Acute Blood Pressure and Cardiovascular Effects of Near-Roadway Exposures With and Without N95 Respirators
Bibliographic record
Abstract
BACKGROUND: The risk for cardiovascular events increases within hours of near-roadway exposures. We aimed to determine the traffic-related air pollution (TRAP) and biological mechanisms involved and if reducing particulate matter <2.5 µm (PM2.5) inhalation is protective. METHODS: Fifty healthy-adults underwent multiple 2-hour near-roadway exposures (Tuesdays to Fridays) in Ann Arbor during 2 separate weeks (randomized to wear an N95 respirator during 1 week). Monday both weeks, participants rested 2 hours in an exam room (once wearing an N95 respirator). Brachial blood pressure, aortic hemodynamics, and heart rate variability were repeatedly measured during exposures. Endothelial function (reactive hyperemia index [RHI]) was measured post-exposures (Thursdays). Black carbon (BC), total particle count (PC), PM2.5, noise and temperature were measured throughout exposures. RESULTS: PM2.5 (9.3 ± 7.7 µg/m3), BC (1.3 ± 0.6 µg/m3), PC (8,375 ± 4,930 particles/cm3) and noise (69.2 ± 4.2 dB) were higher (P values <0.01) and aortic hemodynamic parameters trended worse while near-roadway (P values<0.15 vs. exam room). Other outcomes were unchanged. Aortic hemodynamics trended towards improvements with N95 respirator usage while near-roadway (P values<0.15 vs. no-use), whereas other outcomes remained unaffected. Higher near-roadway PC and BC exposures were associated with increases in aortic augmentation pressures (P values<0.05) and trends toward lower RHI (P values <0.2). N95 respirator usage did not mitigate these adverse responses (nonsignificant pollutant-respirator interactions). Near-roadway outdoor-temperature and noise were also associated with cardiovascular changes. CONCLUSIONS: Exposure to real-world combustion-derived particulates in TRAP, even at relatively low concentrations, acutely worsened aortic hemodynamics. Our mixed findings regarding the health benefits of wearing N95 respirators support that further studies are needed to validate if they adequately protect against TRAP given their growing worldwide usage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".