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Original Research

The Age-Related Performance Decline in Ironman Triathlon Starts Earlier in Swimming Than in Cycling and Running

Käch, Ilja W.1; Rüst, Christoph A.1; Nikolaidis, Pantelis T.2; Rosemann, Thomas1; Knechtle, Beat1,3

Author Information
Journal of Strength and Conditioning Research: February 2018 - Volume 32 - Issue 2 - p 379-395
doi: 10.1519/JSC.0000000000001796
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Abstract

Introduction

Ironman triathlon is considered as one of the most challenging ultraendurance events in the world (31). The classical Ironman triathlon consists of 3 disciplines—swimming, cycling, and running (performed in this order)—and is held over the distance of 3.8 km swimming, 180 km cycling, and 42.2 km running (4). Triathlon presents an intriguing model to analyze the age-related trends in endurance performance because the trends can be analyzed in the same subject for overall performance and for the 3 disciplines separately (5,27,29,33).

For athletes and coaches, the age of peak Ironman performance is important in planning a career (27). The age of peak Ironman performance has been reported at ∼32–34 years for both women and men (27,47,55). However, differences seem to exist in the age of peak Ironman performance between qualifiers for “Ironman Hawaii” and “Ironman Hawaii” itself. Over the last 3 decades, the age of the annual top 10 finishers in “Ironman Hawaii” increased in male and female athletes (10). In contrast, in “Ironman Switzerland,” a qualifier race for “Ironman Hawaii,” the age of peak Ironman performance increased for the annual top 10 women between 1995 and 2011, but not for men (45). Indeed, a study showed a lower proportion of finishes and slower race times for certain age groups competing in “Ironman Hawaii” compared with its qualifier races, as well as a higher percentage of female and lower percentage of male finishers (56). Therefore, the different participation rate of certain age-group athletes in “Ironman Hawaii” compared with its qualifier races might lead to a selection bias.

Over the last decades, the participation of age-group athletes increased both in “Ironman Hawaii” (32) and in qualifier races such as “Ironman Switzerland” (54). In “Ironman Switzerland,” the number of overall male finishers increased in the past years, whereas the relative participation of master athletes considerably increased (54). Also in “Ironman Hawaii,” the number of overall male and female finishers increased in the past 30 years, whereas the relative participation of master athletes increased (32). In addition to the increase in participation, an improvement in performance of elite athletes has been reported (10,45). Similar to elite athletes, master athletes improved their Ironman triathlon performance over the last decades, both in “Ironman Hawaii” (32) and “Ironman Switzerland” (54). However, analyzing only the top 10 athletes competing in “Ironman Hawaii” may lead to a severe selection bias because most Ironman athletes are recreational age-group athletes and less than 1 percent of the overall number of those participating in any Ironman triathlon is considered.

Up to now, the performance and participation trends in male and female Ironman triathletes have been analyzed only for single races such as an Ironman qualifier (e.g., “Ironman Switzerland”) (45,54) and “Ironman Hawaii” (32). The trend of an increase in participation and an improvement in performance of age-group athletes has been reported only for single Ironman races; thus, the assumption that it reflects a worldwide trend needs verification. Considering other ultraendurance performances, a recent study reported that ultramarathoners competing in time-limited races of different durations became slower while getting older in the past 40 years (23), which is contradictory to the findings for Ironman athletes competing in “Ironman Hawaii,” where the annual 10 fastest became faster and older in the past 30 years (10). According to Knechtle et al. (23), the most probable explanation for the discrepancy between these 2 findings is the different sampling methods. Although Gallmann et al. (10) analyzed the annual 10 fastest men and women in “Ironman Hawaii,” Knechtle et al. (23) included all annual finishers in their analysis of ultramarathoners of different race durations. An analysis including all recorded finishers of all races instead of a fixed number of athletes, for example the top 10 per age group during a certain period (48), might eliminate a potential selection bias.

