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A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010

Stephen S Lim1, Theo Vos, Abraham D. Flaxman1  +208 moreInstitutions (92)
15 Dec 2012-The Lancet (Elsevier)-Vol. 380, Iss: 9859, pp 2224-2260

TL;DR: In this paper, the authors estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010.

AbstractMethods We estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent eff ects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010. W e estimated exposure distributions for each year, region, sex, and age group, and relative risks per unit of exposure by systematically reviewing and synthesising published and unpublished data. We used these estimates, together with estimates of cause-specifi c deaths and DALYs from the Global Burden of Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden, relative risks, and exposures into our estimates of attributable burden. Findings In 2010, the three leading risk factors for global disease burden were high blood pressure (7·0% [95% uncertainty interval 6·2–7·7] of global DALYs), tobacco smoking including second-hand smoke (6·3% [5·5–7·0]), and alcohol use (5·5% [5·0–5·9]). In 1990, the leading risks were childhood underweight (7·9% [6·8–9·4]), household air pollution from solid fuels (HAP; 7·0% [5·6–8·3]), and tobacco smoking including second-hand smoke (6·1% [5·4–6·8]). Dietary risk factors and physical inactivity collectively accounted for 10·0% (95% UI 9·2–10·8) of global DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in sodium. Several risks that primarily aff ect childhood communicable diseases, including unimproved water and sanitation and childhood micronutrient defi ciencies, fell in rank between 1990 and 2010, with unimproved water

Summary (1 min read)

Convincing evidence

  • Evidence based on epidemiological studies showing consistent associations between exposure and disease, with little or no evidence to the contrary.
  • The available evidence is based on a substantial number of studies including prospective observational studies and where relevant, randomised controlled trials of sufficient size, duration, and quality showing consistent effects.

Probable evidence

  • Evidence based on epidemiological studies showing fairly consistent associations between exposure and disease, but for which there are perceived shortcomings in the available evidence or some evidence to the contrary, which precludes a more definite judgment.
  • Shortcomings in the evidence may be any of the following: insufficient duration of trials (or studies); insufficient trials (or studies) available; inadequate sample sizes; or incomplete follow-up.

Possible evidence

  • Evidence based mainly on findings from case-control and cross-sectional studies.
  • Insufficient randomised controlled trials, observational studies, or non-randomised controlled trials are available.
  • Evidence based on non-epidemiological studies, such as clinical and laboratory investigations, is supportive.
  • More trials are needed to support the tentative associations, which should be biologically plausible.

Insufficient evidence

  • Evidence based on findings of a few studies which are suggestive, but insufficient to establish an association between exposure and disease.
  • Burden of disease attributable to individual risk factors are shown sequentially for ease of presentation.

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A comparative risk assessment of burden of disease and
injury attributable to 67 risk factors and risk factor clusters in
21 regions, 1990—2010: a systematic analysis for the Global
Burden of Disease Study 2010
Author
Lim, Stephen S, Vos, Theo, Flaxman, Abraham D, Danaei, Goodarz, Shibuya, Kenji, Adair-
Rohani, Heather, Amann, Markus, Anderson, H Ross, Andrews, Kathryn G, Aryee, Martin,
Atkinson, Charles, Bacchus, Loraine J, Bahalim, Adil N, Balakrishnan, Kalpana, Balmes, John,
Barker-Collo, Suzanne, Baxter, Amanda, Bell, Michelle L, Blore, Jed D, Blyth, Fiona, Bonner,
Carissa, Borges, Guilherme, Bourne, Rupert, Boussinesq, Michel, Brauer, Michael, Brooks,
Peter, Bruce, Nigel G, Brunekreef, Bert, Bryan-Hancock, Claire, Bucello, Chiara, Buchbinder,
Rachelle, Bull, Fiona, Burnett, Richard T, Byers, Tim E, Calabria, Bianca, Carapetis, Jonathan,
Carnahan, Emily, Chafe, Zoe, Charlson, Fiona, Chen, Honglei, Chen, Jian Shen, Cheng,
Andrew Tai-Ann, Child, Jennifer Christine, Cohen, Aaron, Colson, K Ellicott, Cowie, Benjamin C,
Darby, Sarah, Darling, Susan, Davis, Adrian, Degenhardt, Louisa, Dentener, Frank, Des Jarlais,
Don C, Devries, Karen, Dherani, Mukesh, Ding, Eric L, Dorsey, E Ray, Driscoll, Tim, Edmond,
Karen, Ali, Suad Eltahir, Engell, Rebecca E, Erwin, Patricia J, Fahimi, Saman, Falder, Gail,
Farzadfar, Farshad, Ferrari, Alize, Finucane, Mariel M, Flaxman, Seth, Fowkes, Francis Gerry
R, Freedman, Greg, Freeman, Michael K, Gakidou, Emmanuela, Ghosh, Santu, Giovannucci,
Edward, Gmel, Gerhard, Graham, Kathryn, Grainger, Rebecca, Grant, Bridget, Gunnell, David,
Gutierrez, Hialy R, Hall, Wayne, Hoek, Hans W, Hogan, Anthony, Hosgood, H Dean, Hoy,
Damian, Hu, Howard, Hubbell, Bryan J, Hutchings, Sally J, Ibeanusi, Sydney E, Jacklyn,
Gemma L, Jasrasaria, Rashmi, Jonas, Jost B, Kan, Haidong, Kanis, John A, Kassebaum,
Nicholas, Kawakami, Norito, Khang, Young-Ho, Khatibzadeh, Shahab, Khoo, Jon-Paul, Kok,
Cindy, Laden, Francine, Lalloo, Ratilal, Lan, Qing, Lathlean, Tim, Leasher, Janet L, Leigh,
James, Li, Yang, Lin, John Kent, Lipshultz, Steven E, London, Stephanie, Lozano, Rafael,
Lu, Yuan, Mak, Joelle, Malekzadeh, Reza, Mallinger, Leslie, Marcenes, Wagner, March, Lyn,
Marks, Robin, Martin, Randall, McGale, Paul, McGrath, John, Mehta, Sumi, Mensah, George
A, Merriman, Tony R, Micha, Renata, Michaud, Catherine, Mishra, Vinod, Hanafiah, Khayriyyah
Mohd, Mokdad, Ali A, Morawska, Lidia, Mozaffarian, Dariush, Murphy, Tasha, Naghavi,
Mohsen, Neal, Bruce, Nelson, Paul K, Miquel Nolla, Joan, Norman, Rosana, Olives, Casey,
Omer, Saad B, Orchard, Jessica, Osborne, Richard, Ostro, Bart, Page, Andrew, Pandey, Kiran
D, Parry, Charles DH, Passmore, Erin, Patra, Jayadeep, Pearce, Neil, Pelizzari, Pamela M,
Petzold, Max, Phillips, Michael R, Pope, Dan, Pope, C Arden, Powles, John, Rao, Mayuree,
Razavi, Homie, Rehfuess, Eva A, Rehm, Juergen T, Ritz, Beate, Rivara, Frederick P, Roberts,
Thomas, Robinson, Carolyn, Rodriguez-Portales, Jose A, Romieu, Isabelle, Room, Robin,
Rosenfeld, Lisa C, Roy, Ananya, Rushton, Lesley, Salomon, Joshua A, Sampson, Uchechukwu,
Sanchez-Riera, Lidia, Sanman, Ella, Sapkota, Amir, Seedat, Soraya, Shi, Peilin, Shield, Kevin,
Shivakoti, Rupak, Singh, Gitanjali M, Sleet, David A, Smith, Emma, Smith, Kirk R, Stapelberg,
Nicolas JC, Steenland, Kyle, Stoeckl, Heidi, Stovner, Lars Jacob, Straif, Kurt, Straney, Lahn,
Thurston, George D, Tran, Jimmy H, Van Dingenen, Rita, van Donkelaar, Aaron, Veerman,
J Lennert, Vijayakumar, Lakshmi, Weintraub, Robert, Weissman, Myrna M, White, Richard
A, Whiteford, Harvey, Wiersma, Steven T, Wilkinson, James D, Williams, Hywel C, Williams,
Warwick, Wilson, Nicholas, Woolf, Anthony D, Yip, Paul, Zielinski, Jan M, Lopez, Alan D,
Murray, Christopher JL, Ezzati, Majid
Published
2012

