High pregnancy rates and reproductive health indicators among female injection-drug users in Vancouver, Canada
Bibliographic record
Abstract
OBJECTIVE: To determine the incidence of pregnancy among active injection-drug users and to identify factors associated with becoming pregnant. METHODS: The Vancouver Injection Drug User Study (VIDUS) is a prospective cohort study that began in 1996. Women who had completed a baseline and at least one follow-up questionnaire between June 1996 and January 2002 were included in the study. Parametric and non-parametric methods were used to compare characteristics of women who reported pregnancy over the study period with those who did not over the same time period. RESULTS: A total of 104 women reported a primary pregnancy over the study period. The incidence of pregnancy over the follow-up period was 6.46 (95% confidence interval (CI) 5.24-7.87) per 100 person-years. The average age of women who reported pregnancy was younger than that of women who did not report pregnancy (27 vs. 32 years, p < 0.001). Women of Aboriginal ethnicity were more likely to report pregnancy (odds ratio 1.6, 95% CI 1.0-2.5). Comparison of drug use showed no significant differences in pregnancy rate with respect to the use of heroin, cocaine or crack (p > 0.05). In examining sexual behavior, women who reported having had a regular partner in the previous 6 months were three times more likely to have reported pregnancy. Despite the fact that 67% of women in this study reported using some form of contraception, the use of reliable birth control was low. Only 5% of women in our study reported the use of hormonal contraceptives. CONCLUSION: There were a high number of pregnancies among high-risk women in this cohort. This corresponded with very low uptake of reliable contraception. Innovative strategies to provide reproductive health services to at-risk women who are injecting drugs is a public health priority.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".