ArticlePDF AvailableLiterature Review

Lactate Threshold Concepts How Valid are They?

Authors:

Abstract and Figures

During the last nearly 50 years, the blood lactate curve and lactate thresholds (LTs) have become important in the diagnosis of endurance performance. An intense and ongoing debate emerged, which was mainly based on terminology and/or the physiological background of LT concepts. The present review aims at evaluating LTs with regard to their validity in assessing endurance capacity. Additionally, LT concepts shall be integrated within the 'aerobic-anaerobic transition' - a framework which has often been used for performance diagnosis and intensity prescriptions in endurance sports. Usually, graded incremental exercise tests, eliciting an exponential rise in blood lactate concentrations (bLa), are used to arrive at lactate curves. A shift of such lactate curves indicates changes in endurance capacity. This very global approach, however, is hindered by several factors that may influence overall lactate levels. In addition, the exclusive use of the entire curve leads to some uncertainty as to the magnitude of endurance gains, which cannot be precisely estimated. This deficiency might be eliminated by the use of LTs. The aerobic-anaerobic transition may serve as a basis for individually assessing endurance performance as well as for prescribing intensities in endurance training. Additionally, several LT approaches may be integrated in this framework. This model consists of two typical breakpoints that are passed during incremental exercise: the intensity at which bLa begin to rise above baseline levels and the highest intensity at which lactate production and elimination are in equilibrium (maximal lactate steady state [MLSS]). Within this review, LTs are considered valid performance indicators when there are strong linear correlations with (simulated) endurance performance. In addition, a close relationship between LT and MLSS indicates validity regarding the prescription of training intensities. A total of 25 different LT concepts were located. All concepts were divided into three categories. Several authors use fixed bLa during incremental exercise to assess endurance performance (category 1). Other LT concepts aim at detecting the first rise in bLa above baseline levels (category 2). The third category consists of threshold concepts that aim at detecting either the MLSS or a rapid/distinct change in the inclination of the blood lactate curve (category 3). Thirty-two studies evaluated the relationship of LTs with performance in (partly simulated) endurance events. The overwhelming majority of those studies reported strong linear correlations, particularly for running events, suggesting a high percentage of common variance between LT and endurance performance. In addition, there is evidence that some LTs can estimate the MLSS. However, from a practical and statistical point of view it would be of interest to know the variability of individual differences between the respective threshold and the MLSS, which is rarely reported. Although there has been frequent and controversial debate on the LT phenomenon during the last three decades, many scientific studies have dealt with LT concepts, their value in assessing endurance performance or in prescribing exercise intensities in endurance training. The presented framework may help to clarify some aspects of the controversy and may give a rationale for performance diagnosis and training prescription in future research as well as in sports practice.
Content may be subject to copyright.
Terms and Conditions for Use of PDF
The provision of PDFs for authors’ personal use is subject to the following Terms &Conditions:
The PDF provided is protected by copyright. All rights not specifically granted in these Terms &Conditions are expressly
reserved. Printing and storage is for scholarly research and educational and personal use. Any copyright or other notices or
disclaimers must not be removed, obscured or modified. The PDF may not be posted on an open-access website (including
personal and university sites).
The PDF may be used as follows:
to make copies of the article for your own personal use, including for your own classroom teaching use (this includes posting
on a closed website for exclusive use by course students);
to make copies and distribute copies (including through e-mail) of the article to research colleagues, for the personal use by
such colleagues (but not commercially or systematically, e.g. via an e-mail list or list serve);
to present the article at a meeting or conference and to distribute copies of such paper or article to the delegates attending
the meeting;
to include the article in full or in part in a thesis or dissertation (provided that this is not to be published commercially).
This material is the copyright of the original publisher.
Unauthorised copying and distribution is prohibited.
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
Lactate Threshold Concepts
How Valid are They?
Oliver Faude,
1,2
Wilfried Kindermann
2
and Tim Meyer
1,2
1 Institute of Sports Medicine, University Paderborn, Paderborn, Germany
2 Institute of Sports and Preventive Medicine, University of Saarland, Saarbru
¨cken, Germany
Contents
Abstract................................................................................. 469
1. Historical Remarks on Endurance Performance Diagnosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 470
2. Incremental Exercise Testing and the Interpretation of Blood Lactate Curves . . . . . . . . . . . . . . . . . . . 471
2.1 The Entire Blood Lactate Curve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471
2.1.1 Test Design and Data Treatment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 472
2.1.2 Methodology of Blood Lactate Determination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 472
2.2 A Framework for Endurance Diagnosis and Training Prescriptions. . . . . . . . . . . . . . . . . . . . . . . . . . 473
3. Validation of Lactate Thresholds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 474
3.1 Competition Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 474
3.2 The Maximal Lactate Steady State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 474
4. Lactate Threshold Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 475
4.1 Located Lactate Threshold Concepts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 475
4.1.1 Aerobic Lactate Thresholds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 475
4.1.2 Anaerobic Lactate Thresholds. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 476
4.2 Lactate Thresholds and (Simulated) Competition Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477
4.3 Lactate Thresholds and Maximal Lactate Steady State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480
5. Conclusions and Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484
Abstract During the last nearly 50 years, the blood lactate curve and lactate
thresholds (LTs) have become important in the diagnosis of endurance per-
formance. An intense and ongoing debate emerged, which was mainly based
on terminology and/or the physiological background of LT concepts. The
present review aims at evaluating LTs with regard to their validity in assessing
endurance capacity. Additionally, LT concepts shall be integrated within the
‘aerobic-anaerobic transition’ a framework which has often been used for
performance diagnosis and intensity prescriptions in endurance sports.
Usually, graded incremental exercise tests, eliciting an exponential rise in
blood lactate concentrations (bLa), are used to arrive at lactate curves. A shift
of such lactate curves indicates changes in endurance capacity. This very
global approach, however, is hindered by several factors that may influence
overall lactate levels. In addition, the exclusive use of the entire curve leads to
some uncertainty as to the magnitude of endurance gains, which cannot be
precisely estimated. This deficiency might be eliminated by the use of LTs.
The aerobic-anaerobic transition may serve as a basis for individually
assessing endurance performance as well as for prescribing intensities in
REVIEW ARTICLE Sports Med 2009; 39 (6): 469-490
0112-1642/09/0006-0469/$49.95/0
ª2009 Adis Data Information BV. All rights reserved.
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
endurance training. Additionally, several LT approaches may be integrated
in this framework. This model consists of two typical breakpoints that are
passed during incremental exercise: the intensity at which bLa begin to rise
above baseline levels and the highest intensity at which lactate production
and elimination are in equilibrium (maximal lactate steady state [MLSS]).
Within this review, LTs are considered valid performance indicators when
there are strong linear correlations with (simulated) endurance performance.
In addition, a close relationship between LT and MLSS indicates validity
regarding the prescription of training intensities.
A total of 25 different LT concepts were located. All concepts were divided
into three categories. Several authors use fixed bLa during incremental
exercise to assess endurance performance (category 1). Other LT concepts
aim at detecting the first rise in bLa above baseline levels (category 2). The
third category consists of threshold concepts that aim at detecting either the
MLSS or a rapid/distinct change in the inclination of the blood lactate curve
(category 3).
Thirty-two studies evaluated the relationship of LTs with performance in
(partly simulated) endurance events. The overwhelming majority of those
studies reported strong linear correlations, particularly for running events,
suggesting a high percentage of common variance between LT and endurance
performance. In addition, there is evidence that some LTs can estimate the
MLSS. However, from a practical and statistical point of view it would be of
interest to know the variability of individual differences between the
respective threshold and the MLSS, which is rarely reported.
Although there has been frequent and controversial debate on the LT
phenomenon during the last three decades, many scientific studies have dealt
with LT concepts, their value in assessing endurance performance or in pre-
scribing exercise intensities in endurance training. The presented framework
may help to clarify some aspects of the controversy and may give a rationale
for performance diagnosis and training prescription in future research as well
as in sports practice.
1. Historical Remarks on Endurance
Performance Diagnosis
As early as 1808, Berzelius observed that lactic
acid was produced in the muscles of hunted
stags.
[1]
About a century later, several scientists
studied the biochemistry of energy metabolism
and muscle contraction in more detail. This led to
a much deeper understanding of the formation of
lactic acid (lactate and hydrogen ions) during in-
tense exercise.
[2-5]
At that time, it was common
belief that lactic acid is a waste product of glyco-
lysis and will be formed when oxygen delivery to
exercising muscles is not sufficient and muscle
anaerobiosis occurs.
[2,6,7]
This view has been
challenged considerably during the last two dec-
ades. Anaerobic glycolysis and, thus, lactate
kinetics rather seem to be an ongoing process
even in the resting individual which is highly
related to the metabolic rate but not necessarily
to oxygen availability (for detailed review see
Gladden,
[1,8]
Brooks,
[9]
Robergs et al.
[10]
).
In the first half of the 20th century the concept
of maximum oxygen consumption as the first and
probably most common means of evaluating
aerobic endurance capacity was developed by the
working group of Nobel Laureate AV Hill.
[6]
maximal oxygen uptake (V
O
2max
) has been es-
tablished as a valuable tool to distinguish
between fit and unfit subjects. However, several
concerns were raised regarding the sensitivity of
V
O
2max
. For instance, it is difficult to discriminate
470 Faude et al.
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
between subjects of homogenous performance
levels by means of V
O
2max
.
[11-18]
In addition,
sufficient effort during whole-body work and,
therefore, adequate motivation of the investi-
gated subject is necessary to appropriately de-
termine V
O
2max
. Particularly in clinical settings
with diseased patients, whole-body exhaustion is
difficult to attain or is even avoided because of
the risk of adverse events.
[19,20]
Therefore, attempts have been made to estab-
lish sub-maximal parameters to assess cardio-
respiratory fitness in patients and athletes. Early
research by the working group of Hollmann
established the so-called ‘point of optimum ven-
tilatory efficiency’ corresponding to the first in-
crease in the ventilatory equivalent of oxygen
and of arterial lactate concentrations during
incremental exercise.
[19,21]
A few years later,
Wasserman and McIllroy
[22]
determined this in-
tensity by plotting ventilation versus oxygen
uptake in cardiac patients and named it the
‘anaerobic threshold’ (LT
An
). At that time,
routine determination of blood lactate con-
centrations (bLa) was associated with several
difficulties and gas exchange measurements were
more common especially in clinical settings.
Therefore, it became popular to detect the LT
An
by means of gas exchange analysis.
In the 1960s, the enzymatic method for mea-
suring lactate concentrations from capillary
blood samples was developed. This led to the in-
creasing popularity of using bLa as a parameter
to assess endurance capacity as well as for clas-
sifying work rate during exercise.
[19,23,24]
In the
following years, numerous lactate threshold (LT)
concepts were developed. The number of scien-
tific studies on LTs has increased enormously up
to now and the sub-maximal course of bLa dur-
ing incremental exercise has probably become
one of the most important means in the diagnosis
of endurance performance in sports prac-
tice.
[15,16,25,26]
However, the variety of different
threshold concepts has led to considerable con-
fusion and misinterpretation.
An intense and ongoing debate emerged,
which was mainly based upon terminology
and/or the physiological background of LT con-
cepts.
[27]
Early assumptions on lactate produc-
tion and distribution in the organism have been
challenged.
[1,8-10,28]
It has been argued that bLa
increase continuously rather than show a clear
threshold during incremental exercise. Further-
more, the contribution of aerobic and anaerobic
pathways to energy production does not change
suddenly but shows a continuous transition
and, therefore, the term ‘threshold’ might be
misleading.
[29]
Against this background and to unravel the
confusion, it seems valuable to give a summary
on published LT concepts. The present review is
mainly aimed at evaluating the located LT con-
cepts with regard to their validity in assessing
aerobic endurance capacity and prescribing
training intensity. A further aim was to try
to integrate those concepts into a framework
that was originally called the aerobic-anaerobic
transition.
[30-32]
It has to be emphasized that this text focuses
on LTs only. Although a close link between lac-
tate and gas exchange markers has often been
proposed,
[21,31,33-36]
there is still controversial
debate with regard to the underlying physiologi-
cal mechanisms.
[37]
A comprehensive review on
gas exchange thresholds has recently been pub-
lished.
[31]
Additionally, it is not within the scope
of this article to exhaustively review the bio-
chemistry of glycolysis and lactate metabolism.
2. Incremental Exercise Testing and the
Interpretation of Blood Lactate Curves
2.1 The Entire Blood Lactate Curve
Usually, graded incremental exercise tests
(GXTs) are used to evaluate aerobic endurance
performance capacity. Typically, an exponential
rise in bLa during incremental exercise testing
can be observed (figure 1). The issue of interest is
to interpret the resulting lactate curve with regard
to endurance capacity. It is generally accepted
that a rightward shift of the lactate curve (lower
bLa at given workload) can be interpreted in
terms of an improved endurance capacity
[38-40]
and, in contrast, a shift to the left (higher bLa at
given workload) is usually considered to re-
present worsening endurance capacity.
[41]
Validity of Lactate Thresholds 471
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
Overall lactate levels are known to be influ-
enced by depleted glycogen stores (due to a low
carbohydrate diet or preceding exhaustive ex-
ercise).
[42-44]
For instance, lower bLa at the same
work rates have been reported in a glycogen-
depleted subject compared with a subject in nor-
mal condition. This may lead to a downward
shift of the lactate curve and it is important
that this is not falsely interpreted as an enhance-
ment in endurance capacity.
[45]
Furthermore,
several other factors like muscle fibre composi-
tion, glycolytic and lipolytic enzyme activity as
well as capillary or mitochondrial density might
influence blood lactate curves.
[46]
Additionally,
the entire lactate curve is dependent on several
other methodological issues, which should be ta-
ken into account when interpreting test results.
2.1.1 Test Design and Data Treatment
It is of note that the specific GXT protocol can
vary considerably with regard to starting and
subsequent work rates, work rate increments and
stage duration. A recent review focused on the
influence of varying test protocols on markers
usually used in the diagnosis of endurance per-
formance.
[47]
For instance, varying stage dura-
tion or work rate increments may lead to relevant
differences in blood lactate curves and LTs.
[48-50]
A possible reason might be the time allowed for
lactate diffusion in the blood until the next work
rate increment.
[47]
In addition, there has been great debate on the
best fitting procedure for the obtained bLa data
set. For instance, a single-
[51]
or double-phase
model
[52]
using two or three linear regression
segments, a double-log model,
[53]
a third-order
polymonial
[54]
or an exponential function
[55]
have
been used in previous studies. Up to now, no
generally accepted fitting procedure has been
established.
[47]
Thus, it seems appropriate that
test design as well as data fitting procedures
should be chosen (and reported) as has been
originally described for a certain LT.
2.1.2 Methodology of Blood Lactate Determination
From a methodological point of view, the site
(earlobe, fingertip) as well as the method (venous,
arterial, capillary) of blood sampling
[56,57]
and
the laboratory methods (lactate analyser, ana-
lysed blood medium)
[58-60]
may also affect the test
result. Samples taken from the earlobe have uni-
formly been shown to result in lower bLa than
samples taken from the fingertip.
[57,61,62]
With
regard to the analysed blood medium, plasma
values were considerably higher than whole
venous lactate concentrations, with capillary
values lying in between.
