ABSTRACT
OBJECTIVES: We examined racial/ethnic disparities in highly active antiretroviral therapy (HAART) use and whether differences are moderated by substance use or insurance status, using data from the Women's Interagency HIV Study (WIHS). METHODS: Logistic regression examined HAART use in a longitudinal cohort of women for whom HAART was clinically indicated in 2005 (N = 1354). RESULTS: Approximately 3 of every 10 eligible women reported not taking HAART. African American and Hispanic women were less likely than were White women to use HAART. After we adjusted for potential confounders, the higher likelihood of not using HAART persisted for African American but not for Hispanic women. Uninsured and privately insured women, regardless of race/ethnicity, were less likely than were Medicaid enrollees to use HAART. Although alcohol use was related to HAART nonuse, illicit drug use was not. CONCLUSIONS: These findings suggest that expanding and improving insurance coverage should increase access to antiretroviral therapy across racial/ethnic groups, but it is not likely to eliminate the disparity in use of HAART between African American and White women with HIV/AIDS.
Subject(s)
Antiretroviral Therapy, Highly Active , HIV Infections , Insurance, Health/economics , Medication Adherence/ethnology , Substance-Related Disorders/ethnology , Adult , Black or African American/ethnology , Antiretroviral Therapy, Highly Active/economics , Antiretroviral Therapy, Highly Active/statistics & numerical data , Cross-Sectional Studies , Female , Follow-Up Studies , HIV Infections/complications , HIV Infections/drug therapy , HIV Infections/ethnology , Health Care Surveys , Health Services Accessibility , Healthcare Disparities , Hispanic or Latino/ethnology , Humans , Insurance Coverage/economics , Logistic Models , Medicaid/statistics & numerical data , Medically Uninsured/statistics & numerical data , Medication Adherence/statistics & numerical data , Middle Aged , Multivariate Analysis , Socioeconomic Factors , Substance-Related Disorders/complications , United States/epidemiology , White People/ethnologyABSTRACT
Many studies in the social and behavioral sciences involve multivariate discrete measurements, which are often characterized by the presence of an underlying individual trait, the existence of clusters such as domains of measurements, and the availability of multiple waves of cohort data. Motivated by an application in child development, we propose a class of extended multivariate discrete hidden Markov models for analyzing domain-based measurements of cognition and behavior. A random effects model is used to capture the long-term trait. Additionally, we develop a model selection criterion based on the Bayes factor for the extended hidden Markov model. The National Longitudinal Survey of Youth (NLSY) is used to illustrate the methods. Supplementary technical details and computer codes are available online.
