The energetics of middle-distance running

Comparative Effects of Advanced Footwear Technology in Track Spikes and Road-Racing Shoes on Running Economy

PURPOSE

Determine the effects of advanced footwear technology (AFT) in track spikes and road-racing shoes on running economy (RE).

METHODS

Four racing shoes (3 AFT and 1 control) and 3 track spikes (2 AFT and 1 control) were tested in 9 male distance runners on 2 visits. Shoes were tested in a random sequence over 5-minute trials on visit 1 (7 trials at 16 km·h-1; 5-min rest between trials) and in the reverse/mirrored order on visit 2. Metabolic data were collected and averaged across visits.

RESULTS

There were significant differences across footwear conditions for oxygen consumption (F = 13.046; P < .001) and energy expenditure (F = 14.710; P < .001). Oxygen consumption (in milliliters per kilogram per minute) in both the first AFT spike (49.1 [1.7]; P < .001; dz = 2.1) and the other AFT spike (49.3 [1.7]; P < .001; dz = 1.7) was significantly lower than the control spike (50.2 [1.6]), which represented a 2.1% (1.0%) and 1.8% (1.0%) improvement in RE, respectively, for the AFT spikes. When comparing the subjects' most economic shoe by oxygen consumption (49.0 [1.5]) against their most economic spike (49.0 [1.8]), there were no statistical differences (P = .82). Similar statistical conclusions were made when comparing energy expenditure (in watts per kilogram).

CONCLUSIONS

AFT track spikes improved RE ∼2% relative to a traditional spike. Despite their heavier mass, AFT shoes resulted in similar RE as AFT spikes. This could make the AFT shoe an attractive option for longer track races, particularly in National Collegiate Athletic Association and high school athletics, where there are no stack-height rules.

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).

Acute pre-exercise hydrogen rich water intake does not improve running performance at maximal aerobic speed in trained track and field runners: A randomized, double-blind, placebo-controlled crossover study

PURPOSE

This study investigated the effects of acute, pre-exercise, hydrogen rich water (HRW) ingestion on running time to exhaustion at maximal aerobic speed in trained track and field runners.

METHODS

Twenty-four, male runners aged 17.5 ± 1.8 years, with body mass index = 21.0 ± 1.3 kg⋅m-2, and maximal oxygen uptake = 55.0 ± 4.6 ml⋅kg-1⋅min-1 (mean ± standard deviation) participated in this randomized, double-blind, placebo-controlled crossover study. All runners ingested 1260 ml of HRW which was divided into four doses and taken at 120 min (420 ml), 60 min (420 ml), 30 min (210 ml), and 10 min (210 ml) prior to exercise. The running protocol consisted of three phases: warm-up performed at 10 km⋅h-1 for 3 min, followed by a transition phase performed at an individually determined speed (10 km⋅h-1 + maximal aerobic speed)/2 for 1 min, and finally the third phase performed at individual maximal aerobic speed until exhaustion. Time to exhaustion, cardiorespiratory variables, and post-exercise blood lactate concentration were measured.

RESULTS

When running to exhaustion at maximal aerobic speed, compared with placebo, HRW had no significant effects on the following variables: time to exhaustion (217 ± 49 and 227 ± 53 s, p = 0.20), post-exercise blood lactate concentration (9.9 ± 2.2 and 10.1 ± 2.0 mmol⋅L-1, p = 0.42), maximal heart rate (186 ± 9 and 186 ± 9 beats⋅min-1, p = 0.80), and oxygen uptake (53.1 ± 4.5 and 52.2 ± 4.7 ml⋅kg-1⋅min-1, p = 0.33). No variable assessed as a candidate moderator was significantly correlated with time to exhaustion (Spearman's correlation coefficients ranged from -0.28 to 0.30, all p ≥ 0.16).

CONCLUSIONS

Pre-exercise administration of 1260 ml of HRW showed no ergogenic effect on running performance to exhaustion at maximal aerobic speed in trained track and field runners.

Time limit and V̇O2 kinetics at maximal aerobic velocity: Continuous vs. intermittent swimming trials

The time sustained during exercise with oxygen uptake (V̇O₂) reaching maximal rates (V̇O_2peak) or near peak responses (i.e., above second ventilatory threshold [t@VT₂) or 90% V̇O_2peak (t@90%V̇O_2peak)] is recognized as the training pace required to enhance aerobic power and exercise tolerance in the severe domain (time-limit, t_Lim). This study compared physiological and performance indexes during continuous and intermittent trials at maximal aerobic velocity (MAV) to analyze each exercise schedule, supporting their roles in conditioning planning. Twenty-two well-trained swimmers completed a discontinuous incremental step-test for V̇O_2peak, VT₂, and MAV assessments. Two other tests were performed in randomized order, to compare continuous (CT) vs. intermittent trials (IT₁₀₀) at MAV until exhaustion, to determine peak oxygen uptake (Peak-V̇O₂) and V̇O₂ kinetics (V̇O₂K). Distance and time variables were registered to determine the t_Lim, t@VT₂, and t@90%V̇O_2peak tests. Blood lactate concentration ([La⁻]) was analyzed, and rate of perceived exertion (RPE) was recorded. The tests were conducted using a breath-by-breath apparatus connected to a snorkel for pulmonary gas sampling, with pacing controlled by an underwater visual pacer. V̇O_2peak (55.2 ± 5.6 ml·kg·min⁻¹) was only reached in CT (100.7 ± 3.1 %V̇O_2peak). In addition, high V̇O₂ values were reached at IT₁₀₀ (96.4 ± 4.2 %V̇O_2peak). V̇O_2peak was highly correlated with Peak-V̇O₂ during CT (r = 0.95, p < 0.01) and IT₁₀₀ (r = 0.91, p < 0.01). Compared with CT, the IT₁₀₀ presented significantly higher values for t_Lim (1,013.6 ± 496.6 vs. 256.2 ± 60.3 s), distance (1,277.3 ± 638.1 vs. 315.9 ± 63.3 m), t@VT₂ (448.1 ± 211.1 vs. 144.1 ± 78.8 s), and t@90%V̇O_2peak (321.9 ± 208.7 vs. 127.5 ± 77.1 s). V̇O₂K time constants (IT₁₀₀: 25.9 ± 9.4 vs. CT: 26.5 ± 7.5 s) were correlated between tests (r = 0.76, p < 0.01). Between CT and IT₁₀₀, t_Lim were not related, and RPE (8.9 ± 0.9 vs. 9.4 ± 0.8) and [La⁻] (7.8 ± 2.7 vs. 7.8 ± 2.8 mmol·l⁻¹) did not differ between tests. MAV is suitable for planning swimming intensities requiring V̇O_2peak rates, whatever the exercise schedule (continuous or intermittent). Therefore, the results suggest IT₁₀₀ as a preferable training schedule rather than the CT for aerobic capacity training since IT₁₀₀ presented a significantly higher t_Lim, t@VT₂, and t@90%V̇O_2peak (∼757, ∼304, and ∼194 s more, respectively), without differing regards to [La⁻] and RPE. The V̇O₂K seemed not to influence t_Lim and times spent near V̇O_2peak in both workout modes.

