The relative age effect (RAE) is a phenomenon whereby children born in, or right after, a critical age cutoff month may have an advantage in both school and sports because of their physical and emotional maturity relative to their peers (17). The RAE has evolved over time to include sports, as well as test scores (2), high school leadership (10), gifted programs (23), and “academic redshirting” (9,14). One study has also reported that children born immediately after an activity cutoff date (relatively “older” children) are more likely to succeed and persevere in sports and in school when compared with their relatively “younger” peers (1).
Most commonly, youth sports athletes are grouped into teams and leagues based on specific age cutoffs, rather than by chronologic age, size, or physical maturity. This age grouping may span 1 or 2 yr, and the specific age cutoff month may vary based on factors including sport, state, and organization. For many soccer competitions, for example, the age group consists of players born between January 1 and December 31, inclusively. Players can therefore differ in age by nearly 12 months. Importantly, for the younger age groups, a year of growth and maturation can be a critical factor determining athletic performance, success, and possibly injury. These regulations indicate that potentially, those athletes who are born closest to the cutoff date for the competition (i.e., the “oldest” athletes) tend to excel in sports and may have a lower risk of injury due to size, skill, and cognitive development advantages. Results of meta-analytical research have identified a consistent prevalence of RAE in sport (6). Furthermore, recent research that examined the birth distribution for adolescent and mature age players older than 20 yr, selected in the Australian Football League National Draft between 2001 and 2012, showed a clear bias in the birth distribution of adolescent draftees toward relatively older players who were born in the first part of the classification period compared with relatively younger players. The selection bias toward relatively older players may be related to advanced physical and psychological maturity and exposure to higher-level coaching compared with their younger counterparts (7).
The RAE in sport was first reported in the literature by Barnsley and Barnsley (1) in a study of professional ice hockey players. They observed that 40% of all National Hockey League players were born in January, February, or March, indicating that athletes born earlier in the calendar year may have an advantage relative to those born almost a full year later. This potentially indicates that athletes born earlier in the year may possess both physical and emotional developmental advantages due to the arbitrary activity age cutoff of January 1. Older children may excel early in sporting events because of their relative size and strength advantage, and this early success may lead to more attention from coaches, more training time, and may culminate in improved athletic performance throughout adolescence (Fig. 1) (16,18). Conversely, younger players may self-remove due to their age-related disadvantages (Fig. 1) (24). Currently, there is evidence of the RAE in sports participation in adult men’s sports including baseball, basketball, cricket, football, handball, hockey, soccer (16), tennis, volleyball (23), and rugby (32). The RAE has also been demonstrated in many youth sports including soccer, basketball, tennis, ice hockey, and baseball (1,8,11,31).
Recent trends indicate that widespread participation in organized sports by children is occurring at a younger age, and early sports specialization is continuing to rise (19,21). Many authorities in pediatric exercise science and sports medicine agree that sports participation across a variety of sports by children provides both physical and social benefits (12,30,34,36). However, with younger participants in particular, there is a concern about safety and the growing prevalence of youth sports injuries (3,33). At this time, there is no research available on how the RAE may influence sports injury risk and safe participation during athletic activities in the physically active youth. Therefore, the purpose of this study was to determine if an RAE exists on sports injuries within a cohort of young athletes. Based on prior literature that supports a RAE in sports related to physical, developmental, and social advantages, we hypothesized that in a study cohort of children age 5–17 yr with sports injuries, those children born right after the age cutoff (i.e., the oldest children in a given sport) would be less likely to sustain injuries when compared with their relatively younger peers.
The study population consisted of all patient visits to the sports medicine division of a children’s hospital from January 01, 2000, to December 31, 2009. Before data collection, the study was reviewed and approved of by the hospital’s institutional review board. The patients presented to the clinic with many types of injuries related to sports participation, from acute traumatic to nontraumatic and overuse. Patients included in the study were children 5 to 17 yr of age. There were a total of 121,047 patient visits by children in this age range, from which we randomly drew a 5% probability sample. We then accessed the electronic medical records corresponding to each selected patient visit.
The following inclusion criteria were used: 1) the individual reported to the clinic for an injury sustained as a result of one or more organized physical activities that involved athletic competition, and 2) a clear medical record about the activity in which the patient was participating in during the time the injury occurred. Exclusion criteria consisted of patients who reported to the clinic for injuries sustained as a result of everyday accidents (e.g., falling down the stairs or falling off a bike while riding recreationally) or underlying congenital disorders and anomalies. The final study sample included 1997 cases. To investigate if the RAE differed between age groups, the cohort of patients was divided into two groups: prepubescent (5–13 yr) and pubescent (14–17 yr) age groups. These separate cohorts were selected to reflect the age of children in elementary and middle school, and high school, respectively.
