Human papillomavirus vaccination uptake and determinant factors among adolescent schoolgirls in sub-Saharan Africa: A systematic review and meta-analysis.

Despite the ongoing global vaccination campaign aimed at preventing human papillomavirus (HPV) related health issues, the uptake of the HPV vaccine remains unacceptably low in developing regions, particularly in sub-Saharan Africa (SSA). Therefore, this systematic review and meta-analysis aimed at determining the pooled prevalence and associated factors of HPV vaccine uptake among adolescent school girls in SSA. Electronic bio-medical databases were explored. Pooled prevalence, publication bias, meta-regression, sub-group, and sensitivity analysis were performed. The estimated pooled prevalence of HPV vaccine uptake was 28.53% [95% CI: (5.25, 51.81)]. Having good knowledge and a positive attitude was significantly associated with HPV vaccine uptake in SSA. Subgroup analysis revealed the highest uptake was 62.52% from Kenya and the lowest was 3.77% in Nigeria. The HPV vaccine uptake is low. It underscores the need for community education, school-based immunization, and education programs that promote the uptake of the vaccine to increase coverage.

Double burden of malnutrition and associated factors among women of reproductive age in sub-Saharan Africa: a multilevel multinomial logistic regression analysis.

BACKGROUND: Globally, malnutrition among women of reproductive age is on the rise and significantly contributing to non-communicable disease, deaths and disability. Even though the double burden of malnutrition (DBM) is a common problem among women in sub-Saharan Africa (SSA), there are limited studies examining the factors contributing to underweight, overweight, and obesity at the SSA level. OBJECTIVE: To determine the factors associated with the DBM, and their relative magnitude, among women of reproductive age in SSA. DESIGN: Cross-sectional study design. SETTING: 33 SSA countries. PARTICIPANTS: 240 414 women of reproductive age. PRIMARY AND SECONDARY OUTCOME MEASURES: A multilevel multinomial logistic regression model was applied to identify factors associated with malnutrition. The adjusted relative risk ratio with 95% CI was used to declare the statistical significance of the association. RESULTS: The pooled prevalence of underweight, overweight and obesity among women in SSA were 8.87%, 16.47% and 6.10%, respectively. Women who are from rural residence and smoke cigarettes were more likely to be underweight. Conversely, women between the age of 24-34 and 35-49, who have higher education, belong to a middle and rich household, are ever married, have high parity, use contraceptives, have media exposure and smoke cigarettes were more likely to be overweight and/or obese. CONCLUSION: The findings of our study suggest that certain factors such as residence, education status, wealth, marital status, occupation, cigarette smoking, and contraceptive use have a significant assocation with malnutrition among women. Therefore, it is important for public health programs aimed at preventing the double burden of malnutrition to focus on these factors through comprehensive public awareness and cost-effective operational health interventions.

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.

Risk factors of necrotizing enterocolitis among neonates admitted to the neonatal intensive care unit at the selected public hospitals in southern Ethiopia, 2023.

Introduction: Necrotizing enterocolitis (NEC) is a serious intestinal condition characterized by ischemic necrosis of the intestinal mucosa, inflammation, and invasion by gas-forming organisms, posing a significant threat to neonatal health. Necrotizing enterocolitis remains a significant cause of neonatal morbidity and mortality, particularly in developing countries. Due to limited research conducted in Ethiopia and the study area, there is a lack of information regarding the risk factors associated with necrotizing enterocolitis. Therefore, the goal of this study is to fill the aforementioned gap. Objective: This study aims to identify the risk factors of necrotizing enterocolitis among neonates admitted to the neonatal intensive care unit (NICU) at selected general and referral hospitals in southern Ethiopia in the year 2023. Methods and materials: A facility-based unmatched case-control study was conducted. All neonates admitted to the NICU and diagnosed with necrotizing enterocolitis by the attending physician during the data collection period were considered as cases, whereas neonates admitted to the NICU but not diagnosed with necrotizing enterocolitis during the data collection period were considered as controls. Data were collected through face-to-face interviews and record reviews using the Kobo toolbox platform. The binary logistic regression method was used to determine the relationship between a dependent variable and independent variables. Finally, a p-value of < 0.05 was considered statistically significant. Results: This study included 111 cases and 332 controls. Normal BMI [AOR = 0.11, 95% CI: (0.02, 0.58)], history of khat chewing [AOR = 4.21, 95% CI: (1.96, 9.06)], term gestation [AOR = 0.06, 95% CI: (0.01, 0.18)], history of cigarette smoking [AOR = 2.86, 95% CI: (1.14, 7.14)], length of hospital stay [AOR = 3.3, 95% CI: (1.43, 7.67)], and premature rupture of membrane [AOR = 3.51, 95% CI: (1.77, 6.98)] were significantly associated with NEC. Conclusion: The study identified several risk factors for necrotizing enterocolitis, including body mass index, history of khat chewing, gestational age, history of cigarette smoking, length of hospital stays, and premature rupture of membrane. Therefore, healthcare providers should be aware of these risk factors to identify newborns at high risk and implement preventive measures.

