Influence of body mass and height on the energy cost of running in highly trained middle- and long-distance runners

Estimating Metabolic Energy Expenditure During Level Running in Healthy, Military-Age Women and Men

ABSTRACT

Looney, DP, Hoogkamer, W, Kram, R, Arellano, CJ, and Spiering, BA. Estimating metabolic energy expenditure during level running in healthy, military-age women and men. J Strength Cond Res 37(12): 2496-2503, 2023-Quantifying the rate of metabolic energy expenditure (Ṁ) of varied aerobic exercise modalities is important for optimizing fueling and performance and maintaining safety in military personnel operating in extreme conditions. However, although equations exist for estimating oxygen uptake during running, surprisingly, there are no general equations that estimate Ṁ. Our purpose was to generate a general equation for estimating Ṁ during level running in healthy, military-age (18-44 years) women and men. We compiled indirect calorimetry data collected during treadmill running from 3 types of sources: original individual subject data (n = 45), published individual subject data (30 studies; n = 421), and published group mean data (20 studies, n = 619). Linear and quadratic equations were fit on the aggregated data set using a mixed-effects modeling approach. A chi-squared (χ2) difference test was conducted to determine whether the more complex quadratic equation was justified (p < 0.05). Our primary indicator of model goodness-of-fit was the root-mean-square deviation (RMSD). We also examined whether individual characteristics (age, height, body mass, and maximal oxygen uptake [V̇O2max]) could minimize prediction errors. The compiled data set exhibited considerable variability in Ṁ (14.54 ± 3.52 W·kg-1), respiratory exchange ratios (0.89 ± 0.06), and running speeds (3.50 ± 0.86 m·s-1). The quadratic regression equation had reduced residual sum of squares compared with the linear fit (χ2, 3,484; p < 0.001), with higher combined accuracy and precision (RMSD, 1.31 vs. 1.33 W·kg-1). Age (p = 0.034), height (p = 0.026), and body mass (p = 0.019) were associated with the magnitude of under and overestimation, which was not the case for V̇O2max (p = 0.898). The newly derived running energy expenditure estimation (RE3) model accurately predicts level running Ṁ at speeds from 1.78 to 5.70 m·s-1 in healthy, military-age women and men. Users can rely on the following equations for improved predictions of running Ṁ as a function of running speed (S, m·s-1) in either watts (W·kg-1 = 4.43 + 1.51·S + 0.37·S2) or kilocalories per minute (kcal·kg-1·min-1 = 308.8 + 105.2·S + 25.58·S2).

Anthropometric profiles and body composition of male runners at different distances

Anthropometric parameters are crucial prerequisite to achieve success in professional running sports. However, it is not clear how these parameters are relevant for athletes performing on a less demanding sport level as academic competitions. To help coaches and selectors working on this level, we have explored anthropometric variables and body composition in 68 academic athletes: 26 sprinters, 22 middle distance runners, and 20 long distance runners. Sprinters have a more massive body shape, shorter lower legs in relation to the length of the thigh, broader shoulders and narrower hips, greater musculature and cellular mass. A slender figure, a longer shin, and the greatest subcutaneous fat and extracellular mass characterize long-distance runners. Middle-distance runners are the slimmest, and have a narrow trunk and little subcutaneous fat. Sprinters and long-distance runners are mesomorphic, while middle-distance runners present more mixed mesomorph-ectomorph type. The principal component analysis highlighted the importance of the overall size of the body, limbs musculature and the length of the lower limb together with its segments, and also body fatness. This approach emphasized the morphological distinctiveness of runners at particular distances and allows the use of somatic features as predictors of running performance.

Individual physiological responses to changes in shoe bending stiffness: a cluster analysis study on 96 runners

BACKGROUND

Shoe longitudinal bending stiffness is known to influence running economy (RE). Recent studies showed divergent results ranging from 3% deterioration to 3% improvement in RE when bending stiffness increases. The variability of these results highlights inter-individual differences. Thus, our purpose was to study the runner-specific metabolic responses to changes in shoe bending stiffness.

METHODS

After assessing their maximal oxygen consumption ([Formula: see text] max) and aerobic speed (MAS) during a first visit, 96 heterogeneous runners performed two treadmill 5 min runs at 75% [Formula: see text] max with two different prototypes of shoes on a second day. Prototypes differed only by their forefoot bending stiffness (17 N/mm vs. 10.4 N/mm). RE and stride kinematics were recorded during each trial. A clustering analysis was computed by comparing the measured RE and the technical measurement error of our gas exchange analyzer to identify functional groups of runners, i.e., responding similarly to footwear interventions. ANOVAs were then computed on biomechanical and morphological variables to compare the functional groups.

RESULTS

Considering the whole sample (n = 96), there was no significant difference in RE between the two conditions. Cluster 1 (n = 29) improves RE in the stiffest condition (2.7 ± 2.1%). Cluster 2 (n = 26) impairs RE in the stiffest condition (2.7 ± 1.3%). Cluster 3 (n = 41) demonstrated no change in RE (0.28 ± 0.65%). Cluster 1 demonstrated 1.7 km·h^-1 greater MAS compared to cluster 2 (p = 0.014).

CONCLUSION

The present study highlights that the effect of shoe bending stiffness on RE is runner-specific. High-level runners took advantage of increased bending stiffness, whereas medium-level runners did not. Finally, this study emphasizes the importance of individual response examination to understand the effect of footwear on runner's performance.

Sex Differences in Racing History of Recreational 10 km to Ultra Runners (Part B)-Results from the NURMI Study (Step 2)

Sex differences in anatomy and physiology are the primary underlying factor for distinctions in running performance. Overall participation in recreational running events has been dominated by males, although increasing female participation has been reported in recent years. The NURMI study participants filled in a survey following the cross-sectional study design with questions on sociodemographic data, running and racing motivations, training behaviors, and racing history and experience. Data analysis included 141 female and 104 male participants aged 39 (IQR 17) with a healthy median BMI (21.7 kg/m²; IQR 3.5). Statistical analyses revealed sex differences with the males performing faster at half-marathon (p < 0.001) and marathon (p < 0.001) events but no difference at ultra-marathons (p = 0.760). Mediation analyses revealed no significant sex differences in the performance of half-marathon and marathon when considering training behaviors (p > 0.05), racing history (p > 0.05), or racing experience (p > 0.05). Differences in recreational performance may be more closely related to social constraints and expectations of females rather than the physiological advantages of the male athlete. Health professionals who guide and support recreational runners as well as the runners themselves and their coaches may benefit from this study's results in order to improve the best time performance through a deeper understanding of the areas that mediate sex differences.

