Global, regional, and national comparative risk assessment of 84 behavioral, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the GBD Study 2017
Published November 8, 2018, in The Lancet (opens in a new window)
Abstract
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 synthesizing 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 behavioral, 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 randomized 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 modeling 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 behavioral 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.
Findings
In 2017, 34.1 million (95% uncertainty interval [UI] 33.3–35.0) deaths and 1.21 billion (1.14–1.28) DALYs were attributable to GBD risk factors. Globally, 61.0% (59.6–62.4) of deaths and 48.3% (46.3–50.2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10.4 million (9.39–11.5) deaths and 218 million (198–237) DALYs, followed by smoking (7.10 million [6.83–7.37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6.53 million [5.23–8.23] deaths and 171 million [144–201] DALYs), high body mass index (BMI; 4.72 million [2.99–6.70] deaths and 148 million [98.6–202] DALYs), and short gestation for birthweight (1.43 million [1.36–1.51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4.9% (3.3–6.5) between 2007 and 2017. In the absence of demographic changes (i.e., population growth and aging), changes in risk exposure and risk-deleted DALYs would have led to a 23.5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18.6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardized DALY rates was high SBP in four super-regions: Central Europe, Eastern Europe, and Central Asia; North Africa and Middle East; South Asia; and Southeast Asia, East Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in North Africa and the Middle East were notably low.
Interpretation
By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and program efforts might have been successful and highlights current priorities for public health action. Decreases in behavioral, environmental, and occupational risks have largely offset the effects of population growth and aging, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population aging will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision-making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesizing data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning.
Citation
GBD 2017 Risk Factor Collaborators. 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. The Lancet. 8 Nov 2018;392:1923-94. doi: http://dx.doi.org/10.1016/S0140-6736(18)32225-6.
Authors
- Jeff Stanaway,
- Christopher J.L. Murray,
- Ashkan Afshin,
- Emmanuela Gakidou,
- Stephen Lim,
- Tahiya Alam,
- Komal Ali,
- Jason Anderson,
- Brigette Blacker,
- Michael Brauer,
- Kate Causey,
- Kelly Cercy,
- Adrienne Chew,
- Aaron Cohen,
- Leslie Cornaby,
- Elizabeth Cromwell,
- Lalit Dandona,
- Rakhi Dandona,
- Louisa Degenhardt,
- Selina Deiparine,
- Ani Deshpande,
- Samath D. Dharmaratne,
- Charbel El Bcheraoui,
- Kara Estep,
- Kairsten Fay,
- Valery Feigin,
- Giannina Ferrara,
- Kyle Foreman,
- Nancy Fullman,
- William Gardner,
- Caitlin Hawley,
- Simon Hay,
- Thomas Hsiao,
- Chantal Huynh,
- Caleb Irvine,
- Spencer James,
- Nicholas Kassebaum,
- Grant Kemp,
- Ibrahim Khalil,
- Kris Krohn,
- Hmwe Hmwe Kyu,
- Sam Larson,
- Rafael Lozano,
- Helena Manguerra,
- Ashley Marks,
- Anoushka Millear,
- Molly Miller-Petrie,
- Awoke Misganaw Temesgen,
- Ali Mokdad,
- Kate Muller,
- Mohsen Naghavi,
- Grant Nguyen,
- Minh Nguyen,
- Emma Nichols,
- Molly Nixon,
- Elaine Nsoesie,
- Chris Odell,
- Helen Olsen,
- Liane Ong,
- Katherine Paulson,
- Caroline Purcell,
- Bobby Reiner,
- Marissa Reitsma,
- Yesenia Roman,
- Gregory Roth,
- David Smith,
- Mari Smith,
- Reed Sorensen,
- Vinay Srinivasan,
- Michelle Subart,
- Patrick Sur,
- Andrew Theis,
- Anna Torre,
- Hayley Tymeson,
- Rachel Updike,
- Stein Emil Vollset,
- Theo Vos,
- Harvey Whiteford,
- Simon Yadgir,
- Steph Zimsen
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.