Electronic Theses and Dissertations (Masters)

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    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, Duane
    Background: 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.
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    Experiences of healthcare workers using the AwezaMed translation application in antenatal settings
    (University of the Witwatersrand, Johannesburg, 2023-06) Cason, Caroline Marian; Slemming, Wiedaad; Wilken, Ilana
    Introduction: Language barriers impede quality health care service in South Africa. Trained interpreters could alleviate this problem, but they are not employed in public or private health settings. Health care workers rely on informal interpreters, who do not necessarily provide an adequate service, and may be resentful of this extra task. AwezaMed is a smart application developed by the Council for Scientific and Industrial Research (CSIR) with content developed for maternal health settings. The aim of this study was to assess usability and user experience relating to AwezaMed. Methods: A user experience study was conducted using mixed methods. The systems usability scale (SUS) was employed, surveying 12 users, to generate a quantitative score, representing the overall usability of the system. Interviews were conducted with 14 users and analysed thematically to identify themes of usability and user experience, and recognise factors which contribute to use of the application. Results: The application (app) achieved a total score of 66.25, rating it between ‘OK/Fair’ and ‘Good’. Understandability, operability, attractiveness, and trust were important usability themes. Users also reported using the app as an aid to language learning. Factors which influenced the use of the app included previous experience with mHealth, experiencing a language barrier in health settings, and unavailability of, or problems with interpreters. Discussion: While the app was received positively, it did not meet users’ expectations, as two-way communication could not be achieved. Due to the often-strained relationship between healthcare workers and informal interpreters, there remains a demand for a usable, trustworthy mHealth solution. A framework is proposed, based on these findings, to evaluate mHealth translation applications in South Africa in the future.
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    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, Derk
    Background: 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.
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    Indoor/outdoor PM4 (respirable dust) and respirable crystalline silica source tracking in households located in close proximity to gold mine tailing dumps
    (University of the Witwatersrand, Johannesburg, 2023-10) Makhubele, Nkateko Rawendar; Mizan, Gabriel; Manganyi, Jeanneth; Masekameni, Masilu Daniel
    Background: Particulate matter (PM) is a major contributor to air pollution in indoor and outdoor environmental spaces. Exposure to respirable dust (PM4) and respirable crystalline silica (RCS) indoor and outdoor in communities located in close proximity to gold mine tailings dumps in South Africa has not yet been determined. Aim: The aim of this study was to investigate the concentration of RCS and PM4 mass in samples measured indoor and outdoor of the nine (9) selected households located in close proximity to a gold mine tailings dumps. Methodology: Sampling locations were separated according to grids, based on the distance from the mine tailings dumps. Three different grids were determined as follows: A (<500m from the dump), B (>500m<1km) and C (1km – 3 km). Three households were selected from each grid zone to measure indoor and outdoor PM4 samples continuously over a 24-hour period using GilAir constant sampling pumps calibrated at the flowrate of 2.2 L/min in both the dry and wet seasons. PM4 samples were collected on a 37mm polyvinyl chloride (PVC) filter with a pore size of 0.8, which was assembled on the Higgin Dewell cyclones fitted with a filter pad of the same pore size. PM4 sample filters were gravimetrically weighed before and after sampling to determine the mass concentration of PM4. The respirable crystalline silica in PM4 samples were analysed by an X-ray diffraction method by South African National Accreditation System (SANAS) accredited laboratory of the National Institute for Occupational Health (NIOH). Samples were collected during the dry and wet seasons in the Riverlea community, Johannesburg. Results: During the wet and dry seasons, the mean indoor and outdoor PM4 mass concentration ranged from 0.02±0.01 µg/m3 to 2.26±0.02 µg/m3, respectively. The dry season mean PM4 mass concentrations were higher than the wet season PM4 mass concentrations in all zones. The pairwise comparison of PM4 mass concentration for dry and wet season revealed no statistically significance difference (p<0.05) at 95% confidence interval. Results presented in Figure 5 depicts the mean indoor PM4 mass concentration distribution for the dry season. The zone with the highest mean indoor PM4 mass concentration was