Compounding Prevalence of Inflammatory Bowel Disease in a 2024 Population‐Based Study From Canterbury, New Zealand
Bibliographic record
Abstract
Background and Aim: The epidemiological patterns of inflammatory bowel disease (IBD) can give insights into disease etiology and health system burden. This study aimed to measure the population-based prevalence in Canterbury and consider the region's position within the 4-stage epidemiological model of IBD. Methods: Gastroenterology clinics in Canterbury were searched for patients with a confirmed diagnosis of IBD. Demographic and disease details (including Montreal phenotype) were extracted from individual medical records. The prevalence of IBD, Crohn's disease (CD), ulcerative colitis (UC) and inflammatory bowel disease unclassified (IBDU) was established for the total population and for age, sex, and ethnic sub-groups. Results: Altogether 4042 individuals (1 in 150 people) in Canterbury with IBD were identified. The point prevalence of IBD on 1st January 2024 was 671 (95% CI 651-692) per 100 000 persons. The prevalence of CD 386 (95% CI 370-402) was higher than UC 264 (95% CI 251-277) each per 100 000. Almost three times as many individuals had IBD in 2024, compared to a 2005 study. The majority of the cohort were New Zealand European (92.9%) followed by Māori (4.2%), Asian (2.6%) and Pacific peoples (0.3%). Older adults (65+ years) comprised 21% of the population with a prevalence of 845 (95% CI 789-904) per 100 000 persons. Conclusion: Canterbury has the highest reported prevalence of IBD in Oceania to date, and there is a growing proportion of older age patients. The rapid rise in cases supports the hypothesis that Canterbury is in the compounding prevalence stage of the epidemiological model of IBD.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".