Women in the triathlon—the differences between female and male triathletes: a narrative review

Introduction: Triathlon events have gained popularity in recent years. With the increasing participation of women, aspects that influence performance and physiology, as well as differences between women and men, are of interest to athletes and coaches. A review of the existing literature concerning differences between women and men in triathlon is lacking. Therefore, this narrative review aimed to compare female and male triathletes in terms of participation, performance, and the different influences on performance (e.g., physiology, age, pacing, motivation).

Methods: A literature search was conducted in PubMed and Scopus using the search terms “female triathletes”, “women in triathlon”, “triathlon AND gender difference”, and “triathlon AND sex difference”. 662 articles were found using this search strategy, of which 147 were relevant for this review. All distances from sprint to ultra-triathlon (e.g., x-times IRONMAN® distance) were analyzed.

Results: The results showed that the participation of female triathletes, especially female master triathletes increased over time. An improvement in the performance of female and older triathletes was observed at the different distances in the last decades. Sex differences in performance varied across distances and in the three disciplines. Female triathletes showed a significantly lower VO2max and higher lactate thresholds compared to men. They also had a higher body fat percentage and lower body mass. The age for peak performance in the IRONMAN® triathlons is achieved between 25 and 39 years for both women and men. Strong predictors of IRONMAN® race performance in both female and male triathletes include achieving a personal best time in a marathon and a previous best time in triathlon races.

Conclusion: Further studies need to balance the representation of female and male athletes in study cohorts to ensure that findings are relevant to both sexes. Another research gap that should be addressed by future studies is the effect of menstruation and female hormones, the presence of premenstrual syndrome, and the impact of pregnancy and childbirth on the triathlon performance to better understand the differences with men and to account for hormonal fluctuations in training.

1 Introduction

Triathlon is a unique endurance sports discipline in which swimming, cycling and running are combined and performed one after the other (1). The length of the individual disciplines varies depending on the length of the event. The different distances are shown in Table 1 (2, 3). Distances longer than the IRONMAN® distance are typically referred to as ultra-triathlons (3). Each of these distances places specific demands on the athletes’ physical performance, physiological systems, training preparation and recovery strategies.

Table 1

Table 1. The different triathlon lengths in kilometres.

In recent years, endurance events such as marathons and triathlons have become increasingly popular (4–7). In triathlon events, the IRONMAN® triathlon is especially popular, as both the number of races and athletes increase annually (8). Due to the increasing interest in participation in triathlon, numerous studies have been published in recent years addressing various aspects of such races, including participation trends (3, 9–11), performance trends over the years (12–14), predictive variables of performance (15–18), the different characteristics of participants (19–22), age-related aspects (23–27), training (28–30), nutrition (31, 32) and pacing (33–36).

With increasing participation, the performance also changed. In the Ironman World Championship “IRONMAN® Hawaii”, both elite (24) and age group athletes (37) have improved their performance over the last decades. In contrast, Sousa et al. showed a negative trend in the performance of women and men in ultra-triathlon (Double Iron, Triple Iron, Quintuple Iron (19 km swimming, 900 km cycling, and 211 km running) and Deca Iron ultra-triathlon between 1985 and 2018 (38). Several studies have aimed to identify the factors influencing endurance performance in running and triathlon. Success in endurance events is determined by a complex interplay among various factors, including oxidative capacity, the energy cost of locomotion, substrate efficiency, fatigue resistance and musculoskeletal conditioning, race nutrition, gastrointestinal function, age, sex, experience, pain management, decision-making, and motivation and psychological disposition (14, 34, 39–44).

While triathlon was originally heavily dominated by men, the number of female participants has increased significantly in recent decades. Women have made significant progress in both amateur and professional sports and have increasingly established themselves in competitions (45–47). Nevertheless, there are still striking differences in participation rates, performance, and physiological requirements between female and male athletes.

Since the number of female triathletes has increased and sex influences on performance, significant attention has been paid to the sex difference in endurance sports performance, notwithstanding the fact that the number of scientific studies involving the female population remains significantly lower than those involving the male population (48). Triathlon provides an intriguing alternative model to analyze the sex difference in endurance performance because the sex difference can be analyzed both for the same subject as a whole and for the three disciplines separately (3, 13, 25, 49). With the increase in women's participation in amateur and elite endurance sports over the past three decades, the sex performance gap appears to be narrowing (7, 10). This also appears to be associated with improvements in women's performance in recent decades (45–47). Some authors have wondered whether the sex gap in endurance performance will close (50–52). However, more recent studies have shown that the sex gap is no longer narrowing (53, 54).

The gap between sexes in endurance performance is a crucial subject for athletes, coaches and researchers in sports science and sports medicine. A comprehensive understanding of these differences is important for identifying the challenges and opportunities specific to women in triathlon and for developing strategies to promote sex equality and participation in sports. According to a recent consensus of the American College of Sports Medicine, women had a 10%–30% lower performance in sports, where endurance and muscle power played a dominant role (55). The aim of the present narrative review is therefore to provide insights into the differences between female and male triathletes in terms of participation, performance and the various influences on performance (e.g., physiology, age, pacing, motivation). The main focus is on the extent to which the performance of women and men differs at different triathlon lengths and which physiological and psychological factors influence these differences. In addition to the obvious differences in performance, the numerous social, cultural and biological factors that can play a role are also taken into account.

2 Methods

To comprehensively examine the participation and performance trends of women in triathlon as well as the differences between women and men, a narrative review was conducted to identify, select and analyze relevant literature. For this narrative review, a literature search was performed using PubMed and Scopus databases. The search was not limited by publication date; all studies published until November 2024 were considered.

The following terms were used for the literature search: “female triathlete”, “women in triathlon”, “triathlon AND gender difference”, “triathlon AND sex difference”. All studies on women's participation, performance and influencing factors in triathlon (e.g., physiology, age, training, motivation, pacing, experience) were included. Studies that did not specifically address these topics or focused exclusively on male athletes were excluded.

Figure 1 shows the flowchart of the searching strategy used.

Figure 1

Figure 1. Flowchart of the searching strategy.

Following the literature search, the identified studies were categorized based on their research focus according to the main topics of interest of the present narrative review. The findings of the literature search were systematically recorded in tables. These tables contain the key information for each article, including the number of participants, the triathlon distance, the observation of the study and the main findings. This ensured that the overview of the relevant literature was clearly structured. Several studies were included twice or more in each related category of interest because they focused on two or more of the areas of interest.

3 Results and discussion

The focus of the present narrative review was on participation (11 studies) and performance trends (66 studies) of women at different triathlon distances and the factors influencing performance, such as aspects of physiology and anthropometry (47 studies), age (20 studies), training/experience (23 studies), pacing (11 studies), nutrition (4 studies) and motivation (8 studies).

3.1 Participation

A total of 11 studies focused on the participation trends of female triathletes were identified. Participation in the IRONMAN® 70.3 (6), the IRONMAN® (7) and the ultra-triathlon (e.g., Double and Triple Iron) (9, 56) has steadily increased for both sexes, while numbers in Quadruple to Deca Iron events remain stable (3, 57). No major changes in participation were also observed in the Olympic distance triathlon (58). This is also supported by the analysis of the Olympic distance “Zurich Triathlon” between 2000 and 2010, where only the participation of female triathletes aged 40–54 years increased (47). However, no studies could be found with current numbers of participants at the Olympic distance.

Figure 2 illustrates participation trends in female and male triathletes across different time periods and race distances, as reported by various studies. The figure highlights differences in participation rates, showing that despite an increase in female participation over time, the number of male triathletes remains consistently higher.

Figure 2

Figure 2. The participation rate trends across different studies (3, 9, 11, 37, 47, 57, 58, 60, 225, 226).

Table 2 shows the main findings of studies investigating the changes in participation in different triathlon distances over time.

Table 2

Table 2. Overview of the key findings of studies investigating the participation trends in different triathlon distances.

3.1.1 Female participation

The number of female participants has progressively increased since 1980 (37). In the 1981 “IRONMAN® Hawaii” event, there were 20 female finishers (6% of participants), while in 2010 the number rose to 470 (27% of participants) (7, 37). A look at the IRONMAN® Triathlon World Championship between 1983 and 2012 shows that the number of female participants increased more rapidly than the overall number of participants. The number of male participants rose from 720 to 1362 during this period, which corresponds to a relative increase of 189%, while the number of women increased by 455% (from 115 to 524 participants) (59). This trend can also be observed in the marathon running. In a study between 1980 and 2009, Lepers et al. showed that the participation of female marathon runners increased at a higher rate (5). In contrast, a study investigating sex differences in IRONMAN® races worldwide between 2002 and 2022 found that the number of male finishers increased more than the number of female finishers, leading to an increase in the men-to-women ratio over the years (60).

The reasons for the increase in female participation are not clear. Still, social phenomena such as an enhanced focus on personal physical fitness and the positive impact of a healthy lifestyle on longevity could have been potential explanations (61). The increasing social acceptance of “active” women may also have played a role in the increased participation of women (62). Furthermore, greater media visibility of female athletes, targeted initiatives to promote women in endurance sports, and a broader societal shift toward sex equality in sport may have contributed to this trend. Role models in elite sports and the growing availability of women-only races or training groups could also be motivating factors.

In the context of age group triathletes, the rise in the number of female participants has surpassed that of male participants (7). Increased life expectancy and improved training opportunities for master athletes could explain the growing participation in endurance events in recent years (37).

Despite the increase in female participants, the proportion of women in triathlon events remains lower compared to men, with the female rate varying between 25% and 40% of the total field (13, 37, 58). In contemporary times, female triathletes have access to comparable training and competitive opportunities as their male counterparts across most regions globally. Nonetheless, female participation rates persistently lag below those of men, particularly in long-distance triathlon events (63). The female participation rate seems to have declined in the IRONMAN® to Double Deca Iron ultra-triathlon between 1978 and 2013. Rüst et al. found the highest percentage of women at the “IRONMAN® Hawaii” with 22.1% and the lowest at the Deca Iron ultra-triathlon with 6.5% (64). The analysis of the Triple Iron ultra-triathlon between 1988 and 2011 indicated that the number of female participants remained constant at 8%, while overall participation, especially among men, increased over this period (11). Other studies have also found a low participation rate of female triathletes in ultra-triathlons (3, 65). Additionally, due to the different men-to-women ratios in the different race lengths, the ratio also varied across the age groups. A study investigating sex differences in IRONMAN® age group triathletes found that the ratio increased with increasing age (60).

In contrast to other traditional endurance events such as marathons, the participation rate of female athletes in triathlons, particularly at the IRONMAN® distance, persists at a lower level (7). However, the rate is higher than for ultra-endurance events like a 161-km ultra-marathon (7). Knechtle et al. have recently shown that female runners participate more often in shorter race distances and less often in marathons and ultra-marathons, and that the male-to-female ratio increases with increasing race distance (66). The lower rate of women finishers in longer race distances is also consistent with the findings in duathlon (67). This might be explained by motivational reasons, differences in training practices and sociocultural contexts (7, 68, 69).

Data from Hunter and Stevens provided evidence that lower female participation in competitions such as marathon running and less depth among women competitors could exacerbate the sex difference in running speed beyond the sole physiological sex difference (70).

Future research on triathlon participation should place greater focus on current trends among female athletes, as recent data in this area remain limited. In addition, studies should consider the factors influencing female athletes’ engagement in the sport. Understanding the barriers to participation, such as the availability of resources, training support, and the possible impact of social and economic limitations based on sex, should receive careful consideration. Further investigation into the specific motivations driving female participation, and how these may differ from or align with those of male athletes would also provide valuable insights.

3.2 Performance

3.2.1 Changes in performance across years

In addition to the increase in participation in recent decades, there has also been an increase in performance. Both elite and non-elite female and male triathletes have demonstrated performance improvements and sex differences in performance have received considerable attention over the last few decades (7, 37, 63, 64, 71).

Table 3 lists the key findings of studies that have examined changes in performance at different triathlon distances across years. In terms of overall race time, women have shown greater improvements compared to men. For example, during the period between 1995 and 2011 at the “IRONMAN® Switzerland”, the top 10 elite women demonstrated a more pronounced improvement in total time by 12.7%, whereas the top 10 elite men improved their total time by 6.4% (72). It should be noted that women accounted for 10.6% of all finishers in this study.

Table 3

Table 3. Overview of key findings from studies investigating performance trends in different triathlon distances across the years.

3.2.2 Sex difference in overall performance

Sex differences in performance vary across the different disciplines and distances in triathlon. (7) Table 4 shows the key findings of the studies investigating the sex difference in overall performance in different distances from Olympic distance to Double Deca ultra-triathlon. With the increase in female participation in recent years, the gap between sexes in performance seems to be generally narrowing (7, 10). Although there has been an improvement in female performance (73), there still exists a gap between the sexes (74).

Table 4

Table 4. Overview of key findings from studies investigating sex differences in overall performance in different triathlon distances.

The sex gap in overall triathlon performance at the IRONMAN® distance in elite triathletes has been reduced to less than 10% thanks to significant improvements in marathon performance among women (63). Compared to the IRONMAN® distance, a recent study demonstrated that in the Olympic distance, an 8% sex difference in overall performance was observed among amateur athletes (71). Higher differences were evident when examining the top 10 amateur athletes at the World Championship from 2009 to 2011 (12% sex difference in overall race time) (75) and in an analysis of the “Zurich Triathlon” between 2000 and 2010 for the top 5 overall elite triathletes (14.8% in overall race time) (47). It should be noted that the comparison of sex-specific differences is complicated by the varying competition conditions at different events (63) and the diverse levels of performance (71).

When comparing the sex differences in the IRONMAN® performance with those in the Double or Triple Iron ultra-triathlon distances, discrepancies amplify with the length of the ultra-triathlon (3). While the sex difference remained consistent on the Double Iron ultra-triathlon distance over the years (56), there was an observable augmentation in the performance gap between sexes on the Triple Iron ultra-triathlon distance (11). Women became slower in the Triple Iron ultra-triathlon between 1988 and 2011, increasing in the sex difference from 10% in 1992 to 42% in 2011 (11).

Despite some authors questioning whether the gap between women and men can be closed (50–52), newer studies have not confirmed this and have shown that the sex difference in both endurance performances (53, 54) and anaerobic sprints (76) is no longer decreasing. It appears that the sex difference in performance has reached a plateau (53). This is also evidenced by an analysis of the “IRONMAN® Hawaii” between 1981 and 2007 (13).

3.2.3 Sex differences in performance in the different split disciplines

Performance disparities between sexes are evident in the subdisciplines of triathlon (swimming, cycling, running) (63). For instance, at the IRONMAN® 70.3 and IRONMAN® distance, a smaller sex difference was observed in swimming compared to cycling and running across in age group athletes (6, 25, 63), while at the Olympic, the sex difference in cycling was smaller compared to swimming and running for both elite and age group athletes (47). Table 5 summarizes the key findings of studies investigating the sex differences in performance in the split disciplines.

Table 5

Table 5. Overview of key findings from studies investigating sex differences in the split disciplines’ performance in different triathlon distances.

The differences across triathlon distances can be attributed to factor such as pacing strategies (34), competition density (70), and variations in training and experience levels (22, 77). In contrast, a more significant sex difference in cycling compared to running and swimming was found in an investigation of the IRONMAN® races between 2002 and 2022 (60). The contrasting findings on sex differences in triathlon disciplines may be explained by methodological differences, course and environmental factors (78, 79), participation rates and competitive depth (70).

