Inflammatory Bowel Diseases Before and After 1990
Bibliographic record
Abstract
Background and Aims Inflammatory bowel disease (IBD) is caused by interaction of genetic and environmental risk factors. We evaluated potential determinants of the post-1990 increased incidence in North America. Methods Using fitted generalized linear models, we assessed clinical features, smoking and genetic risk scores (GRS) for Crohn's disease (CD) and ulcerative colitis (UC) in the National Institutes of Diabetes, Digestion and Kidney Diseases IBD Genetics Consortium database, before and post 1990. Results Among 2744 patients (55% CD, 42.2% UC), smoking status and GRS were the main determinants of diagnosis age. After 1990, smoking at diagnosis declined significantly in both UC and CD (34.1% vs 20.8%, P < .001, and 14.7% vs 8.7%, P = .06, respectively). In UC, ex-smoking increased (9% vs 15%, P < .001), and nonsmoking rates remained unchanged, whereas in CD, ex-smoking remained unchanged. CD-GRS and IBD-GRS were significantly associated with young diagnosis age, Jewish ethnicity, IBD family history, and surgery. CD-GRS showed a borderline significant decrease ( P = .058) in multivariate analysis post 1990 but only when excluding surgery in the model; surgery significantly decreased post 1990 in both CD and UC. CD-GRS inversely correlated with smoking at diagnosis ( P < .001) suggesting that, in the presence of smoking, CD may only require a low genetic risk to develop. Conclusion Significantly increase in ex-smoking correlates with UC incidence post 1990. Conversely, smoking risk decreased significantly post 1990 despite rising CD incidence. CD-GRS likewise trended to decrease post 1990 only when not accounting for a significant decrease in CD surgery. We therefore deduce that unaccounted risk factors (eg, dietary, obesity, antibiotic use, improved hygiene, etc.) or greater detection or presence of mild CD may underlie post-1990 increased CD incidence.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".