Relationship Between Lactate Threshold Essay

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Relationship Between Lactate Threshold

Abstract

Research into the relationship between physiological variables and running performance has been variable. The aim of this study was to examine the relationship between 5k running performance and a number of physiological variables in a group of 11 trained club runners (Age 21.451.63yrs, Height 175.092.77cm, Weight 67.865.12kg). The athletes underwent a laboratory treadmill test to determine their maximum oxygen uptake (VO2 max) and running velocities at lactate threshold (v-Tlac) and blood lactate concentration of 4mM (v-OBLA). Running performance was determined by a 5k time-trial on an athletics track for which the average time was 1097.09 ± 108.02 secs. The mean velocities for v-Tlac and v-OBLA were 15.18 ± 1.5km/h, 16.76 ± 1.60 km/h and mean VO2max was 59.10 ± 3.54 ml/kg/min. The best single predictors of 5k running performance were v-OBLA and VO2max (p = .003, p = .007) while v-Tlac was slightly poorer (p = .013). It is concluded that lactate variables may be valid and reproducible predictors for 5km running performance.

Introduction

Research throughout history has established that a number of physiological variables relate to distance running performance, including Lactate Threshold (Tlac), OBLA and VO2 Max (Conley and Krahenbuhl, 1980; Costill, Thomason and Roberts, 1973; Coyle et al, 1983; Farrell et al, 1979; Hagberg and Coyle, 1983; Lafontaine, Londeree and Spath, 1982). The results from this research have been variable. Evidence has shown that blood lactate variables highly correlate with running performance over a variety of distances. Additionally, these variables contribute to running performance variance more than any other physiological variables (Yoshida et al, 1990, 1993). ‘Lactate Threshold’ describes the point at which exercise begins to hurt more than it should because the body’s lactate production exceeds the body’s ability to flush it away (Robergs & Roberts, 1997). It is the exercise intensity at which lactate threshold occurs that can be used as a significant predictor of endurance performance (Allen et al, 1985; Coyle et al, 1988; Farrell et al, 1979).

It is considered a powerful tool for developing effective training regimes and as a method of monitoring adaptation to endurance performance, although to be effective at fulfilling these roles, the measurement of lactate threshold must be reliable. OBLA is the Onset of Blood Lactate Accumulation. OBLA is accepted as an incremental method for detecting the lactate deflection point (Australian Sports Commission, 2000). Being able to detect this point is crucial as it is an indication of when an athlete switches from a predominantly aerobic to anaerobic metabolism, which leads to hastened fatigue. It is established that a level of ~ 2 – 4 millimoles per dm3 (litre) represents OBLA. Duggan and Tebbutt (1990) examined blood lactate concentrations of non-athletes during a treadmill protocol at 12 km/h.

Results suggested vOBLA to be a reproducible performance predictor. In addition to Lactate variables, sports scientists measure VO2 max to objectively evaluate a subject’s functional aerobic capacity. VO2 max is the maximum volume of oxygen that can be utilised in one minute during maximal or exhaustive exercise (Bassett & Howley 2000). The majority of research using heterogeneous groups has found that VO2 Max correlates highly with running performance (Costill et al, 1973; Thomason and Roberts, 1973; Foster et al, 1978). However, when moderately homogeneous groups were tested, low-moderate correlations were found (Conley and Krahenbuhl, 1980; Morgan et al, 1989). Saltin and Astrand (1967) discovered that high VO2 Max values in subjects have been related to successful running performance, because traditionally the oxygen cost of running is directly proportional to running speed.

Grant et al (1997) conducted a study involving treadmill protocols to assess all of the variables considered above and a time trial on an indoor 200m track to determine 3km-running performance. The main findings concluded that lactate variables were the best single predictors of v-3km. Further research and development of knowledge concerning the dominant physiological contributors that underlie short-distance running performance will enable greater specificity in training methods, allowing for improved competitive performance. Therefore, this study aims to investigate the relationships between Lactate Threshold, OBLA, VO2 Max and 5km Running Performance.

