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      Global, Regional, and National Burden of Cardiovascular Diseases for 10 Causes, 1990 to 2015

      research-article
      , MD, MPH a , , , PhD a , , MPH b , , MD c , , MSc d , , MS d , , MPH, MBA e , , MD f , , MPH a , , PhD g , , PhD h , , PhD i , , MD j , , PhD k , , PhD l , , PhD m , , MSc d , , PhD n , , MSc o , , DPhil p , , PhD q , , MD r , , MD s , , MD t , , MSc d , , PhD u , , MPH d , , PhD, MBBS v , , MPH w , , MBBS, PhD x , , PhD y , , MD, PhD z , , MSc aa , , MPH bb , , PhD cc , , PhD dd , , DMSCi ee , , MD ff , , MD gg , , MD, MPH hh , , MD ii , , PhD jj , , MD a , kk , , PhD a , kk , , MD, PhD, MPH ll , , MD mm , , MD, DM, MSc nn , , MPhil oo , , MPH a , , MD, PhD pp , , MD qq , , MD rr , , MD ss , , PhD r , , PhD tt , , ScD r , , PhD uu , , MPH e , , MD r , , MSc a , , PhD vv , , MD, PhD ww , , MSc xx , , MD rr , , MBA d , , MSc d , , MD x , , MPH yy , , MS e , , PhD y , , DSc a , u , , MPH zz , , PhD aaa , , PhD bbb , , MD, MPH ccc , , PhD ddd , , PhD nn , , MBA, MPH eee , , MD fff , , MD ggg , , MD hhh , , PhD rr , , ShD iii , , MD jjj , , MD kkk , , MD lll , , MBBS, MPH, MBA mmm , , MBBS, PhD nnn , , DrPH ooo , , MD ppp , , MD qqq , , BA a , , PhD kk , , MD rrr , , MD kk , , PhD l , , MD MPH, DrPH sss , , MS, PhD g , , DrPH ttt , , MBBCh pp , , MD rr , , PhD uuu , , PhD vvv , , MPH d , , MD www , , PhD g , , MSc d , , PhD xxx , , MD yyy ,   , PhD zzz , , MD, MPH aaaa , , MD bbbb , , MD, PhD cccc , , MBChB, PhD dddd , , MSc eeee , , MPH a , , PhD ffff , , MBBS, MSc, DMed gggg , , MD g , , MS hhhh , , PharmD, PhD iiii , , PhD jjjj , , DM u , , MPH kkkk , , PhD llll , , MD z , , PhD mmmm , , PhD r , , PhD ttt , , MD, MSc, PhD q , , PhD nnnn , , PhD oooo , , MD, PhD, MPH rr , , MD, MPH, MA, MS pppp , , PhD qqqq , , DO, MPH f , , MPH rrrr , , PhD ssss , , MD, MPhil, PhD tttt , , MD, PhD uuuu , , MD vvvv , , PhD cc , , MS yy , , MSc d , , MD wwww ,   , PhD xxxx , , PhD yyyy , , MD, PhD, DMSc zzzz , , PhD aaaaa , , MD bbbbb , , PhD ccccc , , PhD ddddd , , MD eeeee , , DrPH fffff , , MSc e , , MD, MPH a , , MBBS ggggg , , PhD hhhhh , , PhD hhhhh , , PhD iiiii , , MD jjjjj , , MPH e , , PhD kkkkk , , MD lllll , , PhD mmmmm , , MPH nnnnn , , DhPH ooooo , , PhD ppppp , , PhD a , , PhD a , , DPhil a
      Journal of the American College of Cardiology
      Elsevier Biomedical
      cause of death, epidemiology, global health, CVD, cardiovascular disease, DALY, disability-adjusted life-year, IHD, ischemic heart disease, PAD, peripheral arterial disease, RHD, rheumatic heart disease, SDI, sociodemographic index, UI, uncertainty interval, YLD, years lived with disability, YLL, years of life lost

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          Abstract

          Background

          The burden of cardiovascular diseases (CVDs) remains unclear in many regions of the world.

          Objectives

          The GBD (Global Burden of Disease) 2015 study integrated data on disease incidence, prevalence, and mortality to produce consistent, up-to-date estimates for cardiovascular burden.

