Cited by 1,302Injury Epidemiology and PreventionTrauma and Emergency Care StudiesHealth and Conflict Studies

The DOI matches its Crossref record; 48 of the 50 references it cites were found in a registry or an index, and 1 are not checked yet; none of the 34 sources its claims cite is checked for support yet.

The global burden of injury: incidence, mortality, disability-adjusted life years and time trends from the Global Burden of Disease study 2013

Open access
Haagsma, Juanita A, Graetz, Nicholas, Bolliger, Ian, Naghavi, Mohsen, Higashi, Hideki, Mullany, Erin C, Abera, Semaw Ferede, Abraham, Jerry Puthenpurakal, Adofo, Koranteng, Alsharif, Ubai, Ameh, Emmanuel A, Ammar, Walid, Antonio, Carl Abelardo T, Barrero, Lope H, Bekele, Tolesa, Bose, Dipan, Brazinova, Alexandra, Catalá-López, Ferrán, Dandona, Lalit, Dandona, Rakhi, Dargan, Paul I, De Leo, Diego, Degenhardt, Louisa, Derrett, Sarah, Dharmaratne, Samath D, Driscoll, Tim R, Duan, Leilei, Petrovich Ermakov, Sergey, Farzadfar, Farshad, Feigin, Valery L, Franklin, Richard C, Gabbe, Belinda, Gosselin, Richard A, Hafezi-Nejad, Nima, Hamadeh, Randah Ribhi, Hijar, Martha, Hu, Guoqing, Jayaraman, Sudha P, Jiang, Guohong, Khader, Yousef Saleh, Khan, Ejaz Ahmad, Krishnaswami, Sanjay, Kulkarni, Chanda, Lecky, Fiona E, Leung, Ricky, Lunevicius, Raimundas, Lyons, Ronan Anthony, Majdan, Marek, Mason-Jones, Amanda J, Matzopoulos, Richard, Meaney, Peter A, Mekonnen, Wubegzier, Miller, Ted R, Mock, Charles N, Norman, Rosana E, Orozco, Ricardo, Polinder, Suzanne, Pourmalek, Farshad, Rahimi-Movaghar, Vafa, Refaat, Amany, Rojas-Rueda, David, Roy, Nobhojit, Schwebel, David C, Shaheen, Amira, Shahraz, Saeid, Skirbekk, Vegard, Søreide, Kjetil, Soshnikov, Sergey, Stein, Dan J, Sykes, Bryan L, Tabb, Karen M, Temesgen, Awoke Misganaw, Tenkorang, Eric Yeboah, Theadom, Alice M, Tran, Bach Xuan, Vasankari, Tommi J, Vavilala, Monica S, Vlassov, Vasiliy Victorovich, Woldeyohannes, Solomon Meseret, Yip, Paul, Yonemoto, Naohiro, Younis, Mustafa Z, Yu, Chuanhua, Murray, Christopher J L, Vos, Theo, Balalla, Shivanthi, Phillips, Michael R·2016·Injury Prevention

Abstract

Background: The Global Burden of Diseases (GBD), Injuries, and Risk Factors study used the disability-adjusted life year (DALY) to quantify the burden of diseases, injuries, and risk factors. This paper provides an overview of injury estimates from the 2013 update of GBD, with detailed information on incidence, mortality, DALYs and rates of change from 1990 to 2013 for 26 causes of injury, globally, by region and by country. Methods: Injury mortality was estimated using the extensive GBD mortality database, corrections for ill-defined cause of death and the cause of death ensemble modelling tool. Morbidity estimation was based on inpatient and outpatient data sets, 26 cause-of-injury and 47 nature-of-injury categories, and seven follow-up studies with patient-reported long-term outcome measures. Results: In 2013, 973 million (uncertainty interval (UI) 942 to 993) people sustained injuries that warranted some type of healthcare and 4.8 million (UI 4.5 to 5.1) people died from injuries. Between 1990 and 2013 the global age-standardised injury DALY rate decreased by 31% (UI 26% to 35%). The rate of decline in DALY rates was significant for 22 cause-of-injury categories, including all the major injuries. Conclusions: Injuries continue to be an important cause of morbidity and mortality in the developed and developing world. The decline in rates for almost all injuries is so prominent that it warrants a general statement that the world is becoming a safer place to live in. However, the patterns vary widely by cause, age, sex, region and time and there are still large improvements that need to be made.

