Olufunke Alaba

Utilization of traditional healers in South Africa and costs to patients: Findings from a national household survey

The use of traditional medicine is widespread in developing countries. We report on the utilization of traditional healers, using data obtained in a 2008 national survey of 4762 households in South Africa. Only 1.2 per cent of survey participants reported utilization of traditional healers. Respondents’ reasons for visiting traditional healers included continuity of care and a belief in their effectiveness. Traditional healer utilization rates (0.02 visits per month) were considerably lower compared to utilization rates of public sector clinics (0.18 visits per month) or hospitals (0.09 visits per month). Almost three-quarters of the poorest quintile spent more than 10 per cent of their household expenditure in the previous month on traditional healers. Given the use of two parallel health-care systems, policy-makers should develop strategies to protect poor South Africans from out-of-pocket payments for health care. Simultaneous utilization of these systems evidently absorbs expenditure from low-income households significantly.

The social determinants of multimorbidity in South Africa

IntroductionMultimorbidity is a growing concern worldwide, with approximately 1 in 4 adults affected. Most of the evidence on multimorbidity, its prevalence and effects, comes from high income countries. Not much is known about multimorbidity in low income countries, particularly in sub-Saharan Africa. The aim of this study was to determine the prevalence of multimorbidity and examine its association with various social determinants of health in South Africa.MethodThe data used in this study are taken from the South Africa National Income Dynamic Survey (SA-NIDS) of 2008. Multimorbidity was defined as the coexistence of two or more chronic diseases in an individual. Multinomial logistic regression models were constructed to analyse the relationship between multimorbidity and several indicators including socioeconomic status, area of residence and obesity.ResultsThe prevalence of multimorbidity in South Africa was 4% in the adult population. Over 70% of adults with multimorbidity were females. Factors associated with multimorbidity were social assistance (Odds ratio (OR) 2.35; Confidence Interval (CI) 1.59-3.49), residence (0.65; 0.46-0.93), smoking (0.61; 0.38-0.96); obesity (2.33; 1.60-3.39), depression (1.07; 1.02-1.11) and health facility visits (5.14; 3.75-7.05). Additionally, income was strongly positively associated with multimorbidity. The findings are similar to observations made in studies conducted in developed countries.ConclusionThe findings point to a potential difference in the factors associated with single chronic disease and multimorbidity. Income was consistently significantly associated with multimorbidity, but not single chronic diseases. This should be investigated further in future research on the factors affecting multimorbidity.

Socioeconomic inequalities in adult obesity prevalence in South Africa: a decomposition analysis.

In recent years, there has been a dramatic increase in obesity in low and middle income countries. However, there is limited research in these countries showing the prevalence and determinants of obesity. In this study, we examine the socioeconomic inequalities in obesity among South African adults. We use nationally representative data from the South Africa National Income Dynamic Survey of 2008 to: (1) construct an asset index using multiple correspondence analyses (MCA) as a proxy for socioeconomic status; (2) estimate concentration indices (CI) to measure socioeconomic inequalities in obesity; and (3) perform a decomposition analysis to determine the factors that contribute to socioeconomic related inequalities. Consistent with other studies, we find that women are more obese than men. The findings show that obesity inequalities exist in South Africa. Rich men are more likely to be obese than their poorer counterparts with a concentration index of 0.27. Women on the other hand have similar obesity patterns, regardless of socioeconomic status with CI of 0.07. The results of the decomposition analysis suggest that asset index contributes positively and highly to socio-economic inequality in obesity among females; physical exercise contributes negatively to the socio-economic inequality. In the case of males, educational attainment and asset index contributed more to socio-economic inequalities in obesity. Our findings suggest that focusing on economically well-off men and all women across socioeconomic status is one way to address the obesity problem in South Africa.

Moving towards universal coverage in South Africa? Lessons from a voluntary government insurance scheme

Background : In 2005, the South African government introduced a voluntary, subsidised health insurance scheme for civil servants. In light of the global emphasis on universal coverage, empirical evidence is needed to understand the relationship between new health financing strategies and health care access thereby improving global understanding of these issues. Objectives : This study analysed coverage of the South African government health insurance scheme, the population groups with low uptake, and the individual-level factors, as well as characteristics of the scheme, that influenced enrolment. Methods : Multi-stage random sampling was used to select 1,329 civil servants from the health and education sectors in four of South Africas nine provinces. They were interviewed to determine factors associated with enrolment in the scheme. The analysis included both descriptive statistics and multivariate logistic regression. Results : Notwithstanding the availability of a non-contributory option within the insurance scheme and access to privately-provided primary care, a considerable portion of socio-economically vulnerable groups remained uninsured (57.7% of the lowest salary category). Non-insurance was highest among men, black African or coloured ethnic groups, less educated and lower-income employees, and those living in informal-housing. The relatively poor uptake of the contributory and non-contributory insurance options was mostly attributed to insufficient information, perceived administrative challenges of taking up membership, and payment costs. Conclusion : Barriers to enrolment include insufficient information, unaffordability of payments and perceived administrative complexity. Achieving universal coverage requires good physical access to service providers and appropriate benefit options within pre-payment health financing mechanisms.BACKGROUND In 2005, the South African government introduced a voluntary, subsidised health insurance scheme for civil servants. In light of the global emphasis on universal coverage, empirical evidence is needed to understand the relationship between new health financing strategies and health care access thereby improving global understanding of these issues. OBJECTIVES This study analysed coverage of the South African government health insurance scheme, the population groups with low uptake, and the individual-level factors, as well as characteristics of the scheme, that influenced enrolment. METHODS Multi-stage random sampling was used to select 1,329 civil servants from the health and education sectors in four of South Africas nine provinces. They were interviewed to determine factors associated with enrolment in the scheme. The analysis included both descriptive statistics and multivariate logistic regression. RESULTS Notwithstanding the availability of a non-contributory option within the insurance scheme and access to privately-provided primary care, a considerable portion of socio-economically vulnerable groups remained uninsured (57.7% of the lowest salary category). Non-insurance was highest among men, black African or coloured ethnic groups, less educated and lower-income employees, and those living in informal-housing. The relatively poor uptake of the contributory and non-contributory insurance options was mostly attributed to insufficient information, perceived administrative challenges of taking up membership, and payment costs. CONCLUSION Barriers to enrolment include insufficient information, unaffordability of payments and perceived administrative complexity. Achieving universal coverage requires good physical access to service providers and appropriate benefit options within pre-payment health financing mechanisms.