Levels of stunting associated factors among under-five children in Ethiopia: A multi-level ordinal logistic regression analysis.

INTRODUCTION: Stunting is a major public health problem affecting more than one-third of under five year's old children in Ethiopia. It has short and long (irreversible) consequences, including stunted growth, never reaching physical and cognitive potential, struggles in school, and increased morbidity and mortality due to infections. Though stunting is the leading cause of child mortality in Ethiopia, evidence is scarce on the prevalence and predictors of stunting among under-five years old children in Ethiopia. Therefore, this study aimed to estimate the prevalence and predictors of stunting severity among under-5 children in Ethiopia. MATERIALS AND METHODS: This study was based on 2019 Mini-Ethiopian Demographic and Health Survey (EDHS) data. A weighted total sample of 4972 under-five years old children was included in the study. Height measurement was collected for each child. Anthropometric indicator, height-for-age was determined for children using World Health Organization growth standards (Z-scores for Height-for-Age (HAZ)) to asses stunting level. Given the ordinal nature of stunting and the hierarchical nature of EDHS data, a multilevel ordinal logistic regression model was applied. Brant test was used to check the proportional odds assumption, which was satisfied (P-value ≥0.05). Moreover, deviance was used for model comparison. For the multivariable analysis, variables with a p-value ≤0.2 in the bivariable analysis were considered. The Adjusted Odds Ratio (AOR) with 95% Confidence Interval (CI) was reported as associated factor to the severity levels of stunting in the multivariable multilevel proportional odds model. RESULTS: The overall prevalence of stunting among under-5 children in Ethiopia was 35.7% [95% CI: 34.4%, 37.1%]. Of these, 12.1% were severely stunted, and 24.9% were moderately stunted. Being male [AOR = 0.83, 95% CI: 0.74, 0.93], children aged 6-23 months [AOR = 2.38, 95% CI: 1.84, 3.07], ≥ 24 months [AOR = 4.15, 95% CI: 3.26, 5.28], children whose maternal age 15-24 years [AOR = 0.73, 95% CI: 0.58, 0.92], children from the poorest, poorer, middle, and richer household wealth were [AOR = 1.84, 95% CI: 1.32, 2.57], [AOR = 1.66, 95% CI: 1.20, 2.31], [AOR = 1.78, 95% CI: 1.29, 2.44], and [AOR = 1.62, 95% CI: 1.20, 2.17], children whose maternal educational status of no formal education and primary education had [AOR = 1.90, 95% CI: 1.28, 2.82], [AOR = 1.78, 95% CI: 1.22, 2.60], Tigray [AOR = 2.95, 95% CI: 1.78, 4.86], Afar [AOR = 1.85, 95% CI: 1.11, 3.10], Amhara [AOR = 1.90, 95% CI: 1.14, 3.14] and Harari [AOR = 1.97, 95% CI: 1.20, 3.25]regions, low community maternal education [AOR = 0.76, 95% CI: 0.62, 0.92] were significantly associated with stunting severity levelling. CONCLUSION: Stunting among children under five years of old in Ethiopia remains a major public health issue. Improving access to maternal education is related to appropriate child feeding practices and health, particularly in younger and uneducated mothers. Strengthening the family's wealth status is also recommended to reduce stunting. In addition, it is better to support strategies of preconception care for mothers during pregnancy to reduce stunting in the long term.

Determinants of high-risk fertility behavior among women of reproductive age in Kenya: a multilevel analysis based on 2022 Kenyan demographic and health survey.

