Relationships between physical activity and perceived qualities of life in old age. Results of the SNAC study
Bibliographic record
Abstract
OBJECTIVES: The aim of the present study was to investigate the relationships of different types of quality of life to strenuous and light physical activity in old age. METHODS: The Swedish SNAC-Blekinge baseline database, consisting of data on 585 men and 817 women 60-96 years of age, was utilized. The independent variables were light and strenuous physical activity. Four dependent variables concerned with various quality of life components were employed (well-being, engagement, emotional support and social anchorage). Age, gender, functional ability and co-morbidity were included as possible confounders. Non-parametric bivariate and multivariate statistical tests were performed. RESULTS: Correlations suggested there to generally be a positive relationship between physical activity and quality of life. Multivariate logistic regression analyses controlling for possible confounders showed light physical activity to increase the odds of experiencing well-being, engagement and social anchorage, whereas strenuous physical activity increased the odds of experiencing engagement and emotional support. Thus, light physical activity and strenuous physical activity differed in their relation to quality of life generally. CONCLUSIONS: The results indicate that physical activity has a salutogenic effect by enhancing the quality of life, and it can be assumed to be connected to quality of life by generating pleasure and relaxation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".