Which dietary patterns fend off nonalcoholic fatty liver disease? A systematic review of observational and interventional studies
Bibliographic record
Abstract
BACKGROUND: The global burden of non-alcoholic fatty liver disease (NAFLD) has significantly risen over the past decade. Dietary intake strongly influences its development and should be a component of any prevention and treatment plan strategy. Dietary pattern analysis enables the investigation of the overall diet and permits the consideration of interactions and cumulative effects of dietary components. The current study aimed to systematically review observational studies and intervention trials to determine the associations between various dietary patterns and NAFLD. METHODS: The protocol was written according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched PubMed, Embase, and the Cochrane Library. We included studies that reported a priori dietary pattern (i.e., diet quality scores) or a posteriori method, which identified existing eating patterns (i.e., principal component analysis) in adult participants. Two investigators conducted independent screening, extraction, and quality assessment using the Newcastle‒Ottawa or Jadad scale. A third reviewer resolved conflicts. RESULTS: We identified 27 relevant observational and 16 interventional studies from 16 countries. A Mediterranean or DASH diet might prevent and improve NAFLD, whereas dietary patterns such as Western dietary patterns characterized by high consumption of sweets and animal foods such as red meat and fast food are positively associated with NAFLD. A low-carbohydrate diet effectively prevents and treats NAFLD; however, we need more research on the effects of a low-fat diet and the type of fats. CONCLUSION: Healthy dietary patterns, mainly plant-based or adjusted macronutrient distributions, such as the adoption of a low-carbohydrate diet, are linked to a reduced risk of NAFLD and could halt its progression. We proposed recommendations for future studies to fill the gap in knowledge regarding the management of NAFLD via dietary modifications.
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 | 0.031 | 0.112 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.017 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| 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".