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Comparative Analysis of Metabolic Syndrome Diagnostic Criteria and Its Effects on Prevalence in a Multiethnic Population.
Metabolic Syndrome and related Disorders 2021 March 2
Background: Accurate prevalence measurement and diagnosis to prevent type 2 diabetes mellitus and cardiovascular disease cannot occur without consistent diagnostic criteria that can be applied to varying populations. Objective: The objective of this study was to determine the prevalence of metabolic syndrome in Caucasian, Filipino, Native Hawaiian, and Japanese populations utilizing different definitions. Methods: This study utilized cross-sectional study data from the Native Hawaiian/Multiethnic Health Research Project, collected from a population living in Kohala, Hawai'i. The National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATPII), International Diabetes Federation (IDF), and World Health Organization (WHO) definitions were utilized, and each of the 1452 participants were evaluated on the criteria for metabolic syndrome based on all three definitions. Additionally, the average biomarker values associated with the diagnosis were taken for each ethnic group represented in the study and compared with Caucasians. Results: The overall prevalence of metabolic syndrome in this population varied from 22.31% to 39.05% using the different definitions. Ethnic disparities also occur, implying that certain populations are more prone to having severe abnormalities than others-shown when comparing the average biomarker values associated with metabolic syndrome diagnosis. Of all ethnic groups included in the study, Caucasians had the lowest prevalence of metabolic syndrome, while part-Hawaiians had the highest prevalence. Additionally, within the same ethnic group, the definitions yielded varying prevalence values. Conclusions: This implies that discrepancies exist among the criteria alone. Implications of this study revolve around not only the correct definition to apply to the population being studied but also the most accurate way to detect certain biomarker abnormalities to accurately assess the prevalence of metabolic syndrome in a multiethnic population.
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