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Analysing trends and levels of the burden of disease at the national level can mask inequalities in health-related progress in lower administrative units such as provinces and districts. We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to analyse health patterns in Indonesia at the provincial level between 1990 and 2019. Long-term analyses of disease burden provide insights on Indonesia's advance to universal health coverage and its ability to meet the United Nations Sustainable Development Goals by 2030.We analysed GBD 2019 estimated cause-specific mortality, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), life expectancy at birth, healthy life expectancy, and risk factors for 286 causes of death, 369 causes of non-fatal health loss, and 87 risk factors by year, age, and sex for Indonesia and its 34 provinces from 1990 to 2019. To generate estimates for Indonesia at the national level, we used 138 location-years of data to estimate Indonesia-specific demographic indicators, 317 location-years of data for Indonesia-specific causes of death, 689 location-years of data for Indonesia-specific non-fatal outcomes, 250 location-years of data for Indonesia-specific risk factors, and 1641 location-years of data for Indonesia-specific covariates. For subnational estimates, we used the following source counts: 138 location-years of data to estimate Indonesia-specific demographic indicators; 5848 location-years of data for Indonesia-specific causes of death; 1534 location-years of data for Indonesia-specific non-fatal outcomes; 650 location-years of data for Indonesia-specific risk factors; and 16 016 location-years of data for Indonesia-specific covariates. We generated our GBD 2019 estimates for Indonesia by including 1 915 207 total source metadata rows, and we used 821 total citations.Life expectancy for males across Indonesia increased from 62·5 years (95% uncertainty interval 61·3-63·7) to 69·4 years (67·2-71·6) between 1990 and 2019, a positive change of 6·9 years. For females during the same period, life expectancy increased from 65·7 years (64·5-66·8) to 73·5 years (71·6-75·6), an increase of 7·8 years. There were large disparities in health outcomes among provinces. In 2019, Bali had the highest life expectancy at birth for males (74·4 years, 70·90-77·9) and North Kalimantan had the highest life expectancy at birth for females (77·7 years, 74·7-81·2), whereas Papua had the lowest life expectancy at birth for males (64·5 years, 60·9-68·2) and North Maluku had the lowest life expectancy at birth for females (64·0 years, 60·7-67·3). The difference in life expectancy for males between the highest-ranked and lowest-ranked provinces was 9·9 years and the difference in life expectacy for females between the highest-ranked and lowest-ranked provinces was 13·7 years. Age-standardised death, YLL, and YLD rates also varied widely among the provinces in 2019. High systolic blood pressure, tobacco, dietary risks, high fasting plasma glucose, and high BMI were the five leading risks contributing to health loss measured as DALYs in 2019.Our findings highlight that Indonesia faces a double burden of communicable and non-communicable diseases that varies across provinces. From 1990 to 2019, Indonesia witnessed a decline in the infectious disease burden, although communicable diseases such as tuberculosis, diarrhoeal diseases, and lower respiratory infections have remained a main source of DALYs in Indonesia. During that same period, however, all-ages death and disability rates from non-communicable diseases and exposure to their risk factors accounted for larger shares of health loss. The differences in health outcomes between the highest-performing and lowest-performing provinces have also widened since 1990. Our findings support a comprehensive process to revisit current health policies, examine the root causes of variation in the burden of disease among provinces, and strengthen programmes and policies aimed at reducing disparities across the country.The BillMelinda Gates Foundation and the Government of Indonesia.For the Bahasa Indonesia translation of the abstract see Supplementary Materials section.

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.

