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. 2018 Nov 10;392(10159):1736-1788.
doi: 10.1016/S0140-6736(18)32203-7. Epub 2018 Nov 8.

Global, Regional, and National Age-Sex-Specific Mortality for 282 Causes of Death in 195 Countries and Territories, 1980-2017: A Systematic Analysis for the Global Burden of Disease Study 2017

Collaborators
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Global, Regional, and National Age-Sex-Specific Mortality for 282 Causes of Death in 195 Countries and Territories, 1980-2017: A Systematic Analysis for the Global Burden of Disease Study 2017

GBD 2017 Causes of Death Collaborators. Lancet. .
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Erratum in

  • Department of Error.
    Lancet. 2019 Jun 22;393(10190):e44. doi: 10.1016/S0140-6736(19)31049-9. Lancet. 2019. PMID: 31232379 Free PMC article. No abstract available.
  • Erratum: Department of Error.
    Lancet. 2018 Nov 17;392(10160):2170. doi: 10.1016/S0140-6736(18)32833-2. Lancet. 2018. PMID: 31329658 Free PMC article.

Abstract

Background: Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017.

Methods: The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries-Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised.

Findings: At the broadest grouping of causes of death (Level 1), non-communicable diseases (NCDs) comprised the greatest fraction of deaths, contributing to 73·4% (95% uncertainty interval [UI] 72·5-74·1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 18·6% (17·9-19·6), and injuries 8·0% (7·7-8·2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22·7% (21·5-23·9), representing an additional 7·61 million (7·20-8·01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7·9% (7·0-8·8). The number of deaths for CMNN causes decreased by 22·2% (20·0-24·0) and the death rate by 31·8% (30·1-33·3). Total deaths from injuries increased by 2·3% (0·5-4·0) between 2007 and 2017, and the death rate from injuries decreased by 13·7% (12·2-15·1) to 57·9 deaths (55·9-59·2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118·0% (88·8-148·6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36·4% (32·2-40·6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33·6% (31·2-36·1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respiratory infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990-neonatal disorders, lower respiratory infections, and diarrhoeal diseases-were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases.

Interpretation: Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade.

Funding: Bill & Melinda Gates Foundation.

