Ambient particulate air pollution and acute lower respiratory infections: a systematic review and implications for estimating the global burden of disease
Bibliographic record
Abstract
Acute lower respiratory infections (ALRI) account for nearly one fifth of mortality in young children worldwide and have been associated with exposures to indoor and outdoor sources of combustion-derived air pollution. A systematic review was conducted to identify relevant articles on air pollution and ALRI in children. Using a Bayesian approach to meta-analysis, a summary estimate of 1.12 (1.03, 1.30) increased risk in ALRI occurrence per 10 μg/m 3 increase in annual average PM 2.5 concentration was derived from the longer-term (subchronic and chronic) effects studies. This analysis strengthens the evidence for a causal relationship between exposure to PM 2.5 and the occurrence of ALRI and provides a basis for estimating the global attributable burden of mortality due to ALRI that is not influenced by the wide variation in regional case fatality rates. Most studies, however, have been conducted in settings with relatively low levels of PM 2.5 . Extrapolating their results to other, more polluted, regions will require a model that is informed by evidence from studies of the effects on ALRI of exposure to PM 2.5 from other combustion sources, such as secondhand smoke and household solid fuel use.
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 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 | 0.009 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".