zone A, followed by zone B. Since the mean outdoor PM4 concentration in zone C was the lowest, this suggests that the mine tailings dumps were the primary source of PM. The dry season mean indoor/outdoor ratio was greater than one across all zones; indicating that indoor activities were the primary source of PM. In both seasons, the mean indoor and outdoor percentages of crystalline silica ranged from 0.08±0.01% to 0.08±0.01%. The mean indoor and outdoor 24hr RCS concentrations in both seasons were below the California Office of Environmental Health Hazard Assessment (OEHHA) defined 24hr ambient exposure threshold of 3µg/m3. Recommendations: The results of this study suggest that nearby mine tailings dumps may be the primary source of PM in the indoor and outdoor environments; however the strength of this source in comparison to other sources remains unknown. Therefore, it is recommended that further studies focusing on source apportionment be carried out to determine the relative contribution of the mine tailings dust to the overall PM load in the environment. Although the difference was not statistically significant, indoor and outdoor PM4 concentrations were greater in Zones A&B, with the lowest PM4 concentrations in Zone C. The I/O ratio indicated that there was contribution of PM from outdoor. It is also recommended that further studies be conducted, with focus on monitoring PM4 over a 30 days period, to determine the level of free crystalline silica that may be present in PM4 mass concentrations. Conclusion: In the South African context, studies that focus on the investigation of indoor and outdoor PM4 concentrations in households located in close proximity to gold mine tailings are limited. The findings of this study can be used to provide valuable information on the indoor and outdoor PM4 concentrations, which can be used in modelling exposure and conducting probabilistic health risk assessment. High dust levels are related with dry season weather conditions due to strong wind conditions. Therefore, the PM4 mass concentrations in all zones were higher during the dry season than during wet season. Since the mean outdoor PM4 concentration in zone C was the lowest, this suggests that the mine tailings dumps were the primary source of PM.
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    A Cost Comparison study of the electronic tick register with a paper based tick register in clinics within the Ekurhuleni District
    (University of the Witwatersrand, Johannesburg, 2023-08) Khoza, Courage Macduff; Thomas, Leena Susan
    Introduction & Background: A paper-based register is used to capture routine health information from Primary Health Care (PHC) clinics into the District Health Information System (DHIS) in South Africa. However, DHIS data was reportedly unreliable and inaccurate, as the paper-based system was error-prone. To address this, the Ekurhuleni Health District in the Gauteng Department of Health (GDOH) developed and piloted an electronic (E-tick) PHC register in three of its facilities. Upon completing the pilot in 2019, the implementation of this system was halted as it was not incorporated into the GDOH budget, partly due to inadequate information on its costs compared to the paper-based system. Aim: This study aims to cost and compare the expenditure of the electronic tick register and the paper-based tick register systems and determine provider views on their use in the Ekurhuleni Health District. Methods: Two methods were used: a) a descriptive cost-comparison study of the paper-based tick and the E-tick registers from November 2017 to December 2019 and b) a descriptive cross-sectional study using interviewer-administered questionnaires about health worker experiences using both registers during the stated period. Results: The study found that the E-tick register was less costly than the paper-based register. The year 2018/19, which was the only complete financial year in the study period is used for comparison. The paper-based register cost the district R42.4 per patient, while the E-tick cost R29.9 (29.5% cheaper). Of ten study theme areas explored in the interviews, the E-tick was advantageous in eight, these were: Convenience, easy accesses, quick recording time, safe information storage, immediate data capturing, ability to add more elements, fewer errors and good font size and legibility. The paper-based register was found to be advantageous in just four study themes which were: Convenience, easy accesses, independence from electricity supply and sufficient writing space. Conclusions: The E-tick register was found to be preferred over the paper-based register as it was quicker, cheaper, and acceptable to most of the health workers who used it. These are important findings for the health district as the study generates local evidence that the Ekurhuleni Health District and the Gauteng Department of Health can use to justify investments in scaling up and sustaining locally developed innovative digital solutions such as the E-tick register. This further enables the health district to improve recording times and compliance with record management legislation.
