Doctoral Degrees (DCMSS)

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Browsing Doctoral Degrees (DCMSS) by Subject "Namibia"

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    Multivariate statistical modelling of family formation processes among women in Namibia
    (University of Namibia, 2015) Pazvakawambwa, Lillian
    Family 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.
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    Statistical modelling of the association between dietary diversity, dietary patterns and non-communicable diseases in Namibia
    (University of Namibia, 2024) Mbongo, Laina Tulipomwene; Kazembe, Lawrence
    Globalization 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 diseases