Open-water ultra-distance swimming has a long history where the ‘English Channel’ (~33 km) was crossed in 1875 for the first time. Nowadays, the three most challenging open-water swims worldwide are the 21-miles (34 km) ‘English Channel Swim’, the 20.1-miles (32.2 km) ‘Catalina Channel Swim’ and the 28.5-miles (45.9 km) ‘Manhattan Island Marathon Swim’, also called the ‘Triple Crown of Open Water Swimming’. Recent studies showed that women were able to achieve men’s performance in the ‘English Channel Swim’ or to even outperform men in the ‘Manhattan Island Marathon Swim’. However, the analysis of the ‘Catalina Channel Swim’ as part of the ‘Triple Crown of Open Water Swimming’ is missing. We investigated performance and sex difference in performance for successful women and men crossing the ‘Catalina Channel’ between 1927 and 2014. The fastest woman ever was ~22 min faster than the fastest man ever. Although the three fastest women ever were ~20 min faster than the three fastest men ever, the difference reached not statistical significance (p > 0.05). Similarly for the ten fastest ever, the ~1 min difference for women was not significant (p > 0.05). However, when the swimming times of the annual fastest women (n = 39) and the annual fastest men (n = 50) competing between 1927 and 2014 were compared, women (651 ± 173 min) were 52.9 min (16 ± 12%) faster than men (704 ± 279 min) (p < 0.0001). Across years, swimming times decreased non-linearly in the annual fastest men (polynomial 2nd degree) and women (polynomial 3rd degree) whereas the sex difference decreased linearly from 52.4% (1927) to 7.1% (2014). In summary, the annual fastest women crossed the ‘Catalina Channel’ faster than the annual fastest men. The non-linear decrease in swimming times suggests that female and male swimmers have reached a limit in this event. However, the linear decrease in the sex difference may indicate that women continuously narrow the gap to men.
Ultra-endurance; Women; Men; Sex difference
Exercise-associated hyponatremia (EAH), rhabdomyolysis and renal failure appear to be a unique problem in ultra-endurance racers.
We investigated the combined occurrence of EAH and rhabdomyolysis in seven different ultra-endurance races and disciplines (i.e. multi-stage mountain biking, 24-h mountain biking, 24-h ultra-running and 100-km ultra-running).
Two (15.4 %) ultra-runners (man and woman) from hyponatremic ultra-athletes (n = 13) and four (4 %) ultra-runners (four men) from the normonatremic group (n = 100) showed rhabdomyolysis following elevated blood creatine kinase (CK) levels > 10,000 U/L without the development of renal failure and the necessity of a medical treatment. Post-race creatine kinase, plasma and urine creatinine significantly increased, while plasma [Na+] and creatine clearance decreased in hyponatremic and normonatremic athletes, respectively. The percentage increase of CK was higher in the hyponatremic compared to the normonatremic group (P < 0.05). Post-race CK levels were higher in ultra-runners compared to mountain bikers (P < 0.01), in faster normonatremic (P < 0.05) and older and more experienced hyponatremic ultra-athletes (P < 0.05). In all finishers, pre-race plasma [K+] was related to post-race CK (P < 0.05).
Hyponatremic ultra-athletes tended to develop exercise-induced rhabdomyolysis more frequently than normonatremic ultra-athletes. Ultra-runners tended to develop rhabdomyolysis more frequently than mountain bikers. We found no association between post-race plasma [Na+] and CK concentration in both hypo- and normonatremic ultra-athletes.
Mountain biking; Running; Long distances
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).
Swimming; Cycling; Running; Personal best time
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.
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.
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.
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 (VO2max) with ultra-triathlon race performance in order to investigate whether these characteristics are also predictive for ultra-triathlon race performance.
swimming; cycling; running; age; experience; ultra-endurance
Marathon (42 km) and 100 km ultramarathon races are increasing in popularity. The aim of the present study was to investigate the potential associations of anthropometric and training variables with performance in these long-distance running competitions.
Training and anthropometric data from a large cohort of marathoners and 100 km ultramarathoners provided the basis of this work. Correlations between training and anthropometric indices of subjects and race performance were assessed using bivariate and multiple regression analyses.
