Differential correlations between anthropometry, training volume, and performance in male and female Ironman triathletes

Europe has the fastest Ironman race courses and the fastest Ironman age group triathletes

The majority of participants in Ironman triathlon races are age group athletes. We have extensive knowledge about recreational athletes' training and competition participation. Nonetheless, Ironman age group triathletes must achieve fast race times to qualify for the Ironman World Championship in Hawaii. They can, therefore, benefit from knowing where the fastest Ironman racecourses in the world are. The aim of the present study was to investigate where the fastest Ironman racecourses for age group triathletes are located in the world. Data from 677,702 Ironman age group finishers' records (544,963 from men and 132,739 from women) originating from 228 countries and participating in 444 events across 66 different Ironman race locations between 2002 and 2022 were analyzed. Data was analyzed through traditional descriptive statistics and with machine learning regression models. Four algorithms were tested (Random Forest Regressor, XG Boost Regressor, Cat Boot Regressor, and Decision Tree Regressor). The models used gender, age group, country of origin, environmental factors (average air and water temperatures), and the event location as independent variables to predict the final overall race time. Despite the majority of successful Ironman age group triathletes originating from the USA (274,553), followed by athletes from the United Kingdom (55,410) and Canada (38,264), these countries exhibited average overall race times that were significantly slower compared to the fastest countries. Most of the triathletes competed in Ironman Wisconsin (38,545), followed by Ironman Florida (38,157) and Ironman Lake Placid (34,341). The fastest overall race times were achieved in Ironman Copenhagen (11.68 ± 1.38 h), followed by Ironman Hawaii (11.72 ± 1.86 h), Ironman Barcelona (11.78 ± 1.43 h), Ironman Florianópolis (11.80 ± 1.52 h), Ironman Frankfurt (12.03 ± 1.38 h) and Ironman Kalmar (12.08 ± 1.47 h). The fastest athletes originated from Belgium (11.48 ± 1.47 h), followed by athletes from Denmark (11.59 ± 1.40 h), Switzerland (11.62 ± 1.49 h), Austria (11.68 ± 1.50), Finland (11.68 ± 1.40 h) and Germany (11.74 ± 15.1 h). Flat running and cycling courses were associated with faster overall race times. Three of the predictive models identified the 'country' and 'age group' variables as the most important predictors. Environmental characteristics showed the lowest influence regarding the other variables. The origin of the athlete was the most predictive variable whereas environmental characteristics showed the lowest influence. Flat cycling and flat running courses were associated with faster overall race times. The fastest overall race times were achieved mainly in European races such as Ironman Copenhagen, Ironman Hawaii, Ironman Barcelona, Ironman Florianópolis, Ironman Frankfurt and Ironman Kalmar. The fastest triathletes originated from European countries such as Belgium, Denmark, Switzerland, Austria, Finland, and Germany.

Advances in Understanding the Interplay between Dietary Practices, Body Composition, and Sports Performance in Athletes

The dietary practices of athletes play a crucial role in shaping their body composition, influencing sports performance, training adaptations, and overall health. However, despite the widely acknowledged significance of dietary intake in athletic success, there exists a gap in our understanding of the intricate relationships between nutrition, body composition, and performance. Furthermore, emerging evidence suggests that many athletes fail to adopt optimal nutritional practices, which can impede their potential achievements. In response, this Special Issue seeks to gather research papers that delve into athletes' dietary practices and their potential impacts on body composition and sports performance. Additionally, studies focusing on interventions aimed at optimizing dietary habits are encouraged. This paper outlines the key aspects and points that will be developed in the ensuing articles of this Special Issue.

Performance and pacing of professional IRONMAN triathletes: the fastest IRONMAN World Championship ever-IRONMAN Hawaii 2022

Pacing during cycling and running in an IRONMAN triathlon has been investigated in only one study with elite IRONMAN triathletes. We have, however, no knowledge of how professional triathletes pace during an IRONMAN World Championship. To investigate the split-by-split speed, pacing strategies and pacing variability in professional female and male IRONMAN World Championship participants in the fastest IRONMAN World Championship ever in IRONMAN Hawaii 2022. For both cycling and running, 25 specific split times were recorded in each discipline. The best 30 men and 30 women overall were chosen from the official IRONMAN website database for further analysis. They were divided into three performance groups: Top 10, 11-20th place, and 21st-30th place. Mean speed, individual linear regressions with the corresponding correlation coefficients, and coefficient of variation were calculated to assess split-by-split speed, pacing strategies, and pacing variability, respectively. In both men's and women's cycling and running segments, the top ten participants exhibited faster split times compared to the slower performance groups. Notably, no discernible differences existed between the 11-20th and 21st-30th place in men's cycling and women's running times. Conversely, in men's running and women's cycling segments, those in the 11-20th place displayed quicker times than those in the 21st-30th place. In the cycling segment across all groups, men demonstrated a more negative pacing pattern (indicating an increase in speed), whereas women exhibited more consistent pacing. In the running segment, the top 10 men and all women's groups showcased relatively similar slightly positive pacing profiles. However, men ranking 11-20th and 21st-30th displayed more pronounced positive pacing strategies, implying a more significant decline in speed over time. In terms of cycling, the variability in pacing remained relatively consistent across the three performance groups. Conversely, during the running segment, the top ten male triathletes and those in the 11-20th place displayed lower pacing variability than their counterparts in the 21st-30th position place and all women's groups. In summary, performance and pacing were examined in professional male and female IRONMAN World Championship participants during IRONMAN Hawaii 2022. Top performers showed faster cycling and running split times, with differences in pacing strategies between sexes. The pacing was more consistent in cycling, while running pacing varied more, particularly among male triathletes in different performance groups.

Best practice recommendations for body composition considerations in sport to reduce health and performance risks: a critical review, original survey and expert opinion by a subgroup of the IOC consensus on Relative Energy Deficiency in Sport (REDs)

BACKGROUND

The assessment of body composition (BC) in sport raises concern for athlete health, especially where an overfocus on being lighter or leaner increases the risk of Relative Energy Deficiency in Sport (REDs) and disordered eating.

METHODS

We undertook a critical review of the effect of BC on performance (29 longitudinal, prospective or intervention studies) and explored current practice related to BC considerations via a follow-up to a 2013 internationally distributed survey.

RESULTS

The review found that a higher level of body fat was negatively associated with endurance performance, while a gain in muscle mass resulted in performance benefits across sports. BC did not contribute to early talent identification, and no unique cut-off to signify a performance advantage for BC was identified. BC appears to be one of an array of variables impacting performance, and its influence should not be overstated. The survey (125 practitioners, 61 sports and 26 countries) showed subtle changes in BC considerations over time, such as an increased role for sport dietitian/nutrition practitioners as BC measurers (2013: 54%, 2022: 78%); less emphasis on reporting of body fat percentage (2013: 68%, 2022: 46%) and reduced frequency of BC assessment if ≥every fourth week (2013: 18%, 2022: 5%). Respondents remained concerned about a problematic focus on BC (2013: 69%, 2022: 78%). To address these findings, we provide detailed recommendations for BC considerations, including an overview of preferable BC methodology.

CONCLUSIONS

The 'best practice' guidelines stress the importance of a multidisciplinary athlete health and performance team, and the treatment of BC data as confidential medical information. The guidelines provide a health focus around BC, aiming to reduce the associated burden of disordered eating, problematic low energy availability and REDs.

CrossFit®: 'Unknowable' or Predictable?-A Systematic Review on Predictors of CrossFit® Performance

The functional fitness training program CrossFit^® is experiencing fast-growing and widespread popularity with day-to-day varying 'Workouts of the Day' (WOD). Even among tactical athletes, the training program is widely applied. Nevertheless, there is a lack of data on which parameters influence CrossFit^® performance. For this reason, the purpose of this study is to conduct a systematic review of the existing literature to identify and summarize predictors of CrossFit^® performance and performance enhancement. In accordance with the PRISMA guidelines, a systematic search of the following databases was conducted in April 2022: PubMed, SPORTDiscus, Scopus, and Web of Science. Using the keyword 'CrossFit', 1264 entries are found, and 21 articles are included based on the eligibility criteria. In summary, the studies show conflicting results, and no specific key parameter was found that predicts CrossFit^® performance regardless of the type of WOD. In detail, the findings indicate that physiological parameters (in particular, body composition) and high-level competitive experience have a more consistent influence than specific performance variables. Nevertheless, in one-third of the studies, high total body strength (i.e., CrossFit^® Total performance) and trunk strength (i.e., back squat performance) correlate with higher workout scores. For the first time, this review presents a summary of performance determinants in CrossFit^®. From this, a guiding principle for training strategies may be derived, suggesting that a focus on body composition, body strength, and competition experience may be recommended for CrossFit^® performance prediction and performance enhancement.

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

BACKGROUND

Nutrition in sport is a priority; it is the basis for maintaining optimal health and a prerequisite for the high performance necessary for competitions. The aim of this study was to assess low energy availability and its possible consequences among female triathletes by using the Low Energy Availability in Females Questionnaire (LEAF-Q).

METHODS

The study involved 30 female triathetes. The LEAF-Q was used in the study. An analysis of the body composition was carried out with the seca device mBCA 515 medical Body Composition Analyzer.

