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A systematic review, meta-analysis and meta-regression of the effect of protein supplementation on resistance training-induced gains in muscle mass and strength in healthy adults

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Abstract

Objective We performed a systematic review, meta-analysis and meta-regression to determine if dietary protein supplementation augments resistance exercise training (RET)-induced gains in muscle mass and strength. Data sources A systematic search of Medline, Embase, CINAHL and SportDiscus. Eligibility criteria Only randomised controlled trials with RET ≥6 weeks in duration and dietary protein supplementation. Design Random-effects meta-analyses and meta-regressions with four a priori determined covariates. Two-phase break point analysis was used to determine the relationship between total protein intake and changes in fat-free mass (FFM). Results Data from 49 studies with 1863 participants showed that dietary protein supplementation significantly (all p<0.05) increased changes (means (95% CI)) in: strength—one-repetition-maximum (2.49 kg (0.64, 4.33)), FFM (0.30 kg (0.09, 0.52)) and muscle size—muscle fibre cross-sectional area (CSA; 310 µm² (51, 570)) and mid-femur CSA (7.2 mm² (0.20, 14.30)) during periods of prolonged RET. The impact of protein supplementation on gains in FFM was reduced with increasing age (−0.01 kg (−0.02,–0.00), p=0.002) and was more effective in resistance-trained individuals (0.75 kg (0.09, 1.40), p=0.03). Protein supplementation beyond total protein intakes of 1.62 g/kg/day resulted in no further RET-induced gains in FFM. Summary/conclusion Dietary protein supplementation significantly enhanced changes in muscle strength and size during prolonged RET in healthy adults. Increasing age reduces and training experience increases the efficacy of protein supplementation during RET. With protein supplementation, protein intakes at amounts greater than ~1.6 g/kg/day do not further contribute RET-induced gains in FFM.
1
Morton RW, etal. Br J Sports Med 2017;0:1–10. doi:10.1136/bjsports-2017-097608
ABSTRACT
Objective We performed a systematic review, meta-
analysis and meta-regression to determine if dietary
protein supplementation augments resistance exercise
training (RET)-induced gains in muscle mass and
strength.
Data sources A systematic search of Medline, Embase,
CINAHL and SportDiscus.
Eligibility criteria Only randomised controlled trials
with RET ≥6 weeks in duration and dietary protein
supplementation.
Design Random-effects meta-analyses and meta-
regressions with four a priori determined covariates. Two-
phase break point analysis was used to determine the
relationship between total protein intake and changes in
fat-free mass (FFM).
Results Data from 49 studies with 1863 participants
showed that dietary protein supplementation
significantly (all p<0.05) increased changes (means
(95% CI)) in: strength—one-repetition-maximum
(2.49 kg (0.64, 4.33)), FFM (0.30 kg (0.09, 0.52)) and
muscle size—muscle fibre cross-sectional area (CSA;
310 µm2 (51, 570)) and mid-femur CSA (7.2 mm2 (0.20,
14.30)) during periods of prolonged RET. The impact of
protein supplementation on gains in FFM was reduced
with increasing age (−0.01 kg (−0.02,–0.00), p=0.002)
and was more effective in resistance-trained individuals
(0.75 kg (0.09, 1.40), p=0.03). Protein supplementation
beyond total protein intakes of 1.62 g/kg/day resulted in
no further RET-induced gains in FFM.
Summary/conclusion Dietary protein supplementation
significantly enhanced changes in muscle strength and
size during prolonged RET in healthy adults. Increasing
age reduces and training experience increases the
efficacy of protein supplementation during RET. With
protein supplementation, protein intakes at amounts
greater than ~1.6 g/kg/day do not further contribute
RET-induced gains in FFM.
INTRODUCTION
Resistance exercise training (RET) in combination
with dietary protein supplementation is a common
practice, in athletes and recreational exercisers
alike, with the aim of enhancing RET-induced
gains in muscle mass and strength. Recognised as a
potent antisarcopenic stimulus, protein supplemen-
tation has also been advocated for ageing persons
participating in RET. Despite a large volume of
work in this area, narrative reviews1–5 and even
meta-analyses6–12 yield conflicting results as to the
actual effectiveness of protein supplementation to
enhance RET-mediated gains in muscle mass and
strength. This lack of agreement on the efficacy of
protein supplementation6–12 is likely due to the use
of divergent study inclusion criteria and inclusion
of subjects with differing: ages, training statuses,
total protein intakes, protein sources and protein
doses. Thus, an evidence-based answer to the main
question of the efficacy of protein supplementa-
tion, while previously reported,7 now appears to be
controversial.4
We conducted a meta-analysis that was more
inclusive in nature than previous meta-analyses6–12
to provide a broad, systematic and evidence-based
assessment on whether protein supplementation
can augment changes in relevant RET outcomes.
We used meta-regression to evaluate the impact
of important potentially mediating covariates that
were decided a priori to the meta-analysis. The
present meta-analysis includes more than double
the number of studies and participants than the
largest published comprehensive meta-analysis on
protein supplementation during RET to date.7ST1
We also undertook an additional rational, mech-
anism-based analysis that had the aim of answering
the following question: is there a protein intake
beyond which protein supplementation ceases to
provide a measurable benefit in increasing muscle
mass during RET? To answer this question, we
recognised that the process of muscle protein
synthesis (MPS), as the primary determinant of
muscle hypertrophy,13 shows a saturable dose-re-
sponse relationship with increasing protein intake.14
Since measures of MPS show good agreement with
hypertrophy13 we theorised that the effect of daily
protein intake on RET-induced changes in muscle
mass would show a dose-responsive relationship
but that this would ultimately plateau.
METHODS
Inclusion criteria
Any randomised controlled trials (RCTs) that
combined a RET and protein supplement interven-
tion were considered for this meta-analysis. Trials
had to be at least six weeks in duration, participants
A systematic review, meta-analysis and meta-
regression of the effect of protein supplementation
on resistance training-induced gains in muscle mass
and strength in healthyadults
Robert W Morton,1 Kevin T Murphy,1 Sean R McKellar,1 Brad J Schoenfeld,2
Menno Henselmans,3 Eric Helms,4 Alan A Aragon,5 Michaela C Devries,6
Laura Banfield,7 James W Krieger,8 Stuart M Phillips1
Review
To cite: MortonRW,
MurphyKT, McKellarSR, etal.
Br J Sports Med Published
Online First: [please include
Day Month Year]. doi:10.1136/
bjsports-2017-097608
Additional material is
published online only. To view
please visit the journal online
(http:// dx. doi. org/ 10. 1136/
bjsports- 2017- 097608).
1Department of Kinesiology,
McMaster University, Hamilton,
Canada
2Department of Health Sciences,
Lehman College of CUNY,
Bronx, New York, USA
3Bayesian Bodybuilding,
Gorinchem, Netherlands
4Sport Performance Research
Institute New Zealand, AUT
University, Auckland, New
Zealand
5California State University,
Northridge, California, USA
6Department of Kinesiology,
University of Waterloo, Waterloo,
Canada
7Health Sciences Library,
McMaster University, Hamilton,
Canada
8Weightology, LLC, Issaquah,
Washington, USA
Correspondence to
Dr Stuart M Phillips, Department
of Kinesiology, McMaster
University, 1280 Main Street,
West Hamilton, Ontario,
Canada; phillis@ mcmaster. ca
Accepted 31 May 2017
BJSM Online First, published on July 11, 2017 as 10.1136/bjsports-2017-097608
Copyright Article author (or their employer) 2017. Produced by BMJ Publishing Group Ltd under licence.
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2Morton RW, etal. Br J Sports Med 2017;0:1–10. doi:10.1136/bjsports-2017-097608
Review
had to be performing RET at least twice per week, and at least
one group had to be given a protein supplement that was not
co-ingested with other potentially hypertrophic agents (eg,
creatine, β-HMB, or testosterone-enhancing compounds). Only
trials with humans who were healthy and not energy-restricted
were accepted. Manuscripts had to be original research (not a
review or conference abstract) and be written in English.
Search strategy
A systematic search of the literature was conducted (LB) in
Medline, Embase, CINAHL and SportDiscus, current to January
2017 (see online supplementary appendix 1). As appropriate,
a combination of keywords and subject headings was used for
the following concepts: protein supplementation and resistance
training or muscle strength. The original search yielded 3056
studies. Any overlooked trials were identified by consulting
other reviews and meta-analyses on the subject and were added
in manually (17 studies). After deduplication and screening
for inclusion criteria, 155 articles were independently read/
reviewed by three authors (RWM, KTM and SRM). A total of 49
RCTs were selected for inclusion in this meta-analysis (figure 1).
Data extraction
Predetermined relevant variables from each included study
were gathered independently by three investigators (RWM,
KTM and SRM). Relevant variables included those regarding
the study design, details of the RET intervention, partici-
pant characteristics, protein supplement information, placebo/
control information, performance outcomes, body composi-
tion outcomes and any other notable information (eg, sources
of bias/conflict of interest). Where data were not presented
in table or text and authors could not be reached, data were
extracted using WebPlotDigitizer (Web Plot Digitizer, V.3.11.
Texas, USA: Ankit Rohatgi, 2017) or calculated from base-
line values and/or percentage change. Where there were any
discrepancies between the three reviewers the manuscripts were
revisited by all reviewers (RWM, KTM and SRM) and agreed
on by discussion. We also conducted a post hoc reassessment
Figure 1 PRISMA flow chart.
