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Polarized training has greater impact on key endurance variables than threshold, high intensity, or high volume training

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Endurance athletes integrate four conditioning concepts in their training programs: high-volume training (HVT), “threshold-training” (THR), high-intensity interval training (HIIT) and a combination of these aforementioned concepts known as polarized training (POL). The purpose of this study was to explore which of these four training concepts provides the greatest response on key components of endurance performance in well-trained endurance athletes. Methods: Forty eight runners, cyclists, triathletes, and cross-country skiers (peak oxygen uptake: (VO2peak): 62.6 ± 7.1 mL·min−1·kg−1) were randomly assigned to one of four groups performing over 9 weeks. An incremental test, work economy and a VO2peak tests were performed. Training intensity was heart rate controlled. Results: POL demonstrated the greatest increase in VO2peak (+6.8 ml·min·kg−1 or 11.7%, P < 0.001), time to exhaustion during the ramp protocol (+17.4%, P < 0.001) and peak velocity/power (+5.1%, P < 0.01). Velocity/power at 4 mmol·L−1 increased after POL (+8.1%, P < 0.01) and HIIT (+5.6%, P < 0.05). No differences in pre- to post-changes of work economy were found between the groups. Body mass was reduced by 3.7% (P < 0.001) following HIIT, with no changes in the other groups. With the exception of slight improvements in work economy in THR, both HVT and THR had no further effects on measured variables of endurance performance (P > 0.05). Conclusion: POL resulted in the greatest improvements in most key variables of endurance performance in well-trained endurance athletes. THR or HVT did not lead to further improvements in performance related variables.
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ORIGINAL RESEARCH ARTICLE
published: 04 February 2014
doi: 10.3389/fphys.2014.00033
Polarized training has greater impact on key endurance
variables than threshold, high intensity, or high volume
training
Thomas Stöggl1,2*and Billy Sperlich3
1Department of Sport Science and Kinesiology, University of Salzburg, Salzburg, Austria
2Department of Health Sciences, Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden
3Institute of Sport Science, University of Würzburg, Würzburg, Germany
Edited by:
Niels H. Secher, University of
Copenhagen, Denmark
Reviewed by:
Niels H. Secher, University of
Copenhagen, Denmark
Stefanos Volianitis, Aalborg
University, Denmark
*Correspondence:
Thomas Stöggl, Department of
Sport Science and Kinesiology,
University of Salzburg, Schlossallee
49, 5400 Hallein/Rif, Salzburg,
Austria
e-mail: thomas.stoeggl@sbg.ac.at
Endurance athletes integrate four conditioning concepts in their training programs:
high-volume training (HVT), “threshold-training” (THR), high-intensity interval training
(HIIT) and a combination of these aforementioned concepts known as polarized training
(POL). The purpose of this study was to explore which of these four training concepts
provides the greatest response on key components of endurance performance in
well-trained endurance athletes.
Methods: Forty eight runners, cyclists, triathletes, and cross-country skiers (peak oxygen
uptake: (VO2peak): 62.6±7.1mL·min1·kg1) were randomly assigned to one of four
groups performing over 9 weeks. An incremental test, work economy and a VO2peak tests
were performed. Training intensity was heart rate controlled.
Results: POL demonstrated the greatest increase in VO2peak (+6.8 ml·min·kg1or 11.7%,
P<0.001), time to exhaustion during the ramp protocol (+17.4%, P<0.001) and peak
velocity/power (+5.1%, P<0.01). Velocity/power at 4 mmol·L1increased after POL
(+8.1%, P<0.01) a n d H IIT (+5.6%, P<0.05). No differences in pre- to post-changes
of work economy were found between the groups. Body mass was reduced by 3.7%
(P<0.001) following HIIT, with no changes in the other groups. With the exception of
slight improvements in work economy in THR, both HVT and THR had no further effects
on measured variables of endurance performance (P>0.05).
Conclusion: POL resulted in the greatest improvements in most key variables of
endurance performance in well-trained endurance athletes. THR or HVT did not lead to
further improvements in performance related variables.
Keywords: lactate threshold, peak power, peak oxygen uptake, time to exhaustion, work economy
INTRODUCTION
Athletes participating in endurance sports such as running,
cycling, and cross-country skiing integrate four conditioning
concepts into their training program to maximize athletic perfor-
mance. The first conditioning concept is prolonged high-volume
low-intensity exercise (HVT). The second is training at or near the
lactate threshold (THR); third is low-volume high-intensity inter-
val training (HIIT) and the fourth concept is a combination of the
aforementioned concepts known as “polarized” training (POL).
There is a debate as to which of these training concepts may be
superior in maximizing adaptations and performance.
HVT executed with low (LOW) intensity [approximately
65–75% of peak oxygen uptake (VO2peak)<80% of peak heart
rate (HRpeak)or<2 mmol·L1blood lactate (Laursen and
Jenkins, 2002; Seiler and Kjerland, 2006)] and prolonged dura-
tion is thought to be a fundamental training concept in preparing
for endurance events. This type of exercise improves VO2peak
by increasing stroke and plasma volume and induces molecular
adaptations for capillary and mitochondrial biogenesis, thereby
improving the efficiency of metabolic key components for energy
fueling (Romijn et al., 1993; Midgley et al., 2006).
HIIT has revealed great improvements in athletic performance
and related key variables of endurance (e.g., time to exhaustion,
time trial performance, VO2peak, maximal and submaximal run-
ning speed, running economy) in both trained and untrained
individuals (Laursen and Jenkins, 2002). These improvements
were largely due to increases in O2availability, extraction and
utilization and the increases in VO2peak (Daussin et al., 2007;
Helgerud et al., 2007). A condensed 2 week block of 10–13 ses-
sions of HIIT led to a 7% increase in VO2peak (Stølen et al.,
2005).
Training at or close to the lactate threshold (LT) (Faude et al.,
2009), referred to as “threshold training,” improves endurance
performance, particularly in untrained participants (Denis et al.,
1984; Londeree, 1997). However, Norwegian world-class sprint
cross-country skiers demonstrated greater training volume close
to the LT when compared to national-level skiers (Sandbakk
et al., 2011). Furthermore, in elite cross-country skiers greater
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Stöggl and Sperlich Endurance training concepts
improvements in running speed at lactate threshold and perfor-
mance in a 20-min run when exercising at an intensity elicit-
ing 3–4 mmol·L1lactate compared with low intensity training
(<3–4 mmol·L1)werefound(Evertsen et al., 2001). In contrast,
experimental and correlational data from well-trained athletes
suggest that training time close to LT may be ineffective, or even
counterproductive (Esteve-Lanao et al., 2007; Guellich and Seiler,
2010).
Retrospective analysis of the intensity, duration and fre-
quency of the training load of international-level cross-country
skiers (Seiler and Kjerland, 2006), rowers (Steinacker et al.,
1998), cyclists (Schumacher and Mueller, 2002), and runners
(Billat et al., 2001; Esteve-Lanao et al., 2005) revealed that elite
endurance athletes completed most of their yearly training ses-
sions at either intensities below (75% of total training volume)
or well above (15–20% of total training volume) their LT. Six
weeks of cycling using POL resulted in greater systemic adap-
tation in already well-trained athletes when compared to THR
(Neal et al., 2013). However, no study has investigated the POL
concept in well-trained endurance athletes to determine whether
this concept may be superior to the aforementioned training
strategies.
Inmanyendurancesports,fivekeyvariableshavebeenused
as a benchmark to compare athletic performance in and between
endurance athletes: (i) VO2peak (Bassett and Howley, 2000); (ii)
velocity/power output at the lactate threshold (V/PLT )(Bassett
and Howley, 2000; Midgley et al., 2007; Faude et al., 2009); (iii)
work economy (Di Prampero et al., 1986; Helgerud et al., 2001);
(iv) peak running velocity or power output (V/Ppeak)(Midgley
et al., 2007); and (v) time to exhaustion (TTE) (Laursen and
Jenkins, 2002). The aim of this study was to compare the effects
of four training concepts (HVT vs. THR vs. HIIT vs. POL) on the
aforementioned key variables of endurance performance in well-
trained athletes. We hypothesized that the POL and HIIT group
would lead to superior improvements compared with HVT and
THR.
