Athletic Performance and Weight Changes during the “Marathon of Sands” in Athletes Well-trained in Endurance

Ad libitum ice slurry ingestion and half-marathon performance in a hot environment: A study comparing the effects of the amount and moment of ingestion between ice slurry and water at 37 °C

Ice slurry ingestion during prolonged exercises may improve performance in hot environments; however, the ideal amount and timing of ingestion are still uncertain. We determined whether ad libitum ice slurry ingestion influences physiological and perceptual variables and half-marathon performance while comparing the effects of the amount and moment of ingestion between ice slurry and water at 37 °C. Ten trained participants (28 ± 2 years; mean and SD) were required to run two half marathons while consuming either ice slurry (-1 °C; Ad-1) or water (37 °C; 37 CE) ad libitum. They then performed two other half marathons where, during one, they were required to ingest an amount of water equivalent to the amount consumed during the Ad-1 trial (Pro37), and in the other, to ingest ice slurry in the amount consumed during the 37 CE trial (Pro-1). During the half marathons, dry-bulb temperature and relative humidity were controlled at 33.1 ± 0.3 °C and 60 ± 3%, respectively. Ad-1 ingestion (349.6 ± 58.5 g) was 45% less than 37 CE ingestion (635.5 ± 135.8 g). Physical performance, heart rate, perceived exertion, body temperatures, and thermal perception were not influenced by the temperature or amount of beverage ingestion. However, a secondary analysis suggested that lower beverage ingestion was associated with improved performance (Ad-1 + Pro37 vs. 37 CE + Pro-1: -4.0 min, Cohen's d = 0.39), with a significant relationship between lower beverage ingestion and faster running time (b = 0.02, t = 4.01, p < 0.001). In conclusion, ice slurry ingestion does not affect performance or physiological or perceptual variables during a half marathon in a hot environment. Preliminary evidence suggests that lower beverage ingestion (ice slurry or warm water) is associated with improved performance compared to higher ingestion.

Amateur runners more influenced than elite runners by temperature and air pollution during the UK's Great North Run half marathon

The short- and long-term impacts of air pollution on human health are well documented and include cardiovascular, neurological, immune system and developmental damage. Additionally, the irritant qualities of air pollutants can cause respiratory and cardiovascular distress. This can be heightened during exercise and especially so for those with respiratory conditions such as asthma. Meteorological conditions have also been shown to adversely impact athletic performance; but research has mostly examined the impact of pollution and meteorology on marathon times or running under laboratory settings. This study focuses on the half marathon distance (13.1 miles/21.1 km) and utilises the Great North Run held in Newcastle-upon-Tyne, England, between 2006 and 2019. Local meteorological (temperature, relative humidity, heat index and wind speed) and air quality (ozone, nitrogen dioxide and PM_2.5) data is used in conjunction with finishing times of the quickest and slowest amateur participants, along with the elite field, to determine the extent to which each group is influenced in real-world conditions. Results show that increased temperatures, heat index and ozone concentrations are significantly detrimental to amateur half marathon performances. The elite field meanwhile is influenced by higher ozone concentrations. It is thought that the increased exposure time to the environmental conditions contributes to this greater decrease in performance for the slowest participants. For elite athletes that are performing closer to their maximal capacity (VO₂ max), the higher ozone concentrations likely results in respiratory irritation and decreased performance. Nitrogen dioxide and PM_2.5 pollution showed no significant relationship with finishing times. These results provide additional insight into the environmental effects on exercise, which is particularly important under the increasing effects climate change and regional air pollution. This study can be used to inform event organisation and start times for both mass participation and major elite events with the aim to reduce heat- and pollution-related incidents.

