A population based case–control study of association between dietary calcium intake and ulcerative colitis in adults
Bibliographic record
Abstract
Limited data are available on the association of dietary calcium intake and ulcerative colitis (UC). We aimed to investigate the relation between dietary calcium intake and UC prevalence in Iranian adults. In this population-based case-control study, diagnosed patients with UC by gastroenterologists that were registered in the Iranian inflammatory bowel disease registry were included as cases. Age and sex-matched healthy controls were selected from Study on the Epidemiology of Psychological, Alimentary Health and Nutrition (SEPAHAN) dataset. Dietary calcium intakes of participants were examined through a validated food frequency questionnaire. We included 327 middle-aged participants (109 cases and 218 controls) in the analysis; 52.1% of them were females. After adjustments for potential confounders, individuals in the third tertile of dietary calcium intake had 92% lower odds of UC, compared to those in the first tertile (OR = 0.08, 95% CI 0.02-0.27). Our analysis based on recommended dietary allowances (RDAs) intake showed that dietary Ca intake deficiency was related to increased odds of UC (OR = 9.5, 95% CI 2.98-30.91). Stratified analysis by gender revealed that these associations were significant in both genders; although the results were stronger in the male population. A Significant decreasing trend was observed for odds of UC in tertiles of dietary calcium intakes, in both males and females. Higher dietary calcium intake was associated with lower UC prevalence in Iranian adults. Inadequate dietary calcium intake was also linked to elevated odds of UC. Further prospective investigations are needed to affirm these findings.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".