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Morton RW, etal. Br J Sports Med 2017;0:1–10. doi:10.1136/bjsports-2017-097608
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of 10 randomly selected studies and compared the extracted
results.15 Coder drift was <10% in all cases for each investigator
and inter-rater (RWM, KTM and SRM) reliability was excellent
(>95%).
A total of 58 different body composition and 66 perfor-
mance outcomes were extracted from the final 49 studies.16–64
Primary outcomes were limited and amalgamated to include two
different performance outcomes and four different body compo-
sition outcomes based on those most commonly reported in the
49 RCTs. Performance outcomes were: one-repetition-max-
imum strength (1RM; measured by any 1RM strength test) and
maximum voluntary contraction (MVC; measured by both isoki-
netic and/or isometric contractions using a dynamometer with
any muscle group/action). Body anthropometric and composi-
tion outcomes included: total body mass (TBM; measured by
any scale); fat-free mass (FFM) and bone-free mass (or lean mass
if FFM was not available; FFM; measured by dual-energy X-ray
absorptiometry (DXA), hydrodensitometry, or whole-body air
plethysmography (BodPod) ); fat mass (FM; measured by DXA,
hydrodensitometry and/or BodPod); muscle fibre cross-sec-
tional area (CSA;measured in any fibre subtype (I, IIa, and/or
IIx) obtained from either vastus lateralis and/or latissimus dorsi
biopsies using microscopy); and mid-femur whole muscle CSA
(mid-femur CSA, measured by MRI and/or CT).
Data syntheses
When data were reported in different units (eg, pounds vs kilo-
grams) the data were converted to metric units. In all analyses
the comparator group received an identical RET intervention
but was non-supplemented or placebo-supplemented. If a study
included a protein-supplemented group, a non-supplemented
control group and a placebo-supplemented control group that
were all part of the RET intervention, the protein-supplemented
and placebo-supplemented groups were retrieved. If a study had
multiple time points, only the preintervention and postinterven-
tion outcomes were retrieved. Where the change in SD (ΔSD)
was available it was collected alongside the preintervention and
postintervention SD. Where ΔSD was not reported, the correla-
tion coefficient (corr) for each primary outcome was calculated
according to the Cochrane Handbook for Systematic Reviews
of Interventions:65 corr = (SDpre
2 + ΔSDpost
2 SDchange
2) / (2 ×
SDpre× SDpost) and the ΔSD was then calculated as:
ΔSD = (SDpre
2
+ ΔSDpost
2 – 2 × corr × SDpre× SDpost).
The change in mean (ΔMean) and ΔSD were calculated for
each condition and uploaded to RevMan (Review Manager
(RevMan), V.5.3. Copenhagen: The Nordic Cochrane Centre,
The Cochrane Collaboration, 2014). Where studies had more
than one protein-supplemented group (eg, soy and whey),
measure of MVC (eg, isokinetic and isometric) or measure of
1RM (eg, bench press and leg press) the ΔMean and ΔSD were
independently calculated and later combined, unless other-
wise stated, using the RevMan calculator (Review Manager
(RevMan), V.5.3. Copenhagen: The Nordic Cochrane Centre,
The Cochrane Collaboration, 2014).
Meta-analyses
Random-effects meta-analyses were performed in RevMan
(Review Manager (RevMan), V.5.3. Copenhagen: The Nordic
Cochrane Centre, The Cochrane Collaboration, 2014) on the
change in each outcome. Effect sizes are presented as mean
difference (MD) with means±SD and 95% CIs for 1RM, TBM,
FFM, FM, fibre CSA and mid-femur CSA and as standardised
mean difference (SMD) and 95% CIs for MVC because it had
multiple outcomes presented on non-comparable scales (eg, N
and Nm).
Heterogeneity and risk of bias
Heterogeneity was assessed by χ2 and I2 and significance was set
at p<0.05. The internal validity of each study was determined
by domain-based evaluation to quantify risk of bias for each
study65 and was independently performed by three investigators
(RWM, KTM and SRM). The data included in the meta-analyses
were restricted to studies with less than three reported high or
unclear risk domains (predominately due to reported conflicts
of interest and lack of blinding investigators and/or participants;
(see online supplementary appendix 2)). Funnel plots were visu-
ally inspected to determine publication bias. Multiple sensitivity
analyses were performed to determine if any of the results were
influenced by the studies that were removed.
Meta-regression
In an effort to understand the sources of heterogeneity meta-re-
gressions were performed on 1RM, FFM and fibre CSA because
they were statistically significant, had considerable unexplained
heterogeneity (I2) and had a sufficient number of studies (≥10).
Meta-regression was used instead of subgroup analyses to allow
for the use of continuous covariates and to allow for the inclu-
sion of more than one covariate at a time. Four covariates were
chosen a priori to be included in our meta-regression: baseline
protein intake (g/kg/day), postexercise protein dose (g), chrono-
logical age and training status because there is evidence that
baseline protein intake,66 protein dose,14 age67 and training
status68 could influence the efficacy of protein supplementa-
tion; summarised here.4 5 These covariates were meta-regressed
individually and together in a random-effects meta-regression
model using Stata (StataCorp. 2011. Stata Statistical Software:
Release 12. College Station, Texas, USA). The random-effects
meta-regression used residual restricted maximum likelihood
to measure between-study variance (τ2) with a Knapp-Hartung
modification as recommended.69 When all four covariates were
analysed together permutation tests were performed (n=1000)
to address the issue of multiple testing by calculating adjusted
p values.70 Additional covariates were identified and individually
analysed post hoc to further explore the unexplained variance of
the effect of protein supplementation during RET on changes in
1RM and FFM. Continuous covariates were: MD in the change
in protein intake (g/day), MD in the total relative protein intake
(g/kg/day), number of repetitions/set, number of sets/exercise,
number of exercises/session, number of sessions/week, number
of weeks and total RET volume in kg: repetitions/set × sets/exer-
cise × exercises/session × sessions/week × intervention duration
in weeks. Categorical variables were: protein supplement source
(whey vs soy), sex (male vs female), type (dietary-supplement
vs RET-supplement), whole-body RET (whole-body RET vs
not whole-body RET) and RET supervision (supervised vs not
supervised). Protein supplement source was limited to soy and
whey because there were few study groups that were provided
either a casein (n=321 59 60;) or pea (n=122;) protein supplement
exclusively.
Subgroup analyses
Subgroup analyses were performed in RevMan (Review Manager
(RevMan), V.5.3. Copenhagen: The Nordic Cochrane Centre,
The Cochrane Collaboration, 2014). Subgroup analyses were
performed on changes in FFM and 1RM with training status
(untrained vs trained) as the subgroup to generate forest plots
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and neatly present training status as a categorical variable.
Subgroup analyses were also performed on changes in FFM with
age categorised into subgroups (old (>45 years) and young (<45
years)) to be presented below for the interested reader.
Breakpoint analysis
To investigate the influence of protein intake as a continuous vari-
able on individual study arms (as opposed being limited to MDs
between groups in a meta-regression) linear and segmental regres-
sions on the change in FFM (measured by DXA) were plotted
against daily and baseline protein intake. Linear and segmental
regressions were performed using GraphPad Prism (V.6, GraphPad
Software, La Jolla, California, USA) to determine models of best fit
as has been previously done in acute tracer trials measuring MPS.14
Where segmental regression was the preferred model the slope
of the second line was set to zero to determine the break point
(biphasic regression). Each group from each study that presented
daily or baseline protein intake with changes in FFM from DXA
was included. Significance was set at p<0.05 and data for the
break point is presented as mean (95% CI).
RESULTS
Participant characteristics
Participant details and outcomes are presented elsewhere
(see online supplementary table 1. A total of 49 studies from
17 countries met the inclusion criteria (figure 1). There were 10
studies in resistance-trained participants and 14 study groups in
exclusively female participants. Publications ranged from 1962
to 2016. There was a total of 1863 participants (mean±SD;
35±20 years).
RETcharacteristics
The RET characteristics are also presented elsewhere
(see online supplementary table 1). The RET interventions
lasted from 6 weeks to 52 weeks (13±8 weeks) performing
RET between 2 days and 5 days per week (3±1 days/week) with
between 1 to 14 exercises per session (7±3 exercises/session),
1 to 12 sets per exercise (4±2 sets/exercise) and anywhere
between 3 to 25 repetitions per set (9±4 repetitions/set). Four
studies used just lower-body RET, two studies used just knee
extensor RET, one study used elbow flexor RET only, and two
studies used one lower-body and one upper-body exercise only.
Protein supplementation
Details regarding the experimental (protein supplementation)
and control (placebo- or no-supplement) groups are presented
elsewhere (see online supplementary table 2). A range of 4 g to
106 g of protein was supplemented per day to the protein
group (36±30 g/day; young: 42±32 g/day; old: 20±18 g/day)
with a range of 5 g to 44 g of protein supplemented postexer-
cise on training days (24±11 g; young: 24±12 g; old: 23±10
g). Twenty-three conditions supplemented with whey protein,
3 with casein protein, 6 with soy protein, 1 with pea protein, 10
with milk or milk protein, 7 with whole food (eg, beef, yogurt,
between-meal snack) and 13 with non-specific protein blends or
blends containing multiple protein sources (eg, whey, casein, soy
and egg). In 40 studies the participants consumed part or all
of their daily protein supplement after their RET sessions. In
36 studies with 48 different conditions authors reported either
total (g/day) or relative (g/kg/day or %kcal/day) daily protein
intake preintervention and/or postintervention. There was an
increase in daily protein intake in the protein group (mean±SD;
range: 23±41 g/day; −25 g/day to 158 g/day; p=0.004) and no
change in the control group (1±14 g/day; −17 g/day to 40 g/
day; p=0.83) such that the change in daily protein intake was
significantly greater in the protein group (p=0.01). Relative
daily protein intake (g/kg/day) increased in the protein group
(pre: 1.4±0.4, post: 1.8±0.7, Δ: 0.3±0.5 g/kg/day, p=0.002)
and did not change in the control group (pre: 1.4±0.3, post:
1.3±0.3, Δ: −0.02±0.1 g/kg/day, p=0.48) such that there was
a greater change in the protein group (p<0.001). Daily energy
intake (kcal/day) was gathered from 23 studies with 29 condi-
tions and did not change with the prolonged RET and protein
supplementation nor was it significantly different between the
protein or control groups (Δ protein group: 50±293 kcal/day, Δ
control group: 70±231 kcal/day, p=0.71).
