Association of dietary acid load and plant-based diet index with sleep, stress, anxiety and depression in diabetic women
Bibliographic record
Abstract
Diabetes is a common chronic disease with various complications. The present study was conducted to determine the association of plant-based diet index (PDI) and dietary acid load (DAL) with sleep status as well as mental health in type 2 diabetic women. In this cross-sectional study, a validated FFQ was used to assess dietary intakes of 230 diabetic patients. We created a whole PDI, healthful PDI (hPDI) and unhealthful PDI (uPDI). DAL was calculated based on potential renal acid load and net endogenous acid production method. The Pittsburgh Sleep Quality Index and twenty-one-item Depression, Anxiety and Stress Scale were used to assess sleep and mental health disorders, respectively. Participants in the top group of uPDI had greater risk of poor sleep (OR 6·47, 95 % CI 2·75, 15·24). However, patients who were in the top group of hPDI had a lower risk of sleep problems (OR 0·28, 95 % CI 0·13, 0·62). Participants in the top group of uPDI had greater risk of depression, anxiety and stress (OR 9·35, 95 % CI 3·96, 22·07; OR 4·74, 95 % CI 2·28, 9·85; OR 4·24, 95 % CI 2·14, 8·38, respectively). In conclusion, participants with higher DAL scores and patients who adhered to animal-based diets rather than plant-based diets were more likely to be poor sleepers and have mental health disorders.
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 | 0.000 | 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".