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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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Autores principales: Abd El–Wahab, Ekram W., Shatat, Hanan Z., Charl, Fahmy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822183/
https://www.ncbi.nlm.nih.gov/pubmed/31662026
http://dx.doi.org/10.1177/2150132719882760
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author Abd El–Wahab, Ekram W.
Shatat, Hanan Z.
Charl, Fahmy
author_facet Abd El–Wahab, Ekram W.
Shatat, Hanan Z.
Charl, Fahmy
author_sort Abd El–Wahab, Ekram W.
collection PubMed
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.
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spelling pubmed-68221832019-11-06 Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing Countries Abd El–Wahab, Ekram W. Shatat, Hanan Z. Charl, Fahmy J Prim Care Community Health Original Research 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. SAGE Publications 2019-10-29 /pmc/articles/PMC6822183/ /pubmed/31662026 http://dx.doi.org/10.1177/2150132719882760 Text en © The Author(s) 2019 http://www.creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Abd El–Wahab, Ekram W.
Shatat, Hanan Z.
Charl, Fahmy
Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing Countries
title 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_short 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
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822183/
https://www.ncbi.nlm.nih.gov/pubmed/31662026
http://dx.doi.org/10.1177/2150132719882760
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