1
Vol.:(0123456789)
Scientific Reports |         (2023) 13:9303  
| https://doi.org/10.1038/s41598-023-36050-2
www.nature.com/scientificreports
Participation and performance 
trends in short‑, medium, 
and long‑distance duathlon
Jonas Turnwald 1, Caio Victor Sousa 2, Marilia Santos Andrade 3, Mabliny Thuany 4, Ivan Cuk 5, 
Pantelis Theodoros Nikolaidis 6, Katja Weiss 1 & Beat Knechtle 1,7*
Participation and performance trends of male and female athletes have been thoroughly analyzed 
in various endurance sports. Knowing these trends can help coaches and athletes prepare for 
competitions and may influence their training strategy and career planning. However, duathlon 
events—consisted of two splits of running (Run1 and Run2) interspersed by a split of cycling (Bike)—
have not been thoroughly studied, unlike other endurance sports. The present study aimed to 
compare participation and performance trends in duathletes who competed in duathlon races hosted 
by World Triathlon or affiliated National Federations between 1990 and 2021. A total of 25,130 
results of age group finishers who competed in run‑bike‑run duathlon races of varying distances 
were analyzed with different general linear models. Races were divided into three distances: short‑
distance (up to 5.5 km run, 21 km bike, 5 km run), medium‑distance (5–10 km run, 30–42 km bike, 
7–11 km run) and long‑distance (at least 14 km run, 60 km bike, 25 km run). On average, women 
represented 45.6% of all finishers in short‑distance, 39.6% in medium‑distance and 24.9% in long‑
distance duathlon races. Throughout the years, men were consistently faster than women in all three 
race legs (Run 1, Bike, and Run 2) in all three distances across all age groups, and women could not 
reduce the performance gap. Concerning the age of peak performance, duathletes of the age group 
30–34 finished most often in the top three in short‑ and medium‑distance duathlons, whereas male 
duathletes of the age group 25–29 and female duathletes of the age group 30–34 finished most often 
in the top three in long‑distance duathlons. Women participated less, especially in longer distances, 
and were constantly slower than men. Duathletes of the age group 30–34 finished most often in the 
top three. Future studies should analyze participation and performance trends in further subgroups 
(e.g., elite athletes) and pacing behaviours.
Abbreviations
APP 
 Age of peak performance
GLM 
 General linear models
ITU 
 International Triathlon Union
WT 
 World Triathlon
Non-professional endurance sports have been consistently growing in popularity during the last decades. Accord-
ingly, the scientific community has studied participation and performance trends in various sports such as 
 triathlon1,2, distance  running3–5,  cycling6,7 and  duathlon8–10. Duathlon is a unique multi-discipline sport in which 
athletes compete in a run-bike-run format. It is internationally governed by Word Triathlon (WT), formerly the 
International Triathlon Union (ITU). WT distances include a sprint-distance (5 km run, 20 km bike, 2.5 km run), 
standard-distance (5–10 km run, 30–40 km bike, 5 km run), middle-distance (10–20 km run, 60–90 km bike, 
10 km run) and long-distance (10–20 km run, 120–150 km bike, 20–30 km run), but individual race distances 
can  vary11. Participation and performance trends in duathlons have been investigated before. Nonetheless, to 
the best of our knowledge, the current literature is either based on a specific  race8,10,12 or a specific  distance9.
OPEN
1Institute of Primary Care, University of Zurich, Zurich, Switzerland. 2Health and Human Sciences, Loyola 
Marymount University, Los Angeles, USA. 3Department of Physiology, University of Sao Paulo, Sao Paulo, 
Brazil. 4Faculty of Sports, University of Porto, Porto, Portugal. 5Faculty of Sport and Physical Education, 
University of Belgrade, Belgrade, Serbia. 6School of Health and Caring Sciences, University of West Attica, 
Athens, Greece. 7Medbase St. Gallen Am Vadianplatz, Vadianstrasse 26, 9001 St. Gallen, Switzerland. *email: 
beat.knechtle@hispeed.ch
2
Vol:.(1234567890)
Scientific Reports |         (2023) 13:9303  | 
https://doi.org/10.1038/s41598-023-36050-2
www.nature.com/scientificreports/
The performance gap between sexes is one of the main points of interest in endurance sports research. Con-
sistent with studies on other endurance  sports1,3–6,13, slower race times of women were observed in previously 
studied duathlon  events8–10. Recently, Romero-Ramos et al.9 analyzed performance differences, with regard to 
age and sex, of the top ten age group athletes competing in the ITU Duathlon World Championships from 2005 
to 2016 on the standard-distance length. Men outperformed women in all age groups in all race legs and with 
advancing age, the differences between both sexes  increased9. Previous investigations focused on the Powerman 
Zofingen with its two distances (short-distance: ~ 10 km run, 50 km bike, 5 km run; long-distance: ~ 10 km run, 
150 km bike, 30 km run)8,10. A consistent sex difference of ~ 18–19% in all race legs and total times was observed 
in the annual top ten elite athletes who participated in the long-distance races between 2002 and  201110. When all 
finishers of the short- and long-distance races from 2003 to 2017 were analyzed, the sex difference was similar in 
both versions (~ 8%)8. These differences in race times between females and males might be explained by physi-
ological, anthropometric, genetic, hormonal and psychological  factors13–15. However, the sex gap seems to be 
dependent on the race distance. In other endurance sports, such as distance running, the sex gap has been shown 
to decrease in ultra-endurance-distances15–17. In a study by Waldvogel et al.16, a higher sex gap was observed in 
50 mile (9.13%) than in 100 mile (4.41%) ultra-marathon races.
