Global Health Metricswww.thelancet.comVol 396 October 17, 20201205IntroductionThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on disease and injury incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries.1–3 In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound and up-to-date evidence on trends—both progress and adverse patterns—by cause at the national level is essential to reflect effects of public health policy and medical care delivery.4–7GBD 2019 provides an opportunity to incorporate newly available datasets, enhance method performance and standardisation, and reflect changes in scientific understanding. Since GBD 2017,1–3 no comprehensive update of descriptive epidemiology levels and trends has been released, to our knowledge. In this study, we summarise GBD methods and present integrated results on fatal and non-fatal outcomes for the GBD disease and injury hierarchical cause list. GBD 2019 includes estimation of numerous different models for disease and injury outcomes. This Article provides a high-level over-view of our findings. Results are presented both broadly and in detail for a selection of diseases, injuries, and impairments in two-page summaries with a standard set of tables and figures.MethodsOverviewThe general approach to estimating causes of death and disease incidence and prevalence for GBD 2019 is the same as for GBD 2017.2,3 Appendix 1 provides details on the methods used to model each disease and injury. Here, we provide an overview of the methods, with an Research in contextEvidence before this studyThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 reported on incidence, prevalence, and mortality from 359 diseases and injuries. Information on prevalence and mortality was also analysed in terms of summary measures: years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy. GBD is the only comprehensive assessment providing time trends for a mutually exclusive and collectively exhaustive list of diseases and injuries. For the first time, GBD 2017 also produced internally consistent estimates of population, fertility, mortality, and migration by age, sex, and year for 1950–2017. GBD 2017 also included subnational assessments for 16 countries at administrative level 1 and for local authorities in England.Added value of this studyGBD 2019 updates and expands beyond GBD 2017 in ten ways. (1) The number of countries for which subnational assessments have been undertaken was expanded to include Italy, Nigeria, Pakistan, the Philippines, and Poland. (2) 12 new causes were added to the GBD modelling framework, including pulmonary arterial hypertension, nine new sites of cancer, and two new sites of osteoarthritis (hand and other joints). (3) For each disease, the preferred or reference case definition or measurement method was clearly defined and stored in a database. For both risks and diseases, the statistical relationship between the alternative and reference measurement method was analysed using network meta-regression using only data where two different approaches were measured in the same location–time period. Although statistical cross-walking between alternative and reference definitions and measurement methods has been a feature in all GBD studies, the approach in GBD 2019 was highly standardised and used improved methods across diseases and risks. (4) Some prior distributionsused in DisMod-MR, the Bayesian meta-regression tool used to simultaneously estimate incidence, prevalence, remission, excess mortality, and cause-specific mortality, were revised on the basis of simulation studies showing that less informative priors helped to improve the coverage of uncertainty intervals. (5) Redistribution algorithms for sepsis, heart failure, pulmonary embolism, acute kidney injury, hepatic failure, acute respiratory failure, pneumonitis, and five intermediate causes in the central nervous systemwere revised according to an analysis of 116 million deaths that were attributed to multiple causes. (6) Processing of clinical informatics data on hospital and clinic visits was revised to better take into account differential access across locations to health-care facilities. (7) To enhance the stability of models in the presence of the addition of subnational data in different GBD cycles, we adopted a set of standard locations for the estimation of covariate effects in models. (8) 7333 national and 24657 subnational vital registration systems, 16984 published studies, and 1654 household surveys were used in the analysis, including many newly available data sources. (9) Results are presented so as to integrate causes of death, incidence, prevalence, YLDs, YLLs, and DALYs into a comprehensive assessment of each disease and injury. (10) Closer technical coordination with WHO has led to the addition of nine WHO member states to the analysis and revisions of the analytical approach for select diseases.Implications of all the available evidenceGBD 2019 provides the most up-to-date assessment of the descriptive epidemiology of a mutually exclusive and collectively exhaustive list of diseases and injuries for 204 countries and territories from 1990 to 2019. The comprehensive nature of the assessment provides policy-relevant information on the trends of major causes of burden globally, regionally, and by country or territory.See Onlinefor appendix 1
Global Health Metrics1206www.thelancet.comVol 396 October 17, 2020emphasis on the main methodology changes since GBD 2017.For each iteration of GBD, the estimates for the whole time series are updated on the basis of addition of new data and change in methods where appropriate. Thus, the GBD 2019 results supersede those from previous rounds of GBD.GBD 2019 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) statement (appendix 1 section 1.4).8 Analyses were com-pleted with Python version 3.6.2, Stata version 13, and R version 3.5.0. Statistical codeused for GBD estimation is publicly available online.Geographical units, age groups, time periods, and cause levelsGBD 2019 estimated each epidemiological quantity of interest—incidence, prevalence, mortality, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs)—for 23 age groups; males, females, and both sexes combined; and 204 countries and territories that were grouped into 21 regions and seven super-regions. For GBD 2019, nine countries and territories (Cook Islands, Monaco, San Marino, Nauru, Niue, Palau, Saint Kitts and Nevis, Tokelau, and Tuvalu) were added, such that the GBD location hierarchy now includes all WHO member states. GBD 2019 includes subnational analyses for Italy, Nigeria, Pakistan, the Philippines, and Poland, and 16 countries previously estimated at subnational levels (Brazil, China, Ethiopia, India, Indonesia, Iran, Japan, Kenya, Mexico, New Zealand, Norway, Russia, South Africa, Sweden, the UK, and the USA). All subnational analyses are