Endurance training and performance in runners: research limitations and unanswered questions

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.

Predictive Performance Models in Long-Distance Runners: A Narrative Review

Physiological variables such as maximal oxygen uptake (VO₂max), velocity at maximal oxygen uptake (vVO₂max), running economy (RE) and changes in lactate levels are considered the main factors determining performance in long-distance races. The aim of this review was to present the mathematical models available in the literature to estimate performance in the 5000 m, 10,000 m, half-marathon and marathon events. Eighty-eight articles were identified, selections were made based on the inclusion criteria and the full text of the articles were obtained. The articles were reviewed and categorized according to demographic, anthropometric, exercise physiology and field test variables were also included by athletic specialty. A total of 58 studies were included, from 1983 to the present, distributed in the following categories: 12 in the 5000 m, 13 in the 10,000 m, 12 in the half-marathon and 21 in the marathon. A total of 136 independent variables associated with performance in long-distance races were considered, 43.4% of which pertained to variables derived from the evaluation of aerobic metabolism, 26.5% to variables associated with training load and 20.6% to anthropometric variables, body composition and somatotype components. The most closely associated variables in the prediction models for the half and full marathon specialties were the variables obtained from the laboratory tests (VO₂max, vVO₂max), training variables (training pace, training load) and anthropometric variables (fat mass, skinfolds). A large gap exists in predicting time in long-distance races, based on field tests. Physiological effort assessments are almost exclusive to shorter specialties (5000 m and 10,000 m). The predictor variables of the half-marathon are mainly anthropometric, but with moderate coefficients of determination. The variables of note in the marathon category are fundamentally those associated with training and those derived from physiological evaluation and anthropometric parameters.

Association between Trace Elements and Body Composition Parameters in Endurance Runners

The aim of this study was to determine the possible correlations between essential and toxic trace elements of plasma with several anthropometric and body composition parameters and performance in endurance runners. Sixty-five high-level middle and long-distance runners (21  ±  3 years; 1.77 ± 0.05 m; 64.97 ± 7.36 kg; VO₂ max. 67.55 ± 4.11 mL/min/kg) participated in the present study. Abdominal, subscapular, iliac crest, triceps, front thigh and medial calf skinfold thicknesses and an incremental test until exhaustion were recorded. Body, fat, muscle and bone mass were estimated. Plasma trace elements were analyzed with inductively coupled plasma mass spectrometry (ICP-MS). Correlations and simple linear regression were used to assess the relationship between trace elements and several variables. Different skinfolds, fat mass, muscle mass and bone mass correlated positively and negatively with trace elements such as copper, manganese, selenium, vanadium, zinc, lithium, rubidium, strontium, arsenic, beryllium and lead. Lithium was related with performance. In conclusion, endurance training causes changes in the body concentrations of several trace elements that trigger modifications in body composition that may be interesting, if confirmed in the future, for the control of metabolic diseases such as obesity.

Hormonal Changes in High-Level Aerobic Male Athletes during a Sports Season

The aim of this study was to determine the possible changes in plasma of several hormones such as Luteinizing Hormone, Testosterone, Cortisol and Insulin in endurance runners during the sports season. Twenty-one high-level male endurance runners (22 ± 3.2 years, 1.77 ± 0.05 m) participated in the study. Basal plasma hormones were measured at four moments during the season (initial, 3, 6 and 9 months), and were analyzed using ELISA (enzyme-linked immunosorbent assay). Testosterone and Luteinizing Hormone (LH) suffered very significant decreases (p < 0.01) at 3 months compared with the beginning and an increase (p < 0.05) at 6 and 9 months compared with 3 months. Insulin level was significantly lower (p < 0.05) at 3, 6 and 9 months compared with the initial test. Insulin and cortisol were associated inversely (r = 0.363; β = -0.577; p = 0.017) and positively (r = 0.202; β = 0.310; p = 0.043), respectively, with the amount of km per week performed by the runners. There was a significant association between km covered at a higher intensity than the anaerobic threshold and I (r = 0.580; β = -0.442; p = 0.000). Our findings indicate that testosterone, LH and insulin were more sensitive to changes in training volume and intensity than cortisol in high-level endurance runners. Basal testosterone and LH concentrations decrease in athletes who perform a high volume of aerobic km in situations of low energy availability.

