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In developing countries, one-quarter of young women have suffered from anemia. However, the available studies in Ethiopia have been usually used the traditional stastical methods. Therefore, this study aimed to employ multiple machine learning algorithms to identify the most effective model for the prediction of anemia among youth girls in Ethiopia. A total of 5642 weighted samples of young girls from the 2016 Ethiopian Demographic and Health Survey dataset were utilized. The data underwent preprocessing, with 80% of the observations used for training the model and 20% for testing. Eight machine learning algorithms were employed to build and compare models. The model performance was assessed using evaluation metrics in Python software. Various data balancing techniques were applied, and the Boruta algorithm was used to select the most relevant features. Besides, association rule mining was conducted using the Apriori algorithm in R software. The random forest classifier with an AUC value of 82% outperformed in predicting anemia among all the tested classifiers. Region, poor wealth index, no formal education, unimproved toilet facility, rural residence, not used contraceptive method, religion, age, no media exposure, occupation, and having more than 5 family size were the top attributes to predict anemia. Association rule mining was identified the top seven best rules that most frequently associated with anemia. The random forest classifier is the best for predicting anemia. Therefore, making it potentially valuable as decision-support tools for the relevant stakeholders and giving emphasis for the identified predictors could be an important intervention to halt anemia among youth girls. [ABSTRACT FROM AUTHOR]

Background: Immunization estimated to prevent 2 to 3 million children deaths every year from vaccine preventable disease. In Ethiopia, limited and inconclusive studies have been conducted on immunization coverage so far. Therefore, this umbrella review was intended to estimate the pooled national immunization coverage and its associated factors among children age 12–23 months in Ethiopia. Methods: This umbrella review included five systematic reviews and meta-analyses through literature search from PubMed, Science direct, and web of science, CINHALE, and data bases specific to systematic reviews such as the Cochrane Database of Systematic Reviews and Prospero, the International Prospective Register of Systematic Reviews from May 1 to 30/ 2023. Only systematic reviews and meta-analyses published in English from inception to May 1, 2023, were included. The quality of each study was assessed using Assessment of Multiple Systematic Reviews. Data were extracted using Microsoft excel 2016 and analyzed using STATA 17.0 statistical software. Heterogeneity among studies was assessed using the Cochran Q statistics and I2 test. The pooled effect sizes were determined using pooled proportion for the full vaccination coverage and odds ratios for the associated factors with the corresponding 95% confidence interval were used to declare statically significance. Results: Five studies with 77,161 children aged 12–23 months were included. The overall pooled full vaccination coverage was 57.72% (95% CI 50.17, 65.28). Institutional delivery (OR: 2.12, 95% CI: 1.78–2.52), travel to vaccination site for <2 hours (OR: 2.43, 95%CI: 1.97–3.00), received at least one antenatal (ANC) visit (OR: 3.2, 95%CI: 2.46–4.1), good maternal knowledge of immunization (OR: 3.63, 95%CI: 2.82–4.67), being informed on immunization schedule (OR: 2.54, 95%CI: 2.02–3.2), living in urban areas (OR: 2, 95% CI: 1.54–2.6), and a household visit by health-care providers (HCP) during the postnatal period (OR: 2.23, 95%CI: 1.22–4.09) were the independent predictors of immunization coverage. Conclusion: This study showed the full immunization coverage in Ethiopia was lower compared to the WHO-recommended level. Besides, the current umbrella review identifies several factors that contribute to higher immunization coverage. These includes; institutional delivery, near to vaccination site, having ANC visit, being urban residence, household visited by HCP, having good knowledge and informed on immunization schedule. Thus, the government should intensify the growth of immunization services by emphasizing outreach initiatives to reach remote areas and professionals must combine child immunization service with other medical services offered by health institutions. [ABSTRACT FROM AUTHOR]

