ArticlePDF Available

Effects of long-term training cessation in young top-level road cyclists

Authors:

Abstract and Figures

In cycling, it is common practice to have a break in the off season longer than 4 weeks while adopting an almost sedentary lifestyle, and such a break is considered to be long-term detraining. No previous studies have assessed the effect of training cessation with highly trained young cyclists. The purpose of the present investigation was to examine effects of 5 weeks of training cessation in 10 young (20.1 ± 1.4 years) male road cyclists for body composition, haematological and physiological parameters. After training cessation, body mass of cyclists increased (P = 0.014; ES = 0.9). V_O2max (L ·min−1 = −8.8 ± 5.0%,mL · kg−1·min−1 = −10.8 ± 4.2%,), Wmax (W = −6.5 ± 3.1%, W · kg−1 = −8.5 ± 3.3%,), WLT1 (W = −12.9 ± 7.0%, W · kg−1 = −14.8 ± 7.4%,), WLT2 (W = −11.5 ± 7.0%, W · kg−1 = −13.4 ± 7.6%,) and haematological (red blood cells count, −6.6 ± 4.8%; haemoglobin, −5.4 ± 4.3% and haematocrit, −2.9 ± 3.0%) values decreased (P ≤ 0.028; ES ≥ 0.9). Five weeks of training cessation resulted in large decreases in physiological and haematological values in young top-level road cyclists suggesting the need for a shorter training stoppage. This long-term detraining is more pronounced when expressed relative to body mass emphasising the influence of such body mass on power output. A maintenance programme based on reduced training strategies should be implemented to avoid large declines in physiological values in young cyclists who aspire to become professionals.
Content may be subject to copyright.
Full Terms & Conditions of access and use can be found at
http://www.tandfonline.com/action/journalInformation?journalCode=rjsp20
Download by: [Universidad Del Pais Vasco] Date: 01 August 2016, At: 04:13
Journal of Sports Sciences
ISSN: 0264-0414 (Print) 1466-447X (Online) Journal homepage: http://www.tandfonline.com/loi/rjsp20
Effects of long-term training cessation in young
top-level road cyclists
Sara Maldonado-Martín, Jesús Cámara, David V.B. James, Juan Ramón
Fernández-López & Xabier Artetxe-Gezuraga
To cite this article: Sara Maldonado-Martín, Jesús Cámara, David V.B. James, Juan Ramón
Fernández-López & Xabier Artetxe-Gezuraga (2016): Effects of long-term training cessation in
young top-level road cyclists, Journal of Sports Sciences, DOI: 10.1080/02640414.2016.1215502
To link to this article: http://dx.doi.org/10.1080/02640414.2016.1215502
Published online: 01 Aug 2016.
Submit your article to this journal
View related articles
View Crossmark data
Effects of long-term training cessation in young top-level road cyclists
Sara Maldonado-Martín
a
, Jesús Cámara
a
, David V.B. James
b
, Juan Ramón Fernández-López
c
and Xabier Artetxe-Gezuraga
a
a
Laboratory of Performance Analysis in Sport, Department of Physical Education and Sport, Faculty of Physical Activity and Sport Sciences,
University of the Basque Country (UPV/EHU), Vitoria-Gasteiz, Spain;
b
Department of Sport & Exercise, University of Gloucestershire, Gloucester, UK;
c
Department for Education, Linguistic Policy and Culture of the Basque Government, KIROLENE Public Centre for Sports Education, Durango, Spain
ABSTRACT
In cycling, it is common practice to have a break in the off season longer than 4 weeks while adopting an
almost sedentary lifestyle, and such a break is considered to be long-term detraining. No previous studies have
assessed the effect of training cessation with highly trained young cyclists. The purpose of the present
investigation was to examine effects of 5 weeks of training cessation in 10 young (20.1 ± 1.4 years) male road
cyclists for body composition, haematological and physiological parameters. After training cessation, body
mass of cyclists increased (P= 0.014; ES = 0.9). _
VO2max (L · min
1
=8.8 ± 5.0%, mL · kg
1
·min
1
=10.8 ± 4.2%,),
W
max
(W = 6.5 ± 3.1%, W · kg
1
=8.5 ± 3.3%,), W
LT1
(W = 12.9 ± 7.0%, W · kg
1
=14.8 ± 7.4%,), W
LT2
(W = 11.5 ± 7.0%, W · kg
1
=13.4 ± 7.6%,) and haematological (red blood cells count, 6.6 ± 4.8%;
haemoglobin, 5.4 ± 4.3% and haematocrit, 2.9 ± 3.0%) values decreased (P0.028; ES 0.9). Five weeks
of training cessation resulted in large decreases in physiological and haematological values in young top-level
road cyclists suggesting the need for a shorter training stoppage. This long-term detraining is more pro-
nouncedwhenexpressedrelativetobodymassemphasising the influence of such body mass on power
output. A maintenance programme based on reduced training strategies should be implemented to avoid
large declines in physiological values in young cyclists who aspire to become professionals.
ARTICLE HISTORY
Accepted 15 July 2016
KEYWORDS
Detraining consequences;
submaximal variables; body
mass; athletic performance
Introduction
Road cycling is predominantly an endurance sport, where
performance is highly correlated with maximum oxygen
uptake ( _
VO2 max), muscle fibre type, economy and lactate
threshold (LT1) (Atkinson, Davison, Jeukendrup, & Passfield,
2003). There is also substantial evidence that maximum exter-
nal power output (W
max
) and power at LT1 and onset of blood
lactate accumulation (OBLA or LT2) obtained during a max-
imum incremental cycling test predict cycling performance
(Atkinson et al., 2003; Faria, Parker, & Faria, 2005; Padilla,
Mujika, Cuesta, & Goiriena, 1999). The _
VO2 max is considered
one of the gold standards for the purpose of evaluating and
selecting elite-standard cyclists and as a prerequisite to per-
form at high level. The upper limit for this _
VO2 max is usually
achieved during relatively large muscle mass exercise and
represents the integrative ability of the heart to generate a
high cardiac output, total body haemoglobin, high muscle
blood flow and muscle oxygen extraction, and in some cases
the ability of the lungs to oxygenate the blood (Joyner &
Coyle, 2008). Furthermore, cyclists who are able to tolerate
high submaximal constant intensities, i.e., close to LT2, have a
further advantage, since most of the racing time during pro-
fessional road cycling completion is not spent at W
max
.
Accordingly, different road specialists have high-power output
at both LT1 and LT2 and possess the ability to generate those
high powers of short duration during the mass start, steep
climbing and at the race finish (Faria et al., 2005; Mujika &
Padilla, 2001c). These physiological variables have been used
for monitoring the training status of competitive cyclists in
order to evaluate training methods and their efficacy, both
during the competitive season and in the post-season break
(Faria et al., 2005; Mujika & Padilla, 2003).
Cycling periodisation in young top-level cyclists, who are
not professionals, typically incorporates a transition period of
reduced stress to allow physical and mental recovery after the
end of the competition season, i.e., complete training cessa-
tion in the off season. However, this period is usually longer
than 4 weeks with no tradition of reduced training strategies,
but instead the adoption of an almost sedentary lifestyle.
Long-term detraining has been defined as the partial or com-
plete loss of training-induced anatomical, physiological and
performance adaptations, as a consequence of more than
4 weeks training reduction or cessation and in response to
an insufficient training stimulus (Mujika & Padilla, 2000a,
2000b). Large decreases in cardiorespiratory metabolic and
muscular characteristics have been presented as a result of
detraining in highly trained individuals (Mujika & Padilla,
2001a,2001b). Consequently, specific athletic performance
could decline quickly in high-level athletes (Mujika & Padilla,
2000b).