Alternative Metabolic Strategies are Employed by Endurance Runners of Different Body Sizes; Implications for Human Evolution

Objective

A suite of adaptations facilitating endurance running (ER) evolved within the hominin lineage. This may have improved our ability to reach scavenging sites before competitors, or to hunt prey over long distances. Running economy (RE) is a key determinant of endurance running performance, and depends largely on the magnitude of force required to support body mass. However, numerous environmental factors influence body mass, thereby significantly affecting RE. This study tested the hypothesis that alternative metabolic strategies may have emerged to enable ER in individuals with larger body mass and poor RE.

Methods

A cohort of male (n = 25) and female (n = 19) ultra-endurance runners completed submaximal and exhaustive treadmill protocols to determine RE, and V̇O2Max.

Results

Body mass was positively associated with sub-maximal oxygen consumption at both LT1 (male r=0.66, p<0.001; female LT1 r=0.23, p=0.177) and LT2 (male r=0.59, p=0.001; female r=0.23, p=0.183) and also with V̇O2Max (male r=0.60, p=0.001; female r=0.41, p=0.046). Additionally, sub-maximal oxygen consumption varied positively with V̇O2Max in both male (LT1 r=0.54, p=0.003; LT2 r=0.77, p<0.001) and female athletes (LT1 r=0.88, p<0.001; LT2 r=0.92, p<0.001).

Conclusions

The results suggest that, while individuals with low mass and good RE can glide economically as they run, larger individuals can compensate for the negative effects their mass has on RE by increasing their capacity to consume oxygen. The elevated energy expenditure of this low-economy high-energy turnover approach to ER may bring costs associated with energy diversion away from other physiological processes, however.

Could middle- and long-distance running performance of well-trained athletes be best predicted by the same aerobic parameters?

The prediction of running performance at different competitive distances is a challenge, since it can be influenced by several physiological, morphological and biomechanical factors. In experienced male runners heterogeneous for maximal oxygen uptake (VO₂max), endurance running performance can be well predicted by several key parameters of aerobic fitness such as VO₂max and its respective velocity (vVO₂max), running economy, blood lactate response to exercise, oxygen uptake kinetics and critical velocity. However, for a homogeneous group of well-trained endurance runners, the relationship between aerobic fitness parameters and endurance running performance seems to be influenced by the duration of the race (i.e., middle vs. long). Although middle-distance and ultramarathon runners present high aerobic fitness levels, there is no accumulating evidence showing that the aerobic key parameters influence both 800-m and ultramarathon performance in homogeneous group of well-trained runners. The vVO₂max seems to be the best predictor of performance for 1500 m. For 3000 m, both vVO₂max and blood lactate response to exercise are the main predictors of performance. Finally, for long distance events (5000 m, 10,000 m, marathon and ultramarathon), blood lactate response seems to be main predictor of performance. The different limiting/determinants factors and/or training-induced changes in aerobic parameters can help to explain this time- or distance-dependent pattern.

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Endurance running performance can be well predicted by several key parameters of aerobic fitness.

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The prediction of running exercise performance is crucial to elaborate the evaluation processes and training prescription.

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The contribution of key aerobic parameters to running performance of well-trained athletes presents a time- or distance-dependent pattern.

Relationship Between Body Segment Mass and Running Performance in Well-Trained Endurance Runners

This study examined the relationship between body segment mass and running performance in endurance runners. The total (muscle, fat, and bone masses), lean (muscle mass), and fat masses of the leg, arm, and trunk segments in 37 well-trained endurance runners were measured using dual-energy X-ray absorptiometer. The relative segment mass was calculated by normalizing the absolute mass to body mass. There were no significant correlations between absolute total, lean, and fat masses of all 3 segments and personal best 5000-m race time. No significant correlations were also observed between all 3 relative masses of the arm segment and personal best 5000-m race time. In contrast, medium positive correlations were observed between the relative total and lean masses of the leg segment and personal best 5000-m race time (r = .387 and .335, respectively, both P ≤ .031). Furthermore, large negative correlations were observed between the relative total and lean masses of the trunk segment and personal best 5000-m race time (r = -.500 and -.548, respectively, both P ≤ .002). These findings suggest that a mass distribution with smaller leg mass and greater trunk mass may be advantageous for achieving better running performance in endurance runners.

Characterising running economy and change of direction economy between soccer players of different playing positions, levels and sex

Traditional movement economy (ME) measures the energetic cost of in-line running. However, it is debatable whether such a measure is representative of movement efficiency for team sport athletes who are required to run and change direction repeatedly. This study evaluated ME during both in-line running and runs with directional changes and provided a preliminary exploration as to whether these abilities discriminate soccer players according to playing position, level, and sex. Forty-three soccer players were assessed for ME as extrapolated from oxygen uptake during in-line running (RE) and running with changes of directions (using 20 and 10 m shuttle runs [SRE₂₀ and SRE₁₀]) at 8.4 km/h mean speed. ME worsened with change of direction frequency (p < 0.001). Coefficient of determination was high between RE and SRE₂₀ (r²=0.601) but dropped below 0.5 for RE and SRE₁₀ (r² = 0.280) as change of direction frequency increased. No significant differences were observed between different player positions, however, centre midfielders reported the best ME across any position and running mode, with the largest differences observed in centre backs over SRE₁₀ (41.9 ± 2.7 ml/kg/min [centre midfielders] vs 45 ± 1.8 ml/kg/min [centre backs]; ES = 1.19). No significant differences were observed for ME over any running condition for male players of different playing levels. Female players exhibited better ME than male players with significant differences observed for SRE₁₀ (41.5 ± 2.6 ml/kg/min [females] vs 44 ± 2.6 ml/kg/min [males]; p = 0.013; ES = 0.94). RE does not adequately account for efficiency during activities that involve changes of direction. SRE₁₀ is a stronger discriminator of ME between soccer players of different position and sex.