The following studies have separately focused on performance in ultra-distance swimming, ultra-cycling, and ultra-running separately. In terms of swimming performance, Knechtle et al. demonstrated that women can outperform men in ultra-swimming events such as the “Manhattan Island Marathon Swim” between 1983 and 2013. The best women were −12%–14% faster than the men in a 46-km open water ultradistance race with temperatures under 20 degrees (80). Other studies have similarly suggested that women can achieve comparable or even superior performance to men in ultra-swimming (81–83). A review by Knechtle et al. showed that women were ∼0.06 km/h faster than men in open-water long-distance swimming events of the “Triple Crown of Open Water Swimming” (“Catalina Channel Swim”, “English Channel Swim” and “Manhattan Island Marathon Swim”) (84). An explanation for this could be women's greater ability to metabolize fat, the better hydrodynamics, and the more even pacing strategy compared to men, which may be advantageous, especially during prolonged swimming competitions (85).

Several studies have also shown a significant decrease in the sex difference in open-water ultra-distance swimming performance over the last years (81, 83, 86, 87). Additionally, a decrease in sex differences with increasing distance has been noted in shorter events. Tanaka et al. demonstrated a gradual narrowing of the sex gap in swimming with extended distances. While the difference was 19% at 50 m, it decreased to 11% at 1,500 m (88). In contrast, other studies showed no changes in sex difference in short distance (89) and ultra-distance swimming (90) over the years.

In ultra-cycling, Baumgartner et al. showed that men were faster than women for race distances between 100 and 500 miles (169.9 km and 804.7 km) in most of the years from 1996 to 2018. The sex difference was greatest in 100-mile races, while it was able to be reduced in the longer distances (200-, 400-, and 500-mile races) (91).

Similar results have also been observed in ultra-running. According to a recent analysis of ultra-running, sex differences decreased with older age and longer distance, while in 100-mile races the difference was 4.41% and in 50-mile races 9.13% (92).

Between 1988 and 2007, women improved their Hawaii IRONMAN® marathon time by 0.8 min per year, while men's times remained constant (13). It appears that women have narrowed the gap to men the most in the marathon running during the IRONMAN® (7). From 1985 to 2004, women's marathon performance improved nearly threefold greater than the rate observed in men (53). Notably, the sex difference in the marathon run of “IRONMAN® Hawaii” aligns that of the “New York Marathon”, suggesting that swimming and cycling factors do not exacerbate the sex gap in running (13).

Nevertheless, women are unable to match men in ultra-running (93, 94) and ultra-cycling (95, 96). A study investigating performance and sex differences in ultra-triathlons between 1978 and 2013 for the three fastest finishers ever revealed that as the distance increases, sex differences in performance remained stable with increasing distance, except in the swimming split where the sex difference increased (64). In contrast to the studies mentioned earlier, this research demonstrated that the sex difference in swimming amplified with distance (64). One plausible explanation for this phenomenon is the athlete's background. Triathletes must compete in three different sports, and each athlete may have a unique background. Many triathletes might have more experience in running or cycling than in swimming (64). Considering the established correlation between performance in cycling and running with success in ultra-triathlons (97, 98) as well as in other distances (14, 99–101), athletes benefit from their experience in these areas in particular.

3.2.4 Predictive variables for race performance

Research studies vary on which discipline is the optimal predictor of overall triathlon performance. There is disagreement as to whether cycling or running is the superior predictor of performance (2, 102, 103). Notably, in the Olympic distance, it has been determined that the running split emerges as the crucial determinant (14, 99). Conversely, Weiss et al. have recently illustrated that cycling demonstrated the strongest correlation with overall race time on the IRONMAN® 70.3 distance, followed by running (100). In a correlation analysis to verify the association level between the overall race time and the split time in IRONMAN® 70.3 age group triathletes have been showed that there were stronger associations of cycling and running with overall race time than swimming and a more negligible difference in swimming performance between women and men (104). A study examining 43 IRONMAN® triathletes (27 men, 16 women) revealed that among men, cycling exhibited the highest correlation with overall race time, whereas among women, running and cycling displayed approximately equivalent associations (101). However, no study has established swimming as a predictor of performance. The contribution of swimming split times to the overall race time is notably lower compared to cycling and running in ultra-triathlon (77).

Potential predictive variables for a fast race time for the IRONMAN® distance and ultra-triathlon have been analyzed. The most important predictive variables for a fast IRONMAN® race time were age of 30–35 years (women and men), a fast personal best time in the Olympic distance triathlon (women and men), a fast personal best time in marathon running (women and men), both a high volume and a high speed in training where high volume was more important than high speed (women and men), low body fat, low skin-fold thicknesses and low circumference of upper arm (only men), and origin from the United States of America (women and men) (15). Knechtle et al. also found that the origin of the athlete and the age group were the most important predictors in IRONMAN® races (105). For ultra-triathlon, the most important predictive variables were male sex, low body fat, age of 35–40 years, extensive previous experience, a fast time in cycling and running but not swimming, and origins in Central Europe (77).

To summarize this section, future studies need to consider the impact of the male-to-female ratio on participation, as this can influence competitive dynamics and the observed performance gap. Recent studies have shown that women are still underrepresented in research (106, 107). Whereas 10 years ago the proportion of women was 39%, today it has risen to 43.95% (48, 106). Additionally, in sports science, there are more male-only (31%) studies than female-only (6%) studies, leading to a knowledge gap in women-specific physiology and performance (107). This indicates that, despite progress, there remains a substantial need for further effort in research to achieve equitable sex representation. Future research should also account for advancements in technology over recent decades, such as improvements in equipment, racewear, and recovery tools, which may have affected the performance of female and male athletes differently. Furthermore, there is limited information on how environmental factors, such as the surrounding temperature, affect the performance in female and male triathletes. Therefore, future studies need to investigate the influence of the environmental conditions on triathlon performance.

3.3 Physiology, morphology, and anthropometry

There is consensus in the literature that maximal oxygen uptake (VO₂max) and body composition are key variables associated with performance in longer triathlon distance events (108). It is also well-established that male athletes generally demonstrate superior aerobic performance in various endurance sports compared to female athletes (63, 71).

In Table 6, the key findings from studies examining physiological characteristics in female and male triathletes are summarized.

Table 6

Table 6. Overview of key findings from studies investigating aspects of physiology in female and male triathletes.

3.3.1 Maximum oxygen uptake (Vo₂max)

In literature, there is consensus that female athletes tend to exhibit relatively lower VO₂max values (ml/min/kg) during cycling or running compared to their male counterparts (63, 71). The Table 7 summarizes the values of VO₂max from studies that investigated physiological characteristics in triathletes. The mean values in these studies for VO₂max were for women in Sprint distance 45.9 ± 2.5 ml/kg/min and in Olympic distance 50 ± 0.6 ml/kg/min, and for men 51.4 ± 1.0 ml/kg/min and 57.6 ± 3 ml/kg/min, respectively. Compared to a study, where 33 female IRONMAN® triathletes were measured, the values for VO₂max in Sprint and Olympic distances were smaller (109). It should be noted that the sample sizes of these studies were small and the level of the participants and the used measurements were different.

Table 7

Table 7. Values for VO₂max and anaerobic threshold from studies investigating physiological variables.

VO₂max is limited by the cardiovascular capacity to transport oxygen, in the vast majority of people (110), showing a strong relationship with total hemoglobin (111) and maximal stroke volume (112). The discrepancy of VO₂max is frequently ascribed to central factors, such as women's smaller hearts and lower hemoglobin mass, which may limit their capacity to supply oxygen to skeletal muscles (113, 114). Further variables affecting VO₂max include blood cell mass, and hematocrit (110). Typically, women present lower values for these parameters (115–117). When comparing women's hemoglobin levels with those of “age and race-matched” men, women consistently demonstrated 12% lower mean hemoglobin levels irrespective of iron status (111, 118). Women's VO₂max values adjusted to body mass are typically ∼20%-25% lower than men's (119, 120). A recent study by Martins et al. found no significant difference between women and men in VO₂max values when adjusted for lean mass, even at submaximal training intensities (120). This parameter reflects muscular aerobic capacity and is limited by peripheral conditions such as capillary density, mitochondrial content in muscles, and enzyme levels in mitochondria (121). Given the absence of disparities in VO₂max values adjusted for lean mass between the sexes, it can be inferred that skeletal muscles in female and male athletes possess equivalent oxygen extraction capabilities (120). However, some studies have reported differences in VO₂max values adjusted for lean mass (122, 123). The discrepancies in findings from previous studies may be attributed to variations in the level of physical conditioning among female and male participants, small sample sizes, the methodologies used to assess lean mass, and the specialization of event distance (e.g., focusing on training for Olympic or IRONMAN® distances) (19, 120).Given that the performance gaps between the sexes are smaller than the discrepancy in VO₂max (124), other physiological factors significantly influence performance (120).

3.3.2 Anaerobic threshold

In addition to VO₂max as an important parameter for performance, the lactate threshold also correlates with endurance performance (124). In triathletes, female athletes showed higher anaerobic thresholds than male athletes (17, 71). Similar results were found for athletes in the Olympic distance triathlon race, where Fernandes et al. (2023) studied 41 triathletes (22 men and 19 women) showing that the female athletes run at a higher percentage of the ventilatory threshold than the male athletes (27). Values for the anaerobic threshold listed in Table 7 are based on studies examining physiological factors in triathletes. In the different studies, a cardiorespiratory maximal test on a treadmill or a cycling ergometer were performed to identify the ventilatory threshold. The ventilatory threshold was identified by an increase in the ventilatory equivalent for oxygen without a corresponding rise in the ventilatory equivalent for carbon dioxide along with an increase in the partial pressure of exhale oxygen. The mean values in these studies for ventilatory threshold were for women in Sprint distance 69.9 ± 6.3% and at the Olympic distance 78.3 ± 2.8%, and for men 68.8 ± 6.2% and 74.3 ± 0.3% of VO₂max, respectively.

In most of the studies investigating anaerobic threshold values for ventilatory threshold were available. Quittmann et al. (2022) measured the blood lactate in 24 runners and 20 triathletes with a total of 15 female and 29 male participants. They found a higher fractional utilization of VO₂max at lactate threshold according to a fixed lactate concentration of 4 mmol/L (onset of blood lactate accumulation) in women (125).

A key factor in achieving a high lactate threshold is the capacity of mitochondria in muscles to increase their volume in response to training (126). Endurance training has been demonstrated to enhance lactate threshold (127, 128). Importantly, lactate threshold has been shown to correlate significantly with performance in prolonged running events like the marathon (124). Elite athletes can sustain 80%–90% of their VO₂max for prolonged periods with a minor rise in blood lactate (124). Similar findings to triathletes were found in runners. In a study involving 75 long-distance runners (37 men and 38 women), slightly higher lactate thresholds (2.5%) were found in women than in men (129).

3.3.3 Body composition

Moreover, body composition significantly impacts endurance performance. Body fat percentage has emerged as a crucial predictive factor in events such as the IRONMAN® 70.3 (16), IRONMAN® (21, 77), and ultra-triathlon distances (77). Table 8 shows the key findings of the studies investigating the aspects of body composition in female and male triathletes.

Table 8

Table 8. Overview of key findings from studies investigating aspects of body composition in female and male triathletes.

Regarding the association between body fat percentage and race performance, Knechtle et al. found a correlation between body fat percentage and overall race time in IRONMAN® distance events, but only in male participants (22). This observation was consistent with findings from another study (21). However, no significant correlation between anthropometric measures and performance was identified in Triple Iron (97, 98) and Deca Iron ultra-triathlon (130) events. It is worth noting, however, that these studies focused exclusively on male athletes.

Sex differences in body composition are notable among IRONMAN® triathletes, with men exhibiting an average body fat percentage of 14%, compared to 23% in female counterparts, measured with the anthropometric method using the skin-fold calliper (21). In addition to their lower body fat percentage, men typically exhibit greater muscle mass and muscle strength compared to women (21). In 27 male and 16 female IRONMAN® triathletes, it was shown that men had 41 kg of muscle mass, while women showed a muscle mass of 28 kg (21). Furthermore, women generally have lower body mass and height (71), although no discrepancies were observed in trunk fat percentage. However, women showed a higher proportion of gynoid fat mass (71). Table 9 summarizes the values of body mass in kilograms and body fat percentage from studies investigating anthropometric variables in triathletes. The values differ between the length of the race. The mean body weight (63.7 ± 0.2 kg in Sprint vs. 59.2 ± 0.9 kg in Olympic, 60.2 ± 0.8 kg in IRONMAN®) and the body fat percentage (28.1 ± 0.1% in Sprint vs. 22.8 ± 0.6% in Olympic, 23.1 ± 0.5% in the IRONMAN®) in women was greatest in Sprint distance. It must be noted that different methods were used to asses body composition, with DEXA (Dual Energy x-ray Absorptiometry) applied for sprint and Olympic distances, and anthropometric with a skin-fold calliper in the studies investigating the IRONMAN® distance. In each length, the mean values for body weight in women were smaller compared to men and the body fat percentage was higher. However, it is difficult to compare the studies as the level of the participants was different, the sample sizes were small, and varying methods of body composition measurement were used.

Table 9

Table 9. Values for body mass, and body fat percentage from studies investigating anthropometric variables.

The higher body fat percentage in women can confer advantages in the swimming discipline, as it increases buoyancy in water (63), potentially contributing to the smaller sex difference observed in this discipline (131). Body fat might be related to greater substrate efficiency in ultra-endurance sports, where a prolonged exercise would induce the recruitment of fat stores (132). Moreover, body fat distribution is associated with performance (133), with higher android fat percentage reducing buoyancy and swimming speed (134). Additionally, increased body fat percentage provides better insolation in cold water (135), benefiting women's swimming performance, particularly in open-water long-distance swimming in cold temperatures (135, 136). However, during a 1.5 km swimming distance with a water temperature of around 20°C, women's higher body fat percentage does not confer advantages (47).

In addition to the lower muscle mass in female triathletes (21), studies indicated that women experience the loss of muscle mass and strength at an earlier stage than men (53, 137). This observation agreed with those in general population, where women had shorter limb levers, weaker bones and less muscle mass and muscle strength (138).

Research has also shown that women exhibit lower levels of muscular fatigue and faster recovery during endurance training (113). In controlled studies, it has been shown that women generally exhibit greater fatigue resistance than their male counterparts (139, 140). Even during high-intensity interval training (HIIT), Hottenrott et al. suggested that women may demonstrate greater fatigue resistance and enhanced metabolic recovery (141). This lower fatigue may be attributed to the higher proportion of type 1 muscle fibers in women (142).

To conclude this section, future studies investigating VO₂max should adjust measurements to lean body mass, ensuring more accurate comparisons between female and male athletes. These studies would benefit from larger sample sizes and should include athletes of comparable skill levels, using standardized measurement protocols to ensure consistency. Additionally, future studies need to investigate running economy in female triathletes, as it was found to be a determinant of performance (143). Given known sex differences in fatigue resistance, biomechanics, and substrate utilization, research in this area could provide important insights for optimizing performance and training strategies for triathletes. Furthermore, there are no consistent findings on the performance during the menstrual cycle in other endurance sports (144–146). In triathlon-specific research, the effects of the menstrual cycle on triathlon performance are still scarce. Given the unique demands of the sport, further research is needed to understand how different menstrual cycle phases impact performance, recovery, and training in female triathletes. Understanding hormonal influences could help optimize training and race strategies for women in triathletes.