Therefore, the aim of this study was to investigate participation and performance trends of pro and all age-group athletes ranked in all Ironman triathlon races held worldwide between 2002 and 2015 to analyze the worldwide trend. We hypothesized that the participation of age-group athletes would increase while their performance would improve. In comparison to previous studies, we investigated all finishers in all Ironman races held worldwide for the studied period, therefore minimizing the selection bias caused by selecting only single races and considering only a fixed number of finishers instead of all finishers. Furthermore, we analyzed the age-related performance decline for swimming, cycling, running, and overall race time.

Methods

Experimental Approach to the Problem

To test our hypotheses, all women and men who finished an Ironman triathlon between 2002 and 2015 were considered. All data were obtained from the official website of Ironman triathlon races (http://eu.ironman.com/events/triathlon-races).

Subjects

Split and overall race times of successful female and male pro- and age-group finishers (age range: 18–79 years old) of all Ironman races held worldwide and documented by the official Ironman triathlon website between 2002 and 2015 were collected because full data were only available starting in the year 2002. Before 2002, athletes were not ranked in age groups. Because of missing data or missing age-group assignment, the data of 12 races could not be gathered. All procedures used in the study were approved by the Institutional Review Board of Kanton St. Gallen, Switzerland with a waiver of the requirement for informed consent of the participants given the fact that the study involved the analysis of publicly available data.

Procedures

Split and overall race times of a total of 343,079 male and 85,923 female finishers competing in 253 Ironman races were collected (Table 1). From this set of data, a total of 14,013 male (4.7%) and 4,108 female (5.5%) athletes had to be excluded either because of shortened course lengths in 5 races or because of missing or incorrect split times. Ultimately, a total of 329,066 (80%) male and 81,815 (20%) female athletes were considered for final data analysis. To analyze performance and participation trends, male and female athletes were categorized into pro and age groups of 5-year intervals (i.e., from 18–24 to 75–79 years). Table 2 shows the number of finishers per calendar year and per age group.

Table 1.
Table 1.:
Included races, sorted by continent.
Table 2.
Table 2.:
Participation across calendar years for all age groups.

Statistical Analyses

The change in participation across years was investigated using single linear regression analyses. To investigate changes in performance of finishers, a mixed-effects regression model with finisher as random variable to consider finishers who completed several races was used. We included sex and calendar year as fixed variables. Models were calculated for each age group, and the final model was selected by means of Akaike information criterion. Sex difference was calculated using the equation ([time in men] – [time in women]/[time in men] × 100). To facilitate reading, all sex differences were transformed to absolute values before analyzing and afterward investigated for changes by linear regression models. The change in sex difference across years was investigated using single linear regression analyses. Performance in split and overall race times for all athletes ranked in all age groups from 2002 to 2015 was compared using 1-way analysis of variance (ANOVA) with subsequent Tukey's multiple comparison tests with a single pooled variance. A 2-way ANOVA examined the sex × age group interaction and the main effects of sex and age group on race time of each discipline and overall performance. Within each sex, a 1-way ANOVA examined differences among age groups, too. Statistical analyses were performed using IBM SPSS Statistics (Version 22; IBM SPSS, Chicago, IL, USA) and GraphPad Prism (Version 6.01; GraphPad Software, La Jolla, CA, USA). Significance was accepted at p ≤ 0.05 (2-sided for t tests). Data are given as mean ± SD.

Results

Participation Trends

From 2002 to 2015, a total of 81,815 female athletes completed at least in 1 of the 253 included Ironman races (Table 1). The number of finishers increased significantly between 2002 and 2015 in all female age groups from 18–24 to 65–69 (p < 0.0001) years as well as in the age group 70–74 years (r = 0.42, p = 0.013) except age group 75–79 years (r = 0.02, p = 0.60) (Table 2). During the same period, a total of 329,066 male athletes completed at least in 1 of the 253 included Ironman races (Table 1). The number of finishers increased significantly in all age groups from 18–24 to 75–59 years (p < 0.0001) (Table 2).

