Increasing Protein Ingestion Minimally Increases Lean Mass and Muscle Strength in Subjects Enrolled in Resistance Exercise Training a Systematic Review and Meta-Analysis
Bibliographic record
Abstract
This systematic review, meta-analysis, and meta-regression aimed to determine if increasing daily protein ingestion contributes to gaining lean mass (LM), muscle strength, and physical/functional test performance in healthy persons. The present review was registered on PROSPERO - CRD42020159001. A systematic search in Medline, Embase, CINAHL, and Web of Sciences databases was undertaken. Randomized controlled trials (RCT) including healthy and non-obese adult participants increasing daily protein intake were selected. Subgroup analysis, splitting the studies by participation in resistance exercise training (RE), age (< 65 or ≥ 65 y), and daily protein ingestion were also performed. 74 RCT fit our inclusion criteria. The age range of the participants was 19 to 85 y, and study protocols in the trials lasted from 6 to 108 wks (76% of the studies between 8 and 12 wks). In ∼80% of the studies, baseline protein ingestion was at least 1.2 g of protein/kg/d. Increasing daily protein ingestion may lead to small gains in LM in subjects enrolled in RE (SMD [standardized mean difference] = 0.22, CI95% [95% confidence interval] 0.14:0.30, P < 0.01, 62 studies, moderate level of evidence). Also, ≥ 65 y subjects ingesting 1.2–1.59 g of protein/kg/d and younger subjects (< 65 y) increasing their ingestion to ≥ 1.6 g of protein/kg/d during RE showed a higher LM gain. Lower-body strength gain was slightly higher at ≥ 1.6 g of protein/kg/d during RE (SMD = 0.40, CI95% 0.09:0.35, P < 0.01, 19 studies, low level of evidence). Bench press strength was slightly increased by ingesting more protein in < 65 y subjects during RE (SMD = 0.18, CI95% 0.03:0.33, P = 0.01, 32 studies, low level of evidence). Effects on handgrip strength are unclear and only marginal for performance in physical function tests. The number of studies increasing daily protein ingestion alone was too low (n = 6) to conduct a meta-analysis. The current evidence shows that increasing protein ingestion by consuming supplements or food, resulted in small additional gain in LM, and lower body muscle strength in healthy adults enrolled in RE. Effects on bench press strength and performance in physical function tests are minimal. The effect on handgrip strength was unclear. This research received a grant from the International Life Science Institute (Europe) and CNPq.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".