Background: The maternal mortality rate in poor nations remains unacceptably high. The purpose of this study was to identify factors associated with institutional delivery usage. Methods: The data came from the Ethiopian mini demographic and health survey, which was conducted in 2019. This study comprised 3978 women of reproductive age who had given birth within the previous 5 years. To uncover significantly linked parameters associated with institutional delivery, we used a multilevel logistic regression model. Statistical significance was declared at p < 0.05, and we assessed the strength of association using adjusted odds ratios with 95% confidence intervals. Results: More than half of the women (53.67%) among 3978 women with last birth had their babies delivered in a health facility. In the multilevel logistic regression analysis, women in age group 45–49 (AOR = 2.43, 95% CI: 1.280, 4.591), primary educational level (AOR = 2.21, 95% CI: 1.864, 2.625, secondary and above education level (AOR = 6.37, 95% CI: 4.600, 8.837), being Muslim (AOR = 2.57, 95% CI: 1.245, 2.166), women who visited ANC service four up to seven times (AOR = 2.75, 95% CI: 2.175, 3.473), women visited ANC service eight times and above (AOR = 3.295% CI: 1.685, 6.050), women who reside in middle wealth index (AOR = 1.57, 95% CI: 1.273, 1.950), and rich wealth index (AOR = 3.43, 95% CI: 2.782, 4.225) were more likely to give birth at health institution compared to their counterparts. Furthermore, women being in rural area (AOR = 0.34, 95% CI:- 0.283, 0.474) and protestant women (AOR = 0.1.57, 95% CI: 0.479, 0.852) were less likely to deliver at health institution. Conclusions: Ethiopia still has a low level of institutionalized delivery. Institutional delivery in Ethiopia should be improved through context-specific and personalized programs, such as educating women and enhancing access to ANC services.

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Background: Maternal health has become a global public health issue as a result of the fact that maternal health care issuer utilization can save the lives of tens of thousands of women in the reproductive age group. Objectives: The purpose of this study was to determine how often Maternal Health Services were used in the Sheka zone of southwest Ethiopia. Study Design: Sheka Southwest was the site of the cross-sectional investigation. Method: A total of 1779 observed samples were selected from the Sheka area in southwest Ethiopia using a simple random selection method. In the version of binary logistic regression, the impact of objects on maternal fitness care carrier utilization is estimated using a variant of logistic regression. Results: From a total of 1779 Women in Fertility age responses, 917 (51.5%) of women had at least four ANC visits, while 862 (48.5%) had fewer than four ANC visits during their final pregnancy, and 841 (47.3%) of women had delivered their baby at a health facility. 938 (52.7%) of women gave birth at home, and 803 (45.1%) of women had missed at least one postnatal care appointment in the previous six weeks. Despite the fact that 976 women (54.9%) had received within the first six weeks, you should seek postnatal care at the very least. ANC, institutional delivery, and PNC were all used 51.5, 52.7, and 54.9% of the time, respectively. The use of the ANC Service has become inextricably linked to women's education. When compared to women with no training, high school and above-knowledgeable women (AOR = 1.672, 95% CI = 1.179-2.373) are substantially more likely to apply for ANC Service. PNC Service has been inextricably linked to women's education. When compared to women with no training, elementary women (AOR = 1.587, 95% CI = 1.205-2.091) are substantially more likely to apply to PNC Service. Conclusion: Within the studied area, the use of maternal health care services is much below the national goal. The most important predictors of maternal fitness care carrier use are maternal training status, wealth status, work status, number of children, parity, fertility risk, and marital status. Providing information and instruction to women about the ideal family, maternal health care provider use, and the use of various fitness training strategies should be addressed.

Background. Glaucoma is one of the most frequent vision-threatening eye diseases. It is frequently associated with excessive intraocular pressure (IOP), which can cause vision loss and damaged optic nerves. The main objective of this study was to model time to blindness of glaucoma patients by using appropriate statistical models. Study Design. A Retrospective Community-Based Longitudinal Study design was applied. Materials and Procedures. The data were obtained from Ophthalmology Department of JUSH from the period of January 2016 to August 2020. The glaucoma patient’s information was extracted from the patient card and 321 samples were included in the study. To discover the factors that affect time to blindness of glaucoma patients’, researchers used the Accelerated Failure Time (AFT) model. Results. 81.3 percent of the 321 glaucoma patients were blind. Unilaterally and bilaterally blinded female and male glaucoma patients were 24.92 and 56.38%, respectively. After glaucoma disease was confirmed, the median time to the blindness of both eyes and one eye was 12 months. The multivariable log-logistic accelerated failure-time model fits the glaucoma patient’s time to blind dataset well. The result showed that the chance of blindness of glaucoma patients who have absolute stage of glaucoma, medium duration of diagnosis, long duration of diagnosis, and IOP greater than 21 mmHg were high with parameters (ϕ = 2.425, p value = 0.049, 95% CI [2.249, 2.601]), (ϕ = 1.505, p value = 0.001, 95% CI [0.228, 0.589]), (ϕ = 3.037, p value = 0.001, 95% C.I [2.850, 3.22]) and (ϕ 0.851, p value = 0.034, 95% C.I [0.702, 0.999]), respectively. Conclusion. The multivariable log-logistic accelerated failure time model evaluates the prognostic factors of time to blindness of glaucoma patients. Under this finding, duration of diagnosis, IOP, and stage of glaucoma were a key determinant factors of time to blindness of glaucoma patients’. Finally, the log-logistic accelerated failure-time model was the best-fitted parametric model based on AIC and BIC values.