Performance Trends Across Calendar Years

In swimming (Tables 3 and 4), pro athletes and athletes in age groups from 50–54 to 65–69 years improved their performance (Table 5). Athletes in age groups from 18–24 to 45–49 years impaired their performance. In athletes in age groups between 70–74 and 75–79 years, performance remained unchanged. Men were faster than women in pro athletes and age-group athletes from 18–24 to 70–74 years, but not 75–79 years. In cycling (Tables 3 and 4), pro athletes and athletes in age groups from 35–39 to 55–59 years improved performance; athletes in age groups from 18–24 to 30–34 years impaired performance; and athletes in age groups from 60–64 to 75–79 years showed no changes in performance (Table 6). Men were faster than women in pro athletes and athletes in age groups from 18–24 to 70–74 years, but not 75–79 years. In running (Tables 3 and 4), pro athletes and age-group athletes in age groups from 18–24 to 40–44 years improved performance; athletes in age groups from 45–49 to 70–74 years impaired performance; and in athletes in age group 75–79 years, no changes in performance were detected (Table 7). Men were faster than women in pro athletes and athletes in age groups from 18–24 to 65–69 years, but not between 70–74 and 75–79 years. For overall race time (Tables 3 and 4), pro athletes and athletes in age groups between 30–34 and 35–39 years improved performance. Athletes in age groups 18–24, 25–29, and from 40–44 to 65–69 years impaired performance. In athletes in age groups between 70–74 and 75–79 years, no changes in performance were found (Table 8). Men were faster than women in pro athletes and all age-group athletes.

Table 3.
Table 3.:
Split and overall race times for women by age group, times are expressed as hour:minute.
Table 4.
Table 4.:
Split and overall race times for men by age group, times are expressed as hour:minute.
Table 5.
Table 5.:
Results of the mixed-effects regression analysis for swimming by age group.
Table 6.
Table 6.:
Results of the mixed-effects regression analysis for cycling by age group.
Table 7.
Table 7.:
Results of the mixed-effects regression analysis for running by age group.
Table 8.
Table 8.:
Results of the mixed-effects regression analysis for overall race time by age group.

Performance by Sex and Age Group

A 2-way ANOVA showed a sex × age group interaction on overall performance and the 3 split disciplines (p < 0.001, η2 < 0.001), which was of trivial magnitude. A main effect of sex on overall performance and the 3 split disciplines, where men were faster than women, was observed (p < 0.001, η2 ≤ 0.001), which was also of trivial magnitude. Age groups differed (p < 0.001) for swimming time (η2 = 0.080, medium effect size [ES]), cycling time (η2 = 0.069, medium ES), running time (η2 = 0.068, medium ES), and overall race time (η2 = 0.091, medium ES). Pro group was the fastest in all race times (Figure 1). Among the age groups, the 18–24 years age group was the fastest in swimming, the 30–34 years age group in cycling (but it did not differ from 25 to 29), and the 25–29 years age group in running and in overall performance (but it did not differ from 30 to 34) (Figure 1). Thus, the age-related decline in performance started in the 25–29 years age group in swimming and the 35–39 years age group in cycling, running, and overall race time.

Figure 1.
Figure 1.:
Race time in swimming, cycling, running, and overall race by sex and age group. Women are depicted by ▲ and men by ●.

Within each sex, a 1-way ANOVA showed that fastest was the pro group in all race times (p < 0.001). In women, age groups differed for swimming (p < 0.001, η2 = 0.139, medium ES), cycling (p < 0.001, η2 = 0.126, medium ES), running (p < 0.001, η2 = 0.133, medium ES), and overall race time (p < 0.001, η2 = 0.171, large ES); the fastest was in age group 18–24 group in swimming and 25–29 group in the other performances (Figure 1). Overall, the age-related decline in performance in women started in age group 25–29 years in swimming and in age group 30–34 years in other performances. In men, age groups differed for swimming (p < 0.001, η2 = 0.095), cycling (p < 0.001, η2 = 0.082), running (p < 0.001, η2 = 0.081), and overall race time (p < 0.001, η2 = 0.108), too; the fastest was age group 18–24 years in swimming and age group 30–34 years in the other performances (Figure 1). Thus, the age-related decline in performance in men started in age group 25–29 years in swimming, age group 35–39 years in cycling, running, and overall race time.

