Seyifemickael A Yilema | University of Pretoria (original) (raw)

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Papers by Seyifemickael A Yilema

Background Hypertension is a common, long-term condition that tends to be associated with age and... more Background Hypertension is a common, long-term condition that tends to be associated with age and can lead to significant cardiovascular complications. This study aimed to identify factors influencing the longitudinal Pulse Pressure of hypertensive patients treated at Assosa General Hospital (AGH), Western Ethiopia. Methods A retrospective study design was conducted from 325 randomly selected HTN patients in the outpatient department (OPD) clinic at AGH during the follow-up period from January 2022 to January 2024. The analysis included exploratory data analysis and the application of a linear mixed model. This model was used to analyze the longitudinally measured pulse pressure in patients with hypertension. The appropriate variance-covariance structure chosen for this analysis was the unstructured (UN) format. Result Among the 325 patients included in the study, 51.5% were female, and 54.2% were from urban areas. The variables: Age (p-value < 0.0001), Urban (p-value = 0.012), FHHTN (p-value < 0.0238), Stage-I HTN (p-value = 0.0403), Stage-II HTN (p-value = 0.0022), DM (p-value < 0.0001), CKD (p-value < 0.0001), Smoking (p-value < 0.0001), Enalapril + Nifedipine (p-value = 0.0249), and follow-up time (p-value < 0.0001) were significant factors for the progression of pulse pressure. Conclusion The profile plot showed that the patient’s pulse pressure decreases slowly as follow-up time increases. Age, Residence, FHHTN, DM, CKD, Smoking status, and Stages of HTN were positively associated with pulse pressure, whereas Treatment type and follow-up time were negatively associated with pulse pressure. So, Healthcare providers should prioritize addressing the modifiable risk factors mentioned above to help mitigate the progression of blood pressure specifically pulse pressure in hypertensive patients.

HIV is a worldwide social and health pandemic that poses a significant problem. This study contri... more HIV is a worldwide social and health pandemic that poses a significant problem. This study contributes to the 2030 global agenda of reducing HIV prevalence. The study analyzed HIV prevalence using the 2016 Ethiopian Demographic and Health Survey data. The study included men aged 15–54 years and women aged 15–49 years who responded to questions about HIV tests. A generalized geo-additive model (GAM) was fitted to HIV data using nonparametric smooth terms for geolocations. Two smoothing techniques were used in GAMs to evaluate spatial disparities and the probable effects of variables on HIV risk. There were certain areas in Ethiopia that were identified as hot spot zones for HIV, including Nuer and Agnuak in Gambella, West Wollega and Illubabor in Oromia, Benchi Maji and Shaka in SNNPR, Awsi, Fantana, Kilbet, and Gabi in the Afar region, Shinilie of the Somalia region, North and South Wollo, Oromia special zones of the Amhara region, Central Ethiopia, and Addis Ababa city. On the other hand, the eastern parts of Ethiopia, particularly most zones in the Somalia region, were identified as cold spot zones with the lowest HIV odds ratio. The odds of HIV+ were higher for those who reside in rural areas than in urban areas. Furthermore, people who have STIs, who used contraceptive methods, and who learned at the secondary level of education were more likely to be infected with HIV. After adjusting for confounding variables, the results indicated that there are substantially significant spatial variations in HIV prevalence across Ethiopian zones. These results provide essential information to strategically target geographic areas to allocate resources and policy interventions at zonal level administrations.

Sample surveys are extensively used to provide reliable direct estimates for large areas or domai... more Sample surveys are extensively used to provide reliable direct estimates for large areas or domains with enough
sample sizes at national and regional levels. However, zones are unplanned domains by the Demographic and Health
Survey (DHS) program and need more sample sizes to produce direct survey estimates with adequate precision. Conducting surveys in small areas (like zones) is too expensive and time-consuming, making it unfeasible for developing
countries like Ethiopia. Therefore, this study aims to use the Hierarchical Bayes (HB) Small Area Estimation (SAE) model
to estimate the Community-Based Health Insurance (CBHI) coverage at the zone levels in Ethiopia. To achieve this, we
combined the 2019 Ethiopia Mini-Demographic and Health Survey (EMDHS) data with the 2007 population census
data. SAE has addressed the challenge of producing reliable parameter estimates for small or even zero sample sizes
across Ethiopian zones by utilizing auxiliary information from the population census. The results show that modelbased estimates generated by the SAE approach are more accurate than direct survey estimates of CBHI. A map
of CBHI scheme coverage was also used to visualize the spatial variation in the distribution of CBHI scheme coverage. From the CBHI scheme coverage map, we noticed notable variations in CBHI scheme coverage across Ethiopian
zones. Additionally, this research identifed areas with high and low CBHI scheme coverage to improve decisionmaking and increase coverage in Ethiopia. One of the novelties of this paper is estimating the non-sampled zones;
therefore, the policymakers will give equal attention similar to the sampled zones

