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Resistance Training Load Effects on Muscle
Hypertrophy and Strength Gain: Systematic
Review and Network Meta-analysis
PEDRO LOPEZ
1,2
, RÉGIS RADAELLI
3
, DENNIS R. TAAFFE
1,2
, ROBERT U. NEWTON
1,2,4
,DANIELA.GALVÃO
1,2
,
GABRIEL S. TRAJANO
5
, JULIANA L. TEODORO
3
, WILLIAM J. KRAEMER
6
, KEIJO HÄKKINEN
7
,andRONEIS.PINTO
3
1
Exercise Medicine Research Institute, Edith Cowan University, Joondalup, Western Australia, AUSTRALIA;
2
School of Medical
and Health Sciences, Edith Cowan University, Joondalup, Western Australia, AUSTRALIA;
3
Exercise Research Laboratory,
School of Physical Education, Physiotherapy and Dance, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS,
BRAZIL;
4
School of Human Movement and Nutrition Sciences, University of Queensland, Queensland, AUSTRALIA;
5
School of
Exercise and Nutrition Sciences, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Queensland,
AUSTRALIA;
6
Department of Human Sciences, The Ohio State University, Columbus, OH; and
7
Neuromuscular Research
Center, Biology of Physical Activity, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
ABSTRACT
LOPEZ, P., R. RADAELLI, D. R. TAAFFE, R. U. NEWTON, D. A. GALVÃO, G. S. TRAJANO, J. L. TEODORO, W. J. KRAEMER, K.
HÄKKINEN, and R. S. PINTO. Resistance Training Load Effects on Muscle Hypertrophy and Strength Gain: Systematic Review and Net-
work Meta-analysis. Med. Sci. Sports Exerc.,Vol.53,No.6,pp.1206–1216, 2021. Purpose: This study aimed to analyze the effect of resis-
tance training (RT) performed until volitional failure with low, moderate, andhigh loads on musclehypertrophy and muscle strength in healthy
adults and to assess the possible participant-, design-, and training-related covariates that may affect the adaptations. Methods: Using Pre-
ferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, MEDLINE, CINAHL, EMBASE, SPORTDiscus, and Web
of Science databases were searched. Including only studies that performed sets to volitional failure, the effects of low- (>15 repetitions max-
imum (RM)), moderate- (9–15 RM), and high-load (≤8 RM) RTs were examined in healthy adults. Network meta-analysis was undertaken to
calculate the standardized meandifference (SMD) between RT loads in overall and subgroup analyses involving studies deemed of high qual-
ity. Associations between participant-, design-, and training-related covariates with SMD were assessed by univariate and multivariate net-
work meta-regression analyses. Results: Twenty-eight studies involving 747 healthy adults were included. Although no differences in
muscle hypertrophy between RT loads were found in overall (P=0.113–0.469) or subgroup analysis (P=0.871–0.995), greater effects were
observed in untrained participants (P= 0.033) and participants with some training background who undertook more RT sessions
(P=0.031–0.045). Muscle strength improvement was superior for both high-load and moderate-load compared with low-load RT in overall
andsubgroupanalysis(SMD,0.60–0.63 and 0.34–0.35, respectively; P<0.001–0.003), with a nonsignificant but superior effect for high
compared with moderate load (SMD, 0.26–0.28, P= 0.068). Conclu sions: Although muscle hypertrophy improvements seem to be load in-
dependent, increases in muscle strength are superior in high-load RT programs. Untrained participants exhibit greater muscle hypertrophy,
whereas undertaking more RT sessions provides superior gains in those with previous training experience. Key Words: STRENGTH
TRAINING, VOLITIONAL FAILURE, MUSCLE HYPERTROPHY, MUSCLE STRENGTH
Resistance training is a popular and effective modality
to improve muscle function, functional performance,
and health parameters in a wide range of healthy and
clinical populations. Among the many expected outcomes, in-
creases in muscle size and strength are considered important
and desirable by individuals and clinicians either for perfor-
mance or health and functional improvement. In the 1940s,
DeLorme and Watkins (1) proposed undertaking resistance
exercise sets until neuromuscular volitional failure to maxi-
mize such benefits. Although a vast body of research work
in this area has been published (2–7), issues regarding how
to optimize resistance training outcomes remain (8,9). Further-
more, controversies regarding how volitional failure is opera-
tionalized call into question the implementation of this
technique in populations other than strength athletes, as
Address for correspondence: Pedro Lopez, M.Sc., Exercise Medicine Research
Institute, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA
6027, Australia; E-mail: p.lopezda@our.ecu.edu.au.
Submitted for publication August 2020.
Accepted for publication December 2020.
Supplemental digital content is available for this article. Direct URL citations
appear in the printed text and are provided in the HTML and PDF versions
of this article on the journal’s Web site (www.acsm-msse.org).
0195-9131/20/5306-1206/0
MEDICINE & SCIENCE IN SPORTS & EXERCISE
®
Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on
behalf of the American College of Sports Medicine. This is an open-access article
distributed under the terms of the Creative Commons Attribution-Non Commercial-
No Derivatives License 4.0 (CCBY-NC- ND), where it is permissible to download
and share the work provided it is properly cited. The work cannot be changed in any
way or used commercially without permission from the journal.
DOI: 10.1249/MSS.0000000000002585
1206
APPLIED SCIENCES
participants’motivation and tolerance, discomfort, and neuro-
muscular fatigue affect the performance and results related to
this training program.
