Effects of age on marathon finishing time among male amateur runners in Stockholm Marathon 1979-2014

Analysis of the 50-mile ultramarathon distance using a predictive XGBoost model

Although the 50-mile ultramarathon is one of the most common race distances, it has received little scientific attention. The objective of this study was to assess how an athlete's age group, sex, nationality, and the race location, affect race speed. Utilizing a dataset with ultramarathon races from 1863 to 2022, a machine learning model based on the XGBoost algorithm was developed to predict the race speed based on the aforementioned variables. Model explainability tools, including model features relative importances and prediction distribution plots were then used to investigate how each feature affects the predicted race speed. The most important features, with respect to the predictive power of the XGBoost model, were the location of the race and the athlete's gender. The top 3 countries with the fastest predicted median race speeds were Slovenia, New Zealand, and Bulgaria for nationality and New Zealand, Croatia, and Serbia for the race location. The fastest median race speed was predicted for the age group 20-24 years, but a marked age-related performance decline only became apparent from the age group 40-44 years onward. Model predictions for male athletes were faster than for female athletes. This study offers insights into factors influencing race speed in 50-mile ultramarathons, which may be beneficial for athletes, coaches, and race organizers. The identification of nationalities and event countries with fast race speeds provides a foundation for further exploration in the field of ultramarathon events.

Running trends in Switzerland from 1999 to 2019: An exploratory observational study

BACKGROUND

Several single race events (5 km, 10 km, half-marathon, marathon, ultra-marathon) in different countries and different years have been analyzed in multiple studies, representing the rising interest in endurance-based activity and thus physical health. With focus on participation numbers, performance or sex difference, many single study results were obtained. The running trends in a whole country covering a longer period of time and several race distances are missing so far.

OBJECTIVES

The aim of this study is therefore to examine 5 km, 10 km, half-marathon, marathon and ultra-marathon races by age, sex, participation numbers and performance during two decades (1999-2019) for one country (Switzerland).

METHODS

In this exploratory observational study, we analyzed 1,172,836 finishers (370,517 women and 802,319 men) competing between 1999 and 2019 in 5 different race distances in Switzerland. We used publicly available data about the athletes and examined total finishing numbers, sex, age and performances (measured in m/s) via descriptive analyses and linear mixed models. Do-not-finishers were excluded.

RESULTS

The most frequented race was the half-marathon (33.1% of finishers), the less frequented was the ultra-marathon distance (8.5% of finishers). In most recent years, only the number of finishers in ultra-marathon, especially in trail runs increased. In total, there were more male finishers (68.4%) than female finishers (31.6%) and only in 5 km races, more women finished than men (55.3%). Men were faster than women and both sexes were running slower in all race distances across years. Athletes in 10 km races had the best performance within the five analyzed race distances. Median age increased with longer race distance and decreased in ultra-marathon in recent years.

CONCLUSION

In summary, finishing numbers especially in ultra-marathons increased with a focus on trail runs, female and male athletes had a declining performance across years in all race distances and men ran faster than women. Median age increased with longer race distance leading to more aged endurance-trained athletes. A downtrend in median age is found only in ultra-marathon in recent years. The results are important for athletes, race directors and coaches with regard to training schedules and the trend towards long distance races as well as for the medical attendance especially of older athletes, being more and more interested in endurance running.

Periodic paralysis across the life course: age-related phenotype transition and sarcopenia overlap

In Periodic Paralysis (PP), a rare inherited condition caused by mutation in skeletal muscle ion channels, the phenotype changes with age, transitioning from the episodic attacks of weakness that give the condition its name, to a more degenerative phenotype of permanent progressive weakness and myopathy. This leads to disability and reduced quality of life. Neither the cause of this phenotype transition, nor why it occurs around the age of 40 is known. However, 40 is also the age of onset of 'normal' age-related physiological decline when we consider (a) muscle mass and strength (b) physical function at the world class level and (c) age-related mitochondrial dysfunction. Elevated Na+, mitochondrial dysfunction and sarcoplasmic Ca2+ leak via the skeletal muscle ryanodine receptor (RyR1) have been implicated in both periodic paralysis myopathy and skeletal muscle ageing. We suggest this combination may trigger a negative spiral ultimately leading to progressive muscle failure. Understanding the interaction between ageing physiology and disease phenotype will provide a window into the healthy ageing process but also help understand how, and why PP phenotype changes with age. Understanding the mechanism underlying PP phenotype-transition and its link with ageing physiology, not only has the potential to identify the first disease modifying therapies for PP, but also to identify novel and potentially tractable mechanisms that contribute to sarcopenia, the pathological loss of muscle mass and function with age.

