Dairy Food Consumption and Mammographic Breast Density: The Role of Fat
Bibliographic record
Abstract
Aim: This cross-sectional study aimed to evaluate the associations between low and high-fat dairy food (DF) intake and breast density (BD). Materials and Methods: A total of 775 premenopausal and 771 postmenopausal women recruited during screening mammography completed a food frequency questionnaire. Adjusted linear regression models were used to assess the associations. Results: As frequency quartiles of high-fat DF consumption increased, the adjusted mean of absolute BD increased from 31.5 to 36.1 cm<sup>2</sup> for all women (p<sub>trend</sub>=0.0034) and from 42.4 to 50.1 cm<sup>2</sup> for premenopausal women (p<sub>trend</sub>=0.0047). Conversely, as frequency quartiles of low-fat DF consumption increased, the adjusted mean of absolute BD decreased from 34.7 to 29.6 cm<sup>2</sup> for all women (p<sub>trend</sub>=0.001) and from 49.7 to 40.7 cm<sup>2</sup> for premenopausal women (p<sub>trend</sub>=0.0012). Conclusion: A higher intake of high-fat and low-fat DF is respectively associated with higher and lower BD, particularly in premenopausal women.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".