Happy birthday?

Cast your mind back, to your school days. Were you one of the oldest in your year, relatively speaking? And did you ever imagine that this had much of an influence on your life?

Relative age ultimately stems from how we've chosen to group youth into cohorts (grades or year) in school and to determine their eligibility for sports teams. For example, in England a child's age by 31 August is used to determine which school year they should be in for the upcoming academic session. If a child is five years old on or before 31 August, they are eligible to be in Year 1 of England's school structure. A child born on 30 August will be approximately 12 months younger than a peer born on 1 September of the previous calendar year. However, for the briefest period, these two children will both be five years of age and they are therefore placed within the same school year. The same process is used to group youth on sports teams. Relative-age effects describe the consequences of relative-age difference within cohorts such as school years and sports teams.

Academic and athletic outcomes

The domain with the longest history of examining relative-age effects is education (e.g. Jinks, 1964), where the bulk of the evidence indicates that relatively older pupils are more likely to attain higher grades than their relatively younger peers. This effect has been reported across a range of subjects (Donofrio, 1977; Massey et al., 1996), among males and females, and within both the primary and secondary stages of education (Bell & Daniels, 1990; Sharp et al., 1994). In a recent study from our research team (Cobley et al., 2009b) we observed that the top 20 per cent of achievers across all subjects (based on a composite attainment score from their grades from all subjects) were approximately four and a half times more likely to be relatively older rather than relatively younger. Importantly, this relationship is not limited to the UK; the influence of relative age on academic proficiency has been reported around the world. Data from the Trends in International Mathematics and Science Study (TIMSS), from 19 OECD countries (www.oecd.org), demonstrated a 4–12 percentile lower score for the relatively youngest among 4th grade children (approximately nine years of age) and a 2–9 percentile decrease for relatively younger 8th grade children (approximately 13 years of age).

Given the relationship between relative age and academic achievement, it should come as no surprise that relatively older and younger youth have qualitatively different experiences in school, particularly with regard to ability streaming (grouping children in hierarchies of academic proficiency). Indeed, during secondary education, relatively older pupils are more likely to be in the top ability streams and identified as 'gifted and talented' (Cobley et al., 2009b; Thompson, 1971). One study even reported that relatively older children were up to 11 per cent more likely to occupy leadership roles in secondary school (Dhuey & Lipscomb, 2008).

The flip side of this coin shows that relatively younger children are more likely to be placed in lower-ability streams (Thompson, 1971) and identified as having 'special educational needs' in England (Bookbinder, 1967; Wilson, 2000) and the United States (Martin et al., 2004; Wallingford & Prout, 2000). Relatively younger pupils are also overrepresented among those identified as learning disabled (Maddux, 1980). More relatively younger pupils than relatively older pupils (approximately 60 per cent vs. 40 per cent) are also referred for psychological counselling due to academic and/or behavioural problems, a trend that is consistent from kindergarten to the 8th grade (Drabman et al., 1987; Tarnowski et al., 1990). The last indication that relatively younger children may have qualitatively different experiences in school comes from school attendance records. Carroll (1992) reported lower attendance rates among a sample of primary school pupils from Wales, and more recently (Cobley et al., 2009b) the same trends were reported in a sample of secondary school pupils in England. These findings have been interpreted as young people's attempts to avoid and/or protect themselves from contexts with which they have negative associations.

A similar relationship has been noted in sports. One of the earliest studies on relative age in sports performance noted that 40 per cent of elite Canadian professional ice hockey players were born in the first three months of the hockey selection year (January to December) compared to less than 10 per cent born in the last three months (Barnsley et al., 1985). Over the intervening two and half decades, similar effects have been reported in sports ranging from team activities like soccer, handball and volleyball to individual sports like swimming and tennis (see Cobley et al., 2009a, for a review).

The effect is presumably driven by the sophisticated and highly competitive talent identification and development systems used by many sports. Increasing attention placed on the identification of early sporting 'talent' promotes a system where coaches and trainers strive to identify qualities that determine early success (e.g. speed, power, and physical size). As a result, because these variables are often determined by chronological age rather than innate potential, coaches and trainers confuse maturation for innate talent (see Baker et al., 2010; Wattie et al., 2008).

