Trends in socioeconomic inequalities in self-assessed health in 10 European countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Changes over time in inequalities in self-reported health are studied for increasingly more countries, but a comprehensive overview encompassing several countries is still lacking. The general aim of this article is to determine whether inequalities in self-assessed health in 10 European countries showed a general tendency either to increase or to decrease between the 1980s and the 1990s and whether trends varied among countries. METHODS: Data were obtained from nationally representative interview surveys held in Finland, Sweden, Norway, Denmark, England, The Netherlands, West Germany, Austria, Italy, and Spain. The proportion of respondents with self-assessed health less than 'good' was measured in relation to educational level and income level. Inequalities were measured by means of age-standardized prevalence rates and odds ratios (ORs). RESULTS: Socioeconomic inequalities in self-assessed health showed a high degree of stability in European countries. For all countries together, the ORs comparing low with high educational levels remained stable for men (2.61 in the 1980s and 2.54 in the 1990s) but increased slightly for women (from 2.48 to 2.70). The ORs comparing extreme income quintiles increased from 3.13 to 3.37 for men and from 2.43 to 2.86 for women. Increases could be demonstrated most clearly for Italian and Spanish men and women, and for Dutch women, whereas inequalities in health in the Nordic countries showed no tendency to increase. CONCLUSIONS: The results underscore the persistent nature of socioeconomic inequalities in health in modern societies. The relatively favourable trends in the Nordic countries suggest that these countries' welfare states were able to buffer many of the adverse effects of economic crises on the health of disadvantaged groups.
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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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 it