Load selection has been considered an important resistance
training variable to successfully increase muscle size and strength
across different populations (10). Considering Henneman’ssize
principle (i.e., motor units are recruited from smallest to largest)
(11), studies have advocated in favor of either high loads
(12–15) or both low and high loads (16) to achieve maximal
or near-maximal recruitment of motor units during fatiguing
contractions to induce muscle hypertrophy. Although this is
a topic of intense debate in the literature, when low-load sets
are performed until volitional failure, neuromuscular fatigue
necessitates increasing percentage recruitment of the motor
unit pool, and through this mechanism (12), such training
may produce a meaningful drive for muscle hypertrophy.
For example, Mitchell et al. (6) and Lim et al. (5) have re-
ported that 10 wk of resistance training until volitional failure
in untrained men at low and high loads (30% and 80% of 1
repetition maximum (1-RM)) resulted in similar increases in
quadriceps femoris muscle volume (6.8% and 7.2%, respec-
tively) and muscle fiber cross-sectional area of the vastus
lateralis (ranging from 15% to 20% in both groups). These
findings indicate that muscle hypertrophy may be more respon-
sive in untrained individuals because of the large window for
adaptation, masking differential effects of training modalities
and dosages (17), and not show an obvious load-dependent re-
lationship when resistance training sets are performed until vo-
litional failure (6,18). In contrast, Schoenfeld and colleagues (7)
reported that 8 wk of resistance training at high loads (2–4RM)
induced greater strength gains in recreationally trained men
compared with moderate loads (8–12 RM), whereas increases
in elbow extensor and quadriceps femoris muscle thickness
were higher for the moderate-load group. Consequently, it is
unclear as to loading effects on muscle hypertrophy when resis-
tance training is undertaken until volitional failure. Further-
more, despite previous meta-analyses examining low (≤60%
of 1-RM) and higher resistance training load (>60% of 1-RM)
effects on muscle strength and hypertrophy (9,19), the lack of
meta-analyses comprising a large number of studies comparing
well-defined ranges of load such as low- (<60% of 1-RM),
moderate- (between 60% and 79% of 1-RM), and high-load re-
sistance training (≥80% of 1-RM) through robust meta-analytic
approaches such as network meta-analysis precludes the deter-
mination of an appropriate load for outcomes of interest in
healthy adults with different pretraining genetic and morpho-
logical characteristics.
Other issues comparing resistance training loads are related
to the heterogeneity of study designs such as the participants
involved (men vs women or combined), training status (untrained
vs recreationally trained vs strength athletes), experimental de-
sign (between- and within-subject), assessed outcomes (lower-,
upper-, and whole-body), and training prescription (number
of sessions; operational definition of volitional failure and its
implementation and verification). These different characteristics
among studies may preclude the accurate evaluation of an
optimal resistance training load, considering specific methodo-
logical or resistance training prescription characteristics when full
and similar recruitment of the motor unit pool is achieved. As a
result, the purposes of the review and analysis are to 1) analyze
the effect of resistance training performed until failure with
low, moderate, and high loads on muscle hypertrophy and
muscle strength in healthy adults and 2) assess the possible
participant-, design-, and training-related covariates that may af-
fect the hypertrophy and strength gains.
METHODS
Study selection procedure. The study was undertaken
in accordance with the Preferred Reporting Items for System-
atic Reviews and Meta-Analyses statement (20,21), and the
method used was based on the minimum criteria established
by the Cochrane Back Review Group (22). The review in-
cluded published data from experimental studies that evalu-
ated the effects of low (<60% of 1-RM, or >15 RM),
moderate (between 60% and 79% of 1-RM, or 9–15 RM),
and high (≥80% of 1-RM, or ≤8 RM) loads in resistance train-
ing performed until volitional failure in healthy adults (23).
The primary outcomes of this review were muscle hypertro-
phy (i.e., defined as a measure of muscle mass or size) and
muscle strength (i.e., defined by 1-RM tests). Studies were ex-
cluded when 1) they did not present sufficient information re-
garding the comparisons between different loads or pretraining
and posttraining values in the resistance training programs; 2) in-
terventions were shorter than 6 wk; 3) specific outcomes for this
review or sufficient information were not reported (e.g., baseline
and postintervention assessment, and within- and between-group
mean difference); 4) resistance training involving blood flow
restriction protocols; and 5) written in a language other than
English. In the search strategy, titles and abstracts were first
independently evaluated. When abstracts did not provide suf-
ficient information, they were selected for full-text evaluation.
Eligibility was assessed independently by two authors (P. L.
and J. L. T.), with differences resolved by consensus.
The search was conducted up to December 2019 using the
following electronic databases: MEDLINE, CINAHL, EMBASE,
SPORTDiscus, and Web of Science. The terms used were as
follows: “resistance training until failure”and “muscle hyper-
trophy”or “muscle strength”in association with a list of sen-
sitive terms to search for experimental studies. In addition, a
manual search was performed in the reference lists provided
in the selected articles as well as in a previous systematic re-
view (9) to detect studies potentially eligible for inclusion.
The search strategy used is shown in the Supplemental Digital
Content Table S1 (see in Supplemental Digital Content 1, lit-
erature search strategy, http://links.lww.com/MSS/C233).
Data extraction. The data extraction was performed via a
standardized form. Information regarding participants, resis-
tance training protocols, outcomes, and assessment techniques
was collected. Study characteristics, intervention duration, num-
ber of sessions, sex, experimental design, training status, assessed
outcomes, and resistance training prescription method were
RESISTANCE TRAINING IN HEALTHY ADULTS Medicine & Science in Sports & Exercise
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extracted, along with the main outcomes, whereas outcomes
were extracted in their absolute units (e.g., kilograms for 1-RM
assessments; millimeters or centimeters for muscle thickness).
