The maximum metabolic steady-state: Definition, measurement, and application

By Dr Ed Maunder and Dr Dan Plews

Recently, we blogged about the importance of the lactate threshold in long-distance triathlon training and performance. As we discussed, the lactate threshold is also referred to as the ‘aerobic threshold’, or VT₁ and LT₁. In this blog we are going to discuss the importance of the second physiological threshold, commonly referred to as the ‘anaerobic threshold’, ‘lactate turn-point’, or VT₂ and LT₂ (29). We refer to this second threshold as the ‘maximum metabolic steady-state’ (MMSS), and in this blog, we will explain why.

 The maximum metabolic steady-state

 The MMSS refers to the intensity at which we transition from ‘steady-state’ to ‘non-steady-state’ metabolic responses to prolonged exercise. When we are in a metabolic steady-state, exercising at a constant-power or pace will produce stable responses; that is, muscle and blood lactate concentrations, acid-base balance, phosphocreatine availability, and oxygen consumption (VO₂) will plateau and stabilise (21). When we are in metabolic non-steady-state, the exercise intensity is high enough that these responses can no longer stabilise; muscle and blood lactate concentrations progressively rise, we become increasingly more acidic, and VO₂ continues to increase, eventually to our own maximum rate (21). The MMSS, therefore, defines the boundary between exercise intensities at which these steady-state and non-steady-state responses are observed, what some have referred to as the boundary between heavy- and severe-intensity domains (18) (although it should be acknowledged here that in reality, it is more likely this boundary is more of a phase transition than a threshold (28)).

 Assessment methods

 The MMSS is estimated through a range of different methods, most of which have been studied in laboratory settings (6, 15, 18, 20, 24, 26, 31, 33). Some common methods include:

• Critical power (CP) is a concept analogous to the MMSS and uses plots of an individual’s power-sustainable duration relationship to estimate critical power (or velocity), which is defined as the asymptote of this curve. In a laboratory setting, these curves are constructed using three-to-five constant-load time-to-exhaustion trials in the severe-domain (i.e. above MMSS) are performed, lasting ~2-15 minutes (3, 13, 20, 21, 37). These testing procedures have been shown to produce critical power (or MMSS) estimates that distinguish steady and non-steady metabolic responses (4, 21, 30, 34). Recently, the use of training data to estimate critical power has been assessed, with underwhelming results, although race data may ultimately prove to be more useful (32).
  
  
• CP via the three-minute all-out test. This is a rather gnarly alternative assessment method is the “three-minute all-out test”, which has been found to estimate the MMSS some success when performed in laboratory environments (7, 35). This test involves three minutes of non-paced, all-out exercise, with continuous measurement of power (7, 35, 36), and critical power is defined as the average power during the final 30 s of the test (7). We are currently running a study to determine if this three-minute all-out test, when performed remotely by unsupervised cyclists at home in typical road bike-smart trainer set-ups, provides a valid estimate of the MMSS. We will let you know the results when we have them!
  
  
• Incremental step test. A very common method used in laboratories to estimate MMSS is the incremental exercise test, where blood lactate concentration is measured at a range of work-rates and then plotted against power or pace. Whilst there is no universally accepted metric of turning this data into an estimate of the MMSS, several exist (15, 16, 27), with curve-fitting functions such as the modified Dmax method appearing to be one of the most appropriate (15). The methods that are used for estimating the MMSS are trying to identify the point on the curve at which blood lactate begins to rise in an exponential fashion against exercise intensity.
  
  
• Maximal lactate steady-state (MLSS): Blood lactate concentrations are also used to define the MMSS in what is called MLSS testing (2). This protocol involves having an athlete exercise at a particular constant work-rate for 30 minutes, with measurement of blood lactate concentration at 10 and 30 min. If blood lactate increases by more than ~1 mmol^.L^-1 the response is deemed non-steady; if it does not, the response is deemed steady. This protocol is repeated at several different work-rates, on different days, and the highest work-rate at which a stable blood lactate concentration is observed is the estimate of the MMSS (19, 22). The main practical shortcoming of this assessment is the need for multiple days of testing to produce an estimate.
  