The relationships between age and running performance variables in master runners

Purpose

Peak aerobic capacity (V̇O2peak) declines with age, but running economy (RE) may not. We evaluated VO2peak and RE in master runners and determined whether age is associated with these measures.

Methods

In a cross-sectional study, runners completed two running tests within four weeks of a goal race of 10-26.2 miles. Subjects ran for five min at 88% of predicted maximum heart rate, approximating a marathon-intensity effort (MIE), then performed a V̇O2peak test. Running economy in the MIE was measured using oxygen cost with body mass scaled allometrically (alloV̇O2); energy cost (EC), determined using caloric equivalents; and percent of V̇O2peak (%V̇O2peak). Pearson's correlations were used to determine relationships between age and running performance variables.

Results

Runners (n = 31, 13 females; mean age 54.9 ± 8.4 years) had a mean VO2peak of 52.5 ± 7.9 ml O2 kg-1 min-1. Age was significantly correlated with V̇O2peak (r = - 0.580, p = 0.001) and alloV̇O2 (r = - 0.454, p = 0.034). Age was related to EC in females (r = 0.649, p = 0.042) and MIE V̇O2 in males (r = - 0.600, p = 0.039).

Conclusions

In this population, age was negatively associated with V̇O2peak and alloV̇O2. Females showed a positive relationship between age and EC, while males had a negative correlation between age and MIE V̇O2. Aerobic capacity declines with age, but there may be sex differences in age-related alterations to submaximal running.

"Question Your Categories": the Misunderstood Complexity of Middle-Distance Running Profiles With Implications for Research Methods and Application

Middle-distance running provides unique complexity where very different physiological and structural/mechanical profiles may achieve similar elite performances. Training and improving the key determinants of performance and applying interventions to athletes within the middle-distance event group are probably much more divergent than many practitioners and researchers appreciate. The addition of maximal sprint speed and other anaerobic and biomechanical based parameters, alongside more commonly captured aerobic characteristics, shows promise to enhance our understanding and analysis within the complexities of middle-distance sport science. For coaches, athlete diversity presents daily training programming challenges in order to best individualize a given stimulus according to the athletes profile and avoid “non-responder” outcomes. It is from this decision making part of the coaching process, that we target this mini-review. First we ask researchers to “question their categories” concerning middle-distance event groupings. Historically broad classifications have been used [from 800 m (~1.5 min) all the way to 5,000 m (~13–15 min)]. Here within we show compelling rationale from physiological and event demand perspectives for narrowing middle-distance to 800 and 1,500 m alone (1.5–5 min duration), considering the diversity of bioenergetics and mechanical constraints within these events. Additionally, we provide elite athlete data showing the large diversity of 800 and 1,500 m athlete profiles, a critical element that is often overlooked in middle-distance research design. Finally, we offer practical recommendations on how researchers, practitioners, and coaches can advance training study designs, scientific interventions, and analysis on middle-distance athletes/participants to provide information for individualized decision making trackside and more favorable and informative study outcomes.

Secular Trend in Thinness Prevalence for 26 Years (1989 - 2014) among High School Runners in Japan

Background

Female distance runners are predisposed to thinness for performance reasons and at greater risk for health-related consequences than the general population.

Objectives

The aim of the study was to evaluate the secular trends in thinness among competitive distance runners in Japanese high schools with sex-specific comparison.

Methods

Body mass index (BMI) were analysed in 9,881 female and 12,786 male runners participating in the annual national road relay races between 1989 and 2014 using the directory of a track and field magazine. The age-specific trends of these variables and the prevalence of thinness were tested by linear and logistic regression, respectively.

Results

Although BMI declined significantly among both male and female runners (coefficients: boys, -0.033, -0.030, and -0.032; girls, -0.033, -0.034, and -0.034 [all P < 0.001] in 15.5-, 16.5-, and 17.5-year-olds, respectively), the prevalence of severely thin runners significantly increased only among girls (odds ratios for the yearly change = 1.05 and 1.06 [both P < 0.01] for 16.5- and 17.5-year-olds, respectively). Only 0.13% of male runners were regarded as severely thin throughout the study period.

Conclusions

The results suggested that severely thin girl runners has steadily increased. Surveys on the health consequences of extreme thinness are necessary for the female adolescent runners.