Introduction: Diarrhea is particularly prevalent in low-income or marginalized populations because these groups have less access to clean water sources, hygienic conditions, and healthcare. Dehydration due to electrolyte and fluid loss is the main cause of deaths associated with diarrhea. An especially important factor in this death from dehydration is the caregivers' knowledge, attitude, and diarrhea management techniques. While a number of research have been done on managing diarrhea at home, the results tend not to be consistent. This systematic review and meta-analysis aimed to assess the pooled estimate of knowledge, attitude and practice of home-based management of diarrhea in East Africa. Methods: Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines was used to search articles from electronic databases (Cochrane library, Ovid platform (Medline, Embase, and Emcare), Google Scholar, CINAHL, PubMed, and institutional repositories in East Africa countries. The last search date was on 01/06/ 2023 Gregorian Calendar. The authors extracted year of publication, country, study design, knowledge level, attitude level and practice level of home-based management of diarrhea. A weighted inverse variance random-effects model was used to estimate the pooled prevalence of knowledge, attitude and practice of home-based management of diarrhea. Subgroup analysis was done by country, and sample size. Publication bias and sensitivity analysis were also done. Results: A total of 19 articles with (n = 7470 participants) were included for the final analysis. From the random-effects model analysis, the pooled prevalence of good practice, good knowledge and favorable attitude towards home based management of diarrhea in East Africa was found to be 52.62% (95% CI: 45.32%, 59.92%) (95% CI: I2 = 78.3%; p < 0.001), 37.44% (95% CI: 26.99%, 47.89%) (95% CI: I2 = 89.2%; p < 0.001) and 63.05% (95% CI: 35.7%, 90.41%) (95% CI: I2 = 97.8%; p < 0.001) respectively. Conclusion and recommendations: The level of good knowledge, attitude and practice of home based management of diarrhea in East Africa is found to be low. A collaborative effort from different stakeholders to enhance the knowledge, attitude and practice is needed to tackle the burden of diarrhea and its consequences. [ABSTRACT FROM AUTHOR]

The seventh author's name is spelled incorrectly. The correct name is: Befkad Derese Tilahun.By Alemu Birara Zemariam; Gebremeskel Kibret Abebe; Mulat Awoke Kassa; Addis Wondemagegn Alamaw; Rediet Woldesenbet Molla; Biruk Beletew Abate; Befkad Derese Tilahun; Wubet Tazeb Wondie; Rahel Asres Shimelash and Molla FentanewReported by Author; Author; Author; Author; Author; Author; Author; Author; Author; Author [Extracted from the article]

Background: Poor attachment, suckling, and positioning contribute to ineffective breastfeeding techniques. Poor weight gain, stunting, and decreased immunity are caused by insufficient breast milk intake owing to ineffective breastfeeding techniques. Numerous primary studies conducted in Ethiopia have revealed negative effects of ineffective breastfeeding techniques. However, inconsistencies have been observed among these studies, and no review has been conducted to report the amalgamated magnitude and associated factors. Therefore, this review aimed to estimate the national prevalence and factors associated with ineffective breastfeeding techniques in Ethiopia. Methods: Using PRISMA standards, we systematically reviewed and meta-analyzed articles from PubMed, Cochrane Library, and Google Scholar to investigate the prevalence and associated factors of ineffective breastfeeding techniques. Q and I2 tests were used to assess heterogeneity across studies. To evaluate the national prevalence and effect size of the linked covariates, a weighted inverse variance random-effects model was used. Subgroup analysis was performed based on the region, sample size, and year of publication. Funnel plots and Egger's regression tests were used to examine publication bias. A sensitivity analysis was also performed to determine the impact of the studies. Results: The analysis included a total of eleven studies with 4,470 participants used in the analysis. The pooled prevalence of ineffective breastfeeding techniques in Ethiopia was 53.13% (45.49, 60.78) no formal education (AOR = 3.42; 95% CI:1.67–5.18; I2 = 72.2%; P = 0.0132), primipara (AOR = 2.72;95% CI:1.81–3.64; I2 = 46.7%; P = 0.131), postnatal care (PNC) (AOR = 1.84; 95% CI:1.35–2.32; I2 = 0%; P = 0.53), breastfeeding counseling (AOR = 1.93; 95% CI:1.23–2.63; I2 = 0%;P = 0.35), home delivery and having breast problem (AOR = 3.11; 95% CI:1.09–5.16; I2 = 0%;P = 0.877) and (AOR = 2.22; 95% CI:1.28–3.16; I2 = 0%;P = 0.80) respectively were significantly associated with ineffective breastfeeding techniques. Conclusion: The prevalence of ineffective breastfeeding techniques in Ethiopia remains high. Policymakers and program officials should focus on empowering women, increasing institutional delivery, and providing counseling on breastfeeding throughout the maternal continuum of care. These measures will improve breastfeeding techniques and lead to better health of both infants and women. [ABSTRACT FROM AUTHOR]

