Author: "Coates, Matthew M." / Topic: mortality - Searchworks@Jio Institute Digital Library Search Results

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1. Estimating Health Adjusted Age at Death (HAAD).

Author: Johansson KA, Økland JM, Skaftun EK, Bukhman G, Norheim OF, Coates MM, and Haaland ØA
Subjects: Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Child, Child, Preschool, Epilepsy epidemiology, Female, Humans, Infant, Infant, Newborn, Leukemia, Myeloid, Acute epidemiology, Male, Middle Aged, Precursor Cell Lymphoblastic Leukemia-Lymphoma epidemiology, Schizophrenia epidemiology, United States epidemiology, Young Adult, Epilepsy mortality, Health Status, Leukemia, Myeloid, Acute mortality, Mortality trends, Precursor Cell Lymphoblastic Leukemia-Lymphoma mortality, Quality-Adjusted Life Years, Schizophrenia mortality
Abstract: Objectives: At any point in time, a person's lifetime health is the number of healthy life years they are expected to experience during their lifetime. In this article we propose an equity-relevant health metric, Health Adjusted Age at Death (HAAD), that facilitates comparison of lifetime health for individuals at the onset of different medical conditions, and allows for the assessment of which patient groups are worse off. A method for estimating HAAD is presented, and we use this method to rank four conditions in six countries according to several criteria of "worse off" as a proof of concept., Methods: For individuals with specific conditions HAAD consists of two components: past health (before disease onset) and future expected health (after disease onset). Four conditions (acute myeloid leukemia (AML), acute lymphoid leukemia (ALL), schizophrenia, and epilepsy) are analysed in six countries (Ethiopia, Haiti, China, Mexico, United States and Japan). Data from 2017 for all countries and for all diseases were obtained from the Global Burden of Disease Study database. In order to assess who are the worse off, we focus on four measures: the proportion of affected individuals who are expected to have HAAD<20 (T20), the 25th and 75th percentiles of HAAD for affected individuals (Q1 and Q3, respectively), and the average HAAD (aHAAD) across all affected individuals., Results: Even in settings where aHAAD is similar for two conditions, other measures may vary. One example is AML (aHAAD = 59.3, T20 = 2.0%, Q3-Q1 = 14.8) and ALL (58.4, T20 = 4.6%, Q3-Q1 = 21.8) in the US. Many illnesses, such as epilepsy, are associated with more lifetime health in high-income settings (Q1 in Japan = 59.2) than in low-income settings (Q1 in Ethiopia = 26.3)., Conclusion: Using HAAD we may estimate the distribution of lifetime health of all individuals in a population, and this distribution can be incorporated as an equity consideration in setting priorities for health interventions., Competing Interests: The authors have declared that no competing interests exist.
Published: 2020
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2. Cause-specific mortality for 240 causes in China during 1990-2013: a systematic subnational analysis for the Global Burden of Disease Study 2013.

Author: Zhou M, Wang H, Zhu J, Chen W, Wang L, Liu S, Li Y, Wang L, Liu Y, Yin P, Liu J, Yu S, Tan F, Barber RM, Coates MM, Dicker D, Fraser M, González-Medina D, Hamavid H, Hao Y, Hu G, Jiang G, Kan H, Lopez AD, Phillips MR, She J, Vos T, Wan X, Xu G, Yan LL, Yu C, Zhao Y, Zheng Y, Zou X, Naghavi M, Wang Y, Murray CJ, Yang G, and Liang X
Subjects: Adolescent, Adult, Age Factors, Aged, Cause of Death, Child, Child, Preschool, China epidemiology, Cost of Illness, Female, History, 20th Century, History, 21st Century, Humans, Infant, Infant, Newborn, Life Expectancy, Male, Middle Aged, Young Adult, Mortality history
Abstract: Background: China has experienced a remarkable epidemiological and demographic transition during the past three decades. Far less is known about this transition at the subnational level. Timely and accurate assessment of the provincial burden of disease is needed for evidence-based priority setting at the local level in China., Methods: Following the methods of the Global Burden of Disease Study 2013 (GBD 2013), we have systematically analysed all available demographic and epidemiological data sources for China at the provincial level. We developed methods to aggregate county-level surveillance data to inform provincial-level analysis, and we used local data to develop specific garbage code redistribution procedures for China. We assessed levels of and trends in all-cause mortality, causes of death, and years of life lost (YLL) in all 33 province-level administrative units in mainland China, all of which we refer to as provinces, for the years between 1990 and 2013., Findings: All provinces in mainland China have made substantial strides to improve life expectancy at birth between 1990 and 2013. Increases ranged from 4.0 years in Hebei province to 14.2 years in Tibet. Improvements in female life expectancy exceeded those in male life expectancy in all provinces except Shanghai, Macao, and Hong Kong. We saw significant heterogeneity among provinces in life expectancy at birth and probability of death at ages 0-14, 15-49, and 50-74 years. Such heterogeneity is also present in cause of death structures between sexes and provinces. From 1990 to 2013, leading causes of YLLs changed substantially. In 1990, 16 of 33 provinces had lower respiratory infections or preterm birth complications as the leading causes of YLLs. 15 provinces had cerebrovascular disease and two (Hong Kong and Macao) had ischaemic heart disease. By 2013, 27 provinces had cerebrovascular disease as the leading cause, five had ischaemic heart disease, and one had lung cancer (Hong Kong). Road injuries have become a top ten cause of death in all provinces in mainland China. The most common non-communicable diseases, including ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and cancers (liver, stomach, and lung), contributed much more to YLLs in 2013 compared with 1990., Interpretation: Rapid transitions are occurring across China, but the leading health problems and the challenges imposed on the health system by epidemiological and demographic change differ between groups of Chinese provinces. Localised health policies need to be implemented to tackle the diverse challenges faced by local health-care systems., Funding: China National Science & Technology Pillar Program 2013 (2013BAI04B02) and Bill & Melinda Gates Foundation., (Copyright © 2016 Elsevier Ltd. All rights reserved.)
Published: 2016
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3. Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015 : a systematic analysis for the Global Burden of Disease Study 2015

Author: Kassebaum, Nicholas J., Arora, Megha, Barber, Ryan M., Bhutta, Zulfigar A., Carter, Austin, Casey, Daniel C., Charlson, Fiona J., Coates, Matthew M., Coggeshall, Megan, Cornaby, Leslie, Dandona, Lalit, Dicker, Daniel J., Erskine, Holly E., Ferrari, Alize J., Fitzmaurice, Christina, Foreman, Kyle, Forouzanfar, Mohammad H., Fullman, Nancy, Gething, Peter W., Goldberg, Ellen M., Graetz, Nicholas, Haagsma, Juanita A., Johnson, Catherine, Kemmer, Laura, Khalil, Ibrahim A., Kinfu, Yohannes, Kutz, Michael J., Kyu, Hmwe H., Leung, Janni, Liang, Xiaofeng, Lim, Stephen S., Lozano, Rafael, Mensah, George A., Mikesell, Joe, Mokdad, Ali H., Mooney, Meghan D., Naghavi, Mohsen, Nguyen, Grant, Nsoesie, Elaine, Pigott, David M., Pinho, Christine, Rankin, Zane, Reinig, Nikolas, Salomon, Joshua A., Sandar, Logan, Lallukka, Tea, Meretoja, Atte, Meretoja, Tuomo J., Weiderpass, Elisabete, GBD 2015 DALY & HALE, Clinicum, Department of Public Health, Department of Neurosciences, Neurologian yksikkö, University of Helsinki, Department of Oncology, Department of Medical and Clinical Genetics, and Center for Population, Health and Society
Subjects: MORTALITY, SUSTAINABLE DEVELOPMENT GOALS, 3122 Cancers, 3112 Neurosciences, UNITED-STATES, 187 COUNTRIES, TRENDS, RECOMMENDATIONS, 3142 Public health care science, environmental and occupational health, 3124 Neurology and psychiatry, PREVALENCE, MORBIDITY, BACK-PAIN, 3121 General medicine, internal medicine and other clinical medicine, COMPRESSION
Abstract: Background Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development. Methods We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specific death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate. Findings Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs off set by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2.9 years (95% uncertainty interval 2.9-3.0) for men and 3.5 years (3.4-3.7) for women, while HALE at age 65 years improved by 0.85 years (0.78-0.92) and 1.2 years (1.1-1.3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs. Interpretation Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued efforts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specific health performance and SDG progress. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum. Copyright (C) The Author(s). Published by Elsevier Ltd.
Published: 2016

4. Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015:a systematic analysis for the Global Burden of Disease Study 2015