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    Assessing the potential interaction between CBD and TBR1 CBD and T-box domain
    (University of the Witwatersrand, Johannesburg, 2024) Blignaut, Chanel; Sylvia, Fanucchi; Adeyemi, Samson
    In 2020, Cannabidiol (CBD) emerged as the most commonly used recreational substance among pregnant women and was perceived as a natural and safer option for alleviating pregnancy- related symptoms, yet its potential effects on foetal neurodevelopment remain uncertain. With varied results from existing literature on the association between prenatal cannabis use and Autism Spectrum Disorder (ASD) development, this study focuses on filling these knowledge gaps. It investigates the potential interaction of CBD with the T-box domain of TBR1, a transcription factor implicated in ASD. CBD may cross the placenta and distribute throughout the developing foetal organs, including the brain, where it may interact with TBR1. This study's objective is to lay the groundwork for future research into the impact of CBD binding on TBR1 functionality, whose dysregulation is implicated in ASD. The study aims to use in vitro and in silico methods to identify and characterise the interaction between CBD and TBR1 T-box Domain. Initially, predictive models were utilised to determine the structure of the TBR1 T-box domain and its binding domains. Subsequently, the ADMET properties of CBD are assessed to determine its potential interaction with TBR1 T-box domain within the body. Through the optimisation of the TBR1 T-box domain and CBD structures, induced fit docking and molecular dynamics simulations, the study aims to predict the potential interaction sites, dynamics and stability of this interaction. The study confirms the computational results using in vitro methodologies. After expressing and purifying the TBR1 T-box domain, a pull-down assay (PDA), thermal shift assay (TSA) and Time-resolved Fourier-transformed infrared spectroscopy (TR-FTIR) are used to evaluate the potential binding, stability and physiochemical properties of the interaction. Computational analysis, using Maestro Schrödinger Induced Fit Protocol, predicts that CBD binds stably within a hydrophobic pocket of TBR1 T-box domain, away from its DNA-interacting residues. Pose 2 and 3 from molecular docking shows the highest binding affinity and molecular dynamics simulations, using Maestro Schrödinger Desmond Molecular Dynamics System, reveal that the TBR1 T-box domain stabilises upon interaction with CBD. Specifically, the interaction is facilitated by hydrophobic interactions and hydrogen bond formation with residues Ser238, Pro335, Thr360, Glu363 and Asn240. Experimental validation through PDA and TSA provided inconclusive results, but TR-FTIR confirmed the dynamic nature of the CBD-TBR1 interaction, characterised by time-dependent spectral changes. While the results do not directly indicate an impact of CBD on TBR1 functionality, further DNA binding studies are necessary for confirmation. This study suggests caution in using CBD during pregnancy due to its complex and largely unexplored interaction with TBR1, underscoring the need for more comprehensive research to conclusively understand its influence on neurodevelopmental disorders and its therapeutic potential
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    Efficacy of noise control measures at high noise zones from a copper mine in Zambia
    (University of the Witwatersrand, Johannesburg, 2024) Nchimunya, Bbautu; Hayumbu, Patrick; Masekameni, Masilu Daniel
    Noise exposure is a global problem, it is estimated that about 30 million workers in the United States of America (USA) are exposed to high noise levels while across Europe, 28% of the workers are exposed to high noise levels. Hazardous noise exposure is associated with a wide range of health effects that include noise induced hearing loss (NIHL), stress, poor concentration, communication difficulties and fatigue due to lack of sleep. The mining industry worldwide is struggling with hearing loss due to noise overexposure and in a copper mining set-up, the concentrator section is assumed to be among high noise zones exposing workers to noise above the occupational exposure limit (OEL) of 85 dB(A). This study aimed at evaluating the efficacy of noise control measures at various sections at Konkola Copper Mine concentrator section in Zambia. This quantitative cross-sectional study was conducted at Konkola Copper Mines (KCM) Konkola Business Unit (KBU) in Chililabombwe District in the Copperbelt Province of Zambia. A walk through survey was conducted to collect information to describe the operations, identify noise sources, understand noise release mechanisms and describe noise control measures. Quality control was achieved by triplicate noise measurement per location using an instrument with a valid annual calibration certificate. Raw data was pre-processed by cleaning to make it ideal for use. An