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 Running Spatiotemporal Kinematics and Muscle Performance in Well-Trained Youth Female Athletes. A Cross-Sectional Study

The purpose of this cross-sectional study was to analyse the relationship of neuromuscular performance and spatiotemporal parameters in 18 adolescent distance athletes (age, 15.5 ± 1.1 years). Using the OptoGait system, the power, rhythm, reactive strength index, jump flying time, and jump height of the squat jump, countermovement jump, and eight maximal hoppings test (HT_8max) and the contact time (CT), flying time (FT), step frequency, stride angle, and step length of running at different speeds were measured. Maturity offset was determined based on anthropometric variables. Analysis of variance (ANOVA) of repeated measurements showed a reduction in CT (p < 0.000) and an increase in step frequency, step length, and stride angle (p < 0.001), as the velocity increased. The HT_8max test showed significant correlations with very large effect sizes between neuromuscular performance variables (reactive strength index, power, jump flying time, jump height, and rhythm) and both step frequency and step length. Multiple linear regression found this relationship after adjusting spatiotemporal parameters with neuromuscular performance variables. Some variables of neuromuscular performance, mainly in reactive tests, were the predictors of spatiotemporal parameters (CT, FT, stride angle, and VO). Rhythm and jump flying time in the HT_8max test and power in the countermovement jump test are parameters that can predict variables associated with running biomechanics, such as VO, CT, FT, and stride angle.

Set distance time trials for predicting maximal aerobic speed in female Australian Rules Footballers

OBJECTIVES

Maximal aerobic speed (MAS) may be predicted from 2.0km time trial (TT) running speed in male Australian Rules football (AF) players. Given the between-sex differences in physiological variables precursory to endurance performance, and the impact of this on MAS distance limit, this study determined running speed across various TT distances best approximating MAS in female AF players.

METHOD

33 female AF players completed assessments of MAS and TT performance separated by at least 48h. In a randomised order, half of the athletes completed TT distances of 1.2, 1.6 and 2.0km, and the other half completed distances of 1.4, 1.8 and 2.2km. Bias, limits of agreement (LOA) and linear mixed modelling determined agreement between TT-derived running speed and MAS.

RESULTS

Average speed for all TT distances were different to MAS (bias≥0.59±0.45km·h^-1; p≤0.015) with the exception of the 1.4km TT (bias=-0.12±0.26km·h^-1; p=0.34). LOA was narrowest for the 1.4km TT (±0.76km·h^-1; ±6.1%) compared to other TT distances (±0.82-1.67km·h^-1; ±6.7-12.9%). A significant linear association between bias and TT distance (r=-0.73; p<0.001) indicated TT speed would be equal to MAS when a 1.4-1.5km TT was completed, and that MAS may be predicted from any distance between 1.2 and 2.2km.

CONCLUSIONS

MAS was best approximated by a 1.4-1.5km TT in female AF players, but may be predicted from TT speed for any distance between 1.2 and 2.2km. TT-derived MAS provides a time and resource efficient method for the quantification of aerobic fitness and prescription of future training intensities.

Oral taurine improves critical power and severe-intensity exercise tolerance

This study investigated the effects of acute oral taurine ingestion on: (1) the power-time relationship using the 3-min all-out test (3MAOT); (2) time to exhaustion (TTE) 5% > critical power (CP) and (3) the estimated time to complete (T_lim) a range of fixed target intensities. Twelve males completed a baseline 3MAOT test on a cycle ergometer. Following this, a double-blind, randomised cross-over design was followed, where participants were allocated to one of four conditions, separated by 72 h: TTE + taurine; TTE + placebo; 3MAOT + taurine; 3MAOT + placebo. Taurine was provided at 50 mg kg^-1, whilst the placebo was 3 mg kg^-1 maltodextrin. CP was higher (P < 0.05) in taurine (212 ± 36 W) than baseline (197 ± 40 W) and placebo (193 ± 35 W). Work end power was not affected by supplement (P > 0.05), yet TTE 5% > CP increased (P < 0.05) by 1.7 min after taurine (17.7 min) compared to placebo (16.0 min) and there were higher (P < 0.001) estimated T_lim across all work targets. Acute supplementation of 50 mg kg^-1 of taurine improved CP and estimated performance at a range of severe work intensities. Oral taurine can be taken prior to exercise to enhance endurance performance.

Kinematic alterations after two high-intensity intermittent training protocols in endurance runners

PURPOSE

This study aimed to evaluate running kinematic characteristics during the early and late stages of 2 high-intensity intermittent training (HIIT) protocols with similar external load but different average running pace, as well as to compare the fatigue-induced changes during both HIIT protocols at a kinematic level.

METHODS

Eighteen endurance runners were tested on a track on 2 occasions: 10 runs of 400 m with 90-120 s recovery between running bouts (10 × 400 m), and 40 runs of 100 m with 25-30 s recovery between running bouts (40 × 100 m). Heart rate was monitored during both protocols; blood lactate accumulation and rate of perceived exertion were recorded after both exercises. A high-speed camera was used to measure sagittal-plane kinematics at the first and last runs during both HIIT protocols. The dependent variables were spatial-temporal parameters (step length and contact and flight time), joint angles during support (relative angles of the hip, knee, and ankle), and foot strike pattern.

