The Relationship between Ambient Air Pollution and Heart Rate Variability Differs for Individuals with Heart and Pulmonary Disease
Bibliographic record
Abstract
Associations between concentrations of ambient fine particles [particulate matter < 2.5 microm aerodynamic diameter (PM2.5)] and heart rate variability (HRV) have differed by study population. We examined the effects of ambient pollution on HRV for 18 individuals with chronic obstructive pulmonary disease (COPD) and 12 individuals with recent myocardial infarction (MI) living in Atlanta, Georgia. HRV, baseline pulmonary function, and medication data were collected for each participant on 7 days in fall 1999 and/or spring 2000. Hourly ambient pollution concentrations were obtained from monitoring sites in Atlanta. The association between ambient pollution and HRV was examined using linear mixed-effect models. Ambient pollution had opposing effects on HRV in our COPD and MI participants, resulting in no significant effect of ambient pollution on HRV in the entire population for 1-, 4-, or 24-hr moving averages. For individuals with COPD, interquartile range (IQR) increases in 4-hr ambient PM2.5 (11.65 microg/m3)) and nitrogen dioxide (11.97 ppb) were associated with 8.3% [95% confidence interval (CI), 1.7-15.3%] and 7.7% (95% CI, 0.1-15.9%) increase in the SD of normal R-R intervals (SDNN), respectively. For individuals with MI, IQR increases in 4-hr PM2.5 (8.54 microg/m3) and NO2 (9.25 ppb) were associated with a nonsignificant 2.9% (95% CI, -7.8 to 2.3) and significant 12.1 (95% CI, -19.5 to -4.0) decrease in SDNN. Beta-blocker and bronchodilator intake and baseline forced expiratory volume in 1 sec modified the PM-SDNN association significantly, with effects consistent with those by disease group. Results indicate heterogeneity in the autonomic response to air pollution due to differences in baseline health, with significant associations for ambient NO2 suggesting an important role for traffic-related pollution.
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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 | 0.002 | 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 | 0.002 | 0.001 |
| 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".