The age of the best ultramarathon performance - the case of the "Comrades Marathon"

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.

From Athens to Sparta-37 Years of Spartathlon

(1) Background: Recent studies analyzed the participation and performance trends of historic races such as the oldest ultra-marathon (Comrades) or the oldest 100-km ultra-marathon (Biel). One of the toughest and historic ultra-marathons in the world is the ‘Spartathlon’ (246-km ultra-marathon from Athens to Sparta). The present study aimed to analyze the trends in participation and performance of this race. (2) Methods: Different general linear models were applied as follows: the first model was a two-way ANOVA (Decade × Sex), with separate models for all participants and for only the top five finishers in each race; the second model was a two-way ANOVA (Age Group × Sex); the third model was a two-way ANOVA (Nationality × Sex). (3) Results: Between 1982 and 2019, 3504 ultra-marathoners (3097 men and 407 women) officially finished the Spartathlon at least once. Athletes from Japan were the majority with 737 participants, followed by far by runners from Germany (n = 393), Greece (n = 326), and France (n = 274). The nations with the highest numbers of athletes amongst the top five performers were Japan (n = 71), followed by Germany (n = 59), and Great Britain (n = 31). Runners from the USA were the fastest in men, and runners from Great Britain were the fastest in women. Female and male runners improved performance across the decades. The annual five fastest women and men improved their performance over time. Runners achieved their best performance earlier in life (20–29 and 30–39 years) than female runners (30–39 and 40–49 years). Runners in age group 30–39 years were the fastest for all nationalities, except for Greece. (4) Conclusions: Successful finishers in the Spartathlon improved performance in the last four decades and male runners achieved their best performance ~10 years earlier in life than female runners.

Longitudinal Master Track and Field Performance Decline Rates Are Lower and Performance Is Better Compared to Athletes Competing Only Once

In master athletics research, cross-sectional data are easier to obtain than longitudinal data. While cross-sectional data give the age-related performance decline for a population, longitudinal data show individual trajectories. It is not known whether athletes who repeatedly compete have (a) a better performance and (b) a slower age-related decline in performance than that obtained from cross-sectional data from athletes competing only once. To investigate this, we analyzed 33 254 results of 14 118 male athletes from 8 disciplines in the database of "Swedish Veteran Athletics." For each discipline and for the pooled data of all disciplines, quadratic models of the evolution of performance over time were analyzed by ANCOVA/ANOCOVA using MATLAB. The performance was higher in athletes with 2 or more data points compared to those with only n = 1 (p < .001), with further increases in performance with an increasing number of data points per athlete. The estimated performance decline was lower in people with 2 or more results (sprint, 10 km, jumps; p < .001). In conclusion, we showed that longitudinal data are associated with higher performance and lower performance decline rates.

Training and Racing Behavior of Recreational Runners by Race Distance-Results From the NURMI Study (Step 1)

The present study investigated pre-race preparation of a large sample of recreational runners competing in different race distances (e.g., shorter than half-marathon, half-marathon, marathon and ultra-marathon). An online questionnaire was used and a total of 3,835 participants completed the survey. Of those participants, 2,864 (75%) met the inclusion criteria and 1,628 (57%) women and 1,236 (43%) men remained after data clearance. Participants were categorized according to race distance in half-marathon (HM), and marathon/ultra-marathon (M/UM). Marathon and ultra-marathon data were pooled since the marathon distance is included in an ultra-marathon. The most important findings were (i) marathon and ultra-marathon runners were more likely to seek advice from a professional trainer, and (ii) spring was most commonly reported across all subgroups as the planned season for racing, (iii) training volume increased with increasing race distance, and (iv) male runners invested more time in training compared to female runners. In summary, runners competing in different race distances prepare differently for their planned race.

Clinical Trial Registration:www.ClinicalTrials.gov, identifier ISRCTN73074080. Retrospectively registered 12th June 2015.

An Analysis of Participation and Performance of 2067 100-km Ultra-Marathons Worldwide

This study aimed to analyze the number of successful finishers and the performance of the athletes in 100-km ultra-marathons worldwide. A total of 2067 100-km ultra-marathon races with 369,969 men and 69,668 women competing between 1960 and 2019 were analyzed, including the number of successful finishers, age, sex, and running speed. The results showed a strong increase in the number of running events as well as a strong increase in the number of participants in the 100-km ultra-marathons worldwide. The performance gap disappeared in athletes older than 60 years. Nevertheless, the running speed of athletes over 70 years has improved every decade. In contrast, the performance gap among the top three athletes remains persistent over all decades (F = 83.4, p < 0.001; _pη² = 0.039). The performance gap between the sexes is not significant in the youngest age groups (20–29 years) and the oldest age groups (>90 years) among recreational athletes and among top-three athletes over 70 years. In summary, especially for older athletes, a 100-km ultra-marathon competition shows an increasing number of opponents and a stronger performance challenge. This will certainly be of interest for coaches and athletes in the future, both from a scientific and sporting point of view.