Journal Title
The Lancet
Version
Post-print
DOI
https://doi.org/10.1016/S0140-6736(12)61766-8
Copyright Statement
© 2012 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-
NoDerivatives 4.0 International Licence which permits unrestricted, non-commercial use,
distribution and reproduction in any medium, providing that the work is properly cited.
Downloaded from
http://hdl.handle.net/10072/49807
Griffith Research Online
https://research-repository.griffith.edu.au

A comparative risk assessment of burden of disease and injury
attributable to 67 risk factors and risk factor clusters in 21
regions, 1990–2010: a systematic analysis for the Global Burden
of Disease Study 2010
A full list of authors and affiliations appears at the end of the article.
Summary
Background—Quantification of the disease burden caused by different risks informs prevention
by providing an account of health loss different to that provided by a disease-by-disease analysis.
No complete revision of global disease burden caused by risk factors has been done since a
comparative risk assessment in 2000, and no previous analysis has assessed changes in burden
attributable to risk factors over time.
Methods—We estimated deaths and disability-adjusted life years (DALYs; sum of years lived
with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67
risk factors and clusters of risk factors for 21 regions in 1990 and 2010. We estimated exposure
distributions for each year, region, sex, and age group, and relative risks per unit of exposure by
systematically reviewing and synthesising published and unpublished data. We used these
estimates, together with estimates of cause-specific deaths and DALYs from the Global Burden of
Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared
with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden,
relative risks, and exposures into our estimates of attributable burden.
Findings—In 2010, the three leading risk factors for global disease burden were high blood
pressure (7·0% [95% uncertainty interval 6·2–7·7] of global DALYs), tobacco smoking including
second-hand smoke (6·3% [5·5–7·0]), and alcohol use (5·5% [5·0–5·9]). In 1990, the leading risks
were childhood underweight (7·9% [6·8–9·4]), household air pollution from solid fuels (HAP;
7·0% [5·6–8·3]), and tobacco smoking including second-hand smoke (6·1% [5·4–6·8]). Dietary
risk factors and physical inactivity collectively accounted for 10·0% (95% UI 9·2–10·8) of global
DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in
sodium. Several risks that primarily affect childhood communicable diseases, including
unimproved water and sanitation and childhood micronutrient deficiencies, fell in rank between
Correspondence to: Dr Stephen S Lim, Institute for, Health Metrics and Evaluation, 2301 Fifth Ave, Suite 600, Seattle, WA 98121,
USA, stevelim@uw.edu.
*
Author listed alphabetically
Joint senior authors
Contributors
CJLM, SSL, and ME wrote the first draft. SSL, TV, AF, GD, KS, ADL, CJLM, and ME revised the report. ME, CJLM, and ADL
designed the study and provided overall guidance. SSL, EC, GF, CA, ESa, KA, REE, and LCR did comparative analyses of risk
factors. All other authors developed the estimates of risk-specific exposure, theoretical-minimum-risk exposure distribution, and RR
inputs, and checked and interpreted results.

1990 and 2010, with unimproved water we and sanitation accounting for 0·9% (0·4–1·6) of global
DALYs in 2010. However, in most of sub-Saharan Africa childhood underweight, HAP, and non-
exclusive and discontinued breastfeeding were the leading risks in 2010, while HAP was the
leading risk in south Asia. The leading risk factor in Eastern Europe, most of Latin America, and
southern sub-Saharan Africa in 2010 was alcohol use; in most of Asia, North Africa and Middle
East, and central Europe it was high blood pressure. Despite declines, tobacco smoking including
second-hand smoke remained the leading risk in high-income north America and western Europe.
High body-mass index has increased globally and it is the leading risk in Australasia and southern
Latin America, and also ranks high in other high-income regions, North Africa and Middle East,
and Oceania.
Interpretation—Worldwide, the contribution of different risk factors to disease burden has
changed substantially, with a shift away from risks for communicable diseases in children towards
those for non-communicable diseases in adults. These changes are related to the ageing
population, decreased mortality among children younger than 5 years, changes in cause-of-death
composition, and changes in risk factor exposures. New evidence has led to changes in the
magnitude of key risks including unimproved water and sanitation, vitamin A and zinc
deficiencies, and ambient particulate matter pollution. The extent to which the epidemiological
shift has occurred and what the leading risks currently are varies greatly across regions. In much
of sub-Saharan Africa, the leading risks are still those associated with poverty and those that affect
children.
Funding—Bill & Melinda Gates Foundation.
Introduction
Measurement of the burden of diseases and injuries is a crucial input into health policy.
Equally as important, is a comparative assessment of the contribution of potentially
modifiable risk factors for these diseases and injuries. The attribution of disease burden to
various risk factors provides a different account compared with disease-by-disease analysis
of the key drivers of patterns and trends in health. It is essential for informing prevention of
disease and injury.
Understanding the contribution of risk factors to disease burden has motivated several
comparative studies in the past few decades. The seminal work of Doll and Peto
1
provided a
comparative assessment of the importance of different exposures, particularly tobacco
smoking, in causing cancer. Peto and colleagues
2
subsequently estimated the effects of
tobacco smoking on mortality in developed countries since 1950. Although these risk factor-
specific or cause-specific analyses are useful for policy, a more comprehensive global
assessment of burden of disease attributable to risk factors can strengthen the basis for
action to reduce disease burden and promote health. The Global Burden of Disease Study
(GBD) 1990 provided the first global and regional comparative assessment of mortality and
disability adjusted life-years (DALYs) attributable to ten major risk factors.
3
However,
different epidemiological traditions for different risks limited the comparability of the
results. Subsequently, Murray and Lopez
4
proposed a framework for global comparative risk
assessment, which laid the basis for assessment of 26 risks in 2000.
5–7
Since this work,
WHO has provided estimates for some risks by the same methods but with updated
Lim et al. Page 2

