Lifetime Induced Abortions and Live Births: A 40-Year Historical Cohort Study
Bibliographic record
Abstract
OBJECTIVES: Little is known about whether induced abortions are associated with the final lifetime number of live births (life births). The objective of this study was to examine the association between the number of life births with the number of abortions a female has had in her lifetime. METHODS: In a national cohort design, we followed all Danish females from ages 15 to 44 years through the period 1977-2017 for induced abortions and live births. For each lifetime number of induced abortions, the average number of life births was assessed, and rates with 95% CI were calculated. RESULTS: The study included 409 497 females who completed 222 482 induced abortions and 831 742 live births. Of 265 573 (64.9%) females who did not have any induced abortion, the average number of life births was 2.09 (95% CI 2.08-2.10). For females with 1 (23.4%), 2 (7.4%), 3 (2.6%), 4 (1.0%), and ≥5 (0.7%) induced abortions during their reproductive lifespan, the average number of life births was 1.88 (1.87-1.89), 1.99 (1.98-2.00), 2.09 (2.06-2.11), 2.13 (2.09-2.15), and 2.25 (2.21-2.29), respectively. The increase in number of life births in females with 1 to females with 5+ induced abortions was 4.7% for each additional induced abortion. CONCLUSION: We found the number of induced abortions during a woman's reproductive lifespan to be positively correlated to the number of live births. This association is likely explained by a high fecundity in females with multiple pregnancies including induced abortions and suggests that even several induced abortions do not compromise a woman's general reproductive end points.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".