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Assessing clustering of metabolic syndrome components available at primary care for Bantu Africans using factor analysis in the general population

BACKGROUND: To provide a step-by-step description of the application of factor analysis and interpretation of the results based on anthropometric parameters(body mass index or BMI and waist circumferenceor WC), blood pressure(BP), lipid-lipoprotein(triglycerides and HDL-C) and glucose among Bantu Af...

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Autores principales: Nasila Sungwacha, John, Tyler, Joanne, Longo-Mbenza, Benjamin, Lasi On'Kin, Jean Bosco Kasiam, Gombet, Thierry, Erasmus, Rajiv T
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3685560/
https://www.ncbi.nlm.nih.gov/pubmed/23758878
http://dx.doi.org/10.1186/1756-0500-6-228
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author Nasila Sungwacha, John
Tyler, Joanne
Longo-Mbenza, Benjamin
Lasi On'Kin, Jean Bosco Kasiam
Gombet, Thierry
Erasmus, Rajiv T
author_facet Nasila Sungwacha, John
Tyler, Joanne
Longo-Mbenza, Benjamin
Lasi On'Kin, Jean Bosco Kasiam
Gombet, Thierry
Erasmus, Rajiv T
author_sort Nasila Sungwacha, John
collection PubMed
description BACKGROUND: To provide a step-by-step description of the application of factor analysis and interpretation of the results based on anthropometric parameters(body mass index or BMI and waist circumferenceor WC), blood pressure(BP), lipid-lipoprotein(triglycerides and HDL-C) and glucose among Bantu Africans with different numbers and cutoffs of components of metabolic syndrome(MS). METHODS: This study was a cross-sectional, comparative, and correlational survey conducted between January and April 2005, in Kinshasa Hinterland, DRC. The clustering of cardiovascular risk factors was defined in all, MS group according to IDF(WC, BP, triglycerides, HDL-C, glucose), absence and presence of cardiometabolic risk(CDM) group(BMI,WC, BP, fasting glucose, and post-load glucose). RESULTS: Out of 977 participants, 17.4%( n = 170), 11%( n = 107), and 7.7%(n = 75) had type 2 diabetes mellitus(T2DM), MS, and CDM, respectively. Gender did not influence on all variables. Except BMI, levels of the rest variables were significantly higher in presence of T2DM than non-diabetics. There was a negative correlation between glucose types and BP in absence of CDM. In factor analysis for all, BP(factor 1) and triglycerides-HDL(factor 2) explained 55.4% of the total variance. In factor analysis for MS group, triglycerides-HDL-C(factor 1), BP(factor 2), and abdominal obesity-dysglycemia(factor 3) explained 75.1% of the total variance. In absence of CDM, glucose (factor 1) and obesity(factor 2) explained 48.1% of the total variance. In presence of CDM, 3 factors (factor 1 = glucose, factor 2 = BP, and factor 3 = obesity) explained 73.4% of the total variance. CONCLUSION: The MS pathogenesis may be more glucose-centered than abdominal obesity-centered in not considering lipid-lipoprotein , while BP and triglycerides-HDL-C could be the most strong predictors of MS in the general population. It should be specifically defined by ethnic cut-offs of waist circumference among Bantu Africans.
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spelling pubmed-36855602013-06-26 Assessing clustering of metabolic syndrome components available at primary care for Bantu Africans using factor analysis in the general population Nasila Sungwacha, John Tyler, Joanne Longo-Mbenza, Benjamin Lasi On'Kin, Jean Bosco Kasiam Gombet, Thierry Erasmus, Rajiv T BMC Res Notes Research Article BACKGROUND: To provide a step-by-step description of the application of factor analysis and interpretation of the results based on anthropometric parameters(body mass index or BMI and waist circumferenceor WC), blood pressure(BP), lipid-lipoprotein(triglycerides and HDL-C) and glucose among Bantu Africans with different numbers and cutoffs of components of metabolic syndrome(MS). METHODS: This study was a cross-sectional, comparative, and correlational survey conducted between January and April 2005, in Kinshasa Hinterland, DRC. The clustering of cardiovascular risk factors was defined in all, MS group according to IDF(WC, BP, triglycerides, HDL-C, glucose), absence and presence of cardiometabolic risk(CDM) group(BMI,WC, BP, fasting glucose, and post-load glucose). RESULTS: Out of 977 participants, 17.4%( n = 170), 11%( n = 107), and 7.7%(n = 75) had type 2 diabetes mellitus(T2DM), MS, and CDM, respectively. Gender did not influence on all variables. Except BMI, levels of the rest variables were significantly higher in presence of T2DM than non-diabetics. There was a negative correlation between glucose types and BP in absence of CDM. In factor analysis for all, BP(factor 1) and triglycerides-HDL(factor 2) explained 55.4% of the total variance. In factor analysis for MS group, triglycerides-HDL-C(factor 1), BP(factor 2), and abdominal obesity-dysglycemia(factor 3) explained 75.1% of the total variance. In absence of CDM, glucose (factor 1) and obesity(factor 2) explained 48.1% of the total variance. In presence of CDM, 3 factors (factor 1 = glucose, factor 2 = BP, and factor 3 = obesity) explained 73.4% of the total variance. CONCLUSION: The MS pathogenesis may be more glucose-centered than abdominal obesity-centered in not considering lipid-lipoprotein , while BP and triglycerides-HDL-C could be the most strong predictors of MS in the general population. It should be specifically defined by ethnic cut-offs of waist circumference among Bantu Africans. BioMed Central 2013-06-12 /pmc/articles/PMC3685560/ /pubmed/23758878 http://dx.doi.org/10.1186/1756-0500-6-228 Text en Copyright © 2013 Nasila Sungwacha et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Nasila Sungwacha, John
Tyler, Joanne
Longo-Mbenza, Benjamin
Lasi On'Kin, Jean Bosco Kasiam
Gombet, Thierry
Erasmus, Rajiv T
Assessing clustering of metabolic syndrome components available at primary care for Bantu Africans using factor analysis in the general population
title Assessing clustering of metabolic syndrome components available at primary care for Bantu Africans using factor analysis in the general population
title_full Assessing clustering of metabolic syndrome components available at primary care for Bantu Africans using factor analysis in the general population
title_fullStr Assessing clustering of metabolic syndrome components available at primary care for Bantu Africans using factor analysis in the general population
title_full_unstemmed Assessing clustering of metabolic syndrome components available at primary care for Bantu Africans using factor analysis in the general population
title_short Assessing clustering of metabolic syndrome components available at primary care for Bantu Africans using factor analysis in the general population
title_sort assessing clustering of metabolic syndrome components available at primary care for bantu africans using factor analysis in the general population
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3685560/
https://www.ncbi.nlm.nih.gov/pubmed/23758878
http://dx.doi.org/10.1186/1756-0500-6-228
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