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Kyle J Foreman

Bio: Kyle J Foreman is an academic researcher from Institute for Health Metrics and Evaluation. The author has contributed to research in topics: Population & Years of potential life lost. The author has an hindex of 63, co-authored 80 publications receiving 92476 citations. Previous affiliations of Kyle J Foreman include Imperial College London & University of Washington.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
Ryan M Barber1, Nancy Fullman1, Reed J D Sorensen1, Thomas J. Bollyky  +757 moreInstitutions (314)
TL;DR: In this paper, the authors use the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015.

427 citations

Journal ArticleDOI
Jeffrey D. Stanaway, Robert Reiner, Brigette F. Blacker, Ellen M Goldberg, Ibrahim A Khalil, Christopher Troeger, Jason R. Andrews, Zulfiqar A Bhutta, John A. Crump, Justin Im, Florian Marks, Eric D. Mintz, Se Eun Park, Anita K. M. Zaidi, Zegeye Abebe, Ayenew Negesse Abejie, Isaac Akinkunmi Adedeji, Beriwan Abdulqadir Ali, Azmeraw T. Amare, Hagos Tasew Atalay, Euripide Frinel G Arthur Avokpaho, Umar Bacha, Aleksandra Barac, Neeraj Bedi, Adugnaw Berhane, Annie J. Browne, Jesus L. Chirinos, Abdulaal A Chitheer, Christiane Dolecek, Maysaa El Sayed Zaki, Babak Eshrati, Kyle J Foreman, Abdella Gemechu, Rashmi Gupta, Gessessew Bugssa Hailu, Andualem Henok, Desalegn Tsegaw Hibstu, Chi Linh Hoang, Olayinka Stephen Ilesanmi, Veena R. Iyer, Amaha Kahsay, Amir Kasaeian, Tesfaye Dessale Kassa, Ejaz Ahmad Khan, Young-Ho Khang, Hassan Magdy Abd El Razek, Mulugeta Melku, Desalegn Tadese Mengistu, Karzan Abdulmuhsin Mohammad, Shafiu Mohammed, Ali H. Mokdad, Jean B. Nachega, Aliya Naheed, Cuong Tat Nguyen, Huong Lan Thi Nguyen, Long Hoang Nguyen, Nam Ba Nguyen, Trang Huyen Nguyen, Yirga Legesse Nirayo, Tikki Pangestu, George C Patton, Mostafa Qorbani, Rajesh Kumar Rai, Saleem M Rana, Chhabi Lal Ranabhat, Kedir Teji Roba, Nicholas L S Roberts, Salvatore Rubino, Saeid Safiri, Benn Sartorius, Monika Sawhney, Mekonnen Sisay Shiferaw, David L. Smith, Bryan L. Sykes, Bach Xuan Tran, Tung Thanh Tran, Kingsley N. Ukwaja, Giang Thu Vu, Linh Gia Vu, Fitsum Weldegebreal, Melaku Kindie Yenit, Christopher J L Murray, Simon I. Hay 
TL;DR: Although improvements in water and sanitation remain essential, increased vaccine use and improved data and surveillance to inform vaccine rollout are likely to drive the greatest improvements in the global burden of the disease.
Abstract: Summary Background Efforts to quantify the global burden of enteric fever are valuable for understanding the health lost and the large-scale spatial distribution of the disease. We present the estimates of typhoid and paratyphoid fever burden from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, and the approach taken to produce them. Methods For this systematic analysis we broke down the relative contributions of typhoid and paratyphoid fevers by country, year, and age, and analysed trends in incidence and mortality. We modelled the combined incidence of typhoid and paratyphoid fevers and split these total cases proportionally between typhoid and paratyphoid fevers using aetiological proportion models. We estimated deaths using vital registration data for countries with sufficiently high data completeness and using a natural history approach for other locations. We also estimated disability-adjusted life-years (DALYs) for typhoid and paratyphoid fevers. Findings Globally, 14·3 million (95% uncertainty interval [UI] 12·5–16·3) cases of typhoid and paratyphoid fevers occurred in 2017, a 44·6% (42·2–47·0) decline from 25·9 million (22·0–29·9) in 1990. Age-standardised incidence rates declined by 54·9% (53·4–56·5), from 439·2 (376·7–507·7) per 100 000 person-years in 1990, to 197·8 (172·0–226·2) per 100 000 person-years in 2017. In 2017, Salmonella enterica serotype Typhi caused 76·3% (71·8–80·5) of cases of enteric fever. We estimated a global case fatality of 0·95% (0·54–1·53) in 2017, with higher case fatality estimates among children and older adults, and among those living in lower-income countries. We therefore estimated 135·9 thousand (76·9–218·9) deaths from typhoid and paratyphoid fever globally in 2017, a 41·0% (33·6–48·3) decline from 230·5 thousand (131·2–372·6) in 1990. Overall, typhoid and paratyphoid fevers were responsible for 9·8 million (5·6–15·8) DALYs in 2017, down 43·0% (35·5–50·6) from 17·2 million (9·9–27·8) DALYs in 1990. Interpretation Despite notable progress, typhoid and paratyphoid fevers remain major causes of disability and death, with billions of people likely to be exposed to the pathogens. Although improvements in water and sanitation remain essential, increased vaccine use (including with typhoid conjugate vaccines that are effective in infants and young children and protective for longer periods) and improved data and surveillance to inform vaccine rollout are likely to drive the greatest improvements in the global burden of the disease. Funding Bill & Melinda Gates Foundation.

