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Showing papers by "Stephen S Lim 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
TL;DR: PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.
Abstract: Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.

1,283 citations


Journal ArticleDOI
TL;DR: The findings show substantial progress in the reduction of lower respiratory infection burden, but this progress has not been equal across locations, has been driven by decreases in several primary risk factors, and might require more effort among elderly adults.
Abstract: Summary Background Lower respiratory infections are a leading cause of morbidity and mortality around the world The Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2016, provides an up-to-date analysis of the burden of lower respiratory infections in 195 countries This study assesses cases, deaths, and aetiologies spanning the past 26 years and shows how the burden of lower respiratory infection has changed in people of all ages Methods We used three separate modelling strategies for lower respiratory infections in GBD 2016: a Bayesian hierarchical ensemble modelling platform (Cause of Death Ensemble model), which uses vital registration, verbal autopsy data, and surveillance system data to predict mortality due to lower respiratory infections; a compartmental meta-regression tool (DisMod-MR), which uses scientific literature, population representative surveys, and health-care data to predict incidence, prevalence, and mortality; and modelling of counterfactual estimates of the population attributable fraction of lower respiratory infection episodes due to Streptococcus pneumoniae, Haemophilus influenzae type b, influenza, and respiratory syncytial virus We calculated each modelled estimate for each age, sex, year, and location We modelled the exposure level in a population for a given risk factor using DisMod-MR and a spatio-temporal Gaussian process regression, and assessed the effectiveness of targeted interventions for each risk factor in children younger than 5 years We also did a decomposition analysis of the change in LRI deaths from 2000–16 using the risk factors associated with LRI in GBD 2016 Findings In 2016, lower respiratory infections caused 652 572 deaths (95% uncertainty interval [UI] 586 475–720 612) in children younger than 5 years (under-5s), 1 080 958 deaths (943 749–1 170 638) in adults older than 70 years, and 2 377 697 deaths (2 145 584–2 512 809) in people of all ages, worldwide Streptococcus pneumoniae was the leading cause of lower respiratory infection morbidity and mortality globally, contributing to more deaths than all other aetiologies combined in 2016 (1 189 937 deaths, 95% UI 690 445–1 770 660) Childhood wasting remains the leading risk factor for lower respiratory infection mortality among children younger than 5 years, responsible for 61·4% of lower respiratory infection deaths in 2016 (95% UI 45·7–69·6) Interventions to improve wasting, household air pollution, ambient particulate matter pollution, and expanded antibiotic use could avert one under-5 death due to lower respiratory infection for every 4000 children treated in the countries with the highest lower respiratory infection burden Interpretation Our findings show substantial progress in the reduction of lower respiratory infection burden, but this progress has not been equal across locations, has been driven by decreases in several primary risk factors, and might require more effort among elderly adults By highlighting regions and populations with the highest burden, and the risk factors that could have the greatest effect, funders, policy makers, and programme implementers can more effectively reduce lower respiratory infections among the world's most susceptible populations Funding Bill & Melinda Gates Foundation

