Nomogram to predict risk of neonatal mortality among preterm neonates admitted with sepsis at University of Gondar Comprehensive Specialized Hospital: risk prediction model development and validation.

BACKGROUND: Mortality in premature neonates is a global public health problem. In developing countries, nearly 50% of preterm births ends with death. Sepsis is one of the major causes of death in preterm neonates. Risk prediction model for mortality in preterm septic neonates helps for directing the decision making process made by clinicians. OBJECTIVE: We aimed to develop and validate nomogram for the prediction of neonatal mortality. Nomograms are tools which assist the clinical decision making process through early estimation of risks prompting early interventions. METHODS: A three year retrospective follow up study was conducted at University of Gondar Comprehensive Specialized Hospital and a total of 603 preterm neonates with sepsis were included. Data was collected using KoboCollect and analyzed using STATA version 16 and R version 4.2.1. Lasso regression was used to select the most potent predictors and to minimize the problem of overfitting. Nomogram was developed using multivariable binary logistic regression analysis. Model performance was evaluated using discrimination and calibration. Internal model validation was done using bootstrapping. Net benefit of the nomogram was assessed through decision curve analysis (DCA) to assess the clinical relevance of the model. RESULT: The nomogram was developed using nine predictors: gestational age, maternal history of premature rupture of membrane, hypoglycemia, respiratory distress syndrome, perinatal asphyxia, necrotizing enterocolitis, total bilirubin, platelet count and kangaroo-mother care. The model had discriminatory power of 96.7% (95% CI: 95.6, 97.9) and P-value of 0.165 in the calibration test before and after internal validation with brier score of 0.07. Based on the net benefit analysis the nomogram was found better than treat all and treat none conditions. CONCLUSION: The developed nomogram can be used for individualized mortality risk prediction with excellent performance, better net benefit and have been found to be useful in clinical practice with contribution in preterm neonatal mortality reduction by giving better emphasis for those at high risk.

Incidence of loss to follow-up and its predictors among HIV-infected under-five children after initiation of antiretroviral therapy in West Amhara Comprehensive Specialized Referral Hospitals, Northwest Ethiopia: a multicenter retrospective follow-up study.

BACKGROUND: Loss to follow-up (LTFU) among under-five children from HIV care profoundly affects the treatment outcomes of this vulnerable population. It is a major factor that negatively affects the benefits of antiretroviral therapy (ART). Current information about LTFU among HIV-positive under-five children on ART is essential for effective treatments. To far, nevertheless, limited research has been done in Ethiopia to address this issue. Thus, this study aimed to assess the incidence and predictors of LTFU among HIV-infected under-five children receiving ART in West Amhara Comprehensive Specialized Referral Hospitals. METHODS: A multicenter institution-based retrospective follow-up study was conducted among 435 HIV-infected under-five children on ART selected by simple random sampling from January 1, 2010 to December 31, 2019, and data were collected between December 1, 2021, and January 31, 2022. A standardized data extraction tool adapted from the ART entry and follow-up forms was used. The event of interest for this study was LTFU, whereas the absence of LTFU was censored. Before being transferred to STATA version 14 for analysis, the data were entered into Epi-Data version 3.1. The Kaplan‒Meier curve was used to estimate an individual's survival-free probability at each specific point in time. The Cox proportional hazards model was used to identify predictors of LTFU. RESULTS: Among the 420 records included in the final analysis, 30 (7.14%) of the individuals were LTFUs. The incidence rate of LTFU was 3.4 per 1000 person-months of observation (95% CI: 2.43-4.87). The survival probabilities of children after 12, 24, 36, and 48 months were 0.97, 0.92, 0.88, and 0.77, respectively. The independent predictors of LTFU were HIV infection in under-five children who lived in rural areas (AHR = 3.64; 95% CI: 1.41, 9.37), poor adherence to ART (AHR = 4.37; 95% CI: 1.59, 12.02), not receiving cotrimoxazole preventive therapy (AHR = 3.75; 95% CI: 1.39, 10.08), not receiving isoniazid prophylaxis (AHR = 3.4; 95% CI: 1.29, 9.01), and having a severe WHO clinical stage (AHR = 5.43; 95% CI: 1.38, 11.43). CONCLUSION AND RECOMMENDATION: The incidence of loss to follow-up was high, especially in the first two years after ART initiation. The risk of LTFU was greater for those who were rural residents, had poor adherence, lacked cotrimoxazole preventive therapy, not given isoniazid prophylaxis, and presented with WHO clinical stages III and IV. Therefore, clinicians should emphasize for cotrimoxazole preventive therapy and isoniazid prophylaxis, for those living in rural areas, who present with poor adherence and WHO clinical stages III and IV.

Trend, and multivariate decomposition of perinatal mortality in Ethiopia using further analysis of EDHS 2005-2016.

