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The performance in swimming, as in other cyclic sports such cycling
and running, has been linked strongly to physiological, technical
and physical capacities. But, as water locomotion demands more energy
per unit distance than locomotion on land (Capelli, 1999;
di Prampero, 1986),
the control of technical level may be important to increase propulsive
force and reduce active drag (Hollander et al., 1986;
Kolmogorov and Duplischeva, 1992).
The level of propulsive force and active drag can interfere on the
energy expenditure and propelling efficiency (Chatard et al., 1990;
Wakayoshi et al., 1995).
The swimming speed is equal to the product of stroke rate (SR) and
stroke length (SL). The SR corresponds to the number of cycles performed
per unit of time, and SL is the distance the body travels per stroke
cycles (Pelayo et al., 1996; 1997). These technical indexes have shown significant correlation
with performance in short (Huot-Marchand et al., 2005; Wakayoshi et al., 1995)
and long duration tests (Dekerle et al., 2005a),
and seem to discriminate swimmers of different performance levels
(Dekerle et al., 2002).
Comparing male and female swimmers, some studies have verified that
male had similar SR, but greater SL values than females in short
(100 and 200 m) (Arellano et al., 1994;
Chengalur and Brown, 1992;
Kennedy et al., 1990;
Pai et al., 1984)
and long distances (1500 and 3000 m) (Seifert et al., 2004),
which could be explained by anthropometric data (Arellano et al.,
1994;
Chengalur and Brown, 1992;
Kennedy et al., 1990;
Pai et al., 1984;
Seifert et al., 2004).
The difference in SL values between genders may exist, even when
the performance level and swimming skill are similar (Zamparo, 2006).
Critical speed (CS) and the average speed on a 30-min maximal test
(S30) are among the noninvasive methods most widely used for aerobic
assessment during swimming (Dekerle et al., 2005b;
Greco et al., 2003;
Greco and Denadai, 2005;
Olbrecht et al., 1985;
Wakayoshi et al., 1992).
Several studies have verified in swimmers with different ages (chronological
and biological) and training status that CS can be used to predict
aerobic performance and aerobic capacity. In adult trained swimmers
(19 years), CS determined trough distances between 100 and 400 m
have presented high correlation levels with swimming velocity associated
with 4 mM of blood lactate (r = 0.89) (Wakayoshi et al., 1992)
and maximal lactate steady state (r = 0.91 and 0.87) (Wakayoshi
et al., 1993;
Dekerle et al., 2005b,
respectively). In the same way, this index has been considered a
good predictor of 400-m swimming performance (r = 0.99) (Wakayoshi
et al., 1992)
and S30 (r = 0.77) (Dekerle et al., 2002).
In young and less experienced swimmers, studies have also found
a good capacity of CS to predict aerobic performance and aerobic
capacity. Hill and Smart, 2001
verified, in 17-year-old swimmers, that the CS was equal to the
speed corresponding to maximal lactate steady state, with a high
correlation between these speeds (r = 0.81). In male and female
younger swimmers, Greco and Denadai, 2005
verified that S30 was similar and moderately correlated with CS
determined with distances of 100, 200, and 400 m in all groups in
which age was determined by chronological age (r = 0.87 to 0.97)
or by sexual maturation (r = 0.93 to 0.98).
Thus, although the speeds of young swimmers can be lower than in
more experienced adult swimmers, age and performance level seem
not to influence the relationship between CS and S30. But, for coaches,
CS seem to be more interesting in this population by the possibility
to use short distances (100 to 400 m) which can avoid problems related
to the lack of experience and motivation to swim long distances
trials and the less time required to determine this index.