When graphs were used instead of numerical data, the graphs
were measured using a specific tool for data extraction
(WebPlotDigitizer, San Francisco, CA).
Assessment of risk of bias. The risk of bias of individ-
ual studies was evaluated according to the second version of
the Cochrane risk-of-bias tool for randomized trials (RoB 2)
(24), focusing on different aspects of trial design, conduct,
and reporting. Each assessment using the RoB 2 tool is fo-
cused on the outcome level. The six-item instrument used to
evaluate each included randomized controlled trial in each out-
come of interest is as follows: 1) randomization process, 2) de-
viation from intended interventions, 3) missing outcome data,
4) measurement of the outcome, 5) selection of the reported re-
sult, and 6) overall analysis. Overall risk of bias was expressed
as “low risk of bias”if all domains where classified as low risk,
“some concerns”if some concern was raised in at least one do-
main but not classified as at high risk in any other, or “high risk
of bias”if at least one domain was classified as high risk, or
have multiple domains with some concerns (24).
Data analysis. In the network meta-analysis, the pooled-effect
estimates were obtained from the standardized mean difference
(SMD) of baseline to the final assessment of the intervention for
each group. When studies did not provide standard deviation
(SD) of change in the outcomes, these values were estimated
using a correlation coefficient (r) of 0.5 and the equation:
SDchange ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
SD2
baseline þSD2
final
−2rSDbaseline SDfinal
ðÞ
q
as per the Cochrane Handbookguideline (25). Furthermore, to
avoid overestimating the weight of a study by entering it mul-
tiple times in the analysis (25), experimental groups from the
studies were combined when considered within the same resis-
tance training load group (e.g., three sets of 30–40 RM and
three sets of 100–150 RM defined aslow-load resistance train-
ing [2]), as well as outcomes when considered within the same
outcome category (e.g., lower-body muscle hypertrophy or
upper-body muscle strength). Analyses were conducted for
overall studies, and a subgroup analysis was provided for
best-quality studies based on the risk of bias assessment.
The network meta-analysis was performed following the cur-
rent Preferred Reporting Items for Systematic Reviews and
Meta-Analyses guideline items (26,27): 1) a network geome-
try was created to explore the comparisons between resis-
tance training loads; 2) transitivity was tested by fitting a
network inconsistency assumption along with Qtest and
side-splitting analyses between indirect and direct compari-
sons; and 3) effect size (ES) was generated considering the
heterogeneity and the inconsistency level in the models. Sta-
tistical significance was assumed when the SMD reached an
αvalue ≤0.05. According to Cohen (28), ES values of 0.0 to
≤0.5 indicate small; 0.51 to 0.79, medium; and ≥0.8, large ef-
fects. Furthermore, an estimation of the probability to be the
best resistance training program for the outcome was provided
based on the consistency values and expressed as a percentage.
Outliers were explored by sensitivity analyses omitting one
study at a time, generating pooled estimates, and comparing with
the original estimates. To check for the presence of publication
bias, a network funnel plot and the Egger’stestwereused,
with a significant publication bias considered if the Pvalue
was <0.1 (29). The network meta-analysis was conducted
using R (R Core Team, 2019) with the package netmeta
(30). Forest plots presented for the outcome measures are after
sensitivity analysis adjustments.
To test the association between SMD and specific covari-
ates such as year of publication, experimental design (i.e.,
between-subject vs within-subject), sex (i.e., women vs men),
training status (i.e., untrained vs recreationally trained), number
of sessions, assessed outcomes (i.e., lower- vs upper-body out-
comes), and the prescription method (i.e., %1-RM vs RM), uni-
variate and multivariate network meta-regressions were used
(31). Dichotomy variables were coded as 0 and 1, whereas
continuous variables were used in the model to explain the
variations in muscle hypertrophy and strength among all com-
parisons. The network meta-regression was conducted using
Stata 14.0 with the package mvmeta (31).
RESULTS
Studies included. All studies selected reported the aim to
compare the effect of different resistance training loads (i.e.,
low, moderate, or high) on muscle hypertrophy and strength
in healthy men and women. We retrieved 5924 studies, 2629
of which were retained for screening after duplicate removals.
Of these, 2515 were excluded, and 114 full-text articles were
assessed for eligibility (Fig. 1). The eligibility assessment re-
sulted in a total of 28 (2–7,32–53) studies included in the pres-
ent review, network meta-analyses, and meta-regression, of
which 24 studies (3–7,32–40,42–53) examined muscle hyper-
trophy and 23 studies (2–7,32,33,35,38–48,50–52) examined
muscle strength. During the eligibility assessment, one of the
authors from the studies of Au et al. (54) and Morton et al.
(43) was contacted for further information, and it was con-
firmed that the study of Au et al. (54) was a follow-up analysis
from Morton et al. (43). As a result, only the study of Morton
et al. (43) was included in the systematic review.
Participants and intervention characteristics. A
total of 747 healthy men and women with an average age of
23.4 ± 3.0 yr participated in the included studies. Seventeen
studies compared low- versus high-load resistance training
(2,5,6,33,34,36,38,39,42–46,49–51,53), four compared low-
versus moderate-load (35,40,47,52), five compared moderate-
versus high-load (7,32,37,41,48), and two studies compared
low- versus moderate- versus high-load (3,4). Most of the
studies involved men (19 of 28, or 67.9% [2–7,34,38–42,
44–48,53]) and untrained participants (21 of 28, or 75.0%
[2–6,32–39,42,44–46,49–52]; Table S2, Supplemental Digital
Content 2, characteristics of included studies, http://links.lww.
com/MSS/C234). None of the studies included highly strength-
trained individuals as defined by 1-RM test values reported in
http://www.acsm-msse.org1208 Official Journal of the American College of Sports Medicine
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studies involving elite athletes (average relative strength of 2.0
body weights for back squat and 1.5 body weights for bench
press (55,56).
