The effect of consuming low- versus high-glycemic index meals after exercise on postprandial blood lipid response following a next-day high-fat meal
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Exercise performed shortly before (that is, within half a day of) a high-fat meal is beneficial for stimulating fat oxidation after the meal and reducing postprandial triglycerides (TG). This benefit of exercise is unfortunately negated if the after-exercise food choice to replace the calories expended during exercise is one containing high-glycemic index (HGI) carbohydrates. We determined the effect of consuming low-glycemic index (LGI) carbohydrates after an exercise session on fat oxidation and TG after a subsequent high-fat meal. SUBJECTS/METHODS: Using a randomized, counterbalanced crossover design, 23 overweight or obese individuals (body mass index ⩾25 kg m(-2)) performed: walking exercise (90 min) at 1800 h followed by no meal (EX); exercise followed by a meal with LGI carbohydrates (that is, lentils, EX-LGI); exercise followed by a meal with HGI carbohydrates (that is, instant potatoes, white bread, EX-HGI); and a control condition with no exercise or meal. After a 10-h overnight fast, participants were given a standardized high-fat meal. Fat oxidation was estimated before and for 6 h after this meal from respiratory gas measures and TG determined from blood samples. RESULTS: Fat oxidation (mean±s.d.) was higher with EX (6.9±1.7 g h(-1)) than EX-HGI (6.3±1.6 g h(-1); P=0.007) and Control (5.9±1.7 g h(-1); P=0.00002), and EX-LGI (6.6±1.7 g h(-1)) was higher than Control (P=0.002). TG total area under the curve was 18-32% lower with EX and EX-LGI compared with control (P=0.0005 and P=0.0001, respectively) and EX-HGI (P=0.05 and P=0.021, respectively). CONCLUSIONS: A meal containing HGI carbohydrates consumed after an evening exercise session cancels the beneficial effect of exercise for stimulating fat oxidation and lowering TG after a subsequent high-fat meal, whereas consuming a post-exercise meal with LGI carbohydrates retains the positive effect of exercise.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".