Training & Testing 517
Comparison of Selected Lactate Threshold Parameters with Maximal Lactate Steady State in Cycling
Affiliations
Key words ▶ maximal lactate● steady-state ▶ lactate threshold ● ▶ endurance performance ● diagnostic ▶ cycling ● ▶ blood-lactate-concentration ●
T. Hauser1*, J. Adam2*, H. Schulz1 1 2
Sportsmedicine/-biology, Chemnitz University of Technology, Chemnitz, Germany Department of Internal Medicine/Cardiology, University of Leipzig, Heart Centre, Leipzig, Germany
Abstract
▼
The aim of the present investigation was to compare power at “onset of blood lactate accumulation” (OBLA), “individual anaerobic threshold” (IAT) and “ + 1.5 mmol ∙ l − 1 lactate model” with power in maximal lactate steady state (MLSS) in cycling. However, there is a lack of studies concerning the absolute individual differences between different lactate parameters and MLSS. A total of 57 male participants performed several 30-min constant-load tests to determine MLSS by measuring blood lactate concentration (BLC). Depending on BLC, power was increased or decreased by 10 W in the following 30-min test. For detecting power at different threshold parameters, an incremental test was performed
Introduction accepted after revision July 14, 2013 Bibliography DOI http://dx.doi.org/ 10.1055/s-0033-1353176 Published online: November 13, 2013 Int J Sports Med 2014; 35: 517–521 © Georg Thieme Verlag KG Stuttgart · New York ISSN 0172-4622 Correspondence Dr. Thomas Hauser Sportsmedicine/-biology Chemnitz University of Technology Thüringer Weg 11 09126 Chemnitz Germany Tel.: + 49/371/531 36959 Fax: + 49/371/531 36959 thomas.hauser@s2002. tu-chemnitz.de
▼
Measuring endurance performance is a primary activity in sports medicine. One physiological parameter representing endurance performance is the maximal lactate steady state (MLSS) [19]. It is defined as the highest workload that can be maintained without an increase of blood-lactateconcentration of more than 0.05 mmol ∙ l − 1 ∙ min − 1 during the last 20 min of a 30-min constant-loadtest [2, 13, 15, 16]. Higher workloads than MLSS lead to an accumulation of lactate in the active muscle, resulting in a decrease of the pH-value [21]. As a result, the workload cannot be maintained. However, measuring MLSS is not useful for a daily performance diagnostic routine, since it can only be determined by several constant load tests performed on different days [15]. Therefore, endurance performance diagnostics are based on only one incremental test to approximate MLSS [11] by using lactate threshold parameters, e. g.
that began at 40 W and increased by 40 W every 4 min. Highly significant correlations were found between OBLA and MLSS: r = 0.89 (mean difference − 7.4 W); IAT and MLSS: r = 0.83 (mean difference 12.4W), “ + 1.5 mmol ∙ l − 1 lactate model” and MLSS: r = 0.88 (mean difference −37.4W). On average, the parameters of OBLA and IAT approximate MLSS with no significant differences. The “ + 1.5 mmol ∙ l − 1 lactate model” underestimates MLSS significantly. Based on Bland-and-Altman, the comparison of power of all threshold parameters with power in MLSS shows great individual differences despite the high regression coefficients and low mean differences between these methods.
the “onset of blood lactate accumulation” (OBLA) [18, 22], the “individual anaerobic threshold” (IAT) [23] or the “ + 1.5 mmol ∙ l − 1 lactate model” [6]. Based on the determination of the lactate threshold, training recommendations could be given, aiming at an increase in endurance performance. Therefore, good accordance between power of lactate thresholds and MLSS is absolutely necessary. However, only few studies have investigated the relation between power measured by lactate threshold parameters and MLSS [8]. Most of the studies showed a high correlation between power according to different lactate threshold parameters and MLSS (r = 0.71 to r = 0.98) [1, 7, 13, 15, 17, 20, 24, 25, 26]. However, the mentioned studies had a relatively low number of participants (n = 8 to n = 22) and they fail to present the absolute differences and thus the agreement between the different lactate threshold parameters and MLSS. This problem has already been pointed out by Faude [8], who also asserts that this relation is less established in cycling compared to running.
* These authors contributed equally to this article. Hauser T et al. Comparison of Selected Lactate … Int J Sports Med 2014; 35: 517–521
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
Authors
518 Training & Testing
The purpose of this investigation is therefore to compare the power according to the lactate threshold parameters of OBLA, IAT and “ + 1.5 mmol ∙ l − 1 lactate model” with MLSS as well as to present their absolute differences in cycle ergometry.
Onset of blood lactate accumulation The power corresponding to a fixed lactate concentration of 4 mmol ∙ l − 1 was calculated by linear interpolation from the lactate performance curve [12].
Individual anaerobic threshold
▼
Participants A total of 57 male participants (25.2 ± 4.5 years, 74.6 ± 7.4 kg, 179.4 ± 6.7 cm, VO2peak = 59.2 ± 7, 8 ml min − 1 kg − 1) with different endurance levels participated in this study (training volume: n = 20 between 10 and 14 h/week, n = 19 between 2 and 8 h/week, n = 18 no sport). This investigation was been approved by an ethics committee. Participants were informed about the aims of the study, gave their written consent and were free to withdraw from it at any time. All procedures conformed to the declaration of Helsinki [9].
IAT was determined by using the blood lactate performance relationship during and immediately after the 1st, 3rd, 5th, 7th and 10th min of the incremental graded exercise [23]. In the present work IAT was detected through the usual graphical determination [5].
