Fruit and Vegetable Consumption Among Adolescent Secondary School Students in Boukombe and Natitingou, North Benin
Bibliographic record
Abstract
Fruit and vegetables (F&V) are recommended for a healthy life. Adolescence is a critical period for the onset of eating disorders and future health. F&V consumption among adolescents is globally low, making this group a key target for diet/nutrition-related interventions. This cross-sectional study aimed to assess F&V consumption among secondary school students in the food-insecure communes of Boukombe (rural) and Natitingou (urban), Benin. Using probabilistic random sampling, 303 students completed F&V intake frequency questionnaires and 24-h dietary recalls on school and non-school days. Poisson models identified factors associated with F&V consumption. The results showed that only 8.8% (Boukombe) and 11% (Natitingou) of students consumed fruit at least twice per day, and over 80% of students had not eaten fruit in the preceding 24 h; 9.9% and 11.4%, respectively, consumed vegetables at least twice per day. On average, 45.5% of students in Boukombe and 68% in Natitingou consumed at least three types of vegetables on school days. The most commonly consumed fruits were oranges in Boukombe and lemons in Natitingou. Factors influencing fruit consumption included sex (p = 0.005), age (p = 0.04), and mothers’ occupation (p = 0.03) on school days/and school or non-school days, while commune (p = 0.00017) and ethnic group affected vegetable consumption. Such low F&V consumption among surveyed students is a matter of public health concern, as it is likely to affect their health―in terms of micronutrient deficiency―and intellectual performance. These results should incentivize nutrition researchers, project managers, public health officials, and policymakers to (re)design and implement broader measures targeting secondary school students’ dietary practices to increase their F&V consumption.
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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 | 0.000 |
| 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) | 0.002 | 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".