The effects of training cessation have been investigated in
athletes such as soccer players (Koundourakis et al., 2014),
swimmers (Ormsbee & Arciero, 2012), kayakers (Garcia-
Pallares, Sanchez-Medina, Perez, Izquierdo-Gabarren, &
Izquierdo, 2010), handball players (Marques & Gonzalez-
CONTACT Sara Maldonado-Martín sara.maldonado@ehu.eus
JOURNAL OF SPORTS SCIENCES, 2016
http://dx.doi.org/10.1080/02640414.2016.1215502
© 2016 Informa UK Limited, trading as Taylor & Francis Group
Downloaded by [Universidad Del Pais Vasco] at 04:13 01 August 2016
Badillo, 2006), rowers (Godfrey, Ingham, Pedlar, & Whyte,
2005) and runners (Houmard et al., 1992), but data are scarce
in cycling after a period of long-term detraining. Thus, studies
are needed, first to demonstrate the effects of cessation of
training in a sport where physiological markers are determi-
nants of performance, and second to challenge the traditional
training concepts in young cyclists. A previous study evaluated
the influence of ageing on cardiovascular effects after
2 months of detraining in male cyclists showing nearly similar
left ventricular morphological modifications in the two age
groups (i.e., young, range 1925 years, and older, range
5065 years) (Giada et al., 1998). However, it has not been
investigated yet the effect of training cessation in highly
trained young riders who aspire to become professional
cyclers.
Therefore, the purpose of the present investigation was to
examine the effects of 5 weeks of training cessation in young
top-level road cyclists on body composition, haematological
and physiological parameters related to performance.
Methods
Study design
The present investigation is an observational study without a
control group, where the cyclists completed 2 laboratory-
based progressive exercise tests to assess selected physiologi-
cal variables. One test was at the end of the competition
phase of the cycling season (September = T1) and the second
after 5 weeks of training cessation coinciding with the start of
the season (November = T2). During the cessation period,
cyclists discontinued any kind of physical training with no
control over the cyclistsdiet.
Participants
Ten young male road cyclists were recruited from the same
cycling team. Characteristics of participants were: age
20.1 ± 1.4 years, body mass 68.4 ± 6.3 kg, stature
177.9 ± 5.8 cm (mean ± SD) with a mean of 2 years of
competitive experience at national level (range of 15 years).
Their _
VO2 max was 5.3 ± 0.4 L min
1
, 78.5 ± 5.5 mL · kg
1
·min
1
and 1386 ± 87 mL · kg
0.32
· min
1
with a W
max
of 396 ± 31 W,
5.8 ± 0.4 W · kg
1
and 103 ± 7 W · kg
0.32
. All participants
competed at national standard or above covering a total of
20,00025,000 km per year, with a mean weekly training
duration of 1822 h.
The study was approved by the Bioethics Commission of
the first authors University.
Procedures
Participants were accustomed to the experimental protocol.
Laboratory conditions under which the cyclists performed the
tests were controlled (i.e., 1923°C and 4050% humidity),
including no exhaustive exercise during the 48 h before test-
ing and a standardised diet, with no food intake 3 h before the
test, allowing water ad libitum. Athletes were cooled using
an electric fan during testing.
Anthropometry included stature, body mass and 6 skinfold
thicknesses (Harpenden, Germany) (subscapular, triceps bra-
chii, supraspinale, abdominal, anterior thigh, medial calf).
Skinfolds were assessed on the right side of the body by the
same experienced investigator in accordance with guidelines
from International Society for the Advancement of
Kinanthropometry (Norton et al., 1996).
The assessment consisted of a progressive incremental
protocol to volitional exhaustion on an electrically braked
ergometer (Lode Excalibur Sport, Lode, Groningen, NL, soft-
ware LODE v. 5.1.5) with increments of 35 W every 3 min. The
ergometer was calibrated every day before starting the tests
for intensities of 1001000 W, and after that, prior to every
single test. Each cyclists bike set-up (saddle height, reach and
handle bar height) was recorded and registered for both tests.
Handle bar height and reach were also adjusted to allow a
comfortable position. Clip pedals and set crank lengths of
170 mm were also used. These settings were replicated in
the second trial. The tests were not preceded by any type of
warming-up, and participants cycled at their freely chosen
cadence at each intensity. Initial intensity was 100 W.
Participants were asked to keep their cadence constant at
their preferred rate based on visual feedback from a display
unit. During the test, athletes were encouraged verbally by the
laboratory technicians as well as by their team coach. The
highest intensity (W
max
) was taken to be the highest a cyclist
could maintain for a complete 3-min period. When the last
intensity was not completed for 3 min, W
max
was computed
as: W
max
=Wf+[(t/180) × 35] (Kuipers, Verstappen, Keizer,
Geurten, & Van, 1985), where Wf is the value of the last
completed intensity (in W), tis the time the last uncompleted
intensity was maintained (in s), and 35 is the power output
difference between the last 2 intensities. A single capillary
blood sample was withdrawn from the left earlobe immedi-
ately after completion of each intensity avoiding any contact
with the electrode. Blood lactate concentration was deter-
mined with an automatic analyser (Lactate Pro
TM
). The analy-
ser was calibrated before each test as recommended by the
manufacturer. The exercise intensity corresponding to LT2 was
identified on the blood lactate concentration-power output
curve by straight-line interpolation between the 2 closest
points as the power output eliciting a blood lactate concen-
tration of 4 mmol · l
1
(Sjödin & Jacobs, 1981). The lactate
threshold was identified on individual blood lactate concen-
tration-power output curves as the exercise intensity eliciting
a 1 mmol · l
1
increase in blood lactate concentration above
mean baseline lactate values measured when exercising at
4060% of W
max
(Hagberg & Coyle, 1983). Intensities at LT2
(W
LT2
) and LT1 (W
LT1
) were also determined by straight-line
interpolation (Padilla, Mujika, Santisteban, Impellizzeri, &
Goiriena, 2008). Maximum oxygen uptake was determined
via a breath-by-breath automated gas analysis system
(Jaeger Oxycon Delta System, Hoechberg, Germany) calibrated
before each testing session in line with the manufacturers
guidelines. Maximum oxygen uptake was defined as the
2S. MALDONADO-MARTÍN ET AL.
Downloaded by [Universidad Del Pais Vasco] at 04:13 01 August 2016
highest ˙
VO2value attained towards the end of the test.
Achievement of _
VO2 max was assumed on attainment of at
least 2 of the following 3 criteria: a plateau in ˙
VO2with
increasing speeds (<2.0 mL · kg
1
· min
1
); a respiratory
exchange ratio above 1.10; a heart rate within ±10 beats · min
1
of age predicted maximum heart rate (220-age) (Duncan,
Howley, & Johnson, 1997). Previous studies have shown that
mass exponents of 0.32 and 1 can evaluate level and uphill
cycling ability, respectively (Padilla et al., 1999). Therefore,
because road cycling occurs in a variety of terrains (including
uphill roads) both values adjusted to body mass raised to the
power 0.32 and simple ratio standards were used to compare
the participants (Winter & Nevill, 2009).
For the determination of complete and differential blood
counts (haematological variables), all venous blood samples
were processed by impedancemetric method in a blood ana-
lyser habitually used in Medikosta laboratory (Sysmex XE 2100
Roche). All the samples were analysed within 4 h of collection
in BD Vacutainer Plastic SSTII Advance Tube 8.5 ml. The ana-
lysers (Sysmex XE 2100 Roche) were regularly calibrated and
underwent quality controls, as described by the manufac-
turers. Blood was drawn between 8 am and 10 am in fasting
condition, in the same specialised clinical chemistry centre for
the 2 tests, using standardised venepuncture techniques in
the antecubital vein in the bend of the elbow. Samples were
collected by a phlebotomist.
Statistical analyses
Before all statistical analyses, data were checked for violations
of normality using a ShapiroWilk test. To evaluate the effects
of training cessation on each outcome, 2-sample paired t-tests
were performed using data at baseline and 5 weeks later.
Change between T2 and T1 data were also presented as a
percentage of the baseline values and were arcsine trans-
formed before being compared to reduce skewness. To
distinguish the effects of detraining expressed in relative (nor-
malised by dividing by body mass and by allometric scaling, i.
e., body mass to the power of 0.32) and absolute terms,
changes (expressed as percentages) were compared using 2-
sample paired t-tests. Additionally, 95% confidence interval
(95% CI) constructed around means.