Background: Neonatal jaundice is a significant contributor to illness and death in newborns, leading to frequent admissions to neonatal intensive care units. To better understand this issue, a study was conducted to identify the factors contributing to neonatal jaundice among newborns admitted to Dessie and Woldia comprehensive specialized hospitals in northeast Ethiopia. Methods: The study took place from April 1 to May 30, 2022, using unmatched case-control design. A total of 320 neonates paired with their mothers were involved, including 64 cases and 256 controls. Data were collected through a structured interviewer-administered questionnaire and a review of medical records. The collected data were analyzed using SPSS Version 23, and a multivariate logistic regression model was employed to understand the relationship between independent factors and the occurrence of neonatal jaundice. Statistical significance was determined at a threshold of P value less than 0.05. Results: The study findings revealed that maternal age over 35 years, residing in urban areas [adjusted odds ratio (AOR) = 2.4, 95% confidence interval (CI): 1.23, 4.82], male gender (AOR = 4.3, 95% CI: 1.90, 9.74), prematurity (AOR = 3.9, 95% CI: 1.88, 8.09), and ABO incompatibility (AOR = 2.6, 95% CI: 1.16, 5.96) were significant determinants of neonatal jaundice. Conversely, the study indicated that cesarean birth was associated with a 76% lower likelihood of infant jaundice compared to vaginal delivery (AOR = 0.24, 95% CI: 0.08, 0.72). Conclusion: To prevent, diagnose, and treat neonatal jaundice effectively, efforts should primarily focus on managing ABO incompatibility and early detection of prematurity. Additionally, special attention should be given to neonates born through vaginal delivery, those with mothers over 35 years old, and those residing in urban areas, as they are at higher risk of developing newborn jaundice. Close monitoring of high-risk mother-infant pairs during the antenatal and postnatal periods, along with early intervention, is crucial for reducing the severity of neonatal jaundice in this study setting. [ABSTRACT FROM AUTHOR]

Health professionals need a strong prediction system to reach appropriate disease diagnosis, particularly for under-five child with health problems like anemia. Diagnosis and treatment delay can potentially lead to devastating disease complications resulting in childhood mortality. However, the application of machine learning techniques using a large data set provides scientifically sounded information to solve such palpable critical health and health-related problems. Therefore, this study aimed to determine the predictors of anemia among under-5 year's age children in Ethiopia using a machine learning approach. A cross-sectional study design was done using the Ethiopian Demographic and Health Survey 2016 data set. A two-stage stratified cluster sampling technique was employed to select the samples. The data analysis was conducted using Statistical Package for Social Sciences/SPSS version 25 and R-software. Data were derived from Ethiopian Demographic and Health Survey. Boruta algorism was applied to select the features and determine the predictors of anemia among under-5 years-old children in Ethiopia. The machine learning algorism showed that number of children, distance to health facilities, health insurance coverage, youngest child's stool disposal, residence, mothers' wealth index, type of cooking fuel, number of family members, mothers' educational status and receiving rotavirus vaccine were the top ten important predictors for anemia among under-five children. Machine-learning algorithm was applied to determine the predictors of anemia among under- 5 year's age children in Ethiopia. We have identified the determinant factors by conducting a feature importance analysis with the Boruta algorithm. The most significant predictors were number of children, distance to health facility, health insurance coverage, youngest child's stool disposal, residence, mothers' wealth index, and type of cooking fuel. Machine learning model plays a paramount role for policy and intervention strategies related to anemia prevention and control among under-five children. [ABSTRACT FROM AUTHOR]

Introduction: Despite several strategies exist for anemia prevention and control, it has been the major public health important problem in the world. Numerous immediate and long-term health issues were reported in children who have history of anemia including decreased work productivity in adult hood period. Although analyzing data on burden and risk factors of anemia are the recommended action areas of World Health Organization framework for accelerating anemia reduction, the aggregated national burden and contributors of anemia in Ethiopia has not been determined so far. There for, this systematic and meta-analysis study is aimed to assess the pooled prevalence and associated factors of anemia among children aged 6–23 months in Ethiopia. Methods: The electronic databases including PubMed, Scopus, EMBASE, Web of Science, Science Direct, Google scholar and institutional repositories were searched using search terms. The studies that reported the prevalence and/or risk factors of anemia in children 6–23 months of age were included. The JBI quality assessment tool was used to evaluate the quality of each study. The data was extracted with Microsoft Excel, 2019 and analyzed with STATA 17.0 statistical software. A random effect model was used to estimate the pooled prevalence of anemia and its associated factors. The Cochrane Q-test statistics and I2 test were used to measure heterogeneity between the included studies. Furthermore, publication bias was examined using the funnel plot graph and statistical tests (Egger's and begg tests). Outliers also visualized using Galbraith plot. When necessary, sensitivity analysis was also employed to detect small study effect. Result: Ten studies with a total population of 14, 733 were included for analysis. The pooled prevalence of anemia among children aged 6–23 months of age in Ethiopia was found to be 57.76% (95%CI; 51.61–63.91; I2 = 97.192%; p < 0.001). Having history of diarrhea AOR = 2.44 (95%CI: 1.03–3.85), being stunted AOR = 2.00 (95%CI: 1.38–2.61), living in food insecure house hold AOR = 2.08 (95%CI: 1.10–3.07), consuming less diversified food AOR = 2.73 (95%CI: 2.06–3.39) and being 6–11 months of age AOR = 1.59 (95%CI: 1.23–1.95) were associated with anemia. Conclusion and recommendation: The prevalence of anemia is in the range of severe public health problem among children aged 6–23 months in Ethiopia. Diarrhea, stunting, house hold food insecurity, dietary diversity, and age were the predictors of anemia. Further, prospective cohort and random controlled trial studies are recommended. Further, random controlled trial especially effectiveness of nutritional education interventions trial is important. To reduce prevalence of anemia, strengthening diarrhea reduction program, securing household food insecurity, preventing stunting, giving special attention for infants age 6–11 months and encouraging food diversification are important. [ABSTRACT FROM AUTHOR]