Age is another important aspect affecting performance in endurance sports. With advancing age, cellular 
deterioration and loss of tissue function occur, affecting physical performance in different manners based on the 
specific requirements of the  activity18–20. Compared to sprint races, the age of peak performance (APP) seems to 
be higher in endurance  races2,20. This relationship is also reflected in endurance events of different distances. For 
instance, Nikolaidis et al.12 investigated the APP in the short- and long-distance races of the Powerman Zofingen 
and reported that the fastest age group was younger in the short-distance race (age group 20–24) than in the long-
distance race (age group 25–29). Conversely, Romero-Ramos et al.9 reported a higher APP (age group 30–34) 
in both genders when the overall performance of the top ten athletes of each age group at the ITU Duathlon 
World Championships on the standard-distance was compared. As the race distances (~ 10 km run, 40 km bike, 
5 km run) were shorter compared to the short version of the Powerman Zofingen (~ 10 km run, 50 km bike, 
5 km run), the difference in the observed APP might be explained by the different study designs and the specific 
characteristics of the Powerman Zofingen. This highlights the importance of a more extensive dataset for a better 
understanding of the trends in  duathlon9,12. Up to now, no study regarding the APP in the sprint-distance exists.
The two disciplines, running and cycling, represent different types of locomotion with their own anthro-
pometric and physiological  correlates21,22. When the age-related performance decline of each discipline was 
analyzed separately, the cycling performance could be better maintained than the running performance in 
older  athletes8,9,23. This phenomenon was also observed in triathlon events, where the performance decline with 
increasing age was more prominent in swimming and running than in  cycling1.
Little is known so far concerning participation trends in duathlon. When investigating finishers of the Power-
man Zofingen from 2003 to 2017, 15.2% of all finishers in the long-distance and 15.9% of all finishers in the short-
distance were  women8. In the shorter ITU Duathlon World Championships (standard-distance), higher participa-
tion of women was observed from 2005 to 2016. Romero-Ramos et al.9 reported that 23.5% of all finishers were 
women. More studies have been conducted on triathlon races, with an increase in female participants observed 
since the  1980s1. Also, in triathlon, it seems that women tend to compete in shorter than longer  distances1,24–26.
Although the above-mentioned literature provides some information about participation and performance 
trends in duathlon, no study has investigated the worldwide trends across different race distances so far. Knowl-
edge of these trends would not only be interesting for scientists but could also help athletes and coaches prepare 
for races and could influence their training strategy depending on the sex and age of an athlete and the specific 
distance of a race. Furthermore, duathletes who are aware of different APPs in different race distances would be 
able to plan their career more precisely.
Therefore, the present study aimed to investigate the worldwide participation and performance trends in 
duathlon with an extensive dataset, including results from finishers who participated in duathlon races worldwide 
across different distances over several decades. Based upon the previously mentioned findings, we hypothesized 
firstly that more male than female finishers would be recorded for all distances and especially for longer distances, 
secondly, that men would be faster than women, thirdly that the sex gap would narrow throughout the years and 
fourthly, that the APP is higher in longer race distances.
Methods
Ethical approval and consent to participate. 
This study was approved by the Institutional Review 
Board of Kanton St. Gallen, Switzerland, with a waiver of the requirement for informed consent of the partici-
pants as the study involved the analysis of publicly available data (EKSG 01/06/2010). The study was conducted 
in accordance with recognized ethical standards according to the Declaration of Helsinki adopted in 1964 and 
revised in 2013.
Duathlon events. 
Results of international events hosted by WT or affiliated National Federations were 
obtained from the results section of WT’s official  website27. To ensure comparability, we only included regular 
international duathlon races that were either World Championship or Continental Championship races, and 
excluded Cross- or Winter-Duathlons. A total of 187 races were identified, which have taken place from 1990 to 
2021. However, distances were not stated on the downloadable result lists. Therefore, information about the race 
distances had to be retrieved in multiple ways. The race distances were listed in the “Program notes” section for 
some participant groups. If this was not available, we searched the event page of a specific race with the three 
tabs “Event Info”, “Local Info” and “Contact” for any information. If no distance was available, we scanned the 
event page for an external link to the official event website of the race. If available, we thoroughly browsed this 
3
Vol.:(0123456789)
Scientific Reports |         (2023) 13:9303  | 
https://doi.org/10.1038/s41598-023-36050-2
www.nature.com/scientificreports/
website to find the relevant data. An external link was found for some races, but the website was no longer active 
or contained non-corresponding content. In this case, we searched for archived versions of the event website on 
the Wayback Machine of the Internet Archive to get any information regarding the  distances28. Nonetheless, no 
distances could be retrieved for some events/participant groups. We only included data of participant groups, if 
a clear association of a respective participant group with a specific distance was present. As individual race dis-
tances differed and did not always match a specific WT distance, we divided the races into three distances: short-
distance (up to 5.5 km run, 21 km bike, 5 km run), medium-distance (5–10 km run, 30–42 km bike, 7–11 km 
run) and long-distance (at least 14 km run, 60 km bike, 25 km run).
For the purpose of this study, we only included successful finishers of adult age group categories who com-
peted in a duathlon race in a run-bike-run race mode. Except for the age group 18–19 years, each age group 
covers a five-year period (20–24 years through to 85–89 years). Required data from the race results included 
the name of an athlete, the sex, the split times, the total time and the age group. The year and name of an event, 
obtained from the corresponding event page on WT’s website, and the distance were added. No races from the 
years 1990, 1992, 1996, 1997, and 2004 could be included. In short-distance duathlon, the first race that could be 
included was in 2011, in medium-distance duathlon in 1991, and in long-distance duathlon in 2002. Excluded 
were results from the 1997 Guernica ITU Duathlon World Championships, as the split times did not match the 
overall times in most cases, and the 2003 Affoltern ITU Duathlon World Championships, as the stated distance 
appeared to be wrong. Moreover, finishers with empty race times and statistical outliers in any of the race legs 
(slower/faster by three standard deviations from the mean) were excluded. In total, 66 races met the inclusion 
criteria.