1,147 citations



Journal ArticleDOI
Christopher Troeger, Brigette F. Blacker, Ibrahim A Khalil, Puja C Rao, Shujin Cao, Stephanie R. M. Zimsen, Samuel B. Albertson, Jeffery D Stanaway, Aniruddha Deshpande, Zegeye Abebe, Nelson Alvis-Guzman, Azmeraw T. Amare, Solomon Weldegebreal Asgedom, Zelalem Alamrew Anteneh, Carl Abelardo T. Antonio, Olatunde Aremu, Ephrem Tsegay Asfaw, Tesfay Mehari Atey, Suleman Atique, Euripide Frinel G Arthur Avokpaho, Ashish Awasthi, Henok Tadesse Ayele, Aleksandra Barac, Mauricio Lima Barreto, Quique Bassat, Saba Abraham Belay, Isabela M. Benseñor, Zulfiqar A Bhutta, Ali Bijani, Hailemichael Bizuneh, Carlos A Castañeda-Orjuela, Abel Fekadu Dadi, Lalit Dandona, Rakhi Dandona, Huyen Phuc Do, Manisha Dubey, Eleonora Dubljanin, Dumessa Edessa, Aman Yesuf Endries, Babak Eshrati, Tamer H. Farag, Garumma Tolu Feyissa, Kyle J Foreman, Mohammad H. Forouzanfar, Nancy Fullman, Peter W. Gething, Melkamu Dedefo Gishu, William W Godwin, Harish Chander Gugnani, Rashmi Gupta, Gessessew Bugssa Hailu, Hamid Yimam Hassen, Desalegn Tsegaw Hibstu, Olayinka Stephen Ilesanmi, Jost B. Jonas, Amaha Kahsay, Gagandeep Kang, Amir Kasaeian, Yousef Khader, Ejaz Ahmad Khan, Muhammad Ali Khan, Young-Ho Khang, Niranjan Kissoon, Sonali Kochhar, Karen L. Kotloff, Ai Koyanagi, G Anil Kumar, Hassan Magdy Abd El Razek, Reza Malekzadeh, Deborah Carvalho Malta, Suresh Mehata, Walter Mendoza, Desalegn Tadese Mengistu, Bereket Gebremichael Menota, Haftay Berhane Mezgebe, Fitsum Weldegebreal Mlashu, Srinivas Murthy, Gurudatta Naik, Cuong Tat Nguyen, Trang Huyen Nguyen, Dina Nur Anggraini Ningrum, Felix Akpojene Ogbo, Andrew T Olagunju, Deepak Paudel, James A Platts-Mills, Mostafa Qorbani, Anwar Rafay, Rajesh Kumar Rai, Saleem M Rana, Chhabi Lal Ranabhat, Davide Rasella, Sarah E Ray, Cesar Reis, Andre M. N. Renzaho, Mohammad Sadegh Rezai, George Mugambage Ruhago, Saeid Safiri, Joshua A. Salomon, Juan Sanabria, Benn Sartorius, Monika Sawhney, Sadaf G. Sepanlou, Mika Shigematsu, Mekonnen Sisay, Ranjani Somayaji, Chandrashekhar T Sreeramareddy, Bryan L. Sykes, Getachew Redae Taffere, Roman Topor-Madry, Bach Xuan Tran, Kald Beshir Tuem, Kingsley N. Ukwaja, Stein Emil Vollset, Judd L. Walson, Marcia R. Weaver, Kidu Gidey Weldegwergs, Andrea Werdecker, Abdulhalik Workicho, Muluken Azage Yenesew, Biruck Desalegn Yirsaw, Naohiro Yonemoto, Maysaa El Sayed Zaki, Theo Vos, Stephen S Lim, Mohsen Naghavi, Christopher J L Murray, Ali H. Mokdad, Simon I. Hay, Robert Reiner 
TL;DR: Substantial progress has been made globally in reducing the burden of diarrhoeal diseases, driven by decreases in several primary risk factors, however, this reduction has not been equal across locations, and burden among adults older than 70 years requires attention.
Abstract: Summary Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 provides an up-to-date analysis of the burden of diarrhoea in 195 countries. This study assesses cases, deaths, and aetiologies in 1990–2016 and assesses how the burden of diarrhoea has changed in people of all ages. Methods We modelled diarrhoea mortality with a Bayesian hierarchical modelling platform that evaluates a wide range of covariates and model types on the basis of vital registration and verbal autopsy data. We modelled diarrhoea incidence with a compartmental meta-regression tool that enforces an association between incidence and prevalence, and relies on scientific literature, population representative surveys, and health-care data. Diarrhoea deaths and episodes were attributed to 13 pathogens by use of a counterfactual population attributable fraction approach. Diarrhoea risk factors are also based on counterfactual estimates of risk exposure and the association between the risk and diarrhoea. Each modelled estimate accounted for uncertainty. Findings In 2016, diarrhoea was the eighth leading cause of death among all ages (1 655 944 deaths, 95% uncertainty interval [UI] 1 244 073–2 366 552) and the fifth leading cause of death among children younger than 5 years (446 000 deaths, 390 894–504 613). Rotavirus was the leading aetiology for diarrhoea mortality among children younger than 5 years (128 515 deaths, 105 138–155 133) and among all ages (228 047 deaths, 183 526–292 737). Childhood wasting (low weight-for-height score), unsafe water, and unsafe sanitation were the leading risk factors for diarrhoea, responsible for 80·4% (95% UI 68·2–85·0), 72·1% (34·0–91·4), and 56·4% (49·3–62·7) of diarrhoea deaths in children younger than 5 years, respectively. Prevention of wasting in 1762 children (95% UI 1521–2170) could avert one death from diarrhoea. Interpretation Substantial progress has been made globally in reducing the burden of diarrhoeal diseases, driven by decreases in several primary risk factors. However, this reduction has not been equal across locations, and burden among adults older than 70 years requires attention. Funding Bill & Melinda Gates Foundation.

