Enjoyment of life and declining physical function at older ages: a longitudinal cohort study
Bibliographic record
Abstract
BACKGROUND: Positive affective well-being (i.e., feelings of happiness and enjoyment) has been associated with longer survival and reduced incidence of serious illness. Our objective was to discover whether enjoyment of life also predicted a reduced risk of functional impairment over an 8-year period in a large population sample. METHODS: We carried out a prospective analysis involving 3199 men and women aged 60 years or older from the English Longitudinal Study of Ageing. Enjoyment of life was assessed by questionnaire. Outcomes were impairment in 2 or more activities of daily living and changes in gait speed on a walking test. Covariates included sociodemographic factors, baseline health, depressive symptoms, impairment of mobility and health behaviours. RESULTS: Two or more impaired activities of daily living developed among 4.4%, 11.7% and 16.8% of participants in the high, medium and low enjoyment-of-life tertiles, respectively. After adjustment for covariates, the odds of impaired activities of daily living developing were 1.83 (95% confidence interval 1.13-2.96) in the low compared with high tertile. Gait speed after 8 years was also related to baseline enjoyment of life after adjustment for gait speed and other covariates at baseline (p < 0.001). We obtained similar results when we limited analyses to participants younger than 70 years at baseline. INTERPRETATION: This is an observational study, so causal conclusions cannot be drawn. But our results provide evidence that reduced enjoyment of life may be related to the future disability and mobility of older people.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".