Sex differences in pacing during 'Ultraman Hawaii'

Ultra-Cycling- Past, Present, Future: A Narrative Review

BACKGROUND

Ultra-endurance events are gaining popularity in multiple exercise disciplines, including cycling. With increasing numbers of ultra-cycling events, aspects influencing participation and performance are of interest to the cycling community.

MAIN BODY

The aim of this narrative review was, therefore, to assess the types of races offered, the characteristics of the cyclists, the fluid and energy balance during the race, the body mass changes after the race, and the parameters that may enhance performance based on existing literature. A literature search was conducted in PubMed, Scopus, and Google Scholar using the search terms 'ultracycling', 'ultra cycling', 'ultra-cycling', 'ultra-endurance biking', 'ultra-bikers' and 'prolonged cycling'. The search yielded 948 results, of which 111 were relevant for this review. The studies were classified according to their research focus and the results were summarized. The results demonstrated changes in physiological parameters, immunological and oxidative processes, as well as in fluid and energy balance. While the individual race with the most published studies was the Race Across America, most races were conducted in Europe, and a trend for an increase in European participants in international races was observed. Performance seems to be affected by characteristics such as age and sex but not by anthropometric parameters such as skin fold thickness. The optimum age for the top performance was around 40 years. Most participants in ultra-cycling events were male, but the number of female athletes has been increasing over the past years. Female athletes are understudied due to their later entry and less prominent participation in ultra-cycling races. A post-race energy deficit after ultra-cycling events was observed.

CONCLUSION

Future studies need to investigate the causes for the observed optimum race age around 40 years of age as well as the optimum nutritional supply to close the observed energy gap under consideration of the individual race lengths and conditions. Another research gap to be filled by future studies is the development of strategies to tackle inflammatory processes during the race that may persist in the post-race period.

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.

Participation and performance trends in short-, medium, and long-distance duathlon

Participation and performance trends of male and female athletes have been thoroughly analyzed in various endurance sports. Knowing these trends can help coaches and athletes prepare for competitions and may influence their training strategy and career planning. However, duathlon events-consisted of two splits of running (Run1 and Run2) interspersed by a split of cycling (Bike)-have not been thoroughly studied, unlike other endurance sports. The present study aimed to compare participation and performance trends in duathletes who competed in duathlon races hosted by World Triathlon or affiliated National Federations between 1990 and 2021. A total of 25,130 results of age group finishers who competed in run-bike-run duathlon races of varying distances were analyzed with different general linear models. Races were divided into three distances: short-distance (up to 5.5 km run, 21 km bike, 5 km run), medium-distance (5-10 km run, 30-42 km bike, 7-11 km run) and long-distance (at least 14 km run, 60 km bike, 25 km run). On average, women represented 45.6% of all finishers in short-distance, 39.6% in medium-distance and 24.9% in long-distance duathlon races. Throughout the years, men were consistently faster than women in all three race legs (Run 1, Bike, and Run 2) in all three distances across all age groups, and women could not reduce the performance gap. Concerning the age of peak performance, duathletes of the age group 30-34 finished most often in the top three in short- and medium-distance duathlons, whereas male duathletes of the age group 25-29 and female duathletes of the age group 30-34 finished most often in the top three in long-distance duathlons. Women participated less, especially in longer distances, and were constantly slower than men. Duathletes of the age group 30-34 finished most often in the top three. Future studies should analyze participation and performance trends in further subgroups (e.g., elite athletes) and pacing behaviours.

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.

