Oral contraceptive use among women aged 15 to 49: Results from the Canadian Health Measures Survey.
Bibliographic record
Abstract
BACKGROUND: Oral contraceptives (OCs) have been available in Canada for over 50 years and are the most commonly used method of reversible contraception. OCs have evolved over time, with decreasing estrogen doses, new progestins, and different dosing regimens. Detailed data about OCs use among Canadian women are lacking. DATA AND METHODS: Data from Statistics Canada's 2007/2009 and 2009/2011 Canadian Health Measures Survey (CHMS) were used to estimate OC use, by selected sociodemographic characteristics, cardiovascular risk factors, and estrogen dose and progestin type. Logistic regression was used to model relationships between OC use and sociodemographic factors. RESULTS: An estimated 1.3 million (16%) women aged 15 to 49 reported taking OCs in the previous month. OC use decreased with age (30% among 15- to 19-year-olds; 3% among 40- to 49-year-olds). OC users were significantly more likely than non-users to be nulliparous, sexually active and Canadian-born. At ages 35 to 49, users were less likely than non-users to have one or more cardiovascular risk factors. Almost all (99%) OC users took combined formulations containing ethinyl estradiol (EE) and progestin. Two-thirds of OCs users took formulations containing 30 or more mcg of EE. Women aged 15 to 24 were more likely than those aged 35 to 49 to use lower-dose formulations (less than 30 mcg of EE). INTERPRETATION: A substantial percentage of reproductive-aged Canadian women, particularly younger women, used OCs. OC use varied by sociodemographic and some cardiovascular risk factors. The majority took formulations containing 30 or more mcg of EE.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".