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. 2023 Sep;57(18):1211-1220.
doi: 10.1136/bjsports-2023-106807. Epub 2023 Jul 6.

Resistance training prescription for muscle strength and hypertrophy in healthy adults: a systematic review and Bayesian network meta-analysis

Affiliations

Resistance training prescription for muscle strength and hypertrophy in healthy adults: a systematic review and Bayesian network meta-analysis

Brad S Currier et al. Br J Sports Med. 2023 Sep.

Abstract

Objective: To determine how distinct combinations of resistance training prescription (RTx) variables (load, sets and frequency) affect muscle strength and hypertrophy.

Data sources: MEDLINE, Embase, Emcare, SPORTDiscus, CINAHL, and Web of Science were searched until February 2022.

Eligibility criteria: Randomised trials that included healthy adults, compared at least 2 predefined conditions (non-exercise control (CTRL) and 12 RTx, differentiated by load, sets and/or weekly frequency), and reported muscle strength and/or hypertrophy were included.

Analyses: Systematic review and Bayesian network meta-analysis methodology was used to compare RTxs and CTRL. Surface under the cumulative ranking curve values were used to rank conditions. Confidence was assessed with threshold analysis.

Results: The strength network included 178 studies (n=5097; women=45%). The hypertrophy network included 119 studies (n=3364; women=47%). All RTxs were superior to CTRL for muscle strength and hypertrophy. Higher-load (>80% of single repetition maximum) prescriptions maximised strength gains, and all prescriptions comparably promoted muscle hypertrophy. While the calculated effects of many prescriptions were similar, higher-load, multiset, thrice-weekly training (standardised mean difference (95% credible interval); 1.60 (1.38 to 1.82) vs CTRL) was the highest-ranked RTx for strength, and higher-load, multiset, twice-weekly training (0.66 (0.47 to 0.85) vs CTRL) was the highest-ranked RTx for hypertrophy. Threshold analysis demonstrated these results were extremely robust.

Conclusion: All RTx promoted strength and hypertrophy compared with no exercise. The highest-ranked prescriptions for strength involved higher loads, whereas the highest-ranked prescriptions for hypertrophy included multiple sets.

Prospero registration number: CRD42021259663 and CRD42021258902.

Keywords: aging; muscle; muscle, skeletal; weight lifting.

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Conflict of interest statement

Competing interests: SMP reports grants or research contracts from the US National Dairy Council, Canadian Institutes for Health Research, Dairy Farmers of Canada, Roquette Freres, Ontario Centre of Innovation, Nestle Health Sciences, Myos, National Science and Engineering Research Council and the US NIH during the conduct of the study; personal fees from Nestle Health Sciences, non-financial support from Enhanced Recovery, outside the submitted work. SMP has patents licensed to Exerkine but reports no financial gains from any patent or related work. The remaining authors report no competing interests.

Figures

Figure 1
Figure 1
PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram of study selection.
Figure 2
Figure 2
Network geometry for all available studies evaluating strength (A) and hypertrophy (B). Each node represents a unique condition, and the size of each node is proportional to the sample size per condition. Each edge represents direct evidence, and the width of each edge is proportional to the number of studies comparing connected nodes. Resistance training prescriptions are denoted with a three-character acronym—XY#—where X is load (H, ≥80% 1-repetition maximum (1RM); L, <80% 1 RM); Y is sets (M, multiset; S, single-set); and # is the weekly frequency (3, ≥3 days/week; 2, 2 days/week; 1, 1 day/week), respectively. For example, ‘HM2’ denotes higher-load, multiset, twice-weekly training. CTRL, non-exercising control group.
Figure 3
Figure 3
Forest plots displaying network estimates for relative effects of resistance training prescriptions versus non-exercising control for strength (A) and hypertrophy (B). Each resistance training prescription (RTx) is denoted with a three-character acronym—XY#—where X is load (H, ≥80% 1-repetition maximum (1RM); L, <80% 1 RM); Y is sets (M, multiset; S, single-set); and # is the weekly frequency (3, ≥3 days/week; 2, 2 days/week; 1, 1 day/week), respectively. For example, ‘HM2’ denotes higher-load, multiset, twice-weekly training. CTRL, non-exercising control; SMD, standardised mean difference; 95% CrI, 95% credible interval.
Figure 4
Figure 4
Probability for each condition ranking in the top three most effective for strength (A) and hypertrophy (B). Scores closer to 100% indicate a greater chance of being ranked in the top three. Resistance training prescriptions are denoted with a three-character acronym—XY#—where X is load (H, ≥80% 1-repetition maximum (1RM); L, <80% 1 RM); Y is sets (M, multiset; S, single-set); and # is the weekly frequency (3, ≥3 days/week; 2, 2 days/week; 1, 1 day/week), respectively. For example, ‘HM2’ denotes higher-load, multiset, twice-weekly training. CTRL, non-exercising control group.
Figure 5
Figure 5
Forest plots displaying network estimates for relative effects of resistance training prescriptions versus non-exercising control for mobility (A), gait speed (B) and balance/flexibility. Each resistance training prescription (RTx) is denoted with a three-character acronym—XY#—where X is load (H, ≥80% 1-repetition maximum (1RM); L, <80% 1 RM); Y is sets (M, multiset; S, single-set); and # is the weekly frequency (3, ≥3 days/week; 2, 2 days/week; 1, 1 day/week), respectively. For example, ‘HM2’ denotes higher-load, multiset, twice-weekly training. CTRL, non-exercising control; SMD, standardised mean difference; 95% CrI, 95% credible interval.

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