Sex Difference Across Calendar Years

Between 2002 and 2015, the sex difference decreased in swimming in age groups 25–29 years (r2 = 0.69, p < 0.0001), 50–54 years (r2 = 0.38, p = 0.019), and 55–59 years (r2 = 0.66, p = 0.0004) but remained unchanged for all other age groups (Table 9). In cycling, the sex difference in performance decreased in age groups 25–29 years (r2 = 0.52, p = 0.0037), 45–49 years (r2 = 0.42, p = 0.011), and 65–69 years (r2 = 0.47, p = 0.0058) but remained unchanged for all other age groups (Table 9). In running, the sex difference decreased in pro athletes (r2 = 0.82, p < 0.0001), increased in athletes in age groups between 40–44 years (r2 = 0.37, p = 0.021) and 45–49 years (r2 = 0.37, p = 0.021), decreased in athletes in age group 65–69 years (r2 = 0.36, p = 0.030), and remained unchanged in all other age groups (Table 9). For overall race time, the sex difference in performance decreased in age groups 25–29 years (r2 = 0.33, p = 0.032) and 65–69 years (r2 = 0.63, p = 0.0012) and remained unchanged in all other age groups (Table 9).

Table 9.
Table 9.:
Sex difference (%) in split and overall race times by age group.

Discussion

In this study, we examined the worldwide participation and performance trends of age-group athletes and the age-related performance decline for split and overall race times. The main findings were that (a) participation increased in pro athletes and all age groups, except for women in age group 75–79 years, (b) performance improved in younger age groups for running and older age groups for swimming and cycling, (c) the age-related decline in performance started at 25–29 years in swimming for women and men and in cycling, running, and overall race time between 30–34 years and 35–39 years for women and men, respectively, and (d) the sex difference remained stable across years with minor exceptions, where women were able to reduce the sex difference.

Increase in Participation in Age Groups Across Calendar Years

A first important finding was that the participation in Ironman triathlon over the studied period increased in pro athletes and all age group athletes, except for women in age group 75–79 years. This finding is in accordance with previous studies in triathletes and runners. In the past few years, numerous studies investigated the participation trends for different ultraendurance events (13,18,32,46,47,54). In ultrarunning, an increased participation has been shown in the “Western States 100-Mile Endurance Run” held in California, USA (15). With regards to “Ironman Hawaii” (32) and “Ironman Switzerland” (54), the participation of age group athletes increased over the last decades, whereas the percentage of master athletes (i.e., athletes older than 35 years) considerably increased. Over the last decades, an increased participation has also been reported in Double (18), Triple (18,46), and Deca Iron ultratriathlon (18).

Different reasons for the increased participation in ultraendurance events, especially in Ironman triathlon, have been discussed. Mainly, the increased popularity of Ironman triathlons attracted more athletes and especially more master athletes in recent years (32,54). The increase in participation in master athletes has previously been described and is most likely due to the increased life expectancy (www.oecdbetterlifeindex.org/topics/health/) and increased training facilities for master athletes (32). Another reason might be that the myth of “Ironman Hawaii” is undiminished and still attracts many ultraendurance athletes each year. In addition, the “Ironman Hawaii” has a substantial advertising appeal, and might therefore also have an impact on the increase in participation in Ironman races in general.

Younger Athletes Improved in Running and Older Athletes in Swimming and Cycling

Another important finding was that performance improved in pro athletes for all disciplines. Furthermore, performance improved in younger age-group athletes for running and older age-group athletes for swimming and cycling. Our results are in accordance with previous studies reporting the improved performance of older age-group athletes in swimming, cycling, and overall race time, as well as the performance improvement in pro athletes.