Background The present study sought to analyze smoking prevalence and smoking-attributable mortality estimates produced by the 2017 Global Burden of Disease Study for Brazil, 26 states, and the Federal District. Methods Prevalence of current smokers from 1990 to 2017 by sex and age was estimated using spatiotemporal Gaussian process regression. Population-attributable fractions were calculated for different risk-outcome pairs to generate estimates of smoking-attributable mortality. A cohort analysis of smoking prevalence by birth-year cohort was performed to better understand temporal age patterns in smoking. Smoking-attributable mortality rates were described and analyzed by development at state levels, using the Socio-Demographic Index (SDI). Finally, a decomposition analysis was conducted to evaluate the contribution of different factors to the changes in the number of deaths attributable to smoking between 1990 and 2017. Results Between 1990 and 2017, prevalence of smoking in the population (≥ 20 years old) decreased from 35.3 to 11.3% in Brazil. This downward trend was seen for both sexes and in all states, with a marked reduction in exposure to this risk factor in younger cohorts. Smoking-attributable mortality rates decreased by 57.8% (95% UI − 61.2, − 54.1) between 1990 and 2017. Overall, larger reductions were observed in states with higher SDI (Pearson correlation 0.637; p < 0.01). In Brazil, smoking remains responsible for a considerable amount of deaths, especially due to cardiovascular diseases and neoplasms. Conclusions Brazil has adopted a set of regulatory measures and implemented anti-tobacco policies that, along with improvements in socioeconomic conditions, have contributed to the results presented in the present study. Other regulatory measures need to be implemented to boost a reduction in smoking in order to reach the goals established in the scope of the 2030 United Nations Agenda for Sustainable Development.

Background Monitoring and reducing premature mortality due to non-communicable diseases (NCDs) is a global priority of Agenda 2030. This study aimed to describe the mortality trends and disability-adjusted life years (DALYs) lost due to NCDs between 1990 and 2017 for Brazil and to project those for 2030 as well as the risk factors (RFs) attributed deaths according to estimates of the Global Burden of Disease Study. Methods We analyzed cardiovascular diseases, chronic respiratory diseases, neoplasms, and diabetes, and compared the mortality rates in 1990 and 2017 for all of Brazil and states. The study used the definition of premature mortality (30–69 years) that is used by the World Health Organization. The number of deaths, mortality rates, DALYs, and years of life lost (YLL) were used to compare 1990 and 2017. We analyzed the YLL for NCDs attributable to RFs. Results There was a reduction of 35.3% from 509.1 deaths/100,000 inhabitants (1990) to 329.6 deaths/100,000 inhabitants due to NCDs in 2017. The DALY rate decreased by 33.6%, and the YLL rate decreased by 36.0%. There were reductions in NCDs rates in all 27 states. The main RFs related to premature deaths by NCDs in 2017 among women were high body mass index (BMI), dietary risks, high systolic blood pressure, and among men, dietary risks, high systolic blood pressure, tobacco, and high BMI. Trends in mortality rates due to NCDs declined during the study period; however, after 2015, the curve reversed, and rates fluctuated and tended to increase. Conclusion Our findings highlighted a decline in premature mortality rates from NCDs nationwide and in all states. There was a greater reduction in deaths from cardiovascular diseases, followed by respiratory diseases, and we observed a minor reduction for those from diabetes and neoplasms. The observed fluctuations in mortality rates over the last 3 years indicate that if no further action is taken, we may not achieve the NCD Sustainable Development Goals. These findings draw attention to the consequences of austerity measures in a socially unequal setting with great regional disparities in which the majority of the population is dependent on state social policies.

