The association between dietary protein intake and metabolic syndrome: a GRADE-assessed systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
Abstract Objectives The primary aim of this meta-analysis is to assess the association of dietary protein with the risk of metabolic syndrome (MetS) in observational studies. In addition, the secondary aim is to evaluate the effectiveness of protein intake on MetS components. Methods An Initial search was conducted from PubMed, Web of Science (WOS), and Scopus until May 2024. Cohort, cross-sectional, and case-control studies were included, and their quality and certainty were evaluated by the Newcastle – Ottawa Quality Assessment Scale (NOS) and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) tools, respectively. Result Based on our meta-analysis, we found that plant protein (PP), and animal protein (AP) had an inverse association with MetS (OR: 0.77, 95% CI: 0.69, 0.87, P < 0.001; I 2 = 93.0%; P heterogeneity < 0.001), (OR: 0.92, 95% CI: 0.86, 0.98, P = 0.012; I 2 = 83.5%; P heterogeneity < 0.001), respectively. Besides, there was no association between total protein (TP) and MetS (OR: 0.90, 95% CI: 0.82, 1.00, P < 0.051; I 2 = 91.3%; P heterogeneity < 0.001) as the primary outcomes. Furthermore, TP, AP, and PP had a negative association with MetS components, except TP-WC (OR: 0.78; 95% CI: 0.55, 1.12; P = 0.178; I 2 = 80.0%; P heterogeneity < 0.001), TP-FBS (OR: 0.93; 95% CI: 0.82, 1.05; P = 0.231; I 2 = 91.0%; P heterogeneity < 0.001), TP-BP (OR: 0.86; 95% CI: 0.76, 0.96; P = 0.008; I 2 = 87.9%; P heterogeneity < 0.001), AP-FBS (OR: 1.04, 95% CI: 1.00, 1.07, P = 0.061; I 2 = 29.6%; P heterogeneity >0.001), PP-FBS (OR: 0.94, 95% CI: 0.86, 1.03, P = 0.207; I 2 = 72.2%; P heterogeneity =0.001). Conclusion Current evidence suggests that PP and AP intake may be associated with reduced risk of MetS as the primary outcome. However, in specific contexts, such as some of the secondary outcomes, results showed no reaction, e.g., TP-WC, TP-FBS, TP-BP, AP-FBS, PP-FBS. Besides, due to the high heterogeneity, methodological quality, and significant bias in PP-MetS and PP-TG, recommendations must be made cautiously. Finally, no definitive conclusions can be drawn regarding a causal or uniform protective relationship. Trial registration Prospero ID 1020957.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.027 | 0.071 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.045 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 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".