The Impact of the 2002 Delaware Smoking Ordinance on Heart Attack and Asthma
Bibliographic record
Abstract
In the United States, smoking is the leading cause of death - having a mortality rate of approximately 435,000 people in 2000-accounting for 8.1% of all US deaths recorded that year. Consequently, we analyzed the Delaware Hospital Discharge Database, and identified state and non-state residents discharged with AMI or asthma for the years 1999 to 2004. Statistical data analysis compared the incidence of AMI or asthma for each group before (1999-2002) and after (2003-2004) the amendment. As a result, we found that pre-ordinance and post-ordinance quarterly rates of AMI for Delaware residents were 451 (se = 21) and 430 (se = 21) respectively, representing a 4.7% reduction. Over the same time period, there was negligible change in the incidence of AMI for non-Delaware residents. After adjusting for population growth, the Risk Ratio (RR) for asthma in Delaware residents post-ordinance was 0.95 (95% CI, 0.90 to 0.999), which represented a significant reduction (P = 0.046). By comparison, non-Delaware residents had an increased RR for asthma post-ordinance of 1.62 (95% CI, 1.46 to 1.86; P < 0.0001).The results suggest that Delaware's comprehensive non-smoking ordinance effectively was associated with a statistically significant decrease in the incidence of AMI and asthma in Delaware residents when compared to non-Delaware residents.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".