The Effects of Diet on the Proportion of Intramuscular Fat in Human Muscle: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: There is an increasing trend in the consumption of poor-quality diets worldwide, contributing to the increase of non-communicable diseases. Diet directly influences physiological composition and subsequently physical health. Studies have shown that dietary macronutrient and energy content can influence the proportion of intramuscular fat (IMF), which mediates various metabolic and endocrine dysfunction. The purpose of this systematic review was to identify evidence in the literature assessing the association between different dietary interventions on the proportion of IMF in humans. METHODS: Three medical databases were investigated (Medline, EMBASE, and Cochrane) to identify studies assessing changes in IMF after dietary interventions. The primary outcome measure was the change in IMF proportions after a dietary intervention. The effects of high-fat, high-carbohydrate, low-calorie, and starvation diets were assessed qualitatively. A meta-analysis assessing the effect of high-fat diets was conducted. Follow-up sensitivity and subgroup analyses were also conducted. RESULTS: = 0.003). Diets with an increased proportion of carbohydrates decreased IMF proportions; however, increasing caloric intake with carbohydrates increased IMF. Starvation diets increased IMF stores, and hypocaloric diets did not result in any IMF proportion changes. CONCLUSION: This systematic review suggests that high-fat diets and diets with caloric intake increased above the amount required to maintain BMI with carbohydrates, and short-term starvation diets are associated with increases in IMF content. Further studies are needed to assess the effects of macronutrient combinations on IMF and the influence of diet-induced IMF alterations on health outcomes. In addition, IMF poses a possibly effective clinical marker of health.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.030 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".