The Impact of Sex and Performance Level on Pacing Behavior in a 24-h Ultramarathon

The Use of a Just Noticeable Difference Approach to Improve Perceptual Acuity Ability in Male Runners

We were interested in micro-variations in an athlete's psychophysical state that separate peak exertion from physiological collapse. Thus, we measured perceptual acuity in runners using a classic psychophysical approach, the just noticeable difference (JND) on two standard stimuli runs at treadmill speed corresponding to 70%VO2max and 80%VO2max. Thirty-four male runners (M age = 35.26, SD = 7.33 years) first performed a maximal treadmill test to determine the speed of a standard exercise bout for the JND trials. The JND trials consisted of four 5-minute running bouts on a treadmill with 5-minute rests between bouts. For bouts 1 and 3, participants ran at the standard stimuli pace, but for bouts 2 and 4, they adjusted their speeds to achieve a level of exertion at a JND above/below the SS. They achieved differences in the final 30 seconds of the VO2 between each JND bout and the previous standard stimuli at just above (JND-A) and just below (JND-B) the JND perceived exertions. We used a Generalized Linear Model analysis to compare the JND-A and JND-B within and between ventilatory threshold groups (lower/higher) in absolute and relative VO2 and in terms of the total JND magnitude. The magnitude of JND-A was greater than that of JND-B at 70%VO2max and 80%VO2max in absolute units (70%VO2 Δ = 2.62; SE = 0.37; p < .001; 80%VO2 Δ = 1.67; SE = 0.44; p = .002) and in relative units (70%VO2max Δ = 4.70; SE = 0.66; p < .001; 80%VO2max Δ = 2.96; SE = 0.80; p = .002). The total magnitude was greater in the 70%VO2max trial than 80%VO2max in absolute units (70%VO2 M = 3.78, SE = 0.31 mL·kg-1·min-1; 80%VO2 M = 2.62, SE = 0.37 mL·kg-1·min-1; p = .020) and in relative units (70%VO2max M = 6.57, SE = 0.53%VO2max; 80%VO2max M = 4.71, SE = 0.64%VO2max; p = .030). The JND range narrowed when physiologic demand increased, for both physical (speed) and psychological (RPE) variables.

Spatiotemporal parameters and kinematics differ between race stages in trail running-a field study

Introduction

Trail running is an emerging discipline with relatively few studies performed in ecological conditions. The aim of this work was to investigate if and how spatiotemporal parameters (STP) and kinematics differ between initial and final stage of a field trial.

Methods

Twenty trail runners (10 F, 10 M) were recruited and ran a solo 9.1 km trial. During the test, participants wore a GPS watch and an IMU-based motion capture system. Running speed, elapsed time, STP and kinematics were compared between initial and final stage, separately for uphill (UH) and downhill (DH) sections.

Results

Running speed decreased in the final stage ( p < 0.05 ). Total test time was more correlated to the time elapsed in UH sections. In the final stage and in both UH and DH sections, contact time and duty factor increased, whilst stride length and flight time decreased ( p < 0.05 ). In the final stage, ankle joint was more dorsiflexed in stance and swing phases in UH sections and stance phase only in DH sections ( p < 0.05 ). In the final stage, knee joint was less extended in swing phase in UH and DH sections, as well as less extended in stance in UH sections ( p < 0.05 ). In the final stage, hip joint was less flexed in the swing phase in UH and DH sections ( p < 0.05 ). In the final stage, forward trunk lean was higher across the entire gait cycle in in UH sections ( p < 0.05 ). Trunk contralateral axial rotation was lower, in DH sections ( p < 0.05 ).

Discussion

During the final stage, results indicate a less efficient propulsion phase, in both UH and DH sections. In UH sections, results suggest lower energy generation at the ankle joint. In DH sections, results suggest that the kinematics of swing leg may play a role in sub-optimizing propulsion phase. This study demonstrates how, in UH and DH sections, similar changes in spatiotemporal parameters can be elicited by dissimilar changes in running kinematics. To optimize performance in trail running, coaches and practitioners are advised to work on different (incline-specific) aspects of running technique.

