Intimate Partner Violence: A Potential Challenge for Women’s Health in Angola
Bibliographic record
Abstract
Intimate partner violence (IPV), as the most common form of violence against women, is recognised as a fundamental violation of women’s human rights and a significant public health concern worldwide. IPV is also a widespread phenomenon in Africa where the associated health challenges can be particularly serious due to fragile healthcare systems. To date, there is no systematic research on IPV and its association with healthcare use among adult women in Angola. Therefore, we conducted the present study on IPV among women of childbearing age (15–49 years) in Angola by analysing cross-sectional data from Angola Demographic and Health Survey (2015–2016). The objectives were to assess the predictors of IPV and its association with healthcare use. IPV was assessed by women’s experience of physical, emotional and sexual violence, and healthcare use was assessed by self-reported medical visits during last 12 months. Logistic regression methods were used to analyse the data. Our findings showed that more than two-fifths of the women reported experiencing any IPV (41.1%, 95%Confidence Interval (CI)= 38.7 to 43.6), with physical IPV (32.3%, 95%CI = 30.3 to 34.5) being the most prevalent followed by emotional (27.3%, 95%CI = 25.3 to 29.4), and sexual IPV (7.4%, 95%I = 6.6 to 8.4). In the multivariate analysis, women’s religious background, husband’s alcohol drinking, spousal age difference, and frequency of attending church appeared to be the most important predictors of IPV. Nonpregnant women who experienced emotional [OR = 1.476, 95%CI = 1.154,1.887] and sexual IPV [Odds Ratio (OR) = 1.393, 95%CI = 1.068,1.816] had increase odds of healthcare visits during last 12 months. In conclusion, our findings suggest a noticeably high prevalence of IPV among Angolan women. Those who experience emotional and sexual IPV might be at higher odds of suffering from medical conditions and should be given special attention in primary care settings.
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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 | 0.002 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".