Background: An edible oil factory is a labor-intensive and technologically complex industry, with workers potentially exposed to a variety of dangers associated with such industries. Personal protective equipment is a universal, legal requirement, and an important strategy for preventing occupational injuries and illnesses caused by workplace hazards. However, such industries receive little attention, especially in Ethiopia.
Objective: To assess personal protective equipment utilization and its associated factors among workers in the PhiBela edible oil factory in Burie, Ethiopia, in 2022.
Methods: A cross-sectional study was employed among the PhiBela edible oil factory workers in Burie. A simple random sampling technique was used to select 389 PhiBela edible oil factory workers. Face-to-face interviews and self-administered structured questionnaires were used to collect data on workers' protective equipment utilization practice, socio-demographic, work-related, environmental, and organizational factors. Data was analyzed using SPSS version 25. The logistic regression method was used to see factors associated with workers' protective equipment utilization. The strength of the association was calculated using an odds ratio at 95% confidence intervals.
Results: Of the total workers, 216, 55.52% (48.33-57.78) workers utilize personal protective equipment in the factory. The study showed safety training [AOR (4.68, 95%CI (2.76-7.45)], availability of personal protective equipment [AOR = 4.86; 95%CI: 2.23-6.98], regular health and safety supervision [AOR = 2.751; 95%CI: 1.806-3.801], availability of safety guideline at workplace [AOR = 3.798; 95%CI: 1.248-6.173], having work experience 3 years and above [AOR = 1.64; 95%CI: 1.06-2.18], not using alcohol [AOR = 3.07; 95%CI: 2.11-4.76], and not smoking cigarette [AOR = 1.88; 95%CI: 1.55-3.11] were predictors of personal protective equipment utilization.
Conclusion: The level of personal protective equipment utilization among Phibela edible oil factory workers is 55.52%, which is moderate when compared to other studies done in developing countries. The presence of Safety training, availability of personal protective equipment, regular health and safety supervision, availability of guidelines at workplaces, having work experiences, not using alcohol, and cigarrete smoking were factors found to be a significant predictors of personal protective equipment utilization. As a result, close workplace supervision, safety training, and availing guidelines are the recommendations to be in place.

Keywords: Ethiopia; Utilization; factory worker; personal protective equipment.

Background: An edible oil factory is a labor-intensive and technologically complex industry, with workers potentially exposed to a variety of dangers associated with such industries. Personal protective equipment is a universal, legal requirement, and an important strategy for preventing occupational injuries and illnesses caused by workplace hazards. However, such industries receive little attention, especially in Ethiopia.
Objective: To assess personal protective equipment utilization and its associated factors among workers in the PhiBela edible oil factory in Burie, Ethiopia, in 2022.
Methods: A cross-sectional study was employed among the PhiBela edible oil factory workers in Burie. A simple random sampling technique was used to select 389 PhiBela edible oil factory workers. Face-to-face interviews and self-administered structured questionnaires were used to collect data on workers' protective equipment utilization practice, socio-demographic, work-related, environmental, and organizational factors. Data was analyzed using SPSS version 25. The logistic regression method was used to see factors associated with workers' protective equipment utilization. The strength of the association was calculated using an odds ratio at 95% confidence intervals.
Results: Of the total workers, 216, 55.52% (48.33-57.78) workers utilize personal protective equipment in the factory. The study showed safety training [AOR (4.68, 95%CI (2.76-7.45)], availability of personal protective equipment [AOR = 4.86; 95%CI: 2.23-6.98], regular health and safety supervision [AOR = 2.751; 95%CI: 1.806-3.801], availability of safety guideline at workplace [AOR = 3.798; 95%CI: 1.248-6.173], having work experience 3 years and above [AOR = 1.64; 95%CI: 1.06-2.18], not using alcohol [AOR = 3.07; 95%CI: 2.11-4.76], and not smoking cigarette [AOR = 1.88; 95%CI: 1.55-3.11] were predictors of personal protective equipment utilization.
Conclusion: The level of personal protective equipment utilization among Phibela edible oil factory workers is 55.52%, which is moderate when compared to other studies done in developing countries. The presence of Safety training, availability of personal protective equipment, regular health and safety supervision, availability of guidelines at workplaces, having work experiences, not using alcohol, and cigarrete smoking were factors found to be a significant predictors of personal protective equipment utilization. As a result, close workplace supervision, safety training, and availing guidelines are the recommendations to be in place.

