Diabetes mellitus (DM) is a public health problem in developing as well as developed nations. DM leads to many complications that are associated with higher morbidity and mortality worldwide. Therefore, the current study was planned to assess the prevalence and risk factors of type-2 DM in Ethiopian population. Six electronic databases such as: PubMed, Scopus, Hinari, Web of science, Google Scholar, and African Journals Online were searched for studies published in English up December 30, 2020. Newcastle–Ottawa Scale was used for quality assessment of the included studies. The data was extracted by Microsoft excel and analyzed through Stata version 16 software. The random effect meta-regression analysis was computed at 95% CI to assess the pooled prevalence and risk factors of type-2 DM. Forty observational studies were included in this systematic review and meta-analysis. The pooled prevalence of DM in Ethiopia was 6.5% (95% CI (5.8, 7.3)). The sub-group analysis revealed that the highest prevalence of DM was found in Dire Dawa city administration (14%), and the lowest prevalence was observed in Tigray region (2%). The pooled prevalence of DM was higher (8%) in studies conducted in health facility. Factors like: Age ≥ 40 years ((Adjusted Odds Ratio (AOR): 1.91 (95% CI: 1.05, 3.49)), Illiterate (AOR: 2.74 (95% CI: 1.18, 6.34)), Cigarette smoking (AOR: 1.97 (95% CI: 1.17, 3.32)), Body mass index (BMI) ≥ 25 kg/m2 (AOR: 2.01 (95 CI: 1.46, 2.27)), family history of DM (AOR: 6.14 (95% CI: 2.80, 13.46)), history of hypertension (AOR: 3.00 (95% CI: 1.13, 7.95)) and physical inactivity (AOR: 5.79 (95% CI: 2.12, 15.77)) were significantly associated with type-2 DM in Ethiopian population. In this review, the prevalence of type-2 DM was high. Factors like: Older age, illiteracy, cigarette smoking, MBI ≥ 25, family history of DM, history of hypertension and physical inactivity were an identified risk factors of type-2 DM. Therefore, health education and promotion will be warranted. Further, large scale prospective studies will be recommended to address possible risk factors of type-2 DM in Ethiopian population.
Background: TB/HIV co-infection is a major public health problem in many parts of the world. But the prevalence of co-infection was varies among countries. This study was designed to assess prevalence of TB/HIV co-infection and to determine its factors. Methods: A retrospective study was done among HIV-positive patients at Hiwot Fana hospital from December, 2014 to 2018. The study participants were selected by simple random sampling. Patients with incomplete chart reviews were exclud- ed and demographic, clinical and laboratory information were analyzed using SPSS and STATA. Uni-vitiate and bivariate logistic regressions were applied. Results: Five hundred fourteen patients were enrolled in this study. Of these, 187(37.4%) had TB. Bivariate logistic analysis showed that HIV patients with regards to marital status[AOR = 2.6; 95%CI = 1.19- 2.89] , education status [AOR = 3.74; 95%CI = 2.47–5.66], weight less than 50kg [AOR = 2.54; 95% CI = 1.35 – 4.81], CD4 level < 200cells/mm3 [AOR = 4.57; 95%CI = 2.38– 6.86] and patient who were at WHO clinical stage III [AOR = 7.8; 95%CI = 5.15 – 8.55] were significantly associated with TB/HIV co-infection. Conclusion: The prevalence of TB among HIV patients was high and predicted by marital, education status, weight, CD4 cell count and WHO clinical stage III. Keywords: Prevalence; TB; HIV; co-infection; Harari Region.
Diabetes mellitus is a group of metabolic chronic diseases characterized by high blood sugar levels with multi-system complications. The objective of this study was to assess the risk factors for developing type-2 diabetes mellitus over time in their random blood sugar and to obtain better predictive model for type 2 diabetes patients' random blood sugar (RBS) level in the University of Gondar Comprehensive Specialized Hospital. A retrospective cohort study with a total of 330 diabetic patients who have been active in the follow-up treatment for at least 3 times in three month interval in the hospital from February 2014 to February 2016 was conducted. Linear mixed effects model for longitudinal data were employed to measure the changes in RBS level. The results revealed that the linear distribution trend in the mean RBS level accounted for 79% of the variability in the data and the mean RBS level decreased over time. Age, residence, family history, alcohol intake, dietary type, BMI, treatment, exercise and education status were the significant factors for the change in mean RBS level of the diabetes patients over time. The study also confirmed that among the factors of RBS level included in the study, meat dietary type, patients who do not perform exercise, and body mass index (BMI) were positively correlated with the RBS level while the rest were negatively correlated. It was significant for the patients to do daily self-care activities to prevent long term complications. The government should also contribute to the education of communities to spread awareness creation and enhance prevention mechanisms of diabetes.
