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Asian Journal of Sports Medicine logoLink to Asian Journal of Sports Medicine
. 2014 Jun;5(2):73–90.

Relationship of Anthropometric and Training Characteristics with Race Performance in Endurance and Ultra-Endurance Athletes

Beat Knechtle 1,2,*
PMCID: PMC4374609  PMID: 25834701

Abstract

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.

Keywords: Swimming, Cycling, Running, Skin-Fold, Body Fat, Ultra-Endurance

INTRODUCTION

In endurance and ultra-endurance athletes, a variety of different anthropometric characteristics (i.e. body mass, body fat, skin-fold thicknesses, body height, length and circumferences of limbs), training characteristics (i.e. speed during training units, duration of training units, training volume) and physiological variables (i.e. maximum oxygen uptake, anaerobic threshold, lactate threshold, ventilatory threshold) have been identified as important predictor variables for race performance.

In contrast to an endurance performance, an ultra-endurance performance is defined as an event exceeding six hours in duration [1]. These longer events rely particularly on long-term preparation, sufficient nutrition, accommodation of environmental stressors, and psychological toughness [1]. Ultra-endurance races such as ultra-swimming [2-5], ultra-cycling [6-8], ultra-running [9-15] and the combination of these disciplines in multi-sports disciplines such as duathlon [16] and triathlon [17] have become of increasing popularity in recent decades.

This narrative review intends to focus on the association between anthropometric and training characteristics with ultra-endurance race performance. A literature search was performed in PUBMED (http://www.ncbi.nlm.nih.gov/pubmed/) using the terms ‘anthropometry’, ‘training’, ‘performance’, ‘endurance’, ‘ultra’, and ‘athlete’ by the end of April 2013. All resulting papers were searched for related citations. The following anthropometric characteristics such as single skin-fold thickness [18-25] , the sum of skin-fold thicknesses [18-54], the circumferences of limbs [21-27,29,31-33,35,37-39,50-52,55-61], the length of limbs [29-33, 36,46,48,50,54,59,61-63], body mass [19-23,26,29,31-33,36-39,42,45,48,50-54,57,59-61,64-71], body height [22,23,25-27,29-33,36,46-51,56,59-63,67,71-74], body mass index [19-23,25-27, 29,31-33,36,37,39,44,46,50-57,59-62,65,66,71,75], and percent body fat [9,19-27,29,31-34,36-39,40,44-48,50-54,56,58-61,65,66,76-81] were considered. Based upon these results, the aspects of training and previous experience were also included. Results of bi- and multi-variate analyses were presented in details.

ANTHROPOMETRIC CHARACTERISTICS

Anthropometric characteristics have been reported to affect endurance and ultra-endurance performance. Several studies investigated the relationship between specific anthropometric characteristics such as single skin-fold thicknesses and the sum of skin-fold thicknesses [18-54], circumferences of limbs [21-27,29,31-33,35,37-39,50-52,55-61], length of limbs [29,31,33,36,46,48,50,54,59,61-63], body mass [19,20,22,23,26,29,31-33,36,37,39,42,45,46,48,50-54,57,59-61,64-71], body height [22,23,25-27,29,31,33,36,46,48,50,51,56,59-63,67,71-74], body mass index [19,20,22,23,29,25-27,31-33,36,37,39,44,46,50-52,54,56,57,59-62,65,66,71,75], and percent body fat [9,19,20,22,23.25-27,29,31-34,36-39,40,44-48,50-54,56,58,59-61,65,66,76-81] with endurance performance in bi-variate analyses.

Single Skin-Fold Thicknesses at Upper and Lower Body

In 2006, Arrese and Ostariz investigated a potential association between single skin-fold thicknesses and race performance in high-level runners competing in races between 100m and 1,500m [18]. The most important finding was that specific single skinfold thicknesses at the lower limb were positively associated with running time over several distances, and the authors suggested that the determination of single skin-fold thicknesses might be a useful predictor of athletic performance. High correlations were found between the front thigh and the medial calf skinfolds and 1,500m run times, and between the front thigh and the medial calf skinfold thickness and 10,000m run times. In women, the front thigh and medial calf skinfolds were highly correlated with 400m run time. In men, however, the pectoral, suprailiacal, abdominal, biceps, triceps, subscapular skinfolds and the sum of six skinfolds were not associated with performance score for any of the distances.

Subsequent studies based upon these findings investigating a potential association between single skin-fold thicknesses and the sum of skin-folds in athletes competing over different distances and in different disciplines lead to disparate findings. Table 1 summarizes the associations between single skin-fold thicknesses and performance for female and male endurance and ultra-endurance athletes. For the upper body skin-folds at pectoral, mid-axilla, triceps and subscapular site, similar findings were reported. The pectoral, mid-axillar, triceps and subscapular site skin-fold thicknesses were related to race time in female [19,20] and male half-marathoners [21], in male marathoners [22,23], and in male 100-km ultra-marathoners [24]. However, pectoral, mid-axilla, triceps and subscapular skin-folds were not associated with performance in male ultra-marathoners such as multi-stage ultra-marathoners [25,28], and 24-hour ultra-marathoners [29,30]. Furthermore, pectoral skin-fold was not associated with race times in triathletes such as male multi-stage ultra-endurance triathletes [31], male Triple Iron ultra-triathletes [32], and female Ironman triathletes [33]. Also for male ultra-endurance cyclists, no correlation between race performance and pectoral, mid-axilla, triceps and subscapular skin-fold thickness existed [34].

