Current and past trends in physical activity in four OECD countries
Bibliographic record
Abstract
Physical inactivity and sedentary behaviours have been rising throughout the OECD in recent decades. Lack of physical activity and excessive sedentary behaviour are well-known risk factors for non-communicable diseases, such as heart diseases, stroke, diabetes, and osteoporosis. As such, reducing physical inactivity and sedentary behaviours and increasing daily physical activity has become a crucial public health issue. Using nationally representative time use surveys, this paper presents the trends in physical activity (PA) and sedentary behaviours over time, in Canada, France, Germany and the United States. A particular focus of this analysis is placed on sport activities. Men and women spend between 80 and 105 minutes daily in physical activities, with women spending more time in domestic physical activity, and men more time in sports. Participation in sport activities has been increasing over time, but no global trend for time spent in sports is visible; additionally, women are consistently less likely than men to report engagement in sport activities. Meanwhile, participation in active travel has been decreasing, displaying no overall trend for duration either. Education-based inequalities for sports participation are higher in men than in women, while income-based inequalities for sports are higher in women than in men. Men and women with a low level of income are more likely to report active travel in all countries. Additional MET (metabolic equivalent) hours spent in sports and non-sports leisure PA, domestic PA, and active travel are all associated with an increase in total PA, while work-related PA as well as other activities are associated with a decrease in total PA. At the individual level, an increase in time spent in all previously mentioned activities is associated with a decrease in total time spent in sedentary behaviours.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".