MATERIALS AND METHODS
PARTICIPANTS
Forty eight healthy competitive endurance athletes who partici-
pated in either cross-country skiing, cycling, triathlon, middle—
or long-distance running volunteered to take part in this study
(mean ±SD:age:31±6 years, body mass: 73.8 ±9kg,
height: 180 ±8 cm). All participants were well-trained [62.6
±7.1 mL·min1·kg1(range: 52–75 mL·min1·kg1)] athletes,
accustomed to a workload of more than five sessions per week
(10–20 h·wk1)andhadfrequentlybeeninvolvedinendurance
competitions for at least 8–20 years. Participants were members
of the Austrian cross-country skiing national team (n=8), run-
ning (n=21), triathlon (n=4) or cycling (n=15) teams during
or since the year before the current study. Retrospective analysis
of training protocols over 6 months prior to the study revealed
that none of the participants had regularly executed HIIT. All had
followed a HVT training protocol with a maximum of two THR
training sessions per week.
Based on the participants’ baseline VO2peak and training mode
(running or cycling), all athletes were randomized into HIIT,
HVT, THR or POL. At baseline, the four groups were not sta-
tistically different with regard to age, height, body mass or
VO2peak . During an initial visit, study details and participation
requirements were explained, and written informed consent was
obtained. The study received approval from the University of
Salzburg Austria Ethics Committee and was conducted in accor-
dance with the Declaration of Helsinki.
DESIGN
The intervention lasted 9 weeks plus 2 days of pre- and post-
testing. All athletes (n=15 cyclists; n=3 triathletes) engaging
in cycling training trained with their own bike and completed
all tests on a bicycle ergometer (Ergoline, Ergoselect 100P; Bitz,
Germany) using their own cycling shoes and pedal system.
Other athletes (n=16 runners, n=6 triathletes, n=8 cross-
country skiers) ran during the study and completed their pre-
and post-testing on a motorized treadmill (HP Cosmos, Saturn,
Traunstein, Germany). All participants were instructed not to
change their diet throughout the training period and to main-
tain strength training, if it was part of their training program.
Participants’ nutritional intake was not standardized or con-
trolled during the study, but for the 3h prior to all testing in which
food intake was not permitted. The training intensity was con-
trolled by HR based on the baseline incremental test: (i) LOW
(HR at blood lactate value <2 mmol·L1); (ii) LT (HR corre-
sponding to a blood lactate of 3–5 mmol·L1); (iii) HIGH (>90%
HRpeak)]. The HR was measured during each training session and
athletes documented training mode, exercise duration, and inten-
sity in a diary. As a control and for detailed analysis, HR for all
training sessions was stored digitally and analyzed retrospectively.
HVT INTERVENTION
The HVT included three blocks each lasting 3 weeks: 2 weeks of
high-volume training followed by 1 week of recovery (Figure 1A).
The two high volume weeks each included six training sessions
with three 90 min LOW sessions, two 150–240 min LOW sessions
(according to the training mode: running, cycling, or roller ski-
ing) and one 60 min LT session using different types of interval
training (e.g., 5 ×7 min with 2 min recovery, 3 ×15 min with
3 min recovery). The recovery week included three training ses-
sions with two 90 min LOW sessions and one 150–180 min LOW
session.
THR INTERVENTION
The THR included three blocks, each lasting 3 weeks: 2 weeks
of high volume and intensity training followed by 1 week of
recovery (Figure 1B). The two high volume and intensity weeks
each included six training sessions with two 60 min interval ses-
sions at the LT (5 ×6 min and 2min recovery in the first block,
6×7mininthesecondblockand6×8 min in the last block),
one 90 min LT session with longer intervals (3 ×15 min with
3 min active recovery in the first block and 3 ×20 min for the
remaining two blocks), one 75 min session with varying changes
in intensity (“fartlek”) (intensities resulting in a blood lactate
of 1.5–5 mmol·L1) and two 90 min LOW sessions. The recov-
ery week included one 60 min LOW session and two 60min LT
interval sessions (5 ×6 min with 2 min of active recovery).
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Stöggl and Sperlich Endurance training concepts
FIGURE 1 | Training program for 3-weeks of (A) high volume (HVT), (B)
threshold (THR), (C) polarized (POL) training, and (D) the training
program for the first block of high intensity interval training (HIIT),
excluding the recovery week. LOW, low training intensity (<2 mmol·L1);
LT, training intensity around the lactate threshold (3–5 mmol·L1); FL, fartlek;
HIIT, high intensity interval training (>90% HRpeak); R, recovery day.
HIIT INTERVENTION
The HIIT included two interval blocks of 16 days with one adap-
tation week prior to and one recovery week after each block.
The adaptation week included two 60 min HIIT sessions, three
90 min LOW sessions, one 120min LOW session and 1 day of
recovery. The condensed 16 day interval block included 12 HIIT
sessions within 15 days, integrating four blocks of three HIIT
sessions for three consecutive days followed by 1 day of recov-
ery. The recovery week contained four LOW sessions of 90 min
and 3 days without any training (not presented in Figure 1D).
All of the HIIT sessions included a 20 min warm-up at 75%
of HRpeak,4×4 min at 90–95% of HRpeak with 3 min active
recovery and a 15 min cool-down at 75% HRpeak based on the
protocol proposed earlier (Helgerud et al., 2007). The LOW
sessions lasted 90–150 min depending on the training mode
(running vs. cycling) at an intensity resulting blood lactate of
<2 mmol·L1.
POL INTERVENTION
The POL included three blocks, each lasting 3 weeks: 2 weeks of
high volume and intensity training followed by 1 week of recov-
ery (Figure 1C). The high volume and intensity week included six
sessions with two 60 min HIIT sessions, two 150–240 min long
duration LOW sessions (duration according to training mode:
cycling, running or roller skiing), which included six to eight
maximal sprints of 5 s separated by at least 20 min, and two
90 min LOW sessions. The recovery week included one 60 min
HIIT session, one 120–180 min LOW session and one 90min
LOW session.
PRE AND POST-TESTING
All participants were asked to report well-hydrated and to refrain
from consuming alcohol and caffeine for at least 24-h, as well as
from engaging in strenuous exercise at least 48-h prior to testing.
The pre- and post-tests included the determination of body mass,
an incremental test protocol, a work economy and VO2peak ramp
protocol.
On the first day participants performed an incremental test on
a treadmill (7.2 km·h1; increment: 1.8 km·h1every 5 min, with
30 s recovery between stages, inclination 1%) or cycle ergome-
ter (80 W; increment: 40 W every 5 min, cadence >80 rpm) until
volitionalexhaustionwasachievedtoassessthepeakveloc-
ity/power output (V/Ppeak), HR, blood lactate, as well as the
velocity, power output and HR at 2 and 4 mmol·L1blood lac-
tate (V/P2,V/P
4and HR2,HR
4). The participants’ HR was
recorded by telemetry (Suunto t6, Helsinki, Finland) at 2-s inter-
vals. The mean HR over the last 30 s of each increment was used
for statistical analysis. A 20 µl blood sample from the right ear-
lobe was collected immediately after each increment, as well as
3 and 5 min after the completion of the test into a capillary
tube (Eppendorf AG, Hamburg, Germany). All samples were ana-
lyzed amperometric-enzymatically (Biosen 5140, EKF-diagnostic
GmbH, Magdeburg, Germany) in duplicate, and the mean of the
two measures was used for statistical analysis. The lactate sensor
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Stöggl and Sperlich Endurance training concepts
was calibrated before each test using a lactate standard sample
of 12 mmol·L1. Results within a range of ±0.1 mmol·L1were
accepted.
