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Greenness, Obesity and Incident Breast Cancer: Evidence from the Canadian National Breast Screening Study

2019· article· en· W2981968200 on OpenAlexaffabout
Paul J. Villeneuve, Reza Mansouri, Dan L. Crouse, To T, Clare Wall, Anthony B. Miller

Bibliographic record

VenueEnvironmental Epidemiology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of New BrunswickUniversity of TorontoCarleton University
Fundersnot available
KeywordsBreast cancerMedicineBody mass indexObesityNational Death IndexMammographyDemographyEnvironmental healthHazard ratioIncidence (geometry)Normalized Difference Vegetation IndexCancerConfidence intervalInternal medicineClimate change

Abstract

fetched live from OpenAlex

S07: Of moderators and mediators: Complex relationships between greenness, air pollution, noise, and health behaviors in driving health outcomes, Beatrix Theater, August 27, 2019, 10:30 AM - 12:00 PM Background: Breast cancer is the most commonly diagnosed cancer among Canadian women. Environmental exposures, including air pollution, have been associated with an increased risk of breast cancer. More recently, findings from a multi-centre case-control study in Spain, and the US Nurses Health Study suggest that proximity to greenness may reduce the risk of breast cancer. Both publications highlight the need to better understand the pathways involved. Methods: To address this gap, we investigated associations between residential greenness, obesity and the incidence of breast cancer among 89,247 participants of the Canadian National Breast Screening Study. The original aim of this randomized controlled trial was to investigate whether mammography screening reduced the mortality of breast cancer. Enrollments occurred between 1980 and 1985, and record linkage to national cancer incidence identified approximately 6500 cases of breast cancer through 2005. Estimates of the Normalized Difference Vegetation Index (NDVI) within a 500 m buffer and ambient PM2.5 were linked to the participants’ place at residence at enrollment. Baseline surveys were used to collect information on risk factors for breast cancer, and measured height and weight were obtained used to derive body mass index (BMI). Cox proportional hazards models using attained age as the time scale were fit to provide estimates of the hazard ratios associated with the NDVI and BMI. Findings: Ambient PM2.5 and the NDVI were inversely associated with each other (r= - 0.14). An interquartile range increase in the NDVI was associated with a 4% reduction in the risk of breast cancer (hazard ratio (HR)=0.96, 95% CI=0.92 – 0.99). Analyses of variance indicated that those who were obese (BMI>30) lived in areas with a lower mean NDVI (p<0.05). Conclusions: Our findings provide further support for the hypothesis that proximity to greenness may reduce the risk of breast cancer independently of air pollution, or obesity.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.070
GPT teacher head0.329
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2019
Admission routes2
Has abstractyes

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