Own education, current conditions, parental material circumstances, and risk of myocardial infarction in a former communist country
Bibliographic record
Abstract
OBJECTIVE: To study the association between own education, adult and parental circumstances and the risk of myocardial infarction in a former communist country. DESIGN: Population based case-control study. SETTING: General population of five districts of the Czech Republic in the age group 25-64 years. PARTICIPANTS: Random sample of population (938 men and 1048 women, response rate 77%) served as controls to 282 male and 80 female cases of non-fatal first myocardial infarctions. MAIN OUTCOME MEASURES: Myocardial infarction was defined by the WHO MONICA criteria based on ECG, enzymes and symptoms. The following socioeconomic indicators were studied: own education, crowded housing conditions (more than one person per room), car ownership, and education and occupation of mother and father. RESULTS: There was a weak correlation between education and car ownership, and a strong association between own education and parental education and occupation. Crowding was not related to other socioeconomic factors. The risk of myocardial infarction was inversely related to education, and was unrelated to material conditions and parental education and occupation. The age-sex-district adjusted odds ratios for apprenticeship, secondary, and university education, compared with primary education, were 0.87, 0.74 and 0.46, respectively (p for trend 0.009); odds ratios for car ownership and crowding were 1.01 (95% confidence intervals 0.77, 1.34) and 0.92 (0.76, 1.12), respectively. Further adjustment for parental circumstances and adult height did not change these estimates but adjustment for coronary risk factors reduced the gradient. Increased height seemed, anomalously, to confer a small increased risk. CONCLUSIONS: In this population, the social gradient in non-fatal myocardial infarction is only apparent for own education. Materialist explanations for this gradient seem unlikely but behaviours seem responsible for a part of the gradient.
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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 | 0.013 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".