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The aims of this thesis were to determine the relative contribution of Pdx-1, MafA and β2 to the human insulin promoter.  Additionally, characterisation of the conserved CRE element (CRE2) was undertaken to identify the factor(s) that bind CRE2 to mediate affects upon the transcription of insulin.  Finally, the ectopic expression of insulin was investigated using an engineered zinc finger protein (ZFP-INS) that ‘switched on’ the endogenous insulin gene in a non-β cell (HEK293). Consistent with previous findings, Pdx-1, MafA and β2 were shown to synergistically activate the rat insulin 1 promoter.  However due to subtle sequence divergence, similar synergistic interaction was not observed on the human promoter.  Synergistic interactions were re-established in a rat insulin 1-like mutated human insulin construct.  The CRE binding protein activating transcription factor-2 (ATF-2) was shown to bind and stimulate transcription via CRE2 while CRE binding protein-1 (CREB-1) inhibited insulin transcription independently of CRE1 or CRE2.  ZFP-INS was shown to induce the ectopic expression of insulin in HEK293 cells via the ILPR region, inducing modifications of histone proteins at the insulin promoter.  Collectively, the continued characterisation of the human insulin promoter may reveal unique regulatory mechanisms controlling the expression of insulin under normal and diabetic conditions.

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A research report submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in the Field of Population-Based Field Epidemiology / Socio-economic status (SES) disparities do not only exist between racial groups in South Africa but also exists within the vulnerable black population with the devastating impacts of the HIV epidemic. Households are important determinants of human welfare. However, little is known about the effect of household socio-economic status on the establishment and break-up of households within a low-resource setting and a severe HIV epidemic. It is in the midst of these challenges in rural South Africa that this study examined the effect of household SES on household formation and dissolution among the black population in rural northern KwaZulu-Natal. METHODS Using longitudinal data from the period 2003-2012 from the Africa Centre for Health and Population Studies, the study used a cross-sectional study design approach to examine the effect of household SES on household formation. It also examined the effect of household SES change (i.e. either positive, negative change or stable SES) between the start and end of observation of a household within the study period. Household formation was defined as when an individual or individuals come from different households to form a new social unit with a new household head. Dissolution occurred when all individuals in a household end their membership to a household due to death, out-migration or by joining other households. Separate regression models for the two outcomes, household formation and dissolution were explored with household SES covariates while adjusting for other household variables. RESULTS Household formation and dissolution trends both decreased over the study period. Out of a total of 18,249 households, newly formed households had a relatively higher percentage of tertiary educated household heads (10.7% versus 2.5%), unemployed household members (41.6% versus 28.5%), grant recipient household members (37.1% versus 8.5 %) and households within the average to richest wealth quintiles (44.1% versus 36.4 %) than pre-existing households. Multivariate analysis showed that tertiary educated household heads (aOR=2.96, 95% (CI) 2.26-3.89) and households within the average to richest wealth quintiles most especially the 4th quintile (aOR=3.29, 95% (CI) 2.69-4.04) were associated with a higher odds of households being newly formed. However, the lesser the employed members (aOR=0.31, 95% (CI) 0.21-0.45) and grant recipients per household size in a household (aOR=0.15, 95% (CI) 0.12-0.18) the lower the odds of formation. Furthermore, small size households (aOR=0.68, 95% (CI) 0.56-0.80) and unmarried household heads (aOR =0.47, 95% (CI) 0.40-0.55) were associated with lower odds of being newly formed. Whereas female headed households (aOR=2.23, 95% (CI) 1.93-2.57) were associated with a higher odds of household formation. With regards to household dissolution, close to a quarter of households had an increase in SES over the study period compared to households with a decreased SES (24.6% versus 8.6 %). Similar to household formation, male headed households dominated the study population with the highest proportion in dissolved households (63.8% and 61.5% at start and end of household observation respectively). Also unmarried household heads were the majority in dissolved households (62.7% and 64.1% at start and end of household observation respectively). Approximately 65.6% of households that never dissolved had an extended family type of composition compared to 36.6% of dissolved households. The area was predominantly rural with about 47.2% households in rural segment of the study area. The study has shown that households had lower odds of dissolving if there is a positive change (i.e. an increase) in household SES compared with households with an unchanged SES over the period. In exact terms, an increment in the number of employed household members over the study period was associated 49% lower odds of a household being a dissolved (aOR=0.51 95% (CI) 0.42-0.61). Also, an increment in the number of household grant recipients over the period of observation was associated with a 69% lower odds to result in the dissolution (aOR=0.31 95% (CI) 0.25-0.39). Households with an improved wealth index over the period of study were associated with 55% lower odds of dissolution (aOR =0.45, 95% (CI) 0.38-0.54). However, households with both male and female death (multiple sex) were more likely to dissolve. Similarly, peri-urban (aOR=0.71; 95% (CI) 0.58-0.86) households were more likely to dissolve compared to urban households. Surprisingly divorced, widowed and separated couples were not significantly associated with household dissolution. CONCLUSION SES is an important determinant of household existence and stability. This study has shown a complex relationship between household SES and household formation. Although education and improved household wealth index were more likely to result in household formation, an increase in the number of employed household members and household grant recipients did not necessary have an effect on household formation. Government cash transfers, education, employment of household members are valuable cushioning mechanisms necessary for household stability. There is need for government and non-governmental organisations to set up interventions to improve the socio-economic conditions of poor households prioritising rural and female headed households. This is especially critical in a high HIV prevalence area where these interventions will also mitigate against the burden of the HIV epidemic on the population. / MT2017