BACKGROUND: Women's high-risk fertility behavior (HRFB), which is characterized by narrow birth intervals, high birth order, and younger maternal age at birth, have been scientifically reported to have detrimental effects on the mother and child's health. To date, there has been limited research into the underlying factors contributing to high-risk fertility behavior in Kenya. Thus, the aim of this study is to identify the factors associated with high-risk fertility behavior among women of reproductive age in Kenya. METHOD: The 2022 Kenyan Demography and Health Survey data was used for the current study. This study included 15,483 women of reproductive age. To account for the clustering effects of DHS data and the binary nature of the outcome variable, a multilevel binary logistic regression model was applied. An adjusted odds ratio with a 95% confidence interval was reported to declare the statistical significance. In addition, the model that had the lowest deviance was the one that best fit the data. RESULTS: The overall prevalence of HRFB among Kenyan women were 70.86% (95%CI = 69.96, 71.40). Women with primary, secondary, and higher educational levels, Protestant and Muslim religion followers, women whose husbands/partners had secondary and higher educational levels, a high household wealth index, ever had a terminated pregnancy, and rural residence, all of these factors were found to be strongly associated with high-risk fertility behavior. CONCLUSION: As per the findings of our study, in Kenya a significant proportion of women has experienced HRFB. This is a matter of concern as it poses a significant challenge to the healthcare system. The high prevalence of HRFB indicates that there is an urgent need to take appropriate measures in order to mitigate its impact. The situation calls for a comprehensive and coordinated approach involving all stakeholders to address this issue effectively. It would benefit policymakers to create programs that consider factors like education, wealth, and residence that make women more susceptible to HRFB. Targeting women living in high HRFB-prevalence areas could help address the root causes of the issue. This approach can alleviate negative impacts and ensure effective and sustainable solutions.

Development and Validation of a Risk Prediction Model to Estimate the Risk of Stroke Among Hypertensive Patients in University of Gondar Comprehensive Specialized Hospital, Gondar, 2012 to 2022.

Background: A risk prediction model to predict the risk of stroke has been developed for hypertensive patients. However, the discriminating power is poor, and the predictors are not easily accessible in low-income countries. Therefore, developing a validated risk prediction model to estimate the risk of stroke could help physicians to choose optimal treatment and precisely estimate the risk of stroke. Objective: This study aims to develop and validate a risk prediction model to estimate the risk of stroke among hypertensive patients at the University of Gondar Comprehensive Specialized Hospital. Methods: A retrospective follow-up study was conducted among 743 hypertensive patients between September 01/2012 and January 31/2022. The participants were selected using a simple random sampling technique. Model performance was evaluated using discrimination, calibration, and Brier scores. Internal validity and clinical utility were evaluated using bootstrapping and a decision curve analysis. Results: Incidence of stroke was 31.4 per 1000 person-years (95% CI: 26.0, 37.7). Combinations of six predictors were selected for model development (sex, residence, baseline diastolic blood pressure, comorbidity, diabetes, and uncontrolled hypertension). In multivariable logistic regression, the discriminatory power of the model was 0.973 (95% CI: 0.959, 0.987). Calibration plot illustrated an overlap between the probabilities of the predicted and actual observed risks after 10,000 times bootstrap re-sampling, with a sensitivity of 92.79%, specificity 93.51%, and accuracy of 93.41%. The decision curve analysis demonstrated that the net benefit of the model was better than other intervention strategies, starting from the initial point. Conclusion: An internally validated, accurate prediction model was developed and visualized in a nomogram. The model is then changed to an offline mobile web-based application to facilitate clinical applicability. The authors recommend that other researchers eternally validate the model.

Determinants of anemia level among reproductive-age women in 29 Sub-Saharan African countries: A multilevel mixed-effects modelling with ordered logistic regression analysis.

