A Systematic Review of Qualitative Research on HIV and Food Insecurity in High-Income Countries
Bibliographic record
Abstract
OBJECTIVES: Food insecurity leads to adverse health outcomes in people living with HIV, including obesity, poor mental health and viral non-suppression. Qualitative studies in low- and middle-income countries have described the impact of food insecurity on medication adherence. However, limited qualitative research exists on the lived experiences of food insecurity among people living with HIV in high-income countries (HICs). We aimed to synthesize qualitative literature on food insecurity among people living with HIV in HICs. DESIGN: Systematic review and textual narrative synthesis. METHODS: We searched MEDLINE, CINAHL, Scopus, Embase, and PsycINFO, extracting data from included articles on a standardized form in Covidence. We synthesized literature using a textual narrative approach. We conducted quality appraisal (Critical Appraisal Skills Programme Qualitative Studies Checklist) and graded certainty of findings (GRADE-CERQual). RESULTS: We reviewed 2772 articles, reduced to 940 after deduplication, with 12 articles included after full text screening. Included articles reported on studies conducted in the United States ( n = 7), and Canada ( n = 5). We identified three key themes, each with their own sub-themes: the role of structural inequalities in shaping and navigating food insecurity; the impacts of food insecurity on health and wellbeing; and the labour of acquiring of food. CONCLUSIONS: Our review highlights the syndemic nature of food insecurity and HIV; intersecting experiences of multiple structural hardships constellate and interact synergistically to amplify poor health outcomes. Interventions should address the multiple and reinforcing social and structural conditions that shape food insecurity among people living with HIV.
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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 | 0.066 | 0.134 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.017 | 0.021 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".