Aerobic Fitness Indices of Children Differed Not by Body Weight Status but by Level of Engagement in Physical Activity
Bibliographic record
Abstract
BACKGROUND: Moderate-to-vigorous physical activity (MVPA) improves aerobic fitness in children, which is usually assessed by maximal oxygen consumption. However, other indices of aerobic fitness have been understudied. OBJECTIVE: To compare net oxygen (VO2net), net energy consumption (Enet), net mechanical efficiency (MEnet), and lipid oxidation rate in active and inactive children across body weight statuses. DESIGN: The sample included normal-weight, overweight, and obese children of whom 44 are active (≥30 min of MVPA/d) and 41 are inactive (<30 min of MVPA/d). VO2net, Enet, MEnet and lipid oxidation rate were determined during an incremental maximal cycling test. RESULTS: Active obese participants had significantly lower values of VO2net and Enet and higher MEnet than inactive obese participants at all load stages. In addition, active obese participants showed a significantly higher lipid oxidation rate compared with inactive obese and active overweight and normal-weight participants. VO2net, Enet, and MEnet were similar across active children, regardless of body weight status. CONCLUSIONS: Thirty minutes or more of MVPA per day is associated with a potentiation of aerobic fitness indicators in obese prepubertal children. Moreover, the indices of aerobic fitness of inactive obese children are significantly different from those of active obese and nonobese ones.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".