3.4 Aspect of age

The literature search identified a total of 20 studies that focused on age in triathletes. The Table 10 presents the key findings of studies investigating the effect of age on performance in triathlon and the age of peak performance in female and male triathletes. It is widely acknowledged that physiological, morphological, and functional capacities change with age (147). Furthermore, sex differences in endurance performance alter with increasing age (6, 7, 104). Multiple studies provide evidence of age-related effects on performance. Therefore, comprehending the age at which peak performance is achievable holds significant importance for athletes and their coaches regarding career strategizing (148).

Table 10

Table 10. Overview of key findings from studies investigating the effect of age on performance in triathlon and the age of peak performance in female and male triathletes.

3.4.1 Age of peak performance

The age of peak performance in IRONMAN® triathlons is between 25 and 39 years for both women and men (13, 25, 72). Knechtle et al. investigated the specific ages associated with peak performance across various distances (148). They determined that for women, the age of peak performance was 26.6 ± 4.4 years in the Olympic distance, 31.6 ± 3.4 years in the IRONMAN® 70.3 distance, and 34.4 ± 4.4 years in the IRONMAN® distance. The age of the annual top 10 women and men remained unchanged over the period from 2003 to 2013 in the IRONMAN® 70.3 and IRONMAN® distances (148). However, a study of the “IRONMAN® Hawaii” from 1983 to 2012 revealed a trend of increasing age among the annual top 10 performers alongside performance improvement. For men, the age of the annual top 10 increased from 27 ± 2 to 34 ± 3 years, and for women from 26 ± 5 to 35 ± 5 years (24). Overall, it seems that the age of peak triathlon performances increases with increasing race distance from the Olympic distance to IRONMAN® distance.

Regarding distances longer than the IRONMAN® distance, it was observed that the average age of finishers in the Deca Iron ultra-triathlon is notably higher than in the Triple Iron ultra-triathlon. Furthermore, the average age of finishers increased from 1992 to 2010 in both ultra-distances (149). Similarly, in ultra-marathons, it has been demonstrated that the age at which peak performance is attained is higher for longer distances (73, 74, 150, 151).

3.4.2 Age-related performance decline

As illustrated in the preceding section, there has been a notable rise in the number of master athletes. Alongside this surge in participation among master athletes, remarkable improvements in performance have been observed, while the performance of athletes under the age of 40 years has remained relatively static (24, 37, 47, 152). It appears that athletes in younger age brackets have reached a plateau in performance across the IRONMAN® distance (24, 37). However, performance begins to decline with age (37, 137).

Table 11 summarizes the key findings of studies investigating the age-related performance decline in female and male triathletes.

Table 11

Table 11. Overview of key findings from studies investigating the age-related performance decline in female and male triathletes.

Puccinelli et al. have recently shown that female amateur triathletes in the “IRONMAN® Hawaii” present a similar pattern in age-related performance decline as their male counterparts. No differences in overall race time were found in the age groups from 25 to 29 years until 40–44 years. Female and male triathletes broke this plateau trend in the 45–49 age group, and the times for older age groups increased progressively (153).

In triathlon, the age-related performance decline appears to be contingent on the discipline involved (1, 149). Cycling showed a lesser decline compared to swimming and running (154). This discrepancy can be explained by the physiological and mechanical differences between cycling, running, and swimming, such as the transition from a weightless to a weight-bearing activity and the shift from a concentric muscle action in cycling to a stretching and shortening activity with eccentric contractions in running (155). Additionally, differences in training stimuli may explain the lower age-related performance decline in cycling compared to running and swimming (154, 155). Furthermore, it has been observed that the extent of the age-related decline varies depending on the race distance, with a more significant decline in cycling and running performance observed in the IRONMAN® distance compared to the Olympic distance (154).

Potential explanations for the performance improvements observed in master athletes may include increased participation rates, expanded training opportunities tailored to older individuals and a heightened competitive drive (37). Furthermore, analogous performance improvements have been observed among master athletes in other sporting domains, such as swimming (156) and ultra-marathon running (157).

The age-related decline in performance was also demonstrated in other endurance sport, for example in swimming (88, 158) and running (46). This decline typically became noticeable around the ages of 40–50 years, exhibiting a moderate progression until the age of 70, followed by an exponential decrease in endurance performance (46, 88, 158). Various factors contribute to the age-related decline in endurance performance. Age serves as a limiting factor for VO₂max (159, 160). The progressive reduction in VO₂max is the primary mechanism driving performance decline with age (161). Additionally, there is a concurrent loss of muscle mass with aging, which tends to occur faster in women than men (162, 163).

Further reasons for the more significant decline in performance with increasing age may encompass lifestyle adjustments, alterations in training regimens characterized by reduced volume and intensity, and dietary considerations among older athletes (147, 161, 164–167). The natural aging process can either be hastened or decelerated by lifestyle choices. The training status of master athletes emerges as a critical modulator of performance deterioration with advancing age. Changes in physiological functions and running performance with age are closely related to the extent of running training (167).

3.4.3 Changes in sex differences in performance with age

An increase in sex differences with age at the IRONMAN® distance is evident. In Table 12, the key findings of studies investigating the changes in sex differences in performance with age in female and male triathletes are summarized. Lepers & Maffiuletti demonstrated that sex gaps in overall performance significantly widened with increasing age, particularly beyond 55 years of age, while remaining relatively stable before the age of 55 (25). Male athletes aged 60 exhibited a 27% slower pace than triathletes aged 30–40 years, whereas the difference for women was 38% (25). Additionally, Gries et al. showed an increase of the sex difference to 20% in the age group of 65-69 years (168).

Table 12

Table 12. Overview of key findings from studies investigating the changes in sex differences in performance with age in female and male triathletes.

Explanations for this increase may encompass diverse physiological influencing factors (25) and the earlier onset of muscle mass loss in women (162, 163). Lepers et al. also noted the diminished participation of women in older age cohorts, which could contribute to a heightened sex difference (25). Moreover, hormonal differences pre- and post-menopause could further explain the more conspicuous age-related decline in performance among women (169). In addition to the pre- and post-menopause changes, female triathletes may also discover barriers that prevent them from returning to an exercise routine, including muscle weakness, fatigue, depression, and physical changes (170). The postpartum period is influenced by the number of births, the interval between births, the type and duration of labor and delivery as well as the length of time spent breastfeeding (170).

Future studies should explore the impact of pregnancy and childbirth on female triathletes, particularly how prolonged break from training affects recovery and fitness return. Additionally, research is needed on menopause-related hormonal changes and their effects on endurance, muscle function, and recovery, to develop training strategies tailored to aging female athletes.

3.5 Training, experience, pacing, nutrition and motivation

3.5.1 Training and experience

Training (22, 171) and experience in triathlon (15, 77, 172, 173) are central factors influencing performance in triathlon competitions. The main conclusions of the studies examining the elements of experience and training in female and male triathletes are compiled in Table 13.

Table 13

Table 13. Overview of the key findings from studies investigating the aspects of training and experience in female and male triathletes.

3.5.1.1 Training

In a study with 27 male and 16 female nonprofessional IRONMAN® triathletes, the weekly average training volume was 14.8 ± 3.2 h for men and 13.9 ± 3.4 h for women (22). The most training was spent in cycling with 8.0 ± 2.0 h for men and 7.5 ± 2.4 h in women (22). Similar results were found in 166 male and 224 female long-distance triathletes with a weekly training volume of 16 ± 4.9 h in men and 13.6 ± 5.5 h in women (30). In contrast, for Olympic distance triathlon the training volume per week was 8 h and 48 min (mean for 6 male and 5 female recreational-level triathletes) (174).

Weekly training duration impacts IRONMAN® performance differently across sexes. Research indicates that while weekly training volume significantly correlates with the total race time in women, this association is not observed in men (22, 101). Interestingly, neither sex showed a correlation between training speeds in swimming, cycling, and running and the actual speeds in these disciplines during the race (22). In the context of ultra-triathlons, training distance appeared to outweigh training pace in its influence on performance (175–177).

An older study highlighted the importance of training parameters such as distance, time, and experience over anthropometric factors in predicting the performance of female triathletes in short-distance races (178). Despite similar training volumes between the sexes, men tend to swim and cycle faster in training compared to women (101).

Triathletes showed a strong focus on training at low- to moderate- intensities below lactate threshold (179, 180). For example, a world-class female Olympic distance triathlete completed 74% of her swim training, 88% of her cycling training, and 85% of her running training at intensities below her individual lactate threshold (179). Also, at IRONMAN® distance, an improved performance has also been linked to extended duration of training at low to moderate intensities (180). This is also evident in other sports, including swimming (181), cycling (182), and running (183).

A recent narrative review looked at the effect of altitude training (184). The live high-train low method, meaning live at a high altitude (1,250–3,000 m) and train at low altitude or sea-level (0–1,200 m), has been used across a range of endurance-based disciplines (185). Studies have shown significant benefits for performance (186, 187).

3.5.1.2 Experience

Previous participation in triathlon events (16) and achieving personal best times in both IRONMAN® and shorter distances like the Olympic distance (22, 188–190) have been robustly linked to faster IRONMAN® race times (15). Moreover, achieving a personal best time in a marathon has emerged as a strong predictor of performance in IRONMAN® races for both women (189) and men (190). In ultra-distances, the significance of race experience diminishes compared to shorter distances (172), contrary to the findings of Herbst et al. (191). Specifically, Herbst et al. found associations between the number of completed Triple Iron ultra-triathlons and personal best times in a Triple Iron ultra-triathlon with overall race time in a Deca Iron ultra-triathlon (191). However, studies across other endurance disciplines (running, cycling) have shown that the number of races completed does not correlate with overall race time (192–195).

Personal best time in an IRONMAN® triathlon is a robust predictor of race time in both women and men (22). Notably, Knechtle et al. revealed that female winners of the “IRONMAN® Hawaii” exhibit greater prior experience in IRONMAN® races and shorter distances than male winners (15). Given the association between personal best time at the IRONMAN® and race performance across sexes, it can be inferred that race experience holds greater significance than anthropometric parameters and training volume (22).

3.5.2 Pacing

Pacing is a crucial element in endurance performance (196) and has been extensively studied across various triathlon distances (34, 197, 198). In IRONMAN® triathlon, pacing, alongside numerous other factors such as age, previous experience, sex, origin, anthropometry, physiology, and performance in individual disciplines, emerges as a significant predictor for race outcomes (15). Table 14 provides a summary of the main conclusions from the research on the pacing characteristics of female and male triathletes.

Table 14

Table 14. Overview of the key findings from studies investigating the aspects of pacing in female and male triathletes.

To mitigate premature fatigue resulting from overly aggressive cycling or running, athletes must effectively manage their metabolic energy expenditure, typically achieved through strategic adjustments of speed and intensity to optimize performance (199).

Six distinct pacing strategies have been identified: negative pacing (gradually increasing speed), positive pacing (gradual slowing), all-out pacing (maximal speed exertion), even pacing (maintaining a consistent speed), parabolic-shaped pacing (combining positive and negative pacing across race segments), and variable pacing (marked fluctuations in speed) (196). Numerous studies have shown that positive pacing is a viable strategy across various races and disciplines (200–202). Notably, elite female and male triathletes competing in the “IRONMAN® Hawaii” commonly employed positive pacing strategies during both cycling and running segments. In six out of thirteen races analyzed, female athletes notably reduced their cycling speed to a greater extent than their male counterparts, with no significant sex differences observed in speed adjustments during the running segment. (33)

In a study conducted on the “IRONMAN® Hawaii” event in 2022, it was found that male athletes displayed a predominantly negative pacing strategy during the cycling split, while female athletes maintained a more consistent pacing approach (203).

Studies have shown that men often commence the swim and cycling segments of draft-legal Olympic races with a relatively aggressive initial pace compared to women (204, 205). Despite physiological and morphological disparities between the sexes and the weight-bearing aspect of running (7, 206), both female and male triathletes typically demonstrate similar positive pacing patterns during the running segment of draft-legal Olympic-distance triathlons (204, 207).

3.5.3 Nutrition

In endurance events, appropriate fueling is crucial for both safety and peak performance (208). Carbohydrates remain the primary energy source during moderate- to high intensity exercise (209), and recommendations for intake are typically based on event duration (210). However, a narrative review of Lodge et al. showed that the average carbohydrate intake in female athletes falls below current recommendations (211).

Several studies highlight that low energy availability (LEA) is a fundamental factor contributing to the Female Athlete Triad, which involves the interplay between eating disorders, irregular or absent menstrual cycles, and low bone mineral density (212–214). A study investigating low energy availability (LEA) in 30 female triathletes found that 23.3% had a monthly cycle disorder and that 20% of the participants either had, at the time of the study, or had had in the past monthly cycle disorders that could indicate an immediate LEA (215). This issue is often underestimated by both athletes and coaches, highlighting the need for greater awareness of the health-performance balance in endurance sports. Therefore, it is important to audit current guidelines for carbohydrate intake to include sport-specific recommendations and strategies for female athletes to support their health and performance (211). Furthermore, it should be noted, however, that most of the studies were not specific to triathletes, highlighting the need for triathlon-specific data on carbohydrate intake in female triathletes.

Hydration strategies also present sex-related risks, particularly with regard to exercise-associated hyponatremia (EAH) (216). EAH occurs when blood sodium levels drop below 135 mmol/L, often due to excessive fluid intake and inadequate release of vasopressin during prolonged exercise, such as an IRONMAN® race (216). This condition can lead to symptoms ranging from mild nausea and confusion to severe complications like seizures or cerebral oedema, particularly in endurance athletes. Female athletes, slower race times, extreme hot or cold external temperatures, and use of nonsteroidal anti-inflammatory drugs have been associated with a higher EAH risk (216, 217).

A study investigating EAH in female and male IRONMAN® triathletes between 1989 and 2019 confirmed that women are more likely to be hyponatremic during ultra-endurance exercise. It was found that 29.7% of women who received bloodwork testing were hyponatremic, compared to 21.2% of men. Furthermore, the women receiving bloodwork showed significantly lower serum sodium values (137.4 mEq/L vs. 139.7 mEq/L in men) (218).

3.5.4 Motivation and other psychological factors

The preparation for a triathlon race requires a major commitment from the athletes. The load of trainings could influence their behavioral and psychological characteristics (219). Motivation varies between the sexes. Women's motivation often revolves around goals such as fat reduction, fitness improvement and social interaction (220–222), whereas competition and winning are more significant motivators for men. Furthermore, research by Dolan et al. suggests that most participants engage in endurance sports for reasons related to health, enjoyment, social engagement, and personal accomplishments rather than for competitive purposes (31). Interestingly, Lopez-Fernandez et al. found that female and male triathletes competing at the international level exhibit similar motivation profiles. No sex differences in sport motivation were found based on the competition level and age (223).

Table 15 summarizes the key findings of studies investigating the aspects of motivation in female and male triathletes.

Table 15

Table 15. Overview of the key findings from studies investigating the aspects of motivation in female and male triathletes.

A study investigated the psychological profile of amateur triathletes over a training period of six months prior to and after a long-distance triathlon(219). They found that the participants were more harmonious than obsessive with their triathlon's passion. Positive emotions increased until the sixth month and were significantly higher than the negative emotions (219).