Checked 2026-10-06 · 1 reference not checked yet

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

In 2013, an estimated 973 million people sustained injuries warranting healthcare and 4.8 million died from injuries, while the global age-standardised injury DALY rate fell by 31% between 1990 and 2013. The decline was significant for 22 of 26 cause-of-injury categories, but patterns varied widely by cause, age, sex, region, and time.

Key findings

  • In 2013, 973 million (UI 942 to 993) people had injuries warranting some healthcare and 4.8 million (UI 4.5 to 5.1) died from injuries. Major causes of injury death were road injury (29.1%), self-harm (17.6%), falls (11.6%), and interpersonal violence (8.5%).
  • Injuries accounted for 10.1% (UI 9.5 to 10.8) of the global burden of disease; YLLs made up 85.2% (UI 81.2 to 88.7) of injury DALYs. Main DALY contributors were road injuries (29.3%), self-harm (14.0%), falls (12.0%), drowning (8.7%), and interpersonal violence (8.4%).
  • Global age-standardised injury DALY rates declined by 30.9% (UI 26.1 to 34.7) from 1990 to 2013, an annualised decline of 1.6%. YLD rates fell by 37.0%, YLL rates by 29.6%, and incidence rates by 19.5%.
  • Regional changes varied: Andean Latin America had a 54.8% decline in injury DALY rates, while Oceania had a non-significant 6.4% increase. Road injury DALY rates fell 15.7% globally, with large declines in high-income Asia Pacific (−66.9%) and western Europe (−61.1%), but non-significant increases in South Asia (6.5%), West sub-Saharan Africa (13.1%), and South sub-Saharan Africa (35.2%).

Methods

  • GBD 2013 estimated injury mortality using the GBD mortality database, corrections for ill-defined cause of death, and the cause of death ensemble modelling (CODEm) tool. Morbidity estimation used inpatient and outpatient datasets, 26 cause-of-injury and 47 nature-of-injury categories, and seven follow-up studies with patient-reported long-term outcome measures.
  • DALYs were calculated as YLLs plus YLDs; YLLs multiplied deaths by remaining life expectancy, and YLDs multiplied prevalent cases by disability weights. Incidence was estimated with DisMod-MR 2.0, cause-nature-of-injury matrices were applied, short- and long-term disability were modelled, uncertainty was propagated through 1000 draws, and rates were age-standardised to the GBD 2013 standard population.
  • Data sources included vital registration, verbal autopsy, mortality surveillance, censuses, surveys, hospitals, police records, and mortuaries; police and crime reports were uniquely used for road injury, self-harm, and interpersonal violence deaths.

Limitations

  • The paper states that vital registration coverage is low or absent in large parts of the world, requiring model-based prediction from covariates and verbal autopsy; police records tend to underestimate deaths; estimates for sparse data are less precise; and 95% UIs may not capture all uncertainty.
  • The paper states that probabilities of long-term health loss relied on follow-up studies from only China, the Netherlands, and the USA; rare nature-of-injury codes had limited cases; different injury classifications and patient-reported outcome measures required mapping, adding uncertainty and potential bias; and some outpatient cases may have been misclassified.
  • The paper states that short-term duration estimates were based on a limited sample from the Netherlands only and may be affected by recall bias, while untreated-injury durations relied on expert opinion; the health-system access proxy mainly reflects maternal and child health indicators and may not reflect trauma services. The text also makes evident that DisMod-MR’s steady-state assumption may be inaccurate if incidence or mortality trends are large, and that hospital data inclusion allowed a low bar of at least 45% cause-of-injury coding, which may not be representative.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1136/injuryprev-2015-041616

