Research Outputs (Public Health)

Permanent URI for this collectionhttps://hdl.handle.net/10539/36984

This collection includes content from the MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt) which has been operating the Agincourt health and demographic surveillance system since 1992. Work has evolved since then into a robust research infrastructure supporting advanced community-based research with studies ranging from the biomedical to the ethnographic, making rural voices heard.

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    Predictors of health care use by adults 50 years and over in a rural South African setting
    (2014) Ameh, S; Kahn, K; Tollman, S.M; et al
    BACKGROUND: South Africa's epidemiological transition is characterised by an increasing burden of chronic communicable and non-communicable diseases. However, little is known about predictors of health care use (HCU) for the prevention and control of chronic diseases among older adults. OBJECTIVE: To describe reported health problems and determine predictors of HCU by adults aged 50+ living in a rural sub-district of South Africa. DESIGN: A cross-sectional study to measure HCU was conducted in 2010 in the Agincourt sub-district of Mpumalanga Province, an area underpinned by a robust health and demographic surveillance system. HCU, socio-demographic variables, reception of social grants, and type of medical aid were measured, and compared between responders who used health care services with those who did not. Predictors of HCU were determined by binary logistic regression adjusted for socio-demographic variables. RESULTS: Seventy-five percent of the eligible adults aged 50+ responded to the survey. Average age of the targeted 7,870 older adults was 66 years (95% CI: 65.3, 65.8), and there were more women than men (70% vs. 30%, p<0.001). All 5,795 responders reported health problems, of which 96% used health care, predominantly at public health facilities (82%). Reported health problems were: chronic non-communicable diseases (41% - e.g. hypertension), acute conditions (27% - e.g. flu and fever), other conditions (26% - e.g. musculoskeletal pain), chronic communicable diseases (3% - e.g. HIV and TB), and injuries (3%). In multivariate logistic regression, responders with chronic communicable disease (OR=5.91, 95% CI: 1.44, 24.32) and non-communicable disease (OR=2.85, 95% CI: 1.96, 4.14) had significantly higher odds of using health care compared with those with acute conditions. Responders with six or more years of education had a two-fold increased odds of using health care (OR=2.49, 95% CI: 1.27, 4.86) compared with those with no formal education. CONCLUSION: Chronic communicable and non-communicable diseases were the most prevalent and main predictors of HCU in this population, suggesting prioritisation of public health care services for chronic diseases among older people in this rural setting.
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    Essential evidence for guiding health system priorities and policies: anticipating epidemiological transition in Africa
    (2014) Byass, P; De Savigny, D; Lopez, A.D; et al
    BACKGROUND: Despite indications that infection-related mortality in sub-Saharan Africa may be decreasing and the burden of non-communicable diseases increasing, the overwhelming reality is that health information systems across most of sub-Saharan Africa remain too weak to track epidemiological transition in a meaningful and effective way. PROPOSALS: We propose a minimum dataset as the basis of a functional health information system in countries where health information is lacking. This would involve continuous monitoring of cause-specific mortality through routine civil registration, regular documentation of exposure to leading risk factors, and monitoring effective coverage of key preventive and curative interventions in the health sector. Consideration must be given as to how these minimum data requirements can be effectively integrated within national health information systems, what methods and tools are needed, and ensuring that ethical and political issues are addressed. A more strategic approach to health information systems in sub-Saharan African countries, along these lines, is essential if epidemiological changes are to be tracked effectively for the benefit of local health planners and policy makers. CONCLUSION: African countries have a unique opportunity to capitalize on modern information and communications technology in order to achieve this. Methodological standards need to be established and political momentum fostered so that the African continent's health status can be reliably tracked. This will greatly strengthen the evidence base for health policies and facilitate the effective delivery of services.