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Compatibility of Concurrent Aerobic and Strength Training for Skeletal Muscle Size and Function: An Updated Systematic Review and Meta-Analysis

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Background Both athletes and recreational exercisers often perform relatively high volumes of aerobic and strength training simultaneously. However, the compatibility of these two distinct training modes remains unclear. Objective This systematic review assessed the compatibility of concurrent aerobic and strength training compared with strength training alone, in terms of adaptations in muscle function (maximal and explosive strength) and muscle mass. Subgroup analyses were conducted to examine the influence of training modality, training type, exercise order, training frequency, age, and training status. Methods A systematic literature search was conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed/MEDLINE, ISI Web of Science, Embase, CINAHL, SPORTDiscus, and Scopus were systematically searched (12 August 2020, updated on 15 March 2021). Eligibility criteria were as follows. Population: healthy adults of any sex and age; Intervention: supervised concurrent aerobic and strength training for at least 4 weeks; Comparison: identical strength training prescription, with no aerobic training; Outcome: maximal strength, explosive strength, and muscle hypertrophy. Results A total of 43 studies were included. The estimated standardised mean differences (SMD) based on the random-effects model were − 0.06 (95% confidence interval [CI] − 0.20 to 0.09; p = 0.446), − 0.28 (95% CI − 0.48 to − 0.08; p = 0.007), and − 0.01 (95% CI − 0.16 to 0.18; p = 0.919) for maximal strength, explosive strength, and muscle hypertrophy, respectively. Attenuation of explosive strength was more pronounced when concurrent training was performed within the same session ( p = 0.043) than when sessions were separated by at least 3 h ( p > 0.05). No significant effects were found for the other moderators, i.e. type of aerobic training (cycling vs. running), frequency of concurrent training (> 5 vs. < 5 weekly sessions), training status (untrained vs. active), and mean age (< 40 vs. > 40 years). Conclusion Concurrent aerobic and strength training does not compromise muscle hypertrophy and maximal strength development. However, explosive strength gains may be attenuated, especially when aerobic and strength training are performed in the same session. These results appeared to be independent of the type of aerobic training, frequency of concurrent training, training status, and age. PROSPERO: CRD42020203777.
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Vol.:(0123456789)
Sports Medicine (2022) 52:601–612
https://doi.org/10.1007/s40279-021-01587-7
SYSTEMATIC REVIEW
Compatibility ofConcurrent Aerobic andStrength Training
forSkeletal Muscle Size andFunction: AnUpdated Systematic Review
andMeta‑Analysis
MoritzSchumann1 · JoshuaF.Feuerbacher1· MarvinSünkeler1· NilsFreitag1,2· BentR.Rønnestad3· KenjiDoma4·
TommyR.Lundberg5,6
Accepted: 16 October 2021 / Published online: 10 November 2021
© The Author(s) 2021
Abstract
Background Both athletes and recreational exercisers often perform relatively high volumes of aerobic and strength training
simultaneously. However, the compatibility of these two distinct training modes remains unclear.
Objective This systematic review assessed the compatibility of concurrent aerobic and strength training compared with
strength training alone, in terms of adaptations in muscle function (maximal and explosive strength) and muscle mass.
Subgroup analyses were conducted to examine the influence of training modality, training type, exercise order, training
frequency, age, and training status.
Methods A systematic literature search was conducted according to the PRISMA (Preferred Reporting Items for Systematic
Reviews and Meta-Analyses) guidelines. PubMed/MEDLINE, ISI Web of Science, Embase, CINAHL, SPORTDiscus, and
Scopus were systematically searched (12 August 2020, updated on 15 March 2021). Eligibility criteria were as follows.
Population: healthy adults of any sex and age; Intervention: supervised concurrent aerobic and strength training for at least
4weeks; Comparison: identical strength training prescription, with no aerobic training; Outcome: maximal strength, explo-
sive strength, and muscle hypertrophy.
Results A total of 43 studies were included. The estimated standardised mean differences (SMD) based on the random-effects
model were − 0.06 (95% confidence interval [CI] − 0.20 to 0.09; p = 0.446), − 0.28 (95% CI − 0.48 to − 0.08; p = 0.007),
and 0.01 (95% CI − 0.16 to 0.18; p = 0.919) for maximal strength, explosive strength, and muscle hypertrophy, respectively.
Attenuation of explosive strength was more pronounced when concurrent training was performed within the same session
(p = 0.043) than when sessions were separated by at least 3h (p > 0.05). No significant effects were found for the other mod-
erators, i.e. type of aerobic training (cycling vs. running), frequency of concurrent training (> 5 vs. < 5 weekly sessions),
training status (untrained vs. active), and mean age (< 40 vs. > 40years).
Conclusion Concurrent aerobic and strength training does not compromise muscle hypertrophy and maximal strength devel-
opment. However, explosive strength gains may be attenuated, especially when aerobic and strength training are performed
in the same session. These results appeared to be independent of the type of aerobic training, frequency of concurrent train-
ing, training status, and age.
PROSPERO: CRD42020203777.
* Moritz Schumann
m.schumann@dshs-koeln.de
Extended author information available on the last page of the article
1 Introduction
Performing aerobic and strength training concurrently is
an integrative part of physical training aimed at improving
both athletic performance and health. The recommendation
to perform both aerobic and strength training is important
because these activities to some extent induce distinct adap-
tations and health benefits [1, 2]. For example, aerobic train-
ing promotes increased aerobic capacity (i.e. central adap-
tations) and metabolic changes in skeletal muscle, such as
increased mitochondrial density and capillarisation [3]. Con-
versely, regular strength training results in muscle hyper-
trophy and increased strength and power [4] but may also
improve bone mineral density [5]. The role of skeletal mus-
cle in health maintenance has received increased attention
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602 M.Schumann et al.
Key Points
Concurrent aerobic and strength training is recom-
mended to improve physical fitness and health; however,
the compatibility of these two distinct training modes
remains unclear.
In this meta-analysis, we report that concurrent training
does not interfere with adaptations in maximal strength
and muscle hypertrophy, regardless of the type of aero-
bic training (cycling vs. running), frequency of concur-
rent training (> 5 vs. < 5 weekly sessions), training status
(untrained vs. active), mean age (< 40 vs. > 40years),
and training modality (same session vs. same day vs. dif-
ferent day training).
However, concurrent training may attenuate gains in
explosive strength, which is exacerbated when aerobic
and strength training are performed within the same
training session.
To date, few attempts have been made to quantitatively
synthesise the literature concerning concurrent aerobic and
strength training. The first meta-analysis conducted a decade
ago by Wilson etal. [14] showed that peak power was attenu-
ated with concurrent training compared with strength train-
ing alone, whereas the development of muscle hypertrophy
and maximal strength were not compromised. A more recent
meta-analysis aimed to compare the effect of concurrent aero-
bic and strength training with strength training alone on the
development of maximal strength in untrained, moderately
trained, and trained individuals [15]. The results suggested
that concurrent training may have a negative effect on lower
body strength development in trained individuals but not in
moderately trained or untrained individuals. While this study
updated information on the effect of training status on maxi-
mal strength development, several other important outcome
variables related to muscle mass and function have not been
examined in a meta-analysis since 2012. Therefore, the aim of
the current study was to systematically assess the compatibility
of concurrent aerobic and strength training on adaptations in
maximal strength, explosive strength, and muscle hypertrophy
by means of pooled analyses. Subgroup analysis was also con-
ducted to examine the influence of aerobic training type, train-
ing modality, exercise order, concurrent training frequency,
age, and training status. An updated literature synthesis on this
topic is relevant to physicians, physiotherapists, exercise sci-
entists, and sports practitioners designing programmes aimed
at developing both aerobic and strength qualities for health
purposes, rehabilitation, and/or fitness performance.
2 Methods
2.1 Systematic Literature Search
A systematic literature search was conducted according
to the PRISMA (Preferred Reporting Items for System-
atic Reviews and Meta-Analyses) guidelines and was reg-
istered with PROSPERO (the International Database of
Prospectively Registered Systematic Reviews in Health
and Social Care; CRD42020203777). The PubMed/MED-
LINE, ISI Web of Science, Embase, CINAHL, SPORTDis-
cus, and Scopus databases were systematically searched
using a search string specifically adapted to the search
requirements of each database (TableS1 in the electronic
supplementary material [ESM]).
The search was conducted on 12 August 2020 and
updated on 15 March 2021. The literature search process
was performed independently by two researchers and
included saving the online search, removing duplicates,
and screening titles, abstracts, and full texts. Potential
conflicts were resolved by consulting with a third author.
In addition, a grey literature search was performed by
in the last decade, with muscle tissue being understood as
a secretory organ that releases several hundred myokines
related to the function of other organs, such as the brain, adi-
pose tissue, bone, liver, gut, pancreas, vascular bed, and skin
[6]. In addition, the role of muscle power has recently been
highlighted as being strongly associated with a lower risk of
fall-related injuries in older adults [7, 8], further underlining
the importance of both muscle mass and muscle function as
indicators of physical health and independence in daily life.
