Food insecurity impacts diet quality and adherence to the gluten‐free diet in youth with celiac disease
Bibliographic record
Abstract
OBJECTIVES: Celiac disease (CD) is an autoimmune gastrointestinal disorder that requires a strict lifelong gluten-free diet (GFD). Gluten-free (GF) foods are more expensive and less readily accessible than gluten-containing foods, contributing to an increased risk for food insecurity (FI). The study aimed to determine associations between GF-FI, sociodemographic risk factors and child dietary adherence and diet quality (DQ). METHODS: A 26-item, cross-country online survey was administered through social media to parents of children with CD on the GFD. The survey elicited household and CD child sociodemographic and clinical characteristics (e.g., duration of CD), measures of household FI, child DQ and GFD adherence, and parents' concerns related to GF food. Household GF-FI was evaluated using the validated Hunger Vital Sign™ and the US Department of Agriculture Six-Item Short Form Household Food Security Survey Module. RESULTS: GF-FI occurred in 47% of households with children with CD with >30% reporting low to very low food security. Sociodemographic risk factors identified included lower income, renters, rural residency, single-parental households, and having children with additional dietary restrictions (p < 0.001). Regardless of FI status, a majority of households reported experiencing significantly higher GF food expenditure. GF-FI was associated with reduced adherence to the GFD, increased consumption of processed GF food, and lower intakes of fresh fruits and vegetables and GF grains among children with CD (p < 0.05). CONCLUSIONS: GF-FI is prevalent in this multiethnic cohort of households with CD children and is associated with worsening DQ and GFD adherence. Policy interventions are urgently needed to address GF-FI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".