[48,56,63-65]
In addition,
several studies reported partly considerable dif-
ferences between various lactate analysers (port-
able field vs laboratory analysers, amperometric
vs photometric method) and under various cli-
matic conditions.
[58,66-69]
The analysis of the whole blood lactate curve is
a very global approach to evaluating endurance
capacity. On the one hand, this approach is af-
fected by the above-mentioned factors on overall
lactate levels. On the other hand, the use of
the entire curve leads to some uncertainty as to
the magnitude of endurance gains that cannot be
precisely estimated. However, the use of LTs
enables a quantitative evaluation of changes in
endurance performance. In addition, the ideal LT
concept would not be affected by the above-
mentioned factors. There is evidence that approaches
that analyse relative changes in bLa during GXTs
may be favourable compared with the use of
absolute lactate values in this regard.
[56,67]
10
8
6
4
2
Blood lactate concentration (mmol/L)
0
Work intensity
MLSS = anaerobic
threshold
Aerobic threshold
Aerobic-
anaerobic
transition
Moderate-/
high-intensity
endurance
training
Regenerative/
low-intensity
endurance
training
Interval
training
sessions
Fig. 1. A typical lactate-workload plot including the aerobic-
anaerobic transition as a framework to derive endurance training
intensities for different intensity zones. MLSS =maximal lactate
steady state.
472 Faude et al.
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
2.2 A Framework for Endurance Diagnosis
and Training Prescriptions
In 1979, Kindermann et al.
[30]
introduced
the concept of the aerobic-anaerobic transition
as a framework for performance diagnosis
and training prescription in endurance sports
(figure 1). Since then, this framework has been
adopted, applied and refined by several
scientists either using lactate or gas exchange
markers.
[16,26,31,33,34,46,70-75]
This model consists of two typical breakpoints
that are passed during incremental exercise. In
the low intensity range, there is an intensity at
which bLa begin to rise above baseline levels.
This intensity was originally determined using gas
exchange measurements,
[21,22]
and Wasserman
called it the ‘anaerobic threshold’. This term has
since been used for various LTs, particularly those
with a different physiological background,
[33,75]
and, thus, has caused considerable confusion.
Kindermann et al.
[30]
and Skinner and McLel-
lan
[34]
suggested this intensity be called the
‘aerobic threshold’ (LT
Aer
), because it marks the
upper limit of a nearly exclusive aerobic meta-
bolism and allows exercise lasting for hours. This
intensity might be suitable for enhancing cardio-
respiratory fitness in recreational sports, for
cardiac rehabilitation in patients or for low-
intensity and regenerative training sessions in
high level endurance athletes.
[16,25,26,32,70,76-81]
Exercise intensities only slightly above the
LT
Aer
result in elevated but constant bLa during
steady-state exercise and can be maintained for
prolonged periods of time (~4 hours at intensities
in the range of the first increase in bLa
[82-84]
and
4560 minutes at an intensity corresponding to
the maximal lactate steady state [MLSS]
[85,86]
).
Although anaerobic glycolysis is enhanced, it is
speculated that such intensities may induce a
considerable increase in the oxidative metabolism
of muscle cells.
[30,87]
Theoretically, a high stimu-
lation of oxidative metabolism for as long a per-
iod of time as is possible in this intensity range
might be an appropriate load for endurance
training. The highest constant workload that still
leads to an equilibrium between lactate produc-
tion and lactate elimination represents the MLSS.
Some authors suggested that this intensity be
called the ‘anaerobic threshold’.
[27,30,49,88]
It has been shown that the constant bLa at
MLSS is not equal in all individuals and can vary
considerably (values from 2 up to 10 mmol/L
were reported in several studies).
[50,72,86,89-93]
Beneke and von Duvillard
[94]
as well as Beneke
et al.
[95]
reported that bLa at MLSS is dependent
on the motor pattern of exercise. Therefore, it
was suggested that to determine the LT
An
, indi-
vidualized approaches rather than a fixed bLa
should be used.
[88,96,97]
The MLSS represents the upper border of
constant load endurance training.
[30,49,71,95]
Intensities above the MLSS have been used to
guide interval training sessions in different
endurance sports.
[26,31,98-102]
The intensity range between LT
Aer
and LT
An
is called the aerobic-anaerobic transition. The
described thresholds (first increase in bLa and
MLSS) have recently also been called ‘lactate
threshold and lactate turnpoint’, ‘lactate thresh-
old and anaerobic threshold’, or ‘anaerobic
threshold 1 and 2’, respectively.
[26,75,103,104]
With-
in the present review, it was decided to stick to the
originally introduced nomenclature.
[30,31,34]
There has been an exhaustive debate whether
there exist clear breakpoints in the lactate/work
rate relationship or whether lactate increase is
rather a continuous function during incremental
work.
[47]
Furthermore, the terms ‘aerobic’ and
‘anaerobic’ threshold may suggest clearly dis-
cernible physiological processes. However, these
processes are rather of a transitional nature with
aerobic and anaerobic energetic pathways always
simultaneously contributing to energy produc-
tion during both low- and high-intensity exercise.
However, the proposed model seems appropriate
both from a practical and from a didactical point
of view. In addition, there is evidence that the
described breakpoints may have some exercise
physiological relevance. It has been shown that
exercise above the MLSS is associated with an
over-proportional excretion of stress hormones
as well as of immunological markers during
constant load exercise.
[105,106]
Furthermore,
Lucia et al.
[107]
observed changes in electro-
myographical activity of the vastus lateralis and
Validity of Lactate Thresholds 473
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
rectus femoris that were coincidental with the
aerobic-anaerobic transition in 28 elite male
cyclists.
The widespread use of this model as well as
the absence of an accepted alternative was the
rationale for using this framework in the present
review to categorize published LT concepts.
3. Validation of Lactate Thresholds
3.1 Competition Performance
It is widely accepted that LTs (and the sub-
maximal course of bLa during incremental
exercise) are a criterion measure for aerobic
endurance performance.
[24,26,30,72,81,108]
In parti-
cular, it has been shown that LTs are superior to
maximal oxygen uptake when assessing en-
durance performance in homogenous groups of
athletes.
[11,12,109-111]
The obvious gold standard
to validate an LT concept is to compare it with
the most recent competition performance in an
endurance event (concurrent validity) or to assess
its value in predicting endurance performance in
future events (predictive validity). As an alter-
native to competition performance, the results of
laboratory tests simulating an endurance event
can be used. This might have the advantage of
a higher standardization and, therefore, these
test results may be more reliable. Correlations
between the test value (LT) and the validity
criterion (competition performance) can be de-
pendent on several confounding factors such
as, for example, the chosen competitive event
(duration, laboratory or outdoor, athletic track
or off-road), the sport that is evaluated as well
as sex or age group and its heterogeneity in terms
of endurance.
3.2 The Maximal Lactate Steady State
Endurance capacity can from a metabolic
point of view be regarded as the highest steady
state by energy supply from oxidative phosphor-
ylation.
[87]
Therefore, another approach to assess
aerobic endurance performance is the determi-
nation of the highest constant exercise intensity
that can be maintained for a longer period of time
without a continuous rise in bLa. This intensity
represents the MLSS, which has been shown to be
highly related to competition performance in
endurance events (r [correlation coefficient] =
0.92 with 8 km running, r =0.87 with 5 km run-
ning and r =0.84 with 40 km cycling time trial
speed, respectively).
[112-114]
The MLSS has been
defined by some authors as the ‘anaerobic
threshold’ because it represents an exercise
intensity that can be maintained without con-
siderable contribution of anaerobic metabo-
lism.
[27,30,50,72,115]
Each higher intensity results in
a clearly identifiable increase in bLa with time
during constant load work.
[50,86,88]
The gold standard for the determination of the
MLSS is performing several constant load trials
of at least 30 minutes’ duration on different days
at various exercise intensities (in the range of
5090%V
O
2max
, figure 2).
[49,50,86,116,117]
An in-
crease in bLa of not more than 1 mmol/L between
10 and 30 minutes during the constant load trials
appears to be the most reasonable procedure for
MLSS determination.
[86,115]
MLSS represents a steady state in several but
not all physiological parameters. For instance,
oxygen uptake, carbon dioxide output, respira-
tory exchange ratio and bicarbonate concentra-
tion were reported to remain nearly constant
during constant load exercise at MLSS, but
respiratory rate and heart rate significantly
increased during this time.
[85,118]
10
8
6
4
2
Blood lactate concentration (mmol/L)
0
Rest
Time (min)
10 20 30 40
MLSS
Fig. 2. The blood lactate response to several constant workload
exercises with different intensities. The highest workload during
which blood lactate concentrations can be still accepted as being
steady state is defined as the maximal lactate steady state (MLSS).
474 Faude et al.
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
In several endurance sports it is recommended
to aim at a defined metabolic strain when a
certain training stimulus is intended.
[71,73,119,120]
Therefore, it seems likely that training intensities
for endurance training can be appropriately de-
scribed when MLSS is known.
For the purposes of this review based on the
above-mentioned rationales, LTs are considered
valid as performance indicators when there are
high linear correlations with (simulated) en-
durance performance. In addition, a close
relationship between LTs and MLSS suggests
validity with regard to the prescription of training
intensities. Therefore, it is desirable that LTs
should fulfil both validity criteria.
4. Lactate Threshold Concepts
For the purposes of the present paper, the
MEDLINE database PubMed was searched for
the search terms ‘lactate threshold’, ‘aerobic
threshold’ and ‘anaerobic threshold’ combined
with either ‘endurance performance’ or ‘maximal
lactate steady state’. Additionally, the references
of the selected articles were searched for further
relevant papers. The located original publications
were searched for papers describing different LT
concepts (section 4.1), a correlation between LTs
and (simulated) endurance performance (section
4.2) or the relationship between LTs and the
MLSS (section 4.3).
4.1 Located Lactate Threshold Concepts
A total of 25 different LT concepts were
located. Two studies were excluded from the
present analysis because threshold determination
was not solely based on bLa but also took gas
exchange measurements into account.
[121,122]
All
threshold concepts were divided into three cate-
gories. Several authors used so-called fixed blood
lactate thresholds (LT
fix
) during incremental
exercise to evaluate aerobic endurance perfor-
mance. These fixed bLas were set at 2, 2.5, 3 or
4 mmol/L
[24,108,123-125]
with LT4 (4 mmol/L lac-
tate threshold, originally described by Mader
et al.
[24]
and by others later as the onset of blood
lactate accumulation [OBLA]
[108]
) being the most
frequently used method.
4.1.1 Aerobic Lactate Thresholds
Table I shows an overview of LT concepts that
could be categorized as the first rise in bLa above
baseline levels (LT
Aer
). Several researchers de-
scribed the procedure to determine this threshold
with terms like ‘‘the first significant/marked/
systematic/non-linear/sharp/abrupt sustained in-
crease in bLa above baseline’’.
[30,110,126-133,138]
Although the visual determination of the first rise
of bLa above baseline levels seems obvious and
simple, in practice it is associated with consider-
able problems because of the only slight changes
in bLa on the first steps during GXTs. Yeh
et al.
[142]
demonstrated that the visual detection
of the LT
Aer
(in that study called ‘anaerobic
threshold’) led to relevant differences between
observers. Therefore, it does not seem appropri-
ate to determine this threshold by simple visual
inspection. Thus, other methods were developed
to make threshold determination more objective.
For instance, some authors took the typical
error of their lactate analysers into account and
Table I. Lactate threshold concepts that were categorized in the
aerobic threshold category. For further explanation see text
Method and description
Work intensity or oxygen uptake
before/at which bLa begins to increase above baseline level
[110,126]
at which bLa exhibits a marked/systematic/significant/non-linear/
sharp/abrupt sustained increase above baseline
value
[30,110,127-133]
first significant elevation of lactate level (approximately 2 mmol/L)
[30,34]
before an elevation in bLa above baseline (at least 0.2 mmol/L due to
error of lactate analyser)
[123,134]
rise in delta lactate (onset of plasma lactate accumulation)
[109]
at minimum lactate equivalent (bLa divided by oxygen uptake or work
intensity)
[36,135-137]
at which plasma lactate concentration begins to increase when log
bLa is plotted against log (work intensity)
[53]
at which bLa increases 0.5 mmol/L above resting concentration
[138]
at which bLa increas es 1 mmol/L above baseline (i.e. lactate at low
intensity corresponding to 4060%V
O
2max
)
[111,139]
preceding a bLa increase by 1 mmol/L or more
[140,141]
bLa =blood lactate concentrations; V
O
2max
=maximal oxygen up-
take.
Validity of Lactate Thresholds 475
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
determined this LT as the workload 0.2 mmol/L
above the lowest exercise lactate value.
[123]
Hughson and Green
[138]
arbitrarily chose an in-
crease of 0.5 mmol/L above resting lactate con-
centrations. Another work group
[111,139]
chose a
1 mmol/L increment above lactate levels at low
intensity (~40%to 60%V
O
2max
) because it could
be determined objectively and in a standardized
manner in all subjects. Furthermore, the lowest
value when bLa is divided by work intensity or
V
O
2
has also been used as a marker for LT
Aer
(minimum lactate equivalent).
[36,135-137]
Whereas
Beaver and colleagues
[53]
used a log-log transfor-
mation to assess the first rise in bLa more objec-
tively as the intersection of two linear regressions,
Farrell et al.
[109]
plotted the difference in bLa
between two consecutive stages against work in-
tensity and determined the first rise of this rela-
tionship (onset of plasma lactate accumulation).
4.1.2 Anaerobic Lactate Thresholds
All threshold concepts that were assigned ei-
ther to the MLSS or to a rapid/distinct change in
the inclination of the blood lactate curve were
categorized as LT
An
(table II).
Originally, the LT4 was established because it
seemed to be the highest bLa that was sustainable
for a longer duration and, therefore, was regarded
as the upper border for constant load endurance
training.
[24]
It was soon recognized that a fixed
bLa does not take into account considerable
interindividual differences and that LT4 may fre-
quently underestimate (particularly in anaero-
bically trained subjects) or overestimate (in
aerobically trained athletes) real endurance capa-
city.
[88,96,97,146]
Therefore, several so-called ‘in-
dividualized’ LT concepts were developed. For
instance, Keul et al.
[96]
and Simon et al.
[97]
de-
termined the individual anaerobic threshold (IAT)
at a certain inclination of the lactate curve (tan-
gent of 51and 45, respectively). However, it
seems questionable whether the use of a fixed in-
clination may reflect individual lactate kinetics
better than a fixed bLa.
Stegmann et al.
[88]
developed a more compli-
cated model that is based on the exercise lactate
curve as well as on the lactate course during the
early recovery period. This model is based on
several assumptions regarding lactate distribu-
tion in blood and muscle compartments, lactate
diffusion through biological membranes and
lactate elimination. However, some of these pre-
mises have been challenged.
[8,147]
Berg et al.
[137]
defined the LT
An
as the inter-
section point between the tangent at the mini-
mum lactate equivalent and the linear function
Table II. Lactate threshold concepts that were categorized in the anaerobic threshold category. For further explanation see text
Threshold concept Method and description
IAT (Stegmann et al.)
[88]
Tangent to bLa curve from recovery curve where bLa is equal to the value at end of GXT
IAT (Keul et al.)
