Outdoor nitrogen dioxide exposure and longitudinal health status trajectory in the Canadian National Population Health Survey
Bibliographic record
Abstract
Abstract Few studies have examined the association between air pollution and the trajectory of global health status measures related to the functional impacts of chronic disease. To address this gap, we examined the trajectory of the Health Utilities Index (HUI) over 17 years of follow-up among Canadian National Population Health Survey (NPHS) participants. Annual average nitrogen dioxide (NO 2 ) exposures from a national land use regression surface were mapped to 15,631 NPHS participants at their place of residence provided at each follow-up. We modelled HUI trajectory as a cubic polynomial function of age in relation to air pollution and selected covariates using random growth curve models to account for longitudinal repeated measures. Adjusting for covariates selected based on a directed acyclic graph, we found that NO 2 exposure exhibited a significant negative association with HUI in females. It also exhibited a significant positive interaction with the linear age term, and a significant negative interaction with the quadratic age term, resulting in a small non-significant decrease in quality adjusted life years lived after age 20 among females. Our analysis provides a proof of concept for examining the influence of built environment variables on the trajectory of health related quality of life in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".