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Showing papers by "Philimon Gona published in 2018"


Journal ArticleDOI
Gregory A. Roth1, Gregory A. Roth2, Degu Abate3, Kalkidan Hassen Abate4  +1025 moreInstitutions (333)
TL;DR: Non-communicable diseases comprised the greatest fraction of deaths, contributing to 73·4% (95% uncertainty interval [UI] 72·5–74·1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional causes accounted for 18·6% (17·9–19·6), and injuries 8·0% (7·7–8·2).

5,211 citations


Journal ArticleDOI
Jeffrey D. Stanaway1, Ashkan Afshin1, Emmanuela Gakidou1, Stephen S Lim1  +1050 moreInstitutions (346)
TL;DR: This study estimated levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs) by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017 and explored the relationship between development and risk exposure.

2,910 citations


Journal ArticleDOI
Max Griswold1, Nancy Fullman1, Caitlin Hawley1, Nicholas Arian1  +515 moreInstitutions (37)
TL;DR: It is found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero.

1,831 citations


Journal ArticleDOI
Ali H. Mokdad1, Katherine Ballestros1, Michelle Echko1, Scott D Glenn1, Helen E Olsen1, Erin C Mullany1, Alexander Lee1, Abdur Rahman Khan2, Alireza Ahmadi3, Alireza Ahmadi4, Alize J. Ferrari1, Alize J. Ferrari5, Alize J. Ferrari6, Amir Kasaeian7, Andrea Werdecker, Austin Carter1, Ben Zipkin1, Benn Sartorius8, Benn Sartorius9, Berrin Serdar10, Bryan L. Sykes11, Christopher Troeger1, Christina Fitzmaurice12, Christina Fitzmaurice1, Colin D. Rehm13, Damian Santomauro5, Damian Santomauro1, Damian Santomauro6, Daniel Kim14, Danny V. Colombara1, David C. Schwebel15, Derrick Tsoi1, Dhaval Kolte16, Elaine O. Nsoesie1, Emma Nichols1, Eyal Oren17, Fiona J Charlson1, Fiona J Charlson5, Fiona J Charlson6, George C Patton18, Gregory A. Roth1, H. Dean Hosgood19, Harvey Whiteford6, Harvey Whiteford5, Harvey Whiteford1, Hmwe H Kyu1, Holly E. Erskine5, Holly E. Erskine1, Holly E. Erskine6, Hsiang Huang20, Ira Martopullo1, Jasvinder A. Singh15, Jean B. Nachega21, Jean B. Nachega22, Jean B. Nachega23, Juan Sanabria24, Juan Sanabria25, Kaja Abbas26, Kanyin Ong1, Karen M. Tabb27, Kristopher J. Krohn1, Leslie Cornaby1, Louisa Degenhardt28, Louisa Degenhardt1, Mark Moses1, Maryam S. Farvid29, Max Griswold1, Michael H. Criqui30, Michelle L. Bell31, Minh Nguyen1, Mitch T Wallin32, Mitch T Wallin33, Mojde Mirarefin1, Mostafa Qorbani, Mustafa Z. Younis34, Nancy Fullman1, Patrick Liu1, Paul S Briant1, Philimon Gona35, Rasmus Havmoller4, Ricky Leung36, Ruth W Kimokoti37, Shahrzad Bazargan-Hejazi38, Shahrzad Bazargan-Hejazi39, Simon I. Hay40, Simon I. Hay1, Simon Yadgir1, Stan Biryukov1, Stein Emil Vollset1, Stein Emil Vollset41, Tahiya Alam1, Tahvi Frank1, Talha Farid2, Ted R. Miller42, Ted R. Miller43, Theo Vos1, Till Bärnighausen29, Till Bärnighausen44, Tsegaye Telwelde Gebrehiwot45, Yuichiro Yano46, Ziyad Al-Aly47, Alem Mehari48, Alexis J. Handal49, Amit Kandel50, Ben Anderson51, Brian J. Biroscak52, Brian J. Biroscak31, Dariush Mozaffarian53, E. Ray Dorsey54, Eric L. Ding29, Eun-Kee Park55, Gregory R. Wagner29, Guoqing Hu56, Honglei Chen57, Jacob E. Sunshine51, Jagdish Khubchandani58, Janet L Leasher59, Janni Leung51, Janni Leung5, Joshua A. Salomon29, Jürgen Unützer51, Leah E. Cahill29, Leah E. Cahill60, Leslie T. Cooper61, Masako Horino, Michael Brauer62, Michael Brauer1, Nicholas J K Breitborde63, Peter J. Hotez64, Roman Topor-Madry65, Roman Topor-Madry66, Samir Soneji67, Saverio Stranges68, Spencer L. James1, Stephen M. Amrock69, Sudha Jayaraman70, Tejas V. Patel, Tomi Akinyemiju15, Vegard Skirbekk71, Vegard Skirbekk41, Yohannes Kinfu72, Zulfiqar A Bhutta73, Jost B. Jonas44, Christopher J L Murray1 
