12 research outputs found
Factors Affecting Acceptance of COVID-19 Vaccination in Ethiopia: Evidence from Risk Perception and Behavioral Response Survey, 2021
No full textThe dataset contains risk perception and behavioral response for COVID-19 for population age 18 years and above in Ethiopia.</p
Prevalence of high bloodpressure, hyperglycemia, dyslipidemia, metabolic syndrome and their determinants in Ethiopia: Evidences from the National NCDs STEPS Survey, 2015.
No full textThe prevalence of diabetes, dyslipidemias, and high blood pressure is increasing worldwide especially in low and middle income countries. World Health Organization has emphasized the importance of the assessment of the magnitude of the specific disease in each country. We determined the prevalence and determinant factors of high blood pressure, hyperglycemia, dyslipidemias and metabolic syndrome in Ethiopia. A community based survey was conducted from -April to June 2015 using WHO NCD STEPS instrument version 3.1. 2008. Multistage stratified systemic random sampling was used to select representative samples from 9 regions of the country. A total of 10,260 people aged 15-69 years participated in the study. Blood pressure (BP) was measured for 9788 individuals. A total of 9141 people underwent metabolic screening. The prevalence of raised blood pressure (SBP ≥140 and/or DBP ≥ 90 mmHg) was 15.8% (16.3% in females and 15.5% in males). The prevalence of diabetes mellitus (FBS ≥ 126 mg /dl) including those on medication was 3.2% (3.5% males and 3.0% females). The prevalence of impaired fasting glucose was 9.1% with ADA criteria and 3.8% with WHO criteria. Hypercholesterolemia was found in 5.2%, hypertriglyceridemia in 21.0%, high LDL cholesterol occurred in 14.1% and low HDL cholesterol occurred in 68.7%. The prevalence of metabolic syndrome using IDF definition was 4.8% (8.6% in females and vs. 1.8% in males). Advanced age, urban residence, lack of physical exercise, raised waist circumference, raised waist hip ratio, overweight or obesity, and total blood cholesterol were significantly associated with raised blood pressure (BP) and diabetes mellitus. Increased waist- hip ratio was an independent predictor of raised blood pressure, hyperglycemia and raised total cholesterol. Our study showed significantly high prevalence of raised blood pressure, hyperglycemia and dyslipidemia in Ethiopia. Community based interventions are recommended to control these risk factors
Mean and SD values of total cholesterol, blood glucose, diastolic and systolic blood pressure, Ethiopia NCD steps, 2015.
No full textMean and SD values of total cholesterol, blood glucose, diastolic and systolic blood pressure, Ethiopia NCD steps, 2015.</p
Prevalence of dyslipidemia, WHO STEPS survey, Ethiopia 2015.
No full textPrevalence of dyslipidemia, WHO STEPS survey, Ethiopia 2015.</p
Prevalence of raised blood pressure, hyperglycemia and their determinants, WHO STEPs study, 2015, Ethiopia.
No full textPrevalence of raised blood pressure, hyperglycemia and their determinants, WHO STEPs study, 2015, Ethiopia.</p
Bivariate and multivariate analyses of demographic and clinical risk factors for raised blood pressure, raised blood sugar, raised total cholesterol level, Ethiopia NCD Steps 2015.
No full textBivariate and multivariate analyses of demographic and clinical risk factors for raised blood pressure, raised blood sugar, raised total cholesterol level, Ethiopia NCD Steps 2015.</p
Fasting blood glucose level (WHO/IDF, 2006 vs ADA 2003) by background characteristics, Ethiopia Steps 2015.
No full textFasting blood glucose level (WHO/IDF, 2006 vs ADA 2003) by background characteristics, Ethiopia Steps 2015.</p
Prevalence of raised total cholesterol level and metabolic syndrome, and their determinants WHO STEPS survey, Ethiopia 2015.
