CDC-Funded HIV Testing Services Outcomes and Social Determinants of Health in Ending the HIV Epidemic in the U.S. Jurisdictions.
Deesha PatelHollie A ClarkWeston O WilliamsNicole Taylor-AidooCarolyn WrightPublished in: AIDS and behavior (2023)
We performed an ecological analysis to examine associations between CDC-funded HIV testing services outcomes and social determinants of health (SDOH) among Ending the HIV Epidemic in the U.S. jurisdictions. Using National HIV Prevention Program Monitoring & Evaluation (2020) and American Community Survey (2016-2020) data, we ran robust Poisson models (adjusted for race/ethnicity). In healthcare settings, a 10% absolute increase in percentage without health insurance was associated with a 40% lower prevalence of newly diagnosed positivity (aPR = 0.60, 95% CI: 0.43-0.83); a $5,000 increase in median household income (aPR = 1.04, 95% CI: 1.03-1.06) and a 10% absolute increase in percentage unemployed (aPR = 1.80, 95% CI: 1.31-2.46) were associated with 4% and 80%, respectively, higher prevalence of percentage linked to HIV medical care within 30 days of diagnosis (i.e., linkage). In non-healthcare settings, a 10% absolute increase in percentage with less than high school diploma (aPR = 0.53, 95% CI: 0.29-0.96) was associated with a 47% lower prevalence of newly diagnosed positivity, whereas a 10% absolute increase in percentage without health insurance (aPR = 1.92, 95% CI: 1.29-2.88) was associated with a 92% higher prevalence of newly diagnosed positivity; a 10% absolute increase in percentage with less than high school diploma was associated with a 35% lower prevalence of linkage (aPR = 0.65, 95% CI: 0.43-0.97). Addressing SDOH in HIV prevention programs will play an important role in ending the HIV epidemic.
Keyphrases
- hiv testing
- men who have sex with men
- healthcare
- health insurance
- newly diagnosed
- hiv positive
- risk factors
- mental health
- affordable care act
- public health
- human immunodeficiency virus
- antiretroviral therapy
- high school
- primary care
- hiv infected
- machine learning
- health information
- quality improvement
- physical activity
- human health
- social media
- gene expression
- genome wide
- dna methylation
- metabolic syndrome
- artificial intelligence
- cell proliferation