Association of dietary patterns with serum vitamin D concentration among Iranian adults with abdominal obesity
Bibliographic record
Abstract
Introduction Vitamin D is obtained from dermal synthesis and dietary sources. The serum concentration of 25-hydroxyvitamin D [25(OH)D], may be used to evaluate vitamin D status, and this has been related to different dietary patterns (DPs) in previous studies. The bioavailability of vitamin D may be affected by adiposity. We aimed to investigate the relationship between dietary patterns and serum 25(OH)D in an Iranian population sample with abdominal obesity. Methods This cross-sectional study was undertaken in 215 adults who were 30–50 years old, and comprised students and employees of Mashhad University of Medical Sciences (MUMS), who had abdominal obesity. Serum 25(OH)D was measured using an enzyme-linked immunoassay method. A 65-item validated food frequency questionnaire (FFQ) and a principal components factor analysis (PCA) method were used to determine major dietary patterns. Results Two major dietary patterns were identified among the study population using PCA, and were termed "healthy" and "unhealthy". The healthy dietary pattern was characterized by a high intake of fruits, green leafy vegetables, other vegetables, honey, dairy products, olive oil, nuts, poultry, legumes, and soup and low intake of sugar, tea and solid fats. An unhealthy dietary pattern was characterized by high consumption of carbonated beverages, processed meat, fast foods, snacks, mayonnaise, seafood, red meat, refined grains, pickled foods, coffee, mineral water, potato, liquid fats, and egg. Serum concentrations of 25(OH)D were directly associated with adherence to the healthy dietary pattern (r: 0.170, p <0.05); though, there was no association between unhealthy pattern and serum 25(OH)D level. Conclusion Serum 25(OH)D level was significantly associated with adherence to a healthy dietary pattern in a sample of Iranian adults in Mashhad city, Iran.
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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 | 0.001 | 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".