Subscribe to RSS
DOI: 10.1055/a-1958-3876
Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running?
Abstract
Endurance running performance can be predicted by maximal oxygen uptake (V̇O2max), the fractional utilisation of oxygen uptake (%V̇O2max) and running economy at lactate threshold (REOBLA). This study aims to assess maximal lactate accumulation rate (ċLamax) in terms of improving running performance prediction in trained athletes. Forty-four competitive female and male runners/triathletes performed an incremental step test, a 100-m sprint test and a ramp test to determine their metabolic profile. Stepwise linear regression was used to predict 5000-m time trial performance. Split times were recorded every 200-m to examine the ‘finishing kick’. Females had a slower t5k and a lower V̇O2max, ċLamax, ‘finishing kick’ and REOBLA. Augmenting Joyner’s model by means of ċLamax explained an additional 4.4% of variance in performance. When performing the same analysis exclusively for males, ċLamax was not included. ċLamax significantly correlated with %V̇O2max (r=-0.439, p=0.003) and the ‘finishing kick’ (r=0.389, p=0.010). ċLamax allows for significant (yet minor) improvements in 5000-m performance prediction in a mixed-sex group. This margin of improvement might differ in middle-distance events. Due to the relationship to the ‘finishing kick’, ċLamax might be related to individual pacing strategies, which should be assessed in future research.
Publication History
Received: 30 December 2021
Accepted: 26 September 2022
Article published online:
18 December 2022
© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Georg Thieme Verlag
Rüdigerstraße 14, 70469 Stuttgart,
Germany
-
References
- 1 Joyner MJ, Coyle EF. Endurance exercise performance: the physiology of champions. J Physiol 2008; 586: 35-44
- 2 Joyner MJ. Modeling: optimal marathon performance on the basis of physiological factors. J Appl Physiol (1985) 1991; 70: 683-687
- 3 Poole DC, Richardson RS. Determinants of oxygen uptake. Implications for exercise testing. Sports Med 1997; 24: 308-320
- 4 Bassett DR, Howley ET. Limiting factors for maximum oxygen uptake and determinants of endurance performance. Med Sci Sports Exerc 2000; 32: 70-84
- 5 Lundby C, Montero D, Joyner M. Biology of VO2 max: looking under the physiology lamp. Acta Physiol (Oxf) 2017; 220: 218-228
- 6 Anderson T. Biomechanics and running economy. Sports Med 1996; 22: 76-89
- 7 Saunders PU, Pyne DB, Telford RD. et al. Factors affecting running economy in trained distance runners. Sports Med 2004; 34: 465-485
- 8 Lundby C, Montero D, Gehrig S. et al. Physiological, biochemical, anthropometric, and biomechanical influences on exercise economy in humans. Scand J Med Sci Sports 2017; 27: 1627-1637
- 9 Støa EM, Helgerud J, Rønnestad BR. et al. Factors Influencing Running Velocity at Lactate Threshold in Male and Female Runners at Different Levels of Performance. Front Physiol 2020; 11: 585267
- 10 Billat VL, Sirvent P, Py G. et al. The concept of maximal lactate steady state: a bridge between biochemistry, physiology and sport science. Sports Med 2003; 33: 407-426
- 11 Heck H, Mader A, Hess G. et al. Justification of the 4-mmol/l lactate threshold. Int J Sports Med 1985; 6: 117-130
- 12 Wahl P, Zwingmann L, Manunzio C. et al. Higher accuracy of the lactate minimum test compared to established threshold concepts to determine maximal lactate steady state in running. Int J Sports Med 2018; 39: 541-548
- 13 Alvero-Cruz JR, Carnero EA, Garcia MAG. et al. Predictive performance models in long-distance runners: a narrative review. Int J Environ Res Public Health 2020; 17: 8289
- 14 Mader A. Glycolysis and oxidative phosphorylation as a function of cytosolic phosphorylation state and power output of the muscle cell. Eur J Appl Physiol 2003; 88: 317-338
- 15 Wackerhage H, Gehlert S, Schulz H. et al. Lactate thresholds and the simulation of human energy metabolism: contributions by the Cologne Sports Medicine Group in the 1970s and 1980s. Front Physiol 2022; 13: 899670