RESULTS

Of the 30 female triathletes studied, 23.3% had a monthly cycle disorder, defined as an amenorrhea state for more than 90 days. No differences were found in injury rates or training days lost to injury due to menstrual disturbances. Menstruation changes were significantly greater due to increases in exercise intensity, frequency, and duration in the group experiencing menstrual disturbances (85.7 [95% CIs: 42.1-99.6] vs. 8.7 [95% CIs: 1.1-28.0]). The menstrual disorder group had a greater incidence of their periods stopping for more than 3 months than the group without menstrual disturbances.

CONCLUSIONS

The female triathletes did not show abnormalities in body weight or composition, and these were not related to the incidence of menstrual disturbances. However, 20% of the triathletes either had, at the time of the study, or had had in the past monthly cycle disorders that could indicate an immediate risk of low energy availability. The LEAF-Q identified 10% of the triathletes as at risk (score > 8) of low energy availability and the physiological and performance consequences related to relative energy deficiency in sports (RED-S).

Age and Training-Related Changes on Body Composition and Fitness in Male Amateur Cyclists

Master athletes are considered as a model of healthy aging because they can limit the age-related decline of physiological abilities compared to sedentary individuals. The main objective of this study is to analyze age-related changes and annual training on body composition (BC) and cardiorespiratory fitness (CRF) parameters. The participants in this retrospective cross-sectional study were 176 male cyclists, aged 40-60 years. BC was evaluated through anthropometric measurements and CRF was determined by an incremental cycle ergometer test to exhaustion. A comparative study between age groups was carried out through a one-way ANOVA test and the associations between the variables were assessed by Spearman's correlation coefficients and multiple regression analysis to estimate the performance. Training was generally associated with a decrease in both body weight and body fat (p < 0.05). A decrease in resting heart rate was observed as a vagal effect of kilometers cycled per year (p < 0.05). Kilometers cycled per year were associated with an increase in peak power output, which was larger in the master 40 group (p < 0.05) with a non-significant upward in VO2max (p > 0.05). In the performance prediction model, the included variables explained 52% of the variance. In summary, the changes induced by age were minimal in BC and negligible in CRF, whereas HR decreased with age. Training load was generally associated with a decrease in body weight, BMI and body fat percentage that was particularly notable in the abdominal skin folds. A decrease in HRrest was observed as a vagal effect due to kilometers cycled per year, and age did not seem to have a significant effect. The annual cycling kilometers were associated with to high PPO that is greater in the M40 group and a non-significant upward trend in VO2max.

The beginning of success: Performance trends and cut-off values for junior and the U23 triathlon categories

Background

This study sought to determine cut-off values for each triathlon discipline to achieve podium in Junior (short distance; 750 m swim, 20 km cycle and 5 km run) and U23 (standard/Olympic distance; 1.5 km swim, 40 km cycle and 10 km run) triathlon events. Additionally, we aimed to investigate which discipline has the largest relationship with overall Junior and U23 triathlon performance, and the effect of sex and time in performance trends.

Methods

We included all data from Junior and U23 official races (International Triathlon Federation; ITU) of Junior (n = 3,314 finishes) and U23 (n = 5,092 finishes) categories held from 1999 to 2018.

Results

Men were significantly faster than women in both Junior (11.13%) and U23 (12.28%) categories. Swimming and cycling times were faster in 2009-2018 than in the 1999-2008 decade for men (3.36%; 6.49%), women junior (6.50%; 7.09%), men (0.15%; 3.46%) and women U23 (1.61%; 3.31%) respectively. Cycling was the discipline with the greatest influence on overall triathlon performance in Junior and U23 categories, regardless of sex or rank position. The cut-off values for the Junior category were (men/women): swimming, 9.2/9.4 min; cycling, 31.9/38.2 min; running, 16.8/18.9 min. U23's cut-off values were (men/women): swim, 18.0/19.4 min, cycling: 63.4/70.1 min; run, 33.9/38.7 min.

Conclusion

Cycling was the discipline with the greatest influence on overall performance for both men and women in Junior and U23 categories. Moreover, swimming and cycling performances increased over the years for both sexes.

Distribution of body fat is associated with physical performance of male amateur triathlon athletes

BACKGROUND

Endurance sports are strongly associated with maximum oxygen uptake, anaerobic threshold, running economy and body fat percentage. Despite the importance for performance of the low-fat mass being a consensus in the literature, there are no data about the importance of the pattern of fat distribution. Therefore, the aim of the present study was to investigate the association between fat mass distribution with triathlon performance and physiological determinants of performance: maximal oxygen consumption (VO2max), ventilatory threshold (AT) and running economy (RE), and to verify the predictive value for performance of gynoid or android fat mass distribution.

METHODS

Thirty-nine triathletes (38.8±6.9 years, 174.8±6.5cm and 74.3±8.8kg) were evaluated for anthropometric (total body mass, fat mass, lean mass, android and gynoid fat mass) and physiological (VO2max, AT and RE) parameters. Split and overall race times were registered.

RESULTS

Overall race time relationship with gynoid fat mass (r=.529, p<.05) was classified as moderate higher than and with android fat mass (r=.416, p<.05) was classified as low. All split times and overall race time presented significant positive correlation with only total fat mass (%) (r =.329 to .574, p<.05) and with gynoid fat mass (%) (r=.359 to .529, p<.05). Overall race time can be better predicted by gynoid fat mass (ß=0.529, t=4.093, p<0.001, r2=0.28) than by android fat mass (ß =0.416, t=2.997, p=0.005, r2=0.17).

CONCLUSIONS

Fat mass distribution is associated with triathlon performance, and the gynoid fat pattern is worse for triathlon performance than the android pattern.

Structural brain differences between ultra-endurance athletes and sedentary persons

Participation in ultra-endurance events has increased in recent years and requires extreme levels of moderate to vigorous physical activity (MVPA). Moderate levels of MVPA have been associated with increased brain volume but the effects of extreme levels of MVPA on brain volume is unknown. As a result, we sought to compare the brains of those who engage in extremely high levels of MVPA with those who are sedentary using magnetic resonance imaging. We performed whole brain volumetric analyses and voxel-based morphometry on 12 ultra-endurance athletes (1078.75 ± 407.86 min of MVPA/week) and 9 sedentary persons (18.0 ± 56.9 min of MVPA/week). Whole-brain analyses revealed that those who participate in ultra-endurance training have increased grey (p< 0.0001), white (p = 0.031), and total matter volume (p < 0.0001), while regional analyses revealed that ultra-endurance athletes have smaller regional grey matter volume in the right primary sensory and motor cortex, inferior and middle frontal gyrus, and left thalamus. Future research is warranted to determine why ultra-endurance athletes have lower regional volumes in these areas despite having overall increased grey and white matter volumes.

Changes in Triathletes' Performance and Body Composition During a Specific Training Period for a Half-Ironman Race

The number of recreational athletes completing a Half-Ironman triathlon has increased exponentially in recent years. However, there is a lack of research on how to train for this kind of an event. The purpose of this study was thus to analyse triathletes’ changes in performance and body composition following a triathlon-specific training period. Fourteen male amateur triathletes completed a 7-week period of general training and a 13-week period of specific training for a Half-Ironman triathlon. Anthropometric measures and performance tests were carried out to assess the effects of the specific training program. Results showed that the pre-test value of VO_2max for cycling was inversely correlated not only with the percentage of change in cycling performance, but also with the percentage change in several variables of running performance. In swimming, inverse correlations were observed between the time of the first 800 m test and the time percentage change for this test, but not with the percentage change in the performance of other segments of the race. Moreover, the somatotype component of endomorphy and the fat mass percentage of the first anthropometry were highly correlated with the percentage change in VO_2max in the run segment. These results highlight the importance of providing individualised training, considering that the same training program had a different impact on recreational triathletes belonging to the same group. Amateur athletes with higher initial performance levels probably need a greater amount of training to achieve improved adaptation.

Sex Difference in Triathlon Performance

This brief review investigates how sex influences triathlon performance. Performance time for both Olympic distance and Ironman distance triathlons, and physiological considerations are discussed for both elite and non-elite male and female triathletes. The relative participation of female athletes in triathlon has increased over the last three decades, and currently represents 25-40% of the total field. Overall, the sex difference in both Olympic and Ironman distance triathlon performance has narrowed across the years. Sex difference differed with exercise mode and exercise duration. For non-elite Ironman triathletes, the sex difference in swimming time (≈12%) is lower than that which was evidenced for cycling (≈15%) and running (≈18%). For elite triathletes, sex difference in running performance is greater for Olympic triathlon (≈14%) than it is for Ironman distance triathlon (≈7%). Elite Ironman female triathletes have reduced the gap to their male counterparts to less than 10% for the marathon. The sex difference in triathlon performance is likely to be due to physiological (e.g., VO2max) and morphological (e.g., % body fat) factors but hormonal, psychological and societal (e.g., lower participation rate) differences should also be considered. Future studies should address the limited evidence relating sex difference in physiological characteristics such as lactate threshold, exercise economy or peak fat oxidation.

