Background. Missing data are a prevalent problem in almost all types of data analyses, such as survival data analysis. Objective. To evaluate the performance of multivariable imputation via chained equations in determining the factors that affect the survival of multidrug-resistant-tuberculosis (MDR-TB) and HIV-coinfected patients in KwaZulu-Natal. Materials and Methods. Secondary data from 1542 multidrug-resistant tuberculosis patients were used in this study. First, data from patients with some missing observations were deleted from the original data set to obtain the complete case (CC) data set. Second, missing observations in the original data set were imputed 15 times to obtain complete data sets using a multivariable imputation case (MIC). The Cox regression model was fitted to both the CC and MIC data, and the results were compared using the model goodness of fit criteria [likelihood ratio tests, Akaike information criterion (AIC), and Bayesian Information Criterion (BIC)]. Results. The Cox regression model fitted the MIC data set better (likelihood ratio test statistic =76.88 on 10 df with P0.01, AIC =1040.90, and BIC =1099.65) than the CC data set (likelihood ratio test statistic =42.68 on 10 df with P0.01, AIC =1186.05 and BIC =1228.47). Variables that were insignificant when the model was fitted to the CC data set became significant when the model was fitted to the MIC data set. Conclusion. Correcting missing data using multiple imputation techniques for the MDR-TB problem is recommended. This approach led to better estimates and more power in the model./p

Termination of pregnancy continues to be one of the major public health problems. The prevalence and determinants associated with pregnancy termination among women from low-middle income countries such as Tanzania have previously not been thoroughly investigated. Therefore, this study aims to explore the prevalence and determinants associated with pregnancy termination among Tanzanian women. Data for this study was extracted from the 2022 Tanzania Demographic and Health Survey (TDHS). A total of 15,254 women aged 15–49 years, clustered in selected enumerated areas, participated in the survey. A modified Poisson regression model with sampling weights was used to find the factors that are associated with pregnancy termination. The prevalence of pregnancy termination was 14.3% (95% CI: 13.81–14.75%). Our findings reveal that several factors are significantly associated with pregnancy termination. In particular, women’s age, level of education, marital status, history of pregnancy losses, wealth status, attempt to delay or avoid getting pregnant outside the ideal birth spacing, and recent internet use, total children ever born, desire for more children, were significantly associated with pregnancy termination. Women who reside in rural areas, those covered by health insurance and those using contraceptives had a significantly lower likelihood of terminating pregnancy compared to their counterparts. The findings highlighted that the prevalence of terminating pregnancy is alarming in Tanzania, signaling a significant public health challenge. To address the concerning rates of pregnancy termination, the government of Tanzania and other institutions are advised to enhance the accessibility and quality of healthcare services for women, particularly in rural and underserved areas. Bridging socio-economic inequalities and removing geographic barriers to healthcare access will ensure women receive timely and adequate support.

Amasi, a traditional fermented milk produced in Southern Africa, is associated with several health benefits, such as probiotic activities, immune system modulation, and pharmacological (antimicrobial, antitumor and antioxidant) potential. This study investigated the microbial diversity in Amasi (produced from cow’s and goat’s milk) through targeted metagenomic bacterial 16S rRNA and fungal ITS sequencing, the metabolic functional prediction of Amasi samples using the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) and profiled amino acids constituents using Liquid Chromatographic-Mass Spectrophotometry (LC-MS). The results obtained revealed Firmicutes, Bacteroidetes, and Proteobacteria as the most prevalent bacterial phyla, with Lactococcus and Lactobacillus being the most abundant genera. On the other hand, Ascomycota, Basidiomycota, and Mucoromycota were the main fungal phyla, while Aspergillus, Kazachstania, and Debaryomyces spp. dominated the fungal genera. Also, Pseudomonas spp., Bacillus spp., Clostridium spp., Cronobacter spp., Alternaria spp., Diaporthe spp., and Penicillium spp. were the probable pathogenic bacteria and fungi genera found, respectively. Atopobium, Synechococcus, and Parabacteroides were found less often as rare genera. It was found that the amino acid and drug metabolism pathway prediction values in Amasi samples were significantly higher (p < 0.05) than in raw cow and goat milk, according to the inferred analysis (PICRUSt). The amino acid validation revealed glutamine and asparagine values as the most significant (p < 0.05) for Amasi cow milk (ACM) and Amasi goat milk (AGM), respectively. Comparatively, ACM showed more microbial diversity than AGM, though there were relative similarities in their microbiome composition. PICRUSt analysis revealed significant metabolites in the two Amasi samples. Overall, data from this study showed heterogeneity in microbial diversity, abundance distributions, metabolites, and amino acid balance between raw cow/goat milk and Amasi samples.

