International  Journal  of
Environmental Research
and Public Health
Article
Can an Incremental Step Test Be Used for Maximal Lactate
Steady State Determination in Swimming? Clues for Practice
Mário C. Espada 1,2, Francisco B. Alves 3,4, Dália Curto 3, Cátia C. Ferreira 1,5, Fernando J. Santos 1,2,3
,
Dalton M. Pessôa-Filho 6,7
and Joana F. Reis 3,4,*


Citation: Espada, M.C.; Alves, F.B.;
Curto, D.; Ferreira, C.C.; Santos, F.J.;
Pessôa-Filho, D.M.; Reis, J.F. Can an
Incremental Step Test Be Used for
Maximal Lactate Steady State
Determination in Swimming? Clues
for Practice. Int. J. Environ. Res. Public
Health 2021, 18, 477. https://doi.org/
10.3390/ijerph18020477
Received: 11 December 2020
Accepted: 3 January 2021
Published: 8 January 2021
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4.0/).
1
Polytechnic Institute of Setúbal, Department of Science and Technology, 2914-514 Setubal, Portugal;
mario.espada@ese.ips.pt (M.C.E.); catia.ferreira@ese.ips.pt (C.C.F.); fernando.santos@ese.ips.pt (F.J.S.)
2
Quality of Life Research Centre, 2040-413 Rio Maior, Portugal
3
Faculdade de Motricidade Humana, Universidade de Lisboa, 1499-002 Cruz Quebrada-Dafundo, Portugal;
falves@fmh.ulisboa.pt (F.B.A.); daliacurto@fmh.ulisboa.pt (D.C.)
4
Interdisciplinary Center for the Study of Human Performance (CIPER), Faculdade de Motricidade Humana,
Universidade de Lisboa, 1499-002 Cruz Quebrada-Dafundo, Portugal
5
Training Optimization and Sports Performance Research Group (GOERD), Faculty of Sport Science,
University of Extremadura, 10003 Cáceres, Spain
6
Department of Physical Education, São Paulo State University (UNESP), Bauru 17033-360, Brazil;
dalton.pessoa-ﬁlho@unesp.br
7
Institute of Bioscience, Graduate Program in Human Development and Technology, São Paulo State
University (UNESP), Rio Claro 13506-900, Brazil
*
Correspondence: joanareis@fmh.ulisboa.pt; Tel.: +351-21-414-9100
Abstract: We aimed to compare the velocity, physiological responses, and stroke mechanics between
the lactate parameters determined in an incremental step test (IST) and maximal lactate steady state
(MLSS). Fourteen well-trained male swimmers (16.8 ± 2.8 years) were timed for 400 m and 200 m
(T200). Afterwards, a 7 × 200-m front-crawl IST was performed. Swimming velocity, heart rate
(HR), blood lactate concentration (BLC), stroke mechanics, and rate of perceived exertion (RPE) were
measured throughout the IST and in the 30-min continuous test (CT) bouts for MLSS determination.
Swimming velocities at lactate threshold determined with log-log methodology (1.34 ± 0.06 m·s−1)
and Dmax methodology (1.40 ± 0.06 m·s−1); and also, the velocity at BLC of 4 mmol·L−1 (1.36 ± 0.07)
were not signiﬁcantly different from MLSSv, however, Bland–Altman analysis showed wide limits of
agreement and the concordance correlation coefﬁcient showed poor strength of agreement between
the aforementioned parameters which precludes their interchangeable use. Stroke mechanics, HR,
RPE, and BLC in MLSSv were not signiﬁcantly different from the fourth repetition of IST (85%
of T200), which by itself can provide useful support to daily practice of well-trained swimmers.
Nevertheless, the determination of MLSSv, based on a CT, remains more accurate for exercise
evaluation and prescription.
Keywords: well-trained swimmers; maximal lactate steady state; lactate threshold; continuous test;
incremental test; performance markers
1. Introduction
Performance enhancement in sport is closely and decisively related to accuracy in
identifying exercise intensities domains toward the optimization of daily training. Speciﬁ-
cally, the determination of the boundaries (thresholds) that separate the individual training
zones can induce optimal adaptations in athletes and should be periodically assessed
to evaluate training effects [1]. Over the years, this has been challenging for athletes,
coaches, and researchers largely because the time spent in testing procedures may interfere
with the training routines, and fundamentally, the high costs with equipment prevents its
widespread use. Nevertheless, the combination of high accuracy with less time demanding
Int. J. Environ. Res. Public Health 2021, 18, 477. https://doi.org/10.3390/ijerph18020477
https://www.mdpi.com/journal/ijerph
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or invasive procedures sustains the drive for continuing research on the applied physiology
of sports training [2].