exposures and some updates of the effect sizes for each risk.
8
Analyses have also been done
for specific clusters of diseases, like cancers,
9
or clusters of risk factors, like maternal and
child under-nutrition.
10
National comparative risk assessments (including in Australia, Iran,
Japan, Mexico, South Africa, Thailand, USA, and Vietnam) have also been undertaken with
similar approaches.
11–16
GBD 2010 provides an opportunity to re-assess the evidence for exposure and effect sizes of
risks for a broad set of risk factors by use of a common framework and methods.
Particularly, since this work was done in parallel with a complete re-assessment of the
burden of diseases and injuries in 1990 and 2010, for the first time changes in burden of
disease attributable to different risk factors can be analysed over time with comparable
methods. Since uncertainty has been estimated for each disease or injury outcome,
17,18
the
comparative risk assessment for GBD 2010 has also enabled us to incorporate uncertainty
into the final estimates. We describe the general approach and high-level findings for
comparison of the importance of 67 risk factors and clusters of risk factors, globally and for
21 regions of the world, over the past two decades.
Methods
Overview
The basic approach for the GBD 2010 comparative risk assessment is to calculate the
proportion of deaths or disease burden caused by specific risk factors—eg, ischaemic heart
disease caused by increased blood pressure—holding other independent factors unchanged.
These calculations were done for 20 age groups, both sexes, and 187 countries and for 1990,
2005 (results for 2005 not shown, available from authors on request), and 2010. We present
aggregated results for 21 regions.
Table 1 shows the included risk factors and their organisation into a hierarchy with three
levels. Level 1 risks are clusters of risk factors that are related by mechanism, biology, or
potential policy intervention. Most risks are presented at level 2. For occupational
carcinogens, a third level is included to provide additional detail about specific carcinogens.
For suboptimal breastfeeding we also include a third level to distinguish between
nonexclusive breastfeeding during the first 6 months and discontinued breastfeeding from 6
to 23 months.
We calculated burden attributable to all (67) risk factors and clusters of risk factors except
for physiological risks and air pollution. These two clusters present analytical challenges for
computation of the aggregate burden. For example, the effects of high body-mass index are
partly mediated through high blood pressure, high total cholesterol, and high fasting plasma
glucose, and household air pollution from solid fuels (wood, crop, residues, animal dung,
charcoal, and coal) contributes to ambient particulate matter pollution.
We ranked results for 43 risk factors and clusters of risk factors, grouping together
occupational carcinogens, non-exclusive and discontinued breastfeeding, and tobacco
smoking with second-hand smoke on the basis of common exposure sources.
Lim et al. Page 3


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Journal ArticleDOI
Rafael Lozano1, Mohsen Naghavi1, Kyle J Foreman2, Stephen S Lim1  +192 moreInstitutions (95)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2010 aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex, using the Cause of Death Ensemble model.
Abstract: Summary Background Reliable and timely information on the leading causes of death in populations, and how these are changing, is a crucial input into health policy debates. In the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010), we aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex. Methods We attempted to identify all available data on causes of death for 187 countries from 1980 to 2010 from vital registration, verbal autopsy, mortality surveillance, censuses, surveys, hospitals, police records, and mortuaries. We assessed data quality for completeness, diagnostic accuracy, missing data, stochastic variations, and probable causes of death. We applied six different modelling strategies to estimate cause-specific mortality trends depending on the strength of the data. For 133 causes and three special aggregates we used the Cause of Death Ensemble model (CODEm) approach, which uses four families of statistical models testing a large set of different models using different permutations of covariates. Model ensembles were developed from these component models. We assessed model performance with rigorous out-of-sample testing of prediction error and the validity of 95% UIs. For 13 causes with low observed numbers of deaths, we developed negative binomial models with plausible covariates. For 27 causes for which death is rare, we modelled the higher level cause in the cause hierarchy of the GBD 2010 and then allocated deaths across component causes proportionately, estimated from all available data in the database. For selected causes (African trypanosomiasis, congenital syphilis, whooping cough, measles, typhoid and parathyroid, leishmaniasis, acute hepatitis E, and HIV/AIDS), we used natural history models based on information on incidence, prevalence, and case-fatality. We separately estimated cause fractions by aetiology for diarrhoea, lower respiratory infections, and meningitis, as well as disaggregations by subcause for chronic kidney disease, maternal disorders, cirrhosis, and liver cancer. For deaths due to collective violence and natural disasters, we used mortality shock regressions. For every cause, we estimated 95% UIs that captured both parameter estimation uncertainty and uncertainty due to model specification where CODEm was used. We constrained cause-specific fractions within every age-sex group to sum to total mortality based on draws from the uncertainty distributions. Findings In 2010, there were 52·8 million deaths globally. At the most aggregate level, communicable, maternal, neonatal, and nutritional causes were 24·9% of deaths worldwide in 2010, down from 15·9 million (34·1%) of 46·5 million in 1990. This decrease was largely due to decreases in mortality from diarrhoeal disease (from 2·5 to 1·4 million), lower respiratory infections (from 3·4 to 2·8 million), neonatal disorders (from 3·1 to 2·2 million), measles (from 0·63 to 0·13 million), and tetanus (from 0·27 to 0·06 million). Deaths from HIV/AIDS increased from 0·30 million in 1990 to 1·5 million in 2010, reaching a peak of 1·7 million in 2006. Malaria mortality also rose by an estimated 19·9% since 1990 to 1·17 million deaths in 2010. Tuberculosis killed 1·2 million people in 2010. Deaths from non-communicable diseases rose by just under 8 million between 1990 and 2010, accounting for two of every three deaths (34·5 million) worldwide by 2010. 8 million people died from cancer in 2010, 38% more than two decades ago; of these, 1·5 million (19%) were from trachea, bronchus, and lung cancer. Ischaemic heart disease and stroke collectively killed 12·9 million people in 2010, or one in four deaths worldwide, compared with one in five in 1990; 1·3 million deaths were due to diabetes, twice as many as in 1990. The fraction of global deaths due to injuries (5·1 million deaths) was marginally higher in 2010 (9·6%) compared with two decades earlier (8·8%). This was driven by a 46% rise in deaths worldwide due to road traffic accidents (1·3 million in 2010) and a rise in deaths from falls. Ischaemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lower respiratory infections, lung cancer, and HIV/AIDS were the leading causes of death in 2010. Ischaemic heart disease, lower respiratory infections, stroke, diarrhoeal disease, malaria, and HIV/AIDS were the leading causes of years of life lost due to premature mortality (YLLs) in 2010, similar to what was estimated for 1990, except for HIV/AIDS and preterm birth complications. YLLs from lower respiratory infections and diarrhoea decreased by 45–54% since 1990; ischaemic heart disease and stroke YLLs increased by 17–28%. Regional variations in leading causes of death were substantial. Communicable, maternal, neonatal, and nutritional causes still accounted for 76% of premature mortality in sub-Saharan Africa in 2010. Age standardised death rates from some key disorders rose (HIV/AIDS, Alzheimer's disease, diabetes mellitus, and chronic kidney disease in particular), but for most diseases, death rates fell in the past two decades; including major vascular diseases, COPD, most forms of cancer, liver cirrhosis, and maternal disorders. For other conditions, notably malaria, prostate cancer, and injuries, little change was noted. Interpretation Population growth, increased average age of the world's population, and largely decreasing age-specific, sex-specific, and cause-specific death rates combine to drive a broad shift from communicable, maternal, neonatal, and nutritional causes towards non-communicable diseases. Nevertheless, communicable, maternal, neonatal, and nutritional causes remain the dominant causes of YLLs in sub-Saharan Africa. Overlaid on this general pattern of the epidemiological transition, marked regional variation exists in many causes, such as interpersonal violence, suicide, liver cancer, diabetes, cirrhosis, Chagas disease, African trypanosomiasis, melanoma, and others. Regional heterogeneity highlights the importance of sound epidemiological assessments of the causes of death on a regular basis. Funding Bill & Melinda Gates Foundation.

