Changes to acute-care hospitalizations among Indigenous children and youth: Results from the 2006 and 2011 Canadian Census Health and Environment Cohorts
Bibliographic record
Abstract
Background: This study described the differences in the hospitalization rates of First Nations children and youth living on and off reserve, Inuit children and youth living in Inuit Nunangat (excluding Nunavik), and Métis children and youth, relative to non-Indigenous children and youth and examined rate changes across 2006 and 2011. Data and methods: The 2006 and the 2011 Canadian Census Health and Environment Cohorts provided five years of hospital records that Statistics Canada linked to peoples' self-reported Indigenous identity as recorded on the census. Causes of hospitalizations were based on the most responsible diagnosis coded according to the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canada, aggregated by chapter code. Age-standardized hospitalization rates (ASHRs) were calculated per 100,000 population. Rate ratios (RRs) were reported for each Indigenous group relative to non-Indigenous children and youth. Results: For the 2006 and the 2011 cohorts, ASHRs were generally higher among Indigenous children and youth than among non-Indigenous children and youth. For some health conditions, hospitalization patterns also varied across the two time periods within the given Indigenous groups. Among children, leading elevated RRs occurred for diseases of the respiratory system, the digestive system and injuries. Elevated mental health-related RRs were observed among all Indigenous groups for both cohort years of youth. Significant increases in mental health-related ASHRs were observed in 2011 compared with 2006 among all youth groups, except for Inuit youth living in Inuit Nunangat, possibly due in part to data limitations. Among Indigenous youth, elevated RRs were observed for pregnancy, childbirth and the puerperium, and for injuries. For all youth (except Inuit), childbirth-related ASHRs decreased in 2011 compared with 2006. Interpretation: Findings align with previously observed hospitalization disparities between Indigenous and non-Indigenous children and youth. These data enabled the tracking of changes over time to partly address national information gaps about population health outcomes for children and youth, namely hospitalization.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".