Table 1.

Results of the bi-variate associations between single skin-fold thicknesses and race performance for female and male endurance and ultra-endurance athletes. The athletes are listed with increasing race distance or race duration

Variable Pectoral Mid-axilla Triceps Sub-scapular Abdominal Supra-iliacal Thigh Calf
Female half-marathoners + + + + + + +
Male half-marathoners + + + + + + − −/+
Female marathoners + +
Male marathoners + + + + + + + +
Male long-distance inline skaters + +
Female Ironman triathletes − − − − −
Male Ironman triathletes + +
Male 100-km ultra-marathoners + + + + + + + +
Male multi-stage ultra-marathoners − − − − − − − −
Male 24-hour ultra-marathoners − − − − − − − −
Male ultra-endurance cyclists − − − − − − − −
Male Triple Iron ultra-triathletes − − − − −
Male multi-stage ultra-triathletes − − − − −
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For upper body skin-folds around the belly such as the abdominal and the suprailiacal skin-fold, the findings became different compared to the findings at pectoral, mid-axilla, triceps and subscapular site. The abdominal and suprailiacal skin-fold thicknesses were related to race time in runners such as female [19,20] and male [21] half-marathoners, male marathoners [22,23], male 100-km ultra-marathoners [24], and male Ironman triathletes [35], but not in male multi-stage ultra-marathoners [25-28,36], male 24-hour ultra-marathoners [29,30], male ultra-endurance cyclists [34], male multi- stage ultra-endurance triathletes [31], male Triple Iron ultra-triathletes [32], and female Ironman triathletes [33].

For the lower body skin-folds at front thigh and medial calf site, the findings were again differently compared to the reports for upper body skin-folds. The front thigh skin-fold thickness was related to race time in female [37] and male [22,23] marathoners, in male 100-km ultra-marathoners [24,38], in male long-distance inline skaters [39], but not in male runners such as half-marathoners[35], multi-stage ultra-marathoners[25,26,28, 36], 24-hour ultra-marathoners [29,30], in triathletes such as male multi-stage ultra-endurance triathletes [31], male Triple Iron ultra-triathletes [32], female Ironman triathletes [33], and in male ultra-endurance cyclists [34]. The calf skin-fold thickness was related to race time in runners such as female [19,20] and male [21] half-marathoners, female [37] and male [22,23,40] marathoners, male 100-km ultra-marathoners [24], male long-distance inline skaters [39], but not in runners such as male multi-stage ultra-marathoners [25-26,28,36], 24-hour ultra-marathoners [29,30], in triathletes such as male multi-stage ultra-endurance triathletes [31], male Triple Iron ultra-triathletes [32], female Ironman triathletes [33], and in male ultra-endurance cyclists [34].

The Association of Sums of Skin-Folds with Endurance Performance

Apart from single skin-fold thicknesses, also the sum of skin-folds has been reported as an important predictor variable [41-43]. In the different studies, the sums of skin-folds included not always the same single skin-folds or the same number of skin-folds but consisted mostly of a sum of seven to a maximum of ten skin-folds of both the upper and the lower body.

The sum of skin-folds was related to race performance in runners such as male 10-km runners[41], female [37] and male [22,23,42] marathoners, male ultra-runners such as 100-km ultra-marathoners [38,44], multi-stage ultra-marathoners [25,27], and 24-hour ultra-marathoners [45,46], male triathletes such as Ironman [47,48] and Triple Iron ultra-triathletes [38,49,50]. Additionally, the sum of skin-folds was related to performance in male endurance athletes such as long-distance inline skaters[39] and ultra-endurance mountain bikers [51]. The association of the sum of skin-folds with race performance was also investigated for split disciplines in multi-sports athletes such as triathletes. The sum of skin-folds was related to the split times in male Triple Iron ultra-triathletes [38,50], to the split times in swimming, cycling, running, and overall race time in male Ironman triathletes [52], and to the cycling speed in the cycling split in male Ironman triathletes [47]. In Triple Iron ultra-triathletes, the sum of skin-folds was neither associated with the speed in the swim nor in the bike split but showed a significant association with the speed in the run split [49] and overall race time [50]. The sum of skin-folds was not related to race time in male half-marathoners [21], in female Ironman triathletes [33], in male ultra-endurance mountain bikers [53], in male ultra-endurance cyclists [34], and in male open-water ultra-endurance swimmers [54].

Upper and Lower Body Skin-Folds and Their Association with Performance

Differences seemed to exist between single upper and lower body skin-fold thicknesses regarding their association with performance. Arrese and Ostariz showed high correlations between skin-fold thicknesses at the lower limb such as thigh and calf for men in 1,500m and 10,000m running and for women in 400m running [18]. In male Ironman triathletes, the sum of upper body skinfolds and the sum of all skinfolds were related to total race time [47]. The sum of upper body skinfolds and the sum of all skinfolds were also associated with speed in cycling during the race [47].

Taken together, single skin-fold thicknesses seemed to be related to performance in running races for both female and male athletes in rather short distances up to the 100km distance. For longer distances than the 100km ultra-marathon, only male athletes have been investigated and single skin-fold thicknesses showed no relationship to race performance. There seemed also to exist a difference between women and men for the relationship between single skin-fold thicknesses and race performance. Especially for Ironman triathletes, skin-fold thicknesses were related to performance in male, but not in female athletes.

