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Multimorbidity patterns in South Africa: A latent class analysis

INTRODUCTION: South Africa has the largest burden of HIV worldwide and has a growing burden of non-communicable diseases; the combination of which may lead to diseases clustering in ways that are not seen in other regions. This study sought to identify common disease classes and sociodemographic and...

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Autores principales: Roomaney, Rifqah Abeeda, van Wyk, Brian, Cois, Annibale, Pillay van-Wyk, Victoria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9875075/
https://www.ncbi.nlm.nih.gov/pubmed/36711391
http://dx.doi.org/10.3389/fpubh.2022.1082587
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author Roomaney, Rifqah Abeeda
van Wyk, Brian
Cois, Annibale
Pillay van-Wyk, Victoria
author_facet Roomaney, Rifqah Abeeda
van Wyk, Brian
Cois, Annibale
Pillay van-Wyk, Victoria
author_sort Roomaney, Rifqah Abeeda
collection PubMed
description INTRODUCTION: South Africa has the largest burden of HIV worldwide and has a growing burden of non-communicable diseases; the combination of which may lead to diseases clustering in ways that are not seen in other regions. This study sought to identify common disease classes and sociodemographic and lifestyle factors associated with each disease class. METHODS: Data were analyzed from the South African Demographic and Health Survey 2016. A latent class analysis (LCA) was conducted using nine disease conditions. Sociodemographic and behavioral factors associated with each disease cluster were explored. All analysis was conducted in Stata 15 and the LCA Stata plugin was used to conduct the latent class and regression analysis. RESULTS: Multimorbid participants were included (n = 2 368). Four disease classes were identified: (1) HIV, Hypertension and Anemia (comprising 39.4% of the multimorbid population), (2) Anemia and Hypertension (23.7%), (3) Cardiovascular-related (19.9%) and (4) Diabetes and Hypertension (17.0%). Age, sex, and lifestyle risk factors were associated with class membership. In terms of age, with older adults were less likely to belong to the first class (HIV, Hypertension and Anemia). Males were more likely to belong to Class 2 (Anemia and Hypertension) and Class 4 (Diabetes and Hypertension). In terms of alcohol consumption, those that consumed alcohol were less likely to belong to Class 4 (Diabetes and Hypertension). Current smokers were more likely to belong to Class 3 (Cardiovascular-related). People with a higher body mass index tended to belong to Class 3 (Cardiovascular-related) or the Class 4 (Diabetes and Hypertension). CONCLUSION: This study affirmed that integrated care is urgently needed, evidenced by the largest disease class being an overlap of chronic infectious diseases and non-communicable diseases. This study also highlighted the need for hypertension to be addressed. Tackling the risk factors associated with hypertension could avert an epidemic of multimorbidity.
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spelling pubmed-98750752023-01-26 Multimorbidity patterns in South Africa: A latent class analysis Roomaney, Rifqah Abeeda van Wyk, Brian Cois, Annibale Pillay van-Wyk, Victoria Front Public Health Public Health INTRODUCTION: South Africa has the largest burden of HIV worldwide and has a growing burden of non-communicable diseases; the combination of which may lead to diseases clustering in ways that are not seen in other regions. This study sought to identify common disease classes and sociodemographic and lifestyle factors associated with each disease class. METHODS: Data were analyzed from the South African Demographic and Health Survey 2016. A latent class analysis (LCA) was conducted using nine disease conditions. Sociodemographic and behavioral factors associated with each disease cluster were explored. All analysis was conducted in Stata 15 and the LCA Stata plugin was used to conduct the latent class and regression analysis. RESULTS: Multimorbid participants were included (n = 2 368). Four disease classes were identified: (1) HIV, Hypertension and Anemia (comprising 39.4% of the multimorbid population), (2) Anemia and Hypertension (23.7%), (3) Cardiovascular-related (19.9%) and (4) Diabetes and Hypertension (17.0%). Age, sex, and lifestyle risk factors were associated with class membership. In terms of age, with older adults were less likely to belong to the first class (HIV, Hypertension and Anemia). Males were more likely to belong to Class 2 (Anemia and Hypertension) and Class 4 (Diabetes and Hypertension). In terms of alcohol consumption, those that consumed alcohol were less likely to belong to Class 4 (Diabetes and Hypertension). Current smokers were more likely to belong to Class 3 (Cardiovascular-related). People with a higher body mass index tended to belong to Class 3 (Cardiovascular-related) or the Class 4 (Diabetes and Hypertension). CONCLUSION: This study affirmed that integrated care is urgently needed, evidenced by the largest disease class being an overlap of chronic infectious diseases and non-communicable diseases. This study also highlighted the need for hypertension to be addressed. Tackling the risk factors associated with hypertension could avert an epidemic of multimorbidity. Frontiers Media S.A. 2023-01-11 /pmc/articles/PMC9875075/ /pubmed/36711391 http://dx.doi.org/10.3389/fpubh.2022.1082587 Text en Copyright © 2023 Roomaney, van Wyk, Cois and Pillay van-Wyk. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Roomaney, Rifqah Abeeda
van Wyk, Brian
Cois, Annibale
Pillay van-Wyk, Victoria
Multimorbidity patterns in South Africa: A latent class analysis
title Multimorbidity patterns in South Africa: A latent class analysis
title_full Multimorbidity patterns in South Africa: A latent class analysis
title_fullStr Multimorbidity patterns in South Africa: A latent class analysis
title_full_unstemmed Multimorbidity patterns in South Africa: A latent class analysis
title_short Multimorbidity patterns in South Africa: A latent class analysis
title_sort multimorbidity patterns in south africa: a latent class analysis
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9875075/
https://www.ncbi.nlm.nih.gov/pubmed/36711391
http://dx.doi.org/10.3389/fpubh.2022.1082587
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