RESULTS

High levels of exhaustion were reached by the athletes during both workouts (blood lactate accumulation >12 mmol/L, rate of perceived exertion >15; peak heart rate (HR_peak) > 176 bpm). A within-protocol paired t test (first vs. last run) revealed no significant changes (p ≥ 0.05) in kinematic variables during any of the HIIT sessions. A between-protocol comparison with the first run of each protocol revealed the effect of running speed on kinematics: +2.44 km/h during the 40 × 100 m: shorter contact and flight time (p  ≤  0.01) and longer step length (p = 0.001); greater hip flexion (p = 0.031) and ankle extension (p = 0.001) at initial contact; smaller knee and ankle flexion (p < 0.001) at midstance; and greater hip extension at toe-off (p < 0.001).

CONCLUSION

HIIT sessions including runs for 15-90 s and performed at intensity above the velocity associated with maximal oxygen uptake did not consistently perturb the running kinematics of trained endurance runners.

Oxygen uptake and respiratory exchange ratio relative to the lactate threshold running in well-trained distance runners

BACKGROUND

This study compared oxygen uptake (V̇O2) and the respiratory exchange ratio (RER) between well-trained distance runners (DRs) and recreational runners (RRs) below, at, and above the lactate threshold (LT) during a four-minute run and clarified whether these variables reached steady state in DRs.

METHODS

Ten male well-trained DRs (maximal oxygen uptake [V̇O2max], 66.8±5.9 mL/kg/min; LT, 80.0±4.4% V̇O2max) and nine male RRs (V̇O2max, 53.9±3.7 mL/kg/min; LT, 76.6±8.0% V̇O2max) participated in this study. They performed four-minute runs at 70%, 80%, and 90% V̇O2max on a treadmill.

RESULTS

The results illustrated that V̇O2 was higher in the fourth minute than in the third minute in RRs at 80% and 90% V̇O2max (Cohen's d=0.25 and 0.26, respectively), whereas, V̇O2 did not differ between the third and fourth minute in DRs at any intensity (Cohen's d=0.08, 0.03, and 0.04, respectively). The RER at each intensity differed between the third and fourth minutes in RRs (Cohen's d=0.25, 0.21, and 0.41, respectively); similarly, RER was only different between the third and fourth minutes at 90%V̇O2max (Cohen's d=0.39) in DRs.

CONCLUSIONS

These results indicate that the slow component of V̇O2 is not observed in runners with good aerobic capacity even at running intensity exceeding the LT, whereas the RER does not reach steady state at this intensity.

Effects of Strength Training on the Physiological Determinants of Middle- and Long-Distance Running Performance: A Systematic Review

Background

Middle- and long-distance running performance is constrained by several important aerobic and anaerobic parameters. The efficacy of strength training (ST) for distance runners has received considerable attention in the literature. However, to date, the results of these studies have not been fully synthesized in a review on the topic.

Objectives

This systematic review aimed to provide a comprehensive critical commentary on the current literature that has examined the effects of ST modalities on the physiological determinants and performance of middle- and long-distance runners, and offer recommendations for best practice.

Methods

Electronic databases were searched using a variety of key words relating to ST exercise and distance running. This search was supplemented with citation tracking. To be eligible for inclusion, a study was required to meet the following criteria: participants were middle- or long-distance runners with ≥ 6 months experience, a ST intervention (heavy resistance training, explosive resistance training, or plyometric training) lasting ≥ 4 weeks was applied, a running only control group was used, data on one or more physiological variables was reported. Two independent assessors deemed that 24 studies fully met the criteria for inclusion. Methodological rigor was assessed for each study using the PEDro scale.

Results

PEDro scores revealed internal validity of 4, 5, or 6 for the studies reviewed. Running economy (RE) was measured in 20 of the studies and generally showed improvements (2–8%) compared to a control group, although this was not always the case. Time trial (TT) performance (1.5–10 km) and anaerobic speed qualities also tended to improve following ST. Other parameters [maximal oxygen uptake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{{2{ \hbox{max} }}}$$\end{document}V˙O2max), velocity at \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{{2{ \hbox{max} }}}$$\end{document}V˙O2max, blood lactate, body composition] were typically unaffected by ST.

Conclusion

Whilst there was good evidence that ST improves RE, TT, and sprint performance, this was not a consistent finding across all works that were reviewed. Several important methodological differences and limitations are highlighted, which may explain the discrepancies in findings and should be considered in future investigations in this area. Importantly for the distance runner, measures relating to body composition are not negatively impacted by a ST intervention. The addition of two to three ST sessions per week, which include a variety of ST modalities are likely to provide benefits to the performance of middle- and long-distance runners.

New Records in Human Power

Maximal aerobic and anaerobic power are crucial performance determinants in most sport disciplines. Numerous studies have published power data from elite athletes over the years, particularly in runners, cyclists, rowers, and cross-country (XC) skiers. This invited review defines the current "world records" in human upper limits of aerobic and anaerobic power. Currently, [Formula: see text]max values of ∼7.5 and 7.0 L·min^-1 in male XC skiers and rowers, respectively, and/or ∼90 mL·kg^-1·min^-1 in XC skiers, cyclists, and runners can be described as upper human limits for aerobic power. Corresponding values for women are slightly below 5.0 L·min^-1 in rowers and XC skiers and ∼80 mL·kg^-1·min^-1 in XC skiers and runners. Extremely powerful male athletes may reach ∼85 W·kg^-1 in countermovement jump (peak vertical power) and ∼36 W·kg^-1 in sprint running (peak horizontal power), cycling (instantaneous power during force-velocity testing from a standing position), and rowing (instantaneous power). Similarly, their female counterparts may reach ∼70 W·kg^-1 in countermovement jump and ∼30 W·kg^-1 in sprint running, cycling, and rowing. The presented values can serve as reference values for practitioners and scientists working with elite athletes. However, several methodological considerations should be taken into account when interpreting the results. For example, calibrated apparatus and strict procedures are required to ensure high measurement validity and reliability, and the sampling rate for anaerobic power assessments must be strictly predetermined and carefully measured. Doping is also a potential confounding factor when interpreting the human upper limits of aerobic and anaerobic power.