“ + 1.5 mmol ∙ l − 1 lactate model” The + 1.5 mmol ∙ l − 1 lactate threshold was determined by adding the amount of 1.5 mmol ∙ l − 1 on the value of the lowest lactate/ performance ratio [6].
Statistical analysis Procedures The participants performed one incremental test to determine the lactate threshold parameters and at least 2 constant load tests to measure MLSS on a Lode cycle ergometer (Lode Excalibur Sport, Lode, Groningen, NL). Each subject performed all tests at the same time of day within 2 weeks. For recovery, participants rested for at least 48 h between tests. Participants did not participate in any other training sessions during the study. Furthermore they did not change their common nutrition. The investigation was concluded after measuring a single lactate-performancecurve as well as a single MLSS.
Results are presented in means and standard deviations (SD). A paired t-test was used to compare the means of the variables. Differences between MLSS and the lactate threshold parameter values are reported as mean differences (meandiff) and mean error. The correlation between the lactate threshold parameters and MLSS intensities were calculated using Pearson’s correlation coefficients. Power of the different lactate parameters was compared to MLSS by orthogonal regression and Bland-and-Altman-Plots [4]. The level of significance was set at α ≤ 0.05. Comparing power as measured according to different lactate threshold parameters with MLSS, α was corrected to α/3 = 0.02 using the method of Bonferroni.
Incremental test On the first day all participants performed an incremental test. The initial workload was set at 40 W and increased every 4 min by 40 W, corresponding to an increase of 10 W/min. Blood-samples were taken during the last 30 s of each step as well as in the 1st, 3rd, 5th, 7th and 10th min after break off. The test was finished when subjects reached physical exhaustion, complained of shortness of breath, dizziness or other physical issues that prevented them from completing the test [19].
Constant-load-test For detecting MLSS, several constant load tests lasting 30 min were performed [3, 13]. Workload of the first test corresponded to the power at lactate threshold parameter of OBLA. MLSS was defined as the highest workload that can be maintained without an increase in blood lactate concentration of not more than 0.05 mmol ∙ l − 1 ∙ min − 1 during the final 20 test-minutes. In order to quantify the blood lactate concentration, blood-samples were collected after 4 and 8 min and then every 2 min until the end of the test. Depending on the blood lactate concentration, the power of the following test was either increased or decreased by 10 W. All tests were performed at a cadence between 80 and 90 rpm.
Lactate threshold parameters The 3 lactate thresholds were expressed by power output. Lactate concentrations were determined from a hyperemic (Finalgon®, Ingelheim, Germany) earlobe capillary blood sample using the BIOSEN C-line (EKF-Diagnostics, Barleben, Germany; 20 μl end-to-end capillary; 1 ml of hemolysis solution; ≤ 1.5 % coefficient of variation).
Results
▼
Lactate-parameters While thresholds of OBLA and “ + 1.5 mmol ∙ l − 1 lactate model” could be assessed for all 57 participants, IAT was only assessed for 51 participants because of the rapid decline of the first post exercise lactate value. Accordingly, 1 min after the end of the test, lactate level was already below the termination value. Mean power of OBLA (POBLA), IAT (PIAT) and “ + 1.5 mmol ∙ l − 1 lactate model” (P + 1.5 mmol ∙ l − 1) were 214 ± 54 W, 236 ± 47 W and 184 ± 54 W, respectively.
Maximal lactate steady state MLSS could be determined for all 57 participants within 2–8 constant load tests. The mean value of power in MLSS (PMLSS) was 221 ± 43 W, within a range from 141 to 295 W. Mean blood lactate concentration in MLSS (LaMLSS) was 4.75 ± 1.48 mmol ∙ l − 1. It ranged between 2.23 and 9.23 mmol ∙ l − 1. No significant correlation could be found between LaMLSS and PMLSS (r = − 0.22).
Relation between maximal lactate steady state and lactate parameters All power values of MLSS and different threshold parameters are ▶ Table 1. Mean difference between MLSS and presented in ● POBLA and + 1.5 mmol ∙ l − 1 was -7.4 ± 25.1 W and − 37.4 ± 26.4 W, ▶ Fig. 1, 2). Both parameters thus underestimate respectively (● ▶ Fig. 3). MLSS. Power at IAT was 12.4 ± 24.6 W higher than MLSS (● Due to the individual deviations between MLSS and the lactate ▶ Table 2). threshold parameters, mean error was calculated (● The relation between power according to the threshold parameters and MLSS is presented in the Bland-and-Altman-Plots
Hauser T et al. Comparison of Selected Lactate … Int J Sports Med 2014; 35: 517–521
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
Materials & Methods
Training & Testing 519
Power ± SD (W) min–max Blood lactate ± SD (mmol ∙ l − 1) min–max
MLSS (n = 57)
OBLA (n = 57)
IAT (n = 51)
+ 1.5 mmol ∙ l − 1 (n = 57)
221 ± 43 141–295 4.75 ± 1.48
214 ± 54 112–321 –
236 ± 47 139–323 4.96 ± 1.27
184 ± 54 62–287 2.68 ± 0.33
2.8–8.0
2.1–3.6
2.23–9.23
Table 1 Means, standard deviations, minimum and maximum values of power and blood lactate concentration in MLSS and of lactate threshold concepts.
MLSS – maximal lactate steady state, OBAL – Onset of blood lactate accumulation, IAT – individual anaerobic threshold, + 1.5 mmol ∙ l − 1 – + 1.5 mmol ∙ l − 1 lactate model, SD – standard deviation
80
80
+1.96 SD 69.7 W
+1.96 SD
mean
0
–7.4 W –40
–1.96 SD –56.6 W
–80
–120
mean 12.4 W
0
–1.96 SD –35.9 W
–40
–80 0
300 100 200 mean PMLSS and POBLA (W)
400
0
Fig. 1 Bland-and-Altman-plot comparing power assessed using OBLA and MLSS.