Circumferences of Limbs

A further anthropometric characteristic related to endurance performance is the circumference of limbs of the upper arm [24,26,36,37,55-57], the thigh [24,37,48,52,55] and the calf [33,37,39,48]. Table 2 summarizes the associations between circumferences of limbs and performance for female and male endurance and ultra-endurance athletes.

Table 2.

Results of the bi-variate associations between limb circumferences and race performance for female and male endurance and ultra-endurance athletes. The athletes are listed with increasing race distance or race duration

Variable Upper arm Thigh Calf
800m runners +
1,500m runners +
5,000m runners +
10,000m runners +
Female marathoners + + +
Male marathoners − − −
Marathon split time in male Ironman triathletes + +
Ultra-marathon split time in male Triple Iron ultra-triathletes +
Male long-distance inline skaters + +
Male ultra-endurance mountain bikers + − −
Female 100-km ultra-marathoners + − +
Male 100-km ultra-marathoners + + −
Male Ironman triathletes + + +
Female Ironman triathletes − − −
Male multi-stage ultra-marathoners + − −
Male 24-hour ultra-marathoners − − −
Male multi-stage ultra-endurance triathletes − − −
Male Triple Iron ultra-triathletes − − −
Male ultra-endurance indoor swimmers − − −
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The circumference of upper arm was related to race time in runners such as 10-km runners [55], female marathoners [37], female [56] and male [24,57] 100-km ultra-marathoners, male multi-stage ultra-marathoners [26,36], in cyclists such as male ultra-endurance mountain bikers [51], in male long-distance inline skaters [39], and in triathletes such as male Ironman triathletes [48,58]. In triathletes, the upper arm circumference was also related to performance in the marathon split time in male Ironman triathletes [52] and to the run split time in Triple Iron ultra-triathletes [38,50]. The upper arm circumference was not related to race performance in swimmers such as male indoor ultra-endurance swimmers [59], in runners such as male marathoners [22,23], male 24-hour ultra-marathoners [29], and triathletes such as male multi-stage ultra-endurance triathletes [31], female Ironman triathletes [33,35], and male Triple Iron ultra-triathletes [32,50,60].

At the lower body, the associations of the circumferences of thigh and calf with race performance were investigated. The circumference of thigh was related to performance in runners such as 800m runners [55], 1,500m runners [55], 5,000m runners [55], female marathoners [37], and male 100-km ultra-marathoners [24]. In triathletes, the circumference of the thigh was related to overall race time in male Ironman triathletes [48] and marathon split time in male Ironman triathletes [52]. The thigh circumference was, however, not related to race performance in swimmers such as male indoor ultra-endurance swimmers [59], in cyclists such as male ultra-endurance mountain bikers [51], in runners such as female 100-km ultra-marathoners [56], male marathoners [21,22], male multi-stage ultra-marathoners [25-27,36], male 24-hour ultra-marathoners [29], and in multi sports athletes such as male multi-stage ultra-endurance triathletes [31], male Triple Iron ultra-triathletes [32,50,60], and female Ironman triathletes [33,61]. The circumference of calf was related to race time in runners such as female marathoners [37], female 100-km ultra-marathoners [33], male long-distance inline skaters [39], and male Ironman triathletes [48]. In a variety of disciplines and distances, no association between calf circumference and race performance was reported. These were swimmers such as male indoor ultra-endurance swimmers [59], runners such as male marathoners [22,23], ultra-marathoners such as male 100-km ultra-marathoners [24], male 24-hour ultra-marathoners [29], male multi-stage ultra-marathoners [25-27,36], cyclists such as male ultra-endurance mountain bikers [51], and triathletes such as female Ironman triathletes [33,61], male multi-stage ultra-endurance triathletes [31], and male Triple Iron ultra-triathletes [32,50,60].

In summary, the circumferences of limbs were mainly related to performances of rather short duration as has already been found for skin-fold thicknesses. For example, limb circumferences were related to Ironman performance, but not to Triple Iron ultra-triathlon performance for men. There seemed also to exist a sex difference. Especially for Ironman triathletes and marathoners, limb circumferences were related to performance in male, but not in female athletes as has already been found for single skin-fold thicknesses.

Length of Limbs

Also the length of limbs has been reported as an important predictor variable for endurance performance. Table 3 presents the associations between lengths of limbs and performance for female and male endurance and ultra-endurance athletes. The length of the arm was related to race time in male open-water ultra-endurance swimmers [62], but not in male indoor [59] and male open-water [54] ultra-endurance swimmers. Again, no association was found for triathletes such as male multi-stage ultra-endurance triathletes [31], in male Ironman triathletes [48], male Triple Iron ultra-triathletes [50], and female Ironman triathletes [33,61]. The length of the leg was associated with race time in female long-distance inline skaters [63], but not in swimmer such as male indoor [59] and male open-water [54] ultra-endurance swimmers, in runners such as in female 100-km ultra-marathoners [33], male 24-hour ultra-marathoners [29,46], male multi-stage ultra-marathoners [36], and in triathletes such as female [33,61] and male Ironman triathletes[48], male multi-stage ultra-endurance triathletes [31], and male Triple Iron ultra-triathletes [50].

