Adherence to low carbohydrate diet and prevalence of psychological disorders in adults
Bibliographic record
Abstract
BACKGROUND: Although individual macronutrients were studied in relation to mental health, no information exist about the association between adherence to low carbohydrate diet and psychological disorders. This study was conducted to investigate the association between adherence to a low carbohydrate diet and prevalence of psychological disorders among Iranian adults. METHODS: In this cross-sectional study on 3362 adult men and women, dietary intakes were examined by the use of a validated semi-quantitative food frequency questionnaire. Low carbohydrate diet (LCD) score was computed for each participant based on deciles of percentages of energy from macronutrients. Then the scores of carbohydrate, protein and fat intake for each participant were summed up to achieve the overall LCD score, which ranged from 3 (highest carbohydrate intake and lowest fat and protein intakes) to 30 (lowest carbohydrate intake and highest fat and protein intakes). Anxiety, depression, and psychological distress were assessed by validated Iranian versions of the Hospital Anxiety and Depression Scale and General Health Questionnaire-12. RESULTS: Prevalence of depression, anxiety and psychological distress in the whole population were 28.0, 13.3 and 22.6%, respectively. No significant differences were observed in the distribution of depression, anxiety and psychological distress across different quartiles of LCD score. After controlling for potential confounders, no significant association was seen between LCD score and prevalence of depression (OR for the highest vs. the lowest quartile of LCD score: (1.15; 95% CI: 0.93, 1.39). Consumption of LCD was not also associated with increased risk of anxiety (0.82; 95% CI: 0.59, 1.14) and psychological distress (0.92; 95% CI: 0.72, 1.16). These associations did not alter when the analyses were done stratified by gender or BMI status. CONCLUSION: Adherence to the low carbohydrate diet, which contains high amount of fat and proteins but low amounts of carbohydrates, was not associated with increased odds of psychological disorders including depression, anxiety and psychological distress. Given the cross-sectional nature of the study which cannot reflect causal relationships, longitudinal studies, focusing on types of macronutrients, are required to clarify this association.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".