In 2017, opioid overdose deaths in the United States reached a record high. And mayors and local leaders across the country have been scrambling to figure out what’s driving this precipitous rise of opioid mortality in the last two decades. Several theories have been aired, from aggressive Big Pharma marketing to anxiety among Baby Boomers. Unfortunately, no one-size-fits-all answer exist—how and why this public-health problem manifests locally varies greatly across the U.S.
That’s according to a new working paper by Syracuse University sociologist Shannon Monnat and the Institute for New Economic Thinking. It finds that one narrative that gained steam after the 2016 election—the notion of the modern opioid crisis as a disproportionately rural phenomenon that emerged outside of the cities where the “War on Drugs” has been raging for more than three decades—doesn’t hold up. Instead, in both rural and urban communities, two key factors—economic distress and supply of opioids—predict the rate of opioid deaths.
“I really do want to push back against this cliche that addiction does not discriminate,” Monnat says. “The physiological processes that underlie addiction themselves may not discriminate, but the factors that put people in communities at higher risk are are not spatially random.”
In the paper, Monnat examines county-level drug mortality rates. Two-thirds of these deaths involve heroin, fentanyl, and various prescription opiates. She focuses on non-Hispanic whites—a racial group that, as of 2016, has the highest drug mortality rate. After controlling for demographics, she finds that the average drug mortality rates are highest in large metro counties, and increased most since 2000. The rates decline the further one moves away from urban areas. (In an additional analysis, she crunches the numbers on all racial groups and finds similar results.)
Compared to urban counties, the average rate for most rural ones was 6.2 fewer deaths per 100,000 people in the 2014 to 2016 time period. But rural counties had a larger degree of variability among themselves. Southwest Pennsylvania, Central Appalachia, Central Florida, and the Mountain Northwest suffered higher-than-average rates of drug mortality; New York, Virginia, Texas, and the Mississippi Delta saw below-average rates.
So what predicted this variation? Monnat’s analysis found that both economic conditions and drug supply were related to higher mortality rates. With respect to economics, characteristics like family distress, population loss, and heavy reliance on mining and service industries seemed to drive up mortality rates. And on the supply side, Monnat looked at the government data on legal opioid prescriptions in each county. She also measured exposure to fentanyl—a powerful painkiller that has been manufactured illegally and is often mixed with heroin or other types of opiates; it’s been linked to many overdose deaths in recent years. For this metric, she used state-level data on law enforcement encounters in which the person tested positive for this drug.
While both economic conditions and drug supply are factors determining drug mortality, Monnat points out that economic conditions continued to be important, even after controlling for the supply side factors. This is where Monnat’s findings contradict some previous studies and support others.
“What that means is that drug mortality rates aren’t higher in economically distressed places simply because they’ve had a greater supply of opioid prescribing there,” she said. “There’s something about economic distress in and of itself that helps to explain the variation that we’re seeing across the country and the magnitude of the drug crisis.”
How important these factors were also varied: Generally, economic distress seemed to be a stronger determinant in rural areas, whereas in urban areas, it was the supply of drugs. But the effect of these factors was not observed just within county lines. Local economies are interconnected, which means that economic downturn has ripple effects beyond county lines, and drugs travel; that mean drug mortality may also spill over.
“A lot of what’s going on here are regional effects,” she said. “You get regional levels of despair and distress that seemed to reinforce and exacerbate the problem.”
The study has limitations, of course: It gives a snapshot of the crisis over a relatively short period of time, and it can’t say much about how important these predictors are for predicting geographical disparities in opioid overdose among different racial groups. But its findings nevertheless have widespread implications for policymakers grappling with this stubborn problem. Limiting opioid prescriptions and cracking down on illicit fentanyl might be of limited effectiveness when local economic conditions are struggling. Any successful approach would have to to be multifaceted and tailored to the specific region. It would also have to focus on the correct underlying factors that make certain communities more susceptible to this epidemic.
“It’s no coincidence that widespread opioid prescribing first started in the most economically vulnerable places of the country—there was vulnerability there,” Monnat said. “These places had been primed to be vulnerable to opioids, which are drugs that numb both physical and mental pain, through decades of economic and social decline.”
This story originally appeared on CityLab, an editorial partner site. Subscribe to CityLab’s newsletters and follow CityLab on Facebook and Twitter.
