Adherence to the planetary health diet index and obesity indicators in the Brazilian longitudinal study of adult health (ELSA-Brasil)

The EAT-Lancet Commission has proposed a model diet to improve the health of human beings and that of the planet. Recently, we proposed the Planetary Health Diet Index (PHDI) to assess adherence of the population to this model diet. In this study, we aimed to evaluate adherence to the PHDI and obesity outcomes using baseline data from 14, 515 participants in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). The dietary data were assessed using a 114-item FFQ. Body mass index (BMI) and waist circumference (WC) were both used continuously and cat-egorized. Linear and multinomial regression models adjusted for potential confounding factors were performed to assess the relationship between adherence to PHDI and outcomes. An inverse association was observed between adherence to PHDI and obesity indicators. Individuals with high adherence to the PHDI had lower BMI (ß-0.50 95% CI-0.73:-0.27) and WC (ß-1.70 95% CI-2.28:-1.12) values. They were also 24% less likely to be overweight (OR 0.76 95% CI 0.67:0.85) or obese (OR 0.76 95% CI 0.65:0.88), and they were 14% and 27% less likely to have increased WC (OR 0.86 95% CI 0.75:0.98) or substantially increased WC (OR 0.73 95% CI 0.64:0.83) than those with lower adherence. Our results showed that higher adherence to the PHDI may decrease obesity in-dicators. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

The Global Burden of Cancer 2013

IMPORTANCE: Cancer is among the leading causes of death worldwide. Current estimates of cancer burden in individual countries and regions are necessary to inform local cancer control strategies. OBJECTIVE: To estimate mortality, incidence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 28 cancers in 188 countries by sex from 1990 to 2013. EVIDENCE REVIEW: The general methodology of the Global Burden of Disease (GBD) 2013 study was used. Cancer registries were the source for cancer incidence data as well as mortality incidence (MI) ratios. Sources for cause of death data include vital registration system data, verbal autopsy studies, and other sources. The MI ratios were used to transform incidence data to mortality estimates and cause of death estimates to incidence estimates. Cancer prevalence was estimated using MI ratios as surrogates for survival data; YLDs were calculated by multiplying prevalence estimates with disability weights, which were derived from population-based surveys; YLLs were computed by multiplying the number of estimated cancer deaths at each age with a reference life expectancy; and DALYs were calculated as the sum of YLDs and YLLs. FINDINGS: In 2013 there were 14.9 million incident cancer cases, 8.2 million deaths, and 196.3 million DALYs. Prostate cancer was the leading cause for cancer incidence (1.4 million) for men and breast cancer for women (1.8 million). Tracheal, bronchus, and lung (TBL) cancer was the leading cause for cancer death in men and women, with 1.6 million deaths. For men, TBL cancer was the leading cause of DALYs (24.9 million). For women, breast cancer was the leading cause of DALYs (13.1 million). Age-standardized incidence rates (ASIRs) per 100 000 and age-standardized death rates (ASDRs) per 100 000 for both sexes in 2013 were higher in developing vs developed countries for stomach cancer (ASIR, 17 vs 14; ASDR, 15 vs 11), liver cancer (ASIR, 15 vs 7; ASDR, 16 vs 7), esophageal cancer (ASIR, 9 vs 4; ASDR, 9 vs 4), cervical cancer (ASIR, 8 vs 5; ASDR, 4 vs 2), lip and oral cavity cancer (ASIR, 7 vs 6; ASDR, 2 vs 2), and nasopharyngeal cancer (ASIR, 1.5 vs 0.4; ASDR, 1.2 vs 0.3). Between 1990 and 2013, ASIRs for all cancers combined (except nonmelanoma skin cancer and Kaposi sarcoma) increased by more than 10 in 113 countries and decreased by more than 10 in 12 of 188 countries. CONCLUSIONS AND RELEVANCE: Cancer poses a major threat to public health worldwide, and incidence rates have increased in most countries since 1990. The trend is a particular threat to developing nations with health systems that are ill-equipped to deal with complex and expensive cancer treatments. The annual update on the Global Burden of Cancer will provide all stakeholders with timely estimates to guide policy efforts in cancer prevention, screening, treatment, and palliation. Copyright 2015 American Medical Association. All rights reserved

Transitions of cardio-metabolic risk factors in the Americas between 1980 and 2014

