Age Differences in Pacing in Endurance Running: Comparison between Marathon and Half-MarathonMen and Women

Pacing in ultra-marathon running: the Western States 100-mile endurance run 2006-2023

Pacing has been investigated in different running races, including ultra-marathons. We have, however, little knowledge about pacing in ultra-trail running. To date, no study has investigated pacing in one of the most iconic ultra-trail running races, the 'Western States 100-Mile Endurance Run' (WSER), which covers 160 km (100 miles) and includes significant elevation changes (6000 vertical meters uphill and 7500 vertical meters downhill). Therefore, the aim of the study was to investigate pacing for successful finishers in WSER regarding gender, age, and performance level. Official results and split times for the WSER were obtained from the race website, including elevation data from 3837 runners, with 3068 men (80%) and 769 women (20%) competing between 2006 and 2023. The mean race speed was calculated for each participant, as well as the average mean checkpoint speed for each of the 18 race checkpoints (17 aid stations and finish point). The percentage of change in checkpoint speed (CCS) in relation to the average race speed was calculated. CCS was calculated for each of the 18 checkpoints to evaluate each runner's pacing strategy. The average change in checkpoint speed (ACCS) of each participant was calculated as a mean of the 18 CCSs. Eight age groups were formed. Since there were very few runners younger than 25 and older than 65 years, these age groups were merged into < 30 and 60 > groups, respectively. Four performance groups were formed by four quartiles, each consisting of 25% of the total sample separately for men and women. Pacing shows great variability between checkpoints in both men and women, mainly influenced by elevation. Although the race profile is mostly downhill, it appears that the pacing trend is towards positive pacing. The differences between men and women were mainly at the beginning of the race (men start faster) and towards the end (men slow down more). Men have more pacing variability than women, with significant differences in the youngest age group, as well as the 40-44 and 50-54 age groups. In addition, younger men have more variability in pace compared to older men. There are no significant differences in age groups in women. Finally, the slowest and fastest ultra runners had less pacing variability than medium level runners. Pacing in WSER-runners shows great variability between checkpoints in both men and women. Pacing is positive and highly influenced by elevation. Men start faster than women, and men slow down more than women. Pacing differs in male but not in female age group runners. The slowest and fastest ultra runners had less pacing variability than medium level runners.

The Contrasting Effects of Two Distinct Exercise Training Modalities on Exhaustive Exercise-Induced Muscle Damage in Mice May Be Associated with Alterations in the Gut Microbiota

Exhaustive exercise is known to induce muscle damage characterized by inflammation and oxidative stress. Although "regular" and "weekend warrior" exercise regimens have been shown to confer comparable health benefits in human studies, such as reduced risks of all-cause, cardiovascular disease (CVD), and cancer mortality, their differential impacts on muscle damage post-exhaustive exercise remain unclear. This study aimed to compare the effects of long-term, moderate-intensity (LTMI) and short-term, high-intensity (STHI) training modalities, matched for total exercise volume, on gut microbiota, short-chain fatty acids (SCFAs), and exhaustive exercise-induced muscle damage in mice, as well as to evaluate the correlation between these factors. LTMI is considered a regular exercise regimen, while STHI shares some similarities with the "weekend warrior" pattern, such as promoting exercise intensity and condensing training sessions into a short period. Our findings indicate that LTMI training significantly enhanced the abundance of SCFA-producing bacteria, including Akkermansia, Prevotellaceae_NK3B31_group, Odoribacter, Alistipes, and Lactobacillus, thereby increasing SCFA levels and attenuating muscle damage following exhaustive swimming. In contrast, STHI training increased the abundance of opportunistic pathogens such as Staphylococcus and Bilophila, without altering SCFA levels, and was associated with exacerbated muscle damage. Moreover, we observed a significant negative correlation between the abundance of SCFA-producing bacteria and SCFA levels with the expression of inflammatory cytokines in the muscle of mice post-exhaustive exercise. Conversely, the abundance of Staphylococcus and Bilophila showed a notable positive correlation with these cytokines. Additionally, the effects of LTMI and STHI on exhaustive exercise-induced muscle damage were transmissible to untrained mice via fecal microbiota transplantation, suggesting that gut microbiota changes induced by these training modalities may contribute to their contrasting impacts on muscle damage. These results underscore the significance of selecting an appropriate training modality prior to engaging in exhaustive exercise, with implications for athletic training and injury prevention.

