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...

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Omega-3 fatty acid supplements containing both eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have been shown to reduce triglycerides but also increase low-density lipoprotein (LDL). Whether EPA or DHA given as monotherapy has differential effects on serum lipoproteins has not been systematically evaluated. We performed a meta-analysis of randomized placebo-controlled trials of monotherapy with EPA (n=10), DHA (n=17), or EPA versus DHA (n=6). Compared with placebo, DHA raised LDL 7.23 mg/dL (95% CI, 3.98–10.5) whereas EPA non-significantly reduced LDL. In direct comparison studies, DHA raised LDL 4.63 mg/dL (95% CI, 2.15–7.10) more than EPA. Both EPA and DHA reduced triglycerides, with a greater reduction by DHA in direct comparison studies. DHA also raised high-density lipoprotein (4.49 mg/dL; 95% CI, 3.50–5.48) compared with placebo, whereas EPA did not. Although EPA and DHA both reduce triglycerides, they have divergent effects on LDL and high-density lipoprotein. Further research is needed to elucidate the mechanisms and significance of these differences.

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Multimorbidity is prevalent, but its optimal quantification and associations with mortality rate and physical functioning in young through older adults are uncertain. We used data collected using the Short Form-36 in the Nurses' Health Study (enrollment started in 1976), Nurses' Health Study II (begun in 1989), and Health Professionals Follow-up Study (begun in 1986) to identify associations of a multimorbidity-weighted index (MWI) and common alternative indices with mortality and future physical functioning. We used Cox proportional hazard ratios to determine incident 10-year mortality and general linear models to obtain coefficients for the associations of MWI with 4- and 8-year physical functioning. At baseline, mean values for the 219,950 participants were 55.0 (standard deviation, 3.7) years for age; 3.8 (range, 0-51) for MWI; 2.7 (range, 0-23) for disease count, and 0.43 (range, 0-13) for Charlson Comorbidity Index (CCI). During follow-up, 23,709 deaths (10.8%) occurred. CCI, MWI, and disease count were 0 for 77%, 12%, and 19% of participants, respectively. When comparing persons in the highest quartiles with those in the lowest, the hazard ratios for mortality were 6.04 (95% confidence interval (CI): 6.00, 6.09; P for trend < 0.0001) for the MWI, 4.86 (95% CI: 4.81, 4.91; P for trend < 0.0001) for disease count, and 3.29 (95% CI: 3.26, 3.32; P for trend < 0.0001) for the CCI. For future physical functioning, MWI had the best model fit and explained the greatest variance. Multimorbidity has important associations with future physical functioning and mortality that are easily captured with a readily measured index.