Heart failure is a complex, clinical syndrome of signs and symptoms that are caused by defects in cardiac structure, function, or both, resulting in impairment of peripheral circulation and organ oxygenation. It is a staggering clinical and public health problem and the study of the epidemiology on heart failure demonstrated that heart failure is associated with significant mortality, morbidity, and health care expenditures. It is a disorder in which the heart pumps blood inadequately which lead to reduced blood flow, congestion of blood in the veins and lungs, and other changes that may further weaken the heart. The aim of this study is to assess the relative contribution of the various causes of heart failure and its prevalence over time which helps policy makers as a tool for decision making in allocating resources and to analysis the association of heart failure with related factors. To a chive this objective of the study a retrospective cohort study based on data from the heart failure patients at Felege Hiwot referral hospital from 2013 to 2017. The analysis revealed that the prevalence of heart failure was decreased over time when we compared patient who had taken treatment with patients who does not take any treatment. Hypertension, diabetes mellitus, anemia, and infection were highly correlated with heart failure and had significant effect on heart failure (p<0.05) and treatments are the basic way to manage heart failure and to recover from this disease. About 71% of patients who died from heart failure were died within four years of diagnosis.
Introduction Malaria is a severe health threat in the World, mainly in Africa. It is the major cause of health problems in which the risk of morbidity and mortality associated with malaria cases are characterized by spatial variations across the county. This study aimed to investigate the spatial patterns and predictors of malaria distribution in Ethiopia. Methods A weighted sample of 15,239 individuals with rapid diagnosis test obtained from the Central Statistical Agency and Ethiopia malaria indicator survey of 2015. Global Moran’s I and Moran scatter plots were used in determining the distribution of malaria cases, whereas the local Moran’s I statistic was used in identifying exposed areas. The auto logistics spatial binary regression model was used to investigate the predictors of malaria. Results The final auto logistics regression model was reported that male clients had a positive significant effect on malaria cases as compared to female clients [AOR = 2.401, 95% CI: (2.125–2.713) ]. The distribution of malaria across the regions was different. The highest incidence of malaria was found in Gambela [AOR = 52.55, 95%CI: (40.54–68.12)] followed by Beneshangul [AOR = 34.95, 95%CI: (27.159–44.963)]. Similarly, individuals in Amhara [AOR = 0.243, 95% CI:(0.195–0.303], Oromiya [AOR = 0.197, 955 CI: (0.158–0.244)], Dire Dawa [AOR = 0.064, 95%CI(0.049–0.082)], Addis Ababa[AOR = 0.057,95%CI:(0.044–0.075)], Somali[AOR = 0.077,95%CI:(0.059–0.097)], SNNPR[OR = 0.329, 95%CI: (0.261–0.413)] and Harari [AOR = 0.256, 95%CI:(0.201–0.325)] were less likely to had low incidence of malaria as compared with Tigray. Furthermore, for one meter increase in altitude, the odds of positive rapid diagnostic test (RDT) decreases by 1.6% [AOR = 0.984, 95% CI: (0.984–0.984)]. The use of a shared toilet facility was found as a protective factor for malaria in Ethiopia [AOR = 1.671, 95% CI: (1.504–1.854)]. The spatial autocorrelation variable changes the constant from AOR = 0.471 for logistic regression to AOR = 0.164 for auto logistics regression. Conclusions This study found that the incidence of malaria in Ethiopia had a spatial pattern which is associated with socio-economic, demographic, and geographic risk factors. Spatial clustering of malaria cases had occurred in all regions, and the risk of clustering was different across the regions. The risk of malaria was found to be higher for those who live in soil floor-type houses as compared to those who lived in cement or ceramics floor type. Similarly, households with thatched, metal and thin, and other roof-type houses have a higher risk of malaria than ceramics tiles roof houses. Moreover, using a protected anti-mosquito net was reducing the risk of malaria incidence.
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