Global and Chinese Burden of Inflammatory Bowel Disease From 1990 to 2021: A Systematic Analysis and Prediction of Disease Burden
Bibliographic record
Abstract
Background: Recent shifts in the global epidemiology of inflammatory bowel disease (IBD), particularly in emerging industrialized nations like China, underscore the need for in-depth analysis. Methods: Utilizing the Global Burden Of Disease (GBD) 2021 database, we systematically examined IBD incidence, prevalence, death rates, and disability-adjusted life years (DALYs) across Global, different social development index (SDI) regions, and countries from 1990 to 2021. Age-standardized rates (ASR) and statistical metrics (APC, EAPC, AAPC) were employed to assess trends in IBD development, and a Bayesian age-period-cohort (BAPC) model was used to forecast future scenarios. Results: In 2021, the highest IBD incidence rates were observed in Canada (26.83/100000), Greenland (24.57/100000), and New Zealand (23.69/100000), markedly contrasting China's rate of 1.4/100000. Globally, IBD incidence increased modestly from 4.22/100000 in 1990 to 4.45/100000 in 2021 (EAPC = 0.29%). China experienced a more pronounced rise, with incidence jumping from 0.74/100000 to 1.4/100000 (EAPC = 2.93%). Notably, China also witnessed substantial declines in IBD deaths (56.00%) and DALYs (58.22%). The Middle SDI region exhibited a greater magnitude of change than Global and other SDI regions. The temporal trends in the incidence and prevalence of IBD in the countries are predominantly influenced by the period up to the year 2015. In China, between the ages of 15 and 49, the incidence and prevalence of IBD are projected to remain consistent with current standards, while the death rate and DALYs are predicted to exhibit a sustained decline. Conclusion: Despite the notable increase in IBD incidence in China, significant reductions in mortality and morbidity demonstrate the effectiveness of medical interventions and health system improvements.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".