10,602 citations

Journal ArticleDOI
Marie Ng1, Tom P Fleming1, Margaret Robinson1, Blake Thomson1, Nicholas Graetz1, Christopher Margono1, Erin C Mullany1, Stan Biryukov1, Cristiana Abbafati2, Semaw Ferede Abera3, Jerry Abraham4, Niveen M E Abu-Rmeileh, Tom Achoki1, Fadia AlBuhairan5, Zewdie Aderaw Alemu6, Rafael Alfonso1, Mohammed K. Ali7, Raghib Ali8, Nelson Alvis Guzmán9, Walid Ammar, Palwasha Anwari10, Amitava Banerjee11, Simón Barquera, Sanjay Basu12, Derrick A Bennett8, Zulfiqar A Bhutta13, Jed D. Blore14, N Cabral, Ismael Ricardo Campos Nonato, Jung-Chen Chang15, Rajiv Chowdhury16, Karen J. Courville, Michael H. Criqui17, David K. Cundiff, Kaustubh Dabhadkar7, Lalit Dandona18, Lalit Dandona1, Adrian Davis19, Anand Dayama7, Samath D Dharmaratne20, Eric L. Ding21, Adnan M. Durrani22, Alireza Esteghamati23, Farshad Farzadfar23, Derek F J Fay19, Valery L. Feigin24, Abraham D. Flaxman1, Mohammad H. Forouzanfar1, Atsushi Goto, Mark A. Green25, Rajeev Gupta, Nima Hafezi-Nejad23, Graeme J. Hankey26, Heather Harewood, Rasmus Havmoeller27, Simon I. Hay8, Lucia Hernandez, Abdullatif Husseini28, Bulat Idrisov29, Nayu Ikeda, Farhad Islami30, Eiman Jahangir31, Simerjot K. Jassal17, Sun Ha Jee32, Mona Jeffreys33, Jost B. Jonas34, Edmond K. Kabagambe35, Shams Eldin Ali Hassan Khalifa, Andre Pascal Kengne36, Yousef Khader37, Young-Ho Khang38, Daniel Kim39, Ruth W Kimokoti40, Jonas Minet Kinge41, Yoshihiro Kokubo, Soewarta Kosen, Gene F. Kwan42, Taavi Lai, Mall Leinsalu22, Yichong Li, Xiaofeng Liang43, Shiwei Liu43, Giancarlo Logroscino44, Paulo A. Lotufo45, Yuan Qiang Lu21, Jixiang Ma43, Nana Kwaku Mainoo, George A. Mensah22, Tony R. Merriman46, Ali H. Mokdad1, Joanna Moschandreas47, Mohsen Naghavi1, Aliya Naheed48, Devina Nand, K.M. Venkat Narayan7, Erica Leigh Nelson1, Marian L. Neuhouser49, Muhammad Imran Nisar13, Takayoshi Ohkubo50, Samuel Oti, Andrea Pedroza, Dorairaj Prabhakaran, Nobhojit Roy51, Uchechukwu K.A. Sampson35, Hyeyoung Seo, Sadaf G. Sepanlou23, Kenji Shibuya52, Rahman Shiri53, Ivy Shiue54, Gitanjali M Singh21, Jasvinder A. Singh55, Vegard Skirbekk41, Nicolas J. C. Stapelberg56, Lela Sturua57, Bryan L. Sykes58, Martin Tobias1, Bach Xuan Tran59, Leonardo Trasande60, Hideaki Toyoshima, Steven van de Vijver, Tommi Vasankari, J. Lennert Veerman61, Gustavo Velasquez-Melendez62, Vasiliy Victorovich Vlassov63, Stein Emil Vollset64, Stein Emil Vollset41, Theo Vos1, Claire L. Wang65, Xiao Rong Wang66, Elisabete Weiderpass, Andrea Werdecker, Jonathan L. Wright1, Y Claire Yang67, Hiroshi Yatsuya68, Jihyun Yoon, Seok Jun Yoon69, Yong Zhao70, Maigeng Zhou, Shankuan Zhu71, Alan D. Lopez14, Christopher J L Murray1, Emmanuela Gakidou1 
University of Washington1, Sapienza University of Rome2, Mekelle University3, University of Texas at San Antonio4, King Saud bin Abdulaziz University for Health Sciences5, Debre markos University6, Emory University7, University of Oxford8, University of Cartagena9, United Nations Population Fund10, University of Birmingham11, Stanford University12, Aga Khan University13, University of Melbourne14, National Taiwan University15, University of Cambridge16, University of California, San Diego17, Public Health Foundation of India18, Public Health England19, University of Peradeniya20, Harvard University21, National Institutes of Health22, Tehran University of Medical Sciences23, Auckland University of Technology24, University of Sheffield25, University of Western Australia26, Karolinska Institutet27, Birzeit University28, Brandeis University29, American Cancer Society30, Ochsner Medical Center31, Yonsei University32, University of Bristol33, Heidelberg University34, Vanderbilt University35, South African Medical Research Council36, Jordan University of Science and Technology37, New Generation University College38, Northeastern University39, Simmons College40, Norwegian Institute of Public Health41, Boston University42, Chinese Center for Disease Control and Prevention43, University of Bari44, University of São Paulo45, University of Otago46, University of Crete47, International Centre for Diarrhoeal Disease Research, Bangladesh48, Fred Hutchinson Cancer Research Center49, Teikyo University50, Bhabha Atomic Research Centre51, University of Tokyo52, Finnish Institute of Occupational Health53, Heriot-Watt University54, University of Alabama at Birmingham55, Griffith University56, National Center for Disease Control and Public Health57, University of California, Irvine58, Johns Hopkins University59, New York University60, University of Queensland61, Universidade Federal de Minas Gerais62, National Research University – Higher School of Economics63, University of Bergen64, Columbia University65, Shandong University66, University of North Carolina at Chapel Hill67, Fujita Health University68, Korea University69, Chongqing Medical University70, Zhejiang University71
TL;DR: The global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013 is estimated using a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs).
Abstract: Summary Background In 2010, overweight and obesity were estimated to cause 3·4 million deaths, 3·9% of years of life lost, and 3·8% of disability-adjusted life-years (DALYs) worldwide. The rise in obesity has led to widespread calls for regular monitoring of changes in overweight and obesity prevalence in all populations. Comparable, up-to-date information about levels and trends is essential to quantify population health effects and to prompt decision makers to prioritise action. We estimate the global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013. Methods We systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports. We used mixed effects linear regression to correct for bias in self-reports. We obtained data for prevalence of obesity and overweight by age, sex, country, and year (n=19 244) with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs). Findings Worldwide, the proportion of adults with a body-mass index (BMI) of 25 kg/m 2 or greater increased between 1980 and 2013 from 28·8% (95% UI 28·4–29·3) to 36·9% (36·3–37·4) in men, and from 29·8% (29·3–30·2) to 38·0% (37·5–38·5) in women. Prevalence has increased substantially in children and adolescents in developed countries; 23·8% (22·9–24·7) of boys and 22·6% (21·7–23·6) of girls were overweight or obese in 2013. The prevalence of overweight and obesity has also increased in children and adolescents in developing countries, from 8·1% (7·7–8·6) to 12·9% (12·3–13·5) in 2013 for boys and from 8·4% (8·1–8·8) to 13·4% (13·0–13·9) in girls. In adults, estimated prevalence of obesity exceeded 50% in men in Tonga and in women in Kuwait, Kiribati, Federated States of Micronesia, Libya, Qatar, Tonga, and Samoa. Since 2006, the increase in adult obesity in developed countries has slowed down. Interpretation Because of the established health risks and substantial increases in prevalence, obesity has become a major global health challenge. Not only is obesity increasing, but no national success stories have been reported in the past 33 years. Urgent global action and leadership is needed to help countries to more effectively intervene. Funding Bill & Melinda Gates Foundation.

