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Impact of Metabolic Syndrome Components in High-Risk Cardiovascular Disease Development in Older Adults

Authors Gustavo de Sousa Barbalho Y, Morato Stival M, Ramos de Lima L, Cristina Rodrigues da Silva I, de Oliveira Silva A, Vieira Gomes da Costa M, Cristina Morais Santa Barbara Rehem T, Schwerz Funghetto S

Received 5 March 2020

Accepted for publication 25 July 2020

Published 18 September 2020 Volume 2020:15 Pages 1691—1700


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr Richard Walker

Yuri Gustavo de Sousa Barbalho, 1 Marina Morato Stival, 1 Luciano Ramos de Lima, 1 Izabel Cristina Rodrigues da Silva, 1 Alessandro de Oliveira Silva, 2 Manoela Vieira Gomes da Costa, 1 Tania Cristina Morais Santa Barbara Rehem, 1 Silvana Schwerz Funghetto 1

1Graduate Department of Health Sciences and Technologies, University of Brasilia (UnB), Brasilia, Federal District, Brazil; 2Physical Education Department, University Center of Brasilia, Brasilia, Federal District, Brazil

Correspondence: Yuri Gustavo de Sousa Barbalho Tel +55 61 9 9112-7116

Objective: Analyze the influence between the components of metabolic syndrome and the independent risk for cardiovascular disease (CVD) in the elderly.
Methods: A descriptive cross-sectional study was carried out with 205 older adults from a primary healthcare unit of the Federal District, Brazil. The cardiovascular risk was determined by the Framingham Risk Score (FRS). The National Cholesterol Evaluation Program for Adult Treatment Panel III 2001 (NCEP-ATP III) criteria were considered to analyze metabolic syndrome (MS) diagnoses.
Results: There was a strong association between MS and high cardiovascular risk (OR = 8.86). The univariate analysis main findings revealed that male gender, diabetes, smoking habit, systolic blood pressure, HDL level, high blood glucose, glycated hemoglobin, and LDL level were associated with high cardiovascular risk. FRS increases significantly with the presence of four or more MS components (by 30%, if 4 components are present, and by 40%, if 5 components) when compared with the presence of three or fewer components (P < 0.001). A logistic regression analysis of high-risk predictors was described to reduce the effects of confounding and bias factors.
Conclusion: The identification of MS associated with high FRS values represents a cascading of adverse effects on the population’s aging process.

Keywords: aged, metabolic syndrome, cardiovascular system, aging population

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