Sociodemographic Disparities in the Prevalence of Metabolic Syndrome in Rural South Africa: An Analysis of Gender, Age, and Marital, Employment, and Educational Status

Sociodemographic factors affect how metabolic syndrome (MetS) manifests and progresses. This study aimed to investigate the prevalence between MetS and sociodemographic factors among adult participants in the Dikgale HDSS. This was a comprehensive retrospective study where the records of 575 partici...

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Main Authors: Dimakatso Given Mashala, Cairo Bruce Ntimana, Kagiso Peace Seakamela, Reneilwe Given Mashaba, Eric Maimela
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Obesities
Subjects:
Online Access:https://www.mdpi.com/2673-4168/4/4/38
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author Dimakatso Given Mashala
Cairo Bruce Ntimana
Kagiso Peace Seakamela
Reneilwe Given Mashaba
Eric Maimela
author_facet Dimakatso Given Mashala
Cairo Bruce Ntimana
Kagiso Peace Seakamela
Reneilwe Given Mashaba
Eric Maimela
author_sort Dimakatso Given Mashala
collection DOAJ
description Sociodemographic factors affect how metabolic syndrome (MetS) manifests and progresses. This study aimed to investigate the prevalence between MetS and sociodemographic factors among adult participants in the Dikgale HDSS. This was a comprehensive retrospective study where the records of 575 participants were meticulously evaluated. MetS was defined using a joint interim statement (JIS). The data were analyzed using the Statistical Package for SPSS, version 25. A chi-square test was used to compare proportions between groups, with Cramer’s V used to assess the strength of association. Logistic regression was used to determine the association between MetS and sociodemographic profiles. A <i>p</i>-value of less than 0.05 was considered statistically significant. The prevalence of MetS was 28.2% (females 33.3% vs. males 15.6%, <i>p</i> ≤ 0.001). In addition, logistic regression showed males to have lower odds of MetS as compared to females (OR = 0.36, 95% CI: 0.2–0.6, and AOR = 0.4, 95% CI: 0.2–0.6). The 55–60 age group had the highest proportion of affected individuals, and MetS was also more common among individuals with low educational attainment. In addition, on regression, the same association was observed. This study found sociodemographic disparities in MetS among rural adults, especially females, who had an increased risk of MetS, and participants with low educational attainment.
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spelling doaj-art-a4ad142283bc4a0e8c2abff23660285d2024-12-27T14:44:31ZengMDPI AGObesities2673-41682024-11-014448049010.3390/obesities4040038Sociodemographic Disparities in the Prevalence of Metabolic Syndrome in Rural South Africa: An Analysis of Gender, Age, and Marital, Employment, and Educational StatusDimakatso Given Mashala0Cairo Bruce Ntimana1Kagiso Peace Seakamela2Reneilwe Given Mashaba3Eric Maimela4Department of Optometry, Faculty of Health Sciences, University of Limpopo, Polokwane 0727, South AfricaDIMAMO Population Health Research Centre, University of Limpopo, Polokwane 0727, South AfricaDIMAMO Population Health Research Centre, University of Limpopo, Polokwane 0727, South AfricaDIMAMO Population Health Research Centre, University of Limpopo, Polokwane 0727, South AfricaDIMAMO Population Health Research Centre, University of Limpopo, Polokwane 0727, South AfricaSociodemographic factors affect how metabolic syndrome (MetS) manifests and progresses. This study aimed to investigate the prevalence between MetS and sociodemographic factors among adult participants in the Dikgale HDSS. This was a comprehensive retrospective study where the records of 575 participants were meticulously evaluated. MetS was defined using a joint interim statement (JIS). The data were analyzed using the Statistical Package for SPSS, version 25. A chi-square test was used to compare proportions between groups, with Cramer’s V used to assess the strength of association. Logistic regression was used to determine the association between MetS and sociodemographic profiles. A <i>p</i>-value of less than 0.05 was considered statistically significant. The prevalence of MetS was 28.2% (females 33.3% vs. males 15.6%, <i>p</i> ≤ 0.001). In addition, logistic regression showed males to have lower odds of MetS as compared to females (OR = 0.36, 95% CI: 0.2–0.6, and AOR = 0.4, 95% CI: 0.2–0.6). The 55–60 age group had the highest proportion of affected individuals, and MetS was also more common among individuals with low educational attainment. In addition, on regression, the same association was observed. This study found sociodemographic disparities in MetS among rural adults, especially females, who had an increased risk of MetS, and participants with low educational attainment.https://www.mdpi.com/2673-4168/4/4/38metabolic syndromesocioeconomic statusjoint interim statementprevalence
spellingShingle Dimakatso Given Mashala
Cairo Bruce Ntimana
Kagiso Peace Seakamela
Reneilwe Given Mashaba
Eric Maimela
Sociodemographic Disparities in the Prevalence of Metabolic Syndrome in Rural South Africa: An Analysis of Gender, Age, and Marital, Employment, and Educational Status
Obesities
metabolic syndrome
socioeconomic status
joint interim statement
prevalence
title Sociodemographic Disparities in the Prevalence of Metabolic Syndrome in Rural South Africa: An Analysis of Gender, Age, and Marital, Employment, and Educational Status
title_full Sociodemographic Disparities in the Prevalence of Metabolic Syndrome in Rural South Africa: An Analysis of Gender, Age, and Marital, Employment, and Educational Status
title_fullStr Sociodemographic Disparities in the Prevalence of Metabolic Syndrome in Rural South Africa: An Analysis of Gender, Age, and Marital, Employment, and Educational Status
title_full_unstemmed Sociodemographic Disparities in the Prevalence of Metabolic Syndrome in Rural South Africa: An Analysis of Gender, Age, and Marital, Employment, and Educational Status
title_short Sociodemographic Disparities in the Prevalence of Metabolic Syndrome in Rural South Africa: An Analysis of Gender, Age, and Marital, Employment, and Educational Status
title_sort sociodemographic disparities in the prevalence of metabolic syndrome in rural south africa an analysis of gender age and marital employment and educational status
topic metabolic syndrome
socioeconomic status
joint interim statement
prevalence
url https://www.mdpi.com/2673-4168/4/4/38
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