Physical, Psychological, Cognitive and Social Frailty Domains in Community-Dwelling Adults Aged 45–85: a Cross-sectional Analysis of the Canadian Longitudinal Study on Aging (CLSA)
Bibliographic record
Abstract
Background: Reported estimates of frailty prevalence vary considerably. At least partially attributable to differences in the conceptualization of frailty used, a better understanding of the inter-relationships among frailty domains could clarify contributors to the noted heterogeneity. Methods: A global frailty index (FI) created from baseline data on 30,097 Canadian Longitudinal Study on Aging comprehensive cohort participants was used to define physical, psychological, cognitive, and social domain-specific FIs. These were divided into quintiles with the highest 20% (Q5) representing the frailest participants. Logistic regression was used to estimate the associations between age group and biological sex with domain-specific FIs in unadjusted and adjusted (income, smoking status, nutritional risk, physical activity, social participation, interaction between sex and age group) models. The association between Q5 membership among the frailty domains was estimated using polychoric correlation coefficients. Results: <.001 for social. Polychoric correlations were highest between the psychological/physical and psychological/social domains, and decreased with increasing age for all combinations. Conclusion: We found that domain-specific frailty prevalences differed by age group and sex with low associations among frailty domains, particularly at older ages. Understanding the evolution of these findings could be instrumental in developing tailored interventions to prevent frailty or modify its trajectory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| 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".