Aside from the health perspective, many sports require
the athlete to simultaneously incorporate divergent training
modalities, including aerobic and strength training, into their
training regimen. Considering that both athletes and recrea-
tional exercisers often perform relatively high volumes (and/
or frequencies) of aerobic training alongside resistance-type
training, it is pertinent to revisit the compatibility of aerobic
and strength training. Aerobic training has been shown to
interfere with the development of maximal strength when the
overall training volume is high [9]. In contrast, no interfer-
ence in maximal strength was observed when training volume
was reduced to two weekly aerobic and strength training ses-
sions, respectively [1012]. Importantly, however, even low
volumes of concurrent aerobic training have been shown to
decrease gains in rapid force production [10, 13], which could
translate into reduced muscle power-related benefits. Identi-
fying additional moderators hypothesised in the literature to
potentially influence neuromuscular adaptations to concurrent
aerobic and strength training (such as type of aerobic training,
concurrent training modality, age, and training status) could
further aid in fine-tuning exercise guidelines for health and/or
fitness performance.
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603
Compatibility of Concurrent Aerobic and Strength Training
screening Google Scholar and the reference lists of previ-
ously identified eligible full texts. Figure1 is a flowchart
of the search process and study selection.
2.2 Eligibility Criteria
Inclusion criteria were defined based on the PICO (Popu-
lation, Intervention, Control and Outcomes) criteria [16].
The population included healthy adults with no restrictions
in terms of sex and age. The intervention had to consist
of supervised combined aerobic and strength training for
at least 4weeks. As a comparator, eligible studies had to
include a group receiving the identical strength-training
prescription with no aerobic training. Outcomes of interest
included maximal strength, explosive strength, and mus-
cle hypertrophy. The exercise tests had to be specific to the
training performed. For maximal strength, both isometric
and isoinertial measurements were accepted. For explo-
sive strength, any form of jump test, isometric rate of force
development (RFD), or dynamic power measurements
were considered eligible. For muscle hypertrophy, objec-
tive measurements of whole-muscle cross-sectional area or
muscle thickness (e.g. ultrasound, computed tomography
[CT] or magnetic resonance imaging [MRI]) were required.
In addition, segmental lean mass as determined by dual-
energy X-ray absorptiometry (DXA) was accepted if values
were reported separately for segments that were engaged in
training.
Fig. 1 Flowchart of the search process and the study selection
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604 M.Schumann et al.
Exclusion criteria included language other than English
or German, abstracts and dissertations, cross-sectional stud-
ies assessing only acute exercise responses, and observa-
tional studies.
2.3 Data Extraction
Data extraction was performed independently by two
authors. The following data were extracted from each
included study: (1) general characteristics (e.g. author[s],
year of publication and aim of the study), (2) participant
information (e.g. sample size, training status, and age), (3)
intervention data for all groups (e.g. intervention duration,
type of intervention), and (4) specific outcomes (e.g. meas-
ures of maximal and explosive strength and hypertrophy).
If the mean and standard deviation of each group were not
specified, we requested baseline and post-intervention data
from the authors of the primary studies. If data were pre-
sented within a graph and no additional data were provided
upon request, mean and standard deviation were extracted
using WebPlotDigitizer version 4.4 (Pacifica, CA, USA)
[17].
2.4 Data Synthesis andAnalyses
Standardised mean differences (SMD) were calculated, and
an inverse variance-weighted random-effects model was
fitted to the effect sizes (ES). Additionally, log variability
ratios were calculated, and an inverse variance-weighted
random-effects model was fitted to the ES. Meta-analyses
were performed using R (3.6.2), RStudio (1.2.5033), and
the metafor package (version 2.4.0) [18]. ES were calculated
for pre-test post-test control group designs using the previ-
ously recommended raw score standardisation [19, 20]. Fur-
thermore, the exact sampling variance of ES was computed
according to recommendations [19].
Heterogeneity (i.e. τ2) was estimated using the restricted
maximum-likelihood estimator [21]. To complete the hetero-
geneity analyses, the Q-test for heterogeneity [22] and the
I2 statistic [23] were also calculated. Studentised residuals
and Cook’s distances were examined to assess whether stud-
ies might be outliers and/or overly influential [24]. Studies
with a studentised residual greater than the 100 × (1–0.05/
(2 × k))th percentile of a standard normal distribution were
declared potential outliers (i.e. using a Bonferroni correction
with two-sided α = 0.05 for k studies included in the meta-
analyses). Studies with a Cook’s distance larger than the
median plus six times the interquartile range of the Cook’s
distances were considered overly influential. If a study was
identified as a potential outlier or overly influential, a sensi-
tivity analysis was performed. A trim-and-fill-contour funnel
plot was created to estimate the number of studies that may
be missing from the meta-analysis (Fig. S1 in the ESM). We
used the rank correlation test [25] and regression test [26]
using the standard error of observed outcomes as predictor
to check for funnel plot asymmetry.
ES from studies with more than two intervention or con-
trol groups were combined according to the Cochrane hand-
book recommendations [27], except for subgroup analysis
when different interventions from individual studies were
included in separate subgroups. If there were multiple meas-
urements for the same outcome, only one measurement was
included in the analysis, based on the following hierarchies:
Maximal strength: (1) dynamic bilateral leg press, (2)
squat, (3) unilateral isometric torque (knee extension),
and (4) bilateral dynamic knee extension.
Explosive strength: (1) jump height and (2) other meas-
ures of rapid force production as well as squat jump
power and leg press power at 50% of maximal strength.
Muscle hypertrophy: (1) whole-muscle cross-sectional
area of the quadriceps femoris muscles (i.e. panoramic
ultrasound, CT, MRI), (2) muscle thickness of the vastus
lateralis, and (3) segmental DXA of the lower extremi-
ties.
Thus, each study was included in the final analyses with
only one parameter to avoid inflating the weighting of indi-
vidual studies.
Because of a lack of systematic reporting, subgroup
analyses were only performed for aerobic training type (i.e.
cycling vs. running), concurrent training frequency (i.e.
low frequency of 4.1 ± 0.3 vs. high frequency of 6.1 ± 1.6
weekly sessions, based on 2.0 ± 0.3 vs. 3.1 ± 0.6 weekly
sessions in the comparison training group), training status
(i.e. untrained vs. active), mean age of the study population
(18–40 vs. > 40years), and training modality (i.e. concur-
rent training on different days vs. on the same day vs. in the
same session). For studies comparing concurrent training in
the same session, when a sufficient number of studies were
available, training order was also compared (i.e. aerobic
before strength exercise vs. strength before aerobic exercise).
Studies were divided into subgroups based on the descrip-
tion in the manuscript. This was particularly true for training
status, with studies classified as ‘untrained’ if participants
were clearly described as ‘sedentary’, ‘previously untrained’,
or ‘inactive’. Conversely, all other studies were classified as
‘active’ (i.e. ‘recreationally active’, ‘trained’, ‘well-trained’,
etc.). Specific rationale for the exclusion of individual stud-
ies can be found in TableS2 in the ESM.
2.5 Assessment ofMethodological Quality
Risk of bias for the included studies was assessed indepen-
dently by two reviewers using the Physiotherapy Evidence
Database (PEDro) scale. The PEDro scale has previously
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605
Compatibility of Concurrent Aerobic and Strength Training
been assessed as a valid measure of the methodological
quality of randomised trials [28]. Studies scoring > 6 were
classified as ‘high quality’, studies scoring 4–5 were classi-
fied as ‘medium quality’, and studies scoring < 4 were clas-
sified as ‘low quality’. The following sources of bias were
considered: selection (sequence generation and allocation
concealment), performance (blinding of participants/per-
sonnel), detection (blinding outcome assessors), attrition
(incomplete outcome data), reporting (selective reporting),
and other potential biases (e.g. recall bias). The risk-of-bias
scores for the included studies are presented in TableS3
in the ESM. The mean score for scale criteria 2–11 of the
PEDro scale was 4.3/10, i.e., medium quality.
3 Results
3.1 Study Characteristics
The database search identified 15,729 potentially eligible
articles. After further screening and eligibility assessment, a
total of 43 studies were included in the final analysis (Fig.1).
The characteristics of the studies, participants, and training
interventions are summarised in TableS1 in the ESM. The
meta-analysis included a total of 1090 participants, of whom
590 performed supervised combined aerobic and strength
training and 500 performed strength training alone. In the
included studies, cycling was the most common type of aero-
bic training (24 studies), followed by running (16 studies). In
addition, the combination of running and cycling [9], rowing
[29], and continuous repeated leg extensions [30] were each
evaluated by one study.
