A comparison of foetal and infant mortality in the United States and Canada
Bibliographic record
Abstract
BACKGROUND: Infant mortality rates are higher in the United States than in Canada. We explored this difference by comparing gestational age distributions and gestational age-specific mortality rates in the two countries. METHODS: Stillbirth and infant mortality rates were compared for singleton births at >or=22 weeks and newborns weighing>or=500 g in the United States and Canada (1996-2000). Since menstrual-based gestational age appears to misclassify gestational duration and overestimate both preterm and postterm birth rates, and because a clinical estimate of gestation is the only available measure of gestational age in Canada, all comparisons were based on the clinical estimate. Data for California were excluded because they lacked a clinical estimate. Gestational age-specific comparisons were based on the foetuses-at-risk approach. RESULTS: The overall stillbirth rate in the United States (37.9 per 10,000 births) was similar to that in Canada (38.2 per 10,000 births), while the overall infant mortality rate was 23% (95% CI 19-26%) higher (50.8 vs 41.4 per 10,000 births, respectively). The gestational age distribution was left-shifted in the United States relative to Canada; consequently, preterm birth rates were 8.0 and 6.0%, respectively. Stillbirth and early neonatal mortality rates in the United States were lower at term gestation only. However, gestational age-specific late neonatal, post-neonatal and infant mortality rates were higher in the United States at virtually every gestation. The overall stillbirth rates (per 10,000 foetuses at risk) among Blacks and Whites in the United States, and in Canada were 59.6, 35.0 and 38.3, respectively, whereas the corresponding infant mortality rates were 85.6, 49.7 and 42.2, respectively. CONCLUSIONS: Differences in gestational age distributions and in gestational age-specific stillbirth and infant mortality in the United States and Canada underscore substantial differences in healthcare services, population health status and health policy between the two neighbouring countries.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".