Transportation injury inequities among Canadian children in a linked, population-based cohort
Bibliographic record
Abstract
Transportation injury is a leading cause of morbidity and mortality for children. Risk is inequitable, but transportation injury studies often rely on ecological-level indicators of sociodemographics. This study examines individual and household-level social inequities in Canadian children which increase their risk of bicycling, pedestrian and motor vehicle occupant/driver injuries based on a unique linked data set. We analyzed three cohorts linking Canadian census data to health records: an emergency department (ED) cohort (n = ∼1,731,200), a hospitalization cohort (n = ∼3,615,500) and a mortality cohort (N = ∼4,664,000). We used Poisson regression to estimate the incidence rate ratio (IRR) of pedestrian, bicycling and motor vehicle occupant/driver injuries separately in each cohort. We found positive associations across most outcomes for male children and rural residence. For pedestrian and motor vehicle injuries, older age of the child at onset increased risk, while higher parental education level was protective. A single adult household was a predictor for traffic injury ED visits and hospitalizations for all modes of transportation studied. Commute mode of the child or adults in their household was associated with increased risk of both motor vehicle and bicycling injuries, suggesting it may have indicator value for household mode usage. Children experience varying risks of traffic injury based on household and individual characteristics, underscoring the need for systemic and targeted prevention efforts to reduce injuries and address health disparities. Future work could examine how preventive initiatives interact with social and area-level risk factors for children's traffic injury. • Individual sociodemographic factors influence risk of child transportation injuries. • Low income, low parental education, and rurality increased risk. • Indigenous status was one of the main risk factors for any type of child transportation-related hospitalizations. • Visible minority status, female sex, and urban residence decreased risk.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".