4. Electronic Theses and Dissertations (ETDs) - Faculties submissions
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Item Comparing health inequalities in maternal health: An analysis of the South African Demographic and Health Surveys (SADHS) 1998 and 2016(University of the Witwatersrand, Johannesburg, 2023-09) Holden, Celeste Claire; Blaauw, DuaneBackground: Inadequate access to maternal health services (MHS) is directly linked to maternal and neonatal mortality and morbidity. South Africa (SA) is known to be an unequal society. Researching and documenting the utilisation and access to MHS can assist in the appropriate redirection of services to ensure equitable service delivery. The study identifies differences in MHS access between ethnicity groups, residence, province, maternal education level and household wealth quintile. The study quantifies the inequalities in access to MHS in SA in 1998 and 2016, and then evaluates the change in inequalities between the two periods. Methods: Data was analysed from the 1998 and 2016 South African Demographic and Health Surveys. First. the study identifies differences in MHS access between ethnic groups, residence, province, maternal education level and household wealth quintile using regression analyses. Then, the inequalities related to access of MHS in 1998 and 2016 are calculated using the relative (RII) and slope (SII) index of inequality and the concentration index (CI). Lastly, the inequalities between 1998 and 2016 were compared using generalised linear models, indicating whether inequalities increased, decreased, or remained the same. All analyses were done in Stata and adjusted for the multistage-stratified sampling of the surveys. Results: Utilisation of MHS in SA varies between different groups based on ethnicity, residence, province, mothers’ education level, and wealth quintile. In 1998 and 2016, Black/African women have the least utilisation of all MHS. A clear pattern is seen where women with higher education and high wealth quintile, have increased MHS utilisation. In most cases, the inequalities narrowed between 1998 and 2016 for all MHS. However, inequalities are still present in 2016 for many MHS. For example, using simple inequality measures, the largest inequalities in 2016 are seen between women of different ethnicities accessing four or more antenatal visits (ANC4), where there is a 11.1 percentage point difference between the highest group (White & Indian/Asian) and the lowest group (Black/African). For complex inequality measures, there are still significant relative and absolute inequalities in antenatal visits in 2016 for maternal education (RII: 1.25; SII: 1.14) and household wealth quintile (RII: 1.23; SII: 1.11). Conclusions: Between 1998 and 2016, population-level utilisation to MHS increased in all MHS and the majority of within group inequalities narrowed over time. However, inequalities still exist in all maternal health outcomes. SA has implemented multiple programmes and policies to address inequalities in MHS and decrease maternal mortality and morbidity. However, these need to be continuously monitored and evaluated based on the latest data to ensure that efforts are going towards addressing the specific groups where inequalities are still present.Item Reporting Silica Dust Exposure Measurements in South African Gold and Coal Mines: 2005 to 2016(University of the Witwatersrand, Johannesburg, 2023-10) Mongoma, Brian Tshepo; Nelson, Gill; Brouwer, DerkBackground: Arising from the Mine Health and Safety Act 29 of 1996 (MHSA), one of the measures to protect mine workers is monitoring exposure to airborne pollutants. Mines are statutorily required to report airborne pollutant concentrations to the Department of Mineral Resources and Energy (DMRE) on a regular basis. Based on the DMRE's 2013 report, it was determined that 76% of workers were exposed to airborne pollutants at concentrations less than 10% of their respective occupational exposure limits (OELs). Using the same exposure data from the DMRE, the Chamber of Mines of South Africa reported a 14% improvement in the exposure to the airborne pollutants from 2005 to 2013. However, these reported reduced exposures to airborne pollutants are based on the summation of all airborne pollutant exposures by the DMRE. The annual reports refer to the percentage of employees exposed to the combined airborne pollutants, rather than to specific pollutants, such as silica dust – a hazard that is high on the occupational health agenda of the mining industry. From these reports, broad (and perhaps incorrect) conclusions are reached with regard to trends in silica dust and other exposures. The limitations of the SAMI include inaccurate