Running Variability in Marathon-Evaluation of the Pacing Variables

Background and Objectives: Pacing analyses for increasingly popular long-distance running disciplines have been in researchers' spotlight for several years. In particular, assessing pacing variability in long-distance running was hardly achievable since runners must repeat long-running trials for several days. Potential solutions for these problems could be multi-stage long-distance running disciplines. Therefore, this study aimed to assess the long-distance running variability as well as the reliability, validity, and sensitivity of the variables often used for pacing analyses. Materials and Methods: This study collected the split times and finish times for 20 participants (17 men and three women; mean age 55.5 years ± 9.5 years) who completed the multiday marathon running race (five marathons in 5 days), held as part of the Bretzel Ultra Tri in Colmar, France, in 2021. Seven commonly used pacing variables were subsequently calculated: Coefficient of variation (CV), Change in mean speed (CS), Change in first lap speed (CSF), Absolute change in mean speed (ACS), Pace range (PR), Mid-race split (MRS), and First 32 km-10 km split (32-10). Results: Multi-stage marathon running showed low variability between days (Intraclass correlation coefficient (ICC) > 0.920), while only the CV, ACS, and PR variables proved to have moderate to good reliability (0.732 < ICC < 0.785). The same variables were also valid (r > 0.908), and sensitive enough to discern between runners of different performance levels (p < 0.05). Conclusions: Researchers and practitioners who aim to explore pacing in long-distance running should routinely utilize ACS, CV, and PR variables in their analyses. Other examined variables, CS, CSF, MRS, and 32-10, should be used cautiously. Future studies might try to confirm these results using different multi-stage event's data as well as by expanding sensitivity analysis to age and gender differences.

The pacing differences in performance levels of marathon and half-marathon runners

Introduction

Many studies indicate a considerable impact of optimal pacing on long-distance running performance. Given that the amount of carbohydrates in metabolic processes increases supralinearly with the running intensity, we may observe differences between the pacing strategies of two long-distance races and different performance levels of runners. Accordingly, the present study aimed to examine the differences in pacing strategies between marathon and half-marathon races regarding the performance levels of runners.

Methods

The official results and split times from a total of 208,760 (marathon, N = 75,492; half-marathon, N = 133,268) finishers in the "Vienna City Marathon" between 2006 and 2018 were analyzed. The percentage of the average change of speed for each of the five segments (CS 1-5), as well as the absolute change of speed (ACS) were calculated. The CS 1-5 for the marathon are as follows: up to the 10th km, 10th - 20th km, 20th - 30th km, 30th - 40th km, and from the 40th km to the 42.195 km. For the half-marathon, the CS 1-5 are half of the marathon values. Four performance groups were created as quartiles of placement separately for sexes and races: high-level (HL), moderate to high-level (MHL), moderate to low-level (MLL), and low-level (LL).

Results

Positive pacing strategies (i.e., decrease of speed) were observed in all performance groups of both sex and race. Across CS 1-5, significant main effects (p < 0.001) were observed for the segment, performance level, and their interaction in both sex and race groups. All LL groups demonstrated higher ACS (men 7.9 and 6.05%, as well as women 5.83 and 5.49%, in marathon and half-marathon, respectively), while the HL performance group showed significantly lower ACS (men 4.14 and 2.97%, as well as women 3.16 and 2.77%, in marathon and half-marathon, respectively). Significant main effects (p < 0.001) for the race were observed but with a low effect size in women (ŋ2 = 0.001).

Discussion

Better runners showed more even pacing than slower runners. The half-marathoners showed more even pacing than the marathoners across all performance groups but with a trivial practical significance in women.

