Original research Burden of injury along the development spectrum: associations between the Socio-­demographic Index and disability-­adjusted life year estimates from the Global Burden of Disease Study 2017 ►►Additional material is published online only. To view, Juanita A Haagsma,1 Spencer L James ‍ ‍,2 Chris D Castle,2 Zachary V Dingels,2 please visit the journal online Jack T Fox,2 Erin B Hamilton,2 Zichen Liu,2 Lydia R Lucchesi,2 Nicholas L S Roberts,2 (http://​dx.​doi.​org/​10.​1136/​ injuryprev-​2019-​043296). Dillon O Sylte,2 Oladimeji M Adebayo,3 Alireza Ahmadi,4 Muktar Beshir Ahmed,5 For numbered affiliations see Miloud Taki Eddine Aichour,6 Fares Alahdab,7 Suliman A Alghnam,8 end of article. Syed Mohamed Aljunid,9,10 Rajaa M Al-­Raddadi,11 Ubai Alsharif,12 Khalid Altirkawi,13 Correspondence to Mina Anjomshoa,14 Carl Abelardo T Antonio,15,16 Seth Christopher Yaw Appiah,17,18 Dr Spencer L James, Institute for Health Metrics and Evaluation, Olatunde Aremu,19 Amit Arora,20,21 Hamid Asayesh,22 Reza Assadi,23 Ashish Awasthi,24 University of Washington, Beatriz Paulina Ayala Quintanilla,25,26 Shivanthi Balalla,27 Amrit Banstola,28 Seattle, WA 98121, USA; ​ spencj@​uw.​edu Suzanne Lyn Barker-­Collo,29 Till Winfried Bärnighausen,30,31 Received 3 May 2019 Shahrzad Bazargan-­Hejazi,32,33 Neeraj Bedi,34 Masoud Behzadifar,35 Revised 8 August 2019 Meysam Behzadifar,36 Corina Benjet,37 Derrick A Bennett,38 Isabela M Bensenor,39 Accepted 12 August 2019 Published Online First Soumyadeep Bhaumik,40 Zulfiqar A Bhutta,41,42 Ali Bijani,43 Guilherme Borges,37 8 January 2020 Rohan Borschmann,44,45 Dipan Bose,46 Soufiane Boufous,47 Alexandra Brazinova,48 Julio Cesar Campuzano Rincon,49,50 Rosario Cárdenas,51 Juan J Carrero,52 Félix Carvalho,53 Carlos A Castañeda-­Orjuela,54,55 Ferrán Catalá-López,56,57 Jee-­Young J Choi,58 Devasahayam J Christopher,59 Christopher Stephen Crowe,60 Koustuv Dalal,61,62 Ahmad Daryani,63 Dragos Virgil Davitoiu,64,65 Louisa Degenhardt,2,66 Diego De Leo,67 Jan-­Walter De Neve,30 Kebede Deribe,68,69 Getenet Ayalew Dessie,70 Gabrielle Aline deVeber,71 Samath Dhamminda Dharmaratne,2,72 Linh Phuong Doan,73 Kate A Dolan,74 Tim Robert Driscoll,75 Manisha Dubey,76 Ziad El-­Khatib,77,78 Christian Lycke Ellingsen,79 Maysaa El Sayed Zaki,80 Aman Yesuf Endries,81 Sharareh Eskandarieh,82 Andre Faro,83 Seyed-­Mohammad Fereshtehnejad,84,85 Eduarda Fernandes,86 Irina Filip,87,88 Florian Fischer,89 Richard Charles Franklin,90 Takeshi Fukumoto,91,92 Kebede Embaye Gezae,93 Tiffany K Gill,94 Alessandra C Goulart,95,96 Ayman Grada,97 Yuming Guo,98,99 Rahul Gupta,100,101 Hassan Haghparast Bidgoli,102 Arvin Haj-­Mirzaian,103,104 Arya Haj-­Mirzaian,103,105 Randah R Hamadeh,106 Samer Hamidi,107 Josep Maria Haro,108,109 Hadi Hassankhani,110,111 Hamid Yimam Hassen,112,113 Rasmus Havmoeller,114 Delia Hendrie,115 Andualem Henok,112 Martha Híjar,116,117 Michael K Hole,118 Enayatollah Homaie Rad,119,120 Naznin Hossain,121,122 Sorin Hostiuc,123,124 Guoqing Hu,125 Ehimario U Igumbor,126,127 Olayinka Stephen Ilesanmi,128 Seyed Sina Naghibi Irvani,129 Sheikh Mohammed Shariful Islam,130,131 Rebecca Q Ivers,132 Kathryn H Jacobsen,133 Nader Jahanmehr,134,135 Mihajlo Jakovljevic,136 Achala Upendra Jayatilleke,137,138 Ravi Prakash Jha,139 Jost B Jonas,140,141 Zahra Jorjoran Shushtari,142 Jacek Jerzy Jozwiak,143 © Author(s) (or their employer(s)) 2020. Re-­use Mikk Jürisson,144 Ali Kabir,145 Rizwan Kalani,146 Amir Kasaeian,147,148 permitted under CC BY. Abraham Getachew Kelbore,149 Andre Pascal Kengne,150,151 Yousef Saleh Khader,152 Published by BMJ. Morteza Abdullatif Khafaie,153 Nauman Khalid,154 Ejaz Ahmad Khan,155 To cite: Haagsma JA, James SL, Castle CD, et al. Abdullah T Khoja,156,157 Aliasghar A Kiadaliri,158 Young-­Eun Kim,159 Daniel Kim,160 Inj Prev 2020;26:i12–i26. Adnan Kisa,161 Ai Koyanagi,162,163 Barthelemy Kuate Defo,164,165 i12 Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 Original research Burcu Kucuk Bicer,166,167 Manasi Kumar,168,169 Ratilal Lalloo,170 Hilton Lam,171 Faris Hasan Lami,172 Van C Lansingh,173,174 Janet L Leasher,175 Shanshan Li,98 Shai Linn,176 Raimundas Lunevicius,177,178 Flavia R Machado,179 Hassan Magdy Abd El Razek,180 Muhammed Magdy Abd El Razek,181 Narayan Bahadur Mahotra,182 Marek Majdan,183 Azeem Majeed,184 Reza Malekzadeh,185,186 Manzoor Ahmad Malik,187,188 Deborah Carvalho Malta,189 Ana-­Laura Manda,190 Mohammad Ali Mansournia,191 Benjamin Ballard Massenburg,60 Pallab K Maulik,192,193 Hailemariam Abiy Alemu Meheretu,70,194 Man Mohan Mehndiratta,195,196 Addisu Melese,197 Walter Mendoza,198 Melkamu Merid Mengesha,199 Tuomo J Meretoja,200,201 Atte Meretoja,202,203 Tomislav Mestrovic,204,205 Tomasz Miazgowski,206 Ted R Miller,115,207 GK Mini,208,209 Erkin M Mirrakhimov,210,211 Babak Moazen,30,212 Naser Mohammad Gholi Mezerji,213 Roghayeh Mohammadibakhsh,214 Shafiu Mohammed,30,215 Mariam Molokhia,216 Lorenzo Monasta,217 Stefania Mondello,218,219 Pablo A Montero-­Zamora,220,221 Yoshan Moodley,222 Mahmood Moosazadeh,223 Ghobad Moradi,224,225 Maziar Moradi-­Lakeh,226 Lidia Morawska,227 Ilais Moreno Velásquez,228 Shane Douglas Morrison,229 Marilita M Moschos,230,231 Seyyed Meysam Mousavi,232,233 Srinivas Murthy,234 Kamarul Imran Musa,235 Gurudatta Naik,236 Farid Najafi,237 Vinay Nangia,238 Bruno Ramos Nascimento,239 Duduzile Edith Ndwandwe,240 Ionut Negoi,64,241 Trang Huyen Nguyen,242 Son Hoang Nguyen,242 Long Hoang Nguyen,242 Huong Lan Thi Nguyen,243 Dina Nur Anggraini Ningrum,244,245 Yirga Legesse Nirayo,246 Richard Ofori-­Asenso,247,248 Felix Akpojene Ogbo,249 In-­Hwan Oh,250 Olanrewaju Oladimeji,251,252 Andrew T Olagunju,253,254 Tinuke O Olagunju,255 Pedro R Olivares,256 Heather M Orpana,257,258 Stanislav S Otstavnov,259,260 Mahesh P A,261 Smita Pakhale,262 Eun-­Kee Park,263 George C Patton,264,265 Konrad Pesudovs,266 Michael R Phillips,267,268 Suzanne Polinder,1 Swayam Prakash,269 Amir Radfar,270,271 Anwar Rafay,272 Alireza Rafiei,273,274 Siavash Rahimi,275 Vafa Rahimi-­Movaghar,276 Muhammad Aziz Rahman,277,278 Rajesh Kumar Rai,279,280 Kiana Ramezanzadeh,281 Salman Rawaf,184,282 David Laith Rawaf,283,284 Andre M N Renzaho,249,285 Serge Resnikoff,286,287 Shahab Rezaeian,288 Leonardo Roever,289 Luca Ronfani,217 Gholamreza Roshandel,185,290 Yogesh Damodar Sabde,291 Basema Saddik,292 Payman Salamati,276 Yahya Salimi,237,293 Inbal Salz,294 Abdallah M Samy,295 Juan Sanabria,296,297 Lidia Sanchez Riera,298,299 Milena M Santric Milicevic,300,301 Maheswar Satpathy,302,303 Monika Sawhney,304 Susan M Sawyer,44,264 Sonia Saxena,305 Mete Saylan,306 Ione J C Schneider,307 David C Schwebel,308 Soraya Seedat,309 Sadaf G Sepanlou,185,186 Masood Ali Shaikh,310 Mehran Shams-­Beyranvand,311,312 Morteza Shamsizadeh,313 Mahdi Sharif-­Alhoseini,276 Aziz Sheikh,314,315 Jiabin Shen,316 Mika Shigematsu,317 Rahman Shiri,318 Ivy Shiue,319 João Pedro Silva,53 Jasvinder A Singh,320,321 Dhirendra Narain Sinha,322,323 Adauto Martins Soares Filho,324 Joan B Soriano,325,326 Sergey Soshnikov,327 Ireneous N Soyiri,328,329 Vladimir I Starodubov,330 Dan J Stein,323,331 Mark A Stokes,332 Mu’awiyyah Babale Sufiyan,333 Jacob E Sunshine,334 Bryan L Sykes,335 Rafael Tabarés-­Seisdedos,336,337 Karen M Tabb,338 Arash Tehrani-­Banihashemi,226,339 Gizachew Assefa Tessema,340,341 Jarnail Singh Thakur,342 Khanh Bao Tran,343,344 Bach Xuan Tran,345 Lorainne Tudor Car,346 Olalekan A Uthman,347 Benjamin S Chudi Uzochukwu,348 Pascual R Valdez,349,350 Elena Varavikova,351 Ana Maria Nogales Vasconcelos,352,353 Narayanaswamy Venketasubramanian,354,355 Francesco S Violante,356,357 Vasily Vlassov,358 Yasir Waheed,359 Yuan-­Pang Wang,360 Tissa Wijeratne,361,362 Andrea Sylvia Winkler,363,364 Priyanka Yadav,365 Yuichiro Yano,366 Muluken Azage Yenesew,194 Paul Yip,367,368 Engida Yisma,369 Naohiro Yonemoto,370 Mustafa Z Younis,371,372 Chuanhua Yu,373,374 Shamsa Zafar,375 Zoubida Zaidi,376 Sojib Bin Zaman,377,378 Mohammad Zamani,379 Yong Zhao,380 Sanjay Zodpey,381 Simon I Hay,2,382 Alan D Lopez,2,383 Ali H Mokdad,2,382 Theo Vos2,382 Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 i13 Original research Abstract behind changes in development and allow for the identification Background The epidemiological transition of non-­communicable of determinants and mediating factors of injury burden. This diseases replacing infectious diseases as the main contributors to information allows identification determinants of injury burden. disease burden has been well documented in global health literature. This information serves as a crucial input for guiding health Less focus, however, has been given to the relationship between system investments and priority-­setting at the global, regional, sociodemographic changes and injury. The aim of this study was to national and subnational levels. examine the association between disability-­adjusted life years (DALYs) The Global Burden of Disease (GBD) 2015 study introduced from injury for 195 countries and territories at different levels along the a measure of development, the Socio-­demographic Index (SDI). development spectrum between 1990 and 2017 based on the Global SDI combines information on income per capita, education and Burden of Disease (GBD) 2017 estimates. fertility. Comparisons between DALYs and SDI showed that Methods Injury mortality was estimated using the GBD mortality age-­standardised DALY rates for many communicable diseases database, corrections for garbage coding and CODEm—the cause of declined profoundly over time, whereas improvements in SDI death ensemble modelling tool. Morbidity estimation was based on correlated strongly with the increasing importance of NCDs.4 surveys and inpatient and outpatient data sets for 30 cause-­of-­injury This paper aims to provide an overview of injury mortality, with 47 nature-­of-­injury categories each. The Socio-­demographic Index incidence and DALYs from the GBD 2017 study, with detailed (SDI) is a composite indicator that includes lagged income per capita, information on a range of causes of injuries; to examine the asso- average educational attainment over age 15 years and total fertility ciation between years of life lost (YLLs), YLDs and DALYs from rate. injury and development, as measured by SDI, cause of injury, Results For many causes of injury, age-­standardised DALY rates GBD region and over time; and to assess in which regions injury declined with increasing SDI, although road injury, interpersonal DALYs outpace or fall behind changes in development. violence and self-­harm did not follow this pattern. Particularly for self-­harm opposing patterns were observed in regions with similar SDI Methods levels. For road injuries, this effect was less pronounced. GBD 2017 study Conclusions The overall global pattern is that of declining injury The GBD 2017 study methods and results have been described burden with increasing SDI. However, not all injuries