Higher Prevalence of Diabetes Mellitus and Impaired Glucose Tolerance Among the Rural Population in Bulgaria
Bibliographic record
Abstract
Background: The socio-economic level is probably among the central risk factors for type 2 diabetes mellitus (T2DM) along with obesity, decreased physical activity and smoking. The International Diabetes Federation notes in particular that the main impact in the prevalence of diabetes is observed in low and middle-income countries, hence the disease might disproportionately affect lower socio-economic groups. The aim of the study was to determine the prevalence of diabetes and impaired glucose tolerance (IGT) and assess its association with the type of place of residence in Bulgaria - cities, small towns and villages. Methods: We surveyed 2,032 subjects from five major geographic regions of the country, with age and gender proportions according to the latest population census - 27.5% rural population and 72.5% urban population. We included 1,076 women (53%) and 956 men (47%), with a mean age of 49.3 ± 14.8 years (20 - 80 years). Fasting blood glucose was measured in all participants and when indicated oral glucose tolerance test was performed. Diabetes was defined according to the WHO criteria (1999). Results: The prevalence of known T2DM, previously unknown T2DM and IGT was significantly higher among the rural population than in the city population - known T2DM: 8.6% (46/535) vs. 6% (62/1,031), P < 0.02; previously unknown T2DM: 3.55% (19/535) vs. 1.74% (18/1,031), P < 0.02; IGT: 2.4% (13/535) vs. 1.1% (12/1,031), P < 0.04. The combined prevalence of diabetes (known and unknown) and IGT (impaired fasting glucose (IFG) + IGT) was 16.44% (88/535) in the rural population, 14.13% (66/467) (NS) in small towns, and 11.16% in cities (115/1,030) (P < 0.01). Conclusions: National screening programs for diabetes should focus on the rural population due to the higher diabetes prevalence that might be explained by multiple adverse socio-economic factors. J Endocrinol Metab. 2016;6(2):52-58 doi: http://dx.doi.org/10.14740/jem334w
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".