Different Predictor Variables for Women and Men in Ultra-Marathon Running-The Wellington Urban Ultramarathon 2018

Ultra-marathon races are increasing in popularity. Women are now 20% of all finishers, and this number is growing. Predictors of performance have been examined rarely for women in ultra-marathon running. This study aimed to examine the predictors of performance for women and men in the 62 km Wellington Urban Ultramarathon 2018 (WUU2K) and create an equation to predict ultra-marathon race time. For women, volume of running during training per week (km) and personal best time (PBT) in 5 km, 10 km, and half-marathon (min) were all associated with race time. For men, age, body mass index (BMI), years running, running speed during training (min/km), marathon PBT, and 5 km PBT (min) were all associated with race time. For men, ultra-marathon race time might be predicted by the following equation: (r² = 0.44, adjusted r² = 0.35, SE = 78.15, degrees of freedom (df) = 18) ultra-marathon race time (min) = −30.85 ± 0.2352 × marathon PBT + 25.37 × 5 km PBT + 17.20 × running speed of training (min/km). For women, ultra-marathon race time might be predicted by the following equation: (r² = 0.83, adjusted r² = 0.75, SE = 42.53, df = 6) ultra-marathon race time (min) = −148.83 + 3.824 × (half-marathon PBT) + 9.76 × (10 km PBT) − 6.899 × (5 km PBT). This study should help women in their preparation for performance in ultra-marathon and adds to the bulk of knowledge for ultra-marathon preparation available to men.

Structural and functional body components in athletic health and performance phenotypes

Advances in body composition assessment enable a detailed body composition analyses and the respective organization at different levels. Sports-related professionals are interested in understanding how and which body components are relevant for improving performance, prevent injury risk, and monitor athletic health. The aim of this review is to propose an integrative model that links performance, injury risk, and athletic health with body components, and to report their cross-sectional and longitudinal associations. Cross-sectional studies reveal that endurance athletes with higher fat mass (FM) show a longer race time, whereas a higher fat-free mass benefits power and strength-related tasks. Longitudinal studies indicated that increases in intracellular water, assessed through dilution techniques, were associated with power and strength improvements, independently of weight and lean-soft-tissue changes. There is evidence that athletes involved in weight-sensitive sports restrict energy intake, thus reducing energy availability (EA) and compromising bone health (Female Athlete Triad). To counteract the low EA and related negative energy balance, metabolic adaption (MA) occurs to promote energy conservation. Currently, reference values for body composition assessment using anthropometry and DXA are available for a few sports, according to sex. More research is needed to develop a functional body composition profile according to sports-specific requirements.

Revisiting the United States Army body composition standards: a receiver operating characteristic analysis

BACKGROUND

The objective for percent body fat standards in the United States Army Body Composition Program (ABCP) is to ensure soldiers maintain optimal well-being and performance under all conditions. However, conducting large-scale experiments within the United States Army to evaluate the efficacy of the thresholds is challenging.

METHODS

A receiver operating characteristic (ROC) analysis with corresponding area under the curve (AUC) was performed on body mass index (BMI) and waist circumference to determine optimal gender-specific age cohort thresholds that meet ABCP percent body fat standards in the National Health and Nutrition Examination Survey (NHANES) III. A second dataset consisting of a cohort of basic training recruits (N = 20,896 soldiers, 28% female) with BMI and waist circumference measured using a 3D body image scanner was applied to calculate what percent of basic training recruits meet the ABCP percent body fat standards. Regression models to determine the contribution of different circumference sites to the predictions of percent body fat were developed using a database compiled at the New York Obesity Research Center (N = 500).

RESULTS

Optimal BMI thresholds ranged from 23.65 kg/m² (17-21-year-old cohort) to 26.55 kg/m² (40 and over age cohort) for males and 21.75 to 24.85 kg/m² for females. The AUC values were between 0.86 and 0.92. The waist circumference thresholds ranged 81.35 to 97.55 cm for males and 77.05 to 89.35 cm for females with AUC values between 0.90 and 0.91. These BMI thresholds were exceeded by 65% of male and 74% of female basic training recruits and waist circumference thresholds were exceeded by 73% of male and 85% of female recruits. The single circumference that contributed most to prediction of body fat was waist circumference in males and mid-thigh circumference in females.

CONCLUSIONS

The ABCP percent body fat thresholds yield BMI thresholds that are below the United States Army BMI standards, especially in females which suggests the ABCP percent body fat standards may be too restrictive. The United States Army percent body fat standards could instead be matched to existing national health guidelines.

Sex differences in pacing during 'Ultraman Hawaii'

Background

To date, little is known for pacing in ultra-endurance athletes competing in a non-stop event and in a multi-stage event, and especially, about pacing in a multi-stage event with different disciplines during the stages. Therefore, the aim of the present study was to examine the effect of age, sex and calendar year on triathlon performance and variation of performance by events (i.e., swimming, cycling 1, cycling 2 and running) in ‘Ultraman Hawaii’ held between 1983 and 2015.

Methods

Within each sex, participants were grouped in quartiles (i.e., Q1, Q2, Q3 and Q4) with Q1 being the fastest (i.e., lowest overall time) and Q4 the slowest (i.e., highest overall time). To compare performance among events (i.e., swimming, cycling 1, cycling 2 and running), race time in each event was converted in z score and this value was used for further analysis.

Results

A between-within subjects ANOVA showed a large sex × event (p = 0.015, η² = 0.014) and a medium performance group × event interaction (p = 0.001, η² = 0.012). No main effect of event on performance was observed (p = 0.174, η² = 0.007). With regard to the sex × event interaction, three female performance groups (i.e., Q2, Q3 and Q4) increased race time from swimming to cycling 1, whereas only one male performance group (Q4) revealed a similar trend. From cycling 1 to cycling 2, the two slower female groups (Q3 and Q4) and the slowest male group (Q4) increased raced time. In women, the fastest group decreased (i.e., improved) race time from swimming to cycling 1 and thereafter, maintained performance, whereas in men, the fastest group decreased race time till cycling 2 and increased it in the running.

Conclusion

In summary, women pace differently than men during ‘Ultraman Hawaii’ where the fastest women decreased performance on day 1 and could then maintain on day 2 and 3, whereas the fastest men worsened performance on day 1 and 2 but improved on day 3.

Variables that influence Ironman triathlon performance - what changed in the last 35 years?

OBJECTIVE

This narrative review summarizes findings for Ironman triathlon performance and intends to determine potential predictor variables for Ironman race performance in female and male triathletes.

METHODS

A literature search was performed in PubMed using the terms "Ironman", "triathlon", and "performance". All resulting articles were searched for related citations.

RESULTS

Age, previous experience, sex, training, origin, anthropometric and physiological characteristics, pacing, and performance in split disciplines were predictive. Differences exist between the sexes for anthropometric characteristics. 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 Olympic distance triathlon (women and men), a fast personal best time in marathon (women and men), high volume and 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).

CONCLUSION

These findings may help athletes and coaches to plan an Ironman triathlon career. Age and previous experience are important to find the right point in the life of a triathlete to switch from the shorter triathlon distances to the Ironman distance. Future studies need to correlate physiological characteristics such as maximum oxygen uptake with Ironman race time to investigate their potential predictive value and to investigate socio-economic aspects in Ironman triathlon.

What predicts performance in ultra-triathlon races? - a comparison between Ironman distance triathlon and ultra-triathlon

Objective

This narrative review summarizes recent intentions to find potential predictor variables for ultra-triathlon race performance (ie, triathlon races longer than the Ironman distance covering 3.8 km swimming, 180 km cycling, and 42.195 km running). Results from studies on ultra-triathletes were compared to results on studies on Ironman triathletes.

Methods

A literature search was performed in PubMed using the terms “ultra”, “triathlon”, and “performance” for the aspects of “ultra-triathlon”, and “Ironman”, “triathlon”, and “performance” for the aspects of “Ironman triathlon”. All resulting papers were searched for related citations. Results for ultra-triathlons were compared to results for Ironman-distance triathlons to find potential differences.

Results

Athletes competing in Ironman and ultra-triathlon differed in anthropometric and training characteristics, where both Ironmen and ultra-triathletes profited from low body fat, but ultra-triathletes relied more on training volume, whereas speed during training was related to Ironman race time. The most important predictive variables for a fast race time in an ultra-triathlon from Double Iron (ie, 7.6 km swimming, 360 km cycling, and 84.4 km running) and longer were male sex, low body fat, age of 35–40 years, extensive previous experience, a fast time in cycling and running but not in swimming, and origins in Central Europe.

Conclusion

Any athlete intending to compete in an ultra-triathlon should be aware that low body fat and high training volumes are highly predictive for overall race time. Little is known about the physiological characteristics of these athletes and about female ultra-triathletes. Future studies need to investigate anthropometric and training characteristics of female ultra-triathletes and what motivates women to compete in these races. Future studies need to correlate physiological characteristics such as maximum oxygen uptake (VO_2max) with ultra-triathlon race performance in order to investigate whether these characteristics are also predictive for ultra-triathlon race performance.

The best triathletes are older in longer race distances - a comparison between Olympic, Half-Ironman and Ironman distance triathlon

The purpose of this study was (i) to determine the age of peak triathlon performance for world class athletes competing in Olympic, Half-Ironman and Ironman distance races and (ii) to investigate a potential change in the age of the annual fastest athletes across years. Data of ages and race times of all finishers in the international top races over the three distances between 2003 and 2013 were collected and the annual top ten women and men were analysed using linear, non-linear and hierarchical multivariate regression analyses. The age of peak male performance was 27.1 ± 4.9 years in the Olympic, 28.0 ± 3.8 years in the Half-Ironman and 35.1 ± 3.6 years in the Ironman distance and the age of peak male performance was higher in the Ironman compared to the Olympic (p < 0.05) and the Half-Ironman distance (p < 0.05) triathlon. The age of peak female performance was 26.6 ± 4.4 years in the Olympic, 31.6 ± 3.4 years in the Half-Ironman and 34.4 ± 4.4 years in the Ironman distance and the age of peak female performance was lower in the Olympic compared to the Half-Ironman (p < 0.05) and Ironman distance (p < 0.05) triathlon. The age of the annual top ten women and men remained unchanged over the last decade in the Half-Ironman and the Ironman distance. In the Olympic distance, however, the age of the annual top ten men decreased slightly. To summarize, the age of peak triathlon performance was higher in the longer triathlon race distances (i.e. Ironman) and the age of the annual top triathletes remained mainly stable over the last decade. With these findings top athletes competing at world class level can plan their career more precisely as they are able to determine the right time in life to switch from the shorter (i.e. Olympic distance) to the longer triathlon race distances (i.e. Half-Ironman and Ironman) in order to continuously compete in triathlon races at world class level.

