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Item Statistical modelling of the association between dietary diversity, dietary patterns and non-communicable diseases in Namibia(University of Namibia, 2024) Mbongo, Laina Tulipomwene; Kazembe, LawrenceGlobalization coupled with urbanization has placed a significant pressure on the food systems of many developing countries. This has led to lifestyle changes that have become one of the most important influences on dietary patterns. The nutritional transition has affected the dietary pattern and nutrient intake greatly and has led to a rise in the purchases and consumption of processed and convenience foods. Analysis in nutritional epidemiology typically examined diseases in relation to a single or a few nutrients or foods. However, people do not eat isolated nutrients. Instead, they eat meals consisting of a variety of foods with complex combinations of nutrients. The high degree of inter-correlation among nutrients as well as among foods makes it difficult to attribute effects to single dietary components. Dietary patterns can influence health and the risk of developing chronic conditions. Therefore, to gain full understanding of the relationship between diet and the development of non-communicable diseases (NCD), it is desirable to use several methodological approaches. The main objective of this study was to explore the linkages between dietary patterns, dietary diversity and prevalence of non-communicable diseases. Specifically, the study aimed at: (i) applying count models on dietary diversity in Namibia, (ii) using bivariate count modelling approach in analyzing convenience and non-convenience consumption food preference in Windhoek, (iii) applying copula joint modelling of food insecurity indicators with application to food insecurity prevalence (FIP), household dietary diversity score (HDDS) and months of inadequate household food provisioning (MIHFP), (iv) fitting multiple indicators-multiple-cause modelling to examine the relationship between foods consumed and non-communicable diseases. The analysis used two representative survey data, namely the AFSUN-HCP Household Food Security Baseline Survey (2016) and Namibian Household and Income Expenditure (NHIES) of 2015/2016. The study focused on dietary diversity by using different count models. The household dietary diversity score presented a mean score of 6.5, suggesting a moderate diverse diet, with less consumption of food made from beans/lentils; eggs; fruits/vegetables and more consumption of starch food. Determinants for household dietary diversity included educational level, sex of head of household and main source of income (p-value <0.005). The study further used bivariate iii modelling approaches to analyze the food consumption patterns. The results found that, whereas the consumption of food monthly was more on the non-convenience foods, the purchases of convenience was frequent on a weekly basis and in multiple food sources. Moreover, the study employed copula joint modelling of food security indicators. The findings show that AIC of the untruncated (conditional/marginal) Poisson regression model was lower and thus proved to fit the data better. The Frank Copula and Bivariate Normal Copula best fitted the data of establishing the relationship between HFIP and HDDS, and between HFIP and MIHFP respectively. Lastly, we analyzed multiple indicators-multiple causes examining the relationship between foods consumed and non-communicable disease. Principal Component Analysis (PCA) and Structural Equation Models (SEM) were used as data reduction methods to derive dietary patterns. Fruits, foods such as condiments/tea/coffee and potatoes, yams, cassava, or any foods made from roots and tubers accounted for majority of the variation. The study concluded that the usage of appropriate methods for specific data types is very critical. Generalized Poisson Regression models through the usage copula approaches are best to analyze jointly two outcomes in order to test for significant relationships between high-level hierarchical effects (e.g., random effects). Specifically, the bivariate normal and the Frank Copula were found to fit the data best. The unique nature of the bivariate normal model is that it does not allow for a different dependence structure between the outcomes while the frank copula does not have tail dependence and it can model both positive and negative dependencies as the normal copula. SEM and PCA’s were used as data reduction methods. Lastly, the study concludes that food and nutrition insecurity is a major threat to the development of the country and the study recommends for strengthened advocacy for consumption of healthy and diverse diets in the country in order to slow down and arrest proliferation of non-communicable diseasesItem Modelling spatio-temporal patterns of disease risk for data with misalignment and measurement errors: An application on measles and HIV prevalence data in Namibia(University of Namibia, 2018) Ntirampeba, DismasDisease mapping has important applications in public health because it enables the identification of areas which are at high risk of particular health problems. It helps visualising the spatial pattern of the disease distribution, which is of interest to the health sector as it enables the sector to plan, evaluate and redesign prevention and control strategies, and also make important policy decisions particularly for geographically targeted intervention in resource poor settings. Analyses of spatial disease patterns are generally based on data of a single disease and they are often fraught with challenges that include lack of a representative sample, often incomplete and most of which may have measurement errors, and may be spatially and temporally misaligned. This thesis focused on the development and extension of statistical models with particular interest to dealing with misalignment, measurement errors and jointly modeling of data from multiple sources. The first objective was to estimate and map the risk of measles at a sub-region level (i.e. constituency level) in Namibia using