The impact of alcohol consumption on African people in 2012: an analysis of burden of disease
Bibliographic record
Abstract
OBJECTIVES: To determine the impact of alcohol consumption on deaths and disability in Africa. METHODS: We estimated alcohol exposure for 2012, and its impact on deaths and disability in Africa using estimates from the WHO Global Health Estimates for outcome data, and the WHO Global Status Report on Alcohol and Health 2014 for risk relations. We provide a scenario that includes the impact of alcohol on HIV/AIDS incidence, and qualitative predictions on future exposure and harm. RESULTS: Overall, alcohol consumption has a large impact on burden of disease and mortality in African countries. Alcohol-attributable disease burden is more important when the impact of alcohol consumption on the incidence and course of HIV/AIDS is taken into account, with alcohol being responsible, in 2012, for 6.4% of all deaths and 4.7% of all DALYs lost in the African region. Alcohol exposure is expected to increase in the next years, and thus alcohol-attributable fractions. CONCLUSIONS: The weight of new evidence, especially of alcohol's role in the incidence and course of HIV/AIDS, is particularly relevant to African countries and points to the need for a strong policy response to reduce the alcohol-related burden of disease on the continent.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".