Fertility Rate Trends Among Adolescent Girls With Major Mental Illness: A Population-Based Study
Bibliographic record
Abstract
OBJECTIVE: Fertility rates among adolescents have decreased substantially in recent years, yet fertility rates among adolescent girls with mental illness have not been studied. We examined temporal trends in fertility rates among adolescent girls with major mental illness. METHODS: We conducted a repeated annual cross-sectional study of fertility rates among girls aged 15 to 19 years in Ontario, Canada (1999-2009). Girls with major mental illness were identified through administrative health data indicating the presence of a psychotic, bipolar, or major depressive disorder within 5 years preceding pregnancy (60,228 person-years). The remaining girls were classified into the comparison group (4,496,317 person-years). The age-specific fertility rate (number of live births per 1000 girls) was calculated annually and by using 3-year moving averages for both groups. RESULTS: The incidence of births to girls with major mental illness was 1 in 25. The age-specific fertility rate for girls with major mental illness was 44.9 per 1000 (95% confidence interval [CI]: 43.3-46.7) compared with 15.2 per 1000 (95% CI: 15.1-15.3) in unaffected girls (rate ratio: 2.95; 95% CI: 2.84-3.07). Over time, girls with major mental illness had a smaller reduction in fertility rate (relative rate: 0.86; 95% CI: 0.78-0.96) than did unaffected girls (relative rate: 0.78; 95% CI: 0.76-0.79). CONCLUSIONS: These results have key clinical and public policy implications. Our findings highlight the importance of considering major mental illness in the design and implementation of pregnancy prevention programs as well as in targeted antenatal and postnatal programs to ensure maternal and child well-being.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".