follow this pattern, in extensive detail elsewhere, including description of the analyt- which suggests multiple underlying mechanisms influencing injury ical estimation framework used to measure deaths, YLLs, YLDs DALYs. There is a need for a detailed understanding of these patterns and DALYs.4 13 14 A summary overview of the GBD study is to help to inform national and global efforts to address injury-­related provided in online supplementary appendix 1. The methodolog- health outcomes across the development spectrum. ical components specific to injuries estimation and SDI calcula- tion are summarised below. Injury incidence and death are defined as ICD-9 codes E800– E999 and ICD-10 chapters V–Y, except for deaths and cases of Introduction drug overdoses and unintentional alcohol poisoning, which are Injury is an important cause of morbidity and mortality in classified under drug and alcohol use disorders. These external nations at any point of the development spectrum. Previous cause-­of-­injury codes or ‘E codes’ are designated as mutually research has shown that in 2015, injuries accounted for 11% of exclusive and collectively exhaustive within the injuries estima- the global burden of disease, expressed in disability-­adjusted life tion process. In terms of the nature-­of-­injury codes (eg, the lower years (DALYs), with an estimated 973 million people sustaining extremity amputation that can occur with a road injury), inju- injuries warranting some type of healthcare and 4.7 million ries were categorised into 47 mutually exclusive and collectively deaths.1 Globally, since 1990, focused injury burden research has exhaustive nature-­of-­injury categories using chapters S and T in documented a declining trend in the burden of injury of all the International Classification of Disease (ICD) ICD-10 and codes major causes of injury.2 800–999 in ICD-9 to quantify the various disabling outcomes The epidemiological transition of non-­communicable diseases of each cause of injury. Some injuries are trivial and unlikely (NCDs) replacing infectious diseases as the main contributors to account for an important number of DALYs; hence, we only to disease burden has been well-­documented.1 3 4 However, less included injuries in our morbidity analysis that warranted some focus has been given to the relationship between sociodemo- form of healthcare. graphic changes and injury outcomes. Up till now, few studies have been performed that studied the relationship between sociodemographic changes and overall injury rates. There have Injury mortality and YLLs been reports on the associations of gross domestic product and The overall approach to estimate causes of death is provided unemployment with suicides, homicides, road injury and unin- in related publications.13 15 16 A summary is as follows. We first tentional injuries.5–12 However, these studies focused on one mapped data sources using different versions of ICD or alter- specific cause of injury and on one type of injury outcome, native classification systems to the GBD cause list. These data mostly mortality. The findings of these studies indicated that the sources included vital registration, verbal autopsy, mortality relationship between economic development and injury burden surveillance, censuses, surveys, hospitals, police records and is not straightforward and mediated by many factors. A better mortuary data. We then made adjustments for ill-­defined causes understanding of this relationship may be achieved by investi- of death such that they mapped to an underlying cause of death. gating all causes of injury as well as looking at both fatal and Next, we conducted ensemble models using GBD cause of death non-­fatal injury outcome. ensemble modelling (CODEm) software to estimate cause-­ Insight into the epidemiological transitions with regard to specific mortality by age, sex, country, year and cause. CODEm injuries can be achieved by a systematic analysis of the relation- is described in more detail elsewhere but in summary explores ship between development and trends in mortality, incidence a large variety of possible models to estimate trends in causes and burden of disease using a standardised approach. A system- of death using an algorithm to select varying combinations of atic analysis may also reveal where health gains outpace or fall covariates that are run through several modelling classes. The i14 Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 Original research method then creates an ensemble of best-­performing models that for each country–year grouping.26 The HAQ index is scaled from are determined by evaluating out-­of-­sample predictive validity. 0 to 100 and is based on 32 causes of death, covering a range Deaths are then rescaled for each cause so that the sum equals of health service areas, which should not occur if effective care the number of deaths from all causes to ensure internal consis- is present. Finally, we used DisMod-­MR V.2.1 to compute the tency. YLLs were calculated by multiplying deaths by the residual long-­term prevalence (ie, 1 year or more) for each cause–nature life expectancy at the age of death based on the GBD 2017 stan- combination from incidence, which also incorporated increased dard model life table.12 mortality risk of certain nature of injuries, such as traumatic brain injury based on meta-­analyses of studies providing stan- dardised mortality ratios of these conditions. YLDs were calcu- Injury incidence, prevalence and years lived with disability lated as prevalence of a health state multiplied by a disability Our method for estimating the incidence, prevalence and years weight. These estimates were then corrected for comorbidity lived with disability in non-­fatal injury outcomes is provided with other non-­fatal diseases using methods described elsewhere in other GBD publications.2 14 A summary is as follows. We in the GBD study.13 used DisMod-­MR V.2.1 (a meta-­regression tool for epidemio- logical modelling) to model injury incidence using data from Socio-demographic Index emergency department and hospital records and survey data SDI is a composite indicator that includes income per capita, to produce cause-­of-­injury incidence by location, year, age and average educational attainment over age 15 years and total sex. Across every injury cause model, we used national income fertility rate under age 25 years. The SDI has a value that ranges per capita as a covariate on excess mortality, which forces a from 0 to 1. 0 represents the lowest income per capita, lowest negative relationship between income and mortality to take educational attainmentand highest fertility under age 25 years into account higher case fatality in lower-­resource settings. observed across all GBD geographies from 1980 to 2017. 1 After modelling incidence of each cause of injury, we used represents the highest income per capita, highest educational a severity hierarchy to identify the nature-­of-­injury category attainment and lowest fertility under 25 years observed across all that would lead to the most long-­term burden when an indi- GBD geographies from 1980 to 2017. The average relationship vidual experiences multiple injuries. This hierarchy is based on between YLLs, YLDs and YLDs divided by DALYs was calcu- pooled data sets of follow-­up studies in which we translated lated with SDI using Gaussian process regression modelling. We each individual’s health status measure at 1 year after injury used these estimates of expected DALY rates that were predicted into a disability weight. This process is described in more detail based on the full range of SDI to determine whether observed in the GBD literature.12 14 17–22 Then, we generated matrices of health patterns deviated from trends associated with changes the proportions of each cause of injury that are expected to along the development spectrum. lead to each nature of injury as determined in dual-­coded (eg, both cause-­of-­injury and nature-­of-­injury coded) hospital and emergency department data sets and data from the Chinese GATHER compliance National Injury Surveillance System.23 These data sets were This study complies with the GATHER (Guidelines for Accurate used because the data were available in microdata format and Transparent Health Estimates Reporting) recommendations and they included dual-­coded data in the format required for (online supplementary appendix 2). this specific part of the analysis. The resulting cause–nature matrices varied by injury warranting hospital admission versus Results injury warranting other healthcare, high-­income/low-­income Mortality, incidence and burden of injury, 2017 countries, male/female and age group. In the next stage, we In 2017, worldwide 55.9 million (95% Uncertainty Interval (UI) estimated short-­term disability by cause and nature‐of‐injury 55.4 to 56.5 million) people died. Of these deaths, 4.5 million category based on average duration for treated cases for each (95% UI 4.3 to 4.6 million), 8.0% (95% UI 7.7% to 8.2%), were nature-­of-­injury category and for inpatient and outpatient due to injuries. Major causes of injury deaths were road injury injuries from the Dutch Injury Surveillance System.17 18 For (27.7%), self-­ harm (17.7%), falls (15.5%) and interpersonal 19 of the 47 nature-­of-­injury categories (eg, foreign body in violence (9.0%). ear, poisoning and fracture in ear), we supplemented these There were 521 million (95% UI 493 to 548 million) cases estimates with expert-­driven estimates of short-­term duration of non-­ fatal injuries in 2017, representing an increase of for nature-­of-­injury categories when the data set had insuffi- 167 million from the 354 million (95% UI 338 to 372 million) cient information. For untreated injuries, the average factor by cases of non-­fatal injuries in 1990. The global age-­standardised which the duration of short-­term injury outcomes is increased injury death rate was 57.9 per 100 000 (95% UI 55.9 to 59.2), for a given nature-­ of-­injury category when the injury goes with highest death rates for road injury (15.8 deaths per 100 untreated was estimated. 