BACKGROUND: Perinatal mortality is a global health problem, especially in Ethiopia, which has the highest perinatal mortality rate. Studies about perinatal mortality were conducted in Ethiopia, but which factors specifically contribute to the change in perinatal mortality across time is unknown. OBJECTIVES: To assess the trend and multivariate decomposition of perinatal mortality in Ethiopia using EDHS 2005-2016. METHODS: A community-based, cross-sectional study design was used. EDHS 2005-2016 data was used, and weighting has been applied to adjust the difference in the probability of selection. Logit-based multivariate decomposition analysis was used using STATA version 14.1. The best model was selected using the lowest AIC value, and variables were selected with a p-value less than 0.05 at 95% CI. RESULT: The trend of perinatal mortality in Ethiopia decreased from 37 per 1000 births in 2005 to 33 per 1000 births in 2016. About 83.3% of the decrease in perinatal mortality in the survey was attributed to the difference in the endowment (composition) of the women. Among the differences in the endowment, the difference in the composition of ANC visits, taking the TT vaccine, urban residence, occupation, secondary education, and birth attendant significantly decreased perinatal mortality in the last 10 years. Among the differences in coefficients, skilled birth attendants significantly decreased perinatal mortality. CONCLUSION AND RECOMMENDATION: The perinatal mortality rate in Ethiopia has declined over time. Variables like ANC visits, taking the TT vaccine, urban residence, occupation, secondary education, and skilled birth attendants reduce perinatal mortality. To reduce perinatal mortality more, scaling up maternal and newborn health services has a critical role.

Spatial patterns and associated factors of HIV testing and counselling (HTC) as a component of antenatal care services in Ethiopia.

BACKGROUND: While HIV testing and counselling play a crucial role in preventing mother-to-child transmission, numerous pregnant women did not receive these services. Understanding the spatial variation of HIV testing and counselling and its associated factors during antenatal care in Ethiopia remains limited. Thus, this study was aimed at assessing the spatial patterns and factors associated with HIV testing and counselling during antenatal care visits in Ethiopia. METHODS: A cross-sectional study design was employed with a two-stage stratified cluster sampling technique. A total of 2,789 women who gave birth in the two years prior to the survey and had at least one antenatal care visit were included in the study. Stata version 16 and ArcGIS version 10.8 software were used for analysis. A multilevel robust Poisson regression model was fitted to identify significantly associated factors since the prevalence of HIV testing and counselling was higher than 10%. A statistically significant association was declared based on multivariable multilevel robust Poisson regression analysis using an adjusted prevalence ratio with its 95% confidence interval at a p-value < 0.05. Spatial regression analysis was conducted, and the local coefficients of statistically significant spatial covariates were visualised. RESULTS: In Ethiopia, the overall prevalence of HIV testing and counselling during antenatal care visits was 29.5% (95% CI: 27.8%, 31.2%). Significant spatial clustering was observed (Global Moran's I = 0.138, p-value <0.001). In the spatial regression analysis, high and comprehensive knowledge related to HIV, and comprehensive knowledge on the prevention of mother-to-child transmission were significant explanatory variables for the spatial variation of HIV testing and counselling. In the multivariable multilevel robust Poisson regression analysis, education, household wealth, media exposure, number of antenatal care visits, comprehensive knowledge on mother-to-child transmission, comprehensive knowledge on prevention of mother-to-child transmission, and region were significantly associated factors. CONCLUSION: The prevalence of HIV testing and counselling during antenatal care visits was low. Empowering women through education, promoting mass media exposure, increasing numbers of antenatal care visits, and enhancing women's knowledge related to HIV and mother-to-child transmission by targeting cold spot areas could improve HIV testing and counselling service uptake among pregnant women in Ethiopia.

Risk score prediction for bacteriologically confirmed tuberculosis among adults with HIV on antiretroviral therapy in northwest Ethiopia: prognostic model development.

OBJECTIVE: This study was aimed at developing a risk score prediction model for bacteriologically confirmed tuberculosis (TB) among adults with HIV receiving antiretroviral therapy in Ethiopia. METHODS: An institutional-based retrospective follow-up study was conducted among 569 adults with HIV on ART. We used demographic and clinical prognostic factors to develop a risk prediction model. Model performance was evaluated by discrimination and calibration using the area under the receiver operating characteristic (AUROC) curve and calibration plot. Bootstrapping was used for internal validation. A decision curve analysis was used to evaluate the clinical utility. RESULTS: Opportunistic infection, functional status, anemia, isoniazid preventive therapy, and WHO clinical stages were used to develop risk prediction. The AUROC curve of the original model was 87.53% [95% confidence interval (CI): 83.88-91.25] and the calibration plot ( P -value = 0.51). After internal validation, the AUROC curve of 86.61% (95% CI: 82.92-90.29%) was comparable with the original model, with an optimism coefficient of 0.0096 and good calibration ( P -value = 0.10). Our model revealed excellent sensitivity (92.65%) and negative predictive value (NPV) (98.60%) with very good specificity (70.06%) and accuracy (72.76%). After validation, accuracy (74.85%) and specificity (76.27%) were improved, but sensitivity (86.76%) and NPV (97.66%) were relatively reduced. The risk prediction model had a net benefit up to 7.5 threshold probabilities. CONCLUSION: This prognostic model had very good performance. Moreover, it had very good sensitivity and excellent NPV. The model could help clinicians use risk estimation and stratification for early diagnosis and treatment to improve patient outcomes and quality of life.

Spatial variation of zero fruits/vegetables consumption and associated factors among children aged 6-23 months in Ethiopia: geographical weighted regression analysis.