Even Pacing Is Associated with Faster Finishing Times in Ultramarathon Distance Trail Running-The "Ultra-Trail du Mont Blanc" 2008-2019

In recent years, there has been an increasing number of investigations analyzing the effects of sex, performance level, and age on pacing in various running disciplines. However, little is known about the impact of those factors on pacing strategies in ultramarathon trail running. This study investigated the effects of age, sex, and performance level on pacing in the UTMB^® (Ultra-trail du Mont Blanc) and aimed to verify previous findings obtained in the research on other running disciplines and other ultramarathon races. Data from the UTMB^® from 2008 to 2019 for 13,829 race results (12,681 men and 1148 women) were analyzed. A general linear model (two-way analysis of variance (ANOVA)) was applied to identify a sex, age group, and interaction effect in pace average and pace variation. A univariate model (one-way ANOVA) was used to identify a sex effect for age, pace average, and pace variation for the fastest men and women. In our study, pace average and a steadier pace were positively correlated. Even pacing throughout the UTMB^® correlated with faster finishing times. The average pace depended significantly on sex and age group. When considering the top five athletes in each age group, sex and age group also had significant effects on pace variation. The fastest women were older than the fastest men, and the fastest men were faster than the fastest women. Women had a higher pace variation than men. In male competitors, younger age may be advantageous for a successful finish of the UTMB^®. Faster male runners seemed to be younger in ultramarathon trail running with large changes in altitude when compared to other distances and terrains.

Effects of The Performance Level and Race Distance on Pacing in Ultra-Triathlons

The aim of this study was to examine the effects of the performance level and race distance on pacing in ultra-triathlons (Double, Triple, Quintuple and Deca), wherein pacing is defined as the relative time (%) spent in each discipline (swimming, cycling and running). All finishers (n = 3,622) of Double, Triple, Quintuple and Deca Iron ultra-triathlons between 1985 and 2016 were analysed and classified into quartile groups (Q1, Q2, Q3 and Q4) with Q1 being the fastest and Q4 the slowest. Performance of all non-finishers (n = 1,000) during the same period was also examined. Triple and Quintuple triathlons (24.4%) produced the highest rate of non-finishers, and Deca Iron ultra-triathlons produced the lowest rate (18.0%) (χ² = 12.1, p = 0.007, φC = 0.05). For the relative swimming and cycling times (%), Deca triathletes (6.7 ± 1.5% and 48.8 ± 4.9%, respectively) proved the fastest and Double (9.2 ± 1.6% and 49.6 ± 3.6%) Iron ultra-triathletes were the slowest (p < 0.008) with Q4 being the fastest group (8.3 ± 1.6% and 48.8 ± 4.3%) and Q1 the slowest one (9.5 ± 1.5% and 50.9 ± 3.0%) (p < 0.001). In running, Double triathletes were relatively the fastest (41.2 ± 4.0%) and Deca (44.5 ± 5.4%) Iron ultra-triathletes the slowest (p < 0.001) with Q1 being the fastest (39.6 ± 3.3%) and Q4 the slowest group (42.9 ± 4.7%) (p < 0.001). Based on these findings, it was concluded that the fastest ultra-triathletes spent relatively more time swimming and cycling and less time running, highlighting the importance of the role of the latter discipline for the overall ultra-triathlon performance. Furthermore, coaches and ultra-triathletes should be aware of differences in pacing between Double, Triple, Quintuple and Deca Iron triathlons.

The Effect of Aging on Pacing Strategies in Short and Long Distance Duathlon

Background/Study context: Many studies have been conducted on the triathlon during the last several years; however, less information exists with regards to duathlon (i.e., Run 1, Bike and Run 2). The aim of the present study was to examine the effect of age on pacing (i.e., the relative contribution - % - of each discipline and transition times - Transition 1 and Transition 2 - to overall race time) of duathletes competing either to short (i.e., 10 km Run 1, 50 km Bike and 5 km Run 2) or long distance (i.e., 10 km Run 1, 150 km Bike and 30 km Run 2).

METHODS

We analyzed 6,671 finishes (women's, n= 1,037, age 36.6 ± 9.1 years; men's, n= 5,634, 40.0 ± 10.0 years) of 3,881 duathletes competing in 'Powerman Zofingen', the World Championship, from 2003 to 2017, in both the short and the long distance race.