Age Differences in Recovery Rate Following an Aerobic-Based Exercise Protocol Inducing Muscle Damage Among Amateur, Male Athletes

Purpose: Compare recovery rates between active young (Y) and middle-aged (MA) males up to 48H post aerobically based, exercise-induced muscle damage (EIMD) protocol. A secondary aim was to explore the relationships between changes in indices associated with EIMD and recovery throughout this timeframe.

Methods: Twenty-eight Y (n = 14, 26.1 ± 2.9y, 74.5 ± 9.3 kg) and MA (n = 14, 43.6 ± 4.1y, 77.3 ± 12.9 kg) physically active males, completed a 60-min downhill running (DHR) on a treadmill at −10% incline and at 65% of maximal heart rate (HR). Biochemical, biomechanical, psychological, force production and muscle integrity (using MRI diffusion tensor imaging) markers were measured at baseline, immediately-post, and up to 48H post DHR.

Results: During the DHR, HR was lower (p < 0.05) in MA compared to Y, but running pace and distance covered were comparable between groups. No statistical or meaningful differences were observed between groups for any of the outcomes. Yet, Significant (p < 0.05) time-effects within each group were observed: markers of muscle damage, cadence and perception of pain increased, while TNF-a, isometric and dynamic force production and stride-length decreased. Creatine-kinase at 24H-post and 48H-post were correlated (p < 0.05, r range = −0.57 to 0.55) with pain perception, stride-length, and cadence at 24H-post and 48H-post. Significant (p < 0.05) correlations were observed between isometric force production at all time-points and IL-6 at 48H-post DHR (r range = −0.62 to (−0.74).

Conclusion: Y and MA active male amateur athletes recover in a comparable manner following an EIMD downhill protocol. These results indicate that similar recovery strategies can be used by trainees from both age groups following an aerobic-based EIMD protocol.

Blood serum denaturation profile examined by differential scanning calorimetry reflects the effort put into ultramarathon by amateur long-distance runners

The impact of participation in the ultramarathon on the health and mental and physical condition is very complex. Undoubtedly, exercise brings many benefits but also involves health risks. Especially such an extreme effort as the one associated with finishing the ultramarathon run, can be dangerous to the health of the runner. With the variety of possible biomarkers of excessive fatigue that threaten health and life, a question arises which of them are the best and which should be considered in amateur long-distance runners showing particularly high individual variability. In this study differential scanning calorimetry (DSC) has been applied to show the overall effect of the 12-h run on blood sera of participants. Serum samples were obtained from the blood of ten male amateur long-distance runners, collected before and immediately after the run. Distinct changes in the shape of DSC curves have been observed for serum after finishing the run relative to pre-race serum. Statistically significant differences between stages "before" and "after" ultramarathon running have been found for parameters of the endothermic transition associated with denaturation of serum proteins. An increase in the temperature (from 70.9 ± 0.9 to 75.8 ± 2.9 °C) and excess heat capacity (from 0.859 ± 0.201 to 1.102 ± 0.226 Jg-1 °C-1) at peak maximum, the enthalpy of serum denaturation (from 18.55 ± 6.52 to 22.08 ± 5.61 Jg^-1) and the first moment of the thermal transition with respect to the temperature (from the value of 67.0 ± 2.1 to 72.6 ± 2.1 °C) has been observed. These results show a clear impact of running an ultramarathon on the participant's blood serum.

Performance in 100-km Ultramarathoners-At Which Age, It Reaches Its Peak?

Nikolaidis, PT and Knechtle, B. Performance in 100-km ultramarathoners-At which age, it reaches its peak? J Strength Cond Res 34(5): 1409-1415, 2020-The number of those participating in 100-km ultramarathon has increased over the past years; however, we have limited knowledge about performance trends in this sport, and particularly, the effect of age. The aim of this study was to analyze the age when women and men runners achieve their peak performance considering 1- and 5-year age group intervals, and examining all or the fastest (i.e., top 10) participants in each age group. We analyzed 370,051 athletes (i.e., 44,601 women and 325,450 men) who finished a 100-km ultramarathon between 1959 and 2016, and studied the age of peak performance using a second-order nonlinear regression analysis. The age of peak performance was 40-44 years in women and 45-49 years in men when all finishers were analyzed, whereas it was 30-34 years in women and 35-39 years in men when the top 10 finishers were considered in 5-year age groups. When we analyzed finishers in 1-year age groups, we found the age of peak performance at 41 years in women and 45 years in men considering all finishers, and at 39 years in women and 41 years in men considering the top 10 finishers. In conclusion, the age of peak performance was younger in women than in men, which might reflect the overall younger age of women participants than men. Compared with previous studies, we observed the peak performance at an age older by ∼10 years, which could be attributed to an increase of finishers' age across calendar years. Because the knowledge of the age of peak performance is unique for each sport, coaches and fitness trainers might benefit from the findings of this study in the long-term training of their athletes.