Background: After 6 months, nutrient-dense, varied diets containing fruits and vegetables are crucial to supplement breastfeeding. Like many other low-income countries, Ethiopia has very low FV consumption. Zero vegetable or fruit (ZVF) consumption has been shown to significantly raise the risk of non-communicable diseases and has been ranked among the top 10 risk factors for mortality. And it is associated with poor health, an increased risk of obesity, and a higher risk of non-communicable diseases. Thus, this study's goal was to investigate the spatial distribution of ZVF consumption and its spatial determinants among children aged 6-23 months in Ethiopia. Methods: A cross-sectional study design was employed. A total of 1,489 weighted samples were included from kids' datasets from the 2019 Ethiopian mini-demographic and health survey. STATA version 16, ArcGIS version 10.8, Kuldorff's SaTScan version 9.6, and MGWR version 2.0 software were used for analysis. Spatial regression analyses (geographical weighted regression and ordinary least squares analysis) were conducted. Models were compared using AICc and adjusted R2. A p-value of less than 0.05 was used to declare statistically significant spatial predictors, and the corresponding local coefficients were mapped. Results: The spatial distribution of ZVF consumption among children aged 6-23 months was non-random in Ethiopia. Spatial scan analysis revealed a total of 120 significant clusters. Maternal education, wealth status, age of the child, place of delivery, number of under-five children in the house, and current pregnancy status were significant predictors of the spatial variation of ZVF consumption. Conclusion: Significant geographic variation in ZVF consumption was found in this study throughout Ethiopia's regions. Significant predictors of the spatial variation in ZVF consumption were maternal education, wealth status, child age, place of delivery, number of under-five children in the home, and status as a pregnant woman at the time of birth. Therefore, in order to improve children's adequate consumption of fruit and vegetables, area-based interventions that can consider these significant factors into account are needed.

Determinants of fertility experience among reproductive women age (15-49) in Ethiopia: Application of count regression models.

INTRODUCTION: Fertility refers to the average number of children born to a woman over her reproductive years. Due to cultural norms, economic development, education, access to healthcare, and government policies, fertility rates vary significantly across different countries and regions of the world. Ethiopia is one of the developing countries in Sub-Sahara Africa and its fertility rate has consistently been one of the highest in the world. Hence the main goal of this study was to identify the leading factors for the total number of children born per mother in Ethiopia. METHODS: This study used the most recent secondary data obtained from the 2019 Ethiopia Mini Demographic and Health Survey. A total weighted sample of 8885 women aged 15 to 49 was included in the study. The primary outcome variable in this study was the number of children born per mother, and different socio-demographic and economic factors that could influence fertility experience were included. The analysis was performed using STATA version 17 software. Negative Binomial regression model was used to assess the association between outcome and predictor variables. A p-value <0.05 was considered to be statistically significant. RESULTS: From a total of 8885 women, on average approximately 2.73 children were born per mother. Age of mothers (IRR = 1.08, 95% CI: (1.077, 1.082)), religion for Muslim (IRR = 1.13, 95% CI: (1.08, 1.18)) and others (IRR = 1.16, 95% CI: (1.11, 1.22)), level of education secondary and above (IRR = .61, 95% CI: (.58, .65)) and primary (IRR = .84, 95% CI: (.81, .87)), household member of six to nine (IRR = 1.24, 95% CI: (1.20, 1.28)) and household members more than nine people (IRR = 1.14, 95% CI: (1.07, 1.21)), wealth index for rich (IRR = .94, 95%, CI: (.91, .98)), marital status for not married (IRR = .49, 95%, CI: (.48, .51)), pregnant mothers (IRR = 1.08, 95%, CI: (1.02, 1.13)) and contraceptive users (IRR = 1.12, 95%, CI: (1.09, 1.16)) were the signficant variables for number of children ever born per mother. CONCLUSION: In Ethiopia, the average number of children born per mother was approximately 2.73. Poisson and Negative Binomial regression models were compared, and we found the Negative Binomial regression model to be better to identify the determinants of fertility experience in Ethiopia. Age of mothers, religion, current pregnancy, use of contraceptive methods, mothers' education level, household members, wealth index, number of children aged five and under, region (Somali, Gambela, and Addis Ababa), and marital status were the determinants responsible for fertility experience among mothers in Ethiopia. These findings are helpful for policymakers and healthcare professionals for developing targeted interventions and programs aimed at improving the high fertility rate experience in Ethiopia.

Incidence of anaemia and its predictors among HIV-infected children receiving highly active antiretroviral treatment in North-West Ethiopia: a multicentre retrospective follow-up study.

