Role of gender in explaining metabolic syndrome risk factors in an Iranian rural population using structural equation modelling

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Authors

Nouri‑Keshtkar, Marjan
Shahrokhabadi, Mohadeseh Shojaei
Ghaheri, Azadeh
Hosseini, Roya
Ketabi, Hassan
Farjam, Mojtaba
Chen, Ding-Geng (Din)
Rezaeian, Mehdi
Homayounfar, Reza
Tahamtani, Yaser

Journal Title

Journal ISSN

Volume Title

Publisher

Nature Reseach

Abstract

Many factors can lead to an increase in the prevalence of metabolic syndrome (MetS) in different populations. Using an advanced structural equation model (SEM), this study is aimed to determine the most important risk factors of MetS, as a continuous latent variable, using a large number of males and females. We also aimed to evaluate the interrelations among the associated factors involved in the development of MetS. This study used data derived from the Fasa PERSIAN cohort study, a branch of the PERSIAN cohort study, for participants aged 35 to 70 years with 10,138 males and females. SEM was used to evaluate the direct and indirect effects, as well as gender effects of influencing factors. Results from the SEM showed that in females most changes in MetS are described by waist circumference (WC), followed by hypertension (HP) and triglyceride (TG), while in males most changes in MetS are described by WC, followed by TG then fasting blood glucose (FBG). Results from the SEM confirmed the gender effects of social status on MetS, mediated by sleep and controlled by age, BMI, ethnicity and physical activity. This study also shows that the integration of TG and WC within genders could be useful as a screening criterion for MetS in our study population.

Description

DATA AVAILABILITY : The datasets used and/or analyzed during the current study available from the corresponding author on request.

Keywords

Metabolic syndrome (MetS), Structural equation model (SEM), Risk factors, Gender effects

Sustainable Development Goals

None

Citation

Nouri‑Keshtkar, M., Shahrokhabadi, M.S., Ghaheri, A. et al. 2023, 'Role of gender in explaining metabolic syndrome risk factors in an Iranian rural population using structural equation modelling', Scientific Reports, vol. 13, art. 16007, pp. 1-12. https://DOI.org/10.1038/s41598-023-40485-y