data, self-regulation, incomplete employment and exposure records, and historical biases, which hinder its ability to effectively handle occupational health risks. This emphasizes the immediate need for clear and consistent regulations, accurate data collection, and impartial research approaches to protect the health of mine workers. Objectives: The objectives of this study were to describe trends in combined airborne pollutant and silica dust concentrations from 2005 to 2016, and to evaluate the DMRE Mandatory Code of Practice (MCoP) and the EN 689 methods (for testing exposure levels in the workplace against the OEL of 0.1 mg/m3) as published by the European Committee for Standardization (CEN), using reported silica dust concentrations from 2015 and 2016. Methods: This was a cross-sectional study in which secondary airborne pollutants exposure data, reported to the DMRE by coal and gold mining members of the Minerals Council, were analysed. The 282 870 data points were pooled together to describe trends in airborne pollutant exposures as they comprised 69 airborne pollutants reported by different mines with various mining methods, activities, and occupations. The exposure data was categorized into coal and gold mines, and further into four three-yearly periods (i.e. period 1: 2005-2007, period 2: 2008-2010, period 3: 2011-2013, and period 4: 2014-2016). This was conducted in order to have a consistent metric to allow for uniform assessment across different pollutants with varying OELs. Dividing the exposure concentration by its OEL provided a ratio, similarly to the way that an Air Quality Index is calculated. As a result, the data was normalized by dividing each pollutant exposure concentration by its occupational exposure limit (OEL) to obtain a ratio, termed Q. The arithmetic mean, standard deviation, geometric mean, and geometric standard deviation of the Qs were calculated for each of the three groups i.e. coal and gold mines combined, b) coal mines, and c) gold mines, for each period. Jeffreys’s Amazing Statistics Program was used to analyse the Qs and silica dust concentrations. The Kruskal–Wallis test was used to identify statistically significant differences among the four time periods for each commodity group. Additionally, Scheffe’s post-hoc test in JASP was conducted for further analysis and comparison of differences across all observed periods. Two methods, namely the EN 689 and the method required by the DMRE MCoP, were used to assess compliance. EXPOSTATS Tool 1 was used to calculate the arithmetic mean (AM), median, standard deviation (SD), geometric mean (GM), geometric standard deviation (GSD), and 90th and 95th percentiles of the exposure data derived from EN 689. Microsoft Excel was used to calculate the 90th and 95th percentiles of the exposure data based on MCoP method. A total of 127 014 silica dust data points from 2005 to 2016 out of the 282 870 were utilized to describe silica dust exposure trends, and 44 990 data points from the 127 014 were used to assess compliance for the years 2015 and 2016. Results: A total of 282 870 personal airborne pollutant concentrations from 2005 to 2016, obtained from DMRE, were included the analysis. Analysis of the pooled airborne pollutant exposure concentrations indicated that there was a high variability (data points were far apart and also far from the GM) as the GSDs ranged from 6.37 to 7.53, 7.8 to 8.43, and 5.7 to 6.16 for the coal and gold mines combined, coal mines alone, and gold mines alone, respectively. The variabilities of the silica dust concentrations were less than that of the pooled airborne pollutant data. The GSDs of the silica dust concentrations were < 3.5 for all three groups compared to the GSDs calculated from the pooled airborne pollutants concentrations, where the lowest GSD was 5.7. The trends in the pooled airborne pollutant exposure concentrations over the 12-year period, for all three groups, showed that there was a reduction in reported exposures to combined airborne pollutants. The AMs of the ratios (Q) indicated that the reduction in exposures for coal and gold mines combined, gold mining alone and coal mining alone, were 57%, 55% and 26%, respectively. The corresponding GMs of the ratios (Q) for gold mining alone, coal and gold mines combined, and coal mining alone, reduced by 64%, 45% and 15%, respectively, from 2005 to 2016. The distribution of the airborne pollutant data was skewed, which affected AM more than GM, and resulted in differences between the two measures. This was evident in the gold mining data, where the AM decreased by 55% but the GM decreased by 64%. Data for the period 2005-2007 had the highest AM (1.54) and standard deviation (2.75), suggesting that there were