Search

Abstract Background Birth-related mortality is significantly increased by home births without skilled medical assistance during delivery, presenting a major risk to the public’s health. The objective of this study is to predict home delivery and identify the determinants using machine learning algorithm in sub-Saharan African. Methods This study used design science approaches. The data set obtained from demographic health survey in sub-Saharan African weighted sample of 299,759 women was included in the stud. Machine learning models such as Random Forest, Decision Tree, K-Nearest Neighbor, Logistic Regression, Extreme Gradient Boosting, AdaBoost, Artificial Neural Network, and Naive Bayes were used. The predictive model was evaluated by area under the curve, accuracy, precision, recall, and F-measure. Results The final experimentation results indicated that random forest model performed the best to predict home delivery with accuracy (83%) and, ROC curve (89%). The Shapley additive explanation features an importance plot optimized for random forest model to identifying the most predictors of home delivery. Association rules findings showed that inadequate antenatal care visits, marital status married, no education, mobile phone, television, electricity, poor wealth index, infrequent television viewing, and rural residence were predictor of home delivery. Conclusion The random forest machine learning model provides greater predictive power for estimating home delivery risk factors. To reduce the prevalence of home delivery, this finding recommends to emphasis on improving antenatal care services, education, and awareness about health facility delivery.

Abstract Background Colostrum is the first form of milk produced immediately following the delivery of a newborn. It is highly nutritious and contains antibodies to protect the newborn against disease and crucial for the newborn’s health Despite its benefits, some mothers avoid giving colostrum to their newborns. Objective This study aims to assess the prevalence and factors associated with colostrum avoidance among postnatal mothers in Addis Ababa, Ethiopia. Methods A health facility-based mixed-methods of study design was conducted. Both quantitative and qualitative data were collected using pretested questionnaires and key informant interview question guides, respectively.Quantitative data were collected through structured interviews and analyzed using descriptive statistics such as frequencies, means, and standard deviations were performed. Binary logistic regression analysis was employed to assess the associated factors of colostrum avoidance among postnatal mothers at health facilities in study area.Qualitative data were gathered via in-depth interviews and analyzed thematically. Results The prevalence of colostrum avoidance was 8.94% (95% CI: 5.9–10.9). Multivariable analysis revealed significant predictors of colostrum avoidance: lack of counseling about colostrum benefits (AOR = 5.802, 95% CI: 2.467–13.647), cesarean delivery (AOR = 3.420, 95% CI: 1.411–8.288), poor maternal knowledge about colostrum (AOR = 13.111, 95% CI: 5.462–31.468), and late initiation of breastfeeding (AOR = 3.330, 95% CI: 1.242–8.926). Qualitative findings echoed these results, with cultural beliefs and misconceptions about colostrum contributing to its avoidance. Conclusion The study highlights a significant prevalence of colostrum avoidance among postnatal mothers in Addis Ababa. Key predictors include inadequate counseling, cesarean delivery, poor knowledge about colostrum, and delayed breastfeeding initiation. Interventions aimed at improving maternal education and breastfeeding practices are essential to reduce colostrum avoidance.

Abstract Background Early and accurate diagnosis of drug resistance, including resistance to second-line anti-tuberculosis (TB) drugs, is crucial for the effective control and management of pre-extensively drug-resistant TB (pre-XDR-TB) and extensively drug-resistant TB (XDR-TB). The Xpert MTB/XDR assay is the WHO recommended method for detecting resistance to isoniazid and second-line anti-TB drugs when rifampicin resistance is detected. Currently, the Xpert MTB/XDR assay is not yet implemented in Ethiopia, thus the MTBDRsl assay continues to be used. However, the MTBDRsl assay requires additional patient visits and specimen collection, which can lead to delays in diagnosis and treatment initiation. Objective This study aimed to evaluate the feasibility of using extracts from used Xpert MTB/RIF cartridges for detecting resistance to second-line anti-TB drugs by MTBDRsl assay in patients with rifampicin resistant-TB (RR-TB) in Eastern and Western Oromia, Ethiopia. Methods A cross-sectional diagnostic evaluation study was conducted from June 2020 to May 2021 at two TB Referral Laboratories in Eastern and Western Oromia, Ethiopia. Sputum samples from RR-TB patients were split, with one aliquot being subjected for Xpert testing and the other being cultured on Lowenstein-Jensen media. DNA extracted from the used Xpert cartridges was amplified by PCR and tested by MTBDRsl assay, and the results were compared to those obtained from culture isolates. To establish the detection limits, the MTBDRsl assay was performed on cartridge extracts (CEs) from a series of dilutions of drug-susceptible and multidrug-resistant TB strains. Results The MTBDRsl on CEs from dilutions at ≥ 102 CFU/mL (CT ≤ 22) accurately identified susceptibility and resistance patterns for fluoroquinolones (FQL) and second-line injectable drugs (SLIDs). The MTBDRsl on rifampicin-resistant CEs from sputum samples (n = 40) yielded 100% interpretable results for FQL and 90% (4 indeterminate) interpretable results for SLIDs. All interpretable CE results showed complete agreement with the MTBDRsl results from the culture isolates. Conclusion This study demonstrated the feasibility of using extracts from used Xpert MTB/RIF cartridges for detecting resistance to second-line anti-TB drugs using the MTBDRsl assay. This approach could mitigate the need for additional specimen collection and allow for earlier treatment initiation, potentially improving patient outcomes and reducing the transmission of drug-resistant TB strains.