Participation and performance trends by nationality in the 'English Channel Swim' from 1875 to 2013

BACKGROUND

The aim of the present study was to investigate participation and performance trends regarding the nationality of successful solo swimmers in the 'English Channel Swim'.

METHODS

The nationality and swim times for all swimmers who successfully crossed the 33.8-km 'English Channel' from 1875 to 2013 were analysed.

RESULTS

Between 1875 and 2013, the number of successful female (571, 31.4%) and male (1,246, 68.6%) solo swimmers increased exponentially; especially for female British and American swimmers and male British, US-American and Australian swimmers. Most of the swimmers were crossing the 'English Channel' from England to France and most of the competitors were from Great Britain, the United States of America, Australia and Ireland. For women, athletes from the United States of America, Australia and Great Britain achieved the fastest swim times. For men, the fastest swim times were achieved by athletes from the United States of America, Great Britain and Australia. Swim times of the annual fastest women from Great Britain and the United States of America decreased across years. For men, swim times decreased across years in the annual fastest swimmers from Australia, Great Britain, Ireland, South Africa and the United States of America. Men were swimming faster from England to France than from France to England compared to women. Swim times became faster across years for both women and men for both directions.

CONCLUSIONS

Between 1875 and 2013, the most representative nations in the 'English Channel Swim' were Great Britain, the United States of America, Australia and Ireland. The fastest swim times were achieved by athletes from the United States of America, Australia and Great Britain.

A comparison of performance of Deca Iron and Triple Deca Iron ultra-triathletes

This study intended to compare the performance of ultra-triathletes competing in a Deca Iron ultra-triathlon (i.e. 10 times 3.8 km swimming, 180 km cycling, and 42.2 km running) with the performance of athletes competing in a Triple Deca Iron ultra-triathlon (i.e. 30 times 3.8 km swimming, 180 km cycling, and 42.2 km running). Split and overall race times of six male finishers in a Deca Iron ultra-triathlon and eight male finishers in a Triple Deca Iron ultra-triathlon were analysed using multiple t-tests, linear and non-linear regression analyses, and analysis of variance. Among the 19 starters (i.e. 17 men and two women) in the Deca Iron ultra-triathlon, six men (i.e. 35.3% of all starters) finished the race. The mean swimming, cycling, running and overall race times of the six finishers across the ten days were 1:19 ± 0:09 h:min, 6:36 ± 0:19 h:min, 6:03 ± 0:47 h:min and 14:44 ± 1:17 h:min, respectively. The times of the split disciplines and overall race time increased linearly across the ten days. Total transition times did not change significantly across the days and were equals to 48 ± 8 min. Among the 22 starters (i.e. 20 men and two women) in the Triple Deca Iron ultra-triathlon, eight men (i.e. 36.4% of all starters) finished. The mean swimming, cycling, running and overall race times of the eight finishers across the 30 days were 1:11 ± 0:07 h:min, 6:19 ± 0:32 h:min, 5:34 ± 1:15 h:min and 13:44 ± 1:50 h:min, respectively. Split and overall race times showed no change across the 30 days. Total transition times showed no change across the days and were equal to 41 ± 11 min. To summarize, the daily performance decreased across the ten days for the Deca Iron ultra-triathletes (i.e. positive pacing) while it remained unchanged across the 30 days for the Triple Deca Iron ultra-triathletes (i.e. even pacing).

Sex difference in top performers from Ironman to double deca iron ultra-triathlon

This study investigated changes in performance and sex difference in top performers for ultra-triathlon races held between 1978 and 2013 from Ironman (3.8 km swim, 180 km cycle, and 42 km run) to double deca iron ultra-triathlon distance (76 km swim, 3,600 km cycle, and 844 km run). The fastest men ever were faster than the fastest women ever for split and overall race times, with the exception of the swimming split in the quintuple iron ultra-triathlon (19 km swim, 900 km cycle, and 210.1 km run). Correlation analyses showed an increase in sex difference with increasing length of race distance for swimming (r²=0.67, P=0.023), running (r²=0.77, P=0.009), and overall race time (r²=0.77, P=0.0087), but not for cycling (r²=0.26, P=0.23). For the annual top performers, split and overall race times decreased across years nonlinearly in female and male Ironman triathletes. For longer distances, cycling split times decreased linearly in male triple iron ultra-triathletes, and running split times decreased linearly in male double iron ultra-triathletes but increased linearly in female triple and quintuple iron ultra-triathletes. Overall race times increased nonlinearly in female triple and male quintuple iron ultra-triathletes. The sex difference decreased nonlinearly in swimming, running, and overall race time in Ironman triathletes but increased linearly in cycling and running and nonlinearly in overall race time in triple iron ultra-triathletes. These findings suggest that women reduced the sex difference nonlinearly in shorter ultra-triathlon distances (ie, Ironman), but for longer distances than the Ironman, the sex difference increased or remained unchanged across years. It seems very unlikely that female top performers will ever outrun male top performers in ultratriathlons. The nonlinear change in speed and sex difference in Ironman triathlon suggests that female and male Ironman triathletes have reached their limits in performance.

Swimming performances in long distance open-water events with and without wetsuit

Background

Existing literature showed improved swimming performances for swimmers wearing wetsuits competing under standardized conditions in races held in pools on short to middle distances. Data about the influence of wetsuits on swimming performances in long and ultra-long open-water swimming races are missing. It is unknown whether the benefit of wearing wetsuits is comparable in men and women. The aim of this study was to investigate the influence of wearing a wetsuit on open-water swimming performances at the 26.4 km ‘Marathon Swim in Lake Zurich’ in Lake Zurich, Switzerland, and the 3.8 km Lake Ontario Swim Team-Race (LOST-Race) in Lake Ontario, Canada.

Methods

Race times of the fastest female and male swimmers competing with and without wetsuit were compared using multi-level regression analyses and analysis of variance.

Results

In the ‘Marathon Swim’ in Lake Zurich, wearing a wetsuit had no effect on race time regarding the gender where athletes wearing a wetsuit were not faster than athletes without wetsuit. However, the ten fastest men wearing a wetsuit (410.6 ± 26.7 min) were faster (32.7%, p < 0.01) than the ten fastest women without wetsuit (544.9 ± 81.3 min). In the ‘LOST-Race’, the top ten men wearing a wetsuit (51.7 ± 2.5 min) were faster (13.2%, p < 0.01) than the top ten women wearing a wetsuit (58.5 ± 3.2 min). Additionally, the top ten men without wetsuit (52.1 ± 2.4 min) were faster (19.6%, p < 0.01) than the top ten women without wetsuit (62.3 ± 2.5 min). The top ten women wearing a wetsuit (58.5 ± 3.2 min) were faster (6.5%, p < 0.01) than top ten women without a wetsuit (62.3 ± 25 min).

Conclusions

These results suggest that wearing a wetsuit had a positive influence on swimming speed for both women and men but the benefit of the use of wetsuits seemed to depend on additional factors (i.e. race distance). Women seemed to benefit more from wearing wetsuits than men in longer open-water ultra-distance swimming races.

Performance and sex difference in ultra-triathlon performance from Ironman to Double Deca Iron ultra-triathlon between 1978 and 2013

It was assumed that women would be able to outperform men in ultra-marathon running. The present study investigated the sex difference in performance for all ultra-triathlon distances from the Ironman distance (i.e. 3.8 km swimming, 180 km cycling and 42 km running) in the ‘Ironman Hawaii’ to the Double Deca Iron ultra-triathlon distance (i.e. 76 km swimming, 3,600 km cycling and 840 km running) between 1978 and 2013. The changes in performance and in the sex difference in performance for the annual three fastest finishers were analysed using linear, non-linear and multi-variate regression analyses from 46,123 athletes (i.e. 9,802 women and 46,123 men). Women accounted for 11.9 ± 5.8% of the total field and their percentage was highest in ‘Ironman Hawaii’ (22.1%) and lowest in Deca Iron ultra-triathlon (6.5%). In ‘Ironman Hawaii’, the sex difference decreased non-linearly in swimming, cycling, running and overall race time. In Double Iron ultra-triathlon, the sex difference increased non-linearly in overall race time. In Triple Iron ultra-triathlon, the sex difference increased non-linearly in cycling and overall race time but linearly in running. For the three fastest finishers ever, the sex difference in performance showed no change with increasing race distance with the exception for the swimming split where the sex difference increased with increasing race distance (r² = 0.93, P = 0.001). The sex differences for the three fastest finishers ever for swimming, cycling, running and overall race times for all distances from Ironman to Deca Iron ultra-triathlon were 27.0 ± 17.8%, 24.3 ± 9.9%, 24.5 ± 11.0%, and 24.0 ± 6.7%, respectively. To summarize, these findings showed that women reduced the sex difference in the shorter ultra-triathlon distances (i.e. Ironman distance) but extended the sex difference in longer distances (i.e. Double and Triple Iron ultra-triathlon). It seems very unlikely that women will ever outperform men in ultra-triathlons from Ironman to Double Iron ultra-triathlon.