A combination of volume and intensity in training was found to be suitable for prediction of marathon and 100 km ultramarathon race pace. The relative role played by these two variables was different, in that training volume was more important than training pace for the prediction of 100 km ultramarathon performance, while the opposite was found for marathon performance. Anthropometric characteristics in terms of body fat percentage negatively affected 42 km and 100 km race performance. However, when this factor was relatively low (ie, less than 15% body fat), the performance of 42 km and 100 km races could be predicted solely on the basis of training indices.
Mean weekly training distance run and mean training pace were key predictor variables for both marathon and 100 km ultramarathon race performance. Predictive correlations for race performance are provided for runners with a relatively low body fat percentage.
running; performance; training indices; body fat; sports training
Pacing strategy has been investigated in elite 100 km and elite 161 km (100 mile) ultra-marathoners, but not in age group ultra-marathoners. This study investigated changes in running speed over segments in male elite and age group 100 km ultra-marathoners with the assumption that running speed would decrease over segments with increasing age of the athlete. Running speed during segments in male elite and age group finishers for 5-year age groups (ie, 18–24 to 65–69 years) in the 100 km Lauf Biel in Switzerland was investigated during the 2000–2009 period. Average running speed over segment time station (TS) TS1–TS2 (56.1 km) was compared with running speed Start–TS1 (38 km) and Start–TS3 (76.7 km) and running speed TS2–TS3 was compared with running speed Start–Finish. For the top ten athletes in each edition, running speed decreased from 2000 to 2009 for TS1–TS2 and TS2–TS3 (P<0.0001) but not in TS3–Finish (P>0.05). During TS1–TS2, athletes were running at 98.0%±2.1% of the running speed of Start–TS1. In TS2–TS3, they were running at 94.6%±3.4% of the running speed of TS1–TS2. In TS3–Finish, they were running at 95.5%±3.8% of running speed in TS2–TS3. For age group athletes, running speed decreased in TS1–TS2 and TS2–TS3. In TS3–Finish, running speed remained unchanged with the exception of the age group 40–44 years for which running speed increased. Running speed showed the largest decrease in the age group 18–24 years. To summarize, the top ten athletes in each edition maintained their running speed in the last segment (TS3–Finish) although running speed decreased over the first two segments (TS1–TS2 and TS2–TS3). The best pacers were athletes in the age group 40–44 years, who were able to achieve negative pacing in the last segment (TS3–Finish) of the race. The negative pacing in the last segment (TS3–Finish) was likely due to environmental conditions, such as early dawn and the flat circuit in segment TS3–Finish of the race.
running; men; long distance; master athlete
Anecdotal reports have assumed that women would be able to outrun men in long-distance running. The aim of this study was to test this assumption by investigating the changes in performance difference between sexes in the best ultramarathoners in 50-mile, 100-mile, 200-mile, 1,000-mile, and 3,100-mile events held worldwide between 1971 and 2012. The sex differences in running speed for the fastest runners ever were analyzed using one-way analysis of variance with subsequent Tukey–Kramer posthoc analysis. Changes in sex difference in running speed of the annual fastest were analyzed using linear and nonlinear regression analyses, correlation analyses, and mixed-effects regression analyses. The fastest men ever were faster than the fastest women ever in 50-mile (17.5%), 100-mile (17.4%), 200-mile (9.7%), 1,000-mile (20.2%), and 3,100-mile (18.6%) events. For the ten fastest finishers ever, men were faster than women in 50-mile (17.1%±1.9%), 100-mile (19.2%±1.5%), and 1,000-mile (16.7%±1.6%) events. No correlation existed between sex difference and running speed for the fastest ever (r2=0.0039, P=0.91) and the ten fastest ever (r2=0.15, P=0.74) for all distances. For the annual fastest, the sex difference in running speed decreased linearly in 50-mile events from 14.6% to 8.9%, remained unchanged in 100-mile (18.0%±8.4%) and 1,000-mile (13.7%±9.1%) events, and increased in 3,100-mile events from 12.5% to 16.9%. For the annual ten fastest runners, the performance difference between sexes decreased linearly in 50-mile events from 31.6%±3.6% to 8.9%±1.8% and in 100-mile events from 26.0%±4.4% to 24.7%±0.9%. To summarize, the fastest men were ~17%–20% faster than the fastest women for all distances from 50 miles to 3,100 miles. The linear decrease in sex difference for 50-mile and 100-mile events may suggest that women are reducing the sex gap for these distances.
running; sex difference; running speed; ultraendurance
This study investigated changes in normalised running speed as a proxy for effort distribution over segments in male elite and age group 100 km ultra-marathoners with the assumption that older runners would slow down more than younger runners.