Lactate threshold (LT) was originally deﬁned as the onset of blood lactate above
resting values from a blood lactate velocity curve obtained in an incremental step test
(IST) [3]. It represents the ﬁrst increase of a metabolic acidosis and oxidative capacity
of athletes and is a strong determinant of performance within populations of similar
maximum oxygen uptake [4]. It is also an important reference point when setting training
intensities for endurance athletes, having previously been considered by some researchers
as a good surrogate of maximal lactate steady state (MLSS) [5], which by itself represents
not only a boundary intensity between the heavy and severe intensity domains but also
a biomechanical boundary beyond which stoke length (SL) becomes compromised over
time [6]. However, multiple deﬁnitions and methods to determine LT have arisen in
the literature. It has been considered as the initial rise in BLC above rest, the onset of a
ﬁxed blood lactate accumulation ranging from 2.0 to 4.0 mmol L−1, or with curve ﬁtting
procedures [7]. These methods seem to be correlated, but their relationship with the
boundaries that separate the intensity domains are affected by the methodology chosen,
without a clear physiological support for the preference of one of them [8].
The swimming velocity at LT (vLT) is one of the most frequently used indices to
assess the swimming endurance capacity [9,10] and several methods are utilized for its
calculation [11]. More speciﬁcally, the log-log methodology (vLTlog-log), the velocity at
which lactate increased exponentially when the log blood lactate concentration (BLC)
is plotted against the log swimming velocity [12], Dmax methodology (vLTDmax) as the
maximal perpendicular distance of the lactate curve from the line connecting the start with
the endpoint of the lactate curve [13]. On the other hand, V4 is the the swimming velocity
eliciting a lactate concentration of 4 mmol.L−1 through linear interpolation and has been
associated with the onset of blood lactate accumulation (OBLA) [14]. More speciﬁcally,
a 7 × 200-m IST is used to identify aerobic training intensity domains and subsequent
changes during a year-round training plan [15].
Heck et al. [5] were pioneers with respect to the MLSS concept, ﬁrst considered to
occur at a ﬁxed BLC of 2.2 mmol L−1 [16], but more often to 4 mmol L−1, or deﬁned as
OBLA [5]. Later, it was observed that the absolute BLC at MLSS velocity (MLSSv) varied
considerably between individuals and between exercise modalities [17]. However, it is
considered to be the best predictor of aerobic endurance performance [18], deﬁned as the
highest constant exercise intensity that can be sustained while maintaining equilibrium
between the processes of blood lactate accumulation and elimination [1]. It is noteworthy
that very recently Jones et al. [19] outlined concerns with the arbitrariness of the deﬁnition
of, and the procedures for evaluating MLSS, indicating that progress in these ﬁelds has
been slowed by the disagreement over deﬁnitions and procedures, and by a ﬁxation with
the behavior of a single biomarker, BLC.
The methodology associated with MLSS determination separates it from most other
lactate parameters. The major methodological difference is that it requires several exercise
bouts of longer duration (30-min) to be performed in different days at a constant exercise
intensity, a constant intensity test (CT), a method that is very time-consuming and demand-
ing. MLSS is attained when, in a CT lasting at least 30-min, the BLC does not increase
more than 1.0 mmol L−1 after the 10th testing minute [20] and Billat et al. [18] stated that
to achieve a true MLSS it is necessary to have four or ﬁve prolonged exercise sessions of up
to 30-min duration.
Over the last 10 years, studies related to MLSS in swimming are scarce, namely those
using unimpeded swimming (without oxygen uptake breath by breath apparatus), and
the large majority present MLSSv below 1.30 m·s−1, which can preclude the application
of those results to well-trained or high-level swimmers. Some examples are studies with
twelve adult middle-distance and long-distance male swimmers which found a MLSSv
of 1.22 ± 0.05 m·s−1 [6], with ten male swimmers and a MLSSv of 1.17 ± 0.11 m·s−1 [21]
and with seventeen long-distance swimmers with a MLSSv of 1.09 ± 0.14 m·s−1 [9]. More
Int. J. Environ. Res. Public Health 2021, 18, 477
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recently, evaluating twenty well-trained competitive swimmers MLSSv was determined
at 1.29 ± 0.05 m·s−1 [22] and Nikitakis et al. [23] observed that MLSSv was higher in
adolescents compared to children (1.297 ± 0.056 m·s−1 vs. 1.083 ± 0.065 m·s−1).
To overtake the time-consuming limitations of the CT, researchers developed an at-
tempt to determine MLSS from a BLC curve obtained during a swimming IST [11,24] fact
that is somewhat controversial in the scientiﬁc community, namely the interchangeably use
of ISTs and CTs to provide useful indexes of aerobic potential [25]. Despite LT and MLSS
being regularly considered fundamental physiological concepts in sport [17] most of the
studies were conducted in the laboratory using ergometers in the context of running and
cycling [26]. Therefore, research in swimming is scarce compared to other sports because
of the swimming pool constrains. In an individual sport where results and medals are
regularly decided by hundredths of a second, the accuracy of training prescription becomes
extremely relevant. Additionally, from a practical point of view, swim coaches and sport sci-
entists require accurate methods that allow them to evaluate the progress of their swimmers
and to ﬁne point the training prescription with minimal training time interference. Thus,
it is necessary to have an in-depth understanding of assessment protocols and associated
swimmer responses, namely from a physiological and stroke mechanics perspective in
order to select the most suitable evaluation protocols and interpret their results.