Background. Each year, immunization averts an estimated 2–3 million deaths from diphtheria, tetanus, pertussis, and measles. In 2011, nearly 107 million infants (83%) worldwide received at least 3 doses of DTP vaccine; however, approximately 22.4 million failed to receive 3 doses, and this causes large numbers of children susceptible to vaccine-preventable diseases and death. Nearly 8.4 million received at least 1 DTP dose. The aim of this was to assess coverage, opportunity, and challenges of EPI among children of age 12–23 months in Woldia town, Amhara region, Northeast Ethiopia. Method. In this mixed community-based cross-sectional study, 389 study subjects were selected by using a multistage sampling method. Interviewer-administered structured questioners were used. Data were entered and analyzed using SPSS Version 20 and presented by using tables and figures. Documented/recorded file from the qualitative data were transcribed into word narrative. Finally, it was presented by thematic analysis. Result. A total of 389 mothers/caretakers were interviewed. Based on vaccination card and mothers/caretakers' recall, 385 (99%) of the children took at least a single dose of vaccine. From total children, 4 (1%) were not immunized at all, 44 (11.3%) were partially immunized, and 343 (87.7%) were fully immunized. The dropout rate was 9% for BCG to measles, 2.4% for Penta1 to Penta3, 8.3% for penta1 to measles, and 1.6% for pcv1 to Pcv3. A qualitative study revealed that workload, shortage of vaccine, and noncompliance of the mother/caretaker for the next scheduled date was the major challenge faced by health professionals and health extension workers. Conclusion. Vaccination coverage was low compared with the Millennium Development Goals target. It is important to increase and maintain the immunization level to the intended target. Thus, the town health office and concerned stakeholders need to work more to improve the performance of the expanded program on immunization in this area. [ABSTRACT FROM AUTHOR]

Background: Nurses with reduced work ability had a high risk of disability pension, sickness absences, retirement intention, and leave their job and profession early. Nurses frequently suffer from job related stress, occupational fatigue and sleep problems, which can further compromise their work ability. Aims of the study: The aim of this study was to assess perceived work ability and its associated factors among nurses working in the Northwest of Amhara regional state Referral Hospitals, Northwest Ethiopia, 2022. Methods: A multicenter, an institutional based, cross-sectional study was conducted among 410 nurses working in five selected Referral hospitals, found in the Northwest of Amhara regional state, Northwest Ethiopia, 2022. The data were collected using a structured, self-administered questionnaire and entered using Epi info version 7.2.5 software, analyzed using SPSS version 25. Summary statistics (median or IQR for continuous data and frequency and percentage for categorical variables) were used. The ordinal logistic regression was used to assess' the presence of association between dependent and independent variables. Results: The findings of this study revealed that 59.0% of nurses had poor level of work ability, whereas 34.4% and 6.6% of nurses had sub-optimal and optimal level of work ability respectively. Multivariable ordinal logistic regression revealed that being male [AOR = 2.43; 95% CI (1.52, 3.91)], being BSC nurse [AOR = 0.21; 95% CI (0.08, 0.51)], nurses who had poor sleep quality [AOR = 0.34; 95% CI (0.12, 0.98)] and nurses who had chronic disease [AOR = 0.18; 95% CI (0.08, 0.41)] were significantly associated with nurses' level of work ability, p-value < 0.05. Conclusions: In this study, the prevalence of poor level of work ability among nurses was high. Nurses with a female sex, nurses who had chronic disease, BSC holders and nurses who had poor sleep quality had a poor level of work ability. The federal Minister of health and the study hospitals collaborative with concerned stakeholders to design strategies to enhance work ability among nurses. [ABSTRACT FROM AUTHOR]