Association Between Social Determinants of Health and the Risk of Acute Pancreatitis and Related Diseases: A Prospective Cohort Study in the UK Biobank
Bibliographic record
Abstract
BACKGROUND: Social determinants of health (SDH) encompass socioeconomic and environmental factors that influence individual health outcomes. While SDH has been studied in relation to cardiovascular and metabolic diseases, its potential relationship with acute pancreatitis (AP) remains insufficiently explored. METHODS: We conducted a prospective cohort study using data from the UK Biobank, including over 340,000 participants without a history of AP at baseline. A composite SDH score was constructed from multiple indicators, and the association between SDH and incident AP was examined using Cox proportional hazards models. Restricted cubic spline (RCS) regression was used to assess dose-response relationships. Stratified analyses were performed by demographic and clinical subgroups. Associations between SDH and AP-related diseases were also investigated. RESULTS: Elevated SDH scores were significantly associated with increased AP risk ( P < 0.001), with a linear dose-response relationship confirmed by RCS analysis. After full adjustment, the risk of AP was found to be higher in participants with unfavorable SDH (HR: 1.52, 95% CI: 1.37-1.70) compared with those with favorable SDH. In post-AP individuals, participants in the higher SDH group had increased risks of chronic pancreatitis (CP) and type 2 diabetes mellitus (T2DM). However, no significant association was found between SDH and post-AP pancreatic cancer (PC; P = 0.632). CONCLUSIONS: Social disadvantage, as reflected by higher SDH scores, is associated with high risk of AP and AP-related diseases. These findings underscore the importance of considering social context in clinical and public health efforts to reduce the burden of pancreatic diseases.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".