Explaining age-specific inequalities in mortality from all causes, cardiovascular disease and ischaemic heart disease among South Korean male public servants: relative and absolute perspectives
Bibliographic record
Abstract
OBJECTIVE: To examine age-specific patterns in the ability of major cardiovascular risk factors to explain relative and absolute socioeconomic inequalities in mortality from all causes, cardiovascular disease (CVD), and ischaemic heart disease (IHD). DESIGN: Prospective cohort study. SETTING: South Korea. SUBJECTS: 575 377 male public servants aged 30-64 with 16 998 deaths between 1995 and 2003. MAIN OUTCOMES: All-cause, CVD, and IHD mortality. RESULTS: Four cardiovascular risk factors (cigarette smoking, blood pressure, fasting serum glucose, and serum total cholesterol) were significantly associated with mortality risk. Changing relationships in socioeconomic distribution of risk factors with age were observed. The magnitude of reduction in percent change in absolute risk was greater than that in relative risk. While the risk factors explained only 15.2% of excess RR for all-cause mortality in low-income men aged 30-44, the absolute excess risk of all-cause mortality was reduced by 48.3% when the risk factors were removed from the whole population. This pattern was generally true for all causes, CVD, and IHD, and true for all age groups and risk factors examined. Cigarette smoking and hypertension were the leading contributors in explaining relative and absolute inequality in mortality. CONCLUSION: Policy efforts to eliminate major cardiovascular risk factors in the general population may have a significant effect on reducing the absolute burden of socioeconomic inequality in mortality. Policy efforts to attenuate socioeconomic inequality in cardiovascular risk factors need to be directed to younger age groups in South Korea.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".