Review of the Acute Effects of the Daily Exposure to Particulate Matter on Lung Function and Lung Inflammation in Healthy Subjects
Bibliographic record
Abstract
The effects of daily exposure of particles in ambient air on acute respiratory outcomes have shown inconsistent results, and no meta-analysis about this topic has been performed. We aimed to review studies on the association between the daily exposure to particles in ambient air and in occupational settings, and their acute effects on lung function and lung inflammation of healthy adults.Original studies published between 2000 and 2017 were searched in Web of Science, Medline and Pubmed. Studies were included if they assessed exposure to particles (number or mass concentration), and measured at least one spirometric parameter or fractional exhaled nitric oxide (FeNO). Studies were excluded if respiratory outcomes were not measured within 24 hours after exposure, if there was no baseline for health outcomes or if the study population was not composed of healthy adults.2447 studies were considered, and 239 studies were retained after the first screening (title + abstract). The final selection included 51 environmental (27 cross-over, 20 panel and 4 cross-sectional studies) and 34 occupational studies (27 cross-shift, 5 cross-over and 2 panel studies). The most frequent fractions of particulate matter assessed were PM2.5 (41), PM10 (20) and UFP (19). 31 studies evaluated FeNO, while 70 studies included spirometric measures (FEV1 (63), FVC (48), PEF (32) and FEV1/FVC (20) were the most frequent). Population (i.e. age) and exposure characteristics (i.e. duration, composition, type of monitoring, exposure levels) varied greatly between studies. There was also a large variability in the associations observed. Future studies should assess factors that explain such variability.
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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 | 0.001 | 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".