One day after the incremental tests, all athletes completed a
combined work economy and VO2peak ramp protocol to deter-
mine their submaximal and peak VO2(VO2submax and VO2peak)
and HR (HRsubmax and HRpeak), as well as time to exhaustion
(TTE). First, the intensity for running was set at 8 km·h1(incli-
nation: 5%) on the treadmill, and for cycling at 200 W with
a cadence of >80 rpm for 10 min to determine VO2submax and
HRsubmax for this intensity. The mean VO2andHRduringthe
last 5 min of these tests were used for statistical purposes. The
intensity was then increased every 30 s by 0.5 km·h1(inclina-
tion: 10%) on the treadmill or 15 W on the cycle ergometer until
exhaustion. The overall time for the ramp test was defined as time
to exhaustion (TTE). VO2was measured with an open circuit
breath-by-breath spirograph (nSpire, Zan 600 USB, Oberthulba,
Germany), which was calibrated prior to each test using high pre-
cision gas (15.8% O2,5%O
2in N; Praxair, Düsseldorf, Germany)
and a 1L syringe (nSpire, Oberthulba, Germany). All respiratory
data were averaged every 30 s. VO2peak was achieved if three of
the four following criteria were met: (1) plateau in VO2, i.e., an
increase <1.0 mL·min1·kg1despite an increase in velocity or
power output; (2) respiratory exchange ratio >1.1; (3) HR ±5%
of age predicted HRpeak; and (4) peak blood lactate (LApeak)>
6 mmol·L1after exercise. Reliability analysis of The VO2peak test
(n=18) revealed ICC values of 0.96 for VO2peak and 0.98 for
TTE.
STATISTICAL ANALYSES
All data exhibited a Gaussian distribution verified by the Shapiro-
Wilk’s test and, accordingly, the values are presented as means ±
SD.Two-Way2×4 repeated-measures ANOVA (2 times: pre–
post, 4 groups) to test for global differences between pre- and
post-intervention, the four training groups and the interaction
effect between both factors was applied. When a significant
main effect over time was observed, paired t-tests within each
group were conducted. Based on the different units of peak
power/velocity and power/velocity at 2 and 4mmol·L1blood
lactate in the incremental and VO2peak test, percent changes
between pre- to post-values were calculated, and a One-Way
ANOVA between groups was performed using Tukey’s post-hoc
analysis. Furthermore, within group changes for these variables
were calculated using Wilcoxon tests. An alpha value of <0.05
was considered significant. The Statistical Package for the Social
Sciences (Version 20.0; SPSS Inc., Chicago, IL, USA) and Office
Excel 2010 (Microsoft Corporation, Redmond, WA, USA) were
used for statistical analysis.
RESULTS
Forty-one participants completed the 9 week training protocol,
fulfilling more than 95% of the training program and staying
within the given HR zones. Seven subjects (2 in HIIT, 1 in HVT
and 4 in THR) withdrew from the study due to illness (n=2), or
were excluded due to changes in competition schedule (n=3) or
for not fulfilling the training protocol (n=2). The total training
hours, number of training sessions and their percent distribu-
tion within LOW, LTP, and HIIT are presented in Tab l e 1 .POL
and HVT had higher training volume compared with THR and
HIIT (P<0.05–0.001), while having a similar number of train-
ing sessions (P>0.05). HVT demonstrated the greatest amount
of LOW, THR of LT, and HIIT in HIGH training sessions (all,
P<0.05).
Body mass after HIIT was reduced by 3.7±3.0% (baseline:
73.5±6.8 kg, post: 70.7±6.5kg, P<0.01) with no significant
change in the HVT, THR or POL groups. The reduction in
body mass after HIIT was greater compared to other training
interventions (P<0.001).
Percent changes in variables from pre- to post-training
and between the training concepts during the VO2peak-
ramp, work economy, and incremental tests are presented in
Tab l e 2 . POL demonstrated the greatest increase in VO2peak
Table 1 | The distribution of volume and training intensity within the 9 weeks training intervention (excluding strength training).
POL HIIT THR HVT F-Value P-Value
Total hours 104 ±20$66 ±1*84 ±7*102 ±11$a
F(3,37)=20 <0.001
Number of sessions 54 ±347±149±358±3aF(3,37)=1.6 n.s.
Amount of training at low
intensity (%)
37 ±9(68±12%)*20 ±1(43±1%)§23 ±6(46±7%)§49 ±7(83±6%)*aF(3,37)=41 <0.001
Amount of training at lactate
threshold (%)
3±4(6±8%)*0 (0%)*26 ±2(54±7%)*9±3(16±6%)*aF(3,37)=197 <0.001
Amount of training at high
intensity (%)
14 ±3(26±7%)*27 ±1(57±1%)*0 (0%)†‡ 1±1(1±1%)†‡ aF(3,37)=769 <0.001
The values presented are means ±SD. F- and P-values were obtained by One-Way ANOVA (4 training groups). POL, polarized training group; HIIT, High intensity
interval training group; THR, threshold training group; HVT, high volume training group.
*Different from all other groups.
Different from training group “POL.
Different from training group “HIIT.
$Different from training group “THR.
§Different from training group “HVT.
aMain effect between groups.n.s., not significant.
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Table 2 | Changes in physiological variables from pre- to post-training.
POL HIIT THR HVT F-Value P-Value
Pre Post Pre Post Pre Post Pre Post
VO2peak -test
VO2peak
[L·min1·kg1]
60.6±8.367.4±7.7*** 63.7±7.166.6±5.8*63.2±4.660.8±7.160.5±9.462.1±9.8F(1,37)=13.6a<0.001
11.7±8.4% 4.8±5.6% 4.1±6.7%†††‡ 2.6±4.5%F(3,37)=0.5bNS
F(3,37)=11.9c<0.001
VO2peak
[L·min1]
4.4±1.04.9±1.1*** 4.6±0.54.7±4.94.4±0.84.3±9.24.8±0.74.9±0.7F(1,37)=6.4a<0.05
10.4±7.9% 1.1±7.6%3.7±7.0%††† 2.9±4.5%F(3,37)=0.6bNS
F(3,37)=8.0c<0.001
HRpeak [bpm] 187 ±7186±7185±9182±11 18 0 ±10 179 ±9183±4183±4F(1,37)=1.9aNS
0.6±1.9% 1.3±2.3% 0.2±1.9% 0.3±1.9% F(3,37)=1.4bNS
F(3,37)=1.0cNS
LApeak
[mmol·L1]
10.2±1.710.7±1.79.6±1.710.2±1.79.5±1.69.9±2.210.1±1.79.9±2.0F(1,37)=1.7aNS
7.5±20.4% 6.4±8.3% 5.3±19.1% 1.0±11 .8% F(3,37)=0.4bNS
F(3,37)=0.4cNS
Work economy
VO2submax
[mL·min·1kg1]
38.2±5.539.7±5.034.8±6.135.9±6.234.7±5.133.7±4.435.2±4.435.3±4.7F(1,37)=0.5aNS
4.6±10.5% 3.8±12.0% 2.1±7.80.6±9.5% F(3,37)=2.0bNS
F(3,37)=1.0cNS
VO2submax
[%VO2peak]
62.4±12.359.0±9.8*54.8±5.053.2±5.354.9±7.956.0±8.158.9±8.657.7±9.6F(1,37)=2.3aNS
4.8±7.6% 2.5±10.5% 2.5±11 .32.1±7.0% F(3,37)=1.3bNS
F(3,37)=1.4cNS
HRsubmax [bpm] 136 ±10 135 ±13 141 ±13 131 ±6** 143 ±3139±3*136 ±7134±5F(1,37)=11.7a<0.01
3.3±6.4% 6.7±4.4% 2.7±1.01.1±3.4% F(3,37)=0.4bNS
F(3,37)=1.7cNS
HRsubmax
[%HRpeak]
74 .3±5.472.5±6.376.1±4.771.9±2.2*77.8±3.675.8±3.9** 74 .2±2.173.0±1.6F(1,37)=9.3a<0.01
2.4±6.3% 5.4±4.5% 2.6±0.91.6±2.0% F(3,37)=0.7bNS
F(3,37)=1.0cNS
(Continued)
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Stöggl and Sperlich Endurance training concepts
Table 2 | Continued
POL HIIT THR HVT F-Value P-Value
Pre Post Pre Post Pre Post Pre Post
Incremental test
HR2[bpm] 139 ±9136±13 138 ±10 141 ±9152±12 151 ±9138±19 138 ±18 F(1,37)=0.1aNS
2.3±6.1% 2.2±5.9% 0.1±9.50.3±6.5% F(3,37)=3.7b<0.05
F(3,37)=0.5cNS
HR4[bpm] 157 ±14 157 ±13 163 ±12 162 ±11 1 7 1 ±9169±9160±12 162 ±12 F(1,37)=0.2aNS
0.1±3.9% 0.3±3.8% 1.2±3.81.1±4.8% F(3,37)=2.6bNS
F(3,37)=0.5cNS
HRpeak [bpm] 186 ±6184±5*191 ±10 19 1 ±10 187 ±9184±9187±7184±4F(1,37)=5.5a<0.05
0.9±1.3% 0.02 ±2.3% 1.2±2.71.4±2.9% F(3,37)=1.2bNS
F(3,37)=0.6cNS
LApeak
[mmol·L1]
10.6±1.511.1±1.611.1±1.811.9±2.39.9±1.810.2±2.510.8±1.49.8±1.3F(1,37)=0.2aNS
4.7±13.4% 7.7±21.1% 4.0±20.0% 7.2±21.0% F(3,37)=1.6bNS
F(3,37)=1.1cNS
The values presented are means ±SD. F and P values were obtained by Two-Way ANOVA (2 ×4: time ×training group) with repeated measures. POL, polarized training group; HIIT, High intensity interval training
group; THR, threshold training group; HVT, high volume training group; VO2, oxygen uptake; HR, heart rate; LApeak, peak blood lactate concentration; *p<0.05; ** p<0.01; ***p<0.001 significant difference
within groups from pre- to post-training. p<0.05; †††p<0.001 significant different from POL training group.p<0.05 significant different from HIIT training group. aMain effect between pre- and post-test.