Physiological and Biomechanical Mechanisms of Distance Specific Human Running Performance

SYNOPSIS

Running events range from 60-m sprints to ultra-marathons covering 100 miles or more, which presents an interesting diversity in terms of the parameters for successful performance. Here, we review the physiological and biomechanical variations underlying elite human running performance in sprint to ultramarathon distances. Maximal running speeds observed in sprint disciplines are achieved by high vertical ground reaction forces applied over short contact times. To create this high force output, sprint events rely heavily on anaerobic metabolism, as well as a high number and large cross-sectional area of type II fibers in the leg muscles. Middle distance running performance is characterized by intermediates of biomechanical and physiological parameters, with the possibility of unique combinations of each leading to high-level performance. The relatively fast velocities in mid-distance events require a high mechanical power output, though ground reaction forces are less than in sprinting. Elite mid-distance runners exhibit local muscle adaptations that, along with a large anaerobic capacity, provide the ability to generate a high power output. Aerobic capacity starts to become an important aspect of performance in middle distance events, especially as distance increases. In distance running events, V˙O2max is an important determinant of performance, but is relatively homogeneous in elite runners. V˙O2 and velocity at lactate threshold have been shown to be superior predictors of elite distance running performance. Ultramarathons are relatively new running events, as such, less is known about physiological and biomechanical parameters that underlie ultra-marathon performance. However, it is clear that performance in these events is related to aerobic capacity, fuel utilization, and fatigue resistance.

Prediction of performance by heart rate-derived parameters in recreational runners

We investigated whether heart rate (HR)-derived parameters are accurate performance predictors in endurance recreational runners. One hundred thirty recreational athletes completed an incremental running test (4´running + 1´rest). After each stage, we recorded HR, % of maximum HR (%HRmax), and blood lactate. We also assessed HR after each recovery period, and calculated lactate and HR recovery thresholds and HR deflection point. We tested these parameters for associations with running performance, as measured by peak treadmill speed (PTS) and personal best International Association of Athletics Federations (IAAF) score. The %HRmax at 14.5 km·h^-1 correlated with PTS (r = -0.92), and IAAF score (rho = -0.80). The magnitudes of the correlations of lactate-related parameters with PTS (|r| = 0.84 to 0.86) or IAAF score (|rho| = 0.70 to 0.77) in absolute values were slightly lower. The correlations detected between other HR-derived parameters and running performance were weaker (|r or rho| = 0.24 to 0.70). Regression models identified %HRmax at 14.5 km·h^-1 as the strongest predictor of both PTS (β = -0.72) and IAAF score (β = -0.72). Consequently, tests based on %HRmax may provide a non-invasive and inexpensive alternate method for predicting the performance of these athletes.

Different Training Modalities Improve Energy Cost and Performance in Master Runners

Purpose: The aim of this study was to compare the effects of continuous moderate-intensity and discontinuous high-intensity training on running performance in master runners.

Methods: Thirty-four male master runners (47.2 ± 7.4 years) were assigned to three different groups: continuous moderate-intensity training (CMIT), discontinuous high-intensity training (DHIT), and control group (CON). CMIT and DHIT performed 8-week of supervised training (3 session·wk⁻¹; ~35 km·wk⁻¹) while CON maintained their normal training habits (3–4 session·wk⁻¹; ~50 km·wk⁻¹). Peak oxygen consumption (V˙O_2peak) and peak running speed (v_peak) during incremental treadmill exercise, gas exchange threshold (GET), speed at GET, energy cost of running (Cr), and 5-km performance were evaluated before and after training.

Results: Following the training period, both CMIT and DHIT significantly reduced Cr (−4.4 and −4.9%, respectively, P < 0.05), increased speed at GET (3.4 and 5.7%, P < 0.05) and improved 5-km time-trial performance (3.1 and 2.2%, P < 0.05) whereas no differences were found for V˙O_2peak and GET (as %V˙O_2peak). After training, v_peak improved only for DHIT (6%, P < 0.05). No differences were found in any variable for CON.

Conclusions: This study indicates that both CMIT and DHIT may positively affect running performance in middle-aged master runners. This improvement was achieved despite a significant reduction of the amount of weekly training volume.

Does Metabolic Rate Increase Linearly with Running Speed in all Distance Runners?

Running economy (oxygen uptake or metabolic rate for running at a submaximal speed) is one of the key determinants of distance running performance. Previous studies reported linear relationships between oxygen uptake or metabolic rate and speed, and an invariant cost of transport across speed. We quantified oxygen uptake, metabolic rate, and cost of transport in 10 average and 10 sub-elite runners. We increased treadmill speed by 0.45 m · s -1 from 1.78 m · s -1 (day 1) and 2.01 m · s -1 (day 2) during each subsequent 4-min stage until reaching a speed that elicited a rating of perceived exertion of 15. Average runners' oxygen uptake and metabolic rate vs. speed relationships were best described by linear fits. In contrast, the sub-elite runners' relationships were best described by increasing curvilinear fits. For the sub-elites, oxygen cost of transport and energy cost of transport increased by 12.8% and 9.6%, respectively, from 3.58 to 5.14 m · s -1 . Our results indicate that it is not possible to accurately predict metabolic rates at race pace for sub-elite competitive runners from data collected at moderate submaximal running speeds (2.68-3.58 m · s -1 ). To do so, metabolic rate should be measured at speeds that approach competitive race pace and curvilinear fits should be used for extrapolation to race pace.