Participation and Performance in the Oldest Ultramarathon-Comrades Marathon 1921-2019

Participation and performance trends have been analyzed for different ultramarathons for limited time periods. This study examined trends in participation and performance in the oldest ultramarathon in the world, the 'Comrades Marathon' (South Africa), during a century (1921-2019). Data from www.ultra-marathon.org on 100 000 unique finishers were analysed using different general linear models. Women represented 4.2% of the total sample (n=4152), and the first women ran this race in 1978. Before the year 1965, the number of participants in the race ranged between 5 and 35 athletes, then started to grow exponentially until mid 90's. An increase in finishers in the 70 s mainly due to an increase in male athletes in age groups 30-39, 40-49 and 50-59 years was observed (p<0.001). A stable running speed for overall women and men but an improvement in performance for the annual top five women and men were shown (p<0.001). Male runners were faster than female runners for all age groups (p<0.001). While overall performance was not improved across years, the annual top five women and men were able to improve their performance over years.

Longitudinal trends in master track and field performance throughout the aging process: 83,209 results from Sweden in 16 athletics disciplines

In the research of age-related performance declines, the value of cross-sectional versus longitudinal data is an ongoing debate. This paper analyses the largest longitudinal master track and field data set ever published to compare the age-related decline in performance between 16 athletics disciplines in cross-sectional and longitudinal data. The data set contained 83,209 results (64,948 from men, 78.1%; 18,261 from women, 21.9%) from 34,132 athletes (26,186 men, 76.7%; 7946 women, 23.3%), aged 35-97 years. In 61 athletes, 20 or more, and in 312 athletes, 15 or more results were available. The data were analyzed by regression statistics/ANCOVA. Men had a higher performance than women, irrespective of discipline in both cross-sectional and longitudinal data (p < 0.001). The performance in cross-sectional data was lower compared with the longitudinal data in all events and at any age (p ≤ 0.007) except for 1000 m men. The average age was lower in the cross-sectional than the longitudinal data (p < 0.001); men 46 and 58 years, women 44 and 56 years, respectively. The annual percentage rate of decline did not differ significantly between cross-sectional and longitudinal data, or between sexes in most disciplines. Performance declines after age 70 were 1.7 times (men) and 1.4 times (women) as steep as before. In conclusion, although longitudinal master athletics data of athletes with 10 and more results has higher average performance and age compared with cross-sectional data, cross-sectional data give a good impression of the annual percentage decline in performance, which was similar in men and women.

Different Predictor Variables for Women and Men in Ultra-Marathon Running-The Wellington Urban Ultramarathon 2018

Ultra-marathon races are increasing in popularity. Women are now 20% of all finishers, and this number is growing. Predictors of performance have been examined rarely for women in ultra-marathon running. This study aimed to examine the predictors of performance for women and men in the 62 km Wellington Urban Ultramarathon 2018 (WUU2K) and create an equation to predict ultra-marathon race time. For women, volume of running during training per week (km) and personal best time (PBT) in 5 km, 10 km, and half-marathon (min) were all associated with race time. For men, age, body mass index (BMI), years running, running speed during training (min/km), marathon PBT, and 5 km PBT (min) were all associated with race time. For men, ultra-marathon race time might be predicted by the following equation: (r² = 0.44, adjusted r² = 0.35, SE = 78.15, degrees of freedom (df) = 18) ultra-marathon race time (min) = −30.85 ± 0.2352 × marathon PBT + 25.37 × 5 km PBT + 17.20 × running speed of training (min/km). For women, ultra-marathon race time might be predicted by the following equation: (r² = 0.83, adjusted r² = 0.75, SE = 42.53, df = 6) ultra-marathon race time (min) = −148.83 + 3.824 × (half-marathon PBT) + 9.76 × (10 km PBT) − 6.899 × (5 km PBT). This study should help women in their preparation for performance in ultra-marathon and adds to the bulk of knowledge for ultra-marathon preparation available to men.

