Human Movement Science 49 (2016) 258–266
Contents lists available at ScienceDirect

Human Movement Science

journal homepage: www.elsevier .com/ locate/humov
Full Length Article
Do 5% changes around maximal lactate steady state lead
to swimming biophysical modifications?
http://dx.doi.org/10.1016/j.humov.2016.07.009
0167-9457/� 2016 Elsevier B.V. All rights reserved.

⇑ Corresponding author at: 25 de março, 200, Ap 2403, Fortaleza, Ceará, Brazil.
E-mail address: jailtongp@hotmail.com (J.G. Pelarigo).
Jailton Gregório Pelarigo a,b,c,d,⇑, Camila Coelho Greco e, Benedito Sérgio Denadai e,
Ricardo Jorge Fernandes c,d, João Paulo Vilas-Boas c,d, David Robert Pendergast f

aUniversity Catholic Center of Quixadá – UNICATÓLICA, Quixadá, Ceará, Brazil
bMetropolitan College of Grande Fortaleza – FAMETRO, Fortaleza, Ceará, Brazil
cCentre of Research, Education, Innovation and Intervention in Sport, Faculty of Sport, University of Porto, Portugal
d Porto Biomechanics Laboratory, LABIOMEP, University of Porto, Portugal
eHuman Performance Laboratory, Physical Education Department, São Paulo State University – UNESP, Rio Claro, São Paulo, Brazil
fCenter for Research and Education in Special Environments, Department of Physiology and Biophysics, State University of New York at Buffalo, Buffalo, NY, USA

a r t i c l e i n f o a b s t r a c t
Article history:
Received 6 March 2016
Revised 24 July 2016
Accepted 25 July 2016
Available online 9 August 2016

Keywords:
Aerobic capacity
Gas exchange
Oxygen uptake
Oxygen uptake efficiency
Biomechanical parameters
Our purpose was to examine the swimming biophysical responses at velocities (v) of 97.5,
100 and 102.5% of the maximal lactate steady state (MLSS). Ten elite female swimmers
performed three-to-five 30-min constant tests at imposed paces to determine 97.5, 100
and 102.5%MLSS v. Gas exchange, blood lactate concentration ([La-]), stroke rate (SR)
and v were determined during each test. The v values at 97.5, 100 and 102.5%MLSS were
1.21 ± 0.07, 1.24 ± 0.07 and 1.27 ± 0.07 m.s�1, respectively. Oxygen uptake (V_ O2) and
Pulmonary ventilation (V_ E) increased as function of v. SR and stroke length (v/SR = SL)
increased as a function of v. All measured variables were constant as a function of time
at 97.5%MLSS and 100%MLSS. At 102.5%MLSS SR increased (3.5%) and stroke length (SL)
decreased (3.5%) as a function of time. While V_ O2 was constant at 102.5%MLSS, [La-] and
V_ E increased as a function of time, suggesting hyperventilation, at v’s of 97.5%MLSS and
100%MLSS swimmers completed the 30 min swim in spite of decreased SL and increased
SR. However, the decrease in SL and increased SF were accompanied by increased
[La-] and V_ E and resulted in the inability of most swimmers to complete the 30 min swim
presumably due to fatigue at 102.5%MLSS.

� 2016 Elsevier B.V. All rights reserved.
1. Introduction

At low exercise intensities metabolism is from primarily aerobic sources. However, when exercise intensity increases to
near or above maximal aerobic power a mixture of aerobic and anaerobic sources are used, leading to time dependent
increase in muscle and blood lactate. Since the 1960s, researchers have struggled to understand and define the physiologic
state where there is a significant increase in blood lactate concentration ([La-]) (anaerobic threshold – AnT). Of these
attempts, a recent initial definition was termed endurance performance limit (Hollmann, 2001), which has been redefined
as aerobic-anaerobic threshold, individual anaerobic threshold, anaerobic threshold, lactate turnpoint, and individual lactate
minimum, among other terms (Faude, Kindermann, & Meyer, 2009). Another concept related the AnT to the maximal

http://crossmark.crossref.org/dialog/?doi=10.1016/j.humov.2016.07.009&domain=pdf
http://dx.doi.org/10.1016/j.humov.2016.07.009
mailto:jailtongp@hotmail.com
http://dx.doi.org/10.1016/j.humov.2016.07.009
http://www.sciencedirect.com/science/journal/01679457
http://www.elsevier.com/locate/humov


J.G. Pelarigo et al. / Human Movement Science 49 (2016) 258–266 259
intensity that can be maintained as function of time without blood lactate accumulation, i.e. the maximal lactate steady state
– MLSS (Beneke, 2003). This exercise intensity has been used for the evaluation of aerobic capacity for endurance perfor-
mance and training prescription (Beneke & von Duvillard, 1996; Faude et al., 2009).

The MLSS is considered by many as the direct method for the evaluation of aerobic capacity (Beneke, 2003; Beneke & von
Duvillard, 1996; Faude et al., 2009). MLSS is identified as the highest steady state [La-] that can be maintained during
prolonged sub-maximal and constant workload exercise (Beneke, 2003; Beneke & von Duvillard, 1996). At intensities below
and at the MLSS there is a steady-state of [La-] as function of time and exercise can be sustained (Baron, Dekerle, Depretz,
Lefevre, & Pelayo, 2005). However, when the exercise is performed at intensities above the MLSS intensity, a significant
increase in [La-] is observed as function of time, which is associated with voluntary exhaustion (Beneke & von Duvillard,
1996; Heck et al., 1985).

Although the concepts of AnT and MLSS have been previously used to characterize swimming performance, it is com-
monly accepted that there are bioenergetical and biomechanical factors that may influence these parameters. Further exam-
ination of these factors is needed to better understand their possible interaction, helping to understand the swimmers’
adjustments that occur at intensities around MLSS (Faude et al., 2009) and as a function of swimming time.

The inability to maintain a predetermined swimming intensity (fatigue) may be due to the inability to sustain optimal
biomechanical parameters, as the aerobic system bioenergetics has been shown to be stable as a function of time (Baron
et al., 2005). Physiological mechanisms other than metabolism may be time-dependent, such as the ability to sustain force
and its application to the water (Baron et al., 2005; Dekerle, Nesi et al., 2005; Pelarigo, Denadai, & Greco, 2011). Thus, biome-
chanical factors could change the MLSS swimming velocity (v) (Pelarigo et al., 2011), leading to a reduced v or swim time.