Differences in psychological characteristics have been found between modalities and level of professionalism (224). Professional triathletes showed higher scores than amateur triathletes in all psychological dimensions assessed (stress control, influence of performance evaluation, motivation and mental skills). No significant differences between men and women were found. Additionally, the study showed that triathletes scored higher than cyclists in all the variables with a particularly strong effect observed in mental skills and motivation (224).

To conclude this section, future studies need to examine the factors influencing women's motivation in triathlon, including the effect of performance pressure, the presence of role models, and social influences on participation and performance. Studies on the nutrition of female triathletes are scarce. Research should therefore focus on nutrition/fluid intake and energy availability specifically for female athletes. Additionally, studies should investigate training adaptations based on the menstrual cycle to optimize performance, recovery and overall health in female triathletes. Also, the number of female participants in triathlon research should be increased and brought closer to that of men to draw safe conclusions on sex differences.

4 Conclusion

In conclusion, this narrative study highlights the specific problems and opportunities experienced by women in the sport of triathlon. Sex differences in participation and performance varied across distances. In female triathletes, especially in master triathletes, the participation increased and the performance improved. A significantly lower VO₂max and a higher lactate threshold was showed in female triathletes. While the body mass was lower, the body fat percentage was higher in women. The age of peak performance in IRONMAN® triathlons is achieved between 25 and 39 years for both women and men. Personal best time in a marathon and best time in previous triathlons proved to be strong predictors of performance in IRONMAN® races.

A limitation of this narrative review is the absence of a structured assessment of study quality and potential risk of bias, particularly regarding the physiological part. Although not required for narrative reviews, such assessments are considered best practice and could have strengthened the credibility of the findings. Moreover, the lack of formal quality appraisal may limit the ability to weigh the strength of evidence across studies, especially when sample sizes are small or methodologies vary substantially. Additionally, selection bias may have occurred due to the inclusion criteria and the manual selection of studies, potentially influencing the balance of represented findings.

While there is a growing body of research on female athletes in endurance sports, most studies still focus primarily on male athletes, leading to a gap between the sexes in the currently available data. Future research should therefore aim to balance the representation of female and male athletes in the study cohorts, ensuring that the findings are relevant to both sexes. In this way, researchers can develop more comprehensive guidelines that account for the unique physiological and psychological factors influencing women in triathlon, ultimately promoting more effective and inclusive training practices.

The effect of menstruation on training and performance is an important topic that requires further research. In particular, future studies should consider longitudinal designs that track individual athletes across multiple menstrual cycles to better understand fluctuations in performance, recovery, and injury risk. Such research should also account for hormonal contraceptive use, menopausal status, and related hormonal variations.

Additionally, studies need to focus more on the impact of pregnancy and childbirth on female triathletes, as well as the influence of menopause-related hormonal changes on performance, muscle function, recovery, and risk of injury. Furthermore, the inclusion and representation of transgender athletes is another critical area given the evolving policies surrounding gender identity in competitive sports. Future studies should aim to address both the participation and performance outcomes of transgender athletes in order to contribute to a more inclusive understanding of gender in triathlon.

Author contributions

ML: Conceptualization, Writing – original draft. PN: Writing – review & editing. VS: Writing – review & editing. MW: Writing – review & editing. PF: Writing – review & editing. MA: Writing – review & editing. TR: Writing – review & editing. SD: Writing – review & editing. IC: Writing – review & editing. BK: Writing – review & editing.

Funding

The author(s) declare that no financial support was received for the research and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. Bentley DJ, Millet GP, Vleck VE, McNaughton LR. Specific aspects of contemporary triathlon: implications for physiological analysis and performance. Sports Med. (2002) 32:345–59. doi: 10.2165/00007256-200232060-00001

PubMed Abstract | Crossref Full Text | Google Scholar

2. Sousa CV, Aguiar S, Olher RR, Cunha R, Nikolaidis PT, Villiger E, et al. What is the best discipline to predict overall triathlon performance? An analysis of sprint, Olympic, Ironman® 70.3, and Ironman® 140.6. Front Physiol. (2021) 12:654552. doi: 10.3389/fphys.2021.654552

PubMed Abstract | Crossref Full Text | Google Scholar

3. Knechtle B, Knechtle P, Lepers R. Participation and performance trends in ultra-triathlons from 1985 to 2009. Scand J Med Sci Sports. (2011) 21(6):e82–90. doi: 10.1111/j.1600-0838.2010.01160.x

PubMed Abstract | Crossref Full Text | Google Scholar

4. Knechtle B, Nikolaidis PT, Zingg MA, Rosemann T, Rüst CA. Half-marathoners are younger and slower than marathoners. Springerplus. (2016) 5:76. doi: 10.1186/s40064-016-1704-9

PubMed Abstract | Crossref Full Text | Google Scholar

5. Lepers R, Cattagni T. Do older athletes reach limits in their performance during marathon running? Age (Omaha). (2012) 34:773–81. doi: 10.1007/s11357-011-9271-z

PubMed Abstract | Crossref Full Text | Google Scholar

6. Knechtle B, Valero D, Villiger E, Thuany M, Andrade MS, Nikolaidis PT, et al. Comparing the performance gap between males and females in the older age groups in IRONMAN® 70.3: an internet-based cross-sectional study of more than 800,000 race records. Sports Med Open. (2023) 9:88. doi: 10.1186/s40798-023-00636-x

PubMed Abstract | Crossref Full Text | Google Scholar

7. Lepers R, Knechtle B, Stapley PJ. Trends in triathlon performance: effects of sex and age. Sports Med. (2013) 43:851–63. doi: 10.1007/s40279-013-0067-4

PubMed Abstract | Crossref Full Text | Google Scholar

8. Dähler P, Rüst CA, Rosemann T, Lepers R, Knechtle B. Nation related participation and performance trends in ‘ironman Hawaii’ from 1985 to 2012. BMC Sports Sci Med Rehabil. (2014) 6:16. doi: 10.1186/2052-1847-6-16

Crossref Full Text | Google Scholar

9. Meili D, Knechtle B, Rüst CA, Rosemann T, Lepers R. Participation and performance trends in “Ultraman Hawaii” from 1983 to 2012. Extrem Physiol Med. (2013) 2(1):25. doi: 10.1186/2046-7648-2-25

PubMed Abstract | Crossref Full Text | Google Scholar

10. Stiefel M, Rüst CA, Rosemann T, Knechtle B. A comparison of participation and performance in age-group finishers competing in and qualifying for ironman Hawaii. Int J Gen Med. (2013) 6:67–77. doi: 10.2147/IJGM.S40202

PubMed Abstract | Crossref Full Text | Google Scholar

11. Rüst CA, Knechtle B, Knechtle P, Rosemann T, Lepers R. Participation and performance trends in triple iron ultra-triathlon-a cross-sectional and longitudinal data analysis. Asian J Sports Med. (2012) 3(3):145–52. doi: 10.5812/asjsm.34605

Crossref Full Text | Google Scholar

12. Lepers R, Knechtle B, Knechtle P, Rosemann T. Analysis of ultra-triathlon performances. Open Access J Sports Med. (2011) 2:131–6. doi: 10.2147/OAJSM.S22956

PubMed Abstract | Crossref Full Text | Google Scholar

13. Lepers R. Analysis of Hawaii ironman performances in elite triathletes from 1981 to 2007. Med Sci Sports Exerc. (2008) 40:1828–34. doi: 10.1249/MSS.0b013e31817e91a4

PubMed Abstract | Crossref Full Text | Google Scholar

14. Ofoghi B, Zeleznikow J, Macmahon C, Rehula J, Dwyer DB. Performance analysis and prediction in triathlon. J Sports Sci. (2016) 34:607–12. doi: 10.1080/02640414.2015.1065341

PubMed Abstract | Crossref Full Text | Google Scholar

15. Knechtle B, Knechtle R, Stiefel M, Zingg MA, Rosemann T, Rüst CA. Variables that influence ironman triathlon performance & what changed in the last 35 years? Open Access J Sports Med. (2015) 6:277–90. doi: 10.2147/OAJSM.S85310

PubMed Abstract | Crossref Full Text | Google Scholar

16. Gilinsky N, Hawkins KR, Tokar TN, Cooper JA. Predictive variables for half-ironman triathlon performance. J Sci Med Sport. (2014) 17:300–5. doi: 10.1016/j.jsams.2013.04.014

PubMed Abstract | Crossref Full Text | Google Scholar

17. Puccinelli PJ, Lima GHO, Pesquero JB, de Lira CAB, Vancini RL, Nikolaids PT, et al. Previous experience, aerobic capacity and body composition are the best predictors for Olympic distance triathlon performance. Physiol Behav. (2020) 225:113110. doi: 10.1016/j.physbeh.2020.113110

PubMed Abstract | Crossref Full Text | Google Scholar

18. Barbosa JG, de Lira CAB, Vancini RL, dos Anjos VR, Vivan L, Seffrin A, et al. Physiological features of Olympic-distance amateur triathletes, as well as their associations with performance in women and men: a cross–sectional study. Healthcare. (2023) 11:622. doi: 10.3390/healthcare11040622

PubMed Abstract | Crossref Full Text | Google Scholar

19. Millet GP, Vleck VE, Bentley DJ. Physiological requirements in triathlon. J Hum Sport Exerc. (2011) 6:184–204. doi: 10.4100/jhse.2011.62.01

Crossref Full Text | Google Scholar

20. Brunkhorst L, Kielstein H. Comparison of anthropometric characteristics between professional triathletes and cyclists. Biol Sport. (2013) 30:269–73. doi: 10.5604/20831862.1077552

PubMed Abstract | Crossref Full Text | Google Scholar

21. Knechtle B, Wirth A, Baumann B, Knechtle P, Rosemann T, Oliver S. Differential correlations between anthropometry, training volume, and performance in male and female ironman triathletes. J Strength Cond Res. (2010) 24:2785–93. doi: 10.1519/JSC.0b013e3181c643b6

PubMed Abstract | Crossref Full Text | Google Scholar

22. Knechtle B, Wirth A, Baumann B, Knechtle P, Rosemann T. Personal best time, percent body fat, and training are differently associated with race time for male and female ironman triathletes. Res Q Exerc Sport. (2010) 81:62–8. doi: 10.1080/02701367.2010.10599628

PubMed Abstract | Crossref Full Text | Google Scholar

23. Piacentini MF, Vleck V, Lepers R. Effect of age on the sex difference in ironman triathlon performance. Mov Sports Sci - Sci Mot. (2019) (104):21–7. doi: 10.1051/sm/2019030

Crossref Full Text | Google Scholar

24. Gallmann D, Knechtle B, Rüst CA, Rosemann T, Lepers R. Elite triathletes in ‘Ironman Hawaii’ get older but faster. Age (Omaha). (2014) 36:407–16. doi: 10.1007/s11357-013-9534-y

Crossref Full Text | Google Scholar

25. Lepers R, Maffiuletti NA. Age and gender interactions in ultraendurance performance. Med Sci Sports Exerc. (2011) 43(1):134–9. doi: 10.1249/MSS.0b013e3181e57997

PubMed Abstract | Crossref Full Text | Google Scholar

26. dos Anjos VR, Vivan L, Engelke P, de Lira CAB, Vancini RL, Weiss K, et al. Differences in 5-km running pace between female and male triathletes. Int J Sports Med. (2025) 46(2):115–20. doi: 10.1055/a-2443-9921

PubMed Abstract | Crossref Full Text | Google Scholar

27. De Araújo Moury Fernandes GC, Junior JGG B, Seffrin A, Vivan L, de Lira CAB, Vancini RL, et al. Amateur female athletes perform the running split of a triathlon race at higher relative intensity than the male athletes: a cross-sectional study. Healthcare. (2023) 11:418. doi: 10.3390/healthcare11030418

Crossref Full Text | Google Scholar

28. Kienstra CM, Cade WH, Best TM. Training, injury, and lifestyle characteristics of recreational triathletes. Curr Sports Med Rep. (2021) 20:87–91. doi: 10.1249/JSR.0000000000000807

PubMed Abstract | Crossref Full Text | Google Scholar

29. Mallol M, Bentley DJ, Norton L, Norton K, Mejuto G, Yanci J. Comparison of reduced-volume high-intensity interval training and high-volume training on endurance performance in triathletes. Int J Sports Physiol Perform. (2019) 14:239–45. doi: 10.1123/ijspp.2018-0359

PubMed Abstract | Crossref Full Text | Google Scholar

30. Luckin KM, Badenhorst CE, Cripps AJ, Landers GJ, Merrells RJ, Bulsara MK, et al. Strength training in long-distance triathletes: barriers and characteristics. J Strength Cond Res. (2021) 35:495–502. doi: 10.1519/JSC.0000000000002716

PubMed Abstract | Crossref Full Text | Google Scholar

31. Dolan SH, Houston M, Martin SB. Survey results of the training, nutrition, and mental preparation of triathletes: practical implications of findings. J Sports Sci. (2011) 29:1019–28. doi: 10.1080/02640414.2011.574718

PubMed Abstract | Crossref Full Text | Google Scholar

32. Kreutzer A, Graybeal AJ, Moss K, Braun-Trocchio R, Shah M. Caffeine supplementation strategies among endurance athletes. Front Sports Act Living. (2022) 4:821750. doi: 10.3389/fspor.2022.821750

PubMed Abstract | Crossref Full Text | Google Scholar

33. Angehrn N, Rüst CA, Nikolaidis PT, Rosemann T, Knechtle B. Positive pacing in elite ironman triathletes. Chin J Physiol. (2016) 59:305–14. doi: 10.4077/CJP.2016.BAE418

PubMed Abstract | Crossref Full Text | Google Scholar

34. Wu SS, Peiffer JJ, Brisswalter J, Nosaka K, Abbiss CR. Factors influencing pacing in triathlon. Open Access J Sports Med. (2014) 5:223–34. doi: 10.2147/OAJSM.S44392

PubMed Abstract | Crossref Full Text | Google Scholar

35. Stjepanovic M, Knechtle B, Weiss K, Nikolaidis PT, Cuk I, Thuany M, et al. Changes in pacing variation with increasing race duration in ultra-triathlon races. Sci Rep. (2023) 13:3692. doi: 10.1038/s41598-023-30932-1

PubMed Abstract | Crossref Full Text | Google Scholar

36. Knechtle B, Käch I, Rosemann T, Nikolaidis PT. The effect of sex, age and performance level on pacing of ironman triathletes. Res Sports Med. (2019) 27:99–111. doi: 10.1080/15438627.2018.1546703

PubMed Abstract | Crossref Full Text | Google Scholar

37. Lepers R, Rüst CA, Stapley PJ, Knechtle B. Relative improvements in endurance performance with age: evidence from 25 years of Hawaii ironman racing. Age (Omaha). (2013) 35:953–62. doi: 10.1007/s11357-012-9392-z

PubMed Abstract | Crossref Full Text | Google Scholar

38. Sousa CV, Nikolaidis PT, Knechtle B. Ultra-triathlon—pacing, performance trends, the role of nationality, and sex differences in finishers and non-finishers. Scand J Med Sci Sports. (2020) 30:556–63. doi: 10.1111/sms.13598