Institute for Health Metrics and Evaluation1, University of Louisville2, Kermanshah University of Medical Sciences3, Karolinska Institutet4, University of Queensland5, Centre for Mental Health6, Tehran University of Medical Sciences7, University of KwaZulu-Natal8, South African Medical Research Council9, University of Colorado Boulder10, University of California, Irvine11, Fred Hutchinson Cancer Research Center12, Montefiore Medical Center13, Northeastern University14, University of Alabama at Birmingham15, Brown University16, San Diego State University17, University of Melbourne18, Albert Einstein College of Medicine19, Cambridge Health Alliance20, University of Cape Town21, University of Pittsburgh22, Johns Hopkins University23, Marshall University24, Case Western Reserve University25, University of London26, University of Illinois at Urbana–Champaign27, National Drug and Alcohol Research Centre28, Harvard University29, University of California, San Diego30, Yale University31, Veterans Health Administration32, Georgetown University33, Jackson State University34, University of Massachusetts Boston35, State University of New York System36, Simmons College37, Charles R. Drew University of Medicine and Science38, University of California, Los Angeles39, University of Oxford40, Norwegian Institute of Public Health41, Pacific Institute42, Curtin University43, Heidelberg University44, Jimma University45, Northwestern University46, Washington University in St. Louis47, Howard University48, University of New Mexico49, University at Buffalo50, University of Washington51, University of South Florida52, Tufts University53, University of Rochester Medical Center54, Kosin University55, Central South University56, Michigan State University57, Ball State University58, Nova Southeastern University59, Dalhousie University60, Mayo Clinic61, University of British Columbia62, Ohio State University63, Baylor University64, Wrocław Medical University65, Jagiellonian University Medical College66, Dartmouth College67, University of Western Ontario68, Oregon Health & Science University69, Virginia Commonwealth University70, Columbia University71, University of Canberra72, Aga Khan University73
10 Apr 2018-JAMA
TL;DR: There are wide differences in the burden of disease at the state level and specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention.
Abstract: Introduction Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state. Objective To use the results of the Global Burden of Disease Study (GBD) to report trends in the burden of diseases, injuries, and risk factors at the state level from 1990 to 2016. Design and Setting A systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year. Main Outcomes and Measures Prevalence, incidence, mortality, life expectancy, healthy life expectancy (HALE), years of life lost (YLLs) due to premature mortality, years lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 333 causes and 84 risk factors with 95% uncertainty intervals (UIs) were computed. Results Between 1990 and 2016, overall death rates in the United States declined from 745.2 (95% UI, 740.6 to 749.8) per 100 000 persons to 578.0 (95% UI, 569.4 to 587.1) per 100 000 persons. The probability of death among adults aged 20 to 55 years declined in 31 states and Washington, DC from 1990 to 2016. In 2016, Hawaii had the highest life expectancy at birth (81.3 years) and Mississippi had the lowest (74.7 years), a 6.6-year difference. Minnesota had the highest HALE at birth (70.3 years), and West Virginia had the lowest (63.8 years), a 6.5-year difference. The leading causes of DALYs in the United States for 1990 and 2016 were ischemic heart disease and lung cancer, while the third leading cause in 1990 was low back pain, and the third leading cause in 2016 was chronic obstructive pulmonary disease. Opioid use disorders moved from the 11th leading cause of DALYs in 1990 to the 7th leading cause in 2016, representing a 74.5% (95% UI, 42.8% to 93.9%) change. In 2016, each of the following 6 risks individually accounted for more than 5% of risk-attributable DALYs: tobacco consumption, high body mass index (BMI), poor diet, alcohol and drug use, high fasting plasma glucose, and high blood pressure. Across all US states, the top risk factors in terms of attributable DALYs were due to 1 of the 3 following causes: tobacco consumption (32 states), high BMI (10 states), or alcohol and drug use (8 states). Conclusions and Relevance There are wide differences in the burden of disease at the state level. Specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention. These data can be used to inform national health priorities for research, clinical care, and policy.