data obtained at the regional level. Direct inferences at constituency level made on basis of the original level of aggregation may lead to an inferential problem known as a misalignment in the statistical literature. Using measles data from Namibia for the period 2005-2014, both multi-step and direct approaches were applied to correct the misalignment. The multi-step approach model provided a relatively better model. The second objective was to fit a spatio-temporal model while dealing with misalignment and measurement error, again applied to measles data aggregated at regional level over the period 2005 to 2014. Again this leads to a spatial misalignment problem if the purpose is to make decisions at constituency level. Moreover, data on risk factors of measles were not available each year between 2005 and 2014. Thus, assuming that covariates were constant through the study period would induce measurement errors which might have effects on the analysis results. The multi-step approach was further extended to include temporal effects and account for measurement errors. Consequently, spatio-temporal models, which included Bernardinelli and Knorr-Held approaches, and classical measurement error models were adopted. Comparison of the results obtained from the nave method (i.e. modelling that ignored errors in covariates) and those from the approach that accounts for measurement errors showed that the latter modelling approach performed better than the former. The study showed a spatio-temporal variation of the measles risk over the 2009-2014 period. The third objective of this study was to develop a joint spatial model for HIV prevalence, using two sources (i.e. 2014 National HIV Sentinel survey (NHSS) among pregnant women aged 15-49 years attending antenatal care (ANC) and the 2013 Namibia Demographic and Health Surveys (NDHS)), which would enable the estimation at any location of the constituency or district level while dealing with misalignment in data. The shared component modelling approach was adopted through the use of stochastic partial differential equations (SPDE). The bivariate modelling approach developed allowed to combine two data sources that are available at different spatial levels in a single model and it catered for a specification of different spatial processes through the link function. Findings revealed that health districts and constituencies in the northern part of Namibia were highly associated with HIV infection. Also, the study showed that the place of residence, gender, gravida, marital status, number of kids dead, wealth index, education, and condom use were significantly associated with HIV infection in Namibia. Finally, it was shown that the prediction of HIV prevalence using the NDHS data source can be enhanced by jointly modelling other HIV data such as NHSS data. In conclusion, results showed that the multi-step approach may be used to deal with misalignment. Moreover, introducing the error model proved to be a useful approach to correct for measurement errors in data and improve inferences in situations where mismeasured values in covariates are encountered instead of native analyses that ignore the presence of errors in measurements. Lastly, the thesis showed that the prediction of HIV prevalence using the NDHS data source can be enhanced by jointly modelling other HIV data such as NHSS data.Item NRENs cloud architecture framework (NRENs-CAF): Enhancing cloud connectivity among national research education networks in SADC(University of Namibia, 2016) Suresh, NalinaThe development of Science, Technology and Innovation (STI) infrastructure and distribution of Information Communication Technologies (ICTs) to all components of societies are of significant importance to leverage a faster socio-economic development in Africa. The continuous technological changes have influenced service delivery in various sectors. The emergence of new technologies within the education sector has prompted for a review of the way research is conducted among NRENs. Developed countries NRENs were adopting Cloud computing technology, which had been consequently motivating the research in developed countries on related technologies by both the industry and the academia. These new technologies assist in accessing information and have the power to transform the teaching, learning and research paradigm. The flexibility of pay-as-you-go combined with an on-demand scalable model is changing the NREN computing and driving them to adopt Cloud technology. Notwithstanding its benefits, the transition to this computing paradigm raised serious security concerns, which were the subject of several studies. The new concepts that Cloud computing introduced, such as multi-tenancy, resource sharing, Virtualization and outsourcing, created new challenges for the security community. Other challenges playing a major role in slowing down and impacting its acceptance included poor resources such as internet connectivity, lack of technologies, lack of human resources, funding and economic reasons. Although security concerns form the biggest challenge, problems associated with availability, performance, cost, interoperability and regulatory issues come very close to security issues as the perceived set of challenges associated with Cloud adoption. This study took an in-depth look at the current state of SADC NRENs and found that little had been explored in developing countries particularly in SADC region. Alternatively, there was no clear strategy, guidelines nor reference architecture/framework to enhance Cloud computing within NRENs in SADC. Furthermore, it was found that lack of political support for Cloud initiatives, stringent regulations (for instance on data crossing the borders), issues with Service Level Agreements (SLAs) and security infrastructure to mention a few were the factors hindering the adoption of Cloud technology by NRENs. A survey study in the form of an exploratory quantitative research design was used. On the other hand, a descriptive non-experimental quantitative approach was chosen and a survey was conducted through the use of