The annual ten fastest finishers (i.e. elite and age group runners) competing between 2000 and 2009 in the ‘100 km Lauf Biel’ were identified. Normalised average running speed (i.e. relative to segment 1 of the race corrected for gradient) was analysed as a proxy for pacing in elite and age group finishers. For each year, the ratio of the running speed from the final to the first segment for each age cohort was determined. These ratios were combined across years with the assumption that there were no ‘extreme’ wind events etc. which may have impacted the final relative to the first segment across years. The ratios between the age cohorts were compared using one-way ANOVA and Tukey’s post-hoc test. The ratios between elite and age group runners were investigated using one-way ANOVA with Dunnett’s multiple comparison post-hoc tests. The trend across age groups was investigated using simple regression analysis with age as the dependent variable.
Normalised average running speed was different between age group 18–24 years and age groups 25–29, 30–34, 35–39, 40–44, 45–49, 50–54, 55–59 and 65–69 years. Regression analysis showed no trend across age groups (r2 = 0.003, p > 0.05).
To summarize, (i) athletes in age group 18–24 years were slower than athletes in most other age groups and (ii) there was no trend of slowing down for older athletes.
Running; Men; Long-distance; Master athlete
We investigated seventy-four ultra-mountain bikers (MTBers) competing in the solo category in the first descriptive field study to detail nutrition habits and the most common food before during and after the 24 hour race using questionnaires. During the race, bananas (86.5%), energy bars (50.0%), apples (43.2%) and cheese (43.2%) were the most commonly consumed food, followed by bread (44.6%), rice (33.8%) and bananas (33.8%) after the race. Average fluid intake was 0.5 ± 0.2 l/h. The main beverage was isotonic sports drink (82.4%) during and pure water (66.2%) after the race. The most preferred four supplements in the four weeks before, the day before, during and after the race were vitamin C (35.1%), magnesium (44.6%), magnesium (43.2%) and branched-chain amino acids (24.3%), respectively. Total frequency of food intake (30.6 ± 10.5 times/24 hrs) was associated with fluid intake (r = 0.43, P = 0.04) and both were highest at the beginning of the race and lower during the night hours and the last race segment in a subgroup of twenty-three ultra-MTBers. Supplement intake frequency (6.8 ± 8.4 times/24 hrs) was highest during the night hours and lower at the beginning and end of the race. Elevated food and fluid intake among participants tracked across all race segments (P < 0.001). In conclusion, the nutrition strategy employed by ultra-MTBers was similar to those demonstrated in previous studies of ultra-cyclists with some exceptions among selected individuals.
Race nutrition; 24-hour race; Ultra-cycling
We investigated age and performance in distance-limited ultra-marathons held from 50 km to 1,000 km. Age of peak running speed and running speed of the fastest competitors from 1969 to 2012 in 50 km, 100 km, 200 km and 1,000 km ultra-marathons were analyzed using analysis of variance and multi-level regression analyses. The ages of the ten fastest women ever were 40 ± 4 yrs (50 km), 34 ± 7 yrs (100 km), 42 ± 6 yrs (200 km), and 41 ± 5 yrs (1,000 km). The ages were significantly different between 100 km and 200 km and between 100 km and 1,000 km. For men, the ages of the ten fastest ever were 34 ± 6 yrs (50 km), 32 ± 4 yrs (100 km), 44 ± 4 yrs (200 km), and 47 ± 9 yrs (1,000 km). The ages were significantly younger in 50 km compared to 100 km and 200 km and also significantly younger in 100 km compared to 200 km and 1,000 km. The age of the annual ten fastest women decreased in 50 km from 39 ± 8 yrs (1988) to 32 ± 4 yrs (2012) and in men from 35 ± 5 yrs (1977) to 33 ± 5 yrs (2012). In 100 km events, the age of peak running speed of the annual ten fastest women and men remained stable at 34.9 ± 3.2 and 34.5 ± 2.5 yrs, respectively. Peak running speed of top ten runners increased in 50 km and 100 km in women (10.6 ± 1.0 to 15.3 ± 0.7 km/h and 7.3 ± 1.5 to 13.0 ± 0.2 km/h, respectively) and men (14.3 ± 1.2 to 17.5 ± 0.6 km/h and 10.2 ± 1.2 to 15.1 ± 0.2 km/h, respectively). In 200 km and 1,000 km, running speed remained unchanged. In summary, the best male 1,000 km ultra-marathoners were ~15 yrs older than the best male 100 km ultra-marathoners and the best female 1,000 km ultra-marathoners were ~7 yrs older than the best female 100 km ultra-marathoners. The age of the fastest 50 km ultra-marathoners decreased across years whereas it remained unchanged in 100 km ultra-marathoners. These findings may help athletes and coaches to plan an ultra-marathoner’s career. Future studies are needed on the mechanisms by which the fastest runners in the long ultra-marathons tend to be older than those in shorter ultra-marathons.
