Consumption of Ultraprocessed Foods in a Sample of Adolescents With Obesity and Its Association With the Food Educational Style of Their Parent: Observational Study
Bibliographic record
Abstract
BACKGROUND: Both parental education and the food environment influence dietary intake and may therefore contribute to childhood obesity. OBJECTIVE: We aimed to assess the consumption of ultraprocessed foods (UPFs) in a convenience sample of adolescents with obesity and to determine its association with the food educational style of their parent. METHODS: This observational study included 24 participants, 12 adolescents (8 boys and 4 girls) aged from 12 to 14 years and their 12 parents, who were followed in a specialized pediatric obesity clinic in the French-speaking part of Switzerland. The adolescents were asked to take a photograph with a smartphone application of all meals and beverages consumed in their daily routine over 14 consecutive days. They evaluated their parent's food educational style using the Kids' Child Feeding Questionnaire. The parent who was present at the study visits also completed the Feeding Style Questionnaire. A dietitian analyzed the pictures to extract food group portions and to identify UPFs using the NOVA classification. A nonparametric statistical test was used to investigate associations between UPF intake and food educational style. RESULTS: Overall, the adolescents had unbalanced dietary habits compared to national recommendations. They consumed an insufficient quantity of vegetables, fruits, dairy products, and starchy foods and an excessive amount of meat portions and sugary and fatty products compared to the current Swiss recommendations. Their consumption of UPFs accounted for 20% of their food intake. All adolescents defined their parent as being restrictive in terms of diet, with a mean parental restriction score of 3.3±SD 0.4 (norm median=2.1). No parent reported a permissive food educational style. A higher intake of UPFs was associated with a lower parental restriction score (P=.04). CONCLUSIONS: Despite being followed in a specialized pediatric obesity clinic, this small group of adolescents had an unbalanced diet, which included 20% UPFs. The intake of UPFs was lower in participants whose parent was more restrictive, suggesting the importance of parents as role models and to provide adequate food at home. TRIAL REGISTRATION: ClinicalTrials.gov NCT03241121; https://clinicaltrials.gov/ct2/show/NCT03241121.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".