Abstract Universal immunization of children against common vaccine-preventable diseases is crucial in reducing infant and child morbidity and mortality. Assessing the vaccination coverage is a key step to improve utilization and coverage of vaccines for under-five children. Accordingly, vaccination coverage according to the national schedule assesses the vaccination coverage of children aged 12–35 months. However, there is a scarcity of information on the full vaccination coverage according to the national schedule and its determinants in Ghana. Therefore, this study aimed to assess the prevalence and predictors of vaccination coverage according to the national schedule among children aged 12–35 months in Ghana. A cross-sectional study design using the most recent demographic and health survey data from the Ghana Demographic and Health Survey was used. We included a total weighted sample of 1,823 children aged 12–35 months in the five years preceding the survey. We used a multilevel logistic regression model to identify associated factors for vaccination coverage according to the national schedule in Ghana. The adjusted odds ratio at 95% Cl was computed to assess the strength and significance of the association between explanatory and outcome variables. Factors with a p-value of

Abstract Background Depressive symptom is the most common type of psychiatric co-morbidity among persons with epilepsy. Epilepsy patients are identified as at higher risk of suffering depressive symptom explicitly in low- and middle-income countries due to poor mental health care systems and financial burdens. The co-occurrence of depressive symptom among epilepsy patients deteriorates the prognosis of the disease and diminishes the quality of life of both the patients and their families. However, there is limited evidence on the prevalence of depressive symptom and associated factors in Ethiopia. Therefore, this study is intended to assess the prevalence of depressive symptom and associated factors among epilepsy patients attending in Amhara region, Ethiopia. Method A multi-center institution-based cross-sectional study was done among epilepsy patients attending at Amhara region, Ethiopia. The Hospital Anxiety Depression tool was used to assess depressive symptom. To determine the factors associated with depressive symptom, a binary logistic regression model was used. Adjusted Odds Ratio (AOR) with the 95% Confidence Interval (CI) was reported in the multivariable binary logistic regression analysis. Results About 406 participants were registered in the study with a response rate of 97.6%. The prevalence of depressive symptom among epilepsy patients was 53.9% [95%CI: 49.1%, 58.8%]. In the multivariable binary logistic regression analysis, taking polytherapy treatment [AOR = 1.87, 95% CI: 1.04, 3.36], perceived stigma [AOR = 5.73, 95%CI: 3.11, 10.55], poor antiepileptic medication adherence [AOR = 3.33, 95%CI: 1.30, 8.54] and having poor [AOR = 5.83, 95%CI: 2.44, 13.90] and moderate social support [AOR = 3.08, 95%CI: 1.34, 7.09] were significantly associated with depressive symptom. Conclusions This study revealed that the magnitude of depressive symptom among epilepsy patients in Ethiopia was relatively high and multiple factors determined the likelihood of depressive symptom. Thus, healthcare providers and concerned stakeholders should strengthen comprehensive health education to reduce the magnitude and consequences of depressive symptom among this segment of the population. Moreover, strong social support with special attention should be given to epilepsy patients.

