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. MethodsGBD 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 agesex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobac...

Estimates of ground-level ozone concentrations are necessary to determine the human health burden of ozone. To support the Global Burden of Disease Study, we produce yearly fine resolution global surface ozone estimates from 1990 to 2017 through a data fusion of observations and models. As ozone observations are sparse in many populated regions, we use a novel combination of the M3Fusion and Bayesian Maximum Entropy (BME) methods. With M3Fusion, we create a multimodel composite by bias-correcting and weighting nine global atmospheric chemistry models based on their ability to predict observations (8834 sites globally) in each region and year. BME is then used to integrate observations, such that estimates match observations at each monitoring site with the observational influence decreasing smoothly across space and time until the output matches the multimodel composite. After estimating at 0.5° resolution using BME, we add fine spatial detail from an additional model, yielding estimates at 0.1° resolution. Observed ozone is predicted more accurately (R 2 = 0.81 at the test point, 0.63 at 0.1°, and 0.62 at 0.5°) than the multimodel mean (R 2 = 0.28 at 0.5°). Global ozone exposure is estimated to be increasing, driven by highly populated regions of Asia and Africa, despite decreases in the United States and Russia.

City-level estimates of ambient ozone concentrations and associated disease burdens are sparsely available, especially for low and middle-income countries. Recently available high-resolution gridded global ozone concentration estimates allow for estimating ozone concentrations and mortality at urban scales and for urban-rural catchment areas worldwide. We applied existing fine resolution global surface ozone estimates, developed by integrating observations (8,834 sites globally) with nine atmospheric chemistry models, in an epidemiologically-derived health impact function to estimate chronic respiratory disease mortality worldwide in 2019. We compared ozone season daily maximum 8 hour mixing ratio concentrations and ozone-attributable mortality for urban areas worldwide (including cities and densely-populated towns), and their surrounding peri-urban, peri-rural, and rural areas. In 2019, population-weighted mean ozone among all urban-rural catchment areas was greatest in peri-urban areas (52 ppb), followed by urban areas (cities and towns; 49 ppb). Of 423,100 estimated global ozone-attributable deaths, 37% (147,100) occurred in urban areas, where 40% of the world’s population resides, and 56% (254,000) occurred in peri-urban areas (<1 hour from an urban area), where 47% of the world’s population resides. Across 12,946 cities (excluding towns), average population-weighted mean ozone was 51 ppb [sd=13 ppb, range=10–78 ppb]. Three quarters of the ozone-attributable deaths worldwide (77%; 112,700) occurred in cities of South and East Asia. City-level ozone-attributable mortality rates varied by a factor of 10 across world regions. Ozone levels and attributable mortality were greatest in Asian and African cities; however, cities of higher-income regions, like high-income Asia Pacific and North America, continue to experience high ozone concentrations and attributable mortality rates, despite successful national air quality measures for reducing ozone precursor emissions. The disproportionate magnitude of ozone mortality compared with population size in peri-urban areas indicates that reducing ozone precursor emissions in places that influence peri-urban concentrations can yield substantial health benefits in these areas.

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