401 citations

Journal ArticleDOI
TL;DR: The utility of CODEm for the estimation of several major causes of death is demonstrated and it is shown that it produces better estimates of cause of death trends than previous methods and is less susceptible to bias in model specification.
Abstract: Data on causes of death by age and sex are a critical input into health decision-making Priority setting in public health should be informed not only by the current magnitude of health problems but by trends in them However, cause of death data are often not available or are subject to substantial problems of comparability We propose five general principles for cause of death model development, validation, and reporting We detail a specific implementation of these principles that is embodied in an analytical tool - the Cause of Death Ensemble model (CODEm) - which explores a large variety of possible models to estimate trends in causes of death Possible models are identified using a covariate selection algorithm that yields many plausible combinations of covariates, which are then run through four model classes The model classes include mixed effects linear models and spatial-temporal Gaussian Process Regression models for cause fractions and death rates All models for each cause of death are then assessed using out-of-sample predictive validity and combined into an ensemble with optimal out-of-sample predictive performance Ensemble models for cause of death estimation outperform any single component model in tests of root mean square error, frequency of predicting correct temporal trends, and achieving 95% coverage of the prediction interval We present detailed results for CODEm applied to maternal mortality and summary results for several other causes of death, including cardiovascular disease and several cancers CODEm produces better estimates of cause of death trends than previous methods and is less susceptible to bias in model specification We demonstrate the utility of CODEm for the estimation of several major causes of death