33 Ironman triathlons in 33 days-a case study

This case report presents the performance of an athlete who completed for the first time in history the total distance of 33 Ironman triathlons within 33 consecutive days. The athlete finished the total distance of 7,458 km (i.e. 125 km swimming, 5,940 km cycling and 1,393 km running) within a total time of 410 h and a mean time of 12 h 27 min per Ironman distance. During the 33 days, the athlete became slower in swimming (r² = 0.27, p = 0.0019), transition time 1 (r² = 0.66, p < 0.001), and transition time 2 (r² = 0.48, p < 0.0001). However, in cycling (r² = 0.07, p = 0.13), running (r² = 0.04, p = 0.25) and overall race time (r² = 0.10, p = 0.069), the athlete was able to maintain his performance during the 33 days. The coefficients of variation (CV) for the split times in swimming, cycling, running and overall race times were very low (i.e. 2.7%, 3.2%, 4.7%, and 2.7%, respectively) whereas the CV for transition times 1 and 2 were considerably higher (i.e. 25.5% and 55.5%, respectively). During the 33 days, body mass decreased from 83.0 kg to 80.5 kg (r² = 0.55, p < 0.0001). Plasma [Na⁺] remained within the reference range, creatine kinase, blood glucose and liver enzymes were minimally elevated above the reference range after four of five stages where blood analyses were performed. This case report shows that this athlete finished 33 Ironman triathlons within 33 consecutive days with minor variations over time (i.e. even pacing) in both split times and overall race times. This performance was most probably due to the high experience of the athlete, his pacing strategy and the stable environmental conditions.

Sex and age-related differences in performance in a 24-hour ultra-cycling draft-legal event - a cross-sectional data analysis

Background

The purpose of this study was to examine the sex and age-related differences in performance in a draft-legal ultra-cycling event.

Methods

Age-related changes in performance across years were investigated in the 24-hour draft-legal cycling event held in Schötz, Switzerland, between 2000 and 2011 using multi-level regression analyses including age, repeated participation and environmental temperatures as co-variables.

Results

For all finishers, the age of peak cycling performance decreased significantly (β = −0.273, p = 0.036) from 38 ± 10 to 35 ± 6 years in females but remained unchanged (β = −0.035, p = 0.906) at 41.0 ± 10.3 years in males. For the annual fastest females and males, the age of peak cycling performance remained unchanged at 37.3 ± 8.5 and 38.3 ± 5.4 years, respectively. For all female and male finishers, males improved significantly (β = 7.010, p = 0.006) the cycling distance from 497.8 ± 219.6 km to 546.7 ± 205.0 km whereas females (β = −0.085, p = 0.987) showed an unchanged performance of 593.7 ± 132.3 km. The mean cycling distance achieved by the male winners of 960.5 ± 51.9 km was significantly (p < 0.001) greater than the distance covered by the female winners with 769.7 ± 65.7 km but was not different between the sexes (p > 0.05). The sex difference in performance for the annual winners of 19.7 ± 7.8% remained unchanged across years (p > 0.05). The achieved cycling distance decreased in a curvilinear manner with advancing age. There was a significant age effect (F = 28.4, p < 0.0001) for cycling performance where the fastest cyclists were in age group 35–39 years.

Conclusion

In this 24-h cycling draft-legal event, performance in females remained unchanged while their age of peak cycling performance decreased and performance in males improved while their age of peak cycling performance remained unchanged. The annual fastest females and males were 37.3 ± 8.5 and 38.3 ± 5.4 years old, respectively. The sex difference for the fastest finishers was ~20%. It seems that women were not able to profit from drafting to improve their ultra-cycling performance.

Trends in Triathlon Performance: Effects of Sex and Age

The influences of sex and age upon endurance performance have previously been documented for both running and swimming. A number of recent studies have investigated how sex and age influence triathlon performance, a sport that combines three disciplines (swimming, cycling and running), with competitions commonly lasting between 2 (short distance: 1.5-km swim, 40-km cycle and 10-km run) and 8 h (Ironman distance: 3.8-km swim,180-km cycle and 42-km run) for elite triathletes. Age and sex influences upon performance have also been investigated for ultra-triathlons, with distances corresponding to several Ironman distances and lasting several days, and for off-road triathlons combining swimming, mountain biking and trail running. Triathlon represents an intriguing alternative model for analysing the effects of age and sex upon endurance and ultra-endurance ([6 h) performance because sex differences and age-related declines in performance can be analysed in the same individuals across the three separate disciplines. The relative participation of both females and masters athletes (age[40 years) in triathlon has increased consistently over the past 25 years. Sex differences in triathlon performance are also known to differ between the modes of locomotion adopted (swimming, cycling or running) for both elite and non-elite triathletes. Generally, time differences between sexes in swimming have been shown to be smaller on average than during cycling and running. Both physiological and morphological factors contribute to explaining these findings. Performance density (i.e. the time difference between the winner and tenth-placed competitor) has progressively improved (time differences have decreased) for international races over the past two decades for both males and females, with performance density now very similar for both sexes. For age-group triathletes, sex differences in total triathlon performance time increases with age. However,the possible difference in age-related changes in the physiological determinants of endurance and ultra-endurance performances between males and females needs further investigation. Non-physiological factors such as low rates of participation of older female triathletes may also contribute to the greater age-related decline in triathlon performance shown by females. Total triathlon performance has been shown to decrease in a curvilinear manner with advancing age. However, when triathlon performanceis broken down into its three disciplines, there is a smaller age-related decline in cycling performance than in running and swimming performances. Age-associated changes in triathlon performance are also related to the total duration of triathlon races. The magnitude of the declines in cycling and running performances with advancing age for short triathlons are less pronounced than for longer Ironman distance races. Triathlon distance is also important when considering how age affects the rate of the decline in performance. Off-road triathlon performances display greater decrements with age than road-based triathlons, suggesting that the type of discipline (road vs. mountain bike cycling and road vs. trail running) is an important factor in age-associated changes in triathlon performance.Finally, masters triathletes have shown relative improvements in their performances across the three triathlon disciplines and total triathlon event times during Ironman races over the past three decades. This raises an important issue as to whether older male and female triathletes have yet reached their performance limits during Ironman triathlons

Nation related participation and performance trends in 'Ironman Hawaii' from 1985 to 2012

BACKGROUND

This study examined participation and performance trends in 'Ironman Hawaii' regarding the nationality of the finishers.

METHODS

Associations between nationalities and race times of 39,706 finishers originating from 124 countries in the 'Ironman Hawaii' from 1985 to 2012 were analyzed using single and multi-level regression analysis.

RESULTS

Most of the finishers originated from the United States of America (47.5%) followed by athletes from Germany (11.7%), Japan (7.9%), Australia (6.7%), Canada (5.2%), Switzerland (2.9%), France (2.3%), Great Britain (2.0%), New Zealand (1.9%), and Austria (1.5%). German women showed the fastest increase in finishers (r(2) = 0.83, p < 0.0001), followed by Australia (r(2) = 0.78, p < 0.0001), Canada (r(2) = 0.78, p < 0.0001) and the USA (r(2) = 0.69, p < 0.0001). Japanese women showed no change in the number of finishers (r(2) = 0.01, p > 0.05). For men, athletes from France showed the steepest increase (r(2) = 0.85, p < 0.0001), followed by Austria (r(2) = 0.68, p < 0.0001), Australia (r(2) = 0.67, p < 0.0001), Brazil (r(2) = 0.60, p < 0.0001), Great Britain (r(2) = 0.46, p < 0.0001), Germany (r(2) = 0.26, p < 0.0001), the United States of America (r(2) = 0.21, p = 0.013) and Switzerland (r(2) = 0.14, p = 0.0044). The number of Japanese men decreased (r(2) = 0.35, p = 0.0009). The number of men from Canada (r(2) = 0.02, p > 0.05) and New Zealand (r(2) = 0.02, p > 0.05) remained unchanged. Regarding female performance, the largest improvements were achieved by Japanese women (17.3%). The fastest race times in 2012 were achieved by US-American women. Women from Japan, Canada, Germany, Australia, and the United States of America improved race times. For men, the largest improvements were achieved by athletes originating from Brazil (20.9%) whereas the fastest race times in 2012 were achieved by athletes from Germany. Race times for athletes originating from Brazil, Austria, Great Britain, Switzerland, Germany, Australia, Canada, Japan, New Zealand and France decreased. Race times in athletes originating from Australia and the United States of America showed no significant changes. Regarding the fastest race times ever, the fastest women originated from the United States (546 ± 7 min) followed by Great Britain (555 ± 15 min) and Switzerland (558 ± 8 min). In men, the fastest finishers originated from the United States (494 ± 7 min), Germany (496 ± 6 min) and Australia (497 ± 5 min).

CONCLUSIONS

The 'Ironman Hawaii' has been dominated by women and men from the United States of America in participation and performance.

Analysis of sex differences in open-water ultra-distance swimming performances in the FINA World Cup races in 5 km, 10 km and 25 km from 2000 to 2012

BACKGROUND

The present study investigated the changes in swimming speeds and sex differences for elite male and female swimmers competing in 5 km, 10 km and 25 km open-water FINA World Cup races held between 2000 and 2012.

