Food Insecurity and Sexual Risk in an HIV Endemic Community in Uganda
Bibliographic record
Abstract
Food insecurity has been linked to high-risk sexual behavior in sub-Saharan Africa, but there are limited data on these links among people living with HIV/AIDS, and on the mechanisms for how food insecurity predisposes individuals to risky sexual practices. We undertook a series of in-depth open-ended interviews with 41 individuals living with HIV/AIDS to understand the impact of food insecurity on sexual-risk behaviors. Participants were recruited from the Immune Suppression Clinic at the Mbarara University of Science and Technology in Mbarara, Uganda. Interviews were recorded, transcribed verbatim, translated, and coded following the strategy of grounded theory. Four major themes emerged from the interview data: the relationship between food insecurity and transactional sex for women; the impact of a husband's death from HIV on worsening food insecurity among women and children; the impact of food insecurity on control over condom use, and the relationship between food insecurity and staying in violent/abusive relationships. Food insecurity led to increased sexual vulnerability among women. Women were often compelled to engage in transactional sex or remain in violent or abusive relationships due to their reliance on men in their communities to provide food for themselves and their children. There is an urgent need to prioritize food security programs for women living with HIV/AIDS and address broader gender-based inequities that are propelling women to engage in risky sexual behaviors based on hunger. Such interventions will play an important role in improving the health and well-being of people living with HIV/AIDS, and preventing HIV transmission.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".