Statistical analysis. 
Descriptive statistics were presented using mean ± standard deviation and frequencies. 
All data showed parametric distribution and homogeneity of variance through the Kolmogorov–Smirnov’s and 
Levene’s tests, respectively. Average speed (kilometers per hour (km/h)) was established as the dependent vari-
able for all models. General linear models (GLM) with two factors (two-way ANOVA) were applied for each dis-
tance (short, medium, and long) considering the independent factors “sex × age group” and “sex × calendar year”. 
Further GLM were conducted for men and women separately with “event distance × age group” as independent 
factors. Fisher’s least significant difference was applied as a post-hoc test to identify specific differences between 
independent factors. Partial eta square (ηp
2) was applied as a measure of effect size, considering ηp
2 = 0.01 as a 
small effect, ηp
2 = 0.06 as a moderate effect, and ηp
2 = 0.14 as a large effect. Statistical significance was defined as 
p < 0.05. All statistical analyses were carried out with Statistical Software for the Social Sciences  (IBM® SPSS v.25, 
Chicago, Ill, USA).
Results
A total of 25,130 finishers were included. Short-distance duathlon included 4641 men and 2118 women 
(n = 6759), medium-distance duathlon included 9970 men and 3921 women (n = 13,891), and long-distance 
duathlon included 3587 men and 893 women (n = 4480). Women’s participation in individual races ranged from 
18.5 to 55.9% in relation to men in short-distance duathlon (average: 45.6%), 13.3–51.7% in medium-distance 
duathlon (average: 39.6%) and 4.2–37.3% in long-distance duathlon (average: 24.9%). See Fig. 1 for detailed 
participation by sex and year.
Performance trends across age groups showed significant effects of both sex and age group for short-, 
medium-, and long-distance duathlon across all three race legs of the duathlon race (Run 1, Bike, Run 2). See 
Table 1 for details.
Pairwise comparisons showed that men had better performances than women across all age groups in all 
three race legs (Run 1, Bike, and Run 2) in all three duathlon distances. Finally, age group pairwise comparisons 
showed that, in short-distance duathlon, the age group was always significantly different from the previous one, 
but in medium-distance duathlon, the run performance started to drop at the age group 45–49 years in men and 
age group 50–54 years in women, whereas the bike performance started to drop at the age group 50–54 years 
in men and age group 55–59 years in women. In long-distance duathlon, the first running leg was stable until 
the age group 30–34 years in men and age group 50–54 years in women, whereas the bike performance and the 
second running leg were stable until the age group 50–54 years in both men and women. See Fig. 2.
Performance trends across calendar years showed significant effects of both sex and calendar years for short-, 
medium-, and long-distance duathlon across all three race legs of the duathlon race (Run 1, Bike, Run 2). See 
Table 2 for details.
Pairwise comparisons showed that men were consistently faster than women in all race legs and distances 
across all calendar years and no trend was observed that women reduced the sex gap throughout the years. 
Additionally, no apparent performance trend was seen in any distance throughout the years. See Fig. 3.
The GLM for men showed significant “event” and “age group” effects for Run 1 (event: F = 39.5, p < 0.001, 
ηp
2 = 0.52; age group: F = 76.9, p < 0.001, ηp
2 = 0.98; interaction: F = 9.5, p < 0.001, ηp
2 = 0.01), Bike (event: F = 24.5, 
p < 0.001, ηp
2 = 0.14; age group: F = 82.9, p < 0.001, ηp
2 = 0.96; interaction: F = 2.6, p < 0.001, ηp
2 < 0.01) and Run 
2 (event: F = 64.2, p < 0.001, ηp
2 = 0.54; age group: F = 75.2, p < 0.001, ηp
2 = 0.97; interaction: F = 6.0, p < 0.001, 
ηp
2 = 0.01). Similar results were found in women for Run 1 (event: F = 22.7, p < 0.001, ηp
2 = 0.18; age group: 
F = 65.7, p < 0.001, ηp
2 = 0.96; interaction: F = 2.0, p = 0.004, ηp
2 = 0.01), Bike (event: F = 13.8, p < 0.001, ηp
2 = 0.11; 
age group: F = 21.1, p < 0.001, ηp
2 = 0.88; interaction: F = 1.8, p = 0.016, ηp
2 = 0.01) and Run 2 (event: F = 38.9, 
p < 0.001, ηp
2 = 0.32; age group: F = 48.7, p < 0.001, ηp
2 = 0.95; interaction: F = 2.1, p = 0.002, ηp
2 = 0.01). See Fig. 4 
for details.
Pairwise comparisons for the men models showed that the average speeds in the three race distances differed 
from each other up to the age group 65–69 years in the running legs and age group 70–74 years in the cycling leg. 
4
Vol:.(1234567890)
Scientific Reports |         (2023) 13:9303  | 
https://doi.org/10.1038/s41598-023-36050-2
www.nature.com/scientificreports/
For the women models, a slower average speed was observed in long-distance races in comparison to the other 
distances up to the age group 55–59 years in the running legs and age group 60–64 years in the cycling leg (Fig. 4).
In the analyzed short- and medium-distance races, male and female athletes of the age group 30–34 years 
finished most often in the top three compared to other age groups. In long-distance races, men of the age group 
25–29 years and women of the age group 30–34 years finished most often in the top three. Overall, when all 
distances were considered, the age group 30–34 years was the most prevalent one in the top three in men and 
women. See Fig. 5 for details.
