Trajectories of health-related quality of life by socio-economic status in a nationally representative Canadian cohort
Bibliographic record
Abstract
BACKGROUND: Mortality and morbidity have been shown to follow a 'social gradient' in Canada and many other countries around the world. Comparatively little, however, is known about whether ageing amplifies, diminishes or sustains socio-economic inequalities in health. METHODS: Growth curve analysis of seven cycles of the Canadian National Population Health Survey (n=13,682) for adults aged 20 and older at baseline (1994/95). The outcome of interest is the Health Utilities Index Mark 3, a measure of health-related quality of life (HRQL). Models include the deceased so as not to present overly optimistic HRQL values. Socio-economic position is measured separately by household-size-adjusted income and highest level of education attained. RESULTS: HRQL is consistently highest for the most affluent and the most highly educated men and women, and is lower, in turn, for middle and lower income and education groups. HRQL declines with age for both men and women. The rate of the decline in HRQL, however, was related neither to income nor to education for men, suggesting stability in the social gradient in HRQL over time for men. There was a sharper decline in HRQL for upper-middle and highest-income groups for women than for the poorest women. CONCLUSION: HRQL is graded by both income and education in Canadian men and women. The grading of HRQL by social position appears to be 'set' in early adulthood and is stable through mid- and later life.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".