Keywords: Ethiopia; Utilization; factory worker; personal protective equipment.

The primary objective of this study was to investigate the practices and challenges of good governance in urban land administration, with a particular focus on the Debre Markos City Administration. The study selected the Debre Markos City Administration Municipality service office as a case study. This study employed a mixed research approach, and data were collected through questionnaire and interview methods obtained from both public servants and customers. The data was analysed through descriptive analysis. Based on the analysis conducted using three core elements of good governance—transparency, accountability, and responsiveness, the study found that there were poor practices of good governance in urban land administration. On the other hand, the study investigated various challenges of good governance in urban land administration, which emanate from personal, administrative, and socio-economic problems such as the absence of innovative figures of land registration, lack of monitoring and evaluation, inadequate institutional performance, and absence of reward and punishment systems. In general, the findings of this study revealed that due to various challenges, there were poor practices of good governance in terms of transparency, accountability, and responsiveness in the study area. These challenges impede people’s access to quality service in urban areas and undermine the trust between citizens and the government. Finally, enhancing institutional capacity, consistent implementations of monitoring and evaluation, innovative figures of land registration, and giving corrective measures for wrongdoers were stated as recommendations.

Executive Summary Background and objectivesDiabetes mellitus (DM) and hypertension (HTN) are leading causes of cardiovascular disease, death, and disability, with a growing burden in developing countries. Early detection is essential, and machine learning (ML) offers powerful tools for predicting diseases risk by uncovering complex patterns in health data. At the same time, the Health Belief Model (HBM) explains preventive behaviors through constructs such as perceived susceptibility, severity, benefits, barriers, self-efficacy, and cues to action. This study integrates ML-based predictive modeling with the HBM to identify individuals at risk of HTN and DM and to better understand the behavioral factors influencing prevention, employing a dataset collected in 2025. Materials and methodsData on DM and hypertension HTN were collected from 1,771 employees of Debre Markos, Injibara, and Bahir Dar universities in Northwest Ethiopia. The cross-sectional survey included demographic, health-related, and behavioral factors, with constructs from the Health Belief Model (HBM) such as perceived susceptibility, severity, benefits, barriers, self-efficacy, and cues to action. RFE was applied to identify the most relevant predictors of DM and HTN. Four machine learning algorithms—Logistic Regression (LR), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and k-Nearest Neighbor (kNN) were developed using theselected features. Model performance was evaluated based on accuracy, precision, recall, the F1-score, and the area under the ROC curve. ResultsThis study found that the ensemble ML models, RF and GBDT, outperformed in predicting HTN and DM, achieving higher accuracy, precision, recall, F1-score, and area under the ROC curve. Analysis of Health Belief Model (HBM) constructs further showed that preventive behaviors were positively associated with perceived susceptibility, severity, benefits, self-efficacy, and cues to action, while perceived barriers were negatively associated. Perceived susceptibility emerged as a significant predictor of HTN and DM, and cues to action contributed to the identification of undiagnosed DM cases.

Flooding exacerbates health challenges by spreading waterborne diseases like diarrhea throughthe destruction of sanitation infrastructure and contamination of drinking water sources. However,evidence on the prevalence and contributing factors of diarrheal diseases among under-five childrenin the Dasenech district is limited. This study aimed to assess the prevalence of acute diarrhea andits determinants among under-five children in flood-affected areas of the South Ethiopia region. Acommunity-based cross-sectional study was conducted from July 1 to July 15, 2024, in flood-affectedareas of the Dasenech district, involving 696 under-five children. Five kebeles were purposivelyselected, followed by the proportional allocation of households, after which a systematic samplingtechnique was applied to identify study participants. Data were collected using a pretested andstructured questionnaire administered by trained interviewers. Multivariable logistic regressionanalysis was performed to identify factors associated with acute diarrhea, with statistical significanceset at p < 0.05 and a 95% confidence interval (CI). The prevalence of acute diarrhea was 31.6% (95%CI: 28.7–34.3%). Significant predictors of acute diarrhea included non-adherence to exclusivebreastfeeding (AOR: 2.14, 95% CI: 1.65–3.98), lack of latrines (AOR: 12.08, 95% CI: 9.77–13.13), unsafedisposal of child excreta (AOR: 3.86, 95% CI: 2.38–6.26), home delivery (AOR: 6.02, 95% CI: 5.53–8.82),and a recent history of diarrhea among mothers or caregivers (AOR: 3.14, 95% CI: 1.33–5.66). Acutediarrhea is highly prevalent among under-five children in the Dasenech district. The findings underscorethe need for targeted public health measures, such as improving waste management, promotingexclusive breastfeeding, constructing and utilizing latrines, and addressing maternal and caregiverhealth, to mitigate the burden of diarrheal diseases in this vulnerable population.Keywords Acute diarrhea, Dasenech district, Ethiopia, Flood-affected, Under-five childrenDiarrhea is defined as an increase in bowel movement frequency or a change in stool consistency, commonlyidentified as the passage of three or more loose or watery stools within a 24-h period1. This condition oftenresults from intestinal infections caused by bacteria, viruses, or parasites, which are closely associated withlimited access to safe water and inadequate sanitation facilities2. Inadequate water and sanitation contributeto over 94% of the four billion annual cases of diarrhea worldwide3,4. This condition claims approximately twomillion lives each year, representing 4% of global mortality. Alarmingly, 1.3 million of these deaths occur amongchildren annually5.