000 (95% UI 15.2 to 16.3)), self-­harm (10.0 deaths per 100 For longer-­ term injuries, we calculated the proportion of 000 (95% UI 9.4 to 10.3)) and falls (9.2 deaths per 100 000 injuries that would result in disability lasting more than a year (95% UI 8.5 to 9.8)) (see online supplementary appendix table for each nature-­of-­injury category by admission status and age. 1). Injury death rates were over twice as high in men compared This calculation was based on an assumption that disability from with women (80.9 per 100 000 (95% UI 77.7 to 83.0) and injury affects all cases in the short term with a proportion having 35.5 per 100 000 (95% UI 33.9 to 36.5), respectively). The persistent disability 1 year after the injury greater than the pre-­ global age-­standardised injury incidence rate was 6762.6 per injury health status. These probabilities of developing perma- 100 000 (95% UI 6412.0 to 7118.1)), with highest incidence nent health loss were based on a pooled data set of seven large rates for falls (2237.6 new cases per 100 000 (95% UI 1989.7 follow-­up studies from China, the Netherlands and the USA to 2532.3)) and mechanical forces (943.6 new cases per 100 that used patient-­reported outcome measures to assess health 000 (95% UI 808.7 to 1100.6)) (see online supplementary status.17–22 24 25 We used the GBD healthcare access and quality appendix table 1). Injury incidence rates were almost twice (HAQ) index to estimate the ratio of treated to untreated injuries as high in men compared with women (7827.1 per 100 000 Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 i15 Original research (95% UI 7435.3 to 8242.9) and 5654.5 per 100 000 (95% UI (from 197 (95% UI 157 to 228) to 111 (95% UI 93 to 129) 5351.3 to 5962.1), respectively). DALYs per 100 000). Between 1990 and 2017, the age-­ Injuries contributed 10.1% (9.7%–10.5%) to the global standardised rates of YLDs and YLLs from injuries declined burden of disease in 2017 (3267.0 DALYs per 100 000 by 7.8% and 38.8%, respectively, while incidence of injuries (95% UI 3058.2 to 3505.1)). YLLs were responsible for the only declined by 0.9%. majority of the injury DALYs (77%; 2548 YLLs per 100 000 (95% UI 2462 to 2610)). The main contributors to injury DALYs were road injuries (871.1 DALYs per 100 000 (95% Burden of injury by SDI level The contribution of cause-­of-­injury category DALY rates to UI 827.9 to 917.3); 26.7%), falls (459.5 DALYs per 100 000 the total injury DALY rates differed by year, age category, (95% UI 387.1 to 547.5); 14.1%), self-­h arm (429.0 per 100 sex and SDI level. The largest disparity in DALY rate by SDI 000 (95% UI 401.6 to 443.5); 13.1%), interpersonal violence level was found in 0–6 days olds, ranging from a high of (334.3 DALYs per 100 000 (95% UI 304.7 to 360.5); 10.2%) 52 374 DALYs per 100 000 in the lowest SDI quintile to a and drowning (230.0 DALYs per 100 000 (95% UI 219.1 low of 6109 DALYs per 100 000 in the highest SDI quintile. to 241.2); 7.0%) (see online supplementary appendix table In men aged 15–49 years, conflict and terrorism stands out 2). The injury burden was highest in Syria (16 341.1 DALYs because of the high difference between highest and lowest per 100 000 (95% UI 15 892.7 to 16 858.4), Central African DALY rates by level of SDI (countries with low SDI 496 Republic (11 012.7 DALYs per 100 000 (95% UI 8807.9 to DALYs (95% UI 414 to 589) per 100 000; countries with 12 913.8)) and Lesotho (7951.3 DALYs per 100 000 (95% UI high SDI 2 DALYs (95% UI 1 to 2) per 100 000). 6424.8 to 9407.4)) and lowest in Maldives (1282.4 DALYs per 100 000 (95% UI 1138.1 to 1572.9)), Bermuda (1432.2 DALYs per 100 000 (95% UI 1267.5 to 1606.7)) and Italy YLL and YLD rates by SDI level (1458.1 DALYs per 100 000 (95% UI 1237.2 to 1739.4)) For many causes of injury, age-­standardised YLL and YLD (see online supplementary appendix table 3. SDI level for rates declined strikingly with increasing SDI, with propor- each country in 2017 is also provided). tionally largest decreases in YLL rates for conflict and terrorism (low SDI level 163.4 YLLs per 100 000; high SDI Change over time level 0.06 YLLs per 100 000), animal contact (low SDI level Between 1990 and 2017, the age-­standardised injury DALY 140.0 YLLs per 100 000; high SDI level 2 YLLs per 100 000) rates have declined from 4946 (95% UI 4655 to 5233) to and other unintentional injuries (low SDI level 7993 YLLs 3267 DALYs (95% UI 3058 to 3505) per 100 000, with per 100 000; high SDI level 8.4 YLLs per 100 000). Figure 1 largest absolute declines in drowning (from 635 (95% UI shows the level of age-­ s tandardised YLLs and YLDs per 571 to 689) to 230 (95% UI 219 to 241) DALYs per 100 100 000 against SDI (all regions, all years 1990–2017) by 000), road injuries (from 1259 (95% UI 1182 to 1330) to cause-­of-­injury. Largest decreases in YLD rates were seen for 871 (95% UI 828 to 917) DALYs per 100 000), self-­harm cause-­of-­injury categories conflict and terrorism, exposure (from 687 (95% UI 621 to 723) to 429 (95% UI 402 to to forces of nature and adverse effects of medical treatment. 443) DALYs per 100 000), and fire, heat and hot substances Exceptions were road injuries, self-­harm and interpersonal Figure 1 Age-­standardised YLL and YLD rates for 17 cause-­of-­injury categories by level of Socio-­demographic Index. YLL, years of life lost. i16 Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 Original research Figure 2 Co-­evolution of all injury age-­standardised DALY rates with SDI for the world and 21 GBD regions for 1990–2017 with comparison with the values expected on the basis of SDI alone. DALY, disability-­adjusted life year; GBD, Global Burden of Disease; SDI, Socio-­demographic Index. violence. The age-­standardised YLL rate of road injuries was SDI increased over time (see figure 3). South Asia, East Asia, highest at the low-­m iddle range SDI levels and lowest at Southern Sub-­Saharan Africa and Eastern Europe are excep- higher SDI levels, whereas YLDs from road injuries increased tions to this pattern, showing an initial increase and then a at higher SDI. The age-­standardised road injuries YLL rate decline. In GBD 2017, the regions with worse than expected increased from low SDI to low-­m iddle SDI, but declined at road injury DALYs based on SDI included North Africa and higher levels of SDI. For falls, at higher levels of SDI, the Middle East, Southern and Central Sub-­ Saharan Africa, composition of the disease burden shifted towards YLDs as Eastern Europe and Oceania, while regions with markedly the primary driver of DALYs. YLLs made up 63%, 61% and better than expected rates included Eastern Sub-­ Saharan 20% of DALYs from falls in low, middle and high SDI quin- Africa, South Asia and Southern Latin America. tiles, respectively. For road injuries, the proportion of YLLs dropped from 91% in countries with low SDI to 70% in Interpersonal violence countries with high SDI. In 2017, in all regions except for Southern Sub-­ Saharan Africa, Central Latin America, Tropical Latin America, Eastern Expected based on SDI versus observed burden of injury by SDI level, Europe, Caribbean, Oceania and high-­income North America, 1990–2017 the observed interpersonal violence DALY rates were better Figure 2 shows the level of all injury age-­standardised DALYs than expected based on SDI (see figure 4). Between 1990 and per 100 000 against SDI by GBD region from 1990 to 2017 2017, in most regions with higher than expected DALYs, the in comparison with expected values (black line) based on gap between observed and expected interpersonal violence SDI alone. The icons appearing above the black line for DALY rates decreased, except for Caribbean and Tropical Latin DALYs represent worse than expected injury DALYs and the America, where the gap increased. icons appearing below represent better than expected injury DALYs. As SDI generally increases over time, successive Self-harm markers represent years between 1990 and 2017. Regions The patterns of observed and expected self-­ harm DALYs where injury DALY rates were notably greater than expected based on SDI by GBD regions between 1990 and 2017 based on SDI included Central and Southern Sub-­Saharan differed markedly from those of other injuries (see figure 5). Africa, Oceania, Eastern Europe, Central Europe and high-­ In 1990, observed self-­harm DALY rates in East Asia and income North America. Regions where injury DALY rates Eastern Europe were worse than expected based on SDI were notably lower than expected based on SDI included but rapidly declined over time, with observed DALY rates Eastern and Western Sub-­S aharan Africa, South Asia, South- lower than expected in 2017. Southern Sub-­Saharan Africa east Asia and Western Europe. had worse than expected DALY rates but the other regions of Sub-­Saharan Africa had better than expected DALY rates. Road injury North Africa and Middle East, Western Europe, Southeast The expected road injury DALY rate by SDI shows that Asia, and Andean, Central and Tropical Latin America all most regions decreased in terms of road injury DALYs as had better than expected DALY rates. Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 i17 Original research Figure 3 Co-­evolution of road injury age-­standardised DALY rates with SDI for the world and 21 GBD regions for 1990–2017 with comparison with the values expected on the basis of SDI alone. DALY, disability-­adjusted life year; GBD, Global Burden of Disease; SDI, Socio-­demographic Index. Drowning Sub-­Saharan Africa. Eastern and Western Sub-­Saharan Africa, Drowning DALY rates between 1990 and 2017 decreased North Africa and Middle East, Andean, Tropical, Central in almost every GBD region regardless of their SDI value and Southern Latin America, Western Europe and Austral- (figure 6), except for Oceania, Eastern Europe and Southern asia had better than expected DALY rates, while Oceania, Figure 4 Co-­evolution of interpersonal violence age-­standardised DALY rates with SDI for the world and 21 GBD regions for 1990–2017 with comparison with the values expected on the basis of SDI alone. DALY, disability-­adjusted life year; GBD, Global Burden of Disease; SDI, Socio-­ demographic Index. i18 Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 Original research Figure 5 Co-­evolution of self-­harm age-­standardised DALY rates with SDI for the world and 21 GBD regions for 1990–2017 with comparison with the values expected on the basis of SDI alone. DALY, disability-­adjusted life year; GBD, Global Burden of Disease; SDI, Socio-­demographic Index. East Asia and Eastern Europe had worse than expected Asia, Central Asia and Australasia. Among these, Central DALY rates based on SDI. Asia and Central Europe decreased and then increased, while Eastern Europe increased and then decreased. South Falls Asia decreased steadily, while Australasia increased steadily The patterns in falls globally followed more dynamic trends until recent years. Among regions that performed better than across regions as SDI increased from 1990 to 2017 (see expected, Oceania had increasing rates as SDI increased, figure 7). The regions that performed worse than expected while high-­ income North America dropped precipitously in terms of SDI were Central Europe, Eastern Europe, South and then started increasing as SDI increased. Figure 6 Co-­evolution of drowning age-­standardised DALY rates with SDI for the world and 21 GBD regions for 1990–2017 with comparison with the values expected on the basis of SDI alone. DALY, disability-­adjusted life year; GBD, Global Burden of Disease; SDI, Socio-­demographic Index. Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 i19 Original research Figure 7 Co-­evolution of falls age-­standardised DALY rates with SDI for the world and 21 GBD regions for 1990–2017 with comparison with the values expected on the basis of SDI alone. DALY, disability-­adjusted life year; GBD, Global Burden of Disease; SDI, Socio-­demographic Index. Discussion impoverishment, widening social inequality and the breakdown For many causes of injury, age-­standardised DALY rates declined of political institutions.30 31 It should be noted that our study did strikingly with increasing SDI, although road injury, interper- aim to assess determinants of the burden of injury and caution sonal violence and self-­harm did not strictly follow this pattern. is needed in attempting to draw conclusions with regard to Particularly for self-­harm opposing patterns were observed in possible reasons for regional trends and differences. regions with similar SDI levels, for example, the trends in high-­ Another notable finding from our study was that for falls, at income Asia Pacific were opposite the trends in Western Europe, the higher levels of SDI, the composition of the disease burden despite their proximity in terms of SDI. For road injuries, this shifted towards YLDs, rather than YLLs, as a more prominent effect was less pronounced; for nearly all regions, road injury driver of DALYs compared with areas with lower SDI. The DALY rates declined after 2005. proportion of DALYs due to YLDs also increases with higher In Southern Sub-­Saharan Africa, injury DALYs were worse levels of SDI among other injuries. It is possible that this shift than expected based on SDI in the overall injuries category as in distribution reflects decreased mortality among injuries when well as many of the specific injuries. In this region, road injury people in higher SDI locations have access to better healthcare and interpersonal violence were important causes explaining services. The shift in road injuries, for example, could be brought the gap between observed and expected levels of overall injury about by injury-­prevention measures reducing the severity of the DALYs. Many underlying and intertwining determinants of the injury sustained (eg, seat belts and helmets) or by improved access high levels of interpersonal violence have been cited, including to better quality care after an injury (eg, trauma systems). It is income inequality and poverty, high unemployment, rapid social also possible that in age-­standardised analyses, the shift towards change, corruption and poor rule of law, gender inequality, YLDs may be due to the ageing of the population of countries family breakdown, access to firearms, and alcohol and drug with high SDI with commensurate age-­related increases in injury abuse.27 Despite these difficulties, however, and the worse-­than-­ incidence. For example, the incidence of falls increases substan- expected performance relative to SDI, our findings show that tially with age and most of the burden from falls in high-­SDI the DALY rates in Southern Sub-­Saharan Africa have decreased countries occurs in the very old.32 from 2000 to 2017. This trend tallies with a reported declining number of injury deaths among young adults in South Africa.28 Of regions with a middle-­high SDI, Eastern Europe stands out, Limitations because for most causes of injury, DALYs were much worse than Our analysis has several limitations. First, as SDI and time are expected based on SDI, particularly in the period 1990–2005. A correlated, we may be over interpreting SDI as a driver of change compelling explanation for this finding may be the dissolution of as it could well be driven largely by other factors changing over the former Soviet Union and the resulting social and economic time, not necessarily linked to SDI, such as climate change. consequences on health and mortality.29 However, others have Second, limited data are available to quantify burden of argued that causes of the health crisis are more complex and injuries in the world. Major limitations of the cause-­of-­death may result from a combination of historical and contemporary data are low or absent coverage of vital registration or verbal forces, including lifestyle habits, such as alcohol use, economic autopsy data in many parts of the world, incompleteness of i20 Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 Original research death certification systems and differences in the proportion of injury deaths classified in ill-­defined codes.33–36 Few data What is already known on the subject were available for non-­fatal injuries, and if data were avail- able, injury was frequently recorded as a mix of cause and ►► Morbidity and mortality from injuries are known to be nature-­of-­injury codes and often a preponderance of nature-­ affected by socioeconomic development. of-­injury codes, while our analyses require attributing health outcomes to cause of injury. As a result, many non-­fatal injury hospitals and emergency departments data sets could not be What this study adds used. Furthermore, short-­term duration of several nature-­of-­ injury categories was based on expert-­driven estimates because ►► This study provides more recent estimates of global morbidity patient data was not available. Besides, gathering data on and mortality from injuries with a greater level of detail than deaths and morbidity due to forces of nature (ie, disasters) has previously been reported and with an updated method and collective violence is complicated by the fact that their for measuring sociodemographic development. aftereffects may severely disrupt the infrastructure of vital and ►► This study found that many injuries decreased in terms of health registration systems.37 The statistical methods that we morbidity and mortality as sociodemographic development have used to assess mortality, incidence and prevalence can increased over time, but also identified important exceptions borrow strength over time and geography to ensure an esti- to this trend. mate for all causes and all countries. Nevertheless, estimates ►► The study adds to the body of discussion on how economic for populations and time periods with few or absent data are development and sociodemographic changes should be inherently less precise. considered in preventing future injury burden. Non-­fatal injuries are reported by both cause of injury and nature of injury. Since our model requires a one-­to-­o ne rela- tionship between cause-­o f-­injury and nature-­o f-­injury cate- help to identify which prevention and/or healthcare measures gory, we developed a nature-­o f-­injuries severity hierarchy have been taken in these countries. that selects the injury that was likely to be responsible for the largest burden in a person with more than one injury. Author affiliations This means that we ignore the other injuries sustained by 1 Department of Public Health, Erasmus University Medical Center, Rotterdam, The such individuals and this may have led to some underesti- Netherlands 2 mation of the burden of non-­f atal injury. We decided to use Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA such a hierarchy after it proved difficult to use statistical 3 Department of Medicine, University College Hospital Ibadan, Ibadan, Nigeria methods on sparse data to parse estimates across co-­occur- 4 Department of Anesthesiology, Kermanshah University of Medical Sciences, ring injuries. Kermanshah, Iran 5 A second methodological limitation is the assessment of Department of Epidemiology, Jimma University, Jimma, Ethiopia 6 Higher National School of Veterinary Medicine, Algiers, Algeria the probability of permanent health loss, one of the main 7 Evidence Based Practice Center, Mayo Clinic Foundation for Medical Education and drivers of non-­ fatal burden of disease. The probability of Research, Rochester, Minnesota, USA long-­term injury was based on patient-­reported outcome data 8 Department of Population Health Research, King Abdullah International Medical from follow-­ up studies in just three countries. Also, long-­ Research Center, Riyadh, Saudi Arabia 9 term patient-­ reported outcome data may be influenced by Department of Health Policy and Management, Kuwait University, Safat, Kuwait 10 International Centre for Casemix and Clinical Coding, National University of response shift bias. Response shift is a change of outcome due Malaysia, Bandar Tun Razak, Malaysia to a change of the measurement perspective of the respon- 11 Department of Family and Community Medicine, King Abdulaziz University, Jeddah, dent (‘internal measurement scale’), where the usual change Saudi Arabia 12 is towards adaptation. In our study, response shift may have Department of Oral and Maxillofacial Surgery, University Hospital Knappschaftskrankenhaus Bochum, Bochum, Germany resulted in an underestimation of the severity of long-­term 13 King Saud University, Riyadh, Saudi Arabia consequences of injury and consequently, to an underestima- 14 Social Determinants of Health Research Center, Rafsanjan University of Medical tion of the non-­fatal burden of injury. Sciences, Rafsanjan, Iran 15 Third, even though a strong correlation between SDI and Department of Health Policy and Administration, University of the Philippines injury DALYs, YLLs and YLDs was found, this cannot be inter- Manila, Manila, Philippines 16 Department of Applied Social Sciences, Hong Kong Polytechnic University, Hong preted as being causal in nature, because income per capita and Kong, China education, two of the three components of SDI, were also used 17 Department of Sociology and Social Work, Kwame Nkrumah University of Science as covariates in all of the injury models except exposure to forces and Technology, Kumasi, Ghana 18 of nature and collective violence and legal intervention. In its Center for International Health, Ludwig Maximilians University, Munich, Germany 19 School of Health Sciences, Birmingham City University, Birmingham, UK original formulation, Murray et al suggested that SDI utility may 20 School of Science and Health, Western Sydney University, Sydney, New South be improved in the future through consideration of additional Wales, Australia societal elements, such as inequality in each component.1 21 Oral Health Services, Sydney Local Health District, Sydney, New South Wales, Australia 22 Qom University of Medical Sciences, Qom, Iran 23 Conclusions Education Development Center, Mashhad University of Medical Sciences, Mashhad, Iran The overall pattern is that of declining injury burden with 24 Indian Institute of Public Health, Gandhinagar, India increasing development. Not all injuries follow this pattern, 25 The Judith Lumley Centre, La Trobe University, Melbourne, Victoria, Australia 26 suggesting that there are multiple underlying mechanisms influ- General