Introduction The CD4 + count is used to evaluate the clinical status of HIV-infected patients when deciding whether to initiate ART. To study the progression of HIV-infected patients on ART, CD4 + counts in each individual could be measured repeatedly to monitor the patient's AIDS progression and monitor treatment success. Therefore, this study aimed to identify predictors of CD4 + progression in HIV-positive patients receiving ART at the Debre Berhan Referral Hospital. Methods Retrospective data were collected from 322 HIV-infected patients who started ART in the hospital from September 2013 to February 2019. Exploratory analyses were applied to assess subject-specific and mean differences in terms of patients’ CD4 + progression. A linear mixed model was used as data analysis to account random effects. Results Of the 322 HIV-infected patients considered in the study, 225 (69.88%) were females. The baseline mean CD4 + counts was 335.7 and changed to 408.61 over 7 follow-up years. Moreover, predictors such as patients’ gender (male) (β =-0.7512, p-value = 0.019), age at initiation of ART (β = -0.02705, p-value = 0.047), bedridden functional status of the patients at initiation of ART (β = -0.03365, p-value = 0.021), TDF-3TC-NVP regimen class (β = -0.1474, p-value = 0.031), unmarried patients (β = 0.610, p-value = 0.011), patients’ WHO clinical stage-II (β = -0.402, p-value = 0.047), baseline CD4 count (β = 0.020, p-value = 0.0001) and follow-up time (β = 0.613, p-value = 0.0001) were positively as well as negatively associated and had significant impact on CD4 count progression. Conclusions Patients’ gender, age at initiation of ART, bedridden functional status at ART initiation, TDF-3TC-NVP treatment class, unmarried marital status, WHO clinical stage II, baseline CD4 count and follow-up time was found to be a significant predictor of the progression of a patient's CD4 count. Therefore, HIV-positive patients can be advised to start ART treatment as early as possible. Special guidance and attention is also required, especially in elderly patients, males with bedridden functional status, and late WHO clinical stage patients.
Introduction. Currently, Ethiopia, in particular, the rural areas of Ethiopia, faces high levels of food insecurity. In spite of the fact that there have been many studies on food security, most of them have been conducted in specific national settings. Hence, the determinants of food insecurity should be assessed at the national level. Therefore, this study was primarily aimed to identify the determinant factors of household food insecurity in rural Ethiopia. Method. A cross-sectional Ethiopian socioeconomic survey (ESS) data collected from September 2018 to August 2019 was utilized. A sample of 3115 households was selected from 316 clusters across rural Ethiopia using a two-stage probability sampling technique. To identify the determinants of food insecurity, logistic regression was applied. Results. Among 3,115 households, 50.05% of them were food insecure. Factors such as the household head being aged from 30 to 64 (AOR = 0.786, 95% CI: [0.635, 0.973]), widowed, divorced, or separated (AOR = 1.588, 95%CI: [1.001, 2.518]), literate (AOR = 0.702, 95%CI: [0.590, 0.834]), household aid (AOR = 1.339, 95%CI: [1.089, 1.648]), drought-affected (AOR = 0.640, 95%CI: [0.507, 0.808]), nonagricultural business (AOR = 0.655, 95%CI: [0.472, 0.908]), dependency ratio from 50 to 75% (AOR = 0.680, 95%CI: [0.534, 0.867]), having 6 to 10 livestock (AOR = 0.644, 95%CI: [0.496, 0.836]), and more than 10 livestock (AOR = 0.362, 95% CI: [0.284, 0.461]) were found to be significantly associated with the household’s food insecurity at 5% level of significance. Conclusion. The household head’s age from 30 to 64, being literate, drought-affected, having nonagricultural business, dependency ratio from 50 to 75%, and owning more than 10 livestock have been negatively affecting food insecurity. While supporting households, a “widowed, divorced, or separated” household head has had a positive effect on food insecurity in rural Ethiopia positively influencing food insecurity in rural Ethiopia. Policymakers need to pay special attention to very young and old-aged household heads, adult education, household self-help, livestock improvement, and entrepreneurship while implementing poverty reduction programs.
Objectives Evidences showed that stroke is one of the most leading causes of death worldwide, with approximately 11.9 million new stroke patients occurring each year. Thus, the current study aimed to evaluate survival time of stroke patients and its determinants in Debre Berhan comprehensive specialized hospital. Study design and methods: A retrospective study was conducted on 259 stroke patients enrolled from 1st September 2020 to 1st December 2021. Kaplan-Meier curve and Log-rank test were used. Bivariate and multivariable Cox-PH regression models were also applied at 95% confidence level. Finally, both graphical and Schoenfeld residuals tests were used to the Cox-PH model assumptions. Results The mortality rate of stroke patients was 25.12%, and median survival time was 4.438 months. Female patients were 2.894 times more likely to die than males (AHR = 2.894, 95%CI: 1.574, 5.320). Patient age also suggested that the probability of death increased 1.041-fold for each additional month of patient (AHR = 1.041, 95%CI: 1.017, 1.065). Patients with hypertensive stroke were 2.575 times more likely to die than those without hypertension (AHR = 2.575, 95%CI: 1.295, 5.121). It has been also shown that patients with heart disease are 1. 483 times more likely to die than patients without heart disease (AHR = 1.483, 95%CI: 1.059, 1.972). Conclusion The prevalence of stroke mortality is relatively high. The patient's gender, age, hypertension, and heart disease have been shown to be contributing factors to a reduced survival time of stroke patients. Therefore, stroke patients with hypertension and heart disease, especially women, need special attention.
Currently, around 36% of the rural Ethiopian population is accessing drinking water from unimproved sources and it is unevenly distributed through time and geographic regions. Therefore, this study aimed to analyze the spatiotemporal patterns of unimproved drinking water sources and identify hotspot areas in rural Ethiopia. Ethiopian Socioeconomic Survey (ESS) data obtained from the Central Statistical Agency were used. It was conducted in four waves from 2011 to 2019. A two-stage probability sampling design was applied. The sample of enumeration areas and households were taken as the first and second stages of sampling, respectively. A total of 3912, 3775, 3698, and 3115 sample households with complete information on drinking water sources were taken in each wave of ESS data, respectively. Weighted proportions, autocorrelation (Moran’s “I”) statistic, and hotspot analyses were applied to estimate the prevalence, test the presence of clustering, and identify vulnerable areas with unimproved drinking water sources. The STATA version 14, Excel, and ArcGIS 10.6 were used to manage and analyze data. The proportions of households with unimproved drinking water sources were 0.497, 0.385, 0.298, and 0.363 in consecutive waves of ESS data. The results also revealed the existence of geographical and temporal variations of access to drinking water from unimproved sources, and the most recent vulnerable (hotspot) areas in the borders of the West and East Gojjam zones in the western Amhara region, Zone one in southern Afar region, and Liben, Afder, Shebelle, Korahe, and Nobob zones in Somali region were identified. In conclusion, this study reveals significant geographic inequalities in the use of improved drinking water sources. This may be necessary for policies and coverage targeting the most vulnerable regions. The presented map and analytical approaches can provide a mechanism to monitor future reductions in inequality within countries by reflecting resource allocation priorities.
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