Opioid Overdose Deaths in the United States
Race / Ethnicity
SEARCH FOR A COUNTY
LIST OF COUNTIES
Deaths per 100k population
|USDA Region Drug Overdose Mortality Rate|
|U.S. Drug Overdose Mortality Rate|
|Urban / Rural|
|SOCIO DEMOGRAPHIC||USDA Region||United States|
|African American (non-Hispanic)|
|Hispanic or Latino|
|Native Hawaiian/Pacific Islander (non-Hispanic)|
|American Indian/Alaska Native (non-Hispanic)|
|At least High School Diploma (25+)|
|Bachelor's Degree or more (25+)|
|% Residents with a disability (18-64)|
|Median Household Income|
|Mining and Natural Resources|
|Trade, Transportation, & Utilities|
Prescription and illicit opioids killed more than 47,000 people in 2017, nearly six times the number in 1999. The toll of the epidemic is so great that it contributed to the first decline in U.S. life expectancy since 1993.
NORC at the University of Chicago and the U.S. Department of Agriculture’s USDA Rural Development have created this tool to allow users to map overdose hotspots and overlay them with data that provide additional context to opioid addiction and death - including the strength and diversity of local economies, ethnicity, educational attainment, and disability status of residents.
The tool presents age-adjusted mortality rates for the population aged 15 to 64. The combined population estimates for the time period (either 2008-2012 or 2013-2017) are the denominator for the mortality rates. Five-year average mortality rates were used for this tool in order to maximize the number of counties with a reliable age-adjusted mortality rate. 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.
The table below describes each of the data sources and definitions for the variables included in the tool.
|Drug Overdose Mortality Rate||CDC NCHS NVSS – Multiple cause of death data – (2008-2012; 2013-2017)||Age-adjusted mortality rate for population aged 15 to 64. Underlying cause-of-death codes: X40-X44, X60-X64, X85, and Y10-Y14.|
|Opioid Overdose Mortality Rate||CDC NCHS NVSS – Multiple cause of death data – (2008-2012; 2013-2017)||Age-adjusted mortality rate for population aged 15 to 64. Underlying cause-of-death codes: X40-X44, X60-X64, X85, and Y10-Y14. Multiple cause-of-death codes: T40.0, T40.1, T40.2, T40.3, T40.4, T40.6.
*Note: There are variations in reporting across states for the ICD-10 codes on contributing causes. Therefore, these estimates should be used with caution.
|Urban/Rural||USDA Economic Research Services (ERS) 2013 Urban Influence Codes (UIC)||
Urban = Metropolitan counties, UIC Codes 1-2
Rural = Nonmetropolitan counties, UIC Codes 3-12
|Race/Ethnicity||U.S. Census Bureau, ACS 5-year estimates (2008-2012; 2013-2017)||Percentage of total population:
|Age||U.S. Census Bureau, ACS 5-year estimates (2008-2012; 2013-2017)||Percentage of total population:
|Educational Attainment||U.S. Census Bureau, ACS 5-year estimates (2008-2012; 2013-2017)||Percentage of population 25 years and over in the United States:
|Disability Status||U.S. Census Bureau, ACS 5-year estimates (2008-2012; 2013-2017)||Percentage of civilian non-institutionalized population ages 18-64 with a disability|
|Median Household Income||U.S. Census Bureau, ACS 5-year estimates(2008-2012; 2013-2017)||
Median household income in the past 12 months (in 2017 inflation-adjusted dollars)
Median household income in the past 12 months (in 2012 inflation-adjusted dollars)
|Poverty Rate||U.S. Census Bureau, ACS 5-year estimates (2008-2012; 2013-2017)||Among the population for whom poverty status is determined, the percentage of the population that has an income in the past 12 months below the poverty level|
|Unemployment Rate||U.S. Census Bureau, ACS 5-year estimates (2008-2012; 2013-2017)||Among the population 16 years and over, the percentage of the labor force that is unemployed|
|Accident-prone Employment||Bureau of Labor Statistics Quarterly Census of Employment and Wages(2008-2012 average employment; 2013-2017 average employment)||Percent of employed population that is employed in the following:
|Native American Reservations||U.S. Geological Survey Indian Lands shapefile (2014)||
The cartographic boundary files are simplified representations of selected geographic areas from the National Atlas of the United States
USDA Rural Development provides loans and grants to help expand economic opportunities and create jobs in rural areas. This assistance supports infrastructure improvements; business development; housing; community facilities such as schools, public safety and health care; and high-speed internet access in rural areas.
For more information on USDA’s response to the opioid crisis, please visit https://www.usda.gov/topics/opioids.
NORC at the University of Chicago is an objective, non-partisan research institution that delivers reliable data and rigorous analysis to guide critical programmatic, business, and policy decisions. Since 1941, NORC has conducted groundbreaking studies, created and applied innovative methods and tools, and advanced principles of scientific integrity and collaboration. Today, government, corporate, and nonprofit clients around the world partner with NORC to transform increasingly complex information into useful knowledge.
For more information please contact:
NORC Senior External Affairs Manager
Senior Fellow and Co-Director, NORC Walsh Center for Rural Health Analysis
<iframe width="975" height="570" src="https://opioidmisusetool.norc.org/embed/map/map.html" frameborder="1" allowfullscreen></iframe>
Embed table for Menifee County, KY in 2011 - 2015
<iframe width="975" height="630" src="https://opioidmisusetool.norc.org\embed\D\T2\table21165.html" frameborder="1" allowfullscreen> </iframe>
This tool allows researchers, policymakers, journalists, and the general public to create county-level maps illustrating the relationship between community and population demographics and fatal drug overdoses—including opioids—in the United States. Insights derived from this tool can be used to target resources and interventions, and inform media coverage related to overdose deaths in the U.S.
The base layer shows the fatal overdose rate by county at two points in time. Darker-colored counties have higher overdose rates. Lighter-colored counties have lower overdose death rates. You can use the List of Counties to link directly to data on a particular county, or click on it on the map.
Data specific to opioid overdoses can also be shown on the tool by selecting the “Opioid” dot; however, these mortality rates should be used with caution due to differences in reporting between states.
Click on the dot in the “timeframe” slider in the upper-right section of the screen to change the years represented by the overdose layer.
To view state-level data, click the "state/county" drop down in the upper-right section of the screen and select "State".
Use the “urban/rural” drop down to compare data from rural and urban counties.
Choose variables from the left-hand column to layer county-level economic and demographic data on top of the baseline fatal overdose data. By showing the variables as translucent circles of varying sizes, the tool allows users to clearly see how a given measure relates to the baseline fatal overdose rate. For example, choosing “Poverty Rate” will demonstrate the relationship between an individual county’s poverty rate and its overdose mortality rate.
On the right hand side of the screen, there is a drop down for “contextual overlays.” Currently, the tool includes a contextual overlay that shows the geolocation of Native American Reservations. Contextual overlays can be added to the map while also selecting a county-level sociodemographic or economic overlay.