Determinants of Breastfeeding Practices and Success in a Multi‐Ethnic Asian Population
Bibliographic record
Abstract
BACKGROUND: Many countries in Asia report low breastfeeding rates and the risk factors for early weaning are not well studied. We assessed the prevalence, duration, and mode of breastfeeding (direct or expressed) among mothers of three Asian ethnic groups. METHODS: Participants were 1,030 Singaporean women recruited during early pregnancy. Data collected included early breastfeeding experiences, breastfeeding duration, and mode of breastfeeding. Full breastfeeding was defined as the intake of breast milk, with or without water. Cox regression models were used to identify factors associated with discontinuation of any and full breastfeeding. Logistic regression analyses assessed the association of ethnicity with mode of breastfeeding. RESULTS: At 6 months postpartum, the prevalence of any breastfeeding was 46 percent for Chinese mothers, 22 percent for Malay mothers, and 41 percent for Indian mothers; prevalence of full breastfeeding was 11, 2, and 5 percent, respectively. More Chinese mothers fed their infants expressed breast milk, instead of directly breastfeeding them, compared with the other two ethnic groups. Duration of any and full breastfeeding were positively associated with breastfeeding a few hours after birth, higher maternal age and education, and negatively associated with irregular breastfeeding frequency and being shown how to breastfeed. Adjusting for maternal education, breastfeeding duration was similar in the three ethnic groups, but ethnicity remained a significant predictor of mode of breastfeeding. CONCLUSIONS: The low rates and duration of breastfeeding in this population may be improved with breastfeeding education and support, especially in mothers with lower education. Further work is needed to understand the cultural differences in mode of feeding and its implications for maternal and infant health.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".