Differences in adiposity and diet quality among individuals with inflammatory bowel disease in Eastern Canada
Bibliographic record
Abstract
The objective of the current study was to characterize the relationship between diet quality and body composition in participants living with IBD, specifically Crohn's disease (CD) or ulcerative colitis (UC), in Atlantic Canada. Participants from the Atlantic Partnership for Tomorrow's Health (PATH) study are residents of one of the four Atlantic Canada provinces. Participants who completed the dietary questionnaire and had body composition measured were included in the study (n = 12,462 without IBD, n = 111 CD, n = 119 UC). A greater number of participants with IBD reported having multiple chronic conditions compared to those without IBD. Those with UC had statistically higher body weight and body mass index (BMI) compared to those without IBD. Overall, significant positive correlations were observed between adiposity and servings of refined grains, and meats and alternatives such as eggs and fish, whereas negative correlations were observed with servings of vegetables, fruit, whole grains, and alternatives such as tofu, and nuts/seeds. Participants with IBD (both CD and UC) consumed more refined grains than those without IBD. Using logistic regression analysis, participants consuming more servings of vegetables and whole grains were less likely to have CD where as those consuming more serving of fruit and bean/legumes were less likely to have UC. In the Atlantic PATH cohort, which includes a region of the world with a high incidence of IBD, distinct differences in adiposity and diet quality were observed in individuals with specific types of IBD compared to those without. There is a need for collaborative efforts to address weight management and diet quality issues in those living with IBD in the Atlantic Canadian region.
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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 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".