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.

The aims of this study were (1) to investigate the participation and performance trends at the '100 km Lauf Biel' in Switzerland from 1998 to 2010, and (2) to compare the age-related changes in 100-km running performance between males and females. For both sexes, the percent of finishers significantly (P<0.01) decreased for the 18-29 and the 30-39-year age groups, while it significantly (P<0.01) increased for the 40-49 and the 50-59-year age groups over the studied period. From 1998 to 2010, the mean age of the top ten finishers increased by 0.4 years per annum for both females (P=0.02) and males (P=0.003). The running time for the top ten finishers remained stable for females, while it significantly (P=0.001) increased by 2.4 min per annum for males. There was a significant (P<0.001) age effect on running times for both sexes. The best 100-km running times was observed for the age comprised between 30 and 49 years for males, and between 30 and 54 years for females, respectively. The age-related decline in running performance was similar until 60-64 years between males and females, but was greater for females compared to males after 65 years. Future studies should investigate the lifespan from 65 to 75 years to better understand the performance difference between male and female master ultra-marathoners.

We examined the changes in participation and performance trends in ultra‐triathlons, from the Double Iron (7.6 km swimming, 360 km cycling, 84.4 km running) to the Deca Iron (38 km swimming, 1800 km cycling, 422 km running), between 1985 (first year of a Double Iron) and 2009 (25 years). The mean finish rate for all distances and races was 75.8%. Women accounted for ∼8–10% of the ultra‐triathlons starters. For Double and Triple Iron, the number of finishers per year increased, from 17 to 98 and from 7 to 41, respectively. In the Deca Iron, the finishers per race have remained <20 since the first event was held, up to 2009. Concerning World best performances, the men were ∼19% faster than the women in both the Double and Triple Iron, and ∼30% faster in a Deca Iron. With the increasing length of ultra‐triathlons, the best women became relatively slower compared with the best men. Further investigations are required to understand why this gender difference in total performance time increased with the distance in ultra‐triathlons.

Background The coronavirus disease 2019 (COVID-19) pandemic has resulted in a strong negative impact on economic and social life worldwide. It has also negatively influenced people’s general health and quality of life. The aim of the present study was to study the impact of social distancing on physical activity level, and the association between mood state (depression and anxiety level) or sex with actual physical activity levels, the change in physical activity caused by social distancing period, the adhesion level to social distancing, the adoption time of social distancing, family income and age. Methods A self-administered questionnaire with personal, quarantine, physical activity, and mood state disorders information’s was answered by 2140 Brazilians of both sex who were recruited through online advertising. Results The physical activity level adopted during the period of social distancing (2.9 ± 1.1) was lower than that adopted prior to the pandemic period (3.5 ± 0.8, p < 0.001). Thirty percent of the participants presented symptoms of moderate/severe depression and 23.3% displayed moderate/severe anxiety symptoms. A greater presence of symptoms related to anxiety and depression were associated with low physical activity levels, low family monthly income, and younger age. A higher percentage of men who had no mood disorders was observed among those who were very active than among those less active. Conclusion The COVID-19 pandemic has a negative impact on physical activity. Those who reduced their level of physical activity had the highest levels of mood disorders. Therefore, physical activity programs should be encouraged, while respecting the necessary social distancing to prevent the spread of Severe Acute Respiratory Syndrome Coronavirus 2.

Little research has examined ultra-endurance swimming performances. The 'English Channel Swim', where swimmers have to cover a distance of 32 km between England and France represents a unique long-distance, open-water, sea-swimming challenge, and each year swimmers from all over the world try to succeed in this challenge. The best times in minutes and the nationality of successful men and women swimmers were analysed from 1900 to 2010. A total of 1,533 swimmers (455 women and 1,078 men) from more than 40 countries have successfully completed the 'English Channel Swim'. Great Britain was the country most represented, with 38% of the total, followed by the United States with 20%. Swim speed has increased progressively for both sexes (P < 0. women's open-water ultra-swim performances.

