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Introduction: As one of the agglomeration models targeting cluster-based rural development, cluster farming has been promoted in Ethiopia and it is already reported to have significant welfare implications, but participation rates are not as high as expected. This study examines the role of land as a constraint to the development of cluster-based development in Ethiopia both using extensive and intensive measures of cluster farming. The study further disaggregates farm households based on their farm size to better understand potential heterogeneities in the relationship between farm size and cluster farming. The paper also documents other household socio-economic and network characteristics that may matter in cluster farming. Methods: We use a large-scale farm household data from 3,969 households coupled with some expert insights on cluster farming in Ethiopia. Households in the study areas grow major staples such as maize, wheat, teff, malt barley, and sesame in four main regions of Ethiopia. We employ a double hurdle model to examine both the decision to participate and the extent to which households participate in cluster farming. By extent of participation, we refer to the amount of land and share of land farm households contribute to cluster farming. For robustness purposes, we also estimate the Tobit and Linear Probability Models. Results: We show a positive association between farm size and cluster farming both at the extensive and intensive margins. This relationship turns negative for large amounts of land. This shows that cluster farming increases with farm size up to a threshold beyond which it declines. We also find suggestive evidence that participation rates are lower for small-scale farms, but also declines for large-scale farms. In addition, we show that access to information and network characteristics also matter in enabling cluster farming. Conclusion: The findings of this study are relevant in the framework of plans to upscale the cluster-based development initiative in Ethiopia. Attention to landholding issues is key and may be an important area where policy action can be geared to boost cluster farming. Moreover, our results inform potential targeting plans that aim to increase the participation of small-scale farmers who are usually the intended targets of such programs. [ABSTRACT FROM AUTHOR]

Background: Home delivery is a nonclinical childbirth practice that takes place in one's home with or without traditional birth attendants and postnatal care is the care given to the mother and her newborn baby; according to world health organization (WHO), the postnatal phase, begins one hour after birth and lasts six weeks (42 days). This paper aimed to study the spatial pattern and determinant factors of low utilization of delivery care (DC) services and postnatal check-up (PNC) after live births in Ethiopia. Methods: This study used the 2016 Ethiopian Demographic and Health Survey data as a source. A total weighted samples of 11023 women-children pairs were included. The bivariate binary logistic regression analyses with spatial effect were modeled using SAS version 9.4 and ArcGIS version 10.8 was used for mapping. Results: The spatial distribution of low utilization of delivery care service and postnatal check-up were significantly clustered in Ethiopia (Moran's I statistic 0.378, P-value < 0.001 and 0.177, P-value < 0.001 respectively). Among 11023 children-women pair, the prevalence of home delivery and no postnatal check-up within two months following birth were 72.6% and 91.4% respectively. The Liben, Borena, Guji, Bale, Dolo and Zone 2 were predicted to have high prevalence of home delivery and part of Afder, Shabelle, Korahe, Dolo and Zone 2 were high risk areas of no postnatal checkup. Conclusion and recommendations: Lack of occupation, region, large family size, higher birth order, low utilization of antenatal care visit, unable to access mass media, big problem of health facility distance and the spatial variable were found to be jointly significant predictors of low utilization of DC and PNC in Ethiopia. Whereas older age, being reside in rural area and low wealth status affects delivery care service utilization. We suggest health providers, policy makers and stakeholders consider those variables with priority given to Liben, Borena, Guji, Bale, Dolo, Zone 2, Afder, Shabelle and Korahe, where home delivery and no PNC were predicted relatively high. We also recommend researchers to conduct further studies using latest survey data set. [ABSTRACT FROM AUTHOR]