Heterogeneity and risk of bias
Significant heterogeneity was found for changes in 1RM
(χ2=53.49, I2=33%, p=0.003) and fibre CSA (χ2=30.97,
I2=68%, p=0.0006). Nine studies were removed based on risk of
bias17 18 25 26 50 63 (see online supplementary appendix 2) or publi-
cation bias assessment24 32 64 (see online supplementary figure 1).
In particular, four studies were removed from 1RM,17 26 32 50 four
from TBM,17 18 63 64 three from FM,17 18 63 five from FFM,17 18 24 63
64 three from MVC25 26 50 and one from fibre CSA.50
Sensitivity analyses
Sensitivity analysis was performed with the nine high-risk studies
mentioned above included in the outcomes they were removed
from to determine if their removal changed any of the results. The
inclusion of those studies did not influence the difference in means
or significance in 1RM, TBM, FFM or mid-femur CSA; however,
when Mitchell et al50 was included in the fibre CSA assessment
the effect of protein supplementation (310 µm2 (51, 570), p=0.02)
was eliminated (153 µm2 (−137, 443), p=0.30). This is likely
due to the small number of studies that included muscle biopsies
but may warrant caution when interpreting the effect of protein
supplementation on changes fibre CSA during RET. In no instance
did fixed-effect meta-analysis deliver a different magnitude of
effect or significance compared with random-effect meta-analysis.
Meta-analyses
Protein supplementation during prolonged RET significantly
improved gains in 1RM strength (MD: 2.49 kg (0.64, 4.33),
p=0.01; figure 2) but had no effect on MVC (SMD: 0.04
(-0.09, 0.16), p=0.54). Protein supplementation did not have
a significant effect on changes in TBM (MD: 0.11 kg (−0.23,
0.46), p=0.52) but improved changes in FFM (MD: 0.30 kg
(0.09, 0.52), p=0.007; figure 3), FM (MD: −0.41 kg (−0.70,–
0.13), p=0.005), fibre CSA (MD: 310 µm2 (51, 570), p=0.02;
see online supplementary figure 2: panel A) and mid-femur CSA
(MD: 7.2 mm2 (0.20, 14.30), p=0.04; see online supplementary
figure 2: panel B) during prolonged RET.
Meta-regression.
The results from the full model meta-regressions are presented in
table 1. When combined, baseline protein intake, protein dose,
age and training status did not explain any of the variance in the
changes in 1RM (15 studies, 1216 subjects, p=0.77) or FFM (15
studies, 642 participants, p=0.12). There were insufficient obser-
vations (<10) when all covariates were compared with the changes
in fibre CSA.
Univariate meta-regressions on changes in 1RM and FFM
following prolonged RET are also presented in table 1. None
of our covariates explained any of the heterogeneity of protein
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supplementation’s effect on changes in 1RM: baseline protein
intake (21 studies, 814 participants, p=0.59), age (27 studies,
802 participants, p=0.78), training status (28 studies, 858 partic-
ipants, p=0.40) and post-exercise protein dose (23 studies, 589
participants, p=0.13). In contrast, when the ability of protein
supplementation to affect changes in FFM was evaluated with
univariate meta-regressions, the postexercise protein dose was
the only covariate that did not influence the efficacy of protein
supplementation on changes in FFM (20 studies, 793 participants,
p=0.25) whereas baseline protein intake (22 studies, 988 partic-
ipants, p=0.045; see online supplementary figure 3: panel A),
age (25 studies, 1033 participants, p=0.02; figure 4) and training
status (26 studies, 1089 participants, p=0.03) all influenced the
effect of protein supplementation. When the effect of protein
supplementation on changes in FFM was evaluated with age strat-
ified into two subgroups the difference between old (>45; 67±7
years; MD: 0.06 (-0.14, 0.26)) and young (<45; 24±4 years; MD:
0.55 (0.30, 0.81)) participants remained significant (χ2=8.71,
I2=89%, p=0.003). There were no covariates that explained any
of the variance in the change in fibre CSA following RET: age
(10 studies, 474 participants, I2=65%, Adj. R2=-3%, p=0.50),
baseline protein intake (8studies, 384 participants, I2=43%, Adj.
R2=-44%, p=0.84), postexercise protein dose (10 studies, 270
participants, I2=77%, Adj. R2=-38%, p=0.92) and training status
(11 studies, 586 participants, I2=71%, Adj. R2=-24%, p=0.94).
Additional univariate meta-regressions are presented in else-
where (see online supplementary table 3). Only whether the RET
was whole-body (27 studies, including only 4 studies that were not
whole-body RET, I2=2%, Adj. R2=76%, p=0.01) or supervised
(28 studies, I2=5%, Adj. R2=58%, p=0.047) explained part of
the variance in the effectiveness of protein supplementation on
changes in 1RM. No other covariates explained any of the variance
associated with the efficacy of protein supplementation on changes
in 1RM or FFM.
Breakpoint analysis
Biphasic regression (42 study arms, 723 participants) explained
more variation than a linear regression between the change in
Figure 2 Forest plot of the results from a random-effects meta-analysis shown as mean difference with 95% CIs on one-repetition-maximum (1RM;
kg) in untrained and trained participants. For each study, the circle represents the mean difference of the intervention effect with the horizontal line
intersecting it as the lower and upper limits of the 95% CI. The size of each circle is indicative of the relative weight that study carried in the meta-
analysis. The rhombi represent the weighted untrained, trained and total group’s mean difference. Total: 2.49 kg (0.64, 4.33), p=0.01, untrained:
0.99 kg (−0.27, 2.25), p=0.12 and trained: 4.27 kg (0.61, 7.94), p=0.02.
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Figure 3 Forest plot of the results from a random-effects meta-analysis shown as mean difference with 95% CIs on lean or fat-free mass (FFM;
kg) in untrained and trained participants. For each study, the circle represents the mean difference of the intervention effect with the horizontal
line intersecting it as the lower and upper limits of the 95% CI. The size of each circle represents the relative weight that study carried in the meta-
analysis. The rhombi represent the weighted untrained, trained and total group’s mean difference. Total: 0.30 kg (0.09, 0.52) p=0.007, untrained:
0.15 kg (−0.02, 0.31), p=0.08 and trained: 1.05 kg (0.61, 1.50), p<0.0001.
Table 1 Meta-regression output.
Model N
1RM (kg) Fat-free mass(kg)
Coeff. (95% CI) τ2Adj. R2I2pValue N Coeff. (95% CI) τ2Adj. R2I2pValue
No covariates 28 2.49 (0.64 to 4.33) 6.05 33% 0.01 27 0.30 (0.09 to 0.52) 0.05 7% <0.01
Univariate
Baseline protein intake 21 2.85 (-8.15to 13.84) 7.82 1% 37% 0.59 22 0.64 (0.02 to 1.27) 0 100% 0% 0.045
Protein dose 23 0.13 (-0.04to 0.31) 3.16 40% 0% 0.13 20 0.02 (-0.01to 0.04) 0.09 0% 0% 0.25
Age 27 0.01 (-0.09to 0.11) 6.51 −9% 34% 0.78 25 −0.01 (-0.02 to 0.00) 0 100% 0% 0.02
Training status 28 5.77 (-2.96to 7.13) 5.77 5% 31% 0.40 26 0.75 (0.09 to 1.40) 0.03 49% 0% 0.03
All covariates 15 5.36 10% 0% 0.77 15 0 100% 0% 0.12
Baseline protein intake 15 6.40 (-11.62to 24.42) 0.43 15 −0.57 (-2.50to 1.37) 0.95
Protein dose 15 0.05 (-0.78to 0.88) 0.70 15 −0.01 (-0.07to 0.06) 0.99
Age 15 0.07 (-0.18to 0.33) 0.23 15 −0.01 (-0.02to 0.00) 0.19
Training status 15 −2.81 (-20.80to 15.17) 0.63 15 1.19 (-1.34to 2.19) 0.48
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FFM and daily protein intake (break point=1.62 (1.03, 2.20)
g/kg/day, slope=1.75, R2=0.19, df=36) and is presented as
a segmental regression despite not being statistically signifi-
cant (p=0.079;figure 5) When plotting the change in FFM
against baseline protein intake, linear regressions explained
significantly more variance than biphasic regressions in both
young (slope=−1.54 g/kg/day, R2=0.17, df=34) and old
(slope=0.16 g/kg/day, R2=0.04, df=14) participants with a
statistically significant difference between age groups (p=0.042;
see online supplementary figure 3: panel D).
DISCUSSION
This is the largest meta-analysis on interventions including
dietary protein supplementation with muscle and strength-re-
lated outcomes during prolonged RET to date. Our main
finding was that dietary protein supplementation augmented
RET-induced increases in 1RM strength (figure 2) and FFM
(figure 3). For changes in FFM, dietary protein supplementation
was more effective in resistance-trained individuals (table 1 and
figure 3), less effective with increasing chronological age (table 1
and figure 4) and did not increase beyond total protein intakes
of ~1.6 g/kg/day (figure 5). Our data show dietary protein
supplementation is both sufficient and necessary to optimise
RET adaptations in muscle mass and strength.
