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Noninvasive estimation of the maximal lactate steady state in trained cyclists


Medicine & Science in Sports & Exercise: May 1999 - Volume 31 - Issue 5 - p 742-746
Special Communications: Methods

Noninvasive estimation of the maximal lactate steady state in trained cyclists. Med. Sci. Sports Exerc., Vol. 31, No. 5, pp. 742-746, 1999.

Purpose: The purposes of this study were to estimate noninvasively the maximal lactate steady state (MLSS) in trained cyclists on a windload simulator with a velocity based technique and to determine whether the HR at MLSS (HRMLSS) elicited a similar blood lactate concentration (BLC) during field testing.

Methods: To determine and verify MLSS, 10 male cyclists performed five to seven laboratory trials on separate days, including a O2max test; a 5-km time trial (TT); and two or more 30-min trials at specific percentages of each subject's average 5-km TT speed (AVS5km). Mean ± SD for the following variables were obtained at MLSS: velocity was 90.3 ± 2.7% of the AVS5km, BLC was 5.4 ± 1.6 mM, RPE was 15 ± 2.1, O2 was 80 ± 6.3% of O2max, and HR was 167 ± 9.5 beats·min−1, which was 88 ± 3.8% of the mean maximum HR. Field tests included three laps of an 8-km road circuit at HRMLSS ± 3 beats·min−1 and one lap at maximum sustainable velocity (a road TT).

Results: There were no significant differences in BLC, HR, and RPE between the three steady-state road laps and the lab MLSS trial. There was also good agreement between the road and lab MLSS velocity/TT velocity ratios.

Conclusions: Our data suggest that 5-km TT cycling velocity, as measured on a windload simulator, may be used to estimate MLSS and the HR at MLSS for training purposes.

Department of Exercise and Sport Sciences, Ithaca College, Ithaca, NY 14850

Submitted for publication May 1997.

Accepted for publication January 1998.

The authors are deeply indebted to Al Kreitler, who generously donated the windload simulator used in this study.

This project was supported by a Small Grant for Faculty Research and a Summer Research Grant from Ithaca College.

Address for correspondence: Thomas Swensen, Ph.D., Department of Exercise and Sport Sciences, Ithaca College, Ithaca, NY 14850. E-mail:

Success in endurance sports, such as cycling, depends on a number of variables, including O2max, lactate threshold, and economy of movement (4), all of which are improved by training. Athletes and sport scientists have sought the ideal compromise between training volume and intensity to optimize adaptation to an exercise program. Some authors suggests that training at intensities approximating the maximal lactate steady state (MLSS), the highest sustainable intensity of exercise where blood lactate levels remain stable, may optimize training adaptations while also reducing the risk of overtraining (3,5-11,13,14,16-21).

The most accurate way to determine the MLSS is to measure an athlete's blood lactate response to changes in work intensity over time. This procedure requires significant technological resources and involves blood handling, thereby exposing laboratory personnel to a biohazard (6). Given these deterrents to direct MLSS determination, it would be valuable to develop bloodless procedures so that athletes and coaches could evaluate and optimize training programs simply and safely. Recent studies suggest that the MLSS can be estimated noninvasively with relative ease and accuracy in runners and speed skaters using a velocity based method (6,20), or in cyclists, runners, and speed skaters with a percent maximal heart rate technique (6,18). In the most recent of these studies, Foster et al. (6) demonstrated that speed skaters achieve their MLSS at a skating velocity that is between 78% and 88% of the average velocity attained during a 2000-m skating trial. Foster et al. (6) suggested that a similar velocity based approach to estimate MLSS may also apply to cycling.

The purpose of this study was to extend the work of Foster et al. (6) to cycling. In the project's first phase, we sought to determine what percentage of 5-km time trial (TT) velocity corresponded to the MLSS in a controlled laboratory setting. In the project's second phase, we sought to determine whether the lactate/HR relationship measured in the lab at MLSS was maintained during a road or field trial, i.e., could the HR associated with MLSS in the lab be used to regulate exercise intensity on the road. If so, cyclists can estimate their MLSS and the corresponding HR on their windload simulator by performing a short trial at a certain percentage of their average 5-km TT velocity.

