Effect of HIIT versus MICT on body composition and energy intake in dietary restrained and unrestrained adolescents with obesity
Bibliographic record
Abstract
High-intensity interval training (HIIT) has been suggested as an effective alternative to traditional moderate-intensity continuous training (MICT) that can yield improvements in a variety of health outcomes. Yet, despite the urgent need to find effective strategies for the treatment of pediatric obesity, only a few studies have addressed the impact of HIIT on eating behaviors and body composition in this population. This study aimed to compare the effect of HIIT versus MICT on eating behaviors in adolescents with obesity and to assess if the participants’ baseline dietary status is associated with the success of the intervention. Forty-three adolescents with obesity were randomly assigned to a 16-week MICT or HIIT intervention. Body composition and 24-h ad libitum energy intake were assessed at baseline and at the end of the program. Restrained eating, emotional eating, and external eating were assessed using the Dutch Eating Behavior Questionnaire at baseline. Both interventions led to significant weight, body mass index (BMI), and fat mass percentage (FM%) reductions, with better improvements in FM% in the HIIT group; whereas 24-h ad libitum energy intake increased to a similar extent in both groups. HIIT provides better body composition improvements over MICT, despite a similar increase in energy intake. Restrained eaters experienced less weight loss and smaller BMI reduction compared with unrestrained eaters; higher baseline cognitively restrained adolescents showed a greater increase of their ad libitum energy intake. Novelty HIIT favors better body composition improvements compared with MICT. Both MICT and HIIT increased ad libitum energy intake in adolescents with obesity. Weight loss achievement is better among unrestrained eaters.
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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) | 0.001 | 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 | 0.001 |
| 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".