bMain effect between training groups. ctime ×training group interactive effect.
with an 11.7±8.4%, (60.6±8.3–67.4±7.7ml·min1·kg1;
P<0.001), followed by HIIT with a 4.8±5.6% increase (P<
0.05). The change in VO2peak in POL was higher compared to
THR and HVT (P<0.001 and P<0.05). Absolute VO2peak
increased in POL by 10.4±7.9% (P<0.001), which was greater
compared with the other training concepts (HIIT and HVT P<
0.05, THR P<0.001). No changes from pre to post and no dif-
ferences between training groups with respect to HRpeak,LA
peak,
and HR2&4 were detected (P>0.05). Work economy increased
following HIIT (6.7±4.4% decrease in HR, P<0.01) and
THR (2.7±1.0% decrease in HR, P<0.05) with no signif-
icant differences between the other concepts. Work economy
expressed as percent of VO2peak was only improved after POL
(4.8±7.6%, P<0.05) with no significant differences between
the other training groups.
The changes in TTE, V/Ppeak and V/P2&4 from pre- to post-
training and between the single training groups are presented in
Tab l e 3 . The largest percentage increase in TTE, assessed using the
VO2peak ramp test, was observed in response to POL (+17.4%,
P<0.001) followed by HIIT (+8.8%, P<0.01); however, no
statistical differences were found between the four training con-
cepts. V/Ppeak in the incremental test increased in response to
POL and HIIT (5.1±3.0% and 4.4±2.8%, both P<0.01) with
both groups demonstrating greater changes than HVT (P<0.01
and P<0.05). V/P4increased after POL (8.1±4.6%, P<0.01)
and HIIT (5.6±4.8%, P<0.01) demonstrating greater changes
after POL compared to THR and HVT (both P<0.05).
DISCUSSION
The purpose was to determine whether HIIT, HVT, THR, or POL
provides the greatest impact on key variables of endurance per-
formance in well-trained athletes. The main findings were that
(1) POL led to the greatest improvement in VO2peak,TTEand
V/Ppeak;(2)V/P
4increased after POL and HIIT; (3) no significant
differences in work economy were observed pre to post between
any of the groups; and finally (4) body mass decreased by 3.7% in
response to HIIT.
There are several challenges associated with conducting an
exercise training intervention such as the one presented here.
Firstly, the compliance of all athletes is paramount to the success-
ful completion of the study and for the subsequent examination
of the intervention. The athletes attended more than 95% of all
training sessions and all completed their predetermined train-
ing load (intensity based on HR zones, duration, and frequency),
which was confirmed by logging the daily training dose in a diary
and retrospective analysis of HR data. Secondly, an experimen-
tal study is difficult to conduct in elite athletes because typically
neither the athletes nor their coaches like to have the athletes’
training intensity, duration or frequency altered. However, we
successfully managed to conduct the current study in well-trained
male and female athletes (VO2peak: 52–75 mL·min1·kg1)overa
9weekperiod.
Of the four training concepts, POL resulted in the greatest
increase in VO2peak,TTE,V/P
peak and, together with HIIT, in
V/P4.Asmentioned,POLwasconrmedbyretro-perspective
analysis of the intensity, duration and frequency distribution of
the training load in highly trained athletes (Steinacker et al.,
Frontiers in Physiology | Exercise Physiology February 2014 | Volume 5 | Article 33 |6
Stöggl and Sperlich Endurance training concepts
Table 3 | Per cent changes in velocity (V) and power (P) and at various lactate thresholds as well as peak velocity and power.
POL HIIT THR HVT F-Value P-Value
TTE 17.4±16.1*** 8.8±8.6** 6.2±9.08.0±10.3aF(3,37)=2.0NS
V/P29.3±12.412.1±8.8** 2.0±13.80.8±13.3aF(3,37)=1.9NS
V/P48.1±4.6** 5.6±4.8*1.4±4.31.2±6.6aF(3,37)=4.5<0.01
V/Ppeak 5.1±3.0** 4.4±2.8** 1.8±4.81.5±4.9††‡ aF(3,37)=4.6<0.01
The values presented are means ±SD. F and P values were obtained by One-Way ANOVA (4 training groups) calculated over the per cent differences between pre-
to post-training. POL, polarized training group; HIIT, High intensity interval training group; THR, threshold training group; HVT, high volume training group; TTE, time
to exhaustion during the ramp test; V/P2, velocity or power at 2mmol·L1; V/P4, velocity or power at 4 mmol·L1; V/Ppeak, peak velocity or power in the incremental
test; *p<0.05; **p<0.01; ***p<0.001 significant difference within groups from pre- to post-training.
p<0.05; ††p<0.01 significant different from POL training group.
p<0.05significant different from HIIT training group.
aMain effect between groups.
1998; Billat et al., 2001; Schumacher and Mueller, 2002; Seiler
and Kjerland, 2006; Esteve-Lanao et al., 2007). In these studies,
it was demonstrated that endurance athletes perform approxi-
mately 75% of their yearly training program either below or well
above (15–20%) the LT, but little at the LT. In the current study,
POL mimicked this distribution (LOW =68%, LTP =6%, HIGH
=26%). Only the study of Neal et al. (2013) demonstrated that
6 weeks of POL resulted in greater systemic adaptation in trained
cyclists when compared to THR, hence supporting our findings.
