RESEARCH ARTICLE
Performance in youth track and field is
associated with birth quartile. A register-
based study among athletes in Norway from
10 years to senior level
Hilde GundersenID1*, Anette Harris2, Halvard GrendstadID3, Morten Kristoffersen1,
Atle Guttormsen4, Terje Dalen5, Cecilie Brekke Rygh6
1 Department of Sport, Food and Natural Sciences, Western Norway University of Applied Sciences, Bergen,
Norway, 2 Department of Psychosocial Science, Faculty of Psychology, University of Bergen, Bergen,
Norway, 3 Department of Physical Performance, Norwegian School of Sport Sciences, Oslo, Norway,
4 NMBU School of Economics and Business, Norwegian University of Life Sciences (NMBU), Ås, Norway,
5 Department of Physical Education and Sport Science, Faculty of Teacher Education and Arts, Nord
University, Levanger, Norway, 6 Department of Health and Functioning, Western Norway University of
Applied Sciences, Bergen, Norway
* hsg@hvl.no
Abstract
Introduction
Earlier studies have demonstrated that the oldest in a competition class are more likely to
succeed than the youngest, a phenomenon called relative age effect (RAE). Track and field
give us an opportunity to investigate the advantage of being born early in the year based
upon actual performance, since objective criteria are the performance indicators. Hence,
the aim of the present study was to investigate the occurrence of RAE in Norwegian track
and field athletes in events where physical capacity is important for success.
Methods
All individual season best results from the register of The Norwegian Athletics Federation (n
= 28 999) obtained in all competition classes from the age of 10 years to senior in both
sexes on 60m and 600m from 2011 to 2020 were downloaded. One-way ANOVA and LSD
post hoc analyses were used to analyze performance differences according to birth quartiles
between athletes. Further, odds ratios (OR) were used to calculate the odds of being among
the top-100 for athletes for those born in the first quartile of the year compared to the last.
Results
The RAE was present in several of the competition classes in sprint compared to middle-dis-
tance running, and in more male than female competition classes. Overall, the OR of being
among the top-100 in one of the competition classes on 60m sprint when born in first quartile
compared to last quartile was 2.88 [2.30–3.62] for males and 1.54 [1.26–1.89] for females.
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OPEN ACCESS
Citation: Gundersen H, Harris A, Grendstad H,
Kristoffersen M, Guttormsen A, Dalen T, et al.
(2022) Performance in youth track and field is
associated with birth quartile. A register-based
study among athletes in Norway from 10 years to
senior level. PLoS ONE 17(9): e0273472. https://
doi.org/10.1371/journal.pone.0273472
Editor: Caroline Sunderland, Nottingham Trent
University, UNITED KINGDOM
Received: February 3, 2022
Accepted: August 9, 2022
Published: September 6, 2022
Copyright: © 2022 Gundersen et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: Data from athletes
from 13 to 20 years can be retrieved from: https://
www.minfriidrettsstatistikk.info/php/
LandsStatistikk.php?showclass=4&showevent=
0&outdoor=Y&showseason=0&showclub=0 Data
from 10-12 years require permission from The
Norwegian Athletics Federation. If interested, you
may apply to friidrett@friidrett.no.
Funding: The author(s) received no specific
funding for this work.
Conclusion
Being born early in the year in events with high demand for specific physical capacities is an
advantage in both sexes in most of the youngest competition classes. In males, the advan-
tage of being born early in the year lasted longer in sprint than in middle-distance running,
indicating that puberty affects performance in sprint and middle-distance running differently.
Introduction
Organized sport is one of the most popular forms of leisure-time activities worldwide, and at
least one-third of children and adolescents are participating in one or more sports in most
countries [1]. To provide equal opportunities and competition, children and youth usually
compete in age classes based on their chronological age. However, previous studies have
shown that children born early in their birth year are likely to perform better than children
born later in the same age cohort, a phenomenon called relative age effect (RAE) [2]. The mat-
urational hypothesis is perhaps the most common explanation for the RAE, i.e. that chrono-
logically older children have a higher chance of being more physically mature, with
subsequent anthropometric and physiological characteristics that aid performance [3–9].
It is reasonable to expect that the RAE would be more prominent for younger athletes
because of the age differences being relatively larger. During puberty, the RAE is often found
to be strongest in this period related to the large variation in physique and anthropometry due
to age [10]. After puberty, RAE are often found to subside [11], however, secondary effects
may maintain the persistence during senior carrier [12]. Early maturation and success may
increase training motivation and thus the sport-specific skills and experience [11, 13]. Further-
more, those who perform at highest level in youth sports may be favoured by more competent
coaches, more systematic training and better training facilities [14, 15]. Consequences of the
RAE may include favouring the physically mature at the expense of those less mature, and in
worst case athletes dropout from the sports because of late maturation [11, 16].
RAE is well documented in team sports [2, 17], but there is still less evidence regarding
RAE in individual sports [17]. There are, however, some important differences between team
sports and individual sports that may influence the occurrence of RAE. The selection that
occurs in team sports are not seen to the same extent in individual sports. In individual sports,
success is also related to individual performance and not confounded by inter-individual fac-
tors like team formations, tactics and positional roles [18]. Performances are further judged on
objective data in most individual sports, rather than of a subjective evaluation of an individu-
al’s contribution to a team performance. RAE-studies in team sports are most often investigat-
ing the advantage/disadvantage for the selected/non-selected players, and this selection are
based upon subjective criteria. Track and field give us an opportunity to investigate the advan-
tage of being born early in the year based upon actual performance, since objective criteria are
the performance indicators.
