Ultra-marathon Performance Research Articles

Does The Sex-gap In 100-mile Ultramarathon Performance Decrease With Age?

Does The Sex-gap In 100-mile Ultramarathon Performance Decrease With Age?

Sex differences in ultramarathon performance in races with comparable numbers of males and females.

There is a prominent sex-based difference in athletic performance such that males outperform females by 7%-14% in races from 100m to marathon. In ultramarathons, the difference is often much smaller, leading to speculation that females are "built" for the sport. However, data are confounded by the low number of female participants; just 10%-30% in any given race. This study compared data from two ultramarathons where males and females competed in comparable numbers. There were 116 and 146 starters in the 50 mile and 100 mile races, respectively (52% female). Finish times were compared using t tests or Mann-Whitney U tests, a Chi-squared test of independence examined the relationship between sex and ranking, and multivariable linear regressions examined relationships between sex, age, and finish time. There were 96 finishers in the 50 mile race (46% female) and 91 finishers in the 100 mile race (45% female). The median finish time for 50 miles was 12.64±2.11h with no difference between sexes (1.2%, p=0.441). However, the top-10 males finished the race ∼85min faster than the top-10 females (13.8%, p=0.045). The mean finish time for 100 miles was 31.58±3.36h with no difference between sexes (3.2%, p=0.132) and no difference between the top-10 males and top-10 females (4.4%, p=0.150). Linear and multivariable regression models using sex and age were unable to predict overall finish time in either race. In conclusion, the sex-based performance discrepancy shrinks to 1%-3% in ultramarathons when males and females compete in comparable numbers. Top-performing males still retain a considerable advantage over shorter distances.

Analysis of over 1 million race records shows runners from East African countries as the fastest in 50-km ultra-marathons

The 50-km ultra-marathon is a popular race distance, slightly longer than the classic marathon distance. However, little is known about the country of affiliation and age of the fastest 50-km ultra-marathon runners and where the fastest races are typically held. Therefore, this study aimed to investigate a large dataset of race records for the 50-km distance race to identify the country of affiliation and the age of the fastest runners as well as the locations of the fastest races. A total of 1,398,845 50-km race records (men, n = 1,026,546; women, n = 372,299) were analyzed using both descriptive statistics and advanced regression techniques. This study revealed significant trends in the performance of 50-km ultra-marathoners. The fastest 50-km runners came from African countries, while the fastest races were found to occur in Europe and the Middle East. Runners from Ethiopia, Lesotho, Malawi, and Kenya were the fastest in this race distance. The fastest 50-km racecourses, providing ideal conditions for faster race times, are in Europe (Luxembourg, Belarus, and Lithuania) and the Middle East (Qatar and Jordan). Surprisingly, the fastest ultra-marathoners in the 50-km distance were found to fall into the age group of 20–24 years, challenging the conventional belief that peak ultra-marathon performance comes in older age groups. These findings contribute to a better understanding of the performance models in 50-km ultra-marathons and can serve as valuable insights for runners, coaches, and race organizers in optimizing training strategies and racecourse selection.

Total Energy Expenditure and Nutritional Intake in Continuous Multiday Ultramarathon Events.

Continuous multiday ultramarathon competitions are increasingly popular and impose extreme energetic and nutritional demands on competitors. However, few data have been published on energy expenditure during these events. Here, we report doubly labeled water-derived measures of total energy expenditure (in kilocalories per day) and estimated physical activity level (PAL: total energy expenditure/basal metabolic rate) collected from five elite and subelite finishers (four males and one female, age 34.6 ± 4.9years)-and nutritional intake data from the winner-of the Cocodona 250, a ∼402-km race in Arizona, and from a fastest-known-time record (one male, age 30years) on the ∼1,315-km Arizona Trail. PAL during these events exceeded four times basal metabolic rate (Cocodona range: 4.34-6.94; Arizona Trail: 5.63). Combining the results with other doubly labeled water-derived total energy expenditure data from ultraendurance events show a strong inverse relationship between event duration and PAL (r2 = .68, p < .0001). Cocodona race duration was inversely, though not significantly, associated with PAL (r2 = .70, p = .08). Water turnover varied widely between athletes and was not explained by PAL or body mass. The Cocodona race winner met ∼53% of energy demand via dietary intake, 85.6% of which was carbohydrate, while ∼47% of energy demand was met via catabolism of body energy stores. Together, these results illustrate the energetic deficits incurred during competitive continuous multiday ultramarathon efforts and implicate macronutrient absorption and/or storage as key factors in ultramarathon performance.