Figures

Figure 1
Figure 1
Effect of new VR data on Level 1 cause estimates from GBD 2016 to GBD 2017, based on national locations with varying quality of VR data, 2008–16 The figure shows the degree of consistency between GBD 2016 and GBD 2017 estimates for Level 1 causes at the national level from 2008 to 2016. The diagonal line represents no change from GBD 2016 to GBD 2017. Each point represents one country-year, with colours indicating the Level 1 cause grouping (communicable, maternal, neonatal, and nutritional diseases; non-communicable diseases; and injuries). Panels indicate whether or not any new VR data between 2008 and 2016 were added for that location for GBD 2017, and whether or not a location has 4-star or 5-star VR quality. Points that are outside of the standard 95% prediction interval for a linear regression of 2017 values on 2016 values are annotated (if the same location-cause had multiple points in a time series, only the furthest-most point was annotated). The Spearman's correlation coefficient is noted in the lower right-hand corner of each panel. CSMR=cause-specific mortality rate. GBD=Global Burden of Diseases, Injuries, and Risk Factors Study. VR=vital registration.
Figure 2
Figure 2
Out-of-sample model performance for CODEm models and age-standardised cause-specific mortality rate by Level 1 causes Model performance was defined by the root-mean squared error of the ensemble model predictions of the log of the age-specific death rates for a cause with 15% of the data held out from the statistical model building. The figure shows the association between the root-mean squared error and the log of the CSMR, aggregated over 1980–2017. Each point represents one CODEm model specific for model-specific age ranges and sex. Circles denote models run with all locations. Triangles denote models run on only data-rich locations. Colours denote the Level 1 cause categories. Open circles and triangles denote models that were run with restricted age groups of less than 30 years. CODEm=Cause of Death Ensemble model. CSMR=cause-specific mortality rate.
Figure 3
Figure 3
All-age deaths due to fatal discontinuities (violence, disasters, famine, and disease outbreak), for both sexes combined, 1980–2017 We have chosen to show this map in counts to capture the wide range of discontinuity-related deaths ranging from motor vehicle accidents with a smaller number of deaths to natural disasters and conflicts with a larger number of deaths. Deaths are coded to the location of residence for the deceased. Maps by each subtype—violence, disasters, famine, and disease outbreak—are provided in appendix 2. ATG=Antigua and Barbuda. FSM=Federated States of Micronesia. Isl=Islands. LCA=Saint Lucia. TLS=Timor-Leste. TTO=Trinidad and Tobago. VCT=Saint Vincent and the Grenadines.
Figure 4
Figure 4
Sex difference in global mortality for 21 Level 2 causes by age, 2017 This figure represents the difference in mortality between females and males, as well as the cause composition of those differences for each GBD age group for the Level 2 causes in GBD 2017. GBD=Global Burden of Diseases, Injuries, and Risk Factors Study.
Figure 5
Figure 5
Distribution of percentage change in age-standardised mortality rate for Level 1 causes by SDI quintile (A) Communicable, maternal, neonatal, and nutritional diseases. (B) Non-communicable diseases. (C) Injuries. The figure shows the distribution of the percentage change in the age-standardised mortality rate by Level 1 cause over the three 5-year periods (2003–07, 2008–12, and 2013–17). The colours represent SDI quintiles. The solid line represents no change in the age-standardised mortality rate during the specified 5-year period. The dotted line represents the median over all countries in the percentage change. Countries that were outliers (>30% decrease or a 10% increase in a given time period) were removed from the figure in order to better distinguish the shape of the distribution. For communicable, maternal, neonatal, and nutritional diseases, the following countries were excluded: Finland, Georgia, Lithuania, Rwanda, Serbia, South Africa, Turkey, and Ukraine in 2003–07; Botswana, Croatia, Dominica, Malawi, Namibia, Zambia, and Zimbabwe in 2008–12; and Botswana, Lesotho, South Africa, and Swaziland in 2013–17. For injuries, the following were excluded: Afghanistan, Burundi, Cape Verde, Comoros, Georgia, Iran, Iraq, Jamaica, Liberia, São Tomé and Príncipe, Spain, and Trinidad and Tobago in 2003–07; El Salvador, Honduras, Israel, Libya, Mexico, Myanmar, Palestine, Samoa, South Sudan, Sri Lanka, Syria, and Ukraine in 2008–12; and Afghanistan, Honduras, Iraq, Libya, Puerto Rico, Ukraine, and Yemen in 2013–17. SDI=Socio-demographic Index.
Figure 6
Figure 6
Trends of total YLLs (A) and age-standardised YLL rates (B) for both sexes combined from 1980 to 2017, by top five GBD Level 2 causes in 2017, by SDI quintile Shaded areas show 95% uncertainty intervals. GBD=Global Burden of Diseases, Injuries, and Risk Factors Study. SDI=Socio-demographic Index. YLLs=years of life lost.
Figure 7
Figure 7
Leading 20 Level 3 causes of global YLLs for 1990, 2007, and 2017 with percentage change in number of YLLs, in all-age and age-standardised rates for both sexes combined Causes are connected by lines between time periods; solid lines are increases and dashed lines are decreases. For the time period 1990–2007 and for 2007–17, three measures of change are shown: percentage change in the number of YLLs, percentage change in the all-age YLL rate, and percentage change in the age-standardised YLL rate. Communicable, maternal, neonatal, and nutritional diseases are shown in red, non-communicable causes in blue, and injuries in green. Statistically significant changes are shown in bold. COPD=chronic obstructive pulmonary disease. YLLs=years of life lost.
Figure 8
Figure 8
Co-evolution of age-standardised YLLs with SDI globally and for GBD regions for Level 1 causes, for both sexes combined, 1990–2017 (A) Communicable, maternal, neonatal, and nutritional diseases. (B) Non-communicable diseases. (C) Injuries. Coloured lines show global and region values for YLL rates. Each point in a line represents one year starting at 1990 and ending at 2017. In all regions, SDI has increased over time so progress in SDI is associated with points further to the right and later years for a given region. The black lines indicate expected trajectories for each geography expected on the basis of SDI alone. GBD=Global Burden of Diseases, Injuries, and Risk Factors Study. SDI=Socio-demographic Index. YLLs=years of life lost. *Values denoted by asterisks are 18 926·3 for eastern sub-Saharan Africa in 1994 and 35 078·7 for the Caribbean in 2010.
Figure 9
Figure 9
Percentage change in all-age mortality by Level 2 causes at the global level from 2007 to 2017, due to population growth, population ageing, and cause-specific mortality Mental disorders, for which there were 272 deaths globally in 2007 and 327 deaths globally in 2017, are not shown separately but are included in the all-cause category.

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