Social influences on trajectories of self-rated health: evidence from Britain, Germany, Denmark and the USA
Bibliographic record
Abstract
BACKGROUND: This study investigates social inequalities in self-rated health dynamics for working-aged adults in four nations, representing distinct welfare regime types. The aims are to describe average national trajectories of self-rated health over a 7-year period, identify social determinants of cross-sectional and longitudinal health and compare cross-national patterns. METHODS: Data are from national household panel surveys in Britain, Germany, Denmark and the USA. The self-rated health of working-age respondents is measured for the years 1995-2001. Social indicators include education, occupational class, employment status, income, age, gender, minority status and marital status. Latent growth curve models are used to estimate both individual change and average national trajectories of self-rated health, conditioned on the social indicators. RESULTS: Ageing-vector graphs reveal general declines in health as people age. They also show differential patterns of change for specific national cohorts. Older cohorts in Denmark had poorer health and young cohorts in the USA had better health in 2001 than 1995. Social covariates predicted baseline health in all four countries, in ways that were consistent with welfare regime theories. Once inequalities in baseline health were accounted for, the few determinants of mean health decline occurred mainly in the USA, again in line with theoretical expectations. Finally, trajectories of health for those in average and advantaged social circumstances were similar, but disadvantaged individuals had much poorer health trajectories than 'average' individuals. The differences were greatest in the countries with lower levels of public transfers. CONCLUSION: National differences in self-rated health trajectories and their social correlates may be attributed partly to welfare policies.
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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 | 0.037 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".