10 km running performance predicted by a multiple linear regression model with allometrically adjusted variables

The aim of this study was to verify the power of VO_2max, peak treadmill running velocity (PTV), and running economy (RE), unadjusted or allometrically adjusted, in predicting 10 km running performance. Eighteen male endurance runners performed: 1) an incremental test to exhaustion to determine VO_2max and PTV; 2) a constant submaximal run at 12 km·h⁻¹ on an outdoor track for RE determination; and 3) a 10 km running race. Unadjusted (VO_2max, PTV and RE) and adjusted variables (VO_2max^0.72, PTV^0.72 and RE^0.60) were investigated through independent multiple regression models to predict 10 km running race time. There were no significant correlations between 10 km running time and either the adjusted or unadjusted VO_2max. Significant correlations (p < 0.01) were found between 10 km running time and adjusted and unadjusted RE and PTV, providing models with effect size > 0.84 and power > 0.88. The allometrically adjusted predictive model was composed of PTV^0.72 and RE^0.60 and explained 83% of the variance in 10 km running time with a standard error of the estimate (SEE) of 1.5 min. The unadjusted model composed of a single PVT accounted for 72% of the variance in 10 km running time (SEE of 1.9 min). Both regression models provided powerful estimates of 10 km running time; however, the unadjusted PTV may provide an uncomplicated estimation.

Changes in Endurance Performance in Young Athletes During Two Training Seasons

The aim of the study was to assess changes in endurance performance in young runners (females and males) during two training seasons. It involved 19 male and 16 female athletes aged 15-17 specializing in track-and-field middle and long distances runs. The following parameters were measured three times during the training season: maximal oxygen uptake, running economy, and the level of the second ventilatory threshold. Training volume and intensity during each season were analyzed within an 8-week period prior to the exercise tests. The volume and intensity of training at various stages of preparation in both seasons were similar. During the first year of observation, significant improvements in relative volume of maximal oxygen uptake were reported both in female and male athletes. During the second training season, it was found that running economy improved both in women and men, with no changes in maximal oxygen uptake. The same (in terms of volume and intensity) endurance training carried out with young runners during two consecutive training seasons can result in different training effects.

Effect of body composition on respiratory compensation point during an incremental test

Body mass (BM) and composition are considered to be significant determinants of aerobic endurance. The purpose of this study was to examine the influence of BM and its composition makeup on endurance performance. Thirty-nine men were divided into 3 groups of significantly different BM and mass composition: a control group, a group with high body fat (HBF), and a group with high lean body mass (HLBM). Participants in the HBF and HLBM groups had similar BM, which was significantly greater than observed in the control group. All participants performed an incremental treadmill test to volitional failure. Endurance performance was assessed on the basis of respiratory compensation point (RCP). The HBF and HLBM groups exceeded RCP at a much lower work intensity, expressed as %HRmax and %VO2max, compared with the control group. When considered relative to BM and lean body mass, oxygen consumption values at RCP were significantly less in the HBF and HLBM groups compared with the control group. Increased BM, regardless of its composition, substantially reduced aerobic endurance performance. Therefore, athletes and coaches should pay attention to not only the percentage of body fat but also to the amount of lean body mass because any gain may adversely affect aerobic endurance performance.

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.

Rationale and resources for teaching the mathematical modeling of athletic training and performance

A number of professions rely on exercise prescription to improve health or athletic performance, including coaching, fitness/personal training, rehabilitation, and exercise physiology. It is therefore advisable that the professionals involved learn the various tools available for designing effective training programs. Mathematical modeling of athletic training and performance, which we henceforth call "performance modeling," is one such tool. Two models, the critical power (CP) model and the Banister impulse-response (IR) model, offer complementary information. The CP model describes the relationship between work rates and the durations for which an individual can sustain them during constant-work-rate or intermittent exercise. The IR model describes the dynamics by which an individual's performance capacity changes over time as a function of training. Both models elegantly abstract the underlying physiology, and both can accurately fit performance data, such that educating exercise practitioners in the science of performance modeling offers both pedagogical and practical benefits. In addition, performance modeling offers an avenue for introducing mathematical modeling skills to exercise physiology researchers. A principal limitation to the adoption of performance modeling is a lack of education. The goal of this report is therefore to encourage educators of exercise physiology practitioners and researchers to incorporate the science of performance modeling in their curricula and to serve as a resource to support this effort. The resources include a comprehensive review of the concepts associated with the development and use of the models, software to enable hands-on computer exercises, and strategies for teaching the models to different audiences.