Effect of Jump Interval Training on Kinematics of the Lower Limbs and Running Economy

Ache-Dias, J, Pupo, JD, Dellagrana, RA, Teixeira, AS, Mochizuki, L, and Moro, ARP. Effect of jump interval training on kinematics of the lower limbs and running economy. J Strength Cond Res 32(2): 416-422, 2017-This study analyzed the effects of the addition of jump interval training (JIT) to continuous endurance training (40-minute running at 70% of peak aerobic velocity, 3 times per week for 4 weeks) on kinematic variables and running economy (RE) during submaximal constant-load running. Eighteen recreational runners, randomized into control group (CG) or experimental group (EG) performed the endurance training. In addition, the EG performed the JIT twice per week, which consisted of 4-6 bouts of continuous vertical jumping (30 seconds) with 5-minute intervals. The oxygen consumption (V[Combining Dot Above]O2) during the submaximal test (performed at 9 km·h) was similar before (EG: 38.48 ± 2.75 ml·kg·min; CG: 36.45 ± 2.70 ml·kg·min) and after training (EG: 37.42 ± 2.54 ml·kg·min; CG: 35.81 ± 3.10 ml·kg·min). No effect of training, group, or interaction (p > 0.05) was found for RE. There was no interaction or group effect for the kinematic variables (p > 0.05). Most of the kinematic variables had a training effect for both groups (support time [p ≤ 0.05]; step rate [SR; p ≤ 0.05]; and step length [SL; p ≤ 0.05]). In addition, according to the practical significance analysis (percentage chances of a better/trivial/worse effect), important effects in leg stiffness (73/25/2), vertical stiffness (73/25/2), SR (71/27/2), and SL (64/33/3) were found for the EG. No significant relationship between RE and stiffness were found for EG and CG. In conclusion, the results suggest that JIT induces important changes in the kinematics of the lower limbs of recreational runners, but the changes do not affect RE.

A High Intensity Interval Training (HIIT)-Based Running Plan Improves Athletic Performance by Improving Muscle Power

García-Pinillos, F, Cámara-Pérez, JC, Soto-Hermoso, VM, and Latorre-Román, PÁ. A High Intensity Interval Training (HIIT)-based running plan improves athletic performance by improving muscle power. J Strength Cond Res 31(1): 146-153, 2017-This study aimed to examine the effect of a 5-week high-intensity intermittent training (HIIT)-based running plan on athletic performance and to compare the physiological and neuromuscular responses during a sprint-distance triathlon before and after the HIIT period. Thirteen triathletes were matched into 2 groups: the experimental group (EG) and the control group (CG). The CG was asked to maintain their normal training routines, whereas the EG maintained only their swimming and cycling routines and modified their running routine. Participants completed a sprint-distance triathlon before (pretest) and after (posttest) the intervention period. In both pretest and posttest, the participants performed 4 jumping tests: before the race (baseline), postswim, postcycling, and postrun. Additionally, heart rate was monitored (HRmean), whereas rate of perceived exertion (RPE) and blood lactate accumulation (BLa) were registered after the race. No significant differences (p ≥ 0.05) between groups were found before HIIT intervention (at pretest). Significant group-by-training interactions were found in vertical jumping ability and athletic performance: the EG improved jumping performance (∼6-9%, p ≤ 0.05, effect size (ES) > 0.7), swimming performance (p = 0.013, ES = 0.438), and running time (p = 0.001, ES = 0.667) during the competition, whereas the CG remained unchanged (p ≥ 0.05, ES < 0.4). No changes (p ≥ 0.05, ES < 0.4) were observed in RPE, HRmean, and BLa. A linear regression analysis showed that ΔCMJ predicted both the ΔRu_time (R = 0.559; p = 0.008) and the ΔOverall_time (R = 0.391; p = 0.048). This low-volume, HIIT-based running plan combined with the high training volumes of these triathletes in swimming and cycling improved athletic performance during a sprint-distance triathlon. This improvement may be due to improved neuromuscular characteristics that were transferred into improved muscle power and work economy.

Maximal Oxygen Uptake Is Achieved in Hypoxia but Not Normoxia during an Exhaustive Severe Intensity Run

Highly aerobically trained individuals are unable to achieve maximal oxygen uptake (V˙O2max) during exhaustive running lasting ~2 min, instead V˙O2 plateaus below V˙O2max after ~1 min. Hypoxia offers the opportunity to study the (V˙O2) response to an exhaustive run relative to a hypoxia induced reduction in V˙O2max. The aim of this study was to explore whether there is a difference in the percentage of V˙O2max achieved (during a 2 min exhaustive run) in normoxia and hypoxia. Fourteen competitive middle distance runners (normoxic V˙O2max 67.0 ± 5.2 ml.kg⁻¹.min⁻¹) completed exhaustive treadmill ramp tests and constant work rate (CWR) tests in normoxia and hypoxia (F_iO₂ 0.13). The V˙O2 data from the CWR tests were modeled using a single exponential function. End exercise normoxic CWR V˙O2 was less than normoxic V˙O2max (86 ± 6% ramp, P < 0.001). During the hypoxic CWR test, hypoxic V˙O2max was achieved (102 ± 8% ramp, P = 0.490). The phase II time constant was greater in hypoxia (12.7 ± 2.8 s) relative to normoxia (10.4 ± 2.6 s) (P = 0.029). The results demonstrate that highly aerobically trained individuals cannot achieve V˙O2max during exhaustive severe intensity treadmill running in normoxia, but can achieve the lower V˙O2max in hypoxia despite a slightly slower V˙O2 response.

On-field prediction vs monitoring of aerobic capacity markers using submaximal lactate and heart rate measures

This study aimed to validate the use of a single blood lactate concentration measurement taken following a 5-minute running bout at 10 km·h^-1 (BLC₁₀ ) and the speed associated with 90% of maximal heart rate (S₉₀ ) to predict and monitor fixed blood lactate concentration (FBLC) thresholds in athletes. Three complementary studies were undertaken. Study I: A cross-sectional study examining the associations of BLC₁₀ and S₉₀ with running speeds at FBLC of 3 (S3mM) and 4 mmol·L^-1 (S4mM) in 100 athletes. Study II: A cross-validation study assessing the predictive capacity of BLC₁₀ and S₉₀ to estimate FBLC thresholds in real practice. Study III: A longitudinal study examining whether training-induced changes in FBLC thresholds could be monitored using BLC₁₀ and S₉₀ in 80 athletes tested before and after an intensified training period. Study I: BLC₁₀ (r=-.87 to -.89) and S₉₀ (r=.73-.79) were very largely (P<.001) related to FBLC thresholds. Study II: Predictive models yielded robust correlations between estimated and measured FBLC thresholds (r=.75-.91; P<.001). The limits of agreements, however, revealed that prediction of FBLC thresholds could be biased up to 9%-15%. Study III: BLC₁₀ was very largely related to training-induced changes in FBLC thresholds (r=-.72 to -.76; P<.001). Increases in S₉₀ were associated with improvements in FBLC thresholds, but decreases in S₉₀ led to unclear changes in FBLC thresholds. This study supports the use of BLC₁₀ as a simple, low-cost, non-fatiguing, and time-efficient functional variable to monitor, but not predict, FBLC thresholds in athletes. The present results also question the use of S₉₀ to detect declines in endurance performance.