Office for Research and Technological Transfer, Peruvian National Institute encing injury outcomes. The detailed understanding of these of Health, Lima, Peru 27 School of Public Health, Auckland University of Technology, Auckland, New Zealand patterns helps to inform countries how best to respond to 28 Department of Research, Public Health Perspective Nepal, Pokhara-­Lekhnath changes in injury outcomes that occur with development and, in Metropolitan City, Nepal case of countries where health gains outpace development, may 29 School of Psychology, University of Auckland, Auckland, New Zealand Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 i21 Original research 30 78 Heidelberg Institute of Global Health (HIGH), Heidelberg University, Heidelberg, World Health Programme, Université du Québec en Abitibi-­Témiscamingue, Rouyn-­ Germany Noranda, Quebec, Canada 31 79 T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA Department of Pathology, Stavanger University Hospital, Stavanger, Norway 32 80 Department of Psychiatry, Charles R. Drew University of Medicine and Science, Los Department of Clinical Pathology, Mansoura University, Mansoura, Egypt 81 Angeles, California, USA Public Health Department, Saint Paul’s Hospital Millennium Medical College, Addis 33 Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Ababa, Ethiopia 82 Medicine, University of California Los Angeles, Los Angeles, California, USA Multiple Sclerosis Research Center, Tehran University of Medical Sciences, Tehran, 34 Department of Community Medicine, Gandhi Medical College Bhopal, Bhopal, India Iran 35 83 Social Determinants of Health Research Center, Lorestan University of Medical Department of Psychology, Federal University of Sergipe, Sao Cristovao, Brazil Sciences, Khorramabad, Iran 84 Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 36 Department of Epidemiology and Biostatistics, Lorestan University of Medical Stockholm, Sweden Sciences, Khorramabad, Iran 85 Division of Neurology, University of Ottawa, Ottawa, Ontario, Canada 37 Department of Epidemiology and Psychosocial Research, Ramón de la Fuente 86 REQUIMTE/LAQV, University of Porto, Porto, Portugal Muñiz National Institute of Psychiatry, Mexico City, Mexico 87 Psychiatry Department, Kaiser Permanente, Fontana, California, USA 38 Nuffield Department of Population Health, University of Oxford, Oxford, UK 88 School of Health Sciences, A.T. Still University, Mesa, Arizona, USA 39 Department of Internal Medicine, University of São Paulo, São Paulo, Brazil 89 Department of Population Medicine and Health Services Research, Bielefeld 40 The George Institute for Global Health, New Delhi, India University, Bielefeld, Germany 41 Centre for Global Child Health, The Hospital for Sick Children, Toronto, Ontario, 90 College of Public Health, Medical and Veterinary Science, James Cook University, Canada Douglas, Queensland, Australia 42 Centre of Excellence in Women and Child Health, Aga Khan University, Karachi, 91 Gene Expression & Regulation Program, The Wistar Institute, Philadelphia, Pakistan Pennsylvania, USA 43 Social Determinants of Health Research Center, Babol University of Medical 92 Department of Dermatology, Kobe University, Kobe, Japan Sciences, Babol, Iran 93 Department of Biostatistics, Mekelle University, Mekelle, Ethiopia 44 Centre for Adolescent Health, Murdoch Childrens Research Institute, Melbourne, 94 Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia Victoria, Australia 95 Center for Clinical and Epidemiological Research, University of São Paulo, Sao 45 School of Population and Global Health, University of Melbourne, Melbourne, Paulo, Brazil Victoria, Australia 96 Internal Medicine Department, University Hospital, University of São Paulo, Sao 46 Transport & Digital Development, World Bank, Washington, District of Columbia, Paulo, Brazil USA 97 School of Medicine, Boston University, Boston, Massachusetts, USA 47 Transport and Road Safety (TARS) Research Department, University of New South 98 School of Public Health and Preventive Medicine, Monash University, Melbourne, Wales, Sydney, New South Wales, Australia Victoria, Australia 48 Institute of Epidemiology, Comenius University, Bratislava, Slovakia 99 Department of Epidemiology and Biostatistics, Zhengzhou University, Zhengzhou, 49 National Institute of Public Health, Cuernavaca, Mexico China 50 School of Medicine, University of the Valley of Cuernavaca, Cuernavaca, Mexico 100 March of Dimes, Arlington, Virginia, USA 51 Department of Population and Health, Metropolitan Autonomous University, 101 School of Public Health, West Virginia University, Morgantown, West Virginia, USA Mexico City, Mexico 102 Institute for Global Health, University College London, London, UK 52 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 103 Department of Pharmacology, Tehran University of Medical Sciences, Tehran, Iran Stockholm, Sweden 104 53 Obesity Research Center, Shahid Beheshti University of Medical Sciences, Tehran, UCIBIO, University of Porto, Porto, Portugal 54 Iran Colombian National Health Observatory, National Institute of Health, Bogota, 105 Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA Colombia 106 55 Department of Family and Community Medicine, Arabian Gulf University, Epidemiology and Public Health Evaluation Group, National University of Colombia, Manama, Bahrain Bogota, Colombia 107 56 School of Health and Environmental Studies, Hamdan Bin Mohammed Smart National School of Public Health, Carlos III Health Institute, Madrid, Spain 57 University, Dubai, United Arab Emirates Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, 108 Biomedical Research Networking Center for Mental Health Network (CiberSAM), Ontario, Canada 58 Madrid, Spain Department of Biochemistry and Biomedical Science, Seoul National University 109 Hospital, Seoul, South Korea Research and Development Unit, San Juan de Dios Sanitary Park, Sant Boi de 59 Department of Pulmonary Medicine, Christian Medical College and Hospital (CMC), Llobregat, Spain 110 Vellore, India School of Nursing and Midwifery, Tabriz University of Medical Sciences, Tabriz, Iran 111 60 Division of Plastic Surgery, University of Washington, Seattle, Washington, USA Independent Consultant, Tabriz, Iran 112 61 Institute of Public Health Kalyani, Kalyani, India Department of Public Health, Mizan-­Tepi University, Teppi, Ethiopia 113 62 School of Health Science, Orebro University, Orebro, Sweden Unit of Epidemiology and Social Medicine, University Hospital Antwerp, Wilrijk, 63 Toxoplasmosis Research Center, Mazandaran University of Medical Sciences, Sari, Belgium 114 Iran Clinical Sciences, Karolinska University Hospital, Stockholm, Sweden 115 64 Department of General Surgery, Carol Davila University of Medicine and Pharmacy, School of Public Health, Curtin University, Perth, Western Australia, Australia 116 Bucharest, Romania Research Coordination, AC Environments Foundation, Cuernavaca, Mexico 117 65 Department of Surgery, Clinical Emergency Hospital Sf. Pantelimon, Bucharest, CISS, National Institute of Public Health, Cuernavaca, Mexico 118 Romania Department of Pediatrics, Dell Medical School, University of Texas Austin, Austin, 66 National Drug and Alcohol Research Centre, University of New South Wales, Texas, USA 119 Sydney, New South Wales, Australia Guilan Road Trauma Research Center, Guilan University of Medical Sciences, 67 Australian Institute for Suicide Research and Prevention, Griffith University, Mount Rasht, Iran 120 Gravatt, Queensland, Australia Social Determinants of Health Research Center, Guilan University of Medical 68 Department of Global Health and Infection, Brighton and Sussex Medical School, Sciences, Rasht, Iran 121 Brighton, UK Department of Pharmacology and Therapeutics, Dhaka Medical College, Dhaka 69 School of Public Health, Addis Ababa University, Addis Ababa, Ethiopia University, Dhaka, Bangladesh 122 70 Department of Nursing, Debre Markos University, Debre Markos, Ethiopia Department of Pharmacology, Bangladesh Industrial Gases Limited, Tangail, 71 Centre for Global Child Health, The Hospital for Sick Children, University of Toronto, Bangladesh 123 Toronto, Ontario, Canada Faculty of Dentistry, Department of Legal Medicine and Bioethics, Carol Davila 72 Department of Community Medicine, University of Peradeniya, Peradeniya, Sri University of Medicine and Pharmacy, Bucharest, Romania 124 Lanka Clinical Legal Medicine Department, National Institute of Legal Medicine Mina 73 Center of Excellence in Health Service Management, Nguyen Tat Thanh University, Minovici, Bucharest, Romania 125 Ho Chi Minh, Vietnam Department of Epidemiology and Health Statistics, Central South University, 74 Changsha, China University of New South Wales, Sydney, New South Wales, Australia 75 126 Sydney School of Public Health, University of Sydney, Sydney, New South Wales, School of Public Health, University of the Western Cape, Bellville, Cape Town, Australia South Africa 76 127 United Nations World Food Programme, New Delhi, India Department of Public Health, Walter Sisulu University, Mthatha, South Africa 77 128 Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden Department of Community Medicine, University of Ibadan, Ibadan, Nigeria i22 Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 Original research 129 180 Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Radiology Department, Mansoura Faculty of Medicine, Mansoura, Egypt 181 Sciences, Tehran, Iran Ophthalmology Department, Aswan Faculty of Medicine, Aswan, Egypt 130 182 Institute for Physical Activity and Nutrition, Deakin University, Burwood, Victoria, Institute of Medicine, Tribhuvan University, Kathmandu, Nepal 183 Australia Department of Public Health, Trnava University, Trnava, Slovakia 131 184 Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia Department of Primary Care and Public Health, Imperial College London, London, 132 Injury Division, The George Institute for Global Health, Newtown, New South UK 185 Wales, Australia Digestive Diseases Research Institute, Tehran University of Medical Sciences, 133 Department of Global and Community Health, George Mason University, Fairfax, Tehran, Iran 186 Virginia, USA Non-­communicable Diseases Research Center, Shiraz University of Medical 134 School of Management and Medical Education, Shahid Beheshti University of Sciences, Shiraz, Iran 187 Medical Sciences, Tehran, Iran Department of Humanities and Social Sciences, Indian Institute of Technology, 135 Safety Promotion and Injury Prevention Research Center, Shahid Beheshti Roorkee, Haridwar, India 188 University of Medical Sciences, Tehran, Iran Department of Development Studies, International Institute for Population 136 Department for Health Care and Public Health, I.M. Sechenov First Moscow State Sciences, Mumbai, India 189 Medical University, Moscow, Russia Department