Researchers have also investigated a range of behavioural, psychosocial and health outcomes associated with education-based relative age. Research suggests that relatively younger pupils have lower levels of self-esteem (Fenzel, 1992; Thompson et al., 2004), although ambiguous results have also been reported for motivational and engagement outcomes (Martin, 2009). In a nationally representative sample of 5- to 15-year-olds from the UK, relatively younger pupils were at greater risk of psychiatric disorders than relatively older pupils (Goodman et al., 2003). As an indication of the scale of this issue, the authors suggest that if the prevalence of psychiatric disorders were equal across different relative ages then there would be approximately 60,000 fewer cases of child psychiatric disorder in the UK. Similarly, researchers in the United States (Schneider & Eisenberg, 2006) observed that relatively younger youth were approximately 50 per cent more likely to be diagnosed with attention-deficit/hyperactivity disorder (ADHD), particularly with regard to how ADHD-related symptoms were perceived by children's teachers (Elder, 2010). A recent large-scale Canadian study confirmed that relatively younger youth are also more likely to be prescribed medication to treat ADHD (Morrow et al., 2012). If these findings were not enough to convey the potential seriousness of some relative-age effects, Thompson and colleagues (1999) observed an overrepresentation of the relatively young among individuals under 20 years of age who had committed suicide.

The devil is in the details 

While the trends and outcomes described above have serious implications for youth development, it is important to describe some of the nuances of the relative-age effect since they offer insights into the mechanisms of these effects and may even illuminate how they can be moderated or eliminated.

Interestingly, the socio-economic literature has noted some unexpected attainment trends when examining relative-age effects, suggesting that simple mean trends may obfuscate the complexity of these effects. In an investigation of secondary school mathematics exam results, Allen (2008) observed that relatively older pupils had higher average attainment in maths. However, relatively younger pupils were more likely than their relatively older counterparts to score above the 90th percentile. Therefore, mean attainment statistics, which indicated conventional relative-age effects (relatively older = higher attainment; relatively younger = lower attainment), may not reveal important subtleties. This study adds to a growing body of evidence suggesting that in some circumstances there is the potential for relatively younger youths to have some advantages over their older peers. Allen (2008) suggests that relative age may influence social identity (e.g. cool crowd, nerd, etc.), which in turn may exert an influence on academic achievement trends. More generally, however, the results reported by Allen also reiterate the importance of remembering that advantages for relatively older youths are probabilistic and not deterministic.

There is another point to make about relative-age trends in academic achievement, namely the relationship between academic ability streaming and academic achievement. Perhaps most interesting is the fact that two countries, Denmark and Finland, demonstrated no relative-age effects for academic achievement (Bedard & Dhuey, 2006).

The authors highlight one particular educational feature within these countries that may explain the lack of effects: specifically, policies regarding ability streaming (the streaming, selection or organisation of youth into different hierarchies of proficiency). The authors note that these countries also had a lack of, or in the case of Denmark a complete prohibition on, ability streaming until late adolescence (16 years of age). This is in stark contrast to countries like England and the United States which ability stream from the early primary years of education. Indeed, relative age seems to predominantly influence academic achievement in environments where ability streaming is common practice. Whether or not Allen and Barnsley (1993) should have titled their paper 'Streams and tears' rather than 'Streams and tiers', their admonition of ability streaming was poignant nonetheless: 'Observing the relative age effect late in schooling, then makes it easy – too easy, facile really – to simply conclude that strong streaming in school systems produces dead weight loss' (p.658).

Another insight from the socioeconomic literature concerns the intersection between relative age and socio-economic status. Specifically, the observation that high socio-economic status parents were more likely to delay their child's entry to school if they were to be relatively younger members of their cohort, thereby making them relatively older when entered into school (Bedard & Dhuey, 2006). If true, and replicated, relatively younger youth may be more likely to be disadvantaged by both their relative age and their socio-economic status. However, research has not comprehensively considered the intersection of social class and ethnicity with relative age, providing an intriguing avenue for future research.

The last point we would like to make regarding relative-age effects in education concerns the subjective nature of some relative-age effects. Earlier, it was mentioned that relatively younger youth were more likely to be referred for counselling/behavioural problems (Drabman et al., 1987), despite the fact that their scores on standardised tests of behavioural problems were equivalent to those of relatively older youth. This suggests the possibility of a far more insidious aetiology based on perceptions, rather than objective differences in behaviour. There may be a need to consider whether the resultant developmental outcomes so consistently linked with ability streaming and relative age could be described as pathologising individuals' normal reactions/behaviours to their developmental environment. In the case of the findings reported by Drabman and colleagues (1987), there may also be a need to consider whether or not some outcomes may be pathologised without foundation or meaningful cause. More research is needed to explore the role of subjective perceptions on the disproportionate diagnosis of other conditions, such as ADHD, according to relative age.

