Diet and the risk of rheumatoid arthritis – A systematic literature review
Bibliographic record
Abstract
OBJECTIVES: Diet has received attention as a factor possibly contributing to the development of Rheumatoid arthritis (RA). Several dietary exposures have been examined in various populations using different diet assessment methods. The aim of this study was to systematically assess the literature on the relation between dietary patterns, different food and food groups, macronutrients, non-alcoholic beverages and the risk of developing RA. METHODS: A systematic literature search was performed to identify relevant articles on diet and the risk of developing RA. The selection of articles and overall quality assessment of all included studies were performed independently by two examiners. Overall study quality was evaluated using the Newcastle-Ottawa Scales. We excluded all articles where the temporal relation between dietary data collection and time of RA diagnosis was not presented. Main findings were summarized for cohort-based studies and case-control studies separately. RESULTS: A total of 984 articles were screened. Nineteen relevant cohort-based studies, and eight case-control studies, were included in our review. Two articles were excluded due to lacking data on the relation between RA diagnosis and time of dietary data collection and one due to incorrect outcome. Identified studies suggested protective effects of fish, vegetables and Mediterranean-style diets, although study results and methods were heterogenous. An issue in some case-control studies was that unvalidated diet assessment methods were used. A vast majority of the cohort-based studies used validated diet assessment methods, although the definitions of exposures studied varied. CONCLUSION: There is lack of consistent evidence on the role of diet in the development of RA, partly due to differences in study quality and methodology Limited evidence suggests that some healthy eating habits may reduce the risk of RA. More high-quality studies in the area are needed for a deeper understanding of the effect of diet, and to enable strategies to prevent RA.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".