Introduction: Telemedicine is a useful tool for decreasing hospital stress, patient suffering, ambulance needs, hospital anxiety, and costs while improving the standard of care. Nonetheless, the lack of awareness regarding telemedicine poses a barrier to its application, presenting several difficulties in underdeveloped nations like Ethiopia. This review evaluates Ethiopian-specific telemedicine knowledge and associated factors. Methods: This systematic review was conducted using a search of several online databases in addition to the main databases, like Medline, PubMed, Scopus, and Science Direct. The writers have looked for, reviewed, and summarized information about telemedicine knowledge in the healthcare system. This study contained seven studies that examined telemedicine knowledge in the Ethiopian healthcare sector. Studies that followed the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA) were found using search engines. The investigation was carried out using STATA version 11. The indicator of heterogeneity (I2) was used to assess the level of heterogeneity among the included studies. The funnel plot was visually inspected, and Egger's regression test was run to check for publication bias. The pooled effect size of every study is estimated using a random-effect model meta-analysis. Results: Examination of 2160 studies, seven studies involving 2775 health professionals, and seven out of the 2160 publications assessed satisfied the inclusion criteria and were added to the systematic review and meta-analysis. The pooled prevalence of Telemedicine knowledge was 45.20 (95% CI: 34.87–55.53). Whereas the pooled factor was computer training was 2.24 times (AOR = 2.24 (95%; CI: 1.64–3.08)), computer access was 2.07 times (AOR = 2.07 (95% CI: 1.50–2.87)), internet access was 3.09 times (AOR = 3.09 (95% CI: 1.34–7.13)), social media access were 3.09 times (AOR = 3.09(95%; CI: 1.34–7.13)), educational status degree and above were 2.73 times (AOR = 2.73; 95% CI: 0.85–8.82), Awareness were 3.18 times (AOR = 3.18 (95%; CI: 1.02–9.91)), Management support was 1.85 (AOR = 1.85 (95% CI: 01.25–2.75)), computer literacy were 2.90 times (AOR = 2.90 (95% CI: 1.81–4.64)), computer owner were 1.70 times (AOR = 1.70 (95% CI: 1.05–2.76)), male gender were 1.95 times (AOR = 1.95 (95% CI: 1.32–2.87)). Conclusion: The overall pooled prevalence of telemedicine knowledge was low. Gender, education, management support, computer access, social media access, internet access, telemedicine awareness, and telemedicine training associated with telemedicine knowledge. [ABSTRACT FROM AUTHOR]

Childhood anaemia is a public health problem in Ethiopia. Machine learning (ML) is a growing in medicine field to predict diseases. Diagnosis of childhood anaemia is resource intensive. The aim of this study is to apply machine learning (ML) algorithm to predict childhood anaemia using socio-demographic, economic, and maternal and child related variables. The study used data from 2016 Ethiopian demographic health survey (EDHS). We used Python software version 3.11 to apply and test ML algorithms through logistic regression, Random Forest (RF), Decision Tree, and K-Nearest Neighbours (KNN). We evaluated the performance of each of the ML algorithms using discrimination and calibration parameters. The predictive performance of the algorithms was between 60% and 66%. The logistic regression model was the best predictive model of ML with accuracy (66%), sensitivity (82%), specificity (42%), and AUC (69%), followed by RF with accuracy (64%), sensitivity (79%), specificity (42%), and AUC (63%). The logistic regression and the RF models of ML showed poorest family, child age category between 6 and 23 months, uneducated mother, unemployed mother, and stunting as high importance predictors of childhood anaemia. Applying logistic regression and RF models of ML can detect combinations of predictors of childhood anaemia that can be used in primary health care professionals. [ABSTRACT FROM AUTHOR]

Introduction: In low and middle-income countries, adolescent mental health is not only a major public health challenge but also a development concern. Depression and anxiety are the most common mental health disorders and somatic symptoms often co-exist with them. Adolescents with common mental health problems are associated with an increased risk of suicide, future unemployment, and poor quality of life. However, little is known about the mental health of adolescents in Ethiopia. Thus, this study aimed to assess the determinants of depression, anxiety, and somatic symptoms among adolescents in Northwest Ethiopia, in 2022. Methods: An institution-based cross-sectional study was conducted from June 8 to 24, 2022. Two-stage stratified random sampling was used to select 1407 adolescents in Northwest Ethiopia. Structured and standardized self-administered questionnaires were used to collect the data. Non-recursive structural equation modeling was employed to assess the direct, indirect, and total effects of predictors. Adjusted regression coefficients and corresponding 95% confidence intervals were used to interpret the strength of the association. Results: The prevalence of depression, anxiety, and somatic symptoms were 28.21% (95% CI: 25.8, 31%), 25.05% (95%CI: 22.8, 27.5), and 25.24(95% CI: 23, 27.6%) respectively. Alcohol use had a significant positive effect on depression [β = 0.14, 95% CI: 0.073, 0.201], anxiety [β = 0.11, 95% CI: 0.041, 0.188], and somatic symptoms [β = 0.12, 95% CI: 0.062, 0.211]. Stress had a significant positive effect on depression [β = 0.76, 95% CI: 0.642, 0.900], anxiety [β = 1.10, 95% CI: 0.955, 1.264], and somatic symptoms [β = 086, 95% C: 0.700, 1.025]. Depression had a direct positive effect on anxiety [β = 0.74, 95% CI: 0.508, 1.010]. Conclusion: In this study, the prevalence of depression, anxiety, and somatic symptoms was moderate. Alcohol use and stress were significantly related to depression, anxiety, and somatic symptoms. The bidirectional relationship between anxiety and depression was significant. Therefore, public health interventions should focus on the bidirectional relationship between depression and anxiety, as well as on identified factors to reduce the burden of mental illness in adolescents. [ABSTRACT FROM AUTHOR]