Table 3.

Results of the bi-variate associations between limb lengths and race performance for female and male endurance and ultra-endurance athletes. The athletes are listed with increasing race distance or race duration

Variable Arm Leg
Female 100-km ultra-marathoners −
Male 100-km ultra-marathoners
Male multi-stage ultra-marathoners −
Male 24-hour ultra-marathoners −
Female long-distance inline skaters +
Male Ironman triathletes − −
Female Ironman triathletes −
Male multi-stage ultra-endurance triathletes − −
Male Triple Iron ultra-triathletes − −
Male indoor ultra-endurance swimmers − −
Male open-water ultra-endurance swimmers +/− −
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Body mass, Body Height and Body Mass Index

Body mass is an easy-to-determine variable for anthropometry. In addition to body mass, body height is also an easy-to-determine variable for anthropometry. With the determination of body mass and body height, the variable body mass index using the equation body mass (kg) divided by body height (m2) can be calculated. Table 4 shows the associations between body mass, body height and body mass index with performance for female and male endurance and ultra-endurance athletes.

Table 4.

The results of the bi-variate associations between limb circumferences and race performance for female and male endurance and ultra-endurance athletes (The athletes are listed with increasing race distance or race duration)

Variable Body mass Body height Body mass index
3,000m steeple chase runners +
Female half-marathoners + +
Female marathoners + +
Male marathoners +/− − −
Marathon split time in male Ironman triathletes + +
Female 100-km ultra-marathoners + + −
Male 100-km ultra-marathoners + +
Female 161-km ultra-marathoners +
Male 161-km ultra-marathoners +
Male multi-stage ultra-marathoners + − −
Male 24-hour ultra-marathoners +/− − −
Male Ironman triathletes + − +
Female Ironman triathletes − − −
Male long-distance road cyclists +/− +/− −
Male off-road cross country cyclists +/−
Male ultra-endurance mountain bikers − +
Female ultra-endurance indoor swimmers +
Male ultra-endurance indoor swimmers − +/− −
Male open-water ultra-endurance swimmers − + +/−
Female long-distance inline skaters +
Male long-distance inline skaters + +
Male multi-stage ultra-endurance triathletes − − −
Male Triple Iron ultra-triathletes − − −
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Body mass

Body mass was related to race performance in a variety of athletes such as 3,000m steeplechase runners [64], female half-marathoners [19,20], female marathoners [37,65], female [33] and male [57,66] 100-km ultra-marathoners, male 24-hour ultra-marathoners [45,46], male multi-stage ultra-marathoners [26,36], male long-distance inline skaters [39], road cyclists [67], and male off-road cross-country cyclists [68-70]. In triathletes, body mass was related to overall race time in male Ironman triathletes [48,52] and performance in the marathon split in male Ironman triathletes [52]. Body mass was not related to race performance in swimmers such as male indoor [59] and male open-water [54] ultra- endurance swimmers, cyclists such as male ultra-endurance mountain bikers [51,53] and male ultra-endurance road cyclists [71], runners such as male 24-hour ultra-marathoners [29], and triathletes such as female Ironman triathletes [33,61], male multi-stage ultra-endurance triathletes [31], and male Triple Iron ultra-triathletes [32,50,60]. Different findings were reported for body mass in male marathoners where Hagan et al [42] found an association but other studies [22,23] found no association with race times.

Body height

An association between body height and endurance performance has mainly been reported for swimmers [62,72-74]. Body height was related to performance in female and male pool swimmers [72-74] and in male open-water ultra-endurance swimmers [62]. Body height was also related to race performance in road cyclists [67], in female long-distance inline skaters [63], and in female 100-km ultra-marathoners [56]. However, a variety of disciplines showed no association between body height and race performance. These were swimmers such as male indoor ultra-endurance swimmers [59], cyclists such as male ultra-endurance mountain bikers [51] and male ultra-endurance cyclists [71], runners such as male marathoners [22,,23], male 24-hour ultra-marathoners [29,46], male multi-stage ultra-marathoners [25-27,36], triathletes such as male multi-stage ultra-endurance triathletes [31], male Ironman triathletes [48], male Triple Iron ultra-triathletes [50,60] and female Ironman triathletes [33,61].

Body mass index

Body mass index was related to performance in runners such as female half-marathoners [19,20], female marathoners [37,65], male 100-km ultra-marathoners [44,57,66], female and male 161-km ultra-marathoners [75], male long-distance inline skaters [39], male ultra-endurance mountain bikers [51], and male open-water ultra-endurance swimmers [62]. In triathletes, body mass index was related to overall race time [48,52] and to the split time in running [52] in male Ironman triathletes. However, body mass index was not related to race performance in different athletes such as male indoor [59] and male open-water [54] ultra-endurance swimmers, in runners such as male marathoners [22,23], female 100-km ultra-marathoners [56], male multi-stage ultra-marathoners [25-27,36], male 24-hour ultra-marathoners [29,46], and in triathletes such as female Ironman triathletes [33,61], male multi-stage ultra-endurance triathletes [31], male ultra-endurance cyclists [71], and male Triple Iron ultra-triathletes [32,50,60].