We are unaware of any studies that have evaluated bioenergetical and biomechanical factors at intensities at or around
the 100%MLSS in swimming. To examine the interrelationships of biophysical factors they must be evaluated not only as a
function of intensity, but also as a function of exercise duration to understand what limits performance at these v’s. Thus, the
purpose of this study was to analyze the responses of bioenergetical and biomechanical factors while swimming at 97.5, 100
and 102.5%MLSS. We hypothesized that swimming intensities up to 100%MLSS would not require progressive adjustments of
bioenergetical and biomechanical factors and not limit exercise endurance up to 30 min. However, we hypothesized that
swimming above 100%MLSS would compromise bioenergetical and biomechanical factors which would affect the swimmers
ability to sustain set exercise intensities (v) for 30 min.

2. Methods

Ten elite female swimmers (mean ± SD; aged 17.6 ± 1.9 years, height 1.70 ± 0.05 m, body mass 61.3 ± 5.8 kg and percent-
age of body fat mass 15.5 ± 2.9%; maximal oxygen uptake – V_O2max 54.9 ± 6.7 mL.kg.min�1), who specialized in middle- and
long-distance swimming events participated in the present study. The measurements of body mass and fat were assessed by
a segmental body composition analyzer (Tanita, TBF 305, Tokyo, Japan).

Subjects had, at the least, seven years of experience as competitive swimmers and their mean performance over the
400 m freestyle swim was 88.0 ± 3.4% of the 2016 short course world record. The study was approved by the local ethics
committee and was performed according to the Declaration of Helsinki. Subjects and/or parents gave their written informed
consent before participation in experiments.

The test sessions were performed in a 25 m indoor swimming pool, with water temperature of 27–28 �C and air humidity
of 40–60%. Swimmers were advised to refrain from intense training for at least 24 h before the experiments. The tests were
all conducted within a seven day period, at the same time of the day (±2 h) to minimize the effect of circadian rhythm. In all
test sessions, the swimmers performed a 1000 m warm-up at low/moderate aerobic intensity. During the tests, swimmers
swam front crawl and used in-water starts and open turns without underwater glides.

First, the swimmers performed an intermittent progressive protocol until voluntary exhaustion to determine the individ-
ual anaerobic threshold (IAnT). The predetermined initial v of the swim was set at �80% of the subject’s best time for the
400 m front crawl race (S400), the v was increased by 0.05 m.s�1 for each subsequent step until voluntary exhaustion. Thirty
seconds rest intervals were observed in-between each swim. The distance of each step of the incremental test was 200 m.

Earlobe capillary blood samples (5 lL) were collected and analyzed for [La-] with a portable lactate analyzer (Lactate Pro,
Arkray, Inc., Kyoto, Japan). [La-] was measured at rest and in the first 30 s after each step of the incremental test and, imme-
diately after exhaustion and at each 2 min of recovery from the last step until the [La-] peak was found. The IAnT was
assessed by the relationship between [La-] and v with the lactate inflexion point determined as the interception between
a linear and exponential regressions to estimate the v where [La-] increased exponentially (Fernandes et al., 2006;
Machado, Almeida, Morais, Fernandes, & Vilas-Boas, 2006). If a swimmer did not achieve their maximal v and/or exhaustion
with the pre-defined increases in v, the fastest v the subject completed was used to determine the minimum v eliciting the
V_O2max.

After determining IAnT, each swimmer performed three-to-five 30 min submaximal constant swimming tests at imposed
paces to assess the v where a MLSS was achieved and maintained (100%MLSS). The swimming v was set and maintained
using a visual underwater pacer (GBK-Pacer, GBK Electronics, Aveiro, Portugal), with a light strip on the bottom of the pool.
The light strip had lights located 2.5 m apart for 25 m. The swimmers followed the flashing lights to maintain the predeter-
mined v’s. The swimmers were instructed to swim at a speed by looking at and following the visual signal as the lights



260 J.G. Pelarigo et al. / Human Movement Science 49 (2016) 258–266
proceeded along the pool length. Exhaustion was defined and the test finalized when the swimmers remained 5 m behind
the lights. A 24 h interval was imposed between all the tests.

[La-] was determined at rest, and at the 10th and 30th min (or voluntary exhaustion) of each continuous test as described
above. The first trial was performed at the IAnT v, and, if during the first trial a steady state or a decrease in [La-] was
observed, further subsequent trials with 2.5% higher v were performed until no [La-] steady state was observed. If the first
trial resulted in a clearly identifiable increase of the [La-] and/or could not be sustained due to exhaustion, further trials were
conducted with subsequently reduced v’s (Pelarigo et al., 2011). The MLSS was defined as the highest [La-] that increased by
no more than 1 mmol.L�1 between the 10th and the 30th min of the test (Heck et al., 1985). The corresponding [La-] value
was assumed to be the average of the value at the 10th and 30th min of exercise.

Bioenergetical factors were divided into two categories: oxygen uptake (V_O2) and total energy expenditure (Ė). The latter
was the product of _VO2 and caloric equivalent estimated from respiratory exchange ratio. The energy cost of swimming (C)
per unit distance was calculated from Ė and v (Ė/v = C) and was termed economy. V_O2 was calculated from measures of
expired ventilation (V_ E) and O2 and CO2 fractions by a telemetric portable analyzer (K4b2, Cosmed, Italy), using standard
equations. The end-tidal CO2 (ETPaCO2) was used as an estimate of the arterial CO2. The analyzer was connected to the swim-
mer by a low hydrodynamic resistance respiratory snorkel and valve system (New AquaTrainer�, Cosmed, Italy). This system
has been previously validated and used in similar studies (Baldari et al., 2013; Sousa, Vilas-Boas, & Fernandes, 2014). The
equipment was calibrated prior to each swim for V_ E with a calibrated syringe and the O2 and CO2 analyzers with standard
calibration gases. The values of gas exchange were measured breath-by-breath during all the tests and averaged every 5 s
(Fernandes et al., 2012). The ratio of V_O2 and V_ E was calculated and termed oxygen uptake efficiency (OUE) for all conditions
(Baba et al., 1996). Heart rate (HR) was monitored and registered continuously by a HR monitor system (Polar Vantage NV,
Polar electro Oy, Kempele, Finland) and transferred telemetrically to the K4b2 device. The values of HR were also averaged for
5 s intervals.

The energetic parameters were Ė and C. The C was determined using the caloric equivalent of the V_O2 (kcal.L�1 O2) cal-
culated by the respiratory exchange quotient (Fletcher, Esau, & Macintosh, 2009). The C was calculated using the Eq. (1):
C ¼ _VO2 caloric equivalent � v�1 ð1Þ

where C is energy cost of locomotion calculated by indirect calorimetry expressed as kJ.m.�1, V_O2 was measured in L.min�1,
caloric equivalent is in kcal.L�1, and v is velocity in m.min�1. The energy equivalent was converted to SI units, where 1 kcal is
equivalent to 4.184 kJ.
_E:kg�1 ¼ C � v ð2Þ

The Ė was determined by the product of C and v, corrected by the body mass, where Ė is the total energy expenditure

expressed as mL.kg�1.min�1, C as kJ.m�1, v is velocity in m.min�1, body mass is in kg. The energy equivalents were converted
into the SI units according to di Prampero (1986) where 1 mL O2 is equivalent to 20.9 J.