Background The prevalence and burden of disease resulting from obesity have increased worldwide. In Brazil, more than half of the population is now overweight. However, the impact of this growing risk factor on disease burden remains inexact. Using the 2017 Global Burden of Disease (GBD) results, this study sought to estimate mortality and disability-adjusted life years (DALYs) lost to non-communicable diseases caused by high body mass index (BMI) in both sexes and across age categories. This study also aimed to describe the prevalence of overweight and obesity throughout the states of Brazil. Methods Age-standardized prevalence of overweight and obesity were estimated between 1990 and 2017. A comparative risk assessment was applied to estimate DALYs and deaths for non-communicable diseases and for all causes linked to high BMI. Results The prevalence of overweight and obesity increased during the period of analysis. Overall, age-standardized prevalence of obesity in Brazil was higher in females (29.8%) than in males (24.6%) in 2017; however, since 1990, males have presented greater rise in obesity (244.1%) than females (165.7%). Increases in prevalence burden were greatest in states from the North and Northeast regions of Brazil. Overall, burden due to high BMI also increased from 1990 to 2017. In 2017, high BMI was responsible for 12.3% (8.8–16.1%) of all deaths and 8.4% (6.3–10.7%) of total DALYs lost to non-communicable diseases, up from 7.2% (4.1–10.8%), and 4.6% (2.4-6.0%) in 1990, respectively. Change due to risk exposure is the leading contributor to the growth of BMI burden in Brazil. In 2017, high BMI was responsible for 165,954 deaths and 5,095,125 DALYs. Cardiovascular disease and diabetes have proven to be the most prevalent causes of deaths, along with DALYs caused by high BMI, regardless of sex or state. Conclusions This study demonstrates increasing age-standardized prevalence of obesity in all Brazilian states. High BMI plays an important role in disease burdens in terms of cardiovascular diseases, diabetes, and all causes of mortality. Assessing levels and trends in exposures to high BMI and the resulting disease burden highlights the current priority for primary prevention and public health action initiatives focused on obesity.

Background Brazil leads the world in number of firearm deaths and ranks sixth by country in rate of firearm deaths per 100,000 people. This study aims to analyze trends in and burden of mortality by firearms, according to age and sex, for Brazil, and the association between these deaths and indicators of possession and carrying of weapons using data from the global burden of diseases, injuries, and risk factors study (GBD) 2017. Methods We used GBD 2017 estimates of mortality due to physical violence and self-harm from firearms for Brazil to analyze the association between deaths by firearms and explanatory variables. Results Deaths from firearms increased in Brazil from 25,819 in 1990 to 48,493 in 2017. Firearm mortality rates were higher among men and in the 20–24 age group; the rate was 20 times higher than for women in the same age group. Homicide rates increased during the study period, while mortality rates for suicides and accidental deaths decreased. The group of Brazilian federation units with the highest firearm collection rate (median = 7.5) showed reductions in the rate of total violent deaths by firearms. In contrast, the group with the lowest firearm collection rate (median = 2.0) showed an increase in firearm deaths from 2000 to 2017. An increase in the rate of voluntary return of firearms was associated with a reduction in mortality rates of unintentional firearm deaths (r = −0.364, p < 0.001). An increase in socio-demographic index (SDI) was associated with a reduction in all firearm death rates (r = −0.266, p = 0.008). An increase in the composite index of firearms seized or collected was associated with a reduction in rates of deaths by firearm in the subgroup of females, children, and the elderly (r = −0.269, p = 0.005). Conclusions There was a change in the trend of firearms deaths after the beginning of the collection of weapons in 2004. Federation units that collected more guns have reduced rates of violent firearm deaths.

Background: In Ethiopia there is no complete registration system to measure disease burden and risk factors accurately. In this study, the 2015 Global Burden of Diseases, Injuries and Risk factors (GBD) data were used to analyse the incidence, prevalence and mortality rates of malaria in Ethiopia over the last 25 years.\ud \ud Methods: GBD 2015 used verbal autopsy (VA) surveys, reports, and published scientific articles to estimate the burden of malaria in Ethiopia. Age and gender-specific causes of death for malaria were estimated using Cause of Death Ensemble Modelling (CODEm).\ud \ud Results: The number of new cases of malaria declined from 2.8 million (95% uncertainty interval (UI): 1.4-4.5million) in 1990 to 621,345 (95% UI: 462,230-797,442) in 2015. Malaria caused an estimated 30,323.9 deaths (95% UI: 11,533.3-61,215.3) in 1990 and 1,561.7 deaths (95% UI: 752.8-2,660.5) in 2015, a 94.8% reduction over the 25 years. Age-standardized mortality rate of malaria has declined by 96.5% between 1990 and 2015 with an annual rate of change (ARC) of 13.4%. Age-standardized malaria incidence rate among all ages and gender declined by 88.7% between 1990 and 2015. The number of disability-adjusted life years lost (DALY) due to malaria decreased from 2.2 million (95% UI: 0.76-4.7 million) in 1990 to 0.18 million (95% UI: 0.12-0.26 million) in 2015, with a total reduction 91.7%. Similarly, age-standardized DALY rate declined by 94.8% during the same period.\ud \ud Conclusions: Ethiopia has achieved a 50% reduction target of malaria of the Millennium Development Goals (MDGs). The country should strengthen its malaria control and treatment strategies to achieve the Sustainable Development Goals (SDG).