7,968 citations

Journal ArticleDOI
TL;DR: In this paper, a randomized clinical trial was conducted to evaluate the effect of preterax and Diamicron Modified Release Controlled Evaluation (MDE) on the risk of stroke.
Abstract: ABI : ankle–brachial index ACCORD : Action to Control Cardiovascular Risk in Diabetes ADVANCE : Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation AGREE : Appraisal of Guidelines Research and Evaluation AHA : American Heart Association apoA1 : apolipoprotein A1 apoB : apolipoprotein B CABG : coronary artery bypass graft surgery CARDS : Collaborative AtoRvastatin Diabetes Study CCNAP : Council on Cardiovascular Nursing and Allied Professions CHARISMA : Clopidogrel for High Athero-thrombotic Risk and Ischemic Stabilisation, Management, and Avoidance CHD : coronary heart disease CKD : chronic kidney disease COMMIT : Clopidogrel and Metoprolol in Myocardial Infarction Trial CRP : C-reactive protein CURE : Clopidogrel in Unstable Angina to Prevent Recurrent Events CVD : cardiovascular disease DALYs : disability-adjusted life years DBP : diastolic blood pressure DCCT : Diabetes Control and Complications Trial ED : erectile dysfunction eGFR : estimated glomerular filtration rate EHN : European Heart Network EPIC : European Prospective Investigation into Cancer and Nutrition EUROASPIRE : European Action on Secondary and Primary Prevention through Intervention to Reduce Events GFR : glomerular filtration rate GOSPEL : Global Secondary Prevention Strategies to Limit Event Recurrence After MI GRADE : Grading of Recommendations Assessment, Development and Evaluation HbA1c : glycated haemoglobin HDL : high-density lipoprotein HF-ACTION : Heart Failure and A Controlled Trial Investigating Outcomes of Exercise TraiNing HOT : Hypertension Optimal Treatment Study HPS : Heart Protection Study HR : hazard ratio hsCRP : high-sensitivity C-reactive protein HYVET : Hypertension in the Very Elderly Trial ICD : International Classification of Diseases IMT : intima-media thickness INVEST : International Verapamil SR/Trandolapril JTF : Joint Task Force LDL : low-density lipoprotein Lp(a) : lipoprotein(a) LpPLA2 : lipoprotein-associated phospholipase 2 LVH : left ventricular hypertrophy MATCH : Management of Atherothrombosis with Clopidogrel in High-risk Patients with Recent Transient Ischaemic Attack or Ischaemic Stroke MDRD : Modification of Diet in Renal Disease MET : metabolic equivalent MONICA : Multinational MONItoring of trends and determinants in CArdiovascular disease NICE : National Institute of Health and Clinical Excellence NRT : nicotine replacement therapy NSTEMI : non-ST elevation myocardial infarction ONTARGET : Ongoing Telmisartan Alone and in combination with Ramipril Global Endpoint Trial OSA : obstructive sleep apnoea PAD : peripheral artery disease PCI : percutaneous coronary intervention PROactive : Prospective Pioglitazone Clinical Trial in Macrovascular Events PWV : pulse wave velocity QOF : Quality and Outcomes Framework RCT : randomized clinical trial RR : relative risk SBP : systolic blood pressure SCORE : Systematic Coronary Risk Evaluation Project SEARCH : Study of the Effectiveness of Additional Reductions in Cholesterol and SHEP : Systolic Hypertension in the Elderly Program STEMI : ST-elevation myocardial infarction SU.FOL.OM3 : SUpplementation with FOlate, vitamin B6 and B12 and/or OMega-3 fatty acids Syst-Eur : Systolic Hypertension in Europe TNT : Treating to New Targets UKPDS : United Kingdom Prospective Diabetes Study VADT : Veterans Affairs Diabetes Trial VALUE : Valsartan Antihypertensive Long-term Use VITATOPS : VITAmins TO Prevent Stroke VLDL : very low-density lipoprotein WHO : World Health Organization ### 1.1 Introduction Atherosclerotic cardiovascular disease (CVD) is a chronic disorder developing insidiously throughout life and usually progressing to an advanced stage by the time symptoms occur. It remains the major cause of premature death in Europe, even though CVD mortality has …