Long-term effects

Even though the majority of research has focused on youth samples, evidence suggests that relative-age differences may have lasting impacts later in life. Relatively younger youth are also underrepresented (by 7–12 per cent) among those who take pre-university entrance tests (e.g. the SAT) in North American during the last year of secondary school (Bedard & Dhuey, 2006). Consistent with this line of evidence, researchers who examined applications to medical school in the United States found that a greater proportion of applicants were relatively older (Abel et al., 2008). Interestingly, researchers examining cognitive academic achievement and indices of healthy social life of students at one Italian University found that relatively younger, not older, students attained higher grades (Billari & Pellizzari, 2008). There were also concomitant indications that relatively younger students had less active social lives, perhaps an indication that they had more time to focus on educational attainment and/or that these students had developed poorer social skills. The trend for less active social lives among relatively younger students could also be a corollary of the social identity hypothesis described by Allen (2008; see above).

Similarly, results from sport suggest that relative-age differences occurring early in development have long-term implications, affecting one's likelihood of becoming a professional/elite athlete (e.g. Wattie et al., 2007). One's relative age status also predicts salary in professional soccer (Ashworth & Heyndels, 2007) and career length in professional handball (Schorer et al., 2009), although, interestingly, it is the relatively younger athlete who seems advantaged in these outcomes. Furthermore, Baker and Logan (2007) found that relatively younger ice hockey players were more sought after in the National Hockey League's professional sports draft. It is possible that relatively younger athletes who are able to continue in a system that may be biased towards their relatively older counterparts may end up developing superior skills (e.g. through competing against larger, more capable opponents during key stages of development), although this hypothesis has not been explored empirically. These seemingly counterintuitive results highlight the complexity of these effects and how they relate to human health and development. The fact that the processes related to these counterintuitive results are largely not understood highlights the need for future research. 

Conclusions

Collectively, the trends discussed here emphasise the subtle influence that birth date has on human development. Clearly not all relatively older youth experience the advantages described above, just as not all relatively younger youth are disadvantaged and discriminated against. What is clear is that relative age has the potential to influence a variety of different developmental outcomes, affecting the quality of an individual's experience in sport and education, two of our most cherished and ubiquitous social structures. Greater attention to these effects and the social policies underpinning them would help to
ensure a level playing field for all.

Nick Wattie is in the School of Kinesiology and Health Science, York University, Toronto
[email protected]

Joseph Baker is in the School of Kinesiology and Health Science, York University, Toronto
[email protected] 

