Summary 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 ...

SummaryBackgroundA key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016.MethodsDrawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita.FindingsIn 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8–98·1) in Iceland, followed by 96·6 (94·9–97·9) in Norway and 96·1 (94·5–97·3) in the Netherlands, to values as low as 18·6 (13·1–24·4) in the Central African Republic, 19·0 (14·3–23·7) in Somalia, and 23·4 (20·2–26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China,...

Summary Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions acro...

Background and Purpose-Quantification of early ischemic changes (EIC) may predict functional outcome in patients with basilar artery occlusion (BAO). We tested the validity of a novel CT score, the posterior circulation Acute Stroke Prognosis Early CT score (pc-ASPECTS). Methods-Pc-ASPECTS allots the posterior circulation 10 points. Two points each are subtracted for EIC in midbrain or pons and 1 point each for EIC in left or right thalamus, cerebellum or PCA-territory, respectively. We studied 2 different populations: (1) patients with suspected vertebrobasilar ischemia and (2) patients with BAO. We applied pc-ASPECTS to noncontrast CT (NCCT), CT angiography source images (CTASI), and follow-up image by 3-reader consensus. We calculated sensitivity for ischemic changes and analyzed the predictivity of pc-ASPECTS for independent (modified Rankin Scale [mRS] score Յ2) and favorable (mRS score Յ3) outcome. Results-Of 130 patients with suspected vertebrobasilar ischemia, 72% (94) had posterior circulation stroke, 8% (10) transient ischemic attack, and 20% (26)

SummaryBackgroundThe burden of cardiovascular diseases is increasing in India, but a systematic understanding of its distribution and time trends across all the states is not readily available. In this report, we present a detailed analysis of how the patterns of cardiovascular diseases and major risk factors have changed across the states of India between 1990 and 2016.MethodsWe analysed the prevalence and disability-adjusted life-years (DALYs) due to cardiovascular diseases and the major component causes in the states of India from 1990 to 2016, using all accessible data sources as part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016. We placed states into four groups based on epidemiological transition level (ETL), defined using the ratio of DALYs from communicable diseases to those from non-communicable diseases and injuries combined, with a low ratio denoting high ETL and vice versa. We assessed heterogeneity in the burden of major cardiovascular diseases across the states of India, and the contribution of risk factors to cardiovascular diseases. We calculated 95% uncertainty intervals (UIs) for the point estimates.FindingsOverall, cardiovascular diseases contributed 28·1% (95% UI 26·5–29·1) of the total deaths and 14·1% (12·9–15·3) of the total DALYs in India in 2016, compared with 15·2% (13·7–16·2) and 6·9% (6·3–7·4), respectively, in 1990. In 2016, there was a nine times difference between states in the DALY rate for ischaemic heart disease, a six times difference for stroke, and a four times difference for rheumatic heart disease. 23·8 million (95% UI 22·6–25·0) prevalent cases of ischaemic heart disease were estimated in India in 2016, and 6·5 million (6·3–6·8) prevalent cases of stroke, a 2·3 times increase in both disorders from 1990. The age-standardised prevalence of both ischaemic heart disease and stroke increased in all ETL state groups between 1990 and 2016, whereas that of rheumatic heart disease decreased; the increase for ischaemic heart disease was highest in the low ETL state group. 53·4% (95% UI 52·6–54·6) of crude deaths due to cardiovascular diseases in India in 2016 were among people younger than 70 years, with a higher proportion in the low ETL state group. The leading overlapping risk factors for cardiovascular diseases in 2016 included dietary risks (56·4% [95% CI 48·5–63·9] of cardiovascular disease DALYs), high systolic blood pressure (54·6% [49·0–59·8]), air pollution (31·1% [29·0–33·4]), high total cholesterol (29·4% [24·3–34·8]), tobacco use (18·9% [16·6–21·3]), high fasting plasma glucose (16·7% [11·4–23·5]), and high body-mass index (14·7% [8·3–22·0]). The prevalence of high systolic blood pressure, high total cholesterol, and high fasting plasma glucose increased generally across all ETL state groups from 1990 to 2016, but this increase was variable across the states; the prevalence of smoking decreased during this period in all ETL state groups.InterpretationThe burden from the leading cardiovascular diseases in India—ischaemic heart disease and strok...