Recently, Dekerle et al., 2002
showed that the SR determined based on the slope of the regression
line between the number of stroke cycles and time obtained at different
distances (critical stroke rate - SRCS), similar to the method proposed
for the determination of CS, is valid to estimate the SR maintained
in an S30 test (SRS30). But a correction of 3.2% in the CS and 3.9%
in SRCS was suggested to approximate of 30-min test. Greco et al.,
2006
have confirmed the data obtained by Dekerle et al., 2002
in young male swimmers, verifying that the validity of SRCS to estimate
SRS30 is not dependent on the aerobic capacity (S30). When comparing
CS with the blood lactate response, studies have verified CS values
similar (Dekerle et al., 2002;
Greco et al., 2003)
or higher (Greco et al., 2003)
than anaerobic threshold and higher than maximal lactate steady
state (Dekerle et al., 2005b).
Since in general CS is determined by fixed distances, possible differences
on the duration of these predictive loads may explain, at least
in part, these different results. Moreover, as mentioned by Greco
et al., 2003
the lesser experience of young swimmers with long distance tests
may influence the relationship between CS and S30.
In male swimmers, higher levels of propulsive forces can have a
significant contribution to lower durations found for the same distances,
when comparing to female. However, since swimmers of different genders
present similar values of SR in competitive distances (Seifert et
al., 2004),
our main hypothesis is that the relationship between SRS30 and SRCS
is not influenced by gender, irrespectively of aerobic capacity.
However, it is important to note that most studies in the literature
have compared technical indexes in swimmers of different age, gender
and swimming skill, using mainly swimming-pool competitions distances
(50 to 1500 m). Few studies have verified the effect of gender and
aerobic capacity on technical indexes during long-distance-swimming
events. Thus, the central objective of the present study was to
verify the effect of gender on the relationship between SRCS and
SRS30 in swimmers with similar and different aerobic capacity levels.
| METHOD |
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Subjects
Twenty-two male and 14 female swimmers volunteered to participate
of this study. They have at least 4 years of experience in
swimming and a weekly training volume of 30 km to 45 km, and
were competing in regional and national level meets. They
were familiarized with long distance tests (1500 and 2000
m) performed during training sessions. Physical characteristics
of the subjects are presented in Table
1. The subjects were instructed to refrain from intense
training sessions at least 24 h before the experimental sessions.
Subjects were directed to be fully rested when reporting to
the laboratory or for field testing and to have refrained
from using caffeine-containing food or beverages, drugs, alcohol,
cigarette smoking, or any form of nicotine intake 24 h before
testing. All the tests were made 3 hours after the last meal.
Before participation in the study, the swimmers and their
parents or guardians were informed of all test procedures
and they provided voluntary written informed consent to participate
in the study. The protocol was approved by the university's
ethics committee. All procedures were according to Declaration
of Helsinki for research on human subjects.
Experimental
design
The anthropometric characteristics were measured in the first
experimental session. Stature and body mass were measured
trough a scale and a stadiometer (Fillizolla, Brazil). Body
fat was determined by skinfold thickness (triceps and subscapular),
measured with skinfold calipers (Cescorf, Porto Alegre, Brazil),
with precision of 0. 1 cm and constant pressure of 10 g·mm-2,
based on the protocol suggested by Lohman, 1982.
Then the performances of 200 m, 400 m, and a 30 min continuous
swim in front crawl were determined on different days in a
random order. All tests were performed in a 25 m pool, during
training sessions. Individuals performed a standard warm-up
before each test, and after the test they trained normally.
In the first comparison (Study 1), all individuals were divided
by gender (male, GM1 and female, GF), regardless of S30 values.
Then, to analyze the isolated effect of gender in individuals
with similar S30 values, a sub-set of GM1 was selected to
match GF based on their velocity in S30 (GM2) (Study 2). The
S30 was selected as criterion measure (Morrow et al., 2005),
since it has been considered valid for the indirect assessment
of aerobic capacity in swimmers (Olbrecht et al., 1985;
Maglischo, 1993).
For each swimmer, all tests were conducted at the same time
of day and at least 2 h after a meal.
Determination
of critical speed (CS)
During training sessions, the participants were instructed
to swim distances of 200 and 400 m as quickly as possible,
as CS determined trough these distances had been valid to
estimate anaerobic threshold, maximal lactate steady state
and S30 (Dekerle et al., 2002;
Dekerle et al., 2005a;
Greco and Denadai, 2005).