Therefore, the purpose of this study is to determine if the velocities associated with the
lactate parameters determined from a single IST is equivalent to MLSSv determined from
several CT. Additionally, we intent to ascertain if the stroke and physiological parameters,
representative of MLSS, are similar to those obtained during the IST.
2. Materials and Methods
2.1. Study Design
Athletes performed a total of four visits to the water training facility within a 10-day
period. On the ﬁrst visit, all athletes provided written consent to participate in this study,
as well as performed an anthropometric and body composition evaluation. Afterwards, the
athletes performed a maximal 400-m front crawl (T400) in order to use the average velocity
between 50 and the 350 m as an estimate of the maximal aerobic velocity (MAV) [27]. After
one week, swimmers performed the IST. In days 3 and 4, the continuous swimming velocity
MLSS tests (CT) were completed, ﬁrst at 90% of MAV and in day 4 at 95% of MAV. Figure 1
illustrates the experimental protocol.
Figure 1. Schematic representation of the experimental protocol. IST, incremental step test; MLSS,
maximal lactate steady state test (continuous test); MAV, maximal aerobic velocity.
2.2. Participants
Fourteen male competitive swimmers volunteered for this study (mean ± SD;
16.8 ± 2.8 years, 1.78 ± 0.05 m, 66.5 ± 7.2 kg and 10.2 ± 2.6% of body fat). The in-
clusion criteria were: (1) regularly competing at national level for at least three years and
(2) time in 400-m front crawl below 4:35-s. The exclusion criteria were: (1) swimmers with
<14 years of age; and (2) swimmers injured three months before experimental protocol.
Subjects trained regularly at competitive level for at least eight years (seven to eight swim
sessions and 3–4 gym sessions per week the months before data collection with a mean
Int. J. Environ. Res. Public Health 2021, 18, 477
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swimming volume of 40-km per week) and took no drugs or medicine during the study.
Mean performance in 400-m front crawl swimming was determined the week before testing
(4:22 ± 0:11-s), corresponding to 81% of the short course world record. All swimmers
were familiar with the swimming pool exercise testing procedures. The swimmers were
instructed to refrain from intense training sessions at least 24 h before the experimental ses-
sions and to retain their normal nutritional habits. All subjects or their parents/guardians
(when appropriate) signed an informed consent form prior to participation in the research.
The study was approved by the local University Ethical Committee in Human Research
from São Paulo State University (UNESP—CAAE:02402512.7.0000.5398) and conducted in
accordance with the 1975 Declaration of Helsinki.
2.3. Procedures
Tests were conducted at similar time of the day (±2 h) for each swimmer in order
to minimize the circadian effect on performance [28] and in separate days (with at least
24 h of rest between tests) in a 25-m swimming pool with the water temperature at 28.2 ◦C.
Body composition was assessed with Tanita BC-543 (Tokyo, Japan) and all tests were swum
in front crawl. A standardize warm-up of 600-m aerobic swim of low to moderate intensity
was completed in every testing session. During the IST and CT, swimming velocity was
controlled through a visual pacer (TAR. 1.1, GBK-electronics, Aveiro, Portugal), with
ﬂashing lights on the bottom of the pool, helping swimmers to keep up the predetermined
swimming velocity. Split times over 50-m were determined and used by two investigators
positioned at 7.5 and 17.5-m of the swimming pool to control athletes’ swimming pace.
Within a 10-day period, each subject was asked to complete the following tests.
2.3.1. Maximal Lactate Steady State
Subjects performed, in different days, 30 min constant swimming velocity at 90 and
95% of MAV. Each swimmer was asked to maintain the pre-established swim pace for as
long as possible. The test was interrupted when the swimmer could no longer match the
required swimming velocity. Each subject was stopped 30-sec every 400-m for blood sample
collection determined in ﬁngertip using the Lactate Pro portable analyzer (Arkray, Kyoto,
Japan). MLSS was deﬁned as the highest BLC that increased by no more than 1 mmol.L−1
during the ﬁnal 20-min of a 30-min CT [29]. When this criterion was not accomplished, the
test was stopped. MLSSv was the swimming velocity associated with MLSS.
Rate of perceived exertion (RPE) was determined in a 6 to 20 scale [30] by verbal
indication of the swimmers in the 30-sec stop every 400-m, while blood sample was
being collected.
According to the proposal of Craig and Pendergast [31], stroke rate (SR) was cal-
culated for each cycle using the equation (SR = 60/stroke duration) and expressed in
cycles per minute (cycles min−1). Stroke length (SL) was determined with the equation
(SL = V/SR/60) and expressed in meters per cycle (m-cycle−1).
SR was measured from three stroke cycles taken in the middle of the pool for every
50 m, SR was measured from three stroke cycles taken in the middle of the pool for every
50 m and averaged based on 100-m distance during the last 20-min swim for the CT tests
and the last 100 m of each step for the IST.
The average of heart rate (HR) values collected during the last 20 min of MLSS were
determined with Polar Sport Tester (S410), with frequency every 5 s during tests.
