Personal best time, percent body fat, and training are differently associated with race time for male and female ironman triathletes

Beyond Menstrual Dysfunction: Does Altered Endocrine Function Caused by Problematic Low Energy Availability Impair Health and Sports Performance in Female Athletes?

Low energy availability, particularly when problematic (i.e., prolonged and/or severe), has numerous negative consequences for health and sports performance as characterized in relative energy deficiency in sport. These consequences may be driven by disturbances in endocrine function, although scientific evidence clearly linking endocrine dysfunction to decreased sports performance and blunted or diminished training adaptations is limited. We describe how low energy availability-induced changes in sex hormones manifest as menstrual dysfunction and accompanying hormonal dysfunction in other endocrine axes that lead to adverse health outcomes, including negative bone health, impaired metabolic activity, undesired outcomes for body composition, altered immune response, problematic cardiovascular outcomes, iron deficiency, as well as impaired endurance performance and force production, all of which ultimately may influence athlete health and performance. Where identifiable menstrual dysfunction indicates hypothalamic-pituitary-ovarian axis dysfunction, concomitant disturbances in other hormonal axes and their impact on the athlete's health and sports performance must be recognized as well. Given that the margin between podium positions and "losing" in competitive sports can be very small, several important questions regarding low energy availability, endocrinology, and the mechanisms behind impaired training adaptations and sports performance have yet to be explored.

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.

Changes in pacing variation with increasing race duration in ultra-triathlon races

Despite the increasing scientific interest in the relationship between pacing and performance in endurance sports, little information is available about pacing and pacing variation in ultra-endurance events such as ultra-triathlons. Therefore, we aimed to investigate the trends of pacing, pacing variation, the influence of age, sex, and performance level in ultra-triathlons of different distances. We analysed 969 finishers (849 men, 120 women) in 46 ultra-triathlons longer than the original Ironman® distance (e.g., Double-, Triple-, Quintuple- and Deca Iron ultra-triathlons) held from 2004 to 2015. Pacing speed was calculated for every cycling and running lap. Pacing variation was calculated as the coefficient of variation (%) between the average speed of each lap. Performance level (i.e., fast, moderate, slow) was defined according to the 33.3 and 66.6 percentile of the overall race time. A multivariate analysis (two-way ANOVA) was applied for the overall race time as the dependent variable with 'sex' and 'age group' as independent factors. Another multivariate model with 'age' and 'sex' as covariates (two-way ANCOVA) was applied with pacing variation (cycling and running) as the dependent variable with 'race' and 'performance level' as independent factors. Different pacing patterns were observed by event and performance level. The general pacing strategy applied was a positive pacing. In Double and Triple Iron ultra-triathlon, faster athletes paced more evenly with less variation than moderate or slower athletes. The variation in pacing speed increased with the length of the race. There was no significant difference in pacing variation between faster, moderate, and slower athletes in Quintuple and Deca Iron ultra-triathlon. Women had a slower overall performance than men. The best overall times were achieved at the age of 30-39 years. Successful ultra-triathlon athletes adapted a positive pacing strategy in all race distances. The variation in pacing speed increased with the length of the race. In shorter ultra-triathlon distances (i.e., Double and Triple Iron ultra-triathlon), faster athletes paced more evenly with less variation than moderate or slower athletes. In longer ultra-triathlon distances (i.e., Quintuple and Deca Iron ultra-triathlon), there was no significant difference in pacing variation between faster, moderate, and slower athletes.

The Performance, Physiology and Morphology of Female and Male Olympic-Distance Triathletes

Sex differences in triathlon performance have been decreasing in recent decades and little information is available to explain it. Thirty-nine male and eighteen female amateur triathletes were evaluated for fat mass, lean mass, maximal oxygen uptake (VO2 max), ventilatory threshold (VT), respiratory compensation point (RCP), and performance in a national Olympic triathlon race. Female athletes presented higher fat mass (p = 0.02, d = 0.84, power = 0.78) and lower lean mass (p < 0.01, d = 3.11, power = 0.99). VO2 max (p < 0.01, d = 1.46, power = 0.99), maximal aerobic velocity (MAV) (p < 0.01, d = 2.05, power = 0.99), velocities in VT (p < 0.01, d = 1.26, power = 0.97), and RCP (p < 0.01, d = 1.53, power = 0.99) were significantly worse in the female group. VT (%VO2 max) (p = 0.012, d = 0.73, power = 0.58) and RCP (%VO2 max) (p = 0.005, d = 0.85, power = 0.89) were higher in the female group. Female athletes presented lower VO2 max value, lower lean mass, and higher fat mass. However, females presented higher values of aerobic endurance (%VO2 max), which can attenuate sex differences in triathlon performance. Coaches and athletes should consider that female athletes can maintain a higher percentage of MAV values than males during the running split to prescribe individual training.