Cites

48 of 49 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Figure 1 Flowchart of Global Burden of Disease Injury years lived with disability (YLD) estimation.
Figure 1 Flowchart of Global Burden of Disease Injury years lived with disability (YLD) estimation.CC BY-NC · PubMed Central
Figure 2 Disability-adjusted life year (DALY) rates by cause of injury, sex and region, ages 0–14 years. For the purposes of these plots, all non-road unintentional injuries have been collapsed to “All Other Unintent” (other transport injury, animal contact categories, foreign body categories, and adverse effects of medical treatment).
Figure 2 Disability-adjusted life year (DALY) rates by cause of injury, sex and region, ages 0–14 years. For the purposes of these plots, all non-road unintentional injuries have been collapsed to “All Other Unintent” (other transport injury, animal contact categories, foreign body categories, and adverse effects of medical treatment).CC BY-NC · PubMed Central
Figure 3 Disability-adjusted life year (DALY) rates by cause of injury, sex and region, ages 15–49 years of injury, sex and region.
Figure 3 Disability-adjusted life year (DALY) rates by cause of injury, sex and region, ages 15–49 years of injury, sex and region.CC BY-NC · PubMed Central
Figure 4 Disability-adjusted life year (DALY) rates by cause of injury, sex and region, ages 50–79 years of injury, sex and region.
Figure 4 Disability-adjusted life year (DALY) rates by cause of injury, sex and region, ages 50–79 years of injury, sex and region.CC BY-NC · PubMed Central
Figure 5 Disability-adjusted life year (DALY) rates by cause of injury, sex and region, ages 80 years and above of injury, sex and region.
Figure 5 Disability-adjusted life year (DALY) rates by cause of injury, sex and region, ages 80 years and above of injury, sex and region.CC BY-NC · PubMed Central
Figure 6 Percent change in age-standardised all-injury disability-adjusted life year (DALY) rates 1990–2013.
Figure 6 Percent change in age-standardised all-injury disability-adjusted life year (DALY) rates 1990–2013.CC BY-NC · PubMed Central
Figure 7 Percent change in age-standardised road injury disability-adjusted life year (DALY) rates 1990–2013.
Figure 7 Percent change in age-standardised road injury disability-adjusted life year (DALY) rates 1990–2013.CC BY-NC · PubMed Central
Figure 8 Percent change in age-standardised falls disability-adjusted life year (DALY) rates 1990–2013.
Figure 8 Percent change in age-standardised falls disability-adjusted life year (DALY) rates 1990–2013.CC BY-NC · PubMed Central
Figure 9 Percent change in age-standardised fire injury disability-adjusted life year (DALY) rates 1990–2013.
Figure 9 Percent change in age-standardised fire injury disability-adjusted life year (DALY) rates 1990–2013.CC BY-NC · PubMed Central
Figure 10 Percent change in age-standardised poisoning injury disability-adjusted life year (DALY) rates 1990–2013.
Figure 10 Percent change in age-standardised poisoning injury disability-adjusted life year (DALY) rates 1990–2013.CC BY-NC · PubMed Central
Figure 11 Percent change in age-standardised interpersonal violence disability-adjusted life year (DALY) rates 1990–2013.
Figure 11 Percent change in age-standardised interpersonal violence disability-adjusted life year (DALY) rates 1990–2013.CC BY-NC · PubMed Central
Figure 12 Percent change in age-standardised self-harm disability-adjusted life year (DALY) rates 1990–2013.
Figure 12 Percent change in age-standardised self-harm disability-adjusted life year (DALY) rates 1990–2013.CC BY-NC · PubMed Central

Verification

Claims the paper makes

74 Own result · 37 Own method · 19 Not checked yet · 14 No basis given · 12 Own interpretation

Verify all 34 references — free account
  • It may state two separate claims as one. 53
  • The quote only partly states this claim. 1
  • Probably not a substantial claim. 35
79 of 79
  • The paper relies on this without support.

