Low dietary magnesium and fiber intakes among women with metabolic syndrome in Kuwait
Bibliographic record
Abstract
Introduction Metabolic syndrome (MetS) is a growing health concern among Kuwaiti women. Dietary magnesium and fiber have been implicated in reducing the risk of MetS; however, their specific effects on this population remain underexplored. This study aimed to investigate the association of dietary magnesium and fiber intake with the prevalence of MetS and its components among women in Kuwait. Methods This study included 170 women aged 18–65 (years) recruited from AL-Adan Hospital, Mubarak Hospital, and Riqqa Polyclinic. Data were collected using a modified Semi-Quantitative Food Frequency Questionnaire (SFFQ) to assess dietary intake, and biochemical measurements were performed to evaluate serum magnesium and other metabolic markers. MetS was diagnosed according to International Diabetes Federation (IDF) and Adult Treatment Panel III (ATP III) criteria. Statistical analyses included Mann–Whitney U -tests, chi-square tests, Spearman correlations, logistic and linear regression models, and Cohen’s kappa statistics. Results The prevalence of MetS was 24 and 18% based on the IDF and ATP III criteria, respectively. Women with MetS had significantly lower dietary magnesium and fiber intakes than those in women without MetS ( p < 0.001). A strong positive correlation was found among dietary magnesium intake, fiber intake, and serum magnesium levels ( r = 0.957, p < 0.001 for magnesium; r = 0.917, p < 0.001 for fiber). Increased dietary magnesium and fiber intakes were linked to reduced odds of developing MetS and its components, except for blood pressure measurements. Cohen’s kappa demonstrated a strong agreement ( K = 0.70, p < 0.001) between dietary and serum magnesium inadequacy. Conclusion Increased dietary intakes of magnesium and fiber are associated with reduced odds of developing MetS among Kuwaiti women. These findings support the promotion of magnesium- and fiber-rich diets as preventive strategies against MetS.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".