of Maternal and Child Nursing and Public Health, Federal University 137 Institute of Medicine, University of Colombo, Colombo, Sri Lanka of Minas Gerais, Belo Horizonte, Brazil 138 190 Faculty of Graduate Studies, University of Colombo, Colombo, Sri Lanka Surgery Department, Emergency University Hospital Bucharest, Bucharest, 139 Department of Community Medicine, Banaras Hindu University, Varanasi, India Romania 140 191 Department of Ophthalmology, Heidelberg University, Mannheim, Germany Department of Epidemiology and Biostatistics, Tehran University of Medical 141 Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Beijing, China Sciences, Tehran, Iran 142 192 Social Determinants of Health Research Center, University of Social Welfare and Research Department, The George Institute for Global Health, New Delhi, India 193 Rehabilitation Sciences, Tehran, Iran School of Medicine, University of New South Wales, Sydney, New South Wales, 143 Department of Family Medicine and Public Health, University of Opole, Opole, Australia 194 Poland School of Public Health, Bahir Dar University, Bahir Dar, Ethiopia 144 195 Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia Neurology Department, Janakpuri Super Specialty Hospital Society, New Delhi, 145 Minimally Invasive Surgery Research Center, Iran University of Medical Sciences, India 196 Tehran, Iran Neurology Department, Govind Ballabh Institute of Medical Education and 146 Department of Neurology, University of Washington, Seattle, Washington, USA Research, New Delhi, India 147 197 Hematology-­Oncology and Stem Cell Transplantation Research Center, Tehran Department of Medical Laboratory Sciences, Bahir Dar University, Bahir Dar, University of Medical Sciences, Tehran, Iran Ethiopia 148 198 Pars Advanced and Minimally Invasive Medical Manners Research Center, Iran Peru Country Office, United Nations Population Fund (UNFPA), Lima, Peru 199 University of Medical Sciences, Tehran, Iran Department of Epidemiology and Biostatistics, Haramaya University, Harar, 149 Department of Dermatology, Wolaita Sodo University, Wolaita Sodo, Ethiopia Ethiopia 150 200 Non-­communicable Diseases Research Unit, Medical Research Council South Breast Surgery Unit, Helsinki University Hospital, Helsinki, Finland 201 Africa, Cape Town, South Africa University of Helsinki, Helsinki, Finland 151 202 Department of Medicine, University of Cape Town, Cape Town, South Africa Neurocenter, Helsinki University Hospital, Helsinki, Finland 152 203 Department of Public Health and Community Medicine, Jordan University of School of Health Sciences, University of Melbourne, Melbourne, Victoria, Australia 204 Science and Technology, Ramtha, Jordan Clinical Microbiology and Parasitology Unit, Zora Profozic Polyclinic, Zagreb, 153 Social Determinants of Health Research Center, Ahvaz Jundishapur University of Croatia 205 Medical Sciences, Ahvaz, Iran University Centre Varazdin, University North, Varazdin, Croatia 154 206 School of Food and Agricultural Sciences, University of Management and Department of Propedeutics of Internal Diseases & Arterial Hypertension, Technology, Lahore, Pakistan Pomeranian Medical University, Szczecin, Poland 155 207 Epidemiology and Biostatistics Department, Health Services Academy, Islamabad, Pacific Institute for Research & Evaluation, Calverton, Maryland, USA 208 Pakistan Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for 156 Department of Public Health, Imam Muhammad Ibn Saud Islamic University, Medical Sciences and Technology, Trivandrum, India 209 Riyadh, Saudi Arabia Global Institute of Public Health (GIPH), Ananthapuri Hospitals and Research 157 Department of Health Policy and Management, Johns Hopkins University, Centre, Trivandrum, India 210 Baltimore, Maryland, USA Faculty of Internal Medicine, Kyrgyz State Medical Academy, Bishkek, Kyrgyzstan 158 211 Clinical Epidemiology Unit, Lund University, Lund, Sweden Department of Atherosclerosis and Coronary Heart Disease, National Center of 159 Department of Preventive Medicine, Korea University, Seoul, South Korea Cardiology and Internal Disease, Bishkek, Kyrgyzstan 160 212 Department of Health Sciences, Northeastern University, Boston, Massachusetts, Institute of Addiction Research (ISFF), Frankfurt University of Applied Sciences, USA Frankfurt, Germany 161 213 School of Health Sciences, Kristiania University College, Oslo, Norway Department of Biostatistics, Hamadan University of Medical Sciences, Hamadan, 162 CIBERSAM, San Juan de Dios Sanitary Park, Sant Boi de Llobregat, Spain Iran 163 214 Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain Hamadan University of Medical Sciences, Hamadan, Iran 164 215 Department of Demography, University of Montreal, Montreal, Quebec, Canada Health Systems and Policy Research Unit, Ahmadu Bello University, Zaria, Nigeria 165 216 Department of Social and Preventive Medicine, University of Montreal, Montreal, Faculty of Life Sciences and Medicine, King’s College London, London, UK 217 Quebec, Canada Clinical Epidemiology and Public Health Research Unit, Burlo Garofolo Institute for 166 Department of Public Health, Yuksek Ihtisas University, Ankara, Turkey Maternal and Child Health, Trieste, Italy 167 218 Department of Public Health, Hacettepe University, Ankara, Turkey Department of Biomedical and Dental Sciences and Morphofunctional Imaging, 168 Department of Psychiatry, University of Nairobi, Nairobi, Kenya University of Messina, Messina, Italy 169 219 Division of Psychology and Language Sciences, University College London, Department of Neurology, Oasi Research Institute, Troina, Italy 220 London, UK Department of Public Health Sciences, University of Miami, Miami, Florida, USA 170 221 School of Dentistry, The University of Queensland, Brisbane, Queensland, Australia Center for Health Systems Research, National Institute of Public Health, 171 Institute of Health Policy and Development Studies, National Institutes of Health, Cuernavaca, Mexico 222 Manila, Philippines Department of Public Health Medicine, University of KwaZulu-­Natal, Durban, 172 Department of Community and Family Medicine, University of Baghdad, Baghdad, South Africa 223 Iraq Health Sciences Research Center, Mazandaran University of Medical Sciences, Sari, 173 HelpMeSee, New York City, New York, USA Iran 174 224 International Relations Department, Mexican Institute of Ophthalmology, Social Determinants of Health Research Center, Kurdistan University of Medical Queretaro, Mexico Sciences, Sanandaj, Iran 175 225 College of Optometry, Nova Southeastern University, Fort Lauderdale, Florida, USA Department of Epidemiology and Biostatistics, Kurdistan University of Medical 176 School of Public Health, University of Haifa, Haifa, Israel Sciences, Sanandaj, Iran 177 226 Department of General Surgery, Aintree University Hospital National Health Preventive Medicine and Public Health Research Center, Iran University of Medical Service (NHS) Foundation Trust, Liverpool, UK Sciences, Tehran, Iran 178 227 Department of Surgery, University of Liverpool, Liverpool, UK International Laboratory for Air Quality and Health, Queensland University of 179 Anesthesiology, Pain and Intensive Care Department, Federal University of São Technology, Brisbane, Queensland, Australia 228 Paulo, Sao Paulo, Brazil Gorgas Memorial Institute for Health Studies, Panama City, Panama Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 i23 Original research 229 276 Department of Surgery, University of Washington, Seattle, Washington, USA Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, 230 1st Department of Ophthalmology, University of Athens, Athens, Greece Tehran, Iran 231 277 Biomedical Research Foundation, Academy of Athens, Athens, Greece School of Nursing and Healthcare Professions, Federation University, Heidelberg, 232 Health Management Reserach Center, Baqiyatallah University of Medical Sciences, Victoria, Australia 278 Tehran, Iran National Centre for Farmer Health, Deakin University, Waurn Ponds, Victoria, 233 Department of Health Management and Economics, Tehran University of Medical Australia 279 Sciences, Tehran, Iran Society for Health and Demographic Surveillance, Suri, India 234 280 Department of Pediatrics, University of British Columbia, Vancouver, British Department of Economics, University of Göttingen, Göttingen, Germany 281 Columbia, Canada Department of Pharmacology, Shahid Beheshti University of Medical Sciences, 235 School of Medical Sciences, Science University of Malaysia, Kubang Kerian, Tehran, Iran 282 Malaysia Academic Public Health Department, Public Health England, London, UK 236 283 Department of Epidemiology, University of Alabama at Birmingham, Birmingham, WHO Collaborating Centre for Public Health Education and Training, Imperial Alabama, USA College London, London, UK 237 284 Department of Epidemiology & Biostatistics, Kermanshah University of Medical University College London Hospitals, London, UK 285 Sciences, Kermanshah, Iran School of Social Sciences and Psychology, Western Sydney University, Penrith, New 238 Suraj Eye Institute, Nagpur, India South Wales, Australia 239 286 Hospital of the Federal University of Minas Gerais, Federal University of Minas Brien Holden Vision Institute, Sydney, New South Wales, Australia 287 Gerais, Belo Horizonte, Brazil Organization for the Prevention of Blindness, Paris, France 240 288 Cochrane South Africa, South African Medical Research Council, Cape Town, South Kermanshah University of Medical Sciences, Kermanshah, Iran 289 Africa Department of Clinical Research, Federal University of Uberlândia, Uberlândia, 241 General Surgery Department, Emergency Hospital of Bucharest, Bucharest, Brazil 290 Romania Golestan Research Center of Gastroenterology and Hepatology, Golestan 242 Center of Excellence in Behavioral Medicine, Nguyen Tat Thanh University, Ho Chi University of Medical Sciences, Gorgan, Iran 291 Minh, Vietnam National Institute for Research in Environmental Health, Indian Council of Medical 243 Institute for Global Health Innovations, Duy Tan University, Hanoi, Vietnam Research, Bhopal, India 244 292 Public Health Department, Universitas Negeri Semarang, Kota Semarang, College of Medicine, University of Sharjah, Sharjah, United Arab Emirates 293 Indonesia Social Development & Health Promotion Research Center, Kermanshah University 245 Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei City, of Medical Sciences, Kermanshah, Iran 294 Taiwan Health and Disability Intelligence Group, Ministry of Health, Wellington, New 246 Clinical Pharmacy Unit, Mekelle University, Mekelle, Ethiopia Zealand 247 295 Centre of Cardiovascular Research and Education in Therapeutics, Monash Department of Entomology, Ain Shams University, Cairo, Egypt 296 University, Melbourne, Victoria, Australia Department of Surgery, Marshall University, Huntington, West Virginia, USA 