- 16 Tucker R. The anticipatory regulation of performance: the physiological basis for pacing strategies and the development of a perception-based model for exercise performance. Br J Sports Med 2009; 43: 392-400
- 17 Hauser T, Bartsch D, Baumgartel L. et al. Reliability of maximal lactate-steady-state. Int J Sports Med 2013; 34: 196-199
- 18 Adam J, Ohmichen M, Ohmichen E. et al. Reliability of the calculated maximal lactate steady state in amateur cyclists. Biol Sport 2015; 32: 97-102
- 19 Hauser T, Adam J, Schulz H. Comparison of calculated and experimental power in maximal lactate-steady state during cycling. Theor Biol Med Model 2014; 11: 25
- 20 Quittmann OJ, Appelhans D, Abel T. et al. Evaluation of a sport-specific field test to determine maximal lactate accumulation rate and sprint performance parameters in running. J Sci Med Sport 2020; 23: 27-34
- 21 Quittmann OJ, Schwarz YM, Mester J. et al. Maximal lactate accumulation rate in all-out exercise differs between cycling and running. Int J Sports Med 2021; 42: 314-322
- 22 Corrado D, Pelliccia A, Bjornstad HH. et al. Cardiovascular pre-participation screening of young competitive athletes for prevention of sudden death: proposal for a common European protocol. Consensus Statement of the Study Group of Sport Cardiology of the Working Group of Cardiac Rehabilitation and Exercise Physiology and the Working Group of Myocardial and Pericardial Diseases of the European Society of Cardiology. Eur Heart J 2005; 26: 516-524
- 23 Coates AM, Berard JA, King TJ. et al. Physiological determinants of ultramarathon trail-running performance. Int J Sports Physiol Perform 2021; 16: 1454-1461
- 24 Pastor FS, Besson T, Varesco G. et al. Performance determinants in trail-running races of different distances. Int J Sports Physiol Perform 2022; 17: 844-851
- 25 Pařízková J. Lean body mass and depot fat during ontogenesis in humans. In: Pařízková J, Hrsg. Body Fat and Physical Fitness. Dordrecht: Springer Netherlands; 1977: 24-51
- 26 Jones AM, Doust JH. A 1% treadmill grade most accurately reflects the energetic cost of outdoor running. J Sports Sci 1996; 14: 321-327
- 27 Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc 1982; 14: 377-381
- 28 Heck H, Schulz H, Bartmus U. Diagnostics of anaerobic power and capacity. Eur J Sport Sci 2003; 3: 1-23
- 29 Manunzio C, Mester J, Kaiser W. et al. Training intensity distribution and changes in performance and physiology of a 2nd place finisher team of the race across america over a 6 month preparation period. Front Physiol 2016; 7: 642
- 30 Howley ET, Bassett DR, Welch HG. Criteria for maximal oxygen uptake: review and commentary. Med Sci Sports Exerc 1995; 27: 1292-1301
- 31 Ghasemi A, Zahediasl S. Normality tests for statistical analysis: a guide for non-statisticians. Int J Endocrinol Metab 2012; 10: 486-489
- 32 Das KR, Imon AHMR. A brief review of tests for normality. Am J Theor Appl Stat 2016; 5: 5-12
- 33 Vetter TR. Fundamentals of research data and variables: the devil is in the details. Anesth Analg 2017; 125: 1375-1380
- 34 Jones AM, Carter H. The effect of endurance training on parameters of aerobic fitness. Sports Med 2000; 29: 373-386
- 35 Maunder E, Seiler S, Mildenhall MJ. et al. The importance of ‘durability’ in the physiological profiling of endurance athletes. Sports Med 2021; 51: 1619-1628
- 36 Medbø JI, Toska K. Lactate release, concentration in blood, and apparent distribution volume after intense bicycling. Jpn J Physiol 2001; 51: 303-312
- 37 Durand R, Galli M, Chenavard M. et al. Modelling of blood lactate time-courses during exercise and/or the subsequent recovery: limitations and few perspectives. Front Physiol 2021; 12: 702252
- 38 Joyner MJ. Physiological limits to endurance exercise performance: influence of sex. J Physiol 2017; 595: 2949-2954