Previous meta-analyses6–12 have reached varying conclusions
when examining the impact of protein supplementation on
changes in lean mass or FFM and 1RM strength during RET. The
discrepancies are likely a consequence of differing study inclusion
criteria. For example, previous meta-analyses have included only
trained participants,8 only older adults,9 11 supplements containing
more than just protein,8 10 only one source of protein,8 12 shorter
RET interventions,10 12 frail/sarcopenic participants7 9 11 and/or
participants who were energy-restricted.6 7 12 Previously, the largest
comprehensive meta-analysis to date on protein supplementation
during RET included 22 studies and 680 participants7 and did
show a significant effect of protein supplementation on RET-stim-
ulated gains in strength and FFM. In agreement with this previous
report,7 and strengthening the conclusion of that same report by
including 49 studies and 1863 participants, we show that protein
supplementation augmented gains in FFM and strength with RET.
Strength
The average RET-induced increase, with all measures of 1RM
included, was 27 kg (mean±SD ; 27±22 kg22 32). Notably,
dietary protein supplementation augmented the increase in 1RM
strength by 2.49 kg (9%; figure 2;Figure 2 see online supple-
mentary figure 4), which strongly suggests that the practice of
RET is a far more potent stimulus for increasing muscle strength
than the addition of dietary protein supplementation. None of
our covariates (age, training status, postexercise protein dose or
baseline protein intake) influenced the efficacy of protein supple-
mentation on changes in 1RM strength. Improving performance
of a specific task (eg, the 1RM of an exercise) is predominately
determined by the practice of that task.71 Though protein supple-
mentation may slightly augment changes in 1RM (~9%), which
may be important for those competing in powerlifting or weight-
lifting, it is pragmatic to advocate that if an increase in 1RM is
the objective of an RET programme, a sufficient amount of work
and practice at or around the 1RM is far more influential than
protein supplementation.
Muscle mass
In addition to increasing changes in muscle strength, RET alone
(≥6; 13±8 weeks) resulted in an increase in FFM (1.1±1.2 kg ),
an increase in fibre CSA (808±) and an increase in mid-femur
CSA (52±30 mm239 65). Dietary protein supplementation
augmented the increase in FFM by 0.30 kg (27%; Figure 3;
see online supplementary figure 4), fibre CSA by 310 µm2 (38%;
see online supplementary figure 1: Panel A) and mid-femur CSA
by 7.2 mm2 (14%; see online supplementary figure 1: panel
B). The postexercise protein dose did not affect the efficacy
of protein supplementation on RET-induced changes in FFM
whereas training status (positive), age (negative) and baseline
protein intake (positive) did. Relative to untrained participants,
resistance-trained participants have a smaller potential for
muscle growth72 and an attenuated postexercise muscle protein
turnover.73 As a result, we speculate that trained persons may
have less ‘degrees of freedom’ to change with RET and therefore
have a greater need for protein supplementation to see increases
in muscle mass. Our thesis is supported by the observation of
a more consistent impact of protein supplementation on gains
Figure 4 Random-effects univariate meta-regression between age
and the mean difference in fat-free mass (FFM) between groups.
Each circle represents a study and the size of the circle reflects the
influence of that study on the model (inversely proportionate to the SE
of that study). The regression prediction is represented by the solid line
(−0.01 kg (−0.02,–0.00), p=0.02).
Figure 5 Segmental linear regression between relative total protein
intake (g/kg body mass/day) and the change in fat-free mass (ΔFFM)
measured by dual energy X-ray absorptiometry. Each circle represents a
single group from a study. Dashed arrow indicates the breakpoint=1.62
g protein/kg/day, p=0.079. Solid arrow indicates 95% CI, (1.03to 2.20).
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in FFM in resistance-trained individuals than in novice trainees
(figure 3).
Older individuals are anabolically resistant74 and require
higher per-meal protein doses to achieve similar rates of MPS,
the primary variable regulating changes in skeletal muscle
mass,75 compared with younger participants.14 The average
supplemental daily protein dose given to older participants was
surprisingly low (20±18 g/day); thus, it is perhaps not surprising
that we did not find that older individuals were responsive to
protein supplementation (Figure 4). Though age did not affect
the RET-induced change in fibre CSA, the negative effect age
had on changes in FFM leads us to speculate that even though
exercise sensitises muscle to the effect of protein ingestion,3
older persons have an increased need for higher protein intakes
to optimally respond to this effect and see gains in FFM.76
It has been theorised that the increased deviation from normal
protein intake (g/kg/day) will positively affect the RET-induced
gains in FFM.77 Contrary to this thesis, we found that a higher
prestudy protein intake actually resulted in a greater effect of
protein supplementation on changes in FFM (table 1); however,
this was likely driven by the lower mean baseline protein intake
(old: 1.2±0.2 g/kg/day, young: 1.5±0.4 g/kg/day) and daily
protein dose (old: 20±18 g/day, young: 42±32 g/day) in the
studies that included older participants (see online supplemen-
tary figure 3: panel B and D). Indeed, a sensitivity analysis that
did not include older (>45; 65±14 years) versus younger (<45;
24±4 years) individuals found that baseline protein intake had
no effect on the efficacy of protein supplementation in young
individuals (see online supplementary figure 3, panel C). In an
unadjusted meta-regression analysis, a higher baseline protein
intake in young individuals actually attenuated the change in
FFM (see online supplementary figure 3, panel D).
A goal of this meta-analysis was to deliver evidence-based recom-
mendations that could be readily translated. A crucial point is that
even though the mean baseline protein intake for the 1863 partic-
ipants was ~1.4 g protein/kg/day, which is 75% greater than the
current US/Canadian recommended dietary allowance (RDA),78
an average supplementation of ~35 g protein/day still augmented
RET-stimulated gain in FFM (figure 3) and 1RM strength
(figure 2). Thus, consuming protein at the RDA of 0.8 g protein/
kg/day appears insufficient for those who have the goal of gaining
greater strength and FFM with RET. This conclusion is emphasised
for older men79 and women80 81 wishing to obtain strength and
gain lean mass with RET and protein supplementation.
A recent retrospective analysis showed a ‘breakpoint’ for the
stimulation of MPS when ingesting an isolated protein source at
0.24 g protein/kg and 0.40 g protein/kg in younger and older
participants, respectively.14 Given the observation of a dose-re-
sponsive relationship between protein intake and MPS82–85 and
the fact that MPS is aligned with muscle hypertrophy,13 we
elected to use an identical two-segment regression approach
between total daily protein intake and changes in FFM (figure 5)
as has been done for changes in protein dose and MPS.14 Here
we provide significant insight (using 42 study arms including 723
young and old participants with protein intakes ranging from 0.9
g protein/kg/day to 2.4 g protein/kg/day) by reporting an unad-
justed plateau in RET-induced gains in FFM at 1.62 g protein/kg/
day (95% CI: 1.03 to 2.20). These results are largely in congru-
ence with previous narrative reviews that comment on the
optimal nutritional strategies to augment skeletal muscle adapta-
tion during RET.3 86 Given that the CI of this estimate spanned
from 1.03 to 2.20, it may be prudent to recommend ~2.2 g
protein/kg/d for those seeking to maximise resistance train-
ing-induced gains in FFM. Though we acknowledge that there
are limitations to this approach, we propose that these findings
are based on reasonable evidence and theory and provide a prag-
matic estimate with an incumbent error that the reader could
take into consideration.
Although the present analysis provides important and novel
data, there are limitations that we acknowledge. First, the lack of
RET research in older individuals has led to inconclusive recom-
mendations from previous meta-analyses specifically focusing on
older individuals.9 11 Indeed, in this manuscript there were only
13 studies that met our inclusion criteria in older (>45 years)
individuals and only six of those studies reported baseline protein
intakes with changes in FFM. In addition, only four studies27 29
33 45 in older individuals had participants that consumed what
we consider to be close to optimal total protein intake (~1.2 g/
kg/day to 1.6 g/kg/day) in non-exercising adults5 during or postin-
tervention provided. Furthermore, only two studies23 30 in older
individuals provided a postexercise supplemental protein dose that
we consider to be close to optimal (~35–40 g) to stimulate FFM
accretion in elderly individuals.76 Given that older adults require
more protein per day,79–81 consume less protein per day87 and that
dietary protein ingestion and RET are effective strategies to main-
tain muscle mass and function with age,67 future RET research
should focus on using higher protein doses (or potentially higher
leucine), larger sample sizes and longer interventions in ageing
populations. Second, we included a variety of additional covari-
ates into univariate meta-regressions to elucidate the variables that
may modify whether protein supplementation affects RET-induced
changes in muscle mass and strength. Such an approach is gener-
ally considered to be hypothesis generating. The only significant
findings we found were that if the RET sessions were whole-body
(adjusted R2=76%, p=0.01) or supervised (adjusted R2=58%,
p=0.047), protein supplementation was more effective at
augmenting changes in 1RM. No variable affected changes in FFM
(see online supplementary table 3). Given the relatively small effect
that protein supplementation has on changes in FFM and 1RM,
clearly other variables as a component of RET programmes are of
much greater importance. Our meta-analyses also only included
studies with participants that were at or above their energy require-
ments, which may have omitted the significant impact protein has
during periods of weight loss with RET.88 Lastly, we found that
the postexercise protein dose did not affect the efficacy of protein
supplementation on RET-induced changes in FFM. Our analysis,
and those from others,6 leads us to conclude that the specifics of
protein supplementation (eg, timing, postexercise protein dose or
protein source) play a minor, if any, role in determining RET-in-
duced gains in FFM and strength over a period of weeks. Instead,
our results indicate that a daily protein intake of ~1.6 g/kg/day,
separated into ~0.25 g/kg doses,14 is more influential on adaptive
changes with RET, at least for younger individuals.