381 citations

Journal ArticleDOI
Anoop P. Patel, James L. Fisher, Emma Nichols, Foad Abd-Allah, Jemal Abdela, Ahmed Abdelalim, Haftom Niguse Abraha, Dominic Agius, Fares Alahdab, Tahiya Alam, Christine A. Allen, Nahla Anber, Ashish Awasthi, Hamid Badali, Abate Bekele Belachew, Ali Bijani, Tone Bjørge, Félix Carvalho, Ferrán Catalá-López, Jee-Young Jasmine Choi, Ahmad Daryani, Meaza Girma Degefa, Gebre Teklemariam Demoz, Huyen Phuc Do, Manisha Dubey, Eduarda Fernandes, Irina Filip, Kyle J Foreman, Abadi Kahsu Gebre, Yilma Chisha Dea Geramo, Nima Hafezi-Nejad, Samer Hamidi, James D. Harvey, Hamid Yimam Hassen, Simon I. Hay, Seyed Sina Naghibi Irvani, Mihajlo Jakovljevic, Ravi Prakash Jha, Amir Kasaeian, Ibrahim A Khalil, Ejaz Ahmad Khan, Young-Ho Khang, Yun Jin Kim, Getnet Mengistu, Karzan Abdulmuhsin Mohammad, Ali H. Mokdad, Gabriele Nagel, Mohsen Naghavi, Gurudatta Naik, Huong Lan Thi Nguyen, Long Hoang Nguyen, Trang Huyen Nguyen, Molly R Nixon, Andrew T Olagunju, David M. Pereira, Gabriel David Pinilla-Monsalve, Hossein Poustchi, Mostafa Qorbani, Amir Radfar, Robert Reiner, Gholamreza Roshandel, Hosein Safari, Saeid Safiri, Abdallah M. Samy, Shahabeddin Sarvi, Masood Ali Shaikh, Mehdi Sharif, Rajesh Sharma, Sara Sheikhbahaei, Reza Shirkoohi, Jasvinder A. Singh, Mari Smith, Rafael Tabarés-Seisdedos, Bach Xuan Tran, Khanh Bao Tran, Irfan Ullah, Elisabete Weiderpass, Kidu Gidey Weldegwergs, Ebrahim M Yimer, Vesna Zadnik, Zoubida Zaidi, Richard G. Ellenbogen, Theo Vos, Valery L. Feigin, Christopher J L Murray, Christina Fitzmaurice 
TL;DR: This analysis aimed to provide a comparable and comprehensive estimation of the global burden of brain cancer between 1990 and 2016 and found significant geographical and regional variation in the incidence might be reflective of differences in diagnoses and reporting practices or unknown environmental and genetic risk factors.
Abstract: Summary Background Brain and CNS cancers (collectively referred to as CNS cancers) are a source of mortality and morbidity for which diagnosis and treatment require extensive resource allocation and sophisticated diagnostic and therapeutic technology. Previous epidemiological studies are limited to specific geographical regions or time periods, making them difficult to compare on a global scale. In this analysis, we aimed to provide a comparable and comprehensive estimation of the global burden of brain cancer between 1990 and 2016. Methods We report means and 95% uncertainty intervals (UIs) for incidence, mortality, and disability-adjusted life-years (DALYs) estimates for CNS cancers (according to the International Classification of Diseases tenth revision: malignant neoplasm of meninges, malignant neoplasm of brain, and malignant neoplasm of spinal cord, cranial nerves, and other parts of CNS) from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016. Data sources include vital registration and cancer registry data. Mortality was modelled using an ensemble model approach. Incidence was estimated by dividing the final mortality estimates by mortality to incidence ratios. DALYs were estimated by summing years of life lost and years lived with disability. Locations were grouped into quintiles based on the Socio-demographic Index (SDI), a summary indicator of income per capita, years of schooling, and total fertility rate. Findings In 2016, there were 330 000 (95% UI 299 000 to 349 000) incident cases of CNS cancer and 227 000 (205 000 to 241 000) deaths globally, and age-standardised incidence rates of CNS cancer increased globally by 17·3% (95% UI 11·4 to 26·9) between 1990 and 2016 (2016 age-standardised incidence rate 4·63 per 100 000 person-years [4·17 to 4·90]). The highest age-standardised incidence rate was in the highest quintile of SDI (6·91 [5·71 to 7·53]). Age-standardised incidence rates increased with each SDI quintile. East Asia was the region with the most incident cases of CNS cancer for both sexes in 2016 (108 000 [95% UI 98 000 to 122 000]), followed by western Europe (49 000 [37 000 to 54 000]), and south Asia (31 000 [29 000 to 37 000]). The top three countries with the highest number of incident cases were China, the USA, and India. CNS cancer was responsible for 7·7 million (95% UI 6·9 to 8·3) DALYs globally, a non-significant change in age-standardised DALY rate of −10·0% (−16·4 to 2·6) between 1990 and 2016. The age-standardised DALY rate decreased in the high SDI quintile (−10·0% [–27·1 to −0·1]) and high-middle SDI quintile (−10·5% [–18·4 to −1·4]) over time but increased in the low SDI quintile (22·5% [11·2 to 50·5]). Interpretation CNS cancer is responsible for substantial morbidity and mortality worldwide, and incidence increased between 1990 and 2016. Significant geographical and regional variation in the incidence of CNS cancer might be reflective of differences in diagnoses and reporting practices or unknown environmental and genetic risk factors. Future efforts are needed to analyse CNS cancer burden by subtype. Funding Bill & Melinda Gates Foundation.

