Cargando…

Predictors of Lipid Profile Abnormalities Among Patients with Metabolic Syndrome in Southwest Ethiopia: A Cross-Sectional Study

BACKGROUND: Lipid profile abnormalities are an integral part of metabolic syndrome (MetS) and major underlying causes of cardiovascular disease (CVD) and type-2 diabetes mellitus (T2DM). Lipid profile abnormalities in a patient with MetS are resulted due to the presence of central obesity and insuli...

Descripción completa

Detalles Bibliográficos
Autores principales: Haile, Kassahun, Haile, Admasu, Timerga, Abebe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8360354/
https://www.ncbi.nlm.nih.gov/pubmed/34393487
http://dx.doi.org/10.2147/VHRM.S319161
_version_ 1783737724564406272
author Haile, Kassahun
Haile, Admasu
Timerga, Abebe
author_facet Haile, Kassahun
Haile, Admasu
Timerga, Abebe
author_sort Haile, Kassahun
collection PubMed
description BACKGROUND: Lipid profile abnormalities are an integral part of metabolic syndrome (MetS) and major underlying causes of cardiovascular disease (CVD) and type-2 diabetes mellitus (T2DM). Lipid profile abnormalities in a patient with MetS are resulted due to the presence of central obesity and insulin resistance. In Ethiopia, the burden and predictors of lipid profile abnormalities in a patient with MetS are not well known. Thus, this study aimed to determine the prevalence of lipid profile abnormalities and predictors among patients with MetS in southwest Ethiopia. METHODS AND MATERIALS: A cross-sectional study was conducted among 381 patients with MetS from September to December 2019 with a response rate of 100%. A structured questionnaire was used to collect data on socio-demographic and behavioral factors. Waist circumference, height, weight, and blood pressures were measured. The venous blood sample was collected for glucose and lipid profile determination. Data were entered and analyzed by using SPSS version 21. Binary logistic regression and Pearson's correlation analyses were performed. A p-value was set at a <0.05 for statistical significance. RESULTS: In this study, about 58% of participants were at least one or more lipid profile abnormalities with the 95% CI (52.8–62.7). About 67.2%, 44.6%,18.4%, and 14.2% of study participants were low HDL, high TG, LDL, and TC, respectively. Central obesity (adjusted odds ratio (AOR): 1.89, 95% CI: 1.14–3.14), increasing age (AOR: 2.08, 95% CI: 1.27–3.4), higher BMI (AOR: 2.06, 95% CI: 1.23–3.4), being hypertensive (AOR: 3.48, 95% CI: 2.12–5.7) and increasing blood glucose level (AOR: 2.34, 95% CI: 1.36–4.03) were independent predictors of lipid profile abnormalities (dyslipidemia). CONCLUSION: In this study area, a high (58%) prevalence of dyslipidemia was observed in study participants, and increasing age, higher BMI, central obesity, hypertension, and high blood glucose level were identified as independent predictors of dyslipidemia among patients with MetS. Prevention and control of dyslipidemia and its predictors among patients with MetS were recommended.
format Online
Article
Text
id pubmed-8360354
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Dove
record_format MEDLINE/PubMed
spelling pubmed-83603542021-08-13 Predictors of Lipid Profile Abnormalities Among Patients with Metabolic Syndrome in Southwest Ethiopia: A Cross-Sectional Study Haile, Kassahun Haile, Admasu Timerga, Abebe Vasc Health Risk Manag Original Research BACKGROUND: Lipid profile abnormalities are an integral part of metabolic syndrome (MetS) and major underlying causes of cardiovascular disease (CVD) and type-2 diabetes mellitus (T2DM). Lipid profile abnormalities in a patient with MetS are resulted due to the presence of central obesity and insulin resistance. In Ethiopia, the burden and predictors of lipid profile abnormalities in a patient with MetS are not well known. Thus, this study aimed to determine the prevalence of lipid profile abnormalities and predictors among patients with MetS in southwest Ethiopia. METHODS AND MATERIALS: A cross-sectional study was conducted among 381 patients with MetS from September to December 2019 with a response rate of 100%. A structured questionnaire was used to collect data on socio-demographic and behavioral factors. Waist circumference, height, weight, and blood pressures were measured. The venous blood sample was collected for glucose and lipid profile determination. Data were entered and analyzed by using SPSS version 21. Binary logistic regression and Pearson's correlation analyses were performed. A p-value was set at a <0.05 for statistical significance. RESULTS: In this study, about 58% of participants were at least one or more lipid profile abnormalities with the 95% CI (52.8–62.7). About 67.2%, 44.6%,18.4%, and 14.2% of study participants were low HDL, high TG, LDL, and TC, respectively. Central obesity (adjusted odds ratio (AOR): 1.89, 95% CI: 1.14–3.14), increasing age (AOR: 2.08, 95% CI: 1.27–3.4), higher BMI (AOR: 2.06, 95% CI: 1.23–3.4), being hypertensive (AOR: 3.48, 95% CI: 2.12–5.7) and increasing blood glucose level (AOR: 2.34, 95% CI: 1.36–4.03) were independent predictors of lipid profile abnormalities (dyslipidemia). CONCLUSION: In this study area, a high (58%) prevalence of dyslipidemia was observed in study participants, and increasing age, higher BMI, central obesity, hypertension, and high blood glucose level were identified as independent predictors of dyslipidemia among patients with MetS. Prevention and control of dyslipidemia and its predictors among patients with MetS were recommended. Dove 2021-08-08 /pmc/articles/PMC8360354/ /pubmed/34393487 http://dx.doi.org/10.2147/VHRM.S319161 Text en © 2021 Haile et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Haile, Kassahun
Haile, Admasu
Timerga, Abebe
Predictors of Lipid Profile Abnormalities Among Patients with Metabolic Syndrome in Southwest Ethiopia: A Cross-Sectional Study
title Predictors of Lipid Profile Abnormalities Among Patients with Metabolic Syndrome in Southwest Ethiopia: A Cross-Sectional Study
title_full Predictors of Lipid Profile Abnormalities Among Patients with Metabolic Syndrome in Southwest Ethiopia: A Cross-Sectional Study
title_fullStr Predictors of Lipid Profile Abnormalities Among Patients with Metabolic Syndrome in Southwest Ethiopia: A Cross-Sectional Study
title_full_unstemmed Predictors of Lipid Profile Abnormalities Among Patients with Metabolic Syndrome in Southwest Ethiopia: A Cross-Sectional Study
title_short Predictors of Lipid Profile Abnormalities Among Patients with Metabolic Syndrome in Southwest Ethiopia: A Cross-Sectional Study
title_sort predictors of lipid profile abnormalities among patients with metabolic syndrome in southwest ethiopia: a cross-sectional study
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8360354/
https://www.ncbi.nlm.nih.gov/pubmed/34393487
http://dx.doi.org/10.2147/VHRM.S319161
work_keys_str_mv AT hailekassahun predictorsoflipidprofileabnormalitiesamongpatientswithmetabolicsyndromeinsouthwestethiopiaacrosssectionalstudy
AT haileadmasu predictorsoflipidprofileabnormalitiesamongpatientswithmetabolicsyndromeinsouthwestethiopiaacrosssectionalstudy
AT timergaabebe predictorsoflipidprofileabnormalitiesamongpatientswithmetabolicsyndromeinsouthwestethiopiaacrosssectionalstudy