Factors affecting performance in an ultraendurance triathlon

Multidimensional Analysis of Physiological Entropy during Self-Paced Marathon Running

The pacing of a marathon is arguably the most challenging aspect for runners, particularly in avoiding a sudden decline in speed, or what is colloquially termed a "wall", occurring at approximately the 30 km mark. To gain further insight into the potential for optimizing self-paced marathon performance through the coding of comprehensive physiological data, this study investigates the complex physiological responses and pacing strategies during a marathon, with a focus on the application of Shannon entropy and principal component analysis (PCA) to quantify the variability and unpredictability of key cardiorespiratory measures. Nine recreational marathon runners were monitored throughout the marathon race, with continuous measurements of oxygen uptake (V˙O2), carbon dioxide output (V˙CO2), tidal volume (Vt), heart rate, respiratory frequency (Rf), and running speed. The PCA revealed that the entropy variance of V˙O2, V˙CO2, and Vt were captured along the F1 axis, while cadence and heart rate variances were primarily captured along the F2 axis. Notably, when distance and physiological responses were projected simultaneously on the PCA correlation circle, the first 26 km of the race were positioned on the same side of the F1 axis as the metabolic responses, whereas the final kilometers were distributed on the opposite side, indicating a shift in physiological state as fatigue set in. The separation of heart rate and cadence entropy variances from the metabolic parameters suggests that these responses are independent of distance, contrasting with the linear increase in heart rate and decrease in cadence typically observed. Additionally, Agglomerative Hierarchical Clustering further categorized runners' physiological responses, revealing distinct clusters of entropy profiles. The analysis identified two to four classes of responses, representing different phases of the marathon for individual runners, with some clusters clearly distinguishing the beginning, middle, and end of the race. This variability emphasizes the personalized nature of physiological responses and pacing strategies, reinforcing the need for individualized approaches. These findings offer practical applications for optimizing pacing strategies, suggesting that real-time monitoring of entropy could enhance marathon performance by providing insights into a runner's physiological state and helping to prevent the onset of hitting the wall.

Cycling is the most important predictive split discipline in professional Ironman® 70.3 triathletes

Introduction

Our study examined 16,611 records of professional triathletes from 163 Ironman® 70.3 races across 97 countries (2004-2020). The aim was to identify the most predictive discipline-swim, bike, or run-for overall race time.

Methods

We used correlation matrices to compare the dependent variable "finish time" with independent variables "swim time," "bike time," and "run time." This analysis was conducted separately for male and female athletes. Additionally, univariate and multiple linear regression models assessed the strength of these associations.

Results

The results indicated that "bike time" had the strongest correlation with finish time (0.85), followed by "run time" (0.75 for females, 0.82 for males) and "swim time" (0.46 for females, 0.63 for males). Regression models confirmed "bike time" as the strongest predictor of overall race time (R² = 0.8), with "run time" and "swim time" being less predictive.

Discussion

The study concludes that in Ironman 70.3 races, "bike time" is the most significant predictor of overall race performance for both sexes, suggesting a focus on cycling in training and competition strategies. It also highlights a smaller performance gap between genders in swimming than in cycling or running.

Using Physiological Laboratory Tests and Neuromuscular Functions to Predict Extreme Ultratriathlon Performance

Purpose: This study aims to investigate the relationship between split disciplines and overall extreme ultra-triathlon (EUT) performance and verify the relationship among physiological and neuromuscular measurements with both fractional and total EUT performance while checking which variables could predict partial and overall EUT race time. Methods: Eleven volunteers (37 ± 6 years; 176.9 ± 6.1 cm; 77.9 ± 10.9 kg) performed two maximal graded tests (cycling and running) for physiological measurements and muscle strength/power tests to assess neuromuscular functions. Results: The correlation of swimming split times to predict overall EUT race times was lower than for cycling and running split times (r2 = 0.005; p > .05; r2 = 0.949; p < .001 and r2 = 0.925; p < .001, respectively). VO2peak obtained during running test (VO2peakrun) and VT power output assessed during cycling test (VTPO) were the highest predictors of cycling performance (r2 = 0.92; p = .017), whereas VO2peakrun and peakpower output in the cycling test (PPO) were the highest predictors of running performance (r2 = 0.94; p = .008). Conclusion: VO2peakrun and VTPO, associated to jump height assessed during countermovement jump (CMJ) test were the highest correlated variables to predict total EUT performance (r2 = 0.99; p = .007). In practical terms, coaches should include the assessment of VO2peakrun, VTPO, and CMJ to evaluate the athletes' status and monitor their performance throughout the season. Future studies should test how the improvement of these variables would affect EUT performance during official races.