There are few previous studies investigating RAEs in track and field, and as far as we know,
only one study from the Scandinavian countries [19]. In addition, the majority of previous
studies in track and field have focused on athletes who are 14 years (U15) or older who com-
pete at international level [20–26]. The occurrence of RAE has further been investigated more
in males than females [19, 20, 23, 27, 28]. Since the Norwegian Athletics Federation has regis-
tered seasonal best for each athlete in all events obtained in official competitions from the age
of 10 years to senior the last decades, the register will provide as an unique opportunity to
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Competing interests: The authors have declared
that no competing interests exist.
investigate RAE in track and filed from child to adult in both sexes. Since biological matura-
tion is suggested as an explanation for the RAE, the aim of the present study was to investigate
the occurrence of RAE in events where physical capacity is important for the result in all com-
petition classes, in both sexes. We aimed to use two different approaches 1) to investigate per-
formance differences between athletes born in different quartiles of the year in all competition
classes in sprint (60m) and middle-distance running (600m) in both sexes, and 2) to calculate
the OR of being among the top-100 athletes in each of the competition class for those born in
first vs. last quartile of the year in all competition classes for both sexes.
Methods
The Norwegian Athletics Federation has the last decades registered all results obtained in offi-
cial competitions by Norwegian athletes. The register includes an overview of the best result of
each athlete in each event in all competition classes, from 10 years to senior. For each result,
competition class and competition date are registered. Birth year is registered for all athletes,
and birth date for most of the athletes. The present study was conducted in accordance with
the declaration of Helsinki and approved by the Norwegian centre for research data (NSD)
(324455) and the Norwegian Athletics Association. Since the data are based on publicly avail-
able resources, no informed consent was obtained.
Procedures
Results available on 60m and 600m in the database from 2011 to 2020 were downloaded on
the 1st of January 2021. Only indoor results were included to avoid differences in wind and
temperature conditions, and since 60m is the main sprint distance indoor in all competition
classes. 60m is an international distance indoors. In Norway, youth athletes are organized
within one-year age bands from the age of 10 until the age of 17 years, and in two-years age
band for 18 and 19 years old (U20). Senior included results obtained from the age between 20
and 34 years, although athletes can compete in the senior class when 15 years old in Norway.
Only the best result for each athlete in each competition classes were included in the analyses.
Results obtained without electronic timing and athletes without registered birth date were
excluded. Birth months was categorised in birth quartiles; Q1: January-March, Q2: April-June,
Q3: July-September, Q4: October-December.
Data analyses
Data are presented as mean with standard deviation (SD) or as frequencies. Visual inspection
confirmed that all data were normally distributed. One-way ANOVA analyses were performed
to analyse whether there were differences between results obtained from athletes born in dif-
ferent quartiles (Q1, Q2, Q3 and Q4) for each competition class and event, separated by sex.
Post hoc analyses were performed with the least significant difference (LSD) test. Frequencies
of the top 100 athletes born in each competition class and event for females and males were
calculated. Crosstab analyses were performed to assess odds ratio (OR) and 95% confidence
interval [CI] of being among the top 100 athletes (yes/no) for those born in first vs. fourth
quartile of the year. IBM SPSS Statistics (version 27) was used for all statistical analyses and sta-
tistical significance was accepted at p < 0.05.
Results
Totally, 28 999 results were registered along with birth date for 60m sprint and 600m middle
distance running, 15 244 and 13 755 results for females and males respectively. For 60m sprint,
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a total of 21 419 results were registered (11 512 for females and 9907 for males), and for 600m
middle distance running, a total of 7580 results were registered (3732 for females and 3848 for
males).
Result difference between athletes born in different quartiles of the year
There were significant differences in results obtained by athletes born in different quartiles,
especially among the youngest athletes. Being born in the first quartile was an advantage
regarding performance compared to being born in the last quartile for both events in all com-
petition classes from 11 to 13 years (See Fig 1 and Tables 1 and 2 for more specific informa-
tion). In sprint, there were better results in first quartile compared to the last quartile in all
completion classes until the age of 16 years in females (Table 1 and Fig 1), and in most of the
competition classes until U20 in males (Table 2 and Fig 1). In middle-distance running
(600m), there were better results in first quartile compared to the last quartile in all competi-
tion classes until the competition class 13 year in females (Table 1 and Fig 1), and until 14
years in males (Table 2 and Fig 1). In females, the largest main effect was seen in the competi-
tion class 13 years on 60m sprint performance and in the competition class 12 years on 600m
middle distance running. There was no significant result difference between quartiles from the
age of 17 years in any of the two events. In males, the largest main effect was seen in the com-
petition class 13 years for both events. No significant result difference was found at senior level
in sprint performance and from the age of 15 years on middle-distance running performance.
For an overview of number of athletes born in each quartile see S1 and S2 Tables.
OR of being among the top-100 athletes
There were higher ORs for being among the top-100 athletes when born in first quartile of the
year compared to the last quartile. Overall, the OR of being among the top-100 in one of the
competition classes on 60m sprint when born in first quartile compared to last quartile was
2.88 [2.30–3.62] for males and 1.54 [1.26–1.89] for females. Similar, overall OR of being
among top-100 athletes on 600m middle-distance running was 2.05 [1.64–2.54] and 1.88
Fig 1. Mean of best indoor running times on 60-meter sprint (A) and 600-meter middle-distance running (B) for different age groups in male and female track and field
athletes from 2011–2020. Q1: born in January-March, Q2: born April-June, Q3: born in July-September, Q4: born in October-December.
https://doi.org/10.1371/journal.pone.0273472.g001
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[1.48–2.38] for males and females, respectively. In females, highest ORs were seen in the com-
petition class 10 years in both events, although significantly higher OR was seen until competi-
tion class 14 years on 60m and until 13 years on 600m. In males, highest ORs were seen in
competition class 14 years on sprint, and in competition class 13 years on 600m. Significant
higher OR was seen in most competition classes until senior level on 60m and until the compe-
tition class 14 years on 600m (see Table 3 and Fig 2 for more details).