Background The Sustainable Development Goals (SDGs), adopted by all United Nations (UN) member states in 2015, established a set of bold and ambitious health-related targets to achieve by 2030. Understanding China’s progress toward these targets is critical to improving population health for its 1.4 billion people. Methods and findings We used estimates from the Global Burden of Disease (GBD) Study 2016, national surveys and surveillance data from China, and qualitative data. Twenty-eight of the 37 indicators included in the GBD Study 2016 were analyzed. We developed an attainment index of health-related SDGs, a scale of 0–100 based on the values of indicators. The projection model is adjusted based on the one developed by the GBD Study 2016 SDG collaborators. We found that China has achieved several health-related SDG targets, including decreasing neonatal and under-5 mortality rates and the maternal mortality ratios and reducing wasting and stunting for children. However, China may only achieve 12 out of the 28 health-related SDG targets by 2030. The number of target indicators achieved varies among provinces and municipalities. In 2016, among the seven measured health domains, China performed best in child nutrition and maternal and child health and reproductive health, with the attainment index scores of 93.0 and 91.8, respectively, followed by noncommunicable diseases (NCDs) (69.4), road injuries (63.6), infectious diseases (63.0), environmental health (62.9), and universal health coverage (UHC) (54.4). There are daunting challenges to achieve the targets for child overweight, infectious diseases, NCD risk factors, and environmental exposure factors. China will also have a formidable challenge in achieving UHC, particularly in ensuring access to essential healthcare for all and providing adequate financial protection. The attainment index of child nutrition is projected to drop to 80.5 by 2025 because of worsening child overweight. The index of NCD risk factors is projected to drop to 38.8 by 2025. Regional disparities are substantial, with eastern provinces generally performing better than central and western provinces. Sex disparities are clear, with men at higher risk of excess mortality than women. The primary limitations of this study are the limited data availability and quality for several indicators and the adoption of "business-as-usual" projection methods. Conclusion The study found that China has made good progress in improving population health, but challenges lie ahead. China has substantially improved the health of children and women and will continue to make good progress, although geographic disparities remain a great challenge. Meanwhile, China faced challenges in NCDs, mental health, and some infectious diseases. Poor control of health risk factors and worsening environmental threats have posed difficulties in further health improvement. Meanwhile, an inefficient health system is a barrier to tackling these challenges among such a rapidly aging population. The eastern provinces are predicted to perform better than the central and western provinces, and women are predicted to be more likely than men to achieve these targets by 2030. In order to make good progress, China must take a series of concerted actions, including more investments in public goods and services for health and redressing the intracountry inequities., Shenglan Tang and colleagues report China's current situation and projected achievement of the health related sustainable development goals by 2030., Author summary Why was the study done? China has made impressive progress in the Millennium Development Goals (MDGs) era, which ended in 2015. Despite China’s success in achieving the MDGs, it faces formidable challenges in achieving many targets in the health-related Sustainable Development Goals (SDGs), which have a 2030 target date. Understanding China’s current situation and progress toward achieving these goals is critical to the development of practical solutions for improving population health for its 1.4 billion people in the SDG era. What did the researchers do and find? We conducted an analysis of progress toward the health-related SDGs using data from the Global Burden of Disease (GBD) Study 2016, national surveys, surveillance data from China, and qualitative study results. We developed an index of the attainment of the health-related SDGs, using a scale of 0–100 based on the absolute values of indicators. We adjusted the projection model developed by the GBD 2016 SDG collaborators to produce sex-specific estimates, stratified by province, and explore sex and regional disparities. Around 120 key informants were purposively approached for thematic interviews. This research found that China has achieved several health-related SDG targets, especially on child nutrition and maternal and child health and reproductive health. Nevertheless, China may only achieve 12 out of the 28 selected health-related SDG targets by 2030. There are daunting challenges ahead for China in achieving the targets for child overweight, infectious diseases, noncommunicable disease risk factors, environmental exposure factors, and universal health coverage. Regional disparities were substantial, with eastern coastal provinces generally performing better than central and western provinces in most of the indicators. Sex disparities were clear, with men at higher risk of excess mortality than women. What do these findings mean? To achieve the targets of the health-related SDGs, China must take a series of concerted actions, including increased investment in public goods and services for health, addressing the regional inequities, and tackling the emerging new health challenges to ensure that no one is left behind. In those areas where China has already achieved the SDG targets, the government should synthesize the experiences and good practices that can be applied to the regions/provinces that need to catch up to the level of health development witnessed in developed regions/provinces. The Chinese government needs to examine the root causes of the challenges in achieving the health-related SDGs and develop an action plan to address these causes. The plan should prioritize key policy interventions for target populations and mobilize adequate resources to tackle these health challenges. It is important to address common problems by tackling cross-cutting issues in advancing the health-related SDGs, such as strengthening the enforcement of laws and regulations, establishing effective organizational structures, and human resources development.

