Estimating the prevalence of infertility in Canada
Bibliographic record
Abstract
BACKGROUND: Over the past 10 years, there has been a significant increase in the use of assisted reproductive technologies in Canada, however, little is known about the overall prevalence of infertility in the population. The purpose of the present study was to estimate the prevalence of current infertility in Canada according to three definitions of the risk of conception. METHODS: Data from the infertility component of the 2009-2010 Canadian Community Health Survey were analyzed for married and common-law couples with a female partner aged 18-44. The three definitions of the risk of conception were derived sequentially starting with birth control use in the previous 12 months, adding reported sexual intercourse in the previous 12 months, then pregnancy intent. Prevalence and odds ratios of current infertility were estimated by selected characteristics. RESULTS: Estimates of the prevalence of current infertility ranged from 11.5% (95% CI 10.2, 12.9) to 15.7% (95% CI 14.2, 17.4). Each estimate represented an increase in current infertility prevalence in Canada when compared with previous national estimates. Couples with lower parity (0 or 1 child) had significantly higher odds of experiencing current infertility when the female partner was aged 35-44 years versus 18-34 years. Lower odds of experiencing current infertility were observed for multiparous couples regardless of age group of the female partner, when compared with nulliparous couples. CONCLUSIONS: The present study suggests that the prevalence of current infertility has increased since the last time it was measured in Canada, and is associated with the age of the female partner and parity.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".