Acute Blood Pressure Responses in Healthy Adults During Controlled Air Pollution Exposures
Bibliographic record
Abstract
Exposure to air pollution has been shown to cause arterial vasoconstriction and alter autonomic balance. Because these biologic responses may influence systemic hemodynamics, we investigated the effect of air pollution on blood pressure (BP). Responses during 2-hr exposures to concentrated ambient fine particles (particulate matter < 2.5 microm in aerodynamic diameter; PM2.5) plus ozone (CAP+O3) were compared with those of particle-free air (PFA) in 23 normotensive, nonsmoking healthy adults. Mean concentrations of PM2.5 were 147 +/- 27 versus 2 +/- 2 microg/m3, respectively, and those of O3 were 121 +/- 3 versus 8 +/- 5 ppb, respectively (p < 0.0001 for both). A significant increase in diastolic BP (DBP) was observed at 2 hr of CAP+O3 [median change, 6 mm Hg (9.3%); binomial 95% confidence interval (CI), 0 to 11; p = 0.013, Wilcoxon signed rank test] above the 0-hr value. This increase was significantly different (p = 0.017, unadjusted for basal BP) from the small 2-hr change during PFA (median change, 1 mm Hg; 95% CI, -2 to 4; p = 0.24). This prompted further investigation of the CAP+O3 response, which showed a strong association between the 2-hr change in DBP (and mean arterial pressure) and the concentration of the organic carbon fraction of PM2.5 (r = 0.53, p < 0.01; r = 0.56, p < 0.01, respectively) but not with total PM2.5 mass (r < or = 0.25, p > or = 0.27). These findings suggest that exposure to environmentally relevant concentrations of PM2.5 and O3 rapidly increases DBP. The magnitude of BP change is associated with the PM2.5 carbon content. Exposure to vehicular traffic may provide a common link between our observations and previous studies in which traffic exposure was identified as a potential risk factor for cardiovascular disease.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".