A Crossover Study of In-Vehicle Air Filtration and Acute Changes in Heart Rate Variability and Cognition among Healthy Adults
Bibliographic record
Abstract
Background: Traffic-related air pollutants (TRAP) are known to negatively affect cardiovascular health, and personal exposures may be highest during rush hour commutes. We examined the effectiveness of cabin air filtration at reducing in-vehicle exposures to TRAP, and whether these exposures were associated with short term changes in heart rate variability (HRV) and cognition in healthy adults.Methods: A crossover study of cabin air filtration and in-cabin exposure to TRAP was conducted in Montreal, Canada in 2014. Forty-eight participants were exposed to TRAP during two separate commutes of approximately 90 minutes: one trip with an electrostatic cabin air filter and one trip without a cabin air filter. In-vehicle and outdoor rooftop measures of ultrafine particles (UFPs), fine particle matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), and volatile organic compounds (VOCs) were collected during the commute. HRV parameters were measured before, during, and after each exposure period. Linear mixed effects models were used to examine relationships between in-cabin air pollution concentrations and changes in time and frequency domain measures of HRV.Results: The cabin air filter reduced in-vehicle UFP concentrations by 28%, (mean difference= 26,232/cm3, 95% CI: 11,733-40,730), PM2.5 by 30% (mean difference= 6 ug/m3 95% CI: 5-8), and BC by 32% (mean difference= 1,348 ng/m3 95% CI: -1,654-1,042 ng/m3). The air filter did not reduce in-vehicle concentrations of NO2 or VOCs. In general, cabin air filtration was not consistently associated with changes in HRV. PM2.5, UFPs and BC were positively associated with changes in both time and frequency-domain measures of HRV during and after the commute; these associations tended to be stronger among women.Conclusions: Electrostatic cabin air filters can lower in-vehicle exposures to TRAP, particularly those pollutants produced in high concentrations by diesel vehicle traffic, and may modify acute cardiac effects of TRAP.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".