International variations in the gestational age distribution of births: an ecological study in 34 high-income countries
Bibliographic record
Abstract
Background: Few studies have investigated international variations in the gestational age (GA) distribution of births. While preterm births (22-36 weeks GA) and early term births (37-38 weeks) are at greater risk of adverse health outcomes compared to full term births (39-40 weeks), it is not known if countries with high preterm birth rates also have high early term birth rates. We examined rate associations between preterm and early term births and mean term GA by mode of delivery onset. Methods: We used routine aggregate data on the GA distribution of singleton live births from up to 34 high-income countries/regions in 1996, 2000, 2004, 2008 and 2010 to study preterm and early term births overall and by spontaneous or indicated onset. Pearson correlation coefficients were adjusted for clustering in time trend analyses. Results: Preterm and early term births ranged from 4.1% to 8.2% (median 5.5%) and 15.6% to 30.8% (median 22.2%) of live births in 2010, respectively. Countries with higher preterm birth rates in 2004-2010 had higher early term birth rates (r > 0.50, P < 0.01) and changes over time were strongly correlated overall (adjusted-r = 0.55, P < 0.01) and by mode of onset. Conclusion: Positive associations between preterm and early term birth rates suggest that common risk factors could underpin shifts in the GA distribution. Targeting modifiable population risk factors for delivery before 39 weeks GA may provide a useful preterm birth prevention paradigm.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".