Experimental Hypothesis

It is to be hypothesised that participants reaching higher velocities upon reaching lactate threshold will display superior 5k running performance and that there will be a significant relationship between the two variables. It is to be hypothesised that participants reaching higher velocities upon reaching OBLA will display superior 5k running performance and that there will be a significant relationship between the two variables. It is to be hypothesised that participants with a greater Vo2 Max (oxygen capacity) will display superior 5k running performance and that there will be a moderate relationship between the two variables.

Null Hypothesis

It is to be hypothesised that there will be no significant relationship between velocity at lactate threshold and 5k running performance. It is to be hypothesised that there will be no significant relationship between velocity at OBLA and 5k running performance. It is to be hypothesised that there will be no significant relationship between VO2 Max and 5k running performance.

Method
Participants

A total of 11 Trained Club Athletes, who have been free from injury for the past three months, were tested (Age 21.451.63yrs, Height 175.092.77cm, Weight 67.865.12kg). All participants were asked to complete a consent form.

Research design

The experiment involved 2 experimental trials; a lab based test to determine Tlac, OBLA and VO2 Max and a 5k running time-trial on the athletics track, completed in a counterbalanced order with 1 week separating each trial. Both trials were conducted on the same day and at the same time of day (10:00 – 11:00 am). Laboratory conditions were 21 0.3 (C) and track conditions were 20 0.2 (C).

Procedures

Screening: Participants were screened prior to exercise to ensure they had an appropriate health status for exercise. Screening included taking resting heart rate using a heart rate monitor (Polar, T31, Finland), and blood pressure using a blood pressure monitor (Omron, MX3 Plus, Netherlands); Resting heart rate >90bpm; systolic blood pressure >140 mmHg; and diastolic blood pressure >90 mmHg.

Participant Preparation: Prior to exercise participants were prepared and fitted with the necessary equipment. A heart rate monitor (Polar, T31, Finland) was fitted and a resting blood lactate measurement taken. Prior to blood sampling, hands were washed, gloves were worn and the area of sampling was cleansed with an alcohol wipe. A small insertion was made to the participant’s earlobe using a lancet. The first blood droplet was wiped away and blood was collected using a capillary tube. The blood was then mixed and analysed using a lactate analyser (Analox Analyser Micro-Stat, P-GM7, USA). The participant was then prepared for exercise. A nose clip, breathing pneumotach and mouthpiece (Hans Rudolf, USA) were equipped. The following equipment was then attached to an automated gas analyser (Medgraphics, CPX Cardio II, USA), allowing the measurement of oxygen uptake.

Exercise Protocol: As all participants were catagorised as trained athletes, creating a homogeneous group, a warm-up speed intensity of 12km/h (Endurance Athletes) was selected, in relation to ‘The guidelines for establishing exercise intensity for the determination of TLAC during treadmill running in adults’ (Adapted from Jones and Doust in Eston And Reilly, 2001) (Appendix 1.2). Following a 5-minute warm-up on the treadmill (Woodway, ELG, Germany), the participants completed an incremental graded exercise test. Increments lasted 4 minutes, timed on a stopwatch (Fast Time, 1) and at the end of each increment the participant rested for a period of 1 minute, this allowed for the collection of a capillary blood sample.

The speed was increased by 1kph per increment. Upon attaining a blood lactate value of 4 mmol.L-1, the test became incremental and continuous, continuing the 1kph increase in speed but now per 2 minutes with no resting period. The participant was ran to volitional exhaustion and then asked to complete a cool-down at a running intensity below the warm-up level. Participants lactate thresholds were determined by monitoring their 2mmol point; OBLA by monitoring their 4mmol point and VO2 Max was the participant’s maximal oxygen uptake from the protocol.

