Background: Malnutrition is associated with both under nutrition and over nutrition which causes the body to get improp- er amount of nutrients to maintain tissues and organ function. Under nutrition is the result of insufficient intake of food, poor utilization of nutrients due to illnesses, or a combination of these factors. The purpose of this study was to identify associated risk factors and assess the variation of underweight among under-five children of different regions in Ethiopia. Methods: Ethiopian Demography and Health Survey (EDHS-2016) weight-to-age data for under-five children is used. In order to achieve the objective of this study; descriptive, single level and multilevel ordinal logistic regression analysis were used. Results: From a total of 8935 children about 8.1% were severely underweight, 17.1% were moderately underweight and 74.8% were normal. The test of heterogeneity suggested that underweight varies among region and multilevel ordinal model fit data better than single level ordinal model. Conclusion: Educational level of mother, religion, birth order, type of birth, sex of child, mother body mass index, birth size of child, existence of diarrhea for last two weeks before survey, existence of fever for last two weeks before survey, duration of breast feeding, age child and wealth index had significant effect on underweight among under-five children in Ethiopia. The finding revealed that among the fitted multilevel partial proportional odds model, the random intercept model with fixed coefficients is appropriate to assess the risk factors of underweight among under-five children in Ethiopia. The findings of this study have important policy implications. The government should work closely with both the private sector and civil society to teach women to have sufficient knowledge, awareness and mechanisms of improving under-five under- weight for children’s wellbeing. Keywords: Underweight; Partial proportional odds model; Multilevel partial proportional odds model; under-five children.

BackgroundThis paper studies the effect of mosquito abundance and malaria incidence in the last 3 weeks, and their interaction, on the hazard of time to malaria in a previously studied cohort of children in Ethiopia.MethodsWe model the mosquito abundance and time to malaria data jointly in a Bayesian framework.ResultsWe found that the interaction of mosquito abundance and incidence plays a prominent role on malaria risk. We quantify and compare relative risks of various factors, and determine the predominant role of the interaction between incidence and mosquito abundance in describing malaria risk. Seasonal rain patterns, distance to a water source of the households, temperature and relative humidity are all significant in explaining mosquito abundance, and through this affect malaria risk.ConclusionAnalyzing jointly the time to malaria data and the mosquito abundance allows a precise comparison of factors affecting the spread of malaria. The effect of the interaction between mosquito abundances and local presence of malaria parasites has an important effect on the hazard of time to malaria, beyond abundance alone. Each additional one km away from the dam gives an average reduction of malaria relative risk of 5.7%. The importance of the interaction between abundance and incidence leads to the hypothesis that preventive intervention could advantageously target the infectious population, in addition to mosquito control, which is the typical intervention today.

Background Both short and long birth intervals are associated with many risk factors and about 29% of births are short birth intervals in Ethiopia. The purpose of this study is to model the birth intervals of adult women aged 15–49 years using accelerated failure time and shared frailty models in order to analyze the birth intervals of Ethiopian women. Methods The data was obtained from the 2016 Ethiopian Demographic and Health Survey (EDHS). Accelerated failure time with different baseline and shared frailty models are used for the analysis to identify important demographic and socio-economic factors affecting the length of birth intervals and correlates of the birth intervals respectively. Results The data consists of 9147 women, of which about 7842 (85.5%) are closed interval and the rest of 1323(14.5%) are open interval. Accelerated failure time (AFT) result revealed that women education level, husbands education level, age at first birth, marital status, religion and family wealth index are significant factors affecting birth interval of women in Ethiopia. Conclusion Women with closely spaced births tend to have larger family sizes when compared with women with longer inter-birth interval. Longer successive birth interval tends to reduce the total fertility rate of women. Furthermore, improvements in socio-economic status and level of education of women associate with reduced fertility, improved maternal and child wellbeing, and longer birth interval.

Perinatal mortality is the death of a fetus after the age of viability until the 7th day of life. Perinatal mortality is estimated by the addition of stillbirths plus the early neonatal mortality, which represents deaths occurring during the first 7 days after delivery. Perinatal mortality remains a great burden in Ethiopia. The purpose of this study was to assess and compare the demographic and socio-economic determinant factors of perinatal mortality in Ethiopia using the 2011 and 2016 Ethiopian Demographic Health Surveys (EDHS). For data analysis, the Bayesian multilevel  Model was used in this study. The study revealed that there is a regional variation in perinatal mortality and this variation was high in 2011 EDHS than in 2016 EDHS data. Factors like sex of the child, age of mother, wealth index, family size, birth order, source of drinking water, place of residence, place of delivery, and child twin were found to be the determinant factors of perinatal mortality in both 2011 and 2016 EDHS. In this study, we found that perinatal mortality variation across regions has decreased from 2011 to 2016 surveys which shows the promising progress of health intervention in the country.