Neuromuscular changes after a Long Distance Triathlon World Championship

ABSTRACTThis study aimed to determine the neuromuscular changes in muscle contractile properties and countermovement jump (CMJ) performance after a long distance (LD) triathlon, inquiring to what extent it is influenced by gender and the evaluated muscle, and to explore for response differences. Four elite (2 females and 2 males) and 18 well-trained triathletes (3 females and 15 males) who competed in the 2019 LD Triathlon World Championship undergone, prior and post-race, a CMJ and a muscle contractile properties assessment in vastus lateralis (VL) and biceps femoris (BF) using tensiomyography. A mixed ANOVA was carried out to detect triathletes' neuromuscular changes after the competition. A large decrease in jump height and flight time was found in CMJ (p = 0.001, ηp2 = 0.767) with gender differences (ηp2 = 0.308). contraction (Tc), delay (Td) and sustain times (Ts) also showed a large decrease (p = 0.001, ηp2 = 0.174-0.413). However, maximum radial muscle belly displacement was not altered by the competition, but did greatly increase radial displacement velocity (p = 0.031; ηp2 = 0.212). No gender differences were found in contractile properties. Correlation analysis between race performance and the jumping and tensiomyography parameters only showed a moderate negative correlation with Tc of the BF in pre- and post-competition (r = -0.44; -0.43; p = 0.05). In conclusion, triathletes after a LD World Championship suffer a sharp drop in jump performance and variations in VL's and BF's contractile properties, showing decreases in Tc, Td and Ts without gender differences. The regular use of these parameters can allow the monitoring of triathlete's neuromuscular fatigue and aid in the distribution of more efficient loads in their training cycles.HighlightsTrainers and researchers in neuromuscular fatigue can have reference data of elite and well-trained triathletes after performing LD race.The magnitude of change in the CMJ and the contractile properties of BF and VL achieved in competition by these elite reference triathletes can guide to modulate triathletes training.The regular use of the parameters using these references can allow an exhaustive neuromuscular fatigue monitoring during the sessions or training cycles throughout the season.

VO2max (VO2peak) in elite athletes under high-intensity interval training: A meta-analysis

Consensus is lacking regarding whether high-intensity interval training (HIIT) effectively improves VO₂max (VO₂peak) in elite athletes (Athlete must be involved in regular competition at the national level). This meta-analysis compared the effects of HIIT and conventional training methods (continuous training, repeated-sprint training, high volume low-intensity training, high-intensity continuous running, sprint-interval training, moderate-intensity continuous training)on VO₂max in elite athletes. Nine studies were included, comprising 176 elite athletes (80 female). Compared to that with conventional training, VO₂max was significantly increased after HIIT (overall: 0.58 [0.30, 0.87], I² = 0.49, P = 0.03; males: 0.41 [0.06, 0.76], I² = 0%, P = 0.89). VO₂max had positive training effects when the HIIT recovery period had an interval time ≥2 min (0.44 [0.03, 0.84], I² = 0%, P = 0.99) and recovery phase intensity ≤40% (0.38 [0.05, 0.71], I² = 0%, P = 0.96). Thus, HIIT shows superiority over conventional training methods in improving VO₂max, promoting aerobic capacity, in elite athletes.

Downhill Sections Are Crucial for Performance in Trail Running Ultramarathons-A Pacing Strategy Analysis

Trail running is an increasingly popular discipline, especially over long-distance races (>42.195 km). Pacing strategy, i.e., how athletes modulate running speed for managing their energies during a race, appears to have a significant impact on overall performance. The aims of this study were to investigate whether performance level, terrain (i.e., uphill or downhill) and race stage affect pacing strategy and whether any interactions between these factors are evident. Race data from four race courses, with multiple editions (total races = 16), were retrieved from their respective events websites. A linear mixed effect model was applied to the full dataset, as well as to two subgroups of the top 10 male and female finishers, to assess potential differences in pacing strategy (i.e., investigated in terms of relative speed). Better finishers (i.e., athletes ranking in the best positions) tend to run downhill sections at higher relative speeds and uphill sections at lower relative speeds than slower counterparts (p < 0.001). In the later race stages, the relative speed decrease is larger in downhill sections than in uphill ones (p < 0.001) and in downhill sections, slower finishers perform systematically worse than faster ones, but the performance difference (i.e., between slower and faster finishers) becomes significantly larger in the later race stages (p < 0.001). Among elite athletes, no difference in pacing strategy between faster and slower finishers was found (p > 0.05). Both men (p < 0.001) and women (p < 0.001), in the later race stages, slow down more in downhill sections than in uphill ones. Moreover, elite women tend to slow down more than men (p < 0.001) in the later race stages, regardless of the terrain, in contrast to previous studies focusing on road ultramarathons. In conclusion, running downhill sections at higher relative speeds, most likely due to less accentuated fatigue effects, as well as minimizing performance decrease in the later race stages in downhill sections, appears to be a hallmark of the better finishers.

The Effects of Sodium Phosphate Supplementation on the Cardiorespiratory System and Gross Efficiency during Exercise under Hypoxia in Male Cyclists: A Randomized, Placebo-Controlled, Cross-Over Study

The main aim of this study was to evaluate the effects of six days of tri-sodium phosphate (SP) supplementation on the cardiorespiratory system and gross efficiency (GE) during exercise under hypoxia in cyclists. Twenty trained male cyclists received SP (50 mg·kg⁻¹ of fat-free mass/day) or placebo for six days in a randomized, cross-over study, with a three-week washout period between supplementation phases. Before and after each supplementation phase, the subjects performed an incremental exercise test to exhaustion under normobaric hypoxia (FiO₂ = 16%, ~2500 m). It was observed that short-term SP supplementation led to a decrease in heart rate, an increase in stroke volume, and an improvement in oxygen pulse (VO₂/HR) during low and moderate-intensity exercise under hypoxia. These changes were accompanied by an increase in the serum inorganic phosphate level by 8.7% (p < 0.05). No significant changes were observed in serum calcium levels. GE at a given workload did not change significantly after SP supplementation. These results indicated that SP promotes improvements in the efficiency of the cardiorespiratory system during exercise in a hypoxic environment. Thus, SP supplementation may be beneficial for endurance exercise in hypoxia.