Effect size was calculated by dividing the difference
between means for the outcome variable by the pooled stan-
dard deviation and interpreted as 0.00.19 trivial, 0.200.49
small, 0.500.79 moderate and 0.80 and above large. Analyses
were carried out with SPSS 15.0 (SPSS Inc, Chicago, USA) soft-
ware with alpha set at P< 0.05. Values are reported as
mean ± standard deviation, unless otherwise stated.
Results
Body mass and composition
Changes in body composition are reported in Table 1.
Compared with baseline (T1), body mass (68.4 ± 6.3 vs.
70.1 ± 7.2 kg; 95% CI = 2.8 to 0.4; ES = 0.9; P= 0.014,
+2.3 ± 2.4%) and sum of 6 skinfolds (45.2 ± 9.5 vs.
50.6 ± 7.4 mm; 95% CI = 13.5 to 2.7; ES = 0.5; P= 0.16;
+15.1 ± 23.7%) increased after 5 weeks of detraining period
(at T2).
Haematological variables
There were decreases at T2 for red blood cell count (4.9 ± 0.2
vs. 4.6 ± 0.2 10
6
/μL; 95% CI = 0.10.5; ES = 1.3; P= 0.007;
6.6 ± 4.8%), haemoglobin (14.9 ± 0.7 vs. 14.0 ± 0.5 g/dL;
CI = 0.31.4; ES = 1.2; P= 0.010, 5.4 ± 4.3%) and haematocrit
(43.0 ± 2.0 vs. 41.7 ± 1.9%; CI = 0.22.4; ES = 0.9; P= 0.028,
2.9 ± 3.0%) after the training cessation period (Table 1).
Physiological variables
There were decreases (P< 0.001) at T2 in physiological
responses for W
max
(6.5 ± 3.1%, CI = 0.30.6), _
VO2 max
Table 1. Mean values ± standard deviation for anthropometric, haematological and physiological values in the 2 tests.
Variables T1 T2 Pvalue ES %Change
ANTHROPOMETRICS
Mass (kg) 68.4 ± 6.3 70.1 ± 7.2 0.014 0.9 2.3 ± 2.4
Skinfolds (mm) 45.2 ± 9.5 50.6 ± 7.4 0.16 0.5 15.1 ± 23.7
HAEMATOLOGICAL
RBC (10
6
/μL) 4.9 ± 0.2 4.6 ± 0.2 0.007 1.3 6.6 ± 4.8
Haemoglobin (g/dL) 14.9 ± 0.7 14.0 ± 0.5 0.010 1.2 5.4 ± 4.3
Haematocrit (%) 43.0 ± 2.0 41.7 ± 1.9 0.028 0.9 2.9 ± 3.0
PHYSIOLOGICAL
VO
2max
(L · min
1
) 5.3 ± 0.4 4.8 ± 0.4 <0.001 1.7 8.8 ± 5.0
VO
2max
(mL · kg
1
· min
1
) 78.5 ± 5.5 69.9 ± 4.6 <0.001 2.4 10.8 ± 4.2
VO
2max
(mL · kg
0.32
· min
1
) 1386 ± 87 1253 ± 79 <0.001 2.0 9.4 ± 5.0
W
max
(W) 396 ± 31 371 ± 28 <0.001 1.9 6.5 ± 3.1
W
max
(W·kg
1
) 5.8 ± 0.4 5.3 ± 0.3 <0.001 2.4 8.5 ± 3.3
W
max
(W · kg
0.32
) 103 ± 7 95.8 ± 5.1 <0.001 2.2 7.1 ± 3.0
W
LT1
(W) 303 ± 31 264 ± 36 <0.001 2.1 12.9 ± 7.0
W
LT1
(W · kg
1
) 4.4 ± 0.3 3.8 ± 0.4 <0.001 2.0 14.8 ± 7.4
W
LT1
(W · kg
0.32
) 78.4 ± 6.6 67.8 ± 8.1 <0.001 2.1 13.5 ± 6.8
W
LT2
(W) 336 ± 36 298 ± 40 <0.001 1.8 11.5 ± 7.0
W
LT2
(W · kg
1
) 4.9 ± 0.4 4.3 ± 0.5 <0.001 1.7 13.4 ± 7.6
W
LT2
(W · kg
0.32
) 87.0 ± 7.6 76.4 ± 9.1 <0.001 2.0 12.1 ± 7.0
T1, first test at the end of the competition phase of the cycling season. T2, second test after 5 weeks of training cessation. Pvalue,
difference between T1 and T2. ES, effect size between T1 and T2. % of change between tests. RBC, red blood cells;
_
VO2 max,
maximum oxygen uptake; W
max
, maximum intensity; W
LT1
, intensity at lactate threshold; W
LT2
, intensity at onset of blood lactate
accumulation.
JOURNAL OF SPORTS SCIENCES 3
Downloaded by [Universidad Del Pais Vasco] at 04:13 01 August 2016
(8.8 ± 5.0%, CI = 6.111.1), W
LT1
(12.9 ± 7.0%, CI = 0.40.9),
W
LT2
(11.5 ± 7.0%, CI = 0.40.9) (Table 1). There were larger
decreases (P< 0.05) when changes were expressed in relative
terms (i.e., accounting for changes in body mass) when com-
pared with absolute terms (Table 1 and Figure 1). Results did
not differ when measures allometrically scaled to kg
0.32
com-
pared with ratio standard (Table 1). Effect sizes for all the
physiological variables between T1 and T2 were large (>1)
(Table 1).
Discussion
To our knowledge, this is the first study to report changes in
body composition, haematological and physiological variables
related to performance after 5 weeks of training cessation in
young top-level cyclists. The results of the study indicate that
all the investigated outcomes were adversely affected by the
abrupt cessation of training stimulus, with increases in body
mass and decline in haematological and physiological vari-
ables (Table 1). The larger decreases for physiological variables
expressed relative to body mass, emphasise the importance of
the body mass of a cyclist and its influence on the outcomes
associated with performance (Atkinson et al., 2003).
The present study has shown a decline in variables (abso-
lute and relatives, i.e., normalised by dividing by body mass
and by body mass to the power of 0.32, respectively) asso-
ciated with endurance performance for the young top-level
cyclists after 5 weeks of insufficient training stimulus (Table 1).