3.2 Maximal Strength
The final analysis included 37 studies [911, 2962], with
525 participants performing combined aerobic and strength
training and 442 participants performing strength training
alone. The observed SMD ranged from 1.37 to 1.99, and
the estimated average SMD based on the random-effects
model was 0.06 (95% confidence interval [CI] 0.20 to
0.09; p = 0.446), indicating no interference effect of aerobic
training (Fig.2). The estimated log variability ratio based
on the random-effects model was 0.05 (95% CI 0.05 to
0.15; p = 0.311). According to the Q-test, there was no sig-
nificant heterogeneity in the true outcomes (Q(36) = 32.591,
p = 0.632,
̂𝜏 2
= 0.000, I2 = 0.00%). An examination of the
studentised residuals showed no evidence of outliers within
this model, and none of the studies were overly influential.
Subgroup analyses showed no statistical differences
(p > 0.05) (Figs. S2–S7 in the ESM).
3.3 Explosive Strength
The final analyses included 18 studies [11, 31, 34, 38, 39,
42, 49, 5154, 56, 5860, 6264], with 270 participants per-
forming combined aerobic and strength training and 208 per-
forming strength training alone. The observed SMD ranged
from 1.60 to 0.22, and the estimated mean SMD based
on the random-effects model was 0.28 (95% CI 0.48
to − 0.08; p = 0.007), indicating an interference effect of
aerobic training (Fig.3). The estimated log variability ratio
based on the random-effects model was 0.04 (95% CI 0.09
to 0.18; p = 0.533). According to the Q test, there was no sig-
nificant heterogeneity in the true outcomes (Q(17) = 26.675,
p = 0.068,
̂𝜏 2
= 0.068, I2 = 35.81%). The studentised residuals
highlighted Mikkola etal. [31] as a potential outlier that may
have been overly influential. Sensitivity analyses revealed
that excluding this study reduced the amount of observed
heterogeneity to I2 = 0.00% (Q(16) = 13.860, p = 0.061,
̂𝜏 2
=
0.061).
Subgroup analyses showed no statistical differences
(p > 0.05) (Figs. S8–S11 in the ESM). When studies were
grouped by type of aerobic training, the SMD was signifi-
cantly in favour of strength training for cycling − 0.44 (95%
CI − 0.86 to − 0.01; p = 0.043) but not for running (Fig. S8
in the ESM). However, after the overly influential study by
Mikkola etal. [31] was removed, this effect was no longer
observed (SMD 0.27; 95% CI 0.58 to 0.04; p = 0.086).
A similar effect was also seen for low concurrent training
frequency, with an initial SMD of 0.45 (95% CI 0.87
to − 0.02; p = 0.039) in favour of the strength training group
(Fig. S9 in the ESM). After the study by Mikkola etal. [31]
was removed, this reduced to − 0.25 (95% CI 0.50 to 0.01;
p = 0.059). Conversely, when studies were grouped by train-
ing modality, a significant interference effect was observed
for studies that performed concurrent training within the
same session (≤ 20min between aerobic and strength train-
ing; SMD − 0.31; 95% CI − 0.62 to − 0.01; p = 0.043) but not
when concurrent training was separated by at least 3h (Fig.
S11 in the ESM).
3.4 Muscle Hypertrophy
The final analyses included 15 studies [10, 11, 33, 4547,
49, 54, 55, 59, 62, 6568], with 201 participants perform-
ing combined aerobic and strength training and 188 per-
forming strength training alone. The observed SMD in
each trial ranged from 0.67 to 0.28, and the estimated
mean SMD based on the random-effects model was 0.01
(95% CI 0.16 to 0.18; p = 0.919), indicating no interfer-
ence effect of aerobic training (Fig.4). The estimated log
variability ratio based on the random-effects model was 0.04
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606 M.Schumann et al.
(95% CI 0.11 to 0.19; p = 0.567). According to the Q test,
there was no significant heterogeneity in the true outcomes
(Q(14) = 4.687; p = 0.990,
̂𝜏 2
= 0.000, I2 = 0.00%). An exami-
nation of the studentised residuals showed no potential out-
lier within this model. According to the Cook’s distances,
no study could be considered overly influential. Subgroup
analyses revealed no statistical differences (p > 0.05) (Figs.
S12–S14 in the ESM).
4 Discussion
The aim of this study was to provide a systematic and evi-
dence-based appraisal of whether aerobic training interfered
with adaptations to strength training in terms of muscle func-
tion (maximal and explosive strength) and whole-muscle
hypertrophy. In addition, the impact of important mediating
covariates such as type of aerobic training, training modal-
ity, exercise order, concurrent training frequency, age, and
training status were assessed. The main finding was that con-
current aerobic and strength training did not interfere with
the development of maximal strength and muscle hypertro-
phy compared with strength training alone. However, the
development of explosive strength was negatively affected
by concurrent training. Our subgroup analysis showed that
this negative effect was exacerbated when concurrent train-
ing was performed within the same session, compared with
when aerobic and strength training were separated by at least
3h. No significant effects were found for other moderators,
such as type of aerobic training (cycling vs. running), fre-
quency of concurrent training (> 5 vs. < 5 weekly sessions),
training status (untrained vs. active), and mean age (< 40
vs. > 40years).
An important goal of this meta-analysis was to provide
evidence that can be translated into optimised and fine-tuned
exercise recommendations for fitness and health purposes.
Although our results are generally consistent with those
reported by Wilson etal. [14] a decade ago, these authors
Fig. 2 Forest plot of studies comparing differences in maximal strength. CI confidence interval, RE random effects, SMD standardised mean dif-
ference
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607
Compatibility of Concurrent Aerobic and Strength Training
considered anaerobic power measures such as Wingate per-
formance as indicators of explosive strength. Since we inten-
tionally included only direct measures of explosive strength
(i.e. jump performance, isometric RFD, and dynamic leg
press power), our findings reinforce that concurrent aerobic
and strength training can compromise strength qualities that
require rapid neural activation.
The mechanism for compromised explosive but not maxi-
mal strength is interesting and requires further research. Our
findings are supported by an early study showing that muscle
hypertrophy and maximal strength were unaffected by con-
current training, whereas RFD was blunted, likely because
of interference with rapid voluntary neural activation [10].
More specifically, although the maximal neural activation
was not compromised, the increase in the integrated elec-
tromyographic signal during the first 500ms was attenuated
in the group performing both aerobic and strength training.
Since the rate of recruitment and maximal discharge of
motor neurons largely determines the maximal RFD [69], it
appears that the rate of recruitment and discharge of motor
units is particularly sensitive to the interference effect of
aerobic training. It could be speculated that residual fatigue
induced by aerobic training affects the corticospinal inputs
received by the motor neurons before force is generated,
which would subsequently compromise rapid force genera-
tion. The latter could potentially reduce the quality but not
the quantity of strength training sessions performed concur-
rently with aerobic training, thereby potentially reducing the
development of explosive strength but not maximal strength
or muscle hypertrophy. This, in turn, could have implications
for programme design, as it is apparent that concurrently
improving both cardiorespiratory fitness and rapid force pro-
duction through rather generic exercise recommendations
presents a physiological challenge.
Consistent with this, our subgroup analysis indicated that
the magnitude of interference in explosive strength devel-
opment was dependent on the programming of the exer-
cise sessions, with significant interference observed when
aerobic and strength training were performed within the
same training session. Previous studies have indicated that
Fig. 3 Forest plot of studies comparing differences in explosive strength. CI confidence interval, RE random effects, SMD standardised mean dif-
ference
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608 M.Schumann et al.
neuromuscular interference may be more pronounced when
strength training is immediately preceded by aerobic train-
ing in both young [70] and older individuals [71]. However,
our pooled analysis did not provide evidence for an order-
specific effect but rather highlights that combining aerobic
and strength training in close proximity attenuates adapta-
tions in explosive strength regardless of exercise order. Other
studies have suggested that, apart from limitations in rapid
neural drive [10], adaptations in pennation angle and fascicle
length [54] or patella tendon cross-sectional area [72] could
be possible mechanistic explanations for these findings.
The moderators, including frequency of concurrent
training, type of training, age, and training status, did
not significantly influence adaptations in maximal and
explosive strength, nor muscle hypertrophy. Similarly, no
significant effects were observed in our analysis of log
variability, indicating no within-group differences in vari-
ability after concurrent training compared with strength
training alone. Our results differ from the recently pub-
lished meta-analysis that focused exclusively on the effect
of training status on maximal strength during concurrent
training [15]. In this study, the one-repetition maximum
for leg press and squat was negatively affected by concur-
rent training in trained individuals but not in moderately
trained or untrained individuals compared with strength
training alone. Moreover, their subgroup analysis sug-
gested that the negative effect observed in trained indi-
viduals occurred only when aerobic and strength training
were performed within the same training session. How-
ever, given the lack of consistent reporting, we chose not
to divide the active participants into moderately or well-
trained athletes, which may have diluted potential signifi-
cant effects. Furthermore, albeit the exact calculations of
Petré etal. [15] were not published, their analysis appears
to differ from our approach. Apart from the smaller num-
ber of studies included (27 vs. 37 studies), studies consist-
ing of multiple intervention groups with only one com-
parator were included multiple times in the same analysis,
potentially inflating power [73]. Although the results did
not reach statistical significance, our subgroup analysis for
Fig. 4 Forest plot of studies comparing differences in muscle hypertrophy. CI confidence interval, CSA cross-sectional area, DXA dual energy
X-ray absorptiometry, RE random effects, SMD standardised mean difference
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609
Compatibility of Concurrent Aerobic and Strength Training
training status showed a similar direction for the SMD in
trained versus untrained participants as reported by Petré
etal. [15].