Pacing Variation in Multistage Ultramarathons: Internet-Based Cross-Sectional Study

BACKGROUND

Ultramarathon running is the most popular ultraendurance competition in terms of the number of races and runners competing annually worldwide; however, no study has compared pacing and performance over a long period.

OBJECTIVE

This study analyzes the pacing of successful finishers and nonfinishers in multistage ultramarathons worldwide.

METHODS

A total of 4079 athletes (men=3288; women=791) competing in 99 multistage ultramarathon events from 1983 to 2021 were analyzed, including the number of participants, age, gender, rank, and running speed of successful finishers.

RESULTS

The results showed a significant increase in the number of events (n=338) and a significant increase in the number of finishers and nonfinishers (n=5575) in the ultramarathons worldwide during this period. The general linear models (GLMs) of pacing variation showed nonsignificant effects for gender (F1,36.2=2.5; P=.127; ηp2=0.063) and age group (F10,10=0.6; P=.798; ηp2=0.367), but it showed a significant interaction (gender × age) effect (F10,2689=2.3; P=.008; ηp2=0.009). Post hoc analyses showed that men have a higher pacing variation than women in the under 30 years (U30), U35, U45, and U50 groups. Additionally, the fastest women's age group (U35) had the lowest pacing variation. The GLM of pacing variation by gender and event distance showed significant effects for both gender (F1,3=18.5; P<.001; ηp2=0.007) and distance (F2,3=20.1; P<.001; ηp2=0.015). Post hoc analyses showed a growing pacing variation with increasing race distance for both men and women. In addition, men had a higher variation in long events. Furthermore, there was a significant main effect for both genders (F1,3=33.7; P<.001; ηp2=0.012) and rank (F1,3=136.6; P<.001; ηp2=0.048) on performance, with men being faster than women. Pacing varied greatly due to gender (F1,3=4.0; P=.047; ηp2=0.001), with a lower (ie, more even) pacing variation for male athletes in the top 3 finishers. Male nonfinishers showed a higher performance than female nonfinishers (F1,1340=25.6; P<.001), and no difference was identified for pacing variation (F1,789=1.5; P=.228) based on gender. In addition, a weak but significant correlation (r=-0.130; P<.001) was identified between the average running speed and pacing variation for both female and male nonfinishers.

CONCLUSIONS

In summary, multistage ultramarathon competitions showed an increasing number of competitors and a higher performance challenge. Men have a higher pacing (ie, less even) variation than women, especially observed in longer events. A higher pacing variation was associated with lower performance for men, women, and nonfinishers.

Is There Evidence for the Development of Sex-Specific Guidelines for Ultramarathon Coaches and Athletes? A Systematic Review

BACKGROUND

There is evidence of sex differences in the physiology of endurance exercise, yet most of the advice and guidelines on training, racing, nutrition, and recovery for ultramarathons are based on research that has largely excluded female athletes. The objective was therefore to review the current knowledge of sex differences in ultramarathon runners and determine if sufficient evidence exists for providing separate guidelines for males and females.

METHODS

This systematic review was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Three databases were searched for studies investigating differences in elite and recreational male and female ultramarathon runners. Studies were included if they compared males and females and looked at outcomes relating to the performance or health of ultramarathon runners. The quality of the included studies was determined using the Grading of Recommendations Assessment Development and Evaluation (GRADE) approach.

RESULTS

The search strategy identified 45 studies that met the inclusion criteria. Most studies were observational in design, with only three papers based on randomised controlled trials. The overall quality of the evidence was low. Sex differences in the predictors of ultramarathon performance; physiological responses to training, racing, and recovery; chronic and acute health issues; and pacing strategies were found. There were areas with contradictory findings, and very few studies examined specific interventions.

CONCLUSION

The results from this review suggest that the development of sex-specific guidelines for ultramarathon coaches and athletes could have a significant effect on the performance and health of female runners. At present, there is insufficient high-quality evidence on which to formulate these guidelines, and further research is required.

The Effects of Sex, Age and Performance Level on Pacing in Ultra-Marathon Runners in the ‘Spartathlon’

Background

Pacing has been investigated in different kinds of ultra-marathon races, but not in one of the toughest ultra-marathons in the world, the ‘Spartathlon’.

Objective

The aim of the present study was to analyse the pacing of female and male finishers competing in the ‘Spartathlon’ in regards to their age and performance groups.

