Determinants of breastfeeding practices among mothers in Malawi: a population-based survey
Bibliographic record
Abstract
BACKGROUND: High rates of early initiation and exclusive breastfeeding have been reported in Malawi, yet the underlying factors are unknown. Our objective is to examine the determinants of breastfeeding practices for mothers of infants less than 24 months old in Malawi. METHODS: A cross-sectional study was conducted using nationally representative data from the 2010 Malawi Demographic and Health Survey. Multivariate logistic regression analysis was used. RESULTS: Of 7282 women, 95.4% initiated breastfeeding within 1 hour after birth; thereafter 71.3% of women practiced exclusive breastfeeding, 6.1% predominantly breastfed, and 1.9% chose bottle feeding exclusively. The odds of early initiation were higher among women with frequent antenatal care visits and multiparous mothers. Similarly, frequent antenatal care visits and hospital delivery were positive determinants for exclusive breastfeeding. Infants at 6 months of age were more likely to predominantly breastfeed than they were at 1 month. The odds of bottle feeding were higher among women who were educated, who delivered at a hospital. CONCLUSIONS: Optimal breastfeeding practices are highly prevalent in Malawi. Health care practice emphasizing frequent antenatal care visits that provide breastfeeding education and breastfeeding support in hospital care after childbirth are important for sustaining breastfeeding.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".