Biomechanical factors measured were stroke rate (SR), stroke length (SL) and the product of v and SL (stroke index – SI) at
each v studied. The biomechanical analysis was conducted during the pure swimming phase of each lap in the middle of the
pool (between 7.5 and 17.5 m). SR was determined from images of an above-water video camera (DCR-HC42E, Sony, Japan)
operating at a frequency of 50 Hz. The SR and SL were determined from two limbs cycles for each condition and the data
were averaged. The video data were then used to calculate v (m.s�1) and SR (cycles.min�1). SR was determined by the num-
ber of upper limb cycles per unit of time and SL was calculated by the ratio of v and SR.

To normalize for differences in v and time for each subject, the data for the continuous tests at 97.5, 100 and 102.5%MLSS
v’s were normalized to the total time of each swim (100%). The data were split into eight time points corresponding to rest,
the initial steady state determined during the 4th min of the swim and then 25, 33, 50, 66, 75 and 100% of the total duration
of exercise.

The data are presented as mean and standard deviation (±SD). Normality and sphericity of data were checked with the
Shapiro-Wilk’s W and Mauchley tests. When the assumption was not attained, Greenhouse-Geisser or the Huynh-Feld
adjusted univariate tests for repeated measures were used. Beyond descriptive statistics, the analyses of V_O2, V_ E and C
and SR, SL and SI were performed using multivariate ANOVA. The analysis of [La-] and v values were performed using the
univariate ANOVA. All analyses were repeated measures ANOVAs, complemented with the Tukey correction post hoc test.
The significance level of p < 0.05 was used for all comparisons.

3. Results

The results of the experiments are presented for the v’s at 97.5, 100 and 102.5% MLSS intensities. For each v, data at rest,
at the 4th min, and at 25, 33, 50, 66, 75 and 100% of swimming time are also shown. The average v values for the three con-
ditions were different from each other, with 97.5%MLSS slowest and 102.5%MLSS fastest (Fig. 1). All swimmers completed
the 30 min swims at 97.5 and 100%MLSS. However, eight out of the ten swimmers were not able to maintain the predeter-
mined v during the 30 min of the 102.5%MLSS swim, reaching voluntary exhaustion on average at 19.3 ± 4.9 min of exercise.
Regarding the statistical hypothesis decomposition, the interaction effect, i.e., significance level (p < 0.05) between the



Fig. 1. Mean ± SEMI-SD of oxygen uptake corrected for body mass (V_ O2relative), total energy expenditure (Ė), energy cost of locomotion (C) and blood lactate
concentration ([La-]) values at velocities corresponding to 97.5, 100 and 102.5% (slowest to highest velocity, respectively) of the maximal lactate steady
state (MLSS) plotted as a function of velocity. 1,2 Values significantly different to 97.5 and 100%MLSS, respectively (p < 0.05).

J.G. Pelarigo et al. / Human Movement Science 49 (2016) 258–266 261
intensity and its time effects, only occurred with the V_ E and OUE, in which the remaining bioenergetical and biomechanical
variables achieved an intensity and/or time effect.

Fig. 1 presents V_O2, Ė, C and [La-] values as a function of v during the three swimming conditions. Oxygen uptake cor-
rected for body mass (V_O2relative) and Ė increased significantly as a function of v throughout the studied intensities. C
increased as a function of v between 97.5 and 102.5%MLSS. [La-] values were similar at 97.5 and 100%MLSS, however, the
values were higher at 102.5%MLSS. Furthermore, the [La-] values as a function of time were similar at the 10th min and
30th min (or voluntary exhaustion) for 97.5 (1.4 ± 0.3 and 1.6 ± 0.5 mmol.L�1), 100 (1.9 ± 0.8 and 1.9 ± 0.7 mmol.L�1) and
102.5%MLSS (2.8 ± 0.9 and 3.1 ± 1.0 mmol.L�1), respectively.

The bioenergetical and biomechanical parameters are presented in Table 1. The resting values of all parameters were not
different among the three swimming conditions. As expected, the V_O2, and Ė increased significantly as a function of v. C
increased as function of v between 97.5 and 102.5%MLSS. V_ E increased significantly as a function of v’s at 97.5, 100 and
102.5%MLSS. The HR values increased as a function of v and were significantly higher at 102.5%MLSS compared to 97.5%
MLSS. The OUE values were lower at the 4th min and 50, 66, 75 and 100% of swim time at 102.5%MLSS than at 97.5%MLSS.

V_O2 did not significantly change as a function of time for v’s at 97.5, 100 and 102.5%MLSS and averaged 2.62 ± 0.04,
2.82 ± 0.04 and 3.03 ± 0.02 L.min�1, respectively. Similarly Ė and C did not significantly change as a function of time for
v’s at 97.5, 100 and 102.5%MLSS. V_ E did not significantly change as a function of time for v’s at 97.5 and 100%MLSS and aver-
aged 63.94 ± 1.29 and 69.73 ± 1.15 L.min�1, respectively. However at 102.5%MLSS, V_ E increased significantly as function of
time from 75.7 ± 6.7 L.min�1 at 4th min to 82.9 ± 9.4 L.min�1 at 100% of swim time (hyperventilation). The differences for V_ E
described above have to acknowledge that there was a statistical interaction between swimming v (97.5, 100 and 102.5%
MLSS) and the time points (4th min, 25, 33, 50, 66, 75 and 100%) of measurements and for OUE.

ETPaCO2 values were similar at all v’s, at 102.5%MLSS, however, it showed a tendency to be lower (mean = 37.60 mmHg)
than at the two lower v’s (97.5%MLSS – mean = 38.92 mmHg; p = 0.103 and 100%MLSS – mean = 38.99 mmHg; p = 0.083) and
what is considered normal PaCO2 (40 mmHg). Furthermore, the ETPaCO2 values decreased as a function of time in the 102.5%
MLSS swim from the start of the exercise (4th min) to its end for all swimming speeds (F6,54 = 10.328, p < 0.001, ήp2 = 0.499).

Regarding the time effect, the V_O2 values were lower at the 50, 66 and 100% compared to 4th min, and at the 50% com-
pared to 25% of exercise. Subsequent to the decreased V_O2, C and Ė were lower at the 50% time compared to the 4th min and
the 25% time of exercise. The HR values increased at the all swim times compared to the 4th min, as well as at 66, 75 and
100% of exercise compared to the 25%, at 75% and 100% comparing 33%, and comparing 100% than at 50% time point.

