The impact of immigration on the breastfeeding practices of Mainland Chinese immigrants in Hong Kong
Bibliographic record
Abstract
BACKGROUND: Researchers have found breastfeeding disparities between immigrant and native-born women in many countries. However, most studies on immigration and breastfeeding practices have been in Western countries. The aim of this study was to examine the effect of length of time since immigration on the breastfeeding practices of Mainland Chinese immigrants living in Hong Kong. METHODS: We recruited 2704 mother-infant pairs from the postnatal wards of four public hospitals in Hong Kong. We examined the effect of migration status on the duration of any and exclusive breastfeeding. RESULTS: Breastfeeding duration was progressively shorter as the time since immigration increased. When compared with mothers who had lived in Hong Kong for <5 years, Hong Kong-born participants had a 30% higher risk of stopping any breastfeeding (hazard ratio [HR] 1.34 [95% confidence interval {CI} 1.10-1.63]) and exclusive breastfeeding (HR 1.33 [95% CI 1.11-1.58]). In both Hong Kong-born and immigrant participants, breastfeeding cessation was associated with return to work postpartum and the husband's preference for infant formula or mixed feeding. Intention to exclusively breastfeed and to breastfeed for >6 months, and previous breastfeeding experience substantially reduced the risk of breastfeeding cessation for both Hong Kong-born and immigrant participants. CONCLUSIONS: Health care professionals should consider immigration history in their assessment of pregnant women and provide culturally adapted breastfeeding support and encouragement to this population.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".