The State of US Health, 1990-2016: Burden of Diseases, Injuries, and Risk Factors Among US States
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...
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| Published in | JAMA : the journal of the American Medical Association Vol. 319; no. 14; pp. 1444 - 1472 |
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| Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article Publication |
| Language | English |
| Published |
United States
American Medical Association
10.04.2018
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0098-7484 1538-3598 1538-3598 |
| DOI | 10.1001/jama.2018.0158 |
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| Abstract | 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), and West 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. |
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| AbstractList | 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), and West 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. Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state. 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. A systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year. 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. 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), and West 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). 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. Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state.IntroductionSeveral studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state.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.ObjectiveTo 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.A systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year.Design and SettingA systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year.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.Main Outcomes and MeasuresPrevalence, 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.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), and West 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).ResultsBetween 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), and West 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).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.Conclusions and RelevanceThere 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. In this study, Global Burden of Disease investigators characterize trends in mortality, life expectancy, and prevalence associated with most common diseases and disease and mortality risk factors in the United States between 1990 and 2016. |
| Author | Roth, Gregory A Colombara, Danny Havmoller, Rasmus Schwebel, David C Sykes, Bryan L Nachega, Jean B Akinyemiju, Tomi Murray, Christopher J. L Kandel, Amit Carter, Austin Erskine, Holly E Miller, Ted Leasher, Janet Stranges, Saverio Kimokoti, Ruth Soneji, Samir James, Spencer Moses, Mark Kyu, Hmwe Patel, Tejas Cornaby, Leslie Ferrari, Alize J Nichols, Emma Serdar, Berrin Rehm, Colin D Park, Eun-Kee Gebrehiwot, Tsegaye Telwelde Tsoi, Derrick Whiteford, Harvey A Ahmadi, Alireza Mullany, Erin Anderson, Ben Younis, Mustafa Hay, Simon I Breitborde, Nicholas Yadgir, Simon Krohn, Kristopher J Degenhardt, Louisa Wagner, Gregory Mehari, Alem Cahill, Leah Criqui, Michael Chen, Honglei Leung, Janni Bazargan-Hejazi, Shahrzad Ding, Eric L Liu, Patrick Khubchandani, Jagdish Kasaeian, Amir Briant, Paul Lee, Alex Hotez, Peter Hu, Guoqing Bärnighausen, Till Frank, Tahvi Leung, Ricky Biryukov, Stan Al-Aly, Ziyad Tabb, Karen Wallin, Mitch Skirbekk, Vegard Kolte, Dhaval Farvid, Maryam Abbas, Kaja Nsoesie, Elaine Zipkin, Ben Fullman, Nancy Gona, Philimon Sanabria, Juan R Bel |
| AuthorAffiliation | 33 Yale University, New Haven, Connecticut 19 Murdoch Childrens Research Institute, Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia 7 Hematology-Oncology and Stem Cell Transplantation Research Center, and Hematologic Malignancies Research Center, Tehran University of Medical Sciences, Tehran, Iran 54 College of Medicine, Howard University, Washington, DC 10 UKZN Gastrointestinal Cancer Research Centre, South African Medical Research Council, Durban, South Africa 21 Cambridge Health Alliance, Cambridge, Massachusetts 50 Institute of Public Health, Heidelberg University, Heidelberg, Germany 53 Washington University in St Louis, St Louis, Missouri 71 University of British Columbia, Vancouver, Canada 9 Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa 8 Competence Center Mortality-Follow-Up of the German National Cohort, Federal Institute for Population Research, Wiesbaden, Hessen, Germany 39 University of |
| AuthorAffiliation_xml | – name: 15 Department of Health Sciences, Northeastern University, Boston, Massachusetts – name: 63 Department of Epidemiology and Health Statistics, School of Public Health, Central South University, Changsha, Hunan, China – name: 81 White Plains Hospital, White Plains, New York – name: 56 University at Buffalo, Buffalo, New York – name: 24 Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland – name: 55 University of New Mexico, Albuquerque – name: 60 University of Rochester Medical Center, Rochester, New York – name: 57 University of Washington, Seattle – name: 78 Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg – name: 9 Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa – name: 32 University of California, San Diego, La Jolla, California – name: 26 Case Western Reserve University, Cleveland, Ohio – name: 62 Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts – name: 85 Centre of Excellence in Women and Child Health, Aga Khan University, Karachi, Pakistan – name: 8 Competence Center Mortality-Follow-Up of the German National Cohort, Federal Institute for Population Research, Wiesbaden, Hessen, Germany – name: 22 Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania – name: 41 Simmons College, Boston, Massachusetts – name: 51 Jimma University, Jimma, Oromia, Ethiopia – name: 29 National Drug and Alcohol Research Centre, University of New South Wales, Sydney, Australia – name: 48 Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts – name: 74 Institute of Public Health, Faculty of Health Sciences, Jagiellonian University Medical College, Kraków, Poland – name: 87 Department of Ophthalmology, Medical Faculty Mannheim, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany – name: 71 University of British Columbia, Vancouver, Canada – name: 35 Neurology Department, Georgetown University, Washington, DC – name: 77 Department of Epidemiology & Biostatistics, Schulich School of Medicine & Dentistry, Western University, London, Canada – name: 6 Queensland Centre for Mental Health