The Perinatal Effects of Delayed Childbearing
Bibliographic record
Abstract
OBJECTIVE: To determine if the rates of pregnancy complications, preterm birth, small for gestational age, perinatal mortality, and serious neonatal morbidity are higher among mothers aged 35-39 years or 40 years or older, compared with mothers 20-24 years. METHODS: We performed a population-based study of all women in Nova Scotia, Canada, who delivered a singleton fetus between 1988 and 2002 (N = 157,445). Family income of women who delivered between 1988 and 1995 was obtained through a confidential linkage with tax records (n = 76,300). The primary outcome was perinatal death (excluding congenital anomalies) or serious neonatal morbidity. Analysis was based on logistic models. RESULTS: Older women were more likely to be married, affluent, weigh 70 kg or more, attend prenatal classes, and have a bad obstetric history but less likely to be nulliparous and to smoke. They were more likely to have hypertension, diabetes mellitus, placental abruption, or placenta previa. Preterm birth and small-for-gestational age rates were also higher; compared with women aged 20-24 years, adjusted rate ratios for preterm birth among women aged 35-39 years and 40 years or older were 1.61 (95% confidence interval [CI] 1.42-1.82; P < .001) and 1.80 (95% CI 1.37-2.36; P < .001), respectively. Adjusted rate ratios for perinatal mortality/morbidity were 1.46 (95% CI 1.11-1.92; P = .007) among women 35-39 years and 1.95 (95% CI 1.13-3.35; P = .02) among women 40 years or older. Perinatal mortality rates were low at all ages, especially in recent years. CONCLUSION: Older maternal age is associated with relatively higher risks of perinatal mortality/morbidity, although the absolute rate of such outcomes is low.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 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".