CONCLUSION
Dietary protein supplementation augments changes in muscle
mass and strength during prolonged RET. Protein supple-
mentation is more effective at improving FFM in young or
resistance-trained individuals than in older or untrained individ-
uals. Protein supplementation is sufficient at ~1.6 g/kg/day in
healthy adults during RET. Based on limited data we observed no
overtly apparent sex-based differences but acknowledge that far
less work has been done in women than men. This analysis shows
that dietary protein supplementation can be, if protein intake
is less than 1.6 g protein/kg/day, both sufficient and necessary
to optimise RET-induced changes in FFM and 1RM strength.
However, performance of RET alone is the much more potent
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Morton RW, etal. Br J Sports Med 2017;0:1–10. doi:10.1136/bjsports-2017-097608
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stimulus, accounting, at least according to this meta-analysis, for
a substantially greater portion of the variance in RET-induced
gains in muscle mass and strength.
Summarybox
Background
There is no consensus on the efficacy of protein
supplementation during prolonged resistance exercise
training(RET).
Novel findings
Dietary protein supplementation augments changes in
fat-free mass (FFM, (0.30 kg (0.09, 0.52), p=0.007) and
one-repetition-maximum strength (2.49 kg (0.64, 4.33),
p=0.01) during prolonged RET.
Dietary protein supplementation during RET is more
effective at increasing changes in FFM in resistance-trained
individuals (0.75 kg (0.09, 1.40), p=0.03) and less effective
in older individuals (−0.01 kg (−0.02,–0.00), p=0.02).
Protein supplementation beyond a total daily protein intake
of~1.6 g/kg/day during RET provided no further benefit on
gains in muscle mass or strength.
Acknowledgements SMP thanksthe Canada Research Chairs, Canadian Institutes
for Health Research, and the Natural Science and Engineering Research Council of
Canada for their support during the completion of this work.
Contributors RWM, BJS, MH, EH, AAA, MCD, JWK and SMP contributed to the
conception and design of the study. RWM, BJS, MH, EH, AAA, MCD, LB, JWK and
SMP contributed to the development of the search strategy. LB conducted the
systematic search. RWM, KTM and SRM completed the acquisition of data. RWM
and SMP performed the data analysis. All authors assisted with the interpretation.
RWM and SMP were the principal writers of the manuscript. All authors contributed
to the drafting and revision of the final article. All authors approved the final
submitted version of the manuscript.
Competing interests SMP has received grant support, travel expenses, and
honoraria for presentations from the US National Dairy Council. This agency has
supported trials reviewed in this analysis.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement All data are available in the submitted manuscript or as
supplementary files.
© Article author(s) (or their employer(s) unless otherwise stated in the text of the
article) 2017. All rights reserved. No commercial use is permitted unless otherwise
expressly granted.
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strength in healthy adults
training-induced gains in muscle mass and
supplementation on resistance
meta-regression of the effect of protein
A systematic review, meta-analysis and
Laura Banfield, James W Krieger and Stuart M Phillips
Menno Henselmans, Eric Helms, Alan A Aragon, Michaela C Devries,
Robert W Morton, Kevin T Murphy, Sean R McKellar, Brad J Schoenfeld,
published online July 11, 2017Br J Sports Med
http://bjsm.bmj.com/content/early/2017/07/11/bjsports-2017-097608
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... Besides exercise, dietary protein intake is considered to be the second most potent physiological stimulus to support muscle hypertrophy. Indeed, protein supplementation has been shown to further augment the adaptive response to resistance exercise training [20,21]. However, compared to the robust but heterogeneous effect of prolonged resistance exercise training, the incremental effect of protein supplementation on muscle mass gains is relatively subtle. ...
... Therefore, an exercise training study comparing the impact of supplementing 40 vs 50 g of protein (red area) corresponds to a smaller effect size (ES) as compared to the impact of 10 vs 20 g of protein (green area), despite the same absolute differences in protein supplementation. As a result, for a given sample size, the former study is less likely to detect a statistically significant difference between treatments than the latter study. of protein supplementation will likely be lower when habitual protein intake is already high [21]. The example of protein supplementation during resistance exercise training is further complicated by other determinants such as protein quality. ...
... The validity and reliability of Web Plot Digitizer have been examined in previous studies, showing high levels of intercoder reliability and validity (Burda et al., 2017;Drevon et al., 2017). Moreover, it is a commonly used tool in meta-analyses published in peer-reviewed journals (e.g., Morton et al., 2018;Zangri et al., 2022). ...
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Objective This meta-analysis reviewed the existing literature on attentional biases towards emotional stimuli measured with eye-tracking methodologies in individuals with chronic pain. Method Eighteen relevant studies (n = 1331 participants) were identified through three electronic databases: PubMed, PsycInfo, and Scopus. A multilevel random-effects meta-analysis was conducted by using the standardized mean difference between gaze variables for emotional and neutral stimuli with Hedge's correction as the effect size (ES). Results Between-group analyses revealed that healthy individuals make longer first fixation towards neutral stimuli compared to chronic pain patients. Within-group analyses showed that, compared to the healthy control group, the chronic pain group had more first fixations towards pain-related stimuli than to neutral ones and had shorter fixation duration towards anger-related stimuli than to neutral stimuli. A moderation effect of paradigm and type of stimuli was also found. Conclusions This is the first meta-analysis exploring attentional biases not only towards pain-related stimuli, but also towards other emotional information. Our findings revealed that chronic pain individuals tend to focus their attention firstly on pain-related information in comparison to healthy individuals. Furthermore, chronic pain individuals maintain their attention on anger-related stimuli less than on neutral ones.
... An exceptional protein source rich in essential amino acids known to promote the production of new muscle is whey protein (WP). [4] which is better than other protein sources of inferior quality [5]. The aforementioned features are said to speed up the restoration of muscular function in WP. ...
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The best pharmacological treatments and dietary regimens for cancer continue to be a problem for public health. In the scientific field of oncology, whey protein WP is frequently used as a dietary strategy. The goal of the current meta-analysis is to ascertain the positive impact of WP supplements on cancer patients. A comprehensive literature search was conducted to identify RCTs that investigated WP in cancer patients. Cochrane Database of Clinical Trials, Scopus, PubMed, Google Scholar and WOS with no language restrictions for relevant studies. Reports were fully assessed based on the inclusion criteria found only 23. Only four studies were included in the systematic review and meta‐analysis. Body weight and weight change showed the difference was significantly favoring the whey protein arm at 12 weeks (MD = 1.41 [0.14, 2.69]). BMI and change in BMI, lean tissue mass and increase in lean tissue mass showed nonsignificant differences throughout follow-up. Handgrip strength and change in handgrip strength showed significantly higher in the whey-treated arm after 3 and 6 months (MD = 3.11 [1.45, 4.78], 1.04 [− 0.55, 2.63], respectively. Whey protein significantly decreased the hematological toxicity of chemotherapy (RR = 0.55 [0.30, 0.98]) compared to the control group However, gastrointestinal toxicity was not reduced with whey protein treatment (RR = 0.58 [0.19, 1.79]). In malnourished cancer patients undergoing Chemotherapy supplementation with WP may improve body weight, and handgrip strength and reduce Chemotherapy toxicity, which may lead to improved treatment efficacy.
... Kas protein sentezi (MPS) ve protein yıkımı arasındaki denge, kas protein net dengesini belirler ve bu denge, antrenman sonrası optimal beslenme ile pozitif hale getirilebilir (Atherton & Smith, 2012). Yeterli protein alımı olmaksızın, kasların antrenman sonrası toparlanma ve adaptasyon süreçleri yavaşlar, bu da kas hipertrofisinin ve kuvvet kazanımının engellenmesine yol açar (Morton et al., 2018). Günlük protein ihtiyacı, sporcular için egzersiz şiddeti ve yoğunluğuna bağlı olacak şekilde genellikle kilogram başına 1.2-2.0 ...