The Golden Ticket: Examining the Impact of Winning the Western States Endurance Run Lottery on Subsequent Ultramarathon Performance and Travel Decisions

The Golden Ticket: Examining the Impact of Winning the Western States Endurance Run Lottery on Subsequent Ultramarathon Performance and Travel Decisions

Could middle- and long-distance running performance of well-trained athletes be best predicted by the same aerobic parameters?

The prediction of running performance at different competitive distances is a challenge, since it can be influenced by several physiological, morphological and biomechanical factors. In experienced male runners heterogeneous for maximal oxygen uptake (VO2max), endurance running performance can be well predicted by several key parameters of aerobic fitness such as VO2max and its respective velocity (vVO2max), running economy, blood lactate response to exercise, oxygen uptake kinetics and critical velocity. However, for a homogeneous group of well-trained endurance runners, the relationship between aerobic fitness parameters and endurance running performance seems to be influenced by the duration of the race (i.e., middle vs. long). Although middle-distance and ultramarathon runners present high aerobic fitness levels, there is no accumulating evidence showing that the aerobic key parameters influence both 800-m and ultramarathon performance in homogeneous group of well-trained runners. The vVO2max seems to be the best predictor of performance for 1500 m. For 3000 m, both vVO2max and blood lactate response to exercise are the main predictors of performance. Finally, for long distance events (5000 m, 10,000 m, marathon and ultramarathon), blood lactate response seems to be main predictor of performance. The different limiting/determinants factors and/or training-induced changes in aerobic parameters can help to explain this time- or distance-dependent pattern.

Performance determinants, running energetics and spatiotemporal gait parameters during a treadmill ultramarathon

PurposeThe objective of this study was to investigate the changes in metabolic variables, running energetics and spatiotemporal gait parameters during an 80.5 km treadmill ultramarathon and establish which key predictive variables best determine ultramarathon performance.MethodsTwelve participants (9 male and 3 female, age 34 ± 7 years, and maximal oxygen uptake (dot{V}O2max) 60.4 ± 5.8 ml·kg−1·min−1) completed an 80.5 km time trial on a motorised treadmill in the fastest possible time. Metabolic variables: oxygen consumption (dot{V}O2), carbon dioxide production (dot{V}CO2) and pulmonary ventilation (dot{V}E) were measured via indirect calorimetry every 16.1 km at a controlled speed of 8 km·h−1 and used to calculate respiratory exchange ratio (RER), the energy cost of running (Cr) and fractional utilisation of dot{V}O2max (F). Spatiotemporal gait parameters: stride length (SL) and cadence (SPM) were calculated via tri-axial accelerometery.ResultsTrial completion time was 09:00:18 ± 01:14:07 (hh:mm:ss). There were significant increases in dot{V}O2, Cr, F, dot{V}E and heart rate (HR) (p < 0.01); a significant decrease in RER (p < 0.01) and no change in SL and SPM (p > 0.05) across the measured timepoints. F and Cr accounted for 61% of the variance in elapsed finish time (R_{{{text{adj}}}}^{{2}} = 0.607, p < 0.01).ConclusionA treadmill ultramarathon elicits significant changes in metabolic variables, running energetics and spatiotemporal gait parameters. With F and Cr explaining 61% of variance in finish time. Therefore, those able to maintain a higher F, while adopting strategies to minimise an increase in Cr may be best placed to maximise ultramarathon performance.