Differences between Treadmill and Cycle Ergometer Cardiopulmonary Exercise Testing Results in Triathletes and Their Association with Body Composition and Body Mass Index

Cardiopulmonary exercise testing (CPET) is the method of choice to assess aerobic fitness. Previous research was ambiguous as to whether treadmill (TE) and cycle ergometry (CE) results are transferrable or different between testing modalities in triathletes. The aim of this paper was to investigate the differences in HR and VO2 at maximum exertion between TE and CE, at anaerobic threshold (AT) and respiratory compensation point (RCP) and evaluate their association with body fat (BF), fat-free mass (FFM) and body mass index (BMI). In total, 143 adult (n = 18 female), Caucasian triathletes had both Tr and CE CPET performed. The male group was divided into <40 years (n = 80) and >40 years (n = 45). Females were aged between 18 and 46 years. Body composition was measured with bioelectrical impedance before tests. Differences were evaluated using paired t-tests, and associations were evaluated in males using multiple linear regression (MLR). Significant differences were found in VO2 and HR at maximum exertion, at AT and at RCP between CE and TE testing, in both males and females. VO2AT was 38.8 (±4.6) mL/kg/min in TE vs. 32.8 (±5.4) in CE in males and 36.0 (±3.6) vs. 32.1 (±3.8) in females (p < 0.001). HRAT was 149 (±10) bpm in TE vs. 136 (±11) in CE in males and 156 (±7) vs. 146 (±11) in females (p < 0.001). VO2max was 52 (±6) mL/kg/min vs. 49 (±7) in CE in males and 45.3 (±4.9) in Tr vs. 43.9 (±5.2) in females (p < 0.001). HRmax was 183 (±10) bpm in TE vs. 177 (±10) in CE in males and 183 (±9) vs. 179 (±10) in females (p < 0.001). MLR showed that BMI, BF and FFM are significantly associated with differences in HR and VO2 at maximum, AT and RCP in males aged >40. Both tests should be used independently to achieve optimal fitness assessments and further training planning.

The Personal Food Systems of Pre-Season NCAA Division 1 High-Contact, Low-Contact, and Non-Contact College Athletes

Previous research indicates that dietary habits may differ between athletes of different sports. In this cross-sectional study, we hypothesize meal frequency, food choices, and food preferences will significantly differ between contact types. The participants were athletes (n = 92; men: n = 57, body fat percent (BF%): 14.8 ± 8.4%, body mass index (BMI): 25.5 ± 5.5 kg·m^-2; women: n = 36, BF%: 26.7 ± 7.3%, BMI: 22.3 ± 2.7 kg·m^-2) from high-contact (HCS), low-contact (LCS), and non-contact (NCS) sports. Meal frequency, food preference, and food choice questionnaires assessed factors influencing dietary habits. Dual-energy X-ray absorptiometry (DXA) measured lean body mass, fat mass, and body fat. A GLM multivariate analysis was used with significance accepted at p < 0.05. Significant body composition differences were observed between genders (p < 0.001) and among sports (p < 0.001). Dinner (83.7%), lunch (67.4%), and breakfast (55.4%) were the most frequently eaten meals, followed by evening snack (17.8%), afternoon snack (15.2%), and morning snack (8.7%). Greater preferences for starches were observed for HCS (p = 0.04; η² = 0.07) and for a greater preference for vegetables was found for NCS (p = 0.02; η² = 0.09). Significant differences also existed in the importance of health (p = 0.04; η² = 0.07), weight control (p = 0.05; η² = 0.11), natural content (p = 0.04; η² = 0.07), and price (p = 0.04; η² = 0.07). These results support our hypothesis that food choices and food preferences differ between contact types. This may help sports dieticians create more individualized nutrition programs.

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.

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.

Pre-race determinants influencing performance and finishing of a transcontinental 4486-km ultramarathon

BACKGROUND

Pre-race determinants influencing performance and finishing of one of the largest transcontinental multistage ultramarathons were investigated.