BACKGROUND: Anaemia is one of the most common problems in HIV-infected patients associated with increased HIV progression, decreased functional capacity, survival and quality of life. For better interventions, up-to-date information concerning anaemia among HIV-infected children less than 5 years of age on antiretroviral therapy (ART) is vital. Thus, this study aims to determine the predictors of anaemia among HIV-infected children less than 5 years of age receiving ART in North-West Ethiopia. DESIGN: An institution-based retrospective follow-up study was conducted. STUDY SETTING: Amhara region Comprehensive Specialized Hospitals, North-West Ethiopia. PARTICIPANTS: In total, we examined 460 HIV-infected children less than 5 years of age who had followed highly active antiretroviral treatment from 2010 to 2020. OUTCOME MEASURES: The outcome measures were median time to detection of anaemia, the incidence and the effects of cotrimoxazole preventive therapy (CPT), ART adherence, tuberculosis (TB), WHO clinical stage and wasting on anaemia. RESULTS: The overall follow-up time was 9234 person-months of observation. The incidence density of anaemia was 8.34 per 1000 person-months of observation (95% CI 6.67 to 10.43). The cumulative survival probability of children after the last months of follow-up was 0.54. The independent predictors of anaemia were not receiving CPT (adjusted HR (AHR)=4.44; 95% CI 2.48 to 7.93), poor adherence to ART (AHR=2.46; 95% CI 1.37 to 4.42), TB (AHR=3.40; 95% CI 1.72 to 6.72), severe WHO clinical stage (AHR=3.03; 95% CI 1.40 to 6.58) and severe wasting (AHR=1.98; 95% CI 1.08 to 3.64). CONCLUSION AND RECOMMENDATION: The incidence rate of anaemia was high and it was provoked by predictors like CPT, ART adherence, TB, WHO clinical stage and wasting. Therefore, it is necessary to emphasise for these predictors.

Geographically weighted regression analysis to assess hotspots of early sexual initiation and associated factors in Ethiopia.

Background: Early sexual initiation (ESI) causes unintended pregnancy, sexually transmitted infections (STI), high risk of depression and anxiety, developmental delays, lack of emotional maturity, and difficulty in pursuing education. This study aims to analyze the geographically weighted regression and associated factors of ESI of women in Ethiopia. Methods: The study utilized data from the Ethiopian Demographic and Health Survey, 2016. It included a weighted sample of 11,775 women. Spatial regression was carried out to determine which factors are related to hotspots of ESI of women. To identify the factors associated with ESI, a multilevel Poisson regression model with robust variance was conducted. An adjusted prevalence ratio (APR) with its 95 % confidence interval was presented. Results: The prevalence of ESI was 75.3 % (95%CI: 74.6 %, 76.1 %), showing notable spatial variation across different regions of Ethiopia. Areas of significant hotspots of ESI were identified in Western and Southern Tigray, most parts of Amhara, Southern, Central and Western Afar, Eastern Gambella, and North Western SNNPR. The significant variables for the spatial variation of ESI were; being single, rural residence, and having no formal education of the women. Factors including; wealth index, marital status, khat chewing, education level, residence, and region were associated significantly with ESI in the multilevel robust Poisson analysis. Conclusion: A higher proportion of ESI in women was found. Public health interventions must be made by targeting hotspot areas of ESI through increasing health care access and education (specifically among rural residents), developing a comprehensive sexual education, implementing policies and laws that outlaw early marriage, and mass community-based programs to increase awareness about the importance of delaying sexual activity.

Spatial variation and associated factors of inadequate counselling regarding pregnancy danger signs during antenatal care visits among pregnant women in Ethiopia: a Geographically Weighted Regression Model.

INTRODUCTION: Inadequate counselling of pregnant women regarding pregnancy danger signs contributes to a delay in deciding to seek care, which causes up to 77% of all maternal deaths in developing countries. However, its spatial variation and region-specific predictors have not been studied in Ethiopia. Hence, the current study aimed to model its predictors using geographically weighted regression analysis. METHODS: The 2019 Ethiopian Mini Demographic and Health Survey data were used. A total weighted sample of 2922 women from 283 clusters was included in the final analysis. The analysis was performed using ArcGIS Pro, STATA V.14.2 and SaTScan V.10.1 software. The spatial variation of inadequate counselling was examined using hotspot analysis. Ordinary least squares regression was used to identify factors for geographical variations. Geographically weighted regression was used to explore the spatial heterogeneity of selected variables to predict inadequate counselling. RESULTS: Significant hotspots of inadequate counselling regarding pregnancy danger signs were found in Gambella region, the border between Amhara and Afar regions, Somali region and parts of Oromia region. Antenatal care provided by health extension workers, late first antenatal care initiation and antenatal care follow-up at health centres were spatially varying predictors. The geographically weighted regression model explained about 66% of the variation in the model. CONCLUSION: Inadequate counselling service regarding pregnancy danger signs in Ethiopia varies across regions and there exists within country inequality in the service provision and utilisation. Prioritisation and extra efforts should be made by concerned actors for those underprivileged areas and communities (as shown in the maps), and health extension workers, as they are found in the study.

Geospatial variation of exclusive breastfeeding and its determinants among mothers of infants under 6 months in Ethiopia: spatial and geographical weighted regression analysis.