Distance running as an ideal domain for showing a sex difference in competitiveness

Men are over-represented in the arts, sciences, and sports. This has been hypothesized to reflect an evolved male predisposition for enduring competitiveness or long-term motivation to improve one's performance and "show-off." Evidence for this hypothesis is equivocal, however, because there are viable alternative explanations for men's dominance in most cultural display domains. Here, I argue that distance running is an ideal domain for addressing this issue. Distance running is ideal because it indicates enduring competitiveness, allows objective comparisons, and is accessible, acceptable, and popular for both men and women. I review recent studies and present new data showing that substantially more men than women run relatively fast in the U.S., that this sex difference in relative performance can be attributed, at least in part, to men's greater training motivation, and that this pattern has been stable for several decades. Distance running thus provides compelling evidence for an evolved male predisposition for enduring competitiveness. I conclude with suggestions regarding how variation in achievement motivation can be informed by considering how evolved predispositions interact with environmental and social conditions.

Effects of recovery mode (active vs. passive) on performance during a short high-intensity interval training program: a longitudinal study

The aim of this longitudinal study was to compare two recovery modes (active vs. passive) during a seven-week high-intensity interval training program (SWHITP) aimed to improve maximal oxygen uptake ([Formula: see text]), maximal aerobic velocity (MAV), time to exhaustion (t lim) and time spent at a high percentage of [Formula: see text], i.e., above 90 % (t90 [Formula: see text]) and 95 % (t95 [Formula: see text]) of [Formula: see text]. Twenty-four adults were randomly assigned to a control group that did not train (CG, n = 6) and two training groups: intermittent exercise (30 s exercise/30 s recovery) with active (IEA, n = 9) or passive recovery (IEP, n = 9). Before and after seven weeks with (IEA and IEP) or without (CG) high-intensity interval training (HIT) program, all subjects performed a maximal graded test to determine their [Formula: see text] and MAV. Subsequently only the subjects of IEA and IEP groups carried out an intermittent exercise test consisting of repeating as long as possible 30 s intensive runs at 105 % of MAV alternating with 30 s active recovery at 50 % of MAV (IEA) or 30 s passive recovery (IEP). Within IEA and IEP, mean t lim and MAV significantly increased between the onset and the end of the SWHITP and no significant difference was found in t90 VO2max and t95 VO2max. Furthermore, before and after the SWHITP, passive recovery allowed a longer t lim for a similar time spent at a high percentage of VO2max. Finally, within IEA, but not in IEP, mean VO2max increased significantly between the onset and the end of the SWHITP both in absolute (p < 0.01) and relative values (p < 0.05). In conclusion, our results showed a significant increase in VO2max after a SWHITP with active recovery in spite of the fact that t lim was significantly longer (more than twice longer) with respect to passive recovery.

Anaerobic Work Capacity’s Contribution to 5-km-Race Performance in Female Runners

Purpose:

The purpose of this study was to examine the relationship between anaerobic characteristics and 5-km-race performance in trained female cross-country runners (N = 13).

Methods:

The runners performed 50-m sprints and a 5-km time trial on an outdoor 400-m track and maximal anaerobic (MART) and aerobic running tests on a motorized treadmill. Anaerobic characteristics were determined by the mean velocity of the 50-m sprint (v50m) and the peak velocity in the MART (vMART). The aerobic characteristics were obtained during the aerobic treadmill test and included maximal oxygen uptake (VO2max), running economy, and ventilatory threshold (VT).

Results:

Both the vMART (r = .69, P < .01) and VO2max (r = .80, P < .01) correlated with the mean velocity of the 5-km (v5km). A multiple-linear-regression analysis revealed that the combination of VO2max, vMART, and VT explained 81% (R2 = .81, P < .001) of the variation seen in the v5km. The vMART accounted for 31% of the total shared variance, while the combination of VO2max and VT explained the remaining 50%.

Conclusions:

These results suggest that among trained female runners who are relatively matched, anaerobic energy production can effectively discriminate the v5km and explain a significant amount of the variation seen in 5-km-race performance.

