Exploratory Analysis: The Spatial Patterns of Motor Vehicle Crashes and Drug Overdose Deaths across the United States

Authors: Nandi Taylor*, ASPPH/NHTSA Public Health Fellow, Jeremiah Kinsman, DOT-NHTSA
Topics: Medical and Health Geography, Geographic Information Science and Systems, United States
Keywords: health, motor vehicle crashes, drug
Session Type: Poster
Day: 4/4/2019
Start / End Time: 3:05 PM / 4:45 PM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: No File Uploaded

Introduction: Motor vehicle crashes (MVCs) and drug overdoses are the leading causes of unintentional injuries and mortality in the United States. Both outcomes have a significant impact on individuals, families and communities. This analysis aims to explore the spatial patterns of both motor vehicle crashes and drug overdoses deaths to determine characteristics of areas that are experiencing both burdens. Methods: 2012 – 2016 county-level data from three sources was analyzed. Drug Overdose deaths rates were obtained from the Center for Disease Control and Prevention’s WONDER Database and MVC fatality rates were calculated from the National Highway Traffic Safety Administration’s Fatality Analysis Reporting System. Demographic characteristics from the U.S. Census American Consumer Survey were included. Counties were grouped into 4 categories based on MVC and drug overdose death rate percentiles. ArcGIS Desktop was used to map both outcomes along with High/Low groups to access spatial patterns. One-Way ANOVA was performed in SAS 9.4. to assess demographic characteristics of selected counties. Results: Spatial patterns of both events varied across the United States. Counties with high rates of both drug overdose and MVC deaths (HCHD, n=91) were mainly located in the South and were classified as non-metropolitan counties. Demographic characteristics of counties significantly vary across groups. Conclusion: Our results highlight the spatial patterns of MVCs and drug overdose deaths and potential areas experiencing burdens from both health outcomes. Further analysis should be done to better understand what factors are influencing both outcomes to better develop interventions and community based programs.

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