In other concurrent training research, numerous stud-
ies have focused on the possible interference mechanisms
related to muscle hypertrophy [74]. The rationale for these
studies stems from rodent and cellular models indicating
possible inhibition of mechanistic target of rapamycin sig-
nalling through activation of AMP-activated protein kinase
(AMPK) following aerobic exercise [7578]. However,
subsequent human studies failed to confirm these find-
ings when examining physiological mechanisms such as
metabolic stress and AMPK activation [67, 79] or protein
synthesis [80] following concurrent exercise. Based on our
systematic review, this is not surprising as none of the
identified studies reported a significant interference effect
on muscle hypertrophy. Although Wilson etal. [14] con-
cluded from their subgroup analysis that there was a nega-
tive relationship between the ES for hypertrophy and both
aerobic training frequency and duration, our results do
not confirm these observations. There are several possible
explanations for this inconsistency, apart from the obvi-
ous fact that our analysis was conducted almost a decade
later and therefore included more studies. First, the inclu-
sion criteria differed since Wilson etal. [14] included fibre
hypertrophy as an outcome parameter and also included
studies without a strength training control group. Second,
we conducted our analysis based on an inverse variance-
weighted random-effects model in a pre-test post-test
control group design [18], whereas Wilson etal. [14] esti-
mated the ES of each individual group, resulting in a total
of 72 ES for muscle hypertrophy. The reported aerobic
training duration and intensity were then correlated with
ES, potentially leading to significant positive correlations.
Although the current meta-analysis provides updated
and novel information, some limitations should be acknowl-
edged. First, it should be noted that the majority of the
included studies were only classified as of medium quality
(mean PEDro score 4.3 ± 0.9), and seven studies were of low
quality. However, it is important to note that it may not be
possible to achieve all items related to blinding in exercise
trials. In addition, poor reporting quality may have biased the
outcome of this ranking. Thus, more importance can possi-
bly be given to the studentised residuals and the Cook’s dis-
tance [24]. Furthermore, meta-analyses are generally limited
to the information provided within the included individual
studies. Even though we contacted authors to request addi-
tional information, the response rate was low. Therefore, to
avoid speculation, we decided to include only clearly defined
moderators. For example, aerobic exercise intensity was
not included because the included studies did not provide
consistent information. However, it is possible that aerobic
exercise intensity may impact on the compatibility of aerobic
and strength training. A meta-analysis examining the effects
of concurrent high-intensity interval training (HIIT) and
strength training reported that lower body strength develop-
ment was compromised by concurrent training compared
with strength training alone, even though the authors noted
that a possible negative effect on lower body strength may
be ameliorated by the inclusion of running-based HIIT and
longer intermodal rest periods [81]. This was further sup-
ported by a recent narrative review reporting that HIIT could
minimise the risk of neuromuscular interference and that this
effect was even more pronounced when HIIT was replaced
with sprint-interval training [82]. However, it should be
acknowledged that previous research appears to indicate that
the overall health benefits of concurrent training, apart from
muscle function and size, appear to be greater than those
obtained with isolated training of either aerobic or strength
training [83, 84] and that the overall risk of interference
effects is rather low. Therefore, most individuals, includ-
ing recreational athletes, can enjoy complementary benefits
from incorporating both aerobic and strength training into
their training programme.
5 Conclusion
This updated meta-analysis shows that concurrent aerobic
and strength training does not interfere with the develop-
ment of maximal strength and muscle hypertrophy compared
with strength training alone. This appears to be independent
of the type of aerobic training (cycling vs. running), fre-
quency of concurrent training (> 5 vs. < 5 weekly sessions),
training status (untrained vs. active), and mean age (< 40
vs. > 40years). However, the evidence of reduced develop-
ment of explosive strength with concurrent training, particu-
larly when aerobic and strength training are performed in
the same session, suggests that practitioners who prioritize
explosive strength may benefit from separating aerobic and
strength training to achieve optimal adaptations.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s40279- 021- 01587-7.
Acknowledgements The authors thank Dr. James Steele (Solent Uni-
versity, UK) for his valuable input concerning the data analysis.
Declarations
Funding Open Access funding enabled and organized by Projekt
DEAL. No funding sources were used in the preparation of this article.
Conflict of interest Moritz Schumann, Joshua F. Feuerbacher, Marvin
Sünkeler, Nils Freitag, Bent R. Rønnestad, Kenji Doma and Tommy
Lundberg have no conflicts of interest relevant to the content of this
review.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
610 M.Schumann et al.
Availability of data and material Not applicable.
Code availability The code will be available upon reasonable request.
Author contribution Design of the study: MS, JFF, MSü, NF, KD,
BRR, TL. Literature search: MS, JFF, MSü. Data screening and extrac-
tion: JFF, MSü. Statistical analyses: MS, JFF, MSü, NF, TL. Manu-
script preparation and editing: MS, JFF, TL. All authors have read and
agreed to the submitted version.
Ethics approval Not applicable.
Consent to participate Not applicable.
Consent for publication Not applicable.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
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otherwise in a credit line to the material. If material is not included in
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Authors and Aliations
MoritzSchumann1 · JoshuaF.Feuerbacher1· MarvinSünkeler1· NilsFreitag1,2· BentR.Rønnestad3· KenjiDoma4·
TommyR.Lundberg5,6
1 Department ofMolecular andCellular Sports Medicine,
Institute ofCardiovascular Research andSports Medicine,
German Sport University, Am Sportpark Müngersdorf 6,
50933Cologne, Germany
2 Olympic Training Centre Berlin, Berlin, Germany
3 Section forHealth andExercise Physiology, Department
ofPublic Health andSport Sciences, Inland Norway
University ofApplied Sciences, Elverum, Norway
4 Sport andExercise Science, College ofHealthcare Sciences,
James Cook University, Townsville, QLD, Australia
5 Division ofClinical Physiology, Department ofLaboratory
Medicine, Karolinska Institutet, Stockholm, Sweden
6 Unit ofClinical Physiology, Karolinska University Hospital,
Stockholm, Sweden
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
1.
2.
3.
4.
5.
6.
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... This is to some extent surprising. Based on our previous meta-analysis [4], we hypothesized that an interference effect and thus an attenuated development in explosive strength would be apparent when aerobic and strength training are performed within the same muscle group. However, it is noteworthy that in this analysis, despite effect sizes indicating attenuated improvements [4], actual significant differences between strength training alone and combined aerobic and strength training were demonstrated in only six [2,3,9,[29][30][31] out of the 18 included studies. ...
... Based on our previous meta-analysis [4], we hypothesized that an interference effect and thus an attenuated development in explosive strength would be apparent when aerobic and strength training are performed within the same muscle group. However, it is noteworthy that in this analysis, despite effect sizes indicating attenuated improvements [4], actual significant differences between strength training alone and combined aerobic and strength training were demonstrated in only six [2,3,9,[29][30][31] out of the 18 included studies. Thus, the absence of an interference effect in our research, particularly when comparing between-group differences, aligns with previous findings, which also reported no interference effect on explosive strength [32,33]. ...
... For instance, research has indicated that longer aerobic sessions often lead to interference [5], while in fact, shorter HIIT intervals have shown interference in explosive strength as well [2,3]. Moreover, it has been argued that the potential for interference may be more pronounced when aerobic and strength training are conducted within the same session [4]. However, some studies have also shown that training in aerobic endurance and strength on different days leads to interference in explosive strength [1], while in the present study same-session concurrent aerobic and strength training did not lead to blunted explosive strength adaptations. ...