Impact of Repeated Acute Exposures to Low and Moderate Exercise-Induced Hypohydration on Physiological and Subjective Responses and Endurance Performance

This study aimed to examine whether repeated exposures to low (2%) and moderate (4%) exercise-induced hypohydration may reverse the potentially deleterious effect of hypohydration on endurance performance. Using a randomized crossover protocol, ten volunteers (23 years, V˙O_2max: 54 mL∙kg^-1∙min^-1) completed two 4-week training blocks interspersed by a 5-week washout period. During one block, participants replaced all fluid losses (EUH) while in the other they were fluid restricted (DEH). Participants completed three exercise sessions per week (walking/running, 55% V˙O_2max, 40 °C): (1) 1 h while fluid restricted or drinking ad libitum, (2) until 2 and (3) 4% of body mass has been lost or replaced. During the first and the fourth week of each training block, participants completed a 12 min time-trial immediately after 2% and 4% body mass loss has been reached. Exercise duration and distance completed (14.1 ± 2.7 vs. 6.9 ± 1.5 km) during the fixed-intensity exercise bouts were greater in the 4 compared to the 2% condition (p < 0.01) with no difference between DEH and EUH. During the first week, heart rate, rectal temperature and perceived exertion were higher (p < 0.05) with DEH than EUH, and training did not change these outcomes. Exercise-induced hypohydration of 2% and 4% body mass impaired time-trial performance in a practical manner both at the start and end of the training block. In conclusion, exercise-induced hypohydration of 2% and 4% body mass impairs 12 min walking/running time-trial, and repeated exposures to these hypohydration levels cannot reverse the impairment in performance.

Resistance Exercise in a Hot Environment Alters Serum Markers in Untrained Males

Purpose: We examined the effects of moderate resistance exercise (RE) on serum cortisol, testosterone, extracellular heat shock protein (HSP70), and interleukin (IL)-6 and IL-15 concentrations in untrained males in a hot environment.

Methods: Ten untrained young males (26 ± 3 years; 75.8 ± 6 kg; 177.4 ± 5.3 cm) performed two series of full body RE [3 sets of 8 to 10 repetitions, 30–60 s recovery between series with 70% of one maximal repetition (1-RM), with a rest period of 1 to 3 min between exercises] carried out in a random order in both heated (∼35°C) and thermoneutral (22°C) conditions. Serum concentrations of testosterone, cortisol, HSP70, and IL-6 and IL-15 were measured before, at the end, and 1 h after RE sessions. Participants in both groups consumed 4 ml of water/kg body mass every 15 min.

Results: There were time-related changes in testosterone, HSP70, and IL-6 (P < 0.001), and cortisol and IL-15 (P < 0.05). Levels of cortisol, HSP70, and IL-6 increased immediately for RE at 35°C, and testosterone and IL-15 levels were decreased. Changes in serum testosterone, HSP70, cortisol, and IL-15 and IL-6 levels were reversed after 1 h. A significant time × condition interaction was observed for IL-15 and HSP70 (P < 0.001), cortisol and IL-6 (P < 0.05), but not for testosterone (P > 0.05).

Conclusion: RE in a heated environment may not be appropriate for achieving muscle adaptations due to acute changes of hormonal and inflammatory markers.

Fluid Metabolism in Athletes Running Seven Marathons in Seven Consecutive Days

Purpose: Hypohydration and hyperhydration are significant disorders of fluid metabolism in endurance performance; however, little relevant data exist regarding multi-stage endurance activities. The aim of the present study was to examine the effect of running seven marathons in 7 consecutive days on selected anthropometric, hematological and biochemical characteristics with an emphasis on hydration status.

Methods: Participants included 6 women and 20 men (age 42.6 ± 6.2 years). Data was collected before day 1 (B₁) and after day 1 (A₁), 4 (A₄), and 7 (A₇).

Results: The average marathon race time was 4:44 h:min (ranging from 3:09 – 6:19 h:min). Plasma sodium, plasma potassium and urine sodium were maintained during the race. Body mass (p < 0.001, η² = 0.501), body fat (p < 0.001, η² = 0.572) and hematocrit (p < 0.001, η² = 0.358) decreased. Plasma osmolality (Posm) (p < 0.001, η² = 0.416), urine osmolality (Uosm) (p < 0.001, η² = 0.465), urine potassium (p < 0.001, η² = 0.507), urine specific gravity (Usg) (p < 0.001, η² = 0.540), plasma urea (PUN) (p < 0.001, η² = 0.586), urine urea (UUN) (p < 0.001, η² = 0.532) and transtubular potassium gradient (p < 0.001, η² = 0.560) increased at A₁, A₄, and A₇ vs. B₁. Posm correlated with PUN at A₁ (r = 0.59, p = 0.001) and A₄ (r = 0.58, p = 0.002). The reported post-race fluid intake was 0.5 ± 0.2 L/h and it correlated negatively with plasma [Na⁺] (r = −0.42, p = 0.007) at A₄ and (r = −0.50, p = 0.009) at A₇. Uosm was associated with UUN at A₁ (r = 0.80, p < 0.001), at A₄ (r = 0.81, p < 0.001) and at A₇ (r = 0.86, p < 0.001) and with Usg (r = 0.71, p < 0.001) at A₁, (r = 0.52, p = 0.006) at A₄ and (r = 0.46, p = 0.02) at A₇.