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.

World Records in Half-Marathon Running by Sex and Age

The relationship between age and elite marathon race times is well investigated, but little is known for half-marathon running. This study investigated the relationship between half-marathon race times and age in 1-year intervals by using the world single age records in half-marathon running and the sex difference in performance from 5 to 91 years in men and 5 to 93 years in women. We found a fourth-order polynomial relationship between age and race time for both women and men. Women achieve their best half-marathon race time earlier in life than men, 23.89 years compared with 28.13 years, but when using a nonlinear regression analysis, the age of the fastest race time does not differ between men and women, with 26.62 years in women and 26.80 years in men. Moreover, the sex difference in half-marathon running performance increased with advancing age.

The Age of Peak Marathon Performance in Cross-Country Skiing-The "Engadin Ski Marathon"

Knechtle, B and Nikolaidis, PT. The age of peak marathon performance in cross-country skiing-the "Engadin Ski Marathon." J Strength Cond Res 32(4): 1131-1136, 2018-The age of the best endurance performance has been well investigated in flat city running marathons. However, we have no knowledge about the age of peak marathon performance in cross-country skiing, which would be of great practical value for athletes and coaches. Therefore, the aim of the present study was to examine the age of peak marathon performance in cross-country skiing. Participants were 162,991 men and 34,833 women competing between 1998 and 2016 in the "Engadin Ski Marathon." We considered the fastest for both women and men, and all finishers in 1-year age intervals. The men-to-women ratio increased across ages (r = 0.55, p < 0.0001). Men (44.27 ± 0.03 years, 15.73 ± 0.01 km·h) were 5.98 ± 0.07 years older and 2.14 ± 0.02 km·h faster (p < 0.0001) than women (38.29 ± 0.06 years, 13.58 ± 0.01 km·h). Considering the fastest participants in 1-year age intervals, the fastest speed for men (30.33 km·h) was achieved at the age of 29 years, and for women (28.76 km·h) at the age of 24 years. Considering all participants, the fastest speed for men (17.69 km·h) was observed at the age of 18 years, whereas for women (15.76 km·h) it was at the age of 17 years. In summary, for athletes and coaches, the age of peak performance in cross-country skiers competing in a marathon distance was much younger and closer to the peak of aerobic capacity than what was found by previous studies in marathon road runners.

Should Body Size Categories Be More Common in Endurance Running Events?

Thousands of endurance running events are held each year in the United States, and most of them use age and sex categories to account for documented effects of those factors on running performance. However, most running events do not provide categories of body mass, despite abundant evidence that it, too, dramatically influences endurance running performance. The purposes of this article are to (1) discuss how body mass affects endurance running performance, (2) explain several mechanisms through which body mass influences endurance running performance, and (3) suggest possible ways in which body mass might be categorized in endurance running events.

Sex- and age-related differences in half-marathon performance and competitiveness in the world's largest half-marathon - the GöteborgsVarvet

In road runners, the age-related performance decline has been well investigated for marathoners, but little is known for half-marathoners. We analysed data from 138,616 runners (48,148 women and 90,469 men) competing between 2014 and 2016 in GöteborgsVarvet, the world's largest half-marathon. The men-to-women ratio in participants increased with age, the fastest race times were observed in age groups ˂35 and 35-39 years in women and in age group 35-39 years in men, the main effect of sex and the sex × age group interaction on race time were trivial, and the competitiveness was denser in men and in the younger age groups. In summary, in half-marathon running in the largest half-marathon in the world, the GöteborgsVarvet, women achieved the fastest race time at an earlier age compared to men where the fastest race times were observed in women in age groups ˂35 and 35-39 years and in men in age group 35-39 years.

The age-related performance decline in marathon cross-country skiing - the Engadin Ski Marathon

Demographic and performance data from 197,825 athletes competing in "Engadin Ski Marathon" between 1998 and 2016 were analysed. When all finishers per age group were considered, there was no gender difference in time (2:59:00 in women versus 2:59:09 h:min:s in men; P = 0.914, η² < 0.001) and the main effect of age group on time was trivial (P < 0.001, η² = 0.007). When the top 10 finishers per age group were considered, men were faster than women (1:27:32 versus 1:34:19 h:min:s, respectively; P < 0.001, η² = 0.373), there was a large effect of age group on time (P < 0.001, η² = 0.590) and the gender difference was larger in the older than in the younger age groups (P < 0.001, η² = 0.534). The age of peak performance for all finishers by 1-year interval age group was 40.3 and 39.6 years in all women and men, respectively. The top 10 finishers by 1-year interval age group achieved their peak performance in the age of 38.4 and 42.2 years in women and men, respectively. The age of peak performance was older and the age-related performance decline occurred earlier in marathon cross-country skiing, compared to road-based marathon running.