References

Abel, E.L., Sokol, R.J., Kruger, M.L. & Yargeau, D. (2008). Birthdates of medical school applicants. Educational Studies, 34, 271–275.
Allen, J. (2008). Relative age, identity and schooling. Journal of Socio-Economics, 37, 343–352.
Allen, J.M. & Barnsley, R.H. (1993). Streams and tiers: The interaction of ability, maturity, and training in systems with age-dependent recursive selection. Journal of Human Resources, 28, 649–659.
Ashworth, J. & Heyndels, B. (2007). Selection bias and peer effects in team sports. Journal of Sports Economics, 8, 355–377.
Baker, J., Cobley, S., Montelpare, W.J. et al. (2010). Exploring proposed mechanism of the relative age effect in Canadian Minor Hockey. International Journal of Sport Psychology, 41, 148–159.
Baker, J. & Logan, A.J. (2007). Developmental contexts and sporting success: Birth date and birthplace effects in national hockey league draftees 2000–2005. British Journal of Sports Medicine, 41, 515–517.
Barnsley, R.H., Thompson, A.H. & Barnsley, P.E. (1985). Hockey success and birthdate: The relative age effect. Canadian Association of Health, Physical Education and Recreation Journal, 51, 23–28.
Bedard, K. & Dhuey, E. (2006). The persistence of early childhood maturity: International evidence of long-run age effects. Quarterly Journal of Economics, 121, 1437–1472.
Bell, J.F. & Daniels, S. (1990). Are summer-born children disadvantaged? Oxford Review of Education, 16, 67–80.
Billari, F.C. & Pellizzari, M. (2008). The younger the better? Relative age effects at university. IZA Discussion Paper No. 3795.
Bookbinder, G.E. (1967). The preponderance of summer-born children in E.S.N. classes. Educational Psychology, 9, 213–218.
Carroll, H.C.M. (1992). Season of birth and school attendance. British Journal of Educational Psychology, 62, 391–396.
Cobley, S., Baker, J., Wattie, N. & McKenna, J. (2009a). Annual age-grouping and athlete development. Sports Medicine, 39, 235–256.
Cobley, S., Baker, J., Wattie, N. & McKenna, J. (2009b). How pervasive are relative age effects in secondary school education? Journal of Educational Psychology, 101, 520–528.
Dhuey, E. & Lipscomb, S. (2008). What makes a leader? Relative age and high school leadership. Economics of Education Review, 27, 173–183.
Donofrio, A.F. (1977). Grade repetition: Therapy of choice. Journal of Learning Disability, 10, 349–351.
Drabman, R.S., Tarnowski, K.J. & Kelly, P.A. (1987). Are younger classroom children disproportionately referred for childhood academic and behavior problems? Journal of Consulting and Clinical Psychology, 55, 907–909.
Elder, T.E. (2010). The importance of relative standards in ADHD diagnoses. Journal of Health Economics, 29, 641–656.
Fenzel, L. (1992). The effect of relative age on self-esteem, role strain, GPA, and anxiety. Journal of Early Adolescence, 12, 253–266.
Goodman, R., Gledhill, J. & Ford, T. (2003). Child psychiatric disorder and relative age within school year. British Journal of Medicine, 327, 472–475.
Jinks, P.C. (1964) An investigation into the effect of date of birth on subsequent school performance. Educational Research, 6, 220–225.
Maddux, C.D. (1980). 1st-Grade entry age in a sample of children labeled learning-disabled. Learning Disability Quarterly, 3, 79–83.
Martin, A.J. (2009). Age appropriateness and motivation, engagement, and performance in high school effects of age within cohort, grade retention, and delayed school entry. Journal of Educational Psychology, 101, 101–114.
Martin, R.P., Foels, P., Clanton, G. & Moon, K. (2004). Season of birth is related to child retention rates, achievement, and rate of diagnosis of specific LD. Journal of Learning Disabilities, 37, 307–317.
Massey, A., Elliot, G. & Ross, E. (1996). Season of birth, sex and success in GCSE English, mathematics and science. Research Papers in Education, 11, 129–150.
Morrow, R.L., Garland, E.J., Wright, J.M. et al. (2012). Influence of relative age on diagnosis and treatment of attention-deficit/hyperactivity disorder in children. Canadian Medical Association Journal. doi: 10.1503/cmaj.111619
Schneider, H. & Eisenberg, D. (2006). Who receives a diagnosis of attention-deficit/hyperactivity disorder in the United States elementary school population. Pediatrics, 117, e601–e609.
Schorer, J., Cobley, S., Büsch, D. et al. (2009). Influences of competition level, gender, player nationality, career stage and playing position on relative age effects. Scandinavian Journal of Medicine & Science in Sports, 19, 720–730.
Sharp, C., Hutchison, D. & Whetton, C. (1994). How do season of birth and length of school affect children's attainment at key stage 1? Educational Research, 36, 107–121.
Tarnowski, K.J., Drabman, R.S., Anderson, D.F. & Kelly, P.A. (1990). Disproportionate referrals for child academic behavior problems. Journal of Consulting and Clinical Psychology, 58, 240–243.
Thompson, A.H., Barnsley, R.H. & Battle, J. (2004). The relative age effect and the development of self-esteem. Educational Research, 46, 313–320.
Thompson, A.H., Barnsley, R.H. & Dyck, R.J. (1999). A new factor in youth suicide. Canadian Journal of Psychiatry, 44, 82–85.
Thompson, D. (1971). Season of birth and success in the secondary school. Educational Research, 14, 56–60.
Wallingford, E.L. & Prout, H.T. (2000). The relationship of season of birth and special education referral. Psychology in the Schools, 37, 379–387.
Wattie, N., Baker, J., Cobley, S. & Montelpare, W.J. (2007). A historical examination of relative age effects in Canadian hockey players. International Journal of Sport Psychology, 38, 178–186.
Wattie, N., Cobley, S. & Baker, J. (2008).  Toward a unified understanding of relative age effects. Journal of Sports Sciences, 26, 1403–1409.
Wilson, G. (2000). The effects of season of birth, sex and cognitive abilities on the assessment of special educational needs. Educational Psychology, 20, 153–166.