248 297 Independent Consultant, Accra, Ghana Department of Nutrition and Preventive Medicine, Case Western Reserve 249 Translational Health Research Institute, Western Sydney University, Penrith, New University, Cleveland, Ohio, USA 298 South Wales, Australia Rheumatology Department, University Hospitals Bristol NHS Foundation Trust, 250 Department of Preventive Medicine, Kyung Hee University, Dongdaemun-­gu, Bristol, UK 299 South Korea Institute of Bone and Joint Research, University of Sydney, Syndey, New South 251 HAST, Human Sciences Research Council, Durban, South Africa Wales, Australia 252 300 School of Public Health, Faculty of Health Sciences, University of Namibia, Institute of Social Medicine, University of Belgrade, Belgrade, Serbia 301 Osakhati, Namibia Centre-­School of Public Health and Health Management, University of Belgrade, 253 Department of Psychiatry and Behavioural Neurosciences, McMaster University, Belgrade, Serbia 302 Hamilton, ON, Canada UGC Centre of Advanced Study in Psychology, Utkal University, Bhubaneswar, 254 Department of Psychiatry, University of Lagos, Lagos, Nigeria India 255 303 Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Udyam-­Global Association for Sustainable Development, Bhubaneswar, India 304 Ontario, Canada Department of Public Health Sciences, University of North Carolina at Charlotte, 256 Institute of Physical Activity and Health, Autonomous University of Chile, Talca, Charlotte, North Carolina, USA 305 Chile School of Public Health, Imperial College London, London, UK 257 306 Applied Research Division, Public Health Agency of Canada, Ottawa, Ontario, Market Access Department, Bayer, Istanbul, Turkey 307 Canada School of Health Sciences, Federal University of Santa Catarina, Ararangua, Brazil 258 308 School of Psychology, University of Ottawa, Ottawa, Ontario, Canada Department of Psychology, University of Alabama at Birmingham, Birmingham, 259 Analytical Center, Moscow Institute of Physics and Technology, Dolgoprudny, Alabama, USA 309 Russia Department of Psychiatry, Stellenbosch University, Cape Town, South Africa 260 310 Committee for the Comprehensive Assessment of Medical Devices and Independent Consultant, Karachi, Pakistan 311 Information Technology, Health Technology Assessment Association, Moscow, Russia School of Medicine, Dezful University of Medical Sciences, Dezful, Iran 261 312 Department of Respiratory Medicine, Jagadguru Sri Shivarathreeswara Academy of School of Medicine, Alborz University of Medical Sciences, Karaj, Iran 313 Health Education and Research, Mysore, India Chronic Diseases (Home Care) Research Center, Hamadan University of Medical 262 Department of Medicine, Ottawa Hospital Research Institute, University of Ottawa, Sciences, Hamadan, Iran 314 Ottawa, Ontario, Canada Centre for Medical Informatics, University of Edinburgh, Edinburgh, UK 263 315 Department of Medical Humanities and Social Medicine, Kosin University, Busan, Division of General Internal Medicine and Primary Care, Harvard University, South Korea Boston, Massachusetts, USA 264 316 Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia Center for Pediatric Trauma Research, Research Institute at Nationwide Children’s 265 Population Health Department, Murdoch Childrens Research Institute, Melbourne, Hospital, Columbus, Ohio, USA 317 Victoria, Australia National Institute of Infectious Diseases, Tokyo, Japan 266 318 School of Optometry and Vision Science, University of New South Wales, Sydney, Finnish Institute of Occupational Health, Helsinki, Finland 319 New South Wales, Australia Institute of Medical Epidemiology, Martin Luther University Halle-­Wittenberg, 267 Shanghai Mental Health Center, Shanghai Jiao Tong University, Shanghai, China Halle, Germany 268 320 Department of Psychiatry, Department of Epidemiology, Columbia University, New Department of Medicine, University of Alabama at Birmingham, Birmingham, York City, New York, USA Alabama, USA 269 321 Department of Nephrology, Sanjay Gandhi Postgraduate Institute of Medical Medicine Service, US Department of Veteran Affairs, Birmingham, Alabama, USA 322 Sciences, Lucknow, India Department of Epidemiology, School of Preventive Oncology, Patna, India 270 323 College of Medicine, University of Central Florida, Orlando, Florida, USA Department of Epidemiology, Healis Sekhsaria Institute for Public Health, Mumbai, 271 College of Graduate Health Sciences, A.T. Still University, Mesa, Arizona, USA India 272 324 Department of Epidemiology & Biostatistics, Contech School of Public Health, Department of Diseases and Noncommunicable Diseases and Health Promotion, Lahore, Pakistan Federal Ministry of Health, Brasilia, Brazil 273 325 Department of Immunology, Mazandaran University of Medical Sciences, Sari, Iran Hospital Universitario de la Princesa, Autonomous University of Madrid, Madrid, 274 Molecular and Cell Biology Research Center, Mazandaran University of Medical Spain 326 Sciences, Sari, Iran Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), 275 Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran Madrid, Spain i24 Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 Original research 327 380 Department of Research Development, Federal Research Institute for Health School of Public Health and Management, Chongqing Medical University, Organization and Informatics of the Ministry of Health (FRIHOI), Moscow, Russia Chongqing, China 328 381 Hull York Medical School, University of Hull, Hull City, UK Indian Institute of Public Health, Public Health Foundation of India, Gurugram, 329 Usher Institute of Population Health Sciences and Informatics, University of India 382 Edinburgh, Edinburgh, UK Department of Health Metrics Sciences, School of Medicine, University of 330 Federal Research Institute for Health Organization and Informatics of the Ministry Washington, Seattle, Washington, USA 383 of Health (FRIHOI), Moscow, Russia University of Melbourne, Melbourne, Queensland, Australia 331 Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa Acknowledgements Mihajlo Jakovljevic Serbia acknowledges support through 332 Department of Psychology, Deakin University, Burwood, Victoria, Australia 333 the Grant OI 175 014 of the Ministry of Education Science and Technological Department of Community Medicine, Ahmadu Bello University, Zaria, Nigeria 334 Development of the Republic of Serbia. Shahrzad Bazargan-­Hejai acknowledges Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, Washington, USA support through the NIH National Center for Advancing Translational Science 335 Department of Criminology, Law and Society, University of California Irvine, Irvine, (NCATS) UCLA CTSI Grant Number UL1TR001881". Ashish Awasthi acknowledges California, USA support from the Department of Science and Technology, Government of India, New 336 Department of Medicine, University of Valencia, Valencia, Spain Delhi through INSPIRE Faculty program. Rafael Tabarés-­Seisdedos acknowledges 337 Carlos III Health Institute, Biomedical Research Networking Center for Mental support in part by grant number PROMETEOII/2015/021 from Generalitat Health Network (CiberSAM), Madrid, Spain Valenciana and the national grant PI17/00719 from ISCIII-­FEDER. Abdallah M 338 School of Social Work, University of Illinois, Urbana, Illinois, USA Samy acknowledges support from a fellowship from the Egyptian Fulbright Mission 339 Department of Community Medicine, Iran University of Medical Sciences, Tehran, Program. Eduarda Fernandes acknowledges support ID/MULTI/04378/2019 and Iran UID/QUI/50006/2019 with FCT/MCTES support through Portuguese national 340 Institute of Public Health, University of Gondar, Gondar, Ethiopia 341 funds. Félix Carvalho acknowledges support ID/MULTI/04378/2019 and UID/ School of Public Health, University of Adelaide, Adelaide, South Australia, Australia 342 School of Public Health, Post Graduate Institute of Medical Education and QUI/50006/2019 with FCT/MCTES support through Portuguese national funds. Research, Chandigarh, India Ilais Moreno Velásquezis acknowledges support from the Sistema Nacional de 343 Molecular Medicine and Pathology Department, University of Auckland, Auckland, Investigacion, SENACYT (Panama). Louisa Degenhardt acknowledges support by an New Zealand NHMRC research fellowship (#1135991) and by NIH grant NIDA R01DA1104470; 344 Clinical Hematology and Toxicology, Military Medical University, Hanoi, Vietnam The National Drug and Alcohol Research Centre is supported by funding from 345 Department of Health Economics, Hanoi Medical University, Hanoi, Vietnam the Australian Government Department of Health under the Drug and Alcohol 346 Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Program. Milena Santric Milicevic acknowledges the support from the Ministry of Singapore Education, Science and Technological Development, Republic of Serbia (Contract 347 Division of Health Sciences, University of Warwick, Coventry, UK No. 175087). Kebede Deribe KD is supported by a grant from the Wellcome Trust 348 Department of Community Medicine, University of Nigeria Nsukka, Enugu, Nigeria 349 [grant number 201900] as part of his International Intermediate Fellowship. Syed Argentine Society of Medicine, Buenos Aires, Argentina 350 Velez Sarsfield Hospital, Buenos Aires, Argentina Aljunid acknowledges support from the International Centre for Casemix and Clinical 351 Central Research Institute of Cytology and Genetics, Federal Research Institute Coding, Faculty of Medicine, National University of Malaysia and Department of for Health Organization and Informatics of the Ministry of Health (FRIHOI), Moscow, Health Policy and Management, Faculty of Public Health, Kuwait University for the Russia approval and support to participate in this research project. Jan-­Walter De Neve 352 Department of Statistics, University of Brasília, Brasília, Brazil was supported by the Alexander von Humboldt Foundation. Michael R Phillips 353 Directorate of Social Studies and Policies, Federal District Planning Company, acknowledges support from the Chinese National Natural Science Foundation of Brasília, Brazil China (NSFC, No. 81371502). Sheikh Mohammed Shariful Islam acknowledges 354 Raffles Neuroscience Centre, Raffles Hospital, Singapore, Singapore support from the National Heart Foundation of Australia and from a senior research 355 Yong Loo Lin School of Medicine, National University of Singapore, Singapore, fellowship from Deakin University. Duduzile Edith Ndwandwe acknowledges support Singapore 356 from Cochrane South Africa, South African Medical Research Council.Tissa Wijeratne Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy 357 Occupational Health Unit, Sant’Orsola Malpighi Hospital, Bologna, Italy acknowledges the Department of Medicine, Faculty of Medicine, University of 358 Department of Health Care Administration and Economics, National Research Rajarata, Saliyapura, Anuradhapura, Sri Lanka for their support. University Higher School of Economics, Moscow, Russia Funding Funding for GBD 2017 was provided by the Bill and Melinda Gates 359 Foundation University Medical College, Foundation University, Islamabad, Pakistan Foundation. 