Long-Term Exposure to PM2.5 and Ozone and Acute Respiratory Infections Risk: A Community-Based Prospective Cohort Study (Preprint)
Bibliographic record
Abstract
Background: Acute respiratory infections (ARIs) remain a major global health concern. Although long-term air pollution exposure has been linked to ARIs, prospective evidence from community-based populations remains limited. Objective: This study aimed to quantify the burden of ARIs in the community and examine the associations between long-term exposure to particulate matter 2.5 (PM2.5) and ozone (O3) and the risks of ARIs, with additional analyses using influenza-like illness (ILI) as a more specific outcome. Methods: We conducted a prospective cohort study including 3617 residents in Shanghai, China, who were followed weekly for 1 year. Individual-level exposure to PM2.5 and O3 concentrations was estimated using high-resolution datasets. Cox proportional hazards models with shared frailty were applied to assess associations with ARIs. Exposure windows of 3, 6, 9, and 12 months were evaluated, and the optimal window was selected based on the Akaike information criterion. Effect estimates were reported per IQR increase. Dose-response relationships, subgroup analyses, and multiple sensitivity analyses were performed. Results: During 3217 person-years of follow-up, 885 ARI events were documented (0.27 per person-year). In the fully adjusted model using the 12-month exposure window, each IQR increase in PM2.5 was associated with higher risks of ARIs (hazard ratio [HR] 1.594, 95% CI 1.340-1.897), with stronger associations observed for ILI (HR 1.948, 95% CI 1.484-2.557). For O3, the corresponding HRs were 1.510 (95% CI 1.135-2.007) for ARIs, with stronger associations for ILI (HR 2.229, 95% CI 1.385-3.588). PM2.5 showed a nonlinear association with ARIs, whereas linear relationships were observed for PM2.5 with ILI and O3 with both outcomes. Evidence of effect modification was observed by age, residence, and season for PM2.5 and by season for O3. Results were robust across multiple sensitivity analyses. Conclusions: Long-term exposure to PM2.5 and O3 is associated with increased risk of ARIs, with similar associations observed for ILI. These findings highlight the importance of long-term air pollution control and targeted interventions for susceptible populations, particularly during cold seasons.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".