Author: Kassebaum, Nicholas J., Arora, Megha, Barber, Ryan M., Bhutta, Zulfigar A., Carter, Austin, Casey, Daniel C., Charlson, Fiona J., Coates, Matthew M., Coggeshall, Megan, Cornaby, Leslie, Dandona, Lalit, Dicker, Daniel J., Erskine, Holly E., Ferrari, Alize J., Fitzmaurice, Christina, Foreman, Kyle, Forouzanfar, Mohammad H., Fullman, Nancy, Gething, Peter W., Goldberg, Ellen M., Graetz, Nicholas, Haagsma, Juanita A., Johnson, Catherine, Kemmer, Laura, Khalil, Ibrahim A., Kinfu, Yohannes, Kutz, Michael J., Kyu, Hmwe H., Leung, Janni, Liang, Xiaofeng, Lim, Stephen S., Lozano, Rafael, Mensah, George A., Mikesell, Joe, Mokdad, Ali H., Mooney, Meghan D., Naghavi, Mohsen, Nguyen, Grant, Nsoesie, Elaine, Pigott, David M., Pinho, Christine, Rankin, Zane, Reinig, Nikolas, Salomon, Joshua A., Sandar, Logan, Amare, Azmeraw T., Hoek, Hans W., Singh, Abhishek, and Tura, Abera Kenay
Subjects: MORBIDITY, BACK-PAIN, MORTALITY, SUSTAINABLE DEVELOPMENT GOALS, UNITED-STATES, COMPRESSION, 187 COUNTRIES, TRENDS, RECOMMENDATIONS, PREVALENCE
Abstract: Background Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development. Methods We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specific death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate. Findings Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs off set by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2.9 years (95% uncertainty interval 2.9-3.0) for men and 3.5 years (3.4-3.7) for women, while HALE at age 65 years improved by 0.85 years (0.78-0.92) and 1.2 years (1.1-1.3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs. Interpretation Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued efforts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specific health performance and SDG progress. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum. Copyright (C) The Author(s). Published by Elsevier Ltd.
Published: 2016
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5. 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

Author: Wang, Haidong, Naghavi, Mohsen, Allen, Christine, Barber, Ryan M., Bhutta, Zulfiqar A., Carter, Austin, Casey, Daniel C., Charlson, Fiona J., Chen, Alan Zian, Coates, Matthew M., Coggeshall, Megan, Dandona, Lalit, Dicker, Daniel J., Erskine, Holly E., Ferrari, Alize J., Fitzmaurice, Christina, Foreman, Kyle, Forouzanfar, Mohammad H., Fraser, Maya S., Fullman, Nancy, Gething, Peter W., Goldberg, Ellen M., Graetz, Nicholas, Haagsma, Juanita A., Hay, Simon I., Huynh, Chantal, Johnson, Catherine O., Kassebaum, Nicholas J., Kinfu, Yohannes, Kulikoff, Xie Rachel, Kutz, Michael, Kyu, Hmwe H., Larson, Heidi J., Leung, Janni, Liang, Xiaofeng, Lim, Stephen S., Lind, Margaret, Lozano, Rafael, Marquez, Neal, Mensah, George A., Mikesell, Joe, Mokdad, Ali H., Mooney, Meghan D., Nguyen, Grant, Nsoesie, Elaine, Pigott, David M., Pinho, Christine, Roth, Gregory A., Salomon, Joshua A., Sandar, Logan, Silpakit, Naris, Sligar, Amber, Sorensen, Reed J. D., Stanaway, Jeffrey, Steiner, Caitlyn, Teeple, Stephanie, Thomas, Bernadette A., Troeger, Christopher, VanderZanden, Amelia, Vollset, Stein Emil, Wanga, Valentine, Whiteford, Harvey A., Wolock, Timothy, Zoeckler, Leo, Szoeke, Cassandra E. I., and GBD 2015 Mortality and Causes of Death Collaborators
Subjects: life expectancy, mortality
Abstract: 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.
Published: 2016

6. Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013

Author: Meghan D. Mooney, Ken Takahashi, Andrea Stewart, Jonathan C Brown, Shireen Sindi, Amany H Refaat, Ruben Castro, Sara Sheikhbahaei, Kyle R. Heuton, Gillian M. Hansen, Chante Karimkhani, Bryan K. Phillips, Ibrahim Abubakar, Yohannes Kinfu, Victoria F Bachman, Konstantinos Stroumpoulis, Megan Coggeshall, Lucía Cuevas-Nasu, Yichong Li, Vineet K. Chadha, Andrew G. M. Bulloch, Takayoshi Ohkubo, Don C. Des Jarlais, Giancarlo Logroscino, Francis Apolinary Mhimbira, Jefferson G Fernandes, Cheng Huang, Ejaz Ahmad Khan, Fortuné Gbètoho Gankpé, Roderick J Hay, Itamar S. Santos, Zanfina Ademi, Fiona J Charlson, Norlinah Mohamed Ibrahim, Anwar Rafay, Andrew L. Thorne-Lyman, Juanita A. Haagsma, Emmanuel A. Ameh, John J. McGrath, Massimo Cirillo, Wubegzier Mekonnen, Holly Hagan, Naohiro Yonemoto, Frida Namnyak Ngalesoni, Dietrich Plass, Matias Trillini, David Phillips, Braden Te Ao, Wanqing Chen, Yun Jin Kim, David Rojas-Rueda, Christina Papachristou, Andrew E. Moran, Richard A. Gosselin, Maziar Moradi-Lakeh, Soraya Seedat, Janet L Leasher, Belinda K Lloyd, Lorenzo Monasta, Bruno F. Sunguya, Eun-Kee Park, Eduardo A. Undurraga, Mohammad A. AlMazroa, Mohammad H. Forouzanfar, Young-Ho Khang, Vasiliki Stathopoulou, Dima M. Qato, James Scott, Ileana Heredia-Pi, Luca Ronfani, Haidong Kan, Tasara T. Mazorodze, Murugesan Raju, Saeid Shahraz, Taavi Tillmann, Wang Wenzhi, Neil Pearce, Eric Y. Tenkorang, Aliya Naheed, Ferrán Catalá-López, Sudan Prasad Neupane, Emily Dansereau, Michael McKee, Derrick A Bennett, Mazeda Hossain, Paul S. F. Yip, Grant Nguyen, Norberto Perico, Miguel Angel Alegretti, Babak Eshrati, Boris Bikbov, Palwasha Anwari, Guoqing Hu, Amelia Bertozzi-Villa, Peter A. Meaney, Farshad Farzadfar, Svetlana Popova, Tara Templin, Hmwe H Kyu, Uche S. Uchendu, Kebede Deribe, Sergey Soshnikov, Nobhojit Roy, Daniel Kim, Ilana N. Ackerman, Homie Razavi, Leslie T. Cooper, Sandra Nolte, David T. Felson, John J Huang, Yang Liu, Fiorella Cavalleri, Adrian Davis, Héctor Gómez Dantés, Klara Dokova, Yuantao Hao, Catalina Medina, Austin E Schumacher, Stan Biryukov, Jane Rowley, Arindam Basu, Jose C. Adsuar, Rosana E. Norman, Yousef Khader, Rafael Alfonso-Cristancho, Sukanta Saha, Simón Barquera, Diego Gonzalez-Medina, Philip B. Mitchell, Lars Barregard, Haidong Wang, Yongmei Li, Ami R. Moore, Marie Ng, Raghib Ali, Peter T. Serina, Lijing L Yan, Ayse Abbasoglu Ozgoren, Ricky Leung, Michelle L. Bell, Tim Driscoll, Azmeraw T. Amare, Farshad Pourmalek, Tea Lallukka, Benjamin O Anderson, Raimundas Lunevicius, Corine Karema, Robert G. Weintraub, Erin C Mullany, Anders Larsson, Glen Mola, Paulo A. Lotufo, Luke Nyakarahuka, Sayed Saidul Alam, Louisa Degenhardt, Hugh R. Taylor, E. Ray Dorsey, Suzanne Polinder, Hilton Lam, Urbano Fra Paleo, David Zonies, Rahman Shiri, Marco A Avila, Alicia Elena Beatriz Lawrynowicz, Katya Anne Shackelford, Lynne Gaffikin, Konstantin Kazanjan, Mark T Mackay, Jasvinder A. Singh, Bryan L. Sykes, Sadaf G. Sepanlou, Chantal Huynh, Rakhi Dandona, Logan Sandar, Lavanya Singh, Dietrich Rothenbacher, Theo Vos, Steven E. Lipshultz, Coen H. Van Gool, Peggy P. Chiang, Mark G. Shrime, Christopher J L Murray, Scott Weichenthal, Jae-Hyun Park, Samia Alhabib, Philimon Gona, Christian Kieling, Yuichiro Yano, Ronny Westerman, Thomas Truelsen, Rajeev Gupta, Megan Bohensky, Abdullatif Husseini, Qing Lan, Luke D. Knibbs, Yousef M. Elshrek, H. Ross Anderson, Guohong Jiang, Madeline L. Moyer, Vinod K. Paul, Wim H. van Brakel, Emin Murat Tuzcu, Kara Estep, Lalit Dandona, Uchechukwu K.A. Sampson, Mohammad Tavakkoli, Ying Jiang, Joseph A Wagner, Mitsuru Mukaigawara, In-Hwan Oh, Siyi Shangguan, Noela M. Prasad, Charles D.A. Wolfe, Borja del Pozo-Cruz, Gokalp Kadri Yentur, Hilda L Harb, Elena Alvarez, Carlos A Castañeda-Orjuela, Mustafa Z. Younis, Herbert C. Duber, Erica Leigh Slepak, George A. Mensah, Knud Juel, Graeme J. Hankey, Natan M. Bornstein, Martha Híjar, Johan Ärnlöv, Mohamed Hsairi, Katherine T. Lofgren, Murray B. Stein, Renata Micha, Luigi Naldi, Margreet ten Have, Bolajoko O. Olusanya, Kyle J Foreman, Kenji Shibuya, F. Gerry R. Fowkes, Abdullah Sulieman Terkawi, Rana J. Asghar, Karen M. Tabb, Kovin Naidoo, Rogelio Pérez-Padilla, Honglei Chen, Antônio Luiz Pinho Ribeiro, Rasmus Havmoeller, Yukito Shinohara, Bongani M. Mayosi, Ernst J Kuipers, Konrad Pesudovs, Mouhanad Hammami, Lee Richardson, Rintaro Mori, Thomas D. Fleming, Pouria Heydarpour, Stephen G. Waller, Nicholas Graetz, Chanda Kulkarni, Peter Brooks, Gulfaraz Khan, Marcel Tanner, Van C. Lansingh, François Alla, Jamie Hancock, Yohannes Adama Melaku, Neeraj Bedi, Anthony D. Woolf, Tariku Jibat Beyene, Amanda W Pain, Eric L. Ding, Narayanaswamy Venketasubramanian, Semaw Ferede Abera, Devina Nand, Odgerel Chimed-Ochir, George D Thurston, Victor Aboyans, Alanur Çavlin, Jefferson Traebert, Michael R. Phillips, Yingfeng Zheng, Baffour Awuah, Carlo Irwin A. Panelo, Selen Begüm Uzun, Muhammad Imran Nisar, Samir Soneji, Veena S. Kulkarni, Mukesh Dherani, Stephen S Lim, Andre Keren, Kingsley N. Ukwaja, Sajjad Ur Rahman, Giuseppe Remuzzi, Kjetil Søreide, Blake Thomson, Samath D Dharmaratne, Christopher D. Blosser, David H. Rothstein, Amanda G. Thrift, Fabrizio Tediosi, Andrew H. Kemp, H. Dean Hosgood, Yoshihiro Kokubo, Miia Kivipelto, Amitava Banerjee, Edgar P. Simard, Reza Malekzadeh, Maggie Lind, Robert P. Dellavalle, Emerito Jose A. Faraon, Lydia S. Atkins, Tom Achoki, Aslam Pervaiz, Peter Scarborough, Hans W. Hoek, Ettore Beghi, Emilie Agardh, Abraham D. Flaxman, Dariush Mozaffarian, Juan R. Sanabria, Muluken Dessalegn, David C. Schwebel, Caitlyn Steiner, Ubai Alsharif, Richard C. 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Ray, Driscoll, Tim R, Duber, Herbert C, Ebel, Beth E, Edmond, Karen M, Elshrek, Yousef M, Ermakov, Sergey P, Erskine, Holly E, Faraon, Emerito Jose A, Fay, Derek F, Feigin, Valery L, Felson, David T, Fereshtehnejad, Seyed Mohammad, Fernandes, Jefferson G, Ferrari, Alize J, Flaxman, Abraham D, Fleming, Thomas D, Forouzanfar, Mohammad H, Fowkes, F. Gerry R, Paleo, Urbano Fra, Franklin, Richard C, Gankpé, Fortuné G, Geleijnse, Johanna M, Gessner, Bradford D, Gibney, Katherine B, González Medina, Diego, Gosselin, Richard A, Gotay, Carolyn C, Gouda, Hebe N, Gugnani, Harish C, Gutiérrez, Reyna A, Hafezi Nejad, Nima, Halasa, Yara A, Hamadeh, Randah R, Hankey, Graeme J, Hansen, Gillian M, Harb, Hilda L, Hay, Simon I, Hay, Roderick J, Heredia Pi, Ileana B, Heuton, Kyle R, Hoek, Hans W, Hoffman, Howard J, Hosgood, H. Dean, Hotez, Peter J, Hoy, Damian G, Huang, John J, Iannarone, Marissa L, Iburg, Kim M, Jacobsen, Kathryn H, Jarvis, Deborah L, Jassal, Simerjot K, Jensen, Paul N, Jonas, Jost B, Karema, Corine K, Kassebaum, Nicholas J, Kemp, Andrew H, Kengne, Andre P, Khader, Yousef S, Khalifa, Shams Eldin A, Khan, Ejaz A, Khang, Young Ho, Kinge, Jonas M, Knibbs, Luke D, Kuipers, Ernst J, Kulkarni, Veena S, Kumar, G. Anil, Kyu, Hmwe H, Lansingh, Van C, Lawrynowicz, Alicia E. B, Leasher, Janet L, Levitz, Carly E, Lim, Stephen S, Lipshultz, Steven E, Lloyd, Belinda K, Lofgren, Katherine T, Looker, Katharine J, Lortet Tieulent, Joannie, Lotufo, Paulo A, Lucas, Robyn M, Lyons, Ronan A, Macintyre, Michael F, Mackay, Mark T, Margolis, David J, Marzan, Melvin B, Masci, Joseph R, Mashal, Mohammad T, Mayosi, Bongani M, Mazorodze, Tasara T, Mcgill, Neil W, Mcgrath, John J, Meaney, Peter A, Melaku, Yohannes A, Memish, Ziad A, Mensah, George A, Mhimbira, Francis A, Miller, Ted R, Mills, Edward J, Mitchell, Philip B, Mock, Charles N, Mohammad, Karzan A, Mokdad, Ali H, Mola, Glen L. D, Montine, Thomas J, Mooney, Meghan D, Moore, Ami R, Moradi Lakeh, Maziar, Moran, Andrew E, Moturi, Wilkister N, Moyer, Madeline L, Msemburi, William T, Mueller, Ulrich O, Mullany, Erin C, Murdoch, Michele E, Murthy, Kinnari S, Naidoo, Kovin S, Narayan, K. M. Venkat, Neupane, Sudan P, Newton, Charles R, Ngalesoni, Frida N, Nisar, Muhammad I, Norheim, Ole F, Norman, Rosana E, Oh, In Hwan, Ohno, Summer L, Olusanya, Bolajoko O, Pain, Amanda W, Pandian, Jeyaraj D, Panelo, Carlo Irwin A, Park, Eun Kee, Park, Jae Hyun, Patten, Scott B, Patton, George C, Paul, Vinod K, Pavlin, Boris I, Pereira, David M, Perez Padilla, Rogelio, Perez Ruiz, Fernando, Peterson, Carrie B, Phillips, Michael R, Phillips, Bryan K, Phillips, David E, Piel, Frédéric B, Poulton, Richie G, Prasad, Noela M, Pullan, Rachel L, Qato, Dima M, Quistberg, D. Alex, Rahman, Sajjad U, Rana, Saleem M, Reddy, K. Srinath, Ribeiro, Antonio L, Roberts, D. Allen, Rojas Rueda, David, Roth, Gregory A, Rothstein, David H, Rowley, Jane T, Ruhago, George M, Saeedi, Mohammad Y, Sampson, Uchechukwu K. A, Sanabria, Juan R, Santos, Itamar S, Schneider, Ione J, Schumacher, Austin E, Schwebel, David C, Scott, James G, Sepanlou, Sadaf G, Serina, Peter T, Servan Mori, Edson E, Shackelford, Katya A, Shrime, Mark G, Sigfusdottir, Inga D, Silberberg, Donald H, Simard, Edgar P, Singh, Jasvinder A, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Stanaway, Jeffrey D, Stein, Dan J, Stein, Murray B, Steiner, Timothy J, Stovner, Lars J, Sunguya, Bruno F, Sykes, Bryan L, Tabb, Karen M, Taylor, Hugh R, Ao, Braden J. Te, Temesgen, Awoke M, Tenkorang, Eric Y, Terkawi, Abdullah S, Thorne Lyman, Andrew L, Thrift, Amanda G, Thurston, George D, Tran, Bach X, Tuzcu, Emin M, Uchendu, Uche S, Ukwaja, Kingsley N, Undurraga, Eduardo