Molecular Portrait of an Athlete

Sequencing of the human genome and further developments in "omics" technologies have opened up new possibilities in the study of molecular mechanisms underlying athletic performance. It is expected that molecular markers associated with the development and manifestation of physical qualities (speed, strength, endurance, agility, and flexibility) can be successfully used in the selection systems in sports. This includes the choice of sports specialization, optimization of the training process, and assessment of the current functional state of an athlete (such as overtraining). This review summarizes and analyzes the genomic, proteomic, and metabolomic studies conducted in the field of sports medicine.

Changes in Anthropometric and Performance Parameters in High-Level Endurance Athletes during a Sports Season

Several anthropometric and performance parameters related to aerobic metabolism are associated with performance in endurance runners and are modified according to the training performed. The objective of this study was to investigate the ergospirometric and body composition changes in endurance runners during a sports season in relation to their training. Twenty highly trained men endurance runners performed an incremental test until exhaustion (initial, and at 3, 6, and 9 months) on a treadmill to determine maximal oxygen consumption (VO₂ max), second ventilatory threshold (VT₂), and their associated running speeds. Skinfolds, perimeters, and weights were measured. No changes were obtained in VO₂ max or VT₂ during the study, although their associated running speeds increased (p < 0.05) after 3 months of the study. Decreases in fat mass (p < 0.05) and muscle mass (p < 0.05) were observed at the end of the season (9 months). Changes occurred in the different skinfolds according to the characteristics of the training performed during the season. In conclusion, vVO₂ max and vVT₂ increase with a greater volume of kilometres trained and can be adversely affected by loss of muscle mass.

Predicting middle-distance track and cross-country performances of national and international level adolescent runners

AbstractThis study evaluated the contribution of physiological data collected during laboratory testing in predicting race performances of trained junior middle-distance track (TK) and cross-country (XC) athletes. Participants performed a submaximal incremental ramp test, followed by an incremental test to exhaustion in a laboratory, with the results used to predict either 800 m TK, 1500 m TK or 4000-6000 m XC race performance. Twenty-eight participants (male (M), 15; female (F), 13) were analysed (age = 17 ± 2 years, height = 1.72 ± 0.08 m, body mass = 58.9 ± 8.9 kg). Performance times (min:s) for 800 m were: M, 1:56.55 ± 0:05.55 and F, 2:14.21 ± 0:03.89; 1500 m: M, 3:51.98 ± 0:07.35 and F 4:36.71 ± 0:16.58; XC: M (4900 ± 741 m), 16:00 ± 01:53; F (4628 ± 670 m), 17:41 ± 02:09. Stepwise regression analysis indicated significant contributions of speed at V̇O_2max (V̇O_2max), and heart rate maximum (HR_max) to the prediction of 800 m TK (F(_2,15) = 22.51, p < 0.001, adjusted R²= 0.72), V̇O_2max for 1500 m TK (F(_1,13) = 36.65, p < 0.001, adjusted R²= 0.72) and V̇O_2max, allometrically scaled to body mass and speed at lactate threshold (sLT) for XC (F(_2,17) = 25.1, p < 0.001, adjusted R²= 0.72). Laboratory-based physiological measures can explain 72% of the variance in junior TK and XC events, although factors that explain performance alter depending on the race distance and tactics. The factors determining performance in TK and XC events are not interchangeable.

Anthropometric Characteristics, Body Composition and Somatotype of Elite Male Young Runners

The purpose of the present study was to describe the anthropometric characteristics, body composition and somatotype of elite male young runners (EYR), and to compare these variables according to the specialty in which they engaged (middle-distance vs. long-distance). This will enable an anthropometric profile chart to be established for them. Ninety EYR aged 17 to 23 years (18.4 ± 2.0) participated in the study. Athletes were divided into two groups according to the event in which they participated: middle-distance runners (MDR, n = 56) and long-distance runners (LDR, n = 34). Sixteen anthropometric variables were recorded for each participant: Weight, height, eight skinfolds, four girths, and two breadths. Body mass index (BMI), body composition and somatotype were calculated. Comparing MDR with the group of LDR, significant differences were found to exist for height, weight, relaxed upper arm girth, flexed and tensed upper arm girth, total upper arm area, upper arm muscle area, and thigh muscle area. No significant differences were observed in the other variables. MDR are taller, heavier and have larger girths than LDR. Coaches and sports scientists can use the data obtained to better control training, as well as for talent identification and athlete selection.

Double-Poling Physiology and Kinematics of Elite Cross-Country Skiers: Specialized Long-Distance Versus All-Round Skiers

PURPOSE

Long-distance cross-country skiers specialize to compete in races >50 km predominantly using double poling (DP). This emphasizes the need for highly developed upper-body endurance capacities and an efficient DP technique. The aim of this study was to investigate potential effects of specialization by comparing physiological capacities and kinematics in DP between long-distance skiers and skiers competing using both techniques (skating/classic) in several competition formats ("all-round skiers").

METHODS

Seven male long-distance (32 [6] y, 183 [6] cm, 76 [5] kg) and 6 all-round (25 [3] y, 181 [5] cm, 75 [6] kg) skiers at high international levels conducted submaximal workloads and an incremental test to exhaustion for determination of peak oxygen uptake (VO2peak) and time to exhaustion (TTE) in DP and running.

RESULTS

In DP and running maximal tests, TTE showed no difference between groups. However, long-distance skiers had 5-6% lower VO2peak in running (81 [5] vs 85 [3] mL·kg-1·min-1; P = .07) and DP (73 [3] vs 78 [3] mL·kg-1·min-1; P < .01) than all-round skiers. In DP, long-distance skiers displayed lower submaximal O2 cost than all-round skiers (3.8 ± 3.6%; P < .05) without any major differences in cycle times or cyclic patterns of joint angles and center of mass. Lactate concentration over a wide range of speeds (45-85% of VO2peak) did not differ between groups, even though each workload corresponded to a slightly higher percentage of VO2peak for long-distance skiers (effect size: 0.30-0.68).

CONCLUSIONS

The long-distance skiers displayed lower VO2peak but compensated with lower O2 cost to perform equally with the all-round skiers on a short TTE test in DP. Furthermore, similar submaximal lactate concentration and reduced O2 cost could be beneficial in sustaining high skiing speeds in long-duration competitions.

