Assessment of long-distance running performance in elite male runners using onset of blood lactate accumulation

Biomechanical, physiological and anthropometrical predictors of performance in recreational runners

Background

The maximal running speed (VMAX) determined on a graded treadmill test is well-recognized as a running performance predictor. However, few studies have assessed the variables that predict VMAX in recreationally active runners.

Methods

We used a mathematical procedure combining Fick's law and metabolic cost analysis to verify the relation between (1) VMAX versus anthropometric and physiological determinants of running performance and, (2) theoretical metabolic cost versus running biomechanical parameters. Linear multiple regression and bivariate correlation were applied. We aimed to verify the biomechanical, physiological, and anthropometrical determinants of VMAX in recreationally active runners. Fifteen recreationally active runners participated in this observational study. A Conconi and a stead-steady running test were applied using a heart rate monitor and a simple video camera to register the physiological and mechanical variables, respectively.

Results

Statistical analysis revealed that the speed at the second ventilatory threshold, theoretical metabolic cost, and fat-mass percentage confidently estimated the individual running performance as follows: VMAX = 58.632 + (-0.183 * fat percentage) + (-0.507 * heart rate percentage at second ventilatory threshold) + (7.959 * theoretical metabolic cost) (R2 = 0.62, p = 0.011, RMSE = 1.50 km.h-1). Likewise, the theoretical metabolic cost was significantly explained (R2 = 0.91, p = 0.004, RMSE = 0.013 a.u.) by the running spatiotemporal and elastic-related parameters (contact and aerial times, stride length and frequency, and vertical oscillation) as follows: theoretical metabolic cost = 10.421 + (4.282 * contact time) + (-3.795 * aerial time) + (-2.422 * stride length) + (-1.711 * stride frequency) + (0.107 * vertical oscillation).

Conclusion

Critical determinants of elastic mechanism, such as maximal vertical force and vertical and leg stiffness were unrelated to the metabolic economy. VMAX, a valuable marker of running performance, and its physiological and biomechanical determinants can be effectively evaluated using a heart rate monitor, treadmill, and a digital camera, which can be used in the design of training programs to recreationally active runners.

Exercise Stress Testing in Athletes

Exercise stress testing (EST) is indicated for diagnostic and prognostic purposes in the general population. In athletes, stress tests can also be useful to inform the risk of high-intensity training and competition, to assess athletic conditioning, and to refine training regimens. Many specific indications for EST are unique to athletes. Treadmill and cycle ergometer protocols each have their strengths and disadvantages; extensive protocol customization may be necessary to answer the clinical question at hand. A comprehensive understanding of the available tools for exercise testing, their strengths, and their limitations is crucial to providing cardiovascular care to athletic individuals.

Effects of jump training on physical fitness and athletic performance in endurance runners: A meta-analysis

This systematic review and meta-analysis aimed to assess the effects of jump training (JT) on measures of physical fitness and athletic performances in endurance runners. Controlled studies which involved healthy endurance runners, of any age and sex, were considered. A random-effects model was used to calculate effect sizes (ES; Hedge's g). Means and standard deviations of outcomes were converted to ES with alongside 95% confidence intervals (95%CI). Twenty-one moderate-to-high quality studies were included in the meta-analysis, and these included 511 participants. The main analyses revealed a significant moderate improvement in time-trial performance (i.e. distances between 2.0 and 5.0 km; ES = 0.88), without enhancements in maximal oxygen consumption (VO₂max), velocity at VO₂max, velocity at submaximal lactate levels, heart rate at submaximal velocities, stride rate at submaximal velocities, stiffness, total body mass or maximal strength performance. However, significant small-to-moderate improvements were noted for jump performance, rate of force development, sprint performance, reactive strength, and running economy (ES = 0.36-0.73; p < 0.001 to 0.031; I² = 0.0% to 49.3%). JT is effective in improving physical fitness and athletic performance in endurance runners. Improvements in time-trial performance after JT may be mediated through improvements in force generating capabilities and running economy.

Lack of concordance amongst measurements of individual anaerobic threshold and maximal lactate steady state on a cycle ergometer

INTRODUCTION

The calculation of exertion intensity, in which a change is produced in the metabolic processes which provide the energy to maintain physical work, has been defined as the anaerobic threshold (AT). The direct calculation of maximal lactate steady state (MLSS) would require exertion intensities over a long period of time and with sufficient rest periods which would prove significantly difficult for daily practice. Many protocols have been used for the indirect calculation of MLSS.

OBJECTIVES

The aim of this study is to determine if the results of measurements with 12 different AT calculation methods and calculation software [Keul, Simon, Stegmann, Bunc, Dickhuth (TKM and WLa), Dmax, Freiburg, Geiger-Hille, Log-Log, Lactate Minimum] can be used interchangeably, including the method of the fixed threshold of Mader/OBLA's 4 mmol/l and then to compare them with the direct measurement of MLSS.

METHODS

There were two parts to this research. Phase 1: results from 162 exertion tests chosen at random from the 1560 tests. Phase 2: sixteen athletes (n = 16) carried out different tests on five consecutive days.

RESULTS

There was very high concordance among all the methods [intraclass correlation coefficient (ICC) > 0.90], except Log-Log in relation to the Stegamnn, Dmax, Dickhuth-WLa and Geiger-Hille. The Dickhuth-TKM showed a high tendency towards concordance, with Dmax (2.2 W) and Dickhuth-WLa (0.1 W). The Dickhuth-TKM method presented a high tendency to concordance with Dickhuth-WLa (0.5 W), Freiburg (7.4 W), MLSS (2.0 W), Bunc (8.9 W), Dmax (0.1 W). The calculation of MLSS power showed a high tendency to concordance, with Dickhuth-TKM (2 W), Dmax (2.1 W), Dickhuth-WLa (1.5 W).

CONCLUSION

The fixed threshold of 4 mmol/l or OBLA produces slightly different and higher results than those obtained with all the methods analyzed, including MLSS, meaning an overestimation of power in the individual anaerobic threshold. The Dickhuth-TKM, Dmax and Dickhuth-WLa methods defined a high concordance on a cycle ergometer. Dickhuth-TKM, Dmax, Dickhuth-WLa described a high concordance with the power calculated to know the MLSS.

Relationship between perceived exertion and blood lactate concentrations during incremental running test in young females

BACKGROUND

To investigate more practical handling of Borg's ratings of perceived exertion (RPE) and category-ratio scale of RPE (CR-10), we evaluated interrelationships between RPE, CR-10, and blood lactate concentrations (bLa) during incremental treadmill running tests for young females with different aerobic fitness levels.

METHODS

Oxygen consumption, heart rate, bLa, RPE, and CR-10 were measured from distance runners (DR; n = 15), race walkers (RW; n = 6), and untrained females (UT; n = 11). These variables corresponding to the lactate threshold (LT) and onset of blood lactate accumulation (OBLA) were compared among these groups.

RESULTS

The UT had significantly lower RPE at LT than DR and RW, although the CR-10 at LT was not significantly different among these groups. The CR-10 at OBLA was significantly lower for the UT than DR. The relationship between bLa and CR-10 was approximated well by two linear regression lines in all groups. The bLa at the intersection only for the RW was significantly lower than that at LT, however, such intersections were observed at CR-10 = 3.1 to 3.2 without significant group differences. The CR-10 scores at LT and intersections were not significantly different in each group.

CONCLUSION

These results suggested that an intersection between CR-10 and bLa was observed at the CR-10 score around three points of first half regardless of the aerobic fitness levels in young females, and such CR-10 scores would be associated with LT.

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

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