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Antrenman bilimi, sporcuların performansını artırmak ve uzun vadeli başarı sağlamak için sürekli gelişen bir alan olmuştur. Ancak günümüzün dinamik spor dünyasında, sadece kısa vadeli performans artışı değil, uzun süreli sürdürülebilir bir gelişim de giderek daha fazla önem kazanmaktadır. Sürdürülebilirlik kavramı, antrenman bilimi içinde, hem sporcuların fiziksel ve zihinsel sağlığını korumayı hem de spor kaynaklarını ve çevresel etkiyi optimize etmeyi içerir. Bu bağlamda, sürdürülebilir bir antrenman yönetimi, sporcuların uzun yıllar boyunca en üst düzeyde performans gösterebilmesi ve sporun gelecek nesiller için aynı etkiyi devam ettirebilmesi açısından kritik bir rol oynamaktadır. Antrenman bilimi alanında sürdürülebilirlik, üç temel bileşen etrafında şekillenir: fizyolojik, psikolojik ve çevresel. Fizyolojik sürdürülebilirlik, sporcuların aşırı antrenman, sakatlık ve yorgunluk gibi sorunlarla karşılaşmadan gelişimlerini sürdürebilmelerini sağlamayı hedefler. Psikolojik sürdürülebilirlik ise sporcuların zihinsel dayanıklılığını artırarak, motivasyonlarının uzun süre devam etmesine katkı sağlar. Çevresel sürdürülebilirlik ise antrenman süreçlerinde kullanılan malzeme, ekipman ve tesislerin çevre dostu olmasını ve antrenmanların doğaya minimum zarar vermesini içerir. Bu noktada, nitel araştırmalar, sürdürülebilir antrenman uygulamalarının anlaşılması ve geliştirilmesi açısından önemli bir yöntemdir. Niteliksel araştırma yöntemleri, sporcuların bireysel deneyimlerini, antrenörlerin stratejilerini ve uzun vadeli başarı planlarını daha derinlemesine anlamamıza olanak tanır. Mülakatlar, vaka incelemeleri ve katılımcı gözlem gibi nitel yöntemler, sürdürülebilir antrenman programlarının nasıl yapılandırılması gerektiği konusunda değerli bilgiler sunar. Örneğin, nitel araştırmalar yoluyla sporcuların antrenman süreçlerinde karşılaştıkları zorluklar, motivasyon kayıpları ya da sürdürülebilir bir başarı için hangi stratejilerin daha etkili olduğu gibi sorulara yanıt bulmak mümkündür. Aynı şekilde, antrenörlerin sürdürülebilirlik konusundaki bakış açıları, bu alandaki politikaların ve uygulamaların iyileştirilmesine yardımcı olabilir. Bu kitap, antrenman bilimi alanında sürdürülebilirlik konusunu derinlemesine ele almakta ve bu süreçte nitel araştırmaların nasıl bir katkı sağladığını irdelemektedir. Kitap boyunca, antrenmanların sürdürülebilirliğini artırmak için kullanılabilecek stratejilere ve bu stratejilerin uygulanabilirliğini destekleyen nitel araştırma bulgularına yer verilecektir. Sporcu sağlığı ve performansının sürdürülebilirliği üzerine odaklanan bu çalışma hem akademisyenler hem de pratikte çalışan antrenörler için değerli bir kaynak olmayı hedeflemektedir. Ayrıca bu kitap Sürdürülebilir Spor ve Niteliksel Araştırmalar Serimizin üçüncü kitabını oluşturmaktadır. Alan yazına bilimsel olarak büyük anlamlar katacak bir araştırma kitabı olması temennisiyle.
... Consequently, women probably require more dietary protein than men due to this increased protein oxidation and biosynthesis. The suggested baseline for women is 1.6 g/kg/day, compared to a lower baseline of 1.2 g/kg/day for men [61,62]. Resistance training further increases these needs, especially for women who exercise. ...
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Background: Branched-chain amino acids (BCAAs) are widely studied for their effects on muscle recovery and performance. Aims: This study examined the effects of BCAA supplementation on anthropometric data, physical performance, delayed onset muscle soreness (DOMS), and fatigue in recreational weightlifters. Methods: The trial involved 100 participants (50 men and 50 women), randomized into BCAA and placebo groups. Subjects in the BCAA group took five daily capsules of 500 mg L-leucine, 250 mg L-isoleucine, and 250 mg L-valine for six months. A two-way ANOVA was used to analyze the main and interaction effects of sex and treatment. Results: Notable findings include significant improvements in muscle recovery, as indicated by reduced DOMS, particularly in women who showed a decrement of 18.1 ± 9.4 mm compared to 0.8 ± 1.2 mm in the placebo group of a horizontal 100 mm line. Fatigue perception was also significantly lower in the BCAA group, with women reporting a greater decrease (2.6 ± 1.5 scores) compared to the placebo group (0.6 ± 0.7 scores). Strength gains were prominent, especially in men, with a 10% increase in bench press maximum observed in the BCAA group. The interaction between sex and treatment was significant, suggesting sex-specific responses to BCAA supplementation. Conclusions: These results underscore the effectiveness of BCAA supplementation in enhancing muscle recovery, reducing fatigue, and improving strength. This study also highlights sex-specific responses, with women benefiting more in terms of DOMS and fatigue reduction, while men experienced greater strength gains, suggesting a need for tailored supplementation strategies.
... Temos o conhecimento de que a hipertrofia muscular tem como força motriz o treinamento resistido, este que se correlaciona com alimentação e descanso adequado, neste artigo iremos analisar os principais componentes que compõem uma boa dieta para pacientes com sobrepeso ou obesidade que buscam uma dieta para emagrecimento e ganho de massa muscular.Com uma dieta de déficit calórico bem alinhada com o treino, é possível que o indivíduo ganhe massa muscular enquanto perde massa gorda, este acontecimento é bem comum em indivíduos iniciantes(Barakat et al., 2020).2.1 Proteínas2.1.1 Quantidades recomendadas e impacto nas atividades físicasDe acordo com a maior revisão da literatura científica que temos até o momento, conduzida porMorton et al. (2018), foram exibidas 3 conclusões sobre a proteína.A primeira foi que a ingestão de proteínas aumenta de forma expressiva a força, a massa magra e o tamanho dos músculos durante uma sessão de treinamento resistido.A segunda conclusão foi que a influência da proteína nos ganhos de massa magra foi mais eficaz em indivíduos já treinados e menos eficaz em indivíduos mais velhos. ...
Article
A junção de dieta e musculação pode ser uma ótima estratégia para potencializar o emagrecimento e a hipertrofia, visto que ambos podem causar impactos positivos em nossa saúde de diversas formas, sendo um deles a melhora na flexibilidade metabólica. É importante lembrar que um indivíduo só irá perder peso se estiver em uma dieta com déficit calórico, o que nunca vai ser o mesmo para todos dependendo da quantidade de gordura corporal e estado geral do indivíduo. Assim, sempre será necessário verificar o balanço calórico da dieta, distribuindo macro e micronutrientes de forma inteligente, visando otimizar tanto o emagrecimento, quanto a hipertrofia, causando uma recomposição corporal. Entretanto, cada pessoa possui determinadas necessidades nutricionais, individualidades e rotinas únicas, por isso que toda a dieta deve ser individualizada e aplicada de acordo com o contexto que o paciente vive. O que nos leva a esse estudo a passar os possíveis processos encontrados em cada indivíduo e aperfeiçoamento de dieta equilibrada. Como metodologia foi utilizado o método de revisão bibliográfica da leitura científica, no período entre 2012 a 2024. A combinação apresentada e uma estratégia dotada de planejamentos cuidadosos de dieta e de treinos acompanhados levando em consideração a prevenção e controle de patologias. Nesse âmbito a nutrição contribui para uma maior eficácia de melhoria do bem-estar e saúde.
... Protein consumption in this population exceeds the recommended intake by the Mediterranean diet of 10-15% of total dietary energy in the form of proteins, with consumption around 20% in both groups. In this regard, higher protein intakes seem to enhance training adaptations [35]. These intake levels can be easily achieved through a varied diet, if energy intake is sufficient to meet training demands [36]. ...
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Training schedule is a factor that influences sports performance optimization. In a sport like soccer, there is often significant disparity in training schedules among different teams within the same club, without considering whether this may affect players' performance. The aim of this study was to describe differences in nutrient intake and body composition in elite youth soccer players from the Spanish league with different training schedules (morning and evening). A cross-sectional study was conducted to determine differences in anthropometric variables and dietary assessment in a sample of Spanish young soccer players. A total of 41 players participated in this study. After comparing the groups according to their training schedule, no differences were observed in body composition between both groups; the evening-night training group showed higher consumption of lipids and saturated fats. In summary, more experimental studies are needed to determine the effects on various health and performance parameters of different training schedules in young population.
... The increase in strength observed across all groups is attributed to the adaptations induced by RT. Additionally, the enhanced performance in the groups that combined RT with WP supplementation may be linked to increased muscle and liver glycogen stores, which are known to be boosted by WP supplementation, as previously reported in studies by Morifuji et al. (Morifuji et al., 2005) In addition, concerning daily protein consumption, a dose of approximately 1.6 g/kg body weight is sufficient for potentiation in one repetition maximum (1RM) strength gains (Morton et al., 2018). The gene expression of mTOR was higher in the trained and supplemented groups, indicating a potential role of RT in stimulating protein synthesis pathways. ...
Article
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Introduction: The combination of resistance training (RT) and whey protein supplementation (WPS) is widely practiced by both athletes and recreational exercisers to promote muscle growth and increase strength. Objectiveː This study examined the effect of different doses of whey proteins on muscle strength, body composition and gene expression of mTOR and MuRF-1 in trained Wistar rats. Methodsː 80 male Wistar rats were divided into 8-groups (n=10): sedentary control (C), RT-control (TC), groups consuming whey protein at varying doses (W2, W4, and W6; respectively 2/4/6g/kg/day), and groups consuming whey protein at varying doses combined to RT (TW2, TW4, and TW6; respectively 2/4/6g/kg/day). The RT program was conducted for 12 weeks, three days a week, with the training intensity increasing from 50 to 100% of the rats' body weight. The rats receiving the whey supplement via the gavage method based on their body weight. Resultsː Muscle strength significantly increased in all trained groups (p<0.0001), with a more significant increase in the groups RT and WPS combined. In addition, the expression of mTOR was higher in the RT groups compared to the sedentary groups (p<0.01), but supplementation did not yield significant differences. WPS decreased MuRF-1 expression (p<0.01) independently of RT. Conclusionː In conclusion, RT combined with WPS for 12 weeks improved muscle strength. Furthermore, mTOR expression increased in trained rats, but not in sedentary rats who used different doses of WPS. However, WPS at any dose reduced MuRF-1 expression, independently of RT. Higher WPS doses did not enhance observed gains compared to a lower dose. Keywords: whey protein, body composition, resistance training, mTOR, MuRF-1.