BACKGROUND: Exclusive breastfeeding (EBF) is a major public health problem in Ethiopia. However, the spatial variation of EBF and the associated factors have not been studied as much as we have searched. This study aimed at assessing geospatial variation and the predictors of EBF using geographically weighted regression. METHODS: A cross-sectional study was conducted using the 2019 Mini-Ethiopian Demographic and Health Survey data set. The study used a total weighted sample of 548 infants. Hotspot spatial analysis showed the hotspot and cold spot areas of EBF. The spatial distribution of EBF was interpolated for the target population using spatial interpolation analysis. SaTScan V.9.6 software was used to detect significant clusters. Ordinary least squares regression analysis identified significant spatial predictors. In geographically weighted regression analysis, the effect of predictor variables on the spatial variation of EBF was detected using local coefficients. RESULTS: The weighted prevalence of EBF in Ethiopia was 58.97% (95% CI 52.67% to 64.99%), and its spatial distribution was found to be clustered (global Moran's I=0.56, p<0.001). Significant hotspot areas were located in Amhara, Tigray, Southern Nations, Nationalities, and Peoples' Region, and Somali regions, while significant cold spots were located in Dire Dawa, Addis Ababa and Oromia regions. Kulldorff's SaTScan V.9.6 was used to detect significant clusters of EBF using a 50% maximum cluster size per population. The geographically weighted regression model explained 35.75% of the spatial variation in EBF. The proportions of households with middle wealth index and married women were significant spatial predictors of EBF. CONCLUSION: Middle wealth index and married women were significant spatial predictors of EBF. Our detailed map of EBF hotspot areas will help policymakers and health programmers encourage the practice of EBF in hotspot areas and set national and regional programmes focused on improving EBF in cold spots by considering significant predictor variables.

Factors associated with problematic internet use among University of Gondar undergraduate students, Northwest Ethiopia: Structural equation modeling.

BACKGROUND: For young adults and adolescents, excessive internet use has become a serious public health concern due to its negative impact on their health. It has been associated with detrimental effects on both physical and mental health. Negative academic outcomes were observed in the students, including missing classes, lower grades, and academic dismissal. Therefore, the purpose of the current study was to identify factors associated with PIU among undergraduate students at the University of Gondar. METHOD: A cross-sectional study was conducted at the University of Gondar among 1514 undergraduate students from June 1-20, 2022. The study participants were selected using a stratified simple random selection procedure. Using structural equation modeling, the degree of relationship was ascertained. A p-value of less than 0.05 and an adjusted regression coefficient with a 95% confidence interval (CI) were used to interpret the data. RESULTS: In our study, being from non-health departments [ß = 0.11, 95% CI: 0.037, 0.181], current alcohol use [ß = 0.12, 95% CI: 0.061, 0.187], depressive symptoms [ß = 0.23, 95% CI: 0.175, 0.291], insomnia symptoms [ß = 0.12, 95% CI: 0.060, 0.196], and ADHD symptoms [ß = 0.11, 95% CI: 0.049, 0.166] had a significant positive effect on PIU, while having a history of head injury had a significant negative effect [ß = -0.12, 95% CI: -0.226, -0.021] on PIU. CONCLUSION AND RECOMMENDATION: Factors such as current alcohol use, non-health department type, depressive symptoms, insomnia, and ADHD symptoms were positively associated with PIU. However, a history of head injuries was negatively associated with PIU. Therefore, strategies aimed at the early identification of PIU may lead to an improvement in the psychosocial health of university students.

Spatial variation and geographical weighted regression analysis to explore open defecation practice and its determinants among households in Ethiopia.

BACKGROUND: In Ethiopia, recent evidence revealed that over a quarter (27%) of households (HHs) defecated openly in bush or fields, which play a central role as the source of many water-borne infectious diseases, including cholera. Ethiopia is not on the best track to achieve the SDG of being open-defecation-free by 2030. Therefore, this study aimed to explore the spatial variation and geographical inequalities of open defecation (OD) among HHs in Ethiopia. METHODS: This was a country-wide community-based cross-sectional study among a weighted sample of 8663 HHs in Ethiopia. The global spatial autocorrelation was explored using the global Moran's-I, and the local spatial autocorrelation was presented by Anselin Local Moran's-I to evaluate the spatial patterns of OD practice in Ethiopia. Hot spot and cold spot areas of OD were detected using ArcGIS 10.8. The most likely high and low rates of clusters with OD were explored using SaTScan 10.1. Geographical weighted regression analysis (GWR) was fitted to explore the geographically varying coefficients of factors associated with OD. RESULTS: The prevalence of OD in Ethiopia was 27.10% (95% CI: 22.85-31.79). It was clustered across enumeration areas (Global Moran's I = 0.45, Z-score = 9.88, P-value ≤ 0.001). Anselin Local Moran's I analysis showed that there was high-high clustering of OD at Tigray, Afar, Northern Amhara, Somali, and Gambela regions, while low-low clustering of OD was observed at Addis Ababa, Dire-Dawa, Harari, SNNPR, and Southwest Oromia. Hotspot areas of OD were detected in the Tigray, Afar, eastern Amhara, Gambela, and Somali regions. Tigray, Afar, northern Amhara, eastern Oromia, and Somali regions were explored as having high rates of OD. The GWR model explained 75.20% of the geographical variation of OD among HHs in Ethiopia. It revealed that as the coefficients of being rural residents, female HH heads, having no educational attainment, having no radio, and being the poorest HHs increased, the prevalence of OD also increased. CONCLUSION: The prevalence of OD in Ethiopia was higher than the pooled prevalence in sub-Saharan Africa. Tigray, Afar, northern Amhara, eastern Oromia, and Somali regions had high rates of OD. Rural residents, being female HH heads, HHs with no educational attainment, HHs with no radio, and the poorest HHs were spatially varying determinants that affected OD. Therefore, the government of Ethiopia and stakeholders need to design interventions in hot spots and high-risk clusters. The program managers should plan interventions and strategies like encouraging health extension programs, which aid in facilitating basic sanitation facilities in rural areas and the poorest HHs, including female HHs, as well as community mobilization with awareness creation, especially for those who are uneducated and who do not have radios.