Conclusions: Despite the decrease in body mass, fluid and electrolyte balance was maintained with no decrease in plasma volume after running seven marathons in seven consecutive days. Current findings support the hypothesis that body mass changes do not reflect changes in the hydration status during prolonged exercise.

High-intensity interval training improves acute plasma volume responses to exercise that is age dependent

Plasma volume (PV) is affected by several factors including age, physical training and, acutely, by exercise intensity. The purpose of this study was to investigate the effects of 6 weeks of high-intensity interval training (HIT) on PV and blood pressure (BP) changes among sedentary individuals. Thirty subjects aged between 18 and 71 years [body mass index=30.1(1.2) kg/m2 ] completed a 6-weeks HIT program. Anthropometric and fitness variables were obtained at pre- and post- HIT. PV variations during warm-up and after supramaximal cycling test (SCT) were calculated using two methods based on Hematocrit (Ht) and Hemoglobin (Hb) measures. After both the warm-up and SCT, PV decreased significantly among participants at pre- and at post-HIT (P < 0.01). However, PV decreases were significantly greater at pre-HIT compared with post-HIT during warm-up and after SCT (P < 0.01, respectively). In addition, at pre-HIT, a positive relationship was found between age and both PV variations at warm-up and after SCT (r2  = 0.55 and r2  = 0.46; P < 0.01 respectively). However, no relationship was found during the post-HIT period. After SCT and after both visits, only body weight predicted 22% of PV variations. In the current study, a significant relationship was found between systolic and diastolic BP improvements and PV variations in post-HIT (r2  = 0.54 and r2 =0.56, P < 0.05, respectively). Our results suggest that HIT may improve PV values and reduce the effects of age on the decrease in PV. These interventions led to improvements in systolic and diastolic BP values among participants.

What predicts performance in ultra-triathlon races? - a comparison between Ironman distance triathlon and ultra-triathlon

Objective

This narrative review summarizes recent intentions to find potential predictor variables for ultra-triathlon race performance (ie, triathlon races longer than the Ironman distance covering 3.8 km swimming, 180 km cycling, and 42.195 km running). Results from studies on ultra-triathletes were compared to results on studies on Ironman triathletes.

Methods

A literature search was performed in PubMed using the terms “ultra”, “triathlon”, and “performance” for the aspects of “ultra-triathlon”, and “Ironman”, “triathlon”, and “performance” for the aspects of “Ironman triathlon”. All resulting papers were searched for related citations. Results for ultra-triathlons were compared to results for Ironman-distance triathlons to find potential differences.

Results

Athletes competing in Ironman and ultra-triathlon differed in anthropometric and training characteristics, where both Ironmen and ultra-triathletes profited from low body fat, but ultra-triathletes relied more on training volume, whereas speed during training was related to Ironman race time. The most important predictive variables for a fast race time in an ultra-triathlon from Double Iron (ie, 7.6 km swimming, 360 km cycling, and 84.4 km running) and longer were male sex, low body fat, age of 35–40 years, extensive previous experience, a fast time in cycling and running but not in swimming, and origins in Central Europe.

Conclusion

Any athlete intending to compete in an ultra-triathlon should be aware that low body fat and high training volumes are highly predictive for overall race time. Little is known about the physiological characteristics of these athletes and about female ultra-triathletes. Future studies need to investigate anthropometric and training characteristics of female ultra-triathletes and what motivates women to compete in these races. Future studies need to correlate physiological characteristics such as maximum oxygen uptake (VO_2max) with ultra-triathlon race performance in order to investigate whether these characteristics are also predictive for ultra-triathlon race performance.