Describing the prevalence and trends of cardiometabolic risk factors that are associated with non-communicable diseases (NCDs) is crucial for monitoring progress, planning prevention, and providing evidence to support policy efforts. We aimed to analyse the transition in body-mass index (BMI), obesity, blood pressure, raised blood pressure, and diabetes in the Americas, between 1980 and 2014

Primary stroke prevention worldwide : translating evidence into action

Funding Information: The stroke services survey reported in this publication was partly supported by World Stroke Organization and Auckland University of Technology. VLF was partly supported by the grants received from the Health Research Council of New Zealand. MOO was supported by the US National Institutes of Health (SIREN U54 HG007479) under the H3Africa initiative and SIBS Genomics (R01NS107900, R01NS107900-02S1, R01NS115944-01, 3U24HG009780-03S5, and 1R01NS114045-01), Sub-Saharan Africa Conference on Stroke Conference (1R13NS115395-01A1), and Training Africans to Lead and Execute Neurological Trials & Studies (D43TW012030). AGT was supported by the Australian National Health and Medical Research Council. SLG was supported by a National Heart Foundation of Australia Future Leader Fellowship and an Australian National Health and Medical Research Council synergy grant. We thank Anita Arsovska (University Clinic of Neurology, Skopje, North Macedonia), Manoj Bohara (HAMS Hospital, Kathmandu, Nepal), Denis ?erimagi? (Poliklinika Glavi?, Dubrovnik, Croatia), Manuel Correia (Hospital de Santo Ant?nio, Porto, Portugal), Daissy Liliana Mora Cuervo (Hospital Moinhos de Vento, Porto Alegre, Brazil), Anna Cz?onkowska (Institute of Psychiatry and Neurology, Warsaw, Poland), Gloria Ekeng (Stroke Care International, Dartford, UK), Jo?o Sargento-Freitas (Centro Hospitalar e Universit?rio de Coimbra, Coimbra, Portugal), Yuriy Flomin (MC Universal Clinic Oberig, Kyiv, Ukraine), Mehari Gebreyohanns (UT Southwestern Medical Centre, Dallas, TX, USA), Ivete Pillo Gon?alves (Hospital S?o Jos? do Avai, Itaperuna, Brazil), Claiborne Johnston (Dell Medical School, University of Texas, Austin, TX, USA), Kristaps Jurj?ns (P Stradins Clinical University Hospital, Riga, Latvia), Rizwan Kalani (University of Washington, Seattle, WA, USA), Grzegorz Kozera (Medical University of Gda?sk, Gda?sk, Poland), Kursad Kutluk (Dokuz Eylul University, ?zmir, Turkey), Branko Malojcic (University Hospital Centre Zagreb, Zagreb, Croatia), Micha? Maluchnik (Ministry of Health, Warsaw, Poland), Evija Migl?ne (P Stradins Clinical University Hospital, Riga, Latvia), Cassandra Ocampo (University of Botswana, Princess Marina Hospital, Botswana), Louise Shaw (Royal United Hospitals Bath NHS Foundation Trust, Bath, UK), Lekhjung Thapa (Upendra Devkota Memorial-National Institute of Neurological and Allied Sciences, Kathmandu, Nepal), Bogdan Wojtyniak (National Institute of Public Health, Warsaw, Poland), Jie Yang (First Affiliated Hospital of Chengdu Medical College, Chengdu, China), and Tomasz Zdrojewski (Medical University of Gda?sk, Gda?sk, Poland) for their comments on early draft of the manuscript. The views expressed in this article are solely the responsibility of the authors and they do not necessarily reflect the views, decisions, or policies of the institution with which they are affiliated. We thank WSO for funding. The funder had no role in the design, data collection, analysis and interpretation of the study results, writing of the report, or the decision to submit the study results for publication. Funding Information: The stroke services survey reported in this publication was partly supported by World Stroke Organization and Auckland University of Technology. VLF was partly supported by the grants received from the Health Research Council of New Zealand. MOO was supported by the US National Institutes of Health (SIREN U54 HG007479) under the H3Africa initiative and SIBS Genomics (R01NS107900, R01NS107900-02S1, R01NS115944-01, 3U24HG009780-03S5, and 1R01NS114045-01), Sub-Saharan Africa Conference on Stroke Conference (1R13NS115395-01A1), and Training Africans to Lead and Execute Neurological Trials & Studies (D43TW012030). AGT was supported by the Australian National Health and Medical Research Council. SLG was supported by a National Heart Foundation of Australia Future Leader Fellowship and an Australian National Health and Medical Research Council synergy grant. We thank Anita Arsovska (University Clinic of Neurology, Skopje, North Macedonia), Manoj Bohara (HAMS Hospital, Kathmandu, Nepal), Denis