Association between dietary acid load and risk of osteoporotic fractures in adults: a systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
We aimed to systematically review and conduct a meta-analysis of the available evidence about the association between dietary acid load (DAL) and fractures in adults. Relevant studies were searched through Web of Science, Scopus, PubMed, and Google Scholar until October 2024. The random-effect model was used to calculate the pooled Odd ratios (OR) and 95% confidence intervals (CIs). Publication bias was evaluated by statistical test of Egger. Subgroup analyses were conducted by study confounders. Moreover, the quality of studies was asessed using the Newcastle Ottawa Scale which is designed for observational studies. Six studies were included in this review. According to the methodological heterogeneity between studies and their different charactristics, we performed the analysis based on random-effect model that indicated a marginally significant association between DAL and risk of fracture (N event = 5275, Pooled OR: 1.10; 95% CI: 0.99–1.21, P = 0.073) (I2 = 12.9%; P = 0.321). According to subgroup analysis, there was no significant association between DAL and risk of fracture in the cross-sectional effect sizes (N event = 337, OR:0.69; 95%CI:0.47–1.00). There was a significant association between DAL and a greater risk of fracture in cohort studies (N event = 4938, OR:1.12; 95%CI:1.03–1.22, P = 0.006). Also, high-quality studies (OR:1.12; 95%CI:1.03–1.22; P = 0.006) showed a significant association between DAL and fracture risk. DAL was marginally related to a higher risk of fracture. This finding is a trigger for bone health management with a healthy balanced dietary intake.
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.030 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".