Dietary Copper Intake and Bone Health: A Systematic Review and Meta-Analysis of Observational Studies
Bibliographic record
Abstract
Abstract Studies evaluating habitual dietary copper intake and bone mineral density have garnered significant interest due to copper’s indispensable role in collagen cross-linking and osteogenesis. These investigations, which employ dietary assessment tools alongside DXA measurements of skeletal sites, have nonetheless yielded heterogeneous results regarding the impact of copper consumption on bone health. Consequently, elucidating the nature and magnitude of this association is of paramount importance for both nutritional epidemiology and osteoporosis prevention. The review was conducted in accordance with PRISMA guidelines and registered in Prospero (CRD42024617075). Electronic literature searches were performed up to February 2025 in EMBASE, PubMed, OVID, Scopus, and Web of Science to identify observational studies assessing dietary copper intake and DXA-measured BMD, and study quality was appraised using the Newcastle–Ottawa Scale. Data were pooled via a generic inverse-variance random-effects model, with heterogeneity assessed by the Q test and I 2 statistic. A random-effects meta‐analysis of three studies (n = 9059) found that higher dietary copper intake was associated with a modest but significant increase in lumbar spine BMD (MD 0.02 g/cm 2 ; 95% CI 0.00–0.04; p = 0.04; I 2 = 36%), whereas a separate meta‐analysis of four studies (n = 14,345) for hip BMD showed a similar MD of 0.02 g/cm 2 that did not reach significance (95% CI − 0.00–0.04; p = 0.07; I 2 = 74%). Higher dietary copper intake is modestly associated with increased lumbar spine BMD, while evidence for hip BMD remains inconclusive, underscoring copper’s potential role in osteoporosis prevention.
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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 | 0.017 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.030 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".