Discussion
This study intended to investigate the worldwide participation and performance trends of short-, medium- and 
long-distance duathlon over several decades. The participation in the investigated races did not increase over 
the years. This finding might not be generalized to the sport itself, as we considered only events hosted by WT 
or affiliated National Federations which were listed on WT’s website and did not compare the same races every 
year. Furthermore, the present study analyzed world and continental championships, but not local events, which 
may be preferred by age group athletes. Non-elite athletes often face real-world commitments and financial 
Figure 1.  Participation of men and women in short- (A), medium- (B), and long-distance (C) duathlon across 
calendar years.
5
Vol.:(0123456789)
Scientific Reports |         (2023) 13:9303  | 
https://doi.org/10.1038/s41598-023-36050-2
www.nature.com/scientificreports/
Table 1.  General linear model results with average speed as the dependent variable.
Duathlon
Sex
Age group
Sex × Age group
F
p
ηp
2
F
p
ηp
2
F
p
ηp
2
Short
Run 1
180.6
< 0.001
0.66
58.2
< 0.001
0.99
5.0
< 0.001
0.01
Bike
147.2
< 0.001
0.20
68.2
< 0.001
0.99
1.5
0.14
< 0.01
Run 2
135.4
< 0.001
0.47
58.3
< 0.001
0.99
3.5
< 0.001
0.01
Medium
Run 1
231.0
< 0.001
0.38
108.7
< 0.001
0.99
4.3
< 0.001
0.01
Bike
104.7
< 0.001
0.04
71.0
< 0.001
0.99
1.4
0.16
< 0.01
Run 2
137.3
< 0.001
0.10
156.4
< 0.001
0.99
2.0
0.02
< 0.01
Long
Run 1
119.8
< 0.001
0.30
31.7
< 0.001
0.97
1.4
0.16
< 0.01
Bike
119.9
< 0.001
0.29
19.4
< 0.001
0.95
1.4
0.19
< 0.01
Run 2
41.6
< 0.001
0.10
23.0
< 0.001
0.95
1.15
0.32
< 0.01
Figure 2.  Average speed in the three duathlon race legs of men and women in short-, medium-, and long-
distance duathlon across age groups. * over line: statistical significance between all age groups; *: statistical 
significance in comparison to the previous age group; # over line: statistical significance for sex across all age 
groups.
6
Vol:.(1234567890)
Scientific Reports |         (2023) 13:9303  | 
https://doi.org/10.1038/s41598-023-36050-2
www.nature.com/scientificreports/
Table 2.  General linear model results with average speed as the dependent variable.
Duathlon
Sex
Calendar year
Sex × Calendar year
F
p
ηp
2
F
p
ηp
2
F
p
ηp
2
Short
Run 1
275.2
< 0.001
0.94
8.6
0.001
0.90
3.7
< 0.001
0.01
Bike
292.7
< 0.001
0.94
43.7
< 0.001
0.98
3.9
< 0.001
0.01
Run 2
230.5
< 0.001
0.93
10.4
< 0.001
0.91
3.3
< 0.001
0.01
Medium
Run 1
303.8
< 0.001
0.32
31.6
< 0.001
0.97
2.0
< 0.001
< 0.01
Bike
245.1
< 0.001
0.31
98.0
< 0.001
0.99
2.2
0.001
< 0.01
Run 2
177.7
< 0.001
0.24
25.0
< 0.001
0.96
2.1
0.001
< 0.01
Long
Run 1
870.6
< 0.001
0.96
70.9
< 0.001
0.98
0.56
0.91
< 0.01
Bike
714.4
< 0.001
0.96
65.2
< 0.001
0.99
0.78
0.19
0.99
Run 2
226.9
< 0.001
0.88
27.6
< 0.001
0.97
0.75
0.77
< 0.01
Figure 3.  Average speed in the three race legs of men and women in short-, medium-, and long-distance 
duathlon across calendar years. # over line: statistical significance for sex across all calendar years.
7
Vol.:(0123456789)
Scientific Reports |         (2023) 13:9303  | 
https://doi.org/10.1038/s41598-023-36050-2
www.nature.com/scientificreports/
constraints that can make it difficult for them to travel to events and  compete29. In other endurance sports, such 
as long-distance running and cycling, an increased participation rate was observed in recent  years30–32. In addi-
tion, the number of members in national federations has grown in the last decades. In Germany, for example, the 
number of members of the National Triathlon Federation has more than doubled between 2001 and  202233,34.
An important finding was the lower number of female duathletes compared to male duathletes in all dis-
tances across all years. Women accounted on average for 45.6% of finishers in short-distance duathlon, 39.4% in 
medium-distance duathlon and 24.9% in long-distance duathlon. The lower rate of women finishers in longer race 
distances is in accordance with previous findings in triathlon and might be explained by motivational reasons, 
differences in training behaviour and sociocultural  conditions1,35,36.
Regarding performance, men were faster than women in all race legs in all distances across all age groups 
and calendar years. There is extensive literature on factors that explain the differences in performance between 
Figure 4.  Average speed in the three race legs of men and women separately in short-, medium-, and long-
distance duathlon across age groups. ** over line: statistical significance between all three events; *: statistically 
significant from the other two events.