at the first level of admin-istrative organisation within each country except for New Zealand (by Māori ethnicity), Sweden (by Stockholm and non-Stockholm), the UK (by local gov-ernment authorities), and the Philippines (by province). In this publication, we present subnational estimates for Brazil, India, Indonesia, Japan, Kenya, Mexico, Sweden, the UK, and the USA; given space constraints, these results are presented in appendix 2. At the most detailed spatial resolution, we generated estimates for 990 locations. The GBD diseases and injuries analytical framework generated estimates for every year from 1990 to 2019.Diseases and injuries were organised into a levelled cause hierarchy from the three broadest causes of death and disability at Level 1 to the most specific causes at Level 4. Within the three Level 1 causes—communicable, maternal, neonatal, and nutritional diseases; non-commu-nicable diseases; and injuries—there are 22 Level 2 causes, 174 Level 3 causes, and 301 Level 4 causes (including 131 Level 3 causes that are not further disaggregated at Level 4; see appendix 1 sections 3.4 and 4.12 for the full list of causes). 364 total causes are non-fatal and 286 are fatal. For GBD 2019, 12 new causes were added to the modelling framework: pulmonary arterial hypertension, eye cancer, soft tissue and other extraosseous sarcomas, malignant neoplasm of bone and articular cartilage, and neuro-blastoma and other peripheral nervous cell tumours at Level 3, and hepatoblastoma, Burkitt lymphoma, other non-Hodgkin lymphoma, retinoblastoma, other eye can-cers, and two sites of osteoarthritis (hand and other joints) at Level 4.DataThe GBD estimation process is based on identifying multiple relevant data sources for each disease or injury including censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifi-cations, and other sources. Each of these types of data are identified from systematic review of published studies, searches of government and international organisation websites, published reports, primary data sources such as the Demographic and Health Surveys, and contributions of datasets by GBD collaborators. 86249 sources were used in this analysis, including 19354 sources reporting deaths, 31499 reporting incidence, 19773 reporting prev-alence, and 26631 reporting other metrics. Each newly identified and obtained data source is given a unique identifier by a team of librarians and included in the Global Health Data Exchange (GHDx). The GHDx makes publicly available the metadata for each source included in GBD as well as the data, where allowed by the data provider. Readers can use the GHDx source toolto identify which sources were used for estimating any disease or injury outcome in any given location.Data processingA crucial step in the GBD analytical process is correcting for known bias by redistributing deaths from unspecified codes to more specific disease categories, and by adjusting data with alternative case definitions or measurement methods to the reference method. We highlight several major changes in data processing that in some cases have affected GBD results.Cause of death redistributionVital registration with medical certification of cause of death is a crucial resource for the GBD cause of death analysis in many countries. Cause of death data obtained using various revisions of the International Classification of Diseases and Injuries (ICD)9 were mapped to the GBD cause list. Many deaths, however, are assigned to causes that cannot be the underlying cause of death (eg, cardiopulmonary failure) or are inadequately speci-fied (eg, injury from undetermined intent). These deaths were reassigned to the mostprobable underlying causes of death as part of the data processing for GBD. Redistribution algorithms can be divided into three categories: proportionate redistribution, fixed proportion redistribution based on published studies or expert See Onlinefor appendix 2For the GHDx see http://ghdx.healthdata.orgFor the statistical code see http://ghdx.healthdata.org/gbd-2019/codeFor the GHDx source tool see http://ghdx.healthdata.org/gbd-2019/data-input-sources
Global Health Metricswww.thelancet.comVol 396 October 17, 20201207judgment, or statistical algorithms. For GBD 2019, data for 116 million deaths attributed to multiple causes were analysed to produce more empirical redistribution algo-rithms for sepsis,10 heart failure, pulmonary embolism, acute kidney injury, hepatic failure, acute respiratory failure, pneumonitis, and five intermediate causes (hydrocephalus, toxic encephalopathy, compression of brain, encephalopathy, and cerebral oedema) in the central nervous system. To redistribute unspecified injuries, we used a method similar to that of intermediate cause redistribution, using the pattern of the nature of injury codesin the causal chain where the ICD codes X59 (“exposure to unspecified factor”) and Y34 (“unspecified event, undetermined intent”) and GBD injury causes were the underlying cause of death. These new algorithms led to important changes in the causes to which these intermediate outcomes were redistributed. Additionally, data on deaths from diabetes and stroke lack the detail on subtype in many countries; we ran regressions on vital registration data with at least 50% of deaths coded specifically to type 1 or 2 diabetes and ischaemic, haemorrhagic, or subarachnoid stroke to predict deaths by these subtypes when these were coded to unspecified diabetes or stroke.Correcting for non-reference case definitions or measurement methodsIn previous cycles of GBD, data reported using alternative case definitions or measurement methods were corrected to the reference definition or measurement method primarily as part of the Bayesian meta-regression models. For example, in DisMod-MR, the population data were simultaneously modelled as a function of country covar-iates for variation in true rates and as a function of indicator variables capturing alternative measurement methods. To enhance transparency and to standardise and improve methods in GBD 2019, we estimated correction factors for alternative case definitions or measurement methods using network meta-regression, including only data where two methods were assessed in the same location–time period or in the exact same population. This included validation studies where two methods had been compared in populations that were not necessarily random samples of the general popu-lation. Details on the correction factors from alternative to reference measurement methods are provided in appendix 1 (section 4.4.2).Clinical informaticsClinical informatics data include inpatient admissions, outpatient (including general practitioner) visits, and health insurance claims. Several data processing steps were undertaken. Inpatient hospital data with a single diagnosis only were adjusted to account for non-primary diagnoses as