Machine learning algorithms to predict healthcare-seeking behaviors of mothers for acute respiratory infections and their determinants among children under five in sub-Saharan Africa.

Background: Acute respiratory infections (ARIs) are the leading cause of death in children under the age of 5 globally. Maternal healthcare-seeking behavior may help minimize mortality associated with ARIs since they make decisions about the kind and frequency of healthcare services for their children. Therefore, this study aimed to predict the absence of maternal healthcare-seeking behavior and identify its associated factors among children under the age 5 in sub-Saharan Africa (SSA) using machine learning models. Methods: The sub-Saharan African countries' demographic health survey was the source of the dataset. We used a weighted sample of 16,832 under-five children in this study. The data were processed using Python (version 3.9), and machine learning models such as extreme gradient boosting (XGB), random forest, decision tree, logistic regression, and Naïve Bayes were applied. In this study, we used evaluation metrics, including the AUC ROC curve, accuracy, precision, recall, and F-measure, to assess the performance of the predictive models. Result: In this study, a weighted sample of 16,832 under-five children was used in the final analysis. Among the proposed machine learning models, the random forest (RF) was the best-predicted model with an accuracy of 88.89%, a precision of 89.5%, an F-measure of 83%, an AUC ROC curve of 95.8%, and a recall of 77.6% in predicting the absence of mothers' healthcare-seeking behavior for ARIs. The accuracy for Naïve Bayes was the lowest (66.41%) when compared to other proposed models. No media exposure, living in rural areas, not breastfeeding, poor wealth status, home delivery, no ANC visit, no maternal education, mothers' age group of 35-49 years, and distance to health facilities were significant predictors for the absence of mothers' healthcare-seeking behaviors for ARIs. On the other hand, undernourished children with stunting, underweight, and wasting status, diarrhea, birth size, married women, being a male or female sex child, and having a maternal occupation were significantly associated with good maternal healthcare-seeking behaviors for ARIs among under-five children. Conclusion: The RF model provides greater predictive power for estimating mothers' healthcare-seeking behaviors based on ARI risk factors. Machine learning could help achieve early prediction and intervention in children with high-risk ARIs. This leads to a recommendation for policy direction to reduce child mortality due to ARIs in sub-Saharan countries.

Prevalence of Hepatitis B virus infection and its determinants among pregnant women in East Africa: Systematic review and Meta-analysis.

INTRODUCTION: Hepatitis B virus (HBV) is one of the major public health problems globally and needs an urgent response. It is one of the most responsible causes of mortality among the five hepatitis viruses, and it affects almost every class of individuals. Different studies were conducted on the prevalence of HBV among pregnant women in East African countries, but none of them showed the pooled prevalence of HBV among the pregnant women. Thus, the main objective of this study was to determine the pooled prevalence and its determinants among pregnant women in East Africa. METHODS: We searched studies using PubMed, Scopus, Embase, ScienceDirect, Google Scholar and grey literature that were published between January 01/2020 to January 30/2024. The studies were assessed using the Newcastle Ottawa Scale (NOS) quality assessment scale. The random-effect (DerSimonian) model was used to determine the pooled prevalence and associated factors of HBV among pregnant women. Heterogeneity were assessed by I2 statistic, sub-group analysis, and sensitivity analysis. Publication bias was assessed by Egger test, and the analysis was done using STATA version 17. RESULT: A total of 45 studies with 35639 pregnant women were included in this systematic review and meta-analysis. The overall pooled prevalence of HBV among pregnant women in East Africa was 6.0% (95% CI: 6.0%-7.0%, I2 = 89.7%). The highest prevalence of 8% ((95% CI: 6%, 10%), I2 = 91.08%) was seen in 2021, and the lowest prevalence 5% ((95% CI: 4%, 6%) I2 = 52.52%) was observed in 2022. A pooled meta-analysis showed that history of surgical procedure (OR = 2.14 (95% CI: 1.27, 3.61)), having multiple sexual partners (OR = 3.87 (95% CI: 2.52, 5.95), history of body tattooing (OR = 2.55 (95% CI: 1.62, 4.01)), history of tooth extraction (OR = 2.09 (95% CI: 1.29, 3.39)), abortion history(OR = 2.20(95% CI: 1.38, 3.50)), history of sharing sharp material (OR = 1.88 (95% CI: 1.07, 3.31)), blood transfusion (OR = 2.41 (95% CI: 1.62, 3.57)), family history of HBV (OR = 4.87 (95% CI: 2.95, 8.05)) and history needle injury (OR = 2.62 (95% CI: 1.20, 5.72)) were significant risk factors associated with HBV infection among pregnant women. CONCLUSIONS: The pooled prevalence of HBV infection among pregnant women in East Africa was an intermediate level and different across countries ranging from 1.5% to 22.2%. The result of this pooled prevalence was an indication of the need for screening, prevention, and control of HBV infection among pregnant women in the region. Therefore, early identification of risk factors, awareness creation on the mode of transmission HBV and implementation of preventive measures are essential in reducing the burden of HBV infection among pregnant women.