33 Ironman triathlons in 33 days-a case study

This case report presents the performance of an athlete who completed for the first time in history the total distance of 33 Ironman triathlons within 33 consecutive days. The athlete finished the total distance of 7,458 km (i.e. 125 km swimming, 5,940 km cycling and 1,393 km running) within a total time of 410 h and a mean time of 12 h 27 min per Ironman distance. During the 33 days, the athlete became slower in swimming (r² = 0.27, p = 0.0019), transition time 1 (r² = 0.66, p < 0.001), and transition time 2 (r² = 0.48, p < 0.0001). However, in cycling (r² = 0.07, p = 0.13), running (r² = 0.04, p = 0.25) and overall race time (r² = 0.10, p = 0.069), the athlete was able to maintain his performance during the 33 days. The coefficients of variation (CV) for the split times in swimming, cycling, running and overall race times were very low (i.e. 2.7%, 3.2%, 4.7%, and 2.7%, respectively) whereas the CV for transition times 1 and 2 were considerably higher (i.e. 25.5% and 55.5%, respectively). During the 33 days, body mass decreased from 83.0 kg to 80.5 kg (r² = 0.55, p < 0.0001). Plasma [Na⁺] remained within the reference range, creatine kinase, blood glucose and liver enzymes were minimally elevated above the reference range after four of five stages where blood analyses were performed. This case report shows that this athlete finished 33 Ironman triathlons within 33 consecutive days with minor variations over time (i.e. even pacing) in both split times and overall race times. This performance was most probably due to the high experience of the athlete, his pacing strategy and the stable environmental conditions.

Running Interval Training and Estimated Plasma-Volume Variation

The effect of endurance interval training (IT) on hematocrit (Ht), hemoglobin (Hb), and estimated plasma-volume variation (PVV) in response to maximal exercise was studied in 15 male subjects (21.1 ± 1.1 y; control group n = 6, and training group, n = 9). The training group participated in interval training 3 times a week for 7 wk. A maximal graded test (GXT) was performed to determine maximal aerobic power (MAP) and maximal aerobic speed (MAS) both before and after the training program. To determine Ht, Hb concentration, and lactate concentrations, blood was collected at rest, at the end of GXT, and after 10 and 30 min of recovery. MAP and MAS increased significantly (P < .05) after training only in training group. Hematocrit determined at rest was significantly lower in the training group than in the control group after the training period (P < .05). IT induced a significant increase of estimated PVV at rest for training group (P < .05), whereas there were no changes for control group. Hence, significant relationships were observed after training between PVV determined at the end of the maximal test and MAS (r = .60, P < .05) and MAP (r = .76, P < .05) only for training group. In conclusion, 7 wk of IT led to a significant increase in plasma volume that possibly contributed to the observed increase of aerobic fitness (MAP and MAS).

Analysis of participation and performance in athletes by age group in ultramarathons of more than 200 km in length

Background

Participation and performance trends for athletes by age group have been investigated for marathoners and ultramarathoners competing in races up to 161 km, but not for longer distances of more than 200 km.

Methods

Participation and performance trends in athletes by age group in the Badwater (217 km) and Spartathlon (246 km) races were compared from 2000 to 2012.

Results

The number of female and male finishers increased in both races across years (P < 0.05). The age of the annual five fastest men decreased in Badwater from 42.4 ± 4.2 years to 39.8 ± 5.7 years (r² = 0.33, P = 0.04). For women, the age remained unchanged at 42.3 ± 3.8 years in Badwater (P > 0.05). In Spartathlon, the age of the annual five fastest finishers was unchanged at 39.7 ± 2.4 years for men and 44.6 ± 3.2 years for women (P > 0.05). In Badwater, running speed increased in men from 7.9 ± 0.7 km/hour to 8.7 ± 0.6 km/hour (r² = 0.51, P < 0.01) and in women from 5.4 ± 1.1 km/hour to 6.6 ± 0.5 km/hour (r² = 0.61, P < 0.01). In Spartathlon, running speed remained unchanged at 10.8 ± 0.7 km/hour in men and 8.7 ± 0.5 km/hour in women (P > 0.05). In Badwater, the number of men in age groups 30–34 years (r² = 0.37, P = 0.03) and 40–44 years (r² = 0.75, P < 0.01) increased. In Spartathlon, the number of men increased in the age group 40–44 years (r² = 0.33, P = 0.04). Men in age groups 30–34 (r² = 0.64, P < 0.01), 35–39 (r² = 0.33, P = 0.04), 40–44 (r² = 0.34, P = 0.04), and 55–59 years (r² = 0.40, P = 0.02) improved running speed in Badwater. In Spartathlon, no change in running speed was observed.

