The risk relationships between alcohol consumption, alcohol use disorder and alcohol use disorder mortality: A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Increasing levels of alcohol use are associated with a risk of developing an alcohol use disorder (AUD), which, in turn, is associated with considerable burden. Our aim was to estimate the risk relationships between alcohol consumption and AUD incidence and mortality. METHOD: A systematic literature search was conducted, using Medline, Embase, PsycINFO and Web of Science for case-control or cohort studies published between 1 January 2000 and 8 July 2022. These were required to report alcohol consumption, AUD incidence and/or AUD mortality (including 100% alcohol-attributable deaths). The protocol was registered with PROSPERO (CRD42022343201). Dose-response and random-effects meta-analyses were used to determine the risk relationships between alcohol consumption and AUD incidence and mortality and mortality rates in AUD patients, respectively. RESULTS: Of the 5904 reports identified, seven and three studies from high-income countries and Brazil met the inclusion criteria for quantitative and qualitative syntheses, respectively. In addition, two primary US data sources were analyzed. Higher levels of alcohol consumption increased the risk of developing or dying from an AUD exponentially. At an average consumption of four standard drinks (assuming 10 g of pure alcohol/standard drink) per day, the risk of developing an AUD was increased sevenfold [relative risk (RR) = 7.14, 95% confidence interval (CI) = 5.13-9.93] and the risk of dying fourfold (RR = 3.94, 95% CI = 3.53-4.40) compared with current non-drinkers. The mortality rate in AUD patients was 3.13 (95% CI = 1.07-9.13) per 1000 person-years. CONCLUSIONS: There are exponential positive risk relationships between alcohol use and both alcohol use disorder incidence and mortality. Even at an average consumption of 20 g/day (about one large beer), the risk of developing an alcohol use disorder (AUD) is nearly threefold that of current non-drinkers and the risk of dying from an AUD is approximately double that of current non-drinkers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".