In the past few years, numerous studies investigated performance trends for different ultraendurance events (10,15,18,22,45,46). In the “100 km Lauf Biel” held in Switzerland (22), performance remained stable across years. In the “Western States 100-Mile Endurance Run” held in California, USA, female runners improved their finishing times across years, whereas the performance of male runners remained stable (15). In Triple Iron ultratriathlons, male finishers improved their performance across years, whereas female finishers became slower over the years (46). In Double and Deca Iron ultratriathlons, performance remained unchanged over the last decades (18). Regarding Ironman triathlon, recent studies showed an improvement of performance over the last decades (10,45).

The first official Ironman race was held in 1978 in Hawaii (www.ironman.com). After an initial increase in participation in “new” sporting events, the age of the participating athletes increases across years leading to an increased participation in older age groups (48). With increasing participation of older athletes, the level of competition rises in older age groups and leads to improvements in athletic performance (2). Athletes who finished an Ironman in its early days (i.e., in the nineties of the last century) at the age of ∼25–35 years would nowadays (i.e., 2016) be at an age of ∼50–60 years. It is very likely that athletes, who have continued their training and competed in Ironman races across years, should be able to preserve their level of performance. The improvement of athletic performance has been progressively greater in older age groups in the past few years (2). Akkari et al. (2) showed that athletic performance in athletes older than 45 years continues to improve compared with younger athletes. They hypothesized that with increasing participation of older athletes, the level of competition would rise, leading to an improvement of performance, whereas the performance of younger athletes would remain stable. Stiefel et al. (54) also showed that master Ironman triathletes have not yet reached their limits. It is also known that master runners suffer more injuries than younger athletes, which limits their performance (36). This might also attribute to the selection process, meaning that successful athletes older than ∼40 years might be less susceptible to injuries through better estimation of the extent of their performance because of their accumulated experience. Also, older athletes might stop competing after an injury, which furthers the selection process in a way that could be best described as “the survival of the fittest.” As shown in several studies, Ironman triathlon performance has stagnated in younger age groups, whereas master athletes were still able to improve their performance (45,54).

Our results also show an improved running performance in younger age-group athletes. Previous studies showed a stagnation in performance trends in younger age-group athletes. This finding could be explained by the different sampling method, which includes all finishers instead of only the top 10 finishers. Younger athletes might have improved their running split times as a result of a higher training volume for running to close the gap to the top athletes. The unchanged performance in the oldest age-group athletes is most likely because of the small sample size due to the low participation in these age groups. Therefore, no significant change in performance could be found.

Performance Decline Starts Earlier in Swimming Than in Cycling and Running

A very astonishing finding was that the age-related decline in swimming performance already started in age group 25–29 for both women and men. The performance decline in cycling, running, and overall race time started in age group 30–34 years in women and 35–39 years in men.

The earlier decline in performance in women than in men might be associated with the different ages of peak endurance between sexes; this age is 17–21 years in males and 12–15 years in females (40,44). In addition, women show a faster rate of performance decline (61). The earlier decline in swimming performances compared with previous studies can be explained by the different sampling method, which takes all finishers into consideration instead of only the top 10 athletes. Therefore, the selection bias of previous studies could be eliminated.

To date, the age-related performance decline in endurance (5,34,35,42,58) and ultraendurance performance (15,22,32) has been well documented. Several studies concluded that endurance performance seems to be maintained until the age of ∼35–40 years, with a moderate decline until the age of 50 years and a growing decrease afterward (43,57,58). After the age of 70 years, the greatest decline in endurance performance occurs (30). The decline in endurance performance seems to be caused primarily by an age-related decrease in maximum oxygen uptake (V̇o2max) and lactate threshold (43,58). This decline can be decelerated by nonbiological factors such as experience (25,26), learning (50), and mental strength and motivation (41). Said decline can also be regulated by changing both the intensity and the volume of training (58).

Previous studies found that Ironman triathlon performance started to decrease at the age of ∼45 years in swimming and running, and at the age of ∼50 years in cycling (33). With advancing age, athletes move toward longer distances, such as Ironman triathlon (27), where performance is more related to endurance capacities and experience than V̇o2max and lactate threshold (27,32). Fitness benefits and social factors seem to be the main drivers for older athletes to perform in Ironman triathlons (51). Therefore, it can be explained that athletes are able to maintain the same level of performance until the age of ∼50 years. Indeed, Leyk et al. (34,35) showed that mean marathon and half-marathon times were virtually identical from the age of ∼20 to ∼49 years, and age-related losses did not occur before the age of 50 years. Also, Hoffmann and Wegelin (15) showed that the performance of athletes competing at the age of ∼40 to ∼49 years in a 161-km ultramarathon was not different from athletes competing in the younger age groups.