Prospective Observational Study of Weight-based Assessment of Sodium Supplements on Ultramarathon Performance (WASSUP)

BackgroundSodium supplements are ubiquitous in endurance running, but their impact on performance has been subjected to much debate. The objective of the study was to assess the effect of sodium supplementation as a weight-based predictor of race performance in ultramarathon runners.MethodsProspective observational study during an 80 km (50 mi) stage of a 6-stage 250 km (155 mi) ultramarathon in Chile, Patagonia, Namibia, and Mongolia. Finish line hydration status as measured by weight change, point-of-care serum sodium, and questionnaire provided sodium ingestion categories at 33rd percentile and 66th percentile both for weight-adjusted rate and total sodium consumption, then analyzed for significant relationships to race performance, dysnatremia, and hydration.ResultsTwo hundred sixty-six participants were enrolled, with 217 (82%) with complete sodium supplement rate data, 174 (80%) with finish line sodium, and 161 (74%) with both pre-race weights and total sodium ingestion allowing weight-based analysis. Sodium intake ranged from 131–533 mg/h/kg (2–7.2 gm), with no statistically significant impact on pace, race time, or quintile rank. These outcomes did not change when sodium intake was analyzed as a continuous variable or by sub-group analysis of the 109 (68%) normonatremic runners. When controlled for weight-adjusted sodium intake, performance was poorly correlated with hydration (r = − 0.152, 95% CI − 0.348–0.057). Dehydrated runners outperformed those overhydrated, with 11% of top 25th percentile finishers dehydrated (versus 2.8% overhydrated), with 3.6 min/km faster pace and time 4.6 h faster finishing time.ConclusionsNo association was found between sodium supplement intake and ultramarathon performance. Dehydrated runners were found to have the best performance. This reinforces the message to avoid overhydration.

Mental toughness and self-efficacy of elite ultra-marathon runners.

Minimal research has examined psychological processes underpinning ultra-marathon runners’ performance. This study examined the relationships between mental toughness and self-efficacy with performance in an elite sample of ultra-marathon runners competing in the 2019 Hawaiian Ultra Running Team’s Trail 100-mile endurance run (HURT100). The Mental Toughness Questionnaire (SMTQ) and the Endurance Sport Self-Efficacy Scale (ESSES) were completed by 56 elite ultra-marathon runners in the HURT100 (38 males, 18 females; Mage = 38.86 years, SDage = 9.23). Findings revealed mental toughness and self-efficacy are highly related constructs (r(54) = 0.72, p < 0.001). Mental toughness and self-efficacy did not significantly relate to ultra-marathon performance (mental toughness and self-efficacy with Ultra-Trail World Tour (UTWT) rank F(2, 53) = 0.738, p = 0.483; mental toughness and self-efficacy with likelihood would finish the HURT100 χ2 = 0.56, p = 0.756; mental toughness and self-efficacy with HURT100 placing and time F(2, 53) = 1.738, p = 0.186 and F(2, 30) = 2.046, p = 0.147, respectively). However, participants had significantly and meaningfully higher mental toughness (M = 45.42, SD = 4.26, medium and large effect sizes) than athletes from other sports previously published. Our interpretation is that these results taken in conjunction, suggest a threshold of mental toughness that performers require to be of the standard needed to be able to prepare for and compete in elite ultra-marathon events such as the HURT100; once this mental toughness threshold is met, other factors are likely to be more influential in determining elite level ultra-marathon performance.