Changes in Sex Difference in Time-Limited Ultra-Cycling Races from 6 Hours to 24 Hours

Background and objective: Existing research shows that the sex differences in distance-limited ultra-cycling races decreased with both increasing race distance and increasing age. It is unknown, however, whether the sex differences in time-limited ultra-cycling races will equally decrease with increasing race distance and age. This study aimed to examine the sex differences regarding performance for time-limited ultra-cycling races (6, 12, and 24 h). Methods: Data were obtained from the online database of the Ultra-Cycling Marathon Association (UMCA) of time-limited ultra-cycling races (6, 12, and 24 h) from the years 1983–2019. A total of 18,241 race results were analyzed to compare cycling speed between men and women by calendar year, age group (<29; 30–39; 40–49; 50–59; 60–69; >70 years), and race duration. Results: The participation of both men (85.1%) and women (14.9%) increased between 1983 and 2019. The age of peak performance was between 40 and 59 years for men and between 30 and 59 years for women. Between 2000 and 2019, more men (63.1% of male participants and 52.2% of female participants) competed in 24 h races. In the 24 h races, the sex difference decreased significantly in all age groups. Men cycled 9.6% faster than women in the 12 h races and 4% faster in the 24 h races. Both women and men improved their performance significantly across the decades. Between 2000 and 2019, the improvement in the 24 h races were 15.6% for men and 21.9% for women. Conclusion: The sex differences in cycling speed decreased between men and women with increasing duration of ultra-cycling races and with increasing age. Women showed a greater performance improvement than men in the last 20 years. The average cycling speed of men and women started to converge in the 24 h races.

Exploring the relationship between gut microbiota and exercise: short-chain fatty acids and their role in metabolism

The human body is host to a multitude of bacteria, fungi, viruses and other species in the intestine, collectively known as the microbiota. Dietary carbohydrates which bypass digestion and absorption are broken down and fermented by the microbiota to produce short-chain fatty acids (SCFAs). Previous research has established the role of SCFAs in the control of human metabolic pathways. In this review, we evaluate SCFAs as a metabolic regulator and how they might improve endurance performance in athletes. By looking at research conducted in animal models, we identify several pathways downstream of SCFAs, either directly modulating metabolic pathways through second messenger pathways or through neuronal pathways, that contribute to energy utilisation. These pathways contribute to efficient energy metabolism and are thus key to maximising substrate utilisation in endurance exercise. Future research may prove the usefulness of targeted dietary interventions allowing athletes to maximise their performance in competition.

Do Sex Differences in Physiology Confer a Female Advantage in Ultra-Endurance Sport?

Ultra-endurance has been defined as any exercise bout that exceeds 6 h. A number of exceptional, record-breaking performances by female athletes in ultra-endurance sport have roused speculation that they might be predisposed to success in such events. Indeed, while the male-to-female performance gap in traditional endurance sport (e.g., marathon) remains at ~ 10%, the disparity in ultra-endurance competition has been reported as low as 4% despite the markedly lower number of female participants. Moreover, females generally outperform males in extreme-distance swimming. The issue is complex, however, with many sports-specific considerations and caveats. This review summarizes the sex-based differences in physiological functions and draws attention to those which likely determine success in extreme exercise endeavors. The aim is to provide a balanced discussion of the female versus male predisposition to ultra-endurance sport. Herein, we discuss sex-based differences in muscle morphology and fatigability, respiratory-neuromechanical function, substrate utilization, oxygen utilization, gastrointestinal structure and function, and hormonal control. The literature indicates that while females exhibit numerous phenotypes that would be expected to confer an advantage in ultra-endurance competition (e.g., greater fatigue resistance, greater substrate efficiency, and lower energetic demands), they also exhibit several characteristics that unequivocally impinge on performance (e.g., lower O₂-carrying capacity, increased prevalence of GI distress, and sex-hormone effects on cellular function/injury risk). Crucially, the advantageous traits may only manifest as ergogenic in the extreme endurance events which, paradoxically, are those that females less often contest. The title question should be revisited in the coming years, when/if the number of female participants increases.

Exercise Intensity during Olympic-Distance Triathlon in Well-Trained Age-Group Athletes: An Observational Study

The aim of this study was to examine the exercise intensity during the swimming, cycling, and running legs of nondraft legal, Olympic-distance triathlons in well-trained, age-group triathletes. Seventeen male triathletes completed incremental swimming, cycling, and running tests to exhaustion. Heart rate (HR) and workload corresponding to aerobic and anaerobic thresholds, maximal workloads, and maximal HR (HR_max) in each exercise mode were analyzed. HR and workload were monitored throughout the race. The intensity distributions in three HR zones for each discipline and five workload zones in cycling and running were quantified. The subjects were then assigned to a fast or slow group based on the total race time (range, 2 h 07 min–2 h 41 min). The mean percentages of HR_max in the swimming, cycling, and running legs were 89.8% ± 3.7%, 91.1% ± 4.4%, and 90.7% ± 5.1%, respectively, for all participants. The mean percentage of HR_max and intensity distributions during the swimming and cycling legs were similar between groups. In the running leg, the faster group spent relatively more time above HR at anaerobic threshold (AnT) and between workload at AnT and maximal workload. In conclusion, well-trained male triathletes performed at very high intensity throughout a nondraft legal, Olympic-distance triathlon race, and sustaining higher intensity during running might play a role in the success of these athletes.

