The impact of high-quality dietary patterns on the prevention of osteoporosis: a meta-analysis of observational studies
Bibliographic record
Abstract
Current prevention and treatment strategies for osteoporosis face limitations such as uncertain long-term efficacy, potential safety concerns, and poor adherence. Given these challenges, dietary interventions have emerged as a possible alternative. This study conducts a meta-analysis to systematically evaluate the association between high-quality dietary patterns and osteoporosis risk. We conducted a systematic search of PubMed and Web of Science databases through March 2025. We included observational studies that examined the association between high-quality dietary patterns (HEI, DASH, AHEI, hPDI, MeDS) and osteoporosis. The study selection followed predefined inclusion and exclusion criteria, and the Newcastle-Ottawa Scale was used for quality assessment. A total of 9 articles (including 22 studies) with 243,846 participants were ultimately included. Random-effects model analysis showed that high-quality dietary patterns overall had significant protective effects against osteoporosis (pooled OR = 0.82, 95% CI: 0.72-0.94). Subgroup analyses indicated: DASH (OR = 0.71, 95% CI: 0.57-0.90) and HEI (OR = 0.46, 95% CI: 0.33-0.66) showed significant protective effects. North America (OR = 0.85,95% CI: 0.74-0.97) and Asia (OR = 0.63,95% CI: 0.55-0.72) demonstrated protective effects. A potential protective effect (OR = 0.80,95% CI: 0.70-0.92) was shown in cross-sectional studies. The protective effect was more significant in women (OR = 0.63,95% CI: 0.53-0.74). High-quality dietary patterns, particularly DASH and HEI, may significantly reduce osteoporosis risk. Despite high heterogeneity observed in our study, results from subgroup analyses and meta-regression also supported the integration of dietary pattern into osteoporosis prevention. More cohort studies are warranted to remedy the existing limitation of inadequate longitudinal data, and additional cohort investigations are further essential for validating the observed associations between high-quality dietary patterns and osteoporosis. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251009978.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".