6,913 citations

Journal ArticleDOI
TL;DR: WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Jiménez, ScD, SM Lori Chaffin Jordan,MD, PhD Suzanne E. Judd, PhD
Abstract: WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Blaha, MD, MPH Stephanie E. Chiuve, ScD Mary Cushman, MD, MSc, FAHA Sandeep R. Das, MD, MPH, FAHA Rajat Deo, MD, MTR Sarah D. de Ferranti, MD, MPH James Floyd, MD, MS Myriam Fornage, PhD, FAHA Cathleen Gillespie, MS Carmen R. Isasi, MD, PhD, FAHA Monik C. Jiménez, ScD, SM Lori Chaffin Jordan, MD, PhD Suzanne E. Judd, PhD Daniel Lackland, DrPH, FAHA Judith H. Lichtman, PhD, MPH, FAHA Lynda Lisabeth, PhD, MPH, FAHA Simin Liu, MD, ScD, FAHA Chris T. Longenecker, MD Rachel H. Mackey, PhD, MPH, FAHA Kunihiro Matsushita, MD, PhD, FAHA Dariush Mozaffarian, MD, DrPH, FAHA Michael E. Mussolino, PhD, FAHA Khurram Nasir, MD, MPH, FAHA Robert W. Neumar, MD, PhD, FAHA Latha Palaniappan, MD, MS, FAHA Dilip K. Pandey, MBBS, MS, PhD, FAHA Ravi R. Thiagarajan, MD, MPH Mathew J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Rodriguez, MD, MPH, FAHA Gregory A. Roth, MD, MPH Wayne D. Rosamond, PhD, FAHA Comilla Sasson, MD, PhD, FAHA Amytis Towfighi, MD Connie W. Tsao, MD, MPH Melanie B. Turner, MPH Salim S. Virani, MD, PhD, FAHA Jenifer H. Voeks, PhD Joshua Z. Willey, MD, MS John T. Wilkins, MD Jason HY. Wu, MSc, PhD, FAHA Heather M. Alger, PhD Sally S. Wong, PhD, RD, CDN, FAHA Paul Muntner, PhD, MHSc On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart Disease and Stroke Statistics—2017 Update

6,097 citations

Journal ArticleDOI
TL;DR: Author(s): Writing Group Members; Mozaffarian, Dariush; Benjamin, Emelia J; Go, Alan S; Arnett, Donna K; Blaha, Michael J; Cushman, Mary; Das, Sandeep R; de Ferranti, Sarah; Despres, Jean-Pierre; Fullerton, Heather J; Howard, Virginia J; Huffman, Mark D; Isasi, Carmen R; Jimenez, Monik C; Judd, Suzanne
Abstract: Author(s): Writing Group Members; Mozaffarian, Dariush; Benjamin, Emelia J; Go, Alan S; Arnett, Donna K; Blaha, Michael J; Cushman, Mary; Das, Sandeep R; de Ferranti, Sarah; Despres, Jean-Pierre; Fullerton, Heather J; Howard, Virginia J; Huffman, Mark D; Isasi, Carmen R; Jimenez, Monik C; Judd, Suzanne E; Kissela, Brett M; Lichtman, Judith H; Lisabeth, Lynda D; Liu, Simin; Mackey, Rachel H; Magid, David J; McGuire, Darren K; Mohler, Emile R; Moy, Claudia S; Muntner, Paul; Mussolino, Michael E; Nasir, Khurram; Neumar, Robert W; Nichol, Graham; Palaniappan, Latha; Pandey, Dilip K; Reeves, Mathew J; Rodriguez, Carlos J; Rosamond, Wayne; Sorlie, Paul D; Stein, Joel; Towfighi, Amytis; Turan, Tanya N; Virani, Salim S; Woo, Daniel; Yeh, Robert W; Turner, Melanie B; American Heart Association Statistics Committee; Stroke Statistics Subcommittee

5,552 citations


References
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Journal ArticleDOI
TL;DR: In this paper, the authors compared a lifestyle intervention with metformin to prevent or delay the development of Type 2 diabetes in nondiabetic individuals. And they found that the lifestyle intervention was significantly more effective than the medication.
Abstract: Background Type 2 diabetes affects approximately 8 percent of adults in the United States. Some risk factors — elevated plasma glucose concentrations in the fasting state and after an oral glucose load, overweight, and a sedentary lifestyle — are potentially reversible. We hypothesized that modifying these factors with a lifestyle-intervention program or the administration of metformin would prevent or delay the development of diabetes. Methods We randomly assigned 3234 nondiabetic persons with elevated fasting and post-load plasma glucose concentrations to placebo, metformin (850 mg twice daily), or a lifestyle modification program with the goals of at least a 7 percent weight loss and at least 150 minutes of physical activity per week. The mean age of the participants was 51 years, and the mean body-mass index (the weight in kilograms divided by the square of the height in meters) was 34.0; 68 percent were women, and 45 percent were members of minority groups. Results The average follow-up was 2.8 years. The incidence of diabetes was 11.0, 7.8, and 4.8 cases per 100 person-years in the placebo, metformin, and lifestyle groups, respectively. The lifestyle intervention reduced the incidence by 58 percent (95 percent confidence interval, 48 to 66 percent) and metformin by 31 percent (95 percent confidence interval, 17 to 43 percent), as compared with placebo; the lifestyle intervention was significantly more effective than metformin. To prevent one case of diabetes during a period of three years, 6.9 persons would have to participate in the lifestyle-intervention program, and 13.9 would have to receive metformin. Conclusions Lifestyle changes and treatment with metformin both reduced the incidence of diabetes in persons at high risk. The lifestyle intervention was more effective than metformin.

