Estimation and analysis of measures of disease for HIV infection in childbearing women using serial seroprevalence data.

Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2011.The prevalence and the incidence are two primary epidemiological parameters in infectious disease modelling. The incidence is also closely related to the force of infection or the hazard of infection in survival analysis terms. The two measures carry the same information about a disease because they measure the rate at which new infections occur. The disease prevalence gives the proportion of infected individuals in the population at a given time, while the incidence is the rate of new infections. The thesis discusses methods for estimating HIV prevalence, incidence rates and the force of infection, against age and time, using cross-sectional seroprevalence data for pregnant women attending antenatal clinics. The data was collected on women aged 12 to 47 in rural KwaZulu-Natal for each of the years 2001 to 2006. The generalized linear model for binomial response is used extensively. First the logistic regression model is used to estimate annual HIV prevalence by age. It was found that the estimated prevalence for each year increases with age, to peaks of between 36% and 57% in the mid to late twenties, before declining steadily toward the forties. Fitted prevalence for 2001 is lower than for the other years across all ages. Several models for estimating the force of infection are discussed and applied. The fitted force of infection rises with age to a peak of 0.074 at age 15, and then decreases toward higher ages. The force of infection measures the potential risk of infection per individual per unit time. A proportional hazards model of the age to infection is applied to the data, and shows that additional variables such as partner’s age and the number of previous pregnancies do have a significant effect on the infection hazard. Studies for estimating incidence from multiple prevalence surveys are reviewed. The relative inclusion rate (RIR), accounting for the fact that the probability of inclusion in a prevalence sample depends on the individual’s HIV status, and its role in incidence estimation is discussed as a possible future approach of extending the current work

Comparison of the ability of anthropometric indices to predict the risk of diabetes mellitus in South African males: Sanhanes-1

This study aimed to assess the sensitivity of body mass index (BMI) to predict the risk of diabetes mellitus (DM) and whether waist circumference (WC), waist-to-hip (WHR) and waist-toheight (WHtR) ratios are better predictors of the risk of DM than BMI in South African men aged 20 years and older. Data from the first South African National Health and Nutrition Examination Survey (SANHANES-1) were used. Overall, 1405 men who had valid HbA1c outcomes were included. The sensitivity, specificity, and optimal cut-off points for predicting DM were determined using the receiver operating characteristic (ROC) curve analysis. A total of 34.6% percent of the study participants were overweight/obese, while 10.5%, 10.4%, 36.6% and 61.0% had HbA1c, WC, WHR and WHtR above the normal reference ranges, respectively

Body image and the double burden of nutrition among South Africans from diverse sociodemographic backgrounds: SANHANES-1

This study investigated the associations between underweight, obesity and body image (BI) among 15+ year-old South Africans with diverse socio-demographic backgrounds. A cross-sectional survey and the analyses of data for 6411 15+ year-old participants in the first South African National Health and Nutrition Examination Survey was undertaken. Body image was compared to body mass index (BMI) and socio-demography. Data were analyzed using SPSS versions 25. Results are in percentages, means, 95% confidence intervals, p-values, and odds ratios. Overall, participants who were obese of which majority: were females, earned ZAR 9601+, completed grade 6, were non-Black men, were married and resided in urban formal areas, were more likely to underestimate their BMI and desire to be lighter. Participants who were underweight of which majority: were males, had no form of income or education, were black men, were not married, resided in less urban and farm areas, were younger than 25 years, were more likely to overestimate their BMI and desire to be heavier. While underweight and obesity were strong determinants of BI, BI was differentiated by socio-demography. These findings have a public health implication that requires special attention to curb the irrepressible underweight and obesity in South Africa

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

A decade of tobacco control: The South African case of politics, health policy, health promotion and behaviour change

BACKGROUND: The South African (SA) government has implemented comprehensive tobacco control measures in line with the requirements of the Framework Convention on Tobacco Control. The effect of these measures on smoking prevalence and smoking-related attitudes, particularly among young people, is largely unknown. OBJECTIVE: To describe the impact of a comprehensive health promotion approach to tobacco control amongst SA school learners. METHODS: Four successive cross-sectional Global Youth Tobacco Surveys (GYTSs) were conducted in 1999, 2002, 2008 and 2011 among nationally representative samples of SA grades 8 - 10 school learners. We assessed the prevalence of current smoking (having smoked a cigarette on ≥1 day in the 30 days preceding the survey) and smoking-related attitudes and behaviours. RESULTS: Over the 12-year survey period current smoking among learners declined from 23.0% (1999) to 16.9% (2011) - a 26.5% reduction. Reductions in smoking prevalence were less pronounced amongst girls and amongst black learners. We observed an increase in smoking prevalence amongst learners between 2008 and 2011. Smoking-related attitudes and behaviours showed favourable changes over the survey period. CONCLUSION: These surveys demonstrate that the comprehensive and inter-sectorial tobacco control health promotion strategies implemented in SA have led to a gradual reduction in cigarette use amongst school learners. Of concern, however, are the smaller reductions in smoking prevalence amongst girls and black learners and an increase in smoking prevalence from 2008 to 2011. Additional efforts, especially for girls, are needed to ensure continued reduction in smoking prevalence amongst SA youth

Vaccine hesitancy and related factors among South African adults in 2021: unpacking uncertainty versus unwillingness