  
• Functional threshold power (FTP). As many endurance athletes do not have regular or affordable access to these facilities, the field-based FTP test has been adopted by many athletes and coaches. The FTP refers to the maximum work-rate that can be sustained for 60 min. The FTP concept is derived from studies which showed strong correlations between average power during a 60-min time-trial and both 40-km time-trial performance on the road and LT (11, 12). Due to the almost unreasonable demands associated with performing an ‘hour of power’, the 20-min FTP test was proposed, in which 95% of the best-effort power of 20 min is accepted as FTP (FTP₂₀) (1). However, this ‘correction factor’ was not research-derived, and recently 90% of 20-min power has been shown as a better estimate of 60-min power (25). Recent studies have compared FTP₂₀ with traditional laboratory-derived MMSS estimates, with a largely poor agreement between the measures (5, 6, 14, 17, 23, 26). This is perhaps unsurprising given that the 20-min FTP test is an estimate of the 60-min average power, and the 60-min average power is not tied to individual physiological responses. Indeed, it is likely that a key training adaptation sought in endurance sport is improved ‘durability’ at intensities approximating the LT and MMSS.
  
  
• Ramp tests. Many athletes also perform ramp tests to estimate ‘threshold’ or the MMSS. In these tests, power is increased by a fixed amount every minute, and the athlete hangs in as long as they can last amidst the progressively increasing power demands. Typically, power at threshold is estimated using a percentage of the final power output achieved (~75%). These tests are therefore similar to what most laboratories will use for measuring VO₂max, as exhaustion in this type of protocol will usually coincide with the attainment of VO₂ From a scientific standpoint, the accuracy of these tests for estimating the MMSS remains untested, and, as exercise physiologists working with many athletes, we find it hard to believe these tests can be very accurate at an individual level. Different types of athletes have very different profiles, with some hitting threshold quite close to VO₂max (we see this type of profile with a lot of Ironman athletes), and others having a much larger ‘reserve’ between threshold and VO₂max (something we tend to see with those competing over short durations, such as sprint-distance triathlon). That said, these types of tests may be more beneficial for inexperienced athletes who may have trouble effectively pacing time-trial (e.g. 20 min FTP) based tests.

Practical utility

That is all well and good, but why is it important to know your MMSS? In our view, knowledge of your MMSS work-rate is most useful in programming training and monitoring adaptations taking place over-time in response to training. For instance, if a session is being designed such that it generates a large homeostatic disturbance, we can use knowledge of the MMSS to (i) ensure that the muscle metabolic disturbance is in fact substantial and (ii) predict how large that disturbance is likely to be, and therefore make judgements about recovery and subsequent sessions, for example.

Whilst knowledge of the MMSS can be useful in training load monitoring – indeed, most models of training load use estimates of MMSS (such as the “functional threshold power”) as the basis of the calculation – it must be considered that your MMSS work-rate after 15 min of cycling is not the same as in the fourth and fifth hour of a session. This was shown in a recent series of studies using the critical power model (8–10). Training load calculations typically fail to appreciate this, meaning that 10 min at 300 W in the first hour of a session contributes the same value to training load calculations as 10 min at 300 W in the fifth hour. We like to refer to the depreciation in these physiological characteristics over-time during long-duration exercise, or, rather, the ability to stave off these depreciations, as ‘durability’. Therefore, even with an accurate estimate of the MMSS measured when ‘fresh’, it is important to be careful when applying this to training load monitoring. For this purpose, it may be more appropriate to use MMSS heart rate estimates instead.