Explaining health inequalities in South Africa: A political economy perspective

In South Africa inequalities in health have been extensively reported. The poor suffer more ill health than the rich. This paper discusses the need to understand the historical, social and political contexts and power relations that have shaped inequalities in South Africa. This can be achieved in part through a cohesive intersectoral approach that addresses ‘the causes of the causes’. Yet more fundamentally, the authors suggest that success in tackling inequalities in health will only come when existing power structures in South African society are acknowledged.

What do we know about health service utilisation in South Africa

This paper compares data from two household surveys to assess the effect of questionnaire design on estimated use of health services and analyses this across geographic areas and different groups. Deficiencies in the design of Statistics South Africas General Household Survey led to a substantial underestimation of utilisation (capturing less than a third of visits). The South Africa Consortium for Benefit Incidence Analysis survey, which was more comprehensive, indicated that three out of four outpatient visits are to public sector facilities. Medical scheme membership is the most important predictor of using a private provider, particularly for inpatient care. Socioeconomic status and rural versus urban residence also influence overall utilisation rates and use of public versus private providers. It is critical to improve the design of routine household surveys to monitor utilisation patterns during the implementation of the proposed health system reform.

Prevalence of age-adjusted obesity in South Africa and the influence of social determinants: an ecological analysis

Abstract Background Obesity is a major risk factor for a number of non-communicable diseases that are rapidly becoming a public health and economic development concern in developed and developing countries. Assessing prevalence and understanding factors associated with obesity in context are crucial to controlling non-communicable diseases. This study aims to assess the prevalence of obesity in South Africa and investigate individual, household, and community contextual factors associated with obesity. Methods This study combined data from the South Africa National Income Dynamic Survey of 2008 and the South African Index of Multiple Deprivation (SAMID)-2007 using a conceptual hierarchical framework to examine individual economic, psychosocial, social capital, and household indicators as well as neighbourhood economic and environmental factors associated with obesity among South African adults. Findings Age-adjusted obesity (body-mass index >30 kg/m 2 ) prevalence was 21·15%. About 31% (95% CI 30–34) of adult females and 9% (7–11) of adult males were obese. Education, physical activity, and smoking were negatively associated with obesity. Living in less deprived neighbourhoods increased the likelihood of obesity. Increase in adequacy of perceived needs met, which was used as a psychosocial indicator, reduced the odds of obesity. Interpretation The prevalence of obesity is high and should be considered as a serious public health challenge in South Africa. A better understanding of psychosocial influences and structural determinants relating to the environment may be essential in order to control obesity in South Africa. Funding None.

Erratum to: Urban Health Research in Africa: Themes and Priority Research Questions

Oni is with the Division of Public Health Medicine, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa; Smit and Parnell are with the African Centre for Cities, University of Cape Town, Cape Town, South Africa; Matzopoulos is with the Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa; Hunter-Adams and Alaba are with the Health Economics Unit, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa; Pentecost is with the Department of Anthropology, University of Cape Town, Cape Town, South Africa; Pentecost is with the Institute of Social and Cultural Anthropology, University of Oxford, Oxford, UK; Rother is with the Division of Environmental Health and Centre for Environmental and Occupational Health Research, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa; Albertyn is with the Children’s Institute, Department of Paediatrics, University of Cape Town, Cape Town, South Africa; Behroozi is with the Primary Health Care Directorate, University of Cape Town, Cape Town, South Africa; Kaba is with the Division of Health Economics, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa; Kaba is with the Division of Medical Microbiology, Department of Clinical Laboratory Sciences, University of Cape Town, Cape Town, South Africa; van der Westhuizen is with the Alan J Flisher Centre for Public Mental Health, Department of Psychiatry andMental Health, University of Cape Town, Cape Town, South Africa; Shung-King is with the Division of Health Policy and Systems, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa; Levitt is with the Chronic Disease Initiative for Africa and Division of Diabetic Medicine and Endocrinology, Department of Medicine, University of Cape Town, Cape Town, South Africa; Lambert is with the Division of Exercise Science and Sports Medicine, Department of Human Biology, University of Cape Town, Cape Town, South Africa. Correspondence: Tolu Oni, Division of Public Health Medicine, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa. (E-mail: tolullah.oni@uct.ac.za) The online version of the original article can be found at doi:10.1007/s11524-016-0050-0.

A missed wake-up call for the US?

AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH 2011 vol. 35 no. 4