PubMed Abstract | Crossref Full Text | Google Scholar

39. Millet GY, Hoffman MD, Morin JB. Sacrificing economy to improve running performance—a reality in the ultramarathon? J Appl Physiol. (2012) 113:507–9. doi: 10.1152/japplphysiol.00016.2012

PubMed Abstract | Crossref Full Text | Google Scholar

40. Hoffman MD, Lee J, Zhao H, Tsodikov A. Pain perception after running a 100-mile ultramarathon. Arch Phys Med Rehabil. (2007) 88:1042–8. doi: 10.1016/j.apmr.2007.05.004

PubMed Abstract | Crossref Full Text | Google Scholar

41. Tiller NB, Roberts JD, Beasley L, Chapman S, Pinto JM, Smith L, et al. International society of sports nutrition position stand: nutritional considerations for single-stage ultra-marathon training and racing. J Int Soc Sports Nutr. (2019) 16(1):50. doi: 10.1186/s12970-019-0312-9

PubMed Abstract | Crossref Full Text | Google Scholar

42. Cona G, Cavazzana A, Paoli A, Marcolin G, Grainer A, Bisiacchi PS. It’s a matter of mind! Cognitive functioning predicts the athletic performance in ultra-marathon runners. PLoS One. (2015) 10:e0132943. doi: 10.1371/journal.pone.0132943

PubMed Abstract | Crossref Full Text | Google Scholar

43. Thompson MA. Physiological and biomechanical mechanisms of distance specific human running performance. Integr Comp Biol. (2017) 57:293–300. doi: 10.1093/icb/icx069

PubMed Abstract | Crossref Full Text | Google Scholar

44. VanHeest JL, Mahoney CE. Female athletes: factors impacting successful performance. Curr Sports Med Rep. (2007) 6:190–4. doi: 10.1007/s11932-007-0027-6

PubMed Abstract | Crossref Full Text | Google Scholar

45. Jokl P, Sethi PM, Cooper AJ. Master’s performance in the New York City Marathon 1983–1999. Br J Sports Med. (2004) 38:408–12. doi: 10.1136/bjsm.2002.003566

PubMed Abstract | Crossref Full Text | Google Scholar

46. Leyk D, Erley O, Ridder D, Leurs M, Rüther T, Wunderlich M, et al. Age-related changes in marathon and half-marathon performances. Int J Sports Med. (2007) 28:513–7. doi: 10.1055/s-2006-924658

PubMed Abstract | Crossref Full Text | Google Scholar

47. Etter F, Knechtle B, Bukowski A, Rüst CA, Rosemann T, Lepers R. Age and gender interactions in short distance triathlon performance. J Sports Sci. (2013) 31:996–1006. doi: 10.1080/02640414.2012.760747

PubMed Abstract | Crossref Full Text | Google Scholar

48. Costello JT, Bieuzen F, Bleakley CM. Where are all the female participants in sports and exercise medicine research? Eur J Sport Sci. (2014) 14:847–51. doi: 10.1080/17461391.2014.911354

PubMed Abstract | Crossref Full Text | Google Scholar

49. Lepers R, Stapley PJ. Age-related changes in conventional road versus off-road triathlon performance. Eur J Appl Physiol. (2011) 111:1687–94. doi: 10.1007/s00421-010-1805-z

PubMed Abstract | Crossref Full Text | Google Scholar

50. Bam J, Noakes TD, Juritz J, Dennis SC. Could women outrun men in ultramarathon races? Med Sci Sports Exerc. (1997) 29:244–7. doi: 10.1097/00005768-199702000-00013

PubMed Abstract | Crossref Full Text | Google Scholar

51. Coast JR, Blevins JS, Wilson BA. Do gender differences in running performance disappear with distance? Can J Appl Physiol. (2004) 29:139–45. doi: 10.1139/h04-010

PubMed Abstract | Crossref Full Text | Google Scholar

52. Whipp BJ, Ward S. Will women soon outrun men? Nature. (1992) 355:25–25. doi: 10.1038/355025a0

PubMed Abstract | Crossref Full Text | Google Scholar

53. Cheuvront SN, Carter R, DeRuisseau KC, Moffatt RJ. Running performance differences between men and women. Sports Med. (2005) 35:1017–24. doi: 10.2165/00007256-200535120-00002

PubMed Abstract | Crossref Full Text | Google Scholar

54. Sparling PB, O'Donnell EM, Snow TK. The gender difference in distance running performance has plateaued: an analysis of world rankings from 1980 to 1996. Med Sci Sports Exerc. (1998) 30:1725–9. doi: 10.1097/00005768-199812000-00011

PubMed Abstract | Crossref Full Text | Google Scholar

55. Hunter SK, Angadi S S, Bhargava A, Harper J, Hirschberg AL, Levine B D, et al. The biological basis of sex differences in athletic performance: consensus statement for the American college of sports medicine. Med Sci Sports Exerc. (2023) 55:2328–60. doi: 10.1249/MSS.0000000000003300

PubMed Abstract | Crossref Full Text | Google Scholar

56. Sigg K, Knechtle B, Rüst CA, Knechtle P, Lepers R, Rosemann T. Sex difference in double iron ultra-triathlonperformance. Extrem Physiol Med. (2013) 2:12. doi: 10.1186/2046-7648-2-12

PubMed Abstract | Crossref Full Text | Google Scholar

57. Lenherr R, Knechtle B, Rüst C, Rosemann T, Lepers R. From double iron to double deca iron ultra-triathlon - A retrospective data analysis from 1985 to 2011. Phys Cult Sport Stud Res. (2012) 54:55–67. doi: 10.2478/v10141-012-0013-4

Crossref Full Text | Google Scholar

58. Wonerow M, Rüst CA, Nikolaidis PT, Rosemann T, Knechtle B. Performance trends in age group triathletes in the Olympic distance triathlon at the world championships 2009–2014. Chin J Physiol. (2017) 60:137–50. doi: 10.4077/CJP.2017.BAF448

PubMed Abstract | Crossref Full Text | Google Scholar

59. Rüst CA, Knechtle B, Rosemann T, Lepers R. Sex difference in race performance and age of peak performance in the ironman triathlon world championship from 1983 to 2012. Extrem Physiol Med. (2012) 1:15. doi: 10.1186/2046-7648-1-15

PubMed Abstract | Crossref Full Text | Google Scholar

60. Knechtle B, Valero D, Villiger E, Thuany M, Andrade MS, Cuk I, et al. Sex difference in IRONMAN age group triathletes. PLoS One. (2024) 19:e0311202. doi: 10.1371/journal.pone.0311202

PubMed Abstract | Crossref Full Text | Google Scholar

61. Lee MS, Tanaka K. Significance of health fitness appraisal in an aging society. Appl Human Sci. (1997) 16:123–31. doi: 10.2114/jpa.16.123

PubMed Abstract | Crossref Full Text | Google Scholar

62. Deaner RO. Distance running as an ideal domain for showing a sex difference in competitiveness. Arch Sex Behav. (2013) 42:413–28. doi: 10.1007/s10508-012-9965-z

PubMed Abstract | Crossref Full Text | Google Scholar

63. Lepers R. Sex difference in triathlon performance. Front Physiol. (2019) 10:973. doi: 10.3389/fphys.2019.00973

PubMed Abstract | Crossref Full Text | Google Scholar

64. Rüst CA, Rosemann T, Knechtle B. Performance and sex difference in ultra-triathlon performance from ironman to double deca iron ultra-triathlon between 1978 and 2013. Springerplus. (2014) 3:219. doi: 10.1186/2193-1801-3-219

PubMed Abstract | Crossref Full Text | Google Scholar

65. Rüst CA, Knechtle B, Knechtle P, Lepers R, Rosemann T, Onywera V. European Athletes dominate performances in double iron ultra-triathlons – A retrospective data analysis from 1985 to 2010. Eur J Sport Sci. (2014) 14(Suppl 1):S39–50. doi: 10.1080/17461391.2011.641033

Crossref Full Text | Google Scholar

66. Knechtle B, Witthöft A, Valero D, Thuany M, Nikolaidis PT, Scheer V, et al. Elderly female ultra-marathoners reduced the gap to male ultra-marathoners in Swiss running races. Sci Rep. (2023) 13:12521. doi: 10.1038/s41598-023-39690-6

PubMed Abstract | Crossref Full Text | Google Scholar

67. Turnwald J, Sousa CV, Andrade MS, Thuany M, Cuk I, Nikolaidis PT, et al. Participation and performance trends in short-, medium, and long-distance duathlon. Sci Rep. (2023) 13:9303. doi: 10.1038/s41598-023-36050-2

PubMed Abstract | Crossref Full Text | Google Scholar

68. Knechtle B, Tanous DR, Wirnitzer G, Leitzmann C, Rosemann T, Scheer V, et al. Training and racing behavior of recreational runners by race distance-results from the NURMI study (step 1). Front Physiol. (2021) 12:620404. doi: 10.3389/fphys.2021.620404

PubMed Abstract | Crossref Full Text | Google Scholar

69. Hallam LC, Amorim FT. Expanding the gap: an updated look into sex differences in running performance. Front Physiol. (2022) 12:804149. doi: 10.3389/fphys.2021.804149

PubMed Abstract | Crossref Full Text | Google Scholar

70. Hunter SK, Stevens AA. Sex differences in marathon running with advanced age. Med Sci Sports Exerc. (2013) 45:148–56. doi: 10.1249/MSS.0b013e31826900f6

PubMed Abstract | Crossref Full Text | Google Scholar

71. Puccinelli PJ, de Lira CAB, Vancini RL, Nikolaidis PT, Knechtle B, Rosemann T, et al. The performance, physiology and morphology of female and male Olympic-distance triathletes. Healthcare. (2022) 10:797. doi: 10.3390/healthcare10050797

PubMed Abstract | Crossref Full Text | Google Scholar

72. Rüst CA, 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. (2012) 3:175–82. doi: 10.2147/OAJSM.S37115

PubMed Abstract | Crossref Full Text | Google Scholar

73. Hoffman MD, Wegelin JA. The western states 100-mile endurance run. Med Sci Sports Exerc. (2009) 41:2191–8. doi: 10.1249/MSS.0b013e3181a8d553

PubMed Abstract | Crossref Full Text | Google Scholar

74. Knechtle B, Rüst CA, Rosemann T, Lepers R. Age-related changes in 100-km ultra-marathon running performance. Age (Omaha). (2012) 34:1033–45. doi: 10.1007/s11357-011-9290-9

PubMed Abstract | Crossref Full Text | Google Scholar

75. Stevenson JL, Song H, Cooper JA. Age and sex differences pertaining to modes of locomotion in triathlon. Med Sci Sports Exerc. (2013) 45:976–84. doi: 10.1249/MSS.0b013e31827d17eb

PubMed Abstract | Crossref Full Text | Google Scholar

76. Seiler S, De Koning JJ, Foster C. The fall and rise of the gender difference in elite anaerobic performance 1952–2006. Med Sci Sports Exerc. (2007) 39:534–40. doi: 10.1249/01.mss.0000247005.17342.2b

PubMed Abstract | Crossref Full Text | Google Scholar

77. Knechtle B, Zingg MA, Rosemann T, Stiefel M, Rüst CA. What predicts performance in ultra-triathlon races? - a comparison between ironman distance triathlon and ultra-triathlon. Open Access J Sports Med. (2015) 6:149–59. doi: 10.2147/OAJSM.S79273

PubMed Abstract | Crossref Full Text | Google Scholar

78. Gay A, Zacca R, Abraldes JA, Morales-Ortíz E, López-Contreras G, Fernandes RJ, et al. Swimming with swimsuit and wetsuit at typical vs. Cold-water temperatures (26 vs. 18℃). Int J Sports Med. (2021) 42:1305–12. doi: 10.1055/a-1481-8473

PubMed Abstract | Crossref Full Text | Google Scholar

79. Thuany M, Valero D, Villiger E, Andrade M, Weiss K, Nikolaidis PT, et al. A descriptive analysis of the fastest race courses for triathletes. Balt J Sport Health Sci. (2024) 4:14–23. doi: 10.33607/bjshs.v4i131.1463

Crossref Full Text | Google Scholar

80. Knechtle B, Rosemann T, Lepers R, Rüst CA. Women outperform men in ultradistance swimming: the Manhattan island marathon swim from 1983 to 2013. Int J Sports Physiol Perform. (2014) 9:913–24. doi: 10.1123/ijspp.2013-0375

PubMed Abstract | Crossref Full Text | Google Scholar

81. Rüst CA, Knechtle B, Rosemann T, Lepers R. Women reduced the sex difference in open-water ultra-distance swimming la traversée internationale du lac St-Jean, 1955–2012. Appl Physiol Nutr Metab. (2014) 39:270–3. doi: 10.1139/apnm-2013-0222

Crossref Full Text | Google Scholar

82. Eichenberger E, Knechtle B, Knechtle P, RüSt CA, Rosemann T, Lepers R. Best performances by men and women open-water swimmers during the ‘English channel swim’ from 1900 to 2010. J Sports Sci. (2012) 30:1295–301. doi: 10.1080/02640414.2012.709264

PubMed Abstract | Crossref Full Text | Google Scholar

83. Knechtle B, Rosemann T, Rüst CA. Women cross the ‘catalina channel’ faster than men. Springerplus. (2015) 4:332. doi: 10.1186/s40064-015-1086-4

PubMed Abstract | Crossref Full Text | Google Scholar

84. Knechtle B, Dalamitros AA, Barbosa TM, Sousa CV, Rosemann T, Nikolaidis PT. Sex differences in swimming disciplines—can women outperform men in swimming? Int J Environ Res Public Health. (2020) 17:3651. doi: 10.3390/ijerph17103651

PubMed Abstract | Crossref Full Text | Google Scholar

85. Sandbakk Ø, Solli GS, Holmberg H-C. Sex differences in world-record performance: the influence of sport discipline and competition duration. Int J Sports Physiol Perform. (2018) 13:2–8. doi: 10.1123/ijspp.2017-0196

PubMed Abstract | Crossref Full Text | Google Scholar

86. Salihu L. Sex difference in draft-legal ultra-distance events - A comparison between ultra-swimming and ultra-cycling. Chin J Physiol. (2016) 59(2):87–99. doi: 10.4077/CJP.2016.BAE373

PubMed Abstract | Crossref Full Text | Google Scholar

87. Rüst CA, Lepers R, Rosemann T, Knechtle B. Will women soon outperform men in open-water ultra-distance swimming in the 'Maratona del golfo Capri-napoli'? Springerplus. (2014) 3:86. doi: 10.1186/2193-1801-3-86

PubMed Abstract | Crossref Full Text | Google Scholar

88. Tanaka H, Seals DR. Age and gender interactions in physiological functional capacity: insight from swimming performance. J Appl Physiol. (1997) 82:846–51. doi: 10.1152/jappl.1997.82.3.846

PubMed Abstract | Crossref Full Text | Google Scholar

89. Wild S, Rüst CA, Rosemann T, Knechtle B. Changes in sex difference in swimming speed in finalists at FINA world championships and the Olympic games from 1992 to 2013. BMC Sports Sci Med Rehabil. (2014) 6:25. doi: 10.1186/2052-1847-6-25

PubMed Abstract | Crossref Full Text | Google Scholar

90. Eichenberger E, Knechtle B, Knechtle P, Rüst CA, Rosemann T, Lepers R, et al. Sex difference in open-water ultra-swim performance in the longest freshwater lake swim in Europe. J Strength Cond Res. (2013) 27:1362–9. doi: 10.1519/JSC.0b013e318265a3e9