OUE decreased as a function of time at the 66, 75 and 100% of the v at 97.5%MLSS compared to the 4th min of exercise at
97.5%MLSS. For the v at 100%MLSS, OUE was significantly lower at 66% of swim time compared to the 4th min. For the v at
102.5%MLSS, OUE was significantly lower at 66, 75 and 100% of swim time compared to the 4th min and 25 and 33% of swim
time exercise, and 100% of swim time compared to the 50%.

Fig. 2 presents the changes in SR, SL and SI values as a function of v during the three swimming intensities. SR values
increased as a function of v for all intensities. SL was lower at 102.5%MLSS compared to 97.5 and 100%MLSS, 4% on average
across exercise times. The SI values were not significantly different among the three v’s and averaged 2.61 ± 0.02, 2.68 ± 0.03
and 2.65 ± 0.05 m2.s�1cycle�1, respectively.

SR’s during all swims were not significantly different up to 50% of exercise time at all v’s. SR’s significantly increased above
50% exercise time up to 100% of exercise time at each v (3–5%). During the 30 min swim, SL and SI were lower at 75% and 100%
MLSS time compared to the 4th min of exercise, and at 100% compared to the 33% and 50%MLSS of exercise time.

4. Discussion

This study analyzed the effects of intensity and time-dependent variation of bioenergetical and biomechanical factors in
swimming at intensities below, at, and above the MLSS. The MLSS is considered a commonly accepted method for the



Table 1
Bioenergetical and biomechanical parameters associated with the velocity at 97.5, 100 and 102.5% of the maximal lactate steady state (MLSS) for the 8 normalized time moments of the swims. Statistical analyses were
described by intensity and/or time effect or interaction effect (N = 10).

Parameters/Effect Intensity Time Moments

Rest 4th min 25% 33% 50% 66% 75% 100%

V_ O2
#* (L�min�1) 97.5%MLSS 0.44 (0.15) 2.68 (0.28) 2.63 (0.29) 2.61 (0.28) 2.58 (0.28)a,b 2.59 (0.30)a 2.65 (0.28) 2.63 (0.28)a

100%MLSS 0.36 (0.05) 2.88 (0.23)1 2.88 (0.22)1 2.81 (0.21)1 2.78 (0.19)1,a,b 2.80 (0.22)1,a 2.81 (0.17)1 2.80 (0.21)1,a

102.5%MLSS 0.39 (0.06) 3.05 (0.21)1,2 3.05 (0.19)1,2 3.06 (0.22)1,2 3.02 (0.21)1,2,a,b 3.00 (0.22)1,2,a 3.03 (0.21)1,2 3.01(0.20)1,2,a

V_ Ey (L�min�1) 97.5%MLSS 14.7 (5.0) 62.4 (8.1) 63.6 (9.6) 63.3 (8.7) 62.9 (8.9) 64.7 (9.5) 66.2 (10.0) 64.5 (9.3)
100%MLSS 12.1 (1.8) 68.6 (8.2)1 70.7 (8.2)1 69.1 (8.4)1 68.4 (7.1)1 71.5 (7.6)1 69.5 (8.3) 70.3 (10.5)1

102.5%MLSS 14.6 (4.5) 75.7 (6.7)1,2 76.3 (5.8)1,2 76.5 (7.2)1,2 78.4 (9.6)1,2 79.8 (8.6)1,2 80.5 (9.3)1,2 82.9 (9.4)1,2,a,b,c

OUEy (mL O2�L�1 V_ E) 97.5%MLSS 31.0 (5.7) 43.3 (3.5) 41.8 (4.2) 41.5 (3.8) 41.3 (3.5) 40.4 (3.2)a 40.4 (4.1)a 41.1 (4.2)a

100%MLSS 30.0 (2.9) 42.3 (3.2) 41.0 (3.5) 41.1 (3.7) 40.9 (4.3) 39.6 (4.7)a 40.9 (4.3) 40.4 (4.8)
102.5%MLSS 28.3 (5.8) 40.5 (3.3)1 40.2 (3.2) 40.2 (3.0) 38.8 (4.1)1 37.9 (3.9)1,a,b,c 38.0 (4.0)1,2,a,b,c 36.6 (4.2)1,2,a,b,c,d

HR#* (bpm) 97.5%MLSS 77.8 (11.7) 160.4 (16.3) 165.2 (15.9) a 166.6 (14.9) a 168.4 (15.4) a 168.4 (16.2)a,b 170.4 (14.7)a,b,c 170.6 (14.7)a,b,c,d

100%MLSS 73.0 (11.5) 168.9 (7.7) 173.3 (9.8) a 173.8 (11.2) a 173.0 (9.6) a 174.7 (10.2)a,b 175.0 (10.9)a,b,c 176.3 (10.5)a,b,c,d

102.5%MLSS 74.1 (11.6) 173.0 (8.8)1 176.8 (10.0)1,a 178.8 (10.2)1va 180.3 (9.7)1,a 181.7 (9.3)1,a,b 182.1 (9.2)1,a,b,c 182.2 (11.1)1,a,b,c,d

C#* (kJ�m�1) 97.5%MLSS 0.17 (0.04) 0.75 (0.06) 0.74 (0.07) 0.73 (0.06) 0.72 (0.05)a,b 0.73 (0.06) 0.74 (0.06) 0.73 (0.06)
100%MLSS 0.16 (0.04) 0.79 (0.06) 0.79 (0.06) 0.77 (0.06) 0.76 (0.06)a,b 0.77 (0.07) 0.77 (0.06) 0.77 (0.07)
102.5%MLSS1 0.14 (0.03) 0.82 (0.06)1 0.82 (0.07)1 0.82 (0.07)1 0.81 (0.06)1,a,b 0.81 (0.07)1 0.81 (0.07)1 0.81 (0.07)1

Ė#* (mL�kg�1�min�1) 97.5%MLSS 9.4 (2.2) 42.8 (6.9) 42.3 (7.0) 41.9 (7.0) 41.4 (6.9)a,b 41.7 (6.9) 42.5 (6.5) 42.0 (6.3)
100%MLSS 9.2 (2.8) 46.0 (5.4)1 46.3 (5.6)1 45.3 (5.9)1 44.5 (5.0)1,a,b 45.2 (5.2)1 45.0 (4.0)1 44.8 (4.8)1

102.5%MLSS 8.3 (1.7) 48.7 (5.0)1,2 48.9 (4.6)1,2 49.1 (5.5)1,2 48.2 (4.9)1,2,a,b 48.0 (4.3)1,2 48.4 (4.5)1,2 48.1 (4.5)1,2