962 citations


Journal ArticleDOI
01 Oct 2018

810 citations


Journal ArticleDOI
Daniel Dicker1, Grant Nguyen2, Degu Abate, Kalkidan Hassen Abate3  +1155 moreInstitutions (7)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 as mentioned in this paper was the most recent iteration of the GBD, which used all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups.

638 citations


Journal ArticleDOI
TL;DR: The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between1990 and 2000.

623 citations


Journal ArticleDOI
Rafael Lozano1, Nancy Fullman, Degu Abate2, Solomon M Abay  +1313 moreInstitutions (252)
TL;DR: A global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends and a estimates of health-related SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous.

312 citations


Journal ArticleDOI
TL;DR: This work estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods and used the cohort-component method of population projection, with inputs of fertility, mortality, population, and migration data.

287 citations


Journal ArticleDOI
Gregory A. Roth1, Gregory A. Roth2, Catherine O. Johnson1, Kalkidan Hassen Abate3, Foad Abd-Allah4, Muktar Beshir Ahmed3, Khurshid Alam5, Tahiya Alam1, Nelson Alvis-Guzman6, Hossein Ansari, Johan Ärnlöv7, Tesfay Mehari Atey8, Ashish Awasthi9, Tadesse Awoke10, Aleksandra Barac11, Till Bärnighausen12, Neeraj Bedi13, Derrick A Bennett14, Isabela M. Benseñor15, Sibhatu Biadgilign, Carlos A Castañeda-Orjuela, Ferrán Catalá-López16, Kairat Davletov17, Samath D Dharmaratne18, Eric L. Ding12, Manisha Dubey19, Emerito Jose A. Faraon20, Talha Farid21, Maryam S. Farvid12, Valery L. Feigin22, João C. Fernandes23, Joseph Frostad1, Alemseged Aregay Gebru8, Johanna M. Geleijnse24, Philimon Gona25, Max Griswold1, Gessessew Bugssa Hailu8, Graeme J. Hankey5, Hamid Yimam Hassen26, Rasmus Havmoeller7, Simon I. Hay1, Susan R. Heckbert1, Caleb Mackay Salpeter Irvine1, Spencer L. James1, Dube Jara27, Amir Kasaeian28, Abdur Rahman Khan21, Sahil Khera29, Abdullah T Khoja30, Jagdish Khubchandani31, Daniel Kim32, Dhaval Kolte33, Dharmesh Kumar Lal9, Anders Larsson34, Shai Linn35, Paulo A. Lotufo15, Hassan Magdy Abd El Razek36, Mohsen Mazidi37, Toni Meier38, Walter Mendoza39, George A. Mensah40, Atte Meretoja41, Haftay Berhane Mezgebe8, Erkin M. Mirrakhimov42, Shafiu Mohammed43, Andrew E. Moran44, Grant Nguyen1, Minh Nguyen1, Kanyin Liane Ong1, Mayowa O. Owolabi45, Martin A Pletcher1, Farshad Pourmalek46, Caroline A. Purcell1, Mostafa Qorbani, Mahfuzar Rahman47, Rajesh Kumar Rai, Usha Ram19, Marissa B Reitsma1, Andre M. N. Renzaho48, Maria Jesus Rios-Blancas, Saeid Safiri49, Joshua A. Salomon12, Benn Sartorius50, Sadaf G. Sepanlou28, Masood Ali Shaikh, Diego Augusto Santos Silva51, Saverio Stranges52, Rafael Tabarés-Seisdedos16, Niguse Tadele Atnafu53, Jarnail Singh Thakur54, Roman Topor-Madry55, Thomas Truelsen56, E. Murat Tuzcu57, Stefanos Tyrovolas58, Kingsley N. Ukwaja, Tommi Vasankari, Vasiliy Victorovich Vlassov59, Stein Emil Vollset60, Tolassa Wakayo3, Robert G. Weintraub61, Charles D.A. Wolfe62, Abdulhalik Workicho3, Gelin Xu63, Simon Yadgir1, Yuichiro Yano64, Paul S. F. Yip65, Naohiro Yonemoto66, Mustafa Z. Younis67, Chuanhua Yu68, Zoubida Zaidi, Maysaa El Sayed Zaki36, Ben Zipkin1, Ashkan Afshin1, Emmanuela Gakidou1, Stephen S Lim1, Ali H. Mokdad1, Mohsen Naghavi1, Theo Vos1, Christopher J L Murray1 
Institute for Health Metrics and Evaluation1, University of Washington2, Jimma University3, Cairo University4, University of Western Australia5, University of Cartagena6, Karolinska Institutet7, Mekelle University8, Public Health Foundation of India9, University of Gondar10, University of Belgrade11, Harvard University12, Jazan University13, University of Oxford14, University of São Paulo15, University of Valencia16, Kazakh National Medical University17, University of Peradeniya18, International Institute for Population Sciences19, University of the Philippines Manila20, University of Louisville21, Auckland University of