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. 2025 Jan 22;8(1):e70373.
doi: 10.1002/hsr2.70373. eCollection 2025 Jan.

Common Dietary Patterns Among Female Employees Participating in the Persian Cohort Study (Mashhad) and Their Relationship With Metabolic Syndrome

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Common Dietary Patterns Among Female Employees Participating in the Persian Cohort Study (Mashhad) and Their Relationship With Metabolic Syndrome

Fatemeh Davoudi Dastenaie et al. Health Sci Rep. .

Abstract

Background: The protective effect of a healthy diet against chronic diseases has been confirmed in several primary studies. This study identifies the dominant food patterns using factor analysis and determining its relationship with metabolic syndrome in female employees participating in the Persian cohort study.

Methods: Female participants with metabolic syndrome (based on the National Cholesterol Education Program (NCEP ATP III) were studied using a cross-sectional design. Demographic, clinical and anthropometric information of the subjects were analyzed after checking the inclusion and exclusion criteria. Also, dietary intake based on the food frequency questionnaire (FFQ) was extracted from the participants' records.

Results: Waist circumference and HDL were significantly correlated with the healthy food pattern (p < 0.05). In the unadjusted model, a significant relationship was observed between healthy food patterns and low HDL (p = 0.035, OR = 0.674, 95% CI for OR: 0.467-0.973). After adjusting for confounding factors, a significant relationship was observed between low HDL and the third and fourth quartiles of healthy food pattern (p < 0.001, OR = 420, 95% CI for OR: 0.257-0.684, and p < 0.001, OR = 0.294, 95% CI for OR: 0.148-0.585, respectively), indicating that being in the third and fourth quartiles of dietary health was associated with 58% and 70.6% decreased risk of low HDL, respectively.

Conclusions: The results indicated that only healthy dietary patterns could have a preventive role against low HDL criterion of the metabolic syndrome among women.

Keywords: dietary patterns; factor analysis; metabolic syndrome; statistical; women.

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