Inadequate Prenatal Care Utilization and Risks of Infant Mortality and Poor Birth Outcome: A Retrospective Analysis of 28,729,765 U.S. Deliveries over 8 Years
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association between adequacy of prenatal care utilization and risk of fetal and neonatal mortality and adverse outcomes. METHODS: We conducted a population-based cohort study using the Center for Disease Control and Prevention's Linked Birth-Infant Death and Fetal Death data on all deliveries in the United States between 1995 and 2002. Inclusion criteria were singleton births ≥22 weeks of gestation with no known congenital malformation. Inadequate prenatal care was defined according to the Adequacy of Prenatal Care Utilization Index, and its effect on fetal and neonatal death was estimated using unconditional logistic regression analysis adjusting for maternal age, race, education, and other confounding variables. RESULTS: During our 8-year study period, 32,206,417 births occurred, 28,729,765 (89.2%) of which met inclusion criteria. Inadequate prenatal care utilization occurred in 11.2% of expectant mothers, more commonly among women ≤20 years, black non-Hispanic and Hispanic women, and those without high school education. Relative to adequate care, inadequate care was associated with increased risk of prematurity 3.75 (3.73 to 3.77), stillbirth 1.94 (1.89 to 1.99), early neonatal dearth 2.03 (1.97 to 2.09), late neonatal death 1.67 (1.59 to 1.76), and infant death 1.79 (1.76 to 1.82). CONCLUSION: Risk of prematurity, stillbirth, early and late neonatal death, and infant death increased linearly with decreasing care. Given the population effect of this association, public health initiatives should target program expansion to ensure timely and adequate access, particularly for women ≤20 years, Black non-Hispanic and Hispanic women, and those without high school education.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".