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.

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.

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.

Changes in cardiac and muscle biomarkers following an uphill-only marathon

The aim of the study was to evaluate changes in cardiac troponin I levels (cTnI) and the main biomarkers of skeletal muscle damage after an uphill-only marathon, along with its relationship with athletes' physiological parameters. Twenty-two runners participated in the "Supermaratona dell'Etna" (43 km, 0-2850 m AMSL). Before and immediately after the race, body mass and hydration status were measured together with blood sampling. At the end of the race, mean cTnI increased significantly in all athletes (mean +900%), and in 52% of them the cTnI values were over the normal range. Mean creatinine and cortisol increased significantly (by 30.5% and 291.4%), while C-reactive protein levels did not change significantly. Then, an uphill-only marathon showed a significant increase in cardiac and skeletal muscle blood biomarkers of injury, and cTnI levels were not significantly correlated with age, body mass index, V̇O₂max, training status, ultra-endurance training experience, race time and blood parameters.

Physiological intensity profile, exercise load and performance predictors of a 65-km mountain ultra-marathon

The aims of the study were to describe the physiological profile of a 65-km (4000-m cumulative elevation gain) running mountain ultra-marathon (MUM) and to identify predictors of MUM performance. Twenty-three amateur trail-runners performed anthropometric evaluations and an uphill graded exercise test (GXT) for VO_2max, ventilatory thresholds (VTs), power outputs (PMax, PVTs) and heart rate response (HRmax, HR@VTs). Heart rate (HR) was monitored during the race and intensity was expressed as: Zone I (<VT1), Zone II (VT1-VT2), Zone III (>VT2) for exercise load calculation (training impulse, TRIMP). Mean race intensity was 77.1%±4.4% of HRmax distributed as: 85.7%±19.4% Zone I, 13.9%±18.6% Zone II, 0.4%±0.9% Zone III. Exercise load was 766±110 TRIMP units. Race time (11.8±1.6h) was negatively correlated with VO_2max (r = -0.66, P <0.001) and PMax (r = -0.73, P <0.001), resulting these variables determinant in predicting MUM performance, whereas exercise thresholds did not improve performance prediction. Laboratory variables explained only 59% of race time variance, underlining the multi-factorial character of MUM performance. Our results support the idea that VT1 represents a boundary of tolerable intensity in this kind of events, where exercise load is extremely high. This information can be helpful in identifying optimal pacing strategies to complete such extremely demanding MUMs.

Is Marathon Training Harder than the Ironman Training? An ECO-method Comparison

Purpose: To compare the absolute and relative training load of the Marathon (42k) and the Ironman (IM) training in recreational trained athletes.

Methods: Fifteen Marathoners and Fifteen Triathletes participated in the study. Their performance level was the same relative to the sex's absolute winner at the race. No differences were presented neither in age, nor in body weight, height, BMI, running VO_2max max, or endurance training experience (p > 0.05). They all trained systematically for their respective event (IM or 42k). Daily training load was recorded in a training log, and the last 16 weeks were compared. Before this, gas exchange and lactate metabolic tests were conducted in order to set individual training zones. The Objective Load Scale (ECOs) training load quantification method was applied. Differences between IM and 42k athletes' outcomes were assessed using Student's test and significance level was set at p < 0.05.

Results: As expected, Competition Time was significantly different (IM 11 h 45 min ± 1 h 54 min vs. 42k 3 h 6 min ± 28 min, p < 0.001). Similarly, Training Weekly Avg Time (IM 12.9 h ± 2.6 vs. 42k 5.2 ± 0.9), and Average Weekly ECOs (IM 834 ± 171 vs. 42k 526 ± 118) were significantly higher in IM (p < 0.001). However, the Ratio between Training Load and Training Time was superior for 42k runners when comparing ECOs (IM 65.8 ± 11.8 vs. 42k 99.3 ± 6.8) (p < 0.001). Finally, all ratios between training time or load vs. Competition Time were superior for 42k (p < 0.001) (Training Time/Race Time: IM 1.1 ± 0.3 vs. 42k 1.7 ± 0.5), (ECOs Training Load/Race Time: IM 1.2 ± 0.3 vs. 42k 2.9 ± 1.0).

Conclusions: In spite of IM athletes' superior training time and total or weekly training load, when comparing the ratios between training load and training time, and training time or training load vs. competition time, the preparation of a 42k showed to be harder.

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.

