A 15-Year Decline in Physical Fitness Among Children and Adolescents From the Macao Special Administrative Region (2005–2020)
Bibliographic record
Abstract
BACKGROUND: Monitoring temporal trends in physical fitness provides valuable insight into population health that can help identify current and future physical health. This study examined temporal trends in physical fitness among children and adolescents aged 6-18 from the Macao Special Administrative Region between 2005 and 2020. METHODS: Representative repeated cross-sectional physical fitness data were collected in 2005, 2010, 2015, and 2020 (n = 17,987). Body size and physical fitness were objectively measured. Trends in means were calculated using general linear models. Models were adjusted for sex, age, height, and weight. Trends in distributional characteristics were assessed as the ratio of the coefficients of variation and described visually. RESULTS: Despite an increase in body size, we found significant small to large body size adjusted decline in cardiorespiratory fitness (effect size [ES] = -0.27, -0.93) and small declines in reaction time (ES = -0.21, -0.38). Declines in other fitness components varied by age, with negligible to small declines in children's (aged 6-12 y) balance (ES = -0.15) and speed (ES = -0.25) and in adolescents' (aged 13-18 y) muscular power (ES = -0.17, -0.36). A small improvement was observed in adolescents' flexibility (ES = 0.24). Mixed trends were found in distributional variability for flexibility, along with differing trends in distributional asymmetry among fitness components. CONCLUSIONS: These findings underscore the need for targeted interventions to enhance fitness levels in the young Macao population. Addressing these trends is crucial for improving the current and future health outcomes of young people in the region.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".