Association Between Dietary Total Antioxidant Capacity and Diet Quality in Adults
Bibliographic record
Abstract
Background: Diet quality is a major contributor to human health. In addition, antioxidants have a great contribution to several chronic conditions. The purpose of this study was to evaluate if dietary total antioxidant capacity (TAC) can be considered as a measure of diet quality in a Middle Eastern country. Methods: In this cross-sectional study on 6,724 Iranian adults, we used a validated food frequency questionnaire (FFQ) to assess dietary intakes. Data derived from the FFQ was used to calculate dietary TAC and well-known diet quality scores including alternate healthy eating index (AHEI) and dietary diversity score (DDS). Dietary TAC was calculated based on the ferric reducing-antioxidant power (FRAP) values reported in earlier publications. AHEI and DDS have also been constructed based on previous publications. Cross-classification was used to examine the agreement between these measures. Results: < 0.001) compared with those in the lowest tertile. Participants' distribution on the basis of the cross-classification analysis indicated that the classifications were in exact agreement for 42.6%, within an adjacent tertile for 33.05%, and in gross misclassification for 20% of individuals. When this was examined between dietary TAC and DDS, we found that exact agreement in the classifications was for 59.2% of participants. Notably, a very low proportion of gross misclassification was seen in this regard such that only 6% of participants were classified in the opposing tertiles, indicating additional support for a good agreement. Conclusion: We found that dietary TAC might be considered as a proper measure for the assessment of diet quality because it was well correlated with well-known measures of diet quality including DDS and AHEI scores.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".