Fasting Before Evening Exercise Reduces Net Energy Intake and Increases Fat Oxidation, but Impairs Performance in Healthy Males and Females
Bibliographic record
Abstract
Acute morning fasted exercise may create a greater negative 24-hr energy balance than the same exercise performed after a meal, but research exploring fasted evening exercise is limited. This study assessed the effects of 7-hr fasting before evening exercise on energy intake, metabolism, and performance. Sixteen healthy males and females (n = 8 each) completed two randomized, counterbalanced trials. Participants consumed a standardized breakfast (08:30) and lunch (11:30). Two hours before exercise (16:30), participants consumed a meal (543 ± 86 kcal; FED) or remained fasted (FAST). Exercise involved 30-min cycling (∼60% VO2peak) and a 15-min performance test (∼85% VO2peak; 18:30). Ad libitum energy intake was assessed 15 min postexercise. Subjective appetite was measured throughout. Energy intake was 99 ± 162 kcal greater postexercise (p < .05), but 443 ± 128 kcal lower over the day (p < .001) in FAST. Appetite was elevated between the preexercise meal and ad libitum meal in FAST (p < .001), with no further differences (p ≥ .458). Fat oxidation was greater (+3.25 ± 1.99 g), and carbohydrate oxidation was lower (-9.16 ± 5.80 g) during exercise in FAST (p < .001). Exercise performance was 3.8% lower in FAST (153 ± 57 kJ vs. 159 ± 58 kJ, p < .05), with preexercise motivation, energy, readiness, and postexercise enjoyment also lower in FAST (p < .01). Fasted evening exercise reduced net energy intake and increased fat oxidation compared to exercise performed 2 hr after a meal. However, fasting also reduced voluntary performance, motivation, and exercise enjoyment. Future studies are needed to examine the long-term effects of this intervention as a weight management strategy.
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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) | 0.003 | 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".