Detraining has been shown to decrease the _
VO2 max by 620%
due to reduced total blood volume (i.e., red cell volume plus
plasma volume), and to increase blood lactate levels during
submaximal exercise at the same absolute and relative inten-
sities (Mujika & Padilla, 2000b). In the present study, the mean
decline (i.e., difference between T2 and T1 expressed as % of
T1) in _
VO2 max was by 811%. These decreases were similar to
those for swimmers after 5 weeks of swim detraining (7.7%)
(Ormsbee & Arciero, 2012) and kayakers after 4 weeks of
detraining (11.3%) (Garcia-Pallares et al., 2010). Longer peri-
ods of detraining (12 weeks) have shown mean decreases in
_
VO2 maxof 16% (Coyle et al., 1984). There is substantial evi-
dence demonstrating that successful professional cyclists pos-
sess high _
VO2 max values, and those high values are required
for cycling performance (Faria et al., 2005; Lucia, Pardo,
Durantez, Hoyos, & Chicharro, 1998). It has also been shown
that long-term inactivity may promote a decline in cardiac
dimensions and ventilatory efficiency, affecting both _
VO2 max
and endurance performance of athletes (Giada et al., 1998;
Mujika & Padilla, 2000b). The decline in _
VO2 max is mainly a
consequence of a decrease in oxygen delivery to the muscle
(Bosquet & Mujika, 2012). The rapid decrease in blood volume
after the first days of training cessation probably plays an
important role in the cascade of events that reduces maximum
cardiac output, and consequently _
VO2 max (Bosquet & Mujika,
2012; Coyle, Hemmert, & Coggan, 1986; Coyle et al., 1984). In
the present study, the analysis of the haematological variables
suggests a decrease in blood volume because of declines in
red blood cell count (6.6 ± 4.8%) and haemoglobin
(5.4 ± 4.3%). Rather than complete cessation of training,
published studies have presented reduced training valuable
strategies leading to, instead of detraining, maintenance of
the physiological adaptations achieved during previous train-
ing periods (Mujika, 1998). Indeed, unchanged _
VO2 max has
been reported during periods of reduced training (Hickson,
Kanakis, Davis, Moore, & Rich, 1982; Madsen, Pedersen,
Djurhuus, & Klitgaard, 1993). Accordingly, taking into account
that _
VO2 max measurement remains recommended for the pur-
pose of evaluating and selecting elite cyclists and as a pre-
requisite to perform at a high level (Barbeau, Serresse, &
Boulay, 1993), it would be interesting to adopt these strategies
(i.e., reduced training programmes) in athletes who have to
continually undertake assessment for professional team selec-
tion. A superior performance in endurance sports, such as
cycling, clearly requires high LT1 and LT2 values, since these
have been shown to be better predictors of endurance per-
formance than _
VO2 max (Atkinson et al., 2003). The findings of
the present study for maximum data (i.e.,_
VO2 max,W
max
)
showed smaller decreases (P< 0.001) than the mean declines
in submaximal values (i.e., values at LT1 and LT2) also in
absolute terms (12.9 ± 7.0% for W
LT1
and 11.5 ± 7.0% for
W
LT2
). Similarly, in an elite rower after 8 weeks of training
cessation greater decreases occurred in LT1 (27%) than at
peak intensity (20%) (Godfrey et al., 2005). Thus, the excessive
loss of performance at these metabolic zones (i.e., LT1 and
LT2) during the off season in the present study could have
undesired detrimental consequences for the cyclistsperfor-
mance in subsequent competitive season. Previous studies
that investigated intensity of exercise during mass start-stage
races in professional road cycling, concluded that aerobic
capability dominated and that most of competition time dur-
ing the mass start stages was spent at intensities near LT1
(Padilla et al., 2001; Vogt et al., 2006). Participants of the
present study cover around 25,000 km in a year with in excess
of 50 days of competition and participation in races on more
than 3 consecutive days. Nevertheless, since they were
younger than professional riders, and consequently had
fewer years of training volume, the decline at these
Figure 1. Percentages of change for physiological and performance variables.
VO
2max
, maximum oxygen uptake; W
max
, maximum intensity, WLT1, intensity at lactate
threshold; WLT2, intensity at onset of blood lactate accumulation. Difference between all
absolute and relative values (*P< .05).
4S. MALDONADO-MARTÍN ET AL.
Downloaded by [Universidad Del Pais Vasco] at 04:13 01 August 2016
submaximal metabolic zones (i.e., LT1 and LT2) after a detrain-
ing period could have for a larger impact on performance
compared with professional riders who have experienced
more regular and structured training. In this regard, recently,
it has been shown that older trained individuals appear to
have smaller age-related declines in both maximum and sub-
maximal exercise responses than younger trained ones
(Hopker et al., 2013). Additionally, the decrease in maximum
power output (396 vs. 370 W
max,
6.5 ± 3.1%; 5.8 vs.
5.3 W · kg
1
,8.5 ± 3.3% and 102.5 vs. 95.1 W · kg
0.32
,
7.1 ± 3.0% from T1 to T2) after 5 weeks of training cessation
is estimated to correspond to a reduction in cycling speed of
1.3 km · h
1
in a 1-h race (Bassett, Kyle, Passfield, Broker, &
Burke, 1999). Thus, there is little doubt about the conse-
quences of training cessation on performance.
For the physiological outcomes, there were larger
decreases (P< 0.05) in relative (to body mass) changes than
for absolute changes (Figure 1). This difference is related to
the increase in body mass (2.3 ± 2.4%, P= 0.01) and also the
increase in sum of 6 skinfolds (15.1 ± 23.7%, P= 0.16) at T2. It
is well known that body mass, and specifically body fat, is a
key factor that limits endurance performance because it deter-
mines gravity-dependent resistance, having a major influence
on uphill cycling performance (Padilla et al., 1999). A key
limitation of the present study is the lack of a control group
who continued with a reduced training programme. A pre-
vious study has shown that a reduced training intensity and
volume for 21 days could maintain physiological adaptations,
as measured during submaximal and maximal exercise
(Rietjens, Keizer, Kuipers, & Saris, 2001).
Given that improvements from retraining after training
cessation take considerably longer to achieve than losses
from detraining (Godfrey et al., 2005), there is a need to
programme some endurance stimuli during the off-season
period to minimise losses in physiological and performance
measures in top-level cyclists. It is clear that during the
break after the competition season, an alternative training
stimulus including exercises that involve the same muscle
groups as the competitive activity are necessary to maintain
the metabolic adaptations to training (Bosquet & Mujika,
2012).
Conclusion
In young top-level cyclists, 5 weeks of training cessation
results in large decreases in haematological and both submax-
imal and maximal physiological variables. This long-term
detraining is more pronounced when expressed relative to
body mass via allometric scaling, emphasising the relevance
of the body mass of cyclist and its influence on performance.
This suggests that the training break should be shorter and
that a maintenance programme should be implemented to
avoid such a large decline in physiological values in young
cyclists who aspire to become professionals. We interpret
these findings as being consistent with previous investigations
in other sports, emphasising the importance of establishing
the optimal training load in each phase of the training plan to
avoid excessive declines in performance.
Acknowledgements
The authors would like to thank the cyclists of Seguros Bilbao Cycling
Team for their participation, effort and support in this investigation.
Disclosure statement
No potential conflict of interest was reported by the authors.
ORCID
Sara Maldonado-Martín http://orcid.org/0000-0002-2622-5385
References
Atkinson, G., Davison, R., Jeukendrup, A., & Passfield, L. (2003). Science and
cycling: Current knowledge and future directions for research. Journal
of Sports Sciences,21(9), 767787. doi:10.1080/0264041031000102097
Barbeau, P., Serresse, O., & Boulay, M. R. (1993). Using maximal and
submaximal aerobic variables to monitor elite cyclists during a season.
Medicine & Science in Sports & Exercise,25(9), 10621069. doi:10.1249/
00005768-199309000-00015
Bassett, D. R., Jr., Kyle, C. R., Passfield, L., Broker, J. P., & Burke, E. R. (1999).
Comparing cycling world hour records, 1967-1996: Modeling with
empirical data. Medicine & Science in Sports & Exercise,31(11), 1665
1676. doi:10.1097/00005768-199911000-00025
Bosquet, L., & Mujika, I. (2012). Detraining. In I. Mujika (Ed.), Endurance
training. science and practice (1st ed., pp. 99106). Vitoria-Gasteiz: Iñigo
Mujika S.L.U.
Coyle, E. F., Hemmert, M. K., & Coggan, A. R. (1986). Effects of detraining on
cardiovascular responses to exercise: Role of blood volume. Journal of
Applied Physiology,60,9599.
Coyle, E. F., Martin, W. H., III, Sinacore, D. R., Joyner, M. J., Hagberg, J. M., &
Holloszy, J. O. (1984). Time course of loss of adaptations after stopping
prolonged intense endurance training. Journal of Applied Physiology,57
(6), 18571864.
Duncan, G. E., Howley, E. T., & Johnson, B. N. (1997). Applicability of VO
2max
criteria: Discontinuous versus continuous protocols. Medicine & Science in
Sports & Exercise,29(2), 273278. doi:10.1097/00005768-199702000-00017
Faria, E. W., Parker, D. L., & Faria, I. E. (2005). The science of cycling:
Physiology and training - part 1. Sports Medicine,35(4), 285312.
doi:10.2165/00007256-200535040-00002
Garcia-Pallares, J., Sanchez-Medina, L., Perez, C. E., Izquierdo-Gabarren, M.,
& Izquierdo, M. (2010). Physiological effects of tapering and detraining
in world-class kayakers. Medicine & Science in Sports & Exercise,42(6),
12091214.