BACKGROUND: The burden of HIV/AIDS in Ethiopia has not been comprehensively assessed over the last two decades. In this study, we used the 2016 Global Burden of Diseases, Injuries and Risk factors (GBD) data to analyze the incidence, prevalence, mortality and Disability-adjusted Life Years Lost (DALY) rates of Human Immunodeficiency Virus / Acquired Immune Deficiency Syndrome (HIV/AIDS) in Ethiopia over the last 26 years.METHODS: The GBD 2016 used a wide range of data source for Ethiopia such as verbal autopsy (VA), surveys, reports of the Federal Ministry of Health and the United Nations (UN) and published scientific articles. The modified United Nations Programme on HIV/AIDS (UNAIDS) Spectrum model was used to estimate the incidence and mortality rates for HIV/AIDS.RESULTS: In 2016, an estimated 36,990 new HIV infections (95% uncertainty interval [UI]: 8775-80262), 670,906 prevalent HIV cases (95% UI: 568,268-798,970) and 19,999 HIV deaths (95% UI:16426-24412) occurred in Ethiopia. The HIV/AIDS incidence rate peaked in 1995 and declined by 6.3% annually for both sexes with a total reduction of 77% between 1990 and 2016. The annualized HIV/AIDS mortality rate reduction during 1990 to 2016 for both sexes was 0.4%.CONCLUSIONS: Ethiopia has achieved the 50% reduction of the incidence rate of HIV/AIDS based on the Millennium Development Goals (MDGs) target. However, the decline in HIV/AIDS mortality rate has been comparatively slow. The country should strengthen the HIV/AIDS detection and treatment programs at community level to achieve its targets during the Sustainable Development Program (SDGs)-era.

BACKGROUND: The burden of Tuberculosis (TB) has not been comprehensively evaluated over the last 25 years in Ethiopia. In this study, we used the 2016 Global Burden of Diseases, Injuries and Risk Factors (GBD) data to analyze the incidence, prevalence and mortality rates of tuberculosis (TB) in Ethiopia over the last 26 years.\ud \ud METHODS: The GBD 2016 is a mathematical modeling using different data source for Ethiopia such as verbal autopsy (VA), prevalence surveys and annual case notifications. Age and sex specific causes of death for TB were estimated using the Cause of Death Ensemble Modeling (CODEm). We used the available data such as annual notifications and prevalence surveys as an input to estimate incidence and prevalence rates respectively using DisMod-MR 2.1, a Bayesian meta-regression tool.\ud \ud RESULTS: In 2016, we estimated 219,186 (95%UI: 182,977-265,292) new, 151,602 (95% UI: 126,054-180,976) prevalent TB cases and 48,910(95% UI: 40,310-58,195) TB deaths. The age-standardized TB incidence rate decreased from 201.6/100,000 to 88.5/100,000 (with a total decline of 56%) between 1990 to 2016. Similarly, the age standardized TB mortality rate declined from 393.8/100,000 to 100/100,000 between 1990 and 2016(with a total decline of 75%). \ud \ud CONCLUSIONS: Ethiopia has achieved the 50% reduction of most of the Millennium Development Goals (MDGs) targets related to TB. However, the decline of TB incidence and prevalence rates has been comparatively slow. The country should strengthen the TB case detection and treatment programs at community level to achieve its targets during the Sustainable Development Program (SDGs)-era.