well as outpatient care. For each GBD cause that used clinical data, ratios of non-primary to primary diagnosis rates were extracted from claims in the USA, Taiwan (province of China), New Zealand, and the Philippines, as well as USA Healthcare Cost and Utilization Project inpatient data. Ratios of outpatient to inpatient care for each cause were extracted from claims data from the USA and Taiwan (province of China). The log of the ratios for each cause were modelled by age and sex using MR-BRT (Meta-Regression-Bayesian Regularised Trimmed), the Bayesian meta-regression tool. To account for the incomplete health-care access in populations where not every person with a disease or injury would be accounted for in administrative clinical records, we transformed the adjusted admission rates using a scalar derived from the Healthcare Access and Quality Index.11 We used this approach to produce adjusted, standardised clinical data inputs. More details are provided in appendix 1 (section 4.3).ModellingFor most diseases and injuries, processed data are modelled using standardised tools to generate estimates of each quantity of interest by age, sex, location, and year. There are three main standardised tools: Cause of Death Ensemble model (CODEm), spatiotemporal Gaussian process regression (ST-GPR), and DisMod-MR. Previous publications2,3,12 and the appendix provide more details on these general GBD methods. Briefly, CODEm is a highly systematised tool to analyse cause of death data using an ensemble of different modelling methods for rates or cause fractions with varying choices of covariates that perform best with out-of-sample predictive validity testing. DisMod-MR is a Bayesian meta-regression tool that allows evaluation of all available data on incidence, prevalence, remission, and mortality for a disease, enforcing consistency between epidemiological para-meters. ST-GPR is a set of regression methods that borrow strength between locations and over time for single metrics of interest, such as risk factor exposure or mortality rates. In addition, for select diseases, particularly for rarer outcomes, alternative modelling strategies have been developed, which are described in appendix 1 (section 3.2).In GBD 2019, we designated a set of standard locations that included all countries and territories as well as the subnational locations for Brazil, China, India, and the USA. Coefficients of covariates in the three main modelling tools were estimated for these standard locations only—ie, we ignored data from subnational locations other than for Brazil, China, India, and the USA (appendix 1 section 1.1). Using this set of standard locations will prevent changes in regression coefficients from one GBD cycle to the next that are solely due to the addition of new subnational units in the analysis that might have lower quality data or small populations (appendix 1 section 1.1). Changes to CODEm for GBD 2019 included the addition of count models to the model ensemble for rarer causes. We also modified DisMod-MR priors to effectively increase the out-of-sample coverage of
Global Health Metrics1208www.thelancet.comVol 396 October 17, 2020uncertainty intervals (UIs) as assessed in simulation testing (appendix 1 section 4.5).For the cause Alzheimer’s disease and other dementias, we changed the method of addressing large variations between locations and over time in the assignment of dementia as the underlying cause of death. Based on a systematic review of published cohort studies, we estimated the relative risk of death in individuals with dementia. We identified the proportion of excess deaths in patients with dementia where dementia is the under-lying cause of death as opposed to a correlated risk factor (appendix 1 section 2.6.2). We changed the strategy of modelling deaths for acute hepatitis A, B, C, and E from a natural history model relying on inpatient case fatality rates to CODEm models after predicting type-specific acute hepatitis deaths from vital registration data with specified hepatitis type.DisMod-MR was used to estimate deaths from three outcomes (dementia, Parkinson’s, and atrial fibrillation), and to determine the proportions of deaths by underlying aetiologies of cirrhosis, liver cancer, and chronic kidney disease deaths.Socio-demographic Index, annual rate of change, and data presentationThe Socio-demographic Index (SDI) is a composite indicator of a country’s lag-distributed income per capita, average years of schooling, and the fertility rate in females under the age of 25 years (appendix 1 section 6).13For changes over time, we present annualised rates of change as the difference in the natural log of the values at the start and end of the time interval divided by the number of years in the interval. We examine the relationship between SDI and the annualised rate of change in age-standardised DALY rates for all causes, apart from HIV/AIDS, natural disasters, and war and conflict, by country or territory, for the time periods 1990–2010 and 2010–19. We deliberately subtracted out DALYs due to HIV/AIDS because their magnitude in some parts of the world would have obscured the trends in all other causes; we also subtracted out DALY rates from natural disasters and war and conflict to avoid trends in disease burden in some countries being dominated by these sudden and dramatic changes. As a measure of the epidemiological transition, we present the ratio of YLDs due to non-communicable diseases and injuries, and due to total burden in DALYs. We present 95% UIs for every metric based on the 25th and 975th ordered values of 1000 draws of the posterior distribution.Role of the funding sourceThe funders of this study had no role in study design, data collection, data analysis, data interpretation, or the writing of the report. The corresponding author had full access to the data in the study and final responsibility for the decision to submit for publication.ResultsGlobal trendsBetween 1990 and 2019, the number of global DALYs remained almost constant, but once the effects of population growth and ageing were removed by con-verting counts to age-standardised rates, there were clear improvements in overall health (figure 1). Over the past decade, the pace of decline in global age-standardised DALY rates accelerated in age groups younger than 50 years compared with the 1990–2010 time period (table). The annualised rate of decline was greatest in the 0–9-year age group. In the population aged 50 years and older, the rate of change was slower from 2010 to 2019 compared with the earlier time period.These general trends are made up of complex trends for specific diseases and injuries. Overall trends in the number of DALYs across the different age groups between 1990 and 2019 are driven by some key diseases and injuries (figure 2). The ten most important drivers of increasing burden(ie, the causes