300 100 200 mean PMLSS and PIAT (W)
400
Fig. 3 Bland-and-Altman-plot comparing power assessed using IAT and MLSS.
Discussion
▼
40
difference P+1.5 mmol/l - PMLSS (W)
40
+1.96 SD 14.3 W 0
–40
mean –37.4 W
–80
–1.96 SD –89.1 W
–120 0
300 100 200 mean PMLSS and P+1.5 mmol/l (W)
400
Fig. 2 Bland-and-Altman-plot comparing power assessed using + 1.5 mmol · l − 1 lactate model and MLSS.
▶ Fig. 1, 3). Mean power output corresponding to OBLA and IAT (● was highly correlated (r = 0.89**, r = 0.83**, respectively) and not significantly different from MLSS value (p > 0.02). Power output of “ + 1.5 mmol ∙ l − 1 lactate model” was also highly correlated and significant to MLSS (r = 0.88**, p = 0.001).
The aim of the present investigation was to compare the power of different lactate threshold parameters (“onset of blood lactate accumulation”, OBLA [18, 22], “individual anaerobic threshold”, IAT [23] and “ + 1.5 mmol ∙ l − 1 lactate model” [6]) with individually determined power in MLSS during cycling. The aforementioned lactate threshold parameters were primarily evaluated for running [8, 11]. However, these parameters have often been transferred to cycling. Therefore, Faude [8] summarized that a comparison of lactate thresholds and MLSS should be presented on the basis of Bland-and-Altman-Plots for cycling. In the present paper, power of all threshold parameters showed a strongly significant correlation with MLSS. In contrast to IAT and OBLA, power according to “ + 1.5 mmol ∙ l − 1 lactate model” was significantly below MLSS. Mean differences between POBLA, PIAT, P + 1.5 mmol ∙ l − 1 and MLSS were at − 7.4 ± 25.1, 12.4 ± 24.6 W and − 37.4 ± 26,4 W, respectively. The spread of the differences between PMLSS and each lactateparameter is noticeably quite large, which was detected by the method of Bland-and-Altman [4]. In particular, the small mean differences between MLSS and POBLA, and MLSS and PIAT, as well as the high regression coefficient between these methods defy the large individual differences that were found from − 52 to + 56 W, with mean error ranging from 23 to 25 W. These large differences in measurements between PMLSS and power at anaerobic threshold measured at OBLA, IAT and “ + 1.5 mmol ∙ l − 1 lactate model” show that none of these parameters fulfills the criteria for a meaningful individual training recommendation as already pointed out by Heck and Beneke [11]. If the individual lactate threshold is deter-
Hauser T et al. Comparison of Selected Lactate … Int J Sports Med 2014; 35: 517–521
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41.8 W
difference PIAT - PMLSS (W)
difference POBLA - PMLSS (W)
40
520 Training & Testing
Table 2 Mean differences (meandiff), standard deviation (SD), significance of differences (p), minimum, maximum, mean error and correlation coefficient (r).
POBLA – PMLSS (W) PIAT – PMLSS (W) P1.5 mmol ∙ l − 1 – PMLSS (W)
meandiff ± SD
p
min–max
mean error
r
− 7.4 ± 25.1 12.4 ± 24.6 − 37.4 ± 26.4**
0.03 0.04 0.001
58–52 56–69 99–19
25 23 46
0.89** 0.83** 0.88**
PMLSS – power of maximal lactate steady state, POBAL – power of onset of blood lactate accumulation, PIAT – power of individual anaerobic threshold, P1.5 mmol ∙ l − 1 – power of + 1.5 mmol ∙ l − 1 lactate model,. *behind the correlation value indicates significant correlation (p < 0.05). p – significant compared with MLSS
Conclusion
▼
On the basis of the applied loading protocol the lactate threshold parameters of OBLA, IAT and “ + 1.5 mmol ∙ l − 1” show large individual differences for MLSS. Focusing on the individual determination of MLSS it must be concluded, that OBLA, IAT and “ + 1.5 mmol ∙ l − 1” are not valid methods. However, when only comparing the methods (OBLA vs. MLSS or IAT vs. MLSS) and neglecting the individual differences, it can be concluded that on average OBLA and IAT determine MLSS well.
