Adherence to Alternative Healthy Eating Index (AHEI-2010) is not associated with risk of stroke in Iranian adults: A case-control study
Bibliographic record
Abstract
Abstract. Background: Stroke is a major global health problem that contributes to a significant burden of morbidity and mortality. The association of several foods and nutrients with stroke has been well-established. However, the effect of the whole diet on stroke is poorly understood. In this work, we aimed to examine the association between the quality of whole diet, as measured using Alternate Healthy Eating Index-2010 (AHEI-2010), and risk of stroke in Iranian adults. Methods: In this hospital-based case-control study, 193 stroke patients (diagnosed based on clinical and brain CT findings) and 193 controls with no history of cerebrovascular diseases or neurologic disorders were included. The participants’ dietary intakes were examined using a validated 168-item semi-quantitative food frequency questionnaire. AHEI-2010 was constructed based on earlier studies. Participants were classified according to tertiles of AHEI-2010 scores and multivariate logistic regression was used to evaluate the association between whole diet quality and risk of stroke. Results: Individuals with greater adherence to AHEI-2010 had a higher intake of fruits, vegetables, nuts and legumes, whole grains and carbohydrate, and a lower intake of trans-fatty acids, sugar-sweetened beverages, total energy and fat (P < 0.05). After adjusting for potential confounders, adherence to AHEI-2010 was not significantly associated with a reduced risk of stroke (OR: 0.92; 95% CI: 0.56–1.51). Conclusion: We found that adherence to AHEI-2010 was not associated with risk of stroke in Iranian adults. Further prospective studies are warranted to validate this finding and clarify the relationship between whole diet and stroke.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".