In moderately trained persons, HVT improves metabolic and
hemodynamic adaptations over 3 days (Green et al., 1987, 1990;
Coyle, 1999). However, a greater volume of training (3–5 weeks
with 3–5 sessions·wk1) is needed to improve VO2peak (Laursen
and Jenkins, 2002). One reason due to why athletes may choose a
high amount of HVT may be due to that HVT leads to improved
fat and glucose utilization (Romijn et al., 1993), which is ben-
eficial for long lasting endurance events. Therefore, it might be
reasonable to implement HVT in the training programs of elite
endurance athletes for improving oxidative flux, which is impor-
tant for converting energy aerobically and recovery after and
during HIIT sessions with large anaerobic portions. When HVT
becomes the major component of a training program and HIIT
sessions are neglected, no further improvement in VO2peak and
performance in already well-trained athletes occur (Costill et al.,
1988; Laursen and Jenkins, 2002); in line with the findings of
the present study. Further improvements of well-trained ath-
letes require adding high intensity training sessions to HVT, as
demonstrated in POL. However, due to that the participants of
this study mainly used HVT prior to this experiment, the HVT
model might not have provided an adequate stimulus for further
adaptations.
The advantage of HIIT compared to HVT lies in a shorter
period of training time for similar muscular adaptations (Gibala
et al., 2006; Burgomaster et al., 2008). In response to HIIT, sev-
eral central and peripheral adaptations including increased stroke
(Helgerud et al., 2007) and blood volume (Shepley et al., 1992),
O2extraction (Daussin et al., 2007), and improvements in aero-
bic and anaerobic metabolism (Macdougall et al., 1998), such as
increased mitochondrial biogenesis and oxidative capacity, have
been reported (Gibala et al., 2006; Daussin et al., 2007, 2008;
Burgomaster et al., 2008). The aforementioned adaptations in
response to HIIT explain the often documented increases in TTE,
time trial performance (Lindsay et al., 1996), lactate and ventila-
tory threshold (Acevedo and Goldfarb, 1989; Edge et al., 2005)
and VO2peak (Laursen and Jenkins, 2002; Gibala et al., 2006;
Midgley et al., 2006; Daussin et al., 2007, 2008; Burgomaster et al.,
2008).
The present study, as well as that of Helgerud et al. (2007),
demonstrated that training at or near VO2peak maybemoreeffec-
tive in enhancing VO2peak when compared to HVT or THR.
However, POL, a combination of HVT and HIIT, may be supe-
rior for enhancing VO2peak and performance. Numerous studies
using “blocked” or “condensed” HIIT (i.e., several HIIT session
in 1 or 2 weeks) aim to increase VO2peak (Stølen et al., 2005).
Furthermore, in HIIT intervention studies (2–3 HIIT sessions per
week), VO2peak increased approximately 9% over a 10 week train-
ing intervention (McMillan et al., 2005) and 11% over a 6 week
training intervention (Helgerud et al., 2001) in youth and junior
soccer players, suggesting a 0.5% increase in VO2peak per HIIT
training session. In the current study, the increase in VO2peak
following 9 weeks of HIIT (27 HIIT sessions) was 4.8% (0.18%
increase per training session), while POL resulted in an 11.7%
increase in VO2peak with fewer HIIT sessions (14 HIIT) (0.84%
increase per training session). This result may be explained by:
(1) peak adaptation might have been reached following the first
HIIT block, and therefore, repeated HIIT bouts did not pro-
duce any further improvements in VO2peak or performance, or
(2) the combination of HVT and HIIT, much like in POL, leads
to greater long-term adaptations in endurance performance than
with exclusively HIIT or HVT.
THR improves VO2peak, lactate or ventilatory thresholds and
endurance performance in untrained persons (Denis et al., 1984;
Londeree, 1997; Gaskill et al., 2001). These findings contrast those
of the current study, as we did not observe improvements in
VO2peak ,V/P
4,TTEorV/P
peak in our elite athletes in response to
THR. Additionally, it is possible that in well-trained endurance
athletes, repeated training bouts at LT might generate unwar-
ranted sympathetic stress (Chwalbinska-Moneta et al., 1998),
while offering no further stimulus for performance enhance-
ment (Londeree, 1997). In this context, especially within the THR
group, significant variability in the individual changes in VO2peak
from pre- to post-intervention were observed (range: 20 to
www.frontiersin.org February 2014 | Volume 5 | Article 33 |7
Stöggl and Sperlich Endurance training concepts
+4%). However, some THR training might be beneficial to
well-trained athletes since world-class sprint cross-country skiers
demonstrated greater training volume in the low and moderate
intensity zones compared with national-level skiers (Sandbakk
et al., 2011).
The body mass of the well-trained athletes decreased by 3.7%
(approximately 3 kg) after HIIT, but not in response to the other
training concepts. HIIT favors lipid oxidation and promotes adi-
pose tissue loss (Perry et al., 2008; Boutcher, 2011). Depending
on the athlete’s baseline value, reduction in body mass may neg-
atively impact immune function and overall health, as well as
induce a catabolic state. Training blocks with increased volume
and/or exercise intensity might induce symptoms of “overreach-
ing,” reduced physical capacity, burnout symptoms including
tiredness, and lack of energy (Angeli et al., 2004). However,
despite the large differences in the individual responses in some
of the training groups, none of the athletes demonstrated reduced
TTE or V/Ppeak after the study, nor did they report any of the
aforementioned symptoms during and after the 9 week interven-
tion. Based on the observed changes in body mass and smaller
increases in VO2peak in the HIIT group compared with previ-
ously published data (McMillan et al., 2005; Stølen et al., 2005;
Helgerud et al., 2007), longer blocks of training periods with high
intensities could provoke these symptoms.
Except for significant decreases in %VO2peak in the POL group
and HRsubmax/%HRpeak in the HIIT and THR groups (with no
group differences), no improvements in work economy were
found in the current study. Helgerud et al. (2007) reported a 5%
improvement in running economy after THR, HIIT, and HVT
with no differences between groups. These improvements were
mainly attributed to an increased amount of running training.
Therefore, the applied training regimes were largely responsi-
ble for the changes in V/Ppeakand VO2peak, while work economy
remained fairly constant. V/P4was only improved in POL (8.1%)
and HIIT (5.6%). This is consistent with findings demonstrating
that running velocity at lactate threshold follows the improve-
ments in VO2peak (Helgerud et al., 2001; McMillan et al., 2005).
LIMITATIONS AND PERSPECTIVES
Standardized methodology of performance diagnostics (incre-
mental test and VO2peak ramp protocol) was utilized to evaluate
the effects of the four endurance training interventions on key
variables of endurance performance. However, a direct transfer to
specific competition situation (e.g., time trial) need to be estab-
lished in future research. Furthermore, the increase of about 11%
in VO2peak with POL within 9 weeks is large for well-trained
endurance and has to be put in perspective within the annual
training periodization. Long-term training studies are warranted
to evaluate these aspects.
CONCLUSION
In this study of elite athletes performing HIIT, HVT, THR or
POL training, POL results in the greatest improvements in key
variables of endurance performance (VO2peak,TTE,V/P
peak,and
V/P4). HIIT led to a decrease in body mass and less pronounced
increases in VO2peak compared with previous findings using short
term (1–2 weeks) HIIT, suggesting that a 9 week HIIT should be
applied with care. Exclusive training with THR or HVT did not
lead to further improvements in endurance performance related
variables in well-trained athletes.
DISCLOSURE OF FUNDING
No funding was received for this work from the National
Institutes of Health, the Welcome Trust, the Howard Hughes
Medical Institute, or other funding agencies to PubMed Central.
None of the authors had any professional relationships with com-
panies or manufacturers who will benefit from the results of the
present study. The authors declare no conflict of interest.
AUTHOR CONTRIBUTIONS
Conception and design of the experiments: Thomas Stöggl,
Billy Sperlich. Performance of the experiments: Thomas Stöggl.
Data analysis: Thomas Stöggl, Billy Sperlich. Preparation of the
manuscript: Thomas Stöggl and Billy Sperlich. Both authors read
and approved the final manuscript.
ACKNOWLEDGMENTS
The authors would like to thank the athletes, coaches, and
research assistants involved in this study for their participation,
enthusiasm, and cooperation. The authors would like to express
appreciation for the support of Donna Kennedy. Special thanks
to Julia Stöggl, Andreas Hochwimmer and Thomas Damisch for
their great assistance in recruitment, care and control of the ath-
letes during the training intervention and pre- and post-testing.