- 39 Jones AM. The physiology of the world record holder for the women’s marathon. Int J Sports Sci Coach 2006; 1: 101-116
- 40 Semin K, Stahlnecker Iv AC, Heelan K. et al. Discrepancy between training, competition and laboratory measures of maximum heart rate in NCAA division 2 distance runners. J Sports Sci Med 2008; 7: 455-460
- 41 Mikus CR, Earnest CP, Blair SN. et al. Heart rate and exercise intensity during training: observations from the DREW Study. Br J Sports Med 2009; 43: 750-755
- 42 Cheatham CC, Mahon AD, Brown JD. et al. Cardiovascular responses during prolonged exercise at ventilatory threshold in boys and men. Med Sci Sports Exerc 2000; 32: 1080-1087
- 43 Ingjer F. Factors influencing assessment of maximal heart rate. Scand J Med Sci Sports 2007; 1: 134-140
- 44 Boudet G, Garet M, Bedu M. et al. Median maximal heart rate for heart rate calibration in different conditions: laboratory, field and competition. Int J Sports Med 2002; 23: 290-297
- 45 Renberg J, Sandsund M, Wiggen ON. et al. Effect of ambient temperature on female endurance performance. J Therm Biol 2014; 45: 9-14
- 46 McCormick A, Meijen C, Marcora S. Psychological determinants of whole-body endurance performance. Sports Med 2015; 45: 997-1015
- 47 Pallares JG, Moran-Navarro R, Ortega JF. et al. Validity and reliability of ventilatory and blood lactate thresholds in well-trained cyclists. PLoS One 2016; 11: e0163389
- 48 Cerezuela-Espejo V, Courel-Ibanez J, Moran-Navarro R. et al. The relationship between lactate and ventilatory thresholds in runners: validity and reliability of exercise test performance parameters. Front Physiol 2018; 9: 1320
- 49 Dickhuth HH, Yin L, Niess A. et al. Ventilatory, lactate-derived and catecholamine thresholds during incremental treadmill running: relationship and reproducibility. Int J Sports Med 1999; 20: 122-127
- 50 Plato PA, McNulty M, Crunk SM. et al. Predicting lactate threshold using ventilatory threshold. Int J Sports Med 2008; 29: 732-737
- 51 Loat CE, Rhodes EC. Relationship between the lactate and ventilatory thresholds during prolonged exercise. Sports Med 1993; 15: 104-115
- 52 Kouwijzer I, Cowan RE, Maher JL. et al. Interrater and intrarater reliability of ventilatory thresholds determined in individuals with spinal cord injury. Spinal Cord 2019; 57: 669-678
- 53 Jamnick NA, Pettitt RW, Granata C. et al. An examination and critique of current methods to determine exercise intensity. Sports Med 2020; 50: 1729-1756
- 54 Hoefelmann CP, Diefenthaeler F, Costa VP. et al. Test-retest reliability of second lactate turnpoint using two different criteria in competitive cyclists. Eur J Sports Sci 2015; 15: 265-270
- 55 Smith G. Step away from stepwise. J Big Data 2018; 5: 32
- 56 Vandewalle H, Peres G, Monod H. Standard anaerobic exercise tests. Sports Med 1987; 4: 268-289
- 57 Bar-Or O. The Wingate anaerobic test. An update on methodology, reliability and validity. Sports Med 1987; 4: 381-394
- 58 Green S. Measurement of anaerobic work capacities in humans. Sports Med 1995; 19: 32-42
- 59 Robergs RA, Ghiasvand F, Parker D. Biochemistry of exercise-induced metabolic acidosis. Am J Physiol Regul Integr Comp Physiol 2004; 287: R502-R516
- 60 Wawer C, Heine O, Predel H-G. et al. Determination of anaerobic capacity – reliability and validity of sprint running tests. Exerc Sci 2020; 29: 129-137
- 61 Sandford GN, Rogers SA, Sharma AP. et al. Implementing anaerobic speed reserve testing in the field: validation of vvo2max prediction from 1500-m race performance in elite middle-distance runners. Int J Sports Physiol Perform 2019; 14: 1147-1150
- 62 Sandford GN, Kilding AE, Ross A. et al. Maximal sprint speed and the anaerobic speed reserve domain: the untapped tools that differentiate the world’s best male 800 m runners. Sports Med 2019; 49: 843-852
- 63 Julio UF, Panissa VLG, Paludo AC. et al. Use of the anaerobic speed reserve to normalize the prescription of high-intensity interval exercise intensity. Eur J Sport Sci 2020; 20: 166-173