Čerimagić (Poliklinika Glavić, Dubrovnik, Croatia), Manuel Correia (Hospital de Santo António, Porto, Portugal), Daissy Liliana Mora Cuervo (Hospital Moinhos de Vento, Porto Alegre, Brazil), Anna Członkowska (Institute of Psychiatry and Neurology, Warsaw, Poland), Gloria Ekeng (Stroke Care International, Dartford, UK), João Sargento-Freitas (Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal), Yuriy Flomin (MC Universal Clinic Oberig, Kyiv, Ukraine), Mehari Gebreyohanns (UT Southwestern Medical Centre, Dallas, TX, USA), Ivete Pillo Gonçalves (Hospital São José do Avai, Itaperuna, Brazil), Claiborne Johnston (Dell Medical School, University of Texas, Austin, TX, USA), Kristaps Jurjāns (P Stradins Clinical University Hospital, Riga, Latvia), Rizwan Kalani (University of Washington, Seattle, WA, USA), Grzegorz Kozera (Medical University of Gdańsk, Gdańsk, Poland), Kursad Kutluk (Dokuz Eylul University, İzmir, Turkey), Branko Malojcic (University Hospital Centre Zagreb, Zagreb, Croatia), Michał Maluchnik (Ministry of Health, Warsaw, Poland), Evija Miglāne (P Stradins Clinical University Hospital, Riga, Latvia), Cassandra Ocampo (University of Botswana, Princess Marina Hospital, Botswana), Louise Shaw (Royal United Hospitals Bath NHS Foundation Trust, Bath, UK), Lekhjung Thapa (Upendra Devkota Memorial-National Institute of Neurological and Allied Sciences, Kathmandu, Nepal), Bogdan Wojtyniak (National Institute of Public Health, Warsaw, Poland), Jie Yang (First Affiliated Hospital of Chengdu Medical College, Chengdu, China), and Tomasz Zdrojewski (Medical University of Gdańsk, Gdańsk, Poland) for their comments on early draft of the manuscript. The views expressed in this article are solely the responsibility of the authors and they do not necessarily reflect the views, decisions, or policies of the institution with which they are affiliated. We thank WSO for funding. The funder had no role in the design, data collection, analysis and interpretation of the study results, writing of the report, or the decision to submit the study results for publication. Funding Information: VLF declares that the PreventS web app and Stroke Riskometer app are owned and copyrighted by Auckland University of Technology; has received grants from the Brain Research New Zealand Centre of Research Excellence (16/STH/36), Australian National Health and Medical Research Council (NHMRC; APP1182071), and World Stroke Organization (WSO); is an executive committee member of WSO, honorary medical director of Stroke Central New Zealand, and CEO of New Zealand Stroke Education charitable Trust. AGT declares funding from NHMRC (GNT1042600, GNT1122455, GNT1171966, GNT1143155, and GNT1182017), Stroke Foundation Australia (SG1807), and Heart Foundation Australia (VG102282); and board membership of the Stroke Foundation (Australia). SLG is funded by the National Health Foundation of Australia (Future Leader Fellowship 102061) and NHMRC (GNT1182071, GNT1143155, and GNT1128373). RM is supported by the Implementation Research Network in Stroke Care Quality of the European Cooperation in Science and Technology (project CA18118) and by the IRIS-TEPUS project from the inter-excellence inter-cost programme of the Ministry of Education, Youth and Sports of the Czech Republic (project LTC20051). BN declares receiving fees for data management committee work for SOCRATES and THALES trials for AstraZeneca and fees for data management committee work for NAVIGATE-ESUS trial from Bayer. All other authors declare no competing interests. Publisher Copyright: © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseStroke is the second leading cause of death and the third leading cause of disability worldwide and its burden is increasing rapidly in low-income and middle-income countries, many of which are unable to face the challenges it imposes. In this Health Policy paper on primary stroke prevention, we provide an overview of the current situation regarding primary prevention services, estimate the cost of stroke and stroke prevention, and identify deficiencies in existing guidelines and gaps in primary prevention. We also offer a set of pragmatic solutions for implementation of primary stroke prevention, with an emphasis on the role of governments and population-wide strategies, including task-shifting and sharing and health system re-engineering. Implementation of primary stroke prevention involves patients, health professionals, funders, policy makers, implementation partners, and the entire population along the life course.publishersversionPeer reviewe