Article
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Combining aerobic and strength training may attenuate neuromuscular adaptations, particularly when both target the same muscle group. This study assessed whether separating the training modalities by muscle groups mitigates this interference. Ninety‐six participants (56 males and 40 females) completed a 12‐week intervention, divided into three groups: (1) LHLS (lower‐body high‐intensity interval (HIIT) and strength training), (2) LHUS (lower‐body HIIT and upper‐body strength training), and (3) LSUS (lower‐ and upper‐body strength training). Maximal (1RM) and explosive strength were assessed using load–velocity profiling, with mean propulsive velocity (MPV) at 30%, 50%, 70%, and 90% of 1RM as a measure of explosive strength. Muscle cross‐sectional area (CSA) of the M. vastus lateralis and M. pectoralis major was measured using panoramic ultrasound. Lower‐body adaptations were compared between LHLS and LSUS, and upper‐body adaptations were compared between LHUS and LSUS. MPV at 70% and 90% of 1RM for the squat (LHLS and LSUS) and bench press (LHUS and LSUS) showed improvements (p < 0.050), with no significant between‐group differences. Squat 1RM improved in both LHLS and LSUS, and bench press 1RM increased in both LHUS and LSUS (all p < 0.001). M. vastus lateralis CSA increased in LHLS (p = 0.029) but not in LSUS, whereas M. pectoralis major CSA increased in both LHUS and LSUS (p < 0.001), with no between‐group differences. No sex‐based differences were observed. Concurrent aerobic and strength training does not impair explosive strength, maximal strength, or muscle hypertrophy, regardless of whether the same or separate muscle groups are targeted.
... However, previous meta-analyses, predominantly based on adult populations, have suggested that CT might introduce confounding effects on fitness enhancements compared to isolated ET or RT [14][15][16][17]. The applicability of these findings to younger populations is questionable due to significant differences in anthropometrics, physiology, and biomechanics [18]. ...
... The training status of subjects notably contributes to the phenomenon known as the "interference effect." Multiple metaanalyses leveraging adult data indicate that the interference effect predominantly emerges in well-trained subjects [27,39], although certain studies report no significant influence of training status [16]. This discrepancy likely stems from the ambiguous classification of training status employed across studies. ...
... Apprehensions regarding the influence of concurrent training (CT) on muscular strength can be historically situated in the context of 1980, marked by Hickson's seminal study, which reported an antagonistic effect of combined strength and endurance training on peak muscular force, culminating in attenuated strength gains [23]. Recent meta-analytical evidence drawn from adult cohorts posits that the inter-modality intervals [16,61] and sequencing of ET and RT [62] play a causative role in modulating muscular strength and power. For instance, an inter-modality interval of less than 6 h between ET and RT sessions has been demonstrated to significantly impinge upon the development of muscular strength and power [63]. ...
Article
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The decline in fitness levels among children and adolescents underscores the urgent need for effective exercise interventions. Aerobic endurance training (ET) and resistance training (RT) are vital for physical development in this demographic. This study employs multivariate and network meta‐analysis (NMA) to assess the impact of concurrent training (CT), which integrates both ET and RT, on youth physical fitness. The objective is to identify the distinct advantages of CT over either ET or RT alone, emphasizing demographic and training‐specific variables. A systematic literature review of publications from 1980 onward was conducted through ISI Web of Science, PubMed/MEDLINE, and SPORTDiscus databases, adhering to the PICOS criteria for study selection. Data were analyzed using univariate, multivariate, and network meta‐analyses in Stata 17.0, focusing on cardiorespiratory fitness and muscular strength. The methodological quality and risk of bias were evaluated using the PEDro scale and Egger's test, along with sensitivity analyses and meta‐regression to explore heterogeneity and publication bias. This analysis included 36 studies with 2658 participants (mean age: 14.32 ± 2.29 years) from an initial 11 074 publications, indicating low bias risk (PEDro scores ≥ 6). Univariate meta‐analysis showed no significant differences in maximal oxygen uptake (VO2max) between CT and ET (standardized mean difference [SMD] = 0.01; 95% confidence interval [CI]: −0.23 to 0.25; p = 0.93). In contrast, CT significantly improved countermovement jump (CMJ) compared to RT alone (SMD = 0.19; 95% CI: 0.01–0.36; p = 0.04). Multivariate analysis confirmed notable enhancements in endurance and explosiveness for CT compared to ET or RT. NMA indicated significant improvements in lower limb strength, CMJ, and VO2max across interventions compared to controls, with the consecutive resistance training followed by ET (CRE) group yielding the most significant CMJ improvement (SMD = 0.27; 95% CI: 0.07–0.47). Isolated RT showed the highest lower limb strength improvement (SUCRA score 80.1%), while CRE excelled in CMJ advancements (SUCRA score 93.4%), and the CRED group (alternating ET and RT) led in VO2max improvements (SUCRA score 81.6%). Furthermore, high‐intensity interval training (HIIT) significantly enhanced VO2max compared to team sports. This meta‐analysis emphasizes the effectiveness of CT in improving muscle power and VO2max in children and adolescents, surpassing isolated ET or RT, and advocates for integrating ET and RT to optimize physical performance. Future research should explore the mechanisms underlying these enhancements. Trial Registration: PROSPERO registration number CRD42022368452
... In contrast to this view, however, Wilson et al. (117) concluded in a meta-analysis investigating concurrent training studies that power is the major variable affected by concurrent training. The conclusions in an updated meta-analysis (96) published recently concur with the findings of Wilson et al. (117), suggesting that "combining aerobic and strength training in close proximity attenuates adaptations in explosive strength regardless of exercise order." The attenuation of "explosive" strength or more accurately, rapid force production, inseason is problematic because most team sports require rapid force production for efficient acceleration/deceleration type actions, and therefore, there is a need to develop this quality throughout the season. ...
... The attenuation of "explosive" strength or more accurately, rapid force production, inseason is problematic because most team sports require rapid force production for efficient acceleration/deceleration type actions, and therefore, there is a need to develop this quality throughout the season. It has also been concluded that there is little to no interference effect on maximal strength (96). When considering implementing a microdosing strategy, if an athlete requires additional long-duration aerobic stimuli, it is likely to be more beneficial to schedule those on days where there is a greater strength training stimulus. ...
... Lifestyle modifications are vital for managing the progression of various chronic illnesses, including CKD, hypertension, cardiovascular disease, and diabetes mellitus [10]. Aerobic or functional exercise [11] and resistance exercise improved mental health and urea clearance index scores [12]. Physical activity lowers blood pressure and low-density lipoprotein levels by improving cardiac output, stroke volume, heart rate variability, and peak oxygen uptake capacity [13], thereby increasing the body's sensitivity to insulin and reducing blood sugar levels [14] to weaken the symptoms of CKD. ...
... For instance, success in middle-and long-distance running is primarily influenced by factors associated with VO2Max, such as its associated velocity (Noakes;Myburgh;Schall, 1990) and the highest percentage of VO2 sustained at a stable level (Allen et al., 1985). Conversely, factors associated with muscular performance also appear to be strongly related to middle-and long-distance running performance (Blagrove;Howatson;Hayes, 2018;Haugen et al., 2022;Schumann et al., 2022;Smith, 2003). Thus, we can infer that both specific strategies that enable cardiorespiratory evolution and non-specific strategies Considering these observations and the fact that the KBS has been studied alongside a specific running program (Kartages et al., 2019), although with a limited focus on short-duration exercises (sprints), there is a need to understand whether KBS performance could explain endurance performance, as well as the primary predictor of such a sport, the velocity associated with VO2Max or peak velocity (VPeak). ...
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Determinar se o desempenho do Kettlebell Swing (KBS) é preditor da corrida de 5 quilometros (5KM) e da potência aeróbia máxima (VPico) em praticantes recreacionais de corrida. Secundariamente, analisaremos a relação entre a VPico e o desempenho de 5KM. 22 universitários treinados recreativamente para corrida compareceram a 4 visitas. A primeira visita consistiu na caracterização da amostra por bioimpedância e familiarização para o teste de desempenho de 100KBS. A segunda visita consistiu em um teste de exercício incremental máximo em esteira. Na terceira visita foi realizado o teste de desempenho de corrida contrarrelógio de 5KM em esteira (all out). Por fim, na quarta visita, foi realizado o procedimento de repetições de 100KBS em 5 min. O teste de desempenho de corrida de 5KM apresentou tempo médio de 24,9 ± 2,8 min. O melhor modelo preditor foi representado pelas múltiplas variáveis (KBS, idade e massa corporal), apresentando significativa resposta preditiva da performance de 5KM [F(1,20) = 6,179; p = 0,004; R2 = 0,507]. Similarmente, o modelo preditivo utilizando KBS para predizer VPico apresentou significativa resposta [F(1,20) = 23,854; p = 0,001; R2 = 0,544]. A relação entre VPico e o desempenho de 5KM apresentou excelente capacidade preditiva [F(1,20) = 90,799; p = 0,001; R2 = 0,819]. O desempenho de KBS explicou de forma significativa 50% do rendimento de 5KM. Similarmente, KBS mostrou-se como um preditor moderado de VPico. A VPico apresentou-se como um forte preditor do desempenho de 5KM para praticantes recreacionais.
... In a study by (Schumann et al., 2022), it was found that there was a positive linear relationship between training volume and muscle strength gains in a variety of populations, including athletes, individuals training for general fitness, and elderly populations. This suggests that increasing training volume tends to have a positive impact on muscle strength development. ...
