Effects of high-intensity interval training and nutrition advice on cardiometabolic markers and aerobic fitness in adolescent girls with obesity
Bibliographic record
Abstract
The aim of the study was to compare the effects of high-intensity interval training (HIIT) and nutrition advice on cardiometabolic biomarkers, hormonal parameters, and cardiorespiratory fitness in adolescent girls with obesity. Adolescent girls with obesity (n = 44, aged 13–19 years) were randomized into a 12-week intervention as follows: (i) dietary advice and HIIT (n = 22), and (ii) dietary advice only (n = 22). The concentration of biomarkers of inflammation, biochemical and hormonal testing, oral glucose tolerance test, cardiorespiratory fitness, physical activity levels, and nutrition were assessed. After a 3-month intervention, the diet+HIIT group significantly increased insulin sensitivity index (–0.34 ± 1.52 vs. 1.05 ± 3.21; p = 0.001) and work load (0.6 ± 11.3 W vs. 14.6 ± 20.2 W; p = 0.024) and decreased glucose area under the curve (–0.29 ± 4.69 vs. −0.98 ± 4.06; p = 0.040), insulin area under the curve (−9.65 ± 117.9 vs. −98.7 ± 201.8; p = 0.003), and high-sensitivity C-reactive protein (hs-CRP) (0.12 ± 1.92 mg/L vs. −1.47 ± 3.67 mg/L; p = 0.039) in comparison with the diet group. Regarding within-group changes, both groups had significant improvements in body mass index (BMI), BMI-standard deviation score, body fat percentage, and systolic blood pressure. Positive impact on waist circumference, waist circumference/height ratio, diastolic blood pressure, hs-CRP, work load, maximal heart rate, and resting heart rate was observed only after the diet+HIIT intervention. No significant change was noted in peak oxygen uptake, lipid profile, and hormonal parameters between groups after intervention. Novelty HIIT and nutrition advice increased insulin sensitivity and decreased BMI, body fat, systolic blood pressure, and diastolic blood pressure. Nutrition advice decreased BMI, body fat, and systolic blood pressure in adolescent girls 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 | 0.000 | 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) | 0.002 | 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".