    A detailed description of the GBD injury methods and results has not yet been published.

    “However, a detailed description of the GBD injury methods and results has not yet been published.”
  • The authors state this as an assumption.

    The DisMod-MR process assumes a steady state where rates are not changing over time.

    “this process assumes a steady state where rates are not changing over time”
2 of 2

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Metadata

Authors
Haagsma, J. A., Graetz, N., Bolliger, I., Naghavi, M., Higashi, H., Mullany, E. C., Abera, S. F., Abraham, J. P., Adofo, K., Alsharif, U., Ameh, E. A., Ammar, W., Antonio, C. A. T., Barrero, L. H., Bekele, T., Bose, D., Brazinova, A., Catalá-López, F., Dandona, L., Dandona, R., Dargan, P. I., De Leo, D., Degenhardt, L., Derrett, S., Dharmaratne, S. D., Driscoll, T. R., Duan, L., Petrovich Ermakov, S., Farzadfar, F., Feigin, V. L., Franklin, R. C., Gabbe, B., Gosselin, R. A., Hafezi-Nejad, N., Hamadeh, R. R., Hijar, M., Hu, G., Jayaraman, S. P., Jiang, G., Khader, Y. S., Khan, E. A., Krishnaswami, S., Kulkarni, C., Lecky, F. E., Leung, R., Lunevicius, R., Lyons, R. A., Majdan, M., Mason-Jones, A. J., Matzopoulos, R., Meaney, P. A., Mekonnen, W., Miller, T. R., Mock, C. N., Norman, R. E., Orozco, R., Polinder, S., Pourmalek, F., Rahimi-Movaghar, V., Refaat, A., Rojas-Rueda, D., Roy, N., Schwebel, D. C., Shaheen, A., Shahraz, S., Skirbekk, V., Søreide, K., Soshnikov, S., Stein, D. J., Sykes, B. L., Tabb, K. M., Temesgen, A. M., Tenkorang, E. Y., Theadom, A. M., Tran, B. X., Vasankari, T. J., Vavilala, M. S., Vlassov, V. V., Woldeyohannes, S. M., Yip, P., Yonemoto, N., Younis, M. Z., Yu, C., Murray, C. J. L., Vos, T., Balalla, S., & Phillips, M. R.
Affiliations
  • University of Washington (US)
  • Institute for Health Metrics and Evaluation (US)
  • Mekelle University (ET)
  • University of Southern California (US)
  • Kwame Nkrumah University of Science and Technology, Kumasi, Ashanti, Ghana
  • Charité – Universitätsmedizin Berlin (DE)
  • Ahmadu Bello University (NG)
  • Ministry of Public Health (LB)
  • University of the Philippines Manila (PH)
  • Pontificia Universidad Javeriana (CO)
  • Madda Walabu University (ET)
  • World Bank (US)
  • Faculty of Health Sciences and Social Work, Trnava University, Trnava, Slovakia
  • Ministry of Health (ES)
  • Public Health Foundation of India (IN)
  • Guy's and St Thomas' NHS Foundation Trust (GB)
  • Griffith University, Brisbane, Queensland, Australia
  • UNSW Sydney (AU)
  • Massey University (NZ)
  • University of Peradeniya (LK)
  • The University of Sydney (AU)
  • Chinese Center For Disease Control and Prevention (CN)
  • The Institute of Social and Economic Studies of Population at the Russian Academy of Sciences, Moscow, Russia
  • Non-Communicable Diseases Research Center (IR)
  • Auckland University of Technology (NZ)
  • James Cook University (AU)
  • Monash University (AU)
  • University of California, San Francisco (US)
  • Endocrinology and Metabolism Research Center, Tehran University of Medical Sciences, Tehran, Iran
  • Arabian Gulf University (BH)
  • Fundacion Entornos AC, Cuernavaca, Morelos, Mexico
  • Central South University (CN)
  • Virginia Commonwealth University (US)
  • Tianjin Centers for Disease Control and Prevention (CN)
  • Jordan University of Science and Technology (JO)
  • Health Services Academy (PK)
  • Oregon Health & Science University (US)
  • Rajarajeswari Medical College and Hospital (IN)
  • University of Sheffield (GB)
  • University at Albany, State University of New York (US)