Introduction: Occupational health problems are the major issues of the world, particularly in developing countries. Sanitation workers are facing various health problems with little attention while conducting their day today activities. The review emphasizes the critical need for policies that ensure safety standards, provide proper protective gear, and establish regular health monitoring to protect workers' health and wellbeing.
Objective: The aim of the study was to assess the prevalence of respiratory symptoms and associated factors among sanitation workers in Sub-Saharan Africa.
Methods and materials: This systematic review and meta-analysis was done based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA 2020). Literatures were searched using various database like Google scholar, Science-Direct, Pub-Med (Medline), Hinari, and Google. From eligible studies, data was extracted using Microsoft excel and exported to STATA version 14 statistical software for analysis. The prevalence of respiratory symptom was estimated using a random effect model. Publication bias was determined using Egger test and funnel plot whereas heterogeneity was evaluated using I2. Fortunately, 13 studies were included with a total participants of 4,401.
Results: The pooled prevalence of respiratory symptoms among sanitation workers was 43.79% (95% CI: 35.26, 52.33; I 2 = 97.3%, p < 0.000). Sanitation workers with a history of respiratory illness were 4.16 times more likely to have had respiratory symptoms compared to those without a history (OR: 4.16, 95% CI: 2.67, 5.66). Additionally, sanitation workers who did not wear nose/mouse masks were 2.36 times more likely to experience respiratory symptoms compared to their counterparts (OR: 2.36, 95% CI: 1.40, 3.32). Moreover, Sanitation workers with working experiences of greater than five were 1.81 times more likely to experience respiratory symptoms than those with less than 5 years working experiences (OR: 1.81, 95% CI: 1.26, 2.39).
Conclusion: Generally, half of the sanitation workers experienced respiratory symptoms. The symptoms were associated with history of respiratory illness, utilizing of nose/ mouth face mask and working experience. Hence, awareness creation session should conducted mainly for those with history of respiratory illness and poor personal protective users.

Keywords: Sub Saharan Africa; prevalence; respiratory–epidemiology; risk factors; sanitation workers; systematic review and meta-analysis.

Background: Neisseria gonorrhoeae is the causative agent of gonorrhea and accounts for the majority of sexuallytransmitted infections globally. There are few studies on the prevalence and antimicrobial susceptibility patternsof N. gonorrhoeae in Ethiopia.Objective: This study aimed to assess the prevalence, antimicrobial susceptibility patterns, and associated factorsof N. gonorrhoeae.Method: A cross-sectional study was conducted among women attending Debre Markos town health institutions;in Northwest Ethiopia from June 1, 2022 to October 30, 2022. An endocervical swab was collected and culturedon Modified Thayer Martin medium. Antimicrobial susceptibility testing was performed using the modifiedKirby-Bauer disk diffusion technique for isolates, following Clinical and laboratory standards institute guidelines.Logistic regression was applied to show the relationship between dependent and independent variables. P-value