Article
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Background: Muscle strength is an essential factor in maintaining one's health and quality of life. Resistance training programs have been known to be effective in improving muscle strength. However, their success can be affected by various factors, including exercise variety, volume, intensity, frequency, and duration. To optimize the effects of a resistance training program, a comprehensive planning approach is essential. Study Objective: This study aimed to conduct a systematic review of the literature to explore a comprehensive planning approach in optimizing resistance exercise programs to improve muscle strength. Materials and Methods: A systematic method was used to identify relevant studies from various scientific databases. Inclusion and exclusion criteria were established to select studies that fit the research objectives. Data from the selected studies were extracted and analyzed to evaluate the effectiveness and planning approaches used in resistance exercise programs. Results: The results of this systematic review indicate that a comprehensive planning approach, including individualization of the program, progressive and adaptive, integration of functional exercises, and periodic monitoring and evaluation, are critical factors in optimizing resistance exercise programs. Studies showed differences in the effectiveness of resistance training programs based on these factors. Conclusion: By integrating a comprehensive planning approach, resistance exercise programs can be optimized to achieve maximal muscle strength gains. Practical implications of these findings include relevance to specific populations and application in the context of rehabilitation. Future research should focus more on understanding the interactions between these factors and explore more specific planning approaches to improve the effectiveness of resistance training programs.
... The average evaluation score for all participants was 80.94. This is consistent with the findings (Schumann et al., 2022;Wolf et al., 2023); (Siswanto, Samsinar, Alam, et al., 2024;, which indicate that the average score for each participant in the training exceeded 80. ...
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The objective of this training activity is to enhance the skills and understanding of the community regarding digital marketing. The training consists of three phases: pre-activity, implementation, and monitoring and evaluation. It includes relevant materials, practical exercises, and evaluation tests, and was attended by 30 participants from the general public and MSME practitioners in Sleman Regency, held on July 26-27, 2024. The results show that 97% of participants passed the test, while 3% did not pass due to absence during the exam. The highest score achieved in the digital marketing training was 97.5 (by one participant), the lowest was 70 (by two participants), and the average evaluation score for each participant was 80.94. Overall, the training was successfully conducted and met the expected objectives.
... For individuals looking to perform both aerobic and anaerobic workouts in the same session, it is important to note that the order of exercises can influence training outcomes such as muscle hypertrophy 42) . Research suggests that performing resistance training before aerobic exercise may maximize muscle growth, while performing aerobic exercise first might impair strength gains. ...
Article
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Atherosclerosis, a major contributor to cardiovascular diseases (CVD), remains a leading cause of global mortality and morbidity. The pathogenesis of atherosclerosis involves a complex interplay of endothelial dysfunction, chronic inflammation, lipid accumulation, and arterial stiffness. Among the various preventive strategies, physical activity has emerged as a highly effective, non-pharmacological intervention. This review examines the preventive effects of different types of exercise—specifically aerobic exercise, resistance training, and combined training—on atherosclerosis development. Drawing on evidence from landmark studies, we explore the underlying mechanisms by which these exercise modalities improve endothelial function, reduce systemic inflammation, and enhance lipid profiles, thereby mitigating the progression of atherosclerosis. Additionally, the review discusses the dose-response relationship between physical activity and cardiovascular health, the differential effects of exercise intensities, and the potential risks associated with high-intensity training. The synergistic benefits of combined aerobic and resistance training are highlighted, particularly in populations with metabolic syndrome or other high-risk conditions. Emerging trends in personalized exercise medicine and the use of wearable technology for monitoring physical activity are also addressed, underscoring the potential for tailored exercise prescriptions to maximize cardiovascular health. By integrating current research findings, this review provides insights into effective exercise strategies for reducing cardiometabolic risk and emphasizes the importance of personalized approaches in exercise interventions.
... Saat bermain sepak bola, pemain berkontribusi untuk proses terjadinya gol atau mencetak gol. Bermain sepak bola tidak terus menerus berlari cepat saja, namun dalam bermain juga dibutuhkan lari joging agar stamina pemain tidak habis dan tidak mudah cepat lelah (Schumann et al., 2022). Ini yang disebut dengan gerakan intermitten. ...
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Sepak bola adalah olahraga yang menuntut kebugaran fisik yang maksimal. Pada skill related fitness, terdapat beberapa unsur kebugaran jasmani, yaitu diantaranya kecepatan dan kelincahan. Kecepatan dan kelincahan menjadi hal yang saling berkaitan saat pemain bermain sepak bola. Fartlek drill merupakan latihan yang dilakukan secara bertahap disesuaikan dengan intensitas, frekuensi, interval, durasi yang tepat sehingga ada pengaruh dalam kecepatan dan kelincahan pemain sepak bola. Tujuan dari penelitain ini untuk mengetahui pengaruh fartlek drills terhadap kecepatan dan kelincahan pemain Liga 2 PSCS Cilacap. Jenis penelitian atau metode yang digunakan dalam penelitian ini adalah penelitian eksperimen dengan pendekatan deskriptif kuantitatif. Desain yang digunakan dalam penelitian ini menggunakan One Group Post-Test Only Design . Metode penentuan sampel dalam penelitian ini adalah menggunakan sampel jenuh atau total sampling , yaitu teknik penentuan sampel bila semua anggota populasi digunakan sebagai sampel. Jadi, seluruh populasi dalam penelitian ini berjumlah 22 pemain PSCS Cilacap, diberi perlakuan dan post-test. Instrumen tes yang digunakan dalam penelitian ini adalah Illionis Agility Test untuk mengukur kelincahan pemain dan Run 30 Meters untuk mengukur kecepatan lari pemain. Hasil kecepatan, menyatakan nilai signifikansi > 0,05 ( sig = ,400) dan hasil kelincahan menyatakan nilai signifikansi > 0,05 ( sig = ,115) menunjukkan ada pengaruh pada kecepatan dan kelincahan pemain setelah diberi latihan fartlek drill . Kesimpulannya, kecepatan pemain PSCS Cilacap masuk dalam kategori Baik Sekali. Sedangkan kelincahan pemain PSCS Cilacap masuk dalam kategori Baik.
Article
Team sports players are frequently required to integrate multiple physical components, including strength and endurance capacity, to maximize their performance during both training and competitions. The combination of strength and endurance within a periodized program is known as concurrent training. Recently, concurrent training has emerged as an innovative method to enhance both muscular strength and aerobic performance, tailored to the specific requirements and diverse nature of each sport. However, concurrent training may induce excessive fatigue and compromise performance potentiation, depending on training prescription parameters. This distinction between the interference effect and performance enhancement presents a complex challenge for any team sports system. Consequently, the objective of this review is to scrutinize the efficacy, practical application, and methodological aspects of concurrent training. Additionally, it aims to elucidate strategies to mitigate the complexities associated with the interference effect, thereby optimizing the benefits of concurrent training modality for team sports, emphasizing soccer. The major findings indicate that concurrent training can improve strength and endurance qualities in athletes, but under certain conditions, it can also interfere with adaptations. Appropriate programming strategies, such as proper sequencing, scheduling, volume, intensity, and recovery, can help mitigate these negative effects. Additionally, whereas more experienced athletes display greater proficiency in executing concurrent training programs, younger players, particularly those under 14, tend to experience minimal interference effects from this training approach, making it well-suited for their development. Overall, concurrent training has been demonstrated as an effective and efficient method for improving strength and endurance performance in team sports players.
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Background The effect of concurrent training on the development of maximal strength is unclear, especially in individuals with different training statuses. Objective The aim of this systematic review and meta-analysis study was to compare the effect of concurrent resistance and endurance training with that of resistance training only on the development of maximal dynamic strength in untrained, moderately trained, and trained individuals. Methods On the basis of the predetermined criteria, 27 studies that compared effects between concurrent and resistance training only on lower-body 1-repetition maximum (1RM) strength were included. The effect size (ES), calculated as the standardised difference in mean, was extracted from each study, pooled, and analysed with a random-effects model. Results The 1RM for leg press and squat exercises was negatively affected by concurrent training in trained individuals (ES = – 0.35, p < 0.01), but not in moderately trained ( – 0.20, p = 0.08) or untrained individuals (ES = 0.03, p = 0.87) as compared to resistance training only. A subgroup analysis revealed that the negative effect observed in trained individuals occurred only when resistance and endurance training were conducted within the same training session (ES same session = – 0.66, p < 0.01 vs. ES different sessions = – 0.10, p = 0.55). Conclusion This study demonstrated the novel and quantifiable effects of training status on lower-body strength development and shows that the addition of endurance training to a resistance training programme may have a negative impact on lower-body strength development in trained, but not in moderately trained or untrained individuals. This impairment seems to be more pronounced when training is performed within the same session than in different sessions. Trained individuals should therefore consider separating endurance from resistance training during periods where the development of dynamic maximal strength is prioritised.
