Abstract 88: Social Inequalities in Stroke Mortality, Incidence and Case-fatality in Europe.
Bibliographic record
Abstract
Introduction and aim: There are limited comparative data on social inequalities in stroke morbidity across Europe. We aimed to assess the magnitude of educational class inequalities in stroke mortality, incidence and 1-year case-fatality in European populations. Methods: The MORGAM study comprised 45 cohorts from Finland, Denmark, Sweden, Northern Ireland, Scotland, France, Germany, Italy, Lithuania, Poland and Russia, mostly recruited in mid 1980s-early 90s. Baseline data collection and follow-up (median 12 years) for fatal and non-fatal strokes adhered to MONICA-like procedures. Stroke mortality was defined according to the underlying cause of death (ICD-IX codes 430-438 or ICD-X I60-I69). We derived 3 educational classes from population-, sex- and birth year-specific tertiles of years of schooling. We estimated the age-adjusted difference in event rates, and the age- and risk factor-adjusted hazard ratios (HRs), between the bottom and the top of the educational class distribution from sex- and population-specific Poisson and Cox regression models, respectively. The association between 1-year case-fatality and education was estimated through logistic models adjusted for risk factors. Results: Among the 91,563 CVD-free participants aged 35-74 at baseline, 1037 stroke deaths and 3902 incident strokes occurred during follow-up. Low education accounted for 26 additional stroke deaths per 100,000 person-years in men (95%CI: 9 to 42), and 19 (7 to 32) in women. In both genders, inequalities in fatal stroke rates were larger in the East EU and in the Nordic Countries populations. The age-adjusted pooled HRs of first stroke, fatal or non-fatal, for the least educated men and women were 1.52 (95%CI: 1.29-1.78) and 1.51 (1.25-1.81), respectively, consistently across populations. Adjustment for smoking, blood pressure, HDL-cholesterol and diabetes attenuated the pooled HRs to 1.34 (95%CI: 1.14-1.57) in men and 1.29 (1.07-1.55) in women. A significant association between low education and increased 1-year case-fatality was observed in Northern Sweden only. Conclusions: Social inequalities in stroke incidence are widespread in most European populations, and less than half of the gap is explained by major risk factors.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".