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The Dynamics of Metabolic Syndrome Development from Its Isolated Components Among Iranian Adults: Findings from 17 years of the Tehran Lipid and Glucose Study (TLGS)

Overview
Specialty Endocrinology
Date 2021 Jun 28
PMID 34178824
Citations 2
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Abstract

Background: Evaluating the process of changes in the Metabolic Syndrome (MetS) components over time is one of the ways to study of the MetS natural history. This study aimed to determine the trend of changes in the progression of MetS from its isolated components.

Methods: This longitudinal study was performed on four follow-up periods of the Tehran Lipid and Glucose Study (TLGS) between 1999 and 2015. The research population consisted of 3905 adults over the age of 18 years. MetS was diagnosed based on the Joint Interim Statement (JIS). The considered components were abdominal obesity, hypertension, hyperglycemia, and dyslipidemia.

Results: The highest incidence of MetS from its components was related to hypertension in the short term (3.6-year intervals). In the long run, however, the highest increase in the MetS incidence occurred due to abdominal obesity. Overall, the incidence of MetS increased due to obesity and dyslipidemia, but decreased due to the other factors. Nonetheless, the trend of MetS incidence from all components increased in total. The most common components were dyslipidemia with a decreasing trend and obesity with an increasing trend during the study.

Conclusion: The results indicated that obesity and hypertension components played a more important role in the further development of MetS compared to other components in the Iranian adult population. This necessitates careful and serious attention in preventive and control planning.

Citing Articles

Cardiometabolic risk factors trend in Iranian adults with hypertension over 15 years: findings of nationwide steps of 2007-2021.

Jafari A, Mirbehbahani S, Golestani A, Soltani A, Sajjadi-Jazi S, Khosravi S J Diabetes Metab Disord. 2024; 23(2):2315-2328.

PMID: 39610546 PMC: 11599658. DOI: 10.1007/s40200-024-01498-0.


Predicting the natural history of metabolic syndrome with a Markov-system dynamic model: a novel approach.

Rezaianzadeh A, Morasae E, Khalili D, Seif M, Bahramali E, Azizi F BMC Med Res Methodol. 2021; 21(1):260.

PMID: 34837958 PMC: 8627615. DOI: 10.1186/s12874-021-01456-x.

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