Genes Whose Gain or Loss-of-Function Increases Endurance Performance in Mice: A Systematic Literature Review

Endurance is not only a key factor in many sports but endurance-related variables are also associated with good health and low mortality. Twin and family studies suggest that several endurance-associated traits are ≈50% inherited. However, we still poorly understand what DNA sequence variants contribute to endurance heritability. To address this issue, we conducted a systematic review to identify genes whose experimental loss or gain-of-function increases endurance capacity in mice. We found 31 genes including two isoforms of Ppargc1a whose manipulation increases running or swimming endurance performance by up to 1800%. Genes whose gain-of-function increases endurance are Adcy5, Adcy8, Hk2, Il15, Mef2c, Nr4a3, Pck1 (Pepck), Ppard, Ppargc1a (both the a and b isoforms of the protein Pgc-1α), Ppargc1b, Ppp3ca (calcineurin), Scd1, Slc5a7, Tfe3, Tfeb, Trib3 & Trpv1. Genes whose loss-of-function increases endurance in mice are Actn3, Adrb2, Bdkrb2, Cd47, Crym, Hif1a, Myoz1, Pappa, Pknox1, Pten, Sirt4, Thbs1, Thra, and Tnfsf12. Of these genes, human DNA sequence variants of ACTN3, ADCY5, ADRB2, BDKRB2, HIF1A, PPARD, PPARGC1A, PPARGC1B, and PPP3CA are also associated with endurance capacity and/or VO₂max trainability suggesting evolutionary conservation between mice and humans. Bioinformatical analyses show that there are numerous amino acid or copy number-changing DNA variants of endurance genes in humans, suggesting that genetic variation of endurance genes contributes to the variation of human endurance capacity, too. Moreover, several of these genes/proteins change their expression or phosphorylation in skeletal muscle or the heart after endurance exercise, suggesting a role in the adaptation to endurance exercise.

Lower Leg Length is Associated with Running Economy in High Level Caucasian Distance Runners

The aim of the present study was to investigate lower limb anthropometric and composition variables related to running economy (RE) and running performance in a homogeneous group of high level European distance runners. RE at the speeds of 14, 16 and 18 km·h⁻¹ (189 ± 12; 188 ± 11; 187 ± 11 O₂ ml·kg⁻¹·km⁻¹) and maximal oxygen uptake (VO_2max) (67.3 ± 2.9 ml·kg⁻¹·min⁻¹) of 13 high level distance runners were determined on a motorised treadmill. Anthropometric variables and body composition were measured. The BMI was related to RE at the speed of 14 (r² = 0.434; p = 0.014), 16 (r² = 0.436; p = 0.014) and 18 km·h⁻¹ (r² = 0.389; p = 0.023). Lower leg length was negatively related to RE at the speed of 16 and showed such a tendency at the speed of 14 and 18 km·h⁻¹. VO_2max indicated a moderate relationship with RE at the speeds of 14, 16 and 18 km·h⁻¹ (r² = 0.372, p = 0.030; r² = 0.350, p = 0.033; r² = 0.376, p = 0.026, respectively) which was confirmed by subsequent partial correlation analysis. While lower leg length and the BMI presented a relationship with RE, none of the calculated body composition and anthropometric proportions were related to RE or performance. The relationship between RE and VO_2max would confirm the notion that RE could be at least partly compensated by VO_2max to achieve high performance results.

BMI, a performance parameter for speed improvement

The purpose of this study is to investigate the association between anthropometric characteristics and performance in all track and field running events and assess Body Mass Index (BMI) as a relevant performance indicator. Data of mass, height, BMI and speed were collected for the top 100 international men athletes in track events from 100 m to marathon for the 1996-2011 seasons, and analyzed by decile of performance. Speed is significantly associated with mass (r = 0.71) and BMI (r = 0.71) in world-class runners and moderately with height (r = 0.39). Athletes, on average were continuously lighter and smaller with distance increments. In track and field, speed continuously increases with BMI. In each event, performances are organized through physique gradients. « Lighter and smaller is better » in endurance events but « heavier and taller is better » for sprints. When performance increases, BMI variability progressively tightens, but it is always centered around a distance-specific optimum. Running speed is organized through biometric gradients, which both drives and are driven by performance optimization. The highest performance level is associated with narrower biometric intervals. Through BMI indicators, diversity is possible for sprints whereas for long distance events, there is a more restrictive aspect in terms of physique. BMI is a relevant indicator, which allows for a clear differentiation of athletes' capacities between each discipline and level of performance in the fields of human possibilities.

Characteristics, changes and influence of body composition during a 4486 km transcontinental ultramarathon: results from the TransEurope FootRace mobile whole body MRI-project

BACKGROUND

Almost nothing is known about the medical aspects of runners doing a transcontinental ultramarathon over several weeks. The results of differentiated measurements of changes in body composition during the Transeurope Footrace 2009 using a mobile whole body magnetic resonance (MR) imager are presented and the proposed influence of visceral and somatic adipose and lean tissue distribution on performance tested.

METHODS

22 participants were randomly selected for the repeated MR measurements (intervals: 800 km) with a 1.5 Tesla MR scanner mounted on a mobile unit during the 64-stage 4,486 km ultramarathon. A standardized and validated MRI protocol was used: T1 weighted turbo spin echo sequence, echo time 12 ms, repetition time 490 ms, slice thickness 10 mm, slice distance 10 mm (breath holding examinations). For topographic tissue segmentation and mapping a modified fuzzy c-means algorithm was used. A semi-automatic post-processing of whole body MRI data sets allows reliable analysis of the following body tissue compartments: Total body volume (TV), total somatic (TSV) and total visceral volume (TVV), total adipose (TAT) and total lean tissue (TLT), somatic (SLT) and visceral lean tissue (VLT), somatic (SAT) and visceral adipose tissue (VAT) and somatic adipose soft tissue (SAST). Specific volume changes were tested on significance. Tests on difference and relationship regarding prerace and race performance and non-finishing were done using statistical software SPSS.