Physiological determinants of speciality of elite middle- and long-distance runners

The aim of this study was to determine which physiological variables predict excellence in middle- and long-distance runners. Forty middle-distance runners (age 23 ± 4 years, body mass 67.2 ± 5.9 kg, stature 1.80 ± 0.05 m, VO(2max) 65.9 ± 4.5 ml · kg(-1) · min(-1)) and 32 long-distance runners (age 25 ± 4 years, body mass 59.8 ± 5.1 kg, stature 1.73 ± 0.06 m, VO(2max) 71.6 ± 5.0 ml · kg(-1) · min(-1)) competing at international standard performed an incremental running test to exhaustion. Expired gas analysis was performed breath-by-breath and maximum oxygen uptake (VO(2max)) and two ventilatory thresholds (VT(1) and VT(2)) were calculated. Long-distance runners presented a higher VO(2max) than middle-distance runners when expressed relative to body mass (P < 0.001, d = 1.18, 95% CI [0.68, 1.68]). At the intensities corresponding to VT(1) and VT(2), long-distance runners showed higher values for VO(2) expressed relative to body mass or %VO(2max), speed and oxygen cost of running (P < 0.05). When oxygen uptake was adjusted for body mass, differences between groups were consistent. Logistic binary regression analysis showed that VO(2max) (expressed as l · min(-1) and ml · kg(-1) · min(-1)), VO(2VT2) (expressed as ml · kg(-0.94) · min(-1)), and speed at VT(2) (v(VT2)) categorized long-distance runners. In addition, the multivariate model correctly classified 84.7% of the athletes. Thus, VO(2max), VO(2VT2), and v(VT2) discriminate between elite middle-distance and long-distance runners.

More men run relatively fast in U.S. road races, 1981-2006: a stable sex difference in non-elite runners

Recent studies indicate that more men than women run fast relative to sex- specific world records and that this sex difference has been historically stable in elite U.S. runners. These findings have been hypothesized to reflect an evolved male predisposition for enduring competitiveness in "show-off" domains. The current study tests this hypothesis in non-elite runners by analyzing 342 road races that occurred from 1981-2006, most in or near Buffalo, NY. Both absolutely and as a percentage of same-sex finishers, more men ran relatively fast in most races. During the 1980s, as female participation surged, the difference in the absolute number of relatively fast men and women decreased. However, this difference was stable for races that occurred after 1993. Since then, in any given race, about three to four times as many men as women ran relatively fast. The stable sex difference in relative performance shown here for non-elites constitutes new support for the hypothesis of an evolved male predisposition for enduring competitiveness.

The effect of high- vs. low-intensity training on aerobic capacity in well-trained male middle-distance runners

The purpose of this study was to examine the effect of 2 different intervention training regimes on VO2max, VO2max velocity (vVO2max), running economy (RE), lactic threshold velocity (vLT), and running performance on a group of well-trained male middle-distance runners in the precompetition period. Twenty-six well-trained male middle-distance runners took part in the study. All participants were tested on VO2max, vVO2max, RE, lactate threshold (LT), vLT, and a performance test. The participants were matched according to their pretest results, then randomly assigned into 1 of 2 groups, a high-volume (70 km) low-intensity training group (HVLI-group); or a high-intensity low-volume (50 km) training group (HILV-group). No significant differences were found between the 2 groups on all measures both before and after the intervention period. Furthermore, the HILV-group had a marked increase in vVO2max and vLT after the training period when compared with pretest. Both groups had a marked improvement in RE. The performance test showed that the HILV-group made 301 ± 886 m (1.0 ± 2.8 minutes) and the HVLI-group 218 ± 546 m (0.9 ± 1.8 minutes) in progress. The production of lactic acid was notably higher in the HILV-group (0.9 mmol) when compared with the pretest. The findings show that male middle-distance runners tested in this study improved in vVO2max and vLT more when they train around LT, than training with low intensity for a short period of 10 weeks.

Immediate effect of visual and auditory feedback to control the running mechanics of well-trained athletes

The correlation between mechanical factors of running and running economy as measured by metabolic cost is a subject of much interest in the study of locomotion. However, no change in running technique has been shown to result in an immediate improvement in running economy on an intra-individual basis. To evaluate the effect of a modified running technique, it is probably necessary that the individual trains with the new technique for a longer period using a feedback system to control the new kinematics. In this study, we examine the feasibility of using visual and auditory feedback to adapt running technique according to a simplistic model of the mechanical cost of running. The model considers only the mechanical work against gravity, which is the product of the magnitude of the vertical displacement of the runner's centre of mass and the step-frequency. In the experiments reported here, 18 trained runners, running at 16 km · h(-1) on a treadmill, were given feedback on these parameters together with indicated target levels. In almost all cases, the runners were able to adjust their technique accordingly.