2.3.2. Incremental Step Test
Swimmers T200 (performance time in 200-m front crawl) was assessed in formal com-
petition with a maximum distance of 2 months for the determination of the IST swimming
velocities. Afterwards, in a separate session, swimmers completed 7 × 200-m front crawl
IST [10]. All steps started each 5-min, the ﬁrst one at 70% of T200 and the subsequent with
a 5% increment. At rest, immediately after each step and at the end of the tests, RPE and
BLC were recorded. HR, SR, and SL were measured throughout the test.
Int. J. Environ. Res. Public Health 2021, 18, 477
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The BLC values were registered, and the results were plotted against the respective
swimming velocities using Lactate-E software [32]. LT was determined according to the
log-log methodology (LTlog-log), the velocity at which lactate increased exponentially when
the log BLC is plotted against the log swimming velocity [12]. LT was also measured
according to Dmax methodology (LTDmax) as the maximal perpendicular distance of the
lactate curve from the line connecting the start with the endpoint of the lactate curve [13].
vLTDmax and vLTlog-log were the swimming velocities associated to both LT method-
ologies. V4 was considered as the swimming velocity eliciting a lactate concentration
of 4 mmol L−1 through linear interpolation [14]. Vmax was assumed as the swimming
velocity performed in the last repetition of the IST (100% T200).
2.4. Statistical Analysis
The data are expressed as the mean ± standard deviation (SD). The normality of the
distributions was assessed with the Shapiro–Wilk test, parametric statistical procedures
were selected. Linear regression models between swimming velocities in continuous
test (MLSSv) and IST (V4, vLTDmax and vLTlog-log) were computed. Trendline equation,
determination coefﬁcient (R2), and standard error of estimation (SEE) were calculated.
Comparisons of swimming velocities were evaluated using standardized differences with
combined variance, derived from the M and SD of each variable, with 95% conﬁdence
intervals. Paired-samples t-test was used to compare swimming performance markers
using standardized differences with combined variance, derived from the M and SD of
each variable, with 95% conﬁdence intervals. The statistical limits for the effect sizes
Cohen’s d [33] were trivial (0–0.2), small (0.2–0.6), moderate (0.6–1.2), large (1.2–2), very
large (2–4), and extremely large (>4) [34]. The variance analysis (ANOVA) was used to
verify the differences between swimming velocities, the magnitude of the differences was
evaluated by eta square (small 0.01 ≤ η2
p < 0.06), moderate (0.06 ≤ η2
p < 0.15), or large
(η2
p ≥ 0.15) [33]. The post-hoc Bonferroni test was also performed in order to verify which
pairs of means were signiﬁcantly different (p < 0.05). Bland–Altman plot [35] was used
to assess the agreement between MLSSv, vLTlog-log, vLTDmax, and V4 showing the bias
and the limits of agreement. Also, the concordance correlation coefﬁcient (CCC) was
performed using the Lin [36] approach with MedCalc® v11.1.1.0 (2009) software. The CCC
(ρc) contains a measurement of precision ρ and accuracy (ρc = ρ Cb): where ρ is the Pearson
correlation coefﬁcient, which measures how far each observation deviates from the line
of best-ﬁt and is a measure of precision, and Cb is a bias correction factor that measures
how far the best-ﬁt line deviates from the 45◦ line through the origin and is a measure of
accuracy. Data analysis was performed using the Statistical Package for Social Sciences
(SPSS 25.0, SPSS. Inc., Chicago, IL, USA).
3. Results
All the fourteen swimmers were able to perform the 30-min constant swimming at
90% of MAV within the criteria established to assume the MLSS and stopped their CTs
at an intensity equal to 95% of MAV because of exhaustion. MLSSv (1.36 ± 0.06 m·s−1),
was signiﬁcantly lower compared to Vmax (1.53 ± 0.07 m·s−1; 112% MLSSv) and MAV
(1.51 ± 0.07 m·s−1; 111% MLSSv). Vmax and MAV were not signiﬁcantly different (p > 0.05).
vLTDmax (1.40 ± 0.06 m·s−1; 103% MLSSv), V4 (1.36 ± 0.07 m·s−1; 100% MLSSv), and
vLTlog-log (1.34 ± 0.06 m·s−1; 99% MLSSv) were not signiﬁcantly different to MLSSv. In
Table 1 is presented the comparative analysis between the different swimming velocities.
Int. J. Environ. Res. Public Health 2021, 18, 477
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Table 1. Comparative analysis between different swimming velocities.
