Ultraviolet Sunlight Exposure During Adolescence and Adulthood and Breast Cancer Risk: A Population-based Case-Control Study Among Ontario Women
Bibliographic record
Abstract
Recent studies suggest that vitamin D may be associated with reduced breast cancer risk, but most studies have evaluated only dietary vitamin D intake. The associations among ultraviolet radiation from sunlight, factors related to cutaneous vitamin D production, and breast cancer risk were evaluated in a population-based case-control study conducted in Ontario, Canada, between 2003 and 2004 (n = 3,101 cases and n = 3,471 controls). Time spent outdoors was associated with reduced breast cancer risk during 4 periods of life (>21 vs. ≤6 hours/week age-adjusted odds ratio (OR) = 0.71, 95% confidence interval (CI): 0.60, 0.85 in the teenage years; OR = 0.64, 95% CI: 0.53, 0.76 in the 20s-30s; OR = 0.74, 95% CI: 0.61, 0.88 in the 40s-50s; and OR = 0.50, 95% CI: 0.37, 0.66 in the 60s-74 years). Sun protection practices and ultraviolet radiation were not associated with breast cancer risk. A combined solar vitamin D score, including all the variables related to vitamin D production, was significantly associated with reduced breast cancer risk. These associations were not confounded or modified by menopausal status, dietary vitamin D intake, or physical activity. This study suggests that factors suggestive of increased cutaneous production of vitamin D are associated with reduced breast cancer risk.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".