360 Department of Psychiatry, University of São Paulo, São Paulo, Brazil 361 Competing interests Dr. Carl Abelardo T Antonio reports personal fees from Department of Psychology and Counselling, University of Melbourne, Melbourne, Johnson & Johnson (Philippines), Inc., outside the submitted work. Dr. Jasvinder Victoria, Australia 362 Singh reports personal fees from Crealta/Horizon, Medisys, Fidia, UBM LLC, Department of Medicine, University of Melbourne, St Albans, Victoria, Australia 363 Medscape, WebMD, Clinical Care options, Clearview healthcare partners, Putnam Institute of Health and Society, University of Oslo, Oslo, Norway 364 associates, Spherix, the National Institutes of Health and the American College of Department of Neurology, Technical University of Munich, Munich, Germany 365 Rheumatology, stock options in Amarin pharmaceuticals and Viking pharmaceuticals, Centre for the Study of Regional Development, Jawahar Lal Nehru University, New participating in the steering committee of OMERACT, an international organization Delhi, India 366 that develops measures for clinical trials and receives arm’s length funding from Department of Preventive Medicine, Northwestern University, Chicago, Illinois, 12 pharmaceutical companies, including Amgen, Janssen, Novartis, Roche, UCB USA Group, Ardea/Astra Zeneca, Bristol Myers Squibb, Celgene, EliLilly, Horizon Pharma, 367 Centre for Suicide Research and Prevention, University of Hong Kong, Hong Kong, Pfizer, and Centrexion. Dr. Josep Maria Haro reports personal fees from Roche and China Lundbeck, and that the institute for which they work provides services to Eli Lilly 368 Department of Social Work and Social Administration, University of Hong Kong, and Co., outside the submitted work. Dr. Mete Saylan is an employee of Bayer Hong Kong, China AG, outside the submitted work. Dr Sheikh Mohammed Shariful Islam is funded 369 School of Allied Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia by National Heart Foundation of Australia and supported by a senior research 370 Department of Psychopharmacology, National Center of Neurology and Psychiatry, fellowship from Deakin University, outside the submitted work. Dr. Spencer James Tokyo, Japan reports grants from Sanofi Pasteur, outside the submitted work. 371 Health Economics & Finance, Jackson State University, Jackson, Mississippi, USA 372 School of Medicine, Tsinghua University, Beijing, China Patient consent for publication Not required. 373 Department of Epidemiology and Biostatistics, Wuhan University, Wuhan, China Provenance and peer review Not commissioned; externally peer reviewed. 374 Global Health Institute, Wuhan University, Wuhan, China 375 Department of Obstetrics & Gynaecology, A.C.S. Medical College and Hospital, Data availability statement Data are available in a public, open access Islamabad, Pakistan repository (​ghdx.​healthdata.​org). Select data are available on reasonable request. 376 Department of Epidemiology, University Hospital of Setif, Setif, Algeria Select input data may be obtained from a third party and are not publicly available. 377 Maternal and Child Health Division, International Centre for Diarrhoeal Disease Open access This is an open access article distributed in accordance with the Research, Dhaka, Bangladesh Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits 378 Department of Medicine, Monash University, Melbourne, Victoria, Australia others to copy, redistribute, remix, transform and build upon this work for any 379 Student Research Committee, Babol University of Medical Sciences, Babol, Iran purpose, provided the original work is properly cited, a link to the licence is given, Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296 i25 Original research and indication of whether changes were made. See: https://​creativecommons.​org/​ death, 1990-2013: a systematic analysis for the global burden of disease study 2013. licenses/​by/​4.​0/. Lancet 2014. 17 A Haagsma J, Van Beeck EF, Toet H. Posttraumatic stress disorder following injury: ORCID iD trajectories and impact on health-­related quality of life. J Depress Anxiety 2013;S4. Spencer L James http://​orcid.​org/​0000-​0003-​4653-​2507 18 Polinder S, van Beeck EF, Essink-­Bot ML, et al. Functional outcome at 2.5, 5, 9, and 24 months after injury in the Netherlands. J Trauma 2007;62:133–41. 19 Ringburg AN, Polinder S, van Ierland MCP, et al. Prevalence and prognostic factors of References disability after major trauma. J Trauma 2011;70:916–22. 1 Murray CJL, Barber RM, Foreman KJ, et al. Global, regional, and national disability-­ 20 Ringburg AN, Polinder S, Meulman TJ, et al. Cost-­effectiveness and quality-­of-­life adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy analysis of physician-­staffed helicopter emergency medical services. Br J Surg (HALE) for 188 countries, 1990–2013: quantifying the epidemiological transition. The 2009;96:1365–70. Lancet 2015;386:2145–91. 21 United States National Study on the Costs and Outcomes of Trauma Care 2001-2003. 2 Haagsma JA, Graetz N, Bolliger I, et al. The global burden of injury: incidence, Johns Hopkins Bloomberg School of Public Health, University of Washington, Westat, mortality, disability-­adjusted life years and time trends from the global burden of disease study 2013. Inj Prev 2016;22:3–18. Inc. 3 Omran AR. The epidemiologic transition. A theory of the epidemiology of population 22 van Loey NE, van Beeck EF, Faber BW, et al. Health-­related quality of life after burns: a change. Milbank Mem Fund Q 1971;49:509–38. prospective multicenter cohort study with 18 months follow-­up. J Trauma Acute Care 4 Kassebaum NJ, Arora M, Barber RM, et al. Global, regional, and national disability-­ Surg 2011. adjusted life-­years (DALYs) for 315 diseases and injuries and healthy life expectancy 23 Duan L, Deng X, Wang Y, et al. The National injury surveillance system in China: a (HALE), 1990–2015: a systematic analysis for the global burden of disease study six-­year review. Injury 2015;46:572–9. 2015. The Lancet 2016;388:1603–58. 24 Agency for Healthcare Research and Quality (AHRQ). Medical Expenditure Panel 5 Ahmed N, Andersson R. Unintentional injury mortality and socio-­economic Survey 1996-2012. development among 15-44-­year-­olds: in a health transition perspective. Public Health 25 Mackenzie EJ, Rivara FP, Jurkovich GJ, et al. The national study on costs and outcomes 2000;114:416–22. of trauma. J Trauma 2007;63(6 Suppl):S54–S67. 6 Moniruzzaman S, Andersson R. Relationship between economic development and 26 Fullman N, Yearwood J, Abay SM, et al. Measuring performance on the healthcare risk of injuries in older adults and the elderly. A global analysis of unintentional access and quality index for 195 countries and territories and selected subnational injury mortality in an epidemiologic transition perspective. Eur J Public Health locations: a systematic analysis from the global burden of disease study 2016. The 2005;15:454–8. Lancet 2018;391:2236–71. 7 Moniruzzaman S, Andersson R. Economic development as a determinant of injury 27 Norman R, Matzopoulos R, Groenewald P, et al. The high burden of injuries in South mortality - a longitudinal approach. Soc Sci Med 2008;66:1699–708. Africa. Bull World Health Organ 2007;85:695–702. 8 Muazzam S, Nasrullah M. Macro determinants of cause-­specific injury mortality in 28 Bah S. Unnoticed decline in the number of unnatural deaths in South Africa. S Afr Med the OECD countries: an exploration of the importance of GDP and unemployment. J J 2004;94:442–3. Community Health 2011;36:574–82. 29 Grigoriev P, Shkolnikov V, Andreev E, et al. Mortality in Belarus, Lithuania, and 9 Fountoulakis KN. Suicide and the economic situation in Europe: are we experiencing Russia: divergence in recent trends and possible explanations. Eur J Population the development of a ’reverse stigma’? Br J Psychiatry 2016;209:273–4. 2010;26:245–74. 10 Vallin J. Socio-­Economic determinants of mortality in industrialized countries. Popul 30 Chen LC, Wittgenstein F, McKeon E. The upsurge of mortality in Russia: causes and Bull UN 1980;13:26–41. policy implications. Popul Dev Rev 1996;22:517–30. 11 Bishai D, Quresh A, James P, et al. National road casualties and economic 31 Men T, Brennan P, Boffetta P, et al. Russian mortality trends for 1991-2001: analysis development. Health Econ 2006;15:65–81. by cause and region. BMJ 2003;327. 12 Khan UR, Sengoelge M, Zia N, et al. Country level economic disparities in child injury 32 Hartholt KA, Stevens JA, Polinder S, et al. Increase in fall-­related hospitalizations in mortality. Arch Dis Child 2015;100(Suppl 1):S29–S33. the United States, 2001-2008. J Trauma 2011;71:255–8. 13 Wang H, Naghavi M, Allen C, et al. Global, regional, and national life expectancy, 33 Mahapatra P, Shibuya K, Lopez AD, et al. Civil registration systems and vital statistics: all-­cause mortality, and cause-­specific mortality for 249 causes of death, 1980–2015: successes and missed opportunities. The Lancet 2007;370:1653–63. a systematic analysis for the global burden of disease study 2015. The Lancet 34 Joubert J, Rao C, Bradshaw D, et al. Characteristics, availability and uses of vital 2016;388:1459–544. registration and other mortality data sources in post-­democracy South Africa. Glob 14 GBD 2015 Disease and Injury Incidence and Prevalence Collaborators. Global, Health Action 2012;5:19263–19. regional, and national incidence, prevalence, and years lived with disability for 310 35 Obermeyer Z, Rajaratnam JK, Park CH, et al. Measuring adult mortality using sibling diseases and injuries, 1990-2015: a systematic analysis for the global burden of survival: a new analytical method and new results for 44 countries, 1974-2006. PLoS disease study 2015. Lancet 2016;388:1545–602. Med 2010;7:e1000260. 15 Lozano R, Naghavi M, Foreman K, et al. Global and regional mortality from 235 36 Setel PW, Macfarlane SB, Szreter S, et al. A scandal of invisibility: making everyone causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the count by counting everyone. The Lancet 2007;370:1569–77. global burden of disease study 2010. The Lancet 2012;380:2095–128. 37 Obermeyer Z, Murray CJL, Gakidou E. Fifty years of violent war deaths from 16 GBD 2013 Mortality and Causes of Death Collaborators. Global, regional, and Vietnam to Bosnia: analysis of data from the world health survey programme. BMJ national age-­sex specific all-­cause and cause-­specific mortality for 240 causes of 2008;336:1482–6. i26 Haagsma JA, et al. Inj Prev 2020;26:i12–i26. doi:10.1136/injuryprev-2019-043296