An analysis of the São Silvestre race between 2007-2021: An increase in participation but a decrease in performance

This study aimed to investigate the trends of finishers in the São Silvestre race in Brazil, taking into account sex, age, and performance levels. A total of 31 ​775 runners (women, n ​= ​13 ​847; men, n ​= ​17 ​928), aged (45.2 ​± ​16.8) years, finishers in the São Silvestre race between 2007 and 2021, were considered in the present analysis. Data (event year, date of birth, sex, and race times) were downloaded from the official race website. The man-Whitney U test, Spearman correlation, and robust regression model were computed. Participation increased over time for both sexes. Regarding age groups, "31-40 years" (women) and "> 60 years" (men) were those with the highest number of finishers. We found a decrease in performance across the years (β ​= ​2.45; p ​< ​0.005), as well as significant differences in race times for both sexes (U ​= ​42.844; p ​< ​0.001), with men presenting better performances than women. Over time, it was observed an increase in the performance gap between the sexes, but in general, the performance decreased (β ​= ​1.76; p ​< ​0.001). Stakeholders should consider improving the strategies to improve women and young people's participation in running events.

Effects of High-Intensity Warm-Up on 5000-Meter Performance Time in Trained Long-Distance Runners

Warm-up protocols with high intensities before continuous running provide potential benefits for middle-distance runners. Nevertheless, the effect of high-intensity warm-ups on long-distance runners remains unclear. The purpose of this study was to verify the effect of a high-intensity warm-up protocol on 5000 m performance in trained runners. Thirteen male runners (34 ± 10 years, 62 ± 6 kg, 62.7 ± 5.5 ml/kg/min) performed two 5000 m time trials, preceded by two different warm-ups. One high-intensity warm up (HIWU: 1x 500 m (70% of the running intensity) + 3x 250 m (100% of the running intensity) and one low-intensity warm up (LIWU: 1x 500 m (70% of the running intensity) + 3x 250 m (70% of the running intensity)), where the running intensities were calculated using the results obtained in the Cooper test. Physiological and metabolic responses, and endurance running performance parameters, were evaluated by the Counter Movement Jump (CMJ), running rating of perceived exertion (RPE), blood lactate concentration (BLa), and performance running. Total time for the 5000 m was lower using HIWU when compared to LIWU (1141.4 ± 110.4 s vs. 1147.8 ± 111.0 s; p = 0.03; Hedges' g = 0.66). The HIWU warm-up led to an improvement in pacing strategy during the time trial. After warm-up protocols, the performance on the CMJ was improved only when applying HIWU (p = 0.008). Post warm-up BLa was significantly higher for HIWU vs. LIWU (3.5 ± 1.0 mmol·L-1 vs. 2.3 ± 1.0 mmol·L-1; p = 0.02), with similar behavior for the RPE (p = 0.002), internal load of the session (p = 0.03). The study showed that a high-intensity warm-up protocol can improve performance in the 5000 m in trained endurance runners.

Variable Pacing Is Associated with Performance during the OCC® Ultra-Trail du Mont-Blanc® (2017-2021)

The current evidence suggests that pacing may not be affected by performance level or sex in trail-running races as may occur in road running races. However, the previous studies included races of >100 km. Therefore, we aimed to verify the influence of performance level and sex on pacing in the last four (2017, 2018, 2019, and 2021) editions of a shorter (56.3 km) ultra-trail running race (i.e., Orsières-Champex-Chamonix; OCC®) that maintained the same race profile. The mean finishing time for the 5656 participants was 10 h 20 min 33 s ± 2 h 01 min 19 s. Pacing variability (CV%) was higher in high-level participants, thus showing a greater ability to adapt their pace to the race profile than low-level runners. Males also had a higher pacing variability than females although the effect sizes were small. Based on the current findings, we may recommend for non-elite OCC® participants to adapt their pace to the race profile with a slower pace during uphills and a faster pace during downhills. Further studies including participants' experience are necessary to confirm the effectiveness of this suggestion in trail-running races of variable distances.