MSc (Med), Population-Based Field Epidemiology, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand / ABSTRACT Background: World Health Organization (WHO) estimates that more than 1.6 million people die every year because of violence and out of these deaths, homicide accounts for almost one third. Ninety percent (90%) of homicide are thought to occur in low and middle income countries. South Africa has one of the most disturbing rates of homicide in the world. These high homicide rates besides resulting in reduced life expectancy also have serious health, social and economic consequences. Aim: The study aimed at quantifying the burden as well as and identifying factors associated with homicide deaths in rural KwaZulu-Natal in South Africa during the period of 2000 to 2008. Objectives: To estimate a 9 year period (2000-2008) homicide incidence rates as well as identify factors associated with homicide-related deaths. Further, the analysis described spatial distribution of homicide-related deaths in a rural South African population. Design: Analytical longitudinal study. Methods: Using data drawn from the Verbal Autopsies (VAs) conducted on all deaths recorded during annual demographic and health surveillance over a 9-year period (2000-2008), Kaplan-Meier (K-M) survival estimates of incidence rates were used to estimate the cumulative probability of death until the end of the period. Estimates were reported by sex and residency. Weibull regression methods were used to investigate factor associated with homicide deaths. Kulldorff spatial scan statistics was used to describe homicide clustering. Results: With 536 homicide-related deaths, and 814, 715 total Person Years of contribution, the study found an overall incidence rate of 66 (95% CI= (60, 72) per 100, 000 Person Years of v Observation (PYOs) for the period studied. Death due to firearm was reported the leading cause of mortality (65%). Most deaths occurred over the weekends (43%), followed by Friday (16.2%).The highest homicide incidence rates were recorded in 2001 (90; 95% CI= (71, 111) per 100,000 person years at risk and 2004 (86; 95% CI= (68, 108) per 100,000 person years at risk. Males had a rate that was about six times more than females 115 (95% CI=105,127) per 100,000 PYOs. Age-specific homicide rate were highest among males aged 25-29 years (209.90 per 100,000 PYOs) and females aged 50-54 years (78 per 100,000 PYOs). Resident, age, sex, education, socioeconomic status, and employment independently predicted homicide risk. The study identified two geographical clusters with significantly elevated homicide risk. Conclusion: A significant six fold difference in homicide rate existed between males and females. Sex differential increases with age, with males aged 15-54 years the most likely to be killed, and females aged 55 years and above having the highest homicide rate. Increase in wealth status and level of education increases one‘s risk of homicide. Employment per se was protective from homicide risk. Firearm was the leading cause of mortality. Most deaths occur over the weekend. Two geographical areas with elevated homicide risk were observed. These findings underscore the need to have timely information and strategies for effective violence prevention program to subgroups and areas at risk.

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