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: A systematic analysis for the Global Burden of Disease Study 2015

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods: We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings: Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation: Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding: Bill & Melinda Gates Foundation

Global and national burden of diseases and injuries among children and adolescents between 1990 and 2013 findings from the global burden of disease 2013 study

IMPORTANCE: The literature focuses on mortality among children younger than 5 years. Comparable information on nonfatal health outcomes among these children and the fatal and nonfatal burden of diseases and injuries among older children and adolescents is scarce. OBJECTIVE: To determine levels and trends in the fatal and nonfatal burden of diseases and injuries among younger children (aged < 5 years), older children (aged 5-9 years), and adolescents (aged 10-19 years) between 1990 and 2013 in 188 countries from the Global Burden of Disease (GBD) 2013 study. EVIDENCE REVIEW: Data from vital registration, verbal autopsy studies, maternal and child death surveillance, and other sources covering 14 244 site-years (ie, years of cause of death data by geography) from 1980 through 2013 were used to estimate cause-specific mortality. Data from 35 620 epidemiological sources were used to estimate the prevalence of the diseases and sequelae in the GBD 2013 study. Cause-specific mortality for most causes was estimated using the Cause of Death Ensemble Model strategy. For some infectious diseases (eg, HIVinfection/AIDS, measles, hepatitis B) where the disease process is complex or the cause of death data were insufficient or unavailable, we used natural history models. For most nonfatal health outcomes, DisMod-MR2.0, a Bayesian metaregression tool, was used to meta-analyze the epidemiological data to generate prevalence estimates. FINDINGS: Of the 7.7 (95 uncertainty interval UI, 7.4-8.1) million deaths among children and adolescents globally in 2013,6.28 million occurred amongyounger children, 0.48 million among older children, and 0.97 million among adolescents. In 2013, the leading causes of death were lower respiratory tract infections amongyounger children (905 059 deaths; 95% UI, 810 304-998125), diarrheal diseases among older children (38 325 deaths; 95% UI, 30 365-47 678), and road injuries among adolescents (115186 deaths; 95% UI, 105185-124 870). Iron deficiency anemia was the leading cause of years lived with disability among children and adolescents, affecting 619 (95% UI, 618-621) million in 2013. Large between-country variations exist in mortality from leading causes among children and adolescents. Countries with rapid declines in all-cause mortality between 1990 and 2013 also experienced large declines in most leading causes of death, whereas countries with the slowest declines had stagnant or increasing trends in the leading causes of death. In 2013, Nigeria had a 12% global share of deaths from lower respiratory tract infections and a 38% global share of deaths from malaria. India had 33% of the world's deaths from neonatal encephalopathy. Half of the world's diarrheal deaths among children and adolescents occurred injust 5 countries: India, Democratic Republic of the Congo, Pakistan, Nigeria, and Ethiopia. CONCLUSIONS AND RELEVANCE: Understanding the levels and trends of the leading causes of death and disability among children and adolescents is critical to guide investment and inform policies. Monitoring these trends over time is also key to understanding where interventions are having an impact. Proven interventions exist to prevent or treat the leading causes of unnecessary death and disability among children and adolescents. The findings presented here show that these are underused and give guidance to policy makers in countries where more attention is needed. Copyright 2016 American Medical Association. All rights reserved

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980�2015: a systematic analysis for the Global Burden of Disease Study 2015

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14�294 geography�year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61·7 years (95 uncertainty interval 61·4�61·9) in 1980 to 71·8 years (71·5�72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7�17·4), to 62·6 years (56·5�70·2). Total deaths increased by 4·1 (2·6�5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0 (15·8�18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1 (12·6�16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1 (11·9�14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1, 39·1�44·6), malaria (43·1, 34·7�51·8), neonatal preterm birth complications (29·8, 24·8�34·9), and maternal disorders (29·1, 19·3�37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146�000 deaths, 118�000�183�000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393�000 deaths, 228�000�532�000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost YLLs) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY licens

Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

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 across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. INTERPRETATION: This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing

Repositioning of the global epicentre of non-optimal cholesterol

High blood cholesterol is typically considered a feature of wealthy western countries1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol—which is a marker of cardiovascular risk—changed from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million–4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.</p