that had the largest absolute increases in number of DALYs between 1990 and 2019) include six causes that largely affect older adults (ischaemic heart disease, diabetes, stroke, chronic kidney disease, lung cancer, and age-related hearing loss), whereas the other four causes (HIV/AIDS, other musculoskeletal disorders, low back pain, and depressive disorders) are common from teenage years into old age (figure 2). Despite these ten conditions contributing the largest number of additional DALYs over the 30-year period, only HIV/AIDS, other musculoskeletal disorders, and diabetes saw large increases in age-standardised DALY rates, with an increase of 58·5% (95% UI 37·1–89·2) for HIV/AIDS, 30·7% (27·6–34·3) for other musculoskeletal disorders, and 24·4% (18·5–29·7) for diabetes. The burden of HIV/AIDS, however, peaked in 2004 and has dropped substantially after the global scale-up of antiretroviral treatment (ART). The changes in age-standardised rates for chronic kidney disease, age-related hearing loss, and Figure 1: Global DALYs and age-standardised DALY rates, 1990–2019Shaded sections indicate 95% uncertainty intervals. DALY=disability-adjusted life-year.010002000DALY count (millions)Age-standardised DALY rate300001000020000300004000050000600001990200020102019YearAge-standardised DALY rateDALY count
Global Health Metricswww.thelancet.comVol 396 October 17, 20201209depressive disorders were small (figure 2). Substantial declines in age-standardised rates were seen in ischaemic heart disease (28·6%, 95% UI 24·2–33·3), stroke (35·2%, 30·5–40·5), and lung cancer (16·1%, 8·2–24·0).The ten most important contributors to declining burden (ie, the causes that had the largest absolute decreases in number of DALYs between 1990 and 2019) include nine that predominantly affect children (lower respiratory infections, diarrhoeal diseases, neonatal dis-orders, measles, protein-energy malnutrition, congenital birth defects, drowning, tetanus, and malaria), as well as tuberculosis, which largely affects adults. All of these causes with declining burden also had substantial decreases in age-standardised DALY rates, ranging from 32·6% (21·2–42·1) decline for neonatal disorders to 90·4% (87·5–92·8) decline for measles, not just decreases in the absolute number of DALYs due to demographic changes (figure 2A). Although most of the ten leading Level 3 causes of DALYs were the same for both sexes in 2019, road injuries (ranked fourth for males), cirrhosis (ninth), and lung cancer (tenth) were in the top ten for males only, and were replaced by low back pain (ranked sixth for females), gynaecological diseases (ninth), and headache disorders (tenth) for females (appendix 2 figure S5 and tables S2–5, S7, S8, S12, S13, S16). Congenital defects were ranked tenth for both sexes combined in 2019 but did not make the top ten for either sex separately.The burden for children younger than 10 years declined profoundly between 1990 and 2019, by 57·5% (95% UI 50·3–63·1). Key drivers of this progress included large reductions in major infectious diseases affecting children—namely, lower respiratory infections, diarrhoeal diseases, and meningitis, each of which declined by more than 60% between 1990 and 2019 (figure 2). In 2019, neonatal disorders were the leading cause of burden in this age group, accounting for 32·4% (30·7–34·1) of the group’s global DALYs, increasing from 23·0% (22·0–24·1) in 1990. Six infectious diseases were also among the top ten causes of burden in children: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which were fully accounted for by congenital syphilis in this age group; tenth). Congenital birth defects (ranked fourth) as well as two nutritional disorders—dietary iron deficiency (seventh) and protein-energy malnutrition (eighth)—completed the top ten. The percentage change in age-standardised DALY rates for eight of the tenleading causes was large, ranging from a 35·4% (23·8–44·8) decline for neonatal disorders to 78·3% (69·9–85·5) decline for protein-energy malnutrition over the study period. The decreases for the remaining two top-ten causes, sexually transmitted infections and dietary iron deficiency, were much more modest. Sub-Saharan Africa experienced nearly half of the total DALYs (49·9% [47·6–52·3]) for this age group in 2019.The change in disease burden in adolescents aged 10–24 years was much more modest (figure 2). DALYs declined by 6·2% (95% UI 2·1–10·5) overall between 1990 and 2019. DALYs for non-communicable diseases increased by 13·1% (9·5–16·3), whereas injuries declined by 24·8% (19·7–29·3) and infectious diseases by 18·7% (13·4–24·0). Three injury causes were among the top ten causes of global DALYs in this age group in 2019: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth; figure 2). Headache disorders, two mental disorders (depression and anxiety), low back pain, dietary iron deficiency, HIV/AIDS, and diarrhoeal disease were the other causes in the top ten for adolescents. Among the top ten causes in this age group, age-standardised DALY rates for road injuries, self-harm, and diarrhoeal diseases decreased by more than a third each between 1990 and 2019. As in the 0–9-year age group, the large increase in burden due to HIV/AIDS in the 10–24-year age group reflects a rapid increase in the first half of the study period followed by a decline after the global scale-up of ART; despite declining in recent years, the HIV/AIDs burden has not yet returned to 1990 levels. The other causes in the top ten showed small or insignificant change (figure 2). The sex differences in the top ten rankings are striking. The three previously mentioned injuries were the top-ranked causes of DALYs among male adolescents (appendix 2 figure S9), whereas headaches, depressive disorders, and anxiety disorders were the top three causes of DALYs among females (appendix 2 figure S10). DALYs 2019Annualised rate of change, 1990–2010Annualised rate of change, 2010–19Count (millions)Age-standardised rate (per 100000)DA LYsAge-standardised rateDA LYsAge-standardised rate0–9 years531 (458 to 621)19125·7 (16495·1 to 22382·5)−2·3% (−2·5 to −2·2)−2·5% (−2·6 to −2·3)−3·7% (−4·4 to −2·9)−4·0% (−4·7 to −3·2)10–24 years229 (194 to 270)12313·0 (10399·9 to 14478·3)0·2% (0·1 to 0·2)−0·7% (−0·8 to −0·6)−1·1% (−1·4 to −0·9)−1·3% (−1·5 to −1·1)25–49 years616 (533 to 709)22691·2 (19613·7 to 26116·3)1·4% (1·4 to 1·5)−0·4% (−0·4 to −0·3)−0·0% (−0·2 to 0·1)−1·2% (−1·4 to −1·0)50–74 years832 (752 to 919)28263·2 (25527·6 to 31213·4)1·3% (1·2 to 1·3)−1·0% (−1·0 to −0·9)2·0% (1·8 to 2·1)−0·9% (−1·1 to −0·8)≥75 years329 (308 to 351)77320·5 (72372·5 to 82440·3)2·2% (2·2 to 2·2)−0·9% (−0·9 to −0·9)2·3% (2·3 to 2·4)−0·8% (−0·9 to −0·8)All ages2540 (2290 to 2810)32801·7 (29535·1 to 36319·5)−0·0% (−0·1 to 0·0)−1·4% (−1·5 to −1·3)−0·2% (−0·4 to 0·0)−1·3% (−1·5 to −1·1)DALY=disability-adjusted life-year.Table: Global DALYs in 2019 and annualised rate of change in DALYs and age-standardised DALY rates over 1990–2010 and 2010–19, by age group and for all ages
