Feeding practices and factors associated with the provision of iron-rich foods to children aged 6–23 months in Matam area, Senegal
Bibliographic record
Abstract
OBJECTIVE: The objectives of this study were to document feeding practices amongst rural Senegalese children aged 6 to 23 months and to investigate psychosocial and environmental factors associated with the provision of iron-rich foods (IRF). DESIGN: This was a cross-sectional study conducted from January to July 2018. SETTING: The study took place in the region of Matam, northern Senegal. PARTICIPANTS: Ninety-eight mothers of children aged 6-23 months. RESULTS: Results show that 27·6 % of children were fed according to the minimum acceptable diet, and 55·1 % and 53·1 % had the minimum diet diversity and minimum meal frequency, respectively. About 65·3 % of mothers provided IRF to young children the day before the survey, mostly fish. Mother's intention to provide IRF to their children was not associated with the provision of these foods neither was the perceived behavioural control. Child's age (OR = 1·14, 95 % CI (1·03, 1·26), P = 0·012) and household food insecurity score (OR = 0·80, 95 % CI (0·68, 0·96), P = 0·014) were the predictors of the provision of IRF to children aged 6-23 months. CONCLUSIONS: Household food insecurity status and age of the child rather than mothers' psychosocial factors were significant predictors of IRF consumption amongst children aged 6-23 months in the study area. More attention should be given to food environment and child-related factors in order to improve children feeding practices and, in particular, their consumption of IRF in the study setting. For instance, home visits and the 5-month-old vaccine consultation in health centres might be opportunities to reinforce the importance of providing IRF as part of complementary foods from the age of 6 months. Implementation of measures for the improvement of socio-economic conditions and food security of households would also be valuable.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".