Widow Inheritance and HIV Prevalence in Bondo District, Kenya: Baseline Results from a Prospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Widow Inheritance is a widespread cultural practice in sub-Saharan Africa that has been postulated as contributing to risk of HIV transmission. We present baseline results from a study designed to investigate the association between widow inheritance and HIV acquisition. METHODS AND FINDINGS: We performed a cross-sectional analysis of baseline data from a prospective cohort study to investigate if widow inheritance is a risk practice for HIV infection. Study participants were 1,987 widows who were interviewed regarding their inheritance status and sexual behavior profile and tested for HIV. Of these widows, 56.3% were inherited. HIV prevalence, at 63%, was similar among non-inherited and inherited widows. We stratified exposure status by the relationship of the widow to the inheritor and the reason for inheritance, and reexamined the HIV status of four subgroups of inherited women relative to the HIV status of non-inherited women. When adjusting for age and level of formal education, widows who were inherited by non-relatives for sexual ritual were significantly more likely to be infected than widows who were not inherited (OR = 2.07; 95%CI 1.49-2.86); widows who were inherited by relatives for sexual ritual also had elevated odds of HIV infection (OR = 1.34; 95%CI = 1.07-1.70). Widows who were inherited by relatives for companionship were less likely than women who were not inherited to be infected with HIV (OR = 0.85; 95%CI 0.63-1.14). CONCLUSIONS: HIV prevalence among inherited widows varied depending upon why and by whom they were inherited. The cohort study will determine the risk for HIV acquisition among the HIV seronegative widows in this sample.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".