In summary, the variables body mass, body height and body mass index were mainly related to performances of rather short duration as has already been found for skin-fold thicknesses and limb circumferences. For single sports disciplines such as running, body mass and body mass index seemed an important predictor variable, but not for multi-sports disciplines such as triathlon. This might be due to the fact that body mass and body mass index were rather seldom related to performance in swimmers and cyclists, where swimming and cycling are split disciplines in a triathlon.

Body Fat

Body fat has been reported as an important predictor variable for a variety of disciplines and race distances [9,19,20,22,23.25-27,29,31-34,36-39,40,44-48,50-54,56,58,59-61,65,66,76-81]. When single skin-fold thicknesses are determined, body fat percentage can be calculated using anthropometric equations [82-85].

Body fat was related to race performance in runners such as female half-marathoners [19,20], in female [37,65] and male [22,23] marathoners, in ultra-marathoners such as male 100-km [38,44,57,66], 161-km [77], and 24-hour [45,46] ultra-marathoners, in swimmers such as female pool swimmers [78], in male long-distance inline skaters [39], in male ultra-endurance mountain bikers [51], in male ultra-endurance cyclists [35,71], and in triathletes such as male Ironman triathletes [35,40,47,48,52,58,79,80,81] and male Triple Iron ultra-triathletes [58]. Additionally, body fat was related to the run split time in Triple Iron ultra-triathletes [38,50] and to cycling speed in the cycling split in Ironman triathletes [47].

However, body fat was not related to race performance in ultra-endurance swimmers such as male indoor [59] and male open-water [54] ultra-endurance swimmers, in ultra-runners such as male multi-stage ultra-marathoners [25-27,36], male 24-hour ultra-marathoners [29], female 100-km [56] and female 161-km [9] ultra-marathoners, ultra-endurance cyclists such as male mountain bikers [53], in male ultra-endurance cyclists [34], and triathletes such as female Ironman triathletes [33,61,81], male multi-stage ultra-endurance triathletes [31] and in male Triple Iron ultra-triathletes [32,50,60].

Considering these findings, disparate results have been reported for the association between calf skin-fold thickness and performance in male half-marathoners (Table 1), the arm length in male open-water ultra-endurance swimmers (Table 3), body mass in male marathoners, in male long-distance road cyclists, in male off-road cross country cyclists, body height in male long-distance road cyclists and male ultra-endurance indoor swimmers and body mass index in male open-water ultra-endurance swimmers (Table 4). These disparate findings might be explained by different performance levels of the athletes and different numbers of included subjects.

TRAINING CHARACTERISTICS

Apart from selected anthropometric characteristics, training variables such as speed during training and volume have also been reported to be related to endurance performance [86-92].

Training Volume

Volume in training can be expressed as completed kilometers or completed hours. Training volume expressed in kilometers or hours per time period seemed to be an important predictor variable for different sports disciplines and race distances [65,93-96]. The weekly training hours were related to race time in triathletes such as female Ironman triathletes [80,81], male Triple Iron ultra-triathletes [58] and in male 100-km ultra-marathoners [38,44,57,97]. Weekly training hours were, however, not associated with race performance in runners such as male half-marathoners [21], male marathoners [22,23], female [56] and male [97] 100-km ultra-marathoners, male multi-stage ultra-marathoners [27,28], male 24-hour ultra-marathoners [29,30,45], and in triathletes such as female [61] and male [81] Ironman triathletes, and male Triple Iron ultra-triathletes [49,50].

The association of volume in cycling training with race performance was investigated for different cycling disciplines. In ultra-endurance cyclists, the completed cycling distance per training unit and the duration per training unit were related to race time [71,98]. The annually completed cycling kilometers were related to race time in male ultra-endurance mountain bikers [51,53]. The weekly completed running kilometers were related to race time in male half-marathoners [21], in female marathoners [65], in male 100-km ultra-marathoners [38-44,57,66,97], in male Triple Iron ultra-triathletes [58], to race performance in male 24-hour ultra-marathoners [45,46], but not in in male multi-stage ultra-marathoners [27] and female 100-km ultra-marathoners [56].

Additionally, the association between the single training units and race performance was investigated. The duration per training unit was related to race time in male [39,99] and female long-distance inline skaters [100] and in female marathoners [65]. The distance per training unit was associated with race time in male ultra-endurance mountain bikers [51] and in marathon runners [42,101]. The mean duration and the mean distance per training unit were related to race time in male ultra-endurance cyclists [71] and in female marathoners [65]. The number of weekly training units was related to race time in female long-distance inline skaters [63], in male half-marathoners [21], and in male [22] and female marathoners [65,93].

In triathletes, the training volume of the single disciplines was recorded and related to performance in the split disciplines. In male Ironman triathletes, the weekly swim kilometers [40,48] and the weekly swim hours [48] were related to the split time in swimming during the Ironman. Weekly swim hours and weekly swim kilometers were, however, not related to swim split time in female Ironman triathletes [61]. In the cycling split, both the weekly cycling kilometers and weekly cycling hours were related to Ironman race time in female [61] and male [48] Ironman triathletes. The weekly cycling kilometers were related to overall race time in male Triple Iron ultra-triathletes [58].

