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

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dc.contributor.authorNasila Sungwacha, John
dc.contributor.authorTyler, Joanne
dc.contributor.authorLongo-Mbenza, Benjamin
dc.contributor.authorLasi On'Kin, Jean Bosco Kasiam
dc.contributor.authorGombet, Thierry
dc.contributor.authorErasmus, Rajiv T.
dc.date.accessioned2013-06-26T14:09:27Z
dc.date.available2013-06-26T14:09:27Z
dc.date.issued2013-06
dc.date.updated2013-06-18T23:05:13Z
dc.descriptionThe original publication is available at http://www.biomedcentral.com/1756-0500/6/228en_ZA
dc.descriptionBibliography.
dc.description.abstractABSTRACT: 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). 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.en_ZA
dc.description.versionPublishers' Versionen_ZA
dc.format.extent10 p. : ill.
dc.identifier.citationSungwacha, J. N. et al. 2013. Assessing clustering of metabolic syndrome components available at primary care for Bantu Africans using factor analysis in the general population. BMC Research Notes, 6(1):228, doi:10.1186/1756-0500-6-228.en_ZA
dc.identifier.issn1756-0500 (online)
dc.identifier.otherdoi.org/10.1186/1756-0500-6-228
dc.identifier.urihttp://hdl.handle.net/10019.1/80951
dc.language.isoen_ZAen_ZA
dc.language.rfc3066en_ZAen_ZA
dc.publisherBioMed Centralen_ZA
dc.rights.holderJohn Nasila Sungwacha et al.; licensee BioMed Central Ltd.en_ZA
dc.subjectCardiovascular system -- Diseases -- Risk factors -- Africa, Centralen_ZA
dc.subjectMetabolic syndrome -- Symptoms -- Africa, Central -- Researchen_ZA
dc.subjectMedical screeningen_ZA
dc.titleAssessing clustering of metabolic syndrome components available at primary care for Bantu Africans using factor analysis in the general populationen_ZA
dc.typeArticleen_ZA
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