The economics of physical activity programs : evidence from Saskatchewan older adults
Bibliographic record
Abstract
Chronic diseases place a substantial economic burden on the health care system. Physical inactivity, poor diet and smoking are considered to be the main causes of high rates of chronic disease. Evidence clearly supports the positive influence of physical activity on health determinants, other health outcomes and quality of life. This implies that an increase in physical activity improves general health status and has the potential to reduce utilization of expensive healthcare services and disability days. Earlier studies show that physical activity programs would be an effective way of providing preventive care for people with chronic conditions. However studies that relate physical activity programs to health care utilization are limited in economics literature.The aim of this paper is to examine the impact of physical activity programs on healthcare utilization. From 2002 to 2003, adults over the age of 50 years, in a mid-size Canadian city, presenting with excess weight, type 2 diabetes, hypertension, hyperlipidemia or osteoarthritis were recruited. Following a screening process, eligible participants were randomly assigned to one of two programs: a class-based structured program or a home-based unstructured program. Validated questionnaires related to health status and quality of life were completed and physical tests were carried out at baseline, 3, 6, 12 months and 24 months after the program initiation. In addition participants’ use of physician and hospital services and pharmaceutical expenditures were accessed through their administrative data files for three years, one year before and two years after the intervention. Using administrative data from Sask Health and individual level survey data the effects of physical activity programs on health care utilization were estimated. The results showed that structured physical activity program can reduce annual physician costs significantly. The exponential effect of aging was found to be significant on hospital utilization, and the number of comorbidities was found to be significant on prescription drug utilization.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".