The main finding of this present investigation was the fact that selected anthropometric variables having a well-known effect on performance in runners-up to the marathon distance were not associated with total race time in these male 100-km ultrarunners, whereas the average weekly training volume in kilometers and the personal best time in a marathon showed an association with race performance.
We found a correlation between the personal best time in a marathon and total race time (Figure 2). An association between personal best times over shorter distances and performances in a longer race has been shown in 3 studies involving marathoners, ultrarunners, and triathletes. In a recent study of male ultrarunners in a 24-hour run, the personal best time in marathon running was associated with race performance, but anthropometry and training volume showed no relation (22) and, according to Gulbin and Gaffney, previous best performances in short-distance triathlons coupled with weekly cycling distances and the longest training ride could partially predict the overall performance in an Ironman race involving male and female triathletes (13). McKelvie et al. found that the final race time in a marathon was positively related to the best 10-km race time in the previous 12 months before the marathon (34). For those runners who had already performed a 100-km run, their personal best time in a 100-km run showed no association with actual race performance. Presumably, the number of finishers (n = 42) was too small compared with the athletes who had already finished a marathon (n = 63) (Table 2).
In addition to the personal best time in a marathon, the average weekly training volume in kilometers (Figure 1) was associated with total race time. According to the literature, training parameters seem to be of more importance than anthropometric measurements in the prediction of performance in runners (2,3,6,7,8,11,12,14,36). In marathon finishers, the longest mileage covered per training session is the best predictor for a successful completion of a marathon (42). In female marathon runners, the number of training sessions per week and the number of years training were the best predictors of competitive performance at the marathon distance (3), and Scrimgeour et al. found that runners training more than 100 km per week have significantly faster race times over 10-90 km than athletes covering less than 100 km (37). According to Billat al., top class marathon runners train for more total kilometers per week and at a higher velocity than runners at a lower level (6).
However, training volume seems to have clear limits. There exists an upper limit in training volume above which there are no more improvements (38). When training in runners is analyzed in detail, parameters such as previously completed marathons (15), workout days (15), total workouts (15), total kilometers (14), total workout days (14), mean kilometers per workout (14,15), total training minutes (15), maximal kilometers of running per week (15), mean kilometers per week (15), and mean kilometers per day (15) seem to have an effect on a marathon performance. Probably, gender had an influence when the effect of training volume on performance was studied. In one study, Hagan al. investigated female runners (15) and in another male runners (14).
As Bale et al. could demonstrate in 60 male runners, those elite runners with a higher training frequency, higher weekly training volume, and longer running experience had a better 10-km performance (2). According to Hewson and Hopkins, a correlation exists between seasonal weekly duration of moderate continuous running for runners specializing in longer distances (18). In our multiple linear regression analysis, only average kilometers per week were related to race performance, but speed in running during training and average hours of running per week were not related.
A large number of different anthropometric factors are described that have an influence on race performance in runners, dependent on the distance. In this present study, we investigated male ultrarunners beyond the marathon distance, where presumably other factors are of importance. However, in contrast to a previous study of ultrarunners where body mass was associated with race performance (20), in this present investigation, body mass showed no effect on performance. Hagan et al. found that in female marathon runners marathon performance time was positively correlated to BMI, but not to body mass (15). However, body fat was also positively correlated to marathon performance time. Bale et al. described in female marathon runners that elite runners had a lower percentage of fat (3), and Hetland et al. could demonstrate that regional and total body fat correlated inversely to the performance in an incremental treadmill test in long-distance runners (17). In contrast, we could not find an association of percent body fat with race performance in these 100-km runners. Probably, this was because of to gender. Although we investigated male ultrarunners, Hagan et al. (15) and Bale et al. (3) studied female runners.
Low amounts of body fat seem to be advantageous for ultrarunners. In the literature, there are several studies showing an effect of thin skin-fold thicknesses on running performance, especially up to 10,000 m. The amount of fat and the thickness of skin folds seem to be of importance for performance in runners. It has been shown that physical performance is negatively related to body fat and positively related to skeletal muscle mass (27). In runners, a high amount of adipose tissue leads to a higher body mass and an impairment of performance because more weight has to be moved, which does not contribute to power development. The study of Hetland et al. demonstrated that regional and total body fat was negatively correlated with performance in a treadmill test (17). In runners, decreased skin-fold thicknesses in the lower limb were measured after a longer training period; this might be particularly useful in predicting running performance (28). In the study of Legaz and Eston, 3 years of training reduced skin-fold thickness, and the change in performance was related to the change in skin-fold thickness of triceps, front thigh, and medial calf (28).
The lower skin-fold values found in runners might be because of the high performance (29). However, in nonrunners also, fat percentage is significantly associated with 12-minute running performance (33). A low skin-fold thickness seems to be associated with performance. Bale et al. found that total skin-fold, the type and frequency of training, and the number of years of running were the best predictors of running performance and success for the 10-km distance (2). In our male ultrarunners, anthropometric parameters, such as skin-fold thicknesses and the total sum of skin-fold thickness, did not correlate with total race time. Presumably, distances up to the marathon and 100-km runs are not comparable races.
In addition to skin folds, circumferences of extremities seem to have an influence on performance. In 2 studies of ultrarunners in a multistage ultraendurance run over 333 km (20) and over 1,200 km (21), the upper arm circumference was associated with race performance. In one study of Eritrean and Spanish runners, the Eritrean runners had a lower maximal calf circumference compared with the Spaniards (31). However, in our 100-km runners, neither upper arm circumference nor calf circumference had an effect on race performance (Table 1). Probably, a thin upper body is only advantageous in races longer than 100 km.
We have now the dilemma, that in these 100-km runners, both a high training volume (average weekly running kilometers) and a high intensity (personal best marathon time) are correlated to total race time. This means, that a fast race time over 100 km is obviously dependent on both a high mileage in running and a fast running speed in the marathon. However, a high training volume and a high intensity in running are both potentially associated with serious problems: An ultraendurance performance can suppress the hypopituitary-gonadal axis and lead to a decreased testosterone level (23). However, this decrease could be prevented by resistance exercise, thus leading to an increase in testosterone (41). A higher running speed could lead to more forefoot strike (16), thus potentially leading to more injuries of the lower limbs. Fortunately, anthropometry showed no relation to race performance. In case of a low body fat would have been correlated with total race time, anorexia and drive for thinness (10) could also become a problem in ultrarunning. To solve the mentioned dilemma, in future studies with ultrarunners over the 100-km distance, the training should be analyzed in detail and correlated with race performance to find out whether rather a high mileage at low intensity or a low mileage at rather high intensity would be better for a fast race time over 100 km. Furthermore, a training study with 2 groups of ultrarunners where 1 group is performing prerace resistance exercise in addition to the running training and the other group is not could clarify about a potential benefit of resistance exercise during high-volume running. A beneficial effect of resistance exercise on running speed (higher muscle mass) and testosterone (increase despite a higher training mileage) could be expected.
The authors had no conflict of interest and no financial support for the study. For their help in translation, we thank Matthias Knechtle, Lausanne, Switzerland, and Mary Miller from Stockton-on-Tees, Cleveland in England, crew member of an ultraendurance support crew. Special thanks go to Markus Gnädinger, MD, Steinach, Switzerland, and Hans Drexler, MD, PhD, Braunschweig, Germany, for their constructive criticism.
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