National and regional prevalence of interpersonal violence from others’ alcohol use: a systematic review and modelling study
Bibliographic record
Abstract
Background: While alcohol use is an established risk factor for interpersonal violence, the extent to which people are affected by interpersonal violence from others' drinking has not yet been quantified for different world regions. This modelling study aims to provide the first estimates of the national and regional prevalence of interpersonal violence from others' drinking. Methods: An international systematic literature search (02/28/2023, Prospero: CRD42022337364) was conducted to identify general adult population studies assessing the prevalence of interpersonal violence from others' drinking with no restrictions to publication date or language. Reports that did not provide data on interpersonal violence from others' drinking (primary outcome), were no original research studies, or captured a selected group of people only, were excluded. Observed prevalence data were extracted and used to build fractional response regression models to predict past-year prevalence of emotional and physical violence from others' drinking in 2019. Random-effects meta-regression models were used to aggregate the observed prevalence of sexual and intimate partner violence. Study risk of bias (ROB) was assessed using a modified version of the Newcastle-Ottawa Scale. Findings: Out of 13,835 identified reports, 50 were included covering just under 830,000 individuals (women: 347,112; men: 322,331; men/women combined: 160,057) from 61 countries. With an average prevalence of 16·8% (95% CI: 15·2-18·3%) and 28·3% (95% CI: 23·9-32·4%) in men and women combined in the GBD super regions High Income and Central Europe, Eastern Europe, & Central Asia, respectively, emotional violence was the most common form of interpersonal violence from others' drinking. Physical violence averaged around 3% (women) and 5% (men) in both regions. The pooled prevalence of sexual violence from others' drinking in men and women was 1·3% (95% CI: 0·5-3·3%, 95% PI: 0·1-16·9%) and 3·4% (95% CI: 1·4-8·3%, 95% PI: 0·2-35·3%), respectively, and ranged between 0·4% (95% CI: 0·1-1·6%, 95% PI: 0·0-7·3%) and 2·7% (95% CI: 1·1-6·3%, 95% PI: 0·2-30·0%) for different forms of intimate partner violence. ROB was moderate or critical for most reports; accounting for critical ROB did not substantially alter our results. Interpretation: The share of the population experiencing harms from others' drinking is significant and should be an integral part of public health strategies. Funding: Research reported in this publication was supported by the Canadian Institutes of Health Research (CIHR; grant: CIHR FRN 477887).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.037 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".