The "New York City Marathon": participation and performance trends of 1.2M runners during half-century

The aim of the present study was to examine trends in participation, performance, age and nationality during a ~ 50-years period in the largest dataset ever studied in the "New York City Marathon". We analysed 1,174,331 finishers (women, n= 349,145, age 39.7 ± 8.7 years; men, n= 825,186, 41.7 ± 9.2 years). The overall participation increased across calendar years for all nationalities, and this increase was more pronounced in women, which resulted in a decreasing men-to-women ratio. Men were faster and older than women. Ethiopians and Kenyans were the fastest and youngest in women and men, respectively. Japanese were the slowest and Germans were the oldest in both sexes. Race time increased across years. Coaches and fitness trainers should be aware of these trends and should emphasize the development of training programs for older and slower runners.

Russians are the fastest and the youngest in the "Comrades Marathon"

The present retrospective study intended to determine age, performance, the role of nationality and participation trends across calendar years in runners competing in "Comrades Marathon", the ultra-marathon with the longest tradition and the highest number of finishers worldwide. We analysed 235,467 finishers (40,211 women and 195,256 men) competing between 1994 and 2017. In women and men, Russians were the fastest (12.55 ± 2.03 km/h and 12.24 ± 2.93 km/h, respectively) and Indians the slowest (7.87 ± 0.64 km/h and 7.91 ± 0.60 km/h) (p < 0.001, η2 = 0.053 and η2 = 0.010, small effect size, ES). Also, Russians were the youngest (33.9 ± 4.6 and 36.3 ± 5.9 years, respectively) and Japanese the oldest (49.3 ± 9.6 and 51.4 ± 12.3 years, respectively) (p < 0.001, η2 = 0.011, small ES). Performance improved (r = 0.90 in women and r = 0.92 in men), age of finishers (r = 0.91 in women and r = 0.97 in men), participation (r = 0.92 in women and r = 0.87 in men) and sex difference in age increased (r = 0.71), whereas men-to-women ratio (r = -0.91) and sex difference in performance (r = -0.68) decreased across calendar years (p < 0.001). In summary, runners from Russia were the fastest and the youngest in both sexes. The knowledge of the relationship of nationality with performance, age and participation trends of finishers, and changes across calendar years are of practical importance for ultra-runners and coaches working with them.

The effect of sex, age and performance level on pacing of Ironman triathletes

The aim of the present study was to examine the effect of sex, age and performance level on pacing of Ironman triathletes. Split times (i.e. swimming, cycling, and running) and overall race times of 343,345 athletes competing between 2002 and 2015 in 253 different Ironman triathlon races were analyzed. Participants were classified into nine performance groups according to their overall race time. Times in swimming, cycling, running and transition were expressed as percentage of the overall race time. Women spent relatively less time (%) in swimming, running and transition time, and more time (%) in cycling than men (p < 0.001). The fastest performance group was relatively faster in running (34.8 ± 1.4 versus 40.3 ± 3.0%, η²= 0.098) and transition time (0.9 ± 0.3 versus 2.2 ± 0.6%, η²= 0.178), and relatively slower in swimming (10.2 ± 0.8 versus 9.8 ± 1.5%, η²= 0.018) and cycling (54.1 ± 1.4 versus 47.8 ± 2.8%, η²= 0.138) than the slowest performance group (p < 0.001). The younger age groups were relatively faster in swimming, running and transition time, but relatively slower in cycling. In summary, the fastest Ironman triathletes were the relatively fastest in running and transition times. Thus, race tactics in an Ironman triathlon should focus on saving energy during swimming and cycling for the running split.

World Single Age Records in Running From 5 km to Marathon

This study investigated the relationship between race times and age, in 1-year intervals, by using the world single age records, from 5 km to marathon running (i. e., 5 km, 4 miles, 8, 10, 12, 15 km, 10 miles, 20 km, half-marathon, 25 km, 30 km, and marathon). For each race, a regression model was fitted. Effects of sex, alone and in interaction with age, and the effect of country of origin on performance were examined in a multi-variable model. The relationship between age and race time was modeled through a 4th order-polynomial function. Women achieved their best half-marathon and marathon race time, respectively, 1 year and 3 years earlier in life than men. On the contrary, in the other races, the best women performances were achieved later in life than men (i.e., 4 miles and 30 km: 2 years later, 8 km: 3 years later, 15–20–25 km: 1 year later, 10 miles: 4 years) or at the same age (i.e., 5, 10, 12 km). Moreover, age of peak performance did not change monotonically with the distance of race. For all races, except 12 km, sex differences had an absolute maximum at old ages and a relative maximum near the age of peak performance. From 8 km onward, estimated sex differences were increasing with increasing race distance. Regarding country, runners from Canada were slower than runners from the United States of America in 5 km by 00:10:05 h:min:s (p < 0.001) and in half-marathon by 00:18:43 h:min:s (p < 0.01). On the contrary, in marathon, they were 00:18:43 h:min faster (p < 0.05). Moreover, in 10 miles, runners from Great Britain were 00:02:53 h:min:s faster (p < 0.05) than runners from the United States of America. In summary, differences seem to exist in the age of peak performance between women and men and for nearly all distances sex differences showed an absolute maximum at old ages and relative maximum near the age of peak performance. Thus, these findings highlight the need for sex-specific training programs, especially near the age of peak performance and for elder runners.

