Predisposing, facilitating and reinforcing factors of healthy and unhealthy food consumption in schoolchildren: a study in Ouagadougou, Burkina Faso
Bibliographic record
Abstract
OBJECTIVE: African schoolchildren's dietary habits are likely changing in the realm of the nutrition transition, particularly in urban areas, but data on their diet and on determinants are scanty. In order to design relevant interventions for this priority target group, the study aimed to assess food habits and their determinants in schoolchildren of Ouagadougou. METHODS: In a cross-sectional survey, fifth-grade schoolchildren filled during school hours a questionnaire to assess consumption frequency of 'healthy' foods (fruits, vegetables, meat, fish, legumes) and 'unhealthy' (superfluous) items (cake, cookies, candies, ice, soda) and underlying factors, using Green's PRECEDE model. RESULTS: The study included 769 schoolchildren, mean age 11.7 ± 1.4 years, from eight public and four private schools. Consumption scores of unhealthy items were significantly higher than healthy foods (p = 0.001). During the week prior to the survey, 25% of children had eaten no fruit, 20% no meat, 20% no legumes, 17% no fish and 17% no vegetables. While less than 4% ate fruits or vegetables every day, 18.3% ate ice pop every day. Children eating cookies, cakes and candy every day were up to seven-fold those eating fruits, vegetables or legumes. Compared to public-school pupils, those from private schools consumed both healthy and unhealthy items more frequently (p = 0.002 and p = 0.007, respectively). Urban schoolchildren had significantly higher unhealthy food scores (p = 0.027) compared to peri-urban schools. Children's healthy and unhealthy food consumption was primarily explained by perceived decisional power and availability [facilitating factors] for both types of foods, and maternal reinforcement for healthy foods and peers' reinforcement for consumption of unhealthy items. Overall, facilitating factors rated higher for unhealthy than healthy foods. CONCLUSION: The study showed that city schoolchildren's eating behaviours are far from optimal. Nutrition interventions should be tailored to address the underlying factors in order to impact on behaviours, thereby preventing both dietary inadequacies and excess.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".