Research, Brisbane, Australia – name: 30 Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts – name: 14 Montefiore Medical Center, Bronx, New York – name: 86 Centre for Global Child Health, The Hospital for Sick Children, Toronto, Canada – name: 18 Division of Epidemiology & Biostatistics, Graduate School of Public Health, San Diego State University, San Diego, California – name: 4 Karolinska Institutet, Stockholm, Sweden – name: 13 Division of Hematology, Department of Medicine, University of Washington, Seattle, and Fred Hutchinson Cancer Research Center, Seattle – name: 53 Washington University in St Louis, St Louis, Missouri – name: 42 College of Medicine, Charles R. Drew University of Medicine and Science, Los Angeles, California – name: 72 The Ohio State University, Columbus – name: 43 David Geffen School of Medicine, University of California at Los Angeles – name: 20 Albert Einstein College of Medicine, Bronx, New York – name: 65 Department of Nutrition and Health Science, Ball State University, Muncie, Indiana – name: 16 University of Alabama at Birmingham – name: 45 Center for Disease Burden, Norwegian Institute of Public Health, and Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway – name: 36 Hunger Action Los Angeles, Los Angeles, California – name: 2 University of Louisville, Louisville, Kentucky – name: 31 Harvard/MGH Center on Genomics, Vulnerable Populations, and Health Disparities, Mongan Institute for Health Policy, Massachusetts General Hospital, Boston – name: 40 State University of New York, Albany, Rensselaer, New York – name: 64 Michigan State University, East Lansing – name: 70 Bureau of Child, Family & Community Wellness, Nevada Division of Public and Behavioral Health, Carson City – name: 47 School of Public Health, Curtin University, Perth, Australia – name: 73 College of Medicine, Baylor University, Houston, Texas – name: 68 Dalhousie University, Halifax, Canada – name: 83 Columbia University, New York, New York – name: 58 University of South Florida, Tampa – name: 39 University of Massachusetts, Boston – name: 50 Institute of Public Health, Heidelberg University, Heidelberg, Germany – name: 49 Africa Health Research Institute, Mtubatuba, South Africa – name: 76 Dartmouth College, Hanover, New Hampshire – name: 17 Division of Cardiology, Brown University, Providence, Rhode Island – name: 61 Department of Medical Humanities and Social Medicine, College of Medicine, Kosin University, Busan, South Korea – name: 84 Centre for Research and Action in Public Health, University of Canberra, Canberra, Australia – name: 28 School of Social Work, University of Illinois at Urbana-Champaign – name: 46 Pacific Institute for Research & Evaluation, Calverton, Maryland – name: 37 Non-communicable Diseases Research Center, Alborz University of Medical Sciences, Karaj, Alborz, Iran – name: 33 Yale University, New Haven, Connecticut – name: 1 Institute for Health Metrics and Evaluation, University of Washington, Seattle – name: 66 College of Optometry, Nova Southeastern University, Fort Lauderdale, Florida – name: 75 Faculty of Health Sciences, Wroclaw Medical University, Wroclaw, Poland – name: 19 Murdoch Childrens Research Institute, Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia – name: 69 Mayo Clinic, Jacksonville, Florida – name: 5 School of Public Health, University of Queensland, Brisbane, Australia – name: 27 Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, England – name: 67 School of Public Health, University of Queensland, Brisbane, Australia – name: 82 Norwegian Institute of Public Health, Oslo, Norway – name: 52 Department of Preventive Medicine, Northwestern University, Chicago, Illinois – name: 59 Friedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts – name: 23 Stellenbosch University, Cape Town, Western Cape, South Africa – name: 3 Kermanshah University of Medical Sciences, Kermanshah, Iran – name: 25 Joan C. Edwards School of Medicine, Marshall University, Huntington, West Virginia – name: 44 Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom – name: 12 Departments of Criminology, Law & Society, Sociology, and Public Health, University of California, Irvine – name: 80 Department of Surgery, Virginia Commonwealth University, Richmond – name: 21 Cambridge Health Alliance, Cambridge, Massachusetts – name: 34 VA Medical Center, Washington, DC – name: 11 University of Colorado, Aurora – name: 79 Oregon Health & Science University, Portland – name: 7 Hematology-Oncology and Stem Cell Transplantation Research Center, and Hematologic Malignancies Research Center, Tehran University of Medical Sciences, Tehran, Iran – name: 10 UKZN Gastrointestinal Cancer Research Centre, South African Medical Research Council, Durban, South Africa – name: 38 Jackson State University, Jackson, Mississippi – name: 54 College of Medicine, Howard University, Washington, DC |
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L surname: Murray fullname: Murray, Christopher J. L |
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| Snippet | INTRODUCTION: Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by... Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state. To use... INTRODUCTION Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by... Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by... In this study, Global Burden of Disease investigators characterize trends in mortality, life expectancy, and prevalence associated with most common diseases... |
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| SubjectTerms | Adult Adults Alcoholic beverages Back pain Birth Blood pressure Body mass Body mass index Body size Chronic obstructive pulmonary disease Coronary artery disease Cost of Illness Diet Disabled Persons - statistics & numerical data Disorders Fasting Female Geography Glucose Health risks Health Status Disparities Heart Heart diseases Humans Hypertension Injuries Ischemia Laboratory testing Life expectancy Life span Low back pain Lung cancer Lung diseases Male Middle Aged Morbidity - trends Mortality Mortality - trends Mortality, Premature - trends Obstructive lung disease Opioids Original Investigation Pain Quality-Adjusted Life Years Risk analysis Risk Factors Tobacco United States - epidemiology Wounds and Injuries - epidemiology |
| Title | The State of US Health, 1990-2016: Burden of Diseases, Injuries, and Risk Factors Among US States |
| URI | http://dx.doi.org/10.1001/jama.2018.0158 https://www.ncbi.nlm.nih.gov/pubmed/29634829 https://www.proquest.com/docview/2068027862 https://www.proquest.com/docview/2024019173 https://pubmed.ncbi.nlm.nih.gov/PMC5933332 http://kipublications.ki.se/Default.aspx?queryparsed=id |
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