METHODS

The changes in swimming speeds and sex differences across years were analysed using linear, non-linear, and multi-level regression analyses for the annual fastest and the annual ten fastest competitors.

RESULTS

For the annual fastest, swimming speed remained stable for men and women in 5 km (5.50 ± 0.21 and 5.08 ± 0.19 km/h, respectively), in 10 km (5.38 ± 0.21 and 5.05 ± 0.26 km/h, respectively) and in 25 km (5.03 ± 0.32 and 4.58 ± 0.27 km/h, respectively). In the annual ten fastest, swimming speed remained constant in 5 km in women (5.02 ± 0.19 km/h) but decreased significantly and linearly in men from 5.42 ± 0.03 km/h to 5.39 ± 0.02 km/h. In 10 km, swimming speed increased significantly and linearly in women from 4.75 ± 0.01 km/h to 5.74 ± 0.01 km/h but remained stable in men at 5.36 ± 0.21 km/h. In 25 km, swimming speed decreased significantly and linearly in women from 4.60 ± 0.06 km/h to 4.44 ± 0.08 km/h but remained unchanged at 4.93 ± 0.34 km/h in men. For the annual fastest, the sex difference in swimming speed remained unchanged in 5 km (7.6 ± 3.0%), 10 km (6.1 ± 2.5%) and 25 km (9.0 ± 3.7%). For the annual ten fastest, the sex difference remained stable in 5 km at 7.6 ± 0.6%, decreased significantly and linearly in 10 km from 7.7 ± 0.7% to 1.2 ± 0.3% and increased significantly and linearly from 4.7 ± 1.4% to 9.6 ± 1.5% in 25 km.

CONCLUSIONS

To summarize, elite female open-water ultra-distance swimmers improved in 10 km but impaired in 25 km leading to a linear decrease in sex difference in 10 km and a linear increase in sex difference in 25 km. The linear changes in sex differences suggest that women will improve in the near future in 10 km, but not in 25 km.

Performance in Olympic triathlon: changes in performance of elite female and male triathletes in the ITU World Triathlon Series from 2009 to 2012

This study investigated the changes in performance and sex difference in performance of the world best triathletes at the ITU (International Triathlon Union) World Triathlon Series (i.e. 1.5 km swimming, 40 km cycling and 10 km running) during the 2009-2012 period including the 2012 London Olympic Games. Changes in overall race times, split times and sex difference in performance of the top ten women and men of each race were analyzed using single and multi-level regression analyses. Swimming and running split times remained unchanged whereas cycling split times (ß = 0.003, P < 0.001) and overall race times (ß = 0.003, P < 0.001) increased significantly for both women and men. The sex difference in performance remained unchanged for swimming and cycling but decreased for running (ß = -0.001, P = 0.001) from 14.9 ± 2.7% to 13.2 ± 2.6% and for overall race time (ß = -0.001, P = 0.006) from 11.9 ± 1.2% to 11.4 ± 1.4%. The sex difference in running (14.3 ± 2.4%) was greater (P < 0.001) compared to swimming (9.1 ± 5.1%) and cycling (9.5 ± 2.7%). These findings suggest that (i) the world’s best female short-distance triathletes reduced the gap with male athletes in running and total performance at short distance triathlon with drafting during the 2009-2012 period and (ii) the sex difference in running was greater compared to swimming and cycling. Further studies should investigate the reasons why the sex difference in performance was greater in running compared to swimming and cycling in elite short-distance triathletes.

The age of peak performance in Ironman triathlon: a cross-sectional and longitudinal data analysis

BACKGROUND

The aims of the present study were, firstly, to investigate in a cross-sectional analysis the age of peak Ironman performance within one calendar year in all qualifiers for Ironman Hawaii and Ironman Hawaii; secondly, to determine in a longitudinal analysis on a qualifier for Ironman Hawaii whether the age of peak Ironman performance and Ironman performance itself change across years; and thirdly, to determine the gender difference in performance.

METHODS

In a cross-sectional analysis, the age of the top ten finishers for all qualifier races for Ironman Hawaii and Ironman Hawaii was determined in 2010. For a longitudinal analysis, the age and the performance of the annual top ten female and male finishers in a qualifier for Ironman Hawaii was determined in Ironman Switzerland between 1995 and 2010.

RESULTS

In 19 of the 20 analyzed triathlons held in 2010, there was no difference in the age of peak Ironman performance between women and men (p > 0.05). The only difference in the age of peak Ironman performance between genders was in 'Ironman Canada' where men were older than women (p = 0.023). For all 20 races, the age of peak Ironman performance was 32.2 ± 1.5 years for men and 33.0 ± 1.6 years for women (p > 0.05). In Ironman Switzerland, there was no difference in the age of peak Ironman performance between genders for top ten women and men from 1995 to 2010 (F = 0.06, p = 0.8). The mean age of top ten women and men was 31.4 ± 1.7 and 31.5 ± 1.7 years (Cohen's d = 0.06), respectively. The gender difference in performance in the three disciplines and for overall race time decreased significantly across years. Men and women improved overall race times by approximately 1.2 and 4.2 min/year, respectively.

CONCLUSIONS

Women and men peak at a similar age of 32-33 years in an Ironman triathlon with no gender difference. In a qualifier for Ironman Hawaii, the age of peak Ironman performance remained unchanged across years. In contrast, gender differences in performance in Ironman Switzerland decreased during the studied period, suggesting that elite female Ironman triathletes might still narrow the gender gap in the future.

Finisher and performance trends in female and male mountain ultramarathoners by age group

Background

This study examined changes according to age group in the number of finishers and running times for athletes in female and male mountain ultramarathoners competing in the 78 km Swiss Alpine Marathon, the largest mountain ultramarathon in Europe and held in high alpine terrain.

Methods

The association between age and performance was investigated using analysis of variance and both single and multilevel regression analyses.

Results

Between 1998 and 2011, a total of 1,781 women and 12,198 men finished the Swiss Alpine Marathon. The number of female finishers increased (r² = 0.64, P = 0.001), whereas the number of male finishers (r² = 0.18, P = 0.15) showed no change. The annual top ten men became older and slower, whereas the annual top ten women became older but not slower. Regarding the number of finishers in the age groups, the number of female finishers decreased in the age group 18–24 years, whereas the number of finishers increased in the age groups 30–34, 40–44, 45–49, 50–54, 55–59, 60–64, and 70–74 years. In the age groups 25–29 and 35–39 years, the number of finishers showed no changes across the years. In the age group 70–74 years, the increase in number of finishers was linear. For all other age groups, the increase was exponential. For men, the number of finishers decreased in the age groups 18–24, 25–29, 30–34, and 35–39 years. In the age groups 40–44, 45–49, 50–54, 55–59, 60–64, 70–74, and 75–79 years, the number of finishers increased. In the age group 40–44 years, the increase was linear. For all other age groups, the increase was exponential. Female finishers in the age group 40–44 years became faster over time. For men, finishers in the age groups 18–24, 25–29, 30–34, 40–44, and 45–49 years became slower.

Conclusion

The number of women older than 30 years and men older than 40 years increased in the Swiss Alpine Marathon. Performance improved in women aged 40–44 years but decreased in male runners aged 18–49 years.

Participation and performance trends in 'Ultraman Hawaii' from 1983 to 2012

BACKGROUND

Participation and performance trends have been investigated in a single stage Ironman triathlon such as the 'Ironman Hawaii,' but not for a multi-stage ultra-triathlon such as the 'Ultraman Hawaii' covering a total distance of 515 km. The aims of this study were to analyze (1) changes in participation and performance, (2) sex-related differences in overall and split time performances, and (3) the age of peak performance in Ultraman Hawaii.

METHODS

Age and race times including split times for 98 women and 570 men who successfully finished Ultraman Hawaii (day 1 with 10-km swimming and 145-km cycling, day 2 with 276-km cycling, and day 3 with 84-km running) between 1983 and 2012 were analyzed. Changes in variables over time of annual winners and annual top three women and men were investigated using simple linear regression analyses.

RESULTS

The number of female finishers increased (r2 = 0.26, p < 0.01), while the number of male finishers remained stable (r2 = 0.03, p > 0.05). Overall race times decreased for both female (r2 = 0.28, p < 0.01) and male (r2 = 0.14, p < 0.05) winners and for both the annual top three women (r2 = 0.36, p < 0.01) and men (r2 = 0.14, p = 0.02). The sex difference in performance decreased over time from 24.3% to 11.5% (r2 = 0.39, p < 0.01). For the split disciplines, the time performance in cycling on day 1 (r2 = 0.20, p < 0.01) and day 2 decreased significantly for men (r2 = 0.41, p < 0.01) but for women only on day 2 (r2 = 0.45, p < 0.01). Split times showed no changes in swimming and running. The age of the annual winners increased from 28 to 47 years for men (r2 = 0.35, p < 0.01) while it remained stable at 32 ± 6 years for women (r2 < 0.01, p > 0.05). The age of the annual top three finishers increased from 33 ± 6 years to 48 ± 3 years for men (p < 0.01) and from 29 ± 7 years to 49 ± 2 years for women (p < 0.01).

CONCLUSIONS

Both the annual top three women and men improved performance in Ultraman Hawaii during the 1983-2012 period although the age of the annual top three women and men increased. The sex-related difference in performance decreased over time to reach approximately 12% similar to the reports of other endurance and ultra-endurance events. Further investigations are required to better understand the limiting factors of the multi-activities ultra-endurance events taking place over several days.

