Residential greenness and risk of prostate cancer: A case-control study in Montreal, Canada
Bibliographic record
Abstract
BACKGROUND: Recent studies suggest that exposure to greenness favors several health outcomes. We assessed whether living in the proximity of greener areas was related to prostate cancer incidence in a population-based case-control study in Montreal, Canada. MATERIALS AND METHODS: Interviews eliciting lifetime addresses were conducted with 1933 prostate cancer cases diagnosed in 2005-2009 and 1994 population controls. Odds ratios (OR) and 95% confidence intervals (CI) estimated the association between residential greenness, both at recruitment (2005-2009) and about ten years prior (1996), defined by the normalized difference vegetation index (NDVI) around the home, and prostate cancer risk. Three models were developed adjusting for age, individual characteristics, and individual and ecological characteristics, estimating relative risk in relation to an interquartile range (IQR) increase of the NDVI. RESULTS: We observed inverse associations between greenness measured within home buffers of 150m, 300m, 500m and 1000m, at both time points, and risk of prostate cancer, independently of individual and ecological characteristics. For instance, using a buffer of 300m, the OR for an IQR increase of 0.11 in NDVI at the time of recruitment was 0.82 (95%CI 0.74-0.92). The corresponding OR for an IQR increase of 0.15 in NDVI in 1996 was 0.86 (95%CI 0.74-1.00). There were little differences in risks according to buffer size, the time point of exposure, when considering prostate cancer aggressiveness, or when restricting controls to men recently screened for prostate cancer to reduce the likelihood of undiagnosed cancer among them. CONCLUSION: Men living in greener areas, either recently or about a decade earlier, had lower risks of prostate cancer, independently of socio-demographic and lifestyle factors. These observations are novel and require confirmation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.003 | 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".