8
Vol:.(1234567890)
Scientific Reports |         (2023) 13:9303  | 
https://doi.org/10.1038/s41598-023-36050-2
www.nature.com/scientificreports/
men and women in endurance  sports13–15,36. In addition to physiological differences, such as the lower maximal 
oxygen uptake  (VO2max) in female athletes, morphological differences, social factors, psychological factors and 
differences in training characteristics have to be considered concerning the sex  gap13,37. Female athletes were 
able to reduce the sex gap in ultra-endurance sports throughout the years, for example, in most ultra-marathon 
 distances38 and ultra-cycling  distances7. However, our hypothesis was not confirmed, as we did not find such a 
trend in any of the investigated distances throughout the years. Based on past findings, the analyzed distances 
in this study were not long enough to see such a trend, as the physiological and morphological advantages of 
women (e.g., better fatigue resistance, greater substrate efficiency and lesser energetic demands) rather seem to 
play a role in ultra- and extreme  distances15.
Moreover, no apparent performance trend could be observed in any of the investigated distances throughout 
the years. While Nikolaidis et al.8 also found an unchanged performance of male and female finishers in the 
“Powerman Zofingen” from 2003 to 2017, Gallman et al.39 found an increased performance of the annual top 
ten male and female triathletes who competed at the Ironman Hawaii from 1983 to 2012. Methodological dif-
ferences, including sample size, time frame and statistical procedures, may be related to the differences in these 
findings. For example, Gallman et al.39 analyzed the results of the top ten elite athletes, whereas we analyzed all 
successful finishers of adult age group categories. In many studies on performance trends in marathon races, a 
phenomenon was observed that “the faster get faster and the slower get slower”40–43. It is important to note that 
we analyzed data from multiple races, with differences in drafting rules, weather conditions, and track specifica-
tions, and not one specific race over a period of time, what may have impacted the results.
Another finding was that in short-distance duathlon, a statistically significant decline in performance with 
increasing age groups could be observed from the first age group (20–24 years), whereas the performance in 
medium- and long-distance duathlon was relatively stable up to a specific age group. In the analyzed medium-
distance races, a statistically significant drop in performance in the first and second run was for the first time 
observed at the age group 45–49 years in men and 50–54 years in women, while the cycling performance 
dropped later at the age group 50–54 years in men and 55–59 years in women. Previous studies on multi-
discipline sports already showed that the age-related performance decline seems to be higher in running than 
Figure 5.  The number of athletes in each age group who finished in the analyzed races in the top three by sex 
and distance.
9
Vol.:(0123456789)
Scientific Reports |         (2023) 13:9303  | 
https://doi.org/10.1038/s41598-023-36050-2
www.nature.com/scientificreports/
in  cycling1,19,44,45. This might be related to the distinct characteristics of the two disciplines. Running is a weight-
bearing stretch–shortening activity with a predominantly eccentric type of muscle action compared to cycling, 
which is a non-weight-bearing activity with concentric  contractions46,47. However, it is noteworthy that in a 
study performed by Swinnen et al.48 running-specific training could improve running economy while the cycling 
economy could not be improved by cycling-specific training. Regarding long-distance duathlon, a statistically 
significant drop in performance in the first run was for the first time observed at the age group 30–34 years in 
men and 50–54 years in women, while in the cycling and second running leg performance dropped at the age 
group 50–54 years in men and women.
A reason that the performance in medium- and long-distance duathlon was relatively stable up to a specific 
age group in contrast to short-distance duathlon might be that generally, more experienced athletes compete 
in longer race distances and it was postulated before that the amount of experience is highly important for the 
performance in multi-discipline  sports49.
When we analyzed the average speeds of men and women separately in the three race distances across 
the different age groups, particular differences could be observed. In men, a statistically significant difference 
between the average speeds of the three race distances could be observed up to the age group 65–69 years in 
both running legs and 70–74 years in the cycling leg. In women, on the other hand, only the average speed 
in long-distance duathlon was statistically significantly slower compared to the other two distances up to the 
age group 55–59 years in both running legs and 60–64 years in the cycling leg. Interestingly, no statistically 
significant difference could be observed between the average speeds of women in short- and medium-distance 
races. Although this phenomenon does not make physiological sense, it indicates that women have a lot of 
room for performance improvement in short-distance duathlon. In many endurance sports, it was previously 
shown that women adopted a more conservative pacing strategy than  men50–53. This might be explained by dif-
ferences regarding confidence, decision-making, risk perception and  willingness53. For example, compared to 
men, women showed relatively lower speeds in the beginning and relatively higher speeds at the end of a 100 km 
ultra-marathon  race54. One explanation could be that women did not allocate their energy resources in the best 
suitable manner. More studies are necessary to confirm or refute these results.
The only knowledge we have so far regarding pacing in a duathlon is derived from studies by Nikolaidis 
et al., who analyzed the effect of  aging23, sex and performance  level50 as well as the combined effect of aging and 
performance  level55 on pacing. However, these studies are based solely on the “Powerman Zofingen” results from 
2003 to 2017 with its two distances (10 km run, 50 km bike, 5 km run; ~ 10 km run, 150 km bike, 30 km run). 
The authors reported that women adopted a steadier pace and were relatively faster in the second  run50. To the 
best of our knowledge, no information regarding pacing behaviours in short-distance duathlon exists.
Regarding the APP, male and female athletes of the age group 30–34 years finished most often in the top three 
in short- and medium-distance races. This confirms past findings by Romero-Ramos et al.9 who analyzed the 
performance of the top ten athletes of each age group who competed at the ITU Duathlon World Champion-
ships from 2005 to 2016 and found that athletes of the age group 30–34 years performed best in the standard-
distance (~ 10 km run, 40 km bike, 5 km run). In long-distance duathlon, men of the age group 25–29 years and 
women of the age group 30–34 years finished most often in the top three in our study. Therefore, our hypothesis 
that the APP is higher in longer race distances could not be confirmed. This is in contrast to a study by Kne-
chtle et al.2, who analyzed the different APPs of world-class triathletes in different race distances. The authors 
reported that men achieved the best performance at 27.1 ± 4.9 years in the Olympic distance, 28.0 ± 3.8 years in 
the Half-Ironman distance and 35.1 ± 3.6 years in the Ironman distance, while women were best at 26.6 ± 4.4, 
31.6 ± 3.4 and 34.4 ± 4.4 years respectively. However, besides the differences regarding the modes of locomotion, 
the methodological approach was different and we were only able to determine the age group of the finishers 
and not their exact age.