Giada, F., Bertaglia, E., De Piccoli, B., Franceschi, M., Sartori, F., Raviele, A., &
Pascotto, P. (1998). Cardiovascular adaptations to endurance training
and detraining in young and older athletes. International Journal of
Cardiology,65(2), 149155. doi:10.1016/S0167-5273(98)00102-8
Godfrey, R. J., Ingham, S. A., Pedlar, C. R., & Whyte, G. P. (2005). The
detraining and retraining of an elite rower: A case study. Journal of
Science and Medicine in Sport,8(3), 314320. doi:10.1016/S1440-2440
(05)80042-8
Hagberg, J. M., & Coyle, E. F. (1983). Physiological determinants of endur-
ance performance as studied in competitive racewalkers. Medicine &
Science in Sports & Exercise,15(4), 287289. doi:10.1249/00005768-
198315040-00006
Hickson, R. C., Kanakis, C., Jr, Davis, J. R., Moore, A. M., & Rich, S. (1982).
Reduced training duration effects on aerobic power, endurance, and
cardiac growth. Journal of Applied Physiology: Respiratory, Environmental
and Exercise Physiology,53(1), 225229.
Hopker, J. G., Coleman, D. A., Gregson, H. C., Jobson, S. A., Von der, H. T.,
Wiles, J., & Passfield, L. (2013). The influence of training status, age, and
muscle fiber type on cycling efficiency and endurance performance.
Journal of Applied Physiology,115(5), 723729. doi:10.1152/
japplphysiol.00361.2013
JOURNAL OF SPORTS SCIENCES 5
Downloaded by [Universidad Del Pais Vasco] at 04:13 01 August 2016
Houmard, J. A., Hortobagyi, T., Johns, R. A., Bruno, N. J., Nute, C. C.,
Shinebarger, M. H., & Welborn, J. (1992). Effect of short-term training
cessation on performance measures in distance runners. International
Journal of Sports Medicine,13(8), 572576. doi:10.1055/s-2007-1024567
Joyner, M. J., & Coyle, E. F. (2008). Endurance exercise performance: The
physiology of champions. The Journal of Physiology Online,586(1), 35
44. doi:10.1113/jphysiol.2007.143834
Koundourakis, N. E., Androulakis, N. E., Malliaraki, N., Tsatsanis, C., Venihaki,
& M., Margioris, A. N. (2014). Discrepancy between exercise perfor-
mance, body composition, and sex steroid response after a six-week
detraining period in professional soccer players. PloS One,9(2), e87803.
doi:10.1371/journal.pone.0087803
Kuipers, H., Verstappen, F. T., Keizer, H. A., Geurten, P., & Van, K. G. (1985).
Variability of aerobic performance in the laboratory and its physiologic
correlates. International Journal of Sports Medicine,6(4), 197201.
doi:10.1055/s-2008-1025839
Lucia, A., Pardo, J., Durantez, A., Hoyos, J., & Chicharro, J. L. (1998).
Physiological differences between professional and elite road cyclists.
International Journal of Sports Medicine,19(5), 342348. doi:10.1055/s-
2007-971928
Madsen, K., Pedersen, P. K., Djurhuus, M. S., & Klitgaard, N. A. (1993). Effects
of detraining on endurance capacity and metabolic changes during
prolonged exhaustive exercise. Journal of Applied Physiology (Bethesda,
Md.: 1985),75(4), 14441451.
Marques, M. C., & Gonzalez-Badillo, J. J. (2006). In-season resistance train-
ing and detraining in professional team handball players. The Journal of
Strength and Conditioning Research,20(3), 563571.
Mujika, I. (1998). The influence of training characteristics and tapering
on the adaptation in highly trained individuals: A review.
International Journal of Sports Medicine,19(7), 439446. doi:10.1055/
s-2007-971942
Mujika, I., & Padilla, S. (2000a). Detraining: Loss of training-induced phy-
siological and performance adaptations. part I: Short term insufficient
training stimulus. Sports Medicine (Auckland, N.Z.),30(2), 7987.
doi:10.2165/00007256-200030020-00002
Mujika, I., & Padilla, S. (2000b). Detraining: Loss of training-induced phy-
siological and performance adaptations. part II: Long term insufficient
training stimulus. Sports Medicine (Auckland, N.Z.),30(3), 145154.
doi:10.2165/00007256-200030030-00001
Mujika,I.,&Padilla,S.(2001a). Cardiorespiratory and metabolic char-
acteristics of detraining in humans. Medicine and Science in Sports
and Exercise,33(3), 413421. doi:10.1097/00005768-200103000-
00013
Mujika, I., & Padilla, S. (2001b). Muscular characteristics of detraining in
humans. Medicine and Science in Sports and Exercise,33(8), 12971303.
doi:10.1097/00005768-200108000-00009
Mujika, I., & Padilla, S. (2001c). Physiological and performance character-
istics of male professional road cyclists. Sports Medicine (Auckland, N.Z.),
31(7), 479487. doi:10.2165/00007256-200131070-00003
Mujika, I., & Padilla, S. (2003). Physiological and performance conse-
quences of training cessation in athletes: Detraining. In W. R. Frontera
(Ed.), Rehabilitation of sports injuries: Scientific basis (pp. 117143).
Malden, MA: Blackwell Science.
Norton, K., Whittingham, N., Carter, L., Kerr, D., Gore, C., & Marfell-Jones, M.
(1996). Measurement techniques in anthropometry [Estándares
Internacionales para la valoración antropométrica]. In K. Norton & T.
Olds (Eds.), Anthropometrica (pp. 2575). Sydney: UNSW.
Ormsbee, M. J., & Arciero, P. J. (2012). Detraining increases body fat and
weight and decreases VO2peak and metabolic rate. The Journal of
Strength and Conditioning Research,26(8), 20872095. doi:10.1519/
JSC.0b013e31823b874c
Padilla, S., Mujika, I., Cuesta, G., & Goiriena, J. J. (1999). Level ground and
uphill cycling ability in professional road cycling. Medicine & Science in
Sports & Exercise,31, 878885. doi:10.1097/00005768-199906000-00017
Padilla, S., Mujika, I., Orbananos, J., Santisteban, J., Angulo, F., & Jose, G. J.
(2001). Exercise intensity and load during mass-start stage races in profes-
sional road cycling. Medicine & Science in Sports & Exercise,33(5), 796802.
Padilla, S., Mujika, I., Santisteban, J., Impellizzeri, F. M., & Goiriena, J. J.
(2008). Exercise intensity and load during uphill cycling in professional
3-week races. European Journal of Applied Physiology,102(4), 431438.
doi:10.1007/s00421-007-0602-9
Rietjens, G. J., Keizer, H. A., Kuipers, H., & Saris, W. H. (2001). A reduction in
training volume and intensity for 21 days does not impair performance
in cyclists. British Journal of Sports Medicine,35(6), 431434.
doi:10.1136/bjsm.35.6.431
Sjödin, B., & Jacobs, I. (1981). Onset of blood lactate accumulation and
marathon running performance. International Journal of Sports
Medicine,2(1), 2326. doi:10.1055/s-2008-1034579
Vogt, S., Heinrich, L., Schumacher, Y. O., Blum, A., Roecker, K., Dickhuth, -H.-
H., & Schmid, A. (2006). Power output during stage racing in profes-
sional road cycling. Medicine & Science in Sports & Exercise,38(1), 147
151. doi:10.1249/01.mss.0000183196.63081.6a
Winter, E. M., & Nevill, A. M. (2009). Scaling: Adjusting for differences in
body size. In R. Eston & T. Reilly (Ed.), Kinanthropometry and exercise
physiology laboratory manual. volume 2: Anthropometry (3rd ed., pp.
300320). Abingdon: Routledge.
6S. MALDONADO-MARTÍN ET AL.
Downloaded by [Universidad Del Pais Vasco] at 04:13 01 August 2016
... To recover from the strenuous competition period, cyclists' training load is often drastically reduced for 2-3 weeks in the subsequent transition period (Lucia et al., 2000;Sassi et al., 2008). However, too long periods (>4 weeks) of training cessation might lead to deterioration of performance (Mujika and Padilla, 2000;Decroix et al., 2016;Maldonado-Martin et al., 2017). ...