ethical waiver W-CBP-230428-01 was granted as this study did not involve animal or human subjects but only area noise samples using CR: 172B SLM. The study identified the noise sources, described noise release mechanisms, described the noise controls and assessed the efficacy of noise controls in four sections within the concentrator of a copper mine in Zambia. Seventeen noise generating equipment were identified with about 53% of the equipment operated at the crushing section, 18% operated at the Flotation and Filtration section respectively and 11% at Milling section. A substantial portion (65%) of the identified noise sources in the concentrator are not housed, and among these, 36% are mobile in nature. It was also found that none of the noise areas were demarcated There are three types of noise controls (enclosure, silencer & HPD) that are in use at the concentrator and they fall in two categories of the hierarchy of controls (engineering & PPE). Out of the nine noise sources at the Crushing section, 56% (5 of the 9) utilized enclosure as control, 33% (3 of the 9) had HPDs as control and 11% (1 of the 9) source was installed with a silencer as a control. Enclosure is utilized to control noise from the two sources found in the Milling section while HPDs and enclosure are the noise control measures in use at both Flotation and Filtration sections of the concentrator. Enclosure is the most available control in the concentrator at 53%, followed by HPDs at 41%, and the least available is silencer at 6 %. About 76.5% (13) of the noise controls at the concentrator had efficacy strong enough to reduce noise levels to below the OEL while 23.5% (4) of the controls had weak efficacy that failed to reduce noise levels to below the OEL. This has prompted the need to strengthen efficacy in areas where controls were found to be weak. There is need to sustain controls that were found to be strong to maintain their efficacy. About 75% (3 of the 4) of the controls with lower efficacy were from the Crushing section while 25% (1 of the 4) was from Filtration section
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    The relationship between traumatic events and quality of sleep in older adults in rural South Africa
    (University of the Witwatersrand, Johannesburg, 2024) Dzimbanhete, Tsitsi Cherry; Mall, Sumaya; Redman, Kirsten N.
    Introduction: A number of factors are associated with the quality of sleep, a broad measure that includes sleep duration and disturbance. There are many factors associated with quality of sleep including communicable and non-communicable diseases and life course traumatic events (TE). Older adults who have experienced life course TE and the onset of comorbidities may be at risk of fluctuations in their quality of sleep. However, there are limited data on the African continent examining these relationships. Therefore, this study aimed to bridge the aforementioned gap and 1. examine the prevalence of traumatic events (TE), 2. examined the prevalence of poor quality of sleep in adults in the Health and Aging in Africa: a longitudinal study (HAALSI) cohort 3. examine the relationship between the TEs and quality of sleep in the HAALSI cohort in the Mpumalanga Province of South Africa. Methods: A cross sectional analysis using data from the second of four waves of the HAALSI cohort was undertaken. The second wave which recruited 4176 participants was conducted between 2018 and 2019. Measures include the English Longitudinal Study of Aging life history data to estimate prevalence of TE, brief version of Pittsburgh Sleep Quality Index (B-PSQI) to estimate the prevalence of poor sleep quality and the relationship between TE and poor sleep quality. Descriptive analysis, bivariate and multivariate analysis of the data was conducted in Stata 17. Results: The mean age of the participants was 65 years (SD=13). The majority of the sample were of South African origin (70%). With regard to education status, less than half (43%) had not completed a formal education (i.e., primary school). Poor quality of sleep was reported by 27% of the participants. With regards to TEs 66% of the sample reported caregiving trauma, 58% accident and disaster TEs, 30% childhood trauma, 15% war related TEs and 22% community violence. The multivariate analysis suggested that participants with history of exposure to childhood TEs and war related TEs had higher risk of poor sleep quality (OR 1.5 (CI1.2-1.8)) and (OR 1.5(CI 1.2-2.0)) respectively. The other variables associated with higher risk of poor sleep quality were being married (OR=1.2 (CI 1.0-1.4)) history of smoking (OR=1.6 (CI 1.2-3.1)), mild to moderate (OR=1.7 (CI 1.3-2.1)) and major depression symptoms (OR=2.1 (CI 1.8- 2.7)), being obese (OR =1.3 (CI 1.0-1.6)) and being HIV negative (OR= 1.4 (1.0-1.6)). Conclusion: Exposure to war related and childhood TEs were found to be associated with poor sleep quality in the older adults in rural South Africa. While a cross-sectional analysis is valuable, an examination of the full cohort of the trauma at baseline and quality of sleep would inform trauma focused interventions that seek to improve quality of sleep in older adults