338 citations

Journal ArticleDOI
TL;DR: Incidence of MM is highly variable among countries but has increased uniformly since 1990, with the largest increase in middle and low-middle SDI countries, and access to effective care is very limited in many countries of low socioeconomic development.
Abstract: Introduction Multiple myeloma (MM) is a plasma cell neoplasm with substantial morbidity and mortality. A comprehensive description of the global burden of MM is needed to help direct health policy, resource allocation, research, and patient care. Objective To describe the burden of MM and the availability of effective therapies for 21 world regions and 195 countries and territories from 1990 to 2016. Design and Setting We report incidence, mortality, and disability-adjusted life-year (DALY) estimates from the Global Burden of Disease 2016 study. Data sources include vital registration system, cancer registry, drug availability, and survey data for stem cell transplant rates. We analyzed the contribution of aging, population growth, and changes in incidence rates to the overall change in incident cases from 1990 to 2016 globally, by sociodemographic index (SDI) and by region. We collected data on approval of lenalidomide and bortezomib worldwide. Main Outcomes and Measures Multiple myeloma mortality; incidence; years lived with disabilities; years of life lost; and DALYs by age, sex, country, and year. Results Worldwide in 2016 there were 138 509 (95% uncertainty interval [UI], 121 000-155 480) incident cases of MM with an age-standardized incidence rate (ASIR) of 2.1 per 100 000 persons (95% UI, 1.8-2.3). Incident cases from 1990 to 2016 increased by 126% globally and by 106% to 192% for all SDI quintiles. The 3 world regions with the highest ASIR of MM were Australasia, North America, and Western Europe. Multiple myeloma caused 2.1 million (95% UI, 1.9-2.3 million) DALYs globally in 2016. Stem cell transplantation is routinely available in higher-income countries but is lacking in sub-Saharan Africa and parts of the Middle East. In 2016, lenalidomide and bortezomib had been approved in 73 and 103 countries, respectively. Conclusions and Relevance Incidence of MM is highly variable among countries but has increased uniformly since 1990, with the largest increase in middle and low-middle SDI countries. Access to effective care is very limited in many countries of low socioeconomic development, particularly in sub-Saharan Africa. Global health policy priorities for MM are to improve diagnostic and treatment capacity in low and middle income countries and to ensure affordability of effective medications for every patient. Research priorities are to elucidate underlying etiological factors explaining the heterogeneity in myeloma incidence.

328 citations


Cited by
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Journal ArticleDOI
TL;DR: Authors/Task Force Members: Piotr Ponikowski* (Chairperson) (Poland), Adriaan A. Voors* (Co-Chair person) (The Netherlands), Stefan D. Anker (Germany), Héctor Bueno (Spain), John G. F. Cleland (UK), Andrew J. S. Coats (UK)

13,400 citations

Journal ArticleDOI
Rafael Lozano1, Mohsen Naghavi1, Kyle J Foreman2, Stephen S Lim1  +192 moreInstitutions (95)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2010 aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex, using the Cause of Death Ensemble model.

11,809 citations

Journal ArticleDOI
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.

10,401 citations

Journal ArticleDOI
Stephen S Lim1, Theo Vos, Abraham D. Flaxman1, Goodarz Danaei2  +207 moreInstitutions (92)
TL;DR: In this paper, the authors estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010.