RESULTS

A large discipline×distance interaction on relative time (%) was observed in the short distance (p < .001, η²_p = .936); 24.7%, 57.4%, and 15.8% were spent in Run 1, Bike, and Run 2, respectively. In the long distance, the relative contribution of disciplines was 8.0%, 59.0%, and 32.1%, respectively. A trivial discipline×sex interaction on relative time (%) was shown in the short (p < .001, η²_p = .007) and long distance (p < .001, η²_p = .016). In the short distance, a small discipline×age group interaction on relative time (%) was found (p < .001, η²_p = .030) with younger age groups spending less time (%) in Run 1, Transition 1 and Transition 2, and older groups less time (%) in Bike and Run 2. In the long distance, a moderate discipline×age group interaction on relative time (%) was observed (p < .001, η²_p = .077) with younger age groups spending less time (%) in Run 1, Transition 1, Transition 2 and Run 2, and older groups less time (%) in Bike.

CONCLUSIONS

These findings suggest that younger duathletes are relatively faster in Run 1 and transitions, and older duathletes in Bike in both distances. However, older duathletes are relatively faster in Run 2 in the short distance and younger duathletes are relatively faster in Run 2 in the long distance. The magnitude of the combined effect of discipline and age group on pacing was larger in the long than in the short distance. Therefore, athletes and coaches should be aware of the variation of pacing by age group and distance of a duathlon race such as 'Powerman Zofingen'.

The Differences in Pacing Among Age Groups of Amateur Cross-Country Skiers Depend on Performance

Pacing strategies have mainly been investigated for runners, but little is known for cross-country skiers. The aim of the present study was to examine the effects of performance and age on pacing strategies in cross-country skiing. All finishers (women, n = 19,375; men, n = 86,190) in the 'Engadin Ski Marathon' (42 km) between 1998 and 2016 were analysed for the percentage change of speed at 10 km (Change A), 20 km (Change B) and 35 km (Change C). They were classified in performance groups according to quartiles of average race speed (Q1, Q2, Q3 and Q4) and in 5-year age groups (<20, 20-24, 25-29… 85-89 years). Men were faster than women by +14.3% (15.2 ± 4.0 vs. 13.3 ± 3.3 km/h; p < 0.001, η² = 0.215). A small impact of age group × performance group interaction on Change A was shown in women (p < 0.001, η² = 0.026) and men (p < 0.001, η² = 0.025), where Q1 augmented and Q4 attenuated the decrease in speed with aging. However, the impact of age group × performance group interaction on Change B and C was trivial (p = 0.002, η² ≤ 0.010). Based on these findings, it was concluded that the differences in pacing among age groups depended on the performance level. Thus, the coaches and fitness trainers working with cross-country skiers should advise their athletes to consider both age and performance.

The Combined Effect of Aging and Performance Level on Pacing in Duathlon - the "ITU Powerman Long Distance Duathlon World Championships"

The role of age and performance level has been investigated in runners such as marathoners, but not in multi-sports athletes such as duathletes (running, cycling, and running). Thus, the aim of the present study was to examine the combined effects of aging and performance level on pacing of duathletes competing in two different race distances. Pacing (defined as the relative contribution of cycling time, %, to the overall race time) was analyzed for 6,671 duathletes competing from 2003 to 2017 in the short distance race (10 km first run, 50 km cycling and 5 km second run) or long distance race (10 km first run, 150 km cycling and 30 km second run) of “Powerman Zofingen,” the “ITU Powerman Long Distance Duathlon World Championships.” Men were faster, older, and spent less time (%) in cycling than women in both distances races (p < 0.001). Younger age groups spent more time (%) in cycling than their older counterparts in women (both short and long distance, p = 0.036, η_p² = 0.031, p = 0.025, η_p² = 0.044, respectively) and men (long distance race, p < 0.001, η_p² = 0.016). Fast performance groups spent more time (%) in cycling than their slower counterparts in short (women, p < 0.001, η_p² = 0.057; men, p < 0.001, η_p² = 0.035) and long distance (women, p < 0.001, η_p² = 0.070; men, p < 0.001, η_p² = 0.052). A small age group × performance group interaction on cycling time (%) was observed in the men’s short distance (p = 0.001, η_p² = 0.020) – but not in the long distance or in women – with smaller differences between performance groups in the older than in the younger age groups. Women, young and fast duathletes were relatively slower in cycling than men, old and slow duathletes; that was, old duathletes were relatively faster in cycling than in running. Moreover, there was indication that the difference in pacing among performance groups might be attenuated with aging. Since fast duathletes were relatively faster in running than in cycling, slow duathletes should be encouraged to cycle slower and run faster.

