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. In 2017, the leading Level 4 risk factor for age-standardised 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. 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. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. 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 19. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18♶% increase in DALYs during that period. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23♵% decline in DALYs during that period. In total, risk-attributable DALYs declined by 4♹% (3♳–6♵) between 20. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10♴ million (9♳9–11♵) deaths and 218 million (198–237) DALYs, followed by smoking (7♱0 million deaths and 182 million DALYs), high fasting plasma glucose (6♵3 million deaths and 171 million DALYs), high body-mass index (BMI 4♷2 million deaths and 148 million DALYs), and short gestation for birthweight (1♴3 million deaths and 139 million DALYs). Globally, 61♰% (59♶–62♴) of deaths and 48♳% (46♳–50♲) of DALYs were attributed to the GBD 2017 risk factors. In 2017, 34♱ million (95% uncertainty interval 33♳–35♰) deaths and 1♲1 billion (1♱4–1♲8) DALYs were attributable to GBD risk factors.
TONE KING METROPOLITAN DISCONTINUED DRIVERS
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. 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. 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 used statistical models to pool data, adjust for bias, and incorporate covariates. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. 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.
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