A, Uzun, Selen B, Van Brakel, Wim H, van Gool, Coen H, Vasankari, Tommi J, Violante, Francesco S, Vlassov, Vasiliy V, Wagner, Gregory R, Waller, Stephen G, Warouw, Tati S, Weintraub, Robert G, Whiteford, Harvey A, Wilkinson, James D, Williams, Thomas N, Wolfe, Charles D, Wolock, Timothy M, Woolf, Anthony D, Yan, Lijing L, Yentür, Gökalp K, Yoon, Seok Jun, Younis, Mustafa Z, Zaki, Maysaa E, Salomon, Joshua A, Lopez, Alan D, Computational Science and Engineering Department [Daresbury] ( STFC ), Science & Technologie Facilities Council, Neuroépidémiologie Tropicale ( NET ), CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Institut Génomique, Environnement, Immunité, Santé, Thérapeutique ( GEIST ), Université de Limoges ( UNILIM ) -Université de Limoges ( UNILIM ), Service de Chirurgie Thoracique et Vasculaire - Médecine vasculaire [CHU Limoges], CHU Limoges, Weill Cornell Medical College - Qatar, Qatar Foundation - Education City, Doha, Maladies chroniques, santé perçue, et processus d'adaptation ( APEMAC ), Université Paris Descartes - Paris 5 ( UPD5 ) -Université de Lorraine ( UL ), Centre d'Investigation Clinique - Epidemiologie Clinique/essais Cliniques Nancy, Cancéropôle du Grand Est-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Karolinska Institute, karolinska institute, Centro de Estudios Avanzados en Zonas Aridas ( CEAZA ), Ecole Polytechnique Fédérale de Lausanne ( EPFL ), Wisconsin Division of Public Health, Regional Genetic Service, St Mary's Hospital, Manchester, Laboratoire d'Ingénierie des Matériaux ( LIM ), Centre National de la Recherche Scientifique ( CNRS ), Computer Science Department [Bristol], University of Bristol [Bristol], Lawrence Berkeley National Laboratory [Berkeley] ( LBNL ), Samsung Research &Development Institute India - Bangalore (Groupe Samsung) ( SRI-B ), Multimedia Research Center ( MRC ), University of Alberta [Edmonton], Division of Biostatistics ( Biostat - MINNEAPOLIS ), University of Minnesota [Minneapolis], Laboratory of Neurologic Diseases, Mario Negri Institute, Milan, University of Southampton [Southampton], Imperial College London, Neurology Department, Ichilov Medical Center, Department of Public Health and Primary Care, Cambridge University, Interactions, transferts, ruptures artistiques et culturels - EA 6301 ( InTRu ), Université de Tours, Institut Jacques Monod ( IJM ), Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), Institute of Parasitology, STAR laboratory, Stanford University [Stanford], Unité de recherche Virologie et Immunologie Moléculaires ( VIM ), Institut National de la Recherche Agronomique ( INRA ), Tennent Institute of Ophthalmology, National University of Singapore ( NUS ), Multidisciplinary Nanotechnology Centre, Swansea University, Department of Computer Sciences [Scheffield], University of Sheffield [Sheffield], Cyprus International Institute for the Environment and Public Health, Harvard School of Public Health, Glasgow Centre for Physical Organic Chemistry, University of Glasgow, King‘s College London, Université Panthéon-Sorbonne - UFR Science Politique ( UP1 UFR11 ), Université Panthéon-Sorbonne ( UP1 ), National Diagnostics Centre ( NDC ), National University of Ireland [Galway] ( NUI Galway ), Arthritis Research UK Epidemiology Unit ( MANCHESTER - Arthritis Research ), University of Manchester [Manchester], CEGOT - Porto, Universidade do Porto [Porto], Advanced Laboratories on Embedded Systems [Roma] ( ALES ), Department of Biology [Miami], University of Miami [Coral Gables], Division of Human Nutrition, Wageningen University and Research Centre [Wageningen] ( WUR ), Spatial Ecology and Epidemiology Group, University of Oxford [Oxford], Department of Civil Engineering [Hamirpur], National Institute of Technology [Hamirpur], GEMMA — Environmental Engineering and Microbiology Research Group, Department of Hydraulic, Maritime and Environmental Engineering, Universitat Politècnica de Catalunya [Barcelona] ( UPC ), Institut National de Recherche et d'Analyse Physico-Chimique ( INRAP ), Institut National de Recherche et d'Analyse Physico-chimique (INRAP-Tunisie), University of Connecticut ( UCONN ), Norwegian Institute for Air Research ( NILU ), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) ( FEMTO-ST ), Université de Franche-Comté ( UFC ) -Centre National de la Recherche Scientifique ( CNRS ) -Ecole Nationale Supérieure de Mécanique et des Microtechniques ( ENSMM ) -Université de Technologie de Belfort-Montbeliard ( UTBM ), Tehran University, Friedrich-Alexander Universität Erlangen-Nürnberg ( FAU ), Secretariat of the Pacific Community, Public Health Division, Sociétés, Acteurs, Gouvernement en Europe ( SAGE ), Université de Strasbourg ( UNISTRA ) -Centre National de la Recherche Scientifique ( CNRS ), School of Physics and Astronomy, Washington State University ( WSU ), Laboratoire de Physique de l'ENS Lyon ( Phys-ENS ), École normale supérieure - Lyon ( ENS Lyon ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ), Institut de recherche en informatique de Toulouse ( IRIT ), Institut National Polytechnique [Toulouse] ( INP ) -Université Toulouse 1 Capitole ( UT1 ) -Université Toulouse - Jean Jaurès ( UT2J ) -Université Toulouse III - Paul Sabatier ( UPS ), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique ( CNRS ), School of Computer Science - China University of Geosciences (China University of Geosciences (East Area)), Université Catholique de Louvain ( UCL ), Div Cyclotron & Radiopharmaceut Sci ( DRDO, INMAS ), Univ New Delhi, University of St Andrews [Scotland], University of Cape Town, Department of Neuroscience, Karolinska Institutet [Stockholm], Institut de Physique Nucléaire d'Orsay ( IPNO ), Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Centre National de la Recherche Scientifique ( CNRS ), Department of Computer Science and Engineering [Daejeon] (Chungnam National University), Lawrence University, Gastroenterology & Hepatology, Tata Research Development and Design Center ( TRDDC ), TCS Innovation Labs, Laboratoire MOLTECH-Anjou [Angers] ( MOLTECH ANJOU ), Université d'Angers ( UA ) -Centre National de la Recherche Scientifique ( CNRS ), University of Helsinki [Helsinki], Google Inc [Mountain View], Research at Google, Swedish Defense Research Agency ( FOI ), Centre de Recherche en Information Biomédicale sino-français ( CRIBS ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Southeast University [Jiangsu]-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Laboratory of Image Science and Technology [Nanjing] ( LIST ), Southeast University [Jiangsu]-School of Computer Science and Engineering, Laboratoire de glaciologie et géophysique de l'environnement ( LGGE ), Observatoire des Sciences de l'Univers de Grenoble ( OSUG ), Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Centre National de la Recherche Scientifique ( CNRS ), School of Business and Informatics, University of Boras, Department of Mechanical and Automation Engineering ( CAD Laboratory ), The Chinese University of Hong Kong [Hong Kong], Università degli studi di Bari, Heuristique et Diagnostic des Systèmes Complexes [Compiègne] ( Heudiasyc ), Université de Technologie de Compiègne ( UTC ) -Centre National de la Recherche Scientifique ( CNRS ), Department of plant pathology and microbiology - centre for sustainable pest and disease management, Rothamsted Research, RGU, Department of Rheumatology and Connective Tissue Diseases, Medical University of Lublin, Barts and The London School of Medicine and Dentistry, Queen Mary University of London ( QMUL ), Centre d'économie de la Sorbonne ( CES ), Université Panthéon-Sorbonne ( UP1 ) -Centre National de la Recherche Scientifique ( CNRS ), Paris School of Economics ( PSE ), Istituto Dalle Molle di Studi sull'Intelligenza Artificiale ( IDSIA ), Università della Svizzera italiana ( USI ) -Scuola universitaria professionale della Svizzera italiana [Manno] ( SUPSI ), Anaesthetics, Southampton University Hospital, Department of Mathematics, University of Iowa [Iowa City], College of Medicine, Alfaisal University, Saudi Ministry of Health, Institut national des recherches agricoles du Bénin, Centre de Recherches agricoles du Sud, Departments of Epidemiology and Nutrition, Unit of Human Nutrition, Agricultural University of Athens, Department of Animal Science, PennState University [Pennsylvania] ( PSU ), University of Virginia, University of Virginia [Charlottesville], Epidemiology and Biostatistics Unit, Institute for Maternal and Child Health - IRCCS ‘‘Burlo Garofolo', Jet Propulsion Laboratory ( JPL ), NASA-California Institute of Technology ( CALTECH ), Division of Cardiovascular Medicine and Channing Division of Network Medicine, Brigham and Women's Hospital [Boston], Division of Gastroenterology and Hepatology, Department of Immunology, Mayo Clinic, Department of Chemistry, Scientific Computing Research Unit, Department of dermatology, Milano University-Azienda Ospedaleria Ospedali Riuniti di Bergamo, Department of epidemiology and Public Health, Faculty of Medicine, Hong Kong Baptist University ( HKBU ), Département Optique ( OPT ), Université européenne de Bretagne ( UEB ) -Télécom Bretagne-Institut Mines-Télécom [Paris], Department of Neurology Lunds University Hospital Lund, Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux ( SAMOVAR ), Institut Mines-Télécom [Paris]-Télécom SudParis ( TSP ) -Centre National de la Recherche Scientifique ( CNRS ), Département Réseaux et Services Multimédia Mobiles ( RS2M ), Institut Mines-Télécom [Paris]-Télécom SudParis ( TSP ), Electrical Engineering and Computer Science Department - Case Western Reserve University, Case Western Reserve University [Cleveland], Institut Lumière Matière [Villeurbanne] ( ILM ), Université Claude Bernard Lyon 1 ( UCBL ), World Health Organization, Nordic School of Public Health, The James Hutton Institute, Sero, Sero consulting, Evolutionary Ecology of Infectious Disease Group, Department of Zoology, Horia Hulubei National Institute for Physics and Nuclear Engineering, Dunedin School of Medicine, University of Otago, Department of Physics, Clarendon Laboratory, Center for TeleInFrastruktur ( CTIF ), Aalborg University [Denmark] ( AAU ), Physikalisches Institut [Freiburg], Albert-Ludwigs-Universität Freiburg, Savoirs, Textes, Langage (STL) - UMR 8163 ( STL ), Université de Lille-Centre National de la Recherche Scientifique ( CNRS ), Dept.of Computer Science, Indian Institute of Technology Madras ( IIT Madras ), Istituto Mario Negri Bergamo, Centro Ricerche e Trapianti Villa Camozzi, Universidade Estadual Paulista Júlio de Mesquita ( UNESP ), Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Université Grenoble Alpes - UFR Médecine ( UGA UFRM ), Université Grenoble Alpes ( UGA ), Clinical Epidemiology and Aging Research, German Cancer Research Center, Institut Cochin ( UM3 (UMR 8104 / U1016) ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Symantec, European Microsoft Innovation Center ( EMIC ), Microsoft Corporation [Redmond, Wash.], Laboratoire de Mécanique, Physique et Géosciences ( LMPG ), Université Le Havre Normandie ( ULH ), Normandie Université ( NU ) -Normandie Université ( NU ), Novartis institute for tropical diseases, Institut de Génétique et de Biologie Moléculaire et Cellulaire ( IGBMC ), Université de Strasbourg ( UNISTRA ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Departments of Anatomy and Cell Biology, Wayne State University School of Medicine, Departments of Ophthalmology, Departments of Applied Physics [New Haven], Yale University [New Haven], Center for Mathematical Modeling ( CMM ), Universidad de Santiago de Chile [Santiago] ( USACH ), Laboratory for Atmospheric and Space Physics [Boulder] ( LASP ), University of Colorado Boulder [Boulder], University of Occupational and Environmental Health [Kitakyushu] ( UEOH ), Department of Computer Science and Engineering [New Delhi], Indian Institute of Technology Delhi ( IIT Delhi ), Institut de Recherche sur les Phénomènes Hors Equilibre ( IRPHE ), Aix Marseille Université ( AMU ) -Ecole Centrale de Marseille ( ECM ) -Centre National de la Recherche Scientifique ( CNRS ), GlaxoSmithKline, Imperial College London-Clinical Imaging Center, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, Yale School of Medicine-Yale School of Medicine-Yale Stem Cell Center, Maclean Building, Benson Lane, Crowmarsh Gifford, Centre for Ecology and Hydrology, Nanoscience Institute ( NEST ), Dipartimento di Fisica, Università di Pisa, Aristotle University of Thessaloniki, Laboratory Of Immune Cell Biology ( LICB ), National Institutes of Health ( NIH ), Institute of Human Genetics, Bonn Universität [Bonn], Occupational Health Unit, Bologna University Hospital-Sant'Orsola-Malpighi Polyclinic, Royal Institute of Technology [Stockholm] ( KTH ), Institut für Informatik [München/Munich] ( LMU ), Ludwig-Maximilians-Universität München, NICTA [Eveleigh], National ICT Australia [Sydney] ( NICTA ), Manchester Academic Health Sciences Centre, Institut d'Histoire et de Philosophie des Sciences et des Techniques ( IHPST ), Université Panthéon-Sorbonne ( UP1 ) -Département d'Etudes Cognitives - ENS Paris ( DEC ), École normale supérieure - Paris ( ENS Paris ) -École normale supérieure - Paris ( ENS Paris ) -Centre National de la Recherche Scientifique ( CNRS ), Ghent University [Belgium] ( UGENT ), German Research Centre for Geosciences - Helmholtz-Centre Potsdam ( GFZ ), Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique ( LHEEA ), École Centrale de Nantes ( ECN ) -Centre National de la Recherche Scientifique ( CNRS ), Institut de Recherche en Génie Civil et Mécanique ( GeM ), Université de Nantes ( UN ) -École Centrale de Nantes ( ECN ) -Centre National de la Recherche Scientifique ( CNRS ), Neurorestoration Group, King‘s College London-Wolfson Centre for Age-related Diseases, Department of Computer Science [KAIST] ( CS ), Korea Advanced Institute of Science and Technology ( KAIST ), Laboratoire de l'Accélérateur Linéaire ( LAL ), Natl Engn Res Ctr Vegetables, Key Lab Biol & Genet Improvement Hort Crops N Chi, Beijing Acad Agr & Forestry Sci, University Hospital Puerta de Hierro, Madrid, Computational Science and Engineering Department [Daresbury] (STFC), Neuroépidémiologie Tropicale (NET), CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM), Weill Cornell Medicine [Qatar], Maladies chroniques, santé perçue, et processus d'adaptation (APEMAC), Université Paris Descartes - Paris 5 (UPD5)-Université de Lorraine (UL), Cancéropôle du Grand Est-Institut National de la Santé et de la Recherche Médicale (INSERM), Centro de Estudios Avanzados en Zonas Aridas (CEAZA), Ecole Polytechnique Fédérale de Lausanne (EPFL), Laboratoire d'Ingénierie des Matériaux (LIM), Centre National de la Recherche Scientifique (CNRS), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Samsung Research &Development Institute India - Bangalore (Groupe Samsung) (SRI-B), Multimedia Research Center (MRC), University of Alberta, Division of Biostatistics (Biostat - MINNEAPOLIS), University of Minnesota [Twin Cities] (UMN), University of Minnesota System-University of Minnesota System, University of Southampton, University of Cambridge [UK] (CAM), Interactions, transferts, ruptures artistiques et culturels - EA 6301 (InTRu), Université de Tours (UT), Institut Jacques Monod (IJM (UMR_7592)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Stanford University, Unité de recherche Virologie et Immunologie Moléculaires (VIM (UR 0892)), Institut National de la Recherche Agronomique (INRA), National University of Singapore (NUS), Université Paris 1 Panthéon-Sorbonne - UFR Science Politique (UP1 UFR11), Université Paris 1 Panthéon-Sorbonne (UP1), National Diagnostics Centre (NDC), National University of Ireland [Galway] (NUI Galway), Arthritis Research UK Epidemiology Unit (MANCHESTER - Arthritis Research), Universidade do Porto = University of Porto, Advanced Laboratories on Embedded Systems [Roma] (ALES), Wageningen University and Research [Wageningen] (WUR), University of Oxford, Universitat Politècnica de Catalunya [Barcelona] (UPC), Institut National de Recherche et d'Analyse Physico-Chimique (INRAP), University of Connecticut (UCONN), Norwegian Institute for Air Research (NILU), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), University of Tehran, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Sociétés, Acteurs, Gouvernement en Europe (SAGE), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), The George Washington University (GW), Washington State University (WSU), Laboratoire de Physique de l'ENS Lyon (Phys-ENS), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), Université Catholique de Louvain = Catholic University of Louvain (UCL), Div Cyclotron & Radiopharmaceut Sci (DRDO, INMAS), School of Physics and Astronomy [St Andrews], Tata Research Development and Design Center (TRDDC), MOLTECH-Anjou, Université d'Angers (UA)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Swedish Defense Research Agency (FOI), Centre de Recherche en Information Biomédicale sino-français (CRIBS), Université de Rennes (UR)-Southeast University [Jiangsu]-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratory of Image Science and Technology [Nanjing] (LIST), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Department of Mechanical and Automation Engineering (CAD Laboratory), Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro (UNIBA), Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS), Biotechnology and Biological Sciences Research Council (BBSRC)-Biotechnology and Biological Sciences Research Council (BBSRC), Queen Mary University of London (QMUL), Centre d'économie de la Sorbonne (CES), Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS), Paris School of Economics (PSE), Université Paris 1 Panthéon-Sorbonne (UP1)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA), Università della Svizzera italiana = University of Italian Switzerland (USI)-Scuola universitaria professionale della Svizzera italiana = University of Applied Sciences and Arts of Southern Switzerland [Manno] (SUPSI), Pennsylvania State University (Penn State), Penn State System-Penn State System, Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), Hong Kong Baptist University (HKBU), Département Optique (OPT), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Département Réseaux et Services Multimédia Mobiles (TSP - RS2M), University of Melbourne, Organisation Mondiale de la Santé / World Health Organization Office (OMS / WHO), University of Otago [Dunedin, Nouvelle-Zélande], Center for TeleInFrastruktur (CTIF), Aalborg University [Denmark] (AAU), Savoirs, Textes, Langage (STL) - UMR 8163 (STL), Université de Lille-Centre National de la