Discussion
In the present study, we aimed to investigate performance differences between athletes born in
various quartiles of the year in each competition class in sprint (60 meter) and middle-distance
running (600 meter), for both female and male track and field athletes. Moreover, we wanted
to explore the OR of being among the top-100 athletes in each of the competition class for
those born in first vs. last quartile of the year. Our main findings were that being born in the
first quartile was an advantage for both sprint and middle-distance running success, especially
in the youngest age classes. The RAE was present in more of the competition classes in sprint
versus middle-distance running, and in more competition classes in males than in females.
This is to the best of our knowledge, the first study investigating result performance differ-
ences among athletes born in different quartiles of the year in all competition classes from 10
years to senior for both sexes. Our results indicate that chronologically older children and
Table 1. Differences in performance on 60m sprint and 600m middle-distance running in females born in different birth quartiles (Q) for each competition class.
Data are presented as mean ± standard deviation.
Competition classes (years)
Q1
Q2
Q3
Q4
Main effect
Post hoc analyses LSD
January-March
April-June
July-August
Sept.-October
60m sprint (sec)
10 (n = 842)
10.52 ±0.67
10.56 ±0.67
10.80 ±0.78
10.90 ±0.73
F(3,838) = 13.45, p < .001
Q1>Q3, Q4, Q2>Q3, Q4
11 (n = 1367)
10.09 ±0.68
10.14 ±0.63
10.31 ±0.70
10.39 ±0.68
F(3,1363 = 14.64, p < .001
Q1>Q3, Q4, Q2>Q3, Q4
12 (n = 1795)
9.69 ±0.63
9.71 ±0.60
9.93 ±0.70
9.99 ±0.71
F(3,1791) = 22.38, p < .001
Q1>Q3, Q4, Q2>Q3, Q4
13 (n = 2184)
9.39 ±0.60
9.41 ±0.59
9.58 ±0.67
9.67 ±0.69
F(3,2180) = 23.68, p < .001
Q1>Q3, Q4, Q2>Q3, Q4
14 (n = 1828)
9.13 ±0.63
9.11 ±0.55
9.19 ±0.63
9.26 ±0.61
F(3,1824) = 5.19, p < .001
Q1>Q4, Q2>Q4
15 (n = 1300)
8.89 ±0.60
8.88 ±0.51
8.91 ±0.57
9.03 ±0.71
F(3,1296) = 4.02, p = .007
Q1>Q4, Q2>Q4
16 (n = 920)
8.69 ±.050
8.71 ±0.49
8.72 ±0.54
8.82 ±0.52
F(3,916) = 2.90, p = .034
Q1>Q4
17 (n = 604)
8.51 ±0.44
8.56 ± 0.45
8.63 ±0.57
8.56 ±0.44
F(3,600) = 1.55, p = .201
-
U20 (n = 508)
8.42 ±0.54
8.42 ±0.43
8.43 ±0.46
8.48 ±0.52
F(3,504) = 0.40, p = .752
-
Senior (n = 162)
8.09 ±0.47
8.18 ±0.45
8.23 ±0.61
8.22 ±0.54
F(3,158) = 0.64, p = .592
-
600m middle distance running (min)
10 (n = 347)
2.19.87 ±11.15
2.22.17 ±11.40
2.22.31 ±9.99
2.26.24 ±11.58
F(3,343) = 3.95, p < .009
Q1>Q4, Q2>Q4, Q3>Q4
11 (n = 631)
2.13.96 ±11.60
2.15.64 ±11.39
2.17.37±12.56
2.19.68 ±11.36
F(3,627) = 6.17, p < .001
Q1>Q3, Q4, Q2>Q4
12 (n = 758)
2.07.23 ±11.79
2.08.19 ±10.32
2.11.49±11.55
2.11.87 ±12.58
F(3,754) = 7.66, p < .001
Q1>Q3, Q4, Q2>Q3, Q4
13 (n = 762)
2.01.19 ±10.01
2.01.16 ±10.31
2.03.69±11.64
2.04.71 ±10.44
F(3,758) = 5.12, p < .002
Q1>Q3, Q4, Q2>Q3, Q4
14 (n = 587)
1.57.02 ±11.23
1.56.11 ±8.73
1.56.22 ±8.73
1.58.12 ±9.65
F(3,583) = 1.07, p = .360
-
15 (n = 256)
1.53.27 ±8.97
1.52.31 ±8.59
1.52.71 ±8.54
1.55.56 ±10.42
F(3,252) = 1.28, p = .282
-
16 (n = 155)
1.48.27 ±6.99
1.50.61 ±8.19
1.48.25 ±6.47
1.53.48 ± 8.71
F(3,151) = 3.53, p = .016
Q1>Q4, Q3>Q4
17 (n = 120)
1.50.04 ±10.09
1.46.67 ±8.18
1.46.94 ±8.50
1.51.10 ±7.08
F(3,116) = 1.77, p = .158
-
U20 (n = 77)
1.43.71 ±6.86
1.43.81 ±6.04
1.42.75 ±7.17
1.44.03 ±6.67
F(3,73) = 0.13, p = .940
-
Senior (n = 39)
1.42.42 ±11.17
1.38.49 ±2.65
1.42.47 ±10.24
1.41.88 ±7.74
F(3,35) = 0.47, p = .706
-
U20: 18–19 years, Senior: 20–34 years. > indicate significant better performance for athletes born in quartiles at the left side of the sign compared to those born in
quartiles at the right side.
