Changes in single skinfold thickness in 100 km ultramarathoners

Changes in Sex Difference in Time-Limited Ultra-Cycling Races from 6 Hours to 24 Hours

Background and objective: Existing research shows that the sex differences in distance-limited ultra-cycling races decreased with both increasing race distance and increasing age. It is unknown, however, whether the sex differences in time-limited ultra-cycling races will equally decrease with increasing race distance and age. This study aimed to examine the sex differences regarding performance for time-limited ultra-cycling races (6, 12, and 24 h). Methods: Data were obtained from the online database of the Ultra-Cycling Marathon Association (UMCA) of time-limited ultra-cycling races (6, 12, and 24 h) from the years 1983–2019. A total of 18,241 race results were analyzed to compare cycling speed between men and women by calendar year, age group (<29; 30–39; 40–49; 50–59; 60–69; >70 years), and race duration. Results: The participation of both men (85.1%) and women (14.9%) increased between 1983 and 2019. The age of peak performance was between 40 and 59 years for men and between 30 and 59 years for women. Between 2000 and 2019, more men (63.1% of male participants and 52.2% of female participants) competed in 24 h races. In the 24 h races, the sex difference decreased significantly in all age groups. Men cycled 9.6% faster than women in the 12 h races and 4% faster in the 24 h races. Both women and men improved their performance significantly across the decades. Between 2000 and 2019, the improvement in the 24 h races were 15.6% for men and 21.9% for women. Conclusion: The sex differences in cycling speed decreased between men and women with increasing duration of ultra-cycling races and with increasing age. Women showed a greater performance improvement than men in the last 20 years. The average cycling speed of men and women started to converge in the 24 h races.

Sex-specific differences in somatic investment and strategies of physical activity among Portuguese schoolchildren

OBJECTIVES

Physical activity (PA) is required for healthy growth, development, and maturation and plays an important role in the prevention of overweight and obesity in childhood and adolescence. Sex-differences in PA levels are well documented, with boys spending more time in PA, especially in moderate-to-vigorous activities. Following the Life History Theory, our aim is to study if PA affects the fat tissues increases during childhood and juvenile phases in both sexes.

METHODS

Time spent in sedentary, light, and moderate-to-vigorous PA levels were measured in a sample of 415 Portuguese children and juveniles (207 females/208 males; aged 6-11 years), using an accelerometer for 7 days. Skinfolds related with body fat were objectively collected and socioeconomic status factors were reported using a parental questionnaire.

RESULTS

The outcomes show that girls' and boys' fat variables increased during the end of the childhood and the juvenile phase. However, these variables were differently affected by PA. Girls increased fat variables with the sedentary activity while boys decreased fat variables with moderate-to-vigorous PA. Alike, active boys but not girls reduced the fat increase tendency with age.

CONCLUSIONS

Although both sexes displayed a general fat increment with age, moderate-to-vigorous PA dampens the increase only in boys. In fact, active girls increased body fat in the same manner as non-active girls. From an evolutionary perspective, it could explain sex-specific somatic strategies related to future reproduction or, with future mating and intrasexual competition.

Can the Performance Gap between Women and Men be Reduced in Ultra-Cycling?

This study examined a large dataset of ultra-cycling race results to investigate the sex difference in ultra-cycling performance (100 to 500 miles) according to age and race distance. Data from the time period 1996-2018 were obtained from online available database of the ultra-cycling marathon association (UMCA), including distance-limited ultra-cycling races (100, 200, 400, and 500 miles). A total of 12,716 race results were analyzed to compare the performance between men and women by calendar year, age group (18-34, 35-44, 45-59, and 60+ years), and race distance. Men were faster than women in 100 and 200 mile races, but no sex differences were identified for the 400 and 500 mile races. The performance ratio (average cycling speed_men/average cycling speed_women) was smaller in the 200 mile races compared to the 100 mile races and remained stable in the 400 and 500 mile races. In all race distances, the difference in average cycling speed between women and men decreased with increasing age. The gender gap in performance was closed in several distance-limited ultra-cycling races, such as the 400 and 500 mile races.

