Food Insecurity Is Common in Patients with Inflammatory Bowel Disease and Is Associated with Increased Ultra-Processed Food Intake
Bibliographic record
Abstract
Background/Objectives: Food insecurity (FI) is defined as the lack of consistent access to enough food for an active and healthy life. FI affects over 30 million Americans and is associated with poor clinical outcomes and impaired quality of life and drives significant health inequities. Despite the rising prevalence of FI and the federal focus on improving access to healthy food, there is a paucity of research on FI in patients with inflammatory bowel disease (IBD). Therefore, the goal of this study was to define FI in a cohort of IBD patients and determine whether FI was associated with changes in dietary patterns, including specifically an increase in ultra-processed food (UPF) consumption in this high-risk patient population. Methods: This was a single-center, retrospective cohort study of patients with a diagnosis of IBD who were 18 years of age or older and who were seen in a nutrition focused clinic. Patients were screened for FI using the Hunger Vital Sign™, a 2-question validated FI screening tool and underwent a 24-h dietary recall. The degree of food processing was assessed using the NOVA Food Classification System. Results: Among 128 patients with IBD, we observed that FI is increasingly prevalent, with 45% of patients reporting difficulty with sufficient grocery access at least “sometimes” in the last 12 months and 10% reporting decreased food access “often” in the prior year. In addition, the patients at high-risk for FI were significantly more likely to eat NOVA 4 UPFs (54% vs. 27%, p = 0.001) and were significantly less likely to eat NOVA 1 unprocessed foods (32% vs. 61%, p = 0.001) as compared to those not at risk for FI. Finally, only a small percentage of those at highest risk for FI were enrolled in a federal food assistance program for grocery support. Conclusions: The prevalence of FI is increasing in patients with IBD and is associated with reduced dietary quality.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".