Limitations, strengths, and implications for future research. 
A limitation of this study is the use 
of secondary data. We were not able to consider important factors related to endurance performance in ath-
letes of different competitive levels, such as anthropometric and physiological variables, training status, previous 
experience, drafting rules, technical equipment, track specifications and weather conditions. Due to the use 
of secondary data, we cannot exclude that some distances have been rounded. Moreover, data was missing in 
certain years. Other methodological designs, such as longitudinal studies, could offer more information about 
the effect of aging on duathlon performance. Nevertheless, this is the first study that investigated worldwide 
participation and performance trends in duathlon with results from finishers who participated in duathlon races 
worldwide across three different distances over several decades. Future studies should collect data about the 
above-mentioned variables and analyze participation and performance trends in further subgroups (e.g., elite 
athletes) as well as pacing behaviours in short-distance duathlon and the association between place of competi-
tion, participation and performance trends.
Conclusion
More men than women competed in all distances and especially in longer distances. Men were generally faster 
across all age groups and no trend regarding the sex gap was observed at any distance throughout the years. The 
APP did not increase with an increase in the race distance. Men and women of the age group 30–34 finished 
most often in the top three in short- and medium-distance races, whereas in long-distance races, men of the age 
group 25–29 and women of the age group 30–34 finished most often in the top three.
10
Vol:.(1234567890)
Scientific Reports |         (2023) 13:9303  | 
https://doi.org/10.1038/s41598-023-36050-2
www.nature.com/scientificreports/
Data availability
For this study, we have included official results and split times from the official website of WT https:// triat hlon. 
org. The datasets used and/or analyzed during the current study are available from the corresponding author 
on reasonable request.
Received: 10 March 2023; Accepted: 28 May 2023
References
 1. Lepers, R., Knechtle, B. & Stapley, P. J. Trends in triathlon performance: Effects of sex and age. Sports Med. 43(9), 851–863. https:// 
doi. org/ 10. 1007/ s40279- 013- 0067-4 (2013).
 2. Knechtle, R., Rüst, C. A., Rosemann, T. & Knechtle, B. The best triathletes are older in longer race distances: A comparison between 
Olympic, Half-Ironman and Ironman distance triathlon. Springerplus 3, 538 (2014) (PMID:25279329).
 3. Hanley, B. Pacing, packing and sex-based differences in Olympic and IAAF World Championship marathons. J. Sports Sci. 34(17), 
1675–1681 (2016) (PMID:26736042).
 4. Nikolaidis, P. T., Onywera, V. O. & Knechtle, B. Running performance, nationality, sex, and age in the 10-km, Half-Marathon, 
Marathon, and the 100-km Ultramarathon IAAF 1999–2015. J. Strength Cond. Res. 31(8), 2189–2207 (2017) (PMID:28731980).
 5. Senefeld, J., Smith, C. & Hunter, S. K. Sex differences in participation, performance, and age of ultramarathon runners. Int. J. Sports 
Physiol. Perform. 11(7), 635–642 (2016) (PMID:26561864).
 6. Gloor, R. U. et al. Sex-related trends in participation and performance in the “Swiss Bike Masters” from 1994–2012. Percept. Mot. 
Skills 116(2), 640–654 (2013) (PMID:24032336).
 7. Baumgartner, S., Sousa, C. V., Nikolaidis, P. T. & Knechtle, B. Can the performance gap between women and men be reduced in 
ultra-cycling?. Int. J. Environ. Res. Public Health 17(7), 2521 (2020) (PMID:32272640).
 8. Nikolaidis, P. T., Villiger, E. & Knechtle, B. Participation and performance trends in the ITU Duathlon World Championship from 
2003 to 2017. J. Strength Cond. Res. 35(4), 1127–1133 (2021) (PMID:30363036).
 9. Romero-Ramos, O., Fernández-Rodríguez, E., Mayorga-Vega, D., Merino-Marbán, R. & Podstawski, R. Sex and age-related changes 
in performance in the Duathlon World Championships. Rev. Bras. Med. Esporte 26(3), 234–238. https:// doi. org/ 10. 1590/ 1517- 
86922 02026 03190 540 (2020).
 10. Rüst, C. A. et al. Gender difference and age-related changes in performance at the long-distance duathlon. J. Strength Cond. Res. 
27(2), 293–301. https:// doi. org/ 10. 1519/ jsc. 0b013 e3182 5420d0 (2013).
 11. World Triathlon. World Triathlon competition rules 2020 2019 URL: https:// www. triat hlon. org/ uploa ds/ docs/ World_ Triat hlon_ 
Sport_ Compe tition_ Rules_ 2020_ 20181 1253. pdf [accessed 2021–11–07].
 12. Nikolaidis, P. T. et al. The age of peak performance in women and men duathletes: The paradigm of short and long versions in 
“Powerman Zofingen”. Open Access J. Sports Med. 9, 125–130 (2018) (PMID:30140162).
