Does exercise training affect resting metabolic rate in adolescents with obesity?
Bibliographic record
Abstract
We evaluated the hypothesis that resistance exercise training performed alone or in combination with aerobic exercise training would increase resting metabolic rate (RMR) relative to aerobic-only and nonexercising control groups. Postpubertal adolescents (N = 304) aged 14-18 years with obesity (body mass index (BMI) ≥ 95th percentile) or overweight (BMI ≥ 85th percentile + additional diabetes risk factor(s)) were randomized to 4 groups for 22 weeks: Aerobic exercise training, Resistance exercise training, Combined aerobic and resistance exercise training, or Control. All participants received dietary counselling targeting a daily energy deficit of 250 kcal. RMR was measured by indirect calorimetry and body composition by magnetic resonance imaging. There was no significant change in RMR in any group, in spite of significant within-group increases in fat-free mass in the Aerobic, Resistance, and Combined exercise training groups. RMR at baseline and 6 months were Aerobic: 1972 ± 38 and 1990 ± 41; Resistance: 2024 ± 37 and 1992 ± 41; Combined: 2023 ± 38 and 1995 ± 38; Control: 2075 ± 38 and 2073 ± 39 kcal/day (p > 0.05). There were no between-group differences in RMR after adjustment for total body weight or fat-free mass between groups over time. Per-protocol analyses including only participants with ≥70% adherence, and analyses stratified by sex, also showed no within- or between-group differences in RMR. In conclusion, despite an increase in fat-free mass in all exercise groups, 6 months of aerobic, resistance, or combined training with modest dietary restriction did not increase RMR compared with diet only in adolescents with obesity.
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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 | 0.000 | 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) | 0.001 | 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".