Predictors of Unintentional Injuries in Paediatric Immigrants in Ontario
Bibliographic record
Abstract
Abstract BACKGROUND: Unintentional injury is a frequent reason for emergency department visits and is the leading cause of death for Canadian children. Injury is associated with a number of socio-demographic variables but it is not known whether being an immigrant changes this risk. OBJECTIVES: To examine the association between family immigrant status and unintentional injury; and to test this relationship within immigrants by refugee status. DESIGN/METHODS: Retrospective population-based cross-sectional study of children ages 0 to 14 years residing in Ontario, Canada from 2008 to 2012, using linked health administrative databases and Citizenship and Immigration Canada’s Permanent Resident Database. The main exposure was immigration status (immigrant or child of an immigrant vs. Canadian born). Secondary exposure was refugee status. Main outcome measure was unintentional injury events (emergency department visits, hospitaliza-tions, deaths), annualized. Data were analyzed using Poisson regression models to estimate risk ratios (RR) for unintentional injuries. RESULTS: There were 11 464 317 injuries per year. Non-immigrant children sustained 12051 injuries/100 000 and immigrants had 6837 injuries/100 000, annually. In adjusted models, immigrants had a significantly lower risk of injury compared with non-immigrant children (RR 0.60; 95% confidence interval [CI] 0.57, 0.63). Overall, the most materially deprived neighbourhood quintile was associated with a higher rate of injury (RR 1.13; 95% CI 1.07, 1.02, quintile 5 vs. 1) whereas within immigrants, material deprivation was associated with a lower rate of injury (RR 0.96; 95% CI 0.94, 0.98, quintile 5 vs. 1). Other predictors of injury included age (0 to 4 years: RR 0.84; 95% CI 0.81, 0.88; 5 to 9 years: RR 0.70; 95% CI 0.67, 0.73), male sex (RR 1.30; 95% CI 1.26, 1.35), and rural residence (RR 1.50; 95% CI 1.43, 1.57). Injury rates were lower in immigrants across all types of unintentional injuries. Within immigrants, refugees had a higher risk of injury compared with non-refugees (RR 1.12; 95% CI 1.10, 1.14). This risk was particularly high for motor vehicle accidents (RR = 1.58; 95% CI 1.46, 1.71) and scald burns (RR 1.23; 95% CI 1.11, 1.35). CONCLUSION: Risk of unintentional injury is lower among immigrants compared with Canadian-born children. These findings support a healthy immigrant effect. Socioeconomic status has a different effect on injury risk in immigrant and non-immigrant populations, suggesting alternative causal pathways for injuries in immigrants. Risk of unintentional injury is higher in refugees versus non-refugee immigrants, highlighting a population in need of targeted injury prevention strategies.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".