Participation and Performance Trends in the Oldest 100-km Ultramarathon in the World

Participation and performance trends in ultramarathon running have been investigated for large datasets and long period of times with an increase in participants and an improvement in performance. However, the analysis of ultramarathons across many decades is missing. We analyzed these trends for 96,036 athletes (88,286 men and 7750 women) from 67 countries competing between 1956 and 2019 in ‘100 km Lauf Biel’ in Switzerland, the oldest 100-km ultramarathon in the world. More men than women participated in all years. The number of male participants reached a peak at around 1985 and a decline in participation occurred thereafter. Women started competing in 1962. Men were always faster than women and both women and men reduced their race times over years. After about 1985, both overall women and men and both female and male winners were not able to improve race times. For men, athletes from all age groups below the age of 49 years old reached a peak of participation in the 1980s, and showed a decrease since then. Regarding age groups, the decrease first started in age group 20–29 years, followed by 30–39, 40–49, 50–59, and 60–69 years. For athletes in age groups 70–79 and 80–89 years, no decrease occurred. For women, age group athletes in age groups 40–49, 50–59, and 60–69 years increased their participation, whereas age groups 20–29 and 30–39 peaked in the late 1980s and started to decrease or stabilize, respectively. Switzerland, Germany, and France were the countries with the highest numbers of participants throughout the history of the race. In men, race times increased after about 1990 for most nationalities; only runners from Germany seemed to stabilize their performance. In women, runners from Italy, France, and Austria improved their performance over the years. In summary, the analysis of the oldest 100-km ultramarathon in the world showed a decrease in participation and an impairment in performance in the last 60 years. These changes were due to a decrease in the number of male ultramarathoners in around the 1980s, where mainly the number of age group runners younger than 70 years decreased.

Muscle damage, physiological changes, and energy balance in ultra-endurance mountain-event athletes

The biological response to ultra-endurance mountain race events is not yet well understood. The aim of this study was to determine the biochemical and physiological changes after performing an ultra-endurance mountain race in runners. We recruited 11 amateur runners (age: 29.7 ± 10.2 years; height: 179.7 ± 5.4 cm; body mass: 76.7 ± 10.3 kg). Muscle damage, lactate concentration, energy balance, rating of perceived exertion (RPE), heart rate (HR), heart rate variability (HRV), body composition changes, and jump performance were analyzed before, during (only lactate, HR, and HRV), and after the race. Athletes completed 54 km in 6 h, 44 min (±28 min). After the race, myoglobin and creatine kinase concentration increased from 14.9 ± 5.2 to 1419.9 ± 1292.1 μg/L and from 820.0 ± 2087.3 to 2421.1 ± 2336.2 UI/L, respectively (p < 0.01). In addition, lactate dehydrogenase and troponin I significantly increased after the race (p < 0.01). Leukocyte and platelet count increased by 180.6% ± 68.9% and 23.7% ± 11.2%, respectively (p < 0.001). Moreover, after the competition, athletes presented a 3704 kcal negative energy balance; a significant increase in RPE values; a decrease in countermovement and squat jump height; and a decrease in body mass and lower limb girths. During the event, lactate concentration did not change and subjects presented a mean HR of 158.8 ± 17.7 beats/min, a significant decrement in vagal modulation, and a significant increase in sympathetic modulation. Despite the relative “low” intensity achieved, ultra-endurance mountain race is a stressful stimulus that produces a high level of muscle damage in the athletes. These findings may help coaches to design specific training programs that may improve nutritional intake strategies and prevent muscle damage.

Relationship of anthropometric and training characteristics with race performance in endurance and ultra-endurance athletes

A variety of anthropometric and training characteristics have been identified as predictor variables for race performance in endurance and ultra-endurance athletes. Anthropometric characteristics such as skin-fold thicknesses, body fat, circumferences and length of limbs, body mass, body height, and body mass index were bi-variately related to race performance in endurance athletes such as swimmers in pools and in open water, in road and mountain bike cyclists, and in runners and triathletes over different distances. Additionally, training variables such as volume and speed were also bi-variately associated with race performance. Multi-variate regression analyses including anthropometric and training characteristics reduced the predictor variables mainly to body fat and speed during training units. Further multi-variate regression analyses including additionally the aspects of previous experience such as personal best times showed that mainly previous best time in shorter races were the most important predictors for ultra-endurance race times. Ultra-endurance athletes seemed to prepare differently for their races compared to endurance athletes where ultra-endurance athletes invested more time in training and completed more training kilometers at lower speed compared to endurance athletes. In conclusion, the most important predictor variables for ultra-endurance athletes were a fast personal best time in shorter races, a low body fat and a high speed during training units.