MétaCan
Menu
Back to cohort
Record W2982170902 · doi:10.1016/j.envint.2019.105182

Associations between incident breast cancer and ambient concentrations of nitrogen dioxide from a national land use regression model in the Canadian National Breast Screening Study

2019· article· en· W2982170902 on OpenAlexafffundabout
Mark S. Goldberg, Paul J. Villeneuve, Dan L. Crouse, Teresa To, Scott Weichenthal, Claus Wall, Anthony B. Miller

Bibliographic record

VenueEnvironment International · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsHospital for Sick ChildrenPublic Health OntarioMcGill University Health CentreCarleton UniversityMcGill UniversityHealth CanadaUniversity of TorontoUniversity of New Brunswick
FundersHealth Canada
KeywordsBreast cancerMedicineDemographyConfidence intervalRelative riskProportional hazards modelEpidemiologyRate ratioCohort studyCancer registryCancerHazard ratioEnvironmental healthPopulationGynecologyInternal medicine

Abstract

fetched live from OpenAlex

Air pollution has been classified as a human carcinogen based largely on epidemiological studies of lung cancer. Recent research suggests that exposure to ambient air pollution increases the risk of female breast cancer especially in premenopausal women. Our objective was to determine the association between residential exposure to ambient nitrogen dioxide (NO2) and newly diagnosed cases of invasive breast cancer in a cohort of 89,247 women enrolled in the Canadian National Breast Screening Study between 1980 and 1985. Vital status and incident breast cancers through 2005 were determined through record linkage to the Canadian national mortality and cancer registries. Estimates of exposures to NO2 using participants’ addresses at time of entry into the study were derived from a national land use regression model. We classified women as reaching menopause according to information obtained at baseline. In addition, as we had no information from women on their menopausal status during the observation period, we conducted analyses using different cut-points for defining postmenopausal status (i.e., at 50 or at 52 years of age), and hence we had four non-independent cohorts. We computed rate ratios for the incidence of breast cancer and their 95% confidence intervals (CI) separately for premenopausal and postmenopausal women. Our Cox models used attained age as the time axis and the rate ratios were adjusted for several individual-level risk factors, including reproductive history, as well as census-based neighborhood-level characteristics. The median concentration of NO2 was about 15 parts per billion (ppb). After adjusting for personal risk factors and contextual variables, we found no evidence of associations for the incidence of breast cancer in the postmenopausal cohorts. In premenopausal women, the rate ratio for an increase of 9.7 ppb (about the interquartile range) was 1.13 (95%CI: 0.94–1.37) for the 50 years of age cut-off for menopausal status and it was 1.17 (95%CI: 1.00–1.38) for the 52 years of age cut-off. Our findings suggest that exposure to low concentrations of NO2, a marker for traffic-related air pollution, increases the risk of premenopausal breast cancer, but not postmenopausal breast cancer.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.053
GPT teacher head0.312
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; a candidate call from one teacher head, not a consensus.

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

Citations45
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueEnvironment InternationalSame topicAir Quality and Health ImpactsFrench-language works237,207