The Association between Planetary Health Diet Index with the Odds of Breast Cancer: A Case-Control Study
Bibliographic record
Abstract
Background: Breast cancer is the most common cancer among women worldwide. Diet is recognized as an important factor in the prevention of cancer. No research has evaluated the association between the Planetary Health Diet Index (PHDI) and breast cancer risk in the Iranian population. Therefore, the association between PHDI and breast cancer odds in Iranian women was examined in this study. Methods: The present case-control study (n=134 cases, n=267 controls) was conducted in two hospitals in Tehran, Iran. Women aged 30 or older diagnosed with breast cancer through biopsy were included. In the current study, the participants’ food consumption was assessed using a food frequency questionnaire, a reliable and valid tool. Results: A lower odds of breast cancer was observed in the last tertile of the PHDI compared to the first tertile in both crude and adjusted models [adjusted model: Odds Ratio (OR)=0.54; 95% Confidence Interval (CI): 0.31-0.95]. In the subgroup analysis, based on the menopausal status, in the fully adjusted model, lower odds of breast cancer were found in the last tertiles of PHDI compared to the first tertile in the post-menopausal group (OR=0.38; 95% CI: 0.17-0.84). Conclusion: The findings suggest an inverse association between higher PHDI scores and breast cancer risk. An inverse association between PHDI and breast cancer risk was also evident, particularly among post-menopausal women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".