Association of macrosomia with perinatal and postneonatal mortality among First Nations people in Quebec
Bibliographic record
Abstract
BACKGROUND: High prevalence of infant macrosomia (up to 36%, the highest in the world) has been reported in some First Nations communities in the Canadian province of Quebec and the eastern area of the province of Ontario. We aimed to assess whether infant macrosomia was associated with elevated risks of perinatal and postneonatal mortality among First Nations people in Quebec. METHODS: We calculated risk ratios (RRs) of perinatal and postneonatal mortality by birthweight for gestational age, comparing births to First Nations women (n = 5193) versus women whose mother tongue is French (n = 653 424, the majority reference group) in Quebec 1991-2000. RESULTS: The prevalence of infant macrosomia (birthweight for gestational age > 90th percentile) was 27.5% among births to First Nations women, which was 3.3 times (confidence interval [CI] 3.2-3.5) higher than the prevalence (8.3%) among births to women whose mother tongue is French. Risk ratios for perinatal mortality among births to First Nations women were 1.8 (95% CI 1.3-2.5) for births with weight appropriate for gestational age, 4.1 (95% CI 2.4-7.0) for small-for-gestational-age (< 10th percentile) births and < 1 (not significant) for macrosomic births compared to births among women whose mother tongue is French. The RRs for postneonatal mortality were 4.3 (95% CI 2.7-6.7) for infants with appropriate-for-gestational-age birthweight and 8.3 (95% CI 4.0-17.0) for infants with macrosomia. INTERPRETATION: Macrosomia was associated with a generally protective effect against perinatal death, but substantially greater risks of postneonatal death among births to First Nations women in Quebec versus women whose mother tongue is French.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".