Investigating the relationships between socioeconomic status, Kratom legislation, and the COVID-19 pandemic on opioid overdose mortality in the United States.

Abstract

Background: 585,000 people have died from an opioid overdose in the US between 1999 and 2020. The current opioid epidemic has been described as a quadruple wave of overdoses, due in part to the changes in prescription and illicit opioid supply as well as the underlying social and structural factors that led to a subsequent increase in demand. In order to mitigate the opioid epidemic through prevention and protection strategies, we must first understand the social and structural factors that are driving the increase in opioid misuse and abuse. To better understand the socioeconomic factors, we described socioeconomic profiles of US counties and examined their associations with rates of opioid overdose mortality in Aim 1. Since the beginning of the epidemic, rates of opioid-related overdose death have differed in rural and urban counties. We examined the association between urban residence and subsequent opioid overdose mortality in Kentucky, a state highly impacted by the opioid epidemic, and whether this association was modified by the COVID-19 pandemic (Aim 2). With the rise in opioid overdose deaths, people have sought out alternative substances that are advertised to have less side effects and lower abuse potential, such as kratom. Kratom is an herbal extract from evergreen tree leaves indigenous to Southeast Asia that has opiate-like properties. Six states have banned kratom over concerns about its potential for addiction; however, there is no scientific evidence regarding the impact of these laws on the opioid epidemic. Therefore, we examined this association between state-level kratom legislation and opioid overdose mortality across US states (Aim 3). Methods: In all analyses, opioid overdose mortality was classified using the International Statistical Classification of Diseases, 10th revision (ICD-10). Among deaths with drug overdose as the underlying cause, we captured those specifically involving an opioid analgesic including opium, heroin, prescription opioids (i.e., natural and semisynthetic opioids and methadone), synthetic opioids other than methadone, and other and unspecified narcotics. In a nationwide analysis (Aim 1), we identified patterns of demographic, socioeconomic and housing characteristics in US counties using principal components (PC) analysis and used Poisson regression to estimate adjusted relative risks (RRs) and 95% confidence intervals (CIs) of opioid overdose mortality for a one standard deviation increase in PC scores. We used data from all Kentucky inpatient and outpatient hospitalizations from 2016-2020 to estimate odds ratios (ORs) and 95% CIs of opioid overdose mortality for urban versus rural patients with multivariable logistic regression