Background. Diarrheal disease is a major public health problem among under-five children globally. In Ethiopia, it is the second cause of hospital admission and death among children under five years. Objectives. To assess the prevalence of diarrhea, feeding practice, and associated factors among children under five years in Bereh District, Oromia Special Zone Surrounding Finfine, Ethiopia. Methods. A community-based cross-sectional study was conducted among children less than 5 years old in Bereh District from May 15 to 29, 2021. A systematic random sampling technique was used to select a total of 455 study participants. Descriptive statistics were used to measure the prevalence of diarrhea as well as to summarize other study variables. A binary logistic regression model with an adjusted odds ratio and a 95% confidence interval (CI) was used to declare the associated factors with childhood diarrhea. Results. The prevalence of diarrhea was 17.3% in the past 15 days preceding the study period. About 53.4% of the mothers/caregivers were engaged in poor child feeding practices. Age of children [ AOR = 9.146 , 95% CI (2.055, 40.707)], birth order [ AOR = 0.137 , 95% CI (0.057, 0.329)], total family size [AOR: 5.042, 95% CI (2.326, 10.931)], not EBF [AOR: 4.723, 95% CI (1.166, 19.134)], prepare child foods separately [AOR: 0.252, 95% CI (0.091, 0.701)], feeding child immediately after cooking, handwashing method, and source of drinking water were significantly associated with under-five diarrhea. Conclusions. The prevalence of diarrhea among children under five is high. More than half of the participants were engaged in poor IYCF practice. Action targeting the factors associated with diarrhea should be taken to improve under-five child’s health.
Background. Recovery from type 2 diabetes is frequently recurrent, as a single patient may recover from more than one over time. The goal of this study was to know the recurrent event (time to recovery) and associated factors of type 2 diabetes in Adama General Hospital, Ethiopia, by comparing shared lognormal frailty and Cox-PH models. Methods. A retrospective analysis of 302 type 2 diabetic patients (01, 2011–01, and 2016) was considered. Descriptive statistics were used to summarize the study variables. The standard Cox-proportional hazards model and a shared lognormal frailty model have been compared. The latter model with a 95% significance level was fitted, variables with P value < 0. 05 were considered significant, and the adjusted hazard ratio has been used to measure the strength of the risk. Results. About 56.6% of the patients recovered. The average recovery time was 33.53 (standard deviation, 20.404 ) weeks. Gender (adjusted HR = 1.168, 95% CI = (0.93, 1.46), P < 0.05 ), family history (adjusted HR = 0.765, 95% CI = (0.59, 0.99), P < 0.05 ), cholesterol level (adjusted HR = 0.738, 95% CI = (0.57, 0.96), P < 0.05 ), alcohol use (adjusted HR = 0.698, 95% CI = (0.53, 0.92), P < 0.05 ), and smoking cigarette (adjusted HR = 0.674, 95% CI = (0.51, 0.89), P < 0.05 ) were statistically significant. The estimated frailty term’s variance was 0.426 ( P value = 0. 028 ). Also, the author presents a comparison study for the same data by using a model selection criterion and suggests a better model (shared lognormal frailty model). Conclusion. Finally, the median recovery time was 30 weeks. Female patients had a better chance of recovery than male patients. A shared lognormal frailty model outperformed the Cox-PH model in fitting the data and controlling event interdependence. There was risk heterogeneity among patients. Positive family history, high cholesterol level, alcohol use, and smoking have an inverse relationship with the overall likelihood of the patients’ recovery time. Therefore, future improvement measures against type 2 DM recovery should take all events (for example, the first, second, and third recovery in this study) and these identified factors into account.
Introduction. Analyzing the effect of COVID-19 is an important issue in agricultural sectors. However, such analysis requires a complex hierarchical statistical model. Rapid spread of the COVID-19 pandemic has disrupted the world’s production and productivity in many sectors. Among those sectors, the agricultural sector is highly affected. The Bale zone in the larger extent and Sinana district, in particular, is one of the potential agricultural areas in the Oromia regional state, Ethiopia where agriculture is the major sector in supporting the livelihood of thousands of subsistence farmers in the area as well as the country at large. Research Methodology. This study involved primary data collected from the farmers in the Sinana district during the period 2020–2021. A total of 991 farmers were selected from the entire 22 kebeles in the district. The data were analyzed using multilevel binary logistic random intercept regression models with maximum-likelihood parameter estimation. Results. Of the 991 farmers, 549 (55.4%) responded that COVID-19 has brought only challenges in their agricultural production and 311 (31.4%) responded both challenges and opportunities. About 632 (63.8%) of the farmers said that there was wastage of products such as milk, dairy, fruits, and vegetables. Three hundred twenty-eight (33.1%) of the participants obtained modernization in their agricultural production system like use of tractors and irrigation systems. According to the model results, farmer’s sex, age, educational level, family size, farmland size, types of effect, aggravation in food insecurity, input delay, lack of workers, slowdown of service, falling in income, modernization in the system of production, wastage of product, and types of wasted products were identified as significant factors. About 8% of the total variability in the effect of COVID-19 is due to differences across kebeles (ICC = 0.08, P value ≤0.05), and the remaining is due to individual differences. Conclusion. This study further demonstrated the potential of a hierarchical model for the study of COVID-19 effect variation within and between the kebeles. The majority, about 92% variation in the effect, is due to the disparity of individuals (farmers). The farmers with large family sizes and high capacity to produce and who were females were negatively related to the effect of COVID-19 in agricultural production.