... Furthermore, the present study and others (Neufer, 1989;Rietjens et al., 2001) show that maintaining 30-50% of the training volume maintains VO 2max in trained and elite cyclists for short periods (3 weeks). The importance of maintaining a minimum of endurance training is showed in studies where training cessation decreases VO 2max by 7-11% after 3-5 weeks in trained athletes (Coyle et al., 1984;Maldonado-Martin et al., 2017). Changes in blood volume and hemoglobin mass are regarded as main causes for changes in VO 2max (Coyle et al., 1986), and the unchanged VO 2max in the present study is supported by an unchanged blood volume and hemoglobin mass, although this measure was only performed on a sub-set of the participants (see Appendix). ...
Article
Full-text available
The purpose of this study was to investigate the effects of including 30-s sprints in one weekly low-intensity training (LIT) session during a 3-wk transition period in elite cyclists. Sixteen male elite cyclists (maximal oxygen uptake, VO2max: 72±5 mL·kg-1·min-1) reduced their training load by ~60% for 3 wks from the end of competitive season and performed only LIT (CON) or included 30-s sprints in one weekly LIT-session (SPR). Performance and physiological capacities were evaluated during a prolonged (~2.5 hrs) test-session, including a strength test, a submaximal blood lactate profile test, an incremental test to exhaustion to determine VO2max, 1 h continuous cycling including 4 maximal 30-s sprints, and a 20-min all-out test. In addition, mental recovery was evaluated using the Athlete Burnout Questionnaire. The only significant between-group change during the transition period was an 8±11% larger improvement in 30-s sprint performance in SPR compared to CON (SPR: 4±5%, CON: -4±5%, p= .01). Although not different from CON, SPR maintained 20-min all-out performance (-1±5%, p= .37) and fractional utilization of VO2max (1.9±6.1 %-points, p= .18) during the 20-min all-out test, whereas corresponding declines were observed in CON (-3±5%, p= .04, and -2.5±2.9 %-points, p= .02, respectively). Power output at 4 mmol·L-1 blood lactate concentration decreased similarly in SPR (-4±4%, p= .02) and CON (-5±5%, p= .01), while VO2max, maximal aerobic power (Wmax), and total burnout score were unaffected in both groups. Including sprints in one weekly LIT-session in the transition period improves sprint performance and maintains 20-min all-out power and fractional utilization of VO2max without compromising mental recovery. Inclusion of sprints in LIT-sessions may therefore be a plausible, time-efficient strategy during short periods of reduced training.
... To recover from the strenuous competition period, cyclists' training load is often drastically reduced for 2-3 weeks in the subsequent transition period (Lucia et al., 2000;Sassi et al., 2008). However, too long periods (>4 weeks) of training cessation might lead to deterioration of performance (Mujika and Padilla, 2000;Decroix et al., 2016;Maldonado-Martin et al., 2017). ...
... Furthermore, the present study and others (Neufer, 1989;Rietjens et al., 2001) show that maintaining 30-50% of the training volume maintains VO 2max in trained and elite cyclists for short periods (3 weeks). The importance of maintaining a minimum of endurance training is showed in studies where training cessation decreases VO 2max by 7-11% after 3-5 weeks in trained athletes (Coyle et al., 1984;Maldonado-Martin et al., 2017). Changes in blood volume and hemoglobin mass are regarded as main causes for changes in VO 2max (Coyle et al., 1986), and the unchanged VO 2max in the present study is supported by an unchanged blood volume and hemoglobin mass, although this measure was only performed on a sub-set of the participants (see Appendix). ...
... In particular, 2-weeks of inactivity caused a marked reduction in endurance capacity and repeated sprint ability in semi-professional soccer players [14]. Similarly, top-level road cyclists have been shown to produce signi cant reductions in aerobic capacity and power output after ve weeks of detraining [15]. ...
Preprint
Full-text available
This investigation assessed the effect of COVID-19 on the aerobic capacity of professional soccer players who have tested positive. Twenty-one division-1 elite soccer players (age 24.24±5.75 years, height 178.21±5.44 cm, weight 74.12±5.21 kg) participated in this study. This observational study compared the same players' aerobic capacity pre-, and 60-days post COVID-19 recovery. The statistical analysis demonstrated that the infected players had significantly lower VO2max values [t (20) =5.17, p<0.01, d=0.613 (medium effect)], and significantly lower VO2 values at RC [t (20) = 2.97, p<0.05, d= 0.39 (small effect)] after recovery. Furthermore, results indicated a significantly lower running time (RT) on the treadmill [t (20) =4.84, p<0.01, d=0.46 (small effect)] when compared to the results that were obtained before they got infected. In addition, velocity at VO2max ( V VO2 max ) was significantly lower [t (20) =2.34, p<0.05, d=0.41 (small effect)] and the heart rate values at LT [t (20) = -2.79, p<0.01, d= 0.55 (medium effect)] and RC [t (20) = -3.72, p<0.01, d= 0.52 (medium effect)] were significantly higher post recovery. The aforementioned findings indicate that post COVID-19 soccer players may not reach full recovery at two months. Therefore, our results should alert practitioners and fitness coaches of the risk of longer-duration silent symptoms even in athletes that experience mild to moderate manifestations.
... Since our aim was to determine adherence to training using a fitness app, we turned again to literature in order to follow a rule that defined user adherence. Previous researchers have established that exercise-derived health benefits taper off after 4-5 weeks of training cessation [53][54][55][56][57]. Taking this into account, we determined that a user would be considered non-adherent if he/she showed no training activity over a full month (the fourth month). ...
Article
Full-text available
The use of mobile fitness apps has been on the rise for the last decade and especially during the worldwide SARS-CoV-2 pandemic, which led to the closure of gyms and to reduced outdoor mobility. Fitness apps constitute a promising means for promoting more active lifestyles, although their attrition rates are remarkable and adherence to their training plans remains a challenge for developers. The aim of this project was to design an automatic classification of users into adherent and non-adherent, based on their training behavior in the first three months of app usage, for which purpose we proposed an ensemble of regression models to predict their behaviour (adherence) in the fourth month. The study was conducted using data from a total of 246 Mammoth Hunters Fitness app users. Firstly, pre-processing and clustering steps were taken in order to prepare the data and to categorize users into similar groups, taking into account the first 90 days of workout sessions. Then, an ensemble approach for regression models was used to predict user training behaviour during the fourth month, which were trained with users belonging to the same cluster. This was used to reach a conclusion regarding their adherence status, via an approach that combined affinity propagation (AP) clustering algorithm, followed by the long short-term memory (LSTM), rendering the best results (87% accuracy and 85% F1_score). This study illustrates the suggested the capacity of the system to anticipate future adherence or non-adherence, potentially opening the door to fitness app creators to pursue advanced measures aimed at reducing app attrition.
... 7,8 The suspension of competitions places athletes in the transition phase within their training or detraining period, where partial or complete loss of adaptations caused by training may be observed due to insufficient stimuli, 9 reducing maximum and submaximal performance in aerobic exercises in a few weeks, coincident with impairments in cardiovascular function and metabolic muscle potential. 10 During the transition period, cyclists show increases in body weight and decreases in VO2max and maximum power, 11 while runners show decreases in VO2max and time to exhaustion, 12 both of which are facts that may directly affect the physical fitness of these athletes. ...
Article
Full-text available
Introduction: The COVID-19 pandemic has led to social isolation measures in different contexts. In endurance sports, competitions worldwide have been canceled, affecting behavioral, psychological, and physical aspects. Objective: This study aimed to assess potential associations between stress, motivation, behavioral changes, and physical fitness in endurance athletes, and time in social isolation. Methods: A cross-sectional study with the participation of 201 athletes, including mountain bikers (n = 89), runners (n = 88) and triathletes (n = 24). Each participant answered questions about time spent in isolation; body weight; changes in training schedule during the isolation period; levels of motivation; stress levels; loss of physical fitness; what aspect of physical fitness was most jeopardized during the isolation period; alcohol consumption; quality of sleep; quality of diet; and whether they had been ill during the isolation period. Results: The results showed significant differences between the percentage of runners (4.5%) and triathletes (16.7%) who had been isolated from 1-10 days, and between the percentage of cyclists (41.6%) and runners (68.2%) in 11-20 days and >20 days (28.1% and 9.1%) respectively. Social isolation was significantly associated with at least one variable for the three groups of athletes; however, the runners were the most affected by the pandemic, presenting an association with low motivation, high stress, poorer quality of sleep, increased alcohol consumption, and loss of physical fitness. Conclusion: Our study showed that the period of social isolation, specifically over time > 10 days, generated significant changes in the perceptions of motivation, stress, alcohol consumption, and physical fitness of endurance athletes, with runners being the most affected group. Level of Evidence III; Diagnostic studies - Investigation of a diagnostic test; Study of non-consecutive patients, without a “gold standard” applied uniformly.
