Housing Status, Medical Care, and Health Outcomes Among People Living With HIV/AIDS: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Accumulating evidence suggests responses to HIV that combine individual-level interventions with those that address structural or contextual factors that influence risks and health outcomes of infection. Housing is such a factor. Housing occupies a strategic position as an intermediate structural factor, linking "upstream" economic, social, and cultural determinants to the more immediate physical and social environments in which everyday life is lived. The importance of housing status for HIV prevention and care has been recognized, but much of this attention has focused on homeless individuals as a special risk group. Analyses have less often addressed community housing availability and conditions as factors influencing population health or unstable, inadequate, or unaffordable housing as a situation or temporary state. A focus on individual-level characteristics associated with literal homelessness glosses over social, economic, and policy drivers operating largely outside any specific individual's control that affect housing and residential environments and the health resources or risk exposures such contexts provide. OBJECTIVES: We examined the available empirical evidence on the association between housing status (broadly defined), medical care, and health outcomes among people with HIV and analyzed results to inform future research, program development, and policy implementation. SEARCH METHODS: We searched 8 electronic health and social science databases from January 1, 1996, through March 31, 2014, using search terms related to housing, dwelling, and living arrangements and HIV and AIDS. We contacted experts for additional literature. SELECTION CRITERIA: We selected articles if they were quantitative analyses published in English, French, or Spanish that included at least 1 measure of housing status as an independent variable and at least 1 health status, health care, treatment adherence, or risk behavior outcome among people with HIV in high-income countries. We defined housing status to include consideration of material or social dimensions of housing adequacy, stability, and security of tenure. DATA COLLECTION AND ANALYSIS: Two independent reviewers performed data extraction and quality appraisal. We used the Cochrane Risk of Bias Tool for randomized controlled trials and a modified version of the Newcastle Ottawa Quality Appraisal Tool for nonintervention studies. In our quality appraisal, we focused on issues of quality for observational studies: appropriate methods for determining exposure and measuring outcomes and methods to control confounding. RESULTS: Searches yielded 5528 references from which we included 152 studies, representing 139,757 HIV-positive participants. Most studies were conducted in the United States and Canada. Studies examined access and utilization of HIV medical care, adherence to antiretroviral medications, HIV clinical outcomes, other health outcomes, emergency department and inpatient utilization, and sex and drug risk behaviors. With rare exceptions, across studies in all domains, worse housing status was independently associated with worse outcomes, controlling for a range of individual patient and care system characteristics. CONCLUSIONS: Lack of stable, secure, adequate housing is a significant barrier to consistent and appropriate HIV medical care, access and adherence to antiretroviral medications, sustained viral suppression, and risk of forward transmission. Studies that examined the history of homelessness or problematic housing years before outcome assessment were least likely to find negative outcomes, homelessness being a potentially modifiable contextual factor. Randomized controlled trials and observational studies indicate an independent effect of housing assistance on improved outcomes for formerly homeless or inadequately housed people with HIV. Housing challenges result from complex interactions between individual vulnerabilities and broader economic, political, and legal structural determinants of health. The broad structural processes sustaining social exclusion and inequality seem beyond the immediate reach of HIV interventions, but changing housing and residential environments is both possible and promising.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".