Funding: None. Ethical standards: The experiments comply with the current laws of the country. The study was approved by the Ethics Commission. Conflict of interest: The authors declare that they have no conflict of interest. References 1 Beneke R. Anaerobic threshold, individual anaerobic threshold, and maximal lactate steady state in rowing. Med Sci Sports Exerc 1997; 27: 863–867 2 Beneke R. Methodological aspects of maximal lactate steady state-implications for performance testing. Eur J Appl Physiol 2003; 89: 95–99 3 Beneke R, Hütler M, Leithäuser RM. Maximal lactate-steady-state independent of performance. Med Sci Sports Exerc 2000; 32: 1135–1139 4 Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1: 307–310 5 Coen B. Individuelle anaerobe Schwelle. Methodik und Anwendung in der sportmedizinischen Leistungsdiagnostik und Trainingssteuerung leichtathletischer Laufdisziplinen. Köln: Sportverl. Strauß. 1997 6 Dickhuth H-H, Yin L, Niess A, Röcker K, Mayer F, Heitkamp HC, Horstmann T. Ventilatory, lactate-derived and catecholamine thresholds during incremental treadmill running: relationship and reproducibility. Int J Sports Med 1999; 20: 122–127 7 Dörr C. Untersuchung der Validität verschiedener Laktatschwellenkonzepte an Ausdauersportlern. Justus Liebig University Giessen 2010 8 Faude O, Kindermann W, Meyer T. Lactate threshold parameters: how valid are they? Sports Med 2009; 39: 469–490 9 Harriss DJ, Atkinson G. Update – Ethical standards in sport and exercise science research. Int J Sports Med 2011; 32: 819–821 10 Hauser T, Bartsch D, Schulz H. Reliability of Power and Lactate-Concentration of Maximal Lactate Steady-State during Constant-Load Tests in Cycling. Dt Z Sportmed 2011; 10: 16–19 11 Heck H, Beneke R. 30 Years of Lactate Thresholds – what remains to be done? Dt. Z Sportmed 2008; 59: 297–302 12 Heck H. Energiestoffwechsel und medizinische Leistungsdiagnostik. Schorndorf: Hofmann, 1990 13 Heck H. Laktat in der Leistungsdiagnostik. Schorndorf: Hofmann, 1990 14 Heck H, Rosskopf P. Die Laktat- Leistungsdiagnostik – valider ohne Schwellenkonzepte. TW Sport + Medizin 1993; 5: 344–352 15 Heck H, Rosskopf P. Grundlagen verschiedener Laktatschwellenkonzepte und ihre Bedeutung für die Trainingssteuerung. In Clasing D (ed.). Stellenwert der Laktatbestimmung in der Leistungsdiagnostik. Stuttgart, Germany: G. Fischer, 1994; 111–131 16 Heck H, Hess G, Mader A. Vergleichende Untersuchungen zu verschiedenen Laktat-Schwellenkonzepten. Dt Z Sportmed 1985; 1 + 2: 19–25; 40–52
Hauser T et al. Comparison of Selected Lactate … Int J Sports Med 2014; 35: 517–521
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mined to be, for example, 56 W above MLSS, as was the maximum difference in our study, then the individual aerobic training intensities would be too high. This would result in a decrease of endurance performance over time. The practical implication of the findings is that individual MLSS cannot be properly determined by using the lactate threshold parameters of OBLA, IAT and “ + 1.5 mmol ∙ l − 1” based on an incremental test. The power at different threshold parameters may therefore lead to an over- or underestimation of MLSS and thus of the training intensities. The reason for the observed bias between lactate parameters and PMLSS is deeply rooted in the different load protocols used in the original threshold investigations [12]. Using a higher loading rate during the incremental test, power at threshold of “ + 1.5 mmol ∙ l − 1 lactate model” would increase, while power according to IAT would decrease [12]. Thus, both threshold parameters may adequately approximate MLSS by using higher loading rates than those used in the present investigation. In contrast, the OBLA threshold parameter approximates MLSS at lower loading rates [12, 14]. In this study, the loading rate was set low to 10 W/min, which explains the differences of each lactate parameter with MLSS. The differences found between threshold values and PMLSS agree with the results of Heck and Rosskopf [14]. In summary, the lactate threshold parameters of OBLA and IAT showed no significant differences with PMLSS in contrast to the parameter of the “ + 1.5 mmol ∙ l − 1 lactate model”. Thus, on average, the parameter of OBLA and IAT reflect MLSS quite well based on the applied load protocol. However, caution is necessary when using a certain lactate threshold parameter, since each parameter depends on the load protocol and consequently on the loading rate employed. There are some limitations in the present study that must be taken into consideration. First, it must be mentioned that the increase of power per minute has a significant effect on the determination of anaerobic threshold (15). According to Heck and Rosskopf [14] a power increase of 10 W/min leads to no significant difference between MLSS and OBLA, and MLSS and IAT, respectively. Therefore, the results of the present investigation show that both threshold parameters, OBLA and IAT, can be applied on the basis of an incremental test of 40 W/4 min to determine average MLSS. Furthermore it must be taken into consideration that the repeated 30-min tests could lead to training effects influencing MLSS. In the present study, no training effects were determined. These results are consistent with those of Hauser et al. [10], who found no significant differences in power of MLSS performing 8–15 30-min constant load tests. The authors therefore conclude that the applied 30-min tests did not affect MLSS. Subjects were also asked to keep their individual nutrition consistent throughout the study. However, this was not controlled by the authors.
