Energy Deficit Required for Exercise-induced Improvements in Glycemia the Next Day
Bibliographic record
Abstract
PURPOSE: This study determined the impact of an exercise-induced energy deficit on postprandial and 24 h glycemic control the day after a session of exercise. METHODS: Fifteen healthy participants (m/f = 5/10, 27 ± 6 yr, body mass index = 24 ± 3 kg·m, peak oxygen consumption [V˙O2peak] = 36 ± 9 mL·kg·min) completed two separate 5-d experimental trials performed under "free-living" conditions. On day 1 of each trial, participants were fitted with a continuous glucose monitor and abstained from exercise. Day 2 served as a nonexercise control (NoEx). On day 3, participants exercised at 3:00 PM (65% V˙O2peak) until they expended 350 kcals (~45 min). The diet during both experimental trials was identical with the exception of meals after this exercise session. During one trial, the dinner after exercise did not replenish the 350 kcal expended during exercise, thereby establishing an exercise energy deficit (ExDEF). During the other experimental trial, the dinner after exercise contained an additional 350 kcal to compensate for the energy expended during exercise, and thereby maintained energy balance after exercise (ExBAL). Free-living glycemia was measured the day before exercise (NoEx) and the day after exercise under ExDEF and ExBAL conditions. RESULTS: The day after exercise, 3 h postprandial area under the curve was lower after breakfast in ExDEF compared with ExBAL (16.0 ± 1.8 vs 17.0 ± 1.6 mmol·L·h per 3 h, P = 0.01), but did not differ between groups after lunch (P = 0.24), dinner (P = 0.39), or evening snack (P = 0.45). Despite differences in the glycemic response to breakfast, 24 h glycemia did not differ between ExDEF and ExBAL (area under the curve = 128 ± 10 vs 131 ± 10 mmol·L·h per 24 h, respectively; P = 0.54). CONCLUSIONS: An exercise-induced energy deficit lowered the glycemic response to breakfast the next day-but this energy deficit did not impact total 24 h glycemia, the day after exercise in metabolically healthy adults.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".