 13. Lepers, R. Sex difference in triathlon performance. Front. Physiol. 10, 973 (2019) (PMID:31396109).
 14. Smith, F. W. & Smith, P. A. Musculoskeletal differences between males and females. Sports Med. Arthrosc. Rev. 10(1), 98–100. 
https:// doi. org/ 10. 1097/ 00132 585- 20021 0010- 00014 (2002).
 15. Tiller, N. B. et al. Do sex differences in physiology confer a female advantage in ultra-endurance sport?. Sports Med. 51(5), 895–915 
(2021) (PMID:33502701).
 16. Waldvogel, K. J., Nikolaidis, P. T., Di Gangi, S., Rosemann, T. & Knechtle, B. Women reduce the performance difference to men 
with increasing age in ultra-marathon running. Int. J. Environ. Res. Public Health 16(13), 2377 (2019) (PMID:31277399).
 17. Nikolaidis, P. T., Cuk, I., Clemente-Suárez, V. J., Villiger, E. & Knechtle, B. Number of finishers and performance of age group 
women and men in long-distance running: Comparison among 10 km, half-marathon and marathon races in Oslo. Res. Sports 
Med. 29(1), 56–66 (2021) (PMID:32046506).
 18. Sousa-Victor, P., García-Prat, L., Serrano, A. L., Perdiguero, E. & Muñoz-Cánoves, P. Muscle stem cell aging: Regulation and 
rejuvenation. Trends Endocrinol. Metab. 26(6), 287–296 (2015) (PMID:25869211).
 19. Lepers, R., Stapley, P. J. & Cattagni, T. Variation of age-related changes in endurance performance between modes of locomotion 
in men: An analysis of master world records. Int. J. Sports Physiol. Perform. 13(3), 394–397 (2018) (PMID:28714746).
 20. Allen, S. V. & Hopkins, W. G. Age of peak competitive performance of elite athletes: A systematic review. Sports Med. 45(10), 
1431–1441 (2015) (PMID:26088954).
 21. Bentley, D. J., Millet, G. P., Vleck, V. E. & McNaughton, L. R. Specific aspects of contemporary triathlon: Implications for physi-
ological analysis and performance. Sports Med. 32(6), 345–359 (2002) (PMID:11980499).
 22. Millet, G. P., Vleck, V. E. & Bentley, D. J. Physiological differences between cycling and running: Lessons from triathletes. Sports 
Med. 39(3), 179–206 (2009) (PMID:19290675).
 23. Nikolaidis, P. T., Villiger, E., Victor Sousa, C., Rosemann, T. & Knechtle, B. The effect of aging on pacing strategies in short and 
long distance duathlon. Exp. Aging Res. 45(3), 223–233 (2019) (PMID:31021693).
 24. Rüst, C. A., Knechtle, B., Knechtle, P., Rosemann, T. & Lepers, R. Age of peak performance in elite male and female Ironman 
triathletes competing in Ironman Switzerland, a qualifier for the Ironman world championship, Ironman Hawaii, from 1995 to 
2011. Open Access J. Sports Med. 3, 175–182 (2012) (PMID:24198600).
 25. Etter, F. et al. Age and gender interactions in short distance triathlon performance. J. Sports Sci. 31(9), 996–1006. https:// doi. org/ 
10. 1080/ 02640 414. 2012. 760747 (2013).
 26. Knechtle, B., Rüst, C. A., Rosemann, T. & Lepers, R. Age and gender differences in half-Ironman triathlon performances: The 
Ironman 70.3 Switzerland from 2007 to 2010. Open Access J. Sports Med. 3, 59–66 (2012) (PMID:24198588).
 27. World Triathlon. Results—World Triathlon 2023 URL: https:// triat hlon. org/ resul ts [accessed 2023-02-02].
 28. Internet Archive. Wayback Machine 2023 URL: https:// web. archi ve. org/ [accessed 2023-02-02].
 29. Lamont, M., Kennelly, M. & Wilson, E. Competing priorities as constraints in event travel careers. Tour. Manag. 33(5), 1068–1079. 
https:// doi. org/ 10. 1016/j. tourm an. 2011. 12. 005 (2012).
 30. Scheer, V. Participation trends of ultra endurance events. Sports Med. Arthrosc. Rev. 27(1), 3–7 (2019) (PMID:30601393).
 31. Thuany, M. et al. Trends in participation, sex differences and age of peak performance in time-limited ultramarathon events: A 
secular analysis. Medicina (Kaunas) 58(3), 366 (2022) (PMID:35334541).
 32. Shoak, M. A. et al. Participation and performance trends in ultracycling. Open Access J. Sports Med. 4, 41–51 (2013) 
(PMID:24379708).
 33. Deutscher Olympischer Sportbund. Bestandserhebung 2022 URL: https:// cdn. dosb. de/ user_ upload/ www. dosb. de/ uber_ uns/ Besta 
ndser hebung/ Besta ndser hebung_ 2016. pdf [accessed 2023-14-05].
 34. Deutscher Olympischer Sportbund. Bestandserhebung 2001 URL: https:// cdn. dosb. de/ user_ upload/ www. dosb. de/ uber_ uns/ Besta 
ndser hebung/ Besta ndser hebung_ 2001. pdf [accessed 2023-14-05]
 35. Knechtle, B. et al. Training and racing behavior of recreational runners by race distance-results from the NURMI study (step 1). 
Front. Physiol. 12, 620404 (2021) (PMID:33613312).
11
Vol.:(0123456789)
Scientific Reports |         (2023) 13:9303  | 
https://doi.org/10.1038/s41598-023-36050-2
www.nature.com/scientificreports/
 36. Hallam, L. C. & Amorim, F. T. Expanding the gap: An updated look into sex differences in running performance. Front. Physiol. 
12, 804149. https:// doi. org/ 10. 3389/ fphys. 2021. 804149 (2022).
