Absolute Risks of Obstetric Outcomes Risks by Maternal Age at First Birth
Bibliographic record
Abstract
BACKGROUND: First deliveries in women older than 35, 40, or 45 years are at increased risk for adverse pregnancy outcomes compared with those in younger women. However, specific relationships between each additional year of maternal age and pregnancy risks remain unclear, and absolute risks at each maternal age are not known. METHODS: Using a population-based cohort of nulliparous women in British Columbia, Canada, from 2004 to 2014 (n = 203,414), We examined relationships between maternal age (modeled flexibly to allow curvilinear shapes) and pregnancy outcomes using logistic regression. We plotted absolute predicted risks to display curves from age 20 to 50 estimated for two risk profiles: (1) population average values of all risk factors; (2) a low-risk profile without preexisting diabetes/hypertension, smoking, prior spontaneous/therapeutic abortion, diagnosed infertility, inadequate prenatal care, low income, rural residence, or obesity. RESULTS: Risks of hypertensive disorders increased gradually until age 35, then accelerated. Risk of multiple gestations, major congenital anomalies, and maternal mortality or severe morbidity increased slowly until age 30, then accelerated. Cesarean delivery and gestational diabetes risks increased linearly with age. While indicated preterm delivery increased rapidly with maternal age, spontaneous preterm delivery did not. Stillbirth, neonatal mortality, and infant mortality had j-shaped relationships with maternal age, with nadirs near 30. Despite age-related increases, risks of severe outcomes remained low for women 35 and 40: < 1-2% for severe maternal morbidity and 5-7% for fetal-infant composite. CONCLUSIONS: This study provides risks for specific maternal ages to inform clinical counseling and public health messaging regarding the potential implications of delayed childbearing.
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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 | 0.006 |
| 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 | 0.001 |
| 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".