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adolescents of both sexes have an advantage in youth track and field both in sprint and mid-
dle-distance running. Better performance in both sprint and middle-distance running among
athletes born early in the year compared to those born late can probably be explained by the
Table 2. Differences in performance on 60m sprint and 600m middle-distance running for males born in different birth quartiles (Q) for each competition class.
Data are presented as mean ± standard deviation (SD).
Competition classes (years) Q1
Q2
Q3
Q4
Main effect
Post hoc analyses LSD
January-March
April-June
July-August
Sept.-October
60m (sec)
10 (n = 710)
10.39 ±0.76
10.40 ±0.72
10.51 ±0.84
10.60 ±0.70
F(3,706) = 2.59, p = .052
-
11 (n = 1118)
9.96 ±0.76
10.05 ±0.70
10.15 ±0.79
10.23 ±0.73
F(3,1114) = 6.19, p < .001
Q1>Q3, Q4, Q2>Q4
12 (n = 1406)
9.56 ±0.75
9.71 ±0.75
9.80 ±0.76
9.97 ±0.83
F(3,1402 =) 16.31, p < .001
Q1>2Q, 3Q, 4Q, 2Q>4Q 3Q>4Q
13 (n = 1735)
9.18 ±0.75
9.28 ±0.73
9.44 ±0.74
9.66 ±0.73
F(3,1731) = 31.21, p < .001
Q1>Q2, Q3, Q4, Q2>Q3, Q4, Q3>Q4
14 (n = 1335)
8.57 ±0.66
8.69 ±0.62
8.83 ±0.71
8.98 ±0.67
F(3,1331) = 22.81, p < .001
Q1>Q2, Q3, Q4, Q2>Q3, Q4, Q3>Q4
15 (n = 1081)
8.12 ±0.46
8.24 ±0.55
8.28 ±0.56
8.41 ±0.60
F(3,1077) = 11.49, p < .001
Q1>Q2, Q3, Q4, Q2>Q4, Q3>Q4
16 (n = 880)
7.93 ±0.44
7.94 ±0.43
7.99 ±0.48
8.03 ±0.47
F(3,876) = 2.15, p = .092
-
17 (n = 645)
7.68 ±0.34
7.71 ±0.33
7.72 ±0.32
7.81 ±0.36
F(3,641) = 4.29, p = .005
Q1>Q4, Q2>Q4, Q3>Q4
U20 (n = 634)
7.55 ±0.35
7.58 ±0.38
7.64 ±0.44
7.67 ±0.37
F(3,630) = 3.25, p = .022
Q1>Q3, Q4, Q2>Q4
Senior (n = 363)
7.45 ±0.48
7.49 ±0.47
7.51 ±0.45
7.52 ±0.47
F(3,359) = 0.45, p = .718
-
600m middle distance running (min)
10 (n = 363)
2.14.06 ±11.41
2.13.03 ±10.61
2.17.61 ±13.79
2.21.28 ±13.47
F(3,359) = 7.67, p < .001
Q1>Q3, Q4, Q2>Q3, Q4
11 (n = 628)
2.07.94 ±12.04
2.09.20 ±13.03
2.12.11 ±12.46
2.13.09 ±12.62
F(3,624) = 5.41, p < .001
Q1>Q3, Q4, Q2>Q3, Q4
12 (n = 710)
2.00.92 ±11.50
2.02.26 ±11.74
2.04.17 ±11.39
2.04.59 ±12.29
F(3,706) = 3.72, p < .011
Q1>Q3, Q4
13 (n = 808)
1.53.56 ±10.14
1.55.55 ±10.61
1.57.38 ±11.09
2.00.45 ±11.11
F(3,804) = 14.85, p < .001
Q1>Q3, Q4, Q2>Q4, Q3>Q4
14 (n = 559)
1.45.66 ±8.43
1.47.86 ±9.24
1.50.21 ±10.98
1.51.04 ±9.48
F(3,555) = 9.12, p < .001
Q1>Q2, Q3, Q4 Q2>Q3, Q4
15 (n = 250)
1.37.57 ±8.04
1.38.30 ±6.69
1.39.00 ±6.58
1.41.20 ±9.35
F(3,246) = 2.34, p = .074
-
16 (n = 193)
1.35.02 ± 8.71
1.36.22 ± 7.43
1.34.45 ±6.06
1.35.45 ±6.82
F(3,189) = 0.51, p = .675
-
17 (n = 129)
1.30.58 ±4.16
1.31.63 ±4.45
1.31.12 ±5.44
1.33.56 ±5.26
F(3,125) = 2.06, p = .110
-
U20 (n = 128)
1.27.15 ±4.15
1.28.84 ±5.96
1.28.05 ±4.59
1.28.98 ±4.05
F(3,124) = 1.04, p = .379
-
Senior (n = 80)
1.27.42 ±9.16
1.31.54 ±12.02
1.28.74 ±9.12
1.26.28 ±4.56
F(3,76) = 1.00, p = .398
-
U20: 18–19 years, Senior: 20–34 years> indicate significant better performance for athletes born in quartiles at the left side of the sign compared to those born in
quartiles at the right side.
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Table 3. On overview over OR 95% [CI] of being among the top-100 athletes and born in Q1 compared to Q4.