Ultra-marathon; Age of peak running speed; Running speed
The aims of the present study were to investigate the changes in the age and in swimming performance of finalists in World Championships (1994–2013) and Olympic Games (1992–2012) competing in all events/races (stroke and distance). Data of 3,295 performances from 1,615 women and 1,680 men were analysed using correlation analyses and magnitudes of effect sizes. In the World Championships, the age of the finalists increased for all strokes and distances with exception of 200 m backstroke in women, and 400 m freestyle and 200 m breaststroke in men where the age of the finalists decreased. The magnitudes of the effects were small to very large (mean ± SD 2.8 ± 2.7), but extremely large (13.38) for 1,500 m freestyle in women. In the Olympic Games, the age of the finalists increased for all strokes and distances with exception of 800 m freestyle in women and 400 m individual medley in men. The magnitudes of the effects were small to very large (mean ± SD 4.1 ± 7.1), but extremely large for 50 m freestyle in women (10.5) and 200 m butterfly in men (38.0). Swimming performance increased across years in both women and men for all strokes and distances in both the World Championships and the Olympic Games. The magnitudes of the effects were all extremely large in World Championships (mean ± SD 20.1 ± 8.4) and Olympic Games (mean ± SD 52.1 ± 47.6); especially for 100 m and 200 m breaststroke (198) in women in the Olympic Games. To summarize, in the last ~20 years the age of the finalists increased in both the World Championships and the Olympic Games with some minor exceptions (200 m backstroke in women, 400 m freestyle and 200 m breaststroke in men in World Championships and 800 m freestyle in women and 400 m individual medley in men in Olympic Games) and performance of the finalists improved.
Elite swimmers; Age; Performance; Sex difference
Endurance performance decreases during ageing due to alterations in physiological characteristics, energy stores, and psychological factors. To investigate alterations in physiological characteristics and body composition of elderly master athletes in response to an extreme endurance event, we present the case of the first ninety-year-old official male marathon finisher.
Before and directly after the marathon, a treadmill incremental test, dual-energy X-ray absorptiometry, peripheral quantitative computed tomography, mechanography, and dynamometry measurements were conducted. The athlete finished the marathon in 6 h 48 min 55 s, which corresponds to an average competition speed of 6.19 km h-1.
Discussion and Evaluation
Before the marathon,
was 31.5 ml min-1 kg-1 body mass and peak heart rate was 140 beats min-1. Total fat mass increased in the final preparation phase (+3.4%), while leg fat mass and leg lean mass were slightly reduced after the marathon (-3.7 and -1.6%, respectively). Countermovement jump (CMJ) peak power and peak velocity decreased after the marathon (-16.5 and -14.7%, respectively). Total impulse during CMJ and energy cost of running were not altered by the marathon. In the left leg, maximal voluntary ground reaction force (Fm1LH) and maximal isometric voluntary torque (MIVT) were impaired after the marathon (-12.2 and -14.5%, respectively).
Side differences in Fm1LH and MIVT could be attributed to the distinct non-symmetrical running pattern of the athlete. Similarities in alterations in leg composition and CMJ performance existed between the nonagenarian athlete and young marathon runners. In contrast, alterations in total body composition and m1LH performance were markedly different in the nonagenarian athlete when compared to his younger counterparts.
