With improved access to antiretroviral treatment (ART), adults with HIV live longer to reach older age. The number of older adults living with HIV is increasing steadily, giving rise to a new population of interest in HIV research and for invigorated considerations in health service delivery and policy. We analysed the profile of comorbidities in older people (50 years and older) living with HIV in South Africa. We conducted a secondary analysis of all individuals over 15 years who tested HIV positive in the Fifth South African National HIV Prevalence, Incidence, Behaviour and Communication Survey, 2017. We conducted multivariate logistic regression to determine the factors associated with having HIV comorbidity using Stata 15.0 software. We entered 3755 people living with HIV into the analysis, of whom 18.3% (n = 688) were 50 years or older. Older adults had four times greater odds (OR = 4.7 (3.1–7.0)) of having an HIV comorbidity compared to younger adults. Being female (OR = 1.6 (1.1–2.4)) and living in an urban area (OR = 2.6 (1.8–3.7)) increased the odds of HIV comorbidity. Older adults with HIV require comprehensive health care to deal with multimorbidity, to maximise the benefits gained by advances in HIV therapies.

Objectives To review prevalence studies of multimorbidity in South Africa to identify prevalence estimates, common disease clusters and factors associated with multimorbidity. Design Systematic review. Setting South Africa (general community and healthcare facilities). Data sources Articles were retrieved from electronic databases (PubMed, Web of Science, Scopus, CINAHL, Science Direct and JSTOR). Eligibility criteria Studies addressing the prevalence of multimorbidity in South Africa were eligible for inclusion. A systematic search was done in various databases up to December 2020. A risk of bias assessment was conducted for each article using a modified checklist. Study selection Two researchers independently screened titles and abstracts; assessed the risk of bias of each study and extracted data. Included studies were described using a narrative synthesis. Results In total, 1407 titles were retrieved; of which 10 articles were included in the narrative synthesis. Six studies had a low risk of bias and three had a moderate risk of bias. One study was not assessed for risk of bias, because there was no criteria that apply to routine health information systems. Three of the included studies were population-based surveys, four were community-based cohorts and three cross-sectional studies of health facility data. The prevalence of multimorbidity was low to moderate (3%–23%) in studies that included younger people or had a wide range of selected age groups; and moderate to high (30%–87%) in studies of older adults. The common disease clusters were hypertension and diabetes, hypertension and HIV, and TB and HIV. Conclusion All studies indicated that multimorbidity is a norm in South Africa, especially among older adults. Hypertension is the main driver of multimorbidity. Research on multimorbidity in South Africa needs to be strengthened with high-quality study designs. PROSPERO registration number CRD42020196895.

Multimorbidity is a global research priority, yet relatively little is known about it in low and middle income countries. South Africa has the largest burden of HIV worldwide but also has a growing burden of non-communicable diseases; potentially leading to uncommon disease combinations. Information about the prevalence of multimorbidity and factors associated with it can assist in healthcare planning and targeting groups of people for interventions. This study aimed to determine the prevalence of multimorbidity by age and sex, as well as factors associated with multimorbidity in people 15 years and older. This study analyses the nationally representative 2016 South African Demographic Health Survey. The sample included 10 336 people who participated in the Adult Health questionnaire and approximately 7 961 people who provided biomarkers. Multivariate logistic regression was used to measure the association of multimorbidity with age, sex, living in an urban or rural area, education level, wealth level, employment status, body mass index, current alcohol or tobacco use. All analyses were conducted using STATA 15. Multimorbidity was present in 20.7% (95% CI: 19.5%– 21.9%) of participants; in 14.8% (95% CI: 13.4% - 16.3%) of males and 26.2% (95% CI: 24.7–27.7%) of females. Multimorbidity increased with age; with the highest odds in the 55–64 years old age group (OR: 24.910, 95% CI: 14.901–41.641, p < 0.001) compared to those aged 15–24 years. The odds of multimorbidity was also higher in young females compared to young males (OR: 2.734, 95% CI: 1.50–4.99, p = 0.001). Possessing tertiary education (OR: 0.722, 95% CI: 0.537–0.97, p = 0.031), being employed (OR: 0.813, 95% CI: 0.675–0.979, p = 0.029) or currently using alcohol (OR: 0.815, 95% CI: 0.686–0.968, p = 0.02) was protective against multimorbidity. Multimorbidity is prevalent within the South African population, with females and older adults being most affected. However, multimorbidity is also observed in younger adults and most likely driven by the high prevalence of HIV and hypertension.

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.

Multimorbidity is defined as the co-existence of multiple health conditions in one person. However, its use in research has been predominantly applied to non-communicable diseases, because research was conducted almost exclusively in developed countries. More recently, infectious diseases of long duration, such as human immunodeficiency virus (HIV), have also been included in the conceptualization of multimorbidity. While multimorbidity is a growing area of research globally; much less is known about the phenomenon in low and middle-income countries (LMICs) where disease burdens are heavily impacted by HIV. Health systems and services tend to be constrained in LMICs and information on disease patterns are important to better prioritize services. This commentary aims to describe the changing conceptualization of multimorbidity, the dearth of research into multimorbidity in LMICs and how the knowledge generated by research in LMICs can contribute to the global understanding of multimorbidity. LMICs can play a key role in the implementation of integration research.

Introduction: Information pertaining to multimorbidity is frequently informed by studies from high income countries and it is unclear how these findings relate to low and middle income countries, where the burden of infectious disease is high. South Africa has a quadruple burden of disease which includes a high HIV prevalence and a growing burden of non-communicable diseases. This study aimed to analyse the prevalence and patterns (disease classes or clusters) of multimorbidity in South Africa.Methods: A secondary analysis of individuals over the age of 15 years who participated in the Fifth South African National HIV Prevalence, Incidence, Behavior and Communication Survey, 2017 (SABSSM 2017) was done. Six disease conditions were identified in the analysis (cancer, diabetes, heart disease, hypertension/high blood pressure, tuberculosis, and HIV). Chi-square tests were used to test for the differences in disease prevalence by sex. Common disease patterns were identified using a latent class analysis.Results: The sample included 27,896 participants, of which 1,837 had comorbidity or multimorbidity. When taking population-weighting into account, multimorbidity was present in 5.9% (95% CI: 5.4–6.4) of the population The prevalence of multimorbidity tended to be higher among females and increased with age, reaching 21.9% in the oldest age group (70+). The analyses identified seven distinct disease classes in the population. The largest class was “Diabetes and Hypertension” (36.3%), followed by “HIV and Hypertension” (31.0%), and “Heart disease and Hypertension” (14.5%). The four smaller classes were: “HIV, Diabetes, and Heart disease” (6.9%), “TB and HIV” (6.3%), “Hypertension, TB, and Cancer” (2.8%), and “All diseases except HIV” (2.2%).Conclusion: As the South African population continues to age, the prevalence of multimorbidity is likely to increase which will further impact the health care system. The prevalence of multimorbidity in the population was relatively low but reached up to 20% in the oldest age groups. The largest disease cluster was the combination of diabetes and hypertension; followed by HIV and hypertension. The gains in improving adherence to antiretrovirals amongst treatment-experienced people living with HIV, should be expanded to include compliance with lifestyle/behavioral modifications to blood pressure and glucose control, as well as adherence to anti-hypertension and anti-diabetic medication. There is an urgent need to improve the early diagnosis and treatment of disease in the South African population.