5 research outputs found

    Inequity in the distribution of non-communicable disease multimorbidity in adults in South Africa: An analysis of prevalence and patterns

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    The present study examined the prevalence and patterns of noncommunicable disease multimorbidity by wealth quintile among adults in South Africa. The South African National Income Dynamics Study Wave 5 was conducted in 2017 to examine the livelihoods of individuals and households. We analysed data in people aged 15 years and older (N = 27,042), including self-reported diagnosis of diabetes, stroke, heart disease and anthropometric measurements. Logistic regression and latent class analysis were used to analyse factors associated with multimorbidity and common disease patterns

    Prevalence of multimorbidity in South Africa: A systematic review protocol

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    Introduction Multimorbidity has increased globally over the past two decades, due to ageing populations and increased burden of non-communicable diseases (NCDs). In a country like South Africa, with a growing burden of NCDs and a high prevalence of HIV, information on multimorbidity can improve planning for healthcare delivery and utilisation, and reduce costs in the context of constrained health resources. This review aims to synthesise prevalence studies on multimorbidity, and identify dominant clusters and trends of multimorbidity in South Africa. Methods and analysis We will search electronic bibliographic databases (PubMed, Scopus, JSTOR, POPLINE, PsycINFO, ScienceDirect, Web of Science and CINAHL), and the reference lists of included articles. Two researchers will independently screen title and abstracts, and then full text to identify studies published before and in 2020 that report on prevalence of multimorbidity in South Africa. Risk of bias assessments will be done for each study. Information on the prevalence of multimorbidity and disease clusters will be extracted from each study

    A model-based approach to estimating the prevalence of disease combinations in South Africa

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    Background: The development of strategies to better detect and manage patients with multiple long-term conditions requires estimates of the most prevalent condition combinations. However, standard meta-analysis tools are not well suited to synthesising heterogeneous multimorbidity data. Methods: We developed a statistical model to synthesise data on associations between diseases and nationally representative prevalence estimates and applied the model to South Africa. Published and unpublished data were reviewed, and meta-regression analysis was conducted to assess pairwise associations between 10 conditions: arthritis, asthma, chronic obstructive pulmonary disease (COPD), depression, diabetes, HIV, hypertension, ischaemic heart disease (IHD), stroke and tuberculosis. The national prevalence of each condition in individuals aged 15 and older was then independently estimated, and these estimates were integrated with the ORs from the meta-regressions in a statistical model, to estimate the national prevalence of n a statistical model, to estimate the national prevalence of each condition combination. Results: The strongest disease associations in South Africa are between COPD and asthma (OR 14.6, 95% CI 10.3 to 19.9), COPD and IHD (OR 9.2, 95% CI 8.3 to 10.2) and IHD and stroke (OR 7.2, 95% CI 5.9 to 8.4). The most prevalent condition combinations in individuals aged 15+ are hypertension and arthritis (7.6%, 95% CI 5.8% to 9.5%), hypertension and diabetes (7.5%, 95% CI 6.4% to 8.6%) and hypertension and HIV (4.8%, 95% CI 3.3% to 6.6%). The average numbers of comorbidities are greatest in the case of COPD (2.3, 95% CI 2.1 to 2.6), stroke (2.1, 95% CI 1.8 to 2.4) and IHD (1.9, 95% CI 1.6 to 2.2). Conclusion: South Africa has high levels of HIV, hypertension, diabetes and arthritis, by international standards, and these are reflected in the most prevalent condition combinations. However, less prevalent conditions such as COPD, stroke and IHD contribute disproportionately to the multimorbidity burden, with high rates of comorbidity. This modelling approach can be used in other settings to characterise the most important disease combinations and levels of comorbidity

    Epidemiology of lower respiratory infection and pneumonia in South Africa (1997 – 2015) : a systematic review protocol

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    CITATION: Roomaney, R. A., et al. 2016. Epidemiology of lower respiratory infection and pneumonia in South Africa (1997 – 2015) : a systematic review protocol. BMJ Open, 6:e012154, doi:10.1136/bmjopen-2016-012154.The original publication is available at http://bmjopen.bmj.comIntroduction: Lower respiratory infections (LRIs) and pneumonia are among the leading causes of death worldwide, especially in children aged under 5 years, and these patterns are reflected in the South African population. Local epidemiological data for LRIs and pneumonia are required to inform the Second National Burden of Disease Study underway in South Africa. The aim of this systematic review is to identify published studies reporting the prevalence, incidence, case fatality, duration or severity of LRI and pneumonia in adults and children in South Africa. Methods and analysis: Electronic database searches will be conducted to obtain studies reporting on the prevalence, incidence, case fatality, duration and severity of LRI and pneumonia in South Africa between January 1997 and December 2015. Studies that are assessed to have moderate or low risk of bias will be included in a meta-analysis, if appropriate. Where meta-analysis is not possible, the articles will be described narratively. Subgroup analysis (eg, age groups) will also be conducted where enough information is available. Ethics and dissemination: This systematic review will only include published data with no linked patientlevel information; thus, no ethics approval is required. The findings will be used to calculate the burden of disease attributed to LRI and pneumonia in South Africa and will highlight the type of epidemiological data available in the country. The article will be disseminated in a peer-reviewed publication.http://bmjopen.bmj.com/content/6/9/e012154Publisher's versio
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