Multimorbidity patterns in South Africa: A latent class analysis
IntroductionSouth 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 l...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2022.1082587/full |
| _version_ | 1797956004880580608 |
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| author | Rifqah Abeeda Roomaney Rifqah Abeeda Roomaney Brian van Wyk Annibale Cois Annibale Cois Victoria Pillay van-Wyk |
| author_facet | Rifqah Abeeda Roomaney Rifqah Abeeda Roomaney Brian van Wyk Annibale Cois Annibale Cois Victoria Pillay van-Wyk |
| author_sort | Rifqah Abeeda Roomaney |
| collection | DOAJ |
| description | IntroductionSouth 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.MethodsData 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.ResultsMultimorbid 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).ConclusionThis 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. |
| first_indexed | 2024-04-10T23:43:07Z |
| format | Article |
| id | doaj.art-e61420061e9c4f1cbdca2481df7d8102 |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-04-10T23:43:07Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-e61420061e9c4f1cbdca2481df7d81022023-01-11T06:15:20ZengFrontiers Media S.A.Frontiers in Public Health2296-25652023-01-011010.3389/fpubh.2022.10825871082587Multimorbidity patterns in South Africa: A latent class analysisRifqah Abeeda Roomaney0Rifqah Abeeda Roomaney1Brian van Wyk2Annibale Cois3Annibale Cois4Victoria Pillay van-Wyk5Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South AfricaSchool of Public Health, University of the Western Cape, Cape Town, South AfricaSchool of Public Health, University of the Western Cape, Cape Town, South AfricaBurden of Disease Research Unit, South African Medical Research Council, Cape Town, South AfricaDivision of Health Systems and Public Health, Department of Global Health, University of Stellenbosch, Stellenbosch, South AfricaBurden of Disease Research Unit, South African Medical Research Council, Cape Town, South AfricaIntroductionSouth 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.MethodsData 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.ResultsMultimorbid 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).ConclusionThis 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.https://www.frontiersin.org/articles/10.3389/fpubh.2022.1082587/fullmultimorbiditydisease patternsdisease clusterslatent class analysisprevalenceSouth Africa |
| spellingShingle | Rifqah Abeeda Roomaney Rifqah Abeeda Roomaney Brian van Wyk Annibale Cois Annibale Cois Victoria Pillay van-Wyk Multimorbidity patterns in South Africa: A latent class analysis Frontiers in Public Health multimorbidity disease patterns disease clusters latent class analysis prevalence South Africa |
| 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 | multimorbidity disease patterns disease clusters latent class analysis prevalence South Africa |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2022.1082587/full |
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