Speed during Training

Training pace seemed to be an important predictor variable for different sports disciplines [65,102,103]. Peak running velocity was highly predictive of distance running performance in highly-trained endurance runners [104,105]. Peak treadmill running velocity has been shown a good predictor of running performance for both marathoners and ultra-marathoners [89] and short-distance triathletes [102,106]. Swimming speed was related to race time in in male and female open-water ultra-endurance swimmers [62] and swimming split time in male Ironman triathletes [48]. Cycling speed during training was related to overall race time in male [58] but not in female [61] Ironman triathletes. Speed in cycling was related to overall race time in male ultra-endurance road cyclists [98] and male ultra-endurance mountain bikers [51,53], and to the bike split time in an Ironman triathlon [35,40]. Running speed during training was related to race time in female [19,20] and male [21,103] half-marathoners, in female [37] and male [22,23,40] marathoners, in male 100-km ultra-marathoners [44,57,66], and in male multi-stage ultra-marathoners [28]. In triathletes, running speed during training was related to marathon split time [48] and overall race time [107] in male Ironman triathletes.

However, running speed during training was not related to race performance in male 24-hour runners [45,46], and in female Ironman triathletes [61]. In male long-distance inline skaters, skating speed during training was related to race time [39]. No association with training variables was reported for male Triple Iron ultra-triathletes [50] and male multi-stage ultra-marathoners [27].

Interaction between Anthropometric and Training Characteristics

The question arises now whether anthropometric or training characteristics were more important to predict endurance performance. Several studies investigated the interaction between anthropometric and training characteristics using multi-variate correlation analyses [21,22,93,100,108,109] since anthropometry and training were bi-variately related [21,22,24,30,45,110].

An association between physical training and body fat has been reported. It is important to know that training leads to a reduction of both skin-fold thicknesses [111] and body fat percentage [112]. The loss of body appears to be specific to the muscular groups used during training [111]. The thickness of skin-folds seems to decrease with increasing running distance. Legaz Arrese et al. [113] found lower skin-fold thicknesses in marathoners compared to runners competing in shorter running distances. Athletes with lower body fat are lighter and therefore able to run faster. However, the correlation between skin-fold thickness and body fat with running speed does not prove cause and effect. Athletes with low body fat might also have reduced their body fat by diet [114,115]. The prevalence of eating disorders is higher in athletes than in controls, higher in women than in men, and more common among those competing in leanness-dependent and weight-dependent sports than in other sports [116,117].

For runners, it has been shown that lower body fat [20,22,24,45,110] and lower skin-fold thicknesses [19,20,24,45,110] were associated with a faster running speed in training. Additionally, training volume expressed in weekly running kilometers was associated with thickness of skinfolds [24,45,110] and percent body fat [24,45,110]. The circumference of upper arm was related to weekly running kilometers [110] and running speed during training [110] in 100-km ultra-marathoners. In female half-marathoners, running speed during training was related to mid-axilla, subscapular, abdominal, and suprailiacal skin-fold thickness, the sum of eight skin-fold thicknesses and percent body fat [19].

Most probably athletes such as distance runners profit from thinness to achieve fast race times. A recent study investigated the association between anthropometric and training characteristics with race performance for half-marathoners, marathoners and ultra-marathoners [100]. Body fat was related to half-marathon, marathon, and ultra-marathon race times. In half-marathoners and marathoners, speed during training was related to race times. In ultra-marathoners, however, weekly running kilometers were related to running times. This study showed that body fat and training characteristics were associated with running times in half-marathoners, marathoners, and ultra-marathoners.

The distance of the intended race seemed to influence the training behavior in endurance and ultra-endurance athletes [58,66]. Marathoners seemed rather to rely on a high running speed during training whereas ultra-marathoners seemed to rely on a high running volume during training [66]. Marathoners completed significantly fewer hours and significantly fewer kilometers during the training week, but they were running significantly faster during training than ultra-marathoners [66]. Similar findings were reported for the comparison for Ironman triathletes competing for 3.8 km swimming, 180 km cycling and 42.195 km running and Triple Iron ultra-triathletes competing for 11.4 km swimming, 540 km cycling and 126.6 km running [58]. Triple Iron ultra-triathletes relied more on training volume in cycling and running, whereas speed in cycling training was related to race time in Ironman triathletes [58].

A variety of studies showed that both anthropometric and training characteristics predicted performance when anthropometric and training variables were multi-variately associated with performance [21,22,80,109,114]. In male marathoners, both a low body fat and a fast running speed during training were the best predictor variables [22]. Speed during training was of higher relevance since percent body fat explained only 4% of the variance [22]. Low body fat alone might not be sufficient to achieve a fast marathon time [22]. In male half-marathoners, body mass index and running speed during training were the best predictors [21]. In male ultra-endurance cyclists, anthropometry showed a moderate association with speed in the race, whereas training volume showed no association [109]. In female short-distance triathletes, training parameters were more important than anthropometric measures in the prediction of performance [114]. In female and male Ironman triathletes, however, percent body fat was not related to training volume [80].