Statistical analyses

The dependant variables Heart Rate (HR), Rating Of Perceived Exertion (RPE), and Blood Lactate (BLa) were recorded at each of the workload intervals. Atmospheric pressure (mmHg) and air temperature (C) were recorded using a barometer and thermometer and remained constant throughout the experiment. SPSS was used to determine correlations between Velocity at Tlac (Kph), Velocity at OBLA (Kph), VO2 Max and 5k Running performance (seconds); Paired Sample T Test was used to determine the significance of relations between Mean 5k Velocity and Velocity at OBLA. Significance level was set at P ≤ 0.05.

Results

The research experiment of the 11 participants provided a number of important variable measurements of which can be analysed.

Table 1. Mean and Standard Deviation of Physiological Variables. | Velocity at LT (km/h)| Velocity at OBLA (Km/h)| VO2 max (ml/kg/min) | 5k time (secs)| 5k time (mins)| 5k Running Velocity (km/h)| Mean| 15.18| 16.76| 59.10| 1097.09| 18.28| 16.55|

Figure 1. The relationship between v-Tlac and 5k Running Performance.

Table 1. Figure 1. Displays the Velocity at Lactate Threshold results for all 11 participants for the duration of the experiment. Participant’s averaged a Velocity of 15.18 1.5km/h upon reaching Lactate Threshold. There was a high, significant, negative correlation between Velocity at LT (mean ± SD = 15.18 ± 1.5km/h) and 5k Running performance (mean ± SD = 1097.09 ± 108.02sec) of the trained athletes: rho = -.664, N = 11, p = .013, (one-tailed).

Figure 2. The relationship between v-OBLA and 5k Running Performance.

Table 1. Figure 2. Displays the Velocity at OBLA results for all 11 participants for the duration of the experiment. Participant’s averaged a Velocity of 16.76 1.6km/h upon reaching OBLA. There was a very high, significant, negative correlation between Velocity at OBLA (mean ± SD = 16.76 ± 1.60 km/h) and 5k Running Performance (mean ± SD = 1097.09 ± 108.02 sec) of the trained athletes: rho = -.770, N = 11, p = .003, (one-tailed).

Figure 3. The relationship between VO2 Max and 5k Running Performance.

Table 1. Figure 3. Displays the VO2 Max results for all 11 participants for the duration of the experiment. Participant’s averaged a VO2 Max of 59.10 3.54ml/kg/min. There was a very high, significant, negative correlation between VO2max (mean ± SD = 59.10 ± 3.54 ml/kg/min) and 5k Running Performance (mean ± SD = 1097.09 ± 108.02sec) of the trained athletes: rho = -.712, N = 11, p = .007, (one-tailed).

Figure 4. Relationship between Mean 5k Running Velocity and Velocity at OBLA.

The dependent t-test showed that there were statistically no-significant differences between mean velocity (mean ± SD = 16.55 ± 1.57 Nm) and velocity at OBLA (mean ± SD = 16.76 ± 1.60 Nm); t = .692, df = 10, p = .511, (two-tailed).

Discussion

The main finding of the study was that v-OBLA was strongly related to 5k running performance. A simple correlation of v-OBLA and 5km running performance presented high significance (r= -.770; P < 0.01). The correlation between VO2max and 5km running performance in the present study was also highly significant (r= -.712; P < 0.01), succeeding the significance hypothesised and superseding the significance of v-Tlac (r= -.664; P < 0.05). These results agree with that of previous studies expressing high relationships between lactate variables and running performance (Allen et al, 1985; Farrell et al, 1979; Hagberg and Coyle, 1983; Kumagai et al, 1983), and closely relate to a fairly recent study performed by Yoshida et al, (1993), which conveyed simple correlation results of 0.77 and 0.78 between v-Tlac, v-OBLA and 3k running performance. Running velocities at Tlac and OBLA are subjective to a variety of factors, including muscle fibre type.

Further research by Costill et al, (1976) discovered that elite endurance runners have a high proportion of Type I fibres, which have subsequently been linked to low blood lactate concentrations at given work rates (Tesch et al, 1978). The high relationship of lactate variables to 5km running performance suggests that success in distance running can be determined by performance at the highest possible running velocity that can be attained without the accumulation of blood lactate; when velocity exceeds this and lactate production rises, acidosis occurs as a result of glycolysis, which has been proven to cause decreases in force production, consequently affecting performance (Donald son and Hermansen, 1978; Fabiato and Fabiato, 1978).

