Age, SES, and health: a population level analysis of health inequalities over the lifecourse
Bibliographic record
Abstract
This paper tests two competing hypotheses on the relationship between age, SES, and health inequality at the cohort/population level. The accumulation hypothesis predicts that the level of SES-based health inequality, and consequently the overall level of health inequality, within a cohort progressively increases as it ages. The divergence-convergence hypothesis predicts that these inequalities increase only up to early-old age then decrease. Data from a Canadian national health survey are used in this study, and are adjusted for SES-biases in mortality. Bootstrap methods are employed to assess the statistical precision and significance of the results. The Gini coefficient is used to estimate change in the overall level of health inequality with age, and the Concentration coefficient estimates the contribution of SES-based health inequalities to this change. Health is measured using the Health Utilities Index, and income and education provide the measure of SES. First, the findings show that the Gini coefficient progressively increases from 0.048 (95% CI: 0.045, 0.051) at ages 15-29 to 0.147 (95% CI: 0.131, 0.163) at ages 80+. Second, the data reveal that health inequalities between SES groups (Concentration coefficients for income and education) tend to follow a similar pattern of divergence. Together these findings provide support for the accumulation hypothesis. A notable implication of the study's findings is that the level of health inequality increases when compensating for age-specific socio-economic differences in mortality. These selective effects of mortality should be considered in future research on health inequalities and the lifecourse.
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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 | 0.023 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".