Infant and young child feeding practices are associated with childhood anaemia and stunting in sub-Saharan Africa
Bibliographic record
Abstract
BACKGROUND: The co-occurrence of anaemia and stunting (CAS) presents acute development and morbidity challenges to children particularly in sub-Saharan Africa (SSA). Evidence on the effect of child feeding recommendations on CAS is scarce. METHODS: We used data from 22 recent Demographic and Health Surveys in SSA countries to examine the association between caregivers' implementation of recommendations on infant and young child feeding and the CAS in their 6- to 23-mo-old children. RESULTS: Overall, in multiple logistic regression models, child feed index score, high wealth of household, increasing household size, household head with at least secondary school education, improved sanitation of household, an increase in caregiver's age and caregiver's with at least secondary education were associated with lower odds of CAS (i.e. , AOR: 0.86; 95% CI; 0.84 - 0.88: 0.75; 0.69 - 0.82: 0.98, 0.98 - 0.99: 0.76, 0.70 - 0.83: 0.81, 0.74 - 0.87: 0.87, 0.81 - 0.94: 0.69, 0.62 - 0.77 respectively). Having a diarrhoea in the past 2 weeks and having fever in the past month were associated with higher odds of CAS (AOR:1.1, 95% CI; 1.0 - 1.2: 1.1, 1.0 - 1.2, respectively). Results from the decision tree analysis showed that the educational level of women was the most important predictor of CAS, followed by child feeding score, the level of education of the family head and state of drinking water. CONCLUSION: The results buttress the importance of interventions aimed at improving feeding practices and parental educational as a vehicle to improve children's nutritional status.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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".