Equity in maternal health in South Africa: analysis of health service access and health status in a national household survey

Background: South Africa is increasingly focused on reducing maternal mortality. Documenting variation in access to maternal health services across one of the most inequitable nations could assist in re-direction of resources. Methods: Analysis draws on a population-based household survey that used multistage-stratified sampling. Women, who in the past two years were pregnant (1113) or had a child (1304), completed questionnaires and HIV testing. Distribution of access to maternal health services and health status across socio-economic, education and other population groups was assessed using weighted data. Findings: Poorest women had near universal antenatal care coverage (ANC), but only 39.6% attended before 20 weeks gestation; this figure was 2.7-fold higher in the wealthiest quartile (95%CI adjusted odds ratio = 1.2-6.1). Women in rural-formal areas had lowest ANC coverage (89.7%), percentage completing four ANC visits (79.7%) and only 84.0% were offered HIV testing. Testing levels were highest among the poorest quartile (90.1% in past two years), but 10% of women above 40 or with low education had never tested. Skilled birth attendant coverage (overall 95.3%) was lowest in the poorest quartile (91.4%) and rural formal areas (85.6%). Around two thirds of the wealthiest quartile, of white and of formally-employed women had a doctor at childbirth, 11-fold higher than the poorest quartile. Overall, only 44.4% of pregnancies were planned, 31.7% of HIV-infected women and 68.1% of the wealthiest quartile. Self-reported health status also declined considerably with each drop in quartile, education level or age group. Conclusions: Aside from early ANC attendance and deficiencies in care in rural-formal areas, inequalities in utilisation of services were mostly small, with some measures even highest among the poorest. Considerably larger differences were noted in maternal health status across population groups. This may reflect differences between these groups in quality of care received, HIV infection and in social determinants of health

The HIV epidemic in South Africa: Key findings from 2017 national population-based survey

South Africa has the largest number of people living with HIV worldwide. South Africa has implemented five population-based HIV prevalence surveys since 2002 aimed at understanding the dynamics and the trends of the epidemic. This paper presents key findings from the fifth HIV prevalence, incidence, and behaviour survey conducted in 2017 following policy, programme, and epidemic change since the prior survey was conducted in 2012. A cross-sectional populationbased household survey collected behavioural and biomedical data on all members of the eligible households. A total of 39,132 respondents from 11,776 households were eligible to participate, of whom 93.6% agreed to be interviewed, and 61.1% provided blood specimens. The provided blood specimens were used to determine HIV status, HIV incidence, viral load, exposure to antiretroviral treatment, and HIV drug resistance. Overall HIV incidence among persons aged 2 years and above was 0.48% which translates to an estimated 231,000 new infections in 2017

HIV Status and Labor Market Participation in South Africa

Because individuals with HIV are more likely to fall into poverty, and the poor may be at higher risk of contracting HIV, simple estimates of the effect of HIV status on economic outcomes will tend to be biased. In this paper, we use two econometric methods based on the propensity score to estimate the causal effect of HIV status on employment outcomes in South Africa. We rely on rich data on sexual behavior and knowledge of HIV from a large national household-based survey, which included HIV testing, to control for systematic differences between HIV-positive and HIV-negative individuals. This paper provides the first nationally representative estimates of the impact of HIV status on labor market outcomes for southern Africa. We find that being HIV-positive is associated with a 6 to 7 percentage point increase in the likelihood of being unemployed. South Africans with less than a high school education are 10 to 11 percentage points more likely to be unemployed if they are HIV-positive. Despite high unemployment rates, being HIV-positive confers a disadvantage and reinforces existing inequalities in South Africa.

Know your HIV epidemic (KYE) report: review of the HIV epidemic in South Africa.

