Prevalence, Attributes, and Outcomes of Fitness and Frailty in Community-Dwelling Older Adults: Report From the Canadian Study of Health and Aging
Bibliographic record
Abstract
BACKGROUND: Frailty and fitness are important attributes of older persons, but population samples of their prevalence, attributes, and outcomes are limited. METHODS: The authors report data from the community-dwelling sample (n = 9008) of the Canadian Study of Health and Aging, a representative, 5-year prospective cohort study. Fitness and frailty were determined by self-reported exercise and function level and testing of cognition. RESULTS: Among the community-dwelling elderly population, 171 per 1000 were very fit and 12 per 1000 were very frail. Frailty increased with age, so that by age 85 years and older, 44 per 1000 were very frail. The risk for adverse health outcomes increased markedly with frailty: Compared with older adults who exercise, those who were moderately or severely frail had a relative risk for institutionalization of 8.6 (95% confidence interval, 4.9 to 15.2) and for death of 7.3 (95% confidence interval, 4.7 to 11.4). These risks persist after adjustments for age, sex, comorbid conditions, and poor self-rated health. At all ages, men reported higher levels of exercise and less frailty compared with women. Decreased fitness and increased frailty were also associated with poor self-ratings of health (42% in the most frail vs 7% in the most fit), more comorbid illnesses (6 vs 3), and more social isolation (34% vs 29%). CONCLUSIONS: Fitness and frailty form a continuum and predict survival. Exercise influences survival, even in old age. Relative fitness and frailty can be determined quickly in a clinical setting, are potentially useful markers of the risk for adverse health outcomes, and add value to traditional medical assessments that focus on diagnoses.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".