[96]
Tangent to bLa curve at 51
IAT (Simon et al.)
[97]
Tangent to bLa curve at 45
IAT (Berg et al.)
[137]
Intersection point between tangent for the minimum lactate equivalent and the linear function
for the final 90 sec of GXT
IAT (Bunc et al.)
[143]
Intersection between the exponential regression of the lactate curve and the bisector of the
tangents of the upper and lower parts of the lactate curve
IAT (Dickhuth et al.)
[36,136]
1.5 mmol/L above minimum lactate equivalent
IAT (Baldari and Guidetti)
[144]
The sec ond lactate increase of at least 0.5 mmol/L from the previous value
D
max
(Cheng et al.)
[54]
Maximal distance from bLa curve to the line formed by its endpoints
D
mod
(Bishop et al.)
[140]
Maximal distance from bLa curve to the line formed by the point before the first rise in bLa and
the value at cessation of exercise
Lactate turnpoint
[103]
The final running velocity before the observation of a sudden and sustained increase in bLa
between LT
Aer
and V
O
2max
Lactate minimum speed
[145]
Minimum in bLa during GXT after high intensity exercise
bLa =blood lactate concentration; GXT =incremental exercise test; IAT =individual anaerobic threshold; LT
Aer
=aerobic threshold;
V
O
2max
=maximal oxygen uptake.
476 Faude et al.
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
for the final 90 seconds of GXT. Similarly, Bunc
et al.
[143]
determined the LT
An
as the intersection
between the exponential regression of the lactate
curve and the bisector of the tangents on the upper
and lower parts of the regression. A comparable
model was established by Cheng et al.
[54]
and
called the D
max
method. Those authors deter-
mined the maximal perpendicular distance of the
lactate curve from the line connecting the start
with the endpoint of the lactate curve. It is ob-
vious that these threshold models are dependent
on the start intensity as well as the maximal effort
spent by the subjects. To eliminate the influence
of the start point of the GXT, Bishop et al.
[140]
connected the LT
Aer
with the endpoint of the
lactate curve and observed that this modified
D
max
threshold (D
mod
) was also highly correlated
with performance during a 1-hour time trial in 24
female cyclists.
Tegtbur et al.
[145]
developed the so-called lac-
tate minimum test. This test starts with a short
supramaximal exercise leading to high bLa. A
short rest period (about 8 minutes)
[145]
should
allow for an equilibrium between muscle and
bLa. Immediately after this rest period, a stan-
dard incremental exercise test is conducted. After
an initial fall of bLa at low exercise intensities,
bLa begins to rise again. The lowest point of the
lactate curve, the lactate minimum speed (LMS),
is assumed to mark the LT
An
. This procedure has
recently been criticized because standardization
is difficult.
[112,148]
For instance, the induced acido-
sis prior to the incremental test is unlikely to be
uniform for different subjects. Additionally, initial
intensity as well as stage increment and duration
seem to affect LMS. Furthermore, supramaximal
exercise might be contraindicated in some in-
stances, for example in cardiac patients or in ath-
letes at some time points during their training.
Baldari and Guidetti
[144]
defined the IAT as
the workload corresponding to the second lactate
increase of at least 0.5 mmol/L with the second
increase greater than or equal to the first one. A
limitation to this approach is that only discrete
stages according to the test protocol can be
identified as threshold workload. Additionally,
those authors determined the IAT by plotting
each lactate value against the preceding work-
load. This was claimed to be done because during
3-minute stages no steady-state lactate level could
be reached
[147]
and, therefore, it was hypothesized
that a lactate value at a given 3-minute stage
would represent the realistic value of the previous
stage.
From empirical observations, the work group
of Dickhuth et al.
[36,135,136]
estimated the IAT
at a blood lactate concentration 1.5 mmol/L
above the minimum lactate equivalent (i.e. above
LT
Aer
). Finally, the lactate turnpoint (LTP)
has been defined as the final running velocity
before the observation of a sudden and sus-
tained increase in bLa between LT
Aer
and
V
O
2max
.
[103]
Reproducibility of the velocity or power out-
put at LTs has been reported to be high (r >0.9,
independent of whether LT
fix
,LT
Aer
or LT
An
were analysed).
[52,149-152]
For V
O
2
at LTs, relia-
bility coefficients seem to be slightly lower
(r =0.80.9).
[150,152,153]
4.2 Lactate Thresholds and (Simulated)
Competition Results
Thirty-eight studies were located that com-
pared LT values with performance in endurance
events or simulated competitions. Six studies
were excluded from the analysis. Three of these
studies compared an LT obtained during cycling
exercise with running performance,
[110,154,155]
two studies only reported LT as a fraction of
V
O
2max
,
[11,156]
and one study reported correlations
with time-to-exhaustion in an open-end interval
programme.
[157]
A total of 32 studies were thus
included in this analysis.
Eighteen studies evaluated the correlation of
the work intensity (running velocity or V
O
2
)at
various LTs with performance in running compe-
titions of different distances (800 m up to mara-
thon; table III).
[108,109,112,123,124,129-132,134,135,158-164]
Competition distances from 0.8 to 3.2 km, from
5 km to 16.1 km and from 21.1 to 42.2 km were
subsumed as correlates of short-, middle- and
long-distance endurance events. The main result
was that nearly all studies reported high correla-
tion coefficients with (simulated) competition
results. These results were confirmed by Weltman
Validity of Lactate Thresholds 477
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
et al.,
[123,134]
who cross-validated the obtained
regression equations and found high correlation
coefficients between actual and predicted scores.
There is a tendency for higher correlations with
longer endurance events (0.430.93 in short-term
events vs 0.680.98 over the long-distance
competitions). Additionally, correlations tended
to be higher for LT
fix
and LT
An
compared with
LT
Aer
. This might be due to the average intensity
in running events being higher than the intensity
Table III. Correlation coefficients between lactate thresholds and running performance over various distances
Threshold concept 0.83.2 km 5 km16.1 km 19.342.2 km
vV
O
2
vV
O
2
vV
O
2
LT
fix
0.82
[135]
0.88
[123]
0.86
[123]
0.85
[123]
0.87
[134]
0.85
[134]
0.84
[134]
0.93
[158]
0.78
[132]
0.68
[131]
0.85
[131]
0.88
[131]
0.79
[123]
0.75
[123]
0.75
[123]
0.72
[134]
0.74
[134]
0.75
[134]
0.73
[158]
0.60
[132]
0.51
[131]
0.55
[131]
0.69
[131]
0.88
[135]
0.91
[135]
0.91
[159]
0.93
[159]
0.91
[159]
0.84
[159]
0.91
[159]
0.94
[159]
0.83
[160]
0.81
[112]
0.95
[163]
0.94
[163]
0.90
[159]
0.92
[159]
0.92
[159]
0.83
[159]
0.88
[159]
0.93
[159]
0.86
[163]
0.74
[163]
0.91
[135]
0.81
[135]
0.98
[124]
0.98
[124]
0.98
[124]
0.68
[129]
0.96
[108]
0.91
[163]
0.92
[163]
0.76
[161]
0.83
[163]
0.73
[163]
Median (minmax) 0.85 (0.680.93) 0.73 (0.510.79) 0.91 (0.810.95) 0.89 (0.740.93) 0.92 (0.680.98) 0.76 (0.730.83)
LT
Aer
0.74
[135]
0.85
[123]
0.70
[134]
0.93
[158]
0.77
[132]
0.43
[131]
0.65
[131]
0.70
[131]
0.91
[109]
0.77
[123]
0.61
[134]
0.84
[158]
0.69
[132]
0.77
[131]
0.66
[131]
0.64
[131]
0.85
[109]
0.62
[162]
0.66
[162]
0.58
[162]
0.73
[135]
0.79
[135]
0.78
[160]
0.96
[109]
0.97
[109]
0.79
[130]
0.83
[130]
0.79
[130]
0.84
[130]
0.83
[130]
0.81
[130]
0.93
[112]
0.94
[163]
0.92
[163]
0.92
[163]
0.89
[163]
0.87
[163]
0.85
[163]
0.89
[109]
0.91
[109]
0.84
[162]
0.83
[162]
0.79
[162]
0.69
[162]
0.92
[162]
0.79
[162]
0.76
[130]
0.77
[130]
0.84
[130]
0.81
[130]
0.82
[130]
0.88
[130]
0.72
[163]
0.56
[163]
0.66
[163]
0.52
[163]
0.81
[163]
0.69
[163]
0.76
[135]
0.81
[135]
0.78
[129]
0.97
[109]
0.98
[109]
0.90
[163]
0.91
[163]
0.87
[163]
0.86
[163]
0.83
[163]
0.77
[163]
0.91
[109]
0.89
[109]
0.69
[163]
0.52
[163]
0.66
[163]
0.42
[163]
0.80
[163]
0.65
[163]
Median (minmax) 0.74 (0.430.93) 0.66 (0.580.85) 0.84 (0.730.97) 0.79 (0.450.92) 0.86 (0.760.98) 0.68 (0.420.91)
LT
An
0.88
[135]
0.91
[135]
0.92
[135]
0.86
[160]
0.83
[112]
0.93
[163]
0.91
[163]
0.94
[163]
0.90
[163]
0.76
[164]
0.73
[164]
0.83
[163]
0.70
[163]
0.81
[163]
0.66
[163]
0.45
[164]
0.45
[164]
0.93
[135]
0.93
[135]
0.90
[163]
0.91
[163]
0.90
[163]
0.89
[163]
0.68
[161]
0.83
[163]
0.71
[163]
0.81
[163]
0.67
[163]
Median (minmax) 0.88 0.91 (0.830.94) 0.76 (0.660.83) 0.91 (0.890.93) 0.71 (0.670.83)
LT
fix
=fixed lactate threshold; LT
Aer
=aerobic threshold; LT
An
=anaerobic threshold; v=velocity; V
O
2
=oxygen uptake.
478 Faude et al.
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
corresponding to the first increase in bLa. In to-
tal, the results of the analysed studies point to a
common variance of LTs and competition results
in running events between 55%and 85%.
In cycling, a total of eight studies evaluated the
relationship between LTs and (simulated) cycling
time trial performance (table IV).
[12,89,140,141,165-168]
Only one study analysed the correlation with
short-duration time trial performance (4000 m
individual pursuit) and found a high correlation
coefficient of r =0.86 in 18 male high-performance
track cyclists.
[167]
Four studies evaluated dis-
tances between 13.5 and 20 km or time trial dura-
tions between 20 and 30 minutes.
[89,165,166,168]
The
correlation coefficients in these studies were in
most cases higher (between 0.8 and 0.9) than for
the longer time trials (40 km or 6090 minutes,
r~0.7).
[140,141,165]
Overall, the results of these
studies were more heterogeneous. Correlation
coefficients between LTs and (simulated) com-
petition performance varied between r =0.23
[165]
and r =0.93.
[89]
In total, the results of the ana-
lysed studies point to a common variance of LTs
and competition results between 35%and 85%in
cycling events. However, the low number of stu-
dies and the heterogeneous results point to the
need for further carefully designed studies to
arrive at more comprehensive conclusions with
regard to the relationship of LTs and time trial
performance in cycling.
Two studies were found that analysed the re-
lationship of LT markers with mountain bike
cross-country race performance.
[169,170]
Such
races are usually conducted on a graded terrain
with considerable time spent ascending and des-
cending. Impellizzeri et al.
[170]
observed high
correlations between LT
Aer
as well as OBLA and
race time during a 31 km mountain bike race.
Whereas correlations were about 0.7 when LT
was expressed in absolute terms, correlations
became considerably higher (~0.9) when power
output at LT was expressed relative to body
mass. Similarly, Gregory et al.
[169]
reported
higher correlations between LT
Aer
and a cross-
country time trial in 11 male mountain bikers
when LT
Aer
was expressed as related to body
mass (r ~0.5 in absolute terms vs r ~0.8 relative to
body mass). This finding can be explained with
the considerable influence of bodyweight and
body composition on performance capacity in
cyclists during ascents.
[171-173]
In addition to the studies in running and
cycling, another four studies were detected
that evaluated LTs and (simulated) competition
Table IV. Correlation coefficients between lactate thresholds and cycling time trial events over various distances and times
Threshold conc ept 4 km 13.520 km; 2030 min 40 km; 6090 min
PO V
O
2
PO V
O
2
PO V
O
2
LT
fix
0.23
[165]
0.82
[166]
0.90
[166]
0.54
[165]
0.60
[141]
0.81
[140]
Median (minmax) 0.82 (0.230.90) 0.60 (0.540.81)
LT
Aer
0.86
[167]
0.67
[165]
0.88
[166]
0.86
[166]
0.91
[168]
0.88
[168]
0.91
[165]
0.59
[141]
0.61
[140]
0.69
[140]
0.65
[140]
0.93
[12]
Median (minmax) 0.86 0.88 (0.670.91) 0.65 (0.590.91) 0.93
LT
An
0.45
[165]
0.89
[166]
0.91
[166]
0.93
[89]
0.77
[165]
0.58
[141]
0.52
[141]
0.72
[141]
0.84
[140]
0.83
[140]
Median (minmax) 0.90 (0.450.93) 0.75 (0.520.84)
LT
Aer
=aerobic threshold; LT
An
=anaerobic threshold; LT
fix
=fixed lactate threshold; PO =power output; V
O
2
=oxygen uptake.
Validity of Lactate Thresholds 479
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
performance. Two of these studies analysed com-
petitive race walkers. Yoshida et al.
[174]
found
correlation coefficients for OBLA as well as for
LT
Aer
of 0.94 and 0.85, respectively, with walking
pace during a 5 km road race in eight female race
walkers. Similar results were observed by Hagberg
and Coyle
[111]
in a heterogeneous group of race
walkers with correlation coefficients of 0.94 and
0.82 for velocity and oxygen uptake at LT
Aer
in
a 20 km race walking performance.
Two studies dealt with rowing performance
and LTs. Whereas Ingham et al.
[175]
observed high
correlations (r =0.860.92) between work rate at
fixed and aerobic LTs and 2000 m ergometer
performance in 41 rowers of different categories,
Cosgrove et al.
[176]
found considerably lower
correlations (r =0.390.73) in 13 male rowers.
To summarize, the overwhelming majority of
published studies on the relationship between
LTs and endurance performance showed strong
correlations, particularly for running events. This
supports findings of earlier training studies that
found training-induced improvements in compe-
titive performance significantly correlated with
improvements in LTs.
[130,162]
Although it seems
likely that other influences such as central ner-
vous system processes may have regulatory and
decisive characteristics in endurance events as it
was recently claimed,
[177]
peripheral metabolic
adaptations highly related to the LT
[46]
seem to
be a necessary and important prerequisite for
aerobic endurance performance.
4.3 Lactate Thresholds and Maximal Lactate
Steady State
MLSS determination has become very popu-
lar in performance diagnosis in several endurance
sports. Thus, numerous studies have dealt with
the problem of an adequate estimation of MLSS
during one single laboratory visit. For instance,
some authors tried to estimate MLSS from
performance during all-out time trials (5 km or
40 km)
[114,178]
from physiological strain (bLa, heart
rate, ratings of perceived exertion) during stan-
dardized sub-maximal constant-load exercise
[179-182]
or from gas exchange measurements.