The mean exercise intervention duration was 8.9 ± 2.1 wk,
with an average of 24.6 ± 7.5 sessions (range, 16–48). Most of
the studies undertook a between-subject experimental design
(22 of 28, or 78.6% [2,3,5,7,32–38,40–43,46–49,51–53]) and
prescribed the resistance training program by repetitions maxi-
mum (18 of 28, or 64.3% [2,3,7,32,35–37,40–43,46–49,51–53];
Table S2, Supplemental Digital Content 2, characteristics of
included studies, http://links.lww.com/MSS/C234). Regarding
the assessments, muscle hypertrophy was assessed for the lower
limbsin15studies(3–7,32,35–39,43,44,49,50), followed by 8
studies assessing the upper limbs (4,7,32, 34,45,47,48,50) and
5 studies assessing the whole body (e.g., dual-energy x-ray ab-
sorptiometry) (33,40,42,46,53), whereas lower-body muscle
strength was assessed in 20 studies (3–7,32,33,35,38–44,46,
48,50–52), followed by 12 studies assessing upper-body mus-
cle strength (2,4,7,33,40,41,43,45,47,48,50,51), all using the
1-RM test. Eighteen studies reported the total volume per-
formed during the intervention (4,5,7,32–35,37–45,48,50).
The number of studies among the resistance training loads
for muscle hypertrophy and muscle strength is shown in the
network geometry (Fig. 2, panels A and B, respectively).
Risk of bias assessment. For muscle hypertrophy,
87.5% of the studies have some concern (21 of 24 studies
FIGURE 1—Flowchart of study selection process.
FIGURE 2—Network geometry of studies examining muscle hypertrophy (n= 24; A) and muscle strength (n= 23; B). k, number of comparisons; RT, re-
sistance training.
RESISTANCE TRAINING IN HEALTHY ADULTS Medicine & Science in Sports & Exercise
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[3–7,33–39,43–50,53]), whereas the remaining have a high risk
(3 of 24 studies, or 12.5% [32,40,42]) in the overall risk of bias
assessment (Table 1). The concerns in muscle hypertrophy as-
sessment were mainly due to the randomization process as
studies did not report concealment allocation (some concerns:
23 of 24 studies, or 95.8% [3–7,32–40,43–50,53]) or did not
follow any randomization (high risk: 1 of 24 studies, or
4.2% [42], 4.2%). Furthermore, studies were considered to
have some concerns in the measurement of the outcome (8 of
24 studies, or 33.3% [4,7,38,39,44,47,48,50]) when evaluat-
ing muscle hypertrophy through unblinded evaluations and
evaluations requiring technician or assessor direct analysis
and interpretation (e.g., muscle ultrasound imaging), whereas
they had a high risk (3 of 24 studies, or 12.5% [32,40,42])
when they did not use a reliable technique of assessment
(e.g., skinfold or circumference). In the subgroup analysis
for muscle hypertrophy, best-quality studies were those con-
sidered with low risk on the measurement of the outcome
(3,5,6,33–37,43,45,46,49,53).
In the muscle strength overall risk of bias assessment,
87.0% of the studies have some concern (20 of 23 studies
[3–7,32,33,35,38–41,43–48,50,52]), whereas the remaining
have a high risk (3 of 23 studies, or 13.0% [2,42,51]; Table 1).
The concerns were mainly due to the randomization process as
studies did not report concealment allocation (some concerns:
20 of 23 studies, or 87.0% [3–7,32,33,35,38–41,43–48,50,52])
or if the participants were not randomly assigned in the experi-
mental groups (high risk: 3 of 23 studies, or 13.0% [2,42,51]),
and on the measurement of the outcome (some concerns: 23
of 23 studies, or 100% [2–7,32,33,35,38–48,50–52]) as studies
assessed muscle strength with no blinding of testers. In the sub-
group analysis for muscle strength, best-quality studies were
considered those not presenting high risk in overall risk of bias
assessment (3–7,32,33,35,38–41,43–48,50,52). The individual
risk of bias assessment is shown in Supplemental Digital Content
Figures S1A and B (Supplemental Digital Content 3, individual
risk of bias assessment, http://links.lww.com/MSS/C235).
Resistance training load effects on muscle hyper-
trophy. Thirty-five comparisons were undertaken on muscle
hypertrophy involving 24 studies (3–7,32–40,42–53). The re-
sults from the consistency network meta-analysis provided no
differences in muscle hypertrophy between high- and low-
load, moderate- and low-load, or high- and moderate-load re-
sistance training (P=0.113–0.469; Table 2 and Fig. 3). The
heterogeneity was I
2
= 0%. Furthermore, no differences between
the loads were observed in the subgroup analysis involving the
best-quality studies (number of comparisons = 16, I
2
=0%,
P= 0.871–0.995; Table 2). Although the results of the consis-
tency model indicate that moderate-load (84.5%) and high-load
resistance training (75.8%) are the best load for muscle hypertro-
phy in overall and high-quality subgroup analyses, respectively,
the ES values were unlikely to be considered meaningful (small
ES: range, −0.09 to 0.15). The inconsistency between direct
and indirect comparisons was not significant in the network
analysis for all studies (Q=6.2,P= 0.103) or in the subgroup
analysis (Q=0.3,P= 0.957), as well as in the node-splitting anal-
ysis across comparisons between load groups (all studies:
P= 0.424–0.914; best-quality studies: P= 0.615–0.760). No
publication bias was identified after the inspection of funnel plots
asymmetry by Egger’stest(P= 0.497–0.909).