248 Weight-Based Assessment of Sodium Supplements on Ultramarathon Performance

Sodium supplements are ubiquitous in endurance running. Their impact on hydration, dysnatremia, and running pace, all independently associated with performance, has been the subject of much debate. The objective of the study was to assess the effect of sodium supplementation normalized to body weight, as a predictor of race performance in ultramarathon runners. Prospective observational study during an 80 km (50 mi) stage of a 6-stage 250 km (155 mi) ultramarathon in Chile, Patagonia, Namibia and Mongolia. Finish line hydration status, serum sodium, and questionnaires were gathered to define sodium ingestion categories at 33% and 66% both for weight-adjusted and true total sodium consumption, and analyzed for significant relationships to dysnatremia, hydration, and impact on race performance. Results:266 participants were enrolled, with 218 (82%) with complete sodium supplement rate data, with 174 (80%) with finish line sodium, and 161 (74%) with both pre-race weights and total sodium ingestion allowing for normalization of both total amount (mg/hr) and weight-based (mg/hr/kg) rate of ingestion analysis. Participants were stratified as low (<200 mg/hr; <2.79 mg/hr/kg), medium (200 to 360 mg/hr; 2.79 mg/hr/kg - 4.78 mg/hr/kg), or high (>360 mg/hr; >4.78 mg/hr/kg) sodium intake categories. Sodium intake did not impact the pace (0.99), total race time (p=1), quintile rank (p=0.4), incidence of dysnatremia (p=0.74), or quantity of hydration (p=0.7). These outcomes did not change using binary grouping around the 50% ingestion amount, assessed by temperature of race, or when excluding the 34 (27%) dysnatremic runners. When hydration status was controlled by weight-adjusted normalization of sodium intake, dehydration was found to improve performance with faster times [n = 40 (28.1% ), pace = 9.4 min / km (± 2.1), time = 12.4 hrs (±2.9)] compared to euhydration [n = 62 (43.8%), pace = 10.6 min / km (± 2.8), time = 13.8 hrs (±3.7)] and overhydration [n=40 (28.1%), pace = 13 min / km (± 3.4), time = 17 hrs]. Sodium supplements in ultramarathon runners did not meaningfully impact ultramarathon performance. Those runners who were most dehydrated were found to have improved performance.

Performance Determinants in Short (68 km) and Long (121 km) Mountain Ultra-Marathon Races.

Standard performance parameters measured during a laboratory test have been shown to be related to mountain ultra-marathon performance up to a competition length of 75 km. It is not known if a similar relationship exists for longer races. This study aimed to investigate the association between laboratory-based performance parameters and performance times in a short (68 km) and a long (121 km) mountain ultra-marathon. Eleven male finishers of the short race and seven male finishers of the long race were investigated. Participants performed an incremental exercise test to exhaustion in the 2 weeks prior to the event. During the event, the heart rate was monitored and finishing times were registered. The maximal oxygen consumption and the oxygen uptake at the ventilatory thresholds 1 and 2 were related to performance time during the short run (~12h; r = -0.764 up to r = -0.782; p < 0.05), but there was no correlation during the long race (~28h; r = -0.107 to 0.357; p > 0.05). This study shows that physical fitness parameters established in a laboratory setting determine competition completion times in ultra-mountain marathon events lasting for ~12 h. During longer races, i. e. ~28 h, other factors not established in the present investigation, such as experience, race strategy, coping with pain and fatigue resistance, may be important for performance.

Blood cardiac biomarkers responses are associated with 24 h ultramarathon performance

PurposeClinical significance of cardiac biomarkers response in ultra-endurance runners are not completely elucidated because events vary in distance/duration and competitors modulate running intensity according to individual running capacity. The aim of this study was to examine the relationship between self-selected exercise intensity with cardiac biomarkers comparing experienced (EXP, N = 11) and novice (NOV, N = 14) runners able to finish a 24h ultramarathon (24UM) with significant differences in performance. MethodsCardiac biomarkers (i.e. CKMB/totalCK, cTnT and NT-proBNP), inflammatory markers (i.e. leukocytes and CRP) and cortisol were analyzed before and after a 24UM. ResultsEXP finished the race with significant (p < 0.05) longer distance than NOV (158.8 ± 15.8 vs 116.8 ± 10.3 Km). Two-way mixed ANOVA showed significant time × performance level interaction with greater increase of cTnT (F(1,23) = 6.18, p = 0.021), NT-proBNP (F(1,23) = 9.27, p = 0.006) and cortisol (F(1, 23) = 5.13, p = 0.03) in the EXP group. CKMB/totalCK (F(1, 23) = 71.90, p < 0.0001) decreased while leukocytes (F(1, 23) = 100.06, p < 0.0001) and CRP (F(1, 23) = 93.37, p < 0.0001) increased in both groups (main effect of time). Correlations were found between 24UM distance and cortisol (r = 0.58; p = 0.002), CKMB (r = 0.47; p = 0.017), cTnT (r = 0.44; p = 0.027) or NT-proBNP (r = 0.56; p = 0.003). Cortisol and NT-proBNP were also significantly correlated (r = 0.51; p = 0.01). ConclusionsAlthough there is no clear evidence of cardiac risk when comparing cardiac biomarkers levels with clinical cut-off values, cardiac biomarkers are associated with running performance and pituitary-adrenocortical system response. In EXP runners, higher levels of cardiac biomarkers and cortisol suggest a more hemodynamically challenged heart during prolonged endurance exercise.