METHODS

Forty-four participants of the TransEurope FootRace 2009 (TEFR), running 4486 km in 64 stages (average 70.1 km daily) were analyzed regarding training and running history. This included years of regular endurance running (PRY), number of finished marathons, ultramarathons (UM) and multistage ultramarathons (MSUM), pre-race records (PRR) for marathon and specific UM races and the extent of pre-race training (PRT) in the last year before TEFR: volume (km/week), duration (h/week) and intensity (km/h).

RESULTS

Mean total running speed during TEFR was 8.25 km/h.Seventy-one percent of subjects finished the race. The mean PRT-volume extends 5500 km. Finishers and non-finishers of the TEFR did not show significant difference in any tested pre-race determinants. There was no association between PRY, number of finished marathons, UM, and MSUM and TEFR performance. There was very strong positive correlation between PRT-intensity and TEFR performance. PRT volume correlated with a medium effect size to TEFR performance. PRR in specific ultra-races (6-hour, 50-km, 100-km races) showed a high correlation to TEFR performance. Performance in ultramarathon correlates inversely with age.

CONCLUSIONS

Like in other endurance disciplines with shorter distances, in ultra-long multistage endurance running the athletes also need a stage-specific pre-race experience, training and adaptation if he wants to end up with a good performance. But dropping out of a MSUM seems not to be consistent with regard to specific pre-race experience. Further research results of TEFR project may reveal potential risk factors for non-finishing a transcontinental footrace.

Amateur endurance triathletes' performance is improved independently of volume or intensity based training

The aim of the present research was to compare the effects in swimming and running performance, horizontal jump test, autonomic modulation, and body composition of four training weeks with emphasis on volume versus intensity in moderate trained triathletes. Thirty-two amateur triathletes (20 males and 12 females) were randomly divided in three different groups that performed 6 training session per week: Intensity (INT): training focused on performs intensity training Volume (VOL): training focused on performs volume training; and Control (CON): physical active group with no periodized training. Body composition, heart rate variability, horizontal jump test, swimming and 2000 m running test were tested before and after the training period. There were no significant differences between INT and VOL in running test. Furthermore, both INT and VOL training groups improved 50 m (p: 0.046 and 0.042 respectively) and 400 m (p: 0.044 and 0.041 respectively) swimming performance. Moreover, there were no significant differences among groups in any moment in HRV variables. No significant difference was observed for horizontal jump test and body composition between the INT and VOL group at any time. According to the results of the present study, four weeks of training with either high intensity or volume results to similar adaptations in endurance, horizontal jump test and body composition parameters in amateur triathletes.

The effect of sex, age and performance level on pacing of Ironman triathletes

The aim of the present study was to examine the effect of sex, age and performance level on pacing of Ironman triathletes. Split times (i.e. swimming, cycling, and running) and overall race times of 343,345 athletes competing between 2002 and 2015 in 253 different Ironman triathlon races were analyzed. Participants were classified into nine performance groups according to their overall race time. Times in swimming, cycling, running and transition were expressed as percentage of the overall race time. Women spent relatively less time (%) in swimming, running and transition time, and more time (%) in cycling than men (p < 0.001). The fastest performance group was relatively faster in running (34.8 ± 1.4 versus 40.3 ± 3.0%, η²= 0.098) and transition time (0.9 ± 0.3 versus 2.2 ± 0.6%, η²= 0.178), and relatively slower in swimming (10.2 ± 0.8 versus 9.8 ± 1.5%, η²= 0.018) and cycling (54.1 ± 1.4 versus 47.8 ± 2.8%, η²= 0.138) than the slowest performance group (p < 0.001). The younger age groups were relatively faster in swimming, running and transition time, but relatively slower in cycling. In summary, the fastest Ironman triathletes were the relatively fastest in running and transition times. Thus, race tactics in an Ironman triathlon should focus on saving energy during swimming and cycling for the running split.

