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Record W2981856627 · doi:10.1289/ehp5204

Examining the Shape of the Association between Low Levels of Fine Particulate Matter and Mortality across Three Cycles of the Canadian Census Health and Environment Cohort

2019· article· en· W2981856627 on OpenAlexaffabout
Amanda J. Pappin, Tanya Christidis, Lauren Pinault, Dan L. Crouse, Jeffrey R. Brook, Anders C. Erickson, Perry Hystad, Chi Li, Randall V. Martin, Jun Meng, Scott Weichenthal, Aaron van Donkelaar, Michael Tjepkema, Michael Bräuer, Richard T. Burnett

Bibliographic record

VenueEnvironmental Health Perspectives · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsHealth CanadaPublic Health OntarioUniversity of British ColumbiaDalhousie UniversityUniversity of New BrunswickUniversity of TorontoMcGill UniversityStatistics Canada
FundersHealth Effects InstituteU.S. Environmental Protection Agency
KeywordsHazard ratioDemographyConfidence intervalEnvironmental healthProportional hazards modelCensusCohortAerodynamic diameterMedicineAir pollutionParticulatesSocioeconomic statusCohort studyPopulationGeographyGerontologyEnvironmental scienceBiologyInternal medicine

Abstract

fetched live from OpenAlex

Background: Ambient fine particulate air pollution with aerodynamic diameter ≤2.5 μm (PM2.5) is an important contributor to the global burden of disease. Information on the shape of the concentration–response relationship at low concentrations is critical for estimating this burden, setting air quality standards, and in benefits assessments. Objectives: We examined the concentration–response relationship between PM2.5 and nonaccidental mortality in three Canadian Census Health and Environment Cohorts (CanCHECs) based on the 1991, 1996, and 2001 census cycles linked to mobility and mortality data. Methods: Census respondents were linked with death records through 2016, resulting in 8.5 million adults, 150 million years of follow-up, and 1.5 million deaths. Using annual mailing address, we assigned time-varying contextual variables and 3-y moving-average ambient PM2.5 at a 1×1 km spatial resolution from 1988 to 2015. We ran Cox proportional hazards models for PM2.5 adjusted for eight subject-level indicators of socioeconomic status, seven contextual covariates, ozone, nitrogen dioxide, and combined oxidative potential. We used three statistical methods to examine the shape of the concentration–response relationship between PM2.5 and nonaccidental mortality. Results: The mean 3-y annual average estimate of PM2.5 exposure ranged from 6.7 to 8.0 μg/m3 over the three cohorts. We estimated a hazard ratio (HR) of 1.053 [95% confidence interval (CI): 1.041, 1.065] per 10-μg/m3 change in PM2.5 after pooling the three cohort-specific hazard ratios, with some variation between cohorts (1.041 for the 1991 and 1996 cohorts and 1.084 for the 2001 cohort). We observed a supralinear association in all three cohorts. The lower bound of the 95% CIs exceeded unity for all concentrations in the 1991 cohort, for concentrations above 2 μg/m3 in the 1996 cohort, and above 5 μg/m3 in the 2001 cohort. Discussion: In a very large population-based cohort with up to 25 y of follow-up, PM2.5 was associated with nonaccidental mortality at concentrations as low as 5 μg/m3. https://doi.org/10.1289/EHP5204

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.049
GPT teacher head0.313
Teacher spread0.264 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations98
Published2019
Admission routes2
Has abstractyes

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