Recherche Scientifique (CNRS), Indian Institute of Technology Madras (IIT Madras), Universidade Estadual Paulista Júlio de Mesquita Filho = São Paulo State University (UNESP), Erasmus University Medical Center [Rotterdam] (Erasmus MC), Université Grenoble Alpes - UFR Médecine (UGA UFRM), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Institut Cochin (IC UM3 (UMR 8104 / U1016)), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), European Microsoft Innovation Center (EMIC), Laboratoire de Mécanique, Physique et Géosciences (LMPG), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU), Novartis Institute for Tropical Diseases (NITD), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Center for Mathematical Modeling (CMM), Universidad de Chile = University of Chile [Santiago] (UCHILE), Laboratory for Atmospheric and Space Physics [Boulder] (LASP), University of Colorado [Boulder], University of Occupational and Environmental Health [Kitakyushu] (UEOH), Indian Institute of Technology Delhi (IIT Delhi), Institut de Recherche sur les Phénomènes Hors Equilibre (IRPHE), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Yale University [New Haven]-Yale School of Medicine [New Haven, Connecticut] (YSM), Nanoscience Institute (NEST), University of Pisa - Università di Pisa, Laboratory Of Immune Cell Biology (LICB), National Institutes of Health [Bethesda] (NIH), Rheinische Friedrich-Wilhelms-Universität Bonn, Royal Institute of Technology [Stockholm] (KTH ), Institut für Informatik [München/Munich] (LMU), Ludwig-Maximilians-Universität München (LMU), National ICT Australia [Sydney] (NICTA), Institut d'Histoire et de Philosophie des Sciences et des Techniques (IHPST), Université Paris 1 Panthéon-Sorbonne (UP1)-Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Universiteit Gent = Ghent University (UGENT), German Research Centre for Geosciences - Helmholtz-Centre Potsdam (GFZ), Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique (LHEEA), École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche en Génie Civil et Mécanique (GeM), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [KAIST] (CS), Korea Advanced Institute of Science and Technology (KAIST), Kardiyoloji, Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM)-CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Minnesota [Twin Cities], Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), Unité de recherche Virologie et Immunologie Moléculaires (VIM), Université Panthéon-Sorbonne - UFR Science Politique (UP1 UFR11), Université Panthéon-Sorbonne (UP1), Wageningen University and Research Centre [Wageningen] (WUR), Institut National de Recherche et d'Analyse Physico-chimique (Ariana, Tunisie) (INRAP), Université de Franche-Comté (UFC)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Technologie de Belfort-Montbeliard (UTBM), George Washington University (GW), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, Université Catholique de Louvain (UCL), MOLTECH-ANJOU (MOLTECH-ANJOU), Université d'Angers (UA)-Centre National de la Recherche Scientifique (CNRS), University of Helsinki, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Southeast University [Jiangsu]-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Université Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS), Università della Svizzera italiana (USI)-Scuola universitaria professionale della Svizzera italiana [Manno] (SUPSI), California Institute of Technology (CALTECH)-NASA, Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Centre National de la Recherche Scientifique (CNRS), Département Réseaux et Services Multimédia Mobiles (RS2M), Universidade Estadual Paulista Júlio de Mesquita Filho [São José do Rio Preto] (UNESP), Université Grenoble Alpes (UGA), Universidad de Santiago de Chile [Santiago] (USACH), Yale University [New Haven]-Yale University School of Medicine, Université Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris), Ghent University [Belgium] (UGENT), Université de Nantes - Faculté des Sciences et des Techniques, Grelier, Elisabeth, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse III - Paul Sabatier (UT3), Universidade do Porto, Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Université Toulouse 1 Capitole (UT1), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Università degli studi di Bari Aldo Moro (UNIBA), École des Ponts ParisTech (ENPC)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-École des hautes études en sciences sociales (EHESS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Università della Svizzera italiana = University of Italian Switzerland (USI)-Scuola universitaria professionale della Svizzera italiana [Manno] (SUPSI), Institut Mines-Télécom [Paris] (IMT)-Télécom Bretagne-Université européenne de Bretagne - European University of Brittany (UEB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Universiteit Gent = Ghent University [Belgium] (UGENT), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-CHU Limoges-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Belfort-Montbeliard (UTBM), Institut de Chimie du CNRS (INC)-Université d'Angers (UA)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre National de la Recherche Scientifique (CNRS)-École Centrale de Nantes (ECN), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Wolfson Centre for Age-related Diseases-King‘s College London, Cell biology, Public Health, Epidemiology, Health Technology Assessment (HTA), Erasmus MC other, Pathology, and Cardiothoracic Surgery
Subjects: Gerontology, Male, CHANGING RELATION, Nutrition and Disease, MESH : Life Expectancy, MESH : Aged, ECONOMIC-DEVELOPMENT, Poison control, MESH: Global Health, Global Health, Socioeconomic Factor, Communicable Disease, MESH : Chronic Disease, Health Transition, Voeding en Ziekte, Quality-Adjusted Life Year, SELF-RATED HEALTH, MESH : Socioeconomic Factors, Medicine, MESH : Female, MESH: Mortality, Premature, 2. Zero hunger, MESH: Aged, education.field_of_study, MESH: Middle Aged, Mortality rate, Medicine (all), GBD2013 diseases, [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, General Medicine, Middle Aged, 3. Good health, MESH : Wounds and Injuries, Epidemiological transition, MESH: Quality-Adjusted Life Years, MESH: Communicable Diseases, NONCOMMUNICABLE DISEASES, Female, Quality-Adjusted Life Years, MESH: Life Expectancy, MESH: Health Transition, Human, MESH: Socioeconomic Factors, ACUTE MYOCARDIAL-INFARCTION, MESH : Male, MORTALITY TRENDS, Population, MESH : Health Transition, Communicable Diseases, Article, Life Expectancy, EUROPEAN-UNION, SDG 3 - Good Health and Well-being, General & Internal Medicine, SYSTEMATIC ANALYSIS, Disability-adjusted life year, Humans, Life Science, MESH : Middle Aged, Mortality, education, Premature, MESH : Mortality, Premature, VLAG, Aged, MESH: Humans, business.industry, Mortality, Premature, MESH: Chronic Disease, MESH : Communicable Diseases, Wounds and Injurie, MESH : Humans, MESH : Quality-Adjusted Life Years, Non-communicable disease, Chronic Disease, Socioeconomic Factors, Wounds and Injuries, medicine.disease, MESH: Male, LOW SOCIOECONOMIC-STATUS, Years of potential life lost, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, MESH: Wounds and Injuries, Life expectancy, RISK-FACTORS, MESH : Global Health, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, MESH: Female, Demography
Abstract: Summary Background The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age–sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development. Methods We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time. Findings Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6–6·6), from 65·3 years (65·0–65·6) in 1990 to 71·5 years (71·0–71·9) in 2013, HALE at birth rose by 5·4 years (4·9–5·8), from 56·9 years (54·5–59·1) to 62·3 years (59·7–64·8), total DALYs fell by 3·6% (0·3–7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6–29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non–communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries. Interpretation Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition—in which increasing sociodemographic status brings structured change in disease burden—is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions. Funding Bill & Melinda Gates Foundation. BACKGROUND: The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age-sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development. METHODS: We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time. FINDINGS: Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6-6·6), from 65·3 years (65·0-65·6) in 1990 to 71·5 years (71·0-71·9) in 2013, HALE at birth rose by 5·4 years (4·9-5·8), from 56·9 years (54·5-59·1) to 62·3 years (59·7-64·8), total DALYs fell by 3·6% (0·3-7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6-29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non-communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries. INTERPRETATION: Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition-in which increasing sociodemographic status brings structured change in disease burden-is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions. FUNDING: Bill & Melinda Gates Foundation.
Published: 2015
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7. Mapping Plasmodium falciparum Mortality in Africa between 1990 and 2015.

