Breastfeeding and Mixed Feeding Practices in Malawi: Timing, Reasons, Decision Makers, and Child Health Consequences
Bibliographic record
Abstract
BACKGROUND: In order to effectively promote exclusive breastfeeding, it is important to first understand who makes child-care and child-feeding decisions, and why those decisions are made; as in most parts of the world, exclusive breastfeeding until 6 months of age is uncommon in Malawi. OBJECTIVE: To characterize early infant foods in rural northern Malawi, who the decision-makers are, their motivation, and the consequences for child growth, in order to design a more effective program for improved child health and nutrition. METHODS: In a rural area of northern Malawi, 160 caregivers of children 6 to 48 months of age were asked to recall the child's age at introduction of 19 common early infant foods, who decided to introduce the food, and why. The heights and weights of the 160 children were measured. RESULTS: Sixty-five percent of the children were given food in their first month, and only 4% of the children were exclusively breastfed for 6 months. Mzuwula and dawale (two herbal infusions), water, and porridge were common early foods. Grandmothers introduced mzuwula to protect the children from illness; other foods were usually introduced by mothers or grandmothers in response to perceived hunger. The early introduction of porridge and dawale, but not mzuwula, was associated with worse anthropometric status. Mzuwula, which is not associated with poor growth, is usually made with boiled water and given in small amounts. Conversely, porridge, which is associated with poor child growth, is potentially contaminated and is served in larger amounts, which would displace breastmilk. CONCLUSIONS: Promoters of exclusive breastfeeding should target their messages to appropriate decision makers and consider targeting foods that are most harmful to child growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".