Food Environment and Youth Intake May Influence Uptake of Gluten-Free Food Guide Recommendations in Celiac Disease
Bibliographic record
Abstract
A gluten-free (GF) food guide for children and youth (4-18 years) living with celiac disease (CD) has been developed and extensively evaluated by stakeholders, including registered dietitians. A case study analysis was conducted on data from 16 households of youth with CD to examine how factors related to parental food literacy, the home food environment, and food purchasing patterns may influence food guide uptake by Canadian youth with CD and their families. Households were of higher socioeconomic status, parents had good food literacy, and the home food availability of fruits, vegetables and GF grains was diverse. However, households also had a diverse supply of convenience foods and snack options. Youth reported consuming a larger proportion of these foods (>35% dietary intake) and had suboptimal diet quality. Dietary intake of fruits and vegetables were below GF plate model recommendations by over 30%. Despite limited economical barriers, good parental food literacy, and diverse food availability, meeting fruit and vegetable recommendations based on the pediatric GF food guide remains a major challenge. Findings inform that effective strategies and healthy public policies to support the uptake of GF food guide recommendations are needed to improve the health outcomes of youth with CD.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".