Global Epidemiology and Geographic Variations of Pediatric-Onset Inflammatory Bowel Disease: A Comprehensive Analysis of the Global Burden of Disease Study 1990 to 2019
Bibliographic record
Abstract
BACKGROUND: An increasing incidence of pediatric-onset inflammatory bowel disease (PIBD) has been reported in many countries. However, the global burden and distribution of this disease remain less understood. We aimed to examine the global epidemiology and trends of PIBD from 1990 to 2019. METHODS: Data from the 2019 Global Burden of Disease Study, covering 204 countries, were analyzed. We assessed key measures like incidence, prevalence, mortality, and disability-adjusted life years (DALYs) using linear regression to calculate annual percentage changes and assess trends. RESULTS: Between 1990 and 2019, the PIBD incidence rate increased and the DALY rate and mortality rate declined. The incidence rate was notably elevated in the high Socio-demographic Index (SDI) quintile, reaching 6.3 per 100 000 person-years, corresponding to 13 914 new cases in 2019. Incidence and prevalence of PIBD positively correlated with the SDI, while higher death and DALY burdens were observed in lower-SDI countries. In 2019, the top 5 countries with the highest PIBD incidence rates were Canada (19.9 per 100 000 population), Denmark (12.4 per 100 000 population), Hungary (8.5 per 100 000 population), Austria (8.1 per 100 000 population), and the United States (7.4 per 100 000 population). Several countries experienced significant increases in incidence rates from 1990 to 2019, led by Taiwan (annual percent change 4.2%), followed by China (2.8%), Japan (2.1%), Australia (1.8%), and Hungary (1.6%). DISCUSSION: PIBD incidence has significantly increased since 1990. High-SDI countries face higher incidence, while lower-SDI countries experience higher mortality and DALY burdens. The study underscores the need for ongoing monitoring and research to address this emerging public health issue.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| 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) | 0.001 | 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".