Incidence of Inflammatory Bowel Disease in South Asian and Chinese People: A Population-Based Cohort Study from Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD) is now a global disease with incidence increasing throughout Asia. AIM: To determine the incidence of IBD among South Asians and Chinese people residing in Ontario, Canada's most populous province. METHODS: All incident cases of IBD in children (1994-2015) and adults (1999-2015) were identified from population-based health administrative data. We classified South Asian and Chinese ethnicity using immigration records and surnames. We determined standardized incidence of IBD and adjusted incidence rate ratio (aIRR) in South Asians and Chinese compared to the general population. RESULTS: Among 16,230,638 people living in Ontario, standardized incidence of IBD per 100,000 person-years was 24.7 (95% CI 24.4-25.0), compared with 14.6 (95% CI 13.7-15.5) in 982,472 South Asians and with 5.4 (95% CI 4.8-5.9) in 764,397 Chinese. The risk of IBD in South Asians was comparable to the general population after adjusting for immigrant status and confounders (aIRR 1.03, 95% CI 0.96-1.10). South Asians had a lower risk of Crohn's disease (CD) (aIRR 0.66, 95% CI 0.60-0.77), but a higher risk of ulcerative colitis (UC) (aIRR 1.47, 95% CI 1.34-1.61). Chinese people had much lower rates of IBD (aIRR 0.24, 95% CI 0.20-0.28), CD (aIRR 0.21, 95% CI 0.17-0.26), and UC (aIRR 0.28, 95% CI 0.23-0.25). CONCLUSION: Canadians of South Asian ethnicity had a similarly high risk of developing IBD compared to other Canadians, and a higher risk of developing UC, a finding distinct from the Chinese population. Our findings indicate the importance of genetic and environmental risk factors in people of Asian origin who live in the Western world.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".