The 2023 Impact of Inflammatory Bowel Disease in Canada: Epidemiology of IBD
Bibliographic record
Abstract
Inflammatory bowel disease (IBD), consisting of Crohn's disease and ulcerative colitis, is recognized across the world, though Canada has among the highest burdens of IBD in the world. The Canadian Gastro-Intestinal Epidemiology Consortium (CanGIEC) led a six-province study that demonstrated the compounding prevalence of IBD in Canada from 400 per 100,000 in 2002 to 636 per 100,000 in 2014. The prevalence in 2023 is estimated at 825 per 100,000, meaning that over 320,000 people in Canada are living with IBD. Prevalence is forecasted to rise by 2.44% per year such that 1.1% of the population, 470,000 Canadians, will live with IBD by 2035. The overall incidence of IBD in 2023 is 30 per 100,000 person-years, indicating that over 11,000 Canadians will be newly diagnosed with IBD in 2023. Incidence is forecasted to rise by 0.58% per year up to 32.1 per 100,000 by 2035. The rising incidence of IBD is propelled by pediatric-onset IBD, which is rising by 1.23% per year from 15.6 per 100,000 in 2023 to 18.0 per 100,000 in 2035. In contrast, incidence rates among adults and seniors are relatively stable. Understanding the determinates of IBD has expanded through prospective cohort studies such as the Crohn's and Colitis Canada Genetic, Environmental, Microbial (CCC-GEM) project. Consensus recommendations towards diet, lifestyle, behavioural and environmental modifications have been proposed by international organizations with the goal of optimizing disease control and ultimately preventing the development of IBD. Despite these efforts, Canadian healthcare systems will need to prepare for the rising number of people living with IBD.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".