BACKGROUND: Despite the implementation of different nutritional and non-nutritional interventions, 43% of reproductive-age women in Africa suffer from anemia. Recent evidence also shows that none of the Sub-Saharan African (SSA) countries are on the track to achieve the nutrition target of 50% anemia reduction by 2030. To date, information on the level of anemia and its determinants among reproductive-age women at the SSA level is limited. Thus, this study aimed to estimate the pooled prevalence of anemia level and its determinants in SSA countries. METHODS: We used a pooled data of 205,627 reproductive-age women from the recent demographic and health surveys of 29 SSA countries that were conducted between 2010-2021. A multilevel mixed-effects analysis with an ordered logistic regression model was fitted to identify determinants of anemia level and the deviance value was used to select the best-fitted model. First, bivariable ordinal logistic regression analysis was done and the proportional odds assumption was checked for each explanatory variable using a Brant test. Finally, in a multivariable multilevel ordinal logistic regression model, a p-value<0.05 and AOR with the corresponding 95% CI were used to identify determinants of anemia level. All analyses were done using Stata version 17 software. RESULTS: The pooled prevalence of anemia among women of reproductive age in SSA was 40.5% [95% CI = 40.2%-40.7%], where 24.8% [95% CI: 24.6%-25.0%], 11.1% [95% CI = 10.9%-11.2%], and 0.8% [95% CI = 0.7%-0.8%] had mild, moderate, and severe anemia, respectively. The prevalence significantly varied from the lowest of 13% in Rwanda to the highest of 62% in Mali, and anemia was found as a severe public health problem (prevalence of ≥ 40%) in 18 countries. The regression result revealed that polygamous marriage, women and husband illiteracy, poor household wealth, shorter birth interval, non-attendance of antenatal care, underweight, unimproved toilet and water facilities, and low community-level women literacy were positively linked with high anemia level. Additionally, the likelihood of anemia was lower in women who were overweight and used modern contraception. CONCLUSIONS: Overall results showed that anemia among women of reproductive age is a severe public health problem in SSA countries, affecting more than four in ten women. Thus, enhancing access to maternal health services (antenatal care and contraception) and improved sanitation facilities would supplement the existing interventions targeted to reduce anemia. Moreover, strengthening women's education and policies regulating the prohibition of polygamous marriage are important to address the operational constraints.

Suboptimal birth spacing practice and its predictors among reproductive-age women in Sub-Saharan African countries: a multilevel mixed-effects modeling with robust Poisson regression.

BACKGROUND: Despite the availability of exempted family planning services, a significant proportion of women in African countries continue to experience inadequately spaced pregnancies. To the authors' knowledge, evidence of suboptimal birth intervals at the SSA level is lacking and previous studies have been limited to specific geographic area. Therefore, this analysis was aimed to estimate the pooled prevalence of suboptimal birth spacing and its predictors among childbearing women in SSA. METHODS: Pooled DHS data from 35 SSA countries were used and a weighted sample of 221,098 reproductive-age women was considered in the analysis. The survey across all countries employed a cross-sectional study design and collected data on basic sociodemographic characteristics and different health indicators. Forest plot was used to present the overall and country-level prevalence of suboptimal birth spacing. Multilevel mixed-effects models with robust Poisson regression were fitted to identify the predictors of suboptimal birth spacing. Akaike's and Bayesian information criteria and deviance were used to compare the models. In a multivariable regression model, a p-value less than 0.05 and an adjusted prevalence ratio with the corresponding 95% CI were used to assess the statistical significance of the explanatory variables. RESULTS: The pooled prevalence of suboptimal birth spacing among women in SSA was 43.91% (43.71%-44.11%), with South Africa having the lowest prevalence (23.25%) and Chad having the highest (59.28%). It was also found that 14 of the 35 countries had a prevalence above the average for SSA. Rural residence [APR (95% CI) = 1.10 (1.12-1.15)], non-exposure to media [APR (95% CI) = 1.08 (1.07-1.11)], younger maternal age [APR (95% CI) = 2.05 (2.01-2.09)], non-use of contraception [APR (95% CI) = 1.18 (1.16-1.20)], unmet need for family planning [APR (95% CI) = 1.04 (1.03-1.06)], higher birth order [APR (95% CI) = 1.31 (1.28-1.34)], and desire to have at least six children [APR (95% CI) = 1.14 (1.13-1.16)] were the predictors of suboptimal birth spacing practice. CONCLUSION: More than four out of ten reproductive-age women in SSA countries gave birth to a subsequent child earlier than the recommended birth spacing, with considerable variations across the countries. Thus, interventions designed at enhancing optimal birth spacing should pay particular attention to young and socioeconomically disadvantaged women and those residing in rural regions. Strengthening community health programs and improving accessibility and availabilities of fertility control methods that ultimately impacts optimal reproductive behaviors is crucial to address contraceptive utilization and unmet need.

Development and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005-2021.