 37. Bassett, D. R. & Howley, E. T. Limiting factors for maximum oxygen uptake and determinants of endurance performance. Med. 
Sci. Sports Exerc. 32(1), 70–84 (2000) (PMID:10647532).
 38. Knechtle, B. et al. Do women reduce the gap to men in ultra-marathon running?. Springerplus 5(1), 672 (2016) (PMID:27350909).
 39. Gallmann, D., Knechtle, B., Rüst, C. A., Rosemann, T. & Lepers, R. Elite triathletes in ‘Ironman Hawaii’ get older but faster. Age 
(Dordr) 36(1), 407–416 (2013) (PMID:23591938).
 40. Reusser, M. et al. Increased participation and decreased performance in recreational master athletes in “Berlin Marathon” 1974–
2019. Front. Physiol. 12, 631237 (2021) (PMID:34262467).
 41. Maffetone, P. B., Malcata, R., Rivera, I. & Laursen, P. B. The Boston marathon versus the world marathon majors. PLoS ONE 12(9), 
e0184024 (2017) (PMID:28863152).
 42. Knechtle, B., Di Gangi, S., Rüst, C. A. & Nikolaidis, P. T. Performance differences between the sexes in the Boston marathon from 
1972 to 2017. J. Strength Cond. Res. 34(2), 566–576 (2020) (PMID:30664107).
 43. Vitti, A., Nikolaidis, P. T., Villiger, E., Onywera, V. & Knechtle, B. The, “New York City Marathon”: Participation and performance 
trends of 1.2M runners during half-century. Res. Sports Med. 28(1), 121–137 (2020) (PMID:30889965).
 44. Lepers, R. & Stapley, P. J. Age-related changes in conventional road versus off-road triathlon performance. Eur. J. Appl. Physiol. 
111(8), 1687–1694. https:// doi. org/ 10. 1007/ s00421- 010- 1805-z (2011).
 45. Bernard, T., Sultana, F., Lepers, R., Hausswirth, C. & Brisswalter, J. Age-related decline in Olympic triathlon performance: Effect 
of locomotion mode. Exp. Aging Res. 36(1), 64–78. https:// doi. org/ 10. 1080/ 03610 73090 34186 20 (2009).
 46. Bijker, K. E., de Groot, G. & Hollander, A. P. Differences in leg muscle activity during running and cycling in humans. Eur. J. Appl. 
Physiol. 87(6), 556–561 (2002) (PMID:12355196).
 47. Heiden, T. & Burnett, A. The effect of cycling on muscle activation in the running leg of an Olympic distance triathlon. Sports 
Biomech. 2(1), 35–49 (2003) (PMID:14658244).
 48. Swinnen, W., Kipp, S. & Kram, R. Comparison of running and cycling economy in runners, cyclists, and triathletes. Eur. J. Appl. 
Physiol. 118(7), 1331–1338 (2018) (PMID:29663075).
 49. Knechtle, B., Wirth, A. & Rosemann, T. Predictors of race time in male Ironman triathletes: Physical characteristics, training, or 
prerace experience?. Percept. Mot. Skills 111(2), 437–446 (2010) (PMID:21162445).
 50. Nikolaidis, P. T., Villiger, E., Vancini, R. L., Rosemann, T. & Knechtle, B. The effect of sex and performance level on pacing in 
duathlon. Sports (Basel) 6(4), 152 (2018) (PMID:30477088).
 51. Deaner, R. O., Addona, V., Carter, R. E., Joyner, M. J. & Hunter, S. K. Fast men slow more than fast women in a 10 kilometer road 
race. PeerJ 4, e2235 (2016) (PMID:27547544).
 52. Knechtle, B. & Nikolaidis, P. T. Sex differences in pacing during “Ultraman Hawaii”. PeerJ 4, e2509 (2016) (PMID:27703854).
 53. Deaner, R. O. & Lowen, A. Males and females pace differently in high school cross-country races. J. Strength Cond. Res. 30(11), 
2991–2997 (2016) (PMID:26950352).
 54. Renfree, A., do Carmo, E. C. & Martin, L. The influence of performance level, age and gender on pacing strategy during a 100-km 
ultramarathon. Eur. J. Sport Sci. 16(4), 409–415 (2016) (PMID:26034882).
 55. Nikolaidis, P. T. et al. The combined effect of aging and performance level on pacing in duathlon: The “ITU Powerman Long 
Distance Duathlon World Championships”. Front. Psychol. 10, 296 (2019) (PMID:30833921).
Author contributions
J.T. obtained the data and drafted the manuscript, C.V.S. performed the statistical analysis and prepared methods 
and results. M.S.A., M.T., I.C., P.T.N., K.W. and B.K. helped in drafting the final version. All authors read and 
approved the final manuscript.
Competing interests 
The authors declare no competing interests.
Additional information
Correspondence and requests for materials should be addressed to B.K.
Reprints and permissions information is available at www.nature.com/reprints.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and 
institutional affiliations.
Open Access  This article is licensed under a Creative Commons Attribution 4.0 International 
License, which permits use, sharing, adaptation, distribution and reproduction in any medium or 
format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the 
Creative Commons licence, and indicate if changes were made. The images or other third party material in this 
article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the 
material. If material is not included in the article’s Creative Commons licence and your intended use is not 
permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from 
the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
© The Author(s) 2023

Participation and performance trends in short-, medium, and long-distance duathlon.
Turnwald, Jonas,Sousa, Caio Victor,Andrade, Marilia Santos,Thuany, Mabliny,Cuk, Ivan,Nikolaidis, Pantelis Theodoros,Weiss, Katja,Knechtle, Beat