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Opioid Overdose Deaths in the United States

SOCIO DEMOGRAPHIC
CLEAR ×
Race / Ethnicity
Age
Educational Attainment
ECONOMIC
Accident-prone Employment
STATES
LIST OF COUNTIES
DATA VARIABLES
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INTRODUCTION METHODOLOGY & DATA MORE ABOUT NORC
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County Profile :
Drug Overdose Mortality Rate
Deaths per 100k population
(Ages 15-64)
Appalachian Region
U.S.
Total Deaths
Population
Urban / Rural
SOCIO DEMOGRAPHIC Appalachian Region U.S.
Race /Ethnicity
White (non-Hispanic)
African American (non-Hispanic)
Hispanic
Other
Age
Under 15
15-64
65+
Educational Attainment
At least High School Diploma
Bachelor's Degree or more
Disability Status
% Residents with a disability
ECONOMIC
Median Household Income
Poverty Rate
Unemployment Rate
Accident-prone Employment
Construction >
Mining
Manufacturing
Trade, Transportation, & Utilities
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The Growth of an Epidemic
The Opioid Crisis is Contributing to Lowering U.S. Life Expectancy.

Prescription and illicit opioids killed more than 33,000 Americans in 2015, almost quadruple the number in 2000. The toll of the epidemic is so great that is contributed to the first decline in U.S. life expectancy since 1993.

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While this issue is affecting communities across the country, one of the hardest hit areas is Appalachia.
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Residents of the Appalachian region are 55% more likely to die from a drug overdose than residents of the rest of the U.S.
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To better understand the Appalachian opioid crisis and inform effective conversations and interventions...

NORC at the University of Chicago and the Appalachian Regional Commission have created this trend spotting tool to allow users to map overdose hotspots and overlay them with the data that provides additional context to opioid addiction and death - including the strength and diversity of local economies, and ethnicity, educational attainment, and disability status of residents.

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Methodology & Data Sources

The Appalachian Drug Overdose interactive tool was designed and developed by NORC’s Walsh Center for Rural Health Analysis, our Health Media Collaboratory, and our Visualization Laboratory in partnership with the Appalachian Regional Commission.

The interactive tool was created in JavaScript using the Leaflet library. Data was processed using SAS and converted from shapefile to GeoJSON using the ogr2ogr web client. County level drug overdose death rates were downloaded from the National Vital Statistics System Multiple Causes of Death File. Employment data come from the U.S. Bureau of Labor Statistics’ Quarterly Census of Employment and Wages. Additional data were derived from the U.S. Census Bureau’s American Community Survey .

The visualizer presents age-adjusted mortality rates for the population aged 15 to 64. The combined population estimates for the time period (either 2011-2015 or 2006-2010) are the denominator for the mortality rates. If a county has fewer than 20 deaths over the five-year time period, the mortality rate is considered “unreliable” and we present the crude mortality rate. For counties with fewer than 10 deaths over the five-year time period, the number of deaths is suppressed, and therefore a mortality rate is not provided. However, when possible, we have calculated the maximum crude mortality rate based on the population and the assumption of less than 10 deaths.

Counties were classified as “urban” or “rural” based on designations from the Appalachian Research Council (ARC), based on a simplification of the USDA’s Economic Research Services (ERS) 2013 Urban Influence Codes (UIC). Urban counties include large metro counties (counties that include large metropolitan centers of one million population or greater) and small metro counties (counties with metropolitan centers of less than one million population). Rural counties include non-metro counties adjacent to large metros, non-metro counties adjacent to small metros, and non-metro counties not adjacent to a metro.

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More About NORC

For more than 75 years, NORC at the University of Chicago has been one of the world’s leading research organizations. NORC is also a pioneer in understanding difficult to reach audiences, integrating administrative data and social media into social science research, and making data more useful and accessible.

Among many recent projects, The Walsh Center for Rural Analysis has explored how “diseases of despair” have impacted the Appalachian Region, The Health Media Collaboratory has examined how tobacco companies have used Twitter and other social media channels to market e-cigarettes, especially to young people, and our Visualization Laboratory has created a calculator that helps employers compare the costs of substance abuse among employees to the cost of insurance-provided treatment.

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