Extended cost-effectiveness analysis of interventions to improve uptake of diabetes services in South Africa.

The rising prevalence of diabetes in South Africa (SA), coupled with significant levels of unmet need for diagnosis and treatment, results in high rates of diabetes-associated complications. Income status is a determinant of utilization of diagnosis and treatment services, with transport costs and loss of wages being key barriers to care. A conditional cash transfer (CCT) programme, targeted to compensate for such costs, may improve service utilization. We applied extended cost-effectiveness analysis (ECEA) methods and used a Markov model to compare the costs, health benefits and financial risk protection (FRP) attributes of a CCT programme. A population was simulated, drawing from SA-specific data, which transitioned yearly through various health states, based on specific probabilities obtained from local data, over a 45-year time horizon. Costs and disability-adjusted life years (DALYs) were applied to each health state. Three CCT programme strategies were simulated and compared to a 'no programme' scenario: (1) covering diagnosis services only; (2) covering treatment services only; (3) covering both diagnosis and treatment services. Cost-effectiveness was reported as incremental net monetary benefit (INMB) using a cost-effectiveness threshold of USD3015 per DALY for SA, while FRP outcomes were reported as catastrophic health expenditure (CHE) cases averted. Distributions of the outcomes were reported by income quintile and sex. Covering both diagnosis and treatment services for the bottom two quintiles resulted in the greatest INMB (USD22 per person) and the greatest CHE cases averted. There were greater FRP benefits for women compared to men. A CCT programme covering diabetes diagnosis and treatment services was found to be cost-effective, when provided to the poorest 40% of the SA population. ECEA provides a useful platform for including equity considerations to inform priority setting and implementation policies in SA.

The role of structural racism and geographical inequity in diabetes outcomes.

Diabetes is pervasive, exponentially growing in prevalence, and outpacing most diseases globally. In this Series paper, we use new theoretical frameworks and a narrative review of existing literature to show how structural inequity (structural racism and geographical inequity) has accelerated rates of diabetes disease, morbidity, and mortality globally. We discuss how structural inequity leads to large, fixed differences in key, upstream social determinants of health, which influence downstream social determinants of health and resultant diabetes outcomes in a cascade of widening inequity. We review categories of social determinants of health with known effects on diabetes outcomes, including public awareness and policy, economic development, access to high-quality care, innovations in diabetes management, and sociocultural norms. We also provide regional perspectives, grounded in our theoretical framework, to highlight prominent, real-world challenges.

Multimorbidity matters in low and middle-income countries.

Multimorbidity is a complex challenge affecting individuals, families, caregivers, and health systems worldwide. The burden of multimorbidity is remarkable in low- and middle-income countries (LMICs) given the many existing challenges in these settings. Investigating multimorbidity in LMICs poses many challenges including the different conditions studied, and the restriction of data sources to relatively few countries, limiting comparability and representativeness. This has led to a paucity of evidence on multimorbidity prevalence and trends, disease clusters, and health outcomes, particularly longitudinal outcomes. In this paper, based on our experience of investigating multimorbidity in LMICs contexts, we discuss how the structure of the health system does not favor addressing multimorbidity, and how this is amplified by social and economic disparities and, more recently, by the COVID-19 pandemic. We argue that generating epidemiologic data around multimorbidity with similar methods and definition is essential to improve comparability, guide clinical decision-making and inform policies, research priorities, and local responses. We call for action on policy to refinance and prioritize primary care and integrated care as the center of multimorbidity.

Sociodemographic, socioeconomic, clinical and behavioural predictors of body mass index vary by sex in rural South African adults-findings from the AWI-Gen study.

