Concomitant preterm birth and severe small-for-gestational age birth weight among infants of immigrant mothers in Ontario originating from the Philippines and East Asia: a population-based study
Bibliographic record
Abstract
OBJECTIVES: Women from the Philippines form one of the largest immigrant groups to North America. Their newborns experience higher rates of preterm birth (PTB), and separately, small-for-gestational age (SGA) birth weight, compared with other East Asians. It is not known if Filipino women are at elevated risk of concomitant PTB and severe SGA (PTB-SGA), a pathological state likely reflective of placental dysfunction and neonatal morbidity. METHODS: We conducted a population-based study of all singleton or twin live births in Ontario, from 2002 to 2011, among immigrant mothers from the Philippines (n=27 946), Vietnam (n=15 297), Hong Kong (n=5618), South Korea (n=5148) and China (n=42 517). We used modified Poisson regression to generate relative risks (RR) of PTB-SGA, defined as a birth <37 weeks' gestation and a birth weight <5th percentile. RRs were adjusted for maternal age, parity, marital status, income quintile, infant sex and twin births. RESULTS: Relative to mothers from China (2.3 per 1000), the rate of PTB-SGA was significantly higher among infants of mothers from the Philippines (6.5 per 1000; RR 2.91, 95% CI 2.27 to 3.73), and those from Vietnam (3.7 per 1000; RR 1.68, 95% CI 1.21 to 2.34). The RR of PTB-SGA was not higher for infants of mothers from Hong Kong or South Korea. INTERPRETATION: Among infants born to immigrant women from five East Asian birthplaces, the risk of PTB-SGA was highest among those from the Philippines. These women and their fetuses may require additional monitoring and interventions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".