Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing Countries

Background: Metabolic syndrome (MetS) is a cluster of cardiometabolic disturbances that increases the risk of cardiovascular diseases (CVD) and type 2 diabetes mellitus (DM). The early identification of high-risk individuals is the key for halting these conditions. The world is facing a growing epid...

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Main Authors: Ekram W. Abd El–Wahab, Hanan Z. Shatat, Fahmy Charl
Format: Article
Language:English
Published: SAGE Publishing 2019-10-01
Series:Journal of Primary Care & Community Health
Online Access:https://doi.org/10.1177/2150132719882760
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spelling doaj-d25cce49398f42a398534d191f5b29af2020-11-25T03:35:51ZengSAGE PublishingJournal of Primary Care & Community Health2150-13272019-10-011010.1177/2150132719882760Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing CountriesEkram W. Abd El–Wahab0Hanan Z. Shatat1Fahmy Charl2Department of Tropical Health, High Institute of Public Health, Alexandria University, EgyptDepartment of Tropical Health, High Institute of Public Health, Alexandria University, EgyptDepartment of Occupational Health and Air Pollution (Division of Occupational Health and Industrial Medicine), High Institute of Public Health, Alexandria University, EgyptBackground: Metabolic syndrome (MetS) is a cluster of cardiometabolic disturbances that increases the risk of cardiovascular diseases (CVD) and type 2 diabetes mellitus (DM). The early identification of high-risk individuals is the key for halting these conditions. The world is facing a growing epidemic MetS although the magnitude in Egypt is unknown. Objectives: To describe MetS and its determinants among apparently healthy individuals residing in urban and rural communities in Egypt and to establish a model for MetS prediction. Methods: A cross-sectional study was conducted with 270 adults from rural and urban districts in Alexandria, Egypt. Participants were clinically evaluated and interviewed for sociodemographic and lifestyle factors and dietary habits. MetS was defined according to the harmonized criteria set by the AHA/NHLBI. The risk of ischemic heart diseases (IHDs), DM and fatty liver were assessed using validated risk prediction charts. A multiple risk model for predicting MetS was developed, and its performance was compared. Results: In total, 57.8% of the study population met the criteria for MetS and were at high risk for developing IHD, DM, and fatty liver. Silent CVD risk factors were identified in 20.4% of the participants. In our proposed multivariate logistic regression model, the predictors of MetS were obesity [OR (95% CI) = 16.3 (6.03-44.0)], morbid obesity [OR (95% CI) = 21.7 (5.3-88.0)], not working [OR (95% CI) = 2.05 (1.1-3.8)], and having a family history of chronic diseases [OR (95% CI) = 4.38 (2.23-8.61)]. Consumption of caffeine once per week protected against MetS by 27.8-fold. The derived prediction rule was accurate in predicting MetS, fatty liver, high risk of DM, and, to a lesser extent, a 10-year lifetime risk of IHD. Conclusion: Central obesity and sedentary lifestyles are accountable for the rising rates of MetS in our society. Interventions are needed to minimize the potential predisposition of the Egyptian population to cardiometabolic diseases.https://doi.org/10.1177/2150132719882760
collection DOAJ
language English
format Article
sources DOAJ
author Ekram W. Abd El–Wahab
Hanan Z. Shatat
Fahmy Charl
spellingShingle Ekram W. Abd El–Wahab
Hanan Z. Shatat
Fahmy Charl
Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing Countries
Journal of Primary Care & Community Health
author_facet Ekram W. Abd El–Wahab
Hanan Z. Shatat
Fahmy Charl
author_sort Ekram W. Abd El–Wahab
title Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing Countries
title_short Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing Countries
title_full Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing Countries
title_fullStr Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing Countries
title_full_unstemmed Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing Countries
title_sort adapting a prediction rule for metabolic syndrome risk assessment suitable for developing countries
publisher SAGE Publishing
series Journal of Primary Care & Community Health
issn 2150-1327
publishDate 2019-10-01
description Background: Metabolic syndrome (MetS) is a cluster of cardiometabolic disturbances that increases the risk of cardiovascular diseases (CVD) and type 2 diabetes mellitus (DM). The early identification of high-risk individuals is the key for halting these conditions. The world is facing a growing epidemic MetS although the magnitude in Egypt is unknown. Objectives: To describe MetS and its determinants among apparently healthy individuals residing in urban and rural communities in Egypt and to establish a model for MetS prediction. Methods: A cross-sectional study was conducted with 270 adults from rural and urban districts in Alexandria, Egypt. Participants were clinically evaluated and interviewed for sociodemographic and lifestyle factors and dietary habits. MetS was defined according to the harmonized criteria set by the AHA/NHLBI. The risk of ischemic heart diseases (IHDs), DM and fatty liver were assessed using validated risk prediction charts. A multiple risk model for predicting MetS was developed, and its performance was compared. Results: In total, 57.8% of the study population met the criteria for MetS and were at high risk for developing IHD, DM, and fatty liver. Silent CVD risk factors were identified in 20.4% of the participants. In our proposed multivariate logistic regression model, the predictors of MetS were obesity [OR (95% CI) = 16.3 (6.03-44.0)], morbid obesity [OR (95% CI) = 21.7 (5.3-88.0)], not working [OR (95% CI) = 2.05 (1.1-3.8)], and having a family history of chronic diseases [OR (95% CI) = 4.38 (2.23-8.61)]. Consumption of caffeine once per week protected against MetS by 27.8-fold. The derived prediction rule was accurate in predicting MetS, fatty liver, high risk of DM, and, to a lesser extent, a 10-year lifetime risk of IHD. Conclusion: Central obesity and sedentary lifestyles are accountable for the rising rates of MetS in our society. Interventions are needed to minimize the potential predisposition of the Egyptian population to cardiometabolic diseases.
url https://doi.org/10.1177/2150132719882760
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