Differences in blood pressure and vascular responses associated with ambient fine particulate matter exposures measured at the personal versus community level
Bibliographic record
Abstract
BACKGROUND: Higher ambient fine particulate matter (PM₂.₅) levels can be associated with increased blood pressure and vascular dysfunction. OBJECTIVES: To determine the differential effects on blood pressure and vascular function of daily changes in community ambient- versus personal-level PM₂.₅ measurements. METHODS: Cardiovascular outcomes included vascular tone and function and blood pressure measured in 65 non-smoking subjects. PM₂.₅ exposure metrics included 24 h integrated personal- (by vest monitors) and community-based ambient levels measured for up to 5 consecutive days (357 observations). Associations between community- and personal-level PM₂.₅ exposures with alterations in cardiovascular outcomes were assessed by linear mixed models. RESULTS: Mean daily personal and community measures of PM₂.₅ were 21.9±24.8 and 15.4±7.5 μg/m³, respectively. Community PM₂.₅ levels were not associated with cardiovascular outcomes. However, a 10 μg/m³ increase in total personal-level PM₂.₅ exposure (TPE) was associated with systolic blood pressure elevation (+1.41 mm Hg; lag day 1, p<0.001) and trends towards vasoconstriction in subsets of individuals (0.08 mm; lag day 2 among subjects with low secondhand smoke exposure, p=0.07). TPE and secondhand smoke were associated with elevated systolic blood pressure on lag day 1. Flow-mediated dilatation was not associated with any exposure. CONCLUSIONS: Exposure to higher personal-level PM₂.₅ during routine daily activity measured with low-bias and minimally-confounded personal monitors was associated with modest increases in systolic blood pressure and trends towards arterial vasoconstriction. Comparable elevations in community PM₂.₅ levels were not related to these outcomes, suggesting that specific components within personal and background ambient PM₂.₅ may elicit differing cardiovascular responses.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".