Activities and age cutoffs
Children in this sample cohort participated in 56 different organized sports, with a wide range of duration and frequency in their respective activities. To maximize reliability and to minimize the potential of the results being attributable to chance, activities with fewer than 15 patients were not included in the data set (Table 1). The sport-specific activity age cutoffs were determined by contacting the statewide associations in the state of interest in which the hospital was located. In cases where more than one association existed, the authors chose the most popular and/or most competitive association in the state. Activities that use patient’s ages at the time of competition as the cutoff for participation, rendering the RAE meaningless, were excluded. These activities were skateboarding, squash, swimming, and tennis.
For our study purposes, relative age was defined as a measure of a child’s birth month relative to the month that his or her activity uses as an arbitrary age cutoff, listed in Table 1 based on each sport incorporated in the analysis. The relative age measure was expressed using a range from −6 to +5 and was calculated as the difference between birth month and activity cutoff month. Children born within 6 months before the age cutoff were assigned negative scores, ranging from −1 (born 1 month before the cutoff) to −6 (born 6 months before the cutoff), whereas children born within 5 months after the age cutoff were assigned positive scores, ranging from +1 (born 1 month after cutoff) to +5 (born 5 months after cutoff). A child born in the cutoff month was given a score of 0. For example, a child born in January and playing a sport with a January age cutoff has a relative age of 0, a child born in June and playing the same sport would have a relative age of +5, and a child born in November would have a relative age of −2. We hypothesized that three activities in particular—gymnastics, cheerleading, and figure skating—may demonstrate a reverse effect related to athlete size; in these activities, younger athletes may have an advantage because they are smaller (15,20). We accounted for this by reverse coding the relative age measure for these three sports (i.e., by multiplying the relative age measure by −1).
Activity-specific birth month ratio
To calculate the representation of a given birth month among the patients included in the study cohort, we computed an activity-specific birth month ratio (ASBMR). For patients born in month i and involved in activity j,
In this calculation, PFij is the frequency of births in month i for activity j among the patient sample, and SFij is the frequency of births in month i for activity j in the hospital’s home state of Massachusetts. The ASBMR was compared with birth month data for the general state population. The state population birth month data was obtained from the Department of Public Health, Registry of Vital Records, and Statistics, for Massachusetts between the years 1982 and 2004. A ratio equal to one indicates that births from the study cohort in a given month are proportionate to births in the general state population. A ratio less than one indicates that a birth month is underrepresented in the study cohort as compared with the general state population, whereas a ratio greater than one indicates that a birth month is overrepresented in the study cohort as compared with the general state population. Because the ratio is activity-specific, each activity has a unique ASBMR. Table 2 shows the distribution of birth months for patients in this sample and for children born in the state, by age group, as well as the mean ASBMR for each age group. Table 3 identifies the specific ratios for each sport included in the analysis.
To determine the RAE on sports-related injuries, a linear regression model was used to estimate ASBMR using the following equation. Linear regression models are used to explain the relationships among different predictor and outcome variables (29), such as the relative age of a child, the cutoff age, the interaction between these two variables (each predictor variables) and the ASMBR (the outcome variable). Thus, we constructed a linear regression model according to the following equation:
Three variables were included as predictor variables in the model: relative age—the relative age measure, cutoff—a binary variable indicating if the patient was born in the cutoff month or within 5 months after the cutoff month, and relative age*cutoff—an interaction term between these two variables. Accordingly, the relative age coefficient (β1) indicates the relationship between ASBMR and relative age of patients, and the cutoff coefficient (β2) indicates overrepresentation (positive value) or underrepresentation (negative value). Because of the wide age range of patients included in the study, we separated patient data into two separate groups: prepubescent (5–13 yr) and pubescent (14–17 yr) age groups.
The study cohort was 55% female, predominately white (87%), and English speaking (98%).The mean age of the pediatric athletes in the cohort was 14.2 yr. Patients’ zip codes were geocoded and merged with zip code characteristics from the 2000 census. Patients tended to come from middle- to upper-middle class, overwhelmingly white suburbs of Boston. Although a few patients come from several thousand miles away, the median distance traveled to the clinic was 15.6 miles.
