and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEWThe GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs).FINDINGS In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCEThe results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

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ObjectiveOverweight/obesity among women is associated with an increased risk of gestational diabetes, pre-eclampsia, postpartum haemorrhage, low birth weight, congenital malformation and neonatal deaths. Although the magnitude of overweight and obesity among the reproductive age group women is a common problem in Ethiopia, there are limited studies that determine the associated factors of overweight and obesity at the national level. Therefore, this study aimed to identify the determinant factors of overweight/obesity among reproductive age group women in Ethiopia.DesignCross-sectional study design.SettingEthiopia.ParticipantsNon-pregnant women aged 15–49 years.Primary outcomeOverweight/obesity.MethodsThe present study used the Ethiopia Demographic Health Survey (EDHS) data for 2016. A total of 10 938 non-pregnant reproductive age group women were included in the analysis. Both bivariable and multivariable multilevel logistic regression were performed to determine the determinants of overweight and obesity among women in Ethiopia. The OR with a 95% CI was estimated for potential determinants included in the final model.ResultsThose women with secondary education (adjusted OR (AOR)=1.48, 1.01, 2.18), higher education (AOR=1.78, 1.13, 2.81), richer (AOR=1.85, 1.15, 2.98) and richest wealth index (AOR=3.23, 1.98, 5.29), urban residence (AOR=4.46, 2.89, 6.87), married (AOR=1.79, 1.21, 2.64), widowed (AOR=2.42, 1.41, 4.15), divorced (AOR=1.84, 1.13, 3.00), aged 25–34 years (AOR=2.04, 1.43, 2.89), 35–44 years (AOR=2.79, 1.99, 3.93) and 45–49 years (AOR=2.62, 1.54, 4.45) had higher odds of developing overweight and obesity.ConclusionWomen with higher education level, high wealth status, older age, formerly married and those urban dwellers had higher odds of overweight and obesity. Therefore, regular physical activity, reducing consumption of fat/energy-dense food as well as modifying the mode of transportation is recommended.

Background: Health insurance is one of the instruments to achieve universal health coverage. However, in Ethiopia, the coverage of health insurance is very low and varies from place to place as well. Therefore, exploring the spatial distribution of health insurance is important to prioritize and design targeted intervention programs in the country. Methods: A total of 16,583 reproductive age group women (15-49 years) were included in this study. The Bernoulli model was used by applying Kulldorff methods using the SaTScan software to analyse the purely spatial clusters of health insurance coverage. ArcGIS version 10.3 was used to visualize the distribution of health insurance coverage across the country. Mixed-effect logistic regression analysis was also used to identify predictors of health insurance coverage. Results: Health insurance coverage among women aged 15-49 years had spatial variations across the country (Moran's I: 0.115, p < 0.001). Health insurance coverage in Amhara (p < 0.001) and Tigray (p < 0.001) National Regional States clustered spatially. Reading newspapers at least once a week (Adjusted Odds Ratio (AOR) = 1.78, 95% CI: (1.18-2.68))), 40-44 years of age (AOR = 2.14, 95% CI: (1.37-3.35)), clerical working mothers (AOR = 4.33, 95% CI: (2.50-7.49)), mothers' with secondary school education (AOR = 1.77; 95% CI: (1.21-2.58)), mothers' with higher school education (AOR = 2.62; 95% CI: (1.63-4.23)), having more than 5 family members (AOR = 1.25; 95% CI: (1.01-1.55)) and richest wealth quantile (AOR = 3.43, 95% CI: (1.96-6.01)) were predictors of health insurance coverage among reproductive age group women in Ethiopia. Conclusion: Health insurance coverage was very low in Ethiopia and had spatial variations across the country. The hot spot areas with low health insurance coverage need more coherent and harmonized action such as strengthening financial protection through national health packages, sharing experience from regions which have better health insurance coverage and using mass media to increase awareness and confidence of potentials in the systems, which may encourage them to enrol.

Background Diabetes, particularly type 1 diabetes, at younger ages can be a largely preventable cause of death with the correct health care and services. We aimed to evaluate diabetes mortality and trends at ages younger than 25 years globally using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. MethodsWe used estimates of GBD 2019 to calculate international diabetes mortality at ages younger than 25 years in 1990 and 2019. Data sources for causes of death were obtained from vital registration systems, verbal autopsies, and other surveillance systems for 1990-2019. We estimated death rates for each location using the GBD Cause of Death Ensemble model. We analysed the association of age-standardised death rates per 100 000 population with the Socio-demographic Index (SDI) and a measure of universal health coverage (UHC) and described the variability within SDI quintiles. We present estimates with their 95% uncertainty intervals. FindingsIn 2019, 16 300 (95% uncertainty interval 14 200 to 18 900) global deaths due to diabetes (type 1 and 2 combined) occurred in people younger than 25 years and 73•7% (68•3 to 77•4) were classified as due to type 1 diabetes. The age-standardised death rate was 0•50 (0•44 to 0•58) per 100 000 population, and 15 900 (97•5%) of these deaths occurred in low to high-middle SDI countries. The rate was 0•13 (0•12 to 0•14) per 100 000 population in the high SDI quintile, 0•60 (0•51 to 0•70) per 100 000 population in the low-middle SDI quintile, and 0•71 (0•60 to 0•86) per 100 000 population in the low SDI quintile. Within SDI quintiles, we observed large variability in rates across countries, in part explained by the extent of UHC (r²=0•62). From 1990 to 2019, age-standardised death rates decreased globally by 17•0% (-28•4 to -2•9) for all diabetes, and by 21•0% (-33•0 to -5•9) when considering only type 1 diabetes. However, the low SDI quintile had the lowest decline for both all diabetes (-13•6% [-28•4 to 3•4]) and for type 1 diabetes (-13•6% [-29•3 to 8•9]). Interpretation Decreasing diabetes mortality at ages younger than 25 years remains an important challenge, especially in low and low-middle SDI countries. Inadequate diagnosis and treatment of diabetes is likely to be major contributor to these early deaths, highlighting the urgent need to provide better access to insulin and basic diabetes education and care. This mortality metric, derived from readily available and frequently updated GBD data, can help to monitor preventable diabetes-related deaths over time globally, aligned with the UN's Sustainable Development Targets, and serve as an indicator of the adequacy of basic diabetes care for type 1 and type 2 diabetes across nations. Funding Bill & Melinda Gates Foundation.