How variability in pain and pain coping relate to pain interference during multistage ultramarathons.

An important and substantial body of literature has established that maladaptive and adaptive coping strategies significantly impact pain-related outcomes. This literature, however, is based primarily on populations with painful injuries and illnesses. Little is known about coping in individuals who experience pain in other contexts and whether coping impacts outcomes in the same way. In an effort to better understand pain coping in such contexts, this study evaluated pain coping in ultramarathon runners, a population known to experience moderate levels of pain with minimal perceived negative effects. This study reports on pain coping in 204 entrants in 2016 RacingThePlanet multistage ultramarathon events. Participants provided data over 5 consecutive days on pain severity, pain interference, exertion, and coping. Results demonstrated that the study participants were more likely to use adaptive than maladaptive coping responses. However, maladaptive coping, but not adaptive coping, was positively associated with percent time spent thinking about pain and pain-related interference. Taken together, the study supports the idea that this high functioning group of individuals experiencing pain emphasizes the use of adaptive coping strategies over maladaptive strategies, reinforcing the perspective that such a pattern may be the most effective way to cope with pain. Within the group, however, results supported traditional patterns, such that greater use of maladaptive strategies was associated with greater pain-related interference, suggesting that optimizing pain coping may be critical to reducing factors that may interfere with ultramarathon performance.

Physiology and Pathophysiology in Ultra-Marathon Running.

In this overview, we summarize the findings of the literature with regards to physiology and pathophysiology of ultra-marathon running. The number of ultra-marathon races and the number of official finishers considerably increased in the last decades especially due to the increased number of female and age-group runners. A typical ultra-marathoner is male, married, well-educated, and ~45 years old. Female ultra-marathoners account for ~20% of the total number of finishers. Ultra-marathoners are older and have a larger weekly training volume, but run more slowly during training compared to marathoners. Previous experience (e.g., number of finishes in ultra-marathon races and personal best marathon time) is the most important predictor variable for a successful ultra-marathon performance followed by specific anthropometric (e.g., low body mass index, BMI, and low body fat) and training (e.g., high volume and running speed during training) characteristics. Women are slower than men, but the sex difference in performance decreased in recent years to ~10–20% depending upon the length of the ultra-marathon. The fastest ultra-marathon race times are generally achieved at the age of 35–45 years or older for both women and men, and the age of peak performance increases with increasing race distance or duration. An ultra-marathon leads to an energy deficit resulting in a reduction of both body fat and skeletal muscle mass. An ultra-marathon in combination with other risk factors, such as extreme weather conditions (either heat or cold) or the country where the race is held, can lead to exercise-associated hyponatremia. An ultra-marathon can also lead to changes in biomarkers indicating a pathological process in specific organs or organ systems such as skeletal muscles, heart, liver, kidney, immune and endocrine system. These changes are usually temporary, depending on intensity and duration of the performance, and usually normalize after the race. In longer ultra-marathons, ~50–60% of the participants experience musculoskeletal problems. The most common injuries in ultra-marathoners involve the lower limb, such as the ankle and the knee. An ultra-marathon can lead to an increase in creatine-kinase to values of 100,000–200,000 U/l depending upon the fitness level of the athlete and the length of the race. Furthermore, an ultra-marathon can lead to changes in the heart as shown by changes in cardiac biomarkers, electro- and echocardiography. Ultra-marathoners often suffer from digestive problems and gastrointestinal bleeding after an ultra-marathon is not uncommon. Liver enzymes can also considerably increase during an ultra-marathon. An ultra-marathon often leads to a temporary reduction in renal function. Ultra-marathoners often suffer from upper respiratory infections after an ultra-marathon. Considering the increased number of participants in ultra-marathons, the findings of the present review would have practical applications for a large number of sports scientists and sports medicine practitioners working in this field.

Performance Factors in a Mountain Ultramarathon.

