HIV/AIDS mortality attributable to alcohol use in South Africa: a comparative risk assessment by socioeconomic status
Bibliographic record
Abstract
OBJECTIVES: To quantify HIV/AIDS mortality attributable to alcohol use in the adult general population of South Africa in 2012 by socioeconomic status (SES). DESIGN: Comparative risk assessment based on secondary individual data, aggregate data and risk relations reported in the literature. SETTING: South African adult general population. PARTICIPANTS: For metrics of alcohol use by SES, sex and age: 27 070 adults that participated in a nationally representative survey in 2012. For HRs of dying from HIV/AIDS by SES: 87 029 adults that participated in a cohort study (years 2000 to 2014) based out of the Umkhanyakude district, KwaZulu-Natal. MAIN OUTCOME MEASURES: Alcohol-attributable fractions for HIV/AIDS mortality by SES, age and sex were calculated based on the risk of engaging in condom-unprotected sex under the influence of alcohol and interactions between SES and alcohol use. Age-standardised HIV/AIDS mortality rates attributable to alcohol by SES and sex were estimated using alcohol-attributable fractions and SES-specific and sex-specific death counts. Rate ratios were calculated comparing age-standardised rates in low versus high SES by sex. RESULTS: The age-standardised HIV/AIDS mortality rate attributable to alcohol was 31.0 (95% uncertainty interval (UI) 21.6 to 41.3) and 229.6 (95% UI 108.8 to 351.6) deaths per 100 000 adults for men of high and low SES, respectively. For women the respective rates were 10.8 (95% UI 5.5 to 16.1) and 75.5 (95% UI 31.2 to 144.9). The rate ratio was 7.4 (95% UI 3.4 to 13.2) for men and 7.0 (95% UI 2.8 to 18.2) for women. Sensitivity analyses corroborated marked differences in alcohol-attributable HIV/AIDS mortality, with rate ratios between 2.7 (95% UI 0.8 to 7.6; women) and 15.1 (95% UI 6.8 to 27.7; men). CONCLUSIONS: The present study showed that alcohol use contributed considerably to the socioeconomic differences in HIV/AIDS mortality. Targeting HIV infection under the influence of alcohol is a promising strategy for interventions to reduce the HIV/AIDS burden and related socioeconomic differences in South Africa.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| 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".