Background Sub‑Saharan Africa (sSA) continues to rank among the regions in the world with the hig... more Background Sub‑Saharan Africa (sSA) continues to rank among the regions in the world with the highest rates
of maternal mortality and the lowest rates of utilization of maternal health care. The risk of death for women in sSA
is 268 times higher than that of women in high‑income nations. Adequate antenatal care (ANC) services utiliza‑
tion is essential to the mother’s and the baby’s survival and well‑being. This study aimed to identify both individual
and community‑level factors associated with adequate antenatal care services utilization in sSA.
Method We used data from the most recent Health and Demographic Surveys (DHS), which were carried
out between 2012 and 2022 in 33 sSA countries. A total of 240,792 women were included in this study. The two‑level
mixed‑effects logistic regression model was used to identify the individual and community‑level factors associated
with the use of adequate ANC service.
Results The pooled prevalence of adequate ANC service utilization in sSA was 55.48% (95% CI: 55.28–55.68). The
study showed that secondary and above‑educated women (AOR = 2.13, 95% CI 2.07–2.19, secondary and above‑edu‑
cated husbands (AOR = 1.55, 95% CI 1.51–1.60), rich women AOR = 1.26, 95% CI 1.24–1.29), women 35–49 years of age
(AOR = 1.36, 95% CI 1.32–1.41) and distance to a health facility is not a big problem (AOR = 1.13; 95% CI 1.11–1.16)
was significantly and positively correlated with the use of adequate ANC services. However, rural women (AOR = 0.80;
95% CI 0.78–0.82), not having mass media access (AOR = 0.74, 95% CI 0.72–0.75), 5 and above birth order (AOR = 0.73,
95% CI 0.68–0.78) were significantly and negatively correlated with the use of adequate ANC services. Additionally,
the random effects model showed that variables at the community and individual levels were responsible for approxi‑
mately 62.60% of the variation in the use of adequate ANC services.
Conclusion The sSA countries had a low prevalence of adequate utilization of ANC with a significant variation
among countries. Moreover, public health initiatives should focus on rural women, poor women, and uneducated
women to enhance maternal health services utilization. Furthermore, policies and programs that address cluster vari‑
ations in the utilization of adequate ANC services must be developed, and their implementation must be vigorously
pursued.

e mean ow of direct survey estimates is mainly concerning the sample adequacy ful llment unless i... more e mean ow of direct survey estimates is mainly concerning the sample adequacy ful llment unless it has been produced large variance estimates, and therefore, the small area estimations are developed to manage this aw of the path. Small area estimation improved the direct survey estimates by borrowing strength from the census data and at the same time by using historical data from consecutive surveys. In this paper, we applied the spatiotemporal Fay-Herriot (STFH) model for producing fairly reliable disaggregate-level estimates of undernutrition indicators across all zones. e STFH model is an appropriately tted model to the undernutrition data since it has the lowest information criteria (IC) value. e spatiotemporal estimates improved both the direct and spatial estimates of undernutrition under the FH model and have brought e ciency gain in the percent coe cient of variation (CV). ese results may provide useful information to the government's planners, policymakers, and legislative organs for e ective policy formulation and budget allocation in all zones.

PLOS ONE

Introduction Community-based health insurance (CBHI) is a type of volunteer health insurance tha... more Introduction
Community-based health insurance (CBHI) is a type of volunteer health insurance that has
been adopted all over the world in which people of the community pool funds to protect
themselves from the high costs of seeking medical care and treatment for the disease. In
Ethiopia, healthcare services are underutilized due to a lack of resources in the healthcare
system. The study aims to identify the individual and community level factors associated
with community-based health insurance enrollment of households in Ethiopia.
Methods
Data from the Ethiopian mini demographic and health survey 2019 were used to identify factors associated with community-based health insurance enrollment of households in Ethiopia. Multilevel logistic regression analysis was used on a nationally representative sample of
8,663 households nested within 305 communities, considering the data’s layered structure.
We used a p-value<0.05 with a 95% confidence interval for the results.
Result
The prevalence of community-based health insurance enrollment in Ethiopia was 20.2%.
The enrollment rate of households in the scheme was high in both Amhara (57.9), and
Tigray (57.9%) regions and low (3.0%) in the Afar region. At the individual level; the age of
household heads, number of children 5 and under, number of household members, has
land for agriculture, has a mobile telephone, receiving cash of food from the safety Net Program, Owning livestock, and herds of farm animals, wealth index, and at the community
level; the region had a significant association with community-based health insurance
enrollment.
Conclusion
Both individual and community-level characteristics were significant predictors of community-based health insurance enrollment in households. Furthermore, the ministry of health,
health bureaus, and other concerning bodies prioritize clusters with low health insurance

PLOS ONE