This study aimed to determine mountain ultra-marathon (MUM) performance factors in a large group of endurance mountain runners. Maximal aerobic speed (MAS) was assessed one week prior to the MUM. The level and graded (10%) energy cost of running, stiffness, knee extensors force (KEf), and jump height on a counter movement jump (CMJ) were measured in 24 male ultra runners before (pre) and immediately after (post) the Interlacs Trail (75 km and 3 930/3 700 m d+/d-). Performance time was correlated with MAS (r=- 0.74, p<0.001), fraction of MAS (FMAS) sustained (r=- 0.89, p<0.001), KEf (r=- 0.51, p<0.05), and KEf loss (r=- 0.51, p<0.05). A multiple regression analysis was performed using performance time in minutes (T) and the calculated individual characteristics, resulting in T=- 11.852×FMAS-37.195×MAS-0.118×KEf+2090.581 (R2=0.98, with 95% confidence interval). Contrary to expectations, performance was neither correlated to the level or uphill energy cost of running nor to the changes of these costs post-MUM. To perform in a MUM, training should take into account muscle strength of the KE, MAS and FMAS.

Physiological and Biomechanical Mechanisms of Distance Specific Human Running Performance.

Running events range from 60-m sprints to ultra-marathons covering 100 miles or more, which presents an interesting diversity in terms of the parameters for successful performance. Here, we review the physiological and biomechanical variations underlying elite human running performance in sprint to ultramarathon distances. Maximal running speeds observed in sprint disciplines are achieved by high vertical ground reaction forces applied over short contact times. To create this high force output, sprint events rely heavily on anaerobic metabolism, as well as a high number and large cross-sectional area of type II fibers in the leg muscles. Middle distance running performance is characterized by intermediates of biomechanical and physiological parameters, with the possibility of unique combinations of each leading to high-level performance. The relatively fast velocities in mid-distance events require a high mechanical power output, though ground reaction forces are less than in sprinting. Elite mid-distance runners exhibit local muscle adaptations that, along with a large anaerobic capacity, provide the ability to generate a high power output. Aerobic capacity starts to become an important aspect of performance in middle distance events, especially as distance increases. In distance running events, V˙O2max is an important determinant of performance, but is relatively homogeneous in elite runners. V˙O2 and velocity at lactate threshold have been shown to be superior predictors of elite distance running performance. Ultramarathons are relatively new running events, as such, less is known about physiological and biomechanical parameters that underlie ultra-marathon performance. However, it is clear that performance in these events is related to aerobic capacity, fuel utilization, and fatigue resistance.

The age of the best ultramarathon performance – the case of the “Comrades Marathon”

ABSTRACTThe aim of the present study was to determine the age of the fastest running speed in 202,370 runners (34,090 women and 168,280 men) competing in the “Comrades Marathon” between 1994 and 2015 using non-linear regression analysis (second order polynomial function). When all runners were considered in 1-year age intervals, the fastest running speed (9.61 ± 1.65 km/h) was achieved at the age of 29.89 years in men, whereas women achieved it at the age of 35.96 years 8.60 ± 1.10 km/h. When the fastest runners were considered in 1-year intervals, the fastest running speed (16.65 km/h) was achieved in men at the age of 36.38 years. For the fastest women, the age of the fastest running speed (13.89 km/h) was 32.75 years. To summarize, for all runners, men achieved the best ultramarathon performance ~6 years earlier than women. When the fastest runners were considered, however, men achieved the best performance ~4 years later than women.

Effects of training and anthropometric factors on marathon and 100 km ultramarathon race performance.

BackgroundMarathon (42 km) and 100 km ultramarathon races are increasing in popularity. The aim of the present study was to investigate the potential associations of anthropometric and training variables with performance in these long-distance running competitions.MethodsTraining and anthropometric data from a large cohort of marathoners and 100 km ultramarathoners provided the basis of this work. Correlations between training and anthropometric indices of subjects and race performance were assessed using bivariate and multiple regression analyses.ResultsA combination of volume and intensity in training was found to be suitable for prediction of marathon and 100 km ultramarathon race pace. The relative role played by these two variables was different, in that training volume was more important than training pace for the prediction of 100 km ultramarathon performance, while the opposite was found for marathon performance. Anthropometric characteristics in terms of body fat percentage negatively affected 42 km and 100 km race performance. However, when this factor was relatively low (ie, less than 15% body fat), the performance of 42 km and 100 km races could be predicted solely on the basis of training indices.ConclusionMean weekly training distance run and mean training pace were key predictor variables for both marathon and 100 km ultramarathon race performance. Predictive correlations for race performance are provided for runners with a relatively low body fat percentage.

