Dairy intake and risk of hip fracture in prospective cohort studies: non-linear algorithmic dose-response analysis in 486 950 adults
Bibliographic record
Abstract
Abstract Previous studies on the relationship between dairy consumption and hip fracture risk have reported inconsistent findings. Therefore, we aimed to conduct an algorithmically driven non-linear dose-response meta-analysis of studies assessing dairy intake and risk of developing incident hip fracture. Meta-analysis from PubMed and Google Scholar searches for articles of prospective studies of dairy intake and risk of hip fracture, supplemented by additional detailed data provided by authors. Meta-regression derived dose-response relative risks, with comprehensive algorithm-driven dose assessment across the entire dairy consumption spectrum for non-linear associations. Review of studies published in English from 1946 through December 2021. A search yielded 13 studies, with 486 950 adults and 15 320 fractures. Non-linear dose models were found to be empirically superior to a linear explanation for the effects of milk. Milk consumption was associated with incrementally higher risk of hip fractures up to an intake of 400 g/d, with a 7 % higher risk of hip fracture per 200 g/d of milk (RR 1⋅07, 95 % CI 1⋅05, 1⋅10; P < 0⋅0001), peaking with 15 % higher risk (RR 1⋅15, 95 % CI 1⋅09, 1⋅21, P < 0⋅0001) at 400 g/d versus 0 g/d. Although there is a dose-risk attenuation above 400 g/d, milk consumption nevertheless continued to exhibit elevated risk of hip fracture, compared to zero intake, up to 750 g/d. Meanwhile, the analysis of five cohort studies of yoghurt intake per 250 g/d found a linear inverse association with fracture risk (RR 0⋅85, 95 % CI 0⋅82, 0⋅89), as did the five studies of cheese intake per 43 g/d (~1 serving/day) (RR 0⋅81, 95 % CI 0⋅72, 0⋅92); these studies did not control for socioeconomic status. However, no apparent association between total dairy intake and hip fracture (RR per 250 g/d of total dairy = 0⋅97, 95 % CI 0⋅93, 1⋅004; P = 0⋅079). There were both non-linear effects and overall elevated risk of hip fracture associated with greater milk intake, while lower risks of hip fracture were reported for higher yoghurt and cheese intakes.
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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 | 0.026 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.034 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".