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Ten male competitive cyclists served as subjects. Before participation, they signed an informed consent that was approved by the Human Subjects Committee at Ithaca College. Experimental procedures for the use of human subjects in this work were performed in accordance with the American College of Sports Medicine's policy regarding the use of human subjects.

In phase I, subjects reported to the laboratory five to seven times over a period of several weeks. Subjects were asked to avoid strenuous training for 48 h before a testing session. In the first trial, after a 15-min warm-up, O2max was determined on a mechanically braked cycle ergometer (Body Guard 990, Ste Foy, Québec, Canada) that was modified with a racing saddle, drop handle bars, and the subject's pedal system. A continuous protocol was used with an initial workload of 200 W; the workload was increased 40 W every 2 min until the prescribed cadence of 80 rpm was not maintained. O2 was measured via open spirometry using a metabolic cart (SensorMedics 2900, Yorba Linda, CA) and HR via telemetry (Polar Instruments Inc., Oulu, Finland). Perceived exertion was obtained at the end of each 2-min stage using the Borg scale (2). Before and immediately after the max test, three 25 μL blood samples were drawn from the fingertip and analyzed for lactate (YSI 1500 SportTester, Yellow Springs, OH; CV = 5.3%); pre- and post-trial blood lactate were reported as the mean of the three samples. In this and subsequent laboratory trials, temperature was maintained between 19°C and 24°C, and subjects were cooled with a high powered fan while receiving vigorous verbal encouragement.

In the second trial, after the withdrawal of a baseline blood sample and a 15-min warm-up, each subject performed a maximal 5-km TT on his road bike, which was attached to a Kreitler windload simulator equipped with a Killer Headwind resistance unit (Kreitler Rollers Inc., Ottawa, KS). This unit has been shown to closely simulate road conditions when the Headwind unit door is set 1/4 open (15). To ensure consistency among subsequent lab trials, tire pressure was standardized at 100 psi and the tire/roller interface was set so that wheel slippage could not be manually produced. Distance was measured with an Avenir AV-100 cyclocomputer calibrated by measuring the subject's wheel circumference; cyclocomputer accuracy was verified by comparing the speeds registered by the cyclocomputer to a previously calibrated treadmill. In this trial, O2 and HR were monitored continuously, RPE was determined at kilometers 2 and 4, and blood lactate was measured before the warm-up and immediately after the trial.

In the remaining three to five laboratory trials, after the withdrawal of a baseline blood sample and a 15-min warm-up, each subject pedaled his road bike on the windload simulator for 30 min at various percentages of his average 5 km TT velocity (AVS5km). The first 30-min trial was completed at 88% of the AVS5km, the mid-point of the range of speeds (85-90%) that Foster et al. (6) suggested would elicit steady-state lactate conditions in cyclists. In this and subsequent 30-min trials, HR was measured continuously, O2 at minutes 7-9, 17-19, and 27-29, and blood lactate and RPE every 5 min. Subjects were strongly encouraged to drink water before and during these 30-min trials to ensure hydration to attenuate heart rate drift. MLSS was defined as a ≤ 1.0 mM change in blood lactate concentration (BLC) during the final 20 min of a MLSS trial (9).

Based on the blood lactate response during the first 30-min trial, additional 30-min trials were performed at lower or higher percentages of AVS5km as follows: if the BLC rose throughout the first trial, then the next trial was completed at 86% of AVS5km. If the BLC continued to rise in this trial, then the next trial was completed at 84% of AVS5km, and so on until MLSS was attained. If, on the other hand, the BLC fell or remained steady during the first 30-min trial, then subsequent trials were completed at 90, 92, 94, and 96% of AVS5km until MLSS was attained and then verified with an additional trial. Once MLSS was determined, the corresponding HR (HRMLSS) was calculated as the mean HR during the last 20 min of the MLSS trial.

Phase II consisted of two road trials conducted on an 8-km road circuit with lightly rolling terrain. These trials were conducted in the early morning or evening hours to mitigate the effects of summer heat (temperature range during the road trials was 16-29°C). In the first road trial, subjects completed three laps of the course at ± 3 beats·min−1 of HRMLSS. HR was measured continuously, and blood lactate and RPE were measured at the end of each lap; the laps were separated by less than 2 min to permit data collection. Approximately 10 min after the steady-state rides, subjects completed a road TT consisting of one lap of the course at their highest sustainable velocity. The elapsed time from this lap was used to calculate a road MLSS velocity/road TT velocity ratio, which was subsequently compared with the lab MLSS velocity/lab 5 km TT velocity ratio. All lab and road data were compared with a paired Student t-test. Data are reported as mean ± SD.