RESULTS

Total, somatic and visceral volumes showed a significant decrease throughout the race. Adipose tissue showed a significant decrease compared to the start at all measurement times for TAT, SAST and VAT. Lean adipose tissues decreased until the end of the race, but not significantly. The mean relative volume changes of the different tissue compartments at the last measurement compared to the start were: TV -9.5% (SE 1.5%), TSV -9.4% (SE 1.5%), TVV -10.0% (SE 1.4%), TAT -41.3% (SE 2.3%), SAST -48.7% (SE 2.8%), VAT -64.5% (SE 4.6%), intraabdominal adipose tissue (IAAT) -67.3% (SE 4.3%), mediastinal adopose tissue (MAT) -41.5% (SE 7.1%), TLT -1.2% (SE 1.0%), SLT -1.4% (SE 1.1%). Before the start and during the early phase of the Transeurope Footrace 2009, the non-finisher group had a significantly higher percentage volume of TVV, TAT, SAST and VAT compared to the finisher group. VAT correlates significantly with prerace training volume and intensity one year before the race and with 50 km- and 24 hour-race records. Neither prerace body composition nor specific tissue compartment volume changes showed a significant relationship to performance in the last two thirds of the Transeurope Footrace 2009.

CONCLUSIONS

With this mobile MRI field study the complex changes in body composition during a multistage ultramarathon could be demonstrated in detail in a new and differentiated way. Participants lost more than half of their adipose tissue. Even lean tissue volume (mainly skeletal muscle tissue) decreased due to the unpreventable chronic negative energy balance during the race. VAT has the fastest and highest decrease compared to SAST and lean tissue compartments during the race. It seems to be the most sensitive morphometric parameter regarding the risk of non-finishing a transcontinental footrace and shows a direct relationship to prerace-performance. However, body volume or body mass and, therefore, fat volume has no correlation with total race performances of ultra-athletes finishing a 4,500 km multistage race.

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.

What is associated with race performance in male 100-km ultra-marathoners--anthropometry, training or marathon best time?

We investigated the associations of anthropometry, training, and pre-race experience with race time in 93 recreational male ultra-marathoners (mean age 44.6 years, s = 10.0; body mass 74.0 kg, s = 9.0; height 1.77 m, s = 0.06; body mass index 23.4 kg · m(-2), s = 2.0) in a 100-km ultra-marathon using bivariate and multivariate analysis. In the bivariate analysis, body mass index (r = 0.24), the sum of eight skinfolds (r = 0.55), percent body fat (r = 0.57), weekly running hours (r = -0.29), weekly running kilometres (r = -0.49), running speed during training (r = -0.50), and personal best time in a marathon (r = 0.72) were associated with race time. Results of the multiple regression analysis revealed an independent and negative association of weekly running kilometres and average speed in training with race time, as well as a significant positive association between the sum of eight skinfold thicknesses and race time. There was a significant positive association between 100-km race time and personal best time in a marathon. We conclude that both training and anthropometry were independently associated with race performance. These characteristics remained relevant even when controlling for personal best time in a marathon.

Anthropometric and training variables related to half-marathon running performance in recreational female runners

The relationship between skin-fold thickness and running has been investigated in distances ranging from 100 m to the marathon distance (42.195 km), with the exclusion of the half-marathon distance (21.0975 km). We investigated the association between anthropometric variables, prerace experience, and training variables with race time in 42 recreational, nonprofessional, female half-marathon runners using bi- and multivariate analysis. Body weight (r, 0.60); body mass index (r, 0.48); body fat percentage (r, 0.56); pectoral (r, 0.61), mid-axilla (r, 0.69), triceps (r, 0.49), subscapular (r, 0.61), abdominal (r, 0.59), suprailiac (r, 0.55), and medial calf (r, 0.53) skin-fold thickness; mean speed of the training sessions (r, -0.68); and personal best time in a half-marathon (r, 0.69) correlated with race time after bivariate analysis. Body weight (P = 0.0054), pectoral skin-fold thickness (P = 0.0068), and mean speed of the training sessions (P = 0.0041) remained significant after multivariate analysis. Mean running speed during training was related to mid-axilla (r, -0.31), subscapular (r, -0.38), abdominal (r, -0.44), and suprailiac (r, -0.41) skin-fold thickness, the sum of 8 skin-fold thicknesses (r, -0.36); and percent body fat (r, -0.31). It was determined that variables of both anthropometry and training were related to half-marathon race time, and that skin-fold thicknesses were associated with running speed during training. For practical applications, high running speed during training (as opposed to extensive training) may both reduce upper-body skin-fold thicknesses and improve race performance in recreational female half-marathon runners.

Predictor variables for a 100-km race time in male ultra-marathoners

In 169 male 100-km ultra-marathoners, the variables of anthropometry, training, and prerace experience, in order to predict race time, were investigated. In the bivariate analysis, age (r = .24), body mass (r = .20), Body Mass Index (r = .29), circumference of upper arm (r = .26), percent body fat (r = .45), mean weekly running hours (r = -.21), mean weekly running kilometers (r = -.43), mean speed in training (r=-.56), personal best time in a marathon (r = .65), the number of finished 100-km ultra-runs (r = .24), and the personal best time in a 100-km ultra-run (r = .72) were associated with race time. Stepwise multiple regression showed that training speed (p < .0001), mean weekly running kilometers (p < .0001), and age (p < .0001) were the best correlations for a 100-km race time. Performance may be predicted (n=169, r2 = .43) by the following equation: 100-km race time (min) = 1085.60 - 36.26 x (training speed, km/hr.) - 1.43 x (training volume, km/wk.) + 2.50 x (age, yr.). Overall, intensity of training might be more important for a successful outcome in a 100-km race than anthropometric attributes. Motivation to train intensely for such an ultra-endurance run should be explored as this might be the key for a successful finish.