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    The relationship between mental distress and somatization in hospital based health care workers in Gauteng during covid-19 pandemic in 2020
    (University of the Witwatersrand, Johannesburg, 2023) Ramuedi, Ntsako Khosa; Kerry Wilson, Nioh
    Background Mental distress among Health Care Workers (HCWs) is an urgent health concern, and somatization is a known outcome of mental distress. The Covid-19 pandemic increased stress for HCWs globally due to working with Covid-19 patients and resource limitations. Although there was already a lot of mental distress in HCWs in prior years, the coronavirus pandemic made matters worse, with 45% of people reporting that the pandemic had a significant negative impact on their lives. Somatization can lead to increased use of health services, sick leave and poor health. Service delivery is also impacted negatively if the service providers are not well or are suffering from the mental distress and are also showing symptoms. Aim To identify if a relationship exists between mental distress and somatization symptoms in Gauteng hospital-based health care workers in 2020. Objectives. To describe the prevalence of mental distress and somatization among health care workers by socio demographic status. To identify the somatization symptoms associated with high GHQ-12 scores in health care workers during Covid-19. To describe the association between mental distress and somatization among health care workers during covid-19 adjusting for demographic variables. Methods Health care workers can be described as anyone working in the health sector or at a health facility. All staff in the three selected hospital facilities in Johannesburg, were given the opportunity participate in the study. The PHQ-15 and GHQ-12 tools were used to collect information on HCWs somatization and mental distress after the first wave of the Covid-19 pandemic in South Africa. The anonymous questionnaire consisted of the two tools and demographic questions was used. The responses to each question on the tools were summed in order to determine severity of mental distress and somatization in HCWs, a higher score indicating more stress and or more somatization. Logistic regression was used to determine the adjusted relationship between somatization and mental distress. Results The study had a sample size of 295. A large proportion of participants (52%) reported suffering somatic symptoms. Males mean somatization score was significantly lower than the females. The majority (62%) of HCWs were troubled indicating a high burden of mental distress in the health care sector. The most commonly reported symptoms were back pain, headaches and being tired or low energy, all three were significantly associated with mental distress among others. There was a positive moderate correlation between PHQ-15 and GHQ-12 scores (0.30592) (p < 0.0001). Logistic regression indicated somatization was significantly associated with mental distress with a significant OR 2.14 (p = 0.0029) adjusted for demographic factors in these workers. Conclusions There was a statistically significant positive relationship between somatization and poor mental health. Health care workers with mental distress may be at risk of somatization, particularly specific symptoms such as back pain, headache and having low energy. Females were more bothered by most of the somatoform symptoms as compared to their male counterparts. Support for health care worker’s mental health is required as well as increased awareness of somatization linked to mental distress. Policies and services need to be developed to protect and support HCWs mental health during times of stress in the sector
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    The relationship between the combined effects of life-course trauma and HIV on cognition in rural South African adults: A secondary data analysis
    (University of the Witwatersrand, Johannesburg, 2024) Kupa, Nkgodi Obed; Matsena-zingoni, Zvifadzo; Mall, Sumaya