Females
Males
Competition class (years)
60m sprint
600m
60m sprint
600m
10
2.89 [1.36–6.13]
5.15 [2.03–13.06]
2.54 [1.18–5.49]
4.26 [1.77–10.29]
11
2.49 [1.29–4.81]
3.50 [1.64–7.497]
2.26 [1.10–4.66]
3.17 [1.42–7.09]
12
1.60 [.85–3.01]
2.16 [1.11–4.179]
7.82 [3.08–19.85]
1.64 [.88–3.06]
13
1.76 [.87–3.59]
2.06 [1.03–4.149]
5.81 [2.62–12.87]
4.97 [2.37–10.43]
14
2.07[1.06–4.05]
1.69 [.83–3.432]
11.27 [3.49–36.45]
3.21 [1.52–6.75]
15
.96 [.53–1.74]
1.78 [.81–3.931]
2.59 [1.23–5.45]
1.50 [.72–3.14]
16
1.19 [.64–2.22]
2.04 [.77–5.393]
1.88 [.93–3.80]
1.68 [.74–3.82]
17
1.01 [.52–1.94]
.69 [.19–2.520]
2.28 [1.14–4.57]
3.18 [.92–11.03]
U20 (18–19)
1.34 [.70–2.59]

1.62 [.86–3.05]
1.87 [.55–6.32]
Senior (20–34)
1.19 [.49–3.03]

1.98 [1.00–3.91]

 less than 100 results.
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fact that the chronologically oldest athletes in each competition class, on average, are more bio-
logically mature and therefore have more developed anthropometric and physical attributes
that aid performance [5–9, 29–32]. Indeed, another possible explanation for our findings
could also be linked with possible skewed birth date distribution in the greater Norwegian
population. Thus, we checked the Medical Birth Registry of Norway (MBRN) (http://
statistikkbank.fhi.no/mfr/) for quarterly distribution of births in Norway between 1996 and
2010, and found that 24.8%, 26.0%, 26.1% and 23.0% were born in Q1-Q4 respectively. Even
though the number of births was not totally equal between quartiles, it is highly unlikely that
the RAE in the present study can be explained by the distribution of births. Our findings are
thus probably linked to the maturational hypothesis.
In sprint, the advantage of being born early in the year lasted longer in males than in
females. Better results for those born early in the year compared to those born late was seen
until competition class 16 years in females, and until competition class U20 in males. In boys,
higher OR of being among the top-100 sprinters when born in the first quartile compared to
the last quartile was seen in most competition classes and even at senior level. Highest OR
among males was found in the competition class 14 years, where it was 11 times more likely to
be among the top-100 athletes for those born in the first quartile of the year compared to those
born in the last. In girls, higher OR was only seen in the competition classes 10, 11 and 14
years, with the highest OR in the youngest competition class. The above-mentioned sex differ-
ences may be explained by the timing of puberty. The timing of puberty could be one explana-
tion for the high OR for boys in the age of 12 to 14 years in explosive events like 60m sprint,
and also an explanation for high OR in earlier ages (10 and 11 years) in girls. Therefore, we
speculate that the competition classes with high OR are partly due to the fact that these age
groups have larger differences in physical capacity between athletes that are born early and late
in the year. Indeed, girls enter puberty at a younger age compared to boys [33], and the longer
occurrence and larger RAE in males may be explained by the later onset of puberty and the
more pronounced increase in muscle mass which is an advantage in explosive events [34, 35].
Further, increased motivation, more systematic training and better training facilities as a con-
sequence of success in adolescence may explain the persistence of RAE in the present study
after puberty among male senior sprinters [11, 13–15].
Fig 2. An overview of odds ratio (OR) of being among the top 100 athletes and born in Q1 compared to Q4 for girls (A) and boys (B).
https://doi.org/10.1371/journal.pone.0273472.g002
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Kearney and colleagues (2018) found a similar trend among males at highest performance
level in sprint in the UK, showing higher OR of being born in the first quartile of the year com-
pared to the last in all competition classes (U13, U15, U17, U20 and senior), with the highest
OR in U15 (13 and 14 years old). Also, Romann and colleagues (2015) found higher OR
among Swiss boys between 8 and 15 years at highest performance level in sprint. Among girls,
Kearney and colleagues (2018) showed higher OR in the competition classes U13, U15 and
U17, with the highest OR among the youngest (11 and 12 years old). Unlike the present study,
they found RAE in girls over 14 years of age. The longer persisting RAE among girls in the
study by Kearney and colleagues (2018) may be due to the different organization of competi-
tion classes in the UK with two year-bands instead of annual competition classes as in Norway.
In middle-distance running, significant better result among athletes born in the first quar-
tile of the year compared to those born in last quartile was seen until competition class 14
years in males. In middle-distance running, significant better result among athletes born in the
first quartile of the year compared to those born in last quartile was seen until competition
class 14 years in males. In girls RAE was present up to the competition class 16 years, with
exception of in competition the classes 14 and 15 years. The OR of being among the top-100
middle distance runners when born in first quartile compared to last quartile was in the pres-
ent study higher in most competition classes until the age of 14 years in boys. Highest OR was
seen in the competition class 13 years, where it was 5 times more likely to be among the top-
100 athletes for those born in the first quartile of the year compared to those born in the last.
Kearney and colleagues (2018) found higher OR in male middle distance running in the com-
petition classes U13, U15 and U17 in the UK. Highest OR was found in the competition class
U15 (13 and 14 years old), which is in line with our findings. However, again we cannot
exclude that the different organization of competition classes between Norway and the UK can
explain the longer existence of RAE in the UK. In girls, OR progressively decreased from the
competition class from 10 to 13 years. Similar, Kearny and colleagues (2018) found higher OR
in girls U13 (11 and 12 years old) and U15 (13 and 14 years old), with the highest OR among
the youngest. As in sprint highest OR was seen at earlier age in girls than in boys, and may be
due to earlier puberty onset in girls as mentioned above [33]. Unlike in male sprint, RAE did
not last into adulthood in middle-distance running.
