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Record W2997589337 · doi:10.1016/s2468-2667(19)30231-2

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

2020· article· en· W2997589337 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Lancet Public Health · 2020
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
FundersWorld Health Organization
KeywordsMedicineEnvironmental healthPopulationAttributable riskDisease burdenDemographyBurden of diseaseCohort studyCohortInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Alcohol use has increased globally, with varying trends in different parts of the world. This study investigates gender, age, and geographical differences in the alcohol-attributable burden of disease from 2000 to 2016. METHODS: This comparative risk assessment study estimated the alcohol-attributable burden of disease. Population-attributable fractions (PAFs) were estimated by combining alcohol exposure data obtained from production and taxation statistics and from national surveys with corresponding relative risks obtained from meta-analyses and cohort studies. Mortality and morbidity data were obtained from the WHO Global Health Estimates, population data were obtained from the UN Population Division, and human development index (HDI) data were obtained from the UN Development Programme. Uncertainty intervals (UIs) were estimated using a Monte Carlo-like approach. FINDINGS: Globally, we estimated that there were 3·0 million (95% UI 2·6-3·6) alcohol-attributable deaths and 131·4 million (119·4-154·4) disability-adjusted life-years (DALYs) in 2016, corresponding to 5·3% (4·6-6·3) of all deaths and 5·0% (4·6-5·9) of all DALYs. Alcohol use was a major risk factor for communicable, maternal, perinatal, and nutritional diseases (PAF of 3·3% [1·9-5·6]), non-communicable diseases (4·3% [3·6-5·1]), and injury (17·7% [14·3-23·0]) deaths. The alcohol-attributable burden of disease was higher among men than among women, and the alcohol-attributable age-standardised burden of disease was highest in the eastern Europe and western, southern, and central sub-Saharan Africa regions, and in countries with low HDIs. 52·4% of all alcohol-attributable deaths occurred in people younger than 60 years. INTERPRETATION: As a leading risk factor for the burden of disease, alcohol use disproportionately affects people in low HDI countries and young people. Given the variations in the alcohol-attributable burden of disease, cost-effective local and national policy measures that can reduce alcohol use and the resulting burden of disease are needed, especially in low-income and middle-income countries. FUNDING: None.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.312
GPT teacher head0.441
Teacher spread0.129 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it