study, rates of injury on AstroTurf synthetic fields were estimated to be approximately twice as high as those on natural grass for all body regions. However, when the analysis was restricted to games, only lower extremity injury rates on AstroTurf remained twice as high as those occurring on natural grass. Head and neck injury rates were elevated but not to the same extent overall, and not under wet field conditions. This suggests that athlete speed, and thus force of impact, increases on dry artificial turf because of the level field and greater shoe-surface friction.
Other investigators have found differences between artificial turf and natural fields. Specifically, AstroTurf was found to have a higher injury rate than grass fields, although Tartan Turf® (Tartan Turf Industries, Inc., Champlain, New York) had a slightly lower rate than grass (1). Furthermore, Tartan Turf had a higher associated injury rate under wet field conditions as compared with dry conditions (1). However, the investigators did not categorize injuries by body region but rather presented rates of injury overall for the different surfaces. National Collegiate Athletic Association data also indicated higher overall injury rates with artificial turf as compared with natural fields, although these data were not broken down by body region of injury (2). Specifically studying knee injuries, Powell and Schootman found "a tendency for AstroTurf to be associated with an increased risk for knee sprains and MCL and ACL injuries under very specific conditions" (3, p. 692). Other investigators found higher injury rates among professional football players on natural grass as compared with a synthetic field, although it was not clear from that investigation how athlete exposure data were collected or what type of synthetic surface the athletes played on (24).
One very interesting finding in this investigation concerns the field comparisons presented separately for the University of Calgary team and the other teams combined for the years 19931996. Because the University of Calgary team consistently played their home games on AstroTurf while all other team home venues in the Canada West Universities Athletic Association had natural grass, other teams may have had increases in injury rates because of their less frequent exposure to artificial turf (i.e., the change of turf and not the type of turf accounted for the increased injury incidence) (25, 26). This result suggests that artificial surfaces may be safe as long as they are used consistently. However, since our study findings relate only to acute injuries, further research is required to determine the influence of consistent participation on artificial surfaces and gradual-onset injury risk.
There are many arguments both for and against artificial turf (27), and although the evidence from this investigation suggests a higher incidence of injury on artificial turf, further study controlling simultaneously for a number of factorsshoe type, bracing or taping, temperature, history of injury, team, field conditions, athlete position, and whether or not an athlete is a starting player for games played on both artificial turf of various types and natural grassis warranted.
Games versus practice periods
Injury rates were estimated to be substantially higher for all body regions during games as compared with practice periods. This effect was most pronounced for head and neck injuries, where there was a 10-fold increase in the injury rate during games versus practices. Other investigators have provided evidence for a higher incidence of head and neck (5, 8), knee (6, 24), and overall (2, 9, 28) injuries in competition, although the risk changed depending on the type of injury in some studies (28). Still other investigators have found similar absolute numbers of injuries incurred in games and practices but have maintained that if player exposure (i.e., the amount of time players spend participating in games vs. practices) (7, 10, 29) and amount of contact (12) were accounted for, game injury rates would be much higher. Those studies conveying higher numbers of injuries in practices versus games failed to address the issue of player exposure (11, 30). A likely explanation for the higher game injury rate concerns the increased player-to-player contact in games as compared with practices (18). Cantu and Mueller (8) have also noted that catastrophic football injuries, most often associated with blocking and tackling, were more prevalent during games. It has been suggested that limited player contact in practice periods does not affect win-loss records, at least at the high school level (7).
Wet versus dry field conditions
It is interesting to note the difference in lower extremity injury risk associated with participation on artificial turf versus natural turf under wet and dry field conditions during games. It is possible that the condition of the field modifies the risk associated with field type. This is simply speculation, as the confidence intervals for the lower extremity incidence density ratios for the comparison between artificial turf and natural turf demonstrated substantial overlap and thus might have been the same under both conditions. However, similar results were reported by Adkison et al. (1), where wet Tartan Turf had an estimated higher injury rate than dry Tartan Turf. Field conditions should be accounted for in the comparison of turf type.
