Exposure to ambient polycyclic aromatic hydrocarbons and early-onset female breast cancer in a case–control study in Ontario, Canada
Bibliographic record
Abstract
Background: Ambient polycyclic aromatic hydrocarbons (PAHs) are a class of toxicologically important and understudied air pollutants. Epidemiologic evidence suggests that chronic exposure to PAHs increases breast cancer risk; however, there are few studies in nonoccupational settings that focus on early-onset diagnoses. Methods: The relationship between residentially-based ambient PAH concentrations and female breast cancer, among those 18-45 years of age, was characterized in the Ontario Environment and Health Study (OEHS). The OEHS was a population-based case-control study undertaken in Ontario, Canada between 2013 and 2015. Primary incident breast cancers were identified within 3 months of diagnosis, and a population-based series of controls were recruited. Concentrations of ambient PAHs, using fluoranthene as a surrogate, were derived using a chemical transport model at a 2.5 km spatial resolution. These estimates were assigned to participants' residences at the time of the interview and 5 years prior. Logistic regression was used to estimate odds ratios (ORs) and their 95% confidence intervals (CIs) based on a quartile categorization of fluoranthene exposure while adjusting for a series of individual- and area-level risk factors. The shape of the exposure-response trend was evaluated using cubic splines. Results: , respectively. In models adjusted for a parsimonious set of risk factors, the highest quartile of exposure was associated with an increased risk of breast cancer (OR = 2.16; 95% CI = 1.22, 3.84). Restricted spline analyses revealed nonlinear dose-response patterns. Conclusions: These findings support the hypothesis that ambient PAH exposures increases the risk of early-onset breast cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".