THE ASPECT OF RACE DISTANCE AND SPECIFIC PRE-RACE PREPARATION

The different preparations for the different race distances seems to have an effect on both the training and the anthropometry of the athletes [38,40]. Athletes competing in and preparing for shorter distances seemed thinner than athletes competing in and preparing for ultra-distances [23,38,66,118]. Athletes seemed also to adapt their training regarding the intended race distance. Training distances appeared to be more important than training paces in the preparation for an ultra-endurance triathlon such as an Ironman triathlon [119]. The comparison of male half-marathoners and marathoners showed that half-marathoners were heavier, had longer legs, thicker upper arms, a thicker thigh, a higher sum of skinfold thicknesses, a higher body fat percentage and a higher skeletal muscle mass than marathoners [118]. Half-marathoners had fewer years of experience, completed fewer weekly training kilometers, and fewer weekly running hours than the marathoners. Predictor variables for race time were different between half-marathoners and marathoners. Body mass index, percent body fat and speed in running during training were related to race time in half-marathoners. For marathoners, percent body fat and speed in running during training were associated with race time [118]. When anthropometric characteristics were compared between marathoners and 100-km ultra-marathoners, marathoners had a significantly lower calf circumference and a significantly thicker skinfold at pectoral, axilla, and suprailiacal sites compared to ultra-marathoners [66]. When marathoners and 24-hour ultra-marathoners were compared, the 24-hour ultra-marathoners had a lower limb circumference at upper arm and thigh, and a lower skinfold thickness at the pectoral, axilla, and suprailiacal site compared to the marathoners [23]. During training, the 24-hour ultra-marathoners completed more weekly running hours and achieved more running kilometers, however, they were running slower compared with the marathoners [23].

Anthropometric and training characteristics were differently related to performance regarding the length of a race. In 24-hour ultra-marathoners, neither anthropometric nor training variables were associated with achieved race kilometers. In marathoners, however, percent body fat and running speed during training were related to marathon race times [23]. However, the comparison of 100-km ultra-marathoners and Triple Iron ultra-triathletes showed that ultra-triathletes had higher body mass, shorter legs, a higher circumference of upper arm and thigh, a lower sum of skin-folds, and lower percent body fat compared to runners [38]. Weekly training volume was higher for triathletes, and weekly hours in running and weekly kilometers in running were higher for runners. Similar findings were reported for the comparison between Ironman triathletes and Triple Iron ultra-triathletes [58]. The Triple Iron ultra-triathletes were smaller, had shorter limbs, a higher body mass index, and larger limb circumferences than the Ironman triathletes. The Triple Iron ultra-triathletes trained for more hours and covered more kilometers, but speed in running during training was slower compared with the Ironman triathletes [58]. When ultra-endurance cyclists preparing for ‘Paris-Brest-Paris’ where compared with ultra-endurance cyclists preparing for the ‘Race Across America’, the qualifiers in the longer race had greater intensity in training while the qualifiers in the shorter race relied more on training volume [120]. The comparison of finishers and non-finishers in an ultra-cycling race such as the ‘Swiss Cycling Marathon’ covering 720 km showed that the finishers had a lower body mass, a lower body mass index, a lower circumference of upper arm and thigh, a lower percentage of body fat, completed more weekly training units, covered more kilometers in the longest training ride, rode at a faster speed during training, rode more kilometers per week and for more hours, and had more previous finishes in the ‘Swiss Cycling Marathon’ compared to the non-finishers [98].

DIFFERENCES IN ANTHROPOMETRIC AND TRAINING CHARACTERISTICS BETWEEN WOMEN AND MEN

Several studies compared anthropometric and training characteristics between female and male endurance athletes [77,121,122]. Regarding anthropometry, women are smaller than men, have more body fat and a lower skeletal muscle mass [77,123]. These differences lead to differences in the predictor variables [62,124,125]. In a 12-min run, women and men achieved different performances [123]. The average sex difference in 12-min run performance is primarily due to differences in percent fat and cardiorespiratory capacity [123].

When female and male half-marathoners were compared, two skin-fold thicknesses (i.e. abdominal and calf) were significantly and positively correlated with race time in men whereas in women, five (i.e. pectoral, mid-axilla, subscapular, abdominal, and suprailiacal) showed positive and significant relations with total race time [124]. In men, mean weekly running distance, minimum distance run per week, maximum distance run per week, mean weekly hours of running, number of running training sessions per week, and mean speed of the training sessions were significantly and negatively related to total race time, but not in women [124]. Interaction analyses suggested that race time was more strongly associated with anthropometry in women than men. Race time for women was independently associated with the sum of eight skin-folds; but for men, only the mean speed during training sessions was independently associated. Skin-fold thicknesses and training variables in these groups were differently related to race time according to their sex. The comparison of female and male open-water ultra-endurance swimmers showed that body height, body mass index, length of arm, and swim speed during training were related to race time in men [62]. For women, swimming speed during training was associated with race time [62]. In the multivariate analysis for the men, body mass index and swimming speed during training were related to race time [62]. When female and male Ironman triathletes were compared, low skinfold thicknesses of the upper body were related to race performance in male, but not in female Ironman triathletes [47]. Percent body fat showed a relationship to total race time in male triathletes, and training volume showed an association with total race time in female triathletes [80,81]. The comparison of female and male 161-km ultra-marathoners showed that a significant positive correlation between percent body fat and finish time for men but not for women, and percent body fat values were lower for finishers than non-finishers for men and women [77]. In pool swimmers, measurements of body composition and somatotype were predictors of swimming performance in women but not in men [121].

THE ASPECT OF PREVIOUS EXPERIENCE

Previous experience seems to be a very important predictor variable for endurance performance [126-128]. Several studies corrected the association of anthropometric and training characteristics with performance with the aspect of pre-race experience in multi-variate regression analyses [45,48,50,51,61,97,107].