outliers. In this period, ratios (Q) ranged from 0.003 to 7.7, impacting the AM and creating a gap between median and AM values. From 2008 to 2010, the AM (1.26) and SD (2.04) decreased, showing reduced variability. A similar trend was observed from 2011 to 2013, with increased numbers of observations and further reduced variability. In 2014-2016, the AM decreased to 0.67 and SD to 1, indicating stability. The GMs for the coal and gold mines combined, coal mines alone and gold mines alone ranged from 0.17 to 0.31, from 0.22 to 0.28, and from 0.16 to 0.45, respectively. The trends in reported silica dust concentrations in all three groups showed a reduction over the 12-year period. The AMs indicated that the reductions for coal and gold mines combined, gold mining alone and coal mining alone, were 61%, 38% and 34%, respectively. The GMs of the silica dust concentrations indicated that the reductions in exposures for coal and gold mines combined, coal mining alone, and gold mining alone, were 54%, 35% and 31%, respectively. The AMs of the silica dust concentrations for coal and gold mines combined ranged from 0.17 to 0.44 mg/m3, while the coal mines ranged from 0.67 to 1.02 mg/m3 from 2005 to 2016. For gold mines, the AMs ranged from 0.13 to 0.23 mg/m3. Similarly, the GMs of the silica dust concentrations for the coal and gold mines combined ranged from 0.11 to 0.24 mg/m3, whereas coal mines ranged from 0.41 to 0.63 mg/m3, and gold mines ranged from 0.09 to 0.13 mg/m3. The 90th percentiles for the silica dust concentrations almost correlated with the AMs as they reduced by 67%, 40% and 34% for coal and gold mining combined, gold mining alone, and coal mining alone, respectively. The 90th percentiles for silica dust concentrations for the coal and gold mines ranged from 1.64 to 2.48 mg/m3, and 0.29 to 0.51 mg/m3, respectively. Although the trends indicated a reduction in exposure to silica dust concentrations, the AM, GM, 90th and 95th percentiles exceeded the OEL of 0.1 mg/m3 for the entire study period for the three groups, except for the gold mines alone in 2016. In that year, the GM was 0.09 mg/m3 (rounded to 0.1 mg/m3). For coal mining only, the 90th percentiles ranged from 1.64 to 2.48 mg/m3, whereas the 95th percentiles ranged from 2.16 to 3.16 mg/m3. For gold mining only, the 90th percentiles ranged from 0.29 to 0.51 mg/m3, and the 95th percentiles ranged from 0.35 - 0.63 mg/m3. A total of 44 990 silica dust concentrations were used from 2015 to 2016 to compare the 95th percentiles according to EN 689, and the 90th percentiles according to the MCoP. The DMRE MCoP method was shown to underestimate the exceedance of the occupational exposure limit by 5-26%, when compared with the EN 689 method. Conclusion: Despite the variabilities and challenges associated with pooling the airborne pollutants concentrations in the coal and gold mining industries, exposures to the airborne pollutants in the three commodity groups decreased from 2005 to 2016. However, reporting employee exposure as pooled airborne pollutants concentrations is flawed and obscures exposures to individual pollutants such as silica dust. The three commodity groups showed a decrease in silica dust exposure measurements from 2005 to 2016. However, there was still overexposure to silica dust in the three groups (greater than the OEL of 0.1 mg/m3). Inhalation of particles containing silica was higher in the coal than the gold mines, which is contradictory to what is known about the silica content of the ores in which the two commodities are found. The DMRE MCoP approach to compliance with silica dust levels underestimated the exceedance of the OEL in comparison to the EN 689’s approach. The current DMRE reporting methodology, i.e. the pooling of all data, does not allow accurate reporting of silica dust exposures and as a result, it does not provide direction or support for carrying out measures to decrease exposure to silica dust. The MCoP method for compliance testing revealed higher 90th-percentiles for coal mining compared to the 90th-percentile estimated for the population (EN 689). For gold mining it was the opposite. The EN 689 method is a more precise means of estimating OEL compliance, which is crucial for managing silica dust and specific pollutant health hazards and should be used in favour of the method in the MCoP.Item The Extent of the Inclusion and Consideration of Extreme Climate Events and Health in South African Policies; The Case of eThekwini(University of the Witwatersrand, Johannesburg, 2024) Meyer, Charné Amy; Fitchett, Jennifer M.; Wright, Caradee Y.Climatic changes over southern Africa include the increased frequency and intensification of Extreme Climate Events (ECEs) which