Jumping and throwing performance in the World Masters' Athletic Championships 1975-2016

Participation and performance of elite age group athletes from 35-39 to 95-99 years competing in World Masters Athletics (WMA) Championships 1975-2016 were examined for throwing (discus, hammer, javelin and shot put) and jumping (high jump, long jump, pole vault and triple jump) events. Overall, 21,723 observations from 8,974 master athletes were analysed. A mixed regression model with sex, age group, calendar year and interactions terms (sex-age group; sex-year) defined as fixed effects was performed for each event separately. Performances over time were increasing overall for each event, with a cubic trend. Compared with women, men had better performances (e.g. in triple jump the estimated difference was 3.378 meters, p < 0.001). However, women improved their performance more than men across calendar years. Performances declined with age for each event (e.g. in triple jump, compared with age group 45-49 years, performance in age group 35-39 years was 1.041 meter better and in age group 85-89 years was 5.342 meter worse). In summary, performance in jumping and throwing events of WMA Championships improved across calendar years, whereas the decline of performance with age was dependent on sex and event.

Linear Decrease in Athletic Performance During the Human Life Span

Master athletes maintain high physical activity levels and have better health than age-matched non-athletes. World records show accelerated declines after age 70 in swimming, long-distance running and sprint performance. However, less is known about age-related performance declines in the general master athlete population and whether decline rates differ between disciplines and genders. We interrogated a dataset including all track and field athletes of North Rhine from 2001 to 2014 to assess age-related changes in performance. 27,088 results of athletes between 11 and 89 years of age in 12 disciplines were analyzed by regression statistics. The analyses showed an accelerated decline beyond the age of 70 in sprint, middle- and long-distance running, while in throwing and jumping disciplines the performance continued a linear decline. Patterns of decline differed between men and women. The steepest declines were observed in javelin throw and 400 m (women), and in pole vault and 800 m (men). In conclusion, performance declines in aging depend more on the specific profile of requirements than previously assumed.

Cognitive performance and self-reported sleepiness are modulated by time-of-day during a mountain ultramarathon

Ninety-two runners completed the study during a 168 km mountain ultramarathon (MUM). Sleepiness, self-reported sleep duration, and cognitive performance were assessed the day before the race and up to eight checkpoints during the race. Sleepiness was assessed using the Karolinska Sleepiness Scale. Cognitive performance was also assessed using the Digital Symbol Substitution Task (DSST). Runner reported 23.40 ± 22.20 minutes of sleep (mean ± SD) during the race (race time: 29.38 to 46.20 hours). Sleepiness and cognitive performance decrements increased across this race, and this was modulated by time-of-day with higher sleepiness and greater performance decrements occurring during the early morning hours. Runners who slept on the course prior to testing had poorer cognitive performance, which may suggest that naps on the course were taken due to extreme exertion. This study provides evidence that cognitive performance deficits and sleepiness in MUM are sensitive to time into race and time-of-day.

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.

Age of peak performance in 50-km ultramarathoners - is it older than in marathoners?

PURPOSE

Despite the increasing popularity of 50-km ultramarathons during the last few years, only limited information is available regarding the trends in its performance and participation. The aim of the present study was to examine the age of peak running performance in female and male 50-km ultramarathoners using second-order nonlinear regression analyses.

METHODS

Data from 494,414 runners (124,045 women and 370,369 men) who finished a 50-km ultramarathon between 1975 to 2016 were analyzed.

RESULTS

When the top ten finishers in 1-year age-groups were analyzed, the age of peak running speed was 41 years in both women and men. When the fastest finishers in 1-year age-group intervals were analyzed, the age of peak running speed was 40 years in women and 39 years in men.

CONCLUSION

In summary, the age of peak running speed in 50-km ultramarathoners is older than what has been reported by previous studies for marathons. Women seem to achieve the best race time in a 50-km ultramarathon later in life compared with men. These findings are of great practical value for coaches and fitness trainers when setting performance goals for 50-km ultramarathon runners.

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.