The opioid epidemic has cost the US more than one trillion dollars over the past 17 years and is expected to cost more than 500 billion dollars over the next three years. Utilizing state-level panel data from the 2006-2013 Current Population Surveys and Behavioral Risk Factor Surveillance Systems, this paper uses regression analysis to examine the effects of various factors, such as income, unemployment, health insurance coverage, sex, race/ethnicity, marital status, education, age, and health status, on opioid overdose/abuse. By identifying the high-risk groups, resources can be more efficiently allocated to the areas and people in need. These resources include educating the people and the doctors in the affected area, providing accessible Naloxone, providing opioid addiction relief programs, etc. Having these resources accessible to the areas in need will help not only improve the health of the population, but also reduce health care costs. Other researchers have identified high-risk groups on a local level. This study provides a more in-depth statewide review of high-risk groups. This paper finds that people who are impoverished, married, widowed/divorced, have Medicaid, identify as black, aged 45+, or report very good health are more likely to die from opioid overdose. Considering this, additional attention should be placed on these high-risk groups when considering treatment, prevention, and other tactics to help fight the ongoing epidemic.
Additional Speakers
Faculty Sponsors
Faculty Department/Program
Faculty Division
Presentation Type
Do You Approve this Abstract?
Approved
Time Slot
Room
Topic
Session
Moderator