For ultra-distances, personal best times in shorter races were important predictor variables [45,107,126,127,129]. For ultra-runners, personal best marathon time seemed a strong predictor variable. Personal best marathon time was related to performance in male 24-hour ultra-marathoners [29,45,46], in male [44,57,97] and female [56] 100-km ultra-marathoners, in male [107] and female [33] Ironman triathletes, but not in in male multi-stage ultra-marathoners [27]. For Ironman triathletes, both the personal best marathon time and the personal best time in an Olympic distance triathlon were strong predictor variables in both women and men [48,61,107,127]. Personal best time in an Olympic distance triathlon was related to Ironman race time in male [48,107] and female [33,61] Ironman triathletes. These variables were able to predict Ironman race time. Speed in running training, the personal best marathon time and the personal best time in an Olympic distance triathlon explained 64% of the variance in an Ironman triathlon for male triathletes [107]. For female Ironman triathletes, personal best marathon time and personal best time in an Olympic distance triathlon explained 53% of the variance of Ironman race time [61]. In a further study, the previous best performances in an Olympic distance triathlon coupled with the weekly cycling distances and the longest training ride could partially predict overall performance [127].

Also for longer triathlon distances than the Ironman triathlon, the personal best time in a shorter race was an important predictor variable for an ultra-triathlon. Personal best time in an Ironman triathlon was related to race time in a Triple Iron ultra-triathlon [50]. In male Deca Iron ultra-triathletes covering 38 km swimming, 1,800 km cycling and 422 km running, race time was related to both the number of finished Triple Iron ultra-triathlons (i.e. 11.4 km swimming, 540 km cycling, and 126.6 km running) and the personal best time in a Triple Iron ultra-triathlon [129]. In male Triple Iron ultra-triathletes, however, personal best Ironman time was not related to race time but personal best time in Triple Iron ultra-triathlon [50].

The previous personal best time in the same race distance was an important predictor variable for race time. This personal best time was related to race time in male long-distance inline skaters [99], in male ultra-endurance mountain bikers [51], male 100-km ultra-marathoners [57], male Triple Iron ultra-triathletes [50], female and male Ironman triathletes [33,81], and male 24-hour ultra-marathoners [29]. In 24-hour ultra-marathoners, the personal best marathon time, the personal best time in a 100-km ultra-marathon and the best performance in a 24-hour ultra-marathon were the best predictor variables [45]. In another study, the personal best marathon time and the longest training run prior to the race were the best predictors [46].

For some race distances, the number of previously completed races was an important predictor variable. For female marathoners, the number of previous completed marathons was related to marathon race time [65]. The number of completed 100-km ultra-marathons was associated with race time in male 100-km ultra-marathoners [57]. In male 24-hour ultra-marathoners, the number of finished marathons and the number of finished 24-hour ultra-marathons was not related to race performance [29,45]. In female Ironman triathletes, the number of completed Olympic distance triathlons and the number of complete Ironman triathlons were not associated with race time [33]. In male Triple Iron ultra-triathletes, the number of previously completed Ironman and Triple Iron ultra-triathlons was not associated with race time [50].

Anthropometric and training characteristics seemed to be of low importance regarding ultra-endurance performance when corrected with aspects of previous experience[33,48,51]. When anthropometric characteristics, training variables and previous experience were multi-variately associated with Ironman race time in male athletes, personal best marathon time and personal best time in an Olympic distance triathlon were the best predictor variables [48]. In long-distance mountain bikers competing in the ‘Swiss Bike Masters’, personal best time in the ‘Swiss Bike Masters’, annual total cycling kilometers and annual road cycling kilometers were the best predictor variables [51].

In the aspect of previous experience as an athlete, also the number of years training and competing was correlated to race performance. The number of years training was related to marathon race time in female marathoners [93] and to 10 km race time in male runners [41]. Years as active athlete were not related to performance in male multi-stage ultra-marathoners [28], in male open-water ultra-endurance swimmers [54], in male 24-hour ultra-marathoners [45,46], in male 100-km ultra-marathoners[97], in male ultra-endurance mountain bikers [51], and in male ultra-endurance cyclists [71].

PHYSIOLOGICAL CHARACTERISTICS

Apart from anthropometric characteristics, training variables and previous experience, also physiological characteristics predict endurance performance [130,131]. Several laboratory and field studies showed that physiological characteristics such as maximum oxygen uptake (VO2max) [42,96,108,128,132-141], anaerobic threshold [64], lactate threshold [129,140,141], lactate threshold velocity [142,143], VO2 at lactate threshold [143], ventilatory threshold [136], and velocity at VO2max (vVO2max) [144] were related to performance. In off-road cross-country cyclists, VO2max was a strong predictor variable for performance [69,70]. Among well-trained female and male runners heterogeneous in VO2max and running performance, VO2max was the best predictor of running performance [144]. Final treadmill velocity in a VO2max test is the single best predictor of 5000-m performance in untrained and trained states [143]. In top-class marathoners, marathon performance time was inversely correlated with VO2max and predicted 59% of the variance of marathon performance time.

Conclusions

To summarize, although several studies showed strong bi-variate correlations between single anthropometric and training characteristics, previous experience such as personal best time in a shorter race seems the better predictor for endurance and ultra-endurance athletes than a thin body and a high speed during training. Ultra-endurance athletes seemed to prepare differently for their races compared to endurance athletes. The different length of the races seemed also to have an influence on pre-race body composition. 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.

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