Year of varsity sport
Veteran players approaching their fifth year of participation were at increased risk of injury in all body regions in comparison with less experienced players. This effect persisted even when data were controlled for history of injury in the Poisson regression analysis. Other investigators have found similar trends but have suggested that this finding is due to the effects of history of injury (4, 7). However, those studies did not categorize types of injuries into specific body regions. Another study found that experience did not influence the proportion of injuries, although the study was completed among high school athletes and did not account for athlete exposure to participation (11). Jackson et al. (24) found that professional players with less than 2 years of experience were 5.8 times more at risk for knee injuries than players with greater than 2 years of experience. However, this effect was not controlled for previous injury. Factors that could account for the difference between our findings and those of other studies include age, continuing risk-taking behavior, incurred playing time, and the potential cumulative effect of repetitive loading over many years of participation.
History of injury
An almost ubiquitous increase in injury risk was associated with those individuals who had a history of injury to a specific region of the body. Perhaps of most concern was the fivefold elevated risk of injury associated with having experienced a prior neck injury, even after data were controlled for year of varsity sport. A similar though not as dramatic effect was evident for upper extremity, thoracic spine and chest, and lower extremity injuries. Other investigators have observed higher incidence rates for persons who have a history of injury (4, 7, 15). A study on rugby injuries (31) also demonstrated higher injury rates for those with a past injury. This type of information is very useful in preseason screening, because it draws attention to the need to effectively manage those athletes with a prior injury. Specific stretching and/or strengthening intervention programs could be implemented randomly for athletes who have a specific type of previous injury (such as neck injury) to determine whether their injury risk could be lowered.
Limitations of this study
It is evident that a large number of comparisons were made in this analysis. As a result, we must acknowledge the likelihood of type I error (i.e., the probability of false-positive statistical results). However, we chose to present confidence limits in order to provide a plausible range for each effect rather than rely on p values using an arbitrary cutpoint (i.e., = 5 percent) to decide whether these effects were real. The consistency and biologic plausibility of the findings make chance (i.e., spurious associations due to multiple testing) an unlikely explanation for the results.
Using only acute injuries may have changed the effects of many risk factors on the risk of injury. For example, in the comparison of field types, it has been suggested that limiting the analysis to acute injuries might cause one to underestimate any negative effect of artificial turf in producing injuries that occur because of repeated athlete participation on this type of surface (27).
Selection bias is unlikely to have affected these results. Only 2.9 percent of the athletes did not consent to participate in this investigation over the 5-year period (18). The presence of dedicated team athletic therapists and physicians made it unlikely that the athletes would have sustained an injury and sought health care elsewhere, making loss to follow-up a nonissue.
The homogeneity of player ages, skill levels, and other physical characteristics makes confounding by these factors unlikely. Results for history of injury were controlled for year of varsity sport participation and vice versa.
The objective nature of the exposures and the access to athletic therapists and physicians for injury assessment and diagnosis (i.e., outcome), respectively, make information bias an unlikely explanation for the results.
It is possible that those athletes who were more likely to report injuries on the preseason medical form and throughout the season would also be more likely to report subsequent injuries. This cannot be excluded as a possible explanation for the association between past injury and higher subsequent injury risk. However, the associations grew stronger when particular body regions were considered. Our sensitivity analysis also indicated that the underreporting would need to be so extreme as to be untenable to effect a meaningful change in the largest point estimates. It is unlikely, then, that the past injury findings are a consequence of differential injury reporting.
The athletes in this investigation represented "survivors" of all previous years of football in the sense that none had suffered a career-ending injury. This, coupled with the elite level of varsity play and the homogeneous age range, may limit the generalizability of these findings to different age groups and levels of play.
Conclusions
This study was among the first to have captured participation information on individual players in intercollegiate football and on a group of players that were homogeneous in terms of age and skill level. The injury rates derived in this study are therefore more reliable than those from investigations where player exposures were estimated on the basis of overall team participation. We identified several factors that increased injury risk, including having a history of injury, being a veteran approaching the fifth year of play, participating in a game, and playing on an artificial surface, although infrequent use of an artificial surface may explain this relation. This comprehensive study has provided the information necessary to proceed with interventions aimed at reducing the overall incidence of injury in Canadian football.
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ACKNOWLEDGMENTS |
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The athletic therapists and physicians who diligently collected data at the involved institutions were instrumental in the completion of this project.
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NOTES |
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REFERENCES |
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