Pacing Strategy of a Full Ironman Overall Female Winner on a Course With Major Elevation Changes

Pryor, JL, Adams, WM, Huggins, RA, Belval, LN, Pryor, RR, and Casa, DJ. Pacing strategy of a full Ironman overall female winner on a course with major elevation changes. J Strength Cond Res 32(11): 3080-3087, 2018-The purpose of this study was to use a mixed-methods design to describe the pacing strategy of the overall female winner of a 226.3-km Ironman triathlon. During the race, the triathlete wore a global positioning system and heart rate (HR)-enabled watch and rode a bike outfitted with a power and cadence meter. High-frequency (every km) analyses of mean values, mean absolute percent error (MAPE), and normalized graded running pace and power (accounting for changes in elevation) were calculated. During the bike, velocity, power, cadence, and HR averaged 35.6 km·h, 199 W, 84 rpm, and 155 b·min, respectively, with minimal variation except for velocity (measurement unit variation [MAPE]: 7.4 km·h [20.3%], 11.8 W [7.0%], 3.6 rpm [4.6%], 3 b·min [2.3%], respectively). During the run, velocity and HR averaged 13.8 km·h and 154 b·min, respectively, with velocity varying four-fold more than HR (MAPE: 4.8% vs. 1.2%). Accounting for elevation changes, power and running pace were less variable (raw [MAPE] vs. normalized [MAPE]: 199 [7.0%] vs. 204 W [2.7%]; 4:29 [4.8%] vs. 4:24 min·km [3.6%], respectively). Consistent with her planned pre-race pacing strategy, the triathlete minimized fluctuations in HR and watts during the bike and run, whereas velocity varied with changes in elevation. This case report provides observational evidence supporting the utility of a pacing strategy that allows for an oscillating velocity that sustains a consistent physiological effort in full Ironman races.

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

Käch, I, Rüst, CA, Nikolaidis, PT, Rosemann, T, and Knechtle, B. The age-related performance decline in Ironman triathlon starts earlier in swimming than in cycling and running. J Strength Cond Res 32(2): 379-395, 2018-In Ironman triathlon, the number of overall male and female finishers increased in the past 30 years, while an improvement in performance has been reported. Studies concluding these numbers only analyzed the top 10 athletes per age group instead of all finishers; therefore, a selection bias might have occurred. The aim of this study was to investigate participation, performance, and the age-related performance decline of all pro- and age-group triathletes ranked in all Ironman triathlons held worldwide between 2002 and 2015. Split and overall race times of 329,066 (80%) male and 81,815 (20%) female athletes competing in 253 different Ironman triathlon races were analyzed. The number of finishers increased in all age groups with the exception of women in age group 75-79 years. In pro athletes, performance improved in all disciplines. In age-group athletes, performance improved in younger age groups for running (from 18-24 to 40-44 years) and older age groups for swimming (from 50-54 to 65-69 years) and cycling (from 35-39 to 55-59 years), whereas it impaired in younger age groups for swimming (from 18-24 to 45-49 years) and cycling (from 18-24 to 30-34 years), and older age groups in running (from 45-49 to 70-74 years). The age-related performance decline started in women in age group 25-29 years in swimming and in age group 30-34 years in cycling, running, and overall race time, whereas it started in men in age group 25-29 years in swimming and in age group 35-39 years in cycling, running, and overall race time. For athletes and coaches, performance improved in younger age groups for running and older age groups for swimming and cycling, and the age-related decline in performance started earlier in swimming than in cycling and running. In summary, women should start competing in Ironman triathlon before the age of 30 years and men before the age of 35 years to achieve their personal best Ironman race time.