Changes in balance ability, power output, and stretch-shortening cycle utilisation after two high-intensity intermittent training protocols in endurance runners

PURPOSE

This study aimed to describe the acute effects of 2 different high-intensity intermittent trainings (HIITs) on postural control, countermovement jump (CMJ), squat jump (SJ), and stretch-shortening cycle (SSC) utilisation, and to compare the changes induced by both protocols in those variables in endurance runners.

METHODS

Eighteen recreationally trained endurance runners participated in this study and were tested on 2 occasions: 10 runs of 400 m with 90 s recovery between running bouts (10 × 400 m), and 40 runs of 100 m with 30 s recovery between runs (40 × 100 m). Heart rate was monitored during both HIITs; blood lactate accumulation and rate of perceived exertion were recorded after both protocols. Vertical jump ability (CMJ and SJ) and SSC together with postural control were also controlled during both HIITs.

RESULTS

Repeated measures analysis revealed a significant improvement in CMJ and SJ during 10 × 400 m (p < 0.05), whilst no significant changes were observed during 40 × 100 m. Indexes related to SSC did not experience significant changes during any of the protocols. As for postural control, no significant changes were observed in the 40 × 100 m protocol, whilst significant impairments were observed during the 10 × 400 m protocol (p < 0.05).

CONCLUSION

A protocol with a higher number of shorter runs (40 × 100 m) induced different changes in those neuromuscular parameters than those with fewer and longer runs (10 × 400 m). Whereas the 40 × 100 m protocol did not cause any significant changes in vertical jump ability, postural control or SSC utilisation, the 10 × 400 m protocol impaired postural control and caused improvements in vertical jumping tests.

Economical Speed and Energetically Optimal Transition Speed Evaluated by Gross and Net Oxygen Cost of Transport at Different Gradients

The oxygen cost of transport per unit distance (CoT; mL·kg^-1·km^-1) shows a U-shaped curve as a function of walking speed (v), which includes a particular walking speed minimizing the CoT, so called economical speed (ES). The CoT-v relationship in running is approximately linear. These distinctive walking and running CoT-v relationships give an intersection between U-shaped and linear CoT relationships, termed the energetically optimal transition speed (EOTS). This study investigated the effects of subtracting the standing oxygen cost for calculating the CoT and its relevant effects on the ES and EOTS at the level and gradient slopes (±5%) in eleven male trained athletes. The percent effects of subtracting the standing oxygen cost (4.8 ± 0.4 mL·kg^-1·min^-1) on the CoT were significantly greater as the walking speed was slower, but it was not significant at faster running speeds over 9.4 km·h^-1. The percent effect was significantly dependent on the gradient (downhill > level > uphill, P < 0.001). The net ES (level 4.09 ± 0.31, uphill 4.22 ± 0.37, and downhill 4.16 ± 0.44 km·h^-1) was approximately 20% slower than the gross ES (level 5.15 ± 0.18, uphill 5.27 ± 0.20, and downhill 5.37 ± 0.22 km·h^-1, P < 0.001). Both net and gross ES were not significantly dependent on the gradient. In contrast, the gross EOTS was slower than the net EOTS at the level (7.49 ± 0.32 vs. 7.63 ± 0.36 km·h^-1, P = 0.003) and downhill gradients (7.78 ± 0.33 vs. 8.01 ± 0.41 km·h^-1, P < 0.001), but not at the uphill gradient (7.55 ± 0.37 vs. 7.63 ± 0.51 km·h^-1, P = 0.080). Note that those percent differences were less than 2.9%. Given these results, a subtraction of the standing oxygen cost should be carefully considered depending on the purpose of each study.

Predicting maximal aerobic speed through set distance time-trials

PURPOSE

Knowledge of aerobic performance capacity allows for the optimisation of training programs in aerobically dominant sports. Maximal aerobic speed (MAS) is a measure of aerobic performance; however, the time and personnel demands of establishing MAS are considerable. This study aimed to determine whether time-trials (TT), which are shorter and less onerous than traditional MAS protocols, may be used to predict MAS.

METHODS

28 Australian Rules football players completed a test of MAS, followed by TTs of six different distances in random order, each separated by at least 48 h. Half of the participants completed TT distances of 1200, 1600 and 2000 m, and the others completed distances of 1400, 1800 and 2200 m.

RESULTS

Average speed for the 1200 and 1400 m TTs were greater than MAS (P < 0.01). Average speed for 1600, 1800, 2000 and 2200 m TTs were not different from MAS (P > 0.08). Average speed for all TT distances correlated with MAS (r = 0.69-0.84; P < 0.02), but there was a negative association between the difference in average TT speed and MAS with increasing TT distance (r = -0.79; P < 0.01). Average TT speed over the 2000 m distance exhibited the best agreement with MAS.

CONCLUSIONS

MAS may be predicted from the average speed during a TT for any distance between 1200 and 2200 m, with 2000 m being optimal. Performance of a TT may provide a simple alternative to traditional MAS testing.