Similarity of anthropometric measures for male ultra-triathletes and ultra-runners

Previous research concluded that Triple Iron ultra-triathletes were close to runners in anthropometry. We assessed similarities in anthropometry between 64 Triple Iron triathletes who competed over 11.4 km swimming, 540 km cycling, and 126 km running versus 95 100-km ultra-marathoners. Variables of anthropometry such as body mass, body height, length and circumferences of limbs, skin-folds and body fat, and training such as volume and speed were compared between ultra-triathletes and ultra-runners. The Triple Iron triathletes completed their race distance within 2811 min. (SD=379) and the 100-km ultra-marathoners within 691 min. (SD=117). Triathletes were younger, had higher body mass, shorter legs, higher circumference of upper arm and thigh, lower sum of skin-folds, and lower percent body fat compared to runners. Weekly training volume was higher for triathletes, and weekly hours in running and weekly kilometres in running were higher for runners. In the Triple Iron ultra-triathletes, the sum of eight skin-folds correlated to total race time. The circumference of upper arm, the sum of eight skin-folds, and percent body fat correlated with time in the running section .42, .47, and .43, respectively. In the 100-km ultra-marathoners, the sum of eight skin-folds, the skin-fold thickness of thigh, percent body fat, weekly running hours, and weekly running kilometres correlated with race time .55, .40, .56, -.50, and -.51, respectively. However, in the triathletes, none of these training variables was significantly correlated with race time. In the ultra-marathoners, the sum of eight skin-folds, the skin-fold thickness of thigh, percent body fat, weekly running kilometres, and speed in running during training were related to race time (correlations of .55, .40, -.28, and -.51, respectively). Overall, the ultra-triathletes were not similar to ultra-runners in their anthropometric measures and training variables.

Predictor variables for half marathon race time in recreational female runners

INTRODUCTION

The relationship between skin-fold thickness and running performance has been investigated from 100 m to the marathon distance, except the half marathon distance.

OBJECTIVE

To investigate whether anthropometry characteristics or training practices were related to race time in 42 recreational female half marathoners to determine the predictor variables of half-marathon race time and to inform future novice female half marathoners.

METHODS

Observational field study at the 'Half Marathon Basel' in Switzerland.

RESULTS

In the bivariate analysis, body mass (r = 0.60), body mass index (r = 0.48), body fat (r = 0.56), skin-fold at pectoral (r = 0.61), mid-axilla (r = 0.69), triceps (r = 0.49), subscapular (r = 0.61), abdominal (r = 0.59), suprailiac (r = 0.55) medial calf (r = 0.53) site, and speed of the training sessions (r = -0.68) correlated to race time. Mid-axilla skin-fold (p = 0.04) and speed of the training sessions (p = 0.0001) remained significant after multi-variate analysis. Race time in a half marathon might be predicted by the following equation (r² = 0.71): Race time (min) = 166.7 + 1.7x (mid-axilla skin-fold, mm) - 6.4x (speed in training, km/h). Running speed during training was related to skinfold thickness at mid-axilla (r = -0.31), subscapular (r = -0.38), abdominal (r = -0.44), suprailiacal (r = -0.41), the sum of eight skin-folds (r = -0.36) and percent body fat (r = -0.31).

CONCLUSION

Anthropometric and training variables were related to half-marathon race time in recreational female runners. Skin-fold thicknesses at various upper body locations were related to training intensity. High running speed in training appears to be important for fast half-marathon race times and may reduce upper body skin-fold thicknesses in recreational female half marathoners.

Race performance in male mountain ultra-marathoners: anthropometry or training?

The association of anthropometric variables, training volume, and prerace experience with race time was investigated in 25 male mountain ultra-marathoners (M age = 44.5 yr., SD = 7.0; M body mass = 73.0 kg, SD = 7.8; M body height = 1.78 m, SD = 0.07; M Body Mass Index = 22.9 kg/m2, SD = 1.8) in a 7-day mountain ultra-marathon over 350 km with a total 11,000 m of altitude gained and lost. The relationship of anthropometry (body mass, body height, Body Mass Index, percent body fat, circumferences of limbs, and thicknesses of skin-folds), training, and prerace experience (years as active runner, average training volume in hours and kilometres per week, average running speed in training, and personal best time in marathon running) with total race time was investigated using bivariate correlation analysis. None of the variables of anthropometry were related to total race time. Average speed in running during training and personal best time in marathon running were associated with total race time. Speed in running during training was correlated with personal best time in marathon running. The finding that average speed in running during training and personal best marathon time were related to race performance suggests that training and especially intensity might be of increased importance in these ultra-runners compared to anthropometry.

Anthropometry and Pre-Race Experience of Finishers and Nonfinishers in a Multistage Ultra-Endurance Run — Deutschlandlauf 2007

The effects of anthropometry and pre-race experience on race performance were investigated in male nonprofessional ultra-runners performing a multistage run of 1,200 km over 17 days. Of 24 athletes examined pre-race, 14 (58 %) dropped out during the race due to overuse injuries of the lower limbs. During the race, body mass, thickness of the calf skin-fold, skeletal muscle mass, and percent body fat decreased significantly, while circumference of the upper arm, thickness of triceps, and abdominal skin-fold as well as Body Mass Index decreased significantly in the finishers. Neither anthropometry nor pre-race experience and training volume nor previously finished races were associated with the race time of the finishers. In future studies of ultra-runners, the influence of psychological (cognitive and emotional) predictors on race outcome should be investigated.

Body mass and circumference of upper arm are associated with race performance in ultraendurance runners in a multistage race--the Isarrun 2006

In the present study, we investigated the association of anthropometric parameters with race performance in ultraendurance runners in a multistage ultraendurance run, in which athletes had to run 338 km within 5 consectitive days. In 17 male successful finishers, calculations of body mass, body height, skinfold thicknesses, extremity circumference, skeletal muscle mass (SM), and percentage body fat (%BF) were performed before the race to correlate anthropometric parameters with race performance. A positive association was shown between total running time and both body mass (r2 = .29, p < .05) and upper arm circumference (r = .23, p < .05). In contrast, body height, skinfold thicknesses, extremity circumference, SM, and %BF showed no association with race performance (p > .05). We concluded that in a multistage ultraendurance run, body mass and upper arm circumference were nega tively associated with race performance in well experienced ultraendurance runners. In contrast, body height, skinfold thicknesses, circumferences of the other extremities, SM, and %BF showed no association with race performance.

Upper arm circumference is associated with race performance in ultra-endurance runners

OBJECTIVE

To investigate the association of anthropometric parameters to race performance in ultra-endurance runners in a multistage ultra-endurance run.

DESIGN

Descriptive field study.

