Adherence to a DASH-Style Diet in Relation to Stroke: A Case-Control Study
Bibliographic record
Abstract
BACKGROUND: Despite the growing body of evidence from Western societies on the association between dietary patterns and stroke, limited data are available in this regard from developing countries. OBJECTIVE: This study was conducted to examine the association between adherence to the Dietary Approaches to Stop Hypertension (DASH) diet and risk of stroke among the Iranian population. METHODS: This hospital-based case-control study included 194 stroke patients and 194 controls and was conducted at the Alzahra University Hospital, Isfahan, Iran. The cases were stroke patients who were hospitalized in the neurology ward of the Alzahra University Hospital. Controls were randomly selected from among hospitalized patients in the orthopedic or surgical wards of this center. A validated food frequency questionnaire (FFQ) was used to assess the patients' usual dietary intake. We constructed the DASH diet score based on food and nutrients emphasized or minimized in the DASH diet. RESULTS: The prevalence of stroke among those in the top quartile of the DASH diet score was 40%, which was 15% lower than among those in the bottom quartile; this difference was marginally significant (p = 0.10). After controlling for age, sex, and total energy intake, adherence to the DASH diet was inversely associated with the risk of stroke (OR: 0.52; 95% CI: 0.28; 0.98). These associations remained significant even after additionally controlling for physical activity, smoking, hypertension, and diabetes, such that individuals in the highest quartile of the DASH diet score had a 58% lower risk of stroke than those in the lowest category (OR: 0.48; 95% CI: 0.24, 0.96). However, after further adjustment for body mass index (BMI), the association disappeared (OR: 0.62; 95% CI: 0.29, 1.31), indicating an obesity-dependent association. CONCLUSION: We found an inverse relationship between the DASH-style diet and prevalence of stroke. Prospective studies are needed to confirm 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".