Effect of sprint training: training once daily versus twice every second day

This study compared training adaptations between once daily (SINGLE) and twice every second day (REPEATED) sprint training, with same number of training sessions. Twenty physically active males (20.9 ± 1.3 yr) were assigned randomly to the SINGLE (n = 10) or REPEATED (n = 10) group. The SINGLE group trained once per day (5 days per week) for 4 weeks (20 sessions in total). The REPEATED group conducted two consecutive training sessions on the same day, separated by a rest period of 1 h (2-3 days per week) for 4 weeks (20 sessions in total). Each training session consisted of three consecutive 30-s maximal pedalling sets with a 10-min rest between sets. Before and after the training period, the power output during two bouts of 30-s maximal pedalling, exercise duration during submaximal pedalling and resting muscle phosphocreatine (PCr) levels were evaluated. Both groups showed significant increases in peak and mean power output during the two 30-s bouts of maximal pedalling after the training period (P < 0.05). The groups showed similar increases in VO2max after the training period (P < 0.05). The REPEATED group showed a significant increase in the onset of blood lactate accumulation (OBLA) after the training period (P < 0.05), whereas no change was observed in the SINGLE group. The time to exhaustion at 90% of VO2max and muscle PCr concentration at baseline did not change significantly in either group. Sprint training twice every second day improved OBLA during endurance exercise more than the same training once daily.

High-intensity interval training, solutions to the programming puzzle: Part I: cardiopulmonary emphasis

High-intensity interval training (HIT), in a variety of forms, is today one of the most effective means of improving cardiorespiratory and metabolic function and, in turn, the physical performance of athletes. HIT involves repeated short-to-long bouts of rather high-intensity exercise interspersed with recovery periods. For team and racquet sport players, the inclusion of sprints and all-out efforts into HIT programmes has also been shown to be an effective practice. It is believed that an optimal stimulus to elicit both maximal cardiovascular and peripheral adaptations is one where athletes spend at least several minutes per session in their 'red zone,' which generally means reaching at least 90% of their maximal oxygen uptake (VO2max). While use of HIT is not the only approach to improve physiological parameters and performance, there has been a growth in interest by the sport science community for characterizing training protocols that allow athletes to maintain long periods of time above 90% of VO2max (T@VO2max). In addition to T@VO2max, other physiological variables should also be considered to fully characterize the training stimulus when programming HIT, including cardiovascular work, anaerobic glycolytic energy contribution and acute neuromuscular load and musculoskeletal strain. Prescription for HIT consists of the manipulation of up to nine variables, which include the work interval intensity and duration, relief interval intensity and duration, exercise modality, number of repetitions, number of series, as well as the between-series recovery duration and intensity. The manipulation of any of these variables can affect the acute physiological responses to HIT. This article is Part I of a subsequent II-part review and will discuss the different aspects of HIT programming, from work/relief interval manipulation to the selection of exercise mode, using different examples of training cycles from different sports, with continued reference to T@VO2max and cardiovascular responses. Additional programming and periodization considerations will also be discussed with respect to other variables such as anaerobic glycolytic system contribution (as inferred from blood lactate accumulation), neuromuscular load and musculoskeletal strain (Part II).

Longitudinal changes in cardiac autonomic function and aerobic fitness indices in endurance runners: a case study with a high-level team

To determine the effects of preparatory phase training on aerobic parameters, resting heart rate variability (HRV) and 5-km performance of high-level endurance runners and the relationship between the percentage change (% change) of resting HRV with the % change of aerobic parameters and 5-km performance. Six runners were assessed before and after seven weeks of training. The aerobic parameters were determined in an incremental test. The HRV was assessed by a heart rate monitor. Athletes performed a 5-km running test in a track. The analysis revealed 'likely' and 'very likely' improvements for velocity associated with maximal oxygen uptake ([Formula: see text]O2max) (20.0±1.0 km·h(-1) to 21.2±0.6 km·h(-1)) and 5-km performance (18.0±0.4 km·h(-1) to 18.9±0.7 km·h(-1)), respectively, as well as 'likely' decrease in high frequency (41.4±18.5 nu to 30.4±14.3 nu), and increase in low frequency (58.5±18.5 nu to 69.6±14.3 nu) band densities. The variation in the velocity associated with [Formula: see text]O2max showed the highest correlation with 5-km performance (r=0.95). The % change in the square root of the mean sum of the squared differences between R-R intervals and standard deviation 1 were highly correlated with variation in 5-km performance (r=0.69 and 0.66). Changes in the velocity associated with [Formula: see text]O2max and vagally mediated HRV were highly associated with 5-km running performance within the investigated team. These results have important implications because these parameters can be assessed longitudinally to monitor adaptation to training.

Influence of individual energy cost on running capacity in warm, humid environments

PURPOSE

Challenging environmental conditions including heat and humidity are associated with particular risks to the health of runners and triathletes during prolonged events. The heat production of a runner is the product of its energy cost of running (C r) by its velocity. Since C r varies greatly among humans, those individuals with high C r are more exposed to heat stress in warm and humid conditions. Although risk factor awareness is crucial to the prevention of heat stroke and potential fatalities associated therewith, how C r affects the highest sustainable velocity (V) at which maximal heat loss matches heat production has not been quantified to date.

METHODS

Here, we computed in virtual runners weighting 45-75 kg, the influence of C r variability from 3.8 to 4.4 J·m(-1)·kg(-1) on V. Heat loss by radiation, convection, and conduction was assessed from known equations including body dimensions, running velocity (3.4-6.2 m·s(-1)), air temperature (T a, 10-35 °C) and relative humidity (r h, 50, 70 and 90 %).

RESULTS

We demonstrated a marked and almost linear influence of C r on V in hot and humid conditions: +0.1 J·kg(-1)·m(-1) in C r corresponded to -4 % in V. For instance, in conditions 25 °C r h 70 %, 65-kg runners with low C r could sustain a running speed of 5.7 m·s(-1) as compared to only 4.3 m·s(-1) in runners with high C r, which is huge.

CONCLUSION

We conclude that prior knowledge of individual C r in athletes exposed to somewhat warm and humid environments during prolonged running is one obvious recommendation for minimizing heat illness risk.