SR#* (cycles�min�1) 97.5%MLSS – 33.4 (3.3) 33.8 (3.4) 33.4 (3.3) 33.6 (3.4) 33.7 (3.2)a 34.1 (3.6)a 34.2 (3.5)a,c,d

100%MLSS – 34.0 (3.3) 34.5 (3.0)1 34.5 (3.1)1 34.4 (3.2)1 34.8 (3.6)1,a 34.6 (3.8)1,a 35.2 (3.8)1,a,c,d

102.5%MLSS – 35.4 (3.3) 36.1 (3.3)1,2 36.2 (3.1)1,2 36.0 (3.3)1,2 36.7 (2.8)1,2,a 37.3 (3.3)1,2,a 37.2 (3.3)1,2,a,c,d

SL#* (m�cycle�1) 97.5%MLSS – 2.18 (0.14) 2.16 (0.14) 2.18 (0.15) 2.17 (0.14) 2.16 (0.13) 2.14 (0.15)a 2.13 (0.15)a,c,d

100%MLSS – 2.20 (0.13) 2.16 (0.12) 2.17 (0.14) 2.17 (0.13) 2.15 (0.15) 2.16 (0.16)a 2.13 (0.16)a,c,d

102.5%MLSS – 2.16 (0.12) 2.12 (0.14)1,2 2.11 (0.14)1,2 2.12 (0.14)1,2 2.08 (0.14)1,2 2.05 (0.13)1,2,a 2.06 (0.14)1,2,a,c,d

SI* (m2�s�1�cycle�1) 97.5%MLSS – 2.63 (0.20) 2.60 (0.20) 2.63 (0.23) 2.62 (0.18) 2.61 (0.19) 2.58 (0.21)a 2.57 (0.20)a,c,d

100%MLSS – 2.72 (0.19) 2.68 (0.21) 2.69 (0.22) 2.69 (0.19) 2.66 (0.21) 2.67 (0.21)a 2.63 (0.21)a,c,d

102.5%MLSS – 2.73 (0.18) 2.68 (0.22) 2.67 (0.24) 2.68 (0.22) 2.63 (0.25) 2.59 (0.21)a 2.60 (0.22)a,c,d

Intensity and/or time effect or interaction effect are indicated in each parameter.
1,2 Values significantly different to 97.5 and 100%MLSS, respectively; a,b,c,d Values significantly different to the 4th min, 25, 33 and 50%, respectively (p < 0.05).
# Intensity effect.
* Time effect.
y Interaction effect.

262
J.G

.Pelarigo
et

al./H
um

an
M
ovem

ent
Science

49
(2016)

258–
266



Fig. 2. Mean ± SEMI-SD of stroke rate (SR), stroke length (SL) and stroke index (SI) values at velocities corresponding to 97.5, 100 and 102.5% (slowest to
highest velocity, respectively) of the maximal lactate steady state (MLSS) plotted as a function of velocity. 1,2 Values significantly different to 97.5 and 100%
MLSS, respectively (p < 0.05).

J.G. Pelarigo et al. / Human Movement Science 49 (2016) 258–266 263
evaluation of aerobic capacity in sports, including swimming (Beneke, 2003; Beneke & von Duvillard, 1996; Faude et al.,
2009). The main findings of the present study were: (a) V_O2, C and Ė were constant throughout the test time duration at each
one of the three studied swimming intensities (97.5, 100 and 102.5%MLSS), while HR increased as a function of time for all
the three v’s studied; (b) at 97.5 and 100%MLSS, bioenergetical factors did not change as a function of time. However, SR
increased and SL decreased as a function of time in the 30 min swims (biomechanical factors) and; (c) at 102.5%MLSS,
although the V_O2 and C were constant as a function of time, V_ E and HR increased as a function of time. With a constant
V_O2 and an increasing V_ E, OUE decreased. The increased [La-] and V_ E are also likely responsible for eight out of ten of
the subjects’ not completing the 30 min swim at 102.5%MLSS due to locomotor and respiratory muscle fatigue (Harms,
Wetter, St Croix, Pegelow, & Dempsey, 2000).

In the present study, gas exchange values (V_O2 and V_ E) were directly measured breath-by-breath as a function of time for
intensities below, at, and above MLSS in swimming. However, previous researchers used measurements during the recovery
period which were back extrapolated to assess V_O2 and V_ E values during prolonged continuous swimming (Baron et al.,
2005; Dekerle, Nesi et al., 2005). The V_O2 values for 100%MLSS in women were lower in the present study (2.83 L.min�1)
compared to those previously reported for men during submaximal exercise that used the back extrapolation from recovery
method (4.94 L.min�1) (Dekerle, Nesi et al., 2005). The lower V_O2 values in the present study could be explained by
differences in the sex of the subjects studied. Women have been reported to have lower muscle mass, and differences in
pulmonary structure (Hopkins & Harms, 2004; Sheel, Richards, Foster, & Guenette, 2004). This is supported by the well-
established lower V_O2 values for female athletes compared to their male counterparts (Rodriguez & Mader, 2011). In spite
of the gender and method differences, the MLSS in the present study for women occurred at 85% (4% SD) of V_O2max, which is
similar to that reported in a previous study for men (86% V_O2peak) (Dekerle, Nesi et al., 2005), the latter based on the mea-
surements of recovery period.

The increase in V_ E values as function of time during the 30 min swimwere stable at the lower v’s. However, at the highest
v studied (102.5%MLSS) V_ E increased as a function of time. The increased V_ E in this study is in accordance with a previous
study (Baron et al., 2003), who reported similar values (�71.6 L.min�1) for cycling at 100%MLSS. The time-dependent
increase in V_ E, with a constant V_O2 and increased [La-] (hyperventilation), likely occurs as a respiratory compensation
secondary to metabolic acidosis as seen in the present study, and likely due to the Ė of swimming at that velocity exceeding
the aerobic supply capacity. The physiological system adjusts cardiopulmonary variables to match the oxygen delivery to the
exercise intensity/v, i.e. the ratio between V_O2 and V_ E. The ratio of V_O2/V_ E has been described as an index of ventilatory
efficiency (OUE) (Baba et al., 1996), which has also been reported to vary among different athletes (Pelarigo et al., 2014),
and was decreased in this study at the highest v, and as a function of time.