... The interruption of training can increase the maximal heart rate from 3 to 5% 22 in two weeks and seems to stabilize since then 22 . Other cardiovascular repercussions can occur, such as a reduction in the stroke volume in the submaximal exercise of ~ 10 to 14% 22 , a reduction in the maximal cardiac output of ~ 7 to 10% and the estimated left ventricular mass 23 . Concerning the peripheral component of cardiovascular fitness, detraining seems to yield small changes in the capillarization of athletes, which even after this period remains superior to sedentary individuals. ...
Article
Full-text available
In March 2020, the World Health Organization (WHO) declared the disease caused by the SARS-CoV2 virus, known as COVID-19, to be a pandemic. The sporting world, too, is suffering from the global effects of this disease, with the postponement or cancellation of competitions, including the 2020 Tokyo Olympic Games. As a proposal for containing the disease, social isolation was declared. Despite the importance of this measure, it was harmful for Olympic athletes, as they had to stay away from their training site and trainers, as well as their interdisciplinary teams. It is therefore important to study this harm caused, in order to minimize it. In general, it is believed that regular physical activity is associated with improved immune system functioning. The lack of training can therefore have significant consequences for the performance and health of the Olympic athlete. From the athlete’s point of view, the impaired immune system, due to the reduced frequency of physical exercise, leaves them more vulnerable to contracting or developing infections or other diseases. The risk of harm due to the decreased performance of preventive works is also evident in this population. The reductions in training load and intensity can cause changes in the athlete’s body composition and affect various aspects of cardiorespiratory fitness, as well as reducing strength levels and muscle potency. In relation to the athlete’s mental health, two aspects are particularly challenging: isolation and uncertainty. Based on the possible harm caused by social isolation, the need is seen for a specific and joint work, in an attempt to minimize it. This work addresses the following topics: (I) context: transmission, symptoms, diagnosis, treatment, discharge criteria, isolation and post-pandemic consequences; (II) harm and proposals: nutritional, physiological, biomechanical and psychological.
... 12 Reduções no VO 2 máx com três semanas de DT 7,13,14 e com quatro semanas de DT 9,15-18 também foram encontradas em indivíduos não-atletas e atletas. [19][20][21] Contudo, Madsen e cols. 22 e Heffernan e cols. ...
Article
This paper contributes to the debate on anti-doping policies not by evaluating the policy itself but by evaluating the announcement of (new) policy measures. We develop a dynamic model for analyzing the effects of two different types of news shocks: (1) the preannouncement of improved drug testing technological opportunities and (2) the preannouncement of future increases in financial sanctions. We find that the anticipation of policy changes affects the behavior of potentially delinquent athletes. In both scenarios, our simulations show immediately reduced drug abuse among athletes. We conclude that authorities may consider news shocks as an anti-doping strategy.
Article
Full-text available
Purpose: To investigate the effects of including repeated sprints in a weekly low-intensity (LIT)-session during a 3-week transition period on cycling performance 6 weeks into the subsequent preparatory period in elite cyclists. Methods: Eleven elite male cyclists (age: 22.0 [3.8]y, body mass: 73.0 [5.8]kg, height: 186 [7]cm, maximal oxygen uptake (VO2max): 5469 [384] mL·min-1) reduced their training load by 64% and performed only LIT-sessions (CON, n=6), or included 3 sets of 3 x 30-sec maximal sprints in a weekly LIT-session (SPR, n=5) during a 3-week transition period. There were no differences in training load leading up to the transition period, in the reduction during the transition period or in the increase in the preparatory period between groups. Physiological and performance measures were compared between the end of the competitive period (COMP) and 6 weeks into the subsequent preparatory period (PREP). Results: SPR demonstrated a 7.3% [7.2%] improvement in mean power output during a 20-min all-out test (W·kg-1) at PREP, which was greater than CON (-1.3% [4.6%]) (p=0.048). SPR had a corresponding 7.0 [3.6]% improvement in average VO2 during the 20-min all-out test, which was larger than the 0.7 [6.0]% change in CON (p=0.042). No change in VO2max, gross efficiency or power output at blood lactate concentration of 4 mmolL-1 from COMP to PREP occurred in either group. Conclusion: The inclusion of sprints in a weekly low-intensity (LIT)-session during the transition period of elite cyclists provided a performance advantage 6 weeks into the subsequent preparatory period, which coincided with a higher performance-VO2. Accepted for pulication nov 15. 2020.
Article
Full-text available
The aim of this review is to provide greater insight and understanding regarding the scientific nature of cycling. Research findings are presented in a practical manner for their direct application to cycling. The two parts of this review provide information that is useful to athletes, coaches and exercise scientists in the prescription of training regimens, adoption of exercise protocols and creation of research designs. Here for the first time, we present rationale to dispute prevailing myths linked to erroneous concepts and terminology surrounding the sport of cycling. In some studies, a review of the cycling literature revealed incomplete characterisation of athletic performance, lack of appropriate controls and small subject numbers, thereby complicating the understanding of the cycling research. Moreover, a mixture of cycling testing equipment coupled with a multitude of exercise protocols stresses the reliability and validity of the findings. Our scrutiny of the literature revealed key cycling performance-determining variables and their training-induced metabolic responses. The review of training strategies provides guidelines that will assist in the design of aerobic and anaerobic training protocols. Paradoxically, while maximal oxygen uptake (VO2max) is generally not considered a valid indicator of cycling performance when it is coupled with other markers of exercise performance (e.g. blood lactate, power output, metabolic thresholds and efficiency/economy), it is found to gain predictive credibility. The positive facets of lactate metabolism dispel the ‘lactic acid myth’. Lactate is shown to lower hydrogen ion concentrations rather than raise them, thereby retarding acidosis. Every aspect of lactate production is shown to be advantageous to cycling performance. To minimise the effects of muscle fatigue, the efficacy of employing a combination of different high cycling cadences is evident. The subconscious fatigue avoidance mechanism ‘teleoanticipation’ system serves to set the tolerable upper limits of competitive effort in order to assure the athlete completion of the physical challenge. Physiological markers found to be predictive of cycling performance include: (i) power output at the lactate threshold (LT2); (ii) peak power output (Wpeak) indicating a power/weight ratio of ≥5.5 W/kg; (iii) the percentage of type I fibres in the vastus lateralis; (iv) maximal lactate steady-state, representing the highest exercise intensity at which blood lactate concentration remains stable; (v) Wpeak at LT2; and (vi) Wpeak during a maximal cycling test. Furthermore, the unique breathing pattern, characterised by a lack of tachypnoeic shift, found in professional cyclists may enhance the efficiency and metabolic cost of breathing. The training impulse is useful to characterise exercise intensity and load during training and competition. It serves to enable the cyclist or coach to evaluate the effects of training strategies and may well serve to predict the cyclist’s performance. Findings indicate that peripheral adaptations in working muscles play a more important role for enhanced submaximal cycling capacity than central adaptations. Clearly, relatively brief but intense sprint training can enhance both glycolytic and oxidative enzyme activity, maximum short-term power output and VO2max. To that end, it is suggested to replace ~15% of normal training with one of the interval exercise protocols. Tapering, through reduction in duration of training sessions or the frequency of sessions per week while maintaining intensity, is extremely effective for improvement of cycling time-trial performance. Overuse and over-training disabilities common to the competitive cyclist, if untreated, can lead to delayed recovery.