Índices fisiológicos associados com a performance aeróbia de corredores nas distâncias de 1,5 km, 3 km e 5 km

O objetivo do estudo foi analisar a associação entre os índices fisiológicos de potência aeróbia e capacidade aeróbia performance nas distâncias de 1,5 km, 3 km e 5 km. Nove corredores de endurance realizaram os seguintes protocolos: a) teste para determinação do VO2max, vVO2max e OBLA; b) 2-5 testes em dias alternados de 30 min com velocidade constante para determinar a vMLSS e c) determinação da performances. Foram empregadas correlação linear de Pearson ou Spearman e regressão múltipla para determinar as relações entre os índices e a performance nas corridas. Observou-se uma correlação significante somente da vVO2max com o tempo nas distâncias de 1,5 km (r = - 0,78) e 3 km (r = - 0,81). Dessa forma, pode-se sugerir a inclusão de sessões de treinamento em intensidade próxima ou superior à vVO2max na periodização semanal dos corredores. Com base nesses achados, foi possível concluir que a predição da performance por meio de índices de potência aeróbia e da capacidade aeróbia depende da distância e duração da prova.

Energetics of running in top-level marathon runners from Kenya

On ten top-level Kenyan marathon runners (KA) plus nine European controls (EC, equivalent to KA), we measured maximal oxygen consumption (VO2max) and the energy cost of running (Cr) on track during training camps at moderate altitude, to better understand the KA dominance in the marathon. At each incremental running speed, steady-state oxygen consumption (VO2) was measured by telemetric metabolic cart, and lactate by electro-enzymatic method. The speed requiring VO2 = VO2max provided the maximal aerobic velocity (νmax). The energy cost of running was calculated by dividing net VO2 by the corresponding speed. The speed at lactate threshold (ν(ΘAN)) was computed from individual Lâ(b) versus speed curves. The sustainable VO2max fraction (Fd) at ν(ΘAN) (F(ΘAN)) was computed dividing nu(ΘAN) by νmax. The Fd for the marathon (Fmar) was determined as Fmar = 0.92 F(ΘAN). Overall, VO2max (64.9 ± 5.8 vs. 63.9 ± 3.7 ml kg(-1) min(-1)), νmax (5.55 ± 0.30 vs. 5.41 ± 0.29 m s(-1)) and Cr (3.64 ± 0.28 vs. 3.63 ± 0.31 J kg(-1) m(-1)) resulted the same in KA as in EC. In both groups, Cr increased linearly with the square of speed. F(ΘAN) was 0.896 ± 0.054 in KA and 0.909 ± 0.068 in EC; Fmar was 0.825 ± 0.050 in KA and 0.836 ± 0.062 in EC (NS). Accounting for altitude, running speed predictions from present data are close to actual running performances, if F(ΘAN) instead of Fmar is taken as index of Fd. In conclusion, both KA and EC did not have a very high VO2max, but had extremely high Fd, and low Cr, equal between them. The dominance of KA over EC cannot be explained on energetic grounds.

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.

Determinants of performance in 1,500-m runners

Our aim was to investigate the relationship between physiological variables (not previously studied) and performance in elite 1,500-m runners. We assessed eight male athletes with an average personal best time of 233.3 ± 6.9 s (110% of the world record) for the 1,500-m race. Ventilatory measurements, maximal oxygen consumption VO2max maximal vastus lateralis muscle deoxygenation (∆[deoxy(Hb+Mb)])max via near-infrared spectroscopy (NIRS), and maximal velocity (V (max)) were obtained during an incremental treadmill test. During subsequent constant-speed exercise at Vmax, we determined the time to exhaustion (Tlim), end-exercise blood lactate concentration ([La]b(max)), VO2 and ∆[deoxy(Hb+Mb)] kinetics parameters. The mean VO2max, [La]b(max) and Vmax were 70.2 ± 3.9 mL kg(-1) min(-1), 12.7 ± 2.4 mmol L(-1), 21.5 ± 0.5 km h(-1), respectively. VO2 at Vmax showed a significant negative correlation with Tlim, whereas [La]b(max) was positively correlated with Tlim. Race speed was found to significantly correlate with ∆[deoxy(Hb+Mb)](max) (79% of maximal value obtained during a transient limb ischemia), ∆[deoxy(Hb+Mb)] slow component (22.9 ± 9.3% of total amplitude) and [La]b(max) at Vmax. [La]b(max) at Vmax was also significantly correlated with ∆[deoxy(Hb+Mb)] slow component, suggesting a greater release of oxygen from the hemoglobin due to the Bohr effect. We conclude that both the maximal capacity of muscle to extract O2 from the blood and the end-exercise blood lactate accumulation are important predictors of best performance in 1,500-m runners.

Effects of Ramadan intermittent fasting on middle-distance running performance in well-trained runners

OBJECTIVE

To assess whether Ramadan intermittent fasting (RIF) affects 5000-m running performance and physiological parameters classically associated with middle-distance performance.

DESIGN

Two experimental groups (Ramadan fasting, n = 9, vs control, n = 9) participated in 2 experimental sessions, one before RIF and the other at the last week of fasting.

SETTING

For each session, subjects completed 4 tests in the same order: a maximal running test, a maximal voluntary contraction (MVC) of knee extensor, 2 rectangular submaximal exercises on treadmill for 6 minutes at an intensity corresponding to the first ventilatory threshold (VT1), and a running performance test (5000 m).

PARTICIPANTS

Eighteen, well-trained, middle-distance runners.

MAIN OUTCOME MEASURES

Maximal oxygen consumption, MVC, running performance, running efficiency, submaximal VO(2) kinetics parameters (VO(2), VO(2)b, time constant τ, and amplitude A1) and anthropometric parameters were recorded or calculated.

RESULTS

At the end of Ramadan fasting, a decrease in MVC was observed (-3.2%; P < 0.00001; η, 0.80), associated with an increase in the time constant of oxygen kinetics (+51%; P < 0.00007; η, 0.72) and a decrease in performance (-5%; P < 0.0007; η, 0.51). No effect was observed on running efficiency or maximal aerobic power.

CONCLUSIONS

These results suggest that Ramadan changes in muscular performance and oxygen kinetics could affect performance during middle-distance events and need to be considered to choose training protocols during RIF.