Training & Testing 521
23 Sjödin B, Jacobs I. Onset of blood lactate accumulation and marathon running performance. Int J Sports Med 1981; 2: 23–26 24 Stegmann H, Kindermann W, Schnabel A. Lactate Kinetics and Individual Anaerobic Threshold. Int J Sports Med 1981; 2: 160–165 25 Urhausen A, Coen B, Weiler B, Kindermann W. Individual Anaerobic Threshold and Maximum Lactate Steady State. Int J Sports Med 1993; 14: 134–139 26 Van Schuylenbergh R, Vanden Eynde B, Hespel P. Correlations Between Lactate and Ventilatory Thresholds and the Maximal Lactate Steady State in Elite Cyclists. Int J Sports Med 2004; 25: 403–408
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17 Hoogeveen AR, Hoogsteen J, Shep G. The maximal lactate steady state in elite endurance athletes. Jpn J Physiol 1997; 47: 481–485 18 Jones AM, Doust JH. The validity of the lactate minimum test for determination of the maximal lactate steady state. Med Sci Sports Exerc 1998; 30: 1304–1313 19 Mader A, Liesen H, Heck H, Phillipi H, Rost R, Schürch P, Hollmann W. Zur Beurteilung der sportartspezifischen Ausdauerleistungsfähigkeit im Labor. Dt Z Sportmed 1976; 27: 80–88; 109–112 20 Marées H. Sportphysiologie. Köln: Sportverl. Strauß, 2003 21 McLellan TM, Jacobs I. Reliability, reproducibility and validity of the individual anaerobic threshold. Eur J Appl Physiol 1993; 67: 125–131 22 Sahlin K, Harris RC, Nylind B, Hultman E. Lactate content and pH in muscle obtained after dynamic exercise. Pflugers Arch 1976; 367: 143–149
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Comparison of Selected Lactate Threshold Parameters with Maximal Lactate Steady State in Cycling
Affiliations
Key words ▶ maximal lactate● steady-state ▶ lactate threshold ● ▶ endurance performance ● diagnostic ▶ cycling ● ▶ blood-lactate-concentration ●
T. Hauser1*, J. Adam2*, H. Schulz1 1 2
Sportsmedicine/-biology, Chemnitz University of Technology, Chemnitz, Germany Department of Internal Medicine/Cardiology, University of Leipzig, Heart Centre, Leipzig, Germany
Abstract
▼
The aim of the present investigation was to compare power at “onset of blood lactate accumulation” (OBLA), “individual anaerobic threshold” (IAT) and “ + 1.5 mmol ∙ l − 1 lactate model” with power in maximal lactate steady state (MLSS) in cycling. However, there is a lack of studies concerning the absolute individual differences between different lactate parameters and MLSS. A total of 57 male participants performed several 30-min constant-load tests to determine MLSS by measuring blood lactate concentration (BLC). Depending on BLC, power was increased or decreased by 10 W in the following 30-min test. For detecting power at different threshold parameters, an incremental test was performed
Introduction accepted after revision July 14, 2013 Bibliography DOI http://dx.doi.org/ 10.1055/s-0033-1353176 Published online: November 13, 2013 Int J Sports Med 2014; 35: 517–521 © Georg Thieme Verlag KG Stuttgart · New York ISSN 0172-4622 Correspondence Dr. Thomas Hauser Sportsmedicine/-biology Chemnitz University of Technology Thüringer Weg 11 09126 Chemnitz Germany Tel.: + 49/371/531 36959 Fax: + 49/371/531 36959 thomas.hauser@s2002. tu-chemnitz.de
▼
Measuring endurance performance is a primary activity in sports medicine. One physiological parameter representing endurance performance is the maximal lactate steady state (MLSS) [19]. It is defined as the highest workload that can be maintained without an increase of blood-lactateconcentration of more than 0.05 mmol ∙ l − 1 ∙ min − 1 during the last 20 min of a 30-min constant-loadtest [2, 13, 15, 16]. Higher workloads than MLSS lead to an accumulation of lactate in the active muscle, resulting in a decrease of the pH-value [21]. As a result, the workload cannot be maintained. However, measuring MLSS is not useful for a daily performance diagnostic routine, since it can only be determined by several constant load tests performed on different days [15]. Therefore, endurance performance diagnostics are based on only one incremental test to approximate MLSS [11] by using lactate threshold parameters, e. g.
that began at 40 W and increased by 40 W every 4 min. Highly significant correlations were found between OBLA and MLSS: r = 0.89 (mean difference − 7.4 W); IAT and MLSS: r = 0.83 (mean difference 12.4W), “ + 1.5 mmol ∙ l − 1 lactate model” and MLSS: r = 0.88 (mean difference −37.4W). On average, the parameters of OBLA and IAT approximate MLSS with no significant differences. The “ + 1.5 mmol ∙ l − 1 lactate model” underestimates MLSS significantly. Based on Bland-and-Altman, the comparison of power of all threshold parameters with power in MLSS shows great individual differences despite the high regression coefficients and low mean differences between these methods.
the “onset of blood lactate accumulation” (OBLA) [18, 22], the “individual anaerobic threshold” (IAT) [23] or the “ + 1.5 mmol ∙ l − 1 lactate model” [6]. Based on the determination of the lactate threshold, training recommendations could be given, aiming at an increase in endurance performance. Therefore, good accordance between power of lactate thresholds and MLSS is absolutely necessary. However, only few studies have investigated the relation between power measured by lactate threshold parameters and MLSS [8]. Most of the studies showed a high correlation between power according to different lactate threshold parameters and MLSS (r = 0.71 to r = 0.98) [1, 7, 13, 15, 17, 20, 24, 25, 26]. However, the mentioned studies had a relatively low number of participants (n = 8 to n = 22) and they fail to present the absolute differences and thus the agreement between the different lactate threshold parameters and MLSS. This problem has already been pointed out by Faude [8], who also asserts that this relation is less established in cycling compared to running.
* These authors contributed equally to this article. Hauser T et al. Comparison of Selected Lactate … Int J Sports Med 2014; 35: 517–521
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
Authors
518 Training & Testing
The purpose of this investigation is therefore to compare the power according to the lactate threshold parameters of OBLA, IAT and “ + 1.5 mmol ∙ l − 1 lactate model” with MLSS as well as to present their absolute differences in cycle ergometry.
Onset of blood lactate accumulation The power corresponding to a fixed lactate concentration of 4 mmol ∙ l − 1 was calculated by linear interpolation from the lactate performance curve [12].
Individual anaerobic threshold
▼
Participants A total of 57 male participants (25.2 ± 4.5 years, 74.6 ± 7.4 kg, 179.4 ± 6.7 cm, VO2peak = 59.2 ± 7, 8 ml min − 1 kg − 1) with different endurance levels participated in this study (training volume: n = 20 between 10 and 14 h/week, n = 19 between 2 and 8 h/week, n = 18 no sport). This investigation was been approved by an ethics committee. Participants were informed about the aims of the study, gave their written consent and were free to withdraw from it at any time. All procedures conformed to the declaration of Helsinki [9].
