Is Being Single a Risk Factor for Previously Undetected Abnormal Glucose Tolerance?
Bibliographic record
Abstract
BACKGROUND: Type II diabetes represents a chronic disease with costly consequences. It is important to identify all risk factors to allow patients the opportunity to counter its progression. The aim of this study was to evaluate the association between marital status and previously undiagnosed abnormal glucose tolerance (AGT) in a northern Colombian population.METHODS: Secondary data analysis of a cross-sectional screening study in a northern Colombian adult population ages 18-74 using healthcare insurance company data from 2014-2015. The main exposure was marital status, while the outcome was AGT. A descriptive analysis of the variables in the database was conducted, and chi-square analysis of categorical covariates and a t-test of continuous covariates were performed. Unadjusted and adjusted linear regression models were used to evaluate the association between marital status and AGT.RESULTS: Single individuals had a 20% decreased odds of having AGT compared to married individuals (odds ratio (OR) 0.80, 95% confidence interval (CI) 0.7 - 1.0), but this association disappeared after adjusting for covariates (OR 1.0, 95% CI 0.7 - 1.2). There was a 40% increased odds of AGT in women compared to men (OR 1.40, 95% CI 1.1 - 1.8). Hypertension increased the risk of AGT by about 60% (OR 1.60, 95% CI 1.2 - 2.1), while obesity was associated with an 80% increased odds of developing AGT (OR 1.80, 95% CI 1.3 - 2.4).CONCLUSION: Our study suggests that screening for abnormal glucose tolerance may not be necessary in specific marital status groups.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".