The advantage of being born early in the year lasted longer in sprint than in middle-dis-
tance running in males, indicating that puberty affects performance in sprint and middle-dis-
tance running differently in males. This is most likely due to the different physical demands in
the two events. In sprint, force and power are important factors for performance [29, 32],
whereas maximal oxygen uptake is important in middle-distance running [36]. The increase
in body mass/muscle mass during puberty improves force and power relevant for sprint
events. Although the increase in muscle mass associated with growth and maturation facilitates
the use of oxygen and thus improves the absolute VO2max (Lmin-1), the concomitant increase
in body mass results in an almost unchanged VO2max with age during puberty when expressed
in relation to body mass (mlkg-1min-1) [37, 38]. For girls, increased body mass during
puberty is not necessarily an advantage in explosive events or in aerobic events as more body
fat mass is accumulated compared to boys [38]. Increased body mass may affect the occurrence
of RAE, as those born early in the year, on average, might gain weight before those born later
in the year if entering puberty earlier. One causal explanation for the decreasing OR at older
age in this study may be because the relative age difference in each age group are lower at
higher age. i.e. the relative age difference within an age group are higher for the 10-year-old
athletes, than for athletes that are twenty years old.
The stronger RAE found, especially in males, in explosive events compared to in endurance
events, have previously been shown by others [23, 39]. Stronger RAEs among males at higher
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level athletes than in females as in the present study are also in accordance with previous stud-
ies [18, 20–23, 39]. However, some researchers have proposed strategies to limit the RAE in
track and field. For instance, Romann and colleagues (2015) showed a very small or no RAE in
sprint among 8 to 15 years old boys when correcting for relative age within each chronological
age group, so that children were divided into age groups based on rotating cut-off dates. More
recently, Brustio and Boccia [24] investigated an approach where they applied a corrective
adjustment procedure in 16- and 17-year-old male and female top-level sprinters. From their
retrospective analysis based on longitudinal data, the estimated expected performance changes
for each annual group minimized or removed the RAE. Specifically, the results suggested an
annual percentage performance difference between males of 2.02% - 2.23% and for female of
1.65% - 1.78%, and that when race results were adjusted based on these findings a more equal
birth date distribution were evident compared to uncorrected performance times. Thus, to
avoid that child born late in the year always are the youngest in their competition class with
lesser chance to succeed, it could be possible to either adjust their performance times based on
previous longitudinal data [24] or implement an alternative competition structure where com-
petition is based on rolling cut-off birth dates so that children alternate in being the oldest and
youngest in their age group [18]. These strategies may reduce drop-out in athletes born late in
the year.
In conclusion, being born early in the year in events with high demand for specific physical
capacities is an advantage in both sexes in most of the youngest competition classes. The age
with the highest odds of being among the top-100 athletes corresponds with the age where
growth and maturation naturally affect the ability to perform physically in both sexes.
Although RAE and maturation are two different constructs, our findings propose that the
older individuals in each competition class might have benefitted from natural improvements
in performance due to puberty. It is important that both athletes, parents and coaches are
aware of the RAE, and focus on mastery and progress in training and competitions regardless
of performance level. Identifying talents at an early age is a difficult task thus the main goal for
practitioners in track and field events dependent on high physical capacities should be to
ensure that all athletes are given a chance to reach their potential, regardless of chronological
age or maturational status. This could keep children and adolescence within the sport for lon-
ger, which also has implications for lifelong physical activity. It will be of interest in a further
study to investigate the occurrence of RAEs in events as hurdle, high jump and shot-put where
technique may be of greater importance than physical capacities.
Supporting information
S1 Table. Number of athletes born in each quartile who ran 60m.
(TIF)
S2 Table. Number of athletes born in each quartile who ran 600m.
(TIF)
Acknowledgments
Thanks to Trond Engevik for organizing the database and to the The Norwegian Athletics Fed-
eration for given the permission to use the data.
Author Contributions
Conceptualization: Hilde Gundersen, Terje Dalen.
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Data curation: Hilde Gundersen.
Formal analysis: Hilde Gundersen, Anette Harris, Terje Dalen.
Methodology: Terje Dalen.
Project administration: Hilde Gundersen.
Writing – original draft: Hilde Gundersen, Atle Guttormsen, Cecilie Brekke Rygh.
Writing – review & editing: Anette Harris, Halvard Grendstad, Morten Kristoffersen, Atle
Guttormsen, Terje Dalen, Cecilie Brekke Rygh.
References
1.
Aubert S, Barnes JD, Abdeta C, Abi Nader P, Adeniyi AF, Aguilar-Farias N, et al. Global Matrix 3.0
Physical Activity Report Card Grades for Children and Youth: Results and Analysis From 49 Countries.
J Phys Act Health. 2018; 15(S2):S251–S73. https://doi.org/10.1123/jpah.2018-0472 PMID: 30475137
2.
Cobley S, Baker J, Wattie N, McKenna J. Annual age-grouping and athlete development: a meta-analyt-
ical review of relative age effects in sport. Sports Med. 2009; 39(3):235–56. https://doi.org/10.2165/
00007256-200939030-00005 PMID: 19290678
3.
Rogol AD. Androgens and puberty. Mol Cell Endocrinol. 2002; 198(1–2):25–9. https://doi.org/10.1016/
s0303-7207(02)00365-9 PMID: 12573811
4.
