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Updated: Nov 30, 2025

Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome
Published on: September 27, 2024
Exploratory factor analysis of gender-based metabolic syndrome components: Results from the PERSIAN Guilan cohort
Mehrnaz Asgharnezhad1, Farahnaz Joukar2, Mohammadreza Naghipour1
1Gastrointestinal and Liver Diseases Research Center, Guilan University of Medical Sciences, Rasht, Iran.
Background:
One of the important issues related to metabolic syndrome is the underlying factor that remains controversial. The purpose of this study was estimating exploratory factor analysis (EFA) to reveal underlying factors that may explain the observed variants of metabolic syndrome (MetS) components in a population-based study.
Methods:
In this cross-sectional study, the target population consisted of 10,520 individuals aged 35-70 years from Phase 1 of the PERSIAN Guilan cohort study conducted between 2014 and 2017. Exploratory factor analysis (EFA) of components of the metabolic syndrome, including waist circumference (WC), systolic (SBP) and diastolic (DBP) blood pressure, triglyceride (TG), high-density lipoprotein (HDL) and fasting blood glucose (f-Glc) was performed across the population as well as by gender.
Results:
EFA results in the whole population based on eigen values > 1 showed two factors that explain 55.46% of the total variance. Taking factor loadings above 0.3, the first factor included systolic blood pressure, diastolic blood pressure, and waist circumference - called the blood pressure factor. Also, the second factor included triglycerides, negative-loaded HDL, and fasting blood glucose, which was named as lipid factor. In terms of gender, the first factor was similar to the whole population pattern, but in the second factor, in addition to the two components of blood lipids, waist size for men and in fasting blood glucose for women was launched.
Conclusion:
Hypertension and lipids were substantial factors, and obesity is an important factor in this study. Hypertension, having the highest factor load, can generally be a valuable screening parameter for cardiovascular and metabolic risk assessment.
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