Background: The Guji-Gedeo conflict has gradually become the main cause of displacement in the Gedeb district, with 274,548 internally displaced persons (IDPs). Malnutrition is exacerbated in areas affected by conflict. Children affected by the conflict face an imbalanced burden of malnutrition and health problems. The purpose of the current study was to identify determinant factors associated with the nutritional status of the children (aged 6 to 59 months) who returned to the Gedeb District after being internally displaced in Guji-Gedio.Methodology: A cross-sectional study involving 6-59 months aged children who returned to the Gedeb district after being internally displaced in Guji-Gedio was conducted from December 2020- to February 2020. A bayesian binary logistic parametric regression model was applied to model the effects of selected demographic, socioeconomic, health, and environmental factors. An inference was made using the Markov chain Monte Carlo (MCMC) approach.Results: Malnutrition was found to be prevalent in Gedeb district at 45.9 percent. The covariates such as sex: female (OR: 1.358, CI : 0.584, 3.158), birth Interval: less than 24 month (OR: 3.73, CI: 0.6, 22.9), 24 – 47(OR: 2.12, CI: 0.34, 13.263), birth order: 4 – 5(OR: 0.802, CI: 0.19, 3.338), 6 and above (OR: 1.9, CI: 0.479, 7.675), mother's education level: read and write(OR: 0.490, CI: 0.072, 3.346), primary(OR: 0.266, CI: 0.043, 1.664), secondary and above(OR: 0.25, CI: 0.025, 2.45), place of residence: urban(OR:0.399, CI: 0.098, 1.631),toilet: improve(OR: 0.84, CI: 0.265, 2.66 ), mother body mass index: normal(OR:0.777, CI: 0.332, 1.81 ) and diarrhea: yes(OR: 1.2, CI: 0.218, 2.354) were the most important determinants of children nutritional status in Gedeb district. Conclusion: The overall prevalence of malnutrition in Gedeb district is about 46%. Covariates such as sex, birth interval, birth order, mother's education level, place of residence, toilet, mother's body mass index, and diarrhea were statistically related to malnutrition. Creating awareness in society related to those factors associated with child malnutrition should be further motivated. Also, to reduce childhood malnutrition, due emphasis should be given to improving the knowledge and practice of parents on appropriate young child feeding practices and frequent growth monitoring together with appropriate and timely interventions.
Introduction: Anemia is a major public health problem, affecting more than 56 million women worldwide. During pregnancy, hemoglobin concentrations in venous blood below 11 grams per deciliter have significant adverse effects on the health of pregnant women. The main purpose of this study was to investigate the anemia status of the participants and the factors that lead to anemia. Methods: Data for this study were obtained from the 2016 Ethiopian Demographic Health Survey (January 18, 2016, to June 27, 2016). A total of 1053 pregnant women were included in the analysis. The risk factors for anemia status were analyzed using a partial-proportional odds model. Results: The study included 1053 pregnant women, with 32, 214, and 395 suffering from severe, moderate, and mild anemia, respectively. Somalia had the highest proportion of severely anemic people, while Tigray had the lowest. The effect changing in different regions of the sample had various effects on the outcome variable. For example, in the Somali region, the probability of subjects with severe anemia increased by 0.027 (AMPE= 0.027, P = 0.015) percentage points when compared to their counterparts. The effect of changing iron-taking status by one percent on average across the sample decreased by 1.6% (AMPE = -0.016, P= 0.001), 3.7% (AMPE = -0.037, P = 0.001), and 3% (AMPE = -0.030, P = 0.003) points, respectively, for participants in the severe, moderate, and mild classes. The effect of changing place of residence and parity decreased for those in the non-anemic group, but it increased for the wealth index (richest household). Anemia decreased with higher education level [primary: (AMPE = 0.032, P = 0.002), secondary: (AMPE = 0.069, P = 0.025), higher: (AMPE = 0.176, P = 0.000)]. Conclusion: Finally, the authors concluded that iron intake, educational status, wealth index (richest households), place of residence, parity, and selected regions have been identified as prognostic factors for anemia status in pregnant women aged 15 to 49 years. Therefore, action on these predictors is needed to improve anemia among pregnant women in Ethiopia. Furthermore, AMPE should be used with greater motivation to interpret the logistic regression results.
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