Anova One-way
Tests
M ± SD
F
p
η2p
Post-Hoc Test Bonferroni
Vmax (m·s−1)
1.53 ± 0.07
22.20
0.00
0.58
MAV (1.000); vLTDmax (0.000); MLSSv
(0.000); V4 (0.000); vLTlog-log (0.000)
MAV (m·s−1)
1.51 ± 0.07
Vmax (1.000); vLTDmax (0.000); MLSSv
(0.000); V4 (0.000); vLTlog-log (0.000)
vLTDmax (m·s−1)
1.40 ± 0.06
Vmax (0.000); MAV (0.000); MLSSv
(1.000); V4 (1.000); vLTlog-log (0.452)
MLSSv (m·s−1)
1.36 ± 0.06
Vmax (0.000); MAV (0.000); vLTDmax
(1.000); V4 (1.000); vLTlog-log (1.000)
V4 (m·s−1)
1.36 ± 0.07
Vmax (0.000); MAV (0.000); vLTDmax
(1.000) MLSSv (1.000); vLTlog-log (1.000)
vLTlog-log (m·s−1)
1.34 ± 0.06
Vmax (0.000); MAV (0.000); vLTDmax
(0.452) MLSSv (1.000); V4 (1.000)
M ± SD, mean ± standard deviation; Vmax, swimming velocity performed in the last repetition of the incremental step test; MAV, maximal
aerobic velocity; vLTDmax, swimming velocity associated to lactate threshold determined from Dmax methodology; MLSSv, swimming
velocity associated to maximal lactate steady state; V4, swimming velocity eliciting a lactate concentration of 4 mmol.L−1; vLTlog-log,
swimming velocity associated to lactate threshold determined from log-log methodology. Note: Anova one-way F, p and η2
p related to all
swimming velocities. Signiﬁcant differences between swimming velocities (p < 0.05) are observed with post-hoc test.
Regression analysis between MLSSv and V4 revealed adjusted r2 value of 0.81 with
a SEE of 0.027, in spite of standardized residuals remaining within the 95% conﬁdence
interval limits, indicating a fairly good estimation model. The linear regressions with r2
and SEE values between MLSSv, V4, vLTlog-log, and vLTDmax are presented in Figure 2.
Figure 2. Linear regression of MLSSv on V4, vLTlog-log, and vLTDmax with standard error of estimate (SEE).
The agreement between MLSSv and V4 is shown in Figure 3. The 95% limits of
agreement (Loa) ranged from −0.059 to 0.066. Although the bias was 0.004 and there was
no relation between the difference and the mean of the parameters there were somewhat
wide limits of agreement (±5.1%). The bias between MLSSv and vLTlog-log was −0.016 and
the Loa ranged between −0.039 and 0.072, representing a variation of ±4.1% of MLSSv.
There was not a signiﬁcant trend between the difference and the mean of the two measures.
The MLSSv was overestimated by the vLTDmax with a bias of −0.038 with somewhat wide
Loa ranging between −0.092 and 0.017, representing a variation of ±4.1% of MLSSv. There
was not a signiﬁcant trend between the difference and the mean of the two measures.
Int. J. Environ. Res. Public Health 2021, 18, 477
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Figure 3. Bland-Altman plot showing the bias and limits of agreement between MLSSv, vLTDmax, and vLTlog-log.
CCC of the methods are shown in Table 2, where <0.90 indicates a poor strength of
agreement between the methods.
Table 2. Concordance correlation coefﬁcient between MLSSv and the three lactate indexes determined
in the incremental step test.
CCC
Precision
Accuracy
V4 (m·s−1)
0.88
0.90
0.98
vLTlog-log (m·s−1)
0.86
0.89
0.96
vLTDmax (m·s−1)
0.74
0.90
0.83
CCC, concordance correlation coefﬁcient; V4, swimming velocity eliciting a lactate concentration of 4 mmol.L−1;
vLTlog-log, swimming velocity associated to lactate threshold determined from log-log methodology; vLTDmax,
swimming velocity associated to lactate threshold determined from Dmax methodology.
In IST, it was observed that swimmers tend to neglect SL with the purpose of
maintaining the pre-establish swimming velocity throughout all the 7 × 200-m repeti-
tions. Above 85% T200, a stroking efﬁciency breakpoint was observed in all well-trained
swimmers, SR and SL in the fourth repetition in the IST (85% of T200) (respectively
33.88 ± 3.89 cycles min−1 and 2.50 ± 0.32 m cycle−1) were signiﬁcantly different (p < 0.01)
compared to the ﬁfth repetition, at 90% T200 (respectively 36.77 ± 3.20 cycles min−1 and
2.40 ± 0.23 m cycle−1). SL in the third IST repetition (80% of T200 = 2.59 ± 0.31 m cycle−1)
was signiﬁcantly higher compared to the fourth and also SL at MLSSv (2.54 ± 0.33 m cycle−1;
p < 0.01). 85% T200 (1.36 ± 0.05 m·s−1) was not signiﬁcantly different from MLSSv (p > 0.05),
ES was trivial (0.07), and a close relationship between stroke and physiological markers
was observed between both, presented in Table 3.
Table 3. Mean and standard deviation of performance markers during MLSS test and fourth repetition
in the incremental step test, at 85% T200.