Article
Full-text available
Purpose: The aim of this study was to examine the effects of a six-week off-season detraining period on exercise performance, body composition, and on circulating sex steroid levels in soccer players. Methods: Fifty-five professional male soccer players, members of two Greek Superleague Teams (Team A, n = 23; Team B, n = 22), participated in the study. The first two weeks of the detraining period the players abstained from any physical activity. The following four weeks, players performed low-intensity (50%-60% of VO2max) aerobic running of 20 to 30 minutes duration three times per week. Exercise performance testing, anthropometry, and blood sampling were performed before and after the six-week experimental period. Results: Our data showed that in both teams A and B the six-week detraining period resulted in significant reductions in maximal oxygen consumption (60,31±2,52 vs 57,67±2,54; p<0.001, and 60,47±4,13 vs 58,30±3,88; p<0.001 respectively), squat-jump (39,70±3,32 vs 37,30±3,08; p<0.001, and 41,05±3,34 vs 38,18±3,03; p<0.001 respectively), and countermovement-jump (41,04±3,99 vs 39,13±3,26; p<0.001 and 42,82±3,60 vs 40,09±2,79; p<0.001 respectively), and significant increases in 10-meters sprint (1,74±0,063 vs 1,79±0,064; p<0.001, and 1,73±0,065 vs 1,78±0,072; p<0.001 respectively), 20-meters sprint (3,02±0,05 vs 3,06±0,06; p<0.001, and 3,01±0,066 vs 3,06±0,063; p<0.001 respectively), body fat percentage (Team A; p<0.001, Team B; p<0.001), and body weight (Team A; p<0.001, Team B; p<0.001). Neither team displayed any significant changes in the resting concentrations of total-testosterone, free-testosterone, dehydroepiandrosterone-sulfate, Δ4-androstenedione, estradiol, luteinizing hormone, follicle-stimulating hormone, and prolactin. Furthermore, sex steroids levels did not correlate with exercise performance parameters. Conclusion: Our results suggest that the six-week detraining period resulted in a rapid loss of exercise performance adaptations and optimal body composition status, but did not affect sex steroid resting levels. The insignificant changes in sex steroid concentration indicate that these hormones were a non-contributing parameter for the observed negative effects of detraining on exercise performance and body composition.
Chapter
Full-text available
Article
Full-text available
Competitive collegiate swimmers commonly take a month off from swim training after their last major competition. This abrupt cessation of intense physical training has not been well studied and may lead to physiopsychological decline. The purpose of this investigation was to examine the effects of swim detraining (DT) on body composition, aerobic fitness, resting metabolism, mood state, and blood lipids in collegiate swimmers. Eight healthy endurance-trained swimmers (V(O2)peak, 46.7 ± 10.8 ml · kg(-1) · min(-1)) performed 2 identical test days, 1 in the trained (TR) state and 1 in the detrained (~5 weeks) state (DT). Body composition and circumferences, maximal oxygen consumption (V(O2)peak), resting metabolism (RMR), blood lipids, and mood state were measured. After DT, body weight (TR, 68.9 ± 9.7 vs. DT, 69.8 ± 9.8 kg; p = 0.03), fat mass (TR, 14.7 ± 7.6 vs. DT, 16.5 ± 7.4 kg; p = 0.001), and waist circumference (TR, 72.7 ± 3.1 vs. DT, 73.8 ± 3.6 cm; p = 0.03) increased, whereas V(O2)peak (TR, 46.7 ± 10.8 vs. DT, 43.1 ± 10.3 ml · kg(-1) · min(-1); p = 0.02) and RMR (TR, 1.34 ± 0.2 vs. DT, 1.25 ± 0.17 kcal · min(-1); p = 0.008) decreased, and plasma triglycerides showed a trend to increase (p = 0.065). Our data suggest that DT after a competitive collegiate swim season adversely affects body composition, fitness, and metabolism. Athletes and coaches need to be aware of the negative consequences of detraining from swimming, and plan off-season training schedules accordingly to allow for adequate rest/recovery and prevent overuse injuries. It's equally important to mitigate the negative effects on body composition, aerobic fitness and metabolism so performance may continue to improve over the long term.
Article
Seven endurance exercise-trained subjects were studied 12, 21, 56, and 84 days after cessation of training. Maximal O2 uptake (VO2 max) declined 7% (P less than 0.05) during the first 21 days of inactivity and stabilized after 56 days at a level 16% (P less than 0.05) below the initial trained value. After 84 days of detraining the experimental subjects still had a higher VO2 max than did eight sedentary control subjects who had never trained (50.8 vs. 43.3 ml X kg-1 X min-1), due primarily to a larger arterial-mixed venous O2 (a-vO2) difference. Stroke volume (SV) during exercise was high initially and declined during the early detraining period to a level not different from control. Skeletal muscle capillarization did not decline with inactivity and remained 50% above (P less than 0.05) sedentary control. Citrate synthase and succinate dehydrogenase activities in muscle declined with a half-time of 12 days and stabilized at levels 50% above sedentary control (P less than 0.05). The initial decline in VO2 max was related to a reduced SV and the later decline to a reduced a-vO2 difference. Muscle capillarization and oxidative enzyme activity remained above sedentary levels and this may help explain why a-vO2 difference and VO2 max after 84 days of detraining were still higher than in untrained subjects.
Article
The purpose of this study was to assess the influence of age, training status and muscle fibre type distribution on cycling efficiency. Forty males were recruited into one of 4 groups: young and old trained cyclists, young and old untrained individuals. All participants completed an incremental ramp test to measure their VO2peak, maximal heart rate (HRmax) and maximal minute power output (MMP); a submaximal test of ratio corrected cycling gross efficiency at a series of absolute and relative work rates; and in trained participants only, a 1-hour cycling time trial. Finally, all participants underwent a muscle biopsy of their right vastus lateralis muscle. At relative work rates, a general linear model found significant main effects of age and training status on cycling efficiency (P<0.01). The percentage type I muscle fibres was higher in the trained groups (P<0.01), with no difference between age groups. There was no relationship between fibre type and cycling efficiency at any work rate or cadence combination. Stepwise multiple regression indicated that muscle fibre type did not influence cycling performance (P>0.05). Power output in the 1-h performance trial was predicted by average VO2 and GE, with standardised beta coefficients of 0.94 and 0.34 respectively, although some mathematical coupling is evident. These data demonstrate that muscle fibre type does not affect cycling efficiency and was not influenced by the ageing process. Cycling efficiency and the percentage of type I muscle fibres were influenced by training status, but only GE at 120 rev⋅min(-1) was seen to predict cycling performance.
Article
The effect of scattering laser radiation penetrating to the critical region off random density irregularities present in the underdense region of a laser‐produced plasma is investigated. Two approaches are used to clarify the effect and the result is applied to the problem of plasma density profile modification by the ponderomotive force.
Article
This study analyzed changes in neuromuscular, body composition, and endurance markers during 4 wk of tapering and subsequent 5 wk of reduced training (RT) or training cessation (TC). Fourteen world-class kayakers were randomly assigned to either a TC (n = 7) or an RT group (n = 7). One-repetition maximum (1RM) strength, mean concentric velocity with 45% 1RM (V45%) in the bench press (BP) and prone bench pull (PBP) exercises, and body composition assessments were conducted at the start (T0) and end (T1) of a 43-wk training program, after tapering for the world championships (T2) and after TC or RT (T3). A graded exercise test on a kayak ergometer for determination of maximal oxygen uptake at T0, T1, and T3 was also performed. After tapering, no significant changes were observed in 1RM or V45%. TC resulted in significantly greater declines in 1RM strength (-8.9% and -7.8%, P < 0.05, respectively, for BP and PBP) than those observed for RT (-3.9% and -3.4%). Decreases in V45% in BP and PBP were larger for TC (-12.6% and -10.0%) than for RT (-9.0% and -6.7%). Increases in sum of eight skinfolds were observed after both TC and RT, whereas declines in maximal aerobic power were lower for RT (-5.6%) than for TC (-11.3%). Short-term TC results in large decreases in maximal strength and especially V45% in highly trained athletes. These results suggest the need of performing a minimal maintenance program to avoid excessive declines in neuromuscular function in cases where a prolonged break from training is required.