Rates of stillbirth by gestational age and cause in Inuit and First Nations populations in Quebec
Bibliographic record
Abstract
BACKGROUND: Inuit and First Nations populations have higher rates of stillbirth than non-Aboriginal populations in Canada do, but little is known about the timing and cause of stillbirth in Aboriginal populations. We compared gestational age- and cause-specific stillbirth rates in Inuit and First Nations populations with the rates in the non-Aboriginal population in Quebec. METHODS: Data included singleton stillbirths and live births at 24 or more gestational weeks among Quebec residents from 1981 to 2009. We calculated odds ratios (ORs), rate differences and 95% confidence intervals (CIs) for the retrospective cohort of Inuit and First Nations births relative to non-Aboriginal births using fetuses at risk (i.e., ongoing pregnancies) as denominators and adjusting for maternal characteristics. The main outcomes were stillbirth by gestational age (24-27, 28-36, ≥ 37 wk) and cause of death. RESULTS: Rates of stillbirth per 1000 births were greater among Inuit (6.8) and First Nations (5.7) than among non-Aboriginal (3.6) residents. Relative to the non-Aboriginal population, the risk of stillbirth was greater at term (≥ 37 wk) than before term for both Inuit (OR 3.1, 95% CI 1.9 to 4.8) and First Nations (OR 2.6, 95% CI 2.1 to 3.3) populations. Causes most strongly associated with stillbirth were poor fetal growth, placental disorders and congenital anomalies among the Inuit, and hypertension and diabetes among the First Nations residents. INTERPRETATION: Stillbirth rates in Aboriginal populations were particularly high at term gestation. Poor fetal growth, placental disorders and congenital anomalies were important causes of stillbirth among the Inuit, and diabetic and hypertensive complications were important causes in the First Nations population. Prevention may require improvements in pregnancy and obstetric care.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".