787 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
TL;DR: The increase in health loss from diabetes since 1990 in India is the highest among major non-communicable diseases and the relative rate of increase highest in several less developed low ETL states, and policy action is needed urgently to control this potentially explosive public health situation.

326 citations


Journal ArticleDOI
TL;DR: The increasing prevalence and that of several major risk factors in every part of India, especially the highest increase in the prevalence of ischaemic heart disease in the less developed low ETL states, indicates the need for urgent policy and health system response appropriate for the situation in each state.

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.

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.

Journal ArticleDOI
Gregory A. Roth1, Gregory A. Roth2, Catherine O. Johnson2, Kalkidan Hassen Abate3, Foad Abd-Allah4, Muktar Beshir Ahmed3, Khurshid Alam5, Tahiya Alam2, 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 Frostad2, Alemseged Aregay Gebru8, Johanna M. Geleijnse24, Philimon Gona25, Max Griswold2, Gessessew Bugssa Hailu8, Graeme J. Hankey5, Hamid Yimam Hassen26, Rasmus Havmoeller7, Simon I. Hay2, Susan R. Heckbert2, Caleb Mackay Salpeter Irvine2, Spencer L. James2, 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 Nguyen2, Minh Nguyen2, Kanyin Liane Ong2, Mayowa O. Owolabi45, Martin A Pletcher2, Farshad Pourmalek46, Caroline A. Purcell2, Mostafa Qorbani, Mahfuzar Rahman47, Rajesh Kumar Rai, Usha Ram19, Marissa B Reitsma2, 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 Yadgir2, Yuichiro Yano64, Paul S. F. Yip65, Naohiro Yonemoto66, Mustafa Z. Younis67, Chuanhua Yu68, Zoubida Zaidi, Maysaa El Sayed Zaki36, Ben Zipkin2, Ashkan Afshin2, Emmanuela Gakidou2, Stephen S Lim2, Ali H. Mokdad2, Mohsen Naghavi2, Theo Vos2, Christopher J L Murray2 
University of Washington1, Institute for Health Metrics and Evaluation2, 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.

