Socioeconomic Status and Age Variations in Health-Related Quality of Life: Results From the National Health Measurement Study
Bibliographic record
Abstract
OBJECTIVES: We examine whether multiple health-related quality of life (HRQoL) measures are stratified by socioeconomic status (SES) and age in the United States. METHODS: Data are from the 2005/2006 National Health Measurement Study, a telephone survey of a nationally representative sample of U.S. adults. We plot mean HRQoL scores by SES within age groups. Regression analyses test whether education, income, and assets each have independent associations with three "preference-based" HRQoL measures and self-rated health (SRH). We test whether these associations vary by age. RESULTS: There are SES disparities in HRQoL and SRH among adults in the United States at all age groups. Income differentials in HRQoL are strong across current adult age cohorts, except the 75-89 age cohort. Education and assets have statistically significant but weaker associations with HRQoL. All three SES measures are associated with SRH (net of each other) at every age group. Those in the lowest income and education groups in the 35-44 age cohort have worse HRQoL and SRH than those in higher SES groups in the 65+ age cohort. DISCUSSION: Significant improvements in HRQoL at the population level will only be possible if we improve the HRQoL of people at the lowest end of the socioeconomic distribution.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".