Disparities and Trends in Birth Outcomes, Perinatal and Infant Mortality in Aboriginal vs. Non-Aboriginal Populations: A Population-Based Study in Quebec, Canada 1996–2010
Bibliographic record
Abstract
BACKGROUND: Aboriginal populations are at substantially higher risks of adverse birth outcomes, perinatal and infant mortality than their non-Aboriginal counterparts even in developed countries including Australia, U.S. and Canada. There is a lack of data on recent trends in Canada. METHODS: We conducted a population-based retrospective cohort study (n = 254,410) using the linked vital events registry databases for singleton births in Quebec 1996-2010. Aboriginal (First Nations, Inuit) births were identified by mother tongue, place of residence and Indian Registration System membership. Outcomes included preterm birth, small-for-gestational-age, large-for-gestational-age, low birth weight, high birth weight, stillbirth, neonatal death, postneonatal death, perinatal death and infant death. RESULTS: Perinatal and infant mortality rates were 1.47 and 1.80 times higher in First Nations (10.1 and 7.3 per 1000, respectively), and 2.37 and 4.46 times higher in Inuit (16.3 and 18.1 per 1000, respectively) relative to non-Aboriginal (6.9 and 4.1 per 1000, respectively) births (all p<0.001). Compared to non-Aboriginal births, preterm birth rates were persistently (1.7-1.8 times) higher in Inuit, large-for-gestational-age birth rates were persistently (2.7-3.0 times) higher in First Nations births over the study period. Between 1996-2000 and 2006-2010, as compared to non-Aboriginal infants, the relative risk disparities increased for infant mortality (from 4.10 to 5.19 times) in Inuit, and for postneonatal mortality in Inuit (from 6.97 to 12.33 times) or First Nations (from 3.76 to 4.25 times) infants. Adjusting for maternal characteristics (age, marital status, parity, education and rural vs. urban residence) attenuated the risk differences, but significantly elevated risks remained in both Inuit and First Nations births for the risks of perinatal mortality (1.70 and 1.28 times, respectively), infant mortality (3.66 and 1.47 times, respectively) and postneonatal mortality (6.01 and 2.28 times, respectively) in Inuit and First Nations infants (all p<0.001). CONCLUSIONS: Aboriginal vs. non-Aboriginal disparities in adverse birth outcomes, perinatal and infant mortality are persistent or worsening over the recent decade in Quebec, strongly suggesting the needs for interventions to improve perinatal and infant health in Aboriginal populations, and for monitoring the trends in other regions in Canada.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".