Federal University, Birnin Kebbi is a university based in Birnin Kebbi, Kebbi State, Nigeria.The Federal University Birnin-Kebbi (FUBK) was established on 18 February 2013 alongside those of Gusau and Gashua by the Federal Republic of Nigeria under the leadership of President Goodluck Ebele Jonathan, GCFR, in line with the policy of the Government for establishing a Federal University in states that did not have one across the federation.Professor Lawal Suleiman Bilbis, FNSMB, a Professor of Biochemistry and former Deputy Vice-Chancellor Academic at Usmanu Danfodiyo University, Sokoto was appointed as the pioneer Vice Chancellor of the University while Ibrahim Abubakar Mungadi, FCAI, was appointed as the Registrar[citation needed].Academic activities began in November 2014, for the 2014/2015 academic session with a students’ population of 507 and academic staff strength of 102. Accordingly, maiden and second matriculation took place on 5 March 2015, and 9 February 2016, with a total of 507 and 972 Undergraduate sworn-in, respectively.The University currently has three faculties and a College of Health Sciences and offer a total of twenty-four (24) degree programmes.The University has six (6) directorates which include, Academic Planning, Physical Planning, Research and Innovation, ICT Directorate,Entrepreneurship and CSBE Directorate.The University just recently toward the ends of the year 2017 had the substantive leadership, where the federal government approved the appointment of Prof. Bello Bala Shehu as the new university vice-chancellor; Prof. B.B Shehu is a Medical Practitioner of neural science,he was also the former Chief Medical Director of the National Hospital, Abuja[citation needed].The university is maintaining two sites, the takeoff site and the permanent site, the takeoff site maintains the School for Basic and Remedial Studies and Females Hostels at Kalgo; whereas, the permanent site maintains the major campus capacity buildings at Unguwar Jeji (a village 4 kilometers away from the takeoff site.
Zero-dose children, defined as those who have not received a single dose of diphtheria-tetanus-pertussis vaccine (DPT1), represent a critical equity gap in global immunization efforts. Despite national efforts, little is known about the extent and distribution of zero-dose children in Somaliland, where fragile health systems and regional disparities may contribute to immunization inequities. This study aimed to estimate the prevalence of zero-dose immunization and examine regional and sociodemographic patterns among children aged 12–59 months in Somaliland. A descriptive cross-sectional analysis was conducted using data from the 2020 Somaliland Demographic and Health Survey (SDHS). The study population included 447 children aged 12–59 months with valid DPT1 vaccination data. Zero-dose status was defined as the absence of any reported receipt of DPT1, based on vaccination cards, maternal recall, or immunization marks. Weighted frequencies and proportions were used to summarize immunization status across key maternal, household, and geographic variables. Data analysis accounted for the complex survey design using Stata 17, and visualizations were generated with GeoPandas in Python. Half of the children (50
Introduction Institutional delivery dropout (IDD), defined as delivery outside a health facility despite attending antenatal care (ANC), remains a significant barrier to reducing maternal mortality in Nigeria. Traditional statistical models often fall short of capturing the complex, non-linear interactions among the socio-demographic factors that drive this critical health behavior. Methods Using a comprehensive dataset of 16,100 women from the 2018 Nigeria Demographic and Health Survey (NDHS), we applied and compared seven diverse machine learning (ML) algorithms, including models such as Support Vector Machine (SVM), Gradient Boosting (GB), and Extreme Gradient Boosting (XGBoost). The model performance was systematically evaluated using metrics such as accuracy, Area Under the Receiver Operating Characteristic curve (AUROC), F1-score, and detailed confusion matrices. Furthermore, SHapley Additive explanations (SHAP) were used to provide transparent interpretations of feature importance and predictive contributions. Results Gradient Boosting was the best-performing model, achieving the highest F1-score (0.755) and AUROC (0.82). SVM achieved the highest accuracy (0.740) and recall (0.780). SHAP identified education level, household wealth, and religion as strong predictors of IDD. The performance metrics reported with confidence intervals showed modest variability across the models. Conclusion Machine learning approaches were effective in identifying women at an increased risk of institutional delivery dropout. SHAP analysis provides insights into the key sociodemographic predictors of IDD, highlighting the value of interpretable ML methods in maternal health research.