IAT was determined by using the blood lactate performance relationship during and immediately after the 1st, 3rd, 5th, 7th and 10th min of the incremental graded exercise [23]. In the present work IAT was detected through the usual graphical determination [5].
“ + 1.5 mmol ∙ l − 1 lactate model” The + 1.5 mmol ∙ l − 1 lactate threshold was determined by adding the amount of 1.5 mmol ∙ l − 1 on the value of the lowest lactate/ performance ratio [6].
Statistical analysis Procedures The participants performed one incremental test to determine the lactate threshold parameters and at least 2 constant load tests to measure MLSS on a Lode cycle ergometer (Lode Excalibur Sport, Lode, Groningen, NL). Each subject performed all tests at the same time of day within 2 weeks. For recovery, participants rested for at least 48 h between tests. Participants did not participate in any other training sessions during the study. Furthermore they did not change their common nutrition. The investigation was concluded after measuring a single lactate-performancecurve as well as a single MLSS.
Results are presented in means and standard deviations (SD). A paired t-test was used to compare the means of the variables. Differences between MLSS and the lactate threshold parameter values are reported as mean differences (meandiff) and mean error. The correlation between the lactate threshold parameters and MLSS intensities were calculated using Pearson’s correlation coefficients. Power of the different lactate parameters was compared to MLSS by orthogonal regression and Bland-and-Altman-Plots [4]. The level of significance was set at α ≤ 0.05. Comparing power as measured according to different lactate threshold parameters with MLSS, α was corrected to α/3 = 0.02 using the method of Bonferroni.
Incremental test On the first day all participants performed an incremental test. The initial workload was set at 40 W and increased every 4 min by 40 W, corresponding to an increase of 10 W/min. Blood-samples were taken during the last 30 s of each step as well as in the 1st, 3rd, 5th, 7th and 10th min after break off. The test was finished when subjects reached physical exhaustion, complained of shortness of breath, dizziness or other physical issues that prevented them from completing the test [19].
Constant-load-test For detecting MLSS, several constant load tests lasting 30 min were performed [3, 13]. Workload of the first test corresponded to the power at lactate threshold parameter of OBLA. MLSS was defined as the highest workload that can be maintained without an increase in blood lactate concentration of not more than 0.05 mmol ∙ l − 1 ∙ min − 1 during the final 20 test-minutes. In order to quantify the blood lactate concentration, blood-samples were collected after 4 and 8 min and then every 2 min until the end of the test. Depending on the blood lactate concentration, the power of the following test was either increased or decreased by 10 W. All tests were performed at a cadence between 80 and 90 rpm.
Lactate threshold parameters The 3 lactate thresholds were expressed by power output. Lactate concentrations were determined from a hyperemic (Finalgon®, Ingelheim, Germany) earlobe capillary blood sample using the BIOSEN C-line (EKF-Diagnostics, Barleben, Germany; 20 μl end-to-end capillary; 1 ml of hemolysis solution; ≤ 1.5 % coefficient of variation).
Results
▼
Lactate-parameters While thresholds of OBLA and “ + 1.5 mmol ∙ l − 1 lactate model” could be assessed for all 57 participants, IAT was only assessed for 51 participants because of the rapid decline of the first post exercise lactate value. Accordingly, 1 min after the end of the test, lactate level was already below the termination value. Mean power of OBLA (POBLA), IAT (PIAT) and “ + 1.5 mmol ∙ l − 1 lactate model” (P + 1.5 mmol ∙ l − 1) were 214 ± 54 W, 236 ± 47 W and 184 ± 54 W, respectively.
Maximal lactate steady state MLSS could be determined for all 57 participants within 2–8 constant load tests. The mean value of power in MLSS (PMLSS) was 221 ± 43 W, within a range from 141 to 295 W. Mean blood lactate concentration in MLSS (LaMLSS) was 4.75 ± 1.48 mmol ∙ l − 1. It ranged between 2.23 and 9.23 mmol ∙ l − 1. No significant correlation could be found between LaMLSS and PMLSS (r = − 0.22).
Relation between maximal lactate steady state and lactate parameters All power values of MLSS and different threshold parameters are ▶ Table 1. Mean difference between MLSS and presented in ● POBLA and + 1.5 mmol ∙ l − 1 was -7.4 ± 25.1 W and − 37.4 ± 26.4 W, ▶ Fig. 1, 2). Both parameters thus underestimate respectively (● ▶ Fig. 3). MLSS. Power at IAT was 12.4 ± 24.6 W higher than MLSS (● Due to the individual deviations between MLSS and the lactate ▶ Table 2). threshold parameters, mean error was calculated (● The relation between power according to the threshold parameters and MLSS is presented in the Bland-and-Altman-Plots
Hauser T et al. Comparison of Selected Lactate … Int J Sports Med 2014; 35: 517–521
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Materials & Methods
Training & Testing 519
Power ± SD (W) min–max Blood lactate ± SD (mmol ∙ l − 1) min–max
MLSS (n = 57)
OBLA (n = 57)
IAT (n = 51)
+ 1.5 mmol ∙ l − 1 (n = 57)
221 ± 43 141–295 4.75 ± 1.48
214 ± 54 112–321 –
236 ± 47 139–323 4.96 ± 1.27
184 ± 54 62–287 2.68 ± 0.33
2.8–8.0
2.1–3.6
2.23–9.23
Table 1 Means, standard deviations, minimum and maximum values of power and blood lactate concentration in MLSS and of lactate threshold concepts.