Methods

A total of 2598 runners (2255 men and 343 women) finishing ‘Spartathlon’ between 2011 and 2019 were analysed. We selected 10 checkpoints with split times corresponding to important race sections. Average running speed was calculated for each participant and the average checkpoint running speed for each of the 10 race checkpoints. Furthermore, to assess the pacing strategy of each runner, the percentage of change in checkpoint speed (CCS) in relation to the average race speed was calculated (for each of 10 checkpoints). Finally, the average change in checkpoint speed (ACCS) was calculated for each participant as a mean of the 10 CCSs.

Results

Both women and men slowed down through the first 7 checkpoints but increased running speed towards the end of the race (reverse J-shaped pacing). Men showed a significantly greater CCS in the first and second checkpoint (p < 0.01 and p < 0.05, respectively), whereas women showed a more significant change in CCS in the last checkpoint (p < 0.05). Furthermore, age and sex showed no effect on ACCS, whereas ACCS differed between the performance groups. In particular, the slowest and the fastest runners showed a more minor change in ACCS than the two medium groups of both men and women (p < 0.01).

Conclusions

In summary, successful finishers in ‘Spartathlon’ showed a reverse J-shaped pacing curve with a decrease in running speed from the start to the 7th checkpoint and an increase in running speed thereafter. This strategy was most probably due to the profile of the race course. Men showed a more significant change in checkpoint speed in the first two checkpoints, whereas women showed a more substantial change in the last checkpoint. Age and sex did not affect average checkpoint speed, whereas this speed was different between the different performance groups. The slowest and the fastest runners showed fewer changes in average checkpoint speed than the two medium groups in men and women.

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.

Consistency of pacing profile according to performance level in three different editions of the Chicago, London, and Tokyo marathons

Running pacing has become a focus of interest over recent years due to its relationship with performance, however, it is still unknown the consistency of each race in different editions. The aim of this study is to analyze the consistency of pacing profile in three consecutive editions of three marathon races. A database of 282,808 runners, compiled from three different races (Chicago, London, and Tokyo Marathon) and three editions (2017, 2018, and 2019) was analyzed. Participants were categorized according to their time performance in the marathon, every 30 min from 2:30 h to sub-6 h. The relative speed of each section for each runner was calculated as a percentage of the average speed for the entire race. The intraclass correlation coefficients (ICC) of relative speed at the different pacing section, taking into account the runner time categories, was excellent over the three marathon editions (ICC > 0.93). The artificial intelligence model showed an accuracy of 86.8% to classify the runners' data in three marathons, suggesting a consistency between editions with identifiable differences between races. In conclusion, although some differences have been observed between editions in certain sections and marathon runner categories, excellent consistency of the pacing profile was observed. The study of pacing profile in a specific marathon can, therefore, be helpful for runners, coaches and marathon organizers for planning the race and improving its organization.

Sex Differences in Endurance Running

In recent years, there has been a significant expansion in female participation in endurance (road and trail) running. The often reported sex differences in maximal oxygen uptake (VO_2max) are not the only differences between sexes during prolonged running. The aim of this narrative review was thus to discuss sex differences in running biomechanics, economy (both in fatigue and non-fatigue conditions), substrate utilization, muscle tissue characteristics (including ultrastructural muscle damage), neuromuscular fatigue, thermoregulation and pacing strategies. Although males and females do not differ in terms of running economy or endurance (i.e. percentage VO_2max sustained), sex-specificities exist in running biomechanics (e.g. females have greater non-sagittal hip and knee joint motion compared to males) that can be partly explained by anatomical (e.g. wider pelvis, larger femur-tibia angle, shorter lower limb length relative to total height in females) differences. Compared to males, females also show greater proportional area of type I fibres, are more able to use fatty acids and preserve carbohydrates during prolonged exercise, demonstrate a more even pacing strategy and less fatigue following endurance running exercise. These differences confer an advantage to females in ultra-endurance performance, but other factors (e.g. lower O₂ carrying capacity, greater body fat percentage) counterbalance these potential advantages, making females outperforming males a rare exception. The present literature review also highlights the lack of sex comparison in studies investigating running biomechanics in fatigue conditions and during the recovery process.