Moving in extreme environments: extreme loading; carriage versus distance

This review addresses human capacity for movement in the context of extreme loading and with it the combined effects of metabolic, biomechanical and gravitational stress on the human body. This topic encompasses extreme duration, as occurs in ultra-endurance competitions (e.g. adventure racing and transcontinental races) and expeditions (e.g. polar crossings), to the more gravitationally limited load carriage (e.g. in the military context). Juxtaposed to these circumstances is the extreme metabolic and mechanical unloading associated with space travel, prolonged bedrest and sedentary lifestyle, which may be at least as problematic, and are therefore included as a reference, e.g. when considering exposure, dangers and (mal)adaptations. As per the other reviews in this series, we describe the nature of the stress and the associated consequences; illustrate relevant regulations, including why and how they are set; present the pros and cons for self versus prescribed acute and chronic exposure; describe humans' (mal)adaptations; and finally suggest future directions for practice and research. In summary, we describe adaptation patterns that are often U or J shaped and that over time minimal or no load carriage decreases the global load carrying capacity and eventually leads to severe adverse effects and manifest disease under minimal absolute but high relative loads. We advocate that further understanding of load carrying capacity and the inherent mechanisms leading to adverse effects may advantageously be studied in this perspective. With improved access to insightful and portable technologies, there are some exciting possibilities to explore these questions in this context.

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.

Nutrition habits in 24-hour mountain bike racers

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.

Energy balance of triathletes during an ultra-endurance event

The nutritional strategy during an ultra-endurance triathlon (UET) is one of the main concerns of athletes competing in such events. The purpose of this study is to provide a proper characterization of the energy and fluid intake during real competition in male triathletes during a complete UET and to estimate the energy expenditure (EE) and the fluid balance through the race.

METHODS

Eleven triathletes performed a UET. All food and drinks ingested during the race were weighed and recorded in order to assess the energy intake (EI) during the race. The EE was estimated from heart rate (HR) recordings during the race, using the individual HR-oxygen uptake (Vo2) regressions developed from three incremental tests on the 50-m swimming pool, cycle ergometer, and running treadmill. Additionally, body mass (BM), total body water (TBW) and intracellular (ICW) and extracellular water (ECW) were assessed before and after the race using a multifrequency bioimpedance device (BIA).

RESULTS

Mean competition time and HR was 755 ± 69 min and 137 ± 6 beats/min, respectively. Mean EI was 3643 ± 1219 kcal and the estimated EE was 11,009 ± 664 kcal. Consequently, athletes showed an energy deficit of 7365 ± 1286 kcal (66.9% ± 11.7%). BM decreased significantly after the race and significant losses of TBW were found. Such losses were more related to a reduction of extracellular fluids than intracellular fluids.

CONCLUSIONS

Our results confirm the high energy demands of UET races, which are not compensated by nutrient and fluid intake, resulting in a large energy deficit.

Running economy, not aerobic fitness, independently alters thermoregulatory responses during treadmill running

We sought to determine the independent influence of running economy (RE) and aerobic fitness [maximum oxygen consumption (V̇O 2max)] on thermoregulatory responses during treadmill running by conducting two studies. In study 1, seven high (HI-FIT: 61 ± 5 ml O2 · kg(-1) · min(-1)) and seven low (LO-FIT: 45 ± 4 ml O2 · kg(-1) · min(-1)) V̇O 2max males matched for physical characteristics and RE (HI-FIT: 200 ± 21; LO-FIT: 200 ± 18 ml O2 · kg(-1) · km(-1)) ran for 60 min at 1) 60%V̇O 2max and 2) a fixed metabolic heat production (Hprod) of 640 W. In study 2, seven high (HI-ECO: 189 ± 15.3 ml O2 · kg(-1) · km(-1)) and seven low (LO-ECO: 222 ± 10 ml O2 · kg(-1) · km(-1)) RE males matched for physical characteristics and V̇O 2max (HI-ECO: 60 ± 3; LO-ECO: 61 ± 7 ml O2 · kg(-1) · min(-1)) ran for 60 min at a fixed 1) speed of 10.5 km/h and 2) Hprod of 640 W. Environmental conditions were 25.4 ± 0.8°C, 37 ± 12% RH. In study 1, at Hprod of 640 W, similar changes in esophageal temperature (ΔTes; HI-FIT: 0.63 ± 0.20; LO-FIT: 0.63 ± 0.22°C; P = 0.986) and whole body sweat losses (WBSL; HI-FIT: 498 ± 66; LO-FIT: 497 ± 149 g; P = 0.984) occurred despite different relative intensities (HI-FIT: 55 ± 6; LO-FIT: 39 ± 2% V̇O 2max; P < 0.001). At 60% V̇O 2max, ΔTes (P = 0.029) and WBSL (P = 0.003) were greater in HI-FIT (1.14 ± 0.32°C; 858 ± 130 g) compared with LO-FIT (0.73 ± 0.34°C; 609 ± 123 g), as was Hprod (HI-FIT: 12.6 ± 0.9; LO-FIT: 9.4 ± 1.0 W/kg; P < 0.001) and the evaporative heat balance requirement (Ereq; HI-FIT: 691 ± 74; LO-FIT: 523 ± 65 W; P < 0.001). Similar sweating onset ΔTes and thermosensitivities occurred between V̇O 2max groups. In study 2, at 10.5 km/h, ΔTes (1.16 ± 0.31 vs. 0.78 ± 0.28°C; P = 0.017) and WBSL (835 ± 73 vs. 667 ± 139 g; P = 0.015) were greater in LO-ECO, as was Hprod (13.5 ± 0.6 vs. 11.3 ± 0.8 W/kg; P < 0.001) and Ereq (741 ± 89 vs. 532 ± 130 W; P = 0.007). At Hprod of 640 W, ΔTes (P = 0.910) and WBSL (P = 0.710) were similar between HI-ECO (0.55 ± 0.31°C; 501 ± 88 g) and LO-ECO (0.57 ± 0.16°C; 483 ± 88 g), but running speed was different (HI-ECO: 8.2 ± 0.6; LO-ECO: 7.2 ± 0.4 km/h; P = 0.025). In conclusion, thermoregulatory responses during treadmill running are not altered by V̇O 2max, but by RE because of differences in Hprod and Ereq.

