Increasing Prevalence and Stable Incidence Rates of Inflammatory Bowel Disease Among First Nations: Population-Based Evidence From a Western Canadian Province
Bibliographic record
Abstract
BACKGROUND: There is limited to no evidence of the prevalence and incidence rates of inflammatory bowel disease (IBD) among Indigenous peoples. In partnership with Indigenous patients and family advocates, we aimed to estimate the prevalence, incidence, and trends over time of IBD among First Nations (FNs) since 1999 in the Western Canadian province of Saskatchewan. METHODS: We conducted a retrospective population-based study linking provincial administrative health data from the 1999-2000 to 2016-2017 fiscal years. An IBD case definition requiring multiple health care contacts was used. The prevalence and incidence data were modeled using generalized linear models and a negative binomial distribution. Models considered the effect of age groups, sex, diagnosis type (ulcerative colitis [UC], Crohn disease [CD]), and fiscal years to estimate prevalence and incidence rates and trends over time. RESULTS: The prevalence of IBD among FNs increased from 64/100,000 (95% confidence interval [CI], 62-66) in 1999-2000 to 142/100,000 (95% CI, 140-144) people in 2016-2017, with an annual average increase of 4.2% (95% CI, 3.2%-5.2%). Similarly, the prevalence of UC and CD, respectively, increased by 3.4% (95% CI, 2.3%-4.6%) and 4.1% (95% CI, 3.3%-4.9%) per year. In contrast, the incidence rates of IBD, UC, and CD among FNs depicted stable trends over time; no statistically significant changes were observed in the annual change trend tests. The ratio of UC to CD was 1.71. CONCLUSIONS: We provided population-based evidence of the increasing prevalence and stable incidence rates of IBD among FNs. Further studies are needed in other regions to continue understanding the patterns of IBD among Indigenous peoples.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".