Relationship between socioeconomic status and type 2 diabetes: results from Korea National Health and Nutrition Examination Survey (KNHANES) 2010–2012
Bibliographic record
Abstract
OBJECTIVE: To examine the relationship between socioeconomic status (SES) and type 2 diabetes using the Korea National Health and Nutrition Examination Survey (KNHANES) 2010-2012. DESIGN: A pooled sample cross-sectional study. SETTING: A nationally representative population survey data. PARTICIPANTS: A total of 14,330 individuals who participated in the KNHANES 2010-2012 were included in our analysis. PRIMARY OUTCOME: Prevalence of type 2 diabetes. RESULTS: The relationship between SES and type 2 diabetes was assessed using logistic regression after adjusting for covariates including age, gender, marital status, region, body mass index, physical activity, smoking and high-risk drinking behaviour. After adjustment for covariates, our results indicated that individuals with the lowest income were more likely to have type 2 diabetes than those with the highest income (OR 1.35; 95% CI 1.08 to 1.72). In addition, lower educational attainment was an independent factor for a higher prevalence of type 2 diabetes in Korea. CONCLUSIONS: These findings suggest the need for developing a health policy to ameliorate socioeconomic inequalities, in particular income and education-related disparities in type 2 diabetes, along with risk factors at the individual level. In addition, future investigations of type 2 diabetes among Koreans should pay more attention to the social determinants of diabetes in order to understand the various causes of the condition.
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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) | 0.000 | 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".