Factors influencing pacing in triathlon

Triathlon is a multisport event consisting of sequential swim, cycle, and run disciplines performed over a variety of distances. This complex and unique sport requires athletes to appropriately distribute their speed or energy expenditure (ie, pacing) within each discipline as well as over the entire event. As with most physical activity, the regulation of pacing in triathlon may be influenced by a multitude of intrinsic and extrinsic factors. The majority of current research focuses mainly on the Olympic distance, whilst much less literature is available on other triathlon distances such as the sprint, half-Ironman, and Ironman distances. Furthermore, little is understood regarding the specific physiological, environmental, and interdisciplinary effects on pacing. Therefore, this article discusses the pacing strategies observed in triathlon across different distances, and elucidates the possible factors influencing pacing within the three specific disciplines of a triathlon.

Effects of deceptive running speed on physiology, perceptual responses, and performance during sprint-distance triathlon

OBJECTIVE

This study examined the effects of speed deception on performance, physiological and perceptual responses, and pacing during sprint-distance triathlon running.

METHODS

Eight competitive triathletes completed three simulated sprint-distance triathlons (0.75 km swim, 20 km bike, 5 km run) in a randomised order, with swimming and cycling sections replicating baseline triathlon performance. During the first 1.66 km of the run participants maintained an imposed speed, completing the remaining 3.33 km as quickly as possible. Although the participants were informed that initially prescribed running speed would reflect baseline performance, this was true during only one trial (Tri-Run100%). As such, other trials were either 3% faster (Tri-Run103%), or 3% slower (Tri-Run97%) than baseline during this initial period.

RESULTS

Performance during Tri-Run103% (1346±108 s) was likely faster than Tri-Run97% (1371±108 s), and possibly faster than Tri-Run100% (1360±125 s), with these differences likely to be competitively meaningful. The first 1.66 km of Tri-Run103% induced greater physiological strain compared to other conditions, whilst perceptual responses were not significantly different between trials.

CONCLUSIONS

It appears that even during 'all-out' triathlon running, athletes maintain some form of 'reserve' capacity which can be accessed by deception. This suggests that expectations and beliefs have a practically meaningful effect on pacing and performance during triathlon, although it is apparent that an individual's conscious intentions are secondary to the brains sensitivity to potentially harmful levels of physiological and perceptual strain.

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

Training-Intensity Distribution During an Ironman Season: Relationship With Competition Performance

Purpose:

To describe training loads during an Ironman training program based on intensity zones and observe training–performance relationships.

Methods:

Nine triathletes completed a program with the same periodization model aiming at participation in the same Ironman event. Before and during the study, subjects performed ramp-protocol tests, running, and cycling to determine aerobic (AeT) and anaerobic thresholds (AnT) through gas-exchange analysis. For swimming, subjects performed a graded lactate test to determine AeT and AnT. Training was subsequently controlled by heart rate (HR) during each training session over 18 wk. Training and the competition were both quantified based on the cumulative time spent in 3 intensity zones: zone 1 (low intensity; <AeT), zone 2 (moderate intensity; between AeT and AnT), and zone 3 (high intensity; >AnT).

Results:

Most of training time was spent in zone 1 (68% ± 14%), whereas the Ironman competition was primarily performed in zone 2 (59% ± 22%). Significant inverse correlations were found between both total training time and training time in zone 1 vs performance time in competition (r = –.69 and –.92, respectively). In contrast, there was a moderate positive correlation between total training time in zone 2 and performance time in competition (r = .53) and a strong positive correlation between percentage of total training time in zone 2 and performance time in competition (r = .94).

Conclusions:

While athletes perform with HR mainly in zone 2, better performances are associated with more training time spent in zone 1. A high amount of cycling training in zone 2 may contribute to poorer overall performance.

Predictive importance of anthropometric and training data in recreational male Ironman triathletes and marathon runners: comment on the study by Gianoli, et al. (2012)

Anthropometric and training data have been reported as statistically significant predictors of race performance in endurance events. However, it is well established that physiological characteristics, i.e., maximal oxygen uptake (VO2max), the use of a high percentage of VO2max during sustained exercise, and work efficiency are predominant predictors of performance in those events. Thus, the essential issue is whether the anthropometric and training data give additional predictive power beyond these other measures.

Sex difference in Double Iron ultra-triathlon performance

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Race diet of finishers and non-finishers in a 100 mile (161 km) mountain footrace

OBJECTIVE

To determine if food and fluid intake is related to completion of a 161-km ultramarathon.

METHODS

Sixteen consenting runners in the Western States Endurance Run participated in the study. Race diets were analyzed using Nutritionist Pro software. Both total intake and intake by race segment (3 total) were evaluated.