Background: A new coronavirus was first identified in Wuhan, China in December 2019. Since the times of the 1918 influenza pandemic, malnutrition has been known as a risk factor for severity and mortality from viral pneumonia. Similarly, the recently identified SARS-Cov2 infection (COVID-19) and related pneumonia may be closely linked to malnutrition. Therefore, this study will contribute to new knowledge and awareness of the recording and evaluation of each COVID-19 patient's nutritional status by assessing the effect of malnutrition on ICU admission and death of COVID-19 patients in developing countries. Method: We conducted a prospective cohort study in adult COVID-19 patients admitted to selected COVID-19 Isolation and Treatment Centers, Addis Ababa, Ethiopia. Baseline data of the patients were collected using interviewer-administered structured questionnaire and data on the adverse outcomes of follow up were extracted from follow up chart. The main clinical outcomes (ICU admission and death) were captured every week of follow up. We ran a multivariate Cox's regression analysis to determine the relationship between malnutrition at admission and its effect on ICU admission and death. Results: A total of 581 COVID-19 patients were enrolled. From the total of recruited patients, 346 (59.6%) were males and 235 (40.4%) were females. The mean age of the respondents was 55 years (16.45) years. The Cox proportional hazard model controlled for sex, age group, number of co-morbidities, and number of medications found that malnutrition at admission was associated with ICU admission and death. When compared to well-nourished patients, the rate of ICU admission was significantly associated and found to be higher among underweight [(adjusted hazard ratio (AHR) = 10.02, 95% CI: (8.64–12.10)] and overweight [(AHR = 7.7, 95% CI: (6.41–9.62)] patients. The rate of survival probability was significantly associated and was found to be better among well-nourished patients (AHR = 0.06, 95% CI : (0.01–0.44) when compared with malnourished COVID-19 patients. Conclusion: Malnutrition at the time of admission was shown to increase the risk of ICU admission and mortality among COVID-19 patients. Therefore, it is vital to evaluate patients' nutritional condition early in their admission and provide timely intervention to minimize the effects on patients and the healthcare system. [ABSTRACT FROM AUTHOR]

Introduction: Non-communicable diseases (NCDs) currently cause more deaths than all other causes of deaths. Cardiovascular disease, diabetes, cancer, and chronic respiratory diseases-threaten the health and economies of individuals and populations worldwide. This study aimed to assess the availability and readiness of health facilities for chronic non-communicable diseases (NCDs) and describe the changes of service availability for common NCDs in Ethiopia. Methods We used data from the 2014 Ethiopia Service Provision Assessment Plus (ESPA +) and 2016 and 2018 Service Availability and Readiness Assessment (SARA) surveys, which were cross-sectional health facility-based studies. A total of 873 health facilities in 2014, 547 in 2016, 632 in 2018 were included in the analysis. (ESPA+) and SARA surveys are conducted as a census or a nationally/sub-nationally representative sample of health facilities. Proportion of facilities that offered the service for diabetes, cardiovascular disease, chronic respiratory disease, cancer diseases, mental illness, and chronic renal diseases was calculated to measure health service availability. The health facility service readiness was measured using the mean availably of tracer items that are required to offer the service. Thus, 13 tracer items for diabetes disease, 12 for cardiovascular disease, 11 for chronic respiratory disease and 11 cervical cancer services were used. Results: The services available for diagnosis and management did not show improvement between 2014, 2016 and 2018 for diabetes (59%, 22% and 36%); for cardiovascular diseases (73%, 41% and 49%); chronic respiratory diseases (76%, 45% and 53%). Similarly, at the national level, the mean availability of tracer items between 2014, 2016 and 2018 for diabetes (37%, 53% and 48%); cardiovascular diseases (36%, 41% and 42%); chronic respiratory diseases (26%, 27% and 27%); and cancer diseases (6%, 72% and 51%). However, in 2014 survey year, the mean availability of tracer items was 7% each for mental illness and chronic renal diseases, respectively. Conclusions: The majority of the health facilities have low and gradual decrement in the availability to provide NCDs services in Ethiopia. There is a need to increase NCD service availability and readiness at primary hospitals and health centers, and private and rural health facilities where majority of the population need the services. [ABSTRACT FROM AUTHOR]

