Global, regional, and national comparative risk assessment of 84 behavioral, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016
Published September 14, 2017, in The Lancet (opens in a new window)
Abstract
The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of risk factor exposure and attributable burden of disease. By providing estimates over a long time series, this study can monitor risk exposure trends critical to health surveillance and inform policy debates on the importance of addressing risks in context.
Methods
We used the comparative risk assessment 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 behavioral, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2016. This study included 481 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk (RR) and exposure estimates from 22,717 randomized controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources, according to the GBD 2016 source counting methods. 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. Finally, we explored four drivers of trends in attributable burden: population growth, population aging, trends in risk exposure, and all other factors combined.
Findings
Since 1990, exposure increased significantly for 30 risks, did not change significantly for four risks, and decreased significantly for 31 risks. Among risks that are leading causes of burden of disease, child growth failure and household air pollution showed the most significant declines, while metabolic risks, such as body mass index and high fasting plasma glucose, showed significant increases. In 2016, at Level 3 of the hierarchy, the three leading risk factors in terms of attributable DALYs at the global level for men were smoking (124.1 million DALYs [95% UI 111.2 million to 137.0 million]), high systolic blood pressure (122.2 million DALYs [110.3 million to 133.3 million], and low birthweight and short gestation (83.0 million DALYs [78.3 million to 87.7 million]), and for women, were high systolic blood pressure (89.9 million DALYs [80.9 million to 98.2 million]), high body mass index (64.8 million DALYs [44.4 million to 87.6 million]), and high fasting plasma glucose (63.8 million DALYs [53.2 million to 76.3 million]). In 2016 in 113 countries, the leading risk factor in terms of attributable DALYs was a metabolic risk factor. Smoking remained among the leading five risk factors for DALYs for 109 countries, while low birthweight and short gestation was the leading risk factor for DALYs in 38 countries, particularly in sub-Saharan Africa and South Asia. In terms of important drivers of change in trends of burden attributable to risk factors, between 2006 and 2016 exposure to risks explains a 9.3% (6.9–11.6) decline in deaths and a 10.8% (8.3–13.1) decrease in DALYs at the global level, while population aging accounts for 14.9% (12.7–17.5) of deaths and 6.2% (3.9–8.7) of DALYs, and population growth for 12.4% (10.1–14.9) of deaths and 12.4% (10.1–14.9) of DALYs. The largest contribution of trends in risk exposure to disease burden is seen between ages 1 year and 4 years, where a decline of 27.3% (24.9–29.7) of the change in DALYs between 2006 and 2016 can be attributed to declines in exposure to risks.
Interpretation
Increasingly detailed understanding of the trends in risk exposure and the RRs for each risk-outcome pair provide insights into both the magnitude of health loss attributable to risks and how modification of risk exposure has contributed to health trends. Metabolic risks warrant particular policy attention, due to their large contribution to global disease burden, increasing trends, and variable patterns across countries at the same level of development. GBD 2016 findings show that, while it has huge potential to improve health, risk modification has played a relatively small part in the past decade.
Citation
GBD 2016 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet. 14 Sept 2017: 390;1345-1422.
Authors
- Emmanuela Gakidou,
- Christopher J.L. Murray,
- Ashkan Afshin,
- Tahiya Alam,
- Komal Ali,
- Nicholas Arian,
- Ryan Barber,
- James Bennet,
- Stan Biryukov,
- Michael Brauer,
- Blair Bumgarner,
- Kelly Cercy,
- Fiona Charlson,
- Aaron Cohen,
- Haley Comfort,
- Leslie Cornaby,
- Lalit Dandona,
- Rakhi Dandona,
- Louisa Degenhardt,
- Ani Deshpande,
- Samath D. Dharmaratne,
- Holly Erskine,
- Kara Estep,
- Kairsten Fay,
- Valery Feigin,
- Alize Ferrari,
- Christina Fitzmaurice,
- Abraham Flaxman,
- Kyle Foreman,
- Joseph Frostad,
- Nancy Fullman,
- Will Godwin,
- Nick Graetz,
- Jingwen Guo,
- Caitlin Hawley,
- Simon Hay,
- Chad Ikeda,
- Caleb Irvine,
- Catherine Johnson,
- Nicholas Kassebaum,
- Ibrahim Khalil,
- Jun Kim,
- Kris Krohn,
- Michael Kutz,
- Hmwe Hmwe Kyu,
- Alexander Lee,
- Janni Leung,
- Xiaofeng Liang,
- Patrick Liu,
- Rafael Lozano,
- Helena Manguerra,
- Anoushka Millear,
- Shawn Minnig,
- Awoke Misganaw Temesgen,
- Ali Mokdad,
- Maziar Moradi-Lakeh,
- Cliff Mountjoy-Venning,
- Kate Muller,
- Mohsen Naghavi,
- Grant Nguyen,
- Stephen Lim,
- Minh Nguyen,
- Emma Nichols,
- Helen Olsen,
- Martin Pletcher,
- Farshad Pourmalek,
- Caroline Purcell,
- Bobby Reiner,
- Marissa Reitsma,
- Yesenia Roman,
- Gregory Roth,
- Nafis Sadat,
- Joseph Salama,
- Joshua Salomon,
- Damian Santomauro,
- Chloe Shields,
- Erica Leigh Slepak,
- David Smith,
- Mari Smith,
- Reed Sorensen,
- Caitlyn Steiner,
- Bryan Strub,
- Michelle Subart,
- Patrick Sur,
- Ornwipa Thamsuwan,
- Andrew Theis,
- Anna Torre,
- Rachel Updike,
- Stein Emil Vollset,
- Theo Vos,
- Harvey Whiteford,
- Rachel Woodbrook,
- Sarah Wulf Hanson,
- Steph Zimsen,
- Benjamin Zipkin,
- Simon Yadgir,
- Erin Mullany
Datasets
All our datasets are housed in our data catalog, the Global Health Data Exchange (GHDx). Visit the GHDx to download data from this article.