Author: Gething, Peter W., Casey, Daniel C., Weiss, Daniel J., Bisanzio, Donal, Bhatt, Samir, Cameron, Ewan, Battle, Katherine E., Dalrymple, Ursula, Rozier, Jennifer, Rao, Puja C., Kutz, Michael J., Barber, Ryan M., Huynh, Chantal, Shackelford, Katya A., Coates, Matthew M., Nguyen, Grant, Fraser, Maya S., Kulikoff, Rachel, Haidong Wang, and Naghavi, Mohsen
Subjects: *PLASMODIUM falciparum, *MALARIA prevention, *MATHEMATICAL mappings, *DEATH rate, *PUBLIC health, *HISTORY, *DRUG therapy for malaria, *ANTIMALARIALS, *PREVENTION of communicable diseases, *COMPARATIVE studies, *GEOGRAPHIC information systems, *MALARIA, *PROTECTIVE clothing, *RESEARCH methodology, *MEDICAL cooperation, *MORTALITY, *PARASITES, *PROTOZOA, *RESEARCH, *RESEARCH funding, *EVALUATION research, *DISEASE prevalence, *STATISTICAL models, *THERAPEUTICS
Abstract: Background: Malaria control has not been routinely informed by the assessment of subnational variation in malaria deaths. We combined data from the Malaria Atlas Project and the Global Burden of Disease Study to estimate malaria mortality across sub-Saharan Africa on a grid of 5 km2 from 1990 through 2015.Methods: We estimated malaria mortality using a spatiotemporal modeling framework of geolocated data (i.e., with known latitude and longitude) on the clinical incidence of malaria, coverage of antimalarial drug treatment, case fatality rate, and population distribution according to age.Results: Across sub-Saharan Africa during the past 15 years, we estimated that there was an overall decrease of 57% (95% uncertainty interval, 46 to 65) in the rate of malaria deaths, from 12.5 (95% uncertainty interval, 8.3 to 17.0) per 10,000 population in 2000 to 5.4 (95% uncertainty interval, 3.4 to 7.9) in 2015. This led to an overall decrease of 37% (95% uncertainty interval, 36 to 39) in the number of malaria deaths annually, from 1,007,000 (95% uncertainty interval, 666,000 to 1,376,000) to 631,000 (95% uncertainty interval, 394,000 to 914,000). The share of malaria deaths among children younger than 5 years of age ranged from more than 80% at a rate of death of more than 25 per 10,000 to less than 40% at rates below 1 per 10,000. Areas with high malaria mortality (>10 per 10,000) and low coverage (<50%) of insecticide-treated bed nets and antimalarial drugs included much of Nigeria, Angola, and Cameroon and parts of the Central African Republic, Congo, Guinea, and Equatorial Guinea.Conclusions: We estimated that there was an overall decrease of 57% in the rate of death from malaria across sub-Saharan Africa over the past 15 years and identified several countries in which high rates of death were associated with low coverage of antimalarial treatment and prevention programs. (Funded by the Bill and Melinda Gates Foundation and others.). [ABSTRACT FROM AUTHOR]
Published: 2016
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8. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Author: Murray, Christopher J. L., GBD 2013 Risk Factors Collaborators, Forouzanfar, Mohammad H, Alexander, Lily, Anderson, H Ross, Bachman, Victoria F, Biryukov, Stan, Brauer, Michael, Burnett, Richard, Casey, Daniel, Coates, Matthew M, Cohen, Aaron, Delwiche, Kristen, Estep, Kara, Frostad, Joseph J, Kc, Astha, Kyu, Hmwe H, Moradi-Lakeh, Maziar, Ng, Marie, and Slepak, Erica Leigh
Subjects: *DISEASE prevalence, *MEDICAL care research, *ETIOLOGY of diseases, *PREVENTIVE medicine, *MORTALITY
Abstract: Background: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.Methods: Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk-outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990-2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol.Findings: All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8-58·5) of deaths and 41·6% (40·1-43·0) of DALYs. Risks quantified account for 87·9% (86·5-89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa.Interpretation: Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.Funding: Bill & Melinda Gates Foundation. [ABSTRACT FROM AUTHOR]
Published: 2015
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9. 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

