Association between Dairy Product Intake and Risk of Fracture among Adults: A Cohort Study from China Health and Nutrition Survey
Bibliographic record
Abstract
Background: The current literature reports inconsistent associations between dairy product intake and fracture. This study assessed the association between dairy product intake and the risk of fracture among Chinese adults and examined the mediation effects of height and body mass index (BMI) on the association. Methods: Data in 1997−2015 from the China Health and Nutrition Survey were used. Dietary data were collected by a 24-hour dietary recall, and occurrences of fracture were obtained by self-report of participants. Cumulative average intake of daily dairy products was calculated by the sum of the dairy product intake and divided by the total waves of participating in the surveys before fracture. Cox proportion hazard regressions were performed to explore the associations between dairy product intake and the risk of fracture. Mediation analysis models were established to examine the mediation effects of height and BMI on the associations. Results: A total of 14,711 participants were included. Dairy product intake of 0.1−100 g/day was associated with a decreased risk of fracture, while no association was observed among participants with dairy product intake of >100 g/day. The indirect effects of dairy product intake on the fracture mediated by height and BMI were much smaller than the direct effects. Conclusions: Dairy product intake with 0.1−100 g/day is associated with a lower risk of fracture, and the association is mainly a direct result of nutrients in dairy products and much less a result of the mediation effects of height or BMI. Dairy product intake of 0.1−100 g/day might be a cost-effective measure for Chinese adults to decrease fracture incidence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".