Physical fitness before and during the COVID-19 pandemic: Results of annual national physical fitness surveillance among 16,647,699 Japanese children and adolescents between 2013 and 2021
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Limited nationally representative evidence is available on temporal trends in physical fitness (PF) for children and adolescents during the coronavirus disease 2019 (COVID-19) pandemic. The primary aim was to examine the temporal trends in PF for Japanese children and adolescents before and during the COVID-19 pandemic. The secondary aim was to estimate the concurrent trends in body size (measured as body mass and height) and movement behaviors (exercise, screen, and sleep time). METHODS: Census PF data for children in Grade 5 (aged 10-11 years) and adolescents in Grade 8 (aged 13-14 years) were obtained for the years 2013-2021 from the National Survey of Physical Fitness, Athletic Performance, and Exercise Habits in Japan (n = 16,647,699). PF and body size were objectively measured, and movement behaviors were self-reported. Using sample-weighted linear regression, temporal trends in mean PF were calculated before the pandemic (2013-2019) and during the pandemic (2019-2021) with adjustments for age, sex, body size, and exercise time. RESULTS: When adjusted for age, sex, body size, and exercise time, there were significant declines in PF during the pandemic, with the largest declines observed in 20-m shuttle run (standardized (Cohen's) effect size (ES) = -0.109 per annum (p.a.)) and sit-ups performance (ES = -0.133 p.a.). The magnitude of the declines in 20-m shuttle run and sit-ups performances were 18- and 15-fold larger, respectively, than the improvements seen before the pandemic (2013-2019), after adjusting for age, sex, body size, and exercise time. During the pandemic, both body mass and screen time significantly increased, and exercise time decreased. CONCLUSION: Declines in 20-m shuttle run and sit-ups performances suggest corresponding declines in population health during the COVID-19 pandemic.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it