For the prepubescent group, patients born before the activity age cutoff (relatively younger patients) had a greater representation in the study cohort relative to births statewide (Fig. 2A) compared with those born after the activity age cutoff (relatively older patients). Results from the linear regression model indicated that a 1 month change in relative age was significantly associated with an ASBMR increase of 0.030 (SE = 0.008, P < 0.001), moving closer to the age cutoff month (Table 4). The cutoff variable coefficient was significant and negative (b = −0.82, P = 0.041), suggesting an underrepresentation in the study cohort of injured patients (Table 4).
Among children in the study cohort born in the month directly before the cutoff month, the ASBMR was 1.003, indicating that the number of subjects in the study cohort born in this month was approximately proportionate to the number of children born statewide (Table 4). For prepubescent children born in the cutoff month, such as those born in January and playing a sport with a January 1 cutoff, the ASBMR was 0.951, indicating that approximately 5% fewer patients were in our sample than in the general state population. A lower rate for each month after the cutoff month was observed.
Among the pubescent age group, each month closer to the activity age cutoff was associated with an ASBMR decrease of 0.38 (SE = 0.006, P < 0.001, Table 4), indicating that more injured patients were born within the months during or after the cutoff compared with those born before the age cutoff, relative to the statewide births (Fig. 2B). The cutoff variable for those born in or after the cutoff month was significantly associated with an increase in patient sample representation (b = 0.315, SE = 0.032, P < 0.001). This result suggests a positive RAE, that is, an overrepresentation of relatively younger patients in the study cohort, compared with the general population (Table 4). The ASBMR for older patients born within the month before the age cutoff was 0.783, indicating approximately 22% fewer births in the sample than in the general state population (Fig. 2B). The estimated ASBMR for those born in the cutoff month was 1.06, indicating a 6% greater birth rate among patients in this sample than in the general state population, followed by a decline in each month thereafter.
This study set out to determine if there is an RAE on sports-related injuries in youth, by analyzing patient records from a sports medicine division of a children’s hospital. Furthermore, we investigated if the RAE on youth sports injuries varies between prepubescent and pubescent age groups. Children born in December, playing a sport with a January 1 cutoff date, or born in August, playing a sport with a September 1 cutoff date, are examples of a relative age difference in youth sports. These children are considered “relatively younger” as compared with some of their peers, who were born right after the cutoff date, or during the cutoff month (“relatively older”), in their particular sports. The purpose of this study was to evaluate whether or not relatively younger athletes are at increased risk, as compared with the relatively older peers, for sports-related injuries.
In the subset of prepubescent athletes with a sports-related injury, the results revealed that the relatively younger children displayed a higher risk of injury, when compared with their relatively older peers. We also observed, in this same subset of prepubescent athletes with a sports injury, that for each month after the age cutoff, there was a slightly lower rate of sports injury (Fig. 2). This finding supports the hypothesis that among the prepubescent age group, relatively older individuals are less likely to sustain sports injuries when compared with their younger peers. During prepubescence, physical and emotional developmental differences may be divergent among children within a 1-yr time span. Relatively younger children may succumb to injury more readily due to these differences because the size discrepancy may affect risk of injury and/or willingness to participate in sports. Furthermore, this finding may be more substantial in collision types of sports due to aggressive physical contact and the effect of body size on athletically related injuries, and may not pertain to sports where a smaller size is advantageous, including gymnastics, cheerleading, and figure skating. To support this notion, a study conducted by Yard and Comstock (35) reported that young athletes with a low body mass index (BMI) are more likely to sustain fractures, as compared to normal and high BMI athletes in football. This study, however, did not specify if the fractures were a direct result of physical contact. This may further explain why relatively younger athletes, who are more likely to have a lower BMI than their relatively older peers, sustain more sports-related injuries.
Analysis of the pubescent age group indicated that by the time these individuals reach high school, a reverse RAE may exist. Specifically, the athletes in this age category with a sports injury were overrepresented, as compared with the general population, followed by a steady decline in each month thereafter. This result was unexpected given the hypothesis tested. This finding may be explained, in part, by the notion that the relatively older, and more developmentally advantaged athletes for sports participation, receive more attention from coaches, parents, and training staff, ultimately leading to increased athletic exposure over time (Fig. 1). A recent study which followed a cohort of 1190 athletes, with age ranges of 7–18 yr, reported that injured athletes are older and spend more total hours participating in physical activity (21). Additionally, this study reported that sports specialization is an independent risk factor for athletically related injuries. Therefore, the theory presented, as depicted in Figure 1, is that relatively older and more “advantaged” children in sports settings may have persevered in their sports, and may then consequently possess a greater risk of sustaining a sports-related injury.
