Unlocking the power of synergy: High-intensity functional training and early time-restricted eating for transformative changes in body composition and cardiometabolic health in inactive women with obesity
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to examine the long-term effects of time-restricted eating (TRE), with or without high intensity functional training (HIFT), on body composition and cardiometabolic biomarkers among inactive women with obesity. METHODS: Sixty-four women (BMI = 35.03 ± 3.8 kg/m2; age = 32.1 ± 10 years) were randomly allocated to either: (1) TRE (≤8-h daily eating window, with ad libitum energy intake) group; (2) HIFT (3 sessions/week) group; or (3) TRE combined with HIFT (TRE-HIFT) group. The interventions lasted 12 weeks with a pre-post measurement design. A HIFT session consists of 8 sets of multiple functional exercises with self-selected intensity (20 or 30s work/10s rest). RESULTS: TRE-HIFT showed a greater decrease of waist and hip circumferences and fat mass compared to TRE (p = 0.02, p = 0.02 and p<0.01; respectively) and HIFT (p = 0.012, p = 0.028 and p<0.001; respectively). Weight and BMI decreased in TRE-HIFT compared to HIFT group (p<0.001; for both). Fat-free mass was lower in TRE compared to both HIFT and TRE-HIFT groups (p<0.01 and p<0.001; respectively). Total cholesterol, triglyceride, insulin, and HOMA-IR decreased in TRE-HIFT compared to both TRE (p<0.001, p<0.01, p = 0.015 and p<0.01; respectively) and HIFT (p<0.001, p = 0.02, p<0.01 and p<0.001; respectively) groups. Glucose level decreased in TRE-HIFT compared to HIFT (p<0.01). Systolic blood pressure decreased significantly in both TRE-HIFT and HIFT groups compared to TRE group (p = 0.04 and p = 0.02; respectively). CONCLUSION: In inactive women with obesity, combining TRE with HIFT can be a good strategy to induce superior effects on body composition, lipid profile and glucose regulation compared with either diet or exercise intervention alone. TRIAL REGISTRATION: Clinical Trials Number: PACTR202301674821174.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".