    Background: Lifecourse traumatic events (TE) refers to both childhood and adult trauma. Childhood TE refers to a spectrum and domains of adverse experiences occurring before the age of 18. Global and South African-based research suggests that life-course TE are associated with both physical and mental disorders including HIV and poor cognition (also referred to as neurocognitive impairment (NCI)). While data suggests that life-course TE, HIV and NCI are highly prevalent in South Africa and risk of NCI has been researched, little is known of the combined effect of life-course TE and HIV on NCI in adulthood. To fill the gap in the literature, I analysed data from the Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa (HAALSI), from rural Bushbuckridge (Mpumalanga province). Study Aim To examine the combined (interaction) effect of TE and HIV infection on the cognition of older adults in South Africa. Methods: I analysed (secondary) data from the HAALSI study. The main exposures analysed were: life-course TE and HIV-positive status. A pre-analysis phase consisted of several exploratory steps to define the exposure and outcome: First TE data which had been measured by the English Longitudinal Study of Aging (ELSA) life history questionnaire were examined. The main exposure variable was coded 1 if one experiences a TE and 0 otherwise from seven potential TE. NCI, the main outcome variable was defined based on measuring cognitive domains: orientation and memory. A score≥1.5 standard deviations (SD) below the mean of the baseline cognitive function distribution on the cognitive assessment (managing to know the date, day, month and president) will mean no NCI while a score below the means some degree of NCI). The main outcome variable was cognition measured by the Oxford Cognitive Screener (OCS-plus). Based on the validation of Tablet-Based OCS-plus in HAALSI, OCS-Plus included nine brief tests measuring cognitive ability in nine different domains, including language, memory (intentional and incidental), and executive functioning (task switching-alternating jobs between tasks), attention (auditory), and praxis (doing things). A stand-alone application called OCS- Plus was developed using Matlab and Psychophysics Toolbox for Windows Surface Pro tablets. Further preparatory steps for the analysis included: the exposure variables (HIV status and composite trauma-defined as the presence of at least one trauma item-) were created as follows: 1. HIV status was categorized into HIV positive and negative and coded 1 and 0 respectively. 2. Composite trauma was coded 1 if ever experienced any of the seven trauma items and 0 if none were experienced. Four groups of participants were created by exposure status. These were: 1. HIV positive and also experienced TE. 2. HIV negative but experienced TE. 3. HIV positive but TE negative. 4. HIV negative and trauma negative. Descriptive statistics were calculated for both exposures and outcomes as well as relevant sociodemographic variables. Both unadjusted and adjusted logistic regression techniques were employed to examine the combined effect of life course TE and HIV on NCI in older adults. The adjusted logistic regression models were done: 1) handling HIV and composite trauma separately and 2) considering the interaction term of HIV and composite trauma. Variables such as education, employment status, age, nationality, gender, hypertension, stroke, HIV status, marital status and composite trauma were considered confounders and adjusted accordingly. Results: Of the 5,059 study participants recruited and residing in the Agincourt study area in Bushbuckridge, 65% of the study participants had experienced at least 1 TE, and the most common trauma experienced were “ever experiencing severe financial hardship which was experienced by 58.74% of the participants, 39.73% whom “ever experienced a natural disaster” and 23.30% “ever experienced a death of a relative or friend” and the prevalence of NCI was 7% ( n=352).. The median age of participants was 64 (IQR: 55-74) years; 53.07% of the study participants were females; 44.42% had no formal education, and 72.63% of the study participants were not working. In the multiple logistic regression model with the interaction term, the odds of having NCI decreased by 64% (AOR=0.36; 95%CI: 0.25-0.52) and 59% (AOR=0.41; 95%CI: 0.24-0.75) among those who had some primary school (1-7 years) and some secondary school (8+ years), respectively compared to those with no education. The odds of having NCI decreased by 98% (AOR=1.98; 95%CI: 1.05-3.72) among those who were not working compared to those employed. A one-year increase in age was associated with a 5% increase in the odds of having a cognitive impairment (OR=1.05; 95%CI: 1.04-1.07). Those who were married had 37% (OR=0.63, 95%CI: 0.47-0.84) reduced odds of having NCI compared to those who were married. Those without composite trauma had 90% (AOR=0.10; 95%CI: 0.07-0.15) reduced odds of having NCI compared to those who have composite trauma. Those who were HIV positive and had experienced composite trauma had an increased odds of 1.78 (95% CI: 1.04-3.04) of having NCI compared to those who are HIV negative and had not experienced composite trauma. In the interaction model, we found no association between HIV status, stroke, or hypertension and NCI. However, the results of the interactionmodel suggested a significant association between HIV and the composite trauma score on NCI. Conclusions: The results suggest that lifecourse TE and HIV infection influence NCI. The full HAALSI cohort could be employed to examine the effect of TE data collected at baseline and incident NCI at later waves