Author: Haidong, Wang, Mohsen, Naghavi, Christine, Allen, Ryan M, Barber Zulfi, qar A, Bhutta, Austin, Carter, Daniel C, Casey Fiona, J Charlson, Alan Zian, Chen Matthew, M Coates, Megan, Coggeshall, Lalit, Dandona, Daniel J, Dicker Holly, E Erskine, Alize J, Ferrari, Christina, Fitzmaurice, Kyle, Foreman, Mohammad H, Forouzanfar Maya, S Fraser, Nancy, Fullman, Peter W, Gething Ellen, M Goldberg, Nicholas, Graetz, Juanita A, Haagsma Simon, I Hay, Chantal, Huynh, Catherine O, Johnson Nicholas, J Kassebaum, Yohannes, Kinfu, Xie Rachel, Kulikoff, Michael, Kutz, Hmwe H, Kyu Heidi, J Larson, Janni, Leung, Xiaofeng, Liang, Stephen S, Lim, Margaret, Lind, Rafael, Lozano, Neal, Marquez, George A, Mensah, Joe, Mikesell, Ali H, Mokdad Meghan, D Mooney, Grant, Nguyen, Elaine, Nsoesie, David M, Pigott, Christine, Pinho, Gregory A, Roth Joshua, A Salomon, Logan, Sandar, Naris, Silpakit, Amber, Sligar, Reed J, D Sorensen, Jeff rey, Stanaway, Caitlyn, Steiner, Stephanie, Teeple, Bernadette A, Thomas, Christopher, Troeger, Amelia, VanderZanden, Stein Emil, Vollset, Valentine, Wanga, Harvey A, Whiteford, Timothy, Wolock, Leo, Zoeckler, Kalkidan Hassen, Abate, Cristiana, Abbafati, Kaja M, Abbas, Foad, Abd-Allah, Semaw Ferede, Abera Daisy, M X, Abreu Laith, J Abu-Raddad, Gebre Yitayih, Abyu, Tom, Achoki, Ademola Lukman, Adelekan Zanfi, na Ademi, Arsène Kouablan, Adou José, C Adsuar, Kossivi Agbelenko, Afanvi, Ashkan, Afshin, Emilie Elisabet, Agardh, Arnav, Agarwal, Anurag, Agrawal, Aliasghar Ahmad, Kiadaliri Oluremi, N Ajala, Ali Shafqat, Akanda Rufus, Olusola Akinyemi, Tomi F, Akinyemiju, Nadia, Akseer, Faris Hasan, Al Lami, Samer, Alabed, Ziyad, Al-Aly, Khurshid, Alam, Noore K, M Alam, Deena, Alasfoor, Saleh Fahed, Aldhahri Robert, William Aldridge, Miguel Angel, Alegretti Alicia, V Aleman, Zewdie Aderaw, Alemu Lily, T Alexander, Samia, Alhabib, Raghib, Ali, Ala’a, Alkerwi, François, Alla, Peter, Allebeck, Rajaa, Al-Raddadi, Ubai, Alsharif, Khalid A, Altirkawi Elena, Alvarez Martin, Nelson, Alvis-Guzman, Azmeraw T, Amare Adeladza, Kofi Amegah, Emmanuel A, Ameh, Heresh, Amini, Walid, Ammar, Stephen Marc, Amrock Hjalte, H Andersen, Benjamin O, Anderson Gregory, M Anderson, Carl Abelardo, T Antonio, Atsede Fantahun, Aregay, Johan, Ärnlöv, Valentina S, Arsic Arsenijevic, Al, Artaman, Hamid, Asayesh, Rana Jawad, Asghar, Suleman, Atique, Euripide Frinel, G Arthur, Avokpaho, Ashish, Awasthi, Peter, Azzopardi, Umar, Bacha, Alaa, Badawi, Maria C, Bahit, Kalpana, Balakrishnan, Amitava, Banerjee, Aleksandra, Barac, Suzanne L, Barker-Collo, Till, Bärnighausen, Lars, Barregard, Lope H, Barrero, Arindam, Basu, Sanjay, Basu, Yibeltal Tebekaw, Bayou, Shahrzad, Bazargan-Hejazi, Justin, Beardsley, Neeraj, Bedi, Ettore, Beghi, Haileeyesus Adamu, Belay, Brent, Bell, Michelle L, Bell Aminu, K Bello, Derrick A, Bennett Isabela, M Bensenor, Adugnaw, Berhane, Eduardo, Bernabé, Balem Demtsu, Betsu Addisu, Shunu Beyene, Neeraj, Bhala, Ashish, Bhalla, Sibhatu, Biadgilign, Boris, Bikbov, 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Teshome, Gebrehiwot, Tsegaye Tsewelde, Gebremedhin, Amanuel Tesfay, Gebru, Alemseged Aregay, Geleijnse, Johanna M, Gessner, Bradford D, Ghoshal, Aloke Gopal, Gibney, Katherine B, Gillum, Richard F, Gilmour, Stuart, Giref, Ababi Zergaw, Giroud, Maurice, Gishu, Melkamu Dedefo, Giussani, Giorgia, Glaser, Elizabeth, Godwin, William W, Gomez-Dantes, Hector, Gona, Philimon, Goodridge, Amador, Gopalani, Sameer Vali, Gosselin, Richard A, Gotay, Carolyn C, Goto, Atsushi, Gouda, Hebe N, Greaves, Felix, Gugnani, Harish Chander, Gupta, Rahul, Gupta, Rajeev, Gupta, Vipin, Gutiérrez, Reyna A, Hafezi-Nejad, Nima, Haile, Demewoz, Hailu, Alemayehu Desalegne, Hailu, Gessessew Bugssa, Halasa, Yara A, Hamadeh, Randah Ribhi, Hamidi, Samer, Hancock, Jamie, Handal, Alexis J, Hankey, Graeme J, Hao, Yuantao, Harb, Hilda L, Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Havmoeller, Rasmu, Heckbert, Susan R, Heredia-Pi, Ileana Beatriz, Heydarpour, Pouria, Hilderink, Henk B M, Hoek, Hans W, Hogg, Robert S, Horino, Masako, Horita, Nobuyuki, Hosgood, H Dean, Hotez, Peter J, Hoy, Damian G, Hsairi, Mohamed, Htet, Aung Soe, Htike, Maung Maung Than, Hu, Guoqing, Huang, Cheng, Huang, Hsiang, Huiart, Laetitia, Husseini, Abdullatif, Huybrechts, Inge, Huynh, Grace, Iburg, Kim Moesgaard, Innos, Kaire, Inoue, Manami, Iyer, Veena J, Jacobs, Troy A, Jacobsen, Kathryn H, Jahanmehr, Nader, Jakovljevic, Mihajlo B, James, Peter, Javanbakht, Mehdi, Jayaraman, Sudha P, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jensen, Paul N, Jha, Vivekanand, Jiang, Guohong, Jiang, Ying, Jibat, Tariku, Jimenez-Corona, Aida, Jonas, Jost B, Joshi, Tushar Kant, Kabir, Zubair, Kamal, Ritul, Kan, Haidong, Kant, Surya, Karch, André, Karema, Corine Kakizi, Karimkhani, Chante, Karletsos, Dimitri, Karthikeyan, Ganesan, Kasaeian, Amir, Katibeh, Marzieh, Kaul, Anil, Kawakami, Norito, Kayibanda, Jeanne Françoise, Keiyoro, Peter Njenga, Kemmer, Laura, Kemp, Andrew Haddon, Kengne, Andre Pascal, Keren, Andre, Kereselidze, Maia, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khalil, Ibrahim A, Khan, Abdur Rahman, Khan, Ejaz Ahmad, Khang, Young-Ho, Khera, Sahil, Khoja, Tawfik Ahmed Muthafer, Kieling, Christian, Kim, Daniel, Kim, Yun Jin, Kissela, Brett M, Kissoon, Niranjan, Knibbs, Luke D, Knudsen, Ann Kristin, Kokubo, Yoshihiro, Kolte, Dhaval, Kopec, Jacek A, Kosen, Soewarta, Koul, Parvaiz A, Koyanagi, Ai, Krog, Norun Hjertager, Defo, Barthelemy Kuate, Bicer, Burcu Kucuk, Kudom, Andreas A, Kuipers, Ernst J, Kulkarni, Veena S, Kumar, G Anil, Kwan, Gene F, Lal, Aparna, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lam, Jennifer O, Langan, Sinead M, Lansingh, Van C, Larsson, Ander, Laryea, Dennis Odai, Latif, Asma Abdul, Lawrynowicz, Alicia Elena Beatriz, Leigh, Jame, Levi, Miriam, Li, Yongmei, Lindsay, M Patrice, Lipshultz, Steven E, Liu, Patrick Y, Liu, Shiwei, Liu, Yang, Lo, Loon-Tzian, Logroscino, Giancarlo, Lotufo, Paulo A, Lucas, Robyn M, Lunevicius, Raimunda, Lyons, Ronan A, Ma, Stefan, Machado, Vasco Manuel Pedro, Mackay, Mark T, Maclachlan, Jennifer H, Razek, Hassan Magdy Abd El, Magdy, Mohammed, Razek, Abd El, Majdan, Marek, Majeed, Azeem, Malekzadeh, Reza, Manamo, Wondimu Ayele Ayele, Mandisarisa, John, Mangalam, Srikanth, Mapoma, Chabila C, Marcenes, Wagner, Margolis, David Joel, Martin, Gerard Robert, Martinez-Raga, Jose, Marzan, Melvin Barriento, Masiye, Felix, Mason-Jones, Amanda J, Massano, João, Matzopoulos, Richard, Mayosi, Bongani M, Mcgarvey, Stephen Theodore, Mcgrath, John J, Mckee, Martin, Mcmahon, Brian J, Meaney, Peter A, Mehari, Alem, Mehndiratta, Man Mohan, Mejia-Rodriguez, Fabiola, Mekonnen, Alemayehu B, Melaku, Yohannes Adama, Memiah, Peter, Memish, Ziad A, Mendoza, Walter, Meretoja, Atte, Meretoja, Tuomo J, Mhimbira, Francis Apolinary, Micha, Renata, Miller, Ted R, Mirarefin, Mojde, Misganaw, Awoke, Mock, Charles N, Mohammad, Karzan Abdulmuhsin, Mohammadi, Alireza, Mohammed, Shafiu, Mohan, Viswanathan, Mola, Glen Liddell D, Monasta, Lorenzo, Hernandez, Julio Cesar Montañez, Montero, Pablo, Montico, Marcella, Montine, Thomas J, Moradi-Lakeh, Maziar, Morawska, Lidia, Morgan, Katherine, Mori, Rintaro, Mozaffarian, Dariush, Mueller, Ulrich O, Murthy, Gudlavalleti Venkata Satyanarayana, Murthy, Sriniva, Musa, Kamarul Imran, Nachega, Jean B, Nagel, Gabriele, Naidoo, Kovin S, Naik, Nitish, Naldi, Luigi, Nangia, Vinay, Nash, Deni, Nejjari, Chakib, Neupane, Suba, Newton, Charles R, Newton, John N, Ng, Marie, Ngalesoni, Frida Namnyak, de Dieu Ngirabega, Jean, Nguyen, Quyen Le, Nisar, Muhammad Imran, Pete, Patrick Martial Nkamedjie, Nomura, Marika, Norheim, Ole F, Norman, Paul E, Norrving, Bo, Nyakarahuka, Luke, Ogbo, Felix Akpojene, Ohkubo, Takayoshi, Ojelabi, Foluke Adetola, Olivares, Pedro R, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Opio, John Nelson, Oren, Eyal, Ortiz, Alberto, Osman, Majdi, Ota, Erika, Ozdemir, Raziye, Pa, Mahesh, Pandian, Jeyaraj D, Pant, Puspa Raj, Papachristou, Christina, Park, Eun-Kee, Park, Jae-Hyun, Parry, Charles D, Parsaeian, Mahboubeh, Caicedo, Angel J Paternina, Patten, Scott B, Patton, George C, Paul, Vinod K, Pearce, Neil, Pedro, João Mário, Stokic, Ljiljana Pejin, Pereira, David M, Perico, Norberto, Pesudovs, Konrad, Petzold, Max, Phillips, Michael Robert, Piel, Frédéric B, Pillay, Julian David, Plass, Dietrich, Platts-Mills, James A, Polinder, Suzanne, Pope, C Arden, Popova, Svetlana, Poulton, Richie G, Pourmalek, Farshad, Prabhakaran, Dorairaj, Qorbani, Mostafa, Quame-Amaglo, Justice, Quistberg, D Alex, Rafay, Anwar, Rahimi, Kazem, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Rajavi, Zhale, Rajsic, Sasa, Raju, Murugesan, Rakovac, Ivo, Rana, Saleem M, Ranabhat, Chhabi L, Rangaswamy, Thara, Rao, Puja, Rao, Sowmya R, Refaat, Amany H, Rehm, Jürgen, Reitsma, Marissa B, Remuzzi, Giuseppe, Resnikoff, Serge, Ribeiro, Antonio L, Ricci, Stefano, Blancas, Maria Jesus Rio, Roberts, Bayard, Roca, Anna, Rojas-Rueda, David, Ronfani, Luca, Roshandel, Gholamreza, Rothenbacher, Dietrich, Roy, Ambuj, Roy, Nawal K, Ruhago, George Mugambage, Sagar, Rajesh, Saha, Sukanta, Sahathevan, Ramesh, Saleh, Muhammad Muhammad, Sanabria, Juan R, Sanchez-Niño, Maria Dolore, Sanchez-Riera, Lidia, Santos, Itamar S, Sarmiento-Suarez, Rodrigo, Sartorius, Benn, Satpathy, Maheswar, Savic, Miloje, Sawhney, Monika, Schaub, Michael P, Schmidt, Maria Inê, Schneider, Ione J C, Schöttker, Ben, Schutte, Aletta E, Schwebel, David C, Seedat, Soraya, Sepanlou, Sadaf G, Servan-Mori, Edson E, Shackelford, Katya A, Shaddick, Gavin, Shaheen, Amira, Shahraz, Saeid, Shaikh, Masood Ali, Shakh-Nazarova, Marina, Sharma, Rajesh, She, Jun, Sheikhbahaei, Sara, Shen, Jiabin, Shen, Ziyan, Shepard, Donald S, Sheth, Kevin N, Shetty, Balakrishna P, Shi, Peilin, Shibuya, Kenji, Shin, Min-Jeong, Shiri, Rahman, Shiue, Ivy, Shrime, Mark G, Sigfusdottir, Inga Dora, Silberberg, Donald H, Silva, Diego Augusto Santo, Silveira, Dayane Gabriele Alve, 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Bach Xuan, Truelsen, Thoma, Trujillo, Ulise, Tura, Abera Kenay, Tuzcu, Emin Murat, Uchendu, Uche S, Ukwaja, Kingsley N, Undurraga, Eduardo A, Uthman, Olalekan A, Dingenen, Rita Van, van Donkelaar, Aaron, Vasankari, Tommi, Vasconcelos, Ana Maria Nogale, Venketasubramanian, Narayanaswamy, Vidavalur, Ramesh, Vijayakumar, Lakshmi, Villalpando, Salvador, Violante, Francesco S, Vlassov, Vasiliy Victorovich, Wagner, Joseph A, Wagner, Gregory R, Wallin, Mitchell T, Wang, Linhong, Watkins, David A, Weichenthal, Scott, Weiderpass, Elisabete, Weintraub, Robert G, Werdecker, Andrea, Westerman, Ronny, White, Richard A, Wijeratne, Tissa, Wilkinson, James D, Williams, Hywel C, Wiysonge, Charles Shey, Woldeyohannes, Solomon Meseret, Wolfe, Charles D A, Won, Sungho, Wong, John Q, Woolf, Anthony D, Xavier, Deni, Xiao, Qingyang, Xu, Gelin, Yakob, Bereket, Yalew, Ayalnesh Zemene, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Ye, Pengpeng, Yebyo, Henock Gebremedhin, Yip, Paul, Yirsaw, Biruck Desalegn, Yonemoto, Naohiro, Yonga, Gerald, Younis, Mustafa Z, Yu, Shicheng, Zaidi, Zoubida, Zaki, Maysaa El Sayed, Zannad, Faiez, Zavala, Diego E, Zeeb, Hajo, Zeleke, Berihun M, Zhang, Hao, Zodpey, Sanjay, Zonies, David, Zuhlke, Liesl Joanna, Vos, Theo, Lopez, Alan D, and Murray, Christopher J L
Subjects: VITAL-STATISTICS, INTEGRATED APPROACH, ECONOMIC-DEVELOPMENT, DEVELOPMENT ASSISTANCE, UNITED-STATES, Global Health, Communicable Disease, Communicable Diseases, cause of death, Medicine, General & Internal, Life Expectancy, General & Internal Medicine, Humans, Mortality, Medicine(all), Science & Technology, Mortality, Premature, Medicine (all), EPIDEMIOLOGIC TRANSITION, GBD 2015 Mortality and Causes of Death Collaborators, CIVIL REGISTRATION, Public Health, Global Health, Social Medicine and Epidemiology, Articles, 11 Medical And Health Sciences, ROAD TRAFFIC INJURIES, ALZHEIMERS-DISEASE, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, VERBAL AUTOPSY, Life Sciences & Biomedicine, Human
Abstract: 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. Copyright (C) The Author(s). Published by Elsevier Ltd.
Published: 2016

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9 results on '"Coates, Matthew M."'

1. Estimating Health Adjusted Age at Death (HAAD).

2. Cause-specific mortality for 240 causes in China during 1990-2013: a systematic subnational analysis for the Global Burden of Disease Study 2013.

3. Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015 : a systematic analysis for the Global Burden of Disease Study 2015

4. Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015:a systematic analysis for the Global Burden of Disease Study 2015

5. 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

6. Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013

7. Mapping Plasmodium falciparum Mortality in Africa between 1990 and 2015.

8. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

9. 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

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9 results on '"Coates, Matthew M."'

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