Performance modeling in an Olympic 1500-m finalist: a practical approach

The purpose of this study was to test if a simplified impulse-response (IR) model would correlate with competition performances in an elite middle-distance runner over a period of 7 years that encompassed two Olympiads. Daily recorded pace and time obtained from training logs of this individual for the years 2000 to 2006 were used to calculate the impulse (training stress score, or TSS). The daily TSS was used to generate acute and chronic training loads (ATL and CTL, respectively), and a model response output, or p(t), was calculated based on the relationship p(t) = CTL - ATL. Competition performances (800 m-1 mile) were converted to Mercier scores (MS) and compared to p(t) and model parameters TSS, ATL, and CTL. MS was positively correlated with model output response p(t) (p < 0.01) and negatively with ATL (p < 0.01). Quadratic relationships were also observed between MS and both p(t) and CTL (p < 0.001), potentially indicating an optimal balance between fitness, fatigue, and performance. The results of this study demonstrate that the output of this simplified IR modeling approach correlates with performance in at least 1 elite athlete. Further studies are necessary to determine the generalizability of this method, but coaches may wish to use this approach to analyze previous training and performance relationships and iteratively modify training to optimize performance.

Are there differences in running economy at different velocities for well-trained distance runners?

The present study investigated whether there are differences in running economy at different velocities for well-trained distance runners, and to what extent a commonly used incremental protocol for measuring oxygen uptake (VO(2)) at different velocities affects the reliability of these measurements. Fifteen well-trained distance runners (9 male and 6 female) participated in this study. Gross oxygen cost of running (C (R)), heart rate (HR) and [La(-)](b) during 5-min runs at velocities ranging from 8.0 to 17 km h(-1), representing intensities ranging from 60 to 90% of maximal oxygen consumption (VO(2max)) was measured on two different days in random order. The athletes were also tested for lactate threshold, VO(2max) and time to exhaustion at MAS ((t)MAS). No significant differences in C (R) between the different relative velocities or the different set velocities were found up to 90% of VO(2max). The incremental protocol for measuring VO(2) at different velocities was found not to affect the reliability of these measurements. All athletes reached their VO(2max) whilst running to exhaustion at MAS. The females showed significantly lower VO(2max), but significantly better C (R) than the males. At velocities representing intensities between 60 and 90% of VO(2max), no differences in C (R) were found. The commonly used incremental protocol for measuring oxygen uptake (VO(2)) at different velocities was found not to affect the reliability of these measurements. This means that C (R) measured at sub-maximal velocities are representative for C (R) at race velocity for distances above 10,000 m for most runners.

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.

Training characteristics of qualifiers for the U.S. Olympic Marathon Trials

PURPOSE

To describe and compare training characteristics of the 2004 U.S. Olympic Marathon Trials qualifiers.

METHODS

All qualifiers (104 men, 151 women) received questionnaires. Ninety-three (37 men, 56 women) responded and were categorized as elite (men <2 hours 15 min, women <2 hours 40 min) or national class.

RESULTS

Men and women ran 75% and 68% of their weekly training distance, respectively, below marathon race pace. Men trained longer than women (12.2 +/- 5.3 vs 8.8 +/- 5.6 years), ran more often (8.7 +/- 2.8 vs 7.1 +/- 2.5 times/wk), and ran farther (145.3 +/- 25.6 vs 116.0 +/- 26.5 km/wk). Elite women ran more than national-class women (135.8 +/- 31.5 vs 111.3 +/- 23.3 km/wk). Distances run at specific intensities were similar between sexes. For men and women, respectively, 49% and 31% did not have a coach and 65% and 68% trained alone. Marathon performance correlated to 5-km, 10-km, and half-marathon performance and to years training, average and peak weekly distance, number of weekly runs, and number of runs > or = 32 km for women.

CONCLUSIONS

Among U.S. Olympic Marathon Trials qualifiers, there is no consensus as to how to prepare for the marathon beyond running at a pace slower than race pace. Weekly training distance seems to influence women's marathon performance more than it does men's. Because many of these athletes train alone and without a coach, further research is warranted on the reasons that these athletes train the way they do.

