Systematic review/Meta-analysis Coffee consumption and risk of fractures: a meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Recent studies have indicated higher risk of fractures among coffee drinkers. To quantitatively assess the association between coffee consumption and the risk of fractures, we conducted this meta-analysis. MATERIAL AND METHODS: We searched MEDLINE and EMBASE for prospective studies reporting the risk of fractures with coffee consumption. Quality of included studies was assessed with the Newcastle Ottawa scale. We conducted a meta-analysis and a cumulative meta-analysis of relative risk (RR) for an increment of one cup of coffee per day, and explored the potential dose-response relationship. Sensitivity analysis was performed where statistical heterogeneity existed. RESULTS: We included 10 prospective studies covering 214,059 participants and 9,597 cases. There was overall 3.5% higher fracture risk for an increment of one cup of coffee per day (RR = 1.035, 95% CI: 1.019-1.052). Pooled RRs were 1.049 (95% CI: 1.022-1.077) for women and 0.910 (95% CI: 0.873-0.949) for men. Among women, RR was 1.055 (95% CI: 0.999-1.114) for younger participants, and 1.047 (95% CI: 1.016-1.080) for older ones. Cumulative meta-analysis indicated that risk estimates reached a stabilization level (RR = 1.035, 95% CI: 1.019-1.052), and it revealed a positive dose-response relationship between coffee consumption and risk of fractures either for men and women combined or women specifically. CONCLUSIONS: This meta-analysis suggests an overall harm of coffee intake in increasing the risk of fractures, especially for women. But current data are insufficient to reach a convincing conclusion and further research needs to be conducted.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it