In the univariate network meta-regression, the covariates
(i.e., year of publication, experimental design, sex, training
status, number of sessions, assessed limb, and prescription
method) did not explain the variation in muscle hypertrophy
TABLE 1. Risk of bias of included studies.
Outcome
Randomization
Process
Deviation from Intended
Interventions
Missing
Outcome Data
Measurement
of the Outcome
Selection of the
Reported Result Overall Bias
Muscle hypertrophy (n=24)
Low risk 0 24 (100%) 24 (100%) 13 (54.2%) 24 (100%) 0
Some concerns 23 (95.8%) 0 0 8 (33.3%) 0 21 (87.5%)
High risk 1 (4.2%) 0 0 3 (12.5%) 0 3 (12.5%)
Muscle strength (n=23)
Low risk 0 23 (100%) 23 (100%) 0 23 (100%) 0
Some concerns 20 (87.0%) 0 0 23 (100%) 0 20 (87.0%)
High risk 3 (13.0%) 0 0 0 0 3 (13.0%)
TABLE 2. Network meta-analysis consistency models for muscle hypertrophy and muscle strength in studies comparing low-, moderate-, and high-load resistance training in healthy adults.
Outcome Comparisons kSample Pooled SMD 95% CI PBest Intervention Probability
Muscle hypertrophy High vs low All 19 347 0.12 −0.06 to 0.29 0.241 Overall analysis: 84.5% for moderate-load resistance training
Best quality: 75.8% for high-load resistance trainingBest-quality 12 274 0.10 −0.14 to 0.33 0.871
Moderate vs low All 7 128 0.20 −0.04 to 0.44 0.113
Best-quality 2 88 −0.06 −0.54 to 0.42 0.929
High vs moderate All 9 107 −0.09 −0.33 to 0.16 0.469
Best-quality 2 51 0.15 −0.34 to 0.65 0.995
Muscle strength High vs low All
a
19 403 0.60 0.38 to 0.8 2 <0.001 Overall analysis: 98.2% for high-load resistance training
Best quality: 98.2% for high-load resistance trainingBest-quality 16 325 0.63 0.38 to 0.88 <0.001
Moderate vs low All
a
9 152 0.34 0.05 to 0.62 0.003
Best-quality 9 152 0.35 0.05 to 0.65 0.002
High vs moderate All
a
10 125 0.26 −0.02 to 0.54 0.068
Best-quality 10 125 0.28 −0.02 to 0.58 0.066
Bold values are significant.
a
Adjustment after sensitivity analysis omitting one study at a time.
k, Number of comparisons.
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gains (P= 0.278–0.986; Supplemental Digital Content Table S3,
Supplemental Digital Content 4, univariate meta-regression results,
http://links.lww.com/MSS/C236). Regarding the multivariate
model, there was a significant interaction for training status
(P= 0.033), with untrained participants presenting higher ef-
fects on muscle hypertrophy in low- versus high-load resistance
training comparison (Table 3). The number of sessions seems
to influence the results in both moderate- versus low-load
(P= 0.031) and high- versus moderate-load (P= 0.045) re-
sistance training, with a higher number of sessions resulting
in greater effects on muscle hypertrophy (Table 3). The remain-
ing variables (i.e., year of publication, experimental design, sex,
assessed limb, and prescription method) were not significant in
explaining variations in muscle hypertrophy (P= 0.145–0.999).
Resistance training load effects on muscle
strength. Thirty-nine comparisons were undertaken on mus-
cle strength assessed by a 1-RM test involving 23 studies
(2–7,32,33,35, 38–48,50–52). Visual inspection of funnel plots
indicated a presence of publication bias (P= 0.014), and the
study of Anderson and Kearney (2) was considered an outlier
in the analysis. After the adjustment, the consistency network
meta-analysis results show that high-load (SMD, 0.60; 95%
confidence interval [CI], 0.38–0.82) and moderate-load
(SMD, 0.34, 95% CI, 0.05–0.62) resulted in higher muscle
strength effects when compared with low-load resistance
training (P< 0.001 and 0.003, respectively). A nonsignificant
effect (P= 0.068) was found favoring high-load when com-
pared with moderate-load resistance training (Table 2 and
Fig. 4). The heterogeneity was I
2
=39.9%,withnopresence
of publication bias (P= 0.277). The results of the consistency
models indicate that high-load resistance training has a proba-
bility of 98.2% to induce greater effects on muscle strength,
also sustained in subgroup analyses (k=36;Table2)withhet-
erogeneity I
2
= 43.7% and no effect of publication bias
(P= 0.350). The inconsistency between direct and indirect com-
parisons was not significant in the network analysis for all stud-
ies (Q=5.3,P= 0.150) and for subgroup analysis (Q=4.4,
P= 0.219), as well as in the node-splitting analyses (all studies:
P= 0.588–0.892; best-quality studies: P=0.674–0.871).
In the univariate network meta-regression, older studies
accounted for the variation in muscle strength in the overall
analysis (P= 0.021), whereas the remaining variables did not
explain variation in muscle strength (i.e., experimental design,
sex, training status, number of sessions, assessed limb, and pre-
scription method; P= 0.097–0.984; Table S3, Supplemental
Digital Content 4, univariate meta-regression results, http://links.
lww.com/MSS/C236). Regarding the multivariate model, older
studies (P= 0.023) and those with men (P=0.037)presented
higher effects on muscle strength in the low- versus high-load re-
sistance training comparison (Table 3). The remaining variables
FIGURE 3—SMD effects between low-, moderate-, and high-load resistance training performed until volitional failure on muscle hypertrophy. Overall and
subgroup analyses conducted with a network random-effects model. Gray and white circles represent study-specific estimates based on risk of bias assess-
ment (low risk, and some concern or high risk of bias, respectively); diamonds represent pooled estimates of random-effects meta-analysis.