Conclusion

The fastest finishers in ultramarathons more than 200 km in distance were 40–45 years old and have to be classified as “master runners” by definition. In contrast to reports of marathoners and ultramarathoners competing in races of 161 km in distance, the increase in participation and the improvement in performance by age group were less pronounced in ultramarathoners competing in races of more than 200 km.

Ultramarathon runners: nature or nurture?

Ultramarathon running is increasingly popular. An ultramarathon is defined as a running event involving distances longer than the length of a traditional marathon of 42.195 km. In ultramarathon races, ~80% of the finishers are men. Ultramarathoners are typically ~45 y old and achieve their fastest running times between 30 and 49 y for men, and between 30 and 54 y for women. Most probably, ultrarunners start with a marathon before competing in an ultramarathon. In ultramarathoners, the number of previously completed marathons is significantly higher than the number of completed marathons in marathoners. However, recreational marathoners have a faster personal-best marathon time than ultramarathoners. Successful ultramarathoners have 7.6 ± 6.3 y of experience in ultrarunning. Ultramarathoners complete more running kilometers in training than marathoners do, but they run more slowly during training than marathoners. To summarize, ultramarathoners are master runners, have a broad experience in running, and prepare differently for an ultramarathon than marathoners do. However, it is not known what motivates male ultramarathoners and where ultramarathoners mainly originate. Future studies need to investigate the motivation of male ultramarathoners, where the best ultramarathoners originate, and whether they prepare by competing in marathons before entering ultramarathons.

European dominance in multistage ultramarathons: an analysis of finisher rate and performance trends from 1992 to 2010

BACKGROUND

Participation and performance trends regarding the nationality of ultraendurance athletes have been investigated in the triathlon, but not in running. The present study aimed to identify the countries in which multistage ultramarathons were held around the world and the nationalities of successful finishers.

METHODS

Finisher rates and performance trends of finishers in multistage ultramarathons held worldwide between 1992 and 2010 were investigated.

RESULTS

Between 1992 and 2010, the bulk of multistage ultramarathons were held in Germany and France, with more than 30 races organized in each country. Completion rates for men and women increased exponentially, with women representing on average 16.4% of the total field. Since 1992, 6480 athletes have competed in Morocco, 2538 in Germany, and 1842 in France. A total of 81.9% of athletes originated from Europe, and more specifically from France (22.9%), Great Britain (18.0%), and Germany (13.4%).

CONCLUSION

European ultramarathoners dominated the athletes who completed multistage ultramarathons worldwide, with specific dominance of French, British, and German athletes. Future studies should investigate social aspects, such as sport tourism, among European athletes to understand why European athletes are so interested in participating in multistage ultramarathons.

Body mass change and ultraendurance performance: a decrease in body mass is associated with an increased running speed in male 100-km ultramarathoners

We investigated, in 50 recreational male ultrarunners, the changes in body mass, selected hematological and urine parameters, and fluid intake during a 100-km ultramarathon. The athletes lost (mean and SD) 2.6 (1.8) % in body mass (p < 0.0001). Running speed was significantly and negatively related to the change in body mass (p < 0.05). Serum sodium concentration ([Na⁺]) and the concentration of aldosterone increased with increasing loss in body mass (p < 0.05). Urine-specific gravity increased (p < 0.0001). The change in body mass was significantly and negatively related to postrace serum [Na⁺] (p < 0.05). Fluid intake was significantly and positively related to both running speed (r = 0.33, p = 0.0182) and the change in body mass (r = 0.44, p = 0.0014) and significantly and negatively to both postrace serum [Na⁺] (r = -0.42, p = 0.0022) and the change in serum [Na⁺] (r = -0.38, p = 0.0072). This field study showed that recreational, male, 100-km ultramarathoners dehydrated as evidenced by the decrease in >2 % body mass and the increase in urine-specific gravity. Race performance, however, was not impaired because of the loss in body mass. In contrast, faster athletes lost more body mass compared with slower athletes while also drinking more. The concept that a loss of >2% in body mass leads to dehydration and consequently impairs endurance performance must be questioned for ultraendurance athletes competing in the field. For practical applications, a loss in body mass during a 100-km ultramarathon was associated with a faster running speed.

