Widening inequalities in self-rated health by material deprivation? A trend analysis between 2001 and 2011 in Germany
Bibliographic record
Abstract
BACKGROUND: Research on inequalities in health has shown a strong association between the lack of standard of living (defined as material deprivation) and self-rated health (SRH). In this study, we sought to further examine this association in a trend analysis of relative and absolute inequalities in SRH as defined by material deprivation in Germany. METHODS: Data were obtained from the German Socio-Economic Panel (GSOEP) between 2001 and 2011. Material deprivation was measured on the basis of 11 living standard items missing due to financial reasons. We used the relative index of inequality (RII) and slope index of inequality (SII) to measure inequalities in SRH by material deprivation, calculating pooled interval logistic regression with robust SEs. Stepwise models were estimated, including demographic and socioeconomic variables, to assess their inter-relation with inequalities in SRH by material deprivation. RESULTS: The results showed a steady increase in poor SRH over the 10-year duration of the study. A quadratic (inverted U-shaped) trend was observed in material deprivation in the standards of living, which rose from 2001 to 2005, and then declined in 2011. A similar but non-significant trend was found in relative and absolute inequalities in SRH by material deprivation, which increased from 2001 to 2005 and then declined. CONCLUSIONS: Inequality in SRH by material deprivation was relatively stable; however, an observed quadratic trend coincided with active and passive labour market reforms in Germany in early 2005.
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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 | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".