MLSS – maximal lactate steady state, OBAL – Onset of blood lactate accumulation, IAT – individual anaerobic threshold, + 1.5 mmol ∙ l − 1 – + 1.5 mmol ∙ l − 1 lactate model, SD – standard deviation
80
80
+1.96 SD 69.7 W
+1.96 SD
mean
0
–7.4 W –40
–1.96 SD –56.6 W
–80
–120
mean 12.4 W
0
–1.96 SD –35.9 W
–40
–80 0
300 100 200 mean PMLSS and POBLA (W)
400
0
Fig. 1 Bland-and-Altman-plot comparing power assessed using OBLA and MLSS.
300 100 200 mean PMLSS and PIAT (W)
400
Fig. 3 Bland-and-Altman-plot comparing power assessed using IAT and MLSS.
Discussion
▼
40
difference P+1.5 mmol/l - PMLSS (W)
40
+1.96 SD 14.3 W 0
–40
mean –37.4 W
–80
–1.96 SD –89.1 W
–120 0
300 100 200 mean PMLSS and P+1.5 mmol/l (W)
400
Fig. 2 Bland-and-Altman-plot comparing power assessed using + 1.5 mmol · l − 1 lactate model and MLSS.
▶ Fig. 1, 3). Mean power output corresponding to OBLA and IAT (● was highly correlated (r = 0.89**, r = 0.83**, respectively) and not significantly different from MLSS value (p > 0.02). Power output of “ + 1.5 mmol ∙ l − 1 lactate model” was also highly correlated and significant to MLSS (r = 0.88**, p = 0.001).
The aim of the present investigation was to compare the power of different lactate threshold parameters (“onset of blood lactate accumulation”, OBLA [18, 22], “individual anaerobic threshold”, IAT [23] and “ + 1.5 mmol ∙ l − 1 lactate model” [6]) with individually determined power in MLSS during cycling. The aforementioned lactate threshold parameters were primarily evaluated for running [8, 11]. However, these parameters have often been transferred to cycling. Therefore, Faude [8] summarized that a comparison of lactate thresholds and MLSS should be presented on the basis of Bland-and-Altman-Plots for cycling. In the present paper, power of all threshold parameters showed a strongly significant correlation with MLSS. In contrast to IAT and OBLA, power according to “ + 1.5 mmol ∙ l − 1 lactate model” was significantly below MLSS. Mean differences between POBLA, PIAT, P + 1.5 mmol ∙ l − 1 and MLSS were at − 7.4 ± 25.1, 12.4 ± 24.6 W and − 37.4 ± 26,4 W, respectively. The spread of the differences between PMLSS and each lactateparameter is noticeably quite large, which was detected by the method of Bland-and-Altman [4]. In particular, the small mean differences between MLSS and POBLA, and MLSS and PIAT, as well as the high regression coefficient between these methods defy the large individual differences that were found from − 52 to + 56 W, with mean error ranging from 23 to 25 W. These large differences in measurements between PMLSS and power at anaerobic threshold measured at OBLA, IAT and “ + 1.5 mmol ∙ l − 1 lactate model” show that none of these parameters fulfills the criteria for a meaningful individual training recommendation as already pointed out by Heck and Beneke [11]. If the individual lactate threshold is deter-
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41.8 W
difference PIAT - PMLSS (W)
difference POBLA - PMLSS (W)
40
520 Training & Testing
Table 2 Mean differences (meandiff), standard deviation (SD), significance of differences (p), minimum, maximum, mean error and correlation coefficient (r).
POBLA – PMLSS (W) PIAT – PMLSS (W) P1.5 mmol ∙ l − 1 – PMLSS (W)
meandiff ± SD
p
min–max
mean error
r
− 7.4 ± 25.1 12.4 ± 24.6 − 37.4 ± 26.4**
0.03 0.04 0.001
58–52 56–69 99–19
25 23 46
0.89** 0.83** 0.88**
PMLSS – power of maximal lactate steady state, POBAL – power of onset of blood lactate accumulation, PIAT – power of individual anaerobic threshold, P1.5 mmol ∙ l − 1 – power of + 1.5 mmol ∙ l − 1 lactate model,. *behind the correlation value indicates significant correlation (p < 0.05). p – significant compared with MLSS
Conclusion
▼
On the basis of the applied loading protocol the lactate threshold parameters of OBLA, IAT and “ + 1.5 mmol ∙ l − 1” show large individual differences for MLSS. Focusing on the individual determination of MLSS it must be concluded, that OBLA, IAT and “ + 1.5 mmol ∙ l − 1” are not valid methods. However, when only comparing the methods (OBLA vs. MLSS or IAT vs. MLSS) and neglecting the individual differences, it can be concluded that on average OBLA and IAT determine MLSS well.