Comparison of anthropometric and training characteristics between recreational male marathoners and 24-hour ultramarathoners

Background

Of the anthropometry and training variables used to predict race performance in a 24-hour ultrarun, the personal best marathon time is the strongest predictor in recreational male 24-hour ultramarathoners. This finding raises the question of whether similarities exist between male recreational 24-hour ultramarathoners and male recreational marathoners.

Methods

The association between age, anthropometric variables (ie, body mass, body height, body mass index, percent body fat, skeletal muscle mass, limb circumference, and skinfold thickness at the pectoral, mid axillary, triceps, subscapular, abdominal, suprailiac, front thigh, and medial calf sites), previous experience and training characteristics (ie, volume, speed, and personal best time), and race time for 79 male recreational 24-hour ultramarathoners and 126 male recreational marathoners was investigated using bivariate and multivariate analysis.

Results

The 24-hour ultramarathoners were older (P < 0.05), had a lower circumference at both the upper arm (P < 0.05) and thigh (P < 0.01), and a lower skinfold thickness at the pectoral, axillary, and suprailiac sites (P < 0.05) compared with the marathoners. During training, the 24-hour ultramarathoners were running for more hours per week (P < 0.001) and completed more kilometers (P < 0.001), but were running slower (P < 0.01) compared with the marathoners. In the 24-hour ultramarathoners, neither anthropometric nor training variables were associated with kilometers completed in the race (P > 0.05). In the marathoners, percent body fat (P < 0.001) and running speed during training (P < 0.0001) were related to marathon race times.

Conclusion

In summary, differences in anthropometric and training predictor variables do exist between male recreational 24-hour ultramarathoners and male recreational marathoners for race performance.

The Skeleton Coast Diet Plan: body mass and body fat changes on an arduous expedition

OBJECTIVES

No one has ever walked the 500 Km Skeleton Coast of Namibia totally unsupported. Fourteen explorers overcame this by carrying, along with all their other equipment, hand-held pumps to desalinate sea water on a daily basis to produce sufficient potable water. This paper highlights the changes in body mass, waist circumference and body fat in the group on this unique 20 day expedition.

METHODS

Eight males (mean (SD)) 42.3 (9.7) years, height 1.741 (0.043) m, weight 78.7 (8.6) kg, body mass index (BMI) 24.8 (2.0) kg/m(2)) and six females (mean (SD) 40.0 (5.3) years, height 1.628 (0.043) m, weight 63.2 (5.5) kg, BMI 23.8 (1.8) kg/m(2)) undertook the expedition. Average pack weight at the start of the expedition for the men was 32.5 kg, and 26.5 kg for the women. On most days, the team walked for 8 - 10 hours on varying terrain then pumped water for a further 4 hours. Measurements taken included height, body mass, waist circumference and skin-fold thickness at four regions of the body, and were taken before, during and at the end of the expedition. The approximate daily calorific intake for each team member was 2400 - 3000 kcal.

RESULTS

Significant decreases in mean body mass (p < 0.001, d=0.50) and mean BMI (p < 0.001, d = 0.67) were observed after the 20 day trek compared to baseline values. Mean waist circumference decreased during the expedition (p < 0.001, d = 0.67). There were significant reductions in all measures of skinfold thicknesses and overall percentage body fat at Day 13 (p < 0.001, d = 1.19) and Day 21 (p < 0.001, d = 1.98) in comparison to baseline values

CONCLUSIONS

All participants lost significant amounts of both body mass and body fat, with body fat reducing by over 30%.