They started with a push-off and the time taken to swim each
distance was recorded using a manual chronometer. Participants
swam one event per day in random order. CS was determined
using the slope of the linear regression between swimming
distances (200 and 400 m) and the time taken to swim them.
Determination
of maximal speed of 30 min (S30)
S30 was determined through a maximal 30 min test, recording
the distance in m, calculating velocity by dividing the distance
by time. At the 10th min and at the completion of the test,
25 µl of arterialized blood were collected from the ear lobe
through a heparinized capillary tube and immediately transferred
to microcentrifuge tubes containing 50 µl NaF (1%) for lactate
[La] measurement (YSL 2300 STAT, Yellow Springs, OH, USA).
The total time needed for the blood samples had a maximal
duration of 30 s, and was excluded from the total swimming
duration. The blood lactate response has been widely used
for the assessment of aerobic capacity in swimmers (Dekerle
et al., 2002;
Olbrecht et al., 1985;
Wakayoshi et al., 1993).
In adult swimmers, S30 was found to be valid for the prediction
of OBLA (Olbrecht et al., 1985)
and was used for aerobic training prescription (Maglischo,
1993;
Olbrecht et al., 1985).
Determination
of the stroke rates corresponding to CS (SRCS) and S30 (SRS30)
During the 200 and 400 m tests, the time necessary to complete
5 strokes was measured 10 m after the turn for each 50 m of
the 200 and 400 m swims (4 measurements for the 200 m and
8 for the 400 m), and the mean value was calculated. After
this, the number of strokes cycles for the duration of each
trial was determined, as following:
Number
of stroke cycles = (Time of the trial x 5)/Time of 5 strokes
Using
the time and the number of strokes for the distances of 200
and 400 m, SRCS was calculated, through the linear slope of
the regression line between the stroke rate and time, as follows:
Stroke
rate = number of stroke cycles/time
Number of stroke cycles = a + (b.t);
Where 'b' is SRCS, 'a' is the anaerobic capacity and t corresponds
to the time.
During
the 30 min test, the time necessary to complete 5 strokes
was measured during each 400 m and the mean value was calculated.
SRS30 was determined as following:
SRS30
(cycles.min-1) = (5
x 30)/Time of 5 strokes
These
measurements were made after 10 m of the turn to avoid its
influence in swimming speed. As the swimming speed corresponds
to the product of stroke rate and stroke length, then stroke
length was calculated dividing the speed by the stroke rate,
as following:
Swimming speed (m.s-1) = stroke rate x stroke length
and
Stroke length (m) = swimming speed/stroke rate
In
accordance to Dekerle et al., 2002,
the determination of SRCS presents good reliability.
Statistical
analysis
The values were expressed as mean ± SD. The normality of data
was checked by Shapiro-Wilk test. In both studies, the effect
of method (CS and S30) and gender (GM1, GM2 and GF) on the
relationship between speeds and stroke rates corresponding
to CS and S30 was made through two-way ANOVA, with Scheffé
post-hoc tests where appropriate. The comparison of the physical
characteristics between groups of males and females was made
through Student t test for unpaired data. The correlation
between CS and S30, and SRCS and SRS30 was made through linear
regression (Pearson product moment correlation coefficient).
A significance level of 5% was accepted (p < 0.05).
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| RESULTS |
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Study
1
Maximal
swimming performances of 200 and 400 m
Table 2 shows mean ±
SD values of speed (S200 and S400), stroke rate (SR200 and
SR400) and stroke length (SL200 and SL400) corresponding to
maximal performance of 200 and 400 m in the GM1, GM2 and GF
groups. The S200 and SR200 were higher than S400 [F(1,34)
= 12.477; p < 0.01] and SR400 [F(1,34) = 84.031; p <
0.01], respectively, in both groups. The SL200 was significantly
lower than SL400 in GM1 [F(1,34) = 3.973; p = 0.05], but they
were similar in GF. S200 and S400 were higher in GM1 than
GF [F(1,34)=116.260; p < 0.01]. SR200 and SR400 were similar
between genders (GM1 and GF) [F(1,34) = 0.391; p = 0.535].