exacerbate health risks within vulnerable low- and middle-income countries. Examples of health impacts from ECEs include water-, food-, and vector-borne diseases, morbidity, and mortality. Increased interest in ECEs since the beginning of the 21st century strengthened the recognition of the impact thereof on health. Therefore, it is important to analyse policy documents to determine the extent to which they include and comprehend these themes to prepare for and address negative ramifications. This study aims to explore the scope to which policy documents relevant to eThekwini, mention and deliberate the ECE- health nexus. This exploration of existing policies allows a contribution to the nascent literature around the ECE-health intersection and is indicative of possible areas of corrective strategy. This is conducted through a review of relevant policy documents, interviews with key stakeholders, and the analysis of secondary climate and health interview data. Findings reflect a 50% recognition of the ECE-health intersection in policy documents. Stakeholders acknowledge the importance of policy documents recognizing this interconnection. Notably, stakeholders are not aware of such policy documents that currently exist but identify barriers to these policy documents being updated and upheld. Hence, the Municipality does have adaptation strategies in place however, improvements thereof are necessary. Examples include the need for short- term adaptation planning, improved policy implementation, and community education. The lack of such work would exacerbate health concerns and add significant strains on the health sectorItem Implication of Regulated Cannabis Legalisation on Wellbeing and Economic Growth(University of the Witwatersrand, Johannesburg, 2022) Quarshie, Emmanuel; Alagidede, Imhotep PaulThis is a thesis on the cost benefit analysis of cannabis legalisation, public (mis)perception about cannabis usage and cannabis users, the medical application of cannabinoids and their commercial and industrial potential in the new global political economy. The study shows that, although there are misconceptions about cannabis, there is still much to unpack about its effects on human well-being. Drawing on both qualitative and quantitative cross-country dataset from Ghana and South Africa, the study employed a logit model to address the following questions: (a) What does society know about cannabis and its industrial and medical applications? (b) What is the evidence-based scientific claims of cannabis regarding human well-being? (c) What are the existing gaps between perception and knowledge? Among the contributions, this study clarifies the often-misunderstood position of cannabis in society and illuminates the blind side of the role of cannabis as an economic enabler in the post pandemic world. More importantly, while some schools of thought project cannabis as a gateway drug to the infernal realm, this study provides evidenced based on real-time practical experience from well- informed and educated users. The study provides a model for regulated cannabis legalisation, a proper guide on value-added supply chain mechanism, and guiding principles to ensure the model functions properly, based on lessons and best practices from countries that have legalized cannabis, such as the Netherlands, Canada, Lesotho, Malawi, Zambia, South Africa, and Zimbabwe. This study further establishes empirical and theoretical foundations for the key thematic subjects of cannabis use, as well as a policy direction pertaining to its regulated legalisation, prohibition, or decriminalization in Ghana and South Africa. Given the disconnect between knowledge and perception about cannabis, the study recommended knowledge enhancement and adequate advocacy on the pros and cons of cannabis for society to enhance understanding of the benefits and its side effects to provide evidence-based guidance on the medical application and industrial potentialsItem Solar electricity consumption, financial inclusion and welfare in sub-Saharan Africa(University of the Witwatersrand, Johannesburg, 2023) Dube, Andile Precious; Horvey, SylvesterSolar electricity has continuously contributed towards alleviating energy poverty in sub- Saharan Africa. Moreover, the development of off-grid solar electricity technologies and business models that integrate mobile money into solar electricity transactions has improved access to electricity in the region. As a result, the demand and adoption of mobile money have also increased. However, existing literature has not exposed this positive development trend and other economic development opportunities inherent in solar electricity consumption. Most studies have focused on analysing the