Research Articles

Permanent URI for this collection

https://scholar.mzumbe.ac.tz/handle/123456789/364

Browse

Browsing Research Articles by Author "Mbegalo, Tukae"

Now showing 1 - 3 of 3
  • No Thumbnail Available
    Item
    Bayesian multilevel modelling of the association between socio-economic status and stunting among under-five-year children in Tanzania
    (Journal of Health, Population and Nutrition, 2023) Musheiguza, Edwin; Mbegalo, Tukae; Mbukwa, Justine N.
    Background: Stunting is associated with socioeconomic status (SES) which is multidimensional. This study aimed to compare different SES indices in predicting stunting. Methods: This was the secondary data analysis using Tanzania Demographics and Health Surveys (TDHS). The study used 7492, 6668, and 8790 under-five-year children from TDHS 2004/5, 2010, and 2015/16, respectively. The Household Wealth Index (HWI); Water and Sanitation, Assets, Maternal education and Income (WAMI); Wealth Assets, Education, and Occupation (WEO); and the Multidimensional Poverty Index (MPI) indices were compared. The summated scores, principal component analysis (PCA), and random forest (RF) approaches were used to construct indices. The Bayesian and maximum likelihood multilevel generalized linear mixed models (MGLMM) were constructed to determine the association between each SES index and stunting. Results: The study revealed that 42.3%, 38.4%, and 32.4% of the studied under-five-year children were stunted in 2004/5, 2010, and 2015/16, respectively. Compared to other indicators of SES, the MPI had a better prediction of stunting for the TDHS 2004/5 and 2015/16, while the WAMI had a better prediction in 2010. For each score increase in WAMI, the odds of stunting were 64% [BPOR = 0.36; 95% CCI 0.3, 0.4] lower in 2010, while for each score increase in MPI there was 1 [BPOR = 1.1; 95% CCI 1.1, 1.2] times higher odds of stunting in 2015/16. Conclusion: The MPI and WAMI under PCA were the best measures of SES that predict stunting. Because MPI was the best predictor of stunting for two surveys (TDHS 2004/5 and 2015/16), studies dealing with stunting should use MPI as a proxy measure of SES. Use of BE-MGLMM in modelling stunting is encouraged. Strengthened availability of items forming MPI is inevitable for child growth potentials. Further studies should investigate the determinants of stunting using Bayesian spatial models to take into account spatial heterogeneity.
  • No Thumbnail Available
    Item
    Effect of Statistics on Collaboration for Enhancing Institutional Sustainability: A Case of Mzumbe University-Tanzania
    (Springer Nature Switzerland, 2024) Mbukwa, Justine N.; Mbegalo, Tukae; Lwaho, Joseph
    The article discusses the effects of statistics on collaboration and its potential in spearheading sustainable industrial development. In this regard, three days’ workshop were conducted by Mzumbe University Laboratory for Interdisciplinary Analysis (MULISA) in collaboration with the Ifakara health institute. These activities are statistical literacy, scientific writing and winning the research grants. The objective was to create a smooth environment for the sustainability of the statistical laboratory through knowledge. The participants in the workshop were students and lecturers at Mzumbe University, and researchers and interns from Ifakara Research Institute (IHI). The majority of the participants in all three days of workshop were males. The results revealed that the workshop has increased the research and publication activities among MULISA collaborators after the workshop compared to before the workshop. This noted benefit derived from the sharing the skills and collaboration during the workshop. Therefore, the collaborative workshops and training are the engineering tool for sustainability because it allows sharing of new knowledge. The collaboration in writing enhances thoughts, ideas, and knowledge transferability to the next generation.
  • No Thumbnail Available
    Item
    Spatial Distribution and Pattern Analysis of Women Sexual Violence in Tanzania
    (Springer, Cham, 2023) Mbukwa, Justine N.; Mbegalo, Tukae; Levira, Francis
    In sub-Saharan Africa, sexual violence is very common among married women. This has a negative effect on health and wellbeing. This problem has not been well documented geographically, particularly in Tanzania. The main objective of this chapter was to describe the geographical distribution of women sexual violence in Tanzania. We used data from the Tanzanian demographic and health survey (2015/2016), comprising a random sample of 10,333 women aged 15–49 years. The study used ArcMap software version 10.8, for understanding the spatial pattern of sexual violence and Chi-square to find out the drivers of high women sexual prevalence rate across the regions. Findings show sexual violence was more prevalent in the Lake and Central zones. Wealth index, marital status, partner’s education, drinking habit and occupation were the main drivers.