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.

Gender and Age Differences in Performance of Over 70,000 Chinese Finishers in the Half- and Full-Marathon Events

(1) Background: The aim of the present study was to examine the characteristics of over 70,000 long-distance finishers over the last four years in Chinese half- and full-marathon events; (2) Methods: The available data of all finishers (n = 73,485; women, n = 17,134; men, n = 56,351) who performed half- and full-marathon events in Hangzhou from 2016 to 2019 were further analyzed for the characteristics of gender, age and average running speed; (3) Results: The total men-to-women ratio was the lowest in the half-marathon event (1.86) and the highest in the full-marathon event (17.42). Faster running performance in males than in females and faster average running speed in short-distance runners were shown. Gender and race distance were observed to have the most significant effects on average running speed (p < 0.01). For both male and female finishers, the slowest running speed was shown in older age groups (p < 0.01) during the full marathon. Our results indicated that the gender difference in performance was attenuated in the longer race distances and older age groups; (4) Conclusions: Understanding the participation and performances across different running distances would provide insights into physiological and biomechanical characteristics for training protocols and sports gear development in different groups.

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.

The Impact of Marathons on the Recovery of Heart Rate and Blood Pressure in Non-Professional Male Marathoners’ (≥45 Years)

Background and Objectives: Physical activity has a positive impact on health, and the participation in exercise and sports, including marathons, has increased in popularity. This kind of sport requires extreme endurance, which can cause different health problems and even lead to death. Participants without sufficient preparation and, in particular, men 45 years of age and older belong to a high risk group. The aim of this study was to determine the impact of marathons and cofactors associated with marathons on the recovery of heart rate (HR) and blood pressure (BP) of non-professional ≥ 45 years old male marathoners. Materials andMethods: A total of 136 ≥ 45 year old, non-professional (amateur marathoner), male participants were recruited. Data collection involved a questionnaire, body composition measures, and BP and HR results before and after finishing the marathon. Descriptive data, t-test, Mann–Whitney or χ² test, and Pearson’s correlation were applied. Results: Participants (skiing n = 81, cycling n = 29, running n = 26; mean age 51.7 ± 7.1 years old) had previously attended a median of 35 (IQR 17.5–66) marathons and travelled 2111.5 (IQR 920–4565) km. Recovery of HR and BP after finishing and recovery time was insufficient and not associated with marathon preparation. Running was the most burdensome for HR, and cycling was most taxing for BP. Chronic diseases did not influence participation in the marathon. Conclusions: The preparation for the marathon was mainly sufficient, but recovery after the marathon was worrisome. Marathons are demanding for ≥45 year old males and may be too strenuous an activity that has deleterious effects on health.

The effect of mental fatigue on half-marathon performance: a pragmatic trial

Purpose

It is well established that mental fatigue impairs performance during lab-based endurance tests lasting less than 45 min. However, the effects of mental fatigue on longer duration endurance events and in field settings are unknown. The aim of this study was to investigate the effect of mental fatigue on performance during a half-marathon race.

Methods

Forty-six male amateur runners (means ± SD: age 43.8 ± 8.6 years, $$\dot V{O_{2peak}}$$ V ˙ O 2 p e a k 46.0 ± 4.1 ml/kg/min) completed a half-marathon after being randomly allocated to performing a 50-min mentally fatiguing task (mental fatigue group) or reading magazines for 50 min (control group). Running speed, heart rate, and perceived effort were measured during the race.

Results

Runners in the mental fatigue group completed the half-marathon approximately 4 min slower (106.2 ± 12.4 min) than those in the control group (102.4 ± 10.2 min), but this difference was not statistically significant (Cohen’s d = 0.333; p = 0.265). However, equivalence was not established [t(40.88) = 0.239, p = 0.594] and equivalence testing analysis excluded a beneficial effect of mental fatigue on half-marathon performance.

