Using Spatial Analysis to Model the Geographic Distribution of Prescription Opioids and its Relationship to Opioid-Related Health Outcomes in the United States
Topics: Health and Medical
, Quantitative Methods
, Geographic Information Science and Systems
Keywords: united states opioid crisis, prescription opioids, treatment admissions, ARCOS, spatial analysis, spatial lag of X (SLX) model
Session Type: Virtual Paper Abstract
Day: Tuesday
Session Start / End Time: 3/1/2022 09:40 AM (Eastern Time (US & Canada)) - 3/1/2022 11:00 AM (Eastern Time (US & Canada))
Room: Virtual 16
Authors:
Jeffery Charles Sauer, University of Maryland at College Park
Kathleen Stewart, University of Maryland at College Park
Zachary DW Dezman, University of Maryland School of Medicine
Eleanor Artigiani, University of Maryland Center for Substance Abuse Research (CESAR)
Eric D Wish, University of Maryland Center for Substance Abuse Research (CESAR)
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Abstract
While the individual-level relationship between prescription opioids and opioid-related health outcomes are established, the impact of prescription opioid availability at differing levels of geography is less understood. A special, expanded data release from the Drug Enforcement Administration’s Automated Reports and Consolidated Ordering System (ARCOS) allows for novel analyses on the geographic distribution of prescription opioid availability and its relation to opioid-related health outcomes. This study characterizes the state-level and county-level spatial distribution of leading prescription opioids across the United States from 2006 to 2012. Prescription opioid availability was measured as per capita morphine milligram equivalents (MME). County-level relationships between prescription opioid availability and treatment admissions for prescription opioid misuses were estimated using nonspatial and spatial lag of X (SLX) regression models. States with the highest levels of per capita MME were in the southeast and mid-Appalachia. Comparison of several spatial cluster methods showed consistent clusters of high per capita MME in counties along the Kentucky-Virginia border. Regression models indicated a strong, positive relationship between per capita MME, as well as the spatial lag of per capita MME, and treatment admissions for prescription opioid misuse that persisted after controlling for socioeconomic characteristics and state-level fixed effects. Spatial analysis reveals clear geographical differences in the distribution of prescription opioid availability in the core years of the United States opioid overdose crisis. Further analyses of ARCOS data can address pertinent research questions on disparities in prescription opioid distribution, drug reformulation, and anomalous shipments.
Using Spatial Analysis to Model the Geographic Distribution of Prescription Opioids and its Relationship to Opioid-Related Health Outcomes in the United States
Category
Virtual Paper Abstract
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