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did not explain variations in muscle strength in the comparisons
(i.e., experimental design, training status, number of sessions,
assessed limb, and prescription method; P=0.121–0.823, Table 3).
DISCUSSION
There are three important findings from our systematic re-
view and network meta-analysis of the dose–response rela-
tionship between resistance training load and gains in muscle
hypertrophy and strength. First, in untrained and recreationally
trained individuals (i.e., not strength athletes), muscle hyper-
trophy gains are likely to be similar regardless of resistance
training load when performed to volitional failure over rela-
tively short periods of intervention. In line with the physiolog-
ical adaptation principle of diminishing returns, untrained
participants exhibit greater muscle hypertrophy compared with
those with even modest prior experience in resistance training.
Furthermore, undertaking more resistance training sessions pro-
vides superior muscle size gains in those with previous
training experience. Second, effects on muscle strength are
load dependent, with higher loads resulting in greater gains over
the relatively short interventions reviewed. Finally, the results for
muscle hypertrophy and strength were maintained even when only
the higher-quality studies were considered, that is, studies with less
risk of bias. Therefore, although improvements in muscle hypertro-
phy seem to be load independent for untrained and recreationally
trained individuals, muscle strength increases are superior
with high-load resistance training programs of short duration.
The inclusion of experimental studies using repetitions until
volitional failure is based on ensuring that a similar stressful
stimulus was undertaken by all participants in the resistance
training programs (57). Although performing resistance train-
ing until volitional failure is one way to eliminate a large
amount of individual variability related to between-subject en-
durance capacity (i.e., individuals who are able to complete
different numbers of repetitions at a given relative load) and
ensures methodological feasibility when comparing different
resistance training loads (57), other approaches have been
TABLE 3. Network meta-regression models for muscle hypertrophy and muscle strength.
Comparison Covariates Range Coef ± SE 95% CI P
Muscle hypertrophy
High vs low Year of publication 2002–2019 0.05 ± 0.05 −0.04 to 0.14 0.244
Experimental design Between- vs within-group 0.00 ± 0.33 −0.64 to 0.64 0.999
Sex Women vs men 0.22 ± 0.40 −0.64 to 1.01 0.583
Training status Untrained vs recreationally trained −1.38 ± 0.65 −2.67 to −0.11 0.033
Number of sessions 12–48 0.01 ± 0.01 −0.02 to 0.05 0.518
Assessed limb Lower- vs upper-body 0.03 ± 0.25 −0.46 to 0.52 0.902
Prescription method %1-RM vs RM 1.02 ± 0.70 −0.35 to 2.40 0.145
Moderate vs low Year of publication 2002–2019 0.02 ± 0.05 −0.07 to 0.11 0.627
Experimental design Between- vs within-group −0.66 ± 0.86 −2.34 to 1.03 0.447
Sex Women vs men 0.70 ± 0.76 −0.80 to 2.19 0.360
Training status Untrained vs recreationally trained −1.15 ± 0.82 −2.76 to 0.46 0.161
Number of sessions 16–24 0.09 ± 0.04 0.0 1 to 0.16 0.031
Assessed limb Lower- vs upper-body −0.11 ± 0.31 −0.70 to 0.49 0.725
Prescription method
a
%1-RM vs RM ———
High vs moderate Year of publication 1996–2018 −0.03 ± 0.03 −0.09 to 0.03 0.342
Experimental design Between- vs within-group 0.36 ± 0.70 −1.00 to 1.74 0.604
Sex Women vs men 0.48 ± 0.66 −0.82 to 1.78 0.471
Training status Untrained vs recreationally trained 0.23 ± 0.65 −1.05 to 1.51 0.721
Number of sessions 16–33 0.08 ± 0.04 0.0 1 to 0.15 0.045
Assessed limb Lower- vs upper-body −0.14 ± 0.31 −0.74 to 0.46 0.651
Prescription method
a
%1-RM vs RM ———
Muscle strength
High vs low Year of publication 1982–2019 −0.11 ± 0.05 −0.20 to −0.15 0.023
Experimental design Between- vs within-group −0.47 ± 0.58 −1.60 to 0.66 0.411
Sex Women vs men 1.03 ± 0.50 0.06 to 2.00 0.037
Training status Untrained vs recreationally trained 0.73 ± 1.15 −1.53 to 3.00 0.526
Number of sessions 12–48 −0.01 ± 0.03 −0.06 to 0.04 0.715
Assessed limb Lower- vs upper-body 0.28 ± 0.45 −0.60 to 1.16 0.535
Prescription method %1-RM vs RM −1.79 ± 1.15 −4.05 to 0.47 0.121
Moderate vs low Year of publication 2002–2019 −0.06 ± 0.23 −0.52 to 0.39 0.787
Experimental design
a
Between- vs within-group ———
Sex Women vs men −0.95 ± 4.26 −9.30 to 7.40 0.823
Training status Untrained vs recreationally trained 1.65 ± 3.68 −5.56 to 8.86 0.654
Number of sessions 16–27 −0.08 ± 0.07 −0.23 to 0.06 0.263
Assessed limb Lower- vs upper-body −0.20 ± 0.49 −1.16 to 0.76 0.677
Prescription method %1-RM vs RM −2.34 ± 4.26 −10.7 to 6.01 0.583
High vs moderate Year of publication 2002–2017 0.04 ± 0.23 −0.40 to 0.48 0.848
Experimental design
a
Between- vs within-group ———
Sex Women vs men −1.99 ± 4.06 −9.94 to 5.98 0.625
Training status Untrained vs recreationally trained 0.91 ± 3.37 −5.70 to 7.53 0.786
Number of sessions 16–38 −0.07 ± 0.07 −0.20 to 0.06 0.283
Assessed limb Lower- vs upper-body −0.48 ± 0.53 −1.52 to 0.55 0.360
Prescription method %1-RM vs RM −1.02 ± 4.04 −8.95 to 6.90 0.800
Bold values are significant.
