The International Prevalence Study on Physical Activity: results from 20 countries
Bibliographic record
Abstract
BACKGROUND: Physical activity (PA) is one of the most important factors for improving population health, but no standardised systems exist for international surveillance. The International Physical Activity Questionnaire (IPAQ) was developed for international surveillance. The purpose of this study was a comparative international study of population physical activity prevalence across 20 countries. METHODS: Between 2002-2004, a standardised protocol using IPAQ was used to assess PA participation in 20 countries [total N = 52,746, aged 18-65 years]. The median survey response rate was 61%. Physical activity levels were categorised as "low", "moderate" and "high". Age-adjusted prevalence estimates are presented by sex. RESULTS: The prevalence of "high PA" varied from 21-63%; in eight countries high PA was reported for over half of the adult population. The prevalence of "low PA" varied from 9% to 43%. Males more frequently reported high PA than females in 17 of 20 countries. The prevalence of low PA ranged from 7-41% among males, and 6-49% among females. Gender differences were noted, especially for younger adults, with males more active than females in most countries. Markedly lower physical activity prevalence (10% difference) with increasing age was noted in 11 of 19 countries for males, but only in three countries for women. The ways populations accumulated PA differed, with some reporting mostly vigorous intensity activities and others mostly walking. CONCLUSION: This study demonstrated the feasibility of international PA surveillance, and showed that IPAQ is an acceptable surveillance instrument, at least within countries. If assessment methods are used consistently over time, trend data will inform countries about the success of their efforts to promote physical activity.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".