The main difference of our study compared with other studies investigating the subject of an age-related decline in endurance performance is the analysis of the selected samples. Instead of only analyzing the top athletes of every age group, we analyzed all finishers of all age groups, therefore eliminating the selection bias. By taking all finishers in an age group into consideration, our results show the average split and overall race times of each age group instead of only the top athletes per age group. Our results showed that the age-related decline in Ironman triathlon performance starts at the age of 25–29 years in swimming and 35–39 years in cycling, running, and overall race time. This finding could be explained by the fact that many recreational athletes without former experience possibly participate in Ironman triathlons leading to a broad spectrum of split and overall race times. The average race times in age groups are considerably higher than the race times of the top 10 athletes in these age groups. In difference to trained athletes, who are able to sustain their level of performance up to the age of ∼50 years (33), the age-related performance decline in recreational athletes seems to start at an earlier age. This difference might be due to the fact that recreational athletes have less experience, less mental strength, and a lower intensity and volume during training, which are all factors decelerating the decline of age-related performance decline seen in professional athletes (25,26,41,58).

Sex Difference in Performance Across Years

A further important finding was that the sex difference decreased across years for split and overall race times in some age groups (i.e., 25–29, 50–54, and 55–59 years in swimming; 25–29, 45–49, and 65–69 years in cycling for pro athletes and 65–69 years in running and 25–29 and 65–69 years for overall time). The decrease in sex difference in the younger age groups is most likely due to the relative improvement of performance of female athletes compared with male athletes during the studied period.

The sex difference in endurance performance is primarily caused by physiological differences in V̇o2max (19) and anthropometric characteristics such as the difference in skeletal muscle mass and body fat (25). It has been shown that female ultrarunners have a lower skeletal muscle mass and a higher percentage of body fat than male ultrarunners, which leads to a disadvantage for women in ultrarunning performance (22,48). It has previously been observed that the age-related decline in endurance performance is greater in female compared with male athletes (6,31,42), and an increased sex difference with advancing age has been documented in elite athletes (31,53).

The decrease in sex difference across years is in accordance with previous studies (2,54). As mentioned above, in the past few years, master athletes such as age group Ironman athletes were able to improve their performance, whereas the performance of younger athletes remained stable. In the past years, female master athletes had a greater progression of athletic performance than their male counterparts (2,54), which leads to the decreased sex difference in these age groups.

The sex difference in performance could also be due to environmental conditions. In “Isklar Norseman Xtreme Triathlon” held as an Ironman-distance triathlon at rather low temperatures, the number of successful women increased across years, women achieved a similar performance compared with men in swimming, cycling, and overall race time, and women improved their performance in swimming, cycling, and overall race time across years (21).

Other reasons for the sex difference in performance could be different changes in body composition in women and men during an Ironman triathlon (38). Although male Ironman triathletes loose skeletal muscle mass during an Ironman triathlon (17) mainly due to a depletion of glycogen stores of the lower limbs (38), no change in body mass could be detected in female Ironman triathletes (24).

Pacing strategy is also different between female and male triathletes (3,20). During an Ironman triathlon, a positive pacing strategy was adopted by both elite women and men in both cycling and running, where women were slower in half of the considered cycling splits but not slower in the running splits (3). Also in a longer triathlon race such as “Ultraman Hawaii,” women paced differently where performance in the fastest women and men decreased in the beginning, but improved in men toward the end of the race (20).

There is also a difference in the contribution of swimming, cycling, and running to overall race time. Between 1989 and 2014, swimming and cycling contributions changed in an undulating fashion in the Ironman triathlon where the contribution was inversely between the 2 segments for both sexes, whereas running contribution decreased for men (9).