Global Health Metrics1210www.thelancet.comVol 396 October 17, 2020(Figure 2 continues on next page)Leading causes 1990Percentage of DALYs1990Leading causes 2019Percentage of DALYs2019Percentage change innumber of DALYs,1990–2019Percentage change inage-standardised DALY rate, 1990–2019A All agesB0–9 yearsCommunicable, maternal, neonatal, and nutritional diseases Non-communicable diseases Injuries1 Neonatal disorders10·6 (9·9 to 11·4)1 Neonatal disorders7·3 (6·4 to 8·4)2 Lower respiratory infections8·7 (7·6 to 10·0)2 Ischaemic heart disease7·2 (6·5 to 7·9)3 Diarrhoeal diseases7·3 (5·9 to 8·8)3 Stroke5·7 (5·1 to 6·2)4 Ischaemic heart disease4·7 (4·4 to 5·0)4 Lower respiratory infections3·8 (3·3 to 4·3)5 Stroke4·2 (3·9 to 4·5)5 Diarrhoeal diseases3·2 (2·6 to 4·0)6 Congenital birth defects3·2 (2·3 to 4·8)6 COPD2·9 (2·6 to 3·2)7 Tuberculosis3·1 (2·8 to 3·4)7 Road injuries2·9 (2·6 to 3·0)–31·0 (–37·1 to –25·4)8 Road injuries2·7 (2·6 to 3·0)8 Diabetes2·8 (2·5 to 3·1)9 Measles2·7 (0·9 to 5·6)9 Low back pain2·5 (1·9 to 3·1)10 Malaria2·5 (1·4 to 4·1)10 Congenital birth defects2·1 (1·7 to 2·6)11 COPD2·3 (1·9 to 2·5)2·0 (1·6 to 2·7)11 HIV/AIDS1·9 (1·6 to 2·2)12 Protein-energy malnutrition12 Tuberculosis1·9 (1·7 to 2·0)13 Low back pain1·7 (1·2 to 2·1)13 Depressive disorders14 Self-harm1·4 (1·2 to 1·5)14 Malaria1·8 (0·9 to 3·1)15 Cirrhosis1·3 (1·2 to 1·5)15 Headache disorders16 Meningitis1·3 (1·1 to 1·5)16 Cirrhosis1·8 (1·6 to 2·0)17 Drowning1·3 (1·1 to 1·4)1·1 (0·2 to 2·4)1·1 (0·8 to 1·5)17 Lung cancer1·8 (1·6 to 2·0)18 Headache disorders18 Chronic kidney disease19 Depressive disorders19 Other musculoskeletal20 Diabetes1·1 (1·0 to 1·2)20 Age-related hearing loss21 Lung cancer1·0 (1·0 to 1·1)21 Falls1·5 (1·4 to 1·7)22 Falls1·0 (0·9 to 1·2)1·0 (0·7 to 1·3)0·9 (0·9 to 1·0)22 Self-harm1·3 (1·2 to 1·5)–38·9 (–44·3 to –33·0)23 Dietary iron deficiency23 Gynaecological diseases1·2 (0·9 to 1·5)24 Interpersonal violence24 Anxiety disorders1·1 (0·8 to 1·5)25 Whooping cough0·9 (0·4 to 1·7)0·8 (0·6 to 1·1)0·8 (0·8 to 0·9)25 Dietary iron deficiency27 Age-related hearing loss26 Interpersonal violence–23·8 (–28·6 to –17·8)29 Chronic kidney disease40 Meningitis0·6 (0·5 to 0·8)30 HIV/AIDS0·8 (0·6 to 1·0)41 Protein-energy malnutrition32 Gynaecological diseases0·8 (0·6 to 1·0)46 Drowning0·5 (0·5 to 0·6)34 Anxiety disorders0·7 (0·5 to 1·0)0·7 (0·5 to 1·0)55 Whooping cough0·4 (0·2 to 0·7)35 Other musculoskeletal71 Measles0·3 (0·1 to 0·6)1 Neonatal disorders23·0 (22·0 to 24·1)1 Neonatal disorders32·4 (30·7 to 34·1)2 Lower respiratory infections17·0 (14·9 to 19·7)2 Lower respiratory infections11·6 (10·5 to 12·6)3 Diarrhoeal diseases13·1 (10·7 to 15·1)3 Diarrhoeal diseases9·3 (7·9 to 10·8)4 Congenital birth defects 6·6 (4·6 to 10·0)4 Congenital birth defects 8·6 (7·4 to 10·7)5 Measles5·7 (2·0 to 11·8)5 Malaria6·4 (3·3 to 10·8)6 Malaria4·6 (2·5 to 7·5)4·1 (3·1 to 5·5)6 Meningitis2·1 (1·8 to 2·5)7 Protein-energy malnutrition7 Dietary iron deficiency–8·2 (–12·3 to –4·1)8 Meningitis2·3 (2·0 to 2·7)8 Protein-energy malnutrition9 Whooping cough1·9 (0·8 to 3·8)9 Whooping cough1·9 (0·9 to 3·3)10 Drowning1·8 (1·5 to 2·1)10 STIs1·4 (0·5 to 2·8)11 Tuberculosis1·8 (1·5 to 2·1)11 Measles1·3 (0·4 to 2·7)12 Tetanus1·7 (1·4 to 1·9)12 Road injuries1·1 (1·0 to 1·4)13 Road injuries1·3 (1·1 to 1·5)0·9 (0·6 to 1·3)13 Tuberculosis1·0 (0·9 to 1·2)14 Dietary iron deficiency14 HIV/AIDS1·0 (0·9 to 1·2)15 STIs0·7 (0·2 to 1·5)15 iNTS1·0 (0·6 to 1·5)16 Typhoid and paratyphoid0·7 (0·3 to 1·3)16 Drowning0·9 (0·8 to 1·1)17 Foreign body0·6 (0·5 to 0·7)17 Haemoglobinopathies0·9 (0·7 to 1·0)18 HIV/AIDS0·6 (0·5 to 0·7)18 Typhoid and paratyphoid0·8 (0·4 to 1·5)19 Encephalitis0·5 (0·4 to 0·7)19 Asthma0·5 (0·4 to 0·8)20 Acute hepatitis0·5 (0·4 to 0·5)20 Foreign body0·5 (0·4 to 0·5)21 Haemoglobinopathies0·4 (0·3 to 0·6)21 EMBID0·5 (0·4 to 0·6)22 Leukaemia0·4 (0·3 to 0·6)22 Sudden infant death0·5 (0·2 to 1·0)23 Sudden infant death0·4 (0·2 to 0·9)23 Idiopathic epilepsy0·5 (0·3 to 0·6)24 Asthma0·4 (0·3 to 0·5)24 Other unspecified infectious25 Falls0·4 (0·3 to 0·5)25 Dermatitis0·4 (0·2 to 0·7)–6·0 (–6·9 to –5·1)28 Idiopathic epilepsy0·3 (0·2 to 0·4)0·3 (0·2 to 0·4)26 Leukaemia0·4 (0·4 to 0·5)30 Other unspecified infectious27 Falls0·4 (0·3 to 0·5)33 iNTS0·3 (0·1 to 0·4)28 Encephalitis0·4 (0·3 to 0·5)34 EMBID0·3 (0·2 to 0·3)32 Tetanus0·3 (0·3 to 0·5)44 Dermatitis0·2 (0·1 to 0·3)39 Acute hepatitis0·3 (0·2 to 0·3)–35·4 (–44·8 to –23·8)–69·6 (–76·3 to –61·6)–68·5 (–75·9 to –58·4)–40·1 (–55·1 to –17·9)–38·5 (–63·1 to –6·5)–61·0 (–69·2 to –51·1)–78·3 (–85·5 to –69·9)–53·2 (–75·6 to –20·4)–14·9 (–30·1 to 2·5)–90·5 (–92·9 to –87·6)–63·7 (–70·8 to –48·8)–75·5 (–80·6 to –69·2)–25·0 (–35·3 to –13·6)61·4 (20·6 to 109·3)–79·0 (–82·6 to –72·2)–13·7 (–34·3 to 14·7)–50·7 (–62·5 to –36·9)–37·5 (–50·0 to –21·5)–63·6 (–70·2 to –57·1)–22·1 (–36·1 to –6·0)–46·9 (–61·7 to –30·0)–34·0 (–49·1 to –3·8)–29·3 (–50·3 to 3·3)–55·3 (–69·5 to –37·0)–48·3 (–68·7 to –22·6)–68·5 (–77·9 to –50·2)–91·2 (–93·8 to –85·6)–74·1 (–82·6 to –61·1)–36·2 (–45·4 to –24·7)–69·1 (–75·9 to –60·9)–67·8 (–75·3 to –57·2)–41·6 (–54·6 to –17·4)–36·9 (–61·4 to –2·2)–59·7 (–68·1 to –49·3)–0·8 (–5·3 to 3·6)–78·1 (–85·0 to –68·9)–54·7 (–74·7 to –17·3)–16·3 (–30·7 to 1·7)–90·0 (–92·6 to –86·9)–61·5 (–68·7 to –45·0)–74·5 (–79·8 to –67·8)–18·6 (–35·6 to 3·6)68·3 (27·4 to 121·2)–77·6 (–81·3 to –70·1)–10·3 (–30·3 to 22·5)–46·7 (–59·1 to –31·1)–32·2 (–46·2 to –14·5)–62·9 (–69·6 to –56·2)–18·9 (–33·3 to –0·9)–50·6 (–61·6 to –29·8)–30·7 (–45·8 to 3·6)–28·4 (–48·3 to 7·8)2·7 (1·7 to 3·7)–54·8 (–67·7 to –32·9)–47·2 (–67·0 to –18·0)–67·6 (–76·7 to –47·6)–91·3 (–93·8 to –85·6)–73·1 (–81·7 to –59·1)2·0 (1·3 to 2·9)2·0 (1·7 to 2·3)0·4 (0·3 to 0·6)–57·2 (–64·4 to –48·6)–74·5 (–82·0 to –64·5)–68·2 (–71·9 to –62·8)–56·3 (–75·6 to –20·3)–90·4 (–92·8 to –87·5)–6·8 (–8·7 to –4·9)–0·1 (–1·0 to 0·7)–16·4 (–18·7 to –14·0)–14·5 (–22·5 to –7·4)–1·8 (–3·7 to –0·1)30·7 (27·6 to 34·3)6·3 (0·2 to 12·4)–16·2 (–24·0 to –8·2)–26·8 (–32·5 to –19·0)1·1 (–4·2 to 2·9)–37·8 (–61·9 to –6·2)–1·8 (–2·9 to –0·8)–62·8 (–66·6 to –58·0)58·5 (37·1 to 89·2)–40·0 (–52·7 to –17·1)–16·3 (–17·1 to –15·5)24·4 (18·5 to 29·7)–39·8 (–44·9 to –30·2)–64·6 (–71·7 to –54·2)–62·5 (–69·0 to –54·9)–35·2 (–40·5 to –30·5)–28·6 (–33·3 to –24·2)–32·6 (–42·1 to –21·2)–32·3 (–41·7 to –20·8)50·4 (39·9 to 60·2)32·4 (22·0 to 42·2)–56·7 (–64·2 to –47·5)–57·5 (–66·2 to –44·7)25·6 (15·1 to 46·0)2·4 (–6·9 to 10·8)147·9 (135·9 to 158·9)46·9 (43·3 to 50·5)–37·3 (–50·6 to –12·8)127·7 (97·3 to 171·7)–41·0 (–47·2 to –33·5)61·1 (56·9 to 65·0)–29·4 (–56·9 to 6·6)56·7 (52·4 to 62·1)33·0 (22·4 to 48·2)69·1 (53·1 to 85·4)93·2 (81·6 to 105·0)128·9 (122·0 to 136·3)82·8 (75·2 to 88·9)47·1 (31·5 to 61·0)–5·6 (–14·2 to 3·7)48·7 (45·8 to 51·8)53·7 (48·8 to 59·1)13·8 (10·5 to 17·2)1·1 (0·8 to 1·5)1·6 (1·2 to 2·1)1·6 (1·2 to 2·1)1·6 (1·5 to 1·8)1·8 (0·4 to 3·8)1·8 (1·4 to 2·4)–89·8 (–92·3 to –86·8)–54·5 (–74·6 to –16·9)–60·6 (–65·2 to –53·6)–71·1 (–79·6 to –59·7)–51·3 (–59·4 to –42·0)10·2 (3·2 to 19·2)1·1 (1·0 to 1·2)0·6 (0·5 to 0·7)