Urinary Steroid Profile in Ironman Triathletes

The aim of this study was to determine variations in the urinary steroid profile of triathletes following an Ironman event. A total of 10 male participants (age = 36.0 ± 1.27 years; body height = 179.29 ± 10.77 cm; body mass = 74.50 ± 1.04 kg) completed an Ironman Championship. Urine samples were collected before, immediately after, and 24 hours following the race. Gas chromatography-mass spectrometry (GC/MS) was used to detect and quantify catabolic and anabolic hormones: Androsterone, Dehydroepiandrosteone (DHEA), Androstenedione and Testosterone (T), Betaestradiol, Estrone, Progesterone, Cortisol (C), Cortisone, Tetrahydrocortisol (THE) and Tetrahydrocortisone (THF). These were measured in their glucuroconjugated and free forms. Androsterone (3297.80 ± 756.83 vs. 2154.26 ± 1375.38), DHEA (47.80 ± 19.21 vs. 32.62 ± 15.96) and Beta-estradiol (59.36 ± 11.7 vs. 41.67 ± 10.59) levels decreased after the event. The significant decrease of DHEA (47.80 ± 19.21 vs. 32.11 ± 14.03) remained at 24 hours. Cortisol (200.38 ± 56.60 vs. 257.10 ± 74.00) and THE (238.65 ± 81.55 vs. 289.62 ± 77.13) increased after exercise and remained elevated 24 hours later (200.38 ± 56.60 vs. 252.48 ± 62.09; 238.65 ± 81.55 vs. 284.20 ± 66.66). The following anabolic/catabolic ratios fell after exercise: T/C (0.85 ± 0.54 vs. 0.54 ± 0.29), T/THE (0.66 ± 0.29 vs. 0.40 ± 0.08), T/THE+THF (0.38 ± 0.17 vs. 0.24 ± 0.06), DHEA/THE (0.22 ± 0.05 vs. 0.12 ± 0.05), DHEA/THF (0.34 ± 0.02 vs. 0.21 ± 0.01) and DHEA/THE+THF (0.12 ± 0.02 vs. 0.08 ± 0.03). The steroid profile showed that athletes were fatigued after finishing the competition and a catabolic state remained 24 hours later.

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.

Nation related participation and performance trends in 'Norseman Xtreme Triathlon' from 2006 to 2014

We investigated the nation related participation and performance trends in triathletes competing in ‘Norseman Xtreme Triathlon’ between 2006 and 2014 using mixed models, one-way analysis of variance and multi-variate regression analyses. A total of 1594 athletes (139 women and 1455 men) originating from 34 different countries finished the race. Most of the athletes originated from Norway, Germany, Great Britain, Sweden, USA and France. In the mixed model analysis considering all finishers (n = 1594), with calendar year, sex and country as independent and overall race time as dependent variable, calendar year (p < 0.0001), sex (p < 0.0001), country (p < 0.0001) and the interaction sex × calendar year (p = 0.012) were significant. In the model where overall race time was separated in the three disciplines, we found interactions such as country × discipline (p < 0.0001), year × discipline (p < 0.0001), sex × discipline (p < 0.0001), calendar year × sex (p = 0.044), calendar year × sex × discipline (p = 0.031). Overall race time decreased every year, above all in the year 2012. Women were slower than men, but women reduced this gender gap year after year and above all in the year 2007 (p = 0.001). Athletes from Norway and Germany were faster than those from Great Britain and other countries. Split times of the discipline decreased throughout the years. In particular, the discipline having more impact on overall race time was cycling. Most of the podiums were achieved by Norwegian women and men. For women, the fastest split and transition times were achieved by Norwegian women with exception of the run where German women were faster. Norwegian men were the fastest in split and transition times although French athletes were the fastest in swimming. Across years, the annual three fastest Norwegian women improved in cycling, running, overall race time and transition times but not Norwegian and German men. British men, however, improved running split times and transition times. To summarize, most of the finishers in ‘Norseman Xtreme Triathlon’ originated from Norway and the fastest race times were achieved by Norwegian women and men. Norwegian women improved race times across years but not Norwegian men.

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.

The aspect of experience in ultra-triathlon races

Previous experience seems to be an important predictor for endurance and ultra-endurance performance. The present study investigated whether the number of previously completed races and/or the personal best times in shorter races is more predictive for performance in longer non-stop ultra-triathlons such as a Deca Iron ultra-triathlon. All female and male ultra-triathletes who had finished between 1985 and 2014 at least one Double Iron ultra-triathlon (i.e. 7.6 km swimming, 360 km cycling and 84.4 km running), one Triple Iron ultra-triathlon (i.e. 11.4 km swimming, 540 km cycling and 126.6 km running), one Quintuple Iron ultra-triathlon (i.e. 19 km swimming, 900 km cycling and 221 km running) and one Deca Iron ultra-triathlon (i.e. 38 km swimming, 1,800 km cycling and 422 km running) were identified and their best race times for each distance were recorded. Multiple regression analysis (stepwise, forward selection, p of F for inclusion <0.05, p of F for exclusion >0.1, listwise deletion) was used to determine all variables correlating to overall race time and performance in split disciplines for both Quintuple and Deca Iron ultra-triathlon. The number of finished shorter races (i.e. Double and Triple Iron ultra-triathlon) was not associated with the number of finished longer races (i.e. Quintuple and Deca Iron ultra-triathlon) whereas both split and overall race times correlated to split and overall race times of the longer races with the exception of the swimming split times in Double Iron ultra-triathlon showing no correlation with swimming split times in both Quintuple and Deca Iron ultra-triathlon. In summary, previous experience seemed of importance in performance for longer ultra-triathlon races (i.e. Quintuple and Deca Iron ultra-triathlon) where the personal best times of shorter races (i.e. Double and Triple Iron ultra-triathlon) were important, but not the number of previously finished races. For athletes and coaches, fast race times in shorter ultra-triathlon races (i.e. Double and Triple Iron ultra-triathlon) are more important than a large of number finished races in order to achieve a fast race time in a longer ultra-triathlon (i.e. Quintuple and Deca Iron ultra-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.

