Is intimate partner violence vertically transmitted among women in sub-Saharan Africa? Evidence from demographic health surveys between 2010 and 2019
Bibliographic record
Abstract
BACKGROUND: Violence against women is a major human rights violation, and the continuous occurrence of this can have many implications for women's social and health outcomes. The experience of violence from an intimate partner could be more intriguing, especially if such women experienced their mother's intimate partner violence (IPV) issues. Thus, this study examined the vertical transmission of IPV among women in sub-Saharan Africa (SSA). METHODS: A total of 97,542 eligible women were drawn from 27 countries in SSA using a retrospective secondary dataset from Demographic Health Surveys conducted between 2010 and 2019. Multivariable analysis was employed to determine the association between the vertical transmission of IPV from mother to daughter and the covariates associated with IPV in SSA at p < 0.05. RESULTS: The results showed that 40% of the respondents had experienced lifetime IPV, whilst 25% of those women reported that their mothers experienced it in childhood in SSA. Country-specific variations showed the highest prevalence of IPV experienced in Sierra Leone (60%) and the lowest in Comoros (9%). Results from model 1 showed that women who reported that their mothers experienced IPV were found to be significantly more than two times more likely to have experienced any form of IPV compared to those whose mothers did not (aOR = 2.66; 95% CI: 2.59-2.74), after adjusting for cofounders in Model 2, the result still showed that women who reported that their mothers experienced IPV were found to be significantly more than two times more likely to have experienced any form of IPV compared to those whose mothers did not (aOR = 2.56; 95% CI: 2.48-2.63). On the other hand, women with higher-educated partners, women in rural areas, and those from female-headed households were less likely to experience IPV. CONCLUSION: This study concluded that women whose mothers experienced IPV were more likely to have experienced IPV. Our study also identified that education, rural areas, and female-headed households were protective factors against experiencing IPV. To address the groups of women at higher risk for experiencing IPV, we recommend ensuring that girls complete their education to promote greater wealth and resources.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".