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
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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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 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 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".