Association between annual exposure to air pollution and systolic blood pressure among adolescents in Montréal, Canada
Bibliographic record
Abstract
INTRODUCTION: In adults, chronic exposure to air pollution is associated with elevated blood pressure, but few studies have examined this relationship in youth. We investigated the association between annual ambient concentrations of air pollutants (fine particulate matter [PM2.5] and nitrogen dioxide [NO2]) and systolic blood pressure (SBP) among adolescents in Montréal, Canada. METHODS: Participants were students aged 15 to 17 years who provided SBP and residential postal code data in 2004/05 through their enrolment in the Nicotine Dependence in Teens study. Annual estimates for 2004 of residential exposure to NO2 and PM2.5 were provided by the Canadian Urban Environmental Health Research Consortium and linked to participants' residential postal code. Elevated SBP was defined as SBP ≥ 90th percentile adjusted for age, sex and height. Logistic regression was used to estimate odds ratios and 95% confidence intervals (CIs) for each pollutant with respect to elevated SBP, adjusted for relevant confounders. RESULTS: The sample consisted of 508 adolescents (mean age: 16.9, 46% male); 4% had elevated SBP. Although estimates were not statistically significant, there were generally modest positive associations between pollutant levels and SBP. The adjusted prevalence odds ratio of elevated SBP was 1.33 (95% CI: 0.64, 3.05) for every interquartile range (IQR) increase in residential PM2.5 levels (2.1μg/m3). Similarly, the adjusted prevalence odds ratio of elevated SBP was 1.17 (95% CI: 0.47, 2.70) for every IQR increase in residential NO2 levels (10.2 ppb). CONCLUSION: Findings support a possible relationship between exposure to air pollutants and increased SBP in adolescents, warranting further investigation for this important public health concern.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".