Variable
MLSSv
85% T200
t
p
Cohen’s d
HR (beats.min−1)
174.2 ± 7.0
169.5 ± 6.2
1.841
0.077
−0.70
SR (cycles.min−1)
32.76 ± 4.07
33.88 ± 3.89
−0.749
0.461
0.28
SL (m.cycle−1)
2.54 ± 0.33
2.50 ± 0.32
0.269
0.790
−0.10
BLC (mmol.L−1)
4.84 ± 1.53
4.83 ± 0.94
0.015
0.988
−0.01
RPE (6–20 scale)
13.50 ± 1.50
13.28 ± 0.72
0.479
0.637
−0.18
MLSSv, swimming velocity associated to maximal lactate steady state; T200, performance time in 200-m front
crawl; HR, heart rate; SR, stroke rate; SL, stroke length; BLC, blood lactate concentration; RPE, rate of perceived
exertion. ES are considered trivial (0–0.2), small (0.2–0.6), moderate (0.6–1.2), large (1.2–2), very large (2–4) and
extremely large (>4) (Cohen’s d). In all cases p > 0.05 represent no signiﬁcant statistical differences.
Int. J. Environ. Res. Public Health 2021, 18, 477
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Although not signiﬁcantly different, in HR the p value and Cohen’s d revealed values
close to signiﬁcant differences. MLSS ranged between 2.6 and 7.1 mmol L−1 and mean
LTD-max (5.1 ± 0.7 mmol L−1; range 3.9 and 6.2) was not signiﬁcantly different from MLSS,
however, LTlog-log (3.8 ± 0.7 mmol.L−1; range 2.6 and 4.5) was lower (p < 0.01). Mean RPE
during MLSS test was 13.5 ± 1.5, associated to “somewhat hard” with values ranging from
11 to 16 and in the fourth repetition in IT (85% of T200) from 12 to 15.
4. Discussion
The purpose of this study was to determine if the velocities associated with different
lactate parameters determined from IST are equivalent to MLSSv determined from a CT.
Additionally, we intent to ascertain if the stroke and physiological parameters, represen-
tative of MLSS, are similar to those obtained during the IST. The ﬁrst main ﬁnding in
the present study was that MLSS can be determined in well-trained swimmers with only
two to three attempts of 30-min constant swimming velocity performed in different days
assuming the ﬁrst swimming test at 90% MAV, the swimming velocity at which athletes
participating in our study achieved the MLSS. Second, although it is interesting to speculate
if an IST provides reliable indicators of MLSS, we veriﬁed that from a practical perspective,
daily training, some outputs may be useful for swimmers and coaches, but an accurate
evaluation of MLSS is only possible through the traditional methodology, a CT.
Although there was not a signiﬁcant statistical difference between MLSSv, V4,
vLTlog-log, and vLTDmax, there was a poor CCC (<0.90) between the MLSSv and the other
three lactate indexes, which precludes the use of these measures interchangeably. V4 did not
present a bias when compared with MLSSv determined in a CT, however, Bland–Altman
analysis showed somewhat wide limits of agreement (±5.1%), which in a practical point
of view can represent meaningful differences. For example, a swimmer with a MLSSv
of 1.36 m·s−1 can have a V4 of 1.41 or 1.32 m·s−1, which represents a difference of 4 sec
each 100 m. Regarding vLTlog-log, it underestimated MLSSv by 0.02 m·s−1 with limits
of agreement of ±4.1%. Conversely vLTDmax was consistently higher than MLSSv by
0.04 m·s−1, with Bland–Altman analysis also showing limits of agreement of ±4.1%.
Previously, a MLSSv of 1.22 ± 0.09 m·s−1, representing 88.9 ± 3.3% of MAV, was found
in eleven male well-trained competitive swimmers [37]. Also, Baron et al. [29] in ten well-
trained competitive swimmers showed that MLSS corresponded to the velocity a swimmer
spontaneously chooses during the ﬁrst 15 min of a 2-h test. These authors also observed
a MLSSv of 1.22 ± 0.14 m·s−1, corresponding to 86.5 ± 5.1% of MAV (1.41 ± 0.12 m·s−1).
Later, Espada, and Alves [38] also observed a MLSSv of 1.34 ± 0.06 m·s−1 corresponding
to 89.7 ± 1.7% of MAV. However, another study conducted with twelve middle-distance
and long-distance male swimmers showed that the stroke parameters and BLC were
signiﬁcantly different between MLSSv (1.22 ± 0.05 m·s−1; 88.6 ± 1.1% of MAV) and 102.5%
MLSSv (1.25 ± 0.04 m·s−1; 91.3 ± 1.1% MAV) [6].
In the present study, swimmers were able to perform 30-min at 90% of MAV, which
can be related with the level of the swimmers participating in our study since to our best
knowledge this is the ﬁrst study to compare the speed, physiological and stroke parameters
determined from the IST and CT methods in well-trained swimmers with MLSSv above
1.35 m·s−1. However, in previous research some swimmers were able to complete 30-min
at 90% MAV, although, without meeting MLSS criteria. For example Dekerle et al. [37]
reported that ﬁve swimmers could complete the 30-min swim but increased their BLC
values by more than 1 mmol L−1 between the 10th min (4.4 ± 1.6 mmol L−1) and the
30th min (5.9 ± 1.9 mmol L−1) and in Pelarigo et al. [6] study, the 102.5% MLSS intensity
was maintained without exhaustion in the 30-min test but the criteria to be considered
MLSS was also not accomplished.