SETTING

The Deutschlandlauf 2006 race in Germany, where athletes had to run 1200 km within 17 consecutive days. There were no interventions.

SUBJECTS

In total, there were 19 male Caucasian ultra-endurance runners (mean (SD) 46.2 (9.6) years, 71.8 (5.2) kg, 179 (6) cm, BMI 22.5 (1.9) kg/m(2)).

MAIN OUTCOME MEASUREMENTS

Determination of body mass, body height, length of lower limbs, skin-fold thicknesses, circumference of limbs, body mass index (BMI), percentage skeletal muscle mass (%SM), and percentage body fat (%BF) in 19 successful finishers in order to correlate anthropometric parameters with running performance.

RESULTS

A significant association of upper arm circumference with the total running time was found (p<0.05, r2 = 0.26). No significant association was found with the directly measured anthropometric properties body height, body mass, average skin-fold thickness and the circumference of thigh and calf (p>0.05). Furthermore, no significant association was observed between the running time and the calculated parameters BMI, %BF, and %SM (p>0.05).

CONCLUSIONS

In an ultra-endurance run over 1200 km within 17 consecutive days, circumference of the upper arm was the only factor associated with performance in well-experienced ultra-endurance runners. Body mass, BMI, body height, length of limbs, skin-fold thicknesses, circumference of limbs and the calculated percentage body composition of skeletal muscle mass and body fat showed no association with running performance.

Influence of anthropometry on race performance in extreme endurance triathletes: World Challenge Deca Iron Triathlon 2006

OBJECTIVE

To investigate the influence of anthropometric variables on race performance in ultra-endurance triathletes in an ultra-triathlon.

DESIGN

Descriptive field study.

SETTING

The "World Challenge Deca Iron Triathlon 2006" in Monterrey, Mexico, in which everyday for 10 consecutive days athletes had to perform the distance of one Ironman triathlon of 3.8 km swimming, 180 km cycling and 42.195 km running.

SUBJECTS

Eight male ultra-endurance athletes (mean (SD) age 40.6 (10.7) years, weight 76.4 (8.4) kg, height 175 (4) cm and body mass index (BMI) 24.7 (2.2) kg/m2).

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

Direct measurement of body mass, height, leg length, skinfold thicknesses, limb circumference and calculation of BMI, skeletal muscle mass (SM), percentage SM (%SM) and percentage body fat (%BF) in order to correlate measured and calculated anthropometric variables with race performance.

RESULTS

Race time was not significantly (p>0.05) influenced by the directly measured variables, height, leg length, body mass, average skinfold thicknesses, or circumference of thigh, calf or upper arm. Furthermore, no significant (p>0.05) correlation was observed between race time and the calculated variables, BMI, %SM and %BF.

CONCLUSIONS

In a multistage ultra-triathlon over 10 Ironman triathlon distances in 10 consecutive days, there was no effect of body mass, height, leg length, skinfold thicknesses, limb circumference, BMI, %SM or %BF on race performance in the only eight finishers.

VO2 attained during treadmill running: the influence of a specialist (400-m or 800-m) event

PURPOSE

Previously it has been observed that, in well-trained 800-m athletes, VO2max is not attained during middle-distance running events on a treadmill, even when a race-type pacing strategy is adopted. Therefore, the authors investigated whether specialization in a particular running distance (400-m or 800-m) influences the VO2 attained during running on a treadmill.

METHODS

Six 400-m and six 800-m running specialists participated in the study.A 400-m trial and a progressive test to determine VO2max were completed in a counterbalanced order. Oxygen uptakes attained during the 400-m trial were compared to examine the influence of specialist event.

RESULTS

A VO2 plateau was observed in all participants for the progressive test, demonstrating the attainment of VO2max. The VO2max values were 56.2 +/- 4.7 and 69.3 +/- 4.5 mL x kg-1 x min-1 for the 400-m- and 800-m-event specialists, respectively (P = .0003). Durations for the 400-m trial were 55.1 +/- 4.2 s and 55.8 +/- 2.3 s for the 400-m- and 800-m-event specialists, respectively. The VO2 responses achieved were 93.1% +/- 2.0% and 85.7% +/- 3.0% VO2max for the 400-m- and 800-m-event specialists, respectively (P = .001).

CONCLUSIONS

These results demonstrate that specialist running events do appear to influence the percentage of VO2max achieved in the 400-m trial, with the 800-m specialists attaining a lower percentage of VO2max than the 400-m specialists. The 400-m specialists appear to compensate for a lower VO2max by attaining a higher percentage VO2max during a 400-m trial.

Metabolic and behavioral compensatory responses to exercise interventions: barriers to weight loss

An activity-induced increase in energy expenditure theoretically disturbs energy balance (EB) by creating an acute energy deficit. Compensatory responses could influence the weight loss associated with the energy deficit. Individual variability in compensation for perturbations in EB could partly explain why some individuals fail to lose weight with exercise. It is accepted that the regulatory system will readily defend impositions that promote a negative EB. Therefore, a criticism of exercise interventions is that they will be ineffective and futile methods of weight control because the acute energy deficit is counteracted. Compensation for exercise-induced energy deficits can be categorized into behavioral or metabolic responses and automatic or volitional. An automatic compensatory response is a biological inevitability and considered to be obligatory. An automatic compensatory response is typically a metabolic consequence (e.g., reduced resting metabolic rate) of a negative EB. In contrast, a volitional compensatory response tends to be deliberate and behavioral, which the individual intentionally performs (e.g., increased snack intake). The purpose of this review is to highlight the various metabolic and behavioral compensatory responses that could reduce the effectiveness of exercise and explain why some individuals experience a lower than expected weight loss. We propose that the extent and degree of compensation will vary between individuals. That is, some individuals will be predisposed to compensatory responses that render them resistant to the weight loss benefits theoretically associated with an exercise-induced increase in energy expenditure. Therefore, given the inter-individual variability in behavioral and metabolic compensatory responses, exercise prescriptions might be more effective if tailored to suit individuals.

Nutritional status of adventure racers

OBJECTIVE

We describe the usual food intake, body composition, and biochemical profile of adventure racers during their training season and evaluate their energy and nutrient intake in relation to current recommendations for ultraendurance athletes.