The observation that V_O2 was unchanged while V_ E increased as a function of time demonstrates that the subjects were
hyperventilation. The OUE in this study decreased as a function of time at all exercise intensities. At the lowest studied v, the
mild decrease in OUE may be explained by a slight reduction in V_O2 from the 4th min throughout the swim. The reduction in
V_O2 as a function of time may be explained by biomechanical adjustments to promote gross efficiency, with swimmers
improving propelling efficiency and/or decreasing drag (Pelarigo et al., 2011; Toussaint & Hollander, 1994). At the fastest
v (102.5%MLSS), OUE showed a greater, and significant decay as a function of time compared to the lower v’s. The decrease
of OUE as a function of time during the swim at 102.5MLSS is likely explained by the respiratory compensation for metabolic
acidosis (increased [La-]), increasing V_ E when V_O2 remained constant (Baba et al., 1996). Alternatively, there may be an
increased pulmonary dead space due to the reduction in tidal volume, and resultant increase in breathing frequency to meet
the increased V_ E needs as previously suggested (Baba et al., 1996). If the pulmonary dead space significantly increased
during exercise, the V_ E would have to be increased to provide the same alveolar ventilation at a higher energy cost to the
respiratory muscles (Harms et al., 2000). It is possible that the increased V_ E (hyperventilation) observed in this study was



264 J.G. Pelarigo et al. / Human Movement Science 49 (2016) 258–266
respiratory compensation for metabolic acidosis due to the buildup of [La-] and also resulted in an increased pulmonary dead
space. The increased [La-] and V_ E are also likely responsible for eight out of ten of the subjects’ not completing the 30 min
swim at 102.5%MLSS due to locomotor and respiratory muscle fatigue (Harms et al., 2000).

Supporting the role of respiratory compensation for metabolic acidosis at 102.5%MLSS is the reduced end-tidal PaCO2

(ETPaCO2) observed suggesting a decrease in arterial CO2 (PaCO2). The lower PaCO2 is involved in the buffering system
and control of metabolic acidosis. ETPaCO2 values at 102.5%MLSS was lower than at the two lower v’s (97.5 and 100%MLSS)
and than what is considered normal PaCO2 (40 mmHg). Furthermore, the ETPaCO2 values decreased as a function of time in
the 102.5%MLSS swim from the start of the exercise (4th min) to its end for all swimming speeds. Thus, the reductions in
ETPaCO2 as a function of time at all v’s, and particularly for the 102.5%MLSS v confirm the respiratory compensation, and
thus support its role in the reduced OUE.

Lower values of [La-] at 100%MLSS (1.89 mmol.L�1) were observed in the females in the present study compared to swim-
ming literature reported data for males (2.8–3.3 mmol.L�1) (Dekerle, Nesi et al., 2005; Fernandes, Sousa, Machado, & Vilas-
Boas, 2011; Pelarigo et al., 2011). Part of this difference in the [La-] values is due to the lower [La-] values commonly
observed for women compared to men in middle-distance and endurance exercise (Crewther, Cronin, & Keogh, 2006;
Greco, Pelarigo, Figueira, & Denadai, 2007; Holfelder, Brown, & Bubeck, 2013). The lower [La-]’s in women are likely
explained by their lower body mass and lean muscle mass (Crewther et al., 2006; Holfelder et al., 2013). A further potential
difference between men and women is the higher testosterone concentration in men (Deschenes & Kraemer, 2002), which
could suggest a different metabolic balance between carbohydrates and fat throughout prolonged exercises (Greco et al.,
2007; Tarnopolsky, Atkinson, Phillips, & MacDougall, 1995). Another potential factor for the low values of [La-] for women
found in the present study may be due to their potentially greater adaptation of aerobic metabolism during exertion caused
by their higher level of training than the men previously reported. Endurance athletes have been shown to have higher phe-
notypic expression of oxidative muscle fibers compared to sprint athletes (Tanaka & Swensen, 1998). This adaptation could
lead to fibers that consume lactate (Gladden, 2008), supporting a physiological steady state at intensities near the vV_O2max.
These adaptations may explain the low final [La-] values observed in this study as the subjects were middle-distance and
endurance swimmers.

The C (the ratio of Ė and v) has been suggested to be a major determinant of swimming performance (di Prampero,
Pendergast, & Zamparo, 2011). Ė has to include both aerobic and anaerobic energy sources, especially at speeds near or
greater than those than can be sustained using aerobic metabolism only (Fernandes et al., 2006). In the present study C
was measured by direct methods during submaximal constant swimming for MLSS assessment and the anaerobic compo-
nent from an energetic equivalent from blood [La-] (di Prampero et al., 2011). C increased around 5% as a function of v during
the three swimming v’s, as a linear function of v. Previous studies, however, reported that C increases with the v as a non-
linear function (di Prampero et al., 2011) or a cubic function (Rodriguez & Mader, 2011). This apparent discrepancy is likely
explained by differences in the ranges of v’s studied, more narrow in the present study and wider in the studies showing a
nonlinear relationship for v. Previous studies used very low to maximal swimming v’s (Rodriguez & Mader, 2011), contrasted
to the v’s used in this study (2.5% above and below 100%MLSS). Comparing v’s at similar percentages of vV_O2max in front
crawl swimming used in this study, C values of 37.9 mL.m�1 (0.79 kJ.m�1) and 41 mL.m�1 (0.86 kJ.m�1) for high level female
swimmers at mean intensity values of 88% and 95% of maximum 400 m speed, respectively, have previously been reported
(Chatard, Lavoie, & Lacour, 1991). The 400 m race in swimming has been highly associated with the minimum v that elicits
V_O2max (Costill et al., 1985). Although the methodological approach (maximal 400 m vs progressive protocol) and the exer-
cise mode (continuous vs intermittent) used in these studies were different (Chatard et al., 1991), the mean values of C were
similar to those of the present study (0.78 and 0.81 kJ.m�1 at 100 and 102.5MLSS, respectively).

HR presented similar adjustments as a function of time among the three swimming conditions in the present study, drift-
ing up around 10 bpm from the 4th min to the end of the test. The increased HR observed in prolonged exercise, as in the
present study, defined as ‘‘cardiovascular drift” (Fritzsche, Switzer, Hodgkinson, & Coyle, 1999), is likely explained by an
increase in sympathetic nervous system activity and circulating norepinephrine concentrations, as well as other mechanisms
to maintain cardiac output (Baron et al., 2008). The mean HR value at 100%MLSS was of 92% (SD 4%) of HR at V_O2max in the
present study, a value which is similar to that previously reported (Dekerle, Nesi et al., 2005; Dekerle, Pelayo et al., 2005).

The v values at 100%MLSS for females reported in this study are similar to those reported for males in previous studies
(Baron et al., 2005; Dekerle, Pelayo et al., 2005; Pelarigo et al., 2011). In addition the SR, SL and SI values reported in those
same studies using men (Baron et al., 2005; Dekerle, Pelayo et al., 2005; Pelarigo et al., 2011) are similar to those reported in
this study for women. These similarities of the male data from previous studies and the current study are most likely due to
the high technical and training level of our swimmers. This assertion is strengthened by the v at 100%MLSS expressed as a
percentage of vV_O2max observed in the present study (91.8 ± 4.6%) compared to previous reports in swimming (88.9 ± 3.3%)
(Dekerle, Nesi et al., 2005), cycling (78.2 ± 4.9%), and running (75.9 ± 5.1%) (Figueira, Caputo, Pelarigo, & Denadai, 2008).