The Effect of Sex and Performance Level on Pacing in Duathlon

The purpose of the present research was to study the effect of sex and performance on pacing in short (Run1-10 km, Bike-50 km and Run2-5 km) and long distance (Run1-10 km, Bike-150 km and Run2-30 km) in the Powerman World Championship ‘Powerman Zofingen’. All finishers (n = 6671; women, n = 1037; men, n = 5634) competing either in the short or long distance versions of ‘Powerman Zofingen’ from 2003 to 2017 were analyzed for the time spent in each discipline (Run1, Bike and Run2), and in transition (Tran) from Run1 to Bike (Tran1) and from Bike to Run2 (Tran2). Athletes were ranked in quartile (Q) groups (Q1, Q2, Q3 and Q4), with Q1 the fastest and Q4 the slowest. In short distance, in both sexes, a medium discipline/transition × quartile interaction on relative time was observed (p < 0.001, η²_p = 0.103 and η²_p = 0.119, respectively), where Q1 was relatively the fastest in Tran1, Tran2 and Run2, and the slowest in Bike (p < 0.001). In long distance, in both sexes, a large discipline/transition × quartile interaction on relative time was observed (p < 0.001, η²_p = 0.208 and η²_p = 0.180, respectively), where Q1 was relatively the fastest in Tran1, Tran2 and Run2, and the slowest in Bike (p < 0.001). In summary, a similar trend of variation of pacing by performance level was observed in both sexes and distances with the fastest duathletes being the fastest in Run2 and both transitions, and the slowest in Bike.

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.

Psychosocial factors as predictors of dropout in ultra-trailers

OBJECTIVE

Although research on the physiological and psychological factors of endurance performance has been extensive, the factors related to dropping out of ultra-trail races have not been well documented. The aim of this study was to examine psychosocial factors as predictors of dropout in ultra-trail runners.

METHODS

Two hundred and twenty-one volunteer athletes completed a survey that included measures of: (a) motivational variables (self-determined motivation, basic needs satisfaction, achievement goals), (b) theory of planned behavior constructs (attitudes, subjective norms, self-efficacy and intention to finish the race), and (c) coping strategies in sport.

RESULTS

The results showed that finishers had higher scores for self-efficacy and intention to finish the race than withdrawers, whereas withdrawers had higher scores for avoidance coping. Multiple logistic regression showed that the number of started and finished ultra-trail races (OR, 0.44; 95% CI 0.22-0.88; p<0.02), self-efficacy (OR, 2.03; 95% CI 1.06-3.89; p<0.04), intention to finish the race (OR, 0.34; 95% CI 0.16-0.71; p<0.004), mastery-approach goals (OR, 0.56; 95% CI 0.31-1.00; p<0.05), and coping strategies of seeking social support (OR, 0.43; 95% CI 0.26-0.71; p<0.001) were associated with a lower risk of race dropout, whereas avoidance coping strategies (OR, 2.26; 95% CI 1.46-3.52; p<0.001) were associated with an increased dropout rate.

CONCLUSION

Interventions promoting self-efficacy constructs and specific coping strategies might contribute to preventing dropout in ultra-trailers.

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.