Declines in marathon performance: Sex differences in elite and recreational athletes

The first aim of this study was to determine the age group at which marathon performance declines in top male and female runners and to compare that to the runners of average ability. Another aim of this of this study was to examine the age-related yearly decline in marathon performance between age group winners and the average marathon finisher. Data from the New York (NYC), Boston, and Chicago marathons from 2001–2016 were analyzed. Age, sex, and location were used in multiple linear regression models to determine the rate of decline in marathon times. Winners of each age group were assessed in 5-year increments from 16 through 74 years old (n = 47 per age group). The fastest times were between 25–34 years old, with overall champion males at 28.3 years old, and overall champion females at 30.8 years old (p = 0.004). At 35 years of age up to 74 years of age, female age group winners had a faster yearly decline in marathon finishing times compared to male age group winners, irrespective of marathon location [women = (min:sec) 2:33 per year, n = 336; men = 2:06 per year, n = 373, p < 0.01]. The median times between each age group only slowed beginning at 50 years old, thereafter the decline was similar between both men and women (women = 2:36, n = 140; men = 2:57, n = 150, p = 0.11). The median times were fastest at Boston and similar between Chicago and NYC. In conclusion, the rate of decline at 35 years old up to 74 years old is roughly linear (adjusted r² = 0.88, p < 0.001) with female age group winners demonstrating 27 s per year greater decline per year compared to male age group winners.

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

The 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.

Male and female Ethiopian and Kenyan runners are the fastest and the youngest in both half and full marathon

In major marathon races such as the 'World Marathon Majors', female and male East African runners particularly from Ethiopia and Kenya are the fastest. However, whether this trend appears for female and male Ethiopians and Kenyans at recreational level runners (i.e. races at national level) and in shorter road races (e.g. in half-marathon races) has not been studied yet. Thus, the aim of the present study was to examine differences in the performance and the age of female and male runners from East Africa (i.e. Ethiopians and Kenyans) between half- and full marathons. Data from 508,108 athletes (125,894 female and 328,430 male half-marathoners and 10,205 female and 43,489 male marathoners) originating from 126 countries and competing between 1999 and 2014 in all road-based half-marathons and marathons held in one country (Switzerland) were analysed using Chi square (χ(2)) tests, mixed-effects regression analyses and one-way analyses of variance. In half-marathons, 48 women (0.038 %) and 63 men (0.019 %) were from Ethiopia and 80 women (0.063 %) and 134 men (0.040 %) from Kenya. In marathons, three women (0.029 %) and 15 men (0.034 %) were from Ethiopia and two women (0.019 %) and 33 men (0.075 %) from Kenya. There was no statistically significant association between the nationality of East Africans and the format of a race. In both women and men, the fastest race times in half-marathons and marathons were achieved by East African runners (p < 0.001). Ethiopian and Kenyan runners were the youngest in both sexes and formats of race (p < 0.001). In summary, women and men from Ethiopia and Kenya, despite they accounted for <0.1 % in half-marathons and marathons, achieved the fastest race times and were the youngest in both half-marathons and marathons. These findings confirmed in the case of half-marathon the trend previously observed in marathon races for a better performance and a younger age in East African runners from Ethiopia and Kenya.

Half-marathoners are younger and slower than marathoners

Age and performance trends of elite and recreational marathoners are well investigated, but not for half-marathoners. We analysed age and performance trends in 508,108 age group runners (125,894 female and 328,430 male half-marathoners and 10,205 female and 43,489 male marathoners) competing between 1999 and 2014 in all flat half-marathons and marathons held in Switzerland using single linear regression analyses, mixed-effects regression analyses and analyses of variance. The number of women and men increased across years in both half-marathons and marathons. There were 12.3 times more female half-marathoners than female marathoners and 7.5 times more male half-marathoners than male marathoners. For both half-marathons and marathons, most of the female and male finishers were recorded in age group 40-44 years. In half-marathons, women (10.29 ± 3.03 km/h) were running 0.07 ± 0.06 km/h faster (p < 0.001) than men (10.22 ± 3.06 km/h). Also in marathon, women (14.77 ± 4.13 km/h) were running 0.28 ± 0.16 km/h faster (p < 0.001) than men (14.48 ± 4.07 km/h). In marathon, women (42.18 ± 10.63 years) were at the same age than men (42.06 ± 10.45 years) (p > 0.05). Also in half-marathon, women (41.40 ± 10.63 years) were at the same age than men (41.31 ± 10.30 years) (p > 0.05). However, women and men marathon runners were older than their counterpart half-marathon runners (p < 0.001). In summary, (1) more athletes competed in half-marathons than in marathons, (2) women were running faster than men, (3) half-marathoners were running slower than marathoners, and (4) half-marathoners were younger than marathoners.