Training to maximize economy of motion in running gait

Recent reviews of how training affects running performance have indicated, to varying degrees, that running economy (RE) is a determinant of running performance. However, the literature suggests that the relationship between training-induced changes in biomechanics and RE is still largely unknown. While there is some evidence that high intensity interval training, plyometrics, and altitude/hypoxia training can improve economy, it remains unclear how these improvements are mediated. In addition, although it is clear from the literature that meaningful differences in RE exist among runners, the causes for the inherent differences are not clear. Consequently, suggestions are made to explore more individualized and integrated models of the determinants of performance that might better explain the interrelatedness of gait, RE, V.O2max, and peak performance.

Training to enhance the physiological determinants of long-distance running performance: can valid recommendations be given to runners and coaches based on current scientific knowledge?

This article investigates whether there is currently sufficient scientific knowledge for scientists to be able to give valid training recommendations to long-distance runners and their coaches on how to most effectively enhance the maximal oxygen uptake, lactate threshold and running economy. Relatively few training studies involving trained distance runners have been conducted, and these studies have often included methodological factors that make interpretation of the findings difficult. For example, the basis of most of the studies was to include one or more specific bouts of training in addition to the runners' 'normal training', which was typically not described or only briefly described. The training status of the runners (e.g. off-season) during the study period was also typically not described. This inability to compare the runners' training before and during the training intervention period is probably the main factor that hinders the interpretation of previous training studies. Arguably, the second greatest limitation is that only a few of the studies included more than one experimental group. Consequently, there is no comparison to allow the evaluation of the relative efficacy of the particular training intervention. Other factors include not controlling the runners' training load during the study period, and employing small sample sizes that result in low statistical power. Much of the current knowledge relating to chronic adaptive responses to physical training has come from studies using sedentary individuals; however, directly applying this knowledge to formulate training recommendations for runners is unlikely to be valid. Therefore, it would be difficult to argue against the view that there is insufficient direct scientific evidence to formulate training recommendations based on the limited research. Although direct scientific evidence is limited, we believe that scientists can still formulate worthwhile training recommendations by integrating the information derived from training studies with other scientific knowledge. This knowledge includes the acute physiological responses in the various exercise domains, the structures and processes that limit the physiological determinants of long-distance running performance, and the adaptations associated with their enhancement. In the future, molecular biology may make an increasing contribution in identifying effective training methods, by identifying the genes that contribute to the variation in maximal oxygen uptake, the lactate threshold and running economy, as well as the biochemical and mechanical signals that induce these genes. Scientists should be cautious when giving training recommendations to runners and coaches based on the limited available scientific knowledge. This limited knowledge highlights that characterising the most effective training methods for long-distance runners is still a fruitful area for future research.

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.

Effects of extra load position on energy expenditure in treadmill running

The present study was designed to investigate how much running economy would be affected by changing the placement of extra load on running subjects. Twenty-four volunteer college students, 18 males and 6 females between 19 and 25 years ran on a treadmill at three different speeds (6, 8, and 10 km h(-1)). Energy expenditure was measured in O(2 )l min(-1). Subjects were tested under three experimental conditions, presented in random order; a normal (baseline) condition, and two different conditions in which the subjects had to carry extra load. The extra load added 10% to the subjects' body mass, and was placed symmetrically on the subjects' shoulders or around their waists. Loading of the subjects affected running economy negatively in both conditions but more so for the shoulder condition. It is argued that the difference between the conditions is due to the fact that the subjects' balance control deteriorated when their centre of gravity was elevated by adding extra load on their shoulders.

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.

No Effect of 5% Hypohydration on Running Economy of Competitive Runners at 23°C

PURPOSE

Although running economy (RE) is recognized as an integral component of successful endurance performance and is affected by numerous factors, little is known about the influence of body water loss on RE. This investigation examined the effects of hypohydration (HY) on RE and associated physiological responses.

METHODS

Ten highly trained collegiate distance runners (mean +/- SD; age, 20 +/- 3 yr; height, 178.5 +/- 6.3 cm; body mass, 66.7 +/- 5.4 kg; VO2max, 66.5 +/- 4.1 mL x kg(-1) x min(-1)) participated in four experiments on separate days, twice in a euhydrated (EU) and twice in a HY state (-5.5 and -5.7% body mass loss achieved during 24 h). At each hydration level, subjects performed one 10-min treadmill run per day (23 degrees C environment), at either 70% VO2max (EU 70% or HY 70%) or 85% VO2max (EU 85% or HY 85%) in a randomized, repeated-measures design. Cardiopulmonary, metabolic, thermal, hormonal, and perceptual variables were measured.

