Prevalence and Factors Associated With Thriving in Older Adulthood: A 10-Year Population-Based Study
Bibliographic record
Abstract
BACKGROUND: Interest in the determinants of "successful aging" is growing. Nonetheless, successful aging remains ill defined, and its appropriate measurement is hotly contested. Most studies have focused on the absence of disability or deficits in physical performance as outcomes. The present study extends this research by using the Health Utilities Index Mark 3 (HUI3), a multidimensional measure of health status, to examine the maintenance of exceptionally good health among older participants in the Canadian National Population Health Survey (1994--2004). METHODS: The maintenance of exceptionally good health in old age was examined prospectively among 2432 individuals (65-85 years old at baseline) who met the inclusion criteria. The participants were classified into one of four health trajectories: thrivers (who maintained exceptional health with no or only mild disability), nonthrivers (who experienced a moderate or severe disability), the deceased, and the institutionalized. RESULTS: In 10 years of follow-up, 190 (8%) were thrivers (HUI3 score > or = 0.89 at all interviews), 1076 (47%) were nonthrivers, 893 (36%) died, and 273 (9%) were institutionalized. The maintenance of exceptionally good health among the elderly participants was related to younger age at baseline, socioeconomic status (higher income), psychosocial factors (including lower psychological distress), and behavioral factors (never smoked and moderate alcohol use). CONCLUSIONS: The maintenance of exceptionally good health in old age is related, at least in part, to modifiable lifestyle factors. However, elevated socioeconomic status also distinguishes those who are able to maintain exceptionally good health.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".