Dual-energy X-ray absorptiometry; Peripheral quantitative computed tomography; Countermovement jump; Multiple one-legged hopping; Impulse
Effects of course length (25 m versus 50 m) and advances in performance of individual medley swimming were examined for men and women in Swiss national competitions and FINA World Championships during 2000–2011. Linear regression and analysis of variance (ANOVA) were used to analyse 200 m and 400 m race results for 26,081 swims on the Swiss high score list and 382 FINA finalists. Swiss and FINA swimmers of both sexes were, on average, 4.3±3.2% faster on short courses for both race distances. Sex-related differences in swim speed were significantly greater for FINA swimmers competing in short-course events than in long-course events (10.3±0.2% versus 9.7±0.3%, p<0.01), but did not differ for Swiss swimmers (p>0.05). Sex-related differences in swimming speed decreased with increasing race distance for both short- and long-course events for Swiss athletes, and for FINA athletes in long-course events. Performance improved significantly (p<0.05) during 2000–2011 for FINA men competing in either course length and FINA females competing in short-course events, but not for Swiss swimmers. Overall, the results showed that men and women individual medley swimmers, competing at both national and international levels, have faster average swimming speeds on short courses than on long courses, for both 200 m and 400 m distances. FINA athletes demonstrate an improving performance in the vast majority of individual medley events, while performance at national level seems to have reached a plateau during 2000–2011.
swim speed; pool length; sex-related difference; temporal trends
Recent findings showed that elite Ironman triathletes competing in ‘Ironman Hawaii’ improved both split and overall race times. The present study investigated whether elite athletes also improved in transition time (i.e. time needed between disciplines for changing clothes and equipment).
Changes in split times, overall race times and transition times (i.e. expressed in absolute and relative terms) in the annual fastest competing in ‘Ironman Hawaii’ were investigated using linear, non-linear and multi-level regression analyses. To detect a potential difference in transition times between different race distances, we compared transition times in ‘Ironman Hawaii’ to transition times in the World Championships ‘Ironman 70.3’ covering the half distance of the Ironman distance triathlon.
In ‘Ironman Hawaii’, transition times remained unchanged for the annual fastest women but increased linearly for the annual fastest men. For the annual ten fastest, transition times increased linearly for women and men in both absolute and relative terms. The sex difference in transition times remained unchanged for the annual fastest, but decreased linearly for the annual ten fastest. In ‘Ironman 70.3’, transition times remained unchanged for the annual fastest. For the annual ten fastest, transition times decreased linearly for both women and men in absolute and relative terms. The sex difference in transition times remained unchanged for both the annual fastest and the annual ten fastest. Transition times were faster in ‘Ironman 70.3’ for women in 2011 and for men in 2006, 2007, and 2010-2013. In relative terms, transition times were faster in ‘Ironman 70.3’compared to ‘Ironman Hawaii’ during 2006-2013. The sex difference in transition times remained unchanged.
In ‘Ironman Hawaii’, transition times increased for both women and men whereas the sex difference decreased. In ‘Ironman 70.3’, transition times decreased for both women and men whereas the sex difference remained unchanged. Generally, transition times were slower in ‘Ironman Hawaii’ compared to ‘Ironman 70.3’.
Swimming; Cycling; Running; Sex difference; Endurance
Recent studies found that the athlete’s age of the best ultra-marathon performance was higher than the athlete’s age of the best marathon performance and it seemed that the athlete’s age of peak ultra-marathon performance increased in distance-limited races with rising distance.
We investigated the athlete’s age of peak ultra-marathon performance in the fastest finishers in time-limited ultra-marathons from 6 hrs to 10 d. Running performance and athlete’s age of the fastest women and men competing in 6 hrs, 12 hrs, 24 hrs, 48 hrs, 72 hrs, 144 hrs (6 d) and 240 hrs (10 d) were analysed for races held between 1975 and 2012 using analysis of variance and multi-level regression analysis.
The athlete’s ages of the ten fastest women ever in 6 hrs, 12 hrs, 24 hrs, 48 hrs, 72 hrs, 6 d and 10 d were 41 ± 9, 41 ± 6, 42 ± 5, 46 ± 5, 44 ± 6, 42 ± 4, and 37 ± 4 yrs, respectively. The athlete’s age of the ten fastest women was different between 48 hrs and 10 d. For men, the athlete’s ages were 35 ± 6, 37 ± 9, 39 ± 8, 44 ± 7, 48 ± 3, 48 ± 8 and 48 ± 6 yrs, respectively. The athlete’s age of the ten fastest men in 6 hrs and 12 hrs was lower than the athlete’s age of the ten fastest men in 72 hrs, 6 d and 10 d, respectively.