          Methods

          CVD mortality was estimated from vital registration and verbal autopsy data. CVD prevalence was estimated using modeling software and data from health surveys, prospective cohorts, health system administrative data, and registries. Years lived with disability (YLD) were estimated by multiplying prevalence by disability weights. Years of life lost (YLL) were estimated by multiplying age-specific CVD deaths by a reference life expectancy. A sociodemographic index (SDI) was created for each location based on income per capita, educational attainment, and fertility.

          Results

          In 2015, there were an estimated 422.7 million cases of CVD (95% uncertainty interval: 415.53 to 427.87 million cases) and 17.92 million CVD deaths (95% uncertainty interval: 17.59 to 18.28 million CVD deaths). Declines in the age-standardized CVD death rate occurred between 1990 and 2015 in all high-income and some middle-income countries. Ischemic heart disease was the leading cause of CVD health lost globally, as well as in each world region, followed by stroke. As SDI increased beyond 0.25, the highest CVD mortality shifted from women to men. CVD mortality decreased sharply for both sexes in countries with an SDI >0.75.

          Conclusions

          CVDs remain a major cause of health loss for all regions of the world. Sociodemographic change over the past 25 years has been associated with dramatic declines in CVD in regions with very high SDI, but only a gradual decrease or no change in most regions. Future updates of the GBD study can be used to guide policymakers who are focused on reducing the overall burden of noncommunicable disease and achieving specific global health targets for CVD.

          Central Illustration

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          Most cited references50

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          Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015

          Background Non-fatal outcomes of disease and injury increasingly detract from the ability of the world's population to live in full health, a trend largely attributable to an epidemiological transition in many countries from causes affecting children, to non-communicable diseases (NCDs) more common in adults. For the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015), we estimated the incidence, prevalence, and years lived with disability for diseases and injuries at the global, regional, and national scale over the period of 1990 to 2015. Methods We estimated incidence and prevalence by age, sex, cause, year, and geography with a wide range of updated and standardised analytical procedures. Improvements from GBD 2013 included the addition of new data sources, updates to literature reviews for 85 causes, and the identification and inclusion of additional studies published up to November, 2015, to expand the database used for estimation of non-fatal outcomes to 60 900 unique data sources. Prevalence and incidence by cause and sequelae were determined with DisMod-MR 2.1, an improved version of the DisMod-MR Bayesian meta-regression tool first developed for GBD 2010 and GBD 2013. For some causes, we used alternative modelling strategies where the complexity of the disease was not suited to DisMod-MR 2.1 or where incidence and prevalence needed to be determined from other data. For GBD 2015 we created a summary indicator that combines measures of income per capita, educational attainment, and fertility (the Socio-demographic Index [SDI]) and used it to compare observed patterns of health loss to the expected pattern for countries or locations with similar SDI scores. Findings We generated 9·3 billion estimates from the various combinations of prevalence, incidence, and YLDs for causes, sequelae, and impairments by age, sex, geography, and year. In 2015, two causes had acute incidences in excess of 1 billion: upper respiratory infections (17·2 billion, 95% uncertainty interval [UI] 15·4–19·2 billion) and diarrhoeal diseases (2·39 billion, 2·30–2·50 billion). Eight causes of chronic disease and injury each affected more than 10% of the world's population in 2015: permanent caries, tension-type headache, iron-deficiency anaemia, age-related and other hearing loss, migraine, genital herpes, refraction and accommodation disorders, and ascariasis. The impairment that affected the greatest number of people in 2015 was anaemia, with 2·36 billion (2·35–2·37 billion) individuals affected. The second and third leading impairments by number of individuals affected were hearing loss and vision loss, respectively. Between 2005 and 2015, there was little change in the leading causes of years lived with disability (YLDs) on a global basis. NCDs accounted for 18 of the leading 20 causes of age-standardised YLDs on a global scale. Where rates were decreasing, the rate of decrease for YLDs was slower than that of years of life lost (YLLs) for nearly every cause included in our analysis. For low SDI geographies, Group 1 causes typically accounted for 20–30% of total disability, largely attributable to nutritional deficiencies, malaria, neglected tropical diseases, HIV/AIDS, and tuberculosis. Lower back and neck pain was the leading global cause of disability in 2015 in most countries. The leading cause was sense organ disorders in 22 countries in Asia and Africa and one in central Latin America; diabetes in four countries in Oceania; HIV/AIDS in three southern sub-Saharan African countries; collective violence and legal intervention in two north African and Middle Eastern countries; iron-deficiency anaemia in Somalia and Venezuela; depression in Uganda; onchoceriasis in Liberia; and other neglected tropical diseases in the Democratic Republic of the Congo. Interpretation Ageing of the world's population is increasing the number of people living with sequelae of diseases and injuries. Shifts in the epidemiological profile driven by socioeconomic change also contribute to the continued increase in years lived with disability (YLDs) as well as the rate of increase in YLDs. Despite limitations imposed by gaps in data availability and the variable quality of the data available, the standardised and comprehensive approach of the GBD study provides opportunities to examine broad trends, compare those trends between countries or subnational geographies, benchmark against locations at similar stages of development, and gauge the strength or weakness of the estimates available. Funding Bill & Melinda Gates Foundation.
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            Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015