In order to update and consolidate South Africa’s evidence base for HIV-prevention interventions, it was decided by the Government of South Africa to commission a synthesis of the available data on the epidemiology of prevalent and incident HIV infections, and the wider epidemic context of these infections. This know your epidemic (KYE) approach has been successfully implemented in a number of sub-Saharan African countries.2 The process involves a desk review and secondary analysis of existing biological, behavioural and socio-demographic data in order to determine the epidemiology of new HIV infections. KYE reports present key findings and policy and programme recommendations which are grounded in local evidence and aim to support decision-making and improve HIV-prevention results. In 2010, South Africa also conducted a know your response (KYR) review, which critically assessed HIV-prevention policies, programmes and resource allocations. The overall results of this HIV epidemic review and the KYR review will be published in a separate, national KYE/KYR synthesis report

Job Stress, Job Dissatisfaction and Stress Related Illnesses among South African Educators

A ZJER study on job dissatisfaction and job related stress amongst South African educators.The aim of this study was to explore the relationship between self-reported job stress and job dissatisfaction and the prevalence of stress related illnesses and risk factors amongst educators. A cross-sectional survey was conducted in a representative sample of21,307 educators from public schools in South Africa. Self-reported measures of job stress, job satisfaction, and stress-related illnesses (including mental distress) were taken. HIV-antibody tests (ELIZA) and CD-4 count was taken from those educators who agreed to blood specimens. Results indicate that the prevalence of stress-related illnesses were 15.6% for hypertension, 9.1% stomach ulcer, 4.5% diabetes, 3.9% major mental distress, 3.8% minor mental distress, and 3.5% asthma. The study found considerably high stress levels among educators. Job stress was weakly associated with seven out of ten stress related illnesses but none was significant considering effect size calculations. Stress from teaching methods seemed to have higher impact on stress related illnesses than other components of the job stress scale. From three components of the demand-control model two, namely work stress from teaching methods and the educational system, but not low peer support was related to heart disease. The components of the effort-reward model of low socio-economic status and lack of career advancement were both not related to heart disease and only lack of career advancement was inversely related to Hypertension. Most components assessed here of the demand-control model (including stress with teaching methods and educational system, low peer support) and effort- reward model (including job insecurity and lack of career advancement) were related to stomach ulcer and mental distress. It is recommended that changes to the organization of work with particular attention being paid to increasing control and reward conditions be implemented and stress management may be included in work health programmes for educators. Key words: Job stress; job dissatisfaction; risk behaviours; stress-related illnesses; public educators; South Afric

Prevalence of tobacco use among adults in South Africa: Results from the first South African National Health and Nutrition Examination Survey

Smoking is one of the major preventable causes of disease and premature death globally.[1] Tobacco is the second leading risk factor for the global burden of disease, accounting for 6.3% of disability-adjusted life-years lost[2] and causing six million deaths annually.[1] Since 1995 there has been a modest increase in tobacco consumption in low- and middle-income countries (LMICs), but a consistent decline in high-income countries (HICs).[3] By 2030 it is estimated that tobacco will kill more than eight million people annually, with 80% of these deaths occurring in LMICs.[3] Consumers in LMICs such as South Africa (SA) are likely to be less informed about the adverse health consequences of tobacco use than those in HICs, and are therefore likely to bear the major health impact of tobacco unless an aggressive educational programme is mounted

Determinants of HIV infection among adolescent girls and young women aged 15–24 years in South Africa: a 2012 population-based national household survey

Abstract Background South Africa is making tremendous progress in the fight against HIV, however, adolescent girls and young women aged 15–24 years (AGYW) remain at higher risk of new HIV infections. This paper investigates socio-demographic and behavioural determinants of HIV infection among AGYW in South Africa. Methods A secondary data analysis was undertaken based on the 2012 population-based nationally representative multi-stage stratified cluster random household sample. Multivariate stepwise backward and forward regression modelling was used to determine factors independently associated with HIV prevalence. Results Out of 3092 interviewed and tested AGYW 11.4% were HIV positive. Overall HIV prevalence was significantly higher among young women (17.4%) compared to adolescent girls (5.6%). In the AGYW model increased risk of HIV infection was associated with being young women aged 20–24 years (OR = 2.30, p = 0.006), and condom use at last sex (OR = 1.91, p = 0.010), and decreased likelihood was associated with other race groups (OR = 0.06, p < 0.001), sexual partner within 5 years of age (OR = 0.53, p = 0.012), tertiary level education (OR = 0.11, p = 0.002), low risk alcohol use (OR = 0.19, p = 0.022) and having one sexual partner (OR = 0.43, p = 0.028). In the adolescent girls model decreased risk of HIV infection was associated with other race groups (OR = 0.01, p < 0.001), being married (OR = 0.07), p = 0.016], and living in less poor household (OR = 0.08, p = 0.002). In the young women’s models increased risk of HIV infection was associated with condom use at last sex (OR = 2.09, p = 0.013), and decreased likelihood was associated with other race groups (OR = 0.17, p < 0.001), one sexual partner (OR = 0.6, p = 0.014), low risk alcohol use (OR = 0.17, p < 0.001), having a sexual partner within 5 years of age (OR = 0.29, p = 0.022), and having tertiary education (OR = 0.29, p = 0.022). Conclusion These findings support the need to design combination prevention interventions which simultaneously address socio-economic drivers of the HIV epidemic, promote education, equity and access to schooling, and target age-disparate partnerships, inconsistent condom use and risky alcohol consumption