Abstract Background Metabolic syndrome has become a major public health problem worldwide and is attributable to the spread of different non-communicable diseases such as type 2 diabetes mellitus, coronary artery diseases, stroke, and permanent or temporary disabilities. It is not a single disease entity but encompasses different risk factors. However, there were inconsistencies among previously conducted primary studies, hence this systematic review and meta-analysis aimed to determine the pooled prevalence and determinants of metabolic syndrome among type2 diabetes patients in Ethiopia. Method First-hand studies about the metabolic syndrome among adult type 2 diabetic patients in Ethiopia were searched through known and international databases (PubMed, Scopus, Web of Science, and Cochran Library) and search engines (Google and Google Scholar). Data was extracted using a standard data extraction checklist developed according to Joanna Briggs Institute (JBI). The I2 statistics are used to identify heterogeneity across studies. Funnel plot asymmetry and Egger’s tests were used to check for publication bias. A random effect model was used to estimate the pooled prevalence of the metabolic syndrome among non-insulin-dependent patients in Ethiopia. The STATA version 11 software employed for statistical analysis was conducted using STATA version 11 software. Result The overall pooled prevalence of metabolic syndrome among type2 diabetic patients in was 54.56% [95%CI (43.73, 65.38), I2 = 97.0%, P = 0.001] using NCEP-ATP III, 48.32% [95%CI (42.1, 54.44), I2 = 97.0%, P = 0.001] IDF diagnosis criteria, 47.0[95%CI(27.01–66.99)], I2 = 97.5%, p = 0.001 using WHO and 59.37%(95%CI(47.21–71.52), I2 = 91.2%, p = 0.001 using harmonized diagnosis criteria respectively. This meta-analysis identified several significant predictors of metabolic syndrome among type 2 diabetes patients in Ethiopia. The odds of having metabolic syndrome was reduced for females (Adjusted Odds Ratio [AOR] = 0.55, 95% CI: 0.35–0.87) compared to males. However, the odds of metabolic syndrome increased with alcohol intake (AOR = 1.44, 95% CI: 1.03–2.01), the odds of living in urban areas(AOR = 2.12, 95% CI: 1.55–2.88), and the odds of having a diabetes duration of six or more years since diagnosis (AOR = 2.94, 95% CI: 1.17–7.41) were significant predictors. Conclusion The pooled prevalence was considerably high among type 2 diabetic patients in Ethiopia. The pooled prevalence of metabolic syndrome varies as per the diagnosis criteria used with the highest observed in harmonized diagnosis criteria. Being female, being rural residency, alcohol intake, and duration of diabetes since diagnosis were significant predictors of metabolic syndrome among type 2 diabetic patients in Ethiopia.

In this study deuteron induced nuclear reaction on 20Ne target was studied to get nuclear information about 18F and 21Na radioisotopes which are widely used in medical and nuclear reactor technologies respectively. This nuclear reaction is important to get nuclear data since the produced radioisotope is widely used in nuclear medicine due to its appropriate short half-life and positron emitter. The main objective of the study was to analyse and interpret the behaviour of the resulting reaction cross section. It also aimed to compare the computed theoretical result with the experimental data retrieved from IAEA EXFOR for its validity. From such nuclear reaction, the reaction cross sections of 20Ne(d, α)18F, 20Ne(d, x)18F, and 20Ne(d, n)21Na reaction channels were computed using a nuclear computational code called COMPLET. The computed reaction cross sections for each channel were found in good agreement with the experimental data within the specified energy range and show a strong correlation as assessed by Pearson’s correlation coefficient. The analysis of the result shows that compound nucleus reaction is found the dominant reaction mechanism at the lower energies of the projectile.

Introduction: Understanding the extent to which faculty members' beliefs, attitudes, and acceptance of educational technologies for learning is crucial for enhancing the effectiveness of technology and ensuring its long-term viability. However, higher education institutions have made significant investments in educational technology for learning without fully comprehending faculty members' beliefs, attitudes, and level of acceptance of these technologies. This lack of understanding has hindered the effectiveness of these investments. Therefore, this study aims to examine faculty members' beliefs, attitudes and level of acceptance towards educational technology in higher education institutions in Ethiopia. Methods: A survey was conducted at five public higher education institutions that offer priority health training programs. The survey collected data using the Unified Theory of Acceptance and Use of Technology, focusing on four key determinants. Faculty members were asked to rate these determinants on a scale of 1 to 5. Each determinant was analyzed separately, examining the mean value and standard deviation. An overall mean score was calculated by combining all the determinants. Additionally, a logistic regression analysis was performed to determine how different demographic factors influenced faculty members' acceptance of technology for student learning. Result: A total of 330 faculty members participated in the study. The majority of respondents were male lecturers who held a second degree qualification. On average, the participants were 32.9 years old and had six years of teaching experience. Interestingly, nearly three fourth (72.6%) of faculty members hold positive beliefs and exhibit a high level of acceptance of educational technology. Furthermore, the likelihood of accepting and utilizing technologies for learning was found to be 2.3 times higher for faculty members working in teaching settings at research institutions. Conclusion: Faculty members have a favorable attitude towards educational technology, demonstrating a high level of acceptance. This positive belief holds significant implications and is crucial for enhancing the effectiveness of technology and ensuring its long-term viability.

