TRAFFIC-RELATED AIR POLLUTION AND ACUTE CHANGES IN HEART RATE VARIABILITY AND RESPIRATORY FUNCTION IN URBAN CYCLISTS
Bibliographic record
Abstract
Background and Aims: Few studies have examined the acute health effects of air pollution exposures experienced while cycling in traffic. The aim of this study was to examine the relationship between traffic-related air pollutants and acute changes in heart rate variability, lung function, and exhaled NO in healthy cyclists. Methods: Forty-two healthy adults (19 to 58 years of age) cycled for 1-hour on high and low-traffic routes as well as indoors. Ultrafine particles (UFPs) (<0.1 um), PM2.5, black carbon, and volatile organic compounds were measured along each cycling route and ambient NO2, SO2, and O3 levels were recorded from a fixed-site monitor. Mixed-effects models were used to examine the relationship between air pollution exposures and changes in baseline health measures adjusted for potential confounders. Results: An inter-quartile range increase in UFP levels was associated with a 220 ms decrease (95% confidence interval: -386, -53) (approximately 35 %) in high frequency power 4-hours after the start of cycling. Significant inverse relationships were also observed between NO2 and the ratio of low-frequency to high-frequency power and between O3, root mean square of successive differences in adjacent NN intervals (RMSSD), and percentage of adjacent NN intervals differing by more than 50 ms (pNN50). Acute changes in respiratory outcomes were not consistently associated with air pollution levels. Conclusions: Exposure to traffic-related air pollution may contribute to decreased parasympathetic modulation of the heart in the hours immediately following cycling.
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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) | 0.000 | 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) | 0.002 | 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".