Technology22, Catholic University of Portugal23, Wageningen University and Research Centre24, University of Massachusetts Boston25, Mizan–Tepi University26, Debre markos University27, Tehran University of Medical Sciences28, New York Medical College29, Islamic University30, Ball State University31, Northeastern University32, Brown University33, Uppsala University34, University of Haifa35, Mansoura University36, Chinese Academy of Sciences37, Martin Luther University of Halle-Wittenberg38, United Nations Population Fund39, National Institutes of Health40, University of Melbourne41, Kyrgyz State Medical Academy42, Ahmadu Bello University43, Columbia University44, University of Ibadan45, University of British Columbia46, BRAC47, University of Sydney48, University of Maragheh49, University of KwaZulu-Natal50, Universidade Federal de Santa Catarina51, University of Western Ontario52, Addis Ababa University53, Post Graduate Institute of Medical Education and Research54, Jagiellonian University Medical College55, University of Copenhagen56, Cleveland Clinic57, Hospital Sant Joan de Déu Barcelona58, National Research University – Higher School of Economics59, Norwegian Institute of Public Health60, Royal Children's Hospital61, King's College London62, Nanjing University63, University of Mississippi Medical Center64, University of Hong Kong65, Kyoto University66, Jackson State University67, Wuhan University68
TL;DR: Large disparities in total burden of CVD persist between US states despite marked improvements in CVD burden, and increases in risk-deleted CVD DALY rates between 2006 and 2016 in 16 states suggest additional unmeasured risks beyond these traditional factors.
Abstract: Importance Cardiovascular disease (CVD) is the leading cause of death in the United States, but regional variation within the United States is large. Comparable and consistent state-level measures of total CVD burden and risk factors have not been produced previously. Objective To quantify and describe levels and trends of lost health due to CVD within the United States from 1990 to 2016 as well as risk factors driving these changes. Design, Setting, and Participants Using the Global Burden of Disease methodology, cardiovascular disease mortality, nonfatal health outcomes, and associated risk factors were analyzed by age group, sex, and year from 1990 to 2016 for all residents in the United States using standardized approaches for data processing and statistical modeling. Burden of disease was estimated for 10 groupings of CVD, and comparative risk analysis was performed. Data were analyzed from August 2016 to July 2017. Exposures Residing in the United States. Main Outcomes and Measures Cardiovascular disease disability-adjusted life-years (DALYs). Results Between 1990 and 2016, age-standardized CVD DALYs for all states decreased. Several states had large rises in their relative rank ordering for total CVD DALYs among states, including Arkansas, Oklahoma, Alabama, Kentucky, Missouri, Indiana, Kansas, Alaska, and Iowa. The rate of decline varied widely across states, and CVD burden increased for a small number of states in the most recent years. Cardiovascular disease DALYs remained twice as large among men compared with women. Ischemic heart disease was the leading cause of CVD DALYs in all states, but the second most common varied by state. Trends were driven by 12 groups of risk factors, with the largest attributable CVD burden due to dietary risk exposures followed by high systolic blood pressure, high body mass index, high total cholesterol level, high fasting plasma glucose level, tobacco smoking, and low levels of physical activity. Increases in risk-deleted CVD DALY rates between 2006 and 2016 in 16 states suggest additional unmeasured risks beyond these traditional factors. Conclusions and Relevance Large disparities in total burden of CVD persist between US states despite marked improvements in CVD burden. Differences in CVD burden are largely attributable to modifiable risk exposures.

