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Original article Socioeconomic inequalities in metabolic syndrome and its components in a sample of Iranian Kurdish adults
Pardis Mohammadzadeh1,2orcid , Farhad Moradpour3orcid , Bijan Nouri4orcid , Farideh Mostafavi5orcid , Farid Najafi6orcid , Ghobad Moradi1,3orcid
Epidemiol Health 2023;e2023083
DOI: https://doi.org/10.4178/epih.e2023083 [Accepted]
Published online: September 3, 2023
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1Department of Epidemiology and Biostatistics, School of Medicine, Kurdistan University of Medical Sciences, Sanandaj, Iran
2Student Research Committee, Kurdistan University of Medical Sciences, Sanandaj, Iran
3Social Determinants of Health Research Center, Kurdistan University of Medical Sciences, Sanandaj, Iran
4Health Metrics and Evaluation Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran
5Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
6Department of Epidemiology, School of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
Corresponding author:  Ghobad Moradi,
Email: moradi_gh@yahoo.com
Received: 24 February 2023   • Revised: 11 August 2023   • Accepted: 15 August 2023
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Abstract

OBJECTIVES
The worldwide incidence of metabolic syndrome (MetS) has increased in recent decades. In this study, we investigated the socioeconomic inequalities associated with MetS and its components in a sample of the Iranian Kurdish population.
METHODS
We used data from 3996 participants, aged 35 to 70 years, from the baseline phase of the Dehgolan Prospective Cohort Study (February 2018 to March 2019). The concentration index and concentration curve were used to measure inequality and the Blinder-Oaxaca decomposition method was used to examine the contribution of various determinants to the observed socioeconomic inequality in MetS and its components.
RESULTS
The prevalence of MetS was 34.44% (95% CI, 32.97% to 35.93%). The prevalence of MetS was 26.18% for those in the highest socioeconomic status (SES), compared with 40.51% for participants in the lowest SES. There was a significant negative concentration index for MetS (C=-0.13; 95% CI, -0.16 to -0.09), indicating a concentration of MetS among participants with a lower SES. The most prevalent component was abdominal obesity (59.14%) with a significant negative concentration index (C=-0.21; 95% CI, -0.25 to -0.18). According to decomposition analysis, age, gender, and education were the highest contributing factors to inequality in MetS and its components.
CONCLUSIONS
This study showed socioeconomic inequality in MetS. People with a low SES were more likely to have MetS. Therefore, policymakers and health managers need to develop appropriate strategies to reduce these inequalities in MetS across age groups, genders, and education levels, especially among women and the elderly.

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