METHODS

Twenty-four adventure race athletes (18 men and 6 women), 24 to 42 y of age, participated in the study. Food intake was determined with a 3-d food record and body composition by plethysmography. Blood samples were obtained from all subjects for biochemical analyses. All assessments were made during the usual training phase.

RESULTS

Female athletes had a higher body fat percentage than did male athletes (20.2 +/- 5.7% versus 12.5 +/- 3.5%). For men and women, food intake was high in protein (1.9 +/- 0.5 g/kg in men, 2.0 +/- 0.4 g/kg in women) and fat (1.6 +/- 0.3 g/kg in men, 1.5 +/- 1.3 g/kg in women). Carbohydrate intake of male athletes was at the lower limit of that recommended (5.9 +/- 1.8 g/kg). For most vitamins and minerals, athletes' intake was adequate, with the exception of magnesium, zinc, and potassium in men and women and vitamin E and calcium in women, which presented a high probability of being inadequate compared with reference values. High blood levels of total cholesterol and low-density lipoprotein cholesterol were found in female athletes (201.0 +/- 44.7 and 104.1 +/- 43.1 mg/dL, respectively) and all other biochemical analyses were within normal reference values.

CONCLUSION

The adventure racers presented an inadequate nutritional profile when compared with recommendations for endurance exercise. These athletes need to be educated about consuming an adequate diet to meet the nutritional needs of their activity.

Cardiopulmonary physiology and responses of ultramarathon athletes to prolonged exercise

The purpose of this study was to determine the changes of pulmonary function and autonomic cardiovascular control after an ultramarathon and their relation to performance. Eight entrants to the Canadian National Championship 100-km running race participated in the study. Pulmonary function and 30-s maximum voluntary ventilation (MVV30s) tests were conducted one day before the race and within 5 minutes of race completion. Heart rate and blood pressure data were collected 30 min before and 5 min after the race as well as during a 10-min stand test one day prior to the race. During the race, beat-by-beat R-R interval data were collected over the first and last 20 km. The results showed that MVV30s and MVV30s tidal volumes were reduced postrace (p < 0.001). Prerace supine total harmonic variation (p < 0.01) and prerace MVV values (10 s to 30 s) (p < 0.05) were correlated with race finish time. The changes in pulmonary function and MVV30s values from pre- and postrace were not significantly correlated to race performance. We conclude that maximal sustainable ventilatory power and dynamic autonomic cardiovascular control are important factors in determining overall performance in an ultramarathon.

Cross talk between physical activity and appetite control: does physical activity stimulate appetite?

Physical activity has the potential to modulate appetite control by improving the sensitivity of the physiological satiety signalling system, by adjusting macronutrient preferences or food choices and by altering the hedonic response to food. There is evidence for all these actions. Concerning the impact of physical activity on energy balance, there exists a belief that physical activity drives up hunger and increases food intake, thereby rendering it futile as a method of weight control. There is, however, no evidence for such an immediate or automatic effect. Short (1-2 d)-term and medium (7-16 d)-term studies demonstrate that men and women can tolerate substantial negative energy balances of < or = 4 MJ energy cost/d when performing physical activity programmes. Consequently, the immediate effect of taking up exercise is weight loss (although this outcome is sometimes difficult to assess due to changes in body composition or fluid compartmentalization). However, subsequently food intake begins to increase in order to provide compensation for about 30% of the energy expended in activity. This compensation (up to 16 d) is partial and incomplete. Moreover, subjects separate into compensators and non-compensators. The exact nature of these differences in compensation and whether it is actually reflective of non-compliance with protocols is yet to be determined. Some subjects (men and women) performing activity with a cost of < or = 4 MJ/d for 14 d, show no change in daily energy intake. Conversely, it can be demonstrated that when active individuals are forced into a sedentary routine food intake does not decrease to a lower level to match the reduced energy expenditure. Consequently, this situation creates a substantial positive energy balance accompanied by weight gain. The next stage is to further characterize the compensators and non-compensators, and to identify the mechanisms (physiological or behavioural) that are responsible for the rate of compensation and its limits.

Physical activity energy expenditure measured using a portable telemetric device in comparison with a mass spectrometer

BACKGROUND

Several studies have evaluated the accuracy of portable metabolic gas analysis systems, which measure physical activity energy expenditure. Since the Cosmed K2 telemetric system, two K4 devices (RQ and b2) have been developed.

OBJECTIVE

To compare measurements using the Cosmed K4 RQ with measurements by a traditional method (mass spectrometer) for a sample of healthy subjects performing physical exercise of various intensities.

METHODS

Nine healthy male footballers (mean (SD) age 18.3 (2.2) years) performed an incremental exercise running test from 8 km/h to exhaustion, with an increase of 2 km/h for each level of the test protocol. The expired air was collected simultaneously using the Cosmed K4 RQ and Airspec QP9000 mass spectrometer. Oxygen consumption (VO2) and carbon dioxide production (VCO2) were measured at rest and at each exercise intensity.

RESULTS

No significant differences were found between VO2 and VCO2 measured by the two instruments, at rest or during exercise.

CONCLUSIONS

The application of the Cosmed K4 RQ system for VO2 and VCO2 measurements at rest and during both submaximal and maximal exercise may be of interest to sport physiologists, nutritionists, and doctors.

What makes an endurance athlete world-class? Not simply a physiological conundrum

Inter-individual variation in endurance performance capacity is a characteristic, not only of the general population, but also in trained athletes. The ability of sport scientists to predict which athletes amongst an elite group will become world-class is limited. We do not fully understand the interactions between biological factors, training, recovery and competitive performance. Assessment methods and interpretation of results do not take into account the facts that most research is not done on elite athletes and performances of world-class endurance athletes cannot be attributed to aerobic capacity alone. Many lines of evidence suggest that there is a limit to adaptation in aerobic capacity. Recent advances in molecular biology and genetics should be harnessed by exercise biologists in conjunction with previously used physiological, histological and biochemical techniques to study elite athletes and their responses to different training and recovery regimens. Technological advances should be harnessed to study world-class athletes to determine optimal training and competition strategies. In summary, it is likely that multiple factors are essential contributors to world-class endurance performance and that it is only by using a multidisciplinary approach that we will come closer to solving the conundrum: 'What makes an endurance athlete world class?'