Paternal age and birth defects: how strong is the association?
Bibliographic record
Abstract
BACKGROUND: Although the association between maternal age and the risks of birth defects has been well studied, the evidence from population data linking paternal age with birth defects was limited and inconsistent. METHODS: We conducted a population-based retrospective cohort study of 5,213,248 subjects from the 1999-2000 birth registration data of the USA. Multiple logistic regressions were used to estimate the independent effect of paternal age on all birth defects and 21 specific defects groups after adjusting for potential confounding of maternal age, race, education, marital status, parity, prenatal care initiation, maternal smoking and alcohol drinking during pregnancy. RESULTS: A total of 77,514 (1.5%) birth defects were recorded in the study cohort. The adjusted odds ratios were 1.04 (1.01, 1.06), 1.08 (1.04, 1.12), 1.08 (1.02, 1.14) and 1.15 (1.06, 1.24), respectively, for infants born to fathers 30-35, 40-44, 45-49 and over 50 years (test for trend, P = 0.0155), when compared with those infants born to fathers aged 25-29 for any birth defect. Advanced paternal age was associated with increased risks of heart defects, tracheo-oesophageal fistulaoesophageal atresia, other musculoskeletal/integumental anomalies, Down's syndrome and other chromosomal anomalies. Fathers under 25 years of age were also at increased risks of spina bifida/meningocele, microcephalus, omphalocele/gastroschisis and other musculoskeletal/integumental anomalies. CONCLUSIONS: Infants born to older fathers have a slightly increased risk of birth defects. Young paternal age is also associated with slightly increased risk of several selected birth defects in their offspring. However, given the weak association, paternal age appears to play a small role in the aetiology of birth defects.
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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 | 0.008 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".