BackgroundOne of the most common measures of society's health is mortality among neonates. Developing and developed countries still differ significantly in neonatal mortality rates. While there are about 18 neonatal deaths worldwide for every 1,000 live births during the first month of life, less is known about neonatal mortality in developing countries, especially in East Africa. Understanding the extent of mortality during the post-neonatal period and its determinants is crucial for developing appropriate policies and strategies that could help solve the issue. Thus, the aim of this study was to identify the prevalence of post-neonatal mortality in East African countries and the factors that are associated with it.MethodsSecondary data analysis was conducted using data from the most recent Demographic and Health Surveys, which included 11 East African countries between 2014 and 2022. A weighted sample of 225,635 live births had been used in the study. STATA/SE 14 was used for data analysis. The multilevel mixed-effects logistic regression model was applied to determine the factors associated with post-neonatal mortality. In the multilevel logistic regression model, significant factors were deemed to be associated with post-neonatal mortality at p-values

IntroductionDespite the World Health Organization's advice against unhealthy feeding, many low- and middle-income countries, including sub-Saharan Africa (SSA) countries, are experiencing a nutritional transition to high in sugar, unhealthy fats, salts, and processed carbohydrates for younger children. However, there is a scarcity of recently updated multicounty information on unhealthy feeding practices and determinants in SSA countries. Therefore, this study aimed to assess the pooled prevalence of unhealthy feeding practices and determinants among children aged 6-23 months in five SSA countries.MethodA cross-sectional study design was employed with the most recent demographic and health survey secondary data (DHS) from five SSA countries. This secondary data was accessed from the DHS portal through an online request. The DHS is the global data collection initiative that provides detailed and high-quality data on population demographics, health, and nutrition in low- and middle-income countries. We used a weighted sample of 14,064 children aged 6-23 months. A multilevel mixed-effect binary logistic regression model was fitted to identify significant factors associated with unhealthy feeding practices. The level of statistical significance was declared with p-value < 0.05.ResultThis study found that overall, 62.4% (95% CI: 61.62-63.17) of children aged 6-23 months in five SSA countries had unhealthy feeding practices. Rural residents, lower-middle-income SSA countries, and children aged above 12 months had lower odds of unhealthy feeding practices. On the other hand, richer households and women who had not had an optimal antenatal care visit had higher odds of unhealthy feeding practices.ConclusionAccording to this study, nearly two out of three young children in five SSA countries had unhealthy feeding practices. Both individual and community-level factors are significantly associated with unhealthy feeding practices. As a result, responsible bodies shall make all efforts to reduce unhealthy feeding practices among young children in SSA countries.

Due to the rapid rise in the worldwide population, the need for food is expanding constantly. To boost agricultural productivity large amounts of synthetic fertilizers are used. However, the extensive use of these synthetic fertilizers leads to various environmental and health problems. Nanotechnology (NT) offers significant improvement in the fertilizer fabrication with optimal chemical compositions, enhances nutrient usage competence, reduces environmental influence, and increased plant productivity. Nano fertilizers (NF) are nanomaterials (NM) that contrast significantly from their corresponding bulk materials. The concept of NF technology is highly innovative, utilizing physical, chemical, and biological methods for formulation. Additionally, the precise application and targeted delivery of nano-fertilizers ensures a more sustainable and accurate approach to agriculture. The purpose of this review is to provide an overview of the various types of nano fertilizers and their synthesis by different methods. In addition, applications of the NF and advantages are also given over the conventional pesticides. Information is also given on the current applications and challenges of the NF. NF are more effective and efficient than conservative fertilizers. The use of NF is expanding owing to the positive influence on nutritional superiority and stress resistance in plants.