Int. J. Environ. Res. Public Health 2021, 18, 477
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Lower MLSS values were found in studies conducted with swimmers, which can be
attributed to the lower MLSSv values compared to our study. Also lower values were
evident in rowers (3.1 ± 0.5 mmol L−1) but higher in cyclists (5.4 ± 1.0 mmol L−1) and
speed skaters (6.6 ± 0.9 mmol L−1) [17]. In cycling, Van Schuylenbergh et al. [39] found
a signiﬁcant correlation between MLSS workload and V4, which led to the indication
that LT (determined from Dmax methodology) was closely correlated with MLSS power
(r = 0.72). Though, these authors point out that the validity of MLSS predicted from an
IST must be veriﬁed by a 30-min constant load test. In swimming, a signiﬁcant correla-
tion between LT and V4 (r = 0.90; p < 0.01) [40] was found and a study conducted with
ﬁve male long-distance swimmers and eight triathletes showed that vLT (determined
from Dmax methodology), although higher, was not signiﬁcantly different than MLSSv
(1.18 ± 0.08 m·s−1 and 1.13 ± 0.08 m·s−1, respectively) [41]. Conversely, Fernandes et al. [9]
determined V4 and V8 (swimming velocity at 8 mmol.L−1) by linear interpolation or ex-
trapolation of the lactate BLC vs. velocity curve in a IST (respectively 1.20 ± 0.15 and
1.30 ± 0.17 m·s−1), with both being signiﬁcantly higher than MLSSv (1.09 ± 0.14 m·s−1) in
seventeen long-distance swimmers. Although previous research reported that the 7 × 200
protocol is sensible to different training regimens [42] our results seem to conﬁrm that the
parameters derived from this protocol cannot be used interchangeably with the MLSS gold
standard determination protocol.
Furthermore, our results also conﬁrm that it is impossible to link the true MLSS
to a ﬁxed lactate concentration as it was previously pointed [5], because MLSS ranged
from 2.6 to 7.1 mmol.L−1. It should be noted that MLSS in swimming is affected by brief
interruptions in exercise that are necessary for blood sampling. On the other hand, it
was recently indicated that 30 to 45-sec passive recovery between 10 × 200-m swimming
repetitions enables steady BLC, oxygen uptake and HR similar to MLSS [23]. However,
we must acknowledge that the dynamic interaction between the rates of muscle lactate
production, lactate efﬂux from muscle to blood, and lactate clearance/metabolism both
within muscle and from the blood by other organs [43], means that a steady-state in
BLC need not imply the existence of a bioenergetic steady-state in contracting skeletal
muscle [19]. These authors indicated that BLC per se, is neither an appropriate nor a
sufﬁciently sensitive metric to enable a conﬁdent assessment of whether a speciﬁc velocity
or power output may be sustainable in a metabolic steady-state muscle.
Pelarigo et al. [6], found a MLSSv of 1.22 ± 0.05 m·s−1 and a T200 of 1.45 ± 0.05 m·s−1
which means that MLSSv corresponded to around 84% of T200. Additionally, another study
indicated that the decrease in SL started above 85% of MAV [37] and Fernandes et al. [9]
observed that SR was different across the 7 × 200-m particularly after the 4th repetition.
It was previously stressed that MLSS could represent an intensity to develop aerobic
endurance and perform technical work of very-high-standard quality [29,37], fact that
was conﬁrmed by Pelarigo et al. [6] research where the MLSS (3.28 ± 0.97 mmol.L−1) was
signiﬁcantly lower than BLC at 102.5% MLSSv (4.59 ± 1.36 mmol.L−1) and the SR was
maintained in MLSSv between 10th and 30th minute and signiﬁcantly increased at 102.5%
MLSS, contrary to SL, maintained during the 30 min swam at MLSS but signiﬁcantly
decreased at 102.5% MLSSv.
Our study revealed that during IST, the SR and SL at 85% of T200, the fourth repetition,
were closely related to those observed at MLSS throughout the 30 min CT and tend to repre-
sent a boundary of the swimming efﬁciency, showing that the transition from the heavy to
the severe intensity domain is not only related to swimming velocity, RPE and BLC, but also
to stroke parameters. The values we measured in MLSS (SR 32.8 ± 4.1 cycles.min−1/SL
2.54 ± 0.33 m.cycle−1) in well-trained swimmers were also higher compared to previous
studies, such as Dekerle et al. [37] (27.7 ± 2.2 cycles.min−1; 2.64 ± 0.32 m.cycle−1) or
Pelarigo et al. [6] (30.9 ± 3.4 cycles.min−1; 2.47 ± 0.2 m.cycle−1), fact that we consider
associated to the level of swimmers participating in the different studies.