Background Understanding the behaviour of local malaria vectors is essential as effectiveness of the commonly used vector-targeted malaria control tools heavily relies on behaviour of the major malaria vectors. This study was conducted to determine species composition, biting behaviour, host preference and infectivity of anopheline mosquitoes, and assess utilization of insecticide-treated nets (ITNs) in a low transmission setting in Southwest Ethiopia. Methods Adult anopheline mosquitoes were collected using human landing catches (HLCs), Centers for Disease Control and Prevention (CDC) light traps (LTs) and Pyrethrum Spray Catches (PSCs) from June 2016 to May 2018 in Kishe, Jimma Zone, Southwest Ethiopia. The anopheline mosquitoes were morphologically identified. Moreover, sub-sample of An. gambiae s.l. was identified to species using polymerase chain reaction (PCR). Circum-sporozoite proteins (CSPs) and blood meal sources of the anopheline mosquitoes were tested using enzyme-linked immunosorbent assay (ELISA). In addition, a cross-sectional survey was conducted to assess ITN utilization by the inhabitants. Results A total of 3659 anopheline mosquitoes comprising An. coustani complex (84.4%), An. gambiae s.l. (11.3%), and An. pharoensis and An. squamosus comprising less than 5% were collected. The anopheline mosquitoes showed marked outdoor (67%) and early evening (63%) biting behaviour. An. coustani complex and An. gambiae s.l. were predominantly zoophilic and anthropophilic, respectively. None of the sampled anopheline were CSP-positive. Most of the households (97.8%) owned at least one ITN, with modest usage by the inhabitants (73.4%). ITN usage was significantly higher among under-five children (AOR = 7.9, 95% CI: 4.41–14.03), household heads and spouses (AOR = 4.8, 95% CI: 3.0–7.59), those with sufficient access to ITNs (AOR = 1.8, 95% CI: 1.39–2.35), and who were not utilizing alternative mosquito repellents (AOR = 2.2, 95% CI: 1.58–2.99). Conclusion The anopheline mosquito species exhibited predominantly outdoor and early evening biting activity. Household ITN coverage was high with slight gap in usage. Vector control interventions should target outdoor and early biting vectors to further suppress the local mosquito population. Moreover, sensitization of the community on consistent use of ITNs is required.

BackgroundDental caries are a significant public health problem. It is a disease with multifactorial causes. In Sub-Sahara Africa, Ethiopia is one of the countries with a high record of dental caries. This study was to determine the risk factors affecting dental caries using both Bayesian and classical approaches.MethodsThe study design was a retrospective cohort study in the period of March 2009 to March 2013 dental caries patients Hawassa Haik Poly Higher Clinic. The Bayesian logistic regression procedure was adapted to make inference about the parameters of a logistic regression model. The purpose of this method was generating the posterior distribution of the unknown parameters given both the data and some prior density for the unknown parameters.ResultsFrom this study the prevalence of natural dental caries was 87% and non-natural dental caries were 13%. The age group of 18–25 was higher prevalence of dental caries than the other age groups. From Bayesian logistic regression, we found out that rural patients, do not clean their teeth, patients from SNNPR and age group 18–25 are statistically significant. The finding from the Bayesian statistics approach is getting popular in data analysis than classical statistics because the technique is more robust and precise.ConclusionsBayesian approach was found to be better than classical method as the value of the standard errors in Bayesian approaches is smaller than that of classical logistic regression. The Bayesian credible interval is smaller than the length of the confidence interval for all significant risk factors. Age, sex, place of residence, region and habit of cleaning teeth was found to have a significant effect on dental caries patients.

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Background Cholera is a diarrheal disease caused by infection of the intestine with the gram-negative bacteria Vibrio cholera. It is caused by the ingestion of food or water and infected all age groups. This study aimed at identifying risk factors associated with cholera disease in Ethiopia using the Bayesian hierarchical model. Methods The study was conducted in Ethiopia across regions and this study used secondary data obtained from the Ethiopian public health institute. Latent Gaussian models were used in this study; which is a group of models that contains most statistical models used in practice. The posterior marginal distribution of the Latent Gaussian models with different priors is determined by R-Integrated Nested Laplace Approximation. Results There were 2790 cholera patients in Ethiopia across the regions. There were 81.61% of patients are survived from cholera outbreak disease and the rest 18.39% have died. There was 39% variation across the region in Ethiopia. Latent Gaussian models including random and fixed effects with standard priors were the best model to fit the data based on deviance. The odds of surviving from cholera outbreak disease for inpatient status are 0.609 times less than the outpatient status. Conclusions The authors conclude that the fitted latent Gaussian models indicate the predictor variables; admission status, aged between 15 and 44, another sick person in a family, dehydration status, oral rehydration salt, intravenous, and antibiotics were significantly associated with cholera outbreak disease.