Abstract

BackgroundThe increasing prevalence of young people living with HIV (YPLWH) is a major public health concern. In 2017, the Centers for Disease Control and Prevention (CDC) reported that young people accounted for 21% (8164) of the 38,739 new HIV diagnoses in the United States. Therefore, understanding opioid use disorder (OUD) among YPLWH is critical in developing effective treatment and prevention strategies. The study intends to provide evidence regarding the prevalence of opioid use disorder as well as to examine the effects of moderators on the diagnosis of OUD among a subset of YPLWH. MethodsThe National Inpatient Sample data (2008–2017) were analyzed. Participants ranged in age from 13 to 24 years old and had an HIV-related ICD code was included. The outcomes were OUD diagnosis, patterns, and moderators. The adjusted effects of the moderators on the likelihood of being diagnosed with opioid use were examined using multivariable logistic regression. ResultsResults from the study showed that 501 (2%) of the 27,538 HIV-positive young people aged 13 to 24 had comorbid Opioid use disorder (OUD). After adjusting for sex, race, and mental health diagnosis (MHD), having HIV (p < 0.05) and an MHD [OR 2.46 (1.92, 3.16)] was associated with a higher risk of OUD. Individuals with the highest income level were 42% less likely to have OUD (Table 3). The likelihood of having OUD is much lower among YPLWH aged 13–24 years from the United States' southern and western states. ConclusionOpioid use disorder (OUD) among young people living with HIV is of public concern. Understanding the drivers of the increasing prevalence provides opportunities for policies aimed at stemming the rise. Overall, our findings suggest that there is a significant need for interventions and support for young people with comorbid HIV and OUD, particularly those with low income and mental health issues. Addressing socioeconomic factors such as poverty and increasing access to mental health services could help reduce the risk of OUD among this population. Additionally, understanding regional differences in drug use could inform targeted prevention and intervention efforts.

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