a
Collinearity detected given the insufficient number of observations.
%1-RM, percentage of 1-RM.
http://www.acsm-msse.org1212 Official Journal of the American College of Sports Medicine
APPLIED SCIENCES
successfully used such as RM zones and percentage of 1-RM,
where failure is not mandated but monitored to stay within a
training range. Therefore, although exercising until volitional
failure is not mandatory for neuromuscular adaptations (58,59),
it was the strategy required to compare the efficacy of different
resistance training load protocols (57).
Our findings are that performing as many repetitions as pos-
sible per set with different loads over relatively short interven-
tions leads to similar muscle hypertrophy in individuals with
none or moderate resistance training experience. It seems that
any training load can produce a similar magnitude of muscle
hypertrophy for different participants (men and women) and
muscles assessed (lower- and upper-body). Thus, over relatively
short training interventions in untrained or novice subjects, sets to
failure are one strategy for gaining muscle hypertrophy, regard-
less of the load undertaken in resistance training. With other strat-
egies, albeit beyond the scope of this review, if performed with a
load that activates a high percentage of motor units, hypertrophy
is likely to occur. However, it is important to note that the practi-
cal application may still favor the use of a lower number of rep-
etitions using moderate to high loads as the performance of low
loads until volitional failure results in higher discomfort due
to the higher number of repetitions, longer time under muscu-
lar tension, and time required (60).
As revealed by the meta-regression, muscle hypertrophy de-
rived from low-, moderate-, and high-load resistance training
regimes, despite the modest and nonsignificant difference
between them, seems to be affected by training status and
number of sessions completed, that is, volume. Untrained
participants exhibit a greater magnitude of muscle hypertro-
phy compared with those recreationally trained. As reported
in previous literature, trained muscles may already present
with an increased cross-sectional area (61) and lower anabolic
signaling as observed in reduced AMPK and Akt phosphory-
lation after a resistance training session (62), resulting inan at-
tenuated hypertrophic response in participants with previous
resistance training experience. However, our findings also in-
dicate greater muscle hypertrophy in recreationally trained
participants who undertake a higher number of sessions com-
pared with those undertaking less. It seems that participants
with longer experience in resistance training (range, 2–7yr)
(7,40,41,43,47,48,53), although still not highly trained, require
a higher volume of training to produce the same or greater hy-
pertrophic adaptation exhibiting the principle of diminishing
returns. Thus, although there were no differences between
training loads for muscle hypertrophy, the meta-regression re-
sults suggest that novice participants are likely to experience su-
perior gains than those with previous experience in resistance
FIGURE 4—SMD effects between low-, moderate-, andhigh-load resistance training performed until volitional failure on muscle strength. Overall and sub-
group analyses conducted with a network random-effects model. Gray and white circles represent study-specific estimates based on risk of bias assessment
(low risk, and some concern or high risk of bias, respectively); diamonds represent pooled estimates of random-effects meta-analysis.
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training undertaking the same volume, whereas a greater num-
ber of sessions may provide additional muscle hypertrophy for
those with experience in resistance training. Given the lack of
studies with more than 14-wk duration, any interpretation of
these results for longer periods should be viewed with caution.
In contrast to muscle hypertrophy, muscle strength, as de-
fined by 1-RM testing, was found to be dependent on high
loads. This finding is expected following 1) the principle of
specificity (13) as participants allocated in higher-load resis-
tance training groups trained more closely to the requirement
for the 1-RM test and presented greater transfer to this outcome,
and 2) a combination of both neural and skeletal muscle adap-
tations derived from higher-load resistance training programs
resultingingreatereffectsonmusclestrength(38,63–65).
Moreover, the magnitude of change in low- versus high-load re-
sistance training was consistent with that previously reported by
Schoenfeld et al. (9) and across all load comparisons favoring
the highest loads. Regarding the difference between moderate-
and high-load resistance, this comparison approached statistical
significance (P= 0.072), and the ES of ~0.3 suggests a possible
superior gain with high-load training protocols.
Interestingly, within the limitations of the relativepaucity of
training studies in which women were subjects, in the low-
versus high-load comparison, men derived greater muscle
strength benefits than women, whereas women improved their
strength more than men in comparisons involving moderate-load
training. These results may be related to sex differences in prior
experience with resistance training and perceived exertion with
resistance training sessions as previously suggested (66–68),
and possible discrepancies between the prescribed and complied
resistance training dosage (35). Moreover, the different time-
course adaptations between men and women may also account
for differential maximal strength gains over prolonged resistance
training periods (63,64). However, we are unable to confirm this
because of the short duration of the studies analyzed (ranging
from 6 to 12 wk), lack of training variables reported in the studies
undertaken by women (32,33,35–37,49–52), and the inability for
a more robust narrative concerning studies of longer duration that
did not make intensity comparisons in their designs (e.g., see Ref.
