Welfare Regimes and Social Inequalities in Health Dynamics: A Comparative Analysis of Panel Data from Britain, Denmark, Germany and the US
Bibliographic record
Abstract
Objective: 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.\nDesign: Prospective nationally representative household panel studies (the US Panel Study of Income Dynamics; British Household Panel Survey; the German Socio-Economic Panel Survey; the Danish panel from the European Community Household Panel Survey).\nSetting: The US, Britain, Germany and Denmark\nParticipants: Household heads and their partners of working age throughout follow-up (US: 4855; Britain: 4365; Germany: 4694; Denmark: 3252).\nMain Outcome Measure: Repeated measures of self-rated health (1995 – 2001). Social indicators include education, occupational class, employment status, income, age, gender, minority status and marital status, all measured in 1994.\nMethods: Latent growth curve models describe average national trajectories of self-rated health and individual differences in these trajectories. Latent factors representing intercept and slope components are extracted from seven annual observations across time for self-rated health, and are conditioned on predictors measured one year prior to baseline. Aging-vector graphs are used to visualize trajectories of self-rated health.\nResults: The vector graphs for the US and Germany show that self-rated health remained relatively stable for young adults, declined as adults became middle aged and then became more stable again. The graphs for Britain and Denmark indicate a steady decline throughout working life. The Danish model indicates an unfavourable trend in self-rated health during a period that experienced a move to monetarism: ratings were lower for persons of a given age in 2001 than for persons of the same age in 1995. Social covariates predicted baseline health in all four countries, with the strength of association consistent with Esping-Andersen’s welfare regime type. The strongest social gradients were seen in the US, while the weakest were seen in Germany and Denmark. Britain occupied a position between these two extremes. Once inequalities in baseline health had been accounted for, there were few determinants of mean health decline. When these did occur, they were in countries classified as liberal welfare states. There was little difference in the aging trajectories for those with advantaged and average social profiles. By contrast, disadvantage has a strong effect on aging trajectories. Differences were already apparent at 25 years of age in the US and Britain and gaps widened with age in all four countries.\nConclusion: National differences in self-rated health trajectories and their social correlates may be attributed, in part, to welfare policies.\nThe paper is forthcoming in the Journal of Community Health and Epidemiology (JECH).\nPeggy McDonough is an Associate Professor in the Dalla Lana School of Public Health at the University of Toronto. Her research interests in social inequalities in health and women’s health have led her recently to incorporate a comparative welfare state dimension in her studies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".