Effect of an Acute High Carbohydrate Diet on Body Composition Using DXA in Young Men
Bibliographic record
Abstract
AIM: The aim of this study is to investigate the effect of a 3-day high-carbohydrate diet (≥75% of total calories) on body composition using dual-energy X-ray absorptiometry (DXA). METHODS: Twenty non-obese young men (age 22.7 ± 2.6 years, BMI 23.5 ± 2.1 kg/m(2)) completed the study. Two DXA tests were performed for the measurement of total body weight, body mass index (BMI), body fat percentage as well as total, appendicular and central lean body mass (LBM) before and after a high-carbohydrate diet for 3 days. In addition, the participants completed a food diary during the 3-day high-carbohydrate diet to determine the mean percentage of carbohydrates consumed from total kilocalories. RESULTS: The mean percentage of carbohydrate intake over 3 days was 83.7 ± 8.4%. Our results showed a significant increase in total body weight, BMI as well as total and appendicular LBM after the high-carbohydrate diet (p < 0.01). In addition, we observed a strong tendency for lower body fat percentage values after the intervention (p = 0.05). No significant difference was observed for central LBM. CONCLUSIONS: These results indicate that the effect of an acute high carbohydrate diet seems to affect body composition values using DXA, such as total LBM. This study may lead to the need of standardizing a diet prior to using DXA.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".