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Previous research has suggested that concurrent training (CT) may attenuate resistance training (RT)-induced gains in muscle strength and mass, i.e.‚ the interference effect. In 2000, a seminal theoretical model indicated that the interference effect should occur when high-intensity interval training (HIIT) (repeated bouts at 95–100% of the aerobic power) and RT (multiple sets at ~ 10 repetition maximum;10 RM) were performed in the same training routine. However, there was a paucity of data regarding the likelihood of other HIIT-based CT protocols to induce the interference effect at the time. Thus, based on current HIIT-based CT literature and HIIT nomenclature and framework, the present manuscript updates the theoretical model of the interference phenomenon previously proposed. We suggest that very intense HIIT protocols [i.e., resisted sprint training (RST), and sprint interval training (SIT)] can greatly minimize the odds of occurring the interference effect on muscle strength and mass. Thus, very intensive HIIT protocols should be implemented when performing CT to avoid the interference effect. Long and short HIIT-based CT protocols may induce the interference effect on muscle strength when HIIT bout is performed before RT with no rest interval between them.
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Background The importance of concurrent exercise order for improving endurance and resistance adaptations remains unclear, particularly when sessions are performed a few hours apart. We investigated the effects of concurrent training (in alternate orders, separated by ~3 hours) on endurance and resistance training adaptations, compared to resistance-only training. Materials and methods Twenty-nine healthy, moderately-active men (mean ± SD; age 24.5 ± 4.7 y; body mass 74.9 ± 10.8 kg; height 179.7 ± 6.5 cm) performed either resistance-only training (RT, n = 9), or same-day concurrent training whereby high-intensity interval training was performed either 3 hours before (HIIT+RT, n = 10) or after resistance training (RT+HIIT, n = 10), for 3 d.wk⁻¹ over 9 weeks. Training-induced changes in leg press 1-repetition maximal (1-RM) strength, countermovement jump (CMJ) performance, body composition, peak oxygen uptake (V˙O2peak), aerobic power (W˙peak), and lactate threshold (W˙LT) were assessed before, and after both 5 and 9 weeks of training. Results After 9 weeks, all training groups increased leg press 1-RM (~24–28%) and total lean mass (~3-4%), with no clear differences between groups. Both concurrent groups elicited similar small-to-moderate improvements in all markers of aerobic fitness (V˙O2peak ~8–9%; W˙LT ~16-20%; W˙peak ~14-15%). RT improved CMJ displacement (mean ± SD, 5.3 ± 6.3%), velocity (2.2 ± 2.7%), force (absolute: 10.1 ± 10.1%), and power (absolute: 9.8 ± 7.6%; relative: 6.0 ± 6.6%). HIIT+RT elicited comparable improvements in CMJ velocity only (2.2 ± 2.7%). Compared to RT, RT+HIIT attenuated CMJ displacement (mean difference ± 90%CI, -5.1 ± 4.3%), force (absolute: -8.2 ± 7.1%) and power (absolute: -6.0 ± 4.7%). Only RT+HIIT reduced absolute fat mass (mean ± SD, -11.0 ± 11.7%). Conclusions In moderately-active males, concurrent training, regardless of the exercise order, presents a viable strategy to improve lower-body maximal strength and total lean mass comparably to resistance-only training, whilst also improving indices of aerobic fitness. However, improvements in CMJ displacement, force, and power were attenuated when RT was performed before HIIT, and as such, exercise order may be an important consideration when designing training programs in which the goal is to improve lower-body power.
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Physical activity decreases the risk of a network of diseases and exercise may be prescribed as medicine for lifestyle-related disorders such as type 2 diabetes, dementia, cardiovascular diseases and cancer. During the past couple of decades, it has been apparent that skeletal muscle works as an endocrine organ, which can produce and secrete hundreds of myokines that exert their effects in either autocrine, paracrine or endocrine manners. Recent advances show that skeletal muscle produces myokines in response to exercise, which allow for crosstalk between the muscle and other organs, including brain, adipose tissue, bone, liver, gut, pancreas, vascular bed and skin, as well as communication within the muscle itself. Although only few myokines have been allocated to a specific function in humans, it has been identified that the biological roles of myokines include effects on e.g. cognition, lipid and glucose metabolism, browning of white fat, bone formation, endothelial cell function, hypertrophy, skin structure and tumor growth. This suggests that myokines may be useful biomarkers for monitoring exercise prescription for people with e.g. cancer, diabetes or neurodegenerative diseases.
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Conventional meta-analytic procedures assume that effect sizes are independent. When effect sizes are not independent, conclusions based on these conventional procedures can be misleading or even wrong. Traditional approaches, such as averaging the effect sizes and selecting one effect size per study, are usually used to avoid the dependence of the effect sizes. These ad-hoc approaches, however, may lead to missed opportunities to utilize all available data to address the relevant research questions. Both multivariate meta-analysis and three-level meta-analysis have been proposed to handle non-independent effect sizes. This paper gives a brief introduction to these new techniques for applied researchers. The first objective is to highlight the benefits of using these methods to address non-independent effect sizes. The second objective is to illustrate how to apply these techniques with real data in R and Mplus. Researchers may modify the sample R and Mplus code to fit their data.
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Key points We propose and validate a method for accurately identifying the activity of populations of motor neurons during contractions at maximal rate of force development in humans. The behaviour of the motor neuron pool during rapid voluntary contractions in humans is presented. We show with this approach that the motor neuron recruitment speed and maximal motor unit discharge rate largely explains the individual ability in generating rapid force contractions. The results also indicate that the synaptic inputs received by the motor neurons before force is generated dictate human potential to generate force rapidly. This is the first characterization of the discharge behaviour of a representative sample of human motor neurons during rapid contractions. Abstract During rapid contractions, motor neurons are recruited in a short burst and begin to discharge at high frequencies (up to >200 Hz). In the present study, we investigated the behaviour of relatively large populations of motor neurons during rapid (explosive) contractions in humans, applying a new approach to accurately identify motor neuron activity simultaneous to measuring the rate of force development. The activity of spinal motor neurons was assessed by high‐density electromyographic decomposition from the tibialis anterior muscle of 20 men during isometric explosive contractions. The speed of motor neuron recruitment and the instantaneous motor unit discharge rate were analysed as a function of the impulse (the time–force integral) and the maximal rate of force development. The peak of motor unit discharge rate occurred before force generation and discharge rates decreased thereafter. The maximal motor unit discharge rate was associated with the explosive force variables, at the whole population level (r² = 0.71 ± 0.12; P < 0.001). Moreover, the peak motor unit discharge and maximal rate of force variables were correlated with an estimate of the supraspinal drive, which was measured as the speed of motor unit recruitment before the generation of afferent feedback (P < 0.05). We show for the first time the full association between the effective neural drive to the muscle and human maximal rate of force development. The results obtained in the present study indicate that the variability in the maximal contractile explosive force of the human tibialis anterior muscle is determined by the neural activation preceding force generation.