Global Health Metricswww.thelancet.comVol 396 October 17, 20201211Maternal disorders, gynaecological disorders, and dietary iron deficiency were also in the top ten causes for females in this relatively young age group (appendix 2 figure S10).Five causes that were in the top ten for ages 10–24 in 2019 were also in the top ten in the 25–49 age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth; figure 2). Tuberculosis and four non-communicable causes—ischaemic heart disease, gynae-cological disorders, other musculoskeletal disorders, and stroke—completed the top ten rankings. There were substantial improvements since 1990 in DALY rates of (Figure 2 continues on next page)Leading causes 1990Percentage of DALYs1990Leading causes 2019Percentage of DALYs2019Percentage change innumber of DALYs,1990–2019Percentage change inage-standardised DALY rate, 1990–2019C10–24 yearsD25–49 yearsCommunicable, maternal, neonatal, and nutritional diseases Non-communicable diseases Injuries1 Road injuries7·8 (6·9 to 8·8)1 Road injuries6·6 (5·6 to 7·7)2 Self-harm4·9 (4·1 to 5·6)2 Headache disorders5·0 (0·6 to 10·9)3 Headache disorders3·8 (0·4 to 8·2)3 Self-harm3·7 (3·1 to 4·5)4 Tuberculosis3·6 (3·1 to 4·1)4 Depressive disorders3·7 (2·6 to 5·0)5 Diarrhoeal diseases3·2 (2·1 to 4·9)5 Interpersonal violence–15·4 (–21·3 to –7·9)6 Interpersonal violence6 Anxiety disorders3·3 (2·3 to 4·4)7 Maternal disorders3·0 (2·6 to 3·4)7 Low back pain3·2 (2·2 to 4·3)–12·0 (–13·3 to –10·6)8 Depressive disorders2·8 (2·0 to 3·9)8 Dietary iron deficiency–3·5 (–9·5 to 2·0)9 Low back pain2·8 (1·9 to 3·8)9 HIV/AIDS2·6 (1·9 to 3·5)10 Drowning2·7 (2·3 to 3·2)10 Diarrhoeal diseases2·6 (1·9 to 3·6)11 Typhoid and paratyphoid2·6 (1·2 to 4·9)11 Neonatal disorders2·3 (1·8 to 2·8)12 Anxiety disorders2·6 (1·8 to 3·5)12 Tuberculosis2·1 (1·8 to 2·5)13 Dietary iron deficiency13 Gynaecological diseases1·9 (1·4 to 2·6)14 Malaria2·1 (1·3 to 3·3)14 Typhoid and paratyphoid1·8 (0·8 to 3·3)15 Lower respiratory infections1·7 (1·4 to 2·0)15 Maternal disorders1·8 (1·5 to 2·2)16 Conflict and terrorism 1·5 (1·3 to 1·9)16 Malaria1·8 (1·0 to 3·0)17 Gynaecological diseases1·5 (1·1 to 2·1)17 Conduct disorder1·8 (1·1 to 2·6)18 Falls1·5 (1·3 to 1·6)18 Drug use disorders1·6 (1·3 to 2·1)19 Congenital birth defects1·5 (1·3 to 1·7)19 Acne vulgaris1·6 (1·0 to 2·4)20 Idiopathic epilepsy1·4 (1·1 to 1·8)20 Idiopathic epilepsy1·6 (1·2 to 2·1)–11·4 (–22·8 to 4·6)21 Conduct disorder1·3 (0·8 to 2·0)21 Congenital birth defects 1·5 (1·3 to 1·7)–21·2 (–29·7 to –10·5)22 Drug use disorders1·3 (1·0 to 1·6)22 Falls1·4 (1·3 to 1·6)–23·9 (–30·9 to –16·7)23 Asthma1·2 (1·0 to 1·6)23 Drowning1·4 (1·2 to 1·7)24 Stroke1·2 (1·0 to 1·3)24 Lower respiratory infections1·4 (1·2 to 1·7)25 Meningitis1·1 (1·0 to 1·3)25 Age-related hearing loss27 Acne vulgaris1·1 (0·7 to 1·6)27 Asthma1·3 (1·0 to 1·8)–18·0 (–23·8 to –12·4)28 Age-related hearing loss30 Stroke1·1 (0·9 to 1·3)33 HIV/AIDS0·9 (0·6 to 1·5)34 Meningitis0·9 (0·7 to 1·1)35 Neonatal disorders0·9 (0·7 to 1·1)46 Conflict and terrorism 0·6 (0·5 to 0·8)1 Road injuries5·6 (5·1 to 6·1)1 Road injuries5·1 (4·6 to 5·7)2 Tuberculosis5·5 (4·8 to 6·2)2 HIV/AIDS4·8 (4·0 to 5·9)3 Ischaemic heart disease4·4 (3·8 to 4·9)3 Ischaemic heart disease4·7 (4·0 to 5·4)4 Low back pain3·9 (2·9 to 5·1)4 Low back pain3·9 (2·9 to 5·0)5 Self-harm3·8 (3·3 to 4·4)5 Headache disorders3·7 (0·8 to 7·7)6 Stroke3·5 (3·1 to 3·9)6 Depressive disorders3·5 (2·5 to 4·5)7 Headache disorders3·1 (0·7 to 6·4)7 Gynaecological diseases3·3 (2·5 to 4·2)8 Depressive disorders3·0 (2·2 to 3·9)8 Other musculoskeletal9 Cirrhosis2·8 (2·5 to 3·2)9 Stroke3·2 (2·8 to 3·6)–31·0 (–37·9 to –24·6)10 Gynaecological diseases2·8 (2·2 to 3·7)10 Tuberculosis3·0 (2·6 to 3·4)11 Maternal disorders2·6 (2·3 to 2·9)11 Self-harm2·9 (2·4 to 3·4)–37·2 (–43·2 to –30·9)12 Interpersonal violence12 Cirrhosis2·8 (2·4 to 3·2)13 HIV/AIDS2·3 (1·6 to 3·2)13 Interpersonal violence14 Other musculoskeletal14 Diabetes2·2 (1·9 to 2·5)15 Diarrhoeal diseases2·0 (1·3 to 3·1)15 Anxiety disorders2·0 (1·4 to 2·7)16 Falls1·8 (1·6 to 2·0)16 Drug use disorders1·9 (1·5 to 2·2)17 Anxiety disorders1·7 (1·2 to 2·2)17 Falls1·8 (1·6 to 2·0)18 Alcohol use disorders18 Chronic kidney disease19 Neck pain1·3 (0·9 to 2·0)19 Neck pain1·6 (1·1 to 2·4)20 Diabetes1·3 (1·2 to 1·5)20 Alcohol use disorders21 Chronic kidney disease21 Age-related hearing loss22 Drug use disorders1·3 (1·0 to 1·6)22 Schizophrenia1·5 (1·1 to 1·9)23 Schizophrenia1·3 (0·9 to 1·6)23 Maternal disorders1·4 (1·2 to 1·6)24 Age-related hearing loss24 Diarrhoeal diseases1·3 (1·0 to 1·9)25 Lower respiratory infections1·2 (1·1 to 1·4)25 Oral disorders1·2 (0·7 to 2·1)32 Oral disorders1·0 (0·5 to 1·6)27 Lower respiratory infections1·2 (1·0 to 1·4)–23·1 (–30·2 to –16·0)2·8 (0·5 to 5·1)–46·2 (–59·0 to –29·6)–53·4 (–60·5 to –47·2)–0·9 (–2·0 to 0·2)–0·5 (–3·1 to 1·9)–20·9 (–24·2 to –17·9)–3·6 (–6·0 to –1·5)0·7 (–7·3 to 8·4)–18·0 (–23·4 to –13·5)25·4 (19·3 to 31·6)1·1 (0·0 to 2·1)29·2 (21·1 to 36·0)–24·4 (–29·0 to –19·0)–23·8 (–30·1 to –15·1)–55·5 (–60·2 to –50·5)26·7 (23·4 to 30·5)–4·5 (–6·3 to –2·5)–4·9 (–6·4 to –3·4)0·2 (–3·7 to 2·3)–19·2 (–20·5 to –18·0)–18·5 (–26·7 to –10·1)72·2 (52·4 to 91·9)–22·5 (–30·1 to –16·2)–68·5 (–71·6 to –65·1)–38·3 (–45·0 to –30·4)–27·6 (–34·8 to –19·4)–1·2 (–5·7 to 3·2)–34·1 (–41·6 to –25·5)–58·8 (–63·2 to –53·9)18·1 (16·7 to 19·5)0·6 (–4·8 to 6·2)4·4 (2·3 to 6·3)–31·9 (–59·0 to –3·6)–52·5 (–60·2 to –45·3)–46·2 (–54·9 to –38·5)–1·4 (–4·2 to 1·0)–53·8 (–59·1 to –47·7)103·6 (78·4 to 128·5)–37·0 (–50·2 to –17·0)112·8 (84·3 to 141·9)–2·0 (–3·8 to –0·1)0·0 (–2·8 to 2·4)–40·5 (–47·2 to –32·8)3·3 (0·2 to 5·6)–33·6 (–40·4 to –27·7)–20·1 (–28·3 to –12·9)24·6 (20·6 to 27·1)–28·4 (–36·3 to –18·9)20·7 (17·4 to 23·5)2·1 (–5·0 to 11·1)17·9 (15·7 to 20·3)6·0 (4·4 to 7·6)15·9 (8·6 to 22·4)159·0 (115·4 to 211·1)–25·7 (–40·1 to –0·3)143·6 (114·3 to 174·6)–44·3 (–50·7 to –36·9)19·1 (15·8 to 22·0)–35·5 (–46·0 to –26·4)–42·7 (–51·9 to –33·8)–19·4 (–50·8 to 15·8)24·7 (22·2 to 27·0)21·8 (15·2 to 28·7)41·5 (39·8 to 43·2)6·5 (–7·1 to 25·7)–5·6 (–15·6 to 7·4)–8·4 (–16·9 to 0·4)–50·7 (–55·9 to –44·7)–20·9 (–29·9 to –10·5)18·6 (13·4 to 24·2)1·3 (0·9 to 1·8)2·6 (1·9 to 3·4)3·5 (2·9 to 4·1)–1·1 (–8·3 to 5·1)–12·8 (–21·5 to –2·9)–26·0 (–34·0 to –16·4)–62·1 (–65·7 to –57·9)23·2 (11·1 to 33·2)176·2 (131·1 to 244·3)42·7 (28·4 to 57·3)33·0 (29·2 to 36·9)61·2 (56·5 to 64·5)53·2 (49·3 to 56·8)52·7 (49·7 to 56·0)107·1 (101·0 to 114·3)19·9 (8·0 to 31·1)–27·0 (–34·7 to –18·7)–0·9 (–10·3 to 9·1)29·6 (19·0 to 44·5)18·1 (10·7 to 26·5)123·9 (110·1 to 135·3)61·6 (57·5 to 65·4)92·0 (82·7 to 102·5)34·4 (25·8 to 41·7)67·3 (53·9 to 80·3)60·2 (52·4 to 67·9)28·2 (22·9 to 33·2)64·3 (58·7 to 69·1)59·6 (57·5 to 61·9)–28·9 (–39·6 to –19·2)–13·5 (–32·6 to 15·5)70·7 (66·4 to 74·1)1·5 (1·1 to 2·1)1·6 (1·3 to 1·9)1·6 (1·4 to 1·8)2·3 (2·0 to 2·6)3·2 (2·3 to 4·2)26·8 (15·2 to 38·5)3·2 (2·8 to 3·6)2·1 (1·6 to 2·8)1·1 (0·7 to 1·5)2·5 (2·3 to 2·8)2·0 (1·5 to 2·8)1·7 (1·4 to 2·0)1·3 (0·9 to 1·7)1·3 (1·2 to 1·4)
