Relationships between moderate vigorous physical activity, motor- and health-related fitness and motor skills in children Article DOI:
Bibliographic record
Abstract
BACKGROUND: Childhood is an important transitional period for the development of healthy physical activity (PA) behaviours, so it is important to understand its impact on a healthy lifestyle. AIM: This study aimed to determine the influences of sex, socioeconomic status (SES) and body composition (BC) on the relationships between PA, motor skills, motor- and health-related physical fitness in 5-8-year-olds. SETTING: Participants were a subsample consisting of 299 children (150 boys, 149 girls, mean age 6.83 ± 0.96 years) from the Exercise, Arterial Modulation and Nutrition in Youth South Africa study (ExAMIN Youth SA). METHODS: Anthropometric measures, health-related physical fitness (HRPF), motor-related physical fitness (MRPF), objectively measured PA and demographic information were determined. RESULTS: Only 66% achieved the recommended 60 min of daily moderate vigorous physical activity (MVPA) with 19% classified as having unhealthy body composition (11% overweight, 8% obese). Fat-free mass and SES revealed small-to-moderate influences on the relationship between MVPA, standing broad jump (SBJ; r = 0.32), predicted VO2max (r = 0.28) and beep levels (r = 0.22). For MRPF, the quality of running (r = 0.12) and balancing were associated with MVPA. Adjusting for sex, BC and SES in the relationship between PA with HRPF and MRPF, reductions in most correlations were observed. CONCLUSION: Moderate vigorous physical activity levels were positively associated with HRPF, MRPF and some motor skills in 5-8-year-olds. Socioeconomic status (lower parental income, employment and education negatively influenced the association between MVPA and fitness [beeps, SBJ, O2max]).Contribution: This study provides knowledge with regard to the use of accelerometer for baseline data for PA, MRPF, HRPF as well as motor skills in South African 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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".