Estimation of the burden of disease averted by leisure center membership across Spain
Bibliographic record
Abstract
Introduction: Active behavior performed in leisure centers might help reduce the negative health impacts associated with physical inactivity. The disability-adjusted life years (DALYs) is a valuation technique to quantify lifetime disease burden including both non-fatal health consequences of diseases and premature death. Method: This study estimated the role of the largest leisure center in Spain (GO fit) in averting the burden of five diseases and premature deaths during 2017 as a consequence of the physical activity and exercise programs and services delivered. A preferred model was implemented with a static picture of the burden of disease, without including discounting rate and age-weights. Sensitivity analyses were conducted considering these two variables. Results: The estimation was that GO fit services could have averted a total of 1,165.74 DALYs (10.96 DALYs per 1,000 members) coming from type 2 diabetes (22.62 DALYs), colorectal cancer (81.16 DALYs), breast cancer (48.72 DALYs), stroke (206.15 DALYs), and coronary heart disease (807.10 DALYs). Discussion: These results indicate that programs and services delivered in physical activity leisure centers could help the public health agenda aim of promoting a more active lifestyle and reducing the burden of disease associated with physical inactivity.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".