We investigated in 27 male Ironman triathletes aged 30.3 (9.1) years, with 77.7- (9.8) kg body mass, 1.78- (0.06) m body height, 24.3- (2.2) kg·m⁻² body mass index (BMI), and 14.4 (4.8) % body fat and in 16 female Ironman triathletes aged 36.6 (7.0) years, with 59.7- (6.1) kg body mass, 1.66- (0.06) m body height, 21.5 (1.0) kg·m⁻² BMI, and 22.8 (4.8) % body fat to ascertain whether anthropometric or training variables were related to total race time. The male athletes were training 14.8 (3.2) h·wk⁻¹ with a speed of 2.7 (0.6) km·h⁻¹ in swimming, 27.3 (3.0) in cycling, and 10.6 (1.4) in running. The female athletes trained for 13.9 (3.4) h·wk⁻¹ at 2.1 (0.8) km·h⁻¹h in swimming, 23.7 (7.6) km·h⁻¹ in cycling, and 9.0 (3.7) km·h⁻¹ in running, respectively. For male athletes, percent body fat was highly significantly (r² = 0.583; p < 0.001) associated with total race time. In female triathletes, training volume showed a relationship to total race time (r² = 0.466; p < 0.01). Percent body fat was unrelated to training volume for both men (r² = 0.001; p > 0.05) and women (r² = 0.007; p > 0.05). We conclude that percent body fat showed a relationship to total race time in male triathletes, and training volume showed an association with total race time in female triathletes. Presumably, the relationship between percent body fat, training volume, and race performance is genetically determined.

Despite of the growth of ultra-endurance sports events (of duration >6 h) over the previous few decades, the age-related declines in ultra-endurance performance have drawn little attention. The aim of the study was to analyse the changes in participation and performance trends of older (>40 years of age) triathletes between 1986 and 2010 at the Hawaii Ironman triathlon consisting of 3.8 km swimming, 180 km cycling and 42 km running. Swimming, cycling, running and total times of the best male and female triathletes between 18 and 69 years of age who competed in the Hawaii Ironman triathlon were analysed. The relative participation of master triathletes increased during the 1986-2010 period, while the participation of triathletes younger than 40 years of age decreased. Linear regression showed that males older than 44 years and females older than 40 years significantly improved their performances in the three disciplines and in the total time taken to complete the race. Gender differences in total time performance significantly decreased in the same time period for all age groups between the 40-44 and 55-59 years ones. The reasons for these relative improvements of Ironman athlete performances in older age groups remain, however, unknown. Further studies investigating training regimes, competition experience or sociodemographic factors are needed to gain better insights into the phenomenon of increasing participation and improvement of ultra-endurance performance with advancing age.

In 169 male 100-km ultra-marathoners, the variables of anthropometry, training, and prerace experience, in order to predict race time, were investigated. In the bivariate analysis, age (r = .24), body mass (r = .20), Body Mass Index (r = .29), circumference of upper arm (r = .26), percent body fat (r = .45), mean weekly running hours (r = -.21), mean weekly running kilometers (r = -.43), mean speed in training (r=-.56), personal best time in a marathon (r = .65), the number of finished 100-km ultra-runs (r = .24), and the personal best time in a 100-km ultra-run (r = .72) were associated with race time. Stepwise multiple regression showed that training speed (p < .0001), mean weekly running kilometers (p < .0001), and age (p < .0001) were the best correlations for a 100-km race time. Performance may be predicted (n=169, r2 = .43) by the following equation: 100-km race time (min) = 1085.60 - 36.26 x (training speed, km/hr.) - 1.43 x (training volume, km/wk.) + 2.50 x (age, yr.). Overall, intensity of training might be more important for a successful outcome in a 100-km race than anthropometric attributes. Motivation to train intensely for such an ultra-endurance run should be explored as this might be the key for a successful finish.