Microplastics are an emerging class of environmental pollutants that have been widely investigated across various environmental matrices due to their ubiquity and potential toxicity. However, limited studies have explored the contribution of cement production facilities to microplastic pollution. This study evaluated the concentrations, characteristics, and associated health risks of microplastics in tomato fruits (Solanum lycopersicum) cultivated around the Sokoto Cement Factory. Tomato samples were collected from the northern, southern, eastern, and western axes surrounding the facility, homogenized, chemically digested, and analyzed using light microscopy and Fourier Transform Infrared (FTIR) spectroscopy. Microplastic concentrations ranged from 120 to 730 items/g, with the highest levels observed in the southern axis and the lowest in the northern axis. Four major microplastic morphotypes, fragments, fibers, foams, and pellets, were identified, with fibers being the dominant form. Most microplastics were transparent/white and blue in color, with size ranges of 100–500 µm and 500–1000 µm predominating. FTIR analysis identified polyethylene (PE), polyvinyl chloride (PVC), polypropylene (PP), and polyethylene terephthalate (PET), indicating inputs from multiple industrial and packaging-related sources. Heavy metal concentrations (Cd, Ni, Pb, Mn, and Cr) were determined, and correlation analysis revealed varying degrees of association between microplastic abundance and metal levels across the sampling locations. Polymer risk assessment revealed that PP posed a low risk (risk level II), PE and PET posed moderate risks (risk level III), while PVC presented a very high risk (risk level V) across all sampling locations. These results demonstrate that emissions and plastic-related activities associated with cement production can contribute to microplastic contamination of adjacent agricultural lands. Continuous environmental monitoring and improved waste management practices are therefore recommended to mitigate potential environmental and public health risks.
Microplastics, defined as synthetic polymer particles smaller than 5 mm, have become pervasive contaminants in aquatic sediments worldwide, where they function as long-term repositories that integrate multiple environmental stressors. Sediment concentrations are commonly three to five orders of magnitude higher than those measured in overlying water, reflecting continuous inputs from both primary microplastics intentionally produced at small sizes and secondary microplastics formed through fragmentation of larger plastic debris. This review synthesizes a current understanding of microplastic sources, transport processes, and ecological implications in sedimentary environments, while highlighting key barriers to effective management. Microplastics reach sediments through point sources such as wastewater treatment plants and industrial discharges, as well as diffuse pathways including atmospheric deposition and stormwater runoff. Their transport and accumulation are governed by polymer density, particle size, biofilm development, and hydrodynamic conditions. Once deposited, microplastics interact with surrounding sediments by sorbing persistent organic pollutants and trace metals, thereby modifying contaminant partitioning and potential bioavailability. Benthic deposit-feeding organisms are directly exposed through sediment ingestion, although field evidence linking sediment contamination to bioaccumulation and trophic transfer remains limited. Despite growing recognition of risk, major knowledge gaps persist. Methodological inconsistency in sampling, extraction, and polymer identification limits comparability among studies, while limited temporal monitoring constrains understanding of disturbance-driven redistribution. These scientific challenges are compounded by unequal monitoring capacity and regulatory development across regions, creating data-poor areas where contamination burdens may be substantial. Addressing sediment microplastic contamination requires coordinated progress in analytical standardization, advanced monitoring technologies, interdisciplinary collaboration, and integrated mitigation strategies that prioritize source reduction alongside technological and nature-based solutions.
Immunization remains one of the most effective strategies for preventing childhood morbidity and mortality, yet coverage in Somalia continues to be among the lowest globally. Persistent insecurity, population mobility, and systemic health system challenges limit the uptake of routine childhood vaccines. Given the extremely low levels of full immunization coverage reported nationally, this study assessed minimum immunization coverage, defined as a proxy indicator representing receipt of at least one dose of key childhood vaccines. The objective was to estimate the prevalence of minimum immunization coverage and examine maternal and household factors associated with childhood vaccination among children aged 12 to 23 months. This study analyzed nationally representative data from the 2020 Somalia Health and Demographic Survey. A total of 2,969 children aged 12 to 23 months were included. Weighted descriptive statistics were used to summarize population characteristics, with percentages adjusted for the complex survey design, while bivariate and multivariable logistic regression analyses identified factors associated with minimum immunization coverage. All analyses accounted for the complex sampling design, and statistical significance was set at p < 0.05. Only 4