Objectives: Everyone deserves a long and healthy life, but in reality, health outcomes differ across populations. We use results from the Global Burden of Disease Study 2017 (GBD 2017) to report patterns in the burden of diseases, injuries, and risks at the global, regional, national, and subnational level, and by sociodemographic index (SDI), from 1990 to 2017. Design: GBD 2017 undertook a systematic analysis of published studies and available data providing information on prevalence, incidence, remission, and excess mortal­ity. We computed prevalence, incidence, mortality, life expectancy, healthy life expectancy, years of life lost due to prema­ture mortality, years lived with disability, and disability-adjusted life years with 95% uncertainty intervals for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries from 1990 to 2017. We also computed SDI, a summary indicator combining measures of income, education, and fertility. Results: There were wide disparities in the burden of disease by SDI, with smaller burdens in affluent countries and in specific regions within countries. Select diseases and risks, such as drug use disorders, high blood pressure, high body mass index, diet, high fasting plasma glucose, smoking, and alco­hol use disorders warrant increased global attention and indicate a need for greater investment in prevention and treatment across the life course. Conclusions: Policymakers need a com­prehensive picture of what risks and causes result in disability and death. The GBD provides the means to quantify health loss: these findings can be used to examine root causes of disparities and develop pro­grams to improve health and health equity. Ethn Dis. 2019;29(Suppl 1): 159-172; doi:10.18865/ed.29.S1.159.

Introduction Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state. Objective To use the results of the Global Burden of Disease Study (GBD) to report trends in the burden of diseases, injuries, and risk factors at the state level from 1990 to 2016. Design and Setting A systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year. Main Outcomes and Measures Prevalence, incidence, mortality, life expectancy, healthy life expectancy (HALE), years of life lost (YLLs) due to premature mortality, years lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 333 causes and 84 risk factors with 95% uncertainty intervals (UIs) were computed. Results Between 1990 and 2016, overall death rates in the United States declined from 745.2 (95%UI, 740.6 to 749.8) per 100 000 persons to 578.0 (95%UI, 569.4 to 587.1) per 100 000 persons. The probability of death among adults aged 20 to 55 years declined in 31 states and Washington, DC from 1990 to 2016. In 2016, Hawaii had the highest life expectancy at birth (81.3 years) and Mississippi had the lowest (74.7 years), a 6.6-year difference. Minnesota had the highest HALE at birth (70.3 years), andWest Virginia had the lowest (63.8 years), a 6.5-year difference. The leading causes of DALYs in the United States for 1990 and 2016 were ischemic heart disease and lung cancer, while the third leading cause in 1990 was low back pain, and the third leading cause in 2016 was chronic obstructive pulmonary disease. Opioid use disorders moved from the 11th leading cause of DALYs in 1990 to the 7th leading cause in 2016, representing a 74.5%(95%UI, 42.8%to 93.9%) change. In 2016, each of the following 6 risks individually accounted for more than 5%of risk-attributable DALYs: tobacco consumption, high body mass index (BMI), poor diet, alcohol and drug use, high fasting plasma glucose, and high blood pressure. Across all US states, the top risk factors in terms of attributable DALYs were due to 1 of the 3 following causes: tobacco consumption (32 states), high BMI (10 states), or alcohol and drug use (8 states). Conclusions and Relevance There are wide differences in the burden of disease at the state level. Specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention. These data can be used to inform national health priorities for research, clinical care, and policy.