PM2.5 and hospitalizations through the emergency department in people with disabilities: a nationwide case-crossover study in South Korea
Bibliographic record
Abstract
Background Little is known about the impact of PM 2.5 on people with disabilities. We aimed to explore the association between PM 2.5 and hospitalization via the emergency department (ED admission) among people with disabilities, together with the attributable ED admission cases and costs. Methods We applied a time-stratified case-crossover design adjusting ozone, holiday, and temperature using seven years (2015–2021) of claim-based data on ED admissions from the Korean National Health Insurance Database. The analysis included all ED admission cases of beneficiaries with disabilities living in Korea (physical, intellectual, and mental disabilities; brain lesion disorders; blindness or vision loss; deafness or hearing loss; and autism) as well as selected controls without disabilities. Findings There were 900,311 ED admissions among the 3,624,590 people with disabilities. The odds ratios of ED admissions associated with a 10 μg/m 3 increase in PM 2.5 were 1.039 (95% CI: 1.036–1.042) in people with disabilities and 1.022 (95% CI: 1.019–1.025) in people without disabilities. Individuals with mental disability, intellectual disability, and brain lesion disorder showed higher risk estimates compared to other disabilities. The risk estimates of ED admissions for cardiovascular and genitourinary diseases were more prominent among people with disabilities than those without disabilities. Interpretation The impacts of PM 2.5 on ED admissions was generally higher in the population with disabilities than those without disabilities, especially for certain causes of admission. These results could contribute to establishing targeted action plans including early warning system referring different threshold concentrations. Funding National Research Foundation.
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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 | 0.001 |
| 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".