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Conflict of Interest Statement: The authors declare that the research was con-
ducted in the absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Received: 02 October 2013; accepted: 16 January 2014; published online: 04 February
2014.
Citation: Stöggl T and Sperlich B (2014) Polarized training has greater impact on key
endurance variables than threshold, high intensity, or high volume training. Front.
Physiol. 5:33. doi: 10.3389/fphys.2014.00033
This article was submitted to Exercise Physiology, a section of the journal Frontiers in
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... Furthermore, the participants' nutritional intake was not considered during the study. However, no food intake was allowed for three hours before the measurements were performed [11,28]. Participants completed the anthropometric measurement using an 8-electrode segmental multi−frequency bioelectrical impedance analysis (BIA, 50-1000 kHz) (InBody 770; InBody Co. Ltd., Seoul, Republic of Korea). ...
... The test was stopped when the blood lactate concentration (La − ) was greater than 4 mmol�L −1 after each running speed. The initial jogging stage was followed by an additional recovery (cooldown) stage (5 min) [11,[28][29][30]. The same set-up was utilized after nine weeks in the post-ILIE LT test. ...
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The aim of this study was to investigate whether individualized low-intensity exercise (ILIE) within the recovery domain before lactate threshold 1 (LT 1) improves energetic recovery and general endurance capacity in professional soccer players. Twenty-four professional soccer players (age: 24.53 ± 4.85 years, height: 180 ± 6.30 cm, body mass: 75.86 ± 8.01 kg, body fat: 12.19 ± 2.69%) participated in the study (n = 24). The 1-h ILIE intervention involved 27 jogging sessions spanning nine weeks and jogging speed corresponding to 72% of LT 1 (7.15 ± 0.95 km�h −1). Pre-ILIE and post-ILIE LT testing variables measured within 9 weeks included blood lactate concentrations (La −) and heart rate (HR) at specific exercise intensities during ILIE LT test. The jogging/running speeds (S), delta (Δ) S, HR, and ΔHR were measured at 1.5, 2.0, 3.0, and 4.0 mmol�L −1 La − , respectively. Values of La − and HR at the same exercise intensities (5.4-16.2 km�h −1) in the post-ILIE LT test compared with pre-ILIE LT test were significantly decreased (P < 0.05 and P < 0.01, respectively). Furthermore, S at all specific La − levels (1.5, 2.0, 3.0, and 4.0) were significantly increased, while HR at 2.0, 3.0, and 4.0 La − decreased significantly (P < 0.05 and P < 0.01, respectively). Low to moderate positive correlations were observed between ΔS and ΔHR at 1.5 and 2.0 La − (r = 0.52 and r = 0.40, respectively). The nine-week ILIE improved energy recovery and general endurance of professional soccer players. This relates to repeated high-intensity intermittent sprints during the 90-min soccer game.
... BMC Sports Science, Medicine and Rehabilitation (2022) 14:84 Background Athletes use high-intensity interval training (HIIT) as a complementary training method to continuous endurance training [1]. HIIT sessions are usually less time-consuming but still effective to improve the aerobic fitness compared with high volume low-intensity sessions [2][3][4][5][6]. ...
... Given this lower training volume and a training distribution towards high-intensity training during a HIIT-SM compared to standard training weeks, a novel approach with additional LIT added to the single HIIT sessions (not as separate training sessions) could shed light on the subject of the optimal training volume. The combination of LIT and HIIT applied in regular training weeks (microcycle/mesocycle) is widely accepted to improve endurance performance [4,[21][22][23]. ...
... The widely adopted idea of polarized training [4,21,22], i.e., a combination of LIT and HIIT, leads us to assume that further adaptations may occur in HSM + LIT. LIT serves as a potent stimulus to enhance fat oxidation and glucose utilization, which are essential for aerobic energy provision during prolonged endurance training [61][62][63][64]. ...
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Background Performing multiple high-intensity interval training (HIIT) sessions in a compressed period of time (approximately 7–14 days) is called a HIIT shock microcycle (SM) and promises a rapid increase in endurance performance. However, the efficacy of HIIT-SM, as well as knowledge about optimal training volumes during a SM in the endurance-trained population have not been adequately investigated. This study aims to examine the effects of two different types of HIIT-SM (with or without additional low-intensity training (LIT)) compared to a control group (CG) on key endurance performance variables. Moreover, participants are closely monitored for stress, fatigue, recovery, and sleep before, during and after the intervention using innovative biomarkers, questionnaires, and wearable devices. Methods This is a study protocol of a randomized controlled trial that includes the results of a pilot participant. Thirty-six endurance trained athletes will be recruited and randomly assigned to either a HIIT-SM (HSM) group, HIIT-SM with additional LIT (HSM + LIT) group or a CG. All participants will be monitored before (9 days), during (7 days), and after (14 days) a 7-day intervention, for a total of 30 days. Participants in both intervention groups will complete 10 HIIT sessions over 7 consecutive days, with an additional 30 min of LIT in the HSM + LIT group. HIIT sessions consist of aerobic HIIT, i.e., 5 × 4 min at 90–95% of maximal heart rate interspersed by recovery periods of 2.5 min. To determine the effects of the intervention, physiological exercise testing, and a 5 km time trial will be conducted before and after the intervention. Results The feasibility study indicates good adherence and performance improvement of the pilot participant. Load monitoring tools, i.e., biomarkers and questionnaires showed increased values during the intervention period, indicating sensitive variables. Conclusion This study will be the first to examine the effects of different total training volumes of HIIT-SM, especially the combination of LIT and HIIT in the HSM + LIT group. In addition, different assessments to monitor the athletes' load during such an exhaustive training period will allow the identification of load monitoring tools such as innovative biomarkers, questionnaires, and wearable technology. Trial Registration : clinicaltrials.gov, NCT05067426. Registered 05 October 2021—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT05067426 . Protocol Version Issue date: 1 Dec 2021. Original protocol. Authors: TLS, NH.
... Seiler and Kjerland estimated that elite endurance athletes perform about 75% of their training volume at intensities below the first ventilatory threshold [12], as this type of training enhances their ability to recover from high-intensity exercises [19]. Briefly summarised, previous studies show that low-intensity and high-volume training, as well as high-intensity and lowvolume training, are effective methods to increase athletes' performance [8,10,13,15,20,21]. These and some other studies indicate that it is important to include both methods in the training programs of athletes who participate in high-intensity sports. ...
... For elite athletes competing in intense endurance competitions (e.g., XCO races), a polarized approach has been suggested as the best distribution of training intensity, with 75% of the total training volume performed at low intensities,~15% performed at very high intensities, and the remaining proportions performed somewhere in between [8,12,13,[19][20][21]. Nevertheless, there is neither a training concept that is generally accepted in practice nor scientific evidence that allows reliable statements about the superiority of a certain TID method. ...
... This statistically significant difference has also not been demonstrated in some other studies comparing different training intensity distributions such as POL, LIT, THR, PYR or others [41,42], while some other studies indicate that POL leads to greater improvements in endurance performance compared to other training methods. Nevertheless, the small trend towards the superiority of POL is in line with the results of some previous studies that examined the effects of different training modalities on cycling performance [10,13,20,21,43]. Stöggl and Sperlich examined 48 endurance athletes in four intervention groups (LIT, THR, HIIT, POL) before and after a 9-week training period. ...
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To improve performance in endurance sports, it is important to include both high-intensity and low-intensity training, but there is neither a universally accepted practice nor clear scientific evidence that allows reliable statements about the predominance of a specific training method. This randomized controlled trial compared the effects of a polarized training model (POL) to a low-intensity training model (LIT) on physiological parameters and mountain bike cross-country Olympic (XCO) race performance in eighteen competitive XCO athletes (17.9 ± 3.6 years). The superiority of one of the two methods could not be shown in this study. The results did not show statistically significant differences between POL and LIT, as both interventions led to slight improvements. However, a small tendency toward better effects for POL was seen for cycling power output during the race (4.4% vs. –2.2%), at the 4 mmol/L (6.1% vs. 2.8%) and individual anaerobic lactate threshold (5.1% vs. 2.3%), and for maximal aerobic performance (4.4% vs. 2.6%), but not for maximal efforts lasting 10 to 300 s. Despite the lack of significant superiority in this and some other studies, many athletes and coaches prefer POL because it produces at least equivalent effects and requires less training time.
