Developing the evidence base for overdose policies: a multilevel analysis of NHBS

摘要：过量（OD）流行是21世纪美国最严重的危机之一，注射者

Abstract: The overdose (OD) epidemic is one of the worst crises of the 21st century US, and people who inject drugs (PWID) are at its epicenter. ODs are the leading cause of death for PWID, and the number of PWID is rising. We are, though, routinely missing opportunities to develop the evidence base for interventions for PWID:  Many states are enacting laws to combat the opioid epidemic (Prescription Drug Monitoring Programs [PDMPs], Naloxone Access Laws, Good Samaritan Laws), and a high-impact body of research is now analyzing how these laws, and other health policies (Medicaid Expansion, Medical Marijuana Laws [MMLs]), affect ODs in the general population. To date, though, this research has ignored PWID, a highly vulnerable population that may respond differently to these laws than members of the general population.  The growing body of research on place characteristics (e.g., neighborhood poverty rates) and ODs has also neglected PWID. The range and impact of place-based exposures, however, may differ for PWID. NIDA prioritizes generating scientific evidence to guide policy. As policymakers confront this health crisis, however, they are crafting laws with scant evidence about their possible effects on PWID. Likewise, the lack of scientific evidence about the effects of place characteristics on ODs among PWID cuts off whole arenas of place-based interventions, interventions that have proven effective for other health outcomes among PWID. Guided by the Risk Environment Model and Public Health Law Research principles, we will integrate CDC National HIV Behavioral Surveillance (NHBS) data on ~38,800 PWID in 20+ US metropolitan statistical areas (MSAs) in 2009, 2012, 2015, and 2018 with existing data on state laws and on characteristics of the MSAs, counties, and ZIP codes where these PWID live. This rich database will allow us to achieve three aims: Aim 1: Apply multilevel methods to analyze relationships of PDMPs, Medicaid Expansion, and MMLs to self- reported ODs, OD risk factors, and (for PDMPs and Medicaid) substance use disorder treatment among PWID. We will analyze if relationships vary by (a) PWID race/ethnicity, gender, age, and HIV status; and (b) characteristics of the ZIP codes and counties where PWID live. Aim 2. Apply multilevel methods to analyze relationships of Naloxone Access Laws and Good Samaritan Laws to naloxone access and bystander responses to ODs, and learn if relationships vary by (a) PWID race/ethnicity, gender, age, and HIV status; and (b) characteristics of ZIP codes and counties where PWID live. Aim 3. Use multilevel methods to analyze relationships of characteristics of PWID ZIP codes, counties, and MSAs to self-reported ODs, OD risk factors, and substance use disorder treatment; and test if relationships vary by PWID race/ethnicity, gender, age, and HIV status. Each Aim will also use multilevel structural equation models to analyze pathways linking exposures to outcomes. Results will provide some of the first evidence to help develop laws and place-based interven- tions to combat ODs among PWID, a growing and neglected population at the epicenter of the OD epidemic.