Background: Big health data is a large and complex dataset that the health sector has collected andstored continuously to generate healthcare evidence for intervening the future healthcare un-certainty. However, data use for decision-making practices has been significantly low in devel-oping countries, especially in Ethiopia. Hence, it is critical to ascertain which elements influencethe health sector’s decision to adopt big health data analytics in health sectors. The aim of thisstudy was to identify the level of readiness for big health data analytics and its associated factorsin healthcare sectors.Methods: A cross-sectional study design was conducted among 845 target employees using thestructural equation modeling approach by using technological, organizational, and environ-mental (TOE) frameworks. The target population of the study was health sector managers, di-rectors, team leaders, healthcare planning officers, ICT/IT managers, and health professionals.For data analysis, exploratory factor analysis using SPSS 20.0 and structural equation modelingusing AMOS software were used.Result: 58.85 % of the study participants had big health data analytics readiness. Complexity (CX),Top management support (TMS), training (TR) and government law policies and legislation(GLAL) and government IT policies (GITP) had positive direct effect, compatibility (CT), andoptimism (OP) had negative direct effect on BD readiness (BDR)Conclusion: The technological, organizational, and environmental factors significantly contributedto big health data readiness in the healthcare sector. The Complexity, compatibility, optimism,Top management support, training (TR) and government law and IT policies (GITP) had effect onbig health data analytics readiness. Formulating efficient reform in healthcare sectors, especially
or evidence-based decision-making and jointly working with stakeholders will be more relevantfor effective implementation of big health data analytics in healthcare sectors.
Keywords: Big health data, Data analytics, Data management, Health information revolution, Health sectors, Readiness

Background: Children on the streets are still vulnerable to early and unsafe sexual experiences. Having multiple sexual partners and the limited use of condoms were major risk factors for the spread of sexually transmitted diseases among youths in Ethiopia.
Objective: This study aimed to explore the risk factors of sexual and reproductive health problems, service utilization, and challenges among street youths in the East Gojjam Zone.
Method: A phenomenological study design was employed on street youths residing in the East Gojjam Zone. Study participants were purposively recruited from four town administrations in the East Gojjam Zone. The primary study unit was street youths who live in the zone. Eight in-depth interviews and eight focus group discussions were conducted. The data were audio recorded and analyzed using inductive thematic analysis.
Results: In this study, the risk factors that exposed street youths to sexual and reproductive health problems included low perceived susceptibility, lack of awareness of sexual and reproductive health, having multiple sexual partners, exposure to pornographic films, and utilization of alcoholic drinks and substances. Mainly, those street youths who were engaged in transactional sexual relationships were utilizing condoms consistently and had regular HIV screening tests. In addition, few street youths ever utilized maternal and child health services. The unsupportive behavior of health professionals, the absence of exact data, the health system, and lack of specific responsible organization on the sexual and reproductive health of street youths were considered major challenges.
Conclusion and recommendation: Most of the street youths were not utilizing reproductive health services. Limitation on the accessibility of sexual and reproductive health services to this segment of the population was the main contributing factor. So, the health system and policy should take front-line responsibility for the sexual and reproductive health of street youths and consider convenient reproductive health service programs for them.

Keywords: Risk factors; Sexual and reproductive health service utilization; Street youths.

Background Understanding the student’s perspective of their clinical learning environment (CLE) might assist todiscover solutions to improve the learning process and increase engagement. However, there is a lack of informationon this issue, particularly in Ethiopia. The purpose of this study was to assess the satisfaction of undergraduatemedical and health science students with their clinical learning environment, as well as to identify the factors thataffect it.Methods Institutional-based cross-sectional study was conducted using a self-administered questionnaire among412 medical and health science students from Debre Markos University in 2023 through a simple random samplingtechnique. Mean, median, frequencies, and percentages were used to describe the data. A multivariate logisticregression model was fitted to test the association of dependent and independent variables. The Hosmer-Lemeshowgoodness-of-fit test was used to check the fitness of the model. Variables with a p-value < 0.05 with a 95% confidenceinterval were considered statistically significant.Results The questionnaire was completed by 394 individuals in total, generating a response rate of 95.63%.Approximately half (49.7%) of the participants were satisfied with their CLE. Age (AOR = 1.12; 95%CI = 1.02, 1.22),university positive perceptions (AOR = 1.60; 95%CI = 1.04, 2.43) and curriculum positive perception (AOR = 2.70;95%CI = 1.73, 4.10) were all positively associated with CLE satisfaction.Conclusion In this study, approximately half of the respondents were satisfied with their CLE. Age, positiveperceptions of the university and positive perceptions of the curriculum were all positively associated with CLEsatisfaction. The university and clinical facilitators should work together to improve infrastructure, and the facilities