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.

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.

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.

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.

Master runners dominate 24-h ultramarathons worldwide-a retrospective data analysis from 1998 to 2011

BACKGROUND

The aims of the present study were to examine (a) participation and performance trends and (b) the age of peak running performance in master athletes competing in 24-h ultra-marathons held worldwide between 1998 and 2011.

METHODS

Changes in both running speed and the age of peak running speed in 24-h master ultra-marathoners (39,664 finishers, including 8,013 women and 31,651 men) were analyzed.

RESULTS

The number of 24-h ultra-marathoners increased for both women and men across years (P < 0.01). The age of the annual fastest woman decreased from 48 years in 1998 to 35 years in 2011. The age of peaking running speed remained unchanged across time at 42.5 ± 5.2 years for the annual fastest men (P > 0.05). The age of the annual top ten women decreased from 42.6 ± 5.9 years (1998) to 40.1 ± 7.0 years (2011) (P < 0.01). For the annual top ten men, the age of peak running speed remained unchanged at 42 ± 2 years (P > 0.05). Running speed remained unchanged over time at 11.4 ± 0.4 km h-1 for the annual fastest men and 10.0 ± 0.2 km/h for the annual fastest women, respectively (P > 0.05). For the annual ten fastest women, running speed increased over time by 3.2% from 9.3 ± 0.3 to 9.6 ± 0.3 km/h (P < 0.01). Running speed of the annual top ten men remained unchanged at 10.8 ± 0.3 km/h (P > 0.05). Women in age groups 25-29 (r2 = 0.61, P < 0.01), 30-34 (r2 = 0.48, P < 0.01), 35-39 (r2 = 0.42, P = 0.01), 40-44 (r2 = 0.46, P < 0.01), 55-59 (r2 = 0.41, P = 0.03), and 60-64 (r2 = 0.57, P < 0.01) improved running speed; while women in age groups 45-49 and 50-54 maintained running speed (P > 0.05). Men improved running speed in age groups 25-29 (r2 = 0.48, P = 0.02), 45-49 (r2 = 0.34, P = 0.03), 50-54 (r2 = 0.50, P < 0.01), 55-59 (r2 = 0.70, P < 0.01), and 60-64 (r2 = 0.44, P = 0.03); while runners in age groups 30-34, 35-39, and 40-44 maintained running speed (P > 0.05).

CONCLUSIONS

Female and male age group runners improved running speed. Runners aged >40 years achieved the fastest running speeds. By definition, runners aged >35 are master runners. The definition of master runners aged >35 years needs to be questioned for ultra-marathoners competing in 24-h ultra-marathons.

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 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.

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.

Does Muscle Mass Affect Running Times in Male Long-distance Master Runners?

Purpose

The aim of the present study was to investigate associations between skeletal muscle mass, body fat and training characteristics with running times in master athletes (age > 35 years) in half-marathon, marathon and ultra-marathon.

Methods

We compared skeletal muscle mass, body fat and training characteristics in master half-marathoners (n=103), master marathoners (n=91) and master ultra-marathoners (n=155) and investigated associations between body composition and training characteristics with race times using bi- and multi-variate analyses.

Results

After multi-variate analysis, body fat was related to half-marathon (β=0.9, P=0.0003), marathon (β=2.2, P<0.0001), and ultra-marathon (β=10.5, P<0.0001) race times. In master half-marathoners (β=-4.3, P<0.0001) and master marathoners (β=-11.9, P<0.0001), speed during training was related to race times. In master ultra-marathoners, however, weekly running kilometers (β=-1.6, P<0.0001) were related to running times.