... In elite athletes, a polarised training approach combining moderate and high intensity training has been shown to be superior to both low-volume HIIT and heavy intensity training. 39 Laursen 40 argued that HIIT and more prolonged training sessions at a lower intensity might cause similar aerobic adaptations in the skeletal muscle via different molecular pathways, while low-intensity training might also promote autonomic balance and recovery. Therefore, their combination in a training programme might result in highest performance improvements. ...
... have consistently shown greater improvements following polarised training. 39 41 43 In real-life situations, a combination of training intensities might be more practicable and enjoyable, cardiometabolic health benefits more thorough, the physiological training stimulation more varied and a combination of different training intensities could result in better management of training stress. ...
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Physical activity (PA) guidelines for the general population are designed to mitigate the rise of chronic and debilitating diseases brought by inactivity and sedentariness. Although essential, they are insufficient as rates of cardiovascular, pulmonary, renal, metabolic and other devastating and lifelong diseases remain on the rise. This systemic failure supports the need for an improved exercise prescription approach that targets the individual. Significant interindividual variability of cardiorespiratory fitness (CRF) responses to exercise are partly explained by biological and methodological factors, and the modulation of exercise volume and intensity seem to be key in improving prescription guidelines. The use of physiological thresholds, such as lactate, ventilation, as well as critical power, have demonstrated excellent results to improve CRF in those struggling to respond to the current homogenous prescription of exercise. However, assessing physiological thresholds requires laboratory resources and expertise and is incompatible for a general population approach. A case must be made that balances the effectiveness of an exercise programme to improve CRF and accessibility of resources. A population-wide approach of exercise prescription guidelines should include free and accessible self-assessed threshold tools, such as rate of perceived exertion, where the homeostatic perturbation induced by exercise reflects physiological thresholds. The present critical review outlines factors for individuals exercise prescription and proposes a new theoretical hierarchal framework to help shape PA guidelines based on accessibility and effectiveness as part of a personalised exercise prescription that targets the individual.
... 6,10 However, randomized controlled trial studies conducted on non-elite subjects lasting 6-10 weeks reported superior responses to polarized especially when compared with pyramidal or threshold intensity distribution. [22][23][24] Furthermore, it has been shown that polarized intensity distribution is a strategy adopted by successful elite athletes during the competition phase. 24 Regarding this aspect, when looking at Figure 1, it is easy to understand that during the racing weeks the intensity distribution tends to be more polarized compared with training weeks in all the three cyclists. ...
... Total days (n) 17 22 29 Days in stage races (n) 17 19 29 Days in one day races (n) 0 3 0 is well-known that high-intensity training leads to rapid adaptions of various tissues and to an increase of aerobic and anaerobic performance indexes in less time compared with other exercise intensities, 25,26 a huge amount of high-intensity volume over several weeks leads to no further adaptations 23,27 and might even lead to distress symptoms. 19,24 This could be one of the reasons contributing to the high-volume pyramidal distribution observed in the training of all the three cyclists. ...
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The aim of this study was to describe individual training strategies in preparation to Giro d’Italia of three world class road cyclists who achieved a top 5 in the general classification. Day‐to‐day power meter training and racing data of three road cyclists (age: 26, 27, 25 years; relative maximum oxygen consumption: 81, 82, 80 mL·min‐1·kg‐1; relative 20‐min record power output: 6.6, 6.6, 6.4 W·kg‐1) of the 22 weeks (December‐May) leading up to the top 5 in Giro d’Italia general classification were retrospectively analyzed. Weekly volume and intensity distribution were considered. Cyclists completed 17, 22, 29 races, trained averagely for 19.7 (7.9), 16.2 (7.0), 14.7 (6.2) hours per week, with a training intensity distribution of 91.3‐6.5‐2.2, 83.6‐10.6‐5.8, 86.7‐8.9‐4.4 in zone 1‐zone 2‐zone 3 before the Giro d’Italia. Two cyclists spent 55 and 39 days at altitude, one did not attend any altitude camp. Cyclists adopted an overall pyramidal intensity distribution with a relevant increase in high‐intensity volume and polarization index in races weeks. Tapering phases seem to be dictated by race schedule instead of literature prescription, with no strength training performed by the three cyclists throughout the entire periodization.
... Variables such as a total training volume, exercise intensity and training intensity distribution (TID) have been commonly analyzed in this kind of researches. TID is defined as the time of the exercise that an athlete spends at the three different zones of training intensity (Stöggl and Sperlich, 2014): zone 1, at or below the first ventilatory threshold (<VT1); zone 2, between first and second ventilatory threshold (VT1-VT2); zone 3, at or beyond the second ventilatory threshold (>VT2) (Skinner and McLellan, 1980). Polarized model, which is based on a high percentage of time at zone 1 and greater percentages at zone 3 than at zone 2, has been presented as the optimal model of TID to enhance the performance of endurance athletes (Seiler and Kjerland, 2006;Neal et al., 2013;Stöggl and Sperlich, 2014). ...
... TID is defined as the time of the exercise that an athlete spends at the three different zones of training intensity (Stöggl and Sperlich, 2014): zone 1, at or below the first ventilatory threshold (<VT1); zone 2, between first and second ventilatory threshold (VT1-VT2); zone 3, at or beyond the second ventilatory threshold (>VT2) (Skinner and McLellan, 1980). Polarized model, which is based on a high percentage of time at zone 1 and greater percentages at zone 3 than at zone 2, has been presented as the optimal model of TID to enhance the performance of endurance athletes (Seiler and Kjerland, 2006;Neal et al., 2013;Stöggl and Sperlich, 2014). However, not all findings on polarized TID point to its superiority (Treff et al., 2017). ...
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There is a growing interest in the scientific literature for reporting top-class endurance athletes training programs. This case study reports on the training program of a world-class male triathlete preparing to compete in the Tokyo 2020 Olympic Games. A macrocycle of 43 weeks is presented. The triathlete performed 14.74 ± 3.01 h of weekly endurance training volume. Training intensity distribution (TID) was 81.93% ± 6.74%/7.16% ± 2.03%/10.91% ± 6.90% for zones 1 (low intensity, VT2) respectively. Pyramidal TID model is observed during the initial stages of the periodization and Polarized TID model is observed at the end of the macrocycle. The triathlete’s peak ⩒O2 was increased by 20% on cycling and by 14% on running. Peak power was increased by 3.13% on cycling test and peak speed by 9.71% on running test. Finally, the triathlete placed 12th in Olympic distance and 10th in Mixed Relay in Tokyo 2020 Olympic games.
... Even though the total training volume of HIIT sessions is generally considerably lower than that of 'High-Volume (low-intensity) Training' without recovery breaks (<65% of HR max, blood lactate levels < 2 mmol/L, training duration > 30 min), comparative studies often proved similar or even better effects on endurance capacity and maximal oxygen uptake capacity when HIIT sessions were used. These studies were conducted with moderately trained children, teenagers and adults [23][24][25][26][27]. Additionally, highly trained endurance athletes, who predominantly use 'High-Volume low-intensity Training', seem to profit when at least regularly implementing HIIT protocols in their training schedule [24]. ...