questionnaires. This was supported by document review on current emerging Cloud techniques. Close to fifty (50) participants from Eight (8) SADC NREN member countries that formed their NRENs was engaged in this study. There is no doubt that NRENS in the region are not effectively utilizing Cloud based technology. However, this study proposed some modern Cloud based approaches that could be adopted. Further, an explanation on how NRENs could be consolidated on a common Cloud platform was also provided. The research sample size of fifty (50) participants from Eight (8) SADC countries, who have formed their NRENs were engaged. The data was analyzed using SPSS version 21 (Statistical Packages for the Social Sciences). A p value <0.05 was considered as statistically significant. Data analysis was initiated with a check of the outliers, missing data and normality through correlation values that could affect relations between variables. In view of the above, NRENs Cloud Architecture Framework, which in this study is abbreviated as NRENs-CAF, was conceived to design a Cloud based architecture framework for NRENs in SADC region. An overview of existing NRENs in both developed and developing country was reviewed. The main objective of this study was to design an NRENs-CAF that would envision the transition of every NREN into Cloud based system and make them interoperable with each other. The study also aimed to harness Cloud technology in such a way that it facilitated research in tertiary institutions and enhance the collaboration among SADC NRENs. The NRENs-CAF intended to design a framework with new components to support Cloud connectivity and service delivery. Overall, the NRENs-CAF was proposed to build and deliver highly interconnected and high performance networks for Universities and other Educational and Research Institutions more specifically among SADC that enable them to share educational resources and collaborate within and globally.Item Multivariate statistical modelling of family formation processes among women in Namibia(University of Namibia, 2015) Pazvakawambwa, LillianFamily formation is a significant event in life-course of individuals. Many studies have revealed shifts in demographic processes including child-bearing patterns, age at sexual debut and first marriage, and marital status over the years. While there have been numerous studies in demographic processes in specific populations, very few studies have focused on family formation processes, and little or no quantitative research has been conducted on the distribution and dynamics and determinants of family formation in Namibia. This study employed a cross-sectional retrospective mixed methods design to achieve various objectives namely: to examine emerging marital patterns and trends in Namibia since attaining its independence in 1990; to analyze the hazards of first marriage and sexual debut and determinants of age at first marriage and sexual debut ; to establish factors associated with non-marital fertility; to examine perceptions of women regarding key union principles and values on matters of divorce, cohabiting, widowhood, polygamy, sex before and outside marriage based on a qualitative study; and to come up with family formation recommendations to guide policy and also pave way for further research. The study used data from the Namibia 1992 to 2006/7 DHS and from focus group discussions, which gave in-depth understanding on perceptions on family formation processes. Trend analysis, binary and multinomial logistic regression models were used to model the patterns and determinants of marital status. Discrete time hazard models through Bayesian Structured Additive Regression (STAR) approach were used to estimate the hazards of a woman’s sexual debut and first marriage. The Hurdle Logit Negative Binomial (HLNB) regression model was used to model non-marital fertility. Findings indicated a general change away from marriage, with a shift in mean age at marriage which rose from 21 years in 1992 to almost 23 years in 2006. Cohabitation was prevalent among those less than 30 years of age; the odds were higher in urban areas and increased since the year 1992. Be as it may marriage remained a persistent nuptiality pattern, and common among the less educated and employed, but had lower odds in urban areas. Multinomial regression results suggested that marital status was associated with age-at-first-marriage, total children born, region, place of residence, education level and religion. Marital patterns have undergone significant transformation over the past two decades in Namibia, with a coexistence of traditional marriage framework with co-habitation, and sizeable proportion of women remaining unmarried to the late 30s. An upward shift in the mean age is becoming distinctive in the Namibian society. Period and cohort effects in the timing of first sex were evident among women in Namibia. Efforts to discourage early sexual debut should be stepped up especially in North-Eastern Namibia. Results did not suggest a significant nonlinear pattern of age at first marriage with age, cohort and period. First marriage timing in Namibia was influenced by the woman’s age, birth cohort, period, place of residence, highest educational level, socio-economic status and region. Intervention strategies should not only target schools and the wider community in isolation, but should involve the individual family units as they have a bigger role to play in this regard. Non-marital fertility was associated with the age, educational level, urbanity, and socio-economic status. Rural women had higher fertility propensity compared to their urban counterparts even though there was no significant difference in fertility intensity. Fertility intensity decreased as the women got richer. Intervention efforts should focus on promoting education among girls and women especially in rural areas to improve their socio-economic status, reduce teenage pregnancy and non-marital fertility. Qualitative findings supported the quantitative findings and gave an in-depth understanding of women’s perceptions on family formation processes.