References

1. Allen H, Coggan AR. Training and racing with a power meter. Boulder, CO: Velopress, 2006.
2. Beneke R, von Duvillard SP. Determination of maximal lactate steady-state response in selected sports events. Med Sci Sports Exerc 28: 241–246, 1996.
3. Bishop D, Jenkins DG, Howard A. The critical power function is dependent on the duration of the predictive exercise tests chosen. Int J Sports Med 19: 125–129, 1998.
4. Black MI, Jones AM, Blackwell JR, Bailey SJ, Wylie LJ, McDonagh STJ, Thompson C, Kelly J, Sumners P, Mileva KN, Bowtell JL, Vanhatalo A. Muscle metabolic and neuromuscular determinants of fatigue during cycling in different exercise intensity domains. J Appl Physiol 122: 446–459, 2017.
5. Borszcz FK, Tramontin AF, Bossi AH, Carminatti LJ, Costa VP. Functional threshold power in cyclists: Validity of the concept and physiological responses. Int J Sports Med 39: 737–742, 2018.
6. Borszcz FK, Tramontin AF, Costa VP. Is the functional threshold power interchangeable with the maximal lactate steady state in trained cyclists? Int J Sports Physiol Perform 14: 1029–1035, 2019.
7. Burnley M, Doust JH, Vanhatalo A. A 3-min all-out test to determine peak oxygen uptake and the maximal steady-state. Med Sci Sports Exerc 38: 1995–2003, 2006.
8. Clark IE, Vanhatalo A, Bailey SJ, Wylie LJ, Kirby BS, Wilkins BW, Jones AM. Effects of two hours of heavy-intensity exercise on the power–duration relationship. Med Sci Sports Exerc 50: 1658–1668, 2018.
9. Clark IE, Vanhatalo A, Thompson C, Joseph C, Black MI, Blackwell JR, Wylie LJ, Tan R, Bailey SJ, Wilkins BW, Kirby BS, Jones AM. Dynamics of the power-duration relationship during prolonged endurance exercise and influence of carbohydrate ingestion. J Appl Physiol 127: 726–736, 2019.
10. Clark IE, Vanhatalo A, Thompson C, Wylie LJ, Bailey SJ, Kirby BS, Wilkins BW, Jones AM. Changes in the power-duration relationship following prolonged exercise: estimation using conventional and all-out protocols and relationship with muscle glycogen. Am J Physiol - Regul Integr Comp Physiol 317: R59–R67, 2019.
11. Coyle EF, Coggan AR, Hopper MK, Walters TJ. Determinants of endurance in well-trained cyclists. J Appl Physiol 64: 2622–2630, 1988.
12. Coyle EF, Feltner ME, Kautz SA, Hamilton MT, Montain SJ, Baylor AM, Abraham LD, Petrek GW. Physiological and biomechanical factors associated with elite endurance cycling performance. Med Sci Sports Exerc 23: 93–107, 1991.
13. Hill DW. The critical power concept: A review. Sports Med 16: 237–254, 1993.
14. Inglis EC, Iannetta D, Pass L, Murias JM. Maximal lactate steady state versus the 20-minute functional threshold power test in well-trained individuals: “ Watts ” the big deal? Int J Sports Physiol Perform : 1–7, 2019.
15. Jamnick NA, Botella J, Pyne DB, Bishop DJ. Manipulating graded exercise test variables affects the validity of the lactate threshold and VO2peak. PLoS One 13: 1–21, 2018.
16. Jamnick NA, Pettitt RW, Granata C, Pyne DB, Bishop DJ. An examination and critique of current methods to determine exercise intensity. Sports Med (2020). doi: 10.1007/s40279-020-01322-8.
17. Jeffries O, Simmons R, Patterson SD, Waldron M. Functional threshold power is not equivalent to lactate parameters in trained cyclists. J Strength Cond Res Jul 1: 000–000, 2019.
18. Jones AM, Burnley M, Black MI, Poole DC, Vanhatalo A. The maximal metabolic steady state: redefining the ‘gold standard.’ Physiol Rep 7: 1–16, 2019.
