The Relationship of Chronic Disease and Demographic Variables to Physical Activity in a Sample of Women Aged 65 to 79 Years
Bibliographic record
Abstract
This study explored the relationship between physical activity, marital status, income, education, and chronic disease in older women to determine which individuals are at risk of being inactive and to identify potential moderators of physical activity behavior. This was an analysis of cross-sectional data from a convenience sample of 271 community-dwelling women aged 65 to 79 years. Self-reported physical activity was measured using the Physical Activity Scale for the Elderly. Socio-demographic characteristics (including age, gender, marital status, education, employment, and income) and self-reported health were measured using previously validated instruments. To avoid seasonal variations in physical activity, data were collected during the summer months. Physical activity was negatively associated with age and the presence of cardio-respiratory disease and positively associated with income greater than $20,000 (p < 0.05). After controlling for other co-variates, no significant differences were observed in physical activity between married and unmarried individuals. Given the strong association between cardio-respiratory disease and income with physical activity, women 65 years of age and older in lower income brackets and suffering from these health conditions should be targeted for exercise counseling and support. Intervention research is needed to determine the most effective means to decrease inactivity among these women.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".