  • Aintree University Hospital NHS Foundation Trust, Liverpool, UK
  • Swansea University (GB)
  • Faculty of Health Sciences and Social Work, Department of Public Health, Trnava University, Trnava, Slovakia
  • University of York, York, UK
  • South African Medical Research Council (ZA)
  • Children's Hospital of Philadelphia (US)
  • Addis Ababa University (ET)
  • Curtin University (AU)
  • Queensland University of Technology (AU)
  • Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz (MX)
  • Erasmus MC (NL)
  • University of British Columbia (CA)
  • Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
  • Suez Canal University (EG)
  • Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Catalonia, Spain
  • Bhabha Atomic Research Centre (IN)
  • University of Alabama at Birmingham (US)
  • An-Najah National University (PS)
  • Tufts Medical Center (US)
  • Norwegian Institute of Public Health (NO)
  • Stavanger University Hospital (NO)
  • Federal Research Institute for Health Organization and Informatics (RU)
  • University of Cape Town (ZA)
  • University of California, Irvine (US)
  • University of Illinois Urbana-Champaign (US)
  • Memorial University of Newfoundland (CA)
  • Johns Hopkins University (US)
  • Urho Kaleva Kekkonen Institute (FI)
  • Higher School of Economics, Moscow, Russia
  • University of Gondar (ET)
  • University of Hong Kong (HK)
  • National Center of Neurology and Psychiatry (JP)
  • Jackson State University (US)
  • Wuhan University (CN)
  • Emory University (US)
Corresponding author
Haagsma, Juanita A
Venue
Injury Prevention
Publisher
BMJ
Published
2015-12-03
Volume
22
Issue
1
Pages
3-18
ISSN
  • 1353-8047 (ISSN-L)
  • 1475-5785
OpenAlex
W2221016424
Cited by
1,302
References
50
Citations by year
2026: 67 · 2025: 87 · 2024: 128 · 2023: 124 · 2022: 149 · 2021: 165 · 2020: 172 · 2019: 151 · 2018: 120 · 2017: 94 · 2016: 42 · 2015: 1
FWCI
91.87
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
  • Injury Prevention (publishedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
  • QUT ePrints (Queensland University of Technology) (submittedVersion, cc-by-nc)
  • ResearchOnline - JCU (James Cook University) (submittedVersion, cc-by-nc)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, cc-by-nc)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • BIBSYS Brage (BIBSYS (Norway)) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
  • eSpace (Curtin University) (submittedVersion)
  • NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
  • HighWire Press Open Archive (submittedVersion)
  • RePub (Erasmus University Rotterdam) (submittedVersion)
  • Griffith Research Online (submittedVersion, cc-by-nc)
Funders
  • Bill and Melinda Gates Foundation
  • Medical Research Council (MR/K006525/1)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Injury Epidemiology and Prevention
  • Health Sciences › Medicine › Emergency Medicine › Trauma and Emergency Care Studies
  • Health Sciences › Health Professions › General Health Professions › Health and Conflict Studies
Keywords
injury burden, trauma mortality, injury incidence, disability-adjusted life years, temporal trends, global burden of disease, trauma morbidity, global health trends
MeSH terms
Adolescent, Adult, Aged, Aged, 80 and over, Cause of Death, Child, Child, Preschool, Female, Disabled Persons, Persons with Disabilities, Humans, Infant, Male, Middle Aged, Mortality, Risk Factors, Global Health, Wounds and Injuries, Incidence, Cost of Illness, Quality-Adjusted Life Years, Young Adult

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