PubMed Abstract | Crossref Full Text | Google Scholar

91. Baumgartner S, Sousa CV, Nikolaidis PT, Knechtle B. Can the performance gap between women and men be reduced in ultra-cycling? Int J Environ Res Public Health. (2020) 17:2521. doi: 10.3390/ijerph17072521

PubMed Abstract | Crossref Full Text | Google Scholar

92. Waldvogel KJ, Nikolaidis PT, 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. (2019) 16:2377. doi: 10.3390/ijerph16132377

PubMed Abstract | Crossref Full Text | Google Scholar

93. Peter L, Rüst CA, Knechtle B, Rosemann T, Lepers R. Sex differences in 24-hour ultra-marathon performance - A retrospective data analysis from 1977 to 2012. Clinics. (2014) 69:38–46. doi: 10.6061/clinics/2014(01)06

PubMed Abstract | Crossref Full Text | Google Scholar

94. Zingg MA, Karner-Rezek K, Rosemann T, Knechtle B, Lepers R, Rüst CA. Will women outrun men in ultra-marathon road races from 50 km to 1,000 km? Springerplus. (2014) 3:97. doi: 10.1186/2193-1801-3-97

PubMed Abstract | Crossref Full Text | Google Scholar

95. Zingg M, Knechtle B, Rüst CA, Rosemann T, Lepers R. Age and gender difference in non-drafting ultra-endurance cycling performance - the 'Swiss cycling marathon'. Extrem Physiol Med. (2013) 2:18. doi: 10.1186/2046-7648-2-18

PubMed Abstract | Crossref Full Text | Google Scholar

96. Rüst CA, Knechtle B, Rosemann T, Lepers R. Men cross America faster than women—the 'Race across America' from 1982 to 2012. Int J Sports Physiol Perform. (2013) 8:611–7. doi: 10.1123/ijspp.8.6.611

Crossref Full Text | Google Scholar

97. Knechtle B, Duff B, Amtmann G, Kohler G. Cycling and running performance, not anthropometric factors, are associated with race performance in a triple iron triathlon. Res Sports Med. (2007) 15:257–69. doi: 10.1080/15438620701693264

PubMed Abstract | Crossref Full Text | Google Scholar

98. Knechtle B, Kohler G. Running performance, not anthropometric factors, is associated with race success in a triple iron triathlon. Br J Sports Med. (2009) 43:437–41. doi: 10.1136/bjsm.2007.039602

PubMed Abstract | Crossref Full Text | Google Scholar

99. Etxebarria N, Wright J, Jeacocke H, Mesquida C, Pyne DB. Running your best triathlon race. Int J Sports Physiol Perform. (2021) 16:744–7. doi: 10.1123/ijspp.2020-0838

PubMed Abstract | Crossref Full Text | Google Scholar

100. Weiss K, Valero D, Andrade MS, Villiger E, Thuany M, Knechtle B. Cycling is the most important predictive split discipline in professional ironman® 70.3 triathletes. Front Sports Act Living. (2024) 6:1214929. doi: 10.3389/fspor.2024.1214929

PubMed Abstract | Crossref Full Text | Google Scholar

101. Knechtle B, Knechtle P, Rosemann T. Upper body skinfold thickness is related to race performance in male ironman triathletes. Int J Sports Med. (2011) 32:20–7. doi: 10.1055/s-0030-1268435

PubMed Abstract | Crossref Full Text | Google Scholar

102. Sousa C, Barbosa L, Sales M, Santos P, Tiozzo E, Simões H, et al. Cycling as the best sub-8-hour performance predictor in full distance triathlon. Sports. (2019) 7:24. doi: 10.3390/sports7010024

PubMed Abstract | Crossref Full Text | Google Scholar

103. Figueiredo P, Marques EA, Lepers R. Changes in contributions of swimming, cycling, and running performances on overall triathlon performance over a 26-year period. J Strength Cond Res. (2016) 30:2406–15. doi: 10.1519/JSC.0000000000001335

PubMed Abstract | Crossref Full Text | Google Scholar

104. Nikolaidis PT, Valero D, Weiss K, Villiger E, Thuany M, Sousa CV, et al. Predicting overall performance in ironman 70.3 age group triathletes through split disciplines. Sci Rep. (2023) 13:11492. doi: 10.1038/s41598-023-38181-y

PubMed Abstract | Crossref Full Text | Google Scholar

105. Knechtle B, Thuany M, Valero D, Villiger E, Nikolaidis PT, Cuk I, et al. Europe has the fastest ironman race courses and the fastest ironman age group triathletes. Sci Rep. (2024) 14:20903. doi: 10.1038/s41598-024-71866-6

PubMed Abstract | Crossref Full Text | Google Scholar

106. Ose BM, Eisenhauer J, Roepe I, Herda AA, Vopat BG, Vopat LM. Where are all the female participants in sports and exercise medicine research? A decade later. Am J Sports Med. (2025):3635465241278350. doi: 10.1177/03635465241278350

PubMed Abstract | Crossref Full Text | Google Scholar

107. Cowley ES, Olenick AA, McNulty KL, Ross EZ. 'Invisible sportswomen': the sex data gap in sport and exercise science research. Women Sport Phys Act J. (2021) 29:146–51. doi: 10.1123/wspaj.2021-0028

Crossref Full Text | Google Scholar

108. Lanferdini FJ, Diefenthaeler F, Ardigò LP, Peyré-Tartaruga LA, Padulo J. Editorial: structural and mechanistic determinants of endurance performance. Front Physiol. (2022) 13:1035583. doi: 10.3389/fphys.2022.1035583

PubMed Abstract | Crossref Full Text | Google Scholar

109. Leischik R. Physiological performance and cardiac function in female ironman- triathletes. Am J Sports Sci. (2014) 2:41. doi: 10.11648/j.ajss.20140202.16

Crossref Full Text | Google Scholar

110. Bassett DR Jr, Howley ET. Limiting factors for maximum oxygen uptake and determinants of endurance performance. Med Sci Sports Exerc. (2000) 32(1):70–84. doi: 10.1097/00005768-200001000-00012

PubMed Abstract | Crossref Full Text | Google Scholar

111. Schmidt W, Prommer N. Impact of alterations in total hemoglobin mass on V˙O2max. Exerc Sport Sci Rev. (2010) 38:68–75. doi: 10.1097/JES.0b013e3181d4957a

PubMed Abstract | Crossref Full Text | Google Scholar

112. Joyner MJ, Coyle EF. Endurance exercise performance: the physiology of champions. J Physiol. (2008) 586:35–44. doi: 10.1113/jphysiol.2007.143834

PubMed Abstract | Crossref Full Text | Google Scholar

113. Santisteban KJ, Lovering AT, Halliwill JR, Minson CT. Sex differences in VO2max and the impact on endurance-exercise performance. Int J Environ Res Public Health. (2022) 19:4946. doi: 10.3390/ijerph19094946

PubMed Abstract | Crossref Full Text | Google Scholar

114. Coyle EF. Physiological determinants of endurance exercise performance. J Sci Med Sport. (1999) 2:181–9. doi: 10.1016/S1440-2440(99)80172-8

PubMed Abstract | Crossref Full Text | Google Scholar

115. Shaskey DJ, Green GA. Sports haematology. Sports Med. (2000) 29:27–38. doi: 10.2165/00007256-200029010-00003

PubMed Abstract | Crossref Full Text | Google Scholar

116. Cureton K, Bishop P, Hutchinson P, Newland H, Vickery S, Zwiren L. Sex difference in maximal oxygen uptake. Eur J Appl Physiol Occup Physiol. (1986) 54:656–60. doi: 10.1007/BF00943356

PubMed Abstract | Crossref Full Text | Google Scholar

117. Ansdell P, Thomas K, Hicks KM, Hunter SK, Howatson G, Goodall S. Physiological sex differences affect the integrative response to exercise: acute and chronic implications. Exp Physiol. (2020) 105:2007–21. doi: 10.1113/EP088548

PubMed Abstract | Crossref Full Text | Google Scholar

118. Murphy WG. The sex difference in haemoglobin levels in adults — mechanisms, causes, and consequences. Blood Rev. (2014) 28:41–7. doi: 10.1016/j.blre.2013.12.003

PubMed Abstract | Crossref Full Text | Google Scholar

119. Millet GP, Bentley DJ. The physiological responses to running after cycling in elite junior and senior triathletes. Int J Sports Med. (2004) 25:191–7. doi: 10.1055/s-2003-45259

PubMed Abstract | Crossref Full Text | Google Scholar

120. Martins HA, Barbosa JG, Seffrin A, Vivan L, , Souza VR dos A, de Lira CAB, et al. Sex differences in maximal oxygen uptake adjusted for skeletal muscle mass in amateur endurance athletes: a cross sectional study. Healthcare. (2023) 11:1502. doi: 10.3390/healthcare11101502

PubMed Abstract | Crossref Full Text | Google Scholar

121. Trinschek J, Zieliński J, Kusy K. Maximal oxygen uptake adjusted for skeletal muscle mass in competitive speed-power and endurance male athletes: changes in a one-year training cycle. Int J Environ Res Public Health. (2020) 17:6226. doi: 10.3390/ijerph17176226

PubMed Abstract | Crossref Full Text | Google Scholar

122. Sparling PB. A meta-analysis of studies comparing maximal oxygen uptake in men and women. Res Q Exerc Sport. (1980) 51:542–52. doi: 10.1080/02701367.1980.10608077

PubMed Abstract | Crossref Full Text | Google Scholar

123. Ruby BC, Coggan AR, Zderic TW. Gender differences in glucose kinetics and substrate oxidation during exercise near the lactate threshold. J Appl Physiol. (2002) 92:1125–32. doi: 10.1152/japplphysiol.00296.2001

PubMed Abstract | Crossref Full Text | Google Scholar

124. Bassett DR. Scientific contributions of A. V. Hill: exercise physiology pioneer. J Appl Physiol. (2002) 93:1567–82. doi: 10.1152/japplphysiol.01246.2001

PubMed Abstract | Crossref Full Text | Google Scholar

125. Quittmann OJ, Foitschik T, Vafa R, Freitag FJ, Sparmann N, Nolte S, et al. Is maximal lactate accumulation rate promising for improving 5000-m prediction in running? Int J Sports Med. (2023) 44:268–79. doi: 10.1055/a-1958-3876

PubMed Abstract | Crossref Full Text | Google Scholar

126. Holloszy JO, Coyle EF. Adaptations of skeletal muscle to endurance exercise and their metabolic consequences. J Appl Physiol. (1984) 56:831–8. doi: 10.1152/jappl.1984.56.4.831

PubMed Abstract | Crossref Full Text | Google Scholar

127. Lundby C, Robach P. Performance enhancement: what are the physiological limits? Physiology. (2015) 30:282–92. doi: 10.1152/physiol.00052.2014

PubMed Abstract | Crossref Full Text | Google Scholar

128. Pilegaard H, Bangsbo J, Richter EA, Juel C. Lactate transport studied in sarcolemmal giant vesicles from human muscle biopsies: relation to training status. J Appl Physiol. (1994) 77:1858–62. doi: 10.1152/jappl.1994.77.4.1858

PubMed Abstract | Crossref Full Text | Google Scholar

129. Støa EM, Helgerud J, Rønnestad BR, Hansen J, Ellefsen S, Støren Ø. Factors influencing running velocity at lactate threshold in male and female runners at different levels of performance. Front Physiol. (2020) 11:585267. doi: 10.3389/fphys.2020.585267

PubMed Abstract | Crossref Full Text | Google Scholar

130. Knechtle B, Knechtle P, Andonie JL, Kohler G. Influence of anthropometry on race performance in extreme endurance triathletes: world challenge deca iron triathlon 2006. Br J Sports Med. (2007) 41:644–8. doi: 10.1136/bjsm.2006.035014

PubMed Abstract | Crossref Full Text | Google Scholar

131. Mclean SP, Hinrichs RN. Sex differences in the centre of buoyancy location of competitive swimmers. J Sports Sci. (1998) 16:373–83. doi: 10.1080/02640419808559365

PubMed Abstract | Crossref Full Text | Google Scholar

132. Tiller NB, Elliott-Sale KJ, Knechtle B, Wilson PB, Roberts JD, Millet GY. Do sex differences in physiology confer a female advantage in ultra-endurance sport? Sports Med. (2021) 51:895–915. doi: 10.1007/s40279-020-01417-2

PubMed Abstract | Crossref Full Text | Google Scholar

133. Puccinelli P, de Lira CA, Vancini RL, Nikolaidis PT, Knechtle B, Andrade MS. Distribution of body fat is associated with physical performance of male amateur triathlon athletes. J Sports Med Phys Fitness. (2022) 62(2):215–21. doi: 10.23736/S0022-4707.21.12075-4

PubMed Abstract | Crossref Full Text | Google Scholar

134. Cortesi M, Gatta G, Michielon G, Di Michele R, Bartolomei S, Scurati R. Passive drag in young swimmers: effects of body composition, morphology and gliding position. Int J Environ Res Public Health. (2020) 17:2002. doi: 10.3390/ijerph17062002

PubMed Abstract | Crossref Full Text | Google Scholar

135. Keatinge WR. Hypothermia during sports swimming in water below 11degreesC. Br J Sports Med. (2001) 35:352–3. doi: 10.1136/bjsm.35.5.352

PubMed Abstract | Crossref Full Text | Google Scholar

136. Knechtle B, Christinger N, Kohler G, Knechtle P, Rosemann T. Swimming in ice cold water. Ir J Med Sci. (2009) 178:507–11. doi: 10.1007/s11845-009-0427-0

PubMed Abstract | Crossref Full Text | Google Scholar

137. Bernard T, Sultana F, Lepers R, Hausswirth C, Brisswalter J. Age-Related decline in Olympic triathlon performance: effect of locomotion mode. Exp Aging Res. (2009) 36:64–78. doi: 10.1080/03610730903418620

PubMed Abstract | Crossref Full Text | Google Scholar

138. Bassett AJ, Ahlmen A, Rosendorf JM, Romeo AA, Erickson BJ, Bishop ME. The biology of sex and sport. JBJS Rev. (2020) 8:e0140. doi: 10.2106/JBJS.RVW.19.00140

PubMed Abstract | Crossref Full Text | Google Scholar

139. Hunter SK. Sex differences in human fatigability: mechanisms and insight to physiological responses. Acta Physiol. (2014) 210:768–89. doi: 10.1111/apha.12234

PubMed Abstract | Crossref Full Text | Google Scholar

140. Hicks AL, Kent-Braun J, Ditor DS. Sex differences in human skeletal muscle fatigue. Exerc Sport Sci Rev. (2001) 29:109–12. doi: 10.1097/00003677-200107000-00004

PubMed Abstract | Crossref Full Text | Google Scholar

141. Hottenrott L, Möhle M, Ide A, Ketelhut S, Stoll O, Hottenrott K. Recovery from different high-intensity interval training protocols: comparing well-trained women and men. Sports. (2021) 9:34. doi: 10.3390/sports9030034

PubMed Abstract | Crossref Full Text | Google Scholar

142. Besson T, Macchi R, Rossi J, Morio CYM, Kunimasa Y, Nicol C, et al. Sex differences in endurance running. Sports Med. (2022) 52:1235–57. doi: 10.1007/s40279-022-01651-w