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Background: At least one-third of community-dwelling people over 65 years of age fall each year. Exercises that target balance, gait and muscle strength have been found to prevent falls in these people. An up-to-date synthesis of the evidence is important given the major long-term consequences associated with falls and fall-related injuries OBJECTIVES: To assess the effects (benefits and harms) of exercise interventions for preventing falls in older people living in the community. Search methods: We searched CENTRAL, MEDLINE, Embase, three other databases and two trial registers up to 2 May 2018, together with reference checking and contact with study authors to identify additional studies. Selection criteria: We included randomised controlled trials (RCTs) evaluating the effects of any form of exercise as a single intervention on falls in people aged 60+ years living in the community. We excluded trials focused on particular conditions, such as stroke. Data collection and analysis: We used standard methodological procedures expected by Cochrane. Our primary outcome was rate of falls. Main results: We included 108 RCTs with 23,407 participants living in the community in 25 countries. There were nine cluster-RCTs. On average, participants were 76 years old and 77% were women. Most trials had unclear or high risk of bias for one or more items. Results from four trials focusing on people who had been recently discharged from hospital and from comparisons of different exercises are not described here.Exercise (all types) versus control Eighty-one trials (19,684 participants) compared exercise (all types) with control intervention (one not thought to reduce falls). Exercise reduces the rate of falls by 23% (rate ratio (RaR) 0.77, 95% confidence interval (CI) 0.71 to 0.83; 12,981 participants, 59 studies; high-certainty evidence). Based on an illustrative risk of 850 falls in 1000 people followed over one year (data based on control group risk data from the 59 studies), this equates to 195 (95% CI 144 to 246) fewer falls in the exercise group. Exercise also reduces the number of people experiencing one or more falls by 15% (risk ratio (RR) 0.85, 95% CI 0.81 to 0.89; 13,518 participants, 63 studies; high-certainty evidence). Based on an illustrative risk of 480 fallers in 1000 people followed over one year (data based on control group risk data from the 63 studies), this equates to 72 (95% CI 52 to 91) fewer fallers in the exercise group. Subgroup analyses showed no evidence of a difference in effect on both falls outcomes according to whether trials selected participants at increased risk of falling or not.The findings for other outcomes are less certain, reflecting in part the relatively low number of studies and participants. Exercise may reduce the number of people experiencing one or more fall-related fractures (RR 0.73, 95% CI 0.56 to 0.95; 4047 participants, 10 studies; low-certainty evidence) and the number of people experiencing one or more falls requiring medical attention (RR 0.61, 95% CI 0.47 to 0.79; 1019 participants, 5 studies; low-certainty evidence). The effect of exercise on the number of people who experience one or more falls requiring hospital admission is unclear (RR 0.78, 95% CI 0.51 to 1.18; 1705 participants, 2 studies, very low-certainty evidence). Exercise may make little important difference to health-related quality of life: conversion of the pooled result (standardised mean difference (SMD) -0.03, 95% CI -0.10 to 0.04; 3172 participants, 15 studies; low-certainty evidence) to the EQ-5D and SF-36 scores showed the respective 95% CIs were much smaller than minimally important differences for both scales.Adverse events were reported to some degree in 27 trials (6019 participants) but were monitored closely in both exercise and control groups in only one trial. Fourteen trials reported no adverse events. Aside from two serious adverse events (one pelvic stress fracture and one inguinal hernia surgery) reported in one trial, the remainder were non-serious adverse events, primarily of a musculoskeletal nature. There was a median of three events (range 1 to 26) in the exercise groups.Different exercise types versus controlDifferent forms of exercise had different impacts on falls (test for subgroup differences, rate of falls: P = 0.004, I² = 71%). Compared with control, balance and functional exercises reduce the rate of falls by 24% (RaR 0.76, 95% CI 0.70 to 0.81; 7920 participants, 39 studies; high-certainty evidence) and the number of people experiencing one or more falls by 13% (RR 0.87, 95% CI 0.82 to 0.91; 8288 participants, 37 studies; high-certainty evidence). Multiple types of exercise (most commonly balance and functional exercises plus resistance exercises) probably reduce the rate of falls by 34% (RaR 0.66, 95% CI 0.50 to 0.88; 1374 participants, 11 studies; moderate-certainty evidence) and the number of people experiencing one or more falls by 22% (RR 0.78, 95% CI 0.64 to 0.96; 1623 participants, 17 studies; moderate-certainty evidence). Tai Chi may reduce the rate of falls by 19% (RaR 0.81, 95% CI 0.67 to 0.99; 2655 participants, 7 studies; low-certainty evidence) as well as reducing the number of people who experience falls by 20% (RR 0.80, 95% CI 0.70 to 0.91; 2677 participants, 8 studies; high-certainty evidence). We are uncertain of the effects of programmes that are primarily resistance training, or dance or walking programmes on the rate of falls and the number of people who experience falls. No trials compared flexibility or endurance exercise versus control. Authors' conclusions: Exercise programmes reduce the rate of falls and the number of people experiencing falls in older people living in the community (high-certainty evidence). The effects of such exercise programmes are uncertain for other non-falls outcomes. Where reported, adverse events were predominantly non-serious.Exercise programmes that reduce falls primarily involve balance and functional exercises, while programmes that probably reduce falls include multiple exercise categories (typically balance and functional exercises plus resistance exercises). Tai Chi may also prevent falls but we are uncertain of the effect of resistance exercise (without balance and functional exercises), dance, or walking on the rate of falls.
Article
Progressive resistance training (PRT) combined with weight-bearing impact exercise are recommended to optimize bone health, but the optimal frequency and dose of training remains uncertain. This study, which is a secondary analysis of an 18-month intervention in men aged 50–79 years, examined the association between exercise frequency and the volume of training with changes in DXA and QCT-derived femoral neck (FN) and lumbar spine (LS) bone outcomes, respectively. Men were allocated to either thrice-weekly PRT plus impact exercise training (n = 87) or a non-exercising (n = 85) group. Average weekly exercise frequency (ExFreq) and training volume per session [PRT volume (weight lifted, kg), number of weight-bearing impacts (jumps completed) and total training volume] over the 18-months were calculated from the participants' exercise cards. Regression analysis showed that average weekly ExFreq and training volume per session were positively associated with the 18-month changes in FN BMD and LS trabecular volumetric BMD. Men completing on average 1 to <2 and ≥ 2 sessions/week had a 1.6 to 2.2% greater net gain in FN BMD relative to non-exercising men, while those completing ≥2 sessions/week had 3.9 to 5.2% net gain in LS trabecular vBMD compared to non-exercising men and those completing <1 session/week. Further analysis showed that the average number of impact loads per session, but not the average PRT weight-lifted, was positively associated with changes in BMD. Every 10 impact loads per session over 18 months was associated with a 0.3% and 1.3% increase in FN BMD and LS trabecular vBMD, respectively. In conclusion, this study indicates that exercise frequency and training volume were predictors of the changes in hip and spine BMD following a multi-component exercise program, and that the number of impact loads rather than PRT weight lifted per session was more important for eliciting positive skeletal responses in middle-aged and older men.
Article
Purpose: To investigate strength and structural adaptations after 12 weeks of resistance, endurance cycling, and concurrent training. Methods: Thirty-two healthy males undertook 12 weeks of resistance-only (RT; n = 10), endurance-only (END; n = 10), or concurrent resistance and endurance training (CONC; n = 12). Biceps femoris long head (BFlh) architecture, strength (3-lift 1-repetition maximum), and body composition were assessed. Results: Fascicle length of the BFlh reduced 15% (6%) (P < .001) and 9% (6%) (P < .001) in the END and CONC groups postintervention, with no change in the RT group (-4% [11%], P = .476). All groups increased BFlh pennation angle (CONC: 18% [9%], RT: 14% [8%], and END: 18% [10%]). Thickness of the BFlh increased postintervention by 7% (6%) (P = .002) and 7% (7%) (P = .003) in the CONC and RT groups, respectively, but not in the END group (0% [3%], P = .994). Both the CONC and RT groups significantly increased by 27% (11%) (P < .001) and 33% (12%) (P < .001) in 3-lift totals following the intervention, with no changes in the END cohort (6% [6%], P = .166). No significant differences were found for total body (CONC: 4% [2%], RT: 4% [2%], and END: 3% [2%]) and leg (CONC: 5% [3%], RT: 6% [3%], and END: 5% [3%]) fat-free mass. Conclusions: Twelve weeks of RT, END, or CONC significantly modified BFlh architecture. This study suggests that conventional resistance training may dampen BFlh fascicle shortening from cycling training while increasing strength simultaneously in concurrent training. Furthermore, the inclusion of a cycle endurance training stimulus may result in alterations to hamstring architecture that increase the risk of future injury. Therefore, the incorporation of endurance cycling training within concurrent training paradigms should be reevaluated when trying to modulate injury risk.
Article
Spiliopoulou, P, Zaras, N, Methenitis, S, Papadimas, G, Papadopoulos, C, Bogdanis, GC, and Terzis, G. Effect of concurrent power training and high-intensity interval cycling on muscle morphology and performance. J Strength Cond Res XX(X): 000-000, 2019-The aim of the study was to examine the effect of performing high-intensity interval cycling on muscle morphology and performance immediately after power training (PT). Twenty healthy female physical education students were assigned into 2 training groups. One group performed PT, and the other group performed the same PT followed by high-intensity interval aerobic training on a cycle ergometer (PTC). Training was performed 3 days per week for 6 weeks. Countermovement jump (CMJ) height and CMJ power, half-squat maximal strength (1 repetition maximum), maximum aerobic power, vastus lateralis muscle fiber composition, and cross-sectional area (CSA) were evaluated before and after the intervention. Countermovement jump height increased after PT (10.1 ± 6.6%, p = 0.002) but not after PTC (-5.1 ± 10.5%, p = 0.099), with significant difference between groups (p = 0.001). Countermovement jump power increased after PT (4.5 ± 4.9%, p = 0.021) but not after PTC (-2.4 ± 6.4, p = 0.278), with significant difference between groups (p = 0.017). One repetition maximum increased similarly in both groups. Muscle fiber composition was not altered after either PT or PTC. Vastus lateralis muscle fiber CSA increased significantly and similarly after both PT (I: 16.9 ± 16.2%, p = 0.035, ΙΙΑ: 12.7 ± 10.9%, p = 0.008,ΙΙΧ: 15.5 ± 17.1%, p = 0.021) and PTC (Ι: 18.0 ± 23.7%, p = 0.033,ΙΙΑ: 18.2 ± 11.4%, p = 0.001,ΙΙΧ: 25.5 ± 19.6%, p = 0.003). These results suggest that the addition of high-intensity interval cycling to PT inhibits the anticipated increase in jumping performance induced by PT per se. This inhibition is not explained by changes in muscle fiber type composition or vastus lateralis muscle fiber CSA adaptations.