[69]). Regarding the year of publication as a covariate, this vari-
able was used because of the different results on muscle strength
between current (5,9) and past literatures (2,51). These differ-
ences are likely to be related to study design, conduct, and control
because well-designed studies tend to get smaller effects and re-
ducing bias over the years (70). The larger effect found in the
study by Anderson and Kearney (2) also seems to be explained
by the low-load resistance training prescription involving
more repetitions than any other study (Table S2, Supplemen-
tal Digital Content 2, characteristics of included studies,
http://links.lww.com/MSS/C234), driving the heterogeneity
and significance of this covariate in the muscle strength
model. Furthermore, omitting the studies with a high risk of
bias (2,42,51) also reduced the significance of this covariate
in the model.
The strengths of the present review, network meta-analysis,
and meta-regression are as follows: 1) a large number of studies
(n= 28) with up to 747 healthy adults; 2) a model involving
simultaneous comparison among low-, moderate-, and high-load
resistance training; and 3) methodological feasibility for com-
paring different resistance training loads (i.e., statistical transi-
tivity in the network meta-analysis model). In addition,
considering previous findings on this topic (9,19), the present
review also extends the results on muscle hypertrophy and
strength, taking into account different moderators of resistance
exercise response such as participants, training status, experi-
mental design, assessed outcomes, and training prescription
when different resistance training loads are undertaken until
volitional failure. However, the present study has some limita-
tions worthy ofcomment. First, studies included in the present
review were mostly of low quality because of concerns regard-
ing the randomization process and measurement of the out-
come. Nonetheless, we used a subgroup analysis involving
the “best-quality”studies to minimize such bias, and the re-
sults were maintained with minimal differences in the consis-
tency analysis. Second, the present investigation excluded
nonspecific muscle strength/performance measures such as
maximal voluntary contraction and muscle endurance due to
the variability in methods used to assess these outcomes and
relevance to our specified outcomes, which would have in-
creased the heterogeneity among studies. Therefore, our
results regarding muscle strength should not be extended
to nonspecific muscle strength tests such as isometric or
isokinetic muscle strength tests. Third, although recreationally
trained participants were included in our analyses, the strength
levels reported in the studies were relatively modest, and cer-
tainly, the present results cannot be extrapolated for highly
strength-trained individuals (e.g., bodybuilders, collegiate ath-
letes in structured and supervised strength and conditioning
programs, and power or strength athletes). Fourth, several
studies (4,5,33,37,38,43–45,50,52) have performed multiple
1-RM testing throughout the study duration (range, 3–5
times). This may also be considered an issue masking an even
greater difference between low- versus moderate- and
high-load resistance training programs because of the number
of exposures to maximal strength tests and the potential in-
creases in muscle strength not related to the intervention per
se (71). Fifth, the assessment of muscle size presents numer-
ous challenges when evaluating training effects with regard
to load, movement, range, and type of contraction, all
influencing regional hypertrophy and further complicated by
location of measurement, technology, and methodology (72).
Finally, the present investigation included mostly studies un-
dertaken in young adults (23.4 ± 2.9 yr) and should be
interpreted with caution when extrapolated to different popula-
tions, as exercising until volitional failure is not considered a
feasible resistance training prescription for all (73).
In summary, the present study explored the resistance
training dosage for muscle hypertrophy and strength in
healthy young adults. Our findings suggest that to promote
muscle hypertrophy, varying loads of resistance training
can be undertaken, and one strategy is to perform the exercise
to the point of volitional failure. However, other approaches for
http://www.acsm-msse.org1214 Official Journal of the American College of Sports Medicine
APPLIED SCIENCES
maximizing recruitment of the motor unit pool maybe as ef-
fective, without the issues described previously regarding
performing high numbers of repetitions with light loads.
Thus, a practical application of our results is that a
high-load resistance training program (≥80% of 1-RM, or
≤8 RM) can target both outcomes in shorter periods of train-
ing, whereas a moderate range of repetitions (9–15 RM)
should be part of the resistance training program for those
who do not tolerate exercising at higher (i.e., higher intensity
or higher resistance) loads, eliciting gains in muscle hypertro-
phy and muscle strength superior to a low-load program. Fur-
thermore, our results can also be applied to those participants
with experience in resistance training, indicating a superior
muscle hypertrophy effect undertaking more resistance train-
ing sessions.
P. L. is supported by the National Health and Medical Research
Council Centre of Research Excellence in Prostate Cancer Survivor-
ship Scholarship. D. A. G. and R. U. N. are funded by the National
Health and Medical Research Council Centre of Research Excellence
in Prostate Cancer Survivorship. The results of the study are presented
clearly, honestly, without fabrication, falsification,or inappropriate data
manipulation, and do notconstitute endorsement by the American Col-
lege of Sports Medicine.
The authors have no conflict of interest to declare.
Sponsors had no involvement in the study design, analysis or inter-
pretation of data, manuscript writing, and decision to submit the man-
uscript for publication.
Substantial contributions to the conception and design of the work
weredonebyP.L.,R.R.,D.R.T.,R.U.N.,D.A.G.,andR.S.P.Thework
draft and revision, as well as the approval of the final version, were done
byP.L.,R.R.,D.R.T.,R.U.N.,D.A.G.,G.S.T.,J.L.T.,W.J.K.,K.H.,and
R. S. P. In addition, all aspects of this work related to the accuracy or
integritywereensuredbyP.L.,R.R.,D.R.T.,R.U.N.,D.A.G.,G.S.T.,
J.L.T.,W.J.K.,K.H.,andR.S.P.
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