Infant sex at birth and long‐term maternal mortality
Bibliographic record
Abstract
BACKGROUND: Maternal adaptations may vary by foetal sex. Whether male infants influence long-term mortality in mothers remains uncertain. OBJECTIVE: The objective of the study was to examine whether male infants increase the risk of maternal mortality. METHODS: This study included pregnant women enrolled at 12 US sites from 1959 to 1966 in the Collaborative Perinatal Project (CPP). Collaborative Perinatal Project records were linked to the National Death Index and the Social Security Master Death File to ascertain deaths until 2016. Foetal sex was determined by infant sex at birth, defined as the total number of male or female infants in pregnancies prior to or during enrolment in the CPP. In secondary analyses, exposure was defined as infant sex at the last CPP delivery. Outcomes included all-cause and underlying causes of mortality. We used Cox proportional hazards models weighted by the number of prior live births and stratified our models by parity and race/ethnicity. RESULTS: Among 48,188 women, 50.8% had a male infant at their last registered CPP pregnancy and 39.0% had a recorded death after a mean follow-up of 47.8 years (SD 10.5 years). No linear association was found between the number of liveborn males and all-cause mortality (primipara women: HR 1.02, 95% CI 0.95, 1.09, multipara women, 1 prior live birth: HR 0.96, 95% CI 0.89, 1.03, multipara women, ≥2 prior live births: HR 0.97, 95% CI 0.85, 1.11). A similar trend was noted for cardiovascular- and cancer-related mortality. At the last delivery, women with a male infant did not have an increased risk of all-cause or cause-specific mortality compared to women with a female infant. These findings were consistent across racial/ethnic groups. CONCLUSIONS: Women who give birth to male infants, regardless of number, are not at increased risk of all-cause and cause-specific mortality. These findings suggest that giving birth to male infants may not independently influence the long-term health of women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".