PubMed Abstract | Crossref Full Text | Google Scholar

143. Saunders PU, Pyne DB, Telford RD, Hawley JA. Factors affecting running economy in trained distance runners. Sports Med. (2004) 34:465–85. doi: 10.2165/00007256-200434070-00005

PubMed Abstract | Crossref Full Text | Google Scholar

144. Ekenros L, von Rosen P, Solli GS, Sandbakk Ø, Holmberg H-C, Hirschberg AL, et al. Perceived impact of the menstrual cycle and hormonal contraceptives on physical exercise and performance in 1,086 athletes from 57 sports. Front Physiol. (2022) 13:954760. doi: 10.3389/fphys.2022.954760

PubMed Abstract | Crossref Full Text | Google Scholar

145. McNulty KL, Elliott-Sale KJ, Dolan E, Swinton PA, Ansdell P, Goodall S, et al. The effects of menstrual cycle phase on exercise performance in eumenorrheic women: a systematic review and meta-analysis. Sports Med. (2020) 50:1813–27. doi: 10.1007/s40279-020-01319-3

PubMed Abstract | Crossref Full Text | Google Scholar

146. Carmichael MA, Thomson RL, Moran LJ, Wycherley TP. The impact of menstrual cycle phase on Athletes’ performance: a narrative review. Int J Environ Res Public Health. (2021) 18:1667. doi: 10.3390/ijerph18041667

PubMed Abstract | Crossref Full Text | Google Scholar

147. Tanaka H, Seals DR. Endurance exercise performance in masters athletes: age-associated changes and underlying physiological mechanisms. J Physiol. (2008) 586:55–63. doi: 10.1113/jphysiol.2007.141879

PubMed Abstract | Crossref Full Text | Google Scholar

148. Knechtle R, Rüst CA, Rosemann T, Knechtle B. The best triathletes are older in longer race distances – a comparison between Olympic, half-ironman and ironman distance triathlon. Springerplus. (2014) 3:538. doi: 10.1186/2193-1801-3-538

PubMed Abstract | Crossref Full Text | Google Scholar

149. Knechtle B, Rüst CA, Knechtle P, Rosemann T, Lepers R. Age-related changes in ultra-triathlon performances. Extrem Physiol Med. (2012) 1:5. doi: 10.1186/2046-7648-1-5

PubMed Abstract | Crossref Full Text | Google Scholar

150. Hoffman MD. Performance trends in 161-km ultramarathons. Int J Sports Med. (2010) 31:31–7. doi: 10.1055/s-0029-1239561

PubMed Abstract | Crossref Full Text | Google Scholar

151. Knechtle B, Rosemann T, Knechtle P, Lepers R. Predictor variables for A 100-km race time in male ultra-marathoners. Percept Mot Skills. (2010) 111:681–93. doi: 10.2466/05.25.PMS.111.6.681-693

PubMed Abstract | Crossref Full Text | Google Scholar

152. Stiefel M, Knechtle B, Lepers R. Master triathletes have not reached limits in their ironman triathlon performance. Scand J Med Sci Sports (2014) 24:89–97. doi: 10.1111/j.1600-0838.2012.01473.x

PubMed Abstract | Crossref Full Text | Google Scholar

153. Puccinelli P, Sacchelli AN, Seffrin A, Knechtle B, Weiss K, Andrade MS. Origin and age group of the fastest amateur triathletes competing in ‘ironman Hawaii’ between 2003 and 2019. Sports Med Health Sci. (2024) 6:70–5. doi: 10.1016/j.smhs.2023.07.008

PubMed Abstract | Crossref Full Text | Google Scholar

154. Lepers R, Sultana F, Bernard T, Hausswirth C, Brisswalter J. Age-Related changes in triathlon performances. Int J Sports Med. (2010) 31:251–6. doi: 10.1055/s-0029-1243647

PubMed Abstract | Crossref Full Text | Google Scholar

155. Bijker KE, de Groot G, Hollander AP. Differences in leg muscle activity during running and cycling in humans. Eur J Appl Physiol. (2002) 87:556–61. doi: 10.1007/s00421-002-0663-8

PubMed Abstract | Crossref Full Text | Google Scholar

156. Knechtle B, Nikolaidis P, Rosemann T. Performance trends in age group breaststroke swimmers in the FINA world championships 1986–2014. Chin J Physiol. (2016) 59:247–59. doi: 10.4077/CJP.2016.BAE406

PubMed Abstract | Crossref Full Text | Google Scholar

157. Zingg MA, Knechtle B, Rüst CA, Rosemann T, Lepers R. Analysis of participation and performance in athletes by age group in ultramarathons of more than 200 km in length. Int J Gen Med. (2013) 6:209–20. doi: 10.2147/IJGM.S43454

PubMed Abstract | Crossref Full Text | Google Scholar

158. Donato AJ, Tench K, Glueck DH, Seals DR, Eskurza I, Tanaka H. Declines in physiological functional capacity with age: a longitudinal study in peak swimming performance. J Appl Physiol. (2003) 94:764–9. doi: 10.1152/japplphysiol.00438.2002

PubMed Abstract | Crossref Full Text | Google Scholar

159. Millet G, Vleck V, Bentley D. Physiological differences between cycling and running. Rev Med Suisse. (2009) 5:1564–7. doi: 10.2165/00007256-200939030-00002

PubMed Abstract | Crossref Full Text | Google Scholar

160. Kaminsky LA, Arena R, Myers J. Reference standards for cardiorespiratory fitness measured with cardiopulmonary exercise testing. Mayo Clin Proc. (2015) 90:1515–23. doi: 10.1016/j.mayocp.2015.07.026

PubMed Abstract | Crossref Full Text | Google Scholar

161. Tanaka H, Seals DR. Invited review: dynamic exercise performance in masters athletes: insight into the effects of primary human aging on physiological functional capacity. J Appl Physiol (1985). (2003) 95:2152–62. doi: 10.1152/japplphysiol.00320.2003

PubMed Abstract | Crossref Full Text | Google Scholar

162. Phillips SK, Rook KM, Siddle NC, Bruce SA, Woledge RC. Muscle weakness in women occurs at an earlier age than in men, but strength is preserved by hormone replacement therapy. Clin Sci. (1993) 84:95–8. doi: 10.1042/cs0840095

PubMed Abstract | Crossref Full Text | Google Scholar

163. Samson MM, Meeuwsen IB, Crowe A, Dessens JA, Duursma SA, Verhaar HJ. Relationships between physical performance measures, age, height and body weight in healthy adults. Age Ageing. (2000) 29:235–42. doi: 10.1093/ageing/29.3.235

PubMed Abstract | Crossref Full Text | Google Scholar

164. Fitzgerald MD, Tanaka H, Tran ZV, Seals DR. Age-related declines in maximal aerobic capacity in regularly exercising vs. sedentary women: a meta-analysis. J Appl Physiol (1985). (1997) 83:160–5. doi: 10.1152/jappl.1997.83.1.160

PubMed Abstract | Crossref Full Text | Google Scholar

165. Pollock ML, Mengelkoch LJ, Graves JE, Lowenthal DT, Limacher MC, Foster C, et al. Twenty-year follow-up of aerobic power and body composition of older track athletes. J Appl Physiol. (1997) 82:1508–16. doi: 10.1152/jappl.1997.82.5.1508

PubMed Abstract | Crossref Full Text | Google Scholar

166. Leyk D, Erley O, Gorges W, Ridder D, Rüther T, Wunderlich M, et al. Performance, training and lifestyle parameters of marathon runners aged 20–80 years: results of the PACE-study. Int J Sports Med. (2009) 30:360–5. doi: 10.1055/s-0028-1105935

PubMed Abstract | Crossref Full Text | Google Scholar

167. Trappe S. Marathon runners: how do they age? Sports Med. (2007) 37:302–5. doi: 10.2165/00007256-200737040-00008

PubMed Abstract | Crossref Full Text | Google Scholar

168. Gries KJ, Witto PE. Age and sex differences in IRONMAN world championship performance. J Strength Cond Res. (2025) 39(2):269–76. doi: 10.1519/JSC.0000000000004972

PubMed Abstract | Crossref Full Text | Google Scholar

169. Horstman AM, Dillon EL, Urban RJ, Sheffield-Moore M. The role of androgens and estrogens on healthy aging and longevity. J Gerontol A Biol Sci Med Sci. (2012) 67:1140–52. doi: 10.1093/gerona/gls068

PubMed Abstract | Crossref Full Text | Google Scholar

170. Thein-Nissenbaum J. The postpartum triathlete. Phys Ther Sport. (2016) 21:95–106. doi: 10.1016/j.ptsp.2016.07.006

PubMed Abstract | Crossref Full Text | Google Scholar

171. Etxebarria N, Anson JM, Pyne DB, Ferguson RA. High-intensity cycle interval training improves cycling and running performance in triathletes. Eur J Sport Sci. (2014) 14:521–9. doi: 10.1080/17461391.2013.853841

PubMed Abstract | Crossref Full Text | Google Scholar

172. Knechtle B, Zingg MA, Rosemann T, Rüst CA. The aspect of experience in ultra-triathlon races. Springerplus. (2015) 4:278. doi: 10.1186/s40064-015-1050-3

PubMed Abstract | Crossref Full Text | Google Scholar

173. Sinisgalli R, de Lira CAB, Vancini RL, Puccinelli PJG, Hill L, Knechtle B, et al. Impact of training volume and experience on amateur ironman triathlon performance. Physiol Behav. (2021) 232:113344. doi: 10.1016/j.physbeh.2021.113344

PubMed Abstract | Crossref Full Text | Google Scholar

174. Falk Neto JH, Parent EC, Vleck V, Kennedy MD. The training characteristics of recreational-level triathletes: influence on fatigue and health. Sports. (2021) 9:94. doi: 10.3390/sports9070094

PubMed Abstract | Crossref Full Text | Google Scholar

175. O'Toole ML. Training for ultraendurance triathlons. Med Sci Sports Exerc. (1989) 21:S209–13.

Google Scholar

176. Gulbin JP, Gaffney PT. Ultraendurance triathlon participation: typical race preparation of lower level triathletes. J Sports Med Phys Fitness. (1999) 39:12–5.10230162

PubMed Abstract | Google Scholar

177. Hendy HM, Boyer BJ. Specificity in the relationship between training and performance in triathlons. Percept Mot Skills. (1995) 81:1231–40. doi: 10.2466/pms.1995.81.3f.1231

PubMed Abstract | Crossref Full Text | Google Scholar

178. Leake CN, Carter JEL. Comparison of body composition and somatotype of trained female triathletes. J Sports Sci. (1991) 9:125–35. doi: 10.1080/02640419108729874

PubMed Abstract | Crossref Full Text | Google Scholar

179. Mujika I. Olympic preparation of a world-class female triathlete. Int J Sports Physiol Perform. (2014) 9:727–31. doi: 10.1123/ijspp.2013-0245

PubMed Abstract | Crossref Full Text | Google Scholar

180. Muñoz I, Cejuela R, Seiler S, Larumbe E, Esteve-Lanao J. Training-Intensity distribution during an ironman season: relationship with competition performance. Int J Sports Physiol Perform. (2014) 9:332–9. doi: 10.1123/ijspp.2012-0352

PubMed Abstract | Crossref Full Text | Google Scholar

181. Mujika I, Chatard J-C, Busso T, Geyssant A, Barale F, Lacoste L. Effects of training on performance in competitive swimming. Can J Appl Physiol. (1995) 20:395–406. doi: 10.1139/h95-031

PubMed Abstract | Crossref Full Text | Google Scholar

182. Sanders D, Myers T, Akubat I. Training-intensity distribution in road cyclists: objective versus subjective measures. Int J Sports Physiol Perform. (2017) 12:1232–7. doi: 10.1123/ijspp.2016-0523

PubMed Abstract | Crossref Full Text | Google Scholar

183. Esteve-Lanao J, Juan AFS, Earnest CP, Foster C, Lucia A. How do endurance runners actually train? Relationship with competition performance. Med Sci Sports Exerc. (2005) 37:496–504. doi: 10.1249/01.MSS.0000155393.78744.86

PubMed Abstract | Crossref Full Text | Google Scholar

184. Bonato G, Goodman SPJ, Tjh L. Physiological and performance effects of live high train low altitude training for elite endurance athletes: a narrative review. Curr Res Physiol. (2023) 6:100113. doi: 10.1016/j.crphys.2023.100113

PubMed Abstract | Crossref Full Text | Google Scholar

185. Sinex JA, Chapman RF. Hypoxic training methods for improving endurance exercise performance. J Sport Health Sci. (2015) 4:325–32. doi: 10.1016/j.jshs.2015.07.005

Crossref Full Text | Google Scholar

186. Wehrlin JP, Zuest P, Hallén J, Marti B. Live high-train low for 24 days increases hemoglobin mass and red cell volume in elite endurance athletes. J Appl Physiol. (2006) 100:1938–45. doi: 10.1152/japplphysiol.01284.2005

PubMed Abstract | Crossref Full Text | Google Scholar

187. Bonetti DL, Hopkins WG. Sea-level exercise performance following adaptation to hypoxia. Sports Med. (2009) 39:107–27. doi: 10.2165/00007256-200939020-00002

PubMed Abstract | Crossref Full Text | Google Scholar

188. Knechtle B, Wirth A, Rosemann T. Predictors of race time in male ironman triathletes: physical characteristics, training, or prerace experience? Percept Mot Skills. (2010) 111:437–46. doi: 10.2466/05.25.PMS.111.5.437-446

PubMed Abstract | Crossref Full Text | Google Scholar

189. Rüst CA, Knechtle B, Wirth A, Knechtle P, Ellenrieder B, Rosemann T, et al. Personal best times in an Olympic distance triathlon and a marathon predict an ironman race time for recreational female triathletes. Chin J Physiol. (2012) 55:156–62. doi: 10.4077/CJP.2012.BAA014

Crossref Full Text | Google Scholar

190. Rüst CA, Knechtle B, Knechtle P, Rosemann T, Lepers R. Personal best times in an Olympic distance triathlon and in a marathon predict ironman race time in recreational male triathletes. Open Access J Sports Med. (2011) 2:121–9. doi: 10.2147/OAJSM.S23229

PubMed Abstract | Crossref Full Text | Google Scholar

191. Herbst L, Knechtle B, Lopez CL, Andonie JL, Fraire OS, Kohler G, et al. Pacing strategy and change in body composition during a deca iron triathlon. Chin J Physiol. (2011) 54:255–63. doi: 10.4077/CJP.2011.AMM115

PubMed Abstract | Crossref Full Text | Google Scholar

192. Knechtle B, Knechtle P, Rosemann T, Lepers R. Personal best marathon time and longest training run, not anthropometry, predict performance in recreational 24-hour ultrarunners. J Strength Cond Res. (2011) 25:2212–8. doi: 10.1519/JSC.0b013e3181f6b0c7

PubMed Abstract | Crossref Full Text | Google Scholar

193. Knechtle B, Knechtle P, Barandun U, Rosemann T. Anthropometric and training variables related to half-marathon running performance in recreational female runners. Phys Sportsmed. (2011) 39:158–66. doi: 10.3810/psm.2011.05.1907