[183-189]
However, an overview of those studies is beyond the
scope of the present review.
There are several studies that examined the
metabolic responses during steady-state exercise
intensities related to LTs but did not analyse ex-
ercise intensities slightly above or below. Schnabel
et al.
[190]
observed average steady-state lactate
concentrations (~4.5 mmol/L) during 50-minute
runs at the IAT according to Stegmann et al.
[88]
However, no other intensity was analysed in this
investigation. Stegmann and Kindermann
[146]
compared 50-minute cycling exercise in 19 subjects
at the IAT as well as at LT4 and found steady-state
lactate levels (~4 mmol/L) during IAT trials,
whereas exercise at LT4 resulted in continuously
rising bLa (up to 9.6 mmol/L) and a premature
cessation. This is in line with findings of Oyono-
Enguelle et al.,
[191]
who similarly reported no lac-
tate steady state in three out of five subjects during
exercise at LT4. In contrast, Loat and Rhodes
[189]
found continuously increasing bLa (on average
from 3.4 mmol/L after 15 minutes to 4.6 mmol/L
after 45 minutes) and premature fatigue during
60-minute constant load trials at the IAT. However,
those authors did not use the originally described
test protocol and Heck
[50]
has shown that IAT
determination is dependent on the protocol used.
Baldari and Guidetti
[144]
compared steady-
state running at their IAT determined when lactate
values were plotted against the corresponding
exercise intensity (IAT
m
) and against the pre-
ceding intensity (IAT
a
) and found steady-state
lactate levels for IAT
a
(~4 mmol/L
-1
) but not for
IAT
m
. However, due to the determination pro-
cedure, the difference between both thresholds
was exactly one stage increment and no other
intensities in between were evaluated. Ribeiro
et al.
[192]
assessed a 40-minute steady-state cy-
cling exercise at LT
Aer
, between LT
Aer
and LT
An
(LTP), at LT
An
as well as between LT
An
and maxi-
mum. Those authors found on average steady-
state lactate levels up to LT
An
(~5 mmol/L
-1
),
whereas at the highest intensity, bLa increased
continuously and exercise had to be terminated
prematurely.
Bacon and Kern
[193]
and Tegtbur et al.
[145]
compared constant load trials at LMS and 5%
or 0.2 m/s, respectively, above the LMS. Those
480 Faude et al.
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
authors found that LMS intensity but not the
higher intensity on average resulted in a lactate
steady state. However, in the study of Bacon and
Kern,
[193]
the average blood lactate increase be-
tween minutes 12 and 28 during the constant load
trial at the LMS +5%intensity was 1.2 mmol/L,
and in four out of ten subjects a lactate steady
state according to the recommended criter-
ion
[72,115]
was present.
A total of 11 studies evaluated the relationship
between one or more LT concepts and MLSS
using the recommended procedure, including
several constant load trials of at least 30 minutes’
duration to determine the MLSS (table V). One
study determined MLSS with 20-minute constant
load trials.
[113]
Most researchers analysed the relationship of
LT4 with MLSS.
[49,72,90,92,112,117]
For instance,
Heck and colleagues
[49,50,72]
found strong corre-
lations between LT4 and MLSS during running
as well as during cycling exercise. However, the
fitness level of their subjects was quite hetero-
geneous and, therefore, the high correlations to
some extent might be spurious. Additionally,
they observed that the velocity at LT4 was higher
than MLSS velocity when stage duration during
the GXT was 3 minutes, whereas this was not
the case with 5-minute stages. Therefore, these
authors concluded that LT4 gives a valuable
estimate of the MLSS when stage duration is
at least 5 minutes. Also, Jones and Doust
[112]
found a high correlation between LT4 and the
MLSS in a homogenous group of trained runners
with LT4 being higher than MLSS (3-minute
stages). Lower correlations were found by
van Schuylenbergh et al.
[92]
in elite cyclists as
well as by Beneke
[117]
in a homogenous group
of rowers. Also, LT4 and MLSS did not differ
significantly with 6-minute stages,
[92]
whereas
LT4 was considerably higher than MLSS with
3-minute stages.
[117]
Lajoie et al.
[90]
evaluated
whether the intensity corresponding to 4 mmol/L
lactate during a GXT with 8-minute stages and
30 W increments is appropriate to estimate the
MLSS in nine cyclists. Average power output at
MLSS and LT4 was not significantly different.
However, because bLa at MLSS differed consi-
derably between subjects, the authors concluded
that it is unrealistic to rely on a blood lactate
value of 4 mmol/L as a universal criterion for
MLSS. Unfortunately, a more detailed analysis
regarding the correlation or individual differ-
ences between LT4 and MLSS was not reported.
Heck et al.
[49,50]
observed high correlations
between MLSS and the IAT according to
Stegmann et al.
[88]
In addition, running velocity
was not significantly different between IAT
and MLSS independent of stage duration (3 or
5 minutes), whereas in cycling IAT was about
8%higher than MLSS. Urhausen et al.
[86]
found
in runners as well as in cyclists that constant load
trials at IAT resulted on average in a lactate
steady state, whereas a 5%higher intensity led to
a continuous rise in bLa. Similarly, McLellan and
Jacobs
[91]
arrived at the conclusion that the IAT
is a valid estimate for the MLSS in most subjects,
although there exists a considerable difference in
a few cases. Unfortunately, these studies reported
no measure of correlation between IAT and
MLSS or no quantitative data on individual dif-
ferences between IAT and MLSS. In contrast to
the previously mentioned studies, Beneke
[117]
found the IAT to be considerably higher than
MLSS in nine rowers. Additionally, the correla-
tion in this study was lower than was observed
by Heck et al.
[49]
This finding might be due to
the more homogenous performance level of the
rowers as well as to the slow increment in the
chosen test protocol.
[50]
Heck et al.
[49]
and Heck
[50]
found high corre-
lations between the IAT according to Keul
et al.
[96]
and Bunc et al.
[143]
and the MLSS in run-
ning and cycling. However, the high correlations
might be partly accounted for by the hetero-
genous endurance level of the subjects. Further-
more, both thresholds were dependent on the test
protocol during the running tests (3-minute vs
5-minute stages).
The LMS was evaluated in two studies.
[89,112]
The results of these studies were contradictory.
Jones and Doust
[112]
found only a low correlation
between LMS and MLSS. Additionally, LMS
was considerably lower than MLSS. In con-
trast, LMS was not significantly different from
MLSS in the study of MacIntosh et al.
[89]
These
contrasting observations might have been due to
Validity of Lactate Thresholds 481
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
Table V. Comparison of lactate threshold concepts with MLSS determined by several constant load trials of different intensity
Threshold concept Subjects Main outcome Reference
LT4, OBLA 16 healthy
males
(running)
High correlation between LT4 and MLSS (r =0.98)
LT4 on average 0.12 m/s higher than MLSS with 3 min stages but not
with 5 min stages during GXT
Heterogenous endurance level
Heck et al.
[49,72]
22 healthy
subjects
(cycling)
Significant correlation between LT4 and MLSS (r =0.92)
LT4 on average 19.9 W higher than MLSS
Heterogenous endurance level, slow increase in power output
(+6W/min)
Heck
[50]
8 trained male
runners
High correlation (r =0.93) between OBLA and MLSS
OBLA on average 0.4 km/h higher than MLSS
Jones and
Doust
[112]
21 elite cyclists Low correlation (r =0.71) between LT4 and MLSS
No significant difference between LT4 and MLSS (MLSS 15 W higher)
Homogenous endurance level
Van Schuylenbergh
et al.
[92]
9 male rowers Significant correlation (r =0.82) between LT4 and MLSS
LT4 significan tly higher (32 W) than MLSS
Homogenous endurance level
Beneke
[117]
10 well trained
cyclists
Average power output at LT4 and MLSS was not significantly different
(282 W vs 277 W)
Strong MLSS criterion (<0.75 mmol/L from 1060 min)
No further data on correlations or intraindividual differences between
LT4 and MLSS
Lajoie et al.
[90]
IAT (Stegmann et al.
[88]
) 16 healthy
males
(running)
High correlation between IAT and MLSS (r =0.960.98)
IAT velocity on average similar to MLSS for 3 min as well as 5 min
stages during GXT
Heterogenous endurance level of subjects
Heck et al.
[49]
22 healthy
subjects
(cycling)
Significant correlation between IAT and MLSS (r =0.87)
IAT on average 15.1 W higher than MLSS
Heterogenous endurance level, slow increase in power output
(+6W/min) not corresponding to the originally described test protocol
Heck
[50]
16 trained
cyclists
14 trained
runners
CLT at and below IAT resulted on average in LSS but not CLT at
105%IAT
100%IAT does not in all individuals exactly represent MLSS
LSS was found in 6 (of 14 runners) and 9 (of 16 cyclists) at 105%IAT
No further data on correlations or intraindividual differences between
IAT and MLSS
CLT at LT4 (cycling at 104%IAT) resulted on average not in a LSS
Urhausen et al.
[86]
11 males
(cycling)
No LSS during CLT at IAT +5%V
O
2max
; only 1 LSS during CLT at IAT
+2.5%V
O
2max
Two subjects showed no LSS during CLT at IAT -7.5%V
O
2max
, all
other subjects showed LSS during CLT at IAT -2.5%V
O
2max
No further data on correlations or intraindividual differences between
IAT and MLSS
McLellan and
Jacobs
[91]
9 male rowers Significant correlation (r =0.81) between IAT and MLSS
IAT significantly higher (32 W) than MLSS
Beneke
[117]
IAT (Keul et al.
[96]
) 16 healthy
males
(running)
High correlation between IAT and MLSS (r =0.98)
IAT velocity on average 0.2 m/s higher than MLSS with 3 min stages
and slightly lower with 5 min stages during GXT
Heterogenous endurance level of subjects
Heck et al.
[49]
22 healthy
subjects
(cycling)
Significant correlation between IAT and MLSS (r =0.94)
IAT on average 21.0 W higher than MLSS
Heterogenous endurance level, slow increase in power output
(+6W/min
-1
)
Heck
[50]
Continued next page
482 Faude et al.
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
the considerably different test protocols used in
both studies. This is in line with the findings of
Carter et al.
[148]
showing that LMS is highly de-
pendent on the test protocol.
For other threshold concepts, scientific data
regarding the relationship of the threshold and
MLSS are scarce. Van Schuylenbergh et al.
[92]
found a significant correlation between the D
mod
-
threshold and MLSS, although D
mod
was sig-
nificantly lower than MLSS. In contrast, LTP
was found to be not different from MLSS on aver-
age, but it was not correlated to MLSS and the
95%limits of agreement (LoA)
[194]
of the differ-
ence between LTP and MLSS were wide.
[103]
There were also two studies that analysed the
relationship between MLSS and LT
Aer
.
[112,113]
As
could be expected, LT
Aer
was situated con-
siderably below the MLSS in both studies.
Whereas Jones and Doust
[112]
reported a high
correlation between LT
Aer
and MLSS, Haverty
et al.
[113]
did not. This might be due to short
constant load trials (20 minutes) and the strict
MLSS criterion (<0.2 mmol/L increase during the
last 10 minutes) in the latter study, which does
not sufficiently consider the time course of bLa
changes and may have led to an underestimation
of the real MLSS.
[115]
To summarize, there is evidence that some LT
concepts might be able to estimate the MLSS.
In particular, the IAT according to Stegmann
et al.,
[88]
and LT4 were repeatedly examined.
Mostly linear regressions or average lactate
courses were reported. Correlations and regres-
sions determine relative reliability of two meth-
ods but do not assess systematic bias or absolute
agreement. Furthermore, they depend greatly on
the range of values in the analysed sample.
[195]
Thus, from a practical and statistical point of
Table V. Contd
Threshold concept Subjects Main outcome Reference
IAT (Bunc et al.
[143]
) 16 healthy
males
(running)
High correlation between IAT and MLSS (r =0.980.99)
IAT velocity on average considerably higher than MLSS for 3-min
(+0.31 m/s) as well as 5 min stages (+0.14 m/s) during GXT
Heterogenous endurance level of subjects
Heck et al.
[49]
22 healthy
subjects
(cycling)
Significant correlation between IAT and MLSS (r =0.89)
IAT on average 71.5 W higher than MLSS
Heterogenous endurance level, slow increase in power output
(+6W/min)
Heck
[50]
LMS 10 trained male
runners
Low correlation (r =0.61) between LMS and MLSS
LMS on average 0.8 km/h lower than MLSS
Jones and
Doust
[112]
14 cyclists or
triathletes
LMS on average not different from MLSS
No good estimate of MLSS by LMS in three subjects
MLSS criterion: <0.7 mmol/L during last 20 min
No further data on correlations or intraindividual differences between
LMS and MLSS
MacIntosh et al.
[89]
D
mod
21 elite cyclists Significant correlation (r =0.85) between D
mod
threshold and MLSS
D
mod
threshold significantly lower (-23 W) than MLSS
Van Schuylenbergh
et al.
[92]
LTP 8 males
(running)
No correlation betwe en LTP and MLSS (r =0.18)
On average no difference between LTP and MLSS (13.7 vs 13.8 km/h)
95%LoA
[194]
=–1.8 km/h
Smith and
Jones
[103]
LT
Aer
10 trained male
runners
High correlation (r =0.94) between LT
Aer
and MLSS
LT
Aer
on average 0.6 km /h lower than MLSS
Jones and
Doust
[112]
11 male
recreational
runners
No correlation of LT
Aer
with MLSS (speed: r =-0.01; V
O
2
:r=-0.47)
LT
Aer
on average 1.1 km /h lower than MLSS
20 min CLT, but stron g MLSS criterion (<0.2 mmol/L)
Haverty et al.
[113]
CLT =constant load trial; D
mod
=maximal distance from blood lactate concentration (bLa) curve to the line formed by the point before the first
rise in bLa and the value at cessation of exercise; GXT =incremental exercise test; IAT =individual anaerobic threshold; LMS =lactate
minimum speed; LoA =limits of agreement; LSS =lactate steady state; LT4 =4 mmol/L lactate threshold; LT
Aer
=aerobic threshold;
LTP =lactate turnpoint; MLSS =maximal lactate steady state; OBLA =onset of blood lactate accumulation; r=correlation coefficient;
V
O
2max
=maximal oxygen uptake.
Validity of Lactate Thresholds 483
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
view it would be of interest to know the absolute
variability of individual differences between the
LT and MLSS. An appropriate means to report
this variability may be the mean bias and the 95%
LoA as it was described by Bland and Alt-
man.
[194]
There is only one study available that
applied this procedure.
[103]
Such a procedure
would also allow for assessing heteroscedasticity
(i.e. whether the differences depend on the mag-
nitude of the mean or in this case endurance
capacity).
[195]
Table VI shows an example calculation of the
mean bias and the 95%LoA for four different LT
concepts from raw data reported by Heck et
al.
[49,50,72]
These data show a mean bias between
0.5%and 8%, with LoA of about 10%in a run-
ning exercise. This means that for each new
subject within the study population it could be
expected (with a 95%probability) that the dif-
ference between MLSS and the respective LT is
within these LoA.
[195]
For the cycling exercise the
results are more heterogenous with greater mean
bias and LoA. However, due to the limited data
points these observations are preliminary and
should be confirmed by further research.