Conclusion

Due to its posttest-only design and the achievable sample size, the study did not have enough power to provide evidence that the observed 4-min increase in half-marathon time is statistically significant. However, equivalence testing suggests that mental fatigue has no beneficial effect on half-marathon performance in male amateur runners, and a harmful effect cannot be excluded. Overall, it seems prudent for endurance athletes to avoid mentally fatiguing tasks before competitions.

The Role of Environmental Conditions on Master Marathon Running Performance in 1,280,557 Finishers the 'New York City Marathon' From 1970 to 2019

Aim: This study investigated the influence of weather conditions on running performance in female and male age group runners in the largest marathon in the world, the “New York City Marathon.”

Methods: The analysis included data from 1,280,557 finishers the “New York City Marathon” from the years 1970 to 2019. Linear mixed models for men and women finishers with race time (min) as dependent variable and 5-year age groups, temperature, wind and relative humidity tertiles (low, medium, high) as independent factors and finisher as random intercept was performed. Additional models with an interaction between age groups and one weather variable each were performed.

Results: Temperature was positively associated with race time while wind speed and humidity were negatively associated (p < 0.001). Men were significantly greater affected wind speed and humidity than women (p < 0.001 for interaction) but not by temperature (p = 0.17 for interaction). With an average of 8 min longer race time, high temperature had the greatest effect on race time. The effect of high humidity on race time was significantly increased in 40–59 years old men and 25–65 years old women. High temperatures had an increased effect on race time in 30–64 years old men and 40–64 years old women. The inverse association between race time and high wind speed was pronounced in finishers with younger age.

Conclusion: Performance was lower on days with high temperature, low humidity and low wind speed. Men seemed to benefit more from higher humidity and wind speed than women. Aged (70 +) finishers were not greater affected by high temperatures.

Pacing in Long-Distance Running: Sex and Age Differences in 10-km Race and Marathon

Background and objective: The recent availability of data from mass-participation running events has allowed researchers to examine pacing from the perspective of non-elite distance runners. Based on an extensive analysis of the literature, we concluded that no study utilizing mass-participation events data has ever directly compared pacing in the 10-km race, with other long-distance races. Therefore, the main aim of this study was to assess and compare pacing between 10-km runners and marathoners, in regards to their sex and age. Materials and methods: For the purpose of this study, official results from the Oslo marathon (n = 8828) and 10-km race (n = 16,315) held from 2015 to 2018 were included. Results: Both 10-km runners and marathoners showed positive pacing strategies. Moreover, two-way analysis of variance showed that women were less likely to slow in the marathon than men (9.85% in comparison to 12.70%) however, not in the 10-km race (3.99% in comparison to 3.38%). Finally, pace changing is more prominent in youngest and oldest marathoners comparing to the other age groups (12.55% in comparison to 10.96%). Conclusions: Based on these findings, practitioners should adopt different training programmes for marathoners in comparison to shorter long-distance runners.

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.

Tower Running-Participation, Performance Trends, and Sex Difference

Though there are exhaustive data about participation, performance trends, and sex differences in performance in different running disciplines and races, no study has analyzed these trends in stair climbing and tower running. The aim of the present study was therefore to investigate these trends in tower running. The data, consisting of 28,203 observations from 24,007 climbers between 2014 and 2019, were analyzed. The effects of sex and age, together with the tower characteristics (i.e., stairs and floors), were examined through a multivariable statistical model with random effects on intercept, at climber’s level, accounting for repeated measurements. Men were faster than women in each age group (p < 0.001 for ages ≤69 years, p = 0.003 for ages > 69 years), and the difference in performance stayed around 0.20 km/h, with a minimum of 0.17 at the oldest age. However, women were able to outperform men in specific situations: (i) in smaller buildings (<600 stairs), for ages between 30 and 59 years and >69 years; (ii) in higher buildings (>2200 stairs), for age groups <20 years and 60–69 years; and (iii) in buildings with 1600–2200 stairs, for ages >69 years. In summary, men were faster than women in this specific running discipline; however, women were able to outperform men in very specific situations (i.e., specific age groups and specific numbers of stairs).