The economic burden, patients' well-being, and social determinants related to diabetes in South Africa

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2024

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University of Cape Town

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Background: The health systems in Sub-Saharan Africa (SSA) are confronted by a growing prevalence of diabetes mellitus, with an estimated 24 million adults affected in 2021, a number expected to more than double by 2045. This rise in diabetes not only increases the risk of premature death, but also significantly reduces the quality of life and work productivity. South Africa is leading the diabetes epidemic in SSA, with the incidence rate increasing both in urban and rural settings, equally affecting both genders. While diabetes imposes high levels of health, financial and economic burdens, there is a dearth of studies focusing on identifying and analysing the factors that predict or influence a patient's well-being and quantifying productivity loss in relation to diabetes, particularly in SSA. Objectives: This thesis aims to evaluate the economic and well-being burden of diabetes in South Africa, focusing on productivity impacts, associated social determinants on patient outcomes and predictors of quality of life. The specific objectives are: firstly, to use population life table modelling to estimate the impact of type 2 diabetes (T2D) on the South African population, particularly in terms of productivity-adjusted life of years (PALYs) metric; secondly, to review and synthesise information regarding the costs and cost-effectiveness of managing T2D in SSA to enhance awareness, optimise resource allocation, and support evidence-based decision-making; thirdly, to investigate the role of social determinants of health (SDoH) in diabetes self-care management practices, emphasising the importance of maintaining optimal glycemic control; and lastly, to assess health-related quality of life (HRQoL) and associated factors among people with diabetes in South Africa; lastly, to develop locally relevant utility score valuations for more accurate economic evaluations and healthcare decision-making in South Africa. Methods: The thesis combined diverse methodological approaches to investigate the impact of T2D in South Africa. Life table modelling was used to simulate the health trajectory of individuals aged 20 to 65 with T2D, comparing cohorts with and without diabetes in terms of excess deaths, years of life lost (YLL), and PALYs. These simulations included adjustments 2 for variables like Gross Domestic Product (GDP), productivity indices, labour force dropout, and mortality risks, using data from the International Diabetes Federation (IDF), Statistics South Africa (Stats SA), and other sources, with the World Health Organisation (WHO) 3% annual discount rate for YLL and PALYs applied. For the second objective, a comprehensive systematic literature review, encompassing databases like PubMed-Medline and Google Scholar from 2010 to 2022, analysed the economic aspects of T2D management. Costs were normalised to 2023 US dollars, considering inflation and exchange rates. The third and fourth objectives utilised cross-sectional data of 539 people living with diabetes (PLWD) from urban and rural primary healthcare (PHC) facilities in Western Cape, South Africa. The third objective focused on assessing HRQoL using the EuroQol-3 Dimensions Questionnaire (EQ-5D-3L). The EQ-5D-3L responses were meticulously converted into a unified summary index score employing the UK time trade-off value set. HRQoL was assessed using the ordinal logistic regression. Lastly, the fourth objective explored the influence of SDoH on people with diabetes. Self-care management and adherence to recommended activities were measured, ranging from '0' (never) to '7' (daily adherence). The study employed binary and multinomial logistic regression analyses to investigate the interplay between SDoH, self-management, self-care management and self-care guidelines. Results: In 2019, T2D affected 9.5% of the working-age population in South Africa, totalling 3.2 million individuals. Projections indicate that T2D will lead to 669,427 excess deaths, a loss of 6.2 million years of life (9.3%), and 13 million productivity-adjusted life years (PALYs, 30.6%) by the retirement age of this cohort. Economically, T2D's impact is significant, with the loss of PALYs estimated at US$223 billion or US$69,875 per person, based on 2019's GDP per full-time employee. In the systematic review, most studies assessed costs from the provider perspective (direct and outpatient costs) and reported T2D costs as enormous in SSA. The annual cost ranged from $337.50 for basic medical care of uncomplicated T2D to $2330.74 total provider cost per patient. The highest burden was among individuals in the low-income quantile. Furthermore, analysis utilising cross-sectional data of 539 participants older than 18 years receiving care from rural and urban clinics in the Western Cape, South Africa, revealed that healthcare utilisation was inversely related to diabetes self-care scores, indicating that patients with less frequent healthcare visits tended to have higher self-care scores. SDoH factors such as urban residency, education level, and obesity status were significant determinants of self-care guidelines. Specifically, urban residency (AOR=0.50; 95%CI= 0.29, 0.88; p=0.03), secondary education (AOR=1.13; 95%CI= 1.02, 2.03; p=0.05), and being obese 3 (AOR=0.43; 95%CI= 0.19, 1.00; p=0.03) were associated with varying levels of self-care. Additionally, food insecurity and long travel distances to healthcare facilities negatively impacted self-care adherence, while having a stable house was positively associated with higher self-care management. Regarding HRQoL, the study's participants had a mean utility score of 0.85. Males reported higher HRQoL compared to females (AOR=1.64; 95%CI= 0.96, 2.80; p= 0.07), and urban residents had lower HRQoL than rural (AOR= 0.41; 95%CI= 0.27, 0.63; p<0.01). Having at least primary education (AOR= 0.53; 95%CI= 0.36, 0.79; p<0.01) is associated with lower HRQoL, while higher AUDIT score correlated with increased HRQoL (AOR= 1.89; 95%CI= 1.13, 3.18; p= 0.02). Factors like higher self-efficacy and severe mental health issues were significantly associated with HRQoL, with the latter predicting very low HRQoL (AOR= 18.31; 95%CI= 2.21, 152.08; p= 0.01). Other factors, including body mass index (BMI), marital status, housing stability, and food security, showed no significant impact on HRQoL. Conclusions: This series of studies emphasises the multifaceted impact of diabetes in South Africa, spanning public health, economics, individual well-being, and Social Determinants of Health. The findings call for a multi-pronged strategy encompassing prevention, effective management, and a broader socio-economic approach to tackle the diabetes epidemic. By addressing these areas, it is possible to mitigate the escalating impact of diabetes in South Africa and improve overall health outcomes for individuals living with this chronic condition.
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