5. Conclusions and Perspectives
In conclusion, it can be stated that a huge
amount of evidence exists that LT concepts are of
considerable importance for the diagnosis as well
as the prediction of aerobic endurance perfor-
mance. The concept of the aerobic-anaerobic
transition may serve as a reasonable means for
performance diagnosis and intensity prescription
in endurance sports. However, there are several
open questions that should be appropriately
addressed by future research. These are:
Whereas the relationship of LTs with competi-
tion performance is well established in running
events and less strongly in cycling, there is lack
of evidence for most other endurance sports.
Scientific studies comparing LTs with MLSS
are rare and the results are partially conflict-
ing. This might be due to different methodo-
logical approaches. It is suggested that the
MLSS be assessed by the established proce-
dure using several constant load trials with
different intensities
[72,115]
and that the MLSS
be compared with a chosen LT. To do so,
measures of absolute agreement between LTs
and MLSS should be reported according
to the method introduced by Bland and
Altman.
[194]
In this context, it is important to know the basic
variability and reproducibility of the MLSS. Up
to now, no scientific data addressing this ques-
tion exist. Therefore, it is recommended to eval-
uate the variability of MLSS in future research.
Of note, this may enable an evaluation of the
differences between LT and MLSS compared
with the basic variability of the MLSS and,
thus, give more detailed information on the
quality of the MLSS estimate.
Although there has been much and con-
troversial debate on the LT phenomenon during
the last three decades, many scientific studies
have dealt with LT concepts, their value in as-
Table VI. Mean bias (difference maximal lactate steady state [MLSS]-LT) and 95%limits of agreement (LoA) for four different lactate
threshold concepts during treadmill (n =16) and cycle ergometry (n =22). Results calculated from raw data reported by Heck et al.
[49,50,72]
(with
permission)
Lactate threshold concept Treadmill ergometry
3 min stages, +0.4 m/s
Treadmill ergometry
5 min stages, +0.4 m/s
Cycle ergometry
2 min stages, +25 W
mean bias
(m/s)
LoA
(m/s)
LoA
(%)
mean bias
(m/s)
LoA
(m/s)
LoA
(%)
mean bias
(W)
LoA
(W)
LoA
(%)
LT4 -0.13 0.35 8 0.02 0.39 9-19.8 28.4 14
IAT (Keul et al.
[96]
)-0.20 0.39 9 0.06 0.35 8-21.0 22.4 11
IAT (Stegmann et al.
[88]
)-0.03 0.51 12 -0.03 0.37 9-15.0 35.0 18
IAT (Bunc et al.
[143]
)-0.33 0.33 8-0.14 0.37 9-71.4 52.8 27
IAT =individual anaerobic threshold; LT4 =4 mmol/L threshold.
484 Faude et al.
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
sessing endurance performance or in prescribing
exercise intensities in endurance training. It might
be speculated that a considerable part of the de-
bate has to be attributed to the misinterpretation
of the physiological basis of the phenomenon.
The presented framework may help to clarify the
controversy and may give a rational basis for
performance diagnosis and training prescriptions
in future research as well as in sports practice.
Acknowledgements
No sources of funding were used to assist in the prepara-
tion of this review. The authors have no conflicts of interest
that are relevant to the content of this manuscript.
References
1. Gladden LB. Lactate metabolism: a new paradigm for the
third millennium. J Physiol 2004 Jul 1; 558 (Pt 1): 5-30
2. Fletcher WM, Hopkins FG. Lactic acid in amphibian
muscle. J Physiol (London) 1907; 35: 247-309
3. Meyerhof O. Untersuchung u
¨ber die Wa
¨rmestro
¨mung der
vitalen Oxydationsvorga
¨nge. Biochem Z 1911; 5: 246-328
4. Douglas CG, Haldane JS. The regulation of normal
breathing. J Physiol 1909; 38: 420-40
5. Ryffel GH. Lactic acid metabolism: a critical review. Quart
J Med 1910; 3: 221-3
6. Hill AV, Lupton H. Muscular exercise, lactic acid and the
supply and utilization of oxygen. Quart J Med 1923; 16:
135-71
7. Margaria R, Edwards HT, Dill DB. The possible mechan-
ism of contracting and paying the oxygen debt and the
role of lactic acid in muscular contraction. Am J Physiol
1933; 106: 689-714
8. Gladden LB. Muscle as a consumer of lactate. Med Sci
Sports Exerc 2000 Apr; 32 (4): 764-71
9. Brooks GA. The lactate shuttle during exercise and
recovery. Med Sci Sports Exerc 1986 Jun; 18 (3): 360-8
10. Robergs RA, Ghiasvand F, Parker D. Biochemistry of
exercise-induced metabolic acidosis. Am J Physiol Regul
Integr Comp Physiol 2004 Sep; 287 (3): R502-16
11. Coyle EF, Coggan AR, Hopper MK, et al. Determinants of
endurance in well-trained cyclists. J Appl Physiol 1988;
64 (6): 2622-30
12. Coyle EF, Feltner ME, Kautz SA, et al. Physiological and
biomechanical factors associated with elite endurance
cycling performance. Med Sci Sports Exerc 1991 Jan;
23 (1): 93-107
13. Lucı
´a A, Pardo J, Dura
´ntez A, et al. Physiological differ-
ences between professional and elite road cyclists. Int J
Sports Med 1998; 19: 342-8
14. Impellizzeri FM, Marcora SM, Rampinini E, et al. Corre-
lations between physiological variables and performance
in high level cross-country off-road cyclists. Br J Sports
Med 2005 Oct; 39 (10): 747-51
15. Sjodin B, Svedenhag J. Applied physiology of marathon
running. Sports Med 1985 Mar-Apr; 2 (2): 83-99
16. Faria EW, Parker DL, Faria IE. The science of cycling:
physiology and training, part 1. Sports Med 2005; 35 (4):
285-312
17. Jacobs I. Blood lactate: implications for training and sports
performance. Sports Med 1986; 3 (1): 10-25
18. Conley DL, Krahenbuhl GS. Running economy and dis-
tance running performance of highly trained athletes.
Med Sci Sports Exerc 1980; 12 (5): 357-60
19. Hollmann W. 42 years ago: development of the concepts of
ventilatory and lactate threshold. Sports Med 2001; 31 (5):
315-20
20. Meyer T, Scharhag J, Kindermann W. Peak oxygen up-
take: myth and truth about an internationally accepted
reference value. Z Kardiol 2005 Apr; 94 (4): 255-64
21. Hollmann W. Ho
¨chst- und dauerleistungsfa
¨higkeit des
sportlers. Mu
¨nchen: Barth, 1963
22. Wasserman K, McIlroy MB. Detecting the threshold of
anaerobic metabolism in cardiac patients. Am J Cardiol
1964; 14: 844-52
23. Wells JG, Balke B, Van Fossan DD. Lactic acid accumu-
lation during work: a suggested standardization of work
classification. J Appl Physiol 1957 Jan; 10 (1): 51-55
24. Mader A, Liesen H, Heck H, et al. Zur Beurteilung der
sportartspezifischen ausdauerleistungsfa
¨higkeit im labor.
Sportarzt Sportmed 1976; 27: 80-8, 109-12
25. Atkinson G, Davison R, Jeukendrup A, et al. Science and
cycling: current knowledge and future directions for re-
search. J Sports Sci 2003 Sep; 21 (9): 767-87
26. Jones AM. The physiology of the world record holder for
the women
´s marathon. Int J Sports Sci Coaching 2006;
1 (2): 101-16
27. Svedahl K, MacIntosh BR. Anaerobic threshold: the con-
cept and methods of measurement. Can J Appl Physiol
2003 Apr; 28 (2): 299-323
28. Brooks GA. Anaerobic threshold: review of the concept
and directions for future research. Med Sci Sports Exerc
1985; 17 (1): 22-34
29. Myers J, Ashley E. Dangerous curves: a perspective on
exercise, lactate, and the anaerobic threshold. Chest 1997
Mar; 111 (3): 787-95
30. Kindermann W, Simon G, Keul J. The significance of the
aerobic-anaerobic transition for the determination of
work load intensities during endurance training. Eur J
Appl Physiol 1979; 42: 25-34
31. Meyer T, Lucia A, Earnest CP, et al. A conceptual frame-
work for performance diagnosis and training prescription
from submaximal gas exchange parameters: theory and
application. Int J Sports Med 2005 Feb; 26 Suppl. 1:
S38-48
32. McLellan TM, Skinner JS. The use of the aerobic threshold
as a basis for training. Can J Appl Sport Sci 1981; 6 (4):
197-201
33. McLellan TM. The anaerobic threshold: concept and
controversy. Austr J Sci Med Sport 1987; 19 (2): 3-8
34. Skinner JS, McLellan TH. The transition from aerobic to
anaerobic metabolism. Res Q Exerc Sport 1980; 51 (1):
234-48
Validity of Lactate Thresholds 485
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
35. Wasserman K, Whipp BJ, Koyl SN, et al. Anaerobic
threshold and respiratory gas exchange during exercise.
J Appl Physiol 1973; 35 (2): 236-43
36. Dickhuth HH, Yin L, Niess A, et al. Ventilatory, lactate-
derived and catecholamine thresholds during incremental
treadmill running: relationship and reproducibility. Int J
Sports Med 1999 Feb; 20 (2): 122-7
37. Peronnet F, Aguilaniu B. Lactic acid buffering, non-
metabolic CO2 and exercise hyperventilation: a cri-
tical reappraisal. Respir Physiol Neurobiol 2006 Jan 25;
150 (1): 4-18
38. Yoshida T, Udo M, Chida M, et al. Specificity of physio-
logical adaptation to endurance training in distance run-
ners and competitive walkers. Eur J Appl Physiol Occup
Physiol 1990; 61 (3-4): 197-201
39. Acevedo EO, Goldfarb AH. Increased training intensity
effects on plasma lactate, ventilatory threshold, and en-
durance. Med Sci Sports Exerc 1989; 21 (5): 563-8
40. Bosquet L, Leger L, Legros P. Methods to determine
aerobic endurance. Sports Med 2002; 32 (11): 675-700
41. Mujika I, Padilla S. Cardiorespiratory and metabolic
characteristics of detraining in humans. Med Sci Sports
Exerc 2001 Mar; 33 (3): 413-21
42. McLellan TM, Gass GC. The relationship between the
ventilation and lactate thresholds following normal, low
and high carbohydrate diets. Eur J Appl Physiol Occup
Physiol 1989; 58 (6): 568-76
43. Reilly T, Woodbridge V. Effects of moderate dietary mani-
pulations on swim performance and on blood lactate-
swimming velocity curves. Int J Sports Med 1999 Feb;
20 (2): 93-7
44. Yoshida T. Effect of dietary modifications on lactate
threshold and onset of blood lactate accumulation during
incremental exercise. Eur J Appl Physiol 1984; 53 (3):
200-5
45. Maassen N, Busse MW. The relationship between lactic
acid and work load: a measure for endurance capacity or
an indicator of carbohydrate deficiency? Eur J Appl
Physiol Occup Physiol 1989; 58 (7): 728-37
46. Midgley AW, McNaughton LR, Jones AM. Training to
enhance the physiological determinants of long-distance
running performance: can valid recommendations be
given to runners and coaches based on current scientific
knowledge? Sports Med 2007; 37 (10): 857-80
47. Bentley DJ, Newell J, Bishop D. Incremental exercise test
design and analysis: implications for performance diag-
nostics in endurance athletes. Sports Med 2007; 37 (7):
575-86
48. Foxdal P, Sjodin B, Sjodin A, et al. The validity and accu-
racy of blood lactate measurements for prediction of
maximal endurance running capacity: dependency of
analyzed blood media in combination with different
designs of the exercise test. Int J Sports Med 1994; 15 (2):
89-95
49. Heck H, Hess G, Mader A. Comparative study of different
lactate threshold concepts [Vergleichende Untersuchung
zu verschiedenen Laktat-Schwellenkonzepten]. Dtsch Z
Sportmed 1985; 36 (1+2): 19-25, 40-52
50. Heck H. Laktat in der Leistungsdiagnostik. Schorndorf:
Hofmann, 1991
51. Lundberg MA, Hughson RL, Weisiger KH, et al. Com-
puterized estimation of lactate threshold. Comput
Biomed Res 1986 Oct; 19 (5): 481-6
52. Grant S, McMillan K, Newell J, et al. Reproducibility of
the blood lactate threshold, 4 mmol.l(-1) marker, heart
rate and ratings of perceived exertion during incremental
treadmill exercise in humans. Eur J Appl Physiol 2002
Jun; 87 (2): 159-66
53. Beaver WL, Wasserman K, Whipp BJ. Improved detection
of lactate threshold during exercise using a log-log trans-
formation. J Appl Physiol 1985; 59 (6): 1936-40
54. Cheng B, Kuipers H, Snyder AC, et al. A new approach for
the determination of ventilatory and lactate thresholds.
Int J Sports Med 1992; 13 (7): 518-22
55. Hughson RL, Weisiger KH, Swanson GD. Blood lactate
concentration increases as a continuous function in pro-
gressive exercise. J Appl Physiol 1987; 62 (5): 1975-81
56. Robergs RA, Chwalbinska-Moneta J, Mitchell JB, et al.
Blood lactate threshold differences between arterialized
and venous blood. Int J Sports Med 1990; 11 (6): 446-51
57. Feliu J, Ventura JL, Segura R, et al. Differences between
lactate concentration of samples from ear lobe and the
finger tip. J Physiol Biochem 1999 Dec; 55 (4): 333-9
58. McNaughton LR, Thompson D, Philips G, et al. A com-
parison of the lactate Pro, Accusport, Analox GM7 and
Kodak Ektachem lactate analysers in normal, hot and
humid conditions. Int J Sports Med 2002 Feb; 23 (2): 130-5
59. Thin AG, Hamzah Z, FitzGerald MX, et al. Lactate de-
termination in exercise testing using an electrochemical
analyser: with or without blood lysis? Eur J Appl Physiol
Occup Physiol 1999 Jan; 79 (2): 155-9
60. Buono MJ, Yeager JE. Intraerythrocyte and plasma lactate
concentrations during exercise in humans. Eur J Appl
Physiol Occup Physiol 1986; 55 (3): 326-9
61. Forsyth JJ, Farrally MR. A comparison of lactate con-
centration in plasma collected from the toe, ear, and fin-
gertip after a simulated rowing exercise. Br J Sports Med
2000 Feb; 34 (1): 35-8
62. Draper N, Brent S, Hale B, et al. The influence of sampling
site and assay method on lactate concentration in re-
sponse to rock climbing. Eur J Appl Physiol 2006 Nov;
98 (4): 363-72
63. Hildebrand A, Lormes W, Emmert J, et al. Lactate con-
centration in plasma and red blood cells during incre-
mental exercise. Int J Sports Med 2000 Oct; 21 (7): 463-8
64. Foxdal P, Sjodin B, Rudstam H, et al. Lactate concentra-
tion differences in plasma, whole blood, capillary finger
blood and erythrocytes during submaximal graded ex-
ercise in humans. Eur J Appl Physiol Occup Physiol 1990;
61 (3-4): 218-22
65. Foxdal P, Sjodin A, Ostman B, et al. The effect of different
blood sampling sites and analyses on the relationship bet-
ween exercise intensity and 4.0 mmol.l-1 blood lactate
concentration. Eur J Appl Physiol Occup Physiol 1991;