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Introduction Skeletal muscle satellite cells (SC) contribute to the adaptive process of resistance exercise training (RET) and may be influenced by nutritional supplementation. However, little research exists on the impact of multi-ingredient supplementation on the SC response to RET. Purpose We tested the effect of a multi-ingredient supplement (MIS) including whey protein, creatine, leucine, calcium citrate, and vitamin D on SC content and activity as well as myonuclear accretion, SC and myonuclear domain compared with a collagen control (COL) throughout a 10-wk RET program. Methods Twenty-six participants underwent a 10-wk linear RET program while consuming either the MIS or COL supplement twice daily. Muscle biopsies were taken from the vastus lateralis at baseline and 48 h after a bout of damaging exercise, before and after RET. Muscle tissue was analyzed for SC and myonuclear content, domain, acute SC activation, and fiber cross-sectional area (fCSA). Results MIS resulted in a greater increase in type II fCSA following 10 wk of RET (effect size (ES) = 0.89) but not myonuclear accretion or SC content. Change in myonuclei per fiber was positively correlated with type I and II and total fiber hypertrophy in the COL group only, indicating a robust independent effect of MIS on fCSA. Myonuclear domain increased similarly in both groups, whereas SC domain remained unchanged following RET. SC activation was similar between groups for all fiber types in the untrained state but showed a trend toward greater increases with MIS after RET (ES = 0.70). Conclusions SC responses to acute damaging exercise and long-term RET are predominantly similar in MIS and COL groups. However, MIS can induce greater increases in type II fCSA with RET and potentially SC activation following damage in the trained state.
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Supplements are products widely used among athletes to improve sports performance and reduce fatigue symptoms. The aim of the study was to determine the differences of the use of dietary supplements among students of the Faculty of Sport and Physical Education, University of Niš (by year of study and gender), as well as the differences between the frequency and duration of physical activity with the use of dietary supplements. The survey was conducted on a sample of 201 students of both genders, all four years of undergraduate studies, aged 19 to 23. The respondents completed questionnaire containing questions related to dietary supplementation, physical activity and the existence of fatigue symptoms. Survey results show that 40.8% of respondents use supplements. Male students used dietary supplementation more often than female . Students most commonly take vitamins (68.3%), proteins and amino acids (15.1%) whereas 5.6% of them use minerals. The results have shown that with the increase of the year of study, the number of students taking supplements decreases significantly. Also, the analysis of the results by gender showed that male students were more likely to take amino acid supplements. No differences were found between the duration and frequency of physical activity and the use of supplements. It could be concluded that with the increase of the year of study, we note positive changes in students' attitudes to the use of supplements, which could be explained by the acquisition of knowledge in the field of sports nutrition and supplementation through the curriculum contents of the study program.
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Background and aims Physical activity and nutritional supplementation interventions may be used to ameliorate age-related loss of skeletal muscle mass and function. Previous reviews have demonstrated the beneficial effects of resistance exercise training (RET) combined with protein or essential amino acids (EAA) in younger populations. Whether or not older adults also benefit is unclear. The aim of this review was to determine whether regular dietary supplementation with protein/EAA during a RET regimen augments the effects of RET on skeletal muscle in older adults. Methods A literature search was conducted in August 2015 using MEDLINE, EMBASE, SPORTDiscus, and CINAHL Plus to identify all controlled trials using a RET regimen with and without protein/EAA supplementation. Outcome variables included muscle strength, muscle size, functional ability, and body composition. Results Fifteen studies fulfilled the eligibility criteria, including 917 participants with a mean age of 77.4 years. Studies involving both healthy participants and those described as frail or sarcopenic were included. Overall, results indicated that protein supplementation did not significantly augment the effects of RET on any of the specified outcomes. Exceptions included some measures of muscle strength (3 studies) and body composition (2 studies). Meta-analyses were conducted but were limited because of methodologic differences between studies, and results were inconclusive. Conclusions Systematic review and meta-analysis of controlled trials reveal that protein/EAA supplementation does not significantly augment the effects of progressive RET in older adults.
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Muscle strength is often measured through the performance of a one-repetition maximum (1RM). However, we that feel a true measurement of ‘strength’ remains elusive. For example, low-load alternatives to traditional resistance training result in muscle hypertrophic changes similar to those resulting from traditional high-load resistance training, with less robust changes observed with maximal strength measured by the 1RM. However, when strength is measured using a test to which both groups are ‘naive’, differences in strength become less apparent. We suggest that the 1RM is a specific skill, which will improve most when training incorporates its practice or when a lift is completed at a near-maximal load. Thus, if we only recognize increases in the 1RM as indicative of strength, we will overlook many effective and diverse alternatives to traditional high-load resistance training. We wish to suggest that multiple measurements of strength assessment be utilized in order to capture a more complete picture of the adaptation to resistance training.
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Background: To our knowledge the efficacy of soy-dairy protein blend (PB) supplementation with resistance exercise training (RET) has not been evaluated in a longitudinal study. Objective: Our aim was to determine the effect of PB supplementation during RET on muscle adaptation. Methods: In this double-blind randomized clinical trial, healthy young men [18-30 y; BMI (in kg/m(2)): 25 ± 0.5] participated in supervised whole-body RET at 60-80% 1-repetition maximum (1-RM) for 3 d/wk for 12 wk with random assignment to daily receive 22 g PB (n = 23), whey protein (WP) isolate (n = 22), or an isocaloric maltodextrin (carbohydrate) placebo [(MDP) n = 23]. Serum testosterone, muscle strength, thigh muscle thickness (MT), myofiber cross-sectional area (mCSA), and lean body mass (LBM) were assessed before and after 6 and 12 wk of RET. Results: All treatments increased LBM (P < 0.001). ANCOVA did not identify an overall treatment effect at 12 wk (P = 0.11). There tended to be a greater change in LBM from baseline to 12 wk in the PB group than in the MDP group (0.92 kg; 95% CI: -0.12, 1.95 kg; P = 0.09); however, changes in the WP and MDP groups did not differ. Pooling data from combined PB and WP treatments showed a trend for greater change in LBM from baseline to 12 wk compared with MDP treatment (0.69 kg; 95% CI: -0.08, 1.46 kg; P = 0.08). Muscle strength, mCSA, and MT increased (P < 0.05) similarly for all treatments and were not different (P > 0.10) between treatments. Testosterone was not altered. Conclusions: PB supplementation during 3 mo of RET tended to slightly enhance gains in whole-body and arm LBM, but not leg muscle mass, compared with RET without protein supplementation. Although protein supplementation minimally enhanced gains in LBM of healthy young men, there was no enhancement of gains in strength. This trial was registered at clinicaltrials.gov as NCT01749189.
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The response to resistance training and protein supplementation in the latissimus dorsi muscle (LDM) has never been investigated. We investigated the effects of resistance training (RT) and protein supplementation on muscle mass, strength, and fiber characteristics of the LDM. Eighteen healthy young subjects were randomly assigned to a progressive eight-week RT program with a normal protein diet (NP) or high protein diet (HP) (NP 0.85 vs. HP 1.8 g of protein·kg(-1)·day(-1)). One repetition maximum tests, magnetic resonance imaging for cross-sectional muscle area (CSA), body composition, and single muscle fibers mechanical and phenotype characteristics were measured. RT induced a significant gain in strength (+17%, p < 0.0001), whole muscle CSA (p = 0.024), and single muscle fibers CSA (p < 0.05) of LDM in all subjects. Fiber isometric force increased in proportion to CSA (+22%, p < 0.005) and thus no change in specific tension occurred. A significant transition from 2X to 2A myosin expression was induced by training. The protein supplementation showed no significant effects on all measured outcomes except for a smaller reduction of 2X myosin expression. Our results suggest that in LDM protein supplementation does not further enhance RT-induced muscle fiber hypertrophy nor influence mechanic muscle fiber characteristics but partially counteracts the fast-to-slow fiber shift.
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Background: Muscle mass maintenance is largely regulated by basal muscle protein synthesis rates and the ability to increase muscle protein synthesis after protein ingestion. To our knowledge, no previous studies have evaluated the impact of habituation to either low protein intake (LOW PRO) or high protein intake (HIGH PRO) on the postprandial muscle protein synthetic response. Objective: We assessed the impact of LOW PRO compared with HIGH PRO on basal and postprandial muscle protein synthesis rates after the ingestion of 25 g whey protein. Design: Twenty-four healthy, older men [age: 62 ± 1 y; body mass index (in kg/m(2)): 25.9 ± 0.4 (mean ± SEM)] participated in a parallel-group randomized trial in which they adapted to either a LOW PRO diet (0.7 g · kg(-1) · d(-1); n = 12) or a HIGH PRO diet (1.5 g · kg(-1) · d(-1); n = 12) for 14 d. On day 15, participants received primed continuous l-[ring-(2)H5]-phenylalanine and l-[1-(13)C]-leucine infusions and ingested 25 g intrinsically l-[1-(13)C]-phenylalanine- and l-[1-(13)C]-leucine-labeled whey protein. Muscle biopsies and blood samples were collected to assess muscle protein synthesis rates as well as dietary protein digestion and absorption kinetics. Results: Plasma leucine concentrations and exogenous phenylalanine appearance rates increased after protein ingestion (P < 0.01) with no differences between treatments (P > 0.05). Plasma exogenous phenylalanine availability over the 5-h postprandial period was greater after LOW PRO than after HIGH PRO (61% ± 1% compared with 56% ± 2%, respectively; P < 0.05). Muscle protein synthesis rates increased from 0.031% ± 0.004% compared with 0.039% ± 0.007%/h in the fasted state to 0.062% ± 0.005% compared with 0.057% ± 0.005%/h in the postprandial state after LOW PRO compared with HIGH PRO, respectively (P < 0.01), with no differences between treatments (P = 0.25). Conclusion: Habituation to LOW PRO (0.7 g · kg(-1) · d(-1)) compared with HIGH PRO (1.5 g · kg(-1) · d(-1)) augments the postprandial availability of dietary protein-derived amino acids in the circulation and does not lower basal muscle protein synthesis rates or increase postprandial muscle protein synthesis rates after ingestion of 25 g protein in older men. This trial was registered at clinicaltrials.gov as NCT01986842.