Trends, spatiotemporal variation and decomposition analysis of pregnancy termination among women of reproductive age in Ethiopia: Evidence from the Ethiopian demographic and health survey, from 2000 to 2016.

Background: Pregnancy termination is a major public health problem, and complications of unsafe abortion are among the proximate and major causes of maternal mortality. Mapping the trend and spatiotemporal variation and identifying factors that are responsible for the changes in pregnancy termination help achieve the sustainable development goal of reducing maternal mortality in Ethiopia by understanding the epidemiology and regional variations. Methods: Data from the 2000-2016 Ethiopian Demographic and Health Survey were analyzed with a total weighted sample of 40,983 women of reproductive age. Variables with a p-value <0.05 in a logit multivariable decomposition analysis were considered significant predictors of the decline in pregnancy termination over time. Spatial analysis was used separately for each survey to show the changes in regional disparities in pregnancy termination in Ethiopia. Results: The magnitude of pregnancy termination among women of reproductive age decreased by 39.5 %, from 17.7 % in 2000 to 10.7 % in 2016. The difference in the effects of literacy, working status, marital status, age at first intercourse, age at first cohabitation, knowledge about contraceptives, and knowledge of the ovulatory cycle were the significant predictors that contributed to the change in pregnancy termination over time. Significant clusters of pregnancy terminations were observed in central and northern Ethiopia (Addis Ababa, eastern Amhara, and Tigray regions). Conclusions: Despite the substantial decrease in terminated pregnancies over time in Ethiopia, the magnitude is still high. The government should focus on promoting education for girls and women, providing reproductive health education, including access to contraceptives, and raising the minimum age for girls to engage in sexual activities or marriage by implementing policies.

Factors related to blood pressure assessment during pregnancy in Ethiopia: Multilevel analysis using the 2019 mini demographic and health survey data.

INTRODUCTION: Blood pressure assessment is an essential strategy for early detection and treatment of hypertension and hypotension. Hypertensive disorders of pregnancy (HDP) are major public health problems resulting in a significant burden of perinatal and maternal morbidity and mortality. In Ethiopia, among pregnancies complicated by HDP, 25% end up with perinatal death. Perinatal and maternal mortality related to HDP were found to be higher in Ethiopia compared to high-income and most of the low- and middle-income countries. Despite its importance, there is limited evidence on blood pressure assessment during pregnancy. Therefore, this study aimed to determine the prevalence of blood pressure assessment during pregnancy and its associated factors in Ethiopia. METHODS: This study was based on the 2019 Mini Ethiopian Demographic and Health Survey data. A total weighted sample of 2923 women who had a live birth five years before the survey were included and Stata version 16 software was used for statistical analysis. To identify associated factors, a multilevel robust Poisson regression model was fitted since the prevalence of blood pressure assessment was higher than 10%. Variables with p-value < 0.2 in the bi-variable analysis were exported to the multivariable analysis. In the multivariable analysis, the adjusted prevalence ratio with its 95% confidence interval was used to declare a statistically significant association. RESULTS: In Ethiopia, the prevalence of blood pressure assessment during pregnancy was 88.1% (95% CI: 86.9%, 89.2%). In the multivariable multilevel robust Poisson analysis, primary education and secondary education, grand-multiparity, initiation of antenatal care before three months and 3-6 months, four and above antenatal care visits, being counselled by a health professional, being from richer and richest households, residing in Afar and Amhara regions were significantly associated with BP assessment during pregnancy in Ethiopia. CONCLUSION AND RECOMMENDATIONS: To reduce the high burden of mortality related to hypertensive disorders of pregnancy in the country, blood pressure assessment should be improved. Therefore, policymakers should design interventions that empower women in terms of education and economy, promoting early initiation of antenatal care visits and prenatal counselling could improve blood pressure assessment.

Predicting the individualized risk of human immunodeficiency virus infection among sexually active women in Ethiopia using a nomogram: prediction model development and validation.

Introduction: Women are more vulnerable to HIV infection due to biological and socioeconomic reasons. Developing a predictive model for these vulnerable populations to estimate individualized risk for HIV infection is relevant for targeted preventive interventions. The objective of the study was to develop and validate a risk prediction model that allows easy estimations of HIV infection risk among sexually active women in Ethiopia. Methods: Data from the 2016 Ethiopian Demographic and Health Survey, which comprised 10,253 representative sexually active women, were used for model development. Variables were selected using the least absolute shrinkage and selection operator (LASSO). Variables selected by LASSO were incorporated into the multivariable mixed-effect logistic regression model. Based on the multivariable model, an easy-to-use nomogram was developed to facilitate its applicability. The performance of the nomogram was evaluated using discrimination and calibration abilities, Brier score, sensitivity, and specificity. Internal validation was carried out using the bootstrapping method. Results: The model selected seven predictors of HIV infection, namely, age, education, marital status, sex of the household head, age at first sex, multiple sexual partners during their lifetime, and residence. The nomogram had a discriminatory power of 89.7% (95% CI: 88.0, 91.5) and a calibration p-value of 0.536. In addition, the sensitivity and specificity of the nomogram were 74.1% (95% CI: 68.4, 79.2) and 80.9% (95% CI: 80.2, 81.7), respectively. The internally validated model had a discriminatory ability of 89.4% (95% CI: 87.7, 91.1) and a calibration p-value of 0.195. Sensitivity and specificity after validation were 72.9% (95% CI: 67.2, 78.2) and 80.1% (95% CI: 79.3, 80.9), respectively. Conclusion: A new prediction model that quantifies the individualized risk of HIV infection has been developed in the form of a nomogram and internally validated. It has very good discriminatory power and good calibration ability. This model can facilitate the identification of sexually active women at high risk of HIV infection for targeted preventive measures.