Journal ArticleDOI
TL;DR: The substantial heterogeneity in the state-level incidence rate and health loss trends of the different types of cancer in India over this 26-year period should be taken into account to strengthen infrastructure and human resources for cancer prevention and control at both the national and state levels.
Abstract: Summary Background Previous efforts to report estimates of cancer incidence and mortality in India and its different parts include the National Cancer Registry Programme Reports, Sample Registration System cause of death findings, Cancer Incidence in Five Continents Series, and GLOBOCAN We present a comprehensive picture of the patterns and time trends of the burden of total cancer and specific cancer types in each state of India estimated as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 because such a systematic compilation is not readily available Methods We used all accessible data from multiple sources, including 42 population-based cancer registries and the nationwide Sample Registration System of India, to estimate the incidence of 28 types of cancer in every state of India from 1990 to 2016 and the deaths and disability-adjusted life-years (DALYs) caused by them, as part of GBD 2016 We present incidence, DALYs, and death rates for all cancers together, and the trends of all types of cancers, highlighting the heterogeneity in the burden of specific types of cancers across the states of India We also present the contribution of major risk factors to cancer DALYs in India Findings 8·3% (95% uncertainty interval [UI] 7·9–8·6) of the total deaths and 5·0% (4·6–5·5) of the total DALYs in India in 2016 were due to cancer, which was double the contribution of cancer in 1990 However, the age-standardised incidence rate of cancer did not change substantially during this period The age-standardised cancer DALY rate had a 2·6 times variation across the states of India in 2016 The ten cancers responsible for the highest proportion of cancer DALYs in India in 2016 were stomach (9·0% of the total cancer DALYs), breast (8·2%), lung (7·5%), lip and oral cavity (7·2%), pharynx other than nasopharynx (6·8%), colon and rectum (5·8%), leukaemia (5·2%), cervical (5·2%), oesophageal (4·3%), and brain and nervous system (3·5%) cancer Among these cancers, the age-standardised incidence rate of breast cancer increased significantly by 40·7% (95% UI 7·0–85·6) from 1990 to 2016, whereas it decreased for stomach (39·7%; 34·3–44·0), lip and oral cavity (6·4%; 0·4–18·6), cervical (39·7%; 26·5–57·3), and oesophageal cancer (31·2%; 27·9–34·9), and leukaemia (16·1%; 4·3–24·2) We found substantial inter-state heterogeneity in the age-standardised incidence rate of the different types of cancers in 2016, with a 3·3 times to 11·6 times variation for the four most frequent cancers (lip and oral, breast, lung, and stomach) Tobacco use was the leading risk factor for cancers in India to which the highest proportion (10·9%) of cancer DALYs could be attributed in 2016 Interpretation The substantial heterogeneity in the state-level incidence rate and health loss trends of the different types of cancer in India over this 26-year period should be taken into account to strengthen infrastructure and human resources for cancer prevention and control at both the national and state levels These efforts should focus on the ten cancers contributing the highest DALYs in India, including cancers of the stomach, lung, pharynx other than nasopharynx, colon and rectum, leukaemia, oesophageal, and brain and nervous system, in addition to breast, lip and oral cavity, and cervical cancer, which are currently the focus of screening and early detection programmes Funding Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India