Academic counseling plays a crucial role in student support within higher education institutions, contributing not only to academic achievement but also to career development and entrepreneurial initiatives. This study investigates the impact of academic advising on fostering entrepreneurial intentions among students at the Durban Institute of Technology (DUT) in South Africa. Utilizing planned behavioral theory as a conceptual framework, this research explores how academic guidance affects students' attitudes toward entrepreneurship, subjective norms, and perceived behavioral control, ultimately influencing their intention to engage in entrepreneurial activities. Data analysis conducted using SPSS 30.0 revealed a significant positive correlation between academic counseling and entrepreneurial intentions (r = 0.612, p < 0.001). Key findings indicate that academic advising enhances entrepreneurial awareness and provides essential information while also highlighting a gap in connecting students with practical resources, such as business planning and funding support. Additionally, this study reveals that Generation Z students prefer digital advisory tools, although they still value traditional learning methods for guidance. Recommendations include expanding mentoring programs, enhancing collaboration between universities and industries, and leveraging technology to improve advisory services. Moreover, addressing gender-influenced and culturally integrated advisory practices can support underrepresented student groups in entrepreneurship. Future research should focus on the longitudinal effects of academic advising on entrepreneurial success and explore best practices for integrating entrepreneurship into academic counseling models.

This study investigated teachers’ preparedness, attitudes, and the perceived impact of technology use in lesson delivery in selected Zimbabwean secondary schools. Guided by the Technology Acceptance Model (TAM) and the Technological Pedagogical Content Knowledge (TPCK) Framework, it examined how teacher readiness, institutional support, and infrastructure affect ICT integration. Quantitative data from 59 teachers were analysed using SPSS version 30. Results indicated that teachers generally had positive attitudes and moderate ICT competence, recognising technology’s benefits for student engagement and performance. However, inadequate infrastructure and limited support constrained effective use. The study recommends continuous training, improved resources, and supportive policies for sustainable ICT-driven education.

Cervical cancer continues to be a major global public health problem, with 661,021 estimated new cases and 348,189 deaths reported in 2022. Approximately 53% of women in Jordan reported not being screened for CC in recent years. This study aimed to investigate the determinants associated with not being screened for CC amongst Jordanian women of child-bearing age. This was a cross-sectional study derived from the 2023 Jordanian Demographic Health Survey (JDHS) with 12,580 women aged 15–49 years. The study employed a non-informative Bayesian binary logistic regression approach to identify the factors that are associated with not being screened for CC. Results showed that the prevalence of not being screened for CC was 83.8% (95% CI: 83.3–84.3). The determinants identified in this study were women’s age group (OR = 0.46; 95% CI: 0.34–0.62), education level (OR = 0.56; 95% CI: 0.34–0.91), smoking status (OR = 0.75; 95% CI: 0.63–0.91), women’s nationality (OR = 4.30; 95% CI: 1.03–27.74), breastfeeding status (OR = 1.64; 95% CI: 1.31–2.07), wealth index (OR = 0.61; 95% CI: 0.53–0.71), self-reported health status (OR = 0.74; 95% CI: 0.64–0.87), marital status (OR = 1.45; 95% CI: 1.08–1.96), and HIV testing status (OR = 0.55; 95% CI: 0.40–0.75). The prevalence of not being screened for CC amongst Jordanian women of child-bearing age was found to be very high: a red flag for attention. There is a need for interventions such as community awareness campaigns and education programmes focusing on women younger than 25 years, especially women living in rural and underserved areas. Additionally, incorporating policy interventions into public health facilities and having easy accessibility to tools or screening tests may improve rates of CC screening, and thus reduce the prevalence of CC.