The athlete’s age of peak ultra-marathon performance did not increase with rising race duration in the best ultra-marathoners. For the fastest women ever in time-limited races, the athlete’s age was lowest in 10 d (~37 yrs) and highest in 48 hrs (~46 yrs). For men, the athlete’s age of the fastest ever in 6 hrs (~35 yrs) and 12 hrs (~37 yrs) was lower than the athlete’s age of the ten fastest in 72 hrs (~48 yrs), 6 d (~48 yrs) and 10 d (~48 yrs). The differences in the athlete’s age of peak performance between female and male ultra-marathoners for the different race durations need further investigations.
Master athlete; Female; Male; Ultra-endurance
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.
Age trends; Endurance; Swimming; Cycling; Running
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’.
The nationality and swim times for all swimmers who successfully crossed the 33.8-km ‘English Channel’ from 1875 to 2013 were analysed.
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.
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.
Swimmer; Ultra endurance; Origin; Country
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).
Triathlon; Swimming; Cycling; Running; Ultra-endurance
The aims of the study were (i) to investigate the relationship between elite marathon race times and age in 1-year intervals by using the world single age records in marathon running from 5 to 93 years and (ii) to evaluate the sex difference in elite marathon running performance with advancing age.
World single age records in marathon running in 1-year intervals for women and men were analysed regarding changes across age for both men and women using linear and non-linear regression analyses for each age for women and men.
The relationship between elite marathon race time and age was non-linear (i.e. polynomial regression 4th degree) for women and men. The curve was U-shaped where performance improved from 5 to ~20 years. From 5 years to ~15 years, boys and girls performed very similar. Between ~20 and ~35 years, performance was quite linear, but started to decrease at the age of ~35 years in a curvilinear manner with increasing age in both women and men. The sex difference increased non-linearly (i.e. polynomial regression 7th degree) from 5 to ~20 years, remained unchanged at ~20 min from ~20 to ~50 years and increased thereafter. The sex difference was lowest (7.5%, 10.5 min) at the age of 49 years.
Elite marathon race times improved from 5 to ~20 years, remained linear between ~20 and ~35 years, and started to increase at the age of ~35 years in a curvilinear manner with increasing age in both women and men. The sex difference in elite marathon race time increased non-linearly and was lowest at the age of ~49 years.
Running; Sex difference; Performance; Boys; Girls; Master runner
Improved performance has been reported for master runners (i.e. athletes older than 40 years) in both single marathons and single ultra-marathons. This study investigated performance trends of age group ultra-marathoners competing in all 100 km and 100 miles races held worldwide between 1971 and 2013. Changes in running speeds across years were investigated for the annual ten fastest 5-year age group finishers using linear, non-linear and multi-level regression analyses. In 100 km, running speed remained unchanged in women in 25–29 years, increased non-linearly in 30–34 to 55–59 years, and linearly in 60–64 years. In men, running speed increased non-linearly in 18–24 to 60–64 years and linearly in 65–69 to 75–79 years. In 100 miles, running speed increased in women linearly in 25–29 and 30–34 years, non-linearly in 35–39 to 45–49 years, and linearly in 50–54 and 55–59 years. For men, running speed increased linearly in 18–24 years, non-linearly in 25–29 to 45–49 years, and linearly in 50–54 to 65–69 years. Overall, the faster race times over the last 30 years are a result of all top ten finishers getting faster. These findings suggest that athletes in younger to middle age groups (i.e. 25–35 to 50–65 years depending upon sex and distance) have reached their limits due to a non-linear increase in running speed whereas runners in very young (i.e. younger than 25–35 years) and older age groups (i.e. older than 50–65 years) depending upon sex and distance might still improve their performance due to a linear increase in running speed.
Running; Ultra-distance; Women; Men
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.
triathlon; swimming; cycling; running; ultra-endurance
This study investigated swimming speeds and sex differences of finalists competing at the Olympic Games (i.e. 624 female and 672 male athletes) and FINA World Championships (i.e. 990 women and 1008 men) between 1992 and 2013.