16,279 citations

Journal ArticleDOI
Rafael Lozano1, Mohsen Naghavi1, Kyle J Foreman2, Stephen S Lim1  +192 moreInstitutions (95)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2010 aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex, using the Cause of Death Ensemble model.
Abstract: Summary Background Reliable and timely information on the leading causes of death in populations, and how these are changing, is a crucial input into health policy debates. In the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010), we aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex. Methods We attempted to identify all available data on causes of death for 187 countries from 1980 to 2010 from vital registration, verbal autopsy, mortality surveillance, censuses, surveys, hospitals, police records, and mortuaries. We assessed data quality for completeness, diagnostic accuracy, missing data, stochastic variations, and probable causes of death. We applied six different modelling strategies to estimate cause-specific mortality trends depending on the strength of the data. For 133 causes and three special aggregates we used the Cause of Death Ensemble model (CODEm) approach, which uses four families of statistical models testing a large set of different models using different permutations of covariates. Model ensembles were developed from these component models. We assessed model performance with rigorous out-of-sample testing of prediction error and the validity of 95% UIs. For 13 causes with low observed numbers of deaths, we developed negative binomial models with plausible covariates. For 27 causes for which death is rare, we modelled the higher level cause in the cause hierarchy of the GBD 2010 and then allocated deaths across component causes proportionately, estimated from all available data in the database. For selected causes (African trypanosomiasis, congenital syphilis, whooping cough, measles, typhoid and parathyroid, leishmaniasis, acute hepatitis E, and HIV/AIDS), we used natural history models based on information on incidence, prevalence, and case-fatality. We separately estimated cause fractions by aetiology for diarrhoea, lower respiratory infections, and meningitis, as well as disaggregations by subcause for chronic kidney disease, maternal disorders, cirrhosis, and liver cancer. For deaths due to collective violence and natural disasters, we used mortality shock regressions. For every cause, we estimated 95% UIs that captured both parameter estimation uncertainty and uncertainty due to model specification where CODEm was used. We constrained cause-specific fractions within every age-sex group to sum to total mortality based on draws from the uncertainty distributions. Findings In 2010, there were 52·8 million deaths globally. At the most aggregate level, communicable, maternal, neonatal, and nutritional causes were 24·9% of deaths worldwide in 2010, down from 15·9 million (34·1%) of 46·5 million in 1990. This decrease was largely due to decreases in mortality from diarrhoeal disease (from 2·5 to 1·4 million), lower respiratory infections (from 3·4 to 2·8 million), neonatal disorders (from 3·1 to 2·2 million), measles (from 0·63 to 0·13 million), and tetanus (from 0·27 to 0·06 million). Deaths from HIV/AIDS increased from 0·30 million in 1990 to 1·5 million in 2010, reaching a peak of 1·7 million in 2006. Malaria mortality also rose by an estimated 19·9% since 1990 to 1·17 million deaths in 2010. Tuberculosis killed 1·2 million people in 2010. Deaths from non-communicable diseases rose by just under 8 million between 1990 and 2010, accounting for two of every three deaths (34·5 million) worldwide by 2010. 8 million people died from cancer in 2010, 38% more than two decades ago; of these, 1·5 million (19%) were from trachea, bronchus, and lung cancer. Ischaemic heart disease and stroke collectively killed 12·9 million people in 2010, or one in four deaths worldwide, compared with one in five in 1990; 1·3 million deaths were due to diabetes, twice as many as in 1990. The fraction of global deaths due to injuries (5·1 million deaths) was marginally higher in 2010 (9·6%) compared with two decades earlier (8·8%). This was driven by a 46% rise in deaths worldwide due to road traffic accidents (1·3 million in 2010) and a rise in deaths from falls. Ischaemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lower respiratory infections, lung cancer, and HIV/AIDS were the leading causes of death in 2010. Ischaemic heart disease, lower respiratory infections, stroke, diarrhoeal disease, malaria, and HIV/AIDS were the leading causes of years of life lost due to premature mortality (YLLs) in 2010, similar to what was estimated for 1990, except for HIV/AIDS and preterm birth complications. YLLs from lower respiratory infections and diarrhoea decreased by 45–54% since 1990; ischaemic heart disease and stroke YLLs increased by 17–28%. Regional variations in leading causes of death were substantial. Communicable, maternal, neonatal, and nutritional causes still accounted for 76% of premature mortality in sub-Saharan Africa in 2010. Age standardised death rates from some key disorders rose (HIV/AIDS, Alzheimer's disease, diabetes mellitus, and chronic kidney disease in particular), but for most diseases, death rates fell in the past two decades; including major vascular diseases, COPD, most forms of cancer, liver cirrhosis, and maternal disorders. For other conditions, notably malaria, prostate cancer, and injuries, little change was noted. Interpretation Population growth, increased average age of the world's population, and largely decreasing age-specific, sex-specific, and cause-specific death rates combine to drive a broad shift from communicable, maternal, neonatal, and nutritional causes towards non-communicable diseases. Nevertheless, communicable, maternal, neonatal, and nutritional causes remain the dominant causes of YLLs in sub-Saharan Africa. Overlaid on this general pattern of the epidemiological transition, marked regional variation exists in many causes, such as interpersonal violence, suicide, liver cancer, diabetes, cirrhosis, Chagas disease, African trypanosomiasis, melanoma, and others. Regional heterogeneity highlights the importance of sound epidemiological assessments of the causes of death on a regular basis. Funding Bill & Melinda Gates Foundation.