Age and ultra-marathon performance - 50 to 1,000km distances from 1969 - 2012.

We investigated age and performance in distance-limited ultra-marathons held from 50 km to 1,000 km. Age of peak running speed and running speed of the fastest competitors from 1969 to 2012 in 50 km, 100 km, 200 km and 1,000 km ultra-marathons were analyzed using analysis of variance and multi-level regression analyses. The ages of the ten fastest women ever were 40 ± 4 yrs (50 km), 34 ± 7 yrs (100 km), 42 ± 6 yrs (200 km), and 41 ± 5 yrs (1,000 km). The ages were significantly different between 100 km and 200 km and between 100 km and 1,000 km. For men, the ages of the ten fastest ever were 34 ± 6 yrs (50 km), 32 ± 4 yrs (100 km), 44 ± 4 yrs (200 km), and 47 ± 9 yrs (1,000 km). The ages were significantly younger in 50 km compared to 100 km and 200 km and also significantly younger in 100 km compared to 200 km and 1,000 km. The age of the annual ten fastest women decreased in 50 km from 39 ± 8 yrs (1988) to 32 ± 4 yrs (2012) and in men from 35 ± 5 yrs (1977) to 33 ± 5 yrs (2012). In 100 km events, the age of peak running speed of the annual ten fastest women and men remained stable at 34.9 ± 3.2 and 34.5 ± 2.5 yrs, respectively. Peak running speed of top ten runners increased in 50 km and 100 km in women (10.6 ± 1.0 to 15.3 ± 0.7 km/h and 7.3 ± 1.5 to 13.0 ± 0.2 km/h, respectively) and men (14.3 ± 1.2 to 17.5 ± 0.6 km/h and 10.2 ± 1.2 to 15.1 ± 0.2 km/h, respectively). In 200 km and 1,000 km, running speed remained unchanged. In summary, the best male 1,000 km ultra-marathoners were ~15 yrs older than the best male 100 km ultra-marathoners and the best female 1,000 km ultra-marathoners were ~7 yrs older than the best female 100 km ultra-marathoners. The age of the fastest 50 km ultra-marathoners decreased across years whereas it remained unchanged in 100 km ultra-marathoners. These findings may help athletes and coaches to plan an ultra-marathoner’s career. Future studies are needed on the mechanisms by which the fastest runners in the long ultra-marathons tend to be older than those in shorter ultra-marathons.

What is the age for the fastest ultra-marathon performance in time-limited races from 6h to 10days?

Recent findings suggested that the age of peak ultra-marathon performance seemed to increase with increasing race distance. The present study investigated the age of peak ultra-marathon performance for runners competing in time-limited ultra-marathons held from 6 to 240 h (i.e. 10 days) during 1975-2013. Age and running performance in 20,238 (21%) female and 76,888 (79%) male finishes (6,863 women and 24,725 men, 22 and 78%, respectively) were analysed using mixed-effects regression analyses. The annual number of finishes increased for both women and men in all races. About one half of the finishers completed at least one race and the other half completed more than one race. Most of the finishes were achieved in the fourth decade of life. The age of the best ultra-marathon performance increased with increasing race duration, also when only one or at least five successful finishes were considered. The lowest age of peak ultra-marathon performance was in 6 h (33.7 years, 95% CI 32.5-34.9 years) and the highest in 48 h (46.8 years, 95% CI 46.1-47.5). With increasing number of finishes, the athletes improved performance. Across years, performance decreased, the age of peak performance increased, and the age of peak ultra-marathon performance increased with increasing number of finishes. In summary, the age of peak ultra-marathon performance increased and performance decreased in time-limited ultra-marathons. The age of peak ultra-marathon performance increased with increasing race duration and with increasing number of finishes. These athletes improved race performance with increasing number of finishes.