Association Between Traffic Volume and Health Care Use for Asthma Among Residents at a U.S.–Canadian Border Crossing Point
Bibliographic record
Abstract
Little information is available about health impacts of the North American Free Trade Agreement (NAFTA) traffic-related pollution on residents near the major traffic corridors along the U.S.-Canadian border. Here we report on a 10 year (1991-2000) retrospective study of commercial traffic volumes across the Peace Bridge and health care use for asthma in a residential community, which serves as a conduit for traffic crossing between Fort Erie, Ontario, Canada, and Buffalo, New York. We hypothesized that commercial traffic pollution was impacting on residents in close proximity to the trade corridor. Commercial traffic volumes, hospital discharges for asthma, and outpatient visits to area hospitals and clinics were analyzed before and after implementation of NAFTA. Results showed a positive association between increased commercial traffic volume and increased health care use for asthma. Zip codes 14201 and 14213, which surround the Peace Bridge Plaza Complex (PBC), had the highest prevalence rates and health care use rates for asthma. Statistical analysis showed the findings to be significant (p < 0.05) in that residential proximity to the PBC was associated with greater hospital discharge rates for asthma. The findings were strongest (p < 0.000) in the zip codes where the PBC was located (14213) and the major highway I-190 passed through (14201). A yearly excess of 230.2 adult asthma hospital discharges was associated with an increase in traffic volume during the period from 1991 to 1996 in the study area. This is in contrast to an overall decrease in the national rate of hospitalizations for asthma by 7.5% in the same period. The results suggest that NAFTA-related commercial traffic has a negative health impact on asthmatics living in close proximity to the trade corridor. Health and social costs due to traffic pollution need to be included in cost estimates of transport decisions related to the NAFTA corridors. Similar health effects due to NAFTA traffic need to be studied at other U.S.-Canada border crossing points.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".