Experiences of violence before and during pregnancy and adverse pregnancy outcomes: An analysis of the Canadian Maternity Experiences Survey
Bibliographic record
Abstract
BACKGROUND: Abuse and violence against women constitute a global public health problem and are particularly important among women of reproductive age. The literature is not conclusive regarding the impact of violence against pregnant women on adverse pregnancy outcomes, such as preterm birth, small for gestational age and postpartum depression. Most studies have been conducted on relatively small samples of high-risk women. Our objective was to investigate what dimensions of violence against pregnant women were associated with preterm birth, small for gestational age and postpartum depression in a nationally representative sample of Canadian women. METHODS: We analysed data of the Maternity Experiences Survey, a nationally representative survey of Canadian women giving birth in 2006. The comprehensive questionnaire included a 19-item section to collect information on different dimensions of abuse and violence, such as type, frequency, timing and perpetrator of violence. The survey design is a stratified simple random sample from the 2006 Canadian Census sampling frame. Participants were 6,421 biological mothers (78% response rate) 15 years and older who gave birth to a singleton live birth and lived with their infant at the time of the survey. Logistic regression was used to compute Odds Ratios. Survey weights were used to obtain point estimates and 95% confidence intervals were obtained with the jacknife method of variance estimation. Covariate control was informed by use of directed acyclic graphs. RESULTS: No statistically significant associations were found for preterm birth or small for gestational age, after adjustment. Most dimensions of violence were associated with postpartum depression, particularly the combination of threats and physical violence starting before and continuing during pregnancy (Adjusted Odds Ratio = 4.1, 95% confidence interval: 1.9, 8.9) and perpetrated by the partner (4.3: 2.1, 8.7). CONCLUSIONS: Our findings provide weak evidence of an association between experiences of abuse before and during pregnancy and preterm birth and small for gestational age but they indicate that several dimensions of abuse and violence are consistently associated with postpartum depression.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.014 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".