IntroductionThe absence of a biological parent from a child's existence had a negative impact on the child's growth, socialization, psychological wellbeing, and economic productivity. Developing nations like Ethiopia experience a huge number of orphans and family-unbounded children. But the exact figure has not been reported yet at the national level recently. Thus, this study aimed to assess the magnitudes and determinants of children living with non-biologic parents in Ethiopia.MethodsSecondary data analysis was conducted based on the demographic and health survey data conducted in Ethiopia in 2016. A total weighted sample of 41,884 children under the age of 18 from 5 years preceding the survey was included in this study. A multi-level logistic regression model was used to identify the determinants of children living with non-biologic parents. The adjusted odds ratio at 95% Cl was computed to assess the strength and significance of the association between explanatory and outcome variables. Factors with a p < 0.05 are declared statistically significant.ResultsThe prevalence of children living with non-biologic parents in Ethiopia was 17.58% (95% CI, 17.22–17.95). Being an orphan (AOR = 4.57, 95% CI: 2.40–7.25), being in first birth order (AOR = 8.22, 95% CI: 6.31–9.17), being from a household lacking formal family structure (AOR = 8.60, 95% CI: 6.20–12.30), and being from a female-headed household (AOR = 3.43, 95% CI: 2.65–4.43) were individual-level factors that were significantly associated with children living with non-biologic parents. Being a rural resident (AOR = 1.94, 95% CI: 1.23–3.08) and having a high community poverty level (AOR = 1.25, 95% CI: 1.01–1.75) were community-level determinants of children living with non-biologic parents.ConclusionAccording to this study, a significant proportion of children live with non-biological parents in Ethiopia. Thus, policymakers, health planners, and implementers need to give special attention to children from rural communities, orphans, firstborn children, and broken families. In addition, efforts shall be made to empower women and, in the long run, improve the economy of the community.

IntroductionChildhood stunting, a major public health concern in many developing countries, is associated with impaired physical and cognitive development, increased risk of infectious diseases, and long-term adverse health and economic consequences. Mozambique is among the countries with the highest stunting rates in sub-Saharan Africa. This study aims to examine the spatial variation and identify the predictors of stunting among children under the age of five years in Mozambique.MethodsWe utilized children’s recode data and geographic coordinates extracted from the 2022–23 Mozambique Demographic and Health Survey dataset. A stratified two-stage cluster sampling approach was employed. The study included a total weighted sample of 3,910 children under the age of five years. A geographically weighted regression was used to identify predictors of stunting.ResultsThe prevalence of stunting among children under the age of five in Mozambique was 31.26% (95% CI: 29.88 to 32.65%). The Nampula (46.00%), Cabo Delgado (43.79%), Manica (40.88%), Zambezia (38.27%), Niassa (35.52%), and Tete (34.85%) regions of Mozambique were identified as hotspot areas of stunting. Several factors were significantly associated with the spatial heterogeneity in stunting, where household wealth index (poor and middle categories) and Mother’s age (15–19 years) were positively associated with higher occurrence of stunting, while having an employed mother and being a child under 2 years of age were negatively associated with stunting occurrence.ConclusionThe spatial heterogeneity in stunting patterns highlighted by this analysis suggests that a one-size-fits-all approach to address child undernutrition in Mozambique may not be effective. Instead, tailored, location-specific strategies that account for the predictors of stunting are necessary to effectively combat this persistent public health challenge. Policymakers and program implementers should prioritize the hotspot regions for targeted interventions, while also maintaining and strengthening the factors contributing to the lower stunting prevalence in the cold spot areas.

Introduction: Intimate partner sexual violence (IPSV) is sexual violence against women by a current or former sexual partner. Sexual violence among pregnant women is higher in low-income countries, particularly in sub-Saharan Africa (SSA), which has numerous negative impacts for both the mother and the growing fetus. There is no recent and distinct information on the magnitude and factors associated with IPSV among pregnant women in SSA. Objective: This study aimed to assess the prevalence of IPSV and its determinants among pregnant women in SSA. Design: A cross-sectional study design using demographic health survey data from 2015 to 2022 in 20 sub-Saharan African countries was used. Methods: The analysis was conducted using a weighted sample of 10,775 women who were pregnant during the survey period (2015–2022). A multilevel logistic regression model was used to identify the determinants of IPSV among pregnant women. The adjusted odds ratio at 95% confidence interval (95% CI) was computed to assess the strength and significance of the association between explanatory and outcome variables. Factors with a p -value of

MXene is a novel type of 2D sheet nanomaterial that shows great application potentials in a variety of fields due to its advantages, such as high electrical conductivities, high surface areas, superior mechanical strength, functional transition metal surfaces, tunable surface chemistries, and excellent dispersion in various solvents. Additionally, due to its adaptability for a diverse range of applications, such as electrochemical energy storage devices, electrocatalysis, sensors, biomedical applications, membranes, flexible and wearable devices, etc., MXene is emerging as a "rising star" material. The scientific community will benefit from having a summary of the most recent research on this family of materials as these applications encourage greater interest in MXene research. In this review, we began by thoroughly summarizing the structures, characteristics, and production methods of materials based on MXenes. Then, a summary of MXenes-based materials' uses for metal air batteries has also been provided. Additionally, in order to inform the readers on the current state of MXenes' growth, we also shared our thoughts and explored their future directions. This review's data should make it easier to translate lab-scale discoveries into products that are marketable.