The Role of Intermittent Fasting and Dieting on Cognition in Adult Population: A Systematic Review of the Randomized Controlled Trials
Bibliographic record
Abstract
OBJECTIVE: A healthy diet is a modifiable risk factor that may impact cognition. A unique type of diet may include intermittent fasting (IF), an eating pattern in which individuals go extended periods with little or no meal intake, intervening with periods of normal food intake. IF has multiple health benefits including maintenance of blood glucose levels, reduction of insulin levels, depletion or reduction of glycogen stores, mobilization of fatty acids, and generation of ketones. IF has shown neuroprotective effects as it may lead to increased neurogenesis in the hippocampus, which may contribute to cognitive resilience. Diets including IF were examined as lifestyle modifications in the prevention and management of cognitive decline. METHODS: A systematic literature search was conducted for randomized controlled trials (RCTs) which assessed the effect of dieting on cognitive functions in adults. RESULTS: Dietary Approaches to Stop Hypertension (DASH), low-glycemic diets, and caloric restriction have shown improvement in cognitive function; however, there was a negative impact on problem-solving in those with comorbid cardiovascular disease. There is also contradictory evidence that caloric restriction and diet alone may not be sufficient for the improvement of cognitive functions and that exercise may have better efficacy on cognition. CONCLUSION: IF is considered a safe intervention, and no adverse effects were found in the reviewed studies; however, evidence is limited as there were only 9 low-quality RCTs that assessed the impact of IF on cognition. DASH, low-glycemic diets, and exercise may have effective roles in the management and prevention of cognitive decline, although further research is needed.
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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 | 0.013 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".