BackgroundAmidst widespread public health recommendations and availability of COVID-19 vaccinations, half of South African adults are vaccinated against COVID-19. This study investigated the socio-behavioral determinants of vaccine hesitancy in South Africa, where vaccine hesitancy was separated into unwilling ness and uncertainty to take a COVID-19 vaccine.MethodsData was collected from a large-scale public survey during June–October 2021 that included online and telephonic surveys. Vaccination hesitancy was based on the question “When available, would you take the COVID 19 vaccine?,” with responses categorized into those who were willing, unwilling, and uncertain about taking a COVID-19 vaccine. Multinomial regression examined the association between socio-behavioral variables and vaccine hesitancy.ResultsOverall, 73.8% reported they would definitely or probably take the vaccine, 16.4% were uncertain and 9.9% reported they probably or definitely would not (n = 16,988). Younger age, White and Colored population groups, no influenza vaccination history, previous vaccination refusal, knowing someone who experienced a serious vaccination side-effect, misperceptions about vaccine benefits, cultural or religious discouragement from taking a COVID-19 vaccination, lack of governmental confidence, concerns about side-effects, perceived lack of safety information, and lack of trust in the pharmaceutical industry and in the information from health care providers were all associated with higher odds of being uncertain and unwilling to take a COVID-19 vaccination. Strengths of association for unwillingness and uncertainty varied by the explanatory variables. Concern about effectiveness due to fast development was associated with uncertainty to take the vaccine but not with unwillingness. Concerns about side-effects had stronger associations with uncertainty than with unwillingness, while previous vaccine refusal, misperceptions of the protective benefits of vaccines, White population group, religious/cultural discouragement, and lack of trust in the pharmaceutical industry and health care providers’ information had stronger associations with unwillingness than uncertainty.ConclusionThe determinants of COVID-19 vaccine hesitancy should be addressed in interventions to improve vaccine uptake. Public health interventions and health communication can be prioritized and tailored to the different forms of vaccination hesitancy

Body image and the double burden of nutrition among South Africans from diverse sociodemographic backgrounds : SANHANES-1

CITATION: Mchiza, Z.J.-R. et al. 2020. Body image and the double burden of nutrition among South Africans from diverse sociodemographic backgrounds: SANHANES-1. International journal of environmental research and public health, 17(3). doi:10.3390/ijerph17030887The original publication is available at https://www.mdpi.com/journal/ijerphThis study investigated the associations between underweight, obesity and body image (BI) among 15+ year-old South Africans with diverse socio-demographic backgrounds. A cross-sectional survey and the analyses of data for 6411 15+ year-old participants in the first South African National Health and Nutrition Examination Survey was undertaken. Body image was compared to body mass index (BMI) and socio-demography. Data were analyzed using SPSS versions 25. Results are in percentages, means, 95% confidence intervals, p-values, and odds ratios. Overall, participants who were obese of which majority: were females, earned ZAR 9601+, completed grade 6, were non-Black men, were married and resided in urban formal areas, were more likely to underestimate their BMI and desire to be lighter. Participants who were underweight of which majority: were males, had no form of income or education, were black men, were not married, resided in less urban and farm areas, were younger than 25 years, were more likely to overestimate their BMI and desire to be heavier. While underweight and obesity were strong determinants of BI, BI was differentiated by socio-demography. These findings have a public health implication that requires special attention to curb the irrepressible underweight and obesity in South Africa. Keywords: body image; body mass index; socio-demography; body size dissatisfaction; body size misreporting; age; household income; ethnicity; gender; education levelhttps://www.mdpi.com/1660-4601/17/3/887Publishers versio

Mapping the Burden of Hypertension in South Africa: A Comparative Analysis of the National 2012 SANHANES and the 2016 Demographic and Health Survey

This study investigates the provincial variation in hypertension prevalence in South Africa in 2012 and 2016, adjusting for individual level demographic, behavioural and socio-economic variables, while allowing for spatial autocorrelation and adjusting simultaneously for the hierarchical data structure and risk factors. Data were analysed from participants aged ≥15 years from the South African National Health and Nutrition Examination Survey (SANHANES) 2012 and the South African Demographic and Health Survey (DHS) 2016. Hypertension was defined as blood pressure ≥ 140/90 mmHg or self-reported health professional diagnosis or on antihypertensive medication. Bayesian geo-additive regression modelling investigated the association of various socio-economic factors on the prevalence of hypertension across South Africa’s nine provinces while controlling for the latent effects of geographical location. Hypertension prevalence was 38.4% in the SANHANES in 2012 and 48.2% in the DHS in 2016. The risk of hypertension was significantly high in KwaZulu-Natal and Mpumalanga in the 2016 DHS, despite being previously nonsignificant in the SANHANES 2012. In both survey years, hypertension was significantly higher among males, the coloured population group, urban participants and those with self-reported high blood cholesterol. The odds of hypertension increased non-linearly with age, body mass index (BMI), waist circumference. The findings can inform decision making regarding the allocation of public resources to the most affected areas of the population

The association between biopsychosocial factors and disability in a national health survey in South Africa

The association between psychosocial factors and disability is less clear. This study investigated the biological and psychosocial (employment and psychological distress) factors associated with level of disability in an adult sample in South Africa. Data were analysed from a cross-sectional survey among adults aged 18–64 (n = 4974). Multiple linear regression was used to investigate the associations of the selected variables with disability. The mean percentage score on the WHODAS scale of disability was 5.31% (95% CI: 4.74–5.88). Age (p < 0.001) and race (p = 0.0002) were significantly associated with disability, and history of stroke (β = 7.19, 95% CI: 3.19–11.20) and heart-related conditions (β = 2.08, 95% CI: [0.23–3.93) showed positive associations. Of the psychosocial variables, psychological distress (β = 10.49 [8.63–12.35]) showed a strong positive association while employment (−1.62 [−2.36 to −0.88]) showed a negative association with disability. The association between demographic factors, medical conditions and increased disability confirms the findings in the literature. The finding that psychological distress is associated with increased disability has not been frequently reported. This study highlights specific psychosocial targets that may be usefully addressed by health policies and interventions in order to improve disability management