High Intensity Exercise: Can It Protect You from A Fast Food Diet?
Bibliographic record
Abstract
The purpose of this study was to assess the ability of high intensity exercise to counteract the deleterious effects of a fast food diet on the cardiometabolic profile of young healthy men. Fifteen men were subjected to an exclusive fast food diet from a popular fast food restaurant chain (three extra value meals/day + optional snack) for 14 consecutive days. Simultaneously, participants were asked to perform each day high intensity interval training (HIIT) (15 × 60 sec sprint intervals (~90% of maximal heart rate)) on a treadmill. Fast food diet and energy expenditure profiles of the participants during the intervention were assessed as well as body composition (DXA), cardiometabolic profile (lipid, hepatic enzymes, glycated hemoglobin, glucose, insulin, hsC-reactive protein (hsCRP) and blood pressure) and estimated maximal oxygen consumption (VO2 max) pre- and post-experiment. We found significant improvements for fat mass, lean body mass, estimated VO2 max, fasting glucose, serum lipoprotein(a) and hsCRP after the intervention (p < 0.05). HDL-cholesterol significantly decreased (p < 0.002), but the triglycerides/HDL-cholesterol ratio did not change. All other cardiometabolic variables measured remained stable, which includes the primary outcome: the HOMA index (pre: 1.83 ± 1.2 vs. post: 1.54 ± 0.7 values; p = 0.35). In conclusion, in large part, insulin resistance and the cardiometabolic profile of young healthy individuals seems to be protected by HIIT from a fast food diet.
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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 | 0.000 | 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".