Int. J. Environ. Res. Public Health 2021, 18, 477
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Baron et al. [44] veriﬁed that during exercise performed at MLSS, exhaustion occurred
while physiological reserve capacity still existed, but in association with an increase in the
RPE, as predicted by the central governor model. This research team added that exercise
termination may be induced by an integrative homoeostatic control of the peripheral phys-
iological system speciﬁcally to ensure the maintenance of homeostasis. Demello et al. [45]
indicated that LT occurs at a feeling of “somewhat hard” and “hard” from the RPE per-
spective, with values ranging from 12.9 to 13.6. Our results are in line with these previous
observations, although the CT values ranged from 11 to 16 and in the 4th repetition, in IST
(85% of T200) from 12 to 15, fact that led us to agree with previous literature stating that the
use of an absolute RPE value to prescribe exercise intensity is unwise [46] because of the
fairly large between-subject variability. Also, Potteiger and Weber [47] investigated RPE
during incremental and constant intensity exercise and concluded that RPE cannot be used
as a particularly accurate marker of exercise intensity.
This study presents some limitations since we did not consider the maturation of the
swimmers or their distance specialty, which may be relevant to the training methodological
framework. We also did not evaluate the potential differences regarding sexes since we
only tested male athletes, neither compared results in short- and long-course swimming
pools, factors that make it impossible to generalize our results to the whole swimming
community. Tracking individual responses during the swimming process is crucial for
training prescription and adjustments as inter-individual differences are signiﬁcant in well-
trained athletes. Future research should consider different swimmers’ level, gender, and the
comparison between CT and IST in long-course swimming pool (50-m), with swimming
velocities increment of 2.5%, as implemented by Pessôa-Filho et al. [48]. The possible
measurement of gas exchange could be useful to better understand the physiological,
metabolic, and stroke parameters pathways associated to CT and IST, as well as more
accurately measure LT and MLSS, understanding the athletes holistic fatigue associated to
the gold standard, not only from the BLC perspective.
5. Conclusions
From a practical application perspective, the main ﬁndings of this study show that
in well-trained swimmers MLSSv can be estimated with a maximum two to three 30-min
constant swimming bouts performed in different days starting at 90% of MAV and elevating
or decreasing that exercise intensity in subsequent bouts. This procedure is more practical
and less time consuming than protocols previously suggested which could be important
for coaches and athletes in daily swimming practice.
Moreover, the 90% of MAV or 85% of T200 may be considered aerobic power zones,
where high-quality technique training may occur. In fact, stroke parameters achieved
during MLSSv are very closely related to the fourth repetition of the IST and represent not
only a physiological, but a mechanical boundary above which athletes achieve fatigue and
the swimming technique starts to deteriorate.
Performing an IST in well-trained swimmers can be very useful for practice because it
provides several useful indicators, nevertheless, this methodology should be used with
caution. Also, the level of the swimmers seems to decisively inﬂuence the obtained results,
this fact should be carefully examined in future research.
V4, vLTDmax, and vLTlog-log were not statistically different from MLSSv, nevertheless,
it is our understanding that both the IST and CT in well-trained swimmers provide useful
indexes of aerobic potential, but they cannot be used interchangeably for MLSSv determi-
nation. The direct determination of MLSSv, with CT testing procedure, remains the more
accurate for evaluation and prescription of swimming training and for research purposes.
Int. J. Environ. Res. Public Health 2021, 18, 477
11 of 13
Author Contributions: Conceptualization: M.C.E., J.F.R. and F.B.A.; methodology: M.C.E., J.F.R.
and F.B.A.; formal analysis, F.B.A.; investigation, M.C.E., J.F.R. and F.B.A.; supervision: F.B.A. and
J.F.R.; data curation: M.C.E., D.C., J.F.R., C.C.F. and F.J.S.; writing—original draft preparation: M.C.E.,
J.F.R., C.C.F. and D.M.P.-F.; writing—review and editing: M.C.E., D.C., J.F.R., C.C.F. and D.M.P.-F.;
visualization: F.B.A.; funding acquisition: M.C.E., F.J.S. All authors have read and agreed to the
published version of the manuscript.
Funding: This research was funded by Foundation for Science and Technology, I.P., Grant/Award
NumberUIDB/04748/2020. M.C.E. also acknowledge the ﬁnancial support from Polytechnic Institute
of Setúbal. D.M.P.F. would like to thank São Paulo Research Foundation—FAPESP (PROCESS
2016/04544-3) for the partial support.
Institutional Review Board Statement: The study was conducted according to the guidelines of the
Declaration of Helsinki and approved by the local University Ethical Committee in Human Research
from São Paulo State University (UNESP—CAAE:02402512.7.0000.5398/2013).
Informed Consent Statement: Informed consent was obtained from all subjects or their parents/
guardians (when appropriate) involved in the study.
Data Availability Statement: The data that support the ﬁndings of this study are available from
the corresponding and ﬁrst authors (joanareis@fmh.ulisboa.pt and mario.espada@ese.ips.pt), upon
reasonable request.
Acknowledgments: We would like to express our gratitude to the swimmers for their time and effort
and the swimming teams for making both their infrastructures and staff available for the study.
Conﬂicts of Interest: The authors declare no conﬂict of interest.
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Can an Incremental Step Test Be Used for Maximal Lactate Steady State Determination in Swimming? Clues for Practice.
Espada, Mário C,Alves, Francisco B,Curto, Dália,Ferreira, Cátia C,Santos, Fernando J,Pessôa-Filho, Dalton M,Reis, Joana F