Journal ArticleDOI
28 Aug 2018-JAMA
TL;DR: Between 195 000 and 276 000 firearm injury deaths globally in 2016 were estimated, the majority of which were firearm homicides, and there was variation among countries and across demographic subgroups.
Abstract: Importance Understanding global variation in firearm mortality rates could guide prevention policies and interventions. Objective To estimate mortality due to firearm injury deaths from 1990 to 2016 in 195 countries and territories. Design, Setting, and Participants This study used deidentified aggregated data including 13 812 location-years of vital registration data to generate estimates of levels and rates of death by age-sex-year-location. The proportion of suicides in which a firearm was the lethal means was combined with an estimate of per capita gun ownership in a revised proxy measure used to evaluate the relationship between availability or access to firearms and firearm injury deaths. Exposures Firearm ownership and access. Main Outcomes and Measures Cause-specific deaths by age, sex, location, and year. Results Worldwide, it was estimated that 251 000 (95% uncertainty interval [UI], 195 000-276 000) people died from firearm injuries in 2016, with 6 countries (Brazil, United States, Mexico, Colombia, Venezuela, and Guatemala) accounting for 50.5% (95% UI, 42.2%-54.8%) of those deaths. In 1990, there were an estimated 209 000 (95% UI, 172 000 to 235 000) deaths from firearm injuries. Globally, the majority of firearm injury deaths in 2016 were homicides (64.0% [95% UI, 54.2%-68.0%]; absolute value, 161 000 deaths [95% UI, 107 000-182 000]); additionally, 27% were firearm suicide deaths (67 500 [95% UI, 55 400-84 100]) and 9% were unintentional firearm deaths (23 000 [95% UI, 18 200-24 800]). From 1990 to 2016, there was no significant decrease in the estimated global age-standardized firearm homicide rate (−0.2% [95% UI, −0.8% to 0.2%]). Firearm suicide rates decreased globally at an annualized rate of 1.6% (95% UI, 1.1-2.0), but in 124 of 195 countries and territories included in this study, these levels were either constant or significant increases were estimated. There was an annualized decrease of 0.9% (95% UI, 0.5%-1.3%) in the global rate of age-standardized firearm deaths from 1990 to 2016. Aggregate firearm injury deaths in 2016 were highest among persons aged 20 to 24 years (for men, an estimated 34 700 deaths [95% UI, 24 900-39 700] and for women, an estimated 3580 deaths [95% UI, 2810-4210]). Estimates of the number of firearms by country were associated with higher rates of firearm suicide ( P R2 = 0.21) and homicide ( P R2 = 0.35). Conclusions and Relevance This study estimated between 195 000 and 276 000 firearm injury deaths globally in 2016, the majority of which were firearm homicides. Despite an overall decrease in rates of firearm injury death since 1990, there was variation among countries and across demographic subgroups.

Journal ArticleDOI
28 Feb 2018-Nature
TL;DR: Geospatial estimates of child growth failure provide a baseline for measuring progress as well as a precision public health platform to target interventions to those populations with the greatest need, in order to reduce health disparities and accelerate progress.
Abstract: Insufficient growth during childhood is associated with poor health outcomes and an increased risk of death. Between 2000 and 2015, nearly all African countries demonstrated improvements for children under 5 years old for stunting, wasting, and underweight, the core components of child growth failure. Here we show that striking subnational heterogeneity in levels and trends of child growth remains. If current rates of progress are sustained, many areas of Africa will meet the World Health Organization Global Targets 2025 to improve maternal, infant and young child nutrition, but high levels of growth failure will persist across the Sahel. At these rates, much, if not all of the continent will fail to meet the Sustainable Development Goal target—to end malnutrition by 2030. Geospatial estimates of child growth failure provide a baseline for measuring progress as well as a precision public health platform to target interventions to those populations with the greatest need, in order to reduce health disparities and accelerate progress.

Journal ArticleDOI
TL;DR: A new comprehensive measure of expected human capital is provided, defined for each birth cohort as the expected years lived from age 20 to 64 years and adjusted for educational attainment, learning or education quality, and functional health status for 195 countries from 1990 to 2016, to facilitate monitoring the production of human capital.


Journal ArticleDOI
28 Feb 2018-Nature
TL;DR: Predicting years of schooling across five by five kilometre grids generates estimates of average educational attainment by age and sex at subnational levels, improving the ability of decision-makers to plan the precisely targeted interventions that will be necessary to deliver progress during the era of the Sustainable Development Goals.
Abstract: Educational attainment for women of reproductive age is linked to reduced child and maternal mortality, lower fertility and improved reproductive health. Comparable analyses of attainment exist only at the national level, potentially obscuring patterns in subnational inequality. Evidence suggests that wide disparities between urban and rural populations exist, raising questions about where the majority of progress towards the education targets of the Sustainable Development Goals is occurring in African countries. Here we explore within-country inequalities by predicting years of schooling across five by five kilometre grids, generating estimates of average educational attainment by age and sex at subnational levels. Despite marked progress in attainment from 2000 to 2015 across Africa, substantial differences persist between locations and sexes. These differences have widened in many countries, particularly across the Sahel. These high-resolution, comparable estimates improve the ability of decision-makers to plan the precisely targeted interventions that will be necessary to deliver progress during the era of the Sustainable Development Goals.