Previous research has examined the effect of body size, such as BMI, on risk of sports-related injuries in children. Although findings differ by sport, injury diagnosis, and anatomical location, lighter hockey players may be at a greater risk of injury in youth hockey (4,13,28). Yet, other research suggests that, when compared with normal-sized high school athletes, obese athletes are more likely to sustain knee injuries, and that these injuries are more likely to result from contact with another person (35). Quarrie and colleagues (26) found that high-BMI male rugby players (those with BMI of 26.5 or greater) were at greater risk of injury relative to rugby players in the lowest BMI category (BMI, <23). The results of a study which investigated the effect of BMI on musculoskeletal injuries in female soccer players found that greater BMI is associated with lower extremity musculoskeletal injuries (BMI, <22.6) (25). Collectively, the current available research suggests that child development, and possibly body size, may play a role in risk of injury, and that this may be modulated by relative age due to developmental factors. One study which examined the effects of yearly increases of BMI on sports-related injuries in teenage female athletes concluded that those who sustained an injury demonstrated greater yearly BMI and body fat percent increases than those who did not sustain an injury (24). This BMI and injury association may be a contributing factor as to why the RAE was not observed in the 14- to 17-yr group. Furthermore, as the variance explained in each age group was relatively low, extrinsic factors may have played a role in predicting the ASBMR in addition to relative age. Future research should continue to examine the relationship between relative age, body size, motor skill development, and injury risk.
The impact of relative age on youth sports demonstrates that activity cutoffs, which are often arbitrary dates selected to ease organization, may influence risk of sports-related injuries. When organized competitive activities were first introduced in the early 20th century, children were grouped according to body size and age. In the 1930s, the YMCA instigated a system which relied solely on grade in school to organize youth sports, and dropped body size as a factor (5). The current results suggest that the organization of youth sports may benefit from consideration of a child’s size and development, in addition to age. This may be particularly important when considering types of sporting activities, including collision and high contact. In this light, team sports including, for example, football and basketball, as compared with sports that rely more on individual performance, like track-and-field and swimming, might be optimal choices. That said, multiple other factors, including, for example, skill development and strength, are critical to both performance and injury prevention and pertain to all sports played by young athletes. Such a restratification may therefore help ensure that more children continue to play sports successfully and safely throughout all stages of development. Collaboratively, policy makers, pediatricians, pediatric exercise specialists, and social scientists should reevaluate the current rules, regulations, and systems of youth sports organization. Previous research has reported that among a cohort of Canadian youth ice hockey players, the risk of concussion was higher in leagues that allowed body checking than those in leagues that did not allow checking (13,22). These studies demonstrate that changes in the rules of a sport and the age at which rules are enacted may affect the incidence rates of sports-related injuries in children (27).
The results of this study should be considered in light of several limitations. The data were collected from a dedicated sports medicine clinic of a large, pediatric, tertiary care center. This may limit the generalizability of the results. Injury incidence cannot be reported given lack of athletic exposure data. The use of electronic medical records limited the data collection on sports competition level and hours of play (i.e., frequency of sports participation per week, level of competition). The majority of the study cohort consisted of middle and upper class white population, limiting the generalizability of the findings to other ethnic groups. Lastly, we did not factor into the data analysis variables pertaining to athlete size and development, including, for example, BMI and Tanner stage.
The goal of this study was to investigate if there is an RAE on a cohort of young athletes with musculoskeletal injuries in youth sports. This study identified that such an effect was present in a study cohort of children age 5–13 yr, and that on reaching high school age, the RAE was reversed. Thus, the findings from this study highlight the notion of organized sports stratification using a variety of factors, including age and size, to promote safe sports participation. Further research on the RAE in youth sports is warranted with regard to how the RAE varies by level of competition, and among children of different races and background, to best guide efforts to prevent youth sports injuries, while promoting a more active and healthy lifestyle.
The funding source for this research was from the Robert Wood Johnson Foundation’s Human Capital Program, Scholars in Health Policy Research awarded to Dr. Hilary Levey Friedman.
The authors have no financial relationships relevant to this article to disclose.
All authors have no conflicts of interest to disclose.
All authors attest that the results of the present study do not constitute endorsement by ACSM.
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Keywords:© 2016 American College of Sports Medicine
RELATIVE-AGE EFFECT; INJURIES; SPORTS; YOUTH ATHLETES