potential of solar electricity consumption in alleviating energy poverty. Although the analysis of solar electricity consumption and poverty alleviation is critical, studies have failed to extend the analysis to other economic development indicators such as financial inclusion, and money demand. This analysis is important because access to financial services and the development of financial systems in sub-Saharan Africa is low, yet economic theory postulates that renewable electricity demand induces the development of and access to financial services and increases capital stock. Therefore, it is critical to examine the broader economic opportunities inherent in solar electricity consumption to provide additional insight into development of prudent renewable energy and economic growth policies. Additionally, the extant literature fails to expose the influence of the macro-economic environment, particularly human development indicators, on the demand for solar electricity. This is important because solar electricity consumption in sub-Saharan Africa is not consistent; it is characterised by rapid fluctuations and declines in some countries. Consumer welfare (education, health, and standard of living) may influence energy consumption patterns. Therefore, this thesis provides empirical evidence of additional economic indicators that influence the demand for solar electricity to contribute to the development of effective renewable electricity policies. The thesis entails three essays that focus on the relationship between solar electricity consumption, financial inclusion, money demand and welfare. It employs a sample of 15 countries in sub-Saharan Africa for the period from 2010 to 2019 for all three essays. The first essay examines the linear and non-linear relationship between solar electricity consumption, and financial inclusion. A Financial Inclusion Index is constructed using the Principal Component Analysis. The effect of solar electricity consumption on financial inclusion is analysed using the Two-Step System Generalised Moments Method. The results show that solar electricity consumption positively influences financial inclusion, implying that solar electricity consumption is a determinant of financial inclusion in sub-Saharan Africa. Furthermore, a threshold point in the relationship between solar electricity consumption and financial inclusion is detected using the Dynamic Panel Threshold Model, and the positive effect of solar electricity consumption declines after the threshold point. The second essay examines the short-run and long-run relationship between solar electricity consumption, mobile money, and money demand in sub-Saharan Africa. It employs the dynamic panel Autoregressive Distributed Lag with Dynamic Fixed Effects and Pooled Mean Group estimators and the Dynamic Ordinary Least Squares method to check the results' robustness. The empirical results reveal that solar electricity consumption has an insignificant effect on money demand (broad money balances) in the short and long run. However, if mobile money is introduced into the money demand function, solar electricity consumption positively impacts money demand. Subsequently, the interaction of solar electricity consumption and mobile money induces an upward effect on money demand. Therefore, the findings reveal that mobile money does not moderate the effects of solar electricity consumption on money demand; instead, it increases money demand leading to adverse effects on monetary policy. It is therefore recommended that monetary authorities should monitor solar electricity expenditure to control price fluctuation and maintain financial stability, particularly in countries where the dominant payment service is mobile money. The third essay investigates the effects of welfare on solar electricity demand using the following proxies: the Human Development Index, inequality in income, government expenditure on education, infant mortality rate, and access to information and communication technology (mobile phone subscriptions and internet users). The study applied the panelquantile regression technique with nonadditive fixed effects, and the results confirmed that welfare has significant effects on solar electricity demand. It reveals that the Human Development Index, education, and infant mortality have an inverse effect on solar electricity demand. However, income inequality has a negative effect in countries with low solar electricity consumption and a positive effect in countries with median-to-high solar electricity consumption. Mobile phone subscriptions positively influence solar electricity demand in countries with low-to-median solar electricity consumption. In contrast, internet users