Exposure to Ambient and Nonambient Components of Particulate Matter
Bibliographic record
Abstract
BACKGROUND: Numerous epidemiologic studies report associations between outdoor concentrations of particles and adverse health effects. Because personal exposure to particles is frequently dominated by exposure to nonambient particles (those originating from indoor sources), we present an approach to evaluate the relative impacts of ambient and nonambient exposures. METHODS: We developed separate estimates of exposures to ambient and nonambient particles of different size ranges (PM2.5, PM10-2.5 and PM10) based on time-activity data and the use of particle sulfate measurements as a tracer for indoor infiltration of ambient particles. To illustrate the application of these estimates, associations between cardiopulmonary health outcomes and the estimated exposures were compared with associations computed using measurements of personal exposures and outdoor concentrations for a repeated-measures panel study of 16 patients with chronic obstructive pulmonary disease conducted in the summer of 1998 in Vancouver. RESULTS: Total personal fine particle exposures were dominated by exposures to nonambient particles, which were not correlated with ambient fine particle exposures or ambient concentrations. Although total and nonambient particle exposures were not associated with any of the health outcomes, ambient exposures (and to a lesser extent ambient concentrations) were associated with decreased lung function, decreased systolic blood pressure, increased heart rate, and increased supraventricular ectopic heartbeats. Measures of heart rate variability showed less consistent relationships among the various exposure metrics. CONCLUSIONS: These results demonstrate the usefulness of separating total personal particle exposures into their ambient and nonambient components. The results support previous epidemiologic findings using ambient concentrations by demonstrating an association between health outcomes and ambient (outdoor origin) particle exposures but not with nonambient (indoor origin) particle exposures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".