10,602 citations

Journal ArticleDOI
TL;DR: Throughout middle and old age, usual blood pressure is strongly and directly related to vascular (and overall) mortality, without any evidence of a threshold down to at least 115/75 mm Hg.
Abstract: BACKGROUND: The age-specific relevance of blood pressure to cause-specific mortality is best assessed by collaborative meta-analysis of individual participant data from the separate prospective studies. METHODS: Information was obtained on each of one million adults with no previous vascular disease recorded at baseline in 61 prospective observational studies of blood pressure and mortality. During 12.7 million person-years at risk, there were about 56000 vascular deaths (12000 stroke, 34000 ischaemic heart disease [IHD], 10000 other vascular) and 66000 other deaths at ages 40-89 years. Meta-analyses, involving "time-dependent" correction for regression dilution, related mortality during each decade of age at death to the estimated usual blood pressure at the start of that decade. FINDINGS: Within each decade of age at death, the proportional difference in the risk of vascular death associated with a given absolute difference in usual blood pressure is about the same down to at least 115 mm Hg usual systolic blood pressure (SBP) and 75 mm Hg usual diastolic blood pressure (DBP), below which there is little evidence. At ages 40-69 years, each difference of 20 mm Hg usual SBP (or, approximately equivalently, 10 mm Hg usual DBP) is associated with more than a twofold difference in the stroke death rate, and with twofold differences in the death rates from IHD and from other vascular causes. All of these proportional differences in vascular mortality are about half as extreme at ages 80-89 years as at ages 40-49 years, but the annual absolute differences in risk are greater in old age. The age-specific associations are similar for men and women, and for cerebral haemorrhage and cerebral ischaemia. For predicting vascular mortality from a single blood pressure measurement, the average of SBP and DBP is slightly more informative than either alone, and pulse pressure is much less informative. INTERPRETATION: Throughout middle and old age, usual blood pressure is strongly and directly related to vascular (and overall) mortality, without any evidence of a threshold down to at least 115/75 mm Hg.

8,409 citations

Book
01 Jan 1996
TL;DR: This is the first in a planned series of 10 volumes that will attempt to "summarize epidemiological knowledge about all major conditions and most risk factors" and use historical trends in main determinants to project mortality and disease burden forward to 2020.
Abstract: This is the first in a planned series of 10 volumes that will attempt to "summarize epidemiological knowledge about all major conditions and most risk factors;...generate assessments of numbers of deaths by cause that are consistent with the total numbers of deaths by age sex and region provided by demographers;...provide methodologies for and assessments of aggregate disease burden that combine--into the Disability-Adjusted Life Year or DALY measure--burden from premature mortality with that from living with disability; and...use historical trends in main determinants to project mortality and disease burden forward to 2020." This first volume includes chapters summarizing results from the project as a whole. (EXCERPT)

7,084 citations

Journal ArticleDOI
Christopher J L Murray1, Theo Vos2, Rafael Lozano1, Mohsen Naghavi1  +366 moreInstitutions (141)
TL;DR: The results for 1990 and 2010 supersede all previously published Global Burden of Disease results and highlight the importance of understanding local burden of disease and setting goals and targets for the post-2015 agenda taking such patterns into account.
Abstract: Summary Background Measuring disease and injury burden in populations requires a composite metric that captures both premature mortality and the prevalence and severity of ill-health. The 1990 Global Burden of Disease study proposed disability-adjusted life years (DALYs) to measure disease burden. No comprehensive update of disease burden worldwide incorporating a systematic reassessment of disease and injury-specific epidemiology has been done since the 1990 study. We aimed to calculate disease burden worldwide and for 21 regions for 1990, 2005, and 2010 with methods to enable meaningful comparisons over time. Methods We calculated DALYs as the sum of years of life lost (YLLs) and years lived with disability (YLDs). DALYs were calculated for 291 causes, 20 age groups, both sexes, and for 187 countries, and aggregated to regional and global estimates of disease burden for three points in time with strictly comparable definitions and methods. YLLs were calculated from age-sex-country-time-specific estimates of mortality by cause, with death by standardised lost life expectancy at each age. YLDs were calculated as prevalence of 1160 disabling sequelae, by age, sex, and cause, and weighted by new disability weights for each health state. Neither YLLs nor YLDs were age-weighted or discounted. Uncertainty around cause-specific DALYs was calculated incorporating uncertainty in levels of all-cause mortality, cause-specific mortality, prevalence, and disability weights. Findings Global DALYs remained stable from 1990 (2·503 billion) to 2010 (2·490 billion). Crude DALYs per 1000 decreased by 23% (472 per 1000 to 361 per 1000). An important shift has occurred in DALY composition with the contribution of deaths and disability among children (younger than 5 years of age) declining from 41% of global DALYs in 1990 to 25% in 2010. YLLs typically account for about half of disease burden in more developed regions (high-income Asia Pacific, western Europe, high-income North America, and Australasia), rising to over 80% of DALYs in sub-Saharan Africa. In 1990, 47% of DALYs worldwide were from communicable, maternal, neonatal, and nutritional disorders, 43% from non-communicable diseases, and 10% from injuries. By 2010, this had shifted to 35%, 54%, and 11%, respectively. Ischaemic heart disease was the leading cause of DALYs worldwide in 2010 (up from fourth rank in 1990, increasing by 29%), followed by lower respiratory infections (top rank in 1990; 44% decline in DALYs), stroke (fifth in 1990; 19% increase), diarrhoeal diseases (second in 1990; 51% decrease), and HIV/AIDS (33rd in 1990; 351% increase). Major depressive disorder increased from 15th to 11th rank (37% increase) and road injury from 12th to 10th rank (34% increase). Substantial heterogeneity exists in rankings of leading causes of disease burden among regions. Interpretation Global disease burden has continued to shift away from communicable to non-communicable diseases and from premature death to years lived with disability. In sub-Saharan Africa, however, many communicable, maternal, neonatal, and nutritional disorders remain the dominant causes of disease burden. The rising burden from mental and behavioural disorders, musculoskeletal disorders, and diabetes will impose new challenges on health systems. Regional heterogeneity highlights the importance of understanding local burden of disease and setting goals and targets for the post-2015 agenda taking such patterns into account. Because of improved definitions, methods, and data, these results for 1990 and 2010 supersede all previously published Global Burden of Disease results. Funding Bill & Melinda Gates Foundation.

6,252 citations


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Frequently Asked Questions (4)
Q1. What are the contributions mentioned in the paper "A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990—2010: a systematic analysis for the global burden of disease study 2010 author" ?

Lim, Stephen S, Vos, Umer, Shibuya, Shibaya, Kenji, AdairRohani, Heather, Amann, Markus, Anderson, H Ross, Andrews, Kathryn G, Aryee, Martin, Gmel, Gerhard, Graham, Kathryn, Grainger, Rebecca, Grant, Bridget, Gunnell, David, Gutierrez, Hialy R, Hall, Wayne, Hoek, Hans W, Hogan, Anne-Charlson, H Dean, this paper, Nolla, Nissim, Nelson, Paul K 

Shortcomings in the evidence may be any of the following: insufficient duration of trials (or studies); insufficient trials (or studies) available; inadequate sample sizes; or incomplete follow-up. 

The available evidence is based on a substantial number of studies including prospective observational studies and where relevant, randomised controlled trials of sufficient size, duration, and quality showing consistent effects. 

In reality, the burden attributable to different risks overlaps because of multicausality and because the effects of some risk factors are partly mediated throughLim et al.