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Behzad Karamimatin 1 Article
Measurement and Decomposition of Socioeconomic Inequality in Metabolic Syndrome: A Cross-sectional Analysis of the RaNCD Cohort Study in the West of Iran
Moslem Soofi, Farid Najafi, Shahin Soltani, Behzad Karamimatin
J Prev Med Public Health. 2023;56(1):50-58.   Published online January 6, 2023
DOI: https://doi.org/10.3961/jpmph.22.373
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AbstractAbstract PDF
Objectives
Socioeconomic inequality in metabolic syndrome (MetS) remains poorly understood in Iran. The present study examined the extent of the socioeconomic inequalities in MetS and quantified the contribution of its determinants to explain the observed inequality, with a focus on middle-aged adults in Iran.
Methods
This cross-sectional study used data from the Ravansar Non-Communicable Disease cohort study. A sample of 9975 middle-aged adults aged 35-65 years was analyzed. MetS was assessed based on the International Diabetes Federation definition. Principal component analysis was used to construct socioeconomic status (SES). The Wagstaff normalized concentration index (CIn) was employed to measure the magnitude of socioeconomic inequalities in MetS. Decomposition analysis was performed to identify and calculate the contribution of the MetS inequality determinants.
Results
The proportion of MetS in the sample was 41.1%. The CIn of having MetS was 0.043 (95% confidence interval, 0.020 to 0.066), indicating that MetS was more concentrated among individuals with high SES. The main contributors to the observed inequality in MetS were SES (72.0%), residence (rural or urban, 46.9%), and physical activity (31.5%).
Conclusions
Our findings indicated a pro-poor inequality in MetS among Iranian middle-aged adults. These results highlight the importance of persuading middle-aged adults to be physically active, particularly those in an urban setting. In addition to targeting physically inactive individuals and those with low levels of education, policy interventions aimed at mitigating socioeconomic inequality in MetS should increase the focus on high-SES individuals and the urban population.
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Citations

Citations to this article as recorded by  
  • Sleep Quality, Nutrient Intake, and Social Development Index Predict Metabolic Syndrome in the Tlalpan 2020 Cohort: A Machine Learning and Synthetic Data Study
    Guadalupe Gutiérrez-Esparza, Mireya Martinez-Garcia, Tania Ramírez-delReal, Lucero Elizabeth Groves-Miralrio, Manlio F. Marquez, Tomás Pulido, Luis M. Amezcua-Guerra, Enrique Hernández-Lemus
    Nutrients.2024; 16(5): 612.     CrossRef
  • Socioeconomic inequalities in metabolic syndrome and its components in a sample of Iranian Kurdish adults
    Pardis Mohammadzadeh, Farhad Moradpour, Bijan Nouri, Farideh Mostafavi, Farid Najafi, Ghobad Moradi
    Epidemiology and Health.2023; : e2023083.     CrossRef

JPMPH : Journal of Preventive Medicine and Public Health