However, the stroke length [F(1,34) = 14.040; p = 0.00] were
higher in males (GM1) than female (GF) in both distances.
The mean percentage difference between S200 and S400 was 7%
and 6%, for GM1 and GF, respectively.
Critical
speed and maximal 30-min swimming performance
Table 3 shows mean ±
SD values of speed and stroke rate corresponding to critical
speed (CS, SRCS) and maximal speed of 30 minutes (S30 and
SRS30), blood lactate concentration at 10th (LAC10th) and
30th min (LAC30th) in the GM1, GM2 and GF groups. When comparing
groups with
different S30 values, CS was higher than S30 in GM1 (6.4%)
and GF groups (3.4%) [F(1,34) = 5.969; p < 0.05]. CS and
S30 were higher in GM1 than GF [F(1,34) = 70.142; p < 0.01].
SRCS and SRS30 were similar in both groups [F(1,34) = 3.811;
p = 0.06] and between genders (GM1 and GF) [F(1,34) = 0.059;
p = 0.81].
The LAC10th was higher than LAC30th in GF [F(1,33) = 12.365;
p < 0.01] but similar in GM1 group. The LAC10th and LAC30th
were higher in GM1 than GF [F(1,33) = 27.098; p < 0.01].
There was a significant correlation between CS and S30 (r
= 0.89, p = 0.000) and SRCS and SRS30 (r = 0.89, p = 0.000)
in GM1 and GF groups (r = 0.94, p = 0.000, and r = 0.80, p
= 0.001, respectively).
Study
2
Maximal
swimming performances of 200 and 400 m
The S200 and SR200 were higher than S400 [F(1,27) = 4.690;
p < 0.05] and SR400 [F(1,27) = 59.896; p < 0. 01], respectively,
in all groups. The mean percentage difference between S200
and S400 was similar in both groups (GM2 - 6%, GF - 6%). The
S200 and S400 were higher in males (GM2) than females (GF)
[F(1,27) = 84.304; p < 0.01]. There was no significant
difference on the SR200 and SR400 between genders (GM2 and
GF) [F(1,27) = 0.317; p = 0.58]. SL200 was similar to SL400
in both groups [F(1,27)=1.454; p = 0.24]. However, the stroke
length were higher in males (GM2) than female (GF) in both
distances [F(1,27) = 6.778; p < 0.05].
Critical
speed and maximal 30-min swimming performance
When comparing groups with similar aerobic capacity levels
(S30), the CS was higher than S30 in GM2 (8.1%) and GF groups
(3.4%) [F(1,27) = 91.114; p < 0.01]. CS presented by GM2
was higher than GF [F(1,27) = 91.114; p < 0.01]. SRCS was
similar to SRS30 in GM2 and GF [F(1,27) = 3.330; p = 0.08].
The SRCS and SRS30 were similar between genders [F(1,27) =
0.009; p = 0.92].
The LAC10th was higher than LAC30th in GF but similar in GM2
group [F(1,27) = 10.397; p < 0.01]. The LAC10th and LAC30th
were higher in GM2 than GF [F(1,27) = 29. 130; p < 0.01]
(Table 3). There was
a significant correlation between CS and S30 (r = 0.90, p
= 0.000) and SRCS and SRS30 (r = 0.88, p = 0.000) in GM.
|
| DISCUSSION |
The central objective of the present study was to analyze the
effect of gender on the relationship between SRCS and SRS30
in young swimmers. Similar to results of other studies conducted
in swimmers with higher performance level (Dekerle et al., 2002),
we verified that SRCS was similar to SRS30 in all groups, irrespectively
of gender and aerobic capacity level. Thus, the CS concept may
simultaneously provide information about aerobic capacity (CS)
and biomechanical skill (SRCS) in this modality, even in less
experienced swimmers. This methodology can be very interesting
for coaches and athletes, since the tests are shorter and easier
to perform.
