Knowledge, Attitude, Feeding Practices and Nutritional Status of Infants and Young Children in Eseka District, Cameroon
Bibliographic record
Abstract
There is limited data on the anthropometric indices and feeding practices of infants and young children in Eseka despite the high burden of malnutrition. This study was designed to evaluate the knowledge, attitude, feeding practices and nutritional status of children aged 0-24 months in Eseka District. A descriptive cross sectional study was conducted among 287 children aged 0-24 months of both sexes together with their mothers or caregivers. Data were collected using a modified questionnaire developed by the FAO/WHO. Information on sociodemographic status, feeding habits and anthropometric parameters were recorded. Anthropometric measurements taken included weight, length, arm circumference and head circumference. The Z-score classifications for malnutrition; weight for length, length for age and weight for age were compared according WHO standards. A subset of 29 children were selected for 24 recall and a 3-day weighed food intake study. There was a low prevalence (47.38%) of early initiation of breastfeeding within the first hour of birth. Only 2.44% practised exclusive breastfeeding, while 50% had introduced solids foods before five months and 22.54% after six months. Very few children (13.68% and 29.72%) consumed animal source foods and fruits respectively. The complementary foods consumed by the children were unbalanced, monotonous, poor in protein and some minerals such iron, and rich in fat. Furthermore, the study showed that 39.3%, 16.72% and 13.94% of children were stunted, wasted and underweight respectively. Stunting was highest in children under 6 months. The prevalence of stunting among children is severe public health problem in this age group. Some of the feeding practices are associated with poor nutritional status and can be improved with good nutrition education programs.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".