Impact of Body Mass Index on the Development of Inflammatory Bowel Disease: A Systematic Review and Dose-Response Analysis of 15.6 Million Participants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: A growing trove of literature describes the effect of malnutrition and underweight on the incidence of inflammatory bowel disease (IBD). However, evidence regarding the association between underweight or obesity and IBD is limited. The study aimed to assess the association of body mass index (BMI) with a risk of IBD (Crohn’s disease (CD) and ulcerative colitis (U.C.)) incidence. Methods: We systematically searched PubMed/Medline, Cochrane, Web of Science, and Scopus for observational studies assessing the association between BMI and IBD that were published up to 30 June 2020. We estimated pooled hazard ratios (HR) with corresponding 95% confidence intervals (CI). Random effect dose-response meta-analysis was performed using the variance weighted least-squares regression (VWLS) models to identify non-linear associations. Results: A total of ten studies involving 15.6 million individuals and 23,371 cases of IBD were included. Overall, obesity was associated with an increased IBD risk (HR: 1.20, 95% CI: 1.08–1.34, I2 = 0%). Compared to normal weight, underweight (BMI < 18.5 kg/m2) and obesity (BMI ≥ 30 kg/m2) were associated with a higher risk of CD, and there was no difference in the risk of U.C. among those with BMI < 18.5 kg/m2 and BMI ≥ 30 kg/m2. There was a significant non-linear association between being underweight and obesity and the risk of development of CD (Coef1 = −0.0902, p1 < 0.001 Coef2 = 0.0713, p2 < 0.001). Conclusions: Obesity increases the risk of IBD development. Underweight and obesity are independently associated with an increased risk of CD, yet there is no evident association between BMI and the risk of U.C. Further studies are needed to clarify the underlying mechanism for these findings, particularly in CD.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it