Gender difference and age-related changes in performance at the long-distance duathlon

The differences in gender- and the age-related changes in triathlon (i.e., swimming, cycling, and running) performances have been previously investigated, but data are missing for duathlon (i.e., running, cycling, and running). We investigated the participation and performance trends and the gender difference and the age-related decline in performance, at the "Powerman Zofingen" long-distance duathlon (10-km run, 150-km cycle, and 30-km run) from 2002 to 2011. During this period, there were 2,236 finishers (272 women and 1,964 men, respectively). Linear regression analyses for the 3 split times, and the total event time, demonstrated that running and cycling times were fairly stable during the last decade for both male and female elite duathletes. The top 10 overall gender differences in times were 16 ± 2, 17 ± 3, 15 ± 3, and 16 ± 5%, for the 10-km run, 150-km cycle, 30-km run and the overall race time, respectively. There was a significant (p < 0.001) age effect for each discipline and for the total race time. The fastest overall race times were achieved between the 25- and 39-year-olds. Female gender and increasing age were associated with increased performance times when additionally controlled for environmental temperatures and race year. There was only a marginal time period effect ranging between 1.3% (first run) and 9.8% (bike split) with 3.3% for overall race time. In accordance with previous observations in triathlons, the age-related decline in the duathlon performance was more pronounced in running than in cycling. Athletes and coaches can use these findings to plan the career in long-distance duathletes with the age of peak performance between 25 and 39 years for both women and men.

Age and gender difference in non-drafting ultra-endurance cycling performance - the 'Swiss Cycling Marathon'

Background

In recent years, there was an increased interest in investigating the gender difference in performance and the age of peak performance in ultra-endurance performances such as ultra-triathlon, ultra-running, and ultra-swimming, but not in ultra-cycling. The aim of the present study was to analyze the gender difference in ultra-cycling performance and the age of peak ultra-cycling performance in the 720-km ‘Swiss Cycling Marathon’, the largest European qualifier for the ‘Race Across America’.

Methods

Changes in the cycling speed and age of 985 finishers including 38 women and 947 men competing in the Swiss Cycling Marathon from 2001 to 2012 covering a distance of 720 km with a change of altitude of 4,993 m were analyzed using linear regression.

Results

The gender difference in performance was 13.6% for the fastest cyclists ever, 13.9% ± 0.5% for the three fastest cyclists ever and 19.1% ± 3.7% for the ten fastest cyclists ever. The gender difference in performance for the annual top three women and men decreased from 35.0% ± 9.5% in 2001 to 20.4% ± 7.7% in 2012 (r² = 0.72, p = 0.01). The annual top three women improved cycling speed from 20.3 ± 3.1 km h⁻¹ in 2003 to 24.8 ± 2.4 km h⁻¹ in 2012 (r² = 0.79, p < 0.01). The cycling speed of the annual top three men remained unchanged at 30.2 ± 0.6 km h⁻¹ (p > 0.05). The age of peak performance for the ten fastest finishers ever was 35.9 ± 9.6 years for men and 38.7 ± 7.8 years for women, respectively (p = 0.47).

Conclusions

The gender difference in ultra-cycling performance decreased over the 2001 to 2012 period in the 720-km Swiss Cycling Marathon for the annual top three cyclists and reached approximately 14%. Both women and men achieved peak performance at the age of approximately 36 to 39 years. Women might close the gender gap in ultra-endurance cycling in longer cycling distances. Future studies need to investigate the gender difference in performance in the Race Across America, the longest nonstop and non-drafting ultra-cycling race in the world.

Participation and performance trends in ultra-endurance running races under extreme conditions - 'Spartathlon' versus 'Badwater'

BACKGROUND

The aim of the present study was to compare the trends in participation, performance and age of finishers in 'Badwater' and 'Spartathlon' as two of the toughest ultramarathons in the world of more than 200 km of distance.

METHODS

Running speed and age of male and female finishers in Badwater and Spartathlon were analyzed from 2000 to 2012. Age of peak performance and sex difference in running speed were investigated during the studied period.

RESULTS

The number of female and male finishes increased in Badwater and Spartathlon. Women accounted on average for 21.5% ± 6.9% in Badwater and 10.8% ± 2.3% in Spartathlon. There was a significant increase in female participation in Badwater from 18.4% to 19.1% (p < 0.01) and in Spartathlon from 11.9% to 12.5% (p = 0.02). In men, the age of finishers was higher in Badwater (46.5 ± 9.3 years) compared to Spartathlon (44.8 ± 8.2 years) (p < 0.01). The age of female finishers of both races was similar with 43.0 ± 7.5 years in Badwater and 44.5 ± 7.8 years in Spartathlon (p > 0.05). Over the years, the age of the annual five fastest men decreased in Badwater from 42.4 ± 4.2 to 39.8 ± 5.7 years (p < 0.05). For women, the age remained unchanged at 42.3 ± 3.8 years in Badwater (p > 0.05). In Spartathlon, the age was unchanged at 39.7 ± 2.4 years for men and 44.6 ± 3.2 years for women (p > 0.05). In Badwater, women and men became faster over the years. The running speed increased from 7.9 ± 0.7 to 8.7 ± 0.6 km/h (p < 0.01) in men and from 5.4 ± 1.1 to 6.6 ± 0.5 km/h (p < 0.01) in women. The sex difference in running speed remained unchanged at 19.8% ± 4.8% (p > 0.05). In Spartathlon, the running speed was stable over time at 10.8 ± 0.7 km/h for men and 8.7 ± 0.5 km/h for women (p > 0.05). The sex difference remained unchanged at 19.6% ± 2.5% (p > 0.05).

CONCLUSIONS

These results suggest that for both Badwater and Spartathlon, (a) female participation increased, (b) the fastest finishers were approximately 40 to 45 years, and (c) the sex difference was at approximately 20%. Women will not outrun men in both Badwater and Spartathlon races. Master ultramarathoners can achieve a high level of performance in ultramarathons greater than 200 km under extreme conditions.

Sex difference in Double Iron ultra-triathlon performance

BACKGROUND

The present study examined the sex difference in swimming (7.8 km), cycling (360 km), running (84 km), and overall race times for Double Iron ultra-triathletes.

METHODS

Sex differences in split times and overall race times of 1,591 men and 155 women finishing a Double Iron ultra-triathlon between 1985 and 2012 were analyzed.

RESULTS

The annual number of finishes increased linearly for women and exponentially for men. Men achieved race times of 1,716 ± 243 min compared to 1,834 ± 261 min for women and were 118 ± 18 min (6.9%) faster (p < 0.01). Men finished swimming within 156 ± 63 min compared to women with 163 ± 31 min and were 8 ± 32 min (5.1 ± 5.0%) faster (p < 0.01). For cycling, men (852 ± 196 min) were 71 ± 70 min (8.3 ± 3.5%) faster than women (923 ± 126 min) (p < 0.01). Men completed the run split within 710 ± 145 min compared to 739 ± 150 min for women and were 30 ± 5 min (4.2 ± 3.4%) faster (p = 0.03). The annual three fastest men improved race time from 1,650 ± 114 min in 1985 to 1,339 ± 33 min in 2012 (p < 0.01). Overall race time for women remained unchanged at 1,593 ± 173 min with an unchanged sex difference of 27.1 ± 8.6%. In swimming, the split times for the annual three fastest women (148 ± 14 min) and men (127 ± 20 min) remained unchanged with an unchanged sex difference of 26.8 ± 13.5%. In cycling, the annual three fastest men improved the split time from 826 ± 60 min to 666 ± 18 min (p = 0.02). For women, the split time in cycling remained unchanged at 844 ± 54 min with an unchanged sex difference of 25.2 ± 7.3%. In running, the annual fastest three men improved split times from 649 ± 77 min to 532 ± 16 min (p < 0.01). For women, however, the split times remained unchanged at 657 ± 70 min with a stable sex difference of 32.4 ± 12.5%.

CONCLUSIONS

To summarize, the present findings showed that men were faster than women in Double Iron ultra-triathlon, men improved overall race times, cycling and running split times, and the sex difference remained unchanged across years for overall race time and split times. The sex differences for overall race times and split times were higher than reported for Ironman triathlon.

Sex Differences in Ultra-Triathlon Performance at Increasing Race Distance

It has been argued that women should be able to outrun men in ultra-endurance distances. The present study investigated the sex difference in overall race times and split times between elite female and male Ironman Triathletes competing in Ironman Hawaii (3.8 km swimming, 180 km cycling, and 42.195 km running) and Double Iron ultra-triathletes (7.6 km swimming, 360 km cycling, and 84.4 km running). Data from 20,638 athletes, including 5,163 women and 15,475 men competing in Ironman Hawaii and from 143 women and 1,252 men competing in Double Iron ultra-triathlon races held worldwide between 1999 and 2011 were analyzed. In Ironman Hawaii, the sex difference in performance of the top three athletes remained unchanged during the period studied for overall race time. For Double Iron ultra-triathletes, the sex difference for the top three athletes remained unchanged for overall race time. Sex differences increased as endurance race distances increased and showed no changes over time. It appears that women are unlikely to close the gap in ultra-endurance performance with men in ultra-triathlons in the near future. Physiological (e.g., maximum oxygen uptake) and anthropometric characteristics (e.g., skeletal muscle mass) may set biological limits for women.