HIV prevalence and associated factors among men in South Africa 30 years into the epidemic : the fifth nationwide cross-sectional survey

We investigated HIV prevalence and associated factors among men ≥ 15 years in South Africa using data from a 2017 nationwide cross-sectional survey. HIV prevalence was 10.5% among 6 646 participants. Prevalence increased from 4.1% in the younger men (15–24 years), 12.5% in young men (25–34 years) to 12.7% in older men (≥ 35 years). Odds of being infected with HIV were lower among younger men who had secondary level education and those who reported poor/fair self-rated health. Young and older men of other race groups had lower odds of HIV infection. Odds of infection were lower among young men who had moderate/high exposure to HIV communication programmes. Men not aware of their HIV status had higher odds of HIV infection, including older men who never married. Improved access to education, behavioral change programmes, and awareness of HIV status are necessary to reduce the risk of HIV infection among Black African men.The President’s Emergency Plan for AIDS Relief through the Centers for Disease Control and Prevention under the terms of Cooperative Agreement Number NU2GGH001629. Additional funding was also received from the South African Department of Science and Technology (now known as the Department of Science and Innovation), South African National AIDS Council, The Global Fund to Fight AIDS, Tuberculosis and Malaria, Right to Care, United Nations Children’s Fund (UNICEF), The Centre for Communication Impact, Soul City, and LoveLife.http://link.springer.com/journal/10461hj2023Psycholog

Short-term real-time prediction of total number of reported COVID-19 cases and deaths in South Africa : a data driven approach

BACKGROUND: The rising burden of the ongoing COVID-19 epidemic in South Africa has motivated the application of modeling strategies to predict the COVID-19 cases and deaths. Reliable and accurate short and long-term forecasts of COVID-19 cases and deaths, both at the national and provincial level, are a key aspect of the strategy to handle the COVID-19 epidemic in the country. METHODS: In this paper we apply the previously validated approach of phenomenological models, fitting several nonlinear growth curves (Richards, 3 and 4 parameter logistic, Weibull and Gompertz), to produce short term forecasts of COVID-19 cases and deaths at the national level as well as the provincial level. Using publicly available daily reported cumulative case and death data up until 22 June 2020, we report 5, 10, 15, 20, 25 and 30-day ahead forecasts of cumulative cases and deaths. All predictions are compared to the actual observed values in the forecasting period. RESULTS: We observed that all models for cases provided accurate and similar short-term forecasts for a period of 5 days ahead at the national level, and that the three and four parameter logistic growth models provided more accurate forecasts than that obtained from the Richards model 10 days ahead. However, beyond 10 days all models underestimated the cumulative cases. Our forecasts across the models predict an additional 23,551–26,702 cases in 5 days and an additional 47,449–57,358 cases in 10 days. While the three parameter logistic growth model provided the most accurate forecasts of cumulative deaths within the 10 day period, the Gompertz model was able to better capture the changes in cumulative deaths beyond this period. Our forecasts across the models predict an additional 145–437 COVID-19 deaths in 5 days and an additional 243–947 deaths in 10 days. CONCLUSIONS: By comparing both the predictions of deaths and cases to the observed data in the forecasting period, we found that this modeling approach provides reliable and accurate forecasts for a maximum period of 10 days ahead.http://www.biomedcentral.com/bmcmedresmethodolpm2021Statistic