Introduction: Maternal and child mortality remained higher in developing regions such as Southern Ethiopia due to poor maternal and child health. Technologies such as mobile applications in health may be an opportunity to reduce maternal and child mortality because they can improve access to information. Therefore, the main aim of this study was to explore the role of mHealth in improving maternal and child health in Southern Ethiopia. Methods: This study employed a qualitative study design to explore the role of mHealth in improving maternal and child health among health professionals in Southern Ethiopia from December 2022 to March 2023. We conducted nine in-depth interviews, six key informants' in-depth interviews, and four focused group discussions among health professionals. This is followed by thematic analyses to synthesize the collected evidence. Results: The results are based on 226 quotations, 5 major themes, and 24 subthemes. The study participants discussed the possible acceptance of mHealth in terms of its fitness in the existing health system, its support to health professionals, and its importance in improving maternal and child health. The participants ascertained the importance of awareness creation before the implementation of mHealth among women, families, communities, and providers. They reported the importance of mHealth for mothers and health professionals and the effectiveness of mHealth services. The participants stated that the main challenges related to acceptance, awareness, negligence, readiness, and workload. However, they also suggested strategic solutions such as using family support, provider support, mothers' forums, and community forums. Conclusion: The evidence generated during this analysis is important information for program implementations and can inform policy-making. The planned intervention needs to introduce mHealth in Southern Ethiopia. Planners, decision-makers, and researchers can use it in mobile technology-related interventions. For challenges identified, we recommend solution-identified-based interventions and quality studies. [ABSTRACT FROM AUTHOR]

Introduction: Most households in low- and middle-income countries still cook using solid fuels in poorly ventilated dwellings. Indoor air pollution causes various health problems, like pneumonia, lung cancer, stillbirth, low birth weight, impaired cognitive development, and cataracts. Nevertheless, a few evidences are available in Africa, including Ethiopia. Therefore, this study aimed to assess the level of indoor air pollution prevention practices and associated factors among household mothers in Olenchiti town, Oromia, Ethiopia. Methods: A community-based cross-sectional study was conducted. Four hundred twenty mothers were randomly selected by systematic random sampling. Data was collected through an interview and observation checklist. The collected data entered into Epi-Info version 7.2.5 was cleaned, edited, and then exported to SPSS version 23 for analysis. Descriptive statistics were used to describe the findings. Binary logistic regression was computed to analyze the effect of each variable on the outcome variable. Model adequacy fitness was checked with the Hosmer-Lemeshow test. The multicollinearity of independent variables was checked with the variance inflation factor. Adjusted odds ratio with 95% confidence interval and P -value <0.05 was used as cutoff points to declare significance in the final model. Results: The overall good practices of mothers towards the prevention of indoor air pollution was 188 (45.0%). Mothers who had under-five children (AOR = 0.49, 95%CI (0.31–0.76), mothers in grade 9–12 (AOR = 0.51, 95%CI (0.28–0.92)) were significantly associated with indoor air pollution prevention practices. Conclusion: The overall good practices of mothers towards indoor air pollution were low compared to different findings. Under-five children and educational status were significantly associated with indoor air pollution prevention practices in the final model. Therefore, the high school curriculums should include indoor air pollution topics. [ABSTRACT FROM AUTHOR]

Sorghum is a staple crop grown in the poorest and most food-insecure regions of Ethiopia. But storage insect pests are its key constraints that have been causing considerable loss. Accordingly, an assessment of the prevalence of insect pests and the associated loss of sorghum stored under farmers' traditional storages was done in randomly selected major sorghum-growing kebeles of Kena District using a nested design between November 1, 2019 and December 30, 2020. It was conducted through the sampling of one kg of grain from a total of 360 randomly selected farmers' storages. Pests' abundance was determined by dividing the total number of individual species by the total number of samples. A count and weight method was used to estimate percent grain damage and weight loss by pests. Sitophilus zeamais, Sitophilus oryzae, Sitotroga cereallella, Tribolium castaneum, Tribolium confusum, Cryptolestes ferrugineus, Cryptolestes pusillus, Rhyzopertha dominica, and Plodia interpunctella were the pests identified from grain samples. When compared to mid-latitude, where they were found in the range between 2.36± 0.21 and 17.50±0.98 mean number of species, all of these pests had a considerably (p < 0.05) larger distribution in low-land kebeles, where they predominated in the range between 5.44±2.00 and 23.61±1.75 amean number. During the nine-month storage period, the degree of pest infestation, percentage of grain damage, and weight loss were significantly (p < 0.05) higher in the bamboo bins when no management measures were implemented in the mid-land and low-land kebeles, respectively, than in the barn. Consequently, bamboo bin storage was considered ineffective for sufficient sorghum grain protection against pests and the associated loss over a longer storage period. But barn storage and the use of cultural pest management practices performed better in protecting stored sorghum from pests. Therefore, improving the bamboo bin storage method is needed to improve its grain protection efficacy. [ABSTRACT FROM AUTHOR]