OP05 Association of ultra-processed food intake with risk of Inflammatory Bowel Disease from the prospective urban rural epidemiology (PURE) study: A prospective cohort study
Bibliographic record
Abstract
Abstract Background Dietary factors may influence the risk of developing inflammatory bowel disease (IBD), but evidence from large, prospective studies is scarce. This study aimed to evaluate the relationship between ultra-processed food intake and the risk of developing IBD in the Prospective Urban Rural Epidemiology (PURE) cohort study. Methods This was a prospective cohort study among 21 low, middle, and high income countries across seven geographic regions of 116,087 individuals between the ages of 35–70 with at least one cycle of follow-up and complete baseline food frequency questionnaire (FFQ) data. Country-specific validated FFQs were used to document baseline dietary intake. Participants were followed prospectively at least every 3 years. The main clinical outcome for this study was development of IBD, including Crohn’s disease (CD) or ulcerative colitis (UC). Cox proportional hazard multivariable models were used to assess associations between ultra-processed food intake and risk of IBD. Results are presented as hazard ratios (HR) with 95% confidence intervals (CI). Results Participants were enrolled in the study between 2003 and 2016. During the median follow-up of 9.7 years (IQR 8.9–11.2), we recorded 467 incident cases of IBD (90 with CD and 377 with UC). Higher ultra-processed food intake was associated with a higher risk of incident IBD (HR 1.82, 95% CI 1.22 to 2.72 for ≥5 servings/day and HR 1.67, 95% CI 1.18 to 2.37, for 1–4 servings/day as compared to <1 serving/day, ptrend=0.006), after adjustment for potential confounding factors. Different subgroups of ultra-processed food including soft drinks, sweets, salty snacks, and processed meat each were associated with higher HR for IBD. Results were consistent in UC and CD with low heterogeneity. White meat, red meat, dairy, starch, fruits, vegetables, and legumes intake were not associated with incident IBD. Conclusion Higher ultra-processed food consumption was positively associated with development of IBD. Further studies are needed to identify the potential culprits within ultra-processed foods.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".