Prevalence and Risk Factors for Intimate Partner Violence in Women Living with HIV in Uganda
Bibliographic record
Abstract
Intimate partner violence (IPV), behavior within an intimate relationship that causes physical, sexual, or psychological harm, is a significant global health problem. IPV is associated with HIV incidence, reduced antiretroviral (ART) adherence, and a lower likelihood of viral load suppression. To inform future IPV interventions we examined IPV prevalence and IPV risk factors among women living with HIV (WLWH) in Uganda. We utilized prospective data from women enrolled in the Uganda AIDS Rural Treatment Outcomes (UARTO) cohort study of HIV-infected adults receiving ART between 2011 and 2015. Bloodwork (CD4 cells/mm3, HIV-RNA) and interviewer-administered questionnaires (socio-demographics, behavior, and health outcomes) were completed quarterly. Sexual and reproductive health data, including IPV and relationship dynamics, were collected annually. We performed analyses with the primary outcome of experiencing physical or sexual IPV at any time during the follow-up period (yes vs. no). Multivariate logistic regression was used to assess socioeconomic and clinical factors associated with IPV. A total of 455 WLWH were included. Median age was 36.3 years, 43% were married, and median time on ART was 4 years. At baseline,131 women (29%) reported a history of experiencing IPV. Over study follow-up, 68 women (15%) reported experiencing current physical or sexual IPV at least once. Of those 68 women, 22 (32%) experienced physical violence only, 30 (44%) experienced sexual violence only, and 16 (24%) experienced both. In the adjusted model, younger age per year (AOR 1.06, 95% CI 1.04–1.10), hazardous drinking (AOR 3.31, 95% CI 1.14–9.63), and being married (AOR 2.64, 95% CI 1.47–4.72) were associated with higher odds of experiencing current IPV. Experiences of physical and sexual IPV are common among women in this study, and many experienced both sexual and physical violence. These results highlight the need to develop effective and integrated IPV screening and treatment interventions for women accessing HIV care. Further research is needed to better understand how alcohol use, younger age, and marital status play a role in the risk of IPV, to inform development and testing of IPV interventions for WLWH. J. E. Haberer, Merck: Consultant, Consulting fee; Natera: Shareholder, Stock ownership
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".