Frailty differences across population characteristics associated with health inequality: a cross-sectional analysis of baseline data from the Canadian Longitudinal Study on Aging (CLSA)
Bibliographic record
Abstract
OBJECTIVE: To evaluate the pattern of frailty across several of social stratifiers associated with health inequalities. DESIGN, SETTING AND PARTICIPANTS: Cross-sectional baseline data on 51 338 community-living women and men aged 45-85 years from the population-based Canadian Longitudinal Study on Aging (collected from September 2011 to May 2015) were used in this study. PRIMARY OUTCOMES AND MEASURES: A Frailty Index (FI) was constructed using self-reported chronic conditions, psychological function and cognitive status and physical functioning variables. Social stratifiers were chosen based on the Pan-Canadian Health Inequalities Reporting Initiative, reflecting key health inequalities in Canada. Unadjusted and adjusted FIs and domain-specific FIs (based on chronic conditions, physical function, psychological/cognitive deficits) were examined across population strata. RESULTS: The overall mean FI was 0.13±0.08. It increased with age and was higher in women than men. Higher mean FIs were found among study participants with low income (0.20±0.10), who did not complete secondary education (0.17±0.09) or had low perceived social standing (0.18±0.10). Values did not differ by Canadian province of residence or urban/rural status. After simultaneously adjusting for population characteristics and other covariates, income explained the most heterogeneity in frailty, especially in younger age groups; similar patterns were found for men and women. The average frailty for people aged 45-54 in the lowest income group was greater than that for those aged 75-85 years. The heterogeneity in the FI among income groups was greatest for the psychological/cognitive domain. CONCLUSIONS: Our results suggest that especially in the younger age groups, psychological/cognitive deficits are most highly associated with both overall frailty levels and the gradient in frailty associated with income. If this is predictive of later increases in the other two domains (and overall frailty), it raises the question whether targeting mental health factors earlier in life might be an effective approach to mitigating frailty.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".