No full textPrevalence of raised total cholesterol level and metabolic syndrome, and their determinants WHO STEPS survey, Ethiopia 2015.</p
Progress in health among regions of Ethiopia, 1990-2019 : a subnational country analysis for the Global Burden of Disease Study 2019
No full textAbstract: Background Previous Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) studies have reported national health estimates for Ethiopia. Substantial regional variations in socioeconomic status, population, demography, and access to health care within Ethiopia require comparable estimates at the subnational level. The GBD 2019 Ethiopia subnational analysis aimed to measure the progress and disparities in health across nine regions and two chartered cities. Methods We gathered 1057 distinct data sources for Ethiopia and all regions and cities that included census, demographic surveillance, household surveys, disease registry, health service use, disease notifications, and other data for this analysis. Using all available data sources, we estimated the Socio-demographic Index (SDI), total fertility rate (TFR), life expectancy, years of life lost, years lived with disability, disability-adjusted life-years, and risk-factor-attributable health loss with 95% uncertainty intervals (UIs) for Ethiopia's nine regions and two chartered cities from 1990 to 2019. Spatiotemporal Gaussian process regression, cause of death ensemble model, Bayesian meta-regression tool, DisMod-MR 2.1, and other models were used to generate fertility, mortality, cause of death, and disability rates. The risk factor attribution estimations followed the general framework established for comparative risk assessment. Findings The SDI steadily improved in all regions and cities from 1990 to 2019, yet the disparity between the highest and lowest SDI increased by 54% during that period. The TFR declined from 6.91 (95% UI 6.59-7.20) in 1990 to 4.43 (4.01-4.92) in 2019, but the magnitude of decline also varied substantially among regions and cities. In 2019, TFR ranged from 6.41 (5.96-6.86) in Somali to 1.50 (1.26-1.80) in Addis Ababa. Life expectancy improved in Ethiopia by 21.93 years (21.79-22.07), from 46.91 years (45.71-48.11) in 1990 to 68.84 years (67.51-70.18) in 2019. Addis Ababa had the highest life expectancy at 70.86 years (68.91-72.65) in 2019; Afar and Benishangul-Gumuz had the lowest at 63.74 years (61.53-66.01) for Afar and 64.28 (61.99-66.63) for Benishangul-Gumuz. The overall increases in life expectancy were driven by declines in under-5 mortality and mortality from common infectious diseases, nutritional deficiency, and war and conflict. In 2019, the age-standardised all-cause death rate was the highest in Afar at 1353.38 per 100 000 population (1195.69-1526.19). The leading causes of premature mortality for all sexes in Ethiopia in 2019 were neonatal disorders, diarrhoeal diseases, lower respiratory infections, tuberculosis, stroke, HIV/AIDS, ischaemic heart disease, cirrhosis, congenital defects, and diabetes. With high SDIs and life expectancy for all sexes, Addis Ababa, Dire Dawa, and Harari had low rates of premature mortality from the five leading causes, whereas regions with low SDIs and life expectancy for all sexes (Afar and Somali) had high rates of premature mortality from the leading causes. In 2019, child and maternal malnutrition; unsafe water, sanitation, and handwashing; air pollution; high systolic blood pressure; alcohol use; and high fasting plasma glucose were the leading risk factors for health loss across regions and cities. Interpretation There were substantial improvements in health over the past three decades across regions and chartered cities in Ethiopia. However, the progress, measured in SDI, life expectancy, TFR, premature mortality, disability, and risk factors, was not uniform. Federal and regional health policy makers should match strategies, resources, and interventions to disease burden and risk factors across regions and cities to achieve national and regional plans, Sustainable Development Goals, and universal health coverage targets. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd
Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016
No full textBackground Measurement of changes in health across locations is useful to compare and contrast changing epidemiological patterns against health system performance and identify specific needs for resource allocation in research, policy development, and programme decision making. Using the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we drew from two widely used summary measures to monitor such changes in population health: disability-adjusted life-years (DALYs) and healthy life expectancy (HALE). We used these measures to track trends and benchmark progress compared with expected trends on the basis of the Socio-demographic Index (SDI).Methods We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2016. We calculated DALYs by summing years of life lost and years of life lived with disability for each location, age group, sex, and year. We estimated HALE using age-specific death rates and years of life lived with disability per capita. We explored how DALYs and HALE differed from expected trends when compared with the SDI: the geometric mean of income per person, educational attainment in the population older than age 15 years, and total fertility rate.Findings The highest globally observed HALE at birth for both women and men was in Singapore, at 75.2 years (95% uncertainty interval 71.9-78.6) for females and 72.0 years (68.8-75.1) for males. The lowest for females was in the Central African Republic (45.6 years [42.0-49.5]) and for males was in Lesotho (41.5 years [39.0-44.0]). From 1990 to 2016, global HALE increased by an average of 6.24 years (5.97-6.48) for both sexes combined. Global HALE increased by 6.04 years (5.74-6.27) for males and 6.49 years (6.08-6.77) for females, whereas HALE at age 65 years increased by 1.78 years (1.61-1.93) for males and 1.96 years (1.69-2.13) for females. Total global DALYs remained largely unchanged from 1990 to 2016 (-2.3% [-5.9 to 0.9]), with decreases in communicable, maternal, neonatal, and nutritional (CMNN) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). The exemplars, calculated as the five lowest ratios of observed to expected age-standardised DALY rates in 2016, were Nicaragua, Costa Rica, the Maldives, Peru, and Israel. The leading three causes of DALYs globally were ischaemic heart disease, cerebrovascular disease, and lower respiratory infections, comprising 16.1% of all DALYs. Total DALYs and age-standardised DALY rates due to most CMNN causes decreased from 1990 to 2016. Conversely, the total DALY burden rose for most NCDs; however, age-standardised DALY rates due to NCDs declined globally.Interpretation At a global level, DALYs and HALE continue to show improvements. At the same time, we observe that many populations are facing growing functional health loss. Rising SDI was associated with increases in cumulative years of life lived with disability and decreases in CMNN DALYs offset by increased NCD DALYs. Relative compression of morbidity highlights the importance of continued health interventions, which has changed in most locations in pace with the gross domestic product per person, education, and family planning. The analysis of DALYs and HALE and their relationship to SDI represents a robust framework with which to benchmark location-specific health performance. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform health policies, health system improvement initiatives, targeted prevention efforts, and development assistance for health, including financial and research investments for all countries, regardless of their level of sociodemographic development. The presence of countries that substantially outperform others suggests the need for increased scrutiny for proven examples of best practices, which can help to extend gains, whereas the presence of underperforming countries suggests the need for devotion of extra attention to health systems that need more robust support. Copyright (C) The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