When comparing middle-distance performances of 200 m with 400
m, the percentage difference observed between S200 and S400
was similar to that found by Seifert et al., 2004
in elite swimmers (male - 6% and female - 5%), which suggest
that the relative difference between maximal speeds of 200 and
400 m is maintained irrespectively of the performance level.
Higher values of S200 and SR200, and higher value of SL200 presented
by GM1 compared to GF is in accordance to Seifert et al., 2004.
These authors found that the increase of speed (3000, 1500,
800, 400, 200, 100, 50 m and maximal speed) is associated with
higher values of SR and lower values of SL. GM2 and GF also
showed higher values of speed and SR, but similar values of
SL in the 200 m in relation to 400 m maximal performance. This
may be partly explained by the low number of subjects and some
error included in the calculation of the SL, as proposed by
Smith et al., 2002.
The speed and SL were higher in male (GM1 and GM2) than female
(GF) in both distances (200 and 400 m). In line with other studies
(Arellano et al., 1994;
Pai et al., 1984;
Pelayo et al., 1996;
Seifert et al., 2004;
Zamparo, 2006),
SL was the main factor explaining the different speeds observed
between male and female. Some studies suggest that anthropometric
data (i.e., arm length, arm span) may help to obtain higher
SL (Arellano et al., 1994;
Chengalur and Brown, 1992;
Zamparo, 2006)
in males. In accordance to Zamparo, 2006,
SL is associated with the ability to exert more strong and efficient
strokes. Moreover, higher levels of propulsive power (Simmons
et al., 2000)
are necessary to swim short and middle-duration events (Pai
et al., 1984;
Pelayo et al., 1996).
CS overestimated S30 in GM1 (6.4%), GM2 (8.1%) and GF (3.4%)
groups. The relationship between the values of CS determined
with distances of 200 and 400 m, and S30 is contradictory among
studies. In young male swimmers of different aerobic capacity
performance levels (S30), Greco et al., 2006
found a difference of 8% in less (CS - 1.17 and S30 - 1.07 m·s-1)
and 5% in more experienced group (CS - 1.30 and S30 - 1.23 m·s-1),
but a significant correlation between S30 and CS (r = 0.84 and
r = 0.68, respectively). In older subjects, Dekerle et al.,
2002
verified higher value of CS (1.35 m·s-1) than S30
(1.31 m·s-1) (3%), with a correlation of 0.77. However,
in young swimmers with a regional level, Greco and Denadai,
2005
included the distance of 100 m on the determination of CS, even
so there were similar values between S30 and CS in either the
10- to 12- (0.90 and 0.89 m·s-1, respectively) or 13- to 15-year-
old age groups (0.99 and 1.00 m·s-1, respectively).
These different relationships between CS and S30 may be explained,
at least in part, by the age, gender and performance levels
of swimmers (Greco et al., 2006;
Greco and Denadai, 2005),
since this factor might determine different durations for the
same distances and change the slope of regression line between
distances and times (Dekerle et al., 2002;
Greco et al., 2003).
Using swimmers with different ages and genders Greco and Denadai,
2005
verified that the younger groups (10-12 years) presented similar
values of CS and S30 and there was no significant difference
in these variables between genders. Males of 13-15 years presented
higher values of these variables than the younger ones. However,
in females, the younger group presented higher values, possibly
by higher level of experience in swimming, and by the age group
of 10-12 years was possible more advanced in maturation status
when comparing to boys. It is possible to verify that, when
the authors compared swimmers considering sexual maturational
status, boys presented higher values than females in all comparisons.
In this study, CS was similar to S30 in all groups. Thus, although
gender and age can interfere on the values of CS and S30, experience
level is also important in this modality.