Estimation bias: body mass and body height in endurance athletes

Body Mass Index is associated with endurance performance in athletes. Reported and measured values of body mass and body height in 1,618 endurance athletes (1,358 men, 260 women) showed that men and women both underestimated their body mass and overestimated their body height, leading to an underestimation of Body Mass Index. There were age and sex differences in estimates of height and weight; for both women and men, underestimation of Body Mass Index amounted to 0.4 kg/m2. Master athletes tended to underestimate their body mass and overestimate their body height thus leading to significant differences between estimated and measured Body Mass Index. However, the magnitude of underestimation of BMI probably has a negligible influence on performance predictions. The differences between measured and estimated body mass, height, and BMI were within the range of normal daily variation, and for body height even within the precision of the measurement (0.5 cm).

A comparison of participation and performance in age-group finishers competing in and qualifying for Ironman Hawaii

Background

Athletes intending to compete in Ironman Hawaii need to qualify in an age-group based qualification system. We compared participation and top ten performances of athletes in various age groups between Ironman Hawaii and its qualifier races.

Methods

Finishes in Ironman Hawaii and in its qualifier races in 2010 were analyzed in terms of performance, age, and sex. Athletes were categorized into age groups from 18–24 to 75–79 years and split and race times were determined for the top ten athletes in each age group.

Results

A higher proportion of athletes aged 25–49 years finished in the qualifier races than in Ironman Hawaii. In athletes aged 18–24 and 50–79 years, the percentage of finishes was higher in Ironman Hawaii than in the qualifier races. For women, the fastest race times were slower in Ironman Hawaii than in the qualifier races for those aged 18–24 (P<0.001), 25–29 (P<0.05), and 60–64 (P<0.05) years. Swim split times were slower in Ironman Hawaii than in the qualifier races for all age groups (P<0.05). Cycling times were slower in Ironman Hawaii for 18–24, 25–29, 40–44, 50–54, and 60–64 years (P<0.05) in age groups. For men, finishers aged 18–24 (P<0.001), 40–44 (P<0.001), 50–54 (P<0.01), 55–59 (P<0.001), 60–64 (P<0.01), and 65–69 (P<0.001) years were slower in Ironman Hawaii than in the qualifier races. Swim split times were slower in Ironman Hawaii than in the qualifier races for all age groups (P<0.05). Cycling times were slower in Ironman Hawaii for those aged 18–24 and those aged 40 years and older (P<0.05).

Conclusion

There are differences in terms of participation and performance for athletes in different age groups between Ironman Hawaii and its qualifier races. Triathletes aged 25–49 years and men generally were underrepresented in Ironman Hawaii compared with in its Ironman qualifier races. These athletes may have had less chance to qualify for Ironman Hawaii than female athletes or younger (<25 years) and older (>50 years) athletes.

Sex difference in race performance and age of peak performance in the Ironman Triathlon World Championship from 1983 to 2012

Background

The fastest Ironman race times in ‘Ironman Hawaii’ were achieved in very recent years. This study investigated the change in sex difference in both race performance and the age of peak performance across years in the top ten athletes for split disciplines and overall race time in the ‘Ironman Hawaii’ between 1983 and 2012.

Methods

Changes in split times, overall race times, and age of athletes across years for the top ten overall and the fastest swimmers, cyclists, and runners were investigated using regression analyses and analyses of variance.

Results

Between 1983 and 2012, the overall top ten men and women finishers improved their swimming (only men), cycling, running, and overall race times. The sex difference in overall race time decreased significantly (p = 0.01) from 15.2% to 11.3% across time. For the split disciplines, the sex difference remained unchanged (p > 0.05) for swimming (12.5 ± 3.7%) and cycling (12.5 ± 2.7%) but decreased for running from 13.5 ± 8.1% to 7.3 ± 2.9% (p = 0.03). The time performance of the top ten swimmers remained stable (p > 0.05), while those of the top ten cyclists and top ten runners improved (p < 0.01). The sex difference in performance remained unchanged (p > 0.05) in swimming (8.0 ± 2.4%), cycling (12.7 ± 1.8%), and running (15.2 ± 3.0%). Between 1983 and 2012, the age of the overall top ten finishers and the fastest swimmers, cyclists, and runners increased across years for both women and men (p < 0.01).

Conclusions

To summarize, for the overall top ten finishers, the sex difference decreased across years for overall race time and running, but not for swimming and cycling. For the top ten per discipline, the sex difference in performance remained unchanged. The athletes improved their performances across years although the age of peak performance increased.

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

Background

The age of peak performance in elite endurance athletes has been investigated for elite marathoners, but not for elite Ironman triathletes. The aim of this study was to analyze the age of peak performance in swimming (3.8 km), cycling (180 km), running (42 km), and overall race time for elite female and male Ironman triathletes competing in Ironman Switzerland, a qualifier for the Ironman world championship, known as the Ironman Hawaii.

Methods

The age of the annual top ten overall swimmers, cyclists, runners, and annual overall finishers for both male and female elite triathletes and their corresponding split and overall race times at the Ironman Switzerland were analyzed between 1995 and 2011.

Results

The mean age of the elite Ironman triathletes was 33 ± 3 years for men and 34 ± 4 years for women. For women, the age of peak performance was not significantly different between the three disciplines (P > 0.05), while for men, the best swimmers (29 ± 3 years) were significantly (P < 0.05) younger than the best runners (35 ± 5 years). During the study period, the age of peak performance remained unchanged for men at 31 ± 3 years (P > 0.05), but increased for women from 30 ± 4 years in 1995 to 36 ± 5 years in 2011 (P < 0.01).

Conclusion

Although both women and men improved their overall race times during the 1995–2011 period, the age of peak performance was similar between women and men in the three disciplines and in overall race time. Future studies need to examine the change in age of peak performance across years in the Ironman Hawaii world championship event.

Participation and Performance Trends in Triple Iron Ultra-triathlon - a Cross-sectional and Longitudinal Data Analysis

Purpose

The aims of the present study were to investigate (i) the changes in participation and performance and (ii) the gender difference in Triple Iron ultra-triathlon (11.4 km swimming, 540 km cycling and 126.6 km running) across years from 1988 to 2011.

Methods

For the cross-sectional data analysis, the association between with overall race times and split times was investigated using simple linear regression analyses and analysis of variance. For the longitudinal data analysis, the changes in race times for the five men and women with the highest number of participations were analysed using simple linear regression analyses.

Results

During the studied period, the number of finishers were 824 (71.4%) for men and 80 (78.4%) for women. Participation increased for men (r²=0.27, P<0.01) while it remained stable for women (8%). Total race times were 2,146 ± 127.3 min for men and 2,615 ± 327.2 min for women (P<0.001). Total race time decreased for men (r²=0.17; P=0.043), while it increased for women (r²=0.49; P=0.001) across years. The gender difference in overall race time for winners increased from 10% in 1992 to 42% in 2011 (r²=0.63; P<0.001). The longitudinal analysis of the five women and five men with the highest number of participations showed that performance decreased in one female (r²=0.45; P=0.01). The four other women as well as all five men showed no change in overall race times across years.

Conclusions

Participation increased and performance improved for male Triple Iron ultra-triathletes while participation remained unchanged and performance decreased for females between 1988 and 2011. The reasons for the increase of the gap between female and male Triple Iron ultra-triathletes need further investigations.

Is body fat a predictor of race time in female long-distance inline skaters?

PURPOSE

The aim of this study was to evaluate predictor variables of race time in female ultra-endurance inliners in the longest inline race in Europe.

METHODS

We investigated the association between anthropometric and training characteristics and race time for 16 female ultra-endurance inline skaters, at the longest inline marathon in Europe, the 'Inline One-eleven' over 111 km in Switzerland, using bi- and multivariate analysis.

RESULTS

The mean (SD) race time was 289.7 (54.6) min. The bivariate analysis showed that body height (r=0.61), length of leg (r=0.61), number of weekly inline skating training sessions (r=-0.51) and duration of each training unit (r=0.61) were significantly correlated with race time. Stepwise multiple regressions revealed that body height, duration of each training unit, and age were the best variables to predict race time.

CONCLUSION

Race time in ultra-endurance inline races such as the 'Inline One-eleven' over 111 km might be predicted by the following equation (r(2)=0.65): Race time (min)=-691.62+521.71 (body height, m)+0.58 (duration of each training unit, min)+1.78 (age, yrs) for female ultra-endurance inline skaters.

Comparison between Recreational Male Ironman Triathletes and Marathon Runners

Recent investigations described a personal best marathon time as a predictor variable for an Ironman race time in recreational male Ironman triathletes. Similarities and differences in anthropometry and training were investigated between 83 recreational male Ironman triathletes and 81 recreational male marathoners. Ironman triathletes were significantly taller and had a higher body mass and a higher skin-fold thickness of the calf compared to the marathoners. Weekly training volume in hours was higher in Ironman triathletes. In the Ironman triathletes, percent body fat was related to overall race time and both the split time in cycling and running. The weekly swim kilometres were related to the split time in swimming, and the speed in cycling was related to the bike split time. For the marathoners, the calf skin-fold thickness and running speed during training were related to marathon race time. Although personal best marathon time was a predictor of Ironman race time in male triathletes, anthropometric and training characteristics of male marathoners were different from those of male Ironman triathletes, probably due to training of different muscle groups and metabolic endurance beyond marathon running, as the triathletes are also training for high-level performance in swimming and cycling. Future studies should compare Olympic distance triathletes and road cyclists with Ironman triathletes.