RESULTS

No between-treatment differences existed for RE (EU 70%, 46.3 +/- 3.2; HY 70%, 47.2 +/- 3.8; EU 85%, 58.6 +/- 2.8; HY 85%, 58.9 +/- 4.1 mL x kg(-1) x min(-1)), postexercise plasma lactate concentration (EU 70%, 1.9 +/- 0.6; HY 70%, 1.8 +/- 0.6; EU 85%, 6.5 +/- 3.5; HY 85%, 6.4 +/- 3.5 mmol x L(-1)), or rating of perceived exertion. HY resulted in a greater (P < 0.05 to 0.001) heart rate (HR), rectal temperature, and plasma norepinephrine concentration (NE), concurrent with reduced cardiac output, stroke volume, and respiratory exchange ratio.

CONCLUSION

HY did not alter the RE or lactate accumulation of endurance athletes during 10 min of exercise at 70 and 85% VO2max. These findings indicate that HY had no effect on RE, but that it increased physiological strain in a 23 degrees C environment.

Estimation of maximal oxygen uptake by bioelectrical impedance analysis

Previous non-exercise models for the prediction of maximal oxygen uptake VO(2max) have failed to accurately discriminate cardiorespiratory fitness within large cohorts. The aim of the present study was to evaluate the feasibility of a completely indirect method for predicting VO(2max) that was based on bioelectrical impedance analysis (BIA) in 66 young, healthy fit men and women. Multiple, stepwise regression analysis was used to determine the usefulness of BIA and additional covariates to estimate VO(2max) (ml min(-1)). BIA was highly correlated to VO(2max) (r = 0.914; P < 0.001) and entered the regression equation first. The inclusion of gender and a physical activity rating further improved the model which accounted for 88% of the variance in VO(2max) and resulted in a relative standard error of the estimate (SEE) of 7.2%. Substantial agreement between the methods was confirmed by the fact that nearly all the differences were within +/-2 SD. Furthermore, in contrast to previously published non-exercise models, no trend of a reduction in prediction accuracy with increasing VO(2max) values was apparent. It was concluded that a non-exercise model based on BIA might be a rapid and useful technique to estimate VO(2max), when a direct test does not seem feasible. However, though the present results are useful to determine the viability of the method, further refinement of the BIA approach and its validation in a large, diverse population is needed before it can be applied to the clinical and epidemiological settings.

Time spent at a high percentage of VO2max for short intermittent runs: active versus passive recovery

The purpose of this study was to compare the effects of recovery type (active vs. passive) on the time spent at VO(2)max and above 90 % of VO(2)max during short intermittent runs (15 s) at 120 % of maximal aerobic speed. Twelve male subjects performed a graded test and intermittent runs (15 s) alternated with 15 s of active recovery (50 % of maximal aerobic speed) or with 15 s of passive recovery to exhaustion. The time to exhaustion during the intermittent runs with active recovery (445 +/- 79 s) was significantly shorter (p < 0.001) compared with passive recovery (745 +/- 171 s). No significant difference was found between time spent at VO(2)max and above 90 % of VO(2)max for intermittent runs alternated with active recovery (180 +/- 121 s and 282 +/- 117 s, respectively ) and intermittent runs alternated with passive recovery (191 +/- 135 s and 317 +/- 132 s, respectively ). The times spent at VO(2)max (p < 0.05) and above 90 % of VO(2)max (p < 0.001), expressed in percentage of time to exhaustion, were significantly longer for intermittent runs alternated with active recovery (41 +/- 27 % and 64 +/- 24 %, respectively) than with passive recovery (25 +/- 16 % and 43 +/- 16%, respectively). In conclusion, the present study has shown that the time to exhaustion during repeated high-intensity exercise was significantly greater for passive compared with active recovery, despite no difference in absolute time spent at a high percentage of VO(2)max. However, the time spent at a high percentage of VO(2)max, expressed as a percentage of time to exhaustion, was significantly higher for active compared with passive recovery.