Poster Paper:
Jobs and Drugs: Time Series Analyses of Labor Market and Income Indicators and Proxies for Opioid Abuse at the County Level.
Friday, November 3, 2017
Regency Ballroom (Hyatt Regency Chicago)
*Names in bold indicate Presenter
A significant early theme of the 2016 US Presidential Election campaign was the opioid epidemic and its effect on communities across the country. According to the National Institutes of Health, between 2002 and 2015, annual overdose deaths from all opioids increased by 280%.[1] The many classes of opioids include heroin but also prescription drugs like oxycodone and fentanyl, among others, whose usage grew 80% between 2000 and 2010.[2] Several competing narratives have been put forward to explain the explosion in opioid-related morbidity and mortality: the introduction of pain as the fifth vital sign in the late 1990s, the hollowing out of the industrial heartland of America, and the acceleration of growth in income inequality since the mid-1970s. This poster uses a data set including the Bureau of Labor Statistics Labor Force Participation rates, aggregated household data from the Current Population Survey, county-level corrections data from the Department of Justice, and aggregated household and hospital data from Agency for Health Care Quality and Research’s Medical Expenditure Panel Survey and Healthcare Cost and Utilization Project normalized at the county level from 2000 to 2015. Using a set of time-series regressions, this poster showcases how the choice of measures can lend credence or refutation to the policy arguments. The dependent variable across the regressions is annual county-level opioid-related mortality while the three independent variables, along with demographic and regional controls, will be tested including: labor force participation, narcotics arrests, and the GINI coefficient. Employing two data tables and an appropriate data visualization each, the poster lays out supporting and countervailing evidence for the narratives above. The poster concludes with a discussion of the fully-loaded time-series analysis including all three independent variables and controls. The goal is to demonstrate that to understand and address a policy problem like the opioid epidemic we need a variety of data sources that provide multiple perspectives on an issue.
[1] National Center for Health Statistics, CDC Wonder. https://www.drugabuse.gov/related-topics/trends-statistics/overdose-death-rates
[2] Sites, B. D., Beach, M. L., & Davis, M. (2014). Increases in the use of prescription opioid analgesics and the lack of improvement in disability metrics among users. Regional anesthesia and pain medicine, 39(1), 6. 10.1097/AAP.0000000000000022
