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Effect of Rural Living on the Development of the Inflammatory Bowel Diseases: A Nested Case-control Study

2011· article· en· W2978774911 on OpenAlexaff
Alexandra Frolkis, James Hubbard, Jennifer deBruyn, Nathalie Jetté, Cynthia H. Seow, Subrata Ghosh, Remo Panaccione, Gilaad G. Kaplan

Bibliographic record

VenueThe American Journal of Gastroenterology · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineOdds ratioInflammatory bowel diseaseSocioeconomic statusIncidence (geometry)Rural areaDemographyInternal medicineObservational studyUlcerative colitisConfidence intervalLogistic regressionEnvironmental healthDiseasePopulation

Abstract

fetched live from OpenAlex

Purpose: Observational studies have demonstrated an increase in ulcerative colitis (UC) and Crohn's disease (CD) incidence in more densely populated areas; however, the risk of developing the inflammatory bowel diseases (IBD) in rural areas has been inadequately studied. The purpose of this study was to investigate the effect of two distinct levels of rural living on the risk of developing IBD. Methods: The health improvement network (THIN) database, which includes prospectively gathered health data in the United Kingdom (UK), was used to identify incident cases of CD (n=367) or UC (n=588), and age and sex-matched controls (5 controls per case). The urban-rural spectrum was divided into three distinctly defined levels based on settlement density profiles of 1 hectare (100 x 100 meters) squares in the UK: urban; town and fringe; village, hamlet, and isolated dwelling. Conditional logistic regression was used to assess whether CD and UC patients were more likely to live in rural areas after adjusting for smoking, socioeconomic status (SES), nonsteroidal anti-inflammatory drugs (NSAIDs), and appendectomy. Risk estimates were presented as odds ratios (OR) with 95% confidence intervals (CI). Joint age-sex modification were explored through likelihood ratio tests. Results: Significant associations were not observed between level of rural living and CD after adjusting for smoking (current versus never OR=1.55; 95% CI: 1.14-2.12), SES (OR= 0.75, 95% CI: 0.49-1.14), NSAIDs (OR=1.31, 95% CI: 0.82-2.09), and appendectomy (OR=1.96, 95% CI: 1.29-2.98). In contrast, living in the most rural area, defined as village, hamlet, or isolated dwelling, was significantly associated with a reduced risk of developing UC (OR 0.59; 95% CI 0.39-0.90) after adjusting for smoking (current versus never OR=0.58; 95% CI 0.42-0.79), SES (OR=0.91; 95% CI 0.64-1.29), NSAIDs (OR=1.05; 95% CI 0.74-1.50), and appendectomy. (OR=0.38; 95% CI 0.22-0.64). However, living in the less rural area, defined as town and fringe, was not associated with UC (OR 0.88; 95% CI = 0.67-1.15) after adjustment for confounders. Effect modification was not observed (p-value 0.8). Conclusion: Rurality was not associated with the risk of CD. In contrast, living in extreme rural areas as defined by settlement density was associated with decreased incidence of UC.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.005
GPT teacher head0.220
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2011
Admission routes1
Has abstractyes

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