Effects of high-intensity exercise training on body composition, abdominal fat loss, and cardiorespiratory fitness in middle-aged Korean females
Bibliographic record
Abstract
The primary purpose of this study was to investigate the effects of high-intensity exercise training under relatively equal energy expenditure on whole body fat and abdominal fat loss, and cardiorespiratory fitness. Twenty-two untrained middle-aged Korean females were randomized into one of the following groups: control, low-intensity training group (LI), and high-intensity training group (HI). Subjects completed 14 weeks of training at 50% maximal oxygen consumption (LI) or 70% maximal oxygen consumption (HI) with the volume of exercise equated relative to kilograms of body weight. Weekly exercise volumes were 13.5 METs⋅h/week for the first 4 weeks, 18 METs⋅h/week for next 5 weeks, and 22.5 METs⋅h/week for the final 5 weeks. Data were analyzed using 2-way repeated measures ANOVA with post hoc test, using Bonferroni's correction. HI showed significant reductions in fat mass (p < 0.05), total abdominal fat (p < 0.01), and subcutaneous abdominal fat (p < 0.01). LI reduced total abdominal fat (p < 0.05), but there were no other significant changes found in the control or LI groups. Maximal oxygen consumption was enhanced in both HI and LI with no significant group difference. High-density lipoprotein cholesterol increased significantly in HI (p < 0.05). IL-6, C-reactive protein, TNF-α, and other blood lipids were unaltered following training. Results indicate that high-intensity exercise training is more beneficial in whole body and abdominal fat loss; however, cardiorespiratory enhancement shows a dose-response relationship with weekly exercise volume. It is suggested that 14 weeks of aerobic exercise training at either high- or low-intensity is not sufficient enough to induce changes in levels of inflammatory proteins.
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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 | 0.000 |
| 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".