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.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".