Funding: None. Ethical standards: The experiments comply with the current laws of the country. The study was approved by the Ethics Commission. Conflict of interest: The authors declare that they have no conflict of interest. References 1 Beneke R. Anaerobic threshold, individual anaerobic threshold, and maximal lactate steady state in rowing. Med Sci Sports Exerc 1997; 27: 863–867 2 Beneke R. Methodological aspects of maximal lactate steady state-implications for performance testing. Eur J Appl Physiol 2003; 89: 95–99 3 Beneke R, Hütler M, Leithäuser RM. Maximal lactate-steady-state independent of performance. Med Sci Sports Exerc 2000; 32: 1135–1139 4 Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1: 307–310 5 Coen B. Individuelle anaerobe Schwelle. Methodik und Anwendung in der sportmedizinischen Leistungsdiagnostik und Trainingssteuerung leichtathletischer Laufdisziplinen. Köln: Sportverl. Strauß. 1997 6 Dickhuth H-H, Yin L, Niess A, Röcker K, Mayer F, Heitkamp HC, Horstmann T. Ventilatory, lactate-derived and catecholamine thresholds during incremental treadmill running: relationship and reproducibility. Int J Sports Med 1999; 20: 122–127 7 Dörr C. Untersuchung der Validität verschiedener Laktatschwellenkonzepte an Ausdauersportlern. Justus Liebig University Giessen 2010 8 Faude O, Kindermann W, Meyer T. Lactate threshold parameters: how valid are they? Sports Med 2009; 39: 469–490 9 Harriss DJ, Atkinson G. Update – Ethical standards in sport and exercise science research. Int J Sports Med 2011; 32: 819–821 10 Hauser T, Bartsch D, Schulz H. Reliability of Power and Lactate-Concentration of Maximal Lactate Steady-State during Constant-Load Tests in Cycling. Dt Z Sportmed 2011; 10: 16–19 11 Heck H, Beneke R. 30 Years of Lactate Thresholds – what remains to be done? Dt. Z Sportmed 2008; 59: 297–302 12 Heck H. Energiestoffwechsel und medizinische Leistungsdiagnostik. Schorndorf: Hofmann, 1990 13 Heck H. Laktat in der Leistungsdiagnostik. Schorndorf: Hofmann, 1990 14 Heck H, Rosskopf P. Die Laktat- Leistungsdiagnostik – valider ohne Schwellenkonzepte. TW Sport + Medizin 1993; 5: 344–352 15 Heck H, Rosskopf P. Grundlagen verschiedener Laktatschwellenkonzepte und ihre Bedeutung für die Trainingssteuerung. In Clasing D (ed.). Stellenwert der Laktatbestimmung in der Leistungsdiagnostik. Stuttgart, Germany: G. Fischer, 1994; 111–131 16 Heck H, Hess G, Mader A. Vergleichende Untersuchungen zu verschiedenen Laktat-Schwellenkonzepten. Dt Z Sportmed 1985; 1 + 2: 19–25; 40–52
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mined to be, for example, 56 W above MLSS, as was the maximum difference in our study, then the individual aerobic training intensities would be too high. This would result in a decrease of endurance performance over time. The practical implication of the findings is that individual MLSS cannot be properly determined by using the lactate threshold parameters of OBLA, IAT and “ + 1.5 mmol ∙ l − 1” based on an incremental test. The power at different threshold parameters may therefore lead to an over- or underestimation of MLSS and thus of the training intensities. The reason for the observed bias between lactate parameters and PMLSS is deeply rooted in the different load protocols used in the original threshold investigations [12]. Using a higher loading rate during the incremental test, power at threshold of “ + 1.5 mmol ∙ l − 1 lactate model” would increase, while power according to IAT would decrease [12]. Thus, both threshold parameters may adequately approximate MLSS by using higher loading rates than those used in the present investigation. In contrast, the OBLA threshold parameter approximates MLSS at lower loading rates [12, 14]. In this study, the loading rate was set low to 10 W/min, which explains the differences of each lactate parameter with MLSS. The differences found between threshold values and PMLSS agree with the results of Heck and Rosskopf [14]. In summary, the lactate threshold parameters of OBLA and IAT showed no significant differences with PMLSS in contrast to the parameter of the “ + 1.5 mmol ∙ l − 1 lactate model”. Thus, on average, the parameter of OBLA and IAT reflect MLSS quite well based on the applied load protocol. However, caution is necessary when using a certain lactate threshold parameter, since each parameter depends on the load protocol and consequently on the loading rate employed. There are some limitations in the present study that must be taken into consideration. First, it must be mentioned that the increase of power per minute has a significant effect on the determination of anaerobic threshold (15). According to Heck and Rosskopf [14] a power increase of 10 W/min leads to no significant difference between MLSS and OBLA, and MLSS and IAT, respectively. Therefore, the results of the present investigation show that both threshold parameters, OBLA and IAT, can be applied on the basis of an incremental test of 40 W/4 min to determine average MLSS. Furthermore it must be taken into consideration that the repeated 30-min tests could lead to training effects influencing MLSS. In the present study, no training effects were determined. These results are consistent with those of Hauser et al. [10], who found no significant differences in power of MLSS performing 8–15 30-min constant load tests. The authors therefore conclude that the applied 30-min tests did not affect MLSS. Subjects were also asked to keep their individual nutrition consistent throughout the study. However, this was not controlled by the authors.
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17 Hoogeveen AR, Hoogsteen J, Shep G. The maximal lactate steady state in elite endurance athletes. Jpn J Physiol 1997; 47: 481–485 18 Jones AM, Doust JH. The validity of the lactate minimum test for determination of the maximal lactate steady state. Med Sci Sports Exerc 1998; 30: 1304–1313 19 Mader A, Liesen H, Heck H, Phillipi H, Rost R, Schürch P, Hollmann W. Zur Beurteilung der sportartspezifischen Ausdauerleistungsfähigkeit im Labor. Dt Z Sportmed 1976; 27: 80–88; 109–112 20 Marées H. Sportphysiologie. Köln: Sportverl. Strauß, 2003 21 McLellan TM, Jacobs I. Reliability, reproducibility and validity of the individual anaerobic threshold. Eur J Appl Physiol 1993; 67: 125–131 22 Sahlin K, Harris RC, Nylind B, Hultman E. Lactate content and pH in muscle obtained after dynamic exercise. Pflugers Arch 1976; 367: 143–149
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