            Summary Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography–year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4–61·9) in 1980 to 71·8 years (71·5–72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7–17·4), to 62·6 years (56·5–70·2). Total deaths increased by 4·1% (2·6–5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8–18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6–16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9–14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1–44·6), malaria (43·1%, 34·7–51·8), neonatal preterm birth complications (29·8%, 24·8–34·9), and maternal disorders (29·1%, 19·3–37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000–183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000–532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Funding Bill & Melinda Gates Foundation.
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              Mortality risk attributable to high and low ambient temperature: a multicountry observational study

              Summary Background Although studies have provided estimates of premature deaths attributable to either heat or cold in selected countries, none has so far offered a systematic assessment across the whole temperature range in populations exposed to different climates. We aimed to quantify the total mortality burden attributable to non-optimum ambient temperature, and the relative contributions from heat and cold and from moderate and extreme temperatures. Methods We collected data for 384 locations in Australia, Brazil, Canada, China, Italy, Japan, South Korea, Spain, Sweden, Taiwan, Thailand, UK, and USA. We fitted a standard time-series Poisson model for each location, controlling for trends and day of the week. We estimated temperature–mortality associations with a distributed lag non-linear model with 21 days of lag, and then pooled them in a multivariate metaregression that included country indicators and temperature average and range. We calculated attributable deaths for heat and cold, defined as temperatures above and below the optimum temperature, which corresponded to the point of minimum mortality, and for moderate and extreme temperatures, defined using cutoffs at the 2·5th and 97·5th temperature percentiles. Findings We analysed 74 225 200 deaths in various periods between 1985 and 2012. In total, 7·71% (95% empirical CI 7·43–7·91) of mortality was attributable to non-optimum temperature in the selected countries within the study period, with substantial differences between countries, ranging from 3·37% (3·06 to 3·63) in Thailand to 11·00% (9·29 to 12·47) in China. The temperature percentile of minimum mortality varied from roughly the 60th percentile in tropical areas to about the 80–90th percentile in temperate regions. More temperature-attributable deaths were caused by cold (7·29%, 7·02–7·49) than by heat (0·42%, 0·39–0·44). Extreme cold and hot temperatures were responsible for 0·86% (0·84–0·87) of total mortality. Interpretation Most of the temperature-related mortality burden was attributable to the contribution of cold. The effect of days of extreme temperature was substantially less than that attributable to milder but non-optimum weather. This evidence has important implications for the planning of public-health interventions to minimise the health consequences of adverse temperatures, and for predictions of future effect in climate-change scenarios. Funding UK Medical Research Council.
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                Author and article information