Global Health Metrics1212www.thelancet.comVol 396 October 17, 2020Figure 2: Leading 25 Level 3 causes of global DALYs and percentage of total DALYs (1990 and 2019), and percentage change in number of DALYs and age-standardised DALY rates from 1990 to 2019 for both sexes combined for all ages (A), children younger than 10 years (B), and ages 10–24 years (C), 25–49 years (D), 50–74 years (E), and 75 years and older (F)Causes are connected by lines between time periods; solid lines are increases in rank and dashed lines are decreases. Age-related hearing loss=age-related and other hearing loss. Alzheimer’s disease=Alzheimer’s disease and other dementias. Atrial fibrillation=atrial fibrillation and flutter. Cirrhosis=cirrhosis and other chronic liver diseases. COPD=chronic obstructive pulmonary disease. EMBID=endocrine, metabolic, blood, and immune disorders. DALY=disability-adjusted life-year. iNTS=invasive non-typhoidal salmonella. Haemoglobinopathies=haemoglobinopathies and haemolytic anaemias. Lung cancer=tracheal, bronchus, and lung cancer. Other musculoskeletal=other musculoskeletal disorders. Other unspecified infectious=other unspecified infectious diseases. Sudden infant death=sudden infant death syndrome. STI=sexually transmitted infections excluding HIV.Leading causes 1990Percentage of DALYs1990Leading causes 2019Percentage of DALYs2019Percentage change innumber of DALYs,1990–2019Percentage change inage-standardised DALY rate, 1990–2019E50–74 yearsF75 years and olderCommunicable, maternal, neonatal, and nutritional diseases Non-communicable diseases Injuries1 Ischaemic heart disease12·5 (11·6 to 13·4)1 Ischaemic heart disease11·8 (10·7 to 12·9)2 Stroke10·9 (10·0 to 11·8)2 Stroke9·3 (8·5 to 10·1)3 COPD6·5 (5·5 to 7·1)3 Diabetes5·1 (4·6 to 5·7)4 Tuberculosis4·0 (3·6 to 4·4)4 COPD4·7 (4·2 to 5·2)–45·9 (–51·4 to –36·2)5 Lung cancer3·6 (3·3 to 3·9)5 Lung cancer3·9 (3·4 to 4·3)6 Diabetes3·1 (2·8 to 3·4)6 Low back pain3·1 (2·3 to 4·0)7 Cirrhosis2·8 (2·6 to 3·1)7 Cirrhosis2·7 (2·4 to 3·0)8 Low back pain2·8 (2·1 to 3·7)8 Chronic kidney disease9 Diarrhoeal diseases2·6 (1·6 to 4·0)9 Age-related hearing loss10 Stomach cancer2·4 (2·2 to 2·6)10 Road injuries2·1 (1·9 to 2·3)11 Road injuries1·9 (1·8 to 2·0)11 Other musculoskeletal12 Lower respiratory infections1·8 (1·6 to 2·0)12 Tuberculosis1·9 (1·7 to 2·1)13 Age-related hearing loss13 Lower respiratory infections1·8 (1·6 to 1·9)14 Chronic kidney disease14 Depressive disorders15 Asthma1·5 (1·2 to 1·9)15 Colorectal cancer1·7 (1·6 to 1·9)16 Hypertensive heart disease16 Falls1·7 (1·5 to 2·0)17 Falls1·4 (1·3 to 1·6)17 Stomach cancer1·7 (1·5 to 1·9)–48·1 (–536 to –42·0)18 Colorectal cancer1·4 (1·3 to 1·5)18 Osteoarthritis1·5 (0·8 to 2·9)19 Depressive disorders19 Blindness and vision loss20 Blindness and vision loss20 Breast cancer1·4 (1·3 to 1·5)21 Liver cancer1·2 (1·0 to 1·3)21 Diarrhoeal diseases1·4 (0·9 to 2·1)22 Breast cancer1·2 (1·1 to 1·2)22 Hypertensive heart disease23 Oesophageal cancer1·1 (0·9 to 1·2)23 Headache disorders24 Osteoarthritis1·1 (0·6 to 2·2)24 Oral disorders1·2 (0·8 to 1·8)25 Self-harm1·1 (1·0 to 1·2)25 Neck pain1·1 (0·7 to 1·7)26 Other musculoskeletal27 Oesophageal cancer1·0 (0·9 to 1·1)28 Oral disorders1·0 (0·6 to 1·5)28 Asthma1·0 (0·8 to 1·1)29 Headache disorders29 Liver cancer0·9 (0·8 to 1·0)–39·9 (–48·5 to –29·5)32 Neck pain0·8 (0·5 to 1·2)31 Self-harm0·9 (0·8 to 1·0)1 Ischaemic heart disease18·6 (17·1 to 19·7)1 Ischaemic heart disease16·2 (14·6 to 17·6)2 Stroke15·5 (14·3 to 16·7)2 Stroke13·0 (11·7 to 14·0)3 COPD9·9 (8·6 to 10·7)3 COPD8·5 (7·5 to 9·2)4 Alzheimer's disease3·8 (1·7 to 8·6)4 Alzheimer's disease5·6 (2·6 to 12·2)5 Lower respiratory infections3·3 (3·0 to 3·6)5 Diabetes4·0 (3·6 to 4·3)6 Diarrhoeal diseases3·1 (2·0 to 4·5)6 Lower respiratory infections3·3 (2·9 to 3·6)7 Diabetes2·6 (2·4 to 2·9)7 Lung cancer2·6 (2·3 to 2·8)8 Hypertensive heart disease8 Falls2·6 (2·2 to 2·9)9 Age-related hearing loss9 Chronic kidney disease10 Lung cancer1·9 (1·8 to 2·0)10 Age-related hearing loss11 Falls1·8 (1·6 to 2·1)11 Hypertensive heart disease12 Tuberculosis1·8 (1·6 to 2·1)12 Diarrhoeal diseases1·9 (1·2 to 3·0)13 Low back pain1·7 (1·2 to 2·3)13 Low back pain1·8 (1·3 to 2·4)14 Chronic kidney disease14 Colorectal cancer1·7 (1·5 to 1·8)15 Stomach cancer1·6 (1·4 to 1·7)15 Blindness and vision loss16 Blindness and vision loss16 Atrial fibrillation1·3 (1·1 to 1·5)17 Colorectal cancer1·4 (1·3 to 1·5)17 Stomach cancer1·3 (1·1 to 1·4)18 Asthma1·2 (1·0 to 1·7)18 Prostate cancer1·1 (1·0 to 1·4)19 Cirrhosis1·2 (1·0 to 1·3)19 Cirrhosis1·1 (1·0 to 1·2)20 Prostate cancer1·0 (0·8 to 1·2)20 Parkinson's disease21 Atrial fibrillation1·0 (0·8 to 1·2)21 Osteoarthritis1·1 (06 to 21)22 Osteoarthritis0·9 (0·5 to 1·7)22 Oral disorders0·9 (0·6 to 1·3)23 Oral disorders0·8 (0·6 to 1·2)23 Tuberculosis0·9 (0·8 to 1·0)24 Parkinson's disease24 Asthma0·8 (0·7 to 1·0)–46·2 (–55·9 to –39·8)25 Upper digestive diseases0·8 (0·7 to 0·9)25 Road injuries0·8 (0·7 to 0·9)26 Road injuries0·7 (0·6 to 0·8)32 Upper digestive diseases0·6 (0·5 to 0·6)1·7 (1·2 to 2·3)1·6 (1·4 to 1·7)1·5 (1·2 to 1·7)1·3 (0·9 to 1·7)1·2 (0·9 to 1·6)1·1 (0·7 to 1·5)0·9 (0·3 to 1·9)–41·0 (–45·5 to –34·5)–51·8 (–58·3 to –46·0)–32·1 (–41·9 to –16·1)5·7 (3·0 to 8·5)–7·4 (–9·6 to –5·1)–1·2 (–7·4 to 2·3)–33·8 (–41·7 to –23·4)–61·0 (–72·1 to –45·8)–9·5 (–16·9 to –2·5)–8·6 (–12·0 to –5·0)4·1 (28 to 5·4)38·2 (18·9 to 71·9)–1·3 (–14·3 to 11·2)22·2 (5·2 to 44·0)20·4 (11·3 to 33·7)115·9 (110·5 to 122·2)90·5 (86·0 to 94·7)102·5 (88·7 to 108·2)36·7 (20·8 to 58·8)–21·0 (–42·4 to 11·9)85·0 (69·9 to 99·4)88·8 (81·9 to 95·8)113·6 (110·9 to 116·4)6·3 (–5·0 to 18·9)–8·4 (–14·1 to –2·6)–5·1 (–12·1 to 1·2)1·5 (0·2 to 2·9)–27·5 (–33·3 to –21·5)–64·7 (–68·9 to –59·4)33·6 (280 to 40·2)–15·2 (–23·2 to –9·9)–2·6 (–4·9 to –0·5)12·1 (3·7 to 19·5)–29·1 (–34·7 to –23·0)–15·9 (–16·9 to –14·9)–19·8 (–27·3 to –12·1)24·5 (18·5 to 30·4)–36·3 (–42·1 to –30·8)–29·1 (–34·2 to –24·1)46·1 (35·6 to 56·4)31·5 (19·5 to 42·9)156·1 (143·4 to 167·9)12·0 (0·9 to 32·3)64·3 (48·8 to 80·2)72·1 (70·0 to 74·3)44·6 (33·2 to 57·1)130·2 (113·0 to 145·6)100·8 (96·0 to 104·9)72·9 (56·5 to 83·9)172·0 (160·6 to 187·4)–27·8 (–36·2 to –16·9)49·8 (37·9 to 62·4)107·3 (104·7 to 110·1)95·1 (80v8 to 108·2)88·3 (76·5 to 100·0)1·2 (0·4 to 2·5)1·3 (1·0 to 1·5)1·4 (1·1 to 2·0)1·7 (1·3 to 2·3)1·9 (1·4 to 2·6)2·3 (2·1 to 2·5)2·2 (1·5 to 3·0)–32·4 (–35·8 to –29·4)–33·4 (–38·3 to –28·5)–31·0 (–37·1 to –21·9)2·6 (–2·1 to 6·6)23·1 (18·6 to 27·5)–25·3 (–29·3 to –20·4)16·4 (7·4 to 24·9)6·4 (0·4 to 13·3)21·6 (12·6 to 27·4)–2·2 (–4·3 to –0·2)–15·1 (–31·5 to –5·0)–51·0 (–64·9 to –30·4)–12·5 (–13·8 to –11·3)–4·5 (–9·7 to 0·1)–7·4 (–9·9 to –4·8)–1·8 (–6·9 to 2·5)–32·9 (–37·5 to –28·0)–8·5 (–14·6 to 2·1)–21·3 (–30·2 to –13·5)6·0 (0·0 to 11·1)0·8 (–0·4 to 2·1)–10·9 (–12·9 to –8·8)–59·2 (–64·0 to –50·3)–9·3 (–13·5 to –5·9)–43·8 (–48·4 to –38·7)34·0 (22·8 to 46·2)110·0 (99·8 to 118·1)25·2 (3·2 to 41·2)–6·3 (–16·9 to 14·6)112·0 (106·4 to 117·6)139·5 (136·5 to 142·6)153·7 (138·7 to 166·6)82·3 (62·1 to 100·9)117·0 (102·1 to 142·3)55·0 (43·8 to 66·6)148·6 (134·8 to 161·9)124·7 (119·3 to 130·7)126·9 (113·4 to 138·3)105·7 (100·2 to 111·4)15·1 (–16·8 to 65·3)106·0 (68·5 to 131·7)137·8 (132·0 to 143·9)196·0 (173·9 to 211·1)166·4 (151·1 to 183·4)164·3 (143·6 to 183·8)87·4 (76·2 to 99·6)190·7 (179·4 to 201·0)180·0 (168·0 to 194·7)63·6 (49·1 to 86·1)60·5 (48·7 to 72·5)66·6 (57·7 to 74·2)2·5 (2·3 to 2·7)2·5 (1·9 to 3·3)2·4 (1·8 to 2·7)1·7 (1·3 to 2·2)1·1 (1·0 to 1·2)0·8 (0·8 to 0·9)1·4 (1·1 to 1·8)1·6 (1·5 to 1·8)2·0 (1·5 to 2·7)2·3 (1·9 to 2·5)··