Linear, non-linear and multi-level regression models were used to investigate changes in swimming speeds and sex differences for champions and finalists.
Regarding finalists in FINA World Championships and Olympic Games, swimming speed increased linearly in both women and men in all disciplines and race distances. Male world champions’ swimming speed remained stable in 200 m butterfly, 400 m, 800 m and 1,500 m freestyle. Considering women, swimming speed remained unchanged in 50 m and 400 m freestyle. In the Olympic Games, swimming speed of male champions remained unchanged in 200 m breaststroke, 50 m, 400 m, 800 m and 1,500 m freestyle. Female Olympic champions’ swimming speed remained stable in 100 m and 200 m backstroke, 100 m butterfly, 200 m individual medley, 50 m and 200 m freestyle. Evaluating sex differences between finalists in FINA World Championships, results showed a linear decrease in 100 m breaststroke and 200 m butterfly and a non-linear increase in 100 m backstroke. In finals at the Olympic Games, the sex difference decreased linearly for 100 m backstroke, 400 m and 800 m freestyle. However, a linear increase for 200 m butterfly can be reported. Considering Olympic and world champions, the sex difference remained stable in all disciplines and race distances.
Swimming speed of the finalists at the Olympic Games and FINA World Championships increased linearly. The top annual female swimmers increased swimming speed rather at longer race distances (i.e. 800 m and 1,500 m freestyle, 200 m butterfly, and 400 m individual medley), whereas the top annual male swimmers increased it rather at shorter race distances (i.e. 100 m and 200 m freestyle, 100 m butterfly, and 100 m breaststroke). Sex difference in swimming was unchanged in Olympic and world champions. Finalists and champions at the Olympic Games and FINA World Championships reduced the sex difference with increasing race distance.
Swimming speed; Sex difference
Despite of the growth of ultra-endurance sports events (of duration >6 h) over the previous few decades, the age-related declines in ultra-endurance performance have drawn little attention. The aim of the study was to analyse the changes in participation and performance trends of older (>40 years of age) triathletes between 1986 and 2010 at the Hawaii Ironman triathlon consisting of 3.8 km swimming, 180 km cycling and 42 km running. Swimming, cycling, running and total times of the best male and female triathletes between 18 and 69 years of age who competed in the Hawaii Ironman triathlon were analysed. The relative participation of master triathletes increased during the 1986–2010 period, while the participation of triathletes younger than 40 years of age decreased. Linear regression showed that males older than 44 years and females older than 40 years significantly improved their performances in the three disciplines and in the total time taken to complete the race. Gender differences in total time performance significantly decreased in the same time period for all age groups between the 40–44 and 55–59 years ones. The reasons for these relative improvements of Ironman athlete performances in older age groups remain, however, unknown. Further studies investigating training regimes, competition experience or sociodemographic factors are needed to gain better insights into the phenomenon of increasing participation and improvement of ultra-endurance performance with advancing age.
Master athletes; Endurance; Gender differences; Triathlon; Swimming; Cycling; Running; Aging
A variety of anthropometric and training characteristics have been identified as predictor variables for race performance in endurance and ultra-endurance athletes. Anthropometric characteristics such as skin-fold thicknesses, body fat, circumferences and length of limbs, body mass, body height, and body mass index were bi-variately related to race performance in endurance athletes such as swimmers in pools and in open water, in road and mountain bike cyclists, and in runners and triathletes over different distances. Additionally, training variables such as volume and speed were also bi-variately associated with race performance. Multi-variate regression analyses including anthropometric and training characteristics reduced the predictor variables mainly to body fat and speed during training units. Further multi-variate regression analyses including additionally the aspects of previous experience such as personal best times showed that mainly previous best time in shorter races were the most important predictors for ultra-endurance race times. Ultra-endurance athletes seemed to prepare differently for their races compared to endurance athletes where ultra-endurance athletes invested more time in training and completed more training kilometers at lower speed compared to endurance athletes. In conclusion, the most important predictor variables for ultra-endurance athletes were a fast personal best time in shorter races, a low body fat and a high speed during training units.
Swimming; Cycling; Running; Skin-Fold; Body Fat; Ultra-Endurance
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.
Swimming; Cycling; Running; Multi-sport; Ultra-endurance