BACKGROUND: Diabetic neuropathy is the most common complication in both Type-1 and Type-2 DM patients with more than one half of all patients developing nerve dysfunction in their lifetime. Although, risk prediction model was developed for diabetic neuropathy in developed countries, It is not applicable in clinical practice, due to poor data, methodological problems, inappropriately analyzed and reported. To date, no risk prediction model developed for diabetic neuropathy among DM in Ethiopia, Therefore, this study aimed prediction the risk of diabetic neuropathy among DM patients, used for guiding in clinical decision making for clinicians. OBJECTIVE: Development and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005-2021. METHODS: A retrospective follow up study was conducted with a total of 808 DM patients were enrolled from January 1,2005 to December 30,2021 at two selected referral hospitals in Amhara regional state. Multi-stage sampling techniques were used and the data was collected by checklist from medical records by Kobo collect and exported to STATA version-17 for analysis. Lasso method were used to select predictors and entered to multivariable logistic regression with P-value<0.05 was used for nomogram development. Model performance was assessed by AUC and calibration plot. Internal validation was done through bootstrapping method and decision curve analysis was performed to evaluate net benefit of model. RESULTS: The incidence proportion of diabetic neuropathy among DM patients was 21.29% (95% CI; 18.59, 24.25). In multivariable logistic regression glycemic control, other comorbidities, physical activity, hypertension, alcohol drinking, type of treatment, white blood cells and red blood cells count were statistically significant. Nomogram was developed, has discriminating power AUC; 73.2% (95% CI; 69.0%, 77.3%) and calibration test (P-value = 0.45). It was internally validated by bootstrapping method with discrimination performance 71.7 (95% CI; 67.2%, 75.9%). It had less optimism coefficient (0.015). To make nomogram accessible, mobile based tool were developed. In machine learning, classification and regression tree has discriminating performance of 70.2% (95% CI; 65.8%, 74.6%). The model had high net benefit at different threshold probabilities in both nomogram and classification and regression tree. CONCLUSION: The developed nomogram and decision tree, has good level of accuracy and well calibration, easily individualized prediction of diabetic neuropathy. Both models had added net benefit in clinical practice and to be clinically applicable mobile based tool were developed.

Prevalence and associated factors of active trachoma among 1-9 years of age children in Andabet district, northwest Ethiopia, 2023: A multi-level mixed-effect analysis.

BACKGROUND: Trachoma is the chief cause of preventable blindness worldwide and has been earmarked for elimination as a public health problem by 2030. Despite the five-year Surgery, Antibiotics, Facial cleanliness, and Environmental improvement (SAFE)-based interventions in the Andabet district, the prevalence of trachomatous follicular (TF) was 37%. With such a high prevalence of TF, the determinant factors were not revealed. Besides, there were no reports on the overall prevalence of active trachoma (i.e.TF and or trachomatous intense (TI)). OBJECTIVE: To determine the prevalence and associated factors of active trachoma among 1-9 years of age children in the Andabet district. METHOD: A community-based cross-sectional study was conducted among children aged under nine years from March 1-30, 2023 in Andabet district, Northwest Ethiopia. Multi-stage systematic random sampling was employed to reach 540 children. A multilevel mixed-effect logistic regression analysis was employed to assess factors associated with active trachoma. We fitted both random effect and fixed effect analysis. Finally, variables with p<0.05 in the multivariable multilevel analysis were claimed to be significantly associated with active trachoma. RESULT: In this study, the overall prevalence of active trachoma was 35.37% (95% CI: 31.32%, 39.41%). The prevalence of TF and TI was 31.3% and 4.07% respectively. In the multilevel logistic regression analysis ocular discharge, fly-eye contact, latrine utilization, and source of water were significantly associated with the prevalence of active trachoma. CONCLUSION: In this study, the prevalence of active trachoma was much higher than the World Health Organization (WHO) threshold prevalence. Ocular discharge, fly-eye contact, latrine utilization, and source of water were independent determinants of active trachoma among children (1-9 years). Therefore, paying special attention to these high-risk groups could decrease the prevalence of a neglected hyperendemic disease, active trachoma.

Unimproved source of drinking water and its associated factors: a spatial and multilevel analysis of Ethiopian demographic and health survey.

