| Title: |
Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019 |
| Authors: |
Abbafati, C; Abbas, KM; Abbasi-Kangevari, M; Abd-Allah, F; Abdelalim, A; Abdollahi, M; Abdollahpour, I; Abegaz, KH; Abolhassani, H; Aboyans, V; Abreu, LG; Abrigo, MRM; Abualhasan, A; Abu-Raddad, LJ; Abushouk, AI; Adabi, M; Adekanmbi, V; Adeoye, AM; Adetokunboh, OO; Adham, D; Advani, SM; Afshin, A; Agarwal, G; Aghamir, SMK; Agrawal, A; Ahmad, T; Ahmadi, K; Ahmadi, M; Ahmadieh, H; Ahmed, MB; Akalu, TY; Akinyemi, RO; Akinyemiju, T; Akombi, B; Akunna, CJ; Alahdab, F; Al-Aly, Z; Alam, K; Alam, S; Alam, T; Alanezi, FM; Alanzi, TM; Alemu, BW; Alhabib, KF; Ali, M; Ali, S; Alicandro, G; Alinia, C; Alipour, V; Alizade, H; Aljunid, SM; Alla, F; Allebeck, P; Almasi-Hashiani, A; Al-Mekhlafi, HM; Alonso, J; Altirkawi, KA; Amini-Rarani, M; Amiri, F; Amugsi, DA; Ancuceanu, R; Anderlini, D; Anderson, JA; Andrei, CL; Andrei, T; Angus, C; Anjomshoa, M; Ansari, F; Ansari-Moghaddam, A; Antonazzo, IC; Antonio, CAT; Antony, CM; Antriyandarti, E; Anvari, D; Anwer, R; Appiah, SCY; Arabloo, J; Arab-Zozani, M; Aravkin, AY; Ariani, F; Armoon, B; Ärnlöv, J; Arzani, A; Asadi-Aliabadi, M; Asadi-Pooya, AA; Ashbaugh, C; Assmus, M; Atafar, Z; Atnafu, DD; Atout, MMDW; Ausloos, F; Ausloos, M; Ayala Quintanilla, BP; Ayano, G; Ayanore, MA; Azari, S; Azarian, G; Azene, ZN; Badawi, A; Badiye, AD; Sachdev, Perminder; Degenhardt, Louisa; Pesudovs, Konrad; Jha, Vivekanand; Resnikoff, Serge; Ivers, Rebecca; Maulik, Pallab Kumar; Biswas, Raaj Kishore; Schutte, Alta; Leung, Janni; Peden, Amy; Boufous, Soufiane; Mitchell, Philip; John, Oommen; Godinho, Myron; Iqbal, Usman; Ferreira, Manuela; Berhe, Kidanemaryam; Saddik, Basema |
| Source: |
urn:ISSN:0140-6736 ; urn:ISSN:1474-547X ; Lancet, 396, 10258, 1223-1249 |
| Publisher Information: |
Elsevier |
| Publication Year: |
2020 |
| Collection: |
UNSW Sydney (The University of New South Wales): UNSWorks |
| Subject Terms: |
4202 Epidemiology; 32 Biomedical and Clinical Sciences; 42 Health Sciences; Burden of Illness; Prevention; Behavioral and Social Science; Social Determinants of Health; Health Disparities and Racial or Ethnic Minority Health Research; Basic Behavioral and Social Science; Pediatric Research Initiative; Health Disparities; Nutrition; Generic health relevance; 3 Good Health and Well Being; Body Mass Index; Environmental Exposure; Female; Global Burden of Disease; Global Health; Health Risk Behaviors; Humans; Hyperglycemia; Hypertension; Life Expectancy; Male; Malnutrition; Mortality; Risk Factors; Socioeconomic Factors; Substance-Related Disorders |
| Description: |
Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and ... |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
https://hdl.handle.net/1959.4/unsworks_79499 |
| DOI: |
10.1016/S0140-6736(20)30752-2 |
| Availability: |
https://hdl.handle.net/1959.4/unsworks_79499; https://unsworks.unsw.edu.au/bitstreams/5bb01e84-d1a1-4bf9-9e0d-486ffa6d3081/download; https://doi.org/10.1016/S0140-6736(20)30752-2 |
| Rights: |
open access ; https://purl.org/coar/access_right/c_abf2 ; CC BY ; https://creativecommons.org/licenses/by/4.0/ ; free_to_read |
| Accession Number: |
edsbas.A6B757B7 |
| Database: |
BASE |