Shield · The Lancet. Public health 2020 · Comparative risk assessment modeling study · n=?

National, regional, and global burdens of disease from 2000 to 2016 attributable to alcohol use: a comparative risk assessment study.

Cited 540 times in the scientific literature.

Level 4 - case-series / case-control

Level 4 by design analogy (global comparative risk assessment and epidemiological modeling study using aggregate secondary data).

PubMed 31910980 · doi:10.1016/S2468-2667(19)30231-2 · record verified 2026-08-29

What was done

This comparative risk assessment study modeled national, regional, and global disease burdens attributable to alcohol from 2000 to 2016 across gender, age, and geography. Population-attributable fractions (PAFs) were calculated by combining alcohol exposure data (from national production, taxation records, and surveys) with relative risks from published cohort studies and meta-analyses. Morbidity and mortality estimates came from WHO Global Health Estimates, population data from the UN Population Division, and Human Development Index (HDI) data from the UN Development Programme. Uncertainty intervals (95% UIs) were computed using a Monte Carlo-like approach.

What was found

Globally in 2016, alcohol use accounted for an estimated 3.0 million (95% UI 2.6–3.6) deaths and 131.4 million (119.4–154.4) disability-adjusted life-years (DALYs), representing 5.3% (4.6–6.3) of all deaths and 5.0% (4.6–5.9) of all DALYs. Alcohol-attributable mortality PAFs were 17.7% (14.3–23.0) for injury, 4.3% (3.6–5.1) for non-communicable diseases, and 3.3% (1.9–5.6) for communicable, maternal, perinatal, and nutritional diseases. The disease burden was higher in men than women, and the age-standardised burden was highest in eastern Europe, western, southern, and central sub-Saharan Africa, and low-HDI countries. People younger than 60 years accounted for 52.4% of all alcohol-attributable deaths.

Why it matters

This study quantifies the substantial mortality and disability burden of alcohol worldwide, showing that it disproportionately affects low-income nations and working-age adults under 60. These findings help pinpoint demographic and geographic priorities for targeted taxation and alcohol policy interventions.

Limits

The findings derive from epidemiological modeling and aggregate data synthesis rather than direct prospective observation. Exposure measurements rely on taxation and production statistics as well as self-reported surveys, which may overlook illicit or unrecorded alcohol and suffer from reporting bias or sparse data in low-income regions.

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