Incidence rate of mortality and its predictors among tuberculosis and human immunodeficiency virus coinfected patients on antiretroviral therapy in Ethiopia: systematic review and meta-analysis.

Background: Tuberculosis (TB) is the leading cause of death among HIV-infected adults and children globally. Therefore, this study was aimed at determining the pooled mortality rate and its predictors among TB/HIV-coinfected patients in Ethiopia. Methods: Extensive database searching was done via PubMed, EMBASE, SCOPUS, ScienceDirect, Google Scholar, and Google from the time of idea conception on March 1, 2023, to the last search via Google on March 31, 2023. A meta-analysis was performed using the random-effects model to determine the pooled mortality rate and its predictors among TB/HIV-coinfected patients. Heterogeneity was handled using subgroup analysis, meta-regression, and sensitivity analysis. Results: Out of 2,100 records, 18 articles were included, with 26,291 total patients. The pooled incidence rate of mortality among TB/HIV patients was 12.49 (95% CI: 9.24-15.74) per 100 person-years observation (PYO); I2 = 96.9%. The mortality rate among children and adults was 5.10 per 100 PYO (95% CI: 2.15-8.01; I2 = 84.6%) and 15.78 per 100 PYO (95% CI: 10.84-20.73; I2 = 97.7%), respectively. Age ≥ 45 (pooled hazard ratios (PHR) 2.58, 95% CI: 2.00- 3.31), unemployed (PHR 2.17, 95% CI: 1.37-3.46), not HIV-disclosed (PHR = 2.79, 95% CI: 1.65-4.70), bedridden (PHR 5.89, 95% CI: 3.43-10.12), OI (PHR 3.5, 95% CI: 2.16-5.66), WHO stage IV (PHR 3.16, 95% CI: 2.18-4.58), BMI < 18.5 (PHR 4.11, 95% CI: 2.28-7.40), anemia (PHR 4.43, 95% CI: 2.73-7.18), EPTB 5.78, 95% CI: 2.61-12.78 significantly affected the mortality. The effect of TB on mortality was 1.95 times higher (PHR 1.95, 95% CI: 1.19-3.20; I2 = 0) than in TB-free individuals. Conclusions: The mortality rate among TB/HIV-coinfected patients in Ethiopia was higher compared with many African countries. Many clinical factors were identified as significant risk factors for mortality. Therefore, TB/HIV program managers and clinicians need to design an intervention early.

Anxiety and depression among cancer patients in Ethiopia: a systematic review and meta-analysis.

Introduction: Anxiety and depression are among the common comorbidities of people diagnosed with cancer. However, despite the progress in therapeutic options and outcomes, mental health care and support have lagged behind for cancer patients. Estimating the extent and determinants of mental health disorders among cancer patients is crucial to alert concerned bodies for action. In view of this, we aimed to determine the pooled prevalence and determinants of anxiety and depression among cancer patients in Ethiopia. Methods: Relevant literatures were searched on PubMed, African Journals Online, Hinari, Epistemonikos, Scopus, EMBASE, CINAHL, Cochrane Library, and Gray literature sources. Data were extracted into an Excel spreadsheet and analyzed using STATA 17 statistical software. The random effect model was used to summarize the pooled effect sizes with their respective 95% confidence intervals. The I2 statistics and Egger's regression test in conjunction with the funnel plot were utilized to evaluate heterogeneity and publication bias among included studies respectively. Results: A total of 17 studies with 5,592 participants were considered in this review. The pooled prevalence of anxiety and depression among cancer patients in Ethiopia were 45.10% (95% CI: 36.74, 53.45) and 42.96% (95% CI: 34.98, 50.93), respectively. Primary and above education (OR= 0.76, 95% CI: 0.60, 0.97), poor social support (OR= 2.27, 95% CI: 1.29, 3.98), occupational status (OR= 0.59; 95% CI: 0.43, 0.82), advanced cancer stage (OR= 2.19, 95% CI: 1.38, 3.47), comorbid illness (OR= 1.67; 95% CI: 1.09, 2.58) and poor sleep quality (OR= 11.34, 95% CI: 6.47, 19.89) were significantly associated with depression. Whereas, advanced cancer stage (OR= 1.59, 95% CI: 1.15, 2.20) and poor sleep quality (OR= 12.56, 95% CI: 6.4 1, 24.62) were the factors associated with anxiety. Conclusion: This meta-analysis indicated that a substantial proportion of cancer patients suffer from anxiety and depression in Ethiopia. Educational status, occupational status, social support, cancer stage, comorbid illness and sleep quality were significantly associated with depression. Whereas, anxiety was predicted by cancer stage and sleep quality. Thus, the provision of comprehensive mental health support as a constituent of chronic cancer care is crucial to mitigate the impact and occurrence of anxiety and depression among cancer patients. Besides, families and the community should strengthen social support for cancer patients. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023468621.