Household Supplemental Nutrition Assistance Program Participation is Associated With Higher Fruit and Vegetable Consumption
Bibliographic record
Abstract
OBJECTIVE: Examine whether differences were present by Supplemental Nutrition Assistance Program (SNAP) participation in dietary patterns, achievement of dietary recommendations, and food security for children (aged 7-18 years) receiving free/reduced-price school meals. METHODS: Cross-sectional study. Caregiver-child dyads at a pediatric clinic completed validated surveys. Food security, dietary patterns, and achievement of dietary recommendations were compared between child SNAP participants/nonparticipants. RESULTS: Among 205 caregivers, 128 (62.4%) reported SNAP participation. Percentages of child SNAP participants/nonparticipants meeting recommendations were largely nonsignificantly different and overwhelmingly low. Supplemental Nutrition Assistance Program participants reported higher mean daily servings of vegetables (P = 0.01) and fruits (P = 0.01) than nonparticipants. Caregiver-reported household food security was not significantly different between SNAP participants and nonparticipants (P = 0.44). CONCLUSIONS AND IMPLICATIONS: In this study, child-reported fruit/vegetable intakes were significantly higher among SNAP participants than nonparticipants, suggesting child SNAP participants may experience small but noteworthy benefits related to fruit/vegetable consumption. Additional supports are needed to achieve dietary recommendations.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".