Increase in finishers and improvement of performance of masters runners in the Marathon des Sables

Women Reduce the Performance Difference to Men with Increasing Age in Ultra-Marathon Running

Age and sex are well-known factors influencing ultra-marathon race performance. The fact that women in older age groups are able to achieve a similar performance as men has been documented in swimming. In ultra-marathon running, knowledge is still limited. The aim of this study was to analyze sex-specific performance in ultra-marathon running according to age and distance. All ultra-marathon races documented in the online database of the German Society for Ultra-Marathon from 1964 to 2017 for 50-mile races (i.e., 231,980 records from 91,665 finishers) and from 1953 to 2017 for 100-mile races (i.e., 107,445 records from 39,870 finishers) were analyzed. In 50-mile races, race times were 11.74 ± 1.95 h for men and 12.31 ± 1.69 h for women. In 100-mile races, race times were 26.6 ± 3.49 h for men and 27.47 ± 3.6 h for women. The sex differences decreased with older age and were smaller in 100-mile (4.41%) than in 50-mile races (9.13%). The overall age of peak performance was 33 years for both distances. In summary, women reduced the performance difference to men with advancing age, the relative difference being smaller in 100-mile compared to 50-mile races. These findings might aid coaches and ultra-marathon runners set long-term training goals considering their sex and age.

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.

Increased participation and improved performance in age group backstroke master swimmers from 25-29 to 100-104 years at the FINA World Masters Championships from 1986 to 2014

Participation and performance trends in age group athletes have been investigated for different sport disciplines, but not for master swimmers. The knowledge on this topic is still missing for a particular stroke such as backstroke. Changes in participation and performance of male and female age group backstroke swimmers (≥25 years) competing in 50, 100 and 200 m pool swimming at the FINA World Masters Championships held between 1986 and 2014 were investigated using mixed-effects regression analyses. The overall participation was n = 26,217 including n = 13,708 women and n = 12,509 men. In 50 m, female (age groups 85–89 years; p = 0.002) and male participation (age groups 55–59; p = 0.030 and 80–84 years; p = 0.002) increased, while female participation decreased in age groups 55–59 (p = 0.010) and 60–64 years (p = 0.050). In 100 and 200 m, participation increased in age groups 45–49, 50–54, 65–69, 70–74, 80–84 years. Swimmers in age groups 25–29 to 95–99 years improved performance over all distances. Women were slower than men in age groups 25–29 to 80–84 years, but not in age groups 85–89 to 95–99 years over all distances. In 50 m and 100 m, the sex difference decreased in age groups 40–44 (p = 0.007 and p = 0.005), 45–49 (p = 0.017 and p = 0.034), 50–54 (p = 0.002 and p = 0.040), to 55–59 years (p = 0.002 and p = 0.004). In 200 m, the sex difference decreased in age groups 40–44 (p = 0.044) and 90–94 (p = 0.011), but increased in age group 25–29 years (p = 0.006). In summary, in age group backstroke swimmers, (1) participation increased or remained unchanged (except women in age groups 55–59 and 60–64 years in 50 m), (2) swimming performance improved in all age groups from 25–29 to 95–99 years over all distances, (3) men were faster than women in age groups 25–29 to 80–84 years (except age groups 85–89 to 95–99 years) over time and all distances.

Pacing strategy in male elite and age group 100 km ultra-marathoners

Pacing strategy has been investigated in elite 100 km and elite 161 km (100 mile) ultra-marathoners, but not in age group ultra-marathoners. This study investigated changes in running speed over segments in male elite and age group 100 km ultra-marathoners with the assumption that running speed would decrease over segments with increasing age of the athlete. Running speed during segments in male elite and age group finishers for 5-year age groups (ie, 18-24 to 65-69 years) in the 100 km Lauf Biel in Switzerland was investigated during the 2000-2009 period. Average running speed over segment time station (TS) TS1-TS2 (56.1 km) was compared with running speed Start-TS1 (38 km) and Start-TS3 (76.7 km) and running speed TS2-TS3 was compared with running speed Start-Finish. For the top ten athletes in each edition, running speed decreased from 2000 to 2009 for TS1-TS2 and TS2-TS3 (P<0.0001) but not in TS3-Finish (P>0.05). During TS1-TS2, athletes were running at 98.0%±2.1% of the running speed of Start-TS1. In TS2-TS3, they were running at 94.6%±3.4% of the running speed of TS1-TS2. In TS3-Finish, they were running at 95.5%±3.8% of running speed in TS2-TS3. For age group athletes, running speed decreased in TS1-TS2 and TS2-TS3. In TS3-Finish, running speed remained unchanged with the exception of the age group 40-44 years for which running speed increased. Running speed showed the largest decrease in the age group 18-24 years. To summarize, the top ten athletes in each edition maintained their running speed in the last segment (TS3-Finish) although running speed decreased over the first two segments (TS1-TS2 and TS2-TS3). The best pacers were athletes in the age group 40-44 years, who were able to achieve negative pacing in the last segment (TS3-Finish) of the race. The negative pacing in the last segment (TS3-Finish) was likely due to environmental conditions, such as early dawn and the flat circuit in segment TS3-Finish of the race.