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Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017: A systematic analysis for the Global Burden of Disease Study 2017

  • Jeffrey D. Stanaway
  • , Ashkan Afshin
  • , Emmanuela Gakidou
  • , Stephen S. Lim
  • , Degu Abate
  • , Kalkidan Hassen Abate
  • , Cristiana Abbafati
  • , Nooshin Abbasi
  • , Hedayat Abbastabar
  • , Foad Abd-Allah
  • , Jemal Abdela
  • , Ahmed Abdelalim
  • , Ibrahim Abdollahpour
  • , Rizwan Suliankatchi Abdulkader
  • , Molla Abebe
  • , Zegeye Abebe
  • , Semaw F. Abera
  • , Olifan Zewdie Abil
  • , Haftom Niguse Abraha
  • , Aklilu Roba Abrham
  • Laith Jamal Abu-Raddad, Niveen M.E. Abu-Rmeileh, Manfred Mario Kokou Accrombessi, Dilaram Acharya, Pawan Acharya, Abdu A. Adamu, Akilew Awoke Adane, Oladimeji M. Adebayo, Rufus Adesoji Adedoyin, Victor Adekanmbi, Zanfina Ademi, Olatunji O. Adetokunboh, Mina G. Adib, Amha Admasie, Jose C. Adsuar, Kossivi Agbelenko Afanvi, Mohsen Afarideh, Gina Agarwal, Anju Aggarwal, Sargis Aghasi Aghayan, Anurag Agrawal, Sutapa Agrawal, Alireza Ahmadi, Mehdi Ahmadi, Hamid Ahmadieh, Muktar Beshir Ahmed, Amani Nidhal Aichour, Ibtihel Aichour, Miloud Taki Eddine Aichour, Ibrahim Bou Orm
  • University of Washington
  • Haramaya University
  • Jimma University
  • Non-Communicable Diseases Research Center
  • Tehran University of Medical Sciences
  • McGill University
  • School of Pharmacy
  • Cairo University
  • Manonmaniam Sundaranar University
  • Human Nutrition Department
  • Gondar University
  • University of Hohenheim
  • Wollega University
  • Clinical Pharmacy Unit
  • Weill Cornell Medicine-Qatar
  • Birzeit University
  • Depártment of Epidemiology
  • Bénin Clinical Research Institute (IRCB)
  • Dongguk University
  • Kathmandu University
  • Nepal Development Society
  • Duke University
  • Stellenbosch University
  • Institute Public of Health
  • Sant'Orsola Malpighi Hospital
  • University College Hospital, Ibadan
  • Obafemi Awolowo University
  • Cardiff University
  • School of Public Health and Preventive Medicine
  • Monash University
  • Sechenov First Moscow State Medical University
  • Wolaita Sodo University
  • Université de Lomé
  • Health of the Zio
  • Endocrinology and Metabolism Research Center
  • McMaster University
  • Scientific Center of Zoology and Hydroecology
  • CSIR - Institute of Genomics and Integrative Biology
  • Baylor College of Medicine
  • Non Communicable Diseases
  • Public Health Foundation of India
  • Vital Strategies
  • Environmental Technologies Research Center
  • Ahvaz Jundishapur University of Medical Sciences
  • Ophthalmic Research Center
  • Wuhan University
  • Shahid Beheshti University of Medical Sciences
  • Higher National Veterinary School
  • Ministry of Public Health Lebanon

Research output: Contribution to journalArticlepeer-review

4233 Citations (Scopus)

Abstract

Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk-outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk-outcome pairs, and new data on risk exposure levels and risk- outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017.
Original languageEnglish
Pages (from-to)1923-1994
Number of pages72
JournalThe Lancet
Volume392
Issue number10159
DOIs
Publication statusPublished - 10 Nov 2018
Externally publishedYes

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