Authors: Elisabeth Root*, The Ohio State University, Megan Lindstrom, The Ohio State University
Topics: Geography and Urban Health, Spatial Analysis & Modeling
Keywords: maternal and child health, neonatal abstinence syndrome, opioid, social determinants, spatial cluster analysis
Session Type: Virtual Paper
Start / End Time: 4:40 PM / 5:55 PM
Room: Virtual 8
Presentation File: No File Uploaded
Opioid use in pregnancy has escalated dramatically in recent years, paralleling the epidemic observed in the general population. In Ohio, over 20% of women enrolled in Medicaid have some form of opioid exposure during pregnancy, which has led to higher rates of Neonatal Abstinence Syndrome (NAS), preterm birth, low birthweight, and infant mortality in this population. In response to this crisis, the state of Ohio has partnered with the academic community to explore how data analytics, including geospatial analysis and geovisualization, can be used to examine communities at particularly high risk for opioid addiction and overdose. Data used for this study include link birth-medical claims records for all Medicaid births in Ohio between 2012 and 2017. We used spatial cluster analysis and spatial Conditional Autoregressive (CAR) modeling to find areas with higher than expected rates of maternal opioid addiction and NAS, and determine the ecological correlates of these rates. We find significant geographic variation in maternal opioid exposure in Ohio, with several large clusters (RR>2) centered in rural Appalachian communities. Most of these clusters are temporally persistent, or occurred later in the study period. Community-level drivers of these high rates include lack of education and employment opportunities, access to services, higher grime and poor housing. These results have been used by State partners to develop intervention strategies and recommendations.