Intimate partner violence in older South African women: An analysis of the 2016 Demographic and Health Survey
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: South Africa (SA) has one of the highest rates of intimate partner violence (IPV) in the world. It is also in the midst of a demographic transition in which the number of people aged >60 years is expected to double by mid-century. Despite the confluence of these two public health issues, there are no published studies on the epidemiology and risk factors for IPV in older SA women. OBJECTIVES: To provide a foundational understanding of IPV among women aged ≥50 years in SA. METHODS: This study used the first-ever nationally representative sample of women aged >49 (N=2 265) that includes data on physical, sexual, and emotional IPV. Both lifetime experience of IPV and IPV within the past 12 months were reported, as was the presence of controlling behaviours by the partner. Four multilevel logistic models and one multilevel linear regression model were fit to examine the demographic, developmental and structural correlates of IPV in women aged 50 - 95. RESULTS: The lifetime prevalence rates for all types of IPV were slightly higher among older women than among women aged 15 - 49. Nine percent of respondents reported IPV in the past 12 months, and 35% reported at least one persistent controlling behaviour. Divorced/separated women and those who had witnessed IPV as a child had greater odds of reporting IPV. In contrast to the literature on younger women, education, race and wealth were not strong predictors of IPV in this sample of older women. CONCLUSIONS: This study is the first of its kind in the SA context, and shows that IPV is a persistent threat for women across the lifespan. It suggests that IPV may manifest differently in older women compared with women of reproductive age, necessitating future qualitative and quantitative studies that examine the correlates, causes and points of intervention unique to this growing population.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it