The risk of maternal death in developing countries is projected to be one in 61, while for developed countries it is estimated to be one in 2800. Antenatal care is a protective obstetric health care system aimed at improving the outcome of the pregnant fetus by routine pregnancy monitoring. One of the most important functions of antenatal care is to offer health information and services that can significantly improve the health of women and their infants. 6450 pregnant women from Ethiopian Demographic and Health Survey of 2016 were used to analyze the determinants of the barriers in number of antenatal care service visits among pregnant women in Ethiopia. The data were found to have excess zeros (35%); thus several count data models such as Poisson, Negative Binomial, Zero Inflated Poisson, Zero Inflated Negative Binomial and Hurdle regression models were modeled and fitted. From the exploratory analysis the results showed that among those eligible pregnant women, it was seen that 2240 (34.7%) of them did not visit antenatal care service during their periods of pregnancy months. The visualization of data using scatter plot depicts that all of the variables selected for modeling have an influence on the event of not visiting antenatal care cervices while each of these variables had opposite slope in non-zero number of such events in their respective categories. To select the model which best fits the data, models were compared based on their Akaike information criterion value by using the simulation study. The simulation experiment revealed that models for zero-inflated data such as; Zero Inflated Poisson, Zero Inflated Negative Binomial and Hurdle were models that fitted the data better than the classical models Poisson and Negative Binomial. Each of these zero-inflated models was compared using Voung test and Hurdle model was better fitted the data which was characterized by excess zeros and high variability in the non-zero outcome than any other zero-inflated models. In this study, maternal education, partner education level, age of mothers, religion of mothers and wealth index are major predictors of antenatal care service utilization. Through simulation experiment, it was found that Zero Inflated Poisson, Zero Inflated Negative Binomial and Hurdle models were better fitted zero-inflated data than Poisson and Negative Binomial. Voung test suggests that Hurdle model was better fitted zero-inflated (ZI) data than any other zero inflated models and therefore, it was selected as the best parsimonious model.
Low birth weight (LBW) is a major determinant of morbidity, mortality and disability in infancy and childhood and has a long-term impact on health outcomes in adult life. This study was aimed to model LBW using marginal and generalized linear mixed models as well as identify the potential risk factors of LBW in Ethiopia. Data was taken from the 2011 Ethiopian demographic and health survey, which is a nationally representative survey of children in the 0–59 month age groups. Two model families, generalized estimating equation and alternating logistic regression models from marginal model family, and generalized linear mixed model from cluster specific model family were used for the analysis. The result showed that 34.8% of children were born with LBW. Alternating logistic regression model was best fits the data for population-averaged effects of the given factors on birth weight than generalized estimating equation model. Generalized linear mixed model with two random intercepts was the best model to evaluate within and between regional heterogeneity of birth weight. Both the best-fitted models gave the same conclusion that sex, wealth status, age, antenatal care, marital status, vaccination, anemia and mother education level were the determinant factors of LBW. This study contributes to the understanding of the individual and collective effect of maternal, socio-economic and child related factors influencing infant birth weight in Ethiopia.
Female genital mutilation (FGM), also known as female genital cutting or female circumcision, is one of the deeply rooted traditional practices, in which the external female genital organ is either partially or totally removed for non-medical reasons. In Ethiopia, FGM is widespread across the majority of regions and ethnic groups, having the highest national prevalence that leads them to various complications such as immediate urinary and genital tract infection, pain and hemorrhage, complications in childbirth and social, psychological and sexual complications. This study aimed to model and investigate the potential risk factors of time-to-circumcision of girls in Ethiopia using parametric shared frailty models where regional states of the girls were used as a clustering effect in the models. The data source for the analysis was the 2016 EDHS data collected from January 18, 2016 up to June 27, 2016 from which the survival information of 2930 girls on age at circumcision obtained. The gamma and inverse Gaussian shared frailty distributions with Exponential, Weibull and log-logistic baseline models was employed to analyze risk factors associated with age at circumcision using socio-economic and demographic factors. All the fitted models were compared by using AIC and BIC values from simulation study and actual dataset. The result revealed that about 22.4% of girls were circumcised and 77.6% were not circumcised. The median age at circumcision was 3 years. Based on AIC and BIC values from simulation experiment and graphical evidences, log-logistic model with inverse Gaussian shared frailty distribution preferred when compared with other models for age at circumcision dataset. The clustering effect was significant for modeling the determinants of time-to-circumcision of girls dataset. Based on the result of log-logistic inverse Gaussian shared frailty model, mothers and fathers educational level, place of residence and religion of parents were found to be the most significant determinants of age at circumcision of girls. The estimated acceleration factor for the group of mothers who had secondary and higher educational level were highly prolonged age at circumcision of girls by the factor of ϕ = 3.119 and ϕ = 3.933 respectively. The log-logistic model with inverse Gaussian shared frailty distribution described age at circumcision of girls better than other models and there was heterogeneity between the regions on age at circumcision. Improving parents access to education would be an important way approach for preventing girls' circumcision.
Tuberculosis disease burden remains a fundamental global public health concern for decades. The disease may not uniformly distributed with certain geographical areas recording higher notification rate than others. However, the Ethiopian national TB control program does not provide services based on those areas with the greatest notifications but rather on a uniform strategy. Therefore, this study aimed to assess the spatial distribution and presence of the spatio-temporal clustering of the disease in different geographic settings over 8 years in the East Hararge Zone. A retrospective space-time and spatial analysis were carried out at districts of East Hararghe zone based on a total of 34,564 notified TB cases during the study period. The study identified different case notification rate over districts and clustering effects for the purely spatial and spatiotemporal with different estimated relative risks. The study recommends national tuberculosis control program to give attention to highly observed case notification rates specially Babile, Haramaya and Jarso districs of East Hararge Zone to have effective TB intervention in the study area.
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