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Background Tobacco, one of the risk factors for non-communicable diseases, kills 8 million people each year. Like other sub-Saharan countries, Ethiopia faces the potential challenge of a tobacco epidemic. However, there is no organized data on the prevalence of tobacco use in the country. Therefore, this study aims to determine adult tobacco use in Ethiopia. Methods The study was conducted using the WHO and CDC GATS survey methods. Complex survey analysis was used to obtain prevalence and population estimates with 95% confidence intervals. Bivariate regression analyses were employed to examine factors related to tobacco use. Results The overall tobacco use percentage was 5.0% [95% CI (3.5, 6.9)], of which 65.8% [95% CI (53.4, 76.3)] only smoked tobacco products; 22.5% [95% CI (15.7, 31.2)] used smokeless tobacco only; and 11.8% [95% CI (6.5, 20.4)] used both smoked and smokeless tobacco products. In 2016, more men adults (8.1%) used tobacco than women did (1.8%). Eight out of eleven states have a higher smoking rate than the national average (3.7%). Gender, employment, age, religion, and marital status are closely linked to current tobacco use (p-value Conclusion The prevalence of tobacco use is still low in Ethiopia. However, the percentage of female smokers is increasing, and regional governments such as Afar and Gambella have a relatively high prevalence. This calls for the full implementation of tobacco control laws following the WHO MPOWER packages. A tailored tobacco control intervention targeting women, younger age groups, and regions with a high proportion of tobacco use are recommended.

Background\ud 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.\ud \ud Methods\ud 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.\ud \ud Findings\ud 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.\ud \ud Interpretation\ud 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.\ud \ud Funding\ud Bill & Melinda Gates Foundation.

In the Southern Nations, Nationalities, and Peoples’ Region of Ethiopia, improved water is the main source of water for household purposes. Access to improved water closer to their homes benefits the community in many ways. It improves their health status, saves their time and energy, and improves their productivity in jobs and education they are engaged in. However, due to natural and human activities, improved water sources do not always deliver good quality of water. It can be contaminated by different pathogenic microorganisms and chemicals. The result indicated that 44.7% and 50.9% of the samples were contaminated with Escherichia coli and enterococci respectively, and from the sanitary condition survey, 57.6% of the water sources exhibited from intermediate- to very high-risk level. And the risk priority matrix identifies 95 (27.9%) samples with high risk and 54 (15.9%) of the samples with very high risk. The main risks identified at those unsafe water sources were that the drainage canals were blocked with mud, grass, leaves, and stones; animals drinking the overflow water and grazing in the proximity of water sources and feces such as cow dung were observed; inadequate protection of water sources such as absence of fences and diversion ditches; and stagnant water near the source. The study conducted in the Southern Nations, Nationalities, and Peoples’ Region has clearly indicated that people may be at risk of being exposed to pathogens in half of the improved water sources when used for drinking based on the microbial indicator data or the sanitary inspection risk score. Though no correlation resulted from water quality and sanitary condition of sources, the risk priority matrix did enable prioritization of 54 very high-risk-level water sources for urgent targeted interventions from a total of 340 improved drinking water sources. From this, targeted interventions, improving water management practices, identifying and implementing effective water treatment options, providing sustainable energy sources for the supply of continuous water, and implementing climate resilience water safety planning, are recommended.