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. 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. 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. 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. Bill & Melinda Gates Foundation.

A 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. Drawing 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. In 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, performance ranged from 91·5 (89·1-93·6) in Beijing to 48·0 (43·4-53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6-68·8) in Goa to 34·0 (30·3-38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view-and subsequent provision-of quality health care for all populations. Bill & Melinda Gates Foundation.

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations.

Central Obesity (CO) might arise among individuals with normal body mass index (BMI). We aim to estimate the prevalence of Normal Weight CO (NWCO), using different definitions, and to compare its association with cardiometabolic risk factors in the adult population of Panama. Data from two population-based studies conducted in Panama in 2010 and 2019 were used. Using standard definitions, normal weight was defined as a BMI between 18·5 and 24·9 while CO was defined as a Waist-to-Height Ratio (WHtR) ≥ 0·5 in both sexes or a Waist Circumference (WC) ≥ 90, ≥94, or ≥102 cm for men, and 80 or 88 cm for women. Unconditional logistic regression models were used to estimate the association between each CO definition and dyslipidemia, high blood pressure (HBP), diabetes, and clusters of cardiovascular risk factors. Recent CO prevalence ranged between 3·9% (WC ≥ 102 cm for men and WC ≥ 88 cm for women) and 43·9% (WHtR ≥ 0·5) among individuals classify as normal weigh according to the BMI. Different cardiovascular risk factors were present in this normal weight population but among men the threshold of WC ≥ 102 cm screened less than 1·0%. NWCO was associated with cardiovascular risk factors, particularly with elevated concentration of triglycerides. CO evaluation at the primary health care level may be a useful technique to identify normal weight people with metabolically obese characteristics. Gorgas Memorial Institute for Health studies via Ministry of Economy and Finance of Panama and Inter-American Development Bank.

Background: Recent estimates of hypertension in Panama remain unknown. We aim to describe the variation in prevalence and unawareness of hypertension in two Panamanian provinces using two different cross-sectional population-based studies and to investigate risk factors associated with hypertension unawareness. Methods: Data were derived from a sub-national study conducted in the provinces of Panama and Colon (PREFREC-2010 [2,733 participants]) and from a nationally representative study (ENSPA-2019), in which we restricted our analyses to the same provinces (4,653 participants). Individuals aged 30–75 years who had (a) self-reported history of hypertension or (b) blood pressure (BP) ≥140/90mmHg or (c) a combination or both were classified as hypertensive. Participants with BP≥140/90mmHg who denied a history of hypertension were considered unaware of the condition. Multivariable logistic regression models were used to estimate the association between risk factors and unawareness, expressed as odds ratios (OR) and 95% confidence interval (CI). Findings: In 2010, the prevalence and unawareness of hypertension in men were 51.6% (95% CI: 45.7–57.5) and 32.3% (25.4–40.1), respectively, and in women 46.0% (42.1–49.9) and 16.1% (12.6–20.4), respectively. In 2019, the prevalence and unawareness of hypertension in men were 46.5% (42.1–51.0) and 52.3% (45.9–58.6), and in women 42.1% (39.6–44.7) and 33.3% (29.8–37.0). Men (2010 and 2019), age <50 years (2010 and 2019), having no/primary education (2010), and living in a non-urban region (2019) were positively associated with hypertension unawareness, whereas obesity (2010), physical inactivity (2010), family history of hypertension (2019), and BP assessment in the year before study enrollment (2010 and 2019) were inversely associated with hypertension unawareness. Interpretation: Benefits of a decrease in the prevalence of hypertension are being undermined by an increase in hypertension unawareness. Actions should be encouraged to strengthen the implementation of the existing healthcare program for cardiovascular risk factor control.

Background: Out-of-hospital deaths due to a first myocardial infarction (MI) are frequent and a big challenge for prevention. Increased knowledge about factors influencing MI fatality is needed. Metabolic risk factors have been studied in relation to MI fatality in-hospital but studies considering also out-of-hospital deaths are few. Aim: To assess howdiabetes and other metabolic risk factors associate with death within 7 days after first time MI among subjects aged between 45 and 70 identified in Stockholm County 1992-1994. Methods: Data were collected using questionnaires (close relatives of fatal cases were asked to fill the questionnaire), physical examinations, national registers and autopsy reports. Risk ratios (RR) of 7-day MI fatality with 95% confidence intervals (CI) associated with the risk factors under study were calculated using binomial regression with log link. Results: Out of 1905 first time MI cases included, 524 died within 7 days. After adjustments for age, sex, current smoking, education and general comorbidity, diabetes, but not hypertension and hyperlipidemia, was associated with MI fatality (RR 1.68, 95% CI 1.20-2.28). Overweight, as compared to normal BMI, was inversely associated with MI fatality (multiple adjusted RR 0.68, 95% CI 0.49-0.94); obesity results pointed in the samedirection (multiple adjusted RR 0.79, 0.52-1.16). Conclusions: In this population-based inception cohort study, diabetes but not hypertension and hyperlipidemia were associated with MI fatality. This further emphasizes the importance of diabetes as a cardiovascular risk factor and the need for close surveillance of diabetic patients. Overweight was however associated with decreased MI fatality