Rogol AD, Roemmich JN, Clark PA. Growth at puberty. J Adolesc Health. 2002; 31(6 Suppl):192–200.
5.
Malina RM, Eisenmann JC, Cumming SP, Ribeiro B, Aroso J. Maturity-associated variation in the
growth and functional capacities of youth football (soccer) players 13–15 years. Eur J Appl Physiol.
2004; 91(5–6):555–62. https://doi.org/10.1007/s00421-003-0995-z PMID: 14648128
6.
Malina RM, Martinho DV, Valente-Dos-Santos J, Coelho ESMJ, Koziel SM. Growth and Maturity Status
of Female Soccer Players: A Narrative Review. Int J Environ Res Public Health. 2021; 18(4). https://doi.
org/10.3390/ijerph18041448 PMID: 33557121
7.
Armstrong N, Welsman JR. Cardiovascular responses to submaximal treadmill running in 11 to 13 year
olds. Acta Paediatr. 2002; 91(2):125–31. https://doi.org/10.1080/080352502317285081 PMID:
11951996
8.
Geithner CA, Thomis MA, Vanden Eynde B, Maes HH, Loos RJ, Peeters M, et al. Growth in peak aero-
bic power during adolescence. Med Sci Sports Exerc. 2004; 36(9):1616–24. https://doi.org/10.1249/01.
mss.0000139807.72229.41 PMID: 15354046
9.
Gil SM, Badiola A, Bidaurrazaga-Letona I, Zabala-Lili J, Gravina L, Santos-Concejero J, et al. Relation-
ship between the relative age effect and anthropometry, maturity and performance in young soccer
players. J Sports Sci. 2014; 32(5):479–86. https://doi.org/10.1080/02640414.2013.832355 PMID:
24050650
10.
Rubia A, Bjorndal CT, Sanchez-Molina J, Yague JM, Calvo JL, Maroto-Izquierdo S. The relationship
between the relative age effect and performance among athletes in World Handball Championships.
PLoS One. 2020; 15(3):e0230133. https://doi.org/10.1371/journal.pone.0230133 PMID: 32214322
11.
Musch J, Grondin S. Unequal competition as an impediment to personal development: a review of the
relative age effect in sport. Developmental Review. 2001; 21(2):147–67.
12.
Brustio PR, Lupo C, Ungureanu AN, Frati R, Rainoldi A, Boccia G. The relative age effect is larger in Ital-
ian soccer top-level youth categories and smaller in Serie A. PLoS One. 2018; 13(4):e0196253. https://
doi.org/10.1371/journal.pone.0196253 PMID: 29672644
13.
Harter S. Effectance motivation reconsidered: Toward a developmental model. Human Development.
1978; 1:34–64.
14.
Helsen WF, Starkes JL, Van Winckel J. The influence of relative age on success and dropout in male
soccer players. American Journal of Human Biology. 1998; 10(6):791–8. https://doi.org/10.1002/(SICI)
1520-6300(1998)10:6<791::AID-AJHB10>3.0.CO;2-1 PMID: 28561412
15.
Pena-Gonzalez I, Fernandez-Fernandez J, Moya-Ramon M, Cervello E. Relative Age Effect, Biological
Maturation, and Coaches’ Efficacy Expectations in Young Male Soccer Players. Res Q Exerc Sport.
2018; 89(3):373–9. https://doi.org/10.1080/02701367.2018.1486003 PMID: 30015598
16.
Muller L, Gonaus C, Perner C, Muller E, Raschner C. Maturity status influences the relative age effect in
national top level youth alpine ski racing and soccer. PLoS One. 2017; 12(7):e0181810. https://doi.org/
10.1371/journal.pone.0181810 PMID: 28759890
PLOS ONE
RAE in track and field
PLOS ONE | https://doi.org/10.1371/journal.pone.0273472
September 6, 2022
10 / 12
17.
Smith KL, Weir PL, Till K, Romann M, Cobley S. Relative Age Effects Across and Within Female Sport
Contexts: A Systematic Review and Meta-Analysis. Sports Med. 2018; 48(6):1451–78. https://doi.org/
10.1007/s40279-018-0890-8 PMID: 29536262
18.
Romann M, Cobley S. Relative age effects in athletic sprinting and corrective adjustments as a solution
for their removal. PLoS One. 2015; 10(4):e0122988. https://doi.org/10.1371/journal.pone.0122988
PMID: 25844642
19.
Jakobsson J, Julin AL, Persson G, Malm C. Darwinian Selection Discriminates Young Athletes: the Rel-
ative Age Effect in Relation to Sporting Performance. Sports Med Open. 2021; 7(1):16. https://doi.org/
10.1186/s40798-021-00300-2 PMID: 33650038
20.
Brazo-Sayavera J, Martinez-Valencia MA, Muller L, Andronikos G, Martindale RJJ. Identifying talented
track and field athletes: The impact of relative age effect on selection to the Spanish National Athletics
Federation training camps. J Sports Sci. 2017; 35(22):2172–8. https://doi.org/10.1080/02640414.2016.
1260151 PMID: 27879175
21.
Brazo-Sayavera J, Martinez-Valencia MA, Muller L, Andronikos G, Martindale RJJ. Relative age effects
in international age group championships: A study of Spanish track and field athletes. PLoS One. 2018;
13(4):e0196386. https://doi.org/10.1371/journal.pone.0196386 PMID: 29689117
22.