                Contributors
                Journal
                J Am Coll Cardiol
                J. Am. Coll. Cardiol
                Journal of the American College of Cardiology
                Elsevier Biomedical
                0735-1097
                1558-3597
                04 July 2017
                04 July 2017
                : 70
                : 1
                : 1-25
                Affiliations
                [a ]University of Washington, Seattle, Washington
                [b ]University of Queensland, Brisbane, Queensland, Australia
                [c ]Cairo University, Cairo, Egypt
                [d ]Mekelle University, Addis Ababa, Ethiopia
                [e ]Jimma University, Jimma, Ethiopia
                [f ]Cleveland Clinic, Cleveland, Ohio
                [g ]University of Melbourne, Melbourne, Victoria, Australia
                [h ]University of Lorraine, Nancy, France
                [i ]Universidad de Cartagena, Cartagena, Colombia
                [j ]Oregon Health & Science University, Portland, Oregon
                [k ]Zahedan University of Medical Sciences, Zahedan, Iran
                [l ]Uppsala University, Uppsala, Sweden
                [m ]Qom University of Medical Sciences, Qom, Iran
                [n ]National Institute of Public Health, Cuernavaca, Mexico
                [o ]Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India
                [p ]University College London, London, United Kingdom
                [q ]University of Belgrade, Belgrade, Serbia
                [r ]Harvard University, Boston, Massachusetts
                [s ]University of Gothenburg, Gothenburg, Sweden
                [t ]College of Public Health and Tropical Medicine, Jazan University, Jazan, Saudi Arabia
                [u ]University of Oxford, Oxford, United Kingdom
                [v ]Aga Khan University, Karachi, Pakistan
                [w ]Wolaita Sodo University, Wolaita Sodo, Ethiopia
                [x ]The University of Western Australia, Perth, Western Australia, Australia
                [y ]Karolinska Institutet, Stockholm, Sweden
                [z ]Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
                [aa ]Instituto Nacional de Salud, Bogotá, Colombia
                [bb ]Caja Costarricense de Seguro Social, San José, Costa Rica
                [cc ]University of València/INCLIVA Health Research Institute and CIBERSAM, València, Spain
                [dd ]Seoul National University Hospital, Seoul, South Korea
                [ee ]Bispebjerg University Hospital, Copenhagen, Denmark
                [ff ]University of Salerno, Salerno, Italy
                [gg ]Mayo Clinic, Rochester, Minnesota
                [hh ]University of California, San Diego, California
                [ii ]Long Beach, California
                [jj ]Eduardo Mondlane University, Maputo, Mozambique
                [kk ]Public Health Foundation of India, New Delhi, India
                [ll ]Republican Institute of Cardiology and Internal Diseases, Almaty, Kazakhstan
                [mm ]University of Peradeniya, Peradeniya, Sri Lanka
                [nn ]Centre for Chronic Disease Control, Gurgaon, India
                [oo ]International Institute for Population Sciences, Mumbai, India
                [pp ]Mansoura Faculty of Medicine, Mansoura University, Mansoura, Egypt
                [qq ]University of Philippines Manila, Manila, Philippines
                [rr ]Tehran University of Medical Sciences, Tehran, Iran
                [ss ]University of Louisville, Louisville, Kentucky
                [tt ]Auckland University of Technology, Auckland, New Zealand
                [uu ]University of Edinburgh, Edinburgh United Kingdom
                [vv ]University of Massachusetts Boston, Boston, Massachusetts
                [ww ]Eternal Heart Care Center and Research Institute, Jaipur, India
                [xx ]University of Groningen, Groningen, the Netherlands
                [yy ]Mizan-Tepi University, Mizan Teferi, Ethiopia
                [zz ]Nevada Division of Public and Behavioral Health, Carson City, Nevada
                [aaa ]Baylor College of Medicine, Houston, Texas
                [bbb ]George Mason University, Fairfax, Virginia
                [ccc ]Denver Health/University of Colorado, Denver, Colorado
                [ddd ]University of Aberdeen, Aberdeen, United Kingdom
                [eee ]International Center for Research on Women, New Delhi, India
                [fff ]Ruprecht-Karls Universitaet Heidelberg, Heidelberg, Germany
                [ggg ]Society for Education, Action and Research in Community Health, Gadchiroli, India
                [hhh ]Case Western University Hospitals, Cleveland, Ohio
                [iii ]Jordan University of Science and Technology, Irbid, Jordan
                [jjj ]University of Louisville, Louisville, Kentucky
                [kkk ]Seoul National University, Seoul, South Korea
                [lll ]New York Medical College, Valhalla, New York
                [mmm ]Al-Imam Muhammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia
                [nnn ]Ball State University, Muncie, Indiana
                [ooo ]Northeastern University, Boston, Massachusetts
