Common maternal health problems among Australian-born and migrant women: A prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Migrant women of non-English speaking background make up an increasing proportion of women giving birth in high income countries, such as Australia, Canada and the United Kingdom. The aim of this study was to assess the prevalence of common physical and psychosocial health problems during pregnancy and up to 18 months postpartum among migrant women of non-English speaking background compared to Australian-born women. METHODS: Prospective pregnancy cohort study of 1507 nulliparous women. Women completed self-administered questionnaires or telephone interviews in early and late pregnancy and at 3, 6, 9, 12 and 18 months postpartum. Standardised instruments were used to assess incontinence, depressive symptoms and intimate partner violence. FINDINGS: Migrant women of non-English speaking background (n = 243) and Australian-born mothers (n = 1115) reported a similar pattern of physical health problems during pregnancy and postpartum. The most common physical health problems were: exhaustion, back pain, constipation and urinary incontinence. Around one in six Australian-born women (16.9%) and more than one in four migrant women (22.5%) experienced intimate partner abuse in the first 12 months postpartum. Compared to Australian-born women, migrant women were more likely to report depressive symptoms at 12 and 18 months postpartum. CONCLUSION: Physical and mental health problems are common among women of non-English speaking background and Australian-born women, and frequently persist up to 18 months postpartum. Migrant women experience a higher burden of postpartum depressive symptoms and intimate partner violence, and may face additional challenges accessing appropriate care and support.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".