63 (1): 52-4
66. Medbø JI, Mamen A, Holt Olsen O, et al. Examination of
four different instruments for measuring blood lactate con-
centration. Scand J Clin Lab Invest 2000Aug; 60 (5): 367-80
67. Buckley JD, Bourdon PC, Woolford SM. Effect of mea-
suring blood lactate concentrations using different auto-
486 Faude et al.
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
mated lactate analysers on blood lactate transition
thresholds. J Sci Med Sport 2003 Dec; 6 (4): 408-21
68. van Someren KA, Howatson G, Nunan D, et al. Compar-
ison of the Lactate Pro and Analox GM7 blood lactate
analysers. Int J Sports Med 2005 Oct; 26 (8): 657-61
69. Bishop D. Evaluation of the Accusport lactate analyser. Int
J Sports Med 2001 Oct; 22 (7): 525-30
70. Lucı
´a A, Hoyos J, Chicarro JL. Physiology of professional
road cycling. Sports Med 2001; 31 (5): 325-37
71. Weltman A. The blood lactate response to exercise.
Champaign IL: Human Kinetics, 1995
72. Heck H, Mader A, Hess G, et al. Justification of the
4-mmol/l lactate threshold. Int J Sports Med 1985; 6 (3):
117-30
73. Seiler KS, Kjerland GO. Quantifying training intensity
distribution in elite endurance athletes: is there evidence
for an ‘‘optimal’’ distribution? Scand J Med Sci Sports
2006 Feb; 16 (1): 49-56
74. Esteve-Lanao J, San Juan AF, Earnest CP, et al. How do
endurance runners actually train? Relationship with
competition performance. Med Sci Sports Exerc 2005
Mar; 37 (3): 496-504
75. Bourdon P. Blood lactate transition thresholds: concepts
and controversies. In: Gore J, editor. Physiological tests
for elite athletes/Australian Sports Commission. Cham-
paign (IL): Human Kinetics, 2000: 50-65
76. Meyer T, Faude O, Urhausen A, et al. Different effects of
two regeneration regimens on immunological parameters
in cyclists. Med Sci Sports Exerc 2004 Oct; 36 (10): 1743-9
77. Meyer T, Gorge G, Schwaab B, et al. An alternative
approach for exercise prescription and efficacy testing in
patients with chronic heart failure: a randomized con-
trolled training study. Am Heart J 2005 May; 149 (5): e1-7
78. McConnell TR, Clark BA, Conlin NC, et al. Gas exchange
anaerobic threshold: implications for prescribing exercise
in cardiac rehabilitation. J Cardiopulmonary Rehabil
1993; 13: 31-6
79. Faude O, Meyer T, Urhausen A, et al. Recovery training in
cyclists: ergometric, hormonal and psychometric findings.
Scand J Med Sci Sports. Epub 2008 Apr 23
80. Weltman A, Seip RL, Snead D, et al. Exercise training at
and above the lactate threshold in previously untrained
women. Int J Sports Med 1992; 13 (3): 257-63
81. Londeree BR. Effect of training on lactate/ventilatory
thresholds: a meta-analysis. Med Sci Sports Exerc 1997
Jun; 29 (6): 837-43
82. Scharhag J, Meyer T, Gabriel HH, et al. Does prolonged
cycling of moderate intensity affect immune cell function?
Br J Sports Med 2005 Mar; 39 (3): 171-7
83. Meyer T, Gabriel HH, Auracher M, et al. Metabolic profile
of 4 h cycling in the field with varying amounts of carbo-
hydrate supply. Eur J Appl Physiol 2003 Jan; 88 (4-5):431-7
84. Meyer T, Faude O, Gabriel H, et al. Ventilatory threshold
and individual anaerobic threshold are reliable pre-
scriptors for intensity of cycling training [abstract]. Med
Sci Sports Exerc 2000; 32 Suppl. 5: S171
85. Baron B, Noakes TD, Dekerle J, et al. Why does exercise
terminate at the maximal lactate steady state intensity? Br
J Sports Med 2008 Oct; 42 (10): 528-33
86. Urhausen A, Coen B, Weiler B, et al. Individual anaerobic
threshold and maximum lactate steady state. Int J Sports
Med 1993; 14 (3): 134-9
87. Mader A, Heck H. A theory of the metabolic origin
of ‘‘anaerobic threshold’’. Int J Sports Med 1986 Jun;
7 Suppl. 1: 45-65
88. Stegmann H, Kindermann W, Schnabel A. Lactate kinetics
and individual anaerobic threshold. Int J Sports Med
1981; 2: 160-5
89. MacIntosh BR, Esau S, Svedahl K. The lactate minimum
test for cycling: estimation of the maximal lactate steady
state. Can J Appl Physiol 2002 Jun; 27 (3): 232-49
90. Lajoie C, Laurencelle L, Trudeau F. Physiological re-
sponses to cycling for 60 minutes at maximal lactate
steady state. Can J Appl Physiol 2000 Aug; 25 (4): 250-61
91. McLellan TM, Jacobs I. Reliability reproducibility and
validity of the individual anaerobic threshold. Eur J Appl
Physiol 1993; 67 (2): 125-31
92. Van Schuylenbergh R, Vanden Eynde B, Hespel P. Corre-
lations between lactate and ventilatory thresholds and the
maximal lactate steady state in elite cyclists. Int J Sports
Med 2004 Aug; 25 (6): 403-8
93. Beneke R, Hutler M, Leithauser RM. Maximal lactate-
steady-state independent of performance. Med Sci Sports
Exerc 2000 Jun; 32 (6): 1135-9
94. Beneke R, von Duvillard SP. Determination of maximal
lactate steady state response in selected sports events. Med
Sci Sports Exerc 1996 Feb; 28 (2): 241-6
95. Beneke R, Leithauser RM, Hutler M. Dependence of the
maximal lactate steady state on the motor pattern of ex-
ercise. Br J Sports Med 2001 Jun; 35 (3): 192-6
96. Keul J, Simon G, Berg A, et al. Bestimmung der indi-
viduellen anaeroben Schwelle zur Leistungsbewertung
und Train ingsgestaltung. Dtsch Z Sportmed 1 979; 30: 212-8
97. Simon G, Berg A, Dickhuth H-H, et al. Bestimmung der
anaeroben Schwelle in Abha
¨ngigkeit von Alter und
von der Leistungsfa
¨higkeit. Dtsch Z Sportmed 1981; 32:
7-14
98. Coen B. Individuelle anaerobe Schwelle-Methodik und
Anwendung in der sportmedizinischen Leistungsdiagnostik
und Trainingssteuerung leichtathletischer Laufdisziplinen.
Ko
¨ln: Sport und Buch Strauss, 1997
99. Coen B, Schwarz L, Urhausen A, et al. Control of training
in middle- and long-distance running by means of the
individual anaerobic threshold. Int J Sports Med 1991;
12 (6): 519-24
100. Niess AM, Fehrenbach E, Strobel G, et al. Evaluation of
stress responses to interval training at low and moderate
altitudes. Med Sci Sports Exerc 2003 Feb; 35 (2): 263-9
101. Niess AM, Ro
¨cker K, Baumann I, et al. Laktatverhalten
bei extensiven Tempolaufbelastungen unter Flachland-
und moderaten Ho
¨henbedingungen. Leistungssport 1999;
(3): 49-53
102. Faude O, Meyer T, Scharhag J, et al. Volume vs intensity in
the training of competitive swimmers. Int J Sports Med
2008 Nov; 29 (11): 906-12
103. Smith CG, Jones AM. The relationship between critical
velocity, maximal lactate steady-state velocity and lactate
turnpoint velocity in runners. Eur J Appl Physiol 2001 Jul;
85 (1-2): 19-26
Validity of Lactate Thresholds 487
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
104. Davis HA, Bassett J, Hughes P, et al. Anaerobic threshold
and lactate turnpoint. Eur J Appl Physiol 1983; 50 (3):
383-92
105. Urhausen A, Weiler B, Coen B, et al. Plasma catechola-
mines during endurance exercise of different intensities as
related to the individual anaerobic threshold. Eur J Appl
Physiol 1994; 69: 16-20
106. Gabriel H, Kindermann W. The acute immune response
to exercise: what does it mean? Int J Sports Med 1997;
18 Suppl. 1: S28-45
107. Lucia A, Sanchez O, Carvajal A, et al. Analysis of the
aerobic-anaerobic transition in elite cyclists during incre-
mental exercise with the use of electromyography. Br J
Sports Med 1999 Jun; 33 (3): 178-85
108. Sjodin B, Jacobs I. Onset of blood lactate accumulation
and marathon running performance. Int J Sports Med
1981; 2 (1): 23-6
109. Farrell PA, Wilmore JH, Coyle EF, et al. Plasma lactate
accumulation and distance running performance. Med Sci
Sports 1979; 11 (4): 338-44
110. Yoshida T, Chida M, Ichioka M, et al. Blood lactate
parameters related to aerobic capacity and endurance
performance. Eur J Appl Physiol 1987; 56 (1): 7-11
111. Hagberg JM, Coyle EF. Physiological determinants of en-
durance performance as studied in competitive racewalk-
ers. Med Sci Sports Exerc 1983; 15: 287-9
112. Jones AM, Doust JH. The validity of the lactate minimum
test for determination of the maximal lactate steady state.
Med Sci Sports Exerc 1998 Aug; 30 (8): 1304-13
113. Haverty M, Kenney WL, Hodgson JL. Lactate and gas
exchange responses to incremental and steady state run-
ning. Br J Sports Med 1988; 22 (2): 51-4
114. Harnish CR, Swensen TC, Pate RR. Methods for estimat-
ing the maximal lactate steady state in trained cyclists.
Med Sci Sports Exerc 2001 Jun; 33 (6): 1052-5
115. Beneke R. Methodological aspects of maximal lactate
steady state: implications for performance testing. Eur J
Appl Physiol 2003 Mar; 89 (1): 95-9
116. Billat VL, Sirvent P, Py G, et al. The concept of maxi-
mal lactate steady state: a bridge between biochemistry,
physiology and sport science. Sports Med 2003; 33 (6):
407-26
117. Beneke R. Anaerobic threshold, individual anaerobic
threshold, and maximal lactate steady state in rowing.
Med Sci Sports Exerc 1995; 27 (6): 863-7
118. Baron B, Dekerle J, Robin S, et al. Maximal lactate steady
state does not correspond to a complete physiological
steady state. Int J Sports Med 2003 Nov; 24 (8): 582-7
119. Urhausen A, Coen B, Kindermann W. Individual assess-
ment of the aerobic-anaerobic transition by measure-
ments of blood lactate. In: Garrett Jr WE, Kirkendall DT,
editors. Exercise and sport science. Philadelphia (PA):
Lippincott Williams &Wilkins, 2000: 267-75
120. Mujika I, Busso T, Geyssant A, et al. Modeling the effects
of training in competitive swimming. In: Troup JP,
Hollander AP, Strasse D, editors. Biomechanics and medi-
cine in swimming. London: E &FN Spon, 1996: 221-8
121. Kumagai S, Tanaka K, Matsuura Y, et al. Relationships of
the anaerobic threshold with the 5 km, 10 km, and 10 mile
races. Eur J Appl Physiol 1982; 49 (1): 13-23
122. Aunola S, Rusko H. Does anaerobic threshold correlate
with maximal lactate steady-state? J Sports Sci 1992;
10 (4): 309-23
123. Weltman A, Snead D, Seip R, et al. Prediction of lactate
threshold and fixed blood lactate concentrations from
3200-m running performance in male runners. Int J Sports
Med 1987 Dec; 8 (6): 401-6
124. Fo
¨hrenbach R, Mader A, Hollmann W. Determination of
endurance capacity and prediction of exercise intensities
for training and competition in marathon runners. Int
J Sports Med 1987; 8: 11-8
125. Hurley BF, Hagberg JM, Allen WK, et al. Effect of training
on blood lactate levels during submaximal exercise.
J Appl Physiol 1984; 56 (5): 1260-4
126. Ivy JL, Withers RT, Van Handel PJ, et al. Muscle
respiratory capacity and fiber type as determinants
of the lactate threshold. J Appl Physiol 1980 Mar; 48 (3):
523-7
127. Caiozzo VJ, Davis JA, Ellis JF, et al. A comparison of gas
exchange indices used to detect the anaerobic threshold.
J Appl Physiol 1982; 53 (5): 1184-9
128. Tanaka H. Predicting running velocity at blood lactate
threshold from running performance tests in adolescent
boys. Eur J Appl Physiol 1986; 55 (4): 344-8
129. Tanaka K, Matsuura Y. Marathon performance, anaero-
bic threshold, and onset of blood lactate accumulation.
J Appl Physiol 1984; 57 (3): 640-3
130. Tanaka K, Matsuura Y, Matsuzaka A, et al. A longitudinal
assessment of anaerobic threshold and distance-running
performance. Med Sci Sports Exerc 1984 Jun; 16 (3): 278-82
131. Yoshida T, Udo M, Iwai K, et al. Significance of the con-
tribution of aerobic and anaerobic components to several
distance running performances in female athletes. Eur
J Appl Physiol Occup Physiol 1990; 60 (4): 249-53
132. Yoshida T, Udo M, Iwai K, et al. Physiological character-
istics related to endurance running performance in female
distance runners. J Sports Sci 1993 Feb; 11 (1): 57-62
133. Davis JA, Vodak P, Wilmore JH, et al. Anaerobic thresh-
old and maximal aerobic power for three modes of
exercise. J Appl Physiol 1976 Oct; 41 (4): 544-50
134. Weltman J, Seip R, Levine S, et al. Prediction of lactate
threshold and fixed blood lactate concentrations from
3200-m time trial running performance in untrained
females. Int J Sports Med 1989 Jun; 10 (3): 207-11
135. Roecker K, Schotte O, Niess AM, et al. Predicting com-
petition performance in long-distance running by means
of a treadmill test. Med Sci Sports Exerc 1998 Oct; 30 (10):
1552-7
136. Dickhuth HH, Huonker M, Mu
¨nzel T, et al. Individual
anaerobic threshold for evaluation of competitive athletes
and patients with left ventricular dysfunctions. In: Bachl N,
Graham TE, Lo
¨llgen H, editors. Advances in ergometry.
Berlin: Springer, 1991: 173-9
137. Berg A, Stippig J, Keul J, et al. Zur Beurteilung der
Leistungsfa
¨higkeit und Belastbarkeit von Patienten mit
coronarer Herzkrankheit. Dtsch Z Sportmed 1980; 31:
199-205
138. Hughson RL, Green HJ. Blood acid-base and lactate
relationships studied by ramp work tests. Med Sci Sports
Exerc 1982; 14 (4): 297-302
488 Faude et al.
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
139. Coyle EF, Martin WH, Ehsani AA, et al. Blood lactate
threshold in some well-trained ischemic heart disease
patients. J Appl Physiol 1983 Jan; 54 (1): 18-23
140. Bishop D, Jenkins DG, Mackinnon LT. The relationship
between plasma lactate parameters, W
peak
and 1-h cycling
performance in women. Med Sci Sports Exerc 1998 Aug;
30 (8): 1270-5
141. Amann M, Subudhi AW, Foster C. Predictive validity of
ventilatory and lactate thresholds for cycling time trial
performance. Scand J Med Sci Sports 2006 Feb; 16 (1):
27-34
142. Yeh MP, Gardner RM, Adams TD, et al. ‘‘Anaerobic
threshold’’: problems of determination and validation.
