Logo-jrhs
J Res Health Sci. 2019;19(2): e00442.
  Abstract View: 287
  PDF Download: 65

Original Article

Cardiovascular Disease Risk Assessment: Triglyceride/High-Density Lipoprotein versus Metabolic Syndrome Criteria

Mojgan Gharipour, Masoumeh Sadeghi*, Pouya Nezafati, Minoo Dianatkhah, Nizal Sarrafzadegan
*Corresponding Author: Email: m_sadeghi@crc.mui.ac.ir

Abstract

Background: As finding subjects at risk of cardiovascular diseases based on the presence of metabolic syndrome (MetS) is time-consuming for physicians, we aimed to compare the effectiveness of triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C) compared to MetS criteria in identifying high-risk individuals.

Study design: A prospective cohort study.

Methods: Isfahan cohort study was a longitudinal population-based study conducted on adults aged 35 yr or older, living in three districts in central part of Iran from Jan 2, 2001 to Sep 28, 2001. After 10 years of follow-up, participants were re-evaluated. The hazard ratio (HR) for cardiovascular disease events based on TG/HDL-C, sex-specific cut-off points, and MetS were also estimated. Akaike’s information criteria (AIC) were used as indicators of the goodness of fit of the model and prediction error.

Results: TG/HDL-C alternate cut-off points of 3.76 and 4.42 had a strong predictive value for CVD events but did not perform as well as MetS criteria. The unadjusted HR was greatest in the high-risk individuals by the MetS criteria (HR=2.08, 95% CI: 1.80, 2.41) compared to those identified as high-risks by the TG/HDL cut-off points and continued to be greatest after adjustments in different models. Based on the AIC, the best model is adjusted for sex, age, diabetes, total cholesterol levels, current smoker, diet, physical activity, and BMI.

Conclusion: MetS criteria appears to be a superior marker compared to TC/HDL-C to identify patients at cardiovascular risk, though lipid ratio also shows a remarkable predictive value and could be considered to achieve this goal when appropriate.

First Name
Last Name
Email Address
Comments
Security code


Abstract View: 288

Your browser does not support the canvas element.


PDF Download: 65

Your browser does not support the canvas element.

Submitted: 03 Feb 2019
Revision: 13 May 2019
ePublished: 13 May 2019
EndNote EndNote

(Enw Format - Win & Mac)

BibTeX BibTeX

(Bib Format - Win & Mac)

Bookends Bookends

(Ris Format - Mac only)

EasyBib EasyBib

(Ris Format - Win & Mac)

Medlars Medlars

(Txt Format - Win & Mac)

Mendeley Web Mendeley Web
Mendeley Mendeley

(Ris Format - Win & Mac)

Papers Papers

(Ris Format - Win & Mac)

ProCite ProCite

(Ris Format - Win & Mac)

Reference Manager Reference Manager

(Ris Format - Win only)

Refworks Refworks

(Refworks Format - Win & Mac)

Zotero Zotero

(Ris Format - Firefox Plugin)