RESULTS

Six of 16 subjects completed the race (finishers) in 27.0 ± 2.3 hours (mean ± SD). Non-finishers completed 96.5 ± 20.5 km in 17.0 ± 3.9 h. Overall consumption rates of kilocalories, carbohydrate, fat, and sodium were significantly greater (P < 0.05) in finishers (4.6 ± 1.7 kcal/kg/h, 0.98 ± 0.43 g carbohydrate/kg/h, 0.06 ± 0.03 g fat/kg/h, 10.2 ± 6.0 mg sodium/kg/h) versus non-finishers (2.5 ± 1.3 kcal/kg/h, 0.56 ± 0.32 g carbohydrate/kg/h, 0.02 ± 0.02 g fat/kg/h, 5.2 ± 3.0 mg sodium/kg/h). Kilocalorie, fat, fluid, and sodium consumption rates during segment 1 (first 48 km) were significantly greater in finishers than in non-finishers.

CONCLUSIONS

Completion of this 161-km race was related to greater fuel, fluid, and sodium consumption rates. However, intake ranges for the finishers were large, so factors other than race diet may have contributed to the successful completion of the race.

Nutritional behavior of cyclists during a 24-hour team relay race: a field study report

Background

Information about behavior of energy intake in ultra-endurance cyclists during a 24-hour team relay race is scarce. The nutritional strategy during such an event is an important factor which athletes should plan carefully before the race. The purpose of this study was to examine and compare the nutritional intake of ultra-endurance cyclists during a 24-hour team relay race with the current nutritional guidelines for endurance events. Additionally, we analyzed the relationship among the nutritional and performance variables.

Methods

Using a observational design, nutritional intake of eight males (mean ± SD: 36.7 ± 4.7 years; 71.6 ± 4.9 kg; 174.6 ± 7.3 cm; BMI 23.5 ± 0.5 kg/m²) participating in a 24-hour team relay cycling race was assessed. All food and fluid intake by athletes were weighed and recorded. Additionally, distance and speed performed by each rider were also recorded. Furthermore, before to the race, all subjects carried out an incremental exercise test to determine two heart rate-VO₂ regression equations which were used to estimate the energy expenditure.

Results

The mean ingestion of macronutrients during the event was 943 ± 245 g (13.1 ± 4.0 g/kg) of carbohydrates, 174 ± 146 g (2.4 ± 1.9 g/kg) of proteins and 107 ± 56 g (1.5 ± 0.7 g/kg) of lipids, respectively. This amount of nutrients reported an average nutrient intake of 22.8 ± 8.9 MJ which were significantly lower compared with energy expenditure 42.9 ± 6.8 MJ (P = 0.012). Average fluid consumption corresponded to 10497 ± 2654 mL. Mean caffeine ingestion was 142 ± 76 mg. Additionally, there was no relationship between the main nutritional variables (i.e. energy intake, carbohydrates, proteins, fluids and caffeine ingestion) and the main performance variables (i.e. distance and speed).

Conclusions

A 24-hour hours cycling competition in a team relay format elicited high energy demands which were not compensated by energy intake of the athletes despite that dietary consumption of macronutrients did not differ to the nutritional guidelines for longer events.

Lipid profile, apolipoprotein A-I and oxidative stress in professional footballers, sedentary individuals, and their relatives

OBJECTIVE

To evaluate whether lipid profile (LP), apolipoprotein A-1 (apo A-I) and malondialdehyde (MDA) have any relationship with physical exercise by comparing the groups of footballers (FG) with sedentary individuals (CG) and their relatives (RFG and RCG).

SUBJECTS AND METHODS

Twenty individuals from FG and CG, 60 from RFG, and 57 from RCG were studied.

RESULTS

FG showed lower levels of total cholesterol (119.5 ± 37.9 mg/dL), LDL-cholesterol fraction (53.6 ± 30.3), apo A-I (116.7 ± 11.9), and higher level of HDL-cholesterol fraction (HDLc) (49.7 ± 8.5) compared to RFG (148.3 ± 36.9, P = 0.02; 82.4 ± 37.7, P < 0.01; 124.6 ± 10.2, P = 0.03; and 42.7 ± 7.7, P < 0.01; respectively). Moreover, FG had reduced levels of MDA (101.0 ± 77.0 ng/mL) compared to CG (290.0 ± 341.0, P = 0.03) and RFG (209.9 ± 197.5, P = 0.04).

CONCLUSIONS

These results suggest an association between physical exercise and lower levels of MDA in FG. Physical activity seems to promote beneficial effects on the LP regardless of the genetic influence considering HDLc levels.

Central European triathletes dominate Double Iron ultratriathlon - analysis of participation and performance 1985-2011

Background

A recent study showed that European triathletes performed faster in Double Iron ultratriathlons than North American athletes. The present study analyzed triathletes participating in Double Iron ultratriathlons to determine the origin of the fastest Double Iron ultratriathletes, focusing on European countries.

Methods

Participation and performance trends of finishers in Double Iron ultratriathlons from 1985–2011 of the different countries were investigated. Additionally, the performance trends of the top three women and men overall from 2001–2011 were analyzed.

Results

A total of 1490 finishers originated from 24 different European countries and the United States. The number of European triathletes increased for both women (r² = 0.56; P < 0.01) and men (r² = 0.63; P < 0.01). The number of the North American triathletes increased for women (r² = 0.25; P < 0.01), but not for men (r² = 0.02; P > 0.05). Hungarian triathletes showed a significant improvement in both overall race times and in cycling split times, Swiss triathletes improved both their swim and run times, and French triathletes improved their swim times.