PubMed Abstract | Crossref Full Text | Google Scholar

194. Knechtle B, Knechtle P, Rüst CA, Rosemann T, Lepers R. Finishers and nonfinishers in the 'Swiss cycling marathon' to qualify for the 'Race across America'. J Strength Cond Res. (2011) 25:3257–63. doi: 10.1519/JSC.0b013e31821606b3

PubMed Abstract | Crossref Full Text | Google Scholar

195. Knechtle B, Knechtle P, Rosemann T, Senn O. Personal best time and training volume, not anthropometry, is related to race performance in the ‘Swiss bike masters’ mountain bike ultramarathon. J Strength Cond Res. (2011) 25:1312–7. doi: 10.1519/JSC.0b013e3181d85ac4

PubMed Abstract | Crossref Full Text | Google Scholar

196. Abbiss CR, Laursen PB. Describing and understanding pacing strategies during athletic competition. Sports Med. (2008) 38:239–52. doi: 10.2165/00007256-200838030-00004

PubMed Abstract | Crossref Full Text | Google Scholar

197. Johnson EC, Pryor JL, Casa DJ, Belval LN, Vance JS, DeMartini JK, et al. Bike and run pacing on downhill segments predict ironman triathlon relative success. J Sci Med Sport. (2015) 18:82–7. doi: 10.1016/j.jsams.2013.12.001

PubMed Abstract | Crossref Full Text | Google Scholar

198. Pryor JL, Adams WM, Huggins RA, Belval LN, Pryor RR, Casa DJ. Pacing strategy of a full ironman overall female winner on a course with Major elevation changes. J Strength Cond Res. (2018) 32:3080–7. doi: 10.1519/JSC.0000000000002807

PubMed Abstract | Crossref Full Text | Google Scholar

199. Skorski S, Abbiss CR. The manipulation of pace within endurance sport. Front Physiol. (2017) 8:102. doi: 10.3389/fphys.2017.00102

PubMed Abstract | Crossref Full Text | Google Scholar

200. Casado A, Hanley B, Jiménez-Reyes P, Renfree A. Pacing profiles and tactical behaviors of elite runners. J Sport Health Sci. (2021) 10:537–49. doi: 10.1016/j.jshs.2020.06.011

PubMed Abstract | Crossref Full Text | Google Scholar

201. Heidenfelder A, Rosemann T, Rüst CA, Knechtle B. Pacing strategies of ultracyclists in the 'Race across America'. Int J Sports Physiol Perform. (2016) 11:319–27. doi: 10.1123/ijspp.2015-0051

PubMed Abstract | Crossref Full Text | Google Scholar

202. Wu SSX, Peiffer JJ, Peeling P, Brisswalter J, Lau WY, Nosaka K, et al. Improvement of sprint triathlon performance in trained athletes with positive swim pacing. Int J Sports Physiol Perform. (2016) 11:1024–8. doi: 10.1123/ijspp.2015-0580

PubMed Abstract | Crossref Full Text | Google Scholar

203. Knechtle B, Cuk I, Villiger E, Forte P, Thuany M, Andrade MS, et al. Performance and pacing of professional IRONMAN triathletes: the fastest IRONMAN world championship ever—iRONMAN Hawaii 2022. Sci Rep. (2023) 13:15708. doi: 10.1038/s41598-023-42800-z

PubMed Abstract | Crossref Full Text | Google Scholar

204. Le Meur Y, Hausswirth C, Dorel S, Bignet F, Brisswalter J, Bernard T. Influence of gender on pacing adopted by elite triathletes during a competition. Eur J Appl Physiol. (2009) 106:535–45. doi: 10.1007/s00421-009-1043-4

PubMed Abstract | Crossref Full Text | Google Scholar

205. Vleck VE, Bentley DJ, Millet GP, Bürgi A. Pacing during an elite Olympic distance triathlon: comparison between male and female competitors. J Sci Med Sport. (2008) 11:424–32. doi: 10.1016/j.jsams.2007.01.006

PubMed Abstract | Crossref Full Text | Google Scholar

206. Lambert E V, St Clair Gibson A, Noakes TD. Complex systems model of fatigue: integrative homoeostatic control of peripheral physiological systems during exercise in humans. Br J Sports Med. (2005) 39:52–62. doi: 10.1136/bjsm.2003.011247

PubMed Abstract | Crossref Full Text | Google Scholar

207. Le Meur Y, Bernard T, Dorel S, Abbiss CR, Honnorat G, Brisswalter J, et al. Relationships between triathlon performance and pacing strategy during the run in an international competition. Int J Sports Physiol Perform. (2011) 6:183–94. doi: 10.1123/ijspp.6.2.183

PubMed Abstract | Crossref Full Text | Google Scholar

208. Getzin AR, Milner C, LaFace KM. Nutrition update for the ultraendurance athlete. Curr Sports Med Rep. (2011) 10:330–9. doi: 10.1249/JSR.0b013e318237fcdf

PubMed Abstract | Crossref Full Text | Google Scholar

209. Jeukendrup AE. Nutrition for endurance sports: marathon, triathlon, and road cycling. J Sports Sci. (2011) 29:S91–9. doi: 10.1080/02640414.2011.610348

PubMed Abstract | Crossref Full Text | Google Scholar

210. Getzin AR, Milner C, Harkins M. Fueling the triathlete: evidence-based practical advice for athletes of all levels. Curr Sports Med Rep. (2017) 16:240–6. doi: 10.1249/JSR.0000000000000386

PubMed Abstract | Crossref Full Text | Google Scholar

211. Lodge MT, Ward-Ritacco CL, Melanson KJ. Considerations of low carbohydrate availability (LCA) to relative energy deficiency in sport (RED-S) in female endurance athletes: a narrative review. Nutrients. (2023) 15:4457. doi: 10.3390/nu15204457

PubMed Abstract | Crossref Full Text | Google Scholar

212. Williams NI, Statuta SM, Austin A. Female athlete triad. Clin Sports Med. (2017) 36:671–86. doi: 10.1016/j.csm.2017.05.003

PubMed Abstract | Crossref Full Text | Google Scholar

213. Matzkin E, Curry EJ, Whitlock K. Female athlete Triad. J Am Acad Orthop Sur. (2015) 23:424–32. doi: 10.5435/JAAOS-D-14-00168

Crossref Full Text | Google Scholar

214. Mountjoy M, Sundgot-Borgen JK, Burke LM, Ackerman KE, Blauwet C, Constantini N, et al. IOC consensus statement on relative energy deficiency in sport (RED-S): 2018 update. Br J Sports Med. (2018) 52:687–97. doi: 10.1136/bjsports-2018-099193

PubMed Abstract | Crossref Full Text | Google Scholar

215. Witkoś J, Błażejewski G, Gierach M. The low energy availability in females questionnaire (LEAF-Q) as a useful tool to identify female triathletes at risk for menstrual disorders related to low energy availability. Nutrients. (2023) 15:650. doi: 10.3390/nu15030650

Crossref Full Text | Google Scholar

216. Urso C, Brucculeri S, Caimi G. Physiopathological, epidemiological, clinical and therapeutic aspects of exercise-associated hyponatremia. J Clin Med. (2014) 3:1258–75. doi: 10.3390/jcm3041258

PubMed Abstract | Crossref Full Text | Google Scholar

217. Knechtle B, Chlíbková D, Papadopoulou S, Mantzorou M, Rosemann T, Nikolaidis PT. Exercise-associated hyponatremia in endurance and ultra-endurance performance–aspects of sex, race location, ambient temperature, sports discipline, and length of performance: a narrative review. Medicina (B Aires). (2019) 55:537. doi: 10.3390/medicina55090537

Crossref Full Text | Google Scholar

218. Johnson KB, Connolly CP, Cho SP, Miller TK, Sallis RE, Hiller WDB. Clinical presentation of exercise-associated hyponatremia in male and female IRONMAN® triathletes over three decades. Scand J Med Sci Sports. (2023) 33:1841–9. doi: 10.1111/sms.14401

PubMed Abstract | Crossref Full Text | Google Scholar

219. Boucher VG, Caru M, Martin S-M, Lopes M, Comtois AS, Lalonde F. Psychological status during and after the preparation of a long-distance triathlon event in amateur athletes. Int J Exerc Sci. (2021) 14:134–48. doi: 10.70252/KMCO5090

PubMed Abstract | Crossref Full Text | Google Scholar

220. Bond KA, Batey J. Running for their lives: a qualitative analysis of the exercise experience of female recreational runners. Women Sport Phys Act J. (2005) 14:69–82. doi: 10.1123/wspaj.14.2.69

Crossref Full Text | Google Scholar

221. Hodge K, Allen JB, Smellie L. Motivation in masters sport: achievement and social goals. Psychol Sport Exerc. (2008) 9:157–76. doi: 10.1016/j.psychsport.2007.03.002

Crossref Full Text | Google Scholar

222. Levy SS. Women and the personal meaning of competition: a qualitative investigation. Women Sport Phys Act J (2002) 11(1):107–25. doi: 10.1123/wspaj.11.1.107

Crossref Full Text | Google Scholar

223. López-Fernández I, Merino-Marbán R, Fernández-Rodríguez E. Examining the relationship between sex and motivation in triathletes. Percept Mot Skills. (2014) 119:42–9. doi: 10.2466/30.19.PMS.119c11z1

PubMed Abstract | Crossref Full Text | Google Scholar

224. Olmedilla A, Torres-Luque G, García-Mas A, Rubio VJ, Ducoing E, Ortega E. Psychological profiling of triathlon and road cycling athletes. Front Psychol. (2018) 9:825. doi: 10.3389/fpsyg.2018.00825

PubMed Abstract | Crossref Full Text | Google Scholar

225. Käch IW, Rüst CA, Nikolaidis PT, Rosemann T, Knechtle B. The age-related performance decline in ironman triathlon starts earlier in swimming than in cycling and running. J Strength Cond Res. (2018) 32:379–95. doi: 10.1519/JSC.0000000000001796

PubMed Abstract | Crossref Full Text | Google Scholar

226. Stiefel M, Knechtle B, Rüst CA, Rosemann T, Lepers R. The age of peak performance in ironman triathlon: a cross-sectional and longitudinal data analysis. Extrem Physiol Med. (2013) 2(1):27. doi: 10.1186/2046-7648-2-27

PubMed Abstract | Crossref Full Text | Google Scholar

227. Knechtle B, Rüst CA, 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. (2012) 3:59–66. doi: 10.2147/oajsm.s32922

PubMed Abstract | Crossref Full Text | Google Scholar

228. Rüst CA, Lepers R, Stiefel M, Rosemann T, Knechtle B. Performance in Olympic triathlon: changes in performance of elite female and male triathletes in the ITU world triathlon series from 2009 to 2012. Springerplus. (2013) 2:685. doi: 10.1186/2193-1801-2-685

PubMed Abstract | Crossref Full Text | Google Scholar

229. Knechtle B. Performance and sex differences in 'Isklar norseman Xtreme triathlon'. Chin J Physiol. (2016) 59:276–83. doi: 10.4077/CJP.2016.BAE420

PubMed Abstract | Crossref Full Text | Google Scholar

230. Knechtle B, Zingg MA, Rosemann T, Rüst CA. Sex difference in top performers from ironman to double deca iron ultra-triathlon. Open Access J Sports Med. (2014) 5:159–72. doi: 10.2147/OAJSM.S65977

PubMed Abstract | Crossref Full Text | Google Scholar

231. Rüst CA, Knechtle B, Knechtle P, Rosemann T, Lepers R. Sex differences in ultra-triathlon performance at increasing race distance. Percept Mot Skills. (2013) 116:690–706. doi: 10.2466/30.06.PMS.116.2.690-706

PubMed Abstract | Crossref Full Text | Google Scholar

232. Snoza CT, Berg KE, Slivka DR. Comparison of v˙o 2peak and achievement of v˙o 2peak criteria in three modes of exercise in female triathletes. J Strength Cond Res. (2016) 30:2816–22. doi: 10.1519/JSC.0000000000000710

PubMed Abstract | Crossref Full Text | Google Scholar

233. Vivan L, dos Anjos VR, Engelke P, de Lira CAB, Vancini RL, Weiss K, et al. Cycling intensity effect on running plus cycling performance among triathletes. Int J Sports Med. (2024) 45(14):1074–83. doi: 10.1055/a-2404-8537

PubMed Abstract | Crossref Full Text | Google Scholar

234. Assis MG, Barbosa Junior JG, Seffrin A, Ribeiro dos Anjos Souza V, Vivan L, Matos Rodrigues M, et al. Maximal oxygen uptake, muscular oxidative capacity, and ventilatory threshold in amateur triathletes: eight-month training follow-up. Open Access J Sports Med. (2024) 15:9–17. doi: 10.2147/OAJSM.S453875

PubMed Abstract | Crossref Full Text | Google Scholar

235. Price S, Wiecha S, Cieśliński I, Śliż D, Kasiak PS, Lach J, et al. Differences between treadmill and cycle ergometer cardiopulmonary exercise testing results in triathletes and their association with body composition and body mass Index. Int J Environ Res Public Health. (2022) 19(6):3557. doi: 10.3390/ijerph19063557

PubMed Abstract | Crossref Full Text | Google Scholar

236. Schneider D, Pollack J. Ventilatory threshold and maximal oxygen uptake during cycling and running in female triathletes. Int J Sports Med. (1991) 12:379–83. doi: 10.1055/s-2007-1024698

PubMed Abstract | Crossref Full Text | Google Scholar

237. Del Coso J, González C, Abian-Vicen J, Salinero Martín JJ, Soriano L, Areces F, et al. Relationship between physiological parameters and performance during a half-ironman triathlon in the heat. J Sports Sci. (2014) 32:1680–7. doi: 10.1080/02640414.2014.915425

PubMed Abstract | Crossref Full Text | Google Scholar

238. Knechtle B, Wirth A, Baumann B, Knechtle P, Kohler G, Rosemann T, et al. An ironman triathlon does not lead to a change in body mass in female triathletes. Res Sports Med. (2010) 18:115–26. doi: 10.1080/15438621003627059

PubMed Abstract | Crossref Full Text | Google Scholar

239. Cruz Correa Netto Soares G, Barbosa Junior JGG, Seffrin A, Vivan L, Rosa de Freitas JV, Costa GDCT, et al. Comparison of bone mineral density between female amateur triathletes and nonathletes: a cross-sectional study. Sci Prog. (2024) 107(3):368504241261844. doi: 10.1177/00368504241261844

PubMed Abstract | Crossref Full Text | Google Scholar

240. Sousa CV, Nikolaidis PT, Clemente-Suárez VJ, Rosemann T, Knechtle B. Pacing and performance analysis of the world’s fastest female ultra-triathlete in 5x and 10x ironman. Int J Environ Res Public Health. (2020) 17:1543. doi: 10.3390/ijerph17051543

PubMed Abstract | Crossref Full Text | Google Scholar

241. Poczta J, Almeida N, Malchrowicz-Mośko E. Socio-psychological functions of men and women triathlon participation. Int J Environ Res Public Health. (2021) 18:11766. doi: 10.3390/ijerph182211766

PubMed Abstract | Crossref Full Text | Google Scholar

242. Parsons-Smith RL, Barkase S, Lovell GP, Vleck V, Terry PC. Mood profiles of amateur triathletes: implications for mental health and performance. Front Psychol. (2022) 13:925992. doi: 10.3389/fpsyg.2022.925992

PubMed Abstract | Crossref Full Text | Google Scholar