The correlation between VO2 Max and 5km running performance exceeded the significance found between the two variables in present studies (Hagberg and Coyle, 1983). Literature considering this topic area documents that endurance performance is habitually more highly correlated with lactate variables as appose to VO2 Max (Jacobs, 1986). Studies of well-trained athletes have evidenced that VO2 Max can remain relatively stable throughout the duration of a competitive season, despite athletes displaying changes in performance (Galy et al, 2003; Jones and Carter, 2000). This indicates that VO2 Max isn’t perceptive enough to determine transient improvements in performance, and shouldn’t be solely used as a predictor of endurance running performance.

The dependent testing of mean 5km velocity and v-OBLA documented that there were no significant differences between the two (p = 0.511). This suggests participants were running at approximately the highest velocity that they could attain without the accumulation of blood lactate. The study of Usaj (2000) supports that when velocity exceeds v-OBLA, lactate fluctuations exceed steady conditions and athletes experience fatigue earlier. The variance figures between v-OBLA, v-Tlac and running performance (R2 = 59.3 per cent; R2 = 44.1 per cent) are considerably lower than previous studies, however these still suggest that blood lactate variables must contribute to running performance.

Yoshida et al (1989) reported large portions on common variance between v-OBLA, v-Tlac and running performance (R2 = 88.6 per cent; R2 = 72.8 per cent). Study implications included the inefficiency of obtaining lactate measurements within the time allocation, possibly causing variable results, and an occasional equipment failure when obtaining heart rate measurements. In addition to the variables tested, previous studies have found a relationship between running economy and endurance performance (Ramsbottom et al, 1987; Grant et al, 1997). This may be an area to examine in future research.

Conclusion

The study concludes that in a heterogeneous group of 11 trained endurance athletes, blood lactate variables are the most highly valid and reproducible predictors for 5km running performance, strongly supported by previous research. Contrastingly, although VO2 max results were highly significant, they failed to correlate with previous research and it is to be suggested that VO2 max can only be considered as a moderate alternative predictor.

References

Australian Sports Commission. Physiological Tests for Elite Athletes. Champaign, IL: Human Kinetics, 2000.

Allen, W.K., Seals, D.R., Hurley, B.F., Ehsani, A.A., and Hagberg, J.M., (1985). Lactate threshold and distance running performance in young and older endurance athletes. J. Appl. Physiol. 58, 1281–1284.

Bassett, D.R., & Howley, E.T., (2000). Limiting factors for maximum oxygen uptake and determinants of endurance performance. Medicine and Science in Sport and Exercise. 32, 70-84.

Conley, D.L., and Krahenbuhl, G.S., (1980). Running economy and distance running performance of highly trained athletes. Med. Sci. Sports Exercise. 12, 357-360.

Costill, D.L., Thomason, H., and Roberts, E., (1973). Fractional utilization of the aerobic capacity during distance running. Med. Sci. Sports. 5, 248-252.

Coyle, E.F., Martin, W.H., Ehsani, A.A., Hagberg, J.M., Bloomfield, S.A., Sinacore, D.R., and Holloszy, J.R., (1983). Blood lactate threshold in some well-trained ischemic heart disease patients. J. Appl. Physiol. 54, 18-23.

Coyle, E.F., Coggan, A.R., Hopper, M.K., and Walters, T.J., (1988). Determinants of endurance in well-trained cyclists. J. Appl. Physiol. 64, 2622–2630.

Donaldson, S.K.B., and Hermansen, L., (1978). Differential, direct effects of HI on Ca2″-activated force of skinned fibers from the soleus, cardiac and adductor magnus muscles of rabbits. European Journal of Physiology. 376, 55-65.