Conclusions

To summarize, body fat and training characteristics, not skeletal muscle mass, were associated with running times in master half-marathoners, master marathoners, and master ultra-marathoners. Master half-marathoners and master marathoners rather rely on a high running speed during training whereas master ultra-marathoners rely on a high running volume during training. The common opinion that skeletal muscle mass affects running performance in master runners needs to be questioned.

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.

Age-related changes in ultra-triathlon performances

Background

The age-related decline in performance has been investigated in swimmers, runners and triathletes. No study has investigated the age-related performance decline in ultra-triathletes. The purpose of this study was to analyse the age-related declines in swimming, cycling, running and overall race time for both Triple Iron ultra-triathlon (11.4-km swimming, 540-km cycling and 126.6-km running) and Deca Iron ultra-triathlon (38-km swimming, 1,800-km cycling and 420-km running).

Methods

The age and performances of 423 male Triple Iron ultra-triathletes and 119 male Deca Iron ultra-triathletes were analysed from 1992 to 2010 using regression analyses and ANOVA.

Results

The mean age of the finishers was significantly higher for Deca Iron ultra-triathletes (41.3 ± 3.1 years) compared to a Triple Iron ultra-triathletes (38.5 ± 3.3 years) (P < 0.05). For both ultra-distances, the fastest overall race times were achieved between the ages of 25 and 44 years. Deca Iron ultra-triathletes achieved the same level of performance in swimming and cycling between 25 and 54 years of age.

Conclusions

The magnitudes of age-related declines in performance in the three disciplines of ultra-triathlon differ slightly between Triple and Deca Iron ultra-triathlon. Although the ages of Triple Iron ultra-triathletes were on average younger compared to Deca Iron ultra-triathletes, the fastest race times were achieved between 25 and 44 years for both distances. Further studies should investigate the motivation and training of ultra-triathletes to gain better insights in ultra-triathlon performance.

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.

Age and gender differences in half-Ironman triathlon performances - the Ironman 70.3 Switzerland from 2007 to 2010

Background

To date, the age-related decline and gender differences in performance have been investigated for both Olympic and Ironman distance triathlons, but not for the intermediate distance (ie, the half-Ironman distance triathlon covering 1.9 km swimming, 90 km cycling and 21.1 km running, Ironman 70.3®). We determined the age-related differences in performance and the gender differences for female and male half-Ironman triathletes of 6303 finishers (1115 women and 5188 men) at the Ironman 70.3 Switzerland in Rapperswil, Switzerland, from 2007 to 2010.

Methods

Analyses of variance were used to examine performance trends and differences between the genders.

Results

Gender differences in total event time were affected by age (F = 4.2; P < 0.001). Women achieved their best performance between 25 and 39 years whereas men attained their fastest race times between 18 and 39 years. The gender difference for ages 18–24 years was significantly (P < 0.01) greater compared to older age groups (25–29 years and 40–44 years), and the gender difference for age groups 45–49 years and 50–54 years was significantly (P < 0.01) greater than for those between the ages of 35–39 years.

Conclusion

The present data suggest that the fastest race time in a half-Ironman triathlon was achieved between the age of 25 and 39 years for women and between 18 and 39 years for men. Further studies considering the influences on endurance performance are required to better understand the age and gender interactions in half-Ironman triathlon performances, and these studies may provide valuable information to delineate the difference in performance between female and male half-Ironman triathletes.

European athletes dominate performances in Double Iron ultra-triathlons--a retrospective data analysis from 1985 to 2010

We investigated the participation and performance trends of ultra-endurance triathletes from all nationalities competing in a Double Iron ultra-triathlon (7.6-km swim, 360-km cycle and 84.4-km run) from 1985 to 2010. A total of 1854 athletes participated in 92 Double Iron ultra-triathlons. The majority of the winners came from Europe with 72 victories, followed by North America with 17 victories. The race time for the European ultra-triathletes was 1340 (s=95.3) min, decreasing highly significantly (r (2)=0.28; P<0.0001) across the years. North American ultra-triathletes finished the races within 1556 (s=124.5) min; their race time showed no changes across the years (r (2)=0.045; P=0.07). The race time for the Europeans was highly significantly faster compared to the North Americans (P<0.0001). Future studies should investigate each country in Europe and North America in order to find the country with the largest participation of athletes and their best performance.