                [ppp ]Brown University, Providence, Rhode Island
                [qqq ]Health Policy and Humanities, National Institute of Health Research and Development, Jakarta, Indonesia
                [rrr ]Boston University School of Medicine, Boston, Massachusetts
                [sss ]University of Haifa, Haifa, Israel
                [ttt ]University of São Paulo, São Paulo, Brazil
                [uuu ]Chinese Academy of Sciences, Beijing, China
                [vvv ]Martin Luther University Halle-Wittenberg, Halle, Germany
                [www ]National Institutes of Health, Bethesda, Maryland
                [xxx ]Pacific Institute for Research & Evaluation, Beltsville, Maryland
                [yyy ]Kyrgyz State Medical Academy, Bishkek, Kyrgyzstan
                [zzz ]Ahmadu Bello University, Zaria, Nigeria
                [aaaa ]Columbia University, New York, New York
                [bbbb ]University of Science Malaysia, Penang, Malaysia
                [cccc ]The Mount Sinai Hospital, New York, New York
                [dddd ]The George Institute for Global Health, Newtown, New South Wales, Australia
                [eeee ]Ministry of Health and Social Welfare, Dar es Salaam, Tanzania
                [ffff ]American University of Beirut, Beirut, Lebanon
                [gggg ]College of Medicine, University of Ibadan, Ibadan, Nigeria
                [hhhh ]University of Porto, Porto, Portugal
                [iiii ]University of Illinois at Chicago, Chicago, Illinois
                [jjjj ]Alborz University of Medical Sciences, Karaj, Iran
                [kkkk ]Society for Health and Demographic Surveillance, Birbhum, India
                [llll ]Imperial College London, London, United Kingdom
                [mmmm ]Maragheh University of Medical Sciences, Maragheh, Iran
                [nnnn ]University of KwaZulu-Natal, Durban, South Africa
                [oooo ]North-West University, Potchefstroom, South Africa
                [pppp ]Independent Consultant, Islamabad, Pakistan
                [qqqq ]Korea University, Seoul, South Korea
                [rrrr ]Haramaya University, Dire Dawa, Ethiopia
                [ssss ]Federal University of Santa Catarina, Florianópolis, Brazil
                [tttt ]University of Yaoundé, Yaoundé, Cameroon
                [uuuu ]Luxembourg Institute of Health, Strassen, Luxembourg
                [vvvv ]Indian Council of Medical Research, New Delhi, India
                [wwww ]Postgraduate Institute of Medical Education and Research, Chandigarh, India
                [xxxx ]Monash University, Melbourne, Victoria, Australia
                [yyyy ]Jagiellonian University Medical College, Kraków, Poland
                [zzzz ]University of Copenhagen, Copenhagen, Denmark
                [aaaaa ]Universitat de Barcelona, CIBERSAM, Barcelona, Spain
                [bbbbb ]Federal Teaching Hospital, Abakaliki, Nigeria
                [ccccc ]University of Warwick, Coventry, United Kingdom
                [ddddd ]UKK Institute for Health Promotion Research, Tampere, Finland
                [eeeee ]National Research University Higher School of Economics, Moscow, Russia
                [fffff ]Norwegian Institute of Public Health, Oslo, Norway
                [ggggg ]Royal Children’s Hospital, Melbourne, Victoria, Australia
                [hhhhh ]Federal Institute for Population Research, Wiesbaden, Germany
                [iiiii ]Cochrane South Africa, Tygerberg, South Africa
                [jjjjj ]King’s College London, London, United Kingdom
                [kkkkk ]Nanjing University School of Medicine, Nanjing, China
                [lllll ]Northwestern University, Chicago, Illinois
                [mmmmm ]University of Hong Kong, Pokfulam, Hong Kong
                [nnnnn ]Kyoto University, Kyoto, Japan
                [ooooo ]Jackson State University, Jackson, Mississippi
                [ppppp ]Wuhan University, Wuhan, China
                Author notes
                [] Address for correspondence: Dr. Gregory A. Roth, Division of Cardiology, Department of Medicine, University of Washington, Institute for Health Metrics and Evaluation, 2301 5th Avenue, Suite 600, Seattle, Washington 98121.Division of Cardiology, Department of MedicineUniversity of Washington, Institute for Health Metrics and Evaluation2301 5th Avenue, Suite 600SeattleWashington 98121 rothg@ 123456uw.edu
                Article
                S0735-1097(17)37244-3
                10.1016/j.jacc.2017.04.052
                5491406
                28527533
                12c7fd17-a4f0-497f-840a-ffa37278e3c9
                © 2017 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 8 March 2017
                : 19 April 2017
                : 21 April 2017
                Categories
                Original Investigation

                Cardiovascular Medicine
                cause of death,epidemiology,global health,cvd, cardiovascular disease,daly, disability-adjusted life-year,ihd, ischemic heart disease,pad, peripheral arterial disease,rhd, rheumatic heart disease,sdi, sociodemographic index,ui, uncertainty interval,yld, years lived with disability,yll, years of life lost

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