Duggan, A., and Tebbutt, S.D., (1990). Blood lactate at 12 km/h and vOBLA as predictors of run performance in non-endurance athletes. International Journal of Sports Medicine. 11, 111-115.

Fabiato, A., and Fabiato, F., (1978). Effects of pH on the myofilaments and the sarcoplasmic reticulum of skinned cells from cardiac and skeletal muscles. Journal of Physiology. 276, 233-255.

Farrell, P.A., Wilmore, J.H., Coyle, E.F., Billing, J.E., and Costill, D.L., (1979). Plasma lactate accumulation and distance running performance. Med. Sci. Sports. 11, 338-344.

Foster, C., Costill, D.L., Daniels, J.T. and Fink, W.J. (1978). Skeletal muscle enzyme activity, ® bre composition and ÇV O2 max in relation to distance running performance. European Journal of Applied Physiology. 39, 73-80.

Galy, O., Manetta, J., Coste, O., Maimoun, L., Chamari, K., and Hue, O.,
(2003). Maximal oxygen uptake and power of lower limbs during a competitive season in triathletes. Scandinavian Journal of Medicine and Science in Sports. 13, 185–193. Grant, S., Craig, I., Wilson, J., and Aitchinson, T., (1997). The relationship between running performance and selected physiological variables. Journal of Sport Sciences. 15, 403-410.

Hagberg, J.M., and Coyle, E.F., (1983). Physiological determinants of endurance performance as studied in competitive racewalkers. Med. Sci. Sports Exercise. 15, 287-289.

Jacobs,I., (1986). Blood lactate Implications for training and sports performance. Sports Med. 3, 10-25.

Jones, A.M., and Carter, H., (2000). The effect of endurance training on parameters of aerobic fitness. Sports Medicine. 29, 373–386.

Kumagai, S., Tanaka, K., Matsuura, Y., Matsuzaka,
A., Hirakoba, K. and Asano, K., (1983). Relationships of anaerobic threshold and the onset of blood lactate accumulation with endurance performance. European Journal Of Applied Physiology. 52, 51-56.

Lafontaine, T.P., Londeree, B.R., and Spath, W.K., (1982). The maximal steady state versus selected running events. Med. Sci. Sports Exercise. 13, 190-192.

Morgan, D.W., Baldini, S.D., and Martin, P.E., (1989). VO2max among well-trained male runners. Medicine and Science in Sports and Exercise. 21, 78-83.

Ramsbottom, R., Phil, M., Nute, M.G.L., and Williams C., (1987). Determinants Of Five Kilometre Running Performance In Active Men and Women. British Journal of Sports Medicine. 21, 9-13.

Robergs, R.A., & Roberts, S., (1997). Exercise Physiology: Exercise, performance, and clinical applications. St Louis, Missouri: Mosby.

Saltin, B., and Astrand, P.O., (1967). Maximal Oxygen Uptake in Athletes. Journal of Applied Physiology. 23, 353-358.

Tesch, P., Sjodin, B., and Karlsson, J., (1978). Relationship between lactate accumulation, LDH activity, LDH isozyme and fiber type distribution in human skeletal muscle. Acta Physiologica Scandinavica. 103, 40-46.

Ušaj, A., (2000). The application of criterion OBLA in prescribing running endurance training intensity is limited. KinSI. 6, 57–62.

Yoshida, T., Udo, M., Iwai, K., , Muraoka, I., Tamaki, K., Yamaguchi, T., and Chida, M., (1989). Physiological determinants of race walking performance in female race walkers. British Journal or Sports Medicine. 23, 250-254.

Yoshida, T., Udo, M., Iwai, K., Chida, M., Ichioka, M., Nakadomo, F., and Yamaguchi, T., (1990). Significance of contribution of aerobic and anaerobic components to several distance running performances in female athletes. European Journal of Applied Physiology. 60, 249-253.

Yoshida, T., Udo, M., Iwai, K., and Yamaguchi, T., (1993). Physiological characteristics related to endurance running performance in female distance runners. Journal of Sports Sciences. 11, 57-62.

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