Personal best times in an Olympic distance triathlon and in a marathon predict Ironman race time in recreational male triathletes

Background

The purpose of this study was to define predictor variables for recreational male Ironman triathletes, using age and basic measurements of anthropometry, training, and previous performance to establish an equation for the prediction of an Ironman race time for future recreational male Ironman triathletes.

Methods

Age and anthropometry, training, and previous experience variables were related to Ironman race time using bivariate and multivariate analysis.

Results

A total of 184 recreational male triathletes, of mean age 40.9 ± 8.4 years, height 1.80 ± 0.06 m, and weight 76.3 ± 8.4 kg completed the Ironman within 691 ± 83 minutes. They spent 13.9 ± 5.0 hours per week in training, covering 6.3 ± 3.1 km of swimming, 194.4 ± 76.6 km of cycling, and 45.0 ± 15.9 km of running. In total, 149 triathletes had completed at least one marathon, and 150 athletes had finished at least one Olympic distance triathlon. They had a personal best time of 130.4 ± 44.2 minutes in an Olympic distance triathlon and of 193.9 ± 31.9 minutes in marathon running. In total, 126 finishers had completed both an Olympic distance triathlon and a marathon. After multivariate analysis, both a personal best time in a marathon (P < 0.0001) and in an Olympic distance triathlon (P < 0.0001) were the best variables related to Ironman race time. Ironman race time (minutes) might be partially predicted by the following equation: (r² = 0.65, standard error of estimate = 56.8) = 152.1 + 1.332 × (personal best time in a marathon, minutes) + 1.964 × (personal best time in an Olympic distance triathlon, minutes).

Conclusion

These results suggest that, in contrast with anthropometric and training characteristics, both the personal best time in an Olympic distance triathlon and in a marathon predict Ironman race time in recreational male Ironman triathletes.

Anthropometric and training variables related to half-marathon running performance in recreational female runners

The relationship between skin-fold thickness and running has been investigated in distances ranging from 100 m to the marathon distance (42.195 km), with the exclusion of the half-marathon distance (21.0975 km). We investigated the association between anthropometric variables, prerace experience, and training variables with race time in 42 recreational, nonprofessional, female half-marathon runners using bi- and multivariate analysis. Body weight (r, 0.60); body mass index (r, 0.48); body fat percentage (r, 0.56); pectoral (r, 0.61), mid-axilla (r, 0.69), triceps (r, 0.49), subscapular (r, 0.61), abdominal (r, 0.59), suprailiac (r, 0.55), and medial calf (r, 0.53) skin-fold thickness; mean speed of the training sessions (r, -0.68); and personal best time in a half-marathon (r, 0.69) correlated with race time after bivariate analysis. Body weight (P = 0.0054), pectoral skin-fold thickness (P = 0.0068), and mean speed of the training sessions (P = 0.0041) remained significant after multivariate analysis. Mean running speed during training was related to mid-axilla (r, -0.31), subscapular (r, -0.38), abdominal (r, -0.44), and suprailiac (r, -0.41) skin-fold thickness, the sum of 8 skin-fold thicknesses (r, -0.36); and percent body fat (r, -0.31). It was determined that variables of both anthropometry and training were related to half-marathon race time, and that skin-fold thicknesses were associated with running speed during training. For practical applications, high running speed during training (as opposed to extensive training) may both reduce upper-body skin-fold thicknesses and improve race performance in recreational female half-marathon runners.

The Relationship between Anthropometry and Split Performance in Recreational Male Ironman Triathletes

PURPOSE

The aim of this study was to investigate the relation between anthropometric variables and total race time including split times in 184 recreational male Ironman triathletes.

METHODS

Body mass, body height, body mass index, lengths and circumferences of imbs, thicknesses of skin-folds, sum of skin-fold thicknesses, and percent body fat were related to total race time including split times using correlation analysis and effect size.

RESULTS

A large effect size (r>0.37) was found for the association between body mass index and time in the run split and between both the sum of skin-folds and percent body fat with total race time. A medium effect size (r=0.24-0.36) was observed in the association between body mass and both the split time in running and total race time, between body mass index and total race time, between both the circumferences of upper arm and thigh with split time in the run and between both the sum of skin-folds and percent body fat with split times in swimming, cycling and running.

CONCLUSIONS

The results of this study showed that lower body mass, lower body mass index and lower body fat were associated with both a faster Ironman race and a faster run split; lower circumferences of upper arm and thigh were also related with a faster run split.