9,324 citations

Journal ArticleDOI
Marie Ng1, Tom P Fleming1, Margaret Robinson1, Blake Thomson1, Nicholas Graetz1, Christopher Margono1, Erin C Mullany1, Stan Biryukov1, Cristiana Abbafati2, Semaw Ferede Abera3, Jerry Abraham4, Niveen M E Abu-Rmeileh, Tom Achoki1, Fadia AlBuhairan5, Zewdie Aderaw Alemu6, Rafael Alfonso1, Mohammed K. Ali7, Raghib Ali8, Nelson Alvis Guzmán9, Walid Ammar, Palwasha Anwari10, Amitava Banerjee11, Simón Barquera, Sanjay Basu12, Derrick A Bennett8, Zulfiqar A Bhutta13, Jed D. Blore14, N Cabral, Ismael Ricardo Campos Nonato, Jung-Chen Chang15, Rajiv Chowdhury16, Karen J. Courville, Michael H. Criqui17, David K. Cundiff, Kaustubh Dabhadkar7, Lalit Dandona18, Lalit Dandona1, Adrian Davis19, Anand Dayama7, Samath D Dharmaratne20, Eric L. Ding21, Adnan M. Durrani22, Alireza Esteghamati23, Farshad Farzadfar23, Derek F J Fay19, Valery L. Feigin24, Abraham D. Flaxman1, Mohammad H. Forouzanfar1, Atsushi Goto, Mark A. Green25, Rajeev Gupta, Nima Hafezi-Nejad23, Graeme J. Hankey26, Heather Harewood, Rasmus Havmoeller27, Simon I. Hay8, Lucia Hernandez, Abdullatif Husseini28, Bulat Idrisov29, Nayu Ikeda, Farhad Islami30, Eiman Jahangir31, Simerjot K. Jassal17, Sun Ha Jee32, Mona Jeffreys33, Jost B. Jonas34, Edmond K. Kabagambe35, Shams Eldin Ali Hassan Khalifa, Andre Pascal Kengne36, Yousef Khader37, Young-Ho Khang38, Daniel Kim39, Ruth W Kimokoti40, Jonas Minet Kinge41, Yoshihiro Kokubo, Soewarta Kosen, Gene F. Kwan42, Taavi Lai, Mall Leinsalu22, Yichong Li, Xiaofeng Liang43, Shiwei Liu43, Giancarlo Logroscino44, Paulo A. Lotufo45, Yuan Qiang Lu21, Jixiang Ma43, Nana Kwaku Mainoo, George A. Mensah22, Tony R. Merriman46, Ali H. Mokdad1, Joanna Moschandreas47, Mohsen Naghavi1, Aliya Naheed48, Devina Nand, K.M. Venkat Narayan7, Erica Leigh Nelson1, Marian L. Neuhouser49, Muhammad Imran Nisar13, Takayoshi Ohkubo50, Samuel Oti, Andrea Pedroza, Dorairaj Prabhakaran, Nobhojit Roy51, Uchechukwu K.A. Sampson35, Hyeyoung Seo, Sadaf G. Sepanlou23, Kenji Shibuya52, Rahman Shiri53, Ivy Shiue54, Gitanjali M Singh21, Jasvinder A. Singh55, Vegard Skirbekk41, Nicolas J. C. Stapelberg56, Lela Sturua57, Bryan L. Sykes58, Martin Tobias1, Bach Xuan Tran59, Leonardo Trasande60, Hideaki Toyoshima, Steven van de Vijver, Tommi Vasankari, J. Lennert Veerman61, Gustavo Velasquez-Melendez62, Vasiliy Victorovich Vlassov63, Stein Emil Vollset64, Stein Emil Vollset41, Theo Vos1, Claire L. Wang65, Xiao Rong Wang66, Elisabete Weiderpass, Andrea Werdecker, Jonathan L. Wright1, Y Claire Yang67, Hiroshi Yatsuya68, Jihyun Yoon, Seok Jun Yoon69, Yong Zhao70, Maigeng Zhou, Shankuan Zhu71, Alan D. Lopez14, Christopher J L Murray1, Emmanuela Gakidou1 
University of Washington1, Sapienza University of Rome2, Mekelle University3, University of Texas at San Antonio4, King Saud bin Abdulaziz University for Health Sciences5, Debre markos University6, Emory University7, University of Oxford8, University of Cartagena9, United Nations Population Fund10, University of Birmingham11, Stanford University12, Aga Khan University13, University of Melbourne14, National Taiwan University15, University of Cambridge16, University of California, San Diego17, Public Health Foundation of India18, Public Health England19, University of Peradeniya20, Harvard University21, National Institutes of Health22, Tehran University of Medical Sciences23, Auckland University of Technology24, University of Sheffield25, University of Western Australia26, Karolinska Institutet27, Birzeit University28, Brandeis University29, American Cancer Society30, Ochsner Medical Center31, Yonsei University32, University of Bristol33, Heidelberg University34, Vanderbilt University35, South African Medical Research Council36, Jordan University of Science and Technology37, New Generation University College38, Northeastern University39, Simmons College40, Norwegian Institute of Public Health41, Boston University42, Chinese Center for Disease Control and Prevention43, University of Bari44, University of São Paulo45, University of Otago46, University of Crete47, International Centre for Diarrhoeal Disease Research, Bangladesh48, Fred Hutchinson Cancer Research Center49, Teikyo University50, Bhabha Atomic Research Centre51, University of Tokyo52, Finnish Institute of Occupational Health53, Heriot-Watt University54, University of Alabama at Birmingham55, Griffith University56, National Center for Disease Control and Public Health57, University of California, Irvine58, Johns Hopkins University59, New York University60, University of Queensland61, Universidade Federal de Minas Gerais62, National Research University – Higher School of Economics63, University of Bergen64, Columbia University65, Shandong University66, University of North Carolina at Chapel Hill67, Fujita Health University68, Korea University69, Chongqing Medical University70, Zhejiang University71
TL;DR: The global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013 is estimated using a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs).

9,180 citations