Conclusion

Men and women triathletes from Central European countries such as France, Germany, Switzerland, and Hungary improved Double Iron ultratriathlon overall race times and split times during the 26-year period. The reasons might be the social and economic factors required to be able to participate in such an expensive and lavish race. Also, a favorable climate may provide the ideal conditions for successful training. Future studies need to investigate the motivational aspects of European ultraendurance athletes.

Physiological determinants of speciality of elite middle- and long-distance runners

The aim of this study was to determine which physiological variables predict excellence in middle- and long-distance runners. Forty middle-distance runners (age 23 ± 4 years, body mass 67.2 ± 5.9 kg, stature 1.80 ± 0.05 m, VO(2max) 65.9 ± 4.5 ml · kg(-1) · min(-1)) and 32 long-distance runners (age 25 ± 4 years, body mass 59.8 ± 5.1 kg, stature 1.73 ± 0.06 m, VO(2max) 71.6 ± 5.0 ml · kg(-1) · min(-1)) competing at international standard performed an incremental running test to exhaustion. Expired gas analysis was performed breath-by-breath and maximum oxygen uptake (VO(2max)) and two ventilatory thresholds (VT(1) and VT(2)) were calculated. Long-distance runners presented a higher VO(2max) than middle-distance runners when expressed relative to body mass (P < 0.001, d = 1.18, 95% CI [0.68, 1.68]). At the intensities corresponding to VT(1) and VT(2), long-distance runners showed higher values for VO(2) expressed relative to body mass or %VO(2max), speed and oxygen cost of running (P < 0.05). When oxygen uptake was adjusted for body mass, differences between groups were consistent. Logistic binary regression analysis showed that VO(2max) (expressed as l · min(-1) and ml · kg(-1) · min(-1)), VO(2VT2) (expressed as ml · kg(-0.94) · min(-1)), and speed at VT(2) (v(VT2)) categorized long-distance runners. In addition, the multivariate model correctly classified 84.7% of the athletes. Thus, VO(2max), VO(2VT2), and v(VT2) discriminate between elite middle-distance and long-distance runners.

The COL5A1 Gene, Ultra-Marathon Running Performance, and Range of Motion

Purpose:

Endurance running performance is a multifactorial phenotype that is strongly associated with running economy. Sit and reach range of motion (SR ROM) is negatively associated with running economy, suggesting that reduced SR ROM is advantageous for endurance running performance. The COL5A1 gene has been associated with both endurance running performance and SR ROM in separate cohorts. The aim of this study was to investigate whether COL5A1 is associated with ultra-marathon running performance and whether this relationship could be partly explained by prerace SR ROM.

Methods:

Seventy-two runners (52 male, 20 female) were recruited from the 56 km Two Oceans ultra-marathon and were assessed for prerace SR ROM. The cohort was genotyped for the COL5A1 BsfUI restriction fragment length polymorphism, and race times were collected after the event.

Results:

Participants with a TT genotype (341 ± 41 min, N = 21) completed the 56 km Two Oceans ultra-marathon significantly (P = 0.014) faster than participants with TC and CC genotypes (365 ± 39 min, N = 50). The COL5A1 genotype and age accounted for 19% of performance variance. When the cohort was divided into performance and flexibility quadrants, the T allele was significantly (P = 0.044) over-represented within the fast and inflexible quadrant.

Conclusion:

The COL5A1 genotype was found to be significantly associated with performance in a 56 km ultra-endurance run. This study confirms previous findings and it furthers our understanding of the relationships among ROM, COL5A1, and endurance running performance. We continue to speculate that the COL5A1 gene alters muscle-tendon stiffness.

The Role of Resistance Training in Distance Running

The main determinants of distance running performance include V̇O2max, lactate threshold (LT), and running economy (RE). The conventional way to achieve improvements in these areas is through endurance training due to the principle of training specificity. Some physiologists believe that the addition of resistance training is beneficial to distance running in the form of injury prevention and preparing runners for pace surge and sprint finishes. To date, it is consistent among findings that resistance training does not improve nor compromise V̇O2max in trained distance runners while LT improvements are only found in untrained individuals. RE has been shown to improve significantly post resistance training possibly due to neuromuscular changes including a shortening of the stretch-shortening cycle and an increase in muscle stiffness. The primary purpose of this review is to understand the impact of resistance training on the various factors known to affect distance running performance and to recommend resistance training guidelines for the distance runner to adhere to.

The relationships between science and sport: application in triathlon

The relationships between sport sciences and sports are complex and changeable, and it is not clear how they reciprocally influence each other. By looking at the relationship between sport sciences and the "new" (~30-year-old) sport of triathlon, together with changes in scientific fields or topics that have occurred between 1984 and 2006 (278 publications), one observes that the change in the sport itself (eg, distance of the events, wetsuit, and drafting) can influence the specific focus of investigation. The sport-scientific fraternity has successfully used triathlon as a model of prolonged strenuous competition to investigate acute physiological adaptations and trauma, as support for better understanding cross-training effects, and, more recently, as a competitive sport with specific demands and physiological features. This commentary discusses the evolution of the scientific study of triathlon and how the development of the sport has affected the nature of scientific investigation directly related to triathlon and endurance sport in general.