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Initial subject evaluation included a O2max test and training history questionnaire. On average, the subjects were 24 ± 7.1 yr in age, 1.74 ± 0.07 m in height, and 70 ± 7.6 kg in weight; they also had a mean O2max of 4.70 ± 0.45 L·min−1 and had trained 13.0 ± 1.7 h·wk−1 for 7.0 ± 7.3 yr. The means for velocity, O2, HR, RPE, and post-test BLC for the 5-km lab TT were 43.3 ± 2.0 km·h−1, 4.49 ± 0.47 L·min−1, 190 ± 11 beats·min−1, 17 ± 1.4, and 16.5 ± 2.1 mM. The lab TT means for HR, RPE, and post-test BLC compared favorably with the means obtained from the O2max tests for the same variables (190 ± 13 beats·min−1, 18 ± 4, and 14.9 ± 2.9 mM). The similarity between the respective means indicates that the subjects put forth a maximum effort during the lab TT, which is important to ensure the accuracy of our procedure. Additionally, the mean velocity of the lab TT (43.3 ± 2.0 km·h−1) was similar to the mean velocity (43.3 ± 2.9 km·h−1) the subjects attained in recent competitive TT events of various lengths, again indicating that they performed maximally during the lab TT.

Table 1 presents the lab MLSS data. MLSS occurred at a velocity that was between 85 and 94% of the average 5-km TT velocity, with a mean velocity percentage of 90.3 ± 2.7%; the blood lactate concentration at MLSS ranged from 4.0 mM to 8.5 mM, averaging 5.4 ± 1.6 mM; the O2 at MLSS was 80 ± 6.3% of O2max; and HRMLSS was 167 ± 9.5 beats·min−1, which was 88 ± 3.8% of the mean maximum heart rate (MHR). Last, the subjects completed 3.1 ± 0.7 lab trials before MLSS was identified and verified.



Only nine subjects completed the MLSS road trials because of scheduling difficulties. The means for BLC, HR, and RPE for the these trials were 5.6 ± 1.7 mM, 165 ± 9.9 beats·min−1, and 15 ± 2.0. None of these means were significantly different from the corresponding means measured during the lab MLSS trials. Figures 1, 2, and 3 show the relationship between the respective lab and road values for BLC, HR, and RPE; the correlation between the lab and road values for each variable was significant (P < 0.0001). Because of injury (subject 10), fatigue (subject 1), and scheduling problems (subject 3), data were obtained from only six subjects to compare the MLSS/TT velocity ratio between the lab and road trials. There was good agreement between the velocity ratios, with the road ratio slightly higher (2%; P = 0.002). Despite this small difference, the correlation between the lab and road velocity ratios was significant (P < 0.05) as shown in Figure 4.

Figure 1

Figure 1

Figure 2

Figure 2

Figure 3

Figure 3

Figure 4

Figure 4

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The purposes of this study were to noninvasively estimate MLSS in trained cyclists in a controlled laboratory setting with a velocity based technique and to determine whether the HR that corresponded to MLSS in the lab elicited a similar BLC during field testing. From the first phase of the project, we found that MLSS occurred at a velocity between 85% and 94% of the average 5 km TT velocity, with a mean velocity percentage of 90.3%. The corresponding BLC at MLSS was 5.4 mM, a finding that corroborates recent data from Beneke et al. (1), who showed that BLC at MLSS was 5.4 mM in 16 trained cyclists and triathletes. We also found that HRMLSS was 167 beats·min−1, which was 88% of the mean MHR. This finding agrees closely with data from Snyder et al. (18), who showed that HRMLSS was 86% of the mean MHR over a 30-min period in 12 trained cyclists. In contrast to previous research in which tests of similar duration and intensity were used to estimate MLSS (6,18), HRMLSS was stable in the lab and field over a 40-min interval, with an average variation of ± 3 beats·min−1 at constant speeds.