positively affect solar electricity demand in countries with median-to-high solar electricity consumption. The findings from the first essay endorse the proposition that solar electricity consumption induces the development of and access to financial products and services (energy-finance nexus). Whereas the findings from the second essay reveal the non-moderating effect of mobile money on the relationship between solar electricity consumption and money demand. Finally, the findings from the last essay reveal that human development factors drive solar electricity consumption. It is therefore recommended that policy makers should integrate renewable electricity goals and targets into economic development policies to enhance the transition to clean electricity sources and alleviate energy poverty in sub-Saharan Africa.Item Exploring primary healthcare services for informal workers: a case of South African women informal/ street traders in the City of Johannesburg Region F(University of the Witwatersrand, Johannesburg, 2023-03) Dube, Duduzile Ellen; Niekerk, Robert Van.In all humility and gratitude, I am overwhelmed to acknowledge my depth of gratitude to all those who have assisted me in putting this idea, well over the degree of simplicity and into something concrete. I would like to convey my sincere appreciation and gratitude to my esteemed supervisor Professor Robert Van. Niekerk for his invaluable supervision, tutelage, support, and patience in this challenging and interesting research journey from start to finish. Oh, what a journey of discovery Prof. Thank you to the defence panel committee who generously provided knowledge, expertise and most importantly an endorsement to fulfil my research project. My sincere appreciation to the research participants, this project would not have been possible without, izandla zedlula ikhanda. Ngiyabonga kakhulu boMama!!! I also appreciate my cohort colleagues for the late-night feedback sessions and moral support especially Phello, Max and Basil, many thanks’ gents. Thanks, should also go to my lovely CoJ siblings (Nstako, Millicent, Busi and Chester aka my research assistants) for your selflessness during the data collection phase of my research journey. Additionally, a heartfelt thanks to my CoJ principals/ colleagues for your unwavering support and encouragement there is just too many to mention. Thank you for believing in me even at times when all doubt filled my mind, I will remember you for a very long time. A special acknowledgement to Ms Tembeka Mhlekwa former Executive Director, Department of Economic Development (CoJ) for an important and unprovoked talk in 2018 that has led me to this moment, I am forever grateful. I wish to acknowledge the help provided by Mr Elliot Dubasi in putting together the unit of investigation arguably the most important activity in this project. Ngiyabonga!!!Item Income related health inequalities associated with Covid 19 pandemic in South Africa: evidence from wave 4.(University of the Witwatersrand, Johannesburg, 2023-05-26) Zulu, Abongile; Oyenubi, AdeolaEven though there have been some observable significant developments within the average level of diseases and rates of mortalities in many nations (developed and developing), health inequalities that exist within and between various nations, within social groupings and different religious groups have expanded in the last years (CSDH/WHO, 2007). Respectively, this increase in health inequalities has been a growing concern for many governments across the world. Also, civil society organisations and other organisations operating internationally have been more concerned on how they would go about reducing these inequalities (CSDH/WHO, 2007). On this point, the World Health Organisation has noted previously that the most efficient way for health care sector to contribute to the lessening or reduction of disparities existing in health is by establishing a good systems and procedures of primary health care. The contribution of a well established primary health care system is through the realization of various mediations in order to deal with the social determining factors, and these are social and economic conditions that are inclusive of the health care system structure that is influenced by resources, power and the distribution of money that consequently influence separate and group differences existing within the status of health (Burger & Christian, 2018). The most recent available evidence suggests that primary health care principles and values, equity in health, people centred care and subsequently a most important part for communities in health action can answer to the prospects and challenges faced by the modern-day societies (NICD, 2020)