Similarities and differences in anthropometry and training between recreational male 100-km ultra-marathoners and marathoners

Several recent investigations showed that the best marathon time of an individual athlete is also a strong predictor variable for the race time in a 100-km ultra-marathon. We investigated similarities and differences in anthropometry and training characteristics between 166 100-km ultra-marathoners and 126 marathoners in recreational male athletes. The association of anthropometric variables and training characteristics with race time was assessed by using bi- and multi-variate analysis. Regarding anthropometry, the marathoners had a significantly lower calf circumference (P < 0.05) and a significantly thicker skinfold at pectoral (P < 0.01), axilla (P < 0.05), and suprailiacal sites (P < 0.05) compared to the ultra-marathoners. Considering training characteristics, the marathoners completed significantly fewer hours (P < 0.001) and significantly fewer kilometres (P < 0.001) during the week, but they were running significantly faster during training (P < 0.001). The multi-variate analysis showed that age (P < 0.0001), body mass (P = 0.011), and percent body fat (P = 0.019) were positively and weekly running kilometres (P < 0.0001) were negatively related to 100-km race times in the ultra-marathoners. In the marathoners, percent body fat (P = 0.002) was positively and speed in running training (P < 0.0001) was negatively associated with marathon race times. In conclusion, these data suggest that performance in both marathoners and 100-km ultra-marathoners is inversely related to body fat. Moreover, marathoners rely more on speed in running during training whereas ultra-marathoners rely on volume in running training.

A faster running speed is associated with a greater body weight loss in 100-km ultra-marathoners

In 219 recreational male runners, we investigated changes in body mass, total body water, haematocrit, plasma sodium concentration ([Na(+)]), and urine specific gravity as well as fluid intake during a 100-km ultra-marathon. The athletes lost 1.9 kg (s = 1.4) of body mass, equal to 2.5% (s = 1.8) of body mass (P < 0.001), 0.7 kg (s = 1.0) of predicted skeletal muscle mass (P < 0.001), 0.2 kg (s = 1.3) of predicted fat mass (P < 0.05), and 0.9 L (s = 1.6) of predicted total body water (P < 0.001). Haematocrit decreased (P < 0.001), urine specific gravity (P < 0.001), plasma volume (P < 0.05), and plasma [Na(+)] (P < 0.05) all increased. Change in body mass was related to running speed (r = -0.16, P < 0.05), change in plasma volume was associated with change in plasma [Na(+)] (r = -0.28, P < 0.0001), and change in body mass was related to both change in plasma [Na(+)] (r = -0.36) and change in plasma volume (r = 0.31) (P < 0.0001). The athletes consumed 0.65 L (s = 0.27) fluid per hour. Fluid intake was related to both running speed (r = 0.42, P < 0.0001) and change in body mass (r = 0.23, P = 0.0006), but not post-race plasma [Na(+)] or change in plasma [Na(+)] (P > 0.05). In conclusion, faster runners lost more body mass, runners lost more body mass when they drank less fluid, and faster runners drank more fluid than slower runners.

Impact of environmental parameters on marathon running performance

Purpose

The objectives of this study were to describe the distribution of all runners' performances in the largest marathons worldwide and to determine which environmental parameters have the maximal impact.

Methods

We analysed the results of six European (Paris, London, Berlin) and American (Boston, Chicago, New York) marathon races from 2001 to 2010 through 1,791,972 participants' performances (all finishers per year and race). Four environmental factors were gathered for each of the 60 races: temperature (°C), humidity (%), dew point (°C), and the atmospheric pressure at sea level (hPA); as well as the concentrations of four atmospheric pollutants: NO₂ – SO₂ – O₃ and PM₁₀ (μg.m⁻³).

Results

All performances per year and race are normally distributed with distribution parameters (mean and standard deviation) that differ according to environmental factors. Air temperature and performance are significantly correlated through a quadratic model. The optimal temperatures for maximal mean speed of all runners vary depending on the performance level. When temperature increases above these optima, running speed decreases and withdrawal rates increase. Ozone also impacts performance but its effect might be linked to temperature. The other environmental parameters do not have any significant impact.

Conclusions

The large amount of data analyzed and the model developed in this study highlight the major influence of air temperature above all other climatic parameter on human running capacity and adaptation to race conditions.

Drinking behaviors of elite male runners during marathon competition

OBJECTIVE

To describe the drinking behaviors of elite male marathon runners during major city marathons.

