Does underutilization of prenatal care explain the excess risk for stillbirth among women with migration background in Germany?
Bibliographic record
Abstract
OBJECTIVE: To explore the role of utilization of prenatal care on the risk for stillbirth among women with migration background in Germany by comparing stillbirth rates of women from different origins characterized by adequate and inadequate utilization of prenatal care to German women with adequate utilization of care. DESIGN: Retrospective cohort study. SETTING: Lower Saxony, Germany. POPULATION: Singletons born in 1990, 1995 and 1999 (n = 182,444). METHODS: We analyzed perinatal data collected by obstetricians and midwives prospectively during pregnancy and after birth. The Adequacy of Prenatal Care Utilization Index was applied. Chi-squared tests and bivariate and multivariable logistic regression models were used. MAIN OUTCOME MEASURES: Stillbirth rates. RESULTS: In crude analyses, inadequate utilization of prenatal care (OR = 1.86, 95% CI 1.52, 2.28), and origin from Central and Eastern Europe (OR = 2.05, 95% CI 1.63, 2.58), the Mediterranean (OR = 1.77, 95% CI 1.38, 2.65), the Middle East (OR = 2.63, 95% CI 2.24, 3.09) and other countries (OR = 1.79, 95% CI 1.10, 2.89) were related to stillbirths. After adjustment for age, parity, smoking, inter-pregnancy interval, employment status and year of observation, compared to Germans with adequate utilization of prenatal care, women with adequate utilization of care from Central and Eastern Europe (OR = 1.74, 95% CI 1.33, 2.29) and the Middle East (OR = 1.98, 95% CI 1.64, 2.39) and women with inadequate utilization of prenatal care from the Mediterranean (OR = 3.00, 95% CI 1.71, 5.26) were at higher risk for stillbirths. CONCLUSION: There are inconsistent relation patterns between stillbirth, area of origin and utilization of prenatal care. Among women from the Mediterranean, increasing utilization of prenatal care may result in lower stillbirth rates.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".