Brustio PR, Kearney PE, Lupo C, Ungureanu AN, Mulasso A, Rainoldi A, et al. Relative Age Influences
Performance of World-Class Track and Field Athletes Even in the Adulthood. Front Psychol. 2019;
10:1395. https://doi.org/10.3389/fpsyg.2019.01395 PMID: 31275208
23.
Hollings SC, Hume PA, Hopkins WG. Relative-age effect on competition outcomes at the World Youth
and World Junior Athletics Championships. Eur J Sport Sci. 2014; 14 Suppl 1:S456–61. https://doi.org/
10.1080/17461391.2012.713007 PMID: 24444241
24.
Brustio PR, Boccia G. Corrective procedures remove relative age effect from world-class junior sprint-
ers. J Sports Sci. 2021; 39(22):2603–10. https://doi.org/10.1080/02640414.2021.1947618 PMID:
34210248
25.
Boccia G, Cardinale M, Brustio PR. Performance progression of elite jumpers: Early performances do
not predict later success. Scand J Med Sci Sports. 2021; 31(1):132–9. https://doi.org/10.1111/sms.
13819 PMID: 32881090
26.
Boccia G, Cardinale M, Brustio PR. Elite Junior Throwers Unlikely to Remain at the Top Level in the
Senior Category. Int J Sports Physiol Perform. 2021; 16(9):1281–7. https://doi.org/10.1123/ijspp.2020-
0699 PMID: 33647881
27.
Nakata H, Sakamoto K. Sex differences in relative age effects among Japanese athletes. Percept Mot
Skills. 2012; 115(1):179–86. https://doi.org/10.2466/10.05.17.PMS.115.4.179-186 PMID: 23033755
28.
Romann M, Fuchslocher J. The need to consider relative age effects in women’s talent development
process. Percept Mot Skills. 2014; 118(3):651–62. https://doi.org/10.2466/30.10.PMS.118k24w8
PMID: 25068738
29.
Colyer SL, Nagahara R, Takai Y, Salo AIT. The effect of biological maturity status on ground reaction
force production during sprinting. Scand J Med Sci Sports. 2020; 30(8):1387–97. https://doi.org/10.
1111/sms.13680 PMID: 32285541
30.
Handelsman DJ. Sex differences in athletic performance emerge coinciding with the onset of male
puberty. Clin Endocrinol (Oxf). 2017; 87(1):68–72. https://doi.org/10.1111/cen.13350 PMID: 28397355
31.
Radnor JM, Oliver JL, Waugh CM, Myer GD, Moore IS, Lloyd RS. The Influence of Growth and Matura-
tion on Stretch-Shortening Cycle Function in Youth. Sports Med. 2018; 48(1):57–71. https://doi.org/10.
1007/s40279-017-0785-0 PMID: 28900862
32.
Rumpf MC, Cronin JB, Oliver J, Hughes M. Kinematics and Kinetics of Maximum Running Speed in
Youth Across Maturity. Pediatr Exerc Sci. 2015; 27(2):277–84. https://doi.org/10.1123/pes.2014-0064
PMID: 25389204
33.
Oehme N, Bruserud IS, Madsen A, Juliusson PB. Is puberty starting earlier than before? Tidsskr Nor
Laegeforen. 2020; 140(12).
34.
Ramos E, Frontera WR, Llopart A, Feliciano D. Muscle strength and hormonal levels in adolescents:
gender related differences. Int J Sports Med. 1998; 19(8):526–31. https://doi.org/10.1055/s-2007-
971955 PMID: 9877143
35.
Moran JJ, Sandercock GR, Ramirez-Campillo R, Meylan CM, Collison JA, Parry DA. Age-Related Vari-
ation in Male Youth Athletes’ Countermovement Jump After Plyometric Training: A Meta-Analysis of
Controlled Trials. J Strength Cond Res. 2017; 31(2):552–65. https://doi.org/10.1519/JSC.
0000000000001444 PMID: 28129282
36.
Bassett DR Jr., Howley ET. Limiting factors for maximum oxygen uptake and determinants of endur-
ance performance. Med Sci Sports Exerc. 2000; 32(1):70–84. https://doi.org/10.1097/00005768-
200001000-00012 PMID: 10647532
PLOS ONE
RAE in track and field
PLOS ONE | https://doi.org/10.1371/journal.pone.0273472
September 6, 2022
11 / 12
37.
Armstrong N, Tomkinson G, Ekelund U. Aerobic fitness and its relationship to sport, exercise training
and habitual physical activity during youth. Br J Sports Med. 2011; 45(11):849–58. https://doi.org/10.
1136/bjsports-2011-090200 PMID: 21836169
38.
Landgraff HW, Riiser A, Lihagen M, Skei M, Leirstein S, Hallen J. Longitudinal changes in maximal oxy-
gen uptake in adolescent girls and boys with different training backgrounds. Scand J Med Sci Sports.
2021; 31 Suppl 1:65–72. https://doi.org/10.1111/sms.13765 PMID: 33871085
39.
Kearney PE, Hayes PR, Nevill A. Faster, higher, stronger, older: Relative age effects are most influen-
tial during the youngest age grade of track and field athletics in the United Kingdom. J Sports Sci. 2018;
36(20):2282–8. https://doi.org/10.1080/02640414.2018.1449093 PMID: 29513142
PLOS ONE
RAE in track and field
PLOS ONE | https://doi.org/10.1371/journal.pone.0273472
September 6, 2022
12 / 12

Performance in youth track and field is associated with birth quartile. A register-based study among athletes in Norway from 10 years to senior level.
Gundersen, Hilde,Harris, Anette,Grendstad, Halvard,Kristoffersen, Morten,Guttormsen, Atle,Dalen, Terje,Rygh, Cecilie Brekke