BACKGROUND: Despite increasing obesity in South African adults, data on the prevalence and determinants of body mass index (BMI) from rural communities, home to a significant proportion of the population, are scarce. OBJECTIVES: To investigate overall and sex-specific determinants of BMI in a rural adult South African population undergoing rapid social and epidemiological transitions. METHODS: Baseline cross-sectional demographic, socioeconomic, anthropometric, clinical and behavioural data were collected between 2015 and 2016 from 1388 individuals aged 40-60 years and resident in the Agincourt sub-district of Mpumalanga province, a setting typical of rural northeast South Africa. A Health and Socio-Demographic Surveillance System (HDSS) underpins the sub-district and contributes to the Africa Wits-INDEPTH partnership for Genomic Studies (AWI-Gen). Linear regression was used to investigate univariate associations between log-transformed BMI and individual variables and multiple linear regression was used to investigate independent predictors of BMI overall and in sex-stratified analyses. RESULTS: Median BMI was significantly higher in females (28.7 kg/m2[95% CI 24.2-33.2] vs 23.0 kg/m2[95% CI 20.3-26.8];p < 0.001) with male sex associated with 17% lower BMI. In sex-stratified multiple linear regression models, compared to those never married, BMI was 7% higher in currently married males and 6% in currently married females. Current smoking in men and former smoking in women were associated with reductions in BMI of 13% and 26% respectively, compared with non-smokers. Higher educational attainment in women and higher socioeconomic status in men were both associated with higher BMI, while being HIV-positive and alcohol consumption in women were associated lower BMI. CONCLUSIONS: Female sex strongly predicts higher BMI in this rural African population. While some predictors of higher BMI differ by sex, married individuals in both sexes had a higher BMI, suggesting that, in addition to developing sex-specific interventions to combat overweight and obesity, targeting married couples may result in reduction in population BMI.

Regional and sex-specific variation in BMI distribution in four sub-Saharan African countries: The H3Africa AWI-Gen study.

BACKGROUND: African populations are characterised by diversity at many levels including: demographic history, genetic ancestry, language, wealth, socio-political landscape, culture and behaviour. Several of these have a profound impact on body fat mass. Obesity, a key risk factor for cardiovascular and metabolic diseases, in the wake of the epidemiological and health transitions across the continent, requires detailed analysis together with other major risk factors. OBJECTIVE: To compare regional and sex-specific body mass index (BMI) distributions, using a cross-sectional study design, in adults aged 40-60 years across six study sites in four sub-Saharan African (SSA) countries and to compare the determinants of BMI at each. METHODS: Anthropometric measurements were standardised across sites and BMI calculated. Median BMI and prevalence of underweight, lean, overweight and obesity were compared between the sexes and across sites. Data from multivariable linear regression models for the principal determinants of BMI were summarised from the site-specific studies. RESULTS: BMI was calculated in 10,702 participants (55% female) and was significantly higher in women than men at nearly all sites. The highest prevalence of obesity was observed at the three South African sites (42.3-66.6% in women and 2.81-17.5% in men) and the lowest in West Africa (1.25-4.22% in women and 1.19-2.20% in men). Across sites, higher socio-economic status and educational level were associated with higher BMI. Being married and increased dietary intake were associated with higher BMI in some communities, whilst smoking and alcohol intake were associated with lower BMI, as was HIV infection in the regions where it was prevalent. CONCLUSION: In SSA there is a marked variation in the prevalence of obesity both regionally and between men and women. Our data suggest that the drive for social upliftment within Africa will be associated with rising levels of obesity, which will require the initiation of targeted sex-specific intervention programmes across specific African communities.

Applying a private sector capitation model to the management of type 2 diabetes in the South African public sector: a cost-effectiveness analysis.

BACKGROUND: Diabetes mellitus contributes substantially to the non-communicable disease burden in South Africa. The proposed National Health Insurance system provides an opportunity to consider the development of a cost-effective capitation model of care for patients with type 2 diabetes. The objective of the study was to determine the potential cost-effectiveness of adapting a private sector diabetes management programme (DMP) to the South African public sector. METHODS: Cost-effectiveness analysis was undertaken with a public sector model of the DMP as the intervention and a usual practice model as the comparator. Probabilistic modelling was utilized for incremental cost-effectiveness ratio analysis with life years gained selected as the outcome. Secondary data were used to design the model while cost information was obtained from various sources, taking into account public sector billing. RESULTS: Modelling found an incremental cost-effectiveness ratio (ICER) of ZAR 8 356 (USD 1018) per life year gained (LYG) for the DMP against the usual practice model. This fell substantially below the Willingness-to-Pay threshold with bootstrapping analysis. Furthermore, a national implementation of the intervention could potentially result in an estimated cumulative gain of 96 997 years of life (95% CI 71 073 years - 113 994 years). CONCLUSIONS: Probabilistic modelling found the capitation intervention to be cost-effective, with an ICER of ZAR 8 356 (USD 1018) per LYG. Piloting the service within the public sector is recommended as an initial step, as this would provide data for more accurate economic evaluation, and would also allow for qualitative analysis of the programme.