Swimming v is obtained by the product of SR and SL (Craig & Pendergast, 1979). It has also been shown that fatigue may
interfere with the stroking parameters adopted by the swimmers to maintain a given v (Pelarigo et al., 2011). In the present
study, swimmers did not sustain their SL at 102.5%MLSS compared to 97.5 and 100%MLSS, and thus they had to increased
their SR to maintain their paced v. Indeed, the decline in SL as a function of v resulted in a decrease in SI, suggesting the
importance of the ability to maintain biomechanical efficiency with exercise intensity. These findings are in agreement with
previous studies, who reported decreases in SL and increases in SR in all-out distance trials (Craig & Pendergast, 1979) and
with time at imposed paces (Dekerle, Nesi et al., 2005; Figueiredo et al., 2014; Pelarigo et al., 2011). In addition, SR values in



J.G. Pelarigo et al. / Human Movement Science 49 (2016) 258–266 265
this study increased in the final periods of the 30 min swims compared to the beginning of the swims (4th min). Conversely,
SL and SI were lower in the final periods of the swims compared with the beginning of the swims (4th min). A previous study
(Dekerle, Nesi et al., 2005) reported that, at 100%MLSS, there was a slight decrease of SL (�3.3%) and increase of SR (3.6%)
(non-significant in absolute values), from the beginning to the end of exercise, respectively. Similar trends in SL and SR were
found in the present study during 100%MLSS exercise. Moreover, at 102.5%MLSS fatigue likely developed as a function of
time and was associated with the SL decrease (�4%), and the SR increase (4.3%) from the beginning to the end of exercise.
The biomechanical data show that for all three swimming v’s, SR had to be increased to compensate for the reduced SL to
keep v constant as set by the protocol. In spite of these stroke mechanics changes Ė and C were not affected. As Ė and C
are determined by drag and net mechanical efficiency the absences of changes in Ė suggest either or both drag and net
mechanical efficiency did not change.

5. Conclusions

Our results suggest that, at intensities up to the MLSS, bioenergetical and biomechanical factors are constant as a function
of time in a 30 min swim. However, above the MLSS (102.5%MLSS) there was a decrease in ETPaCO2 which is a result of
hyperventilation (V_ E/V_O2), most likely caused by respiratory compensation for metabolic acidosis (increased [La-]), thus
decreasing OUE. As V_O2 was constant over the 30 min swim at all v’s, increased [La-] and SR most likely caused fatigue
and, together, were associated with the inability of most swimmers to complete the 30 min swim at 102.5%MLSS.

Acknowledgements

This investigation was supported by the Capes Foundation, Ministry of Education of Brazil under Grant (BEX: 0536/10-5),
and the Portuguese Science and Technology Foundation (FCT), project PTDC/DES/101224/2008 under Grant (FCOMP-01-
0124-FEDER-009577).

References

Baba, R., Nagashima, M., Goto, M., Nagano, Y., Yokota, M., Tauchi, N., et al (1996). Oxygen uptake efficiency slope: A new index of cardiorespiratory
functional reserve derived from the relation between oxygen uptake and minute ventilation during incremental exercise. Journal of the American College
of Cardiology, 28, 1567–1572.

Baldari, C., Fernandes, R. J., Meucci, M., Ribeiro, J., Vilas-Boas, J. P., & Guidetti, L. (2013). Is the new AquaTrainer� snorkel valid for VO2 assessment in
swimming? International Journal of Sports Medicine, 34, 344–366.

Baron, B., Dekerle, J., Depretz, S., Lefevre, T., & Pelayo, P. (2005). Self selected speed and maximal lactate steady state speed in swimming. Journal of Sports
Medicine and Physical Fitness, 45, 1–6.

Baron, B., Dekerle, J., Robin, S., Neviere, R., Dupont, L., Matran, R., ... Pelayo, P. (2003). Maximal lactate steady state does not correspond to a complete
physiological steady state. International Journal of Sports Medicine, 24, 582–587.

Baron, B., Noakes, T. D., Dekerle, J., Moullan, F., Robin, S., Matran, R., et al (2008). Why does exercise terminate at the maximal lactate steady state intensity?
British Journal of Sports Medicine, 42, 828–833.

Beneke, R. (2003). Maximal lactate steady state concentration (MLSS): Experimental and modelling approaches. European Journal of Applied Physiology, 88,
361–369.

Beneke, R., & von Duvillard, S. P. (1996). Determination of maximal lactate steady state response in selected sports events.Medicine and Science in Sports and
Exercise, 28, 241–246.

Chatard, J. C., Lavoie, J. M., & Lacour, J. R. (1991). Energy cost of front-crawl swimming in women. European Journal of Applied Physiology and Occupational
Physiology, 63, 12–16.

Costill, D. L., Kovaleski, J., Porter, D., Kirwan, J., Fielding, R., & King, D. (1985). Energy expenditure during front crawl swimming: Predicting success in
middle-distance events. International Journal of Sports Medicine, 6, 266–270.

Craig, A. B., Jr., & Pendergast, D. R. (1979). Relationships of stroke rate, distance per stroke, and velocity in competitive swimming. Medicine and Science in
Sports, 11, 278–283.

Crewther, B., Cronin, J., & Keogh, J. (2006). Possible stimuli for strength and power adaptation: Acute metabolic responses. Sports Medicine, 36, 65–78.
Dekerle, J., Nesi, X., Lefevre, T., Depretz, S., Sidney, M., Marchand, F. H., et al (2005). Stroking parameters in front crawl swimming and maximal lactate

steady state speed. International Journal of Sports Medicine, 26, 53–58.
Dekerle, J., Pelayo, P., Clipet, B., Depretz, S., Lefevre, T., & Sidney, M. (2005). Critical swimming speed does not represent the speed at maximal lactate steady

state. International Journal of Sports Medicine, 26, 524–530.
Deschenes, M. R., & Kraemer, W. J. (2002). Performance and physiologic adaptations to resistance training. American Journal of Physical Medicine and

Rehabilitation, 81, S3–S16.
di Prampero, P. E. (1986). The energy cost of human locomotion on land and in water. International Journal of Sports Medicine, 7, 55–72.
di Prampero, P. E., Pendergast, D., & Zamparo, P. (2011). Swimming economy (Energy Cost) and efficiency. In L. Seifert, D. Chollet, & I. Mujika (Eds.), World

book of swimming: From science to performance (pp. 297–312). New York: Nova.
Faude, O., Kindermann, W., & Meyer, T. (2009). Lactate threshold concepts: How valid are they? Sports Medicine, 39, 469–490.
Fernandes, R. J., Billat, V. L., Cruz, A. C., Colaco, P. J., Cardoso, C. S., & Vilas-Boas, J. P. (2006). Does net energy cost of swimming affect time to exhaustion at the

individual’s maximal oxygen consumption velocity? Journal of Sports Medicine and Physical Fitness, 46, 373–380.
Fernandes, R. J., de Jesus, K., Baldari, C., Sousa, A. C., Vilas-Boas, J. P., & Guidetti, L. (2012). Different VO2max time-averaging intervals in swimming.