19. Jones AM, Doust JH. The validity of the lactate minimum test for determination of the maximal lactate steady state. Med Sci Sports Exerc 30: 1304–1313, 1998.
20. Jones AM, Vanhatalo A. The ‘critical power’ concept: Applications to sports performance with a focus on intermittent high-intensity exercise. Sports Med 47: 65–78, 2017.
21. Jones AM, Wilkerson DP, DiMenna F, Fulford J, Poole DC. Muscle metabolic responses to exercise above and below the “critical power” assessed using 31P-MRS. Am J Physiol - Regul Integr Comp Physiol 294: R585–R593, 2008.
22. Kilding AE, Jones AM. Validity of a single-visit protocol to estimate the maximum lactate steady state. Med Sci Sports Exerc 37: 1734–1740, 2005.
23. Lillo-Bevia JR, Courel-Ibanez J, Cerezuela-Espejo V, Moran-Navarro R, Martinez-Cava A, Pallares JG. Is the functional threshold power a valid metric to estimate the maximal lactate steady state in cyclists? J Strength Cond Res Nov 7: 000–000, 2019.
24. Lucía A, Hoyos J, Pérez M, Chicharro JL. Heart rate and performance parameters in elite cyclists: a longitudinal study. Med Sci Sports Exerc 32: 1777–1782, 2000.
25. MacInnis MJ, Thomas ACQ, Phillips SM. The reliability of 4-minute and 20-minute time trials and their relationships to functional threshold power in trained cyclists. Int J Sports Physiol Perform 14: 38–45, 2019.
26. Morgan PT, Black MI, Bailey SJ, Jones AM, Vanhatalo A. Road cycle TT performance: Relationship to the power-duration model and association with FTP. J Sports Sci 37: 902–910, 2019.
27. Newell J, Higgins D, Madden N, Cruickshank J, Einbeck J, McMillan K, McDonald R. Software for calculating blood lactate endurance markers. J Sports Sci 25: 1403–1409, 2007.
28. Pethick J, Winter SL, Burnley M. Physiological evidence that the critical torque is a phase transition, not a threshold. 2020.
29. Poole DC, Rossiter HB, Brooks GA, Gladden LB. The anaerobic threshold: 50+ years of controversy. J Physiol Oct 28, 2020.
30. Poole DC, Ward SA, Gardner GW, Whipp BJ. Metabolic and respiratory profile of the upper limit for prolonged exercise in man. Ergonomics 31: 1265–1279, 1988.
31. Schneider DA, Phillips SE, Stoffolano S. The simplified V-slope method for detecting the gas exchange threshold. Med Sci Sports Exerc 25: 1180–1184, 1993.
32. Spragg J, Leo P. Can critical power be estimated from training and racing data using mean maximal power outputs? J Sci Cycl 9: 7–10, 2020.
33. Valenzuela PL, Morales JS, Foster C, Lucia A, De La Villa P. Is the functional threshold power a valid surrogate of the lactate threshold? Int J Sports Physiol Perform 13: 1293–1298, 2018.
34. Vanhatalo A, Black MI, DiMenna FJ, Blackwell JR, Schmidt JF, Thompson C, Wylie LJ, Mohr M, Bangsbo J, Krustrup P, Jones AM. The mechanistic bases of the power–time relationship: muscle metabolic responses and relationships to muscle fibre type. J Physiol 594: 4407–4423, 2016.
35. Vanhatalo A, Doust JH, Burnley M. Determination of critical power using a 3-min all-out cycling test. Med Sci Sports Exerc 39: 548–555, 2007.
36. Vanhatalo A, Doust JH, Burnley M. A 3-min all-out cycling test is sensitive to a change in critical power. Med Sci Sports Exerc 40: 1693–1699, 2008.
37. Vanhatalo A, Jones AM, Burnley M. Application of critical power in sport. Int J Sports Physiol Perform 6: 128–136, 2011.