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Record W3207359803 · doi:10.3390/ijerph182010571

Environmental and Occupational Short-Term Exposure to Airborne Particles and FEV1 and FVC in Healthy Adults: A Systematic Review and Meta-Analysis

2021· review· en· W3207359803 on OpenAlexafffund
Alan da Silveira Fleck, Margaux L. Sadoine, Stéphane Buteau, Eva Suarthana, Maximilien Debia, Audrey Smargiassi

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsInstitut National de Santé Publique du QuébecHôpital du Sacré-Cœur de MontréalMcGill University Health CentreUniversité de Montréal
FundersInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsMeta-analysisMedicineLung functionOccupational exposureEnvironmental healthInternal medicineLung

Abstract

fetched live from OpenAlex

Background: No study has compared the respiratory effects of environmental and occupational particulate exposure in healthy adults. Methods: We estimated, by a systematic review and meta-analysis, the associations between short term exposures to fine particles (PM2.5 and PM4) and certain parameters of lung function (FEV1 and FVC) in healthy adults. Results: In total, 33 and 14 studies were included in the qualitative synthesis and meta-analyses, respectively. In environmental studies, a 10 µg/m3 increase in PM2.5 was associated with an FEV1 reduction of 7.63 mL (95% CI: −10.62 to −4.63 mL). In occupational studies, an increase of 10 µg/m3 in PM4 was associated with an FEV1 reduction of 0.87 mL (95% CI: −1.36 to −0.37 mL). Similar results were observed with FVC. Conclusions: Both occupational and environmental short-term exposures to fine particles are associated with reductions in FEV1 and FVC in healthy adults.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.024
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.023
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.264
GPT teacher head0.477
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations8
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Environmental Research and Public Health→Same topicAir Quality and Health Impacts→French-language works237,207→