International Journal of Sports Medicine, 33, 1010–1015.
Fernandes, R. J., Sousa, M., Machado, L., & Vilas-Boas, J. P. (2011). Step length and individual anaerobic threshold assessment in swimming. International

Journal of Sports Medicine, 32, 940–946.
Figueira, T. R., Caputo, F., Pelarigo, J. G., & Denadai, B. S. (2008). Influence of exercise mode and maximal lactate-steady-state concentration on the validity of

OBLA to predict maximal lactate-steady-state in active individuals. Journal of Science and Medicine in Sport, 11, 280–286.
Figueiredo, P., Nazário, R., Sousa, M., Pelarigo, J. G., Vilas-Boas, J. P., & Fernandes, R. (2014). Kinematical analysis along maximal lactate steady state

swimming intensity. Journal of Sports Science & Medicine, 13, 610–615.
Fletcher, J. R., Esau, S. P., & Macintosh, B. R. (2009). Economy of running: Beyond the measurement of oxygen uptake. Journal of Applied Physiology, 107,

1918–1922.

http://refhub.elsevier.com/S0167-9457(16)30102-6/h0005
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0005
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0005
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0010
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0010
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0010
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0010
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0015
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0015
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0020
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0020
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0025
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0025
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0030
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0030
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0035
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0035
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0040
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0040
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0045
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0045
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0050
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0050
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0055
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0060
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0060
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0065
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0065
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0070
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0070
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0075
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0080
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0080
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0085
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0090
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0090
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0095
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0095
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0095
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0100
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0100
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0105
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0105
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0110
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0110
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0115
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0115


266 J.G. Pelarigo et al. / Human Movement Science 49 (2016) 258–266
Fritzsche, R. G., Switzer, T. W., Hodgkinson, B. J., & Coyle, E. F. (1999). Stroke volume decline during prolonged exercise is influenced by the increase in heart
rate. Journal of Applied Physiology, 86, 799–805.

Gladden, L. B. (2008). A lactatic perspective on metabolism. Medicine and Science in Sports and Exercise, 40, 477–485.
Greco, C. C., Pelarigo, J. G., Figueira, T. R., & Denadai, B. S. (2007). Effects of gender on stroke rates, critical speed and velocity of a 30-min swim in young

swimmers. Journal of Sports Science & Medicine, 6, 441–447.
Harms, C. A., Wetter, T. J., St Croix, C. M., Pegelow, D. F., & Dempsey, J. A. (2000). Effects of respiratory muscle work on exercise performance. Journal of

Applied Physiology, 89, 131–138.
Heck, H., Mader, A., Hess, G., Mucke, S., Muller, R., & Hollmann, W. (1985). Justification of the 4-mmol/l lactate threshold. International Journal of Sports

Medicine, 6, 117–130.
Holfelder, B., Brown, N., & Bubeck, D. (2013). The influence of sex, stroke and distance on the lactate characteristics in high performance swimming. PLoS

ONE, 8. 0077185.
Hollmann, W. (2001). 42 years ago–development of the concepts of ventilatory and lactate threshold. Sports Medicine, 31, 315–320.
Hopkins, S. R., & Harms, C. A. (2004). Gender and pulmonary gas exchange during exercise. Exercise and Sport Sciences Reviews, 32, 50–56.
Machado, L., Almeida, M., Morais, P., Fernandes, R., & Vilas-Boas, J. P. (2006). Assessing the individual anaerobic threshold: The mathematical model. In Xth

international symposium of biomechanics and medicine in swimming (pp. 142–144). Portugal: Porto.
Pelarigo, J. G., Denadai, B. S., & Greco, C. C. (2011). Stroke phases responses aroundmaximal lactate steady state in front crawl. Journal of Science and Medicine

in Sport, 14, 168.e1–168.e5.
Pelarigo, J. G., Denadai, B. S., Ribeiro, J., Fernandes, R. J., Greco, C. C., & Vilas-Boas, J. P. (2014). Biophysics of the elite endurance swimmer: A case study during

aerobic capacity evaluation using different methods. In B. Mason (Ed.), XIIth international symposium on biomechanics and medicine in swimming
(pp. 318–325). Canberra, Australia: Australian Institute of Sport.

Rodriguez, F. A., & Mader, A. (2011). Energy systems in swimming. In L. Seifert, D. Chollet, & I. Mujika (Eds.), World book of swimming: From science to
performance (pp. 225–240). New York: Nova.

Sheel, A. W., Richards, J. C., Foster, G. E., & Guenette, J. A. (2004). Sex differences in respiratory exercise physiology. Sports Medicine, 34, 567–579.
Sousa, A. C., Vilas-Boas, J. P., & Fernandes, R. J. (2014). VO2 kinetics and metabolic contributions whilst swimming at 95, 100, and 105% of the velocity at

VO2max. BioMed Research International, 1, 1–9.
Tanaka, H., & Swensen, T. (1998). Impact of resistance training on endurance performance. A new form of cross-training? Sports Medicine, 25, 191–200.
Tarnopolsky, M. A., Atkinson, S. A., Phillips, S. M., & MacDougall, J. D. (1995). Carbohydrate loading and metabolism during exercise in men and women.

Journal of Applied Physiology, 78, 1360–1368.
Toussaint, H. M., & Hollander, A. P. (1994). Energetics of competitive swimming. Implications for training programmes. Sports Medicine, 18, 384–405.

http://refhub.elsevier.com/S0167-9457(16)30102-6/h0120
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0120
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0125
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0130
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0130
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0135
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0135
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0140
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0140
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0145
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0145
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0150
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0155
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0160
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0160
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0165
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0165
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0170
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0170
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0170
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0175
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0175
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0180
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0185
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0185
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0185
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0185
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0190
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0195
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0195
http://refhub.elsevier.com/S0167-9457(16)30102-6/h0200

	Do 5% changes around maximal lactate steady state lead �to swimming biophysical modifications?
	1 Introduction
	2 Methods
	3 Results
	4 Discussion
	5 Conclusions
	Acknowledgements
	References