In our study, higher percentage difference between CS and S30
values was observed in male, probably by their greater propulsive
force and power, as mentioned above. Thus, the use of CS to
prescribe the intensity corresponding to 30 min- swim test in
trained swimmers must be made with caution. However, similar
to found in others studies (Dekerle et al., 2002;
Toussaint et al., 1998),
the moderate to high correlation levels between CS and S30 verified
in all groups indicate a good validity of CS to evaluate aerobic
capacity.
SRCS and SRS30 values were similar to those found by Greco et
al., 2006
but lower than those found by Dekerle et al., 2002
in high trained swimmers, which can be explained by the differences
in the CS and S30 among these studies. However, the relationship
between SRCS and SRS30 found in the present study is in accordance
to these studies. In the study performed by Greco et al., 2006,
SRCS was similar to SRS30 in more experienced (33.07 ± 4.34
and 31.38 ± 4.15 cycles·min-1, respectively) and
less experienced group (35.57 ± 6.52 and 33.54 ± 5.89 cycles·min-1,
respectively), with a significant correlation between them (r
= 0.84 and r = 0.88, respectively). In the same way, Dekerle
et al., 2002
found similar values (37.79 and 36.41 cycle·min-1)
and high correlation (r = 0.86) between SRCS and SRS30 in high
trained swimmers. Therefore, the modifications in the SR technical
pattern (SRCS x SRS30) seem to occur to an extent differing
from the variations in swimming speed (CS x S30), at least at
the level of experience and aerobic capacity analyzed in the
present study. The absence of difference between SLCS and SLS30
in all comparisons may be partly explained by the factors mentioned
above for the 200 and 400 m maximal performances.
In cyclic sports, such as running and cycling, fatigue is associated
with a reduction in the frequency of movements (Morrow et al.,
2005).
Similarly, studies performed in swimming and cycling have shown
a significant change in the movement pattern when the individual
exercises above the intensity corresponding to maximal lactate
steady state (Dekerle et al., 2003;
2005a),
or anaerobic threshold (Huot-Marchand et al., 2005;
Keskinen and Komi, 1988a;
1988b;
Wakayoshi et al., 1993),
suggesting a relationship between metabolic fatigue and a fall
in swimming skill (Dekerle et al., 2005a).
This was related to local fatigue brought partly by high-lactate
levels. This fatigued state could also lead to a progressive
increase in the energy cost of swimming. Therefore, since biomechanical
skill may be compromised as a function of physiological mechanisms
associated with fatigue, the measurement of SRCS or SRS30 and
of CS or S30 might be an important tool to determine the biomechanical
and physiological aspects associated with aerobic capacity (Dekerle
et al., 2005a),
irrespectively of aerobic capacity level and gender.
In the present study, male swimmers presented higher blood lactate
concentration during S30 than female, even when comparing groups
with similar S30 values. These values were similar in male swimmers
(GM1 and GM2 groups), although the endurance capacity of the
two groups was different. This is accordance with the results
observed in the study of Greco and Denadai, 2005,
which verified that the blood lactate level during S30 was lower
in females (10- 12 years - 2.57 and 13- 15 years - 4.59 mmol·L-1)
than males (10- 12 years - 3.81 and 13- 15 years - 4.59 mmol·L-1)
independent of chronological age. It is important to know that
these swimmers have lower performance levels than our subjects.
In cycling, Deschenes et al., 2006
also verified lower values of lactate in women than men during
a 30 min submaximal exercise (60-65% of maximal oxygen uptake).
In the same way, Klusewicz (2005)
found lower values of blood lactate response in male than female
rowers. Some factors that might explain, at least in part, the
lower blood lactate response observed in female swimmers are
lower lean body mass and testosterone concentration, which might
be higher in males (Keskinen and Komi, 1993;
Vercruyssen et al., 1997).
Moreover, in the present study, females presented significant
reduction in the blood lactate concentration, which could suggest
that females may have different metabolic balance of carbohydrates
and fat use during prolonged exercises. Thus, the blood lactate
concentration during S30 seems to depend more of gender than
aerobic capacity level. |
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