BACKGROUND: Drinking water quality has been a major public health concern in lower and middle income countries where access to improved water supplies is limited. Ethiopia is thought to have one of the worst drinking water infrastructures in the world. This study aimed to assess the spatial variation and determinants of using unimproved sources of drinking water in Ethiopia using recent nationally representative data. METHODS: A population-based cross-sectional study was employed with the recent EDHS data of 2019. A total of 8663 households were sampled using a stratified two-stage cluster sampling method. Kuldorff's SaTScan version 9.6 software was used to generate spatial scan statistics. ArcGIS version 10.7 software was used to visualize the spatial patterns of unimproved drinking water sources. A multilevel multivariable mixed-effect logistic regression was used to identify factors associated with the use of an unimproved drinking water source. In the multivariable multilevel analysis, those variables with a p-value < 0.05 were considered to be significant predictors of using an unimproved source of drinking water. RESULT: Around 31% (95% CI: 30%, 32%) of the population in Ethiopia uses unimproved sources of drinking water with significant spatial variation across the country. Households aged 41-60 [AOR = 0.69; 95%CI; 0.53, 0.89] as compared to the households aged 10-25, households having middle wealth index [AOR = 0.48; 95%CI; 0.40, 0.59], and households having a rich wealth index [AOR = 0.31; 95%CI; 0.25, 0.39] as compared to the poor households, living in high community literacy level [AOR = 0.36; 95%CI; 0.16, 0.80], living in high-level community poverty [AOR = 3.03; 95%CI; 1.32, 6.98], rural residence [AOR = 7.88; 95%CI; 2.74, 22.67] were significant predictors of use of unimproved source of drinking water. Hot spot areas of use of unimproved drinking water sources were observed in Amhara, Afar, and Somalia regions and some parts of SNNPR and Oromia regions in Ethiopia. The primary clusters were found in Ethiopia's Somalia and Oromia regions. CONCLUSION: Around one third of the Ethiopian population utilizes unimproved source of drinking water and it was distributed non-randomly across regions of Ethiopia. The age of the household head, wealth status of the household, residence, community poverty level, and community literacy level were found to be significantly associated with utilizing unimproved drinking water source. State authorities, non-governmental organizations and local health administrators should work to improve the quality of drinking water particularly for high risk groups such as communities living in high poverty and low literacy, poor households, rural residents, and hot spot areas to decrease the adverse consequences of using unimproved drinking water source.

Geographic variation and factors associated with under-five mortality in Ethiopia. A spatial and multilevel analysis of Ethiopian mini demographic and health survey 2019.

BACKGROUND: The distribution of under-five mortality (U5M) worldwide is uneven and the burden is higher in Sub-Saharan African countries, which account for more than 53% of the global under-five mortality. In Ethiopia, though U5M decreased substantially between 1990 and 2019, it remains excessively high and unevenly distributed. Therefore, this study aimed to assess geographic variation and factors associated with under-five mortality (U5M) in Ethiopia. METHODS: We sourced data from the most recent nationally representative 2019 Ethiopian Mini-Demographic and Health Survey for this study. A sample size of 5,695 total births was considered. Descriptive, analytical analysis and spatial analysis were conducted using STATA version 16. Both multilevel and spatial analyses were employed to ascertain the factors associated with U5M in Ethiopia. RESULTS: The U5M was 5.9% with a 95% CI 5.4% to 6.6%. Based on the multivariable multilevel logistic regression model results, the following characteristics were associated with under-five mortality: family size (AOR = 0.92, 95% CI: 0.84,0.99), number of under-five children in the family (AOR = 0.17, 95% CI: 0.14, 0.21), multiple birth (AOR = 14.4, 95% CI: 8.5, 24.3), children who were breastfed for less than 6 months (AOR = 5.04, 95% CI: 3.81, 6.67), people whose main roof is palm (AOR = 0.57, 95% CI: 0.34, 0.96), under-five children who are the sixth or more child to be born (AOR = 2.46, 95% CI: 1.49, 4.06), institutional delivery (AOR = 0.57, 95% CI: 0.41, 0.81), resident of Somali and Afar region (AOR = 3.46, 95% CI: 1.58, 7.55) and (AOR = 2.54, 95% CI: 1.10, 5.85), respectively. Spatial analysis revealed that hot spot areas of under-five mortality were located in the Dire Dawa and Somali regions. CONCLUSION: Under-five mortality in Ethiopia is high and unacceptable when compared to the 2030 sustainable development target, which aims for 25 per 1000 live births. Breastfeeding for less than 6 months, twin births, institutional delivery and high-risk areas of under-five mortality (Somali and Dire Dawa) are modifiable risk factors. Therefore, maternal and community education on the advantages of breastfeeding and institutional delivery is highly recommended. Women who deliver twins should be given special attention. An effective strategy should be designed for intervention in under-five mortality hot spot areas such as Somali and Dire Dawa.