Journal ArticleDOI
16 May 2018-PLOS ONE
TL;DR: A significant portion of the patients in Bangladesh are not satisfied with their received care, and patients’ satisfaction can be increased by focusing on improving facility cleanliness, privacy settings and providers’ interpersonal skills.
Abstract: There is a paucity in current literature about the level of patients' satisfaction and factors influencing it in Bangladesh health system. We aimed to measure the level of patients' satisfaction across different types and levels of healthcare facilities and to determine which factors influence this satisfaction level. A patient exit interview was carried out among 2207 patients attending selected health facilities in two administrative divisions of Bangladesh, namely Rajshahi and Sylhet. Information on healthcare experience and satisfaction with received care was collected through an electronic structured questionnaire. Information about 'overall satisfaction with healthcare' was collected on a 10-point scale and then dichotomized based on the median-split. Binomial logistic regressions, both simple and multivariable, were conducted to identify which factors contribute significantly to patients' satisfaction. We found that 63.2% of the participants were satisfied with the healthcare service they received. Patients attending the private facilities had the highest level of satisfaction (i.e. 73%) and patients attending the primary care facilities had the lowest level of satisfaction (i.e. 52%). Factors like convenient opening hours, asking related questions to the providers, facility cleanliness and privacy settings were significantly associated with patients' satisfaction. Being satisfied with facility cleanliness (multivariable OR 4.30; 95% CI: 3.29-5.62) and privacy settings (multivariable OR 1.68; 95% CI: 1.28-2.21) were the strongest predictors of patients' satisfaction. In conclusion, a significant portion of the patients in Bangladesh are not satisfied with their received care. Patients' satisfaction can be increased by focusing on improving facility cleanliness, privacy settings and providers' interpersonal skills.

Journal ArticleDOI
TL;DR: Subnational estimates of U5MR reveal significant within-country variation and could be used for identifying high-need areas and positive deviants, tracking trends in geographic inequalities, and evaluating progress towards international development targets such as the Sustainable Development Goals.
Abstract: The under-5 mortality rate (U5MR) is an important metric of child health and survival. Country-level estimates of U5MR are readily available, but efforts to estimate U5MR subnationally have been limited, in part, due to spatial misalignment of available data sources (e.g., use of different administrative levels, or as a result of historical boundary changes). We analyzed all available complete and summary birth history data in surveys and censuses in six countries (Bangladesh, Cameroon, Chad, Mozambique, Uganda, and Zambia) at the finest geographic level available in each data source. We then developed small area estimation models capable of incorporating spatially misaligned data. These small area estimation models were applied to the birth history data in order to estimate trends in U5MR from 1980 to 2015 at the second administrative level in Cameroon, Chad, Mozambique, Uganda, and Zambia and at the third administrative level in Bangladesh. We found substantial variation in U5MR in all six countries: there was more than a two-fold difference in U5MR between the area with the highest rate and the area with the lowest rate in every country. All areas in all countries experienced declines in U5MR between 1980 and 2015, but the degree varied both within and between countries. In Cameroon, Chad, Mozambique, and Zambia we found areas with U5MRs in 2015 that were higher than in other parts of the same country in 1980. Comparing subnational U5MR to country-level targets for the Millennium Development Goals (MDG), we find that 12.8% of areas in Bangladesh did not meet the country-level target, although the country as whole did. A minority of areas in Chad, Mozambique, Uganda, and Zambia met the country-level MDG targets while these countries as a whole did not. Subnational estimates of U5MR reveal significant within-country variation. These estimates could be used for identifying high-need areas and positive deviants, tracking trends in geographic inequalities, and evaluating progress towards international development targets such as the Sustainable Development Goals.

Journal ArticleDOI
05 Jul 2018-Vaccine
TL;DR: Evidence that determinants should be approached in the context of relevant outcomes, and evidence of specific determinants that could have the greatest impact in these two countries, if targeted are provided.

