Links between household food consumption and nutritional status of children aged 6–59 months: a case study in Burkina Faso
Bibliographic record
Abstract
Introduction: Food insecurity is a major challenge in many developing countries and may impede the achievement of Sustainable Development Goal 2 (SDG2). Nearly 15% of Burkina Faso's population is facing food insecurity. In 2021, 21.6% of children under the age of five (U5) were stunted. This rate remains high. This study aimed to investigate the relationship between Global Acute Malnutrition (GAM) and socio-demographic, economic, and household dietary factors among U5 children in the Sanguié Province in Burkina Faso. Methods: The method used is based on a quantitative cross-sectional study using primary data on food and nutritional security for 237 children under the age of 5 from 150 households. Data analysis was carried out sequentially: a first univariate descriptive stage was used to characterize the variables studied, with a prevalence of MAG [11.4% (7.35-15.44)], which is higher than the 10% alert threshold set by the WHO; this stage is followed by a bivariate analysis to explore their associations. Finally, a multiple correspondence analysis (MCA) was carried out to identify the independent factors associated with acute malnutrition because of its ability to study complex relationships between variables and to represent their structure in the form of factorial spaces. Results and discussion: Findings indicate that malnutrition is associated with high household food expenditure; medium dietary diversity; a medium/high demographic dependency ratio; the absence of toilets; and food reserves that cover less than 6 months. These findings highlight the need to strengthen food security by fostering household economic development and to ensure optimal access to improved sanitation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".