Association of Outdoor Allergens with Respiratory Allergic Diseases: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: The global burden of respiratory allergic diseases linked to outdoor allergens remains poorly quantified despite increasing evidence of the allergens' impacts on respiratory allergic diseases. This systematic review synthesizes epidemiological evidence on the association between exposure to outdoor airborne allergens and respiratory disease incidence. METHODS: Following PRISMA 2020 guidelines, we systematically searched three databases, PubMed, Embase, and the Cochrane Library, until December 2024. Observational studies reporting effect estimates for respiratory outcomes (asthma, allergic rhinitis, COPD exacerbations, and cough) associated with quantified outdoor allergen exposure were eligible. Two reviewers independently conducted screening, data extraction, and quality assessment using an adapted Newcastle-Ottawa Scale (NOS). Random-effects models were employed to pool odds ratios (ORs), with subgroup analyses by sex. Publication bias was evaluated using Begg's and Egger's tests, respectively. RESULTS: From 6,551 identified records, 7 articles with 70 studies (46,325 participants across 3 countries) met the inclusion criteria. High-quality studies (NOS ≥7) constituted 86% of the included articles. Pooled analyses revealed significant associations between outdoor allergen exposure and respiratory outcomes: OR = 1.03 (95% confidence interval [CI]: 1.01-1.04; p = 0.008). Egger's publication bias was non-significant (Egger's p = 0.21), and Begg's publication bias was also non-significant (Begg's p = 0.31). Trim-and-fill funnel plots suggested possible missing small-null studies, but the statistical analysis was non-significant. Sensitivity analyses confirmed robustness when excluding studies with potential residual confounding (pooled OR range: 1.02-1.06). Subgroup analyses demonstrated that the female subgroup, rather than the male subgroup, got stronger effects significantly: OR = 1.04 (95% CI: 1.01-1.07), compared with the male subgroup OR = 1.02 (95% CI: 0.99-1.04). CONCLUSIONS: This comprehensive synthesis provides high-quality evidence that outdoor allergen exposure significantly increases risks of respiratory allergic disease. The female is more likely to get respiratory morbidity compared with the male. Further research should prioritize harmonized exposure metrics and evaluate interactive effects with anthropogenic air pollutants.
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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 | 0.010 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".