Global Health Metricswww.thelancet.comVol 396 October 17, 20201213tuberculosis, road injuries, stroke, and, to a lesser extent, low back pain and ischaemic heart disease. For similar reasons as in the previous age group, HIV/AIDS DALY rates increased substantially. The increase in the residual “other musculoskeletal disorder” category is more difficult to interpret, as it is a collection of several individual diseases.HIV/AIDS, ischaemic heart disease, stroke, and headache disorders appeared in the top-ten rankings for DALYs for both males and females in 2019. Three injury causes (road injuries, self-harm, and inter-personal violence) and cirrhosis ranked prominently among males but not females. Among females, gynae-cological disorders, depressive disorders, other musculo-skeletal disorders, maternal disorders, and anxiety disorders were top ten causes (appendix 2 figures S9, S10).In 2019, the ten leading causes of DALYs in age groups 50–74 years and 75 years and older largely overlapped. Ischaemic heart disease and stroke were ranked first and second, respectively, in both age groups. Chronic obstructive pulmonary disease (COPD), diabetes, lung cancer, chronic kidney disease, and age-related hearing loss appeared in the top ten in both age groups. For ages 50–74 years, low back pain, cirrhosis, and road injuries were the remaining top-ten-ranking causes of DALYs, whereas Alzheimer’s disease and other dementias, lower respiratory infections, and falls appeared in the top ten for those aged 75 years and older. The most notable changes in top ten causes in these two age groups between 1990 and 2019 were large declines in age-standardised DALY rates for ischaemic heart disease, stroke, COPD, cirrhosis, and road injuries, but increases in DALY rates for diabetes and chronic kidney disease. There was a decline in age-standardised lung cancer rates for ages 50–74 years, but an increase in the oldest age category. The ten leading causes for DALYs by sex in both of these older age groups largely overlapped in 2019.Among 50–74-year-olds, breast cancer, other musculoskeletal disorders, and depressive disorders appeared in the top ten for females only, while road injuries, cirrhosis, and tuberculosis made it into the top ten for males. For the oldest age group, falls and hypertensive heart disease ranked in the top ten among females, but not males; lung cancer and prostate cancer ranked among the top ten in males (appendix 2 figures S9, S10).National trendsCountries and territories vary widely in their stages of the epidemiological transition. With increasing SDI, we expect to see a shift in the burden of disease from commu-nicable, maternal, neonatal, and nutritional diseases towards non-communicable causes. We also expect to see a shift towards a larger fraction of the burden due to YLDs compared with YLLs. These two major trends can be summarised by the percentage of all-cause DALYs made up of non-communicable disease and injury YLDs. Figure 3 shows this proportion across 204 countries and territories in 1990 and 2019. In 2019, this measure of the epidemiological transition ranged from 8·4% (95% UI 6·2–10·9) in Chad to 56·9% (48·7–64·3) in Qatar. The values in 1990 ranged from 3·5% (2·6–4·7) in Niger to 47·5% (37·6–56·0) in Andorra. In 2019, non-commu-nicable and injury YLDs contributed to more than half of all disease burden in 11 countries. All but two countries, Ukraine and Lesotho, had higher ratios in 2019 compared with 1990.When comparing the annualised rate of change in age-standardised DALY rates for all causes except HIV/AIDS, natural disasters, and war and conflict between the time periods 1990–2010 and 2010–19 for each country and territory, the rate, as shown by a simple linear regression line, is steeper in the latter time period, suggesting that change has accelerated over the last decade in countries and territories at the lower end of the SDI range (figure 4). Improvements have started to stagnate, or even reverse, in countries with higher SDI, as is the case in Dominica, the Dominican Republic, Guam, Jamaica, Saint Lucia, Saint Vincent and the Grenadines, Ukraine, the USA, and Venezuela. Countries with greater than 2% annual reduc-tions in age-standardised DALY rates over both time periods were Ethiopia, Angola, Burundi, Malawi, Sudan, Myanmar, Laos, and Bangladesh. Four countries from the former Soviet Union—Russia, Belarus, Kazakhstan, and Uzbekistan—experienced increases in age-standardised DALY rates between 1990 and 2010, but recovered in the following decade; Russia, Kazakhstan, and Belarus experienced an estimated annual decline of 2% or greater between 2010 and 2019, and Uzbekistan experienced an estimated 1·5% annual decline. Another former Soviet Union republic, Ukraine, saw modest decline in the 1990 to 2010 period, but a worsening trend in the decade after.Cause-specific trendsTwo-page cause-specific summaries provide detailed results on mortality, prevalence, incidence, YLLs, YLDs, and DALYs for a selection of diseases, injuries, and impairments in the GBD cause hierarchy. These sum-maries include 2019 counts, age-standardised rates, and rankings; the fraction of DALYs attributed to risk factors; patterns over time and age; and the relationship between SDI and DALY rates by country or territory. They were written to increase the accessibility to and transparency of GBD estimates for each cause. Summaries for select causesare highlighted in print (pp S2–213); summaries for all diseases, injuries, and impairmentscan be found online.DiscussionMain findingsGlobal health has steadily improved over the past 30 years, as measured by changes in age-standardised DALY rates. While health has improved, after accounting for population growth and ageing, the absolute number of DALYs has remained stable. The shift to a much For all two-page summaries see https://www.thelancet.com/gbd/summaries