Journal ArticleDOI
TL;DR: This study suggested that health facilities in Bangladesh suffered from lack of readiness in various aspects, most notably in diagnostic capacity.
Abstract: Service readiness of health facilities is an integral part of providing comprehensive quality healthcare to the community. Comprehensive assessment of general and service-specific (i.e. child immunization) readiness will help to identify the bottlenecks in healthcare service delivery and gaps in equitable service provision. Assessing healthcare facilities readiness also helps in optimal policymaking and resource allocation. A health facility survey was conducted between March 2015 and December 2015 in two purposively selected divisions in Bangladesh; i.e. Rajshahi division (high performing) and Sylhet division (low performing). A total of 123 health facilities were randomly selected from different levels of service, both public and private, with variation in sizes and patient loads from the list of facilities. Data on various aspects of healthcare facility were collected by interviewing key personnel. General service and child immunization specific service readiness were assessed using the Service Availability and Readiness Assessment (SARA) manual developed by World Health Organization (WHO). The analyses were stratified by division and level of healthcare facilities. The general service readiness index for pharmacies, community clinics, primary care facilities and higher care facilities were 40.6%, 60.5%, 59.8% and 69.5%, respectively in Rajshahi division and 44.3%, 57.8%, 57.5% and 73.4%, respectively in Sylhet division. Facilities at all levels had the highest scores for basic equipment (ranged between 51.7% and 93.7%) and the lowest scores for diagnostic capacity (ranged between 0.0% and 53.7%). Though facilities with vaccine storage capacity had very high levels of service readiness for child immunization, facilities without vaccine storage capacity lacked availability of many tracer items. Regarding readiness for newly introduced pneumococcal conjugate vaccine (PCV) and inactivated polio vaccine (IPV), most of the surveyed facilities reported lack of sufficient funding and resources (antigen) for training programs. Our study suggested that health facilities suffered from lack of readiness in various aspects, most notably in diagnostic capacity. Conversely, with very few challenges, nearly all the health facilities designated to provide immunization services were ready to deliver routine childhood immunization services as well as newly introduced PCV and IPV.

Journal ArticleDOI
TL;DR: The ‘financing gaps framework’, a new approach for harnessing information to make decisions about health aid, is proposed, designed to be forward-looking, goal-oriented, versatile and customizable to a range of organizational contexts and health aims.
Abstract: As growth in development assistance for health levels off, development assistance partners must make allocation decisions within tighter budget constraints. Furthermore, with the advent of comprehensive and comparable burden of disease and health financing estimates, empirical evidence can increasingly be used to direct funding to those most in need. In our 'financing gaps framework', we propose a new approach for harnessing information to make decisions about health aid. The framework was designed to be forward-looking, goal-oriented, versatile and customizable to a range of organizational contexts and health aims. Our framework brings together expected health spending, potential health spending and spending need, to orient financing decisions around international health targets. As an example of how the framework could be applied, we develop a case study, focused on global goals for child health. The case study harnesses data from the Global Burden of Disease 2013 Study, Financing Global Health 2015, the WHO Global Health Observatory and National Health Accounts. Funding flows are tied to progress toward the Sustainable Development Goal's target for reductions in under-five mortality. The flexibility and comprehensiveness of our framework makes it adaptable for use by a diverse set of governments, donors, policymakers and other stakeholders. The framework can be adapted to short- or long-run time frames, cross-country or subnational scales, and to a number of specific health focus areas. Depending on donor preferences, the framework can be deployed to incentivize local investments in health, ensuring the long-term sustainability of health systems in low- and middle-income countries, while also furnishing international support for progress toward global health goals.


Journal ArticleDOI
26 Nov 2018-Vaccine
TL;DR: This work tracks donor assistance for immunization by funding objective and channel from 1990 to 2016, and illustrates projections through 2020 to inform progress of the GVAP, using available data from development agencies supporting immunization.