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High-Intensity Interval Training (HIIT) promises high training effects on aerobic fitness in children, adolescents and adults in a relatively short time. It is therefore well-established in professional training settings. HIIT methods could also be suited to Physical Education (P.E.) lessons and contribute to students’ health and fitness. Since HIIT sessions need little time and equipment, they can be efficiently implemented in P.E. However, there are few studies which have examined non-running-based HIIT programs in the school sport setting. We therefore conducted an intervention study including 121 students aged 11–15 attending a secondary school in Baden Württemberg, Germany. The effects of three different forms of HIIT training varying in duration and content (4 × 4 HIIT, 12 × 1 HIIT, CIRCUIT) were analyzed. The training was conducted twice a week over 6 weeks (10–12 sessions). Strength and endurance performances were determined in pre- and posttests prior to and after the intervention. Results verified that all three HIIT programs led to significant improvements in aerobic fitness (p < 0.001; part ŋ2 = 0.549) with no significant interaction between time x group. In contrast to the running-based HIIT sessions, CIRCUIT training also led to significant improvements in all of the measured strength parameters. Retrospectively, students were asked to assess their perception of the training intervention. The HIIT sessions were well-suited to students who considered themselves as “athletic”. Less athletic students found it difficult to reach the necessary intensity levels. The evaluation showed that endurance training conducted in P.E. lessons needs a variety of different contents in order to sufficiently motivate students. Students perceiving themselves as “unathletic” may need additional support to reach the required intensities of HIIT. Circuit training sessions using whole-body drills can be efficiently implemented in the P.E. setting and contribute to students’ health and fitness.
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During the last nearly 50 years, the blood lactate curve and lactate thresholds (LTs) have become important in the diagnosis of endurance performance. An intense and ongoing debate emerged, which was mainly based on terminology and/or the physiological background of LT concepts. The present review aims at evaluating LTs with regard to their validity in assessing endurance capacity. Additionally, LT concepts shall be integrated within the 'aerobic-anaerobic transition' - a framework which has often been used for performance diagnosis and intensity prescriptions in endurance sports. Usually, graded incremental exercise tests, eliciting an exponential rise in blood lactate concentrations (bLa), are used to arrive at lactate curves. A shift of such lactate curves indicates changes in endurance capacity. This very global approach, however, is hindered by several factors that may influence overall lactate levels. In addition, the exclusive use of the entire curve leads to some uncertainty as to the magnitude of endurance gains, which cannot be precisely estimated. This deficiency might be eliminated by the use of LTs. The aerobic-anaerobic transition may serve as a basis for individually assessing endurance performance as well as for prescribing intensities in endurance training. Additionally, several LT approaches may be integrated in this framework. This model consists of two typical breakpoints that are passed during incremental exercise: the intensity at which bLa begin to rise above baseline levels and the highest intensity at which lactate production and elimination are in equilibrium (maximal lactate steady state [MLSS]). Within this review, LTs are considered valid performance indicators when there are strong linear correlations with (simulated) endurance performance. In addition, a close relationship between LT and MLSS indicates validity regarding the prescription of training intensities. A total of 25 different LT concepts were located. All concepts were divided into three categories. Several authors use fixed bLa during incremental exercise to assess endurance performance (category 1). Other LT concepts aim at detecting the first rise in bLa above baseline levels (category 2). The third category consists of threshold concepts that aim at detecting either the MLSS or a rapid/distinct change in the inclination of the blood lactate curve (category 3). Thirty-two studies evaluated the relationship of LTs with performance in (partly simulated) endurance events. The overwhelming majority of those studies reported strong linear correlations, particularly for running events, suggesting a high percentage of common variance between LT and endurance performance. In addition, there is evidence that some LTs can estimate the MLSS. However, from a practical and statistical point of view it would be of interest to know the variability of individual differences between the respective threshold and the MLSS, which is rarely reported. Although there has been frequent and controversial debate on the LT phenomenon during the last three decades, many scientific studies have dealt with LT concepts, their value in assessing endurance performance or in prescribing exercise intensities in endurance training. The presented framework may help to clarify some aspects of the controversy and may give a rationale for performance diagnosis and training prescription in future research as well as in sports practice.
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The maximal oxygen uptake (VO2max) is considered an important physiological determinant of middle- and long-distance running performance. Little information exists in the scientific literature relating to the most effective training intensity for the enhancement of VO2max in well trained distance runners. Training intensities of 40–50% VO2max can increase VO2max substantially in untrained individuals. The minimum training intensity that elicits the enhancement of VO2max is highly dependent on the initial VO2max, however, and well trained distance runners probably need to train at relative high percentages of VO2max to elicit further increments. Some authors have suggested that training at 70–80% VO2max is optimal. Many studies have investigated the maximum amount of time runners can maintain 95–100% VO2max with the assertion that this intensity is optimal in enhancing VO2max. Presently, there have been no well controlled training studies to support this premise. Myocardial morphological changes that increase maximal stroke volume, increased capillarisation of skeletal muscle, increased myoglobin concentration, and increased oxidative capacity of type II skeletal muscle fibres are adaptations associated with the enhancement of VO2max. The strength of stimuli that elicit adaptation is exercise intensity dependent up to VO2max, indicating that training at or near VO2max may be the most effective intensity to enhance VO2max in well trained distance runners. Lower training intensities may induce similar adaptation because the physiological stress can be imposed for longer periods. This is probably only true for moderately trained runners, however, because all cardiorespiratory adaptations elicited by submaximal training have probably already been elicited in distance runners competing at a relatively high level. Well trained distance runners have been reported to reach a plateau in VO2max enhancement; however, many studies have demonstrated that the VO2max of well trained runners can be enhanced when training protocols known to elicit 95–100% VO2max are included in their training programmes. This supports the premise that high-intensity training may be effective or even necessary for well trained distance runners to enhance VO2max. However, the efficacy of optimised protocols for enhancing VO2max needs to be established with well controlled studies in which they are compared with protocols involving other training intensities typically used by distance runners to enhance VO2max.
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During the last nearly 50 years, the blood lactate curve and lactate thresholds (LTs) have become important in the diagnosis of endurance performance. An intense and ongoing debate emerged, which was mainly based on terminology and/or the physiological background of LT concepts. The present review aims at evaluating LTs with regard to their validity in assessing endurance capacity. Additionally, LT concepts shall be integrated within the ‘aerobic-anaerobic transition’ — a framework which has often been used for performance diagnosis and intensity prescriptions in endurance sports. Usually, graded incremental exercise tests, eliciting an exponential rise in blood lactate concentrations (bLa), are used to arrive at lactate curves. A shift of such lactate curves indicates changes in endurance capacity. This very global approach, however, is hindered by several factors that may influence overall lactate levels. In addition, the exclusive use of the entire curve leads to some uncertainty as to the magnitude of endurance gains, which cannot be precisely estimated. This deficiency might be eliminated by the use of LTs. The aerobic-anaerobic transition may serve as a basis for individually assessing endurance performance as well as for prescribing intensities in endurance training. Additionally, several LT approaches may be integrated in this framework. This model consists of two typical breakpoints that are passed during incremental exercise: the intensity at which bLa begin to rise above baseline levels and the highest intensity at which lactate production and elimination are in equilibrium (maximal lactate steady state [MLSS]). Within this review, LTs are considered valid performance indicators when there are strong linear correlations with (simulated) endurance performance. In addition, a close relationship between LT and MLSS indicates validity regarding the prescription of training intensities. A total of 25 different LT concepts were located. All concepts were divided into three categories. Several authors use fixed bLa during incremental exercise to assess endurance performance (category 1). Other LT concepts aim at detecting the first rise in bLa above baseline levels (category 2). The third category consists of threshold concepts that aim at detecting either the MLSS or a rapid/distinct change in the inclination of the blood lactate curve (category 3). Thirty-two studies evaluated the relationship of LTs with performance in (partly simulated) endurance events. The overwhelming majority of those studies reported strong linear correlations, particularly for running events, suggesting a high percentage of common variance between LT and endurance performance. In addition, there is evidence that some LTs can estimate the MLSS. However, from a practical and statistical point of view it would be of interest to know the variability of individual differences between the respective threshold and the MLSS, which is rarely reported. Although there has been frequent and controversial debate on the LT phenomenon during the last three decades, many scientific studies have dealt with LT concepts, their value in assessing endurance performance or in prescribing exercise intensities in endurance training. The presented framework may help to clarify some aspects of the controversy and may give a rationale for performance diagnosis and training prescription in future research as well as in sports practice.