J Appl Physiol 1983 Oct; 55 (4): 1178-86
143. Bunc V, Heller J, Novack J, et al. Determination of the
individual anaerobic threshold. Acta Univ Carol, Gym-
nica 1985; 27: 73-81
144. Baldari C, Guidetti L. A simple method for individual
anaerobic threshold as predictor of max lactate
steady state. Med Sci Sports Exerc 2000 Oct; 32 (10):
1798-802
145. Tegtbur U, Busse MW, Braumann KM. Estimation of an
individual equilibrium between lactate production and
catabolism during exercise. Med Sci Sports Exerc 1993
May; 25 (5): 620-7
146. Stegmann H, Kindermann W. Comparison of prolonged
exercise tests at the individual anaerobic threshold and the
fixed anaerobic threshold of 4 mmol/l lactate. Int J Sports
Med 1982; 3 (2): 105-10
147. Orok CJ, Hughson RL, Green HJ, et al. Blood lactate
responses in incremental exercise as predictors of con-
stant load performance. Eur J Appl Physiol 1989; 59 (4):
262-7
148. Carter H, Jones AM, Doust JH. Effect of incremental test
protocol on the lactate minimum speed. Med Sci Sports
Exerc 1999 Jun; 31 (6): 837-45
149. Coen B, Urhausen A, Kindermann W. Individual anaero-
bic threshold: methodological aspects of its assessment in
running. Int J Sports Med 2001 Jan; 22 (1): 8-16
150. Weltman A, Snead D, Stein P, et al. Reliability and validity
of a continuous incremental treadmill protocol for the
determination of lactate threshold, fixed blood lac-
tate concentrations, and V
O
2max
. Int J Sports Med 1990;
11 (1): 26-32
151. Aunola S, Rusko H. Reproducibility of aerobic and anae-
robic thresholds in 20-50 year old men. Eur J Appl Physiol
1984; 53 (3): 260-6
152. Pfitzinger P, Freedson PS. The reliability of lactate mea-
surements during exercise. Int J Sports Med 1998 Jul;
19 (5): 349-57
153. Zhou S, Weston SB. Reliability of using the D-max method
to define physiological responses to incremental exercise
testing. Physiol Meas 1997 May; 18 (2): 145-54
154. Takeshima N, Tanaka K. Prediction of endurance running
performance for middle-aged and older runners. Br J
Sports Med 1995 Mar; 29 (1): 20-3
155. Tanaka K, Matsuura Y, Kumagai S, et al. Relationships of
anaerobic threshold and onset of blood lactate accumu-
lation with endurance performance. Eur J Appl Physiol
Occup Physiol 1983; 52 (1): 51-6
156. Bourdin M, Messonnier L, Hager JP, et al. Peak
power output predicts rowing ergometer performance
in elite male rowers. Int J Sports Med 2004 Jul; 25 (5):
368-73
157. Bjorklund G, Pettersson S, Schagatay E. Performance
predicting factors in prolonged exhausting exercise of
varying intensity. Eur J Appl Physiol 2007 Mar; 99 (4):
423-9
158. Grant S, Craig I, Wilson J, et al. The relationship between
3 km running performance and selected physiological
variables. J Sports Sci 1997 Aug; 15 (4): 403-10
159. Fay L, Londeree BR, LaFontaine TP, et al. Physiological
parameters related to distance running performance in
female athletes. Med Sci Sports Exerc 1989 Jun; 21 (3):
319-24
160. Nicholson RM, Sleivert GG. Indices of lactate threshold
and their relationship with 10-km running velocity. Med
Sci Sports Exerc 2001 Feb; 33 (2): 339-42
161. Lehmann M, Berg A, Kapp R, et al. Correlations between
laboratory testing and distance running performance in
marathoners of similar performance ability. Int J Sports
Med 1983 Nov; 4 (4): 226-30
162. Tanaka K, Watanabe H, Konishi Y, et al. Longitudinal
associations between anaerobic threshold and distance
running performance. Eur J Appl Physiol Occup Physiol
1986; 55 (3): 248-52
163. Tokmakidis SP, Leger LA, Pilianidis TC. Failure to obtain
a unique threshold on the blood lactate concentration
curve during exercise. Eur J Appl Physiol Occup Physiol
1998 Mar; 77 (4): 333-42
164. Stratton E, O’Brien BJ, Harvey J, et al. Treadmill velocity
best predicts 5000-m run performance. Int J Sports Med
2009; 30 (1): 40-5
165. Bentley DJ, McNaughton LR, Thompson D, et al. Peak
power output, the lactate threshold, and time trial per-
formance in cyclists. Med Sci Sports Exerc 2001 Dec;
33 (12): 2077-81
166. McNaughton LR, Roberts S, Bentley DJ. The relationship
among peak power output, lactate threshold, and short-
distance cycling performance: effects of incremental ex-
ercise test design. J Strength Cond Res 2006 Feb; 20 (1):
157-61
167. Craig NP, Norton KI, Bourdon PC, et al. Aerobic and
anaerobic indices contributing to track endurance cycling
performance. Eur J Appl Physiol Occup Physiol 1993;
67 (2): 150-8
168. Nichols JF, Phares SL, Buono MJ. Relationship between
blood lactate response to exercise and endurance perfor-
mance in competitive female master cyclists. Int J Sports
Med 1997 Aug; 18 (6): 458-63
169. Gregory J, Johns DP, Walls JT. Relative versus absolute
physiological measures as predictors of mountain bike
cross-country race performance. J Strength Cond Res
2007 Feb; 21 (1): 17-22
170. Impellizzeri FM, Rampinini E, Sassi A, et al. Physiological
correlates to off-road cycling performance. J Sports Sci
2005 Jan; 23 (1): 41-47
171. Coyle EF. Improved muscular efficiency displayed as Tour
de France champion matures. J Appl Physiol 2005 Jun;
98 (6): 2191-6
Validity of Lactate Thresholds 489
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
This material is
the copyright of the
original publisher.
Unauthorised copying
and distribution
is prohibited.
172. Lucia A, Earnest C, Arribas C. The Tour de France:
a physiological review. Scand J Med Sci Sports 2003 Oct;
13 (5): 275-83
173. Impellizzeri FM, Marcora SM. The physiology of moun-
tain biking. Sports Med 2007; 37 (1): 59-71
174. Yoshida T, Udo M, Iwai K, et al. Physiological determi-
nants of race walking performance in female race walkers.
Br J Sports Med 1989 Dec; 23 (4): 250-4
175. Ingham SA, Whyte GP, Jones K, et al. Determinants of
2000 m rowing ergometer performance in elite rowers. Eur
J Appl Physiol 2002 Dec; 88 (3): 243-6
176. Cosgrove MJ, Wilson J, Watt D, et al. The relationship
between selected physiological variables of rowers and
rowing performance as determined by a 2000 m ergometer
test. J Sports Sci 1999 Nov; 17 (11): 845-52
177. Noakes TD. The central governor model of exercise
regulation applied to the marathon. Sports Med 2007;
37 (4-5): 374-7
178. Swensen TC, Harnish CR, Beitman L, et al. Noninvasive
estimation of the maximal lactate steady state in trained
cyclists. Med Sci Sports Exerc 1999 May; 31 (5): 742-6
179. Snyder AC, Woulfe T, Welsh R, et al. A simplified ap-
proach to estimating the maximal lactate steady state. Int
J Sports Med 1994; 15 (1): 27-31
180. Kilding AE, Jones AM. Validity of a single-visit protocol to
estimate the maximum lactate steady state. Med Sci
Sports Exerc 2005 Oct; 37 (10): 1734-40
181. Billat V, Dalmay F, Antonini MT, et al. A method for
determining the maximal steady state of blood lactate
concentration from two levels of submaximal exercise.
Eur J Appl Physiol Occup Physiol 1994; 69 (3): 196-202
182. Palmer AS, Potteiger JA, Nau KL, et al. A 1-day maximal
lactate steady-state assessment protocol for trained run-
ners. Med Sci Sports Exerc 1999 Sep; 31 (9): 1336-41
183. Loat CE, Rhodes EC. Relationship between the lactate and
ventilatory thresholds during prolonged exercise. Sports
Med 1993; 15 (2): 104-15
184. Simon J, Young JL, Gutin B, et al. Lactate accumulation
relative to the anaerobic and respiratory compensation
thresholds. J Appl Physiol 1983; 54 (1): 13-7
185. Yamamoto Y, Miyashita M, Hughson RL, et al. The
ventilatory threshold gives maximal lactate steady state.
Eur J Appl Physiol 1991; 63 (1): 55-9
186. Scheen A, Juchmes J, Cession-Fossion A. Critical analysis
of the ‘‘anaerobic threshold’’ during exercise at constant
workloads. Eur J Appl Physiol Occup Physiol 1981;
46 (4): 367-77
187. Laplaud D, Guinot M, Favre-Juvin A, et al. Maximal
lactate steady state determination with a single incre-
mental test exercise. Eur J Appl Physiol 2006 Mar; 96 (4):
446-52
188. Dekerle J, Baron B, Dupont L, et al. Maximal lactate
steady state, respiratory compensation threshold and
critical power. Eur J Appl Physiol 2003 May; 89 (3-4):
281-8
189. Loat CER, Rhodes EC. Comparison of the lactate and
ventilatory thresholds during prolonged work. Biol Sport
1996; 13 (1): 3-12
190. Schnabel A, Kindermann W, Schmitt WM, et al. Hormo-
nal and metabolic consequences of prolonged running at
the individual anaerobic threshold. Int J Sports Med 1982;
3 (3): 163-8
191. Oyono-Enguelle S, Heitz A, Marbach J, et al. Blood
lactate during constant-load exercise at aerobic and
anaerobic thresholds. Eur J Appl Physiol 1990; 60 (5):
321-30
192. Ribeiro JP, Hughes V, Fielding RA, et al. Metabolic and
ventilatory responses to steady state exercise relative to
lactate thresholds. Eur J Appl Physiol Occup Physiol
1986; 55 (2): 215-21
193. Bacon L, Kern M. Evaluating a test protocol for predicting
maximum lactate steady state. J Sports Med Phys Fitness
1999 Dec; 39 (4): 300-8
194. Bland JM, Altman DG. Statistical methods for assessing
agreement between two methods of clinical measurement.
Lancet 1986 Feb 8; 1 (8476): 307-10
195. Atkinson G, Nevill AM. Statistical methods for assessing
measurement error (reliability) in variables relevant to
sports medicine. Sports Med 1998 Oct; 26 (4): 217-38
Correspondence: Dr Oliver Faude, Institute of Sports and
Preventive Medicine, University of Saarland, Campus Bldg.
B 8.2, 66123 Saarbru
¨cken, Germany.
E-mail: o.faude@mx.uni-saarland.de
490 Faude et al.
ª2009 Adis Data Information BV. All rights reserved. Sports Med 2009; 39 (6)
... This concept was extensively debated over several years leading to a massive number of publications connected to "anaerobic threshold" and lactate (Poole et al. 2021). Nowadays, the scientific community has recognized that lactate is not a "waste product", it is not causing fatigue, but on the contrary, it is a dynamic metabolite that may be extremely helpful for the characterization of training intensity and planning of training in many sports, including swimming (Faude et al., 2009). Despite many published works use the terms "aerobic" or "anaerobic" threshold, in the current paper the terms "first" and "second" lactate threshold, respectively, will be used to avoid misconceptions concerning thresholds related to oxidative or non-oxidative metabolism. ...
... Moreover, the mathematical modeling of the collected data is an issue of discussion, since each model may fit better to some groups of swimmers but not for others (Nikitakis & Toubekis 2021). Despite the variety in protocols and mathematical modeling the speed vs. lactate curve is used to identify two points in the curve that correspond to the "first" and "second" lactate threshold (Faude et al., 2009). These points may be used to define exercise intensity domains called "moderate", "heavy" and "severe", although there is an open debate for the appearance of an exercise intensity domain called "very heavy". ...
Book
Full-text available
Euswim is an academic and research network whose aim is to develop and spread knowledge about swimming science. Whether you are a student, researcher, or professor, our platform (www.euswim.eu) offers the opportunity to exchange, interact and participate with us through our First annual conference. The book provides an overview of the European Conference of the European Swimming of the most relevant European researchers in swimming: Robin Pla (France), Ricardo Fernandes (Portugal), Argyris Toubekis (Greece), Santiago Veiga (Spain) and Inmaculada Yustres (Spain). Also, it includes all communications and other previous contributions from the foundational member of the network. This book aims to provide the latest research in swimming science and the experience and vision of professionals dedicated to one of the most popular sport followed by millions in the Olympic Games.
... A function describing the relation between wattage and lactate concentration was estimated. Lactate concentrations at around 2 mmol/l are supposed to represent the aerobic threshold [36]. We identified the individual aerobic threshold at lactate concentrations between 1.8 and 2.5 mmol/l according to the previously defined exercise protocol [35]. ...
Article
Full-text available
Background Schizophrenia is accompanied by widespread alterations in static functional connectivity associated with symptom severity and cognitive deficits. Improvements in aerobic fitness have been demonstrated to ameliorate symptomatology and cognition in people with schizophrenia, but the intermediary role of macroscale connectivity patterns remains unknown. Objective Therefore, we aim to explore the relation between aerobic fitness and the functional connectome in individuals with schizophrenia. Further, we investigate clinical and cognitive relevance of the identified fitness-connectivity links. Methods Patients diagnosed with schizophrenia were included in this cross-sectional resting-state fMRI analysis. Multilevel Bayesian partial correlations between aerobic fitness and functional connections across the whole brain as well as between static functional connectivity patterns and clinical and cognitive outcome were performed. Preliminary causal inferences were enabled based on mediation analyses. Results Static functional connectivity between the subcortical nuclei and the cerebellum as well as between temporal seeds mediated the attenuating relation between aerobic fitness and total symptom severity. Functional connections between cerebellar seeds affected the positive link between aerobic fitness and global cognition, while the functional interplay between central and limbic seeds drove the beneficial association between aerobic fitness and emotion recognition. Conclusion The current study provides first insights into the interactions between aerobic fitness, the functional connectome and clinical and cognitive outcome in people with schizophrenia, but causal interpretations are preliminary. Further interventional aerobic exercise studies are needed to replicate the current findings and to enable conclusive causal inferences. Trial registration The study which the manuscript is based on is registered in the International Clinical Trials Database (ClinicalTrials.gov identifier [NCT number]: NCT03466112) and in the German Clinical Trials Register (DRKS-ID: DRKS00009804).
... As this threshold distinguishes exercise intensities for which the intramuscular metabolic milieu can(not) be stabilized, it is a commonly used index for testing, training and monitoring athletes. Traditionally, two threshold concepts have been considered as reference methods to determine the MMSS intensity: critical power, which defines the hyperbolic relationship between power output (PO) and time to exhaustion (Poole et al. 2016), and the maximal lactate (La − ) steady state (MLSS) (Billat et al. 2003;Faude et al. 2009), which defines the highest possible equilibrium in blood [La − ] during exercise. ...