261 citations


Journal ArticleDOI
TL;DR: If current trends in tuberculosis incidence continue, few countries are likely to meet the SDG target to end the tuberculosis epidemic by 2030, and several regions had higher rates of age-standardised incidence and mortality than expected on the basis of their SDI levels in 2016.
Abstract: Summary Background Although a preventable and treatable disease, tuberculosis causes more than a million deaths each year. As countries work towards achieving the Sustainable Development Goal (SDG) target to end the tuberculosis epidemic by 2030, robust assessments of the levels and trends of the burden of tuberculosis are crucial to inform policy and programme decision making. We assessed the levels and trends in the fatal and non-fatal burden of tuberculosis by drug resistance and HIV status for 195 countries and territories from 1990 to 2016. Methods We analysed 15 943 site-years of vital registration data, 1710 site-years of verbal autopsy data, 764 site-years of sample-based vital registration data, and 361 site-years of mortality surveillance data to estimate mortality due to tuberculosis using the Cause of Death Ensemble model. We analysed all available data sources, including annual case notifications, prevalence surveys, population-based tuberculin surveys, and estimated tuberculosis cause-specific mortality to generate internally consistent estimates of incidence, prevalence, and mortality using DisMod-MR 2.1, a Bayesian meta-regression tool. We assessed how the burden of tuberculosis differed from the burden predicted by the Socio-demographic Index (SDI), a composite indicator of income per capita, average years of schooling, and total fertility rate. Findings Globally in 2016, among HIV-negative individuals, the number of incident cases of tuberculosis was 9·02 million (95% uncertainty interval [UI] 8·05–10·16) and the number of tuberculosis deaths was 1·21 million (1·16–1·27). Among HIV-positive individuals, the number of incident cases was 1·40 million (1·01–1·89) and the number of tuberculosis deaths was 0·24 million (0·16–0·31). Globally, among HIV-negative individuals the age-standardised incidence of tuberculosis decreased annually at a slower rate (–1·3% [–1·5 to −1·2]) than mortality did (–4·5% [–5·0 to −4·1]) from 2006 to 2016. Among HIV-positive individuals during the same period, the rate of change in annualised age-standardised incidence was −4·0% (–4·5 to −3·7) and mortality was −8·9% (–9·5 to −8·4). Several regions had higher rates of age-standardised incidence and mortality than expected on the basis of their SDI levels in 2016. For drug-susceptible tuberculosis, the highest observed-to-expected ratios were in southern sub-Saharan Africa (13·7 for incidence and 14·9 for mortality), and the lowest ratios were in high-income North America (0·4 for incidence) and Oceania (0·3 for mortality). For multidrug-resistant tuberculosis, eastern Europe had the highest observed-to-expected ratios (67·3 for incidence and 73·0 for mortality), and high-income North America had the lowest ratios (0·4 for incidence and 0·5 for mortality). Interpretation If current trends in tuberculosis incidence continue, few countries are likely to meet the SDG target to end the tuberculosis epidemic by 2030. Progress needs to be accelerated by improving the quality of and access to tuberculosis diagnosis and care, by developing new tools, scaling up interventions to prevent risk factors for tuberculosis, and integrating control programmes for tuberculosis and HIV. Funding Bill & Melinda Gates Foundation.

Journal ArticleDOI
Ali H. Mokdad1, Peter Azzopardi1, Karly Cini, Elissa Kennedy  +173 moreInstitutions (3)
TL;DR: Even with the return of peace and security, adolescents in the East Mediterranean Region will have a persisting poor health profile that will pose a barrier to socioeconomic growth and development of the EMR.
Abstract: The 22 countries of the East Mediterranean Region (EMR) have large populations of adolescents aged 10-24 years. These adolescents are central to assuring the health, development, and peace of this ...

Journal ArticleDOI
TL;DR: AAW augments traditional CVD risk factors and CAC for prediction of incident adverse CVD events among community‐dwelling adults and appropriately reclassified participants at risk.
Abstract: Background We sought to determine whether increased aortic arch width (AAW) adds to standard Framingham risk factors and coronary artery calcium (CAC) for prediction of incident adverse cardiovascu...