Social Determinants Associated with Pediatric Burn Injury: A Population-Based, Case–Control Study
Bibliographic record
Abstract
Social determinants of health (SDoH) influence risk of injury. We conducted a population-based, case-control study to identify which social determinants influence burn injury in children. Children (≤16 years of age) admitted to a Canadian regional burn center between January 1, 1999 and March 30, 2017 were matched based on age, sex, and geographic location 1:5 with an uninjured control cohort from the general population. Population-level administrative data describing the SDoH at the Manitoba Center for Health Policy (MCHP) were compared between the cohorts. Specific SDoH were chosen based on a published systematic review conducted by the research team. In the final multivariable model, children from a low-income household odds ratio (OR) (95% confidence interval) 1.97 (1.46, 2.65), in care 1.57 (1.11, 2.21), from a family that received income assistance 1.71 (1.33, 2.19) and born to a teen mother 1.43 (1.13, 1.81) were significantly associated with an increased risk of pediatric burn injury. This study identified SDoH that are associated with an increased risk of burn injury. This case-control study supports the finding that children from a low-income household, children in care, from a family that received income assistance, and children born to a teen mother are at an elevated risk of burn injury. Identifying children at increased potential risk allows targeting of burn risk reduction and home safety programs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".