The prevalence and variations in unintended pregnancy by socio-demographic and health-related factors in a population-based cohort of young Australian women
Bibliographic record
Abstract
OBJECTIVE: The aim of this study is to estimate the prevalence of unintended pregnancy and associated socio-demographic and health-related factors among a national cohort of young Australian women. METHODS: Secondary analysis of three waves (2013-2015) of the Australian Longitudinal Study on Women's Health new young cohort. Women born between 1989 and 1995 were recruited through internet and traditional media, and peer referral. Respondents completed a baseline web-based survey in 2013 (n=17,010) on their health and healthcare use and were followed up annually. This analysis uses data from women reporting ever having vaginal sex in waves 2 (n=9,726/11,344) and 3 (n=6,848/8,961). We assessed correlates of lifetime and recent unintended pregnancy using multivariable regression models. RESULTS: At wave 2, among women aged 19-24, lifetime prevalence of unintended pregnancy was 12.6%, rising to 81.0% among ever pregnant women. Pregnancy outcomes among women with a history of unintended pregnancy differed by geographical residence. Disparities in odds of unintended pregnancy were seen by relationship and educational status, contraceptive use, sexual coercion and risky alcohol use. CONCLUSIONS: Unintended pregnancy among young Australians is disproportionally experienced by women with structural disadvantages and exposure to sexual coercion. PUBLIC HEALTH IMPLICATIONS: Service improvements to achieve equitable distribution of contraception and abortion services must be integrated with initiatives responding to sexual coercion.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".