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Key points: Skeletal muscle hypertrophy is one of the main outcomes from resistance training (RT), but how it is modulated throughout training is still unknown. We show that changes in myofibrillar protein synthesis (MyoPS) after an initial resistance exercise (RE) bout in the first week of RT (T1) were greater than those seen post-RE at the third (T2) and tenth week (T3) of RT, with values being similar at T2 and T3. Muscle damage (Z-band streaming) was the highest during post-RE recovery at T1, lower at T2 and minimal at T3. When muscle damage was the highest, so was the integrated MyoPS (at T1), but neither were related to hypertrophy; however, integrated MyoPS at T2 and T3 were correlated with hypertrophy. We conclude that muscle hypertrophy is the result of accumulated intermittent increases in MyoPS mainly after a progressive attenuation of muscle damage. Abstract: Skeletal muscle hypertrophy is one of the main outcomes of resistance training (RT), but how hypertrophy is modulated and the mechanisms regulating it are still unknown. To investigate how muscle hypertrophy is modulated through RT, we measured day-to-day integrated myofibrillar protein synthesis (MyoPS) using deuterium oxide and assessed muscle damage at the beginning (T1), at 3 weeks (T2) and at 10 weeks of RT (T3). Ten young men (27 (1) years, mean (SEM)) had muscle biopsies (vastus lateralis) taken to measure integrated MyoPS and muscle damage (Z-band streaming and indirect parameters) before, and 24 h and 48 h post resistance exercise (post-RE) at T1, T2 and T3. Fibre cross-sectional area (fCSA) was evaluated using biopsies at T1, T2 and T3. Increases in fCSA were observed only at T3 (P = 0.017). Changes in MyoPS post-RE at T1, T2 and T3 were greater at T1 (P < 0.03) than at T2 and T3 (similar values between T2 and T3). Muscle damage was the highest during post-RE recovery at T1, attenuated at T2 and further attenuated at T3. The change in MyoPS post-RE at both T2 and T3, but not at T1, was strongly correlated (r ≈ 0.9, P < 0.04) with muscle hypertrophy. Initial MyoPS response post-RE in an RT programme is not directed to support muscle hypertrophy, coinciding with the greatest muscle damage. However, integrated MyoPS is quickly 'refined' by 3 weeks of RT, and is related to muscle hypertrophy. We conclude that muscle hypertrophy is the result of accumulated intermittent changes in MyoPS post-RE in RT, which coincides with progressive attenuation of muscle damage.
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Background: The current estimated average requirement (EAR) and RDA for protein of 0.66 and 0.8 g ⋅ kg(-1) ⋅ d(-1), respectively, for adults, including older men, are based on nitrogen balance data analyzed by monolinear regression. Recent studies in young men and older women that used the indicator amino acid oxidation (IAAO) technique suggest that those values may be too low. This observation is supported by 2-phase linear crossover analysis of the nitrogen balance data. Objective: The main objective of this study was to determine the protein requirement for older men by using the IAAO technique. Methods: Six men aged >65 y were studied; each individual was tested 7 times with protein intakes ranging from 0.2 to 2.0 g ⋅ kg(-1) ⋅ d(-1) in random order for a total of 42 studies. The diets provided energy at 1.5 times the resting energy expenditure and were isocaloric. Protein was consumed hourly for 8 h as an amino acid mixture with the composition of egg protein with l-[1-(13)C]phenylalanine as the indicator amino acid. The group mean protein requirement was determined by applying a mixed-effects change-point regression analysis to F(13)CO2 (label tracer oxidation in breath (13)CO2), which identified a breakpoint in F(13)CO2 in response to graded intakes of protein. Results: The estimated protein requirement and RDA for older men were 0.94 and 1.24 g ⋅ kg(-1) ⋅ d(-1), respectively, which are not different from values we published using the same method in young men and older women. Conclusions: The current intake recommendations for older adults for dietary protein of 0.66 g ⋅ kg(-1) ⋅ d(-1) for the EAR and 0.8 g ⋅ kg(-1) ⋅ d(-1) for the RDA appear to be underestimated by ∼30%. Future longer-term studies should be conducted to validate these results. This trial was registered at clinicaltrials.gov as NCT01948492.
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Hyperaminoacidemia following protein ingestion enhances the anabolic effect of resistance-type exercise by increasing the stimulation of muscle protein synthesis and attenuating the exercise-mediated increase in muscle protein breakdown rates. Although factors such as the source of protein ingested and the timing of intake relative to exercise can impact post-exercise muscle protein synthesis rates, the amount of protein ingested after exercise appears to be the key nutritional factor dictating the magnitude of the muscle protein synthetic response during post-exercise recovery. In younger adults, muscle protein synthesis rates after resistance-type exercise respond in a dose-dependent manner to ingested protein and are maximally stimulated following ingestion of ~20 g of protein. In contrast to younger adults, older adults are less sensitive to smaller doses of ingested protein (less than ~20 g) after exercise, as evidenced by an attenuated increase in muscle protein synthesis rates during post-exercise recovery. However, older muscle appears to retain the capacity to display a robust stimulation of muscle protein synthesis in response to the ingestion of greater doses of protein (~40 g), and such an amount may be required for older adults to achieve a robust stimulation of muscle protein synthesis during post-exercise recovery. The aim of this article is to discuss the current state of evidence regarding the dose-dependent relationship between dietary protein ingestion and changes in skeletal muscle protein synthesis during recovery from resistance-type exercise in older adults. We provide recommendations on the amount of protein that may be required to maximize skeletal muscle reconditioning in response to resistance-type exercise in older adults.
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Substantial evidence supports the increased consumption of high-quality protein to achieve optimal health outcomes. A growing body of research indicates that protein intakes well above the current Recommended Dietary Allowance help to promote healthy aging, appetite regulation, weight management, and goals aligned with athletic performance. Higher protein intakes may help prevent age-related sarcopenia, the loss of muscle mass, and strength that predisposes older adults to frailty, disability, and loss of autonomy. Higher protein diets also improve satiety and lead to greater reductions in body weight and fat mass compared with standard protein diets, and may therefore serve as a successful strategy to help prevent and/or treat obesity. Athletes can also benefit from higher protein intakes to maximize athletic performance given the critical role protein plays in stimulating muscle protein remodelling after exercise. Protein quality, per meal dose, and timing of ingestion are also important considerations. Despite persistent beliefs to the contrary, we can find no evidence-based link between higher protein diets and renal disease or adverse bone health. This brief synopsis highlights recent learnings based on presentations at the 2015 Canadian Nutrition Society conference, Advances in Protein Nutrition across the Lifespan. Current evidence indicates intakes in the range of at least 1.2 to 1.6 g/(kg·day) of high-quality protein is a more ideal target for achieving optimal health outcomes in adults.
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Background: A dietary protein intake higher than the Recommended Dietary Allowance during an energy deficit helps to preserve lean body mass (LBM), particularly when combined with exercise. Objective: The purpose of this study was to conduct a proof-of-principle trial to test whether manipulation of dietary protein intake during a marked energy deficit in addition to intense exercise training would affect changes in body composition. Design: We used a single-blind, randomized, parallel-group prospective trial. During a 4-wk period, we provided hypoenergetic (∼40% reduction compared with requirements) diets providing 33 ± 1 kcal/kg LBM to young men who were randomly assigned (n = 20/group) to consume either a lower-protein (1.2 g · kg(-1) · d(-1)) control diet (CON) or a higher-protein (2.4 g · kg(-1) · d(-1)) diet (PRO). All subjects performed resistance exercise training combined with high-intensity interval training for 6 d/wk. A 4-compartment model assessment of body composition was made pre- and postintervention. Results: As a result of the intervention, LBM increased (P < 0.05) in the PRO group (1.2 ± 1.0 kg) and to a greater extent (P < 0.05) compared with the CON group (0.1 ± 1.0 kg). The PRO group had a greater loss of fat mass than did the CON group (PRO: -4.8 ± 1.6 kg; CON: -3.5 ± 1.4kg; P < 0.05). All measures of exercise performance improved similarly in the PRO and CON groups as a result of the intervention with no effect of protein supplementation. Changes in serum cortisol during the intervention were associated with changes in body fat (r = 0.39, P = 0.01) and LBM (r = -0.34, P = 0.03). Conclusions: Our results showed that, during a marked energy deficit, consumption of a diet containing 2.4 g protein · kg(-1) · d(-1) was more effective than consumption of a diet containing 1.2 g protein · kg(-1) · d(-1) in promoting increases in LBM and losses of fat mass when combined with a high volume of resistance and anaerobic exercise. Changes in serum cortisol were associated with changes in body fat and LBM, but did not explain much variance in either measure. This trial was registered at clinicaltrials.gov as NCT01776359.