Furthermore, there is also a difference between women and men regarding the internet-related activities and interest for Ironman triathlon competitions. When Google Trends was used from 2004, triathlon-related internet activities correlated negatively with the number of annual finishers, whereas an increase in participation of female athletes who were less likely to surf the Internet could be noticed. Younger athletes who were more likely to access the web were underrepresented in Ironman triathlon races, and there was a significant and positive correlation between the cycling split times and the internet query volumes especially for male athletes (37).

Implications for Training and Competing in Ironman Triathlon

The start of the age-related decline in overall race performance is different between women and men. This decline started in women in age group 30–34 years, it started in age group 35–39 years in men. Although the age of peak Ironman triathlon performance in elite athletes is very similar at 30–35 years for both women and men (8,21,47), female triathletes intending to achieve their best Ironman race time should change from the shorter triathlon distances to the Ironman distance ∼5 years earlier than men. In absolute numbers, women should start competing in Ironman triathlon before the age of 30 years and men before the age of 35 years to achieve their best Ironman race time.

Strength, Weakness, Limitations, and Implications for Future Research

The strength of this study is the large data set including all finishers of all Ironman races held worldwide between 2002 and 2015, where a total 329,066 male and 81,815 female finishers in 253 Ironman races were analyzed, with a dropout of only ∼5%. However, some races might not have been documented in the official Ironman website but the largest Ironman races were all listed. A weakness is that we were not able to consider environmental and geographic conditions for these races.

This cross-sectional, retrospective data analysis suffers some limitations because the studied period of 14 years is relatively short compared with studies investigating the same subject (10,32). In addition, individual factors of endurance performance such as physiological (39,49), anthropometric (13,25), and demographic characteristics (14), as well as training regimes (11,25), motivation (12,16,28), and previous race experience (25) could not be taken into consideration. Also, the influences of environmental conditions of the races were unknown (7,8,52,59,60). Future studies would need to include the aspect of environmental conditions because this aspect seems to a have an influence on pacing (1).

Practical Applications

For athletes and coaches, the participation of age group athletes in Ironman triathlon increased for both sexes, women reduced the sex difference in some age groups across years and the age-related decline in performance started at 25–29 years in swimming and 30–34 and 35–39 years in cycling, running, and overall race time, depending on the sex. This observation is of great practical importance for athletes and coaches working with master triathletes, who are encouraged to manage the relatively early age-related decrease in swimming performance. Although swimming, cycling, and running splits are considered as endurance exercise, each of them correlate differently with anthropometry. A decline in muscle mass with aging might affect performance in swimming more than in the other 2 splits. For instance, an athlete with reduced muscle mass is expected to decrease running performance (where they carry less mass through distance) in a lesser degree than in swimming, where body mass is “supported” by water. Thus, athletes older than 30 years should optimize their training (e.g., including strength training for muscle hypertrophy) and nutrition (e.g., adequate protein intake) to maintain their muscle mass targeting swimming performance. This age-related performance decline starts earlier than reported in existing studies and is most likely due to the inclusion of all athletes per age group instead of only the top 10 athletes per age group in earlier studies. The age-related performance decline in recreational compared with professional athletes seems to start at an earlier age. This difference might be due to the fact that recreational athletes have less experience, mental strength, and a lower intensity and volume of training, which are all factors to decelerate the decline of age-related performance decline seen in professional athletes. To be able to preserve the level of competition in recreational athletes until the age of ∼50 years, these factors are of major importance to the athletes and coaches and should be included in the planning of a recreational triathlon athlete's career. These findings show that aging recreational athletes might benefit the most from an increased training intensity and volume in the swimming split discipline to reduce the gap to professional athletes. Therefore, athletes should increase their training regime in the swimming split discipline in relation to the other split disciplines as they age to achieve an optimal performance improvement. Taken all together, women should start competing in Ironman triathlon before the age of 30 years and men before the age of 35 years to achieve their best Ironman race time.

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Keywords:

age group; sex difference; master athlete; worldwide trend

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