Nutrition and bipolar disorder: a systematic review
Bibliographic record
Abstract
INTRODUCTION: Individuals with bipolar disorder (BD) have higher rates of unhealthy lifestyles and risk for medical comorbidities Research currently suggests that dietary factors may play a role in the development of depression and anxiety. Therefore, nutritional approaches are potential strategies for the treatment of BD. The aim of this review is to summarize the available evidence on nutrition and BD. MATERIALS AND METHODS: The paper was developed based on PRISMA 2020 guidelines. The search was conducted in Sep-2021 using PubMed and Cochrane Library, augmented by manually checked references lists. The search found 986 studies, of which 47 were included, combined with 13 from reference lists, totaling 60 studies. RESULTS: There were 33 observational trials, of which 15 focused on fatty acids, 9 on micronutrients, 5 on specific foods, 4 on macro and micronutrients. The 27 interventional studies mainly focused on fatty acids, micronutrients and N-acetylcysteine (NAC). DISCUSSION: Dietary intake or supplementation of unsaturated fatty acids, mainly Omega-3 seems to be associated with improved BD symptoms, along with seafood, folic acid and zinc. Studies found variable, mainly non-significant impacts of creatine, carnitine, vitamin D, inositol or NAC supplementation on BD. There are promising results associated with Coenzyme Q10 (Coq10) and probiotics. Taken together, these preliminary findings suggest that dietetic approaches might be included as part of BD treatment. Also considering the high risk of metabolic disorders in individuals with BD, they should be encouraged to choose healthy dietary lifestyles, including daily intake of fruits, vegetables, seafood and whole grains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".