Physical activity as a mediator of the impact of chronic conditions on quality of life in older adults
Bibliographic record
Abstract
BACKGROUND: Chronic conditions could negatively affect the quality of life of older adults. This may be partially due to a relative lack of physical activity. We examined whether physical activity mediates the relationship between different chronic conditions and several health outcomes that are important to the quality of life of older adults. METHODS: The data were taken from the Canadian Community Health Survey (cycle 1.1), a cross-section survey completed in 2001. Only respondents who were 65 years or older were included in our study (N = 22,432). The Health Utilities Index Mark 3 (HUI3) was used to measure overall quality of life, and to measure selected health outcomes (dexterity, mobility, pain, cognition, and emotional wellbeing) that are considered to be of importance to the quality of life of older adults. Leisure-time physical activity was assessed by determining weekly energy expenditure (Kcal per week) based on the metabolic equivalents of self-reported leisure activities. Linear and logistic regression models were used to determine the mediating effect of leisure-time physical activity while controlling for demographic variables (age and sex), substance use (tobacco use and alcohol consumption), and obesity. RESULTS: Having a chronic condition was associated with a relative decrease in health utility scores and a relative increase in mobility limitations, dexterity problems, pain, emotional problems (i.e., decreased happiness), and cognitive limitations. These negative consequences could be partially attributed to a relative lack of physical activity in older adults with a chronic condition (14% mediation for the HUI3 score). The corresponding degree of mediation was 18% for mobility limitations, 5% for pain, and 13% for emotional wellbeing (statistically significant mediation was not observed for the other health attributes). These values varied with respect to the different chronic conditions examined in our study. CONCLUSION: Older adults with chronic conditions are less likely to engage in leisure-time physical activities of at least 1,000 Kcal per week, and this association partially accounts for some negative consequences of chronic conditions, including mobility limitations, pain, and emotional problems. These findings provide support for health promotion programs that facilitate or encourage increased leisure-time physical activity in older people with chronic conditions.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".