From the project's second phase, we found that there were no significant differences in the lactate/HR relationship at MLSS between the road and lab trials. This finding means that cyclists can estimate the MLSS training HR on a windload simulator. The use of a windload simulator offers the cyclists two potential advantages when estimating their MLSS: it may increase procedure accuracy by allowing the cyclists to recover completely between the TT and MLSS trials, thereby attenuating the effects of fatigue on the latter trial. If cyclists perform the trials outdoors, thorough rest between stages is inadvisable because of hourly or daily changes in environmental conditions. The use of a windload simulator may also increase procedure reliability, as home and lab environments are fairly stable year round in contrast to the daily, weekly, and seasonal variation in the field. Increased reliability would permit a more meaningful comparison of MLSS data across time if the procedure is used to test an athlete's progress throughout the year or from season to season.

To examine an underlying assumption that the road and lab MLSS/TT velocity ratios would be similar, we had six subjects perform an additional lap of the road circuit approximately 10 min after they finished the three MLSS laps. This fourth lap was completed at their maximum sustainable velocity, and the elapsed time was used to calculate a road MLSS velocity/road TT velocity ratio for comparison with the corresponding lab ratio. We found that the two ratios agreed closely, with the road ratio slightly higher (2%). A possible explanation for this small difference is rider fatigue. Before the road TT the cyclists completed three MLSS laps (about 40 min at a mean lactate level of 5.4 mM), whereas they only completed a 15-min warm-up before the lab TT. The longer distance of the road TT (8 km vs 5 km) and the environmental conditions inherent in the field tests may also have slightly inflated the road ratio. The possible effects of fatigue, the field conditions, and the difference in TT length are reflected by the velocity, peak HR, and post-test BLC data collected from the six subjects who completed both the lab and road TT. These subjects attained a velocity of 43.7 ± 1.1 km·h−1, peak HR of 189.6 ± 8.1 beats·min−1, and post-test BLC of 16.3 ± 3.1 mM during the lab TT. In contrast, the respective values for these variables during the road TT were 41.5 ± 0.9 km·h−1, 183.0 ± 7.1 beats·min−1, and 12.5 ± 2.0 mM. Overall, the similarity between the road and lab MLSS/TT velocity ratios suggests our velocity based procedure to estimate MLSS is potentially accurate and reliable.

Collectively, the data from both phases of the project support previous observations that the average velocity obtained during a short maximal effort can be used to estimate MLSS in trained athletes (3,6,14,20). Our data indicate that cyclists can estimate their MLSS and the corresponding MLSS training heart rate as follows: first, they perform a maximal 5-km TT on a windload simulator. Several days later, after complete recovery, the cyclists then perform a 30-min MLSS trial on the windload simulator, riding at a velocity that is approximately 90% of their average 5-km TT velocity. The mean heart rate attained during the last 20 min of the MLSS trial would be used as the MLSS training heart rate. The efficacy of using this MLSS training heart rate to regulate training intensity on the road is illustrated in Figure 5. This figure shows that of the 27 BLC data points collected during the road trials, only five were not within ± 1 mM of the respective subject's BLC at MLSS as measured in the lab. Furthermore, 40% of these errant values were because of subject 1, who struggled to complete the MLSS road trial at the prescribed HR. This subject also did not complete the road TT because of exhaustion.

Figure 5

Figure 5

The value of this research, as with other MLSS estimation studies (3,5,6,8,14,18,20), is based on the assumption that training at MLSS may optimize training adaptations. Whereas the issue of which training intensity improves performance most efficiently is unresolved, many studies show that training at MLSS is beneficial (3,10,13,16,17,21). In contrast, data from another study demonstrated that intermittent and steady-state training at a power output corresponding to anaerobic threshold produce similar results (12). The mean BLC during the intermittent training sessions in this study, however, was approximately 4 mM, well within the range of steady-state lactate conditions as previously noted (18).

In summary, our results indicate that the average velocity obtained during a short maximal effort can be used to estimate the MLSS in trained cyclists. In addition, since there was no difference in the lactate/HR relationship at MLSS between the lab and road trials, cyclists can use a windload simulator to estimate their MLSS and corresponding HRMLSS. The use of a windload simulator may increase procedure accuracy and reliability by attenuating the environmental and fatigue effects that could influence field tests. If the tests are completed on the road, however, they should be conducted within a relatively short time span on the same day to reduce the effects of environmental factors. Additionally, road tests should be conducted in the morning or evening hours to minimize possible temperature effects on HR during the MLSS trial.

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