DESIGN

Retrospective analysis of drinking behaviors.

SETTING

Institutional.

PARTICIPANTS

Ten (9 winners and 1 second position) male marathon runners during 13 major city marathons.

MAIN OUTCOME MEASURES

Total drinking durations and fluid intake rates during major city marathons.

RESULTS

The ambient conditions during the 13 studied marathon races were 15.3°C ± 8.6°C and 59% ± 17% relative humidity; average marathon competition time was 02:06:31 ± 00:01:08 (hours:minutes:seconds). Total drinking duration during these races was 25.5 ± 15.0 seconds (range, 1.6-50.7 seconds) equating to an extrapolated fluid intake rate of 0.55 ± 0.34 L/h (range, 0.03-1.09 L/h). No significant correlations were found between total drink duration, fluid intake (rate and total), running speed, and ambient temperature. Estimated body mass (BM) loss based on calculated sweat rates and rates of fluid ingestion was 8.8% ± 2.1% (range, 6.6%-11.7%). Measurements of the winner in the 2009 Dubai marathon revealed a BM loss of 9.8%.

CONCLUSIONS

The most successful runners, during major city marathons, drink fluids ad libitum for less than approximately 60 seconds at an extrapolated fluid ingestion rate of 0.55 ± 0.34 L/h and comparable to the current American College of Sports Medicine's recommendations of 0.4-0.8 L/h. Nevertheless, these elite runners do not seem to maintain their BM within current recommended ranges of 2%-3%.

Personal best marathon time and longest training run, not anthropometry, predict performance in recreational 24-hour ultrarunners

In recent studies, a relationship between both low body fat and low thicknesses of selected skinfolds has been demonstrated for running performance of distances from 100 m to the marathon but not in ultramarathon. We investigated the association of anthropometric and training characteristics with race performance in 63 male recreational ultrarunners in a 24-hour run using bi and multivariate analysis. The athletes achieved an average distance of 146.1 (43.1) km. In the bivariate analysis, body mass (r = -0.25), the sum of 9 skinfolds (r = -0.32), the sum of upper body skinfolds (r = -0.34), body fat percentage (r = -0.32), weekly kilometers ran (r = 0.31), longest training session before the 24-hour run (r = 0.56), and personal best marathon time (r = -0.58) were related to race performance. Stepwise multiple regression showed that both the longest training session before the 24-hour run (p = 0.0013) and the personal best marathon time (p = 0.0015) had the best correlation with race performance. Performance in these 24-hour runners may be predicted (r2 = 0.46) by the following equation: Performance in a 24-hour run, km) = 234.7 + 0.481 (longest training session before the 24-hour run, km) - 0.594 (personal best marathon time, minutes). For practical applications, training variables such as volume and intensity were associated with performance but not anthropometric variables. To achieve maximum kilometers in a 24-hour run, recreational ultrarunners should have a personal best marathon time of ∼3 hours 20 minutes and complete a long training run of ∼60 km before the race, whereas anthropometric characteristics such as low body fat or low skinfold thicknesses showed no association with performance.

Physiological adaptation of a mature adult walking the Alps

Research on endurance locomotion has mainly focused on elite athletes rather than common middle-aged subjects. Our report describes the physiological and hematological adaptation of a healthy, active 62-year-old man who trekked alone along a 1300 km/3 month course of Alpine paths (Via Alpina). The following procedures were conducted: pre- and post-trekking and fortnightly field anthropometry (total and lean body mass), functional tests (isometric maximal voluntary force, spontaneous walking speed, relative metabolic cost, and peak oxygen consumption) and clinical chemistry/hematological measurements with laboratory instruments; daily self-administered effort measurements using portable devices along the route (walked distance, ascent, descent, time, metabolic consumption, and cost). Despite the tough trekking route, the subject completed the trek without any worsening of his performance, or any significant health or functional problems. In addition, his peak oxygen consumption increased by 13.2%. His successful adaptation may be attributed to his constant, repeated middle-intensity and extensive exercise and lengthy exposure to high altitude. The clinical chemistry/hematological measurements documented his physiological adaptation. In conclusion, we show how an active, middle-aged man can successfully face endurance trekking, not only without any harm to his health or functions but also with an increase in his capacity to support specific effort.