HIV infection risk among women in South Africa: exploring the interplay between financial autonomy, sexual autonomy and intimate partner violence
Bibliographic record
Abstract
Abstract Aim: To assess the inter-relationships between women’s sexual autonomy (SA), financial autonomy (FA) and experience of intimate partner violence (IPV), and how these factors influence HIV infection risk. Subject and Methods: This is a secondary analysis of the 2016 South-Africa Demographic and Health Survey. The study included all ever-partnered women aged 18-49 who were randomly selected for the domestic violence and HIV test modules. SA was measured from questions about women’s ability to refuse sex or request condom use. FA was measured from questions about women’s employment status, personal earnings, etc. IPV was measured from questions about women’s experience of emotional, physical and/or sexual violence. Bivariate analyses were used to assess the inter-relationships between SA, FA and IPV, and their individual relationships with HIV. Lastly, a multiple logistic regression model assessed their mutually adjusted associations with HIV infection risk. Results: There was no apparent relationship between sexual and financial autonomy, but they were weakly inversely associated with IPV. In the bivariate analyses, all three variables were associated with HIV risk. However, in the mutually adjusted model, only SA and IPV remained associated with HIV risk. Low SA (AOR = 2.01, 95% CI: 1.30 to 3.10, p=0.006) and exposure to sexual violence (AOR = 2.91, 95% CI: 1.14 to 7.43, p = 0.03) were associated with higher odds of HIV seropositivity. Conclusion: This study highlighted the important roles of SA and IPV on women’s HIV risk, as well as the need for further research to clarify the role of FA.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".