Physical activity, energy intake, and obesity prevalence among urban and rural schoolchildren aged 11–12 years in Japan
Bibliographic record
Abstract
The prevalence of childhood overweight and obesity has been shown to differ among regions, including rural-urban regional differences within nations. This study obtained simultaneous accelerometry-derived physical activity, 24 h activity, and food records to clarify the potential contributing factors to rural-urban differences in childhood overweight and obesity in Japan. Sixth-grade children (n = 227, 11-12 years old) from two urban elementary schools in Kyoto and four rural elementary schools in Tohoku participated in the study. The children were instructed to wear a pedometer that included a uniaxial accelerometer and, assisted by their parents, keep minute-by-minute 24 h activity and food records. For 12 children, the total energy expenditure was measured by the doubly labeled water method that was used to correct the Lifecorder-predicted activity energy expenditure and physical activity level. The overweight and obesity prevalence was significantly higher in rural than in urban children. The number of steps per day, activity energy expenditure, physical activity level, and duration of walking to school were significantly lower in rural than in urban children. In contrast, the reported energy intake did not differ significantly between the regions. The physical activity and duration of the walk to school were significantly correlated with body mass index. Rural children had a higher prevalence of overweight and obesity, and this may be at least partly caused by lower physical activity, especially less time spent walking to school, than urban children.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".