Article
Full-text available
Purpose This study longitudinally examined the interchangeable use of critical power (CP), the maximal lactate steady state (MLSS) and the respiratory compensation point (RCP) (i.e., whole-body thresholds), and breakpoints in muscle deoxygenation (m[HHb]BP) and muscle activity (iEMGBP) (i.e., local thresholds). Methods Twenty-one participants were tested on two timepoints (T1 and T2) with a 4-week period (study 1: 10 women, age = 27 ± 3 years, V˙O2peak\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{{2{\text{peak}}}}$$\end{document} = 43.2 ± 7.3 mL min⁻¹kg⁻¹) or a 12-week period (study 2: 11 men, age = 25 ± 4 years, V˙O2peak\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{{2{\text{peak}}}}$$\end{document} = 47.7 ± 5.9 mL min⁻¹ kg⁻¹) in between. The test battery included one ramp incremental test (to determine RCP, m[HHb]BP and iEMGBP) and a series of (sub)maximal constant load tests (to determine CP and MLSS). All thresholds were expressed as oxygen uptake (V˙O2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}) and equivalent power output (PO) for comparison. Results None of the thresholds were significantly different in study 1 (V˙O2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}: P = 0.143, PO: P = 0.281), but differences between whole-body and local thresholds were observed in study 2 (V˙O2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}{\text{O}}_{2}$$\end{document}: P < 0.001, PO: P = 0.024). Whole-body thresholds showed better 4-week test–retest reliability (TEM = 88–125 mL min⁻¹ or 6–10 W, ICC = 0.94–0.98) compared to local thresholds (TEM = 189–195 mL min⁻¹ or 15–18 W, ICC = 0.58–0.89). All five thresholds were strongly associated at T1 and T2 (r = 0.75–0.99), but their changes from T1 to T2 were mostly uncorrelated (r = − 0.41–0.83). Conclusion Whole-body thresholds (CP/MLSS/RCP) showed a close and consistent coherence taking into account a 3–6%-bandwidth of typical variation. In contrast, local thresholds (m[HHb]BP/iEMGBP) were characterized by higher variability and did not consistently coincide with the whole-body thresholds. In addition, we found that most thresholds evolved independently of each other over time. Together, these results do not justify the interchangeable use of whole-body and local exercise thresholds in practice.
... The lactate curve could be used to determine the aerobic and anaerobic threshold and may serve as a basis for individually assessing endurance capacity and training zones. In addition, a maximum lactate concentration provided proof of maximum exertion [22]. ...
Article
Full-text available
It is well-known that children and adolescents with obesity have increased over recent decades which in turn carries greater risk of co-morbidities and poses a preventive as well as a therapeutic challenge. Currently, there are limited recommendations available on proven methods for recording physical fitness in children and adolescents presenting with extreme obesity. In this study, twenty participants, aged 12–17 years, with a body mass index (BMI) above the 99.5th percentile, were comparatively assessed, using a correlation between their physical fitness on a bicycle (BC) and treadmill (TM) cardiopulmonary exercise testing (CPET) with a lactate diagnostic. The results of the BC and the TM were as follows: maximum heart rate (HR max ) 186.4 ± 8.6 beats per minute (bpm) vs. 190.8 ± 8.8 bpm, peak oxygen consumption (VO 2 peak/kg) 23.5 ± 2.9 ml/min/kg vs. 25.4 ± 3.1 ml/min/kg, and maximum lactate (La max ) 6.4 ± 1.6 mmol/l vs. 5.6 ± 1.4 mmol/l. The values of HR max and VO 2 peak/kg were significantly higher for adolescents tested on the TM. However, no significant difference was observed in either La max values or between the genders. Conclusions : The higher values of HR max and VO 2 peak/kg could be attributed to the activation of a higher percentage of muscle mass on the TM. Lower La max values on the TM suggest maximum physical exertion was not achieved. This could be due to the extreme body weight carried by the participants. Both the BC and the TM CPET could be used for assessing physical fitness in children and adolescents with extreme obesity but should not be used interchangeably. What is Known: • Currently, there are only limited recommendations available on proven methods for recording physical fitness in children and adolescents with extreme obesity available. What is New: • Cardiopulmonary exercise testing with maximum physical exertion has been shown to be feasible in children and adolescents with extreme obesity. The results obtained from this study demonstrated that both a bicycle and a treadmill can be effectively used for assessing the physical fitness levels in children and adolescents with extreme obesity.
... Also, BLa was measured in capillary blood at the end of each stage using the Lactate Scout+ portable analyzer (EKF Diagnostics, SensLab, Leipzig, Germany). Lactate threshold was determined as the exercise intensity (as percentages of HRpeak and VO2peak) corresponding to a BLa equal to 4 mmol/L, based on the curvilinear relationship between blood lactate and exercise intensity (21). ...
Article
Purpose: To compare the metabolic, cardiorespiratory and perceptual responses to three isoenergetic high-intensity interval exercise (HIIE) protocols of different bout duration and an isoenergetic continuous exercise protocol. Methods: Eleven healthy males (age, 28 ± 6 y) performed four 20-min cycling trials of equal mean power output one week apart. Participants cycled either continuously (CON) or intermittently with 10s (HIIE10), 30s (HIIE30), or 60s (HIIE60) bouts at intensities corresponding to 49% (CON) or 100% of power at peak oxygen uptake (VO2peak). Recovery intervals during the HIIE trials were 15, 45, and 90s, respectively. Results: Average VO2 was similar in the HIIE trials (2.29 ± 0.42, 2.20 ± 0.43, and 2.12 ± 0.45 L·min-1, for HIIE10, HIIE30 and HIIE60, respectively); whereas, in CON (2.02 ± 0.38 L·min-1), it was lower than HIIE10 (p = 0.002) and HIIE30 (p = 0.043). Average pulmonary ventilation (VE) was higher in HIIE60 compared to HIIE10, HIIE30, and CON (75.8 ± 21.8 vs. 64.1 ± 14.5, 64.1 ± 16.2, and 54.0 ± 12.5 L·min-1, respectively, p < 0.001). The peak values and oscillations of VO2 and VE in HIIE60 were higher compared to all other trials (p < 0.001). Blood lactate concentration was higher in HIIE60 compared to HIIE10, HIIE30, and CON from the 5th min onward, reaching 12.5 ± 3.5, 7.2 ± 2.1, 7.9 ± 2.9, and 4.9 ± 1.6 mmol·L-1, respectively, at the end of exercise (p < 0.001). Rating of perceived exertion (RPE) was higher and affective responses were lower in HIIE60 compared to all other trials toward the end of exercise (p < 0.001). Conclusions: These findings highlight the importance of bout duration in HIIE, since shorter bouts resulted in attenuated metabolic and cardiorespiratory responses, lower RPE and feelings of displeasure compared to a longer bout, despite equal total work, duration, and work-to-recovery ratio. These results may have implications for the prescription of HIIE in various populations.
... Body weight-adjusted P 3 and IAT are both recognized as valid indicators of maximal lactate steady state and therefore cardiovascular www.nature.com/scientificreports/ fitness 89,90 . A GXT post-test was not scheduled since we did not expect fitness gains exceeding a familiarization effect in a training period as short as 2 weeks 6 . ...
Article
Full-text available
In recent years, mounting evidence from animal models and studies in humans has accumulated for the role of cardiovascular exercise (CE) in improving motor performance and learning. Both CE and motor learning may induce highly dynamic structural and functional brain changes, but how both processes interact to boost learning is presently unclear. Here, we hypothesized that subjects receiving CE would show a different pattern of learning-related brain plasticity compared to non-CE controls, which in turn associates with improved motor learning. To address this issue, we paired CE and motor learning sequentially in a randomized controlled trial with healthy human participants. Specifically, we compared the effects of a 2-week CE intervention against a non-CE control group on subsequent learning of a challenging dynamic balancing task (DBT) over 6 consecutive weeks. Structural and functional MRI measurements were conducted at regular 2-week time intervals to investigate dynamic brain changes during the experiment. The trajectory of learning-related changes in white matter microstructure beneath parieto-occipital and primary sensorimotor areas of the right hemisphere differed between the CE vs. non-CE groups, and these changes correlated with improved learning of the CE group. While group differences in sensorimotor white matter were already present immediately after CE and persisted during DBT learning, parieto-occipital effects gradually emerged during motor learning. Finally, we found that spontaneous neural activity at rest in gray matter spatially adjacent to white matter findings was also altered, therefore indicating a meaningful link between structural and functional plasticity. Collectively, these findings may lead to a better understanding of the neural mechanisms mediating the CE-learning link within the brain.
Conference Paper
Full-text available
У матеріалах конференції висвітлено теоретико-методологічні засади розвитку фізичної підготовки та спорту у секторі безпеки і оборони України з урахуванням досвіду бойових дій та військових конфліктів, проблеми підготовки та розвитку військових фахівців з організації фізичної підготовки та спорту у військах (силах), зарубіжний досвід спеціальної фізичної підготовки та спорту у збройних силах провідних країн світу, прикладні аспекти інформаційних технологій фахівців у фізичній підготовці, проблеми розвитку військово-прикладних видів спорту у секторі безпеки і оборони України, акцентовано увагу на психологічних та медико-біологічних аспектах фізичної підготовки у секторі безпеки і оборони України з урахуванням досвіду бойових дій та військових конфліктів. ISBN 978-617-7187-53-9
Article
Full-text available
Purpose The desire-goal motivational conflict helps explain endurance performance, however, the physiological concomitants are unknown. The present study examined disturbances in desire to reduce effort and performance goal value across moderate, heavy, and severe exercise intensity domains, demarcated by the first (LT1) and second (LT2) lactate thresholds. In addition, the within-person relationships between blood lactate concentration, heart rate and desire-goal conflict were examined. Methods Thirty participants (53% female, Mage = 21.03 years; SD = 2.06 years) completed an incremental cycling exercise test, in which work-rate was increased by 25 watts every four minutes, until voluntary exhaustion or sufficient data from the severe intensity domain had been collected. Desire to reduce effort, performance goal value, blood lactate concentration (for determination of LT1 and LT2) and heart rate were measured at the end of each stage and analyzed using multilevel models. Results The desire to reduce effort increased over the exercise test with additional shifts and accelerations after each lactate threshold. The performance goal did not show general declines, nor did it shift at LT1. However, the performance goal value shifted at LT2, and the rate of change increased at both thresholds. Within-person variation in blood lactate concentration positively correlated with the desire to reduce effort and negatively correlated with the performance goal. Within-person variation in heart rate correlated with desire to reduce effort but not the performance goal. Conclusion Transitioning through both lactate thresholds are important phases for motivation during progressive exercise, particularly for the desire to reduce effort. Within-person variation in blood lactate concentration is more influential for motivation, compared to heart rate.
Article
Full-text available
The maximal lactate steady state (MLSS) is defined as the highest blood lactate concentration (MLSSc) and work load (MLSSw) that can be maintained over time without a continual blood lactate accumulation. A close relationship between endurance sport performance and MLSSw has been reported and the average velocity over a marathon is just below MLSSw. This work rate delineates the low-to high-intensity exercises at which carbohydrates contribute more than 50% of the total energy need and at which the fuel mix switches (crosses over) from predominantly fat to predominantly carbohydrate. The rate of metabolic adenosine triphosphate (ATP) turnover increases as a direct function of metabolic power output and the blood lactate at MLSS represents the highest point in the equilibrium between lactate appearance and disappearance both being equal to the lactate turnover. However, MLSSc has been reported to demonstrate a great variability between individuals (from 2–8 mmol/L) in capillary blood and not to be related to MLSSw. The fate of enhanced lactate clearance in trained individuals has been attributed primarily to oxidation in active muscle and gluconeogenesis in liver. The transport of lactate into and out of the cells is facilitated by monocarboxylate transporters (MCTs) which are transmembrane proteins and which are significantly improved by training. Endurance training increases the expression of MCT1 with intervariable effects on MCT4. The relationship between the concentration of the two MCTs and the performance parameters (i.e. the maximal distance run in 20 minutes) in elite athletes has not yet been reported. However, lactate exchange and removal indirectly estimated with velocity constants of the individual blood lactate recovery has been reported to be related to time to exhaustion at maximal oxygen uptake.
Article
Full-text available
Physiological variables, such as maximum work rate or maximal oxygen uptake (V̇O2max), together with other submaximal metabolic inflection points (e.g. the lactate threshold [LT], the onset of blood lactate accumulation and the pulmonary ventilation threshold [VT]), are regularly quantified by sports scientists during an incremental exercise test to exhaustion. These variables have been shown to correlate with endurance performance, have been used to prescribe exercise training loads and are useful to monitor adaptation to training. However, an incremental exercise test can be modified in terms of starting and subsequent work rates, increments and duration of each stage. At the same time, the analysis of the blood lactate/ventilatory response to incremental exercise may vary due to the medium of blood analysed and the treatment (or mathematical modelling) of data following the test to model the metabolic inflection points. Modification of the stage duration during an incremental exercise test may influence the submaximal and maximal physiological variables. In particular, the peak power output is reduced in incremental exercise tests that have stages of longer duration. Furthermore, the VT or LT may also occur at higher absolute exercise work rate in incremental tests comprising shorter stages. These effects may influence the relationship of the variables to endurance performance or potentially influence the sensitivity of these results to endurance training. A difference in maximum work rate with modification of incremental exercise test design may change the validity of using these results for predicting performance, and prescribing or monitoring training. Sports scientists and coaches should consider these factors when conducting incremental exercise testing for the purposes of performance diagnostics.
Article
The purpose of this investigation was to compare the ventilatory threshold (Tvent) with the lactate threshold (Tlact) during 60 min of steady-state exercise at the calculated thresholds. Eight trained, male cyclists (mean age 23.3±3.0 years, body mass 70.0±7.1 kg, V̇O2max 61.02±4.15 ml·kg-1·min-1) performed a progressive intensity cycling test (23 W/min) for determining Tlact and Tvent. Tvent was determined by the non-linear increase in excess CO2 (ExCO2) while Tlact was calculated by the "individual anaerobic threshold" (IAT) method. Subsequently, subjects performed an up to 60 min steady-state exercise at the threshold workloads the results at Tlact being significantly higher from those at Tvent at P<0.01 in V̇O2, ExCO2, HR, blood lactate concentration (BLa) and workload, as calculated by Hotelling's T2-test. During the steady state exercise at each specified workload, V̇O2, BLa, heart rate and ExCO2 were measured at 15 min intervals. All subjects completed the steady-state exercise at Tvent (VSS) while the steady-state exercise at Tlact (LSS) - only 2 subjects (mean time 48.4 min). Comparison of metabolic variables using MANOVA and multiple comparisons revealed significant differences between VSS and LSS for HR and V̇O2 at all time intervals, for BLa at 30 and 45 min intervals and for ExCO2 at the 30 min interval. Furthermore, examination of BLa over time using trend analysis revealed a stabilization during VSS (3.05 mmol·l-1) whereas BLa continuously increased over time during LSS. Our findings indicate that Tlact (IAT method) overestimates the ability to perform prolonged work over 45 min while Tvent (ExCO2) allows for steady-state exercise longer than 60 min.