Metabolic syndrome and its predictors in an urban population in Kenya: A cross sectional study
Abstract Background The metabolic syndrome (MetS) is a clustering of interrelated risk factors which doubles the risk of cardio-vascular disease (CVD) in 5–10 years and increases the risk of type 2 diabetes 5 fold. The identification of modifiable CVD risk factors and predictors of MetS in an otherw...
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doaj-a06de32314fc4d7fa463ca978e22232e2020-11-25T03:13:35ZengBMCBMC Endocrine Disorders1472-68232017-07-0117111110.1186/s12902-017-0188-0Metabolic syndrome and its predictors in an urban population in Kenya: A cross sectional studyGeoffrey Omuse0Daniel Maina1Mariza Hoffman2Jane Mwangi3Caroline Wambua4Elizabeth Kagotho5Angela Amayo6Peter Ojwang7Zulfiqarali Premji8Kiyoshi Ichihara9Rajiv Erasmus10Department of Pathology, Aga Khan University Hospital NairobiDepartment of Pathology, Aga Khan University Hospital NairobiDivision of Chemical Pathology, Department of Pathology, Stellenbosch UniversityPathCare Kenya Ltd.PathCare Kenya Ltd.Department of Pathology, Aga Khan University Hospital NairobiDepartment of Human Pathology, University of NairobiDepartment of Pathology, Maseno UniversityFormerly of Muhimbili University of Health and Allied SciencesGraduate School of Medicine, Faculty of Health Sciences, Yamaguchi UniversityDivision of Chemical Pathology, Department of Pathology, Stellenbosch UniversityAbstract Background The metabolic syndrome (MetS) is a clustering of interrelated risk factors which doubles the risk of cardio-vascular disease (CVD) in 5–10 years and increases the risk of type 2 diabetes 5 fold. The identification of modifiable CVD risk factors and predictors of MetS in an otherwise healthy population is necessary in order to identify individuals who may benefit from early interventions. We sought to determine the prevalence of MetS as defined by the harmonized criteria and its predictors in subjectively healthy black Africans from various urban centres in Kenya. Method We used data collected from healthy black Africans in Kenya as part of a global study on establishing reference intervals for common laboratory tests. We determined the prevalence of MetS and its components using the 2009 harmonized criterion. Receiver operator characteristic (ROC) curve analysis was used to determine the area under the curves (AUC) for various predictors of MetS. Youden index was used to determine optimum cut-offs for quantitative measurements such as waist circumference (WC). Results A total of 528 participants were included in the analysis. The prevalence of MetS was 25.6% (95% CI: 22.0%–29.5%). Among the surrogate markers of visceral adiposity, lipid accumulation product was the best predictor of MetS with an AUC of 0.880 while triglyceride was the best predictor among the lipid parameters with an AUC of 0.816 for all participants. The optimal WC cut-off for diagnosing MetS was 94 cm and 86 cm respectively for males and females. Conclusions The prevalence of MetS was high for a healthy population highlighting the fact that one can be physically healthy but have metabolic derangements indicative of an increased CVD risk. This is likely to result in an increase in the cases of CVD and type 2 diabetes in Kenya if interventions are not put in place to reverse this trend. We have also demonstrated the inappropriateness of the WC cut-off of 80 cm for black African women in Kenya when defining MetS and recommend adoption of 86 cm.http://link.springer.com/article/10.1186/s12902-017-0188-0Metabolic syndromeWaist circumferenceVisceral adiposityCardiovascular riskKenyaAfrica |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Geoffrey Omuse Daniel Maina Mariza Hoffman Jane Mwangi Caroline Wambua Elizabeth Kagotho Angela Amayo Peter Ojwang Zulfiqarali Premji Kiyoshi Ichihara Rajiv Erasmus |
spellingShingle |
Geoffrey Omuse Daniel Maina Mariza Hoffman Jane Mwangi Caroline Wambua Elizabeth Kagotho Angela Amayo Peter Ojwang Zulfiqarali Premji Kiyoshi Ichihara Rajiv Erasmus Metabolic syndrome and its predictors in an urban population in Kenya: A cross sectional study BMC Endocrine Disorders Metabolic syndrome Waist circumference Visceral adiposity Cardiovascular risk Kenya Africa |
author_facet |
Geoffrey Omuse Daniel Maina Mariza Hoffman Jane Mwangi Caroline Wambua Elizabeth Kagotho Angela Amayo Peter Ojwang Zulfiqarali Premji Kiyoshi Ichihara Rajiv Erasmus |
author_sort |
Geoffrey Omuse |
title |
Metabolic syndrome and its predictors in an urban population in Kenya: A cross sectional study |
title_short |
Metabolic syndrome and its predictors in an urban population in Kenya: A cross sectional study |
title_full |
Metabolic syndrome and its predictors in an urban population in Kenya: A cross sectional study |
title_fullStr |
Metabolic syndrome and its predictors in an urban population in Kenya: A cross sectional study |
title_full_unstemmed |
Metabolic syndrome and its predictors in an urban population in Kenya: A cross sectional study |
title_sort |
metabolic syndrome and its predictors in an urban population in kenya: a cross sectional study |
publisher |
BMC |
series |
BMC Endocrine Disorders |
issn |
1472-6823 |
publishDate |
2017-07-01 |
description |
Abstract Background The metabolic syndrome (MetS) is a clustering of interrelated risk factors which doubles the risk of cardio-vascular disease (CVD) in 5–10 years and increases the risk of type 2 diabetes 5 fold. The identification of modifiable CVD risk factors and predictors of MetS in an otherwise healthy population is necessary in order to identify individuals who may benefit from early interventions. We sought to determine the prevalence of MetS as defined by the harmonized criteria and its predictors in subjectively healthy black Africans from various urban centres in Kenya. Method We used data collected from healthy black Africans in Kenya as part of a global study on establishing reference intervals for common laboratory tests. We determined the prevalence of MetS and its components using the 2009 harmonized criterion. Receiver operator characteristic (ROC) curve analysis was used to determine the area under the curves (AUC) for various predictors of MetS. Youden index was used to determine optimum cut-offs for quantitative measurements such as waist circumference (WC). Results A total of 528 participants were included in the analysis. The prevalence of MetS was 25.6% (95% CI: 22.0%–29.5%). Among the surrogate markers of visceral adiposity, lipid accumulation product was the best predictor of MetS with an AUC of 0.880 while triglyceride was the best predictor among the lipid parameters with an AUC of 0.816 for all participants. The optimal WC cut-off for diagnosing MetS was 94 cm and 86 cm respectively for males and females. Conclusions The prevalence of MetS was high for a healthy population highlighting the fact that one can be physically healthy but have metabolic derangements indicative of an increased CVD risk. This is likely to result in an increase in the cases of CVD and type 2 diabetes in Kenya if interventions are not put in place to reverse this trend. We have also demonstrated the inappropriateness of the WC cut-off of 80 cm for black African women in Kenya when defining MetS and recommend adoption of 86 cm. |
topic |
Metabolic syndrome Waist circumference Visceral adiposity Cardiovascular risk Kenya Africa |
url |
http://link.springer.com/article/10.1186/s12902-017-0188-0 |
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