Violence Toward Women, Men's Sexual Risk Factors, and HIV Infection Among Women
Bibliographic record
Abstract
OBJECTIVES: We used the third Rwanda demographic and health survey data to examine the relationship between violence toward women, men sexual risk factors, and HIV prevalence among women. METHODS: The Rwanda demographic and health survey was conducted in 10,272 households in 2005. Analyses were restricted to 2715 women and 2461 men who were legally married or cohabiting. We used logistic regression to analyze associations between HIV and violence toward women. Couple-specific analyses were carried out for assessing the relationship between men sexual risk factors and intimate partner violence (IPV) reported by their wives. RESULTS: Respectively, 29.2%, 22.2%, and 12.4% of women reported having experienced physical, psychological, and sexual IPV, whereas 52.1% reported control practices by their partners. There was a positive link between IPV reported by women and attitudes justifying wife beating endorsed by their husband. After controlling for sociodemographic variables and women sexual risk factors, the odds of HIV prevalence was 3.23 (confidence interval: 1.30 to 8.03) among women with a score from 3 to 4 on the psychological IPV scale compared with those with a score from 0 to 2. Women who reported having experienced interparental violence (father who beat mother) were more likely to test HIV positive as follows: adjusted odds ratio: 1.95; 95% confidence interval: 1.11 to 3.43. There was also a statistically significant relationship between men risky sexual factors and experience of IPV and HIV prevalence among women. CONCLUSIONS: Violence toward women is associated with HIV in Rwanda. Intervention to reduce gender-based violence should be integrated into HIV/AIDS policy.
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 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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".